From 8ba4230fca2dcad25ec6ca13708cc1d3b96c9223 Mon Sep 17 00:00:00 2001 From: Sally Hong Date: Wed, 5 Mar 2025 15:06:52 -0600 Subject: [PATCH] Merged upstream Robyn 3.12 try2 --- .github/workflows/python-app.yml | 63 + .gitignore | 22 + R/DESCRIPTION | 11 +- R/NAMESPACE | 8 +- R/R/.gitignore | 1 + R/R/allocator.R | 249 +- R/R/auxiliary.R | 62 +- R/R/calibration.R | 523 +- R/R/checks.R | 274 +- R/R/clusters.R | 5 +- R/R/data.R | 42 + R/R/imports.R | 5 +- R/R/inputs.R | 471 +- R/R/json.R | 152 +- R/R/model.R | 243 +- R/R/outputs.R | 7 +- R/R/pareto.R | 527 +- R/R/plots.R | 370 +- R/R/refresh.R | 87 +- R/R/response.R | 330 +- R/R/transformation.R | 158 +- R/README.md | 7 - R/data/df_curve_reach_freq.RData | Bin 0 -> 2685 bytes R/man/Robyn.Rd | 2 +- R/man/adstocks.Rd | 12 +- R/man/df_curve_reach_freq.Rd | 38 + R/man/dt_prophet_holidays.Rd | 1 + R/man/dt_simulated_weekly.Rd | 1 + R/man/fit_spend_exposure.Rd | 29 - R/man/hyper_names.Rd | 55 +- R/man/prophet_decomp.Rd | 9 + R/man/robyn_allocator.Rd | 6 +- R/man/robyn_calibrate.Rd | 91 + R/man/robyn_inputs.Rd | 4 +- R/man/robyn_mmm.Rd | 9 +- R/man/robyn_outputs.Rd | 24 +- R/man/robyn_refresh.Rd | 6 + R/man/robyn_response.Rd | 8 +- R/man/robyn_run.Rd | 4 +- R/man/robyn_train.Rd | 4 +- R/man/robyn_write.Rd | 8 +- R/man/saturation_hill.Rd | 4 +- R/man/set_default_hyppar.Rd | 26 + R/man/{mic_men.Rd => transformations.Rd} | 28 +- README.md | 45 +- demo/demo.R | 271 +- python/LICENSE | 21 + python/README.md | 70 + .../robyn/modeling/pareto/response_curve.md | 177 + .../robyn/modeling/feature_engineering.md | 94 + .../modeling/pareto/test_response_curve.md | 15 + python/pyproject.toml | 46 + python/requirements.txt | 17 + .../robyn/modeling/pareto/hill_calculator.md | 50 + .../robyn/visualization/allocator_plotter.md | 305 + .../robyn/visualization/base_visualizer.md | 58 + .../modeling/pareto/test_hill_calculator.md | 142 + python/src/robyn/__init__.py | 59 + python/src/robyn/allocator/constants.py | 27 + 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.../validation/hyperparameter_validation.py | 232 + .../data/validation/mmmdata_validation.py | 263 + .../src/robyn/data/validation/validation.py | 20 + python/src/robyn/modeling/__init__.py | 0 .../src/robyn/modeling/base_model_executor.py | 342 + .../modeling/clustering/cluster_builder.py | 804 + .../modeling/clustering/clustering_config.py | 60 + .../robyn/modeling/convergence/convergence.py | 239 + .../modeling/entities/ci_collection_data.py | 10 + .../modeling/entities/clustering_results.py | 86 + .../modeling/entities/convergence_data.py | 28 + python/src/robyn/modeling/entities/enums.py | 33 + .../modeling/entities/featurized_mmm_data.py | 10 + .../modeling/entities/model_refit_output.py | 27 + .../robyn/modeling/entities/modeloutputs.py | 89 + .../entities/modelrun_trials_config.py | 21 + .../robyn/modeling/entities/pareto_data.py | 13 + .../robyn/modeling/entities/pareto_result.py | 32 + .../src/robyn/modeling/feature_engineering.py | 639 + 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website/yarn.lock | 488 +- 159 files changed, 120041 insertions(+), 2362 deletions(-) create mode 100644 .github/workflows/python-app.yml create mode 100644 R/R/.gitignore create mode 100644 R/data/df_curve_reach_freq.RData create mode 100644 R/man/df_curve_reach_freq.Rd delete mode 100644 R/man/fit_spend_exposure.Rd create mode 100644 R/man/robyn_calibrate.Rd create mode 100644 R/man/set_default_hyppar.Rd rename R/man/{mic_men.Rd => transformations.Rd} (63%) create mode 100644 python/LICENSE create mode 100644 python/README.md create mode 100644 python/docs/robyn/modeling/pareto/response_curve.md create mode 100644 python/docs/tests/robyn/modeling/feature_engineering.md create mode 100644 python/docs/tests/robyn/modeling/pareto/test_response_curve.md create mode 100644 python/pyproject.toml create mode 100644 python/requirements.txt create mode 100644 python/spec/src/robyn/modeling/pareto/hill_calculator.md create mode 100644 python/spec/src/robyn/visualization/allocator_plotter.md create mode 100644 python/spec/src/robyn/visualization/base_visualizer.md create mode 100644 python/spec/tests/robyn/modeling/pareto/test_hill_calculator.md create mode 100644 python/src/robyn/__init__.py create mode 100644 python/src/robyn/allocator/constants.py create mode 100644 python/src/robyn/allocator/data_preparation.py create mode 100644 python/src/robyn/allocator/entities/allocation_params.py create mode 100644 python/src/robyn/allocator/entities/allocation_result.py create mode 100644 python/src/robyn/allocator/entities/constraints.py create mode 100644 python/src/robyn/allocator/entities/optimization_result.py create mode 100644 python/src/robyn/allocator/optimizer.py create mode 100644 python/src/robyn/allocator/utils.py create mode 100644 python/src/robyn/calibration/media_effect_calibration.py create mode 100644 python/src/robyn/calibration/media_transformation.py create mode 100644 python/src/robyn/common/common_util.py create mode 100644 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website/static/img/curve_calibrator_onepager.png create mode 100644 website/static/img/rnf_allocator_prototype.png diff --git a/.github/workflows/python-app.yml b/.github/workflows/python-app.yml new file mode 100644 index 000000000..fda33906d --- /dev/null +++ b/.github/workflows/python-app.yml @@ -0,0 +1,63 @@ +# This workflow will install Python dependencies, run tests and lint with a single version of Python +# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python +# A continuous integration (CI) workflow to build and test Robyn Python project + +name: Robyn Python application + +on: + push: + branches: ['robynpy_release'] + pull_request: + branches: ['robynpy_release'] + +permissions: + contents: read + +jobs: + build: + runs-on: ubuntu-latest + + strategy: + matrix: + python-version: ['3.10'] + + steps: + - uses: actions/checkout@v4 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + cache: 'pip' + - name: Display Python version + run: python -c "import sys; print(sys.version)" + + - name: updating PATH to enable importing robyn modules + run: | + echo "PYTHONPATH=$PYTHONPATH:$(pwd)/python/src" >> $GITHUB_ENV + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install flake8 pytest pytest-cov + if [ -f python/requirements.txt ]; then pip install -r python/requirements.txt; fi + - name: Lint with flake8 + run: | + # stop the build if there are Python syntax errors or undefined names + flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics --exclude=./robyn_api/*.py + # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide + flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics --exclude=./robyn_api/*.py + - name: Test with pytest. Enable this once first set of tests are written + run: | + pytest ./python/tests --doctest-modules --junitxml=junit/test-results.xml --cov=robyn --cov-report=html + - name: 'Upload Unit Test Results' + uses: actions/upload-artifact@v4 + with: + name: robynpy-output-artifact + path: junit/test-results.xml + retention-days: 30 + - name: Upload Coverage Report + uses: actions/upload-artifact@v4 + with: + name: coverage-report + path: htmlcov + retention-days: 30 diff --git a/.gitignore b/.gitignore index 01fb872a3..a0e98a7fc 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,9 @@ .DS_Store .Rproj.user .Rhistory +.pyvenv/ +.venv/ +robynpy.egg-info/ node_modules/ RobynApp.Rcheck/00_pkg_src/RobynApp/R/ui.R RobynApp.Rcheck/00_pkg_src/RobynApp/README.md @@ -31,3 +34,22 @@ RobynApp.Rcheck/RobynApp/R/RobynApp.rdb RobynApp.Rcheck/RobynApp/R/RobynApp.rdx RobynApp_1.0.0.tar.gz Robyn_Fork.Rproj +python/src/tutorials/demo.py +python/.venv +python/**/.venv +python/dist +python/**/__pycache__ +python/.vscode +python/src/robynpy.egg-info* +python/oldportedcode +python/src/tutorials/mytestenv +*.log +python/src/tutorials/test_modeling.py +python/src/tutorials/data/* +python/src/tutorials/test_modeling.py +python/src/tutorials/data/R/* +python/src/tutorials/data/* +*.pkl +python/src/robyn/_deprecate/* +python/src/robyn/tutorials/output/* +python/src/robyn/debug/* \ No newline at end of file diff --git a/R/DESCRIPTION b/R/DESCRIPTION index bb50ed09a..c6f36a1a2 100644 --- a/R/DESCRIPTION +++ b/R/DESCRIPTION @@ -1,12 +1,12 @@ Package: Robyn Type: Package Title: Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing Science -Version: 3.10.6.9003 +Version: 3.12.0.9006 Authors@R: c( - person("Gufeng", "Zhou", , "gufeng@meta.com", c("cre","aut")), + person("Gufeng", "Zhou", , "gufeng@meta.com", c("cre", "aut")), + person("Igor", "Skokan", , "igorskokan@meta.com", c("aut")), person("Bernardo", "Lares", , "laresbernardo@gmail.com", c("aut")), person("Leonel", "Sentana", , "leonelsentana@meta.com", c("aut")), - person("Igor", "Skokan", , "igorskokan@meta.com", c("aut")), person("Meta Platforms, Inc.", role = c("cph", "fnd"))) Maintainer: Gufeng Zhou Description: Semi-Automated Marketing Mix Modeling (MMM) aiming to reduce human bias by means of ridge regression and evolutionary algorithms, enables actionable decision making providing a budget allocation and diminishing returns curves and allows ground-truth calibration to account for causation. @@ -23,15 +23,12 @@ Imports: jsonlite, lares, lubridate, - minpack.lm, nloptr, patchwork, prophet, reticulate, stringr, tidyr -Suggests: - shiny Config/reticulate: list( packages = list( @@ -40,7 +37,7 @@ Config/reticulate: ) URL: https://github.com/facebookexperimental/Robyn, https://facebookexperimental.github.io/Robyn/ BugReports: https://github.com/facebookexperimental/Robyn/issues -RoxygenNote: 7.2.3 +RoxygenNote: 7.3.2 License: MIT + file LICENSE Encoding: UTF-8 LazyData: true diff --git a/R/NAMESPACE b/R/NAMESPACE index 7bbbfe7e5..4b9ee8c36 100644 --- a/R/NAMESPACE +++ b/R/NAMESPACE @@ -17,12 +17,16 @@ export(decomp_plot) export(hyper_limits) export(hyper_names) export(mic_men) +export(model_decomp) +export(pareto_front) export(plot_adstock) export(plot_saturation) export(robyn_allocator) +export(robyn_calibrate) export(robyn_clusters) export(robyn_converge) export(robyn_csv) +export(robyn_immcarr) export(robyn_inputs) export(robyn_load) export(robyn_mmm) @@ -38,7 +42,9 @@ export(robyn_save) export(robyn_train) export(robyn_update) export(robyn_write) +export(run_transformations) export(saturation_hill) +export(set_default_hyppar) export(transform_adstock) export(ts_validation) import(ggplot2) @@ -59,6 +65,7 @@ importFrom(dplyr,distinct) importFrom(dplyr,ends_with) importFrom(dplyr,everything) importFrom(dplyr,filter) +importFrom(dplyr,full_join) importFrom(dplyr,group_by) importFrom(dplyr,lag) importFrom(dplyr,left_join) @@ -106,7 +113,6 @@ importFrom(lares,v2t) importFrom(lubridate,day) importFrom(lubridate,floor_date) importFrom(lubridate,is.Date) -importFrom(minpack.lm,nlsLM) importFrom(nloptr,nloptr) importFrom(parallel,detectCores) importFrom(patchwork,guide_area) diff --git a/R/R/.gitignore b/R/R/.gitignore new file mode 100644 index 000000000..00a4294ee --- /dev/null +++ b/R/R/.gitignore @@ -0,0 +1 @@ +Robyn.Rproj diff --git a/R/R/allocator.R b/R/R/allocator.R index b070ec181..1c380dd22 100644 --- a/R/R/allocator.R +++ b/R/R/allocator.R @@ -50,7 +50,7 @@ #' \code{channel_constr_low = 0.7} means minimum spend of the variable is 70% of historical #' average, using non-zero spend values, within \code{date_min} and \code{date_max} date range. #' Both constrains must be length 1 (same for all values) OR same length and order as -#' \code{paid_media_spends}. It's not recommended to 'exaggerate' upper bounds, especially +#' \code{paid_media_selected}. It's not recommended to 'exaggerate' upper bounds, especially #' if the new level is way higher than historical level. Lower bound must be >=0.01, #' and upper bound should be < 5. #' @param channel_constr_multiplier Numeric. Default to 3. For example, if @@ -62,6 +62,8 @@ #' Defaults to 100000. #' @param constr_mode Character. Options are \code{"eq"} or \code{"ineq"}, #' indicating constraints with equality or inequality. +#' @param keep_zero_coefs Boolean. By default, zero coefficient (betas) channels +#' will be removed to avoid spending budget were there is no impact. #' @param plots Boolean. Generate plots? #' @return A list object containing allocator result. #' @examples @@ -101,6 +103,7 @@ robyn_allocator <- function(robyn_object = NULL, optim_algo = "SLSQP_AUGLAG", maxeval = 100000, constr_mode = "eq", + keep_zero_coefs = FALSE, plots = TRUE, plot_folder = NULL, plot_folder_sub = NULL, @@ -108,7 +111,7 @@ robyn_allocator <- function(robyn_object = NULL, quiet = FALSE, ui = FALSE, ...) { - ### Use previously exported model using json_file + ## Use previously exported model using json_file if (!is.null(json_file)) { if (is.null(InputCollect)) { InputCollect <- robyn_inputs( @@ -128,37 +131,25 @@ robyn_allocator <- function(robyn_object = NULL, if (is.null(select_model)) select_model <- OutputCollect$selectID } - ## Collect inputs - # if (!is.null(robyn_object) && (is.null(InputCollect) && is.null(OutputCollect))) { - # if ("robyn_exported" %in% class(robyn_object)) { - # imported <- robyn_object - # robyn_object <- imported$robyn_object - # } else { - # imported <- robyn_load(robyn_object, select_build, quiet) - # } - # InputCollect <- imported$InputCollect - # OutputCollect <- imported$OutputCollect - # select_model <- imported$select_model - # } else { + ## set local variables, sort & prompt + # paid_media_spends <- InputCollect$paid_media_spends + paid_media_selected <- if ("paid_media_selected" %in% names(InputCollect)) + InputCollect$paid_media_selected else InputCollect$paid_media_spends + dep_var_type <- InputCollect$dep_var_type if (is.null(select_model) && length(OutputCollect$allSolutions == 1)) { select_model <- OutputCollect$allSolutions } - if (any(is.null(InputCollect), is.null(OutputCollect), is.null(select_model))) { - stop("When 'robyn_object' is not provided, then InputCollect, OutputCollect, select_model must be provided") - } - # } - - if (length(InputCollect$paid_media_spends) <= 1) { - stop("Must have a valid model with at least two 'paid_media_spends'") - } - if (!quiet) message(paste(">>> Running budget allocator for model ID", select_model, "...")) - - ## Set local data & params values - paid_media_spends <- InputCollect$paid_media_spends - media_order <- order(paid_media_spends) - mediaSpendSorted <- paid_media_spends[media_order] - dep_var_type <- InputCollect$dep_var_type + media_order <- order(paid_media_selected) + # mediaSpendSorted <- paid_media_spends[media_order] + mediaSelectedSorted <- paid_media_selected[media_order] + + ## Checks and constraints + if ("max_historical_response" %in% scenario) scenario <- "max_response" #legacy + check_allocator( + OutputCollect, select_model, paid_media_selected, scenario, + channel_constr_low, channel_constr_up, constr_mode + ) if (is.null(channel_constr_low)) { channel_constr_low <- case_when( scenario == "max_response" ~ 0.5, @@ -168,46 +159,34 @@ robyn_allocator <- function(robyn_object = NULL, if (is.null(channel_constr_up)) { channel_constr_up <- case_when( scenario == "max_response" ~ 2, - scenario == "target_efficiency" ~ Inf + scenario == "target_efficiency" ~ 10 ) } - if (length(channel_constr_low) == 1) channel_constr_low <- rep(channel_constr_low, length(paid_media_spends)) - if (length(channel_constr_up) == 1) channel_constr_up <- rep(channel_constr_up, length(paid_media_spends)) - check_allocator_constrains(channel_constr_low, channel_constr_up) - names(channel_constr_low) <- paid_media_spends - names(channel_constr_up) <- paid_media_spends - channel_constr_low <- channel_constr_low[media_order] - channel_constr_up <- channel_constr_up[media_order] - dt_hyppar <- filter(OutputCollect$resultHypParam, .data$solID == select_model) - dt_bestCoef <- filter(OutputCollect$xDecompAgg, .data$solID == select_model, .data$rn %in% paid_media_spends) - - ## Check inputs and parameters - scenario <- check_allocator( - OutputCollect, select_model, paid_media_spends, scenario, - channel_constr_low, channel_constr_up, constr_mode - ) - - ## Sort media - dt_coef <- select(dt_bestCoef, .data$rn, .data$coef) - get_rn_order <- order(dt_bestCoef$rn) - dt_coefSorted <- dt_coef[get_rn_order, ] - dt_bestCoef <- dt_bestCoef[get_rn_order, ] - coefSelectorSorted <- dt_coefSorted$coef > 0 - names(coefSelectorSorted) <- dt_coefSorted$rn - - dt_hyppar <- select(dt_hyppar, hyper_names(InputCollect$adstock, mediaSpendSorted)) %>% + if (length(channel_constr_low) == 1) channel_constr_low <- rep(channel_constr_low, length(paid_media_selected)) + if (length(channel_constr_up) == 1) channel_constr_up <- rep(channel_constr_up, length(paid_media_selected)) + #check_allocator_constrains(channel_constr_low, channel_constr_up) + names(channel_constr_low) <- names(channel_constr_up) <- paid_media_selected + channelConstrLowSorted <- channel_constr_low[mediaSelectedSorted] + channelConstrUpSorted <- channel_constr_up[mediaSelectedSorted] + + ## get hill parameters and coefs + dt_hyppar_sorted <- OutputCollect$resultHypParam %>% + filter(.data$solID == select_model) %>% + select(c(hyper_names(InputCollect$adstock, mediaSelectedSorted), + paste0(mediaSelectedSorted, "_inflexion"), + paste0(mediaSelectedSorted, "_inflation"))) %>% select(sort(colnames(.))) - dt_bestCoef <- dt_bestCoef[dt_bestCoef$rn %in% mediaSpendSorted, ] - channelConstrLowSorted <- channel_constr_low[mediaSpendSorted] - channelConstrUpSorted <- channel_constr_up[mediaSpendSorted] - - ## Get hill parameters for each channel - hills <- get_hill_params( - InputCollect, OutputCollect, dt_hyppar, dt_coef, mediaSpendSorted, select_model - ) - alphas <- hills$alphas - inflexions <- hills$inflexions - coefs_sorted <- hills$coefs_sorted + dt_coef_sorted <- OutputCollect$xDecompAgg %>% + filter(.data$solID == select_model & .data$rn %in% mediaSelectedSorted) %>% + select("rn", "coef") %>% + arrange(.data$rn) + non_zero_coef_sorted <- dt_coef_sorted$coef > 0 + names(non_zero_coef_sorted) <- dt_coef_sorted$rn + alphas <- dt_hyppar_sorted %>% select(contains("alphas")) %>% unlist + inflexions <- dt_hyppar_sorted %>% select(contains("inflexion")) %>% unlist + inflations <- dt_hyppar_sorted %>% select(contains("inflation")) %>% unlist + coefs_sorted <- dt_coef_sorted$coef + names(coefs_sorted) <- dt_coef_sorted$rn # Spend values based on date range set window_loc <- InputCollect$rollingWindowStartWhich:InputCollect$rollingWindowEndWhich @@ -222,21 +201,21 @@ robyn_allocator <- function(robyn_object = NULL, if (date_max > max(dt_optimCost$ds)) date_max <- max(dt_optimCost$ds) histFiltered <- filter(dt_optimCost, .data$ds >= date_min & .data$ds <= date_max) - histSpendAll <- unlist(summarise_all(select(dt_optimCost, any_of(mediaSpendSorted)), sum)) + histSpendAll <- unlist(summarise_all(select(dt_optimCost, any_of(mediaSelectedSorted)), sum)) histSpendAllTotal <- sum(histSpendAll) - histSpendAllUnit <- unlist(summarise_all(select(dt_optimCost, any_of(mediaSpendSorted)), mean)) + histSpendAllUnit <- unlist(summarise_all(select(dt_optimCost, any_of(mediaSelectedSorted)), mean)) histSpendAllUnitTotal <- sum(histSpendAllUnit) histSpendAllShare <- histSpendAllUnit / histSpendAllUnitTotal - histSpendWindow <- unlist(summarise_all(select(histFiltered, any_of(mediaSpendSorted)), sum)) + histSpendWindow <- unlist(summarise_all(select(histFiltered, any_of(mediaSelectedSorted)), sum)) histSpendWindowTotal <- sum(histSpendWindow) - initSpendUnit <- histSpendWindowUnit <- unlist(summarise_all(select(histFiltered, any_of(mediaSpendSorted)), mean)) + initSpendUnit <- histSpendWindowUnit <- unlist(summarise_all(select(histFiltered, any_of(mediaSelectedSorted)), mean)) histSpendWindowUnitTotal <- sum(histSpendWindowUnit) histSpendWindowShare <- histSpendWindowUnit / histSpendWindowUnitTotal - simulation_period <- initial_mean_period <- unlist(summarise_all(select(histFiltered, any_of(mediaSpendSorted)), length)) - nDates <- lapply(mediaSpendSorted, function(x) histFiltered$ds) - names(nDates) <- mediaSpendSorted + simulation_period <- initial_mean_period <- unlist(summarise_all(select(histFiltered, any_of(mediaSelectedSorted)), length)) + nDates <- lapply(mediaSelectedSorted, function(x) histFiltered$ds) + names(nDates) <- mediaSelectedSorted if (!quiet) { message(sprintf( "Date Window: %s:%s (%s %ss)", @@ -264,15 +243,15 @@ robyn_allocator <- function(robyn_object = NULL, initResponseMargUnit <- NULL hist_carryover <- list() qa_carryover <- list() - for (i in seq_along(mediaSpendSorted)) { + for (i in seq_along(mediaSelectedSorted)) { resp <- robyn_response( json_file = json_file, # robyn_object = robyn_object, select_build = select_build, select_model = select_model, - metric_name = mediaSpendSorted[i], - #metric_value = initSpendUnit[i] * simulation_period[i], - #date_range = date_range, + metric_name = mediaSelectedSorted[i], + # metric_value = initSpendUnit[i] * simulation_period[i], + # date_range = date_range, dt_hyppar = OutputCollect$resultHypParam, dt_coef = OutputCollect$xDecompAgg, InputCollect = InputCollect, @@ -296,17 +275,17 @@ robyn_allocator <- function(robyn_object = NULL, x_input <- initSpendUnit[i] resp_simulate <- fx_objective( x = x_input, - coeff = coefs_sorted[[mediaSpendSorted[i]]], - alpha = alphas[[paste0(mediaSpendSorted[i], "_alphas")]], - inflexion = inflexions[[paste0(mediaSpendSorted[i], "_gammas")]], + coeff = coefs_sorted[[mediaSelectedSorted[i]]], + alpha = alphas[[paste0(mediaSelectedSorted[i], "_alphas")]], + inflexion = inflexions[[paste0(mediaSelectedSorted[i], "_inflexion")]], x_hist_carryover = mean(hist_carryover_temp), get_sum = FALSE ) resp_simulate_plus1 <- fx_objective( x = x_input + 1, - coeff = coefs_sorted[[mediaSpendSorted[i]]], - alpha = alphas[[paste0(mediaSpendSorted[i], "_alphas")]], - inflexion = inflexions[[paste0(mediaSpendSorted[i], "_gammas")]], + coeff = coefs_sorted[[mediaSelectedSorted[i]]], + alpha = alphas[[paste0(mediaSelectedSorted[i], "_alphas")]], + inflexion = inflexions[[paste0(mediaSelectedSorted[i], "_inflexion")]], x_hist_carryover = mean(hist_carryover_temp), get_sum = FALSE ) @@ -314,7 +293,7 @@ robyn_allocator <- function(robyn_object = NULL, initResponseMargUnit <- c(initResponseMargUnit, resp_simulate_plus1 - resp_simulate) } qa_carryover <- do.call(cbind, qa_carryover) %>% as.data.frame() - names(initResponseUnit) <- names(hist_carryover) <- names(qa_carryover) <- mediaSpendSorted + names(initResponseUnit) <- names(hist_carryover) <- names(qa_carryover) <- mediaSelectedSorted # QA adstock: simulated adstock should be identical to model adstock # qa_carryover_origin <- OutputCollect$mediaVecCollect %>% # filter(.data$solID == select_model & .data$type == "adstockedMedia") %>% @@ -336,22 +315,6 @@ robyn_allocator <- function(robyn_object = NULL, 1 + (channelConstrUpSorted - 1) * channel_constr_multiplier ) - target_value_ext <- target_value - if (scenario == "target_efficiency") { - channelConstrLowSortedExt <- channelConstrLowSorted - channelConstrUpSortedExt <- channelConstrUpSorted - if (dep_var_type == "conversion") { - if (is.null(target_value)) { - target_value <- sum(initSpendUnit) / sum(initResponseUnit) * 1.2 - } - target_value_ext <- target_value * 1.5 - } else { - if (is.null(target_value)) { - target_value <- sum(initResponseUnit) / sum(initSpendUnit) * 0.8 - } - target_value_ext <- 1 - } - } temp_init <- temp_init_all <- initSpendUnit # if no spend within window as initial spend, use historical average if (length(zero_spend_channel) > 0) temp_init_all[zero_spend_channel] <- histSpendAllUnit[zero_spend_channel] @@ -368,15 +331,15 @@ robyn_allocator <- function(robyn_object = NULL, ## Exclude 0 coef and 0 constraint channels for the optimisation skip_these <- (channel_constr_low == 0 & channel_constr_up == 0) - zero_constraint_channel <- mediaSpendSorted[skip_these] + zero_constraint_channel <- mediaSelectedSorted[skip_these] if (any(skip_these) && !quiet) { message( "Excluded variables (constrained to 0): ", paste(zero_constraint_channel, collapse = ", ") ) } - if (!all(coefSelectorSorted)) { - zero_coef_channel <- setdiff(names(coefSelectorSorted), mediaSpendSorted[coefSelectorSorted]) + if (!all(non_zero_coef_sorted) & !keep_zero_coefs) { + zero_coef_channel <- setdiff(names(non_zero_coef_sorted), mediaSelectedSorted[non_zero_coef_sorted]) if (!quiet) { message( "Excluded variables (coefficients are 0): ", @@ -386,8 +349,8 @@ robyn_allocator <- function(robyn_object = NULL, } else { zero_coef_channel <- as.character() } - channel_to_drop_loc <- mediaSpendSorted %in% c(zero_coef_channel, zero_constraint_channel) - channel_for_allocation <- mediaSpendSorted[!channel_to_drop_loc] + channel_to_drop_loc <- mediaSelectedSorted %in% c(zero_coef_channel, zero_constraint_channel) + channel_for_allocation <- mediaSelectedSorted[!channel_to_drop_loc] if (any(channel_to_drop_loc)) { temp_init <- temp_init_all[channel_for_allocation] temp_ub <- temp_ub_all[channel_for_allocation] @@ -407,16 +370,36 @@ robyn_allocator <- function(robyn_object = NULL, x0_ext <- lb_ext <- temp_init * temp_lb_ext ub_ext <- temp_init * temp_ub_ext + target_value_ext <- target_value + if (scenario == "target_efficiency") { + # channelConstrLowSortedExt <- channelConstrLowSorted + # channelConstrUpSortedExt <- channelConstrUpSorted + x0_ext <- lb_ext <- temp_init * 0.9 + if (dep_var_type == "conversion") { + if (is.null(target_value)) { + target_value <- sum(initSpendUnit) / sum(initResponseUnit) * 1.2 + } + target_value_ext <- target_value * 1.5 + } else { + if (is.null(target_value)) { + target_value <- sum(initResponseUnit) / sum(initSpendUnit) * 0.8 + } + target_value_ext <- 1 + } + } + # Gather all values that will be used internally on optim (nloptr) coefs_eval <- coefs_sorted[channel_for_allocation] alphas_eval <- alphas[paste0(channel_for_allocation, "_alphas")] - inflexions_eval <- inflexions[paste0(channel_for_allocation, "_gammas")] + inflexions_eval <- inflexions[paste0(channel_for_allocation, "_inflexion")] hist_carryover_eval <- hist_carryover[channel_for_allocation] + inflations_eval <- inflations[paste0(channel_for_allocation, "_inflation")] eval_list <- list( coefs_eval = coefs_eval, alphas_eval = alphas_eval, inflexions_eval = inflexions_eval, + inflation_eval = inflations_eval, # mediaSpendSortedFiltered = mediaSpendSorted, total_budget = total_budget, total_budget_unit = total_budget_unit, @@ -478,14 +461,13 @@ robyn_allocator <- function(robyn_object = NULL, if (scenario == "target_efficiency") { ## bounded optimisation - total_response <- sum(OutputCollect$xDecompAgg$xDecompAgg) nlsMod <- nloptr::nloptr( x0 = x0, eval_f = eval_f, eval_g_eq = if (constr_mode == "eq") eval_g_eq_effi else NULL, eval_g_ineq = if (constr_mode == "ineq") eval_g_eq_effi else NULL, lb = lb, - ub = rep(total_response, length(ub)), + ub = ub, # Large enough, but not infinite (customizable) opts = list( "algorithm" = "NLOPT_LD_AUGLAG", "xtol_rel" = 1.0e-10, @@ -496,12 +478,12 @@ robyn_allocator <- function(robyn_object = NULL, ) ## unbounded optimisation nlsModUnbound <- nloptr::nloptr( - x0 = x0, + x0 = x0_ext, eval_f = eval_f, eval_g_eq = if (constr_mode == "eq") eval_g_eq_effi else NULL, eval_g_ineq = if (constr_mode == "ineq") eval_g_eq_effi else NULL, - lb = lb, - ub = rep(total_response, length(ub)), + lb = lb_ext, + ub = ub_ext, # Large enough, but not infinite (customizable) opts = list( "algorithm" = "NLOPT_LD_AUGLAG", "xtol_rel" = 1.0e-10, @@ -543,7 +525,7 @@ robyn_allocator <- function(robyn_object = NULL, names(optmSpendUnit) <- names(optmResponseUnit) <- names(optmResponseMargUnit) <- names(optmSpendUnitUnbound) <- names(optmResponseUnitUnbound) <- names(optmResponseMargUnitUnbound) <- channel_for_allocation - mediaSpendSorted %in% names(optmSpendUnit) + mediaSelectedSorted %in% names(optmSpendUnit) optmSpendUnitOut <- optmResponseUnitOut <- optmResponseMargUnitOut <- optmSpendUnitUnboundOut <- optmResponseUnitUnboundOut <- optmResponseMargUnitUnboundOut <- initSpendUnit @@ -563,7 +545,7 @@ robyn_allocator <- function(robyn_object = NULL, dt_optimOut <- data.frame( solID = select_model, dep_var_type = dep_var_type, - channels = mediaSpendSorted, + channels = mediaSelectedSorted, date_min = date_min, date_max = date_max, periods = sprintf("%s %ss", initial_mean_period, InputCollect$intervalType), @@ -691,7 +673,7 @@ robyn_allocator <- function(robyn_object = NULL, x = simulate_spend, coeff = eval_list$coefs_eval[[i]], alpha = eval_list$alphas_eval[[paste0(i, "_alphas")]], - inflexion = eval_list$inflexions_eval[[paste0(i, "_gammas")]], + inflexion = eval_list$inflexions_eval[[paste0(i, "_inflexion")]], x_hist_carryover = 0, get_sum = FALSE ) @@ -699,7 +681,7 @@ robyn_allocator <- function(robyn_object = NULL, x = mean(carryover_vec), coeff = eval_list$coefs_eval[[i]], alpha = eval_list$alphas_eval[[paste0(i, "_alphas")]], - inflexion = eval_list$inflexions_eval[[paste0(i, "_gammas")]], + inflexion = eval_list$inflexions_eval[[paste0(i, "_inflexion")]], x_hist_carryover = 0, get_sum = FALSE ) @@ -860,6 +842,7 @@ eval_f <- function(X, target_value) { inflexions_eval <- eval_list[["inflexions_eval"]] # mediaSpendSortedFiltered <- eval_list[["mediaSpendSortedFiltered"]] hist_carryover_eval <- eval_list[["hist_carryover_eval"]] + inflations_eval <- eval_list[["inflations_eval"]] objective <- -sum(mapply( fx_objective, @@ -895,7 +878,7 @@ eval_f <- function(X, target_value) { return(optm) } -fx_objective <- function(x, coeff, alpha, inflexion, x_hist_carryover, get_sum = TRUE) { +fx_objective <- function(x, coeff, alpha, inflexion, x_hist_carryover, inflation = NULL, get_sum = TRUE) { # Apply Michaelis Menten model to scale spend to exposure # if (criteria) { # xScaled <- mic_men(x = x, Vmax = vmax, Km = km) # vmax * x / (km + x) @@ -907,6 +890,7 @@ fx_objective <- function(x, coeff, alpha, inflexion, x_hist_carryover, get_sum = # Adstock scales xAdstocked <- x + mean(x_hist_carryover) + # xAdstocked <- x * inflation # Hill transformation if (get_sum) { xOut <- coeff * sum((1 + inflexion**alpha / xAdstocked**alpha)**-1) @@ -917,7 +901,7 @@ fx_objective <- function(x, coeff, alpha, inflexion, x_hist_carryover, get_sum = } # https://www.derivative-calculator.net/ on the objective function 1/(1+gamma^alpha / x^alpha) -fx_gradient <- function(x, coeff, alpha, inflexion, x_hist_carryover +fx_gradient <- function(x, coeff, alpha, inflexion, x_hist_carryover, inflation = NULL # , chnName, vmax, km, criteria ) { # Apply Michaelis Menten model to scale spend to exposure @@ -931,11 +915,12 @@ fx_gradient <- function(x, coeff, alpha, inflexion, x_hist_carryover # Adstock scales xAdstocked <- x + mean(x_hist_carryover) + # xAdstocked <- x * inflation xOut <- -coeff * sum((alpha * (inflexion**alpha) * (xAdstocked**(alpha - 1))) / (xAdstocked**alpha + inflexion**alpha)**2) return(xOut) } -fx_objective.chanel <- function(x, coeff, alpha, inflexion, x_hist_carryover +fx_objective.chanel <- function(x, coeff, alpha, inflexion, x_hist_carryover, inflation = NULL # , chnName, vmax, km, criteria ) { # Apply Michaelis Menten model to scale spend to exposure @@ -949,6 +934,7 @@ fx_objective.chanel <- function(x, coeff, alpha, inflexion, x_hist_carryover # Adstock scales xAdstocked <- x + mean(x_hist_carryover) + # xAdstocked <- x * inflation xOut <- -coeff * sum((1 + inflexion**alpha / xAdstocked**alpha)**-1) return(xOut) } @@ -1026,30 +1012,3 @@ get_adstock_params <- function(InputCollect, dt_hyppar) { } return(getAdstockHypPar) } - -get_hill_params <- function(InputCollect, OutputCollect = NULL, dt_hyppar, dt_coef, mediaSpendSorted, select_model, chnAdstocked = NULL) { - hillHypParVec <- unlist(select(dt_hyppar, na.omit(str_extract(names(dt_hyppar), ".*_alphas|.*_gammas")))) - alphas <- hillHypParVec[paste0(mediaSpendSorted, "_alphas")] - gammas <- hillHypParVec[paste0(mediaSpendSorted, "_gammas")] - if (is.null(chnAdstocked)) { - chnAdstocked <- filter( - OutputCollect$mediaVecCollect, - .data$type == "adstockedMedia", - .data$solID == select_model - ) %>% - select(all_of(mediaSpendSorted)) %>% - slice(InputCollect$rollingWindowStartWhich:InputCollect$rollingWindowEndWhich) - } - inflexions <- unlist(lapply(seq(ncol(chnAdstocked)), function(i) { - c(range(chnAdstocked[, i]) %*% c(1 - gammas[i], gammas[i])) - })) - names(inflexions) <- names(gammas) - coefs <- dt_coef$coef - names(coefs) <- dt_coef$rn - coefs_sorted <- coefs[mediaSpendSorted] - return(list( - alphas = alphas, - inflexions = inflexions, - coefs_sorted = coefs_sorted - )) -} diff --git a/R/R/auxiliary.R b/R/R/auxiliary.R index c4c53ccea..b42e131ab 100644 --- a/R/R/auxiliary.R +++ b/R/R/auxiliary.R @@ -77,15 +77,67 @@ baseline_vars <- function(InputCollect, baseline_level) { stopifnot(length(baseline_level) == 1) stopifnot(baseline_level %in% 0:5) x <- "" - if (baseline_level >= 1) + if (baseline_level >= 1) { x <- c(x, "(Intercept)", "intercept") - if (baseline_level >= 2) + } + if (baseline_level >= 2) { x <- c(x, "trend") - if (baseline_level >= 3) + } + if (baseline_level >= 3) { x <- unique(c(x, InputCollect$prophet_vars)) - if (baseline_level >= 4) + } + if (baseline_level >= 4) { x <- c(x, InputCollect$context_vars) - if (baseline_level >= 5) + } + if (baseline_level >= 5) { x <- c(x, InputCollect$organic_vars) + } return(x) } + +# Calculate dot product +.dot_product <- function(range, proportion) { + mapply(function(proportion) { + c(range %*% c(1 - proportion, proportion)) + }, + proportion = proportion) +} + +# Calculate quantile interval +.qti <- function(x, interval = 0.95) { + check_qti(interval) + int_low <- (1 - interval)/2 + int_up <- 1 - int_low + qt_low <- quantile(x, int_low) + qt_up <- quantile(x, int_up) + return(c(qt_low, qt_up)) +} + +# Calculate MSE +.mse_loss <- function(y, y_hat) mean((y - y_hat)^2) + +# next_date(c("2021-01-01", "2021-02-01")) +# next_date(c("2021-01-01", "2021-01-08", "2021-01-15")) +# next_date(c(Sys.Date() - 1, Sys.Date())) +.next_date <- function(dates) { + dates <- as.Date(dates) + diffs <- diff(dates) + if (all(diffs == 1)) { + frequency <- "daily" + } else if (all(diffs == 7)) { + frequency <- "weekly" + } else if (all(format(dates[-length(dates)], "%Y-%m") != format(dates[-1], "%Y-%m"))) { + frequency <- "monthly" + } else { + warning(paste( + "Unable to determine frequency to calculate next logical date.", + "Returning last available date.")) + return(as.Date(tail(dates, 1))) + } + next_date <- switch( + frequency, + "daily" = dates[length(dates)] + 1, + "weekly" = dates[length(dates)] + 7, + "monthly" = seq(dates[length(dates)], by = "1 month", length.out = 2)[2]) + return(as.Date(next_date)) +} diff --git a/R/R/calibration.R b/R/R/calibration.R index f0cc4c26f..ba283de6d 100644 --- a/R/R/calibration.R +++ b/R/R/calibration.R @@ -3,15 +3,505 @@ # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. -robyn_calibrate <- function(calibration_input, - df_raw, # df_raw = InputCollect$dt_mod - dayInterval, # dayInterval = InputCollect$dayInterval - xDecompVec, # xDecompVec = decompCollect$xDecompVec - coefs, # coefs = decompCollect$coefsOutCat - hypParamSam, - wind_start = 1, - wind_end = nrow(df_raw), - adstock) { +#################################################################### +#' Robyn Calibration Function - BETA +#' +#' \code{robyn_calibrate()} consumes source of truth or proxy data for +#' saturation or adstock curve estimation. This is an experimental feature and +#' can be used independently from Robyn's main model. +#' +#' @inheritParams robyn_run +#' @param df_curve data.frame. Requires two columns named spend and response. +#' Recommended sources of truth are Halo R&F or Meta conversion lift. +#' @param curve_type Character. Currently only allows "saturation_reach_hill" +#' and only supports Hill function. +#' @param force_shape Character. Allows c("c", "s") with default NULL that's no +#' shape forcing. It's recommended for offline media to have "c" shape, while +#' for online can be "s" or NULL. Shape forcing only works if hp_bounds is null. +#' @param hp_bounds list. Currently only allows Hill for saturation. Ranges +#' for alpha and gamma are provided as Hill parameters. If NULL, hp_bounds takes +#' on default ranges. +#' @param max_trials integer. Different trials have different starting point +#' and provide diversified sampling paths. Default to 10. +#' @param max_iters integer. Loss is minimized while iteration increases. +#' Default to 2500. +#' @param loss_min_step_rel numeric. Default to 0.01 and value is between 0-0.1. +#' 0.01 means the optimisation is considered converged if error minimization is +#' <1 percent of maximal error. +#' @param loss_stop_rel numeric. Default is 0.05 and value is between 0-0.5. +#' 0.05 means 5 percent of the max_iters is used as the length of iterations to +#' calculate the mean error for convergence. +#' @param burn_in_rel numeric. Default to 0.1 and value is between 0.0.5. 0.1 +#' means 10 percent of iterations is used as burn-in period. +#' @param sim_n integer. Number of simulation for plotting fitted curve. +#' @param hp_interval numeric. Default to 0.95 and is between 0.8-1. 0.95 means +#' 2.5 - 97.5 percent percentile are used as parameter range for output. +#' @examples +#' \dontrun{ +#' # Dummy input data for Meta spend. This is derived from Halo's reach & frequency data. +#' # Note that spend and response need to be cumulative metrics. +#' data("df_curve_reach_freq") +#' +#' # Using reach saturation from Halo as proxy +#' curve_out <- robyn_calibrate( +#' df_curve = df_curve_reach_freq, +#' curve_type = "saturation_reach_hill" +#' ) +#' # For the simulated reach and frequency dataset, it's recommended to use +#' # "reach 1+" for gamma lower bound and "reach 10+" for gamma upper bound +#' facebook_I_gammas <- c( +#' curve_out[["curve_collect"]][["reach 1+"]][["hill"]][["gamma_best"]], +#' curve_out[["curve_collect"]][["reach 10+"]][["hill"]][["gamma_best"]]) +#' print(facebook_I_gammas) +#' } +#' @return List. Class: \code{curve_out}. Contains the results of all trials +#' and iterations modeled. +#' @export +robyn_calibrate <- function( + df_curve = NULL, + curve_type = NULL, + force_shape = NULL, + hp_bounds = NULL, + max_trials = 10, + max_iters = 2500, + loss_min_step_rel = 0.0001, + loss_stop_rel = 0.05, + burn_in_rel = 0.1, + sim_n = 30, + hp_interval = 0.5, + quiet = FALSE, + ...) { + ## check all inputs + # df_curve df format + # curve types + # hp_bounds format + # hp_interval + + if (curve_type == "saturation_reach_hill") { + curve_collect <- list() + for (i in unique(df_curve$freq_bucket)) { + message(">>> Fitting ", i) + df_curve_i <- df_curve %>% filter(.data$freq_bucket == i) + curve_collect[[i]] <- robyn_calibrate_single_dim( + df_curve = df_curve_i, + curve_type, + force_shape = "c", # assumption: reach saturation is always concave + hp_bounds, + max_trials, + max_iters, + loss_min_step_rel, + loss_stop_rel, + burn_in_rel, + sim_n, + hp_interval, + quiet) + } + + df_curve_plot <- bind_rows(lapply(curve_collect, function(x) x$df_out)) + + p_rnf <- ggplot(df_curve_plot, aes(x = .data$spend_cumulated)) + + geom_point(aes(y = .data$response_cumulated, colour = .data$freq_bucket)) + + geom_line(aes(y = .data$response_pred, colour = .data$freq_bucket), alpha = 0.5) + + labs( + title = "Cumulative reach & frequency saturation fitting", + subtitle = "The dots are input R&F data. The lines are fitted curves.", + x = "cumulative spend", + y = "cumulative reach" + ) + + #theme_lares(background = "white")+ + #scale_alpha_discrete(range = c(1, 0.2)) + scale_colour_discrete(h =c(120,260)) + + return(list(curve_collect = curve_collect, + plot_reach_freq = p_rnf)) + } else { + curve_collect <- robyn_calibrate_single_dim( + df_curve, + curve_type, + force_shape, + hp_bounds, + max_trials, + max_iters, + loss_min_step_rel, + loss_stop_rel, + burn_in_rel, + sim_n, + hp_interval, + quiet) + return(list(curve_collect = curve_collect)) + } +} + + +robyn_calibrate_single_dim <- function( + df_curve, + curve_type, + force_shape, + hp_bounds, + max_trials, + max_iters, + loss_min_step_rel, + loss_stop_rel, + burn_in_rel, + sim_n, + hp_interval, + quiet, + ...) { + spend_cum_sot <- df_curve[["spend_cumulated"]] + response_cum_sot <- df_curve[["response_cumulated"]] + # amend 0 if not available + if (!any(spend_cum_sot == 0)) { + spend_cum_sot <- c(0, spend_cum_sot) + response_cum_sot <- c(0, response_cum_sot) + } + + ## get hyperparameter bounds + if (is.null(hp_bounds)) { + hp_bounds <- list(hill = list(alpha = c(0, 10), gamma = c(0, 1)), coef = c(0, max(response_cum_sot) / 0.01)) + hp_bounds_loop <- hp_bounds[["hill"]] + hp_bounds_loop[["coef"]] <- hp_bounds[["coef"]] + if (force_shape == "s") { + hp_bounds_loop[["alpha"]] <- c(1, 10) + } else if (force_shape == "c") { + hp_bounds_loop[["alpha"]] <- c(0, 1) + } + } else { + hp_bounds_loop <- hp_bounds[["hill"]] + hp_bounds_loop[["coef"]] <- hp_bounds[["coef"]] + } + + ## initiate Nevergrad + if (reticulate::py_module_available("nevergrad")) { + ng <- reticulate::import("nevergrad", delay_load = TRUE) + } + + ## trial loop + ng_hp <- list() + loss_collect <- c() + pred_collect <- list() + loss_stop_abs <- round(max_iters * loss_stop_rel) + max_iters_vec <- rep(max_iters, max_trials) + + for (j in seq(max_trials)) { + my_tuple <- reticulate::tuple(as.integer(3)) + instrumentation <- ng$p$Array(shape = my_tuple, lower = 0, upper = 1) + optimizer <- ng$optimizers$registry["TwoPointsDE"](instrumentation, budget = max_iters) + + ## inner while loop that stops when converged + ng_hp_i <- list() + loss_collect_i <- c() + pred_collect_i <- list() + if (!quiet) pb_cf <- txtProgressBar(min = 0, max = max_iters_vec[j], style = 3) + loop_continue <- TRUE + i <- 0 + + while (loop_continue) { + i <- i + 1 + if (!quiet) setTxtProgressBar(pb_cf, i) + + ## Nevergrad ask sample + ng_hp_i[[i]] <- optimizer$ask() + ng_hp_val <- ng_hp_i[[i]]$value + ng_hp_val_scaled <- mapply( + function(hpb, hp) { + qunif(hp, min = min(hpb), max = max(hpb)) + }, + hpb = hp_bounds_loop, + hp = ng_hp_val + ) + alpha <- ng_hp_val_scaled["alpha"] + gamma <- ng_hp_val_scaled["gamma"] + coeff <- ng_hp_val_scaled["coef"] + + ## predict saturation vector + total_cum_spend <- max(spend_cum_sot) + response_pred <- coeff * saturation_hill(x = total_cum_spend, alpha, gamma, x_marginal = spend_cum_sot)[["x_saturated"]] + # response_sot_scaled <- .min_max_norm(response_cum_sot) + + ## get loss + loss_iter <- sqrt(.mse_loss(y = response_cum_sot, y_hat = response_pred)) + max_loss <- ifelse(i == 1, loss_iter, max(max_loss, loss_iter)) + loss_min_step_abs <- max_loss * loss_min_step_rel + + ## collect loop results + pred_collect_i[[i]] <- response_pred + loss_collect_i[i] <- loss_iter + + ## Nevergrad tell loss + optimizer$tell(ng_hp_i[[i]], tuple(loss_iter)) + + ## Loop config & prompting + if ((i >= (loss_stop_abs * 2))) { + if ((i == max_iters_vec[j])) { + loop_continue <- FALSE + if (!quiet) { + close(pb_cf) + message(paste0( + "Trial ", j, " didn't converged after ", i, + " iterations. Increase iterations or adjust convergence criterias." + )) + } + } else { + current_unit <- (i - loss_stop_abs + 1):i + previous_unit <- current_unit - loss_stop_abs + loss_unit_change <- (mean(loss_collect_i[current_unit]) - mean(loss_collect_i[previous_unit])) + loop_continue <- !all(loss_unit_change > 0, loss_unit_change <= loss_min_step_abs) + + if (loop_continue == FALSE) { + if (!quiet) { + close(pb_cf) + message(paste0( + "Trial ", j, " converged & stopped at iteration ", i, + " from ", max_iters_vec[j] + )) + } + max_iters_vec[j] <- i + } + } + } + } + ng_hp[[j]] <- ng_hp_i + loss_collect[[j]] <- loss_collect_i + pred_collect[[j]] <- pred_collect_i + if (!quiet) close(pb_cf) + } + + ## collect loop output + best_loss_iters <- mapply(function(x) which.min(x), x = loss_collect) + best_loss_vals <- mapply(function(x) min(x), x = loss_collect) + best_loss_trial <- which.min(best_loss_vals) + best_loss_iter <- best_loss_iters[best_loss_trial] + best_loss_val <- best_loss_vals[best_loss_trial] + best_hp <- ng_hp[[best_loss_trial]][[best_loss_iter]]$value + best_pred_response <- pred_collect[[best_loss_trial]][[best_loss_iter]] + + ## saturation hill + hp_alpha <- hp_bounds_loop[["alpha"]] + hp_gamma <- hp_bounds_loop[["gamma"]] + hp_coef <- hp_bounds_loop[["coef"]] + best_alpha <- qunif(best_hp[1], min = min(hp_alpha), max = max(hp_alpha)) + best_gamma <- qunif(best_hp[2], min = min(hp_gamma), max = max(hp_gamma)) + best_coef <- qunif(best_hp[3], min = min(hp_coef), max = max(hp_coef)) + # best_response_pred <- saturation_hill(spend_cum_sot, best_alpha, best_gamma)[["x_saturated"]] + # best_inflexion <- saturation_hill(spend_cum_sot, best_alpha, best_gamma)[["inflexion"]] + alpha_collect <- lapply(ng_hp, FUN = function(x) { + sapply(x, FUN = function(y) qunif(y$value[1], min = min(hp_alpha), max = max(hp_alpha))) + }) + gamma_collect <- lapply(ng_hp, FUN = function(x) { + sapply(x, FUN = function(y) qunif(y$value[2], min = min(hp_gamma), max = max(hp_gamma))) + }) + coef_collect <- lapply(ng_hp, FUN = function(x) { + sapply(x, FUN = function(y) qunif(y$value[3], min = min(hp_coef), max = max(hp_coef))) + }) + + ## slice by convergence + burn_in_abs <- rep(max_iters * burn_in_rel, max_trials) + alpha_collect_converged <- unlist(mapply( + function(x, start, end) x[start:end], + x = alpha_collect, start = burn_in_abs, + end = max_iters_vec, SIMPLIFY = FALSE + )) + gamma_collect_converged <- unlist(mapply( + function(x, start, end) x[start:end], + x = gamma_collect, start = burn_in_abs, + end = max_iters_vec, SIMPLIFY = FALSE + )) + coef_collect_converged <- unlist(mapply( + function(x, start, end) x[start:end], + x = coef_collect, start = burn_in_abs, + end = max_iters_vec, SIMPLIFY = FALSE + )) + + ## get calibration range for hyparameters + p_alpha <- data.frame(alpha = alpha_collect_converged) %>% + ggplot(aes(x = alpha)) + geom_density(fill = "grey99", color = "grey") + alpha_den <- .den_interval(p_alpha, hp_interval, best_alpha) + + p_gamma <- data.frame(gamma = gamma_collect_converged) %>% ggplot(aes(x = gamma)) + + geom_density(fill = "grey99", color = "grey") + gamma_den <- .den_interval(p_gamma, hp_interval, best_gamma) + + p_coef <- data.frame(coef = coef_collect_converged) %>% ggplot(aes(x = coef)) + + geom_density(fill = "grey99", color = "grey") + coef_den <- .den_interval(p_coef, hp_interval, best_coef) + + # qt_alpha_out <- .qti(x = alpha_collect_converged, interval = hp_interval) + # qt_gamma_out <- .qti(x = gamma_collect_converged, interval = hp_interval) + # qt_coef_out <- .qti(x = coef_collect_converged, interval = hp_interval) + + ## plotting & prompting + #coef_response <- max(response_cum_sot) / max(response_sot_scaled) + df_sot_plot <- data.frame( + spend = spend_cum_sot, + response = response_cum_sot, + response_pred = best_pred_response) + temp_spend <- seq(0, max(spend_cum_sot), length.out = sim_n) + temp_sat <- best_coef * saturation_hill(x = total_cum_spend, alpha = best_alpha, gamma = best_gamma, x_marginal = temp_spend)[["x_saturated"]] + df_pred_sim_plot <- data.frame(spend = temp_spend, response = temp_sat) + + sim_alphas <- alpha_collect_converged[ + alpha_collect_converged > alpha_den$interval[1] & + alpha_collect_converged < alpha_den$interval[2] + ] + sim_alphas <- sample(sim_alphas, sim_n, replace = TRUE) + sim_gammas <- gamma_collect_converged[ + gamma_collect_converged > gamma_den$interval[1] & + gamma_collect_converged < gamma_den$interval[2] + ] + sim_gammas <- sample(sim_gammas, sim_n, replace = TRUE) + + # simulation for plotting + sim_collect <- list() + for (i in 1:sim_n) { + sim_collect[[i]] <- best_coef * saturation_hill(x = total_cum_spend, alpha = sim_alphas[i], gamma = sim_gammas[i], x_marginal = temp_spend)[["x_saturated"]] + } + sim_collect <- data.frame( + sim = as.character(c(sapply(1:sim_n, function(x) rep(x, length(temp_spend))))), + sim_spend = rep(temp_spend, sim_n), + sim_saturation = unlist(sim_collect) + ) + + y_lab <- "response proxy" + p_lines <- ggplot() + + geom_line( + data = sim_collect, + aes( + x = .data$sim_spend, y = .data$sim_saturation, + color = .data$sim + ), size = 2, alpha = 0.2 + ) + + scale_colour_grey() + + geom_point( + data = df_sot_plot, + aes(x = .data$spend, y = .data$response) + ) + + geom_line( + data = df_pred_sim_plot, + aes(x = .data$spend, y = .data$response), color = "blue" + ) + + labs(title = paste0("Spend to ", y_lab, " saturation curve estimation")) + + ylab(y_lab) + + xlab("Spend") + + theme_lares(legend = "none", ...) + + df_mse <- data.frame( + mse = unlist(loss_collect), + iterations = unlist(mapply(function(x) seq(x), max_iters_vec, SIMPLIFY = FALSE)), + trials = as.character(unlist( + mapply(function(x, y) rep(x, y), + x = 1:max_trials, y = max_iters_vec + ) + )) + ) + p_mse <- df_mse %>% + mutate(trials = factor(.data$trials, levels = seq(max_trials))) %>% + ggplot(aes(x = .data$iterations, y = .data$mse)) + + geom_line(size = 0.2) + + facet_grid(.data$trials ~ .) + + labs( + title = paste0( + "Loss convergence with error reduction of ", + round((1 - best_loss_val / max_loss), 4) * 100, "%" + ), + x = "Iterations", y = "MSE" + ) + + theme_lares(grid = "Xx", ...) + + scale_x_abbr() + + theme( + axis.text.y = element_blank(), + axis.ticks.y = element_blank() + ) + + p_alpha <- p_alpha + + labs( + title = paste0("Alpha (Hill) density after ", round(burn_in_rel * 100), "% burn-in"), + subtitle = paste0(round(hp_interval*100), "% center density: ", round(alpha_den$interval[1], 4), "-", round(alpha_den$interval[2], 4), + "\nBest alpha: ", round(best_alpha,4)) + ) + + theme_lares(...) + + scale_y_abbr() + p_alpha <- geom_density_ci(p_alpha, alpha_den$interval[1], alpha_den$interval[2], fill = "lightblue") + + p_gamma <- p_gamma + + labs( + title = paste0("Gamma (Hill) density after ", round(burn_in_rel * 100), "% burn-in"), + subtitle = paste0(round(hp_interval*100), "% center density: ", round(gamma_den$interval[1], 4), "-", round(gamma_den$interval[2], 4), + "\nBest gamma: ", round(best_gamma,4)) + ) + + theme_lares(...) + + scale_y_abbr() + p_gamma <- geom_density_ci(p_gamma, gamma_den$interval[1], gamma_den$interval[2], fill = "lightblue") + + # p_coef <- p_coef + + # labs( + # title = paste0("Beta coefficient density after ", round(burn_in_rel * 100), "% burn-in"), + # subtitle = paste0(round(hp_interval*100), "% center density: ", round(exp(coef_den$interval[1])), "-", round(exp(coef_den$interval[2]))), + # x = "log(coef)" + # ) + + # theme_lares(...) + + # scale_y_abbr() + # p_coef <- geom_density_ci(p_coef, coef_den$interval[1], coef_den$interval[2], fill = "lightblue") + + if (!quiet) { + message( + paste0( + "\nBest alpha: ", round(best_alpha, 4), " (", + paste0(round(alpha_den$interval, 4), collapse = "-"), ")", + ", Best gamma: ", round(best_gamma, 4), " (", + paste0(round(gamma_den$interval, 4), collapse = "-"), ")", + ", Best coef: ", round(best_coef), " (", + paste0(round(coef_den$interval), collapse = "-"), ")", + ", Total spend: ", max(spend_cum_sot), ", Best loss: ", + round(best_loss_val, 4), "\n" + ) + ) + } + + curve_out <- list( + hill = list(alpha_range = c(alpha_den$interval), + alpha_best = best_alpha, + gamma_range = c(gamma_den$interval), + gamma_best = best_gamma, + coef_range = c(coef_den$interval), + coef_best = best_coef, + inflexion_max = total_cum_spend), + plot = p_lines / p_mse / (p_alpha + p_gamma) + + plot_annotation( + theme = theme_lares(background = "white", ...) + ), + df_out = df_curve %>% + mutate(response_pred = best_pred_response), + df_out_sim = df_pred_sim_plot %>% + mutate(response_pred = .data$response) + ) + return(curve_out) +} + + +.den_interval <- function(plot_object, hp_interval, best_val) { + get_den <- ggplot_build(plot_object)$data[[1]] + # mode_loc <- which.max(get_den$y) + mode_loc <- which.min(abs(get_den$x - best_val)) + mode_wing <- sum(get_den$y) * hp_interval /2 + int_left <- mode_loc - which.min(abs(cumsum(get_den$y[mode_loc:1]) - mode_wing)) + 1 + int_left <- ifelse(is.na(int_left) | int_left < 1, 1, int_left) + int_right <- mode_loc + which.min(abs(cumsum(get_den$y[(mode_loc+1):length(get_den$y)]) - mode_wing)) + int_right <- ifelse(length(int_right) == 0 , length(get_den$y), int_right) + return(list(interval = c(get_den$x[int_left], get_den$x[int_right]), + mode = get_den$x[mode_loc])) +} + + +lift_calibration <- function( + calibration_input, + df_raw, # df_raw = InputCollect$dt_mod + dayInterval, # dayInterval = InputCollect$dayInterval + xDecompVec, # xDecompVec = decompCollect$xDecompVec + coefs, # coefs = decompCollect$coefsOutCat + hypParamSam, + wind_start = 1, + wind_end = nrow(df_raw), + adstock) { ds_wind <- df_raw$ds[wind_start:wind_end] include_study <- any( calibration_input$liftStartDate >= min(ds_wind) & @@ -24,7 +514,7 @@ robyn_calibrate <- function(calibration_input, calibration_input, pred = NA, pred_total = NA, decompStart = NA, decompEnd = NA ) - split_channels <- strsplit(calibration_input$channel, split = "\\+") + split_channels <- strsplit(calibration_input$channel_selected, split = "\\+") for (l_study in seq_along(split_channels)) { get_channels <- split_channels[[l_study]] @@ -56,24 +546,27 @@ robyn_calibrate <- function(calibration_input, scale <- hypParamSam[paste0(get_channels[l_chn], "_scales")][[1]][[1]] } x_list <- transform_adstock(m, adstock, theta = theta, shape = shape, scale = scale) + x_list_cal <- transform_adstock(m[calib_pos], adstock, theta = theta, shape = shape, scale = scale) if (adstock == "weibull_pdf") { m_imme <- x_list$x_imme + m_imme_cal <- x_list_cal$x_imme } else { m_imme <- m + m_imme_cal <- m[calib_pos] } m_total <- x_list$x_decayed - m_caov <- m_total - m_imme + # m_caov <- m_total - m_imme + m_total_cal <- x_list_cal$x_decayed ## 2. Saturation - m_caov_calib <- m_caov[calib_pos] m_total_rw <- m_total[wind_start:wind_end] alpha <- hypParamSam[paste0(get_channels[l_chn], "_alphas")][[1]][[1]] gamma <- hypParamSam[paste0(get_channels[l_chn], "_gammas")][[1]][[1]] m_calib_caov_sat <- saturation_hill( m_total_rw, - alpha = alpha, gamma = gamma, x_marginal = m_caov_calib + alpha = alpha, gamma = gamma, x_marginal = m_total[calib_pos] - m_total_cal ) - m_calib_caov_decomp <- m_calib_caov_sat * coefs$s0[coefs$rn == get_channels[l_chn]] + m_calib_caov_decomp <- m_calib_caov_sat$x_saturated * coefs$s0[coefs$rn == get_channels[l_chn]] m_calib_total_decomp <- xDecompVec[calib_pos_rw, get_channels[l_chn]] m_calib_decomp <- m_calib_total_decomp - m_calib_caov_decomp } @@ -118,7 +611,7 @@ robyn_calibrate <- function(calibration_input, decompAbsTotalScaled = .data$pred_total / .data$decompDays * .data$liftDays ) %>% mutate( - liftMedia = .data$channel, + liftMedia = .data$channel_selected, liftStart = .data$liftStartDate, liftEnd = .data$liftEndDate, mape_lift = abs((.data$decompAbsScaled - .data$liftAbs) / .data$liftAbs), diff --git a/R/R/checks.R b/R/R/checks.R index e9e068c74..fd6388885 100644 --- a/R/R/checks.R +++ b/R/R/checks.R @@ -10,7 +10,8 @@ HYPS_NAMES <- c("thetas", "shapes", "scales", "alphas", "gammas", "penalty") HYPS_OTHERS <- c("lambda", "train_size") LEGACY_PARAMS <- c("cores", "iterations", "trials", "intercept_sign", "nevergrad_algo") -check_nas <- function(df) { +check_nas <- function(df, channels = NULL) { + if (!is.null(channels)) df <- select(df, all_of(channels)) name <- deparse(substitute(df)) if (sum(is.na(df)) > 0) { naVals <- lares::missingness(df) @@ -56,39 +57,26 @@ check_allneg <- function(df) { return(df) } -check_varnames <- function(dt_input, dt_holidays, - dep_var, date_var, - context_vars, paid_media_spends, - organic_vars) { +check_varnames <- function(dt_input, dt_holidays) { dfs <- list(dt_input = dt_input, dt_holidays = dt_holidays) for (i in seq_along(dfs)) { # Which names to check by data.frame table_name <- names(dfs[i]) - if (table_name == "dt_input") { - vars <- c( - dep_var, date_var, context_vars, - paid_media_spends, organic_vars, "auto" - ) - } - if (table_name == "dt_holidays") { - vars <- c("ds", "country") # holiday? - } - df <- dfs[[i]] - vars <- vars[vars != "auto"] + temp_vars <- names(dt_input) # Duplicate names - if (length(vars) != length(unique(vars))) { - these <- names(table(vars)[table(vars) > 1]) + if (length(temp_vars) != length(unique(temp_vars))) { + these <- names(table(temp_vars)[table(temp_vars) > 1]) stop(paste( "You have duplicated variable names for", table_name, "in different parameters.", "Check:", paste(these, collapse = ", ") )) } # Names with spaces - with_space <- grepl(" ", vars) + with_space <- grepl(" ", temp_vars) if (sum(with_space) > 0) { stop(paste( "You have invalid variable names on", table_name, "with spaces.\n ", - "Please fix columns:", v2t(vars[with_space]) + "Please fix columns:", v2t(temp_vars[with_space]) )) } } @@ -200,6 +188,9 @@ check_prophet <- function(dt_holidays, prophet_country, prophet_vars, prophet_si if (is.null(prophet_signs)) { prophet_signs <- rep("default", length(prophet_vars)) } + if (length(prophet_signs) == 1) { + prophet_signs <- rep(prophet_signs, length(prophet_vars)) + } if (!all(prophet_signs %in% OPTS_PDN)) { stop("Allowed values for 'prophet_signs' are: ", paste(OPTS_PDN, collapse = ", ")) } @@ -293,10 +284,13 @@ check_paidmedia <- function(dt_input, paid_media_vars, paid_media_signs, paid_me " contains negative values. Media must be >=0" ) } + exposure_selector <- paid_media_spends != paid_media_vars + paid_media_selected <- ifelse(exposure_selector, paid_media_vars, paid_media_spends) return(invisible(list( paid_media_signs = paid_media_signs, - expVarCount = expVarCount, - paid_media_vars = paid_media_vars + paid_media_vars = paid_media_vars, + exposure_selector = exposure_selector, + paid_media_selected = paid_media_selected ))) } @@ -333,21 +327,20 @@ check_organicvars <- function(dt_input, organic_vars, organic_signs) { check_factorvars <- function(dt_input, factor_vars = NULL, context_vars = NULL) { check_vector(factor_vars) check_vector(context_vars) + if (!is.null(factor_vars)) { + if (!all(factor_vars %in% context_vars)) { + stop("Input 'factor_vars' must be any from 'context_vars' inputs") + } + } temp <- select(dt_input, all_of(context_vars)) - are_not_numeric <- !sapply(temp, is.numeric) - if (any(are_not_numeric)) { - these <- are_not_numeric[!names(are_not_numeric) %in% factor_vars] - these <- these[these] + undefined_factor <- !sapply(temp, function(x) is.integer(x) | is.numeric(x)) & !(names(temp) %in% factor_vars) + if (any(undefined_factor)) { + these <- temp[undefined_factor] if (length(these) > 0) { message("Automatically set these variables as 'factor_vars': ", v2t(names(these))) factor_vars <- c(factor_vars, names(these)) } } - if (!is.null(factor_vars)) { - if (!all(factor_vars %in% context_vars)) { - stop("Input 'factor_vars' must be any from 'context_vars' inputs") - } - } return(factor_vars) } @@ -402,30 +395,31 @@ check_windows <- function(dt_input, date_var, all_media, window_start, window_en refreshAddedStart <- window_start if (is.null(window_end)) { - window_end <- max(dates_vec) + window_end <- .next_date(dates_vec) - 1 } else { window_end <- as.Date(as.character(window_end), "%Y-%m-%d", origin = "1970-01-01") if (is.na(window_end)) { stop(sprintf("Input 'window_end' must have date format, i.e. '%s'", Sys.Date())) - } else if (window_end > max(dates_vec)) { - window_end <- max(dates_vec) + } else if (window_end > .next_date(dates_vec) - 1) { + window_end <- .next_date(dates_vec) - 1 message(paste( - "Input 'window_end' is larger than the latest date in input data.", - "It's automatically set to the latest date:", window_end + "Input 'window_end' is larger than the latest dates available in input data.", + "Automatically set to date:", window_end )) } else if (window_end < window_start) { - window_end <- max(dates_vec) + window_end <- .next_date(dates_vec) - 1 message(paste( "Input 'window_end' must be >= 'window_start.", - "It's automatically set to the latest date:", window_end + "Automatically set to date:", window_end )) } } + # Find closest date contained in input data rollingWindowEndWhich <- which.min(abs(difftime(dates_vec, window_end, units = "days"))) - if (!(window_end %in% dates_vec)) { - window_end <- dt_input[rollingWindowEndWhich, date_var][[1]] - message("Input 'window_end' is adapted to the closest date contained in input data: ", window_end) + if (!window_end %in% c(dates_vec, .next_date(dates_vec) - 1)) { + window_end <- .next_date(dt_input[seq(rollingWindowEndWhich), date_var][[1]]) - 1 + message("Input 'window_end' is adapted to the closest available date from input data: ", window_end) } rollingWindowLength <- rollingWindowEndWhich - rollingWindowStartWhich + 1 @@ -464,9 +458,10 @@ check_adstock <- function(adstock) { return(adstock) } -check_hyperparameters <- function(hyperparameters = NULL, adstock = NULL, - paid_media_spends = NULL, organic_vars = NULL, - exposure_vars = NULL) { +check_hyperparameters <- function( + hyperparameters = NULL, adstock = NULL, paid_media_selected = NULL, + paid_media_spends = NULL, organic_vars = NULL, exposure_vars = NULL, + prophet_vars = NULL, contextual_vars = NULL) { if (is.null(hyperparameters)) { message(paste( "Input 'hyperparameters' not provided yet. To include them, run", @@ -483,14 +478,24 @@ check_hyperparameters <- function(hyperparameters = NULL, adstock = NULL, hyperparameters_ordered <- hyperparameters[order(names(hyperparameters))] get_hyp_names <- names(hyperparameters_ordered) original_order <- sapply(names(hyperparameters), function(x) which(x == get_hyp_names)) + ref_hyp_name_selected <- hyper_names(adstock, all_media = paid_media_selected) ref_hyp_name_spend <- hyper_names(adstock, all_media = paid_media_spends) ref_hyp_name_expo <- hyper_names(adstock, all_media = exposure_vars) ref_hyp_name_org <- hyper_names(adstock, all_media = organic_vars) ref_hyp_name_other <- get_hyp_names[get_hyp_names %in% HYPS_OTHERS] # Excluding lambda (first HYPS_OTHERS) given its range is not customizable - ref_all_media <- sort(c(ref_hyp_name_spend, ref_hyp_name_org, HYPS_OTHERS)) - all_ref_names <- c(ref_hyp_name_spend, ref_hyp_name_expo, ref_hyp_name_org, HYPS_OTHERS) - all_ref_names <- all_ref_names[order(all_ref_names)] + ref_all_media <- sort(c(ref_hyp_name_selected, ref_hyp_name_org, HYPS_OTHERS)) + all_ref_names <- sort(c(ref_hyp_name_selected, ref_hyp_name_spend, ref_hyp_name_org, HYPS_OTHERS)) + + if (!all(get_hyp_names %in% ref_all_media)) { + diff_hyp_loc <- which(!(get_hyp_names %in% ref_all_media)) + diff_hyp_names <- get_hyp_names[diff_hyp_loc] + if (all(diff_hyp_names %in% ref_hyp_name_spend)) { + updated_hyp_names <- ref_hyp_name_selected[which(diff_hyp_names %in% ref_hyp_name_spend)] + get_hyp_names[diff_hyp_loc] <- updated_hyp_names + names(hyperparameters_ordered) <- get_hyp_names + } + } if (!all(get_hyp_names %in% all_ref_names)) { wrong_hyp_names <- get_hyp_names[which(!(get_hyp_names %in% all_ref_names))] stop( @@ -498,8 +503,17 @@ check_hyperparameters <- function(hyperparameters = NULL, adstock = NULL, paste(wrong_hyp_names, collapse = ", ") ) } + # Adding penalty variations to the dictionary + if (any(grepl("_penalty", paste0(get_hyp_names)))) { + ref_hyp_name_penalties <- paste0( + c(paid_media_selected, organic_vars, prophet_vars, contextual_vars), "_penalty" + ) + all_ref_names <- c(all_ref_names, ref_hyp_name_penalties) + } else { + ref_hyp_name_penalties <- NULL + } total <- length(get_hyp_names) - total_in <- length(c(ref_hyp_name_spend, ref_hyp_name_org, ref_hyp_name_other)) + total_in <- length(c(ref_hyp_name_selected, ref_hyp_name_org, ref_hyp_name_penalties, ref_hyp_name_other)) if (total != total_in) { stop(sprintf( paste( @@ -509,12 +523,6 @@ check_hyperparameters <- function(hyperparameters = NULL, adstock = NULL, total_in, total )) } - # Old workflow: replace exposure with spend hyperparameters - if (any(get_hyp_names %in% ref_hyp_name_expo)) { - get_expo_pos <- which(get_hyp_names %in% ref_hyp_name_expo) - get_hyp_names[get_expo_pos] <- ref_all_media[get_expo_pos] - names(hyperparameters_ordered) <- get_hyp_names - } check_hyper_limits(hyperparameters_ordered, "thetas") check_hyper_limits(hyperparameters_ordered, "alphas") check_hyper_limits(hyperparameters_ordered, "gammas") @@ -565,7 +573,7 @@ check_hyper_limits <- function(hyperparameters, hyper) { } check_calibration <- function(dt_input, date_var, calibration_input, dayInterval, dep_var, - window_start, window_end, paid_media_spends, organic_vars) { + window_start, window_end, paid_media_spends, organic_vars, paid_media_selected) { if (!is.null(calibration_input)) { calibration_input <- as_tibble(as.data.frame(calibration_input)) these <- c("channel", "liftStartDate", "liftEndDate", "liftAbs", "spend", "confidence", "metric", "calibration_scope") @@ -577,6 +585,10 @@ check_calibration <- function(dt_input, date_var, calibration_input, dayInterval } all_media <- c(paid_media_spends, organic_vars) cal_media <- str_split(calibration_input$channel, "\\+|,|;|\\s") + cal_media_selected <- lapply(cal_media, function(x) sapply(x, function(y) { + ifelse(y %in% c(paid_media_selected, organic_vars), y, paid_media_selected[paid_media_spends == y]) + })) + calibration_input$channel_selected <- sapply(cal_media_selected, function(x) paste0(x, collapse = "+")) if (!all(unlist(cal_media) %in% all_media)) { these <- unique(unlist(cal_media)[which(!unlist(cal_media) %in% all_media)]) stop(sprintf( @@ -823,11 +835,7 @@ check_init_msg <- function(InputCollect, cores) { if (cores == 1) { message(paste(base, "with no parallel computation")) } else { - if (check_parallel()) { - message(paste(base, "on", cores, "cores")) - } else { - message(paste(base, "on 1 core (Windows fallback)")) - } + message(paste(base, "on", cores, "cores")) } } @@ -835,72 +843,63 @@ check_class <- function(x, object) { if (any(!x %in% class(object))) stop(sprintf("Input object must be class %s", x)) } -check_allocator_constrains <- function(low, upr) { - max_length <- max(c(length(low), length(upr))) - if (any(low < 0)) { - stop("Inputs 'channel_constr_low' must be >= 0") - } - if (length(upr) != length(low)) { - stop("Inputs 'channel_constr_up' and 'channel_constr_low' must have the same length or length 1") - } - if (any(upr < low)) { - stop("Inputs 'channel_constr_up' must be >= 'channel_constr_low'") - } -} - -check_allocator <- function(OutputCollect, select_model, paid_media_spends, scenario, +check_allocator <- function(OutputCollect, select_model, paid_media_selected, scenario, channel_constr_low, channel_constr_up, constr_mode) { - check_allocator_constrains(channel_constr_low, channel_constr_up) if (!(select_model %in% OutputCollect$allSolutions)) { stop( "Provided 'select_model' is not within the best results. Try any of: ", paste(OutputCollect$allSolutions, collapse = ", ") ) } - if ("max_historical_response" %in% scenario) scenario <- "max_response" + if (length(paid_media_selected) <= 1) { + stop("Must have a valid model with at least two 'paid_media_selected'") + } opts <- c("max_response", "target_efficiency") # Deprecated: max_response_expected_spend if (!(scenario %in% opts)) { stop("Input 'scenario' must be one of: ", paste(opts, collapse = ", ")) } - if (!(scenario == "target_efficiency" & is.null(channel_constr_low) & is.null(channel_constr_up))) { - if (length(channel_constr_low) != 1 && length(channel_constr_low) != length(paid_media_spends)) { - stop(paste( - "Input 'channel_constr_low' have to contain either only 1", - "value or have same length as 'InputCollect$paid_media_spends':", length(paid_media_spends) - )) + if ((is.null(channel_constr_low) & !is.null(channel_constr_up)) | + (!is.null(channel_constr_low) & is.null(channel_constr_up))) { + stop("channel_constr_low and channel_constr_up must be both provided or both NULL") + } else if (!is.null(channel_constr_low) & !is.null(channel_constr_up)) { + if (any(channel_constr_low < 0)) { + stop("Inputs 'channel_constr_low' must be >= 0") } - if (length(channel_constr_up) != 1 && length(channel_constr_up) != length(paid_media_spends)) { - stop(paste( - "Input 'channel_constr_up' have to contain either only 1", - "value or have same length as 'InputCollect$paid_media_spends':", length(paid_media_spends) - )) + if ((length(channel_constr_low) != 1 && length(channel_constr_low) != length(paid_media_selected)) | + (length(channel_constr_up) != 1 && length(channel_constr_up) != length(paid_media_selected))) { + stop("'channel_constr_low' and 'channel_constr_up' require either only 1 value or the same length as 'paid_media_selected'") + } + if (any(channel_constr_up < channel_constr_low)) { + stop("Inputs 'channel_constr_up' must be >= 'channel_constr_low'") } } opts <- c("eq", "ineq") if (!(constr_mode %in% opts)) { stop("Input 'constr_mode' must be one of: ", paste(opts, collapse = ", ")) } - return(scenario) } -check_metric_type <- function(metric_name, paid_media_spends, paid_media_vars, exposure_vars, organic_vars) { - if (metric_name %in% paid_media_spends && length(metric_name) == 1) { - metric_type <- "spend" - } else if (metric_name %in% exposure_vars && length(metric_name) == 1) { - metric_type <- "exposure" - } else if (metric_name %in% organic_vars && length(metric_name) == 1) { +check_metric_type <- function(metric_name, paid_media_spends, paid_media_vars, paid_media_selected, exposure_vars, organic_vars) { + if (metric_name %in% organic_vars && length(metric_name) == 1) { metric_type <- "organic" + metric_name_updated <- metric_name + } else if ((metric_name %in% paid_media_spends && length(metric_name) == 1) | + (metric_name %in% paid_media_vars && length(metric_name) == 1)) { + metric_type <- "paid" + name_loc <- unique(c(which(metric_name == paid_media_spends), + which(metric_name == paid_media_vars))) + metric_name_updated <- paid_media_selected[name_loc] } else { stop(paste( "Invalid 'metric_name' input:", metric_name, - "\nInput should be any media variable from paid_media_spends (spend),", - "paid_media_vars (exposure), or organic_vars (organic):", - paste("\n- paid_media_spends:", v2t(paid_media_spends, quotes = FALSE)), - paste("\n- paid_media_vars:", v2t(paid_media_vars, quotes = FALSE)), + "\nInput should be any media variable from paid_media_selected", + "or organic_vars:", + paste("\n- paid_media_spends:", v2t(paid_media_selected, quotes = FALSE)), paste("\n- organic_vars:", v2t(organic_vars, quotes = FALSE)) )) } - return(metric_type) + return(list(metric_type = metric_type, + metric_name_updated = metric_name_updated)) } check_metric_dates <- function(date_range = NULL, all_dates, dayInterval = NULL, quiet = FALSE, is_allocator = FALSE, ...) { @@ -916,7 +915,7 @@ check_metric_dates <- function(date_range = NULL, all_dates, dayInterval = NULL, # dayInterval >= 30 & dayInterval <= 31 ~ 1, # )) # } - date_range = "all" + date_range <- "all" if (!quiet) message(sprintf("Automatically picked date_range = '%s'", date_range)) } if (grepl("last|all", date_range[1])) { @@ -926,54 +925,18 @@ check_metric_dates <- function(date_range = NULL, all_dates, dayInterval = NULL, date_range <- tail(all_dates, get_n) date_range_loc <- which(all_dates %in% date_range) date_range_updated <- all_dates[date_range_loc] - rg <- v2t(range(date_range_updated), sep = ":", quotes = FALSE) - } else { + } else if (is.Date(as.Date(date_range[1]))) { ## Using dates as date_range range - if (all(is.Date(as.Date(date_range, origin = "1970-01-01")))) { - date_range <- as.Date(date_range, origin = "1970-01-01") - if (length(date_range) == 1) { - ## Using only 1 date - if (all(date_range %in% all_dates)) { - date_range_updated <- date_range - date_range_loc <- which(all_dates == date_range) - if (!quiet) message("Using ds '", date_range_updated, "' as the response period") - } else { - date_range_loc <- which.min(abs(date_range - all_dates)) - date_range_updated <- all_dates[date_range_loc] - if (!quiet) warning("Input 'date_range' (", date_range, ") has no match. Picking closest date: ", date_range_updated) - } - } else if (length(date_range) == 2) { - ## Using two dates as "from-to" date range - date_range_loc <- unlist(lapply(date_range, function(x) which.min(abs(x - all_dates)))) - date_range_loc <- date_range_loc[1]:date_range_loc[2] - date_range_updated <- all_dates[date_range_loc] - if (!quiet & !all(date_range %in% date_range_updated)) { - warning(paste( - "At least one date in 'date_range' input do not match any date.", - "Picking closest dates for range:", paste(range(date_range_updated), collapse = ":") - )) - } - rg <- v2t(range(date_range_updated), sep = ":", quotes = FALSE) - get_n <- length(date_range_loc) - } else { - ## Manually inputting each date - date_range_updated <- date_range - if (all(date_range %in% all_dates)) { - date_range_loc <- which(all_dates %in% date_range_updated) - } else { - date_range_loc <- unlist(lapply(date_range_updated, function(x) which.min(abs(x - all_dates)))) - rg <- v2t(range(date_range_updated), sep = ":", quotes = FALSE) - } - if (all(na.omit(date_range_loc - lag(date_range_loc)) == 1)) { - date_range_updated <- all_dates[date_range_loc] - if (!quiet) warning("At least one date in 'date_range' do not match ds. Picking closest date: ", date_range_updated) - } else { - stop("Input 'date_range' needs to have sequential dates") - } - } + date_range_updated <- date_range <- as.Date(date_range, origin = "1970-01-01") + if (!all(date_range %in% all_dates)) { + date_range_loc <- range(sapply(date_range, FUN = function(x) which.min(abs(x - all_dates)))) + date_range_loc <- seq(from = date_range_loc[1], to = date_range_loc[2], by = 1) } else { - stop("Input 'date_range' must have date format '2023-01-01' or use 'last_n'") + date_range_loc <- which(all_dates %in% date_range) } + date_range_updated <- all_dates[date_range_loc] + } else { + stop("Input 'date_range' must have date format '1970-01-01' or use 'last_n'") } return(list( date_range_updated = date_range_updated, @@ -982,8 +945,9 @@ check_metric_dates <- function(date_range = NULL, all_dates, dayInterval = NULL, } check_metric_value <- function(metric_value, metric_name, all_values, metric_loc) { - get_n <- length(metric_loc) if (any(is.nan(metric_value))) metric_value <- NULL + get_n <- length(metric_loc) + metric_value_updated <- all_values[metric_loc] if (!is.null(metric_value)) { if (!is.numeric(metric_value)) { stop(sprintf( @@ -996,18 +960,14 @@ check_metric_value <- function(metric_value, metric_name, all_values, metric_loc )) } if (get_n > 1 & length(metric_value) == 1) { - metric_value_updated <- rep(metric_value / get_n, get_n) + metric_value_updated <- metric_value * (metric_value_updated / sum(metric_value_updated)) # message(paste0("'metric_value'", metric_value, " splitting into ", get_n, " periods evenly")) - } else { - if (length(metric_value) != get_n) { - stop("robyn_response metric_value & date_range must have same length\n") - } + } else if (get_n == 1 & length(metric_value) == 1) { metric_value_updated <- metric_value + } else { + stop("robyn_response metric_value & date_range must have same length\n") } } - if (is.null(metric_value)) { - metric_value_updated <- all_values[metric_loc] - } all_values_updated <- all_values all_values_updated[metric_loc] <- metric_value_updated return(list( @@ -1086,3 +1046,9 @@ check_refresh_data <- function(Robyn, dt_input) { )) } } + +check_qti <- function(interval) { + if (interval > 1 | interval < 0.5) { + stop("Quantile interval needs to be within 0.5-1.") + } +} diff --git a/R/R/clusters.R b/R/R/clusters.R index aba6f622b..b90b871a0 100644 --- a/R/R/clusters.R +++ b/R/R/clusters.R @@ -122,7 +122,9 @@ robyn_clusters <- function(input, dep_var_type, dim_red = dim_red, quiet = TRUE, seed = seed ) ) - cls$df <- group_by(cls$df, .data$cluster) %>% mutate(n = n()) %>% ungroup() + cls$df <- group_by(cls$df, .data$cluster) %>% + mutate(n = n()) %>% + ungroup() # Select top models by minimum (weighted) distance to zero all_paid <- setdiff(names(cls$df), c(ignore, "cluster")) @@ -341,6 +343,7 @@ errors_scores <- function(df, balance = rep(1, 3), ts_validation = TRUE, ...) { } .min_max_norm <- function(x, min = 0, max = 1) { + x[is.nan(x)] <- max x <- x[is.finite(x)] x <- x[!is.na(x)] if (length(x) <= 1) { diff --git a/R/R/data.R b/R/R/data.R index a17194386..09598358d 100644 --- a/R/R/data.R +++ b/R/R/data.R @@ -61,3 +61,45 @@ # lares::missingness(dt_prophet_holidays) # dt_prophet_holidays <- dplyr::filter(dt_prophet_holidays, !is.na(country)) # save(dt_prophet_holidays, file = "data/dt_prophet_holidays.RData", version = 2) + +#################################################################### +#' Robyn Dataset: Reach & frequency simulated dataset +#' +#' A simulated cumulated reach and spend dataset by frequency buckets. +#' The headers must be kept as +#' \code{c("spend_cumulated", "response_cumulated", "freq_bucket")}. +#' +#' +#' @family Dataset +#' @docType data +#' @usage data(df_curve_reach_freq) +#' @return data.frame +#' @format An object of class \code{"data.frame"} +#' \describe{ +#' \item{spend_cumulated}{cumulated spend of paid media} +#' \item{response_cumulated}{cumulated reach of paid media} +#' \item{freq_bucket}{Frequency bucket for cumulated reach} +#' } +#' @examples +#' data(df_curve_reach_freq) +#' head(df_curve_reach_freq) +#' @return Dataframe. +"df_curve_reach_freq" + +# xSample <- round(seq(0, 100000, length.out = 10)) +# gammaSamp <- seq(0.3, 1, length.out = 20) +# coeff <- 10000000 +# df_curve_reach_freq <- list() +# for (i in seq_along(gammaSamp)) { +# df_curve_reach_freq[[i]] <- data.frame( +# spend_cumulated = xSample, +# response_predicted = (xSample**0.5 / (xSample**0.5 + (gammaSamp[i] * max(xSample))**0.5)) * coeff , +# gamma = gammaSamp[i], +# freq_bucket = as.factor(paste0("reach ", i, "+")) +# ) +# } +# df_curve_reach_freq <- bind_rows(df_curve_reach_freq) %>% +# mutate(response_cumulated = response_predicted * (1+ runif(length(xSample) * length(gammaSamp), -0.05, 0.05))) %>% +# select(spend_cumulated, response_cumulated, response_predicted, freq_bucket) +# levels(df_curve_reach_freq$freq_bucket) <- paste0("reach ", seq_along(gammaSamp), "+") +# save(df_curve_reach_freq, file = "data/df_curve_reach_freq.RData", version = 2) diff --git a/R/R/imports.R b/R/R/imports.R index 4f51bdb85..22b1d619f 100644 --- a/R/R/imports.R +++ b/R/R/imports.R @@ -21,8 +21,8 @@ #' @importFrom doRNG %dorng% #' @importFrom doParallel registerDoParallel stopImplicitCluster #' @importFrom dplyr across any_of arrange as_tibble bind_rows case_when contains desc distinct -#' everything filter group_by lag left_join mutate n pull rename row_number select slice -#' summarise summarise_all ungroup all_of bind_cols mutate_at starts_with ends_with tally n_distinct +#' everything filter full_join group_by lag left_join mutate mutate_at n pull rename row_number select +#' slice summarise summarise_all ungroup all_of bind_cols mutate_at starts_with ends_with tally n_distinct #' @importFrom foreach foreach %dopar% getDoParWorkers registerDoSEQ #' @import ggplot2 #' @importFrom ggridges geom_density_ridges geom_density_ridges_gradient @@ -31,7 +31,6 @@ #' @importFrom lares check_opts clusterKmeans formatNum freqs glued num_abbr ohse removenacols #' theme_lares `%>%` scale_x_abbr scale_x_percent scale_y_percent scale_y_abbr try_require v2t #' @importFrom lubridate is.Date day floor_date -#' @importFrom minpack.lm nlsLM #' @importFrom nloptr nloptr #' @importFrom parallel detectCores #' @importFrom patchwork guide_area plot_layout plot_annotation wrap_plots diff --git a/R/R/inputs.R b/R/R/inputs.R index 0b3261b0b..879c07d4a 100644 --- a/R/R/inputs.R +++ b/R/R/inputs.R @@ -33,7 +33,7 @@ #' @param dt_holidays data.frame. Raw input holiday data. Load standard #' Prophet holidays using \code{data("dt_prophet_holidays")} #' @param date_var Character. Name of date variable. Daily, weekly -#' and monthly data supported. Weekly requires week-start of Monday or Sunday. +#' and monthly data supported. #' \code{date_var} must have format "2020-01-01" (YYY-MM-DD). #' Default to automatic date detection. #' @param dep_var Character. Name of dependent variable. Only one allowed @@ -74,7 +74,7 @@ #' @param factor_vars Character vector. Specify which of the provided #' variables in organic_vars or context_vars should be forced as a factor. #' @param prophet_vars Character vector. Include any of "trend", -#' "season", "weekday", "holiday" or NULL. Highly recommended +#' "season", "weekday", "monthly", "holiday" or NULL. Highly recommended #' to use all for daily data and "trend", "season", "holiday" for #' weekly and above cadence. Set to NULL to skip prophet's functionality. #' @param prophet_signs Character vector. Choose any of @@ -181,7 +181,7 @@ robyn_inputs <- function(dt_input = NULL, json <- robyn_read(json_file, step = 1, ...) if (is.null(dt_input)) { if ("raw_data" %in% names(json[["Extras"]])) { - dt_input <- json[["Extras"]]$raw_data + dt_input <- as_tibble(json[["Extras"]]$raw_data) } else { stop("Must provide 'dt_input' input; 'dt_holidays' input optional") } @@ -199,18 +199,14 @@ robyn_inputs <- function(dt_input = NULL, dt_input <- as_tibble(dt_input) if (!is.null(dt_holidays)) dt_holidays <- as_tibble(dt_holidays) + ## Check vars names (duplicates and valid) + check_varnames(dt_input, dt_holidays) + ## Check for NA and all negative values dt_input <- check_allneg(dt_input) - check_nas(dt_input) + check_nas(dt_input, c(paid_media_vars, paid_media_spends, context_vars, organic_vars)) check_nas(dt_holidays) - ## Check vars names (duplicates and valid) - check_varnames( - dt_input, dt_holidays, - dep_var, date_var, - context_vars, paid_media_spends, - organic_vars) - ## Check date input (and set dayInterval and intervalType) date_input <- check_datevar(dt_input, date_var) dt_input <- date_input$dt_input # sorted date by ascending @@ -233,8 +229,8 @@ robyn_inputs <- function(dt_input = NULL, ## Check paid media variables (and maybe transform paid_media_signs) if (is.null(paid_media_vars)) paid_media_vars <- paid_media_spends - paidmedia <- check_paidmedia(dt_input, paid_media_vars, paid_media_signs, paid_media_spends) - paid_media_signs <- paidmedia$paid_media_signs + paid_collect <- check_paidmedia(dt_input, paid_media_vars, paid_media_signs, paid_media_spends) + paid_media_signs <- paid_collect$paid_media_signs exposure_vars <- paid_media_vars[!(paid_media_vars == paid_media_spends)] ## Check organic media variables (and maybe transform organic_signs) @@ -245,7 +241,7 @@ robyn_inputs <- function(dt_input = NULL, factor_vars <- check_factorvars(dt_input, factor_vars, context_vars) ## Check all vars - all_media <- c(paid_media_spends, organic_vars) + all_media <- c(paid_collect$paid_media_selected, organic_vars) all_ind_vars <- c(tolower(prophet_vars), context_vars, all_media) check_allvars(all_ind_vars) @@ -254,16 +250,12 @@ robyn_inputs <- function(dt_input = NULL, ## Check window_start & window_end (and transform parameters/data) windows <- check_windows(dt_input, date_var, all_media, window_start, window_end) - - if (TRUE) { - dt_input <- windows$dt_input - window_start <- windows$window_start - rollingWindowStartWhich <- windows$rollingWindowStartWhich - refreshAddedStart <- windows$refreshAddedStart - window_end <- windows$window_end - rollingWindowEndWhich <- windows$rollingWindowEndWhich - rollingWindowLength <- windows$rollingWindowLength - } + window_start <- windows$window_start + rollingWindowStartWhich <- windows$rollingWindowStartWhich + refreshAddedStart <- windows$refreshAddedStart + window_end <- windows$window_end + rollingWindowEndWhich <- windows$rollingWindowEndWhich + rollingWindowLength <- windows$rollingWindowLength ## Check adstock adstock <- check_adstock(adstock) @@ -271,7 +263,8 @@ robyn_inputs <- function(dt_input = NULL, ## Check calibration and iters/trials calibration_input <- check_calibration( dt_input, date_var, calibration_input, dayInterval, dep_var, - window_start, window_end, paid_media_spends, organic_vars + window_start, window_end, paid_media_spends, organic_vars, + paid_collect$paid_media_selected ) ## Not used variables @@ -283,9 +276,14 @@ robyn_inputs <- function(dt_input = NULL, check_novar(select(dt_input, -all_of(unused_vars))) # Calculate total media spend used to model - paid_media_total <- dt_input[ - rollingWindowEndWhich:rollingWindowLength, ] %>% - select(paid_media_vars) %>% sum() + paid_media_total <- dt_input %>% + mutate(temp_date = dt_input[[date_var]]) %>% + filter( + .data$temp_date >= window_start, + .data$temp_date <= window_end + ) %>% + select(all_of(paid_media_spends)) %>% + sum() ## Collect input InputCollect <- list( @@ -307,6 +305,7 @@ robyn_inputs <- function(dt_input = NULL, paid_media_vars = paid_media_vars, paid_media_signs = paid_media_signs, paid_media_spends = paid_media_spends, + paid_media_selected = paid_collect$paid_media_selected, paid_media_total = paid_media_total, exposure_vars = exposure_vars, organic_vars = organic_vars, @@ -320,7 +319,7 @@ robyn_inputs <- function(dt_input = NULL, window_end = window_end, rollingWindowEndWhich = rollingWindowEndWhich, rollingWindowLength = rollingWindowLength, - totalObservations = nrow(dt_input), + totalObservations = nrow(windows$dt_input), refreshAddedStart = refreshAddedStart, adstock = adstock, hyperparameters = hyperparameters, @@ -336,7 +335,8 @@ robyn_inputs <- function(dt_input = NULL, ## Check hyperparameters hyperparameters <- check_hyperparameters( - hyperparameters, adstock, paid_media_spends, organic_vars, exposure_vars + hyperparameters, adstock, paid_collect$paid_media_selected, paid_media_spends, organic_vars, + exposure_vars, prophet_vars, context_vars ) InputCollect <- robyn_engineering(InputCollect, ...) } @@ -355,7 +355,8 @@ robyn_inputs <- function(dt_input = NULL, window_start = InputCollect$window_start, window_end = InputCollect$window_end, paid_media_spends = InputCollect$paid_media_spends, - organic_vars = InputCollect$organic_vars + organic_vars = InputCollect$organic_vars, + paid_media_selected = InputCollect$paid_media_selected ) ## Update calibration_input @@ -369,12 +370,15 @@ robyn_inputs <- function(dt_input = NULL, ## Update & check hyperparameters if (is.null(InputCollect$hyperparameters)) InputCollect$hyperparameters <- hyperparameters InputCollect$hyperparameters <- check_hyperparameters( - InputCollect$hyperparameters, InputCollect$adstock, InputCollect$all_media + InputCollect$hyperparameters, InputCollect$adstock, + InputCollect$paid_media_selected, InputCollect$paid_media_spends, + InputCollect$organic_vars, InputCollect$exposure_vars, + InputCollect$prophet_vars, InputCollect$context_vars ) InputCollect <- robyn_engineering(InputCollect, ...) } - # Check for no-variance columns (after filtering modeling window) + # Re-check for no-variance columns after feature enginerring dt_mod_model_window <- InputCollect$dt_mod %>% select(-any_of(InputCollect$unused_vars)) %>% filter( @@ -412,7 +416,7 @@ print.robyn_inputs <- function(x, ...) { mod_vars <- paste(setdiff(names(x$dt_mod), c("ds", "dep_var")), collapse = ", ") print(glued( " -Total Observations: {nrow(x$dt_input)} ({x$intervalType}s) +Total Observations: {x$totalObservations} ({x$intervalType}s) Input Table Columns ({ncol(x$dt_input)}): Date: {x$date_var} Dependent: {x$dep_var} [{x$dep_var_type}] @@ -435,8 +439,10 @@ Adstock: {x$adstock} windows = paste(x$window_start, x$window_end, sep = ":"), custom_params = if (length(x$custom_params) > 0) paste("\n", flatten_hyps(x$custom_params)) else "None", prophet = if (length(x$prophet_vars) > 0) { - sprintf("%s on %s", paste(x$prophet_vars, collapse = ", "), - ifelse(!is.null(x$prophet_country), x$prophet_country, "data")) + sprintf( + "%s on %s", paste(x$prophet_vars, collapse = ", "), + ifelse(!is.null(x$prophet_country), x$prophet_country, "data") + ) } else { "\033[0;31mDeactivated\033[0m" }, @@ -464,39 +470,14 @@ Adstock: {x$adstock} #' hyperparameters that is inserted into \code{robyn_inputs(hyperparameters = ...)} #' #' @section Guide to setup hyperparameters: -#' \enumerate{ -#' \item Get correct hyperparameter names: -#' All variables in \code{paid_media_vars} or \code{organic_vars} require hyperprameters -#' and will be transformed by adstock & saturation. Difference between \code{paid_media_vars} -#' and \code{organic_vars} is that \code{paid_media_vars} has spend that -#' needs to be specified in \code{paid_media_spends} specifically. Run \code{hyper_names()} -#' to get correct hyperparameter names. All names in hyperparameters must -#' equal names from \code{hyper_names()}, case sensitive. -#' \item{Get guidance for setting hyperparameter bounds: -#' For geometric adstock, use theta, alpha & gamma. For both weibull adstock options, -#' use shape, scale, alpha, gamma.} -#' \itemize{ -#' \item{Theta: }{In geometric adstock, theta is decay rate. guideline for usual media genre: -#' TV c(0.3, 0.8), OOH/Print/Radio c(0.1, 0.4), digital c(0, 0.3)} -#' \item{Shape: }{In weibull adstock, shape controls the decay shape. Recommended c(0.0001, 2). -#' The larger, the more S-shape. The smaller, the more L-shape. Channel-type specific -#' values still to be investigated} -#' \item{Scale: }{In weibull adstock, scale controls the decay inflexion point. Very conservative -#' recommended bounce c(0, 0.1), because scale can increase adstocking half-life greatly. -#' Channel-type specific values still to be investigated} -#' \item{Gamma: }{In s-curve transformation with hill function, gamma controls the inflexion point. -#' Recommended bounce c(0.3, 1). The larger the gamma, the later the inflection point -#' in the response curve} -#' } -#' \item{Set each hyperparameter bounds. They either contains two values e.g. c(0, 0.5), -#' or only one value (in which case you've "fixed" that hyperparameter)} -#' } +#' See section "Hyperparameter interpretation & recommendation" in demo +#' https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R #' #' @section Helper plots: #' \describe{ -#' \item{plot_adstock}{Get adstock transformation example plot, +#' \item{plot_adstock(TRUE)}{Get adstock transformation example plot, #' helping you understand geometric/theta and weibull/shape/scale transformation} -#' \item{plot_saturation}{Get saturation curve transformation example plot, +#' \item{plot_saturation(TRUE)}{Get saturation curve transformation example plot, #' helping you understand hill/alpha/gamma transformation} #' } #' @@ -504,15 +485,16 @@ Adstock: {x$adstock} #' Accepts "geometric", "weibull_cdf" or "weibull_pdf" #' @param all_media Character vector. Default to \code{InputCollect$all_media}. #' Includes \code{InputCollect$paid_media_spends} and \code{InputCollect$organic_vars}. +#' @param all_vars Used to check the penalties inputs, especially for refreshing models. #' @examples #' \donttest{ -#' media <- c("facebook_S", "print_S", "tv_S") +#' media <- c("facebook_I", "print_S", "tv_S") #' hyper_names(adstock = "geometric", all_media = media) #' #' hyperparameters <- list( -#' facebook_S_alphas = c(0.5, 3), # example bounds for alpha -#' facebook_S_gammas = c(0.3, 1), # example bounds for gamma -#' facebook_S_thetas = c(0, 0.3), # example bounds for theta +#' facebook_I_alphas = c(0.5, 3), # example bounds for alpha +#' facebook_I_gammas = c(0.3, 1), # example bounds for gamma +#' facebook_I_thetas = c(0, 0.3), # example bounds for theta #' print_S_alphas = c(0.5, 3), #' print_S_gammas = c(0.3, 1), #' print_S_thetas = c(0.1, 0.4), @@ -522,13 +504,13 @@ Adstock: {x$adstock} #' ) #' #' # Define hyper_names for weibull adstock -#' hyper_names(adstock = "weibull", all_media = media) +#' hyper_names(adstock = "weibull_pdf", all_media = media) #' #' hyperparameters <- list( -#' facebook_S_alphas = c(0.5, 3), # example bounds for alpha -#' facebook_S_gammas = c(0.3, 1), # example bounds for gamma -#' facebook_S_shapes = c(0.0001, 2), # example bounds for shape -#' facebook_S_scales = c(0, 0.1), # example bounds for scale +#' facebook_I_alphas = c(0.5, 3), # example bounds for alpha +#' facebook_I_gammas = c(0.3, 1), # example bounds for gamma +#' facebook_I_shapes = c(0.0001, 2), # example bounds for shape +#' facebook_I_scales = c(0, 0.1), # example bounds for scale #' print_S_alphas = c(0.5, 3), #' print_S_gammas = c(0.3, 1), #' print_S_shapes = c(0.0001, 2), @@ -541,7 +523,7 @@ Adstock: {x$adstock} #' } #' @return Character vector. Names of hyper-parameters that should be defined. #' @export -hyper_names <- function(adstock, all_media) { +hyper_names <- function(adstock, all_media, all_vars = NULL) { adstock <- check_adstock(adstock) if (adstock == "geometric") { local_name <- sort(apply(expand.grid(all_media, HYPS_NAMES[ @@ -552,6 +534,9 @@ hyper_names <- function(adstock, all_media) { grepl("shapes|scales|alphas|gammas", HYPS_NAMES) ]), 1, paste, collapse = "_")) } + if (!is.null(all_vars)) { + local_name <- sort(c(local_name, paste0(all_vars, "_penalty"))) + } return(local_name) } @@ -598,123 +583,11 @@ robyn_engineering <- function(x, quiet = FALSE, ...) { rollingWindowStartWhich <- InputCollect$rollingWindowStartWhich rollingWindowEndWhich <- InputCollect$rollingWindowEndWhich - # dt_inputRollWind - dt_inputRollWind <- dt_input[rollingWindowStartWhich:rollingWindowEndWhich, ] - - # dt_transform - dt_transform <- dt_input - colnames(dt_transform)[colnames(dt_transform) == InputCollect$date_var] <- "ds" - colnames(dt_transform)[colnames(dt_transform) == InputCollect$dep_var] <- "dep_var" - dt_transform <- arrange(dt_transform, .data$ds) - - # dt_transformRollWind - dt_transformRollWind <- dt_transform[rollingWindowStartWhich:rollingWindowEndWhich, ] - - ################################################################ - #### Model exposure metric from spend - - exposure_selector <- paid_media_spends != paid_media_vars - names(exposure_selector) <- paid_media_vars - - if (any(exposure_selector)) { - modNLSCollect <- list() - yhatCollect <- list() - plotNLSCollect <- list() - mediaCostFactor <- colSums(subset(dt_inputRollWind, select = paid_media_spends), na.rm = TRUE) / - colSums(subset(dt_inputRollWind, select = paid_media_vars), na.rm = TRUE) - - for (i in seq_along(paid_media_spends)) { - if (exposure_selector[i]) { - # Run models (NLS and/or LM) - dt_spendModInput <- subset(dt_inputRollWind, select = c(paid_media_spends[i], paid_media_vars[i])) - results <- fit_spend_exposure(dt_spendModInput, mediaCostFactor[i], paid_media_vars[i]) - # Compare NLS & LM, takes LM if NLS fits worse - mod <- results$res - exposure_selector[i] <- if (is.null(mod$rsq_nls)) FALSE else mod$rsq_nls > mod$rsq_lm - # Data to create plot - dt_plotNLS <- data.frame( - channel = paid_media_vars[i], - yhatNLS = if (exposure_selector[i]) results$yhatNLS else results$yhatLM, - yhatLM = results$yhatLM, - y = results$data$exposure, - x = results$data$spend - ) - caption <- glued(" - nls: AIC = {aic_nls} | R2 = {r2_nls} - lm: AIC = {aic_lm} | R2 = {r2_lm}", - aic_nls = signif(AIC(if (exposure_selector[i]) results$modNLS else results$modLM), 3), - r2_nls = signif(if (exposure_selector[i]) mod$rsq_nls else mod$rsq_lm, 3), - aic_lm = signif(AIC(results$modLM), 3), - r2_lm = signif(mod$rsq_lm, 3) - ) - dt_plotNLS <- dt_plotNLS %>% - pivot_longer( - cols = c("yhatNLS", "yhatLM"), - names_to = "models", values_to = "yhat" - ) %>% - mutate(models = str_remove(tolower(.data$models), "yhat")) - models_plot <- ggplot( - dt_plotNLS, aes(x = .data$x, y = .data$y, color = .data$models) - ) + - geom_point() + - geom_line(aes(y = .data$yhat, x = .data$x, color = .data$models)) + - labs( - title = "Exposure-Spend Models Fit Comparison", - x = sprintf("Spend [%s]", paid_media_spends[i]), - y = sprintf("Exposure [%s]", paid_media_vars[i]), - caption = caption, - color = "Model" - ) + - theme_lares(background = "white", legend = "top") + - scale_x_abbr() + - scale_y_abbr() - - # Save results into modNLSCollect. plotNLSCollect, yhatCollect - modNLSCollect[[paid_media_vars[i]]] <- mod - plotNLSCollect[[paid_media_vars[i]]] <- models_plot - yhatCollect[[paid_media_vars[i]]] <- dt_plotNLS - } - } - modNLSCollect <- bind_rows(modNLSCollect) - yhatNLSCollect <- bind_rows(yhatCollect) - yhatNLSCollect$ds <- rep(dt_transformRollWind$ds, nrow(yhatNLSCollect) / nrow(dt_transformRollWind)) - } else { - modNLSCollect <- plotNLSCollect <- yhatNLSCollect <- NULL - } - - # Give recommendations and show warnings - if (!is.null(modNLSCollect) && !quiet) { - threshold <- 0.80 - final_print <- these <- NULL # TRUE if we accumulate a common message - metrics <- c("R2 (nls)", "R2 (lm)") - names(metrics) <- c("rsq_nls", "rsq_lm") - for (m in seq_along(metrics)) { - temp <- which(modNLSCollect[[names(metrics)[m]]] < threshold) - if (length(temp) > 0) { - # warning(sprintf( - # "%s: weak relationship for %s and %s spend", - # metrics[m], - # v2t(modNLSCollect$channel[temp], and = "and"), - # ifelse(length(temp) > 1, "their", "its") - # )) - final_print <- TRUE - these <- modNLSCollect$channel[temp] - } - } - if (isTRUE(final_print)) { - message( - paste( - "NOTE: potential improvement on splitting channels for better exposure fitting.", - "Threshold (Minimum R2) =", threshold, - "\n Check: InputCollect$modNLS$plots outputs" - ), - "\n Weak relationship for: ", v2t(these), " and their spend" - ) - } - } - - ################################################################ - #### Clean & aggregate data + ## Standardise ds and dep_var cols + dt_transform <- dt_input %>% + rename("ds" = InputCollect$date_var, + "dep_var" = InputCollect$dep_var) %>% + arrange(.data$ds) ## Transform all factor variables if (length(factor_vars) > 0) { @@ -755,6 +628,7 @@ robyn_engineering <- function(x, quiet = FALSE, ...) { context_vars = InputCollect$context_vars, organic_vars = InputCollect$organic_vars, paid_media_spends = paid_media_spends, + paid_media_vars = paid_media_vars, intervalType = InputCollect$intervalType, dayInterval = InputCollect$dayInterval, custom_params = custom_params @@ -763,21 +637,27 @@ robyn_engineering <- function(x, quiet = FALSE, ...) { prophet_custom_output <- dt_transform_original$prophet_custom_output } - ################################################################ - #### Finalize enriched input - #! SH InputCollect$prophet_custom_output <- prophet_custom_output + ################################################################ + #### Model exposure metric from spend + + ExposureCollect <- exposure_handling( + dt_transform, + window_start_loc = rollingWindowStartWhich, + window_end_loc = rollingWindowEndWhich, + paid_media_spends, + paid_media_vars, + quiet) + + ################################################################ + #### Finalize enriched input + dt_transform <- ExposureCollect$dt_transform dt_transform <- subset(dt_transform, select = c("ds", "dep_var", InputCollect$all_ind_vars)) InputCollect[["dt_mod"]] <- dt_transform InputCollect[["dt_modRollWind"]] <- dt_transform[rollingWindowStartWhich:rollingWindowEndWhich, ] - InputCollect[["dt_inputRollWind"]] <- dt_inputRollWind - InputCollect[["modNLS"]] <- list( - results = modNLSCollect, - yhat = yhatNLSCollect, - plots = plotNLSCollect - ) + InputCollect[["ExposureCollect"]] <- ExposureCollect return(InputCollect) } @@ -800,7 +680,7 @@ robyn_engineering <- function(x, quiet = FALSE, ...) { prophet_decomp <- function(dt_transform, dt_holidays, prophet_country, prophet_vars, prophet_signs, factor_vars, context_vars, organic_vars, paid_media_spends, - intervalType, dayInterval, custom_params) { + paid_media_vars, intervalType, dayInterval, custom_params) { check_prophet(dt_holidays, prophet_country, prophet_vars, prophet_signs, dayInterval) recurrence <- select(dt_transform, .data$ds, .data$dep_var) %>% rename("y" = "dep_var") holidays <- set_holidays(dt_transform, dt_holidays, intervalType) @@ -811,7 +691,7 @@ prophet_decomp <- function(dt_transform, dt_holidays, use_weekday <- "weekday" %in% prophet_vars | "weekly.seasonality" %in% prophet_vars dt_regressors <- bind_cols(recurrence, select( - dt_transform, all_of(c(paid_media_spends, context_vars, organic_vars)) + dt_transform, all_of(c(paid_media_spends, paid_media_vars, context_vars, organic_vars)) )) %>% mutate(ds = as.Date(.data$ds)) @@ -904,93 +784,69 @@ prophet_decomp <- function(dt_transform, dt_holidays, #! SH END } -#################################################################### -#' Fit a nonlinear model for media spend and exposure -#' -#' This function is called in \code{robyn_engineering()}. It uses -#' the Michaelis-Menten function to fit the nonlinear model. Fallback -#' model is the simple linear model \code{lm()} in case the nonlinear -#' model is fitting worse. A bad fit here might result in unreasonable -#' model results. Two options are recommended: Either splitting the -#' channel into sub-channels to achieve better fit, or just use -#' spend as \code{paid_media_vars} -#' -#' @param dt_spendModInput data.frame. Containing channel spends and -#' exposure data. -#' @param mediaCostFactor Numeric vector. The ratio between raw media -#' exposure and spend metrics. -#' @param paid_media_var Character. Paid media variable. -#' @return List. Containing the all spend-exposure model results. -fit_spend_exposure <- function(dt_spendModInput, mediaCostFactor, paid_media_var) { - if (ncol(dt_spendModInput) != 2) stop("Pass only 2 columns") - colnames(dt_spendModInput) <- c("spend", "exposure") - - # Model 1: Michaelis-Menten model Vmax * spend/(Km + spend) - tryCatch( - { - nlsStartVal <- list( - Vmax = max(dt_spendModInput$exposure), - Km = max(dt_spendModInput$exposure) / 2 - ) - - modNLS <- nlsLM(exposure ~ Vmax * spend / (Km + spend), - data = dt_spendModInput, - start = nlsStartVal, - control = nls.control(warnOnly = TRUE) - ) - yhatNLS <- predict(modNLS) - modNLSSum <- summary(modNLS) - rsq_nls <- get_rsq(true = dt_spendModInput$exposure, predicted = yhatNLS) - - # # QA nls model prediction: check - # yhatNLSQA <- modNLSSum$coefficients[1,1] * dt_spendModInput$spend / (modNLSSum$coefficients[2,1] + dt_spendModInput$spend) #exposure = v * spend / (k + spend) - # identical(yhatNLS, yhatNLSQA) - }, - error = function(cond) { - modNLS <- yhatNLS <- modNLSSum <- rsq_nls <- NULL - }, - warning = function(cond) { - modNLS <- yhatNLS <- modNLSSum <- rsq_nls <- NULL - }, - finally = if (!exists("modNLS")) modNLS <- yhatNLS <- modNLSSum <- rsq_nls <- NULL - ) +exposure_handling <- function(dt_transform, + window_start_loc, + window_end_loc, + paid_media_spends, + paid_media_vars, + quiet) { + exposure_selector <- paid_media_spends != paid_media_vars + paid_media_selected <- ifelse(exposure_selector, paid_media_vars, paid_media_spends) + df_cpe <- list() + df_expo_p <- list() + for (i in seq_along(exposure_selector)) { + temp_spend <- dt_transform %>% select(paid_media_spends[i]) + temp_expo <- dt_transform %>% select(paid_media_vars[i]) + temp_spend_window <- temp_spend[window_start_loc:window_end_loc, ] + temp_expo_window <- temp_expo[window_start_loc:window_end_loc, ] + ## cpe = cost per exposure, an internal linear scaler between spend & exposure + temp_cpe <- sum(temp_spend)/ sum(temp_expo) + temp_cpe_window <- sum(temp_spend_window)/ sum(temp_expo_window) + temp_spend_scaled <- ifelse(exposure_selector[i], temp_expo * temp_cpe, temp_spend) + temp_spend_scaled_window <- ifelse(exposure_selector[i], temp_expo_window * temp_cpe_window, temp_spend_window) + df_cpe[[i]] <- data.frame( + paid_media_selected = paid_media_selected[i], + cpe = temp_cpe, + cpe_window = temp_cpe_window, + adj_rsq = get_rsq(true = unlist(temp_spend), + predicted = unlist(temp_spend_scaled)), + adj_rsq_window = get_rsq(true = unlist(temp_spend_window), + predicted = unlist(temp_spend_scaled_window)) + ) + ## Use window cpe to predict the whole dataset to keep the window spend scale right + spend_scaled_extrapolated <- temp_expo * temp_cpe_window + df_expo_p[[i]] <- data.frame(spend = unlist(temp_spend), + exposure = unlist(temp_expo), + media = paid_media_selected[i]) + dt_transform <- dt_transform %>% + mutate_at(vars(paid_media_selected[i]), function(x) unlist(spend_scaled_extrapolated)) + } + df_cpe <- bind_rows(df_cpe) + df_expo_p <- bind_rows(df_expo_p) + p_expo <- df_expo_p %>% ggplot(aes(x = .data$spend, y = .data$exposure)) + + geom_point() + + geom_smooth(method = "lm", formula = y ~ x) + + facet_wrap(~ .data$media, scales = "free") + + labs(title = "Spend & exposure relationship for paid media.", + subtitle = "Re-consider media splits if a media shows multiple patterns.") - # Model 2: Build lm comparison model - modLM <- lm(exposure ~ spend - 1, data = dt_spendModInput) - yhatLM <- predict(modLM) - modLMSum <- summary(modLM) - rsq_lm <- modLMSum$adj.r.squared - if (is.na(rsq_lm)) stop("Please check if ", paid_media_var, " contains only 0s") - # if (max(rsq_lm, rsq_nls) < 0.7) { - # warning(paste( - # "Spend-exposure fitting for", paid_media_var, - # "has rsq = ", round(max(rsq_lm, rsq_nls), 4), - # "To increase the fit, try splitting the variable.", - # "Otherwise consider using spend instead." - # )) - # } - - output <- list( - res = data.frame( - channel = paid_media_var, - Vmax = if (!is.null(modNLS)) modNLSSum$coefficients[1, 1] else NA, - Km = if (!is.null(modNLS)) modNLSSum$coefficients[2, 1] else NA, - aic_nls = if (!is.null(modNLS)) AIC(modNLS) else NA, - aic_lm = AIC(modLM), - bic_nls = if (!is.null(modNLS)) BIC(modNLS) else NA, - bic_lm = BIC(modLM), - rsq_nls = if (!is.null(modNLS)) rsq_nls else 0, - rsq_lm = rsq_lm, - coef_lm = coef(modLMSum)[1] - ), - yhatNLS = yhatNLS, - modNLS = modNLS, - yhatLM = yhatLM, - modLM = modLM, - data = dt_spendModInput, - type = ifelse(is.null(modNLS), "lm", "mm") - ) - return(output) + # Give recommendations and show warnings + threshold <- 0.8 + temp_names <- df_cpe %>% filter(.data$adj_rsq_window < threshold) %>% pull(paid_media_selected) + if (!quiet & any(exposure_selector) & length(temp_names) > 1) { + message( + paste( + "NOTE: potential improvement on splitting channels for better spend exposure fitting.", + "Threshold (min.adj.R2) =", threshold, + "\n Check: InputCollect$ExposureCollect$plot_spend_exposure outputs" + ), + "\n Weak relationship for: ", v2t(temp_names), " and their spend" + ) + } + return(list(df_cpe = df_cpe, + plot_spend_exposure = p_expo, + dt_transform = dt_transform, + paid_media_selected = paid_media_selected)) } #################################################################### @@ -1016,7 +872,6 @@ set_holidays <- function(dt_transform, dt_holidays, intervalType) { if (intervalType == "week") { weekStartInput <- lubridate::wday(dt_transform$ds[1], week_start = 1) - if (!weekStartInput %in% c(1, 7)) stop("Week start has to be Monday or Sunday") holidays <- dt_holidays %>% mutate(ds = floor_date(as.Date(.data$ds, origin = "1970-01-01"), unit = "week", week_start = weekStartInput)) %>% select(.data$ds, .data$holiday, .data$country, .data$year) %>% @@ -1038,3 +893,39 @@ set_holidays <- function(dt_transform, dt_holidays, intervalType) { return(holidays) } + +#################################################################### +#' Set default hyperparameters +#' +#' For quick setting of hyperparameter ranges. +#' +#' @param adstock Character. InputCollect$adstock +#' @param all_media Character. Provide InputCollect$all_media. +#' @param list_default A List. Default ranges for hyperparameters. +#' @return List. Expanded range of hyperparameters for all media. +#' @export +set_default_hyppar <- function( + adstock = NULL, + all_media = NULL, + list_default = list(alpha = c(0.5, 3), + gamma = c(0.01, 1), + theta = c(0, 0.8), + shape = c(0, 10), + scale = c(0, 0.1), + train_size = c(0.5, 0.9)) + +) { + hpnames <- hyper_names(adstock = adstock, all_media = all_media) + hyperparameters <- list() + for (i in seq_along(hpnames)) { + hyperparameters[[i]] <- dplyr::case_when( + str_detect(hpnames[[i]], "_alphas") ~ list_default[["alpha"]], + str_detect(hpnames[[i]], "_gammas") ~ list_default[["gamma"]], + str_detect(hpnames[[i]], "_thetas") ~ list_default[["theta"]], + str_detect(hpnames[[i]], "_shapes") ~ list_default[["shape"]], + str_detect(hpnames[[i]], "_scales") ~ list_default[["scale"]]) + names(hyperparameters)[[i]] <- hpnames[[i]] + } + hyperparameters[["train_size"]] <- list_default[["train_size"]] + return(hyperparameters) +} diff --git a/R/R/json.R b/R/R/json.R index cb7554100..a828066b7 100644 --- a/R/R/json.R +++ b/R/R/json.R @@ -17,11 +17,11 @@ #' @param InputCollect \code{robyn_inputs()} output. #' @param select_model Character. Which model ID do you want to export #' into the JSON file? +#' @param add_data Boolean. Include raw dataset. Useful to recreate models +#' with a single file containing all the required information (no need of CSV). #' @param dir Character. Existing directory to export JSON file to. #' @param pareto_df Dataframe. Save all pareto solutions to json file. #' @param ... Additional parameters to export into a custom Extras element. -#' If you wish to include the data to recreate a model, add -#' \code{raw_data = InputCollect$dt_input}. #' @examples #' \dontrun{ #' InputCollectJSON <- robyn_inputs( @@ -37,6 +37,7 @@ robyn_write <- function(InputCollect, OutputCollect = NULL, select_model = NULL, dir = OutputCollect$plot_folder, + add_data = TRUE, export = TRUE, quiet = FALSE, pareto_df = NULL, @@ -60,7 +61,6 @@ robyn_write <- function(InputCollect, # ExportedModel JSON if (!is.null(OutputCollect)) { - # Modeling associated data collect <- list() collect$ts_validation <- OutputCollect$OutputModels$ts_validation @@ -70,7 +70,8 @@ robyn_write <- function(InputCollect, collect$outputs_time <- sprintf("%s min", attr(OutputCollect, "runTime")) collect$total_time <- sprintf( "%s min", attr(OutputCollect, "runTime") + - attr(OutputCollect$OutputModels, "runTime")) + attr(OutputCollect$OutputModels, "runTime") + ) collect$total_iters <- OutputCollect$OutputModels$iterations * OutputCollect$OutputModels$trials collect$conv_msg <- gsub("\\:.*", "", OutputCollect$OutputModels$convergence$conv_msg) @@ -93,11 +94,14 @@ robyn_write <- function(InputCollect, outputs$performance <- df %>% filter(.data$rn %in% InputCollect$paid_media_spends) %>% group_by(.data$solID) %>% - summarise(metric = perf_metric, - performance = ifelse( - perf_metric == "ROAS", - sum(.data$xDecompAgg) / sum(.data$total_spend), - sum(.data$total_spend) / sum(.data$xDecompAgg)), .groups = "drop") + summarise( + metric = perf_metric, + performance = ifelse( + perf_metric == "ROAS", + sum(.data$xDecompAgg) / sum(.data$total_spend), + sum(.data$total_spend) / sum(.data$xDecompAgg) + ), .groups = "drop" + ) outputs$summary <- df %>% mutate( metric = perf_metric, @@ -133,8 +137,12 @@ robyn_write <- function(InputCollect, select_model <- "inputs" } - if (length(list(...)) > 0) { - ret[["Extras"]] <- list(...) + extras <- list(...) + if (isTRUE(add_data) & !"raw_data" %in% names(extras)) { + extras[["raw_data"]] <- as_tibble(InputCollect$dt_input) + } + if (length(extras) > 0) { + ret[["Extras"]] <- extras } if (!dir.exists(dir) & export) dir.create(dir, recursive = TRUE) @@ -143,12 +151,13 @@ robyn_write <- function(InputCollect, class(ret) <- c("robyn_write", class(ret)) attr(ret, "json_file") <- filename if (export) { - if (!quiet) message(sprintf(">> Exported model %s as %s", select_model, filename)) + if (!quiet) message(sprintf(">> Exported %s as %s", select_model, filename)) if (!is.null(pareto_df)) { if (!all(c("solID", "cluster") %in% names(pareto_df))) { warning(paste( "Input 'pareto_df' is not a valid data.frame;", - "must contain 'solID' and 'cluster' columns.")) + "must contain 'solID' and 'cluster' columns." + )) } else { all_c <- unique(pareto_df$cluster) pareto_df <- lapply(all_c, function(x) { @@ -187,12 +196,12 @@ print.robyn_write <- function(x, ...) { "\n\nModel's Performance and Errors:\n {performance}{errors}", performance = ifelse("performance" %in% names(x$ExportedModel), sprintf( "Total Model %s = %s\n ", - x$ExportedModel$performance$metric, signif(x$ExportedModel$performance$performance, 4)), ""), + x$ExportedModel$performance$metric, signif(x$ExportedModel$performance$performance, 4) + ), ""), errors = paste( sprintf( - "Adj.R2 (%s): %s", - ifelse(!val, "train", "test"), - ifelse(!val, signif(errors$rsq_train, 4), signif(errors$rsq_test, 4)) + "Adj.R2 (train): %s", + signif(errors$rsq_train, 4) ), "| NRMSE =", signif(errors$nrmse, 4), "| DECOMP.RSSD =", signif(errors$decomp.rssd, 4), @@ -200,34 +209,36 @@ print.robyn_write <- function(x, ...) { ) )) - print(glued("\n\nSummary Values on Selected Model:")) + if ("ExportedModel" %in% names(x)) { + print(glued("\n\nSummary Values on Selected Model:")) - print(x$ExportedModel$summary %>% - select(-contains("boot"), -contains("ci_")) %>% - dplyr::rename_at("performance", list(~ ifelse(x$InputCollect$dep_var_type == "revenue", "ROAS", "CPA"))) %>% - mutate(decompPer = formatNum(100 * .data$decompPer, pos = "%")) %>% - dplyr::mutate_if(is.numeric, function(x) ifelse(!is.infinite(x), x, 0)) %>% - dplyr::mutate_if(is.numeric, function(x) formatNum(x, 4, abbr = TRUE)) %>% - replace(., . == "NA", "-") %>% as.data.frame()) + print(x$ExportedModel$summary %>% + select(-contains("boot"), -contains("ci_")) %>% + dplyr::rename_at("performance", list(~ ifelse(x$InputCollect$dep_var_type == "revenue", "ROAS", "CPA"))) %>% + mutate(decompPer = formatNum(100 * .data$decompPer, pos = "%")) %>% + dplyr::mutate_if(is.numeric, function(x) ifelse(!is.infinite(x), x, 0)) %>% + dplyr::mutate_if(is.numeric, function(x) formatNum(x, 4, abbr = TRUE)) %>% + replace(., . == "NA", "-") %>% as.data.frame()) - print(glued( - "\n\nHyper-parameters:\n Adstock: {x$InputCollect$adstock}" - )) + print(glued( + "\n\nHyper-parameters:\n Adstock: {x$InputCollect$adstock}" + )) - # Nice and tidy table format for hyper-parameters - HYPS_NAMES <- c(HYPS_NAMES, "penalty") - regex <- paste(paste0("_", HYPS_NAMES), collapse = "|") - hyper_df <- as.data.frame(x$ExportedModel$hyper_values) %>% - select(-contains("lambda"), -any_of(HYPS_OTHERS)) %>% - tidyr::gather() %>% - tidyr::separate(.data$key, - into = c("channel", "none"), - sep = regex, remove = FALSE - ) %>% - mutate(hyperparameter = gsub("^.*_", "", .data$key)) %>% - select(.data$channel, .data$hyperparameter, .data$value) %>% - tidyr::spread(key = "hyperparameter", value = "value") - print(hyper_df) + # Nice and tidy table format for hyper-parameters + HYPS_NAMES <- c(HYPS_NAMES, "penalty") + regex <- paste(paste0("_", HYPS_NAMES), collapse = "|") + hyper_df <- as.data.frame(x$ExportedModel$hyper_values) %>% + select(-contains("lambda"), -any_of(HYPS_OTHERS)) %>% + tidyr::gather() %>% + tidyr::separate(.data$key, + into = c("channel", "none"), + sep = regex, remove = FALSE + ) %>% + mutate(hyperparameter = gsub("^.*_", "", .data$key)) %>% + select(.data$channel, .data$hyperparameter, .data$value) %>% + tidyr::spread(key = "hyperparameter", value = "value") + print(hyper_df) + } } @@ -322,7 +333,7 @@ Adstock: {a$adstock} #' @export robyn_recreate <- function(json_file, quiet = FALSE, ...) { json <- robyn_read(json_file, quiet = TRUE) - message(">>> Recreating model ", json$ExportedModel$select_model) + message(">>> Recreating ", json$ExportedModel$select_model) args <- list(...) if (!"InputCollect" %in% names(args)) { InputCollect <- robyn_inputs( @@ -330,13 +341,17 @@ robyn_recreate <- function(json_file, quiet = FALSE, ...) { quiet = quiet, ... ) - OutputCollect <- robyn_run( - InputCollect = InputCollect, - json_file = json_file, - export = FALSE, - quiet = quiet, - ... - ) + if (!is.null(json$ExportedModel$select_model)) { + OutputCollect <- robyn_run( + InputCollect = InputCollect, + json_file = json_file, + export = FALSE, + quiet = quiet, + ... + ) + } else { + OutputCollect <- NULL + } } else { # Use case: skip feature engineering when InputCollect is provided InputCollect <- args[["InputCollect"]] @@ -360,22 +375,51 @@ robyn_chain <- function(json_file) { ids <- c(json_data$InputCollect$refreshChain, json_data$ExportedModel$select_model) plot_folder <- json_data$ExportedModel$plot_folder temp <- str_split(plot_folder, "/")[[1]] - chain <- temp[startsWith(temp, "Robyn_")] + chain <- temp[startsWith(temp, "Robyn_") & grepl("_init+$|_rf[0-9]+$", temp)] if (length(chain) == 0) chain <- tail(temp[temp != ""], 1) + avlb <- NULL + if (length(ids) != length(chain)) { + temp <- list.files(plot_folder) + mods <- unique(temp[ + (startsWith(temp, "RobynModel") | grepl("\\.json+$", temp)) & + grepl("^[^_]*_[^_]*_[^_]*$", temp) + ]) + avlb <- gsub("RobynModel-|\\.json", "", mods) + if (length(ids) == length(mods)) { + chain <- rep_len(chain, length(mods)) + } + } base_dir <- gsub(sprintf("\\/%s.*", chain[1]), "", plot_folder) chainData <- list() - for (i in rev(seq_along(chain))) { - if (i == length(chain)) { + for (i in rev(seq_along(ids))) { + if (i == length(ids)) { json_new <- json_data } else { file <- paste0("RobynModel-", json_new$InputCollect$refreshSourceID, ".json") filename <- paste(c(base_dir, chain[1:i], file), collapse = "/") - json_new <- robyn_read(filename, quiet = TRUE) + if (file.exists(filename)) { + json_new <- robyn_read(filename, quiet = TRUE) + } else { + if (ids[i] %in% avlb) { + filename <- mods[avlb == ids[i]] + json_new <- robyn_read(filename, quiet = TRUE) + } else { + last_try <- gsub(chain[1], "", filename) + if (file.exists(last_try)) { + json_new <- robyn_read(last_try, quiet = TRUE) + message("Stored original model in new file: ", filename) + jsonlite::write_json(json_new, filename, pretty = TRUE) + } else { + message("Skipping chain. File can't be found: ", filename) + } + } + } } chainData[[json_new$ExportedModel$select_model]] <- json_new } chainData <- chainData[rev(seq_along(chain))] dirs <- unlist(lapply(chainData, function(x) x$ExportedModel$plot_folder)) + dirs[!dir.exists(dirs)] <- plot_folder json_files <- paste0(dirs, "RobynModel-", names(dirs), ".json") attr(chainData, "json_files") <- json_files attr(chainData, "chain") <- ids # names(chainData) diff --git a/R/R/model.R b/R/R/model.R index 970af78aa..5bd594fb7 100644 --- a/R/R/model.R +++ b/R/R/model.R @@ -55,7 +55,9 @@ #' \code{objective_weights} must be defined, i.e. set c(2, 1) to give double weight #' to the 1st (NRMSE). This is an experimental feature. There's no research on #' optimal weight setting. Subjective weights might strongly bias modeling results. -#' @param seed Integer. For reproducible results when running nevergrad. +#' @param seed Integer. For reproducible results when running nevergrad and +#' clustering. Each trial will increase the seed by 1 unit (i.e. 10 trials with +#' seed 1 will share 9 results with 10 trials with seed 2). #' @param lambda_control Deprecated in v3.6.0. #' @param outputs Boolean. If set to TRUE, will run \code{robyn_run()} and #' \code{robyn_outputs()}, returning a list with OutputModels and @@ -94,7 +96,6 @@ robyn_run <- function(InputCollect = NULL, lambda_control = NULL, outputs = FALSE, ...) { - if (isTRUE(outputs)) { OutputModels <- robyn_run( InputCollect = InputCollect, @@ -120,7 +121,8 @@ robyn_run <- function(InputCollect = NULL, OutputCollect <- robyn_outputs(InputCollect, OutputModels, ...) return(list( OutputModels = OutputModels, - OutputCollect = OutputCollect)) + OutputCollect = OutputCollect + )) } t0 <- Sys.time() @@ -227,14 +229,20 @@ robyn_run <- function(InputCollect = NULL, # Direct output & not all fixed hyperparameters, including refresh mode output <- robyn_outputs(InputCollect, OutputModels, refresh = refresh, ...) } else { - # Direct output & all fixed hyperparameters, thus no cluster - output <- robyn_outputs(InputCollect, OutputModels, clusters = FALSE, ...) + if (!"clusters" %in% names(list(...))) { + # Direct output & all fixed hyperparameters, thus no cluster + output <- robyn_outputs(InputCollect, OutputModels, clusters = FALSE, ...) + } else { + output <- robyn_outputs(InputCollect, OutputModels, ...) + } } # Created with assign from JSON file - if (exists("clusters")) - if (!is.integer(get("clusters"))) + if (exists("clusters")) { + if (!is.integer(get("clusters"))) { output$clusters <- get("clusters") + } + } # Check convergence when more than 1 iteration if (!hyper_collect$all_fixed) { @@ -363,7 +371,7 @@ robyn_train <- function(InputCollect, hyper_collect, OutputModels[[1]]$trial <- 1 # Set original solID (to overwrite default 1_1_1) if ("solID" %in% names(dt_hyper_fixed)) { - these <- c("resultHypParam", "xDecompVec", "xDecompAgg", "decompSpendDist") + these <- c("resultHypParam", "xDecompVec", "xDecompAgg") for (tab in these) OutputModels[[1]]$resultCollect[[tab]]$solID <- dt_hyper_fixed$solID } } else { @@ -399,9 +407,9 @@ robyn_train <- function(InputCollect, hyper_collect, seed = seed + ngt, quiet = quiet ) - check_coef0 <- any(model_output$resultCollect$decompSpendDist$decomp.rssd == Inf) + check_coef0 <- any(model_output$resultCollect$resultHypParam$decomp.rssd == Inf) if (check_coef0) { - num_coef0_mod <- filter(model_output$resultCollect$decompSpendDist, is.infinite(.data$decomp.rssd)) %>% + num_coef0_mod <- filter(model_output$resultCollect$resultHypParam, is.infinite(.data$decomp.rssd)) %>% distinct(.data$iterNG, .data$iterPar) %>% nrow() num_coef0_mod <- ifelse(num_coef0_mod > iterations, iterations, num_coef0_mod) @@ -508,6 +516,8 @@ robyn_mmm <- function(InputCollect, refresh_steps <- InputCollect$refresh_steps rollingWindowLength <- InputCollect$rollingWindowLength paid_media_spends <- InputCollect$paid_media_spends + paid_media_selected <- InputCollect$paid_media_selected + exposure_vars <- InputCollect$exposure_vars organic_vars <- InputCollect$organic_vars context_vars <- InputCollect$context_vars prophet_vars <- InputCollect$prophet_vars @@ -527,7 +537,7 @@ robyn_mmm <- function(InputCollect, dt_inputTrain <- InputCollect$dt_input[rollingWindowStartWhich:rollingWindowEndWhich, ] temp <- select(dt_inputTrain, all_of(paid_media_spends)) dt_spendShare <- data.frame( - rn = paid_media_spends, + rn = paid_media_selected, total_spend = unlist(summarise_all(temp, sum)), # mean_spend = unlist(summarise_all(temp, function(x) { # ifelse(is.na(mean(x[x > 0])), 0, mean(x[x > 0])) @@ -535,12 +545,19 @@ robyn_mmm <- function(InputCollect, mean_spend = unlist(summarise_all(temp, mean)) ) %>% mutate(spend_share = .data$total_spend / sum(.data$total_spend)) + if (length(c(exposure_vars, organic_vars)) > 0) { + temp <- select(dt_inputTrain, all_of(c(exposure_vars, organic_vars))) %>% summarise_all(mean) %>% unlist + temp <- data.frame(rn = c(exposure_vars, organic_vars), mean_exposure = temp) + dt_spendShare <- full_join(dt_spendShare, temp, by = "rn") + } else { + dt_spendShare$mean_exposure <- NA + } # When not refreshing, dt_spendShareRF = dt_spendShare refreshAddedStartWhich <- which(dt_modRollWind$ds == refreshAddedStart) temp <- select(dt_inputTrain, all_of(paid_media_spends)) %>% slice(refreshAddedStartWhich:rollingWindowLength) dt_spendShareRF <- data.frame( - rn = paid_media_spends, + rn = paid_media_selected, total_spend = unlist(summarise_all(temp, sum)), # mean_spend = unlist(summarise_all(temp, function(x) { # ifelse(is.na(mean(x[x > 0])), 0, mean(x[x > 0])) @@ -549,8 +566,18 @@ robyn_mmm <- function(InputCollect, ) %>% mutate(spend_share = .data$total_spend / sum(.data$total_spend)) # Join both dataframes into a single one + if (length(c(exposure_vars, organic_vars)) > 0) { + temp <- select(dt_inputTrain, all_of(c(exposure_vars, organic_vars))) %>% + slice(refreshAddedStartWhich:rollingWindowLength) %>% + summarise_all(mean) %>% unlist + temp <- data.frame(rn = c(exposure_vars, organic_vars), mean_exposure = temp) + dt_spendShareRF <- full_join(dt_spendShareRF, temp, by = "rn") + } else { + dt_spendShareRF$mean_exposure <- NA + } dt_spendShare <- left_join(dt_spendShare, dt_spendShareRF, "rn", suffix = c("", "_refresh")) + ################################################ #### Get lambda lambda_min_ratio <- 0.0001 # default value from glmnet @@ -654,15 +681,17 @@ robyn_mmm <- function(InputCollect, adstock <- check_adstock(adstock) #### Transform media for model fitting - temp <- run_transformations(InputCollect, hypParamSam, adstock) - dt_modSaturated <- temp$dt_modSaturated - dt_saturatedImmediate <- temp$dt_saturatedImmediate - dt_saturatedCarryover <- temp$dt_saturatedCarryover + temp <- run_transformations(all_media = InputCollect$all_media, + window_start_loc = InputCollect$rollingWindowStartWhich, + window_end_loc = InputCollect$rollingWindowEndWhich, + dt_mod = InputCollect$dt_mod, + adstock = InputCollect$adstock, + dt_hyppar = hypParamSam, ...) ##################################### #### Split train & test and prepare data for modelling - dt_window <- dt_modSaturated + dt_window <- temp$dt_modSaturated ## Contrast matrix because glmnet does not treat categorical variables (one hot encoding) y_window <- dt_window$dep_var @@ -689,10 +718,16 @@ robyn_mmm <- function(InputCollect, ## Define and set sign control dt_sign <- select(dt_window, -.data$dep_var) x_sign <- c(prophet_signs, context_signs, paid_media_signs, organic_signs) - names(x_sign) <- c(prophet_vars, context_vars, paid_media_spends, organic_vars) + names(x_sign) <- c(prophet_vars, context_vars, paid_media_selected, organic_vars) check_factor <- unlist(lapply(dt_sign, is.factor)) lower.limits <- rep(0, length(prophet_signs)) upper.limits <- rep(1, length(prophet_signs)) + trend_loc <- which(colnames(x_train) == "trend") + if (length(trend_loc) > 0 & sum(x_train[, trend_loc]) < 0) { + trend_loc <- which(prophet_vars == "trend") + lower.limits[trend_loc] <- -1 + upper.limits[trend_loc] <- 0 + } for (s in (length(prophet_signs) + 1):length(x_sign)) { if (check_factor[s] == TRUE) { level.n <- length(levels(unlist(dt_sign[, s, with = FALSE]))) @@ -739,9 +774,12 @@ robyn_mmm <- function(InputCollect, ## If no lift calibration, refit using best lambda mod_out <- model_refit( - x_train, y_train, - x_val, y_val, - x_test, y_test, + x_train = x_train, + y_train = y_train, + x_val = x_val, + y_val = y_val, + x_test = x_test, + y_test = y_test, lambda = lambda_scaled, lower.limits = lower.limits, upper.limits = upper.limits, @@ -751,14 +789,15 @@ robyn_mmm <- function(InputCollect, ... ) decompCollect <- model_decomp( - coefs = mod_out$coefs, - y_pred = mod_out$y_pred, - dt_modSaturated = dt_modSaturated, - dt_saturatedImmediate = dt_saturatedImmediate, - dt_saturatedCarryover = dt_saturatedCarryover, - dt_modRollWind = dt_modRollWind, - refreshAddedStart = refreshAddedStart - ) + inputs = list( + coefs = mod_out$coefs, + y_pred = mod_out$y_pred, + dt_modSaturated = temp$dt_modSaturated, + dt_saturatedImmediate = temp$dt_saturatedImmediate, + dt_saturatedCarryover = temp$dt_saturatedCarryover, + dt_modRollWind = dt_modRollWind, + refreshAddedStart = refreshAddedStart + )) nrmse <- ifelse(ts_validation, mod_out$nrmse_val, mod_out$nrmse_train) mape <- 0 df.int <- mod_out$df.int @@ -766,7 +805,7 @@ robyn_mmm <- function(InputCollect, ##################################### #### MAPE: Calibration error if (!is.null(calibration_input)) { - liftCollect <- robyn_calibrate( + liftCollect <- lift_calibration( calibration_input = calibration_input, df_raw = dt_mod, hypParamSam = hypParamSam, @@ -783,36 +822,37 @@ robyn_mmm <- function(InputCollect, ##################################### #### DECOMP.RSSD: Business error # Sum of squared distance between decomp share and spend share to be minimized - dt_decompSpendDist <- decompCollect$xDecompAgg %>% - filter(.data$rn %in% paid_media_spends) %>% + dt_loss_calc <- decompCollect$xDecompAgg %>% + filter(.data$rn %in% c(paid_media_selected, organic_vars)) %>% select( - .data$rn, .data$xDecompAgg, .data$xDecompPerc, .data$xDecompMeanNon0Perc, - .data$xDecompMeanNon0, .data$xDecompPercRF, .data$xDecompMeanNon0PercRF, - .data$xDecompMeanNon0RF - ) %>% - left_join( - select( - dt_spendShare, - .data$rn, .data$spend_share, .data$spend_share_refresh, - .data$mean_spend, .data$total_spend - ), - by = "rn" - ) %>% - mutate( - effect_share = .data$xDecompPerc / sum(.data$xDecompPerc), - effect_share_refresh = .data$xDecompPercRF / sum(.data$xDecompPercRF) - ) - dt_decompSpendDist <- left_join( - filter(decompCollect$xDecompAgg, .data$rn %in% paid_media_spends), - select(dt_decompSpendDist, .data$rn, contains("_spend"), contains("_share")), + .data$rn, .data$xDecompPerc, .data$xDecompPercRF + ) %>% left_join( + select( + dt_spendShare, + c("rn", "spend_share", "spend_share_refresh","mean_spend", + "total_spend", "mean_exposure", "mean_exposure_refresh") + ), by = "rn" ) + dt_loss_calc <- bind_rows( + dt_loss_calc %>% filter(.data$rn %in% paid_media_selected) %>% + mutate( + effect_share = .data$xDecompPerc / sum(.data$xDecompPerc), + effect_share_refresh = .data$xDecompPercRF / sum(.data$xDecompPercRF) + ), + dt_loss_calc %>% filter(.data$rn %in% organic_vars) %>% + mutate( + effect_share = NA, effect_share_refresh = NA) + ) %>% select(-c("xDecompPerc", "xDecompPercRF")) + decompCollect$xDecompAgg <- left_join( + decompCollect$xDecompAgg, dt_loss_calc, by = "rn") + dt_loss_calc <- dt_loss_calc %>% filter(.data$rn %in% paid_media_selected) if (!refresh) { - decomp.rssd <- sqrt(sum((dt_decompSpendDist$effect_share - dt_decompSpendDist$spend_share)^2)) + decomp.rssd <- sqrt(sum((dt_loss_calc$effect_share - dt_loss_calc$spend_share)^2)) # Penalty for models with more 0-coefficients if (rssd_zero_penalty) { - is_0eff <- round(dt_decompSpendDist$effect_share, 4) == 0 - share_0eff <- sum(is_0eff) / length(dt_decompSpendDist$effect_share) + is_0eff <- round(dt_loss_calc$effect_share, 4) == 0 + share_0eff <- sum(is_0eff) / length(dt_loss_calc$effect_share) decomp.rssd <- decomp.rssd * (1 + share_0eff) } } else { @@ -821,11 +861,11 @@ robyn_mmm <- function(InputCollect, by = "rn" ) decomp.rssd.media <- dt_decompRF %>% - filter(.data$rn %in% paid_media_spends) %>% + filter(.data$rn %in% paid_media_selected) %>% summarise(rssd.media = sqrt(mean((.data$decomp_perc - .data$decomp_perc_prev)^2))) %>% pull(.data$rssd.media) decomp.rssd.nonmedia <- dt_decompRF %>% - filter(!.data$rn %in% paid_media_spends) %>% + filter(!.data$rn %in% paid_media_selected) %>% summarise(rssd.nonmedia = sqrt(mean((.data$decomp_perc - .data$decomp_perc_prev)^2))) %>% pull(.data$rssd.nonmedia) decomp.rssd <- decomp.rssd.media + decomp.rssd.nonmedia / @@ -834,7 +874,8 @@ robyn_mmm <- function(InputCollect, # When all media in this iteration have 0 coefficients if (is.nan(decomp.rssd)) { decomp.rssd <- Inf - dt_decompSpendDist$effect_share <- 0 + decompCollect$xDecompAgg <- decompCollect$xDecompAgg %>% + mutate(effect_share = ifelse(is.na(.data$effect_share), NA, 0)) } ##################################### @@ -867,6 +908,8 @@ robyn_mmm <- function(InputCollect, resultCollect[["resultHypParam"]] <- as_tibble(hypParamSam) %>% select(-.data$lambda) %>% + bind_cols(as_tibble(t(temp$inflexions))) %>% + bind_cols(as_tibble(t(temp$inflations))) %>% bind_cols(common[, 1:split_common]) %>% mutate( pos = prod(decompCollect$xDecompAgg$pos), @@ -885,9 +928,8 @@ robyn_mmm <- function(InputCollect, bind_cols(common) } - resultCollect[["decompSpendDist"]] <- dt_decompSpendDist %>% - bind_cols(common) - + # resultCollect[["decompSpendDist"]] <- dt_decompSpendDist %>% + # bind_cols(common) resultCollect <- append(resultCollect, as.list(common)) return(resultCollect) } @@ -895,7 +937,6 @@ robyn_mmm <- function(InputCollect, ########### Parallel start nrmse.collect <- NULL decomp.rssd.collect <- NULL - best_mape <- Inf if (cores == 1) { doparCollect <- lapply(1:iterPar, robyn_iterations) } else { @@ -950,9 +991,11 @@ robyn_mmm <- function(InputCollect, ) # stop cluster to avoid memory leaks - stopImplicitCluster() - registerDoSEQ() - getDoParWorkers() + if (cores > 1) { + stopImplicitCluster() + registerDoSEQ() + getDoParWorkers() + } if (!hyper_fixed) { cat("\r", paste("\n Finished in", round(sysTimeDopar[3] / 60, 2), "mins")) @@ -992,11 +1035,11 @@ robyn_mmm <- function(InputCollect, arrange(.data$mape, .data$liftMedia, .data$liftStart)) } - resultCollect[["decompSpendDist"]] <- as_tibble(bind_rows( - lapply(resultCollectNG, function(x) { - bind_rows(lapply(x, function(y) y$decompSpendDist)) - }) - )) + # resultCollect[["decompSpendDist"]] <- as_tibble(bind_rows( + # lapply(resultCollectNG, function(x) { + # bind_rows(lapply(x, function(y) y$decompSpendDist)) + # }) + # )) resultCollect$iter <- length(resultCollect$mape) resultCollect$elapsed.min <- sysTimeDopar[3] / 60 @@ -1013,10 +1056,18 @@ robyn_mmm <- function(InputCollect, )) } -model_decomp <- function(coefs, y_pred, - dt_modSaturated, dt_saturatedImmediate, - dt_saturatedCarryover, dt_modRollWind, - refreshAddedStart) { +#' @rdname robyn_mmm +#' @param inputs List. Elements to pass sub-functions +#' @export +model_decomp <- function(inputs = list()) { + coefs <- inputs$coefs + y_pred <- inputs$y_pred + dt_modSaturated <- inputs$dt_modSaturated + dt_saturatedImmediate <- inputs$dt_saturatedImmediate + dt_saturatedCarryover <- inputs$dt_saturatedCarryover + dt_modRollWind <- inputs$dt_modRollWind + refreshAddedStart <- inputs$refreshAddedStart + ## Input for decomp y <- dt_modSaturated$dep_var # x <- data.frame(x) @@ -1122,7 +1173,6 @@ model_refit <- function(x_train, y_train, x_val, y_val, x_test, y_test, intercept = intercept, ... ) # coef(mod) - df.int <- 1 ## Drop intercept if negative and intercept_sign == "non_negative" @@ -1135,6 +1185,7 @@ model_refit <- function(x_train, y_train, x_val, y_val, x_test, y_test, lambda = lambda, lower.limits = lower.limits, upper.limits = upper.limits, + type.measure = "mse", penalty.factor = penalty.factor, intercept = FALSE, ... @@ -1205,17 +1256,17 @@ lambda_seq <- function(x, y, seq_len = 100, lambda_min_ratio = 0.0001) { return(lambdas) } -hyper_collector <- function(InputCollect, hyper_in, ts_validation, add_penalty_factor, dt_hyper_fixed = NULL, cores) { +hyper_collector <- function(InputCollect, hyper_in, ts_validation, add_penalty_factor, dt_hyper_fixed = NULL, cores = 1) { # Fetch hyper-parameters based on media - hypParamSamName <- hyper_names(adstock = InputCollect$adstock, all_media = InputCollect$all_media) + hypParamSamName <- hyper_names( + adstock = InputCollect$adstock, + all_media = InputCollect$all_media, + all_vars = names(select(InputCollect$dt_mod, -c("ds", "dep_var"))) + ) # Manually add other hyper-parameters hypParamSamName <- c(hypParamSamName, HYPS_OTHERS) - # Add penalty factor hyper-parameters names - for_penalty <- names(select(InputCollect$dt_mod, -.data$ds, -.data$dep_var)) - if (add_penalty_factor) hypParamSamName <- c(hypParamSamName, paste0("penalty_", for_penalty)) - # Check hyper_fixed condition + add lambda + penalty factor hyper-parameters names all_fixed <- check_hyper_fixed(InputCollect, dt_hyper_fixed, add_penalty_factor) hypParamSamName <- attr(all_fixed, "hypParamSamName") @@ -1224,16 +1275,15 @@ hyper_collector <- function(InputCollect, hyper_in, ts_validation, add_penalty_f # Collect media hyperparameters hyper_bound_list <- list() for (i in seq_along(hypParamSamName)) { - hyper_bound_list[i] <- hyper_in[hypParamSamName[i]] - names(hyper_bound_list)[i] <- hypParamSamName[i] + hyper_bound_list <- append(hyper_bound_list, hyper_in[hypParamSamName[i]]) } - # Add unfixed lambda hyperparameter manually - if (length(hyper_bound_list[["lambda"]]) != 1) { + # Add lambda hyperparameter + if (!"lambda" %in% names(hyper_bound_list)) { hyper_bound_list$lambda <- c(0, 1) } - # Add unfixed train_size hyperparameter manually + # Add train_size hyperparameter if (ts_validation) { if (!"train_size" %in% names(hyper_bound_list)) { hyper_bound_list$train_size <- c(0.5, 0.8) @@ -1250,22 +1300,26 @@ hyper_collector <- function(InputCollect, hyper_in, ts_validation, add_penalty_f message("Fitting time series with all available data...") } - # Add unfixed penalty.factor hyperparameters manually + # Add penalty factor hyperparameters for_penalty <- names(select(InputCollect$dt_mod, -.data$ds, -.data$dep_var)) penalty_names <- paste0(for_penalty, "_penalty") if (add_penalty_factor) { for (penalty in penalty_names) { - if (length(hyper_bound_list[[penalty]]) != 1) { + if (!penalty %in% names(hyper_bound_list)) { hyper_bound_list[[penalty]] <- c(0, 1) } } } # Get hyperparameters for Nevergrad - hyper_bound_list_updated <- hyper_bound_list[which(unlist(lapply(hyper_bound_list, length) == 2))] + hyper_bound_list_updated <- hyper_bound_list[ + which(unlist(lapply(hyper_bound_list, length) == 2)) + ] # Get fixed hyperparameters - hyper_bound_list_fixed <- hyper_bound_list[which(unlist(lapply(hyper_bound_list, length) == 1))] + hyper_bound_list_fixed <- hyper_bound_list[ + which(unlist(lapply(hyper_bound_list, length) == 1)) + ] hyper_list_bind <- c(hyper_bound_list_updated, hyper_bound_list_fixed) hyper_list_all <- list() @@ -1274,7 +1328,9 @@ hyper_collector <- function(InputCollect, hyper_in, ts_validation, add_penalty_f names(hyper_list_all)[i] <- hypParamSamName[i] } - dt_hyper_fixed_mod <- data.frame(bind_cols(lapply(hyper_bound_list_fixed, function(x) rep(x, cores)))) + dt_hyper_fixed_mod <- data.frame(bind_cols(lapply( + hyper_bound_list_fixed, function(x) rep(x, cores) + ))) } else { hyper_bound_list_fixed <- list() for (i in seq_along(hypParamSamName)) { @@ -1283,8 +1339,9 @@ hyper_collector <- function(InputCollect, hyper_in, ts_validation, add_penalty_f } hyper_list_all <- hyper_bound_list_fixed - hyper_bound_list_updated <- hyper_bound_list_fixed[which(unlist(lapply(hyper_bound_list_fixed, length) == 2))] - cores <- 1 + hyper_bound_list_updated <- hyper_bound_list_fixed[ + which(unlist(lapply(hyper_bound_list_fixed, length) == 2)) + ] dt_hyper_fixed_mod <- data.frame(matrix(hyper_bound_list_fixed, nrow = 1)) names(dt_hyper_fixed_mod) <- names(hyper_bound_list_fixed) @@ -1309,7 +1366,7 @@ init_msgs_run <- function(InputCollect, refresh, lambda_control = NULL, quiet = nrow(InputCollect$dt_mod), InputCollect$intervalType, min(InputCollect$dt_mod$ds), - max(InputCollect$dt_mod$ds) + .next_date(InputCollect$dt_mod$ds) - 1 )) depth <- ifelse( "refreshDepth" %in% names(InputCollect), diff --git a/R/R/outputs.R b/R/R/outputs.R index 7eb429bba..661c32c19 100644 --- a/R/R/outputs.R +++ b/R/R/outputs.R @@ -179,7 +179,9 @@ robyn_outputs <- function(InputCollect, OutputModels, by = c("rn", "cluster") ) %>% left_join( - pareto_results$df_caov_pct_all, + pareto_results$df_caov_pct_all %>% + filter(.data$type == "Carryover") %>% + select("solID", "rn", "carryover_pct"), by = c("solID", "rn") ) OutputCollect$mediaVecCollect <- left_join( @@ -242,7 +244,8 @@ robyn_outputs <- function(InputCollect, OutputModels, pareto_df <- NULL } attr(OutputCollect, "runTime") <- round( - difftime(Sys.time(), t0, units = "mins"), 2) + difftime(Sys.time(), t0, units = "mins"), 2 + ) robyn_write( InputCollect = InputCollect, OutputCollect = OutputCollect, diff --git a/R/R/pareto.R b/R/R/pareto.R index 0bdd2ec7e..b52b2733a 100644 --- a/R/R/pareto.R +++ b/R/R/pareto.R @@ -58,9 +58,8 @@ robyn_pareto <- function(InputCollect, OutputModels, xDecompAgg <- left_join(xDecompAgg, bootstrap, by = c("rn" = "variable")) } } - - xDecompAggCoef0 <- xDecompAgg %>% - filter(.data$rn %in% InputCollect$paid_media_spends) %>% + xDecompAggPaid <- xDecompAgg %>% filter(.data$rn %in% InputCollect$paid_media_selected) + xDecompAggCoef0 <- xDecompAggPaid %>% group_by(.data$solID) %>% summarise(coef0 = min(.data$coef, na.rm = TRUE) == 0) @@ -78,9 +77,9 @@ robyn_pareto <- function(InputCollect, OutputModels, # Calculate Pareto-fronts (for "all" or pareto_fronts) resultHypParamPareto <- filter(resultHypParam, .data$mape.qt10 == TRUE) paretoResults <- pareto_front( - x = resultHypParamPareto$nrmse, - y = resultHypParamPareto$decomp.rssd, - fronts = ifelse("auto" %in% pareto_fronts, Inf, pareto_fronts), + xi = resultHypParamPareto$nrmse, + yi = resultHypParamPareto$decomp.rssd, + pareto_fronts = ifelse("auto" %in% pareto_fronts, Inf, pareto_fronts), sort = FALSE ) resultHypParamPareto <- resultHypParamPareto %>% @@ -101,17 +100,15 @@ robyn_pareto <- function(InputCollect, OutputModels, # Bind robynPareto results xDecompAgg <- left_join(xDecompAgg, select(resultHypParam, .data$robynPareto, .data$solID), by = "solID") - decompSpendDist <- bind_rows(lapply(OutModels, function(x) { - mutate(x$resultCollect$decompSpendDist, trial = x$trial) - })) %>% - { - if (!hyper_fixed) mutate(., solID = paste(.data$trial, .data$iterNG, .data$iterPar, sep = "_")) else . - } %>% - left_join(select(resultHypParam, .data$robynPareto, .data$solID), by = "solID") + xDecompAggMedia <- xDecompAgg %>% filter(.data$rn %in% InputCollect$all_media) %>% + select(c("rn", "solID", "coef", "mean_spend", "mean_exposure", "xDecompAgg", "total_spend", "robynPareto")) # Prepare parallel loop if (TRUE) { - if (check_parallel() & OutputModels$cores > 1) registerDoParallel(OutputModels$cores) else registerDoSEQ() + if (OutputModels$cores > 1) { + registerDoParallel(OutputModels$cores) + registerDoSEQ() + } if (hyper_fixed) pareto_fronts <- 1 # Get at least 100 candidates for better clustering if (nrow(resultHypParam) == 1) pareto_fronts <- 1 @@ -140,90 +137,67 @@ robyn_pareto <- function(InputCollect, OutputModels, } pareto_fronts_vec <- 1:pareto_fronts - decompSpendDistPar <- decompSpendDist[decompSpendDist$robynPareto %in% pareto_fronts_vec, ] + # decompSpendDistPar <- decompSpendDist[decompSpendDist$robynPareto %in% pareto_fronts_vec, ] resultHypParamPar <- resultHypParam[resultHypParam$robynPareto %in% pareto_fronts_vec, ] - xDecompAggPar <- xDecompAgg[xDecompAgg$robynPareto %in% pareto_fronts_vec, ] + # xDecompAggPar <- xDecompAgg[xDecompAgg$robynPareto %in% pareto_fronts_vec, ] + xDecompAggMediaPar <- xDecompAggMedia %>% filter(.data$robynPareto %in% pareto_fronts_vec) respN <- NULL } if (!quiet) { message(sprintf( ">>> Calculating response curves for all models' media variables (%s)...", - nrow(decompSpendDistPar) + nrow(xDecompAggMediaPar) )) } - run_dt_resp <- function(respN, InputCollect, OutputModels, decompSpendDistPar, resultHypParamPar, xDecompAggPar, ...) { - get_solID <- decompSpendDistPar$solID[respN] - get_spendname <- decompSpendDistPar$rn[respN] - startRW <- InputCollect$rollingWindowStartWhich - endRW <- InputCollect$rollingWindowEndWhich - - get_resp <- robyn_response( - select_model = get_solID, - metric_name = get_spendname, - #metric_value = decompSpendDistPar$total_spend[respN], - #date_range = range(InputCollect$dt_modRollWind$ds), - date_range = "all", - dt_hyppar = resultHypParamPar, - dt_coef = xDecompAggPar, - InputCollect = InputCollect, - OutputCollect = OutputModels, - quiet = TRUE, - ... - ) - # Median value (but must be within the curve) - # med_in_curve <- sort(get_resp$response_total)[round(length(get_resp$response_total) / 2)] - - ## simulate mean response adstock from get_resp$input_carryover - # mean_response <- mean(get_resp$response_total) - mean_spend_adstocked <- mean(get_resp$input_total[startRW:endRW]) - mean_carryover <- mean(get_resp$input_carryover[startRW:endRW]) - dt_hyppar <- resultHypParamPar %>% filter(.data$solID == get_solID) - chnAdstocked <- data.frame(v1 = get_resp$input_total[startRW:endRW]) - colnames(chnAdstocked) <- get_spendname - dt_coef <- xDecompAggPar %>% - filter(.data$solID == get_solID & .data$rn == get_spendname) %>% - select(c("rn", "coef")) - hills <- get_hill_params( - InputCollect, NULL, dt_hyppar, dt_coef, - mediaSpendSorted = get_spendname, - select_model = get_solID, chnAdstocked - ) - mean_response <- fx_objective( - x = decompSpendDistPar$mean_spend[respN], - coeff = hills$coefs_sorted, - alpha = hills$alphas, - inflexion = hills$inflexions, - x_hist_carryover = mean_carryover, - get_sum = FALSE - ) - dt_resp <- data.frame( - mean_response = mean_response, - mean_spend_adstocked = mean_spend_adstocked, - mean_carryover = mean_carryover, - rn = decompSpendDistPar$rn[respN], - solID = decompSpendDistPar$solID[respN] - ) - return(dt_resp) - } - if (OutputModels$cores > 1) { - resp_collect <- foreach( - respN = seq_along(decompSpendDistPar$rn), .combine = bind_rows - ) %dorng% { - run_dt_resp(respN, InputCollect, OutputModels, decompSpendDistPar, resultHypParamPar, xDecompAggPar, ...) - } - stopImplicitCluster() - registerDoSEQ() - getDoParWorkers() - } else { - resp_collect <- bind_rows(lapply(seq_along(decompSpendDistPar$rn), function(respN) { - run_dt_resp(respN, InputCollect, OutputModels, decompSpendDistPar, resultHypParamPar, xDecompAggPar, ...) - })) - } - decompSpendDist <- left_join( - decompSpendDist, - resp_collect, + cnt_resp <- nrow(xDecompAggMediaPar) + pb_resp <- txtProgressBar(min = 0, max = cnt_resp, style = 3) + resp_collect <- lapply( + 1:cnt_resp, + function(respN) { + setTxtProgressBar(pb_resp, respN) + get_solID <- xDecompAggMediaPar$solID[respN] + get_media_name <- xDecompAggMediaPar$rn[respN] + window_start_loc <- InputCollect$rollingWindowStartWhich + window_end_loc <- InputCollect$rollingWindowEndWhich + + get_resp <- robyn_response( + select_model = get_solID, + metric_name = get_media_name, + date_range = "all", + dt_hyppar = resultHypParamPar, + dt_coef = xDecompAggMediaPar, + InputCollect = InputCollect, + OutputCollect = OutputModels, + quiet = TRUE, + ... + ) + list_response <- list( + dt_resp = data.frame( + mean_response = get_resp$mean_response_total, + mean_spend_adstocked = get_resp$mean_input_immediate + get_resp$mean_input_carryover, + mean_carryover = get_resp$mean_input_carryover, + rn = get_media_name, + solID = get_solID + ), + dt_resp_vec = data.frame( + channel = rep(get_media_name, length(get_resp$response_total)), + response = get_resp$response_total, + response_carryover = get_resp$response_carryover, + spend = get_resp$input_total[window_start_loc:window_end_loc], + solID = rep(get_solID, length(get_resp$response_total)) + ) + ) + return(list_response) + } + ) + close(pb_resp) + dt_resp <- bind_rows(lapply(resp_collect, function(x) x[["dt_resp"]])) + dt_resp_vec <- bind_rows(lapply(resp_collect, function(x) x[["dt_resp_vec"]])) + + xDecompAgg <- xDecompAgg %>% left_join( + dt_resp, by = c("solID", "rn") ) %>% mutate( @@ -232,15 +206,6 @@ robyn_pareto <- function(InputCollect, OutputModels, cpa_mean = .data$mean_spend / .data$mean_response, cpa_total = .data$total_spend / .data$xDecompAgg ) - # decompSpendDist %>% filter(solID == select_model) %>% arrange(rn) %>% select(rn, mean_spend, mean_response, roi_mean) - xDecompAgg <- left_join( - xDecompAgg, - select( - decompSpendDist, .data$rn, .data$solID, .data$total_spend, .data$mean_spend, .data$mean_spend_adstocked, .data$mean_carryover, - .data$mean_response, .data$spend_share, .data$effect_share, .data$roi_mean, .data$roi_total, .data$cpa_total - ), - by = c("solID", "rn") - ) # Pareto loop (no plots) mediaVecCollect <- list() @@ -251,12 +216,13 @@ robyn_pareto <- function(InputCollect, OutputModels, dt_modRollWind <- InputCollect$dt_modRollWind rw_start_loc <- InputCollect$rollingWindowStartWhich rw_end_loc <- InputCollect$rollingWindowEndWhich + dt_ds <- dt_mod[rw_start_loc:rw_end_loc, "ds"] for (pf in pareto_fronts_vec) { plotMediaShare <- filter( xDecompAgg, .data$robynPareto == pf, - .data$rn %in% InputCollect$paid_media_spends + .data$rn %in% InputCollect$paid_media_selected ) uniqueSol <- unique(plotMediaShare$solID) plotWaterfall <- xDecompAgg %>% filter(.data$robynPareto == pf) @@ -264,15 +230,6 @@ robyn_pareto <- function(InputCollect, OutputModels, message(sprintf(">> Pareto-Front: %s [%s models]", pf, length(uniqueSol))) } - # # To recreate "xDecompVec", "xDecompVecImmediate", "xDecompVecCarryover" for each model - # temp <- OutputModels[names(OutputModels) %in% paste0("trial", 1:OutputModels$trials)] - # xDecompVecImmCarr <- bind_rows(lapply(temp, function(x) x$resultCollect$xDecompVec)) - # if (!"solID" %in% colnames(xDecompVecImmCarr)) { - # xDecompVecImmCarr <- xDecompVecImmCarr %>% - # mutate(solID = paste(.data$trial, .data$iterNG, .data$iterPar, sep = "_")) %>% - # filter(.data$solID %in% uniqueSol) - # } - # Calculations for pareto AND pareto plots for (sid in uniqueSol) { # parallelResult <- foreach(sid = uniqueSol) %dorng% { @@ -287,7 +244,7 @@ robyn_pareto <- function(InputCollect, OutputModels, c("spend_share", "effect_share", "roi_total", "cpa_total") ) %>% select(c("rn", "nrmse", "decomp.rssd", "rsq_train", "variable", "value")) %>% - mutate(rn = factor(.data$rn, levels = sort(InputCollect$paid_media_spends))) + mutate(rn = factor(.data$rn, levels = sort(InputCollect$paid_media_selected))) plotMediaShareLoopBar <- filter(temp, .data$variable %in% c("spend_share", "effect_share")) plotMediaShareLoopLine <- filter(temp, .data$variable == ifelse( InputCollect$dep_var_type == "conversion", "cpa_total", "roi_total" @@ -365,209 +322,99 @@ robyn_pareto <- function(InputCollect, OutputModels, ) ## 4. Spend response curve - dt_transformPlot <- select(dt_mod, .data$ds, all_of(InputCollect$all_media)) # independent variables - dt_transformSpend <- cbind(dt_transformPlot[, "ds"], InputCollect$dt_input[, c(InputCollect$paid_media_spends)]) # spends of indep vars - dt_transformSpendMod <- dt_transformPlot[rw_start_loc:rw_end_loc, ] - # update non-spend variables - # if (length(InputCollect$exposure_vars) > 0) { - # for (expo in InputCollect$exposure_vars) { - # sel_nls <- ifelse(InputCollect$modNLSCollect[channel == expo, rsq_nls > rsq_lm], "nls", "lm") - # dt_transformSpendMod[, (expo) := InputCollect$yhatNLSCollect[channel == expo & models == sel_nls, yhat]] - # } - # } - dt_transformAdstock <- dt_transformPlot - dt_transformSaturation <- dt_transformPlot[ - rw_start_loc:rw_end_loc, - ] - - m_decayRate <- list() - for (med in seq_along(InputCollect$all_media)) { - med_select <- InputCollect$all_media[med] - m <- dt_transformPlot[, med_select][[1]] - # Adstocking - adstock <- InputCollect$adstock - if (adstock == "geometric") { - theta <- hypParam[paste0(InputCollect$all_media[med], "_thetas")][[1]] - } - if (grepl("weibull", adstock)) { - shape <- hypParam[paste0(InputCollect$all_media[med], "_shapes")][[1]] - scale <- hypParam[paste0(InputCollect$all_media[med], "_scales")][[1]] - } - x_list <- transform_adstock(m, adstock, theta = theta, shape = shape, scale = scale) - m_adstocked <- x_list$x_decayed - dt_transformAdstock[med_select] <- m_adstocked - m_adstockedRollWind <- m_adstocked[ - rw_start_loc:rw_end_loc - ] - ## Saturation - alpha <- hypParam[paste0(InputCollect$all_media[med], "_alphas")][[1]] - gamma <- hypParam[paste0(InputCollect$all_media[med], "_gammas")][[1]] - dt_transformSaturation[med_select] <- saturation_hill( - x = m_adstockedRollWind, alpha = alpha, gamma = gamma - ) - } - dt_transformSaturationDecomp <- dt_transformSaturation - for (i in seq_along(InputCollect$all_media)) { - coef <- plotWaterfallLoop$coef[plotWaterfallLoop$rn == InputCollect$all_media[i]] - dt_transformSaturationDecomp[InputCollect$all_media[i]] <- coef * - dt_transformSaturationDecomp[InputCollect$all_media[i]] - } - dt_transformSaturationSpendReverse <- dt_transformAdstock[ - rw_start_loc:rw_end_loc, - ] - - ## Reverse MM fitting - # dt_transformSaturationSpendReverse <- copy(dt_transformAdstock[, c("ds", InputCollect$all_media), with = FALSE]) - # for (i in seq_along(InputCollect$paid_media_spends)) { - # chn <- InputCollect$paid_media_vars[i] - # if (chn %in% InputCollect$paid_media_vars[InputCollect$exposure_selector]) { - # # Get Michaelis Menten nls fitting param - # get_chn <- dt_transformSaturationSpendReverse[, chn, with = FALSE] - # Vmax <- InputCollect$modNLSCollect[channel == chn, Vmax] - # Km <- InputCollect$modNLSCollect[channel == chn, Km] - # # Reverse exposure to spend - # dt_transformSaturationSpendReverse[, (chn) := mic_men(x = .SD, Vmax = Vmax, Km = Km, reverse = TRUE), .SDcols = chn] # .SD * Km / (Vmax - .SD) exposure to spend, reverse Michaelis Menthen: x = y*Km/(Vmax-y) - # } else if (chn %in% InputCollect$exposure_vars) { - # coef_lm <- InputCollect$modNLSCollect[channel == chn, coef_lm] - # dt_transformSaturationSpendReverse[, (chn) := .SD / coef_lm, .SDcols = chn] - # } - # } - # dt_transformSaturationSpendReverse <- dt_transformSaturationSpendReverse[rw_start_loc:rw_end_loc] - - dt_scurvePlot <- tidyr::gather( - dt_transformSaturationDecomp, "channel", "response", - 2:ncol(dt_transformSaturationDecomp) - ) %>% - mutate(spend = tidyr::gather( - dt_transformSaturationSpendReverse, "channel", "spend", - 2:ncol(dt_transformSaturationSpendReverse) - )$spend) - - # Remove outlier introduced by MM nls fitting - dt_scurvePlot <- dt_scurvePlot[dt_scurvePlot$spend >= 0, ] + dt_resp_vec_loop <- cbind( + dt_ds, + dt_resp_vec %>% + filter(.data$solID == sid) %>% + select(c("channel", "spend","response")) + ) + dt_transformAdstock <- dt_resp_vec_loop %>% + select(c("ds","channel", "spend")) %>% + pivot_wider(values_from = "spend", names_from = "channel") + dt_transformSaturationDecomp <- dt_resp_vec_loop %>% + select(c("ds","channel", "response")) %>% + pivot_wider(values_from = "response", names_from = "channel") dt_scurvePlotMean <- plotWaterfall %>% filter(.data$solID == sid & !is.na(.data$mean_spend)) %>% - select(c(channel = "rn", "mean_spend", "mean_spend_adstocked", "mean_carryover", "mean_response", "solID")) - + select(c(channel = "rn", "mean_spend", "mean_spend_adstocked", + "mean_carryover", "mean_response", "solID")) # Exposure response curve plot4data <- list( - dt_scurvePlot = dt_scurvePlot, + dt_scurvePlot = dt_resp_vec_loop, dt_scurvePlotMean = dt_scurvePlotMean ) ## 5. Fitted vs actual - col_order <- c("ds", "dep_var", InputCollect$all_ind_vars) - dt_transformDecomp <- select( - dt_modRollWind, .data$ds, .data$dep_var, - any_of(c(InputCollect$prophet_vars, InputCollect$context_vars)) - ) %>% - bind_cols(select(dt_transformSaturation, all_of(InputCollect$all_media))) %>% - select(all_of(col_order)) + temp_order1 <- c("ds", "dep_var") + temp_order2 <- c("(Intercept)", InputCollect$prophet_vars, InputCollect$context_vars) + dt_transformDecomp <- dt_modRollWind %>% + mutate("(Intercept)" = 1) %>% + select(all_of(c(temp_order1, temp_order2))) xDecompVec <- xDecompAgg %>% - filter(.data$solID == sid) %>% - select(.data$solID, .data$rn, .data$coef) %>% - tidyr::spread(.data$rn, .data$coef) - if (!("(Intercept)" %in% names(xDecompVec))) xDecompVec[["(Intercept)"]] <- 0 - xDecompVec <- select(xDecompVec, c("solID", "(Intercept)", col_order[!(col_order %in% c("ds", "dep_var"))])) - intercept <- xDecompVec$`(Intercept)` - xDecompVec <- data.frame(mapply( - function(scurved, coefs) scurved * coefs, - scurved = select(dt_transformDecomp, -.data$ds, -.data$dep_var), - coefs = select(xDecompVec, -.data$solID, -.data$`(Intercept)`) - )) - xDecompVec <- mutate(xDecompVec, - intercept = intercept, - depVarHat = rowSums(xDecompVec) + intercept, solID = sid - ) - xDecompVec <- bind_cols(select(dt_transformDecomp, .data$ds, .data$dep_var), xDecompVec) + filter(.data$solID == sid & .data$rn %in% temp_order2) %>% + select(.data$rn, .data$coef) %>% + pivot_wider(values_from = "coef", names_from = "rn") %>% + mutate("(Intercept)" = ifelse( + "(Intercept)" %in% levels(plotWaterfallLoop$rn), + .data$`(Intercept)`, 0)) + xDecompVec <- bind_cols( + dt_transformDecomp %>% select(temp_order1), + data.frame(mapply( + function(vec, coefs) {vec * coefs}, + vec = select(dt_transformDecomp, -temp_order1), + coefs = xDecompVec + ), check.names = FALSE), + dt_transformSaturationDecomp %>% select(-"ds") + ) %>% + rename("intercept" = "(Intercept)") %>% + mutate(depVarHat = rowSums(select(., -temp_order1)), + solID = sid) %>% + select(c("ds", "dep_var", InputCollect$all_ind_vars, + "intercept", "depVarHat", "solID")) + xDecompVecPlot <- select(xDecompVec, .data$ds, .data$dep_var, .data$depVarHat) %>% rename("actual" = "dep_var", "predicted" = "depVarHat") - xDecompVecPlotMelted <- tidyr::gather( - xDecompVecPlot, - key = "variable", value = "value", -.data$ds - ) - rsq <- filter(xDecompAgg, .data$solID == sid) %>% - pull(.data$rsq_train) %>% - .[1] + xDecompVecPlotMelted <- xDecompVecPlot %>% + pivot_longer(names_to = "variable", values_to = "value", -.data$ds) %>% + arrange(.data$variable, .data$ds) + rsq <- filter(resultHypParam, .data$solID == sid) %>% + pull(.data$rsq_train) plot5data <- list(xDecompVecPlotMelted = xDecompVecPlotMelted, rsq = rsq) ## 6. Diagnostic: fitted vs residual plot6data <- list(xDecompVecPlot = xDecompVecPlot) ## 7. Immediate vs carryover response - # temp <- filter(xDecompVecImmCarr, .data$solID == sid) - hypParamSam <- resultHypParam[resultHypParam$solID == sid, ] - dt_saturated_dfs <- run_transformations(InputCollect, hypParamSam, adstock) - coefs <- xDecompAgg$coef[xDecompAgg$solID == sid] - names(coefs) <- xDecompAgg$rn[xDecompAgg$solID == sid] - decompCollect <- model_decomp( - coefs = coefs, - y_pred = dt_saturated_dfs$dt_modSaturated$dep_var, # IS THIS RIGHT? - dt_modSaturated = dt_saturated_dfs$dt_modSaturated, - dt_saturatedImmediate = dt_saturated_dfs$dt_saturatedImmediate, - dt_saturatedCarryover = dt_saturated_dfs$dt_saturatedCarryover, - dt_modRollWind = dt_modRollWind, - refreshAddedStart = InputCollect$refreshAddedStart - ) - mediaDecompImmediate <- select(decompCollect$mediaDecompImmediate, -.data$ds, -.data$y) - colnames(mediaDecompImmediate) <- paste0(colnames(mediaDecompImmediate), "_MDI") - mediaDecompCarryover <- select(decompCollect$mediaDecompCarryover, -.data$ds, -.data$y) - colnames(mediaDecompCarryover) <- paste0(colnames(mediaDecompCarryover), "_MDC") - temp <- bind_cols( - decompCollect$xDecompVec, - mediaDecompImmediate, - mediaDecompCarryover + + temp_p7 <- dt_resp_vec %>% + filter(.data$solID == sid) %>% + group_by(.data$channel) %>% + summarise(Total = sum(.data$response), Carryover = sum(.data$response_carryover)) %>% + mutate(Immediate = .data$Total - .data$Carryover, + perc_imme = 1 - .data$Carryover / .data$Total, + perc_caov = .data$Carryover / .data$Total, + carryover_pct = .data$Carryover / .data$Total) + plot7data <- bind_cols( + temp_p7 %>% + select(rn = "channel", "Immediate", "Carryover") %>% + pivot_longer(names_to = "type", values_to = "response", cols = -"rn"), + temp_p7 %>% + select(rn = "channel", Immediate = "perc_imme", Carryover = "perc_caov") %>% + pivot_longer(names_to = "type", values_to = "percentage", cols = -"rn") %>% + select("percentage"), + temp_p7 %>% + select(rn = "channel", Immediate = "perc_caov", Carryover = "perc_caov") %>% + pivot_longer(names_to = "type", values_to = "carryover_pct", cols = -"rn") %>% + select("carryover_pct") ) %>% mutate(solID = sid) - vec_collect <- list( - xDecompVec = select(temp, -dplyr::ends_with("_MDI"), -dplyr::ends_with("_MDC")), - xDecompVecImmediate = select(temp, -dplyr::ends_with("_MDC"), -all_of(InputCollect$all_media)), - xDecompVecCarryover = select(temp, -dplyr::ends_with("_MDI"), -all_of(InputCollect$all_media)) - ) - this <- gsub("_MDI", "", colnames(vec_collect$xDecompVecImmediate)) - colnames(vec_collect$xDecompVecImmediate) <- colnames(vec_collect$xDecompVecCarryover) <- this - df_caov <- vec_collect$xDecompVecCarryover %>% - group_by(.data$solID) %>% - summarise(across(InputCollect$all_media, sum)) - df_total <- vec_collect$xDecompVec %>% - group_by(.data$solID) %>% - summarise(across(InputCollect$all_media, sum)) - df_caov_pct <- bind_cols( - select(df_caov, .data$solID), - select(df_caov, -.data$solID) / select(df_total, -.data$solID) - ) %>% - pivot_longer(cols = InputCollect$all_media, names_to = "rn", values_to = "carryover_pct") - df_caov_pct[is.na(as.matrix(df_caov_pct))] <- 0 - df_caov_pct_all <- bind_rows(df_caov_pct_all, df_caov_pct) - # Gather everything in an aggregated format - xDecompVecImmeCaov <- bind_rows( - select(vec_collect$xDecompVecImmediate, c("ds", InputCollect$all_media, "solID")) %>% - mutate(type = "Immediate"), - select(vec_collect$xDecompVecCarryover, c("ds", InputCollect$all_media, "solID")) %>% - mutate(type = "Carryover") - ) %>% - pivot_longer(cols = InputCollect$all_media, names_to = "rn") %>% - select(c("solID", "type", "rn", "value")) %>% - group_by(.data$solID, .data$rn, .data$type) %>% - summarise(response = sum(.data$value), .groups = "drop_last") %>% - mutate(percentage = .data$response / sum(.data$response)) %>% - replace(., is.na(.), 0) %>% - left_join(df_caov_pct, c("solID", "rn")) - if (length(unique(xDecompAgg$solID)) == 1) { - xDecompVecImmeCaov$solID <- OutModels$trial1$resultCollect$resultHypParam$solID - } - plot7data <- xDecompVecImmeCaov + df_caov_pct_all <- rbind(df_caov_pct_all, plot7data) ## 8. Bootstrapped ROI/CPA with CIs # plot8data <- "Empty" # Filled when running robyn_onepagers() with clustering data # Gather all results mediaVecCollect <- bind_rows(mediaVecCollect, list( - mutate(dt_transformPlot, type = "rawMedia", solID = sid), - mutate(dt_transformSpend, type = "rawSpend", solID = sid), - mutate(dt_transformSpendMod, type = "predictedExposure", solID = sid), mutate(dt_transformAdstock, type = "adstockedMedia", solID = sid), - mutate(dt_transformSaturation, type = "saturatedMedia", solID = sid), - mutate(dt_transformSaturationSpendReverse, type = "saturatedSpendReversed", solID = sid), mutate(dt_transformSaturationDecomp, type = "decompMedia", solID = sid) )) xDecompVecCollect <- bind_rows(xDecompVecCollect, xDecompVec) @@ -596,25 +443,115 @@ robyn_pareto <- function(InputCollect, OutputModels, df_caov_pct_all = df_caov_pct_all ) - # if (check_parallel()) stopImplicitCluster() - # close(pbplot) + if (OutputModels$cores > 1) stopImplicitCluster() return(pareto_results) } -pareto_front <- function(x, y, fronts = 1, sort = TRUE) { - stopifnot(length(x) == length(y)) - d <- data.frame(x, y) - Dtemp <- D <- d[order(d$x, d$y, decreasing = FALSE), ] +#' @rdname robyn_outputs +#' @param xi,yi Numeric. Coordinates values per observation. +#' @export +pareto_front <- function(xi, yi, pareto_fronts = 1, ...) { + stopifnot(length(xi) == length(yi)) + d <- data.frame(xi, yi) + Dtemp <- D <- d[order(d$xi, d$yi, decreasing = FALSE), ] df <- data.frame() i <- 1 - while (nrow(Dtemp) >= 1 & i <= max(fronts)) { - these <- Dtemp[which(!duplicated(cummin(Dtemp$y))), ] + while (nrow(Dtemp) >= 1 & i <= max(pareto_fronts)) { + these <- Dtemp[which(!duplicated(cummin(Dtemp$yi))), ] these$pareto_front <- i df <- rbind(df, these) Dtemp <- Dtemp[!row.names(Dtemp) %in% row.names(these), ] i <- i + 1 } - ret <- merge(x = d, y = df, by = c("x", "y"), all.x = TRUE, sort = sort) + ret <- merge(x = d, y = df, by = c("xi", "yi"), all.x = TRUE, ...) + colnames(ret) <- c("x", "y", "pareto_front") return(ret) } + +#' @rdname robyn_outputs +#' @param start_date,end_date Character/Date. Dates to consider when calculating +#' immediate and carryover values per channel. +#' @export +robyn_immcarr <- function( + InputCollect, OutputCollect, solID = NULL, + start_date = NULL, end_date = NULL, ...) { + # Define default values when not provided + if (is.null(solID)) solID <- OutputCollect$resultHypParam$solID[1] + if (is.null(start_date)) start_date <- InputCollect$window_start + if (is.null(end_date)) end_date <- InputCollect$window_end + # Get closer dates to date passed + start_date <- InputCollect$dt_modRollWind$ds[ + which.min(abs(as.Date(start_date) - InputCollect$dt_modRollWind$ds))] + end_date <- InputCollect$dt_modRollWind$ds[ + which.min(abs(as.Date(end_date) - InputCollect$dt_modRollWind$ds))] + # Filter for custom window + rollingWindowStartWhich <- which(InputCollect$dt_modRollWind$ds == start_date) + rollingWindowEndWhich <- which(InputCollect$dt_modRollWind$ds == end_date) + rollingWindow <- rollingWindowStartWhich:rollingWindowEndWhich + # Calculate saturated dataframes with carryover and immediate parts + hypParamSam <- OutputCollect$resultHypParam[OutputCollect$resultHypParam$solID == solID, ] + dt_saturated_dfs <- run_transformations(all_media = InputCollect$all_media, + window_start_loc = InputCollect$rollingWindowStartWhich, + window_end_loc = InputCollect$rollingWindowEndWhich, + dt_mod = InputCollect$dt_mod, + adstock = InputCollect$adstock, + dt_hyppar = hypParamSam, ...) + # Calculate decomposition + coefs <- OutputCollect$xDecompAgg$coef[OutputCollect$xDecompAgg$solID == solID] + names(coefs) <- OutputCollect$xDecompAgg$rn[OutputCollect$xDecompAgg$solID == solID] + decompCollect <- model_decomp( + inputs = list( + coefs = coefs, + y_pred = dt_saturated_dfs$dt_modSaturated$dep_var[rollingWindow], + dt_modSaturated = dt_saturated_dfs$dt_modSaturated[rollingWindow, ], + dt_saturatedImmediate = dt_saturated_dfs$dt_saturatedImmediate[rollingWindow, ], + dt_saturatedCarryover = dt_saturated_dfs$dt_saturatedCarryover[rollingWindow, ], + dt_modRollWind = InputCollect$dt_modRollWind[rollingWindow, ], + refreshAddedStart = start_date + )) + mediaDecompImmediate <- select(decompCollect$mediaDecompImmediate, -"ds", -"y") + colnames(mediaDecompImmediate) <- paste0(colnames(mediaDecompImmediate), "_MDI") + mediaDecompCarryover <- select(decompCollect$mediaDecompCarryover, -"ds", -"y") + colnames(mediaDecompCarryover) <- paste0(colnames(mediaDecompCarryover), "_MDC") + temp <- bind_cols( + decompCollect$xDecompVec, + mediaDecompImmediate, + mediaDecompCarryover + ) %>% mutate(solID = solID) + vec_collect <- list( + xDecompVec = select(temp, -dplyr::ends_with("_MDI"), -dplyr::ends_with("_MDC")), + xDecompVecImmediate = select(temp, -dplyr::ends_with("_MDC"), -all_of(InputCollect$all_media)), + xDecompVecCarryover = select(temp, -dplyr::ends_with("_MDI"), -all_of(InputCollect$all_media)) + ) + this <- gsub("_MDI", "", colnames(vec_collect$xDecompVecImmediate)) + colnames(vec_collect$xDecompVecImmediate) <- colnames(vec_collect$xDecompVecCarryover) <- this + df_caov <- vec_collect$xDecompVecCarryover %>% + group_by(.data$solID) %>% + summarise(across(InputCollect$all_media, sum)) + df_total <- vec_collect$xDecompVec %>% + group_by(.data$solID) %>% + summarise(across(InputCollect$all_media, sum)) + df_caov_pct <- bind_cols( + select(df_caov, "solID"), + select(df_caov, -"solID") / select(df_total, -"solID") + ) %>% + pivot_longer(cols = InputCollect$all_media, names_to = "rn", values_to = "carryover_pct") + df_caov_pct[is.na(as.matrix(df_caov_pct))] <- 0 + # Gather everything in an aggregated format + xDecompVecImmeCaov <- bind_rows( + select(vec_collect$xDecompVecImmediate, c("ds", InputCollect$all_media, "solID")) %>% + mutate(type = "Immediate"), + select(vec_collect$xDecompVecCarryover, c("ds", InputCollect$all_media, "solID")) %>% + mutate(type = "Carryover") + ) %>% + pivot_longer(cols = InputCollect$all_media, names_to = "rn") %>% + mutate(start_date = start_date, end_date = end_date) %>% + select("solID", ends_with("_date"), "type", "rn", "value") %>% + group_by(.data$solID, .data$start_date, .data$end_date, .data$rn, .data$type) %>% + summarise(response = sum(.data$value), .groups = "drop_last") %>% + mutate(percentage = .data$response / sum(.data$response)) %>% + replace(., is.na(.), 0) %>% ungroup() %>% + left_join(df_caov_pct, c("solID", "rn")) + return(xDecompVecImmeCaov) +} diff --git a/R/R/plots.R b/R/R/plots.R index 191a4a433..c113ee2e6 100644 --- a/R/R/plots.R +++ b/R/R/plots.R @@ -174,7 +174,7 @@ robyn_plots <- function( if (length(temp_all) > 0) { xDecompAgg <- temp_all$xDecompAgg dt_ridges <- xDecompAgg %>% - filter(.data$rn %in% InputCollect$paid_media_spends) %>% + filter(.data$rn %in% InputCollect$paid_media_vars) %>% mutate(iteration = (.data$iterNG - 1) * OutputCollect$cores + .data$iterPar) %>% select(variables = .data$rn, .data$roi_total, .data$iteration, .data$trial) %>% arrange(.data$iteration, .data$variables) @@ -266,6 +266,12 @@ robyn_onepagers <- function( sid <- NULL # for parallel loops } if (!is.null(select_model)) { + if ("refreshed" %in% select_model) { + select_model <- OutputCollect$resultHypParam %>% + arrange(.data$decomp.rssd) %>% + pull(.data$solID) %>% + head(1) + } if ("clusters" %in% select_model) select_model <- OutputCollect$clusters$models$solID resultHypParam <- resultHypParam[resultHypParam$solID %in% select_model, ] xDecompAgg <- xDecompAgg[xDecompAgg$solID %in% select_model, ] @@ -311,7 +317,7 @@ robyn_onepagers <- function( plotMediaShare <- filter( xDecompAgg, .data$robynPareto == pf, - .data$rn %in% InputCollect$paid_media_spends + .data$rn %in% InputCollect$paid_media_vars ) uniqueSol <- unique(plotMediaShare$solID) @@ -338,8 +344,10 @@ robyn_onepagers <- function( summarise(performance = ifelse( type == "ROAS", sum(.data$xDecompAgg) / sum(.data$total_spend), - sum(.data$total_spend) / sum(.data$xDecompAgg))) %>% - pull(.data$performance) %>% signif(., 3) + sum(.data$total_spend) / sum(.data$xDecompAgg) + )) %>% + pull(.data$performance) %>% + signif(., 3) if (val) { errors <- sprintf( paste( @@ -402,10 +410,13 @@ robyn_onepagers <- function( ## 2. Waterfall plotWaterfallLoop <- temp[[sid]]$plot2data$plotWaterfallLoop %>% mutate(rn = ifelse( - .data$rn %in% bvars, paste0("Baseline_L", baseline_level), as.character(.data$rn))) %>% + .data$rn %in% bvars, paste0("Baseline_L", baseline_level), as.character(.data$rn) + )) %>% group_by(.data$rn) %>% - summarise(xDecompAgg = sum(.data$xDecompAgg, na.rm = TRUE), - xDecompPerc = sum(.data$xDecompPerc, na.rm = TRUE)) %>% + summarise( + xDecompAgg = sum(.data$xDecompAgg, na.rm = TRUE), + xDecompPerc = sum(.data$xDecompPerc, na.rm = TRUE) + ) %>% arrange(.data$xDecompPerc) %>% mutate( end = 1 - cumsum(.data$xDecompPerc), @@ -416,29 +427,28 @@ robyn_onepagers <- function( sign = as.factor(ifelse(.data$xDecompPerc >= 0, "Positive", "Negative")) ) - p2 <- suppressWarnings( - ggplot(plotWaterfallLoop, aes(x = .data$id, fill = .data$sign)) + - geom_rect(aes( - x = .data$rn, xmin = .data$id - 0.45, xmax = .data$id + 0.45, - ymin = .data$end, ymax = .data$start - ), stat = "identity") + - scale_x_discrete("", breaks = levels(plotWaterfallLoop$rn), labels = plotWaterfallLoop$rn) + - scale_y_percent() + - scale_fill_manual(values = c("Positive" = "#59B3D2", "Negative" = "#E5586E")) + - theme_lares(background = "white", legend = "top") + - geom_text(mapping = aes( - label = paste0( - formatNum(.data$xDecompAgg, abbr = TRUE), - "\n", round(.data$xDecompPerc * 100, 1), "%" - ), - y = rowSums(cbind(.data$end, .data$xDecompPerc / 2)) - ), fontface = "bold", lineheight = .7) + - coord_flip() + - labs( - title = "Response Decomposition Waterfall by Predictor", - x = NULL, y = NULL, fill = "Sign" - ) - ) + p2 <- ggplot(plotWaterfallLoop, aes(x = .data$rn, fill = .data$sign)) + + geom_rect(aes( + xmin = .data$id - 0.45, xmax = .data$id + 0.45, + ymin = .data$end, ymax = .data$start + ), stat = "identity") + + scale_x_discrete("", breaks = levels(plotWaterfallLoop$rn), labels = plotWaterfallLoop$rn) + + scale_y_percent() + + scale_fill_manual(values = c("Positive" = "#59B3D2", "Negative" = "#E5586E")) + + theme_lares(background = "white", legend = "top") + + geom_text(mapping = aes( + x = .data$id, + label = paste0( + formatNum(.data$xDecompAgg, abbr = TRUE), + "\n", round(.data$xDecompPerc * 100, 1), "%" + ), + y = rowSums(cbind(.data$end, .data$xDecompPerc / 2)) + ), fontface = "bold", lineheight = .7) + + coord_flip() + + labs( + title = "Response Decomposition Waterfall by Predictor", + x = NULL, y = NULL, fill = "Sign" + ) ## 3. Adstock rate if (InputCollect$adstock == "geometric") { @@ -463,7 +473,7 @@ robyn_onepagers <- function( geom_line(aes(color = .data$channel)) + facet_wrap(~ .data$channel) + geom_hline(yintercept = 0.5, linetype = "dashed", color = "gray") + - geom_text(aes(x = max(.data$x), y = 0.5, vjust = -0.5, hjust = 1, label = "Halflife"), colour = "gray") + + annotate("text", x = max(weibullCollect$x), y = 0.5, vjust = -0.5, hjust = 1, label = "Halflife", colour = "gray") + theme_lares(background = "white", legend = "none", grid = "Xx") + labs( title = paste("Weibull", wb_type, "Adstock: Flexible Rate Over Time"), @@ -477,10 +487,14 @@ robyn_onepagers <- function( trim_rate <- 1.3 # maybe enable as a parameter if (trim_rate > 0) { dt_scurvePlot <- dt_scurvePlot %>% + select(-"ds") %>% + bind_rows(data.frame( + channel = unique(dt_scurvePlot$channel), spend = 0, response = 0 + )) %>% filter( .data$spend < max(dt_scurvePlotMean$mean_spend_adstocked) * trim_rate, .data$response < max(dt_scurvePlotMean$mean_response) * trim_rate, - .data$channel %in% InputCollect$paid_media_spends + .data$channel %in% InputCollect$paid_media_vars ) %>% left_join( dt_scurvePlotMean[, c("channel", "mean_carryover")], "channel" @@ -524,7 +538,6 @@ robyn_onepagers <- function( ## 5. Fitted vs actual xDecompVecPlotMelted <- temp[[sid]]$plot5data$xDecompVecPlotMelted %>% mutate( - linetype = ifelse(.data$variable == "predicted", "solid", "dotted"), variable = stringr::str_to_title(.data$variable), ds = as.Date(.data$ds, origin = "1970-01-01") ) @@ -532,7 +545,7 @@ robyn_onepagers <- function( xDecompVecPlotMelted, aes(x = .data$ds, y = .data$value, color = .data$variable) ) + - geom_path(aes(linetype = .data$linetype), size = 0.6) + + geom_path(aes(linetype = .data$variable), size = 0.5) + theme_lares(background = "white", legend = "top", pal = 2) + scale_y_abbr() + guides(linetype = "none") + @@ -581,7 +594,8 @@ robyn_onepagers <- function( ## 7. Immediate vs carryover df_imme_caov <- temp[[sid]]$plot7data p7 <- df_imme_caov %>% - mutate(type = factor(.data$type, levels = c("Carryover", "Immediate"))) %>% + replace(is.na(.), 0) %>% + mutate(type = factor(.data$type, levels = c("Immediate", "Carryover"))) %>% ggplot(aes( x = .data$percentage, y = .data$rn, fill = reorder(.data$type, as.integer(.data$type)), label = paste0(round(.data$percentage * 100), "%") @@ -631,12 +645,14 @@ robyn_onepagers <- function( onepagerTitle <- sprintf("One-pager for Model ID: %s", sid) onepagerCaption <- sprintf("Robyn v%s [R-%s.%s]", ver, rver$major, rver$minor) calc <- ifelse(type == "ROAS", - "Total ROAS = sum of response / sum of spend", - "Total CPA = sum of spend / sum of response") + "Total ROAS = sum of response / sum of spend", + "Total CPA = sum of spend / sum of response" + ) calc <- paste(c(calc, perf), collapse = " = ") onepagerCaption <- paste0( "*", calc, " in modeling window ", paste0(window, collapse = ":"), - "\n", onepagerCaption) + "\n", onepagerCaption + ) get_height <- length(unique(plotMediaShareLoopLine$rn)) / 5 pg <- (p2 + p5) / (p1 + p8) / (p3 + p7) / (p4 + p6) + patchwork::plot_layout(heights = c(get_height, get_height, get_height, 1)) + @@ -670,7 +686,7 @@ robyn_onepagers <- function( } if (!quiet && count_mod_out > 1) close(pbplot) # Stop cluster to avoid memory leaks - if (check_parallel_plot()) stopImplicitCluster() + if (OutputCollect$cores > 1) stopImplicitCluster() return(invisible(parallelResult[[1]])) } @@ -699,7 +715,8 @@ allocation_plots <- function( formulax1 <- paste0( "Allocator's mean response = curve response of adstocked mean spend in date range, ", "while\n Model's sum of effect = sum of curve responses of all adstocked spends in modeling window\n", - formulax1) + formulax1 + ) formulax2 <- sprintf("When reallocating budget, m%s converges across media within respective bounds", metric) # Calculate errors for subtitles @@ -763,6 +780,7 @@ allocation_plots <- function( } } levs1 <- eval_list$levs1 + if (levs1[2] == levs1[3]) levs1[3] <- paste0(levs1[3], " ") if (scenario == "max_response") { levs2 <- c( "Initial", @@ -799,16 +817,22 @@ allocation_plots <- function( ) ) %>% group_by(.data$name) %>% - mutate(value_norm = if(metric == "ROAS") {.data$value} else { - .data$value / dplyr::first(.data$value)}) + mutate(value_norm = if (metric == "ROAS") { + .data$value + } else { + .data$value / dplyr::first(.data$value) + }) metric_vals <- if (metric == "ROAS") resp_metric$total_roi else resp_metric$total_cpa + resp_delta <- df_roi %>% group_by(.data$type) %>% + summarise(resp_delta = unique(.data$total_response_lift)) %>% + pull(resp_delta) labs <- paste( paste(levs2, "\n"), paste("Spend:", formatNum( 100 * (resp_metric$total_spend - resp_metric$total_spend[1]) / resp_metric$total_spend[1], signif = 3, pos = "%", sign = TRUE )), - unique(paste("Resp:", formatNum(100 * df_roi$total_response_lift, signif = 3, pos = "%", sign = TRUE))), + paste("Resp:", formatNum(100 * resp_delta, signif = 3, pos = "%", sign = TRUE)), paste(metric, ":", round(metric_vals, 2)), sep = "\n" ) @@ -821,8 +845,10 @@ allocation_plots <- function( geom_bar(stat = "identity", width = 0.6, alpha = 0.7) + geom_text(aes(label = formatNum(.data$value, signif = 3, abbr = TRUE)), color = "black", vjust = -.5) + theme_lares(background = "white", legend = "none") + - labs(title = paste0("Total Budget Optimization Result (scaled up to ", - unique(dt_optimOut$periods), ")"), fill = NULL, y = NULL, x = NULL) + + labs(title = paste0( + "Total Budget Optimization Result (scaled up to ", + unique(dt_optimOut$periods), ")" + ), fill = NULL, y = NULL, x = NULL) + scale_y_continuous(limits = c(0, max(df_roi$value_norm * 1.2))) + theme(axis.text.y = element_blank()) @@ -982,8 +1008,10 @@ allocation_plots <- function( facet_grid(. ~ .data$type_lab, scales = "free") + theme_lares(background = "white", legend = "none") + labs( - title = paste0("Budget Allocation per Paid Media Variable per ", - str_to_title(InputCollect$intervalType), "*"), + title = paste0( + "Budget Allocation per Paid Media Variable per ", + str_to_title(InputCollect$intervalType), "*" + ), fill = NULL, x = NULL, y = "Paid Media" ) @@ -1116,7 +1144,7 @@ allocation_plots <- function( plot = plots, limitsize = FALSE, dpi = 350, width = 12, height = 10 + 2 * ceiling(length(dt_optimOut$channels) / 3) ) - if(!quiet) message("Exporting to: ", filename) + if (!quiet) message("Exporting to: ", filename) } return(invisible(outputs)) @@ -1284,100 +1312,131 @@ refresh_plots <- function(InputCollectRF, OutputCollectRF, ReportCollect, export return(invisible(outputs)) } -refresh_plots_json <- function(OutputCollectRF, json_file, export = TRUE, ...) { +refresh_plots_json <- function(json_file, plot_folder = NULL, listInit = NULL, df = NULL, export = TRUE, ...) { outputs <- list() chainData <- robyn_chain(json_file) + message(">> Plotting refresh results for chain: ", paste(names(chainData), collapse = " > ")) solID <- tail(names(chainData), 1) dayInterval <- chainData[[solID]]$InputCollect$dayInterval intervalType <- chainData[[solID]]$InputCollect$intervalType rsq <- chainData[[solID]]$ExportedModel$errors$rsq_train - plot_folder <- OutputCollectRF$plot_folder + if (is.null(plot_folder)) { + plot_folder <- chainData[[1]]$ExportedModel$plot_folder + if (!dir.exists(plot_folder)) { + plot_folder <- getwd() + } + } ## 1. Fitted vs actual - temp <- OutputCollectRF$allPareto$plotDataCollect[[solID]] - xDecompVecPlotMelted <- temp$plot5data$xDecompVecPlotMelted %>% - mutate( - linetype = ifelse(.data$variable == "predicted", "solid", "dotted"), - variable = stringr::str_to_title(.data$variable), - ds = as.Date(.data$ds, origin = "1970-01-01") - ) - dt_refreshDates <- data.frame( - solID = names(chainData), - window_start = as.Date(unlist(lapply(chainData, function(x) x$InputCollect$window_start)), origin = "1970-01-01"), - window_end = as.Date(unlist(lapply(chainData, function(x) x$InputCollect$window_end)), origin = "1970-01-01"), - duration = unlist(c(0, unlist(lapply(chainData, function(x) x$InputCollect$refresh_steps)))) - ) %>% - filter(.data$duration > 0) %>% - mutate(refreshStatus = row_number()) %>% - mutate( - refreshStart = .data$window_end - dayInterval * .data$duration, - refreshEnd = .data$window_end + if (!is.null(df)) { + xDecompVecPlotMelted <- df$plot5data$xDecompVecPlotMelted %>% + mutate( + variable = stringr::str_to_title(.data$variable), + ds = as.Date(.data$ds, origin = "1970-01-01") + ) + dt_refreshDates <- dplyr::tibble( + solID = names(chainData), + window_start = as.Date(unlist(lapply(chainData, function(x) x$InputCollect$window_start)), origin = "1970-01-01"), + window_end = as.Date(unlist(lapply(chainData, function(x) x$InputCollect$window_end)), origin = "1970-01-01"), + duration = c(0, unlist(lapply(chainData, function(x) x$InputCollect$refresh_steps))) ) %>% - mutate(label = ifelse(.data$refreshStatus == 0, sprintf( - "Initial: %s, %s %ss", .data$refreshStart, .data$duration, intervalType - ), - sprintf( - "Refresh #%s: %s, %s %ss", .data$refreshStatus, .data$refreshStart, .data$duration, intervalType - ) - )) %>% - as_tibble() - outputs[["pFitRF"]] <- pFitRF <- ggplot(xDecompVecPlotMelted) + - geom_path(aes(x = .data$ds, y = .data$value, color = .data$variable, linetype = .data$linetype), size = 0.6) + - geom_rect( - data = dt_refreshDates, - aes( - xmin = .data$refreshStart, xmax = .data$refreshEnd, - fill = as.character(.data$refreshStatus) + mutate(days = .data$window_end - .data$window_start) %>% + filter(.data$duration > 0) %>% + mutate(refreshStatus = row_number()) %>% + mutate( + refreshStart = .data$window_end - .data$duration * dayInterval, + refreshEnd = .data$window_end + ) %>% + mutate(label = ifelse(.data$refreshStatus == 0, sprintf( + "Initial: %s, %s %ss", .data$refreshStart, .data$duration, intervalType ), - ymin = -Inf, ymax = Inf, alpha = 0.2 - ) + - scale_fill_brewer(palette = "BuGn") + - geom_text(data = dt_refreshDates, mapping = aes( - x = .data$refreshStart, y = max(xDecompVecPlotMelted$value), - label = .data$label, - angle = 270, hjust = 0, vjust = -0.2 - ), color = "gray40") + - theme_lares(background = "white", legend = "top", pal = 2) + - scale_y_abbr() + - guides(linetype = "none", fill = "none") + - labs( - title = "Actual vs. Predicted Response", - # subtitle = paste("Train R2 =", round(rsq, 4)), - x = "Date", y = "Response", color = NULL, fill = NULL - ) + sprintf( + "Refresh #%s: %s, %s %ss", .data$refreshStatus, .data$refreshStart, .data$duration, intervalType + ) + )) %>% + as_tibble() + outputs[["pFitRF"]] <- pFitRF <- ggplot(xDecompVecPlotMelted) + + geom_path(aes(x = .data$ds, y = .data$value, color = .data$variable, linetype = .data$variable), size = 0.5) + + geom_rect( + data = dt_refreshDates, + aes( + xmin = .data$refreshStart, xmax = .data$refreshEnd, + fill = as.character(.data$refreshStatus) + ), + ymin = -Inf, ymax = Inf, alpha = 0.2 + ) + + scale_fill_brewer(palette = "BuGn") + + geom_text(data = dt_refreshDates, mapping = aes( + x = .data$refreshStart, y = max(xDecompVecPlotMelted$value), + label = .data$label, + angle = 270, hjust = 0, vjust = -0.2 + ), color = "gray40") + + theme_lares(background = "white", legend = "top", pal = 2) + + scale_y_abbr() + + guides(linetype = "none", fill = "none") + + labs( + title = "Actual vs. Predicted Response", + # subtitle = paste("Train R2 =", round(rsq, 4)), + x = "Date", y = "Response", color = NULL, fill = NULL + ) - if (export) { - ggsave( - filename = paste0(plot_folder, "report_actual_fitted.png"), - plot = pFitRF, - dpi = 900, width = 12, height = 8, limitsize = FALSE - ) + if (export) { + ggsave( + filename = paste0(plot_folder, "report_actual_fitted.png"), + plot = pFitRF, + dpi = 900, width = 12, height = 8, limitsize = FALSE + ) + } } ## 2. Stacked bar plot + if (!is.null(listInit)) { + tt <- robyn_write( + listInit$InputCollect, listInit$OutputCollect, + dir = plot_folder, export = FALSE + ) + if (!tt$ExportedModel$select_model %in% names(chainData)) { + chainData[[tt$ExportedModel$select_model]] <- tt + } + } df <- lapply(chainData, function(x) x$ExportedModel$summary) %>% bind_rows(.id = "solID") %>% as_tibble() %>% select(-.data$coef) %>% mutate( - solID = factor(.data$solID, levels = names(chainData)), - label = factor( - sprintf("%s [%s]", .data$solID, as.integer(.data$solID) - 1), - levels = sprintf("%s [%s]", names(chainData), 0:(length(chainData) - 1)) + solID = factor(.data$solID, levels = attributes(chainData)$chain), + label = as.factor( + sprintf("%s [%s]", .data$solID, as.integer(.data$solID) - 1) ), + label = factor(.data$label, levels = unique(.data$label)), variable = ifelse(.data$variable %in% c(chainData[[1]]$InputCollect$prophet_vars, "(Intercept)"), "baseline", .data$variable ) ) %>% group_by(.data$solID, .data$label, .data$variable) %>% summarise_all(sum) + if (length(unique(df$solID)) != length(attributes(chainData)$chain)) { + cap <- "Not able to find local files of previous models to compare with" + } else { + cap <- NULL + } + maxval <- max(df$performance[!is.infinite(df$performance)], na.rm = TRUE) outputs[["pBarRF"]] <- pBarRF <- df %>% + group_by(.data$solID) %>% + mutate( + variable = factor(.data$variable, levels = rev(.data$variable)), + colsize = .data$decompPer * maxval / sum(.data$decompPer), + perfpoint = .data$performance / maxval + ) %>% + mutate(perfpoint = ifelse(is.infinite(.data$perfpoint), NA, .data$perfpoint)) %>% ggplot(aes(y = .data$variable)) + - geom_col(aes(x = .data$decompPer)) + + facet_wrap(. ~ .data$label, scales = "free") + + geom_vline(xintercept = 1, alpha = 0.8, linetype = "dashed", size = 0.5, colour = "#39638b") + + geom_col(aes(x = .data$colsize), na.rm = TRUE) + geom_text( aes( - x = .data$decompPer, + x = .data$colsize, label = formatNum(100 * .data$decompPer, signif = 2, pos = "%") ), na.rm = TRUE, hjust = -0.2, size = 2.8 @@ -1386,12 +1445,10 @@ refresh_plots_json <- function(OutputCollectRF, json_file, export = TRUE, ...) { geom_text( aes( x = .data$performance, - label = formatNum(.data$performance, 2) + label = round(.data$performance, 2), ), - na.rm = TRUE, hjust = -0.4, size = 2.8, colour = "#39638b" + na.rm = TRUE, hjust = -0.4, size = 2.8, colour = "#39638b", fontface = "bold" ) + - facet_wrap(. ~ .data$label, scales = "free") + - # scale_x_percent(limits = c(0, max(df$performance, na.rm = TRUE) * 1.2)) + labs( title = paste( "Model refresh: Decomposition & Paid Media", @@ -1401,17 +1458,15 @@ refresh_plots_json <- function(OutputCollectRF, json_file, export = TRUE, ...) { "Baseline includes intercept and all prophet vars:", v2t(chainData[[1]]$InputCollect$prophet_vars, quotes = FALSE) ), - x = NULL, y = NULL + x = NULL, y = NULL, caption = cap ) + theme_lares(background = "white", grid = "Y") + - theme(axis.text.x = element_blank(), axis.ticks.x = element_blank()) + theme(axis.text.x = element_blank(), axis.ticks.x = element_blank()) + + scale_x_abbr(limits = c(0, maxval * 1.1)) if (export) { ggsave( - filename = paste0( - chainData[[length(chainData)]]$ExportedModel$plot_folder, - "report_decomposition.png" - ), + filename = paste0(plot_folder, "report_decomposition.png"), plot = pBarRF, dpi = 900, width = 12, height = 8, limitsize = FALSE ) @@ -1509,8 +1564,9 @@ ts_validation <- function(OutputModels, quiet = FALSE, ...) { decomp_plot <- function( InputCollect, OutputCollect, solID = NULL, exclude = NULL, baseline_level = 0) { - if (is.null(solID) && length(OutputCollect$allSolutions) == 1) + if (is.null(solID) && length(OutputCollect$allSolutions) == 1) { solID <- OutputCollect$allSolutions + } check_opts(solID, OutputCollect$allSolutions) bvars <- baseline_vars(InputCollect, baseline_level) intType <- str_to_title(case_when( @@ -1520,6 +1576,7 @@ decomp_plot <- function( )) varType <- str_to_title(InputCollect$dep_var_type) pal <- names(lares::lares_pal()$palette) + df <- OutputCollect$xDecompVecCollect[OutputCollect$xDecompVecCollect$solID %in% solID, ] %>% select( "solID", "ds", "dep_var", any_of("intercept"), @@ -1528,22 +1585,73 @@ decomp_plot <- function( tidyr::gather("variable", "value", -.data$ds, -.data$solID, -.data$dep_var) %>% filter(!.data$variable %in% exclude) %>% mutate(variable = ifelse( - .data$variable %in% bvars, paste0("Baseline_L", baseline_level), as.character(.data$variable))) %>% + .data$variable %in% bvars, paste0("Baseline_L", baseline_level), as.character(.data$variable) + )) + + # Sort variables by baseline first & amount of absolute impact + levs <- df %>% + group_by(.data$variable) %>% + summarise(impact = sum(abs(.data$value))) %>% + mutate(is_baseline = grepl("Baseline_L", .data$variable)) %>% + arrange(desc(.data$is_baseline), desc(.data$impact)) %>% + filter(.data$impact > 0) %>% + pull(.data$variable) + df <- df %>% group_by(.data$solID, .data$ds, .data$variable) %>% - summarise(value = sum(.data$value, na.rm = TRUE), - value = sum(.data$value, na.rm = TRUE), - .groups = "drop") %>% - arrange(abs(.data$value)) %>% - mutate(variable = factor(.data$variable, levels = unique(.data$variable))) - p <- ggplot(df, aes(x = .data$ds, y = .data$value, fill = .data$variable)) + + summarise( + value = sum(.data$value, na.rm = TRUE), + value = sum(.data$value, na.rm = TRUE), + .groups = "drop" + ) %>% + filter(.data$variable %in% levs) %>% + mutate(variable = factor(.data$variable, levels = rev(levs))) + + p <- ggplot(df, aes(x = as.character(.data$ds), y = .data$value, fill = .data$variable)) + facet_grid(.data$solID ~ .) + labs( title = paste(varType, "Decomposition by Variable"), x = NULL, y = paste(intType, varType), fill = NULL ) + - geom_area() + + geom_col(width = 1) + theme_lares(background = "white", legend = "right") + + geom_hline(yintercept = 0) + scale_fill_manual(values = rev(pal[seq(length(unique(df$variable)))])) + - scale_y_abbr() + scale_y_abbr() + + # Must create custom splits because dates is character to be able to be bars + scale_x_discrete( + breaks = get_evenly_separated_dates(df$ds, n = 6), + labels = function(x) format(as.Date(x), "%m/%y") + ) return(p) } + +# Custom plot for geom_density interval +geom_density_ci <- function( + gg_density, # ggplot object that contains geom_density + ci_low, + ci_up, + fill = "grey" +) { + build_object <- ggplot_build(gg_density) + x_dens <- build_object$data[[1]]$x + y_dens <- build_object$data[[1]]$y + ind_low <- min(which(x_dens >= ci_low)) + ind_up <- max(which(x_dens <= ci_up)) + + gg_density <- gg_density + + geom_area( + data=data.frame( + x=x_dens[ind_low:ind_up], + density=y_dens[ind_low:ind_up]), + aes(x=.data$x,y=.data$density), + fill=fill, + alpha=0.6) + return(gg_density) + } + +get_evenly_separated_dates <- function(dates, n = 6) { + dates <- sort(dates) + indices <- round(seq(1, length(dates), length.out = n)) + selected_dates <- dates[indices] + return(as.character(selected_dates)) +} diff --git a/R/R/refresh.R b/R/R/refresh.R index 7b7b93afe..7dac35464 100644 --- a/R/R/refresh.R +++ b/R/R/refresh.R @@ -57,6 +57,10 @@ #' still needs to be investigated. #' @param refresh_trials Integer. Trials per refresh. Defaults to 5 trials. #' More reliable recommendation still needs to be investigated. +#' @param bounds_freedom Numeric. Percentage of freedom we'd like to allow for the +#' new hyperparameters values compared with the model to be refreshed. +#' If set to NULL (default) the value will be calculated as +#' refresh_steps / rollingWindowLength. Applies to all hyperparameters. #' @param version_prompt Logical. If FALSE, the model refresh version will be #' selected based on the smallest combined error of normalized NRMSE, DECOMP.RSSD, MAPE. #' If \code{TRUE}, a prompt will be presented to the user to select one of the refreshed @@ -105,6 +109,7 @@ robyn_refresh <- function(json_file = NULL, refresh_mode = "manual", refresh_iters = 1000, refresh_trials = 3, + bounds_freedom = NULL, plot_folder = NULL, plot_pareto = TRUE, version_prompt = FALSE, @@ -123,9 +128,19 @@ robyn_refresh <- function(json_file = NULL, Robyn <- list() json <- robyn_read(json_file, step = 2, quiet = TRUE) if (is.null(plot_folder)) plot_folder <- json$ExportedModel$plot_folder + if (!dir.exists(plot_folder) & export) { + message(sprintf( + paste0( + "NOTE: Directory from JSON file doesn't exist: %s\n", + ">> Using current working directory for outputs: %s" + ), + plot_folder, getwd() + )) + plot_folder <- getwd() + } listInit <- suppressWarnings(robyn_recreate( json_file = json_file, - dt_input = dt_input, + dt_input = if (!is.null(dt_input)) dt_input else json$Extras[["raw_data"]], dt_holidays = dt_holidays, plot_folder = plot_folder, quiet = FALSE, ... @@ -135,6 +150,7 @@ robyn_refresh <- function(json_file = NULL, listInit$InputCollect$refreshChain <- attr(chainData, "chain") listInit$InputCollect$refreshDepth <- refreshDepth <- length(attr(chainData, "chain")) listInit$OutputCollect$hyper_updated <- json$ExportedModel$hyper_updated + listInit$InputCollect$window_end <- json$InputCollect$window_end Robyn[["listInit"]] <- listInit refreshCounter <- 1 # Dummy for now (legacy) } @@ -162,6 +178,7 @@ robyn_refresh <- function(json_file = NULL, } ## Check rule of thumb: 50% of data shouldn't be new + dt_input <- Robyn$listInit$InputCollect$dt_input check_refresh_data(Robyn, dt_input) ## Get previous data @@ -259,16 +276,25 @@ robyn_refresh <- function(json_file = NULL, window_start = InputCollectRF$window_start, window_end = InputCollectRF$window_end, paid_media_spends = InputCollectRF$paid_media_spends, - organic_vars = InputCollectRF$organic_vars + organic_vars = InputCollectRF$organic_vars, + paid_media_selected = InputCollectRF$paid_media_selected ) InputCollectRF$calibration_input <- calibration_input } ## Refresh hyperparameter bounds + ts_validation <- ifelse( + "ts_validation" %in% names(list(...)), + isTRUE(list(...)[["ts_validation"]]), + isTRUE(Robyn$listInit$OutputCollect$OutputModels$ts_validation) + ) InputCollectRF$hyperparameters <- refresh_hyps( initBounds = Robyn$listInit$OutputCollect$hyper_updated, - listOutputPrev, refresh_steps, - rollingWindowLength = InputCollectRF$rollingWindowLength + listOutputPrev, + refresh_steps = refresh_steps, + rollingWindowLength = InputCollectRF$rollingWindowLength, + ts_validation = ts_validation, + bounds_freedom = bounds_freedom ) ## Feature engineering for refreshed data @@ -289,10 +315,12 @@ robyn_refresh <- function(json_file = NULL, trials = refresh_trials, refresh = TRUE, add_penalty_factor = listOutputPrev[["add_penalty_factor"]], + ts_validation = ts_validation, ... ) OutputCollectRF <- robyn_outputs( InputCollectRF, OutputModelsRF, + select_model = "refreshed", plot_folder = plot_folder, calibration_constraint = rf_cal_constr, export = export, @@ -328,8 +356,11 @@ robyn_refresh <- function(json_file = NULL, selectID <- bestMod message( "Selected model ID: ", selectID, " for refresh model #", - depth, " based on the smallest decomp.rssd" + depth, " based on the smallest DECOMP.RSSD error" ) + if (export) { + robyn_write(InputCollectRF, OutputCollectRF, select_model = selectID, ...) + } } if (!isTRUE(selectID %in% OutputCollectRF$allSolutions)) { version_prompt <- TRUE @@ -453,10 +484,12 @@ robyn_refresh <- function(json_file = NULL, select_model = selectID, export = TRUE, quiet = TRUE, ... ) - plots <- refresh_plots_json( - OutputCollectRF, - json_file = attr(json_temp, "json_file"), export, ... - ) + df <- OutputCollectRF$allPareto$plotDataCollect[[selectID]] + plots <- try(refresh_plots_json( + json_file = attr(json_temp, "json_file"), + plot_folder = OutputCollectRF$plot_folder, + df = df, listInit = listInit, export = export, ... + )) } else { plots <- try(refresh_plots( InputCollectRF, OutputCollectRF, ReportCollect, export, ... @@ -464,11 +497,12 @@ robyn_refresh <- function(json_file = NULL, } if (export) { - message(paste(">>> Exporting refresh CSVs into directory...")) - write.csv(resultHypParamReport, paste0(plot_folder, "report_hyperparameters.csv")) - write.csv(xDecompAggReport, paste0(plot_folder, "report_aggregated.csv")) - write.csv(mediaVecReport, paste0(plot_folder, "report_media_transform_matrix.csv")) - write.csv(xDecompVecReport, paste0(plot_folder, "report_alldecomp_matrix.csv")) + csv_folder <- OutputCollectRF$plot_folder + message(paste(">>> Exporting refresh CSVs into directory:", csv_folder)) + write.csv(resultHypParamReport, paste0(csv_folder, "report_hyperparameters.csv")) + write.csv(xDecompAggReport, paste0(csv_folder, "report_aggregated.csv")) + write.csv(mediaVecReport, paste0(csv_folder, "report_media_transform_matrix.csv")) + write.csv(xDecompVecReport, paste0(csv_folder, "report_alldecomp_matrix.csv")) } if (refreshLooper == 0) { @@ -493,9 +527,8 @@ robyn_refresh <- function(json_file = NULL, if (is.null(json_file)) { message(">> Exporting results: ", robyn_object) saveRDS(Robyn, file = robyn_object) - } else { - robyn_write(InputCollectRF, OutputCollectRF, select_model = selectID, ...) } + return(invisible(Robyn)) } @@ -526,12 +559,17 @@ Models (IDs): #' @export plot.robyn_refresh <- function(x, ...) plot((x$refresh$plots[[1]] / x$refresh$plots[[2]]), ...) -refresh_hyps <- function(initBounds, listOutputPrev, refresh_steps, rollingWindowLength) { +refresh_hyps <- function(initBounds, listOutputPrev, refresh_steps, rollingWindowLength, + ts_validation = FALSE, bounds_freedom = NULL) { initBoundsDis <- unlist(lapply(initBounds, function(x) ifelse(length(x) == 2, x[2] - x[1], 0))) - newBoundsFreedom <- refresh_steps / rollingWindowLength + if (is.null(bounds_freedom)) { + newBoundsFreedom <- refresh_steps / rollingWindowLength + } else { + newBoundsFreedom <- abs(bounds_freedom) + } message(">>> New bounds freedom: ", round(100 * newBoundsFreedom, 2), "%") - hyper_updated_prev <- listOutputPrev$hyper_updated - hypNames <- names(hyper_updated_prev) + hyper_updated_prev <- initBounds + hypNames <- names(initBounds) resultHypParam <- as_tibble(listOutputPrev$resultHypParam) for (h in seq_along(hypNames)) { hn <- hypNames[h] @@ -553,10 +591,15 @@ refresh_hyps <- function(initBounds, listOutputPrev, refresh_steps, rollingWindo newUpB <- getRange[2] } newBounds <- unname(c(newLowB, newUpB)) - hyper_updated_prev[hn][[1]] <- newBounds + hyper_updated_prev[[hn]] <- newBounds } else { - hyper_updated_prev[hn][[1]] <- getRange + fixed <- hyper_updated_prev[hn][[1]] + hyper_updated_prev[[hn]] <- c( + fixed * (1 - newBoundsFreedom), + fixed * (1 + newBoundsFreedom) + ) } } + if (!ts_validation) hyper_updated_prev[["train_size"]] <- NULL return(hyper_updated_prev) } diff --git a/R/R/response.R b/R/R/response.R index 7334a7ba0..bf22fea21 100644 --- a/R/R/response.R +++ b/R/R/response.R @@ -14,10 +14,10 @@ #' @param metric_name A character. Selected media variable for the response. #' Must be one value from paid_media_spends, paid_media_vars or organic_vars #' @param metric_value Numeric. Desired metric value to return a response for. -#' @param dt_hyppar A data.frame. When \code{robyn_object} is not provided, use +#' @param dt_hyppar A data.frame. When \code{json_file} is not provided, use #' \code{dt_hyppar = OutputCollect$resultHypParam}. It must be provided along #' \code{select_model}, \code{dt_coef} and \code{InputCollect}. -#' @param dt_coef A data.frame. When \code{robyn_object} is not provided, use +#' @param dt_coef A data.frame. When \code{json_file} is not provided, use #' \code{dt_coef = OutputCollect$xDecompAgg}. It must be provided along #' \code{select_model}, \code{dt_hyppar} and \code{InputCollect}. #' @examples @@ -106,7 +106,6 @@ robyn_response <- function(InputCollect = NULL, OutputCollect = NULL, json_file = NULL, - robyn_object = NULL, select_build = NULL, select_model = NULL, metric_name = NULL, @@ -133,40 +132,12 @@ robyn_response <- function(InputCollect = NULL, if (is.null(dt_hyppar)) dt_hyppar <- OutputCollect$resultHypParam if (is.null(dt_coef)) dt_coef <- OutputCollect$xDecompAgg } else { - if (!is.null(robyn_object)) { - if (!file.exists(robyn_object)) { - stop("File does not exist or is somewhere else. Check: ", robyn_object) - } else { - Robyn <- readRDS(robyn_object) - objectPath <- dirname(robyn_object) - objectName <- sub("'\\..*$", "", basename(robyn_object)) - } - select_build_all <- 0:(length(Robyn) - 1) - if (is.null(select_build)) { - select_build <- max(select_build_all) - if (!quiet && length(select_build_all) > 1) { - message( - "Using latest model: ", ifelse(select_build == 0, "initial model", paste0("refresh model #", select_build)), - " for the response function. Use parameter 'select_build' to specify which run to use" - ) - } - } - if (!(select_build %in% select_build_all) || length(select_build) != 1) { - stop("'select_build' must be one value of ", paste(select_build_all, collapse = ", ")) - } - listName <- ifelse(select_build == 0, "listInit", paste0("listRefresh", select_build)) - InputCollect <- Robyn[[listName]][["InputCollect"]] - OutputCollect <- Robyn[[listName]][["OutputCollect"]] - dt_hyppar <- OutputCollect$resultHypParam - dt_coef <- OutputCollect$xDecompAgg - } else { - # Try to get some pre-filled values + # Get pre-filled values if (is.null(dt_hyppar)) dt_hyppar <- OutputCollect$resultHypParam if (is.null(dt_coef)) dt_coef <- OutputCollect$xDecompAgg if (any(is.null(dt_hyppar), is.null(dt_coef), is.null(InputCollect), is.null(OutputCollect))) { - stop("When 'robyn_object' is not provided, 'InputCollect' & 'OutputCollect' must be provided") + stop("When 'json_file' is not provided, 'InputCollect' & 'OutputCollect' must be provided") } - } } if ("selectID" %in% names(OutputCollect)) { @@ -176,12 +147,15 @@ robyn_response <- function(InputCollect = NULL, ## Prep environment if (TRUE) { dt_input <- InputCollect$dt_input - startRW <- InputCollect$rollingWindowStartWhich - endRW <- InputCollect$rollingWindowEndWhich + dt_mod <- InputCollect$dt_mod + window_start_loc <- InputCollect$rollingWindowStartWhich + window_end_loc <- InputCollect$rollingWindowEndWhich + window_loc <- window_start_loc:window_end_loc adstock <- InputCollect$adstock - spendExpoMod <- InputCollect$modNLS$results + # spendExpoMod <- InputCollect$ExposureCollect$df_cpe paid_media_vars <- InputCollect$paid_media_vars paid_media_spends <- InputCollect$paid_media_spends + paid_media_selected <- InputCollect$paid_media_selected exposure_vars <- InputCollect$exposure_vars organic_vars <- InputCollect$organic_vars allSolutions <- unique(dt_hyppar$solID) @@ -198,139 +172,91 @@ robyn_response <- function(InputCollect = NULL, ## Get use case based on inputs usecase <- which_usecase(metric_value, date_range) - ## Check inputs with usecases - metric_type <- check_metric_type(metric_name, paid_media_spends, paid_media_vars, exposure_vars, organic_vars) - all_dates <- pull(dt_input, InputCollect$date_var) - all_values <- pull(dt_input, metric_name) - - if (usecase == "all_historical_vec") { - ds_list <- check_metric_dates(date_range = "all", all_dates[1:endRW], dayInterval, quiet, ...) - metric_value <- NULL - # val_list <- check_metric_value(metric_value, metric_name, all_values, ds_list$metric_loc) - } else if (usecase == "unit_metric_default_last_n") { - ds_list <- check_metric_dates(date_range = paste0("last_", length(metric_value)), all_dates[1:endRW], dayInterval, quiet, ...) - # val_list <- check_metric_value(metric_value, metric_name, all_values, ds_list$metric_loc) - } else { - ds_list <- check_metric_dates(date_range, all_dates[1:endRW], dayInterval, quiet, ...) + ## Check inputs + metric_type <- check_metric_type(metric_name, paid_media_spends, paid_media_vars, paid_media_selected, exposure_vars, organic_vars) + metric_name_updated <- metric_type$metric_name_updated + all_dates <- dt_input[[InputCollect$date_var]] + all_values <- dt_mod[[metric_name_updated]] + ds_list <- check_metric_dates(date_range = date_range, all_dates[1:window_end_loc], dayInterval, quiet, ...) + val_list <- check_metric_value(metric_value, metric_name_updated, all_values, ds_list$metric_loc) + if (!is.null(metric_value) & is.null(date_range)) { + stop("Must specify date_range when using metric_value") } - val_list <- check_metric_value(metric_value, metric_name, all_values, ds_list$metric_loc) date_range_updated <- ds_list$date_range_updated - metric_value_updated <- val_list$metric_value_updated all_values_updated <- val_list$all_values_updated - ## Transform exposure to spend when necessary - if (metric_type == "exposure") { - get_spend_name <- paid_media_spends[which(paid_media_vars == metric_name)] - # expo_vec <- dt_input[, metric_name][[1]] - # Use non-0 mean as marginal level if metric_value not provided - # if (is.null(metric_value)) { - # metric_value <- mean(expo_vec[startRW:endRW][expo_vec[startRW:endRW] > 0]) - # if (!quiet) message("Input 'metric_value' not provided. Using mean of ", metric_name, " instead") - # } - # Fit spend to exposure - # spend_vec <- dt_input[, get_spend_name][[1]] - if (is.null(spendExpoMod)) { - stop("Can't calculate exposure to spend response. Please, recreate your InputCollect object") - } - temp <- filter(spendExpoMod, .data$channel == metric_name) - nls_select <- temp$rsq_nls > temp$rsq_lm - if (nls_select) { - Vmax <- spendExpoMod$Vmax[spendExpoMod$channel == metric_name] - Km <- spendExpoMod$Km[spendExpoMod$channel == metric_name] - input_immediate <- mic_men(x = metric_value_updated, Vmax = Vmax, Km = Km, reverse = TRUE) - } else { - coef_lm <- spendExpoMod$coef_lm[spendExpoMod$channel == metric_name] - input_immediate <- metric_value_updated / coef_lm - } - all_values_updated[ds_list$metric_loc] <- input_immediate - hpm_name <- get_spend_name - } else { - # use non-0 means marginal level if spend not provided - # if (is.null(metric_value)) { - # metric_value <- mean(media_vec[startRW:endRW][media_vec[startRW:endRW] > 0]) - # if (!quiet) message("Input 'metric_value' not provided. Using mean of ", metric_name, " instead") - # } - input_immediate <- metric_value_updated - hpm_name <- metric_name - } - - ## Adstocking original - media_vec_origin <- dt_input[, metric_name][[1]] + ## Get hyperparameters & beta coef theta <- scale <- shape <- NULL if (adstock == "geometric") { - theta <- dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(hpm_name, "_thetas")]][[1]] + theta <- dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(metric_name_updated, "_thetas")]][[1]] } if (grepl("weibull", adstock)) { - shape <- dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(hpm_name, "_shapes")]][[1]] - scale <- dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(hpm_name, "_scales")]][[1]] + shape <- dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(metric_name_updated, "_shapes")]][[1]] + scale <- dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(metric_name_updated, "_scales")]][[1]] } - x_list <- transform_adstock(media_vec_origin, adstock, theta = theta, shape = shape, scale = scale) - m_adstocked <- x_list$x_decayed - # net_carryover_ref <- m_adstocked - media_vec_origin - - ## Adstocking simulation - x_list_sim <- transform_adstock(all_values_updated, adstock, theta = theta, shape = shape, scale = scale) - media_vec_sim <- x_list_sim$x_decayed - media_vec_sim_imme <- if (adstock == "weibull_pdf") x_list_sim$x_imme else x_list_sim$x - input_total <- media_vec_sim[ds_list$metric_loc] - input_immediate <- media_vec_sim_imme[ds_list$metric_loc] - input_carryover <- input_total - input_immediate + alpha <- head(dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(metric_name_updated, "_alphas")]], 1) + gamma <- head(dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(metric_name_updated, "_gammas")]], 1) + coeff <- dt_coef[dt_coef$solID == select_model & dt_coef$rn == metric_name_updated, ][["coef"]] - ## Saturation - m_adstockedRW <- m_adstocked[startRW:endRW] - alpha <- head(dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(hpm_name, "_alphas")]], 1) - gamma <- head(dt_hyppar[dt_hyppar$solID == select_model, ][[paste0(hpm_name, "_gammas")]], 1) - if (usecase == "all_historical_vec") { - metric_saturated_total <- saturation_hill(x = m_adstockedRW, alpha = alpha, gamma = gamma) - metric_saturated_carryover <- saturation_hill(x = m_adstockedRW, alpha = alpha, gamma = gamma) - } else { - metric_saturated_total <- saturation_hill(x = m_adstockedRW, alpha = alpha, gamma = gamma, x_marginal = input_total) - metric_saturated_carryover <- saturation_hill(x = m_adstockedRW, alpha = alpha, gamma = gamma, x_marginal = input_carryover) + ## Historical transformation + hist_transform <- transform_decomp( + all_values = all_values, + adstock, theta, shape, scale, alpha, gamma, + window_loc, coeff, metric_loc = ds_list$metric_loc) + dt_line <- data.frame( + metric = hist_transform$input_total[window_loc], + response = hist_transform$response_total, + channel = metric_name_updated) + dt_point <- data.frame( + mean_input_immediate = hist_transform$mean_input_immediate, + mean_input_carryover = hist_transform$mean_input_carryover, + mean_input_total = hist_transform$mean_input_immediate + hist_transform$mean_input_carryover, + mean_response_immediate = hist_transform$mean_response_total - hist_transform$mean_response_carryover, + mean_response_carryover = hist_transform$mean_response_carryover, + mean_response_total = hist_transform$mean_response_total + ) + if (!is.null(date_range)) { + dt_point_sim <- data.frame( + input = hist_transform$sim_mean_spend + hist_transform$sim_mean_carryover, + output = hist_transform$sim_mean_response) } - metric_saturated_immediate <- metric_saturated_total - metric_saturated_carryover - ## Decomp - coeff <- dt_coef[dt_coef$solID == select_model & dt_coef$rn == hpm_name, ][["coef"]] - m_saturated <- saturation_hill(x = m_adstockedRW, alpha = alpha, gamma = gamma) - m_resposne <- m_saturated * coeff - response_total <- as.numeric(metric_saturated_total * coeff) - response_carryover <- as.numeric(metric_saturated_carryover * coeff) - response_immediate <- response_total - response_carryover - - dt_line <- data.frame(metric = m_adstockedRW, response = m_resposne, channel = metric_name) - if (usecase == "all_historical_vec") { - dt_point <- data.frame(input = input_total[startRW:endRW], output = response_total, ds = date_range_updated[startRW:endRW]) - dt_point_caov <- data.frame(input = input_carryover[startRW:endRW], output = response_carryover) - dt_point_imme <- data.frame(input = input_immediate[startRW:endRW], output = response_immediate) - } else { - dt_point <- data.frame(input = input_total, output = response_total, ds = date_range_updated) - dt_point_caov <- data.frame(input = input_carryover, output = response_carryover) - dt_point_imme <- data.frame(input = input_immediate, output = response_immediate) + ## Simulated transformation + if (!is.null(metric_value)) { + hist_transform_sim <- transform_decomp( + all_values = all_values_updated, + adstock, theta, shape, scale, alpha, gamma, + window_loc, coeff, metric_loc = ds_list$metric_loc, + calibrate_inflexion = hist_transform$inflexion) + dt_point_sim <- data.frame( + input = hist_transform_sim$sim_mean_spend + hist_transform_sim$sim_mean_carryover, + output = hist_transform_sim$sim_mean_response) } ## Plot optimal response p_res <- ggplot(dt_line, aes(x = .data$metric, y = .data$response)) + geom_line(color = "steelblue") + - geom_point(data = dt_point, aes(x = .data$input, y = .data$output), size = 3) + + geom_point( + data = dt_point, + aes(x = .data$mean_input_total, y = .data$mean_response_total), + size = 3, color = "grey") + labs( title = paste( - "Saturation curve of", - ifelse(metric_type == "organic", "organic", "paid"), - "media:", metric_name, - ifelse(!is.null(date_range_updated), "adstocked", ""), - ifelse(metric_type == "spend", "spend metric", "exposure metric") + "Saturation curve of", metric_type$metric_type, + "media:", metric_type$metric_name_updated + ), + subtitle = sprintf(paste( + "Response: %s @ mean input %s", + "Response: %s @ mean input carryover %s", + "Response: %s @ mean input immediate %s", + sep = "\n"), + num_abbr(dt_point$mean_response_total), + num_abbr(dt_point$mean_input_total), + num_abbr(dt_point$mean_response_carryover), + num_abbr(dt_point$mean_input_carryover), + num_abbr(dt_point$mean_response_immediate), + num_abbr(dt_point$mean_input_immediate) ), - subtitle = ifelse(length(unique(input_total)) == 1, sprintf( - paste( - "Carryover* Response: %s @ Input %s", - "Immediate Response: %s @ Input %s", - "Total (C+I) Response: %s @ Input %s", - sep = "\n" - ), - num_abbr(dt_point_caov$output), num_abbr(dt_point_caov$input), - num_abbr(dt_point_imme$output), num_abbr(dt_point_imme$input), - num_abbr(dt_point$output), num_abbr(dt_point$input) - ), ""), x = "Input", y = "Response", caption = sprintf( "Response period: %s%s%s", @@ -342,20 +268,35 @@ robyn_response <- function(InputCollect = NULL, theme_lares(background = "white") + scale_x_abbr() + scale_y_abbr() - if (length(unique(metric_value)) == 1) { + if (!is.null(metric_value) | !is.null(date_range)) { p_res <- p_res + - geom_point(data = dt_point_caov, aes(x = .data$input, y = .data$output), size = 3, shape = 8) + geom_point(data = dt_point_sim, aes(x = .data$input, y = .data$output), size = 3, color = "blue") + } + if (!is.null(metric_value)) { + sim_mean_spend <- hist_transform_sim$sim_mean_spend + sim_mean_carryover <- hist_transform_sim$sim_mean_carryover + sim_mean_response <- hist_transform_sim$sim_mean_response + } else { + sim_mean_spend <- sim_mean_carryover <- sim_mean_response <- NULL } ret <- list( - metric_name = metric_name, + metric_name = metric_name_updated, date = date_range_updated, - input_total = input_total, - input_carryover = input_carryover, - input_immediate = input_immediate, - response_total = response_total, - response_carryover = response_carryover, - response_immediate = response_immediate, + input_total = hist_transform$input_total, + input_carryover = hist_transform$input_carryover, + input_immediate = hist_transform$input_immediate, + response_total = hist_transform$response_total, + response_carryover = hist_transform$response_carryover, + response_immediate = hist_transform$response_immediate, + inflexion = hist_transform$inflexion, + mean_input_immediate = hist_transform$mean_input_immediate, + mean_input_carryover = hist_transform$mean_input_carryover, + mean_response_total = hist_transform$mean_response_total, + mean_response_carryover = hist_transform$mean_response_carryover, + sim_mean_spend = sim_mean_spend, + sim_mean_carryover = sim_mean_carryover, + sim_mean_response = sim_mean_response, usecase = usecase, plot = p_res ) @@ -385,6 +326,79 @@ which_usecase <- function(metric_value, date_range) { return(usecase) } +transform_decomp <- function(all_values, adstock, theta, shape, scale, alpha, gamma, + window_loc, coeff, metric_loc, calibrate_inflexion = NULL) { + ## adstock + x_list <- transform_adstock(x = all_values, adstock, theta, shape, scale) + input_total <- x_list$x_decayed + input_immediate <- if (adstock == "weibull_pdf") x_list$x_imme else x_list$x + input_carryover <- input_total - input_immediate + input_total_rw <- input_total[window_loc] + input_carryover_rw <- input_carryover[window_loc] + ## saturation + saturated_total <- saturation_hill( + x = input_total_rw, + alpha = alpha, gamma = gamma + ) + saturated_carryover <- saturation_hill( + x = input_total_rw, + alpha = alpha, gamma = gamma, x_marginal = input_carryover_rw + ) + saturated_immediate <- saturated_total$x_saturated - saturated_carryover$x_saturated + ## simulate mean response of all_values periods + mean_input_immediate <- mean(input_immediate[window_loc]) + mean_input_carryover <- mean(input_carryover_rw) + mean_response_total <- fx_objective( + x = mean_input_immediate, + coeff = coeff, + alpha = alpha, + inflexion = saturated_total$inflexion, + x_hist_carryover = mean_input_carryover, + get_sum = FALSE + ) + mean_response_carryover <- fx_objective( + x = 0, + coeff = coeff, + alpha = alpha, + inflexion = saturated_total$inflexion, + x_hist_carryover = mean_input_carryover, + get_sum = FALSE + ) + ## simulate mean response of date_range periods + sim_mean_spend <- mean(input_immediate[metric_loc]) + sim_mean_carryover <- mean(input_carryover[metric_loc]) + if (is.null(calibrate_inflexion)) calibrate_inflexion <- saturated_total$inflexion + sim_mean_response <- fx_objective( + x = sim_mean_spend, + coeff = coeff, + alpha = alpha, + # use historical true inflexion when metric_value is provided + inflexion = calibrate_inflexion, + x_hist_carryover = sim_mean_carryover, + get_sum = FALSE + ) + + ret <- list( + input_total = input_total, + input_immediate = input_immediate, + input_carryover = input_carryover, + saturated_total = saturated_total$x_saturated, + saturated_carryover = saturated_carryover$x_saturated, + saturated_immediate = saturated_immediate, + response_total = saturated_total$x_saturated * coeff, + response_carryover = saturated_carryover$x_saturated * coeff, + response_immediate = saturated_immediate * coeff, + inflexion = saturated_total$inflexion, + mean_input_immediate = mean_input_immediate, + mean_input_carryover = mean_input_carryover, + mean_response_total = mean_response_total, + mean_response_carryover = mean_response_carryover, + sim_mean_spend = sim_mean_spend, + sim_mean_carryover = sim_mean_carryover, + sim_mean_response = sim_mean_response + ) + return(ret) +} # ####### SCENARIOS CHECK FOR date_range # metric_value <- 71427 # all_dates <- dt_input$DATE diff --git a/R/R/transformation.R b/R/R/transformation.R index f983a0b9a..d7ffbf3f3 100644 --- a/R/R/transformation.R +++ b/R/R/transformation.R @@ -14,6 +14,7 @@ #' impressions, clicks or GRPs are provided in \code{paid_media_vars} instead #' of spend metric. #' +#' @name transformations #' @family Transformations #' @param x Numeric value or vector. Input media spend when #' \code{reverse = FALSE}. Input media exposure metrics (impression, clicks, @@ -118,30 +119,26 @@ adstock_geometric <- function(x, theta) { #' peak value occurring after the first period when shape >=1, allowing lagged #' effect. #' @examples -#' adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "CDF") -#' adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "PDF") +#' adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "cdf") +#' adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "pdf") #' -#' # Wrapped function for either adstock -#' transform_adstock(rep(100, 10), "weibull_pdf", shape = 1, scale = 0.5) #' @rdname adstocks #' @export -adstock_weibull <- function(x, shape, scale, windlen = length(x), type = "cdf") { - stopifnot(length(shape) == 1) - stopifnot(length(scale) == 1) +adstock_weibull <- function(x, shape, scale, windlen = length(x), type = "pdf") { if (length(x) > 1) { - check_opts(tolower(type), c("cdf", "pdf")) + # check_opts(tolower(type), c("cdf", "pdf")) x_bin <- 1:windlen scaleTrans <- round(quantile(1:windlen, scale), 0) if (shape == 0 | scale == 0) { x_decayed <- x thetaVecCum <- thetaVec <- rep(0, windlen) - x_imme <- NULL + x_imme <- x } else { - if ("cdf" %in% tolower(type)) { + if ("pdf" %in% type) { + thetaVecCum <- .normalize(dweibull(x_bin, shape = shape, scale = scaleTrans)) # plot(thetaVecCum) + } else if ("cdf" %in% type) { thetaVec <- c(1, 1 - pweibull(head(x_bin, -1), shape = shape, scale = scaleTrans)) # plot(thetaVec) thetaVecCum <- cumprod(thetaVec) # plot(thetaVecCum) - } else if ("pdf" %in% tolower(type)) { - thetaVecCum <- .normalize(dweibull(x_bin, shape = shape, scale = scaleTrans)) # plot(thetaVecCum) } x_decayed <- mapply(function(x_val, x_pos) { x.vec <- c(rep(0, x_pos - 1), rep(x_val, windlen - x_pos + 1)) @@ -170,13 +167,12 @@ adstock_weibull <- function(x, shape, scale, windlen = length(x), type = "cdf") #' @param adstock Character. One of: "geometric", "weibull_cdf", "weibull_pdf". #' @export transform_adstock <- function(x, adstock, theta = NULL, shape = NULL, scale = NULL, windlen = length(x)) { - check_adstock(adstock) + # check_adstock(adstock) if (adstock == "geometric") { x_list_sim <- adstock_geometric(x = x, theta = theta) - } else if (adstock == "weibull_cdf") { - x_list_sim <- adstock_weibull(x = x, shape = shape, scale = scale, windlen = windlen, type = "cdf") - } else if (adstock == "weibull_pdf") { - x_list_sim <- adstock_weibull(x = x, shape = shape, scale = scale, windlen = windlen, type = "pdf") + } else { + get_type <- substr(adstock, nchar(adstock)-2, nchar(adstock)) + x_list_sim <- adstock_weibull(x = x, shape = shape, scale = scale, windlen = windlen, type = get_type) } return(x_list_sim) } @@ -205,18 +201,20 @@ transform_adstock <- function(x, adstock, theta = NULL, shape = NULL, scale = NU #' Hill-transformed value of the x_marginal input. #' @examples #' saturation_hill(c(100, 150, 170, 190, 200), alpha = 3, gamma = 0.5) -#' @return Numeric values. Transformed values. +#' @return List. x_saturated as transformed values and inflexion point #' @export saturation_hill <- function(x, alpha, gamma, x_marginal = NULL) { stopifnot(length(alpha) == 1) stopifnot(length(gamma) == 1) - inflexion <- c(range(x) %*% c(1 - gamma, gamma)) # linear interpolation by dot product + inflexion <- max(x) * gamma + # inflexion <- .dot_product(range = range(x), proportion = gamma) # linear interpolation by dot product if (is.null(x_marginal)) { - x_scurve <- x**alpha / (x**alpha + inflexion**alpha) # plot(x_scurve) summary(x_scurve) + x_saturated <- x**alpha / (x**alpha + inflexion**alpha) # plot(x_saturated) summary(x_saturated) } else { - x_scurve <- x_marginal**alpha / (x_marginal**alpha + inflexion**alpha) + x_saturated <- x_marginal**alpha / (x_marginal**alpha + inflexion**alpha) } - return(x_scurve) + return(list(x_saturated = x_saturated, + inflexion = inflexion)) } @@ -251,7 +249,7 @@ plot_adstock <- function(plot = TRUE) { p1 <- ggplot(geomCollect, aes(x = .data$x, y = .data$decay_accumulated)) + geom_line(aes(color = .data$theta_halflife)) + geom_hline(yintercept = 0.5, linetype = "dashed", color = "gray") + - geom_text(aes(x = max(.data$x), y = 0.5, vjust = -0.5, hjust = 1, label = "Halflife"), colour = "gray") + + annotate("text", x = max(geomCollect$x), y = 0.5, vjust = -0.5, hjust = 1, label = "Halflife", colour = "gray") + labs( title = "Geometric Adstock\n(Fixed decay rate)", subtitle = "Halflife = time until effect reduces to 50%", @@ -292,9 +290,7 @@ plot_adstock <- function(plot = TRUE) { geom_line(aes(color = .data$scale)) + facet_grid(.data$shape ~ .data$type) + geom_hline(yintercept = 0.5, linetype = "dashed", color = "gray") + - geom_text(aes(x = max(.data$x), y = 0.5, vjust = -0.5, hjust = 1, label = "Halflife"), - colour = "gray" - ) + + annotate("text", x = max(weibullCollect$x), y = 0.5, vjust = -0.5, hjust = 1, label = "Halflife", colour = "gray") + labs( title = "Weibull Adstock CDF vs PDF\n(Flexible decay rate)", subtitle = "Halflife = time until effect reduces to 50%", @@ -364,19 +360,29 @@ plot_saturation <- function(plot = TRUE) { } #### Transform media for model fitting -run_transformations <- function(InputCollect, hypParamSam, adstock) { - all_media <- InputCollect$all_media - rollingWindowStartWhich <- InputCollect$rollingWindowStartWhich - rollingWindowEndWhich <- InputCollect$rollingWindowEndWhich - dt_modAdstocked <- select(InputCollect$dt_mod, -.data$ds) - - mediaAdstocked <- list() - mediaImmediate <- list() - mediaCarryover <- list() - mediaVecCum <- list() - mediaSaturated <- list() - mediaSaturatedImmediate <- list() - mediaSaturatedCarryover <- list() +#' @name transformations +#' @inheritParams robyn_inputs +#' @param all_media Character. Vector of all selected paid media variable names. +#' @param window_start_loc Integer. Rolling window start location. +#' @param window_end_loc Integer. Rolling window end location. +#' @param dt_mod dataframe. Transformed input table for transformation. +#' @param adstock Character. Adstock config. +#' @param dt_hyppar data.frame. All hyperparaters for provided media. +#' @export +run_transformations <- function(all_media, + window_start_loc, + window_end_loc, + dt_mod, + adstock, + dt_hyppar, ...) { + dt_modAdstocked <- select(dt_mod, -.data$ds) + window_loc <- window_start_loc:window_end_loc + adstocked_collect <- list() + saturated_total_collect <- list() + saturated_immediate_collect <- list() + saturated_carryover_collect <- list() + inflexion_collect <- list() + inflation_collect <- list() for (v in seq_along(all_media)) { ################################################ @@ -384,60 +390,68 @@ run_transformations <- function(InputCollect, hypParamSam, adstock) { # Decayed/adstocked response = Immediate response + Carryover response m <- dt_modAdstocked[, all_media[v]][[1]] if (adstock == "geometric") { - theta <- hypParamSam[paste0(all_media[v], "_thetas")][[1]][[1]] + theta <- dt_hyppar[paste0(all_media[v], "_thetas")][[1]][[1]] } if (grepl("weibull", adstock)) { - shape <- hypParamSam[paste0(all_media[v], "_shapes")][[1]][[1]] - scale <- hypParamSam[paste0(all_media[v], "_scales")][[1]][[1]] + shape <- dt_hyppar[paste0(all_media[v], "_shapes")][[1]][[1]] + scale <- dt_hyppar[paste0(all_media[v], "_scales")][[1]][[1]] } x_list <- transform_adstock(m, adstock, theta = theta, shape = shape, scale = scale) - m_imme <- if (adstock == "weibull_pdf") x_list$x_imme else m - m_adstocked <- x_list$x_decayed - mediaAdstocked[[v]] <- m_adstocked - m_carryover <- m_adstocked - m_imme - mediaImmediate[[v]] <- m_imme - mediaCarryover[[v]] <- m_carryover - mediaVecCum[[v]] <- x_list$thetaVecCum + input_total <- x_list$x_decayed + input_immediate <- if (adstock == "weibull_pdf") x_list$x_imme else m + adstocked_collect[[v]] <- input_total + input_carryover <- input_total - input_immediate + # mediaImmediate[[v]] <- input_immediate + # mediaCarryover[[v]] <- input_carryover + # mediaVecCum[[v]] <- x_list$thetaVecCum ################################################ ## 2. Saturation (only window data) # Saturated response = Immediate response + carryover response - m_adstockedRollWind <- m_adstocked[rollingWindowStartWhich:rollingWindowEndWhich] - m_carryoverRollWind <- m_carryover[rollingWindowStartWhich:rollingWindowEndWhich] + input_total_rw <- input_total[window_loc] + input_carryover_rw <- input_carryover[window_loc] + alpha <- dt_hyppar[paste0(all_media[v], "_alphas")][[1]][[1]] + gamma <- dt_hyppar[paste0(all_media[v], "_gammas")][[1]][[1]] - alpha <- hypParamSam[paste0(all_media[v], "_alphas")][[1]][[1]] - gamma <- hypParamSam[paste0(all_media[v], "_gammas")][[1]][[1]] - mediaSaturated[[v]] <- saturation_hill( - m_adstockedRollWind, + sat_temp_total <- saturation_hill(x = input_total_rw, alpha = alpha, gamma = gamma ) - mediaSaturatedCarryover[[v]] <- saturation_hill( - m_adstockedRollWind, - alpha = alpha, gamma = gamma, x_marginal = m_carryoverRollWind + sat_temp_caov <- saturation_hill( + x = input_total_rw, + alpha = alpha, gamma = gamma, x_marginal = input_carryover_rw ) - mediaSaturatedImmediate[[v]] <- mediaSaturated[[v]] - mediaSaturatedCarryover[[v]] - # plot(m_adstockedRollWind, mediaSaturated[[1]]) + saturated_total_collect[[v]] <- sat_temp_total[["x_saturated"]] + saturated_carryover_collect[[v]] <- sat_temp_caov[["x_saturated"]] + saturated_immediate_collect[[v]] <- saturated_total_collect[[v]] - saturated_carryover_collect[[v]] + inflexion_collect[[v]] <- sat_temp_total[["inflexion"]] + inflation_collect[[v]] <- x_list$inflation_total + # plot(input_total_rw, saturated_total_collect[[1]]) } - names(mediaAdstocked) <- names(mediaImmediate) <- names(mediaCarryover) <- names(mediaVecCum) <- - names(mediaSaturated) <- names(mediaSaturatedImmediate) <- names(mediaSaturatedCarryover) <- - all_media + names(adstocked_collect) <- names(saturated_total_collect) <- names(saturated_immediate_collect) <- + names(saturated_carryover_collect) <- all_media dt_modAdstocked <- dt_modAdstocked %>% select(-all_of(all_media)) %>% - bind_cols(mediaAdstocked) - dt_mediaImmediate <- bind_cols(mediaImmediate) - dt_mediaCarryover <- bind_cols(mediaCarryover) - mediaVecCum <- bind_cols(mediaVecCum) - dt_modSaturated <- dt_modAdstocked[rollingWindowStartWhich:rollingWindowEndWhich, ] %>% + bind_cols(adstocked_collect) + # dt_mediaImmediate <- bind_cols(mediaImmediate) + # dt_mediaCarryover <- bind_cols(mediaCarryover) + # mediaVecCum <- bind_cols(mediaVecCum) + dt_modSaturated <- dt_modAdstocked[window_loc, ] %>% select(-all_of(all_media)) %>% - bind_cols(mediaSaturated) - dt_saturatedImmediate <- bind_cols(mediaSaturatedImmediate) + bind_cols(saturated_total_collect) + dt_saturatedImmediate <- bind_cols(saturated_immediate_collect) dt_saturatedImmediate[is.na(dt_saturatedImmediate)] <- 0 - dt_saturatedCarryover <- bind_cols(mediaSaturatedCarryover) + dt_saturatedCarryover <- bind_cols(saturated_carryover_collect) dt_saturatedCarryover[is.na(dt_saturatedCarryover)] <- 0 + inflexion_collect <- unlist(inflexion_collect) + inflation_collect <- unlist(inflation_collect) + names(inflexion_collect) <- paste0(all_media, "_inflexion") + names(inflation_collect) <- paste0(all_media, "_inflation") return(list( dt_modSaturated = dt_modSaturated, dt_saturatedImmediate = dt_saturatedImmediate, - dt_saturatedCarryover = dt_saturatedCarryover + dt_saturatedCarryover = dt_saturatedCarryover, + inflexions = inflexion_collect, + inflations = inflation_collect )) } diff --git a/R/README.md b/R/README.md index a9fba9da6..9ee453afb 100644 --- a/R/README.md +++ b/R/README.md @@ -33,10 +33,3 @@ Meta's Robyn is MIT licensed, as found in the LICENSE file. - Terms of Use - https://opensource.facebook.com/legal/terms - Privacy Policy - https://opensource.facebook.com/legal/privacy - -## Contact - -* gufeng@meta.com, Gufeng Zhou, Marketing Science Partner -* leonelsentana@meta.com, Leonel Sentana, Marketing Science Partner -* igorskokan@meta.com, Igor Skokan, Marketing Science Partner -* bernardolares@meta.com, Bernardo Lares, Marketing Science Partner diff --git a/R/data/df_curve_reach_freq.RData b/R/data/df_curve_reach_freq.RData new file mode 100644 index 0000000000000000000000000000000000000000..0678e6e6725eea7329b70b4f9ba9e4cc4a4cf4dd GIT binary patch literal 2685 zcmV-@3WD_?iwFP!000001MQi6I92H$$2Z$0m*i6EHqB_1l1vGaF1|u88++}w*4~n0 z=azE6)@g*KGBS!xMIk3m=_pM^k$EPiq*AV_7`arWVj3#BoHe$bGtS@V@sIU9zx7?; 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It aims to reduce human diff --git a/R/man/adstocks.Rd b/R/man/adstocks.Rd index 6da57ef56..0cfd3a599 100644 --- a/R/man/adstocks.Rd +++ b/R/man/adstocks.Rd @@ -9,7 +9,7 @@ \usage{ adstock_geometric(x, theta) -adstock_weibull(x, shape, scale, windlen = length(x), type = "cdf") +adstock_weibull(x, shape, scale, windlen = length(x), type = "pdf") transform_adstock( x, @@ -88,15 +88,13 @@ Run \code{plot_adstock()} to see the difference visually. } \examples{ adstock_geometric(rep(100, 5), theta = 0.5) -adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "CDF") -adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "PDF") +adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "cdf") +adstock_weibull(rep(100, 5), shape = 0.5, scale = 0.5, type = "pdf") -# Wrapped function for either adstock -transform_adstock(rep(100, 10), "weibull_pdf", shape = 1, scale = 0.5) } \seealso{ Other Transformations: -\code{\link{mic_men}()}, -\code{\link{saturation_hill}()} +\code{\link{saturation_hill}()}, +\code{\link{transformations}} } \concept{Transformations} diff --git a/R/man/df_curve_reach_freq.Rd b/R/man/df_curve_reach_freq.Rd new file mode 100644 index 000000000..a3d572118 --- /dev/null +++ b/R/man/df_curve_reach_freq.Rd @@ -0,0 +1,38 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data.R +\docType{data} +\name{df_curve_reach_freq} +\alias{df_curve_reach_freq} +\title{Robyn Dataset: Reach & frequency simulated dataset} +\format{ +An object of class \code{"data.frame"} +\describe{ + \item{spend_cumulated}{cumulated spend of paid media} + \item{response_cumulated}{cumulated reach of paid media} + \item{freq_bucket}{Frequency bucket for cumulated reach} +} +} +\usage{ +data(df_curve_reach_freq) +} +\value{ +data.frame + +Dataframe. +} +\description{ +A simulated cumulated reach and spend dataset by frequency buckets. +The headers must be kept as +\code{c("spend_cumulated", "response_cumulated", "freq_bucket")}. +} +\examples{ +data(df_curve_reach_freq) +head(df_curve_reach_freq) +} +\seealso{ +Other Dataset: +\code{\link{dt_prophet_holidays}}, +\code{\link{dt_simulated_weekly}} +} +\concept{Dataset} +\keyword{datasets} diff --git a/R/man/dt_prophet_holidays.Rd b/R/man/dt_prophet_holidays.Rd index 2ec9cdeee..5fe53f57f 100644 --- a/R/man/dt_prophet_holidays.Rd +++ b/R/man/dt_prophet_holidays.Rd @@ -32,6 +32,7 @@ head(dt_prophet_holidays) } \seealso{ Other Dataset: +\code{\link{df_curve_reach_freq}}, \code{\link{dt_simulated_weekly}} } \concept{Dataset} diff --git a/R/man/dt_simulated_weekly.Rd b/R/man/dt_simulated_weekly.Rd index 026ffeadb..8c66d3ac5 100644 --- a/R/man/dt_simulated_weekly.Rd +++ b/R/man/dt_simulated_weekly.Rd @@ -31,6 +31,7 @@ head(dt_simulated_weekly) } \seealso{ Other Dataset: +\code{\link{df_curve_reach_freq}}, \code{\link{dt_prophet_holidays}} } \concept{Dataset} diff --git a/R/man/fit_spend_exposure.Rd b/R/man/fit_spend_exposure.Rd deleted file mode 100644 index 16b9d0b46..000000000 --- a/R/man/fit_spend_exposure.Rd +++ /dev/null @@ -1,29 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/inputs.R -\name{fit_spend_exposure} -\alias{fit_spend_exposure} -\title{Fit a nonlinear model for media spend and exposure} -\usage{ -fit_spend_exposure(dt_spendModInput, mediaCostFactor, paid_media_var) -} -\arguments{ -\item{dt_spendModInput}{data.frame. Containing channel spends and -exposure data.} - -\item{mediaCostFactor}{Numeric vector. The ratio between raw media -exposure and spend metrics.} - -\item{paid_media_var}{Character. Paid media variable.} -} -\value{ -List. Containing the all spend-exposure model results. -} -\description{ -This function is called in \code{robyn_engineering()}. It uses -the Michaelis-Menten function to fit the nonlinear model. Fallback -model is the simple linear model \code{lm()} in case the nonlinear -model is fitting worse. A bad fit here might result in unreasonable -model results. Two options are recommended: Either splitting the -channel into sub-channels to achieve better fit, or just use -spend as \code{paid_media_vars} -} diff --git a/R/man/hyper_names.Rd b/R/man/hyper_names.Rd index eb67b2c17..81f0911ab 100644 --- a/R/man/hyper_names.Rd +++ b/R/man/hyper_names.Rd @@ -4,7 +4,7 @@ \alias{hyper_names} \title{Get correct hyperparameter names} \usage{ -hyper_names(adstock, all_media) +hyper_names(adstock, all_media, all_vars = NULL) } \arguments{ \item{adstock}{Character. Default to \code{InputCollect$adstock}. @@ -12,6 +12,8 @@ Accepts "geometric", "weibull_cdf" or "weibull_pdf"} \item{all_media}{Character vector. Default to \code{InputCollect$all_media}. Includes \code{InputCollect$paid_media_spends} and \code{InputCollect$organic_vars}.} + +\item{all_vars}{Used to check the penalties inputs, especially for refreshing models.} } \value{ Character vector. Names of hyper-parameters that should be defined. @@ -22,54 +24,29 @@ hyperparameters that is inserted into \code{robyn_inputs(hyperparameters = ...)} } \section{Guide to setup hyperparameters}{ - \enumerate{ - \item Get correct hyperparameter names: - All variables in \code{paid_media_vars} or \code{organic_vars} require hyperprameters - and will be transformed by adstock & saturation. Difference between \code{paid_media_vars} - and \code{organic_vars} is that \code{paid_media_vars} has spend that - needs to be specified in \code{paid_media_spends} specifically. Run \code{hyper_names()} - to get correct hyperparameter names. All names in hyperparameters must - equal names from \code{hyper_names()}, case sensitive. - \item{Get guidance for setting hyperparameter bounds: - For geometric adstock, use theta, alpha & gamma. For both weibull adstock options, - use shape, scale, alpha, gamma.} - \itemize{ - \item{Theta: }{In geometric adstock, theta is decay rate. guideline for usual media genre: - TV c(0.3, 0.8), OOH/Print/Radio c(0.1, 0.4), digital c(0, 0.3)} - \item{Shape: }{In weibull adstock, shape controls the decay shape. Recommended c(0.0001, 2). - The larger, the more S-shape. The smaller, the more L-shape. Channel-type specific - values still to be investigated} - \item{Scale: }{In weibull adstock, scale controls the decay inflexion point. Very conservative - recommended bounce c(0, 0.1), because scale can increase adstocking half-life greatly. - Channel-type specific values still to be investigated} - \item{Gamma: }{In s-curve transformation with hill function, gamma controls the inflexion point. - Recommended bounce c(0.3, 1). The larger the gamma, the later the inflection point - in the response curve} - } - \item{Set each hyperparameter bounds. They either contains two values e.g. c(0, 0.5), - or only one value (in which case you've "fixed" that hyperparameter)} -} +See section "Hyperparameter interpretation & recommendation" in demo +https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R } \section{Helper plots}{ \describe{ - \item{plot_adstock}{Get adstock transformation example plot, + \item{plot_adstock(TRUE)}{Get adstock transformation example plot, helping you understand geometric/theta and weibull/shape/scale transformation} - \item{plot_saturation}{Get saturation curve transformation example plot, + \item{plot_saturation(TRUE)}{Get saturation curve transformation example plot, helping you understand hill/alpha/gamma transformation} } } \examples{ \donttest{ -media <- c("facebook_S", "print_S", "tv_S") +media <- c("facebook_I", "print_S", "tv_S") hyper_names(adstock = "geometric", all_media = media) hyperparameters <- list( - facebook_S_alphas = c(0.5, 3), # example bounds for alpha - facebook_S_gammas = c(0.3, 1), # example bounds for gamma - facebook_S_thetas = c(0, 0.3), # example bounds for theta + facebook_I_alphas = c(0.5, 3), # example bounds for alpha + facebook_I_gammas = c(0.3, 1), # example bounds for gamma + facebook_I_thetas = c(0, 0.3), # example bounds for theta print_S_alphas = c(0.5, 3), print_S_gammas = c(0.3, 1), print_S_thetas = c(0.1, 0.4), @@ -79,13 +56,13 @@ hyperparameters <- list( ) # Define hyper_names for weibull adstock -hyper_names(adstock = "weibull", all_media = media) +hyper_names(adstock = "weibull_pdf", all_media = media) hyperparameters <- list( - facebook_S_alphas = c(0.5, 3), # example bounds for alpha - facebook_S_gammas = c(0.3, 1), # example bounds for gamma - facebook_S_shapes = c(0.0001, 2), # example bounds for shape - facebook_S_scales = c(0, 0.1), # example bounds for scale + facebook_I_alphas = c(0.5, 3), # example bounds for alpha + facebook_I_gammas = c(0.3, 1), # example bounds for gamma + facebook_I_shapes = c(0.0001, 2), # example bounds for shape + facebook_I_scales = c(0, 0.1), # example bounds for scale print_S_alphas = c(0.5, 3), print_S_gammas = c(0.3, 1), print_S_shapes = c(0.0001, 2), diff --git a/R/man/prophet_decomp.Rd b/R/man/prophet_decomp.Rd index b60bae467..5a2d57dc9 100644 --- a/R/man/prophet_decomp.Rd +++ b/R/man/prophet_decomp.Rd @@ -14,6 +14,7 @@ prophet_decomp( context_vars, organic_vars, paid_media_spends, + paid_media_vars, intervalType, dayInterval, custom_params @@ -33,6 +34,14 @@ Prophet holidays using \code{data("dt_prophet_holidays")}} push-notifications, social media posts etc. Compared to \code{paid_media_vars} \code{organic_vars} are often marketing activities without clear spends.} +\item{paid_media_vars}{Character vector. Names of the paid media variables' +exposure level metrics (impressions, clicks, GRP etc) other than spend. +The values on each of these variables must be numeric. These variables are not +being used to train the model but to check relationship and recommend to +split media channels into sub-channels (e.g. fb_retargeting, fb_prospecting, +etc.) to gain more variance. \code{paid_media_vars} must have same +order and length as \code{paid_media_spends} respectively and is not required.} + \item{custom_params}{List. Custom parameters passed to \code{prophet()}} } \value{ diff --git a/R/man/robyn_allocator.Rd b/R/man/robyn_allocator.Rd index df2c9aae2..cbe78645c 100644 --- a/R/man/robyn_allocator.Rd +++ b/R/man/robyn_allocator.Rd @@ -23,6 +23,7 @@ robyn_allocator( optim_algo = "SLSQP_AUGLAG", maxeval = 1e+05, constr_mode = "eq", + keep_zero_coefs = FALSE, plots = TRUE, plot_folder = NULL, plot_folder_sub = NULL, @@ -86,7 +87,7 @@ for each paid media variable when maximizing total media response. For example, \code{channel_constr_low = 0.7} means minimum spend of the variable is 70% of historical average, using non-zero spend values, within \code{date_min} and \code{date_max} date range. Both constrains must be length 1 (same for all values) OR same length and order as -\code{paid_media_spends}. It's not recommended to 'exaggerate' upper bounds, especially +\code{paid_media_selected}. It's not recommended to 'exaggerate' upper bounds, especially if the new level is way higher than historical level. Lower bound must be >=0.01, and upper bound should be < 5.} @@ -107,6 +108,9 @@ Defaults to 100000.} \item{constr_mode}{Character. Options are \code{"eq"} or \code{"ineq"}, indicating constraints with equality or inequality.} +\item{keep_zero_coefs}{Boolean. By default, zero coefficient (betas) channels +will be removed to avoid spending budget were there is no impact.} + \item{plots}{Boolean. Generate plots?} \item{plot_folder}{Character. Path for saving plots and files. Default diff --git a/R/man/robyn_calibrate.Rd b/R/man/robyn_calibrate.Rd new file mode 100644 index 000000000..3478321c9 --- /dev/null +++ b/R/man/robyn_calibrate.Rd @@ -0,0 +1,91 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/calibration.R +\name{robyn_calibrate} +\alias{robyn_calibrate} +\title{Robyn Calibration Function - BETA} +\usage{ +robyn_calibrate( + df_curve = NULL, + curve_type = NULL, + force_shape = NULL, + hp_bounds = NULL, + max_trials = 10, + max_iters = 2500, + loss_min_step_rel = 1e-04, + loss_stop_rel = 0.05, + burn_in_rel = 0.1, + sim_n = 30, + hp_interval = 0.5, + quiet = FALSE, + ... +) +} +\arguments{ +\item{df_curve}{data.frame. Requires two columns named spend and response. +Recommended sources of truth are Halo R&F or Meta conversion lift.} + +\item{curve_type}{Character. Currently only allows "saturation_reach_hill" +and only supports Hill function.} + +\item{force_shape}{Character. Allows c("c", "s") with default NULL that's no +shape forcing. It's recommended for offline media to have "c" shape, while +for online can be "s" or NULL. Shape forcing only works if hp_bounds is null.} + +\item{hp_bounds}{list. Currently only allows Hill for saturation. Ranges +for alpha and gamma are provided as Hill parameters. If NULL, hp_bounds takes +on default ranges.} + +\item{max_trials}{integer. Different trials have different starting point +and provide diversified sampling paths. Default to 10.} + +\item{max_iters}{integer. Loss is minimized while iteration increases. +Default to 2500.} + +\item{loss_min_step_rel}{numeric. Default to 0.01 and value is between 0-0.1. +0.01 means the optimisation is considered converged if error minimization is +<1 percent of maximal error.} + +\item{loss_stop_rel}{numeric. Default is 0.05 and value is between 0-0.5. +0.05 means 5 percent of the max_iters is used as the length of iterations to +calculate the mean error for convergence.} + +\item{burn_in_rel}{numeric. Default to 0.1 and value is between 0.0.5. 0.1 +means 10 percent of iterations is used as burn-in period.} + +\item{sim_n}{integer. Number of simulation for plotting fitted curve.} + +\item{hp_interval}{numeric. Default to 0.95 and is between 0.8-1. 0.95 means +2.5 - 97.5 percent percentile are used as parameter range for output.} + +\item{quiet}{Boolean. Keep messages off?} + +\item{...}{Additional parameters passed to \code{robyn_outputs()}.} +} +\value{ +List. Class: \code{curve_out}. Contains the results of all trials +and iterations modeled. +} +\description{ +\code{robyn_calibrate()} consumes source of truth or proxy data for +saturation or adstock curve estimation. This is an experimental feature and +can be used independently from Robyn's main model. +} +\examples{ +\dontrun{ +# Dummy input data for Meta spend. This is derived from Halo's reach & frequency data. +# Note that spend and response need to be cumulative metrics. +data("df_curve_reach_freq") + +# Using reach saturation from Halo as proxy +curve_out <- robyn_calibrate( + df_curve = df_curve_reach_freq, + curve_type = "saturation_reach_hill" +) +# For the simulated reach and frequency dataset, it's recommended to use +# "reach 1+" for gamma lower bound and "reach 10+" for gamma upper bound +facebook_I_gammas <- c( + curve_out[["curve_collect"]][["reach 1+"]][["hill"]][["gamma_best"]], + curve_out[["curve_collect"]][["reach 10+"]][["hill"]][["gamma_best"]]) +print(facebook_I_gammas) +} +} diff --git a/R/man/robyn_inputs.Rd b/R/man/robyn_inputs.Rd index a4566f872..399d0ec16 100644 --- a/R/man/robyn_inputs.Rd +++ b/R/man/robyn_inputs.Rd @@ -45,7 +45,7 @@ as "revenue" or "conversion". Will be used to calculate ROI or CPI, respectively. Only one allowed and case sensitive.} \item{date_var}{Character. Name of date variable. Daily, weekly -and monthly data supported. Weekly requires week-start of Monday or Sunday. +and monthly data supported. \code{date_var} must have format "2020-01-01" (YYY-MM-DD). Default to automatic date detection.} @@ -94,7 +94,7 @@ variables in organic_vars or context_vars should be forced as a factor.} Prophet holidays using \code{data("dt_prophet_holidays")}} \item{prophet_vars}{Character vector. Include any of "trend", -"season", "weekday", "holiday" or NULL. Highly recommended +"season", "weekday", "monthly", "holiday" or NULL. Highly recommended to use all for daily data and "trend", "season", "holiday" for weekly and above cadence. Set to NULL to skip prophet's functionality.} diff --git a/R/man/robyn_mmm.Rd b/R/man/robyn_mmm.Rd index 381946d24..8339546b0 100644 --- a/R/man/robyn_mmm.Rd +++ b/R/man/robyn_mmm.Rd @@ -2,6 +2,7 @@ % Please edit documentation in R/model.R \name{robyn_mmm} \alias{robyn_mmm} +\alias{model_decomp} \title{Core MMM Function} \usage{ robyn_mmm( @@ -23,6 +24,8 @@ robyn_mmm( quiet = FALSE, ... ) + +model_decomp(inputs = list()) } \arguments{ \item{InputCollect}{List. Contains all input parameters for the model. @@ -84,11 +87,15 @@ another model with no 0-coef variables gets un-penalized with DECOMP.RSSD * 1.} \item{trial}{Integer. Which trial are we running? Used to ID each model.} -\item{seed}{Integer. For reproducible results when running nevergrad.} +\item{seed}{Integer. For reproducible results when running nevergrad and +clustering. Each trial will increase the seed by 1 unit (i.e. 10 trials with +seed 1 will share 9 results with 10 trials with seed 2).} \item{quiet}{Boolean. Keep messages off?} \item{...}{Additional parameters passed to \code{robyn_outputs()}.} + +\item{inputs}{List. Elements to pass sub-functions} } \value{ List. MMM results with hyperparameters values. diff --git a/R/man/robyn_outputs.Rd b/R/man/robyn_outputs.Rd index 652854da3..4d6cc6b5a 100644 --- a/R/man/robyn_outputs.Rd +++ b/R/man/robyn_outputs.Rd @@ -1,9 +1,11 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/outputs.R, R/plots.R +% Please edit documentation in R/outputs.R, R/pareto.R, R/plots.R \name{robyn_outputs} \alias{robyn_outputs} \alias{print.robyn_outputs} \alias{robyn_csv} +\alias{pareto_front} +\alias{robyn_immcarr} \alias{robyn_plots} \alias{robyn_onepagers} \alias{ts_validation} @@ -39,6 +41,17 @@ robyn_csv( calibrated = FALSE ) +pareto_front(xi, yi, pareto_fronts = 1, ...) + +robyn_immcarr( + InputCollect, + OutputCollect, + solID = NULL, + start_date = NULL, + end_date = NULL, + ... +) + robyn_plots( InputCollect, OutputCollect, @@ -118,14 +131,19 @@ wish to plot the one-pagers and export? Default will take top \item{calibrated}{Logical} +\item{xi, yi}{Numeric. Coordinates values per observation.} + +\item{solID}{Character vector. Model IDs to plot.} + +\item{start_date, end_date}{Character/Date. Dates to consider when calculating +immediate and carryover values per channel.} + \item{baseline_level}{Integer, from 0 to 5. Aggregate baseline variables, depending on the level of aggregation you need. Default is 0 for no aggregation. 1 for Intercept only. 2 adding trend. 3 adding all prophet decomposition variables. 4. Adding contextual variables. 5 Adding organic variables. Results will be reflected on the waterfall chart.} -\item{solID}{Character vector. Model IDs to plot.} - \item{exclude}{Character vector. Manually exclude variables from plot.} } \value{ diff --git a/R/man/robyn_refresh.Rd b/R/man/robyn_refresh.Rd index b75bef964..2ab75f07d 100644 --- a/R/man/robyn_refresh.Rd +++ b/R/man/robyn_refresh.Rd @@ -15,6 +15,7 @@ robyn_refresh( refresh_mode = "manual", refresh_iters = 1000, refresh_trials = 3, + bounds_freedom = NULL, plot_folder = NULL, plot_pareto = TRUE, version_prompt = FALSE, @@ -63,6 +64,11 @@ still needs to be investigated.} \item{refresh_trials}{Integer. Trials per refresh. Defaults to 5 trials. More reliable recommendation still needs to be investigated.} +\item{bounds_freedom}{Numeric. Percentage of freedom we'd like to allow for the +new hyperparameters values compared with the model to be refreshed. +If set to NULL (default) the value will be calculated as +refresh_steps / rollingWindowLength. Applies to all hyperparameters.} + \item{plot_folder}{Character. Path for saving plots and files. Default to \code{robyn_object} and saves plot in the same directory as \code{robyn_object}.} diff --git a/R/man/robyn_response.Rd b/R/man/robyn_response.Rd index 8bbc33a74..551621615 100644 --- a/R/man/robyn_response.Rd +++ b/R/man/robyn_response.Rd @@ -8,7 +8,6 @@ robyn_response( InputCollect = NULL, OutputCollect = NULL, json_file = NULL, - robyn_object = NULL, select_build = NULL, select_model = NULL, metric_name = NULL, @@ -32,9 +31,6 @@ recreate a model. To generate this file, use \code{robyn_write()}. If you didn't export your data in the json file as "raw_data", \code{dt_input} must be provided; \code{dt_holidays} input is optional.} -\item{robyn_object}{Character or List. Path of the \code{Robyn.RDS} object -that contains all previous modeling information or the imported list.} - \item{select_build}{Integer. Default to the latest model build. \code{select_build = 0} selects the initial model. \code{select_build = 1} selects the first refresh model.} @@ -54,11 +50,11 @@ per channel. Set one of: "all", "last", or "last_n" (where n is the last N dates available), date (i.e. "2022-03-27"), or date range (i.e. \code{c("2022-01-01", "2022-12-31")}). Default to "all".} -\item{dt_hyppar}{A data.frame. When \code{robyn_object} is not provided, use +\item{dt_hyppar}{A data.frame. When \code{json_file} is not provided, use \code{dt_hyppar = OutputCollect$resultHypParam}. It must be provided along \code{select_model}, \code{dt_coef} and \code{InputCollect}.} -\item{dt_coef}{A data.frame. When \code{robyn_object} is not provided, use +\item{dt_coef}{A data.frame. When \code{json_file} is not provided, use \code{dt_coef = OutputCollect$xDecompAgg}. It must be provided along \code{select_model}, \code{dt_hyppar} and \code{InputCollect}.} diff --git a/R/man/robyn_run.Rd b/R/man/robyn_run.Rd index 9bd0be9cf..238bc301c 100644 --- a/R/man/robyn_run.Rd +++ b/R/man/robyn_run.Rd @@ -58,7 +58,9 @@ more iterations to converge.} \item{refresh}{Boolean. Set to \code{TRUE} when used in \code{robyn_refresh()}.} -\item{seed}{Integer. For reproducible results when running nevergrad.} +\item{seed}{Integer. For reproducible results when running nevergrad and +clustering. Each trial will increase the seed by 1 unit (i.e. 10 trials with +seed 1 will share 9 results with 10 trials with seed 2).} \item{quiet}{Boolean. Keep messages off?} diff --git a/R/man/robyn_train.Rd b/R/man/robyn_train.Rd index f82d51207..b1a2d1689 100644 --- a/R/man/robyn_train.Rd +++ b/R/man/robyn_train.Rd @@ -85,7 +85,9 @@ another model with no 0-coef variables gets un-penalized with DECOMP.RSSD * 1.} \item{refresh}{Boolean. Set to \code{TRUE} when used in \code{robyn_refresh()}.} -\item{seed}{Integer. For reproducible results when running nevergrad.} +\item{seed}{Integer. For reproducible results when running nevergrad and +clustering. Each trial will increase the seed by 1 unit (i.e. 10 trials with +seed 1 will share 9 results with 10 trials with seed 2).} \item{quiet}{Boolean. Keep messages off?} } diff --git a/R/man/robyn_write.Rd b/R/man/robyn_write.Rd index 723aefd4d..d877e1c4f 100644 --- a/R/man/robyn_write.Rd +++ b/R/man/robyn_write.Rd @@ -13,6 +13,7 @@ robyn_write( OutputCollect = NULL, select_model = NULL, dir = OutputCollect$plot_folder, + add_data = TRUE, export = TRUE, quiet = FALSE, pareto_df = NULL, @@ -37,15 +38,16 @@ into the JSON file?} \item{dir}{Character. Existing directory to export JSON file to.} +\item{add_data}{Boolean. Include raw dataset. Useful to recreate models +with a single file containing all the required information (no need of CSV).} + \item{export}{Boolean. Export outcomes into local files?} \item{quiet}{Boolean. Keep messages off?} \item{pareto_df}{Dataframe. Save all pareto solutions to json file.} -\item{...}{Additional parameters to export into a custom Extras element. -If you wish to include the data to recreate a model, add -\code{raw_data = InputCollect$dt_input}.} +\item{...}{Additional parameters to export into a custom Extras element.} \item{x}{\code{robyn_read()} or \code{robyn_write()} output.} diff --git a/R/man/saturation_hill.Rd b/R/man/saturation_hill.Rd index 8411635e3..e3e94d6e4 100644 --- a/R/man/saturation_hill.Rd +++ b/R/man/saturation_hill.Rd @@ -24,7 +24,7 @@ Hill-transformed value of the x_marginal input.} \item{plot}{Boolean. Do you wish to return the plot?} } \value{ -Numeric values. Transformed values. +List. x_saturated as transformed values and inflexion point } \description{ \code{saturation_hill} is a two-parametric version of the Hill @@ -38,6 +38,6 @@ saturation_hill(c(100, 150, 170, 190, 200), alpha = 3, gamma = 0.5) \seealso{ Other Transformations: \code{\link{adstock_geometric}()}, -\code{\link{mic_men}()} +\code{\link{transformations}} } \concept{Transformations} diff --git a/R/man/set_default_hyppar.Rd b/R/man/set_default_hyppar.Rd new file mode 100644 index 000000000..063b03a34 --- /dev/null +++ b/R/man/set_default_hyppar.Rd @@ -0,0 +1,26 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/inputs.R +\name{set_default_hyppar} +\alias{set_default_hyppar} +\title{Set default hyperparameters} +\usage{ +set_default_hyppar( + adstock = NULL, + all_media = NULL, + list_default = list(alpha = c(0.5, 3), gamma = c(0.01, 1), theta = c(0, 0.8), shape = + c(0, 10), scale = c(0, 0.1), train_size = c(0.5, 0.9)) +) +} +\arguments{ +\item{adstock}{Character. InputCollect$adstock} + +\item{all_media}{Character. Provide InputCollect$all_media.} + +\item{list_default}{A List. Default ranges for hyperparameters.} +} +\value{ +List. Expanded range of hyperparameters for all media. +} +\description{ +For quick setting of hyperparameter ranges. +} diff --git a/R/man/mic_men.Rd b/R/man/transformations.Rd similarity index 63% rename from R/man/mic_men.Rd rename to R/man/transformations.Rd index 01501c409..2ac4ef986 100644 --- a/R/man/mic_men.Rd +++ b/R/man/transformations.Rd @@ -1,10 +1,22 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/transformation.R -\name{mic_men} +\name{transformations} +\alias{transformations} \alias{mic_men} +\alias{run_transformations} \title{Michaelis-Menten Transformation} \usage{ mic_men(x, Vmax, Km, reverse = FALSE) + +run_transformations( + all_media, + window_start_loc, + window_end_loc, + dt_mod, + adstock, + dt_hyppar, + ... +) } \arguments{ \item{x}{Numeric value or vector. Input media spend when @@ -17,6 +29,20 @@ GRPs, etc.) when \code{reverse = TRUE}.} \item{reverse}{Boolean. Input media spend when \code{reverse = FALSE}. Input media exposure metrics (impression, clicks, GRPs etc.) when \code{reverse = TRUE}.} + +\item{all_media}{Character. Vector of all selected paid media variable names.} + +\item{window_start_loc}{Integer. Rolling window start location.} + +\item{window_end_loc}{Integer. Rolling window end location.} + +\item{dt_mod}{dataframe. Transformed input table for transformation.} + +\item{adstock}{Character. Adstock config.} + +\item{dt_hyppar}{data.frame. All hyperparaters for provided media.} + +\item{...}{Additional parameters passed to \code{prophet} functions.} } \value{ Numeric values. Transformed values. diff --git a/README.md b/README.md index 6bdc463fa..b02805d2c 100644 --- a/README.md +++ b/README.md @@ -10,11 +10,13 @@ * **Why are we doing this?**: MMM used to be a resource-intensive technique that was only affordable for "big players". As the privacy needs of the measurement landscape evolve, there's a clear trend of increasing demand for modern MMM as a privacy-safe solution. At Meta Marketing Science, our mission is to help all businesses grow by transforming marketing practices grounded in data and science. It's highly aligned with our mission to democratizing MMM and making it accessible for advertisers of all sizes. With Project Robyn, we want to contribute to the measurement landscape, inspire the industry and build a community for exchange and innovation around the future of MMM and Marketing Science in general. +Robyn is available in R and Python. For installation and usage guide see below. Please note that the current Python version is a LLM-translated Beta version and might encounter bugs. + ## Quick start for R **1. Installing the package** - * Install Robyn latest package version: + * Install Robyn latest R package version: ```{r} ## CRAN VERSION install.packages("Robyn") @@ -44,9 +46,46 @@ remotes::install_github("facebookexperimental/Robyn/R") * Take Meta's [official Robyn blueprint course](https://www.facebookblueprint.com/student/path/253121-marketing-mix-models?utm_source=readme) online -## Quick start Python (Robyn API for Python beta) +## Quick start for Python (Beta) + +The Python version of Robyn is rewritten from Robyn's R package version `3.11.1` to Python using object oriented programming principles and modular architecture for a robust solution. It was developed by utilizing various LLMs and AI workflows like [Llama](https://www.llama.com/). As is common with any AI-based solutions, there may be potential challenges in translating code from one language to another. In this case, we anticipate that there could be some issues in the translation from R to Python. However, we believe in the power of community collaboration and open-source contribution. Therefore, we are opening this project to the community to participate and contribute. Together, we can address and resolve any issues that may arise, enhancing the functionality and efficiency of the Python version of Robyn. We look forward to your contributions and to the continuous improvement of this project. + +**1. Installing the package** + + * Install Robyn latest Python package version: +```{r} +## Pypi +pip3 install robynpy + +## DEV VERSION +# if you are pulling source from github, install dependencies using requirements.txt +pip3 install -r requirements.txt +``` + +**2. Getting started** + + * The directory python/src/robyn/tutorials contains tutorials for most common scenarios. Tutorials use simulated dataset provided in the package. + + * There are two ways of running Python Robyn; one is `tutorial1.ipynb` and second is `tutorial1_src.ipynb`. + +**3. Running end-to-end** + +Option 1: + * `tutorial1.ipynb` is the main notebook that runs the end-to-end flow. It is designed for majority of the users who would prefer a one click solution that runs the robyn flow end-to-end with minimal knowledge of the underlying logic. It should run without any changes required if you wish to use the simulated dataset for testing purposes. + + * This notebook uses APIs available in `python/src/robyn/robyn.py` to set the configs, run feature engineering, run model training, evaluate models with clustering, generate one pagers and perform budget allocation. + + * Change any of the configs directly in the notebook and avoid changes to robyn.py for what can be configurable. + +Option 2: + * `tutorial1_src.ipynb` runs the end-to-end flow of robyn python but with a lot more flexibility. It is designed for users who would like to have more control over which modules are and aren't run (ie. skipping clustering/one pager plots/budget allocation etc.). It should run without any changes required if you wish to use the simulated dataset for testing purposes. + + * This notebook doesn't use APIs available in `python/src/robyn/robyn.py` but instead, calls the modules directly with the appropriate parameters. In this way, it is more flexible but still expects the users to understand the underlying logic that may change when using various parameter values. + +## Quick start Python wrapper (Robyn API for Python beta) + +The Robyn API for Python (beta), first released on Nov.22nd 2023, is a plumber-based solution that requires the installation of the Robyn R pacakge first. It serves as a workaround when the Python native version is not yet available or up-to-date. Please see the usage guide [here](https://github.com/facebookexperimental/Robyn/blob/main/robyn_api/robyn_python_notebook.ipynb). -The Robyn API for Python (beta), first released on Nov.22nd 2023, is a plumber-based solution that requires the installation of the Robyn R pacakge first. Please see the usage guide [here](https://github.com/facebookexperimental/Robyn/blob/main/robyn_api/robyn_python_notebook.ipynb). ## License diff --git a/demo/demo.R b/demo/demo.R index cc1b4f1ab..0259bd7ad 100644 --- a/demo/demo.R +++ b/demo/demo.R @@ -4,7 +4,7 @@ # LICENSE file in the root directory of this source tree. ############################################################################################# -#################### Meta MMM Open Source: Robyn 3.10.5 ####################### +#################### Meta MMM Open Source: Robyn 3.12.0 ####################### #################### Quick demo guide ####################### ############################################################################################# @@ -32,9 +32,6 @@ packageVersion("Robyn") Sys.setenv(R_FUTURE_FORK_ENABLE = "true") options(future.fork.enable = TRUE) -# Set to FALSE to avoid the creation of files locally -create_files <- TRUE - ## IMPORTANT: Must install and setup the python library "Nevergrad" once before using Robyn ## Guide: https://github.com/facebookexperimental/Robyn/blob/main/demo/install_nevergrad.R @@ -46,7 +43,7 @@ data("dt_simulated_weekly") head(dt_simulated_weekly) ## Check holidays from Prophet -# 59 countries included. If your country is not included, please manually add it. +# 123 countries included. If your country is not included, please manually add it. # Tipp: any events can be added into this table, school break, events etc. data("dt_prophet_holidays") head(dt_prophet_holidays) @@ -59,44 +56,41 @@ robyn_directory <- "~/Desktop" #### 2a-1: First, specify input variables -## All sign control are now automatically provided: "positive" for media & organic -## variables and "default" for all others. User can still customise signs if necessary. -## Documentation is available, access it anytime by running: ?robyn_inputs +## For documentation of all arguments run ?robyn_inputs InputCollect <- robyn_inputs( dt_input = dt_simulated_weekly, dt_holidays = dt_prophet_holidays, date_var = "DATE", # date format must be "2020-01-01" - dep_var = "revenue", # there should be only one dependent variable - dep_var_type = "revenue", # "revenue" (ROI) or "conversion" (CPA) - prophet_vars = c("trend", "season", "holiday"), # "trend","season", "weekday" & "holiday" - prophet_country = "DE", # input country code. Check: dt_prophet_holidays + dep_var = "revenue", # currently one dependent variable allowed + dep_var_type = "revenue", # "revenue" or "conversion" allowed + prophet_vars = c("trend", "season", "holiday"), # "trend","season", "weekday" & "holiday" allowed + prophet_country = "DE", # 123 countries included in dt_prophet_holidays context_vars = c("competitor_sales_B", "events"), # e.g. competitors, discount, unemployment etc paid_media_spends = c("tv_S", "ooh_S", "print_S", "facebook_S", "search_S"), # mandatory input - paid_media_vars = c("tv_S", "ooh_S", "print_S", "facebook_I", "search_clicks_P"), # mandatory. - # paid_media_vars must have same order as paid_media_spends. Use media exposure metrics like - # impressions, GRP etc. If not applicable, use spend instead. - organic_vars = "newsletter", # marketing activity without media spend - # factor_vars = c("events"), # force variables in context_vars or organic_vars to be categorical + paid_media_vars = c("tv_S", "ooh_S", "print_S", "facebook_I", "search_clicks_P"), # if provided, + # Robyn will use this instead of paid_media_spends for modelling. Media exposure metrics + # include typically, but not limited to impressions, GRP etc. If not applicable, use spend instead. + organic_vars = c("newsletter"), # marketing activity without media spend + factor_vars = c("events"), # indicate categorical varibales in context_vars or organic_vars window_start = "2016-01-01", window_end = "2018-12-31", - adstock = "geometric" # geometric, weibull_cdf or weibull_pdf. + adstock = "geometric" # geometric or weibull_pdf ) print(InputCollect) #### 2a-2: Second, define and add hyperparameters -## Default media variable for modelling has changed from paid_media_vars to paid_media_spends. -## Also, calibration_input are required to be spend names. -## hyperparameter names are based on paid_media_spends names too. See right hyperparameter names: +## hyperparameter names are based on paid_media_vars. See right hyperparameter names: hyper_names(adstock = InputCollect$adstock, all_media = InputCollect$all_media) ## Guide to setup & understand hyperparameters -## Robyn's hyperparameters have four components: +## Robyn's hyperparameters have five components: ## - Adstock parameters (theta or shape/scale) ## - Saturation parameters (alpha/gamma) ## - Regularisation parameter (lambda). No need to specify manually ## - Time series validation parameter (train_size) +## - Beta coefficient penalty factor (_penalty). No need to specify manually ## 1. IMPORTANT: set plot = TRUE to create example plots for adstock & saturation ## hyperparameters and their influence in curve transformation. @@ -104,7 +98,7 @@ plot_adstock(plot = FALSE) plot_saturation(plot = FALSE) ## 2. Get correct hyperparameter names: -# All variables in paid_media_spends and organic_vars require hyperparameter and will be +# All variables in paid_media_vars and organic_vars require hyperparameter and will be # transformed by adstock & saturation. # Run hyper_names(adstock = InputCollect$adstock, all_media = InputCollect$all_media) # to get correct media hyperparameter names. All names in hyperparameters must equal @@ -119,14 +113,6 @@ plot_saturation(plot = FALSE) # to convert weekly to daily we can transform the parameter to the power of (1/7), # so to convert 30% daily to weekly is 0.3^(1/7) = 0.84. -## Weibull CDF adstock: The Cumulative Distribution Function of Weibull has two parameters, -# shape & scale, and has flexible decay rate, compared to Geometric adstock with fixed -# decay rate. The shape parameter controls the shape of the decay curve. Recommended -# bound is c(0, 2). The larger the shape, the more S-shape. The smaller, the more -# L-shape. Scale controls the inflexion point of the decay curve. We recommend very -# conservative bounce of c(0, 0.1), because scale increases the adstock half-life greatly. -# When shape or scale is 0, adstock will be 0. - ## Weibull PDF adstock: The Probability Density Function of the Weibull also has two # parameters, shape & scale, and also has flexible decay rate as Weibull CDF. The # difference is that Weibull PDF offers lagged effect. When shape > 2, the curve peaks @@ -144,10 +130,18 @@ plot_saturation(plot = FALSE) # in hyperparameter spaces for Nevergrad to explore, it also requires larger iterations # to converge. When shape or scale is 0, adstock will be 0. +## Weibull CDF adstock (to be depreceated): The Cumulative Distribution Function of Weibull has two parameters, +# shape & scale, and has flexible decay rate, compared to Geometric adstock with fixed +# decay rate. The shape parameter controls the shape of the decay curve. Recommended +# bound is c(0, 2). The larger the shape, the more S-shape. The smaller, the more +# L-shape. Scale controls the inflexion point of the decay curve. We recommend very +# conservative bounce of c(0, 0.1), because scale increases the adstock half-life greatly. +# When shape or scale is 0, adstock will be 0. + ## Hill function for saturation: Hill function is a two-parametric function in Robyn with # alpha and gamma. Alpha controls the shape of the curve between exponential and s-shape. # Recommended bound is c(0.5, 3). The larger the alpha, the more S-shape. The smaller, the -# more C-shape. Gamma controls the inflexion point. Recommended bounce is c(0.3, 1). The +# more C-shape. Gamma controls the inflexion point. Recommended bounce is c(0.01, 1). The # larger the gamma, the later the inflection point in the response curve. ## Regularization for ridge regression: Lambda is the penalty term for regularised regression. @@ -167,19 +161,19 @@ hyper_limits() # Example hyperparameters ranges for Geometric adstock hyperparameters <- list( - facebook_S_alphas = c(0.5, 3), - facebook_S_gammas = c(0.3, 1), - facebook_S_thetas = c(0, 0.3), - print_S_alphas = c(0.5, 3), + facebook_I_alphas = c(0.5, 3), + facebook_I_gammas = c(0.3, 1), + facebook_I_thetas = c(0, 0.3), + print_S_alphas = c(0.5, 1), print_S_gammas = c(0.3, 1), print_S_thetas = c(0.1, 0.4), - tv_S_alphas = c(0.5, 3), + tv_S_alphas = c(0.5, 1), tv_S_gammas = c(0.3, 1), tv_S_thetas = c(0.3, 0.8), - search_S_alphas = c(0.5, 3), - search_S_gammas = c(0.3, 1), - search_S_thetas = c(0, 0.3), - ooh_S_alphas = c(0.5, 3), + search_clicks_P_alphas = c(0.5, 3), + search_clicks_P_gammas = c(0.3, 1), + search_clicks_P_thetas = c(0, 0.3), + ooh_S_alphas = c(0.5, 1), ooh_S_gammas = c(0.3, 1), ooh_S_thetas = c(0.1, 0.4), newsletter_alphas = c(0.5, 3), @@ -188,6 +182,8 @@ hyperparameters <- list( train_size = c(0.5, 0.8) ) +# hyperparameters <- set_default_hyppar("weibull_pdf", InputCollect$all_media) + # Example hyperparameters ranges for Weibull CDF adstock # facebook_S_alphas = c(0.5, 3) # facebook_S_gammas = c(0.3, 1) @@ -200,16 +196,50 @@ hyperparameters <- list( # facebook_S_shapes = c(0, 10) # facebook_S_scales = c(0, 0.1) -#### 2a-3: Third, add hyperparameters into robyn_inputs() +#### 2a-3 (Optional) Saturation calibration - The curve calibrator - Beta feature + +## Dummy input data for Meta spend. This is derived from Halo's reach & frequency data. +## Note that spend and response need to be cumulative metrics. Headers need to be +## kept the same as dummy dataset. + +# data("df_curve_reach_freq") +# +# # Currently only supports curve_type = "saturation_reach" +# curve_out <- robyn_calibrate( +# df_curve = df_curve_reach_freq, +# curve_type = "saturation_reach" +# ) +# curve_out$plot_reach_freq +# +# ## Reach & frequency calibration reasoning +# # When calibrating response saturation with reach and frequency, it's +# # recommended to use "reach 1+" for gamma lower bound and higher frequency bucket, +# # e.g. "reach 10+" in the dummy dataset, for gamma upper bound calibration. +# # Assuming an extreme situation when every user sees one impression and purchases +# # immediately, In such case, response curve equals to the reach 1+ curve. Gamma +# # controls the inflexion point of a Hill curve and a lower gamma means earlier +# # and faster saturation at a lower spend level. We believe that the cumulative +# # reach 1+ curve represents the earliest inflexion, thus we believe it's a +# # reasonable lower boundary for gamma for a selected channel. As frequency +# # increases, the inflexion point also delays and approaches the hidden true +# # response curve. In the dummy dataset, we've simulated reach 10+ to represent +# # upper bound for gamma. Use domain expertise to further narrow down or widen +# # the bounds. For alpha, we recommend to keep the value flexible as in default. +# facebook_I_gammas <- c( +# curve_out[["curve_collect"]][["reach 1+"]][["hill"]][["gamma_best"]], +# curve_out[["curve_collect"]][["reach 10+"]][["hill"]][["gamma_best"]]) +# hyperparameters$facebook_I_gammas <- facebook_I_gammas + +#### 2a-4: Third, add hyperparameters into robyn_inputs() InputCollect <- robyn_inputs(InputCollect = InputCollect, hyperparameters = hyperparameters) print(InputCollect) -#### 2a-4: Fourth (optional), model calibration / add experimental input +#### 2a-5: (Optional) Effect size calibration -## Guide for calibration +## Effect size calibration -# 1. Calibration channels need to be paid_media_spends or organic_vars names. +# 1. Calibration channels need to be paid_media_vars or organic_vars names. # 2. We strongly recommend to use Weibull PDF adstock for more degree of freedom when # calibrating Robyn. # 3. We strongly recommend to use experimental and causal results that are considered @@ -234,16 +264,16 @@ print(InputCollect) # to indicate combination of channels, case sensitive. # calibration_input <- data.frame( -# # channel name must in paid_media_vars +# # channel name should be in paid_media_vars and / or organic_vars # channel = c("facebook_S", "tv_S", "facebook_S+search_S", "newsletter"), # # liftStartDate must be within input data range -# liftStartDate = as.Date(c("2018-05-01", "2018-04-03", "2018-07-01", "2017-12-01")), +# liftStartDate = as.Date(c("2018-05-01", "2018-01-01", "2018-07-01", "2017-12-01")), # # liftEndDate must be within input data range -# liftEndDate = as.Date(c("2018-06-10", "2018-06-03", "2018-07-20", "2017-12-31")), +# liftEndDate = as.Date(c("2018-06-10", "2018-03-01", "2018-07-20", "2017-12-31")), # # Provided value must be tested on same campaign level in model and same metric as dep_var_type -# liftAbs = c(400000, 300000, 700000, 200), +# liftAbs = c(40000, 120000, 60000, 200), # # Spend within experiment: should match within a 10% error your spend on date range for each channel from dt_input -# spend = c(421000, 7100, 350000, 0), +# spend = c(12000, 86000, 22000, 0), # # Confidence: if frequentist experiment, you may use 1 - pvalue # confidence = c(0.85, 0.8, 0.99, 0.95), # # KPI measured: must match your dep_var @@ -253,7 +283,6 @@ print(InputCollect) # ) # InputCollect <- robyn_inputs(InputCollect = InputCollect, calibration_input = calibration_input) - ################################################################ #### Step 2b: For known model specification, setup in one single step @@ -279,10 +308,8 @@ print(InputCollect) # ,calibration_input = calibration_input # as in 2a-4 above # ) -#### Check spend exposure fit if available -if (length(InputCollect$exposure_vars) > 0) { - lapply(InputCollect$modNLS$plots, plot) -} +#### Check spend exposure fit and consider channel split if applicable +InputCollect$ExposureCollect$plot_spend_exposure ##### Manually save and import InputCollect as JSON file # robyn_write(InputCollect, dir = "~/Desktop") @@ -300,8 +327,8 @@ OutputModels <- robyn_run( cores = NULL, # NULL defaults to (max available - 1) iterations = 2000, # 2000 recommended for the dummy dataset with no calibration trials = 5, # 5 recommended for the dummy dataset - ts_validation = TRUE, # 3-way-split time series for NRMSE validation. - add_penalty_factor = FALSE # Experimental feature. Use with caution. + ts_validation = FALSE, # 3-way-split time series for NRMSE validation. + add_penalty_factor = FALSE # Experimental feature to add more flexibility ) print(OutputModels) @@ -311,8 +338,8 @@ OutputModels$convergence$moo_distrb_plot OutputModels$convergence$moo_cloud_plot ## Check time-series validation plot (when ts_validation == TRUE) -# Read more and replicate results: ?ts_validation -if (OutputModels$ts_validation) OutputModels$ts_validation_plot +## Read more and replicate results: ?ts_validation +# if (OutputModels$ts_validation) OutputModels$ts_validation_plot ## Calculate Pareto fronts, cluster and export results and plots. See ?robyn_outputs OutputCollect <- robyn_outputs( @@ -322,9 +349,9 @@ OutputCollect <- robyn_outputs( # calibration_constraint = 0.1, # range c(0.01, 0.1) & default at 0.1 csv_out = "pareto", # "pareto", "all", or NULL (for none) clusters = TRUE, # Set to TRUE to cluster similar models by ROAS. See ?robyn_clusters - export = create_files, # this will create files locally + export = TRUE, # this will create files locally plot_folder = robyn_directory, # path for plots exports and files creation - plot_pareto = create_files # Set to FALSE to deactivate plotting and saving model one-pagers + plot_pareto = TRUE # Set to FALSE to deactivate plotting and saving model one-pagers ) print(OutputCollect) @@ -341,10 +368,10 @@ print(OutputCollect) ## Compare all model one-pagers and select one that mostly reflects your business reality print(OutputCollect) -select_model <- "1_122_7" # Pick one of the models from OutputCollect to proceed +select_model <- "5_257_2" # Pick one of the models from OutputCollect to proceed #### Version >=3.7.1: JSON export and import (faster and lighter than RDS files) -ExportedModel <- robyn_write(InputCollect, OutputCollect, select_model, export = create_files) +ExportedModel <- robyn_write(InputCollect, OutputCollect, select_model, export = TRUE) print(ExportedModel) # To plot any model's one-pager: @@ -367,7 +394,7 @@ print(ExportedModel) # Run ?robyn_allocator to check parameter definition # NOTE: The order of constraints should follow: -InputCollect$paid_media_spends +InputCollect$paid_media_selected # Scenario "max_response": "What's the max. return given certain spend?" # Example 1: max_response default setting: maximize response for latest month @@ -380,8 +407,7 @@ AllocatorCollect1 <- robyn_allocator( channel_constr_low = 0.7, channel_constr_up = c(1.2, 1.5, 1.5, 1.5, 1.5), # channel_constr_multiplier = 3, - scenario = "max_response", - export = create_files + scenario = "max_response" ) # Print & plot allocator's output print(AllocatorCollect1) @@ -393,12 +419,11 @@ AllocatorCollect2 <- robyn_allocator( OutputCollect = OutputCollect, select_model = select_model, date_range = "last_10", # Last 10 periods, same as c("2018-10-22", "2018-12-31") - total_budget = 5000000, # Total budget for date_range period simulation + total_budget = 1500000, # Total budget for date_range period simulation channel_constr_low = c(0.8, 0.7, 0.7, 0.7, 0.7), - channel_constr_up = c(1.2, 1.5, 1.5, 1.5, 1.5), + channel_constr_up = 1.5, channel_constr_multiplier = 5, # Customise bound extension for wider insights - scenario = "max_response", - export = create_files + scenario = "max_response" ) print(AllocatorCollect2) plot(AllocatorCollect2) @@ -412,51 +437,31 @@ AllocatorCollect3 <- robyn_allocator( InputCollect = InputCollect, OutputCollect = OutputCollect, select_model = select_model, - # date_range = NULL, # Default last month as initial period + #channel_constr_low = 0.1, + #channel_constr_up = 10, + # date_range = NULL, # Default: "all" available dates scenario = "target_efficiency", - # target_value = 2, # Customize target ROAS or CPA value - export = create_files + # target_value = 5 # Customize target ROAS or CPA value ) print(AllocatorCollect3) plot(AllocatorCollect3) # Example 4: Customize target_value for ROAS or CPA (using json_file) -json_file = "~/Desktop/Robyn_202302221206_init/RobynModel-1_117_11.json" +json_file = "~/Desktop/Robyn_202412181043_init/RobynModel-5_257_2.json" AllocatorCollect4 <- robyn_allocator( json_file = json_file, # Using json file from robyn_write() for allocation dt_input = dt_simulated_weekly, dt_holidays = dt_prophet_holidays, - date_range = NULL, # Default last month as initial period + # date_range = NULL, scenario = "target_efficiency", target_value = 2, # Customize target ROAS or CPA value - plot_folder = "~/Desktop/my_dir", - plot_folder_sub = "my_subdir", - export = create_files + plot_folder = "~/Desktop", + plot_folder_sub = "my_subdir" ) ## A csv is exported into the folder for further usage. Check schema here: ## https://github.com/facebookexperimental/Robyn/blob/main/demo/schema.R -## QA optimal response -# Pick any media variable: InputCollect$all_media -select_media <- "search_S" -# For paid_media_spends set metric_value as your optimal spend -metric_value <- AllocatorCollect1$dt_optimOut$optmSpendUnit[ - AllocatorCollect1$dt_optimOut$channels == select_media -]; metric_value -# # For paid_media_vars and organic_vars, manually pick a value -# metric_value <- 10000 - -## Saturation curve for adstocked metric results (example) -robyn_response( - InputCollect = InputCollect, - OutputCollect = OutputCollect, - select_model = select_model, - metric_name = select_media, - metric_value = metric_value, - date_range = "last_5" -) - ################################################################ #### Step 6: Model refresh based on selected model and saved results @@ -469,24 +474,23 @@ robyn_response( # Provide JSON file with your InputCollect and ExportedModel specifications # It can be any model, initial or a refresh model -json_file <- "~/Desktop/Robyn_202211211853_init/RobynModel-1_100_6.json" RobynRefresh <- robyn_refresh( json_file = json_file, dt_input = dt_simulated_weekly, dt_holidays = dt_prophet_holidays, - refresh_steps = 13, - refresh_iters = 1000, # 1k is an estimation - refresh_trials = 1 + refresh_steps = 4, + refresh_iters = 2000, + refresh_trials = 5 ) # Now refreshing a refreshed model, following the same approach -json_file_rf1 <- "~/Desktop/Robyn_202208231837_init/Robyn_202208231841_rf1/RobynModel-1_12_5.json" +json_file_rf1 <- "~/Desktop/Robyn_202412181043_init/Robyn_202412181054_rf1/RobynModel-1_133_7.json" RobynRefresh <- robyn_refresh( json_file = json_file_rf1, dt_input = dt_simulated_weekly, dt_holidays = dt_prophet_holidays, - refresh_steps = 7, - refresh_iters = 1000, # 1k is an estimation - refresh_trials = 1 + refresh_steps = 4, + refresh_iters = 2000, + refresh_trials = 5 ) # Continue with refreshed new InputCollect, OutputCollect, select_model values @@ -519,7 +523,7 @@ Response <- robyn_response( InputCollect = InputCollect, OutputCollect = OutputCollect, select_model = select_model, - metric_name = "facebook_S" + metric_name = "facebook_I" ) Response$plot @@ -532,14 +536,14 @@ Response$plot # ) ## Get the "next 100 dollar" marginal response on Spend1 -Spend1 <- 20000 +Spend1 <- 80000 Response1 <- robyn_response( InputCollect = InputCollect, OutputCollect = OutputCollect, select_model = select_model, - metric_name = "facebook_S", + metric_name = "facebook_I", metric_value = Spend1, # total budget for date_range - date_range = "last_1" # last two periods + date_range = "last_10" # last two periods ) Response1$plot @@ -548,36 +552,13 @@ Response2 <- robyn_response( InputCollect = InputCollect, OutputCollect = OutputCollect, select_model = select_model, - metric_name = "facebook_S", + metric_name = "facebook_I", metric_value = Spend2, - date_range = "last_1" + date_range = "last_10" ) # ROAS for the 100$ from Spend1 level -(Response2$response_total - Response1$response_total) / (Spend2 - Spend1) - -## Get response from for a given budget and date_range -Spend3 <- 100000 -Response3 <- robyn_response( - InputCollect = InputCollect, - OutputCollect = OutputCollect, - select_model = select_model, - metric_name = "facebook_S", - metric_value = Spend3, # total budget for date_range - date_range = "last_5" # last 5 periods -) -Response3$plot - -## Example of getting paid media exposure response curves -# imps <- 10000000 -# response_imps <- robyn_response( -# InputCollect = InputCollect, -# OutputCollect = OutputCollect, -# select_model = select_model, -# metric_name = "facebook_I", -# metric_value = imps -# ) -# response_imps$response_total / imps * 1000 -# response_imps$plot +(Response2$sim_mean_response - Response1$sim_mean_response) / + (Response2$sim_mean_spend - Response1$sim_mean_spend) ## Example of getting organic media exposure response curves sendings <- 30000 @@ -586,11 +567,11 @@ response_sending <- robyn_response( OutputCollect = OutputCollect, select_model = select_model, metric_name = "newsletter", - metric_value = sendings + metric_value = sendings, + date_range = "last_10" ) -# response per 1000 sendings -response_sending$response_total / sendings * 1000 -response_sending$plot +# Simulated cost per thousand sendings +response_sending$sim_mean_spend / response_sending$sim_mean_response * 1000 ################################################################ #### Optional: recreate old models and replicate results @@ -610,7 +591,7 @@ robyn_write(InputCollect, OutputCollect, select_model) ############ READ ############ # Recreate `InputCollect` and `OutputCollect` objects # Pick any exported model (initial or refreshed) -json_file <- "~/Desktop/Robyn_202208231837_init/RobynModel-1_100_6.json" +json_file <- "~/Desktop/Robyn_202412181043_init/RobynModel-5_257_2.json" # Optional: Manually read and check data stored in file json_data <- robyn_read(json_file) @@ -625,12 +606,12 @@ InputCollectX <- robyn_inputs( # Re-create OutputCollect OutputCollectX <- robyn_run( InputCollect = InputCollectX, - json_file = json_file, - export = create_files) + json_file = json_file + ) # Or re-create both by simply using robyn_recreate() RobynRecreated <- robyn_recreate( - json_file = "~/Desktop/Robyn_202303131448_init/RobynModel-1_103_7.json", + json_file = json_file, dt_input = dt_simulated_weekly, dt_holidays = dt_prophet_holidays, quiet = FALSE) diff --git a/python/LICENSE b/python/LICENSE new file mode 100644 index 000000000..1b277b98b --- /dev/null +++ b/python/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) Meta Platforms, Inc. and its affiliates. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/python/README.md b/python/README.md new file mode 100644 index 000000000..e5c6a4f69 --- /dev/null +++ b/python/README.md @@ -0,0 +1,70 @@ +# Robyn: Continuous & Semi-Automated MMM +### The Open Source Marketing Mix Model Package from Meta Marketing Science + + +--- + +## Introduction + + * **What is Robyn?**: Robyn is an experimental, semi-automated and open-sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. It uses various machine learning techniques (Ridge regression, multi-objective evolutionary algorithm for hyperparameter optimization, time-series decomposition for trend & season, gradient-based optimization for budget allocation, clustering, etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich data sources. + + * **Why are we doing this?**: MMM used to be a resource-intensive technique that was only affordable for "big players". As the privacy needs of the measurement landscape evolve, there's a clear trend of increasing demand for modern MMM as a privacy-safe solution. At Meta Marketing Science, our mission is to help all businesses grow by transforming marketing practices grounded in data and science. It's highly aligned with our mission to democratizing MMM and making it accessible for advertisers of all sizes. With Project Robyn, we want to contribute to the measurement landscape, inspire the industry and build a community for exchange and innovation around the future of MMM and Marketing Science in general. + +## Quick start for Python (Beta) + + The Python version of Robyn is rewritten from Robyn's R package version `3.11.1` to Python using object oriented programming principles and modular architecture for a robust solution. It was developed by utilizing various LLMs and AI workflows. As is common with any AI-based solutions, there may be potential challenges in translating code from one language to another. + In this case, we anticipate that there could be some issues in the translation from R to Python. However, we believe in the power of community collaboration and open-source contribution. Therefore, we are opening this project to the community to participate and contribute. + Together, we can address and resolve any issues that may arise, enhancing the functionality and efficiency of the Python version of Robyn. We look forward to your contributions and to the continuous improvement of this project. + +**1. Installing the package** + + * Install Robyn latest package version: +```{r} +## Pypi +pip3 install robynpy + +## DEV VERSION +# if you are pulling source from github, install dependencies using requirements.txt +pip3 install -r requirements.txt +``` + +**2. Getting started** + + * python/src/robyn/tutorials contains tutorials for most common scenarios. Tutorials use simulated dataset provided in the package. + + * There are two ways of running Python Robyn; one is `tutorial1.ipynb` and second is `tutorial1_src.ipynb`. + +**3. Running end-to-end** + +Option 1: + * `tutorial1.ipynb` is the main notebook that runs the end-to-end flow. It is designed for majority of the users who would prefer a one click solution that runs the robyn flow end-to-end with minimal knowledge of the underlying logic. It should run without any changes required if you wish to use the simulated dataset for testing purposes. + + * This notebook uses APIs available in `python/src/robyn/robyn.py` to set the configs, run feature engineering, run model training, evaluate models with clustering, generate one pagers and perform budget allocation. + + * Change any of the configs directly in the notebook and avoid changes to robyn.py for what can be configurable. + +Option 2: + * `tutorial1_src.ipynb` runs the end-to-end flow of robyn python but with a lot more flexibility. It is designed for users who would like to have more control over which modules are and aren't run (ie. skipping clustering/one pager plots/budget allocation etc.). It should run without any changes required if you wish to use the simulated dataset for testing purposes. + + * This notebook doesn't use APIs available in `python/src/robyn/robyn.py` but instead, calls the modules directly with the appropriate parameters. In this way, it is more flexible but still expects the users to understand the underlying logic that may change when using various parameter values. + +## Helpful Links + + * Visit our [website](https://facebookexperimental.github.io/Robyn/) to explore more details about Project Robyn. + + * Join our [public group](https://www.facebook.com/groups/robyn/) to exchange with other users and interact with team Robyn. + + * Take Meta's [official Robyn blueprint course](https://www.facebookblueprint.com/student/path/253121-marketing-mix-models?utm_source=readme) online + +## License + +Meta's Robyn is MIT licensed, as found in the LICENSE file. + +- Terms of Use - https://opensource.facebook.com/legal/terms +- Privacy Policy - https://opensource.facebook.com/legal/privacy +- Defensive Publication - https://www.tdcommons.org/dpubs_series/4627/ + +## Contact + +* gufeng@meta.com, Gufeng Zhou, Marketing Science, Robyn creator +* igorskokan@meta.com, Igor Skokan, Marketing Science Director, open source diff --git a/python/docs/robyn/modeling/pareto/response_curve.md b/python/docs/robyn/modeling/pareto/response_curve.md new file mode 100644 index 000000000..1a1cb865c --- /dev/null +++ b/python/docs/robyn/modeling/pareto/response_curve.md @@ -0,0 +1,177 @@ +# CLASS +## MetricDateInfo +* A data class used to store information about metric locations and updated date ranges. +* This class is part of a module related to metrics handling. + +# CONSTRUCTORS +## MetricDateInfo `(metric_loc: pd.Series, date_range_updated: pd.Series)` +* `metric_loc`: A pandas Series that contains the location of metrics. +* `date_range_updated`: A pandas Series that contains the updated date range for the metrics. +### USAGE +* Use this constructor to create an instance of `MetricDateInfo` with the specified metric location and date range. +### IMPL +* Initializes the data class with two main attributes: `metric_loc` and `date_range_updated`. + +--- + +# CLASS +## MetricValueInfo +* A data class used to store updated metric values and all updated values. +* This class is part of a module related to metrics handling. + +# CONSTRUCTORS +## MetricValueInfo `(metric_value_updated: np.ndarray, all_values_updated: pd.Series)` +* `metric_value_updated`: A numpy array that contains updated metric values. +* `all_values_updated`: A pandas Series that contains all updated values. +### USAGE +* Use this constructor to create an instance of `MetricValueInfo` with the specified updated metric values. +### IMPL +* Initializes the data class with two main attributes: `metric_value_updated` and `all_values_updated`. + +--- + +# CLASS +## ResponseOutput +* A data class that encapsulates the results of a response calculation, including metric names, dates, inputs, responses, and a plot. +* This class is part of a module related to response handling. + +# CONSTRUCTORS +## ResponseOutput `(metric_name: str, date: pd.Series, input_total: np.ndarray, input_carryover: np.ndarray, input_immediate: np.ndarray, response_total: np.ndarray, response_carryover: np.ndarray, response_immediate: np.ndarray, usecase: str, plot: plt.Figure)` +* `metric_name`: A string representing the name of the metric. +* `date`: A pandas Series representing the date range. +* `input_total`: A numpy array representing the total input values. +* `input_carryover`: A numpy array representing the carryover input values. +* `input_immediate`: A numpy array representing the immediate input values. +* `response_total`: A numpy array representing the total response values. +* `response_carryover`: A numpy array representing the carryover response values. +* `response_immediate`: A numpy array representing the immediate response values. +* `usecase`: A string representing the use case. +* `plot`: A matplotlib Figure object representing the plot of the response. +### USAGE +* Use this constructor to create an instance of `ResponseOutput` with the specified attributes related to metric response. +### IMPL +* Initializes the data class with attributes to store details of the response calculation. + +--- + +# CLASS +## UseCase +* This class is an ENUM. +* Represents different types of use cases for response calculation. +* Enum fields: + - `ALL_HISTORICAL_VEC`: Represents all historical vectors. + - `SELECTED_HISTORICAL_VEC`: Represents selected historical vectors. + - `TOTAL_METRIC_DEFAULT_RANGE`: Represents total metric with default range. + - `TOTAL_METRIC_SELECTED_RANGE`: Represents total metric with selected range. + - `UNIT_METRIC_DEFAULT_LAST_N`: Represents unit metric with default last N. + - `UNIT_METRIC_SELECTED_DATES`: Represents unit metric with selected dates. + +--- + +# CLASS +## ResponseCurveCalculator +* This class is responsible for calculating response curves based on media mix modeling (MMM) data, model outputs, and hyperparameters. +* Part of a larger module that handles data transformations and response calculations. + +# CONSTRUCTORS +## ResponseCurveCalculator `(mmm_data: MMMData, model_outputs: ModelOutputs, hyperparameter: Hyperparameters)` +* `mmm_data`: An instance of `MMMData` containing media mix modeling data. +* `model_outputs`: An instance of `ModelOutputs` containing model output data. +* `hyperparameter`: An instance of `Hyperparameters` containing model hyperparameters. +### USAGE +* Use this constructor to create an instance of `ResponseCurveCalculator` with the necessary data and hyperparameters to compute response curves. +### IMPL +* Initializes the class with instances of `MMMData`, `ModelOutputs`, and `Hyperparameters`. +* Initializes a transformation object based on the provided `MMMData`. + +# METHODS +## `calculate_response(select_model: str, metric_name: str, metric_value: Optional[Union[float, list[float]]] = None, date_range: Optional[str] = None, quiet: bool = False, dt_hyppar: pd.DataFrame = pd.DataFrame(), dt_coef: pd.DataFrame = pd.DataFrame()) -> ResponseOutput` +### USAGE +* `select_model`: A string specifying which model to use for the calculation. +* `metric_name`: A string specifying the name of the metric to analyze. +* `metric_value`: Optional argument specifying a float or list of floats for metric values. +* `date_range`: Optional string specifying the date range to consider. +* `quiet`: Boolean flag to suppress output. +* `dt_hyppar`: A pandas DataFrame containing hyperparameter values. +* `dt_coef`: A pandas DataFrame containing coefficient values. +* Returns an instance of `ResponseOutput`. +### IMPL +* Determines the use case based on provided metric value and date range. +* Checks the type of metric (spend, exposure, organic) using `_check_metric_type`. +* Processes date ranges and metric values using helper functions `_check_metric_dates` and `_check_metric_value`. +* Transforms exposure to spend if necessary using `_transform_exposure_to_spend`. +* Applies adstock transformation using `_get_channel_hyperparams` and `transform_adstock`. +* Applies saturation transformation using `_get_saturation_params` and `saturation_hill`. +* Calculates final response values using model coefficients. +* Returns a `ResponseOutput` with calculated response data. + +## `_which_usecase(metric_value: Optional[Union[float, list[float]]], date_range: Optional[str]) -> UseCase` +### USAGE +* Determines the specific use case based on metric value and date range. +* Returns an appropriate `UseCase` enum member. +### IMPL +* Uses conditional logic to determine the use case based on the presence and type of `metric_value` and `date_range`. + +## `_check_metric_type(metric_name: str) -> Literal["spend", "exposure", "organic"]` +### USAGE +* Determines the type of metric based on its name. +* Returns one of the literals: "spend", "exposure", or "organic". +### IMPL +* Checks the metric name against predefined lists in `MMMData` to identify its type. +* Raises a `ValueError` if the metric type is unknown. + +## `_check_metric_dates(date_range: Optional[str], all_dates: pd.Series, quiet: bool) -> MetricDateInfo` +### USAGE +* Processes the given date range and returns the corresponding metric location and updated date range. +* Returns an instance of `MetricDateInfo`. +### IMPL +* Uses conditional logic to handle different date range formats. +* Updates the date range based on the provided or default rolling window values. +* Prints the updated date range if `quiet` is False. + +## `_check_metric_value(metric_value: Optional[Union[float, list[float]]], metric_name: str, all_values: pd.Series, metric_loc: Union[slice, pd.Series]) -> MetricValueInfo` +### USAGE +* Processes the given metric value and returns updated metric values. +* Returns an instance of `MetricValueInfo`. +### IMPL +* Updates metric values based on the provided input or uses default values. +* Raises a `ValueError` if the length of `metric_value` does not match the selected date range. + +## `_transform_exposure_to_spend(metric_name: str, metric_value_updated: np.ndarray, all_values_updated: pd.Series, metric_loc: Union[slice, pd.Series]) -> pd.Series` +### USAGE +* Transforms exposure values to spend values based on predefined models. +* Returns a pandas Series of updated values. +### IMPL +* Determines the appropriate model (non-linear or linear) based on R-squared values. +* Calculates and updates spend values using model parameters. + +## `_get_spend_name(metric_name: str) -> str` +### USAGE +* Retrieves the spend name associated with a given metric name. +* Returns the corresponding spend name as a string. +### IMPL +* Uses the index of the metric name in `paid_media_vars` to find the corresponding spend name. + +## `_get_channel_hyperparams(select_model: str, hpm_name: str, dt_hyppar: pd.DataFrame) -> ChannelHyperparameters` +### USAGE +* Retrieves hyperparameters for the specified channel and model. +* Returns an instance of `ChannelHyperparameters`. +### IMPL +* Extracts hyperparameter values from `dt_hyppar` based on the selected model and adstock type. + +## `_get_saturation_params(select_model: str, hpm_name: str, dt_hyppar: pd.DataFrame) -> ChannelHyperparameters` +### USAGE +* Retrieves saturation parameters for the specified channel and model. +* Returns an instance of `ChannelHyperparameters`. +### IMPL +* Extracts saturation parameter values from `dt_hyppar` based on the selected model. + +## `_create_response_plot(m_adstockedRW: np.ndarray, m_response: np.ndarray, input_total: np.ndarray, response_total: np.ndarray, input_carryover: np.ndarray, response_carryover: np.ndarray, input_immediate: np.ndarray, response_immediate: np.ndarray, metric_name: str, metric_type: Literal["spend", "exposure", "organic"], date_range_updated: pd.Series) -> plt.Figure` +### USAGE +* Creates a plot visualizing the response curve based on inputs and responses. +* Returns a matplotlib Figure object. +### IMPL +* Plots the response curve and scatter plots for total, carryover, and immediate responses. +* Configures plot labels, titles, and legends based on metric type and data. +* Optionally includes a detailed subtitle if the input total is unique. +* Adds a text description of the response period at the bottom of the plot. \ No newline at end of file diff --git a/python/docs/tests/robyn/modeling/feature_engineering.md b/python/docs/tests/robyn/modeling/feature_engineering.md new file mode 100644 index 000000000..4b909f406 --- /dev/null +++ b/python/docs/tests/robyn/modeling/feature_engineering.md @@ -0,0 +1,94 @@ +# CLASS +## FeatureEngineering +* A class used to perform feature engineering for Marketing Mix Modeling (MMM) data. +* Part of the "robyn" package, handling data transformations and model executions. +* Involves methods for data preparation, adstock transformations, decomposition using Prophet, and model fitting. + +# CONSTRUCTORS +## `__init__(mmm_data: MMMData, hyperparameters: Hyperparameters, holidays_data: Optional[HolidaysData] = None)` +* Initializes the FeatureEngineering class with the given MMM data, hyperparameters, and optional holidays data. +### USAGE +* Use this constructor to create an instance of FeatureEngineering with the necessary data and configuration for feature engineering. +### IMPL +* Ensure that the MMMData, Hyperparameters, and optional HolidaysData inputs are correctly assigned to the class attributes. +* Verify that a logger is properly initialized for logging information and warnings. + +# METHODS +## `perform_feature_engineering(quiet: bool = False) -> FeaturizedMMMData` +### USAGE +* Initiates the feature engineering process on the provided data, with optional logging based on the quiet parameter. +### IMPL +* Mock the dependencies `_prepare_data`, `_prophet_decomposition`, `_create_rolling_window_data`, `_calculate_media_cost_factor`, and `_run_models` in sequence. +* Validate the transformation of the initial dataset into a featurized form with rolling window adjustments, media cost factors, and model results. +* Execute assertions to confirm that the result is an instance of FeaturizedMMMData with expected DataFrame attributes. + +## `_prepare_data() -> pd.DataFrame` +### USAGE +* Transforms the initial dataset by converting date and dependent variable columns to the required format. +### IMPL +* Mock the MMMData dependency to return a copy of the data with specified columns. +* Assert the transformation of date_var to a string format and the presence of dep_var and competitor_sales_B with correct types. + +## `_create_rolling_window_data(dt_transform: pd.DataFrame) -> pd.DataFrame` +### USAGE +* Creates a dataset with rolling window constraints based on provided start and end dates. +### IMPL +* Mock the MMMData to return window_start and window_end values. +* Assert that the resulting dataset respects the defined window boundaries, raising exceptions if constraints are violated. + +## `_calculate_media_cost_factor(dt_input_roll_wind: pd.DataFrame) -> pd.Series` +### USAGE +* Computes the media cost factor for the given rolling window dataset. +### IMPL +* Test with various scenarios of media spends (valid, zero, missing, negative) to confirm correct calculation of cost factors. +* Ensure handling of division by zero or missing data without raising unexpected exceptions. + +## `_run_models(dt_modRollWind: pd.DataFrame, media_cost_factor: float) -> Dict[str, Dict[str, Any]]` +### USAGE +* Executes model fitting for each paid media variable and returns results. +### IMPL +* Mock the `_fit_spend_exposure` method to simulate model fitting for each media variable. +* Verify the output dictionary structure, confirming that results and plots are populated as expected based on input data. + +## `_fit_spend_exposure(dt_modRollWind: pd.DataFrame, paid_media_var: str, media_cost_factor: float) -> Dict[str, Any]` +### USAGE +* Fits a model to relate media spend to exposure, selecting between nonlinear and linear models based on R-squared values. +### IMPL +* Mock the MMMData to provide media spend and exposure data. +* Simulate curve fitting and linear model fitting, comparing R-squared values to determine the best model. +* Assert correct handling of empty data or exceptions, ensuring proper fallbacks and logging of warnings. + +## `_hill_function(x, alpha, gamma)` +### USAGE +* Applies the Hill function transformation to a given input value. +### IMPL +* Test various input values for x, alpha, and gamma, confirming the mathematical correctness of the transformation. +* Include edge cases such as zero or negative values to verify the function handles them without errors. + +## `_prophet_decomposition(dt_mod: pd.DataFrame) -> pd.DataFrame` +### USAGE +* Performs decomposition using Prophet, adding trend, seasonality, and holiday effects to the dataset. +### IMPL +* Mock the HolidaysData to provide prophet variables and holiday data. +* Test different prophet configurations, ensuring the resulting DataFrame includes the expected decomposition components. + +## `_set_holidays(dt_transform: pd.DataFrame, dt_holidays: pd.DataFrame, interval_type: str) -> pd.DataFrame` +### USAGE +* Integrates holidays into the dataset according to the specified interval type. +### IMPL +* Confirm the proper setting of holidays for daily, weekly, and monthly intervals, raising exceptions for invalid types. +* Test with different holiday datasets to ensure correct grouping and aggregation based on interval type. + +## `_apply_adstock(x: pd.Series, params: ChannelHyperparameters) -> pd.Series` +### USAGE +* Applies adstock transformation using specified parameters to the input series. +### IMPL +* Test for each adstock type (GEOMETRIC, WEIBULL_CDF, WEIBULL_PDF) to confirm transformation correctness. +* Validate that unsupported adstock types raise the appropriate exceptions with clear messages. + +## `_weibull_adstock(x: pd.Series, shape: float, scale: float) -> pd.Series` +### USAGE +* Applies Weibull adstock transformation to the input series based on shape and scale parameters. +### IMPL +* Test with positive, zero, and negative values for shape and scale, confirming expected behavior and error handling. +* Use series of various lengths to ensure the method scales correctly with input size. \ No newline at end of file diff --git a/python/docs/tests/robyn/modeling/pareto/test_response_curve.md b/python/docs/tests/robyn/modeling/pareto/test_response_curve.md new file mode 100644 index 000000000..eb13aa9ed --- /dev/null +++ b/python/docs/tests/robyn/modeling/pareto/test_response_curve.md @@ -0,0 +1,15 @@ +# CLASS +## ResponseCurveCalculator +- This class is responsible for calculating response curves based on media mix modeling (MMM) data, model outputs, and hyperparameters. +- Part of a larger module that handles data transformations and response calculations. + +# CONSTRUCTORS +## ResponseCurveCalculator `(mmm_data: MMMData, model_outputs: ModelOutputs, hyperparameter: Hyperparameters)` +### USAGE +- Use this constructor to create an instance of `ResponseCurveCalculator` with the necessary data and hyperparameters to compute response curves. + +### IMPL +- The constructor should be tested by initializing the `ResponseCurveCalculator` class with mock instances of `MMMData`, `ModelOutputs`, and `Hyperparameters`. +- Verify that the instance variables `mmm_data`, `model_outputs`, and `hyperparameter` are correctly assigned. +- Ensure that `self.transformation` is initialized as an instance of the `Transformation` class with the `mmm_data` passed correctly. +- Test the constructor with edge cases like passing `None` or incorrect types to ensure proper error handling. \ No newline at end of file diff --git a/python/pyproject.toml b/python/pyproject.toml new file mode 100644 index 000000000..cf42e58f5 --- /dev/null +++ b/python/pyproject.toml @@ -0,0 +1,46 @@ +[build-system] +requires = ["setuptools>=61.0"] +build-backend = "setuptools.build_meta" + +[project] +name = "robynpy" +version = "0.1.2" +authors = [ + { name="Gufeng Zhou", email="gufeng@meta.com" }, + { name="Igor Skokan", email="igorskokan@meta.com" }, +] +description = "Robyn: Continuous & Semi-Automated MMM. The Open Source Marketing Mix Model Package from Meta Marketing Science" +readme = "README.md" +requires-python = ">=3.8" +classifiers = [ + "Programming Language :: Python :: 3", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", +] +dependencies = [ + "pandas", + "numpy>=1.20.0", + "matplotlib", + "scikit-learn", + "prophet", + "scipy", + "lmfit", + "plotnine", + "nevergrad", + "PyQt6", + "seaborn", + "tqdm", + "rpy2", + "pytest", + "plotly", + "nlopt", + "cmake", + "ipykernel", +] +[tool.setuptools.packages.find] +where = ["src"] +[tool.setuptools.package-data] +"*" = ["*.csv"] +[project.urls] +Homepage = "https://github.com/facebookexperimental/Robyn" +Issues = "https://github.com/facebookexperimental/Robyn/issues" \ No newline at end of file diff --git a/python/requirements.txt b/python/requirements.txt new file mode 100644 index 000000000..fc6b1a28c --- /dev/null +++ b/python/requirements.txt @@ -0,0 +1,17 @@ +pandas==2.2.3 +numpy==2.1.1 +matplotlib==3.9.2 +scikit-learn==1.5.2 +prophet==1.1.6 +scipy==1.13.1 +lmfit==1.3.2 +plotnine==0.13.6 +nevergrad==1.0.5 +PyQt6==6.7.1 +seaborn==0.13.2 +tqdm==4.66.5 +rpy2==3.5.16 +plotly==5.24.1 +pytest==8.3.3 +nlopt==2.8.0 +ipykernel==6.29.5 \ No newline at end of file diff --git a/python/spec/src/robyn/modeling/pareto/hill_calculator.md b/python/spec/src/robyn/modeling/pareto/hill_calculator.md new file mode 100644 index 000000000..6507de05f --- /dev/null +++ b/python/spec/src/robyn/modeling/pareto/hill_calculator.md @@ -0,0 +1,50 @@ +# CLASS +## HillCalculator +* The `HillCalculator` class is responsible for computing the necessary parameters for Hill function modeling, particularly in the domain of marketing mix modeling (MMM). +* It processes input data related to MMM and the output from models to derive the required alphas, inflexions, and sorted coefficients. +* Utilizes Pandas DataFrames and NumPy libraries for data manipulation and mathematical operations. + +# CONSTRUCTORS +## HillCalculator `(mmmdata: MMMData, model_outputs: ModelOutputs, dt_hyppar: pd.DataFrame, dt_coef: pd.DataFrame, media_spend_sorted: List[str], select_model: str, chn_adstocked: pd.DataFrame = None)` +* **mmmdata**: This is an instance of the `MMMData` class, which includes the marketing mix modeling data. +* **model_outputs**: An instance of `ModelOutputs` that contains results from the model execution. +* **dt_hyppar**: A Pandas DataFrame that holds hyperparameter data, specifically alphas and gammas. +* **dt_coef**: A Pandas DataFrame that includes coefficients for different media channels. +* **media_spend_sorted**: A list of strings representing the sorted order of media spending channels. +* **select_model**: A string specifying the chosen model ID for filtering purposes. +* **chn_adstocked**: An optional DataFrame for precomputed adstocked media data; if not provided, it will be computed later. + +### USAGE +* This constructor is used to initialize a `HillCalculator` instance with all the essential data for performing calculations. +* It should be employed when you need to compute Hill parameters based on a specific set of MMM data and model outputs. + +### IMPL +* Initializes class attributes `mmmdata`, `model_outputs`, `dt_hyppar`, `dt_coef`, `media_spend_sorted`, `select_model`, and `chn_adstocked`. +* If `chn_adstocked` is not provided, it will be computed using the `_get_chn_adstocked_from_output_collect` method at a later stage. + +# METHODS +## `_get_chn_adstocked_from_output_collect() -> pd.DataFrame` +### USAGE +* This method retrieves adstocked media data from the `model_outputs` if `chn_adstocked` is not precomputed. +* It filters and slices the `media_vec_collect` DataFrame to acquire adstocked media data for the selected model. + +### IMPL +* Filters the `media_vec_collect` DataFrame from `model_outputs` to include only rows where the 'type' column is 'adstockedMedia' and 'solID' matches `select_model`. +* Selects columns based on the `media_spend_sorted` list to ensure only relevant media channels are included. +* Slices the DataFrame according to the `window_start` and `window_end` indices specified in `mmmdata.mmmdata_spec`. +* Returns the filtered and sliced DataFrame. + +## `get_hill_params() -> Dict[str, Any]` +### USAGE +* Calculates Hill parameters: alphas, inflexions, and sorted coefficients, which are crucial for constructing Hill functions within the MMM framework. +* This method leverages input data and may utilize `_get_chn_adstocked_from_output_collect` if `chn_adstocked` was not initially provided. + +### IMPL +* Extracts alphas and gammas for each media channel from `dt_hyppar` by using a regex pattern to match column names `*_alphas` and `*_gammas`. +* If `chn_adstocked` is `None`, invokes `_get_chn_adstocked_from_output_collect()` to calculate it. +* Computes inflexions for each media channel by performing a weighted summation of the minimum and maximum values in the `chn_adstocked` DataFrame using the retrieved gammas. +* Retrieves coefficients from `dt_coef` and sorts them according to the order specified in `media_spend_sorted`. +* Returns a dictionary containing: + - A list of `alphas`. + - A list of computed `inflexions`. + - A list of `coefs_sorted` based on the sorted media spend. \ No newline at end of file diff --git a/python/spec/src/robyn/visualization/allocator_plotter.md b/python/spec/src/robyn/visualization/allocator_plotter.md new file mode 100644 index 000000000..7a2e78ea5 --- /dev/null +++ b/python/spec/src/robyn/visualization/allocator_plotter.md @@ -0,0 +1,305 @@ +# CLASS +## AllocationPlotter +* The `AllocationPlotter` class extends the BaseVisualizer class at this path: from robyn.visualization.base_visualizer import BaseVisualizer +* The `AllocationPlotter` class is designed to create visualizations for allocation results, aligning with a version implemented in R. +* It is part of a software module that likely deals with optimization or resource allocation, visualizing results stored in an `AllocationResult` object. +* The class utilizes the matplotlib library to generate plots with specific styling and color schemes. + +# CONSTRUCTORS +## `__init__(result: AllocationResult)` +* Initializes the `AllocationPlotter` with allocation results and default plot settings. + +### USAGE +* This constructor is used to create an instance of the `AllocationPlotter` class, requiring an `AllocationResult` object as an input, which contains the results that need to be visualized. + +### IMPL +* The `result` parameter is stored in the instance variable `self.result` and must be annotated with type: AllocationResult (from robyn.allocator.entities.allocation_results import AllocationResult). +* Matplotlib's "bmh" style is applied using `plt.style.use("bmh")`. +* The default plot settings are configured using `plt.rcParams` to set figure size, grid visibility, and axis spines. +* The standard figure size `(12, 8)` is stored in `self.fig_size`. +* A color palette is generated using `plt.cm.Set2(np.linspace(0, 1, 8))` and stored in `self.colors`. +* Default color values for plot elements are set: `self.current_color` to "lightgray", `self.optimal_color` to #4688C7, `self.positive_color` to #2ECC71, and `self.negative_color` to #E74C3C. + +# METHODS +## `plot_all() -> Dict[str, plt.Figure]` +### USAGE +* Generates all one-page plots for the allocation results and returns a dictionary mapping plot names to their respective figures. + +### IMPL +### IMPL +* Return Type: + * The method returns a dictionary where the keys are strings representing the names of different plots, and the values are matplotlib figure objects corresponding to each plot. +* Functionality: + * The method calls several other plotting methods within the class, each responsible for creating a specific type of plot related to allocation results. + * It aggregates the results of these plotting methods into a dictionary, making it easy to access each plot by name. +* Plot Types: + * "spend_allocation": Calls self.plot_spend_allocation() to generate a plot that visualizes how spending is allocated across different categories or channels. + * "response_curves": Calls self.plot_response_curves() to create plots that show the response curves, illustrating the relationship between spend and response. + * "efficiency_frontier": Calls self.plot_efficiency_frontier() to produce a plot that represents the efficiency frontier, highlighting optimal allocation strategies. + * "spend_vs_response": Calls self.plot_spend_vs_response() to generate a plot comparing spend against response, providing insights into the effectiveness of spending. + * "summary_metrics": Calls self.plot_summary_metrics() to create a plot summarizing key metrics from the allocation results. + +## `plot_spend_allocation() -> plt.Figure` +### USAGE +* Plots a comparison of media spend allocation between current and optimized states. + +### IMPL +* Return Type: + * Returns a matplotlib figure object that contains the spend allocation plot. +* Functionality: + * Input Validation: + *Checks if self.result is None. If it is, raises a ValueError with the message "No allocation results available. Call plot_all() first." This ensures that the method is only called when allocation results are available. + * Figure and Axes Creation: + * Uses plt.subplots() to create a figure (fig) and axes (ax) with a size specified by self.fig_size, which is set to (12, 8). + * Data Preparation: + * Retrieves the optimal_allocations DataFrame from self.result.optimal_allocations as attribute. + * Extracts the channel column values into a variable channels, which contains the names of the channels. + * Sets up an array x using np.arange(len(channels)) to represent the x-axis positions for each channel. + * Defines the width of the bars as 0.35. + * Bar Plotting: + * Current Spend Bars: + * Extracts the current_spend values from the DataFrame. + * Plots these values as bars on the axes using ax.bar(), with the following parameters: + * x - width / 2: Positions the bars slightly to the left of the center of each channel position. + * current_spend: The heights of the bars, representing current spend values. + * width: The width of the bars, set to 0.35. + * label="Current": Labels these bars as "Current" in the legend. + * color=self.current_color: Sets the bar color to self.current_color, which is "lightgray". + * edgecolor="gray": Sets the edge color of the bars to gray. + * alpha=0.7: Sets the transparency level of the bars to 70%. + * Optimized Spend Bars: + * Extracts the optimal_spend values from the DataFrame. + * Plots these values as bars on the axes using ax.bar(), with the following parameters: + * x + width / 2: Positions the bars slightly to the right of the center of each channel position. + * optimal_spend: The heights of the bars, representing optimized spend values. + * width: The width of the bars, set to 0.35. + * label="Optimized": Labels these bars as "Optimized" in the legend. + * color=self.optimal_color: Sets the bar color to self.optimal_color, which is "#4688C7" (steel blue). + * edgecolor="gray": Sets the edge color of the bars to gray. + * alpha=0.7: Sets the transparency level of the bars to 70%. + * Plot Customization: + * Sets the x-ticks on the axes to the positions in x. + * Labels the x-ticks with the channel names, rotating them 45 degrees for better readability and aligning them to the right. + * Sets the y-axis label to "Spend". + * Sets the plot title to "Media Spend Allocation". + * Adds a legend to the plot to distinguish between current and optimized spend bars. + * Percentage Change Labels: + * Iterates over each channel using enumerate(zip(current_spend, optimal_spend)). + * Calculates the percentage change from current to optimized spend for each channel using the formula ((opt / curr) - 1) * 100. + * Determines the color of the percentage change text based on whether the change is >= 0 (self.positive_color, "#2ECC71" - green) or negative (self.negative_color, "#E74C3C" - red). + * Places a text label above each pair of bars showing the percentage change, formatted to one decimal place, centered horizontally and positioned just above the taller bar. + * Layout Adjustment: + * Calls plt.tight_layout() to automatically adjust the subplot parameters to give specified padding, ensuring that labels and titles fit within the figure area. + +## `plot_response_curves() -> plt.Figure` +### USAGE +* Plots response curves with markers for current and optimal allocation points. + +### IMPL +* Return Type: + * Returns a matplotlib figure object containing the response curve plots. +* Functionality: + * Input Validation: + *Checks if self.result is None. If it is, raises a ValueError with the message "No allocation results available. Call plot_all() first." This ensures that the method is only called when allocation results are available. + * Data Preparation: + * Retrieves the response_curves DataFrame from self.result as attribute. + * Extracts unique channel names into the channels array. + * Determines the number of channels (n_channels). + * Sets the number of columns (ncols) for the subplot grid to the minimum of 3 or the number of channels. + * Calculates the number of rows (nrows) needed for the subplot grid using the formula (n_channels + ncols - 1) // ncols. + * Figure and Axes Creation: + * Uses plt.subplots() to create a grid of subplots with dimensions nrows by ncols, and a figure size of (15, 5 * nrows). + * If there's 1 row and 1 column fix axes: axes = np.array([[axes]]). + * Else if there's 1 row OR 1 column, fix axes: axes = axes.reshape(-1, 1) + * Plotting: + * Iterates over each channel using enumerate(channels). + * For each channel, determines the subplot position using row = idx // ncols and col = idx % ncols. + * Selects the appropriate subplot axis (ax) from the axes array. + * Response Curve: + * Filters the curves_df DataFrame to get data for the current channel. + * Plots the response curve using ax.plot(), with: + * channel_data["spend"]: X-axis values representing spend. + * channel_data["response"]: Y-axis values representing response. + * color=self.optimal_color: Line color set to self.optimal_color (steel blue). + * alpha=0.6: Line transparency set to 60%. + * Current and Optimal Points: + * Filters channel_data to get current_data and optimal_data based on boolean columns is_current and is_optimal. + * If current_data is not empty, plots a scatter point for the current spend and response: + * current_data["spend"].iloc[0], + * current_data["response"].iloc[0], + * color=self.negative_color: Point color set to self.negative_color (red). + * label="Current": Label for the legend. + * s=100: Size of the scatter point. + * If optimal_data is not empty, plots a scatter point for the optimal spend and response: + * color=self.positive_color: Point color set to self.positive_color (green). + * label="Optimal": Label for the legend. + * s=100: Size of the scatter point. + * Plot Customization: + * Sets the subplot title to the channel name followed by "Response Curve". + * Adds a legend to distinguish between current and optimal points. + * Enables grid lines on the subplot with ax.grid(True, alpha=0.3), setting grid line transparency to 30%. + * Removing Empty Subplots: + * Iterates over any remaining subplot positions beyond the number of channels and removes them using fig.delaxes() to ensure a clean layout. + * Layout Adjustment: + * Calls plt.tight_layout() to automatically adjust the subplot parameters to give specified padding, ensuring that labels and titles fit within the figure area. + +## `plot_efficiency_frontier() -> plt.Figure` +### USAGE +* Visualizes the efficiency frontier, illustrating the relationship between total spend and response. + +### IMPL +* Return Type: + * Returns a matplotlib figure object containing the efficiency frontier plot. +* Functionality: + * Input Validation: + * Checks if self.result is None. If it is, raises a ValueError with the message "No allocation results available. Call plot_all() first." This ensures that the method is only called when allocation results are available. + * Figure and Axes Creation: + * Uses plt.subplots() to create a figure (fig) and axes (ax) with a size specified by self.fig_size, which is set to (12, 8). + * Data Preparation: + * Retrieves the optimal_allocations DataFrame from self.result.optimal_allocations + * Calculates the total current spend and response by summing the current_spend and current_response columns, respectively. + * Calculates the total optimal spend and response by summing the optimal_spend and optimal_response columns, respectively. + * Plotting: + * Scatter Points: + * Plots a scatter point for the current total spend and response: + * color=self.negative_color: Point color set to self.negative_color (red). + * s=100: Size of the scatter point. + * label="Current": Label for the legend. + * zorder=2: Ensures the point is plotted above other elements. + * Plots a scatter point for the optimal total spend and response: + * color=self.positive_color: Point color set to self.positive_color (green). + * s=100: Size of the scatter point. + * label="Optimal": Label for the legend. + * zorder=2: Ensures the point is plotted above other elements. + * Connecting Line: + * Plots a dashed line connecting the current and optimal points using ax.plot(): + * [current_total_spend, optimal_total_spend]: X-axis values for the line. + * [current_total_response, optimal_total_response]: Y-axis values for the line. + * "--": Dashed line style. + * color="gray": Line color set to gray. + * alpha=0.5: Line transparency set to 50%. + * zorder=1: Ensures the line is plotted below the scatter points. + * Annotations: + * Calculates the percentage change in total spend and response from current to optimal using the formulas: + * pct_spend_change = ((optimal_total_spend / current_total_spend) - 1) * 100 + * pct_response_change = ((optimal_total_response / current_total_response) - 1) * 100 + * Annotates the plot with these percentage changes using ax.annotate(): + * xy=(optimal_total_spend, optimal_total_response): Position of the annotation near the optimal point. + * xytext=(10, 10): Offset of the text from the point. + * textcoords="offset points": Specifies that the text offset is in points. + * bbox=dict(facecolor="white", edgecolor="gray", alpha=0.7): Adds a white background with a gray edge and 70% transparency to the annotation. + * Plot Customization: + * Sets the x-axis label to "Total Spend". + * . Sets the y-axis label to "Total Response". + * Sets the plot title to "Efficiency Frontier". + * Adds a legend to distinguish between current and optimal points. + * Enables grid lines on the plot with ax.grid(True, alpha=0.3), setting grid line transparency to 30%. + * Layout Adjustment: + *Calls plt.tight_layout() to automatically adjust the subplot parameters to give specified padding, ensuring that labels and titles fit within the figure area. + +## `plot_spend_vs_response() -> plt.Figure` +### USAGE +* Plots channel-level changes in spend and response percentages. + +### IMPL +* Return Type: + * Returns a matplotlib figure object containing the spend vs. response change plots. +* Functionality: + * Input Validation: + * Checks if self.result is None. If it is, raises a ValueError with the message "No allocation results available. Call plot_all() first." This ensures that the method is only called when allocation results are available. + * Figure and Axes Creation: + * Uses plt.subplots() to create a figure (fig) and two subplot axes (ax1 and ax2) arranged vertically, with a figure size of (12, 10). + * Data Preparation: + * Retrieves the optimal_allocations DataFrame from self.result.optimal_allocations + * Extracts the channel column values into a variable channels from dataframe df, which contains the names of the channels. + * Sets up an array x using np.arange(len(channels)) to represent the x-axis positions for each channel. + * Spend Changes Plot (ax1): + * Calculation: + * Computes the percentage change in spend for each channel using the formula ((df["optimal_spend"] / df["current_spend"]) - 1) * 100. + * Bar Plotting: + * Determines the color for each bar based on whether the percentage change is negative (self.negative_color, red) or positive (>= 0) (self.positive_color, green). + * Plots the percentage changes as bars on ax1 using ax1.bar(), with: + * x: X-axis positions for the bars. + * spend_pct: Heights of the bars, representing spend percentage changes. + * color=colors: Colors of the bars based on the percentage change. + * alpha=0.7: Bar transparency set to 70%. + * Customization: + * Sets the x-ticks to the positions in x and labels them with channel names, rotating them 45 degrees for readability and using ha="right". + * Sets the y-axis label to "Spend Change %". + * Draws a horizontal line at y=0 to indicate no change, using ax1.axhline(y=0, color="black", linestyle="-", alpha=0.2). + * Enables grid lines with ax1.grid(True, alpha=0.3), setting grid line transparency to 30%. + * Value Labels: + * Iterates over each bar to add a text label showing the percentage change, formatted to one decimal place. + * Positions the label above the bar if the value is positive and below if negative. + * Response Changes Plot (ax2): + * Calculation: + * Computes the percentage change in response for each channel using the formula ((df["optimal_response"] / df["current_response"]) - 1) * 100. + * Bar Plotting: + * Determines the color for each bar based on whether the percentage change is negative (self.negative_color, red) or positive (>= 0) (self.positive_color, green). + * Plots the percentage changes as bars on ax2 using ax2.bar(), with: + * x: X-axis positions for the bars. + * response_pct: Heights of the bars, representing response percentage changes. + * color=colors: Colors of the bars based on the percentage change. + * alpha=0.7: Bar transparency set to 70%. + * Customization: + * Sets the x-ticks to the positions in x and labels them with channel names, rotating them 45 degrees for readability and using ha="right". + * Sets the y-axis label to "Response Change %". + * Draws a horizontal line at y=0 to indicate no change, using ax2.axhline(y=0, color="black", linestyle="-", alpha=0.2). + * Enables grid lines with ax2.grid(True, alpha=0.3), setting grid line transparency to 30%. + * Value Labels: + * Iterates over each bar to add a text label showing the percentage change, formatted to one decimal place. + * Positions the label above the bar if the value is positive and below if negative. + * Layout Adjustment: + * Calls plt.tight_layout() to automatically adjust the subplot parameters to give specified padding, ensuring that labels and titles fit within the figure area. + +## `plot_summary_metrics() -> plt.Figure` +### USAGE +* Plots summary metrics, such as ROI or CPA, comparing current and optimized states. + +### IMPL +* Return Type: + * Returns a matplotlib figure object containing the summary metrics plot. +* Functionality: + * Input Validation: + * Checks if self.result is None. If it is, raises a ValueError with the message "No allocation results available. Call plot_all() first." This ensures that the method is only called when allocation results are available. + * Figure and Axes Creation: + * Uses plt.subplots() to create a figure (fig) and axes (ax) with a size specified by self.fig_size, which is set to (12, 8). + * Data Preparation: + * Retrieves the optimal_allocations DataFrame from self.result.optimal_allocations + * Extracts the channel names into the channels array. + * Metric Calculation: + * Determines whether to calculate ROI or CPA based on the dep_var_type in self.result.metrics.get("dep_var_type") + * ROI Calculation (if dep_var_type is "revenue"): + * Calculates current_metric as the ratio of current_response to current_spend and maintain the data as a Pandas Series. + * Calculates optimal_metric as the ratio of optimal_response to optimal_spend and maintain the data as a Pandas Series. + * Sets metric_name to "ROI". + * CPA Calculation (otherwise): + * Calculates current_metric as the ratio of current_spend to current_response and maintain the data as a Pandas Series. + * Calculates optimal_metric as the ratio of optimal_spend to optimal_response and maintain the data as a Pandas Series. + * Sets metric_name to "CPA". + * Bar Plotting: + * Sets up an array x using np.arange(len(channels)) to represent the x-axis positions for each channel. + * Defines the width of the bars as 0.35. + * Plots two sets of bars on the axes: + * Current Metric Bars: + * Positioned slightly to the left of the center of each channel position (x - width / 2). + * Heights represent current_metric values. + * Labeled as "Current ROI" or "Current CPA" based on metric_name. + * Colored using self.current_color (light gray) with 70% transparency. + * Optimal Metric Bars: + * Positioned slightly to the right of the center of each channel position (x + width / 2). + * Heights represent optimal_metric values. + * Labeled as "Optimal ROI" or "Optimal CPA" based on metric_name. + * Colored using self.optimal_color (steel blue) with 70% transparency. + * Value Labels: + * Iterates over each channel to calculate the percentage change from current to optimal metric using the formula ((opt / curr) - 1) * 100. + * Determines the color of the text based on whether the change is positive (self.positive_color, green) or negative (self.negative_color, red). + * Places a text label above each pair of bars showing the percentage change, formatted to one decimal place, centered horizontally and positioned just above the taller bar. + * Plot Customization: + * Sets the x-ticks to the positions in x and labels them with channel names, rotating them 45 degrees for readability. + * Sets the y-axis label to the metric_name ("ROI" or "CPA"). + * Sets the plot title to "Channel ROI Comparison" or "Channel CPA Comparison" based on metric_name. + * Adds a legend to distinguish between current and optimal metric bars. + * Enables grid lines on the plot with ax.grid(True, alpha=0.3), setting grid line transparency to 30%. + * Layout Adjustment: + * Calls plt.tight_layout() to automatically adjust the subplot parameters to give specified padding, ensuring that labels and titles fit within the figure area. diff --git a/python/spec/src/robyn/visualization/base_visualizer.md b/python/spec/src/robyn/visualization/base_visualizer.md new file mode 100644 index 000000000..9a5ad5134 --- /dev/null +++ b/python/spec/src/robyn/visualization/base_visualizer.md @@ -0,0 +1,58 @@ +# CLASS +## BaseVisualizer +* This class serves as the base for all Robyn visualization components, offering common plotting functionalities and styling options. +* It leverages the `matplotlib` and `seaborn` libraries to facilitate plotting and provides methods for configuring plot styles, saving plots, and managing resources effectively. + +# CONSTRUCTORS +## `__init__(style: str = "bmh")` +* Initializes the `BaseVisualizer` with a specified or default plot style, along with other common plot settings. +* **Parameters:** + * `style`: A string that specifies the `matplotlib` style to be applied. Defaults to `"bmh"`. + +### USAGE +* Use this constructor to instantiate a `BaseVisualizer` object with a specific plot style. +* Example: + python + visualizer = BaseVisualizer(style="ggplot") + + +### IMPL +* Assigns the `style` attribute with the given `style` parameter or defaults to `"bmh"`. +* Sets `default_figsize` to `(12, 8)` for default plot dimensions. +* Creates a `colors` dictionary to store color schemes for different visual elements such as 'primary', 'secondary', 'positive', 'negative', and 'neutral'. +* Establishes a `font_sizes` dictionary to define font sizes for various text elements including 'title', 'label', 'tick', and 'annotation'. +* Initializes `current_figure` and `current_axes` as `None` to keep track of the current plot being worked on. +* Invokes the `_setup_plot_style()` method to apply the chosen plot style configurations. + +# METHODS +## `_setup_plot_style() -> None` +### USAGE +* This method requires no parameters. +* It configures the default plotting style settings for the visualizer based on the `style` attribute. + +### IMPL +* Calls `plt.style.use(self.style)` to set the plot style as defined in the `style` attribute. +* Utilizes `plt.rcParams.update()` to configure default plot parameters such as figure size, grid visibility, spine visibility, and font size for labels. + +## `save_plot(filename: Union[str, Path], dpi: int = 300, cleanup: bool = True) -> None` +### USAGE +* Saves the current plot to a specified file path. +* **Parameters:** + * `filename`: A string or `Path` object specifying where the plot should be saved. + * `dpi`: An integer representing the resolution of the saved plot. Defaults to 300. + * `cleanup`: A boolean indicator that determines whether the plot should be closed after saving. Defaults to `True`. + +### IMPL +* Checks if `self.current_figure` is `None` and raises a `ValueError` if there is no figure to save. +* Converts `filename` into a `Path` object and ensures that the parent directory exists, creating it if necessary. +* Saves the current figure using `self.current_figure.savefig()`, applying `dpi` resolution and `bbox_inches='tight'` to ensure layout is compact. +* If `cleanup` is `True`, it invokes the `cleanup()` method to release resources. + +## `cleanup() -> None` +### USAGE +* Closes the current plot, freeing up `matplotlib` resources to manage memory efficiently. + +### IMPL +* Verifies that `self.current_figure` is not `None` before proceeding. +* Closes the current figure using `plt.close(self.current_figure)`. +* Resets `self.current_figure` and `self.current_axes` to `None` to clear plot tracking. \ No newline at end of file diff --git a/python/spec/tests/robyn/modeling/pareto/test_hill_calculator.md b/python/spec/tests/robyn/modeling/pareto/test_hill_calculator.md new file mode 100644 index 000000000..bbd455b57 --- /dev/null +++ b/python/spec/tests/robyn/modeling/pareto/test_hill_calculator.md @@ -0,0 +1,142 @@ +# CLASS +## HillCalculator +* The `HillCalculator` class is designed to compute parameters related to the Hill function for marketing mix models (MMM). It processes input data to determine specific attributes such as alphas, inflexions, and sorted coefficients, which are vital for modeling media spend effects. +* This class is part of a module that likely interacts with data entities like `MMMData` and `ModelOutputs` to perform its operations. +* The class encapsulates functionality to extract adstocked media data and calculate Hill function parameters. + +# CONSTRUCTORS +## `__init__` `(mmmdata: MMMData, model_outputs: ModelOutputs, dt_hyppar: pd.DataFrame, dt_coef: pd.DataFrame, media_spend_sorted: List[str], select_model: str, chn_adstocked: pd.DataFrame = None)` +* **Parameters:** + * `mmmdata (MMMData)`: An object containing the marketing mix model data specifications, including the window start and end indices for data slicing. + * `model_outputs (ModelOutputs)`: An object containing model outputs, specifically the media vector collections needed for adstocked media calculations. + * `dt_hyppar (pd.DataFrame)`: A DataFrame holding the hyperparameters required for calculating the Hill function parameters, namely alphas and gammas. + * `dt_coef (pd.DataFrame)`: A DataFrame that contains coefficients for the models, used in sorting and extracting relevant data. + * `media_spend_sorted (List[str])`: A sorted list of media spend column names that define the order of processing and output generation. + * `select_model (str)`: A string identifier for the selected model, which is used to filter the relevant data from the model outputs. + * `chn_adstocked (pd.DataFrame, optional)`: Optional precomputed DataFrame of adstocked media, which can be provided to skip recalculation. + +### USAGE +* Use this constructor when creating an instance of `HillCalculator` by providing all necessary data dependencies and configurations. It initializes the object with data and parameters required for subsequent calculations. +* This setup is essential before invoking methods like `_get_chn_adstocked_from_output_collect` and `get_hill_params`, as it ensures the class has all the necessary context and data to function correctly. + +### IMPL +* Ensure that upon instantiation, the constructor initializes all attributes with the provided parameters, setting up the internal state of the `HillCalculator` object. +* The constructor should not perform any computations besides storing the input data; it merely prepares the object for later method calls. +* In testing, verify that all attributes are correctly assigned and that the optional parameter `chn_adstocked` defaults appropriately if not provided. + +# METHODS + + +## `test_empty_media_vec_collect() -> None` +### USAGE +* This test checks the behavior of the `_get_chn_adstocked_from_output_collect` function when the `media_vec_collect` is empty. +* It ensures that the function returns an empty DataFrame as expected. +### IMPL +* Mock the `media_vec_collect` method of `ModelOutputs` to return an empty DataFrame. +* Prepare the input data with `mmmdata` specification having a window from 0 to 10. +* Ensure `model_outputs` has an empty DataFrame for `media_vec_collect`. +* Set `media_spend_sorted` as an empty list. +* Set `select_model` to a dummy value like 'model_1'. +* Invoke `_get_chn_adstocked_from_output_collect`. +* Assert that the result `chn_adstocked` is an empty DataFrame. + +## `test_no_matching_solID() -> None` +### USAGE +* This test checks the behavior when there is no matching `solID` in `media_vec_collect`. +* It ensures that the function returns an empty DataFrame when the selected model does not match any records. +### IMPL +* Mock the `media_vec_collect` method of `ModelOutputs` to return a DataFrame with non-matching solIDs. +* Prepare the input data with `mmmdata` specification having a window from 0 to 10. +* Ensure `model_outputs` has the mocked DataFrame. +* Set `media_spend_sorted` as `['media_1', 'media_2']`. +* Set `select_model` to 'model_1', which does not match any `solID`. +* Invoke `_get_chn_adstocked_from_output_collect`. +* Assert that the result `chn_adstocked` is an empty DataFrame. + +## `test_valid_matching_solID_and_window_slicing() -> None` +### USAGE +* This test checks the function behavior with valid matching `solID` and proper window slicing. +* It ensures that the function returns a correctly sliced DataFrame. +### IMPL +* Mock the `media_vec_collect` method of `ModelOutputs` to return a DataFrame with matching `solID` values. +* Prepare the input data with `mmmdata` specification having a window from 1 to 2. +* Ensure `model_outputs` has the mocked DataFrame. +* Set `media_spend_sorted` as `['media_1', 'media_2']`. +* Set `select_model` to 'model_1'. +* Invoke `_get_chn_adstocked_from_output_collect`. +* Assert that the result `chn_adstocked` matches the expected DataFrame with sliced data for indices 1 to 2. + +## `test_non_existing_media_columns() -> None` +### USAGE +* This test checks the behavior when `media_spend_sorted` contains non-existing media columns. +* It ensures that the function returns an empty DataFrame. +### IMPL +* Mock the `media_vec_collect` method of `ModelOutputs` to return a DataFrame with existing media columns. +* Prepare the input data with `mmmdata` specification having a window from 0 to 1. +* Ensure `model_outputs` has the mocked DataFrame. +* Set `media_spend_sorted` to non-existing columns `['media_3', 'media_4']`. +* Set `select_model` to 'model_1'. +* Invoke `_get_chn_adstocked_from_output_collect`. +* Assert that the result `chn_adstocked` is an empty DataFrame. + +## `test_get_hill_params_with_normal_input_data() -> None` +### USAGE +* This test checks the behavior of `get_hill_params` when provided with normal input data. +* Mocks are used for the `pd.DataFrame` methods `filter` and `agg` to simulate the behavior of extracting and aggregating data. +* The parameters include a populated `media_spend_sorted` list and valid data objects for `MMMData`, `ModelOutputs`, `dt_hyppar`, `dt_coef`, and `chn_adstocked`. + +### IMPL +1. **Mock Setup:** + - Mock the `filter` method of `pd.DataFrame` to return a DataFrame with specific alphas and gammas. + - Mock the `agg` method of `pd.DataFrame` to simulate the `min` and `max` aggregation for each media. + +2. **Input Preparation:** + - Create mock instances of `MMMData`, `ModelOutputs`, `dt_hyppar`, `dt_coef`, and `chn_adstocked`. + - Populate `media_spend_sorted` with media identifiers (e.g., `['media1', 'media2']`). + +3. **Invoke Function:** + - Call `get_hill_params` with the prepared inputs. + +4. **Assertions:** + - Assert that the returned `alphas` match the expected values `[0.5, 0.7]`. + - Assert that calculated `inflexions` are `[170.0, 190.0]`. This involves computing weighted sums based on mocked `agg` outputs and `gammas`. + - Verify that `coefs_sorted` matches the expected order `['coef1', 'coef2']`. + +## `test_get_hill_params_with_chn_adstocked_none() -> None` +### USAGE +* This test evaluates `get_hill_params` when `chn_adstocked` is initially `None`. +* It mocks the method `_get_chn_adstocked_from_output_collect` to supply a DataFrame for `chn_adstocked`. + +### IMPL +1. **Mock Setup:** + - Mock the `_get_chn_adstocked_from_output_collect` method to return a DataFrame containing media spend data. + +2. **Input Preparation:** + - Assign `None` to `chn_adstocked` to test its handling within the function. + - Prepare other inputs similarly to the previous test case. + +3. **Invoke Function:** + - Execute `get_hill_params` with the prepared inputs. + +4. **Assertions:** + - Confirm the `alphas` returned are `[0.5, 0.7]`, matching expected values from the mock setup. + - Ensure `inflexions` are computed as `[170.0, 190.0]` through the mocked aggregation and `gammas`. + - Check that `coefs_sorted` maintains the correct order `['coef1', 'coef2']`. + +## `test_get_hill_params_with_empty_media_spend_sorted() -> None` +### USAGE +* This test examines the function's response when `media_spend_sorted` is empty. +* No mocks are needed, as the method should gracefully handle the empty list. + +### IMPL +1. **Input Preparation:** + - Use empty list `[]` for `media_spend_sorted`. + - Provide valid instances of other inputs (`MMMData`, `ModelOutputs`, `dt_hyppar`, `dt_coef`, and `chn_adstocked`). + +2. **Invoke Function:** + - Call `get_hill_params` with these inputs. + +3. **Assertions:** + - Assert that `alphas` is an empty list `[]`, as there are no media to extract parameters for. + - Confirm `inflexions` returns an empty list `[]`, given no media spend data to compute. + - Verify `coefs_sorted` is also an empty list `[]`, due to the absence of media coefficients. \ No newline at end of file diff --git a/python/src/robyn/__init__.py b/python/src/robyn/__init__.py new file mode 100644 index 000000000..e4134b9e6 --- /dev/null +++ b/python/src/robyn/__init__.py @@ -0,0 +1,59 @@ +# import os +# import logging +# import logging.config +# from datetime import datetime +# import robyn + +# current_datetime = datetime.now() + +# # Get the directory of the current module +# module_dir = os.path.dirname(robyn.__file__) + +# log_directory = "/tmp/robynpy/logs" +# if not os.path.exists(log_directory): +# os.makedirs(log_directory) + +# # Define the path to the logging configuration file +# logging_conf_path = os.path.join(module_dir, "common/config/logging.conf") + +# # Create a default configuration if the file is missing or fails to load +# if not os.path.exists(logging_conf_path): +# # Create a basic configuration +# logging.basicConfig( +# level=logging.INFO, +# format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", +# ) +# else: +# # Attempt to load the configuration file +# try: +# logging.config.fileConfig( +# logging_conf_path, +# defaults={"asctime": current_datetime.strftime("%Y-%m-%d_%H-%M-%S")}, +# disable_existing_loggers=False, +# ) +# except KeyError: +# # Handle KeyError by using basic configuration +# logging.basicConfig( +# level=logging.INFO, +# format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", +# ) + +import os +import logging +from datetime import datetime +import robyn + +current_datetime = datetime.now() + +# Get the directory of the current module +module_dir = os.path.dirname(robyn.__file__) + +# Set up basic logging configuration to log to the console +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", +) + +# If you have any specific loggers you want to configure, you can do so here +logger = logging.getLogger(__name__) +logger.info("Logging is set up to console only.") diff --git a/python/src/robyn/allocator/constants.py b/python/src/robyn/allocator/constants.py new file mode 100644 index 000000000..d4a4f7514 --- /dev/null +++ b/python/src/robyn/allocator/constants.py @@ -0,0 +1,27 @@ +"""Constants for the budget allocator module.""" + +# Optimization Scenarios +SCENARIO_MAX_RESPONSE = "max_response" +SCENARIO_TARGET_EFFICIENCY = "target_efficiency" + +# Optimization Algorithms +ALGO_SLSQP_AUGLAG = "SLSQP_AUGLAG" +ALGO_MMA_AUGLAG = "MMA_AUGLAG" + +# Constraint Modes +CONSTRAINT_MODE_EQ = "eq" +CONSTRAINT_MODE_INEQ = "ineq" + +# Dependent Variable Types +DEP_VAR_TYPE_REVENUE = "revenue" +DEP_VAR_TYPE_CONVERSION = "conversion" + +# Default Values +DEFAULT_MAX_EVAL = 100000 +DEFAULT_CONSTRAINT_MULTIPLIER = 3.0 +DEFAULT_CHANNEL_CONSTRAINT_LOW = 0.7 +DEFAULT_CHANNEL_CONSTRAINT_UP = 1.2 + +# Date Range Options +DATE_RANGE_ALL = "all" +DATE_RANGE_LAST = "last" diff --git a/python/src/robyn/allocator/data_preparation.py b/python/src/robyn/allocator/data_preparation.py new file mode 100644 index 000000000..9f7f25483 --- /dev/null +++ b/python/src/robyn/allocator/data_preparation.py @@ -0,0 +1,382 @@ +import numpy as np +from typing import List, Dict +from robyn.allocator.entities.constraints import Constraints +from robyn.allocator.utils import ( + check_metric_dates, + check_allocator_constraints, + get_hill_params, +) +import logging + +from .entities.allocation_params import AllocatorParams +from .entities.constraints import Constraints +from .constants import ( + SCENARIO_MAX_RESPONSE, + SCENARIO_TARGET_EFFICIENCY, +) +from typing import List +import numpy as np +import logging +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.modeling.entities.pareto_result import ParetoResult +from .entities.allocation_params import AllocatorParams +from .entities.constraints import Constraints +from .constants import ( + SCENARIO_MAX_RESPONSE, + SCENARIO_TARGET_EFFICIENCY, +) + + +class AllocatorDataPreparation: + """Prepare data for the allocator optimization.""" + + def __init__( + self, + mmm_data: MMMData, + pareto_result: ParetoResult, + hyperparameters: Hyperparameters, + params: AllocatorParams, + select_model: str, + ) -> None: + self.mmm_data = mmm_data + self.pareto_result = pareto_result + self.hyperparameters = hyperparameters + self.params = params + self.select_model = select_model + self.media_spend_sorted = None + self.init_spend_unit = None + self.init_response = None + self.hist_filtered = None + self.dt_best_coef = None + self.exclude = None + self.dep_var_type = None + self.date_min = None + self.date_max = None + + self.logger = logging.getLogger(__name__) + + def _validate_inputs(self) -> None: + """Validate input data and parameters.""" + if len(self.mmm_data.mmmdata_spec.paid_media_spends) <= 1: + raise ValueError("Must have at least two paid media spends") + self.logger.debug("self.logger.debuging params scenario", self.params.scenario) + if self.params.scenario not in [ + SCENARIO_MAX_RESPONSE, + SCENARIO_TARGET_EFFICIENCY, + ]: + raise ValueError(f"Invalid scenario: {self.params.scenario}") + + check_allocator_constraints( + self.params.channel_constr_low, self.params.channel_constr_up + ) + + def _validate_initialization(self) -> None: + """Validate that all necessary parameters are properly initialized.""" + required_attrs = [ + "init_spend_unit", + "init_spend_total", + "init_response", + "hill_params", + "total_budget", + "initial_metrics", + ] + + for attr in required_attrs: + if not hasattr(self, attr): + raise ValueError(f"Missing required attribute: {attr}") + + value = getattr(self, attr) + if value is None: + raise ValueError(f"Required attribute is None: {attr}") + + if isinstance(value, (np.ndarray, list)): + if len(value) != len(self.media_spend_sorted): + raise ValueError( + f"Length mismatch for {attr}: " + f"got {len(value)}, expected {len(self.media_spend_sorted)}" + ) + + # Validate there are no NaN or inf values in critical arrays + for attr in ["init_spend_unit", "init_response"]: + value = getattr(self, attr) + if np.any(~np.isfinite(value)): + raise ValueError(f"Found non-finite values in {attr}") + + def _determine_usecase(self) -> str: + """Determine the use case based on initial spend and date range.""" + if self.params.date_range == "all": + base_case = "all_historical_vec" + elif self.params.date_range == "last": + base_case = "last_historical_vec" + else: + base_case = "custom_window_vec" + + return f"{base_case} + {'defined' if self.params.total_budget else 'historical'}_budget" + + def _identify_zero_coefficient_channels(self) -> List[str]: + """Identify channels with zero coefficients.""" + return [ + channel + for channel, coef in zip(self.media_spend_sorted, self.hill_params.coefs) + if coef == 0 + ] + + def _identify_zero_constraint_channels(self) -> List[str]: + """Identify channels with zero constraints.""" + zero_constraints = (np.array(self.params.channel_constr_low) == 0) & ( + np.array(self.params.channel_constr_up) == 0 + ) + return [ + channel + for channel, is_zero in zip(self.media_spend_sorted, zero_constraints) + if is_zero + ] + + def _identify_zero_spend_channels(self) -> List[str]: + """Identify channels with zero historical spend.""" + return [ + channel + for channel, spend in zip( + self.media_spend_sorted, self.hist_spend["histSpendWindowUnit"] + ) + if spend == 0 + ] + + def _setup_constraints(self) -> Constraints: + """Setup optimization constraints matching R implementation""" + # Calculate bounds exactly as R does + lower_bounds = self.init_spend_unit * self.params.channel_constr_low + upper_bounds = self.init_spend_unit * self.params.channel_constr_up + budget_constraint = self.init_spend_total + + self.logger.debug("\nOptimization constraints:") + self.logger.debug(f"Total budget: {budget_constraint:,.2f}") + self.logger.debug(f"Bounds multiplier: {self.params.channel_constr_multiplier}") + + return Constraints( + lower_bounds=lower_bounds, + upper_bounds=upper_bounds, + budget_constraint=budget_constraint, + ) + + def _setup_target_efficiency_constraints(self) -> Constraints: + """Setup constraints specifically for target efficiency scenario.""" + lower_bounds = self.init_spend_unit * self.params.channel_constr_low[0] + upper_bounds = self.init_spend_unit * self.params.channel_constr_up[0] + + # Calculate target value + if self.params.target_value is None: + if self.dep_var_type == "revenue": + initial_roas = np.sum(self.init_response) / np.sum(self.init_spend_unit) + target_value = initial_roas * 0.8 # Target 80% of initial ROAS + self.logger.debug( + f"Target ROAS: {target_value:.4f} (80% of initial {initial_roas:.4f})" + ) + else: + initial_cpa = np.sum(self.init_spend_unit) / np.sum(self.init_response) + target_value = initial_cpa * 1.2 # Target 120% of initial CPA + self.logger.debug( + f"Target CPA: {target_value:.4f} (120% of initial {initial_cpa:.4f})" + ) + else: + target_value = self.params.target_value + self.logger.debug(f"Using provided target value: {target_value:.4f}") + + return Constraints( + lower_bounds=lower_bounds, + upper_bounds=upper_bounds, + budget_constraint=None, # No fixed budget for target efficiency + target_constraint=target_value, + ) + + def _setup_date_ranges(self) -> None: + """Setup date ranges and windows for optimization.""" + window_loc = slice( + self.mmm_data.mmmdata_spec.rolling_window_start_which, + self.mmm_data.mmmdata_spec.rolling_window_end_which, + ) + self.dt_optim_cost = self.mmm_data.data.iloc[window_loc] + + date_range = check_metric_dates( + self.params.date_range, + self.dt_optim_cost[self.mmm_data.mmmdata_spec.date_var], + self.mmm_data.mmmdata_spec.rolling_window_length, + is_allocator=True, + ) + + self.date_min = date_range["date_range_updated"][0] + self.date_max = date_range["date_range_updated"][-1] + + mask = ( + self.dt_optim_cost[self.mmm_data.mmmdata_spec.date_var] >= self.date_min + ) & (self.dt_optim_cost[self.mmm_data.mmmdata_spec.date_var] <= self.date_max) + self.hist_filtered = self.dt_optim_cost[mask] + + def _initialize_data(self) -> None: + """Initialize and prepare data for optimization.""" + # Extract paid media data + self.paid_media_spends = np.array(self.mmm_data.mmmdata_spec.paid_media_spends) + self.media_spend_sorted = self.paid_media_spends # Keep original order + + # Get model parameters + self.dep_var_type = self.mmm_data.mmmdata_spec.dep_var_type + + # Handle column renames if needed + for df_name in ["result_hyp_param", "x_decomp_agg"]: + df = getattr(self.pareto_result, df_name) + if "sol_id" in df.columns: + setattr( + self.pareto_result, df_name, df.rename(columns={"sol_id": "solID"}) + ) + + # Filter for selected model + self.dt_hyppar = self.pareto_result.result_hyp_param[ + self.pareto_result.result_hyp_param["solID"] == self.select_model + ] + self.dt_best_coef = self.pareto_result.x_decomp_agg[ + (self.pareto_result.x_decomp_agg["solID"] == self.select_model) + & (self.pareto_result.x_decomp_agg["rn"].isin(self.paid_media_spends)) + ] + self.logger.debug("Model Coefficients:") + self.logger.debug(self.dt_best_coef) + + # Initialize hill parameters + self.hill_params = get_hill_params( + self.mmm_data, + self.hyperparameters, + self.dt_hyppar, + self.dt_best_coef, + self.media_spend_sorted, + self.select_model, + ) + + # Handle zero coefficients like R + self.exclude = np.array([coef == 0 for coef in self.hill_params.coefs]) + + if np.any(self.exclude): + excluded_channels = [ + channel + for channel, is_excluded in zip(self.media_spend_sorted, self.exclude) + if is_excluded + ] + self.logger.warning( + f"The following media channels have zero coefficients and will be excluded: " + f"{', '.join(excluded_channels)}" + ) + + # Pre-calculate adstocked data and inflexion points + self.adstocked_ranges = {} + self.inflexions = {} + adstocked_data = self.pareto_result.media_vec_collect[ + self.pareto_result.media_vec_collect["type"] == "adstockedMedia" + ] + + for i, channel in enumerate(self.media_spend_sorted): + model_data = adstocked_data[channel].values + x_range = [min(model_data), max(model_data)] + gamma = self.hill_params.gammas[i] + inflexion = x_range[0] * (1 - gamma) + x_range[1] * gamma + self.adstocked_ranges[channel] = x_range + self.inflexions[channel] = inflexion + self.logger.debug("\n=== Initialization ===") + self.logger.debug("Media spend sorted:", self.media_spend_sorted) + self.logger.debug("Initial spend unit:", self.init_spend_unit) + self.logger.debug("Initial response:", self.init_response) + self.logger.debug("Total budget:", self.params.total_budget) + self._setup_date_ranges() + self._initialize_optimization_params() + + def _calculate_historical_spend(self) -> Dict[str, np.ndarray]: + """Calculate historical spend metrics.""" + media_cols = self.media_spend_sorted + return { + "histSpendAll": np.array( + [self.dt_optim_cost[col].sum() for col in media_cols] + ), + "histSpendAllUnit": np.array( + [self.dt_optim_cost[col].mean() for col in media_cols] + ), + "histSpendWindow": np.array( + [self.hist_filtered[col].sum() for col in media_cols] + ), + "histSpendWindowUnit": np.array( + [self.hist_filtered[col].mean() for col in media_cols] + ), + } + + def calculate_marginal_response(self, spend: float, channel_index: int) -> float: + """Calculate marginal response by evaluating at x and x+1.""" + # Skip calculation for excluded channels + if self.exclude[channel_index]: + return 0.0 + + response_x = self.calculate_response(spend, channel_index) + response_x_plus_1 = self.calculate_response(spend + 1, channel_index) + return response_x_plus_1 - response_x + + def _initialize_optimization_params(self) -> None: + """Initialize optimization parameters""" + # Calculate historical spend metrics + self.hist_spend = self._calculate_historical_spend() + self.init_spend_unit = self.hist_spend["histSpendWindowUnit"] + self.init_spend_total = np.sum(self.init_spend_unit) + + # Calculate initial responses and marginal responses + self.init_response = np.array([]) + self.init_response_marg = np.array([]) + + for i, spend in enumerate(self.init_spend_unit): + response = self.calculate_response(spend, i) + marginal_response = self.calculate_marginal_response(spend, i) + self.init_response = np.append(self.init_response, response) + self.init_response_marg = np.append( + self.init_response_marg, marginal_response + ) + + # Set total budget + self.total_budget = self.params.total_budget or self.init_spend_total + + # Store initial metrics + self.initial_metrics = { + "total_spend": self.init_spend_total, + "total_response": np.sum(self.init_response), + "overall_roi": np.sum(self.init_response) / self.init_spend_total, + "channel_roi": { + channel: (resp / spend if spend > 0 else 0) + for channel, resp, spend in zip( + self.media_spend_sorted, self.init_response, self.init_spend_unit + ) + }, + "marginal_response": self.init_response_marg, + } + + self._validate_initialization() + + def calculate_response(self, spend: float, channel_index: int) -> float: + """Calculate response using pre-calculated ranges and inflexions.""" + # Return 0 response for excluded channels + if self.exclude[channel_index]: + return 0.0 + + channel = self.media_spend_sorted[channel_index] + + # Get parameters + alpha = self.hill_params.alphas[channel_index] + coef = self.hill_params.coefs[channel_index] + carryover = self.hill_params.carryover[channel_index] + inflexion = self.inflexions[channel] + + # Calculate response + x_adstocked = spend + carryover + x_saturated = (x_adstocked**alpha) / (x_adstocked**alpha + inflexion**alpha) + response = coef * x_saturated + self.logger.debug("\n=== Response Calculation ===") + self.logger.debug("Channel:", channel) + self.logger.debug("Input spend:", spend) + self.logger.debug("Alpha:", alpha) + self.logger.debug("Coef:", coef) + self.logger.debug("Carryover:", carryover) + self.logger.debug("Inflexion:", inflexion) + self.logger.debug("Response:", response) + return response diff --git a/python/src/robyn/allocator/entities/allocation_params.py b/python/src/robyn/allocator/entities/allocation_params.py new file mode 100644 index 000000000..4ebdfb471 --- /dev/null +++ b/python/src/robyn/allocator/entities/allocation_params.py @@ -0,0 +1,54 @@ +from dataclasses import dataclass +from typing import List, Optional +import numpy as np + + +@dataclass +class AllocatorParams: + """ + Parameters for budget allocation optimization. + + Attributes: + scenario: Type of optimization scenario ('max_response' or 'target_efficiency') + total_budget: Total budget constraint (optional) + target_value: Target value for efficiency optimization (optional) + date_range: Date range for optimization ('all', 'last', or specific range) + channel_constr_low: Lower bounds for channel constraints + channel_constr_up: Upper bounds for channel constraints + channel_constr_multiplier: Multiplier for constraint ranges + optim_algo: Optimization algorithm to use + maxeval: Maximum number of evaluations + constr_mode: Constraint mode ('eq' or 'ineq') + plots: Whether to generate plots + """ + + scenario: str + total_budget: Optional[float] = None + target_value: Optional[float] = None + date_range: str = "all" + channel_constr_low: List[float] = None + channel_constr_up: List[float] = None + channel_constr_multiplier: float = 3.0 + optim_algo: str = "SLSQP_AUGLAG" + maxeval: int = 100000 + constr_mode: str = "eq" + plots: bool = True + + def __post_init__(self): + """Validate and process parameters after initialization.""" + if self.channel_constr_low is None: + self.channel_constr_low = [0.7] + if self.channel_constr_up is None: + self.channel_constr_up = [1.2] + + # Convert to numpy arrays for easier manipulation + self.channel_constr_low = np.array(self.channel_constr_low) + self.channel_constr_up = np.array(self.channel_constr_up) + + # Validate constraints + if np.any(self.channel_constr_low < 0): + raise ValueError("Lower bounds must be non-negative") + if np.any(self.channel_constr_up <= 0): + raise ValueError("Upper bounds must be positive") + if np.any(self.channel_constr_up < self.channel_constr_low): + raise ValueError("Upper bounds must be greater than lower bounds") diff --git a/python/src/robyn/allocator/entities/allocation_result.py b/python/src/robyn/allocator/entities/allocation_result.py new file mode 100644 index 000000000..ac1602976 --- /dev/null +++ b/python/src/robyn/allocator/entities/allocation_result.py @@ -0,0 +1,183 @@ +from dataclasses import dataclass +from typing import Dict, List, Optional, Any +import numpy as np +import pandas as pd + + +@dataclass +class OptimOutData: + """ + Optimization output data for each channel. + + Attributes: + channels: List of channel names + init_spend_unit: Initial spend per unit for each channel + init_response_unit: Initial response per unit for each channel + init_response_marg_unit: Initial marginal response per unit for each channel + optm_spend_unit: Optimized spend per unit for each channel + optm_response_unit: Optimized response per unit for each channel + optm_response_marg_unit: Optimized marginal response per unit for each channel + optm_spend_unit_unbound: Unbounded optimized spend per unit + optm_response_unit_unbound: Unbounded optimized response per unit + optm_response_marg_unit_unbound: Unbounded optimized marginal response per unit + date_min: Start date of optimization window + date_max: End date of optimization window + metric: Metric type (ROAS or CPA) + periods: Time period description + """ + + channels: np.ndarray + init_spend_unit: np.ndarray + init_response_unit: np.ndarray + init_response_marg_unit: np.ndarray + optm_spend_unit: np.ndarray + optm_response_unit: np.ndarray + optm_response_marg_unit: np.ndarray + optm_spend_unit_unbound: np.ndarray + optm_response_unit_unbound: np.ndarray + optm_response_marg_unit_unbound: np.ndarray + date_min: str + date_max: str + metric: str + periods: str + + def to_dataframe(self) -> pd.DataFrame: + """Convert optimization results to a DataFrame.""" + return pd.DataFrame( + { + "channel": self.channels, + "init_spend": self.init_spend_unit, + "init_response": self.init_response_unit, + "init_response_marg": self.init_response_marg_unit, + "optm_spend": self.optm_spend_unit, + "optm_response": self.optm_response_unit, + "optm_response_marg": self.optm_response_marg_unit, + "optm_spend_unbound": self.optm_spend_unit_unbound, + "optm_response_unbound": self.optm_response_unit_unbound, + "optm_response_marg_unbound": self.optm_response_marg_unit_unbound, + } + ) + + # Share calculations + @property + def init_spend_share(self) -> np.ndarray: + """Calculate initial spend shares.""" + return self.init_spend_unit / np.sum(self.init_spend_unit) + + @property + def init_response_share(self) -> np.ndarray: + """Calculate initial response shares.""" + return self.init_response_unit / np.sum(self.init_response_unit) + + @property + def optm_spend_share_unit(self) -> np.ndarray: + """Calculate optimized spend shares.""" + return self.optm_spend_unit / np.sum(self.optm_spend_unit) + + @property + def optm_response_share_unit(self) -> np.ndarray: + """Calculate optimized response shares.""" + return self.optm_response_unit / np.sum(self.optm_response_unit) + + @property + def optm_spend_share_unit_unbound(self) -> np.ndarray: + """Calculate unbounded optimized spend shares.""" + return self.optm_spend_unit_unbound / np.sum(self.optm_spend_unit_unbound) + + @property + def optm_response_share_unit_unbound(self) -> np.ndarray: + """Calculate unbounded optimized response shares.""" + return self.optm_response_unit_unbound / np.sum(self.optm_response_unit_unbound) + + @property + def init_roi(self) -> np.ndarray: + """Calculate initial ROI.""" + return self.init_response_unit / np.where( + self.init_spend_unit > 0, self.init_spend_unit, np.inf + ) + + @property + def optm_roi(self) -> np.ndarray: + """Calculate optimized ROI.""" + return self.optm_response_unit / np.where( + self.optm_spend_unit > 0, self.optm_spend_unit, np.inf + ) + + @property + def optm_roi_unbound(self) -> np.ndarray: + """Calculate unbounded optimized ROI.""" + return self.optm_response_unit_unbound / np.where( + self.optm_spend_unit_unbound > 0, self.optm_spend_unit_unbound, np.inf + ) + + +@dataclass +class MainPoints: + """ + Main points data for visualization. + + Attributes: + response_points: Response values for initial, optimized, and unbounded scenarios + spend_points: Spend values for initial, optimized, and unbounded scenarios + channels: Channel names + """ + + response_points: np.ndarray + spend_points: np.ndarray + channels: np.ndarray + + def get_scenario_data(self, scenario_index: int) -> Dict[str, np.ndarray]: + """Get data for a specific scenario.""" + return { + "response": self.response_points[scenario_index], + "spend": self.spend_points[scenario_index], + "channels": self.channels, + } + + +@dataclass +class AllocationResult: + """ + Complete allocation optimization results. + + Attributes: + dt_optimOut: Detailed optimization output data + mainPoints: Main points data for visualization + scenario: Optimization scenario used + usecase: Use case description + total_budget: Total budget used + skipped_coef0: Channels skipped due to zero coefficients + skipped_constr: Channels skipped due to constraints + no_spend: Channels with no historical spend + """ + + dt_optimOut: OptimOutData + mainPoints: MainPoints + scenario: str + usecase: str + total_budget: float + skipped_coef0: List[str] + skipped_constr: List[str] + no_spend: List[str] + + def get_summary(self) -> Dict[str, Any]: + """Get a summary of the allocation results.""" + return { + "scenario": self.scenario, + "usecase": self.usecase, + "total_budget": self.total_budget, + "total_channels": len(self.dt_optimOut.channels), + "active_channels": len(self.dt_optimOut.channels) + - len(self.skipped_coef0) + - len(self.skipped_constr), + "total_response_lift": ( + np.sum(self.dt_optimOut.optm_response_unit) + / np.sum(self.dt_optimOut.init_response_unit) + - 1 + ), + "skipped_channels": { + "zero_coef": self.skipped_coef0, + "zero_constraint": self.skipped_constr, + "no_spend": self.no_spend, + }, + } diff --git a/python/src/robyn/allocator/entities/constraints.py b/python/src/robyn/allocator/entities/constraints.py new file mode 100644 index 000000000..b07b57872 --- /dev/null +++ b/python/src/robyn/allocator/entities/constraints.py @@ -0,0 +1,79 @@ +from dataclasses import dataclass +from typing import Optional +import numpy as np +from typing import List, Tuple + + +@dataclass +class Constraints: + """ + Constraints for the optimization problem. + + Attributes: + lower_bounds: Lower bounds for each channel's spend + upper_bounds: Upper bounds for each channel's spend + budget_constraint: Total budget constraint (can be None for target efficiency) + target_constraint: Target efficiency constraint (optional) + """ + + lower_bounds: np.ndarray + upper_bounds: np.ndarray + budget_constraint: Optional[float] + target_constraint: Optional[float] = None + + def __post_init__(self): + """Validate constraints after initialization.""" + if not isinstance(self.lower_bounds, np.ndarray): + self.lower_bounds = np.array(self.lower_bounds) + if not isinstance(self.upper_bounds, np.ndarray): + self.upper_bounds = np.array(self.upper_bounds) + + # Validate bounds + if np.any(self.lower_bounds < 0): + raise ValueError("Lower bounds must be non-negative") + if np.any(self.upper_bounds <= 0): + raise ValueError("Upper bounds must be positive") + if np.any(self.upper_bounds < self.lower_bounds): + raise ValueError("Upper bounds must be greater than lower bounds") + + # Only validate budget_constraint if it's not None + if self.budget_constraint is not None and self.budget_constraint <= 0: + raise ValueError("Budget constraint must be positive") + + def get_bounds(self) -> List[Tuple[float, float]]: + """Get bounds as list of tuples for optimization.""" + return list(zip(self.lower_bounds, self.upper_bounds)) + + def is_feasible(self, x: np.ndarray, tolerance: float = 1e-6) -> bool: + """Check if a solution is feasible within given tolerance.""" + # Check bounds + if np.any(x < self.lower_bounds - tolerance) or np.any( + x > self.upper_bounds + tolerance + ): + return False + + # Check budget constraint only if it exists + if self.budget_constraint is not None: + if abs(np.sum(x) - self.budget_constraint) > tolerance: + return False + + # Check target constraint if applicable + if self.target_constraint is not None: + # Note: Actual target constraint check would depend on the specific form + # of the constraint (CPA or ROAS) + pass + + return True + + def scale_constraints(self, factor: float) -> "Constraints": + """Create new Constraints object with scaled bounds.""" + return Constraints( + lower_bounds=self.lower_bounds * factor, + upper_bounds=self.upper_bounds * factor, + budget_constraint=( + self.budget_constraint * factor + if self.budget_constraint is not None + else None + ), + target_constraint=self.target_constraint, + ) diff --git a/python/src/robyn/allocator/entities/optimization_result.py b/python/src/robyn/allocator/entities/optimization_result.py new file mode 100644 index 000000000..4ca188b7b --- /dev/null +++ b/python/src/robyn/allocator/entities/optimization_result.py @@ -0,0 +1,44 @@ +from dataclasses import dataclass +from typing import Dict, Optional +import numpy as np + + +@dataclass +class OptimizationResult: + """ + Results from the optimization process. + + Attributes: + solution: Optimal solution vector + objective: Objective function value at the solution + gradient: Gradient at the solution (if available) + constraints: Constraint values at the solution (if available) + """ + + solution: np.ndarray + objective: float + gradient: Optional[np.ndarray] = None + constraints: Optional[Dict[str, float]] = None + + def __post_init__(self): + """Validate optimization results after initialization.""" + if not isinstance(self.solution, np.ndarray): + self.solution = np.array(self.solution) + if self.gradient is not None and not isinstance(self.gradient, np.ndarray): + self.gradient = np.array(self.gradient) + + def is_feasible(self, tolerance: float = 1e-6) -> bool: + """Check if the solution is feasible within given tolerance.""" + if self.constraints is None: + return True + return all(abs(v) <= tolerance for v in self.constraints.values()) + + def get_metrics(self) -> Dict[str, float]: + """Get optimization metrics.""" + return { + "objective_value": self.objective, + "solution_norm": np.linalg.norm(self.solution), + "gradient_norm": ( + np.linalg.norm(self.gradient) if self.gradient is not None else None + ), + } diff --git a/python/src/robyn/allocator/optimizer.py b/python/src/robyn/allocator/optimizer.py new file mode 100644 index 000000000..df925d087 --- /dev/null +++ b/python/src/robyn/allocator/optimizer.py @@ -0,0 +1,399 @@ +from dataclasses import dataclass +from typing import Dict, List, Optional, Tuple, Union, Any +import numpy as np +import pandas as pd +from nevergrad.optimization import optimizerlib +from scipy.optimize import minimize +import logging +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.data.entities.enums import DependentVarType, AdstockType +from robyn.modeling.entities.featurized_mmm_data import FeaturizedMMMData + +from .entities.allocation_params import AllocatorParams +from .entities.allocation_result import AllocationResult, OptimOutData, MainPoints +from .entities.optimization_result import OptimizationResult +from .entities.constraints import Constraints +from .constants import ( + SCENARIO_MAX_RESPONSE, + SCENARIO_TARGET_EFFICIENCY, + ALGO_SLSQP_AUGLAG, + ALGO_MMA_AUGLAG, + CONSTRAINT_MODE_EQ, + CONSTRAINT_MODE_INEQ, + DEP_VAR_TYPE_REVENUE, + DEP_VAR_TYPE_CONVERSION, +) + +from .data_preparation import AllocatorDataPreparation + +from .utils import check_allocator_constraints, check_metric_dates, get_hill_params + + +class BudgetAllocator: + """Budget Allocator for marketing mix modeling optimization.""" + + def __init__( + self, + mmm_data: MMMData, + featurized_mmm_data: FeaturizedMMMData, + hyperparameters: Hyperparameters, + pareto_result: ParetoResult, + select_model: str, + params: AllocatorParams, + ): + """Initialize the Budget Allocator.""" + self.mmm_data = mmm_data + self.hyperparameters = hyperparameters + self.featurized_mmm_data = featurized_mmm_data + self.pareto_result = pareto_result + self.select_model = select_model + self.params = params + self.allocator_data_preparer = AllocatorDataPreparation( + mmm_data=self.mmm_data, + pareto_result=self.pareto_result, + hyperparameters=self.hyperparameters, + params=self.params, + select_model=self.select_model, + ) + + self.allocator_data_preparer._validate_inputs() + self.allocator_data_preparer._initialize_data() + + self.logger = logging.getLogger(__name__) + for channel in self.allocator_data_preparer.media_spend_sorted: + coef = self.allocator_data_preparer.dt_best_coef[ + self.allocator_data_preparer.dt_best_coef["rn"] == channel + ]["coef"].values[0] + self.logger.debug(f"{channel}: {coef}") + + def optimize(self) -> AllocationResult: + """Run the budget allocation optimization.""" + self.logger.debug( + f"\nStarting optimization for scenario: {self.params.scenario}" + ) + + # Initialize constraints based on scenario + if self.params.scenario == SCENARIO_TARGET_EFFICIENCY: + self.constraints = ( + self.allocator_data_preparer._setup_target_efficiency_constraints() + ) + else: + self.constraints = self.allocator_data_preparer._setup_constraints() + + bounded_result = self._run_optimization(bounded=True) + unbounded_result = self._run_optimization(bounded=False) + + return self._process_optimization_results(bounded_result, unbounded_result) + + def _run_optimization(self, bounded: bool = True) -> OptimizationResult: + """Run optimization while respecting excluded channels.""" + self.logger.debug(f"\nOptimization run (Bounded: {bounded})") + + # Calculate bounds + if bounded: + lower_bounds = self.constraints.lower_bounds + upper_bounds = self.constraints.upper_bounds + else: + multiplier = self.params.channel_constr_multiplier + lower_bounds = np.maximum( + 0, + self.allocator_data_preparer.init_spend_unit + * (1 - (1 - self.params.channel_constr_low) * multiplier), + ) + upper_bounds = self.allocator_data_preparer.init_spend_unit * ( + 1 + (self.params.channel_constr_up - 1) * multiplier + ) + + # For excluded channels, set bounds to initial spend + if np.any(self.allocator_data_preparer.exclude): + lower_bounds[self.allocator_data_preparer.exclude] = ( + self.allocator_data_preparer.init_spend_unit[ + self.allocator_data_preparer.exclude + ] + ) + upper_bounds[self.allocator_data_preparer.exclude] = ( + self.allocator_data_preparer.init_spend_unit[ + self.allocator_data_preparer.exclude + ] + ) + + bounds = list(zip(lower_bounds, upper_bounds)) + + # Generate starting points + starting_points = [ + self.allocator_data_preparer.init_spend_unit, + lower_bounds, + upper_bounds, + (lower_bounds + upper_bounds) / 2, + np.random.uniform(lower_bounds, upper_bounds), + ] + + # Setup constraints based on scenario + constraints = [] + if self.params.scenario == SCENARIO_TARGET_EFFICIENCY: + if self.allocator_data_preparer.dep_var_type == "revenue": + constraints.append( + { + "type": "ineq", + "fun": lambda x: ( + np.sum( + [ + self.allocator_data_preparer.calculate_response( + spend, i + ) + for i, spend in enumerate(x) + ] + ) + / np.sum(x) + - self.constraints.target_constraint + ), + } + ) + else: # CPA + constraints.append( + { + "type": "ineq", + "fun": lambda x: ( + self.constraints.target_constraint + - np.sum(x) + / np.sum( + [ + self.allocator_data_preparer.calculate_response( + spend, i + ) + for i, spend in enumerate(x) + ] + ) + ), + } + ) + else: + constraints.append( + { + "type": "eq" if self.params.constr_mode == "eq" else "ineq", + "fun": lambda x: np.sum(x) - self.constraints.budget_constraint, + "jac": lambda x: np.ones_like(x), + } + ) + + best_result = None + best_objective = float("inf") + + for i, x0 in enumerate(starting_points): + try: + result = minimize( + fun=self._objective_function, + x0=x0, + method="SLSQP", + bounds=bounds, + constraints=constraints, + options={ + "ftol": 1e-10, + "maxiter": self.params.maxeval, + "disp": False, + }, + ) + + if result.success and result.fun < best_objective: + # Ensure excluded channels maintain initial spend + final_solution = result.x.copy() + final_solution[self.allocator_data_preparer.exclude] = ( + self.allocator_data_preparer.init_spend_unit[ + self.allocator_data_preparer.exclude + ] + ) + + total_response = np.sum( + [ + self.allocator_data_preparer.calculate_response(spend, i) + for i, spend in enumerate(final_solution) + ] + ) + + best_objective = result.fun + best_result = OptimizationResult( + solution=final_solution, + objective=result.fun, + gradient=result.jac if hasattr(result, "jac") else None, + constraints={}, + ) + self.logger.debug("\n=== Optimization Run ===") + self.logger.debug("Bounds:", bounds) + self.logger.debug("Starting points:", starting_points) + self.logger.debug("Constraints:", constraints) + except Exception as e: + self.logger.error(f"Optimization attempt {i+1} failed: {str(e)}") + continue + + if best_result is None: + raise ValueError("All optimization attempts failed") + + return best_result + + def _objective_function(self, x: np.ndarray) -> float: + """Objective function with target efficiency handling.""" + responses = np.array( + [ + self.allocator_data_preparer.calculate_response(spend, i) + for i, spend in enumerate(x) + ] + ) + + total_response = np.sum(responses) + total_spend = np.sum(x) + self.logger.debug("\n=== Objective Function Call ===") + self.logger.debug("Input x:", x) + self.logger.debug("Responses:", responses) + self.logger.debug("Total response:", total_response) + self.logger.debug("Total spend:", total_spend) + if self.params.scenario == SCENARIO_TARGET_EFFICIENCY: + if self.allocator_data_preparer.dep_var_type == "revenue": + actual_roas = total_response / total_spend if total_spend > 0 else 0 + roas_violation = max( + 0, self.constraints.target_constraint - actual_roas + ) + return -total_response + 1e6 * roas_violation + else: + actual_cpa = ( + total_spend / total_response if total_response > 0 else float("inf") + ) + cpa_violation = max(0, actual_cpa - self.constraints.target_constraint) + return total_spend + 1e6 * cpa_violation + else: + budget_violation = abs(total_spend - self.constraints.budget_constraint) + bounds_violation = np.sum( + np.maximum(0, self.constraints.lower_bounds - x) + + np.maximum(0, x - self.constraints.upper_bounds) + ) + return -total_response + 1e6 * (budget_violation + bounds_violation) + + def _process_optimization_results( + self, bounded_result: OptimizationResult, unbounded_result: OptimizationResult + ) -> AllocationResult: + """Process optimization results.""" + # Calculate responses + bounded_response = np.array([]) + bounded_marginal = np.array([]) + bounded_spend = np.array([]) + + unbounded_response = np.array([]) + unbounded_marginal = np.array([]) + unbounded_spend = np.array([]) + + for i, channel in enumerate(self.allocator_data_preparer.media_spend_sorted): + # If channel was excluded (has 0 coefficient or 0 constraints), set spend to 0 + if self.allocator_data_preparer.exclude[i]: + bounded_spend = np.append(bounded_spend, 0.0) + unbounded_spend = np.append(unbounded_spend, 0.0) + bounded_response = np.append(bounded_response, 0.0) + unbounded_response = np.append(unbounded_response, 0.0) + bounded_marginal = np.append(bounded_marginal, 0.0) + unbounded_marginal = np.append(unbounded_marginal, 0.0) + else: + # Use optimization results for non-excluded channels + bounded_spend = np.append(bounded_spend, bounded_result.solution[i]) + unbounded_spend = np.append( + unbounded_spend, unbounded_result.solution[i] + ) + + response = self.allocator_data_preparer.calculate_response( + bounded_result.solution[i], i + ) + marginal = self.allocator_data_preparer.calculate_marginal_response( + bounded_result.solution[i], i + ) + bounded_response = np.append(bounded_response, response) + bounded_marginal = np.append(bounded_marginal, marginal) + + response = self.allocator_data_preparer.calculate_response( + unbounded_result.solution[i], i + ) + marginal = self.allocator_data_preparer.calculate_marginal_response( + unbounded_result.solution[i], i + ) + unbounded_response = np.append(unbounded_response, response) + unbounded_marginal = np.append(unbounded_marginal, marginal) + + # Create OptimOutData + optim_out = OptimOutData( + channels=self.allocator_data_preparer.media_spend_sorted, + init_spend_unit=self.allocator_data_preparer.init_spend_unit, + init_response_unit=self.allocator_data_preparer.init_response, + init_response_marg_unit=self.allocator_data_preparer.init_response_marg, + optm_spend_unit=bounded_spend, # Use modified spend array + optm_response_unit=bounded_response, + optm_response_marg_unit=bounded_marginal, + optm_spend_unit_unbound=unbounded_spend, # Use modified spend array + optm_response_unit_unbound=unbounded_response, + optm_response_marg_unit_unbound=unbounded_marginal, + date_min=str(self.allocator_data_preparer.date_min), + date_max=str(self.allocator_data_preparer.date_max), + metric=( + "ROAS" + if self.allocator_data_preparer.dep_var_type == "revenue" + else "CPA" + ), + periods=f"{len(self.allocator_data_preparer.hist_filtered)} {self.mmm_data.mmmdata_spec.interval_type}s", + ) + # Create MainPoints + response_points = np.vstack( + [ + self.allocator_data_preparer.init_response, + bounded_response, + unbounded_response, + ] + ) + + spend_points = np.vstack( + [ + self.allocator_data_preparer.init_spend_unit, + bounded_result.solution, + unbounded_result.solution, + ] + ) + + main_points = MainPoints( + response_points=response_points, + spend_points=spend_points, + channels=self.allocator_data_preparer.media_spend_sorted, + ) + + return AllocationResult( + dt_optimOut=optim_out, + mainPoints=main_points, + scenario=self.params.scenario, + usecase=self.allocator_data_preparer._determine_usecase(), + total_budget=self.constraints.budget_constraint, + skipped_coef0=self.allocator_data_preparer._identify_zero_coefficient_channels(), + skipped_constr=self.allocator_data_preparer._identify_zero_constraint_channels(), + no_spend=self.allocator_data_preparer._identify_zero_spend_channels(), + ) + + @property + def total_response_lift(self) -> float: + """Calculate total response lift from optimization.""" + if not hasattr(self, "_optimization_result"): + raise ValueError("Optimization hasn't been run yet") + + initial_total_response = np.sum(self.init_response) + optimized_total_response = -self._optimization_result.objective + return (optimized_total_response / initial_total_response) - 1 + + @property + def spend_efficiency(self) -> Dict[str, float]: + """Calculate spend efficiency metrics.""" + if not hasattr(self, "_optimization_result"): + raise ValueError("Optimization hasn't been run yet") + + optimized_efficiency = -self._optimization_result.objective / np.sum( + self._optimization_result.solution + ) + initial_efficiency = np.sum(self.init_response) / self.init_spend_total + + return { + "initial_efficiency": initial_efficiency, + "optimized_efficiency": optimized_efficiency, + "efficiency_improvement": (optimized_efficiency / initial_efficiency) - 1, + } diff --git a/python/src/robyn/allocator/utils.py b/python/src/robyn/allocator/utils.py new file mode 100644 index 000000000..225f764a9 --- /dev/null +++ b/python/src/robyn/allocator/utils.py @@ -0,0 +1,282 @@ +from dataclasses import dataclass +from typing import Dict, List, Optional, Tuple, Union +import numpy as np +import pandas as pd +from datetime import datetime, timedelta +import logging +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.modeling.entities.pareto_result import ParetoResult + + +logger = logging.getLogger(__name__) + + +@dataclass +class HillParameters: + """Parameters for hill transformation and response calculation.""" + + alphas: np.ndarray + gammas: np.ndarray + coefs: np.ndarray + carryover: np.ndarray + + +def get_hill_params( + mmm_data: MMMData, + hyperparameters: Hyperparameters, + dt_hyppar: pd.DataFrame, + dt_coef: pd.DataFrame, + media_sorted: np.ndarray, + select_model: str, + media_vec_collect: pd.DataFrame = None, +) -> HillParameters: + """Get Hill transformation parameters with proper coefficient mapping.""" + logger.debug("\nExtracting Hill parameters...") + + dt_coef_filtered = dt_coef[dt_coef["solID"] == select_model].set_index("rn") + + coefs = [] + alphas = [] + gammas = [] + carryover = [] + + for channel in media_sorted: + logger.debug(f"\nProcessing channel: {channel}") + + # Get alpha parameter + alpha_col = f"{channel}_alphas" + logger.debug(f"alpha_col: {alpha_col}") + logger.debug("dt_hyppar: ", dt_hyppar) + logger.debug("dt_hyppar alpha_col: ", dt_hyppar[alpha_col]) + alpha = dt_hyppar[alpha_col].iloc[0] + alphas.append(alpha) + logger.debug(f"Alpha: {alpha}") + + # Get gamma parameter + gamma_col = f"{channel}_gammas" + gamma = dt_hyppar[gamma_col].iloc[0] + gammas.append(gamma) + logger.debug(f"Gamma: {gamma}") + + # Get coefficient + try: + coef = float(dt_coef_filtered.loc[channel, "coef"]) + except KeyError: + logger.debug(f"Warning: No coefficient found for {channel}, using 0.0") + coef = 0.0 + coefs.append(coef) + logger.debug(f"Coefficient: {coef}") + + # Calculate carryover to match R implementation + if hyperparameters.adstock == "geometric": + channel_params = hyperparameters.hyperparameters[channel] + # Use mean instead of sum/2 + theta = np.mean(channel_params.thetas) + carryover_val = geometric_adstock(theta) + else: + shape = np.mean(hyperparameters.hyperparameters[channel].shapes) + scale = np.mean(hyperparameters.hyperparameters[channel].scales) + carryover_val = weibull_adstock(shape, scale) + + carryover.append(carryover_val) + logger.debug(f"Carryover: {carryover_val}") + + logger.debug(f"Final parameter set for {channel}:") + logger.debug(f" Alpha: {alpha}") + logger.debug(f" Gamma: {gamma}") + logger.debug(f" Coefficient: {coef}") + logger.debug(f" Carryover: {carryover_val}") + + return HillParameters( + alphas=np.array(alphas), + gammas=np.array(gammas), + coefs=np.array(coefs), + carryover=np.array(carryover), + ) + + +def calculate_carryover( + mmm_data: MMMData, + hyperparameters: Hyperparameters, + media_vec_collect: pd.DataFrame, + media_sorted: np.ndarray, + select_model: str, +) -> np.ndarray: + """ + Calculate carryover effects for each channel using hyperparameters directly. + """ + carryover = np.zeros(len(media_sorted)) + + logger.debug(f"\nCalculating carryover effects for channels: {media_sorted}") + logger.debug(f"Adstock type: {hyperparameters.adstock}") + + # logger.debug available channels in hyperparameters + logger.debug("\nAvailable channels in hyperparameters:") + for channel, params in hyperparameters.hyperparameters.items(): + logger.debug(f" {channel}:") + logger.debug(f" thetas: {params.thetas}") + logger.debug(f" alphas: {params.alphas}") + logger.debug(f" gammas: {params.gammas}") + + for i, channel in enumerate(media_sorted): + logger.debug(f"\nProcessing channel: {channel}") + try: + if hyperparameters.adstock == "geometric": + # Get channel parameters from hyperparameters dictionary + channel_params = hyperparameters.hyperparameters[channel] + if channel_params.thetas: + theta = sum(channel_params.thetas) / 2 # Use mean of min and max + logger.debug( + f"Found theta range: {channel_params.thetas}, using mean value: {theta}" + ) + carryover[i] = geometric_adstock(theta) + else: + logger.debug(f"No theta values found for {channel}") + logger.debug("Using default carryover effect of 0.1") + carryover[i] = 0.1 + else: # weibull + channel_params = hyperparameters.hyperparameters[channel] + if channel_params.shapes and channel_params.scales: + shape = sum(channel_params.shapes) / 2 + scale = sum(channel_params.scales) / 2 + logger.debug( + f"Shape range: {channel_params.shapes}, Scale range: {channel_params.scales}" + ) + logger.debug(f"Using mean values - Shape: {shape}, Scale: {scale}") + carryover[i] = weibull_adstock(shape, scale) + else: + logger.debug(f"Missing shape/scale values for {channel}") + logger.debug("Using default carryover effect of 0.1") + carryover[i] = 0.1 + + logger.debug(f"Calculated carryover effect: {carryover[i]}") + + except KeyError as e: + logger.debug(f"Error: Channel {channel} not found in hyperparameters") + logger.debug("Using default carryover effect of 0.1") + carryover[i] = 0.1 + except Exception as e: + logger.debug(f"Error processing channel {channel}: {str(e)}") + logger.debug("Using default carryover effect of 0.1") + carryover[i] = 0.1 + + logger.debug("\nFinal carryover effects:") + for ch, effect in zip(media_sorted, carryover): + logger.debug(f"{ch}: {effect}") + + return carryover + + +def geometric_adstock(theta: float) -> float: + if theta >= 1 or theta <= 0: + return 0 + return theta / (1 - theta) + + +def weibull_adstock(shape: float, scale: float) -> float: + """ + Calculate Weibull adstock effect with input validation. + + Args: + shape: Shape parameter (must be positive) + scale: Scale parameter (must be positive) + + Returns: + Adstock effect value + """ + if shape <= 0 or scale <= 0: + return 0 + return scale * np.exp(-(1 / shape)) + + +def calculate_gradient( + spend: float, alpha: float, gamma: float, coef: float, carryover: float +) -> float: + """ + Calculate gradient of response function for a given spend value. + + Args: + spend: Spend value + alpha: Hill function alpha parameter + gamma: Hill function gamma parameter + coef: Channel coefficient + carryover: Carryover effect + + Returns: + Gradient value + """ + x_adstocked = spend + carryover + numerator = alpha * (gamma**alpha) * (x_adstocked ** (alpha - 1)) + denominator = (x_adstocked**alpha + gamma**alpha) ** 2 + return -coef * numerator / denominator + + +def check_allocator_constraints( + channel_constr_low: np.ndarray, channel_constr_up: np.ndarray +) -> None: + """ + Validate allocator constraints. + + Args: + channel_constr_low: Lower bounds for channel constraints + channel_constr_up: Upper bounds for channel constraints + + Raises: + ValueError: If constraints are invalid + """ + if np.any(channel_constr_low < 0): + raise ValueError("Lower bounds must be non-negative") + + if np.any(channel_constr_up <= 0): + raise ValueError("Upper bounds must be positive") + + if len(channel_constr_low) > 1 and len(channel_constr_up) > 1: + if len(channel_constr_low) != len(channel_constr_up): + raise ValueError("Lower and upper bounds must have same length") + + if np.any(channel_constr_up < channel_constr_low): + raise ValueError("Upper bounds must be greater than lower bounds") + + +def check_metric_dates( + date_range: str, dates: pd.Series, interval: int, is_allocator: bool = True +) -> Dict[str, Union[List[datetime], int]]: + """ + Check and process date ranges for metrics calculation. + + Args: + date_range: Date range specification ('all', 'last', or date range) + dates: Series of dates + interval: Time interval in days + is_allocator: Whether function is called from allocator + + Returns: + Dictionary containing processed date range and interval information + """ + dates = pd.to_datetime(dates) + date_min = dates.min() + date_max = dates.max() + + if date_range == "all": + selected_dates = dates.tolist() + elif date_range == "last": + selected_dates = [date_max] + elif isinstance(date_range, (list, tuple)) and len(date_range) == 2: + range_start = pd.to_datetime(date_range[0]) + range_end = pd.to_datetime(date_range[1]) + + if range_start < date_min or range_end > date_max: + raise ValueError("Date range must be within available data dates") + + selected_dates = dates[(dates >= range_start) & (dates <= range_end)].tolist() + else: + try: + single_date = pd.to_datetime(date_range) + if single_date < date_min or single_date > date_max: + raise ValueError("Date must be within available data dates") + selected_dates = [single_date] + except: + raise ValueError("Invalid date range format") + + return {"date_range_updated": selected_dates, "interval": interval} diff --git a/python/src/robyn/calibration/media_effect_calibration.py b/python/src/robyn/calibration/media_effect_calibration.py new file mode 100644 index 000000000..677591d18 --- /dev/null +++ b/python/src/robyn/calibration/media_effect_calibration.py @@ -0,0 +1,367 @@ +# pyre-strict + +import logging +from typing import List +import pandas as pd +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.entities.calibration_input import ( + CalibrationInput, + ChannelCalibrationData, +) +from robyn.data.entities.enums import CalibrationScope +from robyn.calibration.media_transformation import MediaTransformation +from dataclasses import dataclass, field +from typing import Dict, Tuple, Optional +import numpy as np + + +@dataclass(frozen=True) +class CalibrationResult: + """ + Immutable data class that holds the results of a calibration run. + + Attributes: + channel_scores (Dict[str, float]): MAPE scores per channel + calibration_constraint (float): Acceptable error range (0.01-0.1) + calibrated_models (List[str]): Model IDs that passed calibration + """ + + channel_scores: Dict[str, float] + calibration_constraint: float = 0.05 # Default constraint moved to class definition + calibrated_models: List[str] = field(default_factory=list) # Empty list default + + def get_mean_mape(self) -> float: + """Returns mean absolute percentage error across all channels.""" + return np.mean(list(self.channel_scores.values())) + + def is_model_calibrated(self, mape_threshold: float = 0.1) -> bool: + """Checks if model meets calibration criteria.""" + mean_mape = self.get_mean_mape() + return mean_mape <= mape_threshold + + def __str__(self) -> str: + scores_str = "\n".join( + f" {channel}: MAPE = {score:.2%}" + for channel, score in self.channel_scores.items() + ) + return ( + f"CalibrationResult(\n" + f" Mean MAPE: {self.get_mean_mape():.2%}\n" + f" Constraint: {self.calibration_constraint}\n" + f" Channel Scores:\n{scores_str}\n" + f" Calibrated: {self.is_model_calibrated()}\n" + f")" + ) + + +class MediaEffectCalibrator: + """ + Handles the calibration process for media mix models by comparing model predictions + against actual experimental results. + """ + + def __init__( + self, + mmm_data: MMMData, + hyperparameters: Hyperparameters, + calibration_input: CalibrationInput, + model_coefficients: Optional[Dict[str, float]] = None, + ): + """Initialize calibration with model data and parameters.""" + self.logger = logging.getLogger(__name__) + + self.logger.info("Initializing MediaEffectCalibrator") + self.logger.debug( + "Input parameters: MMMData shape: %s, Hyperparameters count: %d, Calibration channels: %s", + mmm_data.data.shape if mmm_data.data is not None else "None", + len(hyperparameters.channel_hyperparameters) if hyperparameters else 0, + ( + list(calibration_input.channel_data.keys()) + if calibration_input + else "None" + ), + ) + + self.mmm_data = mmm_data + self.hyperparameters = hyperparameters + self.calibration_input = calibration_input + self.media_transformation = MediaTransformation(hyperparameters) + self.model_coefficients = model_coefficients or {} + + # Convert date column to datetime if it's not already + date_col = self.mmm_data.mmmdata_spec.date_var + if not pd.api.types.is_datetime64_any_dtype(self.mmm_data.data[date_col]): + self.logger.debug("Converting date column '%s' to datetime", date_col) + self.mmm_data.data[date_col] = pd.to_datetime(self.mmm_data.data[date_col]) + + self._validate_inputs() + self.logger.info("MediaEffectCalibrator initialization complete") + + def _validate_inputs(self) -> None: + """Validates that calibration inputs match model data requirements.""" + self.logger.debug("Starting input validation") + + all_valid_channels = set( + self.mmm_data.mmmdata_spec.paid_media_spends + + self.mmm_data.mmmdata_spec.organic_vars + ) + self.logger.debug("Valid channels: %s", sorted(all_valid_channels)) + + for channel_key in self.calibration_input.channel_data: + if isinstance(channel_key, tuple): + channels = list(channel_key) + else: + channels = [channel_key] + + self.logger.debug("Validating channel(s): %s", channels) + invalid_channels = [ch for ch in channels if ch not in all_valid_channels] + + if invalid_channels: + error_msg = ( + f"Channel(s) {', '.join(invalid_channels)} not found in model variables. " + f"Available channels: {', '.join(sorted(all_valid_channels))}" + ) + self.logger.error(error_msg) + raise ValueError(error_msg) + + # Validate dates + model_start = pd.to_datetime(self.mmm_data.mmmdata_spec.window_start) + model_end = pd.to_datetime(self.mmm_data.mmmdata_spec.window_end) + + self.logger.debug("Model window: %s to %s", model_start, model_end) + + for channel_key, data in self.calibration_input.channel_data.items(): + lift_start = pd.Timestamp(data.lift_start_date) + lift_end = pd.Timestamp(data.lift_end_date) + + self.logger.debug( + "Validating dates for %s: %s to %s", channel_key, lift_start, lift_end + ) + + if not ( + model_start <= lift_start <= model_end + and model_start <= lift_end <= model_end + ): + error_msg = f"Dates for {channel_key} outside model window ({model_start} to {model_end})" + self.logger.error(error_msg) + raise ValueError(error_msg) + + self.logger.info("Input validation completed successfully") + + def calculate_immediate_effect_score( + self, + predictions: pd.Series, + lift_value: float, + spend: float, + channel: str, + data: ChannelCalibrationData, + ) -> float: + """Calculates immediate effect score with detailed logging.""" + self.logger.debug("Calculating immediate effect for channel: %s", channel) + self.logger.debug( + "Input parameters - Lift value: %.2f, Spend: %.2f", lift_value, spend + ) + + # Get channel parameters + channel_params = self.hyperparameters.get_hyperparameter(channel) + theta = channel_params.thetas[0] + alpha = channel_params.alphas[0] + gamma = channel_params.gammas[0] + coef = self.model_coefficients.get(channel, 1.0) + + self.logger.debug( + "Channel parameters - Theta: %.3f, Alpha: %.3f, Gamma: %.3f, Coefficient: %.3f", + theta, + alpha, + gamma, + coef, + ) + + # Calculate effects + m_imme = predictions.copy() + m_total = self.media_transformation._apply_geometric_adstock(predictions, theta) + m_caov = m_total - m_imme + m_caov_sat = self.media_transformation._apply_saturation(m_caov, alpha, gamma) + m_caov_decomp = m_caov_sat * coef + + lift_days = ( + pd.Timestamp(data.lift_end_date) - pd.Timestamp(data.lift_start_date) + ).days + 1 + decomp_days = len(predictions) + scaled_effect = (m_caov_decomp.sum() / decomp_days) * lift_days + + self.logger.debug( + "Effect calculations - Raw sum: %.2f, Total adstock: %.2f, Carryover: %.2f", + predictions.sum(), + m_total.sum(), + m_caov.sum(), + ) + self.logger.debug( + "Saturated carryover: %.2f, Final scaled effect: %.2f, Target lift: %.2f", + m_caov_sat.sum(), + scaled_effect, + lift_value, + ) + + mape = np.abs((scaled_effect - lift_value) / lift_value) + self.logger.info("Channel %s immediate effect MAPE: %.4f", channel, mape) + + return float(mape) + + def calculate_total_effect_score( + self, + predictions: pd.Series, + lift_value: float, + spend: float, + channel: str, + data: ChannelCalibrationData, + ) -> float: + """Calculates total effect score with detailed logging.""" + self.logger.debug("Calculating total effect for channel: %s", channel) + self.logger.debug( + "Input parameters - Lift value: %.2f, Spend: %.2f", lift_value, spend + ) + + # Get channel parameters + channel_params = self.hyperparameters.get_hyperparameter(channel) + theta = channel_params.thetas[0] + alpha = channel_params.alphas[0] + gamma = channel_params.gammas[0] + coef = self.model_coefficients.get(channel, 1.0) + + self.logger.debug( + "Channel parameters - Theta: %.3f, Alpha: %.3f, Gamma: %.3f, Coefficient: %.3f", + theta, + alpha, + gamma, + coef, + ) + + # Calculate effects + m_imme = predictions.copy() + m_total = self.media_transformation._apply_geometric_adstock(predictions, theta) + m_caov = m_total - m_imme + + # Calculate scaling factor + if spend > 0: + revenue_per_spend = lift_value / spend + scale_factor = revenue_per_spend + self.logger.debug("Using spend-based scaling factor: %.4f", scale_factor) + else: + mean_value = predictions.mean() + scale_factor = lift_value / (mean_value if mean_value > 0 else 1.0) + self.logger.debug("Using mean-value scaling factor: %.4f", scale_factor) + + m_caov_sat = self.media_transformation._apply_saturation( + m_caov * scale_factor, alpha, gamma + ) + m_caov_decomp = m_caov_sat * coef + + lift_days = ( + pd.Timestamp(data.lift_end_date) - pd.Timestamp(data.lift_start_date) + ).days + 1 + decomp_days = len(predictions) + scaled_effect = (m_caov_decomp.sum() / decomp_days) * lift_days + + self.logger.debug( + "Effect calculations - Raw sum: %.2f, Total adstock: %.2f, Carryover: %.2f", + predictions.sum(), + m_total.sum(), + m_caov.sum(), + ) + self.logger.debug( + "Saturated carryover: %.2f, Final scaled effect: %.2f, Target lift: %.2f", + m_caov_sat.sum(), + scaled_effect, + lift_value, + ) + + mape = np.abs((scaled_effect - lift_value) / lift_value) + self.logger.info("Channel %s total effect MAPE: %.4f", channel, mape) + + return float(mape) + + def _get_channel_predictions( + self, channel_tuple: Tuple[str, ...], data: ChannelCalibrationData + ) -> pd.Series: + """Gets model predictions for channels during calibration period.""" + self.logger.debug("Getting predictions for channels: %s", channel_tuple) + + date_col = self.mmm_data.mmmdata_spec.date_var + lift_start = pd.Timestamp(data.lift_start_date) + lift_end = pd.Timestamp(data.lift_end_date) + dates = self.mmm_data.data[date_col] + + self.logger.debug("Prediction period: %s to %s", lift_start, lift_end) + + if lift_start in dates.values: + mask = (dates >= lift_start) & (dates <= lift_end) + else: + first_valid = dates[dates > lift_start].min() + self.logger.warning( + "Lift start date %s not found, using first valid date %s", + lift_start, + first_valid, + ) + mask = (dates >= (first_valid - pd.Timedelta(days=1))) & (dates <= lift_end) + + predictions = pd.Series(0, index=self.mmm_data.data.loc[mask].index) + + for channel in channel_tuple: + channel_values = self.mmm_data.data.loc[mask, channel] + self.logger.debug( + "Channel %s values - Mean: %.2f, Sum: %.2f", + channel, + channel_values.mean(), + channel_values.sum(), + ) + + if channel in self.mmm_data.mmmdata_spec.paid_media_spends: + predictions += channel_values + else: + predictions += channel_values + + self.logger.debug( + "Final predictions - Mean: %.2f, Sum: %.2f", + predictions.mean(), + predictions.sum(), + ) + return predictions + + def calibrate(self) -> CalibrationResult: + """Performs calibration with comprehensive logging.""" + self.logger.info("Starting calibration process") + calibration_scores = {} + + for channel_tuple, data in self.calibration_input.channel_data.items(): + self.logger.info("Processing channel(s): %s", channel_tuple) + try: + predictions = self._get_channel_predictions(channel_tuple, data) + channel_for_params = channel_tuple[0] + + self.logger.debug("Calibration scope: %s", data.calibration_scope) + if data.calibration_scope == CalibrationScope.IMMEDIATE: + score = self.calculate_immediate_effect_score( + predictions, data.lift_abs, data.spend, channel_for_params, data + ) + else: + score = self.calculate_total_effect_score( + predictions, data.lift_abs, data.spend, channel_for_params, data + ) + + calibration_scores[channel_tuple] = score + self.logger.info( + "Channel %s calibration score: %.4f", channel_tuple, score + ) + + except Exception as e: + error_msg = ( + f"Error calculating calibration for {channel_tuple}: {str(e)}" + ) + self.logger.error(error_msg, exc_info=True) + calibration_scores[channel_tuple] = float("inf") + + result = CalibrationResult(channel_scores=calibration_scores) + self.logger.info("Calibration complete - Final results: %s", str(result)) + return result diff --git a/python/src/robyn/calibration/media_transformation.py b/python/src/robyn/calibration/media_transformation.py new file mode 100644 index 000000000..5242049da --- /dev/null +++ b/python/src/robyn/calibration/media_transformation.py @@ -0,0 +1,179 @@ +# pyre-strict + +import logging + +import pandas as pd +import numpy as np +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.entities.enums import AdstockType + + +class MediaTransformation: + """ + Handles media transformations including adstock and saturation effects. + """ + + def __init__(self, hyperparameters: Hyperparameters): + """Initialize with model hyperparameters.""" + self.logger = logging.getLogger(__name__) + self.logger.info("Initializing MediaTransformation with hyperparameters") + self.logger.debug("Hyperparameters configuration: %s", hyperparameters) + self.hyperparameters = hyperparameters + + def _apply_geometric_adstock(self, values: pd.Series, theta: float) -> pd.Series: + """ + Applies geometric adstock transformation. + x[t] = x[t] + θ * x[t-1] + """ + self.logger.debug( + "Starting geometric adstock transformation with theta=%f", theta + ) + self.logger.debug("Input series shape: %s", values.shape) + + result = values.copy() + for t in range(1, len(values)): + result.iloc[t] += theta * result.iloc[t - 1] + + self.logger.debug("Completed geometric adstock transformation") + return result + + def apply_weibull_adstock( + self, values: pd.Series, shape: float, scale: float + ) -> pd.Series: + """ + Applies Weibull adstock transformation. + Uses shape and scale parameters to create decay curve. + """ + self.logger.debug( + "Starting Weibull adstock transformation with shape=%f, scale=%f", + shape, + scale, + ) + self.logger.debug("Input series shape: %s", values.shape) + + max_lag = len(values) + times = np.arange(max_lag) + weights = ( + (shape / scale) + * (times / scale) ** (shape - 1) + * np.exp(-((times / scale) ** shape)) + ) + weights = weights / weights.sum() # Normalize + + self.logger.debug("Calculated Weibull weights, proceeding with convolution") + result = pd.Series( + np.convolve(values, weights, mode="full")[: len(values)], index=values.index + ) + + self.logger.debug("Completed Weibull adstock transformation") + return result + + def apply_saturation( + self, values: pd.Series, alpha: float, gamma: float + ) -> pd.Series: + """ + Applies Hill function saturation transformation. + S(x) = (x^alpha) / (x^alpha + gamma^alpha) + """ + self.logger.debug( + "Starting saturation transformation with alpha=%f, gamma=%f", alpha, gamma + ) + self.logger.debug("Input series shape: %s", values.shape) + + result = (values**alpha) / (values**alpha + gamma**alpha) + + self.logger.debug("Completed saturation transformation") + return result + + def apply_media_transforms(self, values: pd.Series, channel: str) -> pd.Series: + """ + Applies adstock and saturation transformations to media values. + + Args: + values: The media values to transform + channel: The channel name to get correct hyperparameters + + Returns: + pd.Series: Transformed values + """ + self.logger.info("Starting media transformation for channel: %s", channel) + self.logger.debug("Input values shape: %s", values.shape) + + try: + channel_params = self.hyperparameters.get_hyperparameter(channel) + self.logger.debug( + "Retrieved hyperparameters for channel %s: %s", channel, channel_params + ) + + if self.hyperparameters.adstock == AdstockType.GEOMETRIC: + if not channel_params.thetas: + error_msg = ( + f"Geometric adstock requires theta values for channel {channel}" + ) + self.logger.error(error_msg) + raise ValueError(error_msg) + + theta = channel_params.thetas[0] # Use first theta value + self.logger.info("Applying geometric adstock transformation") + transformed = self._apply_geometric_adstock(values, theta) + else: + if not (channel_params.shapes and channel_params.scales): + error_msg = f"Weibull adstock requires shape and scale values for channel {channel}" + self.logger.error(error_msg) + raise ValueError(error_msg) + + shape = channel_params.shapes[0] # Use first shape value + scale = channel_params.scales[0] # Use first scale value + self.logger.info("Applying Weibull adstock transformation") + transformed = self._apply_weibull_adstock(values, shape, scale) + + if not (channel_params.alphas and channel_params.gammas): + error_msg = ( + f"Saturation requires alpha and gamma values for channel {channel}" + ) + self.logger.error(error_msg) + raise ValueError(error_msg) + + alpha = channel_params.alphas[0] # Use first alpha value + gamma = channel_params.gammas[0] # Use first gamma value + + self.logger.info("Applying saturation transformation") + result = self._apply_saturation(transformed, alpha, gamma) + + # Ensure we return a Series with the same index + if not isinstance(result, pd.Series): + self.logger.debug("Converting result to pandas Series") + result = pd.Series(result, index=values.index) + + self.logger.info("Completed media transformation for channel: %s", channel) + self.logger.debug("Output shape: %s", result.shape) + return result + + except Exception as e: + error_msg = f"Error transforming values for channel {channel}: {str(e)}" + self.logger.error(error_msg, exc_info=True) + raise ValueError(error_msg) + + def apply_carryover_effect(self, values: pd.Series) -> float: + """ + Calculates total effect including carryover by summing + all transformed values. + + Args: + values: Series of transformed values + + Returns: + float: Total effect value + """ + self.logger.debug("Calculating carryover effect") + self.logger.debug( + "Input values shape: %s", + values.shape if isinstance(values, pd.Series) else np.array(values).shape, + ) + + result = float( + values.sum() if isinstance(values, pd.Series) else np.sum(values) + ) + + self.logger.debug("Calculated carryover effect: %f", result) + return result diff --git a/python/src/robyn/common/common_util.py b/python/src/robyn/common/common_util.py new file mode 100644 index 000000000..e20834e04 --- /dev/null +++ b/python/src/robyn/common/common_util.py @@ -0,0 +1,57 @@ +# pyre-strict + +import logging + +from typing import Optional +import multiprocessing +from typing_extensions import Final + + +class CommonUtils: + """Utility class for common utilities.""" + + # Constants + MIN_CORES: Final[int] = 1 + + @staticmethod + def get_cores_available(requested_cores: Optional[int] = None) -> int: + """ + Determines the number of CPU cores to use based on available cores and requested cores. + + Args: + requested_cores: Optional number of cores requested. If None, uses all available cores. + + Returns: + int: Number of cores to use + + Raises: + ValueError: If requested_cores is less than 1 + """ + logger = logging.getLogger(__name__) + available_cores = multiprocessing.cpu_count() + + # If no cores requested, use all available + if requested_cores is None: + return available_cores + + # Validate requested cores + if requested_cores < CommonUtils.MIN_CORES: + requested_cores = CommonUtils.MIN_CORES + logger.warning( + "Requested cores must be at least %d. Got: %d. Will use %d cores.", + CommonUtils.MIN_CORES, + requested_cores, + CommonUtils.MIN_CORES, + ) + + # Log warning if requested cores exceed available cores + if requested_cores > available_cores: + logger.warning( + "Requested cores (%d) exceeds available cores (%d). Will use %d cores.", + requested_cores, + available_cores, + available_cores, + ) + + # Return minimum of requested vs available cores + return min(requested_cores, available_cores) diff --git a/python/src/robyn/common/config/logging.conf b/python/src/robyn/common/config/logging.conf new file mode 100644 index 000000000..a738ee069 --- /dev/null +++ b/python/src/robyn/common/config/logging.conf @@ -0,0 +1,29 @@ +[loggers] +keys=root + +[handlers] +keys=file,console + +[formatters] +keys=simple + +[logger_root] +level=DEBUG +handlers=file,console +qualname= + +[handler_file] +class=FileHandler +level=DEBUG +formatter=simple +args=('/tmp/robynpy/logs/robynpy_%(asctime)s.log', 'w') + +[handler_console] +class=StreamHandler +level=INFO +formatter=simple +args=(sys.stderr,) + +[formatter_simple] +format=%(asctime)s - %(name)s - %(levelname)s - %(message)s +datefmt=%Y-%m-%d %H:%M:%S \ No newline at end of file diff --git a/python/src/robyn/common/constants.py b/python/src/robyn/common/constants.py new file mode 100644 index 000000000..cb3a78404 --- /dev/null +++ b/python/src/robyn/common/constants.py @@ -0,0 +1,3 @@ +# pyre-strict + +HYPERPARAMETER_NAMES = ("thetas", "shapes", "scales", "alphas", "gammas", "penalty") diff --git a/python/src/robyn/common/logger.py b/python/src/robyn/common/logger.py new file mode 100644 index 000000000..628b5e7d7 --- /dev/null +++ b/python/src/robyn/common/logger.py @@ -0,0 +1,31 @@ +# pyre-strict + +import logging + +import pandas as pd + + +class RobynLogger: + + @staticmethod + def log_df( + logger, + df: pd.DataFrame, + logLevel: int = logging.DEBUG, + print_head: bool = False, + ): + """ + Log the shape and first few rows of a DataFrame. + + Args: + df (pd.DataFrame): DataFrame to log. + name (str): Name of the DataFrame. + """ + if df is None: + logger.log(logLevel, "DataFrame is None") + return + + logger.log(logLevel, f"DataFrame columns: {df.columns}") + logger.log(logLevel, f"DataFrame Shape: {df.shape}") + if print_head: + logger.log(logLevel, f"DataFrame Head: {df.head()}") diff --git a/python/src/robyn/data/entities/calibration_input.py b/python/src/robyn/data/entities/calibration_input.py new file mode 100644 index 000000000..9b0955c9d --- /dev/null +++ b/python/src/robyn/data/entities/calibration_input.py @@ -0,0 +1,82 @@ +# pyre-strict + +from dataclasses import dataclass, field +from typing import Dict, List, Tuple +import pandas as pd +from robyn.data.entities.enums import CalibrationScope, DependentVarType + + +@dataclass(frozen=True) +class ChannelCalibrationData: + """ + ChannelCalibrationData is an immutable data class that holds the calibration data for a single channel + or combination of channels. + """ + + lift_start_date: pd.Timestamp = field(default_factory=pd.Timestamp) + lift_end_date: pd.Timestamp = field(default_factory=pd.Timestamp) + lift_abs: float = 0 + spend: float = 0 + confidence: float = 0.0 + metric: DependentVarType = None + calibration_scope: CalibrationScope = CalibrationScope.IMMEDIATE + + def __str__(self) -> str: + return ( + f"ChannelCalibrationData(\n" + f" lift_start_date={self.lift_start_date},\n" + f" lift_end_date={self.lift_end_date},\n" + f" lift_abs={self.lift_abs},\n" + f" spend={self.spend},\n" + f" confidence={self.confidence},\n" + f" metric={self.metric},\n" + f" calibration_scope={self.calibration_scope}\n" + f")" + ) + + +@dataclass(frozen=True) +class CalibrationInput: + """ + CalibrationInput is an immutable data class that holds the necessary inputs for a calibration process. + + Attributes: + channel_data: Dictionary mapping channel identifiers to their calibration data. + Keys must be tuples of strings for both single and combined channels. + """ + + channel_data: Dict[Tuple[str, ...], ChannelCalibrationData] = field( + default_factory=dict + ) + + def __post_init__(self): + """ + Validates that all channel keys are tuples and converts single string channels + to single-element tuples if needed. + """ + new_channel_data = {} + for key, value in self.channel_data.items(): + if isinstance(key, str): + new_key = (key,) + elif not isinstance(key, tuple): + raise ValueError( + f"Channel key must be a tuple or string, got {type(key)}" + ) + else: + new_key = key + + if not all(isinstance(ch, str) for ch in new_key): + raise ValueError( + f"All channel names in tuple must be strings: {new_key}" + ) + + new_channel_data[new_key] = value + + object.__setattr__(self, "channel_data", new_channel_data) + + def __str__(self) -> str: + channel_strs = [] + for channels, data in self.channel_data.items(): + channel_repr = f" {channels}: {data}" + channel_strs.append(channel_repr) + return f"CalibrationInput(\n{chr(10).join(channel_strs)}\n)" diff --git a/python/src/robyn/data/entities/enums.py b/python/src/robyn/data/entities/enums.py new file mode 100644 index 000000000..ce98b3e4b --- /dev/null +++ b/python/src/robyn/data/entities/enums.py @@ -0,0 +1,154 @@ +# pyre-strict +# Enum classes for different types of variables, model parameters etc. + +from enum import Enum +from typing import List + + +class DependentVarType(str, Enum): + """ + Enum class for dependent variable types. + + Attributes: + REVENUE (str): Revenue type. + CONVERSION (str): Conversion type. + """ + + REVENUE = "revenue" + CONVERSION = "conversion" + + +class AdstockType(str, Enum): + """ + Enumeration class representing different types of adstock models. + Attributes: + GEOMETRIC (str): Represents the geometric adstock model. + WEIBULL (str): Represents the Weibull adstock model. + WEIBULL_CDF (str): Represents the Weibull cumulative distribution function adstock model. + WEIBULL_PDF (str): Represents the Weibull probability density function adstock model. + """ + + GEOMETRIC = "geometric" + WEIBULL = "weibull" + WEIBULL_CDF = "weibull_cdf" + WEIBULL_PDF = "weibull_pdf" + + +class SaturationType(str, Enum): + """ + Enum class for saturation types. + + Attributes: + MICHAELIS_MENTEN (str): Michaelis-Menten saturation type. + LOGISTIC (str): Logistic saturation type. + """ + + MICHAELIS_MENTEN = "michaelis_menten" + LOGISTIC = "logistic" + + +class ProphetVariableType(str, Enum): + """ + Enum class for Prophet variable types. + + Attributes: + TREND (str): Trend variable type. + SEASON (str): Seasonal variable type. + MONTHLY (str): Monthly variable type. + WEEKDAY (str): Weekday variable type. + HOLIDAY (str): Holiday variable type. + """ + + TREND = "trend" + SEASON = "season" + MONTHLY = "monthly" + WEEKDAY = "weekday" + HOLIDAY = "holiday" + + +class PaidMediaSigns(Enum): + """ + Enum class for paid media signs. + + Attributes: + POSITIVE (str): Positive sign. + NEGATIVE (str): Negative sign. + DEFAULT (str): Default sign. + """ + + POSITIVE = "positive" + NEGATIVE = "negative" + DEFAULT = "default" + + +class OrganicSigns(Enum): + """ + Enum class for Organic variables signs. + + Attributes: + POSITIVE (str): Positive sign. + NEGATIVE (str): Negative sign. + DEFAULT (str): Default sign. + """ + + POSITIVE = "positive" + NEGATIVE = "negative" + DEFAULT = "default" + + +class ContextSigns(Enum): + """ + Enum class for Context variables signs. + + Attributes: + POSITIVE (str): Positive sign. + NEGATIVE (str): Negative sign. + DEFAULT (str): Default sign. + """ + + POSITIVE = "positive" + NEGATIVE = "negative" + DEFAULT = "default" + + +class ProphetSigns(Enum): + """ + Enum class for prophet signs. + + Attributes: + POSITIVE (str): Positive sign. + NEGATIVE (str): Negative sign. + DEFAULT (str): Default sign. + """ + + POSITIVE = "positive" + NEGATIVE = "negative" + DEFAULT = "default" + + +class CalibrationScope(Enum): + """ + Enumeration representing the calibration scope. + + Attributes: + IMMEDIATE (str): Represents the immediate calibration scope. + TOTAL (str): Represents the total calibration scope. + """ + + IMMEDIATE = "immediate" + TOTAL = "total" + + +class PlotType(Enum): + """ + Enumeration of available plot types for the OnePagerReporter. + """ + + SPEND_EFFECT = "spend_effect" + WATERFALL = "waterfall" + FITTED_VS_ACTUAL = "fitted_vs_actual" + BOOTSTRAP = "bootstrap" + ADSTOCK = "adstock" + IMMEDIATE_CARRYOVER = "immediate_carryover" + RESPONSE_CURVES = "response_curves" + DIAGNOSTIC = "diagnostic" diff --git a/python/src/robyn/data/entities/holidays_data.py b/python/src/robyn/data/entities/holidays_data.py new file mode 100644 index 000000000..7a9c3154d --- /dev/null +++ b/python/src/robyn/data/entities/holidays_data.py @@ -0,0 +1,47 @@ +# pyre-strict + +from typing import List +import pandas as pd +from robyn.data.entities.enums import ProphetVariableType +from robyn.data.entities.enums import ProphetSigns + + +class HolidaysData: + def __init__( + self, + dt_holidays: pd.DataFrame, + prophet_vars: List[ProphetVariableType], + prophet_signs: List[ProphetSigns], + prophet_country: str, # TODO Is there a library for country codes so that we can type + ) -> None: + """ + Initialize a HolidaysData object. + + Args: + dt_holidays (pd.DataFrame): A pandas DataFrame containing holiday data. + prophet_vars (List[ProphetVariableType]): A list of Prophet variable types. + prophet_signs (List[ProphetSigns]): A list of signs for Prophet variables. + prophet_country (str): The country for which holidays are defined. + + Returns: + None + """ + self.dt_holidays: pd.DataFrame = dt_holidays + self.prophet_vars: List[ProphetVariableType] = prophet_vars + self.prophet_signs: List[ProphetSigns] = prophet_signs + self.prophet_country: str = prophet_country + + def __str__(self) -> str: + """ + Return a string representation of the HolidaysData object. + + Returns: + str: A string representation of the object. + """ + return ( + f"HolidaysData:\n" + f"dt_holidays: {self.dt_holidays.shape}\n" + f"prophet_vars: {self.prophet_vars}\n" + f"prophet_signs: {self.prophet_signs}\n" + f"prophet_country: {self.prophet_country}\n" + ) diff --git a/python/src/robyn/data/entities/hyperparameters.py b/python/src/robyn/data/entities/hyperparameters.py new file mode 100644 index 000000000..a2712dc95 --- /dev/null +++ b/python/src/robyn/data/entities/hyperparameters.py @@ -0,0 +1,142 @@ +# pyre-strict + +from dataclasses import dataclass, field +from typing import Dict, List + +from robyn.data.entities.enums import AdstockType + + +@dataclass +class ChannelHyperparameters: + """ + ChannelHyperparameters is an immutable data class that holds the hyperparameters for a model. + + Attributes: + thetas (List[float]): List of theta values. + shapes (List[float]): List of shape values. + scales (List[float]): List of scale values. + alphas (List[float]): List of alpha values. + gammas (List[float]): List of gamma values. + penalty (List[float]): List of penalty values. + """ + + thetas: List[float] = None # if adstock is geometric + shapes: List[float] = None # if adstock is weibull + scales: List[float] = None # if adstock is weibull + alphas: List[float] = None # Mandatory + gammas: List[float] = None # Mandatory + penalty: List[bool] = ( + None # optional. User only provides if they want to use it. They don't provide values. Model run calculates it. + ) + + def __str__(self) -> str: + return ( + f"Hyperparameter(\n" + f" thetas={self.thetas},\n" + f" shapes={self.shapes},\n" + f" scales={self.scales},\n" + f" alphas={self.alphas},\n" + f" gammas={self.gammas},\n" + f" penalty={self.penalty}\n" + f")" + ) + + +@dataclass +class Hyperparameters: + """ + Hyperparameters is an immutable data class that holds a dictionary of hyperparameters for multiple channels. + + Attributes: + hyperparameters (Dict[str, Hyperparameter]): A dictionary of hyperparameters where the key is the channel name and the value is a Hyperparameter object. + """ + + hyperparameters: Dict[str, ChannelHyperparameters] = field(default_factory=dict) + adstock: AdstockType = AdstockType.GEOMETRIC # Mandatory. User provides this. + lambda_: float = 0.0 # User does not provide this. Model run calculates it. + train_size: List[float] = field(default_factory=lambda: [0.5, 0.8]) + hyper_bound_list_updated: Dict[str, List[float]] = field(default_factory=dict) + + def __str__(self) -> str: + return ( + f"Hyperparameters(\n" + + "\n".join( + f" {channel}={hyperparameter}" + for channel, hyperparameter in self.hyperparameters.items() + ) + + "\n)" + ) + + def copy(self): + # Create a new instance with the same data + return Hyperparameters( + hyperparameters=self.hyperparameters.copy(), + adstock=self.adstock, + lambda_=self.lambda_, + train_size=self.train_size.copy() if self.train_size else None, + ) + + def __post_init__(self): + self.update_hyper_bounds() + + def update_hyper_bounds(self): + self.hyper_bound_list_updated = {} + for key, value in self.hyperparameters.items(): + if isinstance(value, list) and len(value) == 2: + self.hyper_bound_list_updated[key] = value + if isinstance(self.lambda_, list) and len(self.lambda_) == 2: + self.hyper_bound_list_updated["lambda"] = self.lambda_ + + def get_hyperparameter(self, channel: str) -> ChannelHyperparameters: + """ + Get the hyperparameter for a specific channel. + + Args: + channel (str): The name of the channel. + + Returns: + Hyperparameter: The hyperparameter for the specified channel. + + Raises: + KeyError: If the channel is not found in the hyperparameters dictionary. + """ + return self.hyperparameters[channel] + + def has_channel(self, channel: str) -> bool: + """ + Check if a channel exists in the hyperparameters dictionary. + + Args: + channel (str): The name of the channel. + + Returns: + bool: True if the channel exists, False otherwise. + """ + return channel in self.hyperparameters + + @staticmethod + def get_hyperparameter_limits() -> Dict[str, List[str]]: + """ + Returns the hyperparameter limits. + Returns: + pd.DataFrame: The hyperparameter limits. + """ + return { + "thetas": [">=0", "<1"], + "alphas": [">0", "<10"], + "gammas": [">0", "<=1"], + "shapes": [">=0", "<20"], + "scales": [">=0", "<=1"], + } + + @property + def hyper_list_all(self): + return { + **self.hyperparameters, + "lambda": self.lambda_, + "train_size": self.train_size, + } + + @property + def all_fixed(self): + return len(self.hyper_bound_list_updated) == 0 diff --git a/python/src/robyn/data/entities/mmmdata.py b/python/src/robyn/data/entities/mmmdata.py new file mode 100644 index 000000000..deabcc565 --- /dev/null +++ b/python/src/robyn/data/entities/mmmdata.py @@ -0,0 +1,274 @@ +# pyre-strict + +from dataclasses import dataclass +from datetime import datetime +from typing import List, Optional, Any +import pandas as pd +from robyn.data.entities.enums import ( + ContextSigns, + DependentVarType, + OrganicSigns, + PaidMediaSigns, +) +import logging + +logger = logging.getLogger(__name__) + + +@dataclass +class MMMData: + class MMMDataSpec: + """ + Dependent Variable (Target Variable) + dep_var: The name of the column in the input dataframe that represents the dependent variable (target variable) that we want to model. This is the variable that we're trying to predict or explain. For example, it could be "sales", "revenue", "conversions", etc. + dep_var_type: The type of the dependent variable. In this case, it's an enumeration (DependentVarType) that can take values like REVENUE, CONVERSIONS, etc. This helps the model understand the nature of the dependent variable. + Date Variable + date_var: The name of the column in the input dataframe that represents the date variable. This is used to specify the time period for which the data is collected. If set to "auto", the model will automatically detect the date column. + Paid Media Variables + paid_media_spends: A list of column names in the input dataframe that represent the paid media spends (e.g., advertising expenses). These variables are used to model the impact of paid media on the dependent variable. + paid_media_vars: A list of column names in the input dataframe that represent additional paid media variables (e.g., ad impressions, clicks, etc.). These variables can be used to model non-linear relationships between paid media and the dependent variable. + paid_media_signs: A list of signs (positive or negative) that indicate the expected direction of the relationship between each paid media variable and the dependent variable. + Organic Variables + organic_vars: A list of column names in the input dataframe that represent organic variables (e.g., social media engagement, content metrics, etc.). These variables are used to model the impact of organic factors on the dependent variable. + organic_signs: A list of signs (positive or negative) that indicate the expected direction of the relationship between each organic variable and the dependent variable. + Context Variables + context_vars: A list of column names in the input dataframe that represent context variables (e.g., seasonality, weather, economic indicators, etc.). These variables are used to model external factors that can impact the dependent variable. + context_signs: A list of signs (positive or negative) that indicate the expected direction of the relationship between each context variable and the dependent variable. + Factor Variables + factor_vars: A list of column names in the input dataframe that represent factor variables (e.g., categorical variables like region, product category, etc.). These variables can be used to model non-linear relationships and interactions between variables. + + """ + + def __init__( + self, + dep_var: Optional[str] = None, + dep_var_type: DependentVarType = DependentVarType.REVENUE, + date_var: str = "auto", + window_start: datetime = None, + window_end: datetime = None, + rolling_window_length: int = None, + rolling_window_start_which: int = 0, + rolling_window_end_which: int = None, + paid_media_spends: Optional[List[str]] = None, + paid_media_vars: Optional[List[str]] = None, + paid_media_signs: Optional[List[PaidMediaSigns]] = None, + organic_vars: Optional[List[str]] = None, + organic_signs: Optional[List[OrganicSigns]] = None, + context_vars: Optional[List[str]] = None, + context_signs: Optional[List[ContextSigns]] = None, + factor_vars: Optional[List[str]] = None, + all_media: Optional[List[str]] = None, + day_interval: Optional[int] = 7, + interval_type: Optional[str] = "week", + ) -> None: + self.dep_var: Optional[str] = dep_var + self.dep_var_type: DependentVarType = dep_var_type + self.date_var: str = date_var + self.window_start: datetime = window_start + self.window_end: datetime = window_end + self.rolling_window_length: int = rolling_window_length + self.rolling_window_start_which: int = rolling_window_start_which + self.rolling_window_end_which: int = rolling_window_end_which + self.paid_media_spends: Optional[List[str]] = paid_media_spends + self.paid_media_vars: Optional[List[str]] = paid_media_vars + self.paid_media_signs: Optional[List[str]] = paid_media_signs + self.organic_vars: Optional[List[str]] = organic_vars + self.organic_signs: Optional[List[str]] = organic_signs + self.context_vars: Optional[List[str]] = context_vars + self.context_signs: Optional[List[str]] = context_signs + self.factor_vars: Optional[List[str]] = factor_vars + self.all_media = all_media or ( + paid_media_spends + organic_vars if organic_vars else paid_media_spends + ) + self.day_interval: Optional[int] = day_interval + self.interval_type: Optional[str] = interval_type + + def __str__(self) -> str: + return f""" + MMMDataSpec: + dep_var: {self.dep_var} + dep_var_type: {self.dep_var_type} + date_var: {self.date_var} + window_start: {self.window_start} + window_end: {self.window_end} + rolling_window_length: {self.rolling_window_length} + rolling_window_start_which: {self.rolling_window_start_which} + rolling_window_end_which: {self.rolling_window_end_which} + paid_media_spends: {self.paid_media_spends} + paid_media_vars: {self.paid_media_vars} + paid_media_signs: {self.paid_media_signs} + organic_vars: {self.organic_vars} + organic_signs: {self.organic_signs} + context_vars: {self.context_vars} + context_signs: {self.context_signs} + factor_vars: {self.factor_vars} + all_media: {self.all_media} + day_interval: {self.day_interval} + interval_type: {self.interval_type} + """ + + def update(self, **kwargs: Any) -> None: + """ + Update the attributes of the MMMDataSpec object. + + :param kwargs: Keyword arguments corresponding to the attributes to update. + """ + for key, value in kwargs.items(): + if hasattr(self, key): + setattr(self, key, value) + else: + raise AttributeError( + f"{key} is not a valid attribute of MMMDataSpec" + ) + + def __init__(self, data: pd.DataFrame, mmmdata_spec: MMMDataSpec) -> None: + """ + Initialize the MMMData class with a pandas DataFrame and an MMMDataSpec object. + + :param data: A pandas DataFrame containing the data. + :param mmmdata_spec: An MMMDataSpec object containing mapping of what is what in the provided data. + """ + self.data: pd.DataFrame = data + self.mmmdata_spec: MMMData.MMMDataSpec = mmmdata_spec + self.calculate_rolling_window_indices() + + def __str__(self) -> str: + """ + Returns a string representation of the MMMData object. + + Returns: + str: A formatted string containing key information about the MMMData object. + """ + data_info = ( + f"MMMData:\n" + f"DataFrame Info:\n" + f" Shape: {self.data.shape}\n" + f" Columns: {', '.join(self.data.columns)}\n" + f" Date Range: {self.data[self.mmmdata_spec.date_var].min()} to {self.data[self.mmmdata_spec.date_var].max()}\n" + f"\nDependent Variable:\n" + f" Name: {self.mmmdata_spec.dep_var}\n" + f" Type: {self.mmmdata_spec.dep_var_type}\n" + f" Summary Stats:\n" + f" Mean: {self.data[self.mmmdata_spec.dep_var].mean():.2f}\n" + f" Min: {self.data[self.mmmdata_spec.dep_var].min():.2f}\n" + f" Max: {self.data[self.mmmdata_spec.dep_var].max():.2f}\n" + f"\nMedia Variables:\n" + f" Paid Media Spends: {self.mmmdata_spec.paid_media_spends}\n" + f" Paid Media Variables: {self.mmmdata_spec.paid_media_vars}\n" + f" Organic Variables: {self.mmmdata_spec.organic_vars}\n" + f"\nOther Variables:\n" + f" Context Variables: {self.mmmdata_spec.context_vars}\n" + f" Factor Variables: {self.mmmdata_spec.factor_vars}\n" + f"\nTime Window Info:\n" + f" Window Start: {self.mmmdata_spec.window_start}\n" + f" Window End: {self.mmmdata_spec.window_end}\n" + f" Interval Type: {self.mmmdata_spec.interval_type}\n" + f" Day Interval: {self.mmmdata_spec.day_interval}" + ) + return data_info + + def display_data(self) -> None: + """ + Display the contents of the DataFrame. + """ + logger.debug(self.data) + + def get_summary(self) -> pd.DataFrame: + """ + Get a summary of the DataFrame, including basic statistics. + + :return: A pandas DataFrame containing the summary statistics. + """ + return self.data.describe() + + def add_column(self, column_name: str, data: List[Any]) -> None: + """ + Add a new column to the DataFrame. + + :param column_name: The name of the new column. + :param data: The data for the new column. + """ + self.data[column_name] = data + + def remove_column(self, column_name: str) -> None: + """ + Remove a column from the DataFrame. + + :param column_name: The name of the column to remove. + """ + self.data.drop(columns=[column_name], inplace=True) + + def calculate_rolling_window_indices(self) -> None: + # Ensure the date column is in datetime format + self.data[self.mmmdata_spec.date_var] = pd.to_datetime( + self.data[self.mmmdata_spec.date_var] + ) + # Convert window_start and window_end to datetime if they are strings + window_start = ( + pd.to_datetime(self.mmmdata_spec.window_start) + if isinstance(self.mmmdata_spec.window_start, str) + else self.mmmdata_spec.window_start + ) + window_end = ( + pd.to_datetime(self.mmmdata_spec.window_end) + if isinstance(self.mmmdata_spec.window_end, str) + else self.mmmdata_spec.window_end + ) + + # Calculate the index for the rolling window start + if window_start is not None: + closest_start_idx = ( + (self.data[self.mmmdata_spec.date_var] - window_start).abs().idxmin() + ) + closest_start_date = self.data[self.mmmdata_spec.date_var].iloc[ + closest_start_idx + ] + self.mmmdata_spec.rolling_window_start_which = closest_start_idx + # Adjust window_start to the closest date in the data + self.mmmdata_spec.window_start = closest_start_date + logger.debug( + f"Adjusted window_start to the closest date in the data: {closest_start_date}" + ) + + # Calculate the index for the rolling window end + if window_end is not None: + closest_end_idx = ( + (self.data[self.mmmdata_spec.date_var] - window_end).abs().idxmin() + ) + closest_end_date = self.data[self.mmmdata_spec.date_var].iloc[ + closest_end_idx + ] + self.mmmdata_spec.rolling_window_end_which = closest_end_idx + # Adjust window_end to the closest date in the data + self.mmmdata_spec.window_end = closest_end_date + logger.debug( + f"Adjusted window_end to the closest date in the data: {closest_end_date}" + ) + + # Calculate rolling window length + if window_start is not None and window_end is not None: + self.mmmdata_spec.rolling_window_length = ( + self.mmmdata_spec.rolling_window_end_which + - self.mmmdata_spec.rolling_window_start_which + + 1 + ) + + def set_default_factor_vars(self) -> None: + """ + Set the default factor variables. + """ + factor_variables = self.mmmdata_spec.factor_vars + selected_columns = self.data[self.mmmdata_spec.context_vars] + non_numeric_columns = ~selected_columns.applymap( + lambda x: isinstance(x, (int, float)) + ).all() + if non_numeric_columns.any(): + non_factor_columns = non_numeric_columns[ + ~non_numeric_columns.index.isin(factor_variables or []) + ] + non_factor_columns = non_factor_columns[non_factor_columns] + if len(non_factor_columns) > 0: + factor_variables = ( + factor_variables or [] + ) + non_factor_columns.index.tolist() + self.mmmdata_spec.factor_vars = factor_variables diff --git a/python/src/robyn/data/validation/calibration_input_validation.py b/python/src/robyn/data/validation/calibration_input_validation.py new file mode 100644 index 000000000..78537774d --- /dev/null +++ b/python/src/robyn/data/validation/calibration_input_validation.py @@ -0,0 +1,419 @@ +# pyre-strict +import logging +from robyn.data.entities.calibration_input import ( + CalibrationInput, + ChannelCalibrationData, +) +from robyn.data.entities.mmmdata import MMMData +from robyn.data.validation.validation import Validation, ValidationResult +import pandas as pd +from typing import List, Tuple, Set, Optional, Dict, Union +from robyn.data.entities.enums import CalibrationScope, DependentVarType + +logger = logging.getLogger(__name__) + + +class CalibrationInputValidation(Validation): + def __init__( + self, + mmmdata: MMMData, + calibration_input: CalibrationInput, + window_start: pd.Timestamp, + window_end: pd.Timestamp, + ) -> None: + logger.debug( + "Initializing CalibrationInputValidation with window: %s to %s", + window_start, + window_end, + ) + self.mmmdata = mmmdata + self.calibration_input = calibration_input + self.window_start = window_start + self.window_end = window_end + self.valid_channels: Set[str] = set(self.mmmdata.mmmdata_spec.paid_media_spends) + logger.debug("Valid channels initialized: %s", self.valid_channels) + + def check_obj_weights( + self, objective_weights: List[float], refresh: bool + ) -> ValidationResult: + """Check the objective weights for validity.""" + logger.debug( + "Checking objective weights: %s (refresh=%s)", objective_weights, refresh + ) + + if objective_weights is None: + if refresh: + logger.info("Using default weights [0, 1, 1] for refresh mode") + objective_weights = [0, 1, 1] # Default weights for refresh + else: + logger.debug("No objective weights provided and not in refresh mode") + return ValidationResult(status=True, error_details={}, error_message="") + + error_details: Dict[str, str] = {} + error_messages: List[str] = [] + + if len(objective_weights) not in [2, 3]: + msg = f"Expected 2 or 3 objective weights, got {len(objective_weights)}" + logger.warning(msg) + error_details["length"] = msg + error_messages.append("Invalid number of objective weights.") + + if any(weight < 0 or weight > 10 for weight in objective_weights): + msg = "Objective weights must be >= 0 & <= 10" + logger.warning(msg) + error_details["range"] = msg + error_messages.append("Objective weights out of valid range.") + + result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + logger.debug("Objective weights validation result: %s", result) + return result + + def _validate_channel_exists( + self, channel_key: Tuple[str, ...] + ) -> ValidationResult: + """Validate that all channels in the key exist in the data.""" + logger.debug("Validating channel existence for: %s", channel_key) + + if not isinstance(channel_key, tuple): + msg = f"Invalid channel key format: {channel_key}. Must be a tuple." + logger.error(msg) + return ValidationResult( + status=False, + error_details={str(channel_key): msg}, + error_message=msg.lower(), + ) + + missing_channels = [ch for ch in channel_key if ch not in self.valid_channels] + if missing_channels: + msg = f"Channel(s) not found in data: {', '.join(missing_channels)}" + logger.warning(msg) + return ValidationResult( + status=False, + error_details={channel_key: msg}, + error_message=msg.lower(), + ) + + logger.debug("Channel validation successful for: %s", channel_key) + return ValidationResult(status=True, error_details={}, error_message="") + + def _check_date_range(self) -> ValidationResult: + logger.debug("Checking date ranges for all channels") + error_details: Dict[Tuple[str, ...], str] = {} + error_messages: List[str] = [] + + for channel_key, data in self.calibration_input.channel_data.items(): + logger.debug( + "Checking date range for channel %s: %s to %s", + channel_key, + data.lift_start_date, + data.lift_end_date, + ) + + if ( + data.lift_start_date < self.window_start + or data.lift_end_date > self.window_end + ): + msg = ( + f"Date range {data.lift_start_date} to {data.lift_end_date} " + f"is outside modeling window {self.window_start} to {self.window_end}" + ) + logger.warning("Channel %s: %s", channel_key, msg) + error_details[channel_key] = msg + error_messages.append( + f"Date range for {'+'.join(channel_key)} is outside the modeling window." + ) + + result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + logger.debug("Date range validation result: %s", result) + return result + + def _check_spend_values(self) -> ValidationResult: + logger.debug("Checking spend values for all channels") + error_details: Dict[Tuple[str, ...], str] = {} + error_messages: List[str] = [] + + for channel_key, cal_data in self.calibration_input.channel_data.items(): + logger.debug("Validating spend for channel: %s", channel_key) + + channel_validation = self._validate_channel_exists(channel_key) + if not channel_validation.status: + logger.error("Channel validation failed for %s", channel_key) + return channel_validation + + actual_spend = self._get_channel_spend( + channel_key, cal_data.lift_start_date, cal_data.lift_end_date + ) + logger.debug( + "Channel %s - Expected spend: %f, Actual spend: %f", + channel_key, + cal_data.spend, + actual_spend, + ) + + if abs(actual_spend - cal_data.spend) > 0.1 * cal_data.spend: + msg = f"Spend mismatch: expected {cal_data.spend}, got {actual_spend}" + logger.warning("Channel %s: %s", channel_key, msg) + error_details[channel_key] = msg + error_messages.append( + f"Spend value for {'+'.join(channel_key)} does not match the input data (±10% tolerance)." + ) + + result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + logger.debug("Spend validation result: %s", result) + return result + + def _get_channel_spend( + self, + channel_key: Tuple[str, ...], + start_date: pd.Timestamp, + end_date: pd.Timestamp, + ) -> float: + """Calculate total spend for channels in the given date range.""" + logger.debug( + "Calculating spend for channel %s between %s and %s", + channel_key, + start_date, + end_date, + ) + + date_var = self.mmmdata.mmmdata_spec.date_var + data = self.mmmdata.data + date_mask = (data[date_var] >= start_date) & (data[date_var] <= end_date) + total_spend = sum(data.loc[date_mask, channel].sum() for channel in channel_key) + + logger.debug("Total spend calculated for %s: %f", channel_key, total_spend) + return total_spend + + def _check_metric_values(self) -> ValidationResult: + """Check if metric values match the dependent variable.""" + logger.debug("Checking metric values against dependent variable") + error_details: Dict[Tuple[str, ...], str] = {} + error_messages: List[str] = [] + + dep_var = self.mmmdata.mmmdata_spec.dep_var + + for channel_key, data in self.calibration_input.channel_data.items(): + logger.debug( + "Checking metric for channel %s: %s vs %s", + channel_key, + data.metric, + dep_var, + ) + + if data.metric != DependentVarType(dep_var): + msg = f"Metric mismatch: {data.metric} vs. {dep_var}" + logger.warning("Channel %s: %s", channel_key, msg) + error_details[channel_key] = msg + error_messages.append( + f"Metric for {'+'.join(channel_key)} does not match the dependent variable ({dep_var})." + ) + + result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + logger.debug("Metric validation result: %s", result) + return result + + def _check_confidence_values(self) -> ValidationResult: + """Check if confidence values are within acceptable range.""" + logger.debug("Checking confidence values for all channels") + error_details: Dict[Tuple[str, ...], str] = {} + error_messages: List[str] = [] + + for channel_key, data in self.calibration_input.channel_data.items(): + logger.debug( + "Checking confidence for channel %s: %f", channel_key, data.confidence + ) + + if data.confidence < 0.8: + msg = f"Low confidence: {data.confidence}" + logger.warning("Channel %s: %s", channel_key, msg) + error_details[channel_key] = msg + error_messages.append( + f"Confidence for {'+'.join(channel_key)} is lower than 80%, " + f"which is considered low confidence." + ) + + result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + logger.debug("Confidence validation result: %s", result) + return result + + def _check_lift_values(self) -> ValidationResult: + """Check if lift values are valid numbers.""" + logger.debug("Checking lift values for all channels") + error_details: Dict[Tuple[str, ...], str] = {} + error_messages: List[str] = [] + + for channel_key, data in self.calibration_input.channel_data.items(): + logger.debug( + "Checking lift value for channel %s: %s", channel_key, data.lift_abs + ) + + if not isinstance(data.lift_abs, (int, float)) or pd.isna(data.lift_abs): + msg = f"Invalid lift value: {data.lift_abs}" + logger.warning("Channel %s: %s", channel_key, msg) + error_details[channel_key] = msg + error_messages.append( + f"Lift value for {'+'.join(channel_key)} must be a valid number." + ) + + result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + logger.debug("Lift validation result: %s", result) + return result + + def validate(self) -> List[ValidationResult]: + """ + Implement the abstract validate method from the Validation base class. + Returns a list containing the calibration validation result. + """ + logger.info("Starting validation of calibration input") + results = [self.check_calibration()] + logger.info("Validation completed with status: %s", results[0].status) + return results + + def check_calibration(self) -> ValidationResult: + """Check all calibration inputs for consistency and correctness.""" + logger.info("Starting comprehensive calibration check") + + if self.calibration_input is None: + logger.debug("No calibration input provided, skipping validation") + return ValidationResult(status=True, error_details={}, error_message="") + + error_details = {} + error_messages = [] + + checks = [ + ("date_range", self._check_date_range()), + ("spend_values", self._check_spend_values()), + ("metric_values", self._check_metric_values()), + ("confidence_values", self._check_confidence_values()), + ("lift_values", self._check_lift_values()), + ] + + for check_name, result in checks: + logger.debug("Running %s check", check_name) + if not result.status: + logger.warning("%s check failed: %s", check_name, result.error_message) + error_details.update(result.error_details) + error_messages.append(result.error_message) + + final_result = ValidationResult( + status=len(error_details) == 0, + error_details=error_details, + error_message="\n".join(error_messages), + ) + + logger.info("Calibration check completed with status: %s", final_result.status) + return final_result + + @staticmethod + def create_modified_calibration_input( + original_input: CalibrationInput, + channel_name: Union[Tuple[str, ...], str], + **kwargs, + ) -> CalibrationInput: + """Create a modified version of a calibration input with updated values.""" + logger.debug( + "Creating modified calibration input for channel: %s", channel_name + ) + + # Convert string to single-element tuple if needed + if isinstance(channel_name, str): + channel_tuple = (channel_name,) + else: + channel_tuple = channel_name + + logger.debug("Processing modifications: %s", kwargs) + + # For test cases with non-existent channels + if any("nonexistent_channel" in ch for ch in channel_tuple): + logger.info("Creating test case for non-existent channel") + return CalibrationInput( + channel_data={ + channel_tuple: ChannelCalibrationData( + lift_start_date=pd.Timestamp( + kwargs.get("lift_start_date", "2022-01-01") + ), + lift_end_date=pd.Timestamp( + kwargs.get("lift_end_date", "2022-01-05") + ), + lift_abs=kwargs.get("lift_abs", 1000), + spend=kwargs.get("spend", 300), + confidence=kwargs.get("confidence", 0.9), + metric=kwargs.get("metric", DependentVarType.REVENUE), + calibration_scope=kwargs.get( + "calibration_scope", CalibrationScope.IMMEDIATE + ), + ) + } + ) + + # For updating existing channels + if channel_tuple in original_input.channel_data: + logger.debug("Updating existing channel data") + original_channel_data = original_input.channel_data[channel_tuple] + + new_channel_data = ChannelCalibrationData( + lift_start_date=pd.Timestamp( + kwargs.get("lift_start_date", original_channel_data.lift_start_date) + ), + lift_end_date=pd.Timestamp( + kwargs.get("lift_end_date", original_channel_data.lift_end_date) + ), + lift_abs=kwargs.get("lift_abs", original_channel_data.lift_abs), + spend=kwargs.get("spend", original_channel_data.spend), + confidence=kwargs.get("confidence", original_channel_data.confidence), + metric=kwargs.get("metric", original_channel_data.metric), + calibration_scope=kwargs.get( + "calibration_scope", original_channel_data.calibration_scope + ), + ) + + new_channel_data_dict = original_input.channel_data.copy() + new_channel_data_dict[channel_tuple] = new_channel_data + logger.debug("Created updated channel data: %s", new_channel_data) + return CalibrationInput(channel_data=new_channel_data_dict) + + # Default for new channels + logger.info("Creating new channel calibration data") + return CalibrationInput( + channel_data={ + channel_tuple: ChannelCalibrationData( + lift_start_date=pd.Timestamp( + kwargs.get("lift_start_date", "2022-01-01") + ), + lift_end_date=pd.Timestamp( + kwargs.get("lift_end_date", "2022-01-05") + ), + lift_abs=kwargs.get("lift_abs", 1000), + spend=kwargs.get("spend", 300), + confidence=kwargs.get("confidence", 0.9), + metric=kwargs.get("metric", DependentVarType.REVENUE), + calibration_scope=kwargs.get( + "calibration_scope", CalibrationScope.IMMEDIATE + ), + ) + } + ) diff --git a/python/src/robyn/data/validation/holidays_data_validation.py b/python/src/robyn/data/validation/holidays_data_validation.py new file mode 100644 index 000000000..2a2337785 --- /dev/null +++ b/python/src/robyn/data/validation/holidays_data_validation.py @@ -0,0 +1,210 @@ +# pyre-strict + +import logging +from typing import List +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.enums import ProphetVariableType +from robyn.data.validation.validation import Validation, ValidationResult +import numpy as np + + +class HolidaysDataValidation(Validation): + def __init__(self, holidays_data: HolidaysData) -> None: + self.holidays_data: HolidaysData = holidays_data + self.logger = logging.getLogger(__name__) + self.logger.debug( + "Initializing HolidaysDataValidation with holidays_data: %s", + holidays_data.__class__.__name__, + ) + + def check_holidays(self) -> ValidationResult: + """ + Check if the holidays data is valid. + Check for missing (NA) values in the dt_holidays DataFrame. + Check for missing required columns. + Check for invalid characters (spaces) in the column names. + + Returns: + - ValidationResult: A ValidationResult object containing the status (True if the holidays data is valid, False otherwise), + error details, and error message. + """ + self.logger.debug("Starting holidays data validation check") + dt_holidays = self.holidays_data.dt_holidays + + if dt_holidays is None: + self.logger.info("No holidays data provided, skipping validation") + return ValidationResult(status=True, error_details={}, error_message="") + + self.logger.debug( + "Validating holidays DataFrame with shape: %s", dt_holidays.shape + ) + error_details = {} + error_message = "" + + # Check for NA values + self.logger.debug("Checking for NA values in holidays data") + na_cols = dt_holidays.columns[dt_holidays.isnull().any()].tolist() + if na_cols: + na_details = [] + for col in na_cols: + missing_count = dt_holidays[col].isnull().sum() + missing_percentage = (missing_count / len(dt_holidays)) * 100 + na_details.append( + f"{col} ({missing_count} | {missing_percentage:.2f}%)" + ) + self.logger.warning( + "Column '%s' contains %d missing values (%.2f%%)", + col, + missing_count, + missing_percentage, + ) + + error_details["missing"] = na_cols + error_message += f"Dataset dt_holidays contains missing (NA) values. Missing values: {', '.join(na_details)}. " + + # Check for missing required columns + self.logger.debug("Checking for required columns presence") + vars_to_check = ["ds", "country"] + missing_cols = [var for var in vars_to_check if var not in dt_holidays.columns] + if missing_cols: + self.logger.error( + "Required columns missing in holidays data: %s", missing_cols + ) + error_details["missing_columns"] = missing_cols + error_message += f"Missing required columns in holidays data: {', '.join(missing_cols)}. " + + # Check for invalid characters (spaces) + self.logger.debug("Checking for invalid characters in column names") + invalid = [var for var in dt_holidays.columns if " " in var] + if invalid: + self.logger.error( + "Invalid column names found (contains spaces): %s", invalid + ) + error_details["invalid"] = invalid + error_message += f"Invalid column names (contains spaces) in holidays data: {', '.join(invalid)}. " + + validation_result = ValidationResult( + status=not error_details, + error_details=error_details, + error_message=error_message, + ) + self.logger.info( + "Holidays validation completed. Status: %s", validation_result.status + ) + return validation_result + + def check_prophet(self) -> ValidationResult: + """ + Check if the Prophet model is valid for the given data. + + Returns: + - ValidationResult: A ValidationResult object containing the status (True if the holidays data is valid, False otherwise), + error details, and error message. + """ + self.logger.debug("Starting Prophet model validation check") + dt_holidays = self.holidays_data.dt_holidays + prophet_vars = self.holidays_data.prophet_vars + prophet_signs = self.holidays_data.prophet_signs + prophet_country = self.holidays_data.prophet_country + + self.logger.debug( + "Prophet validation parameters - vars: %s, signs: %s, country: %s", + prophet_vars, + prophet_signs, + prophet_country, + ) + + error_details = {} + error_message = "" + + try: + if dt_holidays is None or prophet_vars is None: + self.logger.info( + "No holidays data or prophet variables provided, skipping validation" + ) + return ValidationResult(status=True, error_details={}, error_message="") + + if ProphetVariableType.HOLIDAY not in prophet_vars: + if prophet_country is not None: + warning_message = f"Warning: Input 'prophet_country' is defined as {prophet_country} but 'holiday' is not setup within 'prophet_vars' parameter." + self.logger.warning(warning_message) + prophet_country = None + + if ProphetVariableType.HOLIDAY in prophet_vars: + self.logger.debug( + "Validating prophet_country against available countries" + ) + if prophet_country is None: + self.logger.error( + "prophet_country is None but HOLIDAY type is specified in prophet_vars" + ) + elif prophet_country not in dt_holidays["country"].unique(): + available_countries = dt_holidays["country"].unique() + self.logger.error( + "Invalid prophet_country '%s'. Available countries: %s", + prophet_country, + available_countries, + ) + error_details["prophet_country"] = ( + f"Invalid prophet_country. Available countries: {', '.join(available_countries)}" + ) + error_message += f"Invalid prophet_country. " + return ValidationResult( + status=False, + error_details=error_details, + error_message=error_message, + ) + + if prophet_signs is None: + self.logger.debug("Initializing default prophet_signs") + prophet_signs = ["default"] * len(prophet_vars) + + if len(prophet_signs) == 1: + self.logger.debug( + "Expanding single prophet_sign to match prophet_vars length" + ) + prophet_signs = prophet_signs * len(prophet_vars) + + if len(prophet_signs) != len(prophet_vars): + self.logger.error( + "Length mismatch: prophet_signs (%d) != prophet_vars (%d)", + len(prophet_signs), + len(prophet_vars), + ) + error_details["prophet_signs_length"] = ( + "prophet_signs must have same length as prophet_vars" + ) + error_message += "Mismatch in prophet_signs and prophet_vars length. " + + validation_result = ValidationResult( + status=not bool(error_details), + error_details=error_details, + error_message=error_message.strip(), + ) + self.logger.info( + "Prophet validation completed. Status: %s", validation_result.status + ) + return validation_result + + except Exception as e: + self.logger.error( + "Prophet validation failed with error: %s", str(e), exc_info=True + ) + return ValidationResult( + status=False, error_details=error_details, error_message=str(e) + ) + + def validate(self) -> List[ValidationResult]: + """ + Perform all validations and return the result. + + Returns: + - ValidationResult: The result of the validation operation. + """ + self.logger.info("Starting complete validation process") + results = [self.check_holidays(), self.check_prophet()] + self.logger.info( + "Validation complete. Overall status: %s", + all(result.status for result in results), + ) + return results diff --git a/python/src/robyn/data/validation/hyperparameter_validation.py b/python/src/robyn/data/validation/hyperparameter_validation.py new file mode 100644 index 000000000..29a01ca95 --- /dev/null +++ b/python/src/robyn/data/validation/hyperparameter_validation.py @@ -0,0 +1,232 @@ +import logging +from typing import List +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.validation.validation import Validation, ValidationResult +from robyn.data.entities.enums import AdstockType + +logger = logging.getLogger(__name__) + + +class HyperparametersValidation(Validation): + + def __init__(self, hyperparameters: Hyperparameters) -> None: + self.hyperparameters: Hyperparameters = hyperparameters + logger.debug( + "Initialized HyperparametersValidation with hyperparameters: %s", + getattr(hyperparameters, "__dict__", str(hyperparameters)), + ) + + def check_hyperparameters(self) -> ValidationResult: + """ + Check if the hyperparameters are valid. + Returns: + ValidationResult: + An object containing the validation status, error details, and error message. + The status is True if no errors were found, False otherwise. + Error details is a dictionary containing specific error information for each invalid parameter. + Error message is a string summarizing all errors found during validation. + """ + logger.info("Starting hyperparameters validation") + error_details = {} + error_message = "" + + if self.hyperparameters.train_size is None: + logger.warning("train_size is not set, using default values [0.5, 0.8]") + self.hyperparameters.train_size = [0.5, 0.8] + + logger.debug("Validating train_size: %s", self.hyperparameters.train_size) + try: + self.check_train_size() + except ValueError as e: + logger.error("Train size validation failed: %s", str(e)) + error_details["train_size"] = str(e) + error_message += f"Error in train_size: {str(e)}. " + + try: + all_media = self.hyperparameters.hyperparameters.keys() + logger.debug("Processing media channels: %s", all_media) + hyper_names = self.hyper_names(all_media=all_media) + logger.debug("Generated hyperparameter names: %s", hyper_names) + + for hyper in ["thetas", "alphas", "gammas", "shapes", "scales"]: + logger.debug("Checking limits for hyperparameter: %s", hyper) + self.check_hyper_limits(hyper) + except Exception as e: + logger.error("Hyperparameter validation failed: %s", str(e)) + error_details["hyperparameters"] = str(e) + error_message += f"Error in hyperparameters: {str(e)}. " + + validation_result = ValidationResult( + status=not error_details, + error_details=error_details, + error_message=error_message, + ) + logger.info( + "Hyperparameter validation completed. Status: %s", validation_result.status + ) + if error_message: + logger.error("Validation errors: %s", error_message) + + return validation_result + + def check_train_size(self): + logger.debug("Checking train_size validation") + train_size = self.hyperparameters.train_size + + if not isinstance(train_size, List) or len(train_size) != 2: + logger.error("Invalid train_size format: %s", train_size) + raise ValueError("train_size must be a list with exactly 2 elements") + + lower, upper = train_size + if not all(isinstance(val, float) for val in train_size): + logger.error("Invalid train_size value types: %s", train_size) + raise TypeError("train_size values must be floats") + + if lower < 0.1 or lower >= upper or upper > 1: + logger.error( + "Train_size values out of bounds: lower=%s, upper=%s", lower, upper + ) + raise ValueError( + "train_size must be [lower, upper] where 0.1 <= lower < upper <= 1" + ) + + logger.debug("Train_size validation passed: %s", train_size) + + def hyper_names(self, all_media: List[str]) -> List[str]: + """ + Get the names of all hyperparameters based on the adstock type. + + :return: A list of hyperparameter names. + """ + logger.debug( + "Generating hyperparameter names for adstock type: %s", + self.hyperparameters.adstock, + ) + adstock = self.hyperparameters.adstock + + if adstock == AdstockType.GEOMETRIC: + names = [f"{media}_thetas" for media in all_media] + elif adstock in [AdstockType.WEIBULL_CDF, AdstockType.WEIBULL_PDF]: + names = [ + f"{media}_{param}" + for media in all_media + for param in ["shapes", "scales"] + ] + else: + logger.error("Invalid adstock type encountered: %s", adstock) + raise ValueError(f"Invalid adstock type: {adstock}") + + names.extend([f"{media}_alphas" for media in all_media]) + names.extend([f"{media}_gammas" for media in all_media]) + names.extend(["lambda", "train_size"]) + + logger.debug("Generated hyperparameter names: %s", names) + return names + + def check_hyper_limits(self, hyper: str) -> None: + """ + Check if the hyperparameter values are within the allowed limits. + + :param hyper: The name of the hyperparameter to check. + """ + logger.debug("Checking limits for hyperparameter: %s", hyper) + limits = Hyperparameters.get_hyperparameter_limits()[hyper] + logger.debug("Obtained limits for %s: %s", hyper, limits) + + def parse_limit(limit_str): + logger.debug("Parsing limit string: %s", limit_str) + if limit_str.startswith(">="): + return float(limit_str[2:]), True # inclusive + elif limit_str.startswith(">"): + return float(limit_str[1:]), False # exclusive + elif limit_str.startswith("<="): + return float(limit_str[2:]), True # inclusive + elif limit_str.startswith("<"): + return float(limit_str[1:]), False # exclusive + else: + return float(limit_str), True # assume inclusive if no symbol + + lower_limit, lower_inclusive = parse_limit(limits[0]) + upper_limit, upper_inclusive = parse_limit(limits[1]) + logger.debug( + "Parsed limits - lower: %s (%s), upper: %s (%s)", + lower_limit, + lower_inclusive, + upper_limit, + upper_inclusive, + ) + + for ( + channel, + channel_hyperparams, + ) in self.hyperparameters.hyperparameters.items(): + logger.debug("Checking channel %s hyperparameters", channel) + values = getattr(channel_hyperparams, hyper) + + if values is None: + logger.debug("No values defined for %s in channel %s", hyper, channel) + return + + if len(values) not in [1, 2]: + logger.error( + "Invalid number of values for %s in channel %s: %s", + hyper, + channel, + len(values), + ) + raise ValueError(f"Hyperparameter '{hyper}' must have 1 or 2 values") + + if (lower_inclusive and float(values[0]) < lower_limit) or ( + not lower_inclusive and float(values[0]) <= lower_limit + ): + logger.error( + "Lower bound violation for %s in channel %s: %s", + hyper, + channel, + values[0], + ) + raise ValueError( + f"{hyper}'s hyperparameter must be {'≥' if lower_inclusive else '>'} {lower_limit}" + ) + + if len(values) == 2: + if (upper_inclusive and float(values[1]) > upper_limit) or ( + not upper_inclusive and float(values[1]) >= upper_limit + ): + logger.error( + "Upper bound violation for %s in channel %s: %s", + hyper, + channel, + values[1], + ) + raise ValueError( + f"{hyper}'s hyperparameter must be {'≤' if upper_inclusive else '<'} {upper_limit}" + ) + if float(values[0]) > float(values[1]): + logger.error( + "Invalid bounds order for %s in channel %s: %s", + hyper, + channel, + values, + ) + raise ValueError( + f"{hyper}'s hyperparameter must have lower bound first and upper bound second" + ) + + logger.debug( + "Validation passed for %s in channel %s: %s", hyper, channel, values + ) + + def validate(self) -> List[ValidationResult]: + """ + Perform all validations and return the result. + + :return: The result of the validation operation. + """ + logger.info("Starting validation process") + results = [self.check_hyperparameters()] + logger.info( + "Validation completed with status: %s", + all(result.status for result in results), + ) + return results diff --git a/python/src/robyn/data/validation/mmmdata_validation.py b/python/src/robyn/data/validation/mmmdata_validation.py new file mode 100644 index 000000000..f97256f32 --- /dev/null +++ b/python/src/robyn/data/validation/mmmdata_validation.py @@ -0,0 +1,263 @@ +# pyre-strict +from typing import List +import logging +from robyn.data.entities.mmmdata import MMMData +from robyn.data.validation.validation import Validation, ValidationResult +import pandas as pd +import numpy as np + +logger = logging.getLogger(__name__) + + +class MMMDataValidation(Validation): + def __init__(self, mmm_data: MMMData) -> None: + self.mmm_data: MMMData = mmm_data + logger.debug( + "Initializing MMMDataValidation with data shape: %s", + self.mmm_data.data.shape, + ) + + def check_missing_and_infinite(self) -> ValidationResult: + """ + Check for missing (NA) values and infinite (Inf) values in the DataFrame. + + :return: validation result with error_details containing a dictionary with keys 'missing' and 'infinite', each containing a list of column names with missing or infinite values. + """ + logger.debug("Starting missing and infinite value check") + data = self.mmm_data.data + + missing_cols = data.columns[data.isnull().any()].tolist() + infinite_cols = [ + col + for col in data.columns + if data[col].dtype.kind in "bifc" and np.isinf(data[col]).any() + ] + + error_details = {} + error_message = "" + + if missing_cols: + error_details["missing"] = missing_cols + error_message += f"Dataset contains missing (NA) values in columns: {', '.join(missing_cols)}. " + logger.warning("Found missing values in columns: %s", missing_cols) + + if infinite_cols: + error_details["infinite"] = infinite_cols + error_message += f"Dataset contains infinite (Inf) values in columns: {', '.join(infinite_cols)}. " + logger.warning("Found infinite values in columns: %s", infinite_cols) + + if error_message: + error_message += ( + "These values must be removed or fixed for Robyn to properly work." + ) + logger.error("Validation failed: %s", error_message) + else: + logger.info("Missing and infinite value check passed successfully") + + return ValidationResult( + status=not bool(error_details), + error_details=error_details, + error_message=error_message, + ) + + def check_no_variance(self) -> ValidationResult: + """ + Check for columns with no variance in the input dataframe. + + :return: A list of column names with no variance. + """ + logger.debug("Starting no-variance check") + data = self.mmm_data.data + + no_variance_cols = data.columns[data.nunique() == 1].tolist() + + error_details = {} + error_message = "" + + if no_variance_cols: + error_details["no_variance"] = no_variance_cols + error_message = f"There are {len(no_variance_cols)} column(s) with no-variance: {', '.join(no_variance_cols)}. Please remove the variable(s) to proceed." + logger.warning("Found columns with no variance: %s", no_variance_cols) + else: + logger.info("No-variance check passed successfully") + + return ValidationResult( + status=not bool(error_details), + error_details=error_details, + error_message=error_message, + ) + + def check_variable_names(self) -> ValidationResult: + """ + Check variable names for duplicates and invalid characters. + + :return: A dictionary with keys 'duplicates' and 'invalid', each containing a list of problematic column names. + """ + logger.debug("Starting variable names validation") + mmmdata_spec = self.mmm_data.mmmdata_spec + + # Collect all variable names to check + vars_to_check = [ + mmmdata_spec.dep_var, + mmmdata_spec.date_var, + mmmdata_spec.context_vars, + mmmdata_spec.paid_media_spends, + mmmdata_spec.organic_vars, + ] + vars_to_check = [var for var in vars_to_check if var is not None] + vars_to_check = [ + item + for sublist in vars_to_check + for item in (sublist if isinstance(sublist, list) else [sublist]) + ] + + logger.debug("Checking variable names: %s", vars_to_check) + + # Check for duplicates + duplicates = [var for var in set(vars_to_check) if vars_to_check.count(var) > 1] + + # Check for invalid characters (spaces) + invalid = [var for var in vars_to_check if " " in var] + + error_details = {} + error_message = "" + + if duplicates: + error_details["duplicates"] = duplicates + error_message += "Duplicate variable names present. " + logger.warning("Found duplicate variable names: %s", duplicates) + + if invalid: + error_details["invalid"] = invalid + error_message += "Invalid variable names present. " + logger.warning( + "Found invalid variable names (containing spaces): %s", invalid + ) + + if not error_details: + logger.info("Variable names validation passed successfully") + + return ValidationResult( + status=not error_details, + error_details=error_details, + error_message=error_message, + ) + + def check_date_variable(self) -> ValidationResult: + """ + Checks if the date variable is correct. + + :return: True if the date variable is valid, False otherwise. + """ + logger.debug("Starting date variable validation") + mmmdata_spec = self.mmm_data.mmmdata_spec + data = self.mmm_data.data + date_var = mmmdata_spec.date_var + + error_details = {} + error_message = "" + + if date_var == "auto": + error_message = ( + "Date variable is not set. Please set the date variable to proceed." + ) + logger.error("Date variable validation failed: date variable not set") + return ValidationResult( + status=False, + error_details={"date_variable": error_message}, + error_message=error_message, + ) + + logger.debug("Checking date variable: %s", date_var) + + if date_var not in data.columns: + error_message = f"Date variable '{date_var}' not found in the input data." + logger.error("Date variable validation failed: %s", error_message) + else: + try: + data[date_var] = pd.to_datetime(data[date_var]) + if not data[date_var].is_monotonic_increasing: + error_message = ( + f"Date variable '{date_var}' is not in ascending order." + ) + logger.warning( + "Date variable validation failed: dates not in ascending order" + ) + except ValueError: + error_message = ( + f"Date variable '{date_var}' contains invalid date values." + ) + logger.error("Date variable validation failed: invalid date values") + + if error_message: + error_details["date_variable"] = error_message + else: + logger.info("Date variable validation passed successfully") + + return ValidationResult( + status=not bool(error_details), + error_details=error_details, + error_message=error_message, + ) + + def check_dependent_variables(self) -> ValidationResult: + """ + Checks if dependent variables are valid. + + :return: True if the dependent variables are valid, False otherwise. + """ + logger.debug("Starting dependent variables validation") + mmmdata_spec = self.mmm_data.mmmdata_spec + data = self.mmm_data.data + dep_var = mmmdata_spec.dep_var + + error_details = {} + error_message = "" + + logger.debug("Checking dependent variable: %s", dep_var) + + if dep_var not in data.columns: + error_message = ( + f"Dependent variable '{dep_var}' not found in the input data." + ) + logger.error("Dependent variable validation failed: variable not found") + else: + if not pd.api.types.is_numeric_dtype(data[dep_var]): + error_message = f"Dependent variable '{dep_var}' must be numeric." + logger.error("Dependent variable validation failed: non-numeric type") + + if error_message: + error_details["dependent_variable"] = error_message + else: + logger.info("Dependent variable validation passed successfully") + + return ValidationResult( + status=not bool(error_details), + error_details=error_details, + error_message=error_message, + ) + + def validate(self) -> List[ValidationResult]: + """ + Perform all validations and return the results. + + :return: A dictionary containing the results of all validations. + """ + logger.info("Starting complete MMMData validation") + results = [ + self.check_missing_and_infinite(), + self.check_no_variance(), + self.check_variable_names(), + self.check_date_variable(), + self.check_dependent_variables(), + ] + + failed_validations = [r for r in results if not r.status] + if failed_validations: + logger.error( + "Validation completed with %d failures", len(failed_validations) + ) + else: + logger.info("All validations passed successfully") + + return results diff --git a/python/src/robyn/data/validation/validation.py b/python/src/robyn/data/validation/validation.py new file mode 100644 index 000000000..62988b27c --- /dev/null +++ b/python/src/robyn/data/validation/validation.py @@ -0,0 +1,20 @@ +from abc import ABC, abstractmethod +from dataclasses import dataclass +from typing import List, Optional + + +@dataclass +class ValidationResult: + """Result of a validation operation""" + + status: bool # True if validation was successful, False otherwise + error_message: Optional[str] # Error message if validation failed + error_details: Optional[dict] # Additional error details if validation failed + + +class Validation(ABC): + """Abstract base class for validation operations""" + + @abstractmethod + def validate(self) -> List[ValidationResult]: + """Perform validation and return the result""" diff --git a/python/src/robyn/modeling/__init__.py b/python/src/robyn/modeling/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/python/src/robyn/modeling/base_model_executor.py b/python/src/robyn/modeling/base_model_executor.py new file mode 100644 index 000000000..8ed3982b0 --- /dev/null +++ b/python/src/robyn/modeling/base_model_executor.py @@ -0,0 +1,342 @@ +# base_model_executor.py +# pyre-strict + +from abc import ABC, abstractmethod +from typing import Any, Dict, Optional, List +import numpy as np +import logging +from robyn.data.entities.calibration_input import CalibrationInput +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.enums import Models, NevergradAlgorithm +from robyn.data.entities.enums import AdstockType +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.modeling.entities.modelrun_trials_config import TrialsConfig +from robyn.modeling.feature_engineering import FeaturizedMMMData +from robyn.modeling.transformations.transformations import Transformation +import nevergrad as ng + +logger = logging.getLogger(__name__) + + +class BaseModelExecutor(ABC): + """ + Abstract base class for executing marketing mix models. + + This class defines the interface for model executors and provides common + initialization logic for different types of models. + """ + + def __init__( + self, + mmmdata: MMMData, + holidays_data: HolidaysData, + hyperparameters: Hyperparameters, + calibration_input: CalibrationInput, + featurized_mmm_data: FeaturizedMMMData, + ) -> None: + """ + Initialize the BaseModelExecutor. + + Args: + mmmdata (MMMData): Marketing Mix Model data. + holidays_data (HolidaysData): Holiday data for the model. + hyperparameters (Hyperparameters): Model hyperparameters. + calibration_input (CalibrationInput): Calibration input data. + featurized_mmm_data (FeaturizedMMMData): Featurized MMM data. + """ + logger.info("Initializing BaseModelExecutor") + logger.debug( + "Input data shapes - MMMData: %s, Holidays: %s", + mmmdata.data.shape if hasattr(mmmdata, "data") else "None", + ( + len(holidays_data.holidays) + if hasattr(holidays_data, "holidays") + else "None" + ), + ) + + self.mmmdata = mmmdata + self.holidays_data = holidays_data + self.hyperparameters = hyperparameters + self.calibration_input = calibration_input + self.featurized_mmm_data = featurized_mmm_data + self.transformation = Transformation(mmmdata) + + logger.debug( + "Initialized with %d paid media variables, %d context variables, %d organic variables", + len(mmmdata.mmmdata_spec.paid_media_vars), + len(mmmdata.mmmdata_spec.context_vars), + len(mmmdata.mmmdata_spec.organic_vars), + ) + + @abstractmethod + def model_run( + self, + dt_hyper_fixed: Optional[Dict[str, Any]] = None, + ts_validation: bool = False, + add_penalty_factor: bool = False, + refresh: bool = False, + seed: List[int] = [123], + cores: Optional[int] = None, + trials_config: Optional[TrialsConfig] = None, + rssd_zero_penalty: bool = True, + objective_weights: Optional[Dict[str, float]] = None, + nevergrad_algo: NevergradAlgorithm = NevergradAlgorithm.TWO_POINTS_DE, + intercept: bool = True, + intercept_sign: str = "non_negative", + outputs: bool = False, + model_name: Models = Models.RIDGE, + lambda_control: Optional[float] = None, + ) -> ModelOutputs: + pass + + def _validate_input(self) -> None: + """ + Validate the input data and parameters. + + Raises: + ValueError: If any required data or parameter is missing or invalid. + """ + logger.debug("Validating input parameters") + + validation_errors = [] + if self.mmmdata is None: + validation_errors.append("MMMData is required") + if self.holidays_data is None: + validation_errors.append("HolidaysData is required") + if self.hyperparameters is None: + validation_errors.append("Hyperparameters are required") + if self.featurized_mmm_data is None: + validation_errors.append("FeaturizedMMMData is required") + + if validation_errors: + error_msg = "; ".join(validation_errors) + logger.error("Input validation failed: %s", error_msg) + raise ValueError(error_msg) + + logger.info("Input validation successful") + + def _prepare_hyperparameters( + self, + dt_hyper_fixed: Optional[Dict[str, Any]], + add_penalty_factor: bool, + ts_validation: bool, + ) -> Dict[str, Any]: + logger.info("Preparing hyperparameters") + logger.debug( + "Initial hyperparameters config: fixed=%s, add_penalty=%s, ts_validation=%s", + bool(dt_hyper_fixed), + add_penalty_factor, + ts_validation, + ) + + prepared_hyperparameters = self.hyperparameters.copy() + + if dt_hyper_fixed: + logger.debug( + "Updating with fixed hyperparameters: %s", dt_hyper_fixed.keys() + ) + for key, value in dt_hyper_fixed.items(): + if prepared_hyperparameters.has_channel(key): + channel_params = prepared_hyperparameters.get_hyperparameter(key) + for param in [ + "thetas", + "shapes", + "scales", + "alphas", + "gammas", + "penalty", + ]: + if param in value: + logger.debug("Setting %s.%s = %s", key, param, value[param]) + setattr(channel_params, param, value[param]) + + if add_penalty_factor: + logger.debug("Adding penalty factors to all channels") + for channel in prepared_hyperparameters.hyperparameters: + channel_params = prepared_hyperparameters.get_hyperparameter(channel) + channel_params.penalty = [0, 1] + + if ts_validation and not prepared_hyperparameters.train_size: + logger.debug("Setting default train_size for time series validation") + prepared_hyperparameters.train_size = [0.5, 0.8] + + hyper_to_optimize = {} + for channel, channel_params in prepared_hyperparameters.hyperparameters.items(): + for param in ["thetas", "shapes", "scales", "alphas", "gammas"]: + values = getattr(channel_params, param) + if isinstance(values, list) and len(values) == 2: + hyper_to_optimize[f"{channel}_{param}"] = values + logger.debug( + "Added %s_%s to optimization parameters", channel, param + ) + + if ( + isinstance(prepared_hyperparameters.lambda_, list) + and len(prepared_hyperparameters.lambda_) == 2 + ): + hyper_to_optimize["lambda"] = prepared_hyperparameters.lambda_ + logger.debug("Added lambda to optimization parameters") + + if ( + isinstance(prepared_hyperparameters.train_size, list) + and len(prepared_hyperparameters.train_size) == 2 + ): + hyper_to_optimize["train_size"] = prepared_hyperparameters.train_size + logger.debug("Added train_size to optimization parameters") + + logger.info( + "Completed hyperparameter preparation with %d parameters to optimize", + len(hyper_to_optimize), + ) + + return { + "prepared_hyperparameters": prepared_hyperparameters, + "hyper_to_optimize": hyper_to_optimize, + } + + def _setup_nevergrad_optimizer( + self, + hyperparameters: Dict[str, Any], + iterations: int, + cores: int, + nevergrad_algo: NevergradAlgorithm, + ) -> ng.optimizers.base.Optimizer: + logger.info( + "Setting up Nevergrad optimizer with algorithm: %s", nevergrad_algo.value + ) + hyper_to_optimize = hyperparameters["hyper_to_optimize"] + + if not hyper_to_optimize: + logger.error("No hyperparameters found for optimization") + raise ValueError( + "No hyperparameters to optimize. Please check your hyperparameter configuration." + ) + + logger.debug( + "Creating instrumentation with %d parameters", len(hyper_to_optimize) + ) + instrum_dict = { + name: ng.p.Scalar(lower=bounds[0], upper=bounds[1]) + for name, bounds in hyper_to_optimize.items() + } + + instrum = ng.p.Instrumentation(**instrum_dict) + optimizer = ng.optimizers.registry[nevergrad_algo.value]( + instrum, budget=iterations, num_workers=cores + ) + + logger.info( + "Optimizer setup complete with %d iterations and %d cores", + iterations, + cores, + ) + return optimizer + + def _calculate_objective( + self, + train_score: float, + test_score: Optional[float], + rssd: float, + objective_weights: Optional[Dict[str, float]], + ) -> float: + logger.debug( + "Calculating objective with scores - Train: %.4f, Test: %.4f, RSSD: %.4f", + train_score, + test_score or 0, + rssd, + ) + + if objective_weights is None: + logger.debug("Using default objective weights") + objective_weights = {"train_score": 1.0, "test_score": 1.0, "rssd": 1.0} + + objective = ( + objective_weights["train_score"] * (1 - train_score) + + objective_weights.get("test_score", 0) * (1 - (test_score or 0)) + + objective_weights["rssd"] * rssd + ) + + logger.debug("Calculated objective value: %.4f", objective) + return objective + + def _apply_transformations( + self, channel: str, hyperparameters: Dict[str, Any] + ) -> np.ndarray: + logger.debug("Applying transformations for channel: %s", channel) + + adstock_type = self.mmmdata.adstock + logger.debug("Using adstock type: %s", adstock_type) + + try: + if adstock_type == AdstockType.GEOMETRIC: + logger.debug( + "Applying geometric adstock with theta: %.4f", + hyperparameters[f"{channel}_theta"], + ) + adstock_result = self.transformation.adstock_geometric( + channel, hyperparameters[f"{channel}_theta"] + ) + elif adstock_type in [AdstockType.WEIBULL_CDF, AdstockType.WEIBULL_PDF]: + logger.debug( + "Applying Weibull adstock with shape: %.4f, scale: %.4f", + hyperparameters[f"{channel}_shape"], + hyperparameters[f"{channel}_scale"], + ) + adstock_result = self.transformation.adstock_weibull( + channel, + hyperparameters[f"{channel}_shape"], + hyperparameters[f"{channel}_scale"], + adstock_type=adstock_type.value, + ) + else: + logger.error("Invalid adstock type: %s", adstock_type) + raise ValueError(f"Unsupported adstock type: {adstock_type}") + + adstocked_data = adstock_result["adstocked"] + + logger.debug( + "Applying saturation transformation with alpha: %.4f, gamma: %.4f", + hyperparameters[f"{channel}_alpha"], + hyperparameters[f"{channel}_gamma"], + ) + + saturated_data = self.transformation.saturation_hill( + channel, + hyperparameters[f"{channel}_alpha"], + hyperparameters[f"{channel}_gamma"], + marginal_input=adstocked_data, + ) + + logger.debug("Transformations completed for channel %s", channel) + return saturated_data + + except Exception as e: + logger.error( + "Error applying transformations for channel %s: %s", channel, str(e) + ) + raise + + def _prepare_model_data(self, hyperparameters: Dict[str, Any]) -> np.ndarray: + logger.info("Preparing model data") + transformed_data = {} + + for channel in self.mmmdata.paid_media_vars: + logger.debug("Processing channel: %s", channel) + transformed_data[channel] = self._apply_transformations( + channel, hyperparameters + ) + + logger.debug("Combining transformed data with context and organic variables") + model_data = np.column_stack( + [transformed_data[channel] for channel in self.mmmdata.paid_media_vars] + + [ + self.mmmdata.data[var] + for var in self.mmmdata.context_vars + self.mmmdata.organic_vars + ] + ) + + logger.info("Model data preparation complete. Shape: %s", model_data.shape) + return model_data diff --git a/python/src/robyn/modeling/clustering/cluster_builder.py b/python/src/robyn/modeling/clustering/cluster_builder.py new file mode 100644 index 000000000..2feba1e76 --- /dev/null +++ b/python/src/robyn/modeling/clustering/cluster_builder.py @@ -0,0 +1,804 @@ +# pyre-strict + +import logging +from sys import maxsize +from typing import Dict, List, Optional, Union + +import re +import numpy as np +import pandas as pd +from robyn.common.logger import RobynLogger +from robyn.modeling.clustering.clustering_config import ClusterBy, ClusteringConfig +from robyn.data.entities.enums import DependentVarType +from robyn.modeling.entities.clustering_results import ( + ClusterConfidenceIntervals, + ClusteredResult, + ClusterPlotResults, +) +from robyn.common.constants import HYPERPARAMETER_NAMES + +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.modeling.entities.ci_collection_data import ConfidenceIntervalCollectionData +from robyn.modeling.pareto.pareto_utils import ParetoUtils +from robyn.visualization.cluster_visualizer import ClusterVisualizer +from scipy import stats +from sklearn.cluster import KMeans + + +class ClusterBuilder: + """ + An interface for clustering models based on performance metrics and hyperparameters. + + This interface defines methods for clustering models, calculating confidence intervals, + and generating error scores, among other functionalities. + """ + + def __init__(self, pareto_result: ParetoResult): + """ + Initializes the ClusterBuilder with global instances of ModelOutputs and ParetoResult. + + Args: + pareto_result (ParetoResult): The results of the Pareto optimization process. + """ + self.logger = logging.getLogger(__name__) + self.logger.info("Initializing ClusterBuilder") + self.logger.debug( + "Received ParetoResult with %d solutions", + len(pareto_result.pareto_solutions), + ) + + self.pareto_result: ParetoResult = pareto_result + self.cluster_visualizer = ClusterVisualizer(None, None, None) + self.logger.info("ClusterBuilder initialization complete") + + def cluster_models(self, config: ClusteringConfig) -> ClusteredResult: + """ + Clusters models based on specified criteria. + """ + self.logger.info("Starting model clustering process") + self.logger.debug("Clustering configuration: %s", config) + + allSolutions = self.pareto_result.pareto_solutions + self.logger.debug("Processing %d Pareto solutions", len(allSolutions)) + + x_decomp_agg = self.pareto_result.x_decomp_agg[ + self.pareto_result.x_decomp_agg["sol_id"].isin(allSolutions) + ] + result_hyp_param = self.pareto_result.result_hyp_param[ + self.pareto_result.result_hyp_param["sol_id"].isin(allSolutions) + ] + + if config.all_media is None: + aux = self.pareto_result.media_vec_collect.columns + type_index = aux.get_loc("type") + config.all_media = aux[1:type_index].tolist() + self.logger.info("Auto-detected media channels: %s", config.all_media) + + self.logger.info("Clustering by: %s", config.cluster_by) + if config.cluster_by == ClusterBy.HYPERPARAMETERS: + self.logger.debug("Preparing hyperparameter data for clustering") + df = self._prepare_hyperparameter_data_for_clustering(result_hyp_param) + elif config.cluster_by == ClusterBy.PERFORMANCE: + self.logger.debug("Preparing performance data for clustering") + df = self._prepare_performance_data_for_clustering(x_decomp_agg, config) + else: + self.logger.error(f"Invalid clustering method: {config.cluster_by}") + raise ValueError("Invalid clustering method") + + RobynLogger.log_df(self.logger, df) + ignored_columns = [ + "sol_id", + "mape", + "decomp.rssd", + "nrmse", + "nrmse_test", + "nrmse_train", + "nrmse_val", + "pareto", + ] + limit_clusters = min(len(df) - 1, 30) + + self.logger.debug( + f"Determining optimal number of clusters (limit: {limit_clusters})" + ) + config.k_clusters = self._select_optimal_clusters( + df, config, limit_clusters, ignored_columns + ) + self.logger.info(f"Selected {config.k_clusters} clusters") + + if ( + config.k_clusters < config.min_clusters + or config.k_clusters > limit_clusters + ): + self.logger.error( + f"Invalid number of clusters: {config.k_clusters} " + f"(min: {config.min_clusters}, max: {limit_clusters})" + ) + raise ValueError( + f"Number of clusters {config.k_clusters} is outside the specified range " + f"{config.min_clusters} to {config.max_clusters}." + ) + + self.logger.debug("Performing KMeans clustering") + result = self.clusterKmeans( + df=df, + config=config, + k=config.k_clusters, + limit=limit_clusters, + ignored_columns=ignored_columns, + ) + + self.logger.debug("Processing cluster results") + grouped = result.cluster_data.groupby("cluster", observed=False) + result.cluster_data["n"] = grouped["cluster"].transform("size") + + all_paid = [ + col + for col in result.cluster_data.columns + if col not in ignored_columns + ["cluster"] + ] + + self.logger.debug("Selecting top solutions") + top_solutions = self._select_top_solutions(result.cluster_data, config) + self.logger.info(f"Selected {len(top_solutions)} top solutions") + RobynLogger.log_df(self.logger, top_solutions, print_head=True) + + self.logger.debug("Calculating confidence intervals") + ci_results: ConfidenceIntervalCollectionData = ( + self._calculate_confidence_intervals( + x_decomp_agg, result.cluster_data, config, all_paid + ) + ) + + self.logger.debug("Preparing plot results") + plots = ClusterPlotResults( + top_solutions_errors_plot=self.cluster_visualizer.plot_top_solutions_errors( + df, top_solutions, balance=config.weights + ), + top_solutions_rois_plot=self.cluster_visualizer.plot_topsols_rois( + df, top_solutions, config.all_media + ), + ) + + self.logger.debug("Creating confidence intervals object") + cluster_ci = ClusterConfidenceIntervals( + cluster_confidence_interval_df=ci_results.confidence_interval_df.reset_index( + drop=True + ).drop( + columns=["cluster_title"] + ), + boot_n=ci_results.boot_n, + sim_n=ci_results.sim_n, + clusters_confidence_interval_plot=self.cluster_visualizer.plot_confidence_intervals( + ci_results, config + ), + ) + clustered_data = result.cluster_data.assign( + top_sol=result.cluster_data["sol_id"].isin(top_solutions["sol_id"]), + cluster=result.cluster_data["cluster"].astype(int), + ) + + RobynLogger.log_df(self.logger, clustered_data) + self.logger.info("Clustering process completed successfully") + return ClusteredResult( + cluster_data=clustered_data, + top_solutions=top_solutions, + wss=result.wss, + cluster_ci=cluster_ci, + n_clusters=result.n_clusters, + errors_weights=config.weights, + clusters_means=result.clusters_means, + clusters_pca=None, + clusters_tsne=None, + correlations=None, + plots=plots, + ) + + def _calculate_confidence_intervals( + self, + x_decomp_agg: pd.DataFrame, + clustered_data: pd.DataFrame, + config: ClusteringConfig, + all_paid: List[str], + boot_n: int = 1000, + sim_n: int = 10000, + ) -> ConfidenceIntervalCollectionData: + """Calculate confidence intervals for clustered data""" + self.logger.info("Starting confidence interval calculations") + self.logger.debug(f"Parameters: boot_n={boot_n}, sim_n={sim_n}") + + self.logger.debug("Preparing cluster outcomes data") + df_clusters_outcome = x_decomp_agg.dropna(subset=["total_spend"]).merge( + clustered_data[["sol_id", "cluster"]], on="sol_id", how="left" + )[["sol_id", "cluster", "rn", "roi_total", "cpa_total", "robynPareto"]] + + self.logger.debug("Grouping cluster outcomes") + df_clusters_outcome = ( + df_clusters_outcome.groupby(["cluster", "rn"], observed=False) + .apply(lambda x: x.assign(n=len(x))) + .reset_index(drop=True) + .dropna(subset=["cluster"]) + .sort_values(by=["cluster", "rn"]) + ) + + cluster_collect = [] + + self.logger.debug(f"Processing {config.k_clusters} clusters") + for j in range(0, config.k_clusters): + df_outcome = df_clusters_outcome[df_clusters_outcome["cluster"] == j] + if len(df_outcome["sol_id"].unique()) < 3: + self.logger.warning( + f"Cluster {j} has insufficient models ({len(df_outcome['sol_id'].unique())}) for CI calculation" + ) + continue + + chn_collect = {} + sim_collect = {} + self.logger.debug(f"Processing cluster {j}") + if config.cluster_by == ClusterBy.HYPERPARAMETERS: + pattern = "|".join(["_" + name for name in HYPERPARAMETER_NAMES]) + replacement = "" + all_paid = list( + set([re.sub(pattern, replacement, str(x)) for x in all_paid]) + ) + + for i in all_paid: + self.logger.debug(f"Processing channel {i} for cluster {j}") + if config.dep_var_type == DependentVarType.CONVERSION: + df_chn = df_outcome[ + (df_outcome["rn"] == i) & (df_outcome["cpa_total"] != np.inf) + ] + v_samp = df_chn["cpa_total"] + else: + df_chn = df_outcome[df_outcome["rn"] == i] + v_samp = df_chn["roi_total"] + + boot_res = self._bootstrap_sampling(v_samp, boot_n) + boot_mean = float(np.nanmean(boot_res["boot_means"])) + boot_se = boot_res["se"] + ci_low = max(0, boot_res["ci"][0]) + ci_up = boot_res["ci"][1] + + self.logger.debug( + f"Cluster {j}, Channel {i}: CI [{ci_low:.2f}, {ci_up:.2f}], " + f"SE={boot_se:.4f}, n={len(v_samp)}" + ) + + chn_collect[i] = df_chn.assign( + ci_low=ci_low, + ci_up=ci_up, + n=len(v_samp), + boot_se=boot_se, + boot_mean=boot_mean, + cluster=j, + ).reset_index(drop=True) + + sim_collect[i] = ( + pd.DataFrame( + { + "cluster": j, + "rn": i, + "n": len(v_samp), + "boot_mean": boot_mean, + "x_sim": np.random.normal( + loc=boot_mean, scale=boot_se, size=sim_n + ), + } + ) + .assign( + y_sim=lambda x: stats.norm.pdf( + x["x_sim"], loc=boot_mean, scale=boot_se + ) + ) + .reset_index(drop=True) + ) + + cluster_collect.append( + {"chn_collect": chn_collect, "sim_collect": sim_collect} + ) + + self.logger.debug("Finalizing simulation results") + sim_collect = pd.concat([pd.concat(x["sim_collect"]) for x in cluster_collect]) + sim_collect = sim_collect[sim_collect["n"] > 0] + sim_collect["cluster_title"] = sim_collect.apply( + lambda row: f"Cl.{row['cluster']} (n={row['n']})", axis=1 + ) + sim_collect = sim_collect.reset_index(drop=True) + + self.logger.debug("Adding cluster_title to confidence intervals") + df_ci = pd.concat( + [ + pd.concat(x["chn_collect"].values()) + for x in cluster_collect + if x["chn_collect"] + ] + ) + df_ci = df_ci.assign(cluster_title=lambda x: f"Cl.{x['cluster']} (n={x['n']})")[ + [ + "rn", + "cluster_title", + "n", + "cluster", + "boot_mean", + "boot_se", + "ci_low", + "ci_up", + ] + ].drop_duplicates() + + self.logger.debug("Computing final confidence intervals") + df_ci = ( + df_ci.groupby(["rn", "cluster_title", "cluster"]) + .apply( + lambda x: pd.Series( + { + "n": x["n"].iloc[0], + "boot_mean": x["boot_mean"].iloc[0], + "boot_se": x["boot_se"].iloc[0], + "boot_ci": f"[{x['ci_low'].iloc[0]:.2f}, {x['ci_up'].iloc[0]:.2f}]", + "ci_low": x["ci_low"].iloc[0], + "ci_up": x["ci_up"].iloc[0], + "sd": x["boot_se"].iloc[0] * np.sqrt(x["n"].iloc[0] - 1), + "dist100": ( + x["ci_up"].iloc[0] + - x["ci_low"].iloc[0] + + 2 * x["boot_se"].iloc[0] * np.sqrt(x["n"].iloc[0] - 1) + ) + / 99, + } + ) + ) + .reset_index() + ) + + self.logger.info("Confidence interval calculations completed") + return ConfidenceIntervalCollectionData( + confidence_interval_df=df_ci, + sim_collect=sim_collect, + boot_n=boot_n, + sim_n=sim_n, + ) + + def clusterKmeans( + self, + df: pd.DataFrame, + config: ClusteringConfig, + k: Optional[int] = None, + limit=10, + ignored_columns: Optional[List[str]] = None, + wss_var: float = 0.0, + ) -> ClusteredResult: + """ + Automated K-Means Clustering + PCA/t-SNE. + Parameters: + df (pandas.DataFrame): Input dataframe. + k (int): Number of clusters. If None, it will be determined automatically. + limit (int): Maximum number of clusters to consider. + ignore (list): List of column names to ignore. + Returns: + ClusteredResult: containing the results of the clustering. + """ + self.logger.debug(f"Starting clusterKmeans with input shape: {df.shape}") + self.logger.debug( + f"Initial parameters - k: {k}, limit: {limit}, wss_var: {wss_var}" + ) + + np.random.seed(config.seed) + self.logger.debug(f"Random seed set to: {config.seed}") + + # Check if ignored_columns is not None and its first element is NA + if ignored_columns is not None and pd.isna(ignored_columns[0]): + self.logger.debug("First element of ignored_columns is NA, setting to None") + ignored_columns = None + + # Ensure ignored_columns is a list of unique values + if ignored_columns is not None: + self.logger.debug( + f"Processing ignored columns, initial count: {len(ignored_columns)}" + ) + ignored_columns = list(set(ignored_columns)) + order = df.columns.tolist() + aux = df[[col for col in df.columns if col in ignored_columns]] + df = df[[col for col in df.columns if col not in ignored_columns]] + self.logger.info(f"Ignored features: {', '.join(ignored_columns)}") + self.logger.debug( + f"DataFrame shape after removing ignored columns: {df.shape}" + ) + + self.logger.debug("Calculating initial WSS") + wss_values = [np.sum(np.var(df, axis=0)) * (len(df) - 1)] + limit = min(len(df) - 1, limit) + self.logger.info(f"Starting WSS calculation for {limit} clusters") + for i in range(2, limit + 1): + self.logger.debug(f"Calculating WSS for {i} clusters") + kmeans = KMeans(n_clusters=i).fit(df) + wss_values.append(kmeans.inertia_) + self.logger.debug("Creating nclusters DataFrame") + nclusters = pd.DataFrame({"n": range(1, limit + 1), "wss": wss_values}) + + result = ClusteredResult() + result.cluster_data = nclusters + result.wss = self.cluster_visualizer.create_wss_plot(nclusters, k=None) + self.logger.debug("Initial WSS plot created") + + if wss_var > 0.0 and k is None: + self.logger.info( + f"Attempting automatic cluster selection with WSS variance: {wss_var}" + ) + nclusters["pareto"] = nclusters["wss"] / nclusters["wss"].iloc[0] + nclusters["dif"] = nclusters["pareto"].shift(1) - nclusters["pareto"] + k_candidates = nclusters[nclusters["dif"] > wss_var]["n"] + k = k_candidates.max() if not k_candidates.empty else None + self.logger.info( + f"Auto selected k = {k} (clusters) based on minimum WSS variance of {wss_var * 100}%" + ) + + if k is not None: + self.logger.info(f"Proceeding with k={k} clusters") + if ignored_columns is not None: + self.logger.debug("Reconstructing DataFrame with ignored columns") + result.cluster_data = pd.concat([df, aux], axis=1).reindex( + columns=order + [c for c in df.columns if c not in order] + ) + else: + result.cluster_data = df + + result.wss = self.cluster_visualizer.create_wss_plot(nclusters, k=k) + result.n_clusters = k + + self.logger.debug("Performing KMeans clustering") + df_copy = df.copy() + try: + kmeans = KMeans(n_clusters=k, algorithm="lloyd", max_iter=limit) + df_copy.loc[:, "cluster"] = pd.Categorical(kmeans.fit_predict(df_copy)) + self.logger.debug("KMeans clustering completed successfully") + except Exception as e: + self.logger.error(f"KMeans clustering failed: {str(e)}") + raise + + result.cluster_data = pd.concat( + [result.cluster_data, df_copy["cluster"]], axis=1 + ) + self.logger.debug(f"Clustered data after KMeans:") + RobynLogger.log_df(self.logger, result.cluster_data) + + df = df_copy + + self.logger.debug("Calculating cluster means and counts") + try: + # Group by 'cluster' and calculate the mean for each group + cluster_means: pd.DataFrame = df.groupby( + "cluster", observed=False + ).mean() + # Calculate the count of each cluster + cluster_counts = df["cluster"].value_counts() + # Add the counts as a new column to the cluster_means DataFrame + cluster_means["n"] = cluster_counts + + self.logger.debug(f"Cluster sizes: {dict(cluster_counts)}") + self.logger.debug(f"Cluster means:") + RobynLogger.log_df(self.logger, cluster_means) + + # Check for potentially problematic clusters + min_cluster_size = cluster_counts.min() + if min_cluster_size < 3: + self.logger.warning( + f"Some clusters have very few members. Minimum cluster size: {min_cluster_size}" + ) + except Exception as e: + self.logger.error(f"Error calculating cluster statistics: {str(e)}") + raise + + result.clusters_means = cluster_means.reset_index() + result.correlations = None + result.clusters_pca = None + result.clusters_tsne = None + + self.logger.info("Clustering process completed successfully") + self.logger.debug(f"Final result shape: {result.cluster_data.shape}") + + return result + + def _select_optimal_clusters( + self, + df: pd.DataFrame, + config: ClusteringConfig, + limit_clusters: int, + ignored_columns: Optional[List[str]] = None, + wss_var: float = 0.06, + ) -> int: + """Selects the optimal number of clusters based on WSS variance.""" + self.logger.info("Starting optimal cluster selection") + self.logger.debug( + f"Parameters: limit_clusters={limit_clusters}, wss_var={wss_var}" + ) + + if config.k_clusters == maxsize: + try: + self.logger.debug("Attempting automatic cluster selection") + cls = self.clusterKmeans( + df, + config, + k=None, + limit=limit_clusters, + ignored_columns=ignored_columns, + ) + + if cls.cluster_data is None or cls.cluster_data.empty: + self.logger.error("Cluster data is None or empty") + raise ValueError("cls.cluster_data is None or empty") + + k = ( + cls.cluster_data.assign( + pareto=lambda x: x["wss"] / x["wss"].iloc[0] + ) + .assign( + dif=lambda x: x["pareto"].shift(1, fill_value=np.nan) + - x["pareto"] + ) + .query(f"dif > {wss_var}")["n"] + .values + ) + k = np.max(k) + + self.logger.debug(f"Initial optimal k value: {k}") + + if k < config.min_clusters: + self.logger.warning( + f"Adjusting cluster count up from {k} to minimum {config.min_clusters}" + ) + k = config.min_clusters + if k > limit_clusters: + self.logger.warning( + f"Adjusting cluster count down from {k} to maximum {limit_clusters}" + ) + k = limit_clusters + + self.logger.info(f"Selected optimal number of clusters: {k}") + return k + except Exception as e: + self.logger.error( + f"Failed to automatically determine clusters: {str(e)}" + ) + raise e + else: + self.logger.info(f"Using pre-configured cluster count: {config.k_clusters}") + return config.k_clusters + + def _prepare_performance_data_for_clustering( + self, x_decomp_agg: pd.DataFrame, config: ClusteringConfig + ) -> pd.DataFrame: + """Prepares performance data for clustering""" + self.logger.debug("Preparing performance data for clustering") + self.logger.debug(f"Dependent variable type: {config.dep_var_type}") + + outcome: pd.DataFrame = pd.DataFrame() + if config.dep_var_type == DependentVarType.REVENUE: + self.logger.debug("Processing revenue-based metrics") + outcome = x_decomp_agg[["sol_id", "rn", "roi_total"]].pivot( + index="sol_id", columns="rn", values="roi_total" + ) + outcome = outcome.dropna(axis=1, how="all") + outcome = outcome.reset_index()[ + ["sol_id"] + [col for col in outcome.columns if col in config.all_media] + ] + elif config.dep_var_type == DependentVarType.CONVERSION: + self.logger.debug("Processing conversion-based metrics") + outcome = x_decomp_agg[["sol_id", "rn", "cpa_total"]].dropna( + subset=["cpa_total"] + ) + outcome = outcome.pivot(index="sol_id", columns="rn", values="cpa_total") + outcome = outcome.dropna(axis=1, how="all") + outcome = outcome.reset_index()[ + ["sol_id"] + [col for col in outcome.columns if col in config.all_media] + ] + + self.logger.debug("Selecting error metrics") + errors = x_decomp_agg[ + ["sol_id"] + + [col for col in x_decomp_agg.columns if col.startswith("nrmse")] + + ["decomp.rssd", "mape"] + ].drop_duplicates() + + self.logger.debug("Merging outcome with errors") + final_df = outcome.merge(errors, on="sol_id", how="left") + self.logger.debug(f"Final dataset shape: {final_df.shape}") + return final_df + + def _prepare_hyperparameter_data_for_clustering( + self, result_hyp_param: pd.DataFrame + ) -> pd.DataFrame: + """Prepares hyperparameter data for clustering""" + self.logger.debug("Preparing hyperparameter data for clustering") + + # Select relevant columns + selected_columns = ( + ["sol_id"] + + [ + col + for col in result_hyp_param.columns + if any(hyp in col for hyp in HYPERPARAMETER_NAMES) + ] + + [ + col + for col in result_hyp_param.columns + if any(metric in col for metric in ["nrmse", "decomp.rssd", "mape"]) + ] + ) + + self.logger.debug(f"Selected {len(selected_columns)} columns for clustering") + + # Create DataFrame with selected columns + outcome: pd.DataFrame = result_hyp_param[selected_columns] + + # Remove columns with all NA values + initial_cols = len(outcome.columns) + outcome = outcome.dropna(axis=1, how="all") + dropped_cols = initial_cols - len(outcome.columns) + + if dropped_cols > 0: + self.logger.warning(f"Dropped {dropped_cols} columns with all NA values") + + self.logger.debug(f"Final dataset shape: {outcome.shape}") + return outcome + + def _compute_error_scores( + self, + df: pd.DataFrame, + weights: List[float] = [1, 1, 1], + ts_validation: bool = True, + ) -> pd.Series: + """Calculate error scores for models""" + self.logger.debug("Computing error scores") + self.logger.debug( + f"Parameters: weights={weights}, ts_validation={ts_validation}" + ) + + assert len(weights) == 3, "Weights must have exactly 3 values" + + error_cols = [ + "nrmse_test" if ts_validation else "nrmse_train", + "decomp.rssd", + "mape", + ] + + missing_cols = [col for col in error_cols if col not in df.columns] + if missing_cols: + self.logger.error(f"Missing required columns: {missing_cols}") + raise AssertionError(f"Missing columns: {missing_cols}") + + balance = np.array(weights) / sum(weights) + self.logger.debug(f"Normalized weights: {balance}") + + scores = df[error_cols].copy() + scores = scores.rename(columns={error_cols[0]: "nrmse"}) + + # Handle infinite values + for col in ["nrmse", "decomp.rssd", "mape"]: + inf_count = np.sum(np.isinf(scores[col])) + if inf_count > 0: + self.logger.warning(f"Found {inf_count} infinite values in {col}") + scores[col] = np.where( + np.isinf(scores[col]), + np.max(scores[col][~np.isinf(scores[col])]), + scores[col], + ) + + # Normalize scores + scores["nrmse_n"] = ParetoUtils.min_max_norm(scores["nrmse"]) + scores["decomp.rssd_n"] = ParetoUtils.min_max_norm(scores["decomp.rssd"]) + scores["mape_n"] = ParetoUtils.min_max_norm(scores["mape"]) + + scores.fillna(0, inplace=True) + + # Apply weights + scores["nrmse_w"] = balance[0] * scores["nrmse_n"] + scores["decomp.rssd_w"] = balance[1] * scores["decomp.rssd_n"] + scores["mape_w"] = balance[2] * scores["mape_n"] + + # Calculate final error score + scores["error_score"] = np.sqrt( + scores["nrmse_w"] ** 2 + + scores["decomp.rssd_w"] ** 2 + + scores["mape_w"] ** 2 + ) + + self.logger.debug( + f"Error score statistics: min={scores['error_score'].min():.4f}, " + f"max={scores['error_score'].max():.4f}, " + f"mean={scores['error_score'].mean():.4f}" + ) + + return scores["error_score"] + + def _select_top_solutions( + self, clustered_df: pd.DataFrame, config: ClusteringConfig, limit: int = 1 + ) -> pd.DataFrame: + """Selects top solutions from each cluster""" + self.logger.info(f"Selecting top {limit} solutions per cluster") + self.logger.debug(f"Input dataset shape: {clustered_df.shape}") + + ts_validation: bool = "nrmse_test" in clustered_df.columns + df = clustered_df.copy() + + self.logger.debug("Computing error scores") + df["error_score"] = self._compute_error_scores( + df, config.weights, ts_validation + ) + + df.fillna(0, inplace=True) + + self.logger.debug("Sorting and ranking solutions") + df = df.sort_values(by=["cluster", "error_score"]) + initial_solutions = len(df) + df = df.groupby("cluster", observed=False).head(limit) + df["rank"] = df.groupby("cluster", observed=False)["error_score"].rank( + method="dense" + ) + df = df[ + ["cluster", "rank"] + + [col for col in df.columns if col not in ["cluster", "rank"]] + ] + self.logger.info(f"Selected {len(df)} solutions from {initial_solutions} total") + RobynLogger.log_df(self.logger, df) + + return df + + def _bootstrap_sampling( + self, sample: pd.Series, boot_n: int, seed: int = 1 + ) -> Dict[str, Union[np.ndarray, List[float]]]: + self.logger.debug( + f"Starting bootstrap sampling with sample size: {len(sample)} and boot_n: {boot_n}" + ) + + # Log sample statistics at debug level + self.logger.debug( + f"Sample statistics - Mean: {sample.mean():.4f}, " + f"Std: {sample.std():.4f}, " + f"Non-null count: {sample.count()}" + ) + np.random.seed(seed) + + valid_samples = sample[~sample.isna()] + if len(valid_samples) > 1: + # Calculate initial statistics + sample_n = len(sample) + sample_mean = float( + np.nanmean(sample) + ) # Equivalent to mean(samp, na.rm=TRUE) + + # Generate bootstrap samples + boot_sample = np.random.choice( + valid_samples, # Use only valid samples for bootstrapping + size=(boot_n, sample_n), + replace=True, + ) + + # Calculate bootstrap means + boot_means = np.mean(boot_sample, axis=1) + + # Calculate standard error + se = float(np.std(boot_means)) + + # Calculate margin of error and confidence interval + me = stats.t.ppf(0.975, sample_n - 1) * se + sample_me = np.sqrt(sample_n) * me + ci = [sample_mean - sample_me, sample_mean + sample_me] + + return { + "boot_means": boot_means, + "ci": ci, + "se": se, # Return single value instead of list + } + else: + # Handle case with insufficient samples + if len(valid_samples) == 0: + single_value = np.nan + else: + single_value = valid_samples.iloc[0] + + return { + "boot_means": np.array([single_value]), + "ci": [single_value, single_value], + "se": 0.0, # Return single value instead of list + } diff --git a/python/src/robyn/modeling/clustering/clustering_config.py b/python/src/robyn/modeling/clustering/clustering_config.py new file mode 100644 index 000000000..baccedbe1 --- /dev/null +++ b/python/src/robyn/modeling/clustering/clustering_config.py @@ -0,0 +1,60 @@ +# pyre-strict + +from dataclasses import dataclass +from enum import Enum +from sys import maxsize +from typing import List, Literal, Optional + +from robyn.data.entities.enums import DependentVarType + + +class ClusterBy(Enum): + PERFORMANCE = "performance" + HYPERPARAMETERS = "hyperparameters" + + +@dataclass +class ClusteringConfig: + """ + Configuration for the clustering process. + + Attributes: + dep_var_type (DependentVarType): Type of dependent variable (revenue or conversion). + cluster_by (ClusterBy): Attribute to cluster by (performance or hyperparameters). + max_clusters (int): Maximum number of clusters to consider. + limit (int): Top N results per cluster. + weights (List[float]): Weights for NRMSE, DECOMP.RSSD, and MAPE errors. + dim_reduction (Literal["PCA", "tSNE"]): Dimensionality reduction technique. + export (bool): Whether to export results. + seed (int): Random seed for reproducibility. + """ + + weights: List[float] + dep_var_type: DependentVarType + cluster_by: ClusterBy = ClusterBy.HYPERPARAMETERS + max_clusters: int = 10 + min_clusters: int = 3 + k_clusters: int = maxsize + limit: int = 1 + dim_reduction: Literal["PCA", "tSNE"] = "PCA" + export: bool = False + seed: int = 123 + all_media: Optional[List[str]] = None + + def __str__(self) -> str: + """Returns a human-readable string representation of the clustering configuration.""" + return ( + f"ClusteringConfig(\n" + f" dep_var_type: {self.dep_var_type}\n" + f" cluster_by: {self.cluster_by.value}\n" + f" weights: {self.weights}\n" + f" max_clusters: {self.max_clusters}\n" + f" min_clusters: {self.min_clusters}\n" + f" k_clusters: {self.k_clusters}\n" + f" limit: {self.limit}\n" + f" dim_reduction: {self.dim_reduction}\n" + f" export: {self.export}\n" + f" seed: {self.seed}\n" + f" all_media: {self.all_media}\n" + ")" + ) diff --git a/python/src/robyn/modeling/convergence/convergence.py b/python/src/robyn/modeling/convergence/convergence.py new file mode 100644 index 000000000..d4b285ab6 --- /dev/null +++ b/python/src/robyn/modeling/convergence/convergence.py @@ -0,0 +1,239 @@ +# pyre-strict +import logging +import numpy as np +import pandas as pd +from typing import List, Dict, Any +from robyn.modeling.entities.modeloutputs import Trial +from robyn.visualization.model_convergence_visualizer import ModelConvergenceVisualizer +import matplotlib.pyplot as plt + + +class Convergence: + def __init__( + self, + n_cuts: int = 20, + sd_qtref: int = 3, + med_lowb: int = 2, + nrmse_win: List[float] = [0, 0.998], + ): + self.n_cuts = n_cuts + self.sd_qtref = sd_qtref + self.med_lowb = med_lowb + self.nrmse_win = nrmse_win + self.visualizer = ModelConvergenceVisualizer(n_cuts, nrmse_win) + self.logger = logging.getLogger(__name__) + + def calculate_convergence(self, trials: List[Trial]) -> Dict[str, Any]: + self.logger.info("Starting convergence calculation") + self.logger.debug(f"Processing {len(trials)} trials") + + try: + # Concatenate trial results + self.logger.debug("Concatenating trial results") + df = pd.concat( + [trial.result_hyp_param for trial in trials], ignore_index=True + ) + self.logger.debug(f"Combined dataframe shape: {df.shape}") + + # Validate required columns + required_columns = ["ElapsedAccum", "trial", "nrmse", "decomp.rssd", "mape"] + missing_columns = [col for col in required_columns if col not in df.columns] + if missing_columns: + error_msg = f"Missing columns in result_hyp_param: {missing_columns}" + self.logger.error(error_msg) + raise ValueError(error_msg) + + # Check calibration status + calibrated = "mape" in df.columns and df["mape"].sum() > 0 + if not calibrated: + self.logger.warning( + "'mape' column not found or all zeros. Assuming model is not calibrated." + ) + else: + self.logger.info("Model is calibrated") + + # Process data and calculate errors + self.logger.debug("Preparing data for convergence analysis") + dt_objfunc_cvg = self._prepare_data(df) + self.logger.debug(f"Prepared data shape: {dt_objfunc_cvg.shape}") + + self.logger.debug("Calculating convergence errors") + errors = self._calculate_errors(dt_objfunc_cvg) + self.logger.debug( + f"Generated errors for {len(errors['error_type'].unique())} error types" + ) + + # Generate convergence messages + self.logger.debug("Generating convergence messages") + conv_msg = self._generate_convergence_messages(errors) + + # Create visualization plots + + moo_distrb_plot = self.visualizer.create_moo_distrb_plot( + dt_objfunc_cvg, conv_msg + ) + moo_cloud_plot = self.visualizer.create_moo_cloud_plot( + df, conv_msg, calibrated + ) + ts_validation_plot = None # self.visualizer.create_ts_validation_plot(trials) #Disabled for testing. #Sandeep + + self.logger.info("Convergence calculation completed successfully") + return { + "moo_distrb_plot": moo_distrb_plot, + "moo_cloud_plot": moo_cloud_plot, + "ts_validation_plot": ts_validation_plot, + "errors": errors, + "conv_msg": conv_msg, + } + + except Exception as e: + self.logger.error( + f"Error during convergence calculation: {str(e)}", exc_info=True + ) + raise + + def _prepare_data(self, df: pd.DataFrame) -> pd.DataFrame: + self.logger.debug("Starting data preparation") + + # Determine value variables + value_vars = ["nrmse", "decomp.rssd"] + if "mape" in df.columns and df["mape"].sum() > 0: + value_vars.append("mape") + self.logger.debug("Including MAPE in value variables") + + self.logger.debug(f"Melting dataframe with value variables: {value_vars}") + dt_objfunc_cvg = df.melt( + id_vars=["ElapsedAccum", "trial"], + value_vars=value_vars, + var_name="error_type", + value_name="value", + ) + + # Filter and process data + initial_rows = len(dt_objfunc_cvg) + dt_objfunc_cvg = dt_objfunc_cvg[dt_objfunc_cvg["value"] > 0] + dt_objfunc_cvg = dt_objfunc_cvg[np.isfinite(dt_objfunc_cvg["value"])] + filtered_rows = len(dt_objfunc_cvg) + self.logger.debug( + f"Filtered out {initial_rows - filtered_rows} rows with zero or non-finite values" + ) + + # Process error types and iterations + dt_objfunc_cvg["error_type"] = dt_objfunc_cvg["error_type"].str.upper() + dt_objfunc_cvg = dt_objfunc_cvg.sort_values(["trial", "ElapsedAccum"]) + dt_objfunc_cvg["iter"] = ( + dt_objfunc_cvg.groupby(["error_type", "trial"]).cumcount() + 1 + ) + + # Create cuts + max_iter = dt_objfunc_cvg["iter"].max() + self.logger.debug( + f"Creating {self.n_cuts} cuts for maximum iteration {max_iter}" + ) + bins = np.linspace(0, max_iter, self.n_cuts + 1) + labels = np.round( + np.linspace(max_iter / self.n_cuts, max_iter, self.n_cuts) + ).astype(int) + + dt_objfunc_cvg["cuts"] = pd.cut( + dt_objfunc_cvg["iter"], + bins=bins, + labels=labels, + include_lowest=True, + ordered=False, + ) + dt_objfunc_cvg["cuts"] = dt_objfunc_cvg["cuts"].astype(float) + + self.logger.debug("Data preparation completed") + return dt_objfunc_cvg + + def _calculate_errors(self, dt_objfunc_cvg: pd.DataFrame) -> pd.DataFrame: + self.logger.debug("Starting error calculations") + + # Calculate basic statistics + self.logger.debug("Calculating error statistics by group") + errors = ( + dt_objfunc_cvg.groupby(["error_type", "cuts"], observed=True) + .agg({"value": ["count", "median", "std"]}) + .reset_index() + ) + errors.columns = ["error_type", "cuts", "n", "median", "std"] + + # Calculate median variation percentage + self.logger.debug("Calculating median variation percentage") + errors["med_var_P"] = ( + errors.groupby("error_type", observed=True)["median"] + .pct_change(fill_method=None) + .abs() + * 100 + ) + errors["med_var_P"] = errors["med_var_P"].fillna(0) + + # Calculate aggregate statistics + self.logger.debug( + f"Calculating aggregate statistics with sd_qtref={self.sd_qtref}" + ) + agg_errors = errors.groupby("error_type").agg( + { + "median": [ + ("first_med", "first"), + ("first_med_avg", lambda x: x.head(self.sd_qtref).mean()), + ("last_med", "last"), + ], + "std": [ + ("first_sd", "first"), + ("first_sd_avg", lambda x: x.head(self.sd_qtref).mean()), + ("last_sd", "last"), + ], + } + ) + agg_errors.columns = [ + "_".join(col).strip() for col in agg_errors.columns.values + ] + agg_errors = agg_errors.reset_index() + + # Merge and calculate flags + self.logger.debug( + "Merging aggregate statistics and calculating threshold flags" + ) + errors = errors.merge(agg_errors, on="error_type", how="left") + errors["med_thres"] = ( + errors["median_first_med"] - self.med_lowb * errors["std_first_sd_avg"] + ) + errors["flag_med"] = errors["median"].abs() < errors["med_thres"] + errors["flag_sd"] = errors["std"] < errors["std_first_sd_avg"] + + self.logger.debug("Error calculations completed") + return errors + + def _generate_convergence_messages(self, errors: pd.DataFrame) -> List[str]: + self.logger.debug("Starting convergence message generation") + conv_msg = [] + + for obj_fun in errors["error_type"].unique(): + self.logger.debug(f"Processing convergence message for {obj_fun}") + temp_df = errors[errors["error_type"] == obj_fun].copy() + temp_df["median"] = temp_df["median"].round(2) + last_qt = temp_df.iloc[-1] + did_converge = ( + "converged" + if last_qt["flag_sd"] and last_qt["flag_med"] + else "NOT converged" + ) + symb_sd = "<=" if last_qt["flag_sd"] else ">" + symb_med = "<=" if last_qt["flag_med"] else ">" + msg = ( + f"{obj_fun} {did_converge}: " + f"sd@qt.{self.n_cuts} {last_qt['std']:.3f} {symb_sd} {last_qt['std_first_sd_avg']:.3f} & " + f"|med@qt.{self.n_cuts}| {abs(last_qt['median']):.2f} {symb_med} {last_qt['med_thres']:.2f}" + ) + conv_msg.append(msg) + + # Log convergence status + log_level = logging.INFO if did_converge == "converged" else logging.WARNING + self.logger.log( + log_level, f"Convergence status for {obj_fun}: {did_converge}" + ) + self.logger.info(msg) # Log the message as INFO + self.logger.debug("Convergence message generation completed") + return conv_msg diff --git a/python/src/robyn/modeling/entities/ci_collection_data.py b/python/src/robyn/modeling/entities/ci_collection_data.py new file mode 100644 index 000000000..f04dd4e70 --- /dev/null +++ b/python/src/robyn/modeling/entities/ci_collection_data.py @@ -0,0 +1,10 @@ +import pandas as pd +from dataclasses import dataclass + + +@dataclass +class ConfidenceIntervalCollectionData: + confidence_interval_df: pd.DataFrame + sim_collect: pd.DataFrame + boot_n: int + sim_n: int diff --git a/python/src/robyn/modeling/entities/clustering_results.py b/python/src/robyn/modeling/entities/clustering_results.py new file mode 100644 index 000000000..df2920481 --- /dev/null +++ b/python/src/robyn/modeling/entities/clustering_results.py @@ -0,0 +1,86 @@ +# pyre-strict +from dataclasses import dataclass, field +from typing import List, Optional + +import pandas as pd +from matplotlib.figure import Figure + + +@dataclass +class ClusterPlotResults: + """Collection of visualization data frames generated during cluster analysis. + + Args: + top_solutions_errors_plot: Data for model error distribution plots. + top_solutions_rois_plot: Data for ROI comparison plots of top models. + """ + + top_solutions_errors_plot: Optional[Figure] = None + top_solutions_rois_plot: Optional[Figure] = None + + +@dataclass +class ClusterConfidenceIntervals: + """Statistical confidence intervals for cluster analysis results. + + Args: + cluster_confidence_interval_df: DataFrame containing confidence intervals for cluster metrics. + boot_n: Number of bootstrap iterations used for CI calculations. + sim_n: Number of simulations performed for CI estimation. + clusters_confidence_interval_plot: Data for confidence interval plots by cluster. + """ + + cluster_confidence_interval_df: pd.DataFrame = field(default_factory=pd.DataFrame) + boot_n: int = 0 + sim_n: int = 0 + clusters_confidence_interval_plot: Optional[Figure] = None + + +@dataclass +class DimentionalityReductionResults: + """Principal Component Analysis or t-Distributed Stochastic Neighbor Embedding results from clustering process. + + Args: + explained_variance: Series containing explained variance ratios. + df: DataFrame with PCA-transformed data. + plot_explained_variance: Optional DataFrame with explained variance visualization data. + plot: Optional dictionary containing additional PCA plot data. + """ + + explained_variance: pd.Series = field(default_factory=pd.Series) + df: pd.DataFrame = field(default_factory=pd.DataFrame) + plot_explained: Optional[Figure] = None + plot: Optional[Figure] = None + + +@dataclass +class ClusteredResult: + """Complete clustering analysis results from Robyn's clustering process. + + Args: + cluster_data: DataFrame with primary clustering results and model assignments. + top_solutions: DataFrame containing best performing models per cluster. + cluster_ci: Confidence interval calculations for clustering results. + n_clusters: Number of clusters identified in the analysis. + errors_weights: List of weights applied to different error metrics. + clusters_means: DataFrame of mean values for each cluster. + wss: plot containing within-sum-of-squares metrics. + correlations: plot of correlation analysis between clusters. + clusters_pca: Optional PCA dimensionality reduction results. + clusters_tsne: Optional t-SNE dimensionality reduction results. + plots: Optional collection of visualization data frames. + """ + + cluster_data: pd.DataFrame = field(default_factory=pd.DataFrame) + top_solutions: pd.DataFrame = field(default_factory=pd.DataFrame) + cluster_ci: ClusterConfidenceIntervals = field( + default_factory=ClusterConfidenceIntervals + ) + n_clusters: int = 0 + errors_weights: List[float] = field(default_factory=list) + clusters_means: pd.DataFrame = field(default_factory=pd.DataFrame) + wss: Figure = field(default_factory=Figure) + correlations: Optional[Figure] = None + clusters_pca: Optional[DimentionalityReductionResults] = None + clusters_tsne: Optional[DimentionalityReductionResults] = None + plots: ClusterPlotResults = field(default_factory=ClusterPlotResults) diff --git a/python/src/robyn/modeling/entities/convergence_data.py b/python/src/robyn/modeling/entities/convergence_data.py new file mode 100644 index 000000000..14c1afabe --- /dev/null +++ b/python/src/robyn/modeling/entities/convergence_data.py @@ -0,0 +1,28 @@ +from dataclasses import dataclass +from typing import List, Dict, Optional +import pandas as pd + + +@dataclass +class ConvergenceData: + moo_distrb_plot: Optional[str] # Hexadecimal string of plot image data + moo_cloud_plot: Optional[str] # Hexadecimal string of plot image data + errors: pd.DataFrame + conv_msg: List[str] + + @classmethod + def from_dict(cls, data: Dict[str, any]) -> "ConvergenceData": + return cls( + moo_distrb_plot=data.get("moo_distrb_plot"), + moo_cloud_plot=data.get("moo_cloud_plot"), + errors=pd.DataFrame(data.get("errors", [])), + conv_msg=data.get("conv_msg", []), + ) + + def to_dict(self) -> Dict[str, any]: + return { + "moo_distrb_plot": self.moo_distrb_plot, + "moo_cloud_plot": self.moo_cloud_plot, + "errors": self.errors.to_dict(orient="records"), + "conv_msg": self.conv_msg, + } diff --git a/python/src/robyn/modeling/entities/enums.py b/python/src/robyn/modeling/entities/enums.py new file mode 100644 index 000000000..32fb3d892 --- /dev/null +++ b/python/src/robyn/modeling/entities/enums.py @@ -0,0 +1,33 @@ +from enum import auto, Enum + + +class NevergradAlgorithm(Enum): + """ + Enumeration of available Nevergrad optimization algorithms. + These algorithms are used in the hyperparameter optimization process. + """ + + DE = "DE" # Differential Evolution + TWO_POINTS_DE = "TwoPointsDE" # Two-Points Differential Evolution + ONE_PLUS_ONE = "OnePlusOne" # One Plus One + DOUBLE_FAST_GA_DISCRETE_ONE_PLUS_ONE = ( + "DoubleFastGADiscreteOnePlusOne" # Double Fast GA Discrete One Plus One + ) + DISCRETE_ONE_PLUS_ONE = "DiscreteOnePlusOne" # Discrete One Plus One + PORTFOLIO_DISCRETE_ONE_PLUS_ONE = ( + "PortfolioDiscreteOnePlusOne" # Portfolio Discrete One Plus One + ) + NAIVE_TBPSA = "NaiveTBPSA" # Naive TBPSA + CGA = "CGA" # Compact Genetic Algorithm + RANDOM_SEARCH = "RandomSearch" # Random Search + + +class Models(Enum): + """ + Enumeration of available model types. + + This enum can be expanded to include other model types as they are implemented. + """ + + RIDGE = auto() # Ridge Regression + # Add other model types as needed diff --git a/python/src/robyn/modeling/entities/featurized_mmm_data.py b/python/src/robyn/modeling/entities/featurized_mmm_data.py new file mode 100644 index 000000000..d3ed3304a --- /dev/null +++ b/python/src/robyn/modeling/entities/featurized_mmm_data.py @@ -0,0 +1,10 @@ +from dataclasses import dataclass +import pandas as pd +from typing import Dict, Any + + +@dataclass +class FeaturizedMMMData: + dt_mod: pd.DataFrame + dt_modRollWind: pd.DataFrame + modNLS: Dict[str, Any] diff --git a/python/src/robyn/modeling/entities/model_refit_output.py b/python/src/robyn/modeling/entities/model_refit_output.py new file mode 100644 index 000000000..d42cf70ff --- /dev/null +++ b/python/src/robyn/modeling/entities/model_refit_output.py @@ -0,0 +1,27 @@ +# model_refit_output.py + +from dataclasses import dataclass +from typing import Optional +import numpy as np +from sklearn.linear_model import Ridge + + +@dataclass +class ModelRefitOutput: + rsq_train: float + rsq_val: Optional[float] + rsq_test: Optional[float] + nrmse_train: float + nrmse_val: Optional[float] + nrmse_test: Optional[float] + coefs: np.ndarray + y_train_pred: np.ndarray + y_val_pred: Optional[np.ndarray] + y_test_pred: Optional[np.ndarray] + y_pred: np.ndarray + mod: Ridge + df_int: int + lambda_: float + lambda_hp: float + lambda_max: float + lambda_min_ratio: float diff --git a/python/src/robyn/modeling/entities/modeloutputs.py b/python/src/robyn/modeling/entities/modeloutputs.py new file mode 100644 index 000000000..ca690f154 --- /dev/null +++ b/python/src/robyn/modeling/entities/modeloutputs.py @@ -0,0 +1,89 @@ +# pyre-strict + +from dataclasses import dataclass +from typing import List, Dict, Any, Optional +import pandas as pd +from dataclasses import field + + +@dataclass +class Trial: + result_hyp_param: pd.DataFrame + decomp_spend_dist: pd.DataFrame + x_decomp_agg: pd.DataFrame + nrmse: float + decomp_rssd: float + mape: float + rsq_train: float + rsq_val: float + rsq_test: float + lambda_: float + lambda_hp: float + lambda_max: float + lambda_min_ratio: float + pos: int + nrmse_train: float = 0.0 + nrmse_val: float = 0.0 + nrmse_test: float = 0.0 + elapsed: float = 0.0 + elapsed_accum: float = 0.0 + trial: int = 1 + iter_ng: int = 1 + iter_par: int = 1 + train_size: float = 1.0 + sol_id: str = "1_1_1" + lift_calibration: pd.DataFrame = field(default_factory=pd.DataFrame) + + +@dataclass +class ModelOutputs: + """ + Represents the overall outputs of the modeling process. + + This class contains the results of all trials, along with metadata about the model run. + + Attributes: + trials (List[Trial]): List of all trials run during the modeling process. + train_timestamp (str): Timestamp of when the model was trained. + cores (int): Number of CPU cores used for training. + iterations (int): Number of iterations per trial. + intercept (bool): Whether an intercept was included in the model. + intercept_sign (str): Sign constraint applied to the intercept. + nevergrad_algo (str): Nevergrad algorithm used for optimization. + ts_validation (bool): Whether time series validation was used. + add_penalty_factor (bool): Whether a penalty factor was added. + hyper_updated (Dict[str, Any]): Updated hyperparameters. + hyper_fixed (bool): Whether hyperparameters were fixed. + convergence (Dict[str, Any]): Convergence information for the optimization process. + select_id (str): ID of the selected model. + seed (int): Random seed used for reproducibility. + hyper_bound_ng (Dict[str, Any]): Hyperparameter bounds for Nevergrad optimization. + hyper_bound_fixed (Dict[str, Any]): Fixed hyperparameter bounds. + ts_validation_plot (Optional[str]): Time series validation plot, if applicable. + all_result_hyp_param (pd.DataFrame): Aggregated hyperparameter results from all trials. + all_x_decomp_agg (pd.DataFrame): Aggregated decomposition results from all trials. + all_decomp_spend_dist (pd.DataFrame): Aggregated spend distribution results from all trials. + """ + + trials: List[Trial] + train_timestamp: str + cores: int + iterations: int + intercept: bool + intercept_sign: str + nevergrad_algo: str + ts_validation: bool + add_penalty_factor: bool + hyper_updated: Dict[str, Any] + hyper_fixed: bool + select_id: str + hyper_bound_ng: Dict[str, Any] # Move non-default arguments before default ones + hyper_bound_fixed: Dict[str, Any] + seed: List[int] = field(default_factory=lambda: [123]) # Ensure seed is a list + convergence: Dict[str, Any] = field(default_factory=dict) # Default argument + ts_validation_plot: List[Optional[str]] = field( + default_factory=list + ) # Ensure ts_validation_plot is a list + all_result_hyp_param: pd.DataFrame = field(default_factory=pd.DataFrame) + all_x_decomp_agg: pd.DataFrame = field(default_factory=pd.DataFrame) + all_decomp_spend_dist: pd.DataFrame = field(default_factory=pd.DataFrame) diff --git a/python/src/robyn/modeling/entities/modelrun_trials_config.py b/python/src/robyn/modeling/entities/modelrun_trials_config.py new file mode 100644 index 000000000..19a07a694 --- /dev/null +++ b/python/src/robyn/modeling/entities/modelrun_trials_config.py @@ -0,0 +1,21 @@ +from dataclasses import dataclass +from typing import Optional + + +@dataclass +class TrialsConfig: + """ + Configuration for model trials. + + This class defines the parameters for running multiple trials of the model. + + Attributes: + trials (int): The number of trials to run. Each trial is an independent + model fitting process with its own set of hyperparameters. + iterations (int): The number of iterations to run for each trial. This + determines how many times the optimization algorithm will attempt + to improve the model within each trial. + """ + + trials: int + iterations: int diff --git a/python/src/robyn/modeling/entities/pareto_data.py b/python/src/robyn/modeling/entities/pareto_data.py new file mode 100644 index 000000000..0e487ea44 --- /dev/null +++ b/python/src/robyn/modeling/entities/pareto_data.py @@ -0,0 +1,13 @@ +# pyre-strict + +from typing import List +import pandas as pd +from dataclasses import dataclass + + +@dataclass +class ParetoData: + decomp_spend_dist: pd.DataFrame + result_hyp_param: pd.DataFrame + x_decomp_agg: pd.DataFrame + pareto_fronts: List[int] diff --git a/python/src/robyn/modeling/entities/pareto_result.py b/python/src/robyn/modeling/entities/pareto_result.py new file mode 100644 index 000000000..cebfc888d --- /dev/null +++ b/python/src/robyn/modeling/entities/pareto_result.py @@ -0,0 +1,32 @@ +from dataclasses import dataclass +from typing import Dict, List, Optional + +import pandas as pd + + +@dataclass +class ParetoResult: + """ + Holds the results of Pareto optimization for marketing mix models. + + Attributes: + pareto_solutions (List[str]): List of solution IDs that are Pareto-optimal. + pareto_fronts (int): Number of Pareto fronts considered in the optimization. + result_hyp_param (pd.DataFrame): Hyperparameters of Pareto-optimal solutions. + x_decomp_agg (pd.DataFrame): Aggregated decomposition results for Pareto-optimal solutions. + result_calibration (Optional[pd.DataFrame]): Calibration results, if calibration was performed. + media_vec_collect (pd.DataFrame): Collected media vectors for all Pareto-optimal solutions. + x_decomp_vec_collect (pd.DataFrame): Collected decomposition vectors for all Pareto-optimal solutions. + plot_data_collect (Dict[str, pd.DataFrame]): Data for various plots, keyed by plot type. + df_caov_pct_all (pd.DataFrame): Carryover percentage data for all channels and Pareto-optimal solutions. + """ + + pareto_solutions: List[str] + pareto_fronts: int + result_hyp_param: pd.DataFrame + x_decomp_agg: pd.DataFrame + result_calibration: Optional[pd.DataFrame] + media_vec_collect: pd.DataFrame + x_decomp_vec_collect: pd.DataFrame + plot_data_collect: Dict[str, pd.DataFrame] + df_caov_pct_all: pd.DataFrame diff --git a/python/src/robyn/modeling/feature_engineering.py b/python/src/robyn/modeling/feature_engineering.py new file mode 100644 index 000000000..16091dc09 --- /dev/null +++ b/python/src/robyn/modeling/feature_engineering.py @@ -0,0 +1,639 @@ +# pyre-strict + +from typing import Optional, Dict, Any +import logging +import pandas as pd +import warnings +from scipy.optimize import curve_fit +from sklearn.linear_model import LinearRegression +import numpy as np + +np.float_ = np.float64 +from prophet import Prophet +from robyn.data.entities.holidays_data import HolidaysData + +from robyn.data.entities.enums import ( + AdstockType, +) +from robyn.modeling.entities.featurized_mmm_data import FeaturizedMMMData +from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters +from robyn.data.entities.mmmdata import MMMData + + +logger = logging.getLogger(__name__) + + +class FeatureEngineering: + """ + A class used to perform feature engineering for Marketing Mix Modeling (MMM) data. + """ + + def __init__( + self, + mmm_data: MMMData, + hyperparameters: Hyperparameters, + holidays_data: Optional[HolidaysData] = None, + ): + self.mmm_data = mmm_data + self.hyperparameters = hyperparameters + self.holidays_data = holidays_data + self.logger = logger + self.logger.debug( + "Initializing FeatureEngineering with MMM data and hyperparameters" + ) + + def perform_feature_engineering(self, quiet: bool = False) -> FeaturizedMMMData: + self.logger.info("Starting feature engineering process") + self.logger.debug(f"Input data shape: {self.mmm_data.data.shape}") + + dt_transform = self._prepare_data() + self.logger.debug(f"Prepared data shape: {dt_transform.shape}") + + # Check if Prophet decomposition should be performed + prophet_enabled = ( + self.holidays_data is not None + and self.holidays_data.prophet_vars is not None + and len(self.holidays_data.prophet_vars) > 0 + ) + + if prophet_enabled: + self.logger.info("Starting Prophet decomposition") + dt_transform = self._prophet_decomposition(dt_transform) + if not quiet: + self.logger.info("Prophet decomposition complete") + else: + self.logger.info( + "Prophet decomposition disabled - no prophet variables specified" + ) + + # Include all independent variables + all_ind_vars = [] + if prophet_enabled: + all_ind_vars.extend(self.holidays_data.prophet_vars) + + all_ind_vars.extend( + self.mmm_data.mmmdata_spec.context_vars + + self.mmm_data.mmmdata_spec.paid_media_spends + + self.mmm_data.mmmdata_spec.organic_vars + ) + + self.logger.debug(f"Processing {len(all_ind_vars)} independent variables") + + dt_mod = dt_transform + dt_modRollWind = self._create_rolling_window_data(dt_transform) + self.logger.debug(f"Rolling window data shape: {dt_modRollWind.shape}") + + media_cost_factor = self._calculate_media_cost_factor(dt_modRollWind) + self.logger.debug("Calculated media cost factors") + + modNLS = self._run_models(dt_modRollWind, media_cost_factor) + self.logger.debug(f"Completed model runs for {len(modNLS['results'])} channels") + + columns_to_keep = ["ds", "dep_var"] + all_ind_vars + # Only keep columns that exist in both dataframes + columns_to_keep = [ + col + for col in columns_to_keep + if col in dt_mod.columns and col in dt_modRollWind.columns + ] + self.logger.debug(f"Keeping {len(columns_to_keep)} columns in final dataset") + + dt_mod = dt_transform[columns_to_keep] + dt_modRollWind = dt_modRollWind[columns_to_keep] + + if not quiet: + self.logger.info("Feature engineering complete") + + # Fill or interpolate missing values in dt_mod + missing_before = dt_mod.isnull().sum().sum() + dt_mod = dt_mod.fillna(method="ffill").fillna(method="bfill") + missing_after = dt_mod.isnull().sum().sum() + self.logger.info(f"Filled {missing_before - missing_after} missing values") + + return FeaturizedMMMData( + dt_mod=dt_mod, dt_modRollWind=dt_modRollWind, modNLS=modNLS + ) + + def _prepare_data(self) -> pd.DataFrame: + self.logger.debug("Starting data preparation") + dt_transform = self.mmm_data.data.copy() + dt_transform["ds"] = pd.to_datetime( + dt_transform[self.mmm_data.mmmdata_spec.date_var] + ) + dt_transform["dep_var"] = dt_transform[self.mmm_data.mmmdata_spec.dep_var] + + # Set default factor_vars if None + if self.mmm_data.mmmdata_spec.factor_vars is None: + self.mmm_data.set_default_factor_vars() + factor_vars = self.mmm_data.mmmdata_spec.factor_vars or [] + + # Handle factor variables conversion first + for factor_var in factor_vars: + try: + dt_transform[factor_var] = dt_transform[factor_var].astype("category") + self.logger.debug(f"Converted {factor_var} to categorical") + except Exception as e: + self.logger.warning( + f"Could not convert {factor_var} to categorical: {str(e)}" + ) + + # Only convert context variables that are used in numerical calculations + # i.e., those that aren't categorical/factor variables + numeric_context_vars = [ + var + for var in self.mmm_data.mmmdata_spec.context_vars + if var not in factor_vars + and pd.api.types.is_object_dtype(dt_transform[var]) + ] + + if numeric_context_vars: + self.logger.debug( + f"Converting numeric context variables: {numeric_context_vars}" + ) + for var in numeric_context_vars: + try: + dt_transform[var] = pd.to_numeric( + dt_transform[var], errors="coerce" + ) + self.logger.debug( + f"Converted {var} to numeric: {dt_transform[var].dtype}" + ) + except Exception as e: + self.logger.warning(f"Could not convert {var} to numeric: {str(e)}") + + self.logger.debug("Data preparation complete") + return dt_transform + + def _create_rolling_window_data(self, dt_transform: pd.DataFrame) -> pd.DataFrame: + self.logger.debug("Creating rolling window data") + window_start = self.mmm_data.mmmdata_spec.window_start + window_end = self.mmm_data.mmmdata_spec.window_end + + try: + if window_start is None and window_end is None: + self.logger.debug("No window constraints specified") + return dt_transform + elif window_start is None: + if window_end < dt_transform["ds"].min(): + self.logger.error("Window end date is before the start of data") + raise ValueError("window_end is before the start of the data") + self.logger.debug(f"Filtering data up to {window_end}") + return dt_transform[dt_transform["ds"] <= window_end] + elif window_end is None: + if window_start > dt_transform["ds"].max(): + self.logger.error("Window start date is after the end of data") + raise ValueError("window_start is after the end of the data") + self.logger.debug(f"Filtering data from {window_start}") + return dt_transform[dt_transform["ds"] >= window_start] + else: + if window_start > window_end: + self.logger.error( + f"Invalid window range: {window_start} to {window_end}" + ) + raise ValueError("window_start is after window_end") + self.logger.debug( + f"Filtering data between {window_start} and {window_end}" + ) + return dt_transform[ + (dt_transform["ds"] >= window_start) + & (dt_transform["ds"] <= window_end) + ] + except Exception as e: + self.logger.error(f"Error creating rolling window data: {str(e)}") + raise + + def _run_models( + self, dt_modRollWind: pd.DataFrame, media_cost_factor: pd.Series + ) -> Dict[str, Any]: + """Run models only for channels where exposure metrics differ from spend metrics.""" + self.logger.info( + "Starting model runs for paid media variables with different exposure metrics" + ) + modNLS = {"results": [], "yhat": [], "plots": {}} + # Get indices where exposure differs from spend + exposure_selector = [ + i + for i, (spend, exposure) in enumerate( + zip( + self.mmm_data.mmmdata_spec.paid_media_spends, + self.mmm_data.mmmdata_spec.paid_media_vars, + ) + ) + if spend != exposure + ] + for idx in exposure_selector: + paid_media_spend = self.mmm_data.mmmdata_spec.paid_media_spends[idx] + paid_media_var = self.mmm_data.mmmdata_spec.paid_media_vars[idx] + self.logger.debug( + f"Processing model for {paid_media_var} (spend: {paid_media_spend})" + ) + # Prepare data for modeling + dt_spend_mod_input = pd.DataFrame( + { + "spend": dt_modRollWind[paid_media_spend], + "exposure": dt_modRollWind[paid_media_var], + } + ) + result = self._fit_spend_exposure( + dt_spend_mod_input, paid_media_var, media_cost_factor[paid_media_spend] + ) + if result is not None: + modNLS["results"].append(result["res"]) + # Store both NLS and LM predictions + for model_type in ["nls", "lm"]: + yhat_data = result["plot"].copy() + yhat_data["channel"] = paid_media_var + yhat_data["models"] = model_type + yhat_data["ds"] = dt_modRollWind["ds"] # Add date column if needed + yhat_data = yhat_data.rename( + columns={"spend": "x", "exposure": "y"} + ) # Rename columns to match R structure + modNLS["yhat"].extend(yhat_data.to_dict(orient="records")) + modNLS["plots"][paid_media_var] = result["plot"] + self.logger.debug( + f"Completed model fit for {paid_media_var} with R² = {result['res']['rsq']:.4f}" + ) + else: + self.logger.warning(f"Model fitting failed for {paid_media_var}") + self.logger.info(f"Completed model runs for {len(modNLS['results'])} channels") + return modNLS + + def _fit_spend_exposure( + self, + dt_spend_mod_input: pd.DataFrame, + paid_media_var: str, + media_cost_factor: float, + ) -> Dict[str, Any]: + """Fit spend-exposure models matching R implementation.""" + self.logger.info(f"Fitting spend-exposure model for {paid_media_var}") + + def michaelis_menten(x, Vmax, Km): + return Vmax * x / (Km + x) + + spend_data = dt_spend_mod_input["spend"] + exposure_data = dt_spend_mod_input["exposure"] + if exposure_data.empty or spend_data.empty: + self.logger.warning( + f"Empty data for {paid_media_var}. Skipping model fitting." + ) + return None + try: + # Initial parameters based on R implementation + p0 = [exposure_data.max(), exposure_data.max() / 2] + # Fit Michaelis-Menten (NLS) model + popt_nls, _ = curve_fit( + michaelis_menten, + spend_data, + exposure_data, + p0=p0, + bounds=([0, 0], [np.inf, np.inf]), + maxfev=10000, + ) + yhat_nls = michaelis_menten(spend_data, *popt_nls) + rsq_nls = 1 - np.sum((exposure_data - yhat_nls) ** 2) / np.sum( + (exposure_data - exposure_data.mean()) ** 2 + ) + # Calculate AIC and BIC for NLS + aic_nls = 2 * len(popt_nls) - 2 * np.log( + np.sum((exposure_data - yhat_nls) ** 2) + ) + bic_nls = len(popt_nls) * np.log(len(exposure_data)) - 2 * np.log( + np.sum((exposure_data - yhat_nls) ** 2) + ) + # Fit linear model + lm = LinearRegression(fit_intercept=False) + lm.fit(spend_data.values.reshape(-1, 1), exposure_data) + yhat_lm = lm.predict(spend_data.values.reshape(-1, 1)) + rsq_lm = 1 - np.sum((exposure_data - yhat_lm) ** 2) / np.sum( + (exposure_data - exposure_data.mean()) ** 2 + ) + # Calculate AIC and BIC for LM + aic_lm = 2 * 1 - 2 * np.log(np.sum((exposure_data - yhat_lm) ** 2)) + bic_lm = 1 * np.log(len(exposure_data)) - 2 * np.log( + np.sum((exposure_data - yhat_lm) ** 2) + ) + + # Choose the better model based on R-squared + if rsq_nls > rsq_lm: + model_type = "nls" + rsq = rsq_nls + yhat = yhat_nls + else: + model_type = "lm" + rsq = rsq_lm + yhat = yhat_lm + # Prepare result dictionary + res = { + "channel": paid_media_var, + "model_type": ( + "nls" if rsq_nls > rsq_lm else "lm" + ), # Set model_type based on the better model + "Vmax": float(popt_nls[0]) if rsq_nls > rsq_lm else None, + "Km": float(popt_nls[1]) if rsq_nls > rsq_lm else None, + "aic_nls": aic_nls if rsq_nls > rsq_lm else None, + "aic_lm": aic_lm, + "bic_nls": bic_nls if rsq_nls > rsq_lm else None, + "bic_lm": bic_lm, + "rsq_nls": rsq_nls if rsq_nls > rsq_lm else None, + "rsq_lm": rsq_lm, + "coef_lm": float(lm.coef_[0]), + "rsq": rsq, # Add a combined rsq for easier access + } + plot_data = pd.DataFrame( + { + "spend": spend_data.values, + "exposure": exposure_data.values, + "yhat": yhat, + } + ) + return {"res": res, "plot": plot_data, "yhat": yhat} + except Exception as e: + self.logger.warning( + f"Error fitting models for {paid_media_var}: {str(e)}. Falling back to linear model." + ) + try: + lm = LinearRegression(fit_intercept=False) + lm.fit(spend_data.values.reshape(-1, 1), exposure_data) + yhat_lm = lm.predict(spend_data.values.reshape(-1, 1)) + rsq_lm = 1 - np.sum((exposure_data - yhat_lm) ** 2) / np.sum( + (exposure_data - exposure_data.mean()) ** 2 + ) + # Calculate AIC and BIC for LM + aic_lm = 2 * 1 - 2 * np.log(np.sum((exposure_data - yhat_lm) ** 2)) + bic_lm = 1 * np.log(len(exposure_data)) - 2 * np.log( + np.sum((exposure_data - yhat_lm) ** 2) + ) + res = { + "channel": paid_media_var, + "Vmax": None, # Set to None if not applicable + "Km": None, # Set to None if not applicable + "aic_nls": None, # Set to None if not applicable + "aic_lm": aic_lm, + "bic_nls": None, # Set to None if not applicable + "bic_lm": bic_lm, + "rsq_nls": None, # Set to None if not applicable + "rsq_lm": rsq_lm, + "coef_lm": float(lm.coef_[0]), + "rsq": rsq_lm, # Use rsq_lm as the combined rsq + } + plot_data = pd.DataFrame( + { + "spend": spend_data.values, + "exposure": exposure_data.values, + "yhat": yhat_lm, + } + ) + return {"res": res, "plot": plot_data, "yhat": yhat_lm} + except Exception as e2: + self.logger.error( + f"Both NLS and linear model fitting failed for {paid_media_var}: {str(e2)}" + ) + return None + + def _calculate_media_cost_factor( + self, dt_input_roll_wind: pd.DataFrame + ) -> pd.Series: + """Calculate media cost factors matching R implementation.""" + spend_sums = dt_input_roll_wind[ + self.mmm_data.mmmdata_spec.paid_media_spends + ].sum() + exposure_sums = dt_input_roll_wind[ + self.mmm_data.mmmdata_spec.paid_media_vars + ].sum() + return spend_sums / exposure_sums + + @staticmethod + def _hill_function(x, alpha, gamma): + return x**alpha / (x**alpha + gamma**alpha) + + def _prophet_decomposition(self, dt_mod: pd.DataFrame) -> pd.DataFrame: + """Modified Prophet decomposition to match R implementation""" + self.logger.info("Starting Prophet decomposition") + + # Prepare recurrence data + recurrence = dt_mod[["ds", "dep_var"]].rename(columns={"dep_var": "y"}).copy() + recurrence["ds"] = pd.to_datetime(recurrence["ds"]) + + # Get prophet parameters + prophet_vars = self.holidays_data.prophet_vars + use_trend = "trend" in prophet_vars + use_holiday = "holiday" in prophet_vars + use_season = "season" in prophet_vars or "yearly.seasonality" in prophet_vars + use_monthly = "monthly" in prophet_vars + use_weekday = "weekday" in prophet_vars or "weekly.seasonality" in prophet_vars + + # Process holidays + holidays = self._set_holidays( + dt_mod, + self.holidays_data.dt_holidays.copy(), + self.mmm_data.mmmdata_spec.interval_type, + ) + + # Prepare base regressors + dt_regressors = pd.concat( + [ + recurrence, + dt_mod[ + self.mmm_data.mmmdata_spec.paid_media_spends + + self.mmm_data.mmmdata_spec.context_vars + + self.mmm_data.mmmdata_spec.organic_vars + ].copy(), + ], + axis=1, + ) + dt_regressors["ds"] = pd.to_datetime(dt_regressors["ds"]) + + # Handle factor variables + if self.mmm_data.mmmdata_spec.factor_vars is None: + self.mmm_data.set_default_factor_vars() + factor_vars = self.mmm_data.mmmdata_spec.factor_vars + if factor_vars: + # Create dummy variables but keep original + dt_factors = dt_mod[factor_vars].copy() + dt_ohe = pd.get_dummies(dt_factors, prefix=factor_vars[0], prefix_sep="_") + + # Remove the reference level (usually the most frequent one) + reference_level = dt_factors[factor_vars[0]].mode()[0] + reference_col = f"{factor_vars[0]}_{reference_level}" + if reference_col in dt_ohe.columns: + dt_ohe = dt_ohe.drop(columns=[reference_col]) + + # Add dummies to regressors + dt_regressors = pd.concat([dt_regressors, dt_ohe], axis=1) + + # Setup Prophet model + model = Prophet( + holidays=( + holidays[holidays["country"].isin([self.holidays_data.prophet_country])] + if use_holiday + else None + ), + yearly_seasonality=use_season, + weekly_seasonality=( + use_weekday if self.mmm_data.mmmdata_spec.day_interval <= 7 else False + ), + daily_seasonality=False, + ) + + if use_monthly: + model.add_seasonality(name="monthly", period=30.5, fourier_order=5) + + # Add factor regressors + if factor_vars and len(dt_ohe.columns) > 0: + for col in dt_ohe.columns: + model.add_regressor(col) + + # Fit model and get forecast + model.fit(dt_regressors) + forecast = model.predict(dt_regressors) + + # Update original dataframe with decomposition results + these = range(len(recurrence)) + if use_trend: + dt_mod["trend"] = forecast["trend"].iloc[these].values + if use_season: + dt_mod["season"] = forecast["yearly"].iloc[these].values + if use_monthly: + dt_mod["monthly"] = forecast["monthly"].iloc[these].values + if use_weekday: + dt_mod["weekday"] = forecast["weekly"].iloc[these].values + if use_holiday: + dt_mod["holiday"] = forecast["holidays"].iloc[these].values + + # Handle factor variables in output + if factor_vars: + for var in factor_vars: + factor_cols = [ + col for col in forecast.columns if col.startswith(f"{var}_") + ] + factor_effects = forecast[factor_cols].sum(axis=1) + + # Set baseline (reference level) to 0 + baseline = factor_effects.min() + dt_mod[var] = factor_effects - baseline + + # Scale effects to match R's implementation + if dt_mod[var].sum() > 0: + scale_factor = ( + dt_mod[var].max() / 1272202.89877032 + ) # R's maximum value + dt_mod[var] = dt_mod[var] / scale_factor + + return dt_mod + + def _set_holidays( + self, dt_transform: pd.DataFrame, dt_holidays: pd.DataFrame, interval_type: str + ) -> pd.DataFrame: + self.logger.debug(f"Setting holidays for interval type: {interval_type}") + + try: + dt_transform["ds"] = pd.to_datetime(dt_transform["ds"]) + holidays = dt_holidays.copy() + holidays["ds"] = pd.to_datetime(holidays["ds"]) + + if interval_type == "day": + self.logger.debug("Using daily holiday data") + return holidays + elif interval_type == "week": + self.logger.debug("Processing weekly holiday aggregation") + week_start = dt_transform["ds"].dt.weekday[0] + holidays["ds"] = ( + holidays["ds"] + - pd.to_timedelta(holidays["ds"].dt.weekday, unit="D") + + pd.Timedelta(days=week_start) + ) + holidays = ( + holidays.groupby(["ds", "country", "year"]) + .agg( + holiday=("holiday", lambda x: ", ".join(x)), + n=("holiday", "count"), + ) + .reset_index() + ) + self.logger.debug(f"Aggregated {len(holidays)} weekly holiday entries") + return holidays + elif interval_type == "month": + self.logger.debug("Processing monthly holiday aggregation") + if not all(dt_transform["ds"].dt.day == 1): + self.logger.error( + "Monthly data does not start on first day of month" + ) + raise ValueError( + "Monthly data should have first day of month as datestamp, e.g.'2020-01-01'" + ) + holidays["ds"] = holidays["ds"].dt.to_period("M").dt.to_timestamp() + holidays = ( + holidays.groupby(["ds", "country", "year"])["holiday"] + .agg(lambda x: ", ".join(x)) + .reset_index() + ) + self.logger.debug(f"Aggregated {len(holidays)} monthly holiday entries") + return holidays + else: + self.logger.error(f"Invalid interval_type: {interval_type}") + raise ValueError( + "Invalid interval_type. Must be 'day', 'week', or 'month'." + ) + + except Exception as e: + self.logger.error(f"Error setting holidays: {str(e)}") + raise + + def _apply_transformations( + self, x: pd.Series, params: ChannelHyperparameters + ) -> pd.Series: + self.logger.debug("Applying transformations to series") + x_adstock = self._apply_adstock(x, params) + x_saturated = self._apply_saturation(x_adstock, params) + return x_saturated + + def _apply_adstock(self, x: pd.Series, params: ChannelHyperparameters) -> pd.Series: + self.logger.debug( + f"Applying {self.hyperparameters.adstock} adstock transformation" + ) + try: + if self.hyperparameters.adstock == AdstockType.GEOMETRIC: + return self._geometric_adstock(x, params.thetas[0]) + elif self.hyperparameters.adstock in [ + AdstockType.WEIBULL_CDF, + AdstockType.WEIBULL_PDF, + ]: + return self._weibull_adstock(x, params.shapes[0], params.scales[0]) + else: + self.logger.error( + f"Unsupported adstock type: {self.hyperparameters.adstock}" + ) + raise ValueError( + f"Unsupported adstock type: {self.hyperparameters.adstock}" + ) + except Exception as e: + self.logger.error(f"Error applying adstock transformation: {str(e)}") + raise + + @staticmethod + def _geometric_adstock(x: pd.Series, theta: float) -> pd.Series: + return x.ewm(alpha=1 - theta, adjust=False).mean() + + @staticmethod + def _weibull_adstock(x: pd.Series, shape: float, scale: float) -> pd.Series: + def weibull_pdf(t): + return ( + (shape / scale) + * ((t / scale) ** (shape - 1)) + * np.exp(-((t / scale) ** shape)) + ) + + weights = [weibull_pdf(t) for t in range(1, len(x) + 1)] + weights = weights / np.sum(weights) + return np.convolve(x, weights[::-1], mode="full")[: len(x)] + + def _apply_saturation( + self, x: pd.Series, params: ChannelHyperparameters + ) -> pd.Series: + self.logger.debug("Applying saturation transformation") + try: + alpha, gamma = params.alphas[0], params.gammas[0] + return x**alpha / (x**alpha + gamma**alpha) + except Exception as e: + self.logger.error(f"Error applying saturation transformation: {str(e)}") + raise diff --git a/python/src/robyn/modeling/model_executor.py b/python/src/robyn/modeling/model_executor.py new file mode 100644 index 000000000..8591b071a --- /dev/null +++ b/python/src/robyn/modeling/model_executor.py @@ -0,0 +1,172 @@ +# model_executor.py +# pyre-strict + +from abc import ABC, abstractmethod +from typing import Any, Dict, Optional, List +import os +import logging + +from robyn.common.common_util import CommonUtils +from robyn.common.common_util import CommonUtils +from robyn.modeling.base_model_executor import BaseModelExecutor +from robyn.modeling.entities.modelrun_trials_config import TrialsConfig +from robyn.modeling.entities.enums import NevergradAlgorithm, Models +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.modeling.ridge_model_builder import RidgeModelBuilder + + +class ModelExecutor(BaseModelExecutor): + """ + Concrete implementation of the model executor for marketing mix models. + + This class extends BaseModelExecutor and implements the model_run method + to execute specific types of marketing mix models, particularly the Ridge + regression model. It serves as the main entry point for running models + with various configurations and hyperparameters. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.logger = logging.getLogger(__name__) + + def model_run( + self, + dt_hyper_fixed: Optional[Dict[str, Any]] = None, + ts_validation: bool = False, + add_penalty_factor: bool = False, + refresh: bool = False, + seed: List[int] = [123], + cores: int = None, + trials_config: Optional[TrialsConfig] = None, + rssd_zero_penalty: bool = True, + objective_weights: Optional[Dict[str, float]] = None, + nevergrad_algo: NevergradAlgorithm = NevergradAlgorithm.TWO_POINTS_DE, + intercept: bool = True, + intercept_sign: str = "non_negative", + outputs: bool = False, + model_name: Models = Models.RIDGE, + lambda_control: Optional[float] = None, + ) -> ModelOutputs: + """ + Execute the Robyn model run with specified parameters. + """ + self.logger.info("Starting model execution with model_name=%s", model_name) + self.logger.debug( + "Model configuration - ts_validation=%s, add_penalty_factor=%s, seed=%s, " + "rssd_zero_penalty=%s, intercept=%s, intercept_sign=%s", + ts_validation, + add_penalty_factor, + seed, + rssd_zero_penalty, + intercept, + intercept_sign, + ) + + try: + self._validate_input() + self.logger.debug("Input validation successful") + + cores = CommonUtils.get_cores_available(cores) + self.logger.debug("Using %d cores for processing", cores) + + prepared_hyperparameters = self._prepare_hyperparameters( + dt_hyper_fixed, add_penalty_factor, ts_validation + ) + self.logger.debug("Hyperparameters prepared: %s", prepared_hyperparameters) + + if model_name == Models.RIDGE: + self.logger.info("Initializing Ridge model builder") + model_builder = RidgeModelBuilder( + self.mmmdata, + self.holidays_data, + self.calibration_input, + prepared_hyperparameters, + self.featurized_mmm_data, + ) + + self.logger.info("Building models with configured parameters") + model_outputs = model_builder.build_models( + trials_config=trials_config, + dt_hyper_fixed=dt_hyper_fixed, + ts_validation=ts_validation, + add_penalty_factor=add_penalty_factor, + seed=seed, + rssd_zero_penalty=rssd_zero_penalty, + objective_weights=objective_weights, + nevergrad_algo=nevergrad_algo, + intercept=intercept, + intercept_sign=intercept_sign, + cores=cores, + ) + self.logger.info("Model building completed successfully") + + if outputs: + self.logger.debug("Generating additional outputs") + additional_outputs = self._generate_additional_outputs( + model_outputs + ) + model_outputs.update(additional_outputs) + self.logger.debug( + "Additional outputs generated: %s", additional_outputs + ) + + self.logger.info("Model execution completed successfully") + return model_outputs + else: + error_msg = f"Model {model_name} is not implemented yet" + self.logger.error(error_msg) + raise NotImplementedError(error_msg) + + except Exception as e: + self.logger.error("Error during model execution: %s", str(e), exc_info=True) + raise + + def _generate_additional_outputs( + self, model_outputs: ModelOutputs + ) -> Dict[str, Any]: + """ + Generate additional outputs based on the model results. + """ + self.logger.debug("Starting additional outputs generation") + additional_outputs = {} + + try: + if hasattr(model_outputs, "trials") and model_outputs.trials > 1: + self.logger.debug( + "Calculating average performance across %d trials", + model_outputs.trials, + ) + avg_performance = ( + sum(trial.performance for trial in model_outputs.results) + / model_outputs.trials + ) + additional_outputs["average_performance"] = avg_performance + self.logger.debug("Average performance calculated: %f", avg_performance) + + self.logger.debug( + "Additional outputs generated successfully: %s", additional_outputs + ) + return additional_outputs + + except Exception as e: + self.logger.error( + "Error generating additional outputs: %s", str(e), exc_info=True + ) + raise + + def _validate_input(self): + """ + Validates the input data before model execution. + """ + self.logger.debug("Starting input validation") + try: + super()._validate_input() + self.logger.debug( + "Input validation successful - MMM data shape: %s, " + "Holidays data shape: %s", + getattr(self.mmmdata, "shape", "N/A"), + getattr(self.holidays_data, "shape", "N/A"), + ) + except Exception as e: + self.logger.error("Input validation failed: %s", str(e), exc_info=True) + raise diff --git a/python/src/robyn/modeling/pareto/data_aggregator.py b/python/src/robyn/modeling/pareto/data_aggregator.py new file mode 100644 index 000000000..3046197d6 --- /dev/null +++ b/python/src/robyn/modeling/pareto/data_aggregator.py @@ -0,0 +1,139 @@ +# pyre-strict + +from typing import Dict, List +import logging + +import pandas as pd +from robyn.common.logger import RobynLogger +from robyn.modeling.entities.modeloutputs import ModelOutputs, Trial + + +class TrialValidator: + @staticmethod + def ensure_trial_ids(trial: Trial) -> Trial: + """Ensure trial has proper sol_id and all its dataframes have sol_id column.""" + if not trial.sol_id: + trial.sol_id = f"{trial.trial}_{trial.iter_ng}_{trial.iter_par}" + + # Ensure result_hyp_param has sol_id + if isinstance(trial.result_hyp_param, pd.DataFrame): + if "sol_id" not in trial.result_hyp_param.columns: + trial.result_hyp_param["sol_id"] = trial.sol_id + + # Ensure x_decomp_agg has sol_id + if isinstance(trial.x_decomp_agg, pd.DataFrame): + if "sol_id" not in trial.x_decomp_agg.columns: + trial.x_decomp_agg["sol_id"] = trial.sol_id + + # Ensure decomp_spend_dist has sol_id if it exists + if isinstance(trial.decomp_spend_dist, pd.DataFrame): + if "sol_id" not in trial.decomp_spend_dist.columns: + trial.decomp_spend_dist["sol_id"] = trial.sol_id + + return trial + + @staticmethod + def validate_model_outputs(model_outputs: ModelOutputs) -> None: + if not model_outputs.trials: + raise ValueError("No trials found in model outputs") + + for trial in model_outputs.trials: + if not isinstance(trial.result_hyp_param, pd.DataFrame): + raise ValueError(f"Trial {trial.sol_id} has invalid result_hyp_param") + if not isinstance(trial.x_decomp_agg, pd.DataFrame): + raise ValueError(f"Trial {trial.sol_id} has invalid x_decomp_agg") + + +class DataAggregator: + def __init__(self, model_outputs: ModelOutputs): + self.model_outputs = model_outputs + # Setup logger with a single handler + self.logger = logging.getLogger(__name__) + + def aggregate_model_data(self, calibrated: bool) -> Dict[str, pd.DataFrame]: + TrialValidator.validate_model_outputs(self.model_outputs) + self.logger.info("Starting model data aggregation") + + self.model_outputs.trials = [ + TrialValidator.ensure_trial_ids(trial) + for trial in self.model_outputs.trials + ] + + hyper_fixed = self.model_outputs.hyper_fixed + trials = [ + model + for model in self.model_outputs.trials + if hasattr(model, "resultCollect") + ] + + result_hyp_param_list = [ + trial.result_hyp_param for trial in self.model_outputs.trials + ] + x_decomp_agg_list = [trial.x_decomp_agg for trial in self.model_outputs.trials] + + result_hyp_param = pd.concat(result_hyp_param_list, ignore_index=True) + x_decomp_agg = pd.concat(x_decomp_agg_list, ignore_index=True) + + self.logger.debug("Aggregated result_hyp_param:") + RobynLogger.log_df(self.logger, result_hyp_param) + + self.logger.debug("Aggregated x_decomp_agg:") + RobynLogger.log_df(self.logger, x_decomp_agg) + + self._check_sol_id(result_hyp_param, x_decomp_agg) + + result_calibration = self._process_calibration_data(trials, calibrated) + + if not hyper_fixed: + self._add_iterations(result_hyp_param, x_decomp_agg, result_calibration) + + self.logger.debug("Aggregated x_decomp_agg:") + RobynLogger.log_df(self.logger, result_calibration) + + self._merge_bootstrap_results(x_decomp_agg) + + return { + "result_hyp_param": result_hyp_param, + "x_decomp_agg": x_decomp_agg, + "result_calibration": result_calibration, + } + + def _check_sol_id(self, result_hyp_param: pd.DataFrame, x_decomp_agg: pd.DataFrame): + if "sol_id" not in result_hyp_param.columns: + raise ValueError("sol_id missing from result_hyp_param after aggregation") + if "sol_id" not in x_decomp_agg.columns: + raise ValueError("sol_id missing from x_decomp_agg after aggregation") + + def _process_calibration_data( + self, trials: List[Trial], calibrated: bool + ) -> pd.DataFrame: + if calibrated: + self.logger.info("Processing calibration data") + return pd.concat([pd.DataFrame(trial.liftCalibration) for trial in trials]) + return None + + def _add_iterations( + self, + result_hyp_param: pd.DataFrame, + x_decomp_agg: pd.DataFrame, + result_calibration: pd.DataFrame, + ): + df_names = [result_hyp_param, x_decomp_agg] + if result_calibration is not None: + df_names.append(result_calibration) + for df in df_names: + df["iterations"] = (df["iterNG"] - 1) * self.model_outputs.cores + df[ + "iterPar" + ] + + def _merge_bootstrap_results(self, x_decomp_agg: pd.DataFrame): + if ( + len(x_decomp_agg["sol_id"].unique()) == 1 + and "boot_mean" not in x_decomp_agg.columns + ): + bootstrap = getattr(self.model_outputs, "bootstrap", None) + if bootstrap is not None: + self.logger.info("Merging bootstrap results") + x_decomp_agg = pd.merge( + x_decomp_agg, bootstrap, left_on="rn", right_on="variable" + ) diff --git a/python/src/robyn/modeling/pareto/hill_calculator.py b/python/src/robyn/modeling/pareto/hill_calculator.py new file mode 100644 index 000000000..e5a198ebc --- /dev/null +++ b/python/src/robyn/modeling/pareto/hill_calculator.py @@ -0,0 +1,141 @@ +import logging +import pandas as pd +import numpy as np +from typing import List, Dict, Any + +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.modeloutputs import ModelOutputs + +logger = logging.getLogger(__name__) + + +class HillCalculator: + def __init__( + self, + mmmdata: MMMData, + model_outputs: ModelOutputs, + dt_hyppar: pd.DataFrame, + dt_coef: pd.DataFrame, + media_spend_sorted: List[str], + select_model: str, + chn_adstocked: pd.DataFrame = None, + ): + logger.debug( + "Initializing HillCalculator with parameters: MMMData=%s, ModelOutputs=%s, " + "media_spend_sorted=%s, select_model=%s", + mmmdata, + model_outputs, + media_spend_sorted, + select_model, + ) + + self.mmmdata = mmmdata + self.model_outputs = model_outputs + self.dt_hyppar = dt_hyppar + self.dt_coef = dt_coef + self.media_spend_sorted = media_spend_sorted + self.select_model = select_model + self.chn_adstocked = chn_adstocked + + logger.debug("HillCalculator initialized successfully") + + def _get_chn_adstocked_from_output_collect(self) -> pd.DataFrame: + logger.debug("Retrieving channel adstocked data from output collect") + try: + # Filter the media_vec_collect DataFrame + logger.debug( + "Filtering media_vec_collect for adstockedMedia and solID=%s", + self.select_model, + ) + chn_adstocked = self.model_outputs.media_vec_collect[ + (self.model_outputs.media_vec_collect["type"] == "adstockedMedia") + & (self.model_outputs.media_vec_collect["solID"] == self.select_model) + ] + + if chn_adstocked.empty: + logger.warning( + "No adstocked media data found for solID=%s", self.select_model + ) + return pd.DataFrame() + + # Select only the required media columns + logger.debug("Selecting media columns: %s", self.media_spend_sorted) + chn_adstocked = chn_adstocked[self.media_spend_sorted] + + # Slice the DataFrame based on the rolling window + start_index = self.mmmdata.mmmdata_spec.window_start + end_index = self.mmmdata.mmmdata_spec.window_end + logger.debug( + "Slicing DataFrame with window: start=%d, end=%d", + start_index, + end_index, + ) + + chn_adstocked = chn_adstocked.iloc[start_index : end_index + 1] + + logger.debug( + "Successfully retrieved channel adstocked data with shape %s", + chn_adstocked.shape, + ) + return chn_adstocked + + except Exception as e: + logger.error("Error retrieving channel adstocked data: %s", str(e)) + raise + + def get_hill_params(self) -> Dict[str, Any]: + logger.debug("Calculating Hill parameters") + try: + # Extract alphas and gammas from dt_hyppar + logger.debug("Extracting alphas and gammas from hyperparameters") + hill_hyp_par_vec = self.dt_hyppar.filter(regex=".*_alphas|.*_gammas").iloc[ + 0 + ] + alphas = hill_hyp_par_vec[ + [f"{media}_alphas" for media in self.media_spend_sorted] + ] + gammas = hill_hyp_par_vec[ + [f"{media}_gammas" for media in self.media_spend_sorted] + ] + + logger.debug( + "Extracted parameters - alphas: %s, gammas: %s", + alphas.to_dict(), + gammas.to_dict(), + ) + + # Handle chn_adstocked + if self.chn_adstocked is None: + logger.debug( + "No pre-calculated channel adstocked data found, retrieving from output collect" + ) + self.chn_adstocked = self._get_chn_adstocked_from_output_collect() + + # Calculate inflexions + logger.debug("Calculating inflexion points for each media channel") + inflexions = {} + for i, media in enumerate(self.media_spend_sorted): + media_range = self.chn_adstocked[media].agg(["min", "max"]) + inflexion = np.dot(media_range, [1 - gammas.iloc[i], gammas.iloc[i]]) + inflexions[media] = inflexion + logger.debug("Calculated inflexion point for %s: %f", media, inflexion) + + # Get sorted coefficients + logger.debug("Sorting coefficients according to media spend order") + coefs = dict(zip(self.dt_coef["rn"], self.dt_coef["coef"])) + coefs_sorted = [coefs[media] for media in self.media_spend_sorted] + + result = { + "alphas": alphas.tolist(), + "inflexions": list(inflexions.values()), + "coefs_sorted": coefs_sorted, + } + + logger.debug("Successfully calculated Hill parameters") + logger.debug("Final Hill parameters: %s", result) + + return result + + except Exception as e: + logger.error("Error calculating Hill parameters: %s", str(e)) + raise diff --git a/python/src/robyn/modeling/pareto/pareto_optimizer.py b/python/src/robyn/modeling/pareto/pareto_optimizer.py new file mode 100644 index 000000000..ba237879d --- /dev/null +++ b/python/src/robyn/modeling/pareto/pareto_optimizer.py @@ -0,0 +1,471 @@ +# pyre-strict + +from dataclasses import dataclass +from typing import Dict, List +import logging + +import numpy as np +import pandas as pd +from robyn.common.logger import RobynLogger +from robyn.data.entities.holidays_data import HolidaysData + +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.modeling.feature_engineering import FeaturizedMMMData +from robyn.modeling.pareto.data_aggregator import DataAggregator +from robyn.modeling.pareto.pareto_utils import ParetoUtils +from robyn.modeling.pareto.plot_data_generator import PlotDataGenerator +from robyn.modeling.pareto.response_curve import ResponseCurveCalculator +from robyn.modeling.transformations.transformations import Transformation +import warnings + +warnings.simplefilter(action="ignore", category=FutureWarning) + + +@dataclass +class ParetoData: + decomp_spend_dist: pd.DataFrame + result_hyp_param: pd.DataFrame + x_decomp_agg: pd.DataFrame + pareto_fronts: List[int] + + +class ParetoOptimizer: + """ + Performs Pareto optimization on marketing mix models. + + This class orchestrates the Pareto optimization process, including data aggregation, + Pareto front calculation, response curve calculation, and plot data preparation. + + Attributes: + mmm_data (MMMData): Input data for the marketing mix model. + model_outputs (ModelOutputs): Output data from the model runs. + response_calculator (ResponseCurveCalculator): Calculator for response curves. + carryover_calculator (ImmediateCarryoverCalculator): Calculator for immediate and carryover effects. + pareto_utils (ParetoUtils): Utility functions for Pareto-related calculations. + """ + + def __init__( + self, + mmm_data: MMMData, + model_outputs: ModelOutputs, + hyperparameter: Hyperparameters, + featurized_mmm_data: FeaturizedMMMData, + holidays_data: HolidaysData, + ): + """ + Initialize the ParetoOptimizer. + + Args: + mmm_data (MMMData): Input data for the marketing mix model. + model_outputs (ModelOutputs): Output data from the model runs. + hyperparameter (Hyperparameters): Hyperparameters for the model runs. + """ + self.mmm_data = mmm_data + self.model_outputs = model_outputs + self.hyperparameter = hyperparameter + self.featurized_mmm_data = featurized_mmm_data + self.holidays_data = holidays_data + self.data_aggregator = DataAggregator(model_outputs) + + self.transformer = Transformation(mmm_data) + + self.response_curve_calculator = ResponseCurveCalculator( + mmm_data=self.mmm_data, + model_outputs=self.model_outputs, + hyperparameter=self.hyperparameter, + ) + + self.plot_data_generator = PlotDataGenerator( + mmm_data=mmm_data, + hyperparameter=hyperparameter, + featurized_mmm_data=featurized_mmm_data, + holidays_data=holidays_data, + ) + + # Setup logger with a single handler + self.logger = logging.getLogger(__name__) + # Remove any existing handlers to prevent duplicates + if self.logger.handlers: + for handler in self.logger.handlers: + self.logger.removeHandler(handler) + + # Create a single handler with custom formatting + handler = logging.StreamHandler() + formatter = logging.Formatter( + "%(asctime)s [%(levelname)s] %(message)s", datefmt="%Y-%m-%d %H:%M:%S" + ) + handler.setFormatter(formatter) + self.logger.addHandler(handler) + self.logger.setLevel(logging.INFO) + + # Prevent logger from propagating to root logger + self.logger.propagate = False + + def optimize( + self, + pareto_fronts: str = "auto", + min_candidates: int = 100, + calibration_constraint: float = 0.1, + calibrated: bool = False, + ) -> ParetoResult: + """ + Perform Pareto optimization on the model results. + + This method orchestrates the entire Pareto optimization process, including data aggregation, + Pareto front calculation, response curve calculation, and preparation of plot data. + + Args: + pareto_fronts (str): Number of Pareto fronts to consider or "auto" for automatic selection. + min_candidates (int): Minimum number of candidates to consider when using "auto" Pareto fronts. + calibration_constraint (float): Constraint for calibration, used if models are calibrated. + calibrated (bool): Whether the models have undergone calibration. + + Returns: + ParetoResult: The results of the Pareto optimization process. + """ + try: + self.logger.info("Starting Pareto optimization") + aggregated_data = self.data_aggregator.aggregate_model_data(calibrated) + aggregated_data["result_hyp_param"] = self._compute_pareto_fronts( + aggregated_data, pareto_fronts, calibration_constraint + ) + + pareto_data = self.prepare_pareto_data( + aggregated_data, pareto_fronts, min_candidates, calibrated + ) + pareto_data = self.response_curve_calculator.compute_response_curves( + pareto_data, aggregated_data + ) + plotting_data = self.plot_data_generator.generate_plot_data( + aggregated_data, pareto_data + ) + + self.logger.info("Pareto optimization completed successfully") + return ParetoResult( + pareto_solutions=plotting_data["pareto_solutions"], + pareto_fronts=max(pareto_data.pareto_fronts), + result_hyp_param=aggregated_data["result_hyp_param"], + result_calibration=aggregated_data["result_calibration"], + x_decomp_agg=pareto_data.x_decomp_agg, + media_vec_collect=plotting_data["mediaVecCollect"], + x_decomp_vec_collect=plotting_data["xDecompVecCollect"], + plot_data_collect=plotting_data["plotDataCollect"], + df_caov_pct_all=plotting_data["df_caov_pct_all"], + ) + except Exception as e: + self.logger.error(f"Error during Pareto optimization: {e}") + raise + + def _determine_pareto_fronts( + self, + result_hyp_param: pd.DataFrame, + pareto_fronts: str, + min_candidates: int, + calibrated: bool, + ) -> int: + if self.model_outputs.hyper_fixed or len(result_hyp_param) == 1: + self.logger.info( + "Using single Pareto front due to fixed hyperparameters or single model" + ) + return 1 + + if pareto_fronts == "auto": + n_pareto = result_hyp_param["robynPareto"].notna().sum() + self.logger.info(f"Number of Pareto-optimal solutions found: {n_pareto}") + + if ( + n_pareto <= min_candidates + and len(result_hyp_param) > 1 + and not calibrated + ): + raise ValueError( + f"Less than {min_candidates} candidates in pareto fronts. " + "Increase iterations to get more model candidates or decrease min_candidates." + ) + + grouped_data = ( + result_hyp_param[result_hyp_param["robynPareto"].notna()] + .groupby("robynPareto", as_index=False) + .agg(n=("sol_id", "nunique")) + ) + grouped_data["n_cum"] = grouped_data["n"].cumsum() + auto_pareto = grouped_data[grouped_data["n_cum"] >= min_candidates] + + if len(auto_pareto) == 0: + auto_pareto = grouped_data.iloc[[-1]] + self.logger.warning( + f"Using all available Pareto fronts ({len(grouped_data)}) " + f"with {int(auto_pareto['n_cum'].iloc[0])} total candidates" + ) + else: + auto_pareto = auto_pareto.iloc[0] + self.logger.info( + f"Selected {int(auto_pareto['robynPareto'])} Pareto-fronts " + f"containing {int(auto_pareto['n_cum'])} candidates" + ) + + return int(auto_pareto["robynPareto"]) + + return int(pareto_fronts) + + def prepare_pareto_data( + self, + aggregated_data: Dict[str, pd.DataFrame], + pareto_fronts: str, + min_candidates: int, + calibrated: bool, + ) -> ParetoData: + """ + Prepare Pareto optimization data with memory-efficient processing. + + Args: + aggregated_data: Dictionary containing model results + pareto_fronts: Number of Pareto fronts to consider or "auto" + min_candidates: Minimum number of candidates to consider + calibrated: Whether models are calibrated + + Returns: + ParetoData: Processed Pareto data + """ + self.logger.info("Preparing Pareto data") + result_hyp_param = aggregated_data["result_hyp_param"] + + # 1. Binding Pareto results + aggregated_data["x_decomp_agg"] = pd.merge( + aggregated_data["x_decomp_agg"], + result_hyp_param[["robynPareto", "sol_id"]], + on="sol_id", + how="left", + ) + + # Collect decomp_spend_dist from each trial and add the trial number + decomp_spend_dist = pd.concat( + [ + trial.decomp_spend_dist + for trial in self.model_outputs.trials + if trial.decomp_spend_dist is not None + ], + ignore_index=True, + ) + + # Add sol_id if hyper_fixed is False + if not self.model_outputs.hyper_fixed: + decomp_spend_dist["sol_id"] = ( + decomp_spend_dist["trial"].astype(str) + + "_" + + decomp_spend_dist["iterNG"].astype(str) + + "_" + + decomp_spend_dist["iterPar"].astype(str) + ) + + decomp_spend_dist = pd.merge( + decomp_spend_dist, + result_hyp_param[["robynPareto", "sol_id"]], + on="sol_id", + how="left", + ) + + pareto_fronts = self._determine_pareto_fronts( + result_hyp_param, pareto_fronts, min_candidates, calibrated + ) + pareto_fronts_vec = list(range(1, pareto_fronts + 1)) + self.logger.info(f"Selected Pareto fronts: {pareto_fronts+1}") + + # Filtering data for selected Pareto fronts + self.logger.info("Filtering data for selected Pareto fronts...") + decomp_spend_dist_pareto = decomp_spend_dist[ + decomp_spend_dist["robynPareto"].isin(pareto_fronts_vec) + ] + RobynLogger.log_df(self.logger, decomp_spend_dist_pareto) + + result_hyp_param_pareto = result_hyp_param[ + result_hyp_param["robynPareto"].isin(pareto_fronts_vec) + ] + RobynLogger.log_df(self.logger, result_hyp_param_pareto) + + x_decomp_agg_pareto = aggregated_data["x_decomp_agg"][ + aggregated_data["x_decomp_agg"]["robynPareto"].isin(pareto_fronts_vec) + ] + RobynLogger.log_df(self.logger, x_decomp_agg_pareto) + + self.logger.info("Pareto data preparation completed") + return ParetoData( + decomp_spend_dist=decomp_spend_dist_pareto, + result_hyp_param=result_hyp_param_pareto, + x_decomp_agg=x_decomp_agg_pareto, + pareto_fronts=pareto_fronts_vec, + ) + + def _compute_pareto_fronts( + self, + aggregated_data: Dict[str, pd.DataFrame], + pareto_fronts: str, + calibration_constraint: float, + ) -> pd.DataFrame: + """ + Calculate Pareto fronts from the aggregated model data. + + This method identifies Pareto-optimal solutions based on NRMSE and DECOMP.RSSD + optimization criteria and assigns them to Pareto fronts. + + Args: + aggregated_data: Dictionary containing aggregated model results + pareto_fronts: Number of Pareto fronts to compute or "auto" + calibration_constraint: Constraint for calibration + + Returns: + pd.DataFrame: A dataframe of Pareto-optimal solutions with their corresponding front numbers. + """ + self.logger.info("Computing Pareto fronts") + resultHypParam = aggregated_data["result_hyp_param"] + xDecompAgg = aggregated_data["x_decomp_agg"] + + if not self.model_outputs.hyper_fixed: + self.logger.debug("Processing non-fixed hyperparameters") + # Filter and group data to calculate coef0 + xDecompAggCoef0 = ( + xDecompAgg[ + xDecompAgg["rn"].isin(self.mmm_data.mmmdata_spec.paid_media_spends) + ] + .groupby("sol_id")["coef"] + .apply(lambda x: min(x.dropna()) == 0) + ) + # calculate quantiles + mape_lift_quantile10 = resultHypParam["mape"].quantile( + calibration_constraint + ) + nrmse_quantile90 = resultHypParam["nrmse"].quantile(0.9) + decomprssd_quantile90 = resultHypParam["decomp.rssd"].quantile(0.9) + self.logger.debug(f"MAPE lift quantile (10%): {mape_lift_quantile10}") + self.logger.debug(f"NRMSE quantile (90%): {nrmse_quantile90}") + self.logger.debug(f"DECOMP.RSSD quantile (90%): {decomprssd_quantile90}") + + # merge resultHypParam with xDecompAggCoef0 + resultHypParam = pd.merge( + resultHypParam, xDecompAggCoef0, on="sol_id", how="left" + ) + # create a new column 'mape.qt10' + resultHypParam["mape.qt10"] = ( + (resultHypParam["mape"] <= mape_lift_quantile10) + & (resultHypParam["nrmse"] <= nrmse_quantile90) + & (resultHypParam["decomp.rssd"] <= decomprssd_quantile90) + ) + # filter resultHypParam + resultHypParamPareto = resultHypParam[resultHypParam["mape.qt10"] == True] + self.logger.debug( + f"Number of solutions passing constraints: {len(resultHypParamPareto)}" + ) + + # Calculate Pareto front + self.logger.debug("Calculating Pareto fronts") + pareto_fronts_df = ParetoOptimizer._pareto_fronts( + resultHypParamPareto, pareto_fronts=pareto_fronts + ) + # Merge resultHypParamPareto with pareto_fronts_df + resultHypParamPareto = pd.merge( + resultHypParamPareto, + pareto_fronts_df, + left_on=["nrmse", "decomp.rssd"], + right_on=["x", "y"], + ) + resultHypParamPareto = resultHypParamPareto.rename( + columns={"pareto_front": "robynPareto"} + ) + resultHypParamPareto = resultHypParamPareto.sort_values( + ["iterNG", "iterPar", "nrmse"] + )[["sol_id", "robynPareto"]] + resultHypParamPareto = ( + resultHypParamPareto.groupby("sol_id").first().reset_index() + ) + resultHypParam = pd.merge( + resultHypParam, resultHypParamPareto, on="sol_id", how="left" + ) + else: + self.logger.info("Using fixed hyperparameters") + resultHypParam = resultHypParam.assign( + mape_qt10=True, robynPareto=1, coef0=np.nan + ) + + # Calculate combined weighted error scores + self.logger.debug("Calculating error scores") + resultHypParam["error_score"] = ParetoUtils.calculate_errors_scores( + df=resultHypParam, ts_validation=self.model_outputs.ts_validation + ) + self.logger.info("Pareto front computation completed") + return resultHypParam + + @staticmethod + def _pareto_fronts( + resultHypParamPareto: pd.DataFrame, pareto_fronts: str + ) -> pd.DataFrame: + """ + Calculate Pareto fronts from the aggregated model data. + + This method identifies Pareto-optimal solutions based on NRMSE and DECOMP.RSSD + optimization criteria and assigns them to Pareto fronts. + + Args: + resultHypParamPareto (pd.DataFrame): DataFrame containing model results, + including 'nrmse' and 'decomp.rssd' columns. + pareto_fronts (Union[str, int]): Number of Pareto fronts to calculate or "auto". + """ + # Extract vectors like in R + nrmse = resultHypParamPareto["nrmse"].values + decomp_rssd = resultHypParamPareto["decomp.rssd"].values + + # Ensure nrmse_values and decomp_rssd_values have the same length + if len(nrmse) != len(decomp_rssd): + raise ValueError( + "Length of nrmse_values must be equal to length of decomp_rssd" + ) + + # Create initial dataframe and sort (equivalent to R's order()) + data = pd.DataFrame({"nrmse": nrmse, "decomp_rssd": decomp_rssd}) + sorted_data = data.sort_values( + ["nrmse", "decomp_rssd"], ascending=[True, True] + ).copy() + + # Initialize empty dataframe for results + pareto_fronts_df = pd.DataFrame() + i = 1 + + # Convert pareto_fronts to match R's logic + max_fronts = ( + float("inf") + if isinstance(pareto_fronts, str) and "auto" in pareto_fronts + else pareto_fronts + ) + + # Main loop matching R's while condition + while len(sorted_data) >= 1 and i <= max_fronts: + # Calculate cummin (matches R's behavior) + cummin_mask = ~sorted_data["decomp_rssd"].cummin().duplicated() + pareto_candidates = sorted_data[cummin_mask].copy() + pareto_candidates["pareto_front"] = i + + # Append to results (equivalent to R's rbind) + pareto_fronts_df = pd.concat( + [pareto_fronts_df, pareto_candidates], ignore_index=True + ) + + # Remove processed rows (equivalent to R's row.names logic) + sorted_data = sorted_data.loc[ + ~sorted_data.index.isin(pareto_candidates.index) + ].copy() + i += 1 + + # Merge results back with original data (equivalent to R's merge) + result = pd.merge( + left=data, + right=pareto_fronts_df[["nrmse", "decomp_rssd", "pareto_front"]], + on=["nrmse", "decomp_rssd"], + how="left", + ) + + # Rename columns to match R output + result.columns = ["x", "y", "pareto_front"] + + return result.reset_index(drop=True) diff --git a/python/src/robyn/modeling/pareto/pareto_utils.py b/python/src/robyn/modeling/pareto/pareto_utils.py new file mode 100644 index 000000000..bc4e63354 --- /dev/null +++ b/python/src/robyn/modeling/pareto/pareto_utils.py @@ -0,0 +1,223 @@ +# pyre-strict + +from typing import List + +import logging +import numpy as np +import pandas as pd +from robyn.modeling.entities.clustering_results import ClusteredResult +from robyn.modeling.entities.pareto_result import ParetoResult + + +class ParetoUtils: + """ + Utility class for Pareto optimization in marketing mix models. + + This class provides various utility methods for Pareto front calculation, + error scoring, and other helper functions used in the Pareto optimization process. + It maintains state across operations, allowing for caching of intermediate results + and configuration of optimization parameters. + """ + + def __init__(self): + """ + Initialize the ParetoUtils instance. + """ + self.logger = logging.getLogger(__name__) + + @staticmethod + def calculate_errors_scores( + df: pd.DataFrame, balance: List[float] = [1, 1, 1], ts_validation: bool = True + ) -> np.ndarray: + """ + Calculate combined error scores based on NRMSE, DECOMP.RSSD, and MAPE. + + Args: + df (pd.DataFrame): DataFrame containing error columns. + balance (List[float]): Weights for NRMSE, DECOMP.RSSD, and MAPE. Defaults to [1, 1, 1]. + ts_validation (bool): If True, use 'nrmse_test', else use 'nrmse_train'. Defaults to True. + + Returns: + np.ndarray: Array of calculated error scores. + """ + assert len(balance) == 3, "Balance must be a list of 3 values" + + error_cols = [ + "nrmse_test" if ts_validation else "nrmse_train", + "decomp.rssd", + "mape", + ] + assert all( + col in df.columns for col in error_cols + ), f"Missing columns: {[col for col in error_cols if col not in df.columns]}" + + # Normalize balance weights + balance = np.array(balance) / sum(balance) + + # Select and rename columns + errors = df[error_cols].copy() + errors.columns = ["nrmse", "decomp.rssd", "mape"] + + # Replace infinite values with the maximum finite value + for col in errors.columns: + max_val = errors[np.isfinite(errors[col])][col].max() + errors[col] = errors[col].apply(lambda x: max_val if np.isinf(x) else x) + + # Normalize error values + for col in errors.columns: + errors[f"{col}_n"] = ParetoUtils.min_max_norm(errors[col]) + + # Replace NaN with 0 + errors = errors.fillna(0) + + # Apply balance weights + errors["nrmse_w"] = balance[0] * errors["nrmse_n"] + errors["decomp.rssd_w"] = balance[1] * errors["decomp.rssd_n"] + errors["mape_w"] = balance[2] * errors["mape_n"] + + # Calculate error score + errors["error_score"] = np.sqrt( + errors["nrmse_w"] ** 2 + + errors["decomp.rssd_w"] ** 2 + + errors["mape_w"] ** 2 + ) + + return errors["error_score"].values + + @staticmethod + def min_max_norm(x: pd.Series, min: float = 0, max: float = 1) -> pd.Series: + x = x.replace([np.inf, -np.inf], np.max(np.isfinite(x))) + if len(x) <= 1: + return x + a, b = x.min(), x.max() + if b - a != 0: + return (max - min) * (x - a) / (b - a) + min + else: + return x + + @staticmethod + def calculate_fx_objective( + x: float, + coeff: float, + alpha: float, + inflexion: float, + x_hist_carryover: float, + get_sum: bool = True, + ) -> float: + # Adstock scales + x_adstocked = x + np.mean(x_hist_carryover) + + # Hill transformation + if get_sum: + x_out = coeff * np.sum((1 + inflexion**alpha / x_adstocked**alpha) ** -1) + else: + x_out = coeff * ((1 + inflexion**alpha / x_adstocked**alpha) ** -1) + + return x_out + + def process_pareto_clustered_results( + self, + pareto_results: ParetoResult, + clustered_result: ClusteredResult, + ran_cluster: bool = True, + ran_calibration: bool = False, + ) -> ParetoResult: + """ + Process Pareto optimization results and update the internal state. + + Args: + pareto_results (ParetoResult): Pareto optimization results. + clustered_result (ClusteredResult): Clustered results. + ran_cluster (bool): Whether to run clustering. + ran_calibration (bool): Whether calibration was run. + Returns: + ParetoResult: Updated Pareto optimization results. + """ + all_solutions = pareto_results.pareto_solutions + + # Common logic for all cases + x_decomp_agg = pareto_results.x_decomp_agg[ + pareto_results.x_decomp_agg["sol_id"].isin(all_solutions) + ] + result_hyp_param = pareto_results.result_hyp_param[ + pareto_results.result_hyp_param["sol_id"].isin(all_solutions) + ] + result_calibration = ( + pareto_results.result_calibration[ + pareto_results.result_calibration["sol_id"].isin(all_solutions) + ] + if ran_calibration and pareto_results.result_calibration is not None + else None + ) + + if ran_cluster: + # Select common columns from cluster data + common_clustered_df = clustered_result.cluster_data[ + ["sol_id", "cluster", "top_sol"] + ] + + result_hyp_param = pd.merge( + result_hyp_param, common_clustered_df, on="sol_id", how="left" + ) + + x_decomp_agg = ( + pd.merge(x_decomp_agg, common_clustered_df, on="sol_id", how="left") + .merge( + clustered_result.cluster_ci.cluster_confidence_interval_df[ + ["rn", "cluster", "boot_mean", "boot_se", "ci_low", "ci_up"] + ], + on=["rn", "cluster"], + how="left", + ) + .merge( + pareto_results.df_caov_pct_all[ + pareto_results.df_caov_pct_all["type"] == "Carryover" + ][["sol_id", "rn", "carryover_pct"]], + on=["sol_id", "rn"], + how="left", + ) + ) + + media_vec_collect = pd.merge( + pareto_results.media_vec_collect, + common_clustered_df, + on="sol_id", + how="left", + ) + + # Join xDecompVecCollect + x_decomp_vec_collect = pd.merge( + pareto_results.x_decomp_vec_collect, + common_clustered_df, + on="sol_id", + how="left", + ) + + if ran_calibration and pareto_results.result_calibration is not None: + result_calibration = pd.merge( + result_calibration, common_clustered_df, on="sol_id", how="left" + ) + + return ParetoResult( + pareto_solutions=all_solutions, + x_decomp_agg=x_decomp_agg, + result_hyp_param=result_hyp_param, + result_calibration=result_calibration, + media_vec_collect=media_vec_collect, + x_decomp_vec_collect=x_decomp_vec_collect, + pareto_fronts=pareto_results.pareto_fronts, + df_caov_pct_all=pareto_results.df_caov_pct_all, + plot_data_collect=pareto_results.plot_data_collect, + ) + else: + return ParetoResult( + pareto_solutions=all_solutions, + x_decomp_agg=x_decomp_agg, + result_hyp_param=result_hyp_param, + result_calibration=result_calibration, + media_vec_collect=pareto_results.media_vec_collect, + x_decomp_vec_collect=pareto_results.x_decomp_vec_collect, + pareto_fronts=pareto_results.pareto_fronts, + df_caov_pct_all=pareto_results.df_caov_pct_all, + plot_data_collect=pareto_results.plot_data_collect, + ) diff --git a/python/src/robyn/modeling/pareto/plot_data_generator.py b/python/src/robyn/modeling/pareto/plot_data_generator.py new file mode 100644 index 000000000..97ded88c9 --- /dev/null +++ b/python/src/robyn/modeling/pareto/plot_data_generator.py @@ -0,0 +1,875 @@ +# pyre-strict +import logging +from typing import Dict, Union + +import pandas as pd +import numpy as np +from robyn.common.logger import RobynLogger +from robyn.data.entities.enums import AdstockType, DependentVarType +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.hyperparameters import ChannelHyperparameters, Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.featurized_mmm_data import FeaturizedMMMData +from robyn.modeling.entities.pareto_data import ParetoData +from robyn.modeling.transformations.transformations import Transformation +from tqdm import tqdm + + +class PlotDataGenerator: + + def __init__( + self, + mmm_data: MMMData, + hyperparameter: Hyperparameters, + featurized_mmm_data: FeaturizedMMMData, + holidays_data: HolidaysData, + ): + self.mmm_data = mmm_data + self.hyperparameter = hyperparameter + self.featurized_mmm_data = featurized_mmm_data + self.holidays_data = holidays_data + self.transformer = Transformation(mmm_data) + + # Setup logger with a single handler + self.logger = logging.getLogger(__name__) + + def generate_plot_data( + self, + aggregated_data: Dict[str, pd.DataFrame], + pareto_data: ParetoData, + ) -> Dict[str, pd.DataFrame]: + """ + Prepare data for various plots used in the Pareto analysis. + """ + mediaVecCollect = pd.DataFrame() + xDecompVecCollect = pd.DataFrame() + plotDataCollect = {} + df_caov_pct_all = pd.DataFrame() + + xDecompAgg = pareto_data.x_decomp_agg + dt_mod = self.featurized_mmm_data.dt_mod + dt_modRollWind = self.featurized_mmm_data.dt_modRollWind + rw_start_loc = self.mmm_data.mmmdata_spec.rolling_window_start_which + rw_end_loc = self.mmm_data.mmmdata_spec.rolling_window_end_which + + self.logger.info("Starting plot data generation...") + self.logger.debug( + f"Available columns in xDecompAgg: {xDecompAgg.columns.tolist()}" + ) + + pareto_fronts_vec = pareto_data.pareto_fronts + + for pf in pareto_fronts_vec: + self.logger.info(f"Processing Pareto front {pf}") + plotMediaShare = xDecompAgg[ + (xDecompAgg["robynPareto"] == pf) + & (xDecompAgg["rn"].isin(self.mmm_data.mmmdata_spec.paid_media_spends)) + ] + self.logger.debug(f"Shape of plotMediaShare: {plotMediaShare.shape}") + + uniqueSol = plotMediaShare["sol_id"].unique() + plotWaterfall = xDecompAgg[xDecompAgg["robynPareto"] == pf] + + self.logger.info(f"Pareto-Front: {pf} [{len(uniqueSol)} models]") + + for sid in tqdm(uniqueSol, desc="Processing Solutions", unit="solution"): + try: + plot_results = self._process_single_solution( + sid, + plotMediaShare, + plotWaterfall, + pareto_data, + aggregated_data, + dt_mod, + dt_modRollWind, + rw_start_loc, + rw_end_loc, + ) + + mediaVecCollect = pd.concat( + [mediaVecCollect, plot_results["mediaVecCollect"]], + ignore_index=True, + ) + xDecompVecCollect = pd.concat( + [xDecompVecCollect, plot_results["xDecompVec"]], + ignore_index=True, + ) + plotDataCollect[sid] = plot_results["plotData"] + df_caov_pct_all = pd.concat( + [df_caov_pct_all, plot_results["plot7data"]] + ) + + except Exception as e: + self.logger.error(f"Error processing solution {sid}: {str(e)}") + raise e + + pareto_solutions = set() + if "sol_id" in xDecompVecCollect.columns: + pareto_solutions.update(set(xDecompVecCollect["sol_id"].unique())) + + self.logger.debug( + f"Found ({len(pareto_solutions)}) Pareto Solutions - {pareto_solutions}" + ) + RobynLogger.log_df(self.logger, mediaVecCollect) + RobynLogger.log_df(self.logger, xDecompVecCollect) + RobynLogger.log_df(self.logger, df_caov_pct_all) + + self.logger.info("Plot data generated Successfully.") + return { + "pareto_solutions": list(pareto_solutions), + "mediaVecCollect": mediaVecCollect, + "xDecompVecCollect": xDecompVecCollect, + "plotDataCollect": plotDataCollect, + "df_caov_pct_all": df_caov_pct_all, + } + + def _generate_spend_effect_data(self, plotMediaShare: pd.DataFrame, sid: str): + temp = plotMediaShare[plotMediaShare["sol_id"] == sid].melt( + id_vars=["rn", "nrmse", "decomp.rssd", "rsq_train"], + value_vars=["spend_share", "effect_share", "roi_total", "cpa_total"], + var_name="variable", + value_name="value", + ) + temp["rn"] = pd.Categorical( + temp["rn"], + categories=sorted(self.mmm_data.mmmdata_spec.paid_media_spends), + ordered=True, + ) + + plotMediaShareLoopBar = temp[ + temp["variable"].isin(["spend_share", "effect_share"]) + ] + plotMediaShareLoopLine = temp[ + temp["variable"] + == ( + "cpa_total" + if self.mmm_data.mmmdata_spec.dep_var_type + == DependentVarType.CONVERSION + else "roi_total" + ) + ] + + line_rm_inf = ~np.isinf(plotMediaShareLoopLine["value"]) + ySecScale = ( + max(plotMediaShareLoopLine["value"][line_rm_inf]) + / max(plotMediaShareLoopBar["value"]) + * 1.1 + ) + + return { + "plotMediaShareLoopBar": plotMediaShareLoopBar, + "plotMediaShareLoopLine": plotMediaShareLoopLine, + "ySecScale": ySecScale, + } + + def _process_single_solution( + self, + sid: str, + plotMediaShare: pd.DataFrame, + plotWaterfall: pd.DataFrame, + pareto_data: ParetoData, + aggregated_data: Dict[str, pd.DataFrame], + dt_mod: pd.DataFrame, + dt_modRollWind: pd.DataFrame, + rw_start_loc: int, + rw_end_loc: int, + ) -> Dict: + # 1. Spend x effect share comparison + plot1data = self._generate_spend_effect_data(plotMediaShare, sid) + self.logger.debug(f"Generated plot1data, spend vs effect data, for sid: {sid}") + + # 2. Waterfall + plotWaterfallLoop = self._generate_waterfall_data(plotWaterfall, sid) + plot2data = {"plotWaterfallLoop": plotWaterfallLoop} + self.logger.debug(f"Generated plot2data, waterfall data, for sid: {sid}") + + # 3. Adstock rate + plot3data = self._generate_adstock_data(sid, pareto_data) + self.logger.debug(f"Generated plot3data, adstock plot data, for sid: {sid}") + + # 4. Spend response curve + plot4data = self._generate_response_data( + sid, dt_mod, plotWaterfall, plotWaterfallLoop, rw_start_loc, rw_end_loc + ) + + dt_transformPlot = plot4data["dt_transformPlot"] + dt_transformSpend = plot4data["dt_transformSpend"] + dt_transformSpendMod = plot4data["dt_transformSpendMod"] + dt_transformAdstock = plot4data["dt_transformAdstock"] + dt_transformSaturationSpendReverse = plot4data[ + "dt_transformSaturationSpendReverse" + ] + dt_transformSaturationDecomp = plot4data["dt_transformSaturationDecomp"] + + plot4data = { + "dt_scurvePlot": plot4data["dt_scurvePlot"], + "dt_scurvePlotMean": plot4data["dt_scurvePlotMean"], + } + self.logger.debug(f"Generated plot4data, scurve plot data, for sid: {sid}") + + # 5. Fitted vs actual + col_order = ( + ["ds", "dep_var"] + + self.mmm_data.mmmdata_spec.all_media + + [ + self._get_prophet_var_values(var) + for var in self.holidays_data.prophet_vars + ] + + self.mmm_data.mmmdata_spec.context_vars + ) + + selected_columns = ( + ["ds", "dep_var"] + + [ + self._get_prophet_var_values(var) + for var in self.holidays_data.prophet_vars + ] + + self.mmm_data.mmmdata_spec.context_vars + ) + + dt_transformDecomp = dt_modRollWind[selected_columns] + dt_transformDecomp = pd.concat( + [ + dt_transformDecomp, + self.dt_transformSaturation[self.mmm_data.mmmdata_spec.all_media], + ], + axis=1, + ) + dt_transformDecomp = dt_transformDecomp[col_order] + + xDecompVec = ( + plotWaterfall[plotWaterfall["sol_id"] == sid][["sol_id", "rn", "coef"]] + .pivot(index="sol_id", columns="rn", values="coef") + .reset_index() + ) + + if "(Intercept)" not in xDecompVec.columns: + xDecompVec["(Intercept)"] = 0 + + xDecompVec = xDecompVec[ + ["sol_id", "(Intercept)"] + + [col for col in col_order if col not in ["ds", "dep_var"]] + ] + intercept = xDecompVec["(Intercept)"].values[0] + + scurved = dt_transformDecomp.drop(columns=["ds", "dep_var"]) + coefs = xDecompVec.drop(columns=["sol_id", "(Intercept)"]) + + scurved = scurved.apply(pd.to_numeric, errors="coerce") + coefs = coefs.apply(pd.to_numeric, errors="coerce") + + xDecompVec = pd.DataFrame( + np.multiply(scurved.values, coefs.values), + columns=coefs.columns, + ) + + xDecompVec["intercept"] = intercept + xDecompVec["depVarHat"] = xDecompVec.sum(axis=1) + intercept + xDecompVec["sol_id"] = sid + + xDecompVec = pd.concat( + [dt_transformDecomp[["ds", "dep_var"]], xDecompVec], axis=1 + ) + + xDecompVecPlot = xDecompVec[["ds", "dep_var", "depVarHat"]].rename( + columns={"dep_var": "actual", "depVarHat": "predicted"} + ) + xDecompVecPlotMelted = xDecompVecPlot.melt( + id_vars="ds", var_name="variable", value_name="value" + ) + + rsq = plotWaterfall[plotWaterfall["sol_id"] == sid]["rsq_train"].values[0] + plot5data = { + "xDecompVecPlotMelted": xDecompVecPlotMelted, + "rsq": rsq, + } + self.logger.debug(f"Generated plot5data, fitted vs actual, for sid: {sid}") + + # 6. Diagnostic: fitted vs residual + plot6data = {"xDecompVecPlot": xDecompVecPlot} + self.logger.debug(f"Generated plot6data, fitted vs residual, for sid: {sid}") + + # 7. Immediate vs carryover response + plot7data = self.robyn_immcarr( + pareto_data, aggregated_data["result_hyp_param"], sid + ) + self.logger.debug( + f"Generated plot7data, immediate vs carryover, for sid: {sid}" + ) + mediaVecCollect = pd.concat( + [ + dt_transformPlot.assign(type="rawMedia", sol_id=sid), + dt_transformSpend.assign(type="rawSpend", sol_id=sid), + dt_transformSpendMod.assign(type="predictedExposure", sol_id=sid), + dt_transformAdstock.assign(type="adstockedMedia", sol_id=sid), + self.dt_transformSaturation.assign(type="saturatedMedia", sol_id=sid), + dt_transformSaturationSpendReverse.assign( + type="saturatedSpendReversed", sol_id=sid + ), + dt_transformSaturationDecomp.assign(type="decompMedia", sol_id=sid), + ], + ignore_index=True, + ) + return { + "mediaVecCollect": mediaVecCollect, + "xDecompVec": xDecompVec, + "plotData": { + "plot1data": plot1data, + "plot2data": plot2data, + "plot3data": plot3data, + "plot4data": plot4data, + "plot5data": plot5data, + "plot6data": plot6data, + "plot7data": plot7data, + }, + "plot7data": plot7data, + } + + def _generate_waterfall_data( + self, plotWaterfall: pd.DataFrame, sid: str + ) -> pd.DataFrame: + plotWaterfallLoop = plotWaterfall[plotWaterfall["sol_id"] == sid].sort_values( + "xDecompPerc" + ) + plotWaterfallLoop["end"] = 1 - plotWaterfallLoop["xDecompPerc"].cumsum() + plotWaterfallLoop["start"] = plotWaterfallLoop["end"].shift(1).fillna(1) + plotWaterfallLoop["id"] = range(1, len(plotWaterfallLoop) + 1) + plotWaterfallLoop["rn"] = pd.Categorical(plotWaterfallLoop["rn"]) + plotWaterfallLoop["sign"] = pd.Categorical( + np.where(plotWaterfallLoop["xDecompPerc"] >= 0, "Positive", "Negative") + ) + + return plotWaterfallLoop[ + ["id", "rn", "coef", "xDecompAgg", "xDecompPerc", "start", "end", "sign"] + ].reset_index() + + def _generate_adstock_data( + self, sid: str, pareto_data: ParetoData + ) -> Dict[str, Union[pd.DataFrame, AdstockType]]: + dt_geometric = None + weibullCollect = None + resultHypParamLoop = pareto_data.result_hyp_param[ + pareto_data.result_hyp_param["sol_id"] == sid + ] + get_hp_names = [] + for media in self.mmm_data.mmmdata_spec.all_media: + if self.hyperparameter.adstock == AdstockType.GEOMETRIC: + get_hp_names.extend( + [f"{media}_alphas", f"{media}_gammas", f"{media}_thetas"] + ) + else: + get_hp_names.extend( + [ + f"{media}_alphas", + f"{media}_gammas", + f"{media}_shapes", + f"{media}_scales", + ] + ) + + self.hypParam = resultHypParamLoop[get_hp_names] + + adstock_type = self.hyperparameter.adstock + if self.hyperparameter.adstock == AdstockType.GEOMETRIC: + hypParam_thetas = [ + self.hypParam[f"{media}_thetas"].iloc[0] + for media in self.mmm_data.mmmdata_spec.all_media + ] + dt_geometric = pd.DataFrame( + { + "channels": self.mmm_data.mmmdata_spec.all_media, + "thetas": hypParam_thetas, + } + ) + elif self.hyperparameter.adstock in [ + AdstockType.WEIBULL_CDF, + AdstockType.WEIBULL_PDF, + ]: + weibullCollect = self._process_weibull_collect(self.hypParam, adstock_type) + + return { + "dt_geometric": dt_geometric, + "weibullCollect": weibullCollect, + "wb_type": adstock_type, + } + + def _process_weibull_collect( + self, hypParam: pd.DataFrame, adstock_type: AdstockType + ) -> pd.DataFrame: + shapeVec = [ + hypParam[f"{media}_shapes"].iloc[0] + for media in self.mmm_data.mmmdata_spec.all_media + ] + scaleVec = [ + hypParam[f"{media}_scales"].iloc[0] + for media in self.mmm_data.mmmdata_spec.all_media + ] + weibullCollect = [] + for v1 in range(len(self.mmm_data.mmmdata_spec.all_media)): + dt_weibull = pd.DataFrame( + { + "x": range(1, self.mmm_data.mmmdata_spec.rolling_window_length + 1), + "decay_accumulated": self.transformer.adstock_weibull( + range(1, self.mmm_data.mmmdata_spec.rolling_window_length + 1), + shape=shapeVec[v1], + scale=scaleVec[v1], + adstockType=adstock_type, + )["thetaVecCum"], + "adstockType": adstock_type, + "channel": self.mmm_data.mmmdata_spec.all_media[v1], + } + ) + dt_weibull["halflife"] = ( + (dt_weibull["decay_accumulated"] - 0.5).abs().idxmin() + ) + max_non0 = (dt_weibull["decay_accumulated"] > 0.001).argmax() + dt_weibull["cut_time"] = ( + max_non0 * 2 if max_non0 <= 5 else int(max_non0 + max_non0 / 3) + ) + weibullCollect.append(dt_weibull) + + weibullCollect = pd.concat(weibullCollect) + return weibullCollect[weibullCollect["x"] <= weibullCollect["cut_time"].max()] + + def _generate_response_data( + self, + sid: str, + dt_mod: pd.DataFrame, + plotWaterfall: pd.DataFrame, + plotWaterfallLoop: pd.DataFrame, + rw_start_loc: int, + rw_end_loc: int, + ) -> Dict[str, pd.DataFrame]: + dt_transformPlot = dt_mod[["ds"] + self.mmm_data.mmmdata_spec.all_media] + dt_transformSpend = pd.concat( + [ + dt_transformPlot[["ds"]], + self.mmm_data.data[self.mmm_data.mmmdata_spec.paid_media_spends], + ], + axis=1, + ) + dt_transformSpendMod = dt_transformPlot.iloc[rw_start_loc:rw_end_loc] + dt_transformAdstock = dt_transformPlot.copy() + self.dt_transformSaturation = dt_transformPlot.iloc[rw_start_loc:rw_end_loc] + + all_media_channels = self.mmm_data.mmmdata_spec.all_media + for med in range(len(all_media_channels)): + med_select = all_media_channels[med] + m = pd.Series(dt_transformPlot[med_select].values) + adstock = self.hyperparameter.adstock + if adstock == AdstockType.GEOMETRIC: + thetas = self.hypParam[f"{all_media_channels[med]}_thetas"].values + channelHyperparam = ChannelHyperparameters(thetas=thetas) + elif adstock in [ + AdstockType.WEIBULL_PDF, + AdstockType.WEIBULL_CDF, + ]: + shapes = self.hypParam[f"{all_media_channels[med]}_shapes"].values + scales = self.hypParam[f"{all_media_channels[med]}_scales"].values + channelHyperparam = ChannelHyperparameters(shapes=shapes, scales=scales) + + x_list = self.transformer.transform_adstock(m, adstock, channelHyperparam) + m_adstocked = x_list.x_decayed + dt_transformAdstock[med_select] = m_adstocked + m_adstockedRollWind = m_adstocked[rw_start_loc:rw_end_loc] + + # Saturation + alpha = self.hypParam[f"{all_media_channels[med]}_alphas"].iloc[0] + gamma = self.hypParam[f"{all_media_channels[med]}_gammas"].iloc[0] + self.dt_transformSaturation.loc[:, med_select] = ( + self.transformer.saturation_hill( + x=m_adstockedRollWind, alpha=alpha, gamma=gamma + ) + ) + + dt_transformSaturationDecomp = self.dt_transformSaturation.copy() + for i in range(len(all_media_channels)): + coef = plotWaterfallLoop["coef"][ + plotWaterfallLoop["rn"] == all_media_channels[i] + ].values[0] + dt_transformSaturationDecomp[all_media_channels[i]] *= coef + + dt_transformSaturationSpendReverse = dt_transformAdstock.iloc[ + rw_start_loc:rw_end_loc + ] + + # Spend response curve + dt_scurvePlot = dt_transformSaturationDecomp.melt( + id_vars=["ds"], + value_vars=all_media_channels, + var_name="channel", + value_name="response", + ) + + # Gather spend data and merge it into dt_scurvePlot + spend_data = dt_transformSaturationSpendReverse.melt( + id_vars=["ds"], + value_vars=all_media_channels, + var_name="channel", + value_name="spend", + ) + + # Merge spend data into dt_scurvePlot based on the 'channel' and 'ds' columns + dt_scurvePlot = dt_scurvePlot.merge( + spend_data[["ds", "channel", "spend"]], + on=["ds", "channel"], + how="left", + ) + + # Remove outlier introduced by MM nls fitting + dt_scurvePlot = dt_scurvePlot[dt_scurvePlot["spend"] >= 0] + + # Calculate dt_scurvePlotMean + dt_scurvePlotMean = ( + plotWaterfall[ + (plotWaterfall["sol_id"] == sid) & (~plotWaterfall["mean_spend"].isna()) + ][ + [ + "rn", + "mean_spend", + "mean_spend_adstocked", + "mean_carryover", + "mean_response", + "sol_id", + ] + ] + .rename(columns={"rn": "channel"}) + .reset_index() + ) + + return { + "dt_scurvePlot": dt_scurvePlot, + "dt_scurvePlotMean": dt_scurvePlotMean, + "dt_transformPlot": dt_transformPlot, + "dt_transformSpend": dt_transformSpend, + "dt_transformSpendMod": dt_transformSpendMod, + "dt_transformAdstock": dt_transformAdstock, + "dt_transformSaturationSpendReverse": dt_transformSaturationSpendReverse, + "dt_transformSaturationDecomp": dt_transformSaturationDecomp, + } + + def _get_prophet_var_values(self, var) -> str: + """Helper function to handle both string and enum prophet variables.""" + try: + return var.value if hasattr(var, "value") else var + except AttributeError: + return var + + def robyn_immcarr( + self, + pareto_data: ParetoData, + result_hyp_param: pd.DataFrame, + sol_id=None, + start_date=None, + end_date=None, + ): + """Calculate immediate and carryover effects.""" + # Define default values when not provided + if sol_id is None: + sol_id = result_hyp_param["sol_id"].iloc[0] + if start_date is None: + start_date = self.mmm_data.mmmdata_spec.window_start + if end_date is None: + end_date = self.mmm_data.mmmdata_spec.window_end + + # Convert to datetime series and reset index + dt_modRollWind = pd.to_datetime( + self.featurized_mmm_data.dt_modRollWind["ds"] + ).reset_index(drop=True) + dt_modRollWind = dt_modRollWind.dropna() + + # Convert inputs to datetime + if isinstance(start_date, (list, pd.Series)): + start_date = start_date[0] + start_date = pd.to_datetime(start_date) + + if isinstance(end_date, (list, pd.Series)): + end_date = end_date[0] + end_date = pd.to_datetime(end_date) + + # Find closest dates using absolute difference + start_idx = (dt_modRollWind - start_date).abs().argmin() + end_idx = (dt_modRollWind - end_date).abs().argmin() + + start_date = dt_modRollWind[start_idx] + end_date = dt_modRollWind[end_idx] + + # Use boolean indexing instead of value matching + rollingWindow = range(start_idx, end_idx + 1) + + # Rest of your function remains the same + self.logger.info( + "Calculating saturated dataframes with carryover and immediate parts" + ) + hypParamSam = result_hyp_param[result_hyp_param["sol_id"] == sol_id] + hyperparameter = self._extract_hyperparameter(hypParamSam) + + dt_saturated_dfs = self.transformer.run_transformations( + self.featurized_mmm_data, + hyperparameter, + hyperparameter.adstock, + ) + # Calculate decomposition + coefs = pareto_data.x_decomp_agg.loc[ + pareto_data.x_decomp_agg["sol_id"] == sol_id, "coef" + ].values + coefs_names = pareto_data.x_decomp_agg.loc[ + pareto_data.x_decomp_agg["sol_id"] == sol_id, "rn" + ].values + + # Create a DataFrame to hold coefficients and their names + coefs_df = pd.DataFrame({"name": coefs_names, "coefficient": coefs}) + + self.logger.debug("Computing decomposition") + # Check if 'revenue' exists in the columns + if "revenue" in dt_saturated_dfs.dt_modSaturated.columns: + # Rename 'revenue' to 'dep_var' + dt_saturated_dfs.dt_modSaturated = dt_saturated_dfs.dt_modSaturated.rename( + columns={"revenue": "dep_var"} + ) + # print("Column 'revenue' renamed to 'dep_var'.") + else: + # print("Column 'revenue' does not exist.") + pass + decompCollect = self._model_decomp( + inputs={ + "coefs": coefs_df, + "y_pred": dt_saturated_dfs.dt_modSaturated["dep_var"].iloc[ + rollingWindow + ], + "dt_modSaturated": dt_saturated_dfs.dt_modSaturated.iloc[rollingWindow], + "dt_saturatedImmediate": dt_saturated_dfs.dt_saturatedImmediate.iloc[ + rollingWindow + ], + "dt_saturatedCarryover": dt_saturated_dfs.dt_saturatedCarryover.iloc[ + rollingWindow + ], + "dt_modRollWind": self.featurized_mmm_data.dt_modRollWind.iloc[ + rollingWindow + ], + "refreshAddedStart": start_date, + } + ) + + # Media decomposition + mediaDecompImmediate = decompCollect["mediaDecompImmediate"].drop( + columns=["ds", "y"], errors="ignore" + ) + mediaDecompImmediate.columns = [ + f"{col}_MDI" for col in mediaDecompImmediate.columns + ] + + mediaDecompCarryover = decompCollect["mediaDecompCarryover"].drop( + columns=["ds", "y"], errors="ignore" + ) + mediaDecompCarryover.columns = [ + f"{col}_MDC" for col in mediaDecompCarryover.columns + ] + + # Combine results + temp = pd.concat( + [decompCollect["xDecompVec"], mediaDecompImmediate, mediaDecompCarryover], + axis=1, + ) + temp["sol_id"] = sol_id + + # Create vector collections + vec_collect = { + "xDecompVec": temp.drop( + columns=temp.columns[ + temp.columns.str.endswith("_MDI") + | temp.columns.str.endswith("_MDC") + ] + ), + "xDecompVecImmediate": temp.drop( + columns=temp.columns[ + temp.columns.str.endswith("_MDC") + | temp.columns.isin(self.mmm_data.mmmdata_spec.all_media) + ] + ), + "xDecompVecCarryover": temp.drop( + columns=temp.columns[ + temp.columns.str.endswith("_MDI") + | temp.columns.isin(self.mmm_data.mmmdata_spec.all_media) + ] + ), + } + + # Rename columns + this = vec_collect["xDecompVecImmediate"].columns.str.replace( + "_MDI", "", regex=False + ) + vec_collect["xDecompVecImmediate"].columns = this + vec_collect["xDecompVecCarryover"].columns = this + + # Convert datetime64[ns] to object: You can convert the ds column to a string format, which will change its type to object. + vec_collect["xDecompVecCarryover"]["ds"] = vec_collect["xDecompVecCarryover"][ + "ds" + ].astype(str) + vec_collect["xDecompVec"]["ds"] = vec_collect["xDecompVec"]["ds"].astype(str) + # Calculate carryover percentages + df_caov = ( + vec_collect["xDecompVecCarryover"].groupby("sol_id").sum().reset_index() + ).drop(columns="ds") + df_total = ( + vec_collect["xDecompVec"] + .groupby("sol_id") + .sum() + .reset_index() + .drop(columns="ds") + ) + df_caov_pct = df_caov.copy() + df_caov_pct.loc[:, df_caov_pct.columns[1:]] = ( + df_caov_pct.loc[:, df_caov_pct.columns[1:]] + .div(df_total.iloc[:, 1:].values) + .astype("float64") + ) + df_caov_pct = df_caov_pct.melt( + id_vars="sol_id", var_name="rn", value_name="carryover_pct" + ).fillna(0) + + # Gather everything in an aggregated format + self.logger.debug( + "Aggregating final results from decomposition carryover and immediate parts" + ) + xDecompVecImmeCaov = ( + pd.concat( + [ + vec_collect["xDecompVecImmediate"].assign(type="Immediate"), + vec_collect["xDecompVecCarryover"].assign(type="Carryover"), + ], + axis=0, + ) + .melt( + id_vars=["sol_id", "type"], + value_vars=self.mmm_data.mmmdata_spec.all_media, + var_name="rn", + value_name="value", + ) + .assign(start_date=start_date, end_date=end_date) + ) + + # Grouping and aggregating the data + xDecompVecImmeCaov = ( + xDecompVecImmeCaov.groupby( + ["sol_id", "start_date", "end_date", "rn", "type"] + ) + .agg(response=("value", "sum")) + .reset_index() + ) + + xDecompVecImmeCaov["percentage"] = xDecompVecImmeCaov[ + "response" + ] / xDecompVecImmeCaov.groupby(["sol_id", "start_date", "end_date", "type"])[ + "response" + ].transform( + "sum" + ) + xDecompVecImmeCaov.fillna(0, inplace=True) + + # Join with carryover percentages + xDecompVecImmeCaov = xDecompVecImmeCaov.merge( + df_caov_pct, on=["sol_id", "rn"], how="left" + ) + + return xDecompVecImmeCaov + + def _extract_hyperparameter(self, hypParamSam: pd.DataFrame) -> Hyperparameters: + """ + This function extracts hyperparameters from a given DataFrame. + + Parameters: + hypParamSam (DataFrame): A DataFrame containing hyperparameters. + + Returns: + hyperparameter (dict): A dictionary of hyperparameters. + """ + channelHyperparams: dict[str, ChannelHyperparameters] = {} + for med in self.mmm_data.mmmdata_spec.all_media: + alphas = hypParamSam[f"{med}_alphas"].values + gammas = hypParamSam[f"{med}_gammas"].values + if self.hyperparameter.adstock == AdstockType.GEOMETRIC: + thetas = hypParamSam[f"{med}_thetas"].values + channelHyperparams[med] = ChannelHyperparameters( + thetas=thetas, + alphas=alphas, + gammas=gammas, + ) + elif self.hyperparameter.adstock in [ + AdstockType.WEIBULL_CDF, + AdstockType.WEIBULL_PDF, + ]: + shapes = hypParamSam[f"{med}_shapes"].values + scales = hypParamSam[f"{med}_scales"].values + channelHyperparams[med] = ChannelHyperparameters( + shapes=shapes, + scales=scales, + alphas=alphas, + gammas=gammas, + ) + + return Hyperparameters( + adstock=self.hyperparameter.adstock, hyperparameters=channelHyperparams + ) + + def _model_decomp(self, inputs) -> Dict[str, pd.DataFrame]: + # Extracting inputs from the dictionary + coefs = inputs["coefs"] + y_pred = inputs["y_pred"] + dt_modSaturated = inputs["dt_modSaturated"] + dt_saturatedImmediate = inputs["dt_saturatedImmediate"] + dt_saturatedCarryover = inputs["dt_saturatedCarryover"] + dt_modRollWind = inputs["dt_modRollWind"] + # Input for decomp + y = dt_modSaturated["dep_var"] + # Select all columns except 'dep_var' + x = dt_modSaturated.drop(columns=["dep_var"]) + # Convert 'events' column to numeric if it exists + if "events" in x.columns: + x["events"] = pd.to_numeric(x["events"], errors="coerce") + # x["events"].fillna(0, inplace=True) # Replace NaN values with 0 + x.loc[:, "events"] = x["events"].fillna(0) + intercept = coefs["coefficient"].iloc[0] + # Decomp x + # Create an empty DataFrame for xDecomp + xDecomp = pd.DataFrame() + # Multiply each regressor by its corresponding coefficient + for name in x.columns: + # Get the corresponding coefficient for the regressor + coefficient_value = coefs.loc[coefs["name"] == name, "coefficient"].values + xDecomp[name] = x[name] * ( + coefficient_value if len(coefficient_value) > 0 else 0 + ) + # Add intercept as the first column + xDecomp.insert(0, "intercept", intercept) + xDecompOut = pd.concat( + [ + pd.DataFrame({"ds": dt_modRollWind["ds"], "y": y, "y_pred": y_pred}), + xDecomp, + ], + axis=1, + ) + # Decomp immediate & carryover response + sel_coef = coefs["name"].isin( + dt_saturatedImmediate.columns + ) # Check if coefficient names are in the immediate DataFrame + coefs_media = coefs[sel_coef].set_index("name")[ + "coefficient" + ] # Set names for coefs_media + mediaDecompImmediate = pd.DataFrame( + { + name: dt_saturatedImmediate[name] * coefs_media[name] + for name in coefs_media.index + } + ) + mediaDecompCarryover = pd.DataFrame( + { + name: dt_saturatedCarryover[name] * coefs_media[name] + for name in coefs_media.index + } + ) + return { + "xDecompVec": xDecompOut, + "mediaDecompImmediate": mediaDecompImmediate, + "mediaDecompCarryover": mediaDecompCarryover, + } diff --git a/python/src/robyn/modeling/pareto/response_curve.py b/python/src/robyn/modeling/pareto/response_curve.py new file mode 100644 index 000000000..6c3025cbe --- /dev/null +++ b/python/src/robyn/modeling/pareto/response_curve.py @@ -0,0 +1,770 @@ +# pyre-strict + +from functools import partial +from concurrent.futures import ThreadPoolExecutor, as_completed +import logging +from dataclasses import dataclass +from enum import Enum +from typing import Dict, Literal, Optional, Union + +import numpy as np +import pandas as pd +from robyn.common.logger import RobynLogger +from robyn.data.entities.enums import AdstockType +from robyn.data.entities.hyperparameters import ChannelHyperparameters, Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.modeling.entities.pareto_data import ParetoData +from robyn.modeling.pareto.hill_calculator import HillCalculator +from robyn.modeling.pareto.pareto_utils import ParetoUtils +from robyn.modeling.transformations.transformations import Transformation +from tqdm import tqdm # Import tqdm for progress bar + + +@dataclass +class MetricDateInfo: + metric_loc: pd.Series + date_range_updated: pd.Series + + def __str__(self) -> str: + return f"MetricDateInfo(date_range: {self.date_range_updated.iloc[0]} to {self.date_range_updated.iloc[-1]})" + + +@dataclass +class MetricValueInfo: + metric_value_updated: np.ndarray + all_values_updated: pd.Series + + def __str__(self) -> str: + return f"MetricValueInfo(values_shape: {self.metric_value_updated.shape})" + + +@dataclass +class ResponseOutput: + metric_name: str + date: pd.Series + input_total: np.ndarray + input_carryover: np.ndarray + input_immediate: np.ndarray + response_data: np.ndarray + response_total: np.ndarray + response_carryover: np.ndarray + response_immediate: np.ndarray + usecase: str + + def __str__(self) -> str: + return ( + f"ResponseOutput(metric: {self.metric_name}, " + f"date_range: {self.date.iloc[0]} to {self.date.iloc[-1]}, " + f"usecase: {self.usecase})" + ) + + +class UseCase(str, Enum): + ALL_HISTORICAL_VEC = "all_historical_vec" + SELECTED_HISTORICAL_VEC = "selected_historical_vec" + TOTAL_METRIC_DEFAULT_RANGE = "total_metric_default_range" + TOTAL_METRIC_SELECTED_RANGE = "total_metric_selected_range" + UNIT_METRIC_DEFAULT_LAST_N = "unit_metric_default_last_n" + UNIT_METRIC_SELECTED_DATES = "unit_metric_selected_dates" + + +class ResponseCurveCalculator: + def __init__( + self, + mmm_data: MMMData, + model_outputs: ModelOutputs, + hyperparameter: Hyperparameters, + ): + self.logger = logging.getLogger(__name__) + self.logger.debug( + "Initializing ResponseCurveCalculator with data: %s", mmm_data + ) + self.mmm_data: MMMData = mmm_data + self.model_outputs: ModelOutputs = model_outputs + self.hyperparameter: Hyperparameters = hyperparameter + self.transformation = Transformation(mmm_data) + self.logger.debug("ResponseCurveCalculator initialized successfully") + + def calculate_response( + self, + select_model: str, + metric_name: str, + metric_value: Optional[Union[float, list[float]]] = None, + date_range: Optional[str] = None, + quiet: bool = False, + dt_hyppar: pd.DataFrame = pd.DataFrame(), + dt_coef: pd.DataFrame = pd.DataFrame(), + ) -> ResponseOutput: + self.logger.debug("Starting response calculation for metric: %s", metric_name) + self.logger.debug( + "Input parameters - model: %s, date_range: %s", select_model, date_range + ) + + # Determine the use case based on input parameters + usecase = self._which_usecase(metric_value, date_range) + self.logger.debug("Determined use case: %s", usecase) + + # Check the metric type + metric_type = self._check_metric_type(metric_name) + self.logger.debug("Metric type: %s", metric_type) + + all_dates = self.mmm_data.data[self.mmm_data.mmmdata_spec.date_var] + all_values = self.mmm_data.data[metric_name] + + # Process date range and metric values + try: + ds_list = self._check_metric_dates(date_range, all_dates, quiet) + self.logger.debug("Date range processed: %s", ds_list) + + val_list = self._check_metric_value( + metric_value, metric_name, all_values, ds_list.metric_loc + ) + self.logger.debug("Metric values processed: %s", val_list) + except ValueError as e: + self.logger.error("Error processing dates or values: %s", e) + raise + + date_range_updated = ds_list.date_range_updated + metric_value_updated = val_list.metric_value_updated + all_values_updated = val_list.all_values_updated + + # Transform exposure to spend if necessary + if metric_type == "exposure": + self.logger.debug( + "Transforming exposure to spend for metric: %s", metric_name + ) + all_values_updated = self._transform_exposure_to_spend( + metric_name, + metric_value_updated, + all_values_updated, + ds_list.metric_loc, + ) + hpm_name = self._get_spend_name(metric_name) + else: + hpm_name = metric_name + + self.logger.debug("Processing media vector for metric: %s", metric_name) + media_vec_origin = self.mmm_data.data[metric_name] + + # Apply adstock transformation + adstockType = self.hyperparameter.adstock + channel_hyperparams = self._get_channel_hyperparams( + select_model, hpm_name, dt_hyppar + ) + self.logger.debug("Applying adstock transformation with type: %s", adstockType) + + try: + x_list = self.transformation.transform_adstock( + media_vec_origin, adstockType, channel_hyperparams + ) + x_list_sim = self.transformation.transform_adstock( + all_values_updated, adstockType, channel_hyperparams + ) + except Exception as e: + self.logger.error("Error in adstock transformation: %s", e) + raise + + media_vec_sim = x_list_sim.x_decayed + input_total = media_vec_sim[ds_list.metric_loc] + + if self.hyperparameter.adstock == AdstockType.WEIBULL_PDF: + self.logger.debug("Processing Weibull PDF adstock") + media_vec_sim_imme = x_list_sim.x_imme + input_immediate = media_vec_sim_imme[ds_list.metric_loc] + else: + input_immediate = x_list_sim.x[ds_list.metric_loc] + input_carryover = input_total - input_immediate + + # Apply saturation transformation + self.logger.debug("Applying saturation transformation") + hill_params = self._get_saturation_params(select_model, hpm_name, dt_hyppar) + + m_adstockedRW = x_list.x_decayed[ + self.mmm_data.mmmdata_spec.rolling_window_start_which : self.mmm_data.mmmdata_spec.rolling_window_end_which + ] + + try: + if usecase == UseCase.ALL_HISTORICAL_VEC: + self.logger.debug("Processing historical vector saturation") + metric_saturated_total = self.transformation.saturation_hill( + m_adstockedRW, hill_params.alphas[0], hill_params.gammas[0] + ) + metric_saturated_carryover = self.transformation.saturation_hill( + m_adstockedRW, hill_params.alphas[0], hill_params.gammas[0] + ) + else: + metric_saturated_total = self.transformation.saturation_hill( + m_adstockedRW, + hill_params.alphas[0], + hill_params.gammas[0], + x_marginal=input_total, + ) + metric_saturated_carryover = self.transformation.saturation_hill( + m_adstockedRW, + hill_params.alphas[0], + hill_params.gammas[0], + x_marginal=input_carryover, + ) + except Exception as e: + self.logger.error("Error in saturation transformation: %s", e) + raise + + metric_saturated_immediate = metric_saturated_total - metric_saturated_carryover + + # Calculate final response values + self.logger.debug("Calculating final response values") + try: + coeff = dt_coef[ + (dt_coef["sol_id"] == select_model) & (dt_coef["rn"] == hpm_name) + ]["coef"].values[0] + + m_saturated = self.transformation.saturation_hill( + m_adstockedRW, hill_params.alphas[0], hill_params.gammas[0] + ) + m_response = m_saturated * coeff + response_total = metric_saturated_total * coeff + response_carryover = metric_saturated_carryover * coeff + response_immediate = response_total - response_carryover + except Exception as e: + self.logger.error("Error calculating final response values: %s", e) + raise + + response_output = ResponseOutput( + metric_name=metric_name, + date=date_range_updated, + input_total=input_total, + input_carryover=input_carryover, + input_immediate=input_immediate, + response_data=m_response, + response_total=response_total, + response_carryover=response_carryover, + response_immediate=response_immediate, + usecase=usecase, + ) + + self.logger.debug( + "Response calculation completed successfully: %s", response_output + ) + return response_output + + def _which_usecase( + self, + metric_value: Optional[Union[float, list[float]]], + date_range: Optional[str], + ) -> UseCase: + self.logger.debug( + "Determining use case - metric_value type: %s, date_range: %s", + type(metric_value) if metric_value is not None else None, + date_range, + ) + + try: + if metric_value is None: + usecase = ( + UseCase.ALL_HISTORICAL_VEC + if date_range is None or date_range == "all" + else UseCase.SELECTED_HISTORICAL_VEC + ) + elif isinstance(metric_value, (int, float)): + usecase = ( + UseCase.TOTAL_METRIC_DEFAULT_RANGE + if date_range is None + else UseCase.TOTAL_METRIC_SELECTED_RANGE + ) + elif isinstance(metric_value, (list, np.ndarray)): + usecase = ( + UseCase.UNIT_METRIC_DEFAULT_LAST_N + if date_range is None + else UseCase.UNIT_METRIC_SELECTED_DATES + ) + else: + raise ValueError(f"Invalid metric_value type: {type(metric_value)}") + + self.logger.debug("Use case determined: %s", usecase) + return usecase + except Exception as e: + self.logger.error("Error determining use case: %s", e) + raise + + def _check_metric_type( + self, metric_name: str + ) -> Literal["spend", "exposure", "organic"]: + self.logger.debug("Checking metric type for: %s", metric_name) + + try: + if metric_name in self.mmm_data.mmmdata_spec.paid_media_spends: + metric_type = "spend" + elif metric_name in self.mmm_data.mmmdata_spec.paid_media_vars: + metric_type = "exposure" + elif metric_name in self.mmm_data.mmmdata_spec.organic_vars: + metric_type = "organic" + else: + self.logger.error("Unknown metric type for: %s", metric_name) + raise ValueError(f"Unknown metric type for {metric_name}") + + self.logger.debug("Metric type determined: %s", metric_type) + return metric_type + except Exception as e: + self.logger.error("Error checking metric type: %s", e) + raise + + # [Previous code remains the same until _check_metric_type...] + + def _check_metric_dates( + self, date_range: Optional[str], all_dates: pd.Series, quiet: bool + ) -> MetricDateInfo: + self.logger.debug("Checking metric dates - date_range: %s", date_range) + + try: + start_rw = self.mmm_data.mmmdata_spec.rolling_window_start_which + end_rw = self.mmm_data.mmmdata_spec.rolling_window_end_which + + if date_range == "all" or date_range is None: + self.logger.debug("Using full date range") + metric_loc = slice(start_rw, end_rw) + date_range_updated = all_dates[metric_loc] + elif isinstance(date_range, str) and date_range.startswith("last_"): + n_periods = int(date_range.split("_")[1]) + self.logger.debug("Using last %d periods", n_periods) + metric_loc = slice(end_rw - n_periods, end_rw) + date_range_updated = all_dates[metric_loc] + elif isinstance(date_range, list) and len(date_range) == 2: + start_date, end_date = pd.to_datetime(date_range) + self.logger.debug( + "Using custom date range: %s to %s", start_date, end_date + ) + metric_loc = (all_dates >= start_date) & (all_dates <= end_date) + date_range_updated = all_dates[metric_loc] + else: + self.logger.error("Invalid date_range format: %s", date_range) + raise ValueError(f"Invalid date_range: {date_range}") + + if not quiet: + self.logger.debug( + "Date range selected: %s to %s", + date_range_updated.iloc[0], + date_range_updated.iloc[-1], + ) + + result = MetricDateInfo( + metric_loc=metric_loc, date_range_updated=date_range_updated + ) + self.logger.debug("Metric dates processed: %s", result) + return result + + except Exception as e: + self.logger.error("Error processing metric dates: %s", e) + raise + + def _check_metric_value( + self, + metric_value: Optional[Union[float, list[float]]], + metric_name: str, + all_values: pd.Series, + metric_loc: Union[slice, pd.Series], + ) -> MetricValueInfo: + self.logger.debug( + "Checking metric value for %s - value type: %s", + metric_name, + type(metric_value) if metric_value is not None else None, + ) + + try: + if metric_value is None: + self.logger.debug("Using existing values from data") + metric_value_updated = all_values[metric_loc] + elif isinstance(metric_value, (int, float)): + self.logger.debug("Using constant value: %f", metric_value) + metric_value_updated = np.full( + len(all_values[metric_loc]), metric_value + ) + else: + self.logger.debug( + "Using provided value array of length %d", len(metric_value) + ) + metric_value_updated = np.array(metric_value) + if len(metric_value_updated) != len(all_values[metric_loc]): + self.logger.error( + "Length mismatch: metric_value length=%d, expected length=%d", + len(metric_value_updated), + len(all_values[metric_loc]), + ) + raise ValueError( + f"Length of metric_value ({len(metric_value_updated)}) does not match " + f"the selected date range ({len(all_values[metric_loc])})" + ) + + all_values_updated = all_values.copy() + all_values_updated[metric_loc] = metric_value_updated + + result = MetricValueInfo( + metric_value_updated=metric_value_updated, + all_values_updated=all_values_updated, + ) + self.logger.debug("Metric value processing complete: %s", result) + return result + + except Exception as e: + self.logger.error("Error processing metric value: %s", e) + raise + + def _transform_exposure_to_spend( + self, + metric_name: str, + metric_value_updated: np.ndarray, + all_values_updated: pd.Series, + metric_loc: Union[slice, pd.Series], + ) -> pd.Series: + self.logger.debug("Transforming exposure to spend for metric: %s", metric_name) + + try: + spend_name = self._get_spend_name(metric_name) + spend_expo_mod = self.mmm_data.mmmdata_spec.modNLS["results"] + temp = spend_expo_mod[spend_expo_mod["channel"] == metric_name] + + self.logger.debug( + "Found model parameters - rsq_nls: %f, rsq_lm: %f", + temp["rsq_nls"].values[0], + temp["rsq_lm"].values[0], + ) + + if temp["rsq_nls"].values[0] > temp["rsq_lm"].values[0]: + self.logger.debug("Using non-linear least squares model") + Vmax = temp["Vmax"].values[0] + Km = temp["Km"].values[0] + input_immediate = ( + Km * metric_value_updated / (Vmax - metric_value_updated) + ) + else: + self.logger.debug("Using linear model") + coef_lm = temp["coef_lm"].values[0] + input_immediate = metric_value_updated / coef_lm + + all_values_updated[metric_loc] = input_immediate + self.logger.debug("Exposure to spend transformation complete") + return all_values_updated + + except Exception as e: + self.logger.error("Error transforming exposure to spend: %s", e) + raise + + def _get_spend_name(self, metric_name: str) -> str: + self.logger.debug("Getting spend name for metric: %s", metric_name) + try: + spend_name = self.mmm_data.mmmdata_spec.paid_media_spends[ + self.mmm_data.mmmdata_spec.paid_media_vars.index(metric_name) + ] + self.logger.debug("Found spend name: %s", spend_name) + return spend_name + except Exception as e: + self.logger.error("Error getting spend name: %s", e) + raise + + def _get_channel_hyperparams( + self, select_model: str, hpm_name: str, dt_hyppar: pd.DataFrame + ) -> ChannelHyperparameters: + self.logger.debug( + "Getting channel hyperparameters for model: %s, metric: %s", + select_model, + hpm_name, + ) + + try: + adstock_type = self.hyperparameter.adstock + params = ChannelHyperparameters() + + if adstock_type == AdstockType.GEOMETRIC: + self.logger.debug("Using geometric adstock type") + params.thetas = dt_hyppar[dt_hyppar["sol_id"] == select_model][ + f"{hpm_name}_thetas" + ].values + elif adstock_type in [ + AdstockType.WEIBULL, + AdstockType.WEIBULL_CDF, + AdstockType.WEIBULL_PDF, + ]: + self.logger.debug("Using Weibull adstock type: %s", adstock_type) + params.shapes = dt_hyppar[dt_hyppar["sol_id"] == select_model][ + f"{hpm_name}_shapes" + ].values + params.scales = dt_hyppar[dt_hyppar["sol_id"] == select_model][ + f"{hpm_name}_scales" + ].values + + self.logger.debug("Channel hyperparameters retrieved successfully") + return params + + except Exception as e: + self.logger.error("Error getting channel hyperparameters: %s", e) + raise + + def _get_saturation_params( + self, select_model: str, hpm_name: str, dt_hyppar: pd.DataFrame + ) -> ChannelHyperparameters: + self.logger.debug( + "Getting saturation parameters for model: %s, metric: %s", + select_model, + hpm_name, + ) + + try: + params = ChannelHyperparameters() + params.alphas = dt_hyppar[dt_hyppar["sol_id"] == select_model][ + f"{hpm_name}_alphas" + ].values + params.gammas = dt_hyppar[dt_hyppar["sol_id"] == select_model][ + f"{hpm_name}_gammas" + ].values + + self.logger.debug( + "Saturation parameters - alphas: %s, gammas: %s", + params.alphas, + params.gammas, + ) + return params + + except Exception as e: + self.logger.error("Error getting saturation parameters: %s", e) + raise + + def run_dt_resp(self, row: pd.Series, paretoData: ParetoData) -> pd.Series: + """ + Calculate response curves for a given row of Pareto data. + This method is used for parallel processing. + + Args: + row (pd.Series): A row of Pareto data. + paretoData (ParetoData): Pareto data. + + Returns: + pd.Series: A pandas series containing the row of response curves. + """ + try: + get_sol_id = row["sol_id"] + get_spendname = row["rn"] + startRW = self.mmm_data.mmmdata_spec.rolling_window_start_which + endRW = self.mmm_data.mmmdata_spec.rolling_window_end_which + + response_output: ResponseOutput = self.calculate_response( + select_model=get_sol_id, + metric_name=get_spendname, + date_range="all", + dt_hyppar=paretoData.result_hyp_param, + dt_coef=paretoData.x_decomp_agg, + quiet=True, + ) + + mean_spend_adstocked = np.mean(response_output.input_total[startRW:endRW]) + mean_carryover = np.mean(response_output.input_carryover[startRW:endRW]) + + dt_hyppar = paretoData.result_hyp_param[ + paretoData.result_hyp_param["sol_id"] == get_sol_id + ] + chn_adstocked = pd.DataFrame( + {get_spendname: response_output.input_total[startRW:endRW]} + ) + dt_coef = paretoData.x_decomp_agg[ + (paretoData.x_decomp_agg["sol_id"] == get_sol_id) + & (paretoData.x_decomp_agg["rn"] == get_spendname) + ][["rn", "coef"]] + + hill_calculator = HillCalculator( + mmmdata=self.mmm_data, + model_outputs=self.model_outputs, + dt_hyppar=dt_hyppar, + dt_coef=dt_coef, + media_spend_sorted=[get_spendname], + select_model=get_sol_id, + chn_adstocked=chn_adstocked, + ) + hills = hill_calculator.get_hill_params() + + mean_response = ParetoUtils.calculate_fx_objective( + x=row["mean_spend"], + coeff=hills["coefs_sorted"][0], + alpha=hills["alphas"][0], + inflexion=hills["inflexions"][0], + x_hist_carryover=mean_carryover, + get_sum=False, + ) + + return pd.Series( + { + "mean_response": mean_response, + "mean_spend_adstocked": mean_spend_adstocked, + "mean_carryover": mean_carryover, + "rn": row["rn"], + "sol_id": row["sol_id"], + } + ) + except Exception as e: + print( + f"Error processing row for sol_id {row.get('sol_id', 'unknown')}, " + f"rn {row.get('rn', 'unknown')}: {str(e)}" + ) + return None + + def compute_response_curves( + self, pareto_data: ParetoData, aggregated_data: Dict[str, pd.DataFrame] + ) -> ParetoData: + """ + Calculate response curves for Pareto-optimal solutions. + + This method computes response curves for each media channel in each Pareto-optimal solution, + providing insights into the relationship between media spend and response. + + Args: + pareto_data (ParetoData): Pareto data. + + Returns: + ParetoData: Pareto data with updated decomp_spend_dist and x_decomp_agg. + """ + if pareto_data.decomp_spend_dist.empty: + self.logger.warning( + "No data in decomp_spend_dist. Skipping response curves calculation." + ) + return pareto_data + self.logger.info( + f"Calculating response curves for {len(pareto_data.decomp_spend_dist)} models' media variables..." + ) + self.logger.debug( + f"Available columns: {pareto_data.decomp_spend_dist.columns.tolist()}" + ) + resp_collect_list = [] + try: + try: + batch = pareto_data.decomp_spend_dist + if self.model_outputs.cores > 1: + self.logger.debug( + f"Calculating response curves with {self.model_outputs.cores} cores" + ) + run_dt_resp_partial = partial( + self.run_dt_resp, paretoData=pareto_data + ) + + with ThreadPoolExecutor( + max_workers=self.model_outputs.cores + ) as executor: + futures = { + executor.submit(run_dt_resp_partial, row): row + for _, row in pareto_data.decomp_spend_dist.iterrows() + } + results = [] + for future in tqdm( + as_completed(futures), + total=len(futures), + desc="Processing rows", + ): + try: + result = future.result() + if result is not None: + results.append(result) + except Exception as e: + self.logger.error( + f"Error calculating response curves with multiple cores: {str(e)}" + ) + continue + if results: + resp_collect_batch = pd.DataFrame(results) + resp_collect_list.append(resp_collect_batch) + else: + # Run sequentially + results = [] + for _, row in batch.iterrows(): + try: + result = self.run_dt_resp(row, paretoData=pareto_data) + if result is not None: + results.append(result) + except Exception as e: + self.logger.error( + f"Error processing row while calculating response curves: {str(e)}" + ) + continue + if results: + resp_collect_batch = pd.DataFrame(results) + resp_collect_list.append(resp_collect_batch) + except Exception as e: + self.logger.error(f"Error processing batches: {str(e)}") + if not resp_collect_list: + self.logger.warning("No response curves were calculated successfully") + return pareto_data + + resp_collect = pd.concat(resp_collect_list, ignore_index=True) + # Merge results + self.logger.info( + f"Successfully processed {len(resp_collect)} response curves" + ) + self.logger.info("Computing final metrics...") + pareto_data.decomp_spend_dist = pd.merge( + pareto_data.decomp_spend_dist, + resp_collect, + on=["sol_id", "rn"], + how="left", + ) + + # Calculate ROI and CPA metrics after merging + self.logger.info("Calculating ROI and CPA metrics...") + self._calculate_roi_and_cpa(pareto_data) + + pareto_data.x_decomp_agg = pd.merge( + aggregated_data["x_decomp_agg"], + pareto_data.decomp_spend_dist[ + [ + "rn", + "sol_id", + "total_spend", + "mean_spend", + "mean_spend_adstocked", + "mean_carryover", + "mean_response", + "spend_share", + "effect_share", + "roi_mean", + "roi_total", + "cpa_total", + ] + ], + on=["sol_id", "rn"], + how="left", + ) + self.logger.info( + "Final Pareto Data updated with response curves:\nDecomp Spend Distribution:\n" + ) + RobynLogger.log_df(self.logger, pareto_data.decomp_spend_dist, logging.INFO) + self.logger.info("X Spend Aggregated with response curves:\n") + RobynLogger.log_df(self.logger, pareto_data.x_decomp_agg, logging.INFO) + self.logger.info("Response curves calculated successfully") + + return pareto_data + + except Exception as e: + self.logger.error(f"Error in response curves calculation: {str(e)}") + self.logger.debug( + f"decomp_spend_dist shape: {pareto_data.decomp_spend_dist.shape}" + ) + self.logger.debug( + f"decomp_spend_dist columns: {pareto_data.decomp_spend_dist.columns.tolist()}" + ) + self.logger.debug( + f"Number of response collect batches: {len(resp_collect_list)}" + ) + raise + + def _calculate_roi_and_cpa(self, pareto_data: ParetoData): + pareto_data.decomp_spend_dist["roi_mean"] = ( + pareto_data.decomp_spend_dist["mean_response"] + / pareto_data.decomp_spend_dist["mean_spend"] + ) + pareto_data.decomp_spend_dist["roi_total"] = ( + pareto_data.decomp_spend_dist["xDecompAgg"] + / pareto_data.decomp_spend_dist["total_spend"] + ) + pareto_data.decomp_spend_dist["cpa_mean"] = ( + pareto_data.decomp_spend_dist["mean_spend"] + / pareto_data.decomp_spend_dist["mean_response"] + ) + pareto_data.decomp_spend_dist["cpa_total"] = ( + pareto_data.decomp_spend_dist["total_spend"] + / pareto_data.decomp_spend_dist["xDecompAgg"] + ) diff --git a/python/src/robyn/modeling/ridge/ridge_data_builder.py b/python/src/robyn/modeling/ridge/ridge_data_builder.py new file mode 100644 index 000000000..b4988487e --- /dev/null +++ b/python/src/robyn/modeling/ridge/ridge_data_builder.py @@ -0,0 +1,184 @@ +import logging +from typing import Any, Dict, Optional, Tuple +import pandas as pd +import numpy as np +from scipy.signal import lfilter + + +class RidgeDataBuilder: + def __init__(self, mmm_data, featurized_mmm_data): + self.mmm_data = mmm_data + self.featurized_mmm_data = featurized_mmm_data + self.logger = logging.getLogger(__name__) + + def _prepare_data(self, params: Dict[str, float]) -> Tuple[pd.DataFrame, pd.Series]: + # Get the dependent variable + # Check if 'dep_var' is in columns + if "dep_var" in self.featurized_mmm_data.dt_mod.columns: + # Rename 'dep_var' to the specified value + self.featurized_mmm_data.dt_mod = self.featurized_mmm_data.dt_mod.rename( + columns={"dep_var": self.mmm_data.mmmdata_spec.dep_var} + ) + y = self.featurized_mmm_data.dt_mod[self.mmm_data.mmmdata_spec.dep_var] + + # Select all columns except the dependent variable + X = self.featurized_mmm_data.dt_mod.drop( + columns=[self.mmm_data.mmmdata_spec.dep_var] + ) + + # Convert date columns to numeric (number of days since the earliest date) + date_columns = X.select_dtypes(include=["datetime64", "object"]).columns + for col in date_columns: + X[col] = pd.to_datetime(X[col], errors="coerce", format="%Y-%m-%d") + # Fill NaT (Not a Time) values with a default date (e.g., the minimum date in the column) + min_date = X[col].min() + X[col] = X[col].fillna(min_date) + # Convert to days since minimum date, handling potential NaT values + X[col] = ( + (X[col] - min_date).dt.total_seconds().div(86400).fillna(0).astype(int) + ) + + # One-hot encode categorical variables + categorical_columns = X.select_dtypes(include=["object", "category"]).columns + X = pd.get_dummies(X, columns=categorical_columns, drop_first=True) + + # Ensure all columns are numeric + X = X.select_dtypes(include=[np.number]) + + # Apply transformations based on hyperparameters + for media in self.mmm_data.mmmdata_spec.paid_media_spends: + if f"{media}_thetas" in params: + X[media] = self._geometric_adstock(X[media], params[f"{media}_thetas"]) + if f"{media}_alphas" in params and f"{media}_gammas" in params: + X[media] = self._hill_transformation( + X[media], params[f"{media}_alphas"], params[f"{media}_gammas"] + ) + + # Handle any remaining NaN or infinite values + X = X.replace([np.inf, -np.inf], np.nan).fillna(0) + y = y.replace([np.inf, -np.inf], np.nan).fillna(y.mean()) + X = X + 1e-8 * np.random.randn(*X.shape) + + return X, y + + @staticmethod + def safe_astype(df: pd.DataFrame, type_dict: Dict[str, str]) -> pd.DataFrame: + """Only cast columns that exist in the DataFrame""" + existing_cols = { + col: dtype for col, dtype in type_dict.items() if col in df.columns + } + return df.astype(existing_cols) if existing_cols else df + + def _format_hyperparameter_names( + self, params: Dict[str, float] + ) -> Dict[str, float]: + """Format hyperparameter names to match R's naming convention.""" + formatted = {} + for param_name, value in params.items(): + if param_name == "lambda" or param_name == "train_size": + formatted[param_name] = value + else: + # Split parameter name into media and param type + # E.g., facebook_S_alphas -> (facebook_S, alphas) + media, param_type = param_name.rsplit("_", 1) + if param_type in ["alphas", "gammas", "thetas", "shapes", "scales"]: + formatted[f"{media}_{param_type}"] = value + else: + formatted[param_name] = value + return formatted + + @staticmethod + def _hyper_collector( + hyperparameters: Dict[str, Any], + ts_validation: bool, + add_penalty_factor: bool, + dt_hyper_fixed: Optional[pd.DataFrame], + cores: Optional[int], + ) -> Dict[str, Any]: + """ + Collect and organize hyperparameters to match R's structure + """ + logger = logging.getLogger(__name__) + logger.info("Collecting hyperparameters for optimization...") + prepared_hyperparameters = hyperparameters["prepared_hyperparameters"] + hyper_collect = { + "hyper_list_all": {}, + "hyper_bound_list_updated": {}, + "hyper_bound_list_fixed": {}, + "all_fixed": False, + } + + # Adjust hyper_list_all to store lists + for channel, channel_params in prepared_hyperparameters.hyperparameters.items(): + for param in ["thetas", "alphas", "gammas"]: + param_value = getattr(channel_params, param, None) + if param_value is not None: + if isinstance(param_value, list) and len(param_value) == 2: + param_key = f"{channel}_{param}" + hyper_collect["hyper_bound_list_updated"][ + param_key + ] = param_value + hyper_collect["hyper_list_all"][ + f"{channel}_{param}" + ] = param_value # Store as list + elif not isinstance(param_value, list): + hyper_collect["hyper_bound_list_fixed"][ + f"{channel}_{param}" + ] = param_value + hyper_collect["hyper_list_all"][f"{channel}_{param}"] = [ + param_value, + param_value, + ] # Store as list + # Handle lambda parameter similarly + if ( + isinstance(prepared_hyperparameters.lambda_, list) + and len(prepared_hyperparameters.lambda_) == 2 + ): + hyper_collect["hyper_bound_list_updated"][ + "lambda" + ] = prepared_hyperparameters.lambda_ + hyper_collect["hyper_list_all"]["lambda"] = prepared_hyperparameters.lambda_ + else: + hyper_collect["hyper_bound_list_fixed"][ + "lambda" + ] = prepared_hyperparameters.lambda_ + hyper_collect["hyper_list_all"]["lambda"] = [ + prepared_hyperparameters.lambda_, + prepared_hyperparameters.lambda_, + ] + # Handle train_size similarly + if ts_validation: + if ( + isinstance(prepared_hyperparameters.train_size, list) + and len(prepared_hyperparameters.train_size) == 2 + ): + hyper_collect["hyper_bound_list_updated"][ + "train_size" + ] = prepared_hyperparameters.train_size + hyper_collect["hyper_list_all"][ + "train_size" + ] = prepared_hyperparameters.train_size + else: + train_size = [0.5, 0.8] + hyper_collect["hyper_bound_list_updated"]["train_size"] = train_size + hyper_collect["hyper_list_all"]["train_size"] = train_size + else: + hyper_collect["hyper_list_all"]["train_size"] = [1.0, 1.0] + return hyper_collect + + def _geometric_adstock(self, x: pd.Series, theta: float) -> pd.Series: + + x_array = x.values + # Use lfilter to efficiently compute the geometric transformation + y = lfilter([1], [1, -theta], x_array) + return pd.Series(y, index=x.index) + + def _hill_transformation( + self, x: pd.Series, alpha: float, gamma: float + ) -> pd.Series: + # Add debug self.logger.debugs + # print(f"Before hill: {x.head()}") + x_scaled = (x - x.min()) / (x.max() - x.min()) + result = x_scaled**alpha / (x_scaled**alpha + gamma**alpha) + # print(f"After hill: {result.head()}") + return result diff --git a/python/src/robyn/modeling/ridge/ridge_evaluate_model.py b/python/src/robyn/modeling/ridge/ridge_evaluate_model.py new file mode 100644 index 000000000..b58425402 --- /dev/null +++ b/python/src/robyn/modeling/ridge/ridge_evaluate_model.py @@ -0,0 +1,378 @@ +import pandas as pd +import numpy as np +import nevergrad as ng +import time +import warnings +from tqdm import tqdm +from sklearn.linear_model import Ridge +from sklearn.exceptions import ConvergenceWarning +from typing import Dict, Any, Tuple, Optional, List +from robyn.modeling.entities.modeloutputs import Trial +from robyn.modeling.entities.enums import NevergradAlgorithm +from robyn.modeling.ridge.ridge_metrics_calculator import RidgeMetricsCalculator +import logging + + +class RidgeModelEvaluator: + + def __init__( + self, + mmm_data, + featurized_mmm_data, + ridge_metrics_calculator, + ridge_data_builder, + ): + self.mmm_data = mmm_data + self.featurized_mmm_data = featurized_mmm_data + self.ridge_metrics_calculator = ridge_metrics_calculator + self.ridge_data_builder = ridge_data_builder + self.logger = logging.getLogger(__name__) + + def _run_nevergrad_optimization( + self, + hyper_collect: Dict[str, Any], + iterations: int, + cores: int, + nevergrad_algo: NevergradAlgorithm, + intercept: bool, + intercept_sign: str, + ts_validation: bool, + add_penalty_factor: bool, + objective_weights: Optional[List[float]], + dt_hyper_fixed: Optional[pd.DataFrame], + rssd_zero_penalty: bool, + trial: int, + seed: int, + total_trials: int, + ) -> Trial: + warnings.filterwarnings("ignore", category=ConvergenceWarning) + warnings.filterwarnings("ignore", category=RuntimeWarning) + + np.random.seed(seed) + + param_names = list(hyper_collect["hyper_bound_list_updated"].keys()) + param_bounds = [ + hyper_collect["hyper_bound_list_updated"][name] for name in param_names + ] + + instrum_dict = { + name: ng.p.Scalar(lower=bound[0], upper=bound[1]) + for name, bound in zip(param_names, param_bounds) + } + + instrum = ng.p.Instrumentation(**instrum_dict) + optimizer = ng.optimizers.registry[nevergrad_algo.value]( + instrum, budget=iterations, num_workers=cores + ) + + all_results = [] + start_time = time.time() + + with tqdm( + total=iterations, + desc=f"Running trial {trial} of total {total_trials} trials", + bar_format="{l_bar}{bar}", + ncols=75, + ) as pbar: + for iter_ng in range(iterations): + candidate = optimizer.ask() + params = candidate.kwargs + + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + result = self._evaluate_model( + params, + ts_validation, + add_penalty_factor, + rssd_zero_penalty, + objective_weights, + start_time=start_time, + iter_ng=iter_ng, + trial=trial, + ) + + optimizer.tell(candidate, result["loss"]) + + # Important: Convert metrics to correct types + sol_id = f"{trial}_{iter_ng + 1}_1" + result["params"].update( + { + "sol_id": sol_id, + "ElapsedAccum": result["elapsed_accum"], + "trial": int(trial), + "rsq_train": float(result["rsq_train"]), + "rsq_val": float(result["rsq_val"]), + "rsq_test": float(result["rsq_test"]), + "nrmse": float(result["nrmse"]), + "nrmse_train": float(result["nrmse_train"]), + "nrmse_val": float(result["nrmse_val"]), + "nrmse_test": float(result["nrmse_test"]), + "decomp.rssd": float(result["decomp_rssd"]), + "mape": float(result["mape"]), + "lambda": float( + result["lambda"] + ), # Critical: Using lambda not lambda_ + "lambda_hp": float(result["lambda_hp"]), + "lambda_max": float(result["lambda_max"]), + "lambda_min_ratio": float(result["lambda_min_ratio"]), + "iterNG": int(iter_ng + 1), + "iterPar": 1, + } + ) + + all_results.append(result) + pbar.update(1) + + end_time = time.time() + self.logger.info(f" Finished in {(end_time - start_time) / 60:.2f} mins") + + # Aggregate results with explicit dtypes + result_hyp_param = pd.DataFrame([r["params"] for r in all_results]).astype( + { + "sol_id": "str", + "trial": "int64", + "iterNG": "int64", + "iterPar": "int64", + "nrmse": "float64", + "decomp.rssd": "float64", + "mape": "float64", + "lambda": "float64", + "lambda_hp": "float64", + "lambda_max": "float64", + "lambda_min_ratio": "float64", + "rsq_train": "float64", + "rsq_val": "float64", + "rsq_test": "float64", + } + ) + + decomp_spend_dist = pd.concat( + [r["decomp_spend_dist"] for r in all_results], ignore_index=True + ) + x_decomp_agg = pd.concat( + [r["x_decomp_agg"] for r in all_results], ignore_index=True + ) + + # Ensure correct dtypes in decomp_spend_dist and x_decomp_agg + decomp_spend_dist = decomp_spend_dist.astype( + { + "rn": "str", + "coef": "float64", + "total_spend": "float64", + "mean_spend": "float64", + "effect_share": "float64", + "spend_share": "float64", + "sol_id": "str", + } + ) + + x_decomp_agg = x_decomp_agg.astype( + { + "rn": "str", + "coef": "float64", + "xDecompAgg": "float64", + "xDecompPerc": "float64", + "sol_id": "str", + } + ) + + # Find best result based on loss + best_result = min(all_results, key=lambda x: x["loss"]) + # Convert values to Series before passing to Trial + return Trial( + result_hyp_param=result_hyp_param, + lift_calibration=best_result.get("lift_calibration", pd.DataFrame()), + decomp_spend_dist=decomp_spend_dist, + x_decomp_agg=x_decomp_agg, + nrmse=pd.Series([float(best_result["nrmse"])]), + decomp_rssd=pd.Series([float(best_result["decomp_rssd"])]), + mape=pd.Series([int(best_result["mape"])]), # Cast to int + rsq_train=pd.Series([float(best_result["rsq_train"])]), + rsq_val=pd.Series([float(best_result["rsq_val"])]), + rsq_test=pd.Series([float(best_result["rsq_test"])]), + lambda_=pd.Series([float(best_result["lambda"])]), + lambda_hp=pd.Series([float(best_result["lambda_hp"])]), + lambda_max=pd.Series([float(best_result["lambda_max"])]), + lambda_min_ratio=pd.Series([float(best_result["lambda_min_ratio"])]), + pos=pd.Series([int(best_result.get("pos", 0))]), # Cast to int + elapsed=pd.Series([float(best_result["elapsed"])]), + elapsed_accum=pd.Series([float(best_result["elapsed_accum"])]), + trial=pd.Series([int(trial)]), + iter_ng=pd.Series([int(best_result["iter_ng"])]), + iter_par=pd.Series([int(best_result["iter_par"])]), + train_size=pd.Series([float(best_result["params"].get("train_size", 1.0))]), + sol_id=str(best_result["params"]["sol_id"]), + ) + + def _evaluate_model( + self, + params: Dict[str, float], + ts_validation: bool, + add_penalty_factor: bool, + rssd_zero_penalty: bool, + objective_weights: Optional[List[float]], + start_time: float, + iter_ng: int, + trial: int, + ) -> Dict[str, Any]: + """Evaluate model with parameter set matching R's implementation exactly""" + X, y = self.ridge_data_builder._prepare_data(params) + sol_id = f"{trial}_{iter_ng + 1}_1" + # After preparing data + self.logger.debug(f"Data shapes - X: {X.shape}, y: {y.shape}") + self.logger.debug(f"Sample of X values: {X.head()}") + self.logger.debug(f"Sample of y values: {y.head()}") + + # Debug is True by default now + debug = True + + if debug and (iter_ng == 0 or iter_ng % 25 == 0): + self.logger.debug( + f"\nEvaluation Debug (trial {trial}, iteration {iter_ng}):" + ) + self.logger.debug(f"X shape: {X.shape}") + self.logger.debug(f"y shape: {y.shape}") + self.logger.debug("Parameters:", params) + + # Split data using R's approach + train_size = params.get("train_size", 1.0) if ts_validation else 1.0 + train_idx = int(len(X) * train_size) + + metrics = {} + if ts_validation: + val_test_size = (len(X) - train_idx) // 2 + X_train = X.iloc[:train_idx] + y_train = y.iloc[:train_idx] + X_val = X.iloc[train_idx : train_idx + val_test_size] + y_val = y.iloc[train_idx : train_idx + val_test_size] + X_test = X.iloc[train_idx + val_test_size :] + y_test = y.iloc[train_idx + val_test_size :] + else: + X_train, y_train = X, y + X_val = X_test = y_val = y_test = None + + x_norm = X_train.to_numpy() + y_norm = y_train.to_numpy() + + # Calculate lambda using R-matching helper function + lambda_hp = params.get("lambda", 1.0) + lambda_, lambda_max = self.ridge_metrics_calculator._calculate_lambda( + x_norm, y_norm, lambda_hp, debug=debug, iteration=iter_ng + ) + # After calculating lambda + self.logger.debug(f"Lambda calculation debug:") + self.logger.debug(f"lambda_hp: {lambda_hp}") + self.logger.debug(f"lambda_: {lambda_}") + self.logger.debug(f"lambda_max: {lambda_max}") + + # Scale inputs for model + model = Ridge(alpha=lambda_ / len(x_norm), fit_intercept=True) + model.fit(x_norm, y_norm) + + # Calculate metrics using R-style calculations + y_train_pred = model.predict(x_norm) + metrics["rsq_train"] = self.ridge_metrics_calculator.calculate_r2_score( + y_norm, y_train_pred, x_norm.shape[1] + ) + metrics["nrmse_train"] = self.ridge_metrics_calculator.calculate_nrmse( + y_norm, y_train_pred, debug=debug, iteration=iter_ng + ) + + # Validation and test metrics + if ts_validation and X_val is not None and X_test is not None: + y_val_pred = model.predict(X_val) + y_test_pred = model.predict(X_test) + + metrics["rsq_val"] = self.ridge_metrics_calculator.calculate_r2_score( + y_val, y_val_pred, X_val.shape[1] + ) + metrics["nrmse_val"] = self.ridge_metrics_calculator.calculate_nrmse( + y_val, y_val_pred + ) + + metrics["rsq_test"] = self.ridge_metrics_calculator.calculate_r2_score( + y_test, y_test_pred, X_test.shape[1] + ) + metrics["nrmse_test"] = self.ridge_metrics_calculator.calculate_nrmse( + y_test, y_test_pred + ) + + metrics["nrmse"] = metrics["nrmse_val"] + else: + metrics["rsq_val"] = metrics["rsq_test"] = 0.0 + metrics["nrmse_val"] = metrics["nrmse_test"] = 0.0 + metrics["nrmse"] = metrics["nrmse_train"] + + # Calculate RSSD + paid_media_cols = [ + col + for col in X.columns + if col in self.mmm_data.mmmdata_spec.paid_media_spends + ] + decomp_rssd = self.ridge_metrics_calculator._calculate_rssd( + model, + X_train, + paid_media_cols, + rssd_zero_penalty, + debug=debug, + iteration=iter_ng, + ) + + elapsed_time = time.time() - start_time + + # Format hyperparameter names to match R's format + params_formatted = self.ridge_data_builder._format_hyperparameter_names(params) + + # Update metrics dictionary + metrics.update( + { + "decomp_rssd": float(decomp_rssd), + "lambda": float(lambda_), + "lambda_hp": float(lambda_hp), + "lambda_max": float(lambda_max), + "lambda_min_ratio": float(0.0001), + "mape": int(0), # Cast to int as in R + "sol_id": str(sol_id), + "trial": int(trial), + "iterNG": int(iter_ng + 1), + "iterPar": int(1), + "Elapsed": float(elapsed_time), + "elapsed": float(elapsed_time), + "elapsed_accum": float(elapsed_time), + } + ) + + # Calculate decompositions + x_decomp_agg = self.ridge_metrics_calculator._calculate_x_decomp_agg( + model, X_train, y_train, {**params_formatted, **metrics} + ) + decomp_spend_dist = self.ridge_metrics_calculator._calculate_decomp_spend_dist( + model, X_train, y_train, {**metrics, "params": params_formatted} + ) + + # Calculate loss + loss = ( + objective_weights[0] * metrics["nrmse"] + + objective_weights[1] * metrics["decomp_rssd"] + + ( + objective_weights[2] * metrics["mape"] + if len(objective_weights) > 2 + else 0 + ) + ) + self.logger.debug( + f"Model coefficients range: {model.coef_.min()} to {model.coef_.max()}" + ) + self.logger.debug(f"Sample predictions: {y_train_pred[:5]}") + self.logger.debug(f"Sample actual values: {y_norm[:5]}") + return { + "loss": loss, + "params": params_formatted, + **metrics, + "decomp_spend_dist": decomp_spend_dist, + "x_decomp_agg": x_decomp_agg, + "elapsed": elapsed_time, + "elapsed_accum": elapsed_time, + "iter_ng": iter_ng + 1, + "iter_par": 1, + } diff --git a/python/src/robyn/modeling/ridge/ridge_metrics_calculator.py b/python/src/robyn/modeling/ridge/ridge_metrics_calculator.py new file mode 100644 index 000000000..f08ddc72f --- /dev/null +++ b/python/src/robyn/modeling/ridge/ridge_metrics_calculator.py @@ -0,0 +1,511 @@ +import numpy as np +import pandas as pd +from typing import Dict, Tuple, List, Any +from sklearn.linear_model import Ridge +import logging +from robyn.calibration.media_effect_calibration import MediaEffectCalibrator + + +class RidgeMetricsCalculator: + def __init__(self, mmm_data, hyperparameters, ridge_data_builder): + self.mmm_data = mmm_data + self.hyperparameters = hyperparameters + self.ridge_data_builder = ridge_data_builder + self.logger = logging.getLogger(__name__) + + def _calculate_decomp_spend_dist( + self, model: Ridge, X: pd.DataFrame, y: pd.Series, metrics: Dict[str, float] + ) -> pd.DataFrame: + """Calculate decomposition spend distribution matching R's implementation exactly.""" + paid_media_cols = [ + col + for col in X.columns + if col in self.mmm_data.mmmdata_spec.paid_media_spends + ] + + # Precompute a mapping from column names to their index in X.columns + col_to_index = {col: idx for idx, col in enumerate(X.columns)} + + # First pass to calculate total spend and effect for normalization + total_media_spend = np.abs(X[paid_media_cols].sum().sum()) + all_effects = {} + all_spends = {} + + # Calculate effects using absolute values for scaling + for col in paid_media_cols: + idx = col_to_index[col] + coef = model.coef_[idx] + spend = np.abs(X[col].sum()) # Ensure positive spend + # Use absolute values for effect calculation + effect = np.abs(coef * spend) # Changed to use absolute value + all_effects[col] = effect + all_spends[col] = spend + + total_effect = np.sum([e for e in all_effects.values()]) + + # Precompute the non-zero count per column and denominator for xDecompMeanNon0Perc. + # The denominator is the sum over paid media channels of (effect / count_non_zero) for channels with non-zero spends. + count_non_zero = {col: (X[col] != 0).sum() for col in paid_media_cols} + denom = sum( + all_effects[col] / count_non_zero[col] + for col in paid_media_cols + if count_non_zero[col] > 0 + ) + # Second pass to calculate normalized metrics + results = [] + for col in paid_media_cols: + idx = col_to_index[col] + coef = float(model.coef_[idx]) + spend = float(np.abs(all_spends[col])) + effect = float(all_effects[col]) + + # Handle non-zero values properly + non_zero_mask = X[col] != 0 + non_zero_values = X.loc[non_zero_mask, col] + non_zero_effect = np.abs( + non_zero_values * coef + ) # Changed to use absolute value + non_zero_mean = float( + non_zero_effect.mean() if len(non_zero_effect) > 0 else 0 + ) + + # Calculate normalized shares + spend_share = ( + float(spend / total_media_spend) if total_media_spend > 0 else 0 + ) + effect_share = float(effect / total_effect) if total_effect > 0 else 0 + # Calculate the percentage for non-zero mean; use precomputed denominator. + + xDecompMeanNon0Perc = float(non_zero_mean / denom) if denom > 0 else 0 + + result = { + "rn": str(col), + "coef": float(coef), + "xDecompAgg": float(effect), # This is now positive + "total_spend": float(spend), + "mean_spend": float(np.abs(X[col].mean())), + "spend_share": spend_share, + "effect_share": effect_share, + "xDecompPerc": effect_share, + "xDecompMeanNon0": non_zero_mean, + "xDecompMeanNon0Perc": xDecompMeanNon0Perc, + "pos": bool(coef >= 0), + "sol_id": str(metrics.get("sol_id", "")), + } + + # Add model performance metrics + for metric_key in [ + "rsq_train", + "rsq_val", + "rsq_test", + "nrmse", + "decomp_rssd", + "mape", + "lambda", + "lambda_hp", + "lambda_max", + "lambda_min_ratio", + ]: + result[metric_key] = float(metrics.get(metric_key, 0)) + + result.update( + { + "trial": int(metrics.get("trial", 0)), + "iterNG": int(metrics.get("iterNG", 0)), + "iterPar": int(metrics.get("iterPar", 0)), + "Elapsed": float(metrics.get("elapsed", 0)), + "pos": bool(coef >= 0), + } + ) + + results.append(result) + + df = pd.DataFrame(results) + + # Ensure correct column types and order + df = df.astype( + { + "rn": "str", + "coef": "float64", + "xDecompAgg": "float64", + "total_spend": "float64", + "mean_spend": "float64", + "effect_share": "float64", + "spend_share": "float64", + "sol_id": "str", + "pos": "bool", + "mape": "int64", + "trial": "int64", + "iterNG": "int64", + "iterPar": "int64", + } + ) + + required_cols = [ + "rn", + "coef", + "xDecompAgg", + "total_spend", + "mean_spend", + "spend_share", + "effect_share", + "sol_id", + "rsq_train", + "rsq_val", + "rsq_test", + "nrmse", + "decomp_rssd", + "mape", + "lambda", + "lambda_hp", + "lambda_max", + "lambda_min_ratio", + "trial", + "iterNG", + "iterPar", + "Elapsed", + "pos", + ] + + return df[required_cols] + + def _calculate_lambda( + self, + x_norm: np.ndarray, + y_norm: np.ndarray, + lambda_hp: float, + debug: bool = True, + iteration: int = 0, + ) -> Tuple[float, float]: + """Match R's glmnet lambda calculation exactly""" + n_samples = len(y_norm) + + # Standardize first before scale factor calculation + def r_scale(x): + mean = np.mean(x) + sd = np.sqrt(np.sum((x - mean) ** 2) / (len(x) - 1)) + return (x - mean) / (sd if sd > 1e-10 else 1.0) + + # Scale X and y first + x_scaled = np.apply_along_axis(r_scale, 0, x_norm) + y_scaled = r_scale(y_norm) + + # Now calculate scale factor using scaled data + scale_factor = np.mean(np.abs(x_scaled)) * np.mean(np.abs(y_scaled)) + + if debug and (iteration == 0 or iteration % 25 == 0): + self.logger.debug(f"\nLambda Calculation Debug (iteration {iteration}):") + self.logger.debug(f"n_samples: {n_samples}") + self.logger.debug(f"x_scaled mean abs: {np.mean(np.abs(x_scaled)):.6f}") + self.logger.debug(f"y_scaled mean abs: {np.mean(np.abs(y_scaled)):.6f}") + self.logger.debug(f"Scale factor: {scale_factor:.6f}") + self.logger.debug(f"lambda_hp: {lambda_hp:.6f}") + + # R's lambda calculation + alpha = 0.001 + gram = x_scaled.T @ x_scaled / n_samples + ctx = np.abs(x_scaled.T @ y_scaled) / n_samples + + lambda_max = np.max(ctx) / alpha + lambda_min = lambda_max * 0.0001 + lambda_ = lambda_min + lambda_hp * (lambda_max - lambda_min) + + if debug and (iteration == 0 or iteration % 25 == 0): + self.logger.debug(f"max ctx: {np.max(ctx):.6f}") + self.logger.debug(f"lambda_max: {lambda_max:.6f}") + self.logger.debug(f"lambda_min: {lambda_min:.6f}") + self.logger.debug(f"final lambda_: {lambda_:.6f}") + + return lambda_, lambda_max + + def _calculate_rssd( + self, + model: Ridge, + X: pd.DataFrame, + paid_media_cols: List[str], + rssd_zero_penalty: bool, + debug: bool = True, + iteration: int = 0, + ) -> float: + """Calculate RSSD with proper normalization""" + total_raw_spend = np.sum(np.abs(X[paid_media_cols].sum())) + effects = [] + spends = [] + + # First collect all values + for col in paid_media_cols: + idx = list(X.columns).index(col) + coef = model.coef_[idx] + raw_spend = np.abs(X[col].sum()) + effect = np.abs(coef * raw_spend) # Keep absolute effect + effects.append(effect) + spends.append(raw_spend) + + if debug and (iteration == 0 or iteration % 25 == 0): + self.logger.debug(f"{col}:") + self.logger.debug(f" coefficient: {coef:.6f}") + self.logger.debug(f" raw spend: {raw_spend:.6f}") + self.logger.debug(f" effect: {effect:.6f}") + + # Convert to numpy arrays + effects = np.array(effects) + spends = np.array(spends) + + # Calculate totals for normalization + total_effect = np.sum(effects) + total_spend = np.sum(spends) + + if total_effect > 0 and total_spend > 0: + # Normalize proportionally + effects_norm = effects / total_effect + spends_norm = spends / total_spend + + if debug and (iteration == 0 or iteration % 25 == 0): + self.logger.debug("\nNormalized values:") + self.logger.debug("Effects:", effects_norm) + self.logger.debug("Spends:", spends_norm) + self.logger.debug("Effect total (check=1):", np.sum(effects_norm)) + self.logger.debug("Spend total (check=1):", np.sum(spends_norm)) + + # Calculate RSSD + squared_diff = (effects_norm - spends_norm) ** 2 + rssd = np.sqrt(np.mean(squared_diff)) + + if rssd_zero_penalty: + zero_effects = sum(1 for e in effects if abs(e) < 1e-10) + if zero_effects > 0: + rssd *= 1 + zero_effects / len(effects) + + return float(rssd) + + return float(np.inf) + + def _calculate_mape( + self, + model: Ridge, + dt_raw: pd.DataFrame, + hypParamSam: Dict[str, float], + wind_start: int, + wind_end: int, + ) -> float: + """ + Calculate MAPE using calibration data + """ + if self.calibration_input is None: + return 0.0 + + try: + # Use the MediaEffectCalibrator for MAPE calculation + calibration_engine = MediaEffectCalibrator( + mmm_data=self.mmm_data, + hyperparameters=self.hyperparameters, + calibration_input=self.calibration_input, + ) + + # Calculate MAPE using calibration engine + lift_collect = calibration_engine.calibrate( + df_raw=dt_raw, + hypParamSam=hypParamSam, + wind_start=wind_start, + wind_end=wind_end, + dayInterval=1, # Default to 1 if not specified + adstock=self.hyperparameters.adstock, + ) + + # Return mean MAPE across all lift studies + if lift_collect is not None and not lift_collect.empty: + return float(lift_collect["mape_lift"].mean()) + return 0.0 + except Exception as e: + self.logger.warning(f"Error calculating MAPE: {str(e)}") + return 0.0 + + def _calculate_x_decomp_agg( + self, model: Ridge, X: pd.DataFrame, y: pd.Series, metrics: Dict[str, Any] + ) -> pd.DataFrame: + """Calculate x decomposition aggregates matching R's implementation exactly""" + # Calculate decomposition effects with R-style scaling + scale_factor = np.mean(np.abs(X)) * np.mean(np.abs(y)) + x_decomp = (X * model.coef_) * scale_factor + x_decomp_sum = x_decomp.to_numpy().sum() # faster summing over all elements + + # Precompute total non-zero mean across all columns once + total_non_zero_mean = sum( + x_decomp[c][x_decomp[c] > 0].mean() if (x_decomp[c] > 0).any() else 0 + for c in X.columns + ) + + results = [] + # Use enumerate to iterate over columns and corresponding coefficients + for idx, col in enumerate(X.columns): + coef = model.coef_[idx] + decomp_values = x_decomp[col] + decomp_sum = decomp_values.sum() + + # Calculate non-zero mean for this column + non_zero_mask = decomp_values != 0 + non_zero_mean = ( + decomp_values[non_zero_mask].mean() if non_zero_mask.any() else 0 + ) + + result = { + "rn": str(col), # Ensure string type + "coef": float(coef), # Ensure float type + "xDecompAgg": float(decomp_sum), # Ensure float type + "xDecompPerc": float( + decomp_sum / x_decomp_sum if x_decomp_sum != 0 else 0 + ), + "xDecompMeanNon0": float(non_zero_mean), + "xDecompMeanNon0Perc": float( + non_zero_mean / total_non_zero_mean + if total_non_zero_mean != 0 + else 0 + ), + "xDecompAggRF": float(decomp_sum), # RF version + "xDecompPercRF": float( + decomp_sum / x_decomp_sum if x_decomp_sum != 0 else 0 + ), + "xDecompMeanNon0RF": float(non_zero_mean), + "xDecompMeanNon0PercRF": float( + non_zero_mean / total_non_zero_mean + if total_non_zero_mean != 0 + else 0 + ), + "pos": bool(coef >= 0), + } + + # Add model performance metrics with correct types + result.update( + { + "train_size": float(metrics.get("train_size", 1.0)), + "rsq_train": float(metrics.get("rsq_train", 0)), + "rsq_val": float(metrics.get("rsq_val", 0)), + "rsq_test": float(metrics.get("rsq_test", 0)), + "nrmse_train": float(metrics.get("nrmse_train", 0)), + "nrmse_val": float(metrics.get("nrmse_val", 0)), + "nrmse_test": float(metrics.get("nrmse_test", 0)), + "nrmse": float(metrics.get("nrmse", 0)), + "decomp.rssd": float(metrics.get("decomp_rssd", 0)), + "mape": float(metrics.get("mape", 0)), + "lambda": float( + metrics.get("lambda", 0) + ), # Critical: Using lambda not lambda_ + "lambda_hp": float(metrics.get("lambda_hp", 0)), + "lambda_max": float(metrics.get("lambda_max", 0)), + "lambda_min_ratio": float(metrics.get("lambda_min_ratio", 0)), + "sol_id": str(metrics.get("sol_id", "")), + "trial": int(metrics.get("trial", 0)), + "iterNG": int(metrics.get("iterNG", 0)), + "iterPar": int(metrics.get("iterPar", 0)), + "Elapsed": float(metrics.get("Elapsed", 0)), + } + ) + + results.append(result) + + df = pd.DataFrame(results) + + # Ensure correct column order and types + required_cols = [ + "rn", + "coef", + "xDecompAgg", + "xDecompPerc", + "xDecompMeanNon0", + "xDecompMeanNon0Perc", + "xDecompAggRF", + "xDecompPercRF", + "xDecompMeanNon0RF", + "xDecompMeanNon0PercRF", + "pos", + "train_size", + "rsq_train", + "rsq_val", + "rsq_test", + "nrmse_train", + "nrmse_val", + "nrmse_test", + "nrmse", + "decomp.rssd", + "mape", + "lambda", + "lambda_hp", + "lambda_max", + "lambda_min_ratio", + "sol_id", + "trial", + "iterNG", + "iterPar", + "Elapsed", + ] + + df = df[required_cols] + return df + + def calculate_r2_score( + self, y_true: np.ndarray, y_pred: np.ndarray, n_features: int, df_int: int = 1 + ) -> float: + """Match R's R² calculation exactly""" + n = len(y_true) + + # Scale data like R + y_mean = np.mean(y_true) + ss_tot = np.sum((y_true - y_mean) ** 2) + ss_res = np.sum((y_true - y_pred) ** 2) + + # Calculate base R² + r2 = 1 - (ss_res / ss_tot) + + # R's adjustment formula + adj_r2 = 1 - ((1 - r2) * (n - df_int) / (n - n_features - df_int)) + + # Match R's scale + if adj_r2 < 0: + adj_r2 = -np.sqrt(np.abs(adj_r2)) # R-style negative scaling + + return float(adj_r2) + + def calculate_nrmse( + self, + y_true: np.ndarray, + y_pred: np.ndarray, + debug: bool = True, + iteration: int = 0, + ) -> float: + """Calculate NRMSE with detailed debugging""" + n = len(y_true) + y_true = np.asarray(y_true) + y_pred = np.asarray(y_pred) + + # Calculate residuals and RSS + residuals = y_true - y_pred + rss = np.sum(residuals**2) + + # Calculate range from true values + y_min = np.min(y_true) + y_max = np.max(y_true) + scale = y_max - y_min + + # Calculate RMSE first + rmse = np.sqrt(rss / n) + + if debug and (iteration == 0 or iteration % 25 == 0): + self.logger.debug(f"\nNRMSE Calculation Debug (iteration {iteration}):") + self.logger.debug(f"n: {n}") + self.logger.debug(f"RSS: {rss:.6f}") + self.logger.debug(f"RMSE: {rmse:.6f}") + self.logger.debug(f"y_true range: [{y_min:.6f}, {y_max:.6f}]") + self.logger.debug(f"scale: {scale:.6f}") + self.logger.debug("First 5 pairs (true, pred, residual):") + for i in range(min(5, len(y_true))): + self.logger.debug( + f" {y_true[i]:.6f}, {y_pred[i]:.6f}, {residuals[i]:.6f}" + ) + + # Calculate final NRMSE + nrmse = rmse / scale if scale > 0 else rmse + + if debug and (iteration == 0 or iteration % 25 == 0): + self.logger.debug(f"Final NRMSE: {nrmse:.6f}") + + return float(nrmse) diff --git a/python/src/robyn/modeling/ridge_model_builder.py b/python/src/robyn/modeling/ridge_model_builder.py new file mode 100644 index 000000000..e08207812 --- /dev/null +++ b/python/src/robyn/modeling/ridge_model_builder.py @@ -0,0 +1,448 @@ +# pyre-strict + +import warnings +import numpy as np +import pandas as pd +from typing import List, Optional, Dict, Any, Tuple +from sklearn.linear_model import Ridge +from sklearn.metrics import r2_score, mean_squared_error +import nevergrad as ng +from tqdm import tqdm + +import logging +import time +from datetime import datetime +from robyn.modeling.convergence.convergence import Convergence +from sklearn.exceptions import ConvergenceWarning +from robyn.data.entities.calibration_input import CalibrationInput +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.modeloutputs import ModelOutputs, Trial +from robyn.modeling.entities.modelrun_trials_config import TrialsConfig +from robyn.modeling.entities.model_refit_output import ModelRefitOutput +from robyn.modeling.feature_engineering import FeaturizedMMMData +from robyn.modeling.entities.enums import NevergradAlgorithm +from robyn.modeling.ridge.ridge_metrics_calculator import ( + RidgeMetricsCalculator, +) +from robyn.modeling.ridge.ridge_evaluate_model import RidgeModelEvaluator +from robyn.modeling.ridge.ridge_data_builder import RidgeDataBuilder + + +class RidgeModelBuilder: + def __init__( + self, + mmm_data: MMMData, + holiday_data: HolidaysData, + calibration_input: CalibrationInput, + hyperparameters: Hyperparameters, + featurized_mmm_data: FeaturizedMMMData, + ): + self.mmm_data = mmm_data + self.holiday_data = holiday_data + self.calibration_input = calibration_input + self.hyperparameters = hyperparameters + self.featurized_mmm_data = featurized_mmm_data + self.ridge_data_builder = RidgeDataBuilder(mmm_data, featurized_mmm_data) + self.ridge_metrics_calculator = RidgeMetricsCalculator( + mmm_data, hyperparameters, self.ridge_data_builder + ) + self.ridge_model_evaluator = RidgeModelEvaluator( + self.mmm_data, + self.featurized_mmm_data, + self.ridge_metrics_calculator, + self.ridge_data_builder, + ) + + self.logger = logging.getLogger(__name__) + + def build_models( + self, + trials_config: TrialsConfig, + dt_hyper_fixed: Optional[pd.DataFrame] = None, + ts_validation: bool = False, + add_penalty_factor: bool = False, + seed: List[int] = [123], + rssd_zero_penalty: bool = True, + objective_weights: Optional[List[float]] = None, + nevergrad_algo: NevergradAlgorithm = NevergradAlgorithm.TWO_POINTS_DE, + intercept: bool = True, + intercept_sign: str = "non_negative", + cores: Optional[int] = None, + ) -> ModelOutputs: + start_time = time.time() + # Initialize hyperparameters with flattened structure + hyper_collect = self.ridge_data_builder._hyper_collector( + self.hyperparameters, + ts_validation, + add_penalty_factor, + dt_hyper_fixed, + cores, + ) + # Convert datetime to string format matching R's format + current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + + # Set up objective weights including calibration if available + if objective_weights is None: + if self.calibration_input is not None: + objective_weights = [1 / 3, 1 / 3, 1 / 3] # NRMSE, RSSD, MAPE + else: + objective_weights = [0.5, 0.5] # NRMSE, RSSD only + # Run trials + trials = [] + for trial in range(1, trials_config.trials + 1): + trial_result = self.ridge_model_evaluator._run_nevergrad_optimization( + hyper_collect=hyper_collect, + iterations=trials_config.iterations, + cores=cores, + nevergrad_algo=nevergrad_algo, + intercept=intercept, + intercept_sign=intercept_sign, + ts_validation=ts_validation, + add_penalty_factor=add_penalty_factor, + objective_weights=objective_weights, + dt_hyper_fixed=dt_hyper_fixed, + rssd_zero_penalty=rssd_zero_penalty, + trial=trial, + seed=seed[0] + trial, # Use the first element of the seed list + total_trials=trials_config.trials, + ) + trials.append(trial_result) + # Calculate convergence + convergence = Convergence() + convergence_results = convergence.calculate_convergence(trials) + + # Aggregate results with explicit type casting + all_result_hyp_param = pd.concat( + [trial.result_hyp_param for trial in trials], ignore_index=True + ) + all_result_hyp_param = self.ridge_data_builder.safe_astype( + all_result_hyp_param, + { + "sol_id": "str", + "trial": "int64", + "iterNG": "int64", + "iterPar": "int64", + "nrmse": "float64", + "decomp.rssd": "float64", + "mape": "int64", + "pos": "int64", + "lambda": "float64", + "lambda_hp": "float64", + "lambda_max": "float64", + "lambda_min_ratio": "float64", + "rsq_train": "float64", + "rsq_val": "float64", + "rsq_test": "float64", + "nrmse_train": "float64", + "nrmse_val": "float64", + "nrmse_test": "float64", + "ElapsedAccum": "float64", + "Elapsed": "float64", + }, + ) + + all_x_decomp_agg = pd.concat( + [trial.x_decomp_agg for trial in trials], ignore_index=True + ) + all_x_decomp_agg = self.ridge_data_builder.safe_astype( + all_x_decomp_agg, + { + "rn": "str", + "coef": "float64", + "xDecompAgg": "float64", + "xDecompPerc": "float64", + "xDecompMeanNon0": "float64", + "xDecompMeanNon0Perc": "float64", + "xDecompAggRF": "float64", + "xDecompPercRF": "float64", + "xDecompMeanNon0RF": "float64", + "xDecompMeanNon0PercRF": "float64", + "sol_id": "str", + "pos": "bool", + "mape": "int64", + }, + ) + + all_decomp_spend_dist = pd.concat( + [ + trial.decomp_spend_dist + for trial in trials + if trial.decomp_spend_dist is not None + ], + ignore_index=True, + ) + all_decomp_spend_dist = self.ridge_data_builder.safe_astype( + all_decomp_spend_dist, + { + "rn": "str", + "coef": "float64", + "total_spend": "float64", + "mean_spend": "float64", + "effect_share": "float64", + "spend_share": "float64", + "xDecompAgg": "float64", + "xDecompPerc": "float64", + "xDecompMeanNon0": "float64", + "xDecompMeanNon0Perc": "float64", + "sol_id": "str", + "pos": "bool", + "mape": "int64", + "nrmse": "float64", + "decomp.rssd": "float64", + "trial": "int64", + "iterNG": "int64", + "iterPar": "int64", + }, + ) + # Convert hyper_bound_ng from dict to DataFrame + hyper_bound_ng_df = pd.DataFrame() + for param_name, bounds in hyper_collect["hyper_bound_list_updated"].items(): + hyper_bound_ng_df.loc[0, param_name] = bounds[0] + hyper_bound_ng_df[param_name] = hyper_bound_ng_df[param_name].astype( + "float64" + ) + if "lambda" in hyper_bound_ng_df.columns: + hyper_bound_ng_df["lambda"] = hyper_bound_ng_df["lambda"].astype("int64") + # Create ModelOutputs + model_outputs = ModelOutputs( + trials=trials, + train_timestamp=current_time, + cores=cores, + iterations=trials_config.iterations, + intercept=intercept, + intercept_sign=intercept_sign, + nevergrad_algo=nevergrad_algo, + ts_validation=ts_validation, + add_penalty_factor=add_penalty_factor, + hyper_updated=hyper_collect["hyper_list_all"], + hyper_fixed=hyper_collect["all_fixed"], + convergence=convergence_results, + select_id=self._select_best_model(trials), + seed=seed, + hyper_bound_ng=hyper_bound_ng_df, + hyper_bound_fixed=hyper_collect["hyper_bound_list_fixed"], + ts_validation_plot=None, + all_result_hyp_param=all_result_hyp_param, + all_x_decomp_agg=all_x_decomp_agg, + all_decomp_spend_dist=all_decomp_spend_dist, + ) + + return model_outputs + + def _select_best_model(self, output_models: List[Trial]) -> str: + # Extract relevant metrics + nrmse_values = np.array([trial.nrmse for trial in output_models]) + decomp_rssd_values = np.array([trial.decomp_rssd for trial in output_models]) + + # Normalize the metrics + nrmse_norm = (nrmse_values - np.min(nrmse_values)) / ( + np.max(nrmse_values) - np.min(nrmse_values) + ) + decomp_rssd_norm = (decomp_rssd_values - np.min(decomp_rssd_values)) / ( + np.max(decomp_rssd_values) - np.min(decomp_rssd_values) + ) + + # Calculate the combined score (assuming equal weights) + combined_score = nrmse_norm + decomp_rssd_norm + + # Find the index of the best model (lowest combined score) + best_index = np.argmin(combined_score) + + # Return the sol_id of the best model (changed from solID) + return output_models[best_index].result_hyp_param["sol_id"].values[0] + + def _model_train( + self, + hyper_collect: Dict[str, Any], + trials_config: TrialsConfig, + intercept_sign: str, + intercept: bool, + nevergrad_algo: NevergradAlgorithm, + dt_hyper_fixed: Optional[pd.DataFrame], + ts_validation: bool, + add_penalty_factor: bool, + objective_weights: Optional[List[float]], + rssd_zero_penalty: bool, + seed: int, + cores: int, + ) -> List[Trial]: + trials = [] + for trial in range(1, trials_config.trials + 1): + trial_result = self.ridge_model_evaluator._run_nevergrad_optimization( + hyper_collect, + trials_config.iterations, + cores, + nevergrad_algo, + intercept, + intercept_sign, + ts_validation, + add_penalty_factor, + objective_weights, + dt_hyper_fixed, + rssd_zero_penalty, + trial, + seed + trial, + trials_config.trials, + ) + + trials.append(trial_result) + return trials + + def _evaluate_model( + self, + params: Dict[str, float], + ts_validation: bool, + add_penalty_factor: bool, + rssd_zero_penalty: bool, + objective_weights: Optional[List[float]], + start_time: float, + iter_ng: int, + trial: int, + ) -> Dict[str, Any]: + """Evaluate model with parameter set matching R's implementation exactly""" + X, y = self._prepare_data(params) + sol_id = f"{trial}_{iter_ng + 1}_1" + # After preparing data + self.logger.debug(f"Data shapes - X: {X.shape}, y: {y.shape}") + self.logger.debug(f"Sample of X values: {X.head()}") + self.logger.debug(f"Sample of y values: {y.head()}") + + # Split data using R's approach + train_size = params.get("train_size", 1.0) if ts_validation else 1.0 + train_idx = int(len(X) * train_size) + + metrics = {} + if ts_validation: + val_test_size = (len(X) - train_idx) // 2 + X_train = X.iloc[:train_idx] + y_train = y.iloc[:train_idx] + X_val = X.iloc[train_idx : train_idx + val_test_size] + y_val = y.iloc[train_idx : train_idx + val_test_size] + X_test = X.iloc[train_idx + val_test_size :] + y_test = y.iloc[train_idx + val_test_size :] + else: + X_train, y_train = X, y + X_val = X_test = y_val = y_test = None + + x_norm = X_train.to_numpy() + y_norm = y_train.to_numpy() + + # Calculate lambda using R-matching helper function + lambda_hp = params.get("lambda", 1.0) + lambda_, lambda_max = self.ridge_metrics_calculator._calculate_lambda( + x_norm, y_norm, lambda_hp + ) + # After calculating lambda + self.logger.debug(f"Lambda calculation debug:") + self.logger.debug(f"lambda_hp: {lambda_hp}") + self.logger.debug(f"lambda_: {lambda_}") + self.logger.debug(f"lambda_max: {lambda_max}") + + # Scale inputs for model + model = Ridge(alpha=lambda_ / len(x_norm), fit_intercept=True) + model.fit(x_norm, y_norm) + + # Calculate metrics using R-style calculations + y_train_pred = model.predict(x_norm) + metrics["rsq_train"] = self.ridge_metrics_calculator.calculate_r2_score( + y_norm, y_train_pred, x_norm.shape[1] + ) + metrics["nrmse_train"] = self.ridge_metrics_calculator.calculate_nrmse( + y_norm, y_train_pred + ) + + # Validation and test metrics + if ts_validation and X_val is not None and X_test is not None: + y_val_pred = model.predict(X_val) + y_test_pred = model.predict(X_test) + + metrics["rsq_val"] = self.ridge_metrics_calculator.calculate_r2_score( + y_val, y_val_pred, X_val.shape[1] + ) + metrics["nrmse_val"] = self.ridge_metrics_calculator.calculate_nrmse( + y_val, y_val_pred + ) + + metrics["rsq_test"] = self.ridge_metrics_calculator.calculate_r2_score( + y_test, y_test_pred, X_test.shape[1] + ) + metrics["nrmse_test"] = self.ridge_metrics_calculator.calculate_nrmse( + y_test, y_test_pred + ) + + metrics["nrmse"] = metrics["nrmse_val"] + else: + metrics["rsq_val"] = metrics["rsq_test"] = 0.0 + metrics["nrmse_val"] = metrics["nrmse_test"] = 0.0 + metrics["nrmse"] = metrics["nrmse_train"] + + # Calculate RSSD + paid_media_cols = [ + col + for col in X.columns + if col in self.mmm_data.mmmdata_spec.paid_media_spends + ] + decomp_rssd = self.ridge_metrics_calculator._calculate_rssd( + model, X_train, paid_media_cols, rssd_zero_penalty + ) + + elapsed_time = time.time() - start_time + + # Format hyperparameter names to match R's format + params_formatted = self._format_hyperparameter_names(params) + + # Update metrics dictionary + metrics.update( + { + "decomp_rssd": float(decomp_rssd), + "lambda": float(lambda_), + "lambda_hp": float(lambda_hp), + "lambda_max": float(lambda_max), + "lambda_min_ratio": float(0.0001), + "mape": int(0), # Cast to int as in R + "sol_id": str(sol_id), + "trial": int(trial), + "iterNG": int(iter_ng + 1), + "iterPar": int(1), + "Elapsed": float(elapsed_time), + "elapsed": float(elapsed_time), + "elapsed_accum": float(elapsed_time), + } + ) + + # Calculate decompositions + x_decomp_agg = self.ridge_metrics_calculator._calculate_x_decomp_agg( + model, X_train, y_train, {**params_formatted, **metrics} + ) + decomp_spend_dist = self.ridge_metrics_calculator._calculate_decomp_spend_dist( + model, X_train, y_train, {**metrics, "params": params_formatted} + ) + + # Calculate loss + loss = ( + objective_weights[0] * metrics["nrmse"] + + objective_weights[1] * metrics["decomp_rssd"] + + ( + objective_weights[2] * metrics["mape"] + if len(objective_weights) > 2 + else 0 + ) + ) + self.logger.debug( + f"Model coefficients range: {model.coef_.min()} to {model.coef_.max()}" + ) + self.logger.debug(f"Sample predictions: {y_train_pred[:5]}") + self.logger.debug(f"Sample actual values: {y_norm[:5]}") + return { + "loss": loss, + "params": params_formatted, + **metrics, + "decomp_spend_dist": decomp_spend_dist, + "x_decomp_agg": x_decomp_agg, + "elapsed": elapsed_time, + "elapsed_accum": elapsed_time, + "iter_ng": iter_ng + 1, + "iter_par": 1, + } diff --git a/python/src/robyn/modeling/transformations/transformations.py b/python/src/robyn/modeling/transformations/transformations.py new file mode 100644 index 000000000..8fcab0f29 --- /dev/null +++ b/python/src/robyn/modeling/transformations/transformations.py @@ -0,0 +1,329 @@ +# pyre-strict + +import logging +from dataclasses import dataclass +from typing import Dict, List, Optional, Union + +import numpy as np +import pandas as pd +from robyn.data.entities.enums import AdstockType +from robyn.data.entities.hyperparameters import ChannelHyperparameters, Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.feature_engineering import FeaturizedMMMData +from scipy import stats + +# Initialize logger +logger = logging.getLogger(__name__) + + +@dataclass +class AdstockResult: + x: pd.Series + x_decayed: pd.Series + x_imme: pd.Series + thetaVec: Optional[pd.Series] + thetaVecCum: pd.Series + inflation_total: float + + def __str__(self) -> str: + return f"AdstockResult(inflation_total={self.inflation_total:.4f}, series_length={len(self.x)})" + + +@dataclass +class TransformationResult: + dt_modSaturated: pd.DataFrame + dt_saturatedImmediate: pd.DataFrame + dt_saturatedCarryover: pd.DataFrame + + def __str__(self) -> str: + return ( + f"TransformationResult(modSaturated_shape={self.dt_modSaturated.shape}, " + f"saturatedImmediate_shape={self.dt_saturatedImmediate.shape}, " + f"saturatedCarryover_shape={self.dt_saturatedCarryover.shape})" + ) + + +class Transformation: + def __init__(self, mmm_data: MMMData): + """Initialize the Transformation class with MMMData.""" + logger.debug("Initializing Transformation with MMMData: %s", mmm_data) + self.mmm_data = mmm_data + + def normalize(self, x: pd.Series) -> pd.Series: + """Normalize a series to [0, 1] range.""" + logger.debug("Normalizing series with length: %d", len(x)) + if x.max() == x.min(): + logger.warning("Series has constant values, returning binary normalization") + return pd.Series([1] + [0] * (len(x) - 1), index=x.index) + return (x - x.min()) / (x.max() - x.min()) + + def mic_men( + x: Union[float, pd.Series], Vmax: float, Km: float, reverse: bool = False + ) -> Union[float, pd.Series]: + """Apply Michaelis-Menten transformation.""" + logger.debug("Applying Michaelis-Menten transform (reverse=%s)", reverse) + if not reverse: + return Vmax * x / (Km + x) + else: + return x * Km / (Vmax - x) + + def adstock_geometric(self, x: pd.Series, theta: float) -> AdstockResult: + """Apply geometric adstock transformation.""" + logger.debug("Applying geometric adstock with theta=%f", theta) + + if not np.isscalar(theta): + logger.error("Invalid theta value: must be scalar") + raise ValueError("theta must be a single value") + + x_decayed = pd.Series(index=x.index, dtype=float) + x_decayed.iloc[0] = x.iloc[0] + + logger.debug("Computing geometric decay") + for xi in range(1, len(x_decayed)): + x_decayed.iloc[xi] = x.iloc[xi] + theta * x_decayed.iloc[xi - 1] + + thetaVecCum = pd.Series(theta ** np.arange(len(x)), index=x.index) + inflation_total = x_decayed.sum() / x.sum() + + logger.debug( + "Completed geometric adstock with inflation_total=%f", inflation_total + ) + return AdstockResult(x, x_decayed, x, None, thetaVecCum, inflation_total) + + def adstock_weibull( + self, + x: pd.Series, + shape: float, + scale: float, + windlen: Optional[int] = None, + adstockType: AdstockType = AdstockType.WEIBULL_CDF, + ) -> AdstockResult: + """Apply Weibull adstock transformation.""" + logger.debug( + "Applying Weibull adstock (type=%s, shape=%f, scale=%f)", + adstockType, + shape, + scale, + ) + + if not (np.isscalar(shape) and np.isscalar(scale)): + logger.error("Invalid shape or scale values: must be scalar") + raise ValueError("shape and scale must be single values") + + windlen = len(x) if windlen is None else windlen + x_bin = pd.Series(range(1, windlen + 1)) + scaleTrans = int(x_bin.quantile(scale)) + + if shape == 0 or scale == 0: + logger.warning("Shape or scale is 0, returning unmodified series") + x_decayed = x + thetaVecCum = thetaVec = pd.Series(np.zeros(windlen), index=x_bin) + x_imme = x + else: + logger.debug("Computing Weibull transformation") + if adstockType == AdstockType.WEIBULL_CDF: + thetaVec = pd.Series( + [1] + + list( + 1 - stats.weibull_min.cdf(x_bin[:-1], shape, scale=scaleTrans) + ), + index=x_bin, + ) + thetaVecCum = thetaVec.cumprod() + elif adstockType == AdstockType.WEIBULL_PDF: + thetaVecCum = self.normalize( + pd.Series( + stats.weibull_min.pdf(x_bin, shape, scale=scaleTrans), + index=x_bin, + ) + ) + + x_decayed = pd.Series(0, index=x.index, dtype=float) + logger.debug("Applying convolution") + for i, xi in enumerate(x): + x_decayed += pd.Series( + np.convolve( + np.concatenate((np.zeros(i), np.repeat(xi, windlen - i))), + thetaVecCum, + )[:windlen], + index=x.index, + ) + + x_imme = ( + x + if adstockType == AdstockType.WEIBULL_CDF + else pd.Series(np.convolve(x, thetaVecCum)[: len(x)], index=x.index) + ) + + inflation_total = x_decayed.sum() / x.sum() + logger.debug( + "Completed Weibull adstock (type=%s) with inflation_total=%f", + adstockType, + inflation_total, + ) + return AdstockResult( + x, + x_decayed, + x_imme, + thetaVec if "thetaVec" in locals() else None, + thetaVecCum, + inflation_total, + ) + + def transform_adstock( + self, + x: pd.Series, + adstockType: AdstockType, + channelHyperparameters: ChannelHyperparameters, + windlen: Optional[int] = None, + ) -> AdstockResult: + """Apply adstock transformation based on the specified method.""" + logger.debug("Starting adstock transformation with type: %s", adstockType) + logger.debug("Input series length: %d", len(x)) + + try: + if adstockType == AdstockType.GEOMETRIC: + theta = channelHyperparameters.thetas[0] + logger.debug("Using geometric adstock with theta=%f", theta) + return self.adstock_geometric(x, theta) + elif adstockType in [AdstockType.WEIBULL_CDF, AdstockType.WEIBULL_PDF]: + shape = channelHyperparameters.shapes[0] + scale = channelHyperparameters.scales[0] + logger.debug( + "Using Weibull adstock with shape=%f, scale=%f", shape, scale + ) + return self.adstock_weibull(self, x, shape, scale, windlen, adstockType) + except Exception as e: + logger.error("Error in adstock transformation: %s", str(e)) + raise + + def saturation_hill( + self, + x: pd.Series, + alpha: float, + gamma: float, + x_marginal: Optional[pd.Series] = None, + ) -> pd.Series: + """Apply Hill function for saturation.""" + logger.debug( + "Applying Hill saturation (alpha=%f, gamma=%f, with_marginal=%s)", + alpha, + gamma, + x_marginal is not None, + ) + + if not (np.isscalar(alpha) and np.isscalar(gamma)): + logger.error("Invalid alpha or gamma values: must be scalar") + raise ValueError("alpha and gamma must be single values") + + inflexion = gamma * x.max() + (1 - gamma) * x.min() + logger.debug("Calculated inflexion point: %f", inflexion) + + result = ( + x**alpha / (x**alpha + inflexion**alpha) + if x_marginal is None + else x_marginal**alpha / (x_marginal**alpha + inflexion**alpha) + ) + + logger.debug("Completed Hill saturation") + return result + + def run_transformations( + self, + featurized_data: FeaturizedMMMData, + hyperparameters: Hyperparameters, + adstockType: AdstockType, + ) -> TransformationResult: + """Run media transformations including adstock and saturation.""" + logger.debug("Starting media transformations") + logger.debug("Input data shape: %s", featurized_data.dt_mod.shape) + + all_media = self.mmm_data.mmmdata_spec.all_media + rollingWindowStartWhich = self.mmm_data.mmmdata_spec.rolling_window_start_which + rollingWindowEndWhich = self.mmm_data.mmmdata_spec.rolling_window_end_which + + # print("Rolling window start which: ", rollingWindowStartWhich) + # print("Rolling window end which: ", rollingWindowEndWhich) + + # if rollingWindowStartWhich is None or rollingWindowEndWhich is None: + # # Use default values if not specified + # rollingWindowStartWhich = 7 + # rollingWindowEndWhich = 163 + # # print("Set default values") + dt_modAdstocked = featurized_data.dt_mod.copy() + if "ds" in dt_modAdstocked.columns: + logger.debug("Removing 'ds' column from data") + dt_modAdstocked.drop(columns="ds", inplace=True) + + mediaAdstocked: Dict[str, pd.Series] = {} + mediaSaturated: Dict[str, pd.Series] = {} + mediaSaturatedImmediate: Dict[str, pd.Series] = {} + mediaSaturatedCarryover: Dict[str, pd.Series] = {} + + for media in all_media: + logger.debug("Processing media channel: %s", media) + try: + m = dt_modAdstocked[media] + channelHyperparameters = hyperparameters.get_hyperparameter(media) + + logger.debug("Applying adstock transformation for %s", media) + x_list = self.transform_adstock(m, adstockType, channelHyperparameters) + + m_imme = x_list.x_imme if adstockType == AdstockType.WEIBULL_PDF else m + m_adstocked = x_list.x_decayed + mediaAdstocked[media] = m_adstocked + m_carryover = m_adstocked - m_imme + + m_adstockedRollWind = m_adstocked.iloc[ + rollingWindowStartWhich : rollingWindowEndWhich + 1 + ] + m_carryoverRollWind = m_carryover.iloc[ + rollingWindowStartWhich : rollingWindowEndWhich + 1 + ] + + logger.debug("Applying saturation transformations for %s", media) + mediaSaturated[media] = self.saturation_hill( + m_adstockedRollWind, + channelHyperparameters.alphas[0], + channelHyperparameters.gammas[0], + ) + mediaSaturatedCarryover[media] = self.saturation_hill( + m_adstockedRollWind, + channelHyperparameters.alphas[0], + channelHyperparameters.gammas[0], + x_marginal=m_carryoverRollWind, + ) + mediaSaturatedImmediate[media] = ( + mediaSaturated[media] - mediaSaturatedCarryover[media] + ) + logger.debug("Completed transformations for media channel: %s", media) + except Exception as e: + logger.error("Error processing media channel %s: %s", media, str(e)) + raise + + logger.debug("Combining transformed data") + dt_modAdstocked = pd.concat( + [dt_modAdstocked.drop(columns=all_media), pd.DataFrame(mediaAdstocked)], + axis=1, + ) + dt_modSaturated = pd.concat( + [ + dt_modAdstocked.iloc[ + rollingWindowStartWhich : rollingWindowEndWhich + 1 + ].drop(columns=all_media), + pd.DataFrame(mediaSaturated), + ], + axis=1, + ).reset_index() + dt_saturatedImmediate = ( + pd.DataFrame(mediaSaturatedImmediate).fillna(0).reset_index() + ) + dt_saturatedCarryover = ( + pd.DataFrame(mediaSaturatedCarryover).fillna(0).reset_index() + ) + + result = TransformationResult( + dt_modSaturated, dt_saturatedImmediate, dt_saturatedCarryover + ) + logger.debug("Completed all transformations: %s", result) + return result diff --git a/python/src/robyn/reporting/onepager_reporting.py b/python/src/robyn/reporting/onepager_reporting.py new file mode 100644 index 000000000..3c994f392 --- /dev/null +++ b/python/src/robyn/reporting/onepager_reporting.py @@ -0,0 +1,528 @@ +import os +from typing import Dict, Optional, List, Tuple, Union +import warnings +import matplotlib.pyplot as plt +from matplotlib.gridspec import GridSpec +from robyn.data.entities.holidays_data import HolidaysData +import seaborn as sns +import pandas as pd +import logging + +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.modeling.entities.clustering_results import ClusteredResult +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.enums import PlotType + +from robyn.visualization.pareto_visualizer import ParetoVisualizer +from robyn.visualization.cluster_visualizer import ClusterVisualizer +from robyn.visualization.response_visualizer import ResponseVisualizer +from robyn.visualization.transformation_visualizer import TransformationVisualizer + +logger = logging.getLogger(__name__) + + +class OnePager: + def __init__( + self, + pareto_result: ParetoResult, + clustered_result: Optional[ClusteredResult] = None, + hyperparameter: Optional[Hyperparameters] = None, + mmm_data: Optional[MMMData] = None, + holidays_data: Optional[HolidaysData] = None, + ): + self.pareto_result = pareto_result + self.clustered_result = clustered_result + self.hyperparameter = hyperparameter + self.mmm_data = mmm_data + self.holidays_data = holidays_data + + # Default plots using PlotType enum directly + self.default_plots = [ + PlotType.WATERFALL, + PlotType.FITTED_VS_ACTUAL, + PlotType.SPEND_EFFECT, + PlotType.BOOTSTRAP, + PlotType.ADSTOCK, + PlotType.IMMEDIATE_CARRYOVER, + PlotType.RESPONSE_CURVES, + PlotType.DIAGNOSTIC, + ] + + # Set up matplotlib style + self._setup_plotting_style() + + def _setup_plotting_style(self): + """Configure the plotting style for the one-pager.""" + plt.style.use("default") + sns.set_theme(style="whitegrid", context="paper") + plt.rcParams.update( + { + "figure.figsize": (30, 34), + "figure.dpi": 100, + "savefig.dpi": 300, + "font.size": 16, + "axes.titlesize": 22, + "axes.labelsize": 12, + "xtick.labelsize": 11, + "ytick.labelsize": 11, + "legend.fontsize": 11, + "figure.titlesize": 16, + "axes.grid": True, + "grid.alpha": 0.3, + "axes.spines.top": False, + "axes.spines.right": False, + } + ) + + def _safe_format(self, value, precision: int = 4) -> str: + """Safely format numeric values with specified precision.""" + try: + if isinstance(value, (pd.DataFrame, pd.Series)): + value = ( + value.iloc[0] if isinstance(value, pd.Series) else value.iloc[0, 0] + ) + if pd.isna(value): + return "0.0000" + return f"{float(value):.{precision}f}" + except (TypeError, ValueError, IndexError): + return "0.0000" + + def _get_model_info(self, solution_id: str) -> Dict[str, str]: + """Get model performance metrics for specific solution.""" + try: + x_decomp_agg = self.pareto_result.x_decomp_agg + plot_media_share = x_decomp_agg[ + (x_decomp_agg["sol_id"] == solution_id) + & ( + x_decomp_agg["rn"].isin( + self.mmm_data.mmmdata_spec.paid_media_spends + ) + ) + ] + + if plot_media_share.empty: + raise ValueError( + f"No media share data found for solution {solution_id}" + ) + + metrics = {} + + # Get training metrics + metrics["rsq_train"] = self._safe_format( + plot_media_share["rsq_train"].iloc[0] + ) + metrics["nrmse_train"] = self._safe_format( + plot_media_share["nrmse_train"].iloc[0] + ) + + # Get validation metrics if available + if "rsq_val" in plot_media_share.columns: + metrics["rsq_val"] = self._safe_format( + plot_media_share["rsq_val"].iloc[0] + ) + metrics["nrmse_val"] = self._safe_format( + plot_media_share["nrmse_val"].iloc[0] + ) + + # Get test metrics if available + if "rsq_test" in plot_media_share.columns: + metrics["rsq_test"] = self._safe_format( + plot_media_share["rsq_test"].iloc[0] + ) + metrics["nrmse_test"] = self._safe_format( + plot_media_share["nrmse_test"].iloc[0] + ) + + # Get decomp.rssd + metrics["decomp_rssd"] = self._safe_format( + plot_media_share["decomp.rssd"].iloc[0] + ) + + # Get MAPE if available + if "mape" in plot_media_share.columns: + metrics["mape"] = self._safe_format(plot_media_share["mape"].iloc[0]) + + # Get train size + metrics["train_size"] = self._safe_format( + plot_media_share["train_size"].iloc[0] + ) + + # Calculate performance (ROAS/CPA) + dep_var_type = self.mmm_data.mmmdata_spec.dep_var_type + type_metric = "CPA" if dep_var_type == "conversion" else "ROAS" + + perf = ( + x_decomp_agg[ + (x_decomp_agg["sol_id"] == solution_id) + & ( + x_decomp_agg["rn"].isin( + self.mmm_data.mmmdata_spec.paid_media_spends + ) + ) + ] + .groupby("sol_id") + .agg({"xDecompAgg": "sum", "total_spend": "sum"}) + ) + + if not perf.empty: + if type_metric == "ROAS": + performance = ( + perf["xDecompAgg"].iloc[0] / perf["total_spend"].iloc[0] + ) + else: # CPA + performance = ( + perf["total_spend"].iloc[0] / perf["xDecompAgg"].iloc[0] + ) + metrics["performance"] = f"{performance:.3g} {type_metric}" + + # Format metrics text + if "rsq_val" in metrics: + metrics_text = ( + f"Adj.R2: train = {metrics['rsq_train']}, " + f"val = {metrics['rsq_val']}, " + f"test = {metrics['rsq_test']} | " + f"NRMSE: train = {metrics['nrmse_train']}, " + f"val = {metrics['nrmse_val']}, " + f"test = {metrics['nrmse_test']} | " + f"DECOMP.RSSD = {metrics['decomp_rssd']}" + ) + else: + metrics_text = ( + f"Adj.R2: train = {metrics['rsq_train']} | " + f"NRMSE: train = {metrics['nrmse_train']} | " + f"DECOMP.RSSD = {metrics['decomp_rssd']}" + ) + + if "mape" in metrics: + metrics_text += f" | MAPE = {metrics['mape']}" + + if "performance" in metrics: + metrics_text += f" | {metrics['performance']}" + + metrics["formatted_text"] = metrics_text + + return metrics + + except Exception as e: + logger.error( + f"Error getting model info for solution {solution_id}: {str(e)}" + ) + return { + "rsq_train": "0.0000", + "nrmse_train": "0.0000", + "decomp_rssd": "0.0000", + "formatted_text": "Error calculating metrics", + } + + def _add_title_and_metrics(self, fig: plt.Figure, solution_id: str) -> None: + """Add title and metrics text to the figure.""" + try: + model_info = self._get_model_info(solution_id) + metrics_text = model_info.get("formatted_text", "") + + # Add title with larger font and bold + fig.suptitle( + f"MMM Analysis One-Pager for Model: {solution_id}", + fontsize=24, # Increased from 18 + y=0.98, + weight="bold", # Makes the text bold + fontfamily="sans-serif", # Clear font family + ) + + # Add metrics text if available + if metrics_text: + fig.text( + 0.5, # Center horizontally + 0.955, # Position below title + metrics_text, + fontsize=16, # Increased from 14 + ha="center", + va="top", + weight="bold", # Also make metrics bold + ) + except Exception as e: + logger.error(f"Error adding title and metrics: {str(e)}") + # Fallback title with same style + fig.suptitle( + f"MMM Analysis One-Pager for Model: {solution_id}", + fontsize=24, + y=0.98, + weight="bold", + fontfamily="sans-serif", + ) + + def _generate_solution_plots( + self, solution_id: str, plots: List[PlotType], gs: GridSpec + ) -> None: + """Generate plots for a single solution with dynamic layout.""" + try: + # Validate plot types + for plot in plots: + if not isinstance(plot, PlotType): + logger.error( + f"Invalid plot type provided: {plot}. Must be PlotType enum." + ) + raise TypeError( + f"Plot type must be PlotType enum, got {type(plot)}" + ) + + # Initialize visualizers + pareto_viz = ( + ParetoVisualizer( + self.pareto_result, + self.mmm_data, + self.holidays_data, + self.hyperparameter, + ) + if self.hyperparameter and self.holidays_data + else None + ) + cluster_viz = ( + ClusterVisualizer( + self.pareto_result, self.clustered_result, self.mmm_data + ) + if self.clustered_result + else None + ) + response_viz = ResponseVisualizer(self.pareto_result, self.mmm_data) + transfor_viz = TransformationVisualizer(self.pareto_result, self.mmm_data) + + # Define plot configurations + plot_config = { + PlotType.SPEND_EFFECT: { + "title": "Share of Total Spend, Effect & Performance", + "func": lambda ax: transfor_viz.generate_spend_effect_comparison( + solution_id, ax + ), + }, + PlotType.WATERFALL: { + "title": "Response Decomposition Waterfall", + "func": lambda ax: ( + pareto_viz.generate_waterfall(solution_id, ax) + if pareto_viz + else None + ), + }, + PlotType.FITTED_VS_ACTUAL: { + "title": "Actual vs. Predicted Response", + "func": lambda ax: ( + pareto_viz.generate_fitted_vs_actual(solution_id, ax) + if pareto_viz + else None + ), + }, + PlotType.DIAGNOSTIC: { + "title": "Fitted vs. Residual", + "func": lambda ax: ( + pareto_viz.generate_diagnostic_plot(solution_id, ax) + if pareto_viz + else None + ), + }, + PlotType.IMMEDIATE_CARRYOVER: { + "title": "Immediate vs. Carryover Response Percentage", + "func": lambda ax: ( + pareto_viz.generate_immediate_vs_carryover(solution_id, ax) + if pareto_viz + else None + ), + }, + PlotType.ADSTOCK: { + "title": "Adstock Rate Analysis", + "func": lambda ax: ( + pareto_viz.generate_adstock_rate(solution_id, ax) + if pareto_viz + else None + ), + }, + PlotType.BOOTSTRAP: { + "title": "Bootstrapped Performance Metrics", + "func": lambda ax: ( + cluster_viz.generate_bootstrap_confidence(solution_id, ax) + if cluster_viz + else None + ), + }, + PlotType.RESPONSE_CURVES: { + "title": "Response Curves and Mean Spends by Channel", + "func": lambda ax: response_viz.generate_response_curves( + solution_id, ax + ), + }, + } + + # Create plots with dynamic positioning + for i, plot_type in enumerate(plots): + if plot_type not in plot_config: + logger.error(f"Unsupported plot type: {plot_type}") + continue + + row = i // 2 + col = i % 2 + + config = plot_config[plot_type] + try: + ax = plt.subplot(gs[row, col]) + config["func"](ax) + ax.set_title(f"{config['title']} (Solution {solution_id})") + except Exception as e: + logger.error( + f"Failed to generate plot {plot_type.name} for solution {solution_id}: {str(e)}", + exc_info=True, + ) + ax.text( + 0.5, + 0.5, + f"Error generating {plot_type.name}", + ha="center", + va="center", + ) + raise e + + except Exception as e: + logger.error( + f"Fatal error generating plots for solution {solution_id}: {str(e)}", + exc_info=True, + ) + raise + + def generate_one_pager( + self, + solution_ids: Union[str, List[str]] = "all", + plots: Optional[List[PlotType]] = None, # Changed from List[str] + figsize: tuple = (30, 34), + save_path: Optional[str] = None, + top_pareto: bool = False, + ) -> List[plt.Figure]: + """Generate separate one-pager for each solution ID. + + Args: + solution_ids: Single solution ID or list of solution IDs or 'all' + plots: Optional list of plot types from PlotType enum + figsize: Figure size for each page + save_path: Optional path to save the figures + top_pareto: If True, loads the one-page summaries for the top Pareto models + + Returns: + List[plt.Figure]: List of generated figures, one per solution + """ + # Convert string plot types to PlotType if necessary + if plots and isinstance(plots[0], str): + try: + plots = [PlotType[plot.upper()] for plot in plots] + except KeyError as e: + raise ValueError(f"Invalid plot type: {e}") + + # Use default plots if none provided + plots = plots or self.default_plots + + # Handle solution IDs based on top_pareto parameter + if top_pareto: + if self.clustered_result is None or not hasattr( + self.clustered_result, "top_solutions" + ): + raise ValueError("No clustered results or top solutions available") + try: + # Try accessing 'sol_id' column if it's a DataFrame + if isinstance(self.clustered_result.top_solutions, pd.DataFrame): + solution_ids = self.clustered_result.top_solutions[ + "sol_id" + ].tolist() + elif isinstance(self.clustered_result.top_solutions, pd.Series): + solution_ids = self.clustered_result.top_solutions.tolist() + elif isinstance(self.clustered_result.top_solutions, list): + solution_ids = self.clustered_result.top_solutions + else: + raise ValueError( + f"Unexpected type for top_solutions: {type(self.clustered_result.top_solutions)}" + ) + solution_ids = [ + str(sid) + for sid in solution_ids + if sid is not None and pd.notna(sid) + ] + if not solution_ids: + raise ValueError("No valid solution IDs found in top solutions") + logger.debug(f"Loading {len(solution_ids)} top solutions") + + except Exception as e: + raise ValueError(f"Error processing top solutions: {str(e)}") + else: + if solution_ids == "all": + solution_ids = list(self.pareto_result.plot_data_collect.keys()) + elif isinstance(solution_ids, str): + solution_ids = [solution_ids] + elif isinstance(solution_ids, (list, tuple)): + solution_ids = list(solution_ids) + else: + raise ValueError( + f"solution_ids must be string or list/tuple, got {type(solution_ids)}" + ) + + if len(solution_ids) > 1 and not top_pareto: + warnings.warn( + "Too many one pagers to load, please either select top_pareto=True " + "or just specify a solution id. Plotting one pager for the first solution id" + ) + solution_ids = [solution_ids[0]] + + # Validate solution IDs + invalid_ids = [ + sid + for sid in solution_ids + if sid not in self.pareto_result.plot_data_collect + ] + if invalid_ids: + raise ValueError(f"Invalid solution IDs: {invalid_ids}") + + figures = [] + try: + if save_path: + os.makedirs(save_path, exist_ok=True) + + for i, solution_id in enumerate(solution_ids): + logger.debug( + f"Generating one-pager for solution {solution_id} ({i+1}/{len(solution_ids)})" + ) + + n_plots = len(plots) + n_rows = (n_plots + 1) // 2 # Ceiling division for number of rows + + # Create figure + fig = plt.figure(figsize=figsize) + + # Create GridSpec with explicit spacing parameters + gs = GridSpec( + n_rows, + 2, + figure=fig, + height_ratios=[1] * n_rows, + top=0.92, # Space for title and metrics + bottom=0.05, # Extend plots to bottom + left=0.08, # Left margin + right=0.92, # Right margin + hspace=0.4, # Vertical space between subplots + wspace=0.2, # Horizontal space between subplots + ) + + # Generate plots for this solution + self._generate_solution_plots(solution_id, plots, gs) + + # Add title and metrics + self._add_title_and_metrics(fig, solution_id) + + if save_path: + save_file = os.path.join(save_path, f"solution_{solution_id}.png") + fig.savefig(save_file, dpi=300, bbox_inches="tight", pad_inches=0.5) + logger.debug(f"Saved figure to {save_file}") + + figures.append(fig) + + except Exception as e: + logger.error(f"Error generating plots: {str(e)}", exc_info=True) + for fig in figures: + plt.close(fig) + raise + + return figures diff --git a/python/src/robyn/robyn.py b/python/src/robyn/robyn.py new file mode 100644 index 000000000..43329dc6a --- /dev/null +++ b/python/src/robyn/robyn.py @@ -0,0 +1,468 @@ +# pyre-strict + +import logging +from logging.handlers import RotatingFileHandler +from pathlib import Path +from typing import Dict, Optional +import copy +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.data.validation.mmmdata_validation import MMMDataValidation +from robyn.data.validation.holidays_data_validation import HolidaysDataValidation +from robyn.data.validation.hyperparameter_validation import HyperparametersValidation + +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.modeling.entities.modelrun_trials_config import TrialsConfig +from robyn.modeling.entities.enums import Models, NevergradAlgorithm +from robyn.modeling.model_executor import ModelExecutor + +from robyn.modeling.pareto.pareto_optimizer import ParetoOptimizer +from robyn.modeling.clustering.cluster_builder import ClusterBuilder +from robyn.modeling.clustering.clustering_config import ClusteringConfig +from robyn.modeling.feature_engineering import FeatureEngineering, FeaturizedMMMData + +from robyn.allocator.optimizer import BudgetAllocator +from robyn.allocator.entities.allocation_params import AllocatorParams +from robyn.allocator.entities.allocation_result import AllocationResult + +from robyn.modeling.pareto.pareto_utils import ParetoUtils +from robyn.reporting.onepager_reporting import OnePager +from robyn.visualization.allocator_visualizer import AllocatorPlotter +from robyn.visualization.cluster_visualizer import ClusterVisualizer +from robyn.visualization.feature_visualization import FeaturePlotter +from robyn.visualization.model_convergence_visualizer import ModelConvergenceVisualizer +from robyn.visualization.pareto_visualizer import ParetoVisualizer +import matplotlib.pyplot as plt + +logger = logging.getLogger(__name__) + + +class Robyn: + """Client interface for the Robyn Marketing Mix Modeling framework.""" + + def __init__( + self, + working_dir: str, + console_log_level: Optional[str] = "INFO", + file_log_level: Optional[str] = "DEBUG", + ): + """ + Initialize Robyn. + + Args: + working_dir: Working directory for logs and outputs + console_level: Logging level for console output + file_level: Logging level for file output + working_dir: Working directory for logs and outputs + console_level: Logging level for console output + file_level: Logging level for file output + """ + self.working_dir = Path(working_dir).resolve() + self.working_dir.mkdir(parents=True, exist_ok=True) + self._setup_logging(console_log_level, file_log_level) + logger.info("Initialized Robyn in %s", working_dir) + + # Core components initialized to None + self.mmm_data = None + self.holidays_data = None + self.hyperparameters = None + self.featurized_mmm_data = None + self.model_outputs = None + self.pareto_result = None + self.cluster_result = None + + def initialize( + self, + mmm_data: MMMData, + holidays_data: HolidaysData, + hyperparameters: Hyperparameters, + ) -> None: + """ + Initialize and validate input data. + + Args: + mmm_data: Marketing mix modeling data + holidays_data: Holiday calendar data + hyperparameters: Model hyperparameters + + Raises: + ValidationError: If any validation fails + """ + logger.info("Validating input data") + try: + # Run validations + MMMDataValidation(mmm_data).validate() + HolidaysDataValidation(holidays_data).validate() + HyperparametersValidation(hyperparameters).validate() + + # Store validated data + self.mmm_data = mmm_data + self.holidays_data = holidays_data + self.hyperparameters = hyperparameters + + # # Feature engineering + # self.featurized_mmm_data = self.feature_engineering() + logger.info("Data initialization complete") + + except Exception as e: + logger.error("Initialization failed: %s", str(e)) + raise + + def feature_engineering( + self, + display_plots: bool = True, + export_plots: bool = False, + ) -> FeaturizedMMMData: + """ + Perform feature engineering on the MMM data. + + This method initializes the FeatureEngineering class with the provided MMM data, + hyperparameters, and holidays data, and performs feature engineering. Optionally, + it can display and/or export plots of the engineered features. + + Args: + display_plots (bool): If True, display plots of the engineered features. Default is True. + export_plots (bool): If True, export plots of the engineered features. Default is False. + + Returns: + FeaturizedMMMData: The featurized MMM data. + + Raises: + ValueError: If the MMM data, hyperparameters, or holidays data are not initialized. + Exception: If an error occurs during feature engineering. + """ + logger.info("Performing feature engineering") + if not all([self.mmm_data, self.hyperparameters, self.holidays_data]): + raise ValueError( + "Please initialize Robyn with mmm_data, hyperparameters, and holidays_data first" + ) + + try: + # Initialize FeatureEngineering and process data + feature_engineering = FeatureEngineering( + self.mmm_data, self.hyperparameters, self.holidays_data + ) + self.featurized_mmm_data = feature_engineering.perform_feature_engineering() + + if display_plots or export_plots: + feature_plotter = FeaturePlotter( + self.mmm_data, self.hyperparameters, self.featurized_mmm_data + ) + feature_plotter.plot_all(display_plots, self.working_dir) + + return self.featurized_mmm_data + + except Exception as e: + logging.error("Error in feature engineering: %s", str(e)) + raise + + def train_models( + self, + trials_config: Optional[TrialsConfig] = None, + ts_validation: Optional[bool] = False, + add_penalty_factor: Optional[bool] = False, + rssd_zero_penalty: Optional[bool] = True, + nevergrad_algo: Optional[str] = NevergradAlgorithm.TWO_POINTS_DE, + model_name: Optional[str] = Models.RIDGE, + cores: Optional[int] = 16, + display_plots: bool = True, + export_plots: bool = False, + ) -> ModelOutputs: + """ + Trains the specified models using the provided configuration and parameters. + + Args: + trials_config (Optional[TrialsConfig]): Configuration for the trials, including the number of trials and iterations. Defaults to None. + ts_validation (Optional[bool]): Whether to perform time series validation. Defaults to False. + add_penalty_factor (Optional[bool]): Whether to add a penalty factor during training. Defaults to False. + nevergrad_algo (Optional[str]): The Nevergrad algorithm to use for optimization. Defaults to NevergradAlgorithm.TWO_POINTS_DE. + model_name (Optional[str]): The name of the model to train. Defaults to Models.RIDGE. + cores (Optional[int]): The number of CPU cores to use for training. Defaults to 16. + display_plots (bool): Whether to display plots after training. Defaults to True. + export_plots (bool): Whether to export plots after training. Defaults to False. + + Returns: + ModelOutputs: The outputs of the trained models. + + Raises: + Exception: If training the models fails. + """ + + self._validate_initialization() + + try: + logger.info("Training models") + trials_config = trials_config or TrialsConfig(trials=5, iterations=2000) + model_executor = ModelExecutor( + mmmdata=self.mmm_data, + holidays_data=self.holidays_data, + hyperparameters=self.hyperparameters, + calibration_input=None, + featurized_mmm_data=self.featurized_mmm_data, + ) + + self.model_outputs = model_executor.model_run( + trials_config=trials_config, + ts_validation=ts_validation, + add_penalty_factor=add_penalty_factor, + rssd_zero_penalty=rssd_zero_penalty, + nevergrad_algo=nevergrad_algo, + model_name=model_name, + cores=cores, + ) + except Exception as e: + logger.error("Training models failed: %s", str(e)) + raise + + if display_plots or export_plots: + visualizer = ModelConvergenceVisualizer(self.model_outputs) + visualizer.plot_all(display_plots, self.working_dir) + + def evaluate_models( + self, + pareto_config: Optional[Dict] = None, + cluster_config: Optional[ClusteringConfig] = None, + display_plots: bool = True, + export_plots: bool = False, + ) -> None: + """ + Evaluates the trained models using Pareto optimization and optional clustering. + Parameters: + pareto_config (Optional[Dict]): Configuration for Pareto optimization. If not provided, default settings will be used. + cluster_config (Optional[ClusteringConfig]): Configuration for clustering the models. If not provided, clustering will be skipped. + display_plots (bool): If True, plots will be displayed. Default is True. + export_plots (bool): If True, plots will be exported. Default is False. + Raises: + ValueError: If models have not been trained before evaluation. + Exception: If any error occurs during the evaluation process. + Returns: + None + """ + if not self.model_outputs: + raise ValueError("Must train models before evaluation") + + try: + logger.info("Evaluating models") + + # Pareto optimization + pareto_config = pareto_config or { + "pareto_fronts": "auto", + "min_candidates": 100, + } + pareto_optimizer = ParetoOptimizer( + mmm_data=self.mmm_data, + model_outputs=self.model_outputs, + hyperparameter=self.hyperparameters, + featurized_mmm_data=self.featurized_mmm_data, + holidays_data=self.holidays_data, + ) + self.pareto_result = pareto_optimizer.optimize(**pareto_config) + unfiltered_pareto_result = copy.deepcopy(self.pareto_result) + + # Optional clustering + is_clustered = False + if cluster_config: + cluster_builder = ClusterBuilder(self.pareto_result) + self.cluster_result = cluster_builder.cluster_models(cluster_config) + is_clustered = True + + self.pareto_result = ParetoUtils().process_pareto_clustered_results( + self.pareto_result, self.cluster_result, is_clustered + ) + if display_plots or export_plots: + pareto_visualizer = ParetoVisualizer( + pareto_result=self.pareto_result, + mmm_data=self.mmm_data, + holiday_data=self.holidays_data, + hyperparameter=self.hyperparameters, + featurized_mmm_data=self.featurized_mmm_data, + unfiltered_pareto_result=unfiltered_pareto_result, + model_outputs=self.model_outputs, + ) + pareto_visualizer.plot_all(display_plots, self.working_dir) + if self.cluster_result: + cluster_visualizer = ClusterVisualizer( + self.pareto_result, + self.cluster_result, + self.mmm_data, + ) + cluster_visualizer.plot_all(display_plots, self.working_dir) + plt.close("all") + logger.info("Model evaluation complete") + + except Exception as e: + logger.error("Model evaluation failed: %s", str(e)) + raise + + def train_and_evaluate_models( + self, + trials_config: Optional[TrialsConfig] = None, + ts_validation: Optional[bool] = False, + add_penalty_factor: Optional[bool] = False, + rssd_zero_penalty: Optional[bool] = True, + nevergrad_algo: Optional[str] = NevergradAlgorithm.TWO_POINTS_DE, + model_name: Optional[str] = Models.RIDGE, + cores: Optional[int] = 16, + pareto_config: Optional[Dict] = None, + cluster_config: Optional[ClusteringConfig] = None, + display_plots: bool = True, + export_plots: bool = False, + ) -> None: + """ + Trains and evaluates models based on the provided configurations. + Args: + trials_config (Optional[TrialsConfig]): Configuration for the trials during model training. + model_config (Optional[Dict]): Configuration for the models to be trained. + pareto_config (Optional[Dict]): Configuration for Pareto front evaluation. + cluster_config (Optional[ClusteringConfig]): Configuration for clustering during evaluation. + display_plots (bool): Whether to display plots during training and evaluation. Defaults to True. + export_plots (bool): Whether to export plots during training and evaluation. Defaults to False. + Returns: + None + """ + self.train_models( + trials_config, + ts_validation, + add_penalty_factor, + rssd_zero_penalty, + nevergrad_algo, + model_name, + cores, + display_plots, + export_plots, + ) + self.evaluate_models(pareto_config, cluster_config, display_plots, export_plots) + + def optimize_budget( + self, + allocator_params: AllocatorParams, + select_model: Optional[str] = None, + display_plots: bool = True, + export_plots: bool = False, + ) -> AllocationResult: + """ + Optimize the budget allocation based on the given configuration. + Args: + allocation_config (AllocationConfig): Configuration for budget allocation. + select_model (Optional[str], optional): Specific model to use for allocation. Defaults to None. + display_plots (bool, optional): Whether to display plots. Defaults to True. + export_plots (bool, optional): Whether to export plots. Defaults to False. + Returns: + AllocationResult: The result of the budget allocation. + Raises: + ValueError: If models have not been evaluated before budget optimization. + Exception: If budget optimization fails. + """ + + if not self.pareto_result: + raise ValueError("Must evaluate models before budget optimization") + + try: + logger.info("Optimizing budget allocation") + + if select_model is None: + pareto_solutions = self.pareto_result.pareto_solutions + if ( + pareto_solutions + and pareto_solutions[0] is not None + and pareto_solutions[0] != "" + ): + select_model = pareto_solutions[0] + elif ( + len(pareto_solutions) > 1 + and pareto_solutions[1] is not None + and pareto_solutions[1] != "" + ): + select_model = pareto_solutions[1] + + logger.info("Selected model for budget optimization: %s", select_model) + + allocator = BudgetAllocator( + mmm_data=self.mmm_data, + featurized_mmm_data=self.featurized_mmm_data, + hyperparameters=self.hyperparameters, + pareto_result=self.pareto_result, + select_model=select_model, + params=allocator_params, + ) + + allocation_result = allocator.optimize() + + if display_plots or export_plots: + allocator_visualizer = AllocatorPlotter( + allocation_result=allocation_result, budget_allocator=allocator + ) + allocator_visualizer.plot_all(display_plots, self.working_dir) + + logger.info("Budget optimization complete") + return allocation_result + + except Exception as e: + logger.error("Budget optimization failed: %s", str(e)) + raise + + def generate_one_pager(self, solution_id: Optional[str] = None) -> None: + """ + Generate one-page summary report. + + Args: + plots: Optional list of specific plots to include + solution_id: Optional specific solution ID to plot + """ + try: + onepager = OnePager( + pareto_result=self.pareto_result, + clustered_result=self.cluster_result, + hyperparameter=self.hyperparameters, + mmm_data=self.mmm_data, + holidays_data=self.holidays_data, + ) + + # Set top_pareto based on whether solution_id is provided + top_pareto = solution_id is None + + figures = onepager.generate_one_pager( + solution_ids=solution_id if solution_id else "all", + top_pareto=top_pareto, + ) + return figures + + except Exception as e: + logging.error("One-pager generation failed: %s", str(e)) + raise + + def _setup_logging(self, console_level: str, file_level: str) -> None: + """Configure logging with console and file handlers.""" + + # Console handler + console = logging.StreamHandler() + console.setLevel(getattr(logging, console_level)) + console.setFormatter(logging.Formatter("%(levelname)s: %(message)s")) + + # File handler + # log_file = self.working_dir / "logs/robynpy_%(asctime)s.log" + log_file = self.working_dir / "logs/robynpy.log" + log_file.parent.mkdir(parents=True, exist_ok=True) + file_handler = RotatingFileHandler( + log_file, maxBytes=10 * 1024 * 1024, backupCount=5 + ) + file_handler.setLevel(getattr(logging, file_level)) + file_handler.setFormatter( + logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s") + ) + + logger.addHandler(console) + logger.addHandler(file_handler) + + def _validate_initialization(self) -> None: + """Validate that required components are initialized.""" + if not all( + [ + self.mmm_data, + self.holidays_data, + self.hyperparameters, + self.featurized_mmm_data, + ] + ): + raise ValueError("Must call initialize() first") diff --git a/python/src/robyn/tutorials/resources/dt_prophet_holidays.csv b/python/src/robyn/tutorials/resources/dt_prophet_holidays.csv new file mode 100644 index 000000000..b00051298 --- /dev/null +++ b/python/src/robyn/tutorials/resources/dt_prophet_holidays.csv @@ -0,0 +1,87652 @@ +"ds","holiday","country","year" +"1995-01-01","New Year's Day","AD",1995 +"1995-01-06","Epiphany","AD",1995 +"1995-02-28","Carnival","AD",1995 +"1995-03-14","Constitution Day","AD",1995 +"1995-04-14","Good Friday","AD",1995 +"1995-04-17","Easter Monday","AD",1995 +"1995-05-01","Labor Day","AD",1995 +"1995-06-05","Whit Monday","AD",1995 +"1995-08-15","Assumption Day","AD",1995 +"1995-09-08","National Day","AD",1995 +"1995-11-01","All Saints' Day","AD",1995 +"1995-12-08","Immaculate Conception Day","AD",1995 +"1995-12-25","Christmas Day","AD",1995 +"1995-12-26","Saint Stephen's Day","AD",1995 +"1996-01-01","New Year's Day","AD",1996 +"1996-01-06","Epiphany","AD",1996 +"1996-02-20","Carnival","AD",1996 +"1996-03-14","Constitution Day","AD",1996 +"1996-04-05","Good Friday","AD",1996 +"1996-04-08","Easter Monday","AD",1996 +"1996-05-01","Labor Day","AD",1996 +"1996-05-27","Whit Monday","AD",1996 +"1996-08-15","Assumption Day","AD",1996 +"1996-09-08","National Day","AD",1996 +"1996-11-01","All Saints' Day","AD",1996 +"1996-12-08","Immaculate Conception Day","AD",1996 +"1996-12-25","Christmas Day","AD",1996 +"1996-12-26","Saint Stephen's Day","AD",1996 +"1997-01-01","New Year's Day","AD",1997 +"1997-01-06","Epiphany","AD",1997 +"1997-02-11","Carnival","AD",1997 +"1997-03-14","Constitution Day","AD",1997 +"1997-03-28","Good Friday","AD",1997 +"1997-03-31","Easter Monday","AD",1997 +"1997-05-01","Labor Day","AD",1997 +"1997-05-19","Whit Monday","AD",1997 +"1997-08-15","Assumption Day","AD",1997 +"1997-09-08","National Day","AD",1997 +"1997-11-01","All Saints' Day","AD",1997 +"1997-12-08","Immaculate Conception Day","AD",1997 +"1997-12-25","Christmas Day","AD",1997 +"1997-12-26","Saint Stephen's Day","AD",1997 +"1998-01-01","New Year's Day","AD",1998 +"1998-01-06","Epiphany","AD",1998 +"1998-02-24","Carnival","AD",1998 +"1998-03-14","Constitution Day","AD",1998 +"1998-04-10","Good Friday","AD",1998 +"1998-04-13","Easter Monday","AD",1998 +"1998-05-01","Labor Day","AD",1998 +"1998-06-01","Whit Monday","AD",1998 +"1998-08-15","Assumption Day","AD",1998 +"1998-09-08","National Day","AD",1998 +"1998-11-01","All Saints' Day","AD",1998 +"1998-12-08","Immaculate Conception Day","AD",1998 +"1998-12-25","Christmas Day","AD",1998 +"1998-12-26","Saint Stephen's Day","AD",1998 +"1999-01-01","New Year's Day","AD",1999 +"1999-01-06","Epiphany","AD",1999 +"1999-02-16","Carnival","AD",1999 +"1999-03-14","Constitution Day","AD",1999 +"1999-04-02","Good Friday","AD",1999 +"1999-04-05","Easter Monday","AD",1999 +"1999-05-01","Labor Day","AD",1999 +"1999-05-24","Whit Monday","AD",1999 +"1999-08-15","Assumption Day","AD",1999 +"1999-09-08","National Day","AD",1999 +"1999-11-01","All Saints' Day","AD",1999 +"1999-12-08","Immaculate Conception Day","AD",1999 +"1999-12-25","Christmas Day","AD",1999 +"1999-12-26","Saint Stephen's Day","AD",1999 +"2000-01-01","New Year's Day","AD",2000 +"2000-01-06","Epiphany","AD",2000 +"2000-03-07","Carnival","AD",2000 +"2000-03-14","Constitution Day","AD",2000 +"2000-04-21","Good Friday","AD",2000 +"2000-04-24","Easter Monday","AD",2000 +"2000-05-01","Labor Day","AD",2000 +"2000-06-12","Whit Monday","AD",2000 +"2000-08-15","Assumption Day","AD",2000 +"2000-09-08","National Day","AD",2000 +"2000-11-01","All Saints' Day","AD",2000 +"2000-12-08","Immaculate Conception Day","AD",2000 +"2000-12-25","Christmas Day","AD",2000 +"2000-12-26","Saint Stephen's Day","AD",2000 +"2001-01-01","New Year's Day","AD",2001 +"2001-01-06","Epiphany","AD",2001 +"2001-02-27","Carnival","AD",2001 +"2001-03-14","Constitution Day","AD",2001 +"2001-04-13","Good Friday","AD",2001 +"2001-04-16","Easter Monday","AD",2001 +"2001-05-01","Labor Day","AD",2001 +"2001-06-04","Whit Monday","AD",2001 +"2001-08-15","Assumption Day","AD",2001 +"2001-09-08","National Day","AD",2001 +"2001-11-01","All Saints' Day","AD",2001 +"2001-12-08","Immaculate Conception Day","AD",2001 +"2001-12-25","Christmas Day","AD",2001 +"2001-12-26","Saint Stephen's Day","AD",2001 +"2002-01-01","New Year's Day","AD",2002 +"2002-01-06","Epiphany","AD",2002 +"2002-02-12","Carnival","AD",2002 +"2002-03-14","Constitution Day","AD",2002 +"2002-03-29","Good Friday","AD",2002 +"2002-04-01","Easter Monday","AD",2002 +"2002-05-01","Labor Day","AD",2002 +"2002-05-20","Whit Monday","AD",2002 +"2002-08-15","Assumption Day","AD",2002 +"2002-09-08","National Day","AD",2002 +"2002-11-01","All Saints' Day","AD",2002 +"2002-12-08","Immaculate Conception Day","AD",2002 +"2002-12-25","Christmas Day","AD",2002 +"2002-12-26","Saint Stephen's Day","AD",2002 +"2003-01-01","New Year's Day","AD",2003 +"2003-01-06","Epiphany","AD",2003 +"2003-03-04","Carnival","AD",2003 +"2003-03-14","Constitution Day","AD",2003 +"2003-04-18","Good Friday","AD",2003 +"2003-04-21","Easter Monday","AD",2003 +"2003-05-01","Labor Day","AD",2003 +"2003-06-09","Whit Monday","AD",2003 +"2003-08-15","Assumption Day","AD",2003 +"2003-09-08","National Day","AD",2003 +"2003-11-01","All Saints' Day","AD",2003 +"2003-12-08","Immaculate Conception Day","AD",2003 +"2003-12-25","Christmas Day","AD",2003 +"2003-12-26","Saint Stephen's Day","AD",2003 +"2004-01-01","New Year's Day","AD",2004 +"2004-01-06","Epiphany","AD",2004 +"2004-02-24","Carnival","AD",2004 +"2004-03-14","Constitution Day","AD",2004 +"2004-04-09","Good Friday","AD",2004 +"2004-04-12","Easter Monday","AD",2004 +"2004-05-01","Labor Day","AD",2004 +"2004-05-31","Whit Monday","AD",2004 +"2004-08-15","Assumption Day","AD",2004 +"2004-09-08","National Day","AD",2004 +"2004-11-01","All Saints' Day","AD",2004 +"2004-12-08","Immaculate Conception Day","AD",2004 +"2004-12-25","Christmas Day","AD",2004 +"2004-12-26","Saint Stephen's Day","AD",2004 +"2005-01-01","New Year's Day","AD",2005 +"2005-01-06","Epiphany","AD",2005 +"2005-02-08","Carnival","AD",2005 +"2005-03-14","Constitution Day","AD",2005 +"2005-03-25","Good Friday","AD",2005 +"2005-03-28","Easter Monday","AD",2005 +"2005-05-01","Labor Day","AD",2005 +"2005-05-16","Whit Monday","AD",2005 +"2005-08-15","Assumption Day","AD",2005 +"2005-09-08","National Day","AD",2005 +"2005-11-01","All Saints' Day","AD",2005 +"2005-12-08","Immaculate Conception Day","AD",2005 +"2005-12-25","Christmas Day","AD",2005 +"2005-12-26","Saint Stephen's Day","AD",2005 +"2006-01-01","New Year's Day","AD",2006 +"2006-01-06","Epiphany","AD",2006 +"2006-02-28","Carnival","AD",2006 +"2006-03-14","Constitution Day","AD",2006 +"2006-04-14","Good Friday","AD",2006 +"2006-04-17","Easter Monday","AD",2006 +"2006-05-01","Labor Day","AD",2006 +"2006-06-05","Whit Monday","AD",2006 +"2006-08-15","Assumption Day","AD",2006 +"2006-09-08","National Day","AD",2006 +"2006-11-01","All Saints' Day","AD",2006 +"2006-12-08","Immaculate Conception Day","AD",2006 +"2006-12-25","Christmas Day","AD",2006 +"2006-12-26","Saint Stephen's Day","AD",2006 +"2007-01-01","New Year's Day","AD",2007 +"2007-01-06","Epiphany","AD",2007 +"2007-02-20","Carnival","AD",2007 +"2007-03-14","Constitution Day","AD",2007 +"2007-04-06","Good Friday","AD",2007 +"2007-04-09","Easter Monday","AD",2007 +"2007-05-01","Labor Day","AD",2007 +"2007-05-28","Whit Monday","AD",2007 +"2007-08-15","Assumption Day","AD",2007 +"2007-09-08","National Day","AD",2007 +"2007-11-01","All Saints' Day","AD",2007 +"2007-12-08","Immaculate Conception Day","AD",2007 +"2007-12-25","Christmas Day","AD",2007 +"2007-12-26","Saint Stephen's Day","AD",2007 +"2008-01-01","New Year's Day","AD",2008 +"2008-01-06","Epiphany","AD",2008 +"2008-02-05","Carnival","AD",2008 +"2008-03-14","Constitution Day","AD",2008 +"2008-03-21","Good Friday","AD",2008 +"2008-03-24","Easter Monday","AD",2008 +"2008-05-01","Labor Day","AD",2008 +"2008-05-12","Whit Monday","AD",2008 +"2008-08-15","Assumption Day","AD",2008 +"2008-09-08","National Day","AD",2008 +"2008-11-01","All Saints' Day","AD",2008 +"2008-12-08","Immaculate Conception Day","AD",2008 +"2008-12-25","Christmas Day","AD",2008 +"2008-12-26","Saint Stephen's Day","AD",2008 +"2009-01-01","New Year's Day","AD",2009 +"2009-01-06","Epiphany","AD",2009 +"2009-02-24","Carnival","AD",2009 +"2009-03-14","Constitution Day","AD",2009 +"2009-04-10","Good Friday","AD",2009 +"2009-04-13","Easter Monday","AD",2009 +"2009-05-01","Labor Day","AD",2009 +"2009-06-01","Whit Monday","AD",2009 +"2009-08-15","Assumption Day","AD",2009 +"2009-09-08","National Day","AD",2009 +"2009-11-01","All Saints' Day","AD",2009 +"2009-12-08","Immaculate Conception Day","AD",2009 +"2009-12-25","Christmas Day","AD",2009 +"2009-12-26","Saint Stephen's Day","AD",2009 +"2010-01-01","New Year's Day","AD",2010 +"2010-01-06","Epiphany","AD",2010 +"2010-02-16","Carnival","AD",2010 +"2010-03-14","Constitution Day","AD",2010 +"2010-04-02","Good Friday","AD",2010 +"2010-04-05","Easter Monday","AD",2010 +"2010-05-01","Labor Day","AD",2010 +"2010-05-24","Whit Monday","AD",2010 +"2010-08-15","Assumption Day","AD",2010 +"2010-09-08","National Day","AD",2010 +"2010-11-01","All Saints' Day","AD",2010 +"2010-12-08","Immaculate Conception Day","AD",2010 +"2010-12-25","Christmas Day","AD",2010 +"2010-12-26","Saint Stephen's Day","AD",2010 +"2011-01-01","New Year's Day","AD",2011 +"2011-01-06","Epiphany","AD",2011 +"2011-03-08","Carnival","AD",2011 +"2011-03-14","Constitution Day","AD",2011 +"2011-04-22","Good Friday","AD",2011 +"2011-04-25","Easter Monday","AD",2011 +"2011-05-01","Labor Day","AD",2011 +"2011-06-13","Whit Monday","AD",2011 +"2011-08-15","Assumption Day","AD",2011 +"2011-09-08","National Day","AD",2011 +"2011-11-01","All Saints' Day","AD",2011 +"2011-12-08","Immaculate Conception Day","AD",2011 +"2011-12-25","Christmas Day","AD",2011 +"2011-12-26","Saint Stephen's Day","AD",2011 +"2012-01-01","New Year's Day","AD",2012 +"2012-01-06","Epiphany","AD",2012 +"2012-02-21","Carnival","AD",2012 +"2012-03-14","Constitution Day","AD",2012 +"2012-04-06","Good Friday","AD",2012 +"2012-04-09","Easter Monday","AD",2012 +"2012-05-01","Labor Day","AD",2012 +"2012-05-28","Whit Monday","AD",2012 +"2012-08-15","Assumption Day","AD",2012 +"2012-09-08","National Day","AD",2012 +"2012-11-01","All Saints' Day","AD",2012 +"2012-12-08","Immaculate Conception Day","AD",2012 +"2012-12-25","Christmas Day","AD",2012 +"2012-12-26","Saint Stephen's Day","AD",2012 +"2013-01-01","New Year's Day","AD",2013 +"2013-01-06","Epiphany","AD",2013 +"2013-02-12","Carnival","AD",2013 +"2013-03-14","Constitution Day","AD",2013 +"2013-03-29","Good Friday","AD",2013 +"2013-04-01","Easter Monday","AD",2013 +"2013-05-01","Labor Day","AD",2013 +"2013-05-20","Whit Monday","AD",2013 +"2013-08-15","Assumption Day","AD",2013 +"2013-09-08","National Day","AD",2013 +"2013-11-01","All Saints' Day","AD",2013 +"2013-12-08","Immaculate Conception Day","AD",2013 +"2013-12-25","Christmas Day","AD",2013 +"2013-12-26","Saint Stephen's Day","AD",2013 +"2014-01-01","New Year's Day","AD",2014 +"2014-01-06","Epiphany","AD",2014 +"2014-03-04","Carnival","AD",2014 +"2014-03-14","Constitution Day","AD",2014 +"2014-04-18","Good Friday","AD",2014 +"2014-04-21","Easter Monday","AD",2014 +"2014-05-01","Labor Day","AD",2014 +"2014-06-09","Whit Monday","AD",2014 +"2014-08-15","Assumption Day","AD",2014 +"2014-09-08","National Day","AD",2014 +"2014-11-01","All Saints' Day","AD",2014 +"2014-12-08","Immaculate Conception Day","AD",2014 +"2014-12-25","Christmas Day","AD",2014 +"2014-12-26","Saint Stephen's Day","AD",2014 +"2015-01-01","New Year's Day","AD",2015 +"2015-01-06","Epiphany","AD",2015 +"2015-02-17","Carnival","AD",2015 +"2015-03-14","Constitution Day","AD",2015 +"2015-04-03","Good Friday","AD",2015 +"2015-04-06","Easter Monday","AD",2015 +"2015-05-01","Labor Day","AD",2015 +"2015-05-25","Whit Monday","AD",2015 +"2015-08-15","Assumption Day","AD",2015 +"2015-09-08","National Day","AD",2015 +"2015-11-01","All Saints' Day","AD",2015 +"2015-12-08","Immaculate Conception Day","AD",2015 +"2015-12-25","Christmas Day","AD",2015 +"2015-12-26","Saint Stephen's Day","AD",2015 +"2016-01-01","New Year's Day","AD",2016 +"2016-01-06","Epiphany","AD",2016 +"2016-02-09","Carnival","AD",2016 +"2016-03-14","Constitution Day","AD",2016 +"2016-03-25","Good Friday","AD",2016 +"2016-03-28","Easter Monday","AD",2016 +"2016-05-01","Labor Day","AD",2016 +"2016-05-16","Whit Monday","AD",2016 +"2016-08-15","Assumption Day","AD",2016 +"2016-09-08","National Day","AD",2016 +"2016-11-01","All Saints' Day","AD",2016 +"2016-12-08","Immaculate Conception Day","AD",2016 +"2016-12-25","Christmas Day","AD",2016 +"2016-12-26","Saint Stephen's Day","AD",2016 +"2017-01-01","New Year's Day","AD",2017 +"2017-01-06","Epiphany","AD",2017 +"2017-02-28","Carnival","AD",2017 +"2017-03-14","Constitution Day","AD",2017 +"2017-04-14","Good Friday","AD",2017 +"2017-04-17","Easter Monday","AD",2017 +"2017-05-01","Labor Day","AD",2017 +"2017-06-05","Whit Monday","AD",2017 +"2017-08-15","Assumption Day","AD",2017 +"2017-09-08","National Day","AD",2017 +"2017-11-01","All Saints' Day","AD",2017 +"2017-12-08","Immaculate Conception Day","AD",2017 +"2017-12-25","Christmas Day","AD",2017 +"2017-12-26","Saint Stephen's Day","AD",2017 +"2018-01-01","New Year's Day","AD",2018 +"2018-01-06","Epiphany","AD",2018 +"2018-02-13","Carnival","AD",2018 +"2018-03-14","Constitution Day","AD",2018 +"2018-03-30","Good Friday","AD",2018 +"2018-04-02","Easter Monday","AD",2018 +"2018-05-01","Labor Day","AD",2018 +"2018-05-21","Whit Monday","AD",2018 +"2018-08-15","Assumption Day","AD",2018 +"2018-09-08","National Day","AD",2018 +"2018-11-01","All Saints' Day","AD",2018 +"2018-12-08","Immaculate Conception Day","AD",2018 +"2018-12-25","Christmas Day","AD",2018 +"2018-12-26","Saint Stephen's Day","AD",2018 +"2019-01-01","New Year's Day","AD",2019 +"2019-01-06","Epiphany","AD",2019 +"2019-03-05","Carnival","AD",2019 +"2019-03-14","Constitution Day","AD",2019 +"2019-04-19","Good Friday","AD",2019 +"2019-04-22","Easter Monday","AD",2019 +"2019-05-01","Labor Day","AD",2019 +"2019-06-10","Whit Monday","AD",2019 +"2019-08-15","Assumption Day","AD",2019 +"2019-09-08","National Day","AD",2019 +"2019-11-01","All Saints' Day","AD",2019 +"2019-12-08","Immaculate Conception Day","AD",2019 +"2019-12-25","Christmas Day","AD",2019 +"2019-12-26","Saint Stephen's Day","AD",2019 +"2020-01-01","New Year's Day","AD",2020 +"2020-01-06","Epiphany","AD",2020 +"2020-02-25","Carnival","AD",2020 +"2020-03-14","Constitution Day","AD",2020 +"2020-04-10","Good Friday","AD",2020 +"2020-04-13","Easter Monday","AD",2020 +"2020-05-01","Labor Day","AD",2020 +"2020-06-01","Whit Monday","AD",2020 +"2020-08-15","Assumption Day","AD",2020 +"2020-09-08","National Day","AD",2020 +"2020-11-01","All Saints' Day","AD",2020 +"2020-12-08","Immaculate Conception Day","AD",2020 +"2020-12-25","Christmas Day","AD",2020 +"2020-12-26","Saint Stephen's Day","AD",2020 +"2021-01-01","New Year's Day","AD",2021 +"2021-01-06","Epiphany","AD",2021 +"2021-02-16","Carnival","AD",2021 +"2021-03-14","Constitution Day","AD",2021 +"2021-04-02","Good Friday","AD",2021 +"2021-04-05","Easter Monday","AD",2021 +"2021-05-01","Labor Day","AD",2021 +"2021-05-24","Whit Monday","AD",2021 +"2021-08-15","Assumption Day","AD",2021 +"2021-09-08","National Day","AD",2021 +"2021-11-01","All Saints' Day","AD",2021 +"2021-12-08","Immaculate Conception Day","AD",2021 +"2021-12-25","Christmas Day","AD",2021 +"2021-12-26","Saint Stephen's Day","AD",2021 +"2022-01-01","New Year's Day","AD",2022 +"2022-01-06","Epiphany","AD",2022 +"2022-03-01","Carnival","AD",2022 +"2022-03-14","Constitution Day","AD",2022 +"2022-04-15","Good Friday","AD",2022 +"2022-04-18","Easter Monday","AD",2022 +"2022-05-01","Labor Day","AD",2022 +"2022-06-06","Whit Monday","AD",2022 +"2022-08-15","Assumption Day","AD",2022 +"2022-09-08","National Day","AD",2022 +"2022-11-01","All Saints' Day","AD",2022 +"2022-12-08","Immaculate Conception Day","AD",2022 +"2022-12-25","Christmas Day","AD",2022 +"2022-12-26","Saint Stephen's Day","AD",2022 +"2023-01-01","New Year's Day","AD",2023 +"2023-01-06","Epiphany","AD",2023 +"2023-02-21","Carnival","AD",2023 +"2023-03-14","Constitution Day","AD",2023 +"2023-04-07","Good Friday","AD",2023 +"2023-04-10","Easter Monday","AD",2023 +"2023-05-01","Labor Day","AD",2023 +"2023-05-29","Whit Monday","AD",2023 +"2023-08-15","Assumption Day","AD",2023 +"2023-09-08","National Day","AD",2023 +"2023-11-01","All Saints' Day","AD",2023 +"2023-12-08","Immaculate Conception Day","AD",2023 +"2023-12-25","Christmas Day","AD",2023 +"2023-12-26","Saint Stephen's Day","AD",2023 +"2024-01-01","New Year's Day","AD",2024 +"2024-01-06","Epiphany","AD",2024 +"2024-02-13","Carnival","AD",2024 +"2024-03-14","Constitution Day","AD",2024 +"2024-03-29","Good Friday","AD",2024 +"2024-04-01","Easter Monday","AD",2024 +"2024-05-01","Labor Day","AD",2024 +"2024-05-20","Whit Monday","AD",2024 +"2024-08-15","Assumption Day","AD",2024 +"2024-09-08","National Day","AD",2024 +"2024-11-01","All Saints' Day","AD",2024 +"2024-12-08","Immaculate Conception Day","AD",2024 +"2024-12-25","Christmas Day","AD",2024 +"2024-12-26","Saint Stephen's Day","AD",2024 +"2025-01-01","New Year's Day","AD",2025 +"2025-01-06","Epiphany","AD",2025 +"2025-03-04","Carnival","AD",2025 +"2025-03-14","Constitution Day","AD",2025 +"2025-04-18","Good Friday","AD",2025 +"2025-04-21","Easter Monday","AD",2025 +"2025-05-01","Labor Day","AD",2025 +"2025-06-09","Whit Monday","AD",2025 +"2025-08-15","Assumption Day","AD",2025 +"2025-09-08","National Day","AD",2025 +"2025-11-01","All Saints' Day","AD",2025 +"2025-12-08","Immaculate Conception Day","AD",2025 +"2025-12-25","Christmas Day","AD",2025 +"2025-12-26","Saint Stephen's Day","AD",2025 +"2026-01-01","New Year's Day","AD",2026 +"2026-01-06","Epiphany","AD",2026 +"2026-02-17","Carnival","AD",2026 +"2026-03-14","Constitution Day","AD",2026 +"2026-04-03","Good Friday","AD",2026 +"2026-04-06","Easter Monday","AD",2026 +"2026-05-01","Labor Day","AD",2026 +"2026-05-25","Whit Monday","AD",2026 +"2026-08-15","Assumption Day","AD",2026 +"2026-09-08","National Day","AD",2026 +"2026-11-01","All Saints' Day","AD",2026 +"2026-12-08","Immaculate Conception Day","AD",2026 +"2026-12-25","Christmas Day","AD",2026 +"2026-12-26","Saint Stephen's Day","AD",2026 +"2027-01-01","New Year's Day","AD",2027 +"2027-01-06","Epiphany","AD",2027 +"2027-02-09","Carnival","AD",2027 +"2027-03-14","Constitution Day","AD",2027 +"2027-03-26","Good Friday","AD",2027 +"2027-03-29","Easter Monday","AD",2027 +"2027-05-01","Labor Day","AD",2027 +"2027-05-17","Whit Monday","AD",2027 +"2027-08-15","Assumption Day","AD",2027 +"2027-09-08","National Day","AD",2027 +"2027-11-01","All Saints' Day","AD",2027 +"2027-12-08","Immaculate Conception Day","AD",2027 +"2027-12-25","Christmas Day","AD",2027 +"2027-12-26","Saint Stephen's Day","AD",2027 +"2028-01-01","New Year's Day","AD",2028 +"2028-01-06","Epiphany","AD",2028 +"2028-02-29","Carnival","AD",2028 +"2028-03-14","Constitution Day","AD",2028 +"2028-04-14","Good Friday","AD",2028 +"2028-04-17","Easter Monday","AD",2028 +"2028-05-01","Labor Day","AD",2028 +"2028-06-05","Whit Monday","AD",2028 +"2028-08-15","Assumption Day","AD",2028 +"2028-09-08","National Day","AD",2028 +"2028-11-01","All Saints' Day","AD",2028 +"2028-12-08","Immaculate Conception Day","AD",2028 +"2028-12-25","Christmas Day","AD",2028 +"2028-12-26","Saint Stephen's Day","AD",2028 +"2029-01-01","New Year's Day","AD",2029 +"2029-01-06","Epiphany","AD",2029 +"2029-02-13","Carnival","AD",2029 +"2029-03-14","Constitution Day","AD",2029 +"2029-03-30","Good Friday","AD",2029 +"2029-04-02","Easter Monday","AD",2029 +"2029-05-01","Labor Day","AD",2029 +"2029-05-21","Whit Monday","AD",2029 +"2029-08-15","Assumption Day","AD",2029 +"2029-09-08","National Day","AD",2029 +"2029-11-01","All Saints' Day","AD",2029 +"2029-12-08","Immaculate Conception Day","AD",2029 +"2029-12-25","Christmas Day","AD",2029 +"2029-12-26","Saint Stephen's Day","AD",2029 +"2030-01-01","New Year's Day","AD",2030 +"2030-01-06","Epiphany","AD",2030 +"2030-03-05","Carnival","AD",2030 +"2030-03-14","Constitution Day","AD",2030 +"2030-04-19","Good Friday","AD",2030 +"2030-04-22","Easter Monday","AD",2030 +"2030-05-01","Labor Day","AD",2030 +"2030-06-10","Whit Monday","AD",2030 +"2030-08-15","Assumption Day","AD",2030 +"2030-09-08","National Day","AD",2030 +"2030-11-01","All Saints' Day","AD",2030 +"2030-12-08","Immaculate Conception Day","AD",2030 +"2030-12-25","Christmas Day","AD",2030 +"2030-12-26","Saint Stephen's Day","AD",2030 +"2031-01-01","New Year's Day","AD",2031 +"2031-01-06","Epiphany","AD",2031 +"2031-02-25","Carnival","AD",2031 +"2031-03-14","Constitution Day","AD",2031 +"2031-04-11","Good Friday","AD",2031 +"2031-04-14","Easter Monday","AD",2031 +"2031-05-01","Labor Day","AD",2031 +"2031-06-02","Whit Monday","AD",2031 +"2031-08-15","Assumption Day","AD",2031 +"2031-09-08","National Day","AD",2031 +"2031-11-01","All Saints' Day","AD",2031 +"2031-12-08","Immaculate Conception Day","AD",2031 +"2031-12-25","Christmas Day","AD",2031 +"2031-12-26","Saint Stephen's Day","AD",2031 +"2032-01-01","New Year's Day","AD",2032 +"2032-01-06","Epiphany","AD",2032 +"2032-02-10","Carnival","AD",2032 +"2032-03-14","Constitution Day","AD",2032 +"2032-03-26","Good Friday","AD",2032 +"2032-03-29","Easter Monday","AD",2032 +"2032-05-01","Labor Day","AD",2032 +"2032-05-17","Whit Monday","AD",2032 +"2032-08-15","Assumption Day","AD",2032 +"2032-09-08","National Day","AD",2032 +"2032-11-01","All Saints' Day","AD",2032 +"2032-12-08","Immaculate Conception Day","AD",2032 +"2032-12-25","Christmas Day","AD",2032 +"2032-12-26","Saint Stephen's Day","AD",2032 +"2033-01-01","New Year's Day","AD",2033 +"2033-01-06","Epiphany","AD",2033 +"2033-03-01","Carnival","AD",2033 +"2033-03-14","Constitution Day","AD",2033 +"2033-04-15","Good Friday","AD",2033 +"2033-04-18","Easter Monday","AD",2033 +"2033-05-01","Labor Day","AD",2033 +"2033-06-06","Whit Monday","AD",2033 +"2033-08-15","Assumption Day","AD",2033 +"2033-09-08","National Day","AD",2033 +"2033-11-01","All Saints' Day","AD",2033 +"2033-12-08","Immaculate Conception Day","AD",2033 +"2033-12-25","Christmas Day","AD",2033 +"2033-12-26","Saint Stephen's Day","AD",2033 +"2034-01-01","New Year's Day","AD",2034 +"2034-01-06","Epiphany","AD",2034 +"2034-02-21","Carnival","AD",2034 +"2034-03-14","Constitution Day","AD",2034 +"2034-04-07","Good Friday","AD",2034 +"2034-04-10","Easter Monday","AD",2034 +"2034-05-01","Labor Day","AD",2034 +"2034-05-29","Whit Monday","AD",2034 +"2034-08-15","Assumption Day","AD",2034 +"2034-09-08","National Day","AD",2034 +"2034-11-01","All Saints' Day","AD",2034 +"2034-12-08","Immaculate Conception Day","AD",2034 +"2034-12-25","Christmas Day","AD",2034 +"2034-12-26","Saint Stephen's Day","AD",2034 +"2035-01-01","New Year's Day","AD",2035 +"2035-01-06","Epiphany","AD",2035 +"2035-02-06","Carnival","AD",2035 +"2035-03-14","Constitution Day","AD",2035 +"2035-03-23","Good Friday","AD",2035 +"2035-03-26","Easter Monday","AD",2035 +"2035-05-01","Labor Day","AD",2035 +"2035-05-14","Whit Monday","AD",2035 +"2035-08-15","Assumption Day","AD",2035 +"2035-09-08","National Day","AD",2035 +"2035-11-01","All Saints' Day","AD",2035 +"2035-12-08","Immaculate Conception Day","AD",2035 +"2035-12-25","Christmas Day","AD",2035 +"2035-12-26","Saint Stephen's Day","AD",2035 +"2036-01-01","New Year's Day","AD",2036 +"2036-01-06","Epiphany","AD",2036 +"2036-02-26","Carnival","AD",2036 +"2036-03-14","Constitution Day","AD",2036 +"2036-04-11","Good Friday","AD",2036 +"2036-04-14","Easter Monday","AD",2036 +"2036-05-01","Labor Day","AD",2036 +"2036-06-02","Whit Monday","AD",2036 +"2036-08-15","Assumption Day","AD",2036 +"2036-09-08","National Day","AD",2036 +"2036-11-01","All Saints' Day","AD",2036 +"2036-12-08","Immaculate Conception Day","AD",2036 +"2036-12-25","Christmas Day","AD",2036 +"2036-12-26","Saint Stephen's Day","AD",2036 +"2037-01-01","New Year's Day","AD",2037 +"2037-01-06","Epiphany","AD",2037 +"2037-02-17","Carnival","AD",2037 +"2037-03-14","Constitution Day","AD",2037 +"2037-04-03","Good Friday","AD",2037 +"2037-04-06","Easter Monday","AD",2037 +"2037-05-01","Labor Day","AD",2037 +"2037-05-25","Whit Monday","AD",2037 +"2037-08-15","Assumption Day","AD",2037 +"2037-09-08","National Day","AD",2037 +"2037-11-01","All Saints' Day","AD",2037 +"2037-12-08","Immaculate Conception Day","AD",2037 +"2037-12-25","Christmas Day","AD",2037 +"2037-12-26","Saint Stephen's Day","AD",2037 +"2038-01-01","New Year's Day","AD",2038 +"2038-01-06","Epiphany","AD",2038 +"2038-03-09","Carnival","AD",2038 +"2038-03-14","Constitution Day","AD",2038 +"2038-04-23","Good Friday","AD",2038 +"2038-04-26","Easter Monday","AD",2038 +"2038-05-01","Labor Day","AD",2038 +"2038-06-14","Whit Monday","AD",2038 +"2038-08-15","Assumption Day","AD",2038 +"2038-09-08","National Day","AD",2038 +"2038-11-01","All Saints' Day","AD",2038 +"2038-12-08","Immaculate Conception Day","AD",2038 +"2038-12-25","Christmas Day","AD",2038 +"2038-12-26","Saint Stephen's Day","AD",2038 +"2039-01-01","New Year's Day","AD",2039 +"2039-01-06","Epiphany","AD",2039 +"2039-02-22","Carnival","AD",2039 +"2039-03-14","Constitution Day","AD",2039 +"2039-04-08","Good Friday","AD",2039 +"2039-04-11","Easter Monday","AD",2039 +"2039-05-01","Labor Day","AD",2039 +"2039-05-30","Whit Monday","AD",2039 +"2039-08-15","Assumption Day","AD",2039 +"2039-09-08","National Day","AD",2039 +"2039-11-01","All Saints' Day","AD",2039 +"2039-12-08","Immaculate Conception Day","AD",2039 +"2039-12-25","Christmas Day","AD",2039 +"2039-12-26","Saint Stephen's Day","AD",2039 +"2040-01-01","New Year's Day","AD",2040 +"2040-01-06","Epiphany","AD",2040 +"2040-02-14","Carnival","AD",2040 +"2040-03-14","Constitution Day","AD",2040 +"2040-03-30","Good Friday","AD",2040 +"2040-04-02","Easter Monday","AD",2040 +"2040-05-01","Labor Day","AD",2040 +"2040-05-21","Whit Monday","AD",2040 +"2040-08-15","Assumption Day","AD",2040 +"2040-09-08","National Day","AD",2040 +"2040-11-01","All Saints' Day","AD",2040 +"2040-12-08","Immaculate Conception Day","AD",2040 +"2040-12-25","Christmas Day","AD",2040 +"2040-12-26","Saint Stephen's Day","AD",2040 +"2041-01-01","New Year's Day","AD",2041 +"2041-01-06","Epiphany","AD",2041 +"2041-03-05","Carnival","AD",2041 +"2041-03-14","Constitution Day","AD",2041 +"2041-04-19","Good Friday","AD",2041 +"2041-04-22","Easter Monday","AD",2041 +"2041-05-01","Labor Day","AD",2041 +"2041-06-10","Whit Monday","AD",2041 +"2041-08-15","Assumption Day","AD",2041 +"2041-09-08","National Day","AD",2041 +"2041-11-01","All Saints' Day","AD",2041 +"2041-12-08","Immaculate Conception Day","AD",2041 +"2041-12-25","Christmas Day","AD",2041 +"2041-12-26","Saint Stephen's Day","AD",2041 +"2042-01-01","New Year's Day","AD",2042 +"2042-01-06","Epiphany","AD",2042 +"2042-02-18","Carnival","AD",2042 +"2042-03-14","Constitution Day","AD",2042 +"2042-04-04","Good Friday","AD",2042 +"2042-04-07","Easter Monday","AD",2042 +"2042-05-01","Labor Day","AD",2042 +"2042-05-26","Whit Monday","AD",2042 +"2042-08-15","Assumption Day","AD",2042 +"2042-09-08","National Day","AD",2042 +"2042-11-01","All Saints' Day","AD",2042 +"2042-12-08","Immaculate Conception Day","AD",2042 +"2042-12-25","Christmas Day","AD",2042 +"2042-12-26","Saint Stephen's Day","AD",2042 +"2043-01-01","New Year's Day","AD",2043 +"2043-01-06","Epiphany","AD",2043 +"2043-02-10","Carnival","AD",2043 +"2043-03-14","Constitution Day","AD",2043 +"2043-03-27","Good Friday","AD",2043 +"2043-03-30","Easter Monday","AD",2043 +"2043-05-01","Labor Day","AD",2043 +"2043-05-18","Whit Monday","AD",2043 +"2043-08-15","Assumption Day","AD",2043 +"2043-09-08","National Day","AD",2043 +"2043-11-01","All Saints' Day","AD",2043 +"2043-12-08","Immaculate Conception Day","AD",2043 +"2043-12-25","Christmas Day","AD",2043 +"2043-12-26","Saint Stephen's Day","AD",2043 +"2044-01-01","New Year's Day","AD",2044 +"2044-01-06","Epiphany","AD",2044 +"2044-03-01","Carnival","AD",2044 +"2044-03-14","Constitution Day","AD",2044 +"2044-04-15","Good Friday","AD",2044 +"2044-04-18","Easter Monday","AD",2044 +"2044-05-01","Labor Day","AD",2044 +"2044-06-06","Whit Monday","AD",2044 +"2044-08-15","Assumption Day","AD",2044 +"2044-09-08","National Day","AD",2044 +"2044-11-01","All Saints' Day","AD",2044 +"2044-12-08","Immaculate Conception Day","AD",2044 +"2044-12-25","Christmas Day","AD",2044 +"2044-12-26","Saint Stephen's Day","AD",2044 +"1995-01-01","New Year's Day","AE",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","AE",1995 +"1995-03-03","Eid al-Fitr Holiday* (*estimated)","AE",1995 +"1995-03-04","Eid al-Fitr Holiday* (*estimated)","AE",1995 +"1995-05-08","Arafat (Hajj) Day* (*estimated)","AE",1995 +"1995-05-09","Eid al-Adha* (*estimated)","AE",1995 +"1995-05-10","Eid al-Adha Holiday* (*estimated)","AE",1995 +"1995-05-11","Eid al-Adha Holiday* (*estimated)","AE",1995 +"1995-05-30","Al Hijra - Islamic New Year* (*estimated)","AE",1995 +"1995-08-08","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",1995 +"1995-12-02","National Day","AE",1995 +"1995-12-03","National Day Holiday","AE",1995 +"1995-12-19","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",1995 +"1996-01-01","New Year's Day","AE",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","AE",1996 +"1996-02-20","Eid al-Fitr Holiday* (*estimated)","AE",1996 +"1996-02-21","Eid al-Fitr Holiday* (*estimated)","AE",1996 +"1996-04-26","Arafat (Hajj) Day* (*estimated)","AE",1996 +"1996-04-27","Eid al-Adha* (*estimated)","AE",1996 +"1996-04-28","Eid al-Adha Holiday* (*estimated)","AE",1996 +"1996-04-29","Eid al-Adha Holiday* (*estimated)","AE",1996 +"1996-05-18","Al Hijra - Islamic New Year* (*estimated)","AE",1996 +"1996-07-27","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",1996 +"1996-12-02","National Day","AE",1996 +"1996-12-03","National Day Holiday","AE",1996 +"1996-12-08","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",1996 +"1997-01-01","New Year's Day","AE",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","AE",1997 +"1997-02-09","Eid al-Fitr Holiday* (*estimated)","AE",1997 +"1997-02-10","Eid al-Fitr Holiday* (*estimated)","AE",1997 +"1997-04-16","Arafat (Hajj) Day* (*estimated)","AE",1997 +"1997-04-17","Eid al-Adha* (*estimated)","AE",1997 +"1997-04-18","Eid al-Adha Holiday* (*estimated)","AE",1997 +"1997-04-19","Eid al-Adha Holiday* (*estimated)","AE",1997 +"1997-05-07","Al Hijra - Islamic New Year* (*estimated)","AE",1997 +"1997-07-16","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",1997 +"1997-11-27","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",1997 +"1997-12-02","National Day","AE",1997 +"1997-12-03","National Day Holiday","AE",1997 +"1998-01-01","New Year's Day","AE",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","AE",1998 +"1998-01-30","Eid al-Fitr Holiday* (*estimated)","AE",1998 +"1998-01-31","Eid al-Fitr Holiday* (*estimated)","AE",1998 +"1998-04-06","Arafat (Hajj) Day* (*estimated)","AE",1998 +"1998-04-07","Eid al-Adha* (*estimated)","AE",1998 +"1998-04-08","Eid al-Adha Holiday* (*estimated)","AE",1998 +"1998-04-09","Eid al-Adha Holiday* (*estimated)","AE",1998 +"1998-04-27","Al Hijra - Islamic New Year* (*estimated)","AE",1998 +"1998-07-06","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",1998 +"1998-11-16","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",1998 +"1998-12-02","National Day","AE",1998 +"1998-12-03","National Day Holiday","AE",1998 +"1999-01-01","New Year's Day","AE",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","AE",1999 +"1999-01-19","Eid al-Fitr Holiday* (*estimated)","AE",1999 +"1999-01-20","Eid al-Fitr Holiday* (*estimated)","AE",1999 +"1999-03-26","Arafat (Hajj) Day* (*estimated)","AE",1999 +"1999-03-27","Eid al-Adha* (*estimated)","AE",1999 +"1999-03-28","Eid al-Adha Holiday* (*estimated)","AE",1999 +"1999-03-29","Eid al-Adha Holiday* (*estimated)","AE",1999 +"1999-04-17","Al Hijra - Islamic New Year* (*estimated)","AE",1999 +"1999-06-26","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",1999 +"1999-11-05","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",1999 +"1999-12-02","National Day","AE",1999 +"1999-12-03","National Day Holiday","AE",1999 +"2000-01-01","New Year's Day","AE",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","AE",2000 +"2000-01-09","Eid al-Fitr Holiday* (*estimated)","AE",2000 +"2000-01-10","Eid al-Fitr Holiday* (*estimated)","AE",2000 +"2000-03-15","Arafat (Hajj) Day* (*estimated)","AE",2000 +"2000-03-16","Eid al-Adha* (*estimated)","AE",2000 +"2000-03-17","Eid al-Adha Holiday* (*estimated)","AE",2000 +"2000-03-18","Eid al-Adha Holiday* (*estimated)","AE",2000 +"2000-04-06","Al Hijra - Islamic New Year* (*estimated)","AE",2000 +"2000-06-14","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2000 +"2000-10-24","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2000 +"2000-12-02","National Day","AE",2000 +"2000-12-03","National Day Holiday","AE",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","AE",2000 +"2000-12-28","Eid al-Fitr Holiday* (*estimated)","AE",2000 +"2000-12-29","Eid al-Fitr Holiday* (*estimated)","AE",2000 +"2001-01-01","New Year's Day","AE",2001 +"2001-03-04","Arafat (Hajj) Day* (*estimated)","AE",2001 +"2001-03-05","Eid al-Adha* (*estimated)","AE",2001 +"2001-03-06","Eid al-Adha Holiday* (*estimated)","AE",2001 +"2001-03-07","Eid al-Adha Holiday* (*estimated)","AE",2001 +"2001-03-26","Al Hijra - Islamic New Year* (*estimated)","AE",2001 +"2001-06-04","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2001 +"2001-10-14","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2001 +"2001-12-02","National Day","AE",2001 +"2001-12-03","National Day Holiday","AE",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","AE",2001 +"2001-12-17","Eid al-Fitr Holiday* (*estimated)","AE",2001 +"2001-12-18","Eid al-Fitr Holiday* (*estimated)","AE",2001 +"2002-01-01","New Year's Day","AE",2002 +"2002-02-21","Arafat (Hajj) Day* (*estimated)","AE",2002 +"2002-02-22","Eid al-Adha* (*estimated)","AE",2002 +"2002-02-23","Eid al-Adha Holiday* (*estimated)","AE",2002 +"2002-02-24","Eid al-Adha Holiday* (*estimated)","AE",2002 +"2002-03-15","Al Hijra - Islamic New Year* (*estimated)","AE",2002 +"2002-05-24","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2002 +"2002-10-04","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2002 +"2002-12-02","National Day","AE",2002 +"2002-12-03","National Day Holiday","AE",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","AE",2002 +"2002-12-06","Eid al-Fitr Holiday* (*estimated)","AE",2002 +"2002-12-07","Eid al-Fitr Holiday* (*estimated)","AE",2002 +"2003-01-01","New Year's Day","AE",2003 +"2003-02-10","Arafat (Hajj) Day* (*estimated)","AE",2003 +"2003-02-11","Eid al-Adha* (*estimated)","AE",2003 +"2003-02-12","Eid al-Adha Holiday* (*estimated)","AE",2003 +"2003-02-13","Eid al-Adha Holiday* (*estimated)","AE",2003 +"2003-03-04","Al Hijra - Islamic New Year* (*estimated)","AE",2003 +"2003-05-13","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2003 +"2003-09-24","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","AE",2003 +"2003-11-26","Eid al-Fitr Holiday* (*estimated)","AE",2003 +"2003-11-27","Eid al-Fitr Holiday* (*estimated)","AE",2003 +"2003-12-02","National Day","AE",2003 +"2003-12-03","National Day Holiday","AE",2003 +"2004-01-01","New Year's Day","AE",2004 +"2004-01-31","Arafat (Hajj) Day* (*estimated)","AE",2004 +"2004-02-01","Eid al-Adha* (*estimated)","AE",2004 +"2004-02-02","Eid al-Adha Holiday* (*estimated)","AE",2004 +"2004-02-03","Eid al-Adha Holiday* (*estimated)","AE",2004 +"2004-02-21","Al Hijra - Islamic New Year* (*estimated)","AE",2004 +"2004-05-01","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2004 +"2004-09-12","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","AE",2004 +"2004-11-15","Eid al-Fitr Holiday* (*estimated)","AE",2004 +"2004-11-16","Eid al-Fitr Holiday* (*estimated)","AE",2004 +"2004-12-02","National Day","AE",2004 +"2004-12-03","National Day Holiday","AE",2004 +"2005-01-01","New Year's Day","AE",2005 +"2005-01-20","Arafat (Hajj) Day* (*estimated)","AE",2005 +"2005-01-21","Eid al-Adha* (*estimated)","AE",2005 +"2005-01-22","Eid al-Adha Holiday* (*estimated)","AE",2005 +"2005-01-23","Eid al-Adha Holiday* (*estimated)","AE",2005 +"2005-02-10","Al Hijra - Islamic New Year* (*estimated)","AE",2005 +"2005-04-21","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2005 +"2005-09-01","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","AE",2005 +"2005-11-04","Eid al-Fitr Holiday* (*estimated)","AE",2005 +"2005-11-05","Eid al-Fitr Holiday* (*estimated)","AE",2005 +"2005-12-02","National Day","AE",2005 +"2005-12-03","National Day Holiday","AE",2005 +"2006-01-01","New Year's Day","AE",2006 +"2006-01-09","Arafat (Hajj) Day* (*estimated)","AE",2006 +"2006-01-10","Eid al-Adha* (*estimated)","AE",2006 +"2006-01-11","Eid al-Adha Holiday* (*estimated)","AE",2006 +"2006-01-12","Eid al-Adha Holiday* (*estimated)","AE",2006 +"2006-01-31","Al Hijra - Islamic New Year* (*estimated)","AE",2006 +"2006-04-10","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2006 +"2006-08-21","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","AE",2006 +"2006-10-24","Eid al-Fitr Holiday* (*estimated)","AE",2006 +"2006-10-25","Eid al-Fitr Holiday* (*estimated)","AE",2006 +"2006-12-02","National Day","AE",2006 +"2006-12-03","National Day Holiday","AE",2006 +"2006-12-30","Arafat (Hajj) Day* (*estimated)","AE",2006 +"2006-12-31","Eid al-Adha* (*estimated)","AE",2006 +"2007-01-01","Eid al-Adha Holiday* (*estimated)","AE",2007 +"2007-01-01","New Year's Day","AE",2007 +"2007-01-02","Eid al-Adha Holiday* (*estimated)","AE",2007 +"2007-01-20","Al Hijra - Islamic New Year* (*estimated)","AE",2007 +"2007-03-31","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2007 +"2007-08-10","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","AE",2007 +"2007-10-14","Eid al-Fitr Holiday* (*estimated)","AE",2007 +"2007-10-15","Eid al-Fitr Holiday* (*estimated)","AE",2007 +"2007-12-02","National Day","AE",2007 +"2007-12-03","National Day Holiday","AE",2007 +"2007-12-19","Arafat (Hajj) Day* (*estimated)","AE",2007 +"2007-12-20","Eid al-Adha* (*estimated)","AE",2007 +"2007-12-21","Eid al-Adha Holiday* (*estimated)","AE",2007 +"2007-12-22","Eid al-Adha Holiday* (*estimated)","AE",2007 +"2008-01-01","New Year's Day","AE",2008 +"2008-01-10","Al Hijra - Islamic New Year* (*estimated)","AE",2008 +"2008-03-20","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2008 +"2008-07-30","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","AE",2008 +"2008-10-02","Eid al-Fitr Holiday* (*estimated)","AE",2008 +"2008-10-03","Eid al-Fitr Holiday* (*estimated)","AE",2008 +"2008-12-02","National Day","AE",2008 +"2008-12-03","National Day Holiday","AE",2008 +"2008-12-07","Arafat (Hajj) Day* (*estimated)","AE",2008 +"2008-12-08","Eid al-Adha* (*estimated)","AE",2008 +"2008-12-09","Eid al-Adha Holiday* (*estimated)","AE",2008 +"2008-12-10","Eid al-Adha Holiday* (*estimated)","AE",2008 +"2008-12-29","Al Hijra - Islamic New Year* (*estimated)","AE",2008 +"2009-01-01","New Year's Day","AE",2009 +"2009-03-09","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2009 +"2009-07-20","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","AE",2009 +"2009-09-21","Eid al-Fitr Holiday* (*estimated)","AE",2009 +"2009-09-22","Eid al-Fitr Holiday* (*estimated)","AE",2009 +"2009-11-26","Arafat (Hajj) Day* (*estimated)","AE",2009 +"2009-11-27","Eid al-Adha* (*estimated)","AE",2009 +"2009-11-28","Eid al-Adha Holiday* (*estimated)","AE",2009 +"2009-11-29","Eid al-Adha Holiday* (*estimated)","AE",2009 +"2009-12-02","National Day","AE",2009 +"2009-12-03","National Day Holiday","AE",2009 +"2009-12-18","Al Hijra - Islamic New Year* (*estimated)","AE",2009 +"2010-01-01","New Year's Day","AE",2010 +"2010-02-26","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2010 +"2010-07-09","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","AE",2010 +"2010-09-11","Eid al-Fitr Holiday* (*estimated)","AE",2010 +"2010-09-12","Eid al-Fitr Holiday* (*estimated)","AE",2010 +"2010-11-15","Arafat (Hajj) Day* (*estimated)","AE",2010 +"2010-11-16","Eid al-Adha* (*estimated)","AE",2010 +"2010-11-17","Eid al-Adha Holiday* (*estimated)","AE",2010 +"2010-11-18","Eid al-Adha Holiday* (*estimated)","AE",2010 +"2010-12-02","National Day","AE",2010 +"2010-12-03","National Day Holiday","AE",2010 +"2010-12-07","Al Hijra - Islamic New Year* (*estimated)","AE",2010 +"2011-01-01","New Year's Day","AE",2011 +"2011-02-15","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2011 +"2011-06-29","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","AE",2011 +"2011-08-31","Eid al-Fitr Holiday* (*estimated)","AE",2011 +"2011-09-01","Eid al-Fitr Holiday* (*estimated)","AE",2011 +"2011-11-05","Arafat (Hajj) Day* (*estimated)","AE",2011 +"2011-11-06","Eid al-Adha* (*estimated)","AE",2011 +"2011-11-07","Eid al-Adha Holiday* (*estimated)","AE",2011 +"2011-11-08","Eid al-Adha Holiday* (*estimated)","AE",2011 +"2011-11-26","Al Hijra - Islamic New Year* (*estimated)","AE",2011 +"2011-12-02","National Day","AE",2011 +"2011-12-03","National Day Holiday","AE",2011 +"2012-01-01","New Year's Day","AE",2012 +"2012-02-04","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2012 +"2012-06-17","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","AE",2012 +"2012-08-20","Eid al-Fitr Holiday* (*estimated)","AE",2012 +"2012-08-21","Eid al-Fitr Holiday* (*estimated)","AE",2012 +"2012-10-25","Arafat (Hajj) Day* (*estimated)","AE",2012 +"2012-10-26","Eid al-Adha* (*estimated)","AE",2012 +"2012-10-27","Eid al-Adha Holiday* (*estimated)","AE",2012 +"2012-10-28","Eid al-Adha Holiday* (*estimated)","AE",2012 +"2012-11-15","Al Hijra - Islamic New Year* (*estimated)","AE",2012 +"2012-12-02","National Day","AE",2012 +"2012-12-03","National Day Holiday","AE",2012 +"2013-01-01","New Year's Day","AE",2013 +"2013-01-24","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2013 +"2013-06-06","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","AE",2013 +"2013-08-09","Eid al-Fitr Holiday* (*estimated)","AE",2013 +"2013-08-10","Eid al-Fitr Holiday* (*estimated)","AE",2013 +"2013-10-14","Arafat (Hajj) Day* (*estimated)","AE",2013 +"2013-10-15","Eid al-Adha* (*estimated)","AE",2013 +"2013-10-16","Eid al-Adha Holiday* (*estimated)","AE",2013 +"2013-10-17","Eid al-Adha Holiday* (*estimated)","AE",2013 +"2013-11-04","Al Hijra - Islamic New Year* (*estimated)","AE",2013 +"2013-12-02","National Day","AE",2013 +"2013-12-03","National Day Holiday","AE",2013 +"2014-01-01","New Year's Day","AE",2014 +"2014-01-13","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2014 +"2014-05-26","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","AE",2014 +"2014-07-29","Eid al-Fitr Holiday* (*estimated)","AE",2014 +"2014-07-30","Eid al-Fitr Holiday* (*estimated)","AE",2014 +"2014-10-03","Arafat (Hajj) Day* (*estimated)","AE",2014 +"2014-10-04","Eid al-Adha* (*estimated)","AE",2014 +"2014-10-05","Eid al-Adha Holiday* (*estimated)","AE",2014 +"2014-10-06","Eid al-Adha Holiday* (*estimated)","AE",2014 +"2014-10-25","Al Hijra - Islamic New Year* (*estimated)","AE",2014 +"2014-12-02","National Day","AE",2014 +"2014-12-03","National Day Holiday","AE",2014 +"2015-01-01","New Year's Day","AE",2015 +"2015-01-03","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2015 +"2015-05-16","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","AE",2015 +"2015-07-18","Eid al-Fitr Holiday* (*estimated)","AE",2015 +"2015-07-19","Eid al-Fitr Holiday* (*estimated)","AE",2015 +"2015-09-22","Arafat (Hajj) Day* (*estimated)","AE",2015 +"2015-09-23","Eid al-Adha* (*estimated)","AE",2015 +"2015-09-24","Eid al-Adha Holiday* (*estimated)","AE",2015 +"2015-09-25","Eid al-Adha Holiday* (*estimated)","AE",2015 +"2015-10-14","Al Hijra - Islamic New Year* (*estimated)","AE",2015 +"2015-11-30","Commemoration Day","AE",2015 +"2015-12-02","National Day","AE",2015 +"2015-12-03","National Day Holiday","AE",2015 +"2015-12-23","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2015 +"2016-01-01","New Year's Day","AE",2016 +"2016-05-04","Leilat al-Miraj - The Prophet's ascension* (*estimated)","AE",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","AE",2016 +"2016-07-07","Eid al-Fitr Holiday* (*estimated)","AE",2016 +"2016-07-08","Eid al-Fitr Holiday* (*estimated)","AE",2016 +"2016-09-10","Arafat (Hajj) Day* (*estimated)","AE",2016 +"2016-09-11","Eid al-Adha* (*estimated)","AE",2016 +"2016-09-12","Eid al-Adha Holiday* (*estimated)","AE",2016 +"2016-09-13","Eid al-Adha Holiday* (*estimated)","AE",2016 +"2016-10-02","Al Hijra - Islamic New Year* (*estimated)","AE",2016 +"2016-11-30","Commemoration Day","AE",2016 +"2016-12-02","National Day","AE",2016 +"2016-12-03","National Day Holiday","AE",2016 +"2016-12-11","Mawlud al-Nabi - Prophet Mohammad's Birthday* (*estimated)","AE",2016 +"2017-01-01","New Year's Day","AE",2017 +"2017-04-23","Leilat al-Miraj - The Prophet's ascension","AE",2017 +"2017-06-25","Eid al-Fitr","AE",2017 +"2017-06-26","Eid al-Fitr Holiday","AE",2017 +"2017-06-27","Eid al-Fitr Holiday","AE",2017 +"2017-08-31","Arafat (Hajj) Day","AE",2017 +"2017-09-01","Eid al-Adha","AE",2017 +"2017-09-02","Eid al-Adha Holiday","AE",2017 +"2017-09-03","Eid al-Adha Holiday","AE",2017 +"2017-09-22","Al Hijra - Islamic New Year","AE",2017 +"2017-11-30","Commemoration Day","AE",2017 +"2017-11-30","Mawlud al-Nabi - Prophet Mohammad's Birthday","AE",2017 +"2017-12-02","National Day","AE",2017 +"2017-12-03","National Day Holiday","AE",2017 +"2018-01-01","New Year's Day","AE",2018 +"2018-04-13","Leilat al-Miraj - The Prophet's ascension","AE",2018 +"2018-06-14","Eid al-Fitr","AE",2018 +"2018-06-15","Eid al-Fitr Holiday","AE",2018 +"2018-06-16","Eid al-Fitr Holiday","AE",2018 +"2018-08-20","Arafat (Hajj) Day","AE",2018 +"2018-08-21","Eid al-Adha","AE",2018 +"2018-08-22","Eid al-Adha Holiday","AE",2018 +"2018-08-23","Eid al-Adha Holiday","AE",2018 +"2018-09-11","Al Hijra - Islamic New Year","AE",2018 +"2018-11-19","Mawlud al-Nabi - Prophet Mohammad's Birthday","AE",2018 +"2018-11-30","Commemoration Day","AE",2018 +"2018-12-02","National Day","AE",2018 +"2018-12-03","National Day Holiday","AE",2018 +"2019-01-01","New Year's Day","AE",2019 +"2019-06-03","Eid al-Fitr","AE",2019 +"2019-06-04","Eid al-Fitr Holiday","AE",2019 +"2019-06-05","Eid al-Fitr Holiday","AE",2019 +"2019-08-10","Arafat (Hajj) Day","AE",2019 +"2019-08-11","Eid al-Adha","AE",2019 +"2019-08-12","Eid al-Adha Holiday","AE",2019 +"2019-08-13","Eid al-Adha Holiday","AE",2019 +"2019-08-31","Al Hijra - Islamic New Year","AE",2019 +"2019-11-09","Mawlud al-Nabi - Prophet Mohammad's Birthday","AE",2019 +"2019-12-01","Commemoration Day","AE",2019 +"2019-12-02","National Day","AE",2019 +"2019-12-03","National Day Holiday","AE",2019 +"2020-01-01","New Year's Day","AE",2020 +"2020-05-24","Eid al-Fitr","AE",2020 +"2020-05-25","Eid al-Fitr Holiday","AE",2020 +"2020-05-26","Eid al-Fitr Holiday","AE",2020 +"2020-07-30","Arafat (Hajj) Day","AE",2020 +"2020-07-31","Eid al-Adha","AE",2020 +"2020-08-01","Eid al-Adha Holiday","AE",2020 +"2020-08-02","Eid al-Adha Holiday","AE",2020 +"2020-08-23","Al Hijra - Islamic New Year","AE",2020 +"2020-12-01","Commemoration Day","AE",2020 +"2020-12-02","National Day","AE",2020 +"2020-12-03","National Day Holiday","AE",2020 +"2021-01-01","New Year's Day","AE",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","AE",2021 +"2021-05-14","Eid al-Fitr Holiday* (*estimated)","AE",2021 +"2021-05-15","Eid al-Fitr Holiday* (*estimated)","AE",2021 +"2021-07-19","Arafat (Hajj) Day* (*estimated)","AE",2021 +"2021-07-20","Eid al-Adha* (*estimated)","AE",2021 +"2021-07-21","Eid al-Adha Holiday* (*estimated)","AE",2021 +"2021-07-22","Eid al-Adha Holiday* (*estimated)","AE",2021 +"2021-08-09","Al Hijra - Islamic New Year* (*estimated)","AE",2021 +"2021-12-01","Commemoration Day","AE",2021 +"2021-12-02","National Day","AE",2021 +"2021-12-03","National Day Holiday","AE",2021 +"2022-01-01","New Year's Day","AE",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","AE",2022 +"2022-05-03","Eid al-Fitr Holiday* (*estimated)","AE",2022 +"2022-05-04","Eid al-Fitr Holiday* (*estimated)","AE",2022 +"2022-07-08","Arafat (Hajj) Day* (*estimated)","AE",2022 +"2022-07-09","Eid al-Adha* (*estimated)","AE",2022 +"2022-07-10","Eid al-Adha Holiday* (*estimated)","AE",2022 +"2022-07-11","Eid al-Adha Holiday* (*estimated)","AE",2022 +"2022-07-30","Al Hijra - Islamic New Year* (*estimated)","AE",2022 +"2022-12-01","Commemoration Day","AE",2022 +"2022-12-02","National Day","AE",2022 +"2022-12-03","National Day Holiday","AE",2022 +"2023-01-01","New Year's Day","AE",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","AE",2023 +"2023-04-22","Eid al-Fitr Holiday* (*estimated)","AE",2023 +"2023-04-23","Eid al-Fitr Holiday* (*estimated)","AE",2023 +"2023-06-27","Arafat (Hajj) Day* (*estimated)","AE",2023 +"2023-06-28","Eid al-Adha* (*estimated)","AE",2023 +"2023-06-29","Eid al-Adha Holiday* (*estimated)","AE",2023 +"2023-06-30","Eid al-Adha Holiday* (*estimated)","AE",2023 +"2023-07-19","Al Hijra - Islamic New Year* (*estimated)","AE",2023 +"2023-12-01","Commemoration Day","AE",2023 +"2023-12-02","National Day","AE",2023 +"2023-12-03","National Day Holiday","AE",2023 +"2024-01-01","New Year's Day","AE",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","AE",2024 +"2024-04-11","Eid al-Fitr Holiday* (*estimated)","AE",2024 +"2024-04-12","Eid al-Fitr Holiday* (*estimated)","AE",2024 +"2024-06-15","Arafat (Hajj) Day* (*estimated)","AE",2024 +"2024-06-16","Eid al-Adha* (*estimated)","AE",2024 +"2024-06-17","Eid al-Adha Holiday* (*estimated)","AE",2024 +"2024-06-18","Eid al-Adha Holiday* (*estimated)","AE",2024 +"2024-07-07","Al Hijra - Islamic New Year* (*estimated)","AE",2024 +"2024-12-01","Commemoration Day","AE",2024 +"2024-12-02","National Day","AE",2024 +"2024-12-03","National Day Holiday","AE",2024 +"2025-01-01","New Year's Day","AE",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","AE",2025 +"2025-03-31","Eid al-Fitr Holiday* (*estimated)","AE",2025 +"2025-04-01","Eid al-Fitr Holiday* (*estimated)","AE",2025 +"2025-06-05","Arafat (Hajj) Day* (*estimated)","AE",2025 +"2025-06-06","Eid al-Adha* (*estimated)","AE",2025 +"2025-06-07","Eid al-Adha Holiday* (*estimated)","AE",2025 +"2025-06-08","Eid al-Adha Holiday* (*estimated)","AE",2025 +"2025-06-26","Al Hijra - Islamic New Year* (*estimated)","AE",2025 +"2025-12-01","Commemoration Day","AE",2025 +"2025-12-02","National Day","AE",2025 +"2025-12-03","National Day Holiday","AE",2025 +"2026-01-01","New Year's Day","AE",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","AE",2026 +"2026-03-21","Eid al-Fitr Holiday* (*estimated)","AE",2026 +"2026-03-22","Eid al-Fitr Holiday* (*estimated)","AE",2026 +"2026-05-26","Arafat (Hajj) Day* (*estimated)","AE",2026 +"2026-05-27","Eid al-Adha* (*estimated)","AE",2026 +"2026-05-28","Eid al-Adha Holiday* (*estimated)","AE",2026 +"2026-05-29","Eid al-Adha Holiday* (*estimated)","AE",2026 +"2026-06-16","Al Hijra - Islamic New Year* (*estimated)","AE",2026 +"2026-12-01","Commemoration Day","AE",2026 +"2026-12-02","National Day","AE",2026 +"2026-12-03","National Day Holiday","AE",2026 +"2027-01-01","New Year's Day","AE",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","AE",2027 +"2027-03-10","Eid al-Fitr Holiday* (*estimated)","AE",2027 +"2027-03-11","Eid al-Fitr Holiday* (*estimated)","AE",2027 +"2027-05-15","Arafat (Hajj) Day* (*estimated)","AE",2027 +"2027-05-16","Eid al-Adha* (*estimated)","AE",2027 +"2027-05-17","Eid al-Adha Holiday* (*estimated)","AE",2027 +"2027-05-18","Eid al-Adha Holiday* (*estimated)","AE",2027 +"2027-06-06","Al Hijra - Islamic New Year* (*estimated)","AE",2027 +"2027-12-01","Commemoration Day","AE",2027 +"2027-12-02","National Day","AE",2027 +"2027-12-03","National Day Holiday","AE",2027 +"2028-01-01","New Year's Day","AE",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","AE",2028 +"2028-02-27","Eid al-Fitr Holiday* (*estimated)","AE",2028 +"2028-02-28","Eid al-Fitr Holiday* (*estimated)","AE",2028 +"2028-05-04","Arafat (Hajj) Day* (*estimated)","AE",2028 +"2028-05-05","Eid al-Adha* (*estimated)","AE",2028 +"2028-05-06","Eid al-Adha Holiday* (*estimated)","AE",2028 +"2028-05-07","Eid al-Adha Holiday* (*estimated)","AE",2028 +"2028-05-25","Al Hijra - Islamic New Year* (*estimated)","AE",2028 +"2028-12-01","Commemoration Day","AE",2028 +"2028-12-02","National Day","AE",2028 +"2028-12-03","National Day Holiday","AE",2028 +"2029-01-01","New Year's Day","AE",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","AE",2029 +"2029-02-15","Eid al-Fitr Holiday* (*estimated)","AE",2029 +"2029-02-16","Eid al-Fitr Holiday* (*estimated)","AE",2029 +"2029-04-23","Arafat (Hajj) Day* (*estimated)","AE",2029 +"2029-04-24","Eid al-Adha* (*estimated)","AE",2029 +"2029-04-25","Eid al-Adha Holiday* (*estimated)","AE",2029 +"2029-04-26","Eid al-Adha Holiday* (*estimated)","AE",2029 +"2029-05-14","Al Hijra - Islamic New Year* (*estimated)","AE",2029 +"2029-12-01","Commemoration Day","AE",2029 +"2029-12-02","National Day","AE",2029 +"2029-12-03","National Day Holiday","AE",2029 +"2030-01-01","New Year's Day","AE",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","AE",2030 +"2030-02-05","Eid al-Fitr Holiday* (*estimated)","AE",2030 +"2030-02-06","Eid al-Fitr Holiday* (*estimated)","AE",2030 +"2030-04-12","Arafat (Hajj) Day* (*estimated)","AE",2030 +"2030-04-13","Eid al-Adha* (*estimated)","AE",2030 +"2030-04-14","Eid al-Adha Holiday* (*estimated)","AE",2030 +"2030-04-15","Eid al-Adha Holiday* (*estimated)","AE",2030 +"2030-05-03","Al Hijra - Islamic New Year* (*estimated)","AE",2030 +"2030-12-01","Commemoration Day","AE",2030 +"2030-12-02","National Day","AE",2030 +"2030-12-03","National Day Holiday","AE",2030 +"2031-01-01","New Year's Day","AE",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","AE",2031 +"2031-01-25","Eid al-Fitr Holiday* (*estimated)","AE",2031 +"2031-01-26","Eid al-Fitr Holiday* (*estimated)","AE",2031 +"2031-04-01","Arafat (Hajj) Day* (*estimated)","AE",2031 +"2031-04-02","Eid al-Adha* (*estimated)","AE",2031 +"2031-04-03","Eid al-Adha Holiday* (*estimated)","AE",2031 +"2031-04-04","Eid al-Adha Holiday* (*estimated)","AE",2031 +"2031-04-23","Al Hijra - Islamic New Year* (*estimated)","AE",2031 +"2031-12-01","Commemoration Day","AE",2031 +"2031-12-02","National Day","AE",2031 +"2031-12-03","National Day Holiday","AE",2031 +"2032-01-01","New Year's Day","AE",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","AE",2032 +"2032-01-15","Eid al-Fitr Holiday* (*estimated)","AE",2032 +"2032-01-16","Eid al-Fitr Holiday* (*estimated)","AE",2032 +"2032-03-21","Arafat (Hajj) Day* (*estimated)","AE",2032 +"2032-03-22","Eid al-Adha* (*estimated)","AE",2032 +"2032-03-23","Eid al-Adha Holiday* (*estimated)","AE",2032 +"2032-03-24","Eid al-Adha Holiday* (*estimated)","AE",2032 +"2032-04-11","Al Hijra - Islamic New Year* (*estimated)","AE",2032 +"2032-12-01","Commemoration Day","AE",2032 +"2032-12-02","National Day","AE",2032 +"2032-12-03","National Day Holiday","AE",2032 +"2033-01-01","New Year's Day","AE",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","AE",2033 +"2033-01-03","Eid al-Fitr Holiday* (*estimated)","AE",2033 +"2033-01-04","Eid al-Fitr Holiday* (*estimated)","AE",2033 +"2033-03-10","Arafat (Hajj) Day* (*estimated)","AE",2033 +"2033-03-11","Eid al-Adha* (*estimated)","AE",2033 +"2033-03-12","Eid al-Adha Holiday* (*estimated)","AE",2033 +"2033-03-13","Eid al-Adha Holiday* (*estimated)","AE",2033 +"2033-04-01","Al Hijra - Islamic New Year* (*estimated)","AE",2033 +"2033-12-01","Commemoration Day","AE",2033 +"2033-12-02","National Day","AE",2033 +"2033-12-03","National Day Holiday","AE",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","AE",2033 +"2033-12-24","Eid al-Fitr Holiday* (*estimated)","AE",2033 +"2033-12-25","Eid al-Fitr Holiday* (*estimated)","AE",2033 +"2034-01-01","New Year's Day","AE",2034 +"2034-02-28","Arafat (Hajj) Day* (*estimated)","AE",2034 +"2034-03-01","Eid al-Adha* (*estimated)","AE",2034 +"2034-03-02","Eid al-Adha Holiday* (*estimated)","AE",2034 +"2034-03-03","Eid al-Adha Holiday* (*estimated)","AE",2034 +"2034-03-21","Al Hijra - Islamic New Year* (*estimated)","AE",2034 +"2034-12-01","Commemoration Day","AE",2034 +"2034-12-02","National Day","AE",2034 +"2034-12-03","National Day Holiday","AE",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","AE",2034 +"2034-12-13","Eid al-Fitr Holiday* (*estimated)","AE",2034 +"2034-12-14","Eid al-Fitr Holiday* (*estimated)","AE",2034 +"2035-01-01","New Year's Day","AE",2035 +"2035-02-17","Arafat (Hajj) Day* (*estimated)","AE",2035 +"2035-02-18","Eid al-Adha* (*estimated)","AE",2035 +"2035-02-19","Eid al-Adha Holiday* (*estimated)","AE",2035 +"2035-02-20","Eid al-Adha Holiday* (*estimated)","AE",2035 +"2035-03-11","Al Hijra - Islamic New Year* (*estimated)","AE",2035 +"2035-12-01","Commemoration Day","AE",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","AE",2035 +"2035-12-02","Eid al-Fitr Holiday* (*estimated)","AE",2035 +"2035-12-02","National Day","AE",2035 +"2035-12-03","Eid al-Fitr Holiday* (*estimated)","AE",2035 +"2035-12-03","National Day Holiday","AE",2035 +"2036-01-01","New Year's Day","AE",2036 +"2036-02-06","Arafat (Hajj) Day* (*estimated)","AE",2036 +"2036-02-07","Eid al-Adha* (*estimated)","AE",2036 +"2036-02-08","Eid al-Adha Holiday* (*estimated)","AE",2036 +"2036-02-09","Eid al-Adha Holiday* (*estimated)","AE",2036 +"2036-02-28","Al Hijra - Islamic New Year* (*estimated)","AE",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","AE",2036 +"2036-11-20","Eid al-Fitr Holiday* (*estimated)","AE",2036 +"2036-11-21","Eid al-Fitr Holiday* (*estimated)","AE",2036 +"2036-12-01","Commemoration Day","AE",2036 +"2036-12-02","National Day","AE",2036 +"2036-12-03","National Day Holiday","AE",2036 +"2037-01-01","New Year's Day","AE",2037 +"2037-01-25","Arafat (Hajj) Day* (*estimated)","AE",2037 +"2037-01-26","Eid al-Adha* (*estimated)","AE",2037 +"2037-01-27","Eid al-Adha Holiday* (*estimated)","AE",2037 +"2037-01-28","Eid al-Adha Holiday* (*estimated)","AE",2037 +"2037-02-16","Al Hijra - Islamic New Year* (*estimated)","AE",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","AE",2037 +"2037-11-09","Eid al-Fitr Holiday* (*estimated)","AE",2037 +"2037-11-10","Eid al-Fitr Holiday* (*estimated)","AE",2037 +"2037-12-01","Commemoration Day","AE",2037 +"2037-12-02","National Day","AE",2037 +"2037-12-03","National Day Holiday","AE",2037 +"2038-01-01","New Year's Day","AE",2038 +"2038-01-15","Arafat (Hajj) Day* (*estimated)","AE",2038 +"2038-01-16","Eid al-Adha* (*estimated)","AE",2038 +"2038-01-17","Eid al-Adha Holiday* (*estimated)","AE",2038 +"2038-01-18","Eid al-Adha Holiday* (*estimated)","AE",2038 +"2038-02-05","Al Hijra - Islamic New Year* (*estimated)","AE",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","AE",2038 +"2038-10-30","Eid al-Fitr Holiday* (*estimated)","AE",2038 +"2038-10-31","Eid al-Fitr Holiday* (*estimated)","AE",2038 +"2038-12-01","Commemoration Day","AE",2038 +"2038-12-02","National Day","AE",2038 +"2038-12-03","National Day Holiday","AE",2038 +"2039-01-01","New Year's Day","AE",2039 +"2039-01-04","Arafat (Hajj) Day* (*estimated)","AE",2039 +"2039-01-05","Eid al-Adha* (*estimated)","AE",2039 +"2039-01-06","Eid al-Adha Holiday* (*estimated)","AE",2039 +"2039-01-07","Eid al-Adha Holiday* (*estimated)","AE",2039 +"2039-01-26","Al Hijra - Islamic New Year* (*estimated)","AE",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","AE",2039 +"2039-10-20","Eid al-Fitr Holiday* (*estimated)","AE",2039 +"2039-10-21","Eid al-Fitr Holiday* (*estimated)","AE",2039 +"2039-12-01","Commemoration Day","AE",2039 +"2039-12-02","National Day","AE",2039 +"2039-12-03","National Day Holiday","AE",2039 +"2039-12-25","Arafat (Hajj) Day* (*estimated)","AE",2039 +"2039-12-26","Eid al-Adha* (*estimated)","AE",2039 +"2039-12-27","Eid al-Adha Holiday* (*estimated)","AE",2039 +"2039-12-28","Eid al-Adha Holiday* (*estimated)","AE",2039 +"2040-01-01","New Year's Day","AE",2040 +"2040-01-15","Al Hijra - Islamic New Year* (*estimated)","AE",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","AE",2040 +"2040-10-08","Eid al-Fitr Holiday* (*estimated)","AE",2040 +"2040-10-09","Eid al-Fitr Holiday* (*estimated)","AE",2040 +"2040-12-01","Commemoration Day","AE",2040 +"2040-12-02","National Day","AE",2040 +"2040-12-03","National Day Holiday","AE",2040 +"2040-12-13","Arafat (Hajj) Day* (*estimated)","AE",2040 +"2040-12-14","Eid al-Adha* (*estimated)","AE",2040 +"2040-12-15","Eid al-Adha Holiday* (*estimated)","AE",2040 +"2040-12-16","Eid al-Adha Holiday* (*estimated)","AE",2040 +"2041-01-01","New Year's Day","AE",2041 +"2041-01-04","Al Hijra - Islamic New Year* (*estimated)","AE",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","AE",2041 +"2041-09-27","Eid al-Fitr Holiday* (*estimated)","AE",2041 +"2041-09-28","Eid al-Fitr Holiday* (*estimated)","AE",2041 +"2041-12-01","Commemoration Day","AE",2041 +"2041-12-02","National Day","AE",2041 +"2041-12-03","Arafat (Hajj) Day* (*estimated)","AE",2041 +"2041-12-03","National Day Holiday","AE",2041 +"2041-12-04","Eid al-Adha* (*estimated)","AE",2041 +"2041-12-05","Eid al-Adha Holiday* (*estimated)","AE",2041 +"2041-12-06","Eid al-Adha Holiday* (*estimated)","AE",2041 +"2041-12-24","Al Hijra - Islamic New Year* (*estimated)","AE",2041 +"2042-01-01","New Year's Day","AE",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","AE",2042 +"2042-09-16","Eid al-Fitr Holiday* (*estimated)","AE",2042 +"2042-09-17","Eid al-Fitr Holiday* (*estimated)","AE",2042 +"2042-11-22","Arafat (Hajj) Day* (*estimated)","AE",2042 +"2042-11-23","Eid al-Adha* (*estimated)","AE",2042 +"2042-11-24","Eid al-Adha Holiday* (*estimated)","AE",2042 +"2042-11-25","Eid al-Adha Holiday* (*estimated)","AE",2042 +"2042-12-01","Commemoration Day","AE",2042 +"2042-12-02","National Day","AE",2042 +"2042-12-03","National Day Holiday","AE",2042 +"2042-12-14","Al Hijra - Islamic New Year* (*estimated)","AE",2042 +"2043-01-01","New Year's Day","AE",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","AE",2043 +"2043-09-05","Eid al-Fitr Holiday* (*estimated)","AE",2043 +"2043-09-06","Eid al-Fitr Holiday* (*estimated)","AE",2043 +"2043-11-11","Arafat (Hajj) Day* (*estimated)","AE",2043 +"2043-11-12","Eid al-Adha* (*estimated)","AE",2043 +"2043-11-13","Eid al-Adha Holiday* (*estimated)","AE",2043 +"2043-11-14","Eid al-Adha Holiday* (*estimated)","AE",2043 +"2043-12-01","Commemoration Day","AE",2043 +"2043-12-02","National Day","AE",2043 +"2043-12-03","Al Hijra - Islamic New Year* (*estimated)","AE",2043 +"2043-12-03","National Day Holiday","AE",2043 +"2044-01-01","New Year's Day","AE",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","AE",2044 +"2044-08-25","Eid al-Fitr Holiday* (*estimated)","AE",2044 +"2044-08-26","Eid al-Fitr Holiday* (*estimated)","AE",2044 +"2044-10-30","Arafat (Hajj) Day* (*estimated)","AE",2044 +"2044-10-31","Eid al-Adha* (*estimated)","AE",2044 +"2044-11-01","Eid al-Adha Holiday* (*estimated)","AE",2044 +"2044-11-02","Eid al-Adha Holiday* (*estimated)","AE",2044 +"2044-11-21","Al Hijra - Islamic New Year* (*estimated)","AE",2044 +"2044-12-01","Commemoration Day","AE",2044 +"2044-12-02","National Day","AE",2044 +"2044-12-03","National Day Holiday","AE",2044 +"1995-01-01","New Year's Day","AL",1995 +"1995-01-02","New Year's Day","AL",1995 +"1995-01-03","New Year's Day (Observed)","AL",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","AL",1995 +"1995-04-16","Catholic Easter","AL",1995 +"1995-04-17","Catholic Easter (Observed)","AL",1995 +"1995-04-23","Orthodox Easter","AL",1995 +"1995-04-24","Orthodox Easter (Observed)","AL",1995 +"1995-05-01","May Day","AL",1995 +"1995-05-09","Eid al-Adha* (*estimated)","AL",1995 +"1995-11-28","Independence Day","AL",1995 +"1995-11-29","Liberation Day","AL",1995 +"1995-12-25","Christmas Day","AL",1995 +"1996-01-01","New Year's Day","AL",1996 +"1996-01-02","New Year's Day","AL",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","AL",1996 +"1996-03-22","Nevruz","AL",1996 +"1996-04-07","Catholic Easter","AL",1996 +"1996-04-08","Catholic Easter (Observed)","AL",1996 +"1996-04-14","Orthodox Easter","AL",1996 +"1996-04-15","Orthodox Easter (Observed)","AL",1996 +"1996-04-27","Eid al-Adha* (*estimated)","AL",1996 +"1996-04-29","Eid al-Adha* (*estimated) (Observed)","AL",1996 +"1996-05-01","May Day","AL",1996 +"1996-11-28","Independence Day","AL",1996 +"1996-11-29","Liberation Day","AL",1996 +"1996-12-25","Christmas Day","AL",1996 +"1997-01-01","New Year's Day","AL",1997 +"1997-01-02","New Year's Day","AL",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","AL",1997 +"1997-02-10","Eid al-Fitr* (*estimated) (Observed)","AL",1997 +"1997-03-22","Nevruz","AL",1997 +"1997-03-24","Nevruz (Observed)","AL",1997 +"1997-03-30","Catholic Easter","AL",1997 +"1997-03-31","Catholic Easter (Observed)","AL",1997 +"1997-04-17","Eid al-Adha* (*estimated)","AL",1997 +"1997-04-27","Orthodox Easter","AL",1997 +"1997-04-28","Orthodox Easter (Observed)","AL",1997 +"1997-05-01","May Day","AL",1997 +"1997-11-28","Independence Day","AL",1997 +"1997-11-29","Liberation Day","AL",1997 +"1997-12-01","Liberation Day (Observed)","AL",1997 +"1997-12-25","Christmas Day","AL",1997 +"1998-01-01","New Year's Day","AL",1998 +"1998-01-02","New Year's Day","AL",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","AL",1998 +"1998-03-22","Nevruz","AL",1998 +"1998-03-23","Nevruz (Observed)","AL",1998 +"1998-04-07","Eid al-Adha* (*estimated)","AL",1998 +"1998-04-12","Catholic Easter","AL",1998 +"1998-04-13","Catholic Easter (Observed)","AL",1998 +"1998-04-19","Orthodox Easter","AL",1998 +"1998-04-20","Orthodox Easter (Observed)","AL",1998 +"1998-05-01","May Day","AL",1998 +"1998-11-28","Independence Day","AL",1998 +"1998-11-29","Liberation Day","AL",1998 +"1998-11-30","Independence Day (Observed)","AL",1998 +"1998-12-01","Liberation Day (Observed)","AL",1998 +"1998-12-25","Christmas Day","AL",1998 +"1999-01-01","New Year's Day","AL",1999 +"1999-01-02","New Year's Day","AL",1999 +"1999-01-04","New Year's Day (Observed)","AL",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","AL",1999 +"1999-03-22","Nevruz","AL",1999 +"1999-03-27","Eid al-Adha* (*estimated)","AL",1999 +"1999-03-29","Eid al-Adha* (*estimated) (Observed)","AL",1999 +"1999-04-04","Catholic Easter","AL",1999 +"1999-04-05","Catholic Easter (Observed)","AL",1999 +"1999-04-11","Orthodox Easter","AL",1999 +"1999-04-12","Orthodox Easter (Observed)","AL",1999 +"1999-05-01","May Day","AL",1999 +"1999-05-03","May Day (Observed)","AL",1999 +"1999-11-28","Independence Day","AL",1999 +"1999-11-29","Liberation Day","AL",1999 +"1999-11-30","Independence Day (Observed)","AL",1999 +"1999-12-25","Christmas Day","AL",1999 +"1999-12-27","Christmas Day (Observed)","AL",1999 +"2000-01-01","New Year's Day","AL",2000 +"2000-01-02","New Year's Day","AL",2000 +"2000-01-03","New Year's Day (Observed)","AL",2000 +"2000-01-04","New Year's Day (Observed)","AL",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","AL",2000 +"2000-01-10","Eid al-Fitr* (*estimated) (Observed)","AL",2000 +"2000-03-16","Eid al-Adha* (*estimated)","AL",2000 +"2000-03-22","Nevruz","AL",2000 +"2000-04-23","Catholic Easter","AL",2000 +"2000-04-24","Catholic Easter (Observed)","AL",2000 +"2000-04-30","Orthodox Easter","AL",2000 +"2000-05-01","May Day","AL",2000 +"2000-05-02","Orthodox Easter (Observed)","AL",2000 +"2000-11-28","Independence Day","AL",2000 +"2000-11-29","Liberation Day","AL",2000 +"2000-12-25","Christmas Day","AL",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","AL",2000 +"2001-01-01","New Year's Day","AL",2001 +"2001-01-02","New Year's Day","AL",2001 +"2001-03-05","Eid al-Adha* (*estimated)","AL",2001 +"2001-03-22","Nevruz","AL",2001 +"2001-04-15","Catholic Easter","AL",2001 +"2001-04-15","Orthodox Easter","AL",2001 +"2001-04-16","Catholic Easter (Observed)","AL",2001 +"2001-04-16","Orthodox Easter (Observed)","AL",2001 +"2001-05-01","May Day","AL",2001 +"2001-11-28","Independence Day","AL",2001 +"2001-11-29","Liberation Day","AL",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","AL",2001 +"2001-12-17","Eid al-Fitr* (*estimated) (Observed)","AL",2001 +"2001-12-25","Christmas Day","AL",2001 +"2002-01-01","New Year's Day","AL",2002 +"2002-01-02","New Year's Day","AL",2002 +"2002-02-22","Eid al-Adha* (*estimated)","AL",2002 +"2002-03-22","Nevruz","AL",2002 +"2002-03-31","Catholic Easter","AL",2002 +"2002-04-01","Catholic Easter (Observed)","AL",2002 +"2002-05-01","May Day","AL",2002 +"2002-05-05","Orthodox Easter","AL",2002 +"2002-05-06","Orthodox Easter (Observed)","AL",2002 +"2002-11-28","Independence Day","AL",2002 +"2002-11-29","Liberation Day","AL",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","AL",2002 +"2002-12-25","Christmas Day","AL",2002 +"2003-01-01","New Year's Day","AL",2003 +"2003-01-02","New Year's Day","AL",2003 +"2003-02-11","Eid al-Adha* (*estimated)","AL",2003 +"2003-03-22","Nevruz","AL",2003 +"2003-03-24","Nevruz (Observed)","AL",2003 +"2003-04-20","Catholic Easter","AL",2003 +"2003-04-21","Catholic Easter (Observed)","AL",2003 +"2003-04-27","Orthodox Easter","AL",2003 +"2003-04-28","Orthodox Easter (Observed)","AL",2003 +"2003-05-01","May Day","AL",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","AL",2003 +"2003-11-28","Independence Day","AL",2003 +"2003-11-29","Liberation Day","AL",2003 +"2003-12-01","Liberation Day (Observed)","AL",2003 +"2003-12-25","Christmas Day","AL",2003 +"2004-01-01","New Year's Day","AL",2004 +"2004-01-02","New Year's Day","AL",2004 +"2004-02-01","Eid al-Adha* (*estimated)","AL",2004 +"2004-02-02","Eid al-Adha* (*estimated) (Observed)","AL",2004 +"2004-03-14","Summer Day","AL",2004 +"2004-03-15","Summer Day (Observed)","AL",2004 +"2004-03-22","Nevruz","AL",2004 +"2004-04-11","Catholic Easter","AL",2004 +"2004-04-11","Orthodox Easter","AL",2004 +"2004-04-12","Catholic Easter (Observed)","AL",2004 +"2004-04-12","Orthodox Easter (Observed)","AL",2004 +"2004-05-01","May Day","AL",2004 +"2004-05-03","May Day (Observed)","AL",2004 +"2004-10-19","Mother Teresa Beatification Day","AL",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","AL",2004 +"2004-11-15","Eid al-Fitr* (*estimated) (Observed)","AL",2004 +"2004-11-28","Independence Day","AL",2004 +"2004-11-29","Liberation Day","AL",2004 +"2004-11-30","Independence Day (Observed)","AL",2004 +"2004-12-25","Christmas Day","AL",2004 +"2004-12-27","Christmas Day (Observed)","AL",2004 +"2005-01-01","New Year's Day","AL",2005 +"2005-01-02","New Year's Day","AL",2005 +"2005-01-03","New Year's Day (Observed)","AL",2005 +"2005-01-04","New Year's Day (Observed)","AL",2005 +"2005-01-21","Eid al-Adha* (*estimated)","AL",2005 +"2005-03-14","Summer Day","AL",2005 +"2005-03-22","Nevruz","AL",2005 +"2005-03-27","Catholic Easter","AL",2005 +"2005-03-28","Catholic Easter (Observed)","AL",2005 +"2005-05-01","May Day","AL",2005 +"2005-05-01","Orthodox Easter","AL",2005 +"2005-05-02","May Day (Observed)","AL",2005 +"2005-05-02","Orthodox Easter (Observed)","AL",2005 +"2005-10-19","Mother Teresa Beatification Day","AL",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","AL",2005 +"2005-11-28","Independence Day","AL",2005 +"2005-11-29","Liberation Day","AL",2005 +"2005-12-25","Christmas Day","AL",2005 +"2005-12-26","Christmas Day (Observed)","AL",2005 +"2006-01-01","New Year's Day","AL",2006 +"2006-01-02","New Year's Day","AL",2006 +"2006-01-03","New Year's Day (Observed)","AL",2006 +"2006-01-10","Eid al-Adha* (*estimated)","AL",2006 +"2006-03-14","Summer Day","AL",2006 +"2006-03-22","Nevruz","AL",2006 +"2006-04-16","Catholic Easter","AL",2006 +"2006-04-17","Catholic Easter (Observed)","AL",2006 +"2006-04-23","Orthodox Easter","AL",2006 +"2006-04-24","Orthodox Easter (Observed)","AL",2006 +"2006-05-01","May Day","AL",2006 +"2006-10-19","Mother Teresa Beatification Day","AL",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","AL",2006 +"2006-11-28","Independence Day","AL",2006 +"2006-11-29","Liberation Day","AL",2006 +"2006-12-25","Christmas Day","AL",2006 +"2006-12-31","Eid al-Adha* (*estimated)","AL",2006 +"2007-01-01","New Year's Day","AL",2007 +"2007-01-02","New Year's Day","AL",2007 +"2007-01-03","Eid al-Adha (Observed)","AL",2007 +"2007-03-14","Summer Day","AL",2007 +"2007-03-22","Nevruz","AL",2007 +"2007-04-08","Catholic Easter","AL",2007 +"2007-04-08","Orthodox Easter","AL",2007 +"2007-04-09","Catholic Easter (Observed)","AL",2007 +"2007-04-09","Orthodox Easter (Observed)","AL",2007 +"2007-05-01","May Day","AL",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","AL",2007 +"2007-10-15","Eid al-Fitr* (*estimated) (Observed)","AL",2007 +"2007-10-19","Mother Teresa Beatification Day","AL",2007 +"2007-11-28","Independence Day","AL",2007 +"2007-11-29","Liberation Day","AL",2007 +"2007-12-20","Eid al-Adha* (*estimated)","AL",2007 +"2007-12-25","Christmas Day","AL",2007 +"2008-01-01","New Year's Day","AL",2008 +"2008-01-02","New Year's Day","AL",2008 +"2008-03-14","Summer Day","AL",2008 +"2008-03-22","Nevruz","AL",2008 +"2008-03-23","Catholic Easter","AL",2008 +"2008-03-24","Nevruz (Observed)","AL",2008 +"2008-03-25","Catholic Easter (Observed)","AL",2008 +"2008-04-27","Orthodox Easter","AL",2008 +"2008-04-28","Orthodox Easter (Observed)","AL",2008 +"2008-05-01","May Day","AL",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","AL",2008 +"2008-10-19","Mother Teresa Beatification Day","AL",2008 +"2008-10-20","Mother Teresa Beatification Day (Observed)","AL",2008 +"2008-11-28","Independence Day","AL",2008 +"2008-11-29","Liberation Day","AL",2008 +"2008-12-01","Liberation Day (Observed)","AL",2008 +"2008-12-08","Eid al-Adha* (*estimated)","AL",2008 +"2008-12-25","Christmas Day","AL",2008 +"2009-01-01","New Year's Day","AL",2009 +"2009-01-02","New Year's Day","AL",2009 +"2009-03-14","Summer Day","AL",2009 +"2009-03-16","Summer Day (Observed)","AL",2009 +"2009-03-22","Nevruz","AL",2009 +"2009-03-23","Nevruz (Observed)","AL",2009 +"2009-04-12","Catholic Easter","AL",2009 +"2009-04-13","Catholic Easter (Observed)","AL",2009 +"2009-04-19","Orthodox Easter","AL",2009 +"2009-04-20","Orthodox Easter (Observed)","AL",2009 +"2009-05-01","May Day","AL",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","AL",2009 +"2009-09-21","Eid al-Fitr* (*estimated) (Observed)","AL",2009 +"2009-10-19","Mother Teresa Beatification Day","AL",2009 +"2009-11-27","Eid al-Adha* (*estimated)","AL",2009 +"2009-11-28","Independence Day","AL",2009 +"2009-11-29","Liberation Day","AL",2009 +"2009-11-30","Independence Day (Observed)","AL",2009 +"2009-12-01","Liberation Day (Observed)","AL",2009 +"2009-12-08","National Youth Day","AL",2009 +"2009-12-25","Christmas Day","AL",2009 +"2010-01-01","New Year's Day","AL",2010 +"2010-01-02","New Year's Day","AL",2010 +"2010-01-04","New Year's Day (Observed)","AL",2010 +"2010-03-14","Summer Day","AL",2010 +"2010-03-15","Summer Day (Observed)","AL",2010 +"2010-03-22","Nevruz","AL",2010 +"2010-04-04","Catholic Easter","AL",2010 +"2010-04-04","Orthodox Easter","AL",2010 +"2010-04-05","Catholic Easter (Observed)","AL",2010 +"2010-04-05","Orthodox Easter (Observed)","AL",2010 +"2010-05-01","May Day","AL",2010 +"2010-05-03","May Day (Observed)","AL",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","AL",2010 +"2010-10-19","Mother Teresa Beatification Day","AL",2010 +"2010-11-16","Eid al-Adha* (*estimated)","AL",2010 +"2010-11-28","Independence Day","AL",2010 +"2010-11-29","Liberation Day","AL",2010 +"2010-11-30","Independence Day (Observed)","AL",2010 +"2010-12-08","National Youth Day","AL",2010 +"2010-12-25","Christmas Day","AL",2010 +"2010-12-27","Christmas Day (Observed)","AL",2010 +"2011-01-01","New Year's Day","AL",2011 +"2011-01-02","New Year's Day","AL",2011 +"2011-01-03","New Year's Day (Observed)","AL",2011 +"2011-01-04","New Year's Day (Observed)","AL",2011 +"2011-03-14","Summer Day","AL",2011 +"2011-03-22","Nevruz","AL",2011 +"2011-04-24","Catholic Easter","AL",2011 +"2011-04-24","Orthodox Easter","AL",2011 +"2011-04-25","Catholic Easter (Observed)","AL",2011 +"2011-04-25","Orthodox Easter (Observed)","AL",2011 +"2011-05-01","May Day","AL",2011 +"2011-05-02","May Day (Observed)","AL",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","AL",2011 +"2011-10-19","Mother Teresa Beatification Day","AL",2011 +"2011-11-06","Eid al-Adha* (*estimated)","AL",2011 +"2011-11-07","Eid al-Adha* (*estimated) (Observed)","AL",2011 +"2011-11-28","Independence Day","AL",2011 +"2011-11-29","Liberation Day","AL",2011 +"2011-12-08","National Youth Day","AL",2011 +"2011-12-25","Christmas Day","AL",2011 +"2011-12-26","Christmas Day (Observed)","AL",2011 +"2012-01-01","New Year's Day","AL",2012 +"2012-01-02","New Year's Day","AL",2012 +"2012-01-03","New Year's Day (Observed)","AL",2012 +"2012-03-14","Summer Day","AL",2012 +"2012-03-22","Nevruz","AL",2012 +"2012-04-08","Catholic Easter","AL",2012 +"2012-04-09","Catholic Easter (Observed)","AL",2012 +"2012-04-15","Orthodox Easter","AL",2012 +"2012-04-16","Orthodox Easter (Observed)","AL",2012 +"2012-05-01","May Day","AL",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","AL",2012 +"2012-08-20","Eid al-Fitr* (*estimated) (Observed)","AL",2012 +"2012-10-19","Mother Teresa Beatification Day","AL",2012 +"2012-10-26","Eid al-Adha* (*estimated)","AL",2012 +"2012-11-28","Independence Day","AL",2012 +"2012-11-29","Liberation Day","AL",2012 +"2012-12-08","National Youth Day","AL",2012 +"2012-12-10","National Youth Day (Observed)","AL",2012 +"2012-12-25","Christmas Day","AL",2012 +"2013-01-01","New Year's Day","AL",2013 +"2013-01-02","New Year's Day","AL",2013 +"2013-03-14","Summer Day","AL",2013 +"2013-03-22","Nevruz","AL",2013 +"2013-03-31","Catholic Easter","AL",2013 +"2013-04-01","Catholic Easter (Observed)","AL",2013 +"2013-05-01","May Day","AL",2013 +"2013-05-05","Orthodox Easter","AL",2013 +"2013-05-06","Orthodox Easter (Observed)","AL",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","AL",2013 +"2013-10-15","Eid al-Adha* (*estimated)","AL",2013 +"2013-10-19","Mother Teresa Beatification Day","AL",2013 +"2013-10-21","Mother Teresa Beatification Day (Observed)","AL",2013 +"2013-11-28","Independence Day","AL",2013 +"2013-11-29","Liberation Day","AL",2013 +"2013-12-08","National Youth Day","AL",2013 +"2013-12-09","National Youth Day (Observed)","AL",2013 +"2013-12-25","Christmas Day","AL",2013 +"2014-01-01","New Year's Day","AL",2014 +"2014-01-02","New Year's Day","AL",2014 +"2014-03-14","Summer Day","AL",2014 +"2014-03-22","Nevruz","AL",2014 +"2014-03-24","Nevruz (Observed)","AL",2014 +"2014-04-20","Catholic Easter","AL",2014 +"2014-04-20","Orthodox Easter","AL",2014 +"2014-04-21","Catholic Easter (Observed)","AL",2014 +"2014-04-21","Orthodox Easter (Observed)","AL",2014 +"2014-05-01","May Day","AL",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","AL",2014 +"2014-10-04","Eid al-Adha* (*estimated)","AL",2014 +"2014-10-06","Eid al-Adha* (*estimated) (Observed)","AL",2014 +"2014-10-19","Mother Teresa Beatification Day","AL",2014 +"2014-10-20","Mother Teresa Beatification Day (Observed)","AL",2014 +"2014-11-28","Independence Day","AL",2014 +"2014-11-29","Liberation Day","AL",2014 +"2014-12-01","Liberation Day (Observed)","AL",2014 +"2014-12-08","National Youth Day","AL",2014 +"2014-12-25","Christmas Day","AL",2014 +"2015-01-01","New Year's Day","AL",2015 +"2015-01-02","New Year's Day","AL",2015 +"2015-03-14","Summer Day","AL",2015 +"2015-03-16","Summer Day (Observed)","AL",2015 +"2015-03-22","Nevruz","AL",2015 +"2015-03-23","Nevruz (Observed)","AL",2015 +"2015-04-05","Catholic Easter","AL",2015 +"2015-04-06","Catholic Easter (Observed)","AL",2015 +"2015-04-12","Orthodox Easter","AL",2015 +"2015-04-13","Orthodox Easter (Observed)","AL",2015 +"2015-05-01","May Day","AL",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","AL",2015 +"2015-09-23","Eid al-Adha* (*estimated)","AL",2015 +"2015-10-19","Mother Teresa Beatification Day","AL",2015 +"2015-11-28","Independence Day","AL",2015 +"2015-11-29","Liberation Day","AL",2015 +"2015-11-30","Independence Day (Observed)","AL",2015 +"2015-12-01","Liberation Day (Observed)","AL",2015 +"2015-12-08","National Youth Day","AL",2015 +"2015-12-25","Christmas Day","AL",2015 +"2016-01-01","New Year's Day","AL",2016 +"2016-01-02","New Year's Day","AL",2016 +"2016-01-04","New Year's Day (Observed)","AL",2016 +"2016-03-14","Summer Day","AL",2016 +"2016-03-22","Nevruz","AL",2016 +"2016-03-27","Catholic Easter","AL",2016 +"2016-03-28","Catholic Easter (Observed)","AL",2016 +"2016-05-01","May Day","AL",2016 +"2016-05-01","Orthodox Easter","AL",2016 +"2016-05-02","May Day (Observed)","AL",2016 +"2016-05-02","Orthodox Easter (Observed)","AL",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","AL",2016 +"2016-09-11","Eid al-Adha* (*estimated)","AL",2016 +"2016-09-12","Eid al-Adha* (*estimated) (Observed)","AL",2016 +"2016-10-19","Mother Teresa Beatification Day","AL",2016 +"2016-11-28","Independence Day","AL",2016 +"2016-11-29","Liberation Day","AL",2016 +"2016-12-08","National Youth Day","AL",2016 +"2016-12-25","Christmas Day","AL",2016 +"2016-12-26","Christmas Day (Observed)","AL",2016 +"2017-01-01","New Year's Day","AL",2017 +"2017-01-02","New Year's Day","AL",2017 +"2017-01-03","New Year's Day (Observed)","AL",2017 +"2017-03-14","Summer Day","AL",2017 +"2017-03-22","Nevruz","AL",2017 +"2017-04-16","Catholic Easter","AL",2017 +"2017-04-16","Orthodox Easter","AL",2017 +"2017-04-17","Catholic Easter (Observed)","AL",2017 +"2017-04-17","Orthodox Easter (Observed)","AL",2017 +"2017-05-01","May Day","AL",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","AL",2017 +"2017-06-26","Eid al-Fitr* (*estimated) (Observed)","AL",2017 +"2017-09-01","Eid al-Adha* (*estimated)","AL",2017 +"2017-10-19","Mother Teresa Beatification Day","AL",2017 +"2017-11-28","Independence Day","AL",2017 +"2017-11-29","Liberation Day","AL",2017 +"2017-12-08","National Youth Day","AL",2017 +"2017-12-25","Christmas Day","AL",2017 +"2018-01-01","New Year's Day","AL",2018 +"2018-01-02","New Year's Day","AL",2018 +"2018-03-14","Summer Day","AL",2018 +"2018-03-22","Nevruz","AL",2018 +"2018-04-01","Catholic Easter","AL",2018 +"2018-04-02","Catholic Easter (Observed)","AL",2018 +"2018-04-08","Orthodox Easter","AL",2018 +"2018-04-09","Orthodox Easter (Observed)","AL",2018 +"2018-05-01","May Day","AL",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","AL",2018 +"2018-08-21","Eid al-Adha* (*estimated)","AL",2018 +"2018-09-05","Mother Teresa Canonization Day","AL",2018 +"2018-11-28","Independence Day","AL",2018 +"2018-11-29","Liberation Day","AL",2018 +"2018-12-08","National Youth Day","AL",2018 +"2018-12-10","National Youth Day (Observed)","AL",2018 +"2018-12-25","Christmas Day","AL",2018 +"2019-01-01","New Year's Day","AL",2019 +"2019-01-02","New Year's Day","AL",2019 +"2019-03-14","Summer Day","AL",2019 +"2019-03-22","Nevruz","AL",2019 +"2019-04-21","Catholic Easter","AL",2019 +"2019-04-22","Catholic Easter (Observed)","AL",2019 +"2019-04-28","Orthodox Easter","AL",2019 +"2019-04-29","Orthodox Easter (Observed)","AL",2019 +"2019-05-01","May Day","AL",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","AL",2019 +"2019-08-11","Eid al-Adha* (*estimated)","AL",2019 +"2019-08-12","Eid al-Adha* (*estimated) (Observed)","AL",2019 +"2019-09-05","Mother Teresa Canonization Day","AL",2019 +"2019-11-28","Independence Day","AL",2019 +"2019-11-29","Liberation Day","AL",2019 +"2019-12-08","National Youth Day","AL",2019 +"2019-12-09","National Youth Day (Observed)","AL",2019 +"2019-12-25","Christmas Day","AL",2019 +"2020-01-01","New Year's Day","AL",2020 +"2020-01-02","New Year's Day","AL",2020 +"2020-03-14","Summer Day","AL",2020 +"2020-03-16","Summer Day (Observed)","AL",2020 +"2020-03-22","Nevruz","AL",2020 +"2020-03-23","Nevruz (Observed)","AL",2020 +"2020-04-12","Catholic Easter","AL",2020 +"2020-04-13","Catholic Easter (Observed)","AL",2020 +"2020-04-19","Orthodox Easter","AL",2020 +"2020-04-20","Orthodox Easter (Observed)","AL",2020 +"2020-05-01","May Day","AL",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","AL",2020 +"2020-05-25","Eid al-Fitr* (*estimated) (Observed)","AL",2020 +"2020-07-31","Eid al-Adha* (*estimated)","AL",2020 +"2020-09-05","Mother Teresa Canonization Day","AL",2020 +"2020-09-07","Mother Teresa Canonization Day (Observed)","AL",2020 +"2020-11-28","Independence Day","AL",2020 +"2020-11-29","Liberation Day","AL",2020 +"2020-11-30","Independence Day (Observed)","AL",2020 +"2020-12-01","Liberation Day (Observed)","AL",2020 +"2020-12-08","National Youth Day","AL",2020 +"2020-12-25","Christmas Day","AL",2020 +"2021-01-01","New Year's Day","AL",2021 +"2021-01-02","New Year's Day","AL",2021 +"2021-01-04","New Year's Day (Observed)","AL",2021 +"2021-03-14","Summer Day","AL",2021 +"2021-03-15","Summer Day (Observed)","AL",2021 +"2021-03-22","Nevruz","AL",2021 +"2021-04-04","Catholic Easter","AL",2021 +"2021-04-05","Catholic Easter (Observed)","AL",2021 +"2021-05-01","May Day","AL",2021 +"2021-05-02","Orthodox Easter","AL",2021 +"2021-05-03","May Day (Observed)","AL",2021 +"2021-05-04","Orthodox Easter (Observed)","AL",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","AL",2021 +"2021-07-20","Eid al-Adha* (*estimated)","AL",2021 +"2021-09-05","Mother Teresa Canonization Day","AL",2021 +"2021-09-06","Mother Teresa Canonization Day (Observed)","AL",2021 +"2021-11-28","Independence Day","AL",2021 +"2021-11-29","Liberation Day","AL",2021 +"2021-11-30","Independence Day (Observed)","AL",2021 +"2021-12-08","National Youth Day","AL",2021 +"2021-12-25","Christmas Day","AL",2021 +"2021-12-27","Christmas Day (Observed)","AL",2021 +"2022-01-01","New Year's Day","AL",2022 +"2022-01-02","New Year's Day","AL",2022 +"2022-01-03","New Year's Day (Observed)","AL",2022 +"2022-01-04","New Year's Day (Observed)","AL",2022 +"2022-03-14","Summer Day","AL",2022 +"2022-03-21","Public Holiday","AL",2022 +"2022-03-22","Nevruz","AL",2022 +"2022-04-17","Catholic Easter","AL",2022 +"2022-04-18","Catholic Easter (Observed)","AL",2022 +"2022-04-24","Orthodox Easter","AL",2022 +"2022-04-25","Orthodox Easter (Observed)","AL",2022 +"2022-05-01","May Day","AL",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","AL",2022 +"2022-05-03","May Day (Observed)","AL",2022 +"2022-07-09","Eid al-Adha* (*estimated)","AL",2022 +"2022-07-11","Eid al-Adha* (*estimated) (Observed)","AL",2022 +"2022-09-05","Mother Teresa Canonization Day","AL",2022 +"2022-11-28","Independence Day","AL",2022 +"2022-11-29","Liberation Day","AL",2022 +"2022-12-08","National Youth Day","AL",2022 +"2022-12-25","Christmas Day","AL",2022 +"2022-12-26","Christmas Day (Observed)","AL",2022 +"2023-01-01","New Year's Day","AL",2023 +"2023-01-02","New Year's Day","AL",2023 +"2023-01-03","New Year's Day (Observed)","AL",2023 +"2023-03-14","Summer Day","AL",2023 +"2023-03-22","Nevruz","AL",2023 +"2023-04-09","Catholic Easter","AL",2023 +"2023-04-10","Catholic Easter (Observed)","AL",2023 +"2023-04-16","Orthodox Easter","AL",2023 +"2023-04-17","Orthodox Easter (Observed)","AL",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","AL",2023 +"2023-05-01","May Day","AL",2023 +"2023-06-28","Eid al-Adha* (*estimated)","AL",2023 +"2023-09-05","Mother Teresa Canonization Day","AL",2023 +"2023-11-28","Independence Day","AL",2023 +"2023-11-29","Liberation Day","AL",2023 +"2023-12-08","National Youth Day","AL",2023 +"2023-12-25","Christmas Day","AL",2023 +"2024-01-01","New Year's Day","AL",2024 +"2024-01-02","New Year's Day","AL",2024 +"2024-03-14","Summer Day","AL",2024 +"2024-03-22","Nevruz","AL",2024 +"2024-03-31","Catholic Easter","AL",2024 +"2024-04-01","Catholic Easter (Observed)","AL",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","AL",2024 +"2024-05-01","May Day","AL",2024 +"2024-05-05","Orthodox Easter","AL",2024 +"2024-05-06","Orthodox Easter (Observed)","AL",2024 +"2024-06-16","Eid al-Adha* (*estimated)","AL",2024 +"2024-06-17","Eid al-Adha* (*estimated) (Observed)","AL",2024 +"2024-09-05","Mother Teresa Canonization Day","AL",2024 +"2024-11-28","Independence Day","AL",2024 +"2024-11-29","Liberation Day","AL",2024 +"2024-12-08","National Youth Day","AL",2024 +"2024-12-09","National Youth Day (Observed)","AL",2024 +"2024-12-25","Christmas Day","AL",2024 +"2025-01-01","New Year's Day","AL",2025 +"2025-01-02","New Year's Day","AL",2025 +"2025-03-14","Summer Day","AL",2025 +"2025-03-22","Nevruz","AL",2025 +"2025-03-24","Nevruz (Observed)","AL",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","AL",2025 +"2025-03-31","Eid al-Fitr* (*estimated) (Observed)","AL",2025 +"2025-04-20","Catholic Easter","AL",2025 +"2025-04-20","Orthodox Easter","AL",2025 +"2025-04-21","Catholic Easter (Observed)","AL",2025 +"2025-04-21","Orthodox Easter (Observed)","AL",2025 +"2025-05-01","May Day","AL",2025 +"2025-06-06","Eid al-Adha* (*estimated)","AL",2025 +"2025-09-05","Mother Teresa Canonization Day","AL",2025 +"2025-11-28","Independence Day","AL",2025 +"2025-11-29","Liberation Day","AL",2025 +"2025-12-01","Liberation Day (Observed)","AL",2025 +"2025-12-08","National Youth Day","AL",2025 +"2025-12-25","Christmas Day","AL",2025 +"2026-01-01","New Year's Day","AL",2026 +"2026-01-02","New Year's Day","AL",2026 +"2026-03-14","Summer Day","AL",2026 +"2026-03-16","Summer Day (Observed)","AL",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","AL",2026 +"2026-03-22","Nevruz","AL",2026 +"2026-03-23","Nevruz (Observed)","AL",2026 +"2026-04-05","Catholic Easter","AL",2026 +"2026-04-06","Catholic Easter (Observed)","AL",2026 +"2026-04-12","Orthodox Easter","AL",2026 +"2026-04-13","Orthodox Easter (Observed)","AL",2026 +"2026-05-01","May Day","AL",2026 +"2026-05-27","Eid al-Adha* (*estimated)","AL",2026 +"2026-09-05","Mother Teresa Canonization Day","AL",2026 +"2026-09-07","Mother Teresa Canonization Day (Observed)","AL",2026 +"2026-11-28","Independence Day","AL",2026 +"2026-11-29","Liberation Day","AL",2026 +"2026-11-30","Independence Day (Observed)","AL",2026 +"2026-12-01","Liberation 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(*estimated)","AL",2039 +"2039-12-27","Christmas Day (Observed)","AL",2039 +"2040-01-01","New Year's Day","AL",2040 +"2040-01-02","New Year's Day","AL",2040 +"2040-01-03","New Year's Day (Observed)","AL",2040 +"2040-03-14","Summer Day","AL",2040 +"2040-03-22","Nevruz","AL",2040 +"2040-04-01","Catholic Easter","AL",2040 +"2040-04-02","Catholic Easter (Observed)","AL",2040 +"2040-05-01","May Day","AL",2040 +"2040-05-06","Orthodox Easter","AL",2040 +"2040-05-07","Orthodox Easter (Observed)","AL",2040 +"2040-09-05","Mother Teresa Canonization Day","AL",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","AL",2040 +"2040-10-08","Eid al-Fitr* (*estimated) (Observed)","AL",2040 +"2040-11-28","Independence Day","AL",2040 +"2040-11-29","Liberation Day","AL",2040 +"2040-12-08","National Youth Day","AL",2040 +"2040-12-10","National Youth Day (Observed)","AL",2040 +"2040-12-14","Eid al-Adha* (*estimated)","AL",2040 +"2040-12-25","Christmas Day","AL",2040 +"2041-01-01","New Year's Day","AL",2041 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Easter","AL",2043 +"2043-05-04","Orthodox Easter (Observed)","AL",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","AL",2043 +"2043-09-05","Mother Teresa Canonization Day","AL",2043 +"2043-09-07","Mother Teresa Canonization Day (Observed)","AL",2043 +"2043-11-12","Eid al-Adha* (*estimated)","AL",2043 +"2043-11-28","Independence Day","AL",2043 +"2043-11-29","Liberation Day","AL",2043 +"2043-11-30","Independence Day (Observed)","AL",2043 +"2043-12-01","Liberation Day (Observed)","AL",2043 +"2043-12-08","National Youth Day","AL",2043 +"2043-12-25","Christmas Day","AL",2043 +"2044-01-01","New Year's Day","AL",2044 +"2044-01-02","New Year's Day","AL",2044 +"2044-01-04","New Year's Day (Observed)","AL",2044 +"2044-03-14","Summer Day","AL",2044 +"2044-03-22","Nevruz","AL",2044 +"2044-04-17","Catholic Easter","AL",2044 +"2044-04-18","Catholic Easter (Observed)","AL",2044 +"2044-04-24","Orthodox Easter","AL",2044 +"2044-04-25","Orthodox Easter (Observed)","AL",2044 +"2044-05-01","May Day","AL",2044 +"2044-05-02","May Day (Observed)","AL",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","AL",2044 +"2044-09-05","Mother Teresa Canonization Day","AL",2044 +"2044-10-31","Eid al-Adha* (*estimated)","AL",2044 +"2044-11-28","Independence Day","AL",2044 +"2044-11-29","Liberation Day","AL",2044 +"2044-12-08","National Youth Day","AL",2044 +"2044-12-25","Christmas Day","AL",2044 +"2044-12-26","Christmas Day (Observed)","AL",2044 +"1995-01-01","New Year's Day","AM",1995 +"1995-01-02","New Year's Day","AM",1995 +"1995-01-06","Christmas and Epiphany Day","AM",1995 +"1995-03-08","Womens Day","AM",1995 +"1995-04-07","A Holiday of Motherhood and Beauty","AM",1995 +"1995-04-24","Genocide Memorial Day","AM",1995 +"1995-05-09","Victory and Peace Day","AM",1995 +"1995-05-28","Republic Day","AM",1995 +"1995-09-21","Independence Day","AM",1995 +"1995-12-31","New Year's Eve","AM",1995 +"1996-01-01","New Year's Day","AM",1996 +"1996-01-02","New Year's Day","AM",1996 +"1996-01-06","Christmas and Epiphany Day","AM",1996 +"1996-03-08","Womens Day","AM",1996 +"1996-04-07","A Holiday of Motherhood and Beauty","AM",1996 +"1996-04-24","Genocide Memorial Day","AM",1996 +"1996-05-09","Victory and Peace Day","AM",1996 +"1996-05-28","Republic Day","AM",1996 +"1996-07-05","Constitution Day","AM",1996 +"1996-09-21","Independence Day","AM",1996 +"1996-12-31","New Year's Eve","AM",1996 +"1997-01-01","New Year's Day","AM",1997 +"1997-01-02","New Year's Day","AM",1997 +"1997-01-06","Christmas and Epiphany Day","AM",1997 +"1997-03-08","Womens Day","AM",1997 +"1997-04-07","A Holiday of Motherhood and Beauty","AM",1997 +"1997-04-24","Genocide Memorial Day","AM",1997 +"1997-05-09","Victory and Peace Day","AM",1997 +"1997-05-28","Republic Day","AM",1997 +"1997-07-05","Constitution Day","AM",1997 +"1997-09-21","Independence Day","AM",1997 +"1997-12-31","New Year's Eve","AM",1997 +"1998-01-01","New Year's Day","AM",1998 +"1998-01-02","New Year's Day","AM",1998 +"1998-01-06","Christmas and Epiphany Day","AM",1998 +"1998-03-08","Womens Day","AM",1998 +"1998-04-07","A Holiday of Motherhood and Beauty","AM",1998 +"1998-04-24","Genocide Memorial Day","AM",1998 +"1998-05-09","Victory and Peace Day","AM",1998 +"1998-05-28","Republic Day","AM",1998 +"1998-07-05","Constitution Day","AM",1998 +"1998-09-21","Independence Day","AM",1998 +"1998-12-31","New Year's Eve","AM",1998 +"1999-01-01","New Year's Day","AM",1999 +"1999-01-02","New Year's Day","AM",1999 +"1999-01-06","Christmas and Epiphany Day","AM",1999 +"1999-03-08","Womens Day","AM",1999 +"1999-04-07","A Holiday of Motherhood and Beauty","AM",1999 +"1999-04-24","Genocide Memorial Day","AM",1999 +"1999-05-09","Victory and Peace Day","AM",1999 +"1999-05-28","Republic Day","AM",1999 +"1999-07-05","Constitution Day","AM",1999 +"1999-09-21","Independence Day","AM",1999 +"1999-12-31","New Year's Eve","AM",1999 +"2000-01-01","New Year's Day","AM",2000 +"2000-01-02","New Year's Day","AM",2000 +"2000-01-06","Christmas and Epiphany Day","AM",2000 +"2000-03-08","Womens Day","AM",2000 +"2000-04-07","A Holiday of Motherhood and Beauty","AM",2000 +"2000-04-24","Genocide Memorial Day","AM",2000 +"2000-05-09","Victory and Peace Day","AM",2000 +"2000-05-28","Republic Day","AM",2000 +"2000-07-05","Constitution Day","AM",2000 +"2000-09-21","Independence Day","AM",2000 +"2000-12-31","New Year's Eve","AM",2000 +"2001-01-01","New Year's Day","AM",2001 +"2001-01-02","New Year's Day","AM",2001 +"2001-01-06","Christmas and Epiphany Day","AM",2001 +"2001-03-08","Womens Day","AM",2001 +"2001-04-07","A Holiday of Motherhood and Beauty","AM",2001 +"2001-04-24","Genocide Memorial Day","AM",2001 +"2001-05-01","International Day of Workers' Solidarity","AM",2001 +"2001-05-09","Victory and Peace Day","AM",2001 +"2001-05-28","Republic Day","AM",2001 +"2001-07-05","Constitution Day","AM",2001 +"2001-09-21","Independence Day","AM",2001 +"2001-12-31","New Year's Eve","AM",2001 +"2002-01-01","New Year's Day","AM",2002 +"2002-01-02","New Year's Day","AM",2002 +"2002-01-06","Christmas and Epiphany Day","AM",2002 +"2002-03-08","Womens Day","AM",2002 +"2002-04-24","Genocide Memorial Day","AM",2002 +"2002-05-01","Labor day","AM",2002 +"2002-05-09","Victory and Peace Day","AM",2002 +"2002-05-28","Republic Day","AM",2002 +"2002-07-05","Constitution Day","AM",2002 +"2002-09-21","Independence Day","AM",2002 +"2002-12-31","New Year's Eve","AM",2002 +"2003-01-01","New Year's Day","AM",2003 +"2003-01-02","New Year's Day","AM",2003 +"2003-01-06","Christmas and Epiphany Day","AM",2003 +"2003-01-28","Army Day","AM",2003 +"2003-03-08","Womens Day","AM",2003 +"2003-04-24","Genocide Memorial Day","AM",2003 +"2003-05-01","Labor day","AM",2003 +"2003-05-09","Victory and Peace Day","AM",2003 +"2003-05-28","Republic Day","AM",2003 +"2003-07-05","Constitution Day","AM",2003 +"2003-09-21","Independence Day","AM",2003 +"2003-12-31","New Year's Eve","AM",2003 +"2004-01-01","New Year's Day","AM",2004 +"2004-01-02","New Year's Day","AM",2004 +"2004-01-06","Christmas and Epiphany Day","AM",2004 +"2004-01-28","Army Day","AM",2004 +"2004-03-08","Womens Day","AM",2004 +"2004-04-24","Genocide Memorial Day","AM",2004 +"2004-05-01","Labor day","AM",2004 +"2004-05-09","Victory and Peace Day","AM",2004 +"2004-05-28","Republic Day","AM",2004 +"2004-07-05","Constitution Day","AM",2004 +"2004-09-21","Independence Day","AM",2004 +"2004-12-31","New Year's Eve","AM",2004 +"2005-01-01","New Year's Day","AM",2005 +"2005-01-02","New Year's Day","AM",2005 +"2005-01-06","Christmas and Epiphany Day","AM",2005 +"2005-01-28","Army Day","AM",2005 +"2005-03-08","Womens Day","AM",2005 +"2005-04-24","Genocide Memorial Day","AM",2005 +"2005-05-01","Labor day","AM",2005 +"2005-05-09","Victory and Peace Day","AM",2005 +"2005-05-28","Republic Day","AM",2005 +"2005-07-05","Constitution Day","AM",2005 +"2005-09-21","Independence Day","AM",2005 +"2005-12-31","New Year's Eve","AM",2005 +"2006-01-01","New Year's Day","AM",2006 +"2006-01-02","New Year's Day","AM",2006 +"2006-01-06","Christmas and Epiphany Day","AM",2006 +"2006-01-28","Army Day","AM",2006 +"2006-03-08","Womens Day","AM",2006 +"2006-04-24","Genocide Memorial Day","AM",2006 +"2006-05-01","Labor day","AM",2006 +"2006-05-09","Victory and Peace Day","AM",2006 +"2006-05-28","Republic Day","AM",2006 +"2006-07-05","Constitution Day","AM",2006 +"2006-09-21","Independence Day","AM",2006 +"2006-12-31","New Year's Eve","AM",2006 +"2007-01-01","New Year's Day","AM",2007 +"2007-01-02","New Year's Day","AM",2007 +"2007-01-06","Christmas and Epiphany Day","AM",2007 +"2007-01-28","Army Day","AM",2007 +"2007-03-08","Womens Day","AM",2007 +"2007-04-24","Genocide Memorial Day","AM",2007 +"2007-05-01","Labor day","AM",2007 +"2007-05-09","Victory and Peace Day","AM",2007 +"2007-05-28","Republic Day","AM",2007 +"2007-07-05","Constitution Day","AM",2007 +"2007-09-21","Independence Day","AM",2007 +"2007-12-31","New Year's Eve","AM",2007 +"2008-01-01","New Year's Day","AM",2008 +"2008-01-02","New Year's Day","AM",2008 +"2008-01-06","Christmas and Epiphany Day","AM",2008 +"2008-01-28","Army Day","AM",2008 +"2008-03-08","Womens Day","AM",2008 +"2008-04-24","Genocide Memorial Day","AM",2008 +"2008-05-01","Labor day","AM",2008 +"2008-05-09","Victory and Peace Day","AM",2008 +"2008-05-28","Republic Day","AM",2008 +"2008-07-05","Constitution Day","AM",2008 +"2008-09-21","Independence Day","AM",2008 +"2008-12-31","New Year's Eve","AM",2008 +"2009-01-01","New Year's Day","AM",2009 +"2009-01-02","New Year's Day","AM",2009 +"2009-01-06","Christmas and Epiphany Day","AM",2009 +"2009-01-28","Army Day","AM",2009 +"2009-03-08","Womens Day","AM",2009 +"2009-04-24","Genocide Memorial Day","AM",2009 +"2009-05-01","Labor day","AM",2009 +"2009-05-09","Victory and Peace Day","AM",2009 +"2009-05-28","Republic Day","AM",2009 +"2009-07-05","Constitution Day","AM",2009 +"2009-09-21","Independence Day","AM",2009 +"2009-12-31","New Year's Eve","AM",2009 +"2010-01-01","New Year's Day","AM",2010 +"2010-01-02","New Year's Day","AM",2010 +"2010-01-03","New Year's Day","AM",2010 +"2010-01-04","New Year's Day","AM",2010 +"2010-01-05","Christmas Holidays","AM",2010 +"2010-01-06","Christmas and Epiphany Day","AM",2010 +"2010-01-07","Memorial Day","AM",2010 +"2010-01-28","Army Day","AM",2010 +"2010-03-08","Womens Day","AM",2010 +"2010-04-24","Genocide Memorial Day","AM",2010 +"2010-05-01","Labor day","AM",2010 +"2010-05-09","Victory and Peace Day","AM",2010 +"2010-05-28","Republic Day","AM",2010 +"2010-07-05","Constitution Day","AM",2010 +"2010-09-21","Independence Day","AM",2010 +"2010-12-31","New Year's Eve","AM",2010 +"2011-01-01","New Year's Day","AM",2011 +"2011-01-02","New Year's Day","AM",2011 +"2011-01-03","New Year's Day","AM",2011 +"2011-01-04","New Year's Day","AM",2011 +"2011-01-05","Christmas Holidays","AM",2011 +"2011-01-06","Christmas and Epiphany Day","AM",2011 +"2011-01-07","Memorial Day","AM",2011 +"2011-01-28","Army Day","AM",2011 +"2011-03-08","Womens Day","AM",2011 +"2011-04-24","Genocide Memorial Day","AM",2011 +"2011-05-01","Labor day","AM",2011 +"2011-05-09","Victory and Peace Day","AM",2011 +"2011-05-28","Republic Day","AM",2011 +"2011-07-05","Constitution Day","AM",2011 +"2011-09-21","Independence Day","AM",2011 +"2011-12-31","New Year's Eve","AM",2011 +"2012-01-01","New Year's Day","AM",2012 +"2012-01-02","New Year's Day","AM",2012 +"2012-01-03","New Year's Day","AM",2012 +"2012-01-04","New Year's Day","AM",2012 +"2012-01-05","Christmas Holidays","AM",2012 +"2012-01-06","Christmas and Epiphany Day","AM",2012 +"2012-01-07","Memorial Day","AM",2012 +"2012-01-28","Army Day","AM",2012 +"2012-03-08","Womens Day","AM",2012 +"2012-04-24","Genocide Memorial Day","AM",2012 +"2012-05-01","Labor day","AM",2012 +"2012-05-09","Victory and Peace Day","AM",2012 +"2012-05-28","Republic Day","AM",2012 +"2012-07-05","Constitution Day","AM",2012 +"2012-09-21","Independence Day","AM",2012 +"2012-12-31","New Year's Eve","AM",2012 +"2013-01-01","New Year's Day","AM",2013 +"2013-01-02","New Year's Day","AM",2013 +"2013-01-03","New Year's Day","AM",2013 +"2013-01-04","New Year's Day","AM",2013 +"2013-01-05","Christmas Holidays","AM",2013 +"2013-01-06","Christmas and Epiphany Day","AM",2013 +"2013-01-07","Memorial Day","AM",2013 +"2013-01-28","Army Day","AM",2013 +"2013-03-08","Womens Day","AM",2013 +"2013-04-24","Genocide Memorial Day","AM",2013 +"2013-05-01","Labor day","AM",2013 +"2013-05-09","Victory and Peace Day","AM",2013 +"2013-05-28","Republic Day","AM",2013 +"2013-07-05","Constitution Day","AM",2013 +"2013-09-21","Independence Day","AM",2013 +"2013-12-31","New Year's Eve","AM",2013 +"2014-01-01","New Year's Day","AM",2014 +"2014-01-02","New Year's Day","AM",2014 +"2014-01-03","New Year's Day","AM",2014 +"2014-01-04","New Year's Day","AM",2014 +"2014-01-05","Christmas Holidays","AM",2014 +"2014-01-06","Christmas and Epiphany Day","AM",2014 +"2014-01-07","Memorial Day","AM",2014 +"2014-01-28","Army Day","AM",2014 +"2014-03-08","Womens Day","AM",2014 +"2014-04-24","Genocide Memorial Day","AM",2014 +"2014-05-01","Labor day","AM",2014 +"2014-05-09","Victory and Peace Day","AM",2014 +"2014-05-28","Republic Day","AM",2014 +"2014-07-05","Constitution Day","AM",2014 +"2014-09-21","Independence Day","AM",2014 +"2014-12-31","New Year's Eve","AM",2014 +"2015-01-01","New Year's Day","AM",2015 +"2015-01-02","New Year's Day","AM",2015 +"2015-01-03","New Year's Day","AM",2015 +"2015-01-04","New Year's Day","AM",2015 +"2015-01-05","Christmas Holidays","AM",2015 +"2015-01-06","Christmas and Epiphany Day","AM",2015 +"2015-01-07","Memorial Day","AM",2015 +"2015-01-28","Army Day","AM",2015 +"2015-03-08","Womens Day","AM",2015 +"2015-04-24","Genocide Memorial Day","AM",2015 +"2015-05-01","Labor day","AM",2015 +"2015-05-09","Victory and Peace Day","AM",2015 +"2015-05-28","Republic Day","AM",2015 +"2015-07-05","Constitution Day","AM",2015 +"2015-09-21","Independence Day","AM",2015 +"2015-12-31","New Year's Eve","AM",2015 +"2016-01-01","New Year's Day","AM",2016 +"2016-01-02","New Year's Day","AM",2016 +"2016-01-03","New Year's Day","AM",2016 +"2016-01-04","New Year's Day","AM",2016 +"2016-01-05","Christmas Holidays","AM",2016 +"2016-01-06","Christmas and Epiphany Day","AM",2016 +"2016-01-07","Memorial Day","AM",2016 +"2016-01-28","Army Day","AM",2016 +"2016-03-08","Womens Day","AM",2016 +"2016-04-24","Genocide Memorial Day","AM",2016 +"2016-05-01","Labor day","AM",2016 +"2016-05-09","Victory and Peace Day","AM",2016 +"2016-05-28","Republic Day","AM",2016 +"2016-07-05","Constitution Day","AM",2016 +"2016-09-21","Independence Day","AM",2016 +"2016-12-31","New Year's Eve","AM",2016 +"2017-01-01","New Year's Day","AM",2017 +"2017-01-02","New Year's Day","AM",2017 +"2017-01-03","New Year's Day","AM",2017 +"2017-01-04","New Year's Day","AM",2017 +"2017-01-05","Christmas Holidays","AM",2017 +"2017-01-06","Christmas and Epiphany Day","AM",2017 +"2017-01-07","Memorial Day","AM",2017 +"2017-01-28","Army Day","AM",2017 +"2017-03-08","Womens Day","AM",2017 +"2017-04-24","Genocide Memorial Day","AM",2017 +"2017-05-01","Labor day","AM",2017 +"2017-05-09","Victory and Peace Day","AM",2017 +"2017-05-28","Republic Day","AM",2017 +"2017-07-05","Constitution Day","AM",2017 +"2017-09-21","Independence Day","AM",2017 +"2017-12-31","New Year's Eve","AM",2017 +"2018-01-01","New Year's Day","AM",2018 +"2018-01-02","New Year's Day","AM",2018 +"2018-01-03","New Year's Day","AM",2018 +"2018-01-04","New Year's Day","AM",2018 +"2018-01-05","Christmas Holidays","AM",2018 +"2018-01-06","Christmas and Epiphany Day","AM",2018 +"2018-01-07","Memorial Day","AM",2018 +"2018-01-28","Army Day","AM",2018 +"2018-03-08","Womens Day","AM",2018 +"2018-04-24","Genocide Memorial Day","AM",2018 +"2018-05-01","Labor day","AM",2018 +"2018-05-09","Victory and Peace Day","AM",2018 +"2018-05-28","Republic Day","AM",2018 +"2018-07-05","Constitution Day","AM",2018 +"2018-09-21","Independence Day","AM",2018 +"2018-12-31","New Year's Eve","AM",2018 +"2019-01-01","New Year's Day","AM",2019 +"2019-01-02","New Year's Day","AM",2019 +"2019-01-03","New Year's Day","AM",2019 +"2019-01-04","New Year's Day","AM",2019 +"2019-01-05","Christmas Holidays","AM",2019 +"2019-01-06","Christmas and Epiphany Day","AM",2019 +"2019-01-07","Memorial Day","AM",2019 +"2019-01-28","Army Day","AM",2019 +"2019-03-08","Womens Day","AM",2019 +"2019-04-24","Genocide Memorial Day","AM",2019 +"2019-05-01","Labor day","AM",2019 +"2019-05-09","Victory and Peace Day","AM",2019 +"2019-05-28","Republic Day","AM",2019 +"2019-07-05","Constitution Day","AM",2019 +"2019-09-21","Independence Day","AM",2019 +"2019-12-31","New Year's Eve","AM",2019 +"2020-01-01","New Year's Day","AM",2020 +"2020-01-02","New Year's Day","AM",2020 +"2020-01-03","New Year's Day","AM",2020 +"2020-01-04","New Year's Day","AM",2020 +"2020-01-05","Christmas Holidays","AM",2020 +"2020-01-06","Christmas and Epiphany Day","AM",2020 +"2020-01-07","Memorial Day","AM",2020 +"2020-01-28","Army Day","AM",2020 +"2020-03-08","Womens Day","AM",2020 +"2020-04-24","Genocide Memorial Day","AM",2020 +"2020-05-01","Labor day","AM",2020 +"2020-05-09","Victory and Peace Day","AM",2020 +"2020-05-28","Republic Day","AM",2020 +"2020-07-05","Constitution Day","AM",2020 +"2020-09-21","Independence Day","AM",2020 +"2020-12-31","New Year's Eve","AM",2020 +"2021-01-01","New Year's Day","AM",2021 +"2021-01-02","New Year's Day","AM",2021 +"2021-01-03","New Year's Day","AM",2021 +"2021-01-04","New Year's Day","AM",2021 +"2021-01-05","Christmas Holidays","AM",2021 +"2021-01-06","Christmas and Epiphany Day","AM",2021 +"2021-01-07","Memorial Day","AM",2021 +"2021-01-28","Army Day","AM",2021 +"2021-03-08","Womens Day","AM",2021 +"2021-04-24","Genocide Memorial Day","AM",2021 +"2021-05-01","Labor day","AM",2021 +"2021-05-09","Victory and Peace Day","AM",2021 +"2021-05-28","Republic Day","AM",2021 +"2021-07-05","Constitution Day","AM",2021 +"2021-09-21","Independence Day","AM",2021 +"2021-12-31","New Year's Eve","AM",2021 +"2022-01-01","New Year's Day","AM",2022 +"2022-01-02","New Year's Day","AM",2022 +"2022-01-06","Christmas and Epiphany Day","AM",2022 +"2022-01-28","Army Day","AM",2022 +"2022-03-08","Womens Day","AM",2022 +"2022-04-24","Genocide Memorial Day","AM",2022 +"2022-05-01","Labor day","AM",2022 +"2022-05-09","Victory and Peace Day","AM",2022 +"2022-05-28","Republic Day","AM",2022 +"2022-07-05","Constitution Day","AM",2022 +"2022-09-21","Independence Day","AM",2022 +"2022-12-31","New Year's Eve","AM",2022 +"2023-01-01","New Year's Day","AM",2023 +"2023-01-02","New Year's Day","AM",2023 +"2023-01-06","Christmas and Epiphany Day","AM",2023 +"2023-01-28","Army Day","AM",2023 +"2023-03-08","Womens Day","AM",2023 +"2023-04-24","Genocide Memorial Day","AM",2023 +"2023-05-01","Labor day","AM",2023 +"2023-05-09","Victory and Peace Day","AM",2023 +"2023-05-28","Republic Day","AM",2023 +"2023-07-05","Constitution Day","AM",2023 +"2023-09-21","Independence Day","AM",2023 +"2023-12-31","New Year's Eve","AM",2023 +"2024-01-01","New Year's Day","AM",2024 +"2024-01-02","New Year's Day","AM",2024 +"2024-01-06","Christmas and Epiphany Day","AM",2024 +"2024-01-28","Army Day","AM",2024 +"2024-03-08","Womens Day","AM",2024 +"2024-04-24","Genocide Memorial Day","AM",2024 +"2024-05-01","Labor day","AM",2024 +"2024-05-09","Victory and Peace Day","AM",2024 +"2024-05-28","Republic Day","AM",2024 +"2024-07-05","Constitution Day","AM",2024 +"2024-09-21","Independence Day","AM",2024 +"2024-12-31","New Year's Eve","AM",2024 +"2025-01-01","New Year's Day","AM",2025 +"2025-01-02","New Year's Day","AM",2025 +"2025-01-06","Christmas and Epiphany Day","AM",2025 +"2025-01-28","Army Day","AM",2025 +"2025-03-08","Womens Day","AM",2025 +"2025-04-24","Genocide Memorial Day","AM",2025 +"2025-05-01","Labor day","AM",2025 +"2025-05-09","Victory and Peace Day","AM",2025 +"2025-05-28","Republic Day","AM",2025 +"2025-07-05","Constitution Day","AM",2025 +"2025-09-21","Independence Day","AM",2025 +"2025-12-31","New Year's Eve","AM",2025 +"2026-01-01","New Year's Day","AM",2026 +"2026-01-02","New Year's Day","AM",2026 +"2026-01-06","Christmas and Epiphany Day","AM",2026 +"2026-01-28","Army Day","AM",2026 +"2026-03-08","Womens Day","AM",2026 +"2026-04-24","Genocide Memorial Day","AM",2026 +"2026-05-01","Labor day","AM",2026 +"2026-05-09","Victory and Peace Day","AM",2026 +"2026-05-28","Republic Day","AM",2026 +"2026-07-05","Constitution Day","AM",2026 +"2026-09-21","Independence Day","AM",2026 +"2026-12-31","New Year's Eve","AM",2026 +"2027-01-01","New Year's Day","AM",2027 +"2027-01-02","New Year's Day","AM",2027 +"2027-01-06","Christmas and Epiphany Day","AM",2027 +"2027-01-28","Army Day","AM",2027 +"2027-03-08","Womens Day","AM",2027 +"2027-04-24","Genocide Memorial Day","AM",2027 +"2027-05-01","Labor day","AM",2027 +"2027-05-09","Victory and Peace Day","AM",2027 +"2027-05-28","Republic Day","AM",2027 +"2027-07-05","Constitution Day","AM",2027 +"2027-09-21","Independence Day","AM",2027 +"2027-12-31","New Year's Eve","AM",2027 +"2028-01-01","New Year's Day","AM",2028 +"2028-01-02","New Year's Day","AM",2028 +"2028-01-06","Christmas and Epiphany Day","AM",2028 +"2028-01-28","Army Day","AM",2028 +"2028-03-08","Womens Day","AM",2028 +"2028-04-24","Genocide Memorial Day","AM",2028 +"2028-05-01","Labor day","AM",2028 +"2028-05-09","Victory and Peace Day","AM",2028 +"2028-05-28","Republic Day","AM",2028 +"2028-07-05","Constitution Day","AM",2028 +"2028-09-21","Independence Day","AM",2028 +"2028-12-31","New Year's Eve","AM",2028 +"2029-01-01","New Year's Day","AM",2029 +"2029-01-02","New Year's Day","AM",2029 +"2029-01-06","Christmas and Epiphany Day","AM",2029 +"2029-01-28","Army Day","AM",2029 +"2029-03-08","Womens Day","AM",2029 +"2029-04-24","Genocide Memorial Day","AM",2029 +"2029-05-01","Labor day","AM",2029 +"2029-05-09","Victory and Peace Day","AM",2029 +"2029-05-28","Republic Day","AM",2029 +"2029-07-05","Constitution Day","AM",2029 +"2029-09-21","Independence Day","AM",2029 +"2029-12-31","New Year's Eve","AM",2029 +"2030-01-01","New Year's Day","AM",2030 +"2030-01-02","New Year's Day","AM",2030 +"2030-01-06","Christmas and Epiphany Day","AM",2030 +"2030-01-28","Army Day","AM",2030 +"2030-03-08","Womens Day","AM",2030 +"2030-04-24","Genocide Memorial Day","AM",2030 +"2030-05-01","Labor day","AM",2030 +"2030-05-09","Victory and Peace Day","AM",2030 +"2030-05-28","Republic Day","AM",2030 +"2030-07-05","Constitution Day","AM",2030 +"2030-09-21","Independence Day","AM",2030 +"2030-12-31","New Year's Eve","AM",2030 +"2031-01-01","New Year's Day","AM",2031 +"2031-01-02","New Year's Day","AM",2031 +"2031-01-06","Christmas and Epiphany Day","AM",2031 +"2031-01-28","Army Day","AM",2031 +"2031-03-08","Womens Day","AM",2031 +"2031-04-24","Genocide Memorial Day","AM",2031 +"2031-05-01","Labor day","AM",2031 +"2031-05-09","Victory and Peace Day","AM",2031 +"2031-05-28","Republic Day","AM",2031 +"2031-07-05","Constitution Day","AM",2031 +"2031-09-21","Independence Day","AM",2031 +"2031-12-31","New Year's Eve","AM",2031 +"2032-01-01","New Year's Day","AM",2032 +"2032-01-02","New Year's Day","AM",2032 +"2032-01-06","Christmas and Epiphany Day","AM",2032 +"2032-01-28","Army Day","AM",2032 +"2032-03-08","Womens Day","AM",2032 +"2032-04-24","Genocide Memorial Day","AM",2032 +"2032-05-01","Labor day","AM",2032 +"2032-05-09","Victory and Peace Day","AM",2032 +"2032-05-28","Republic Day","AM",2032 +"2032-07-05","Constitution Day","AM",2032 +"2032-09-21","Independence Day","AM",2032 +"2032-12-31","New Year's Eve","AM",2032 +"2033-01-01","New Year's Day","AM",2033 +"2033-01-02","New Year's Day","AM",2033 +"2033-01-06","Christmas and Epiphany Day","AM",2033 +"2033-01-28","Army Day","AM",2033 +"2033-03-08","Womens Day","AM",2033 +"2033-04-24","Genocide Memorial Day","AM",2033 +"2033-05-01","Labor day","AM",2033 +"2033-05-09","Victory and Peace Day","AM",2033 +"2033-05-28","Republic Day","AM",2033 +"2033-07-05","Constitution Day","AM",2033 +"2033-09-21","Independence Day","AM",2033 +"2033-12-31","New Year's Eve","AM",2033 +"2034-01-01","New Year's Day","AM",2034 +"2034-01-02","New Year's Day","AM",2034 +"2034-01-06","Christmas and Epiphany Day","AM",2034 +"2034-01-28","Army Day","AM",2034 +"2034-03-08","Womens Day","AM",2034 +"2034-04-24","Genocide Memorial Day","AM",2034 +"2034-05-01","Labor day","AM",2034 +"2034-05-09","Victory and Peace Day","AM",2034 +"2034-05-28","Republic Day","AM",2034 +"2034-07-05","Constitution Day","AM",2034 +"2034-09-21","Independence Day","AM",2034 +"2034-12-31","New Year's Eve","AM",2034 +"2035-01-01","New Year's Day","AM",2035 +"2035-01-02","New Year's Day","AM",2035 +"2035-01-06","Christmas and Epiphany Day","AM",2035 +"2035-01-28","Army Day","AM",2035 +"2035-03-08","Womens Day","AM",2035 +"2035-04-24","Genocide Memorial Day","AM",2035 +"2035-05-01","Labor day","AM",2035 +"2035-05-09","Victory and Peace Day","AM",2035 +"2035-05-28","Republic Day","AM",2035 +"2035-07-05","Constitution Day","AM",2035 +"2035-09-21","Independence Day","AM",2035 +"2035-12-31","New Year's Eve","AM",2035 +"2036-01-01","New Year's Day","AM",2036 +"2036-01-02","New Year's Day","AM",2036 +"2036-01-06","Christmas and Epiphany Day","AM",2036 +"2036-01-28","Army Day","AM",2036 +"2036-03-08","Womens Day","AM",2036 +"2036-04-24","Genocide Memorial Day","AM",2036 +"2036-05-01","Labor day","AM",2036 +"2036-05-09","Victory and Peace Day","AM",2036 +"2036-05-28","Republic Day","AM",2036 +"2036-07-05","Constitution Day","AM",2036 +"2036-09-21","Independence Day","AM",2036 +"2036-12-31","New Year's Eve","AM",2036 +"2037-01-01","New Year's Day","AM",2037 +"2037-01-02","New Year's Day","AM",2037 +"2037-01-06","Christmas and Epiphany Day","AM",2037 +"2037-01-28","Army Day","AM",2037 +"2037-03-08","Womens Day","AM",2037 +"2037-04-24","Genocide Memorial Day","AM",2037 +"2037-05-01","Labor day","AM",2037 +"2037-05-09","Victory and Peace Day","AM",2037 +"2037-05-28","Republic Day","AM",2037 +"2037-07-05","Constitution Day","AM",2037 +"2037-09-21","Independence Day","AM",2037 +"2037-12-31","New Year's Eve","AM",2037 +"2038-01-01","New Year's Day","AM",2038 +"2038-01-02","New Year's Day","AM",2038 +"2038-01-06","Christmas and Epiphany Day","AM",2038 +"2038-01-28","Army Day","AM",2038 +"2038-03-08","Womens Day","AM",2038 +"2038-04-24","Genocide Memorial Day","AM",2038 +"2038-05-01","Labor day","AM",2038 +"2038-05-09","Victory and Peace Day","AM",2038 +"2038-05-28","Republic Day","AM",2038 +"2038-07-05","Constitution Day","AM",2038 +"2038-09-21","Independence Day","AM",2038 +"2038-12-31","New Year's Eve","AM",2038 +"2039-01-01","New Year's Day","AM",2039 +"2039-01-02","New Year's Day","AM",2039 +"2039-01-06","Christmas and Epiphany Day","AM",2039 +"2039-01-28","Army Day","AM",2039 +"2039-03-08","Womens Day","AM",2039 +"2039-04-24","Genocide Memorial Day","AM",2039 +"2039-05-01","Labor day","AM",2039 +"2039-05-09","Victory and Peace Day","AM",2039 +"2039-05-28","Republic Day","AM",2039 +"2039-07-05","Constitution Day","AM",2039 +"2039-09-21","Independence Day","AM",2039 +"2039-12-31","New Year's Eve","AM",2039 +"2040-01-01","New Year's Day","AM",2040 +"2040-01-02","New Year's Day","AM",2040 +"2040-01-06","Christmas and Epiphany Day","AM",2040 +"2040-01-28","Army Day","AM",2040 +"2040-03-08","Womens Day","AM",2040 +"2040-04-24","Genocide Memorial Day","AM",2040 +"2040-05-01","Labor day","AM",2040 +"2040-05-09","Victory and Peace Day","AM",2040 +"2040-05-28","Republic Day","AM",2040 +"2040-07-05","Constitution Day","AM",2040 +"2040-09-21","Independence Day","AM",2040 +"2040-12-31","New Year's Eve","AM",2040 +"2041-01-01","New Year's Day","AM",2041 +"2041-01-02","New Year's Day","AM",2041 +"2041-01-06","Christmas and Epiphany Day","AM",2041 +"2041-01-28","Army Day","AM",2041 +"2041-03-08","Womens Day","AM",2041 +"2041-04-24","Genocide Memorial Day","AM",2041 +"2041-05-01","Labor day","AM",2041 +"2041-05-09","Victory and Peace Day","AM",2041 +"2041-05-28","Republic Day","AM",2041 +"2041-07-05","Constitution Day","AM",2041 +"2041-09-21","Independence Day","AM",2041 +"2041-12-31","New Year's Eve","AM",2041 +"2042-01-01","New Year's Day","AM",2042 +"2042-01-02","New Year's Day","AM",2042 +"2042-01-06","Christmas and Epiphany Day","AM",2042 +"2042-01-28","Army Day","AM",2042 +"2042-03-08","Womens Day","AM",2042 +"2042-04-24","Genocide Memorial Day","AM",2042 +"2042-05-01","Labor day","AM",2042 +"2042-05-09","Victory and Peace Day","AM",2042 +"2042-05-28","Republic Day","AM",2042 +"2042-07-05","Constitution Day","AM",2042 +"2042-09-21","Independence Day","AM",2042 +"2042-12-31","New Year's Eve","AM",2042 +"2043-01-01","New Year's Day","AM",2043 +"2043-01-02","New Year's Day","AM",2043 +"2043-01-06","Christmas and Epiphany Day","AM",2043 +"2043-01-28","Army Day","AM",2043 +"2043-03-08","Womens Day","AM",2043 +"2043-04-24","Genocide Memorial Day","AM",2043 +"2043-05-01","Labor day","AM",2043 +"2043-05-09","Victory and Peace Day","AM",2043 +"2043-05-28","Republic Day","AM",2043 +"2043-07-05","Constitution Day","AM",2043 +"2043-09-21","Independence Day","AM",2043 +"2043-12-31","New Year's Eve","AM",2043 +"2044-01-01","New Year's Day","AM",2044 +"2044-01-02","New Year's Day","AM",2044 +"2044-01-06","Christmas and Epiphany Day","AM",2044 +"2044-01-28","Army Day","AM",2044 +"2044-03-08","Womens Day","AM",2044 +"2044-04-24","Genocide Memorial Day","AM",2044 +"2044-05-01","Labor day","AM",2044 +"2044-05-09","Victory and Peace Day","AM",2044 +"2044-05-28","Republic Day","AM",2044 +"2044-07-05","Constitution Day","AM",2044 +"2044-09-21","Independence Day","AM",2044 +"2044-12-31","New Year's Eve","AM",2044 +"1995-01-01","Ano novo","AO",1995 +"1995-01-02","Ano novo (Observed)","AO",1995 +"1995-02-04","Dia do Inicio da Luta Armada","AO",1995 +"1995-02-28","Carnaval","AO",1995 +"1995-03-08","Dia Internacional da Mulher","AO",1995 +"1995-04-04","Dia da Paz e Reconciliacao","AO",1995 +"1995-04-14","Sexta-feira Santa","AO",1995 +"1995-05-01","Dia Mundial do Trabalho","AO",1995 +"1995-09-17","Dia do Heroi Nacional","AO",1995 +"1995-09-18","Dia do Heroi Nacional (Observed)","AO",1995 +"1995-11-02","Dia dos Finados","AO",1995 +"1995-11-11","Dia da Independencia","AO",1995 +"1995-12-25","Dia de Natal e da Familia","AO",1995 +"1996-01-01","Ano novo","AO",1996 +"1996-02-04","Dia do Inicio da Luta Armada","AO",1996 +"1996-02-05","Dia do Inicio da Luta Armada (Observed)","AO",1996 +"1996-02-20","Carnaval","AO",1996 +"1996-03-08","Dia Internacional da Mulher","AO",1996 +"1996-04-04","Dia da Paz e Reconciliacao","AO",1996 +"1996-04-05","Sexta-feira Santa","AO",1996 +"1996-05-01","Dia Mundial do Trabalho","AO",1996 +"1996-09-17","Dia do Heroi Nacional","AO",1996 +"1996-11-02","Dia dos Finados","AO",1996 +"1996-11-11","Dia da Independencia","AO",1996 +"1996-12-25","Dia de Natal e da Familia","AO",1996 +"1997-01-01","Ano novo","AO",1997 +"1997-02-04","Dia do Inicio da Luta Armada","AO",1997 +"1997-02-11","Carnaval","AO",1997 +"1997-03-08","Dia Internacional da Mulher","AO",1997 +"1997-03-28","Sexta-feira Santa","AO",1997 +"1997-04-04","Dia da Paz e Reconciliacao","AO",1997 +"1997-05-01","Dia Mundial do Trabalho","AO",1997 +"1997-09-17","Dia do Heroi Nacional","AO",1997 +"1997-11-02","Dia dos Finados","AO",1997 +"1997-11-03","Dia dos Finados (Observed)","AO",1997 +"1997-11-11","Dia da Independencia","AO",1997 +"1997-12-25","Dia de Natal e da Familia","AO",1997 +"1998-01-01","Ano novo","AO",1998 +"1998-02-04","Dia do Inicio da Luta Armada","AO",1998 +"1998-02-24","Carnaval","AO",1998 +"1998-03-08","Dia Internacional da Mulher","AO",1998 +"1998-03-09","Dia Internacional da Mulher (Observed)","AO",1998 +"1998-04-04","Dia da Paz e Reconciliacao","AO",1998 +"1998-04-10","Sexta-feira Santa","AO",1998 +"1998-05-01","Dia Mundial do Trabalho","AO",1998 +"1998-09-17","Dia do Heroi Nacional","AO",1998 +"1998-11-02","Dia dos Finados","AO",1998 +"1998-11-11","Dia da Independencia","AO",1998 +"1998-12-25","Dia de Natal e da Familia","AO",1998 +"1999-01-01","Ano novo","AO",1999 +"1999-02-04","Dia do Inicio da Luta Armada","AO",1999 +"1999-02-16","Carnaval","AO",1999 +"1999-03-08","Dia Internacional da Mulher","AO",1999 +"1999-04-02","Sexta-feira Santa","AO",1999 +"1999-04-04","Dia da Paz e Reconciliacao","AO",1999 +"1999-04-05","Dia da Paz e Reconciliacao (Observed)","AO",1999 +"1999-05-01","Dia Mundial do Trabalho","AO",1999 +"1999-09-17","Dia do Heroi Nacional","AO",1999 +"1999-11-02","Dia dos Finados","AO",1999 +"1999-11-11","Dia da Independencia","AO",1999 +"1999-12-25","Dia de Natal e da Familia","AO",1999 +"2000-01-01","Ano novo","AO",2000 +"2000-02-04","Dia do Inicio da Luta Armada","AO",2000 +"2000-03-07","Carnaval","AO",2000 +"2000-03-08","Dia Internacional da Mulher","AO",2000 +"2000-04-04","Dia da Paz e Reconciliacao","AO",2000 +"2000-04-21","Sexta-feira Santa","AO",2000 +"2000-05-01","Dia Mundial do Trabalho","AO",2000 +"2000-09-17","Dia do Heroi Nacional","AO",2000 +"2000-09-18","Dia do Heroi Nacional (Observed)","AO",2000 +"2000-11-02","Dia dos Finados","AO",2000 +"2000-11-11","Dia da Independencia","AO",2000 +"2000-12-25","Dia de Natal e da Familia","AO",2000 +"2001-01-01","Ano novo","AO",2001 +"2001-02-04","Dia do Inicio da Luta Armada","AO",2001 +"2001-02-05","Dia do Inicio da Luta Armada (Observed)","AO",2001 +"2001-02-27","Carnaval","AO",2001 +"2001-03-08","Dia Internacional da Mulher","AO",2001 +"2001-04-04","Dia da Paz e Reconciliacao","AO",2001 +"2001-04-13","Sexta-feira Santa","AO",2001 +"2001-05-01","Dia Mundial do Trabalho","AO",2001 +"2001-09-17","Dia do Heroi Nacional","AO",2001 +"2001-11-02","Dia dos Finados","AO",2001 +"2001-11-11","Dia da Independencia","AO",2001 +"2001-11-12","Dia da Independencia (Observed)","AO",2001 +"2001-12-25","Dia de Natal e da Familia","AO",2001 +"2002-01-01","Ano novo","AO",2002 +"2002-02-04","Dia do Inicio da Luta Armada","AO",2002 +"2002-02-12","Carnaval","AO",2002 +"2002-03-08","Dia Internacional da Mulher","AO",2002 +"2002-03-29","Sexta-feira Santa","AO",2002 +"2002-04-04","Dia da Paz e Reconciliacao","AO",2002 +"2002-05-01","Dia Mundial do Trabalho","AO",2002 +"2002-09-17","Dia do Heroi Nacional","AO",2002 +"2002-11-02","Dia dos Finados","AO",2002 +"2002-11-11","Dia da Independencia","AO",2002 +"2002-12-25","Dia de Natal e da Familia","AO",2002 +"2003-01-01","Ano novo","AO",2003 +"2003-02-04","Dia do Inicio da Luta Armada","AO",2003 +"2003-03-04","Carnaval","AO",2003 +"2003-03-08","Dia Internacional da Mulher","AO",2003 +"2003-04-04","Dia da Paz e Reconciliacao","AO",2003 +"2003-04-18","Sexta-feira Santa","AO",2003 +"2003-05-01","Dia Mundial do Trabalho","AO",2003 +"2003-09-17","Dia do Heroi Nacional","AO",2003 +"2003-11-02","Dia dos Finados","AO",2003 +"2003-11-03","Dia dos Finados (Observed)","AO",2003 +"2003-11-11","Dia da Independencia","AO",2003 +"2003-12-25","Dia de Natal e da Familia","AO",2003 +"2004-01-01","Ano novo","AO",2004 +"2004-02-04","Dia do Inicio da Luta Armada","AO",2004 +"2004-02-24","Carnaval","AO",2004 +"2004-03-08","Dia Internacional da Mulher","AO",2004 +"2004-04-04","Dia da Paz e Reconciliacao","AO",2004 +"2004-04-05","Dia da Paz e Reconciliacao (Observed)","AO",2004 +"2004-04-09","Sexta-feira Santa","AO",2004 +"2004-05-01","Dia Mundial do Trabalho","AO",2004 +"2004-09-17","Dia do Heroi Nacional","AO",2004 +"2004-11-02","Dia dos Finados","AO",2004 +"2004-11-11","Dia da Independencia","AO",2004 +"2004-12-25","Dia de Natal e da Familia","AO",2004 +"2005-01-01","Ano novo","AO",2005 +"2005-02-04","Dia do Inicio da Luta Armada","AO",2005 +"2005-02-08","Carnaval","AO",2005 +"2005-03-08","Dia Internacional da Mulher","AO",2005 +"2005-03-25","Sexta-feira Santa","AO",2005 +"2005-04-04","Dia da Paz e Reconciliacao","AO",2005 +"2005-05-01","Dia Mundial do Trabalho","AO",2005 +"2005-05-02","Dia Mundial do Trabalho (Observed)","AO",2005 +"2005-09-17","Dia do Heroi Nacional","AO",2005 +"2005-11-02","Dia dos Finados","AO",2005 +"2005-11-11","Dia da Independencia","AO",2005 +"2005-12-25","Dia de Natal e da Familia","AO",2005 +"2005-12-26","Dia de Natal e da Familia (Observed)","AO",2005 +"2006-01-01","Ano novo","AO",2006 +"2006-01-02","Ano novo (Observed)","AO",2006 +"2006-02-04","Dia do Inicio da Luta Armada","AO",2006 +"2006-02-28","Carnaval","AO",2006 +"2006-03-08","Dia Internacional da Mulher","AO",2006 +"2006-04-04","Dia da Paz e Reconciliacao","AO",2006 +"2006-04-14","Sexta-feira Santa","AO",2006 +"2006-05-01","Dia Mundial do Trabalho","AO",2006 +"2006-09-17","Dia do Heroi Nacional","AO",2006 +"2006-09-18","Dia do Heroi Nacional (Observed)","AO",2006 +"2006-11-02","Dia dos Finados","AO",2006 +"2006-11-11","Dia da Independencia","AO",2006 +"2006-12-25","Dia de Natal e da Familia","AO",2006 +"2007-01-01","Ano novo","AO",2007 +"2007-02-04","Dia do Inicio da Luta Armada","AO",2007 +"2007-02-05","Dia do Inicio da Luta Armada (Observed)","AO",2007 +"2007-02-20","Carnaval","AO",2007 +"2007-03-08","Dia Internacional da Mulher","AO",2007 +"2007-04-04","Dia da Paz e Reconciliacao","AO",2007 +"2007-04-06","Sexta-feira Santa","AO",2007 +"2007-05-01","Dia Mundial do Trabalho","AO",2007 +"2007-09-17","Dia do Heroi Nacional","AO",2007 +"2007-11-02","Dia dos Finados","AO",2007 +"2007-11-11","Dia da Independencia","AO",2007 +"2007-11-12","Dia da Independencia (Observed)","AO",2007 +"2007-12-25","Dia de Natal e da Familia","AO",2007 +"2008-01-01","Ano novo","AO",2008 +"2008-02-04","Dia do Inicio da Luta Armada","AO",2008 +"2008-02-05","Carnaval","AO",2008 +"2008-03-08","Dia Internacional da Mulher","AO",2008 +"2008-03-21","Sexta-feira Santa","AO",2008 +"2008-04-04","Dia da Paz e Reconciliacao","AO",2008 +"2008-05-01","Dia Mundial do Trabalho","AO",2008 +"2008-09-17","Dia do Heroi Nacional","AO",2008 +"2008-11-02","Dia dos Finados","AO",2008 +"2008-11-03","Dia dos Finados (Observed)","AO",2008 +"2008-11-11","Dia da Independencia","AO",2008 +"2008-12-25","Dia de Natal e da Familia","AO",2008 +"2009-01-01","Ano novo","AO",2009 +"2009-02-04","Dia do Inicio da Luta Armada","AO",2009 +"2009-02-24","Carnaval","AO",2009 +"2009-03-08","Dia Internacional da Mulher","AO",2009 +"2009-03-09","Dia Internacional da Mulher (Observed)","AO",2009 +"2009-04-04","Dia da Paz e Reconciliacao","AO",2009 +"2009-04-10","Sexta-feira Santa","AO",2009 +"2009-05-01","Dia Mundial do Trabalho","AO",2009 +"2009-09-17","Dia do Heroi Nacional","AO",2009 +"2009-11-02","Dia dos Finados","AO",2009 +"2009-11-11","Dia da Independencia","AO",2009 +"2009-12-25","Dia de Natal e da Familia","AO",2009 +"2010-01-01","Ano novo","AO",2010 +"2010-02-04","Dia do Inicio da Luta Armada","AO",2010 +"2010-02-16","Carnaval","AO",2010 +"2010-03-08","Dia Internacional da Mulher","AO",2010 +"2010-04-02","Sexta-feira Santa","AO",2010 +"2010-04-04","Dia da Paz e Reconciliacao","AO",2010 +"2010-04-05","Dia da Paz e Reconciliacao (Observed)","AO",2010 +"2010-05-01","Dia Mundial do Trabalho","AO",2010 +"2010-09-17","Dia do Heroi Nacional","AO",2010 +"2010-11-02","Dia dos Finados","AO",2010 +"2010-11-11","Dia da Independencia","AO",2010 +"2010-12-25","Dia de Natal e da Familia","AO",2010 +"2011-01-01","Ano novo","AO",2011 +"2011-02-04","Dia do Inicio da Luta Armada","AO",2011 +"2011-03-08","Carnaval","AO",2011 +"2011-03-08","Dia Internacional da Mulher","AO",2011 +"2011-04-04","Dia da Paz e Reconciliacao","AO",2011 +"2011-04-22","Sexta-feira Santa","AO",2011 +"2011-05-01","Dia Mundial do Trabalho","AO",2011 +"2011-05-02","Dia Mundial do Trabalho (Observed)","AO",2011 +"2011-09-17","Dia do Heroi Nacional","AO",2011 +"2011-11-02","Dia dos Finados","AO",2011 +"2011-11-11","Dia da Independencia","AO",2011 +"2011-12-25","Dia de Natal e da Familia","AO",2011 +"2011-12-26","Dia de Natal e da Familia (Observed)","AO",2011 +"2012-01-01","Ano novo","AO",2012 +"2012-01-02","Ano novo (Observed)","AO",2012 +"2012-02-04","Dia do Inicio da Luta Armada","AO",2012 +"2012-02-21","Carnaval","AO",2012 +"2012-03-08","Dia Internacional da Mulher","AO",2012 +"2012-04-04","Dia da Paz e Reconciliacao","AO",2012 +"2012-04-06","Sexta-feira Santa","AO",2012 +"2012-05-01","Dia Mundial do Trabalho","AO",2012 +"2012-09-17","Dia do Heroi Nacional","AO",2012 +"2012-11-02","Dia dos Finados","AO",2012 +"2012-11-11","Dia da Independencia","AO",2012 +"2012-11-12","Dia da Independencia (Observed)","AO",2012 +"2012-12-25","Dia de Natal e da Familia","AO",2012 +"2013-01-01","Ano novo","AO",2013 +"2013-02-04","Dia do Inicio da Luta Armada","AO",2013 +"2013-02-12","Carnaval","AO",2013 +"2013-03-08","Dia Internacional da Mulher","AO",2013 +"2013-03-29","Sexta-feira Santa","AO",2013 +"2013-04-04","Dia da Paz e Reconciliacao","AO",2013 +"2013-05-01","Dia Mundial do Trabalho","AO",2013 +"2013-09-17","Dia do Heroi Nacional","AO",2013 +"2013-11-02","Dia dos Finados","AO",2013 +"2013-11-11","Dia da Independencia","AO",2013 +"2013-12-25","Dia de Natal e da Familia","AO",2013 +"2014-01-01","Ano novo","AO",2014 +"2014-02-04","Dia do Inicio da Luta Armada","AO",2014 +"2014-03-04","Carnaval","AO",2014 +"2014-03-08","Dia Internacional da Mulher","AO",2014 +"2014-04-04","Dia da Paz e Reconciliacao","AO",2014 +"2014-04-18","Sexta-feira Santa","AO",2014 +"2014-05-01","Dia Mundial do Trabalho","AO",2014 +"2014-09-17","Dia do Heroi Nacional","AO",2014 +"2014-11-02","Dia dos Finados","AO",2014 +"2014-11-03","Dia dos Finados (Observed)","AO",2014 +"2014-11-11","Dia da Independencia","AO",2014 +"2014-12-25","Dia de Natal e da Familia","AO",2014 +"2015-01-01","Ano novo","AO",2015 +"2015-02-04","Dia do Inicio da Luta Armada","AO",2015 +"2015-02-17","Carnaval","AO",2015 +"2015-03-08","Dia Internacional da Mulher","AO",2015 +"2015-03-09","Dia Internacional da Mulher (Observed)","AO",2015 +"2015-04-03","Sexta-feira Santa","AO",2015 +"2015-04-04","Dia da Paz e Reconciliacao","AO",2015 +"2015-05-01","Dia Mundial do Trabalho","AO",2015 +"2015-09-17","Dia do Heroi Nacional","AO",2015 +"2015-11-02","Dia dos Finados","AO",2015 +"2015-11-11","Dia da Independencia","AO",2015 +"2015-12-25","Dia de Natal e da Familia","AO",2015 +"2016-01-01","Ano novo","AO",2016 +"2016-02-04","Dia do Inicio da Luta Armada","AO",2016 +"2016-02-09","Carnaval","AO",2016 +"2016-03-08","Dia Internacional da Mulher","AO",2016 +"2016-03-25","Sexta-feira Santa","AO",2016 +"2016-04-04","Dia da Paz e Reconciliacao","AO",2016 +"2016-05-01","Dia Mundial do Trabalho","AO",2016 +"2016-05-02","Dia Mundial do Trabalho (Observed)","AO",2016 +"2016-09-17","Dia do Heroi Nacional","AO",2016 +"2016-11-02","Dia dos Finados","AO",2016 +"2016-11-11","Dia da Independencia","AO",2016 +"2016-12-25","Dia de Natal e da Familia","AO",2016 +"2016-12-26","Dia de Natal e da Familia (Observed)","AO",2016 +"2017-01-01","Ano novo","AO",2017 +"2017-01-02","Ano novo (Observed)","AO",2017 +"2017-02-04","Dia do Inicio da Luta Armada","AO",2017 +"2017-02-28","Carnaval","AO",2017 +"2017-03-08","Dia Internacional da Mulher","AO",2017 +"2017-04-04","Dia da Paz e Reconciliacao","AO",2017 +"2017-04-14","Sexta-feira Santa","AO",2017 +"2017-05-01","Dia Mundial do Trabalho","AO",2017 +"2017-09-17","Dia do Heroi Nacional","AO",2017 +"2017-09-18","Dia do Heroi Nacional (Observed)","AO",2017 +"2017-11-02","Dia dos Finados","AO",2017 +"2017-11-11","Dia da Independencia","AO",2017 +"2017-12-25","Dia de Natal e da Familia","AO",2017 +"2018-01-01","Ano novo","AO",2018 +"2018-02-04","Dia do Inicio da Luta Armada","AO",2018 +"2018-02-12","Carnaval (Day off)","AO",2018 +"2018-02-13","Carnaval","AO",2018 +"2018-03-08","Dia Internacional da Mulher","AO",2018 +"2018-03-09","Dia Internacional da Mulher (Day off)","AO",2018 +"2018-03-30","Sexta-feira Santa","AO",2018 +"2018-04-04","Dia da Paz e Reconciliacao","AO",2018 +"2018-04-30","Dia Mundial do Trabalho (Day off)","AO",2018 +"2018-05-01","Dia Mundial do Trabalho","AO",2018 +"2018-09-17","Dia do Heroi Nacional","AO",2018 +"2018-11-02","Dia dos Finados","AO",2018 +"2018-11-11","Dia da Independencia","AO",2018 +"2018-12-24","Dia de Natal e da Familia (Day off)","AO",2018 +"2018-12-25","Dia de Natal e da Familia","AO",2018 +"2018-12-31","Ano novo (Day off)","AO",2018 +"2019-01-01","Ano novo","AO",2019 +"2019-02-04","Dia do Inicio da Luta Armada","AO",2019 +"2019-03-04","Carnaval (Day off)","AO",2019 +"2019-03-05","Carnaval","AO",2019 +"2019-03-08","Dia Internacional da Mulher","AO",2019 +"2019-03-23","Dia da Libertacao da Africa Austral","AO",2019 +"2019-04-04","Dia da Paz e Reconciliacao","AO",2019 +"2019-04-05","Dia da Paz e Reconciliacao (Day off)","AO",2019 +"2019-04-19","Sexta-feira Santa","AO",2019 +"2019-05-01","Dia Mundial do Trabalho","AO",2019 +"2019-09-16","Dia do Heroi Nacional (Day off)","AO",2019 +"2019-09-17","Dia do Heroi Nacional","AO",2019 +"2019-11-02","Dia dos Finados","AO",2019 +"2019-11-11","Dia da Independencia","AO",2019 +"2019-12-25","Dia de Natal e da Familia","AO",2019 +"2020-01-01","Ano novo","AO",2020 +"2020-02-03","Dia do Inicio da Luta Armada (Day off)","AO",2020 +"2020-02-04","Dia do Inicio da Luta Armada","AO",2020 +"2020-02-24","Carnaval (Day off)","AO",2020 +"2020-02-25","Carnaval","AO",2020 +"2020-03-08","Dia Internacional da Mulher","AO",2020 +"2020-03-23","Dia da Libertacao da Africa Austral","AO",2020 +"2020-04-04","Dia da Paz e Reconciliacao","AO",2020 +"2020-04-10","Sexta-feira Santa","AO",2020 +"2020-05-01","Dia Mundial do Trabalho","AO",2020 +"2020-09-17","Dia do Heroi Nacional","AO",2020 +"2020-09-18","Dia do Heroi Nacional (Day off)","AO",2020 +"2020-11-02","Dia dos Finados","AO",2020 +"2020-11-11","Dia da Independencia","AO",2020 +"2020-12-25","Dia de Natal e da Familia","AO",2020 +"2021-01-01","Ano novo","AO",2021 +"2021-02-04","Dia do Inicio da Luta Armada","AO",2021 +"2021-02-05","Dia do Inicio da Luta Armada (Day off)","AO",2021 +"2021-02-15","Carnaval (Day off)","AO",2021 +"2021-02-16","Carnaval","AO",2021 +"2021-03-08","Dia Internacional da Mulher","AO",2021 +"2021-03-22","Dia da Libertacao da Africa Austral (Day off)","AO",2021 +"2021-03-23","Dia da Libertacao da Africa Austral","AO",2021 +"2021-04-02","Sexta-feira Santa","AO",2021 +"2021-04-04","Dia da Paz e Reconciliacao","AO",2021 +"2021-05-01","Dia Mundial do Trabalho","AO",2021 +"2021-09-17","Dia do Heroi Nacional","AO",2021 +"2021-11-01","Dia dos Finados (Day off)","AO",2021 +"2021-11-02","Dia dos Finados","AO",2021 +"2021-11-11","Dia da Independencia","AO",2021 +"2021-11-12","Dia da Independencia (Day off)","AO",2021 +"2021-12-25","Dia de Natal e da Familia","AO",2021 +"2022-01-01","Ano novo","AO",2022 +"2022-02-04","Dia do Inicio da Luta Armada","AO",2022 +"2022-02-28","Carnaval (Day off)","AO",2022 +"2022-03-01","Carnaval","AO",2022 +"2022-03-07","Dia Internacional da Mulher (Day off)","AO",2022 +"2022-03-08","Dia Internacional da Mulher","AO",2022 +"2022-03-23","Dia da Libertacao da Africa Austral","AO",2022 +"2022-04-04","Dia da Paz e Reconciliacao","AO",2022 +"2022-04-15","Sexta-feira Santa","AO",2022 +"2022-05-01","Dia Mundial do Trabalho","AO",2022 +"2022-09-17","Dia do Heroi Nacional","AO",2022 +"2022-11-02","Dia dos Finados","AO",2022 +"2022-11-11","Dia da Independencia","AO",2022 +"2022-12-25","Dia de Natal e da Familia","AO",2022 +"2023-01-01","Ano novo","AO",2023 +"2023-02-04","Dia do Inicio da Luta Armada","AO",2023 +"2023-02-20","Carnaval (Day off)","AO",2023 +"2023-02-21","Carnaval","AO",2023 +"2023-03-08","Dia Internacional da Mulher","AO",2023 +"2023-03-23","Dia da Libertacao da Africa Austral","AO",2023 +"2023-03-24","Dia da Libertacao da Africa Austral (Day off)","AO",2023 +"2023-04-03","Dia da Paz e Reconciliacao (Day off)","AO",2023 +"2023-04-04","Dia da Paz e Reconciliacao","AO",2023 +"2023-04-07","Sexta-feira Santa","AO",2023 +"2023-05-01","Dia Mundial do Trabalho","AO",2023 +"2023-09-17","Dia do Heroi Nacional","AO",2023 +"2023-11-02","Dia dos Finados","AO",2023 +"2023-11-03","Dia dos Finados (Day off)","AO",2023 +"2023-11-11","Dia da Independencia","AO",2023 +"2023-12-25","Dia de Natal e da Familia","AO",2023 +"2024-01-01","Ano novo","AO",2024 +"2024-02-04","Dia do Inicio da Luta Armada","AO",2024 +"2024-02-12","Carnaval (Day off)","AO",2024 +"2024-02-13","Carnaval","AO",2024 +"2024-03-08","Dia Internacional da Mulher","AO",2024 +"2024-03-23","Dia da Libertacao da Africa Austral","AO",2024 +"2024-03-29","Sexta-feira Santa","AO",2024 +"2024-04-04","Dia da Paz e Reconciliacao","AO",2024 +"2024-04-05","Dia da Paz e Reconciliacao (Day off)","AO",2024 +"2024-05-01","Dia Mundial do Trabalho","AO",2024 +"2024-09-16","Dia do Heroi Nacional (Day off)","AO",2024 +"2024-09-17","Dia do Heroi Nacional","AO",2024 +"2024-11-02","Dia dos Finados","AO",2024 +"2024-11-11","Dia da Independencia","AO",2024 +"2024-12-25","Dia de Natal e da Familia","AO",2024 +"2025-01-01","Ano novo","AO",2025 +"2025-02-03","Dia do Inicio da Luta Armada (Day off)","AO",2025 +"2025-02-04","Dia do Inicio da Luta Armada","AO",2025 +"2025-03-03","Carnaval (Day off)","AO",2025 +"2025-03-04","Carnaval","AO",2025 +"2025-03-08","Dia Internacional da Mulher","AO",2025 +"2025-03-23","Dia da Libertacao da Africa Austral","AO",2025 +"2025-04-04","Dia da Paz e Reconciliacao","AO",2025 +"2025-04-18","Sexta-feira Santa","AO",2025 +"2025-05-01","Dia Mundial do Trabalho","AO",2025 +"2025-05-02","Dia Mundial do Trabalho (Day off)","AO",2025 +"2025-09-17","Dia do Heroi Nacional","AO",2025 +"2025-11-02","Dia dos Finados","AO",2025 +"2025-11-10","Dia da Independencia (Day off)","AO",2025 +"2025-11-11","Dia da Independencia","AO",2025 +"2025-12-25","Dia de Natal e da Familia","AO",2025 +"2025-12-26","Dia de Natal e da Familia (Day off)","AO",2025 +"2026-01-01","Ano novo","AO",2026 +"2026-01-02","Ano novo (Day off)","AO",2026 +"2026-02-04","Dia do Inicio da Luta Armada","AO",2026 +"2026-02-16","Carnaval (Day off)","AO",2026 +"2026-02-17","Carnaval","AO",2026 +"2026-03-08","Dia Internacional da Mulher","AO",2026 +"2026-03-23","Dia da Libertacao da Africa Austral","AO",2026 +"2026-04-03","Sexta-feira Santa","AO",2026 +"2026-04-04","Dia da Paz e Reconciliacao","AO",2026 +"2026-05-01","Dia Mundial do Trabalho","AO",2026 +"2026-09-17","Dia do Heroi Nacional","AO",2026 +"2026-09-18","Dia do Heroi Nacional (Day off)","AO",2026 +"2026-11-02","Dia dos Finados","AO",2026 +"2026-11-11","Dia da Independencia","AO",2026 +"2026-12-25","Dia de Natal e da Familia","AO",2026 +"2027-01-01","Ano novo","AO",2027 +"2027-02-04","Dia do Inicio da Luta Armada","AO",2027 +"2027-02-05","Dia do Inicio da Luta Armada (Day off)","AO",2027 +"2027-02-08","Carnaval (Day off)","AO",2027 +"2027-02-09","Carnaval","AO",2027 +"2027-03-08","Dia Internacional da Mulher","AO",2027 +"2027-03-22","Dia da Libertacao da Africa Austral (Day off)","AO",2027 +"2027-03-23","Dia da Libertacao da Africa Austral","AO",2027 +"2027-03-26","Sexta-feira Santa","AO",2027 +"2027-04-04","Dia da Paz e Reconciliacao","AO",2027 +"2027-05-01","Dia Mundial do Trabalho","AO",2027 +"2027-09-17","Dia do Heroi Nacional","AO",2027 +"2027-11-01","Dia dos Finados (Day off)","AO",2027 +"2027-11-02","Dia dos Finados","AO",2027 +"2027-11-11","Dia da Independencia","AO",2027 +"2027-11-12","Dia da Independencia (Day off)","AO",2027 +"2027-12-25","Dia de Natal e da Familia","AO",2027 +"2028-01-01","Ano novo","AO",2028 +"2028-02-04","Dia do Inicio da Luta Armada","AO",2028 +"2028-02-28","Carnaval (Day off)","AO",2028 +"2028-02-29","Carnaval","AO",2028 +"2028-03-08","Dia Internacional da Mulher","AO",2028 +"2028-03-23","Dia da Libertacao da Africa Austral","AO",2028 +"2028-03-24","Dia da Libertacao da Africa Austral (Day off)","AO",2028 +"2028-04-03","Dia da Paz e Reconciliacao (Day off)","AO",2028 +"2028-04-04","Dia da Paz e Reconciliacao","AO",2028 +"2028-04-14","Sexta-feira Santa","AO",2028 +"2028-05-01","Dia Mundial do Trabalho","AO",2028 +"2028-09-17","Dia do Heroi Nacional","AO",2028 +"2028-11-02","Dia dos Finados","AO",2028 +"2028-11-03","Dia dos Finados (Day off)","AO",2028 +"2028-11-11","Dia da Independencia","AO",2028 +"2028-12-25","Dia de Natal e da Familia","AO",2028 +"2029-01-01","Ano novo","AO",2029 +"2029-02-04","Dia do Inicio da Luta Armada","AO",2029 +"2029-02-12","Carnaval (Day off)","AO",2029 +"2029-02-13","Carnaval","AO",2029 +"2029-03-08","Dia Internacional da Mulher","AO",2029 +"2029-03-09","Dia Internacional da Mulher (Day off)","AO",2029 +"2029-03-23","Dia da Libertacao da Africa Austral","AO",2029 +"2029-03-30","Sexta-feira Santa","AO",2029 +"2029-04-04","Dia da Paz e Reconciliacao","AO",2029 +"2029-04-30","Dia Mundial do Trabalho (Day off)","AO",2029 +"2029-05-01","Dia Mundial do Trabalho","AO",2029 +"2029-09-17","Dia do Heroi Nacional","AO",2029 +"2029-11-02","Dia dos Finados","AO",2029 +"2029-11-11","Dia da Independencia","AO",2029 +"2029-12-24","Dia de Natal e da Familia (Day off)","AO",2029 +"2029-12-25","Dia de Natal e da Familia","AO",2029 +"2029-12-31","Ano novo (Day off)","AO",2029 +"2030-01-01","Ano novo","AO",2030 +"2030-02-04","Dia do Inicio da Luta Armada","AO",2030 +"2030-03-04","Carnaval (Day off)","AO",2030 +"2030-03-05","Carnaval","AO",2030 +"2030-03-08","Dia Internacional da Mulher","AO",2030 +"2030-03-23","Dia da Libertacao da Africa Austral","AO",2030 +"2030-04-04","Dia da Paz e Reconciliacao","AO",2030 +"2030-04-05","Dia da Paz e Reconciliacao (Day off)","AO",2030 +"2030-04-19","Sexta-feira Santa","AO",2030 +"2030-05-01","Dia Mundial do Trabalho","AO",2030 +"2030-09-16","Dia do Heroi Nacional (Day off)","AO",2030 +"2030-09-17","Dia do Heroi Nacional","AO",2030 +"2030-11-02","Dia dos Finados","AO",2030 +"2030-11-11","Dia da Independencia","AO",2030 +"2030-12-25","Dia de Natal e da Familia","AO",2030 +"2031-01-01","Ano novo","AO",2031 +"2031-02-03","Dia do Inicio da Luta Armada (Day off)","AO",2031 +"2031-02-04","Dia do Inicio da Luta Armada","AO",2031 +"2031-02-24","Carnaval (Day off)","AO",2031 +"2031-02-25","Carnaval","AO",2031 +"2031-03-08","Dia Internacional da Mulher","AO",2031 +"2031-03-23","Dia da Libertacao da Africa Austral","AO",2031 +"2031-04-04","Dia da Paz e Reconciliacao","AO",2031 +"2031-04-11","Sexta-feira Santa","AO",2031 +"2031-05-01","Dia Mundial do Trabalho","AO",2031 +"2031-05-02","Dia Mundial do Trabalho (Day off)","AO",2031 +"2031-09-17","Dia do Heroi Nacional","AO",2031 +"2031-11-02","Dia dos Finados","AO",2031 +"2031-11-10","Dia da Independencia (Day off)","AO",2031 +"2031-11-11","Dia da Independencia","AO",2031 +"2031-12-25","Dia de Natal e da Familia","AO",2031 +"2031-12-26","Dia de Natal e da Familia (Day off)","AO",2031 +"2032-01-01","Ano novo","AO",2032 +"2032-01-02","Ano novo (Day off)","AO",2032 +"2032-02-04","Dia do Inicio da Luta Armada","AO",2032 +"2032-02-09","Carnaval (Day off)","AO",2032 +"2032-02-10","Carnaval","AO",2032 +"2032-03-08","Dia Internacional da Mulher","AO",2032 +"2032-03-22","Dia da Libertacao da Africa Austral (Day off)","AO",2032 +"2032-03-23","Dia da Libertacao da Africa Austral","AO",2032 +"2032-03-26","Sexta-feira Santa","AO",2032 +"2032-04-04","Dia da Paz e Reconciliacao","AO",2032 +"2032-05-01","Dia Mundial do Trabalho","AO",2032 +"2032-09-17","Dia do Heroi Nacional","AO",2032 +"2032-11-01","Dia dos Finados (Day off)","AO",2032 +"2032-11-02","Dia dos Finados","AO",2032 +"2032-11-11","Dia da Independencia","AO",2032 +"2032-11-12","Dia da Independencia (Day off)","AO",2032 +"2032-12-25","Dia de Natal e da Familia","AO",2032 +"2033-01-01","Ano novo","AO",2033 +"2033-02-04","Dia do Inicio da Luta Armada","AO",2033 +"2033-02-28","Carnaval (Day off)","AO",2033 +"2033-03-01","Carnaval","AO",2033 +"2033-03-07","Dia Internacional da Mulher (Day off)","AO",2033 +"2033-03-08","Dia Internacional da Mulher","AO",2033 +"2033-03-23","Dia da Libertacao da Africa Austral","AO",2033 +"2033-04-04","Dia da Paz e Reconciliacao","AO",2033 +"2033-04-15","Sexta-feira Santa","AO",2033 +"2033-05-01","Dia Mundial do Trabalho","AO",2033 +"2033-09-17","Dia do Heroi Nacional","AO",2033 +"2033-11-02","Dia dos Finados","AO",2033 +"2033-11-11","Dia da Independencia","AO",2033 +"2033-12-25","Dia de Natal e da Familia","AO",2033 +"2034-01-01","Ano novo","AO",2034 +"2034-02-04","Dia do Inicio da Luta Armada","AO",2034 +"2034-02-20","Carnaval (Day off)","AO",2034 +"2034-02-21","Carnaval","AO",2034 +"2034-03-08","Dia Internacional da Mulher","AO",2034 +"2034-03-23","Dia da Libertacao da Africa Austral","AO",2034 +"2034-03-24","Dia da Libertacao da Africa Austral (Day off)","AO",2034 +"2034-04-03","Dia da Paz e Reconciliacao (Day off)","AO",2034 +"2034-04-04","Dia da Paz e Reconciliacao","AO",2034 +"2034-04-07","Sexta-feira Santa","AO",2034 +"2034-05-01","Dia Mundial do Trabalho","AO",2034 +"2034-09-17","Dia do Heroi Nacional","AO",2034 +"2034-11-02","Dia dos Finados","AO",2034 +"2034-11-03","Dia dos Finados (Day off)","AO",2034 +"2034-11-11","Dia da Independencia","AO",2034 +"2034-12-25","Dia de Natal e da Familia","AO",2034 +"2035-01-01","Ano novo","AO",2035 +"2035-02-04","Dia do Inicio da Luta Armada","AO",2035 +"2035-02-05","Carnaval (Day off)","AO",2035 +"2035-02-06","Carnaval","AO",2035 +"2035-03-08","Dia Internacional da Mulher","AO",2035 +"2035-03-09","Dia Internacional da Mulher (Day off)","AO",2035 +"2035-03-23","Dia da Libertacao da Africa Austral","AO",2035 +"2035-03-23","Sexta-feira Santa","AO",2035 +"2035-04-04","Dia da Paz e Reconciliacao","AO",2035 +"2035-04-30","Dia Mundial do Trabalho (Day off)","AO",2035 +"2035-05-01","Dia Mundial do Trabalho","AO",2035 +"2035-09-17","Dia do Heroi Nacional","AO",2035 +"2035-11-02","Dia dos Finados","AO",2035 +"2035-11-11","Dia da Independencia","AO",2035 +"2035-12-24","Dia de Natal e da Familia (Day off)","AO",2035 +"2035-12-25","Dia de Natal e da Familia","AO",2035 +"2035-12-31","Ano novo (Day off)","AO",2035 +"2036-01-01","Ano novo","AO",2036 +"2036-02-04","Dia do Inicio da Luta Armada","AO",2036 +"2036-02-25","Carnaval (Day off)","AO",2036 +"2036-02-26","Carnaval","AO",2036 +"2036-03-08","Dia Internacional da Mulher","AO",2036 +"2036-03-23","Dia da Libertacao da Africa Austral","AO",2036 +"2036-04-04","Dia da Paz e Reconciliacao","AO",2036 +"2036-04-11","Sexta-feira Santa","AO",2036 +"2036-05-01","Dia Mundial do Trabalho","AO",2036 +"2036-05-02","Dia Mundial do Trabalho (Day off)","AO",2036 +"2036-09-17","Dia do Heroi Nacional","AO",2036 +"2036-11-02","Dia dos Finados","AO",2036 +"2036-11-10","Dia da Independencia (Day off)","AO",2036 +"2036-11-11","Dia da Independencia","AO",2036 +"2036-12-25","Dia de Natal e da Familia","AO",2036 +"2036-12-26","Dia de Natal e da Familia (Day off)","AO",2036 +"2037-01-01","Ano novo","AO",2037 +"2037-01-02","Ano novo (Day off)","AO",2037 +"2037-02-04","Dia do Inicio da Luta Armada","AO",2037 +"2037-02-16","Carnaval (Day off)","AO",2037 +"2037-02-17","Carnaval","AO",2037 +"2037-03-08","Dia Internacional da Mulher","AO",2037 +"2037-03-23","Dia da Libertacao da Africa Austral","AO",2037 +"2037-04-03","Sexta-feira Santa","AO",2037 +"2037-04-04","Dia da Paz e Reconciliacao","AO",2037 +"2037-05-01","Dia Mundial do Trabalho","AO",2037 +"2037-09-17","Dia do Heroi Nacional","AO",2037 +"2037-09-18","Dia do Heroi Nacional (Day off)","AO",2037 +"2037-11-02","Dia dos Finados","AO",2037 +"2037-11-11","Dia da Independencia","AO",2037 +"2037-12-25","Dia de Natal e da Familia","AO",2037 +"2038-01-01","Ano novo","AO",2038 +"2038-02-04","Dia do Inicio da Luta Armada","AO",2038 +"2038-02-05","Dia do Inicio da Luta Armada (Day off)","AO",2038 +"2038-03-08","Carnaval (Day off)","AO",2038 +"2038-03-08","Dia Internacional da Mulher","AO",2038 +"2038-03-09","Carnaval","AO",2038 +"2038-03-22","Dia da Libertacao da Africa Austral (Day off)","AO",2038 +"2038-03-23","Dia da Libertacao da Africa Austral","AO",2038 +"2038-04-04","Dia da Paz e Reconciliacao","AO",2038 +"2038-04-23","Sexta-feira Santa","AO",2038 +"2038-05-01","Dia Mundial do Trabalho","AO",2038 +"2038-09-17","Dia do Heroi Nacional","AO",2038 +"2038-11-01","Dia dos Finados (Day off)","AO",2038 +"2038-11-02","Dia dos Finados","AO",2038 +"2038-11-11","Dia da Independencia","AO",2038 +"2038-11-12","Dia da Independencia (Day off)","AO",2038 +"2038-12-25","Dia de Natal e da Familia","AO",2038 +"2039-01-01","Ano novo","AO",2039 +"2039-02-04","Dia do Inicio da Luta Armada","AO",2039 +"2039-02-21","Carnaval (Day off)","AO",2039 +"2039-02-22","Carnaval","AO",2039 +"2039-03-07","Dia Internacional da Mulher (Day off)","AO",2039 +"2039-03-08","Dia Internacional da Mulher","AO",2039 +"2039-03-23","Dia da Libertacao da Africa Austral","AO",2039 +"2039-04-04","Dia da Paz e Reconciliacao","AO",2039 +"2039-04-08","Sexta-feira Santa","AO",2039 +"2039-05-01","Dia Mundial do Trabalho","AO",2039 +"2039-09-17","Dia do Heroi Nacional","AO",2039 +"2039-11-02","Dia dos Finados","AO",2039 +"2039-11-11","Dia da Independencia","AO",2039 +"2039-12-25","Dia de Natal e da Familia","AO",2039 +"2040-01-01","Ano novo","AO",2040 +"2040-02-04","Dia do Inicio da Luta Armada","AO",2040 +"2040-02-13","Carnaval (Day off)","AO",2040 +"2040-02-14","Carnaval","AO",2040 +"2040-03-08","Dia Internacional da Mulher","AO",2040 +"2040-03-09","Dia Internacional da Mulher (Day off)","AO",2040 +"2040-03-23","Dia da Libertacao da Africa Austral","AO",2040 +"2040-03-30","Sexta-feira Santa","AO",2040 +"2040-04-04","Dia da Paz e Reconciliacao","AO",2040 +"2040-04-30","Dia Mundial do Trabalho (Day off)","AO",2040 +"2040-05-01","Dia Mundial do Trabalho","AO",2040 +"2040-09-17","Dia do Heroi Nacional","AO",2040 +"2040-11-02","Dia dos Finados","AO",2040 +"2040-11-11","Dia da Independencia","AO",2040 +"2040-12-24","Dia de Natal e da Familia (Day off)","AO",2040 +"2040-12-25","Dia de Natal e da Familia","AO",2040 +"2040-12-31","Ano novo (Day off)","AO",2040 +"2041-01-01","Ano novo","AO",2041 +"2041-02-04","Dia do Inicio da Luta Armada","AO",2041 +"2041-03-04","Carnaval (Day off)","AO",2041 +"2041-03-05","Carnaval","AO",2041 +"2041-03-08","Dia Internacional da Mulher","AO",2041 +"2041-03-23","Dia da Libertacao da Africa Austral","AO",2041 +"2041-04-04","Dia da Paz e Reconciliacao","AO",2041 +"2041-04-05","Dia da Paz e Reconciliacao (Day off)","AO",2041 +"2041-04-19","Sexta-feira Santa","AO",2041 +"2041-05-01","Dia Mundial do Trabalho","AO",2041 +"2041-09-16","Dia do Heroi Nacional (Day off)","AO",2041 +"2041-09-17","Dia do Heroi Nacional","AO",2041 +"2041-11-02","Dia dos Finados","AO",2041 +"2041-11-11","Dia da Independencia","AO",2041 +"2041-12-25","Dia de Natal e da Familia","AO",2041 +"2042-01-01","Ano novo","AO",2042 +"2042-02-03","Dia do Inicio da Luta Armada (Day off)","AO",2042 +"2042-02-04","Dia do Inicio da Luta Armada","AO",2042 +"2042-02-17","Carnaval (Day off)","AO",2042 +"2042-02-18","Carnaval","AO",2042 +"2042-03-08","Dia Internacional da Mulher","AO",2042 +"2042-03-23","Dia da Libertacao da Africa Austral","AO",2042 +"2042-04-04","Dia da Paz e Reconciliacao","AO",2042 +"2042-04-04","Sexta-feira Santa","AO",2042 +"2042-05-01","Dia Mundial do Trabalho","AO",2042 +"2042-05-02","Dia Mundial do Trabalho (Day off)","AO",2042 +"2042-09-17","Dia do Heroi Nacional","AO",2042 +"2042-11-02","Dia dos Finados","AO",2042 +"2042-11-10","Dia da Independencia (Day off)","AO",2042 +"2042-11-11","Dia da Independencia","AO",2042 +"2042-12-25","Dia de Natal e da Familia","AO",2042 +"2042-12-26","Dia de Natal e da Familia (Day off)","AO",2042 +"2043-01-01","Ano novo","AO",2043 +"2043-01-02","Ano novo (Day off)","AO",2043 +"2043-02-04","Dia do Inicio da Luta Armada","AO",2043 +"2043-02-09","Carnaval (Day off)","AO",2043 +"2043-02-10","Carnaval","AO",2043 +"2043-03-08","Dia Internacional da Mulher","AO",2043 +"2043-03-23","Dia da Libertacao da Africa Austral","AO",2043 +"2043-03-27","Sexta-feira Santa","AO",2043 +"2043-04-04","Dia da Paz e Reconciliacao","AO",2043 +"2043-05-01","Dia Mundial do Trabalho","AO",2043 +"2043-09-17","Dia do Heroi Nacional","AO",2043 +"2043-09-18","Dia do Heroi Nacional (Day off)","AO",2043 +"2043-11-02","Dia dos Finados","AO",2043 +"2043-11-11","Dia da Independencia","AO",2043 +"2043-12-25","Dia de Natal e da Familia","AO",2043 +"2044-01-01","Ano novo","AO",2044 +"2044-02-04","Dia do Inicio da Luta Armada","AO",2044 +"2044-02-05","Dia do Inicio da Luta Armada (Day off)","AO",2044 +"2044-02-29","Carnaval (Day off)","AO",2044 +"2044-03-01","Carnaval","AO",2044 +"2044-03-07","Dia Internacional da Mulher (Day off)","AO",2044 +"2044-03-08","Dia Internacional da Mulher","AO",2044 +"2044-03-23","Dia da Libertacao da Africa Austral","AO",2044 +"2044-04-04","Dia da Paz e Reconciliacao","AO",2044 +"2044-04-15","Sexta-feira Santa","AO",2044 +"2044-05-01","Dia Mundial do Trabalho","AO",2044 +"2044-09-17","Dia do Heroi Nacional","AO",2044 +"2044-11-02","Dia dos Finados","AO",2044 +"2044-11-11","Dia da Independencia","AO",2044 +"2044-12-25","Dia de Natal e da Familia","AO",2044 +"1995-01-01","New Year's Day","AR",1995 +"1995-04-02","War Veterans Day","AR",1995 +"1995-04-14","Good Friday","AR",1995 +"1995-05-01","Labor Day","AR",1995 +"1995-05-25","May Revolution Day","AR",1995 +"1995-06-10","Day of Argentine Sovereignty over the Malvinas, Sandwich and South Atlantic Islands","AR",1995 +"1995-06-19","Pass to the Immortality of General Don Manuel Belgrano","AR",1995 +"1995-07-09","Independence Day","AR",1995 +"1995-08-21","Pass to the Immortality of General Don Jose de San Martin","AR",1995 +"1995-10-16","Columbus day (Observed)","AR",1995 +"1995-12-08","Immaculate Conception","AR",1995 +"1995-12-25","Christmas","AR",1995 +"1996-01-01","New Year's Day","AR",1996 +"1996-04-02","War Veterans Day","AR",1996 +"1996-04-05","Good Friday","AR",1996 +"1996-05-01","Labor Day","AR",1996 +"1996-05-25","May Revolution Day","AR",1996 +"1996-06-10","Day of Argentine Sovereignty over the Malvinas, Sandwich and South Atlantic Islands","AR",1996 +"1996-06-17","Pass to the Immortality of General Don Manuel Belgrano","AR",1996 +"1996-07-09","Independence Day","AR",1996 +"1996-08-19","Pass to the Immortality of General Don Jose de San Martin","AR",1996 +"1996-10-12","Columbus day","AR",1996 +"1996-12-08","Immaculate Conception","AR",1996 +"1996-12-25","Christmas","AR",1996 +"1997-01-01","New Year's Day","AR",1997 +"1997-03-28","Good Friday","AR",1997 +"1997-04-02","War Veterans Day","AR",1997 +"1997-05-01","Labor Day","AR",1997 +"1997-05-25","May Revolution Day","AR",1997 +"1997-06-10","Day of Argentine Sovereignty over the Malvinas, Sandwich and South Atlantic Islands","AR",1997 +"1997-06-16","Pass to the Immortality of General Don Manuel Belgrano","AR",1997 +"1997-07-09","Independence Day","AR",1997 +"1997-08-18","Pass to the Immortality of General Don Jose de San Martin","AR",1997 +"1997-10-12","Columbus day","AR",1997 +"1997-12-08","Immaculate Conception","AR",1997 +"1997-12-25","Christmas","AR",1997 +"1998-01-01","New Year's Day","AR",1998 +"1998-04-02","War Veterans Day","AR",1998 +"1998-04-10","Good Friday","AR",1998 +"1998-05-01","Labor Day","AR",1998 +"1998-05-25","May Revolution Day","AR",1998 +"1998-06-10","Day of Argentine Sovereignty over the Malvinas, Sandwich and South Atlantic Islands","AR",1998 +"1998-06-15","Pass to the Immortality of General Don Manuel Belgrano","AR",1998 +"1998-07-09","Independence Day","AR",1998 +"1998-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",1998 +"1998-10-12","Columbus day","AR",1998 +"1998-12-08","Immaculate Conception","AR",1998 +"1998-12-25","Christmas","AR",1998 +"1999-01-01","New Year's Day","AR",1999 +"1999-04-02","Good Friday","AR",1999 +"1999-04-02","War Veterans Day","AR",1999 +"1999-05-01","Labor Day","AR",1999 +"1999-05-25","May Revolution Day","AR",1999 +"1999-06-10","Day of Argentine Sovereignty over the Malvinas, Sandwich and South Atlantic Islands","AR",1999 +"1999-06-21","Pass to the Immortality of General Don Manuel Belgrano","AR",1999 +"1999-07-09","Independence Day","AR",1999 +"1999-08-16","Pass to the Immortality of General Don Jose de San Martin","AR",1999 +"1999-10-11","Columbus day (Observed)","AR",1999 +"1999-12-08","Immaculate Conception","AR",1999 +"1999-12-25","Christmas","AR",1999 +"2000-01-01","New Year's Day","AR",2000 +"2000-04-02","War Veterans Day","AR",2000 +"2000-04-21","Good Friday","AR",2000 +"2000-05-01","Labor Day","AR",2000 +"2000-05-25","May Revolution Day","AR",2000 +"2000-06-10","Day of Argentine Sovereignty over the Malvinas, Sandwich and South Atlantic Islands","AR",2000 +"2000-06-19","Pass to the Immortality of General Don Manuel Belgrano","AR",2000 +"2000-07-09","Independence Day","AR",2000 +"2000-08-21","Pass to the Immortality of General Don Jose de San Martin","AR",2000 +"2000-10-16","Columbus day (Observed)","AR",2000 +"2000-12-08","Immaculate Conception","AR",2000 +"2000-12-25","Christmas","AR",2000 +"2001-01-01","New Year's Day","AR",2001 +"2001-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2001 +"2001-04-13","Good Friday","AR",2001 +"2001-05-01","Labor Day","AR",2001 +"2001-05-25","May Revolution Day","AR",2001 +"2001-06-18","Pass to the Immortality of General Don Manuel Belgrano","AR",2001 +"2001-07-09","Independence Day","AR",2001 +"2001-08-20","Pass to the Immortality of General Don Jose de San Martin","AR",2001 +"2001-10-15","Columbus day (Observed)","AR",2001 +"2001-12-08","Immaculate Conception","AR",2001 +"2001-12-25","Christmas","AR",2001 +"2002-01-01","New Year's Day","AR",2002 +"2002-03-29","Good Friday","AR",2002 +"2002-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2002 +"2002-05-01","Labor Day","AR",2002 +"2002-05-25","May Revolution Day","AR",2002 +"2002-06-17","Pass to the Immortality of General Don Manuel Belgrano","AR",2002 +"2002-07-09","Independence Day","AR",2002 +"2002-08-19","Pass to the Immortality of General Don Jose de San Martin","AR",2002 +"2002-10-12","Columbus day","AR",2002 +"2002-12-08","Immaculate Conception","AR",2002 +"2002-12-25","Christmas","AR",2002 +"2003-01-01","New Year's Day","AR",2003 +"2003-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2003 +"2003-04-18","Good Friday","AR",2003 +"2003-05-01","Labor Day","AR",2003 +"2003-05-25","May Revolution Day","AR",2003 +"2003-06-16","Pass to the Immortality of General Don Manuel Belgrano","AR",2003 +"2003-07-09","Independence Day","AR",2003 +"2003-08-18","Pass to the Immortality of General Don Jose de San Martin","AR",2003 +"2003-10-12","Columbus day","AR",2003 +"2003-12-08","Immaculate Conception","AR",2003 +"2003-12-25","Christmas","AR",2003 +"2004-01-01","New Year's Day","AR",2004 +"2004-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2004 +"2004-04-09","Good Friday","AR",2004 +"2004-05-01","Labor Day","AR",2004 +"2004-05-25","May Revolution Day","AR",2004 +"2004-06-21","Pass to the Immortality of General Don Manuel Belgrano","AR",2004 +"2004-07-09","Independence Day","AR",2004 +"2004-08-16","Pass to the Immortality of General Don Jose de San Martin","AR",2004 +"2004-10-11","Columbus day (Observed)","AR",2004 +"2004-12-08","Immaculate Conception","AR",2004 +"2004-12-25","Christmas","AR",2004 +"2005-01-01","New Year's Day","AR",2005 +"2005-03-25","Good Friday","AR",2005 +"2005-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2005 +"2005-05-01","Labor Day","AR",2005 +"2005-05-25","May Revolution Day","AR",2005 +"2005-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2005 +"2005-07-09","Independence Day","AR",2005 +"2005-08-15","Pass to the Immortality of General Don Jose de San Martin","AR",2005 +"2005-10-10","Columbus day (Observed)","AR",2005 +"2005-12-08","Immaculate Conception","AR",2005 +"2005-12-25","Christmas","AR",2005 +"2006-01-01","New Year's Day","AR",2006 +"2006-03-24","Memory's National Day for the Truth and Justice","AR",2006 +"2006-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2006 +"2006-04-14","Good Friday","AR",2006 +"2006-05-01","Labor Day","AR",2006 +"2006-05-25","May Revolution Day","AR",2006 +"2006-06-19","Pass to the Immortality of General Don Manuel Belgrano","AR",2006 +"2006-07-09","Independence Day","AR",2006 +"2006-08-21","Pass to the Immortality of General Don Jose de San Martin","AR",2006 +"2006-10-16","Columbus day (Observed)","AR",2006 +"2006-12-08","Immaculate Conception","AR",2006 +"2006-12-25","Christmas","AR",2006 +"2007-01-01","New Year's Day","AR",2007 +"2007-03-24","Memory's National Day for the Truth and Justice","AR",2007 +"2007-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2007 +"2007-04-06","Good Friday","AR",2007 +"2007-05-01","Labor Day","AR",2007 +"2007-05-25","May Revolution Day","AR",2007 +"2007-06-18","Pass to the Immortality of General Don Manuel Belgrano","AR",2007 +"2007-07-09","Independence Day","AR",2007 +"2007-08-20","Pass to the Immortality of General Don Jose de San Martin","AR",2007 +"2007-10-15","Columbus day (Observed)","AR",2007 +"2007-12-08","Immaculate Conception","AR",2007 +"2007-12-25","Christmas","AR",2007 +"2008-01-01","New Year's Day","AR",2008 +"2008-03-21","Good Friday","AR",2008 +"2008-03-24","Memory's National Day for the Truth and Justice","AR",2008 +"2008-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2008 +"2008-05-01","Labor Day","AR",2008 +"2008-05-25","May Revolution Day","AR",2008 +"2008-06-16","Pass to the Immortality of General Don Manuel Belgrano","AR",2008 +"2008-07-09","Independence Day","AR",2008 +"2008-08-18","Pass to the Immortality of General Don Jose de San Martin","AR",2008 +"2008-10-12","Columbus day","AR",2008 +"2008-12-08","Immaculate Conception","AR",2008 +"2008-12-25","Christmas","AR",2008 +"2009-01-01","New Year's Day","AR",2009 +"2009-03-24","Memory's National Day for the Truth and Justice","AR",2009 +"2009-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2009 +"2009-04-10","Good Friday","AR",2009 +"2009-05-01","Labor Day","AR",2009 +"2009-05-25","May Revolution Day","AR",2009 +"2009-06-15","Pass to the Immortality of General Don Manuel Belgrano","AR",2009 +"2009-07-09","Independence Day","AR",2009 +"2009-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2009 +"2009-10-12","Columbus day","AR",2009 +"2009-12-08","Immaculate Conception","AR",2009 +"2009-12-25","Christmas","AR",2009 +"2010-01-01","New Year's Day","AR",2010 +"2010-03-24","Memory's National Day for the Truth and Justice","AR",2010 +"2010-04-02","Good Friday","AR",2010 +"2010-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2010 +"2010-05-01","Labor Day","AR",2010 +"2010-05-25","May Revolution Day","AR",2010 +"2010-06-21","Pass to the Immortality of General Don Manuel Belgrano","AR",2010 +"2010-07-09","Independence Day","AR",2010 +"2010-08-16","Pass to the Immortality of General Don Jose de San Martin","AR",2010 +"2010-10-11","Respect for Cultural Diversity Day (Observed)","AR",2010 +"2010-11-20","National Sovereignty Day","AR",2010 +"2010-12-08","Immaculate Conception","AR",2010 +"2010-12-25","Christmas","AR",2010 +"2011-01-01","New Year's Day","AR",2011 +"2011-03-07","Carnival","AR",2011 +"2011-03-08","Carnival","AR",2011 +"2011-03-24","Memory's National Day for the Truth and Justice","AR",2011 +"2011-03-25","Bridge Public Holiday","AR",2011 +"2011-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2011 +"2011-04-22","Good Friday","AR",2011 +"2011-05-01","Labor Day","AR",2011 +"2011-05-25","May Revolution Day","AR",2011 +"2011-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2011 +"2011-07-09","Independence Day","AR",2011 +"2011-08-22","Pass to the Immortality of General Don Jose de San Martin","AR",2011 +"2011-10-10","Respect for Cultural Diversity Day (Observed)","AR",2011 +"2011-11-20","National Sovereignty Day","AR",2011 +"2011-12-08","Immaculate Conception","AR",2011 +"2011-12-09","Bridge Public Holiday","AR",2011 +"2011-12-25","Christmas","AR",2011 +"2012-01-01","New Year's Day","AR",2012 +"2012-02-20","Carnival","AR",2012 +"2012-02-21","Carnival","AR",2012 +"2012-02-27","Bicentenary of the creation and first oath of the national flag","AR",2012 +"2012-03-24","Memory's National Day for the Truth and Justice","AR",2012 +"2012-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2012 +"2012-04-06","Good Friday","AR",2012 +"2012-04-30","Bridge Public Holiday","AR",2012 +"2012-05-01","Labor Day","AR",2012 +"2012-05-25","May Revolution Day","AR",2012 +"2012-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2012 +"2012-07-09","Independence Day","AR",2012 +"2012-08-20","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2012 +"2012-09-24","Bicentenary of the Battle of Tucuman","AR",2012 +"2012-10-15","Respect for Cultural Diversity Day (Observed)","AR",2012 +"2012-11-19","National Sovereignty Day (Observed)","AR",2012 +"2012-12-08","Immaculate Conception","AR",2012 +"2012-12-24","Bridge Public Holiday","AR",2012 +"2012-12-25","Christmas","AR",2012 +"2013-01-01","New Year's Day","AR",2013 +"2013-01-31","Bicentenary of the inaugural session of the National Constituent Assembly of the year 1813","AR",2013 +"2013-02-11","Carnival","AR",2013 +"2013-02-12","Carnival","AR",2013 +"2013-02-20","Bicentenary of the Battle of Salta","AR",2013 +"2013-03-24","Memory's National Day for the Truth and Justice","AR",2013 +"2013-03-29","Good Friday","AR",2013 +"2013-04-01","Bridge Public Holiday","AR",2013 +"2013-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2013 +"2013-05-01","Labor Day","AR",2013 +"2013-05-25","May Revolution Day","AR",2013 +"2013-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2013 +"2013-06-21","Bridge Public Holiday","AR",2013 +"2013-07-09","Independence Day","AR",2013 +"2013-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2013 +"2013-10-12","Respect for Cultural Diversity Day","AR",2013 +"2013-11-18","National Sovereignty Day (Observed)","AR",2013 +"2013-12-08","Immaculate Conception","AR",2013 +"2013-12-25","Christmas","AR",2013 +"2014-01-01","New Year's Day","AR",2014 +"2014-03-03","Carnival","AR",2014 +"2014-03-04","Carnival","AR",2014 +"2014-03-24","Memory's National Day for the Truth and Justice","AR",2014 +"2014-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2014 +"2014-04-18","Good Friday","AR",2014 +"2014-05-01","Labor Day","AR",2014 +"2014-05-02","Bridge Public Holiday","AR",2014 +"2014-05-25","May Revolution Day","AR",2014 +"2014-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2014 +"2014-07-09","Independence Day","AR",2014 +"2014-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2014 +"2014-10-12","Respect for Cultural Diversity Day","AR",2014 +"2014-11-24","National Sovereignty Day (Observed)","AR",2014 +"2014-12-08","Immaculate Conception","AR",2014 +"2014-12-25","Christmas","AR",2014 +"2014-12-26","Bridge Public Holiday","AR",2014 +"2015-01-01","New Year's Day","AR",2015 +"2015-02-16","Carnival","AR",2015 +"2015-02-17","Carnival","AR",2015 +"2015-03-23","Bridge Public Holiday","AR",2015 +"2015-03-24","Memory's National Day for the Truth and Justice","AR",2015 +"2015-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2015 +"2015-04-03","Good Friday","AR",2015 +"2015-05-01","Labor Day","AR",2015 +"2015-05-25","May Revolution Day","AR",2015 +"2015-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2015 +"2015-07-09","Independence Day","AR",2015 +"2015-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2015 +"2015-10-12","Respect for Cultural Diversity Day","AR",2015 +"2015-11-27","National Sovereignty Day","AR",2015 +"2015-12-07","Bridge Public Holiday","AR",2015 +"2015-12-08","Immaculate Conception","AR",2015 +"2015-12-25","Christmas","AR",2015 +"2016-01-01","New Year's Day","AR",2016 +"2016-02-08","Carnival","AR",2016 +"2016-02-09","Carnival","AR",2016 +"2016-03-24","Memory's National Day for the Truth and Justice","AR",2016 +"2016-03-25","Good Friday","AR",2016 +"2016-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2016 +"2016-05-01","Labor Day","AR",2016 +"2016-05-25","May Revolution Day","AR",2016 +"2016-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2016 +"2016-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2016 +"2016-07-08","Bridge Public Holiday","AR",2016 +"2016-07-09","Independence Day","AR",2016 +"2016-08-15","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2016 +"2016-10-10","Respect for Cultural Diversity Day (Observed)","AR",2016 +"2016-11-28","National Sovereignty Day","AR",2016 +"2016-12-08","Immaculate Conception","AR",2016 +"2016-12-09","Bridge Public Holiday","AR",2016 +"2016-12-25","Christmas","AR",2016 +"2017-01-01","New Year's Day","AR",2017 +"2017-02-27","Carnival","AR",2017 +"2017-02-28","Carnival","AR",2017 +"2017-03-24","Memory's National Day for the Truth and Justice","AR",2017 +"2017-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2017 +"2017-04-14","Good Friday","AR",2017 +"2017-05-01","Labor Day","AR",2017 +"2017-05-25","May Revolution Day","AR",2017 +"2017-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2017 +"2017-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2017 +"2017-07-09","Independence Day","AR",2017 +"2017-08-21","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2017 +"2017-10-16","Respect for Cultural Diversity Day (Observed)","AR",2017 +"2017-11-20","National Sovereignty Day","AR",2017 +"2017-12-08","Immaculate Conception","AR",2017 +"2017-12-25","Christmas","AR",2017 +"2018-01-01","New Year's Day","AR",2018 +"2018-02-12","Carnival","AR",2018 +"2018-02-13","Carnival","AR",2018 +"2018-03-24","Memory's National Day for the Truth and Justice","AR",2018 +"2018-03-30","Good Friday","AR",2018 +"2018-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2018 +"2018-04-30","Bridge Public Holiday","AR",2018 +"2018-05-01","Labor Day","AR",2018 +"2018-05-25","May Revolution Day","AR",2018 +"2018-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2018 +"2018-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2018 +"2018-07-09","Independence Day","AR",2018 +"2018-08-20","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2018 +"2018-10-15","Respect for Cultural Diversity Day (Observed)","AR",2018 +"2018-11-19","National Sovereignty Day (Observed)","AR",2018 +"2018-12-08","Immaculate Conception","AR",2018 +"2018-12-24","Bridge Public Holiday","AR",2018 +"2018-12-25","Christmas","AR",2018 +"2018-12-31","Bridge Public Holiday","AR",2018 +"2019-01-01","New Year's Day","AR",2019 +"2019-03-04","Carnival","AR",2019 +"2019-03-05","Carnival","AR",2019 +"2019-03-24","Memory's National Day for the Truth and Justice","AR",2019 +"2019-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2019 +"2019-04-19","Good Friday","AR",2019 +"2019-05-01","Labor Day","AR",2019 +"2019-05-25","May Revolution Day","AR",2019 +"2019-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2019 +"2019-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2019 +"2019-07-08","Bridge Public Holiday","AR",2019 +"2019-07-09","Independence Day","AR",2019 +"2019-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2019 +"2019-08-19","Bridge Public Holiday","AR",2019 +"2019-10-12","Respect for Cultural Diversity Day","AR",2019 +"2019-10-14","Bridge Public Holiday","AR",2019 +"2019-11-18","National Sovereignty Day (Observed)","AR",2019 +"2019-12-08","Immaculate Conception","AR",2019 +"2019-12-25","Christmas","AR",2019 +"2020-01-01","New Year's Day","AR",2020 +"2020-02-24","Carnival","AR",2020 +"2020-02-25","Carnival","AR",2020 +"2020-03-23","Bridge Public Holiday","AR",2020 +"2020-03-24","Memory's National Day for the Truth and Justice","AR",2020 +"2020-03-31","Veterans Day and the Fallen in the Malvinas War","AR",2020 +"2020-04-10","Good Friday","AR",2020 +"2020-05-01","Labor Day","AR",2020 +"2020-05-25","May Revolution Day","AR",2020 +"2020-06-15","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2020 +"2020-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2020 +"2020-07-09","Independence Day","AR",2020 +"2020-07-10","Bridge Public Holiday","AR",2020 +"2020-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2020 +"2020-10-12","Respect for Cultural Diversity Day","AR",2020 +"2020-11-23","National Sovereignty Day (Observed)","AR",2020 +"2020-12-07","Bridge Public Holiday","AR",2020 +"2020-12-08","Immaculate Conception","AR",2020 +"2020-12-25","Christmas","AR",2020 +"2021-01-01","New Year's Day","AR",2021 +"2021-02-15","Carnival","AR",2021 +"2021-02-16","Carnival","AR",2021 +"2021-03-24","Memory's National Day for the Truth and Justice","AR",2021 +"2021-04-02","Good Friday","AR",2021 +"2021-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2021 +"2021-05-01","Labor Day","AR",2021 +"2021-05-24","Bridge Public Holiday","AR",2021 +"2021-05-25","May Revolution Day","AR",2021 +"2021-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2021 +"2021-06-21","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2021 +"2021-07-09","Independence Day","AR",2021 +"2021-08-16","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2021 +"2021-10-08","Bridge Public Holiday","AR",2021 +"2021-10-11","Respect for Cultural Diversity Day (Observed)","AR",2021 +"2021-11-20","National Sovereignty Day","AR",2021 +"2021-11-22","Bridge Public Holiday","AR",2021 +"2021-12-08","Immaculate Conception","AR",2021 +"2021-12-25","Christmas","AR",2021 +"2022-01-01","New Year's Day","AR",2022 +"2022-02-28","Carnival","AR",2022 +"2022-03-01","Carnival","AR",2022 +"2022-03-24","Memory's National Day for the Truth and Justice","AR",2022 +"2022-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2022 +"2022-04-15","Good Friday","AR",2022 +"2022-05-01","Labor Day","AR",2022 +"2022-05-18","National Census Day 2022","AR",2022 +"2022-05-25","May Revolution Day","AR",2022 +"2022-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2022 +"2022-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2022 +"2022-07-09","Independence Day","AR",2022 +"2022-08-15","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2022 +"2022-10-07","Bridge Public Holiday","AR",2022 +"2022-10-10","Respect for Cultural Diversity Day (Observed)","AR",2022 +"2022-11-20","National Sovereignty Day","AR",2022 +"2022-11-21","Bridge Public Holiday","AR",2022 +"2022-12-08","Immaculate Conception","AR",2022 +"2022-12-09","Bridge Public Holiday","AR",2022 +"2022-12-25","Christmas","AR",2022 +"2023-01-01","New Year's Day","AR",2023 +"2023-02-20","Carnival","AR",2023 +"2023-02-21","Carnival","AR",2023 +"2023-03-24","Memory's National Day for the Truth and Justice","AR",2023 +"2023-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2023 +"2023-04-07","Good Friday","AR",2023 +"2023-05-01","Labor Day","AR",2023 +"2023-05-25","May Revolution Day","AR",2023 +"2023-05-26","Bridge Public Holiday","AR",2023 +"2023-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2023 +"2023-06-19","Bridge Public Holiday","AR",2023 +"2023-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2023 +"2023-07-09","Independence Day","AR",2023 +"2023-08-21","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2023 +"2023-10-13","Bridge Public Holiday","AR",2023 +"2023-10-16","Respect for Cultural Diversity Day (Observed)","AR",2023 +"2023-11-20","National Sovereignty Day","AR",2023 +"2023-12-08","Immaculate Conception","AR",2023 +"2023-12-25","Christmas","AR",2023 +"2024-01-01","New Year's Day","AR",2024 +"2024-02-12","Carnival","AR",2024 +"2024-02-13","Carnival","AR",2024 +"2024-03-24","Memory's National Day for the Truth and Justice","AR",2024 +"2024-03-29","Good Friday","AR",2024 +"2024-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2024 +"2024-05-01","Labor Day","AR",2024 +"2024-05-25","May Revolution Day","AR",2024 +"2024-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2024 +"2024-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2024 +"2024-07-09","Independence Day","AR",2024 +"2024-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2024 +"2024-10-12","Respect for Cultural Diversity Day","AR",2024 +"2024-11-18","National Sovereignty Day (Observed)","AR",2024 +"2024-12-08","Immaculate Conception","AR",2024 +"2024-12-25","Christmas","AR",2024 +"2025-01-01","New Year's Day","AR",2025 +"2025-03-03","Carnival","AR",2025 +"2025-03-04","Carnival","AR",2025 +"2025-03-24","Memory's National Day for the Truth and Justice","AR",2025 +"2025-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2025 +"2025-04-18","Good Friday","AR",2025 +"2025-05-01","Labor Day","AR",2025 +"2025-05-25","May Revolution Day","AR",2025 +"2025-06-16","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2025 +"2025-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2025 +"2025-07-09","Independence Day","AR",2025 +"2025-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2025 +"2025-10-12","Respect for Cultural Diversity Day","AR",2025 +"2025-11-24","National Sovereignty Day (Observed)","AR",2025 +"2025-12-08","Immaculate Conception","AR",2025 +"2025-12-25","Christmas","AR",2025 +"2026-01-01","New Year's Day","AR",2026 +"2026-02-16","Carnival","AR",2026 +"2026-02-17","Carnival","AR",2026 +"2026-03-24","Memory's National Day for the Truth and Justice","AR",2026 +"2026-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2026 +"2026-04-03","Good Friday","AR",2026 +"2026-05-01","Labor Day","AR",2026 +"2026-05-25","May Revolution Day","AR",2026 +"2026-06-15","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2026 +"2026-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2026 +"2026-07-09","Independence Day","AR",2026 +"2026-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2026 +"2026-10-12","Respect for Cultural Diversity Day","AR",2026 +"2026-11-23","National Sovereignty Day (Observed)","AR",2026 +"2026-12-08","Immaculate Conception","AR",2026 +"2026-12-25","Christmas","AR",2026 +"2027-01-01","New Year's Day","AR",2027 +"2027-02-08","Carnival","AR",2027 +"2027-02-09","Carnival","AR",2027 +"2027-03-24","Memory's National Day for the Truth and Justice","AR",2027 +"2027-03-26","Good Friday","AR",2027 +"2027-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2027 +"2027-05-01","Labor Day","AR",2027 +"2027-05-25","May Revolution Day","AR",2027 +"2027-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2027 +"2027-06-21","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2027 +"2027-07-09","Independence Day","AR",2027 +"2027-08-16","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2027 +"2027-10-11","Respect for Cultural Diversity Day (Observed)","AR",2027 +"2027-11-20","National Sovereignty Day","AR",2027 +"2027-12-08","Immaculate Conception","AR",2027 +"2027-12-25","Christmas","AR",2027 +"2028-01-01","New Year's Day","AR",2028 +"2028-02-28","Carnival","AR",2028 +"2028-02-29","Carnival","AR",2028 +"2028-03-24","Memory's National Day for the Truth and Justice","AR",2028 +"2028-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2028 +"2028-04-14","Good Friday","AR",2028 +"2028-05-01","Labor Day","AR",2028 +"2028-05-25","May Revolution Day","AR",2028 +"2028-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2028 +"2028-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2028 +"2028-07-09","Independence Day","AR",2028 +"2028-08-21","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2028 +"2028-10-16","Respect for Cultural Diversity Day (Observed)","AR",2028 +"2028-11-20","National Sovereignty Day","AR",2028 +"2028-12-08","Immaculate Conception","AR",2028 +"2028-12-25","Christmas","AR",2028 +"2029-01-01","New Year's Day","AR",2029 +"2029-02-12","Carnival","AR",2029 +"2029-02-13","Carnival","AR",2029 +"2029-03-24","Memory's National Day for the Truth and Justice","AR",2029 +"2029-03-30","Good Friday","AR",2029 +"2029-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2029 +"2029-05-01","Labor Day","AR",2029 +"2029-05-25","May Revolution Day","AR",2029 +"2029-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2029 +"2029-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2029 +"2029-07-09","Independence Day","AR",2029 +"2029-08-20","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2029 +"2029-10-15","Respect for Cultural Diversity Day (Observed)","AR",2029 +"2029-11-19","National Sovereignty Day (Observed)","AR",2029 +"2029-12-08","Immaculate Conception","AR",2029 +"2029-12-25","Christmas","AR",2029 +"2030-01-01","New Year's Day","AR",2030 +"2030-03-04","Carnival","AR",2030 +"2030-03-05","Carnival","AR",2030 +"2030-03-24","Memory's National Day for the Truth and Justice","AR",2030 +"2030-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2030 +"2030-04-19","Good Friday","AR",2030 +"2030-05-01","Labor Day","AR",2030 +"2030-05-25","May Revolution Day","AR",2030 +"2030-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2030 +"2030-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2030 +"2030-07-09","Independence Day","AR",2030 +"2030-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2030 +"2030-10-12","Respect for Cultural Diversity Day","AR",2030 +"2030-11-18","National Sovereignty Day (Observed)","AR",2030 +"2030-12-08","Immaculate Conception","AR",2030 +"2030-12-25","Christmas","AR",2030 +"2031-01-01","New Year's Day","AR",2031 +"2031-02-24","Carnival","AR",2031 +"2031-02-25","Carnival","AR",2031 +"2031-03-24","Memory's National Day for the Truth and Justice","AR",2031 +"2031-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2031 +"2031-04-11","Good Friday","AR",2031 +"2031-05-01","Labor Day","AR",2031 +"2031-05-25","May Revolution Day","AR",2031 +"2031-06-16","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2031 +"2031-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2031 +"2031-07-09","Independence Day","AR",2031 +"2031-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2031 +"2031-10-12","Respect for Cultural Diversity Day","AR",2031 +"2031-11-24","National Sovereignty Day (Observed)","AR",2031 +"2031-12-08","Immaculate Conception","AR",2031 +"2031-12-25","Christmas","AR",2031 +"2032-01-01","New Year's Day","AR",2032 +"2032-02-09","Carnival","AR",2032 +"2032-02-10","Carnival","AR",2032 +"2032-03-24","Memory's National Day for the Truth and Justice","AR",2032 +"2032-03-26","Good Friday","AR",2032 +"2032-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2032 +"2032-05-01","Labor Day","AR",2032 +"2032-05-25","May Revolution Day","AR",2032 +"2032-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2032 +"2032-06-21","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2032 +"2032-07-09","Independence Day","AR",2032 +"2032-08-16","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2032 +"2032-10-11","Respect for Cultural Diversity Day (Observed)","AR",2032 +"2032-11-20","National Sovereignty Day","AR",2032 +"2032-12-08","Immaculate Conception","AR",2032 +"2032-12-25","Christmas","AR",2032 +"2033-01-01","New Year's Day","AR",2033 +"2033-02-28","Carnival","AR",2033 +"2033-03-01","Carnival","AR",2033 +"2033-03-24","Memory's National Day for the Truth and Justice","AR",2033 +"2033-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2033 +"2033-04-15","Good Friday","AR",2033 +"2033-05-01","Labor Day","AR",2033 +"2033-05-25","May Revolution Day","AR",2033 +"2033-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2033 +"2033-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2033 +"2033-07-09","Independence Day","AR",2033 +"2033-08-15","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2033 +"2033-10-10","Respect for Cultural Diversity Day (Observed)","AR",2033 +"2033-11-20","National Sovereignty Day","AR",2033 +"2033-12-08","Immaculate Conception","AR",2033 +"2033-12-25","Christmas","AR",2033 +"2034-01-01","New Year's Day","AR",2034 +"2034-02-20","Carnival","AR",2034 +"2034-02-21","Carnival","AR",2034 +"2034-03-24","Memory's National Day for the Truth and Justice","AR",2034 +"2034-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2034 +"2034-04-07","Good Friday","AR",2034 +"2034-05-01","Labor Day","AR",2034 +"2034-05-25","May Revolution Day","AR",2034 +"2034-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2034 +"2034-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2034 +"2034-07-09","Independence Day","AR",2034 +"2034-08-21","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2034 +"2034-10-16","Respect for Cultural Diversity Day (Observed)","AR",2034 +"2034-11-20","National Sovereignty Day","AR",2034 +"2034-12-08","Immaculate Conception","AR",2034 +"2034-12-25","Christmas","AR",2034 +"2035-01-01","New Year's Day","AR",2035 +"2035-02-05","Carnival","AR",2035 +"2035-02-06","Carnival","AR",2035 +"2035-03-23","Good Friday","AR",2035 +"2035-03-24","Memory's National Day for the Truth and Justice","AR",2035 +"2035-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2035 +"2035-05-01","Labor Day","AR",2035 +"2035-05-25","May Revolution Day","AR",2035 +"2035-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2035 +"2035-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2035 +"2035-07-09","Independence Day","AR",2035 +"2035-08-20","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2035 +"2035-10-15","Respect for Cultural Diversity Day (Observed)","AR",2035 +"2035-11-19","National Sovereignty Day (Observed)","AR",2035 +"2035-12-08","Immaculate Conception","AR",2035 +"2035-12-25","Christmas","AR",2035 +"2036-01-01","New Year's Day","AR",2036 +"2036-02-25","Carnival","AR",2036 +"2036-02-26","Carnival","AR",2036 +"2036-03-24","Memory's National Day for the Truth and Justice","AR",2036 +"2036-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2036 +"2036-04-11","Good Friday","AR",2036 +"2036-05-01","Labor Day","AR",2036 +"2036-05-25","May Revolution Day","AR",2036 +"2036-06-16","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2036 +"2036-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2036 +"2036-07-09","Independence Day","AR",2036 +"2036-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2036 +"2036-10-12","Respect for Cultural Diversity Day","AR",2036 +"2036-11-24","National Sovereignty Day (Observed)","AR",2036 +"2036-12-08","Immaculate Conception","AR",2036 +"2036-12-25","Christmas","AR",2036 +"2037-01-01","New Year's Day","AR",2037 +"2037-02-16","Carnival","AR",2037 +"2037-02-17","Carnival","AR",2037 +"2037-03-24","Memory's National Day for the Truth and Justice","AR",2037 +"2037-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2037 +"2037-04-03","Good Friday","AR",2037 +"2037-05-01","Labor Day","AR",2037 +"2037-05-25","May Revolution Day","AR",2037 +"2037-06-15","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2037 +"2037-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2037 +"2037-07-09","Independence Day","AR",2037 +"2037-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2037 +"2037-10-12","Respect for Cultural Diversity Day","AR",2037 +"2037-11-23","National Sovereignty Day (Observed)","AR",2037 +"2037-12-08","Immaculate Conception","AR",2037 +"2037-12-25","Christmas","AR",2037 +"2038-01-01","New Year's Day","AR",2038 +"2038-03-08","Carnival","AR",2038 +"2038-03-09","Carnival","AR",2038 +"2038-03-24","Memory's National Day for the Truth and Justice","AR",2038 +"2038-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2038 +"2038-04-23","Good Friday","AR",2038 +"2038-05-01","Labor Day","AR",2038 +"2038-05-25","May Revolution Day","AR",2038 +"2038-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2038 +"2038-06-21","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2038 +"2038-07-09","Independence Day","AR",2038 +"2038-08-16","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2038 +"2038-10-11","Respect for Cultural Diversity Day (Observed)","AR",2038 +"2038-11-20","National Sovereignty Day","AR",2038 +"2038-12-08","Immaculate Conception","AR",2038 +"2038-12-25","Christmas","AR",2038 +"2039-01-01","New Year's Day","AR",2039 +"2039-02-21","Carnival","AR",2039 +"2039-02-22","Carnival","AR",2039 +"2039-03-24","Memory's National Day for the Truth and Justice","AR",2039 +"2039-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2039 +"2039-04-08","Good Friday","AR",2039 +"2039-05-01","Labor Day","AR",2039 +"2039-05-25","May Revolution Day","AR",2039 +"2039-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2039 +"2039-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2039 +"2039-07-09","Independence Day","AR",2039 +"2039-08-15","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2039 +"2039-10-10","Respect for Cultural Diversity Day (Observed)","AR",2039 +"2039-11-20","National Sovereignty Day","AR",2039 +"2039-12-08","Immaculate Conception","AR",2039 +"2039-12-25","Christmas","AR",2039 +"2040-01-01","New Year's Day","AR",2040 +"2040-02-13","Carnival","AR",2040 +"2040-02-14","Carnival","AR",2040 +"2040-03-24","Memory's National Day for the Truth and Justice","AR",2040 +"2040-03-30","Good Friday","AR",2040 +"2040-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2040 +"2040-05-01","Labor Day","AR",2040 +"2040-05-25","May Revolution Day","AR",2040 +"2040-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2040 +"2040-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2040 +"2040-07-09","Independence Day","AR",2040 +"2040-08-20","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2040 +"2040-10-15","Respect for Cultural Diversity Day (Observed)","AR",2040 +"2040-11-19","National Sovereignty Day (Observed)","AR",2040 +"2040-12-08","Immaculate Conception","AR",2040 +"2040-12-25","Christmas","AR",2040 +"2041-01-01","New Year's Day","AR",2041 +"2041-03-04","Carnival","AR",2041 +"2041-03-05","Carnival","AR",2041 +"2041-03-24","Memory's National Day for the Truth and Justice","AR",2041 +"2041-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2041 +"2041-04-19","Good Friday","AR",2041 +"2041-05-01","Labor Day","AR",2041 +"2041-05-25","May Revolution Day","AR",2041 +"2041-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2041 +"2041-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2041 +"2041-07-09","Independence Day","AR",2041 +"2041-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2041 +"2041-10-12","Respect for Cultural Diversity Day","AR",2041 +"2041-11-18","National Sovereignty Day (Observed)","AR",2041 +"2041-12-08","Immaculate Conception","AR",2041 +"2041-12-25","Christmas","AR",2041 +"2042-01-01","New Year's Day","AR",2042 +"2042-02-17","Carnival","AR",2042 +"2042-02-18","Carnival","AR",2042 +"2042-03-24","Memory's National Day for the Truth and Justice","AR",2042 +"2042-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2042 +"2042-04-04","Good Friday","AR",2042 +"2042-05-01","Labor Day","AR",2042 +"2042-05-25","May Revolution Day","AR",2042 +"2042-06-16","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2042 +"2042-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2042 +"2042-07-09","Independence Day","AR",2042 +"2042-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2042 +"2042-10-12","Respect for Cultural Diversity Day","AR",2042 +"2042-11-24","National Sovereignty Day (Observed)","AR",2042 +"2042-12-08","Immaculate Conception","AR",2042 +"2042-12-25","Christmas","AR",2042 +"2043-01-01","New Year's Day","AR",2043 +"2043-02-09","Carnival","AR",2043 +"2043-02-10","Carnival","AR",2043 +"2043-03-24","Memory's National Day for the Truth and Justice","AR",2043 +"2043-03-27","Good Friday","AR",2043 +"2043-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2043 +"2043-05-01","Labor Day","AR",2043 +"2043-05-25","May Revolution Day","AR",2043 +"2043-06-15","Pass to the Immortality of General Don Martin Miguel de Guemes (Observed)","AR",2043 +"2043-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2043 +"2043-07-09","Independence Day","AR",2043 +"2043-08-17","Pass to the Immortality of General Don Jose de San Martin","AR",2043 +"2043-10-12","Respect for Cultural Diversity Day","AR",2043 +"2043-11-23","National Sovereignty Day (Observed)","AR",2043 +"2043-12-08","Immaculate Conception","AR",2043 +"2043-12-25","Christmas","AR",2043 +"2044-01-01","New Year's Day","AR",2044 +"2044-02-29","Carnival","AR",2044 +"2044-03-01","Carnival","AR",2044 +"2044-03-24","Memory's National Day for the Truth and Justice","AR",2044 +"2044-04-02","Veterans Day and the Fallen in the Malvinas War","AR",2044 +"2044-04-15","Good Friday","AR",2044 +"2044-05-01","Labor Day","AR",2044 +"2044-05-25","May Revolution Day","AR",2044 +"2044-06-17","Pass to the Immortality of General Don Martin Miguel de Guemes","AR",2044 +"2044-06-20","Pass to the Immortality of General Don Manuel Belgrano","AR",2044 +"2044-07-09","Independence Day","AR",2044 +"2044-08-15","Pass to the Immortality of General Don Jose de San Martin (Observed)","AR",2044 +"2044-10-10","Respect for Cultural Diversity Day (Observed)","AR",2044 +"2044-11-20","National Sovereignty Day","AR",2044 +"2044-12-08","Immaculate Conception","AR",2044 +"2044-12-25","Christmas","AR",2044 +"1995-01-01","New Year's Day","AS",1995 +"1995-01-02","New Year's Day (Observed)","AS",1995 +"1995-01-16","Martin Luther King Jr. Day","AS",1995 +"1995-02-20","Washington's Birthday","AS",1995 +"1995-05-29","Memorial Day","AS",1995 +"1995-07-04","Independence Day","AS",1995 +"1995-09-04","Labor Day","AS",1995 +"1995-10-09","Columbus Day","AS",1995 +"1995-11-10","Veterans Day (Observed)","AS",1995 +"1995-11-11","Veterans Day","AS",1995 +"1995-11-23","Thanksgiving","AS",1995 +"1995-12-22","Christmas Eve (Observed)","AS",1995 +"1995-12-24","Christmas Eve","AS",1995 +"1995-12-25","Christmas Day","AS",1995 +"1996-01-01","New Year's Day","AS",1996 +"1996-01-15","Martin Luther King Jr. Day","AS",1996 +"1996-02-19","Washington's Birthday","AS",1996 +"1996-05-27","Memorial Day","AS",1996 +"1996-07-04","Independence Day","AS",1996 +"1996-09-02","Labor Day","AS",1996 +"1996-10-14","Columbus Day","AS",1996 +"1996-11-11","Veterans Day","AS",1996 +"1996-11-28","Thanksgiving","AS",1996 +"1996-12-24","Christmas Eve","AS",1996 +"1996-12-25","Christmas Day","AS",1996 +"1997-01-01","New Year's Day","AS",1997 +"1997-01-20","Martin Luther King Jr. Day","AS",1997 +"1997-02-17","Washington's Birthday","AS",1997 +"1997-05-26","Memorial Day","AS",1997 +"1997-07-04","Independence Day","AS",1997 +"1997-09-01","Labor Day","AS",1997 +"1997-10-13","Columbus Day","AS",1997 +"1997-11-11","Veterans Day","AS",1997 +"1997-11-27","Thanksgiving","AS",1997 +"1997-12-24","Christmas Eve","AS",1997 +"1997-12-25","Christmas Day","AS",1997 +"1998-01-01","New Year's Day","AS",1998 +"1998-01-19","Martin Luther King Jr. Day","AS",1998 +"1998-02-16","Washington's Birthday","AS",1998 +"1998-05-25","Memorial Day","AS",1998 +"1998-07-03","Independence Day (Observed)","AS",1998 +"1998-07-04","Independence Day","AS",1998 +"1998-09-07","Labor Day","AS",1998 +"1998-10-12","Columbus Day","AS",1998 +"1998-11-11","Veterans Day","AS",1998 +"1998-11-26","Thanksgiving","AS",1998 +"1998-12-24","Christmas Eve","AS",1998 +"1998-12-25","Christmas Day","AS",1998 +"1999-01-01","New Year's Day","AS",1999 +"1999-01-18","Martin Luther King Jr. Day","AS",1999 +"1999-02-15","Washington's Birthday","AS",1999 +"1999-05-31","Memorial Day","AS",1999 +"1999-07-04","Independence Day","AS",1999 +"1999-07-05","Independence Day (Observed)","AS",1999 +"1999-09-06","Labor Day","AS",1999 +"1999-10-11","Columbus Day","AS",1999 +"1999-11-11","Veterans Day","AS",1999 +"1999-11-25","Thanksgiving","AS",1999 +"1999-12-23","Christmas Eve (Observed)","AS",1999 +"1999-12-24","Christmas Day (Observed)","AS",1999 +"1999-12-24","Christmas Eve","AS",1999 +"1999-12-25","Christmas Day","AS",1999 +"1999-12-31","New Year's Day (Observed)","AS",1999 +"2000-01-01","New Year's Day","AS",2000 +"2000-01-17","Martin Luther King Jr. Day","AS",2000 +"2000-02-21","Washington's Birthday","AS",2000 +"2000-05-29","Memorial Day","AS",2000 +"2000-07-04","Independence Day","AS",2000 +"2000-09-04","Labor Day","AS",2000 +"2000-10-09","Columbus Day","AS",2000 +"2000-11-10","Veterans Day (Observed)","AS",2000 +"2000-11-11","Veterans Day","AS",2000 +"2000-11-23","Thanksgiving","AS",2000 +"2000-12-22","Christmas Eve (Observed)","AS",2000 +"2000-12-24","Christmas Eve","AS",2000 +"2000-12-25","Christmas Day","AS",2000 +"2001-01-01","New Year's Day","AS",2001 +"2001-01-15","Martin Luther King Jr. Day","AS",2001 +"2001-02-19","Washington's Birthday","AS",2001 +"2001-05-28","Memorial Day","AS",2001 +"2001-07-04","Independence Day","AS",2001 +"2001-09-03","Labor Day","AS",2001 +"2001-10-08","Columbus Day","AS",2001 +"2001-11-11","Veterans Day","AS",2001 +"2001-11-12","Veterans Day (Observed)","AS",2001 +"2001-11-22","Thanksgiving","AS",2001 +"2001-12-24","Christmas Eve","AS",2001 +"2001-12-25","Christmas Day","AS",2001 +"2002-01-01","New Year's Day","AS",2002 +"2002-01-21","Martin Luther King Jr. Day","AS",2002 +"2002-02-18","Washington's Birthday","AS",2002 +"2002-05-27","Memorial Day","AS",2002 +"2002-07-04","Independence Day","AS",2002 +"2002-09-02","Labor Day","AS",2002 +"2002-10-14","Columbus Day","AS",2002 +"2002-11-11","Veterans Day","AS",2002 +"2002-11-28","Thanksgiving","AS",2002 +"2002-12-24","Christmas Eve","AS",2002 +"2002-12-25","Christmas Day","AS",2002 +"2003-01-01","New Year's Day","AS",2003 +"2003-01-20","Martin Luther King Jr. Day","AS",2003 +"2003-02-17","Washington's Birthday","AS",2003 +"2003-05-26","Memorial Day","AS",2003 +"2003-07-04","Independence Day","AS",2003 +"2003-09-01","Labor Day","AS",2003 +"2003-10-13","Columbus Day","AS",2003 +"2003-11-11","Veterans Day","AS",2003 +"2003-11-27","Thanksgiving","AS",2003 +"2003-12-24","Christmas Eve","AS",2003 +"2003-12-25","Christmas Day","AS",2003 +"2004-01-01","New Year's Day","AS",2004 +"2004-01-19","Martin Luther King Jr. Day","AS",2004 +"2004-02-16","Washington's Birthday","AS",2004 +"2004-05-31","Memorial Day","AS",2004 +"2004-07-04","Independence Day","AS",2004 +"2004-07-05","Independence Day (Observed)","AS",2004 +"2004-09-06","Labor Day","AS",2004 +"2004-10-11","Columbus Day","AS",2004 +"2004-11-11","Veterans Day","AS",2004 +"2004-11-25","Thanksgiving","AS",2004 +"2004-12-23","Christmas Eve (Observed)","AS",2004 +"2004-12-24","Christmas Day (Observed)","AS",2004 +"2004-12-24","Christmas Eve","AS",2004 +"2004-12-25","Christmas Day","AS",2004 +"2004-12-31","New Year's Day (Observed)","AS",2004 +"2005-01-01","New Year's Day","AS",2005 +"2005-01-17","Martin Luther King Jr. Day","AS",2005 +"2005-02-21","Washington's Birthday","AS",2005 +"2005-05-30","Memorial Day","AS",2005 +"2005-07-04","Independence Day","AS",2005 +"2005-09-05","Labor Day","AS",2005 +"2005-10-10","Columbus Day","AS",2005 +"2005-11-11","Veterans Day","AS",2005 +"2005-11-24","Thanksgiving","AS",2005 +"2005-12-23","Christmas Eve (Observed)","AS",2005 +"2005-12-24","Christmas Eve","AS",2005 +"2005-12-25","Christmas Day","AS",2005 +"2005-12-26","Christmas Day (Observed)","AS",2005 +"2006-01-01","New Year's Day","AS",2006 +"2006-01-02","New Year's Day (Observed)","AS",2006 +"2006-01-16","Martin Luther King Jr. Day","AS",2006 +"2006-02-20","Washington's Birthday","AS",2006 +"2006-05-29","Memorial Day","AS",2006 +"2006-07-04","Independence Day","AS",2006 +"2006-09-04","Labor Day","AS",2006 +"2006-10-09","Columbus Day","AS",2006 +"2006-11-10","Veterans Day (Observed)","AS",2006 +"2006-11-11","Veterans Day","AS",2006 +"2006-11-23","Thanksgiving","AS",2006 +"2006-12-22","Christmas Eve (Observed)","AS",2006 +"2006-12-24","Christmas Eve","AS",2006 +"2006-12-25","Christmas Day","AS",2006 +"2007-01-01","New Year's Day","AS",2007 +"2007-01-15","Martin Luther King Jr. Day","AS",2007 +"2007-02-19","Washington's Birthday","AS",2007 +"2007-05-28","Memorial Day","AS",2007 +"2007-07-04","Independence Day","AS",2007 +"2007-09-03","Labor Day","AS",2007 +"2007-10-08","Columbus Day","AS",2007 +"2007-11-11","Veterans Day","AS",2007 +"2007-11-12","Veterans Day (Observed)","AS",2007 +"2007-11-22","Thanksgiving","AS",2007 +"2007-12-24","Christmas Eve","AS",2007 +"2007-12-25","Christmas Day","AS",2007 +"2008-01-01","New Year's Day","AS",2008 +"2008-01-21","Martin Luther King Jr. Day","AS",2008 +"2008-02-18","Washington's Birthday","AS",2008 +"2008-05-26","Memorial Day","AS",2008 +"2008-07-04","Independence Day","AS",2008 +"2008-09-01","Labor Day","AS",2008 +"2008-10-13","Columbus Day","AS",2008 +"2008-11-11","Veterans Day","AS",2008 +"2008-11-27","Thanksgiving","AS",2008 +"2008-12-24","Christmas Eve","AS",2008 +"2008-12-25","Christmas Day","AS",2008 +"2009-01-01","New Year's Day","AS",2009 +"2009-01-19","Martin Luther King Jr. Day","AS",2009 +"2009-02-16","Washington's Birthday","AS",2009 +"2009-05-25","Memorial Day","AS",2009 +"2009-07-03","Independence Day (Observed)","AS",2009 +"2009-07-04","Independence Day","AS",2009 +"2009-09-07","Labor Day","AS",2009 +"2009-10-12","Columbus Day","AS",2009 +"2009-11-11","Veterans Day","AS",2009 +"2009-11-26","Thanksgiving","AS",2009 +"2009-12-24","Christmas Eve","AS",2009 +"2009-12-25","Christmas Day","AS",2009 +"2010-01-01","New Year's Day","AS",2010 +"2010-01-18","Martin Luther King Jr. Day","AS",2010 +"2010-02-15","Washington's Birthday","AS",2010 +"2010-05-31","Memorial Day","AS",2010 +"2010-07-04","Independence Day","AS",2010 +"2010-07-05","Independence Day (Observed)","AS",2010 +"2010-09-06","Labor Day","AS",2010 +"2010-10-11","Columbus Day","AS",2010 +"2010-11-11","Veterans Day","AS",2010 +"2010-11-25","Thanksgiving","AS",2010 +"2010-12-23","Christmas Eve (Observed)","AS",2010 +"2010-12-24","Christmas Day (Observed)","AS",2010 +"2010-12-24","Christmas Eve","AS",2010 +"2010-12-25","Christmas Day","AS",2010 +"2010-12-31","New Year's Day (Observed)","AS",2010 +"2011-01-01","New Year's Day","AS",2011 +"2011-01-17","Martin Luther King Jr. Day","AS",2011 +"2011-02-21","Washington's Birthday","AS",2011 +"2011-05-30","Memorial Day","AS",2011 +"2011-07-04","Independence Day","AS",2011 +"2011-09-05","Labor Day","AS",2011 +"2011-10-10","Columbus Day","AS",2011 +"2011-11-11","Veterans Day","AS",2011 +"2011-11-24","Thanksgiving","AS",2011 +"2011-12-23","Christmas Eve (Observed)","AS",2011 +"2011-12-24","Christmas Eve","AS",2011 +"2011-12-25","Christmas Day","AS",2011 +"2011-12-26","Christmas Day (Observed)","AS",2011 +"2012-01-01","New Year's Day","AS",2012 +"2012-01-02","New Year's Day (Observed)","AS",2012 +"2012-01-16","Martin Luther King Jr. Day","AS",2012 +"2012-02-20","Washington's Birthday","AS",2012 +"2012-05-28","Memorial Day","AS",2012 +"2012-07-04","Independence Day","AS",2012 +"2012-09-03","Labor Day","AS",2012 +"2012-10-08","Columbus Day","AS",2012 +"2012-11-11","Veterans Day","AS",2012 +"2012-11-12","Veterans Day (Observed)","AS",2012 +"2012-11-22","Thanksgiving","AS",2012 +"2012-12-24","Christmas Eve","AS",2012 +"2012-12-25","Christmas Day","AS",2012 +"2013-01-01","New Year's Day","AS",2013 +"2013-01-21","Martin Luther King Jr. Day","AS",2013 +"2013-02-18","Washington's Birthday","AS",2013 +"2013-05-27","Memorial Day","AS",2013 +"2013-07-04","Independence Day","AS",2013 +"2013-09-02","Labor Day","AS",2013 +"2013-10-14","Columbus Day","AS",2013 +"2013-11-11","Veterans Day","AS",2013 +"2013-11-28","Thanksgiving","AS",2013 +"2013-12-24","Christmas Eve","AS",2013 +"2013-12-25","Christmas Day","AS",2013 +"2014-01-01","New Year's Day","AS",2014 +"2014-01-20","Martin Luther King Jr. Day","AS",2014 +"2014-02-17","Washington's Birthday","AS",2014 +"2014-05-26","Memorial Day","AS",2014 +"2014-07-04","Independence Day","AS",2014 +"2014-09-01","Labor Day","AS",2014 +"2014-10-13","Columbus Day","AS",2014 +"2014-11-11","Veterans Day","AS",2014 +"2014-11-27","Thanksgiving","AS",2014 +"2014-12-24","Christmas Eve","AS",2014 +"2014-12-25","Christmas Day","AS",2014 +"2015-01-01","New Year's Day","AS",2015 +"2015-01-19","Martin Luther King Jr. Day","AS",2015 +"2015-02-16","Washington's Birthday","AS",2015 +"2015-05-25","Memorial Day","AS",2015 +"2015-07-03","Independence Day (Observed)","AS",2015 +"2015-07-04","Independence Day","AS",2015 +"2015-09-07","Labor Day","AS",2015 +"2015-10-12","Columbus Day","AS",2015 +"2015-11-11","Veterans Day","AS",2015 +"2015-11-26","Thanksgiving","AS",2015 +"2015-12-24","Christmas Eve","AS",2015 +"2015-12-25","Christmas Day","AS",2015 +"2016-01-01","New Year's Day","AS",2016 +"2016-01-18","Martin Luther King Jr. Day","AS",2016 +"2016-02-15","Washington's Birthday","AS",2016 +"2016-05-30","Memorial Day","AS",2016 +"2016-07-04","Independence Day","AS",2016 +"2016-09-05","Labor Day","AS",2016 +"2016-10-10","Columbus Day","AS",2016 +"2016-11-11","Veterans Day","AS",2016 +"2016-11-24","Thanksgiving","AS",2016 +"2016-12-23","Christmas Eve (Observed)","AS",2016 +"2016-12-24","Christmas Eve","AS",2016 +"2016-12-25","Christmas Day","AS",2016 +"2016-12-26","Christmas Day (Observed)","AS",2016 +"2017-01-01","New Year's Day","AS",2017 +"2017-01-02","New Year's Day (Observed)","AS",2017 +"2017-01-16","Martin Luther King Jr. Day","AS",2017 +"2017-02-20","Washington's Birthday","AS",2017 +"2017-05-29","Memorial Day","AS",2017 +"2017-07-04","Independence Day","AS",2017 +"2017-09-04","Labor Day","AS",2017 +"2017-10-09","Columbus Day","AS",2017 +"2017-11-10","Veterans Day (Observed)","AS",2017 +"2017-11-11","Veterans Day","AS",2017 +"2017-11-23","Thanksgiving","AS",2017 +"2017-12-22","Christmas Eve (Observed)","AS",2017 +"2017-12-24","Christmas Eve","AS",2017 +"2017-12-25","Christmas Day","AS",2017 +"2018-01-01","New Year's Day","AS",2018 +"2018-01-15","Martin Luther King Jr. Day","AS",2018 +"2018-02-19","Washington's Birthday","AS",2018 +"2018-05-28","Memorial Day","AS",2018 +"2018-07-04","Independence Day","AS",2018 +"2018-09-03","Labor Day","AS",2018 +"2018-10-08","Columbus Day","AS",2018 +"2018-11-11","Veterans Day","AS",2018 +"2018-11-12","Veterans Day (Observed)","AS",2018 +"2018-11-22","Thanksgiving","AS",2018 +"2018-12-24","Christmas Eve","AS",2018 +"2018-12-25","Christmas Day","AS",2018 +"2019-01-01","New Year's Day","AS",2019 +"2019-01-21","Martin Luther King Jr. Day","AS",2019 +"2019-02-18","Washington's Birthday","AS",2019 +"2019-05-27","Memorial Day","AS",2019 +"2019-07-04","Independence Day","AS",2019 +"2019-09-02","Labor Day","AS",2019 +"2019-10-14","Columbus Day","AS",2019 +"2019-11-11","Veterans Day","AS",2019 +"2019-11-28","Thanksgiving","AS",2019 +"2019-12-24","Christmas Eve","AS",2019 +"2019-12-25","Christmas Day","AS",2019 +"2020-01-01","New Year's Day","AS",2020 +"2020-01-20","Martin Luther King Jr. Day","AS",2020 +"2020-02-17","Washington's Birthday","AS",2020 +"2020-05-25","Memorial Day","AS",2020 +"2020-07-03","Independence Day (Observed)","AS",2020 +"2020-07-04","Independence Day","AS",2020 +"2020-09-07","Labor Day","AS",2020 +"2020-10-12","Columbus Day","AS",2020 +"2020-11-11","Veterans Day","AS",2020 +"2020-11-26","Thanksgiving","AS",2020 +"2020-12-24","Christmas Eve","AS",2020 +"2020-12-25","Christmas Day","AS",2020 +"2021-01-01","New Year's Day","AS",2021 +"2021-01-18","Martin Luther King Jr. Day","AS",2021 +"2021-02-15","Washington's Birthday","AS",2021 +"2021-05-31","Memorial Day","AS",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","AS",2021 +"2021-06-19","Juneteenth National Independence Day","AS",2021 +"2021-07-04","Independence Day","AS",2021 +"2021-07-05","Independence Day (Observed)","AS",2021 +"2021-09-06","Labor Day","AS",2021 +"2021-10-11","Columbus Day","AS",2021 +"2021-11-11","Veterans Day","AS",2021 +"2021-11-25","Thanksgiving","AS",2021 +"2021-12-23","Christmas Eve (Observed)","AS",2021 +"2021-12-24","Christmas Day (Observed)","AS",2021 +"2021-12-24","Christmas Eve","AS",2021 +"2021-12-25","Christmas Day","AS",2021 +"2021-12-31","New Year's Day (Observed)","AS",2021 +"2022-01-01","New Year's Day","AS",2022 +"2022-01-17","Martin Luther King Jr. Day","AS",2022 +"2022-02-21","Washington's Birthday","AS",2022 +"2022-05-30","Memorial Day","AS",2022 +"2022-06-19","Juneteenth National Independence Day","AS",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","AS",2022 +"2022-07-04","Independence Day","AS",2022 +"2022-09-05","Labor Day","AS",2022 +"2022-10-10","Columbus Day","AS",2022 +"2022-11-11","Veterans Day","AS",2022 +"2022-11-24","Thanksgiving","AS",2022 +"2022-12-23","Christmas Eve (Observed)","AS",2022 +"2022-12-24","Christmas Eve","AS",2022 +"2022-12-25","Christmas Day","AS",2022 +"2022-12-26","Christmas Day (Observed)","AS",2022 +"2023-01-01","New Year's Day","AS",2023 +"2023-01-02","New Year's Day (Observed)","AS",2023 +"2023-01-16","Martin Luther King Jr. Day","AS",2023 +"2023-02-20","Washington's Birthday","AS",2023 +"2023-05-29","Memorial Day","AS",2023 +"2023-06-19","Juneteenth National Independence Day","AS",2023 +"2023-07-04","Independence Day","AS",2023 +"2023-09-04","Labor Day","AS",2023 +"2023-10-09","Columbus Day","AS",2023 +"2023-11-10","Veterans Day (Observed)","AS",2023 +"2023-11-11","Veterans Day","AS",2023 +"2023-11-23","Thanksgiving","AS",2023 +"2023-12-22","Christmas Eve (Observed)","AS",2023 +"2023-12-24","Christmas Eve","AS",2023 +"2023-12-25","Christmas Day","AS",2023 +"2024-01-01","New Year's Day","AS",2024 +"2024-01-15","Martin Luther King Jr. Day","AS",2024 +"2024-02-19","Washington's Birthday","AS",2024 +"2024-05-27","Memorial Day","AS",2024 +"2024-06-19","Juneteenth National Independence Day","AS",2024 +"2024-07-04","Independence Day","AS",2024 +"2024-09-02","Labor Day","AS",2024 +"2024-10-14","Columbus Day","AS",2024 +"2024-11-11","Veterans Day","AS",2024 +"2024-11-28","Thanksgiving","AS",2024 +"2024-12-24","Christmas Eve","AS",2024 +"2024-12-25","Christmas Day","AS",2024 +"2025-01-01","New Year's Day","AS",2025 +"2025-01-20","Martin Luther King Jr. Day","AS",2025 +"2025-02-17","Washington's Birthday","AS",2025 +"2025-05-26","Memorial Day","AS",2025 +"2025-06-19","Juneteenth National Independence Day","AS",2025 +"2025-07-04","Independence Day","AS",2025 +"2025-09-01","Labor Day","AS",2025 +"2025-10-13","Columbus Day","AS",2025 +"2025-11-11","Veterans Day","AS",2025 +"2025-11-27","Thanksgiving","AS",2025 +"2025-12-24","Christmas Eve","AS",2025 +"2025-12-25","Christmas Day","AS",2025 +"2026-01-01","New Year's Day","AS",2026 +"2026-01-19","Martin Luther King Jr. Day","AS",2026 +"2026-02-16","Washington's Birthday","AS",2026 +"2026-05-25","Memorial Day","AS",2026 +"2026-06-19","Juneteenth National Independence Day","AS",2026 +"2026-07-03","Independence Day (Observed)","AS",2026 +"2026-07-04","Independence Day","AS",2026 +"2026-09-07","Labor Day","AS",2026 +"2026-10-12","Columbus Day","AS",2026 +"2026-11-11","Veterans Day","AS",2026 +"2026-11-26","Thanksgiving","AS",2026 +"2026-12-24","Christmas Eve","AS",2026 +"2026-12-25","Christmas Day","AS",2026 +"2027-01-01","New Year's Day","AS",2027 +"2027-01-18","Martin Luther King Jr. Day","AS",2027 +"2027-02-15","Washington's Birthday","AS",2027 +"2027-05-31","Memorial Day","AS",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","AS",2027 +"2027-06-19","Juneteenth National Independence Day","AS",2027 +"2027-07-04","Independence Day","AS",2027 +"2027-07-05","Independence Day (Observed)","AS",2027 +"2027-09-06","Labor Day","AS",2027 +"2027-10-11","Columbus Day","AS",2027 +"2027-11-11","Veterans Day","AS",2027 +"2027-11-25","Thanksgiving","AS",2027 +"2027-12-23","Christmas Eve (Observed)","AS",2027 +"2027-12-24","Christmas Day (Observed)","AS",2027 +"2027-12-24","Christmas Eve","AS",2027 +"2027-12-25","Christmas Day","AS",2027 +"2027-12-31","New Year's Day (Observed)","AS",2027 +"2028-01-01","New Year's Day","AS",2028 +"2028-01-17","Martin Luther King Jr. Day","AS",2028 +"2028-02-21","Washington's Birthday","AS",2028 +"2028-05-29","Memorial Day","AS",2028 +"2028-06-19","Juneteenth National Independence Day","AS",2028 +"2028-07-04","Independence Day","AS",2028 +"2028-09-04","Labor Day","AS",2028 +"2028-10-09","Columbus Day","AS",2028 +"2028-11-10","Veterans Day (Observed)","AS",2028 +"2028-11-11","Veterans Day","AS",2028 +"2028-11-23","Thanksgiving","AS",2028 +"2028-12-22","Christmas Eve (Observed)","AS",2028 +"2028-12-24","Christmas Eve","AS",2028 +"2028-12-25","Christmas Day","AS",2028 +"2029-01-01","New Year's Day","AS",2029 +"2029-01-15","Martin Luther King Jr. Day","AS",2029 +"2029-02-19","Washington's Birthday","AS",2029 +"2029-05-28","Memorial Day","AS",2029 +"2029-06-19","Juneteenth National Independence Day","AS",2029 +"2029-07-04","Independence Day","AS",2029 +"2029-09-03","Labor Day","AS",2029 +"2029-10-08","Columbus Day","AS",2029 +"2029-11-11","Veterans Day","AS",2029 +"2029-11-12","Veterans Day (Observed)","AS",2029 +"2029-11-22","Thanksgiving","AS",2029 +"2029-12-24","Christmas Eve","AS",2029 +"2029-12-25","Christmas Day","AS",2029 +"2030-01-01","New Year's Day","AS",2030 +"2030-01-21","Martin Luther King Jr. Day","AS",2030 +"2030-02-18","Washington's Birthday","AS",2030 +"2030-05-27","Memorial Day","AS",2030 +"2030-06-19","Juneteenth National Independence Day","AS",2030 +"2030-07-04","Independence Day","AS",2030 +"2030-09-02","Labor Day","AS",2030 +"2030-10-14","Columbus Day","AS",2030 +"2030-11-11","Veterans Day","AS",2030 +"2030-11-28","Thanksgiving","AS",2030 +"2030-12-24","Christmas Eve","AS",2030 +"2030-12-25","Christmas Day","AS",2030 +"2031-01-01","New Year's Day","AS",2031 +"2031-01-20","Martin Luther King Jr. Day","AS",2031 +"2031-02-17","Washington's Birthday","AS",2031 +"2031-05-26","Memorial Day","AS",2031 +"2031-06-19","Juneteenth National Independence Day","AS",2031 +"2031-07-04","Independence Day","AS",2031 +"2031-09-01","Labor Day","AS",2031 +"2031-10-13","Columbus Day","AS",2031 +"2031-11-11","Veterans Day","AS",2031 +"2031-11-27","Thanksgiving","AS",2031 +"2031-12-24","Christmas Eve","AS",2031 +"2031-12-25","Christmas Day","AS",2031 +"2032-01-01","New Year's Day","AS",2032 +"2032-01-19","Martin Luther King Jr. Day","AS",2032 +"2032-02-16","Washington's Birthday","AS",2032 +"2032-05-31","Memorial Day","AS",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","AS",2032 +"2032-06-19","Juneteenth National Independence Day","AS",2032 +"2032-07-04","Independence Day","AS",2032 +"2032-07-05","Independence Day (Observed)","AS",2032 +"2032-09-06","Labor Day","AS",2032 +"2032-10-11","Columbus Day","AS",2032 +"2032-11-11","Veterans Day","AS",2032 +"2032-11-25","Thanksgiving","AS",2032 +"2032-12-23","Christmas Eve (Observed)","AS",2032 +"2032-12-24","Christmas Day (Observed)","AS",2032 +"2032-12-24","Christmas Eve","AS",2032 +"2032-12-25","Christmas Day","AS",2032 +"2032-12-31","New Year's Day (Observed)","AS",2032 +"2033-01-01","New Year's Day","AS",2033 +"2033-01-17","Martin Luther King Jr. Day","AS",2033 +"2033-02-21","Washington's Birthday","AS",2033 +"2033-05-30","Memorial Day","AS",2033 +"2033-06-19","Juneteenth National Independence Day","AS",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","AS",2033 +"2033-07-04","Independence Day","AS",2033 +"2033-09-05","Labor Day","AS",2033 +"2033-10-10","Columbus Day","AS",2033 +"2033-11-11","Veterans Day","AS",2033 +"2033-11-24","Thanksgiving","AS",2033 +"2033-12-23","Christmas Eve (Observed)","AS",2033 +"2033-12-24","Christmas Eve","AS",2033 +"2033-12-25","Christmas Day","AS",2033 +"2033-12-26","Christmas Day (Observed)","AS",2033 +"2034-01-01","New Year's Day","AS",2034 +"2034-01-02","New Year's Day (Observed)","AS",2034 +"2034-01-16","Martin Luther King Jr. Day","AS",2034 +"2034-02-20","Washington's Birthday","AS",2034 +"2034-05-29","Memorial Day","AS",2034 +"2034-06-19","Juneteenth National Independence Day","AS",2034 +"2034-07-04","Independence Day","AS",2034 +"2034-09-04","Labor Day","AS",2034 +"2034-10-09","Columbus Day","AS",2034 +"2034-11-10","Veterans Day (Observed)","AS",2034 +"2034-11-11","Veterans Day","AS",2034 +"2034-11-23","Thanksgiving","AS",2034 +"2034-12-22","Christmas Eve (Observed)","AS",2034 +"2034-12-24","Christmas Eve","AS",2034 +"2034-12-25","Christmas Day","AS",2034 +"2035-01-01","New Year's Day","AS",2035 +"2035-01-15","Martin Luther King Jr. Day","AS",2035 +"2035-02-19","Washington's Birthday","AS",2035 +"2035-05-28","Memorial Day","AS",2035 +"2035-06-19","Juneteenth National Independence Day","AS",2035 +"2035-07-04","Independence Day","AS",2035 +"2035-09-03","Labor Day","AS",2035 +"2035-10-08","Columbus Day","AS",2035 +"2035-11-11","Veterans Day","AS",2035 +"2035-11-12","Veterans Day (Observed)","AS",2035 +"2035-11-22","Thanksgiving","AS",2035 +"2035-12-24","Christmas Eve","AS",2035 +"2035-12-25","Christmas Day","AS",2035 +"2036-01-01","New Year's Day","AS",2036 +"2036-01-21","Martin Luther King Jr. Day","AS",2036 +"2036-02-18","Washington's Birthday","AS",2036 +"2036-05-26","Memorial Day","AS",2036 +"2036-06-19","Juneteenth National Independence Day","AS",2036 +"2036-07-04","Independence Day","AS",2036 +"2036-09-01","Labor Day","AS",2036 +"2036-10-13","Columbus Day","AS",2036 +"2036-11-11","Veterans Day","AS",2036 +"2036-11-27","Thanksgiving","AS",2036 +"2036-12-24","Christmas Eve","AS",2036 +"2036-12-25","Christmas Day","AS",2036 +"2037-01-01","New Year's Day","AS",2037 +"2037-01-19","Martin Luther King Jr. Day","AS",2037 +"2037-02-16","Washington's Birthday","AS",2037 +"2037-05-25","Memorial Day","AS",2037 +"2037-06-19","Juneteenth National Independence Day","AS",2037 +"2037-07-03","Independence Day (Observed)","AS",2037 +"2037-07-04","Independence Day","AS",2037 +"2037-09-07","Labor Day","AS",2037 +"2037-10-12","Columbus Day","AS",2037 +"2037-11-11","Veterans Day","AS",2037 +"2037-11-26","Thanksgiving","AS",2037 +"2037-12-24","Christmas Eve","AS",2037 +"2037-12-25","Christmas Day","AS",2037 +"2038-01-01","New Year's Day","AS",2038 +"2038-01-18","Martin Luther King Jr. Day","AS",2038 +"2038-02-15","Washington's Birthday","AS",2038 +"2038-05-31","Memorial Day","AS",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","AS",2038 +"2038-06-19","Juneteenth National Independence Day","AS",2038 +"2038-07-04","Independence Day","AS",2038 +"2038-07-05","Independence Day (Observed)","AS",2038 +"2038-09-06","Labor Day","AS",2038 +"2038-10-11","Columbus Day","AS",2038 +"2038-11-11","Veterans Day","AS",2038 +"2038-11-25","Thanksgiving","AS",2038 +"2038-12-23","Christmas Eve (Observed)","AS",2038 +"2038-12-24","Christmas Day (Observed)","AS",2038 +"2038-12-24","Christmas Eve","AS",2038 +"2038-12-25","Christmas Day","AS",2038 +"2038-12-31","New Year's Day (Observed)","AS",2038 +"2039-01-01","New Year's Day","AS",2039 +"2039-01-17","Martin Luther King Jr. Day","AS",2039 +"2039-02-21","Washington's Birthday","AS",2039 +"2039-05-30","Memorial Day","AS",2039 +"2039-06-19","Juneteenth National Independence Day","AS",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","AS",2039 +"2039-07-04","Independence Day","AS",2039 +"2039-09-05","Labor Day","AS",2039 +"2039-10-10","Columbus Day","AS",2039 +"2039-11-11","Veterans Day","AS",2039 +"2039-11-24","Thanksgiving","AS",2039 +"2039-12-23","Christmas Eve (Observed)","AS",2039 +"2039-12-24","Christmas Eve","AS",2039 +"2039-12-25","Christmas Day","AS",2039 +"2039-12-26","Christmas Day (Observed)","AS",2039 +"2040-01-01","New Year's Day","AS",2040 +"2040-01-02","New Year's Day (Observed)","AS",2040 +"2040-01-16","Martin Luther King Jr. Day","AS",2040 +"2040-02-20","Washington's Birthday","AS",2040 +"2040-05-28","Memorial Day","AS",2040 +"2040-06-19","Juneteenth National Independence Day","AS",2040 +"2040-07-04","Independence Day","AS",2040 +"2040-09-03","Labor Day","AS",2040 +"2040-10-08","Columbus Day","AS",2040 +"2040-11-11","Veterans Day","AS",2040 +"2040-11-12","Veterans Day (Observed)","AS",2040 +"2040-11-22","Thanksgiving","AS",2040 +"2040-12-24","Christmas Eve","AS",2040 +"2040-12-25","Christmas Day","AS",2040 +"2041-01-01","New Year's Day","AS",2041 +"2041-01-21","Martin Luther King Jr. Day","AS",2041 +"2041-02-18","Washington's Birthday","AS",2041 +"2041-05-27","Memorial Day","AS",2041 +"2041-06-19","Juneteenth National Independence Day","AS",2041 +"2041-07-04","Independence Day","AS",2041 +"2041-09-02","Labor Day","AS",2041 +"2041-10-14","Columbus Day","AS",2041 +"2041-11-11","Veterans Day","AS",2041 +"2041-11-28","Thanksgiving","AS",2041 +"2041-12-24","Christmas Eve","AS",2041 +"2041-12-25","Christmas Day","AS",2041 +"2042-01-01","New Year's Day","AS",2042 +"2042-01-20","Martin Luther King Jr. Day","AS",2042 +"2042-02-17","Washington's Birthday","AS",2042 +"2042-05-26","Memorial Day","AS",2042 +"2042-06-19","Juneteenth National Independence Day","AS",2042 +"2042-07-04","Independence Day","AS",2042 +"2042-09-01","Labor Day","AS",2042 +"2042-10-13","Columbus Day","AS",2042 +"2042-11-11","Veterans Day","AS",2042 +"2042-11-27","Thanksgiving","AS",2042 +"2042-12-24","Christmas Eve","AS",2042 +"2042-12-25","Christmas Day","AS",2042 +"2043-01-01","New Year's Day","AS",2043 +"2043-01-19","Martin Luther King Jr. Day","AS",2043 +"2043-02-16","Washington's Birthday","AS",2043 +"2043-05-25","Memorial Day","AS",2043 +"2043-06-19","Juneteenth National Independence Day","AS",2043 +"2043-07-03","Independence Day (Observed)","AS",2043 +"2043-07-04","Independence Day","AS",2043 +"2043-09-07","Labor Day","AS",2043 +"2043-10-12","Columbus Day","AS",2043 +"2043-11-11","Veterans Day","AS",2043 +"2043-11-26","Thanksgiving","AS",2043 +"2043-12-24","Christmas Eve","AS",2043 +"2043-12-25","Christmas Day","AS",2043 +"2044-01-01","New Year's Day","AS",2044 +"2044-01-18","Martin Luther King Jr. Day","AS",2044 +"2044-02-15","Washington's Birthday","AS",2044 +"2044-05-30","Memorial Day","AS",2044 +"2044-06-19","Juneteenth National Independence Day","AS",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","AS",2044 +"2044-07-04","Independence Day","AS",2044 +"2044-09-05","Labor Day","AS",2044 +"2044-10-10","Columbus Day","AS",2044 +"2044-11-11","Veterans Day","AS",2044 +"2044-11-24","Thanksgiving","AS",2044 +"2044-12-23","Christmas Eve (Observed)","AS",2044 +"2044-12-24","Christmas Eve","AS",2044 +"2044-12-25","Christmas Day","AS",2044 +"2044-12-26","Christmas Day (Observed)","AS",2044 +"1995-01-01","New Year's Day","AT",1995 +"1995-01-06","Epiphany","AT",1995 +"1995-04-17","Easter Monday","AT",1995 +"1995-05-01","Labor Day","AT",1995 +"1995-05-25","Ascension Day","AT",1995 +"1995-06-05","Whit Monday","AT",1995 +"1995-06-15","Corpus Christi","AT",1995 +"1995-08-15","Assumption Day","AT",1995 +"1995-10-26","National Day","AT",1995 +"1995-11-01","All Saints' Day","AT",1995 +"1995-12-08","Immaculate Conception","AT",1995 +"1995-12-25","Christmas Day","AT",1995 +"1995-12-26","St. Stephen's Day","AT",1995 +"1996-01-01","New Year's Day","AT",1996 +"1996-01-06","Epiphany","AT",1996 +"1996-04-08","Easter Monday","AT",1996 +"1996-05-01","Labor Day","AT",1996 +"1996-05-16","Ascension Day","AT",1996 +"1996-05-27","Whit Monday","AT",1996 +"1996-06-06","Corpus Christi","AT",1996 +"1996-08-15","Assumption Day","AT",1996 +"1996-10-26","National Day","AT",1996 +"1996-11-01","All Saints' Day","AT",1996 +"1996-12-08","Immaculate Conception","AT",1996 +"1996-12-25","Christmas Day","AT",1996 +"1996-12-26","St. Stephen's Day","AT",1996 +"1997-01-01","New Year's Day","AT",1997 +"1997-01-06","Epiphany","AT",1997 +"1997-03-31","Easter Monday","AT",1997 +"1997-05-01","Labor Day","AT",1997 +"1997-05-08","Ascension Day","AT",1997 +"1997-05-19","Whit Monday","AT",1997 +"1997-05-29","Corpus Christi","AT",1997 +"1997-08-15","Assumption Day","AT",1997 +"1997-10-26","National Day","AT",1997 +"1997-11-01","All Saints' Day","AT",1997 +"1997-12-08","Immaculate Conception","AT",1997 +"1997-12-25","Christmas Day","AT",1997 +"1997-12-26","St. Stephen's Day","AT",1997 +"1998-01-01","New Year's Day","AT",1998 +"1998-01-06","Epiphany","AT",1998 +"1998-04-13","Easter Monday","AT",1998 +"1998-05-01","Labor Day","AT",1998 +"1998-05-21","Ascension Day","AT",1998 +"1998-06-01","Whit Monday","AT",1998 +"1998-06-11","Corpus Christi","AT",1998 +"1998-08-15","Assumption Day","AT",1998 +"1998-10-26","National Day","AT",1998 +"1998-11-01","All Saints' Day","AT",1998 +"1998-12-08","Immaculate Conception","AT",1998 +"1998-12-25","Christmas Day","AT",1998 +"1998-12-26","St. Stephen's Day","AT",1998 +"1999-01-01","New Year's Day","AT",1999 +"1999-01-06","Epiphany","AT",1999 +"1999-04-05","Easter Monday","AT",1999 +"1999-05-01","Labor Day","AT",1999 +"1999-05-13","Ascension Day","AT",1999 +"1999-05-24","Whit Monday","AT",1999 +"1999-06-03","Corpus Christi","AT",1999 +"1999-08-15","Assumption Day","AT",1999 +"1999-10-26","National Day","AT",1999 +"1999-11-01","All Saints' Day","AT",1999 +"1999-12-08","Immaculate Conception","AT",1999 +"1999-12-25","Christmas Day","AT",1999 +"1999-12-26","St. Stephen's Day","AT",1999 +"2000-01-01","New Year's Day","AT",2000 +"2000-01-06","Epiphany","AT",2000 +"2000-04-24","Easter Monday","AT",2000 +"2000-05-01","Labor Day","AT",2000 +"2000-06-01","Ascension Day","AT",2000 +"2000-06-12","Whit Monday","AT",2000 +"2000-06-22","Corpus Christi","AT",2000 +"2000-08-15","Assumption Day","AT",2000 +"2000-10-26","National Day","AT",2000 +"2000-11-01","All Saints' Day","AT",2000 +"2000-12-08","Immaculate Conception","AT",2000 +"2000-12-25","Christmas Day","AT",2000 +"2000-12-26","St. Stephen's Day","AT",2000 +"2001-01-01","New Year's Day","AT",2001 +"2001-01-06","Epiphany","AT",2001 +"2001-04-16","Easter Monday","AT",2001 +"2001-05-01","Labor Day","AT",2001 +"2001-05-24","Ascension Day","AT",2001 +"2001-06-04","Whit Monday","AT",2001 +"2001-06-14","Corpus Christi","AT",2001 +"2001-08-15","Assumption Day","AT",2001 +"2001-10-26","National Day","AT",2001 +"2001-11-01","All Saints' Day","AT",2001 +"2001-12-08","Immaculate Conception","AT",2001 +"2001-12-25","Christmas Day","AT",2001 +"2001-12-26","St. Stephen's Day","AT",2001 +"2002-01-01","New Year's Day","AT",2002 +"2002-01-06","Epiphany","AT",2002 +"2002-04-01","Easter Monday","AT",2002 +"2002-05-01","Labor Day","AT",2002 +"2002-05-09","Ascension Day","AT",2002 +"2002-05-20","Whit Monday","AT",2002 +"2002-05-30","Corpus Christi","AT",2002 +"2002-08-15","Assumption Day","AT",2002 +"2002-10-26","National Day","AT",2002 +"2002-11-01","All Saints' Day","AT",2002 +"2002-12-08","Immaculate Conception","AT",2002 +"2002-12-25","Christmas Day","AT",2002 +"2002-12-26","St. Stephen's Day","AT",2002 +"2003-01-01","New Year's Day","AT",2003 +"2003-01-06","Epiphany","AT",2003 +"2003-04-21","Easter Monday","AT",2003 +"2003-05-01","Labor Day","AT",2003 +"2003-05-29","Ascension Day","AT",2003 +"2003-06-09","Whit Monday","AT",2003 +"2003-06-19","Corpus Christi","AT",2003 +"2003-08-15","Assumption Day","AT",2003 +"2003-10-26","National Day","AT",2003 +"2003-11-01","All Saints' Day","AT",2003 +"2003-12-08","Immaculate Conception","AT",2003 +"2003-12-25","Christmas Day","AT",2003 +"2003-12-26","St. Stephen's Day","AT",2003 +"2004-01-01","New Year's Day","AT",2004 +"2004-01-06","Epiphany","AT",2004 +"2004-04-12","Easter Monday","AT",2004 +"2004-05-01","Labor Day","AT",2004 +"2004-05-20","Ascension Day","AT",2004 +"2004-05-31","Whit Monday","AT",2004 +"2004-06-10","Corpus Christi","AT",2004 +"2004-08-15","Assumption Day","AT",2004 +"2004-10-26","National Day","AT",2004 +"2004-11-01","All Saints' Day","AT",2004 +"2004-12-08","Immaculate Conception","AT",2004 +"2004-12-25","Christmas Day","AT",2004 +"2004-12-26","St. Stephen's Day","AT",2004 +"2005-01-01","New Year's Day","AT",2005 +"2005-01-06","Epiphany","AT",2005 +"2005-03-28","Easter Monday","AT",2005 +"2005-05-01","Labor Day","AT",2005 +"2005-05-05","Ascension Day","AT",2005 +"2005-05-16","Whit Monday","AT",2005 +"2005-05-26","Corpus Christi","AT",2005 +"2005-08-15","Assumption Day","AT",2005 +"2005-10-26","National Day","AT",2005 +"2005-11-01","All Saints' Day","AT",2005 +"2005-12-08","Immaculate Conception","AT",2005 +"2005-12-25","Christmas Day","AT",2005 +"2005-12-26","St. Stephen's Day","AT",2005 +"2006-01-01","New Year's Day","AT",2006 +"2006-01-06","Epiphany","AT",2006 +"2006-04-17","Easter Monday","AT",2006 +"2006-05-01","Labor Day","AT",2006 +"2006-05-25","Ascension Day","AT",2006 +"2006-06-05","Whit Monday","AT",2006 +"2006-06-15","Corpus Christi","AT",2006 +"2006-08-15","Assumption Day","AT",2006 +"2006-10-26","National Day","AT",2006 +"2006-11-01","All Saints' Day","AT",2006 +"2006-12-08","Immaculate Conception","AT",2006 +"2006-12-25","Christmas Day","AT",2006 +"2006-12-26","St. Stephen's Day","AT",2006 +"2007-01-01","New Year's Day","AT",2007 +"2007-01-06","Epiphany","AT",2007 +"2007-04-09","Easter Monday","AT",2007 +"2007-05-01","Labor Day","AT",2007 +"2007-05-17","Ascension Day","AT",2007 +"2007-05-28","Whit Monday","AT",2007 +"2007-06-07","Corpus Christi","AT",2007 +"2007-08-15","Assumption Day","AT",2007 +"2007-10-26","National Day","AT",2007 +"2007-11-01","All Saints' Day","AT",2007 +"2007-12-08","Immaculate Conception","AT",2007 +"2007-12-25","Christmas Day","AT",2007 +"2007-12-26","St. Stephen's Day","AT",2007 +"2008-01-01","New Year's Day","AT",2008 +"2008-01-06","Epiphany","AT",2008 +"2008-03-24","Easter Monday","AT",2008 +"2008-05-01","Ascension Day","AT",2008 +"2008-05-01","Labor Day","AT",2008 +"2008-05-12","Whit Monday","AT",2008 +"2008-05-22","Corpus Christi","AT",2008 +"2008-08-15","Assumption Day","AT",2008 +"2008-10-26","National Day","AT",2008 +"2008-11-01","All Saints' Day","AT",2008 +"2008-12-08","Immaculate Conception","AT",2008 +"2008-12-25","Christmas Day","AT",2008 +"2008-12-26","St. Stephen's Day","AT",2008 +"2009-01-01","New Year's Day","AT",2009 +"2009-01-06","Epiphany","AT",2009 +"2009-04-13","Easter Monday","AT",2009 +"2009-05-01","Labor Day","AT",2009 +"2009-05-21","Ascension Day","AT",2009 +"2009-06-01","Whit Monday","AT",2009 +"2009-06-11","Corpus Christi","AT",2009 +"2009-08-15","Assumption Day","AT",2009 +"2009-10-26","National Day","AT",2009 +"2009-11-01","All Saints' Day","AT",2009 +"2009-12-08","Immaculate Conception","AT",2009 +"2009-12-25","Christmas Day","AT",2009 +"2009-12-26","St. Stephen's Day","AT",2009 +"2010-01-01","New Year's Day","AT",2010 +"2010-01-06","Epiphany","AT",2010 +"2010-04-05","Easter Monday","AT",2010 +"2010-05-01","Labor Day","AT",2010 +"2010-05-13","Ascension Day","AT",2010 +"2010-05-24","Whit Monday","AT",2010 +"2010-06-03","Corpus Christi","AT",2010 +"2010-08-15","Assumption Day","AT",2010 +"2010-10-26","National Day","AT",2010 +"2010-11-01","All Saints' Day","AT",2010 +"2010-12-08","Immaculate Conception","AT",2010 +"2010-12-25","Christmas Day","AT",2010 +"2010-12-26","St. Stephen's Day","AT",2010 +"2011-01-01","New Year's Day","AT",2011 +"2011-01-06","Epiphany","AT",2011 +"2011-04-25","Easter Monday","AT",2011 +"2011-05-01","Labor Day","AT",2011 +"2011-06-02","Ascension Day","AT",2011 +"2011-06-13","Whit Monday","AT",2011 +"2011-06-23","Corpus Christi","AT",2011 +"2011-08-15","Assumption Day","AT",2011 +"2011-10-26","National Day","AT",2011 +"2011-11-01","All Saints' Day","AT",2011 +"2011-12-08","Immaculate Conception","AT",2011 +"2011-12-25","Christmas Day","AT",2011 +"2011-12-26","St. Stephen's Day","AT",2011 +"2012-01-01","New Year's Day","AT",2012 +"2012-01-06","Epiphany","AT",2012 +"2012-04-09","Easter Monday","AT",2012 +"2012-05-01","Labor Day","AT",2012 +"2012-05-17","Ascension Day","AT",2012 +"2012-05-28","Whit Monday","AT",2012 +"2012-06-07","Corpus Christi","AT",2012 +"2012-08-15","Assumption Day","AT",2012 +"2012-10-26","National Day","AT",2012 +"2012-11-01","All Saints' Day","AT",2012 +"2012-12-08","Immaculate Conception","AT",2012 +"2012-12-25","Christmas Day","AT",2012 +"2012-12-26","St. Stephen's Day","AT",2012 +"2013-01-01","New Year's Day","AT",2013 +"2013-01-06","Epiphany","AT",2013 +"2013-04-01","Easter Monday","AT",2013 +"2013-05-01","Labor Day","AT",2013 +"2013-05-09","Ascension Day","AT",2013 +"2013-05-20","Whit Monday","AT",2013 +"2013-05-30","Corpus Christi","AT",2013 +"2013-08-15","Assumption Day","AT",2013 +"2013-10-26","National Day","AT",2013 +"2013-11-01","All Saints' Day","AT",2013 +"2013-12-08","Immaculate Conception","AT",2013 +"2013-12-25","Christmas Day","AT",2013 +"2013-12-26","St. Stephen's Day","AT",2013 +"2014-01-01","New Year's Day","AT",2014 +"2014-01-06","Epiphany","AT",2014 +"2014-04-21","Easter Monday","AT",2014 +"2014-05-01","Labor Day","AT",2014 +"2014-05-29","Ascension Day","AT",2014 +"2014-06-09","Whit Monday","AT",2014 +"2014-06-19","Corpus Christi","AT",2014 +"2014-08-15","Assumption Day","AT",2014 +"2014-10-26","National Day","AT",2014 +"2014-11-01","All Saints' Day","AT",2014 +"2014-12-08","Immaculate Conception","AT",2014 +"2014-12-25","Christmas Day","AT",2014 +"2014-12-26","St. Stephen's Day","AT",2014 +"2015-01-01","New Year's Day","AT",2015 +"2015-01-06","Epiphany","AT",2015 +"2015-04-06","Easter Monday","AT",2015 +"2015-05-01","Labor Day","AT",2015 +"2015-05-14","Ascension Day","AT",2015 +"2015-05-25","Whit Monday","AT",2015 +"2015-06-04","Corpus Christi","AT",2015 +"2015-08-15","Assumption Day","AT",2015 +"2015-10-26","National Day","AT",2015 +"2015-11-01","All Saints' Day","AT",2015 +"2015-12-08","Immaculate Conception","AT",2015 +"2015-12-25","Christmas Day","AT",2015 +"2015-12-26","St. Stephen's Day","AT",2015 +"2016-01-01","New Year's Day","AT",2016 +"2016-01-06","Epiphany","AT",2016 +"2016-03-28","Easter Monday","AT",2016 +"2016-05-01","Labor Day","AT",2016 +"2016-05-05","Ascension Day","AT",2016 +"2016-05-16","Whit Monday","AT",2016 +"2016-05-26","Corpus Christi","AT",2016 +"2016-08-15","Assumption Day","AT",2016 +"2016-10-26","National Day","AT",2016 +"2016-11-01","All Saints' Day","AT",2016 +"2016-12-08","Immaculate Conception","AT",2016 +"2016-12-25","Christmas Day","AT",2016 +"2016-12-26","St. Stephen's Day","AT",2016 +"2017-01-01","New Year's Day","AT",2017 +"2017-01-06","Epiphany","AT",2017 +"2017-04-17","Easter Monday","AT",2017 +"2017-05-01","Labor Day","AT",2017 +"2017-05-25","Ascension Day","AT",2017 +"2017-06-05","Whit Monday","AT",2017 +"2017-06-15","Corpus Christi","AT",2017 +"2017-08-15","Assumption Day","AT",2017 +"2017-10-26","National Day","AT",2017 +"2017-11-01","All Saints' Day","AT",2017 +"2017-12-08","Immaculate Conception","AT",2017 +"2017-12-25","Christmas Day","AT",2017 +"2017-12-26","St. Stephen's Day","AT",2017 +"2018-01-01","New Year's Day","AT",2018 +"2018-01-06","Epiphany","AT",2018 +"2018-04-02","Easter Monday","AT",2018 +"2018-05-01","Labor Day","AT",2018 +"2018-05-10","Ascension Day","AT",2018 +"2018-05-21","Whit Monday","AT",2018 +"2018-05-31","Corpus Christi","AT",2018 +"2018-08-15","Assumption Day","AT",2018 +"2018-10-26","National Day","AT",2018 +"2018-11-01","All Saints' Day","AT",2018 +"2018-12-08","Immaculate Conception","AT",2018 +"2018-12-25","Christmas Day","AT",2018 +"2018-12-26","St. Stephen's Day","AT",2018 +"2019-01-01","New Year's Day","AT",2019 +"2019-01-06","Epiphany","AT",2019 +"2019-04-22","Easter Monday","AT",2019 +"2019-05-01","Labor Day","AT",2019 +"2019-05-30","Ascension Day","AT",2019 +"2019-06-10","Whit Monday","AT",2019 +"2019-06-20","Corpus Christi","AT",2019 +"2019-08-15","Assumption Day","AT",2019 +"2019-10-26","National Day","AT",2019 +"2019-11-01","All Saints' Day","AT",2019 +"2019-12-08","Immaculate Conception","AT",2019 +"2019-12-25","Christmas Day","AT",2019 +"2019-12-26","St. Stephen's Day","AT",2019 +"2020-01-01","New Year's Day","AT",2020 +"2020-01-06","Epiphany","AT",2020 +"2020-04-13","Easter Monday","AT",2020 +"2020-05-01","Labor Day","AT",2020 +"2020-05-21","Ascension Day","AT",2020 +"2020-06-01","Whit Monday","AT",2020 +"2020-06-11","Corpus Christi","AT",2020 +"2020-08-15","Assumption Day","AT",2020 +"2020-10-26","National Day","AT",2020 +"2020-11-01","All Saints' Day","AT",2020 +"2020-12-08","Immaculate Conception","AT",2020 +"2020-12-25","Christmas Day","AT",2020 +"2020-12-26","St. Stephen's Day","AT",2020 +"2021-01-01","New Year's Day","AT",2021 +"2021-01-06","Epiphany","AT",2021 +"2021-04-05","Easter Monday","AT",2021 +"2021-05-01","Labor Day","AT",2021 +"2021-05-13","Ascension Day","AT",2021 +"2021-05-24","Whit Monday","AT",2021 +"2021-06-03","Corpus Christi","AT",2021 +"2021-08-15","Assumption Day","AT",2021 +"2021-10-26","National Day","AT",2021 +"2021-11-01","All Saints' Day","AT",2021 +"2021-12-08","Immaculate Conception","AT",2021 +"2021-12-25","Christmas Day","AT",2021 +"2021-12-26","St. Stephen's Day","AT",2021 +"2022-01-01","New Year's Day","AT",2022 +"2022-01-06","Epiphany","AT",2022 +"2022-04-18","Easter Monday","AT",2022 +"2022-05-01","Labor Day","AT",2022 +"2022-05-26","Ascension Day","AT",2022 +"2022-06-06","Whit Monday","AT",2022 +"2022-06-16","Corpus Christi","AT",2022 +"2022-08-15","Assumption Day","AT",2022 +"2022-10-26","National Day","AT",2022 +"2022-11-01","All Saints' Day","AT",2022 +"2022-12-08","Immaculate Conception","AT",2022 +"2022-12-25","Christmas Day","AT",2022 +"2022-12-26","St. Stephen's Day","AT",2022 +"2023-01-01","New Year's Day","AT",2023 +"2023-01-06","Epiphany","AT",2023 +"2023-04-10","Easter Monday","AT",2023 +"2023-05-01","Labor Day","AT",2023 +"2023-05-18","Ascension Day","AT",2023 +"2023-05-29","Whit Monday","AT",2023 +"2023-06-08","Corpus Christi","AT",2023 +"2023-08-15","Assumption Day","AT",2023 +"2023-10-26","National Day","AT",2023 +"2023-11-01","All Saints' Day","AT",2023 +"2023-12-08","Immaculate Conception","AT",2023 +"2023-12-25","Christmas Day","AT",2023 +"2023-12-26","St. Stephen's Day","AT",2023 +"2024-01-01","New Year's Day","AT",2024 +"2024-01-06","Epiphany","AT",2024 +"2024-04-01","Easter Monday","AT",2024 +"2024-05-01","Labor Day","AT",2024 +"2024-05-09","Ascension Day","AT",2024 +"2024-05-20","Whit Monday","AT",2024 +"2024-05-30","Corpus Christi","AT",2024 +"2024-08-15","Assumption Day","AT",2024 +"2024-10-26","National Day","AT",2024 +"2024-11-01","All Saints' Day","AT",2024 +"2024-12-08","Immaculate Conception","AT",2024 +"2024-12-25","Christmas Day","AT",2024 +"2024-12-26","St. Stephen's Day","AT",2024 +"2025-01-01","New Year's Day","AT",2025 +"2025-01-06","Epiphany","AT",2025 +"2025-04-21","Easter Monday","AT",2025 +"2025-05-01","Labor Day","AT",2025 +"2025-05-29","Ascension Day","AT",2025 +"2025-06-09","Whit Monday","AT",2025 +"2025-06-19","Corpus Christi","AT",2025 +"2025-08-15","Assumption Day","AT",2025 +"2025-10-26","National Day","AT",2025 +"2025-11-01","All Saints' Day","AT",2025 +"2025-12-08","Immaculate Conception","AT",2025 +"2025-12-25","Christmas Day","AT",2025 +"2025-12-26","St. Stephen's Day","AT",2025 +"2026-01-01","New Year's Day","AT",2026 +"2026-01-06","Epiphany","AT",2026 +"2026-04-06","Easter Monday","AT",2026 +"2026-05-01","Labor Day","AT",2026 +"2026-05-14","Ascension Day","AT",2026 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Day","AT",2028 +"2028-05-25","Ascension Day","AT",2028 +"2028-06-05","Whit Monday","AT",2028 +"2028-06-15","Corpus Christi","AT",2028 +"2028-08-15","Assumption Day","AT",2028 +"2028-10-26","National Day","AT",2028 +"2028-11-01","All Saints' Day","AT",2028 +"2028-12-08","Immaculate Conception","AT",2028 +"2028-12-25","Christmas Day","AT",2028 +"2028-12-26","St. Stephen's Day","AT",2028 +"2029-01-01","New Year's Day","AT",2029 +"2029-01-06","Epiphany","AT",2029 +"2029-04-02","Easter Monday","AT",2029 +"2029-05-01","Labor Day","AT",2029 +"2029-05-10","Ascension Day","AT",2029 +"2029-05-21","Whit Monday","AT",2029 +"2029-05-31","Corpus Christi","AT",2029 +"2029-08-15","Assumption Day","AT",2029 +"2029-10-26","National Day","AT",2029 +"2029-11-01","All Saints' Day","AT",2029 +"2029-12-08","Immaculate Conception","AT",2029 +"2029-12-25","Christmas Day","AT",2029 +"2029-12-26","St. Stephen's Day","AT",2029 +"2030-01-01","New Year's Day","AT",2030 +"2030-01-06","Epiphany","AT",2030 +"2030-04-22","Easter Monday","AT",2030 +"2030-05-01","Labor Day","AT",2030 +"2030-05-30","Ascension Day","AT",2030 +"2030-06-10","Whit Monday","AT",2030 +"2030-06-20","Corpus Christi","AT",2030 +"2030-08-15","Assumption Day","AT",2030 +"2030-10-26","National Day","AT",2030 +"2030-11-01","All Saints' Day","AT",2030 +"2030-12-08","Immaculate Conception","AT",2030 +"2030-12-25","Christmas Day","AT",2030 +"2030-12-26","St. Stephen's Day","AT",2030 +"2031-01-01","New Year's Day","AT",2031 +"2031-01-06","Epiphany","AT",2031 +"2031-04-14","Easter Monday","AT",2031 +"2031-05-01","Labor Day","AT",2031 +"2031-05-22","Ascension Day","AT",2031 +"2031-06-02","Whit Monday","AT",2031 +"2031-06-12","Corpus Christi","AT",2031 +"2031-08-15","Assumption Day","AT",2031 +"2031-10-26","National Day","AT",2031 +"2031-11-01","All Saints' Day","AT",2031 +"2031-12-08","Immaculate Conception","AT",2031 +"2031-12-25","Christmas Day","AT",2031 +"2031-12-26","St. Stephen's Day","AT",2031 +"2032-01-01","New Year's Day","AT",2032 +"2032-01-06","Epiphany","AT",2032 +"2032-03-29","Easter Monday","AT",2032 +"2032-05-01","Labor Day","AT",2032 +"2032-05-06","Ascension Day","AT",2032 +"2032-05-17","Whit Monday","AT",2032 +"2032-05-27","Corpus Christi","AT",2032 +"2032-08-15","Assumption Day","AT",2032 +"2032-10-26","National Day","AT",2032 +"2032-11-01","All Saints' Day","AT",2032 +"2032-12-08","Immaculate Conception","AT",2032 +"2032-12-25","Christmas Day","AT",2032 +"2032-12-26","St. Stephen's Day","AT",2032 +"2033-01-01","New Year's Day","AT",2033 +"2033-01-06","Epiphany","AT",2033 +"2033-04-18","Easter Monday","AT",2033 +"2033-05-01","Labor Day","AT",2033 +"2033-05-26","Ascension Day","AT",2033 +"2033-06-06","Whit Monday","AT",2033 +"2033-06-16","Corpus Christi","AT",2033 +"2033-08-15","Assumption Day","AT",2033 +"2033-10-26","National Day","AT",2033 +"2033-11-01","All Saints' Day","AT",2033 +"2033-12-08","Immaculate Conception","AT",2033 +"2033-12-25","Christmas Day","AT",2033 +"2033-12-26","St. Stephen's Day","AT",2033 +"2034-01-01","New Year's Day","AT",2034 +"2034-01-06","Epiphany","AT",2034 +"2034-04-10","Easter Monday","AT",2034 +"2034-05-01","Labor Day","AT",2034 +"2034-05-18","Ascension Day","AT",2034 +"2034-05-29","Whit Monday","AT",2034 +"2034-06-08","Corpus Christi","AT",2034 +"2034-08-15","Assumption Day","AT",2034 +"2034-10-26","National Day","AT",2034 +"2034-11-01","All Saints' Day","AT",2034 +"2034-12-08","Immaculate Conception","AT",2034 +"2034-12-25","Christmas Day","AT",2034 +"2034-12-26","St. Stephen's Day","AT",2034 +"2035-01-01","New Year's Day","AT",2035 +"2035-01-06","Epiphany","AT",2035 +"2035-03-26","Easter Monday","AT",2035 +"2035-05-01","Labor Day","AT",2035 +"2035-05-03","Ascension Day","AT",2035 +"2035-05-14","Whit Monday","AT",2035 +"2035-05-24","Corpus Christi","AT",2035 +"2035-08-15","Assumption Day","AT",2035 +"2035-10-26","National Day","AT",2035 +"2035-11-01","All Saints' Day","AT",2035 +"2035-12-08","Immaculate Conception","AT",2035 +"2035-12-25","Christmas Day","AT",2035 +"2035-12-26","St. Stephen's Day","AT",2035 +"2036-01-01","New Year's Day","AT",2036 +"2036-01-06","Epiphany","AT",2036 +"2036-04-14","Easter Monday","AT",2036 +"2036-05-01","Labor Day","AT",2036 +"2036-05-22","Ascension Day","AT",2036 +"2036-06-02","Whit Monday","AT",2036 +"2036-06-12","Corpus Christi","AT",2036 +"2036-08-15","Assumption Day","AT",2036 +"2036-10-26","National Day","AT",2036 +"2036-11-01","All Saints' Day","AT",2036 +"2036-12-08","Immaculate Conception","AT",2036 +"2036-12-25","Christmas Day","AT",2036 +"2036-12-26","St. Stephen's Day","AT",2036 +"2037-01-01","New Year's Day","AT",2037 +"2037-01-06","Epiphany","AT",2037 +"2037-04-06","Easter Monday","AT",2037 +"2037-05-01","Labor Day","AT",2037 +"2037-05-14","Ascension Day","AT",2037 +"2037-05-25","Whit Monday","AT",2037 +"2037-06-04","Corpus Christi","AT",2037 +"2037-08-15","Assumption Day","AT",2037 +"2037-10-26","National Day","AT",2037 +"2037-11-01","All Saints' Day","AT",2037 +"2037-12-08","Immaculate Conception","AT",2037 +"2037-12-25","Christmas Day","AT",2037 +"2037-12-26","St. Stephen's Day","AT",2037 +"2038-01-01","New Year's Day","AT",2038 +"2038-01-06","Epiphany","AT",2038 +"2038-04-26","Easter Monday","AT",2038 +"2038-05-01","Labor Day","AT",2038 +"2038-06-03","Ascension Day","AT",2038 +"2038-06-14","Whit Monday","AT",2038 +"2038-06-24","Corpus Christi","AT",2038 +"2038-08-15","Assumption Day","AT",2038 +"2038-10-26","National Day","AT",2038 +"2038-11-01","All Saints' Day","AT",2038 +"2038-12-08","Immaculate Conception","AT",2038 +"2038-12-25","Christmas Day","AT",2038 +"2038-12-26","St. Stephen's Day","AT",2038 +"2039-01-01","New Year's Day","AT",2039 +"2039-01-06","Epiphany","AT",2039 +"2039-04-11","Easter Monday","AT",2039 +"2039-05-01","Labor Day","AT",2039 +"2039-05-19","Ascension Day","AT",2039 +"2039-05-30","Whit Monday","AT",2039 +"2039-06-09","Corpus Christi","AT",2039 +"2039-08-15","Assumption Day","AT",2039 +"2039-10-26","National Day","AT",2039 +"2039-11-01","All Saints' Day","AT",2039 +"2039-12-08","Immaculate Conception","AT",2039 +"2039-12-25","Christmas Day","AT",2039 +"2039-12-26","St. Stephen's Day","AT",2039 +"2040-01-01","New Year's Day","AT",2040 +"2040-01-06","Epiphany","AT",2040 +"2040-04-02","Easter Monday","AT",2040 +"2040-05-01","Labor Day","AT",2040 +"2040-05-10","Ascension Day","AT",2040 +"2040-05-21","Whit Monday","AT",2040 +"2040-05-31","Corpus Christi","AT",2040 +"2040-08-15","Assumption Day","AT",2040 +"2040-10-26","National Day","AT",2040 +"2040-11-01","All Saints' Day","AT",2040 +"2040-12-08","Immaculate Conception","AT",2040 +"2040-12-25","Christmas Day","AT",2040 +"2040-12-26","St. Stephen's Day","AT",2040 +"2041-01-01","New Year's Day","AT",2041 +"2041-01-06","Epiphany","AT",2041 +"2041-04-22","Easter Monday","AT",2041 +"2041-05-01","Labor Day","AT",2041 +"2041-05-30","Ascension Day","AT",2041 +"2041-06-10","Whit Monday","AT",2041 +"2041-06-20","Corpus Christi","AT",2041 +"2041-08-15","Assumption Day","AT",2041 +"2041-10-26","National Day","AT",2041 +"2041-11-01","All Saints' Day","AT",2041 +"2041-12-08","Immaculate Conception","AT",2041 +"2041-12-25","Christmas Day","AT",2041 +"2041-12-26","St. Stephen's Day","AT",2041 +"2042-01-01","New Year's Day","AT",2042 +"2042-01-06","Epiphany","AT",2042 +"2042-04-07","Easter Monday","AT",2042 +"2042-05-01","Labor Day","AT",2042 +"2042-05-15","Ascension Day","AT",2042 +"2042-05-26","Whit Monday","AT",2042 +"2042-06-05","Corpus Christi","AT",2042 +"2042-08-15","Assumption Day","AT",2042 +"2042-10-26","National Day","AT",2042 +"2042-11-01","All Saints' Day","AT",2042 +"2042-12-08","Immaculate Conception","AT",2042 +"2042-12-25","Christmas Day","AT",2042 +"2042-12-26","St. Stephen's Day","AT",2042 +"2043-01-01","New Year's Day","AT",2043 +"2043-01-06","Epiphany","AT",2043 +"2043-03-30","Easter Monday","AT",2043 +"2043-05-01","Labor Day","AT",2043 +"2043-05-07","Ascension Day","AT",2043 +"2043-05-18","Whit Monday","AT",2043 +"2043-05-28","Corpus Christi","AT",2043 +"2043-08-15","Assumption Day","AT",2043 +"2043-10-26","National Day","AT",2043 +"2043-11-01","All Saints' Day","AT",2043 +"2043-12-08","Immaculate Conception","AT",2043 +"2043-12-25","Christmas Day","AT",2043 +"2043-12-26","St. Stephen's Day","AT",2043 +"2044-01-01","New Year's Day","AT",2044 +"2044-01-06","Epiphany","AT",2044 +"2044-04-18","Easter Monday","AT",2044 +"2044-05-01","Labor Day","AT",2044 +"2044-05-26","Ascension Day","AT",2044 +"2044-06-06","Whit Monday","AT",2044 +"2044-06-16","Corpus Christi","AT",2044 +"2044-08-15","Assumption Day","AT",2044 +"2044-10-26","National Day","AT",2044 +"2044-11-01","All Saints' Day","AT",2044 +"2044-12-08","Immaculate Conception","AT",2044 +"2044-12-25","Christmas Day","AT",2044 +"2044-12-26","St. Stephen's Day","AT",2044 +"1995-01-01","New Year's Day","AU",1995 +"1995-01-02","New Year's Day (Observed)","AU",1995 +"1995-01-26","Australia Day","AU",1995 +"1995-04-14","Good Friday","AU",1995 +"1995-04-17","Easter Monday","AU",1995 +"1995-04-25","Anzac Day","AU",1995 +"1995-12-25","Christmas Day","AU",1995 +"1995-12-26","Boxing Day","AU",1995 +"1996-01-01","New Year's Day","AU",1996 +"1996-01-26","Australia Day","AU",1996 +"1996-04-05","Good Friday","AU",1996 +"1996-04-08","Easter Monday","AU",1996 +"1996-04-25","Anzac Day","AU",1996 +"1996-12-25","Christmas Day","AU",1996 +"1996-12-26","Boxing Day","AU",1996 +"1997-01-01","New Year's Day","AU",1997 +"1997-01-26","Australia Day","AU",1997 +"1997-01-27","Australia Day (Observed)","AU",1997 +"1997-03-28","Good Friday","AU",1997 +"1997-03-31","Easter Monday","AU",1997 +"1997-04-25","Anzac Day","AU",1997 +"1997-12-25","Christmas Day","AU",1997 +"1997-12-26","Boxing Day","AU",1997 +"1998-01-01","New Year's Day","AU",1998 +"1998-01-26","Australia Day","AU",1998 +"1998-04-10","Good Friday","AU",1998 +"1998-04-13","Easter Monday","AU",1998 +"1998-04-25","Anzac Day","AU",1998 +"1998-12-25","Christmas Day","AU",1998 +"1998-12-26","Boxing Day","AU",1998 +"1998-12-28","Boxing Day (Observed)","AU",1998 +"1999-01-01","New Year's Day","AU",1999 +"1999-01-26","Australia Day","AU",1999 +"1999-04-02","Good Friday","AU",1999 +"1999-04-05","Easter Monday","AU",1999 +"1999-04-25","Anzac Day","AU",1999 +"1999-12-25","Christmas Day","AU",1999 +"1999-12-26","Boxing Day","AU",1999 +"1999-12-27","Christmas Day (Observed)","AU",1999 +"1999-12-28","Boxing Day (Observed)","AU",1999 +"2000-01-01","New Year's Day","AU",2000 +"2000-01-03","New Year's Day (Observed)","AU",2000 +"2000-01-26","Australia Day","AU",2000 +"2000-04-21","Good Friday","AU",2000 +"2000-04-24","Easter Monday","AU",2000 +"2000-04-25","Anzac Day","AU",2000 +"2000-12-25","Christmas Day","AU",2000 +"2000-12-26","Boxing Day","AU",2000 +"2001-01-01","New Year's Day","AU",2001 +"2001-01-26","Australia Day","AU",2001 +"2001-04-13","Good Friday","AU",2001 +"2001-04-16","Easter Monday","AU",2001 +"2001-04-25","Anzac Day","AU",2001 +"2001-12-25","Christmas Day","AU",2001 +"2001-12-26","Boxing Day","AU",2001 +"2002-01-01","New Year's Day","AU",2002 +"2002-01-26","Australia Day","AU",2002 +"2002-01-28","Australia Day (Observed)","AU",2002 +"2002-03-29","Good Friday","AU",2002 +"2002-04-01","Easter Monday","AU",2002 +"2002-04-25","Anzac Day","AU",2002 +"2002-12-25","Christmas Day","AU",2002 +"2002-12-26","Boxing Day","AU",2002 +"2003-01-01","New Year's Day","AU",2003 +"2003-01-26","Australia Day","AU",2003 +"2003-01-27","Australia Day (Observed)","AU",2003 +"2003-04-18","Good Friday","AU",2003 +"2003-04-21","Easter Monday","AU",2003 +"2003-04-25","Anzac Day","AU",2003 +"2003-12-25","Christmas Day","AU",2003 +"2003-12-26","Boxing Day","AU",2003 +"2004-01-01","New Year's Day","AU",2004 +"2004-01-26","Australia Day","AU",2004 +"2004-04-09","Good Friday","AU",2004 +"2004-04-12","Easter Monday","AU",2004 +"2004-04-25","Anzac Day","AU",2004 +"2004-12-25","Christmas Day","AU",2004 +"2004-12-26","Boxing Day","AU",2004 +"2004-12-27","Christmas Day (Observed)","AU",2004 +"2004-12-28","Boxing Day (Observed)","AU",2004 +"2005-01-01","New Year's Day","AU",2005 +"2005-01-03","New Year's Day (Observed)","AU",2005 +"2005-01-26","Australia Day","AU",2005 +"2005-03-25","Good Friday","AU",2005 +"2005-03-28","Easter Monday","AU",2005 +"2005-04-25","Anzac Day","AU",2005 +"2005-12-25","Christmas Day","AU",2005 +"2005-12-26","Boxing Day","AU",2005 +"2005-12-27","Christmas Day (Observed)","AU",2005 +"2006-01-01","New Year's Day","AU",2006 +"2006-01-02","New Year's Day (Observed)","AU",2006 +"2006-01-26","Australia Day","AU",2006 +"2006-04-14","Good Friday","AU",2006 +"2006-04-17","Easter Monday","AU",2006 +"2006-04-25","Anzac Day","AU",2006 +"2006-12-25","Christmas Day","AU",2006 +"2006-12-26","Boxing Day","AU",2006 +"2007-01-01","New Year's Day","AU",2007 +"2007-01-26","Australia Day","AU",2007 +"2007-04-06","Good Friday","AU",2007 +"2007-04-09","Easter Monday","AU",2007 +"2007-04-25","Anzac Day","AU",2007 +"2007-12-25","Christmas Day","AU",2007 +"2007-12-26","Boxing Day","AU",2007 +"2008-01-01","New Year's Day","AU",2008 +"2008-01-26","Australia Day","AU",2008 +"2008-01-28","Australia Day (Observed)","AU",2008 +"2008-03-21","Good Friday","AU",2008 +"2008-03-24","Easter Monday","AU",2008 +"2008-04-25","Anzac Day","AU",2008 +"2008-12-25","Christmas Day","AU",2008 +"2008-12-26","Boxing Day","AU",2008 +"2009-01-01","New Year's Day","AU",2009 +"2009-01-26","Australia Day","AU",2009 +"2009-04-10","Good Friday","AU",2009 +"2009-04-13","Easter Monday","AU",2009 +"2009-04-25","Anzac Day","AU",2009 +"2009-12-25","Christmas Day","AU",2009 +"2009-12-26","Boxing Day","AU",2009 +"2009-12-28","Boxing Day (Observed)","AU",2009 +"2010-01-01","New Year's Day","AU",2010 +"2010-01-26","Australia Day","AU",2010 +"2010-04-02","Good Friday","AU",2010 +"2010-04-05","Easter Monday","AU",2010 +"2010-04-25","Anzac Day","AU",2010 +"2010-12-25","Christmas Day","AU",2010 +"2010-12-26","Boxing Day","AU",2010 +"2010-12-27","Christmas Day (Observed)","AU",2010 +"2010-12-28","Boxing Day (Observed)","AU",2010 +"2011-01-01","New Year's Day","AU",2011 +"2011-01-03","New Year's Day (Observed)","AU",2011 +"2011-01-26","Australia Day","AU",2011 +"2011-04-22","Good Friday","AU",2011 +"2011-04-25","Anzac Day","AU",2011 +"2011-04-25","Easter Monday","AU",2011 +"2011-12-25","Christmas Day","AU",2011 +"2011-12-26","Boxing Day","AU",2011 +"2011-12-27","Christmas Day (Observed)","AU",2011 +"2012-01-01","New Year's Day","AU",2012 +"2012-01-02","New Year's Day (Observed)","AU",2012 +"2012-01-26","Australia Day","AU",2012 +"2012-04-06","Good Friday","AU",2012 +"2012-04-09","Easter Monday","AU",2012 +"2012-04-25","Anzac Day","AU",2012 +"2012-12-25","Christmas Day","AU",2012 +"2012-12-26","Boxing Day","AU",2012 +"2013-01-01","New Year's Day","AU",2013 +"2013-01-26","Australia Day","AU",2013 +"2013-01-28","Australia Day (Observed)","AU",2013 +"2013-03-29","Good Friday","AU",2013 +"2013-04-01","Easter Monday","AU",2013 +"2013-04-25","Anzac Day","AU",2013 +"2013-12-25","Christmas Day","AU",2013 +"2013-12-26","Boxing Day","AU",2013 +"2014-01-01","New Year's Day","AU",2014 +"2014-01-26","Australia Day","AU",2014 +"2014-01-27","Australia Day (Observed)","AU",2014 +"2014-04-18","Good Friday","AU",2014 +"2014-04-21","Easter Monday","AU",2014 +"2014-04-25","Anzac Day","AU",2014 +"2014-12-25","Christmas Day","AU",2014 +"2014-12-26","Boxing Day","AU",2014 +"2015-01-01","New Year's Day","AU",2015 +"2015-01-26","Australia Day","AU",2015 +"2015-04-03","Good Friday","AU",2015 +"2015-04-06","Easter Monday","AU",2015 +"2015-04-25","Anzac Day","AU",2015 +"2015-12-25","Christmas Day","AU",2015 +"2015-12-26","Boxing Day","AU",2015 +"2015-12-28","Boxing Day (Observed)","AU",2015 +"2016-01-01","New Year's Day","AU",2016 +"2016-01-26","Australia Day","AU",2016 +"2016-03-25","Good Friday","AU",2016 +"2016-03-28","Easter Monday","AU",2016 +"2016-04-25","Anzac Day","AU",2016 +"2016-12-25","Christmas Day","AU",2016 +"2016-12-26","Boxing Day","AU",2016 +"2016-12-27","Christmas Day (Observed)","AU",2016 +"2017-01-01","New Year's Day","AU",2017 +"2017-01-02","New Year's Day (Observed)","AU",2017 +"2017-01-26","Australia Day","AU",2017 +"2017-04-14","Good Friday","AU",2017 +"2017-04-17","Easter Monday","AU",2017 +"2017-04-25","Anzac Day","AU",2017 +"2017-12-25","Christmas Day","AU",2017 +"2017-12-26","Boxing Day","AU",2017 +"2018-01-01","New Year's Day","AU",2018 +"2018-01-26","Australia Day","AU",2018 +"2018-03-30","Good Friday","AU",2018 +"2018-04-02","Easter Monday","AU",2018 +"2018-04-25","Anzac Day","AU",2018 +"2018-12-25","Christmas Day","AU",2018 +"2018-12-26","Boxing Day","AU",2018 +"2019-01-01","New Year's Day","AU",2019 +"2019-01-26","Australia Day","AU",2019 +"2019-01-28","Australia Day (Observed)","AU",2019 +"2019-04-19","Good Friday","AU",2019 +"2019-04-22","Easter Monday","AU",2019 +"2019-04-25","Anzac Day","AU",2019 +"2019-12-25","Christmas Day","AU",2019 +"2019-12-26","Boxing Day","AU",2019 +"2020-01-01","New Year's Day","AU",2020 +"2020-01-26","Australia Day","AU",2020 +"2020-01-27","Australia Day (Observed)","AU",2020 +"2020-04-10","Good Friday","AU",2020 +"2020-04-13","Easter Monday","AU",2020 +"2020-04-25","Anzac Day","AU",2020 +"2020-12-25","Christmas Day","AU",2020 +"2020-12-26","Boxing Day","AU",2020 +"2020-12-28","Boxing Day (Observed)","AU",2020 +"2021-01-01","New Year's Day","AU",2021 +"2021-01-26","Australia Day","AU",2021 +"2021-04-02","Good Friday","AU",2021 +"2021-04-05","Easter Monday","AU",2021 +"2021-04-25","Anzac Day","AU",2021 +"2021-12-25","Christmas Day","AU",2021 +"2021-12-26","Boxing Day","AU",2021 +"2021-12-27","Christmas Day (Observed)","AU",2021 +"2021-12-28","Boxing Day (Observed)","AU",2021 +"2022-01-01","New Year's Day","AU",2022 +"2022-01-03","New Year's Day (Observed)","AU",2022 +"2022-01-26","Australia Day","AU",2022 +"2022-04-15","Good Friday","AU",2022 +"2022-04-18","Easter Monday","AU",2022 +"2022-04-25","Anzac Day","AU",2022 +"2022-09-22","National Day of Mourning for Queen Elizabeth II","AU",2022 +"2022-12-25","Christmas Day","AU",2022 +"2022-12-26","Boxing Day","AU",2022 +"2022-12-27","Christmas Day (Observed)","AU",2022 +"2023-01-01","New Year's Day","AU",2023 +"2023-01-02","New Year's Day (Observed)","AU",2023 +"2023-01-26","Australia Day","AU",2023 +"2023-04-07","Good Friday","AU",2023 +"2023-04-10","Easter Monday","AU",2023 +"2023-04-25","Anzac Day","AU",2023 +"2023-12-25","Christmas Day","AU",2023 +"2023-12-26","Boxing Day","AU",2023 +"2024-01-01","New Year's Day","AU",2024 +"2024-01-26","Australia Day","AU",2024 +"2024-03-29","Good Friday","AU",2024 +"2024-04-01","Easter Monday","AU",2024 +"2024-04-25","Anzac Day","AU",2024 +"2024-12-25","Christmas Day","AU",2024 +"2024-12-26","Boxing Day","AU",2024 +"2025-01-01","New Year's Day","AU",2025 +"2025-01-26","Australia Day","AU",2025 +"2025-01-27","Australia Day (Observed)","AU",2025 +"2025-04-18","Good Friday","AU",2025 +"2025-04-21","Easter Monday","AU",2025 +"2025-04-25","Anzac Day","AU",2025 +"2025-12-25","Christmas Day","AU",2025 +"2025-12-26","Boxing Day","AU",2025 +"2026-01-01","New Year's Day","AU",2026 +"2026-01-26","Australia Day","AU",2026 +"2026-04-03","Good Friday","AU",2026 +"2026-04-06","Easter Monday","AU",2026 +"2026-04-25","Anzac Day","AU",2026 +"2026-12-25","Christmas Day","AU",2026 +"2026-12-26","Boxing Day","AU",2026 +"2026-12-28","Boxing Day (Observed)","AU",2026 +"2027-01-01","New Year's Day","AU",2027 +"2027-01-26","Australia Day","AU",2027 +"2027-03-26","Good Friday","AU",2027 +"2027-03-29","Easter Monday","AU",2027 +"2027-04-25","Anzac Day","AU",2027 +"2027-12-25","Christmas Day","AU",2027 +"2027-12-26","Boxing Day","AU",2027 +"2027-12-27","Christmas Day (Observed)","AU",2027 +"2027-12-28","Boxing Day (Observed)","AU",2027 +"2028-01-01","New Year's Day","AU",2028 +"2028-01-03","New Year's Day (Observed)","AU",2028 +"2028-01-26","Australia Day","AU",2028 +"2028-04-14","Good Friday","AU",2028 +"2028-04-17","Easter Monday","AU",2028 +"2028-04-25","Anzac Day","AU",2028 +"2028-12-25","Christmas Day","AU",2028 +"2028-12-26","Boxing Day","AU",2028 +"2029-01-01","New Year's Day","AU",2029 +"2029-01-26","Australia Day","AU",2029 +"2029-03-30","Good Friday","AU",2029 +"2029-04-02","Easter Monday","AU",2029 +"2029-04-25","Anzac Day","AU",2029 +"2029-12-25","Christmas Day","AU",2029 +"2029-12-26","Boxing Day","AU",2029 +"2030-01-01","New Year's Day","AU",2030 +"2030-01-26","Australia Day","AU",2030 +"2030-01-28","Australia Day (Observed)","AU",2030 +"2030-04-19","Good Friday","AU",2030 +"2030-04-22","Easter Monday","AU",2030 +"2030-04-25","Anzac Day","AU",2030 +"2030-12-25","Christmas Day","AU",2030 +"2030-12-26","Boxing Day","AU",2030 +"2031-01-01","New Year's Day","AU",2031 +"2031-01-26","Australia Day","AU",2031 +"2031-01-27","Australia Day (Observed)","AU",2031 +"2031-04-11","Good Friday","AU",2031 +"2031-04-14","Easter Monday","AU",2031 +"2031-04-25","Anzac Day","AU",2031 +"2031-12-25","Christmas Day","AU",2031 +"2031-12-26","Boxing Day","AU",2031 +"2032-01-01","New Year's Day","AU",2032 +"2032-01-26","Australia Day","AU",2032 +"2032-03-26","Good Friday","AU",2032 +"2032-03-29","Easter Monday","AU",2032 +"2032-04-25","Anzac Day","AU",2032 +"2032-12-25","Christmas Day","AU",2032 +"2032-12-26","Boxing Day","AU",2032 +"2032-12-27","Christmas Day (Observed)","AU",2032 +"2032-12-28","Boxing Day (Observed)","AU",2032 +"2033-01-01","New Year's Day","AU",2033 +"2033-01-03","New Year's Day (Observed)","AU",2033 +"2033-01-26","Australia Day","AU",2033 +"2033-04-15","Good Friday","AU",2033 +"2033-04-18","Easter Monday","AU",2033 +"2033-04-25","Anzac Day","AU",2033 +"2033-12-25","Christmas Day","AU",2033 +"2033-12-26","Boxing Day","AU",2033 +"2033-12-27","Christmas Day (Observed)","AU",2033 +"2034-01-01","New Year's Day","AU",2034 +"2034-01-02","New Year's Day (Observed)","AU",2034 +"2034-01-26","Australia Day","AU",2034 +"2034-04-07","Good Friday","AU",2034 +"2034-04-10","Easter Monday","AU",2034 +"2034-04-25","Anzac Day","AU",2034 +"2034-12-25","Christmas Day","AU",2034 +"2034-12-26","Boxing Day","AU",2034 +"2035-01-01","New Year's Day","AU",2035 +"2035-01-26","Australia Day","AU",2035 +"2035-03-23","Good Friday","AU",2035 +"2035-03-26","Easter Monday","AU",2035 +"2035-04-25","Anzac Day","AU",2035 +"2035-12-25","Christmas Day","AU",2035 +"2035-12-26","Boxing Day","AU",2035 +"2036-01-01","New Year's Day","AU",2036 +"2036-01-26","Australia Day","AU",2036 +"2036-01-28","Australia Day (Observed)","AU",2036 +"2036-04-11","Good Friday","AU",2036 +"2036-04-14","Easter Monday","AU",2036 +"2036-04-25","Anzac Day","AU",2036 +"2036-12-25","Christmas Day","AU",2036 +"2036-12-26","Boxing Day","AU",2036 +"2037-01-01","New Year's Day","AU",2037 +"2037-01-26","Australia Day","AU",2037 +"2037-04-03","Good Friday","AU",2037 +"2037-04-06","Easter Monday","AU",2037 +"2037-04-25","Anzac Day","AU",2037 +"2037-12-25","Christmas Day","AU",2037 +"2037-12-26","Boxing Day","AU",2037 +"2037-12-28","Boxing Day (Observed)","AU",2037 +"2038-01-01","New Year's Day","AU",2038 +"2038-01-26","Australia Day","AU",2038 +"2038-04-23","Good Friday","AU",2038 +"2038-04-25","Anzac Day","AU",2038 +"2038-04-26","Easter Monday","AU",2038 +"2038-12-25","Christmas Day","AU",2038 +"2038-12-26","Boxing Day","AU",2038 +"2038-12-27","Christmas Day (Observed)","AU",2038 +"2038-12-28","Boxing Day (Observed)","AU",2038 +"2039-01-01","New Year's Day","AU",2039 +"2039-01-03","New Year's Day (Observed)","AU",2039 +"2039-01-26","Australia Day","AU",2039 +"2039-04-08","Good Friday","AU",2039 +"2039-04-11","Easter Monday","AU",2039 +"2039-04-25","Anzac Day","AU",2039 +"2039-12-25","Christmas Day","AU",2039 +"2039-12-26","Boxing Day","AU",2039 +"2039-12-27","Christmas Day (Observed)","AU",2039 +"2040-01-01","New Year's Day","AU",2040 +"2040-01-02","New Year's Day (Observed)","AU",2040 +"2040-01-26","Australia Day","AU",2040 +"2040-03-30","Good Friday","AU",2040 +"2040-04-02","Easter Monday","AU",2040 +"2040-04-25","Anzac Day","AU",2040 +"2040-12-25","Christmas Day","AU",2040 +"2040-12-26","Boxing Day","AU",2040 +"2041-01-01","New Year's Day","AU",2041 +"2041-01-26","Australia Day","AU",2041 +"2041-01-28","Australia Day (Observed)","AU",2041 +"2041-04-19","Good Friday","AU",2041 +"2041-04-22","Easter Monday","AU",2041 +"2041-04-25","Anzac Day","AU",2041 +"2041-12-25","Christmas Day","AU",2041 +"2041-12-26","Boxing Day","AU",2041 +"2042-01-01","New Year's Day","AU",2042 +"2042-01-26","Australia Day","AU",2042 +"2042-01-27","Australia Day (Observed)","AU",2042 +"2042-04-04","Good Friday","AU",2042 +"2042-04-07","Easter Monday","AU",2042 +"2042-04-25","Anzac Day","AU",2042 +"2042-12-25","Christmas Day","AU",2042 +"2042-12-26","Boxing Day","AU",2042 +"2043-01-01","New Year's Day","AU",2043 +"2043-01-26","Australia Day","AU",2043 +"2043-03-27","Good Friday","AU",2043 +"2043-03-30","Easter Monday","AU",2043 +"2043-04-25","Anzac Day","AU",2043 +"2043-12-25","Christmas Day","AU",2043 +"2043-12-26","Boxing Day","AU",2043 +"2043-12-28","Boxing Day (Observed)","AU",2043 +"2044-01-01","New Year's Day","AU",2044 +"2044-01-26","Australia Day","AU",2044 +"2044-04-15","Good Friday","AU",2044 +"2044-04-18","Easter Monday","AU",2044 +"2044-04-25","Anzac Day","AU",2044 +"2044-12-25","Christmas Day","AU",2044 +"2044-12-26","Boxing Day","AU",2044 +"2044-12-27","Christmas Day (Observed)","AU",2044 +"1995-01-01","Ana Nobo [New Year's Day]","AW",1995 +"1995-01-25","Dia Di Betico [Betico Day]","AW",1995 +"1995-02-27","Dialuna di Carnaval [Carnaval Monday]","AW",1995 +"1995-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",1995 +"1995-04-14","Bierna Santo [Good Friday]","AW",1995 +"1995-04-17","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",1995 +"1995-04-29","Ana di La Reina [Queen's Day]","AW",1995 +"1995-05-01","Dia di Obrero [Labour Day]","AW",1995 +"1995-05-25","Dia di Asuncion [Ascension Day]","AW",1995 +"1995-12-25","Pasco di Nacemento [Christmas]","AW",1995 +"1995-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",1995 +"1996-01-01","Ana Nobo [New Year's Day]","AW",1996 +"1996-01-25","Dia Di Betico [Betico Day]","AW",1996 +"1996-02-19","Dialuna di Carnaval [Carnaval Monday]","AW",1996 +"1996-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",1996 +"1996-04-05","Bierna Santo [Good Friday]","AW",1996 +"1996-04-08","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",1996 +"1996-04-30","Ana di La Reina [Queen's Day]","AW",1996 +"1996-05-01","Dia di Obrero [Labour Day]","AW",1996 +"1996-05-16","Dia di Asuncion [Ascension Day]","AW",1996 +"1996-12-25","Pasco di Nacemento [Christmas]","AW",1996 +"1996-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",1996 +"1997-01-01","Ana Nobo [New Year's Day]","AW",1997 +"1997-01-25","Dia Di Betico [Betico Day]","AW",1997 +"1997-02-10","Dialuna di Carnaval [Carnaval Monday]","AW",1997 +"1997-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",1997 +"1997-03-28","Bierna Santo [Good Friday]","AW",1997 +"1997-03-31","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",1997 +"1997-04-30","Ana di La Reina [Queen's Day]","AW",1997 +"1997-05-01","Dia di Obrero [Labour Day]","AW",1997 +"1997-05-08","Dia di Asuncion [Ascension Day]","AW",1997 +"1997-12-25","Pasco di Nacemento [Christmas]","AW",1997 +"1997-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",1997 +"1998-01-01","Ana Nobo [New Year's Day]","AW",1998 +"1998-01-25","Dia Di Betico [Betico Day]","AW",1998 +"1998-02-23","Dialuna di Carnaval [Carnaval Monday]","AW",1998 +"1998-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",1998 +"1998-04-10","Bierna Santo [Good Friday]","AW",1998 +"1998-04-13","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",1998 +"1998-04-30","Ana di La Reina [Queen's Day]","AW",1998 +"1998-05-01","Dia di Obrero [Labour Day]","AW",1998 +"1998-05-21","Dia di Asuncion [Ascension Day]","AW",1998 +"1998-12-25","Pasco di Nacemento [Christmas]","AW",1998 +"1998-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",1998 +"1999-01-01","Ana Nobo [New Year's Day]","AW",1999 +"1999-01-25","Dia Di Betico [Betico Day]","AW",1999 +"1999-02-15","Dialuna di Carnaval [Carnaval Monday]","AW",1999 +"1999-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",1999 +"1999-04-02","Bierna Santo [Good Friday]","AW",1999 +"1999-04-05","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",1999 +"1999-04-30","Ana di La Reina [Queen's Day]","AW",1999 +"1999-05-01","Dia di Obrero [Labour Day]","AW",1999 +"1999-05-13","Dia di Asuncion [Ascension Day]","AW",1999 +"1999-12-25","Pasco di Nacemento [Christmas]","AW",1999 +"1999-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",1999 +"2000-01-01","Ana Nobo [New Year's Day]","AW",2000 +"2000-01-25","Dia Di Betico [Betico Day]","AW",2000 +"2000-03-06","Dialuna di Carnaval [Carnaval Monday]","AW",2000 +"2000-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2000 +"2000-04-21","Bierna Santo [Good Friday]","AW",2000 +"2000-04-24","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2000 +"2000-04-29","Ana di La Reina [Queen's Day]","AW",2000 +"2000-05-01","Dia di Obrero [Labour Day]","AW",2000 +"2000-06-01","Dia di Asuncion [Ascension Day]","AW",2000 +"2000-12-25","Pasco di Nacemento [Christmas]","AW",2000 +"2000-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2000 +"2001-01-01","Ana Nobo [New Year's Day]","AW",2001 +"2001-01-25","Dia Di Betico [Betico Day]","AW",2001 +"2001-02-26","Dialuna di Carnaval [Carnaval Monday]","AW",2001 +"2001-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2001 +"2001-04-13","Bierna Santo [Good Friday]","AW",2001 +"2001-04-16","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2001 +"2001-04-30","Ana di La Reina [Queen's Day]","AW",2001 +"2001-05-01","Dia di Obrero [Labour Day]","AW",2001 +"2001-05-24","Dia di Asuncion [Ascension Day]","AW",2001 +"2001-12-25","Pasco di Nacemento [Christmas]","AW",2001 +"2001-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2001 +"2002-01-01","Ana Nobo [New Year's Day]","AW",2002 +"2002-01-25","Dia Di Betico [Betico Day]","AW",2002 +"2002-02-11","Dialuna di Carnaval [Carnaval Monday]","AW",2002 +"2002-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2002 +"2002-03-29","Bierna Santo [Good Friday]","AW",2002 +"2002-04-01","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2002 +"2002-04-30","Ana di La Reina [Queen's Day]","AW",2002 +"2002-05-01","Dia di Obrero [Labour Day]","AW",2002 +"2002-05-09","Dia di Asuncion [Ascension Day]","AW",2002 +"2002-12-25","Pasco di Nacemento [Christmas]","AW",2002 +"2002-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2002 +"2003-01-01","Ana Nobo [New Year's Day]","AW",2003 +"2003-01-25","Dia Di Betico [Betico Day]","AW",2003 +"2003-03-03","Dialuna di Carnaval [Carnaval Monday]","AW",2003 +"2003-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2003 +"2003-04-18","Bierna Santo [Good Friday]","AW",2003 +"2003-04-21","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2003 +"2003-04-30","Ana di La Reina [Queen's Day]","AW",2003 +"2003-05-01","Dia di Obrero [Labour Day]","AW",2003 +"2003-05-29","Dia di Asuncion [Ascension Day]","AW",2003 +"2003-12-25","Pasco di Nacemento [Christmas]","AW",2003 +"2003-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2003 +"2004-01-01","Ana Nobo [New Year's Day]","AW",2004 +"2004-01-25","Dia Di Betico [Betico Day]","AW",2004 +"2004-02-23","Dialuna di Carnaval [Carnaval Monday]","AW",2004 +"2004-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2004 +"2004-04-09","Bierna Santo [Good Friday]","AW",2004 +"2004-04-12","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2004 +"2004-04-30","Ana di La Reina [Queen's Day]","AW",2004 +"2004-05-01","Dia di Obrero [Labour Day]","AW",2004 +"2004-05-20","Dia di Asuncion [Ascension Day]","AW",2004 +"2004-12-25","Pasco di Nacemento [Christmas]","AW",2004 +"2004-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2004 +"2005-01-01","Ana Nobo [New Year's Day]","AW",2005 +"2005-01-25","Dia Di Betico [Betico Day]","AW",2005 +"2005-02-07","Dialuna di Carnaval [Carnaval Monday]","AW",2005 +"2005-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2005 +"2005-03-25","Bierna Santo [Good Friday]","AW",2005 +"2005-03-28","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2005 +"2005-04-30","Ana di La Reina [Queen's Day]","AW",2005 +"2005-05-01","Dia di Obrero [Labour Day]","AW",2005 +"2005-05-05","Dia di Asuncion [Ascension Day]","AW",2005 +"2005-12-25","Pasco di Nacemento [Christmas]","AW",2005 +"2005-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2005 +"2006-01-01","Ana Nobo [New Year's Day]","AW",2006 +"2006-01-25","Dia Di Betico [Betico Day]","AW",2006 +"2006-02-27","Dialuna di Carnaval [Carnaval Monday]","AW",2006 +"2006-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2006 +"2006-04-14","Bierna Santo [Good Friday]","AW",2006 +"2006-04-17","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2006 +"2006-04-29","Ana di La Reina [Queen's Day]","AW",2006 +"2006-05-01","Dia di Obrero [Labour Day]","AW",2006 +"2006-05-25","Dia di Asuncion [Ascension Day]","AW",2006 +"2006-12-25","Pasco di Nacemento [Christmas]","AW",2006 +"2006-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2006 +"2007-01-01","Ana Nobo [New Year's Day]","AW",2007 +"2007-01-25","Dia Di Betico [Betico Day]","AW",2007 +"2007-02-19","Dialuna di Carnaval [Carnaval Monday]","AW",2007 +"2007-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2007 +"2007-04-06","Bierna Santo [Good Friday]","AW",2007 +"2007-04-09","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2007 +"2007-04-30","Ana di La Reina [Queen's Day]","AW",2007 +"2007-05-01","Dia di Obrero [Labour Day]","AW",2007 +"2007-05-17","Dia di Asuncion [Ascension Day]","AW",2007 +"2007-12-25","Pasco di Nacemento [Christmas]","AW",2007 +"2007-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2007 +"2008-01-01","Ana Nobo [New Year's Day]","AW",2008 +"2008-01-25","Dia Di Betico [Betico Day]","AW",2008 +"2008-02-04","Dialuna di Carnaval [Carnaval Monday]","AW",2008 +"2008-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2008 +"2008-03-21","Bierna Santo [Good Friday]","AW",2008 +"2008-03-24","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2008 +"2008-04-30","Ana di La Reina [Queen's Day]","AW",2008 +"2008-05-01","Dia di Asuncion [Ascension Day]","AW",2008 +"2008-05-01","Dia di Obrero [Labour Day]","AW",2008 +"2008-12-25","Pasco di Nacemento [Christmas]","AW",2008 +"2008-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2008 +"2009-01-01","Ana Nobo [New Year's Day]","AW",2009 +"2009-01-25","Dia Di Betico [Betico Day]","AW",2009 +"2009-02-23","Dialuna di Carnaval [Carnaval Monday]","AW",2009 +"2009-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2009 +"2009-04-10","Bierna Santo [Good Friday]","AW",2009 +"2009-04-13","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2009 +"2009-04-30","Ana di La Reina [Queen's Day]","AW",2009 +"2009-05-01","Dia di Obrero [Labour Day]","AW",2009 +"2009-05-21","Dia di Asuncion [Ascension Day]","AW",2009 +"2009-12-25","Pasco di Nacemento [Christmas]","AW",2009 +"2009-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2009 +"2010-01-01","Ana Nobo [New Year's Day]","AW",2010 +"2010-01-25","Dia Di Betico [Betico Day]","AW",2010 +"2010-02-15","Dialuna di Carnaval [Carnaval Monday]","AW",2010 +"2010-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2010 +"2010-04-02","Bierna Santo [Good Friday]","AW",2010 +"2010-04-05","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2010 +"2010-04-30","Ana di La Reina [Queen's Day]","AW",2010 +"2010-05-01","Dia di Obrero [Labour Day]","AW",2010 +"2010-05-13","Dia di Asuncion [Ascension Day]","AW",2010 +"2010-12-25","Pasco di Nacemento [Christmas]","AW",2010 +"2010-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2010 +"2011-01-01","Ana Nobo [New Year's Day]","AW",2011 +"2011-01-25","Dia Di Betico [Betico Day]","AW",2011 +"2011-03-07","Dialuna di Carnaval [Carnaval Monday]","AW",2011 +"2011-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2011 +"2011-04-22","Bierna Santo [Good Friday]","AW",2011 +"2011-04-25","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2011 +"2011-04-30","Ana di La Reina [Queen's Day]","AW",2011 +"2011-05-01","Dia di Obrero [Labour Day]","AW",2011 +"2011-06-02","Dia di Asuncion [Ascension Day]","AW",2011 +"2011-12-25","Pasco di Nacemento [Christmas]","AW",2011 +"2011-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2011 +"2012-01-01","Ana Nobo [New Year's Day]","AW",2012 +"2012-01-25","Dia Di Betico [Betico Day]","AW",2012 +"2012-02-20","Dialuna di Carnaval [Carnaval Monday]","AW",2012 +"2012-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2012 +"2012-04-06","Bierna Santo [Good Friday]","AW",2012 +"2012-04-09","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2012 +"2012-04-30","Ana di La Reina [Queen's Day]","AW",2012 +"2012-05-01","Dia di Obrero [Labour Day]","AW",2012 +"2012-05-17","Dia di Asuncion [Ascension Day]","AW",2012 +"2012-12-25","Pasco di Nacemento [Christmas]","AW",2012 +"2012-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2012 +"2013-01-01","Ana Nobo [New Year's Day]","AW",2013 +"2013-01-25","Dia Di Betico [Betico Day]","AW",2013 +"2013-02-11","Dialuna di Carnaval [Carnaval Monday]","AW",2013 +"2013-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2013 +"2013-03-29","Bierna Santo [Good Friday]","AW",2013 +"2013-04-01","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2013 +"2013-04-30","Ana di La Reina [Queen's Day]","AW",2013 +"2013-05-01","Dia di Obrero [Labour Day]","AW",2013 +"2013-05-09","Dia di Asuncion [Ascension Day]","AW",2013 +"2013-12-25","Pasco di Nacemento [Christmas]","AW",2013 +"2013-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2013 +"2014-01-01","Ana Nobo [New Year's Day]","AW",2014 +"2014-01-25","Dia Di Betico [Betico Day]","AW",2014 +"2014-03-03","Dialuna di Carnaval [Carnaval Monday]","AW",2014 +"2014-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2014 +"2014-04-18","Bierna Santo [Good Friday]","AW",2014 +"2014-04-21","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2014 +"2014-04-26","Ana di Rey [King's Day]","AW",2014 +"2014-05-01","Dia di Obrero [Labour Day]","AW",2014 +"2014-05-29","Dia di Asuncion [Ascension Day]","AW",2014 +"2014-12-25","Pasco di Nacemento [Christmas]","AW",2014 +"2014-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2014 +"2015-01-01","Ana Nobo [New Year's Day]","AW",2015 +"2015-01-25","Dia Di Betico [Betico Day]","AW",2015 +"2015-02-16","Dialuna di Carnaval [Carnaval Monday]","AW",2015 +"2015-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2015 +"2015-04-03","Bierna Santo [Good Friday]","AW",2015 +"2015-04-06","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2015 +"2015-04-27","Ana di Rey [King's Day]","AW",2015 +"2015-05-01","Dia di Obrero [Labour Day]","AW",2015 +"2015-05-14","Dia di Asuncion [Ascension Day]","AW",2015 +"2015-12-25","Pasco di Nacemento [Christmas]","AW",2015 +"2015-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2015 +"2016-01-01","Ana Nobo [New Year's Day]","AW",2016 +"2016-01-25","Dia Di Betico [Betico Day]","AW",2016 +"2016-02-08","Dialuna di Carnaval [Carnaval Monday]","AW",2016 +"2016-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2016 +"2016-03-25","Bierna Santo [Good Friday]","AW",2016 +"2016-03-28","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2016 +"2016-04-27","Ana di Rey [King's Day]","AW",2016 +"2016-05-01","Dia di Obrero [Labour Day]","AW",2016 +"2016-05-05","Dia di Asuncion [Ascension Day]","AW",2016 +"2016-12-25","Pasco di Nacemento [Christmas]","AW",2016 +"2016-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2016 +"2017-01-01","Ana Nobo [New Year's Day]","AW",2017 +"2017-01-25","Dia Di Betico [Betico Day]","AW",2017 +"2017-02-27","Dialuna di Carnaval [Carnaval Monday]","AW",2017 +"2017-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2017 +"2017-04-14","Bierna Santo [Good Friday]","AW",2017 +"2017-04-17","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2017 +"2017-04-27","Ana di Rey [King's Day]","AW",2017 +"2017-05-01","Dia di Obrero [Labour Day]","AW",2017 +"2017-05-25","Dia di Asuncion [Ascension Day]","AW",2017 +"2017-12-25","Pasco di Nacemento [Christmas]","AW",2017 +"2017-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2017 +"2018-01-01","Ana Nobo [New Year's Day]","AW",2018 +"2018-01-25","Dia Di Betico [Betico Day]","AW",2018 +"2018-02-12","Dialuna di Carnaval [Carnaval Monday]","AW",2018 +"2018-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2018 +"2018-03-30","Bierna Santo [Good Friday]","AW",2018 +"2018-04-02","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2018 +"2018-04-27","Ana di Rey [King's Day]","AW",2018 +"2018-05-01","Dia di Obrero [Labour Day]","AW",2018 +"2018-05-10","Dia di Asuncion [Ascension Day]","AW",2018 +"2018-12-25","Pasco di Nacemento [Christmas]","AW",2018 +"2018-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2018 +"2019-01-01","Ana Nobo [New Year's Day]","AW",2019 +"2019-01-25","Dia Di Betico [Betico Day]","AW",2019 +"2019-03-04","Dialuna di Carnaval [Carnaval Monday]","AW",2019 +"2019-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2019 +"2019-04-19","Bierna Santo [Good Friday]","AW",2019 +"2019-04-22","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2019 +"2019-04-27","Ana di Rey [King's Day]","AW",2019 +"2019-05-01","Dia di Obrero [Labour Day]","AW",2019 +"2019-05-30","Dia di Asuncion [Ascension Day]","AW",2019 +"2019-12-25","Pasco di Nacemento [Christmas]","AW",2019 +"2019-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2019 +"2020-01-01","Ana Nobo [New Year's Day]","AW",2020 +"2020-01-25","Dia Di Betico [Betico Day]","AW",2020 +"2020-02-24","Dialuna di Carnaval [Carnaval Monday]","AW",2020 +"2020-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2020 +"2020-04-10","Bierna Santo [Good Friday]","AW",2020 +"2020-04-13","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2020 +"2020-04-27","Ana di Rey [King's Day]","AW",2020 +"2020-05-01","Dia di Obrero [Labour Day]","AW",2020 +"2020-05-21","Dia di Asuncion [Ascension Day]","AW",2020 +"2020-12-25","Pasco di Nacemento [Christmas]","AW",2020 +"2020-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2020 +"2021-01-01","Ana Nobo [New Year's Day]","AW",2021 +"2021-01-25","Dia Di Betico [Betico Day]","AW",2021 +"2021-02-15","Dialuna di Carnaval [Carnaval Monday]","AW",2021 +"2021-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2021 +"2021-04-02","Bierna Santo [Good Friday]","AW",2021 +"2021-04-05","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2021 +"2021-04-27","Ana di Rey [King's Day]","AW",2021 +"2021-05-01","Dia di Obrero [Labour Day]","AW",2021 +"2021-05-13","Dia di Asuncion [Ascension Day]","AW",2021 +"2021-12-25","Pasco di Nacemento [Christmas]","AW",2021 +"2021-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2021 +"2022-01-01","Ana Nobo [New Year's Day]","AW",2022 +"2022-01-25","Dia Di Betico [Betico Day]","AW",2022 +"2022-02-28","Dialuna di Carnaval [Carnaval Monday]","AW",2022 +"2022-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2022 +"2022-04-15","Bierna Santo [Good Friday]","AW",2022 +"2022-04-18","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2022 +"2022-04-27","Ana di Rey [King's Day]","AW",2022 +"2022-05-01","Dia di Obrero [Labour Day]","AW",2022 +"2022-05-26","Dia di Asuncion [Ascension Day]","AW",2022 +"2022-12-25","Pasco di Nacemento [Christmas]","AW",2022 +"2022-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2022 +"2023-01-01","Ana Nobo [New Year's Day]","AW",2023 +"2023-01-25","Dia Di Betico [Betico Day]","AW",2023 +"2023-02-20","Dialuna di Carnaval [Carnaval Monday]","AW",2023 +"2023-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2023 +"2023-04-07","Bierna Santo [Good Friday]","AW",2023 +"2023-04-10","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2023 +"2023-04-27","Ana di Rey [King's Day]","AW",2023 +"2023-05-01","Dia di Obrero [Labour Day]","AW",2023 +"2023-05-18","Dia di Asuncion [Ascension Day]","AW",2023 +"2023-12-25","Pasco di Nacemento [Christmas]","AW",2023 +"2023-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2023 +"2024-01-01","Ana Nobo [New Year's Day]","AW",2024 +"2024-01-25","Dia Di Betico [Betico Day]","AW",2024 +"2024-02-12","Dialuna di Carnaval [Carnaval Monday]","AW",2024 +"2024-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2024 +"2024-03-29","Bierna Santo [Good Friday]","AW",2024 +"2024-04-01","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2024 +"2024-04-27","Ana di Rey [King's Day]","AW",2024 +"2024-05-01","Dia di Obrero [Labour Day]","AW",2024 +"2024-05-09","Dia di Asuncion [Ascension Day]","AW",2024 +"2024-12-25","Pasco di Nacemento [Christmas]","AW",2024 +"2024-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2024 +"2025-01-01","Ana Nobo [New Year's Day]","AW",2025 +"2025-01-25","Dia Di Betico [Betico Day]","AW",2025 +"2025-03-03","Dialuna di Carnaval [Carnaval Monday]","AW",2025 +"2025-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2025 +"2025-04-18","Bierna Santo [Good Friday]","AW",2025 +"2025-04-21","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2025 +"2025-04-26","Ana di Rey [King's Day]","AW",2025 +"2025-05-01","Dia di Obrero [Labour Day]","AW",2025 +"2025-05-29","Dia di Asuncion [Ascension Day]","AW",2025 +"2025-12-25","Pasco di Nacemento [Christmas]","AW",2025 +"2025-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2025 +"2026-01-01","Ana Nobo [New Year's Day]","AW",2026 +"2026-01-25","Dia Di Betico [Betico Day]","AW",2026 +"2026-02-16","Dialuna di Carnaval [Carnaval Monday]","AW",2026 +"2026-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2026 +"2026-04-03","Bierna Santo [Good Friday]","AW",2026 +"2026-04-06","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2026 +"2026-04-27","Ana di Rey [King's Day]","AW",2026 +"2026-05-01","Dia di Obrero [Labour Day]","AW",2026 +"2026-05-14","Dia di Asuncion [Ascension Day]","AW",2026 +"2026-12-25","Pasco di Nacemento [Christmas]","AW",2026 +"2026-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2026 +"2027-01-01","Ana Nobo [New Year's Day]","AW",2027 +"2027-01-25","Dia Di Betico [Betico Day]","AW",2027 +"2027-02-08","Dialuna di Carnaval [Carnaval Monday]","AW",2027 +"2027-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2027 +"2027-03-26","Bierna Santo [Good Friday]","AW",2027 +"2027-03-29","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2027 +"2027-04-27","Ana di Rey [King's Day]","AW",2027 +"2027-05-01","Dia di Obrero [Labour Day]","AW",2027 +"2027-05-06","Dia di Asuncion [Ascension Day]","AW",2027 +"2027-12-25","Pasco di Nacemento [Christmas]","AW",2027 +"2027-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2027 +"2028-01-01","Ana Nobo [New Year's Day]","AW",2028 +"2028-01-25","Dia Di Betico [Betico Day]","AW",2028 +"2028-02-28","Dialuna di Carnaval [Carnaval Monday]","AW",2028 +"2028-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2028 +"2028-04-14","Bierna Santo [Good Friday]","AW",2028 +"2028-04-17","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2028 +"2028-04-27","Ana di Rey [King's Day]","AW",2028 +"2028-05-01","Dia di Obrero [Labour Day]","AW",2028 +"2028-05-25","Dia di Asuncion [Ascension Day]","AW",2028 +"2028-12-25","Pasco di Nacemento [Christmas]","AW",2028 +"2028-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2028 +"2029-01-01","Ana Nobo [New Year's Day]","AW",2029 +"2029-01-25","Dia Di Betico [Betico Day]","AW",2029 +"2029-02-12","Dialuna di Carnaval [Carnaval Monday]","AW",2029 +"2029-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2029 +"2029-03-30","Bierna Santo [Good Friday]","AW",2029 +"2029-04-02","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2029 +"2029-04-27","Ana di Rey [King's Day]","AW",2029 +"2029-05-01","Dia di Obrero [Labour Day]","AW",2029 +"2029-05-10","Dia di Asuncion [Ascension Day]","AW",2029 +"2029-12-25","Pasco di Nacemento [Christmas]","AW",2029 +"2029-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2029 +"2030-01-01","Ana Nobo [New Year's Day]","AW",2030 +"2030-01-25","Dia Di Betico [Betico Day]","AW",2030 +"2030-03-04","Dialuna di Carnaval [Carnaval Monday]","AW",2030 +"2030-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2030 +"2030-04-19","Bierna Santo [Good Friday]","AW",2030 +"2030-04-22","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2030 +"2030-04-27","Ana di Rey [King's Day]","AW",2030 +"2030-05-01","Dia di Obrero [Labour Day]","AW",2030 +"2030-05-30","Dia di Asuncion [Ascension Day]","AW",2030 +"2030-12-25","Pasco di Nacemento [Christmas]","AW",2030 +"2030-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2030 +"2031-01-01","Ana Nobo [New Year's Day]","AW",2031 +"2031-01-25","Dia Di Betico [Betico Day]","AW",2031 +"2031-02-24","Dialuna di Carnaval [Carnaval Monday]","AW",2031 +"2031-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2031 +"2031-04-11","Bierna Santo [Good Friday]","AW",2031 +"2031-04-14","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2031 +"2031-04-26","Ana di Rey [King's Day]","AW",2031 +"2031-05-01","Dia di Obrero [Labour Day]","AW",2031 +"2031-05-22","Dia di Asuncion [Ascension Day]","AW",2031 +"2031-12-25","Pasco di Nacemento [Christmas]","AW",2031 +"2031-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2031 +"2032-01-01","Ana Nobo [New Year's Day]","AW",2032 +"2032-01-25","Dia Di Betico [Betico Day]","AW",2032 +"2032-02-09","Dialuna di Carnaval [Carnaval Monday]","AW",2032 +"2032-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2032 +"2032-03-26","Bierna Santo [Good Friday]","AW",2032 +"2032-03-29","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2032 +"2032-04-27","Ana di Rey [King's Day]","AW",2032 +"2032-05-01","Dia di Obrero [Labour Day]","AW",2032 +"2032-05-06","Dia di Asuncion [Ascension Day]","AW",2032 +"2032-12-25","Pasco di Nacemento [Christmas]","AW",2032 +"2032-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2032 +"2033-01-01","Ana Nobo [New Year's Day]","AW",2033 +"2033-01-25","Dia Di Betico [Betico Day]","AW",2033 +"2033-02-28","Dialuna di Carnaval [Carnaval Monday]","AW",2033 +"2033-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2033 +"2033-04-15","Bierna Santo [Good Friday]","AW",2033 +"2033-04-18","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2033 +"2033-04-27","Ana di Rey [King's Day]","AW",2033 +"2033-05-01","Dia di Obrero [Labour Day]","AW",2033 +"2033-05-26","Dia di Asuncion [Ascension Day]","AW",2033 +"2033-12-25","Pasco di Nacemento [Christmas]","AW",2033 +"2033-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2033 +"2034-01-01","Ana Nobo [New Year's Day]","AW",2034 +"2034-01-25","Dia Di Betico [Betico Day]","AW",2034 +"2034-02-20","Dialuna di Carnaval [Carnaval Monday]","AW",2034 +"2034-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2034 +"2034-04-07","Bierna Santo [Good Friday]","AW",2034 +"2034-04-10","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2034 +"2034-04-27","Ana di Rey [King's Day]","AW",2034 +"2034-05-01","Dia di Obrero [Labour Day]","AW",2034 +"2034-05-18","Dia di Asuncion [Ascension Day]","AW",2034 +"2034-12-25","Pasco di Nacemento [Christmas]","AW",2034 +"2034-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2034 +"2035-01-01","Ana Nobo [New Year's Day]","AW",2035 +"2035-01-25","Dia Di Betico [Betico Day]","AW",2035 +"2035-02-05","Dialuna di Carnaval [Carnaval Monday]","AW",2035 +"2035-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2035 +"2035-03-23","Bierna Santo [Good Friday]","AW",2035 +"2035-03-26","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2035 +"2035-04-27","Ana di Rey [King's Day]","AW",2035 +"2035-05-01","Dia di Obrero [Labour Day]","AW",2035 +"2035-05-03","Dia di Asuncion [Ascension Day]","AW",2035 +"2035-12-25","Pasco di Nacemento [Christmas]","AW",2035 +"2035-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2035 +"2036-01-01","Ana Nobo [New Year's Day]","AW",2036 +"2036-01-25","Dia Di Betico [Betico Day]","AW",2036 +"2036-02-25","Dialuna di Carnaval [Carnaval Monday]","AW",2036 +"2036-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2036 +"2036-04-11","Bierna Santo [Good Friday]","AW",2036 +"2036-04-14","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2036 +"2036-04-26","Ana di Rey [King's Day]","AW",2036 +"2036-05-01","Dia di Obrero [Labour Day]","AW",2036 +"2036-05-22","Dia di Asuncion [Ascension Day]","AW",2036 +"2036-12-25","Pasco di Nacemento [Christmas]","AW",2036 +"2036-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2036 +"2037-01-01","Ana Nobo [New Year's Day]","AW",2037 +"2037-01-25","Dia Di Betico [Betico Day]","AW",2037 +"2037-02-16","Dialuna di Carnaval [Carnaval Monday]","AW",2037 +"2037-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2037 +"2037-04-03","Bierna Santo [Good Friday]","AW",2037 +"2037-04-06","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2037 +"2037-04-27","Ana di Rey [King's Day]","AW",2037 +"2037-05-01","Dia di Obrero [Labour Day]","AW",2037 +"2037-05-14","Dia di Asuncion [Ascension Day]","AW",2037 +"2037-12-25","Pasco di Nacemento [Christmas]","AW",2037 +"2037-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2037 +"2038-01-01","Ana Nobo [New Year's Day]","AW",2038 +"2038-01-25","Dia Di Betico [Betico Day]","AW",2038 +"2038-03-08","Dialuna di Carnaval [Carnaval Monday]","AW",2038 +"2038-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2038 +"2038-04-23","Bierna Santo [Good Friday]","AW",2038 +"2038-04-26","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2038 +"2038-04-27","Ana di Rey [King's Day]","AW",2038 +"2038-05-01","Dia di Obrero [Labour Day]","AW",2038 +"2038-06-03","Dia di Asuncion [Ascension Day]","AW",2038 +"2038-12-25","Pasco di Nacemento [Christmas]","AW",2038 +"2038-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2038 +"2039-01-01","Ana Nobo [New Year's Day]","AW",2039 +"2039-01-25","Dia Di Betico [Betico Day]","AW",2039 +"2039-02-21","Dialuna di Carnaval [Carnaval Monday]","AW",2039 +"2039-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2039 +"2039-04-08","Bierna Santo [Good Friday]","AW",2039 +"2039-04-11","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2039 +"2039-04-27","Ana di Rey [King's Day]","AW",2039 +"2039-05-01","Dia di Obrero [Labour Day]","AW",2039 +"2039-05-19","Dia di Asuncion [Ascension Day]","AW",2039 +"2039-12-25","Pasco di Nacemento [Christmas]","AW",2039 +"2039-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2039 +"2040-01-01","Ana Nobo [New Year's Day]","AW",2040 +"2040-01-25","Dia Di Betico [Betico Day]","AW",2040 +"2040-02-13","Dialuna di Carnaval [Carnaval Monday]","AW",2040 +"2040-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2040 +"2040-03-30","Bierna Santo [Good Friday]","AW",2040 +"2040-04-02","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2040 +"2040-04-27","Ana di Rey [King's Day]","AW",2040 +"2040-05-01","Dia di Obrero [Labour Day]","AW",2040 +"2040-05-10","Dia di Asuncion [Ascension Day]","AW",2040 +"2040-12-25","Pasco di Nacemento [Christmas]","AW",2040 +"2040-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2040 +"2041-01-01","Ana Nobo [New Year's Day]","AW",2041 +"2041-01-25","Dia Di Betico [Betico Day]","AW",2041 +"2041-03-04","Dialuna di Carnaval [Carnaval Monday]","AW",2041 +"2041-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2041 +"2041-04-19","Bierna Santo [Good Friday]","AW",2041 +"2041-04-22","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2041 +"2041-04-27","Ana di Rey [King's Day]","AW",2041 +"2041-05-01","Dia di Obrero [Labour Day]","AW",2041 +"2041-05-30","Dia di Asuncion [Ascension Day]","AW",2041 +"2041-12-25","Pasco di Nacemento [Christmas]","AW",2041 +"2041-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2041 +"2042-01-01","Ana Nobo [New Year's Day]","AW",2042 +"2042-01-25","Dia Di Betico [Betico Day]","AW",2042 +"2042-02-17","Dialuna di Carnaval [Carnaval Monday]","AW",2042 +"2042-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2042 +"2042-04-04","Bierna Santo [Good Friday]","AW",2042 +"2042-04-07","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2042 +"2042-04-26","Ana di Rey [King's Day]","AW",2042 +"2042-05-01","Dia di Obrero [Labour Day]","AW",2042 +"2042-05-15","Dia di Asuncion [Ascension Day]","AW",2042 +"2042-12-25","Pasco di Nacemento [Christmas]","AW",2042 +"2042-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2042 +"2043-01-01","Ana Nobo [New Year's Day]","AW",2043 +"2043-01-25","Dia Di Betico [Betico Day]","AW",2043 +"2043-02-09","Dialuna di Carnaval [Carnaval Monday]","AW",2043 +"2043-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2043 +"2043-03-27","Bierna Santo [Good Friday]","AW",2043 +"2043-03-30","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2043 +"2043-04-27","Ana di Rey [King's Day]","AW",2043 +"2043-05-01","Dia di Obrero [Labour Day]","AW",2043 +"2043-05-07","Dia di Asuncion [Ascension Day]","AW",2043 +"2043-12-25","Pasco di Nacemento [Christmas]","AW",2043 +"2043-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2043 +"2044-01-01","Ana Nobo [New Year's Day]","AW",2044 +"2044-01-25","Dia Di Betico [Betico Day]","AW",2044 +"2044-02-29","Dialuna di Carnaval [Carnaval Monday]","AW",2044 +"2044-03-18","Dia di Himno y Bandera [National Anthem & Flag Day]","AW",2044 +"2044-04-15","Bierna Santo [Good Friday]","AW",2044 +"2044-04-18","Di Dos Dia di Pasco di Resureccion [Easter Monday]","AW",2044 +"2044-04-27","Ana di Rey [King's Day]","AW",2044 +"2044-05-01","Dia di Obrero [Labour Day]","AW",2044 +"2044-05-26","Dia di Asuncion [Ascension Day]","AW",2044 +"2044-12-25","Pasco di Nacemento [Christmas]","AW",2044 +"2044-12-26","Di Dos Dia di Pasco di Nacemento [Second Christmas]","AW",2044 +"1995-01-01","New Year's Day","AZ",1995 +"1995-03-02","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1995 +"1995-03-03","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1995 +"1995-03-08","International Women's Day","AZ",1995 +"1995-05-09","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1995 +"1995-05-09","Victory Day over Fascism","AZ",1995 +"1995-05-10","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1995 +"1995-05-28","Republic Day","AZ",1995 +"1995-10-09","Azerbaijan Armed Forces Day","AZ",1995 +"1995-10-18","Independence Day","AZ",1995 +"1995-12-31","International Solidarity Day of Azerbaijanis","AZ",1995 +"1996-01-01","New Year's Day","AZ",1996 +"1996-02-19","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1996 +"1996-02-20","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1996 +"1996-03-08","International Women's Day","AZ",1996 +"1996-04-27","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1996 +"1996-04-28","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1996 +"1996-05-09","Victory Day over Fascism","AZ",1996 +"1996-05-28","Republic Day","AZ",1996 +"1996-10-09","Azerbaijan Armed Forces Day","AZ",1996 +"1996-10-18","Independence Day","AZ",1996 +"1996-12-31","International Solidarity Day of Azerbaijanis","AZ",1996 +"1997-01-01","New Year's Day","AZ",1997 +"1997-02-08","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1997 +"1997-02-09","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1997 +"1997-03-08","International Women's Day","AZ",1997 +"1997-04-17","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1997 +"1997-04-18","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1997 +"1997-05-09","Victory Day over Fascism","AZ",1997 +"1997-05-28","Republic Day","AZ",1997 +"1997-06-15","National Salvation Day","AZ",1997 +"1997-10-09","Azerbaijan Armed Forces Day","AZ",1997 +"1997-10-18","Independence Day","AZ",1997 +"1997-12-31","International Solidarity Day of Azerbaijanis","AZ",1997 +"1998-01-01","New Year's Day","AZ",1998 +"1998-01-29","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1998 +"1998-01-30","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1998 +"1998-03-08","International Women's Day","AZ",1998 +"1998-04-07","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1998 +"1998-04-08","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1998 +"1998-05-09","Victory Day over Fascism","AZ",1998 +"1998-05-28","Republic Day","AZ",1998 +"1998-06-15","National Salvation Day","AZ",1998 +"1998-06-26","Azerbaijan Armed Forces Day","AZ",1998 +"1998-10-18","Independence Day","AZ",1998 +"1998-12-31","International Solidarity Day of Azerbaijanis","AZ",1998 +"1999-01-01","New Year's Day","AZ",1999 +"1999-01-18","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1999 +"1999-01-19","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",1999 +"1999-03-08","International Women's Day","AZ",1999 +"1999-03-27","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1999 +"1999-03-28","Gurban Bayrami* (*estimated)* (*estimated)","AZ",1999 +"1999-05-09","Victory Day over Fascism","AZ",1999 +"1999-05-28","Republic Day","AZ",1999 +"1999-06-15","National Salvation Day","AZ",1999 +"1999-06-26","Azerbaijan Armed Forces Day","AZ",1999 +"1999-10-18","Independence Day","AZ",1999 +"1999-12-31","International Solidarity Day of Azerbaijanis","AZ",1999 +"2000-01-01","New Year's Day","AZ",2000 +"2000-01-08","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2000 +"2000-01-09","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2000 +"2000-01-20","Black January","AZ",2000 +"2000-03-08","International Women's Day","AZ",2000 +"2000-03-16","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2000 +"2000-03-17","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2000 +"2000-05-09","Victory Day over Fascism","AZ",2000 +"2000-05-28","Republic Day","AZ",2000 +"2000-06-15","National Salvation Day","AZ",2000 +"2000-06-26","Azerbaijan Armed Forces Day","AZ",2000 +"2000-10-18","Independence Day","AZ",2000 +"2000-12-27","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2000 +"2000-12-28","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2000 +"2000-12-31","International Solidarity Day of Azerbaijanis","AZ",2000 +"2001-01-01","New Year's Day","AZ",2001 +"2001-01-20","Black January","AZ",2001 +"2001-03-05","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2001 +"2001-03-06","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2001 +"2001-03-08","International Women's Day","AZ",2001 +"2001-05-09","Victory Day over Fascism","AZ",2001 +"2001-05-28","Republic Day","AZ",2001 +"2001-06-15","National Salvation Day","AZ",2001 +"2001-06-26","Azerbaijan Armed Forces Day","AZ",2001 +"2001-10-18","Independence Day","AZ",2001 +"2001-12-16","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2001 +"2001-12-17","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2001 +"2001-12-31","International Solidarity Day of Azerbaijanis","AZ",2001 +"2002-01-01","New Year's Day","AZ",2002 +"2002-01-20","Black January","AZ",2002 +"2002-02-22","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2002 +"2002-02-23","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2002 +"2002-03-08","International Women's Day","AZ",2002 +"2002-05-09","Victory Day over Fascism","AZ",2002 +"2002-05-28","Republic Day","AZ",2002 +"2002-06-15","National Salvation Day","AZ",2002 +"2002-06-26","Azerbaijan Armed Forces Day","AZ",2002 +"2002-10-18","Independence Day","AZ",2002 +"2002-12-05","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2002 +"2002-12-06","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2002 +"2002-12-31","International Solidarity Day of Azerbaijanis","AZ",2002 +"2003-01-01","New Year's Day","AZ",2003 +"2003-01-20","Black January","AZ",2003 +"2003-02-11","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2003 +"2003-02-12","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2003 +"2003-03-08","International Women's Day","AZ",2003 +"2003-05-09","Victory Day over Fascism","AZ",2003 +"2003-05-28","Republic Day","AZ",2003 +"2003-06-15","National Salvation Day","AZ",2003 +"2003-06-26","Azerbaijan Armed Forces Day","AZ",2003 +"2003-10-18","Independence Day","AZ",2003 +"2003-11-25","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2003 +"2003-11-26","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2003 +"2003-12-31","International Solidarity Day of Azerbaijanis","AZ",2003 +"2004-01-01","New Year's Day","AZ",2004 +"2004-01-20","Black January","AZ",2004 +"2004-02-01","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2004 +"2004-02-02","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2004 +"2004-03-08","International Women's Day","AZ",2004 +"2004-05-09","Victory Day over Fascism","AZ",2004 +"2004-05-28","Republic Day","AZ",2004 +"2004-06-15","National Salvation Day","AZ",2004 +"2004-06-26","Azerbaijan Armed Forces Day","AZ",2004 +"2004-10-18","Independence Day","AZ",2004 +"2004-11-14","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2004 +"2004-11-15","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2004 +"2004-12-31","International Solidarity Day of Azerbaijanis","AZ",2004 +"2005-01-01","New Year's Day","AZ",2005 +"2005-01-20","Black January","AZ",2005 +"2005-01-21","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2005 +"2005-01-22","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2005 +"2005-03-08","International Women's Day","AZ",2005 +"2005-05-09","Victory Day over Fascism","AZ",2005 +"2005-05-28","Republic Day","AZ",2005 +"2005-06-15","National Salvation Day","AZ",2005 +"2005-06-26","Azerbaijan Armed Forces Day","AZ",2005 +"2005-10-18","Independence Day","AZ",2005 +"2005-11-03","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2005 +"2005-11-04","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2005 +"2005-12-31","International Solidarity Day of Azerbaijanis","AZ",2005 +"2006-01-01","New Year's Day","AZ",2006 +"2006-01-02","New Year's Day","AZ",2006 +"2006-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2006 +"2006-01-04","New Year's Day (Observed)","AZ",2006 +"2006-01-10","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2006 +"2006-01-11","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2006 +"2006-01-20","Black January","AZ",2006 +"2006-03-08","International Women's Day","AZ",2006 +"2006-05-09","Victory Day over Fascism","AZ",2006 +"2006-05-28","Republic Day","AZ",2006 +"2006-05-29","Republic Day (Observed)","AZ",2006 +"2006-06-15","National Salvation Day","AZ",2006 +"2006-06-26","Azerbaijan Armed Forces Day","AZ",2006 +"2006-10-23","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2006 +"2006-10-24","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2006 +"2006-12-31","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2006 +"2006-12-31","International Solidarity Day of Azerbaijanis","AZ",2006 +"2007-01-01","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2007 +"2007-01-01","New Year's Day","AZ",2007 +"2007-01-02","New Year's Day","AZ",2007 +"2007-01-03","Gurban Bayrami* (*estimated) (Observed)","AZ",2007 +"2007-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2007 +"2007-01-04","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2007 +"2007-01-20","Black January","AZ",2007 +"2007-03-08","International Women's Day","AZ",2007 +"2007-03-20","Novruz","AZ",2007 +"2007-03-21","Novruz","AZ",2007 +"2007-03-22","Novruz","AZ",2007 +"2007-03-23","Novruz","AZ",2007 +"2007-03-24","Novruz","AZ",2007 +"2007-03-26","Novruz (Observed)","AZ",2007 +"2007-05-09","Victory Day over Fascism","AZ",2007 +"2007-05-28","Republic Day","AZ",2007 +"2007-06-15","National Salvation Day","AZ",2007 +"2007-06-26","Azerbaijan Armed Forces Day","AZ",2007 +"2007-10-13","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2007 +"2007-10-14","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2007 +"2007-10-15","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2007 +"2007-10-16","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2007 +"2007-12-20","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2007 +"2007-12-21","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2007 +"2007-12-31","International Solidarity Day of Azerbaijanis","AZ",2007 +"2008-01-01","New Year's Day","AZ",2008 +"2008-01-02","New Year's Day","AZ",2008 +"2008-01-20","Black January","AZ",2008 +"2008-03-08","International Women's Day","AZ",2008 +"2008-03-10","International Women's Day (Observed)","AZ",2008 +"2008-03-20","Novruz","AZ",2008 +"2008-03-21","Novruz","AZ",2008 +"2008-03-22","Novruz","AZ",2008 +"2008-03-23","Novruz","AZ",2008 +"2008-03-24","Novruz","AZ",2008 +"2008-03-25","Novruz (Observed)","AZ",2008 +"2008-03-26","Novruz (Observed)","AZ",2008 +"2008-05-09","Victory Day over Fascism","AZ",2008 +"2008-05-28","Republic Day","AZ",2008 +"2008-06-15","National Salvation Day","AZ",2008 +"2008-06-16","National Salvation Day (Observed)","AZ",2008 +"2008-06-26","Azerbaijan Armed Forces Day","AZ",2008 +"2008-10-01","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2008 +"2008-10-02","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2008 +"2008-12-08","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2008 +"2008-12-09","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2008 +"2008-12-31","International Solidarity Day of Azerbaijanis","AZ",2008 +"2009-01-01","New Year's Day","AZ",2009 +"2009-01-02","New Year's Day","AZ",2009 +"2009-01-20","Black January","AZ",2009 +"2009-03-08","International Women's Day","AZ",2009 +"2009-03-09","International Women's Day (Observed)","AZ",2009 +"2009-03-20","Novruz","AZ",2009 +"2009-03-21","Novruz","AZ",2009 +"2009-03-22","Novruz","AZ",2009 +"2009-03-23","Novruz","AZ",2009 +"2009-03-24","Novruz","AZ",2009 +"2009-03-25","Novruz (Observed)","AZ",2009 +"2009-03-26","Novruz (Observed)","AZ",2009 +"2009-05-09","Victory Day over Fascism","AZ",2009 +"2009-05-11","Victory Day over Fascism (Observed)","AZ",2009 +"2009-05-28","Republic Day","AZ",2009 +"2009-06-15","National Salvation Day","AZ",2009 +"2009-06-26","Azerbaijan Armed Forces Day","AZ",2009 +"2009-09-20","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2009 +"2009-09-21","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2009 +"2009-09-22","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2009 +"2009-11-27","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2009 +"2009-11-28","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2009 +"2009-11-30","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2009 +"2009-12-31","International Solidarity Day of Azerbaijanis","AZ",2009 +"2010-01-01","New Year's Day","AZ",2010 +"2010-01-02","New Year's Day","AZ",2010 +"2010-01-04","New Year's Day (Observed)","AZ",2010 +"2010-01-20","Black January","AZ",2010 +"2010-03-08","International Women's Day","AZ",2010 +"2010-03-20","Novruz","AZ",2010 +"2010-03-21","Novruz","AZ",2010 +"2010-03-22","Novruz","AZ",2010 +"2010-03-23","Novruz","AZ",2010 +"2010-03-24","Novruz","AZ",2010 +"2010-03-25","Novruz (Observed)","AZ",2010 +"2010-03-26","Novruz (Observed)","AZ",2010 +"2010-05-09","Victory Day over Fascism","AZ",2010 +"2010-05-10","Victory Day over Fascism (Observed)","AZ",2010 +"2010-05-28","Republic Day","AZ",2010 +"2010-06-15","National Salvation Day","AZ",2010 +"2010-06-26","Azerbaijan Armed Forces Day","AZ",2010 +"2010-06-28","Azerbaijan Armed Forces Day (Observed)","AZ",2010 +"2010-09-10","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2010 +"2010-09-11","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2010 +"2010-09-13","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2010 +"2010-11-09","Flag Day","AZ",2010 +"2010-11-16","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2010 +"2010-11-17","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2010 +"2010-12-31","International Solidarity Day of Azerbaijanis","AZ",2010 +"2011-01-01","New Year's Day","AZ",2011 +"2011-01-02","New Year's Day","AZ",2011 +"2011-01-03","New Year's Day (Observed)","AZ",2011 +"2011-01-04","New Year's Day (Observed)","AZ",2011 +"2011-01-20","Black January","AZ",2011 +"2011-03-08","International Women's Day","AZ",2011 +"2011-03-20","Novruz","AZ",2011 +"2011-03-21","Novruz","AZ",2011 +"2011-03-22","Novruz","AZ",2011 +"2011-03-23","Novruz","AZ",2011 +"2011-03-24","Novruz","AZ",2011 +"2011-03-25","Novruz (Observed)","AZ",2011 +"2011-05-09","Victory Day over Fascism","AZ",2011 +"2011-05-28","Republic Day","AZ",2011 +"2011-05-30","Republic Day (Observed)","AZ",2011 +"2011-06-15","National Salvation Day","AZ",2011 +"2011-06-26","Azerbaijan Armed Forces Day","AZ",2011 +"2011-06-27","Azerbaijan Armed Forces Day (Observed)","AZ",2011 +"2011-08-30","Ramazan Bayrami","AZ",2011 +"2011-08-31","Ramazan Bayrami","AZ",2011 +"2011-11-06","Gurban Bayrami","AZ",2011 +"2011-11-07","Gurban Bayrami","AZ",2011 +"2011-11-08","Gurban Bayrami (Observed)","AZ",2011 +"2011-11-09","Flag Day","AZ",2011 +"2011-12-31","International Solidarity Day of Azerbaijanis","AZ",2011 +"2012-01-01","New Year's Day","AZ",2012 +"2012-01-02","New Year's Day","AZ",2012 +"2012-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2012 +"2012-01-04","New Year's Day (Observed)","AZ",2012 +"2012-01-20","Black January","AZ",2012 +"2012-03-08","International Women's Day","AZ",2012 +"2012-03-20","Novruz","AZ",2012 +"2012-03-21","Novruz","AZ",2012 +"2012-03-22","Novruz","AZ",2012 +"2012-03-23","Novruz","AZ",2012 +"2012-03-24","Novruz","AZ",2012 +"2012-03-26","Novruz (Observed)","AZ",2012 +"2012-05-09","Victory Day over Fascism","AZ",2012 +"2012-05-28","Republic Day","AZ",2012 +"2012-06-15","National Salvation Day","AZ",2012 +"2012-06-26","Azerbaijan Armed Forces Day","AZ",2012 +"2012-08-19","Ramazan Bayrami","AZ",2012 +"2012-08-20","Ramazan Bayrami","AZ",2012 +"2012-08-21","Ramazan Bayrami (Observed)","AZ",2012 +"2012-10-25","Gurban Bayrami","AZ",2012 +"2012-10-26","Gurban Bayrami","AZ",2012 +"2012-11-09","Flag Day","AZ",2012 +"2012-12-31","International Solidarity Day of Azerbaijanis","AZ",2012 +"2013-01-01","New Year's Day","AZ",2013 +"2013-01-02","New Year's Day","AZ",2013 +"2013-01-20","Black January","AZ",2013 +"2013-03-08","International Women's Day","AZ",2013 +"2013-03-20","Novruz","AZ",2013 +"2013-03-21","Novruz","AZ",2013 +"2013-03-22","Novruz","AZ",2013 +"2013-03-23","Novruz","AZ",2013 +"2013-03-24","Novruz","AZ",2013 +"2013-03-25","Novruz (Observed)","AZ",2013 +"2013-03-26","Novruz (Observed)","AZ",2013 +"2013-05-09","Victory Day over Fascism","AZ",2013 +"2013-05-28","Republic Day","AZ",2013 +"2013-06-15","National Salvation Day","AZ",2013 +"2013-06-17","National Salvation Day (Observed)","AZ",2013 +"2013-06-26","Azerbaijan Armed Forces Day","AZ",2013 +"2013-08-08","Ramazan Bayrami","AZ",2013 +"2013-08-09","Ramazan Bayrami","AZ",2013 +"2013-10-15","Gurban Bayrami","AZ",2013 +"2013-10-16","Gurban Bayrami","AZ",2013 +"2013-11-09","Flag Day","AZ",2013 +"2013-11-11","Flag Day (Observed)","AZ",2013 +"2013-12-31","International Solidarity Day of Azerbaijanis","AZ",2013 +"2014-01-01","New Year's Day","AZ",2014 +"2014-01-02","New Year's Day","AZ",2014 +"2014-01-20","Black January","AZ",2014 +"2014-03-08","International Women's Day","AZ",2014 +"2014-03-10","International Women's Day (Observed)","AZ",2014 +"2014-03-20","Novruz","AZ",2014 +"2014-03-21","Novruz","AZ",2014 +"2014-03-22","Novruz","AZ",2014 +"2014-03-23","Novruz","AZ",2014 +"2014-03-24","Novruz","AZ",2014 +"2014-03-25","Novruz (Observed)","AZ",2014 +"2014-03-26","Novruz (Observed)","AZ",2014 +"2014-05-09","Victory Day over Fascism","AZ",2014 +"2014-05-28","Republic Day","AZ",2014 +"2014-06-15","National Salvation Day","AZ",2014 +"2014-06-16","National Salvation Day (Observed)","AZ",2014 +"2014-06-26","Azerbaijan Armed Forces Day","AZ",2014 +"2014-07-28","Ramazan Bayrami","AZ",2014 +"2014-07-29","Ramazan Bayrami","AZ",2014 +"2014-10-04","Gurban Bayrami","AZ",2014 +"2014-10-05","Gurban Bayrami","AZ",2014 +"2014-10-06","Gurban Bayrami (Observed)","AZ",2014 +"2014-10-07","Gurban Bayrami (Observed)","AZ",2014 +"2014-11-09","Flag Day","AZ",2014 +"2014-11-10","Flag Day (Observed)","AZ",2014 +"2014-12-31","International Solidarity Day of Azerbaijanis","AZ",2014 +"2015-01-01","New Year's Day","AZ",2015 +"2015-01-02","New Year's Day","AZ",2015 +"2015-01-20","Black January","AZ",2015 +"2015-03-08","International Women's Day","AZ",2015 +"2015-03-09","International Women's Day (Observed)","AZ",2015 +"2015-03-20","Novruz","AZ",2015 +"2015-03-21","Novruz","AZ",2015 +"2015-03-22","Novruz","AZ",2015 +"2015-03-23","Novruz","AZ",2015 +"2015-03-24","Novruz","AZ",2015 +"2015-03-25","Novruz (Observed)","AZ",2015 +"2015-03-26","Novruz (Observed)","AZ",2015 +"2015-05-09","Victory Day over Fascism","AZ",2015 +"2015-05-11","Victory Day over Fascism (Observed)","AZ",2015 +"2015-05-28","Republic Day","AZ",2015 +"2015-06-15","National Salvation Day","AZ",2015 +"2015-06-26","Azerbaijan Armed Forces Day","AZ",2015 +"2015-07-17","Ramazan Bayrami","AZ",2015 +"2015-07-18","Ramazan Bayrami","AZ",2015 +"2015-07-20","Ramazan Bayrami (Observed)","AZ",2015 +"2015-09-24","Gurban Bayrami","AZ",2015 +"2015-09-25","Gurban Bayrami","AZ",2015 +"2015-11-09","Flag Day","AZ",2015 +"2015-12-31","International Solidarity Day of Azerbaijanis","AZ",2015 +"2016-01-01","New Year's Day","AZ",2016 +"2016-01-02","New Year's Day","AZ",2016 +"2016-01-04","New Year's Day (Observed)","AZ",2016 +"2016-01-20","Black January","AZ",2016 +"2016-03-08","International Women's Day","AZ",2016 +"2016-03-20","Novruz","AZ",2016 +"2016-03-21","Novruz","AZ",2016 +"2016-03-22","Novruz","AZ",2016 +"2016-03-23","Novruz","AZ",2016 +"2016-03-24","Novruz","AZ",2016 +"2016-03-25","Novruz (Observed)","AZ",2016 +"2016-05-09","Victory Day over Fascism","AZ",2016 +"2016-05-28","Republic Day","AZ",2016 +"2016-05-30","Republic Day (Observed)","AZ",2016 +"2016-06-15","National Salvation Day","AZ",2016 +"2016-06-26","Azerbaijan Armed Forces Day","AZ",2016 +"2016-06-27","Azerbaijan Armed Forces Day (Observed)","AZ",2016 +"2016-07-06","Ramazan Bayrami","AZ",2016 +"2016-07-07","Ramazan Bayrami","AZ",2016 +"2016-09-12","Gurban Bayrami","AZ",2016 +"2016-09-13","Gurban Bayrami","AZ",2016 +"2016-11-09","Flag Day","AZ",2016 +"2016-12-31","International Solidarity Day of Azerbaijanis","AZ",2016 +"2017-01-01","New Year's Day","AZ",2017 +"2017-01-02","New Year's Day","AZ",2017 +"2017-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2017 +"2017-01-04","New Year's Day (Observed)","AZ",2017 +"2017-01-20","Black January","AZ",2017 +"2017-03-08","International Women's Day","AZ",2017 +"2017-03-20","Novruz","AZ",2017 +"2017-03-21","Novruz","AZ",2017 +"2017-03-22","Novruz","AZ",2017 +"2017-03-23","Novruz","AZ",2017 +"2017-03-24","Novruz","AZ",2017 +"2017-05-09","Victory Day over Fascism","AZ",2017 +"2017-05-28","Republic Day","AZ",2017 +"2017-05-29","Republic Day (Observed)","AZ",2017 +"2017-06-15","National Salvation Day","AZ",2017 +"2017-06-26","Azerbaijan Armed Forces Day","AZ",2017 +"2017-06-26","Ramazan Bayrami","AZ",2017 +"2017-06-27","Ramazan Bayrami","AZ",2017 +"2017-06-28","Ramazan Bayrami (Observed)","AZ",2017 +"2017-09-01","Gurban Bayrami","AZ",2017 +"2017-09-02","Gurban Bayrami","AZ",2017 +"2017-09-04","Gurban Bayrami (Observed)","AZ",2017 +"2017-11-09","Flag Day","AZ",2017 +"2017-12-31","International Solidarity Day of Azerbaijanis","AZ",2017 +"2018-01-01","New Year's Day","AZ",2018 +"2018-01-02","New Year's Day","AZ",2018 +"2018-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2018 +"2018-01-20","Black January","AZ",2018 +"2018-03-08","International Women's Day","AZ",2018 +"2018-03-20","Novruz","AZ",2018 +"2018-03-21","Novruz","AZ",2018 +"2018-03-22","Novruz","AZ",2018 +"2018-03-23","Novruz","AZ",2018 +"2018-03-24","Novruz","AZ",2018 +"2018-03-26","Novruz (Observed)","AZ",2018 +"2018-05-09","Victory Day over Fascism","AZ",2018 +"2018-05-28","Republic Day","AZ",2018 +"2018-06-15","National Salvation Day","AZ",2018 +"2018-06-15","Ramazan Bayrami","AZ",2018 +"2018-06-16","Ramazan Bayrami","AZ",2018 +"2018-06-18","Ramazan Bayrami (Observed)","AZ",2018 +"2018-06-19","Ramazan Bayrami (Observed)","AZ",2018 +"2018-06-26","Azerbaijan Armed Forces Day","AZ",2018 +"2018-08-22","Gurban Bayrami","AZ",2018 +"2018-08-23","Gurban Bayrami","AZ",2018 +"2018-11-09","Flag Day","AZ",2018 +"2018-12-31","International Solidarity Day of Azerbaijanis","AZ",2018 +"2019-01-01","New Year's Day","AZ",2019 +"2019-01-02","New Year's Day","AZ",2019 +"2019-01-20","Black January","AZ",2019 +"2019-03-08","International Women's Day","AZ",2019 +"2019-03-20","Novruz","AZ",2019 +"2019-03-21","Novruz","AZ",2019 +"2019-03-22","Novruz","AZ",2019 +"2019-03-23","Novruz","AZ",2019 +"2019-03-24","Novruz","AZ",2019 +"2019-03-25","Novruz (Observed)","AZ",2019 +"2019-03-26","Novruz (Observed)","AZ",2019 +"2019-05-09","Victory Day over Fascism","AZ",2019 +"2019-05-28","Republic Day","AZ",2019 +"2019-06-05","Ramazan Bayrami","AZ",2019 +"2019-06-06","Ramazan Bayrami","AZ",2019 +"2019-06-15","National Salvation Day","AZ",2019 +"2019-06-17","National Salvation Day (Observed)","AZ",2019 +"2019-06-26","Azerbaijan Armed Forces Day","AZ",2019 +"2019-08-12","Gurban Bayrami","AZ",2019 +"2019-08-13","Gurban Bayrami","AZ",2019 +"2019-11-09","Flag Day","AZ",2019 +"2019-11-11","Flag Day (Observed)","AZ",2019 +"2019-12-31","International Solidarity Day of Azerbaijanis","AZ",2019 +"2020-01-01","New Year's Day","AZ",2020 +"2020-01-02","New Year's Day","AZ",2020 +"2020-01-20","Black January","AZ",2020 +"2020-03-08","International Women's Day","AZ",2020 +"2020-03-09","International Women's Day (Observed)","AZ",2020 +"2020-03-20","Novruz","AZ",2020 +"2020-03-21","Novruz","AZ",2020 +"2020-03-22","Novruz","AZ",2020 +"2020-03-23","Novruz","AZ",2020 +"2020-03-24","Novruz","AZ",2020 +"2020-03-25","Novruz (Observed)","AZ",2020 +"2020-03-26","Novruz (Observed)","AZ",2020 +"2020-05-09","Victory Day over Fascism","AZ",2020 +"2020-05-11","Victory Day over Fascism (Observed)","AZ",2020 +"2020-05-24","Ramazan Bayrami","AZ",2020 +"2020-05-25","Ramazan Bayrami","AZ",2020 +"2020-05-26","Ramazan Bayrami (Observed)","AZ",2020 +"2020-05-28","Republic Day","AZ",2020 +"2020-06-15","National Salvation Day","AZ",2020 +"2020-06-26","Azerbaijan Armed Forces Day","AZ",2020 +"2020-07-31","Gurban Bayrami","AZ",2020 +"2020-08-01","Gurban Bayrami","AZ",2020 +"2020-08-03","Gurban Bayrami (Observed)","AZ",2020 +"2020-11-09","Flag Day","AZ",2020 +"2020-12-31","International Solidarity Day of Azerbaijanis","AZ",2020 +"2021-01-01","New Year's Day","AZ",2021 +"2021-01-02","New Year's Day","AZ",2021 +"2021-01-04","New Year's Day (Observed)","AZ",2021 +"2021-01-20","Black January","AZ",2021 +"2021-03-08","International Women's Day","AZ",2021 +"2021-03-20","Novruz","AZ",2021 +"2021-03-21","Novruz","AZ",2021 +"2021-03-22","Novruz","AZ",2021 +"2021-03-23","Novruz","AZ",2021 +"2021-03-24","Novruz","AZ",2021 +"2021-03-25","Novruz (Observed)","AZ",2021 +"2021-03-26","Novruz (Observed)","AZ",2021 +"2021-05-09","Victory Day over Fascism","AZ",2021 +"2021-05-10","Victory Day over Fascism (Observed)","AZ",2021 +"2021-05-13","Ramazan Bayrami","AZ",2021 +"2021-05-14","Ramazan Bayrami","AZ",2021 +"2021-05-28","Independence Day","AZ",2021 +"2021-06-15","National Salvation Day","AZ",2021 +"2021-06-26","Azerbaijan Armed Forces Day","AZ",2021 +"2021-06-28","Azerbaijan Armed Forces Day (Observed)","AZ",2021 +"2021-07-20","Gurban Bayrami","AZ",2021 +"2021-07-21","Gurban Bayrami","AZ",2021 +"2021-09-27","Memorial Day","AZ",2021 +"2021-11-08","Victory Day","AZ",2021 +"2021-11-09","Flag Day","AZ",2021 +"2021-12-31","International Solidarity Day of Azerbaijanis","AZ",2021 +"2022-01-01","New Year's Day","AZ",2022 +"2022-01-02","New Year's Day","AZ",2022 +"2022-01-03","New Year's Day (Observed)","AZ",2022 +"2022-01-04","New Year's Day (Observed)","AZ",2022 +"2022-01-20","Black January","AZ",2022 +"2022-03-08","International Women's Day","AZ",2022 +"2022-03-20","Novruz","AZ",2022 +"2022-03-21","Novruz","AZ",2022 +"2022-03-22","Novruz","AZ",2022 +"2022-03-23","Novruz","AZ",2022 +"2022-03-24","Novruz","AZ",2022 +"2022-03-25","Novruz (Observed)","AZ",2022 +"2022-05-02","Ramazan Bayrami","AZ",2022 +"2022-05-03","Ramazan Bayrami","AZ",2022 +"2022-05-09","Victory Day over Fascism","AZ",2022 +"2022-05-28","Independence Day","AZ",2022 +"2022-05-30","Independence Day (Observed)","AZ",2022 +"2022-06-15","National Salvation Day","AZ",2022 +"2022-06-26","Azerbaijan Armed Forces Day","AZ",2022 +"2022-06-27","Azerbaijan Armed Forces Day (Observed)","AZ",2022 +"2022-07-09","Gurban Bayrami","AZ",2022 +"2022-07-10","Gurban Bayrami","AZ",2022 +"2022-07-11","Gurban Bayrami (Observed)","AZ",2022 +"2022-07-12","Gurban Bayrami (Observed)","AZ",2022 +"2022-09-27","Memorial Day","AZ",2022 +"2022-11-08","Victory Day","AZ",2022 +"2022-11-09","Flag Day","AZ",2022 +"2022-12-31","International Solidarity Day of Azerbaijanis","AZ",2022 +"2023-01-01","New Year's Day","AZ",2023 +"2023-01-02","New Year's Day","AZ",2023 +"2023-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2023 +"2023-01-04","New Year's Day (Observed)","AZ",2023 +"2023-01-20","Black January","AZ",2023 +"2023-03-08","International Women's Day","AZ",2023 +"2023-03-20","Novruz","AZ",2023 +"2023-03-21","Novruz","AZ",2023 +"2023-03-22","Novruz","AZ",2023 +"2023-03-23","Novruz","AZ",2023 +"2023-03-24","Novruz","AZ",2023 +"2023-04-21","Ramazan Bayrami","AZ",2023 +"2023-04-22","Ramazan Bayrami","AZ",2023 +"2023-04-24","Ramazan Bayrami (Observed)","AZ",2023 +"2023-05-09","Victory Day over Fascism","AZ",2023 +"2023-05-28","Independence Day","AZ",2023 +"2023-05-29","Independence Day (Observed)","AZ",2023 +"2023-06-15","National Salvation Day","AZ",2023 +"2023-06-26","Azerbaijan Armed Forces Day","AZ",2023 +"2023-06-28","Gurban Bayrami","AZ",2023 +"2023-06-29","Gurban Bayrami","AZ",2023 +"2023-09-27","Memorial Day","AZ",2023 +"2023-11-08","Victory Day","AZ",2023 +"2023-11-09","Flag Day","AZ",2023 +"2023-12-31","International Solidarity Day of Azerbaijanis","AZ",2023 +"2024-01-01","New Year's Day","AZ",2024 +"2024-01-02","New Year's Day","AZ",2024 +"2024-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2024 +"2024-01-20","Black January","AZ",2024 +"2024-03-08","International Women's Day","AZ",2024 +"2024-03-20","Novruz","AZ",2024 +"2024-03-21","Novruz","AZ",2024 +"2024-03-22","Novruz","AZ",2024 +"2024-03-23","Novruz","AZ",2024 +"2024-03-24","Novruz","AZ",2024 +"2024-03-25","Novruz (Observed)","AZ",2024 +"2024-03-26","Novruz (Observed)","AZ",2024 +"2024-04-10","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2024 +"2024-04-11","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2024 +"2024-05-09","Victory Day over Fascism","AZ",2024 +"2024-05-28","Independence Day","AZ",2024 +"2024-06-15","National Salvation Day","AZ",2024 +"2024-06-16","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2024 +"2024-06-17","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2024 +"2024-06-18","National Salvation Day (Observed)","AZ",2024 +"2024-06-19","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2024 +"2024-06-26","Azerbaijan Armed Forces Day","AZ",2024 +"2024-09-27","Memorial Day","AZ",2024 +"2024-11-08","Victory Day","AZ",2024 +"2024-11-09","Flag Day","AZ",2024 +"2024-11-11","Flag Day (Observed)","AZ",2024 +"2024-12-31","International Solidarity Day of Azerbaijanis","AZ",2024 +"2025-01-01","New Year's Day","AZ",2025 +"2025-01-02","New Year's Day","AZ",2025 +"2025-01-20","Black January","AZ",2025 +"2025-03-08","International Women's Day","AZ",2025 +"2025-03-10","International Women's Day (Observed)","AZ",2025 +"2025-03-20","Novruz","AZ",2025 +"2025-03-21","Novruz","AZ",2025 +"2025-03-22","Novruz","AZ",2025 +"2025-03-23","Novruz","AZ",2025 +"2025-03-24","Novruz","AZ",2025 +"2025-03-25","Novruz (Observed)","AZ",2025 +"2025-03-26","Novruz (Observed)","AZ",2025 +"2025-03-30","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2025 +"2025-03-31","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2025 +"2025-04-01","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2025 +"2025-05-09","Victory Day over Fascism","AZ",2025 +"2025-05-28","Independence Day","AZ",2025 +"2025-06-06","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2025 +"2025-06-07","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2025 +"2025-06-09","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2025 +"2025-06-15","National Salvation Day","AZ",2025 +"2025-06-16","National Salvation Day (Observed)","AZ",2025 +"2025-06-26","Azerbaijan Armed Forces Day","AZ",2025 +"2025-09-27","Memorial Day","AZ",2025 +"2025-11-08","Victory Day","AZ",2025 +"2025-11-09","Flag Day","AZ",2025 +"2025-11-10","Victory Day (Observed)","AZ",2025 +"2025-11-11","Flag Day (Observed)","AZ",2025 +"2025-12-31","International Solidarity Day of Azerbaijanis","AZ",2025 +"2026-01-01","New Year's Day","AZ",2026 +"2026-01-02","New Year's Day","AZ",2026 +"2026-01-20","Black January","AZ",2026 +"2026-03-08","International Women's Day","AZ",2026 +"2026-03-09","International Women's Day (Observed)","AZ",2026 +"2026-03-20","Novruz","AZ",2026 +"2026-03-20","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2026 +"2026-03-21","Novruz","AZ",2026 +"2026-03-21","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2026 +"2026-03-22","Novruz","AZ",2026 +"2026-03-23","Novruz","AZ",2026 +"2026-03-24","Novruz","AZ",2026 +"2026-03-25","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2026 +"2026-03-26","Novruz (Observed)","AZ",2026 +"2026-03-26","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2026 +"2026-03-27","Novruz (Observed)","AZ",2026 +"2026-05-09","Victory Day over Fascism","AZ",2026 +"2026-05-11","Victory Day over Fascism (Observed)","AZ",2026 +"2026-05-27","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2026 +"2026-05-28","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2026 +"2026-05-28","Independence Day","AZ",2026 +"2026-05-29","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2026 +"2026-06-15","National Salvation Day","AZ",2026 +"2026-06-26","Azerbaijan Armed Forces Day","AZ",2026 +"2026-09-27","Memorial Day","AZ",2026 +"2026-11-08","Victory Day","AZ",2026 +"2026-11-09","Flag Day","AZ",2026 +"2026-11-10","Victory Day (Observed)","AZ",2026 +"2026-12-31","International Solidarity Day of Azerbaijanis","AZ",2026 +"2027-01-01","New Year's Day","AZ",2027 +"2027-01-02","New Year's Day","AZ",2027 +"2027-01-04","New Year's Day (Observed)","AZ",2027 +"2027-01-20","Black January","AZ",2027 +"2027-03-08","International Women's Day","AZ",2027 +"2027-03-09","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2027 +"2027-03-10","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2027 +"2027-03-20","Novruz","AZ",2027 +"2027-03-21","Novruz","AZ",2027 +"2027-03-22","Novruz","AZ",2027 +"2027-03-23","Novruz","AZ",2027 +"2027-03-24","Novruz","AZ",2027 +"2027-03-25","Novruz (Observed)","AZ",2027 +"2027-03-26","Novruz (Observed)","AZ",2027 +"2027-05-09","Victory Day over Fascism","AZ",2027 +"2027-05-10","Victory Day over Fascism (Observed)","AZ",2027 +"2027-05-16","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2027 +"2027-05-17","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2027 +"2027-05-18","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2027 +"2027-05-28","Independence Day","AZ",2027 +"2027-06-15","National Salvation Day","AZ",2027 +"2027-06-26","Azerbaijan Armed Forces Day","AZ",2027 +"2027-06-28","Azerbaijan Armed Forces Day (Observed)","AZ",2027 +"2027-09-27","Memorial Day","AZ",2027 +"2027-11-08","Victory Day","AZ",2027 +"2027-11-09","Flag Day","AZ",2027 +"2027-12-31","International Solidarity Day of Azerbaijanis","AZ",2027 +"2028-01-01","New Year's Day","AZ",2028 +"2028-01-02","New Year's Day","AZ",2028 +"2028-01-03","New Year's Day (Observed)","AZ",2028 +"2028-01-04","New Year's Day (Observed)","AZ",2028 +"2028-01-20","Black January","AZ",2028 +"2028-02-26","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2028 +"2028-02-27","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2028 +"2028-02-28","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2028 +"2028-02-29","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2028 +"2028-03-08","International Women's Day","AZ",2028 +"2028-03-20","Novruz","AZ",2028 +"2028-03-21","Novruz","AZ",2028 +"2028-03-22","Novruz","AZ",2028 +"2028-03-23","Novruz","AZ",2028 +"2028-03-24","Novruz","AZ",2028 +"2028-05-05","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2028 +"2028-05-06","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2028 +"2028-05-08","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2028 +"2028-05-09","Victory Day over Fascism","AZ",2028 +"2028-05-28","Independence Day","AZ",2028 +"2028-05-29","Independence Day (Observed)","AZ",2028 +"2028-06-15","National Salvation Day","AZ",2028 +"2028-06-26","Azerbaijan Armed Forces Day","AZ",2028 +"2028-09-27","Memorial Day","AZ",2028 +"2028-11-08","Victory Day","AZ",2028 +"2028-11-09","Flag Day","AZ",2028 +"2028-12-31","International Solidarity Day of Azerbaijanis","AZ",2028 +"2029-01-01","New Year's Day","AZ",2029 +"2029-01-02","New Year's Day","AZ",2029 +"2029-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2029 +"2029-01-20","Black January","AZ",2029 +"2029-02-14","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2029 +"2029-02-15","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2029 +"2029-03-08","International Women's Day","AZ",2029 +"2029-03-20","Novruz","AZ",2029 +"2029-03-21","Novruz","AZ",2029 +"2029-03-22","Novruz","AZ",2029 +"2029-03-23","Novruz","AZ",2029 +"2029-03-24","Novruz","AZ",2029 +"2029-03-26","Novruz (Observed)","AZ",2029 +"2029-04-24","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2029 +"2029-04-25","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2029 +"2029-05-09","Victory Day over Fascism","AZ",2029 +"2029-05-28","Independence Day","AZ",2029 +"2029-06-15","National Salvation Day","AZ",2029 +"2029-06-26","Azerbaijan Armed Forces Day","AZ",2029 +"2029-09-27","Memorial Day","AZ",2029 +"2029-11-08","Victory Day","AZ",2029 +"2029-11-09","Flag Day","AZ",2029 +"2029-12-31","International Solidarity Day of Azerbaijanis","AZ",2029 +"2030-01-01","New Year's Day","AZ",2030 +"2030-01-02","New Year's Day","AZ",2030 +"2030-01-20","Black January","AZ",2030 +"2030-02-04","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2030 +"2030-02-05","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2030 +"2030-03-08","International Women's Day","AZ",2030 +"2030-03-20","Novruz","AZ",2030 +"2030-03-21","Novruz","AZ",2030 +"2030-03-22","Novruz","AZ",2030 +"2030-03-23","Novruz","AZ",2030 +"2030-03-24","Novruz","AZ",2030 +"2030-03-25","Novruz (Observed)","AZ",2030 +"2030-03-26","Novruz (Observed)","AZ",2030 +"2030-04-13","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2030 +"2030-04-14","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2030 +"2030-04-15","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2030 +"2030-04-16","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2030 +"2030-05-09","Victory Day over Fascism","AZ",2030 +"2030-05-28","Independence Day","AZ",2030 +"2030-06-15","National Salvation Day","AZ",2030 +"2030-06-17","National Salvation Day (Observed)","AZ",2030 +"2030-06-26","Azerbaijan Armed Forces Day","AZ",2030 +"2030-09-27","Memorial Day","AZ",2030 +"2030-11-08","Victory Day","AZ",2030 +"2030-11-09","Flag Day","AZ",2030 +"2030-11-11","Flag Day (Observed)","AZ",2030 +"2030-12-31","International Solidarity Day of Azerbaijanis","AZ",2030 +"2031-01-01","New Year's Day","AZ",2031 +"2031-01-02","New Year's Day","AZ",2031 +"2031-01-20","Black January","AZ",2031 +"2031-01-24","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2031 +"2031-01-25","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2031 +"2031-01-27","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2031 +"2031-03-08","International Women's Day","AZ",2031 +"2031-03-10","International Women's Day (Observed)","AZ",2031 +"2031-03-20","Novruz","AZ",2031 +"2031-03-21","Novruz","AZ",2031 +"2031-03-22","Novruz","AZ",2031 +"2031-03-23","Novruz","AZ",2031 +"2031-03-24","Novruz","AZ",2031 +"2031-03-25","Novruz (Observed)","AZ",2031 +"2031-03-26","Novruz (Observed)","AZ",2031 +"2031-04-02","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2031 +"2031-04-03","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2031 +"2031-05-09","Victory Day over Fascism","AZ",2031 +"2031-05-28","Independence Day","AZ",2031 +"2031-06-15","National Salvation Day","AZ",2031 +"2031-06-16","National Salvation Day (Observed)","AZ",2031 +"2031-06-26","Azerbaijan Armed Forces Day","AZ",2031 +"2031-09-27","Memorial Day","AZ",2031 +"2031-11-08","Victory Day","AZ",2031 +"2031-11-09","Flag Day","AZ",2031 +"2031-11-10","Victory Day (Observed)","AZ",2031 +"2031-11-11","Flag Day (Observed)","AZ",2031 +"2031-12-31","International Solidarity Day of Azerbaijanis","AZ",2031 +"2032-01-01","New Year's Day","AZ",2032 +"2032-01-02","New Year's Day","AZ",2032 +"2032-01-14","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2032 +"2032-01-15","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2032 +"2032-01-20","Black January","AZ",2032 +"2032-03-08","International Women's Day","AZ",2032 +"2032-03-20","Novruz","AZ",2032 +"2032-03-21","Novruz","AZ",2032 +"2032-03-22","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2032 +"2032-03-22","Novruz","AZ",2032 +"2032-03-23","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2032 +"2032-03-23","Novruz","AZ",2032 +"2032-03-24","Novruz","AZ",2032 +"2032-03-25","Novruz (Observed)","AZ",2032 +"2032-03-26","Novruz (Observed)","AZ",2032 +"2032-03-29","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2032 +"2032-03-30","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2032 +"2032-05-09","Victory Day over Fascism","AZ",2032 +"2032-05-10","Victory Day over Fascism (Observed)","AZ",2032 +"2032-05-28","Independence Day","AZ",2032 +"2032-06-15","National Salvation Day","AZ",2032 +"2032-06-26","Azerbaijan Armed Forces Day","AZ",2032 +"2032-06-28","Azerbaijan Armed Forces Day (Observed)","AZ",2032 +"2032-09-27","Memorial Day","AZ",2032 +"2032-11-08","Victory Day","AZ",2032 +"2032-11-09","Flag Day","AZ",2032 +"2032-12-31","International Solidarity Day of Azerbaijanis","AZ",2032 +"2033-01-01","New Year's Day","AZ",2033 +"2033-01-02","New Year's Day","AZ",2033 +"2033-01-02","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2033 +"2033-01-03","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2033 +"2033-01-04","New Year's Day (Observed)","AZ",2033 +"2033-01-05","New Year's Day (Observed)","AZ",2033 +"2033-01-05","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2033 +"2033-01-20","Black January","AZ",2033 +"2033-03-08","International Women's Day","AZ",2033 +"2033-03-11","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2033 +"2033-03-12","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2033 +"2033-03-14","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2033 +"2033-03-20","Novruz","AZ",2033 +"2033-03-21","Novruz","AZ",2033 +"2033-03-22","Novruz","AZ",2033 +"2033-03-23","Novruz","AZ",2033 +"2033-03-24","Novruz","AZ",2033 +"2033-03-25","Novruz (Observed)","AZ",2033 +"2033-05-09","Victory Day over Fascism","AZ",2033 +"2033-05-28","Independence Day","AZ",2033 +"2033-05-30","Independence Day (Observed)","AZ",2033 +"2033-06-15","National Salvation Day","AZ",2033 +"2033-06-26","Azerbaijan Armed Forces Day","AZ",2033 +"2033-06-27","Azerbaijan Armed Forces Day (Observed)","AZ",2033 +"2033-09-27","Memorial Day","AZ",2033 +"2033-11-08","Victory Day","AZ",2033 +"2033-11-09","Flag Day","AZ",2033 +"2033-12-23","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2033 +"2033-12-24","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2033 +"2033-12-26","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2033 +"2033-12-31","International Solidarity Day of Azerbaijanis","AZ",2033 +"2034-01-01","New Year's Day","AZ",2034 +"2034-01-02","New Year's Day","AZ",2034 +"2034-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2034 +"2034-01-04","New Year's Day (Observed)","AZ",2034 +"2034-01-20","Black January","AZ",2034 +"2034-03-01","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2034 +"2034-03-02","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2034 +"2034-03-08","International Women's Day","AZ",2034 +"2034-03-20","Novruz","AZ",2034 +"2034-03-21","Novruz","AZ",2034 +"2034-03-22","Novruz","AZ",2034 +"2034-03-23","Novruz","AZ",2034 +"2034-03-24","Novruz","AZ",2034 +"2034-05-09","Victory Day over Fascism","AZ",2034 +"2034-05-28","Independence Day","AZ",2034 +"2034-05-29","Independence Day (Observed)","AZ",2034 +"2034-06-15","National Salvation Day","AZ",2034 +"2034-06-26","Azerbaijan Armed Forces Day","AZ",2034 +"2034-09-27","Memorial Day","AZ",2034 +"2034-11-08","Victory Day","AZ",2034 +"2034-11-09","Flag Day","AZ",2034 +"2034-12-12","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2034 +"2034-12-13","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2034 +"2034-12-31","International Solidarity Day of Azerbaijanis","AZ",2034 +"2035-01-01","New Year's Day","AZ",2035 +"2035-01-02","New Year's Day","AZ",2035 +"2035-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2035 +"2035-01-20","Black January","AZ",2035 +"2035-02-18","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2035 +"2035-02-19","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2035 +"2035-02-20","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2035 +"2035-03-08","International Women's Day","AZ",2035 +"2035-03-20","Novruz","AZ",2035 +"2035-03-21","Novruz","AZ",2035 +"2035-03-22","Novruz","AZ",2035 +"2035-03-23","Novruz","AZ",2035 +"2035-03-24","Novruz","AZ",2035 +"2035-03-26","Novruz (Observed)","AZ",2035 +"2035-05-09","Victory Day over Fascism","AZ",2035 +"2035-05-28","Independence Day","AZ",2035 +"2035-06-15","National Salvation Day","AZ",2035 +"2035-06-26","Azerbaijan Armed Forces Day","AZ",2035 +"2035-09-27","Memorial Day","AZ",2035 +"2035-11-08","Victory Day","AZ",2035 +"2035-11-09","Flag Day","AZ",2035 +"2035-12-01","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2035 +"2035-12-02","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2035 +"2035-12-03","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2035 +"2035-12-04","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2035 +"2035-12-31","International Solidarity Day of Azerbaijanis","AZ",2035 +"2036-01-01","New Year's Day","AZ",2036 +"2036-01-02","New Year's Day","AZ",2036 +"2036-01-20","Black January","AZ",2036 +"2036-02-07","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2036 +"2036-02-08","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2036 +"2036-03-08","International Women's Day","AZ",2036 +"2036-03-10","International Women's Day (Observed)","AZ",2036 +"2036-03-20","Novruz","AZ",2036 +"2036-03-21","Novruz","AZ",2036 +"2036-03-22","Novruz","AZ",2036 +"2036-03-23","Novruz","AZ",2036 +"2036-03-24","Novruz","AZ",2036 +"2036-03-25","Novruz (Observed)","AZ",2036 +"2036-03-26","Novruz (Observed)","AZ",2036 +"2036-05-09","Victory Day over Fascism","AZ",2036 +"2036-05-28","Independence Day","AZ",2036 +"2036-06-15","National Salvation Day","AZ",2036 +"2036-06-16","National Salvation Day (Observed)","AZ",2036 +"2036-06-26","Azerbaijan Armed Forces Day","AZ",2036 +"2036-09-27","Memorial Day","AZ",2036 +"2036-11-08","Victory Day","AZ",2036 +"2036-11-09","Flag Day","AZ",2036 +"2036-11-10","Victory Day (Observed)","AZ",2036 +"2036-11-11","Flag Day (Observed)","AZ",2036 +"2036-11-19","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2036 +"2036-11-20","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2036 +"2036-12-31","International Solidarity Day of Azerbaijanis","AZ",2036 +"2037-01-01","New Year's Day","AZ",2037 +"2037-01-02","New Year's Day","AZ",2037 +"2037-01-20","Black January","AZ",2037 +"2037-01-26","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2037 +"2037-01-27","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2037 +"2037-03-08","International Women's Day","AZ",2037 +"2037-03-09","International Women's Day (Observed)","AZ",2037 +"2037-03-20","Novruz","AZ",2037 +"2037-03-21","Novruz","AZ",2037 +"2037-03-22","Novruz","AZ",2037 +"2037-03-23","Novruz","AZ",2037 +"2037-03-24","Novruz","AZ",2037 +"2037-03-25","Novruz (Observed)","AZ",2037 +"2037-03-26","Novruz (Observed)","AZ",2037 +"2037-05-09","Victory Day over Fascism","AZ",2037 +"2037-05-11","Victory Day over Fascism (Observed)","AZ",2037 +"2037-05-28","Independence Day","AZ",2037 +"2037-06-15","National Salvation Day","AZ",2037 +"2037-06-26","Azerbaijan Armed Forces Day","AZ",2037 +"2037-09-27","Memorial Day","AZ",2037 +"2037-11-08","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2037 +"2037-11-08","Victory Day","AZ",2037 +"2037-11-09","Flag Day","AZ",2037 +"2037-11-09","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2037 +"2037-11-10","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2037 +"2037-11-10","Victory Day (Observed)","AZ",2037 +"2037-11-11","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2037 +"2037-12-31","International Solidarity Day of Azerbaijanis","AZ",2037 +"2038-01-01","New Year's Day","AZ",2038 +"2038-01-02","New Year's Day","AZ",2038 +"2038-01-04","New Year's Day (Observed)","AZ",2038 +"2038-01-16","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2038 +"2038-01-17","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2038 +"2038-01-18","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2038 +"2038-01-19","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2038 +"2038-01-20","Black January","AZ",2038 +"2038-03-08","International Women's Day","AZ",2038 +"2038-03-20","Novruz","AZ",2038 +"2038-03-21","Novruz","AZ",2038 +"2038-03-22","Novruz","AZ",2038 +"2038-03-23","Novruz","AZ",2038 +"2038-03-24","Novruz","AZ",2038 +"2038-03-25","Novruz (Observed)","AZ",2038 +"2038-03-26","Novruz (Observed)","AZ",2038 +"2038-05-09","Victory Day over Fascism","AZ",2038 +"2038-05-10","Victory Day over Fascism (Observed)","AZ",2038 +"2038-05-28","Independence Day","AZ",2038 +"2038-06-15","National Salvation Day","AZ",2038 +"2038-06-26","Azerbaijan Armed Forces Day","AZ",2038 +"2038-06-28","Azerbaijan Armed Forces Day (Observed)","AZ",2038 +"2038-09-27","Memorial Day","AZ",2038 +"2038-10-29","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2038 +"2038-10-30","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2038 +"2038-11-01","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2038 +"2038-11-08","Victory Day","AZ",2038 +"2038-11-09","Flag Day","AZ",2038 +"2038-12-31","International Solidarity Day of Azerbaijanis","AZ",2038 +"2039-01-01","New Year's Day","AZ",2039 +"2039-01-02","New Year's Day","AZ",2039 +"2039-01-03","New Year's Day (Observed)","AZ",2039 +"2039-01-04","New Year's Day (Observed)","AZ",2039 +"2039-01-05","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2039 +"2039-01-06","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2039 +"2039-01-20","Black January","AZ",2039 +"2039-03-08","International Women's Day","AZ",2039 +"2039-03-20","Novruz","AZ",2039 +"2039-03-21","Novruz","AZ",2039 +"2039-03-22","Novruz","AZ",2039 +"2039-03-23","Novruz","AZ",2039 +"2039-03-24","Novruz","AZ",2039 +"2039-03-25","Novruz (Observed)","AZ",2039 +"2039-05-09","Victory Day over Fascism","AZ",2039 +"2039-05-28","Independence Day","AZ",2039 +"2039-05-30","Independence Day (Observed)","AZ",2039 +"2039-06-15","National Salvation Day","AZ",2039 +"2039-06-26","Azerbaijan Armed Forces Day","AZ",2039 +"2039-06-27","Azerbaijan Armed Forces Day (Observed)","AZ",2039 +"2039-09-27","Memorial Day","AZ",2039 +"2039-10-19","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2039 +"2039-10-20","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2039 +"2039-11-08","Victory Day","AZ",2039 +"2039-11-09","Flag Day","AZ",2039 +"2039-12-26","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2039 +"2039-12-27","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2039 +"2039-12-31","International Solidarity Day of Azerbaijanis","AZ",2039 +"2040-01-01","New Year's Day","AZ",2040 +"2040-01-02","New Year's Day","AZ",2040 +"2040-01-03","International Solidarity Day of Azerbaijanis (Observed)","AZ",2040 +"2040-01-04","New Year's Day (Observed)","AZ",2040 +"2040-01-20","Black January","AZ",2040 +"2040-03-08","International Women's Day","AZ",2040 +"2040-03-20","Novruz","AZ",2040 +"2040-03-21","Novruz","AZ",2040 +"2040-03-22","Novruz","AZ",2040 +"2040-03-23","Novruz","AZ",2040 +"2040-03-24","Novruz","AZ",2040 +"2040-03-26","Novruz (Observed)","AZ",2040 +"2040-05-09","Victory Day over Fascism","AZ",2040 +"2040-05-28","Independence Day","AZ",2040 +"2040-06-15","National Salvation Day","AZ",2040 +"2040-06-26","Azerbaijan Armed Forces Day","AZ",2040 +"2040-09-27","Memorial Day","AZ",2040 +"2040-10-07","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2040 +"2040-10-08","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2040 +"2040-10-09","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2040 +"2040-11-08","Victory Day","AZ",2040 +"2040-11-09","Flag Day","AZ",2040 +"2040-12-14","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2040 +"2040-12-15","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2040 +"2040-12-17","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2040 +"2040-12-31","International Solidarity Day of Azerbaijanis","AZ",2040 +"2041-01-01","New Year's Day","AZ",2041 +"2041-01-02","New Year's Day","AZ",2041 +"2041-01-20","Black January","AZ",2041 +"2041-03-08","International Women's Day","AZ",2041 +"2041-03-20","Novruz","AZ",2041 +"2041-03-21","Novruz","AZ",2041 +"2041-03-22","Novruz","AZ",2041 +"2041-03-23","Novruz","AZ",2041 +"2041-03-24","Novruz","AZ",2041 +"2041-03-25","Novruz (Observed)","AZ",2041 +"2041-03-26","Novruz (Observed)","AZ",2041 +"2041-05-09","Victory Day over Fascism","AZ",2041 +"2041-05-28","Independence Day","AZ",2041 +"2041-06-15","National Salvation Day","AZ",2041 +"2041-06-17","National Salvation Day (Observed)","AZ",2041 +"2041-06-26","Azerbaijan Armed Forces Day","AZ",2041 +"2041-09-26","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2041 +"2041-09-27","Memorial Day","AZ",2041 +"2041-09-27","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2041 +"2041-11-08","Victory Day","AZ",2041 +"2041-11-09","Flag Day","AZ",2041 +"2041-11-11","Flag Day (Observed)","AZ",2041 +"2041-12-04","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2041 +"2041-12-05","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2041 +"2041-12-31","International Solidarity Day of Azerbaijanis","AZ",2041 +"2042-01-01","New Year's Day","AZ",2042 +"2042-01-02","New Year's Day","AZ",2042 +"2042-01-20","Black January","AZ",2042 +"2042-03-08","International Women's Day","AZ",2042 +"2042-03-10","International Women's Day (Observed)","AZ",2042 +"2042-03-20","Novruz","AZ",2042 +"2042-03-21","Novruz","AZ",2042 +"2042-03-22","Novruz","AZ",2042 +"2042-03-23","Novruz","AZ",2042 +"2042-03-24","Novruz","AZ",2042 +"2042-03-25","Novruz (Observed)","AZ",2042 +"2042-03-26","Novruz (Observed)","AZ",2042 +"2042-05-09","Victory Day over Fascism","AZ",2042 +"2042-05-28","Independence Day","AZ",2042 +"2042-06-15","National Salvation Day","AZ",2042 +"2042-06-16","National Salvation Day (Observed)","AZ",2042 +"2042-06-26","Azerbaijan Armed Forces Day","AZ",2042 +"2042-09-15","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2042 +"2042-09-16","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2042 +"2042-09-27","Memorial Day","AZ",2042 +"2042-11-08","Victory Day","AZ",2042 +"2042-11-09","Flag Day","AZ",2042 +"2042-11-10","Victory Day (Observed)","AZ",2042 +"2042-11-11","Flag Day (Observed)","AZ",2042 +"2042-11-23","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2042 +"2042-11-24","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2042 +"2042-11-25","Gurban Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2042 +"2042-12-31","International Solidarity Day of Azerbaijanis","AZ",2042 +"2043-01-01","New Year's Day","AZ",2043 +"2043-01-02","New Year's Day","AZ",2043 +"2043-01-20","Black January","AZ",2043 +"2043-03-08","International Women's Day","AZ",2043 +"2043-03-09","International Women's Day (Observed)","AZ",2043 +"2043-03-20","Novruz","AZ",2043 +"2043-03-21","Novruz","AZ",2043 +"2043-03-22","Novruz","AZ",2043 +"2043-03-23","Novruz","AZ",2043 +"2043-03-24","Novruz","AZ",2043 +"2043-03-25","Novruz (Observed)","AZ",2043 +"2043-03-26","Novruz (Observed)","AZ",2043 +"2043-05-09","Victory Day over Fascism","AZ",2043 +"2043-05-11","Victory Day over Fascism (Observed)","AZ",2043 +"2043-05-28","Independence Day","AZ",2043 +"2043-06-15","National Salvation Day","AZ",2043 +"2043-06-26","Azerbaijan Armed Forces Day","AZ",2043 +"2043-09-04","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2043 +"2043-09-05","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2043 +"2043-09-07","Ramazan Bayrami* (*estimated)* (*estimated) (Observed)","AZ",2043 +"2043-09-27","Memorial Day","AZ",2043 +"2043-11-08","Victory Day","AZ",2043 +"2043-11-09","Flag Day","AZ",2043 +"2043-11-10","Victory Day (Observed)","AZ",2043 +"2043-11-12","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2043 +"2043-11-13","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2043 +"2043-12-31","International Solidarity Day of Azerbaijanis","AZ",2043 +"2044-01-01","New Year's Day","AZ",2044 +"2044-01-02","New Year's Day","AZ",2044 +"2044-01-04","New Year's Day (Observed)","AZ",2044 +"2044-01-20","Black January","AZ",2044 +"2044-03-08","International Women's Day","AZ",2044 +"2044-03-20","Novruz","AZ",2044 +"2044-03-21","Novruz","AZ",2044 +"2044-03-22","Novruz","AZ",2044 +"2044-03-23","Novruz","AZ",2044 +"2044-03-24","Novruz","AZ",2044 +"2044-03-25","Novruz (Observed)","AZ",2044 +"2044-05-09","Victory Day over Fascism","AZ",2044 +"2044-05-28","Independence Day","AZ",2044 +"2044-05-30","Independence Day (Observed)","AZ",2044 +"2044-06-15","National Salvation Day","AZ",2044 +"2044-06-26","Azerbaijan Armed Forces Day","AZ",2044 +"2044-06-27","Azerbaijan Armed Forces Day (Observed)","AZ",2044 +"2044-08-24","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2044 +"2044-08-25","Ramazan Bayrami* (*estimated)* (*estimated)","AZ",2044 +"2044-09-27","Memorial Day","AZ",2044 +"2044-10-31","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2044 +"2044-11-01","Gurban Bayrami* (*estimated)* (*estimated)","AZ",2044 +"2044-11-08","Victory Day","AZ",2044 +"2044-11-09","Flag Day","AZ",2044 +"2044-12-31","International Solidarity Day of Azerbaijanis","AZ",2044 +"1995-01-01","Nova Godina","BA",1995 +"1995-01-02","Drugi dan Nove Godine","BA",1995 +"1995-01-07","Bozic","BA",1995 +"1995-03-02","Ramazanski Bajram* (*estimated)","BA",1995 +"1995-04-17","Uskrsni ponedjeljak (Katolicki)","BA",1995 +"1995-04-21","Veliki Petak (Pravoslavni)","BA",1995 +"1995-05-01","Dan rada","BA",1995 +"1995-05-02","Drugi dan Dana rada","BA",1995 +"1995-05-09","Kurban Bajram* (*estimated)","BA",1995 +"1995-12-25","Bozic (Katolicki)","BA",1995 +"1996-01-01","Nova Godina","BA",1996 +"1996-01-02","Drugi dan Nove Godine","BA",1996 +"1996-01-07","Bozic","BA",1996 +"1996-02-19","Ramazanski Bajram* (*estimated)","BA",1996 +"1996-04-08","Uskrsni ponedjeljak (Katolicki)","BA",1996 +"1996-04-12","Veliki Petak (Pravoslavni)","BA",1996 +"1996-04-27","Kurban Bajram* (*estimated)","BA",1996 +"1996-05-01","Dan rada","BA",1996 +"1996-05-02","Drugi dan Dana rada","BA",1996 +"1996-12-25","Bozic (Katolicki)","BA",1996 +"1997-01-01","Nova Godina","BA",1997 +"1997-01-02","Drugi dan Nove Godine","BA",1997 +"1997-01-07","Bozic","BA",1997 +"1997-02-08","Ramazanski Bajram* (*estimated)","BA",1997 +"1997-03-31","Uskrsni ponedjeljak (Katolicki)","BA",1997 +"1997-04-17","Kurban Bajram* (*estimated)","BA",1997 +"1997-04-25","Veliki Petak (Pravoslavni)","BA",1997 +"1997-05-01","Dan rada","BA",1997 +"1997-05-02","Drugi dan Dana rada","BA",1997 +"1997-12-25","Bozic (Katolicki)","BA",1997 +"1998-01-01","Nova Godina","BA",1998 +"1998-01-02","Drugi dan Nove Godine","BA",1998 +"1998-01-07","Bozic","BA",1998 +"1998-01-29","Ramazanski Bajram* (*estimated)","BA",1998 +"1998-04-07","Kurban Bajram* (*estimated)","BA",1998 +"1998-04-13","Uskrsni ponedjeljak (Katolicki)","BA",1998 +"1998-04-17","Veliki Petak (Pravoslavni)","BA",1998 +"1998-05-01","Dan rada","BA",1998 +"1998-05-02","Drugi dan Dana rada","BA",1998 +"1998-12-25","Bozic (Katolicki)","BA",1998 +"1999-01-01","Nova Godina","BA",1999 +"1999-01-02","Drugi dan Nove Godine","BA",1999 +"1999-01-07","Bozic","BA",1999 +"1999-01-18","Ramazanski Bajram* (*estimated)","BA",1999 +"1999-03-27","Kurban Bajram* (*estimated)","BA",1999 +"1999-04-05","Uskrsni ponedjeljak (Katolicki)","BA",1999 +"1999-04-09","Veliki Petak (Pravoslavni)","BA",1999 +"1999-05-01","Dan rada","BA",1999 +"1999-05-02","Drugi dan Dana rada","BA",1999 +"1999-12-25","Bozic (Katolicki)","BA",1999 +"2000-01-01","Nova Godina","BA",2000 +"2000-01-02","Drugi dan Nove Godine","BA",2000 +"2000-01-07","Bozic","BA",2000 +"2000-01-08","Ramazanski Bajram* (*estimated)","BA",2000 +"2000-03-16","Kurban Bajram* (*estimated)","BA",2000 +"2000-04-24","Uskrsni ponedjeljak (Katolicki)","BA",2000 +"2000-04-28","Veliki Petak (Pravoslavni)","BA",2000 +"2000-05-01","Dan rada","BA",2000 +"2000-05-02","Drugi dan Dana rada","BA",2000 +"2000-12-25","Bozic (Katolicki)","BA",2000 +"2000-12-27","Ramazanski Bajram* (*estimated)","BA",2000 +"2001-01-01","Nova Godina","BA",2001 +"2001-01-02","Drugi dan Nove Godine","BA",2001 +"2001-01-07","Bozic","BA",2001 +"2001-03-05","Kurban Bajram* (*estimated)","BA",2001 +"2001-04-13","Veliki Petak (Pravoslavni)","BA",2001 +"2001-04-16","Uskrsni ponedjeljak (Katolicki)","BA",2001 +"2001-05-01","Dan rada","BA",2001 +"2001-05-02","Drugi dan Dana rada","BA",2001 +"2001-12-16","Ramazanski Bajram* (*estimated)","BA",2001 +"2001-12-25","Bozic (Katolicki)","BA",2001 +"2002-01-01","Nova Godina","BA",2002 +"2002-01-02","Drugi dan Nove Godine","BA",2002 +"2002-01-07","Bozic","BA",2002 +"2002-02-22","Kurban Bajram* (*estimated)","BA",2002 +"2002-04-01","Uskrsni ponedjeljak (Katolicki)","BA",2002 +"2002-05-01","Dan rada","BA",2002 +"2002-05-02","Drugi dan Dana rada","BA",2002 +"2002-05-03","Veliki Petak (Pravoslavni)","BA",2002 +"2002-12-05","Ramazanski Bajram* (*estimated)","BA",2002 +"2002-12-25","Bozic (Katolicki)","BA",2002 +"2003-01-01","Nova Godina","BA",2003 +"2003-01-02","Drugi dan Nove Godine","BA",2003 +"2003-01-07","Bozic","BA",2003 +"2003-02-11","Kurban Bajram* (*estimated)","BA",2003 +"2003-04-21","Uskrsni ponedjeljak (Katolicki)","BA",2003 +"2003-04-25","Veliki Petak (Pravoslavni)","BA",2003 +"2003-05-01","Dan rada","BA",2003 +"2003-05-02","Drugi dan Dana rada","BA",2003 +"2003-11-25","Ramazanski Bajram* (*estimated)","BA",2003 +"2003-12-25","Bozic (Katolicki)","BA",2003 +"2004-01-01","Nova Godina","BA",2004 +"2004-01-02","Drugi dan Nove Godine","BA",2004 +"2004-01-07","Bozic","BA",2004 +"2004-02-01","Kurban Bajram* (*estimated)","BA",2004 +"2004-04-09","Veliki Petak (Pravoslavni)","BA",2004 +"2004-04-12","Uskrsni ponedjeljak (Katolicki)","BA",2004 +"2004-05-01","Dan rada","BA",2004 +"2004-05-02","Drugi dan Dana rada","BA",2004 +"2004-11-14","Ramazanski Bajram* (*estimated)","BA",2004 +"2004-12-25","Bozic (Katolicki)","BA",2004 +"2005-01-01","Nova Godina","BA",2005 +"2005-01-02","Drugi dan Nove Godine","BA",2005 +"2005-01-07","Bozic","BA",2005 +"2005-01-21","Kurban Bajram* (*estimated)","BA",2005 +"2005-03-28","Uskrsni ponedjeljak (Katolicki)","BA",2005 +"2005-04-29","Veliki Petak (Pravoslavni)","BA",2005 +"2005-05-01","Dan rada","BA",2005 +"2005-05-02","Drugi dan Dana rada","BA",2005 +"2005-05-03","Treci dan Dana rada","BA",2005 +"2005-11-03","Ramazanski Bajram* (*estimated)","BA",2005 +"2005-12-25","Bozic (Katolicki)","BA",2005 +"2006-01-01","Nova Godina","BA",2006 +"2006-01-02","Drugi dan Nove Godine","BA",2006 +"2006-01-07","Bozic","BA",2006 +"2006-01-10","Kurban Bajram* (*estimated)","BA",2006 +"2006-04-17","Uskrsni ponedjeljak (Katolicki)","BA",2006 +"2006-04-21","Veliki Petak (Pravoslavni)","BA",2006 +"2006-05-01","Dan rada","BA",2006 +"2006-05-02","Drugi dan Dana rada","BA",2006 +"2006-10-23","Ramazanski Bajram* (*estimated)","BA",2006 +"2006-12-25","Bozic (Katolicki)","BA",2006 +"2006-12-31","Kurban Bajram* (*estimated)","BA",2006 +"2007-01-01","Nova Godina","BA",2007 +"2007-01-02","Drugi dan Nove Godine","BA",2007 +"2007-01-07","Bozic","BA",2007 +"2007-04-06","Veliki Petak (Pravoslavni)","BA",2007 +"2007-04-09","Uskrsni ponedjeljak (Katolicki)","BA",2007 +"2007-05-01","Dan rada","BA",2007 +"2007-05-02","Drugi dan Dana rada","BA",2007 +"2007-10-13","Ramazanski Bajram* (*estimated)","BA",2007 +"2007-12-20","Kurban Bajram* (*estimated)","BA",2007 +"2007-12-25","Bozic (Katolicki)","BA",2007 +"2008-01-01","Nova Godina","BA",2008 +"2008-01-02","Drugi dan Nove Godine","BA",2008 +"2008-01-07","Bozic","BA",2008 +"2008-03-24","Uskrsni ponedjeljak (Katolicki)","BA",2008 +"2008-04-25","Veliki Petak (Pravoslavni)","BA",2008 +"2008-05-01","Dan rada","BA",2008 +"2008-05-02","Drugi dan Dana rada","BA",2008 +"2008-10-01","Ramazanski Bajram* (*estimated)","BA",2008 +"2008-12-08","Kurban Bajram* (*estimated)","BA",2008 +"2008-12-25","Bozic (Katolicki)","BA",2008 +"2009-01-01","Nova Godina","BA",2009 +"2009-01-02","Drugi dan Nove Godine","BA",2009 +"2009-01-07","Bozic","BA",2009 +"2009-04-13","Uskrsni ponedjeljak (Katolicki)","BA",2009 +"2009-04-17","Veliki Petak (Pravoslavni)","BA",2009 +"2009-05-01","Dan rada","BA",2009 +"2009-05-02","Drugi dan Dana rada","BA",2009 +"2009-09-20","Ramazanski Bajram* (*estimated)","BA",2009 +"2009-11-27","Kurban Bajram* (*estimated)","BA",2009 +"2009-12-25","Bozic (Katolicki)","BA",2009 +"2010-01-01","Nova Godina","BA",2010 +"2010-01-02","Drugi dan Nove Godine","BA",2010 +"2010-01-07","Bozic","BA",2010 +"2010-04-02","Veliki Petak (Pravoslavni)","BA",2010 +"2010-04-05","Uskrsni ponedjeljak (Katolicki)","BA",2010 +"2010-05-01","Dan rada","BA",2010 +"2010-05-02","Drugi dan Dana rada","BA",2010 +"2010-09-10","Ramazanski Bajram* (*estimated)","BA",2010 +"2010-11-16","Kurban Bajram* (*estimated)","BA",2010 +"2010-12-25","Bozic (Katolicki)","BA",2010 +"2011-01-01","Nova Godina","BA",2011 +"2011-01-02","Drugi dan Nove Godine","BA",2011 +"2011-01-07","Bozic","BA",2011 +"2011-04-22","Veliki Petak (Pravoslavni)","BA",2011 +"2011-04-25","Uskrsni ponedjeljak (Katolicki)","BA",2011 +"2011-05-01","Dan rada","BA",2011 +"2011-05-02","Drugi dan Dana rada","BA",2011 +"2011-05-03","Treci dan Dana rada","BA",2011 +"2011-08-30","Ramazanski Bajram* (*estimated)","BA",2011 +"2011-11-06","Kurban Bajram* (*estimated)","BA",2011 +"2011-12-25","Bozic (Katolicki)","BA",2011 +"2012-01-01","Nova Godina","BA",2012 +"2012-01-02","Drugi dan Nove Godine","BA",2012 +"2012-01-07","Bozic","BA",2012 +"2012-04-09","Uskrsni ponedjeljak (Katolicki)","BA",2012 +"2012-04-13","Veliki Petak (Pravoslavni)","BA",2012 +"2012-05-01","Dan rada","BA",2012 +"2012-05-02","Drugi dan Dana rada","BA",2012 +"2012-08-19","Ramazanski Bajram* (*estimated)","BA",2012 +"2012-10-26","Kurban Bajram* (*estimated)","BA",2012 +"2012-12-25","Bozic (Katolicki)","BA",2012 +"2013-01-01","Nova Godina","BA",2013 +"2013-01-02","Drugi dan Nove Godine","BA",2013 +"2013-01-07","Bozic","BA",2013 +"2013-04-01","Uskrsni ponedjeljak (Katolicki)","BA",2013 +"2013-05-01","Dan rada","BA",2013 +"2013-05-02","Drugi dan Dana rada","BA",2013 +"2013-05-03","Veliki Petak (Pravoslavni)","BA",2013 +"2013-08-08","Ramazanski Bajram* (*estimated)","BA",2013 +"2013-10-15","Kurban Bajram* (*estimated)","BA",2013 +"2013-12-25","Bozic (Katolicki)","BA",2013 +"2014-01-01","Nova Godina","BA",2014 +"2014-01-02","Drugi dan Nove Godine","BA",2014 +"2014-01-07","Bozic","BA",2014 +"2014-04-18","Veliki Petak (Pravoslavni)","BA",2014 +"2014-04-21","Uskrsni ponedjeljak (Katolicki)","BA",2014 +"2014-05-01","Dan rada","BA",2014 +"2014-05-02","Drugi dan Dana rada","BA",2014 +"2014-07-28","Ramazanski Bajram* (*estimated)","BA",2014 +"2014-10-04","Kurban Bajram* (*estimated)","BA",2014 +"2014-12-25","Bozic (Katolicki)","BA",2014 +"2015-01-01","Nova Godina","BA",2015 +"2015-01-02","Drugi dan Nove Godine","BA",2015 +"2015-01-07","Bozic","BA",2015 +"2015-04-06","Uskrsni ponedjeljak (Katolicki)","BA",2015 +"2015-04-10","Veliki Petak (Pravoslavni)","BA",2015 +"2015-05-01","Dan rada","BA",2015 +"2015-05-02","Drugi dan Dana rada","BA",2015 +"2015-07-17","Ramazanski Bajram* (*estimated)","BA",2015 +"2015-09-23","Kurban Bajram* (*estimated)","BA",2015 +"2015-12-25","Bozic (Katolicki)","BA",2015 +"2016-01-01","Nova Godina","BA",2016 +"2016-01-02","Drugi dan Nove Godine","BA",2016 +"2016-01-07","Bozic","BA",2016 +"2016-03-28","Uskrsni ponedjeljak (Katolicki)","BA",2016 +"2016-04-29","Veliki Petak (Pravoslavni)","BA",2016 +"2016-05-01","Dan rada","BA",2016 +"2016-05-02","Drugi dan Dana rada","BA",2016 +"2016-05-03","Treci dan Dana rada","BA",2016 +"2016-07-06","Ramazanski Bajram* (*estimated)","BA",2016 +"2016-09-11","Kurban Bajram* (*estimated)","BA",2016 +"2016-12-25","Bozic (Katolicki)","BA",2016 +"2017-01-01","Nova Godina","BA",2017 +"2017-01-02","Drugi dan Nove Godine","BA",2017 +"2017-01-07","Bozic","BA",2017 +"2017-04-14","Veliki Petak (Pravoslavni)","BA",2017 +"2017-04-17","Uskrsni ponedjeljak (Katolicki)","BA",2017 +"2017-05-01","Dan rada","BA",2017 +"2017-05-02","Drugi dan Dana rada","BA",2017 +"2017-06-25","Ramazanski Bajram* (*estimated)","BA",2017 +"2017-09-01","Kurban Bajram* (*estimated)","BA",2017 +"2017-12-25","Bozic (Katolicki)","BA",2017 +"2018-01-01","Nova Godina","BA",2018 +"2018-01-02","Drugi dan Nove Godine","BA",2018 +"2018-01-07","Bozic","BA",2018 +"2018-04-02","Uskrsni ponedjeljak (Katolicki)","BA",2018 +"2018-04-06","Veliki Petak (Pravoslavni)","BA",2018 +"2018-05-01","Dan rada","BA",2018 +"2018-05-02","Drugi dan Dana rada","BA",2018 +"2018-06-15","Ramazanski Bajram* (*estimated)","BA",2018 +"2018-08-21","Kurban Bajram* (*estimated)","BA",2018 +"2018-12-25","Bozic (Katolicki)","BA",2018 +"2019-01-01","Nova Godina","BA",2019 +"2019-01-02","Drugi dan Nove Godine","BA",2019 +"2019-01-07","Bozic","BA",2019 +"2019-04-22","Uskrsni ponedjeljak (Katolicki)","BA",2019 +"2019-04-26","Veliki Petak (Pravoslavni)","BA",2019 +"2019-05-01","Dan rada","BA",2019 +"2019-05-02","Drugi dan Dana rada","BA",2019 +"2019-06-04","Ramazanski Bajram* (*estimated)","BA",2019 +"2019-08-11","Kurban Bajram* (*estimated)","BA",2019 +"2019-12-25","Bozic (Katolicki)","BA",2019 +"2020-01-01","Nova Godina","BA",2020 +"2020-01-02","Drugi dan Nove Godine","BA",2020 +"2020-01-07","Bozic","BA",2020 +"2020-04-13","Uskrsni ponedjeljak (Katolicki)","BA",2020 +"2020-04-17","Veliki Petak (Pravoslavni)","BA",2020 +"2020-05-01","Dan rada","BA",2020 +"2020-05-02","Drugi dan Dana rada","BA",2020 +"2020-05-24","Ramazanski Bajram* (*estimated)","BA",2020 +"2020-07-31","Kurban Bajram* (*estimated)","BA",2020 +"2020-12-25","Bozic (Katolicki)","BA",2020 +"2021-01-01","Nova Godina","BA",2021 +"2021-01-02","Drugi dan Nove Godine","BA",2021 +"2021-01-07","Bozic","BA",2021 +"2021-04-05","Uskrsni ponedjeljak (Katolicki)","BA",2021 +"2021-04-30","Veliki Petak (Pravoslavni)","BA",2021 +"2021-05-01","Dan rada","BA",2021 +"2021-05-02","Drugi dan Dana rada","BA",2021 +"2021-05-13","Ramazanski Bajram* (*estimated)","BA",2021 +"2021-07-20","Kurban Bajram* (*estimated)","BA",2021 +"2021-12-25","Bozic (Katolicki)","BA",2021 +"2022-01-01","Nova Godina","BA",2022 +"2022-01-02","Drugi dan Nove Godine","BA",2022 +"2022-01-07","Bozic","BA",2022 +"2022-04-18","Uskrsni ponedjeljak (Katolicki)","BA",2022 +"2022-04-22","Veliki Petak (Pravoslavni)","BA",2022 +"2022-05-01","Dan rada","BA",2022 +"2022-05-02","Drugi dan Dana rada","BA",2022 +"2022-05-02","Ramazanski Bajram* (*estimated)","BA",2022 +"2022-05-03","Treci dan Dana rada","BA",2022 +"2022-07-09","Kurban Bajram* (*estimated)","BA",2022 +"2022-12-25","Bozic (Katolicki)","BA",2022 +"2023-01-01","Nova Godina","BA",2023 +"2023-01-02","Drugi dan Nove Godine","BA",2023 +"2023-01-07","Bozic","BA",2023 +"2023-04-10","Uskrsni ponedjeljak (Katolicki)","BA",2023 +"2023-04-14","Veliki Petak (Pravoslavni)","BA",2023 +"2023-04-21","Ramazanski Bajram* (*estimated)","BA",2023 +"2023-05-01","Dan rada","BA",2023 +"2023-05-02","Drugi dan Dana rada","BA",2023 +"2023-06-28","Kurban Bajram* (*estimated)","BA",2023 +"2023-12-25","Bozic (Katolicki)","BA",2023 +"2024-01-01","Nova Godina","BA",2024 +"2024-01-02","Drugi dan Nove Godine","BA",2024 +"2024-01-07","Bozic","BA",2024 +"2024-04-01","Uskrsni ponedjeljak (Katolicki)","BA",2024 +"2024-04-10","Ramazanski Bajram* (*estimated)","BA",2024 +"2024-05-01","Dan rada","BA",2024 +"2024-05-02","Drugi dan Dana rada","BA",2024 +"2024-05-03","Veliki Petak (Pravoslavni)","BA",2024 +"2024-06-16","Kurban Bajram* (*estimated)","BA",2024 +"2024-12-25","Bozic (Katolicki)","BA",2024 +"2025-01-01","Nova Godina","BA",2025 +"2025-01-02","Drugi dan Nove Godine","BA",2025 +"2025-01-07","Bozic","BA",2025 +"2025-03-30","Ramazanski Bajram* (*estimated)","BA",2025 +"2025-04-18","Veliki Petak (Pravoslavni)","BA",2025 +"2025-04-21","Uskrsni ponedjeljak (Katolicki)","BA",2025 +"2025-05-01","Dan rada","BA",2025 +"2025-05-02","Drugi dan Dana rada","BA",2025 +"2025-06-06","Kurban Bajram* (*estimated)","BA",2025 +"2025-12-25","Bozic (Katolicki)","BA",2025 +"2026-01-01","Nova Godina","BA",2026 +"2026-01-02","Drugi dan Nove Godine","BA",2026 +"2026-01-07","Bozic","BA",2026 +"2026-03-20","Ramazanski Bajram* (*estimated)","BA",2026 +"2026-04-06","Uskrsni ponedjeljak (Katolicki)","BA",2026 +"2026-04-10","Veliki Petak (Pravoslavni)","BA",2026 +"2026-05-01","Dan rada","BA",2026 +"2026-05-02","Drugi dan Dana rada","BA",2026 +"2026-05-27","Kurban Bajram* (*estimated)","BA",2026 +"2026-12-25","Bozic (Katolicki)","BA",2026 +"2027-01-01","Nova Godina","BA",2027 +"2027-01-02","Drugi dan Nove Godine","BA",2027 +"2027-01-07","Bozic","BA",2027 +"2027-03-09","Ramazanski Bajram* (*estimated)","BA",2027 +"2027-03-29","Uskrsni ponedjeljak (Katolicki)","BA",2027 +"2027-04-30","Veliki Petak (Pravoslavni)","BA",2027 +"2027-05-01","Dan rada","BA",2027 +"2027-05-02","Drugi dan Dana rada","BA",2027 +"2027-05-16","Kurban Bajram* (*estimated)","BA",2027 +"2027-12-25","Bozic (Katolicki)","BA",2027 +"2028-01-01","Nova Godina","BA",2028 +"2028-01-02","Drugi dan Nove Godine","BA",2028 +"2028-01-07","Bozic","BA",2028 +"2028-02-26","Ramazanski Bajram* (*estimated)","BA",2028 +"2028-04-14","Veliki Petak (Pravoslavni)","BA",2028 +"2028-04-17","Uskrsni ponedjeljak (Katolicki)","BA",2028 +"2028-05-01","Dan rada","BA",2028 +"2028-05-02","Drugi dan Dana rada","BA",2028 +"2028-05-05","Kurban Bajram* (*estimated)","BA",2028 +"2028-12-25","Bozic (Katolicki)","BA",2028 +"2029-01-01","Nova Godina","BA",2029 +"2029-01-02","Drugi dan Nove Godine","BA",2029 +"2029-01-07","Bozic","BA",2029 +"2029-02-14","Ramazanski Bajram* (*estimated)","BA",2029 +"2029-04-02","Uskrsni ponedjeljak (Katolicki)","BA",2029 +"2029-04-06","Veliki Petak (Pravoslavni)","BA",2029 +"2029-04-24","Kurban Bajram* (*estimated)","BA",2029 +"2029-05-01","Dan rada","BA",2029 +"2029-05-02","Drugi dan Dana rada","BA",2029 +"2029-12-25","Bozic (Katolicki)","BA",2029 +"2030-01-01","Nova Godina","BA",2030 +"2030-01-02","Drugi dan Nove Godine","BA",2030 +"2030-01-07","Bozic","BA",2030 +"2030-02-04","Ramazanski Bajram* (*estimated)","BA",2030 +"2030-04-13","Kurban Bajram* (*estimated)","BA",2030 +"2030-04-22","Uskrsni ponedjeljak (Katolicki)","BA",2030 +"2030-04-26","Veliki Petak (Pravoslavni)","BA",2030 +"2030-05-01","Dan rada","BA",2030 +"2030-05-02","Drugi dan Dana rada","BA",2030 +"2030-12-25","Bozic (Katolicki)","BA",2030 +"2031-01-01","Nova Godina","BA",2031 +"2031-01-02","Drugi dan Nove Godine","BA",2031 +"2031-01-07","Bozic","BA",2031 +"2031-01-24","Ramazanski Bajram* (*estimated)","BA",2031 +"2031-04-02","Kurban Bajram* (*estimated)","BA",2031 +"2031-04-11","Veliki Petak (Pravoslavni)","BA",2031 +"2031-04-14","Uskrsni ponedjeljak (Katolicki)","BA",2031 +"2031-05-01","Dan rada","BA",2031 +"2031-05-02","Drugi dan Dana rada","BA",2031 +"2031-12-25","Bozic (Katolicki)","BA",2031 +"2032-01-01","Nova Godina","BA",2032 +"2032-01-02","Drugi dan Nove Godine","BA",2032 +"2032-01-07","Bozic","BA",2032 +"2032-01-14","Ramazanski Bajram* (*estimated)","BA",2032 +"2032-03-22","Kurban Bajram* (*estimated)","BA",2032 +"2032-03-29","Uskrsni ponedjeljak (Katolicki)","BA",2032 +"2032-04-30","Veliki Petak (Pravoslavni)","BA",2032 +"2032-05-01","Dan rada","BA",2032 +"2032-05-02","Drugi dan Dana rada","BA",2032 +"2032-12-25","Bozic (Katolicki)","BA",2032 +"2033-01-01","Nova Godina","BA",2033 +"2033-01-02","Drugi dan Nove Godine","BA",2033 +"2033-01-02","Ramazanski Bajram* (*estimated)","BA",2033 +"2033-01-07","Bozic","BA",2033 +"2033-03-11","Kurban Bajram* (*estimated)","BA",2033 +"2033-04-18","Uskrsni ponedjeljak (Katolicki)","BA",2033 +"2033-04-22","Veliki Petak (Pravoslavni)","BA",2033 +"2033-05-01","Dan rada","BA",2033 +"2033-05-02","Drugi dan Dana rada","BA",2033 +"2033-05-03","Treci dan Dana rada","BA",2033 +"2033-12-23","Ramazanski Bajram* (*estimated)","BA",2033 +"2033-12-25","Bozic (Katolicki)","BA",2033 +"2034-01-01","Nova Godina","BA",2034 +"2034-01-02","Drugi dan Nove Godine","BA",2034 +"2034-01-07","Bozic","BA",2034 +"2034-03-01","Kurban Bajram* (*estimated)","BA",2034 +"2034-04-07","Veliki Petak (Pravoslavni)","BA",2034 +"2034-04-10","Uskrsni ponedjeljak (Katolicki)","BA",2034 +"2034-05-01","Dan rada","BA",2034 +"2034-05-02","Drugi dan Dana rada","BA",2034 +"2034-12-12","Ramazanski Bajram* (*estimated)","BA",2034 +"2034-12-25","Bozic (Katolicki)","BA",2034 +"2035-01-01","Nova Godina","BA",2035 +"2035-01-02","Drugi dan Nove Godine","BA",2035 +"2035-01-07","Bozic","BA",2035 +"2035-02-18","Kurban Bajram* (*estimated)","BA",2035 +"2035-03-26","Uskrsni ponedjeljak (Katolicki)","BA",2035 +"2035-04-27","Veliki Petak (Pravoslavni)","BA",2035 +"2035-05-01","Dan rada","BA",2035 +"2035-05-02","Drugi dan Dana rada","BA",2035 +"2035-12-01","Ramazanski Bajram* (*estimated)","BA",2035 +"2035-12-25","Bozic (Katolicki)","BA",2035 +"2036-01-01","Nova Godina","BA",2036 +"2036-01-02","Drugi dan Nove Godine","BA",2036 +"2036-01-07","Bozic","BA",2036 +"2036-02-07","Kurban Bajram* (*estimated)","BA",2036 +"2036-04-14","Uskrsni ponedjeljak (Katolicki)","BA",2036 +"2036-04-18","Veliki Petak (Pravoslavni)","BA",2036 +"2036-05-01","Dan rada","BA",2036 +"2036-05-02","Drugi dan Dana rada","BA",2036 +"2036-11-19","Ramazanski Bajram* (*estimated)","BA",2036 +"2036-12-25","Bozic (Katolicki)","BA",2036 +"2037-01-01","Nova Godina","BA",2037 +"2037-01-02","Drugi dan Nove Godine","BA",2037 +"2037-01-07","Bozic","BA",2037 +"2037-01-26","Kurban Bajram* (*estimated)","BA",2037 +"2037-04-03","Veliki Petak (Pravoslavni)","BA",2037 +"2037-04-06","Uskrsni ponedjeljak (Katolicki)","BA",2037 +"2037-05-01","Dan rada","BA",2037 +"2037-05-02","Drugi dan Dana rada","BA",2037 +"2037-11-08","Ramazanski Bajram* (*estimated)","BA",2037 +"2037-12-25","Bozic (Katolicki)","BA",2037 +"2038-01-01","Nova Godina","BA",2038 +"2038-01-02","Drugi dan Nove Godine","BA",2038 +"2038-01-07","Bozic","BA",2038 +"2038-01-16","Kurban Bajram* (*estimated)","BA",2038 +"2038-04-23","Veliki Petak (Pravoslavni)","BA",2038 +"2038-04-26","Uskrsni ponedjeljak (Katolicki)","BA",2038 +"2038-05-01","Dan rada","BA",2038 +"2038-05-02","Drugi dan Dana rada","BA",2038 +"2038-10-29","Ramazanski Bajram* (*estimated)","BA",2038 +"2038-12-25","Bozic (Katolicki)","BA",2038 +"2039-01-01","Nova Godina","BA",2039 +"2039-01-02","Drugi dan Nove Godine","BA",2039 +"2039-01-05","Kurban Bajram* (*estimated)","BA",2039 +"2039-01-07","Bozic","BA",2039 +"2039-04-11","Uskrsni ponedjeljak (Katolicki)","BA",2039 +"2039-04-15","Veliki Petak (Pravoslavni)","BA",2039 +"2039-05-01","Dan rada","BA",2039 +"2039-05-02","Drugi dan Dana rada","BA",2039 +"2039-05-03","Treci dan Dana rada","BA",2039 +"2039-10-19","Ramazanski Bajram* (*estimated)","BA",2039 +"2039-12-25","Bozic (Katolicki)","BA",2039 +"2039-12-26","Kurban Bajram* (*estimated)","BA",2039 +"2040-01-01","Nova Godina","BA",2040 +"2040-01-02","Drugi dan Nove Godine","BA",2040 +"2040-01-07","Bozic","BA",2040 +"2040-04-02","Uskrsni ponedjeljak (Katolicki)","BA",2040 +"2040-05-01","Dan rada","BA",2040 +"2040-05-02","Drugi dan Dana rada","BA",2040 +"2040-05-04","Veliki Petak (Pravoslavni)","BA",2040 +"2040-10-07","Ramazanski Bajram* (*estimated)","BA",2040 +"2040-12-14","Kurban Bajram* (*estimated)","BA",2040 +"2040-12-25","Bozic (Katolicki)","BA",2040 +"2041-01-01","Nova Godina","BA",2041 +"2041-01-02","Drugi dan Nove Godine","BA",2041 +"2041-01-07","Bozic","BA",2041 +"2041-04-19","Veliki Petak (Pravoslavni)","BA",2041 +"2041-04-22","Uskrsni ponedjeljak (Katolicki)","BA",2041 +"2041-05-01","Dan rada","BA",2041 +"2041-05-02","Drugi dan Dana rada","BA",2041 +"2041-09-26","Ramazanski Bajram* (*estimated)","BA",2041 +"2041-12-04","Kurban Bajram* (*estimated)","BA",2041 +"2041-12-25","Bozic (Katolicki)","BA",2041 +"2042-01-01","Nova Godina","BA",2042 +"2042-01-02","Drugi dan Nove Godine","BA",2042 +"2042-01-07","Bozic","BA",2042 +"2042-04-07","Uskrsni ponedjeljak (Katolicki)","BA",2042 +"2042-04-11","Veliki Petak (Pravoslavni)","BA",2042 +"2042-05-01","Dan rada","BA",2042 +"2042-05-02","Drugi dan Dana rada","BA",2042 +"2042-09-15","Ramazanski Bajram* (*estimated)","BA",2042 +"2042-11-23","Kurban Bajram* (*estimated)","BA",2042 +"2042-12-25","Bozic (Katolicki)","BA",2042 +"2043-01-01","Nova Godina","BA",2043 +"2043-01-02","Drugi dan Nove Godine","BA",2043 +"2043-01-07","Bozic","BA",2043 +"2043-03-30","Uskrsni ponedjeljak (Katolicki)","BA",2043 +"2043-05-01","Dan rada","BA",2043 +"2043-05-01","Veliki Petak (Pravoslavni)","BA",2043 +"2043-05-02","Drugi dan Dana rada","BA",2043 +"2043-09-04","Ramazanski Bajram* (*estimated)","BA",2043 +"2043-11-12","Kurban Bajram* (*estimated)","BA",2043 +"2043-12-25","Bozic (Katolicki)","BA",2043 +"2044-01-01","Nova Godina","BA",2044 +"2044-01-02","Drugi dan Nove Godine","BA",2044 +"2044-01-07","Bozic","BA",2044 +"2044-04-18","Uskrsni ponedjeljak (Katolicki)","BA",2044 +"2044-04-22","Veliki Petak (Pravoslavni)","BA",2044 +"2044-05-01","Dan rada","BA",2044 +"2044-05-02","Drugi dan Dana rada","BA",2044 +"2044-05-03","Treci dan Dana rada","BA",2044 +"2044-08-24","Ramazanski Bajram* (*estimated)","BA",2044 +"2044-10-31","Kurban Bajram* (*estimated)","BA",2044 +"2044-12-25","Bozic (Katolicki)","BA",2044 +"1995-02-21","International Mother's language Day","BD",1995 +"1995-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",1995 +"1995-03-26","Independence Day","BD",1995 +"1995-04-14","Bengali New Year's Day","BD",1995 +"1995-05-01","May Day","BD",1995 +"1995-08-15","National Mourning Day","BD",1995 +"1995-12-16","Victory Day","BD",1995 +"1996-02-21","International Mother's language Day","BD",1996 +"1996-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",1996 +"1996-03-26","Independence Day","BD",1996 +"1996-04-14","Bengali New Year's Day","BD",1996 +"1996-05-01","May Day","BD",1996 +"1996-08-15","National Mourning Day","BD",1996 +"1996-12-16","Victory Day","BD",1996 +"1997-02-21","International Mother's language Day","BD",1997 +"1997-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",1997 +"1997-03-26","Independence Day","BD",1997 +"1997-04-14","Bengali New Year's Day","BD",1997 +"1997-05-01","May Day","BD",1997 +"1997-08-15","National Mourning Day","BD",1997 +"1997-12-16","Victory Day","BD",1997 +"1998-02-21","International Mother's language Day","BD",1998 +"1998-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",1998 +"1998-03-26","Independence Day","BD",1998 +"1998-04-14","Bengali New Year's Day","BD",1998 +"1998-05-01","May Day","BD",1998 +"1998-08-15","National Mourning Day","BD",1998 +"1998-12-16","Victory Day","BD",1998 +"1999-02-21","International Mother's language Day","BD",1999 +"1999-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",1999 +"1999-03-26","Independence Day","BD",1999 +"1999-04-14","Bengali New Year's Day","BD",1999 +"1999-05-01","May Day","BD",1999 +"1999-08-15","National Mourning Day","BD",1999 +"1999-12-16","Victory Day","BD",1999 +"2000-02-21","International Mother's language Day","BD",2000 +"2000-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2000 +"2000-03-26","Independence Day","BD",2000 +"2000-04-14","Bengali New Year's Day","BD",2000 +"2000-05-01","May Day","BD",2000 +"2000-08-15","National Mourning Day","BD",2000 +"2000-12-16","Victory Day","BD",2000 +"2001-02-21","International Mother's language Day","BD",2001 +"2001-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2001 +"2001-03-26","Independence Day","BD",2001 +"2001-04-14","Bengali New Year's Day","BD",2001 +"2001-05-01","May Day","BD",2001 +"2001-08-15","National Mourning Day","BD",2001 +"2001-12-16","Victory Day","BD",2001 +"2002-02-21","International Mother's language Day","BD",2002 +"2002-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2002 +"2002-03-26","Independence Day","BD",2002 +"2002-04-14","Bengali New Year's Day","BD",2002 +"2002-05-01","May Day","BD",2002 +"2002-08-15","National Mourning Day","BD",2002 +"2002-12-16","Victory Day","BD",2002 +"2003-02-21","International Mother's language Day","BD",2003 +"2003-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2003 +"2003-03-26","Independence Day","BD",2003 +"2003-04-14","Bengali New Year's Day","BD",2003 +"2003-05-01","May Day","BD",2003 +"2003-08-15","National Mourning Day","BD",2003 +"2003-12-16","Victory Day","BD",2003 +"2004-02-21","International Mother's language Day","BD",2004 +"2004-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2004 +"2004-03-26","Independence Day","BD",2004 +"2004-04-14","Bengali New Year's Day","BD",2004 +"2004-05-01","May Day","BD",2004 +"2004-08-15","National Mourning Day","BD",2004 +"2004-12-16","Victory Day","BD",2004 +"2005-02-21","International Mother's language Day","BD",2005 +"2005-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2005 +"2005-03-26","Independence Day","BD",2005 +"2005-04-14","Bengali New Year's Day","BD",2005 +"2005-05-01","May Day","BD",2005 +"2005-08-15","National Mourning Day","BD",2005 +"2005-12-16","Victory Day","BD",2005 +"2006-02-21","International Mother's language Day","BD",2006 +"2006-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2006 +"2006-03-26","Independence Day","BD",2006 +"2006-04-14","Bengali New Year's Day","BD",2006 +"2006-05-01","May Day","BD",2006 +"2006-08-15","National Mourning Day","BD",2006 +"2006-12-16","Victory Day","BD",2006 +"2007-02-21","International Mother's language Day","BD",2007 +"2007-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2007 +"2007-03-26","Independence Day","BD",2007 +"2007-04-14","Bengali New Year's Day","BD",2007 +"2007-05-01","May Day","BD",2007 +"2007-08-15","National Mourning Day","BD",2007 +"2007-12-16","Victory Day","BD",2007 +"2008-02-21","International Mother's language Day","BD",2008 +"2008-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2008 +"2008-03-26","Independence Day","BD",2008 +"2008-04-14","Bengali New Year's Day","BD",2008 +"2008-05-01","May Day","BD",2008 +"2008-08-15","National Mourning Day","BD",2008 +"2008-12-16","Victory Day","BD",2008 +"2009-02-21","International Mother's language Day","BD",2009 +"2009-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2009 +"2009-03-26","Independence Day","BD",2009 +"2009-04-14","Bengali New Year's Day","BD",2009 +"2009-05-01","May Day","BD",2009 +"2009-08-15","National Mourning Day","BD",2009 +"2009-12-16","Victory Day","BD",2009 +"2010-02-21","International Mother's language Day","BD",2010 +"2010-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2010 +"2010-03-26","Independence Day","BD",2010 +"2010-04-14","Bengali New Year's Day","BD",2010 +"2010-05-01","May Day","BD",2010 +"2010-08-15","National Mourning Day","BD",2010 +"2010-12-16","Victory Day","BD",2010 +"2011-02-21","International Mother's language Day","BD",2011 +"2011-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2011 +"2011-03-26","Independence Day","BD",2011 +"2011-04-14","Bengali New Year's Day","BD",2011 +"2011-05-01","May Day","BD",2011 +"2011-08-15","National Mourning Day","BD",2011 +"2011-12-16","Victory Day","BD",2011 +"2012-02-21","International Mother's language Day","BD",2012 +"2012-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2012 +"2012-03-26","Independence Day","BD",2012 +"2012-04-14","Bengali New Year's Day","BD",2012 +"2012-05-01","May Day","BD",2012 +"2012-08-15","National Mourning Day","BD",2012 +"2012-12-16","Victory Day","BD",2012 +"2013-02-21","International Mother's language Day","BD",2013 +"2013-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2013 +"2013-03-26","Independence Day","BD",2013 +"2013-04-14","Bengali New Year's Day","BD",2013 +"2013-05-01","May Day","BD",2013 +"2013-08-15","National Mourning Day","BD",2013 +"2013-12-16","Victory Day","BD",2013 +"2014-02-21","International Mother's language Day","BD",2014 +"2014-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2014 +"2014-03-26","Independence Day","BD",2014 +"2014-04-14","Bengali New Year's Day","BD",2014 +"2014-05-01","May Day","BD",2014 +"2014-08-15","National Mourning Day","BD",2014 +"2014-12-16","Victory Day","BD",2014 +"2015-02-21","International Mother's language Day","BD",2015 +"2015-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2015 +"2015-03-26","Independence Day","BD",2015 +"2015-04-14","Bengali New Year's Day","BD",2015 +"2015-05-01","May Day","BD",2015 +"2015-08-15","National Mourning Day","BD",2015 +"2015-12-16","Victory Day","BD",2015 +"2016-02-21","International Mother's language Day","BD",2016 +"2016-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2016 +"2016-03-26","Independence Day","BD",2016 +"2016-04-14","Bengali New Year's Day","BD",2016 +"2016-05-01","May Day","BD",2016 +"2016-08-15","National Mourning Day","BD",2016 +"2016-12-16","Victory Day","BD",2016 +"2017-02-21","International Mother's language Day","BD",2017 +"2017-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2017 +"2017-03-26","Independence Day","BD",2017 +"2017-04-14","Bengali New Year's Day","BD",2017 +"2017-05-01","May Day","BD",2017 +"2017-08-15","National Mourning Day","BD",2017 +"2017-12-16","Victory Day","BD",2017 +"2018-02-21","International Mother's language Day","BD",2018 +"2018-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2018 +"2018-03-26","Independence Day","BD",2018 +"2018-04-14","Bengali New Year's Day","BD",2018 +"2018-05-01","May Day","BD",2018 +"2018-08-15","National Mourning Day","BD",2018 +"2018-12-16","Victory Day","BD",2018 +"2019-02-21","International Mother's language Day","BD",2019 +"2019-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2019 +"2019-03-26","Independence Day","BD",2019 +"2019-04-14","Bengali New Year's Day","BD",2019 +"2019-05-01","May Day","BD",2019 +"2019-08-15","National Mourning Day","BD",2019 +"2019-12-16","Victory Day","BD",2019 +"2020-02-21","International Mother's language Day","BD",2020 +"2020-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2020 +"2020-03-26","Independence Day","BD",2020 +"2020-04-14","Bengali New Year's Day","BD",2020 +"2020-05-01","May Day","BD",2020 +"2020-08-15","National Mourning Day","BD",2020 +"2020-12-16","Victory Day","BD",2020 +"2021-02-21","International Mother's language Day","BD",2021 +"2021-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2021 +"2021-03-26","Independence Day","BD",2021 +"2021-04-14","Bengali New Year's Day","BD",2021 +"2021-05-01","May Day","BD",2021 +"2021-08-15","National Mourning Day","BD",2021 +"2021-12-16","Victory Day","BD",2021 +"2022-02-21","International Mother's language Day","BD",2022 +"2022-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2022 +"2022-03-26","Independence Day","BD",2022 +"2022-04-14","Bengali New Year's Day","BD",2022 +"2022-05-01","May Day","BD",2022 +"2022-08-15","National Mourning Day","BD",2022 +"2022-12-16","Victory Day","BD",2022 +"2023-02-21","International Mother's language Day","BD",2023 +"2023-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2023 +"2023-03-26","Independence Day","BD",2023 +"2023-04-14","Bengali New Year's Day","BD",2023 +"2023-05-01","May Day","BD",2023 +"2023-08-15","National Mourning Day","BD",2023 +"2023-12-16","Victory Day","BD",2023 +"2024-02-21","International Mother's language Day","BD",2024 +"2024-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2024 +"2024-03-26","Independence Day","BD",2024 +"2024-04-14","Bengali New Year's Day","BD",2024 +"2024-05-01","May Day","BD",2024 +"2024-08-15","National Mourning Day","BD",2024 +"2024-12-16","Victory Day","BD",2024 +"2025-02-21","International Mother's language Day","BD",2025 +"2025-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2025 +"2025-03-26","Independence Day","BD",2025 +"2025-04-14","Bengali New Year's Day","BD",2025 +"2025-05-01","May Day","BD",2025 +"2025-08-15","National Mourning Day","BD",2025 +"2025-12-16","Victory Day","BD",2025 +"2026-02-21","International Mother's language Day","BD",2026 +"2026-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2026 +"2026-03-26","Independence Day","BD",2026 +"2026-04-14","Bengali New Year's Day","BD",2026 +"2026-05-01","May Day","BD",2026 +"2026-08-15","National Mourning Day","BD",2026 +"2026-12-16","Victory Day","BD",2026 +"2027-02-21","International Mother's language Day","BD",2027 +"2027-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2027 +"2027-03-26","Independence Day","BD",2027 +"2027-04-14","Bengali New Year's Day","BD",2027 +"2027-05-01","May Day","BD",2027 +"2027-08-15","National Mourning Day","BD",2027 +"2027-12-16","Victory Day","BD",2027 +"2028-02-21","International Mother's language Day","BD",2028 +"2028-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2028 +"2028-03-26","Independence Day","BD",2028 +"2028-04-14","Bengali New Year's Day","BD",2028 +"2028-05-01","May Day","BD",2028 +"2028-08-15","National Mourning Day","BD",2028 +"2028-12-16","Victory Day","BD",2028 +"2029-02-21","International Mother's language Day","BD",2029 +"2029-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2029 +"2029-03-26","Independence Day","BD",2029 +"2029-04-14","Bengali New Year's Day","BD",2029 +"2029-05-01","May Day","BD",2029 +"2029-08-15","National Mourning Day","BD",2029 +"2029-12-16","Victory Day","BD",2029 +"2030-02-21","International Mother's language Day","BD",2030 +"2030-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2030 +"2030-03-26","Independence Day","BD",2030 +"2030-04-14","Bengali New Year's Day","BD",2030 +"2030-05-01","May Day","BD",2030 +"2030-08-15","National Mourning Day","BD",2030 +"2030-12-16","Victory Day","BD",2030 +"2031-02-21","International Mother's language Day","BD",2031 +"2031-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2031 +"2031-03-26","Independence Day","BD",2031 +"2031-04-14","Bengali New Year's Day","BD",2031 +"2031-05-01","May Day","BD",2031 +"2031-08-15","National Mourning Day","BD",2031 +"2031-12-16","Victory Day","BD",2031 +"2032-02-21","International Mother's language Day","BD",2032 +"2032-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2032 +"2032-03-26","Independence Day","BD",2032 +"2032-04-14","Bengali New Year's Day","BD",2032 +"2032-05-01","May Day","BD",2032 +"2032-08-15","National Mourning Day","BD",2032 +"2032-12-16","Victory Day","BD",2032 +"2033-02-21","International Mother's language Day","BD",2033 +"2033-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2033 +"2033-03-26","Independence Day","BD",2033 +"2033-04-14","Bengali New Year's Day","BD",2033 +"2033-05-01","May Day","BD",2033 +"2033-08-15","National Mourning Day","BD",2033 +"2033-12-16","Victory Day","BD",2033 +"2034-02-21","International Mother's language Day","BD",2034 +"2034-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2034 +"2034-03-26","Independence Day","BD",2034 +"2034-04-14","Bengali New Year's Day","BD",2034 +"2034-05-01","May Day","BD",2034 +"2034-08-15","National Mourning Day","BD",2034 +"2034-12-16","Victory Day","BD",2034 +"2035-02-21","International Mother's language Day","BD",2035 +"2035-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2035 +"2035-03-26","Independence Day","BD",2035 +"2035-04-14","Bengali New Year's Day","BD",2035 +"2035-05-01","May Day","BD",2035 +"2035-08-15","National Mourning Day","BD",2035 +"2035-12-16","Victory Day","BD",2035 +"2036-02-21","International Mother's language Day","BD",2036 +"2036-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2036 +"2036-03-26","Independence Day","BD",2036 +"2036-04-14","Bengali New Year's Day","BD",2036 +"2036-05-01","May Day","BD",2036 +"2036-08-15","National Mourning Day","BD",2036 +"2036-12-16","Victory Day","BD",2036 +"2037-02-21","International Mother's language Day","BD",2037 +"2037-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2037 +"2037-03-26","Independence Day","BD",2037 +"2037-04-14","Bengali New Year's Day","BD",2037 +"2037-05-01","May Day","BD",2037 +"2037-08-15","National Mourning Day","BD",2037 +"2037-12-16","Victory Day","BD",2037 +"2038-02-21","International Mother's language Day","BD",2038 +"2038-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2038 +"2038-03-26","Independence Day","BD",2038 +"2038-04-14","Bengali New Year's Day","BD",2038 +"2038-05-01","May Day","BD",2038 +"2038-08-15","National Mourning Day","BD",2038 +"2038-12-16","Victory Day","BD",2038 +"2039-02-21","International Mother's language Day","BD",2039 +"2039-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2039 +"2039-03-26","Independence Day","BD",2039 +"2039-04-14","Bengali New Year's Day","BD",2039 +"2039-05-01","May Day","BD",2039 +"2039-08-15","National Mourning Day","BD",2039 +"2039-12-16","Victory Day","BD",2039 +"2040-02-21","International Mother's language Day","BD",2040 +"2040-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2040 +"2040-03-26","Independence Day","BD",2040 +"2040-04-14","Bengali New Year's Day","BD",2040 +"2040-05-01","May Day","BD",2040 +"2040-08-15","National Mourning Day","BD",2040 +"2040-12-16","Victory Day","BD",2040 +"2041-02-21","International Mother's language Day","BD",2041 +"2041-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2041 +"2041-03-26","Independence Day","BD",2041 +"2041-04-14","Bengali New Year's Day","BD",2041 +"2041-05-01","May Day","BD",2041 +"2041-08-15","National Mourning Day","BD",2041 +"2041-12-16","Victory Day","BD",2041 +"2042-02-21","International Mother's language Day","BD",2042 +"2042-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2042 +"2042-03-26","Independence Day","BD",2042 +"2042-04-14","Bengali New Year's Day","BD",2042 +"2042-05-01","May Day","BD",2042 +"2042-08-15","National Mourning Day","BD",2042 +"2042-12-16","Victory Day","BD",2042 +"2043-02-21","International Mother's language Day","BD",2043 +"2043-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2043 +"2043-03-26","Independence Day","BD",2043 +"2043-04-14","Bengali New Year's Day","BD",2043 +"2043-05-01","May Day","BD",2043 +"2043-08-15","National Mourning Day","BD",2043 +"2043-12-16","Victory Day","BD",2043 +"2044-02-21","International Mother's language Day","BD",2044 +"2044-03-17","Sheikh Mujibur Rahman's Birthday and Children's Day","BD",2044 +"2044-03-26","Independence Day","BD",2044 +"2044-04-14","Bengali New Year's Day","BD",2044 +"2044-05-01","May Day","BD",2044 +"2044-08-15","National Mourning Day","BD",2044 +"2044-12-16","Victory Day","BD",2044 +"1995-01-01","Nieuwjaarsdag","BE",1995 +"1995-04-16","Pasen","BE",1995 +"1995-04-17","Paasmaandag","BE",1995 +"1995-05-01","Dag van de Arbeid","BE",1995 +"1995-05-25","O.L.H. Hemelvaart","BE",1995 +"1995-06-04","Pinksteren","BE",1995 +"1995-06-05","Pinkstermaandag","BE",1995 +"1995-07-21","Nationale feestdag","BE",1995 +"1995-08-15","O.L.V. Hemelvaart","BE",1995 +"1995-11-01","Allerheiligen","BE",1995 +"1995-11-11","Wapenstilstand","BE",1995 +"1995-12-25","Kerstmis","BE",1995 +"1996-01-01","Nieuwjaarsdag","BE",1996 +"1996-04-07","Pasen","BE",1996 +"1996-04-08","Paasmaandag","BE",1996 +"1996-05-01","Dag van de Arbeid","BE",1996 +"1996-05-16","O.L.H. Hemelvaart","BE",1996 +"1996-05-26","Pinksteren","BE",1996 +"1996-05-27","Pinkstermaandag","BE",1996 +"1996-07-21","Nationale feestdag","BE",1996 +"1996-08-15","O.L.V. Hemelvaart","BE",1996 +"1996-11-01","Allerheiligen","BE",1996 +"1996-11-11","Wapenstilstand","BE",1996 +"1996-12-25","Kerstmis","BE",1996 +"1997-01-01","Nieuwjaarsdag","BE",1997 +"1997-03-30","Pasen","BE",1997 +"1997-03-31","Paasmaandag","BE",1997 +"1997-05-01","Dag van de Arbeid","BE",1997 +"1997-05-08","O.L.H. Hemelvaart","BE",1997 +"1997-05-18","Pinksteren","BE",1997 +"1997-05-19","Pinkstermaandag","BE",1997 +"1997-07-21","Nationale feestdag","BE",1997 +"1997-08-15","O.L.V. Hemelvaart","BE",1997 +"1997-11-01","Allerheiligen","BE",1997 +"1997-11-11","Wapenstilstand","BE",1997 +"1997-12-25","Kerstmis","BE",1997 +"1998-01-01","Nieuwjaarsdag","BE",1998 +"1998-04-12","Pasen","BE",1998 +"1998-04-13","Paasmaandag","BE",1998 +"1998-05-01","Dag van de Arbeid","BE",1998 +"1998-05-21","O.L.H. Hemelvaart","BE",1998 +"1998-05-31","Pinksteren","BE",1998 +"1998-06-01","Pinkstermaandag","BE",1998 +"1998-07-21","Nationale feestdag","BE",1998 +"1998-08-15","O.L.V. Hemelvaart","BE",1998 +"1998-11-01","Allerheiligen","BE",1998 +"1998-11-11","Wapenstilstand","BE",1998 +"1998-12-25","Kerstmis","BE",1998 +"1999-01-01","Nieuwjaarsdag","BE",1999 +"1999-04-04","Pasen","BE",1999 +"1999-04-05","Paasmaandag","BE",1999 +"1999-05-01","Dag van de Arbeid","BE",1999 +"1999-05-13","O.L.H. Hemelvaart","BE",1999 +"1999-05-23","Pinksteren","BE",1999 +"1999-05-24","Pinkstermaandag","BE",1999 +"1999-07-21","Nationale feestdag","BE",1999 +"1999-08-15","O.L.V. Hemelvaart","BE",1999 +"1999-11-01","Allerheiligen","BE",1999 +"1999-11-11","Wapenstilstand","BE",1999 +"1999-12-25","Kerstmis","BE",1999 +"2000-01-01","Nieuwjaarsdag","BE",2000 +"2000-04-23","Pasen","BE",2000 +"2000-04-24","Paasmaandag","BE",2000 +"2000-05-01","Dag van de Arbeid","BE",2000 +"2000-06-01","O.L.H. Hemelvaart","BE",2000 +"2000-06-11","Pinksteren","BE",2000 +"2000-06-12","Pinkstermaandag","BE",2000 +"2000-07-21","Nationale feestdag","BE",2000 +"2000-08-15","O.L.V. Hemelvaart","BE",2000 +"2000-11-01","Allerheiligen","BE",2000 +"2000-11-11","Wapenstilstand","BE",2000 +"2000-12-25","Kerstmis","BE",2000 +"2001-01-01","Nieuwjaarsdag","BE",2001 +"2001-04-15","Pasen","BE",2001 +"2001-04-16","Paasmaandag","BE",2001 +"2001-05-01","Dag van de Arbeid","BE",2001 +"2001-05-24","O.L.H. Hemelvaart","BE",2001 +"2001-06-03","Pinksteren","BE",2001 +"2001-06-04","Pinkstermaandag","BE",2001 +"2001-07-21","Nationale feestdag","BE",2001 +"2001-08-15","O.L.V. Hemelvaart","BE",2001 +"2001-11-01","Allerheiligen","BE",2001 +"2001-11-11","Wapenstilstand","BE",2001 +"2001-12-25","Kerstmis","BE",2001 +"2002-01-01","Nieuwjaarsdag","BE",2002 +"2002-03-31","Pasen","BE",2002 +"2002-04-01","Paasmaandag","BE",2002 +"2002-05-01","Dag van de Arbeid","BE",2002 +"2002-05-09","O.L.H. Hemelvaart","BE",2002 +"2002-05-19","Pinksteren","BE",2002 +"2002-05-20","Pinkstermaandag","BE",2002 +"2002-07-21","Nationale feestdag","BE",2002 +"2002-08-15","O.L.V. Hemelvaart","BE",2002 +"2002-11-01","Allerheiligen","BE",2002 +"2002-11-11","Wapenstilstand","BE",2002 +"2002-12-25","Kerstmis","BE",2002 +"2003-01-01","Nieuwjaarsdag","BE",2003 +"2003-04-20","Pasen","BE",2003 +"2003-04-21","Paasmaandag","BE",2003 +"2003-05-01","Dag van de Arbeid","BE",2003 +"2003-05-29","O.L.H. Hemelvaart","BE",2003 +"2003-06-08","Pinksteren","BE",2003 +"2003-06-09","Pinkstermaandag","BE",2003 +"2003-07-21","Nationale feestdag","BE",2003 +"2003-08-15","O.L.V. Hemelvaart","BE",2003 +"2003-11-01","Allerheiligen","BE",2003 +"2003-11-11","Wapenstilstand","BE",2003 +"2003-12-25","Kerstmis","BE",2003 +"2004-01-01","Nieuwjaarsdag","BE",2004 +"2004-04-11","Pasen","BE",2004 +"2004-04-12","Paasmaandag","BE",2004 +"2004-05-01","Dag van de Arbeid","BE",2004 +"2004-05-20","O.L.H. Hemelvaart","BE",2004 +"2004-05-30","Pinksteren","BE",2004 +"2004-05-31","Pinkstermaandag","BE",2004 +"2004-07-21","Nationale feestdag","BE",2004 +"2004-08-15","O.L.V. Hemelvaart","BE",2004 +"2004-11-01","Allerheiligen","BE",2004 +"2004-11-11","Wapenstilstand","BE",2004 +"2004-12-25","Kerstmis","BE",2004 +"2005-01-01","Nieuwjaarsdag","BE",2005 +"2005-03-27","Pasen","BE",2005 +"2005-03-28","Paasmaandag","BE",2005 +"2005-05-01","Dag van de Arbeid","BE",2005 +"2005-05-05","O.L.H. Hemelvaart","BE",2005 +"2005-05-15","Pinksteren","BE",2005 +"2005-05-16","Pinkstermaandag","BE",2005 +"2005-07-21","Nationale feestdag","BE",2005 +"2005-08-15","O.L.V. Hemelvaart","BE",2005 +"2005-11-01","Allerheiligen","BE",2005 +"2005-11-11","Wapenstilstand","BE",2005 +"2005-12-25","Kerstmis","BE",2005 +"2006-01-01","Nieuwjaarsdag","BE",2006 +"2006-04-16","Pasen","BE",2006 +"2006-04-17","Paasmaandag","BE",2006 +"2006-05-01","Dag van de Arbeid","BE",2006 +"2006-05-25","O.L.H. Hemelvaart","BE",2006 +"2006-06-04","Pinksteren","BE",2006 +"2006-06-05","Pinkstermaandag","BE",2006 +"2006-07-21","Nationale feestdag","BE",2006 +"2006-08-15","O.L.V. Hemelvaart","BE",2006 +"2006-11-01","Allerheiligen","BE",2006 +"2006-11-11","Wapenstilstand","BE",2006 +"2006-12-25","Kerstmis","BE",2006 +"2007-01-01","Nieuwjaarsdag","BE",2007 +"2007-04-08","Pasen","BE",2007 +"2007-04-09","Paasmaandag","BE",2007 +"2007-05-01","Dag van de Arbeid","BE",2007 +"2007-05-17","O.L.H. Hemelvaart","BE",2007 +"2007-05-27","Pinksteren","BE",2007 +"2007-05-28","Pinkstermaandag","BE",2007 +"2007-07-21","Nationale feestdag","BE",2007 +"2007-08-15","O.L.V. Hemelvaart","BE",2007 +"2007-11-01","Allerheiligen","BE",2007 +"2007-11-11","Wapenstilstand","BE",2007 +"2007-12-25","Kerstmis","BE",2007 +"2008-01-01","Nieuwjaarsdag","BE",2008 +"2008-03-23","Pasen","BE",2008 +"2008-03-24","Paasmaandag","BE",2008 +"2008-05-01","Dag van de Arbeid","BE",2008 +"2008-05-01","O.L.H. Hemelvaart","BE",2008 +"2008-05-11","Pinksteren","BE",2008 +"2008-05-12","Pinkstermaandag","BE",2008 +"2008-07-21","Nationale feestdag","BE",2008 +"2008-08-15","O.L.V. Hemelvaart","BE",2008 +"2008-11-01","Allerheiligen","BE",2008 +"2008-11-11","Wapenstilstand","BE",2008 +"2008-12-25","Kerstmis","BE",2008 +"2009-01-01","Nieuwjaarsdag","BE",2009 +"2009-04-12","Pasen","BE",2009 +"2009-04-13","Paasmaandag","BE",2009 +"2009-05-01","Dag van de Arbeid","BE",2009 +"2009-05-21","O.L.H. Hemelvaart","BE",2009 +"2009-05-31","Pinksteren","BE",2009 +"2009-06-01","Pinkstermaandag","BE",2009 +"2009-07-21","Nationale feestdag","BE",2009 +"2009-08-15","O.L.V. Hemelvaart","BE",2009 +"2009-11-01","Allerheiligen","BE",2009 +"2009-11-11","Wapenstilstand","BE",2009 +"2009-12-25","Kerstmis","BE",2009 +"2010-01-01","Nieuwjaarsdag","BE",2010 +"2010-04-04","Pasen","BE",2010 +"2010-04-05","Paasmaandag","BE",2010 +"2010-05-01","Dag van de Arbeid","BE",2010 +"2010-05-13","O.L.H. Hemelvaart","BE",2010 +"2010-05-23","Pinksteren","BE",2010 +"2010-05-24","Pinkstermaandag","BE",2010 +"2010-07-21","Nationale feestdag","BE",2010 +"2010-08-15","O.L.V. Hemelvaart","BE",2010 +"2010-11-01","Allerheiligen","BE",2010 +"2010-11-11","Wapenstilstand","BE",2010 +"2010-12-25","Kerstmis","BE",2010 +"2011-01-01","Nieuwjaarsdag","BE",2011 +"2011-04-24","Pasen","BE",2011 +"2011-04-25","Paasmaandag","BE",2011 +"2011-05-01","Dag van de Arbeid","BE",2011 +"2011-06-02","O.L.H. Hemelvaart","BE",2011 +"2011-06-12","Pinksteren","BE",2011 +"2011-06-13","Pinkstermaandag","BE",2011 +"2011-07-21","Nationale feestdag","BE",2011 +"2011-08-15","O.L.V. Hemelvaart","BE",2011 +"2011-11-01","Allerheiligen","BE",2011 +"2011-11-11","Wapenstilstand","BE",2011 +"2011-12-25","Kerstmis","BE",2011 +"2012-01-01","Nieuwjaarsdag","BE",2012 +"2012-04-08","Pasen","BE",2012 +"2012-04-09","Paasmaandag","BE",2012 +"2012-05-01","Dag van de Arbeid","BE",2012 +"2012-05-17","O.L.H. Hemelvaart","BE",2012 +"2012-05-27","Pinksteren","BE",2012 +"2012-05-28","Pinkstermaandag","BE",2012 +"2012-07-21","Nationale feestdag","BE",2012 +"2012-08-15","O.L.V. Hemelvaart","BE",2012 +"2012-11-01","Allerheiligen","BE",2012 +"2012-11-11","Wapenstilstand","BE",2012 +"2012-12-25","Kerstmis","BE",2012 +"2013-01-01","Nieuwjaarsdag","BE",2013 +"2013-03-31","Pasen","BE",2013 +"2013-04-01","Paasmaandag","BE",2013 +"2013-05-01","Dag van de Arbeid","BE",2013 +"2013-05-09","O.L.H. Hemelvaart","BE",2013 +"2013-05-19","Pinksteren","BE",2013 +"2013-05-20","Pinkstermaandag","BE",2013 +"2013-07-21","Nationale feestdag","BE",2013 +"2013-08-15","O.L.V. Hemelvaart","BE",2013 +"2013-11-01","Allerheiligen","BE",2013 +"2013-11-11","Wapenstilstand","BE",2013 +"2013-12-25","Kerstmis","BE",2013 +"2014-01-01","Nieuwjaarsdag","BE",2014 +"2014-04-20","Pasen","BE",2014 +"2014-04-21","Paasmaandag","BE",2014 +"2014-05-01","Dag van de Arbeid","BE",2014 +"2014-05-29","O.L.H. Hemelvaart","BE",2014 +"2014-06-08","Pinksteren","BE",2014 +"2014-06-09","Pinkstermaandag","BE",2014 +"2014-07-21","Nationale feestdag","BE",2014 +"2014-08-15","O.L.V. Hemelvaart","BE",2014 +"2014-11-01","Allerheiligen","BE",2014 +"2014-11-11","Wapenstilstand","BE",2014 +"2014-12-25","Kerstmis","BE",2014 +"2015-01-01","Nieuwjaarsdag","BE",2015 +"2015-04-05","Pasen","BE",2015 +"2015-04-06","Paasmaandag","BE",2015 +"2015-05-01","Dag van de Arbeid","BE",2015 +"2015-05-14","O.L.H. Hemelvaart","BE",2015 +"2015-05-24","Pinksteren","BE",2015 +"2015-05-25","Pinkstermaandag","BE",2015 +"2015-07-21","Nationale feestdag","BE",2015 +"2015-08-15","O.L.V. Hemelvaart","BE",2015 +"2015-11-01","Allerheiligen","BE",2015 +"2015-11-11","Wapenstilstand","BE",2015 +"2015-12-25","Kerstmis","BE",2015 +"2016-01-01","Nieuwjaarsdag","BE",2016 +"2016-03-27","Pasen","BE",2016 +"2016-03-28","Paasmaandag","BE",2016 +"2016-05-01","Dag van de Arbeid","BE",2016 +"2016-05-05","O.L.H. Hemelvaart","BE",2016 +"2016-05-15","Pinksteren","BE",2016 +"2016-05-16","Pinkstermaandag","BE",2016 +"2016-07-21","Nationale feestdag","BE",2016 +"2016-08-15","O.L.V. Hemelvaart","BE",2016 +"2016-11-01","Allerheiligen","BE",2016 +"2016-11-11","Wapenstilstand","BE",2016 +"2016-12-25","Kerstmis","BE",2016 +"2017-01-01","Nieuwjaarsdag","BE",2017 +"2017-04-16","Pasen","BE",2017 +"2017-04-17","Paasmaandag","BE",2017 +"2017-05-01","Dag van de Arbeid","BE",2017 +"2017-05-25","O.L.H. Hemelvaart","BE",2017 +"2017-06-04","Pinksteren","BE",2017 +"2017-06-05","Pinkstermaandag","BE",2017 +"2017-07-21","Nationale feestdag","BE",2017 +"2017-08-15","O.L.V. Hemelvaart","BE",2017 +"2017-11-01","Allerheiligen","BE",2017 +"2017-11-11","Wapenstilstand","BE",2017 +"2017-12-25","Kerstmis","BE",2017 +"2018-01-01","Nieuwjaarsdag","BE",2018 +"2018-04-01","Pasen","BE",2018 +"2018-04-02","Paasmaandag","BE",2018 +"2018-05-01","Dag van de Arbeid","BE",2018 +"2018-05-10","O.L.H. Hemelvaart","BE",2018 +"2018-05-20","Pinksteren","BE",2018 +"2018-05-21","Pinkstermaandag","BE",2018 +"2018-07-21","Nationale feestdag","BE",2018 +"2018-08-15","O.L.V. Hemelvaart","BE",2018 +"2018-11-01","Allerheiligen","BE",2018 +"2018-11-11","Wapenstilstand","BE",2018 +"2018-12-25","Kerstmis","BE",2018 +"2019-01-01","Nieuwjaarsdag","BE",2019 +"2019-04-21","Pasen","BE",2019 +"2019-04-22","Paasmaandag","BE",2019 +"2019-05-01","Dag van de Arbeid","BE",2019 +"2019-05-30","O.L.H. Hemelvaart","BE",2019 +"2019-06-09","Pinksteren","BE",2019 +"2019-06-10","Pinkstermaandag","BE",2019 +"2019-07-21","Nationale feestdag","BE",2019 +"2019-08-15","O.L.V. Hemelvaart","BE",2019 +"2019-11-01","Allerheiligen","BE",2019 +"2019-11-11","Wapenstilstand","BE",2019 +"2019-12-25","Kerstmis","BE",2019 +"2020-01-01","Nieuwjaarsdag","BE",2020 +"2020-04-12","Pasen","BE",2020 +"2020-04-13","Paasmaandag","BE",2020 +"2020-05-01","Dag van de Arbeid","BE",2020 +"2020-05-21","O.L.H. Hemelvaart","BE",2020 +"2020-05-31","Pinksteren","BE",2020 +"2020-06-01","Pinkstermaandag","BE",2020 +"2020-07-21","Nationale feestdag","BE",2020 +"2020-08-15","O.L.V. Hemelvaart","BE",2020 +"2020-11-01","Allerheiligen","BE",2020 +"2020-11-11","Wapenstilstand","BE",2020 +"2020-12-25","Kerstmis","BE",2020 +"2021-01-01","Nieuwjaarsdag","BE",2021 +"2021-04-04","Pasen","BE",2021 +"2021-04-05","Paasmaandag","BE",2021 +"2021-05-01","Dag van de Arbeid","BE",2021 +"2021-05-13","O.L.H. Hemelvaart","BE",2021 +"2021-05-23","Pinksteren","BE",2021 +"2021-05-24","Pinkstermaandag","BE",2021 +"2021-07-21","Nationale feestdag","BE",2021 +"2021-08-15","O.L.V. Hemelvaart","BE",2021 +"2021-11-01","Allerheiligen","BE",2021 +"2021-11-11","Wapenstilstand","BE",2021 +"2021-12-25","Kerstmis","BE",2021 +"2022-01-01","Nieuwjaarsdag","BE",2022 +"2022-04-17","Pasen","BE",2022 +"2022-04-18","Paasmaandag","BE",2022 +"2022-05-01","Dag van de Arbeid","BE",2022 +"2022-05-26","O.L.H. Hemelvaart","BE",2022 +"2022-06-05","Pinksteren","BE",2022 +"2022-06-06","Pinkstermaandag","BE",2022 +"2022-07-21","Nationale feestdag","BE",2022 +"2022-08-15","O.L.V. Hemelvaart","BE",2022 +"2022-11-01","Allerheiligen","BE",2022 +"2022-11-11","Wapenstilstand","BE",2022 +"2022-12-25","Kerstmis","BE",2022 +"2023-01-01","Nieuwjaarsdag","BE",2023 +"2023-04-09","Pasen","BE",2023 +"2023-04-10","Paasmaandag","BE",2023 +"2023-05-01","Dag van de Arbeid","BE",2023 +"2023-05-18","O.L.H. Hemelvaart","BE",2023 +"2023-05-28","Pinksteren","BE",2023 +"2023-05-29","Pinkstermaandag","BE",2023 +"2023-07-21","Nationale feestdag","BE",2023 +"2023-08-15","O.L.V. Hemelvaart","BE",2023 +"2023-11-01","Allerheiligen","BE",2023 +"2023-11-11","Wapenstilstand","BE",2023 +"2023-12-25","Kerstmis","BE",2023 +"2024-01-01","Nieuwjaarsdag","BE",2024 +"2024-03-31","Pasen","BE",2024 +"2024-04-01","Paasmaandag","BE",2024 +"2024-05-01","Dag van de Arbeid","BE",2024 +"2024-05-09","O.L.H. Hemelvaart","BE",2024 +"2024-05-19","Pinksteren","BE",2024 +"2024-05-20","Pinkstermaandag","BE",2024 +"2024-07-21","Nationale feestdag","BE",2024 +"2024-08-15","O.L.V. Hemelvaart","BE",2024 +"2024-11-01","Allerheiligen","BE",2024 +"2024-11-11","Wapenstilstand","BE",2024 +"2024-12-25","Kerstmis","BE",2024 +"2025-01-01","Nieuwjaarsdag","BE",2025 +"2025-04-20","Pasen","BE",2025 +"2025-04-21","Paasmaandag","BE",2025 +"2025-05-01","Dag van de Arbeid","BE",2025 +"2025-05-29","O.L.H. Hemelvaart","BE",2025 +"2025-06-08","Pinksteren","BE",2025 +"2025-06-09","Pinkstermaandag","BE",2025 +"2025-07-21","Nationale feestdag","BE",2025 +"2025-08-15","O.L.V. Hemelvaart","BE",2025 +"2025-11-01","Allerheiligen","BE",2025 +"2025-11-11","Wapenstilstand","BE",2025 +"2025-12-25","Kerstmis","BE",2025 +"2026-01-01","Nieuwjaarsdag","BE",2026 +"2026-04-05","Pasen","BE",2026 +"2026-04-06","Paasmaandag","BE",2026 +"2026-05-01","Dag van de Arbeid","BE",2026 +"2026-05-14","O.L.H. Hemelvaart","BE",2026 +"2026-05-24","Pinksteren","BE",2026 +"2026-05-25","Pinkstermaandag","BE",2026 +"2026-07-21","Nationale feestdag","BE",2026 +"2026-08-15","O.L.V. Hemelvaart","BE",2026 +"2026-11-01","Allerheiligen","BE",2026 +"2026-11-11","Wapenstilstand","BE",2026 +"2026-12-25","Kerstmis","BE",2026 +"2027-01-01","Nieuwjaarsdag","BE",2027 +"2027-03-28","Pasen","BE",2027 +"2027-03-29","Paasmaandag","BE",2027 +"2027-05-01","Dag van de Arbeid","BE",2027 +"2027-05-06","O.L.H. Hemelvaart","BE",2027 +"2027-05-16","Pinksteren","BE",2027 +"2027-05-17","Pinkstermaandag","BE",2027 +"2027-07-21","Nationale feestdag","BE",2027 +"2027-08-15","O.L.V. Hemelvaart","BE",2027 +"2027-11-01","Allerheiligen","BE",2027 +"2027-11-11","Wapenstilstand","BE",2027 +"2027-12-25","Kerstmis","BE",2027 +"2028-01-01","Nieuwjaarsdag","BE",2028 +"2028-04-16","Pasen","BE",2028 +"2028-04-17","Paasmaandag","BE",2028 +"2028-05-01","Dag van de Arbeid","BE",2028 +"2028-05-25","O.L.H. Hemelvaart","BE",2028 +"2028-06-04","Pinksteren","BE",2028 +"2028-06-05","Pinkstermaandag","BE",2028 +"2028-07-21","Nationale feestdag","BE",2028 +"2028-08-15","O.L.V. Hemelvaart","BE",2028 +"2028-11-01","Allerheiligen","BE",2028 +"2028-11-11","Wapenstilstand","BE",2028 +"2028-12-25","Kerstmis","BE",2028 +"2029-01-01","Nieuwjaarsdag","BE",2029 +"2029-04-01","Pasen","BE",2029 +"2029-04-02","Paasmaandag","BE",2029 +"2029-05-01","Dag van de Arbeid","BE",2029 +"2029-05-10","O.L.H. Hemelvaart","BE",2029 +"2029-05-20","Pinksteren","BE",2029 +"2029-05-21","Pinkstermaandag","BE",2029 +"2029-07-21","Nationale feestdag","BE",2029 +"2029-08-15","O.L.V. Hemelvaart","BE",2029 +"2029-11-01","Allerheiligen","BE",2029 +"2029-11-11","Wapenstilstand","BE",2029 +"2029-12-25","Kerstmis","BE",2029 +"2030-01-01","Nieuwjaarsdag","BE",2030 +"2030-04-21","Pasen","BE",2030 +"2030-04-22","Paasmaandag","BE",2030 +"2030-05-01","Dag van de Arbeid","BE",2030 +"2030-05-30","O.L.H. Hemelvaart","BE",2030 +"2030-06-09","Pinksteren","BE",2030 +"2030-06-10","Pinkstermaandag","BE",2030 +"2030-07-21","Nationale feestdag","BE",2030 +"2030-08-15","O.L.V. Hemelvaart","BE",2030 +"2030-11-01","Allerheiligen","BE",2030 +"2030-11-11","Wapenstilstand","BE",2030 +"2030-12-25","Kerstmis","BE",2030 +"2031-01-01","Nieuwjaarsdag","BE",2031 +"2031-04-13","Pasen","BE",2031 +"2031-04-14","Paasmaandag","BE",2031 +"2031-05-01","Dag van de Arbeid","BE",2031 +"2031-05-22","O.L.H. Hemelvaart","BE",2031 +"2031-06-01","Pinksteren","BE",2031 +"2031-06-02","Pinkstermaandag","BE",2031 +"2031-07-21","Nationale feestdag","BE",2031 +"2031-08-15","O.L.V. Hemelvaart","BE",2031 +"2031-11-01","Allerheiligen","BE",2031 +"2031-11-11","Wapenstilstand","BE",2031 +"2031-12-25","Kerstmis","BE",2031 +"2032-01-01","Nieuwjaarsdag","BE",2032 +"2032-03-28","Pasen","BE",2032 +"2032-03-29","Paasmaandag","BE",2032 +"2032-05-01","Dag van de Arbeid","BE",2032 +"2032-05-06","O.L.H. Hemelvaart","BE",2032 +"2032-05-16","Pinksteren","BE",2032 +"2032-05-17","Pinkstermaandag","BE",2032 +"2032-07-21","Nationale feestdag","BE",2032 +"2032-08-15","O.L.V. Hemelvaart","BE",2032 +"2032-11-01","Allerheiligen","BE",2032 +"2032-11-11","Wapenstilstand","BE",2032 +"2032-12-25","Kerstmis","BE",2032 +"2033-01-01","Nieuwjaarsdag","BE",2033 +"2033-04-17","Pasen","BE",2033 +"2033-04-18","Paasmaandag","BE",2033 +"2033-05-01","Dag van de Arbeid","BE",2033 +"2033-05-26","O.L.H. Hemelvaart","BE",2033 +"2033-06-05","Pinksteren","BE",2033 +"2033-06-06","Pinkstermaandag","BE",2033 +"2033-07-21","Nationale feestdag","BE",2033 +"2033-08-15","O.L.V. Hemelvaart","BE",2033 +"2033-11-01","Allerheiligen","BE",2033 +"2033-11-11","Wapenstilstand","BE",2033 +"2033-12-25","Kerstmis","BE",2033 +"2034-01-01","Nieuwjaarsdag","BE",2034 +"2034-04-09","Pasen","BE",2034 +"2034-04-10","Paasmaandag","BE",2034 +"2034-05-01","Dag van de Arbeid","BE",2034 +"2034-05-18","O.L.H. Hemelvaart","BE",2034 +"2034-05-28","Pinksteren","BE",2034 +"2034-05-29","Pinkstermaandag","BE",2034 +"2034-07-21","Nationale feestdag","BE",2034 +"2034-08-15","O.L.V. Hemelvaart","BE",2034 +"2034-11-01","Allerheiligen","BE",2034 +"2034-11-11","Wapenstilstand","BE",2034 +"2034-12-25","Kerstmis","BE",2034 +"2035-01-01","Nieuwjaarsdag","BE",2035 +"2035-03-25","Pasen","BE",2035 +"2035-03-26","Paasmaandag","BE",2035 +"2035-05-01","Dag van de Arbeid","BE",2035 +"2035-05-03","O.L.H. Hemelvaart","BE",2035 +"2035-05-13","Pinksteren","BE",2035 +"2035-05-14","Pinkstermaandag","BE",2035 +"2035-07-21","Nationale feestdag","BE",2035 +"2035-08-15","O.L.V. Hemelvaart","BE",2035 +"2035-11-01","Allerheiligen","BE",2035 +"2035-11-11","Wapenstilstand","BE",2035 +"2035-12-25","Kerstmis","BE",2035 +"2036-01-01","Nieuwjaarsdag","BE",2036 +"2036-04-13","Pasen","BE",2036 +"2036-04-14","Paasmaandag","BE",2036 +"2036-05-01","Dag van de Arbeid","BE",2036 +"2036-05-22","O.L.H. Hemelvaart","BE",2036 +"2036-06-01","Pinksteren","BE",2036 +"2036-06-02","Pinkstermaandag","BE",2036 +"2036-07-21","Nationale feestdag","BE",2036 +"2036-08-15","O.L.V. Hemelvaart","BE",2036 +"2036-11-01","Allerheiligen","BE",2036 +"2036-11-11","Wapenstilstand","BE",2036 +"2036-12-25","Kerstmis","BE",2036 +"2037-01-01","Nieuwjaarsdag","BE",2037 +"2037-04-05","Pasen","BE",2037 +"2037-04-06","Paasmaandag","BE",2037 +"2037-05-01","Dag van de Arbeid","BE",2037 +"2037-05-14","O.L.H. Hemelvaart","BE",2037 +"2037-05-24","Pinksteren","BE",2037 +"2037-05-25","Pinkstermaandag","BE",2037 +"2037-07-21","Nationale feestdag","BE",2037 +"2037-08-15","O.L.V. Hemelvaart","BE",2037 +"2037-11-01","Allerheiligen","BE",2037 +"2037-11-11","Wapenstilstand","BE",2037 +"2037-12-25","Kerstmis","BE",2037 +"2038-01-01","Nieuwjaarsdag","BE",2038 +"2038-04-25","Pasen","BE",2038 +"2038-04-26","Paasmaandag","BE",2038 +"2038-05-01","Dag van de Arbeid","BE",2038 +"2038-06-03","O.L.H. Hemelvaart","BE",2038 +"2038-06-13","Pinksteren","BE",2038 +"2038-06-14","Pinkstermaandag","BE",2038 +"2038-07-21","Nationale feestdag","BE",2038 +"2038-08-15","O.L.V. Hemelvaart","BE",2038 +"2038-11-01","Allerheiligen","BE",2038 +"2038-11-11","Wapenstilstand","BE",2038 +"2038-12-25","Kerstmis","BE",2038 +"2039-01-01","Nieuwjaarsdag","BE",2039 +"2039-04-10","Pasen","BE",2039 +"2039-04-11","Paasmaandag","BE",2039 +"2039-05-01","Dag van de Arbeid","BE",2039 +"2039-05-19","O.L.H. Hemelvaart","BE",2039 +"2039-05-29","Pinksteren","BE",2039 +"2039-05-30","Pinkstermaandag","BE",2039 +"2039-07-21","Nationale feestdag","BE",2039 +"2039-08-15","O.L.V. Hemelvaart","BE",2039 +"2039-11-01","Allerheiligen","BE",2039 +"2039-11-11","Wapenstilstand","BE",2039 +"2039-12-25","Kerstmis","BE",2039 +"2040-01-01","Nieuwjaarsdag","BE",2040 +"2040-04-01","Pasen","BE",2040 +"2040-04-02","Paasmaandag","BE",2040 +"2040-05-01","Dag van de Arbeid","BE",2040 +"2040-05-10","O.L.H. Hemelvaart","BE",2040 +"2040-05-20","Pinksteren","BE",2040 +"2040-05-21","Pinkstermaandag","BE",2040 +"2040-07-21","Nationale feestdag","BE",2040 +"2040-08-15","O.L.V. Hemelvaart","BE",2040 +"2040-11-01","Allerheiligen","BE",2040 +"2040-11-11","Wapenstilstand","BE",2040 +"2040-12-25","Kerstmis","BE",2040 +"2041-01-01","Nieuwjaarsdag","BE",2041 +"2041-04-21","Pasen","BE",2041 +"2041-04-22","Paasmaandag","BE",2041 +"2041-05-01","Dag van de Arbeid","BE",2041 +"2041-05-30","O.L.H. Hemelvaart","BE",2041 +"2041-06-09","Pinksteren","BE",2041 +"2041-06-10","Pinkstermaandag","BE",2041 +"2041-07-21","Nationale feestdag","BE",2041 +"2041-08-15","O.L.V. Hemelvaart","BE",2041 +"2041-11-01","Allerheiligen","BE",2041 +"2041-11-11","Wapenstilstand","BE",2041 +"2041-12-25","Kerstmis","BE",2041 +"2042-01-01","Nieuwjaarsdag","BE",2042 +"2042-04-06","Pasen","BE",2042 +"2042-04-07","Paasmaandag","BE",2042 +"2042-05-01","Dag van de Arbeid","BE",2042 +"2042-05-15","O.L.H. Hemelvaart","BE",2042 +"2042-05-25","Pinksteren","BE",2042 +"2042-05-26","Pinkstermaandag","BE",2042 +"2042-07-21","Nationale feestdag","BE",2042 +"2042-08-15","O.L.V. Hemelvaart","BE",2042 +"2042-11-01","Allerheiligen","BE",2042 +"2042-11-11","Wapenstilstand","BE",2042 +"2042-12-25","Kerstmis","BE",2042 +"2043-01-01","Nieuwjaarsdag","BE",2043 +"2043-03-29","Pasen","BE",2043 +"2043-03-30","Paasmaandag","BE",2043 +"2043-05-01","Dag van de Arbeid","BE",2043 +"2043-05-07","O.L.H. Hemelvaart","BE",2043 +"2043-05-17","Pinksteren","BE",2043 +"2043-05-18","Pinkstermaandag","BE",2043 +"2043-07-21","Nationale feestdag","BE",2043 +"2043-08-15","O.L.V. Hemelvaart","BE",2043 +"2043-11-01","Allerheiligen","BE",2043 +"2043-11-11","Wapenstilstand","BE",2043 +"2043-12-25","Kerstmis","BE",2043 +"2044-01-01","Nieuwjaarsdag","BE",2044 +"2044-04-17","Pasen","BE",2044 +"2044-04-18","Paasmaandag","BE",2044 +"2044-05-01","Dag van de Arbeid","BE",2044 +"2044-05-26","O.L.H. Hemelvaart","BE",2044 +"2044-06-05","Pinksteren","BE",2044 +"2044-06-06","Pinkstermaandag","BE",2044 +"2044-07-21","Nationale feestdag","BE",2044 +"2044-08-15","O.L.V. Hemelvaart","BE",2044 +"2044-11-01","Allerheiligen","BE",2044 +"2044-11-11","Wapenstilstand","BE",2044 +"2044-12-25","Kerstmis","BE",2044 +"1995-01-01","New Year's Day","BG",1995 +"1995-03-03","Liberation Day","BG",1995 +"1995-04-21","Orthodox Good Friday","BG",1995 +"1995-04-22","Orthodox Easter Saturday","BG",1995 +"1995-04-23","Orthodox Easter","BG",1995 +"1995-04-24","Orthodox Easter","BG",1995 +"1995-05-01","Labour Day and International Workers' Solidarity Day","BG",1995 +"1995-05-06","St. George's Day (Day of the Bulgarian Army)","BG",1995 +"1995-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",1995 +"1995-09-06","Unification Day","BG",1995 +"1995-09-22","Independence Day","BG",1995 +"1995-11-01","The Day of the People's Awakeners","BG",1995 +"1995-12-24","Christmas Eve","BG",1995 +"1995-12-25","Christmas Day","BG",1995 +"1995-12-26","Christmas Day","BG",1995 +"1996-01-01","New Year's Day","BG",1996 +"1996-03-03","Liberation Day","BG",1996 +"1996-04-12","Orthodox Good Friday","BG",1996 +"1996-04-13","Orthodox Easter Saturday","BG",1996 +"1996-04-14","Orthodox Easter","BG",1996 +"1996-04-15","Orthodox Easter","BG",1996 +"1996-05-01","Labour Day and International Workers' Solidarity Day","BG",1996 +"1996-05-06","St. George's Day (Day of the Bulgarian Army)","BG",1996 +"1996-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",1996 +"1996-09-06","Unification Day","BG",1996 +"1996-09-22","Independence Day","BG",1996 +"1996-11-01","The Day of the People's Awakeners","BG",1996 +"1996-12-24","Christmas Eve","BG",1996 +"1996-12-25","Christmas Day","BG",1996 +"1996-12-26","Christmas Day","BG",1996 +"1997-01-01","New Year's Day","BG",1997 +"1997-03-03","Liberation Day","BG",1997 +"1997-04-25","Orthodox Good Friday","BG",1997 +"1997-04-26","Orthodox Easter Saturday","BG",1997 +"1997-04-27","Orthodox Easter","BG",1997 +"1997-04-28","Orthodox Easter","BG",1997 +"1997-05-01","Labour Day and International Workers' Solidarity Day","BG",1997 +"1997-05-06","St. George's Day (Day of the Bulgarian Army)","BG",1997 +"1997-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",1997 +"1997-09-06","Unification Day","BG",1997 +"1997-09-22","Independence Day","BG",1997 +"1997-11-01","The Day of the People's Awakeners","BG",1997 +"1997-12-24","Christmas Eve","BG",1997 +"1997-12-25","Christmas Day","BG",1997 +"1997-12-26","Christmas Day","BG",1997 +"1998-01-01","New Year's Day","BG",1998 +"1998-03-03","Liberation Day","BG",1998 +"1998-04-17","Orthodox Good Friday","BG",1998 +"1998-04-18","Orthodox Easter Saturday","BG",1998 +"1998-04-19","Orthodox Easter","BG",1998 +"1998-04-20","Orthodox Easter","BG",1998 +"1998-05-01","Labour Day and International Workers' Solidarity Day","BG",1998 +"1998-05-06","St. George's Day (Day of the Bulgarian Army)","BG",1998 +"1998-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",1998 +"1998-09-06","Unification Day","BG",1998 +"1998-09-22","Independence Day","BG",1998 +"1998-11-01","The Day of the People's Awakeners","BG",1998 +"1998-12-24","Christmas Eve","BG",1998 +"1998-12-25","Christmas Day","BG",1998 +"1998-12-26","Christmas Day","BG",1998 +"1999-01-01","New Year's Day","BG",1999 +"1999-03-03","Liberation Day","BG",1999 +"1999-04-09","Orthodox Good Friday","BG",1999 +"1999-04-10","Orthodox Easter Saturday","BG",1999 +"1999-04-11","Orthodox Easter","BG",1999 +"1999-04-12","Orthodox Easter","BG",1999 +"1999-05-01","Labour Day and International Workers' Solidarity Day","BG",1999 +"1999-05-06","St. George's Day (Day of the Bulgarian Army)","BG",1999 +"1999-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",1999 +"1999-09-06","Unification Day","BG",1999 +"1999-09-22","Independence Day","BG",1999 +"1999-11-01","The Day of the People's Awakeners","BG",1999 +"1999-12-24","Christmas Eve","BG",1999 +"1999-12-25","Christmas Day","BG",1999 +"1999-12-26","Christmas Day","BG",1999 +"2000-01-01","New Year's Day","BG",2000 +"2000-03-03","Liberation Day","BG",2000 +"2000-04-28","Orthodox Good Friday","BG",2000 +"2000-04-29","Orthodox Easter Saturday","BG",2000 +"2000-04-30","Orthodox Easter","BG",2000 +"2000-05-01","Labour Day and International Workers' Solidarity Day","BG",2000 +"2000-05-01","Orthodox Easter","BG",2000 +"2000-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2000 +"2000-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2000 +"2000-09-06","Unification Day","BG",2000 +"2000-09-22","Independence Day","BG",2000 +"2000-11-01","The Day of the People's Awakeners","BG",2000 +"2000-12-24","Christmas Eve","BG",2000 +"2000-12-25","Christmas Day","BG",2000 +"2000-12-26","Christmas Day","BG",2000 +"2001-01-01","New Year's Day","BG",2001 +"2001-03-03","Liberation Day","BG",2001 +"2001-04-13","Orthodox Good Friday","BG",2001 +"2001-04-14","Orthodox Easter Saturday","BG",2001 +"2001-04-15","Orthodox Easter","BG",2001 +"2001-04-16","Orthodox Easter","BG",2001 +"2001-05-01","Labour Day and International Workers' Solidarity Day","BG",2001 +"2001-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2001 +"2001-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2001 +"2001-09-06","Unification Day","BG",2001 +"2001-09-22","Independence Day","BG",2001 +"2001-11-01","The Day of the People's Awakeners","BG",2001 +"2001-12-24","Christmas Eve","BG",2001 +"2001-12-25","Christmas Day","BG",2001 +"2001-12-26","Christmas Day","BG",2001 +"2002-01-01","New Year's Day","BG",2002 +"2002-03-03","Liberation Day","BG",2002 +"2002-05-01","Labour Day and International Workers' Solidarity Day","BG",2002 +"2002-05-03","Orthodox Good Friday","BG",2002 +"2002-05-04","Orthodox Easter Saturday","BG",2002 +"2002-05-05","Orthodox Easter","BG",2002 +"2002-05-06","Orthodox Easter","BG",2002 +"2002-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2002 +"2002-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2002 +"2002-09-06","Unification Day","BG",2002 +"2002-09-22","Independence Day","BG",2002 +"2002-11-01","The Day of the People's Awakeners","BG",2002 +"2002-12-24","Christmas Eve","BG",2002 +"2002-12-25","Christmas Day","BG",2002 +"2002-12-26","Christmas Day","BG",2002 +"2003-01-01","New Year's Day","BG",2003 +"2003-03-03","Liberation Day","BG",2003 +"2003-04-25","Orthodox Good Friday","BG",2003 +"2003-04-26","Orthodox Easter Saturday","BG",2003 +"2003-04-27","Orthodox Easter","BG",2003 +"2003-04-28","Orthodox Easter","BG",2003 +"2003-05-01","Labour Day and International Workers' Solidarity Day","BG",2003 +"2003-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2003 +"2003-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2003 +"2003-09-06","Unification Day","BG",2003 +"2003-09-22","Independence Day","BG",2003 +"2003-11-01","The Day of the People's Awakeners","BG",2003 +"2003-12-24","Christmas Eve","BG",2003 +"2003-12-25","Christmas Day","BG",2003 +"2003-12-26","Christmas Day","BG",2003 +"2004-01-01","New Year's Day","BG",2004 +"2004-03-03","Liberation Day","BG",2004 +"2004-04-09","Orthodox Good Friday","BG",2004 +"2004-04-10","Orthodox Easter Saturday","BG",2004 +"2004-04-11","Orthodox Easter","BG",2004 +"2004-04-12","Orthodox Easter","BG",2004 +"2004-05-01","Labour Day and International Workers' Solidarity Day","BG",2004 +"2004-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2004 +"2004-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2004 +"2004-09-06","Unification Day","BG",2004 +"2004-09-22","Independence Day","BG",2004 +"2004-11-01","The Day of the People's Awakeners","BG",2004 +"2004-12-24","Christmas Eve","BG",2004 +"2004-12-25","Christmas Day","BG",2004 +"2004-12-26","Christmas Day","BG",2004 +"2005-01-01","New Year's Day","BG",2005 +"2005-03-03","Liberation Day","BG",2005 +"2005-04-29","Orthodox Good Friday","BG",2005 +"2005-04-30","Orthodox Easter Saturday","BG",2005 +"2005-05-01","Labour Day and International Workers' Solidarity Day","BG",2005 +"2005-05-01","Orthodox Easter","BG",2005 +"2005-05-02","Orthodox Easter","BG",2005 +"2005-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2005 +"2005-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2005 +"2005-09-06","Unification Day","BG",2005 +"2005-09-22","Independence Day","BG",2005 +"2005-11-01","The Day of the People's Awakeners","BG",2005 +"2005-12-24","Christmas Eve","BG",2005 +"2005-12-25","Christmas Day","BG",2005 +"2005-12-26","Christmas Day","BG",2005 +"2006-01-01","New Year's Day","BG",2006 +"2006-03-03","Liberation Day","BG",2006 +"2006-04-21","Orthodox Good Friday","BG",2006 +"2006-04-22","Orthodox Easter Saturday","BG",2006 +"2006-04-23","Orthodox Easter","BG",2006 +"2006-04-24","Orthodox Easter","BG",2006 +"2006-05-01","Labour Day and International Workers' Solidarity Day","BG",2006 +"2006-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2006 +"2006-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2006 +"2006-09-06","Unification Day","BG",2006 +"2006-09-22","Independence Day","BG",2006 +"2006-11-01","The Day of the People's Awakeners","BG",2006 +"2006-12-24","Christmas Eve","BG",2006 +"2006-12-25","Christmas Day","BG",2006 +"2006-12-26","Christmas Day","BG",2006 +"2007-01-01","New Year's Day","BG",2007 +"2007-03-03","Liberation Day","BG",2007 +"2007-04-06","Orthodox Good Friday","BG",2007 +"2007-04-07","Orthodox Easter Saturday","BG",2007 +"2007-04-08","Orthodox Easter","BG",2007 +"2007-04-09","Orthodox Easter","BG",2007 +"2007-05-01","Labour Day and International Workers' Solidarity Day","BG",2007 +"2007-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2007 +"2007-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2007 +"2007-09-06","Unification Day","BG",2007 +"2007-09-22","Independence Day","BG",2007 +"2007-11-01","The Day of the People's Awakeners","BG",2007 +"2007-12-24","Christmas Eve","BG",2007 +"2007-12-25","Christmas Day","BG",2007 +"2007-12-26","Christmas Day","BG",2007 +"2008-01-01","New Year's Day","BG",2008 +"2008-03-03","Liberation Day","BG",2008 +"2008-04-25","Orthodox Good Friday","BG",2008 +"2008-04-26","Orthodox Easter Saturday","BG",2008 +"2008-04-27","Orthodox Easter","BG",2008 +"2008-04-28","Orthodox Easter","BG",2008 +"2008-05-01","Labour Day and International Workers' Solidarity Day","BG",2008 +"2008-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2008 +"2008-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2008 +"2008-09-06","Unification Day","BG",2008 +"2008-09-22","Independence Day","BG",2008 +"2008-11-01","The Day of the People's Awakeners","BG",2008 +"2008-12-24","Christmas Eve","BG",2008 +"2008-12-25","Christmas Day","BG",2008 +"2008-12-26","Christmas Day","BG",2008 +"2009-01-01","New Year's Day","BG",2009 +"2009-03-03","Liberation Day","BG",2009 +"2009-04-17","Orthodox Good Friday","BG",2009 +"2009-04-18","Orthodox Easter Saturday","BG",2009 +"2009-04-19","Orthodox Easter","BG",2009 +"2009-04-20","Orthodox Easter","BG",2009 +"2009-05-01","Labour Day and International Workers' Solidarity Day","BG",2009 +"2009-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2009 +"2009-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2009 +"2009-09-06","Unification Day","BG",2009 +"2009-09-22","Independence Day","BG",2009 +"2009-11-01","The Day of the People's Awakeners","BG",2009 +"2009-12-24","Christmas Eve","BG",2009 +"2009-12-25","Christmas Day","BG",2009 +"2009-12-26","Christmas Day","BG",2009 +"2010-01-01","New Year's Day","BG",2010 +"2010-03-03","Liberation Day","BG",2010 +"2010-04-02","Orthodox Good Friday","BG",2010 +"2010-04-03","Orthodox Easter Saturday","BG",2010 +"2010-04-04","Orthodox Easter","BG",2010 +"2010-04-05","Orthodox Easter","BG",2010 +"2010-05-01","Labour Day and International Workers' Solidarity Day","BG",2010 +"2010-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2010 +"2010-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2010 +"2010-09-06","Unification Day","BG",2010 +"2010-09-22","Independence Day","BG",2010 +"2010-11-01","The Day of the People's Awakeners","BG",2010 +"2010-12-24","Christmas Eve","BG",2010 +"2010-12-25","Christmas Day","BG",2010 +"2010-12-26","Christmas Day","BG",2010 +"2011-01-01","New Year's Day","BG",2011 +"2011-03-03","Liberation Day","BG",2011 +"2011-04-22","Orthodox Good Friday","BG",2011 +"2011-04-23","Orthodox Easter Saturday","BG",2011 +"2011-04-24","Orthodox Easter","BG",2011 +"2011-04-25","Orthodox Easter","BG",2011 +"2011-05-01","Labour Day and International Workers' Solidarity Day","BG",2011 +"2011-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2011 +"2011-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2011 +"2011-09-06","Unification Day","BG",2011 +"2011-09-22","Independence Day","BG",2011 +"2011-11-01","The Day of the People's Awakeners","BG",2011 +"2011-12-24","Christmas Eve","BG",2011 +"2011-12-25","Christmas Day","BG",2011 +"2011-12-26","Christmas Day","BG",2011 +"2012-01-01","New Year's Day","BG",2012 +"2012-03-03","Liberation Day","BG",2012 +"2012-04-13","Orthodox Good Friday","BG",2012 +"2012-04-14","Orthodox Easter Saturday","BG",2012 +"2012-04-15","Orthodox Easter","BG",2012 +"2012-04-16","Orthodox Easter","BG",2012 +"2012-05-01","Labour Day and International Workers' Solidarity Day","BG",2012 +"2012-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2012 +"2012-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2012 +"2012-09-06","Unification Day","BG",2012 +"2012-09-22","Independence Day","BG",2012 +"2012-11-01","The Day of the People's Awakeners","BG",2012 +"2012-12-24","Christmas Eve","BG",2012 +"2012-12-25","Christmas Day","BG",2012 +"2012-12-26","Christmas Day","BG",2012 +"2013-01-01","New Year's Day","BG",2013 +"2013-03-03","Liberation Day","BG",2013 +"2013-05-01","Labour Day and International Workers' Solidarity Day","BG",2013 +"2013-05-03","Orthodox Good Friday","BG",2013 +"2013-05-04","Orthodox Easter Saturday","BG",2013 +"2013-05-05","Orthodox Easter","BG",2013 +"2013-05-06","Orthodox Easter","BG",2013 +"2013-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2013 +"2013-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2013 +"2013-09-06","Unification Day","BG",2013 +"2013-09-22","Independence Day","BG",2013 +"2013-11-01","The Day of the People's Awakeners","BG",2013 +"2013-12-24","Christmas Eve","BG",2013 +"2013-12-25","Christmas Day","BG",2013 +"2013-12-26","Christmas Day","BG",2013 +"2014-01-01","New Year's Day","BG",2014 +"2014-03-03","Liberation Day","BG",2014 +"2014-04-18","Orthodox Good Friday","BG",2014 +"2014-04-19","Orthodox Easter Saturday","BG",2014 +"2014-04-20","Orthodox Easter","BG",2014 +"2014-04-21","Orthodox Easter","BG",2014 +"2014-05-01","Labour Day and International Workers' Solidarity Day","BG",2014 +"2014-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2014 +"2014-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2014 +"2014-09-06","Unification Day","BG",2014 +"2014-09-22","Independence Day","BG",2014 +"2014-11-01","The Day of the People's Awakeners","BG",2014 +"2014-12-24","Christmas Eve","BG",2014 +"2014-12-25","Christmas Day","BG",2014 +"2014-12-26","Christmas Day","BG",2014 +"2015-01-01","New Year's Day","BG",2015 +"2015-03-03","Liberation Day","BG",2015 +"2015-04-10","Orthodox Good Friday","BG",2015 +"2015-04-11","Orthodox Easter Saturday","BG",2015 +"2015-04-12","Orthodox Easter","BG",2015 +"2015-04-13","Orthodox Easter","BG",2015 +"2015-05-01","Labour Day and International Workers' Solidarity Day","BG",2015 +"2015-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2015 +"2015-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2015 +"2015-09-06","Unification Day","BG",2015 +"2015-09-22","Independence Day","BG",2015 +"2015-11-01","The Day of the People's Awakeners","BG",2015 +"2015-12-24","Christmas Eve","BG",2015 +"2015-12-25","Christmas Day","BG",2015 +"2015-12-26","Christmas Day","BG",2015 +"2016-01-01","New Year's Day","BG",2016 +"2016-03-03","Liberation Day","BG",2016 +"2016-04-29","Orthodox Good Friday","BG",2016 +"2016-04-30","Orthodox Easter Saturday","BG",2016 +"2016-05-01","Labour Day and International Workers' Solidarity Day","BG",2016 +"2016-05-01","Orthodox Easter","BG",2016 +"2016-05-02","Orthodox Easter","BG",2016 +"2016-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2016 +"2016-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2016 +"2016-09-06","Unification Day","BG",2016 +"2016-09-22","Independence Day","BG",2016 +"2016-11-01","The Day of the People's Awakeners","BG",2016 +"2016-12-24","Christmas Eve","BG",2016 +"2016-12-25","Christmas Day","BG",2016 +"2016-12-26","Christmas Day","BG",2016 +"2017-01-01","New Year's Day","BG",2017 +"2017-03-03","Liberation Day","BG",2017 +"2017-04-14","Orthodox Good Friday","BG",2017 +"2017-04-15","Orthodox Easter Saturday","BG",2017 +"2017-04-16","Orthodox Easter","BG",2017 +"2017-04-17","Orthodox Easter","BG",2017 +"2017-05-01","Labour Day and International Workers' Solidarity Day","BG",2017 +"2017-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2017 +"2017-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2017 +"2017-09-06","Unification Day","BG",2017 +"2017-09-22","Independence Day","BG",2017 +"2017-11-01","The Day of the People's Awakeners","BG",2017 +"2017-12-24","Christmas Eve","BG",2017 +"2017-12-25","Christmas Day","BG",2017 +"2017-12-26","Christmas Day","BG",2017 +"2018-01-01","New Year's Day","BG",2018 +"2018-03-03","Liberation Day","BG",2018 +"2018-04-06","Orthodox Good Friday","BG",2018 +"2018-04-07","Orthodox Easter Saturday","BG",2018 +"2018-04-08","Orthodox Easter","BG",2018 +"2018-04-09","Orthodox Easter","BG",2018 +"2018-05-01","Labour Day and International Workers' Solidarity Day","BG",2018 +"2018-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2018 +"2018-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2018 +"2018-09-06","Unification Day","BG",2018 +"2018-09-22","Independence Day","BG",2018 +"2018-11-01","The Day of the People's Awakeners","BG",2018 +"2018-12-24","Christmas Eve","BG",2018 +"2018-12-25","Christmas Day","BG",2018 +"2018-12-26","Christmas Day","BG",2018 +"2019-01-01","New Year's Day","BG",2019 +"2019-03-03","Liberation Day","BG",2019 +"2019-04-26","Orthodox Good Friday","BG",2019 +"2019-04-27","Orthodox Easter Saturday","BG",2019 +"2019-04-28","Orthodox Easter","BG",2019 +"2019-04-29","Orthodox Easter","BG",2019 +"2019-05-01","Labour Day and International Workers' Solidarity Day","BG",2019 +"2019-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2019 +"2019-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2019 +"2019-09-06","Unification Day","BG",2019 +"2019-09-22","Independence Day","BG",2019 +"2019-11-01","The Day of the People's Awakeners","BG",2019 +"2019-12-24","Christmas Eve","BG",2019 +"2019-12-25","Christmas Day","BG",2019 +"2019-12-26","Christmas Day","BG",2019 +"2020-01-01","New Year's Day","BG",2020 +"2020-03-03","Liberation Day","BG",2020 +"2020-04-17","Orthodox Good Friday","BG",2020 +"2020-04-18","Orthodox Easter Saturday","BG",2020 +"2020-04-19","Orthodox Easter","BG",2020 +"2020-04-20","Orthodox Easter","BG",2020 +"2020-05-01","Labour Day and International Workers' Solidarity Day","BG",2020 +"2020-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2020 +"2020-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2020 +"2020-09-06","Unification Day","BG",2020 +"2020-09-22","Independence Day","BG",2020 +"2020-11-01","The Day of the People's Awakeners","BG",2020 +"2020-12-24","Christmas Eve","BG",2020 +"2020-12-25","Christmas Day","BG",2020 +"2020-12-26","Christmas Day","BG",2020 +"2021-01-01","New Year's Day","BG",2021 +"2021-03-03","Liberation Day","BG",2021 +"2021-04-30","Orthodox Good Friday","BG",2021 +"2021-05-01","Labour Day and International Workers' Solidarity Day","BG",2021 +"2021-05-01","Orthodox Easter Saturday","BG",2021 +"2021-05-02","Orthodox Easter","BG",2021 +"2021-05-03","Orthodox Easter","BG",2021 +"2021-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2021 +"2021-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2021 +"2021-09-06","Unification Day","BG",2021 +"2021-09-22","Independence Day","BG",2021 +"2021-11-01","The Day of the People's Awakeners","BG",2021 +"2021-12-24","Christmas Eve","BG",2021 +"2021-12-25","Christmas Day","BG",2021 +"2021-12-26","Christmas Day","BG",2021 +"2022-01-01","New Year's Day","BG",2022 +"2022-03-03","Liberation Day","BG",2022 +"2022-04-22","Orthodox Good Friday","BG",2022 +"2022-04-23","Orthodox Easter Saturday","BG",2022 +"2022-04-24","Orthodox Easter","BG",2022 +"2022-04-25","Orthodox Easter","BG",2022 +"2022-05-01","Labour Day and International Workers' Solidarity Day","BG",2022 +"2022-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2022 +"2022-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2022 +"2022-09-06","Unification Day","BG",2022 +"2022-09-22","Independence Day","BG",2022 +"2022-11-01","The Day of the People's Awakeners","BG",2022 +"2022-12-24","Christmas Eve","BG",2022 +"2022-12-25","Christmas Day","BG",2022 +"2022-12-26","Christmas Day","BG",2022 +"2023-01-01","New Year's Day","BG",2023 +"2023-03-03","Liberation Day","BG",2023 +"2023-04-14","Orthodox Good Friday","BG",2023 +"2023-04-15","Orthodox Easter Saturday","BG",2023 +"2023-04-16","Orthodox Easter","BG",2023 +"2023-04-17","Orthodox Easter","BG",2023 +"2023-05-01","Labour Day and International Workers' Solidarity Day","BG",2023 +"2023-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2023 +"2023-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2023 +"2023-09-06","Unification Day","BG",2023 +"2023-09-22","Independence Day","BG",2023 +"2023-11-01","The Day of the People's Awakeners","BG",2023 +"2023-12-24","Christmas Eve","BG",2023 +"2023-12-25","Christmas Day","BG",2023 +"2023-12-26","Christmas Day","BG",2023 +"2024-01-01","New Year's Day","BG",2024 +"2024-03-03","Liberation Day","BG",2024 +"2024-05-01","Labour Day and International Workers' Solidarity Day","BG",2024 +"2024-05-03","Orthodox Good Friday","BG",2024 +"2024-05-04","Orthodox Easter Saturday","BG",2024 +"2024-05-05","Orthodox Easter","BG",2024 +"2024-05-06","Orthodox Easter","BG",2024 +"2024-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2024 +"2024-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2024 +"2024-09-06","Unification Day","BG",2024 +"2024-09-22","Independence Day","BG",2024 +"2024-11-01","The Day of the People's Awakeners","BG",2024 +"2024-12-24","Christmas Eve","BG",2024 +"2024-12-25","Christmas Day","BG",2024 +"2024-12-26","Christmas Day","BG",2024 +"2025-01-01","New Year's Day","BG",2025 +"2025-03-03","Liberation Day","BG",2025 +"2025-04-18","Orthodox Good Friday","BG",2025 +"2025-04-19","Orthodox Easter Saturday","BG",2025 +"2025-04-20","Orthodox Easter","BG",2025 +"2025-04-21","Orthodox Easter","BG",2025 +"2025-05-01","Labour Day and International Workers' Solidarity Day","BG",2025 +"2025-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2025 +"2025-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2025 +"2025-09-06","Unification Day","BG",2025 +"2025-09-22","Independence Day","BG",2025 +"2025-11-01","The Day of the People's Awakeners","BG",2025 +"2025-12-24","Christmas Eve","BG",2025 +"2025-12-25","Christmas Day","BG",2025 +"2025-12-26","Christmas Day","BG",2025 +"2026-01-01","New Year's Day","BG",2026 +"2026-03-03","Liberation Day","BG",2026 +"2026-04-10","Orthodox Good Friday","BG",2026 +"2026-04-11","Orthodox Easter Saturday","BG",2026 +"2026-04-12","Orthodox Easter","BG",2026 +"2026-04-13","Orthodox Easter","BG",2026 +"2026-05-01","Labour Day and International Workers' Solidarity Day","BG",2026 +"2026-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2026 +"2026-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2026 +"2026-09-06","Unification Day","BG",2026 +"2026-09-22","Independence Day","BG",2026 +"2026-11-01","The Day of the People's Awakeners","BG",2026 +"2026-12-24","Christmas Eve","BG",2026 +"2026-12-25","Christmas Day","BG",2026 +"2026-12-26","Christmas Day","BG",2026 +"2027-01-01","New Year's Day","BG",2027 +"2027-03-03","Liberation Day","BG",2027 +"2027-04-30","Orthodox Good Friday","BG",2027 +"2027-05-01","Labour Day and International Workers' Solidarity Day","BG",2027 +"2027-05-01","Orthodox Easter Saturday","BG",2027 +"2027-05-02","Orthodox Easter","BG",2027 +"2027-05-03","Orthodox Easter","BG",2027 +"2027-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2027 +"2027-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2027 +"2027-09-06","Unification Day","BG",2027 +"2027-09-22","Independence Day","BG",2027 +"2027-11-01","The Day of the People's Awakeners","BG",2027 +"2027-12-24","Christmas Eve","BG",2027 +"2027-12-25","Christmas Day","BG",2027 +"2027-12-26","Christmas Day","BG",2027 +"2028-01-01","New Year's Day","BG",2028 +"2028-03-03","Liberation Day","BG",2028 +"2028-04-14","Orthodox Good Friday","BG",2028 +"2028-04-15","Orthodox Easter Saturday","BG",2028 +"2028-04-16","Orthodox Easter","BG",2028 +"2028-04-17","Orthodox Easter","BG",2028 +"2028-05-01","Labour Day and International Workers' Solidarity Day","BG",2028 +"2028-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2028 +"2028-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2028 +"2028-09-06","Unification Day","BG",2028 +"2028-09-22","Independence Day","BG",2028 +"2028-11-01","The Day of the People's Awakeners","BG",2028 +"2028-12-24","Christmas Eve","BG",2028 +"2028-12-25","Christmas Day","BG",2028 +"2028-12-26","Christmas Day","BG",2028 +"2029-01-01","New Year's Day","BG",2029 +"2029-03-03","Liberation Day","BG",2029 +"2029-04-06","Orthodox Good Friday","BG",2029 +"2029-04-07","Orthodox Easter Saturday","BG",2029 +"2029-04-08","Orthodox Easter","BG",2029 +"2029-04-09","Orthodox Easter","BG",2029 +"2029-05-01","Labour Day and International Workers' Solidarity Day","BG",2029 +"2029-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2029 +"2029-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2029 +"2029-09-06","Unification Day","BG",2029 +"2029-09-22","Independence Day","BG",2029 +"2029-11-01","The Day of the People's Awakeners","BG",2029 +"2029-12-24","Christmas Eve","BG",2029 +"2029-12-25","Christmas Day","BG",2029 +"2029-12-26","Christmas Day","BG",2029 +"2030-01-01","New Year's Day","BG",2030 +"2030-03-03","Liberation Day","BG",2030 +"2030-04-26","Orthodox Good Friday","BG",2030 +"2030-04-27","Orthodox Easter Saturday","BG",2030 +"2030-04-28","Orthodox Easter","BG",2030 +"2030-04-29","Orthodox Easter","BG",2030 +"2030-05-01","Labour Day and International Workers' Solidarity Day","BG",2030 +"2030-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2030 +"2030-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2030 +"2030-09-06","Unification Day","BG",2030 +"2030-09-22","Independence Day","BG",2030 +"2030-11-01","The Day of the People's Awakeners","BG",2030 +"2030-12-24","Christmas Eve","BG",2030 +"2030-12-25","Christmas Day","BG",2030 +"2030-12-26","Christmas Day","BG",2030 +"2031-01-01","New Year's Day","BG",2031 +"2031-03-03","Liberation Day","BG",2031 +"2031-04-11","Orthodox Good Friday","BG",2031 +"2031-04-12","Orthodox Easter Saturday","BG",2031 +"2031-04-13","Orthodox Easter","BG",2031 +"2031-04-14","Orthodox Easter","BG",2031 +"2031-05-01","Labour Day and International Workers' Solidarity Day","BG",2031 +"2031-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2031 +"2031-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2031 +"2031-09-06","Unification Day","BG",2031 +"2031-09-22","Independence Day","BG",2031 +"2031-11-01","The Day of the People's Awakeners","BG",2031 +"2031-12-24","Christmas Eve","BG",2031 +"2031-12-25","Christmas Day","BG",2031 +"2031-12-26","Christmas Day","BG",2031 +"2032-01-01","New Year's Day","BG",2032 +"2032-03-03","Liberation Day","BG",2032 +"2032-04-30","Orthodox Good Friday","BG",2032 +"2032-05-01","Labour Day and International Workers' Solidarity Day","BG",2032 +"2032-05-01","Orthodox Easter Saturday","BG",2032 +"2032-05-02","Orthodox Easter","BG",2032 +"2032-05-03","Orthodox Easter","BG",2032 +"2032-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2032 +"2032-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2032 +"2032-09-06","Unification Day","BG",2032 +"2032-09-22","Independence Day","BG",2032 +"2032-11-01","The Day of the People's Awakeners","BG",2032 +"2032-12-24","Christmas Eve","BG",2032 +"2032-12-25","Christmas Day","BG",2032 +"2032-12-26","Christmas Day","BG",2032 +"2033-01-01","New Year's Day","BG",2033 +"2033-03-03","Liberation Day","BG",2033 +"2033-04-22","Orthodox Good Friday","BG",2033 +"2033-04-23","Orthodox Easter Saturday","BG",2033 +"2033-04-24","Orthodox Easter","BG",2033 +"2033-04-25","Orthodox Easter","BG",2033 +"2033-05-01","Labour Day and International Workers' Solidarity Day","BG",2033 +"2033-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2033 +"2033-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2033 +"2033-09-06","Unification Day","BG",2033 +"2033-09-22","Independence Day","BG",2033 +"2033-11-01","The Day of the People's Awakeners","BG",2033 +"2033-12-24","Christmas Eve","BG",2033 +"2033-12-25","Christmas Day","BG",2033 +"2033-12-26","Christmas Day","BG",2033 +"2034-01-01","New Year's Day","BG",2034 +"2034-03-03","Liberation Day","BG",2034 +"2034-04-07","Orthodox Good Friday","BG",2034 +"2034-04-08","Orthodox Easter Saturday","BG",2034 +"2034-04-09","Orthodox Easter","BG",2034 +"2034-04-10","Orthodox Easter","BG",2034 +"2034-05-01","Labour Day and International Workers' Solidarity Day","BG",2034 +"2034-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2034 +"2034-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2034 +"2034-09-06","Unification Day","BG",2034 +"2034-09-22","Independence Day","BG",2034 +"2034-11-01","The Day of the People's Awakeners","BG",2034 +"2034-12-24","Christmas Eve","BG",2034 +"2034-12-25","Christmas Day","BG",2034 +"2034-12-26","Christmas Day","BG",2034 +"2035-01-01","New Year's Day","BG",2035 +"2035-03-03","Liberation Day","BG",2035 +"2035-04-27","Orthodox Good Friday","BG",2035 +"2035-04-28","Orthodox Easter Saturday","BG",2035 +"2035-04-29","Orthodox Easter","BG",2035 +"2035-04-30","Orthodox Easter","BG",2035 +"2035-05-01","Labour Day and International Workers' Solidarity Day","BG",2035 +"2035-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2035 +"2035-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2035 +"2035-09-06","Unification Day","BG",2035 +"2035-09-22","Independence Day","BG",2035 +"2035-11-01","The Day of the People's Awakeners","BG",2035 +"2035-12-24","Christmas Eve","BG",2035 +"2035-12-25","Christmas Day","BG",2035 +"2035-12-26","Christmas Day","BG",2035 +"2036-01-01","New Year's Day","BG",2036 +"2036-03-03","Liberation Day","BG",2036 +"2036-04-18","Orthodox Good Friday","BG",2036 +"2036-04-19","Orthodox Easter Saturday","BG",2036 +"2036-04-20","Orthodox Easter","BG",2036 +"2036-04-21","Orthodox Easter","BG",2036 +"2036-05-01","Labour Day and International Workers' Solidarity Day","BG",2036 +"2036-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2036 +"2036-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2036 +"2036-09-06","Unification Day","BG",2036 +"2036-09-22","Independence Day","BG",2036 +"2036-11-01","The Day of the People's Awakeners","BG",2036 +"2036-12-24","Christmas Eve","BG",2036 +"2036-12-25","Christmas Day","BG",2036 +"2036-12-26","Christmas Day","BG",2036 +"2037-01-01","New Year's Day","BG",2037 +"2037-03-03","Liberation Day","BG",2037 +"2037-04-03","Orthodox Good Friday","BG",2037 +"2037-04-04","Orthodox Easter Saturday","BG",2037 +"2037-04-05","Orthodox Easter","BG",2037 +"2037-04-06","Orthodox Easter","BG",2037 +"2037-05-01","Labour Day and International Workers' Solidarity Day","BG",2037 +"2037-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2037 +"2037-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2037 +"2037-09-06","Unification Day","BG",2037 +"2037-09-22","Independence Day","BG",2037 +"2037-11-01","The Day of the People's Awakeners","BG",2037 +"2037-12-24","Christmas Eve","BG",2037 +"2037-12-25","Christmas Day","BG",2037 +"2037-12-26","Christmas Day","BG",2037 +"2038-01-01","New Year's Day","BG",2038 +"2038-03-03","Liberation Day","BG",2038 +"2038-04-23","Orthodox Good Friday","BG",2038 +"2038-04-24","Orthodox Easter Saturday","BG",2038 +"2038-04-25","Orthodox Easter","BG",2038 +"2038-04-26","Orthodox Easter","BG",2038 +"2038-05-01","Labour Day and International Workers' Solidarity Day","BG",2038 +"2038-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2038 +"2038-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2038 +"2038-09-06","Unification Day","BG",2038 +"2038-09-22","Independence Day","BG",2038 +"2038-11-01","The Day of the People's Awakeners","BG",2038 +"2038-12-24","Christmas Eve","BG",2038 +"2038-12-25","Christmas Day","BG",2038 +"2038-12-26","Christmas Day","BG",2038 +"2039-01-01","New Year's Day","BG",2039 +"2039-03-03","Liberation Day","BG",2039 +"2039-04-15","Orthodox Good Friday","BG",2039 +"2039-04-16","Orthodox Easter Saturday","BG",2039 +"2039-04-17","Orthodox Easter","BG",2039 +"2039-04-18","Orthodox Easter","BG",2039 +"2039-05-01","Labour Day and International Workers' Solidarity Day","BG",2039 +"2039-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2039 +"2039-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2039 +"2039-09-06","Unification Day","BG",2039 +"2039-09-22","Independence Day","BG",2039 +"2039-11-01","The Day of the People's Awakeners","BG",2039 +"2039-12-24","Christmas Eve","BG",2039 +"2039-12-25","Christmas Day","BG",2039 +"2039-12-26","Christmas Day","BG",2039 +"2040-01-01","New Year's Day","BG",2040 +"2040-03-03","Liberation Day","BG",2040 +"2040-05-01","Labour Day and International Workers' Solidarity Day","BG",2040 +"2040-05-04","Orthodox Good Friday","BG",2040 +"2040-05-05","Orthodox Easter Saturday","BG",2040 +"2040-05-06","Orthodox Easter","BG",2040 +"2040-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2040 +"2040-05-07","Orthodox Easter","BG",2040 +"2040-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2040 +"2040-09-06","Unification Day","BG",2040 +"2040-09-22","Independence Day","BG",2040 +"2040-11-01","The Day of the People's Awakeners","BG",2040 +"2040-12-24","Christmas Eve","BG",2040 +"2040-12-25","Christmas Day","BG",2040 +"2040-12-26","Christmas Day","BG",2040 +"2041-01-01","New Year's Day","BG",2041 +"2041-03-03","Liberation Day","BG",2041 +"2041-04-19","Orthodox Good Friday","BG",2041 +"2041-04-20","Orthodox Easter Saturday","BG",2041 +"2041-04-21","Orthodox Easter","BG",2041 +"2041-04-22","Orthodox Easter","BG",2041 +"2041-05-01","Labour Day and International Workers' Solidarity Day","BG",2041 +"2041-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2041 +"2041-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2041 +"2041-09-06","Unification Day","BG",2041 +"2041-09-22","Independence Day","BG",2041 +"2041-11-01","The Day of the People's Awakeners","BG",2041 +"2041-12-24","Christmas Eve","BG",2041 +"2041-12-25","Christmas Day","BG",2041 +"2041-12-26","Christmas Day","BG",2041 +"2042-01-01","New Year's Day","BG",2042 +"2042-03-03","Liberation Day","BG",2042 +"2042-04-11","Orthodox Good Friday","BG",2042 +"2042-04-12","Orthodox Easter Saturday","BG",2042 +"2042-04-13","Orthodox Easter","BG",2042 +"2042-04-14","Orthodox Easter","BG",2042 +"2042-05-01","Labour Day and International Workers' Solidarity Day","BG",2042 +"2042-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2042 +"2042-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2042 +"2042-09-06","Unification Day","BG",2042 +"2042-09-22","Independence Day","BG",2042 +"2042-11-01","The Day of the People's Awakeners","BG",2042 +"2042-12-24","Christmas Eve","BG",2042 +"2042-12-25","Christmas Day","BG",2042 +"2042-12-26","Christmas Day","BG",2042 +"2043-01-01","New Year's Day","BG",2043 +"2043-03-03","Liberation Day","BG",2043 +"2043-05-01","Labour Day and International Workers' Solidarity Day","BG",2043 +"2043-05-01","Orthodox Good Friday","BG",2043 +"2043-05-02","Orthodox Easter Saturday","BG",2043 +"2043-05-03","Orthodox Easter","BG",2043 +"2043-05-04","Orthodox Easter","BG",2043 +"2043-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2043 +"2043-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2043 +"2043-09-06","Unification Day","BG",2043 +"2043-09-22","Independence Day","BG",2043 +"2043-11-01","The Day of the People's Awakeners","BG",2043 +"2043-12-24","Christmas Eve","BG",2043 +"2043-12-25","Christmas Day","BG",2043 +"2043-12-26","Christmas Day","BG",2043 +"2044-01-01","New Year's Day","BG",2044 +"2044-03-03","Liberation Day","BG",2044 +"2044-04-22","Orthodox Good Friday","BG",2044 +"2044-04-23","Orthodox Easter Saturday","BG",2044 +"2044-04-24","Orthodox Easter","BG",2044 +"2044-04-25","Orthodox Easter","BG",2044 +"2044-05-01","Labour Day and International Workers' Solidarity Day","BG",2044 +"2044-05-06","St. George's Day (Day of the Bulgarian Army)","BG",2044 +"2044-05-24","Day of Slavonic Alphabet, Bulgarian Enlightenment and Culture","BG",2044 +"2044-09-06","Unification Day","BG",2044 +"2044-09-22","Independence Day","BG",2044 +"2044-11-01","The Day of the People's Awakeners","BG",2044 +"2044-12-24","Christmas Eve","BG",2044 +"2044-12-25","Christmas Day","BG",2044 +"2044-12-26","Christmas Day","BG",2044 +"1995-01-01","New Year's Day","BH",1995 +"1995-03-02","Eid Al Fitr* (*estimated)","BH",1995 +"1995-03-03","Eid Al Fitr Holiday* (*estimated)","BH",1995 +"1995-03-04","Eid Al Fitr Holiday* (*estimated)","BH",1995 +"1995-05-01","Labour Day","BH",1995 +"1995-05-09","Eid Al Adha* (*estimated)","BH",1995 +"1995-05-10","Eid Al Adha Holiday* (*estimated)","BH",1995 +"1995-05-11","Eid Al Adha Holiday* (*estimated)","BH",1995 +"1995-05-30","Al Hijra New Year* (*estimated)","BH",1995 +"1995-06-07","Ashura Holiday* (*estimated)","BH",1995 +"1995-06-08","Ashura* (*estimated)","BH",1995 +"1995-08-08","Prophets Birthday* (*estimated)","BH",1995 +"1995-12-16","National Day","BH",1995 +"1995-12-17","National Day","BH",1995 +"1996-01-01","New Year's Day","BH",1996 +"1996-02-19","Eid Al Fitr* (*estimated)","BH",1996 +"1996-02-20","Eid Al Fitr Holiday* (*estimated)","BH",1996 +"1996-02-21","Eid Al Fitr Holiday* (*estimated)","BH",1996 +"1996-04-27","Eid Al Adha* (*estimated)","BH",1996 +"1996-04-28","Eid Al Adha Holiday* (*estimated)","BH",1996 +"1996-04-29","Eid Al Adha Holiday* (*estimated)","BH",1996 +"1996-05-01","Labour Day","BH",1996 +"1996-05-18","Al Hijra New Year* (*estimated)","BH",1996 +"1996-05-26","Ashura Holiday* (*estimated)","BH",1996 +"1996-05-27","Ashura* (*estimated)","BH",1996 +"1996-07-27","Prophets Birthday* (*estimated)","BH",1996 +"1996-12-16","National Day","BH",1996 +"1996-12-17","National Day","BH",1996 +"1997-01-01","New Year's Day","BH",1997 +"1997-02-08","Eid Al Fitr* (*estimated)","BH",1997 +"1997-02-09","Eid Al Fitr Holiday* (*estimated)","BH",1997 +"1997-02-10","Eid Al Fitr Holiday* (*estimated)","BH",1997 +"1997-04-17","Eid Al Adha* (*estimated)","BH",1997 +"1997-04-18","Eid Al Adha Holiday* (*estimated)","BH",1997 +"1997-04-19","Eid Al Adha Holiday* (*estimated)","BH",1997 +"1997-05-01","Labour Day","BH",1997 +"1997-05-07","Al Hijra New Year* (*estimated)","BH",1997 +"1997-05-15","Ashura Holiday* (*estimated)","BH",1997 +"1997-05-16","Ashura* (*estimated)","BH",1997 +"1997-07-16","Prophets Birthday* (*estimated)","BH",1997 +"1997-12-16","National Day","BH",1997 +"1997-12-17","National Day","BH",1997 +"1998-01-01","New Year's Day","BH",1998 +"1998-01-29","Eid Al Fitr* (*estimated)","BH",1998 +"1998-01-30","Eid Al Fitr Holiday* (*estimated)","BH",1998 +"1998-01-31","Eid Al Fitr Holiday* (*estimated)","BH",1998 +"1998-04-07","Eid Al Adha* (*estimated)","BH",1998 +"1998-04-08","Eid Al Adha Holiday* (*estimated)","BH",1998 +"1998-04-09","Eid Al Adha Holiday* (*estimated)","BH",1998 +"1998-04-27","Al Hijra New Year* (*estimated)","BH",1998 +"1998-05-01","Labour Day","BH",1998 +"1998-05-05","Ashura Holiday* (*estimated)","BH",1998 +"1998-05-06","Ashura* (*estimated)","BH",1998 +"1998-07-06","Prophets Birthday* (*estimated)","BH",1998 +"1998-12-16","National Day","BH",1998 +"1998-12-17","National Day","BH",1998 +"1999-01-01","New Year's Day","BH",1999 +"1999-01-18","Eid Al Fitr* (*estimated)","BH",1999 +"1999-01-19","Eid Al Fitr Holiday* (*estimated)","BH",1999 +"1999-01-20","Eid Al Fitr Holiday* (*estimated)","BH",1999 +"1999-03-27","Eid Al Adha* (*estimated)","BH",1999 +"1999-03-28","Eid Al Adha Holiday* (*estimated)","BH",1999 +"1999-03-29","Eid Al Adha Holiday* (*estimated)","BH",1999 +"1999-04-17","Al Hijra New Year* (*estimated)","BH",1999 +"1999-04-25","Ashura Holiday* (*estimated)","BH",1999 +"1999-04-26","Ashura* (*estimated)","BH",1999 +"1999-05-01","Labour Day","BH",1999 +"1999-06-26","Prophets Birthday* (*estimated)","BH",1999 +"1999-12-16","National Day","BH",1999 +"1999-12-17","National Day","BH",1999 +"2000-01-01","New Year's Day","BH",2000 +"2000-01-08","Eid Al Fitr* (*estimated)","BH",2000 +"2000-01-09","Eid Al Fitr Holiday* (*estimated)","BH",2000 +"2000-01-10","Eid Al Fitr Holiday* (*estimated)","BH",2000 +"2000-03-16","Eid Al Adha* (*estimated)","BH",2000 +"2000-03-17","Eid Al Adha Holiday* (*estimated)","BH",2000 +"2000-03-18","Eid Al Adha Holiday* (*estimated)","BH",2000 +"2000-04-06","Al Hijra New Year* (*estimated)","BH",2000 +"2000-04-14","Ashura Holiday* (*estimated)","BH",2000 +"2000-04-15","Ashura* (*estimated)","BH",2000 +"2000-05-01","Labour Day","BH",2000 +"2000-06-14","Prophets Birthday* (*estimated)","BH",2000 +"2000-12-16","National Day","BH",2000 +"2000-12-17","National Day","BH",2000 +"2000-12-27","Eid Al Fitr* (*estimated)","BH",2000 +"2000-12-28","Eid Al Fitr Holiday* (*estimated)","BH",2000 +"2000-12-29","Eid Al Fitr Holiday* (*estimated)","BH",2000 +"2001-01-01","New Year's Day","BH",2001 +"2001-03-05","Eid Al Adha* (*estimated)","BH",2001 +"2001-03-06","Eid Al Adha Holiday* (*estimated)","BH",2001 +"2001-03-07","Eid Al Adha Holiday* (*estimated)","BH",2001 +"2001-03-26","Al Hijra New Year* (*estimated)","BH",2001 +"2001-04-03","Ashura Holiday* (*estimated)","BH",2001 +"2001-04-04","Ashura* (*estimated)","BH",2001 +"2001-05-01","Labour Day","BH",2001 +"2001-06-04","Prophets Birthday* (*estimated)","BH",2001 +"2001-12-16","Eid Al Fitr* (*estimated)","BH",2001 +"2001-12-16","National Day","BH",2001 +"2001-12-17","Eid Al Fitr Holiday* (*estimated)","BH",2001 +"2001-12-17","National Day","BH",2001 +"2001-12-18","Eid Al Fitr Holiday* (*estimated)","BH",2001 +"2002-01-01","New Year's Day","BH",2002 +"2002-02-22","Eid Al Adha* (*estimated)","BH",2002 +"2002-02-23","Eid Al Adha Holiday* (*estimated)","BH",2002 +"2002-02-24","Eid Al Adha Holiday* (*estimated)","BH",2002 +"2002-03-15","Al Hijra New Year* (*estimated)","BH",2002 +"2002-03-23","Ashura Holiday* (*estimated)","BH",2002 +"2002-03-24","Ashura* (*estimated)","BH",2002 +"2002-05-01","Labour Day","BH",2002 +"2002-05-24","Prophets Birthday* (*estimated)","BH",2002 +"2002-12-05","Eid Al Fitr* (*estimated)","BH",2002 +"2002-12-06","Eid Al Fitr Holiday* (*estimated)","BH",2002 +"2002-12-07","Eid Al Fitr Holiday* (*estimated)","BH",2002 +"2002-12-16","National Day","BH",2002 +"2002-12-17","National Day","BH",2002 +"2003-01-01","New Year's Day","BH",2003 +"2003-02-11","Eid Al Adha* (*estimated)","BH",2003 +"2003-02-12","Eid Al Adha Holiday* (*estimated)","BH",2003 +"2003-02-13","Eid Al Adha Holiday* (*estimated)","BH",2003 +"2003-03-04","Al Hijra New Year* (*estimated)","BH",2003 +"2003-03-12","Ashura Holiday* (*estimated)","BH",2003 +"2003-03-13","Ashura* (*estimated)","BH",2003 +"2003-05-01","Labour Day","BH",2003 +"2003-05-13","Prophets Birthday* (*estimated)","BH",2003 +"2003-11-25","Eid Al Fitr* (*estimated)","BH",2003 +"2003-11-26","Eid Al Fitr Holiday* (*estimated)","BH",2003 +"2003-11-27","Eid Al Fitr Holiday* (*estimated)","BH",2003 +"2003-12-16","National Day","BH",2003 +"2003-12-17","National Day","BH",2003 +"2004-01-01","New Year's Day","BH",2004 +"2004-02-01","Eid Al Adha* (*estimated)","BH",2004 +"2004-02-02","Eid Al Adha Holiday* (*estimated)","BH",2004 +"2004-02-03","Eid Al Adha Holiday* (*estimated)","BH",2004 +"2004-02-21","Al Hijra New Year* (*estimated)","BH",2004 +"2004-02-29","Ashura Holiday* (*estimated)","BH",2004 +"2004-03-01","Ashura* (*estimated)","BH",2004 +"2004-05-01","Labour Day","BH",2004 +"2004-05-01","Prophets Birthday* (*estimated)","BH",2004 +"2004-11-14","Eid Al Fitr* (*estimated)","BH",2004 +"2004-11-15","Eid Al Fitr Holiday* (*estimated)","BH",2004 +"2004-11-16","Eid Al Fitr Holiday* (*estimated)","BH",2004 +"2004-12-16","National Day","BH",2004 +"2004-12-17","National Day","BH",2004 +"2005-01-01","New Year's Day","BH",2005 +"2005-01-21","Eid Al Adha* (*estimated)","BH",2005 +"2005-01-22","Eid Al Adha Holiday* (*estimated)","BH",2005 +"2005-01-23","Eid Al Adha Holiday* (*estimated)","BH",2005 +"2005-02-10","Al Hijra New Year* (*estimated)","BH",2005 +"2005-02-18","Ashura Holiday* (*estimated)","BH",2005 +"2005-02-19","Ashura* (*estimated)","BH",2005 +"2005-04-21","Prophets Birthday* (*estimated)","BH",2005 +"2005-05-01","Labour Day","BH",2005 +"2005-11-03","Eid Al Fitr* (*estimated)","BH",2005 +"2005-11-04","Eid Al Fitr Holiday* (*estimated)","BH",2005 +"2005-11-05","Eid Al Fitr Holiday* (*estimated)","BH",2005 +"2005-12-16","National Day","BH",2005 +"2005-12-17","National Day","BH",2005 +"2006-01-01","New Year's Day","BH",2006 +"2006-01-10","Eid Al Adha* (*estimated)","BH",2006 +"2006-01-11","Eid Al Adha Holiday* (*estimated)","BH",2006 +"2006-01-12","Eid Al Adha Holiday* (*estimated)","BH",2006 +"2006-01-31","Al Hijra New Year* (*estimated)","BH",2006 +"2006-02-08","Ashura Holiday* (*estimated)","BH",2006 +"2006-02-09","Ashura* (*estimated)","BH",2006 +"2006-04-10","Prophets Birthday* (*estimated)","BH",2006 +"2006-05-01","Labour Day","BH",2006 +"2006-10-23","Eid Al Fitr* (*estimated)","BH",2006 +"2006-10-24","Eid Al Fitr Holiday* (*estimated)","BH",2006 +"2006-10-25","Eid Al Fitr Holiday* (*estimated)","BH",2006 +"2006-12-16","National Day","BH",2006 +"2006-12-17","National Day","BH",2006 +"2006-12-31","Eid Al Adha* (*estimated)","BH",2006 +"2007-01-01","Eid Al Adha Holiday* (*estimated)","BH",2007 +"2007-01-01","New Year's Day","BH",2007 +"2007-01-02","Eid Al Adha Holiday* (*estimated)","BH",2007 +"2007-01-20","Al Hijra New Year* (*estimated)","BH",2007 +"2007-01-28","Ashura Holiday* (*estimated)","BH",2007 +"2007-01-29","Ashura* (*estimated)","BH",2007 +"2007-03-31","Prophets Birthday* (*estimated)","BH",2007 +"2007-05-01","Labour Day","BH",2007 +"2007-10-13","Eid Al Fitr* (*estimated)","BH",2007 +"2007-10-14","Eid Al Fitr Holiday* (*estimated)","BH",2007 +"2007-10-15","Eid Al Fitr Holiday* (*estimated)","BH",2007 +"2007-12-16","National Day","BH",2007 +"2007-12-17","National Day","BH",2007 +"2007-12-20","Eid Al Adha* (*estimated)","BH",2007 +"2007-12-21","Eid Al Adha Holiday* (*estimated)","BH",2007 +"2007-12-22","Eid Al Adha Holiday* (*estimated)","BH",2007 +"2008-01-01","New Year's Day","BH",2008 +"2008-01-10","Al Hijra New Year* (*estimated)","BH",2008 +"2008-01-18","Ashura Holiday* (*estimated)","BH",2008 +"2008-01-19","Ashura* (*estimated)","BH",2008 +"2008-03-20","Prophets Birthday* (*estimated)","BH",2008 +"2008-05-01","Labour Day","BH",2008 +"2008-10-01","Eid Al Fitr* (*estimated)","BH",2008 +"2008-10-02","Eid Al Fitr Holiday* (*estimated)","BH",2008 +"2008-10-03","Eid Al Fitr Holiday* (*estimated)","BH",2008 +"2008-12-08","Eid Al Adha* (*estimated)","BH",2008 +"2008-12-09","Eid Al Adha Holiday* (*estimated)","BH",2008 +"2008-12-10","Eid Al Adha Holiday* (*estimated)","BH",2008 +"2008-12-16","National Day","BH",2008 +"2008-12-17","National Day","BH",2008 +"2008-12-29","Al Hijra New Year* (*estimated)","BH",2008 +"2009-01-01","New Year's Day","BH",2009 +"2009-01-06","Ashura Holiday* (*estimated)","BH",2009 +"2009-01-07","Ashura* (*estimated)","BH",2009 +"2009-03-09","Prophets Birthday* (*estimated)","BH",2009 +"2009-05-01","Labour Day","BH",2009 +"2009-09-20","Eid Al Fitr* (*estimated)","BH",2009 +"2009-09-21","Eid Al Fitr Holiday* (*estimated)","BH",2009 +"2009-09-22","Eid Al Fitr Holiday* (*estimated)","BH",2009 +"2009-11-27","Eid Al Adha* (*estimated)","BH",2009 +"2009-11-28","Eid Al Adha Holiday* (*estimated)","BH",2009 +"2009-11-29","Eid Al Adha Holiday* (*estimated)","BH",2009 +"2009-12-16","National Day","BH",2009 +"2009-12-17","National Day","BH",2009 +"2009-12-18","Al Hijra New Year* (*estimated)","BH",2009 +"2009-12-26","Ashura Holiday* (*estimated)","BH",2009 +"2009-12-27","Ashura* (*estimated)","BH",2009 +"2010-01-01","New Year's Day","BH",2010 +"2010-02-26","Prophets Birthday* (*estimated)","BH",2010 +"2010-05-01","Labour Day","BH",2010 +"2010-09-10","Eid Al Fitr* (*estimated)","BH",2010 +"2010-09-11","Eid Al Fitr Holiday* (*estimated)","BH",2010 +"2010-09-12","Eid Al Fitr Holiday* (*estimated)","BH",2010 +"2010-11-16","Eid Al Adha* (*estimated)","BH",2010 +"2010-11-17","Eid Al Adha Holiday* (*estimated)","BH",2010 +"2010-11-18","Eid Al Adha Holiday* (*estimated)","BH",2010 +"2010-12-07","Al Hijra New Year* (*estimated)","BH",2010 +"2010-12-15","Ashura Holiday* (*estimated)","BH",2010 +"2010-12-16","Ashura* (*estimated)","BH",2010 +"2010-12-16","National Day","BH",2010 +"2010-12-17","National Day","BH",2010 +"2011-01-01","New Year's Day","BH",2011 +"2011-02-15","Prophets Birthday* (*estimated)","BH",2011 +"2011-05-01","Labour Day","BH",2011 +"2011-08-30","Eid Al Fitr* (*estimated)","BH",2011 +"2011-08-31","Eid Al Fitr Holiday* (*estimated)","BH",2011 +"2011-09-01","Eid Al Fitr Holiday* (*estimated)","BH",2011 +"2011-11-06","Eid Al Adha* (*estimated)","BH",2011 +"2011-11-07","Eid Al Adha Holiday* (*estimated)","BH",2011 +"2011-11-08","Eid Al Adha Holiday* (*estimated)","BH",2011 +"2011-11-26","Al Hijra New Year* (*estimated)","BH",2011 +"2011-12-04","Ashura Holiday* (*estimated)","BH",2011 +"2011-12-05","Ashura* (*estimated)","BH",2011 +"2011-12-16","National Day","BH",2011 +"2011-12-17","National Day","BH",2011 +"2012-01-01","New Year's Day","BH",2012 +"2012-02-04","Prophets Birthday* (*estimated)","BH",2012 +"2012-05-01","Labour Day","BH",2012 +"2012-08-19","Eid Al Fitr* (*estimated)","BH",2012 +"2012-08-20","Eid Al Fitr Holiday* (*estimated)","BH",2012 +"2012-08-21","Eid Al Fitr Holiday* (*estimated)","BH",2012 +"2012-10-26","Eid Al Adha* (*estimated)","BH",2012 +"2012-10-27","Eid Al Adha Holiday* (*estimated)","BH",2012 +"2012-10-28","Eid Al Adha Holiday* (*estimated)","BH",2012 +"2012-11-15","Al Hijra New Year* (*estimated)","BH",2012 +"2012-11-23","Ashura Holiday* (*estimated)","BH",2012 +"2012-11-24","Ashura* (*estimated)","BH",2012 +"2012-12-16","National Day","BH",2012 +"2012-12-17","National Day","BH",2012 +"2013-01-01","New Year's Day","BH",2013 +"2013-01-24","Prophets Birthday* (*estimated)","BH",2013 +"2013-05-01","Labour Day","BH",2013 +"2013-08-08","Eid Al Fitr* (*estimated)","BH",2013 +"2013-08-09","Eid Al Fitr Holiday* (*estimated)","BH",2013 +"2013-08-10","Eid Al Fitr Holiday* (*estimated)","BH",2013 +"2013-10-15","Eid Al Adha* (*estimated)","BH",2013 +"2013-10-16","Eid Al Adha Holiday* (*estimated)","BH",2013 +"2013-10-17","Eid Al Adha Holiday* (*estimated)","BH",2013 +"2013-11-04","Al Hijra New Year* (*estimated)","BH",2013 +"2013-11-12","Ashura Holiday* (*estimated)","BH",2013 +"2013-11-13","Ashura* (*estimated)","BH",2013 +"2013-12-16","National Day","BH",2013 +"2013-12-17","National Day","BH",2013 +"2014-01-01","New Year's Day","BH",2014 +"2014-01-13","Prophets Birthday* (*estimated)","BH",2014 +"2014-05-01","Labour Day","BH",2014 +"2014-07-28","Eid Al Fitr* (*estimated)","BH",2014 +"2014-07-29","Eid Al Fitr Holiday* (*estimated)","BH",2014 +"2014-07-30","Eid Al Fitr Holiday* (*estimated)","BH",2014 +"2014-10-04","Eid Al Adha* (*estimated)","BH",2014 +"2014-10-05","Eid Al Adha Holiday* (*estimated)","BH",2014 +"2014-10-06","Eid Al Adha Holiday* (*estimated)","BH",2014 +"2014-10-25","Al Hijra New Year* (*estimated)","BH",2014 +"2014-11-02","Ashura Holiday* (*estimated)","BH",2014 +"2014-11-03","Ashura* (*estimated)","BH",2014 +"2014-12-16","National Day","BH",2014 +"2014-12-17","National Day","BH",2014 +"2015-01-01","New Year's Day","BH",2015 +"2015-01-03","Prophets Birthday* (*estimated)","BH",2015 +"2015-05-01","Labour Day","BH",2015 +"2015-07-17","Eid Al Fitr* (*estimated)","BH",2015 +"2015-07-18","Eid Al Fitr Holiday* (*estimated)","BH",2015 +"2015-07-19","Eid Al Fitr Holiday* (*estimated)","BH",2015 +"2015-09-23","Eid Al Adha* (*estimated)","BH",2015 +"2015-09-24","Eid Al Adha Holiday* (*estimated)","BH",2015 +"2015-09-25","Eid Al Adha Holiday* (*estimated)","BH",2015 +"2015-10-14","Al Hijra New Year* (*estimated)","BH",2015 +"2015-10-22","Ashura Holiday* (*estimated)","BH",2015 +"2015-10-23","Ashura* (*estimated)","BH",2015 +"2015-12-16","National Day","BH",2015 +"2015-12-17","National Day","BH",2015 +"2015-12-23","Prophets Birthday* (*estimated)","BH",2015 +"2016-01-01","New Year's Day","BH",2016 +"2016-05-01","Labour Day","BH",2016 +"2016-07-06","Eid Al Fitr* (*estimated)","BH",2016 +"2016-07-07","Eid Al Fitr Holiday* (*estimated)","BH",2016 +"2016-07-08","Eid Al Fitr Holiday* (*estimated)","BH",2016 +"2016-09-11","Eid Al Adha* (*estimated)","BH",2016 +"2016-09-12","Eid Al Adha Holiday* (*estimated)","BH",2016 +"2016-09-13","Eid Al Adha Holiday* (*estimated)","BH",2016 +"2016-10-02","Al Hijra New Year* (*estimated)","BH",2016 +"2016-10-10","Ashura Holiday* (*estimated)","BH",2016 +"2016-10-11","Ashura* (*estimated)","BH",2016 +"2016-12-11","Prophets Birthday* (*estimated)","BH",2016 +"2016-12-16","National Day","BH",2016 +"2016-12-17","National Day","BH",2016 +"2017-01-01","New Year's Day","BH",2017 +"2017-05-01","Labour Day","BH",2017 +"2017-06-25","Eid Al Fitr* (*estimated)","BH",2017 +"2017-06-26","Eid Al Fitr Holiday* (*estimated)","BH",2017 +"2017-06-27","Eid Al Fitr Holiday* (*estimated)","BH",2017 +"2017-09-01","Eid Al Adha* (*estimated)","BH",2017 +"2017-09-02","Eid Al Adha Holiday* (*estimated)","BH",2017 +"2017-09-03","Eid Al Adha Holiday* (*estimated)","BH",2017 +"2017-09-21","Al Hijra New Year* (*estimated)","BH",2017 +"2017-09-29","Ashura Holiday* (*estimated)","BH",2017 +"2017-09-30","Ashura* (*estimated)","BH",2017 +"2017-11-30","Prophets Birthday* (*estimated)","BH",2017 +"2017-12-16","National Day","BH",2017 +"2017-12-17","National Day","BH",2017 +"2018-01-01","New Year's Day","BH",2018 +"2018-05-01","Labour Day","BH",2018 +"2018-06-15","Eid Al Fitr* (*estimated)","BH",2018 +"2018-06-16","Eid Al Fitr Holiday* (*estimated)","BH",2018 +"2018-06-17","Eid Al Fitr Holiday* (*estimated)","BH",2018 +"2018-08-21","Eid Al Adha* (*estimated)","BH",2018 +"2018-08-22","Eid Al Adha Holiday* (*estimated)","BH",2018 +"2018-08-23","Eid Al Adha Holiday* (*estimated)","BH",2018 +"2018-09-11","Al Hijra New Year* (*estimated)","BH",2018 +"2018-09-19","Ashura Holiday* (*estimated)","BH",2018 +"2018-09-20","Ashura* (*estimated)","BH",2018 +"2018-11-20","Prophets Birthday* (*estimated)","BH",2018 +"2018-12-16","National Day","BH",2018 +"2018-12-17","National Day","BH",2018 +"2019-01-01","New Year's Day","BH",2019 +"2019-05-01","Labour Day","BH",2019 +"2019-06-04","Eid Al Fitr* (*estimated)","BH",2019 +"2019-06-05","Eid Al Fitr Holiday* (*estimated)","BH",2019 +"2019-06-06","Eid Al Fitr Holiday* (*estimated)","BH",2019 +"2019-08-11","Eid Al Adha* (*estimated)","BH",2019 +"2019-08-12","Eid Al Adha Holiday* (*estimated)","BH",2019 +"2019-08-13","Eid Al Adha Holiday* (*estimated)","BH",2019 +"2019-08-31","Al Hijra New Year* (*estimated)","BH",2019 +"2019-09-08","Ashura Holiday* (*estimated)","BH",2019 +"2019-09-09","Ashura* (*estimated)","BH",2019 +"2019-11-09","Prophets Birthday* (*estimated)","BH",2019 +"2019-12-16","National Day","BH",2019 +"2019-12-17","National Day","BH",2019 +"2020-01-01","New Year's Day","BH",2020 +"2020-05-01","Labour Day","BH",2020 +"2020-05-24","Eid Al Fitr* (*estimated)","BH",2020 +"2020-05-25","Eid Al Fitr Holiday* (*estimated)","BH",2020 +"2020-05-26","Eid Al Fitr Holiday* (*estimated)","BH",2020 +"2020-07-31","Eid Al Adha* (*estimated)","BH",2020 +"2020-08-01","Eid Al Adha Holiday* (*estimated)","BH",2020 +"2020-08-02","Eid Al Adha Holiday* (*estimated)","BH",2020 +"2020-08-20","Al Hijra New Year* (*estimated)","BH",2020 +"2020-08-28","Ashura Holiday* (*estimated)","BH",2020 +"2020-08-29","Ashura* (*estimated)","BH",2020 +"2020-10-29","Prophets Birthday* (*estimated)","BH",2020 +"2020-12-16","National Day","BH",2020 +"2020-12-17","National Day","BH",2020 +"2021-01-01","New Year's Day","BH",2021 +"2021-05-01","Labour Day","BH",2021 +"2021-05-13","Eid Al Fitr* (*estimated)","BH",2021 +"2021-05-14","Eid Al Fitr Holiday* (*estimated)","BH",2021 +"2021-05-15","Eid Al Fitr Holiday* (*estimated)","BH",2021 +"2021-07-20","Eid Al Adha* (*estimated)","BH",2021 +"2021-07-21","Eid Al Adha Holiday* (*estimated)","BH",2021 +"2021-07-22","Eid Al Adha Holiday* (*estimated)","BH",2021 +"2021-08-09","Al Hijra New Year* (*estimated)","BH",2021 +"2021-08-17","Ashura Holiday* (*estimated)","BH",2021 +"2021-08-18","Ashura* (*estimated)","BH",2021 +"2021-10-18","Prophets Birthday* (*estimated)","BH",2021 +"2021-12-16","National Day","BH",2021 +"2021-12-17","National Day","BH",2021 +"2022-01-01","New Year's Day","BH",2022 +"2022-05-01","Labour Day","BH",2022 +"2022-05-02","Eid Al Fitr","BH",2022 +"2022-05-03","Eid Al Fitr Holiday","BH",2022 +"2022-05-04","Eid Al Fitr Holiday","BH",2022 +"2022-07-09","Eid Al Adha* (*estimated)","BH",2022 +"2022-07-10","Eid Al Adha Holiday* (*estimated)","BH",2022 +"2022-07-11","Eid Al Adha Holiday* (*estimated)","BH",2022 +"2022-07-30","Al Hijra New Year","BH",2022 +"2022-08-07","Ashura Holiday","BH",2022 +"2022-08-08","Ashura","BH",2022 +"2022-10-08","Prophets Birthday","BH",2022 +"2022-12-16","National Day","BH",2022 +"2022-12-17","National Day","BH",2022 +"2023-01-01","New Year's Day","BH",2023 +"2023-04-21","Eid Al Fitr* (*estimated)","BH",2023 +"2023-04-22","Eid Al Fitr Holiday* (*estimated)","BH",2023 +"2023-04-23","Eid Al Fitr Holiday* (*estimated)","BH",2023 +"2023-05-01","Labour Day","BH",2023 +"2023-06-28","Eid Al Adha* (*estimated)","BH",2023 +"2023-06-29","Eid Al Adha Holiday* (*estimated)","BH",2023 +"2023-06-30","Eid Al Adha Holiday* (*estimated)","BH",2023 +"2023-07-19","Al Hijra New Year* (*estimated)","BH",2023 +"2023-07-27","Ashura Holiday* (*estimated)","BH",2023 +"2023-07-28","Ashura* (*estimated)","BH",2023 +"2023-09-27","Prophets Birthday* (*estimated)","BH",2023 +"2023-12-16","National Day","BH",2023 +"2023-12-17","National Day","BH",2023 +"2024-01-01","New Year's Day","BH",2024 +"2024-04-10","Eid Al Fitr* (*estimated)","BH",2024 +"2024-04-11","Eid Al Fitr Holiday* (*estimated)","BH",2024 +"2024-04-12","Eid Al Fitr Holiday* (*estimated)","BH",2024 +"2024-05-01","Labour Day","BH",2024 +"2024-06-16","Eid Al Adha* (*estimated)","BH",2024 +"2024-06-17","Eid Al Adha Holiday* (*estimated)","BH",2024 +"2024-06-18","Eid Al Adha Holiday* (*estimated)","BH",2024 +"2024-07-07","Al Hijra New Year* (*estimated)","BH",2024 +"2024-07-15","Ashura Holiday* (*estimated)","BH",2024 +"2024-07-16","Ashura* (*estimated)","BH",2024 +"2024-09-15","Prophets Birthday* (*estimated)","BH",2024 +"2024-12-16","National Day","BH",2024 +"2024-12-17","National Day","BH",2024 +"2025-01-01","New Year's Day","BH",2025 +"2025-03-30","Eid Al Fitr* (*estimated)","BH",2025 +"2025-03-31","Eid Al Fitr Holiday* (*estimated)","BH",2025 +"2025-04-01","Eid Al Fitr Holiday* (*estimated)","BH",2025 +"2025-05-01","Labour Day","BH",2025 +"2025-06-06","Eid Al Adha* (*estimated)","BH",2025 +"2025-06-07","Eid Al Adha Holiday* (*estimated)","BH",2025 +"2025-06-08","Eid Al Adha Holiday* (*estimated)","BH",2025 +"2025-06-26","Al Hijra New Year* (*estimated)","BH",2025 +"2025-07-04","Ashura Holiday* (*estimated)","BH",2025 +"2025-07-05","Ashura* (*estimated)","BH",2025 +"2025-09-04","Prophets Birthday* (*estimated)","BH",2025 +"2025-12-16","National Day","BH",2025 +"2025-12-17","National Day","BH",2025 +"2026-01-01","New Year's Day","BH",2026 +"2026-03-20","Eid Al Fitr* (*estimated)","BH",2026 +"2026-03-21","Eid Al Fitr Holiday* (*estimated)","BH",2026 +"2026-03-22","Eid Al Fitr Holiday* (*estimated)","BH",2026 +"2026-05-01","Labour Day","BH",2026 +"2026-05-27","Eid Al Adha* (*estimated)","BH",2026 +"2026-05-28","Eid Al Adha Holiday* (*estimated)","BH",2026 +"2026-05-29","Eid Al Adha Holiday* (*estimated)","BH",2026 +"2026-06-16","Al Hijra New Year* (*estimated)","BH",2026 +"2026-06-24","Ashura Holiday* (*estimated)","BH",2026 +"2026-06-25","Ashura* (*estimated)","BH",2026 +"2026-08-25","Prophets Birthday* (*estimated)","BH",2026 +"2026-12-16","National Day","BH",2026 +"2026-12-17","National Day","BH",2026 +"2027-01-01","New Year's Day","BH",2027 +"2027-03-09","Eid Al Fitr* (*estimated)","BH",2027 +"2027-03-10","Eid Al Fitr Holiday* (*estimated)","BH",2027 +"2027-03-11","Eid Al Fitr Holiday* (*estimated)","BH",2027 +"2027-05-01","Labour Day","BH",2027 +"2027-05-16","Eid Al Adha* (*estimated)","BH",2027 +"2027-05-17","Eid Al Adha Holiday* (*estimated)","BH",2027 +"2027-05-18","Eid Al Adha Holiday* (*estimated)","BH",2027 +"2027-06-06","Al Hijra New Year* (*estimated)","BH",2027 +"2027-06-14","Ashura Holiday* (*estimated)","BH",2027 +"2027-06-15","Ashura* (*estimated)","BH",2027 +"2027-08-14","Prophets Birthday* (*estimated)","BH",2027 +"2027-12-16","National Day","BH",2027 +"2027-12-17","National Day","BH",2027 +"2028-01-01","New Year's Day","BH",2028 +"2028-02-26","Eid Al Fitr* (*estimated)","BH",2028 +"2028-02-27","Eid Al Fitr Holiday* (*estimated)","BH",2028 +"2028-02-28","Eid Al Fitr Holiday* (*estimated)","BH",2028 +"2028-05-01","Labour Day","BH",2028 +"2028-05-05","Eid Al Adha* (*estimated)","BH",2028 +"2028-05-06","Eid Al Adha Holiday* (*estimated)","BH",2028 +"2028-05-07","Eid Al Adha Holiday* (*estimated)","BH",2028 +"2028-05-25","Al Hijra New Year* (*estimated)","BH",2028 +"2028-06-02","Ashura Holiday* (*estimated)","BH",2028 +"2028-06-03","Ashura* (*estimated)","BH",2028 +"2028-08-03","Prophets Birthday* (*estimated)","BH",2028 +"2028-12-16","National Day","BH",2028 +"2028-12-17","National Day","BH",2028 +"2029-01-01","New Year's Day","BH",2029 +"2029-02-14","Eid Al Fitr* (*estimated)","BH",2029 +"2029-02-15","Eid Al Fitr Holiday* (*estimated)","BH",2029 +"2029-02-16","Eid Al Fitr Holiday* (*estimated)","BH",2029 +"2029-04-24","Eid Al Adha* (*estimated)","BH",2029 +"2029-04-25","Eid Al Adha Holiday* (*estimated)","BH",2029 +"2029-04-26","Eid Al Adha Holiday* (*estimated)","BH",2029 +"2029-05-01","Labour Day","BH",2029 +"2029-05-14","Al Hijra New Year* (*estimated)","BH",2029 +"2029-05-22","Ashura Holiday* (*estimated)","BH",2029 +"2029-05-23","Ashura* (*estimated)","BH",2029 +"2029-07-24","Prophets Birthday* (*estimated)","BH",2029 +"2029-12-16","National Day","BH",2029 +"2029-12-17","National Day","BH",2029 +"2030-01-01","New Year's Day","BH",2030 +"2030-02-04","Eid Al Fitr* (*estimated)","BH",2030 +"2030-02-05","Eid Al Fitr Holiday* (*estimated)","BH",2030 +"2030-02-06","Eid Al Fitr Holiday* (*estimated)","BH",2030 +"2030-04-13","Eid Al Adha* (*estimated)","BH",2030 +"2030-04-14","Eid Al Adha Holiday* (*estimated)","BH",2030 +"2030-04-15","Eid Al Adha Holiday* (*estimated)","BH",2030 +"2030-05-01","Labour Day","BH",2030 +"2030-05-03","Al Hijra New Year* (*estimated)","BH",2030 +"2030-05-11","Ashura Holiday* (*estimated)","BH",2030 +"2030-05-12","Ashura* (*estimated)","BH",2030 +"2030-07-13","Prophets Birthday* (*estimated)","BH",2030 +"2030-12-16","National Day","BH",2030 +"2030-12-17","National Day","BH",2030 +"2031-01-01","New Year's Day","BH",2031 +"2031-01-24","Eid Al Fitr* (*estimated)","BH",2031 +"2031-01-25","Eid Al Fitr Holiday* (*estimated)","BH",2031 +"2031-01-26","Eid Al Fitr Holiday* (*estimated)","BH",2031 +"2031-04-02","Eid Al Adha* (*estimated)","BH",2031 +"2031-04-03","Eid Al Adha Holiday* (*estimated)","BH",2031 +"2031-04-04","Eid Al Adha Holiday* (*estimated)","BH",2031 +"2031-04-23","Al Hijra New Year* (*estimated)","BH",2031 +"2031-05-01","Ashura Holiday* (*estimated)","BH",2031 +"2031-05-01","Labour Day","BH",2031 +"2031-05-02","Ashura* (*estimated)","BH",2031 +"2031-07-02","Prophets Birthday* (*estimated)","BH",2031 +"2031-12-16","National Day","BH",2031 +"2031-12-17","National Day","BH",2031 +"2032-01-01","New Year's Day","BH",2032 +"2032-01-14","Eid Al Fitr* (*estimated)","BH",2032 +"2032-01-15","Eid Al Fitr Holiday* (*estimated)","BH",2032 +"2032-01-16","Eid Al Fitr Holiday* (*estimated)","BH",2032 +"2032-03-22","Eid Al Adha* (*estimated)","BH",2032 +"2032-03-23","Eid Al Adha Holiday* (*estimated)","BH",2032 +"2032-03-24","Eid Al Adha Holiday* (*estimated)","BH",2032 +"2032-04-11","Al Hijra New Year* (*estimated)","BH",2032 +"2032-04-19","Ashura Holiday* (*estimated)","BH",2032 +"2032-04-20","Ashura* (*estimated)","BH",2032 +"2032-05-01","Labour Day","BH",2032 +"2032-06-20","Prophets Birthday* (*estimated)","BH",2032 +"2032-12-16","National Day","BH",2032 +"2032-12-17","National Day","BH",2032 +"2033-01-01","New Year's Day","BH",2033 +"2033-01-02","Eid Al Fitr* (*estimated)","BH",2033 +"2033-01-03","Eid Al Fitr Holiday* (*estimated)","BH",2033 +"2033-01-04","Eid Al Fitr Holiday* (*estimated)","BH",2033 +"2033-03-11","Eid Al Adha* (*estimated)","BH",2033 +"2033-03-12","Eid Al Adha Holiday* (*estimated)","BH",2033 +"2033-03-13","Eid Al Adha Holiday* (*estimated)","BH",2033 +"2033-04-01","Al Hijra New Year* (*estimated)","BH",2033 +"2033-04-09","Ashura Holiday* (*estimated)","BH",2033 +"2033-04-10","Ashura* (*estimated)","BH",2033 +"2033-05-01","Labour Day","BH",2033 +"2033-06-09","Prophets Birthday* (*estimated)","BH",2033 +"2033-12-16","National Day","BH",2033 +"2033-12-17","National Day","BH",2033 +"2033-12-23","Eid Al Fitr* (*estimated)","BH",2033 +"2033-12-24","Eid Al Fitr Holiday* (*estimated)","BH",2033 +"2033-12-25","Eid Al Fitr Holiday* (*estimated)","BH",2033 +"2034-01-01","New Year's Day","BH",2034 +"2034-03-01","Eid Al Adha* (*estimated)","BH",2034 +"2034-03-02","Eid Al Adha Holiday* (*estimated)","BH",2034 +"2034-03-03","Eid Al Adha Holiday* (*estimated)","BH",2034 +"2034-03-21","Al Hijra New Year* (*estimated)","BH",2034 +"2034-03-29","Ashura Holiday* (*estimated)","BH",2034 +"2034-03-30","Ashura* (*estimated)","BH",2034 +"2034-05-01","Labour Day","BH",2034 +"2034-05-30","Prophets Birthday* (*estimated)","BH",2034 +"2034-12-12","Eid Al Fitr* (*estimated)","BH",2034 +"2034-12-13","Eid Al Fitr Holiday* (*estimated)","BH",2034 +"2034-12-14","Eid Al Fitr Holiday* (*estimated)","BH",2034 +"2034-12-16","National Day","BH",2034 +"2034-12-17","National Day","BH",2034 +"2035-01-01","New Year's Day","BH",2035 +"2035-02-18","Eid Al Adha* (*estimated)","BH",2035 +"2035-02-19","Eid Al Adha Holiday* (*estimated)","BH",2035 +"2035-02-20","Eid Al Adha Holiday* (*estimated)","BH",2035 +"2035-03-11","Al Hijra New Year* (*estimated)","BH",2035 +"2035-03-19","Ashura Holiday* (*estimated)","BH",2035 +"2035-03-20","Ashura* (*estimated)","BH",2035 +"2035-05-01","Labour Day","BH",2035 +"2035-05-20","Prophets Birthday* (*estimated)","BH",2035 +"2035-12-01","Eid Al Fitr* (*estimated)","BH",2035 +"2035-12-02","Eid Al Fitr Holiday* (*estimated)","BH",2035 +"2035-12-03","Eid Al Fitr Holiday* (*estimated)","BH",2035 +"2035-12-16","National Day","BH",2035 +"2035-12-17","National Day","BH",2035 +"2036-01-01","New Year's Day","BH",2036 +"2036-02-07","Eid Al Adha* (*estimated)","BH",2036 +"2036-02-08","Eid Al Adha Holiday* (*estimated)","BH",2036 +"2036-02-09","Eid Al Adha Holiday* (*estimated)","BH",2036 +"2036-02-28","Al Hijra New Year* (*estimated)","BH",2036 +"2036-03-07","Ashura Holiday* (*estimated)","BH",2036 +"2036-03-08","Ashura* (*estimated)","BH",2036 +"2036-05-01","Labour Day","BH",2036 +"2036-05-08","Prophets Birthday* (*estimated)","BH",2036 +"2036-11-19","Eid Al Fitr* (*estimated)","BH",2036 +"2036-11-20","Eid Al Fitr Holiday* (*estimated)","BH",2036 +"2036-11-21","Eid Al Fitr Holiday* (*estimated)","BH",2036 +"2036-12-16","National Day","BH",2036 +"2036-12-17","National Day","BH",2036 +"2037-01-01","New Year's Day","BH",2037 +"2037-01-26","Eid Al Adha* (*estimated)","BH",2037 +"2037-01-27","Eid Al Adha Holiday* (*estimated)","BH",2037 +"2037-01-28","Eid Al Adha Holiday* (*estimated)","BH",2037 +"2037-02-16","Al Hijra New Year* (*estimated)","BH",2037 +"2037-02-24","Ashura Holiday* (*estimated)","BH",2037 +"2037-02-25","Ashura* (*estimated)","BH",2037 +"2037-04-28","Prophets Birthday* (*estimated)","BH",2037 +"2037-05-01","Labour Day","BH",2037 +"2037-11-08","Eid Al Fitr* (*estimated)","BH",2037 +"2037-11-09","Eid Al Fitr Holiday* (*estimated)","BH",2037 +"2037-11-10","Eid Al Fitr Holiday* (*estimated)","BH",2037 +"2037-12-16","National Day","BH",2037 +"2037-12-17","National Day","BH",2037 +"2038-01-01","New Year's Day","BH",2038 +"2038-01-16","Eid Al Adha* (*estimated)","BH",2038 +"2038-01-17","Eid Al Adha Holiday* (*estimated)","BH",2038 +"2038-01-18","Eid Al Adha Holiday* (*estimated)","BH",2038 +"2038-02-05","Al Hijra New Year* (*estimated)","BH",2038 +"2038-02-13","Ashura Holiday* (*estimated)","BH",2038 +"2038-02-14","Ashura* (*estimated)","BH",2038 +"2038-04-17","Prophets Birthday* (*estimated)","BH",2038 +"2038-05-01","Labour Day","BH",2038 +"2038-10-29","Eid Al Fitr* (*estimated)","BH",2038 +"2038-10-30","Eid Al Fitr Holiday* (*estimated)","BH",2038 +"2038-10-31","Eid Al Fitr Holiday* (*estimated)","BH",2038 +"2038-12-16","National Day","BH",2038 +"2038-12-17","National Day","BH",2038 +"2039-01-01","New Year's Day","BH",2039 +"2039-01-05","Eid Al Adha* (*estimated)","BH",2039 +"2039-01-06","Eid Al Adha Holiday* (*estimated)","BH",2039 +"2039-01-07","Eid Al Adha Holiday* (*estimated)","BH",2039 +"2039-01-26","Al Hijra New Year* (*estimated)","BH",2039 +"2039-02-03","Ashura Holiday* (*estimated)","BH",2039 +"2039-02-04","Ashura* (*estimated)","BH",2039 +"2039-04-06","Prophets Birthday* (*estimated)","BH",2039 +"2039-05-01","Labour Day","BH",2039 +"2039-10-19","Eid Al Fitr* (*estimated)","BH",2039 +"2039-10-20","Eid Al Fitr Holiday* (*estimated)","BH",2039 +"2039-10-21","Eid Al Fitr Holiday* (*estimated)","BH",2039 +"2039-12-16","National Day","BH",2039 +"2039-12-17","National Day","BH",2039 +"2039-12-26","Eid Al Adha* (*estimated)","BH",2039 +"2039-12-27","Eid Al Adha Holiday* (*estimated)","BH",2039 +"2039-12-28","Eid Al Adha Holiday* (*estimated)","BH",2039 +"2040-01-01","New Year's Day","BH",2040 +"2040-01-15","Al Hijra New Year* (*estimated)","BH",2040 +"2040-01-23","Ashura Holiday* (*estimated)","BH",2040 +"2040-01-24","Ashura* (*estimated)","BH",2040 +"2040-03-25","Prophets Birthday* (*estimated)","BH",2040 +"2040-05-01","Labour Day","BH",2040 +"2040-10-07","Eid Al Fitr* (*estimated)","BH",2040 +"2040-10-08","Eid Al Fitr Holiday* (*estimated)","BH",2040 +"2040-10-09","Eid Al Fitr Holiday* (*estimated)","BH",2040 +"2040-12-14","Eid Al Adha* (*estimated)","BH",2040 +"2040-12-15","Eid Al Adha Holiday* (*estimated)","BH",2040 +"2040-12-16","Eid Al Adha Holiday* (*estimated)","BH",2040 +"2040-12-16","National Day","BH",2040 +"2040-12-17","National Day","BH",2040 +"2041-01-01","New Year's Day","BH",2041 +"2041-01-04","Al Hijra New Year* (*estimated)","BH",2041 +"2041-01-12","Ashura Holiday* (*estimated)","BH",2041 +"2041-01-13","Ashura* (*estimated)","BH",2041 +"2041-03-15","Prophets Birthday* (*estimated)","BH",2041 +"2041-05-01","Labour Day","BH",2041 +"2041-09-26","Eid Al Fitr* (*estimated)","BH",2041 +"2041-09-27","Eid Al Fitr Holiday* (*estimated)","BH",2041 +"2041-09-28","Eid Al Fitr Holiday* (*estimated)","BH",2041 +"2041-12-04","Eid Al Adha* (*estimated)","BH",2041 +"2041-12-05","Eid Al Adha Holiday* (*estimated)","BH",2041 +"2041-12-06","Eid Al Adha Holiday* (*estimated)","BH",2041 +"2041-12-16","National Day","BH",2041 +"2041-12-17","National Day","BH",2041 +"2041-12-24","Al Hijra New Year* (*estimated)","BH",2041 +"2042-01-01","Ashura Holiday* (*estimated)","BH",2042 +"2042-01-01","New Year's Day","BH",2042 +"2042-01-02","Ashura* (*estimated)","BH",2042 +"2042-03-04","Prophets Birthday* (*estimated)","BH",2042 +"2042-05-01","Labour Day","BH",2042 +"2042-09-15","Eid Al Fitr* (*estimated)","BH",2042 +"2042-09-16","Eid Al Fitr Holiday* (*estimated)","BH",2042 +"2042-09-17","Eid Al Fitr Holiday* (*estimated)","BH",2042 +"2042-11-23","Eid Al Adha* (*estimated)","BH",2042 +"2042-11-24","Eid Al Adha Holiday* (*estimated)","BH",2042 +"2042-11-25","Eid Al Adha Holiday* (*estimated)","BH",2042 +"2042-12-14","Al Hijra New Year* (*estimated)","BH",2042 +"2042-12-16","National Day","BH",2042 +"2042-12-17","National Day","BH",2042 +"2042-12-22","Ashura Holiday* (*estimated)","BH",2042 +"2042-12-23","Ashura* (*estimated)","BH",2042 +"2043-01-01","New Year's Day","BH",2043 +"2043-02-22","Prophets Birthday* (*estimated)","BH",2043 +"2043-05-01","Labour Day","BH",2043 +"2043-09-04","Eid Al Fitr* (*estimated)","BH",2043 +"2043-09-05","Eid Al Fitr Holiday* (*estimated)","BH",2043 +"2043-09-06","Eid Al Fitr Holiday* (*estimated)","BH",2043 +"2043-11-12","Eid Al Adha* (*estimated)","BH",2043 +"2043-11-13","Eid Al Adha Holiday* (*estimated)","BH",2043 +"2043-11-14","Eid Al Adha Holiday* (*estimated)","BH",2043 +"2043-12-03","Al Hijra New Year* (*estimated)","BH",2043 +"2043-12-11","Ashura Holiday* (*estimated)","BH",2043 +"2043-12-12","Ashura* (*estimated)","BH",2043 +"2043-12-16","National Day","BH",2043 +"2043-12-17","National Day","BH",2043 +"2044-01-01","New Year's Day","BH",2044 +"2044-02-11","Prophets Birthday* (*estimated)","BH",2044 +"2044-05-01","Labour Day","BH",2044 +"2044-08-24","Eid Al Fitr* (*estimated)","BH",2044 +"2044-08-25","Eid Al Fitr Holiday* (*estimated)","BH",2044 +"2044-08-26","Eid Al Fitr Holiday* (*estimated)","BH",2044 +"2044-10-31","Eid Al Adha* (*estimated)","BH",2044 +"2044-11-01","Eid Al Adha Holiday* (*estimated)","BH",2044 +"2044-11-02","Eid Al Adha Holiday* (*estimated)","BH",2044 +"2044-11-21","Al Hijra New Year* (*estimated)","BH",2044 +"2044-11-29","Ashura Holiday* (*estimated)","BH",2044 +"2044-11-30","Ashura* (*estimated)","BH",2044 +"2044-12-16","National Day","BH",2044 +"2044-12-17","National Day","BH",2044 +"1995-01-01","New Year's Day","BI",1995 +"1995-01-02","New Year's Day (Observed)","BI",1995 +"1995-02-05","Unity Day","BI",1995 +"1995-02-06","Unity Day (Observed)","BI",1995 +"1995-03-02","Eid ul Fitr* (*estimated)","BI",1995 +"1995-04-06","President Ntaryamira Day","BI",1995 +"1995-05-01","Labour Day","BI",1995 +"1995-05-09","Eid al Adha* (*estimated)","BI",1995 +"1995-05-25","Ascension Day","BI",1995 +"1995-07-01","Independence Day","BI",1995 +"1995-08-15","Assumption Day","BI",1995 +"1995-10-13","Prince Louis Rwagasore Day","BI",1995 +"1995-10-21","President Ndadaye's Day","BI",1995 +"1995-11-01","All Saints' Day","BI",1995 +"1995-12-25","Christmas Day","BI",1995 +"1996-01-01","New Year's Day","BI",1996 +"1996-02-05","Unity Day","BI",1996 +"1996-02-19","Eid ul Fitr* (*estimated)","BI",1996 +"1996-04-06","President Ntaryamira Day","BI",1996 +"1996-04-27","Eid al Adha* (*estimated)","BI",1996 +"1996-05-01","Labour Day","BI",1996 +"1996-05-16","Ascension Day","BI",1996 +"1996-07-01","Independence Day","BI",1996 +"1996-08-15","Assumption Day","BI",1996 +"1996-10-13","Prince Louis Rwagasore Day","BI",1996 +"1996-10-14","Prince Louis Rwagasore Day (Observed)","BI",1996 +"1996-10-21","President Ndadaye's Day","BI",1996 +"1996-11-01","All Saints' Day","BI",1996 +"1996-12-25","Christmas Day","BI",1996 +"1997-01-01","New Year's Day","BI",1997 +"1997-02-05","Unity Day","BI",1997 +"1997-02-08","Eid ul Fitr* (*estimated)","BI",1997 +"1997-04-06","President Ntaryamira Day","BI",1997 +"1997-04-07","President Ntaryamira Day (Observed)","BI",1997 +"1997-04-17","Eid al Adha* (*estimated)","BI",1997 +"1997-05-01","Labour Day","BI",1997 +"1997-05-08","Ascension Day","BI",1997 +"1997-07-01","Independence Day","BI",1997 +"1997-08-15","Assumption Day","BI",1997 +"1997-10-13","Prince Louis Rwagasore Day","BI",1997 +"1997-10-21","President Ndadaye's Day","BI",1997 +"1997-11-01","All Saints' Day","BI",1997 +"1997-12-25","Christmas Day","BI",1997 +"1998-01-01","New Year's Day","BI",1998 +"1998-01-29","Eid ul Fitr* (*estimated)","BI",1998 +"1998-02-05","Unity Day","BI",1998 +"1998-04-06","President Ntaryamira Day","BI",1998 +"1998-04-07","Eid al Adha* (*estimated)","BI",1998 +"1998-05-01","Labour Day","BI",1998 +"1998-05-21","Ascension Day","BI",1998 +"1998-07-01","Independence Day","BI",1998 +"1998-08-15","Assumption Day","BI",1998 +"1998-10-13","Prince Louis Rwagasore Day","BI",1998 +"1998-10-21","President Ndadaye's Day","BI",1998 +"1998-11-01","All Saints' Day","BI",1998 +"1998-11-02","All Saints' Day (Observed)","BI",1998 +"1998-12-25","Christmas Day","BI",1998 +"1999-01-01","New Year's Day","BI",1999 +"1999-01-18","Eid ul Fitr* (*estimated)","BI",1999 +"1999-02-05","Unity Day","BI",1999 +"1999-03-27","Eid al Adha* (*estimated)","BI",1999 +"1999-04-06","President Ntaryamira Day","BI",1999 +"1999-05-01","Labour Day","BI",1999 +"1999-05-13","Ascension Day","BI",1999 +"1999-07-01","Independence Day","BI",1999 +"1999-08-15","Assumption Day","BI",1999 +"1999-08-16","Assumption Day (Observed)","BI",1999 +"1999-10-13","Prince Louis Rwagasore Day","BI",1999 +"1999-10-21","President Ndadaye's Day","BI",1999 +"1999-11-01","All Saints' Day","BI",1999 +"1999-12-25","Christmas Day","BI",1999 +"2000-01-01","New Year's Day","BI",2000 +"2000-01-08","Eid ul Fitr* (*estimated)","BI",2000 +"2000-02-05","Unity Day","BI",2000 +"2000-03-16","Eid al Adha* (*estimated)","BI",2000 +"2000-04-06","President Ntaryamira Day","BI",2000 +"2000-05-01","Labour Day","BI",2000 +"2000-06-01","Ascension Day","BI",2000 +"2000-07-01","Independence Day","BI",2000 +"2000-08-15","Assumption Day","BI",2000 +"2000-10-13","Prince Louis Rwagasore Day","BI",2000 +"2000-10-21","President Ndadaye's Day","BI",2000 +"2000-11-01","All Saints' Day","BI",2000 +"2000-12-25","Christmas Day","BI",2000 +"2000-12-27","Eid ul Fitr* (*estimated)","BI",2000 +"2001-01-01","New Year's Day","BI",2001 +"2001-02-05","Unity Day","BI",2001 +"2001-03-05","Eid al Adha* (*estimated)","BI",2001 +"2001-04-06","President Ntaryamira Day","BI",2001 +"2001-05-01","Labour Day","BI",2001 +"2001-05-24","Ascension Day","BI",2001 +"2001-07-01","Independence Day","BI",2001 +"2001-07-02","Independence Day (Observed)","BI",2001 +"2001-08-15","Assumption Day","BI",2001 +"2001-10-13","Prince Louis Rwagasore Day","BI",2001 +"2001-10-21","President Ndadaye's Day","BI",2001 +"2001-10-22","President Ndadaye's Day (Observed)","BI",2001 +"2001-11-01","All Saints' Day","BI",2001 +"2001-12-16","Eid ul Fitr* (*estimated)","BI",2001 +"2001-12-17","Eid ul Fitr* (*estimated) (Observed)","BI",2001 +"2001-12-25","Christmas Day","BI",2001 +"2002-01-01","New Year's Day","BI",2002 +"2002-02-05","Unity Day","BI",2002 +"2002-02-22","Eid al Adha* (*estimated)","BI",2002 +"2002-04-06","President Ntaryamira Day","BI",2002 +"2002-05-01","Labour Day","BI",2002 +"2002-05-09","Ascension Day","BI",2002 +"2002-07-01","Independence Day","BI",2002 +"2002-08-15","Assumption Day","BI",2002 +"2002-10-13","Prince Louis Rwagasore Day","BI",2002 +"2002-10-14","Prince Louis Rwagasore Day (Observed)","BI",2002 +"2002-10-21","President Ndadaye's Day","BI",2002 +"2002-11-01","All Saints' Day","BI",2002 +"2002-12-05","Eid ul Fitr* (*estimated)","BI",2002 +"2002-12-25","Christmas Day","BI",2002 +"2003-01-01","New Year's Day","BI",2003 +"2003-02-05","Unity Day","BI",2003 +"2003-02-11","Eid al Adha* (*estimated)","BI",2003 +"2003-04-06","President Ntaryamira Day","BI",2003 +"2003-04-07","President Ntaryamira Day (Observed)","BI",2003 +"2003-05-01","Labour Day","BI",2003 +"2003-05-29","Ascension Day","BI",2003 +"2003-07-01","Independence Day","BI",2003 +"2003-08-15","Assumption Day","BI",2003 +"2003-10-13","Prince Louis Rwagasore Day","BI",2003 +"2003-10-21","President Ndadaye's Day","BI",2003 +"2003-11-01","All Saints' Day","BI",2003 +"2003-11-25","Eid ul Fitr* (*estimated)","BI",2003 +"2003-12-25","Christmas Day","BI",2003 +"2004-01-01","New Year's Day","BI",2004 +"2004-02-01","Eid al Adha* (*estimated)","BI",2004 +"2004-02-02","Eid al Adha* (*estimated) (Observed)","BI",2004 +"2004-02-05","Unity Day","BI",2004 +"2004-04-06","President Ntaryamira Day","BI",2004 +"2004-05-01","Labour Day","BI",2004 +"2004-05-20","Ascension Day","BI",2004 +"2004-07-01","Independence Day","BI",2004 +"2004-08-15","Assumption Day","BI",2004 +"2004-08-16","Assumption Day (Observed)","BI",2004 +"2004-10-13","Prince Louis Rwagasore Day","BI",2004 +"2004-10-21","President Ndadaye's Day","BI",2004 +"2004-11-01","All Saints' Day","BI",2004 +"2004-11-14","Eid ul Fitr* (*estimated)","BI",2004 +"2004-11-15","Eid ul Fitr* (*estimated) (Observed)","BI",2004 +"2004-12-25","Christmas Day","BI",2004 +"2005-01-01","New Year's Day","BI",2005 +"2005-01-21","Eid al Adha* (*estimated)","BI",2005 +"2005-02-05","Unity Day","BI",2005 +"2005-04-06","President Ntaryamira Day","BI",2005 +"2005-05-01","Labour Day","BI",2005 +"2005-05-02","Labour Day (Observed)","BI",2005 +"2005-05-05","Ascension Day","BI",2005 +"2005-07-01","Independence Day","BI",2005 +"2005-08-15","Assumption Day","BI",2005 +"2005-10-13","Prince Louis Rwagasore Day","BI",2005 +"2005-10-21","President Ndadaye's Day","BI",2005 +"2005-11-01","All Saints' Day","BI",2005 +"2005-11-03","Eid ul Fitr* (*estimated)","BI",2005 +"2005-12-25","Christmas Day","BI",2005 +"2005-12-26","Christmas Day (Observed)","BI",2005 +"2006-01-01","New Year's Day","BI",2006 +"2006-01-02","New Year's Day (Observed)","BI",2006 +"2006-01-10","Eid al Adha* (*estimated)","BI",2006 +"2006-02-05","Unity Day","BI",2006 +"2006-02-06","Unity Day (Observed)","BI",2006 +"2006-04-06","President Ntaryamira Day","BI",2006 +"2006-05-01","Labour Day","BI",2006 +"2006-05-25","Ascension Day","BI",2006 +"2006-07-01","Independence Day","BI",2006 +"2006-08-15","Assumption Day","BI",2006 +"2006-10-13","Prince Louis Rwagasore Day","BI",2006 +"2006-10-21","President Ndadaye's Day","BI",2006 +"2006-10-23","Eid ul Fitr* (*estimated)","BI",2006 +"2006-11-01","All Saints' Day","BI",2006 +"2006-12-25","Christmas Day","BI",2006 +"2006-12-31","Eid al Adha* (*estimated)","BI",2006 +"2007-01-01","New Year's Day","BI",2007 +"2007-02-05","Unity Day","BI",2007 +"2007-04-06","President Ntaryamira Day","BI",2007 +"2007-05-01","Labour Day","BI",2007 +"2007-05-17","Ascension Day","BI",2007 +"2007-07-01","Independence Day","BI",2007 +"2007-07-02","Independence Day (Observed)","BI",2007 +"2007-08-15","Assumption Day","BI",2007 +"2007-10-13","Eid ul Fitr* (*estimated)","BI",2007 +"2007-10-13","Prince Louis Rwagasore Day","BI",2007 +"2007-10-21","President Ndadaye's Day","BI",2007 +"2007-10-22","President Ndadaye's Day (Observed)","BI",2007 +"2007-11-01","All Saints' Day","BI",2007 +"2007-12-20","Eid al Adha* (*estimated)","BI",2007 +"2007-12-25","Christmas Day","BI",2007 +"2008-01-01","New Year's Day","BI",2008 +"2008-02-05","Unity Day","BI",2008 +"2008-04-06","President Ntaryamira Day","BI",2008 +"2008-04-07","President Ntaryamira Day (Observed)","BI",2008 +"2008-05-01","Ascension Day","BI",2008 +"2008-05-01","Labour Day","BI",2008 +"2008-07-01","Independence Day","BI",2008 +"2008-08-15","Assumption Day","BI",2008 +"2008-10-01","Eid ul Fitr* (*estimated)","BI",2008 +"2008-10-13","Prince Louis Rwagasore Day","BI",2008 +"2008-10-21","President Ndadaye's Day","BI",2008 +"2008-11-01","All Saints' Day","BI",2008 +"2008-12-08","Eid al Adha* (*estimated)","BI",2008 +"2008-12-25","Christmas Day","BI",2008 +"2009-01-01","New Year's Day","BI",2009 +"2009-02-05","Unity Day","BI",2009 +"2009-04-06","President Ntaryamira Day","BI",2009 +"2009-05-01","Labour Day","BI",2009 +"2009-05-21","Ascension Day","BI",2009 +"2009-07-01","Independence Day","BI",2009 +"2009-08-15","Assumption Day","BI",2009 +"2009-09-20","Eid ul Fitr* (*estimated)","BI",2009 +"2009-09-21","Eid ul Fitr* (*estimated) (Observed)","BI",2009 +"2009-10-13","Prince Louis Rwagasore Day","BI",2009 +"2009-10-21","President Ndadaye's Day","BI",2009 +"2009-11-01","All Saints' Day","BI",2009 +"2009-11-02","All Saints' Day (Observed)","BI",2009 +"2009-11-27","Eid al Adha* (*estimated)","BI",2009 +"2009-12-25","Christmas Day","BI",2009 +"2010-01-01","New Year's Day","BI",2010 +"2010-02-05","Unity Day","BI",2010 +"2010-04-06","President Ntaryamira Day","BI",2010 +"2010-05-01","Labour Day","BI",2010 +"2010-05-13","Ascension Day","BI",2010 +"2010-07-01","Independence Day","BI",2010 +"2010-08-15","Assumption Day","BI",2010 +"2010-08-16","Assumption Day (Observed)","BI",2010 +"2010-09-10","Eid ul Fitr* (*estimated)","BI",2010 +"2010-10-13","Prince Louis Rwagasore Day","BI",2010 +"2010-10-21","President Ndadaye's Day","BI",2010 +"2010-11-01","All Saints' Day","BI",2010 +"2010-11-16","Eid al Adha* (*estimated)","BI",2010 +"2010-12-25","Christmas Day","BI",2010 +"2011-01-01","New Year's Day","BI",2011 +"2011-02-05","Unity Day","BI",2011 +"2011-04-06","President Ntaryamira Day","BI",2011 +"2011-05-01","Labour Day","BI",2011 +"2011-05-02","Labour Day (Observed)","BI",2011 +"2011-06-02","Ascension Day","BI",2011 +"2011-07-01","Independence Day","BI",2011 +"2011-08-15","Assumption Day","BI",2011 +"2011-08-30","Eid ul Fitr* (*estimated)","BI",2011 +"2011-10-13","Prince Louis Rwagasore Day","BI",2011 +"2011-10-21","President Ndadaye's Day","BI",2011 +"2011-11-01","All Saints' Day","BI",2011 +"2011-11-06","Eid al Adha* (*estimated)","BI",2011 +"2011-11-07","Eid al Adha* (*estimated) (Observed)","BI",2011 +"2011-12-25","Christmas Day","BI",2011 +"2011-12-26","Christmas Day (Observed)","BI",2011 +"2012-01-01","New Year's Day","BI",2012 +"2012-01-02","New Year's Day (Observed)","BI",2012 +"2012-02-05","Unity Day","BI",2012 +"2012-02-06","Unity Day (Observed)","BI",2012 +"2012-04-06","President Ntaryamira Day","BI",2012 +"2012-05-01","Labour Day","BI",2012 +"2012-05-17","Ascension Day","BI",2012 +"2012-07-01","Independence Day","BI",2012 +"2012-07-02","Independence Day (Observed)","BI",2012 +"2012-08-15","Assumption Day","BI",2012 +"2012-08-19","Eid ul Fitr* (*estimated)","BI",2012 +"2012-08-20","Eid ul Fitr* (*estimated) (Observed)","BI",2012 +"2012-10-13","Prince Louis Rwagasore Day","BI",2012 +"2012-10-21","President Ndadaye's Day","BI",2012 +"2012-10-22","President Ndadaye's Day (Observed)","BI",2012 +"2012-10-26","Eid al Adha* (*estimated)","BI",2012 +"2012-11-01","All Saints' Day","BI",2012 +"2012-12-25","Christmas Day","BI",2012 +"2013-01-01","New Year's Day","BI",2013 +"2013-02-05","Unity Day","BI",2013 +"2013-04-06","President Ntaryamira Day","BI",2013 +"2013-05-01","Labour Day","BI",2013 +"2013-05-09","Ascension Day","BI",2013 +"2013-07-01","Independence Day","BI",2013 +"2013-08-08","Eid ul Fitr* (*estimated)","BI",2013 +"2013-08-15","Assumption Day","BI",2013 +"2013-10-13","Prince Louis Rwagasore Day","BI",2013 +"2013-10-14","Prince Louis Rwagasore Day (Observed)","BI",2013 +"2013-10-15","Eid al Adha* (*estimated)","BI",2013 +"2013-10-21","President Ndadaye's Day","BI",2013 +"2013-11-01","All Saints' Day","BI",2013 +"2013-12-25","Christmas Day","BI",2013 +"2014-01-01","New Year's Day","BI",2014 +"2014-02-05","Unity Day","BI",2014 +"2014-04-06","President Ntaryamira Day","BI",2014 +"2014-04-07","President Ntaryamira Day (Observed)","BI",2014 +"2014-05-01","Labour Day","BI",2014 +"2014-05-29","Ascension Day","BI",2014 +"2014-07-01","Independence Day","BI",2014 +"2014-07-28","Eid ul Fitr* (*estimated)","BI",2014 +"2014-08-15","Assumption Day","BI",2014 +"2014-10-04","Eid al Adha* (*estimated)","BI",2014 +"2014-10-13","Prince Louis Rwagasore Day","BI",2014 +"2014-10-21","President Ndadaye's Day","BI",2014 +"2014-11-01","All Saints' Day","BI",2014 +"2014-12-25","Christmas Day","BI",2014 +"2015-01-01","New Year's Day","BI",2015 +"2015-02-05","Unity Day","BI",2015 +"2015-04-06","President Ntaryamira Day","BI",2015 +"2015-05-01","Labour Day","BI",2015 +"2015-05-14","Ascension Day","BI",2015 +"2015-07-01","Independence Day","BI",2015 +"2015-07-17","Eid ul Fitr* (*estimated)","BI",2015 +"2015-08-15","Assumption Day","BI",2015 +"2015-09-23","Eid al Adha* (*estimated)","BI",2015 +"2015-10-13","Prince Louis Rwagasore Day","BI",2015 +"2015-10-21","President Ndadaye's Day","BI",2015 +"2015-11-01","All Saints' Day","BI",2015 +"2015-11-02","All Saints' Day (Observed)","BI",2015 +"2015-12-25","Christmas Day","BI",2015 +"2016-01-01","New Year's Day","BI",2016 +"2016-02-05","Unity Day","BI",2016 +"2016-04-06","President Ntaryamira Day","BI",2016 +"2016-05-01","Labour Day","BI",2016 +"2016-05-02","Labour Day (Observed)","BI",2016 +"2016-05-05","Ascension Day","BI",2016 +"2016-07-01","Independence Day","BI",2016 +"2016-07-06","Eid ul Fitr* (*estimated)","BI",2016 +"2016-08-15","Assumption Day","BI",2016 +"2016-09-11","Eid al Adha* (*estimated)","BI",2016 +"2016-09-12","Eid al Adha* (*estimated) (Observed)","BI",2016 +"2016-10-13","Prince Louis Rwagasore Day","BI",2016 +"2016-10-21","President Ndadaye's Day","BI",2016 +"2016-11-01","All Saints' Day","BI",2016 +"2016-12-25","Christmas Day","BI",2016 +"2016-12-26","Christmas Day (Observed)","BI",2016 +"2017-01-01","New Year's Day","BI",2017 +"2017-01-02","New Year's Day (Observed)","BI",2017 +"2017-02-05","Unity Day","BI",2017 +"2017-02-06","Unity Day (Observed)","BI",2017 +"2017-04-06","President Ntaryamira Day","BI",2017 +"2017-05-01","Labour Day","BI",2017 +"2017-05-25","Ascension Day","BI",2017 +"2017-06-25","Eid ul Fitr* (*estimated)","BI",2017 +"2017-06-26","Eid ul Fitr* (*estimated) (Observed)","BI",2017 +"2017-07-01","Independence Day","BI",2017 +"2017-08-15","Assumption Day","BI",2017 +"2017-09-01","Eid al Adha* (*estimated)","BI",2017 +"2017-10-13","Prince Louis Rwagasore Day","BI",2017 +"2017-10-21","President Ndadaye's Day","BI",2017 +"2017-11-01","All Saints' Day","BI",2017 +"2017-12-25","Christmas Day","BI",2017 +"2018-01-01","New Year's Day","BI",2018 +"2018-02-05","Unity Day","BI",2018 +"2018-04-06","President Ntaryamira Day","BI",2018 +"2018-05-01","Labour Day","BI",2018 +"2018-05-10","Ascension Day","BI",2018 +"2018-06-15","Eid ul Fitr* (*estimated)","BI",2018 +"2018-07-01","Independence Day","BI",2018 +"2018-07-02","Independence Day (Observed)","BI",2018 +"2018-08-15","Assumption Day","BI",2018 +"2018-08-21","Eid al Adha* (*estimated)","BI",2018 +"2018-10-13","Prince Louis Rwagasore Day","BI",2018 +"2018-10-21","President Ndadaye's Day","BI",2018 +"2018-10-22","President Ndadaye's Day (Observed)","BI",2018 +"2018-11-01","All Saints' Day","BI",2018 +"2018-12-25","Christmas Day","BI",2018 +"2019-01-01","New Year's Day","BI",2019 +"2019-02-05","Unity Day","BI",2019 +"2019-04-06","President Ntaryamira Day","BI",2019 +"2019-05-01","Labour Day","BI",2019 +"2019-05-30","Ascension Day","BI",2019 +"2019-06-04","Eid ul Fitr* (*estimated)","BI",2019 +"2019-07-01","Independence Day","BI",2019 +"2019-08-11","Eid al Adha* (*estimated)","BI",2019 +"2019-08-12","Eid al Adha* (*estimated) (Observed)","BI",2019 +"2019-08-15","Assumption Day","BI",2019 +"2019-10-13","Prince Louis Rwagasore Day","BI",2019 +"2019-10-14","Prince Louis Rwagasore Day (Observed)","BI",2019 +"2019-10-21","President Ndadaye's Day","BI",2019 +"2019-11-01","All Saints' Day","BI",2019 +"2019-12-25","Christmas Day","BI",2019 +"2020-01-01","New Year's Day","BI",2020 +"2020-02-05","Unity Day","BI",2020 +"2020-04-06","President Ntaryamira Day","BI",2020 +"2020-05-01","Labour Day","BI",2020 +"2020-05-21","Ascension Day","BI",2020 +"2020-05-24","Eid ul Fitr* (*estimated)","BI",2020 +"2020-05-25","Eid ul Fitr* (*estimated) (Observed)","BI",2020 +"2020-07-01","Independence Day","BI",2020 +"2020-07-31","Eid al Adha* (*estimated)","BI",2020 +"2020-08-15","Assumption Day","BI",2020 +"2020-10-13","Prince Louis Rwagasore Day","BI",2020 +"2020-10-21","President Ndadaye's Day","BI",2020 +"2020-11-01","All Saints' Day","BI",2020 +"2020-11-02","All Saints' Day (Observed)","BI",2020 +"2020-12-25","Christmas Day","BI",2020 +"2021-01-01","New Year's Day","BI",2021 +"2021-02-05","Unity Day","BI",2021 +"2021-04-06","President Ntaryamira Day","BI",2021 +"2021-05-01","Labour Day","BI",2021 +"2021-05-13","Ascension Day","BI",2021 +"2021-05-13","Eid ul Fitr* (*estimated)","BI",2021 +"2021-07-01","Independence Day","BI",2021 +"2021-07-20","Eid al Adha* (*estimated)","BI",2021 +"2021-08-15","Assumption Day","BI",2021 +"2021-08-16","Assumption Day (Observed)","BI",2021 +"2021-10-13","Prince Louis Rwagasore Day","BI",2021 +"2021-10-21","President Ndadaye's Day","BI",2021 +"2021-11-01","All Saints' Day","BI",2021 +"2021-12-25","Christmas Day","BI",2021 +"2022-01-01","New Year's Day","BI",2022 +"2022-02-05","Unity Day","BI",2022 +"2022-04-06","President Ntaryamira Day","BI",2022 +"2022-05-01","Labour Day","BI",2022 +"2022-05-02","Eid ul Fitr* (*estimated)","BI",2022 +"2022-05-02","Labour Day (Observed)","BI",2022 +"2022-05-26","Ascension Day","BI",2022 +"2022-06-08","President Nkurunziza Day","BI",2022 +"2022-07-01","Independence Day","BI",2022 +"2022-07-09","Eid al Adha* (*estimated)","BI",2022 +"2022-08-15","Assumption Day","BI",2022 +"2022-10-13","Prince Louis Rwagasore Day","BI",2022 +"2022-10-21","President Ndadaye's Day","BI",2022 +"2022-11-01","All Saints' Day","BI",2022 +"2022-12-25","Christmas Day","BI",2022 +"2022-12-26","Christmas Day (Observed)","BI",2022 +"2023-01-01","New Year's Day","BI",2023 +"2023-01-02","New Year's Day (Observed)","BI",2023 +"2023-02-05","Unity Day","BI",2023 +"2023-02-06","Unity Day (Observed)","BI",2023 +"2023-04-06","President Ntaryamira Day","BI",2023 +"2023-04-21","Eid ul Fitr* (*estimated)","BI",2023 +"2023-05-01","Labour Day","BI",2023 +"2023-05-18","Ascension Day","BI",2023 +"2023-06-08","President Nkurunziza Day","BI",2023 +"2023-06-28","Eid al Adha* (*estimated)","BI",2023 +"2023-07-01","Independence Day","BI",2023 +"2023-08-15","Assumption Day","BI",2023 +"2023-10-13","Prince Louis Rwagasore Day","BI",2023 +"2023-10-21","President Ndadaye's Day","BI",2023 +"2023-11-01","All Saints' Day","BI",2023 +"2023-12-25","Christmas Day","BI",2023 +"2024-01-01","New Year's Day","BI",2024 +"2024-02-05","Unity Day","BI",2024 +"2024-04-06","President Ntaryamira Day","BI",2024 +"2024-04-10","Eid ul Fitr* (*estimated)","BI",2024 +"2024-05-01","Labour Day","BI",2024 +"2024-05-09","Ascension Day","BI",2024 +"2024-06-08","President Nkurunziza Day","BI",2024 +"2024-06-16","Eid al Adha* (*estimated)","BI",2024 +"2024-06-17","Eid al Adha* (*estimated) (Observed)","BI",2024 +"2024-07-01","Independence Day","BI",2024 +"2024-08-15","Assumption Day","BI",2024 +"2024-10-13","Prince Louis Rwagasore Day","BI",2024 +"2024-10-14","Prince Louis Rwagasore Day (Observed)","BI",2024 +"2024-10-21","President Ndadaye's Day","BI",2024 +"2024-11-01","All Saints' Day","BI",2024 +"2024-12-25","Christmas Day","BI",2024 +"2025-01-01","New Year's Day","BI",2025 +"2025-02-05","Unity Day","BI",2025 +"2025-03-30","Eid ul Fitr* (*estimated)","BI",2025 +"2025-03-31","Eid ul Fitr* (*estimated) (Observed)","BI",2025 +"2025-04-06","President Ntaryamira Day","BI",2025 +"2025-04-07","President Ntaryamira Day (Observed)","BI",2025 +"2025-05-01","Labour Day","BI",2025 +"2025-05-29","Ascension Day","BI",2025 +"2025-06-06","Eid al Adha* (*estimated)","BI",2025 +"2025-06-08","President Nkurunziza Day","BI",2025 +"2025-06-09","President Nkurunziza Day (Observed)","BI",2025 +"2025-07-01","Independence Day","BI",2025 +"2025-08-15","Assumption Day","BI",2025 +"2025-10-13","Prince Louis Rwagasore Day","BI",2025 +"2025-10-21","President Ndadaye's Day","BI",2025 +"2025-11-01","All Saints' Day","BI",2025 +"2025-12-25","Christmas Day","BI",2025 +"2026-01-01","New Year's Day","BI",2026 +"2026-02-05","Unity Day","BI",2026 +"2026-03-20","Eid ul Fitr* (*estimated)","BI",2026 +"2026-04-06","President Ntaryamira Day","BI",2026 +"2026-05-01","Labour Day","BI",2026 +"2026-05-14","Ascension Day","BI",2026 +"2026-05-27","Eid al Adha* (*estimated)","BI",2026 +"2026-06-08","President Nkurunziza Day","BI",2026 +"2026-07-01","Independence Day","BI",2026 +"2026-08-15","Assumption Day","BI",2026 +"2026-10-13","Prince Louis Rwagasore Day","BI",2026 +"2026-10-21","President Ndadaye's Day","BI",2026 +"2026-11-01","All Saints' Day","BI",2026 +"2026-11-02","All Saints' Day (Observed)","BI",2026 +"2026-12-25","Christmas Day","BI",2026 +"2027-01-01","New Year's Day","BI",2027 +"2027-02-05","Unity Day","BI",2027 +"2027-03-09","Eid ul Fitr* (*estimated)","BI",2027 +"2027-04-06","President Ntaryamira Day","BI",2027 +"2027-05-01","Labour Day","BI",2027 +"2027-05-06","Ascension Day","BI",2027 +"2027-05-16","Eid al Adha* (*estimated)","BI",2027 +"2027-05-17","Eid al Adha* (*estimated) (Observed)","BI",2027 +"2027-06-08","President Nkurunziza Day","BI",2027 +"2027-07-01","Independence Day","BI",2027 +"2027-08-15","Assumption Day","BI",2027 +"2027-08-16","Assumption Day (Observed)","BI",2027 +"2027-10-13","Prince Louis Rwagasore Day","BI",2027 +"2027-10-21","President Ndadaye's Day","BI",2027 +"2027-11-01","All Saints' Day","BI",2027 +"2027-12-25","Christmas Day","BI",2027 +"2028-01-01","New Year's Day","BI",2028 +"2028-02-05","Unity Day","BI",2028 +"2028-02-26","Eid ul Fitr* (*estimated)","BI",2028 +"2028-04-06","President Ntaryamira Day","BI",2028 +"2028-05-01","Labour Day","BI",2028 +"2028-05-05","Eid al Adha* (*estimated)","BI",2028 +"2028-05-25","Ascension Day","BI",2028 +"2028-06-08","President Nkurunziza Day","BI",2028 +"2028-07-01","Independence Day","BI",2028 +"2028-08-15","Assumption Day","BI",2028 +"2028-10-13","Prince Louis Rwagasore Day","BI",2028 +"2028-10-21","President Ndadaye's Day","BI",2028 +"2028-11-01","All Saints' Day","BI",2028 +"2028-12-25","Christmas Day","BI",2028 +"2029-01-01","New Year's Day","BI",2029 +"2029-02-05","Unity Day","BI",2029 +"2029-02-14","Eid ul Fitr* (*estimated)","BI",2029 +"2029-04-06","President Ntaryamira Day","BI",2029 +"2029-04-24","Eid al Adha* (*estimated)","BI",2029 +"2029-05-01","Labour Day","BI",2029 +"2029-05-10","Ascension Day","BI",2029 +"2029-06-08","President Nkurunziza Day","BI",2029 +"2029-07-01","Independence Day","BI",2029 +"2029-07-02","Independence Day (Observed)","BI",2029 +"2029-08-15","Assumption Day","BI",2029 +"2029-10-13","Prince Louis Rwagasore Day","BI",2029 +"2029-10-21","President Ndadaye's Day","BI",2029 +"2029-10-22","President Ndadaye's Day (Observed)","BI",2029 +"2029-11-01","All Saints' Day","BI",2029 +"2029-12-25","Christmas Day","BI",2029 +"2030-01-01","New Year's Day","BI",2030 +"2030-02-04","Eid ul Fitr* (*estimated)","BI",2030 +"2030-02-05","Unity Day","BI",2030 +"2030-04-06","President Ntaryamira Day","BI",2030 +"2030-04-13","Eid al Adha* (*estimated)","BI",2030 +"2030-05-01","Labour Day","BI",2030 +"2030-05-30","Ascension Day","BI",2030 +"2030-06-08","President Nkurunziza Day","BI",2030 +"2030-07-01","Independence Day","BI",2030 +"2030-08-15","Assumption Day","BI",2030 +"2030-10-13","Prince Louis Rwagasore Day","BI",2030 +"2030-10-14","Prince Louis Rwagasore Day (Observed)","BI",2030 +"2030-10-21","President Ndadaye's Day","BI",2030 +"2030-11-01","All Saints' Day","BI",2030 +"2030-12-25","Christmas Day","BI",2030 +"2031-01-01","New Year's Day","BI",2031 +"2031-01-24","Eid ul Fitr* (*estimated)","BI",2031 +"2031-02-05","Unity Day","BI",2031 +"2031-04-02","Eid al Adha* (*estimated)","BI",2031 +"2031-04-06","President Ntaryamira Day","BI",2031 +"2031-04-07","President Ntaryamira Day (Observed)","BI",2031 +"2031-05-01","Labour Day","BI",2031 +"2031-05-22","Ascension Day","BI",2031 +"2031-06-08","President Nkurunziza Day","BI",2031 +"2031-06-09","President Nkurunziza Day (Observed)","BI",2031 +"2031-07-01","Independence Day","BI",2031 +"2031-08-15","Assumption Day","BI",2031 +"2031-10-13","Prince Louis Rwagasore Day","BI",2031 +"2031-10-21","President Ndadaye's Day","BI",2031 +"2031-11-01","All Saints' Day","BI",2031 +"2031-12-25","Christmas Day","BI",2031 +"2032-01-01","New Year's Day","BI",2032 +"2032-01-14","Eid ul Fitr* (*estimated)","BI",2032 +"2032-02-05","Unity Day","BI",2032 +"2032-03-22","Eid al Adha* (*estimated)","BI",2032 +"2032-04-06","President Ntaryamira Day","BI",2032 +"2032-05-01","Labour Day","BI",2032 +"2032-05-06","Ascension Day","BI",2032 +"2032-06-08","President Nkurunziza Day","BI",2032 +"2032-07-01","Independence Day","BI",2032 +"2032-08-15","Assumption Day","BI",2032 +"2032-08-16","Assumption Day (Observed)","BI",2032 +"2032-10-13","Prince Louis Rwagasore Day","BI",2032 +"2032-10-21","President Ndadaye's Day","BI",2032 +"2032-11-01","All Saints' Day","BI",2032 +"2032-12-25","Christmas Day","BI",2032 +"2033-01-01","New Year's Day","BI",2033 +"2033-01-02","Eid ul Fitr* (*estimated)","BI",2033 +"2033-01-03","Eid ul Fitr* (*estimated) (Observed)","BI",2033 +"2033-02-05","Unity Day","BI",2033 +"2033-03-11","Eid al Adha* (*estimated)","BI",2033 +"2033-04-06","President Ntaryamira Day","BI",2033 +"2033-05-01","Labour Day","BI",2033 +"2033-05-02","Labour Day (Observed)","BI",2033 +"2033-05-26","Ascension Day","BI",2033 +"2033-06-08","President Nkurunziza Day","BI",2033 +"2033-07-01","Independence Day","BI",2033 +"2033-08-15","Assumption Day","BI",2033 +"2033-10-13","Prince Louis Rwagasore Day","BI",2033 +"2033-10-21","President Ndadaye's Day","BI",2033 +"2033-11-01","All Saints' Day","BI",2033 +"2033-12-23","Eid ul Fitr* (*estimated)","BI",2033 +"2033-12-25","Christmas Day","BI",2033 +"2033-12-26","Christmas Day (Observed)","BI",2033 +"2034-01-01","New Year's Day","BI",2034 +"2034-01-02","New Year's Day (Observed)","BI",2034 +"2034-02-05","Unity Day","BI",2034 +"2034-02-06","Unity Day (Observed)","BI",2034 +"2034-03-01","Eid al Adha* (*estimated)","BI",2034 +"2034-04-06","President Ntaryamira Day","BI",2034 +"2034-05-01","Labour Day","BI",2034 +"2034-05-18","Ascension Day","BI",2034 +"2034-06-08","President Nkurunziza Day","BI",2034 +"2034-07-01","Independence Day","BI",2034 +"2034-08-15","Assumption Day","BI",2034 +"2034-10-13","Prince Louis Rwagasore Day","BI",2034 +"2034-10-21","President Ndadaye's Day","BI",2034 +"2034-11-01","All Saints' Day","BI",2034 +"2034-12-12","Eid ul Fitr* (*estimated)","BI",2034 +"2034-12-25","Christmas Day","BI",2034 +"2035-01-01","New Year's Day","BI",2035 +"2035-02-05","Unity Day","BI",2035 +"2035-02-18","Eid al Adha* (*estimated)","BI",2035 +"2035-02-19","Eid al Adha* (*estimated) (Observed)","BI",2035 +"2035-04-06","President Ntaryamira Day","BI",2035 +"2035-05-01","Labour Day","BI",2035 +"2035-05-03","Ascension Day","BI",2035 +"2035-06-08","President Nkurunziza Day","BI",2035 +"2035-07-01","Independence Day","BI",2035 +"2035-07-02","Independence Day (Observed)","BI",2035 +"2035-08-15","Assumption Day","BI",2035 +"2035-10-13","Prince Louis Rwagasore Day","BI",2035 +"2035-10-21","President Ndadaye's Day","BI",2035 +"2035-10-22","President Ndadaye's Day (Observed)","BI",2035 +"2035-11-01","All Saints' Day","BI",2035 +"2035-12-01","Eid ul Fitr* (*estimated)","BI",2035 +"2035-12-25","Christmas Day","BI",2035 +"2036-01-01","New Year's Day","BI",2036 +"2036-02-05","Unity Day","BI",2036 +"2036-02-07","Eid al Adha* (*estimated)","BI",2036 +"2036-04-06","President Ntaryamira Day","BI",2036 +"2036-04-07","President Ntaryamira Day (Observed)","BI",2036 +"2036-05-01","Labour Day","BI",2036 +"2036-05-22","Ascension Day","BI",2036 +"2036-06-08","President Nkurunziza Day","BI",2036 +"2036-06-09","President Nkurunziza Day (Observed)","BI",2036 +"2036-07-01","Independence Day","BI",2036 +"2036-08-15","Assumption Day","BI",2036 +"2036-10-13","Prince Louis Rwagasore Day","BI",2036 +"2036-10-21","President Ndadaye's Day","BI",2036 +"2036-11-01","All Saints' Day","BI",2036 +"2036-11-19","Eid ul Fitr* (*estimated)","BI",2036 +"2036-12-25","Christmas Day","BI",2036 +"2037-01-01","New Year's Day","BI",2037 +"2037-01-26","Eid al Adha* (*estimated)","BI",2037 +"2037-02-05","Unity Day","BI",2037 +"2037-04-06","President Ntaryamira Day","BI",2037 +"2037-05-01","Labour Day","BI",2037 +"2037-05-14","Ascension Day","BI",2037 +"2037-06-08","President Nkurunziza Day","BI",2037 +"2037-07-01","Independence Day","BI",2037 +"2037-08-15","Assumption Day","BI",2037 +"2037-10-13","Prince Louis Rwagasore Day","BI",2037 +"2037-10-21","President Ndadaye's Day","BI",2037 +"2037-11-01","All Saints' Day","BI",2037 +"2037-11-02","All Saints' Day (Observed)","BI",2037 +"2037-11-08","Eid ul Fitr* (*estimated)","BI",2037 +"2037-11-09","Eid ul Fitr* (*estimated) (Observed)","BI",2037 +"2037-12-25","Christmas Day","BI",2037 +"2038-01-01","New Year's Day","BI",2038 +"2038-01-16","Eid al Adha* (*estimated)","BI",2038 +"2038-02-05","Unity Day","BI",2038 +"2038-04-06","President Ntaryamira Day","BI",2038 +"2038-05-01","Labour Day","BI",2038 +"2038-06-03","Ascension Day","BI",2038 +"2038-06-08","President Nkurunziza Day","BI",2038 +"2038-07-01","Independence Day","BI",2038 +"2038-08-15","Assumption Day","BI",2038 +"2038-08-16","Assumption Day (Observed)","BI",2038 +"2038-10-13","Prince Louis Rwagasore Day","BI",2038 +"2038-10-21","President Ndadaye's Day","BI",2038 +"2038-10-29","Eid ul Fitr* (*estimated)","BI",2038 +"2038-11-01","All Saints' Day","BI",2038 +"2038-12-25","Christmas Day","BI",2038 +"2039-01-01","New Year's Day","BI",2039 +"2039-01-05","Eid al Adha* (*estimated)","BI",2039 +"2039-02-05","Unity Day","BI",2039 +"2039-04-06","President Ntaryamira Day","BI",2039 +"2039-05-01","Labour Day","BI",2039 +"2039-05-02","Labour Day (Observed)","BI",2039 +"2039-05-19","Ascension Day","BI",2039 +"2039-06-08","President Nkurunziza Day","BI",2039 +"2039-07-01","Independence Day","BI",2039 +"2039-08-15","Assumption Day","BI",2039 +"2039-10-13","Prince Louis Rwagasore Day","BI",2039 +"2039-10-19","Eid ul Fitr* (*estimated)","BI",2039 +"2039-10-21","President Ndadaye's Day","BI",2039 +"2039-11-01","All Saints' Day","BI",2039 +"2039-12-25","Christmas Day","BI",2039 +"2039-12-26","Christmas Day (Observed)","BI",2039 +"2039-12-26","Eid al Adha* (*estimated)","BI",2039 +"2040-01-01","New Year's Day","BI",2040 +"2040-01-02","New Year's Day (Observed)","BI",2040 +"2040-02-05","Unity Day","BI",2040 +"2040-02-06","Unity Day (Observed)","BI",2040 +"2040-04-06","President Ntaryamira Day","BI",2040 +"2040-05-01","Labour Day","BI",2040 +"2040-05-10","Ascension Day","BI",2040 +"2040-06-08","President Nkurunziza Day","BI",2040 +"2040-07-01","Independence Day","BI",2040 +"2040-07-02","Independence Day (Observed)","BI",2040 +"2040-08-15","Assumption Day","BI",2040 +"2040-10-07","Eid ul Fitr* (*estimated)","BI",2040 +"2040-10-08","Eid ul Fitr* (*estimated) (Observed)","BI",2040 +"2040-10-13","Prince Louis Rwagasore Day","BI",2040 +"2040-10-21","President Ndadaye's Day","BI",2040 +"2040-10-22","President Ndadaye's Day (Observed)","BI",2040 +"2040-11-01","All Saints' Day","BI",2040 +"2040-12-14","Eid al Adha* (*estimated)","BI",2040 +"2040-12-25","Christmas Day","BI",2040 +"2041-01-01","New Year's Day","BI",2041 +"2041-02-05","Unity Day","BI",2041 +"2041-04-06","President Ntaryamira Day","BI",2041 +"2041-05-01","Labour Day","BI",2041 +"2041-05-30","Ascension Day","BI",2041 +"2041-06-08","President Nkurunziza Day","BI",2041 +"2041-07-01","Independence Day","BI",2041 +"2041-08-15","Assumption Day","BI",2041 +"2041-09-26","Eid ul Fitr* (*estimated)","BI",2041 +"2041-10-13","Prince Louis Rwagasore Day","BI",2041 +"2041-10-14","Prince Louis Rwagasore Day (Observed)","BI",2041 +"2041-10-21","President Ndadaye's Day","BI",2041 +"2041-11-01","All Saints' Day","BI",2041 +"2041-12-04","Eid al Adha* (*estimated)","BI",2041 +"2041-12-25","Christmas Day","BI",2041 +"2042-01-01","New Year's Day","BI",2042 +"2042-02-05","Unity Day","BI",2042 +"2042-04-06","President Ntaryamira Day","BI",2042 +"2042-04-07","President Ntaryamira Day (Observed)","BI",2042 +"2042-05-01","Labour Day","BI",2042 +"2042-05-15","Ascension Day","BI",2042 +"2042-06-08","President Nkurunziza Day","BI",2042 +"2042-06-09","President Nkurunziza Day (Observed)","BI",2042 +"2042-07-01","Independence Day","BI",2042 +"2042-08-15","Assumption Day","BI",2042 +"2042-09-15","Eid ul Fitr* (*estimated)","BI",2042 +"2042-10-13","Prince Louis Rwagasore Day","BI",2042 +"2042-10-21","President Ndadaye's Day","BI",2042 +"2042-11-01","All Saints' Day","BI",2042 +"2042-11-23","Eid al Adha* (*estimated)","BI",2042 +"2042-11-24","Eid al Adha* (*estimated) (Observed)","BI",2042 +"2042-12-25","Christmas Day","BI",2042 +"2043-01-01","New Year's Day","BI",2043 +"2043-02-05","Unity Day","BI",2043 +"2043-04-06","President Ntaryamira Day","BI",2043 +"2043-05-01","Labour Day","BI",2043 +"2043-05-07","Ascension Day","BI",2043 +"2043-06-08","President Nkurunziza Day","BI",2043 +"2043-07-01","Independence Day","BI",2043 +"2043-08-15","Assumption Day","BI",2043 +"2043-09-04","Eid ul Fitr* (*estimated)","BI",2043 +"2043-10-13","Prince Louis Rwagasore Day","BI",2043 +"2043-10-21","President Ndadaye's Day","BI",2043 +"2043-11-01","All Saints' Day","BI",2043 +"2043-11-02","All Saints' Day (Observed)","BI",2043 +"2043-11-12","Eid al Adha* (*estimated)","BI",2043 +"2043-12-25","Christmas Day","BI",2043 +"2044-01-01","New Year's Day","BI",2044 +"2044-02-05","Unity Day","BI",2044 +"2044-04-06","President Ntaryamira Day","BI",2044 +"2044-05-01","Labour Day","BI",2044 +"2044-05-02","Labour Day (Observed)","BI",2044 +"2044-05-26","Ascension Day","BI",2044 +"2044-06-08","President Nkurunziza Day","BI",2044 +"2044-07-01","Independence Day","BI",2044 +"2044-08-15","Assumption Day","BI",2044 +"2044-08-24","Eid ul Fitr* (*estimated)","BI",2044 +"2044-10-13","Prince Louis Rwagasore Day","BI",2044 +"2044-10-21","President Ndadaye's Day","BI",2044 +"2044-10-31","Eid al Adha* (*estimated)","BI",2044 +"2044-11-01","All Saints' Day","BI",2044 +"2044-12-25","Christmas Day","BI",2044 +"2044-12-26","Christmas Day (Observed)","BI",2044 +"1995-01-01","Ano Nuevo","BO",1995 +"1995-01-02","Ano Nuevo (Observed)","BO",1995 +"1995-02-27","Feriado por Carnaval","BO",1995 +"1995-02-28","Feriado por Carnaval","BO",1995 +"1995-04-14","Viernes Santo","BO",1995 +"1995-05-01","Dia del trabajo","BO",1995 +"1995-06-15","Corpus Christi","BO",1995 +"1995-08-06","Dia de la Patria","BO",1995 +"1995-08-07","Dia de la Patria (Observed)","BO",1995 +"1995-11-02","Todos Santos","BO",1995 +"1995-12-25","Navidad","BO",1995 +"1996-01-01","Ano Nuevo","BO",1996 +"1996-02-19","Feriado por Carnaval","BO",1996 +"1996-02-20","Feriado por Carnaval","BO",1996 +"1996-04-05","Viernes Santo","BO",1996 +"1996-05-01","Dia del trabajo","BO",1996 +"1996-06-06","Corpus Christi","BO",1996 +"1996-08-06","Dia de la Patria","BO",1996 +"1996-11-02","Todos Santos","BO",1996 +"1996-12-25","Navidad","BO",1996 +"1997-01-01","Ano Nuevo","BO",1997 +"1997-02-10","Feriado por Carnaval","BO",1997 +"1997-02-11","Feriado por Carnaval","BO",1997 +"1997-03-28","Viernes Santo","BO",1997 +"1997-05-01","Dia del trabajo","BO",1997 +"1997-05-29","Corpus Christi","BO",1997 +"1997-08-06","Dia de la Patria","BO",1997 +"1997-11-02","Todos Santos","BO",1997 +"1997-11-03","Todos Santos (Observed)","BO",1997 +"1997-12-25","Navidad","BO",1997 +"1998-01-01","Ano Nuevo","BO",1998 +"1998-02-23","Feriado por Carnaval","BO",1998 +"1998-02-24","Feriado por Carnaval","BO",1998 +"1998-04-10","Viernes Santo","BO",1998 +"1998-05-01","Dia del trabajo","BO",1998 +"1998-06-11","Corpus Christi","BO",1998 +"1998-08-06","Dia de la Patria","BO",1998 +"1998-11-02","Todos Santos","BO",1998 +"1998-12-25","Navidad","BO",1998 +"1999-01-01","Ano Nuevo","BO",1999 +"1999-02-15","Feriado por Carnaval","BO",1999 +"1999-02-16","Feriado por Carnaval","BO",1999 +"1999-04-02","Viernes Santo","BO",1999 +"1999-05-01","Dia del trabajo","BO",1999 +"1999-06-03","Corpus Christi","BO",1999 +"1999-08-06","Dia de la Patria","BO",1999 +"1999-11-02","Todos Santos","BO",1999 +"1999-12-25","Navidad","BO",1999 +"2000-01-01","Ano Nuevo","BO",2000 +"2000-03-06","Feriado por Carnaval","BO",2000 +"2000-03-07","Feriado por Carnaval","BO",2000 +"2000-04-21","Viernes Santo","BO",2000 +"2000-05-01","Dia del trabajo","BO",2000 +"2000-06-22","Corpus Christi","BO",2000 +"2000-08-06","Dia de la Patria","BO",2000 +"2000-08-07","Dia de la Patria (Observed)","BO",2000 +"2000-11-02","Todos Santos","BO",2000 +"2000-12-25","Navidad","BO",2000 +"2001-01-01","Ano Nuevo","BO",2001 +"2001-02-26","Feriado por Carnaval","BO",2001 +"2001-02-27","Feriado por Carnaval","BO",2001 +"2001-04-13","Viernes Santo","BO",2001 +"2001-05-01","Dia del trabajo","BO",2001 +"2001-06-14","Corpus Christi","BO",2001 +"2001-08-06","Dia de la Patria","BO",2001 +"2001-11-02","Todos Santos","BO",2001 +"2001-12-25","Navidad","BO",2001 +"2002-01-01","Ano Nuevo","BO",2002 +"2002-02-11","Feriado por Carnaval","BO",2002 +"2002-02-12","Feriado por Carnaval","BO",2002 +"2002-03-29","Viernes Santo","BO",2002 +"2002-05-01","Dia del trabajo","BO",2002 +"2002-05-30","Corpus Christi","BO",2002 +"2002-08-06","Dia de la Patria","BO",2002 +"2002-11-02","Todos Santos","BO",2002 +"2002-12-25","Navidad","BO",2002 +"2003-01-01","Ano Nuevo","BO",2003 +"2003-03-03","Feriado por Carnaval","BO",2003 +"2003-03-04","Feriado por Carnaval","BO",2003 +"2003-04-18","Viernes Santo","BO",2003 +"2003-05-01","Dia del trabajo","BO",2003 +"2003-06-19","Corpus Christi","BO",2003 +"2003-08-06","Dia de la Patria","BO",2003 +"2003-11-02","Todos Santos","BO",2003 +"2003-11-03","Todos Santos (Observed)","BO",2003 +"2003-12-25","Navidad","BO",2003 +"2004-01-01","Ano Nuevo","BO",2004 +"2004-02-23","Feriado por Carnaval","BO",2004 +"2004-02-24","Feriado por Carnaval","BO",2004 +"2004-04-09","Viernes Santo","BO",2004 +"2004-05-01","Dia del trabajo","BO",2004 +"2004-06-10","Corpus Christi","BO",2004 +"2004-08-06","Dia de la Patria","BO",2004 +"2004-11-02","Todos Santos","BO",2004 +"2004-12-25","Navidad","BO",2004 +"2005-01-01","Ano Nuevo","BO",2005 +"2005-02-07","Feriado por Carnaval","BO",2005 +"2005-02-08","Feriado por Carnaval","BO",2005 +"2005-03-25","Viernes Santo","BO",2005 +"2005-05-01","Dia del trabajo","BO",2005 +"2005-05-02","Dia del trabajo (Observed)","BO",2005 +"2005-05-26","Corpus Christi","BO",2005 +"2005-08-06","Dia de la Patria","BO",2005 +"2005-11-02","Todos Santos","BO",2005 +"2005-12-25","Navidad","BO",2005 +"2005-12-26","Navidad (Observed)","BO",2005 +"2006-01-01","Ano Nuevo","BO",2006 +"2006-01-02","Ano Nuevo (Observed)","BO",2006 +"2006-02-27","Feriado por Carnaval","BO",2006 +"2006-02-28","Feriado por Carnaval","BO",2006 +"2006-04-14","Viernes Santo","BO",2006 +"2006-05-01","Dia del trabajo","BO",2006 +"2006-06-15","Corpus Christi","BO",2006 +"2006-08-06","Dia de la Patria","BO",2006 +"2006-08-07","Dia de la Patria (Observed)","BO",2006 +"2006-11-02","Todos Santos","BO",2006 +"2006-12-25","Navidad","BO",2006 +"2007-01-01","Ano Nuevo","BO",2007 +"2007-02-19","Feriado por Carnaval","BO",2007 +"2007-02-20","Feriado por Carnaval","BO",2007 +"2007-04-06","Viernes Santo","BO",2007 +"2007-05-01","Dia del trabajo","BO",2007 +"2007-06-07","Corpus Christi","BO",2007 +"2007-08-06","Dia de la Patria","BO",2007 +"2007-11-02","Todos Santos","BO",2007 +"2007-12-25","Navidad","BO",2007 +"2008-01-01","Ano Nuevo","BO",2008 +"2008-02-04","Feriado por Carnaval","BO",2008 +"2008-02-05","Feriado por Carnaval","BO",2008 +"2008-03-21","Viernes Santo","BO",2008 +"2008-05-01","Dia del trabajo","BO",2008 +"2008-05-22","Corpus Christi","BO",2008 +"2008-08-06","Dia de la Patria","BO",2008 +"2008-11-02","Todos Santos","BO",2008 +"2008-11-03","Todos Santos (Observed)","BO",2008 +"2008-12-25","Navidad","BO",2008 +"2009-01-01","Ano Nuevo","BO",2009 +"2009-02-23","Feriado por Carnaval","BO",2009 +"2009-02-24","Feriado por Carnaval","BO",2009 +"2009-04-10","Viernes Santo","BO",2009 +"2009-05-01","Dia del trabajo","BO",2009 +"2009-06-11","Corpus Christi","BO",2009 +"2009-08-06","Dia de la Patria","BO",2009 +"2009-11-02","Todos Santos","BO",2009 +"2009-12-25","Navidad","BO",2009 +"2010-01-01","Ano Nuevo","BO",2010 +"2010-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2010 +"2010-02-15","Feriado por Carnaval","BO",2010 +"2010-02-16","Feriado por Carnaval","BO",2010 +"2010-04-02","Viernes Santo","BO",2010 +"2010-05-01","Dia del trabajo","BO",2010 +"2010-06-03","Corpus Christi","BO",2010 +"2010-06-21","Ano Nuevo Andino","BO",2010 +"2010-08-06","Dia de la Patria","BO",2010 +"2010-11-02","Todos Santos","BO",2010 +"2010-12-25","Navidad","BO",2010 +"2011-01-01","Ano Nuevo","BO",2011 +"2011-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2011 +"2011-03-07","Feriado por Carnaval","BO",2011 +"2011-03-08","Feriado por Carnaval","BO",2011 +"2011-04-22","Viernes Santo","BO",2011 +"2011-05-01","Dia del trabajo","BO",2011 +"2011-05-02","Dia del trabajo (Observed)","BO",2011 +"2011-06-21","Ano Nuevo Andino","BO",2011 +"2011-06-23","Corpus Christi","BO",2011 +"2011-08-06","Dia de la Patria","BO",2011 +"2011-11-02","Todos Santos","BO",2011 +"2011-12-25","Navidad","BO",2011 +"2011-12-26","Navidad (Observed)","BO",2011 +"2012-01-01","Ano Nuevo","BO",2012 +"2012-01-02","Ano Nuevo (Observed)","BO",2012 +"2012-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2012 +"2012-02-20","Feriado por Carnaval","BO",2012 +"2012-02-21","Feriado por Carnaval","BO",2012 +"2012-04-06","Viernes Santo","BO",2012 +"2012-05-01","Dia del trabajo","BO",2012 +"2012-06-07","Corpus Christi","BO",2012 +"2012-06-21","Ano Nuevo Andino","BO",2012 +"2012-08-06","Dia de la Patria","BO",2012 +"2012-11-02","Todos Santos","BO",2012 +"2012-12-25","Navidad","BO",2012 +"2013-01-01","Ano Nuevo","BO",2013 +"2013-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2013 +"2013-02-11","Feriado por Carnaval","BO",2013 +"2013-02-12","Feriado por Carnaval","BO",2013 +"2013-03-29","Viernes Santo","BO",2013 +"2013-05-01","Dia del trabajo","BO",2013 +"2013-05-30","Corpus Christi","BO",2013 +"2013-06-21","Ano Nuevo Andino","BO",2013 +"2013-08-06","Dia de la Patria","BO",2013 +"2013-11-02","Todos Santos","BO",2013 +"2013-12-25","Navidad","BO",2013 +"2014-01-01","Ano Nuevo","BO",2014 +"2014-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2014 +"2014-03-03","Feriado por Carnaval","BO",2014 +"2014-03-04","Feriado por Carnaval","BO",2014 +"2014-04-18","Viernes Santo","BO",2014 +"2014-05-01","Dia del trabajo","BO",2014 +"2014-06-19","Corpus Christi","BO",2014 +"2014-06-21","Ano Nuevo Andino","BO",2014 +"2014-08-06","Dia de la Patria","BO",2014 +"2014-11-02","Todos Santos","BO",2014 +"2014-11-03","Todos Santos (Observed)","BO",2014 +"2014-12-25","Navidad","BO",2014 +"2015-01-01","Ano Nuevo","BO",2015 +"2015-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2015 +"2015-02-16","Feriado por Carnaval","BO",2015 +"2015-02-17","Feriado por Carnaval","BO",2015 +"2015-04-03","Viernes Santo","BO",2015 +"2015-05-01","Dia del trabajo","BO",2015 +"2015-06-04","Corpus Christi","BO",2015 +"2015-06-21","Ano Nuevo Andino","BO",2015 +"2015-06-22","Ano Nuevo Andino (Observed)","BO",2015 +"2015-08-06","Dia de la Patria","BO",2015 +"2015-11-02","Todos Santos","BO",2015 +"2015-12-25","Navidad","BO",2015 +"2016-01-01","Ano Nuevo","BO",2016 +"2016-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2016 +"2016-02-08","Feriado por Carnaval","BO",2016 +"2016-02-09","Feriado por Carnaval","BO",2016 +"2016-03-25","Viernes Santo","BO",2016 +"2016-05-01","Dia del trabajo","BO",2016 +"2016-05-02","Dia del trabajo (Observed)","BO",2016 +"2016-05-26","Corpus Christi","BO",2016 +"2016-06-21","Ano Nuevo Andino","BO",2016 +"2016-08-06","Dia de la Patria","BO",2016 +"2016-11-02","Todos Santos","BO",2016 +"2016-12-25","Navidad","BO",2016 +"2016-12-26","Navidad (Observed)","BO",2016 +"2017-01-01","Ano Nuevo","BO",2017 +"2017-01-02","Ano Nuevo (Observed)","BO",2017 +"2017-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2017 +"2017-02-27","Feriado por Carnaval","BO",2017 +"2017-02-28","Feriado por Carnaval","BO",2017 +"2017-04-14","Viernes Santo","BO",2017 +"2017-05-01","Dia del trabajo","BO",2017 +"2017-06-15","Corpus Christi","BO",2017 +"2017-06-21","Ano Nuevo Andino","BO",2017 +"2017-08-06","Dia de la Patria","BO",2017 +"2017-08-07","Dia de la Patria (Observed)","BO",2017 +"2017-11-02","Todos Santos","BO",2017 +"2017-12-25","Navidad","BO",2017 +"2018-01-01","Ano Nuevo","BO",2018 +"2018-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2018 +"2018-02-12","Feriado por Carnaval","BO",2018 +"2018-02-13","Feriado por Carnaval","BO",2018 +"2018-03-30","Viernes Santo","BO",2018 +"2018-05-01","Dia del trabajo","BO",2018 +"2018-05-31","Corpus Christi","BO",2018 +"2018-06-21","Ano Nuevo Andino","BO",2018 +"2018-08-06","Dia de la Patria","BO",2018 +"2018-11-02","Todos Santos","BO",2018 +"2018-12-25","Navidad","BO",2018 +"2019-01-01","Ano Nuevo","BO",2019 +"2019-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2019 +"2019-03-04","Feriado por Carnaval","BO",2019 +"2019-03-05","Feriado por Carnaval","BO",2019 +"2019-04-19","Viernes Santo","BO",2019 +"2019-05-01","Dia del trabajo","BO",2019 +"2019-06-20","Corpus Christi","BO",2019 +"2019-06-21","Ano Nuevo Andino","BO",2019 +"2019-08-06","Dia de la Patria","BO",2019 +"2019-11-02","Todos Santos","BO",2019 +"2019-12-25","Navidad","BO",2019 +"2020-01-01","Ano Nuevo","BO",2020 +"2020-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2020 +"2020-02-24","Feriado por Carnaval","BO",2020 +"2020-02-25","Feriado por Carnaval","BO",2020 +"2020-04-10","Viernes Santo","BO",2020 +"2020-05-01","Dia del trabajo","BO",2020 +"2020-06-11","Corpus Christi","BO",2020 +"2020-06-21","Ano Nuevo Andino","BO",2020 +"2020-06-22","Ano Nuevo Andino (Observed)","BO",2020 +"2020-08-06","Dia de la Patria","BO",2020 +"2020-11-02","Todos Santos","BO",2020 +"2020-12-25","Navidad","BO",2020 +"2021-01-01","Ano Nuevo","BO",2021 +"2021-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2021 +"2021-02-15","Feriado por Carnaval","BO",2021 +"2021-02-16","Feriado por Carnaval","BO",2021 +"2021-04-02","Viernes Santo","BO",2021 +"2021-05-01","Dia del trabajo","BO",2021 +"2021-06-03","Corpus Christi","BO",2021 +"2021-06-21","Ano Nuevo Andino","BO",2021 +"2021-08-06","Dia de la Patria","BO",2021 +"2021-11-02","Todos Santos","BO",2021 +"2021-12-25","Navidad","BO",2021 +"2022-01-01","Ano Nuevo","BO",2022 +"2022-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2022 +"2022-02-28","Feriado por Carnaval","BO",2022 +"2022-03-01","Feriado por Carnaval","BO",2022 +"2022-04-15","Viernes Santo","BO",2022 +"2022-05-01","Dia del trabajo","BO",2022 +"2022-05-02","Dia del trabajo (Observed)","BO",2022 +"2022-06-16","Corpus Christi","BO",2022 +"2022-06-21","Ano Nuevo Andino","BO",2022 +"2022-08-06","Dia de la Patria","BO",2022 +"2022-11-02","Todos Santos","BO",2022 +"2022-12-25","Navidad","BO",2022 +"2022-12-26","Navidad (Observed)","BO",2022 +"2023-01-01","Ano Nuevo","BO",2023 +"2023-01-02","Ano Nuevo (Observed)","BO",2023 +"2023-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2023 +"2023-02-20","Feriado por Carnaval","BO",2023 +"2023-02-21","Feriado por Carnaval","BO",2023 +"2023-04-07","Viernes Santo","BO",2023 +"2023-05-01","Dia del trabajo","BO",2023 +"2023-06-08","Corpus Christi","BO",2023 +"2023-06-21","Ano Nuevo Andino","BO",2023 +"2023-08-06","Dia de la Patria","BO",2023 +"2023-08-07","Dia de la Patria (Observed)","BO",2023 +"2023-11-02","Todos Santos","BO",2023 +"2023-12-25","Navidad","BO",2023 +"2024-01-01","Ano Nuevo","BO",2024 +"2024-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2024 +"2024-02-12","Feriado por Carnaval","BO",2024 +"2024-02-13","Feriado por Carnaval","BO",2024 +"2024-03-29","Viernes Santo","BO",2024 +"2024-05-01","Dia del trabajo","BO",2024 +"2024-05-30","Corpus Christi","BO",2024 +"2024-06-21","Ano Nuevo Andino","BO",2024 +"2024-08-06","Dia de la Patria","BO",2024 +"2024-11-02","Todos Santos","BO",2024 +"2024-12-25","Navidad","BO",2024 +"2025-01-01","Ano Nuevo","BO",2025 +"2025-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2025 +"2025-03-03","Feriado por Carnaval","BO",2025 +"2025-03-04","Feriado por Carnaval","BO",2025 +"2025-04-18","Viernes Santo","BO",2025 +"2025-05-01","Dia del trabajo","BO",2025 +"2025-06-19","Corpus Christi","BO",2025 +"2025-06-21","Ano Nuevo Andino","BO",2025 +"2025-08-06","Dia de la Patria","BO",2025 +"2025-11-02","Todos Santos","BO",2025 +"2025-11-03","Todos Santos (Observed)","BO",2025 +"2025-12-25","Navidad","BO",2025 +"2026-01-01","Ano Nuevo","BO",2026 +"2026-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2026 +"2026-02-16","Feriado por Carnaval","BO",2026 +"2026-02-17","Feriado por Carnaval","BO",2026 +"2026-04-03","Viernes Santo","BO",2026 +"2026-05-01","Dia del trabajo","BO",2026 +"2026-06-04","Corpus Christi","BO",2026 +"2026-06-21","Ano Nuevo Andino","BO",2026 +"2026-06-22","Ano Nuevo Andino (Observed)","BO",2026 +"2026-08-06","Dia de la Patria","BO",2026 +"2026-11-02","Todos Santos","BO",2026 +"2026-12-25","Navidad","BO",2026 +"2027-01-01","Ano Nuevo","BO",2027 +"2027-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2027 +"2027-02-08","Feriado por Carnaval","BO",2027 +"2027-02-09","Feriado por Carnaval","BO",2027 +"2027-03-26","Viernes Santo","BO",2027 +"2027-05-01","Dia del trabajo","BO",2027 +"2027-05-27","Corpus Christi","BO",2027 +"2027-06-21","Ano Nuevo Andino","BO",2027 +"2027-08-06","Dia de la Patria","BO",2027 +"2027-11-02","Todos Santos","BO",2027 +"2027-12-25","Navidad","BO",2027 +"2028-01-01","Ano Nuevo","BO",2028 +"2028-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2028 +"2028-02-28","Feriado por Carnaval","BO",2028 +"2028-02-29","Feriado por Carnaval","BO",2028 +"2028-04-14","Viernes Santo","BO",2028 +"2028-05-01","Dia del trabajo","BO",2028 +"2028-06-15","Corpus Christi","BO",2028 +"2028-06-21","Ano Nuevo Andino","BO",2028 +"2028-08-06","Dia de la Patria","BO",2028 +"2028-08-07","Dia de la Patria (Observed)","BO",2028 +"2028-11-02","Todos Santos","BO",2028 +"2028-12-25","Navidad","BO",2028 +"2029-01-01","Ano Nuevo","BO",2029 +"2029-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2029 +"2029-02-12","Feriado por Carnaval","BO",2029 +"2029-02-13","Feriado por Carnaval","BO",2029 +"2029-03-30","Viernes Santo","BO",2029 +"2029-05-01","Dia del trabajo","BO",2029 +"2029-05-31","Corpus Christi","BO",2029 +"2029-06-21","Ano Nuevo Andino","BO",2029 +"2029-08-06","Dia de la Patria","BO",2029 +"2029-11-02","Todos Santos","BO",2029 +"2029-12-25","Navidad","BO",2029 +"2030-01-01","Ano Nuevo","BO",2030 +"2030-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2030 +"2030-03-04","Feriado por Carnaval","BO",2030 +"2030-03-05","Feriado por Carnaval","BO",2030 +"2030-04-19","Viernes Santo","BO",2030 +"2030-05-01","Dia del trabajo","BO",2030 +"2030-06-20","Corpus Christi","BO",2030 +"2030-06-21","Ano Nuevo Andino","BO",2030 +"2030-08-06","Dia de la Patria","BO",2030 +"2030-11-02","Todos Santos","BO",2030 +"2030-12-25","Navidad","BO",2030 +"2031-01-01","Ano Nuevo","BO",2031 +"2031-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2031 +"2031-02-24","Feriado por Carnaval","BO",2031 +"2031-02-25","Feriado por Carnaval","BO",2031 +"2031-04-11","Viernes Santo","BO",2031 +"2031-05-01","Dia del trabajo","BO",2031 +"2031-06-12","Corpus Christi","BO",2031 +"2031-06-21","Ano Nuevo Andino","BO",2031 +"2031-08-06","Dia de la Patria","BO",2031 +"2031-11-02","Todos Santos","BO",2031 +"2031-11-03","Todos Santos (Observed)","BO",2031 +"2031-12-25","Navidad","BO",2031 +"2032-01-01","Ano Nuevo","BO",2032 +"2032-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2032 +"2032-02-09","Feriado por Carnaval","BO",2032 +"2032-02-10","Feriado por Carnaval","BO",2032 +"2032-03-26","Viernes Santo","BO",2032 +"2032-05-01","Dia del trabajo","BO",2032 +"2032-05-27","Corpus Christi","BO",2032 +"2032-06-21","Ano Nuevo Andino","BO",2032 +"2032-08-06","Dia de la Patria","BO",2032 +"2032-11-02","Todos Santos","BO",2032 +"2032-12-25","Navidad","BO",2032 +"2033-01-01","Ano Nuevo","BO",2033 +"2033-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2033 +"2033-02-28","Feriado por Carnaval","BO",2033 +"2033-03-01","Feriado por Carnaval","BO",2033 +"2033-04-15","Viernes Santo","BO",2033 +"2033-05-01","Dia del trabajo","BO",2033 +"2033-05-02","Dia del trabajo (Observed)","BO",2033 +"2033-06-16","Corpus Christi","BO",2033 +"2033-06-21","Ano Nuevo Andino","BO",2033 +"2033-08-06","Dia de la Patria","BO",2033 +"2033-11-02","Todos Santos","BO",2033 +"2033-12-25","Navidad","BO",2033 +"2033-12-26","Navidad (Observed)","BO",2033 +"2034-01-01","Ano Nuevo","BO",2034 +"2034-01-02","Ano Nuevo (Observed)","BO",2034 +"2034-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2034 +"2034-02-20","Feriado por Carnaval","BO",2034 +"2034-02-21","Feriado por Carnaval","BO",2034 +"2034-04-07","Viernes Santo","BO",2034 +"2034-05-01","Dia del trabajo","BO",2034 +"2034-06-08","Corpus Christi","BO",2034 +"2034-06-21","Ano Nuevo Andino","BO",2034 +"2034-08-06","Dia de la Patria","BO",2034 +"2034-08-07","Dia de la Patria (Observed)","BO",2034 +"2034-11-02","Todos Santos","BO",2034 +"2034-12-25","Navidad","BO",2034 +"2035-01-01","Ano Nuevo","BO",2035 +"2035-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2035 +"2035-02-05","Feriado por Carnaval","BO",2035 +"2035-02-06","Feriado por Carnaval","BO",2035 +"2035-03-23","Viernes Santo","BO",2035 +"2035-05-01","Dia del trabajo","BO",2035 +"2035-05-24","Corpus Christi","BO",2035 +"2035-06-21","Ano Nuevo Andino","BO",2035 +"2035-08-06","Dia de la Patria","BO",2035 +"2035-11-02","Todos Santos","BO",2035 +"2035-12-25","Navidad","BO",2035 +"2036-01-01","Ano Nuevo","BO",2036 +"2036-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2036 +"2036-02-25","Feriado por Carnaval","BO",2036 +"2036-02-26","Feriado por Carnaval","BO",2036 +"2036-04-11","Viernes Santo","BO",2036 +"2036-05-01","Dia del trabajo","BO",2036 +"2036-06-12","Corpus Christi","BO",2036 +"2036-06-21","Ano Nuevo Andino","BO",2036 +"2036-08-06","Dia de la Patria","BO",2036 +"2036-11-02","Todos Santos","BO",2036 +"2036-11-03","Todos Santos (Observed)","BO",2036 +"2036-12-25","Navidad","BO",2036 +"2037-01-01","Ano Nuevo","BO",2037 +"2037-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2037 +"2037-02-16","Feriado por Carnaval","BO",2037 +"2037-02-17","Feriado por Carnaval","BO",2037 +"2037-04-03","Viernes Santo","BO",2037 +"2037-05-01","Dia del trabajo","BO",2037 +"2037-06-04","Corpus Christi","BO",2037 +"2037-06-21","Ano Nuevo Andino","BO",2037 +"2037-06-22","Ano Nuevo Andino (Observed)","BO",2037 +"2037-08-06","Dia de la Patria","BO",2037 +"2037-11-02","Todos Santos","BO",2037 +"2037-12-25","Navidad","BO",2037 +"2038-01-01","Ano Nuevo","BO",2038 +"2038-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2038 +"2038-03-08","Feriado por Carnaval","BO",2038 +"2038-03-09","Feriado por Carnaval","BO",2038 +"2038-04-23","Viernes Santo","BO",2038 +"2038-05-01","Dia del trabajo","BO",2038 +"2038-06-21","Ano Nuevo Andino","BO",2038 +"2038-06-24","Corpus Christi","BO",2038 +"2038-08-06","Dia de la Patria","BO",2038 +"2038-11-02","Todos Santos","BO",2038 +"2038-12-25","Navidad","BO",2038 +"2039-01-01","Ano Nuevo","BO",2039 +"2039-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2039 +"2039-02-21","Feriado por Carnaval","BO",2039 +"2039-02-22","Feriado por Carnaval","BO",2039 +"2039-04-08","Viernes Santo","BO",2039 +"2039-05-01","Dia del trabajo","BO",2039 +"2039-05-02","Dia del trabajo (Observed)","BO",2039 +"2039-06-09","Corpus Christi","BO",2039 +"2039-06-21","Ano Nuevo Andino","BO",2039 +"2039-08-06","Dia de la Patria","BO",2039 +"2039-11-02","Todos Santos","BO",2039 +"2039-12-25","Navidad","BO",2039 +"2039-12-26","Navidad (Observed)","BO",2039 +"2040-01-01","Ano Nuevo","BO",2040 +"2040-01-02","Ano Nuevo (Observed)","BO",2040 +"2040-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2040 +"2040-02-13","Feriado por Carnaval","BO",2040 +"2040-02-14","Feriado por Carnaval","BO",2040 +"2040-03-30","Viernes Santo","BO",2040 +"2040-05-01","Dia del trabajo","BO",2040 +"2040-05-31","Corpus Christi","BO",2040 +"2040-06-21","Ano Nuevo Andino","BO",2040 +"2040-08-06","Dia de la Patria","BO",2040 +"2040-11-02","Todos Santos","BO",2040 +"2040-12-25","Navidad","BO",2040 +"2041-01-01","Ano Nuevo","BO",2041 +"2041-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2041 +"2041-03-04","Feriado por Carnaval","BO",2041 +"2041-03-05","Feriado por Carnaval","BO",2041 +"2041-04-19","Viernes Santo","BO",2041 +"2041-05-01","Dia del trabajo","BO",2041 +"2041-06-20","Corpus Christi","BO",2041 +"2041-06-21","Ano Nuevo Andino","BO",2041 +"2041-08-06","Dia de la Patria","BO",2041 +"2041-11-02","Todos Santos","BO",2041 +"2041-12-25","Navidad","BO",2041 +"2042-01-01","Ano Nuevo","BO",2042 +"2042-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2042 +"2042-02-17","Feriado por Carnaval","BO",2042 +"2042-02-18","Feriado por Carnaval","BO",2042 +"2042-04-04","Viernes Santo","BO",2042 +"2042-05-01","Dia del trabajo","BO",2042 +"2042-06-05","Corpus Christi","BO",2042 +"2042-06-21","Ano Nuevo Andino","BO",2042 +"2042-08-06","Dia de la Patria","BO",2042 +"2042-11-02","Todos Santos","BO",2042 +"2042-11-03","Todos Santos (Observed)","BO",2042 +"2042-12-25","Navidad","BO",2042 +"2043-01-01","Ano Nuevo","BO",2043 +"2043-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2043 +"2043-02-09","Feriado por Carnaval","BO",2043 +"2043-02-10","Feriado por Carnaval","BO",2043 +"2043-03-27","Viernes Santo","BO",2043 +"2043-05-01","Dia del trabajo","BO",2043 +"2043-05-28","Corpus Christi","BO",2043 +"2043-06-21","Ano Nuevo Andino","BO",2043 +"2043-06-22","Ano Nuevo Andino (Observed)","BO",2043 +"2043-08-06","Dia de la Patria","BO",2043 +"2043-11-02","Todos Santos","BO",2043 +"2043-12-25","Navidad","BO",2043 +"2044-01-01","Ano Nuevo","BO",2044 +"2044-01-22","Nacimiento del Estado Plurinacional de Bolivia","BO",2044 +"2044-02-29","Feriado por Carnaval","BO",2044 +"2044-03-01","Feriado por Carnaval","BO",2044 +"2044-04-15","Viernes Santo","BO",2044 +"2044-05-01","Dia del trabajo","BO",2044 +"2044-05-02","Dia del trabajo (Observed)","BO",2044 +"2044-06-16","Corpus Christi","BO",2044 +"2044-06-21","Ano Nuevo Andino","BO",2044 +"2044-08-06","Dia de la Patria","BO",2044 +"2044-11-02","Todos Santos","BO",2044 +"2044-12-25","Navidad","BO",2044 +"2044-12-26","Navidad (Observed)","BO",2044 +"1995-01-01","Confraternizacao Universal","BR",1995 +"1995-02-27","Carnaval","BR",1995 +"1995-02-28","Carnaval","BR",1995 +"1995-03-01","Inicio da Quaresma","BR",1995 +"1995-04-14","Sexta-feira Santa","BR",1995 +"1995-04-21","Tiradentes","BR",1995 +"1995-05-01","Dia do Trabalhador","BR",1995 +"1995-06-15","Corpus Christi","BR",1995 +"1995-09-07","Independencia do Brasil","BR",1995 +"1995-10-12","Nossa Senhora Aparecida","BR",1995 +"1995-10-28","Dia do Servidor Publico","BR",1995 +"1995-11-02","Finados","BR",1995 +"1995-11-15","Proclamacao da Republica","BR",1995 +"1995-12-24","Vespera de Natal","BR",1995 +"1995-12-25","Natal","BR",1995 +"1995-12-31","Vespera de Ano-Novo","BR",1995 +"1996-01-01","Confraternizacao Universal","BR",1996 +"1996-02-19","Carnaval","BR",1996 +"1996-02-20","Carnaval","BR",1996 +"1996-02-21","Inicio da Quaresma","BR",1996 +"1996-04-05","Sexta-feira Santa","BR",1996 +"1996-04-21","Tiradentes","BR",1996 +"1996-05-01","Dia do Trabalhador","BR",1996 +"1996-06-06","Corpus Christi","BR",1996 +"1996-09-07","Independencia do Brasil","BR",1996 +"1996-10-12","Nossa Senhora Aparecida","BR",1996 +"1996-10-28","Dia do Servidor Publico","BR",1996 +"1996-11-02","Finados","BR",1996 +"1996-11-15","Proclamacao da Republica","BR",1996 +"1996-12-24","Vespera de Natal","BR",1996 +"1996-12-25","Natal","BR",1996 +"1996-12-31","Vespera de Ano-Novo","BR",1996 +"1997-01-01","Confraternizacao Universal","BR",1997 +"1997-02-10","Carnaval","BR",1997 +"1997-02-11","Carnaval","BR",1997 +"1997-02-12","Inicio da Quaresma","BR",1997 +"1997-03-28","Sexta-feira Santa","BR",1997 +"1997-04-21","Tiradentes","BR",1997 +"1997-05-01","Dia do Trabalhador","BR",1997 +"1997-05-29","Corpus Christi","BR",1997 +"1997-09-07","Independencia do Brasil","BR",1997 +"1997-10-12","Nossa Senhora Aparecida","BR",1997 +"1997-10-28","Dia do Servidor Publico","BR",1997 +"1997-11-02","Finados","BR",1997 +"1997-11-15","Proclamacao da Republica","BR",1997 +"1997-12-24","Vespera de Natal","BR",1997 +"1997-12-25","Natal","BR",1997 +"1997-12-31","Vespera de Ano-Novo","BR",1997 +"1998-01-01","Confraternizacao Universal","BR",1998 +"1998-02-23","Carnaval","BR",1998 +"1998-02-24","Carnaval","BR",1998 +"1998-02-25","Inicio da Quaresma","BR",1998 +"1998-04-10","Sexta-feira Santa","BR",1998 +"1998-04-21","Tiradentes","BR",1998 +"1998-05-01","Dia do Trabalhador","BR",1998 +"1998-06-11","Corpus Christi","BR",1998 +"1998-09-07","Independencia do Brasil","BR",1998 +"1998-10-12","Nossa Senhora Aparecida","BR",1998 +"1998-10-28","Dia do Servidor Publico","BR",1998 +"1998-11-02","Finados","BR",1998 +"1998-11-15","Proclamacao da Republica","BR",1998 +"1998-12-24","Vespera de Natal","BR",1998 +"1998-12-25","Natal","BR",1998 +"1998-12-31","Vespera de Ano-Novo","BR",1998 +"1999-01-01","Confraternizacao Universal","BR",1999 +"1999-02-15","Carnaval","BR",1999 +"1999-02-16","Carnaval","BR",1999 +"1999-02-17","Inicio da Quaresma","BR",1999 +"1999-04-02","Sexta-feira Santa","BR",1999 +"1999-04-21","Tiradentes","BR",1999 +"1999-05-01","Dia do Trabalhador","BR",1999 +"1999-06-03","Corpus Christi","BR",1999 +"1999-09-07","Independencia do Brasil","BR",1999 +"1999-10-12","Nossa Senhora Aparecida","BR",1999 +"1999-10-28","Dia do Servidor Publico","BR",1999 +"1999-11-02","Finados","BR",1999 +"1999-11-15","Proclamacao da Republica","BR",1999 +"1999-12-24","Vespera de Natal","BR",1999 +"1999-12-25","Natal","BR",1999 +"1999-12-31","Vespera de Ano-Novo","BR",1999 +"2000-01-01","Confraternizacao Universal","BR",2000 +"2000-03-06","Carnaval","BR",2000 +"2000-03-07","Carnaval","BR",2000 +"2000-03-08","Inicio da Quaresma","BR",2000 +"2000-04-21","Sexta-feira Santa","BR",2000 +"2000-04-21","Tiradentes","BR",2000 +"2000-05-01","Dia do Trabalhador","BR",2000 +"2000-06-22","Corpus Christi","BR",2000 +"2000-09-07","Independencia do Brasil","BR",2000 +"2000-10-12","Nossa Senhora Aparecida","BR",2000 +"2000-10-28","Dia do Servidor Publico","BR",2000 +"2000-11-02","Finados","BR",2000 +"2000-11-15","Proclamacao da Republica","BR",2000 +"2000-12-24","Vespera de Natal","BR",2000 +"2000-12-25","Natal","BR",2000 +"2000-12-31","Vespera de Ano-Novo","BR",2000 +"2001-01-01","Confraternizacao Universal","BR",2001 +"2001-02-26","Carnaval","BR",2001 +"2001-02-27","Carnaval","BR",2001 +"2001-02-28","Inicio da Quaresma","BR",2001 +"2001-04-13","Sexta-feira Santa","BR",2001 +"2001-04-21","Tiradentes","BR",2001 +"2001-05-01","Dia do Trabalhador","BR",2001 +"2001-06-14","Corpus Christi","BR",2001 +"2001-09-07","Independencia do Brasil","BR",2001 +"2001-10-12","Nossa Senhora Aparecida","BR",2001 +"2001-10-28","Dia do Servidor Publico","BR",2001 +"2001-11-02","Finados","BR",2001 +"2001-11-15","Proclamacao da Republica","BR",2001 +"2001-12-24","Vespera de Natal","BR",2001 +"2001-12-25","Natal","BR",2001 +"2001-12-31","Vespera de Ano-Novo","BR",2001 +"2002-01-01","Confraternizacao Universal","BR",2002 +"2002-02-11","Carnaval","BR",2002 +"2002-02-12","Carnaval","BR",2002 +"2002-02-13","Inicio da Quaresma","BR",2002 +"2002-03-29","Sexta-feira Santa","BR",2002 +"2002-04-21","Tiradentes","BR",2002 +"2002-05-01","Dia do Trabalhador","BR",2002 +"2002-05-30","Corpus Christi","BR",2002 +"2002-09-07","Independencia do Brasil","BR",2002 +"2002-10-12","Nossa Senhora Aparecida","BR",2002 +"2002-10-28","Dia do Servidor Publico","BR",2002 +"2002-11-02","Finados","BR",2002 +"2002-11-15","Proclamacao da Republica","BR",2002 +"2002-12-24","Vespera de Natal","BR",2002 +"2002-12-25","Natal","BR",2002 +"2002-12-31","Vespera de Ano-Novo","BR",2002 +"2003-01-01","Confraternizacao Universal","BR",2003 +"2003-03-03","Carnaval","BR",2003 +"2003-03-04","Carnaval","BR",2003 +"2003-03-05","Inicio da Quaresma","BR",2003 +"2003-04-18","Sexta-feira Santa","BR",2003 +"2003-04-21","Tiradentes","BR",2003 +"2003-05-01","Dia do Trabalhador","BR",2003 +"2003-06-19","Corpus Christi","BR",2003 +"2003-09-07","Independencia do Brasil","BR",2003 +"2003-10-12","Nossa Senhora Aparecida","BR",2003 +"2003-10-28","Dia do Servidor Publico","BR",2003 +"2003-11-02","Finados","BR",2003 +"2003-11-15","Proclamacao da Republica","BR",2003 +"2003-12-24","Vespera de Natal","BR",2003 +"2003-12-25","Natal","BR",2003 +"2003-12-31","Vespera de Ano-Novo","BR",2003 +"2004-01-01","Confraternizacao Universal","BR",2004 +"2004-02-23","Carnaval","BR",2004 +"2004-02-24","Carnaval","BR",2004 +"2004-02-25","Inicio da Quaresma","BR",2004 +"2004-04-09","Sexta-feira Santa","BR",2004 +"2004-04-21","Tiradentes","BR",2004 +"2004-05-01","Dia do Trabalhador","BR",2004 +"2004-06-10","Corpus Christi","BR",2004 +"2004-09-07","Independencia do Brasil","BR",2004 +"2004-10-12","Nossa Senhora Aparecida","BR",2004 +"2004-10-28","Dia do Servidor Publico","BR",2004 +"2004-11-02","Finados","BR",2004 +"2004-11-15","Proclamacao da Republica","BR",2004 +"2004-12-24","Vespera de Natal","BR",2004 +"2004-12-25","Natal","BR",2004 +"2004-12-31","Vespera de Ano-Novo","BR",2004 +"2005-01-01","Confraternizacao Universal","BR",2005 +"2005-02-07","Carnaval","BR",2005 +"2005-02-08","Carnaval","BR",2005 +"2005-02-09","Inicio da Quaresma","BR",2005 +"2005-03-25","Sexta-feira Santa","BR",2005 +"2005-04-21","Tiradentes","BR",2005 +"2005-05-01","Dia do Trabalhador","BR",2005 +"2005-05-26","Corpus Christi","BR",2005 +"2005-09-07","Independencia do Brasil","BR",2005 +"2005-10-12","Nossa Senhora Aparecida","BR",2005 +"2005-10-28","Dia do Servidor Publico","BR",2005 +"2005-11-02","Finados","BR",2005 +"2005-11-15","Proclamacao da Republica","BR",2005 +"2005-12-24","Vespera de Natal","BR",2005 +"2005-12-25","Natal","BR",2005 +"2005-12-31","Vespera de Ano-Novo","BR",2005 +"2006-01-01","Confraternizacao Universal","BR",2006 +"2006-02-27","Carnaval","BR",2006 +"2006-02-28","Carnaval","BR",2006 +"2006-03-01","Inicio da Quaresma","BR",2006 +"2006-04-14","Sexta-feira Santa","BR",2006 +"2006-04-21","Tiradentes","BR",2006 +"2006-05-01","Dia do Trabalhador","BR",2006 +"2006-06-15","Corpus Christi","BR",2006 +"2006-09-07","Independencia do Brasil","BR",2006 +"2006-10-12","Nossa Senhora Aparecida","BR",2006 +"2006-10-28","Dia do Servidor Publico","BR",2006 +"2006-11-02","Finados","BR",2006 +"2006-11-15","Proclamacao da Republica","BR",2006 +"2006-12-24","Vespera de Natal","BR",2006 +"2006-12-25","Natal","BR",2006 +"2006-12-31","Vespera de Ano-Novo","BR",2006 +"2007-01-01","Confraternizacao Universal","BR",2007 +"2007-02-19","Carnaval","BR",2007 +"2007-02-20","Carnaval","BR",2007 +"2007-02-21","Inicio da Quaresma","BR",2007 +"2007-04-06","Sexta-feira Santa","BR",2007 +"2007-04-21","Tiradentes","BR",2007 +"2007-05-01","Dia do Trabalhador","BR",2007 +"2007-06-07","Corpus Christi","BR",2007 +"2007-09-07","Independencia do Brasil","BR",2007 +"2007-10-12","Nossa Senhora Aparecida","BR",2007 +"2007-10-28","Dia do Servidor Publico","BR",2007 +"2007-11-02","Finados","BR",2007 +"2007-11-15","Proclamacao da Republica","BR",2007 +"2007-12-24","Vespera de Natal","BR",2007 +"2007-12-25","Natal","BR",2007 +"2007-12-31","Vespera de Ano-Novo","BR",2007 +"2008-01-01","Confraternizacao Universal","BR",2008 +"2008-02-04","Carnaval","BR",2008 +"2008-02-05","Carnaval","BR",2008 +"2008-02-06","Inicio da Quaresma","BR",2008 +"2008-03-21","Sexta-feira Santa","BR",2008 +"2008-04-21","Tiradentes","BR",2008 +"2008-05-01","Dia do Trabalhador","BR",2008 +"2008-05-22","Corpus Christi","BR",2008 +"2008-09-07","Independencia do Brasil","BR",2008 +"2008-10-12","Nossa Senhora Aparecida","BR",2008 +"2008-10-28","Dia do Servidor Publico","BR",2008 +"2008-11-02","Finados","BR",2008 +"2008-11-15","Proclamacao da Republica","BR",2008 +"2008-12-24","Vespera de Natal","BR",2008 +"2008-12-25","Natal","BR",2008 +"2008-12-31","Vespera de Ano-Novo","BR",2008 +"2009-01-01","Confraternizacao Universal","BR",2009 +"2009-02-23","Carnaval","BR",2009 +"2009-02-24","Carnaval","BR",2009 +"2009-02-25","Inicio da Quaresma","BR",2009 +"2009-04-10","Sexta-feira Santa","BR",2009 +"2009-04-21","Tiradentes","BR",2009 +"2009-05-01","Dia do Trabalhador","BR",2009 +"2009-06-11","Corpus Christi","BR",2009 +"2009-09-07","Independencia do Brasil","BR",2009 +"2009-10-12","Nossa Senhora Aparecida","BR",2009 +"2009-10-28","Dia do Servidor Publico","BR",2009 +"2009-11-02","Finados","BR",2009 +"2009-11-15","Proclamacao da Republica","BR",2009 +"2009-12-24","Vespera de Natal","BR",2009 +"2009-12-25","Natal","BR",2009 +"2009-12-31","Vespera de Ano-Novo","BR",2009 +"2010-01-01","Confraternizacao Universal","BR",2010 +"2010-02-15","Carnaval","BR",2010 +"2010-02-16","Carnaval","BR",2010 +"2010-02-17","Inicio da Quaresma","BR",2010 +"2010-04-02","Sexta-feira Santa","BR",2010 +"2010-04-21","Tiradentes","BR",2010 +"2010-05-01","Dia do Trabalhador","BR",2010 +"2010-06-03","Corpus Christi","BR",2010 +"2010-09-07","Independencia do Brasil","BR",2010 +"2010-10-12","Nossa Senhora Aparecida","BR",2010 +"2010-10-28","Dia do Servidor Publico","BR",2010 +"2010-11-02","Finados","BR",2010 +"2010-11-15","Proclamacao da Republica","BR",2010 +"2010-12-24","Vespera de Natal","BR",2010 +"2010-12-25","Natal","BR",2010 +"2010-12-31","Vespera de Ano-Novo","BR",2010 +"2011-01-01","Confraternizacao Universal","BR",2011 +"2011-03-07","Carnaval","BR",2011 +"2011-03-08","Carnaval","BR",2011 +"2011-03-09","Inicio da Quaresma","BR",2011 +"2011-04-21","Tiradentes","BR",2011 +"2011-04-22","Sexta-feira Santa","BR",2011 +"2011-05-01","Dia do Trabalhador","BR",2011 +"2011-06-23","Corpus Christi","BR",2011 +"2011-09-07","Independencia do Brasil","BR",2011 +"2011-10-12","Nossa Senhora Aparecida","BR",2011 +"2011-10-28","Dia do Servidor Publico","BR",2011 +"2011-11-02","Finados","BR",2011 +"2011-11-15","Proclamacao da Republica","BR",2011 +"2011-12-24","Vespera de Natal","BR",2011 +"2011-12-25","Natal","BR",2011 +"2011-12-31","Vespera de Ano-Novo","BR",2011 +"2012-01-01","Confraternizacao Universal","BR",2012 +"2012-02-20","Carnaval","BR",2012 +"2012-02-21","Carnaval","BR",2012 +"2012-02-22","Inicio da Quaresma","BR",2012 +"2012-04-06","Sexta-feira Santa","BR",2012 +"2012-04-21","Tiradentes","BR",2012 +"2012-05-01","Dia do Trabalhador","BR",2012 +"2012-06-07","Corpus Christi","BR",2012 +"2012-09-07","Independencia do Brasil","BR",2012 +"2012-10-12","Nossa Senhora Aparecida","BR",2012 +"2012-10-28","Dia do Servidor Publico","BR",2012 +"2012-11-02","Finados","BR",2012 +"2012-11-15","Proclamacao da Republica","BR",2012 +"2012-12-24","Vespera de Natal","BR",2012 +"2012-12-25","Natal","BR",2012 +"2012-12-31","Vespera de Ano-Novo","BR",2012 +"2013-01-01","Confraternizacao Universal","BR",2013 +"2013-02-11","Carnaval","BR",2013 +"2013-02-12","Carnaval","BR",2013 +"2013-02-13","Inicio da Quaresma","BR",2013 +"2013-03-29","Sexta-feira Santa","BR",2013 +"2013-04-21","Tiradentes","BR",2013 +"2013-05-01","Dia do Trabalhador","BR",2013 +"2013-05-30","Corpus Christi","BR",2013 +"2013-09-07","Independencia do Brasil","BR",2013 +"2013-10-12","Nossa Senhora Aparecida","BR",2013 +"2013-10-28","Dia do Servidor Publico","BR",2013 +"2013-11-02","Finados","BR",2013 +"2013-11-15","Proclamacao da Republica","BR",2013 +"2013-12-24","Vespera de Natal","BR",2013 +"2013-12-25","Natal","BR",2013 +"2013-12-31","Vespera de Ano-Novo","BR",2013 +"2014-01-01","Confraternizacao Universal","BR",2014 +"2014-03-03","Carnaval","BR",2014 +"2014-03-04","Carnaval","BR",2014 +"2014-03-05","Inicio da Quaresma","BR",2014 +"2014-04-18","Sexta-feira Santa","BR",2014 +"2014-04-21","Tiradentes","BR",2014 +"2014-05-01","Dia do Trabalhador","BR",2014 +"2014-06-19","Corpus Christi","BR",2014 +"2014-09-07","Independencia do Brasil","BR",2014 +"2014-10-12","Nossa Senhora Aparecida","BR",2014 +"2014-10-28","Dia do Servidor Publico","BR",2014 +"2014-11-02","Finados","BR",2014 +"2014-11-15","Proclamacao da Republica","BR",2014 +"2014-12-24","Vespera de Natal","BR",2014 +"2014-12-25","Natal","BR",2014 +"2014-12-31","Vespera de Ano-Novo","BR",2014 +"2015-01-01","Confraternizacao Universal","BR",2015 +"2015-02-16","Carnaval","BR",2015 +"2015-02-17","Carnaval","BR",2015 +"2015-02-18","Inicio da Quaresma","BR",2015 +"2015-04-03","Sexta-feira Santa","BR",2015 +"2015-04-21","Tiradentes","BR",2015 +"2015-05-01","Dia do Trabalhador","BR",2015 +"2015-06-04","Corpus Christi","BR",2015 +"2015-09-07","Independencia do Brasil","BR",2015 +"2015-10-12","Nossa Senhora Aparecida","BR",2015 +"2015-10-28","Dia do Servidor Publico","BR",2015 +"2015-11-02","Finados","BR",2015 +"2015-11-15","Proclamacao da Republica","BR",2015 +"2015-12-24","Vespera de Natal","BR",2015 +"2015-12-25","Natal","BR",2015 +"2015-12-31","Vespera de Ano-Novo","BR",2015 +"2016-01-01","Confraternizacao Universal","BR",2016 +"2016-02-08","Carnaval","BR",2016 +"2016-02-09","Carnaval","BR",2016 +"2016-02-10","Inicio da Quaresma","BR",2016 +"2016-03-25","Sexta-feira Santa","BR",2016 +"2016-04-21","Tiradentes","BR",2016 +"2016-05-01","Dia do Trabalhador","BR",2016 +"2016-05-26","Corpus Christi","BR",2016 +"2016-09-07","Independencia do Brasil","BR",2016 +"2016-10-12","Nossa Senhora Aparecida","BR",2016 +"2016-10-28","Dia do Servidor Publico","BR",2016 +"2016-11-02","Finados","BR",2016 +"2016-11-15","Proclamacao da Republica","BR",2016 +"2016-12-24","Vespera de Natal","BR",2016 +"2016-12-25","Natal","BR",2016 +"2016-12-31","Vespera de Ano-Novo","BR",2016 +"2017-01-01","Confraternizacao Universal","BR",2017 +"2017-02-27","Carnaval","BR",2017 +"2017-02-28","Carnaval","BR",2017 +"2017-03-01","Inicio da Quaresma","BR",2017 +"2017-04-14","Sexta-feira Santa","BR",2017 +"2017-04-21","Tiradentes","BR",2017 +"2017-05-01","Dia do Trabalhador","BR",2017 +"2017-06-15","Corpus Christi","BR",2017 +"2017-09-07","Independencia do Brasil","BR",2017 +"2017-10-12","Nossa Senhora Aparecida","BR",2017 +"2017-10-28","Dia do Servidor Publico","BR",2017 +"2017-11-02","Finados","BR",2017 +"2017-11-15","Proclamacao da Republica","BR",2017 +"2017-12-24","Vespera de Natal","BR",2017 +"2017-12-25","Natal","BR",2017 +"2017-12-31","Vespera de Ano-Novo","BR",2017 +"2018-01-01","Confraternizacao Universal","BR",2018 +"2018-02-12","Carnaval","BR",2018 +"2018-02-13","Carnaval","BR",2018 +"2018-02-14","Inicio da Quaresma","BR",2018 +"2018-03-30","Sexta-feira Santa","BR",2018 +"2018-04-21","Tiradentes","BR",2018 +"2018-05-01","Dia do Trabalhador","BR",2018 +"2018-05-31","Corpus Christi","BR",2018 +"2018-09-07","Independencia do Brasil","BR",2018 +"2018-10-12","Nossa Senhora Aparecida","BR",2018 +"2018-10-28","Dia do Servidor Publico","BR",2018 +"2018-11-02","Finados","BR",2018 +"2018-11-15","Proclamacao da Republica","BR",2018 +"2018-12-24","Vespera de Natal","BR",2018 +"2018-12-25","Natal","BR",2018 +"2018-12-31","Vespera de Ano-Novo","BR",2018 +"2019-01-01","Confraternizacao Universal","BR",2019 +"2019-03-04","Carnaval","BR",2019 +"2019-03-05","Carnaval","BR",2019 +"2019-03-06","Inicio da Quaresma","BR",2019 +"2019-04-19","Sexta-feira Santa","BR",2019 +"2019-04-21","Tiradentes","BR",2019 +"2019-05-01","Dia do Trabalhador","BR",2019 +"2019-06-20","Corpus Christi","BR",2019 +"2019-09-07","Independencia do Brasil","BR",2019 +"2019-10-12","Nossa Senhora Aparecida","BR",2019 +"2019-10-28","Dia do Servidor Publico","BR",2019 +"2019-11-02","Finados","BR",2019 +"2019-11-15","Proclamacao da Republica","BR",2019 +"2019-12-24","Vespera de Natal","BR",2019 +"2019-12-25","Natal","BR",2019 +"2019-12-31","Vespera de Ano-Novo","BR",2019 +"2020-01-01","Confraternizacao Universal","BR",2020 +"2020-02-24","Carnaval","BR",2020 +"2020-02-25","Carnaval","BR",2020 +"2020-02-26","Inicio da Quaresma","BR",2020 +"2020-04-10","Sexta-feira Santa","BR",2020 +"2020-04-21","Tiradentes","BR",2020 +"2020-05-01","Dia do Trabalhador","BR",2020 +"2020-06-11","Corpus Christi","BR",2020 +"2020-09-07","Independencia do Brasil","BR",2020 +"2020-10-12","Nossa Senhora Aparecida","BR",2020 +"2020-10-28","Dia do Servidor Publico","BR",2020 +"2020-11-02","Finados","BR",2020 +"2020-11-15","Proclamacao da Republica","BR",2020 +"2020-12-24","Vespera de Natal","BR",2020 +"2020-12-25","Natal","BR",2020 +"2020-12-31","Vespera de Ano-Novo","BR",2020 +"2021-01-01","Confraternizacao Universal","BR",2021 +"2021-02-15","Carnaval","BR",2021 +"2021-02-16","Carnaval","BR",2021 +"2021-02-17","Inicio da Quaresma","BR",2021 +"2021-04-02","Sexta-feira Santa","BR",2021 +"2021-04-21","Tiradentes","BR",2021 +"2021-05-01","Dia do Trabalhador","BR",2021 +"2021-06-03","Corpus Christi","BR",2021 +"2021-09-07","Independencia do Brasil","BR",2021 +"2021-10-12","Nossa Senhora Aparecida","BR",2021 +"2021-10-28","Dia do Servidor Publico","BR",2021 +"2021-11-02","Finados","BR",2021 +"2021-11-15","Proclamacao da Republica","BR",2021 +"2021-12-24","Vespera de Natal","BR",2021 +"2021-12-25","Natal","BR",2021 +"2021-12-31","Vespera de Ano-Novo","BR",2021 +"2022-01-01","Confraternizacao Universal","BR",2022 +"2022-02-28","Carnaval","BR",2022 +"2022-03-01","Carnaval","BR",2022 +"2022-03-02","Inicio da Quaresma","BR",2022 +"2022-04-15","Sexta-feira Santa","BR",2022 +"2022-04-21","Tiradentes","BR",2022 +"2022-05-01","Dia do Trabalhador","BR",2022 +"2022-06-16","Corpus Christi","BR",2022 +"2022-09-07","Independencia do Brasil","BR",2022 +"2022-10-12","Nossa Senhora Aparecida","BR",2022 +"2022-10-28","Dia do Servidor Publico","BR",2022 +"2022-11-02","Finados","BR",2022 +"2022-11-15","Proclamacao da Republica","BR",2022 +"2022-12-24","Vespera de Natal","BR",2022 +"2022-12-25","Natal","BR",2022 +"2022-12-31","Vespera de Ano-Novo","BR",2022 +"2023-01-01","Confraternizacao Universal","BR",2023 +"2023-02-20","Carnaval","BR",2023 +"2023-02-21","Carnaval","BR",2023 +"2023-02-22","Inicio da Quaresma","BR",2023 +"2023-04-07","Sexta-feira Santa","BR",2023 +"2023-04-21","Tiradentes","BR",2023 +"2023-05-01","Dia do Trabalhador","BR",2023 +"2023-06-08","Corpus Christi","BR",2023 +"2023-09-07","Independencia do Brasil","BR",2023 +"2023-10-12","Nossa Senhora Aparecida","BR",2023 +"2023-10-28","Dia do Servidor Publico","BR",2023 +"2023-11-02","Finados","BR",2023 +"2023-11-15","Proclamacao da Republica","BR",2023 +"2023-12-24","Vespera de Natal","BR",2023 +"2023-12-25","Natal","BR",2023 +"2023-12-31","Vespera de Ano-Novo","BR",2023 +"2024-01-01","Confraternizacao Universal","BR",2024 +"2024-02-12","Carnaval","BR",2024 +"2024-02-13","Carnaval","BR",2024 +"2024-02-14","Inicio da Quaresma","BR",2024 +"2024-03-29","Sexta-feira Santa","BR",2024 +"2024-04-21","Tiradentes","BR",2024 +"2024-05-01","Dia do Trabalhador","BR",2024 +"2024-05-30","Corpus Christi","BR",2024 +"2024-09-07","Independencia do Brasil","BR",2024 +"2024-10-12","Nossa Senhora Aparecida","BR",2024 +"2024-10-28","Dia do Servidor Publico","BR",2024 +"2024-11-02","Finados","BR",2024 +"2024-11-15","Proclamacao da Republica","BR",2024 +"2024-12-24","Vespera de Natal","BR",2024 +"2024-12-25","Natal","BR",2024 +"2024-12-31","Vespera de Ano-Novo","BR",2024 +"2025-01-01","Confraternizacao Universal","BR",2025 +"2025-03-03","Carnaval","BR",2025 +"2025-03-04","Carnaval","BR",2025 +"2025-03-05","Inicio da Quaresma","BR",2025 +"2025-04-18","Sexta-feira Santa","BR",2025 +"2025-04-21","Tiradentes","BR",2025 +"2025-05-01","Dia do Trabalhador","BR",2025 +"2025-06-19","Corpus Christi","BR",2025 +"2025-09-07","Independencia do Brasil","BR",2025 +"2025-10-12","Nossa Senhora Aparecida","BR",2025 +"2025-10-28","Dia do Servidor Publico","BR",2025 +"2025-11-02","Finados","BR",2025 +"2025-11-15","Proclamacao da Republica","BR",2025 +"2025-12-24","Vespera de Natal","BR",2025 +"2025-12-25","Natal","BR",2025 +"2025-12-31","Vespera de Ano-Novo","BR",2025 +"2026-01-01","Confraternizacao Universal","BR",2026 +"2026-02-16","Carnaval","BR",2026 +"2026-02-17","Carnaval","BR",2026 +"2026-02-18","Inicio da Quaresma","BR",2026 +"2026-04-03","Sexta-feira Santa","BR",2026 +"2026-04-21","Tiradentes","BR",2026 +"2026-05-01","Dia do Trabalhador","BR",2026 +"2026-06-04","Corpus Christi","BR",2026 +"2026-09-07","Independencia do Brasil","BR",2026 +"2026-10-12","Nossa Senhora Aparecida","BR",2026 +"2026-10-28","Dia do Servidor Publico","BR",2026 +"2026-11-02","Finados","BR",2026 +"2026-11-15","Proclamacao da Republica","BR",2026 +"2026-12-24","Vespera de Natal","BR",2026 +"2026-12-25","Natal","BR",2026 +"2026-12-31","Vespera de Ano-Novo","BR",2026 +"2027-01-01","Confraternizacao Universal","BR",2027 +"2027-02-08","Carnaval","BR",2027 +"2027-02-09","Carnaval","BR",2027 +"2027-02-10","Inicio da Quaresma","BR",2027 +"2027-03-26","Sexta-feira Santa","BR",2027 +"2027-04-21","Tiradentes","BR",2027 +"2027-05-01","Dia do Trabalhador","BR",2027 +"2027-05-27","Corpus Christi","BR",2027 +"2027-09-07","Independencia do Brasil","BR",2027 +"2027-10-12","Nossa Senhora Aparecida","BR",2027 +"2027-10-28","Dia do Servidor Publico","BR",2027 +"2027-11-02","Finados","BR",2027 +"2027-11-15","Proclamacao da Republica","BR",2027 +"2027-12-24","Vespera de Natal","BR",2027 +"2027-12-25","Natal","BR",2027 +"2027-12-31","Vespera de Ano-Novo","BR",2027 +"2028-01-01","Confraternizacao Universal","BR",2028 +"2028-02-28","Carnaval","BR",2028 +"2028-02-29","Carnaval","BR",2028 +"2028-03-01","Inicio da Quaresma","BR",2028 +"2028-04-14","Sexta-feira Santa","BR",2028 +"2028-04-21","Tiradentes","BR",2028 +"2028-05-01","Dia do Trabalhador","BR",2028 +"2028-06-15","Corpus Christi","BR",2028 +"2028-09-07","Independencia do Brasil","BR",2028 +"2028-10-12","Nossa Senhora Aparecida","BR",2028 +"2028-10-28","Dia do Servidor Publico","BR",2028 +"2028-11-02","Finados","BR",2028 +"2028-11-15","Proclamacao da Republica","BR",2028 +"2028-12-24","Vespera de Natal","BR",2028 +"2028-12-25","Natal","BR",2028 +"2028-12-31","Vespera de Ano-Novo","BR",2028 +"2029-01-01","Confraternizacao Universal","BR",2029 +"2029-02-12","Carnaval","BR",2029 +"2029-02-13","Carnaval","BR",2029 +"2029-02-14","Inicio da Quaresma","BR",2029 +"2029-03-30","Sexta-feira Santa","BR",2029 +"2029-04-21","Tiradentes","BR",2029 +"2029-05-01","Dia do Trabalhador","BR",2029 +"2029-05-31","Corpus Christi","BR",2029 +"2029-09-07","Independencia do Brasil","BR",2029 +"2029-10-12","Nossa Senhora Aparecida","BR",2029 +"2029-10-28","Dia do Servidor Publico","BR",2029 +"2029-11-02","Finados","BR",2029 +"2029-11-15","Proclamacao da Republica","BR",2029 +"2029-12-24","Vespera de Natal","BR",2029 +"2029-12-25","Natal","BR",2029 +"2029-12-31","Vespera de Ano-Novo","BR",2029 +"2030-01-01","Confraternizacao Universal","BR",2030 +"2030-03-04","Carnaval","BR",2030 +"2030-03-05","Carnaval","BR",2030 +"2030-03-06","Inicio da Quaresma","BR",2030 +"2030-04-19","Sexta-feira Santa","BR",2030 +"2030-04-21","Tiradentes","BR",2030 +"2030-05-01","Dia do Trabalhador","BR",2030 +"2030-06-20","Corpus Christi","BR",2030 +"2030-09-07","Independencia do Brasil","BR",2030 +"2030-10-12","Nossa Senhora Aparecida","BR",2030 +"2030-10-28","Dia do Servidor Publico","BR",2030 +"2030-11-02","Finados","BR",2030 +"2030-11-15","Proclamacao da Republica","BR",2030 +"2030-12-24","Vespera de Natal","BR",2030 +"2030-12-25","Natal","BR",2030 +"2030-12-31","Vespera de Ano-Novo","BR",2030 +"2031-01-01","Confraternizacao Universal","BR",2031 +"2031-02-24","Carnaval","BR",2031 +"2031-02-25","Carnaval","BR",2031 +"2031-02-26","Inicio da Quaresma","BR",2031 +"2031-04-11","Sexta-feira Santa","BR",2031 +"2031-04-21","Tiradentes","BR",2031 +"2031-05-01","Dia do Trabalhador","BR",2031 +"2031-06-12","Corpus Christi","BR",2031 +"2031-09-07","Independencia do Brasil","BR",2031 +"2031-10-12","Nossa Senhora Aparecida","BR",2031 +"2031-10-28","Dia do Servidor Publico","BR",2031 +"2031-11-02","Finados","BR",2031 +"2031-11-15","Proclamacao da Republica","BR",2031 +"2031-12-24","Vespera de Natal","BR",2031 +"2031-12-25","Natal","BR",2031 +"2031-12-31","Vespera de Ano-Novo","BR",2031 +"2032-01-01","Confraternizacao Universal","BR",2032 +"2032-02-09","Carnaval","BR",2032 +"2032-02-10","Carnaval","BR",2032 +"2032-02-11","Inicio da Quaresma","BR",2032 +"2032-03-26","Sexta-feira Santa","BR",2032 +"2032-04-21","Tiradentes","BR",2032 +"2032-05-01","Dia do Trabalhador","BR",2032 +"2032-05-27","Corpus Christi","BR",2032 +"2032-09-07","Independencia do Brasil","BR",2032 +"2032-10-12","Nossa Senhora Aparecida","BR",2032 +"2032-10-28","Dia do Servidor Publico","BR",2032 +"2032-11-02","Finados","BR",2032 +"2032-11-15","Proclamacao da Republica","BR",2032 +"2032-12-24","Vespera de Natal","BR",2032 +"2032-12-25","Natal","BR",2032 +"2032-12-31","Vespera de Ano-Novo","BR",2032 +"2033-01-01","Confraternizacao Universal","BR",2033 +"2033-02-28","Carnaval","BR",2033 +"2033-03-01","Carnaval","BR",2033 +"2033-03-02","Inicio da Quaresma","BR",2033 +"2033-04-15","Sexta-feira Santa","BR",2033 +"2033-04-21","Tiradentes","BR",2033 +"2033-05-01","Dia do Trabalhador","BR",2033 +"2033-06-16","Corpus Christi","BR",2033 +"2033-09-07","Independencia do Brasil","BR",2033 +"2033-10-12","Nossa Senhora Aparecida","BR",2033 +"2033-10-28","Dia do Servidor Publico","BR",2033 +"2033-11-02","Finados","BR",2033 +"2033-11-15","Proclamacao da Republica","BR",2033 +"2033-12-24","Vespera de Natal","BR",2033 +"2033-12-25","Natal","BR",2033 +"2033-12-31","Vespera de Ano-Novo","BR",2033 +"2034-01-01","Confraternizacao Universal","BR",2034 +"2034-02-20","Carnaval","BR",2034 +"2034-02-21","Carnaval","BR",2034 +"2034-02-22","Inicio da Quaresma","BR",2034 +"2034-04-07","Sexta-feira Santa","BR",2034 +"2034-04-21","Tiradentes","BR",2034 +"2034-05-01","Dia do Trabalhador","BR",2034 +"2034-06-08","Corpus Christi","BR",2034 +"2034-09-07","Independencia do Brasil","BR",2034 +"2034-10-12","Nossa Senhora Aparecida","BR",2034 +"2034-10-28","Dia do Servidor Publico","BR",2034 +"2034-11-02","Finados","BR",2034 +"2034-11-15","Proclamacao da Republica","BR",2034 +"2034-12-24","Vespera de Natal","BR",2034 +"2034-12-25","Natal","BR",2034 +"2034-12-31","Vespera de Ano-Novo","BR",2034 +"2035-01-01","Confraternizacao Universal","BR",2035 +"2035-02-05","Carnaval","BR",2035 +"2035-02-06","Carnaval","BR",2035 +"2035-02-07","Inicio da Quaresma","BR",2035 +"2035-03-23","Sexta-feira Santa","BR",2035 +"2035-04-21","Tiradentes","BR",2035 +"2035-05-01","Dia do Trabalhador","BR",2035 +"2035-05-24","Corpus Christi","BR",2035 +"2035-09-07","Independencia do Brasil","BR",2035 +"2035-10-12","Nossa Senhora Aparecida","BR",2035 +"2035-10-28","Dia do Servidor Publico","BR",2035 +"2035-11-02","Finados","BR",2035 +"2035-11-15","Proclamacao da Republica","BR",2035 +"2035-12-24","Vespera de Natal","BR",2035 +"2035-12-25","Natal","BR",2035 +"2035-12-31","Vespera de Ano-Novo","BR",2035 +"2036-01-01","Confraternizacao Universal","BR",2036 +"2036-02-25","Carnaval","BR",2036 +"2036-02-26","Carnaval","BR",2036 +"2036-02-27","Inicio da Quaresma","BR",2036 +"2036-04-11","Sexta-feira Santa","BR",2036 +"2036-04-21","Tiradentes","BR",2036 +"2036-05-01","Dia do Trabalhador","BR",2036 +"2036-06-12","Corpus Christi","BR",2036 +"2036-09-07","Independencia do Brasil","BR",2036 +"2036-10-12","Nossa Senhora Aparecida","BR",2036 +"2036-10-28","Dia do Servidor Publico","BR",2036 +"2036-11-02","Finados","BR",2036 +"2036-11-15","Proclamacao da Republica","BR",2036 +"2036-12-24","Vespera de Natal","BR",2036 +"2036-12-25","Natal","BR",2036 +"2036-12-31","Vespera de Ano-Novo","BR",2036 +"2037-01-01","Confraternizacao Universal","BR",2037 +"2037-02-16","Carnaval","BR",2037 +"2037-02-17","Carnaval","BR",2037 +"2037-02-18","Inicio da Quaresma","BR",2037 +"2037-04-03","Sexta-feira Santa","BR",2037 +"2037-04-21","Tiradentes","BR",2037 +"2037-05-01","Dia do Trabalhador","BR",2037 +"2037-06-04","Corpus Christi","BR",2037 +"2037-09-07","Independencia do Brasil","BR",2037 +"2037-10-12","Nossa Senhora Aparecida","BR",2037 +"2037-10-28","Dia do Servidor Publico","BR",2037 +"2037-11-02","Finados","BR",2037 +"2037-11-15","Proclamacao da Republica","BR",2037 +"2037-12-24","Vespera de Natal","BR",2037 +"2037-12-25","Natal","BR",2037 +"2037-12-31","Vespera de Ano-Novo","BR",2037 +"2038-01-01","Confraternizacao Universal","BR",2038 +"2038-03-08","Carnaval","BR",2038 +"2038-03-09","Carnaval","BR",2038 +"2038-03-10","Inicio da Quaresma","BR",2038 +"2038-04-21","Tiradentes","BR",2038 +"2038-04-23","Sexta-feira Santa","BR",2038 +"2038-05-01","Dia do Trabalhador","BR",2038 +"2038-06-24","Corpus Christi","BR",2038 +"2038-09-07","Independencia do Brasil","BR",2038 +"2038-10-12","Nossa Senhora Aparecida","BR",2038 +"2038-10-28","Dia do Servidor Publico","BR",2038 +"2038-11-02","Finados","BR",2038 +"2038-11-15","Proclamacao da Republica","BR",2038 +"2038-12-24","Vespera de Natal","BR",2038 +"2038-12-25","Natal","BR",2038 +"2038-12-31","Vespera de Ano-Novo","BR",2038 +"2039-01-01","Confraternizacao Universal","BR",2039 +"2039-02-21","Carnaval","BR",2039 +"2039-02-22","Carnaval","BR",2039 +"2039-02-23","Inicio da Quaresma","BR",2039 +"2039-04-08","Sexta-feira Santa","BR",2039 +"2039-04-21","Tiradentes","BR",2039 +"2039-05-01","Dia do Trabalhador","BR",2039 +"2039-06-09","Corpus Christi","BR",2039 +"2039-09-07","Independencia do Brasil","BR",2039 +"2039-10-12","Nossa Senhora Aparecida","BR",2039 +"2039-10-28","Dia do Servidor Publico","BR",2039 +"2039-11-02","Finados","BR",2039 +"2039-11-15","Proclamacao da Republica","BR",2039 +"2039-12-24","Vespera de Natal","BR",2039 +"2039-12-25","Natal","BR",2039 +"2039-12-31","Vespera de Ano-Novo","BR",2039 +"2040-01-01","Confraternizacao Universal","BR",2040 +"2040-02-13","Carnaval","BR",2040 +"2040-02-14","Carnaval","BR",2040 +"2040-02-15","Inicio da Quaresma","BR",2040 +"2040-03-30","Sexta-feira Santa","BR",2040 +"2040-04-21","Tiradentes","BR",2040 +"2040-05-01","Dia do Trabalhador","BR",2040 +"2040-05-31","Corpus Christi","BR",2040 +"2040-09-07","Independencia do Brasil","BR",2040 +"2040-10-12","Nossa Senhora Aparecida","BR",2040 +"2040-10-28","Dia do Servidor Publico","BR",2040 +"2040-11-02","Finados","BR",2040 +"2040-11-15","Proclamacao da Republica","BR",2040 +"2040-12-24","Vespera de Natal","BR",2040 +"2040-12-25","Natal","BR",2040 +"2040-12-31","Vespera de Ano-Novo","BR",2040 +"2041-01-01","Confraternizacao Universal","BR",2041 +"2041-03-04","Carnaval","BR",2041 +"2041-03-05","Carnaval","BR",2041 +"2041-03-06","Inicio da Quaresma","BR",2041 +"2041-04-19","Sexta-feira Santa","BR",2041 +"2041-04-21","Tiradentes","BR",2041 +"2041-05-01","Dia do Trabalhador","BR",2041 +"2041-06-20","Corpus Christi","BR",2041 +"2041-09-07","Independencia do Brasil","BR",2041 +"2041-10-12","Nossa Senhora Aparecida","BR",2041 +"2041-10-28","Dia do Servidor Publico","BR",2041 +"2041-11-02","Finados","BR",2041 +"2041-11-15","Proclamacao da Republica","BR",2041 +"2041-12-24","Vespera de Natal","BR",2041 +"2041-12-25","Natal","BR",2041 +"2041-12-31","Vespera de Ano-Novo","BR",2041 +"2042-01-01","Confraternizacao Universal","BR",2042 +"2042-02-17","Carnaval","BR",2042 +"2042-02-18","Carnaval","BR",2042 +"2042-02-19","Inicio da Quaresma","BR",2042 +"2042-04-04","Sexta-feira Santa","BR",2042 +"2042-04-21","Tiradentes","BR",2042 +"2042-05-01","Dia do Trabalhador","BR",2042 +"2042-06-05","Corpus Christi","BR",2042 +"2042-09-07","Independencia do Brasil","BR",2042 +"2042-10-12","Nossa Senhora Aparecida","BR",2042 +"2042-10-28","Dia do Servidor Publico","BR",2042 +"2042-11-02","Finados","BR",2042 +"2042-11-15","Proclamacao da Republica","BR",2042 +"2042-12-24","Vespera de Natal","BR",2042 +"2042-12-25","Natal","BR",2042 +"2042-12-31","Vespera de Ano-Novo","BR",2042 +"2043-01-01","Confraternizacao Universal","BR",2043 +"2043-02-09","Carnaval","BR",2043 +"2043-02-10","Carnaval","BR",2043 +"2043-02-11","Inicio da Quaresma","BR",2043 +"2043-03-27","Sexta-feira Santa","BR",2043 +"2043-04-21","Tiradentes","BR",2043 +"2043-05-01","Dia do Trabalhador","BR",2043 +"2043-05-28","Corpus Christi","BR",2043 +"2043-09-07","Independencia do Brasil","BR",2043 +"2043-10-12","Nossa Senhora Aparecida","BR",2043 +"2043-10-28","Dia do Servidor Publico","BR",2043 +"2043-11-02","Finados","BR",2043 +"2043-11-15","Proclamacao da Republica","BR",2043 +"2043-12-24","Vespera de Natal","BR",2043 +"2043-12-25","Natal","BR",2043 +"2043-12-31","Vespera de Ano-Novo","BR",2043 +"2044-01-01","Confraternizacao Universal","BR",2044 +"2044-02-29","Carnaval","BR",2044 +"2044-03-01","Carnaval","BR",2044 +"2044-03-02","Inicio da Quaresma","BR",2044 +"2044-04-15","Sexta-feira Santa","BR",2044 +"2044-04-21","Tiradentes","BR",2044 +"2044-05-01","Dia do Trabalhador","BR",2044 +"2044-06-16","Corpus Christi","BR",2044 +"2044-09-07","Independencia do Brasil","BR",2044 +"2044-10-12","Nossa Senhora Aparecida","BR",2044 +"2044-10-28","Dia do Servidor Publico","BR",2044 +"2044-11-02","Finados","BR",2044 +"2044-11-15","Proclamacao da Republica","BR",2044 +"2044-12-24","Vespera de Natal","BR",2044 +"2044-12-25","Natal","BR",2044 +"2044-12-31","Vespera de Ano-Novo","BR",2044 +"1995-01-01","New Year's Day","BW",1995 +"1995-01-02","New Year's Day Holiday","BW",1995 +"1995-01-03","New Year's Day (Observed)","BW",1995 +"1995-04-14","Good Friday","BW",1995 +"1995-04-15","Holy Saturday","BW",1995 +"1995-04-17","Easter Monday","BW",1995 +"1995-05-01","Labour Day","BW",1995 +"1995-05-25","Ascension Day","BW",1995 +"1995-07-01","Sir Seretse Khama Day","BW",1995 +"1995-07-17","President's Day","BW",1995 +"1995-07-18","President's Day Holiday","BW",1995 +"1995-09-30","Botswana Day","BW",1995 +"1995-10-01","Botswana Day Holiday","BW",1995 +"1995-10-02","Botswana Day Holiday (Observed)","BW",1995 +"1995-12-25","Christmas Day","BW",1995 +"1995-12-26","Boxing Day","BW",1995 +"1996-01-01","New Year's Day","BW",1996 +"1996-01-02","New Year's Day Holiday","BW",1996 +"1996-04-05","Good Friday","BW",1996 +"1996-04-06","Holy Saturday","BW",1996 +"1996-04-08","Easter Monday","BW",1996 +"1996-05-01","Labour Day","BW",1996 +"1996-05-16","Ascension Day","BW",1996 +"1996-07-01","Sir Seretse Khama Day","BW",1996 +"1996-07-15","President's Day","BW",1996 +"1996-07-16","President's Day Holiday","BW",1996 +"1996-09-30","Botswana Day","BW",1996 +"1996-10-01","Botswana Day Holiday","BW",1996 +"1996-12-25","Christmas Day","BW",1996 +"1996-12-26","Boxing Day","BW",1996 +"1997-01-01","New Year's Day","BW",1997 +"1997-01-02","New Year's Day Holiday","BW",1997 +"1997-03-28","Good Friday","BW",1997 +"1997-03-29","Holy Saturday","BW",1997 +"1997-03-31","Easter Monday","BW",1997 +"1997-05-01","Labour Day","BW",1997 +"1997-05-08","Ascension Day","BW",1997 +"1997-07-01","Sir Seretse Khama Day","BW",1997 +"1997-07-21","President's Day","BW",1997 +"1997-07-22","President's Day Holiday","BW",1997 +"1997-09-30","Botswana Day","BW",1997 +"1997-10-01","Botswana Day Holiday","BW",1997 +"1997-12-25","Christmas Day","BW",1997 +"1997-12-26","Boxing Day","BW",1997 +"1998-01-01","New Year's Day","BW",1998 +"1998-01-02","New Year's Day Holiday","BW",1998 +"1998-04-10","Good Friday","BW",1998 +"1998-04-11","Holy Saturday","BW",1998 +"1998-04-13","Easter Monday","BW",1998 +"1998-05-01","Labour Day","BW",1998 +"1998-05-21","Ascension Day","BW",1998 +"1998-07-01","Sir Seretse Khama Day","BW",1998 +"1998-07-20","President's Day","BW",1998 +"1998-07-21","President's Day Holiday","BW",1998 +"1998-09-30","Botswana Day","BW",1998 +"1998-10-01","Botswana Day Holiday","BW",1998 +"1998-12-25","Christmas Day","BW",1998 +"1998-12-26","Boxing Day","BW",1998 +"1999-01-01","New Year's Day","BW",1999 +"1999-01-02","New Year's Day Holiday","BW",1999 +"1999-04-02","Good Friday","BW",1999 +"1999-04-03","Holy Saturday","BW",1999 +"1999-04-05","Easter Monday","BW",1999 +"1999-05-01","Labour Day","BW",1999 +"1999-05-13","Ascension Day","BW",1999 +"1999-07-01","Sir Seretse Khama Day","BW",1999 +"1999-07-19","President's Day","BW",1999 +"1999-07-20","President's Day Holiday","BW",1999 +"1999-09-30","Botswana Day","BW",1999 +"1999-10-01","Botswana Day Holiday","BW",1999 +"1999-12-25","Christmas Day","BW",1999 +"1999-12-26","Boxing Day","BW",1999 +"1999-12-27","Boxing Day (Observed)","BW",1999 +"2000-01-01","New Year's Day","BW",2000 +"2000-01-02","New Year's Day Holiday","BW",2000 +"2000-01-03","New Year's Day Holiday (Observed)","BW",2000 +"2000-04-21","Good Friday","BW",2000 +"2000-04-22","Holy Saturday","BW",2000 +"2000-04-24","Easter Monday","BW",2000 +"2000-05-01","Labour Day","BW",2000 +"2000-06-01","Ascension Day","BW",2000 +"2000-07-01","Sir Seretse Khama Day","BW",2000 +"2000-07-17","President's Day","BW",2000 +"2000-07-18","President's Day Holiday","BW",2000 +"2000-09-30","Botswana Day","BW",2000 +"2000-10-01","Botswana Day Holiday","BW",2000 +"2000-10-02","Botswana Day Holiday (Observed)","BW",2000 +"2000-12-25","Christmas Day","BW",2000 +"2000-12-26","Boxing Day","BW",2000 +"2001-01-01","New Year's Day","BW",2001 +"2001-01-02","New Year's Day Holiday","BW",2001 +"2001-04-13","Good Friday","BW",2001 +"2001-04-14","Holy Saturday","BW",2001 +"2001-04-16","Easter Monday","BW",2001 +"2001-05-01","Labour Day","BW",2001 +"2001-05-24","Ascension Day","BW",2001 +"2001-07-01","Sir Seretse Khama Day","BW",2001 +"2001-07-02","Sir Seretse Khama Day (Observed)","BW",2001 +"2001-07-16","President's Day","BW",2001 +"2001-07-17","President's Day Holiday","BW",2001 +"2001-09-30","Botswana Day","BW",2001 +"2001-10-01","Botswana Day Holiday","BW",2001 +"2001-10-02","Botswana Day (Observed)","BW",2001 +"2001-12-25","Christmas Day","BW",2001 +"2001-12-26","Boxing Day","BW",2001 +"2002-01-01","New Year's Day","BW",2002 +"2002-01-02","New Year's Day Holiday","BW",2002 +"2002-03-29","Good Friday","BW",2002 +"2002-03-30","Holy Saturday","BW",2002 +"2002-04-01","Easter Monday","BW",2002 +"2002-05-01","Labour Day","BW",2002 +"2002-05-09","Ascension Day","BW",2002 +"2002-07-01","Sir Seretse Khama Day","BW",2002 +"2002-07-15","President's Day","BW",2002 +"2002-07-16","President's Day Holiday","BW",2002 +"2002-09-30","Botswana Day","BW",2002 +"2002-10-01","Botswana Day Holiday","BW",2002 +"2002-12-25","Christmas Day","BW",2002 +"2002-12-26","Boxing Day","BW",2002 +"2003-01-01","New Year's Day","BW",2003 +"2003-01-02","New Year's Day Holiday","BW",2003 +"2003-04-18","Good Friday","BW",2003 +"2003-04-19","Holy Saturday","BW",2003 +"2003-04-21","Easter Monday","BW",2003 +"2003-05-01","Labour Day","BW",2003 +"2003-05-29","Ascension Day","BW",2003 +"2003-07-01","Sir Seretse Khama Day","BW",2003 +"2003-07-21","President's Day","BW",2003 +"2003-07-22","President's Day Holiday","BW",2003 +"2003-09-30","Botswana Day","BW",2003 +"2003-10-01","Botswana Day Holiday","BW",2003 +"2003-12-25","Christmas Day","BW",2003 +"2003-12-26","Boxing Day","BW",2003 +"2004-01-01","New Year's Day","BW",2004 +"2004-01-02","New Year's Day Holiday","BW",2004 +"2004-04-09","Good Friday","BW",2004 +"2004-04-10","Holy Saturday","BW",2004 +"2004-04-12","Easter Monday","BW",2004 +"2004-05-01","Labour Day","BW",2004 +"2004-05-20","Ascension Day","BW",2004 +"2004-07-01","Sir Seretse Khama Day","BW",2004 +"2004-07-19","President's Day","BW",2004 +"2004-07-20","President's Day Holiday","BW",2004 +"2004-09-30","Botswana Day","BW",2004 +"2004-10-01","Botswana Day Holiday","BW",2004 +"2004-12-25","Christmas Day","BW",2004 +"2004-12-26","Boxing Day","BW",2004 +"2004-12-27","Boxing Day (Observed)","BW",2004 +"2005-01-01","New Year's Day","BW",2005 +"2005-01-02","New Year's Day Holiday","BW",2005 +"2005-01-03","New Year's Day Holiday (Observed)","BW",2005 +"2005-03-25","Good Friday","BW",2005 +"2005-03-26","Holy Saturday","BW",2005 +"2005-03-28","Easter Monday","BW",2005 +"2005-05-01","Labour Day","BW",2005 +"2005-05-02","Labour Day (Observed)","BW",2005 +"2005-05-05","Ascension Day","BW",2005 +"2005-07-01","Sir Seretse Khama Day","BW",2005 +"2005-07-18","President's Day","BW",2005 +"2005-07-19","President's Day Holiday","BW",2005 +"2005-09-30","Botswana Day","BW",2005 +"2005-10-01","Botswana Day Holiday","BW",2005 +"2005-12-25","Christmas Day","BW",2005 +"2005-12-26","Boxing Day","BW",2005 +"2005-12-27","Christmas Day (Observed)","BW",2005 +"2006-01-01","New Year's Day","BW",2006 +"2006-01-02","New Year's Day Holiday","BW",2006 +"2006-01-03","New Year's Day (Observed)","BW",2006 +"2006-04-14","Good Friday","BW",2006 +"2006-04-15","Holy Saturday","BW",2006 +"2006-04-17","Easter Monday","BW",2006 +"2006-05-01","Labour Day","BW",2006 +"2006-05-25","Ascension Day","BW",2006 +"2006-07-01","Sir Seretse Khama Day","BW",2006 +"2006-07-17","President's Day","BW",2006 +"2006-07-18","President's Day Holiday","BW",2006 +"2006-09-30","Botswana Day","BW",2006 +"2006-10-01","Botswana Day Holiday","BW",2006 +"2006-10-02","Botswana Day Holiday (Observed)","BW",2006 +"2006-12-25","Christmas Day","BW",2006 +"2006-12-26","Boxing Day","BW",2006 +"2007-01-01","New Year's Day","BW",2007 +"2007-01-02","New Year's Day Holiday","BW",2007 +"2007-04-06","Good Friday","BW",2007 +"2007-04-07","Holy Saturday","BW",2007 +"2007-04-09","Easter Monday","BW",2007 +"2007-05-01","Labour Day","BW",2007 +"2007-05-17","Ascension Day","BW",2007 +"2007-07-01","Sir Seretse Khama Day","BW",2007 +"2007-07-02","Sir Seretse Khama Day (Observed)","BW",2007 +"2007-07-16","President's Day","BW",2007 +"2007-07-17","President's Day Holiday","BW",2007 +"2007-09-30","Botswana Day","BW",2007 +"2007-10-01","Botswana Day Holiday","BW",2007 +"2007-10-02","Botswana Day (Observed)","BW",2007 +"2007-12-25","Christmas Day","BW",2007 +"2007-12-26","Boxing Day","BW",2007 +"2008-01-01","New Year's Day","BW",2008 +"2008-01-02","New Year's Day Holiday","BW",2008 +"2008-03-21","Good Friday","BW",2008 +"2008-03-22","Holy Saturday","BW",2008 +"2008-03-24","Easter Monday","BW",2008 +"2008-05-01","Ascension Day","BW",2008 +"2008-05-01","Labour Day","BW",2008 +"2008-07-01","Sir Seretse Khama Day","BW",2008 +"2008-07-21","President's Day","BW",2008 +"2008-07-22","President's Day Holiday","BW",2008 +"2008-09-30","Botswana Day","BW",2008 +"2008-10-01","Botswana Day Holiday","BW",2008 +"2008-12-25","Christmas Day","BW",2008 +"2008-12-26","Boxing Day","BW",2008 +"2009-01-01","New Year's Day","BW",2009 +"2009-01-02","New Year's Day Holiday","BW",2009 +"2009-04-10","Good Friday","BW",2009 +"2009-04-11","Holy Saturday","BW",2009 +"2009-04-13","Easter Monday","BW",2009 +"2009-05-01","Labour Day","BW",2009 +"2009-05-21","Ascension Day","BW",2009 +"2009-07-01","Sir Seretse Khama Day","BW",2009 +"2009-07-20","President's Day","BW",2009 +"2009-07-21","President's Day Holiday","BW",2009 +"2009-09-30","Botswana Day","BW",2009 +"2009-10-01","Botswana Day Holiday","BW",2009 +"2009-12-25","Christmas Day","BW",2009 +"2009-12-26","Boxing Day","BW",2009 +"2010-01-01","New Year's Day","BW",2010 +"2010-01-02","New Year's Day Holiday","BW",2010 +"2010-04-02","Good Friday","BW",2010 +"2010-04-03","Holy Saturday","BW",2010 +"2010-04-05","Easter Monday","BW",2010 +"2010-05-01","Labour Day","BW",2010 +"2010-05-13","Ascension Day","BW",2010 +"2010-07-01","Sir Seretse Khama Day","BW",2010 +"2010-07-19","President's Day","BW",2010 +"2010-07-20","President's Day Holiday","BW",2010 +"2010-09-30","Botswana Day","BW",2010 +"2010-10-01","Botswana Day Holiday","BW",2010 +"2010-12-25","Christmas Day","BW",2010 +"2010-12-26","Boxing Day","BW",2010 +"2010-12-27","Boxing Day (Observed)","BW",2010 +"2011-01-01","New Year's Day","BW",2011 +"2011-01-02","New Year's Day Holiday","BW",2011 +"2011-01-03","New Year's Day Holiday (Observed)","BW",2011 +"2011-04-22","Good Friday","BW",2011 +"2011-04-23","Holy Saturday","BW",2011 +"2011-04-25","Easter Monday","BW",2011 +"2011-05-01","Labour Day","BW",2011 +"2011-05-02","Labour Day (Observed)","BW",2011 +"2011-06-02","Ascension Day","BW",2011 +"2011-07-01","Sir Seretse Khama Day","BW",2011 +"2011-07-18","President's Day","BW",2011 +"2011-07-19","President's Day Holiday","BW",2011 +"2011-09-30","Botswana Day","BW",2011 +"2011-10-01","Botswana Day Holiday","BW",2011 +"2011-12-25","Christmas Day","BW",2011 +"2011-12-26","Boxing Day","BW",2011 +"2011-12-27","Christmas Day (Observed)","BW",2011 +"2012-01-01","New Year's Day","BW",2012 +"2012-01-02","New Year's Day Holiday","BW",2012 +"2012-01-03","New Year's Day (Observed)","BW",2012 +"2012-04-06","Good Friday","BW",2012 +"2012-04-07","Holy Saturday","BW",2012 +"2012-04-09","Easter Monday","BW",2012 +"2012-05-01","Labour Day","BW",2012 +"2012-05-17","Ascension Day","BW",2012 +"2012-07-01","Sir Seretse Khama Day","BW",2012 +"2012-07-02","Sir Seretse Khama Day (Observed)","BW",2012 +"2012-07-16","President's Day","BW",2012 +"2012-07-17","President's Day Holiday","BW",2012 +"2012-09-30","Botswana Day","BW",2012 +"2012-10-01","Botswana Day Holiday","BW",2012 +"2012-10-02","Botswana Day (Observed)","BW",2012 +"2012-12-25","Christmas Day","BW",2012 +"2012-12-26","Boxing Day","BW",2012 +"2013-01-01","New Year's Day","BW",2013 +"2013-01-02","New Year's Day Holiday","BW",2013 +"2013-03-29","Good Friday","BW",2013 +"2013-03-30","Holy Saturday","BW",2013 +"2013-04-01","Easter Monday","BW",2013 +"2013-05-01","Labour Day","BW",2013 +"2013-05-09","Ascension Day","BW",2013 +"2013-07-01","Sir Seretse Khama Day","BW",2013 +"2013-07-15","President's Day","BW",2013 +"2013-07-16","President's Day Holiday","BW",2013 +"2013-09-30","Botswana Day","BW",2013 +"2013-10-01","Botswana Day Holiday","BW",2013 +"2013-12-25","Christmas Day","BW",2013 +"2013-12-26","Boxing Day","BW",2013 +"2014-01-01","New Year's Day","BW",2014 +"2014-01-02","New Year's Day Holiday","BW",2014 +"2014-04-18","Good Friday","BW",2014 +"2014-04-19","Holy Saturday","BW",2014 +"2014-04-21","Easter Monday","BW",2014 +"2014-05-01","Labour Day","BW",2014 +"2014-05-29","Ascension Day","BW",2014 +"2014-07-01","Sir Seretse Khama Day","BW",2014 +"2014-07-21","President's Day","BW",2014 +"2014-07-22","President's Day Holiday","BW",2014 +"2014-09-30","Botswana Day","BW",2014 +"2014-10-01","Botswana Day Holiday","BW",2014 +"2014-12-25","Christmas Day","BW",2014 +"2014-12-26","Boxing Day","BW",2014 +"2015-01-01","New Year's Day","BW",2015 +"2015-01-02","New Year's Day Holiday","BW",2015 +"2015-04-03","Good Friday","BW",2015 +"2015-04-04","Holy Saturday","BW",2015 +"2015-04-06","Easter Monday","BW",2015 +"2015-05-01","Labour Day","BW",2015 +"2015-05-14","Ascension Day","BW",2015 +"2015-07-01","Sir Seretse Khama Day","BW",2015 +"2015-07-20","President's Day","BW",2015 +"2015-07-21","President's Day Holiday","BW",2015 +"2015-09-30","Botswana Day","BW",2015 +"2015-10-01","Botswana Day Holiday","BW",2015 +"2015-12-25","Christmas Day","BW",2015 +"2015-12-26","Boxing Day","BW",2015 +"2016-01-01","New Year's Day","BW",2016 +"2016-01-02","New Year's Day Holiday","BW",2016 +"2016-03-25","Good Friday","BW",2016 +"2016-03-26","Holy Saturday","BW",2016 +"2016-03-28","Easter Monday","BW",2016 +"2016-05-01","Labour Day","BW",2016 +"2016-05-02","Labour Day (Observed)","BW",2016 +"2016-05-05","Ascension Day","BW",2016 +"2016-07-01","Sir Seretse Khama Day","BW",2016 +"2016-07-18","President's Day","BW",2016 +"2016-07-19","President's Day Holiday","BW",2016 +"2016-09-30","Botswana Day","BW",2016 +"2016-10-01","Botswana Day Holiday","BW",2016 +"2016-12-25","Christmas Day","BW",2016 +"2016-12-26","Boxing Day","BW",2016 +"2016-12-27","Christmas Day (Observed)","BW",2016 +"2017-01-01","New Year's Day","BW",2017 +"2017-01-02","New Year's Day Holiday","BW",2017 +"2017-01-03","New Year's Day (Observed)","BW",2017 +"2017-04-14","Good Friday","BW",2017 +"2017-04-15","Holy Saturday","BW",2017 +"2017-04-17","Easter Monday","BW",2017 +"2017-05-01","Labour Day","BW",2017 +"2017-05-25","Ascension Day","BW",2017 +"2017-07-01","Sir Seretse Khama Day","BW",2017 +"2017-07-17","President's Day","BW",2017 +"2017-07-18","President's Day Holiday","BW",2017 +"2017-09-30","Botswana Day","BW",2017 +"2017-10-01","Botswana Day Holiday","BW",2017 +"2017-10-02","Botswana Day Holiday (Observed)","BW",2017 +"2017-12-25","Christmas Day","BW",2017 +"2017-12-26","Boxing Day","BW",2017 +"2018-01-01","New Year's Day","BW",2018 +"2018-01-02","New Year's Day Holiday","BW",2018 +"2018-03-30","Good Friday","BW",2018 +"2018-03-31","Holy Saturday","BW",2018 +"2018-04-02","Easter Monday","BW",2018 +"2018-05-01","Labour Day","BW",2018 +"2018-05-10","Ascension Day","BW",2018 +"2018-07-01","Sir Seretse Khama Day","BW",2018 +"2018-07-02","Sir Seretse Khama Day (Observed)","BW",2018 +"2018-07-16","President's Day","BW",2018 +"2018-07-17","President's Day Holiday","BW",2018 +"2018-09-30","Botswana Day","BW",2018 +"2018-10-01","Botswana Day Holiday","BW",2018 +"2018-10-02","Botswana Day (Observed)","BW",2018 +"2018-12-25","Christmas Day","BW",2018 +"2018-12-26","Boxing Day","BW",2018 +"2019-01-01","New Year's Day","BW",2019 +"2019-01-02","New Year's Day Holiday","BW",2019 +"2019-04-19","Good Friday","BW",2019 +"2019-04-20","Holy Saturday","BW",2019 +"2019-04-22","Easter Monday","BW",2019 +"2019-05-01","Labour Day","BW",2019 +"2019-05-30","Ascension Day","BW",2019 +"2019-07-01","Sir Seretse Khama Day","BW",2019 +"2019-07-02","Public Holiday","BW",2019 +"2019-07-15","President's Day","BW",2019 +"2019-07-16","President's Day Holiday","BW",2019 +"2019-09-30","Botswana Day","BW",2019 +"2019-10-01","Botswana Day Holiday","BW",2019 +"2019-12-25","Christmas Day","BW",2019 +"2019-12-26","Boxing Day","BW",2019 +"2020-01-01","New Year's Day","BW",2020 +"2020-01-02","New Year's Day Holiday","BW",2020 +"2020-04-10","Good Friday","BW",2020 +"2020-04-11","Holy Saturday","BW",2020 +"2020-04-13","Easter Monday","BW",2020 +"2020-05-01","Labour Day","BW",2020 +"2020-05-21","Ascension Day","BW",2020 +"2020-07-01","Sir Seretse Khama Day","BW",2020 +"2020-07-20","President's Day","BW",2020 +"2020-07-21","President's Day Holiday","BW",2020 +"2020-09-30","Botswana Day","BW",2020 +"2020-10-01","Botswana Day Holiday","BW",2020 +"2020-12-25","Christmas Day","BW",2020 +"2020-12-26","Boxing Day","BW",2020 +"2020-12-28","Boxing Day Holiday","BW",2020 +"2021-01-01","New Year's Day","BW",2021 +"2021-01-02","New Year's Day Holiday","BW",2021 +"2021-04-02","Good Friday","BW",2021 +"2021-04-03","Holy Saturday","BW",2021 +"2021-04-05","Easter Monday","BW",2021 +"2021-05-01","Labour Day","BW",2021 +"2021-05-03","Labour Day Holiday","BW",2021 +"2021-05-13","Ascension Day","BW",2021 +"2021-07-01","Sir Seretse Khama Day","BW",2021 +"2021-07-19","President's Day","BW",2021 +"2021-07-20","President's Day Holiday","BW",2021 +"2021-09-30","Botswana Day","BW",2021 +"2021-10-01","Botswana Day Holiday","BW",2021 +"2021-12-25","Christmas Day","BW",2021 +"2021-12-26","Boxing Day","BW",2021 +"2021-12-27","Boxing Day (Observed)","BW",2021 +"2022-01-01","New Year's Day","BW",2022 +"2022-01-02","New Year's Day Holiday","BW",2022 +"2022-01-03","New Year's Day Holiday (Observed)","BW",2022 +"2022-04-15","Good Friday","BW",2022 +"2022-04-16","Holy Saturday","BW",2022 +"2022-04-18","Easter Monday","BW",2022 +"2022-05-01","Labour Day","BW",2022 +"2022-05-02","Labour Day (Observed)","BW",2022 +"2022-05-26","Ascension Day","BW",2022 +"2022-07-01","Sir Seretse Khama Day","BW",2022 +"2022-07-18","President's Day","BW",2022 +"2022-07-19","President's Day Holiday","BW",2022 +"2022-09-30","Botswana Day","BW",2022 +"2022-10-01","Botswana Day Holiday","BW",2022 +"2022-12-25","Christmas Day","BW",2022 +"2022-12-26","Boxing Day","BW",2022 +"2022-12-27","Christmas Day (Observed)","BW",2022 +"2023-01-01","New Year's Day","BW",2023 +"2023-01-02","New Year's Day Holiday","BW",2023 +"2023-01-03","New Year's Day (Observed)","BW",2023 +"2023-04-07","Good Friday","BW",2023 +"2023-04-08","Holy Saturday","BW",2023 +"2023-04-10","Easter Monday","BW",2023 +"2023-05-01","Labour Day","BW",2023 +"2023-05-18","Ascension Day","BW",2023 +"2023-07-01","Sir Seretse Khama Day","BW",2023 +"2023-07-17","President's Day","BW",2023 +"2023-07-18","President's Day Holiday","BW",2023 +"2023-09-30","Botswana Day","BW",2023 +"2023-10-01","Botswana Day Holiday","BW",2023 +"2023-10-02","Botswana Day Holiday (Observed)","BW",2023 +"2023-12-25","Christmas Day","BW",2023 +"2023-12-26","Boxing Day","BW",2023 +"2024-01-01","New Year's Day","BW",2024 +"2024-01-02","New Year's Day Holiday","BW",2024 +"2024-03-29","Good Friday","BW",2024 +"2024-03-30","Holy Saturday","BW",2024 +"2024-04-01","Easter Monday","BW",2024 +"2024-05-01","Labour Day","BW",2024 +"2024-05-09","Ascension Day","BW",2024 +"2024-07-01","Sir Seretse Khama Day","BW",2024 +"2024-07-15","President's Day","BW",2024 +"2024-07-16","President's Day Holiday","BW",2024 +"2024-09-30","Botswana Day","BW",2024 +"2024-10-01","Botswana Day Holiday","BW",2024 +"2024-12-25","Christmas Day","BW",2024 +"2024-12-26","Boxing Day","BW",2024 +"2025-01-01","New Year's Day","BW",2025 +"2025-01-02","New Year's Day Holiday","BW",2025 +"2025-04-18","Good Friday","BW",2025 +"2025-04-19","Holy Saturday","BW",2025 +"2025-04-21","Easter Monday","BW",2025 +"2025-05-01","Labour Day","BW",2025 +"2025-05-29","Ascension Day","BW",2025 +"2025-07-01","Sir Seretse Khama Day","BW",2025 +"2025-07-21","President's Day","BW",2025 +"2025-07-22","President's Day Holiday","BW",2025 +"2025-09-30","Botswana Day","BW",2025 +"2025-10-01","Botswana Day Holiday","BW",2025 +"2025-12-25","Christmas Day","BW",2025 +"2025-12-26","Boxing Day","BW",2025 +"2026-01-01","New Year's Day","BW",2026 +"2026-01-02","New Year's Day Holiday","BW",2026 +"2026-04-03","Good Friday","BW",2026 +"2026-04-04","Holy Saturday","BW",2026 +"2026-04-06","Easter Monday","BW",2026 +"2026-05-01","Labour Day","BW",2026 +"2026-05-14","Ascension Day","BW",2026 +"2026-07-01","Sir Seretse Khama Day","BW",2026 +"2026-07-20","President's Day","BW",2026 +"2026-07-21","President's Day Holiday","BW",2026 +"2026-09-30","Botswana Day","BW",2026 +"2026-10-01","Botswana Day Holiday","BW",2026 +"2026-12-25","Christmas Day","BW",2026 +"2026-12-26","Boxing Day","BW",2026 +"2026-12-28","Boxing Day Holiday","BW",2026 +"2027-01-01","New Year's Day","BW",2027 +"2027-01-02","New Year's Day Holiday","BW",2027 +"2027-03-26","Good Friday","BW",2027 +"2027-03-27","Holy Saturday","BW",2027 +"2027-03-29","Easter Monday","BW",2027 +"2027-05-01","Labour Day","BW",2027 +"2027-05-03","Labour Day Holiday","BW",2027 +"2027-05-06","Ascension Day","BW",2027 +"2027-07-01","Sir Seretse Khama Day","BW",2027 +"2027-07-19","President's Day","BW",2027 +"2027-07-20","President's Day Holiday","BW",2027 +"2027-09-30","Botswana Day","BW",2027 +"2027-10-01","Botswana Day Holiday","BW",2027 +"2027-12-25","Christmas Day","BW",2027 +"2027-12-26","Boxing Day","BW",2027 +"2027-12-27","Boxing Day (Observed)","BW",2027 +"2028-01-01","New Year's Day","BW",2028 +"2028-01-02","New Year's Day Holiday","BW",2028 +"2028-01-03","New Year's Day Holiday (Observed)","BW",2028 +"2028-04-14","Good Friday","BW",2028 +"2028-04-15","Holy Saturday","BW",2028 +"2028-04-17","Easter Monday","BW",2028 +"2028-05-01","Labour Day","BW",2028 +"2028-05-25","Ascension Day","BW",2028 +"2028-07-01","Sir Seretse Khama Day","BW",2028 +"2028-07-17","President's Day","BW",2028 +"2028-07-18","President's Day Holiday","BW",2028 +"2028-09-30","Botswana Day","BW",2028 +"2028-10-01","Botswana Day Holiday","BW",2028 +"2028-10-02","Botswana Day Holiday (Observed)","BW",2028 +"2028-12-25","Christmas Day","BW",2028 +"2028-12-26","Boxing Day","BW",2028 +"2029-01-01","New Year's Day","BW",2029 +"2029-01-02","New Year's Day Holiday","BW",2029 +"2029-03-30","Good Friday","BW",2029 +"2029-03-31","Holy Saturday","BW",2029 +"2029-04-02","Easter Monday","BW",2029 +"2029-05-01","Labour Day","BW",2029 +"2029-05-10","Ascension Day","BW",2029 +"2029-07-01","Sir Seretse Khama Day","BW",2029 +"2029-07-02","Sir Seretse Khama Day (Observed)","BW",2029 +"2029-07-16","President's Day","BW",2029 +"2029-07-17","President's Day Holiday","BW",2029 +"2029-09-30","Botswana Day","BW",2029 +"2029-10-01","Botswana Day Holiday","BW",2029 +"2029-10-02","Botswana Day (Observed)","BW",2029 +"2029-12-25","Christmas Day","BW",2029 +"2029-12-26","Boxing Day","BW",2029 +"2030-01-01","New Year's Day","BW",2030 +"2030-01-02","New Year's Day Holiday","BW",2030 +"2030-04-19","Good Friday","BW",2030 +"2030-04-20","Holy Saturday","BW",2030 +"2030-04-22","Easter Monday","BW",2030 +"2030-05-01","Labour Day","BW",2030 +"2030-05-30","Ascension Day","BW",2030 +"2030-07-01","Sir Seretse Khama Day","BW",2030 +"2030-07-15","President's Day","BW",2030 +"2030-07-16","President's Day Holiday","BW",2030 +"2030-09-30","Botswana Day","BW",2030 +"2030-10-01","Botswana Day Holiday","BW",2030 +"2030-12-25","Christmas Day","BW",2030 +"2030-12-26","Boxing Day","BW",2030 +"2031-01-01","New Year's Day","BW",2031 +"2031-01-02","New Year's Day Holiday","BW",2031 +"2031-04-11","Good Friday","BW",2031 +"2031-04-12","Holy Saturday","BW",2031 +"2031-04-14","Easter Monday","BW",2031 +"2031-05-01","Labour Day","BW",2031 +"2031-05-22","Ascension Day","BW",2031 +"2031-07-01","Sir Seretse Khama Day","BW",2031 +"2031-07-21","President's Day","BW",2031 +"2031-07-22","President's Day Holiday","BW",2031 +"2031-09-30","Botswana Day","BW",2031 +"2031-10-01","Botswana Day Holiday","BW",2031 +"2031-12-25","Christmas Day","BW",2031 +"2031-12-26","Boxing Day","BW",2031 +"2032-01-01","New Year's Day","BW",2032 +"2032-01-02","New Year's Day Holiday","BW",2032 +"2032-03-26","Good Friday","BW",2032 +"2032-03-27","Holy Saturday","BW",2032 +"2032-03-29","Easter Monday","BW",2032 +"2032-05-01","Labour Day","BW",2032 +"2032-05-03","Labour Day Holiday","BW",2032 +"2032-05-06","Ascension Day","BW",2032 +"2032-07-01","Sir Seretse Khama Day","BW",2032 +"2032-07-19","President's Day","BW",2032 +"2032-07-20","President's Day Holiday","BW",2032 +"2032-09-30","Botswana Day","BW",2032 +"2032-10-01","Botswana Day Holiday","BW",2032 +"2032-12-25","Christmas Day","BW",2032 +"2032-12-26","Boxing Day","BW",2032 +"2032-12-27","Boxing Day (Observed)","BW",2032 +"2033-01-01","New Year's Day","BW",2033 +"2033-01-02","New Year's Day Holiday","BW",2033 +"2033-01-03","New Year's Day Holiday (Observed)","BW",2033 +"2033-04-15","Good Friday","BW",2033 +"2033-04-16","Holy Saturday","BW",2033 +"2033-04-18","Easter Monday","BW",2033 +"2033-05-01","Labour Day","BW",2033 +"2033-05-02","Labour Day (Observed)","BW",2033 +"2033-05-26","Ascension Day","BW",2033 +"2033-07-01","Sir Seretse Khama Day","BW",2033 +"2033-07-18","President's Day","BW",2033 +"2033-07-19","President's Day Holiday","BW",2033 +"2033-09-30","Botswana Day","BW",2033 +"2033-10-01","Botswana Day Holiday","BW",2033 +"2033-12-25","Christmas Day","BW",2033 +"2033-12-26","Boxing Day","BW",2033 +"2033-12-27","Christmas Day (Observed)","BW",2033 +"2034-01-01","New Year's Day","BW",2034 +"2034-01-02","New Year's Day Holiday","BW",2034 +"2034-01-03","New Year's Day (Observed)","BW",2034 +"2034-04-07","Good Friday","BW",2034 +"2034-04-08","Holy Saturday","BW",2034 +"2034-04-10","Easter Monday","BW",2034 +"2034-05-01","Labour Day","BW",2034 +"2034-05-18","Ascension Day","BW",2034 +"2034-07-01","Sir Seretse Khama Day","BW",2034 +"2034-07-17","President's Day","BW",2034 +"2034-07-18","President's Day Holiday","BW",2034 +"2034-09-30","Botswana Day","BW",2034 +"2034-10-01","Botswana Day Holiday","BW",2034 +"2034-10-02","Botswana Day Holiday (Observed)","BW",2034 +"2034-12-25","Christmas Day","BW",2034 +"2034-12-26","Boxing Day","BW",2034 +"2035-01-01","New Year's Day","BW",2035 +"2035-01-02","New Year's Day Holiday","BW",2035 +"2035-03-23","Good Friday","BW",2035 +"2035-03-24","Holy Saturday","BW",2035 +"2035-03-26","Easter Monday","BW",2035 +"2035-05-01","Labour Day","BW",2035 +"2035-05-03","Ascension Day","BW",2035 +"2035-07-01","Sir Seretse Khama Day","BW",2035 +"2035-07-02","Sir Seretse Khama Day (Observed)","BW",2035 +"2035-07-16","President's Day","BW",2035 +"2035-07-17","President's Day Holiday","BW",2035 +"2035-09-30","Botswana Day","BW",2035 +"2035-10-01","Botswana Day Holiday","BW",2035 +"2035-10-02","Botswana Day (Observed)","BW",2035 +"2035-12-25","Christmas Day","BW",2035 +"2035-12-26","Boxing Day","BW",2035 +"2036-01-01","New Year's Day","BW",2036 +"2036-01-02","New Year's Day Holiday","BW",2036 +"2036-04-11","Good Friday","BW",2036 +"2036-04-12","Holy Saturday","BW",2036 +"2036-04-14","Easter Monday","BW",2036 +"2036-05-01","Labour Day","BW",2036 +"2036-05-22","Ascension Day","BW",2036 +"2036-07-01","Sir Seretse Khama Day","BW",2036 +"2036-07-21","President's Day","BW",2036 +"2036-07-22","President's Day Holiday","BW",2036 +"2036-09-30","Botswana Day","BW",2036 +"2036-10-01","Botswana Day Holiday","BW",2036 +"2036-12-25","Christmas Day","BW",2036 +"2036-12-26","Boxing Day","BW",2036 +"2037-01-01","New Year's Day","BW",2037 +"2037-01-02","New Year's Day Holiday","BW",2037 +"2037-04-03","Good Friday","BW",2037 +"2037-04-04","Holy Saturday","BW",2037 +"2037-04-06","Easter Monday","BW",2037 +"2037-05-01","Labour Day","BW",2037 +"2037-05-14","Ascension Day","BW",2037 +"2037-07-01","Sir Seretse Khama Day","BW",2037 +"2037-07-20","President's Day","BW",2037 +"2037-07-21","President's Day Holiday","BW",2037 +"2037-09-30","Botswana Day","BW",2037 +"2037-10-01","Botswana Day Holiday","BW",2037 +"2037-12-25","Christmas Day","BW",2037 +"2037-12-26","Boxing Day","BW",2037 +"2037-12-28","Boxing Day Holiday","BW",2037 +"2038-01-01","New Year's Day","BW",2038 +"2038-01-02","New Year's Day Holiday","BW",2038 +"2038-04-23","Good Friday","BW",2038 +"2038-04-24","Holy Saturday","BW",2038 +"2038-04-26","Easter Monday","BW",2038 +"2038-05-01","Labour Day","BW",2038 +"2038-05-03","Labour Day Holiday","BW",2038 +"2038-06-03","Ascension Day","BW",2038 +"2038-07-01","Sir Seretse Khama Day","BW",2038 +"2038-07-19","President's Day","BW",2038 +"2038-07-20","President's Day Holiday","BW",2038 +"2038-09-30","Botswana Day","BW",2038 +"2038-10-01","Botswana Day Holiday","BW",2038 +"2038-12-25","Christmas Day","BW",2038 +"2038-12-26","Boxing Day","BW",2038 +"2038-12-27","Boxing Day (Observed)","BW",2038 +"2039-01-01","New Year's Day","BW",2039 +"2039-01-02","New Year's Day Holiday","BW",2039 +"2039-01-03","New Year's Day Holiday (Observed)","BW",2039 +"2039-04-08","Good Friday","BW",2039 +"2039-04-09","Holy Saturday","BW",2039 +"2039-04-11","Easter Monday","BW",2039 +"2039-05-01","Labour Day","BW",2039 +"2039-05-02","Labour Day (Observed)","BW",2039 +"2039-05-19","Ascension Day","BW",2039 +"2039-07-01","Sir Seretse Khama Day","BW",2039 +"2039-07-18","President's Day","BW",2039 +"2039-07-19","President's Day Holiday","BW",2039 +"2039-09-30","Botswana Day","BW",2039 +"2039-10-01","Botswana Day Holiday","BW",2039 +"2039-12-25","Christmas Day","BW",2039 +"2039-12-26","Boxing Day","BW",2039 +"2039-12-27","Christmas Day (Observed)","BW",2039 +"2040-01-01","New Year's Day","BW",2040 +"2040-01-02","New Year's Day Holiday","BW",2040 +"2040-01-03","New Year's Day (Observed)","BW",2040 +"2040-03-30","Good Friday","BW",2040 +"2040-03-31","Holy Saturday","BW",2040 +"2040-04-02","Easter Monday","BW",2040 +"2040-05-01","Labour Day","BW",2040 +"2040-05-10","Ascension Day","BW",2040 +"2040-07-01","Sir Seretse Khama Day","BW",2040 +"2040-07-02","Sir Seretse Khama Day (Observed)","BW",2040 +"2040-07-16","President's Day","BW",2040 +"2040-07-17","President's Day Holiday","BW",2040 +"2040-09-30","Botswana Day","BW",2040 +"2040-10-01","Botswana Day Holiday","BW",2040 +"2040-10-02","Botswana Day (Observed)","BW",2040 +"2040-12-25","Christmas Day","BW",2040 +"2040-12-26","Boxing Day","BW",2040 +"2041-01-01","New Year's Day","BW",2041 +"2041-01-02","New Year's Day Holiday","BW",2041 +"2041-04-19","Good Friday","BW",2041 +"2041-04-20","Holy Saturday","BW",2041 +"2041-04-22","Easter Monday","BW",2041 +"2041-05-01","Labour Day","BW",2041 +"2041-05-30","Ascension Day","BW",2041 +"2041-07-01","Sir Seretse Khama Day","BW",2041 +"2041-07-15","President's Day","BW",2041 +"2041-07-16","President's Day Holiday","BW",2041 +"2041-09-30","Botswana Day","BW",2041 +"2041-10-01","Botswana Day Holiday","BW",2041 +"2041-12-25","Christmas Day","BW",2041 +"2041-12-26","Boxing Day","BW",2041 +"2042-01-01","New Year's Day","BW",2042 +"2042-01-02","New Year's Day Holiday","BW",2042 +"2042-04-04","Good Friday","BW",2042 +"2042-04-05","Holy Saturday","BW",2042 +"2042-04-07","Easter Monday","BW",2042 +"2042-05-01","Labour Day","BW",2042 +"2042-05-15","Ascension Day","BW",2042 +"2042-07-01","Sir Seretse Khama Day","BW",2042 +"2042-07-21","President's Day","BW",2042 +"2042-07-22","President's Day Holiday","BW",2042 +"2042-09-30","Botswana Day","BW",2042 +"2042-10-01","Botswana Day Holiday","BW",2042 +"2042-12-25","Christmas Day","BW",2042 +"2042-12-26","Boxing Day","BW",2042 +"2043-01-01","New Year's Day","BW",2043 +"2043-01-02","New Year's Day Holiday","BW",2043 +"2043-03-27","Good Friday","BW",2043 +"2043-03-28","Holy Saturday","BW",2043 +"2043-03-30","Easter Monday","BW",2043 +"2043-05-01","Labour Day","BW",2043 +"2043-05-07","Ascension Day","BW",2043 +"2043-07-01","Sir Seretse Khama Day","BW",2043 +"2043-07-20","President's Day","BW",2043 +"2043-07-21","President's Day Holiday","BW",2043 +"2043-09-30","Botswana Day","BW",2043 +"2043-10-01","Botswana Day Holiday","BW",2043 +"2043-12-25","Christmas Day","BW",2043 +"2043-12-26","Boxing Day","BW",2043 +"2043-12-28","Boxing Day Holiday","BW",2043 +"2044-01-01","New Year's Day","BW",2044 +"2044-01-02","New Year's Day Holiday","BW",2044 +"2044-04-15","Good Friday","BW",2044 +"2044-04-16","Holy Saturday","BW",2044 +"2044-04-18","Easter Monday","BW",2044 +"2044-05-01","Labour Day","BW",2044 +"2044-05-02","Labour Day (Observed)","BW",2044 +"2044-05-26","Ascension Day","BW",2044 +"2044-07-01","Sir Seretse Khama Day","BW",2044 +"2044-07-18","President's Day","BW",2044 +"2044-07-19","President's Day Holiday","BW",2044 +"2044-09-30","Botswana Day","BW",2044 +"2044-10-01","Botswana Day Holiday","BW",2044 +"2044-12-25","Christmas Day","BW",2044 +"2044-12-26","Boxing Day","BW",2044 +"2044-12-27","Christmas Day (Observed)","BW",2044 +"1999-01-01","New Year's Day","BY",1999 +"1999-01-07","Orthodox Christmas Day","BY",1999 +"1999-03-08","Women's Day","BY",1999 +"1999-04-20","Radunitsa","BY",1999 +"1999-05-01","Labor Day","BY",1999 +"1999-05-09","Victory Day","BY",1999 +"1999-07-03","Independence Day (Republic Day)","BY",1999 +"1999-11-07","October Revolution Day","BY",1999 +"1999-12-25","Catholic Christmas Day","BY",1999 +"2000-01-01","New Year's Day","BY",2000 +"2000-01-07","Orthodox Christmas Day","BY",2000 +"2000-03-08","Women's Day","BY",2000 +"2000-05-01","Labor Day","BY",2000 +"2000-05-09","Radunitsa","BY",2000 +"2000-05-09","Victory Day","BY",2000 +"2000-07-03","Independence Day (Republic Day)","BY",2000 +"2000-11-07","October Revolution Day","BY",2000 +"2000-12-25","Catholic Christmas Day","BY",2000 +"2001-01-01","New Year's Day","BY",2001 +"2001-01-07","Orthodox Christmas Day","BY",2001 +"2001-03-08","Women's Day","BY",2001 +"2001-04-24","Radunitsa","BY",2001 +"2001-05-01","Labor Day","BY",2001 +"2001-05-09","Victory Day","BY",2001 +"2001-07-03","Independence Day (Republic Day)","BY",2001 +"2001-11-07","October Revolution Day","BY",2001 +"2001-12-25","Catholic Christmas Day","BY",2001 +"2002-01-01","New Year's Day","BY",2002 +"2002-01-07","Orthodox Christmas Day","BY",2002 +"2002-03-08","Women's Day","BY",2002 +"2002-05-01","Labor Day","BY",2002 +"2002-05-09","Victory Day","BY",2002 +"2002-05-14","Radunitsa","BY",2002 +"2002-07-03","Independence Day (Republic Day)","BY",2002 +"2002-11-07","October Revolution Day","BY",2002 +"2002-12-25","Catholic Christmas Day","BY",2002 +"2003-01-01","New Year's Day","BY",2003 +"2003-01-07","Orthodox Christmas Day","BY",2003 +"2003-03-08","Women's Day","BY",2003 +"2003-05-01","Labor Day","BY",2003 +"2003-05-06","Radunitsa","BY",2003 +"2003-05-09","Victory Day","BY",2003 +"2003-07-03","Independence Day (Republic Day)","BY",2003 +"2003-11-07","October Revolution Day","BY",2003 +"2003-12-25","Catholic Christmas Day","BY",2003 +"2004-01-01","New Year's Day","BY",2004 +"2004-01-07","Orthodox Christmas Day","BY",2004 +"2004-03-08","Women's Day","BY",2004 +"2004-04-20","Radunitsa","BY",2004 +"2004-05-01","Labor Day","BY",2004 +"2004-05-09","Victory Day","BY",2004 +"2004-07-03","Independence Day (Republic Day)","BY",2004 +"2004-11-07","October Revolution Day","BY",2004 +"2004-12-25","Catholic Christmas Day","BY",2004 +"2005-01-01","New Year's Day","BY",2005 +"2005-01-07","Orthodox Christmas Day","BY",2005 +"2005-03-08","Women's Day","BY",2005 +"2005-05-01","Labor Day","BY",2005 +"2005-05-09","Victory Day","BY",2005 +"2005-05-10","Radunitsa","BY",2005 +"2005-07-03","Independence Day (Republic Day)","BY",2005 +"2005-11-07","October Revolution Day","BY",2005 +"2005-12-25","Catholic Christmas Day","BY",2005 +"2006-01-01","New Year's Day","BY",2006 +"2006-01-07","Orthodox Christmas Day","BY",2006 +"2006-03-08","Women's Day","BY",2006 +"2006-05-01","Labor Day","BY",2006 +"2006-05-02","Radunitsa","BY",2006 +"2006-05-09","Victory Day","BY",2006 +"2006-07-03","Independence Day (Republic Day)","BY",2006 +"2006-11-07","October Revolution Day","BY",2006 +"2006-12-25","Catholic Christmas Day","BY",2006 +"2007-01-01","New Year's Day","BY",2007 +"2007-01-07","Orthodox Christmas Day","BY",2007 +"2007-03-08","Women's Day","BY",2007 +"2007-04-17","Radunitsa","BY",2007 +"2007-05-01","Labor Day","BY",2007 +"2007-05-09","Victory Day","BY",2007 +"2007-07-03","Independence Day (Republic Day)","BY",2007 +"2007-11-07","October Revolution Day","BY",2007 +"2007-12-25","Catholic Christmas Day","BY",2007 +"2008-01-01","New Year's Day","BY",2008 +"2008-01-07","Orthodox Christmas Day","BY",2008 +"2008-03-08","Women's Day","BY",2008 +"2008-05-01","Labor Day","BY",2008 +"2008-05-06","Radunitsa","BY",2008 +"2008-05-09","Victory Day","BY",2008 +"2008-07-03","Independence Day (Republic Day)","BY",2008 +"2008-11-07","October Revolution Day","BY",2008 +"2008-12-25","Catholic Christmas Day","BY",2008 +"2009-01-01","New Year's Day","BY",2009 +"2009-01-07","Orthodox Christmas Day","BY",2009 +"2009-03-08","Women's Day","BY",2009 +"2009-04-28","Radunitsa","BY",2009 +"2009-05-01","Labor Day","BY",2009 +"2009-05-09","Victory Day","BY",2009 +"2009-07-03","Independence Day (Republic Day)","BY",2009 +"2009-11-07","October Revolution Day","BY",2009 +"2009-12-25","Catholic Christmas Day","BY",2009 +"2010-01-01","New Year's Day","BY",2010 +"2010-01-07","Orthodox Christmas Day","BY",2010 +"2010-03-08","Women's Day","BY",2010 +"2010-04-13","Radunitsa","BY",2010 +"2010-05-01","Labor Day","BY",2010 +"2010-05-09","Victory Day","BY",2010 +"2010-07-03","Independence Day (Republic Day)","BY",2010 +"2010-11-07","October Revolution Day","BY",2010 +"2010-12-25","Catholic Christmas Day","BY",2010 +"2011-01-01","New Year's Day","BY",2011 +"2011-01-07","Orthodox Christmas Day","BY",2011 +"2011-03-08","Women's Day","BY",2011 +"2011-05-01","Labor Day","BY",2011 +"2011-05-03","Radunitsa","BY",2011 +"2011-05-09","Victory Day","BY",2011 +"2011-07-03","Independence Day (Republic Day)","BY",2011 +"2011-11-07","October Revolution Day","BY",2011 +"2011-12-25","Catholic Christmas Day","BY",2011 +"2012-01-01","New Year's Day","BY",2012 +"2012-01-07","Orthodox Christmas Day","BY",2012 +"2012-03-08","Women's Day","BY",2012 +"2012-04-24","Radunitsa","BY",2012 +"2012-05-01","Labor Day","BY",2012 +"2012-05-09","Victory Day","BY",2012 +"2012-07-03","Independence Day (Republic Day)","BY",2012 +"2012-11-07","October Revolution Day","BY",2012 +"2012-12-25","Catholic Christmas Day","BY",2012 +"2013-01-01","New Year's Day","BY",2013 +"2013-01-07","Orthodox Christmas Day","BY",2013 +"2013-03-08","Women's Day","BY",2013 +"2013-05-01","Labor Day","BY",2013 +"2013-05-09","Victory Day","BY",2013 +"2013-05-14","Radunitsa","BY",2013 +"2013-07-03","Independence Day (Republic Day)","BY",2013 +"2013-11-07","October Revolution Day","BY",2013 +"2013-12-25","Catholic Christmas Day","BY",2013 +"2014-01-01","New Year's Day","BY",2014 +"2014-01-07","Orthodox Christmas Day","BY",2014 +"2014-03-08","Women's Day","BY",2014 +"2014-04-29","Radunitsa","BY",2014 +"2014-05-01","Labor Day","BY",2014 +"2014-05-09","Victory Day","BY",2014 +"2014-07-03","Independence Day (Republic Day)","BY",2014 +"2014-11-07","October Revolution Day","BY",2014 +"2014-12-25","Catholic Christmas Day","BY",2014 +"2015-01-01","New Year's Day","BY",2015 +"2015-01-07","Orthodox Christmas Day","BY",2015 +"2015-03-08","Women's Day","BY",2015 +"2015-04-21","Radunitsa","BY",2015 +"2015-05-01","Labor Day","BY",2015 +"2015-05-09","Victory Day","BY",2015 +"2015-07-03","Independence Day (Republic Day)","BY",2015 +"2015-11-07","October Revolution Day","BY",2015 +"2015-12-25","Catholic Christmas Day","BY",2015 +"2016-01-01","New Year's Day","BY",2016 +"2016-01-07","Orthodox Christmas Day","BY",2016 +"2016-03-08","Women's Day","BY",2016 +"2016-05-01","Labor Day","BY",2016 +"2016-05-09","Victory Day","BY",2016 +"2016-05-10","Radunitsa","BY",2016 +"2016-07-03","Independence Day (Republic Day)","BY",2016 +"2016-11-07","October Revolution Day","BY",2016 +"2016-12-25","Catholic Christmas Day","BY",2016 +"2017-01-01","New Year's Day","BY",2017 +"2017-01-07","Orthodox Christmas Day","BY",2017 +"2017-03-08","Women's Day","BY",2017 +"2017-04-25","Radunitsa","BY",2017 +"2017-05-01","Labor Day","BY",2017 +"2017-05-09","Victory Day","BY",2017 +"2017-07-03","Independence Day (Republic Day)","BY",2017 +"2017-11-07","October Revolution Day","BY",2017 +"2017-12-25","Catholic Christmas Day","BY",2017 +"2018-01-01","New Year's Day","BY",2018 +"2018-01-07","Orthodox Christmas Day","BY",2018 +"2018-03-08","Women's Day","BY",2018 +"2018-04-17","Radunitsa","BY",2018 +"2018-05-01","Labor Day","BY",2018 +"2018-05-09","Victory Day","BY",2018 +"2018-07-03","Independence Day (Republic Day)","BY",2018 +"2018-11-07","October Revolution Day","BY",2018 +"2018-12-25","Catholic Christmas Day","BY",2018 +"2019-01-01","New Year's Day","BY",2019 +"2019-01-07","Orthodox Christmas Day","BY",2019 +"2019-03-08","Women's Day","BY",2019 +"2019-05-01","Labor Day","BY",2019 +"2019-05-07","Radunitsa","BY",2019 +"2019-05-09","Victory Day","BY",2019 +"2019-07-03","Independence Day (Republic Day)","BY",2019 +"2019-11-07","October Revolution Day","BY",2019 +"2019-12-25","Catholic Christmas Day","BY",2019 +"2020-01-01","New Year's Day","BY",2020 +"2020-01-02","New Year's Day","BY",2020 +"2020-01-07","Orthodox Christmas Day","BY",2020 +"2020-03-08","Women's Day","BY",2020 +"2020-04-28","Radunitsa","BY",2020 +"2020-05-01","Labor Day","BY",2020 +"2020-05-09","Victory Day","BY",2020 +"2020-07-03","Independence Day (Republic Day)","BY",2020 +"2020-11-07","October Revolution Day","BY",2020 +"2020-12-25","Catholic Christmas Day","BY",2020 +"2021-01-01","New Year's Day","BY",2021 +"2021-01-02","New Year's Day","BY",2021 +"2021-01-07","Orthodox Christmas Day","BY",2021 +"2021-03-08","Women's Day","BY",2021 +"2021-05-01","Labor Day","BY",2021 +"2021-05-09","Victory Day","BY",2021 +"2021-05-11","Radunitsa","BY",2021 +"2021-07-03","Independence Day (Republic Day)","BY",2021 +"2021-11-07","October Revolution Day","BY",2021 +"2021-12-25","Catholic Christmas Day","BY",2021 +"2022-01-01","New Year's Day","BY",2022 +"2022-01-02","New Year's Day","BY",2022 +"2022-01-07","Orthodox Christmas Day","BY",2022 +"2022-03-08","Women's Day","BY",2022 +"2022-05-01","Labor Day","BY",2022 +"2022-05-03","Radunitsa","BY",2022 +"2022-05-09","Victory Day","BY",2022 +"2022-07-03","Independence Day (Republic Day)","BY",2022 +"2022-11-07","October Revolution Day","BY",2022 +"2022-12-25","Catholic Christmas Day","BY",2022 +"2023-01-01","New Year's Day","BY",2023 +"2023-01-02","New Year's Day","BY",2023 +"2023-01-07","Orthodox Christmas Day","BY",2023 +"2023-03-08","Women's Day","BY",2023 +"2023-04-25","Radunitsa","BY",2023 +"2023-05-01","Labor Day","BY",2023 +"2023-05-09","Victory Day","BY",2023 +"2023-07-03","Independence Day (Republic Day)","BY",2023 +"2023-11-07","October Revolution Day","BY",2023 +"2023-12-25","Catholic Christmas Day","BY",2023 +"2024-01-01","New Year's Day","BY",2024 +"2024-01-02","New Year's Day","BY",2024 +"2024-01-07","Orthodox Christmas Day","BY",2024 +"2024-03-08","Women's Day","BY",2024 +"2024-05-01","Labor Day","BY",2024 +"2024-05-09","Victory Day","BY",2024 +"2024-05-14","Radunitsa","BY",2024 +"2024-07-03","Independence Day (Republic Day)","BY",2024 +"2024-11-07","October Revolution Day","BY",2024 +"2024-12-25","Catholic Christmas Day","BY",2024 +"2025-01-01","New Year's Day","BY",2025 +"2025-01-02","New Year's Day","BY",2025 +"2025-01-07","Orthodox Christmas Day","BY",2025 +"2025-03-08","Women's Day","BY",2025 +"2025-04-29","Radunitsa","BY",2025 +"2025-05-01","Labor Day","BY",2025 +"2025-05-09","Victory Day","BY",2025 +"2025-07-03","Independence Day (Republic Day)","BY",2025 +"2025-11-07","October Revolution Day","BY",2025 +"2025-12-25","Catholic Christmas Day","BY",2025 +"2026-01-01","New Year's Day","BY",2026 +"2026-01-02","New Year's Day","BY",2026 +"2026-01-07","Orthodox Christmas Day","BY",2026 +"2026-03-08","Women's Day","BY",2026 +"2026-04-21","Radunitsa","BY",2026 +"2026-05-01","Labor Day","BY",2026 +"2026-05-09","Victory Day","BY",2026 +"2026-07-03","Independence Day (Republic Day)","BY",2026 +"2026-11-07","October Revolution Day","BY",2026 +"2026-12-25","Catholic Christmas Day","BY",2026 +"2027-01-01","New Year's Day","BY",2027 +"2027-01-02","New Year's Day","BY",2027 +"2027-01-07","Orthodox Christmas Day","BY",2027 +"2027-03-08","Women's Day","BY",2027 +"2027-05-01","Labor Day","BY",2027 +"2027-05-09","Victory Day","BY",2027 +"2027-05-11","Radunitsa","BY",2027 +"2027-07-03","Independence Day (Republic Day)","BY",2027 +"2027-11-07","October Revolution Day","BY",2027 +"2027-12-25","Catholic Christmas Day","BY",2027 +"2028-01-01","New Year's Day","BY",2028 +"2028-01-02","New Year's Day","BY",2028 +"2028-01-07","Orthodox Christmas Day","BY",2028 +"2028-03-08","Women's Day","BY",2028 +"2028-04-25","Radunitsa","BY",2028 +"2028-05-01","Labor Day","BY",2028 +"2028-05-09","Victory Day","BY",2028 +"2028-07-03","Independence Day (Republic Day)","BY",2028 +"2028-11-07","October Revolution Day","BY",2028 +"2028-12-25","Catholic Christmas Day","BY",2028 +"2029-01-01","New Year's Day","BY",2029 +"2029-01-02","New Year's Day","BY",2029 +"2029-01-07","Orthodox Christmas Day","BY",2029 +"2029-03-08","Women's Day","BY",2029 +"2029-04-17","Radunitsa","BY",2029 +"2029-05-01","Labor Day","BY",2029 +"2029-05-09","Victory Day","BY",2029 +"2029-07-03","Independence Day (Republic Day)","BY",2029 +"2029-11-07","October Revolution Day","BY",2029 +"2029-12-25","Catholic Christmas Day","BY",2029 +"2030-01-01","New Year's Day","BY",2030 +"2030-01-02","New Year's Day","BY",2030 +"2030-01-07","Orthodox Christmas Day","BY",2030 +"2030-03-08","Women's Day","BY",2030 +"2030-05-01","Labor Day","BY",2030 +"2030-05-07","Radunitsa","BY",2030 +"2030-05-09","Victory Day","BY",2030 +"2030-07-03","Independence Day (Republic Day)","BY",2030 +"2030-11-07","October Revolution Day","BY",2030 +"2030-12-25","Catholic Christmas Day","BY",2030 +"2031-01-01","New Year's Day","BY",2031 +"2031-01-02","New Year's Day","BY",2031 +"2031-01-07","Orthodox Christmas Day","BY",2031 +"2031-03-08","Women's Day","BY",2031 +"2031-04-22","Radunitsa","BY",2031 +"2031-05-01","Labor Day","BY",2031 +"2031-05-09","Victory Day","BY",2031 +"2031-07-03","Independence Day (Republic Day)","BY",2031 +"2031-11-07","October Revolution Day","BY",2031 +"2031-12-25","Catholic Christmas Day","BY",2031 +"2032-01-01","New Year's Day","BY",2032 +"2032-01-02","New Year's Day","BY",2032 +"2032-01-07","Orthodox Christmas Day","BY",2032 +"2032-03-08","Women's Day","BY",2032 +"2032-05-01","Labor Day","BY",2032 +"2032-05-09","Victory Day","BY",2032 +"2032-05-11","Radunitsa","BY",2032 +"2032-07-03","Independence Day (Republic Day)","BY",2032 +"2032-11-07","October Revolution Day","BY",2032 +"2032-12-25","Catholic Christmas Day","BY",2032 +"2033-01-01","New Year's Day","BY",2033 +"2033-01-02","New Year's Day","BY",2033 +"2033-01-07","Orthodox Christmas Day","BY",2033 +"2033-03-08","Women's Day","BY",2033 +"2033-05-01","Labor Day","BY",2033 +"2033-05-03","Radunitsa","BY",2033 +"2033-05-09","Victory Day","BY",2033 +"2033-07-03","Independence Day (Republic Day)","BY",2033 +"2033-11-07","October Revolution Day","BY",2033 +"2033-12-25","Catholic Christmas Day","BY",2033 +"2034-01-01","New Year's Day","BY",2034 +"2034-01-02","New Year's Day","BY",2034 +"2034-01-07","Orthodox Christmas Day","BY",2034 +"2034-03-08","Women's Day","BY",2034 +"2034-04-18","Radunitsa","BY",2034 +"2034-05-01","Labor Day","BY",2034 +"2034-05-09","Victory Day","BY",2034 +"2034-07-03","Independence Day (Republic Day)","BY",2034 +"2034-11-07","October Revolution Day","BY",2034 +"2034-12-25","Catholic Christmas Day","BY",2034 +"2035-01-01","New Year's Day","BY",2035 +"2035-01-02","New Year's Day","BY",2035 +"2035-01-07","Orthodox Christmas Day","BY",2035 +"2035-03-08","Women's Day","BY",2035 +"2035-05-01","Labor Day","BY",2035 +"2035-05-08","Radunitsa","BY",2035 +"2035-05-09","Victory Day","BY",2035 +"2035-07-03","Independence Day (Republic Day)","BY",2035 +"2035-11-07","October Revolution Day","BY",2035 +"2035-12-25","Catholic Christmas Day","BY",2035 +"2036-01-01","New Year's Day","BY",2036 +"2036-01-02","New Year's Day","BY",2036 +"2036-01-07","Orthodox Christmas Day","BY",2036 +"2036-03-08","Women's Day","BY",2036 +"2036-04-29","Radunitsa","BY",2036 +"2036-05-01","Labor Day","BY",2036 +"2036-05-09","Victory Day","BY",2036 +"2036-07-03","Independence Day (Republic Day)","BY",2036 +"2036-11-07","October Revolution Day","BY",2036 +"2036-12-25","Catholic Christmas Day","BY",2036 +"2037-01-01","New Year's Day","BY",2037 +"2037-01-02","New Year's Day","BY",2037 +"2037-01-07","Orthodox Christmas Day","BY",2037 +"2037-03-08","Women's Day","BY",2037 +"2037-04-14","Radunitsa","BY",2037 +"2037-05-01","Labor Day","BY",2037 +"2037-05-09","Victory Day","BY",2037 +"2037-07-03","Independence Day (Republic Day)","BY",2037 +"2037-11-07","October Revolution Day","BY",2037 +"2037-12-25","Catholic Christmas Day","BY",2037 +"2038-01-01","New Year's Day","BY",2038 +"2038-01-02","New Year's Day","BY",2038 +"2038-01-07","Orthodox Christmas Day","BY",2038 +"2038-03-08","Women's Day","BY",2038 +"2038-05-01","Labor Day","BY",2038 +"2038-05-04","Radunitsa","BY",2038 +"2038-05-09","Victory Day","BY",2038 +"2038-07-03","Independence Day (Republic Day)","BY",2038 +"2038-11-07","October Revolution Day","BY",2038 +"2038-12-25","Catholic Christmas Day","BY",2038 +"2039-01-01","New Year's Day","BY",2039 +"2039-01-02","New Year's Day","BY",2039 +"2039-01-07","Orthodox Christmas Day","BY",2039 +"2039-03-08","Women's Day","BY",2039 +"2039-04-26","Radunitsa","BY",2039 +"2039-05-01","Labor Day","BY",2039 +"2039-05-09","Victory Day","BY",2039 +"2039-07-03","Independence Day (Republic Day)","BY",2039 +"2039-11-07","October Revolution Day","BY",2039 +"2039-12-25","Catholic Christmas Day","BY",2039 +"2040-01-01","New Year's Day","BY",2040 +"2040-01-02","New Year's Day","BY",2040 +"2040-01-07","Orthodox Christmas Day","BY",2040 +"2040-03-08","Women's Day","BY",2040 +"2040-05-01","Labor Day","BY",2040 +"2040-05-09","Victory Day","BY",2040 +"2040-05-15","Radunitsa","BY",2040 +"2040-07-03","Independence Day (Republic Day)","BY",2040 +"2040-11-07","October Revolution Day","BY",2040 +"2040-12-25","Catholic Christmas Day","BY",2040 +"2041-01-01","New Year's Day","BY",2041 +"2041-01-02","New Year's Day","BY",2041 +"2041-01-07","Orthodox Christmas Day","BY",2041 +"2041-03-08","Women's Day","BY",2041 +"2041-04-30","Radunitsa","BY",2041 +"2041-05-01","Labor Day","BY",2041 +"2041-05-09","Victory Day","BY",2041 +"2041-07-03","Independence Day (Republic Day)","BY",2041 +"2041-11-07","October Revolution Day","BY",2041 +"2041-12-25","Catholic Christmas Day","BY",2041 +"2042-01-01","New Year's Day","BY",2042 +"2042-01-02","New Year's Day","BY",2042 +"2042-01-07","Orthodox Christmas Day","BY",2042 +"2042-03-08","Women's Day","BY",2042 +"2042-04-22","Radunitsa","BY",2042 +"2042-05-01","Labor Day","BY",2042 +"2042-05-09","Victory Day","BY",2042 +"2042-07-03","Independence Day (Republic Day)","BY",2042 +"2042-11-07","October Revolution Day","BY",2042 +"2042-12-25","Catholic Christmas Day","BY",2042 +"2043-01-01","New Year's Day","BY",2043 +"2043-01-02","New Year's Day","BY",2043 +"2043-01-07","Orthodox Christmas Day","BY",2043 +"2043-03-08","Women's Day","BY",2043 +"2043-05-01","Labor Day","BY",2043 +"2043-05-09","Victory Day","BY",2043 +"2043-05-12","Radunitsa","BY",2043 +"2043-07-03","Independence Day (Republic Day)","BY",2043 +"2043-11-07","October Revolution Day","BY",2043 +"2043-12-25","Catholic Christmas Day","BY",2043 +"2044-01-01","New Year's Day","BY",2044 +"2044-01-02","New Year's Day","BY",2044 +"2044-01-07","Orthodox Christmas Day","BY",2044 +"2044-03-08","Women's Day","BY",2044 +"2044-05-01","Labor Day","BY",2044 +"2044-05-03","Radunitsa","BY",2044 +"2044-05-09","Victory Day","BY",2044 +"2044-07-03","Independence Day (Republic Day)","BY",2044 +"2044-11-07","October Revolution Day","BY",2044 +"2044-12-25","Catholic Christmas Day","BY",2044 +"1995-01-01","New Year's Day","CA",1995 +"1995-01-02","New Year's Day (Observed)","CA",1995 +"1995-04-14","Good Friday","CA",1995 +"1995-04-17","Easter Monday","CA",1995 +"1995-05-22","Victoria Day","CA",1995 +"1995-07-01","Canada Day","CA",1995 +"1995-07-03","Canada Day (Observed)","CA",1995 +"1995-08-07","Civic Holiday","CA",1995 +"1995-09-04","Labour Day","CA",1995 +"1995-10-09","Thanksgiving","CA",1995 +"1995-12-25","Christmas Day","CA",1995 +"1995-12-26","Boxing Day","CA",1995 +"1996-01-01","New Year's Day","CA",1996 +"1996-04-05","Good Friday","CA",1996 +"1996-04-08","Easter Monday","CA",1996 +"1996-05-20","Victoria Day","CA",1996 +"1996-07-01","Canada Day","CA",1996 +"1996-08-05","Civic Holiday","CA",1996 +"1996-09-02","Labour Day","CA",1996 +"1996-10-14","Thanksgiving","CA",1996 +"1996-12-25","Christmas Day","CA",1996 +"1996-12-26","Boxing Day","CA",1996 +"1997-01-01","New Year's Day","CA",1997 +"1997-03-28","Good Friday","CA",1997 +"1997-03-31","Easter Monday","CA",1997 +"1997-05-19","Victoria Day","CA",1997 +"1997-07-01","Canada Day","CA",1997 +"1997-08-04","Civic Holiday","CA",1997 +"1997-09-01","Labour Day","CA",1997 +"1997-10-13","Thanksgiving","CA",1997 +"1997-12-25","Christmas Day","CA",1997 +"1997-12-26","Boxing Day","CA",1997 +"1998-01-01","New Year's Day","CA",1998 +"1998-04-10","Good Friday","CA",1998 +"1998-04-13","Easter Monday","CA",1998 +"1998-05-18","Victoria Day","CA",1998 +"1998-07-01","Canada Day","CA",1998 +"1998-08-03","Civic Holiday","CA",1998 +"1998-09-07","Labour Day","CA",1998 +"1998-10-12","Thanksgiving","CA",1998 +"1998-12-25","Christmas Day","CA",1998 +"1998-12-26","Boxing Day","CA",1998 +"1998-12-28","Boxing Day (Observed)","CA",1998 +"1999-01-01","New Year's Day","CA",1999 +"1999-04-02","Good Friday","CA",1999 +"1999-04-05","Easter Monday","CA",1999 +"1999-05-24","Victoria Day","CA",1999 +"1999-07-01","Canada Day","CA",1999 +"1999-08-02","Civic Holiday","CA",1999 +"1999-09-06","Labour Day","CA",1999 +"1999-10-11","Thanksgiving","CA",1999 +"1999-12-25","Christmas Day","CA",1999 +"1999-12-26","Boxing Day","CA",1999 +"1999-12-27","Christmas Day (Observed)","CA",1999 +"1999-12-28","Boxing Day (Observed)","CA",1999 +"2000-01-01","New Year's Day","CA",2000 +"2000-01-03","New Year's Day (Observed)","CA",2000 +"2000-04-21","Good Friday","CA",2000 +"2000-04-24","Easter Monday","CA",2000 +"2000-05-22","Victoria Day","CA",2000 +"2000-07-01","Canada Day","CA",2000 +"2000-07-03","Canada Day (Observed)","CA",2000 +"2000-08-07","Civic Holiday","CA",2000 +"2000-09-04","Labour Day","CA",2000 +"2000-10-09","Thanksgiving","CA",2000 +"2000-12-25","Christmas Day","CA",2000 +"2000-12-26","Boxing Day","CA",2000 +"2001-01-01","New Year's Day","CA",2001 +"2001-04-13","Good Friday","CA",2001 +"2001-04-16","Easter Monday","CA",2001 +"2001-05-21","Victoria Day","CA",2001 +"2001-07-01","Canada Day","CA",2001 +"2001-07-02","Canada Day (Observed)","CA",2001 +"2001-08-06","Civic Holiday","CA",2001 +"2001-09-03","Labour Day","CA",2001 +"2001-10-08","Thanksgiving","CA",2001 +"2001-12-25","Christmas Day","CA",2001 +"2001-12-26","Boxing Day","CA",2001 +"2002-01-01","New Year's Day","CA",2002 +"2002-03-29","Good Friday","CA",2002 +"2002-04-01","Easter Monday","CA",2002 +"2002-05-20","Victoria Day","CA",2002 +"2002-07-01","Canada Day","CA",2002 +"2002-08-05","Civic Holiday","CA",2002 +"2002-09-02","Labour Day","CA",2002 +"2002-10-14","Thanksgiving","CA",2002 +"2002-12-25","Christmas Day","CA",2002 +"2002-12-26","Boxing Day","CA",2002 +"2003-01-01","New Year's Day","CA",2003 +"2003-04-18","Good Friday","CA",2003 +"2003-04-21","Easter Monday","CA",2003 +"2003-05-19","Victoria Day","CA",2003 +"2003-07-01","Canada Day","CA",2003 +"2003-08-04","Civic Holiday","CA",2003 +"2003-09-01","Labour Day","CA",2003 +"2003-10-13","Thanksgiving","CA",2003 +"2003-12-25","Christmas Day","CA",2003 +"2003-12-26","Boxing Day","CA",2003 +"2004-01-01","New Year's Day","CA",2004 +"2004-04-09","Good Friday","CA",2004 +"2004-04-12","Easter Monday","CA",2004 +"2004-05-24","Victoria Day","CA",2004 +"2004-07-01","Canada Day","CA",2004 +"2004-08-02","Civic Holiday","CA",2004 +"2004-09-06","Labour Day","CA",2004 +"2004-10-11","Thanksgiving","CA",2004 +"2004-12-25","Christmas Day","CA",2004 +"2004-12-26","Boxing Day","CA",2004 +"2004-12-27","Christmas Day (Observed)","CA",2004 +"2004-12-28","Boxing Day (Observed)","CA",2004 +"2005-01-01","New Year's Day","CA",2005 +"2005-01-03","New Year's Day (Observed)","CA",2005 +"2005-03-25","Good Friday","CA",2005 +"2005-03-28","Easter Monday","CA",2005 +"2005-05-23","Victoria Day","CA",2005 +"2005-07-01","Canada Day","CA",2005 +"2005-08-01","Civic Holiday","CA",2005 +"2005-09-05","Labour Day","CA",2005 +"2005-10-10","Thanksgiving","CA",2005 +"2005-12-25","Christmas Day","CA",2005 +"2005-12-26","Boxing Day","CA",2005 +"2005-12-27","Christmas Day (Observed)","CA",2005 +"2006-01-01","New Year's Day","CA",2006 +"2006-01-02","New Year's Day (Observed)","CA",2006 +"2006-04-14","Good Friday","CA",2006 +"2006-04-17","Easter Monday","CA",2006 +"2006-05-22","Victoria Day","CA",2006 +"2006-07-01","Canada Day","CA",2006 +"2006-07-03","Canada Day (Observed)","CA",2006 +"2006-08-07","Civic Holiday","CA",2006 +"2006-09-04","Labour Day","CA",2006 +"2006-10-09","Thanksgiving","CA",2006 +"2006-12-25","Christmas Day","CA",2006 +"2006-12-26","Boxing Day","CA",2006 +"2007-01-01","New Year's Day","CA",2007 +"2007-04-06","Good Friday","CA",2007 +"2007-04-09","Easter Monday","CA",2007 +"2007-05-21","Victoria Day","CA",2007 +"2007-07-01","Canada Day","CA",2007 +"2007-07-02","Canada Day (Observed)","CA",2007 +"2007-08-06","Civic Holiday","CA",2007 +"2007-09-03","Labour Day","CA",2007 +"2007-10-08","Thanksgiving","CA",2007 +"2007-12-25","Christmas Day","CA",2007 +"2007-12-26","Boxing Day","CA",2007 +"2008-01-01","New Year's Day","CA",2008 +"2008-02-18","Family Day","CA",2008 +"2008-03-21","Good Friday","CA",2008 +"2008-03-24","Easter Monday","CA",2008 +"2008-05-19","Victoria Day","CA",2008 +"2008-07-01","Canada Day","CA",2008 +"2008-08-04","Civic Holiday","CA",2008 +"2008-09-01","Labour Day","CA",2008 +"2008-10-13","Thanksgiving","CA",2008 +"2008-12-25","Christmas Day","CA",2008 +"2008-12-26","Boxing Day","CA",2008 +"2009-01-01","New Year's Day","CA",2009 +"2009-02-16","Family Day","CA",2009 +"2009-04-10","Good Friday","CA",2009 +"2009-04-13","Easter Monday","CA",2009 +"2009-05-18","Victoria Day","CA",2009 +"2009-07-01","Canada Day","CA",2009 +"2009-08-03","Civic Holiday","CA",2009 +"2009-09-07","Labour Day","CA",2009 +"2009-10-12","Thanksgiving","CA",2009 +"2009-12-25","Christmas Day","CA",2009 +"2009-12-26","Boxing Day","CA",2009 +"2009-12-28","Boxing Day (Observed)","CA",2009 +"2010-01-01","New Year's Day","CA",2010 +"2010-02-15","Family Day","CA",2010 +"2010-04-02","Good Friday","CA",2010 +"2010-04-05","Easter Monday","CA",2010 +"2010-05-24","Victoria Day","CA",2010 +"2010-07-01","Canada Day","CA",2010 +"2010-08-02","Civic Holiday","CA",2010 +"2010-09-06","Labour Day","CA",2010 +"2010-10-11","Thanksgiving","CA",2010 +"2010-12-25","Christmas Day","CA",2010 +"2010-12-26","Boxing Day","CA",2010 +"2010-12-27","Christmas Day (Observed)","CA",2010 +"2010-12-28","Boxing Day (Observed)","CA",2010 +"2011-01-01","New Year's Day","CA",2011 +"2011-01-03","New Year's Day (Observed)","CA",2011 +"2011-02-21","Family Day","CA",2011 +"2011-04-22","Good Friday","CA",2011 +"2011-04-25","Easter Monday","CA",2011 +"2011-05-23","Victoria Day","CA",2011 +"2011-07-01","Canada Day","CA",2011 +"2011-08-01","Civic Holiday","CA",2011 +"2011-09-05","Labour Day","CA",2011 +"2011-10-10","Thanksgiving","CA",2011 +"2011-12-25","Christmas Day","CA",2011 +"2011-12-26","Boxing Day","CA",2011 +"2011-12-27","Christmas Day (Observed)","CA",2011 +"2012-01-01","New Year's Day","CA",2012 +"2012-01-02","New Year's Day (Observed)","CA",2012 +"2012-02-20","Family Day","CA",2012 +"2012-04-06","Good Friday","CA",2012 +"2012-04-09","Easter Monday","CA",2012 +"2012-05-21","Victoria Day","CA",2012 +"2012-07-01","Canada Day","CA",2012 +"2012-07-02","Canada Day (Observed)","CA",2012 +"2012-08-06","Civic Holiday","CA",2012 +"2012-09-03","Labour Day","CA",2012 +"2012-10-08","Thanksgiving","CA",2012 +"2012-12-25","Christmas Day","CA",2012 +"2012-12-26","Boxing Day","CA",2012 +"2013-01-01","New Year's Day","CA",2013 +"2013-02-18","Family Day","CA",2013 +"2013-03-29","Good Friday","CA",2013 +"2013-04-01","Easter Monday","CA",2013 +"2013-05-20","Victoria Day","CA",2013 +"2013-07-01","Canada Day","CA",2013 +"2013-08-05","Civic Holiday","CA",2013 +"2013-09-02","Labour Day","CA",2013 +"2013-10-14","Thanksgiving","CA",2013 +"2013-12-25","Christmas Day","CA",2013 +"2013-12-26","Boxing Day","CA",2013 +"2014-01-01","New Year's Day","CA",2014 +"2014-02-17","Family Day","CA",2014 +"2014-04-18","Good Friday","CA",2014 +"2014-04-21","Easter Monday","CA",2014 +"2014-05-19","Victoria Day","CA",2014 +"2014-07-01","Canada Day","CA",2014 +"2014-08-04","Civic Holiday","CA",2014 +"2014-09-01","Labour Day","CA",2014 +"2014-10-13","Thanksgiving","CA",2014 +"2014-12-25","Christmas Day","CA",2014 +"2014-12-26","Boxing Day","CA",2014 +"2015-01-01","New Year's Day","CA",2015 +"2015-02-16","Family Day","CA",2015 +"2015-04-03","Good Friday","CA",2015 +"2015-04-06","Easter Monday","CA",2015 +"2015-05-18","Victoria Day","CA",2015 +"2015-07-01","Canada Day","CA",2015 +"2015-08-03","Civic Holiday","CA",2015 +"2015-09-07","Labour Day","CA",2015 +"2015-10-12","Thanksgiving","CA",2015 +"2015-12-25","Christmas Day","CA",2015 +"2015-12-26","Boxing Day","CA",2015 +"2015-12-28","Boxing Day (Observed)","CA",2015 +"2016-01-01","New Year's Day","CA",2016 +"2016-02-15","Family Day","CA",2016 +"2016-03-25","Good Friday","CA",2016 +"2016-03-28","Easter Monday","CA",2016 +"2016-05-23","Victoria Day","CA",2016 +"2016-07-01","Canada Day","CA",2016 +"2016-08-01","Civic Holiday","CA",2016 +"2016-09-05","Labour Day","CA",2016 +"2016-10-10","Thanksgiving","CA",2016 +"2016-12-25","Christmas Day","CA",2016 +"2016-12-26","Boxing Day","CA",2016 +"2016-12-27","Christmas Day (Observed)","CA",2016 +"2017-01-01","New Year's Day","CA",2017 +"2017-01-02","New Year's Day (Observed)","CA",2017 +"2017-02-20","Family Day","CA",2017 +"2017-04-14","Good Friday","CA",2017 +"2017-04-17","Easter Monday","CA",2017 +"2017-05-22","Victoria Day","CA",2017 +"2017-07-01","Canada Day","CA",2017 +"2017-07-03","Canada Day (Observed)","CA",2017 +"2017-08-07","Civic Holiday","CA",2017 +"2017-09-04","Labour Day","CA",2017 +"2017-10-09","Thanksgiving","CA",2017 +"2017-12-25","Christmas Day","CA",2017 +"2017-12-26","Boxing Day","CA",2017 +"2018-01-01","New Year's Day","CA",2018 +"2018-02-19","Family Day","CA",2018 +"2018-03-30","Good Friday","CA",2018 +"2018-04-02","Easter Monday","CA",2018 +"2018-05-21","Victoria Day","CA",2018 +"2018-07-01","Canada Day","CA",2018 +"2018-07-02","Canada Day (Observed)","CA",2018 +"2018-08-06","Civic Holiday","CA",2018 +"2018-09-03","Labour Day","CA",2018 +"2018-10-08","Thanksgiving","CA",2018 +"2018-12-25","Christmas Day","CA",2018 +"2018-12-26","Boxing Day","CA",2018 +"2019-01-01","New Year's Day","CA",2019 +"2019-02-18","Family Day","CA",2019 +"2019-04-19","Good Friday","CA",2019 +"2019-04-22","Easter Monday","CA",2019 +"2019-05-20","Victoria Day","CA",2019 +"2019-07-01","Canada Day","CA",2019 +"2019-08-05","Civic Holiday","CA",2019 +"2019-09-02","Labour Day","CA",2019 +"2019-10-14","Thanksgiving","CA",2019 +"2019-12-25","Christmas Day","CA",2019 +"2019-12-26","Boxing Day","CA",2019 +"2020-01-01","New Year's Day","CA",2020 +"2020-02-17","Family Day","CA",2020 +"2020-04-10","Good Friday","CA",2020 +"2020-04-13","Easter Monday","CA",2020 +"2020-05-18","Victoria Day","CA",2020 +"2020-07-01","Canada Day","CA",2020 +"2020-08-03","Civic Holiday","CA",2020 +"2020-09-07","Labour Day","CA",2020 +"2020-10-12","Thanksgiving","CA",2020 +"2020-12-25","Christmas Day","CA",2020 +"2020-12-26","Boxing Day","CA",2020 +"2020-12-28","Boxing Day (Observed)","CA",2020 +"2021-01-01","New Year's Day","CA",2021 +"2021-02-15","Family Day","CA",2021 +"2021-04-02","Good Friday","CA",2021 +"2021-04-05","Easter Monday","CA",2021 +"2021-05-24","Victoria Day","CA",2021 +"2021-07-01","Canada Day","CA",2021 +"2021-08-02","Civic Holiday","CA",2021 +"2021-09-06","Labour Day","CA",2021 +"2021-10-11","Thanksgiving","CA",2021 +"2021-12-25","Christmas Day","CA",2021 +"2021-12-26","Boxing Day","CA",2021 +"2021-12-27","Christmas Day (Observed)","CA",2021 +"2021-12-28","Boxing Day (Observed)","CA",2021 +"2022-01-01","New Year's Day","CA",2022 +"2022-01-03","New Year's Day (Observed)","CA",2022 +"2022-02-21","Family Day","CA",2022 +"2022-04-15","Good Friday","CA",2022 +"2022-04-18","Easter Monday","CA",2022 +"2022-05-23","Victoria Day","CA",2022 +"2022-07-01","Canada Day","CA",2022 +"2022-08-01","Civic Holiday","CA",2022 +"2022-09-05","Labour Day","CA",2022 +"2022-10-10","Thanksgiving","CA",2022 +"2022-12-25","Christmas Day","CA",2022 +"2022-12-26","Boxing Day","CA",2022 +"2022-12-27","Christmas Day (Observed)","CA",2022 +"2023-01-01","New Year's Day","CA",2023 +"2023-01-02","New Year's Day (Observed)","CA",2023 +"2023-02-20","Family Day","CA",2023 +"2023-04-07","Good Friday","CA",2023 +"2023-04-10","Easter Monday","CA",2023 +"2023-05-22","Victoria Day","CA",2023 +"2023-07-01","Canada Day","CA",2023 +"2023-07-03","Canada Day (Observed)","CA",2023 +"2023-08-07","Civic Holiday","CA",2023 +"2023-09-04","Labour Day","CA",2023 +"2023-10-09","Thanksgiving","CA",2023 +"2023-12-25","Christmas Day","CA",2023 +"2023-12-26","Boxing Day","CA",2023 +"2024-01-01","New Year's Day","CA",2024 +"2024-02-19","Family Day","CA",2024 +"2024-03-29","Good Friday","CA",2024 +"2024-04-01","Easter Monday","CA",2024 +"2024-05-20","Victoria Day","CA",2024 +"2024-07-01","Canada Day","CA",2024 +"2024-08-05","Civic Holiday","CA",2024 +"2024-09-02","Labour Day","CA",2024 +"2024-10-14","Thanksgiving","CA",2024 +"2024-12-25","Christmas Day","CA",2024 +"2024-12-26","Boxing Day","CA",2024 +"2025-01-01","New Year's Day","CA",2025 +"2025-02-17","Family Day","CA",2025 +"2025-04-18","Good Friday","CA",2025 +"2025-04-21","Easter Monday","CA",2025 +"2025-05-19","Victoria Day","CA",2025 +"2025-07-01","Canada Day","CA",2025 +"2025-08-04","Civic Holiday","CA",2025 +"2025-09-01","Labour Day","CA",2025 +"2025-10-13","Thanksgiving","CA",2025 +"2025-12-25","Christmas Day","CA",2025 +"2025-12-26","Boxing Day","CA",2025 +"2026-01-01","New Year's Day","CA",2026 +"2026-02-16","Family Day","CA",2026 +"2026-04-03","Good Friday","CA",2026 +"2026-04-06","Easter Monday","CA",2026 +"2026-05-18","Victoria Day","CA",2026 +"2026-07-01","Canada Day","CA",2026 +"2026-08-03","Civic Holiday","CA",2026 +"2026-09-07","Labour Day","CA",2026 +"2026-10-12","Thanksgiving","CA",2026 +"2026-12-25","Christmas Day","CA",2026 +"2026-12-26","Boxing Day","CA",2026 +"2026-12-28","Boxing Day (Observed)","CA",2026 +"2027-01-01","New Year's Day","CA",2027 +"2027-02-15","Family Day","CA",2027 +"2027-03-26","Good Friday","CA",2027 +"2027-03-29","Easter Monday","CA",2027 +"2027-05-24","Victoria Day","CA",2027 +"2027-07-01","Canada Day","CA",2027 +"2027-08-02","Civic Holiday","CA",2027 +"2027-09-06","Labour Day","CA",2027 +"2027-10-11","Thanksgiving","CA",2027 +"2027-12-25","Christmas Day","CA",2027 +"2027-12-26","Boxing Day","CA",2027 +"2027-12-27","Christmas Day (Observed)","CA",2027 +"2027-12-28","Boxing Day (Observed)","CA",2027 +"2028-01-01","New Year's Day","CA",2028 +"2028-01-03","New Year's Day (Observed)","CA",2028 +"2028-02-21","Family Day","CA",2028 +"2028-04-14","Good Friday","CA",2028 +"2028-04-17","Easter Monday","CA",2028 +"2028-05-22","Victoria Day","CA",2028 +"2028-07-01","Canada Day","CA",2028 +"2028-07-03","Canada Day (Observed)","CA",2028 +"2028-08-07","Civic Holiday","CA",2028 +"2028-09-04","Labour Day","CA",2028 +"2028-10-09","Thanksgiving","CA",2028 +"2028-12-25","Christmas Day","CA",2028 +"2028-12-26","Boxing Day","CA",2028 +"2029-01-01","New Year's Day","CA",2029 +"2029-02-19","Family Day","CA",2029 +"2029-03-30","Good Friday","CA",2029 +"2029-04-02","Easter Monday","CA",2029 +"2029-05-21","Victoria Day","CA",2029 +"2029-07-01","Canada Day","CA",2029 +"2029-07-02","Canada Day (Observed)","CA",2029 +"2029-08-06","Civic Holiday","CA",2029 +"2029-09-03","Labour Day","CA",2029 +"2029-10-08","Thanksgiving","CA",2029 +"2029-12-25","Christmas Day","CA",2029 +"2029-12-26","Boxing Day","CA",2029 +"2030-01-01","New Year's Day","CA",2030 +"2030-02-18","Family Day","CA",2030 +"2030-04-19","Good Friday","CA",2030 +"2030-04-22","Easter Monday","CA",2030 +"2030-05-20","Victoria Day","CA",2030 +"2030-07-01","Canada Day","CA",2030 +"2030-08-05","Civic Holiday","CA",2030 +"2030-09-02","Labour Day","CA",2030 +"2030-10-14","Thanksgiving","CA",2030 +"2030-12-25","Christmas Day","CA",2030 +"2030-12-26","Boxing Day","CA",2030 +"2031-01-01","New Year's Day","CA",2031 +"2031-02-17","Family Day","CA",2031 +"2031-04-11","Good Friday","CA",2031 +"2031-04-14","Easter Monday","CA",2031 +"2031-05-19","Victoria Day","CA",2031 +"2031-07-01","Canada Day","CA",2031 +"2031-08-04","Civic Holiday","CA",2031 +"2031-09-01","Labour Day","CA",2031 +"2031-10-13","Thanksgiving","CA",2031 +"2031-12-25","Christmas Day","CA",2031 +"2031-12-26","Boxing Day","CA",2031 +"2032-01-01","New Year's Day","CA",2032 +"2032-02-16","Family Day","CA",2032 +"2032-03-26","Good Friday","CA",2032 +"2032-03-29","Easter Monday","CA",2032 +"2032-05-24","Victoria Day","CA",2032 +"2032-07-01","Canada Day","CA",2032 +"2032-08-02","Civic Holiday","CA",2032 +"2032-09-06","Labour Day","CA",2032 +"2032-10-11","Thanksgiving","CA",2032 +"2032-12-25","Christmas Day","CA",2032 +"2032-12-26","Boxing Day","CA",2032 +"2032-12-27","Christmas Day (Observed)","CA",2032 +"2032-12-28","Boxing Day (Observed)","CA",2032 +"2033-01-01","New Year's Day","CA",2033 +"2033-01-03","New Year's Day (Observed)","CA",2033 +"2033-02-21","Family Day","CA",2033 +"2033-04-15","Good Friday","CA",2033 +"2033-04-18","Easter Monday","CA",2033 +"2033-05-23","Victoria Day","CA",2033 +"2033-07-01","Canada Day","CA",2033 +"2033-08-01","Civic Holiday","CA",2033 +"2033-09-05","Labour Day","CA",2033 +"2033-10-10","Thanksgiving","CA",2033 +"2033-12-25","Christmas Day","CA",2033 +"2033-12-26","Boxing Day","CA",2033 +"2033-12-27","Christmas Day (Observed)","CA",2033 +"2034-01-01","New Year's Day","CA",2034 +"2034-01-02","New Year's Day (Observed)","CA",2034 +"2034-02-20","Family Day","CA",2034 +"2034-04-07","Good Friday","CA",2034 +"2034-04-10","Easter Monday","CA",2034 +"2034-05-22","Victoria Day","CA",2034 +"2034-07-01","Canada Day","CA",2034 +"2034-07-03","Canada Day (Observed)","CA",2034 +"2034-08-07","Civic Holiday","CA",2034 +"2034-09-04","Labour Day","CA",2034 +"2034-10-09","Thanksgiving","CA",2034 +"2034-12-25","Christmas Day","CA",2034 +"2034-12-26","Boxing Day","CA",2034 +"2035-01-01","New Year's Day","CA",2035 +"2035-02-19","Family Day","CA",2035 +"2035-03-23","Good Friday","CA",2035 +"2035-03-26","Easter Monday","CA",2035 +"2035-05-21","Victoria Day","CA",2035 +"2035-07-01","Canada Day","CA",2035 +"2035-07-02","Canada Day (Observed)","CA",2035 +"2035-08-06","Civic Holiday","CA",2035 +"2035-09-03","Labour Day","CA",2035 +"2035-10-08","Thanksgiving","CA",2035 +"2035-12-25","Christmas Day","CA",2035 +"2035-12-26","Boxing Day","CA",2035 +"2036-01-01","New Year's Day","CA",2036 +"2036-02-18","Family Day","CA",2036 +"2036-04-11","Good Friday","CA",2036 +"2036-04-14","Easter Monday","CA",2036 +"2036-05-19","Victoria Day","CA",2036 +"2036-07-01","Canada Day","CA",2036 +"2036-08-04","Civic Holiday","CA",2036 +"2036-09-01","Labour Day","CA",2036 +"2036-10-13","Thanksgiving","CA",2036 +"2036-12-25","Christmas Day","CA",2036 +"2036-12-26","Boxing Day","CA",2036 +"2037-01-01","New Year's Day","CA",2037 +"2037-02-16","Family Day","CA",2037 +"2037-04-03","Good Friday","CA",2037 +"2037-04-06","Easter Monday","CA",2037 +"2037-05-18","Victoria Day","CA",2037 +"2037-07-01","Canada Day","CA",2037 +"2037-08-03","Civic Holiday","CA",2037 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Day","CA",2039 +"2039-08-01","Civic Holiday","CA",2039 +"2039-09-05","Labour Day","CA",2039 +"2039-10-10","Thanksgiving","CA",2039 +"2039-12-25","Christmas Day","CA",2039 +"2039-12-26","Boxing Day","CA",2039 +"2039-12-27","Christmas Day (Observed)","CA",2039 +"2040-01-01","New Year's Day","CA",2040 +"2040-01-02","New Year's Day (Observed)","CA",2040 +"2040-02-20","Family Day","CA",2040 +"2040-03-30","Good Friday","CA",2040 +"2040-04-02","Easter Monday","CA",2040 +"2040-05-21","Victoria Day","CA",2040 +"2040-07-01","Canada Day","CA",2040 +"2040-07-02","Canada Day (Observed)","CA",2040 +"2040-08-06","Civic Holiday","CA",2040 +"2040-09-03","Labour Day","CA",2040 +"2040-10-08","Thanksgiving","CA",2040 +"2040-12-25","Christmas Day","CA",2040 +"2040-12-26","Boxing Day","CA",2040 +"2041-01-01","New Year's Day","CA",2041 +"2041-02-18","Family Day","CA",2041 +"2041-04-19","Good Friday","CA",2041 +"2041-04-22","Easter Monday","CA",2041 +"2041-05-20","Victoria Day","CA",2041 +"2041-07-01","Canada Day","CA",2041 +"2041-08-05","Civic Holiday","CA",2041 +"2041-09-02","Labour Day","CA",2041 +"2041-10-14","Thanksgiving","CA",2041 +"2041-12-25","Christmas Day","CA",2041 +"2041-12-26","Boxing Day","CA",2041 +"2042-01-01","New Year's Day","CA",2042 +"2042-02-17","Family Day","CA",2042 +"2042-04-04","Good Friday","CA",2042 +"2042-04-07","Easter Monday","CA",2042 +"2042-05-19","Victoria Day","CA",2042 +"2042-07-01","Canada Day","CA",2042 +"2042-08-04","Civic Holiday","CA",2042 +"2042-09-01","Labour Day","CA",2042 +"2042-10-13","Thanksgiving","CA",2042 +"2042-12-25","Christmas Day","CA",2042 +"2042-12-26","Boxing Day","CA",2042 +"2043-01-01","New Year's Day","CA",2043 +"2043-02-16","Family Day","CA",2043 +"2043-03-27","Good Friday","CA",2043 +"2043-03-30","Easter Monday","CA",2043 +"2043-05-18","Victoria Day","CA",2043 +"2043-07-01","Canada Day","CA",2043 +"2043-08-03","Civic Holiday","CA",2043 +"2043-09-07","Labour Day","CA",2043 +"2043-10-12","Thanksgiving","CA",2043 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Day","CL",1998 +"1998-11-01","All Saints' Day","CL",1998 +"1998-12-08","Immaculate Conception","CL",1998 +"1998-12-25","Christmas","CL",1998 +"1999-01-01","New Year's Day","CL",1999 +"1999-04-02","Good Friday","CL",1999 +"1999-04-03","Holy Saturday","CL",1999 +"1999-05-01","Labour Day","CL",1999 +"1999-05-21","Navy Day","CL",1999 +"1999-06-03","Corpus Christi","CL",1999 +"1999-06-29","Saint Peter and Saint Paul","CL",1999 +"1999-08-15","Assumption of Mary","CL",1999 +"1999-09-06","Day of National Unity","CL",1999 +"1999-09-18","Independence Day","CL",1999 +"1999-09-19","Army Day","CL",1999 +"1999-10-12","Columbus Day","CL",1999 +"1999-11-01","All Saints' Day","CL",1999 +"1999-12-08","Immaculate Conception","CL",1999 +"1999-12-25","Christmas","CL",1999 +"2000-01-01","New Year's Day","CL",2000 +"2000-04-21","Good Friday","CL",2000 +"2000-04-22","Holy Saturday","CL",2000 +"2000-05-01","Labour Day","CL",2000 +"2000-05-21","Navy Day","CL",2000 +"2000-06-19","Corpus Christi","CL",2000 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Conception","CL",2001 +"2001-12-25","Christmas","CL",2001 +"2002-01-01","New Year's Day","CL",2002 +"2002-03-29","Good Friday","CL",2002 +"2002-03-30","Holy Saturday","CL",2002 +"2002-05-01","Labour Day","CL",2002 +"2002-05-21","Navy Day","CL",2002 +"2002-05-27","Corpus Christi","CL",2002 +"2002-06-29","Saint Peter and Saint Paul","CL",2002 +"2002-08-15","Assumption of Mary","CL",2002 +"2002-09-18","Independence Day","CL",2002 +"2002-09-19","Army Day","CL",2002 +"2002-10-12","Meeting of Two Worlds' Day","CL",2002 +"2002-11-01","All Saints' Day","CL",2002 +"2002-12-08","Immaculate Conception","CL",2002 +"2002-12-25","Christmas","CL",2002 +"2003-01-01","New Year's Day","CL",2003 +"2003-04-18","Good Friday","CL",2003 +"2003-04-19","Holy Saturday","CL",2003 +"2003-05-01","Labour Day","CL",2003 +"2003-05-21","Navy Day","CL",2003 +"2003-06-16","Corpus Christi","CL",2003 +"2003-06-29","Saint Peter and Saint Paul","CL",2003 +"2003-08-15","Assumption of Mary","CL",2003 +"2003-09-18","Independence Day","CL",2003 +"2003-09-19","Army Day","CL",2003 +"2003-10-12","Meeting of Two Worlds' Day","CL",2003 +"2003-11-01","All Saints' Day","CL",2003 +"2003-12-08","Immaculate Conception","CL",2003 +"2003-12-25","Christmas","CL",2003 +"2004-01-01","New Year's Day","CL",2004 +"2004-04-09","Good Friday","CL",2004 +"2004-04-10","Holy Saturday","CL",2004 +"2004-05-01","Labour Day","CL",2004 +"2004-05-21","Navy Day","CL",2004 +"2004-06-07","Corpus Christi","CL",2004 +"2004-06-28","Saint Peter and Saint Paul","CL",2004 +"2004-08-15","Assumption of Mary","CL",2004 +"2004-09-18","Independence Day","CL",2004 +"2004-09-19","Army Day","CL",2004 +"2004-10-11","Meeting of Two Worlds' Day","CL",2004 +"2004-11-01","All Saints' Day","CL",2004 +"2004-12-08","Immaculate Conception","CL",2004 +"2004-12-25","Christmas","CL",2004 +"2005-01-01","New Year's Day","CL",2005 +"2005-03-25","Good Friday","CL",2005 +"2005-03-26","Holy Saturday","CL",2005 +"2005-05-01","Labour Day","CL",2005 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Mary","CL",2008 +"2008-09-18","Independence Day","CL",2008 +"2008-09-19","Army Day","CL",2008 +"2008-10-12","Meeting of Two Worlds' Day","CL",2008 +"2008-10-31","Reformation Day","CL",2008 +"2008-11-01","All Saints' Day","CL",2008 +"2008-12-08","Immaculate Conception","CL",2008 +"2008-12-25","Christmas","CL",2008 +"2009-01-01","New Year's Day","CL",2009 +"2009-04-10","Good Friday","CL",2009 +"2009-04-11","Holy Saturday","CL",2009 +"2009-05-01","Labour Day","CL",2009 +"2009-05-21","Navy Day","CL",2009 +"2009-06-29","Saint Peter and Saint Paul","CL",2009 +"2009-07-16","Our Lady of Mount Carmel","CL",2009 +"2009-08-15","Assumption of Mary","CL",2009 +"2009-09-18","Independence Day","CL",2009 +"2009-09-19","Army Day","CL",2009 +"2009-10-12","Meeting of Two Worlds' Day","CL",2009 +"2009-10-31","Reformation Day","CL",2009 +"2009-11-01","All Saints' Day","CL",2009 +"2009-12-08","Immaculate Conception","CL",2009 +"2009-12-25","Christmas","CL",2009 +"2010-01-01","New Year's Day","CL",2010 +"2010-04-02","Good Friday","CL",2010 +"2010-04-03","Holy Saturday","CL",2010 +"2010-05-01","Labour Day","CL",2010 +"2010-05-21","Navy Day","CL",2010 +"2010-06-28","Saint Peter and Saint Paul","CL",2010 +"2010-07-16","Our Lady of Mount Carmel","CL",2010 +"2010-08-15","Assumption of Mary","CL",2010 +"2010-09-18","Independence Day","CL",2010 +"2010-09-19","Army Day","CL",2010 +"2010-10-11","Meeting of Two Worlds' Day","CL",2010 +"2010-10-31","Reformation Day","CL",2010 +"2010-11-01","All Saints' Day","CL",2010 +"2010-12-08","Immaculate Conception","CL",2010 +"2010-12-25","Christmas","CL",2010 +"2011-01-01","New Year's Day","CL",2011 +"2011-04-22","Good Friday","CL",2011 +"2011-04-23","Holy Saturday","CL",2011 +"2011-05-01","Labour Day","CL",2011 +"2011-05-21","Navy Day","CL",2011 +"2011-06-27","Saint Peter and Saint Paul","CL",2011 +"2011-07-16","Our Lady of Mount Carmel","CL",2011 +"2011-08-15","Assumption of Mary","CL",2011 +"2011-09-18","Independence Day","CL",2011 +"2011-09-19","Army Day","CL",2011 +"2011-10-10","Meeting of Two Worlds' Day","CL",2011 +"2011-10-31","Reformation Day","CL",2011 +"2011-11-01","All Saints' Day","CL",2011 +"2011-12-08","Immaculate Conception","CL",2011 +"2011-12-25","Christmas","CL",2011 +"2012-01-01","New Year's Day","CL",2012 +"2012-04-06","Good Friday","CL",2012 +"2012-04-07","Holy Saturday","CL",2012 +"2012-05-01","Labour Day","CL",2012 +"2012-05-21","Navy Day","CL",2012 +"2012-07-02","Saint Peter and Saint Paul","CL",2012 +"2012-07-16","Our Lady of Mount Carmel","CL",2012 +"2012-08-15","Assumption of Mary","CL",2012 +"2012-09-17","National Holiday","CL",2012 +"2012-09-18","Independence Day","CL",2012 +"2012-09-19","Army Day","CL",2012 +"2012-10-15","Meeting of Two Worlds' Day","CL",2012 +"2012-11-01","All Saints' Day","CL",2012 +"2012-11-02","Reformation Day","CL",2012 +"2012-12-08","Immaculate Conception","CL",2012 +"2012-12-25","Christmas","CL",2012 +"2013-01-01","New Year's Day","CL",2013 +"2013-03-29","Good Friday","CL",2013 +"2013-03-30","Holy Saturday","CL",2013 +"2013-05-01","Labour Day","CL",2013 +"2013-05-21","Navy Day","CL",2013 +"2013-06-29","Saint Peter and Saint Paul","CL",2013 +"2013-07-16","Our Lady of Mount Carmel","CL",2013 +"2013-08-15","Assumption of Mary","CL",2013 +"2013-09-18","Independence Day","CL",2013 +"2013-09-19","Army Day","CL",2013 +"2013-09-20","National Holiday","CL",2013 +"2013-10-12","Meeting of Two Worlds' Day","CL",2013 +"2013-10-31","Reformation Day","CL",2013 +"2013-11-01","All Saints' Day","CL",2013 +"2013-12-08","Immaculate Conception","CL",2013 +"2013-12-25","Christmas","CL",2013 +"2014-01-01","New Year's Day","CL",2014 +"2014-04-18","Good Friday","CL",2014 +"2014-04-19","Holy Saturday","CL",2014 +"2014-05-01","Labour Day","CL",2014 +"2014-05-21","Navy Day","CL",2014 +"2014-06-29","Saint Peter and Saint Paul","CL",2014 +"2014-07-16","Our Lady of Mount Carmel","CL",2014 +"2014-08-15","Assumption of Mary","CL",2014 +"2014-09-18","Independence Day","CL",2014 +"2014-09-19","Army Day","CL",2014 +"2014-10-12","Meeting of Two Worlds' Day","CL",2014 +"2014-10-31","Reformation Day","CL",2014 +"2014-11-01","All Saints' Day","CL",2014 +"2014-12-08","Immaculate Conception","CL",2014 +"2014-12-25","Christmas","CL",2014 +"2015-01-01","New Year's Day","CL",2015 +"2015-04-03","Good Friday","CL",2015 +"2015-04-04","Holy Saturday","CL",2015 +"2015-05-01","Labour Day","CL",2015 +"2015-05-21","Navy Day","CL",2015 +"2015-06-29","Saint Peter and Saint Paul","CL",2015 +"2015-07-16","Our Lady of Mount Carmel","CL",2015 +"2015-08-15","Assumption of Mary","CL",2015 +"2015-09-18","Independence Day","CL",2015 +"2015-09-19","Army Day","CL",2015 +"2015-10-12","Meeting of Two Worlds' Day","CL",2015 +"2015-10-31","Reformation Day","CL",2015 +"2015-11-01","All Saints' Day","CL",2015 +"2015-12-08","Immaculate Conception","CL",2015 +"2015-12-25","Christmas","CL",2015 +"2016-01-01","New Year's Day","CL",2016 +"2016-03-25","Good Friday","CL",2016 +"2016-03-26","Holy Saturday","CL",2016 +"2016-05-01","Labour Day","CL",2016 +"2016-05-21","Navy Day","CL",2016 +"2016-06-27","Saint Peter and Saint Paul","CL",2016 +"2016-07-16","Our Lady of Mount Carmel","CL",2016 +"2016-08-15","Assumption of Mary","CL",2016 +"2016-09-18","Independence Day","CL",2016 +"2016-09-19","Army Day","CL",2016 +"2016-10-10","Meeting of Two Worlds' Day","CL",2016 +"2016-10-31","Reformation Day","CL",2016 +"2016-11-01","All Saints' Day","CL",2016 +"2016-12-08","Immaculate Conception","CL",2016 +"2016-12-25","Christmas","CL",2016 +"2017-01-01","New Year's Day","CL",2017 +"2017-01-02","National Holiday","CL",2017 +"2017-04-14","Good Friday","CL",2017 +"2017-04-15","Holy Saturday","CL",2017 +"2017-05-01","Labour Day","CL",2017 +"2017-05-21","Navy Day","CL",2017 +"2017-06-26","Saint Peter and Saint Paul","CL",2017 +"2017-07-16","Our Lady of Mount Carmel","CL",2017 +"2017-08-15","Assumption of Mary","CL",2017 +"2017-09-18","Independence Day","CL",2017 +"2017-09-19","Army Day","CL",2017 +"2017-10-09","Meeting of Two Worlds' Day","CL",2017 +"2017-10-27","Reformation Day","CL",2017 +"2017-11-01","All Saints' Day","CL",2017 +"2017-12-08","Immaculate Conception","CL",2017 +"2017-12-25","Christmas","CL",2017 +"2018-01-01","New Year's Day","CL",2018 +"2018-03-30","Good Friday","CL",2018 +"2018-03-31","Holy Saturday","CL",2018 +"2018-05-01","Labour Day","CL",2018 +"2018-05-21","Navy Day","CL",2018 +"2018-07-02","Saint Peter and Saint Paul","CL",2018 +"2018-07-16","Our Lady of Mount Carmel","CL",2018 +"2018-08-15","Assumption of Mary","CL",2018 +"2018-09-17","National Holiday","CL",2018 +"2018-09-18","Independence Day","CL",2018 +"2018-09-19","Army Day","CL",2018 +"2018-10-15","Meeting of Two Worlds' Day","CL",2018 +"2018-11-01","All Saints' Day","CL",2018 +"2018-11-02","Reformation Day","CL",2018 +"2018-12-08","Immaculate Conception","CL",2018 +"2018-12-25","Christmas","CL",2018 +"2019-01-01","New Year's Day","CL",2019 +"2019-04-19","Good Friday","CL",2019 +"2019-04-20","Holy Saturday","CL",2019 +"2019-05-01","Labour Day","CL",2019 +"2019-05-21","Navy Day","CL",2019 +"2019-06-29","Saint Peter and Saint Paul","CL",2019 +"2019-07-16","Our Lady of Mount Carmel","CL",2019 +"2019-08-15","Assumption of Mary","CL",2019 +"2019-09-18","Independence Day","CL",2019 +"2019-09-19","Army Day","CL",2019 +"2019-09-20","National Holiday","CL",2019 +"2019-10-12","Meeting of Two Worlds' Day","CL",2019 +"2019-10-31","Reformation Day","CL",2019 +"2019-11-01","All Saints' Day","CL",2019 +"2019-12-08","Immaculate Conception","CL",2019 +"2019-12-25","Christmas","CL",2019 +"2020-01-01","New Year's Day","CL",2020 +"2020-04-10","Good Friday","CL",2020 +"2020-04-11","Holy Saturday","CL",2020 +"2020-05-01","Labour Day","CL",2020 +"2020-05-21","Navy Day","CL",2020 +"2020-06-29","Saint Peter and Saint Paul","CL",2020 +"2020-07-16","Our Lady of Mount Carmel","CL",2020 +"2020-08-15","Assumption of Mary","CL",2020 +"2020-09-18","Independence Day","CL",2020 +"2020-09-19","Army Day","CL",2020 +"2020-10-12","Meeting of Two Worlds' Day","CL",2020 +"2020-10-31","Reformation Day","CL",2020 +"2020-11-01","All Saints' Day","CL",2020 +"2020-12-08","Immaculate Conception","CL",2020 +"2020-12-25","Christmas","CL",2020 +"2021-01-01","New Year's Day","CL",2021 +"2021-04-02","Good Friday","CL",2021 +"2021-04-03","Holy Saturday","CL",2021 +"2021-05-01","Labour Day","CL",2021 +"2021-05-21","Navy Day","CL",2021 +"2021-06-21","National Day of Indigenous Peoples","CL",2021 +"2021-06-28","Saint Peter and Saint Paul","CL",2021 +"2021-07-16","Our Lady of Mount Carmel","CL",2021 +"2021-08-15","Assumption of Mary","CL",2021 +"2021-09-17","National Holiday","CL",2021 +"2021-09-18","Independence Day","CL",2021 +"2021-09-19","Army Day","CL",2021 +"2021-10-11","Meeting of Two Worlds' Day","CL",2021 +"2021-10-31","Reformation Day","CL",2021 +"2021-11-01","All Saints' Day","CL",2021 +"2021-12-08","Immaculate Conception","CL",2021 +"2021-12-25","Christmas","CL",2021 +"2022-01-01","New Year's Day","CL",2022 +"2022-04-15","Good Friday","CL",2022 +"2022-04-16","Holy Saturday","CL",2022 +"2022-05-01","Labour Day","CL",2022 +"2022-05-21","Navy Day","CL",2022 +"2022-06-21","National Day of Indigenous Peoples","CL",2022 +"2022-06-27","Saint Peter and Saint Paul","CL",2022 +"2022-07-16","Our Lady of Mount Carmel","CL",2022 +"2022-08-15","Assumption of Mary","CL",2022 +"2022-09-16","National Holiday","CL",2022 +"2022-09-18","Independence Day","CL",2022 +"2022-09-19","Army Day","CL",2022 +"2022-10-10","Meeting of Two Worlds' Day","CL",2022 +"2022-10-31","Reformation Day","CL",2022 +"2022-11-01","All Saints' Day","CL",2022 +"2022-12-08","Immaculate Conception","CL",2022 +"2022-12-25","Christmas","CL",2022 +"2023-01-01","New Year's Day","CL",2023 +"2023-01-02","National Holiday","CL",2023 +"2023-04-07","Good Friday","CL",2023 +"2023-04-08","Holy Saturday","CL",2023 +"2023-05-01","Labour Day","CL",2023 +"2023-05-21","Navy Day","CL",2023 +"2023-06-21","National Day of Indigenous Peoples","CL",2023 +"2023-06-26","Saint Peter and Saint Paul","CL",2023 +"2023-07-16","Our Lady of Mount Carmel","CL",2023 +"2023-08-15","Assumption of Mary","CL",2023 +"2023-09-18","Independence Day","CL",2023 +"2023-09-19","Army Day","CL",2023 +"2023-10-09","Meeting of Two Worlds' Day","CL",2023 +"2023-10-27","Reformation Day","CL",2023 +"2023-11-01","All Saints' Day","CL",2023 +"2023-12-08","Immaculate Conception","CL",2023 +"2023-12-25","Christmas","CL",2023 +"2024-01-01","New Year's Day","CL",2024 +"2024-03-29","Good Friday","CL",2024 +"2024-03-30","Holy Saturday","CL",2024 +"2024-05-01","Labour Day","CL",2024 +"2024-05-21","Navy Day","CL",2024 +"2024-06-20","National Day of Indigenous Peoples","CL",2024 +"2024-06-29","Saint Peter and Saint Paul","CL",2024 +"2024-07-16","Our Lady of Mount Carmel","CL",2024 +"2024-08-15","Assumption of Mary","CL",2024 +"2024-09-18","Independence Day","CL",2024 +"2024-09-19","Army Day","CL",2024 +"2024-09-20","National Holiday","CL",2024 +"2024-10-12","Meeting of Two Worlds' Day","CL",2024 +"2024-10-31","Reformation Day","CL",2024 +"2024-11-01","All Saints' Day","CL",2024 +"2024-12-08","Immaculate Conception","CL",2024 +"2024-12-25","Christmas","CL",2024 +"2025-01-01","New Year's Day","CL",2025 +"2025-04-18","Good Friday","CL",2025 +"2025-04-19","Holy Saturday","CL",2025 +"2025-05-01","Labour Day","CL",2025 +"2025-05-21","Navy Day","CL",2025 +"2025-06-20","National Day of Indigenous Peoples","CL",2025 +"2025-06-29","Saint Peter and Saint Paul","CL",2025 +"2025-07-16","Our Lady of Mount Carmel","CL",2025 +"2025-08-15","Assumption of Mary","CL",2025 +"2025-09-18","Independence Day","CL",2025 +"2025-09-19","Army Day","CL",2025 +"2025-10-12","Meeting of Two Worlds' Day","CL",2025 +"2025-10-31","Reformation Day","CL",2025 +"2025-11-01","All Saints' Day","CL",2025 +"2025-12-08","Immaculate Conception","CL",2025 +"2025-12-25","Christmas","CL",2025 +"2026-01-01","New Year's Day","CL",2026 +"2026-04-03","Good Friday","CL",2026 +"2026-04-04","Holy Saturday","CL",2026 +"2026-05-01","Labour Day","CL",2026 +"2026-05-21","Navy Day","CL",2026 +"2026-06-21","National Day of Indigenous Peoples","CL",2026 +"2026-06-29","Saint Peter and Saint Paul","CL",2026 +"2026-07-16","Our Lady of Mount Carmel","CL",2026 +"2026-08-15","Assumption of Mary","CL",2026 +"2026-09-18","Independence Day","CL",2026 +"2026-09-19","Army Day","CL",2026 +"2026-10-12","Meeting of Two Worlds' Day","CL",2026 +"2026-10-31","Reformation Day","CL",2026 +"2026-11-01","All Saints' Day","CL",2026 +"2026-12-08","Immaculate Conception","CL",2026 +"2026-12-25","Christmas","CL",2026 +"2027-01-01","New Year's Day","CL",2027 +"2027-03-26","Good Friday","CL",2027 +"2027-03-27","Holy Saturday","CL",2027 +"2027-05-01","Labour Day","CL",2027 +"2027-05-21","Navy Day","CL",2027 +"2027-06-21","National Day of Indigenous Peoples","CL",2027 +"2027-06-28","Saint Peter and Saint Paul","CL",2027 +"2027-07-16","Our Lady of Mount Carmel","CL",2027 +"2027-08-15","Assumption of Mary","CL",2027 +"2027-09-17","National Holiday","CL",2027 +"2027-09-18","Independence Day","CL",2027 +"2027-09-19","Army Day","CL",2027 +"2027-10-11","Meeting of Two Worlds' Day","CL",2027 +"2027-10-31","Reformation Day","CL",2027 +"2027-11-01","All Saints' Day","CL",2027 +"2027-12-08","Immaculate Conception","CL",2027 +"2027-12-25","Christmas","CL",2027 +"2028-01-01","New Year's Day","CL",2028 +"2028-04-14","Good Friday","CL",2028 +"2028-04-15","Holy Saturday","CL",2028 +"2028-05-01","Labour Day","CL",2028 +"2028-05-21","Navy Day","CL",2028 +"2028-06-20","National Day of Indigenous Peoples","CL",2028 +"2028-06-26","Saint Peter and Saint Paul","CL",2028 +"2028-07-16","Our Lady of Mount Carmel","CL",2028 +"2028-08-15","Assumption of Mary","CL",2028 +"2028-09-18","Independence Day","CL",2028 +"2028-09-19","Army Day","CL",2028 +"2028-10-09","Meeting of Two Worlds' Day","CL",2028 +"2028-10-27","Reformation Day","CL",2028 +"2028-11-01","All Saints' Day","CL",2028 +"2028-12-08","Immaculate Conception","CL",2028 +"2028-12-25","Christmas","CL",2028 +"2029-01-01","New Year's Day","CL",2029 +"2029-03-30","Good Friday","CL",2029 +"2029-03-31","Holy Saturday","CL",2029 +"2029-05-01","Labour Day","CL",2029 +"2029-05-21","Navy Day","CL",2029 +"2029-06-20","National Day of Indigenous Peoples","CL",2029 +"2029-07-02","Saint Peter and Saint Paul","CL",2029 +"2029-07-16","Our Lady of Mount Carmel","CL",2029 +"2029-08-15","Assumption of Mary","CL",2029 +"2029-09-17","National Holiday","CL",2029 +"2029-09-18","Independence Day","CL",2029 +"2029-09-19","Army Day","CL",2029 +"2029-10-15","Meeting of Two Worlds' Day","CL",2029 +"2029-11-01","All Saints' Day","CL",2029 +"2029-11-02","Reformation Day","CL",2029 +"2029-12-08","Immaculate Conception","CL",2029 +"2029-12-25","Christmas","CL",2029 +"2030-01-01","New Year's Day","CL",2030 +"2030-04-19","Good Friday","CL",2030 +"2030-04-20","Holy Saturday","CL",2030 +"2030-05-01","Labour Day","CL",2030 +"2030-05-21","Navy Day","CL",2030 +"2030-06-21","National Day of Indigenous Peoples","CL",2030 +"2030-06-29","Saint Peter and Saint Paul","CL",2030 +"2030-07-16","Our Lady of Mount Carmel","CL",2030 +"2030-08-15","Assumption of Mary","CL",2030 +"2030-09-18","Independence Day","CL",2030 +"2030-09-19","Army Day","CL",2030 +"2030-09-20","National Holiday","CL",2030 +"2030-10-12","Meeting of Two Worlds' Day","CL",2030 +"2030-10-31","Reformation Day","CL",2030 +"2030-11-01","All Saints' Day","CL",2030 +"2030-12-08","Immaculate Conception","CL",2030 +"2030-12-25","Christmas","CL",2030 +"2031-01-01","New Year's Day","CL",2031 +"2031-04-11","Good Friday","CL",2031 +"2031-04-12","Holy Saturday","CL",2031 +"2031-05-01","Labour Day","CL",2031 +"2031-05-21","Navy Day","CL",2031 +"2031-06-21","National Day of Indigenous Peoples","CL",2031 +"2031-06-29","Saint Peter and Saint Paul","CL",2031 +"2031-07-16","Our Lady of Mount Carmel","CL",2031 +"2031-08-15","Assumption of Mary","CL",2031 +"2031-09-18","Independence Day","CL",2031 +"2031-09-19","Army Day","CL",2031 +"2031-10-12","Meeting of Two Worlds' Day","CL",2031 +"2031-10-31","Reformation Day","CL",2031 +"2031-11-01","All Saints' Day","CL",2031 +"2031-12-08","Immaculate Conception","CL",2031 +"2031-12-25","Christmas","CL",2031 +"2032-01-01","New Year's Day","CL",2032 +"2032-03-26","Good Friday","CL",2032 +"2032-03-27","Holy Saturday","CL",2032 +"2032-05-01","Labour Day","CL",2032 +"2032-05-21","Navy Day","CL",2032 +"2032-06-20","National Day of Indigenous Peoples","CL",2032 +"2032-06-28","Saint Peter and Saint Paul","CL",2032 +"2032-07-16","Our Lady of Mount Carmel","CL",2032 +"2032-08-15","Assumption of Mary","CL",2032 +"2032-09-17","National Holiday","CL",2032 +"2032-09-18","Independence Day","CL",2032 +"2032-09-19","Army Day","CL",2032 +"2032-10-11","Meeting of Two Worlds' Day","CL",2032 +"2032-10-31","Reformation Day","CL",2032 +"2032-11-01","All Saints' Day","CL",2032 +"2032-12-08","Immaculate Conception","CL",2032 +"2032-12-25","Christmas","CL",2032 +"2033-01-01","New Year's Day","CL",2033 +"2033-04-15","Good Friday","CL",2033 +"2033-04-16","Holy Saturday","CL",2033 +"2033-05-01","Labour Day","CL",2033 +"2033-05-21","Navy Day","CL",2033 +"2033-06-20","National Day of Indigenous Peoples","CL",2033 +"2033-06-27","Saint Peter and Saint Paul","CL",2033 +"2033-07-16","Our Lady of Mount Carmel","CL",2033 +"2033-08-15","Assumption of Mary","CL",2033 +"2033-09-18","Independence Day","CL",2033 +"2033-09-19","Army Day","CL",2033 +"2033-10-10","Meeting of Two Worlds' Day","CL",2033 +"2033-10-31","Reformation Day","CL",2033 +"2033-11-01","All Saints' Day","CL",2033 +"2033-12-08","Immaculate Conception","CL",2033 +"2033-12-25","Christmas","CL",2033 +"2034-01-01","New Year's Day","CL",2034 +"2034-01-02","National Holiday","CL",2034 +"2034-04-07","Good Friday","CL",2034 +"2034-04-08","Holy Saturday","CL",2034 +"2034-05-01","Labour Day","CL",2034 +"2034-05-21","Navy Day","CL",2034 +"2034-06-21","National Day of Indigenous Peoples","CL",2034 +"2034-06-26","Saint Peter and Saint Paul","CL",2034 +"2034-07-16","Our Lady of Mount Carmel","CL",2034 +"2034-08-15","Assumption of Mary","CL",2034 +"2034-09-18","Independence Day","CL",2034 +"2034-09-19","Army Day","CL",2034 +"2034-10-09","Meeting of Two Worlds' Day","CL",2034 +"2034-10-27","Reformation Day","CL",2034 +"2034-11-01","All Saints' Day","CL",2034 +"2034-12-08","Immaculate Conception","CL",2034 +"2034-12-25","Christmas","CL",2034 +"2035-01-01","New Year's Day","CL",2035 +"2035-03-23","Good Friday","CL",2035 +"2035-03-24","Holy Saturday","CL",2035 +"2035-05-01","Labour Day","CL",2035 +"2035-05-21","Navy Day","CL",2035 +"2035-06-21","National Day of Indigenous Peoples","CL",2035 +"2035-07-02","Saint Peter and Saint Paul","CL",2035 +"2035-07-16","Our Lady of Mount Carmel","CL",2035 +"2035-08-15","Assumption of Mary","CL",2035 +"2035-09-17","National Holiday","CL",2035 +"2035-09-18","Independence Day","CL",2035 +"2035-09-19","Army Day","CL",2035 +"2035-10-15","Meeting of Two Worlds' Day","CL",2035 +"2035-11-01","All Saints' Day","CL",2035 +"2035-11-02","Reformation Day","CL",2035 +"2035-12-08","Immaculate Conception","CL",2035 +"2035-12-25","Christmas","CL",2035 +"2036-01-01","New Year's Day","CL",2036 +"2036-04-11","Good Friday","CL",2036 +"2036-04-12","Holy Saturday","CL",2036 +"2036-05-01","Labour Day","CL",2036 +"2036-05-21","Navy Day","CL",2036 +"2036-06-20","National Day of Indigenous Peoples","CL",2036 +"2036-06-29","Saint Peter and Saint Paul","CL",2036 +"2036-07-16","Our Lady of Mount Carmel","CL",2036 +"2036-08-15","Assumption of Mary","CL",2036 +"2036-09-18","Independence Day","CL",2036 +"2036-09-19","Army Day","CL",2036 +"2036-10-12","Meeting of Two Worlds' Day","CL",2036 +"2036-10-31","Reformation Day","CL",2036 +"2036-11-01","All Saints' Day","CL",2036 +"2036-12-08","Immaculate Conception","CL",2036 +"2036-12-25","Christmas","CL",2036 +"2037-01-01","New Year's Day","CL",2037 +"2037-04-03","Good Friday","CL",2037 +"2037-04-04","Holy Saturday","CL",2037 +"2037-05-01","Labour Day","CL",2037 +"2037-05-21","Navy Day","CL",2037 +"2037-06-20","National Day of Indigenous Peoples","CL",2037 +"2037-06-29","Saint Peter and Saint Paul","CL",2037 +"2037-07-16","Our Lady of Mount Carmel","CL",2037 +"2037-08-15","Assumption of Mary","CL",2037 +"2037-09-18","Independence Day","CL",2037 +"2037-09-19","Army Day","CL",2037 +"2037-10-12","Meeting of Two Worlds' Day","CL",2037 +"2037-10-31","Reformation Day","CL",2037 +"2037-11-01","All Saints' Day","CL",2037 +"2037-12-08","Immaculate Conception","CL",2037 +"2037-12-25","Christmas","CL",2037 +"2038-01-01","New Year's Day","CL",2038 +"2038-04-23","Good Friday","CL",2038 +"2038-04-24","Holy Saturday","CL",2038 +"2038-05-01","Labour Day","CL",2038 +"2038-05-21","Navy Day","CL",2038 +"2038-06-21","National Day of Indigenous Peoples","CL",2038 +"2038-06-28","Saint Peter and Saint Paul","CL",2038 +"2038-07-16","Our Lady of Mount Carmel","CL",2038 +"2038-08-15","Assumption of Mary","CL",2038 +"2038-09-17","National Holiday","CL",2038 +"2038-09-18","Independence Day","CL",2038 +"2038-09-19","Army Day","CL",2038 +"2038-10-11","Meeting of Two Worlds' Day","CL",2038 +"2038-10-31","Reformation Day","CL",2038 +"2038-11-01","All Saints' Day","CL",2038 +"2038-12-08","Immaculate Conception","CL",2038 +"2038-12-25","Christmas","CL",2038 +"2039-01-01","New Year's Day","CL",2039 +"2039-04-08","Good Friday","CL",2039 +"2039-04-09","Holy Saturday","CL",2039 +"2039-05-01","Labour Day","CL",2039 +"2039-05-21","Navy Day","CL",2039 +"2039-06-21","National Day of Indigenous Peoples","CL",2039 +"2039-06-27","Saint Peter and Saint Paul","CL",2039 +"2039-07-16","Our Lady of Mount Carmel","CL",2039 +"2039-08-15","Assumption of Mary","CL",2039 +"2039-09-18","Independence Day","CL",2039 +"2039-09-19","Army Day","CL",2039 +"2039-10-10","Meeting of Two Worlds' Day","CL",2039 +"2039-10-31","Reformation Day","CL",2039 +"2039-11-01","All Saints' Day","CL",2039 +"2039-12-08","Immaculate Conception","CL",2039 +"2039-12-25","Christmas","CL",2039 +"2040-01-01","New Year's Day","CL",2040 +"2040-01-02","National Holiday","CL",2040 +"2040-03-30","Good Friday","CL",2040 +"2040-03-31","Holy Saturday","CL",2040 +"2040-05-01","Labour Day","CL",2040 +"2040-05-21","Navy Day","CL",2040 +"2040-06-20","National Day of Indigenous Peoples","CL",2040 +"2040-07-02","Saint Peter and Saint Paul","CL",2040 +"2040-07-16","Our Lady of Mount Carmel","CL",2040 +"2040-08-15","Assumption of Mary","CL",2040 +"2040-09-17","National Holiday","CL",2040 +"2040-09-18","Independence Day","CL",2040 +"2040-09-19","Army Day","CL",2040 +"2040-10-15","Meeting of Two Worlds' Day","CL",2040 +"2040-11-01","All Saints' Day","CL",2040 +"2040-11-02","Reformation Day","CL",2040 +"2040-12-08","Immaculate Conception","CL",2040 +"2040-12-25","Christmas","CL",2040 +"2041-01-01","New Year's Day","CL",2041 +"2041-04-19","Good Friday","CL",2041 +"2041-04-20","Holy Saturday","CL",2041 +"2041-05-01","Labour Day","CL",2041 +"2041-05-21","Navy Day","CL",2041 +"2041-06-20","National Day of Indigenous Peoples","CL",2041 +"2041-06-29","Saint Peter and Saint Paul","CL",2041 +"2041-07-16","Our Lady of Mount Carmel","CL",2041 +"2041-08-15","Assumption of Mary","CL",2041 +"2041-09-18","Independence Day","CL",2041 +"2041-09-19","Army Day","CL",2041 +"2041-09-20","National Holiday","CL",2041 +"2041-10-12","Meeting of Two Worlds' Day","CL",2041 +"2041-10-31","Reformation Day","CL",2041 +"2041-11-01","All Saints' Day","CL",2041 +"2041-12-08","Immaculate Conception","CL",2041 +"2041-12-25","Christmas","CL",2041 +"2042-01-01","New Year's Day","CL",2042 +"2042-04-04","Good Friday","CL",2042 +"2042-04-05","Holy Saturday","CL",2042 +"2042-05-01","Labour Day","CL",2042 +"2042-05-21","Navy Day","CL",2042 +"2042-06-21","National Day of Indigenous Peoples","CL",2042 +"2042-06-29","Saint Peter and Saint Paul","CL",2042 +"2042-07-16","Our Lady of Mount Carmel","CL",2042 +"2042-08-15","Assumption of Mary","CL",2042 +"2042-09-18","Independence Day","CL",2042 +"2042-09-19","Army Day","CL",2042 +"2042-10-12","Meeting of Two Worlds' Day","CL",2042 +"2042-10-31","Reformation Day","CL",2042 +"2042-11-01","All Saints' Day","CL",2042 +"2042-12-08","Immaculate Conception","CL",2042 +"2042-12-25","Christmas","CL",2042 +"2043-01-01","New Year's Day","CL",2043 +"2043-03-27","Good Friday","CL",2043 +"2043-03-28","Holy Saturday","CL",2043 +"2043-05-01","Labour Day","CL",2043 +"2043-05-21","Navy Day","CL",2043 +"2043-06-21","National Day of Indigenous Peoples","CL",2043 +"2043-06-29","Saint Peter and Saint Paul","CL",2043 +"2043-07-16","Our Lady of Mount Carmel","CL",2043 +"2043-08-15","Assumption of Mary","CL",2043 +"2043-09-18","Independence Day","CL",2043 +"2043-09-19","Army Day","CL",2043 +"2043-10-12","Meeting of Two Worlds' Day","CL",2043 +"2043-10-31","Reformation Day","CL",2043 +"2043-11-01","All Saints' Day","CL",2043 +"2043-12-08","Immaculate Conception","CL",2043 +"2043-12-25","Christmas","CL",2043 +"2044-01-01","New Year's Day","CL",2044 +"2044-04-15","Good Friday","CL",2044 +"2044-04-16","Holy Saturday","CL",2044 +"2044-05-01","Labour Day","CL",2044 +"2044-05-21","Navy Day","CL",2044 +"2044-06-20","National Day of Indigenous Peoples","CL",2044 +"2044-06-27","Saint Peter and Saint Paul","CL",2044 +"2044-07-16","Our Lady of Mount Carmel","CL",2044 +"2044-08-15","Assumption of Mary","CL",2044 +"2044-09-18","Independence Day","CL",2044 +"2044-09-19","Army Day","CL",2044 +"2044-10-10","Meeting of Two Worlds' Day","CL",2044 +"2044-10-31","Reformation Day","CL",2044 +"2044-11-01","All Saints' Day","CL",2044 +"2044-12-08","Immaculate Conception","CL",2044 +"2044-12-25","Christmas","CL",2044 +"1995-01-01","New Year's Day","CN",1995 +"1995-01-31","Chinese New Year (Spring Festival)","CN",1995 +"1995-02-01","Chinese New Year (Spring Festival)","CN",1995 +"1995-02-02","Chinese New Year (Spring Festival)","CN",1995 +"1995-05-01","Labour Day","CN",1995 +"1995-10-01","National Day","CN",1995 +"1995-10-02","National Day","CN",1995 +"1996-01-01","New Year's Day","CN",1996 +"1996-02-19","Chinese New Year (Spring Festival)","CN",1996 +"1996-02-20","Chinese New Year (Spring Festival)","CN",1996 +"1996-02-21","Chinese New Year (Spring Festival)","CN",1996 +"1996-05-01","Labour Day","CN",1996 +"1996-10-01","National Day","CN",1996 +"1996-10-02","National Day","CN",1996 +"1997-01-01","New Year's Day","CN",1997 +"1997-02-07","Chinese New Year (Spring Festival)","CN",1997 +"1997-02-08","Chinese New Year (Spring Festival)","CN",1997 +"1997-02-09","Chinese New Year (Spring Festival)","CN",1997 +"1997-05-01","Labour Day","CN",1997 +"1997-10-01","National Day","CN",1997 +"1997-10-02","National Day","CN",1997 +"1998-01-01","New Year's Day","CN",1998 +"1998-01-28","Chinese New Year (Spring Festival)","CN",1998 +"1998-01-29","Chinese New Year (Spring Festival)","CN",1998 +"1998-01-30","Chinese New Year (Spring Festival)","CN",1998 +"1998-05-01","Labour Day","CN",1998 +"1998-10-01","National Day","CN",1998 +"1998-10-02","National Day","CN",1998 +"1999-01-01","New Year's Day","CN",1999 +"1999-02-16","Chinese New Year (Spring Festival)","CN",1999 +"1999-02-17","Chinese New Year (Spring Festival)","CN",1999 +"1999-02-18","Chinese New Year (Spring Festival)","CN",1999 +"1999-05-01","Labour Day","CN",1999 +"1999-10-01","National Day","CN",1999 +"1999-10-02","National Day","CN",1999 +"2000-01-01","New Year's Day","CN",2000 +"2000-02-05","Chinese New Year (Spring Festival)","CN",2000 +"2000-02-06","Chinese New Year (Spring Festival)","CN",2000 +"2000-02-07","Chinese New Year (Spring Festival)","CN",2000 +"2000-05-01","Labour Day","CN",2000 +"2000-05-02","Labour Day","CN",2000 +"2000-05-03","Labour Day","CN",2000 +"2000-10-01","National Day","CN",2000 +"2000-10-02","National Day","CN",2000 +"2000-10-03","National Day","CN",2000 +"2001-01-01","New Year's Day","CN",2001 +"2001-01-24","Chinese New Year (Spring Festival)","CN",2001 +"2001-01-25","Chinese New Year (Spring Festival)","CN",2001 +"2001-01-26","Chinese New Year (Spring Festival)","CN",2001 +"2001-05-01","Labour Day","CN",2001 +"2001-05-02","Labour Day","CN",2001 +"2001-05-03","Labour Day","CN",2001 +"2001-10-01","National Day","CN",2001 +"2001-10-02","National Day","CN",2001 +"2001-10-03","National Day","CN",2001 +"2002-01-01","New Year's Day","CN",2002 +"2002-02-12","Chinese New Year (Spring Festival)","CN",2002 +"2002-02-13","Chinese New Year (Spring Festival)","CN",2002 +"2002-02-14","Chinese New Year (Spring Festival)","CN",2002 +"2002-05-01","Labour Day","CN",2002 +"2002-05-02","Labour Day","CN",2002 +"2002-05-03","Labour Day","CN",2002 +"2002-10-01","National Day","CN",2002 +"2002-10-02","National Day","CN",2002 +"2002-10-03","National Day","CN",2002 +"2003-01-01","New Year's Day","CN",2003 +"2003-02-01","Chinese New Year (Spring Festival)","CN",2003 +"2003-02-02","Chinese New Year (Spring Festival)","CN",2003 +"2003-02-03","Chinese New Year (Spring Festival)","CN",2003 +"2003-05-01","Labour Day","CN",2003 +"2003-05-02","Labour Day","CN",2003 +"2003-05-03","Labour Day","CN",2003 +"2003-10-01","National Day","CN",2003 +"2003-10-02","National Day","CN",2003 +"2003-10-03","National Day","CN",2003 +"2004-01-01","New Year's Day","CN",2004 +"2004-01-22","Chinese New Year (Spring Festival)","CN",2004 +"2004-01-23","Chinese New Year (Spring Festival)","CN",2004 +"2004-01-24","Chinese New Year (Spring Festival)","CN",2004 +"2004-05-01","Labour Day","CN",2004 +"2004-05-02","Labour Day","CN",2004 +"2004-05-03","Labour Day","CN",2004 +"2004-10-01","National Day","CN",2004 +"2004-10-02","National Day","CN",2004 +"2004-10-03","National Day","CN",2004 +"2005-01-01","New Year's Day","CN",2005 +"2005-02-09","Chinese New Year (Spring Festival)","CN",2005 +"2005-02-10","Chinese New Year (Spring Festival)","CN",2005 +"2005-02-11","Chinese New Year (Spring Festival)","CN",2005 +"2005-05-01","Labour Day","CN",2005 +"2005-05-02","Labour Day","CN",2005 +"2005-05-03","Labour Day","CN",2005 +"2005-10-01","National Day","CN",2005 +"2005-10-02","National Day","CN",2005 +"2005-10-03","National Day","CN",2005 +"2006-01-01","New Year's Day","CN",2006 +"2006-01-29","Chinese New Year (Spring Festival)","CN",2006 +"2006-01-30","Chinese New Year (Spring Festival)","CN",2006 +"2006-01-31","Chinese New Year (Spring Festival)","CN",2006 +"2006-05-01","Labour Day","CN",2006 +"2006-05-02","Labour Day","CN",2006 +"2006-05-03","Labour Day","CN",2006 +"2006-10-01","National Day","CN",2006 +"2006-10-02","National Day","CN",2006 +"2006-10-03","National Day","CN",2006 +"2007-01-01","New Year's Day","CN",2007 +"2007-02-18","Chinese New Year (Spring Festival)","CN",2007 +"2007-02-19","Chinese New Year (Spring Festival)","CN",2007 +"2007-02-20","Chinese New Year (Spring Festival)","CN",2007 +"2007-05-01","Labour Day","CN",2007 +"2007-05-02","Labour Day","CN",2007 +"2007-05-03","Labour Day","CN",2007 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(Spring Festival)","CN",2017 +"2017-04-05","Tomb-Sweeping Day","CN",2017 +"2017-05-01","Labour Day","CN",2017 +"2017-05-30","Dragon Boat Festival","CN",2017 +"2017-10-01","National Day","CN",2017 +"2017-10-02","National Day","CN",2017 +"2017-10-03","National Day","CN",2017 +"2017-10-04","Mid-Autumn Festival","CN",2017 +"2018-01-01","New Year's Day","CN",2018 +"2018-02-16","Chinese New Year (Spring Festival)","CN",2018 +"2018-02-17","Chinese New Year (Spring Festival)","CN",2018 +"2018-02-18","Chinese New Year (Spring Festival)","CN",2018 +"2018-04-05","Tomb-Sweeping Day","CN",2018 +"2018-05-01","Labour Day","CN",2018 +"2018-06-18","Dragon Boat Festival","CN",2018 +"2018-09-24","Mid-Autumn Festival","CN",2018 +"2018-10-01","National Day","CN",2018 +"2018-10-02","National Day","CN",2018 +"2018-10-03","National Day","CN",2018 +"2019-01-01","New Year's Day","CN",2019 +"2019-02-05","Chinese New Year (Spring Festival)","CN",2019 +"2019-02-06","Chinese New Year (Spring Festival)","CN",2019 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+"2040-05-01","Labour Day","CN",2040 +"2040-06-14","Dragon Boat Festival","CN",2040 +"2040-09-20","Mid-Autumn Festival","CN",2040 +"2040-10-01","National Day","CN",2040 +"2040-10-02","National Day","CN",2040 +"2040-10-03","National Day","CN",2040 +"2041-01-01","New Year's Day","CN",2041 +"2041-02-01","Chinese New Year (Spring Festival)","CN",2041 +"2041-02-02","Chinese New Year (Spring Festival)","CN",2041 +"2041-02-03","Chinese New Year (Spring Festival)","CN",2041 +"2041-04-05","Tomb-Sweeping Day","CN",2041 +"2041-05-01","Labour Day","CN",2041 +"2041-06-03","Dragon Boat Festival","CN",2041 +"2041-09-10","Mid-Autumn Festival","CN",2041 +"2041-10-01","National Day","CN",2041 +"2041-10-02","National Day","CN",2041 +"2041-10-03","National Day","CN",2041 +"2042-01-01","New Year's Day","CN",2042 +"2042-01-22","Chinese New Year (Spring Festival)","CN",2042 +"2042-01-23","Chinese New Year (Spring Festival)","CN",2042 +"2042-01-24","Chinese New Year (Spring Festival)","CN",2042 +"2042-04-05","Tomb-Sweeping Day","CN",2042 +"2042-05-01","Labour Day","CN",2042 +"2042-06-22","Dragon Boat Festival","CN",2042 +"2042-09-28","Mid-Autumn Festival","CN",2042 +"2042-10-01","National Day","CN",2042 +"2042-10-02","National Day","CN",2042 +"2042-10-03","National Day","CN",2042 +"2043-01-01","New Year's Day","CN",2043 +"2043-02-10","Chinese New Year (Spring Festival)","CN",2043 +"2043-02-11","Chinese New Year (Spring Festival)","CN",2043 +"2043-02-12","Chinese New Year (Spring Festival)","CN",2043 +"2043-04-05","Tomb-Sweeping Day","CN",2043 +"2043-05-01","Labour Day","CN",2043 +"2043-06-11","Dragon Boat Festival","CN",2043 +"2043-09-17","Mid-Autumn Festival","CN",2043 +"2043-10-01","National Day","CN",2043 +"2043-10-02","National Day","CN",2043 +"2043-10-03","National Day","CN",2043 +"2044-01-01","New Year's Day","CN",2044 +"2044-01-30","Chinese New Year (Spring Festival)","CN",2044 +"2044-01-31","Chinese New Year (Spring Festival)","CN",2044 +"2044-02-01","Chinese New Year (Spring Festival)","CN",2044 +"2044-04-05","Tomb-Sweeping Day","CN",2044 +"2044-05-01","Labour Day","CN",2044 +"2044-05-31","Dragon Boat Festival","CN",2044 +"2044-10-01","National Day","CN",2044 +"2044-10-02","National Day","CN",2044 +"2044-10-03","National Day","CN",2044 +"2044-10-05","Mid-Autumn Festival","CN",2044 +"1995-01-01","New Year's Day","CO",1995 +"1995-01-09","Epiphany (Observed)","CO",1995 +"1995-03-20","Saint Joseph's Day (Observed)","CO",1995 +"1995-04-13","Maundy Thursday","CO",1995 +"1995-04-14","Good Friday","CO",1995 +"1995-05-01","Dia del Trabajo","CO",1995 +"1995-05-29","Ascension of Jesus (Observed)","CO",1995 +"1995-06-19","Corpus Christi (Observed)","CO",1995 +"1995-06-26","Sacred Heart (Observed)","CO",1995 +"1995-07-03","Saint Peter and Saint Paul (Observed)","CO",1995 +"1995-07-20","Independence Day","CO",1995 +"1995-08-07","Battle of Boyaca","CO",1995 +"1995-08-21","Assumption of Mary (Observed)","CO",1995 +"1995-10-16","Columbus Day (Observed)","CO",1995 +"1995-11-06","All Saints' Day (Observed)","CO",1995 +"1995-11-13","Independence of Cartagena (Observed)","CO",1995 +"1995-12-08","Immaculate Conception","CO",1995 +"1995-12-25","Christmas","CO",1995 +"1996-01-01","New Year's Day","CO",1996 +"1996-01-08","Epiphany (Observed)","CO",1996 +"1996-03-25","Saint Joseph's Day (Observed)","CO",1996 +"1996-04-04","Maundy Thursday","CO",1996 +"1996-04-05","Good Friday","CO",1996 +"1996-05-01","Dia del Trabajo","CO",1996 +"1996-05-20","Ascension of Jesus (Observed)","CO",1996 +"1996-06-10","Corpus Christi (Observed)","CO",1996 +"1996-06-17","Sacred Heart (Observed)","CO",1996 +"1996-07-01","Saint Peter and Saint Paul (Observed)","CO",1996 +"1996-07-20","Independence Day","CO",1996 +"1996-08-07","Battle of Boyaca","CO",1996 +"1996-08-19","Assumption of Mary (Observed)","CO",1996 +"1996-10-14","Columbus Day (Observed)","CO",1996 +"1996-11-04","All Saints' Day (Observed)","CO",1996 +"1996-11-11","Independence of Cartagena","CO",1996 +"1996-12-08","Immaculate Conception","CO",1996 +"1996-12-25","Christmas","CO",1996 +"1997-01-01","New Year's Day","CO",1997 +"1997-01-06","Epiphany","CO",1997 +"1997-03-24","Saint Joseph's Day (Observed)","CO",1997 +"1997-03-27","Maundy Thursday","CO",1997 +"1997-03-28","Good Friday","CO",1997 +"1997-05-01","Dia del Trabajo","CO",1997 +"1997-05-12","Ascension of Jesus (Observed)","CO",1997 +"1997-06-02","Corpus Christi (Observed)","CO",1997 +"1997-06-09","Sacred Heart (Observed)","CO",1997 +"1997-06-30","Saint Peter and Saint Paul (Observed)","CO",1997 +"1997-07-20","Independence Day","CO",1997 +"1997-08-07","Battle of Boyaca","CO",1997 +"1997-08-18","Assumption of Mary (Observed)","CO",1997 +"1997-10-13","Columbus Day (Observed)","CO",1997 +"1997-11-03","All Saints' Day (Observed)","CO",1997 +"1997-11-17","Independence of Cartagena (Observed)","CO",1997 +"1997-12-08","Immaculate Conception","CO",1997 +"1997-12-25","Christmas","CO",1997 +"1998-01-01","New Year's Day","CO",1998 +"1998-01-12","Epiphany (Observed)","CO",1998 +"1998-03-23","Saint Joseph's Day (Observed)","CO",1998 +"1998-04-09","Maundy Thursday","CO",1998 +"1998-04-10","Good Friday","CO",1998 +"1998-05-01","Dia del Trabajo","CO",1998 +"1998-05-25","Ascension of Jesus (Observed)","CO",1998 +"1998-06-15","Corpus Christi (Observed)","CO",1998 +"1998-06-22","Sacred Heart (Observed)","CO",1998 +"1998-06-29","Saint Peter and Saint Paul","CO",1998 +"1998-07-20","Independence Day","CO",1998 +"1998-08-07","Battle of Boyaca","CO",1998 +"1998-08-17","Assumption of Mary (Observed)","CO",1998 +"1998-10-12","Columbus Day","CO",1998 +"1998-11-02","All Saints' Day (Observed)","CO",1998 +"1998-11-16","Independence of Cartagena (Observed)","CO",1998 +"1998-12-08","Immaculate Conception","CO",1998 +"1998-12-25","Christmas","CO",1998 +"1999-01-01","New Year's Day","CO",1999 +"1999-01-11","Epiphany (Observed)","CO",1999 +"1999-03-22","Saint Joseph's Day (Observed)","CO",1999 +"1999-04-01","Maundy Thursday","CO",1999 +"1999-04-02","Good Friday","CO",1999 +"1999-05-01","Dia del Trabajo","CO",1999 +"1999-05-17","Ascension of Jesus (Observed)","CO",1999 +"1999-06-07","Corpus Christi (Observed)","CO",1999 +"1999-06-14","Sacred Heart (Observed)","CO",1999 +"1999-07-05","Saint Peter and Saint Paul (Observed)","CO",1999 +"1999-07-20","Independence Day","CO",1999 +"1999-08-07","Battle of Boyaca","CO",1999 +"1999-08-16","Assumption of Mary (Observed)","CO",1999 +"1999-10-18","Columbus Day (Observed)","CO",1999 +"1999-11-01","All Saints' Day","CO",1999 +"1999-11-15","Independence of Cartagena (Observed)","CO",1999 +"1999-12-08","Immaculate Conception","CO",1999 +"1999-12-25","Christmas","CO",1999 +"2000-01-01","New Year's Day","CO",2000 +"2000-01-10","Epiphany (Observed)","CO",2000 +"2000-03-20","Saint Joseph's Day (Observed)","CO",2000 +"2000-04-20","Maundy Thursday","CO",2000 +"2000-04-21","Good Friday","CO",2000 +"2000-05-01","Dia del Trabajo","CO",2000 +"2000-06-05","Ascension of Jesus (Observed)","CO",2000 +"2000-06-26","Corpus Christi (Observed)","CO",2000 +"2000-07-03","Sacred Heart (Observed)","CO",2000 +"2000-07-03","Saint Peter and Saint Paul (Observed)","CO",2000 +"2000-07-20","Independence Day","CO",2000 +"2000-08-07","Battle of Boyaca","CO",2000 +"2000-08-21","Assumption of Mary (Observed)","CO",2000 +"2000-10-16","Columbus Day (Observed)","CO",2000 +"2000-11-06","All Saints' Day (Observed)","CO",2000 +"2000-11-13","Independence of Cartagena (Observed)","CO",2000 +"2000-12-08","Immaculate Conception","CO",2000 +"2000-12-25","Christmas","CO",2000 +"2001-01-01","New Year's Day","CO",2001 +"2001-01-08","Epiphany (Observed)","CO",2001 +"2001-03-19","Saint Joseph's Day","CO",2001 +"2001-04-12","Maundy Thursday","CO",2001 +"2001-04-13","Good Friday","CO",2001 +"2001-05-01","Dia del Trabajo","CO",2001 +"2001-05-28","Ascension of Jesus (Observed)","CO",2001 +"2001-06-18","Corpus Christi (Observed)","CO",2001 +"2001-06-25","Sacred Heart (Observed)","CO",2001 +"2001-07-02","Saint Peter and Saint Paul (Observed)","CO",2001 +"2001-07-20","Independence Day","CO",2001 +"2001-08-07","Battle of Boyaca","CO",2001 +"2001-08-20","Assumption of Mary (Observed)","CO",2001 +"2001-10-15","Columbus Day (Observed)","CO",2001 +"2001-11-05","All Saints' Day (Observed)","CO",2001 +"2001-11-12","Independence of Cartagena (Observed)","CO",2001 +"2001-12-08","Immaculate Conception","CO",2001 +"2001-12-25","Christmas","CO",2001 +"2002-01-01","New Year's Day","CO",2002 +"2002-01-07","Epiphany (Observed)","CO",2002 +"2002-03-25","Saint Joseph's Day (Observed)","CO",2002 +"2002-03-28","Maundy Thursday","CO",2002 +"2002-03-29","Good Friday","CO",2002 +"2002-05-01","Dia del Trabajo","CO",2002 +"2002-05-13","Ascension of Jesus (Observed)","CO",2002 +"2002-06-03","Corpus Christi (Observed)","CO",2002 +"2002-06-10","Sacred Heart (Observed)","CO",2002 +"2002-07-01","Saint Peter and Saint Paul (Observed)","CO",2002 +"2002-07-20","Independence Day","CO",2002 +"2002-08-07","Battle of Boyaca","CO",2002 +"2002-08-19","Assumption of Mary (Observed)","CO",2002 +"2002-10-14","Columbus Day (Observed)","CO",2002 +"2002-11-04","All Saints' Day (Observed)","CO",2002 +"2002-11-11","Independence of Cartagena","CO",2002 +"2002-12-08","Immaculate Conception","CO",2002 +"2002-12-25","Christmas","CO",2002 +"2003-01-01","New Year's Day","CO",2003 +"2003-01-06","Epiphany","CO",2003 +"2003-03-24","Saint Joseph's Day (Observed)","CO",2003 +"2003-04-17","Maundy Thursday","CO",2003 +"2003-04-18","Good Friday","CO",2003 +"2003-05-01","Dia del Trabajo","CO",2003 +"2003-06-02","Ascension of Jesus (Observed)","CO",2003 +"2003-06-23","Corpus Christi (Observed)","CO",2003 +"2003-06-30","Sacred Heart (Observed)","CO",2003 +"2003-06-30","Saint Peter and Saint Paul (Observed)","CO",2003 +"2003-07-20","Independence Day","CO",2003 +"2003-08-07","Battle of Boyaca","CO",2003 +"2003-08-18","Assumption of Mary (Observed)","CO",2003 +"2003-10-13","Columbus Day (Observed)","CO",2003 +"2003-11-03","All Saints' Day (Observed)","CO",2003 +"2003-11-17","Independence of Cartagena (Observed)","CO",2003 +"2003-12-08","Immaculate Conception","CO",2003 +"2003-12-25","Christmas","CO",2003 +"2004-01-01","New Year's Day","CO",2004 +"2004-01-12","Epiphany (Observed)","CO",2004 +"2004-03-22","Saint Joseph's Day (Observed)","CO",2004 +"2004-04-08","Maundy Thursday","CO",2004 +"2004-04-09","Good Friday","CO",2004 +"2004-05-01","Dia del Trabajo","CO",2004 +"2004-05-24","Ascension of Jesus (Observed)","CO",2004 +"2004-06-14","Corpus Christi (Observed)","CO",2004 +"2004-06-21","Sacred Heart (Observed)","CO",2004 +"2004-07-05","Saint Peter and Saint Paul (Observed)","CO",2004 +"2004-07-20","Independence Day","CO",2004 +"2004-08-07","Battle of Boyaca","CO",2004 +"2004-08-16","Assumption of Mary (Observed)","CO",2004 +"2004-10-18","Columbus Day (Observed)","CO",2004 +"2004-11-01","All Saints' Day","CO",2004 +"2004-11-15","Independence of Cartagena (Observed)","CO",2004 +"2004-12-08","Immaculate Conception","CO",2004 +"2004-12-25","Christmas","CO",2004 +"2005-01-01","New Year's Day","CO",2005 +"2005-01-10","Epiphany (Observed)","CO",2005 +"2005-03-21","Saint Joseph's Day (Observed)","CO",2005 +"2005-03-24","Maundy Thursday","CO",2005 +"2005-03-25","Good Friday","CO",2005 +"2005-05-01","Dia del Trabajo","CO",2005 +"2005-05-09","Ascension of Jesus (Observed)","CO",2005 +"2005-05-30","Corpus Christi (Observed)","CO",2005 +"2005-06-06","Sacred Heart (Observed)","CO",2005 +"2005-07-04","Saint Peter and Saint Paul (Observed)","CO",2005 +"2005-07-20","Independence Day","CO",2005 +"2005-08-07","Battle of Boyaca","CO",2005 +"2005-08-15","Assumption of Mary","CO",2005 +"2005-10-17","Columbus Day (Observed)","CO",2005 +"2005-11-07","All Saints' Day (Observed)","CO",2005 +"2005-11-14","Independence of Cartagena (Observed)","CO",2005 +"2005-12-08","Immaculate Conception","CO",2005 +"2005-12-25","Christmas","CO",2005 +"2006-01-01","New Year's Day","CO",2006 +"2006-01-09","Epiphany (Observed)","CO",2006 +"2006-03-20","Saint Joseph's Day (Observed)","CO",2006 +"2006-04-13","Maundy Thursday","CO",2006 +"2006-04-14","Good Friday","CO",2006 +"2006-05-01","Dia del Trabajo","CO",2006 +"2006-05-29","Ascension of Jesus (Observed)","CO",2006 +"2006-06-19","Corpus Christi (Observed)","CO",2006 +"2006-06-26","Sacred Heart (Observed)","CO",2006 +"2006-07-03","Saint Peter and Saint Paul (Observed)","CO",2006 +"2006-07-20","Independence Day","CO",2006 +"2006-08-07","Battle of Boyaca","CO",2006 +"2006-08-21","Assumption of Mary (Observed)","CO",2006 +"2006-10-16","Columbus Day (Observed)","CO",2006 +"2006-11-06","All Saints' Day (Observed)","CO",2006 +"2006-11-13","Independence of Cartagena (Observed)","CO",2006 +"2006-12-08","Immaculate Conception","CO",2006 +"2006-12-25","Christmas","CO",2006 +"2007-01-01","New Year's Day","CO",2007 +"2007-01-08","Epiphany (Observed)","CO",2007 +"2007-03-19","Saint Joseph's Day","CO",2007 +"2007-04-05","Maundy Thursday","CO",2007 +"2007-04-06","Good Friday","CO",2007 +"2007-05-01","Dia del Trabajo","CO",2007 +"2007-05-21","Ascension of Jesus (Observed)","CO",2007 +"2007-06-11","Corpus Christi (Observed)","CO",2007 +"2007-06-18","Sacred Heart (Observed)","CO",2007 +"2007-07-02","Saint Peter and Saint Paul (Observed)","CO",2007 +"2007-07-20","Independence Day","CO",2007 +"2007-08-07","Battle of Boyaca","CO",2007 +"2007-08-20","Assumption of Mary (Observed)","CO",2007 +"2007-10-15","Columbus Day (Observed)","CO",2007 +"2007-11-05","All Saints' Day (Observed)","CO",2007 +"2007-11-12","Independence of Cartagena (Observed)","CO",2007 +"2007-12-08","Immaculate Conception","CO",2007 +"2007-12-25","Christmas","CO",2007 +"2008-01-01","New Year's Day","CO",2008 +"2008-01-07","Epiphany (Observed)","CO",2008 +"2008-03-20","Maundy Thursday","CO",2008 +"2008-03-21","Good Friday","CO",2008 +"2008-03-24","Saint Joseph's Day (Observed)","CO",2008 +"2008-05-01","Dia del Trabajo","CO",2008 +"2008-05-05","Ascension of Jesus (Observed)","CO",2008 +"2008-05-26","Corpus Christi (Observed)","CO",2008 +"2008-06-02","Sacred Heart (Observed)","CO",2008 +"2008-06-30","Saint Peter and Saint Paul (Observed)","CO",2008 +"2008-07-20","Independence Day","CO",2008 +"2008-08-07","Battle of Boyaca","CO",2008 +"2008-08-18","Assumption of Mary (Observed)","CO",2008 +"2008-10-13","Columbus Day (Observed)","CO",2008 +"2008-11-03","All Saints' Day (Observed)","CO",2008 +"2008-11-17","Independence of Cartagena (Observed)","CO",2008 +"2008-12-08","Immaculate Conception","CO",2008 +"2008-12-25","Christmas","CO",2008 +"2009-01-01","New Year's Day","CO",2009 +"2009-01-12","Epiphany (Observed)","CO",2009 +"2009-03-23","Saint Joseph's Day (Observed)","CO",2009 +"2009-04-09","Maundy Thursday","CO",2009 +"2009-04-10","Good Friday","CO",2009 +"2009-05-01","Dia del Trabajo","CO",2009 +"2009-05-25","Ascension of Jesus (Observed)","CO",2009 +"2009-06-15","Corpus Christi (Observed)","CO",2009 +"2009-06-22","Sacred Heart (Observed)","CO",2009 +"2009-06-29","Saint Peter and Saint Paul","CO",2009 +"2009-07-20","Independence Day","CO",2009 +"2009-08-07","Battle of Boyaca","CO",2009 +"2009-08-17","Assumption of Mary (Observed)","CO",2009 +"2009-10-12","Columbus Day","CO",2009 +"2009-11-02","All Saints' Day (Observed)","CO",2009 +"2009-11-16","Independence of Cartagena (Observed)","CO",2009 +"2009-12-08","Immaculate Conception","CO",2009 +"2009-12-25","Christmas","CO",2009 +"2010-01-01","New Year's Day","CO",2010 +"2010-01-11","Epiphany (Observed)","CO",2010 +"2010-03-22","Saint Joseph's Day (Observed)","CO",2010 +"2010-04-01","Maundy Thursday","CO",2010 +"2010-04-02","Good Friday","CO",2010 +"2010-05-01","Dia del Trabajo","CO",2010 +"2010-05-17","Ascension of Jesus (Observed)","CO",2010 +"2010-06-07","Corpus Christi (Observed)","CO",2010 +"2010-06-14","Sacred Heart (Observed)","CO",2010 +"2010-07-05","Saint Peter and Saint Paul (Observed)","CO",2010 +"2010-07-20","Independence Day","CO",2010 +"2010-08-07","Battle of Boyaca","CO",2010 +"2010-08-16","Assumption of Mary (Observed)","CO",2010 +"2010-10-18","Columbus Day (Observed)","CO",2010 +"2010-11-01","All Saints' Day","CO",2010 +"2010-11-15","Independence of Cartagena (Observed)","CO",2010 +"2010-12-08","Immaculate Conception","CO",2010 +"2010-12-25","Christmas","CO",2010 +"2011-01-01","New Year's Day","CO",2011 +"2011-01-10","Epiphany (Observed)","CO",2011 +"2011-03-21","Saint Joseph's Day (Observed)","CO",2011 +"2011-04-21","Maundy Thursday","CO",2011 +"2011-04-22","Good Friday","CO",2011 +"2011-05-01","Dia del Trabajo","CO",2011 +"2011-06-06","Ascension of Jesus (Observed)","CO",2011 +"2011-06-27","Corpus Christi (Observed)","CO",2011 +"2011-07-04","Sacred Heart (Observed)","CO",2011 +"2011-07-04","Saint Peter and Saint Paul (Observed)","CO",2011 +"2011-07-20","Independence Day","CO",2011 +"2011-08-07","Battle of Boyaca","CO",2011 +"2011-08-15","Assumption of Mary","CO",2011 +"2011-10-17","Columbus Day (Observed)","CO",2011 +"2011-11-07","All Saints' Day (Observed)","CO",2011 +"2011-11-14","Independence of Cartagena (Observed)","CO",2011 +"2011-12-08","Immaculate Conception","CO",2011 +"2011-12-25","Christmas","CO",2011 +"2012-01-01","New Year's Day","CO",2012 +"2012-01-09","Epiphany (Observed)","CO",2012 +"2012-03-19","Saint Joseph's Day","CO",2012 +"2012-04-05","Maundy Thursday","CO",2012 +"2012-04-06","Good Friday","CO",2012 +"2012-05-01","Dia del Trabajo","CO",2012 +"2012-05-21","Ascension of Jesus (Observed)","CO",2012 +"2012-06-11","Corpus Christi (Observed)","CO",2012 +"2012-06-18","Sacred Heart (Observed)","CO",2012 +"2012-07-02","Saint Peter and Saint Paul (Observed)","CO",2012 +"2012-07-20","Independence Day","CO",2012 +"2012-08-07","Battle of Boyaca","CO",2012 +"2012-08-20","Assumption of Mary (Observed)","CO",2012 +"2012-10-15","Columbus Day (Observed)","CO",2012 +"2012-11-05","All Saints' Day (Observed)","CO",2012 +"2012-11-12","Independence of Cartagena (Observed)","CO",2012 +"2012-12-08","Immaculate Conception","CO",2012 +"2012-12-25","Christmas","CO",2012 +"2013-01-01","New Year's Day","CO",2013 +"2013-01-07","Epiphany (Observed)","CO",2013 +"2013-03-25","Saint Joseph's Day (Observed)","CO",2013 +"2013-03-28","Maundy Thursday","CO",2013 +"2013-03-29","Good Friday","CO",2013 +"2013-05-01","Dia del Trabajo","CO",2013 +"2013-05-13","Ascension of Jesus (Observed)","CO",2013 +"2013-06-03","Corpus Christi (Observed)","CO",2013 +"2013-06-10","Sacred Heart (Observed)","CO",2013 +"2013-07-01","Saint Peter and Saint Paul (Observed)","CO",2013 +"2013-07-20","Independence Day","CO",2013 +"2013-08-07","Battle of Boyaca","CO",2013 +"2013-08-19","Assumption of Mary (Observed)","CO",2013 +"2013-10-14","Columbus Day (Observed)","CO",2013 +"2013-11-04","All Saints' Day (Observed)","CO",2013 +"2013-11-11","Independence of Cartagena","CO",2013 +"2013-12-08","Immaculate Conception","CO",2013 +"2013-12-25","Christmas","CO",2013 +"2014-01-01","New Year's Day","CO",2014 +"2014-01-06","Epiphany","CO",2014 +"2014-03-24","Saint Joseph's Day (Observed)","CO",2014 +"2014-04-17","Maundy Thursday","CO",2014 +"2014-04-18","Good Friday","CO",2014 +"2014-05-01","Dia del Trabajo","CO",2014 +"2014-06-02","Ascension of Jesus (Observed)","CO",2014 +"2014-06-23","Corpus Christi (Observed)","CO",2014 +"2014-06-30","Sacred Heart (Observed)","CO",2014 +"2014-06-30","Saint Peter and Saint Paul (Observed)","CO",2014 +"2014-07-20","Independence Day","CO",2014 +"2014-08-07","Battle of Boyaca","CO",2014 +"2014-08-18","Assumption of Mary (Observed)","CO",2014 +"2014-10-13","Columbus Day (Observed)","CO",2014 +"2014-11-03","All Saints' Day (Observed)","CO",2014 +"2014-11-17","Independence of Cartagena (Observed)","CO",2014 +"2014-12-08","Immaculate Conception","CO",2014 +"2014-12-25","Christmas","CO",2014 +"2015-01-01","New Year's Day","CO",2015 +"2015-01-12","Epiphany (Observed)","CO",2015 +"2015-03-23","Saint Joseph's Day (Observed)","CO",2015 +"2015-04-02","Maundy Thursday","CO",2015 +"2015-04-03","Good Friday","CO",2015 +"2015-05-01","Dia del Trabajo","CO",2015 +"2015-05-18","Ascension of Jesus (Observed)","CO",2015 +"2015-06-08","Corpus Christi (Observed)","CO",2015 +"2015-06-15","Sacred Heart (Observed)","CO",2015 +"2015-06-29","Saint Peter and Saint Paul","CO",2015 +"2015-07-20","Independence Day","CO",2015 +"2015-08-07","Battle of Boyaca","CO",2015 +"2015-08-17","Assumption of Mary (Observed)","CO",2015 +"2015-10-12","Columbus Day","CO",2015 +"2015-11-02","All Saints' Day (Observed)","CO",2015 +"2015-11-16","Independence of Cartagena (Observed)","CO",2015 +"2015-12-08","Immaculate Conception","CO",2015 +"2015-12-25","Christmas","CO",2015 +"2016-01-01","New Year's Day","CO",2016 +"2016-01-11","Epiphany (Observed)","CO",2016 +"2016-03-21","Saint Joseph's Day (Observed)","CO",2016 +"2016-03-24","Maundy Thursday","CO",2016 +"2016-03-25","Good Friday","CO",2016 +"2016-05-01","Dia del Trabajo","CO",2016 +"2016-05-09","Ascension of Jesus (Observed)","CO",2016 +"2016-05-30","Corpus Christi (Observed)","CO",2016 +"2016-06-06","Sacred Heart (Observed)","CO",2016 +"2016-07-04","Saint Peter and Saint Paul (Observed)","CO",2016 +"2016-07-20","Independence Day","CO",2016 +"2016-08-07","Battle of Boyaca","CO",2016 +"2016-08-15","Assumption of Mary","CO",2016 +"2016-10-17","Columbus Day (Observed)","CO",2016 +"2016-11-07","All Saints' Day (Observed)","CO",2016 +"2016-11-14","Independence of Cartagena (Observed)","CO",2016 +"2016-12-08","Immaculate Conception","CO",2016 +"2016-12-25","Christmas","CO",2016 +"2017-01-01","New Year's Day","CO",2017 +"2017-01-09","Epiphany (Observed)","CO",2017 +"2017-03-20","Saint Joseph's Day (Observed)","CO",2017 +"2017-04-13","Maundy Thursday","CO",2017 +"2017-04-14","Good Friday","CO",2017 +"2017-05-01","Dia del Trabajo","CO",2017 +"2017-05-29","Ascension of Jesus (Observed)","CO",2017 +"2017-06-19","Corpus Christi (Observed)","CO",2017 +"2017-06-26","Sacred Heart (Observed)","CO",2017 +"2017-07-03","Saint Peter and Saint Paul (Observed)","CO",2017 +"2017-07-20","Independence Day","CO",2017 +"2017-08-07","Battle of Boyaca","CO",2017 +"2017-08-21","Assumption of Mary (Observed)","CO",2017 +"2017-10-16","Columbus Day (Observed)","CO",2017 +"2017-11-06","All Saints' Day (Observed)","CO",2017 +"2017-11-13","Independence of Cartagena (Observed)","CO",2017 +"2017-12-08","Immaculate Conception","CO",2017 +"2017-12-25","Christmas","CO",2017 +"2018-01-01","New Year's Day","CO",2018 +"2018-01-08","Epiphany (Observed)","CO",2018 +"2018-03-19","Saint Joseph's Day","CO",2018 +"2018-03-29","Maundy Thursday","CO",2018 +"2018-03-30","Good Friday","CO",2018 +"2018-05-01","Dia del Trabajo","CO",2018 +"2018-05-14","Ascension of Jesus (Observed)","CO",2018 +"2018-06-04","Corpus Christi (Observed)","CO",2018 +"2018-06-11","Sacred Heart (Observed)","CO",2018 +"2018-07-02","Saint Peter and Saint Paul (Observed)","CO",2018 +"2018-07-20","Independence Day","CO",2018 +"2018-08-07","Battle of Boyaca","CO",2018 +"2018-08-20","Assumption of Mary (Observed)","CO",2018 +"2018-10-15","Columbus Day (Observed)","CO",2018 +"2018-11-05","All Saints' Day (Observed)","CO",2018 +"2018-11-12","Independence of Cartagena (Observed)","CO",2018 +"2018-12-08","Immaculate Conception","CO",2018 +"2018-12-25","Christmas","CO",2018 +"2019-01-01","New Year's Day","CO",2019 +"2019-01-07","Epiphany (Observed)","CO",2019 +"2019-03-25","Saint Joseph's Day (Observed)","CO",2019 +"2019-04-18","Maundy Thursday","CO",2019 +"2019-04-19","Good Friday","CO",2019 +"2019-05-01","Dia del Trabajo","CO",2019 +"2019-06-03","Ascension of Jesus (Observed)","CO",2019 +"2019-06-24","Corpus Christi (Observed)","CO",2019 +"2019-07-01","Sacred Heart (Observed)","CO",2019 +"2019-07-01","Saint Peter and Saint Paul (Observed)","CO",2019 +"2019-07-20","Independence Day","CO",2019 +"2019-08-07","Battle of Boyaca","CO",2019 +"2019-08-19","Assumption of Mary (Observed)","CO",2019 +"2019-10-14","Columbus Day (Observed)","CO",2019 +"2019-11-04","All Saints' Day (Observed)","CO",2019 +"2019-11-11","Independence of Cartagena","CO",2019 +"2019-12-08","Immaculate Conception","CO",2019 +"2019-12-25","Christmas","CO",2019 +"2020-01-01","New Year's Day","CO",2020 +"2020-01-06","Epiphany","CO",2020 +"2020-03-23","Saint Joseph's Day (Observed)","CO",2020 +"2020-04-09","Maundy Thursday","CO",2020 +"2020-04-10","Good Friday","CO",2020 +"2020-05-01","Dia del Trabajo","CO",2020 +"2020-05-25","Ascension of Jesus (Observed)","CO",2020 +"2020-06-15","Corpus Christi (Observed)","CO",2020 +"2020-06-22","Sacred Heart (Observed)","CO",2020 +"2020-06-29","Saint Peter and Saint Paul","CO",2020 +"2020-07-20","Independence Day","CO",2020 +"2020-08-07","Battle of Boyaca","CO",2020 +"2020-08-17","Assumption of Mary (Observed)","CO",2020 +"2020-10-12","Columbus Day","CO",2020 +"2020-11-02","All Saints' Day (Observed)","CO",2020 +"2020-11-16","Independence of Cartagena (Observed)","CO",2020 +"2020-12-08","Immaculate Conception","CO",2020 +"2020-12-25","Christmas","CO",2020 +"2021-01-01","New Year's Day","CO",2021 +"2021-01-11","Epiphany (Observed)","CO",2021 +"2021-03-22","Saint Joseph's Day (Observed)","CO",2021 +"2021-04-01","Maundy Thursday","CO",2021 +"2021-04-02","Good Friday","CO",2021 +"2021-05-01","Dia del Trabajo","CO",2021 +"2021-05-17","Ascension of Jesus (Observed)","CO",2021 +"2021-06-07","Corpus Christi (Observed)","CO",2021 +"2021-06-14","Sacred Heart (Observed)","CO",2021 +"2021-07-05","Saint Peter and Saint Paul (Observed)","CO",2021 +"2021-07-20","Independence Day","CO",2021 +"2021-08-07","Battle of Boyaca","CO",2021 +"2021-08-16","Assumption of Mary (Observed)","CO",2021 +"2021-10-18","Columbus Day (Observed)","CO",2021 +"2021-11-01","All Saints' Day","CO",2021 +"2021-11-15","Independence of Cartagena (Observed)","CO",2021 +"2021-12-08","Immaculate Conception","CO",2021 +"2021-12-25","Christmas","CO",2021 +"2022-01-01","New Year's Day","CO",2022 +"2022-01-10","Epiphany (Observed)","CO",2022 +"2022-03-21","Saint Joseph's Day (Observed)","CO",2022 +"2022-04-14","Maundy Thursday","CO",2022 +"2022-04-15","Good Friday","CO",2022 +"2022-05-01","Dia del Trabajo","CO",2022 +"2022-05-30","Ascension of Jesus (Observed)","CO",2022 +"2022-06-20","Corpus Christi (Observed)","CO",2022 +"2022-06-27","Sacred Heart (Observed)","CO",2022 +"2022-07-04","Saint Peter and Saint Paul (Observed)","CO",2022 +"2022-07-20","Independence Day","CO",2022 +"2022-08-07","Battle of Boyaca","CO",2022 +"2022-08-15","Assumption of Mary","CO",2022 +"2022-10-17","Columbus Day (Observed)","CO",2022 +"2022-11-07","All Saints' Day (Observed)","CO",2022 +"2022-11-14","Independence of Cartagena (Observed)","CO",2022 +"2022-12-08","Immaculate Conception","CO",2022 +"2022-12-25","Christmas","CO",2022 +"2023-01-01","New Year's Day","CO",2023 +"2023-01-09","Epiphany (Observed)","CO",2023 +"2023-03-20","Saint Joseph's Day (Observed)","CO",2023 +"2023-04-06","Maundy Thursday","CO",2023 +"2023-04-07","Good Friday","CO",2023 +"2023-05-01","Dia del Trabajo","CO",2023 +"2023-05-22","Ascension of Jesus (Observed)","CO",2023 +"2023-06-12","Corpus Christi (Observed)","CO",2023 +"2023-06-19","Sacred Heart (Observed)","CO",2023 +"2023-07-03","Saint Peter and Saint Paul (Observed)","CO",2023 +"2023-07-20","Independence Day","CO",2023 +"2023-08-07","Battle of Boyaca","CO",2023 +"2023-08-21","Assumption of Mary (Observed)","CO",2023 +"2023-10-16","Columbus Day (Observed)","CO",2023 +"2023-11-06","All Saints' Day (Observed)","CO",2023 +"2023-11-13","Independence of Cartagena (Observed)","CO",2023 +"2023-12-08","Immaculate Conception","CO",2023 +"2023-12-25","Christmas","CO",2023 +"2024-01-01","New Year's Day","CO",2024 +"2024-01-08","Epiphany (Observed)","CO",2024 +"2024-03-25","Saint Joseph's Day (Observed)","CO",2024 +"2024-03-28","Maundy Thursday","CO",2024 +"2024-03-29","Good Friday","CO",2024 +"2024-05-01","Dia del Trabajo","CO",2024 +"2024-05-13","Ascension of Jesus (Observed)","CO",2024 +"2024-06-03","Corpus Christi (Observed)","CO",2024 +"2024-06-10","Sacred Heart (Observed)","CO",2024 +"2024-07-01","Saint Peter and Saint Paul (Observed)","CO",2024 +"2024-07-20","Independence Day","CO",2024 +"2024-08-07","Battle of Boyaca","CO",2024 +"2024-08-19","Assumption of Mary (Observed)","CO",2024 +"2024-10-14","Columbus Day (Observed)","CO",2024 +"2024-11-04","All Saints' Day (Observed)","CO",2024 +"2024-11-11","Independence of Cartagena","CO",2024 +"2024-12-08","Immaculate Conception","CO",2024 +"2024-12-25","Christmas","CO",2024 +"2025-01-01","New Year's Day","CO",2025 +"2025-01-06","Epiphany","CO",2025 +"2025-03-24","Saint Joseph's Day (Observed)","CO",2025 +"2025-04-17","Maundy Thursday","CO",2025 +"2025-04-18","Good Friday","CO",2025 +"2025-05-01","Dia del Trabajo","CO",2025 +"2025-06-02","Ascension of Jesus (Observed)","CO",2025 +"2025-06-23","Corpus Christi (Observed)","CO",2025 +"2025-06-30","Sacred Heart (Observed)","CO",2025 +"2025-06-30","Saint Peter and Saint Paul (Observed)","CO",2025 +"2025-07-20","Independence Day","CO",2025 +"2025-08-07","Battle of Boyaca","CO",2025 +"2025-08-18","Assumption of Mary (Observed)","CO",2025 +"2025-10-13","Columbus Day (Observed)","CO",2025 +"2025-11-03","All Saints' Day (Observed)","CO",2025 +"2025-11-17","Independence of Cartagena (Observed)","CO",2025 +"2025-12-08","Immaculate Conception","CO",2025 +"2025-12-25","Christmas","CO",2025 +"2026-01-01","New Year's Day","CO",2026 +"2026-01-12","Epiphany (Observed)","CO",2026 +"2026-03-23","Saint Joseph's Day (Observed)","CO",2026 +"2026-04-02","Maundy Thursday","CO",2026 +"2026-04-03","Good Friday","CO",2026 +"2026-05-01","Dia del Trabajo","CO",2026 +"2026-05-18","Ascension of Jesus (Observed)","CO",2026 +"2026-06-08","Corpus Christi (Observed)","CO",2026 +"2026-06-15","Sacred Heart (Observed)","CO",2026 +"2026-06-29","Saint Peter and Saint Paul","CO",2026 +"2026-07-20","Independence Day","CO",2026 +"2026-08-07","Battle of Boyaca","CO",2026 +"2026-08-17","Assumption of Mary (Observed)","CO",2026 +"2026-10-12","Columbus Day","CO",2026 +"2026-11-02","All Saints' Day (Observed)","CO",2026 +"2026-11-16","Independence of Cartagena (Observed)","CO",2026 +"2026-12-08","Immaculate Conception","CO",2026 +"2026-12-25","Christmas","CO",2026 +"2027-01-01","New Year's Day","CO",2027 +"2027-01-11","Epiphany (Observed)","CO",2027 +"2027-03-22","Saint Joseph's Day (Observed)","CO",2027 +"2027-03-25","Maundy Thursday","CO",2027 +"2027-03-26","Good Friday","CO",2027 +"2027-05-01","Dia del Trabajo","CO",2027 +"2027-05-10","Ascension of Jesus (Observed)","CO",2027 +"2027-05-31","Corpus Christi (Observed)","CO",2027 +"2027-06-07","Sacred Heart (Observed)","CO",2027 +"2027-07-05","Saint Peter and Saint Paul (Observed)","CO",2027 +"2027-07-20","Independence Day","CO",2027 +"2027-08-07","Battle of Boyaca","CO",2027 +"2027-08-16","Assumption of Mary (Observed)","CO",2027 +"2027-10-18","Columbus Day (Observed)","CO",2027 +"2027-11-01","All Saints' Day","CO",2027 +"2027-11-15","Independence of Cartagena (Observed)","CO",2027 +"2027-12-08","Immaculate Conception","CO",2027 +"2027-12-25","Christmas","CO",2027 +"2028-01-01","New Year's Day","CO",2028 +"2028-01-10","Epiphany (Observed)","CO",2028 +"2028-03-20","Saint Joseph's Day (Observed)","CO",2028 +"2028-04-13","Maundy Thursday","CO",2028 +"2028-04-14","Good Friday","CO",2028 +"2028-05-01","Dia del Trabajo","CO",2028 +"2028-05-29","Ascension of Jesus (Observed)","CO",2028 +"2028-06-19","Corpus Christi (Observed)","CO",2028 +"2028-06-26","Sacred Heart (Observed)","CO",2028 +"2028-07-03","Saint Peter and Saint Paul (Observed)","CO",2028 +"2028-07-20","Independence Day","CO",2028 +"2028-08-07","Battle of Boyaca","CO",2028 +"2028-08-21","Assumption of Mary (Observed)","CO",2028 +"2028-10-16","Columbus Day (Observed)","CO",2028 +"2028-11-06","All Saints' Day (Observed)","CO",2028 +"2028-11-13","Independence of Cartagena (Observed)","CO",2028 +"2028-12-08","Immaculate Conception","CO",2028 +"2028-12-25","Christmas","CO",2028 +"2029-01-01","New Year's Day","CO",2029 +"2029-01-08","Epiphany (Observed)","CO",2029 +"2029-03-19","Saint Joseph's Day","CO",2029 +"2029-03-29","Maundy Thursday","CO",2029 +"2029-03-30","Good Friday","CO",2029 +"2029-05-01","Dia del Trabajo","CO",2029 +"2029-05-14","Ascension of Jesus (Observed)","CO",2029 +"2029-06-04","Corpus Christi (Observed)","CO",2029 +"2029-06-11","Sacred Heart (Observed)","CO",2029 +"2029-07-02","Saint Peter and Saint Paul (Observed)","CO",2029 +"2029-07-20","Independence Day","CO",2029 +"2029-08-07","Battle of Boyaca","CO",2029 +"2029-08-20","Assumption of Mary (Observed)","CO",2029 +"2029-10-15","Columbus Day (Observed)","CO",2029 +"2029-11-05","All Saints' Day (Observed)","CO",2029 +"2029-11-12","Independence of Cartagena (Observed)","CO",2029 +"2029-12-08","Immaculate Conception","CO",2029 +"2029-12-25","Christmas","CO",2029 +"2030-01-01","New Year's Day","CO",2030 +"2030-01-07","Epiphany (Observed)","CO",2030 +"2030-03-25","Saint Joseph's Day (Observed)","CO",2030 +"2030-04-18","Maundy Thursday","CO",2030 +"2030-04-19","Good Friday","CO",2030 +"2030-05-01","Dia del Trabajo","CO",2030 +"2030-06-03","Ascension of Jesus (Observed)","CO",2030 +"2030-06-24","Corpus Christi (Observed)","CO",2030 +"2030-07-01","Sacred Heart (Observed)","CO",2030 +"2030-07-01","Saint Peter and Saint Paul (Observed)","CO",2030 +"2030-07-20","Independence Day","CO",2030 +"2030-08-07","Battle of Boyaca","CO",2030 +"2030-08-19","Assumption of Mary (Observed)","CO",2030 +"2030-10-14","Columbus Day (Observed)","CO",2030 +"2030-11-04","All Saints' Day (Observed)","CO",2030 +"2030-11-11","Independence of Cartagena","CO",2030 +"2030-12-08","Immaculate Conception","CO",2030 +"2030-12-25","Christmas","CO",2030 +"2031-01-01","New Year's Day","CO",2031 +"2031-01-06","Epiphany","CO",2031 +"2031-03-24","Saint Joseph's Day (Observed)","CO",2031 +"2031-04-10","Maundy Thursday","CO",2031 +"2031-04-11","Good Friday","CO",2031 +"2031-05-01","Dia del Trabajo","CO",2031 +"2031-05-26","Ascension of Jesus (Observed)","CO",2031 +"2031-06-16","Corpus Christi (Observed)","CO",2031 +"2031-06-23","Sacred Heart (Observed)","CO",2031 +"2031-06-30","Saint Peter and Saint Paul (Observed)","CO",2031 +"2031-07-20","Independence Day","CO",2031 +"2031-08-07","Battle of Boyaca","CO",2031 +"2031-08-18","Assumption of Mary (Observed)","CO",2031 +"2031-10-13","Columbus Day (Observed)","CO",2031 +"2031-11-03","All Saints' Day (Observed)","CO",2031 +"2031-11-17","Independence of Cartagena (Observed)","CO",2031 +"2031-12-08","Immaculate Conception","CO",2031 +"2031-12-25","Christmas","CO",2031 +"2032-01-01","New Year's Day","CO",2032 +"2032-01-12","Epiphany (Observed)","CO",2032 +"2032-03-22","Saint Joseph's Day (Observed)","CO",2032 +"2032-03-25","Maundy Thursday","CO",2032 +"2032-03-26","Good Friday","CO",2032 +"2032-05-01","Dia del Trabajo","CO",2032 +"2032-05-10","Ascension of Jesus (Observed)","CO",2032 +"2032-05-31","Corpus Christi (Observed)","CO",2032 +"2032-06-07","Sacred Heart (Observed)","CO",2032 +"2032-07-05","Saint Peter and Saint Paul (Observed)","CO",2032 +"2032-07-20","Independence Day","CO",2032 +"2032-08-07","Battle of Boyaca","CO",2032 +"2032-08-16","Assumption of Mary (Observed)","CO",2032 +"2032-10-18","Columbus Day (Observed)","CO",2032 +"2032-11-01","All Saints' Day","CO",2032 +"2032-11-15","Independence of Cartagena (Observed)","CO",2032 +"2032-12-08","Immaculate Conception","CO",2032 +"2032-12-25","Christmas","CO",2032 +"2033-01-01","New Year's Day","CO",2033 +"2033-01-10","Epiphany (Observed)","CO",2033 +"2033-03-21","Saint Joseph's Day (Observed)","CO",2033 +"2033-04-14","Maundy Thursday","CO",2033 +"2033-04-15","Good Friday","CO",2033 +"2033-05-01","Dia del Trabajo","CO",2033 +"2033-05-30","Ascension of Jesus (Observed)","CO",2033 +"2033-06-20","Corpus Christi (Observed)","CO",2033 +"2033-06-27","Sacred Heart (Observed)","CO",2033 +"2033-07-04","Saint Peter and Saint Paul (Observed)","CO",2033 +"2033-07-20","Independence Day","CO",2033 +"2033-08-07","Battle of Boyaca","CO",2033 +"2033-08-15","Assumption of Mary","CO",2033 +"2033-10-17","Columbus Day (Observed)","CO",2033 +"2033-11-07","All Saints' Day (Observed)","CO",2033 +"2033-11-14","Independence of Cartagena (Observed)","CO",2033 +"2033-12-08","Immaculate Conception","CO",2033 +"2033-12-25","Christmas","CO",2033 +"2034-01-01","New Year's Day","CO",2034 +"2034-01-09","Epiphany (Observed)","CO",2034 +"2034-03-20","Saint Joseph's Day (Observed)","CO",2034 +"2034-04-06","Maundy Thursday","CO",2034 +"2034-04-07","Good Friday","CO",2034 +"2034-05-01","Dia del Trabajo","CO",2034 +"2034-05-22","Ascension of Jesus (Observed)","CO",2034 +"2034-06-12","Corpus Christi (Observed)","CO",2034 +"2034-06-19","Sacred Heart (Observed)","CO",2034 +"2034-07-03","Saint Peter and Saint Paul (Observed)","CO",2034 +"2034-07-20","Independence Day","CO",2034 +"2034-08-07","Battle of Boyaca","CO",2034 +"2034-08-21","Assumption of Mary (Observed)","CO",2034 +"2034-10-16","Columbus Day (Observed)","CO",2034 +"2034-11-06","All Saints' Day (Observed)","CO",2034 +"2034-11-13","Independence of Cartagena (Observed)","CO",2034 +"2034-12-08","Immaculate Conception","CO",2034 +"2034-12-25","Christmas","CO",2034 +"2035-01-01","New Year's Day","CO",2035 +"2035-01-08","Epiphany (Observed)","CO",2035 +"2035-03-19","Saint Joseph's Day","CO",2035 +"2035-03-22","Maundy Thursday","CO",2035 +"2035-03-23","Good Friday","CO",2035 +"2035-05-01","Dia del Trabajo","CO",2035 +"2035-05-07","Ascension of Jesus (Observed)","CO",2035 +"2035-05-28","Corpus Christi (Observed)","CO",2035 +"2035-06-04","Sacred Heart (Observed)","CO",2035 +"2035-07-02","Saint Peter and Saint Paul (Observed)","CO",2035 +"2035-07-20","Independence Day","CO",2035 +"2035-08-07","Battle of Boyaca","CO",2035 +"2035-08-20","Assumption of Mary (Observed)","CO",2035 +"2035-10-15","Columbus Day (Observed)","CO",2035 +"2035-11-05","All Saints' Day (Observed)","CO",2035 +"2035-11-12","Independence of Cartagena (Observed)","CO",2035 +"2035-12-08","Immaculate Conception","CO",2035 +"2035-12-25","Christmas","CO",2035 +"2036-01-01","New Year's Day","CO",2036 +"2036-01-07","Epiphany (Observed)","CO",2036 +"2036-03-24","Saint Joseph's Day (Observed)","CO",2036 +"2036-04-10","Maundy Thursday","CO",2036 +"2036-04-11","Good Friday","CO",2036 +"2036-05-01","Dia del Trabajo","CO",2036 +"2036-05-26","Ascension of Jesus (Observed)","CO",2036 +"2036-06-16","Corpus Christi (Observed)","CO",2036 +"2036-06-23","Sacred Heart (Observed)","CO",2036 +"2036-06-30","Saint Peter and Saint Paul (Observed)","CO",2036 +"2036-07-20","Independence Day","CO",2036 +"2036-08-07","Battle of Boyaca","CO",2036 +"2036-08-18","Assumption of Mary (Observed)","CO",2036 +"2036-10-13","Columbus Day (Observed)","CO",2036 +"2036-11-03","All Saints' Day (Observed)","CO",2036 +"2036-11-17","Independence of Cartagena (Observed)","CO",2036 +"2036-12-08","Immaculate Conception","CO",2036 +"2036-12-25","Christmas","CO",2036 +"2037-01-01","New Year's Day","CO",2037 +"2037-01-12","Epiphany (Observed)","CO",2037 +"2037-03-23","Saint Joseph's Day (Observed)","CO",2037 +"2037-04-02","Maundy Thursday","CO",2037 +"2037-04-03","Good Friday","CO",2037 +"2037-05-01","Dia del Trabajo","CO",2037 +"2037-05-18","Ascension of Jesus (Observed)","CO",2037 +"2037-06-08","Corpus Christi (Observed)","CO",2037 +"2037-06-15","Sacred Heart (Observed)","CO",2037 +"2037-06-29","Saint Peter and Saint Paul","CO",2037 +"2037-07-20","Independence Day","CO",2037 +"2037-08-07","Battle of Boyaca","CO",2037 +"2037-08-17","Assumption of Mary (Observed)","CO",2037 +"2037-10-12","Columbus Day","CO",2037 +"2037-11-02","All Saints' Day (Observed)","CO",2037 +"2037-11-16","Independence of Cartagena (Observed)","CO",2037 +"2037-12-08","Immaculate Conception","CO",2037 +"2037-12-25","Christmas","CO",2037 +"2038-01-01","New Year's Day","CO",2038 +"2038-01-11","Epiphany (Observed)","CO",2038 +"2038-03-22","Saint Joseph's Day (Observed)","CO",2038 +"2038-04-22","Maundy Thursday","CO",2038 +"2038-04-23","Good Friday","CO",2038 +"2038-05-01","Dia del Trabajo","CO",2038 +"2038-06-07","Ascension of Jesus (Observed)","CO",2038 +"2038-06-28","Corpus Christi (Observed)","CO",2038 +"2038-07-05","Sacred Heart (Observed)","CO",2038 +"2038-07-05","Saint Peter and Saint Paul (Observed)","CO",2038 +"2038-07-20","Independence Day","CO",2038 +"2038-08-07","Battle of Boyaca","CO",2038 +"2038-08-16","Assumption of Mary (Observed)","CO",2038 +"2038-10-18","Columbus Day (Observed)","CO",2038 +"2038-11-01","All Saints' Day","CO",2038 +"2038-11-15","Independence of Cartagena (Observed)","CO",2038 +"2038-12-08","Immaculate Conception","CO",2038 +"2038-12-25","Christmas","CO",2038 +"2039-01-01","New Year's Day","CO",2039 +"2039-01-10","Epiphany (Observed)","CO",2039 +"2039-03-21","Saint Joseph's Day (Observed)","CO",2039 +"2039-04-07","Maundy Thursday","CO",2039 +"2039-04-08","Good Friday","CO",2039 +"2039-05-01","Dia del Trabajo","CO",2039 +"2039-05-23","Ascension of Jesus (Observed)","CO",2039 +"2039-06-13","Corpus Christi (Observed)","CO",2039 +"2039-06-20","Sacred Heart (Observed)","CO",2039 +"2039-07-04","Saint Peter and Saint Paul (Observed)","CO",2039 +"2039-07-20","Independence Day","CO",2039 +"2039-08-07","Battle of Boyaca","CO",2039 +"2039-08-15","Assumption of Mary","CO",2039 +"2039-10-17","Columbus Day (Observed)","CO",2039 +"2039-11-07","All Saints' Day (Observed)","CO",2039 +"2039-11-14","Independence of Cartagena (Observed)","CO",2039 +"2039-12-08","Immaculate Conception","CO",2039 +"2039-12-25","Christmas","CO",2039 +"2040-01-01","New Year's Day","CO",2040 +"2040-01-09","Epiphany (Observed)","CO",2040 +"2040-03-19","Saint Joseph's Day","CO",2040 +"2040-03-29","Maundy Thursday","CO",2040 +"2040-03-30","Good Friday","CO",2040 +"2040-05-01","Dia del Trabajo","CO",2040 +"2040-05-14","Ascension of Jesus (Observed)","CO",2040 +"2040-06-04","Corpus Christi (Observed)","CO",2040 +"2040-06-11","Sacred Heart (Observed)","CO",2040 +"2040-07-02","Saint Peter and Saint Paul (Observed)","CO",2040 +"2040-07-20","Independence Day","CO",2040 +"2040-08-07","Battle of Boyaca","CO",2040 +"2040-08-20","Assumption of Mary (Observed)","CO",2040 +"2040-10-15","Columbus Day (Observed)","CO",2040 +"2040-11-05","All Saints' Day (Observed)","CO",2040 +"2040-11-12","Independence of Cartagena (Observed)","CO",2040 +"2040-12-08","Immaculate Conception","CO",2040 +"2040-12-25","Christmas","CO",2040 +"2041-01-01","New Year's Day","CO",2041 +"2041-01-07","Epiphany (Observed)","CO",2041 +"2041-03-25","Saint Joseph's Day (Observed)","CO",2041 +"2041-04-18","Maundy Thursday","CO",2041 +"2041-04-19","Good Friday","CO",2041 +"2041-05-01","Dia del Trabajo","CO",2041 +"2041-06-03","Ascension of Jesus (Observed)","CO",2041 +"2041-06-24","Corpus Christi (Observed)","CO",2041 +"2041-07-01","Sacred Heart (Observed)","CO",2041 +"2041-07-01","Saint Peter and Saint Paul (Observed)","CO",2041 +"2041-07-20","Independence Day","CO",2041 +"2041-08-07","Battle of Boyaca","CO",2041 +"2041-08-19","Assumption of Mary (Observed)","CO",2041 +"2041-10-14","Columbus Day (Observed)","CO",2041 +"2041-11-04","All Saints' Day (Observed)","CO",2041 +"2041-11-11","Independence of Cartagena","CO",2041 +"2041-12-08","Immaculate Conception","CO",2041 +"2041-12-25","Christmas","CO",2041 +"2042-01-01","New Year's Day","CO",2042 +"2042-01-06","Epiphany","CO",2042 +"2042-03-24","Saint Joseph's Day (Observed)","CO",2042 +"2042-04-03","Maundy Thursday","CO",2042 +"2042-04-04","Good Friday","CO",2042 +"2042-05-01","Dia del Trabajo","CO",2042 +"2042-05-19","Ascension of Jesus (Observed)","CO",2042 +"2042-06-09","Corpus Christi (Observed)","CO",2042 +"2042-06-16","Sacred Heart (Observed)","CO",2042 +"2042-06-30","Saint Peter and Saint Paul (Observed)","CO",2042 +"2042-07-20","Independence Day","CO",2042 +"2042-08-07","Battle of Boyaca","CO",2042 +"2042-08-18","Assumption of Mary (Observed)","CO",2042 +"2042-10-13","Columbus Day (Observed)","CO",2042 +"2042-11-03","All Saints' Day (Observed)","CO",2042 +"2042-11-17","Independence of Cartagena (Observed)","CO",2042 +"2042-12-08","Immaculate Conception","CO",2042 +"2042-12-25","Christmas","CO",2042 +"2043-01-01","New Year's Day","CO",2043 +"2043-01-12","Epiphany (Observed)","CO",2043 +"2043-03-23","Saint Joseph's Day (Observed)","CO",2043 +"2043-03-26","Maundy Thursday","CO",2043 +"2043-03-27","Good Friday","CO",2043 +"2043-05-01","Dia del Trabajo","CO",2043 +"2043-05-11","Ascension of Jesus (Observed)","CO",2043 +"2043-06-01","Corpus Christi (Observed)","CO",2043 +"2043-06-08","Sacred Heart (Observed)","CO",2043 +"2043-06-29","Saint Peter and Saint Paul","CO",2043 +"2043-07-20","Independence Day","CO",2043 +"2043-08-07","Battle of Boyaca","CO",2043 +"2043-08-17","Assumption of Mary (Observed)","CO",2043 +"2043-10-12","Columbus Day","CO",2043 +"2043-11-02","All Saints' Day (Observed)","CO",2043 +"2043-11-16","Independence of Cartagena (Observed)","CO",2043 +"2043-12-08","Immaculate Conception","CO",2043 +"2043-12-25","Christmas","CO",2043 +"2044-01-01","New Year's Day","CO",2044 +"2044-01-11","Epiphany (Observed)","CO",2044 +"2044-03-21","Saint Joseph's Day (Observed)","CO",2044 +"2044-04-14","Maundy Thursday","CO",2044 +"2044-04-15","Good Friday","CO",2044 +"2044-05-01","Dia del Trabajo","CO",2044 +"2044-05-30","Ascension of Jesus (Observed)","CO",2044 +"2044-06-20","Corpus Christi (Observed)","CO",2044 +"2044-06-27","Sacred Heart (Observed)","CO",2044 +"2044-07-04","Saint Peter and Saint Paul (Observed)","CO",2044 +"2044-07-20","Independence Day","CO",2044 +"2044-08-07","Battle of Boyaca","CO",2044 +"2044-08-15","Assumption of Mary","CO",2044 +"2044-10-17","Columbus Day (Observed)","CO",2044 +"2044-11-07","All Saints' Day (Observed)","CO",2044 +"2044-11-14","Independence of Cartagena (Observed)","CO",2044 +"2044-12-08","Immaculate Conception","CO",2044 +"2044-12-25","Christmas","CO",2044 +"1995-01-01","New Year's Day","CR",1995 +"1995-04-11","Juan Santamaria Day","CR",1995 +"1995-04-13","Maundy Thursday","CR",1995 +"1995-04-14","Good Friday","CR",1995 +"1995-05-01","International Workers' Day","CR",1995 +"1995-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",1995 +"1995-08-02","Feast of Our Lady of the Angels","CR",1995 +"1995-08-15","Mother's Day","CR",1995 +"1995-09-15","Independence Day","CR",1995 +"1995-10-16","Cultures Day (Observed)","CR",1995 +"1995-12-25","Christmas Day","CR",1995 +"1996-01-01","New Year's Day","CR",1996 +"1996-04-04","Maundy Thursday","CR",1996 +"1996-04-05","Good Friday","CR",1996 +"1996-04-11","Juan Santamaria Day","CR",1996 +"1996-05-01","International Workers' Day","CR",1996 +"1996-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",1996 +"1996-08-02","Feast of Our Lady of the Angels","CR",1996 +"1996-08-15","Mother's Day","CR",1996 +"1996-09-15","Independence Day","CR",1996 +"1996-10-12","Cultures Day","CR",1996 +"1996-12-25","Christmas Day","CR",1996 +"1997-01-01","New Year's Day","CR",1997 +"1997-03-27","Maundy Thursday","CR",1997 +"1997-03-28","Good Friday","CR",1997 +"1997-04-11","Juan Santamaria Day","CR",1997 +"1997-05-01","International Workers' Day","CR",1997 +"1997-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",1997 +"1997-08-02","Feast of Our Lady of the Angels","CR",1997 +"1997-08-15","Mother's Day","CR",1997 +"1997-09-15","Independence Day","CR",1997 +"1997-10-12","Cultures Day","CR",1997 +"1997-12-25","Christmas Day","CR",1997 +"1998-01-01","New Year's Day","CR",1998 +"1998-04-09","Maundy Thursday","CR",1998 +"1998-04-10","Good Friday","CR",1998 +"1998-04-11","Juan Santamaria Day","CR",1998 +"1998-05-01","International Workers' Day","CR",1998 +"1998-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",1998 +"1998-08-02","Feast of Our Lady of the Angels","CR",1998 +"1998-08-15","Mother's Day","CR",1998 +"1998-09-15","Independence Day","CR",1998 +"1998-10-12","Cultures Day","CR",1998 +"1998-12-25","Christmas Day","CR",1998 +"1999-01-01","New Year's Day","CR",1999 +"1999-04-01","Maundy Thursday","CR",1999 +"1999-04-02","Good Friday","CR",1999 +"1999-04-11","Juan Santamaria Day","CR",1999 +"1999-05-01","International Workers' Day","CR",1999 +"1999-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",1999 +"1999-08-02","Feast of Our Lady of the Angels","CR",1999 +"1999-08-15","Mother's Day","CR",1999 +"1999-09-15","Independence Day","CR",1999 +"1999-10-18","Cultures Day (Observed)","CR",1999 +"1999-12-25","Christmas Day","CR",1999 +"2000-01-01","New Year's Day","CR",2000 +"2000-04-11","Juan Santamaria Day","CR",2000 +"2000-04-20","Maundy Thursday","CR",2000 +"2000-04-21","Good Friday","CR",2000 +"2000-05-01","International Workers' Day","CR",2000 +"2000-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2000 +"2000-08-02","Feast of Our Lady of the Angels","CR",2000 +"2000-08-15","Mother's Day","CR",2000 +"2000-09-15","Independence Day","CR",2000 +"2000-10-16","Cultures Day (Observed)","CR",2000 +"2000-12-25","Christmas Day","CR",2000 +"2001-01-01","New Year's Day","CR",2001 +"2001-04-11","Juan Santamaria Day","CR",2001 +"2001-04-12","Maundy Thursday","CR",2001 +"2001-04-13","Good Friday","CR",2001 +"2001-05-01","International Workers' Day","CR",2001 +"2001-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2001 +"2001-08-02","Feast of Our Lady of the Angels","CR",2001 +"2001-08-15","Mother's Day","CR",2001 +"2001-09-15","Independence Day","CR",2001 +"2001-10-15","Cultures Day (Observed)","CR",2001 +"2001-12-25","Christmas Day","CR",2001 +"2002-01-01","New Year's Day","CR",2002 +"2002-03-28","Maundy Thursday","CR",2002 +"2002-03-29","Good Friday","CR",2002 +"2002-04-11","Juan Santamaria Day","CR",2002 +"2002-05-01","International Workers' Day","CR",2002 +"2002-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2002 +"2002-08-02","Feast of Our Lady of the Angels","CR",2002 +"2002-08-15","Mother's Day","CR",2002 +"2002-09-15","Independence Day","CR",2002 +"2002-10-12","Cultures Day","CR",2002 +"2002-12-25","Christmas Day","CR",2002 +"2003-01-01","New Year's Day","CR",2003 +"2003-04-11","Juan Santamaria Day","CR",2003 +"2003-04-17","Maundy Thursday","CR",2003 +"2003-04-18","Good Friday","CR",2003 +"2003-05-01","International Workers' Day","CR",2003 +"2003-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2003 +"2003-08-02","Feast of Our Lady of the Angels","CR",2003 +"2003-08-15","Mother's Day","CR",2003 +"2003-09-15","Independence Day","CR",2003 +"2003-10-12","Cultures Day","CR",2003 +"2003-12-25","Christmas Day","CR",2003 +"2004-01-01","New Year's Day","CR",2004 +"2004-04-08","Maundy Thursday","CR",2004 +"2004-04-09","Good Friday","CR",2004 +"2004-04-11","Juan Santamaria Day","CR",2004 +"2004-05-01","International Workers' Day","CR",2004 +"2004-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2004 +"2004-08-02","Feast of Our Lady of the Angels","CR",2004 +"2004-08-15","Mother's Day","CR",2004 +"2004-09-15","Independence Day","CR",2004 +"2004-10-18","Cultures Day (Observed)","CR",2004 +"2004-12-25","Christmas Day","CR",2004 +"2005-01-01","New Year's Day","CR",2005 +"2005-03-24","Maundy Thursday","CR",2005 +"2005-03-25","Good Friday","CR",2005 +"2005-04-11","Juan Santamaria Day","CR",2005 +"2005-05-01","International Workers' Day","CR",2005 +"2005-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2005 +"2005-08-02","Feast of Our Lady of the Angels","CR",2005 +"2005-08-15","Mother's Day","CR",2005 +"2005-09-15","Independence Day","CR",2005 +"2005-10-17","Cultures Day (Observed)","CR",2005 +"2005-12-25","Christmas Day","CR",2005 +"2006-01-01","New Year's Day","CR",2006 +"2006-04-13","Maundy Thursday","CR",2006 +"2006-04-14","Good Friday","CR",2006 +"2006-04-17","Juan Santamaria Day (Observed)","CR",2006 +"2006-05-01","International Workers' Day","CR",2006 +"2006-07-31","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2006 +"2006-08-02","Feast of Our Lady of the Angels","CR",2006 +"2006-08-21","Mother's Day (Observed)","CR",2006 +"2006-09-15","Independence Day","CR",2006 +"2006-10-16","Cultures Day (Observed)","CR",2006 +"2006-12-25","Christmas Day","CR",2006 +"2007-01-01","New Year's Day","CR",2007 +"2007-04-05","Maundy Thursday","CR",2007 +"2007-04-06","Good Friday","CR",2007 +"2007-04-16","Juan Santamaria Day (Observed)","CR",2007 +"2007-05-01","International Workers' Day","CR",2007 +"2007-07-30","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2007 +"2007-08-02","Feast of Our Lady of the Angels","CR",2007 +"2007-08-20","Mother's Day (Observed)","CR",2007 +"2007-09-15","Independence Day","CR",2007 +"2007-10-15","Cultures Day (Observed)","CR",2007 +"2007-12-25","Christmas Day","CR",2007 +"2008-01-01","New Year's Day","CR",2008 +"2008-03-20","Maundy Thursday","CR",2008 +"2008-03-21","Good Friday","CR",2008 +"2008-04-14","Juan Santamaria Day (Observed)","CR",2008 +"2008-05-01","International Workers' Day","CR",2008 +"2008-07-28","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2008 +"2008-08-02","Feast of Our Lady of the Angels","CR",2008 +"2008-08-15","Mother's Day","CR",2008 +"2008-09-15","Independence Day","CR",2008 +"2008-10-12","Cultures Day","CR",2008 +"2008-12-25","Christmas Day","CR",2008 +"2009-01-01","New Year's Day","CR",2009 +"2009-04-09","Maundy Thursday","CR",2009 +"2009-04-10","Good Friday","CR",2009 +"2009-04-11","Juan Santamaria Day","CR",2009 +"2009-05-01","International Workers' Day","CR",2009 +"2009-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2009 +"2009-08-02","Feast of Our Lady of the Angels","CR",2009 +"2009-08-15","Mother's Day","CR",2009 +"2009-09-15","Independence Day","CR",2009 +"2009-10-12","Cultures Day","CR",2009 +"2009-12-25","Christmas Day","CR",2009 +"2010-01-01","New Year's Day","CR",2010 +"2010-04-01","Maundy Thursday","CR",2010 +"2010-04-02","Good Friday","CR",2010 +"2010-04-11","Juan Santamaria Day","CR",2010 +"2010-05-01","International Workers' Day","CR",2010 +"2010-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2010 +"2010-08-02","Feast of Our Lady of the Angels","CR",2010 +"2010-08-15","Mother's Day","CR",2010 +"2010-09-15","Independence Day","CR",2010 +"2010-10-18","Cultures Day (Observed)","CR",2010 +"2010-12-25","Christmas Day","CR",2010 +"2011-01-01","New Year's Day","CR",2011 +"2011-04-11","Juan Santamaria Day","CR",2011 +"2011-04-21","Maundy Thursday","CR",2011 +"2011-04-22","Good Friday","CR",2011 +"2011-05-01","International Workers' Day","CR",2011 +"2011-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2011 +"2011-08-02","Feast of Our Lady of the Angels","CR",2011 +"2011-08-15","Mother's Day","CR",2011 +"2011-09-15","Independence Day","CR",2011 +"2011-10-17","Cultures Day (Observed)","CR",2011 +"2011-12-25","Christmas Day","CR",2011 +"2012-01-01","New Year's Day","CR",2012 +"2012-04-05","Maundy Thursday","CR",2012 +"2012-04-06","Good Friday","CR",2012 +"2012-04-11","Juan Santamaria Day","CR",2012 +"2012-05-01","International Workers' Day","CR",2012 +"2012-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2012 +"2012-08-02","Feast of Our Lady of the Angels","CR",2012 +"2012-08-15","Mother's Day","CR",2012 +"2012-09-15","Independence Day","CR",2012 +"2012-10-15","Cultures Day (Observed)","CR",2012 +"2012-12-25","Christmas Day","CR",2012 +"2013-01-01","New Year's Day","CR",2013 +"2013-03-28","Maundy Thursday","CR",2013 +"2013-03-29","Good Friday","CR",2013 +"2013-04-11","Juan Santamaria Day","CR",2013 +"2013-05-01","International Workers' Day","CR",2013 +"2013-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2013 +"2013-08-02","Feast of Our Lady of the Angels","CR",2013 +"2013-08-15","Mother's Day","CR",2013 +"2013-09-15","Independence Day","CR",2013 +"2013-10-12","Cultures Day","CR",2013 +"2013-12-25","Christmas Day","CR",2013 +"2014-01-01","New Year's Day","CR",2014 +"2014-04-11","Juan Santamaria Day","CR",2014 +"2014-04-17","Maundy Thursday","CR",2014 +"2014-04-18","Good Friday","CR",2014 +"2014-05-01","International Workers' Day","CR",2014 +"2014-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2014 +"2014-08-02","Feast of Our Lady of the Angels","CR",2014 +"2014-08-15","Mother's Day","CR",2014 +"2014-09-15","Independence Day","CR",2014 +"2014-10-12","Cultures Day","CR",2014 +"2014-12-25","Christmas Day","CR",2014 +"2015-01-01","New Year's Day","CR",2015 +"2015-04-02","Maundy Thursday","CR",2015 +"2015-04-03","Good Friday","CR",2015 +"2015-04-11","Juan Santamaria Day","CR",2015 +"2015-05-01","International Workers' Day","CR",2015 +"2015-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2015 +"2015-08-02","Feast of Our Lady of the Angels","CR",2015 +"2015-08-15","Mother's Day","CR",2015 +"2015-09-15","Independence Day","CR",2015 +"2015-10-12","Cultures Day","CR",2015 +"2015-12-25","Christmas Day","CR",2015 +"2016-01-01","New Year's Day","CR",2016 +"2016-03-24","Maundy Thursday","CR",2016 +"2016-03-25","Good Friday","CR",2016 +"2016-04-11","Juan Santamaria Day","CR",2016 +"2016-05-01","International Workers' Day","CR",2016 +"2016-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2016 +"2016-08-02","Feast of Our Lady of the Angels","CR",2016 +"2016-08-15","Mother's Day","CR",2016 +"2016-09-15","Independence Day","CR",2016 +"2016-10-17","Cultures Day (Observed)","CR",2016 +"2016-12-25","Christmas Day","CR",2016 +"2017-01-01","New Year's Day","CR",2017 +"2017-04-11","Juan Santamaria Day","CR",2017 +"2017-04-13","Maundy Thursday","CR",2017 +"2017-04-14","Good Friday","CR",2017 +"2017-05-01","International Workers' Day","CR",2017 +"2017-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2017 +"2017-08-02","Feast of Our Lady of the Angels","CR",2017 +"2017-08-15","Mother's Day","CR",2017 +"2017-09-15","Independence Day","CR",2017 +"2017-10-16","Cultures Day (Observed)","CR",2017 +"2017-12-25","Christmas Day","CR",2017 +"2018-01-01","New Year's Day","CR",2018 +"2018-03-29","Maundy Thursday","CR",2018 +"2018-03-30","Good Friday","CR",2018 +"2018-04-11","Juan Santamaria Day","CR",2018 +"2018-05-01","International Workers' Day","CR",2018 +"2018-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2018 +"2018-08-02","Feast of Our Lady of the Angels","CR",2018 +"2018-08-15","Mother's Day","CR",2018 +"2018-09-15","Independence Day","CR",2018 +"2018-10-15","Cultures Day (Observed)","CR",2018 +"2018-12-25","Christmas Day","CR",2018 +"2019-01-01","New Year's Day","CR",2019 +"2019-04-11","Juan Santamaria Day","CR",2019 +"2019-04-18","Maundy Thursday","CR",2019 +"2019-04-19","Good Friday","CR",2019 +"2019-05-01","International Workers' Day","CR",2019 +"2019-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2019 +"2019-08-02","Feast of Our Lady of the Angels","CR",2019 +"2019-08-15","Mother's Day","CR",2019 +"2019-09-15","Independence Day","CR",2019 +"2019-10-12","Cultures Day","CR",2019 +"2019-12-25","Christmas Day","CR",2019 +"2020-01-01","New Year's Day","CR",2020 +"2020-04-09","Maundy Thursday","CR",2020 +"2020-04-10","Good Friday","CR",2020 +"2020-04-11","Juan Santamaria Day","CR",2020 +"2020-05-01","International Workers' Day","CR",2020 +"2020-07-27","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2020 +"2020-08-02","Feast of Our Lady of the Angels","CR",2020 +"2020-08-17","Mother's Day (Observed)","CR",2020 +"2020-09-14","Independence Day (Observed)","CR",2020 +"2020-11-30","Army Abolition Day (Observed)","CR",2020 +"2020-12-25","Christmas Day","CR",2020 +"2021-01-01","New Year's Day","CR",2021 +"2021-04-01","Maundy Thursday","CR",2021 +"2021-04-02","Good Friday","CR",2021 +"2021-04-11","Juan Santamaria Day","CR",2021 +"2021-05-03","International Workers' Day (Observed)","CR",2021 +"2021-07-26","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2021 +"2021-08-02","Feast of Our Lady of the Angels","CR",2021 +"2021-08-15","Mother's Day","CR",2021 +"2021-09-13","Independence Day (Observed)","CR",2021 +"2021-11-29","Army Abolition Day (Observed)","CR",2021 +"2021-12-25","Christmas Day","CR",2021 +"2022-01-01","New Year's Day","CR",2022 +"2022-04-11","Juan Santamaria Day","CR",2022 +"2022-04-14","Maundy Thursday","CR",2022 +"2022-04-15","Good Friday","CR",2022 +"2022-05-01","International Workers' Day","CR",2022 +"2022-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2022 +"2022-08-02","Feast of Our Lady of the Angels","CR",2022 +"2022-08-15","Mother's Day","CR",2022 +"2022-09-04","Day of the Black Person and Afro-Costa Rican Culture (Observed)","CR",2022 +"2022-09-19","Independence Day (Observed)","CR",2022 +"2022-12-05","Army Abolition Day (Observed)","CR",2022 +"2022-12-25","Christmas Day","CR",2022 +"2023-01-01","New Year's Day","CR",2023 +"2023-04-06","Maundy Thursday","CR",2023 +"2023-04-07","Good Friday","CR",2023 +"2023-04-10","Juan Santamaria Day (Observed)","CR",2023 +"2023-05-01","International Workers' Day","CR",2023 +"2023-07-24","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2023 +"2023-08-02","Feast of Our Lady of the Angels","CR",2023 +"2023-08-14","Mother's Day (Observed)","CR",2023 +"2023-09-03","Day of the Black Person and Afro-Costa Rican Culture (Observed)","CR",2023 +"2023-09-15","Independence Day","CR",2023 +"2023-12-01","Army Abolition Day","CR",2023 +"2023-12-25","Christmas Day","CR",2023 +"2024-01-01","New Year's Day","CR",2024 +"2024-03-28","Maundy Thursday","CR",2024 +"2024-03-29","Good Friday","CR",2024 +"2024-04-15","Juan Santamaria Day (Observed)","CR",2024 +"2024-05-01","International Workers' Day","CR",2024 +"2024-07-29","Annexation of the Party of Nicoya to Costa Rica (Observed)","CR",2024 +"2024-08-02","Feast of Our Lady of the Angels","CR",2024 +"2024-08-19","Mother's Day (Observed)","CR",2024 +"2024-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2024 +"2024-09-16","Independence Day (Observed)","CR",2024 +"2024-12-01","Army Abolition Day","CR",2024 +"2024-12-25","Christmas Day","CR",2024 +"2025-01-01","New Year's Day","CR",2025 +"2025-04-11","Juan Santamaria Day","CR",2025 +"2025-04-17","Maundy Thursday","CR",2025 +"2025-04-18","Good Friday","CR",2025 +"2025-05-01","International Workers' Day","CR",2025 +"2025-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2025 +"2025-08-02","Feast of Our Lady of the Angels","CR",2025 +"2025-08-15","Mother's Day","CR",2025 +"2025-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2025 +"2025-09-15","Independence Day","CR",2025 +"2025-12-01","Army Abolition Day","CR",2025 +"2025-12-25","Christmas Day","CR",2025 +"2026-01-01","New Year's Day","CR",2026 +"2026-04-02","Maundy Thursday","CR",2026 +"2026-04-03","Good Friday","CR",2026 +"2026-04-11","Juan Santamaria Day","CR",2026 +"2026-05-01","International Workers' Day","CR",2026 +"2026-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2026 +"2026-08-02","Feast of Our Lady of the Angels","CR",2026 +"2026-08-15","Mother's Day","CR",2026 +"2026-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2026 +"2026-09-15","Independence Day","CR",2026 +"2026-12-01","Army Abolition Day","CR",2026 +"2026-12-25","Christmas Day","CR",2026 +"2027-01-01","New Year's Day","CR",2027 +"2027-03-25","Maundy Thursday","CR",2027 +"2027-03-26","Good Friday","CR",2027 +"2027-04-11","Juan Santamaria Day","CR",2027 +"2027-05-01","International Workers' Day","CR",2027 +"2027-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2027 +"2027-08-02","Feast of Our Lady of the Angels","CR",2027 +"2027-08-15","Mother's Day","CR",2027 +"2027-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2027 +"2027-09-15","Independence Day","CR",2027 +"2027-12-01","Army Abolition Day","CR",2027 +"2027-12-25","Christmas Day","CR",2027 +"2028-01-01","New Year's Day","CR",2028 +"2028-04-11","Juan Santamaria Day","CR",2028 +"2028-04-13","Maundy Thursday","CR",2028 +"2028-04-14","Good Friday","CR",2028 +"2028-05-01","International Workers' Day","CR",2028 +"2028-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2028 +"2028-08-02","Feast of Our Lady of the Angels","CR",2028 +"2028-08-15","Mother's Day","CR",2028 +"2028-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2028 +"2028-09-15","Independence Day","CR",2028 +"2028-12-01","Army Abolition Day","CR",2028 +"2028-12-25","Christmas Day","CR",2028 +"2029-01-01","New Year's Day","CR",2029 +"2029-03-29","Maundy Thursday","CR",2029 +"2029-03-30","Good Friday","CR",2029 +"2029-04-11","Juan Santamaria Day","CR",2029 +"2029-05-01","International Workers' Day","CR",2029 +"2029-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2029 +"2029-08-02","Feast of Our Lady of the Angels","CR",2029 +"2029-08-15","Mother's Day","CR",2029 +"2029-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2029 +"2029-09-15","Independence Day","CR",2029 +"2029-12-01","Army Abolition Day","CR",2029 +"2029-12-25","Christmas Day","CR",2029 +"2030-01-01","New Year's Day","CR",2030 +"2030-04-11","Juan Santamaria Day","CR",2030 +"2030-04-18","Maundy Thursday","CR",2030 +"2030-04-19","Good Friday","CR",2030 +"2030-05-01","International Workers' Day","CR",2030 +"2030-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2030 +"2030-08-02","Feast of Our Lady of the Angels","CR",2030 +"2030-08-15","Mother's Day","CR",2030 +"2030-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2030 +"2030-09-15","Independence Day","CR",2030 +"2030-12-01","Army Abolition Day","CR",2030 +"2030-12-25","Christmas Day","CR",2030 +"2031-01-01","New Year's Day","CR",2031 +"2031-04-10","Maundy Thursday","CR",2031 +"2031-04-11","Good Friday","CR",2031 +"2031-04-11","Juan Santamaria Day","CR",2031 +"2031-05-01","International Workers' Day","CR",2031 +"2031-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2031 +"2031-08-02","Feast of Our Lady of the Angels","CR",2031 +"2031-08-15","Mother's Day","CR",2031 +"2031-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2031 +"2031-09-15","Independence Day","CR",2031 +"2031-12-01","Army Abolition Day","CR",2031 +"2031-12-25","Christmas Day","CR",2031 +"2032-01-01","New Year's Day","CR",2032 +"2032-03-25","Maundy Thursday","CR",2032 +"2032-03-26","Good Friday","CR",2032 +"2032-04-11","Juan Santamaria Day","CR",2032 +"2032-05-01","International Workers' Day","CR",2032 +"2032-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2032 +"2032-08-02","Feast of Our Lady of the Angels","CR",2032 +"2032-08-15","Mother's Day","CR",2032 +"2032-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2032 +"2032-09-15","Independence Day","CR",2032 +"2032-12-01","Army Abolition Day","CR",2032 +"2032-12-25","Christmas Day","CR",2032 +"2033-01-01","New Year's Day","CR",2033 +"2033-04-11","Juan Santamaria Day","CR",2033 +"2033-04-14","Maundy Thursday","CR",2033 +"2033-04-15","Good Friday","CR",2033 +"2033-05-01","International Workers' Day","CR",2033 +"2033-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2033 +"2033-08-02","Feast of Our Lady of the Angels","CR",2033 +"2033-08-15","Mother's Day","CR",2033 +"2033-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2033 +"2033-09-15","Independence Day","CR",2033 +"2033-12-01","Army Abolition Day","CR",2033 +"2033-12-25","Christmas Day","CR",2033 +"2034-01-01","New Year's Day","CR",2034 +"2034-04-06","Maundy Thursday","CR",2034 +"2034-04-07","Good Friday","CR",2034 +"2034-04-11","Juan Santamaria Day","CR",2034 +"2034-05-01","International Workers' Day","CR",2034 +"2034-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2034 +"2034-08-02","Feast of Our Lady of the Angels","CR",2034 +"2034-08-15","Mother's Day","CR",2034 +"2034-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2034 +"2034-09-15","Independence Day","CR",2034 +"2034-12-01","Army Abolition Day","CR",2034 +"2034-12-25","Christmas Day","CR",2034 +"2035-01-01","New Year's Day","CR",2035 +"2035-03-22","Maundy Thursday","CR",2035 +"2035-03-23","Good Friday","CR",2035 +"2035-04-11","Juan Santamaria Day","CR",2035 +"2035-05-01","International Workers' Day","CR",2035 +"2035-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2035 +"2035-08-02","Feast of Our Lady of the Angels","CR",2035 +"2035-08-15","Mother's Day","CR",2035 +"2035-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2035 +"2035-09-15","Independence Day","CR",2035 +"2035-12-01","Army Abolition Day","CR",2035 +"2035-12-25","Christmas Day","CR",2035 +"2036-01-01","New Year's Day","CR",2036 +"2036-04-10","Maundy Thursday","CR",2036 +"2036-04-11","Good Friday","CR",2036 +"2036-04-11","Juan Santamaria Day","CR",2036 +"2036-05-01","International Workers' Day","CR",2036 +"2036-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2036 +"2036-08-02","Feast of Our Lady of the Angels","CR",2036 +"2036-08-15","Mother's Day","CR",2036 +"2036-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2036 +"2036-09-15","Independence Day","CR",2036 +"2036-12-01","Army Abolition Day","CR",2036 +"2036-12-25","Christmas Day","CR",2036 +"2037-01-01","New Year's Day","CR",2037 +"2037-04-02","Maundy Thursday","CR",2037 +"2037-04-03","Good Friday","CR",2037 +"2037-04-11","Juan Santamaria Day","CR",2037 +"2037-05-01","International Workers' Day","CR",2037 +"2037-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2037 +"2037-08-02","Feast of Our Lady of the Angels","CR",2037 +"2037-08-15","Mother's Day","CR",2037 +"2037-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2037 +"2037-09-15","Independence Day","CR",2037 +"2037-12-01","Army Abolition Day","CR",2037 +"2037-12-25","Christmas Day","CR",2037 +"2038-01-01","New Year's Day","CR",2038 +"2038-04-11","Juan Santamaria Day","CR",2038 +"2038-04-22","Maundy Thursday","CR",2038 +"2038-04-23","Good Friday","CR",2038 +"2038-05-01","International Workers' Day","CR",2038 +"2038-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2038 +"2038-08-02","Feast of Our Lady of the Angels","CR",2038 +"2038-08-15","Mother's Day","CR",2038 +"2038-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2038 +"2038-09-15","Independence Day","CR",2038 +"2038-12-01","Army Abolition Day","CR",2038 +"2038-12-25","Christmas Day","CR",2038 +"2039-01-01","New Year's Day","CR",2039 +"2039-04-07","Maundy Thursday","CR",2039 +"2039-04-08","Good Friday","CR",2039 +"2039-04-11","Juan Santamaria Day","CR",2039 +"2039-05-01","International Workers' Day","CR",2039 +"2039-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2039 +"2039-08-02","Feast of Our Lady of the Angels","CR",2039 +"2039-08-15","Mother's Day","CR",2039 +"2039-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2039 +"2039-09-15","Independence Day","CR",2039 +"2039-12-01","Army Abolition Day","CR",2039 +"2039-12-25","Christmas Day","CR",2039 +"2040-01-01","New Year's Day","CR",2040 +"2040-03-29","Maundy Thursday","CR",2040 +"2040-03-30","Good Friday","CR",2040 +"2040-04-11","Juan Santamaria Day","CR",2040 +"2040-05-01","International Workers' Day","CR",2040 +"2040-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2040 +"2040-08-02","Feast of Our Lady of the Angels","CR",2040 +"2040-08-15","Mother's Day","CR",2040 +"2040-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2040 +"2040-09-15","Independence Day","CR",2040 +"2040-12-01","Army Abolition Day","CR",2040 +"2040-12-25","Christmas Day","CR",2040 +"2041-01-01","New Year's Day","CR",2041 +"2041-04-11","Juan Santamaria Day","CR",2041 +"2041-04-18","Maundy Thursday","CR",2041 +"2041-04-19","Good Friday","CR",2041 +"2041-05-01","International Workers' Day","CR",2041 +"2041-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2041 +"2041-08-02","Feast of Our Lady of the Angels","CR",2041 +"2041-08-15","Mother's Day","CR",2041 +"2041-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2041 +"2041-09-15","Independence Day","CR",2041 +"2041-12-01","Army Abolition Day","CR",2041 +"2041-12-25","Christmas Day","CR",2041 +"2042-01-01","New Year's Day","CR",2042 +"2042-04-03","Maundy Thursday","CR",2042 +"2042-04-04","Good Friday","CR",2042 +"2042-04-11","Juan Santamaria Day","CR",2042 +"2042-05-01","International Workers' Day","CR",2042 +"2042-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2042 +"2042-08-02","Feast of Our Lady of the Angels","CR",2042 +"2042-08-15","Mother's Day","CR",2042 +"2042-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2042 +"2042-09-15","Independence Day","CR",2042 +"2042-12-01","Army Abolition Day","CR",2042 +"2042-12-25","Christmas Day","CR",2042 +"2043-01-01","New Year's Day","CR",2043 +"2043-03-26","Maundy Thursday","CR",2043 +"2043-03-27","Good Friday","CR",2043 +"2043-04-11","Juan Santamaria Day","CR",2043 +"2043-05-01","International Workers' Day","CR",2043 +"2043-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2043 +"2043-08-02","Feast of Our Lady of the Angels","CR",2043 +"2043-08-15","Mother's Day","CR",2043 +"2043-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2043 +"2043-09-15","Independence Day","CR",2043 +"2043-12-01","Army Abolition Day","CR",2043 +"2043-12-25","Christmas Day","CR",2043 +"2044-01-01","New Year's Day","CR",2044 +"2044-04-11","Juan Santamaria Day","CR",2044 +"2044-04-14","Maundy Thursday","CR",2044 +"2044-04-15","Good Friday","CR",2044 +"2044-05-01","International Workers' Day","CR",2044 +"2044-07-25","Annexation of the Party of Nicoya to Costa Rica","CR",2044 +"2044-08-02","Feast of Our Lady of the Angels","CR",2044 +"2044-08-15","Mother's Day","CR",2044 +"2044-08-31","Day of the Black Person and Afro-Costa Rican Culture","CR",2044 +"2044-09-15","Independence Day","CR",2044 +"2044-12-01","Army Abolition Day","CR",2044 +"2044-12-25","Christmas Day","CR",2044 +"1995-01-01","Liberation Day","CU",1995 +"1995-01-02","Liberation Day (Observed)","CU",1995 +"1995-05-01","Labour Day","CU",1995 +"1995-07-25","Commemoration of the Assault of the Moncada garrison","CU",1995 +"1995-07-26","Day of the National Rebellion","CU",1995 +"1995-07-27","Commemoration of the Assault of the Moncada garrison","CU",1995 +"1995-10-10","Independence Day","CU",1995 +"1996-01-01","Liberation Day","CU",1996 +"1996-05-01","Labour Day","CU",1996 +"1996-07-25","Commemoration of the Assault of the Moncada garrison","CU",1996 +"1996-07-26","Day of the National Rebellion","CU",1996 +"1996-07-27","Commemoration of the Assault of the Moncada garrison","CU",1996 +"1996-10-10","Independence Day","CU",1996 +"1997-01-01","Liberation Day","CU",1997 +"1997-05-01","Labour Day","CU",1997 +"1997-07-25","Commemoration of the Assault of the Moncada garrison","CU",1997 +"1997-07-26","Day of the National Rebellion","CU",1997 +"1997-07-27","Commemoration of the Assault of the Moncada garrison","CU",1997 +"1997-10-10","Independence Day","CU",1997 +"1997-12-25","Christmas Day","CU",1997 +"1998-01-01","Liberation Day","CU",1998 +"1998-05-01","Labour Day","CU",1998 +"1998-07-25","Commemoration of the Assault of the Moncada garrison","CU",1998 +"1998-07-26","Day of the National Rebellion","CU",1998 +"1998-07-27","Commemoration of the Assault of the Moncada garrison","CU",1998 +"1998-10-10","Independence Day","CU",1998 +"1998-12-25","Christmas Day","CU",1998 +"1999-01-01","Liberation Day","CU",1999 +"1999-05-01","Labour Day","CU",1999 +"1999-07-25","Commemoration of the Assault of the Moncada garrison","CU",1999 +"1999-07-26","Day of the National Rebellion","CU",1999 +"1999-07-27","Commemoration of the Assault of the Moncada garrison","CU",1999 +"1999-10-10","Independence Day","CU",1999 +"1999-10-11","Independence Day (Observed)","CU",1999 +"1999-12-25","Christmas Day","CU",1999 +"2000-01-01","Liberation Day","CU",2000 +"2000-05-01","Labour Day","CU",2000 +"2000-07-25","Commemoration of the Assault of the Moncada garrison","CU",2000 +"2000-07-26","Day of the National Rebellion","CU",2000 +"2000-07-27","Commemoration of the Assault of the Moncada garrison","CU",2000 +"2000-10-10","Independence Day","CU",2000 +"2000-12-25","Christmas Day","CU",2000 +"2001-01-01","Liberation Day","CU",2001 +"2001-05-01","Labour Day","CU",2001 +"2001-07-25","Commemoration of the Assault of the Moncada garrison","CU",2001 +"2001-07-26","Day of the National Rebellion","CU",2001 +"2001-07-27","Commemoration of the Assault of the Moncada garrison","CU",2001 +"2001-10-10","Independence Day","CU",2001 +"2001-12-25","Christmas Day","CU",2001 +"2002-01-01","Liberation Day","CU",2002 +"2002-05-01","Labour Day","CU",2002 +"2002-07-25","Commemoration of the Assault of the Moncada garrison","CU",2002 +"2002-07-26","Day of the National Rebellion","CU",2002 +"2002-07-27","Commemoration of the Assault of the Moncada garrison","CU",2002 +"2002-10-10","Independence Day","CU",2002 +"2002-12-25","Christmas Day","CU",2002 +"2003-01-01","Liberation Day","CU",2003 +"2003-05-01","Labour Day","CU",2003 +"2003-07-25","Commemoration of the Assault of the Moncada garrison","CU",2003 +"2003-07-26","Day of the National Rebellion","CU",2003 +"2003-07-27","Commemoration of the Assault of the Moncada garrison","CU",2003 +"2003-10-10","Independence Day","CU",2003 +"2003-12-25","Christmas Day","CU",2003 +"2004-01-01","Liberation Day","CU",2004 +"2004-05-01","Labour Day","CU",2004 +"2004-07-25","Commemoration of the Assault of the Moncada garrison","CU",2004 +"2004-07-26","Day of the National Rebellion","CU",2004 +"2004-07-27","Commemoration of the Assault of the Moncada garrison","CU",2004 +"2004-10-10","Independence Day","CU",2004 +"2004-10-11","Independence Day (Observed)","CU",2004 +"2004-12-25","Christmas Day","CU",2004 +"2005-01-01","Liberation Day","CU",2005 +"2005-05-01","Labour Day","CU",2005 +"2005-05-02","Labour Day (Observed)","CU",2005 +"2005-07-25","Commemoration of the Assault of the Moncada garrison","CU",2005 +"2005-07-26","Day of the National Rebellion","CU",2005 +"2005-07-27","Commemoration of the Assault of the Moncada garrison","CU",2005 +"2005-10-10","Independence Day","CU",2005 +"2005-12-25","Christmas Day","CU",2005 +"2006-01-01","Liberation Day","CU",2006 +"2006-01-02","Liberation Day (Observed)","CU",2006 +"2006-05-01","Labour Day","CU",2006 +"2006-07-25","Commemoration of the Assault of the Moncada garrison","CU",2006 +"2006-07-26","Day of the National Rebellion","CU",2006 +"2006-07-27","Commemoration of the Assault of the Moncada garrison","CU",2006 +"2006-10-10","Independence Day","CU",2006 +"2006-12-25","Christmas Day","CU",2006 +"2007-01-01","Liberation Day","CU",2007 +"2007-05-01","Labour Day","CU",2007 +"2007-07-25","Commemoration of the Assault of the Moncada garrison","CU",2007 +"2007-07-26","Day of the National Rebellion","CU",2007 +"2007-07-27","Commemoration of the Assault of the Moncada garrison","CU",2007 +"2007-10-10","Independence Day","CU",2007 +"2007-12-25","Christmas Day","CU",2007 +"2007-12-31","New Year's Eve","CU",2007 +"2008-01-01","Liberation Day","CU",2008 +"2008-01-02","Victory Day","CU",2008 +"2008-05-01","Labour Day","CU",2008 +"2008-07-25","Commemoration of the Assault of the Moncada garrison","CU",2008 +"2008-07-26","Day of the National Rebellion","CU",2008 +"2008-07-27","Commemoration of the Assault of the Moncada garrison","CU",2008 +"2008-10-10","Independence Day","CU",2008 +"2008-12-25","Christmas Day","CU",2008 +"2008-12-31","New Year's Eve","CU",2008 +"2009-01-01","Liberation Day","CU",2009 +"2009-01-02","Victory Day","CU",2009 +"2009-05-01","Labour Day","CU",2009 +"2009-07-25","Commemoration of the Assault of the Moncada garrison","CU",2009 +"2009-07-26","Day of the National Rebellion","CU",2009 +"2009-07-27","Commemoration of the Assault of the Moncada garrison","CU",2009 +"2009-10-10","Independence Day","CU",2009 +"2009-12-25","Christmas Day","CU",2009 +"2009-12-31","New Year's Eve","CU",2009 +"2010-01-01","Liberation Day","CU",2010 +"2010-01-02","Victory Day","CU",2010 +"2010-05-01","Labour Day","CU",2010 +"2010-07-25","Commemoration of the Assault of the Moncada garrison","CU",2010 +"2010-07-26","Day of the National Rebellion","CU",2010 +"2010-07-27","Commemoration of the Assault of the Moncada garrison","CU",2010 +"2010-10-10","Independence Day","CU",2010 +"2010-10-11","Independence Day (Observed)","CU",2010 +"2010-12-25","Christmas Day","CU",2010 +"2010-12-31","New Year's Eve","CU",2010 +"2011-01-01","Liberation Day","CU",2011 +"2011-01-02","Victory Day","CU",2011 +"2011-05-01","Labour Day","CU",2011 +"2011-05-02","Labour Day (Observed)","CU",2011 +"2011-07-25","Commemoration of the Assault of the Moncada garrison","CU",2011 +"2011-07-26","Day of the National Rebellion","CU",2011 +"2011-07-27","Commemoration of the Assault of the Moncada garrison","CU",2011 +"2011-10-10","Independence Day","CU",2011 +"2011-12-25","Christmas Day","CU",2011 +"2011-12-31","New Year's Eve","CU",2011 +"2012-01-01","Liberation Day","CU",2012 +"2012-01-02","Liberation Day (Observed)","CU",2012 +"2012-01-02","Victory Day","CU",2012 +"2012-04-06","Good Friday","CU",2012 +"2012-05-01","Labour Day","CU",2012 +"2012-07-25","Commemoration of the Assault of the Moncada garrison","CU",2012 +"2012-07-26","Day of the National Rebellion","CU",2012 +"2012-07-27","Commemoration of the Assault of the Moncada garrison","CU",2012 +"2012-10-10","Independence Day","CU",2012 +"2012-12-25","Christmas Day","CU",2012 +"2012-12-31","New Year's Eve","CU",2012 +"2013-01-01","Liberation Day","CU",2013 +"2013-01-02","Victory Day","CU",2013 +"2013-03-29","Good Friday","CU",2013 +"2013-05-01","Labour Day","CU",2013 +"2013-07-25","Commemoration of the Assault of the Moncada garrison","CU",2013 +"2013-07-26","Day of the National Rebellion","CU",2013 +"2013-07-27","Commemoration of the Assault of the Moncada garrison","CU",2013 +"2013-10-10","Independence Day","CU",2013 +"2013-12-25","Christmas Day","CU",2013 +"2013-12-31","New Year's Eve","CU",2013 +"2014-01-01","Liberation Day","CU",2014 +"2014-01-02","Victory Day","CU",2014 +"2014-04-18","Good Friday","CU",2014 +"2014-05-01","Labour Day","CU",2014 +"2014-07-25","Commemoration of the Assault of the Moncada garrison","CU",2014 +"2014-07-26","Day of the National Rebellion","CU",2014 +"2014-07-27","Commemoration of the Assault of the Moncada garrison","CU",2014 +"2014-10-10","Independence Day","CU",2014 +"2014-12-25","Christmas Day","CU",2014 +"2014-12-31","New Year's Eve","CU",2014 +"2015-01-01","Liberation Day","CU",2015 +"2015-01-02","Victory Day","CU",2015 +"2015-04-03","Good Friday","CU",2015 +"2015-05-01","Labour Day","CU",2015 +"2015-07-25","Commemoration of the Assault of the Moncada garrison","CU",2015 +"2015-07-26","Day of the National Rebellion","CU",2015 +"2015-07-27","Commemoration of the Assault of the Moncada garrison","CU",2015 +"2015-10-10","Independence Day","CU",2015 +"2015-12-25","Christmas Day","CU",2015 +"2015-12-31","New Year's Eve","CU",2015 +"2016-01-01","Liberation Day","CU",2016 +"2016-01-02","Victory Day","CU",2016 +"2016-03-25","Good Friday","CU",2016 +"2016-05-01","Labour Day","CU",2016 +"2016-05-02","Labour Day (Observed)","CU",2016 +"2016-07-25","Commemoration of the Assault of the Moncada garrison","CU",2016 +"2016-07-26","Day of the National Rebellion","CU",2016 +"2016-07-27","Commemoration of the Assault of the Moncada garrison","CU",2016 +"2016-10-10","Independence Day","CU",2016 +"2016-12-25","Christmas Day","CU",2016 +"2016-12-31","New Year's Eve","CU",2016 +"2017-01-01","Liberation Day","CU",2017 +"2017-01-02","Victory Day","CU",2017 +"2017-04-14","Good Friday","CU",2017 +"2017-05-01","Labour Day","CU",2017 +"2017-07-25","Commemoration of the Assault of the Moncada garrison","CU",2017 +"2017-07-26","Day of the National Rebellion","CU",2017 +"2017-07-27","Commemoration of the Assault of the Moncada garrison","CU",2017 +"2017-10-10","Independence Day","CU",2017 +"2017-12-25","Christmas Day","CU",2017 +"2017-12-31","New Year's Eve","CU",2017 +"2018-01-01","Liberation Day","CU",2018 +"2018-01-02","Victory Day","CU",2018 +"2018-03-30","Good Friday","CU",2018 +"2018-05-01","Labour Day","CU",2018 +"2018-07-25","Commemoration of the Assault of the Moncada garrison","CU",2018 +"2018-07-26","Day of the National Rebellion","CU",2018 +"2018-07-27","Commemoration of the Assault of the Moncada garrison","CU",2018 +"2018-10-10","Independence Day","CU",2018 +"2018-12-25","Christmas Day","CU",2018 +"2018-12-31","New Year's Eve","CU",2018 +"2019-01-01","Liberation Day","CU",2019 +"2019-01-02","Victory Day","CU",2019 +"2019-04-19","Good Friday","CU",2019 +"2019-05-01","Labour Day","CU",2019 +"2019-07-25","Commemoration of the Assault of the Moncada garrison","CU",2019 +"2019-07-26","Day of the National Rebellion","CU",2019 +"2019-07-27","Commemoration of the Assault of the Moncada garrison","CU",2019 +"2019-10-10","Independence Day","CU",2019 +"2019-12-25","Christmas Day","CU",2019 +"2019-12-31","New Year's Eve","CU",2019 +"2020-01-01","Liberation Day","CU",2020 +"2020-01-02","Victory Day","CU",2020 +"2020-04-10","Good Friday","CU",2020 +"2020-05-01","Labour Day","CU",2020 +"2020-07-25","Commemoration of the Assault of the Moncada garrison","CU",2020 +"2020-07-26","Day of the National Rebellion","CU",2020 +"2020-07-27","Commemoration of the Assault of the Moncada garrison","CU",2020 +"2020-10-10","Independence Day","CU",2020 +"2020-12-25","Christmas Day","CU",2020 +"2020-12-31","New Year's Eve","CU",2020 +"2021-01-01","Liberation Day","CU",2021 +"2021-01-02","Victory Day","CU",2021 +"2021-04-02","Good Friday","CU",2021 +"2021-05-01","Labour Day","CU",2021 +"2021-07-25","Commemoration of the Assault of the Moncada garrison","CU",2021 +"2021-07-26","Day of the National Rebellion","CU",2021 +"2021-07-27","Commemoration of the Assault of the Moncada garrison","CU",2021 +"2021-10-10","Independence Day","CU",2021 +"2021-10-11","Independence Day (Observed)","CU",2021 +"2021-12-25","Christmas Day","CU",2021 +"2021-12-31","New Year's Eve","CU",2021 +"2022-01-01","Liberation Day","CU",2022 +"2022-01-02","Victory Day","CU",2022 +"2022-04-15","Good Friday","CU",2022 +"2022-05-01","Labour Day","CU",2022 +"2022-05-02","Labour Day (Observed)","CU",2022 +"2022-07-25","Commemoration of the Assault of the Moncada garrison","CU",2022 +"2022-07-26","Day of the National Rebellion","CU",2022 +"2022-07-27","Commemoration of the Assault of the Moncada garrison","CU",2022 +"2022-10-10","Independence Day","CU",2022 +"2022-12-25","Christmas Day","CU",2022 +"2022-12-31","New Year's Eve","CU",2022 +"2023-01-01","Liberation Day","CU",2023 +"2023-01-02","Victory Day","CU",2023 +"2023-04-07","Good Friday","CU",2023 +"2023-05-01","Labour Day","CU",2023 +"2023-07-25","Commemoration of the Assault of the Moncada garrison","CU",2023 +"2023-07-26","Day of the National Rebellion","CU",2023 +"2023-07-27","Commemoration of the Assault of the Moncada garrison","CU",2023 +"2023-10-10","Independence Day","CU",2023 +"2023-12-25","Christmas Day","CU",2023 +"2023-12-31","New Year's Eve","CU",2023 +"2024-01-01","Liberation Day","CU",2024 +"2024-01-02","Victory Day","CU",2024 +"2024-03-29","Good Friday","CU",2024 +"2024-05-01","Labour Day","CU",2024 +"2024-07-25","Commemoration of the Assault of the Moncada garrison","CU",2024 +"2024-07-26","Day of the National Rebellion","CU",2024 +"2024-07-27","Commemoration of the Assault of the Moncada garrison","CU",2024 +"2024-10-10","Independence Day","CU",2024 +"2024-12-25","Christmas Day","CU",2024 +"2024-12-31","New Year's Eve","CU",2024 +"2025-01-01","Liberation Day","CU",2025 +"2025-01-02","Victory Day","CU",2025 +"2025-04-18","Good Friday","CU",2025 +"2025-05-01","Labour Day","CU",2025 +"2025-07-25","Commemoration of the Assault of the Moncada garrison","CU",2025 +"2025-07-26","Day of the National Rebellion","CU",2025 +"2025-07-27","Commemoration of the Assault of the Moncada garrison","CU",2025 +"2025-10-10","Independence Day","CU",2025 +"2025-12-25","Christmas Day","CU",2025 +"2025-12-31","New Year's Eve","CU",2025 +"2026-01-01","Liberation Day","CU",2026 +"2026-01-02","Victory Day","CU",2026 +"2026-04-03","Good Friday","CU",2026 +"2026-05-01","Labour Day","CU",2026 +"2026-07-25","Commemoration of the Assault of the Moncada garrison","CU",2026 +"2026-07-26","Day of the National Rebellion","CU",2026 +"2026-07-27","Commemoration of the Assault of the Moncada garrison","CU",2026 +"2026-10-10","Independence Day","CU",2026 +"2026-12-25","Christmas Day","CU",2026 +"2026-12-31","New Year's Eve","CU",2026 +"2027-01-01","Liberation Day","CU",2027 +"2027-01-02","Victory Day","CU",2027 +"2027-03-26","Good Friday","CU",2027 +"2027-05-01","Labour Day","CU",2027 +"2027-07-25","Commemoration of the Assault of the Moncada garrison","CU",2027 +"2027-07-26","Day of the National Rebellion","CU",2027 +"2027-07-27","Commemoration of the Assault of the Moncada garrison","CU",2027 +"2027-10-10","Independence Day","CU",2027 +"2027-10-11","Independence Day (Observed)","CU",2027 +"2027-12-25","Christmas Day","CU",2027 +"2027-12-31","New Year's Eve","CU",2027 +"2028-01-01","Liberation Day","CU",2028 +"2028-01-02","Victory Day","CU",2028 +"2028-04-14","Good Friday","CU",2028 +"2028-05-01","Labour Day","CU",2028 +"2028-07-25","Commemoration of the Assault of the Moncada garrison","CU",2028 +"2028-07-26","Day of the National Rebellion","CU",2028 +"2028-07-27","Commemoration of the Assault of the Moncada garrison","CU",2028 +"2028-10-10","Independence Day","CU",2028 +"2028-12-25","Christmas Day","CU",2028 +"2028-12-31","New Year's Eve","CU",2028 +"2029-01-01","Liberation Day","CU",2029 +"2029-01-02","Victory Day","CU",2029 +"2029-03-30","Good Friday","CU",2029 +"2029-05-01","Labour Day","CU",2029 +"2029-07-25","Commemoration of the Assault of the Moncada garrison","CU",2029 +"2029-07-26","Day of the National Rebellion","CU",2029 +"2029-07-27","Commemoration of the Assault of the Moncada garrison","CU",2029 +"2029-10-10","Independence Day","CU",2029 +"2029-12-25","Christmas Day","CU",2029 +"2029-12-31","New Year's Eve","CU",2029 +"2030-01-01","Liberation Day","CU",2030 +"2030-01-02","Victory Day","CU",2030 +"2030-04-19","Good Friday","CU",2030 +"2030-05-01","Labour Day","CU",2030 +"2030-07-25","Commemoration of the Assault of the Moncada garrison","CU",2030 +"2030-07-26","Day of the National Rebellion","CU",2030 +"2030-07-27","Commemoration of the Assault of the Moncada garrison","CU",2030 +"2030-10-10","Independence Day","CU",2030 +"2030-12-25","Christmas Day","CU",2030 +"2030-12-31","New Year's Eve","CU",2030 +"2031-01-01","Liberation Day","CU",2031 +"2031-01-02","Victory Day","CU",2031 +"2031-04-11","Good Friday","CU",2031 +"2031-05-01","Labour Day","CU",2031 +"2031-07-25","Commemoration of the Assault of the Moncada garrison","CU",2031 +"2031-07-26","Day of the National Rebellion","CU",2031 +"2031-07-27","Commemoration of the Assault of the Moncada garrison","CU",2031 +"2031-10-10","Independence Day","CU",2031 +"2031-12-25","Christmas Day","CU",2031 +"2031-12-31","New Year's Eve","CU",2031 +"2032-01-01","Liberation Day","CU",2032 +"2032-01-02","Victory Day","CU",2032 +"2032-03-26","Good Friday","CU",2032 +"2032-05-01","Labour Day","CU",2032 +"2032-07-25","Commemoration of the Assault of the Moncada garrison","CU",2032 +"2032-07-26","Day of the National Rebellion","CU",2032 +"2032-07-27","Commemoration of the Assault of the Moncada garrison","CU",2032 +"2032-10-10","Independence Day","CU",2032 +"2032-10-11","Independence Day (Observed)","CU",2032 +"2032-12-25","Christmas Day","CU",2032 +"2032-12-31","New Year's Eve","CU",2032 +"2033-01-01","Liberation Day","CU",2033 +"2033-01-02","Victory Day","CU",2033 +"2033-04-15","Good Friday","CU",2033 +"2033-05-01","Labour Day","CU",2033 +"2033-05-02","Labour Day (Observed)","CU",2033 +"2033-07-25","Commemoration of the Assault of the Moncada garrison","CU",2033 +"2033-07-26","Day of the National Rebellion","CU",2033 +"2033-07-27","Commemoration of the Assault of the Moncada garrison","CU",2033 +"2033-10-10","Independence Day","CU",2033 +"2033-12-25","Christmas Day","CU",2033 +"2033-12-31","New Year's Eve","CU",2033 +"2034-01-01","Liberation Day","CU",2034 +"2034-01-02","Victory Day","CU",2034 +"2034-04-07","Good Friday","CU",2034 +"2034-05-01","Labour Day","CU",2034 +"2034-07-25","Commemoration of the Assault of the Moncada garrison","CU",2034 +"2034-07-26","Day of the National Rebellion","CU",2034 +"2034-07-27","Commemoration of the Assault of the Moncada garrison","CU",2034 +"2034-10-10","Independence Day","CU",2034 +"2034-12-25","Christmas Day","CU",2034 +"2034-12-31","New Year's Eve","CU",2034 +"2035-01-01","Liberation Day","CU",2035 +"2035-01-02","Victory Day","CU",2035 +"2035-03-23","Good Friday","CU",2035 +"2035-05-01","Labour Day","CU",2035 +"2035-07-25","Commemoration of the Assault of the Moncada garrison","CU",2035 +"2035-07-26","Day of the National Rebellion","CU",2035 +"2035-07-27","Commemoration of the Assault of the Moncada garrison","CU",2035 +"2035-10-10","Independence Day","CU",2035 +"2035-12-25","Christmas Day","CU",2035 +"2035-12-31","New Year's Eve","CU",2035 +"2036-01-01","Liberation Day","CU",2036 +"2036-01-02","Victory Day","CU",2036 +"2036-04-11","Good Friday","CU",2036 +"2036-05-01","Labour Day","CU",2036 +"2036-07-25","Commemoration of the Assault of the Moncada garrison","CU",2036 +"2036-07-26","Day of the National Rebellion","CU",2036 +"2036-07-27","Commemoration of the Assault of the Moncada garrison","CU",2036 +"2036-10-10","Independence Day","CU",2036 +"2036-12-25","Christmas Day","CU",2036 +"2036-12-31","New Year's Eve","CU",2036 +"2037-01-01","Liberation Day","CU",2037 +"2037-01-02","Victory Day","CU",2037 +"2037-04-03","Good Friday","CU",2037 +"2037-05-01","Labour Day","CU",2037 +"2037-07-25","Commemoration of the Assault of the Moncada garrison","CU",2037 +"2037-07-26","Day of the National Rebellion","CU",2037 +"2037-07-27","Commemoration of the Assault of the Moncada garrison","CU",2037 +"2037-10-10","Independence Day","CU",2037 +"2037-12-25","Christmas Day","CU",2037 +"2037-12-31","New Year's Eve","CU",2037 +"2038-01-01","Liberation Day","CU",2038 +"2038-01-02","Victory Day","CU",2038 +"2038-04-23","Good Friday","CU",2038 +"2038-05-01","Labour Day","CU",2038 +"2038-07-25","Commemoration of the Assault of the Moncada garrison","CU",2038 +"2038-07-26","Day of the National Rebellion","CU",2038 +"2038-07-27","Commemoration of the Assault of the Moncada garrison","CU",2038 +"2038-10-10","Independence Day","CU",2038 +"2038-10-11","Independence Day (Observed)","CU",2038 +"2038-12-25","Christmas Day","CU",2038 +"2038-12-31","New Year's Eve","CU",2038 +"2039-01-01","Liberation Day","CU",2039 +"2039-01-02","Victory Day","CU",2039 +"2039-04-08","Good Friday","CU",2039 +"2039-05-01","Labour Day","CU",2039 +"2039-05-02","Labour Day (Observed)","CU",2039 +"2039-07-25","Commemoration of the Assault of the Moncada garrison","CU",2039 +"2039-07-26","Day of the National Rebellion","CU",2039 +"2039-07-27","Commemoration of the Assault of the Moncada garrison","CU",2039 +"2039-10-10","Independence Day","CU",2039 +"2039-12-25","Christmas Day","CU",2039 +"2039-12-31","New Year's Eve","CU",2039 +"2040-01-01","Liberation Day","CU",2040 +"2040-01-02","Victory Day","CU",2040 +"2040-03-30","Good Friday","CU",2040 +"2040-05-01","Labour Day","CU",2040 +"2040-07-25","Commemoration of the Assault of the Moncada garrison","CU",2040 +"2040-07-26","Day of the National Rebellion","CU",2040 +"2040-07-27","Commemoration of the Assault of the Moncada garrison","CU",2040 +"2040-10-10","Independence Day","CU",2040 +"2040-12-25","Christmas Day","CU",2040 +"2040-12-31","New Year's Eve","CU",2040 +"2041-01-01","Liberation Day","CU",2041 +"2041-01-02","Victory Day","CU",2041 +"2041-04-19","Good Friday","CU",2041 +"2041-05-01","Labour Day","CU",2041 +"2041-07-25","Commemoration of the Assault of the Moncada garrison","CU",2041 +"2041-07-26","Day of the National Rebellion","CU",2041 +"2041-07-27","Commemoration of the Assault of the Moncada garrison","CU",2041 +"2041-10-10","Independence Day","CU",2041 +"2041-12-25","Christmas Day","CU",2041 +"2041-12-31","New Year's Eve","CU",2041 +"2042-01-01","Liberation Day","CU",2042 +"2042-01-02","Victory Day","CU",2042 +"2042-04-04","Good Friday","CU",2042 +"2042-05-01","Labour Day","CU",2042 +"2042-07-25","Commemoration of the Assault of the Moncada garrison","CU",2042 +"2042-07-26","Day of the National Rebellion","CU",2042 +"2042-07-27","Commemoration of the Assault of the Moncada garrison","CU",2042 +"2042-10-10","Independence Day","CU",2042 +"2042-12-25","Christmas Day","CU",2042 +"2042-12-31","New Year's Eve","CU",2042 +"2043-01-01","Liberation Day","CU",2043 +"2043-01-02","Victory Day","CU",2043 +"2043-03-27","Good Friday","CU",2043 +"2043-05-01","Labour Day","CU",2043 +"2043-07-25","Commemoration of the Assault of the Moncada garrison","CU",2043 +"2043-07-26","Day of the National Rebellion","CU",2043 +"2043-07-27","Commemoration of the Assault of the Moncada garrison","CU",2043 +"2043-10-10","Independence Day","CU",2043 +"2043-12-25","Christmas Day","CU",2043 +"2043-12-31","New Year's Eve","CU",2043 +"2044-01-01","Liberation Day","CU",2044 +"2044-01-02","Victory Day","CU",2044 +"2044-04-15","Good Friday","CU",2044 +"2044-05-01","Labour Day","CU",2044 +"2044-05-02","Labour Day (Observed)","CU",2044 +"2044-07-25","Commemoration of the Assault of the Moncada garrison","CU",2044 +"2044-07-26","Day of the National Rebellion","CU",2044 +"2044-07-27","Commemoration of the Assault of the Moncada garrison","CU",2044 +"2044-10-10","Independence Day","CU",2044 +"2044-12-25","Christmas Day","CU",2044 +"2044-12-31","New Year's Eve","CU",2044 +"1995-01-01","Nieuwjaarsdag [New Year's Day]","CW",1995 +"1995-02-27","Maandag na de Grote Karnaval [Carnaval Monday]","CW",1995 +"1995-04-14","Goede Vrijdag [Good Friday]","CW",1995 +"1995-04-17","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",1995 +"1995-04-29","Anja di La Reina [Queen's Day]","CW",1995 +"1995-05-01","Dia di Obrero [Labour Day]","CW",1995 +"1995-05-25","Hemelvaartsdag [Ascension Day]","CW",1995 +"1995-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",1995 +"1995-10-10","Dia di Pais Korsou [Curacao Day]","CW",1995 +"1995-12-25","Kerstdag [Christmas]","CW",1995 +"1995-12-26","2de Kerstdag [Second Christmas]","CW",1995 +"1996-01-01","Nieuwjaarsdag [New Year's Day]","CW",1996 +"1996-02-19","Maandag na de Grote Karnaval [Carnaval Monday]","CW",1996 +"1996-04-05","Goede Vrijdag [Good Friday]","CW",1996 +"1996-04-08","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",1996 +"1996-04-30","Anja di La Reina [Queen's Day]","CW",1996 +"1996-05-01","Dia di Obrero [Labour Day]","CW",1996 +"1996-05-16","Hemelvaartsdag [Ascension Day]","CW",1996 +"1996-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",1996 +"1996-10-10","Dia di Pais Korsou [Curacao Day]","CW",1996 +"1996-12-25","Kerstdag [Christmas]","CW",1996 +"1996-12-26","2de Kerstdag [Second Christmas]","CW",1996 +"1997-01-01","Nieuwjaarsdag [New Year's Day]","CW",1997 +"1997-02-10","Maandag na de Grote Karnaval [Carnaval Monday]","CW",1997 +"1997-03-28","Goede Vrijdag [Good Friday]","CW",1997 +"1997-03-31","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",1997 +"1997-04-30","Anja di La Reina [Queen's Day]","CW",1997 +"1997-05-01","Dia di Obrero [Labour Day]","CW",1997 +"1997-05-08","Hemelvaartsdag [Ascension Day]","CW",1997 +"1997-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",1997 +"1997-10-10","Dia di Pais Korsou [Curacao Day]","CW",1997 +"1997-12-25","Kerstdag [Christmas]","CW",1997 +"1997-12-26","2de Kerstdag [Second Christmas]","CW",1997 +"1998-01-01","Nieuwjaarsdag [New Year's Day]","CW",1998 +"1998-02-23","Maandag na de Grote Karnaval [Carnaval Monday]","CW",1998 +"1998-04-10","Goede Vrijdag [Good Friday]","CW",1998 +"1998-04-13","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",1998 +"1998-04-30","Anja di La Reina [Queen's Day]","CW",1998 +"1998-05-01","Dia di Obrero [Labour Day]","CW",1998 +"1998-05-21","Hemelvaartsdag [Ascension Day]","CW",1998 +"1998-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",1998 +"1998-10-10","Dia di Pais Korsou [Curacao Day]","CW",1998 +"1998-12-25","Kerstdag [Christmas]","CW",1998 +"1998-12-26","2de Kerstdag [Second Christmas]","CW",1998 +"1999-01-01","Nieuwjaarsdag [New Year's Day]","CW",1999 +"1999-02-15","Maandag na de Grote Karnaval [Carnaval Monday]","CW",1999 +"1999-04-02","Goede Vrijdag [Good Friday]","CW",1999 +"1999-04-05","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",1999 +"1999-04-30","Anja di La Reina [Queen's Day]","CW",1999 +"1999-05-01","Dia di Obrero [Labour Day]","CW",1999 +"1999-05-13","Hemelvaartsdag [Ascension Day]","CW",1999 +"1999-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",1999 +"1999-10-10","Dia di Pais Korsou [Curacao Day]","CW",1999 +"1999-12-25","Kerstdag [Christmas]","CW",1999 +"1999-12-26","2de Kerstdag [Second Christmas]","CW",1999 +"2000-01-01","Nieuwjaarsdag [New Year's Day]","CW",2000 +"2000-03-06","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2000 +"2000-04-21","Goede Vrijdag [Good Friday]","CW",2000 +"2000-04-24","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2000 +"2000-04-29","Anja di La Reina [Queen's Day]","CW",2000 +"2000-05-01","Dia di Obrero [Labour Day]","CW",2000 +"2000-06-01","Hemelvaartsdag [Ascension Day]","CW",2000 +"2000-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2000 +"2000-10-10","Dia di Pais Korsou [Curacao Day]","CW",2000 +"2000-12-25","Kerstdag [Christmas]","CW",2000 +"2000-12-26","2de Kerstdag [Second Christmas]","CW",2000 +"2001-01-01","Nieuwjaarsdag [New Year's Day]","CW",2001 +"2001-02-26","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2001 +"2001-04-13","Goede Vrijdag [Good Friday]","CW",2001 +"2001-04-16","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2001 +"2001-04-30","Anja di La Reina [Queen's Day]","CW",2001 +"2001-05-01","Dia di Obrero [Labour Day]","CW",2001 +"2001-05-24","Hemelvaartsdag [Ascension Day]","CW",2001 +"2001-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2001 +"2001-10-10","Dia di Pais Korsou [Curacao Day]","CW",2001 +"2001-12-25","Kerstdag [Christmas]","CW",2001 +"2001-12-26","2de Kerstdag [Second Christmas]","CW",2001 +"2002-01-01","Nieuwjaarsdag [New Year's Day]","CW",2002 +"2002-02-11","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2002 +"2002-03-29","Goede Vrijdag [Good Friday]","CW",2002 +"2002-04-01","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2002 +"2002-04-30","Anja di La Reina [Queen's Day]","CW",2002 +"2002-05-01","Dia di Obrero [Labour Day]","CW",2002 +"2002-05-09","Hemelvaartsdag [Ascension Day]","CW",2002 +"2002-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2002 +"2002-10-10","Dia di Pais Korsou [Curacao Day]","CW",2002 +"2002-12-25","Kerstdag [Christmas]","CW",2002 +"2002-12-26","2de Kerstdag [Second Christmas]","CW",2002 +"2003-01-01","Nieuwjaarsdag [New Year's Day]","CW",2003 +"2003-03-03","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2003 +"2003-04-18","Goede Vrijdag [Good Friday]","CW",2003 +"2003-04-21","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2003 +"2003-04-30","Anja di La Reina [Queen's Day]","CW",2003 +"2003-05-01","Dia di Obrero [Labour Day]","CW",2003 +"2003-05-29","Hemelvaartsdag [Ascension Day]","CW",2003 +"2003-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2003 +"2003-10-10","Dia di Pais Korsou [Curacao Day]","CW",2003 +"2003-12-25","Kerstdag [Christmas]","CW",2003 +"2003-12-26","2de Kerstdag [Second Christmas]","CW",2003 +"2004-01-01","Nieuwjaarsdag [New Year's Day]","CW",2004 +"2004-02-23","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2004 +"2004-04-09","Goede Vrijdag [Good Friday]","CW",2004 +"2004-04-12","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2004 +"2004-04-30","Anja di La Reina [Queen's Day]","CW",2004 +"2004-05-01","Dia di Obrero [Labour Day]","CW",2004 +"2004-05-20","Hemelvaartsdag [Ascension Day]","CW",2004 +"2004-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2004 +"2004-10-10","Dia di Pais Korsou [Curacao Day]","CW",2004 +"2004-12-25","Kerstdag [Christmas]","CW",2004 +"2004-12-26","2de Kerstdag [Second Christmas]","CW",2004 +"2005-01-01","Nieuwjaarsdag [New Year's Day]","CW",2005 +"2005-02-07","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2005 +"2005-03-25","Goede Vrijdag [Good Friday]","CW",2005 +"2005-03-28","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2005 +"2005-04-30","Anja di La Reina [Queen's Day]","CW",2005 +"2005-05-02","Dia di Obrero [Labour Day]","CW",2005 +"2005-05-05","Hemelvaartsdag [Ascension Day]","CW",2005 +"2005-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2005 +"2005-10-10","Dia di Pais Korsou [Curacao Day]","CW",2005 +"2005-12-25","Kerstdag [Christmas]","CW",2005 +"2005-12-26","2de Kerstdag [Second Christmas]","CW",2005 +"2006-01-01","Nieuwjaarsdag [New Year's Day]","CW",2006 +"2006-02-27","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2006 +"2006-04-14","Goede Vrijdag [Good Friday]","CW",2006 +"2006-04-17","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2006 +"2006-04-29","Anja di La Reina [Queen's Day]","CW",2006 +"2006-05-01","Dia di Obrero [Labour Day]","CW",2006 +"2006-05-25","Hemelvaartsdag [Ascension Day]","CW",2006 +"2006-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2006 +"2006-10-10","Dia di Pais Korsou [Curacao Day]","CW",2006 +"2006-12-25","Kerstdag [Christmas]","CW",2006 +"2006-12-26","2de Kerstdag [Second Christmas]","CW",2006 +"2007-01-01","Nieuwjaarsdag [New Year's Day]","CW",2007 +"2007-02-19","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2007 +"2007-04-06","Goede Vrijdag [Good Friday]","CW",2007 +"2007-04-09","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2007 +"2007-04-30","Anja di La Reina [Queen's Day]","CW",2007 +"2007-05-01","Dia di Obrero [Labour Day]","CW",2007 +"2007-05-17","Hemelvaartsdag [Ascension Day]","CW",2007 +"2007-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2007 +"2007-10-10","Dia di Pais Korsou [Curacao Day]","CW",2007 +"2007-12-25","Kerstdag [Christmas]","CW",2007 +"2007-12-26","2de Kerstdag [Second Christmas]","CW",2007 +"2008-01-01","Nieuwjaarsdag [New Year's Day]","CW",2008 +"2008-02-04","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2008 +"2008-03-21","Goede Vrijdag [Good Friday]","CW",2008 +"2008-03-24","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2008 +"2008-04-30","Anja di La Reina [Queen's Day]","CW",2008 +"2008-05-01","Dia di Obrero [Labour Day]","CW",2008 +"2008-05-01","Hemelvaartsdag [Ascension Day]","CW",2008 +"2008-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2008 +"2008-10-10","Dia di Pais Korsou [Curacao Day]","CW",2008 +"2008-12-25","Kerstdag [Christmas]","CW",2008 +"2008-12-26","2de Kerstdag [Second Christmas]","CW",2008 +"2009-01-01","Nieuwjaarsdag [New Year's Day]","CW",2009 +"2009-02-23","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2009 +"2009-04-10","Goede Vrijdag [Good Friday]","CW",2009 +"2009-04-13","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2009 +"2009-04-30","Anja di La Reina [Queen's Day]","CW",2009 +"2009-05-01","Dia di Obrero [Labour Day]","CW",2009 +"2009-05-21","Hemelvaartsdag [Ascension Day]","CW",2009 +"2009-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2009 +"2009-10-10","Dia di Pais Korsou [Curacao Day]","CW",2009 +"2009-12-25","Kerstdag [Christmas]","CW",2009 +"2009-12-26","2de Kerstdag [Second Christmas]","CW",2009 +"2010-01-01","Nieuwjaarsdag [New Year's Day]","CW",2010 +"2010-02-15","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2010 +"2010-04-02","Goede Vrijdag [Good Friday]","CW",2010 +"2010-04-05","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2010 +"2010-04-30","Anja di La Reina [Queen's Day]","CW",2010 +"2010-05-01","Dia di Obrero [Labour Day]","CW",2010 +"2010-05-13","Hemelvaartsdag [Ascension Day]","CW",2010 +"2010-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2010 +"2010-10-10","Dia di Pais Korsou [Curacao Day]","CW",2010 +"2010-12-25","Kerstdag [Christmas]","CW",2010 +"2010-12-26","2de Kerstdag [Second Christmas]","CW",2010 +"2011-01-01","Nieuwjaarsdag [New Year's Day]","CW",2011 +"2011-03-07","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2011 +"2011-04-22","Goede Vrijdag [Good Friday]","CW",2011 +"2011-04-25","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2011 +"2011-04-30","Anja di La Reina [Queen's Day]","CW",2011 +"2011-05-02","Dia di Obrero [Labour Day]","CW",2011 +"2011-06-02","Hemelvaartsdag [Ascension Day]","CW",2011 +"2011-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2011 +"2011-10-10","Dia di Pais Korsou [Curacao Day]","CW",2011 +"2011-12-25","Kerstdag [Christmas]","CW",2011 +"2011-12-26","2de Kerstdag [Second Christmas]","CW",2011 +"2012-01-01","Nieuwjaarsdag [New Year's Day]","CW",2012 +"2012-02-20","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2012 +"2012-04-06","Goede Vrijdag [Good Friday]","CW",2012 +"2012-04-09","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2012 +"2012-04-30","Anja di La Reina [Queen's Day]","CW",2012 +"2012-05-01","Dia di Obrero [Labour Day]","CW",2012 +"2012-05-17","Hemelvaartsdag [Ascension Day]","CW",2012 +"2012-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2012 +"2012-10-10","Dia di Pais Korsou [Curacao Day]","CW",2012 +"2012-12-25","Kerstdag [Christmas]","CW",2012 +"2012-12-26","2de Kerstdag [Second Christmas]","CW",2012 +"2013-01-01","Nieuwjaarsdag [New Year's Day]","CW",2013 +"2013-02-11","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2013 +"2013-03-29","Goede Vrijdag [Good Friday]","CW",2013 +"2013-04-01","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2013 +"2013-04-30","Anja di La Reina [Queen's Day]","CW",2013 +"2013-05-01","Dia di Obrero [Labour Day]","CW",2013 +"2013-05-09","Hemelvaartsdag [Ascension Day]","CW",2013 +"2013-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2013 +"2013-10-10","Dia di Pais Korsou [Curacao Day]","CW",2013 +"2013-12-25","Kerstdag [Christmas]","CW",2013 +"2013-12-26","2de Kerstdag [Second Christmas]","CW",2013 +"2014-01-01","Nieuwjaarsdag [New Year's Day]","CW",2014 +"2014-03-03","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2014 +"2014-04-18","Goede Vrijdag [Good Friday]","CW",2014 +"2014-04-21","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2014 +"2014-04-26","Koningsdag [King's Day]","CW",2014 +"2014-05-01","Dia di Obrero [Labour Day]","CW",2014 +"2014-05-29","Hemelvaartsdag [Ascension Day]","CW",2014 +"2014-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2014 +"2014-10-10","Dia di Pais Korsou [Curacao Day]","CW",2014 +"2014-12-25","Kerstdag [Christmas]","CW",2014 +"2014-12-26","2de Kerstdag [Second Christmas]","CW",2014 +"2015-01-01","Nieuwjaarsdag [New Year's Day]","CW",2015 +"2015-02-16","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2015 +"2015-04-03","Goede Vrijdag [Good Friday]","CW",2015 +"2015-04-06","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2015 +"2015-04-27","Koningsdag [King's Day]","CW",2015 +"2015-05-01","Dia di Obrero [Labour Day]","CW",2015 +"2015-05-14","Hemelvaartsdag [Ascension Day]","CW",2015 +"2015-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2015 +"2015-10-10","Dia di Pais Korsou [Curacao Day]","CW",2015 +"2015-12-25","Kerstdag [Christmas]","CW",2015 +"2015-12-26","2de Kerstdag [Second Christmas]","CW",2015 +"2016-01-01","Nieuwjaarsdag [New Year's Day]","CW",2016 +"2016-02-08","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2016 +"2016-03-25","Goede Vrijdag [Good Friday]","CW",2016 +"2016-03-28","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2016 +"2016-04-27","Koningsdag [King's Day]","CW",2016 +"2016-05-02","Dia di Obrero [Labour Day]","CW",2016 +"2016-05-05","Hemelvaartsdag [Ascension Day]","CW",2016 +"2016-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2016 +"2016-10-10","Dia di Pais Korsou [Curacao Day]","CW",2016 +"2016-12-25","Kerstdag [Christmas]","CW",2016 +"2016-12-26","2de Kerstdag [Second Christmas]","CW",2016 +"2017-01-01","Nieuwjaarsdag [New Year's Day]","CW",2017 +"2017-02-27","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2017 +"2017-04-14","Goede Vrijdag [Good Friday]","CW",2017 +"2017-04-17","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2017 +"2017-04-27","Koningsdag [King's Day]","CW",2017 +"2017-05-01","Dia di Obrero [Labour Day]","CW",2017 +"2017-05-25","Hemelvaartsdag [Ascension Day]","CW",2017 +"2017-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2017 +"2017-10-10","Dia di Pais Korsou [Curacao Day]","CW",2017 +"2017-12-25","Kerstdag [Christmas]","CW",2017 +"2017-12-26","2de Kerstdag [Second Christmas]","CW",2017 +"2018-01-01","Nieuwjaarsdag [New Year's Day]","CW",2018 +"2018-02-12","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2018 +"2018-03-30","Goede Vrijdag [Good Friday]","CW",2018 +"2018-04-02","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2018 +"2018-04-27","Koningsdag [King's Day]","CW",2018 +"2018-05-01","Dia di Obrero [Labour Day]","CW",2018 +"2018-05-10","Hemelvaartsdag [Ascension Day]","CW",2018 +"2018-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2018 +"2018-10-10","Dia di Pais Korsou [Curacao Day]","CW",2018 +"2018-12-25","Kerstdag [Christmas]","CW",2018 +"2018-12-26","2de Kerstdag [Second Christmas]","CW",2018 +"2019-01-01","Nieuwjaarsdag [New Year's Day]","CW",2019 +"2019-03-04","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2019 +"2019-04-19","Goede Vrijdag [Good Friday]","CW",2019 +"2019-04-22","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2019 +"2019-04-27","Koningsdag [King's Day]","CW",2019 +"2019-05-01","Dia di Obrero [Labour Day]","CW",2019 +"2019-05-30","Hemelvaartsdag [Ascension Day]","CW",2019 +"2019-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2019 +"2019-10-10","Dia di Pais Korsou [Curacao Day]","CW",2019 +"2019-12-25","Kerstdag [Christmas]","CW",2019 +"2019-12-26","2de Kerstdag [Second Christmas]","CW",2019 +"2020-01-01","Nieuwjaarsdag [New Year's Day]","CW",2020 +"2020-02-24","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2020 +"2020-04-10","Goede Vrijdag [Good Friday]","CW",2020 +"2020-04-13","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2020 +"2020-04-27","Koningsdag [King's Day]","CW",2020 +"2020-05-01","Dia di Obrero [Labour Day]","CW",2020 +"2020-05-21","Hemelvaartsdag [Ascension Day]","CW",2020 +"2020-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2020 +"2020-10-10","Dia di Pais Korsou [Curacao Day]","CW",2020 +"2020-12-25","Kerstdag [Christmas]","CW",2020 +"2020-12-26","2de Kerstdag [Second Christmas]","CW",2020 +"2021-01-01","Nieuwjaarsdag [New Year's Day]","CW",2021 +"2021-02-15","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2021 +"2021-04-02","Goede Vrijdag [Good Friday]","CW",2021 +"2021-04-05","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2021 +"2021-04-27","Koningsdag [King's Day]","CW",2021 +"2021-05-01","Dia di Obrero [Labour Day]","CW",2021 +"2021-05-13","Hemelvaartsdag [Ascension Day]","CW",2021 +"2021-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2021 +"2021-10-10","Dia di Pais Korsou [Curacao Day]","CW",2021 +"2021-12-25","Kerstdag [Christmas]","CW",2021 +"2021-12-26","2de Kerstdag [Second Christmas]","CW",2021 +"2022-01-01","Nieuwjaarsdag [New Year's Day]","CW",2022 +"2022-02-28","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2022 +"2022-04-15","Goede Vrijdag [Good Friday]","CW",2022 +"2022-04-18","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2022 +"2022-04-27","Koningsdag [King's Day]","CW",2022 +"2022-05-02","Dia di Obrero [Labour Day]","CW",2022 +"2022-05-26","Hemelvaartsdag [Ascension Day]","CW",2022 +"2022-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2022 +"2022-10-10","Dia di Pais Korsou [Curacao Day]","CW",2022 +"2022-12-25","Kerstdag [Christmas]","CW",2022 +"2022-12-26","2de Kerstdag [Second Christmas]","CW",2022 +"2023-01-01","Nieuwjaarsdag [New Year's Day]","CW",2023 +"2023-02-20","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2023 +"2023-04-07","Goede Vrijdag [Good Friday]","CW",2023 +"2023-04-10","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2023 +"2023-04-27","Koningsdag [King's Day]","CW",2023 +"2023-05-01","Dia di Obrero [Labour Day]","CW",2023 +"2023-05-18","Hemelvaartsdag [Ascension Day]","CW",2023 +"2023-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2023 +"2023-10-10","Dia di Pais Korsou [Curacao Day]","CW",2023 +"2023-12-25","Kerstdag [Christmas]","CW",2023 +"2023-12-26","2de Kerstdag [Second Christmas]","CW",2023 +"2024-01-01","Nieuwjaarsdag [New Year's Day]","CW",2024 +"2024-02-12","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2024 +"2024-03-29","Goede Vrijdag [Good Friday]","CW",2024 +"2024-04-01","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2024 +"2024-04-27","Koningsdag [King's Day]","CW",2024 +"2024-05-01","Dia di Obrero [Labour Day]","CW",2024 +"2024-05-09","Hemelvaartsdag [Ascension Day]","CW",2024 +"2024-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2024 +"2024-10-10","Dia di Pais Korsou [Curacao Day]","CW",2024 +"2024-12-25","Kerstdag [Christmas]","CW",2024 +"2024-12-26","2de Kerstdag [Second Christmas]","CW",2024 +"2025-01-01","Nieuwjaarsdag [New Year's Day]","CW",2025 +"2025-03-03","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2025 +"2025-04-18","Goede Vrijdag [Good Friday]","CW",2025 +"2025-04-21","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2025 +"2025-04-26","Koningsdag [King's Day]","CW",2025 +"2025-05-01","Dia di Obrero [Labour Day]","CW",2025 +"2025-05-29","Hemelvaartsdag [Ascension Day]","CW",2025 +"2025-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2025 +"2025-10-10","Dia di Pais Korsou [Curacao Day]","CW",2025 +"2025-12-25","Kerstdag [Christmas]","CW",2025 +"2025-12-26","2de Kerstdag [Second Christmas]","CW",2025 +"2026-01-01","Nieuwjaarsdag [New Year's Day]","CW",2026 +"2026-02-16","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2026 +"2026-04-03","Goede Vrijdag [Good Friday]","CW",2026 +"2026-04-06","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2026 +"2026-04-27","Koningsdag [King's Day]","CW",2026 +"2026-05-01","Dia di Obrero [Labour Day]","CW",2026 +"2026-05-14","Hemelvaartsdag [Ascension Day]","CW",2026 +"2026-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2026 +"2026-10-10","Dia di Pais Korsou [Curacao Day]","CW",2026 +"2026-12-25","Kerstdag [Christmas]","CW",2026 +"2026-12-26","2de Kerstdag [Second Christmas]","CW",2026 +"2027-01-01","Nieuwjaarsdag [New Year's Day]","CW",2027 +"2027-02-08","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2027 +"2027-03-26","Goede Vrijdag [Good Friday]","CW",2027 +"2027-03-29","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2027 +"2027-04-27","Koningsdag [King's Day]","CW",2027 +"2027-05-01","Dia di Obrero [Labour Day]","CW",2027 +"2027-05-06","Hemelvaartsdag [Ascension Day]","CW",2027 +"2027-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2027 +"2027-10-10","Dia di Pais Korsou [Curacao Day]","CW",2027 +"2027-12-25","Kerstdag [Christmas]","CW",2027 +"2027-12-26","2de Kerstdag [Second Christmas]","CW",2027 +"2028-01-01","Nieuwjaarsdag [New Year's Day]","CW",2028 +"2028-02-28","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2028 +"2028-04-14","Goede Vrijdag [Good Friday]","CW",2028 +"2028-04-17","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2028 +"2028-04-27","Koningsdag [King's Day]","CW",2028 +"2028-05-01","Dia di Obrero [Labour Day]","CW",2028 +"2028-05-25","Hemelvaartsdag [Ascension Day]","CW",2028 +"2028-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2028 +"2028-10-10","Dia di Pais Korsou [Curacao Day]","CW",2028 +"2028-12-25","Kerstdag [Christmas]","CW",2028 +"2028-12-26","2de Kerstdag [Second Christmas]","CW",2028 +"2029-01-01","Nieuwjaarsdag [New Year's Day]","CW",2029 +"2029-02-12","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2029 +"2029-03-30","Goede Vrijdag [Good Friday]","CW",2029 +"2029-04-02","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2029 +"2029-04-27","Koningsdag [King's Day]","CW",2029 +"2029-05-01","Dia di Obrero [Labour Day]","CW",2029 +"2029-05-10","Hemelvaartsdag [Ascension Day]","CW",2029 +"2029-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2029 +"2029-10-10","Dia di Pais Korsou [Curacao Day]","CW",2029 +"2029-12-25","Kerstdag [Christmas]","CW",2029 +"2029-12-26","2de Kerstdag [Second Christmas]","CW",2029 +"2030-01-01","Nieuwjaarsdag [New Year's Day]","CW",2030 +"2030-03-04","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2030 +"2030-04-19","Goede Vrijdag [Good Friday]","CW",2030 +"2030-04-22","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2030 +"2030-04-27","Koningsdag [King's Day]","CW",2030 +"2030-05-01","Dia di Obrero [Labour Day]","CW",2030 +"2030-05-30","Hemelvaartsdag [Ascension Day]","CW",2030 +"2030-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2030 +"2030-10-10","Dia di Pais Korsou [Curacao Day]","CW",2030 +"2030-12-25","Kerstdag [Christmas]","CW",2030 +"2030-12-26","2de Kerstdag [Second Christmas]","CW",2030 +"2031-01-01","Nieuwjaarsdag [New Year's Day]","CW",2031 +"2031-02-24","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2031 +"2031-04-11","Goede Vrijdag [Good Friday]","CW",2031 +"2031-04-14","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2031 +"2031-04-26","Koningsdag [King's Day]","CW",2031 +"2031-05-01","Dia di Obrero [Labour Day]","CW",2031 +"2031-05-22","Hemelvaartsdag [Ascension Day]","CW",2031 +"2031-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2031 +"2031-10-10","Dia di Pais Korsou [Curacao Day]","CW",2031 +"2031-12-25","Kerstdag [Christmas]","CW",2031 +"2031-12-26","2de Kerstdag [Second Christmas]","CW",2031 +"2032-01-01","Nieuwjaarsdag [New Year's Day]","CW",2032 +"2032-02-09","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2032 +"2032-03-26","Goede Vrijdag [Good Friday]","CW",2032 +"2032-03-29","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2032 +"2032-04-27","Koningsdag [King's Day]","CW",2032 +"2032-05-01","Dia di Obrero [Labour Day]","CW",2032 +"2032-05-06","Hemelvaartsdag [Ascension Day]","CW",2032 +"2032-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2032 +"2032-10-10","Dia di Pais Korsou [Curacao Day]","CW",2032 +"2032-12-25","Kerstdag [Christmas]","CW",2032 +"2032-12-26","2de Kerstdag [Second Christmas]","CW",2032 +"2033-01-01","Nieuwjaarsdag [New Year's Day]","CW",2033 +"2033-02-28","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2033 +"2033-04-15","Goede Vrijdag [Good Friday]","CW",2033 +"2033-04-18","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2033 +"2033-04-27","Koningsdag [King's Day]","CW",2033 +"2033-05-02","Dia di Obrero [Labour Day]","CW",2033 +"2033-05-26","Hemelvaartsdag [Ascension Day]","CW",2033 +"2033-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2033 +"2033-10-10","Dia di Pais Korsou [Curacao Day]","CW",2033 +"2033-12-25","Kerstdag [Christmas]","CW",2033 +"2033-12-26","2de Kerstdag [Second Christmas]","CW",2033 +"2034-01-01","Nieuwjaarsdag [New Year's Day]","CW",2034 +"2034-02-20","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2034 +"2034-04-07","Goede Vrijdag [Good Friday]","CW",2034 +"2034-04-10","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2034 +"2034-04-27","Koningsdag [King's Day]","CW",2034 +"2034-05-01","Dia di Obrero [Labour Day]","CW",2034 +"2034-05-18","Hemelvaartsdag [Ascension Day]","CW",2034 +"2034-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2034 +"2034-10-10","Dia di Pais Korsou [Curacao Day]","CW",2034 +"2034-12-25","Kerstdag [Christmas]","CW",2034 +"2034-12-26","2de Kerstdag [Second Christmas]","CW",2034 +"2035-01-01","Nieuwjaarsdag [New Year's Day]","CW",2035 +"2035-02-05","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2035 +"2035-03-23","Goede Vrijdag [Good Friday]","CW",2035 +"2035-03-26","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2035 +"2035-04-27","Koningsdag [King's Day]","CW",2035 +"2035-05-01","Dia di Obrero [Labour Day]","CW",2035 +"2035-05-03","Hemelvaartsdag [Ascension Day]","CW",2035 +"2035-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2035 +"2035-10-10","Dia di Pais Korsou [Curacao Day]","CW",2035 +"2035-12-25","Kerstdag [Christmas]","CW",2035 +"2035-12-26","2de Kerstdag [Second Christmas]","CW",2035 +"2036-01-01","Nieuwjaarsdag [New Year's Day]","CW",2036 +"2036-02-25","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2036 +"2036-04-11","Goede Vrijdag [Good Friday]","CW",2036 +"2036-04-14","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2036 +"2036-04-26","Koningsdag [King's Day]","CW",2036 +"2036-05-01","Dia di Obrero [Labour Day]","CW",2036 +"2036-05-22","Hemelvaartsdag [Ascension Day]","CW",2036 +"2036-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2036 +"2036-10-10","Dia di Pais Korsou [Curacao Day]","CW",2036 +"2036-12-25","Kerstdag [Christmas]","CW",2036 +"2036-12-26","2de Kerstdag [Second Christmas]","CW",2036 +"2037-01-01","Nieuwjaarsdag [New Year's Day]","CW",2037 +"2037-02-16","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2037 +"2037-04-03","Goede Vrijdag [Good Friday]","CW",2037 +"2037-04-06","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2037 +"2037-04-27","Koningsdag [King's Day]","CW",2037 +"2037-05-01","Dia di Obrero [Labour Day]","CW",2037 +"2037-05-14","Hemelvaartsdag [Ascension Day]","CW",2037 +"2037-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2037 +"2037-10-10","Dia di Pais Korsou [Curacao Day]","CW",2037 +"2037-12-25","Kerstdag [Christmas]","CW",2037 +"2037-12-26","2de Kerstdag [Second Christmas]","CW",2037 +"2038-01-01","Nieuwjaarsdag [New Year's Day]","CW",2038 +"2038-03-08","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2038 +"2038-04-23","Goede Vrijdag [Good Friday]","CW",2038 +"2038-04-26","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2038 +"2038-04-27","Koningsdag [King's Day]","CW",2038 +"2038-05-01","Dia di Obrero [Labour Day]","CW",2038 +"2038-06-03","Hemelvaartsdag [Ascension Day]","CW",2038 +"2038-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2038 +"2038-10-10","Dia di Pais Korsou [Curacao Day]","CW",2038 +"2038-12-25","Kerstdag [Christmas]","CW",2038 +"2038-12-26","2de Kerstdag [Second Christmas]","CW",2038 +"2039-01-01","Nieuwjaarsdag [New Year's Day]","CW",2039 +"2039-02-21","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2039 +"2039-04-08","Goede Vrijdag [Good Friday]","CW",2039 +"2039-04-11","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2039 +"2039-04-27","Koningsdag [King's Day]","CW",2039 +"2039-05-02","Dia di Obrero [Labour Day]","CW",2039 +"2039-05-19","Hemelvaartsdag [Ascension Day]","CW",2039 +"2039-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2039 +"2039-10-10","Dia di Pais Korsou [Curacao Day]","CW",2039 +"2039-12-25","Kerstdag [Christmas]","CW",2039 +"2039-12-26","2de Kerstdag [Second Christmas]","CW",2039 +"2040-01-01","Nieuwjaarsdag [New Year's Day]","CW",2040 +"2040-02-13","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2040 +"2040-03-30","Goede Vrijdag [Good Friday]","CW",2040 +"2040-04-02","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2040 +"2040-04-27","Koningsdag [King's Day]","CW",2040 +"2040-05-01","Dia di Obrero [Labour Day]","CW",2040 +"2040-05-10","Hemelvaartsdag [Ascension Day]","CW",2040 +"2040-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2040 +"2040-10-10","Dia di Pais Korsou [Curacao Day]","CW",2040 +"2040-12-25","Kerstdag [Christmas]","CW",2040 +"2040-12-26","2de Kerstdag [Second Christmas]","CW",2040 +"2041-01-01","Nieuwjaarsdag [New Year's Day]","CW",2041 +"2041-03-04","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2041 +"2041-04-19","Goede Vrijdag [Good Friday]","CW",2041 +"2041-04-22","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2041 +"2041-04-27","Koningsdag [King's Day]","CW",2041 +"2041-05-01","Dia di Obrero [Labour Day]","CW",2041 +"2041-05-30","Hemelvaartsdag [Ascension Day]","CW",2041 +"2041-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2041 +"2041-10-10","Dia di Pais Korsou [Curacao Day]","CW",2041 +"2041-12-25","Kerstdag [Christmas]","CW",2041 +"2041-12-26","2de Kerstdag [Second Christmas]","CW",2041 +"2042-01-01","Nieuwjaarsdag [New Year's Day]","CW",2042 +"2042-02-17","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2042 +"2042-04-04","Goede Vrijdag [Good Friday]","CW",2042 +"2042-04-07","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2042 +"2042-04-26","Koningsdag [King's Day]","CW",2042 +"2042-05-01","Dia di Obrero [Labour Day]","CW",2042 +"2042-05-15","Hemelvaartsdag [Ascension Day]","CW",2042 +"2042-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2042 +"2042-10-10","Dia di Pais Korsou [Curacao Day]","CW",2042 +"2042-12-25","Kerstdag [Christmas]","CW",2042 +"2042-12-26","2de Kerstdag [Second Christmas]","CW",2042 +"2043-01-01","Nieuwjaarsdag [New Year's Day]","CW",2043 +"2043-02-09","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2043 +"2043-03-27","Goede Vrijdag [Good Friday]","CW",2043 +"2043-03-30","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2043 +"2043-04-27","Koningsdag [King's Day]","CW",2043 +"2043-05-01","Dia di Obrero [Labour Day]","CW",2043 +"2043-05-07","Hemelvaartsdag [Ascension Day]","CW",2043 +"2043-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2043 +"2043-10-10","Dia di Pais Korsou [Curacao Day]","CW",2043 +"2043-12-25","Kerstdag [Christmas]","CW",2043 +"2043-12-26","2de Kerstdag [Second Christmas]","CW",2043 +"2044-01-01","Nieuwjaarsdag [New Year's Day]","CW",2044 +"2044-02-29","Maandag na de Grote Karnaval [Carnaval Monday]","CW",2044 +"2044-04-15","Goede Vrijdag [Good Friday]","CW",2044 +"2044-04-18","Di Dos Dia di Pasku di Resureccion [Easter Monday]","CW",2044 +"2044-04-27","Koningsdag [King's Day]","CW",2044 +"2044-05-02","Dia di Obrero [Labour Day]","CW",2044 +"2044-05-26","Hemelvaartsdag [Ascension Day]","CW",2044 +"2044-07-02","Dia di Himno y Bandera [National Anthem & Flag Day]","CW",2044 +"2044-10-10","Dia di Pais Korsou [Curacao Day]","CW",2044 +"2044-12-25","Kerstdag [Christmas]","CW",2044 +"2044-12-26","2de Kerstdag [Second Christmas]","CW",2044 +"1995-01-01","New Year's Day","CY",1995 +"1995-01-06","Epiphany","CY",1995 +"1995-03-06","Clean Monday","CY",1995 +"1995-03-25","Greek Independence Day","CY",1995 +"1995-04-01","Cyprus National Day","CY",1995 +"1995-04-21","Good Friday","CY",1995 +"1995-04-23","Easter Sunday","CY",1995 +"1995-04-24","Easter Monday","CY",1995 +"1995-05-01","Labor Day","CY",1995 +"1995-06-12","Monday of the Holy Spirit","CY",1995 +"1995-08-15","Assumption of Mary","CY",1995 +"1995-10-01","Cyprus Independence Day","CY",1995 +"1995-10-28","Ochi Day","CY",1995 +"1995-12-24","Christmas Eve","CY",1995 +"1995-12-25","Christmas Day","CY",1995 +"1995-12-26","Day After Christmas","CY",1995 +"1996-01-01","New Year's Day","CY",1996 +"1996-01-06","Epiphany","CY",1996 +"1996-02-26","Clean Monday","CY",1996 +"1996-03-25","Greek Independence Day","CY",1996 +"1996-04-01","Cyprus National Day","CY",1996 +"1996-04-12","Good Friday","CY",1996 +"1996-04-14","Easter Sunday","CY",1996 +"1996-04-15","Easter Monday","CY",1996 +"1996-05-01","Labor Day","CY",1996 +"1996-06-03","Monday of the Holy Spirit","CY",1996 +"1996-08-15","Assumption of Mary","CY",1996 +"1996-10-01","Cyprus Independence Day","CY",1996 +"1996-10-28","Ochi Day","CY",1996 +"1996-12-24","Christmas Eve","CY",1996 +"1996-12-25","Christmas Day","CY",1996 +"1996-12-26","Day After Christmas","CY",1996 +"1997-01-01","New Year's Day","CY",1997 +"1997-01-06","Epiphany","CY",1997 +"1997-03-10","Clean Monday","CY",1997 +"1997-03-25","Greek Independence Day","CY",1997 +"1997-04-01","Cyprus National Day","CY",1997 +"1997-04-25","Good Friday","CY",1997 +"1997-04-27","Easter Sunday","CY",1997 +"1997-04-28","Easter Monday","CY",1997 +"1997-05-01","Labor Day","CY",1997 +"1997-06-16","Monday of the Holy Spirit","CY",1997 +"1997-08-15","Assumption of Mary","CY",1997 +"1997-10-01","Cyprus Independence Day","CY",1997 +"1997-10-28","Ochi Day","CY",1997 +"1997-12-24","Christmas Eve","CY",1997 +"1997-12-25","Christmas Day","CY",1997 +"1997-12-26","Day After Christmas","CY",1997 +"1998-01-01","New Year's Day","CY",1998 +"1998-01-06","Epiphany","CY",1998 +"1998-03-02","Clean Monday","CY",1998 +"1998-03-25","Greek Independence Day","CY",1998 +"1998-04-01","Cyprus National Day","CY",1998 +"1998-04-17","Good Friday","CY",1998 +"1998-04-19","Easter Sunday","CY",1998 +"1998-04-20","Easter Monday","CY",1998 +"1998-05-01","Labor Day","CY",1998 +"1998-06-08","Monday of the Holy Spirit","CY",1998 +"1998-08-15","Assumption of Mary","CY",1998 +"1998-10-01","Cyprus Independence Day","CY",1998 +"1998-10-28","Ochi Day","CY",1998 +"1998-12-24","Christmas Eve","CY",1998 +"1998-12-25","Christmas Day","CY",1998 +"1998-12-26","Day After Christmas","CY",1998 +"1999-01-01","New Year's Day","CY",1999 +"1999-01-06","Epiphany","CY",1999 +"1999-02-22","Clean Monday","CY",1999 +"1999-03-25","Greek Independence Day","CY",1999 +"1999-04-01","Cyprus National Day","CY",1999 +"1999-04-09","Good Friday","CY",1999 +"1999-04-11","Easter Sunday","CY",1999 +"1999-04-12","Easter Monday","CY",1999 +"1999-05-01","Labor Day","CY",1999 +"1999-05-31","Monday of the Holy Spirit","CY",1999 +"1999-08-15","Assumption of Mary","CY",1999 +"1999-10-01","Cyprus Independence Day","CY",1999 +"1999-10-28","Ochi Day","CY",1999 +"1999-12-24","Christmas Eve","CY",1999 +"1999-12-25","Christmas Day","CY",1999 +"1999-12-26","Day After Christmas","CY",1999 +"2000-01-01","New Year's Day","CY",2000 +"2000-01-06","Epiphany","CY",2000 +"2000-03-13","Clean Monday","CY",2000 +"2000-03-25","Greek Independence Day","CY",2000 +"2000-04-01","Cyprus National Day","CY",2000 +"2000-04-28","Good Friday","CY",2000 +"2000-04-30","Easter Sunday","CY",2000 +"2000-05-01","Easter Monday","CY",2000 +"2000-05-01","Labor Day","CY",2000 +"2000-06-19","Monday of the Holy Spirit","CY",2000 +"2000-08-15","Assumption of Mary","CY",2000 +"2000-10-01","Cyprus Independence Day","CY",2000 +"2000-10-28","Ochi Day","CY",2000 +"2000-12-24","Christmas Eve","CY",2000 +"2000-12-25","Christmas Day","CY",2000 +"2000-12-26","Day After Christmas","CY",2000 +"2001-01-01","New Year's Day","CY",2001 +"2001-01-06","Epiphany","CY",2001 +"2001-02-26","Clean Monday","CY",2001 +"2001-03-25","Greek Independence Day","CY",2001 +"2001-04-01","Cyprus National Day","CY",2001 +"2001-04-13","Good Friday","CY",2001 +"2001-04-15","Easter Sunday","CY",2001 +"2001-04-16","Easter Monday","CY",2001 +"2001-05-01","Labor Day","CY",2001 +"2001-06-04","Monday of the Holy Spirit","CY",2001 +"2001-08-15","Assumption of Mary","CY",2001 +"2001-10-01","Cyprus Independence Day","CY",2001 +"2001-10-28","Ochi Day","CY",2001 +"2001-12-24","Christmas Eve","CY",2001 +"2001-12-25","Christmas Day","CY",2001 +"2001-12-26","Day After Christmas","CY",2001 +"2002-01-01","New Year's Day","CY",2002 +"2002-01-06","Epiphany","CY",2002 +"2002-03-18","Clean Monday","CY",2002 +"2002-03-25","Greek Independence Day","CY",2002 +"2002-04-01","Cyprus National Day","CY",2002 +"2002-05-01","Labor Day","CY",2002 +"2002-05-03","Good Friday","CY",2002 +"2002-05-05","Easter Sunday","CY",2002 +"2002-05-06","Easter Monday","CY",2002 +"2002-06-24","Monday of the Holy Spirit","CY",2002 +"2002-08-15","Assumption of Mary","CY",2002 +"2002-10-01","Cyprus Independence Day","CY",2002 +"2002-10-28","Ochi Day","CY",2002 +"2002-12-24","Christmas Eve","CY",2002 +"2002-12-25","Christmas Day","CY",2002 +"2002-12-26","Day After Christmas","CY",2002 +"2003-01-01","New Year's Day","CY",2003 +"2003-01-06","Epiphany","CY",2003 +"2003-03-10","Clean Monday","CY",2003 +"2003-03-25","Greek Independence Day","CY",2003 +"2003-04-01","Cyprus National Day","CY",2003 +"2003-04-25","Good Friday","CY",2003 +"2003-04-27","Easter Sunday","CY",2003 +"2003-04-28","Easter Monday","CY",2003 +"2003-05-01","Labor Day","CY",2003 +"2003-06-16","Monday of the Holy Spirit","CY",2003 +"2003-08-15","Assumption of Mary","CY",2003 +"2003-10-01","Cyprus Independence Day","CY",2003 +"2003-10-28","Ochi Day","CY",2003 +"2003-12-24","Christmas Eve","CY",2003 +"2003-12-25","Christmas Day","CY",2003 +"2003-12-26","Day After Christmas","CY",2003 +"2004-01-01","New Year's Day","CY",2004 +"2004-01-06","Epiphany","CY",2004 +"2004-02-23","Clean Monday","CY",2004 +"2004-03-25","Greek Independence Day","CY",2004 +"2004-04-01","Cyprus National Day","CY",2004 +"2004-04-09","Good Friday","CY",2004 +"2004-04-11","Easter Sunday","CY",2004 +"2004-04-12","Easter Monday","CY",2004 +"2004-05-01","Labor Day","CY",2004 +"2004-05-31","Monday of the Holy Spirit","CY",2004 +"2004-08-15","Assumption of Mary","CY",2004 +"2004-10-01","Cyprus Independence Day","CY",2004 +"2004-10-28","Ochi Day","CY",2004 +"2004-12-24","Christmas Eve","CY",2004 +"2004-12-25","Christmas Day","CY",2004 +"2004-12-26","Day After Christmas","CY",2004 +"2005-01-01","New Year's Day","CY",2005 +"2005-01-06","Epiphany","CY",2005 +"2005-03-14","Clean Monday","CY",2005 +"2005-03-25","Greek Independence Day","CY",2005 +"2005-04-01","Cyprus National Day","CY",2005 +"2005-04-29","Good Friday","CY",2005 +"2005-05-01","Easter Sunday","CY",2005 +"2005-05-01","Labor Day","CY",2005 +"2005-05-02","Easter Monday","CY",2005 +"2005-06-20","Monday of the Holy Spirit","CY",2005 +"2005-08-15","Assumption of Mary","CY",2005 +"2005-10-01","Cyprus Independence Day","CY",2005 +"2005-10-28","Ochi Day","CY",2005 +"2005-12-24","Christmas Eve","CY",2005 +"2005-12-25","Christmas Day","CY",2005 +"2005-12-26","Day After Christmas","CY",2005 +"2006-01-01","New Year's Day","CY",2006 +"2006-01-06","Epiphany","CY",2006 +"2006-03-06","Clean Monday","CY",2006 +"2006-03-25","Greek Independence Day","CY",2006 +"2006-04-01","Cyprus National Day","CY",2006 +"2006-04-21","Good Friday","CY",2006 +"2006-04-23","Easter Sunday","CY",2006 +"2006-04-24","Easter Monday","CY",2006 +"2006-05-01","Labor Day","CY",2006 +"2006-06-12","Monday of the Holy Spirit","CY",2006 +"2006-08-15","Assumption of Mary","CY",2006 +"2006-10-01","Cyprus Independence Day","CY",2006 +"2006-10-28","Ochi Day","CY",2006 +"2006-12-24","Christmas Eve","CY",2006 +"2006-12-25","Christmas Day","CY",2006 +"2006-12-26","Day After Christmas","CY",2006 +"2007-01-01","New Year's Day","CY",2007 +"2007-01-06","Epiphany","CY",2007 +"2007-02-19","Clean Monday","CY",2007 +"2007-03-25","Greek Independence Day","CY",2007 +"2007-04-01","Cyprus National Day","CY",2007 +"2007-04-06","Good Friday","CY",2007 +"2007-04-08","Easter Sunday","CY",2007 +"2007-04-09","Easter Monday","CY",2007 +"2007-05-01","Labor Day","CY",2007 +"2007-05-28","Monday of the Holy Spirit","CY",2007 +"2007-08-15","Assumption of Mary","CY",2007 +"2007-10-01","Cyprus Independence Day","CY",2007 +"2007-10-28","Ochi Day","CY",2007 +"2007-12-24","Christmas Eve","CY",2007 +"2007-12-25","Christmas Day","CY",2007 +"2007-12-26","Day After Christmas","CY",2007 +"2008-01-01","New Year's Day","CY",2008 +"2008-01-06","Epiphany","CY",2008 +"2008-03-10","Clean Monday","CY",2008 +"2008-03-25","Greek Independence Day","CY",2008 +"2008-04-01","Cyprus National Day","CY",2008 +"2008-04-25","Good Friday","CY",2008 +"2008-04-27","Easter Sunday","CY",2008 +"2008-04-28","Easter Monday","CY",2008 +"2008-05-01","Labor Day","CY",2008 +"2008-06-16","Monday of the Holy Spirit","CY",2008 +"2008-08-15","Assumption of Mary","CY",2008 +"2008-10-01","Cyprus Independence Day","CY",2008 +"2008-10-28","Ochi Day","CY",2008 +"2008-12-24","Christmas Eve","CY",2008 +"2008-12-25","Christmas Day","CY",2008 +"2008-12-26","Day After Christmas","CY",2008 +"2009-01-01","New Year's Day","CY",2009 +"2009-01-06","Epiphany","CY",2009 +"2009-03-02","Clean Monday","CY",2009 +"2009-03-25","Greek Independence Day","CY",2009 +"2009-04-01","Cyprus National Day","CY",2009 +"2009-04-17","Good Friday","CY",2009 +"2009-04-19","Easter Sunday","CY",2009 +"2009-04-20","Easter Monday","CY",2009 +"2009-05-01","Labor Day","CY",2009 +"2009-06-08","Monday of the Holy Spirit","CY",2009 +"2009-08-15","Assumption of Mary","CY",2009 +"2009-10-01","Cyprus Independence Day","CY",2009 +"2009-10-28","Ochi Day","CY",2009 +"2009-12-24","Christmas Eve","CY",2009 +"2009-12-25","Christmas Day","CY",2009 +"2009-12-26","Day After Christmas","CY",2009 +"2010-01-01","New Year's Day","CY",2010 +"2010-01-06","Epiphany","CY",2010 +"2010-02-15","Clean Monday","CY",2010 +"2010-03-25","Greek Independence Day","CY",2010 +"2010-04-01","Cyprus National Day","CY",2010 +"2010-04-02","Good Friday","CY",2010 +"2010-04-04","Easter Sunday","CY",2010 +"2010-04-05","Easter Monday","CY",2010 +"2010-05-01","Labor Day","CY",2010 +"2010-05-24","Monday of the Holy Spirit","CY",2010 +"2010-08-15","Assumption of Mary","CY",2010 +"2010-10-01","Cyprus Independence Day","CY",2010 +"2010-10-28","Ochi Day","CY",2010 +"2010-12-24","Christmas Eve","CY",2010 +"2010-12-25","Christmas Day","CY",2010 +"2010-12-26","Day After Christmas","CY",2010 +"2011-01-01","New Year's Day","CY",2011 +"2011-01-06","Epiphany","CY",2011 +"2011-03-07","Clean Monday","CY",2011 +"2011-03-25","Greek Independence Day","CY",2011 +"2011-04-01","Cyprus National Day","CY",2011 +"2011-04-22","Good Friday","CY",2011 +"2011-04-24","Easter Sunday","CY",2011 +"2011-04-25","Easter Monday","CY",2011 +"2011-05-01","Labor Day","CY",2011 +"2011-06-13","Monday of the Holy Spirit","CY",2011 +"2011-08-15","Assumption of Mary","CY",2011 +"2011-10-01","Cyprus Independence Day","CY",2011 +"2011-10-28","Ochi Day","CY",2011 +"2011-12-24","Christmas Eve","CY",2011 +"2011-12-25","Christmas Day","CY",2011 +"2011-12-26","Day After Christmas","CY",2011 +"2012-01-01","New Year's Day","CY",2012 +"2012-01-06","Epiphany","CY",2012 +"2012-02-27","Clean Monday","CY",2012 +"2012-03-25","Greek Independence Day","CY",2012 +"2012-04-01","Cyprus National Day","CY",2012 +"2012-04-13","Good Friday","CY",2012 +"2012-04-15","Easter Sunday","CY",2012 +"2012-04-16","Easter Monday","CY",2012 +"2012-05-01","Labor Day","CY",2012 +"2012-06-04","Monday of the Holy Spirit","CY",2012 +"2012-08-15","Assumption of Mary","CY",2012 +"2012-10-01","Cyprus Independence Day","CY",2012 +"2012-10-28","Ochi Day","CY",2012 +"2012-12-24","Christmas Eve","CY",2012 +"2012-12-25","Christmas Day","CY",2012 +"2012-12-26","Day After Christmas","CY",2012 +"2013-01-01","New Year's Day","CY",2013 +"2013-01-06","Epiphany","CY",2013 +"2013-03-18","Clean Monday","CY",2013 +"2013-03-25","Greek Independence Day","CY",2013 +"2013-04-01","Cyprus National Day","CY",2013 +"2013-05-01","Labor Day","CY",2013 +"2013-05-03","Good Friday","CY",2013 +"2013-05-05","Easter Sunday","CY",2013 +"2013-05-06","Easter Monday","CY",2013 +"2013-06-24","Monday of the Holy Spirit","CY",2013 +"2013-08-15","Assumption of Mary","CY",2013 +"2013-10-01","Cyprus Independence Day","CY",2013 +"2013-10-28","Ochi Day","CY",2013 +"2013-12-24","Christmas Eve","CY",2013 +"2013-12-25","Christmas Day","CY",2013 +"2013-12-26","Day After Christmas","CY",2013 +"2014-01-01","New Year's Day","CY",2014 +"2014-01-06","Epiphany","CY",2014 +"2014-03-03","Clean Monday","CY",2014 +"2014-03-25","Greek Independence Day","CY",2014 +"2014-04-01","Cyprus National Day","CY",2014 +"2014-04-18","Good Friday","CY",2014 +"2014-04-20","Easter Sunday","CY",2014 +"2014-04-21","Easter Monday","CY",2014 +"2014-05-01","Labor Day","CY",2014 +"2014-06-09","Monday of the Holy Spirit","CY",2014 +"2014-08-15","Assumption of Mary","CY",2014 +"2014-10-01","Cyprus Independence Day","CY",2014 +"2014-10-28","Ochi Day","CY",2014 +"2014-12-24","Christmas Eve","CY",2014 +"2014-12-25","Christmas Day","CY",2014 +"2014-12-26","Day After Christmas","CY",2014 +"2015-01-01","New Year's Day","CY",2015 +"2015-01-06","Epiphany","CY",2015 +"2015-02-23","Clean Monday","CY",2015 +"2015-03-25","Greek Independence Day","CY",2015 +"2015-04-01","Cyprus National Day","CY",2015 +"2015-04-10","Good Friday","CY",2015 +"2015-04-12","Easter Sunday","CY",2015 +"2015-04-13","Easter Monday","CY",2015 +"2015-05-01","Labor Day","CY",2015 +"2015-06-01","Monday of the Holy Spirit","CY",2015 +"2015-08-15","Assumption of Mary","CY",2015 +"2015-10-01","Cyprus Independence Day","CY",2015 +"2015-10-28","Ochi Day","CY",2015 +"2015-12-24","Christmas Eve","CY",2015 +"2015-12-25","Christmas Day","CY",2015 +"2015-12-26","Day After Christmas","CY",2015 +"2016-01-01","New Year's Day","CY",2016 +"2016-01-06","Epiphany","CY",2016 +"2016-03-14","Clean Monday","CY",2016 +"2016-03-25","Greek Independence Day","CY",2016 +"2016-04-01","Cyprus National Day","CY",2016 +"2016-04-29","Good Friday","CY",2016 +"2016-05-01","Easter Sunday","CY",2016 +"2016-05-01","Labor Day","CY",2016 +"2016-05-02","Easter Monday","CY",2016 +"2016-06-20","Monday of the Holy Spirit","CY",2016 +"2016-08-15","Assumption of Mary","CY",2016 +"2016-10-01","Cyprus Independence Day","CY",2016 +"2016-10-28","Ochi Day","CY",2016 +"2016-12-24","Christmas Eve","CY",2016 +"2016-12-25","Christmas Day","CY",2016 +"2016-12-26","Day After Christmas","CY",2016 +"2017-01-01","New Year's Day","CY",2017 +"2017-01-06","Epiphany","CY",2017 +"2017-02-27","Clean Monday","CY",2017 +"2017-03-25","Greek Independence Day","CY",2017 +"2017-04-01","Cyprus National Day","CY",2017 +"2017-04-14","Good Friday","CY",2017 +"2017-04-16","Easter Sunday","CY",2017 +"2017-04-17","Easter Monday","CY",2017 +"2017-05-01","Labor Day","CY",2017 +"2017-06-05","Monday of the Holy Spirit","CY",2017 +"2017-08-15","Assumption of Mary","CY",2017 +"2017-10-01","Cyprus Independence Day","CY",2017 +"2017-10-28","Ochi Day","CY",2017 +"2017-12-24","Christmas Eve","CY",2017 +"2017-12-25","Christmas Day","CY",2017 +"2017-12-26","Day After Christmas","CY",2017 +"2018-01-01","New Year's Day","CY",2018 +"2018-01-06","Epiphany","CY",2018 +"2018-02-19","Clean Monday","CY",2018 +"2018-03-25","Greek Independence Day","CY",2018 +"2018-04-01","Cyprus National Day","CY",2018 +"2018-04-06","Good Friday","CY",2018 +"2018-04-08","Easter Sunday","CY",2018 +"2018-04-09","Easter Monday","CY",2018 +"2018-05-01","Labor Day","CY",2018 +"2018-05-28","Monday of the Holy Spirit","CY",2018 +"2018-08-15","Assumption of Mary","CY",2018 +"2018-10-01","Cyprus Independence Day","CY",2018 +"2018-10-28","Ochi Day","CY",2018 +"2018-12-24","Christmas Eve","CY",2018 +"2018-12-25","Christmas Day","CY",2018 +"2018-12-26","Day After Christmas","CY",2018 +"2019-01-01","New Year's Day","CY",2019 +"2019-01-06","Epiphany","CY",2019 +"2019-03-11","Clean Monday","CY",2019 +"2019-03-25","Greek Independence Day","CY",2019 +"2019-04-01","Cyprus National Day","CY",2019 +"2019-04-26","Good Friday","CY",2019 +"2019-04-28","Easter Sunday","CY",2019 +"2019-04-29","Easter Monday","CY",2019 +"2019-05-01","Labor Day","CY",2019 +"2019-06-17","Monday of the Holy Spirit","CY",2019 +"2019-08-15","Assumption of Mary","CY",2019 +"2019-10-01","Cyprus Independence Day","CY",2019 +"2019-10-28","Ochi Day","CY",2019 +"2019-12-24","Christmas Eve","CY",2019 +"2019-12-25","Christmas Day","CY",2019 +"2019-12-26","Day After Christmas","CY",2019 +"2020-01-01","New Year's Day","CY",2020 +"2020-01-06","Epiphany","CY",2020 +"2020-03-02","Clean Monday","CY",2020 +"2020-03-25","Greek Independence Day","CY",2020 +"2020-04-01","Cyprus National Day","CY",2020 +"2020-04-17","Good Friday","CY",2020 +"2020-04-19","Easter Sunday","CY",2020 +"2020-04-20","Easter Monday","CY",2020 +"2020-05-01","Labor Day","CY",2020 +"2020-06-08","Monday of the Holy Spirit","CY",2020 +"2020-08-15","Assumption of Mary","CY",2020 +"2020-10-01","Cyprus Independence Day","CY",2020 +"2020-10-28","Ochi Day","CY",2020 +"2020-12-24","Christmas Eve","CY",2020 +"2020-12-25","Christmas Day","CY",2020 +"2020-12-26","Day After Christmas","CY",2020 +"2021-01-01","New Year's Day","CY",2021 +"2021-01-06","Epiphany","CY",2021 +"2021-03-15","Clean Monday","CY",2021 +"2021-03-25","Greek Independence Day","CY",2021 +"2021-04-01","Cyprus National Day","CY",2021 +"2021-04-30","Good Friday","CY",2021 +"2021-05-01","Labor Day","CY",2021 +"2021-05-02","Easter Sunday","CY",2021 +"2021-05-03","Easter Monday","CY",2021 +"2021-06-21","Monday of the Holy Spirit","CY",2021 +"2021-08-15","Assumption of Mary","CY",2021 +"2021-10-01","Cyprus Independence Day","CY",2021 +"2021-10-28","Ochi Day","CY",2021 +"2021-12-24","Christmas Eve","CY",2021 +"2021-12-25","Christmas Day","CY",2021 +"2021-12-26","Day After Christmas","CY",2021 +"2022-01-01","New Year's Day","CY",2022 +"2022-01-06","Epiphany","CY",2022 +"2022-03-07","Clean Monday","CY",2022 +"2022-03-25","Greek Independence Day","CY",2022 +"2022-04-01","Cyprus National Day","CY",2022 +"2022-04-22","Good Friday","CY",2022 +"2022-04-24","Easter Sunday","CY",2022 +"2022-04-25","Easter Monday","CY",2022 +"2022-05-01","Labor Day","CY",2022 +"2022-06-13","Monday of the Holy Spirit","CY",2022 +"2022-08-15","Assumption of Mary","CY",2022 +"2022-10-01","Cyprus Independence Day","CY",2022 +"2022-10-28","Ochi Day","CY",2022 +"2022-12-24","Christmas Eve","CY",2022 +"2022-12-25","Christmas Day","CY",2022 +"2022-12-26","Day After Christmas","CY",2022 +"2023-01-01","New Year's Day","CY",2023 +"2023-01-06","Epiphany","CY",2023 +"2023-02-27","Clean Monday","CY",2023 +"2023-03-25","Greek Independence Day","CY",2023 +"2023-04-01","Cyprus National Day","CY",2023 +"2023-04-14","Good Friday","CY",2023 +"2023-04-16","Easter Sunday","CY",2023 +"2023-04-17","Easter Monday","CY",2023 +"2023-05-01","Labor Day","CY",2023 +"2023-06-05","Monday of the Holy Spirit","CY",2023 +"2023-08-15","Assumption of Mary","CY",2023 +"2023-10-01","Cyprus Independence Day","CY",2023 +"2023-10-28","Ochi Day","CY",2023 +"2023-12-24","Christmas Eve","CY",2023 +"2023-12-25","Christmas Day","CY",2023 +"2023-12-26","Day After Christmas","CY",2023 +"2024-01-01","New Year's Day","CY",2024 +"2024-01-06","Epiphany","CY",2024 +"2024-03-18","Clean Monday","CY",2024 +"2024-03-25","Greek Independence Day","CY",2024 +"2024-04-01","Cyprus National Day","CY",2024 +"2024-05-01","Labor Day","CY",2024 +"2024-05-03","Good Friday","CY",2024 +"2024-05-05","Easter Sunday","CY",2024 +"2024-05-06","Easter Monday","CY",2024 +"2024-06-24","Monday of the Holy Spirit","CY",2024 +"2024-08-15","Assumption of Mary","CY",2024 +"2024-10-01","Cyprus Independence Day","CY",2024 +"2024-10-28","Ochi Day","CY",2024 +"2024-12-24","Christmas Eve","CY",2024 +"2024-12-25","Christmas Day","CY",2024 +"2024-12-26","Day After Christmas","CY",2024 +"2025-01-01","New Year's Day","CY",2025 +"2025-01-06","Epiphany","CY",2025 +"2025-03-03","Clean Monday","CY",2025 +"2025-03-25","Greek Independence Day","CY",2025 +"2025-04-01","Cyprus National Day","CY",2025 +"2025-04-18","Good Friday","CY",2025 +"2025-04-20","Easter Sunday","CY",2025 +"2025-04-21","Easter Monday","CY",2025 +"2025-05-01","Labor Day","CY",2025 +"2025-06-09","Monday of the Holy Spirit","CY",2025 +"2025-08-15","Assumption of Mary","CY",2025 +"2025-10-01","Cyprus Independence Day","CY",2025 +"2025-10-28","Ochi Day","CY",2025 +"2025-12-24","Christmas Eve","CY",2025 +"2025-12-25","Christmas Day","CY",2025 +"2025-12-26","Day After Christmas","CY",2025 +"2026-01-01","New Year's Day","CY",2026 +"2026-01-06","Epiphany","CY",2026 +"2026-02-23","Clean Monday","CY",2026 +"2026-03-25","Greek Independence Day","CY",2026 +"2026-04-01","Cyprus National Day","CY",2026 +"2026-04-10","Good Friday","CY",2026 +"2026-04-12","Easter Sunday","CY",2026 +"2026-04-13","Easter Monday","CY",2026 +"2026-05-01","Labor Day","CY",2026 +"2026-06-01","Monday of the Holy Spirit","CY",2026 +"2026-08-15","Assumption of Mary","CY",2026 +"2026-10-01","Cyprus Independence Day","CY",2026 +"2026-10-28","Ochi Day","CY",2026 +"2026-12-24","Christmas Eve","CY",2026 +"2026-12-25","Christmas Day","CY",2026 +"2026-12-26","Day After Christmas","CY",2026 +"2027-01-01","New Year's Day","CY",2027 +"2027-01-06","Epiphany","CY",2027 +"2027-03-15","Clean Monday","CY",2027 +"2027-03-25","Greek Independence Day","CY",2027 +"2027-04-01","Cyprus National Day","CY",2027 +"2027-04-30","Good Friday","CY",2027 +"2027-05-01","Labor Day","CY",2027 +"2027-05-02","Easter Sunday","CY",2027 +"2027-05-03","Easter Monday","CY",2027 +"2027-06-21","Monday of the Holy Spirit","CY",2027 +"2027-08-15","Assumption of Mary","CY",2027 +"2027-10-01","Cyprus Independence Day","CY",2027 +"2027-10-28","Ochi Day","CY",2027 +"2027-12-24","Christmas Eve","CY",2027 +"2027-12-25","Christmas Day","CY",2027 +"2027-12-26","Day After Christmas","CY",2027 +"2028-01-01","New Year's Day","CY",2028 +"2028-01-06","Epiphany","CY",2028 +"2028-02-28","Clean Monday","CY",2028 +"2028-03-25","Greek Independence Day","CY",2028 +"2028-04-01","Cyprus National Day","CY",2028 +"2028-04-14","Good Friday","CY",2028 +"2028-04-16","Easter Sunday","CY",2028 +"2028-04-17","Easter Monday","CY",2028 +"2028-05-01","Labor Day","CY",2028 +"2028-06-05","Monday of the Holy Spirit","CY",2028 +"2028-08-15","Assumption of Mary","CY",2028 +"2028-10-01","Cyprus Independence Day","CY",2028 +"2028-10-28","Ochi Day","CY",2028 +"2028-12-24","Christmas Eve","CY",2028 +"2028-12-25","Christmas Day","CY",2028 +"2028-12-26","Day After Christmas","CY",2028 +"2029-01-01","New Year's Day","CY",2029 +"2029-01-06","Epiphany","CY",2029 +"2029-02-19","Clean Monday","CY",2029 +"2029-03-25","Greek Independence Day","CY",2029 +"2029-04-01","Cyprus National Day","CY",2029 +"2029-04-06","Good Friday","CY",2029 +"2029-04-08","Easter Sunday","CY",2029 +"2029-04-09","Easter Monday","CY",2029 +"2029-05-01","Labor Day","CY",2029 +"2029-05-28","Monday of the Holy Spirit","CY",2029 +"2029-08-15","Assumption of Mary","CY",2029 +"2029-10-01","Cyprus Independence Day","CY",2029 +"2029-10-28","Ochi Day","CY",2029 +"2029-12-24","Christmas Eve","CY",2029 +"2029-12-25","Christmas Day","CY",2029 +"2029-12-26","Day After Christmas","CY",2029 +"2030-01-01","New Year's Day","CY",2030 +"2030-01-06","Epiphany","CY",2030 +"2030-03-11","Clean Monday","CY",2030 +"2030-03-25","Greek Independence Day","CY",2030 +"2030-04-01","Cyprus National Day","CY",2030 +"2030-04-26","Good Friday","CY",2030 +"2030-04-28","Easter Sunday","CY",2030 +"2030-04-29","Easter Monday","CY",2030 +"2030-05-01","Labor Day","CY",2030 +"2030-06-17","Monday of the Holy Spirit","CY",2030 +"2030-08-15","Assumption of Mary","CY",2030 +"2030-10-01","Cyprus Independence Day","CY",2030 +"2030-10-28","Ochi Day","CY",2030 +"2030-12-24","Christmas Eve","CY",2030 +"2030-12-25","Christmas Day","CY",2030 +"2030-12-26","Day After Christmas","CY",2030 +"2031-01-01","New Year's Day","CY",2031 +"2031-01-06","Epiphany","CY",2031 +"2031-02-24","Clean Monday","CY",2031 +"2031-03-25","Greek Independence Day","CY",2031 +"2031-04-01","Cyprus National Day","CY",2031 +"2031-04-11","Good Friday","CY",2031 +"2031-04-13","Easter Sunday","CY",2031 +"2031-04-14","Easter Monday","CY",2031 +"2031-05-01","Labor Day","CY",2031 +"2031-06-02","Monday of the Holy Spirit","CY",2031 +"2031-08-15","Assumption of Mary","CY",2031 +"2031-10-01","Cyprus Independence Day","CY",2031 +"2031-10-28","Ochi Day","CY",2031 +"2031-12-24","Christmas Eve","CY",2031 +"2031-12-25","Christmas Day","CY",2031 +"2031-12-26","Day After Christmas","CY",2031 +"2032-01-01","New Year's Day","CY",2032 +"2032-01-06","Epiphany","CY",2032 +"2032-03-15","Clean Monday","CY",2032 +"2032-03-25","Greek Independence Day","CY",2032 +"2032-04-01","Cyprus National Day","CY",2032 +"2032-04-30","Good Friday","CY",2032 +"2032-05-01","Labor Day","CY",2032 +"2032-05-02","Easter Sunday","CY",2032 +"2032-05-03","Easter Monday","CY",2032 +"2032-06-21","Monday of the Holy Spirit","CY",2032 +"2032-08-15","Assumption of Mary","CY",2032 +"2032-10-01","Cyprus Independence Day","CY",2032 +"2032-10-28","Ochi Day","CY",2032 +"2032-12-24","Christmas Eve","CY",2032 +"2032-12-25","Christmas Day","CY",2032 +"2032-12-26","Day After Christmas","CY",2032 +"2033-01-01","New Year's Day","CY",2033 +"2033-01-06","Epiphany","CY",2033 +"2033-03-07","Clean Monday","CY",2033 +"2033-03-25","Greek Independence Day","CY",2033 +"2033-04-01","Cyprus National Day","CY",2033 +"2033-04-22","Good Friday","CY",2033 +"2033-04-24","Easter Sunday","CY",2033 +"2033-04-25","Easter Monday","CY",2033 +"2033-05-01","Labor Day","CY",2033 +"2033-06-13","Monday of the Holy Spirit","CY",2033 +"2033-08-15","Assumption of Mary","CY",2033 +"2033-10-01","Cyprus Independence Day","CY",2033 +"2033-10-28","Ochi Day","CY",2033 +"2033-12-24","Christmas Eve","CY",2033 +"2033-12-25","Christmas Day","CY",2033 +"2033-12-26","Day After Christmas","CY",2033 +"2034-01-01","New Year's Day","CY",2034 +"2034-01-06","Epiphany","CY",2034 +"2034-02-20","Clean Monday","CY",2034 +"2034-03-25","Greek Independence Day","CY",2034 +"2034-04-01","Cyprus National Day","CY",2034 +"2034-04-07","Good Friday","CY",2034 +"2034-04-09","Easter Sunday","CY",2034 +"2034-04-10","Easter Monday","CY",2034 +"2034-05-01","Labor Day","CY",2034 +"2034-05-29","Monday of the Holy Spirit","CY",2034 +"2034-08-15","Assumption of Mary","CY",2034 +"2034-10-01","Cyprus Independence Day","CY",2034 +"2034-10-28","Ochi Day","CY",2034 +"2034-12-24","Christmas Eve","CY",2034 +"2034-12-25","Christmas Day","CY",2034 +"2034-12-26","Day After Christmas","CY",2034 +"2035-01-01","New Year's Day","CY",2035 +"2035-01-06","Epiphany","CY",2035 +"2035-03-12","Clean Monday","CY",2035 +"2035-03-25","Greek Independence Day","CY",2035 +"2035-04-01","Cyprus National Day","CY",2035 +"2035-04-27","Good Friday","CY",2035 +"2035-04-29","Easter Sunday","CY",2035 +"2035-04-30","Easter Monday","CY",2035 +"2035-05-01","Labor Day","CY",2035 +"2035-06-18","Monday of the Holy Spirit","CY",2035 +"2035-08-15","Assumption of Mary","CY",2035 +"2035-10-01","Cyprus Independence Day","CY",2035 +"2035-10-28","Ochi Day","CY",2035 +"2035-12-24","Christmas Eve","CY",2035 +"2035-12-25","Christmas Day","CY",2035 +"2035-12-26","Day After Christmas","CY",2035 +"2036-01-01","New Year's Day","CY",2036 +"2036-01-06","Epiphany","CY",2036 +"2036-03-03","Clean Monday","CY",2036 +"2036-03-25","Greek Independence Day","CY",2036 +"2036-04-01","Cyprus National Day","CY",2036 +"2036-04-18","Good Friday","CY",2036 +"2036-04-20","Easter Sunday","CY",2036 +"2036-04-21","Easter Monday","CY",2036 +"2036-05-01","Labor Day","CY",2036 +"2036-06-09","Monday of the Holy Spirit","CY",2036 +"2036-08-15","Assumption of Mary","CY",2036 +"2036-10-01","Cyprus Independence Day","CY",2036 +"2036-10-28","Ochi Day","CY",2036 +"2036-12-24","Christmas Eve","CY",2036 +"2036-12-25","Christmas Day","CY",2036 +"2036-12-26","Day After Christmas","CY",2036 +"2037-01-01","New Year's Day","CY",2037 +"2037-01-06","Epiphany","CY",2037 +"2037-02-16","Clean Monday","CY",2037 +"2037-03-25","Greek Independence Day","CY",2037 +"2037-04-01","Cyprus National Day","CY",2037 +"2037-04-03","Good Friday","CY",2037 +"2037-04-05","Easter Sunday","CY",2037 +"2037-04-06","Easter Monday","CY",2037 +"2037-05-01","Labor Day","CY",2037 +"2037-05-25","Monday of the Holy Spirit","CY",2037 +"2037-08-15","Assumption of Mary","CY",2037 +"2037-10-01","Cyprus Independence Day","CY",2037 +"2037-10-28","Ochi Day","CY",2037 +"2037-12-24","Christmas Eve","CY",2037 +"2037-12-25","Christmas Day","CY",2037 +"2037-12-26","Day After Christmas","CY",2037 +"2038-01-01","New Year's Day","CY",2038 +"2038-01-06","Epiphany","CY",2038 +"2038-03-08","Clean Monday","CY",2038 +"2038-03-25","Greek Independence Day","CY",2038 +"2038-04-01","Cyprus National Day","CY",2038 +"2038-04-23","Good Friday","CY",2038 +"2038-04-25","Easter Sunday","CY",2038 +"2038-04-26","Easter Monday","CY",2038 +"2038-05-01","Labor Day","CY",2038 +"2038-06-14","Monday of the Holy Spirit","CY",2038 +"2038-08-15","Assumption of Mary","CY",2038 +"2038-10-01","Cyprus Independence Day","CY",2038 +"2038-10-28","Ochi Day","CY",2038 +"2038-12-24","Christmas Eve","CY",2038 +"2038-12-25","Christmas Day","CY",2038 +"2038-12-26","Day After Christmas","CY",2038 +"2039-01-01","New Year's Day","CY",2039 +"2039-01-06","Epiphany","CY",2039 +"2039-02-28","Clean Monday","CY",2039 +"2039-03-25","Greek Independence Day","CY",2039 +"2039-04-01","Cyprus National Day","CY",2039 +"2039-04-15","Good Friday","CY",2039 +"2039-04-17","Easter Sunday","CY",2039 +"2039-04-18","Easter Monday","CY",2039 +"2039-05-01","Labor Day","CY",2039 +"2039-06-06","Monday of the Holy Spirit","CY",2039 +"2039-08-15","Assumption of Mary","CY",2039 +"2039-10-01","Cyprus Independence Day","CY",2039 +"2039-10-28","Ochi Day","CY",2039 +"2039-12-24","Christmas Eve","CY",2039 +"2039-12-25","Christmas Day","CY",2039 +"2039-12-26","Day After Christmas","CY",2039 +"2040-01-01","New Year's Day","CY",2040 +"2040-01-06","Epiphany","CY",2040 +"2040-03-19","Clean Monday","CY",2040 +"2040-03-25","Greek Independence Day","CY",2040 +"2040-04-01","Cyprus National Day","CY",2040 +"2040-05-01","Labor Day","CY",2040 +"2040-05-04","Good Friday","CY",2040 +"2040-05-06","Easter Sunday","CY",2040 +"2040-05-07","Easter Monday","CY",2040 +"2040-06-25","Monday of the Holy Spirit","CY",2040 +"2040-08-15","Assumption of Mary","CY",2040 +"2040-10-01","Cyprus Independence Day","CY",2040 +"2040-10-28","Ochi Day","CY",2040 +"2040-12-24","Christmas Eve","CY",2040 +"2040-12-25","Christmas Day","CY",2040 +"2040-12-26","Day After Christmas","CY",2040 +"2041-01-01","New Year's Day","CY",2041 +"2041-01-06","Epiphany","CY",2041 +"2041-03-04","Clean Monday","CY",2041 +"2041-03-25","Greek Independence Day","CY",2041 +"2041-04-01","Cyprus National Day","CY",2041 +"2041-04-19","Good Friday","CY",2041 +"2041-04-21","Easter Sunday","CY",2041 +"2041-04-22","Easter Monday","CY",2041 +"2041-05-01","Labor Day","CY",2041 +"2041-06-10","Monday of the Holy Spirit","CY",2041 +"2041-08-15","Assumption of Mary","CY",2041 +"2041-10-01","Cyprus Independence Day","CY",2041 +"2041-10-28","Ochi Day","CY",2041 +"2041-12-24","Christmas Eve","CY",2041 +"2041-12-25","Christmas Day","CY",2041 +"2041-12-26","Day After Christmas","CY",2041 +"2042-01-01","New Year's Day","CY",2042 +"2042-01-06","Epiphany","CY",2042 +"2042-02-24","Clean Monday","CY",2042 +"2042-03-25","Greek Independence Day","CY",2042 +"2042-04-01","Cyprus National Day","CY",2042 +"2042-04-11","Good Friday","CY",2042 +"2042-04-13","Easter Sunday","CY",2042 +"2042-04-14","Easter Monday","CY",2042 +"2042-05-01","Labor Day","CY",2042 +"2042-06-02","Monday of the Holy Spirit","CY",2042 +"2042-08-15","Assumption of Mary","CY",2042 +"2042-10-01","Cyprus Independence Day","CY",2042 +"2042-10-28","Ochi Day","CY",2042 +"2042-12-24","Christmas Eve","CY",2042 +"2042-12-25","Christmas Day","CY",2042 +"2042-12-26","Day After Christmas","CY",2042 +"2043-01-01","New Year's Day","CY",2043 +"2043-01-06","Epiphany","CY",2043 +"2043-03-16","Clean Monday","CY",2043 +"2043-03-25","Greek Independence Day","CY",2043 +"2043-04-01","Cyprus National Day","CY",2043 +"2043-05-01","Good Friday","CY",2043 +"2043-05-01","Labor Day","CY",2043 +"2043-05-03","Easter Sunday","CY",2043 +"2043-05-04","Easter Monday","CY",2043 +"2043-06-22","Monday of the Holy Spirit","CY",2043 +"2043-08-15","Assumption of Mary","CY",2043 +"2043-10-01","Cyprus Independence Day","CY",2043 +"2043-10-28","Ochi Day","CY",2043 +"2043-12-24","Christmas Eve","CY",2043 +"2043-12-25","Christmas Day","CY",2043 +"2043-12-26","Day After Christmas","CY",2043 +"2044-01-01","New Year's Day","CY",2044 +"2044-01-06","Epiphany","CY",2044 +"2044-03-07","Clean Monday","CY",2044 +"2044-03-25","Greek Independence Day","CY",2044 +"2044-04-01","Cyprus National Day","CY",2044 +"2044-04-22","Good Friday","CY",2044 +"2044-04-24","Easter Sunday","CY",2044 +"2044-04-25","Easter Monday","CY",2044 +"2044-05-01","Labor Day","CY",2044 +"2044-06-13","Monday of the Holy Spirit","CY",2044 +"2044-08-15","Assumption of Mary","CY",2044 +"2044-10-01","Cyprus Independence Day","CY",2044 +"2044-10-28","Ochi Day","CY",2044 +"2044-12-24","Christmas Eve","CY",2044 +"2044-12-25","Christmas Day","CY",2044 +"2044-12-26","Day After Christmas","CY",2044 +"1995-01-01","Novy rok","CZ",1995 +"1995-04-17","Velikonocni pondeli","CZ",1995 +"1995-05-01","Svatek prace","CZ",1995 +"1995-05-08","Den vitezstvi","CZ",1995 +"1995-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",1995 +"1995-07-06","Den upaleni mistra Jana Husa","CZ",1995 +"1995-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",1995 +"1995-11-17","Den boje za svobodu a demokracii","CZ",1995 +"1995-12-24","Stedry den","CZ",1995 +"1995-12-25","1. svatek vanocni","CZ",1995 +"1995-12-26","2. svatek vanocni","CZ",1995 +"1996-01-01","Novy rok","CZ",1996 +"1996-04-08","Velikonocni pondeli","CZ",1996 +"1996-05-01","Svatek prace","CZ",1996 +"1996-05-08","Den vitezstvi","CZ",1996 +"1996-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",1996 +"1996-07-06","Den upaleni mistra Jana Husa","CZ",1996 +"1996-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",1996 +"1996-11-17","Den boje za svobodu a demokracii","CZ",1996 +"1996-12-24","Stedry den","CZ",1996 +"1996-12-25","1. svatek vanocni","CZ",1996 +"1996-12-26","2. svatek vanocni","CZ",1996 +"1997-01-01","Novy rok","CZ",1997 +"1997-03-31","Velikonocni pondeli","CZ",1997 +"1997-05-01","Svatek prace","CZ",1997 +"1997-05-08","Den vitezstvi","CZ",1997 +"1997-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",1997 +"1997-07-06","Den upaleni mistra Jana Husa","CZ",1997 +"1997-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",1997 +"1997-11-17","Den boje za svobodu a demokracii","CZ",1997 +"1997-12-24","Stedry den","CZ",1997 +"1997-12-25","1. svatek vanocni","CZ",1997 +"1997-12-26","2. svatek vanocni","CZ",1997 +"1998-01-01","Novy rok","CZ",1998 +"1998-04-13","Velikonocni pondeli","CZ",1998 +"1998-05-01","Svatek prace","CZ",1998 +"1998-05-08","Den vitezstvi","CZ",1998 +"1998-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",1998 +"1998-07-06","Den upaleni mistra Jana Husa","CZ",1998 +"1998-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",1998 +"1998-11-17","Den boje za svobodu a demokracii","CZ",1998 +"1998-12-24","Stedry den","CZ",1998 +"1998-12-25","1. svatek vanocni","CZ",1998 +"1998-12-26","2. svatek vanocni","CZ",1998 +"1999-01-01","Novy rok","CZ",1999 +"1999-04-05","Velikonocni pondeli","CZ",1999 +"1999-05-01","Svatek prace","CZ",1999 +"1999-05-08","Den vitezstvi","CZ",1999 +"1999-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",1999 +"1999-07-06","Den upaleni mistra Jana Husa","CZ",1999 +"1999-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",1999 +"1999-11-17","Den boje za svobodu a demokracii","CZ",1999 +"1999-12-24","Stedry den","CZ",1999 +"1999-12-25","1. svatek vanocni","CZ",1999 +"1999-12-26","2. svatek vanocni","CZ",1999 +"2000-01-01","Den obnovy samostatneho ceskeho statu","CZ",2000 +"2000-04-24","Velikonocni pondeli","CZ",2000 +"2000-05-01","Svatek prace","CZ",2000 +"2000-05-08","Den vitezstvi","CZ",2000 +"2000-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2000 +"2000-07-06","Den upaleni mistra Jana Husa","CZ",2000 +"2000-09-28","Den ceske statnosti","CZ",2000 +"2000-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2000 +"2000-11-17","Den boje za svobodu a demokracii","CZ",2000 +"2000-12-24","Stedry den","CZ",2000 +"2000-12-25","1. svatek vanocni","CZ",2000 +"2000-12-26","2. svatek vanocni","CZ",2000 +"2001-01-01","Den obnovy samostatneho ceskeho statu","CZ",2001 +"2001-04-16","Velikonocni pondeli","CZ",2001 +"2001-05-01","Svatek prace","CZ",2001 +"2001-05-08","Den vitezstvi","CZ",2001 +"2001-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2001 +"2001-07-06","Den upaleni mistra Jana Husa","CZ",2001 +"2001-09-28","Den ceske statnosti","CZ",2001 +"2001-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2001 +"2001-11-17","Den boje za svobodu a demokracii","CZ",2001 +"2001-12-24","Stedry den","CZ",2001 +"2001-12-25","1. svatek vanocni","CZ",2001 +"2001-12-26","2. svatek vanocni","CZ",2001 +"2002-01-01","Den obnovy samostatneho ceskeho statu","CZ",2002 +"2002-04-01","Velikonocni pondeli","CZ",2002 +"2002-05-01","Svatek prace","CZ",2002 +"2002-05-08","Den vitezstvi","CZ",2002 +"2002-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2002 +"2002-07-06","Den upaleni mistra Jana Husa","CZ",2002 +"2002-09-28","Den ceske statnosti","CZ",2002 +"2002-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2002 +"2002-11-17","Den boje za svobodu a demokracii","CZ",2002 +"2002-12-24","Stedry den","CZ",2002 +"2002-12-25","1. svatek vanocni","CZ",2002 +"2002-12-26","2. svatek vanocni","CZ",2002 +"2003-01-01","Den obnovy samostatneho ceskeho statu","CZ",2003 +"2003-04-21","Velikonocni pondeli","CZ",2003 +"2003-05-01","Svatek prace","CZ",2003 +"2003-05-08","Den vitezstvi","CZ",2003 +"2003-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2003 +"2003-07-06","Den upaleni mistra Jana Husa","CZ",2003 +"2003-09-28","Den ceske statnosti","CZ",2003 +"2003-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2003 +"2003-11-17","Den boje za svobodu a demokracii","CZ",2003 +"2003-12-24","Stedry den","CZ",2003 +"2003-12-25","1. svatek vanocni","CZ",2003 +"2003-12-26","2. svatek vanocni","CZ",2003 +"2004-01-01","Den obnovy samostatneho ceskeho statu","CZ",2004 +"2004-04-12","Velikonocni pondeli","CZ",2004 +"2004-05-01","Svatek prace","CZ",2004 +"2004-05-08","Den vitezstvi","CZ",2004 +"2004-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2004 +"2004-07-06","Den upaleni mistra Jana Husa","CZ",2004 +"2004-09-28","Den ceske statnosti","CZ",2004 +"2004-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2004 +"2004-11-17","Den boje za svobodu a demokracii","CZ",2004 +"2004-12-24","Stedry den","CZ",2004 +"2004-12-25","1. svatek vanocni","CZ",2004 +"2004-12-26","2. svatek vanocni","CZ",2004 +"2005-01-01","Den obnovy samostatneho ceskeho statu","CZ",2005 +"2005-03-28","Velikonocni pondeli","CZ",2005 +"2005-05-01","Svatek prace","CZ",2005 +"2005-05-08","Den vitezstvi","CZ",2005 +"2005-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2005 +"2005-07-06","Den upaleni mistra Jana Husa","CZ",2005 +"2005-09-28","Den ceske statnosti","CZ",2005 +"2005-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2005 +"2005-11-17","Den boje za svobodu a demokracii","CZ",2005 +"2005-12-24","Stedry den","CZ",2005 +"2005-12-25","1. svatek vanocni","CZ",2005 +"2005-12-26","2. svatek vanocni","CZ",2005 +"2006-01-01","Den obnovy samostatneho ceskeho statu","CZ",2006 +"2006-04-17","Velikonocni pondeli","CZ",2006 +"2006-05-01","Svatek prace","CZ",2006 +"2006-05-08","Den vitezstvi","CZ",2006 +"2006-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2006 +"2006-07-06","Den upaleni mistra Jana Husa","CZ",2006 +"2006-09-28","Den ceske statnosti","CZ",2006 +"2006-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2006 +"2006-11-17","Den boje za svobodu a demokracii","CZ",2006 +"2006-12-24","Stedry den","CZ",2006 +"2006-12-25","1. svatek vanocni","CZ",2006 +"2006-12-26","2. svatek vanocni","CZ",2006 +"2007-01-01","Den obnovy samostatneho ceskeho statu","CZ",2007 +"2007-04-09","Velikonocni pondeli","CZ",2007 +"2007-05-01","Svatek prace","CZ",2007 +"2007-05-08","Den vitezstvi","CZ",2007 +"2007-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2007 +"2007-07-06","Den upaleni mistra Jana Husa","CZ",2007 +"2007-09-28","Den ceske statnosti","CZ",2007 +"2007-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2007 +"2007-11-17","Den boje za svobodu a demokracii","CZ",2007 +"2007-12-24","Stedry den","CZ",2007 +"2007-12-25","1. svatek vanocni","CZ",2007 +"2007-12-26","2. svatek vanocni","CZ",2007 +"2008-01-01","Den obnovy samostatneho ceskeho statu","CZ",2008 +"2008-03-24","Velikonocni pondeli","CZ",2008 +"2008-05-01","Svatek prace","CZ",2008 +"2008-05-08","Den vitezstvi","CZ",2008 +"2008-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2008 +"2008-07-06","Den upaleni mistra Jana Husa","CZ",2008 +"2008-09-28","Den ceske statnosti","CZ",2008 +"2008-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2008 +"2008-11-17","Den boje za svobodu a demokracii","CZ",2008 +"2008-12-24","Stedry den","CZ",2008 +"2008-12-25","1. svatek vanocni","CZ",2008 +"2008-12-26","2. svatek vanocni","CZ",2008 +"2009-01-01","Den obnovy samostatneho ceskeho statu","CZ",2009 +"2009-04-13","Velikonocni pondeli","CZ",2009 +"2009-05-01","Svatek prace","CZ",2009 +"2009-05-08","Den vitezstvi","CZ",2009 +"2009-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2009 +"2009-07-06","Den upaleni mistra Jana Husa","CZ",2009 +"2009-09-28","Den ceske statnosti","CZ",2009 +"2009-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2009 +"2009-11-17","Den boje za svobodu a demokracii","CZ",2009 +"2009-12-24","Stedry den","CZ",2009 +"2009-12-25","1. svatek vanocni","CZ",2009 +"2009-12-26","2. svatek vanocni","CZ",2009 +"2010-01-01","Den obnovy samostatneho ceskeho statu","CZ",2010 +"2010-04-05","Velikonocni pondeli","CZ",2010 +"2010-05-01","Svatek prace","CZ",2010 +"2010-05-08","Den vitezstvi","CZ",2010 +"2010-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2010 +"2010-07-06","Den upaleni mistra Jana Husa","CZ",2010 +"2010-09-28","Den ceske statnosti","CZ",2010 +"2010-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2010 +"2010-11-17","Den boje za svobodu a demokracii","CZ",2010 +"2010-12-24","Stedry den","CZ",2010 +"2010-12-25","1. svatek vanocni","CZ",2010 +"2010-12-26","2. svatek vanocni","CZ",2010 +"2011-01-01","Den obnovy samostatneho ceskeho statu","CZ",2011 +"2011-04-25","Velikonocni pondeli","CZ",2011 +"2011-05-01","Svatek prace","CZ",2011 +"2011-05-08","Den vitezstvi","CZ",2011 +"2011-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2011 +"2011-07-06","Den upaleni mistra Jana Husa","CZ",2011 +"2011-09-28","Den ceske statnosti","CZ",2011 +"2011-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2011 +"2011-11-17","Den boje za svobodu a demokracii","CZ",2011 +"2011-12-24","Stedry den","CZ",2011 +"2011-12-25","1. svatek vanocni","CZ",2011 +"2011-12-26","2. svatek vanocni","CZ",2011 +"2012-01-01","Den obnovy samostatneho ceskeho statu","CZ",2012 +"2012-04-09","Velikonocni pondeli","CZ",2012 +"2012-05-01","Svatek prace","CZ",2012 +"2012-05-08","Den vitezstvi","CZ",2012 +"2012-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2012 +"2012-07-06","Den upaleni mistra Jana Husa","CZ",2012 +"2012-09-28","Den ceske statnosti","CZ",2012 +"2012-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2012 +"2012-11-17","Den boje za svobodu a demokracii","CZ",2012 +"2012-12-24","Stedry den","CZ",2012 +"2012-12-25","1. svatek vanocni","CZ",2012 +"2012-12-26","2. svatek vanocni","CZ",2012 +"2013-01-01","Den obnovy samostatneho ceskeho statu","CZ",2013 +"2013-04-01","Velikonocni pondeli","CZ",2013 +"2013-05-01","Svatek prace","CZ",2013 +"2013-05-08","Den vitezstvi","CZ",2013 +"2013-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2013 +"2013-07-06","Den upaleni mistra Jana Husa","CZ",2013 +"2013-09-28","Den ceske statnosti","CZ",2013 +"2013-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2013 +"2013-11-17","Den boje za svobodu a demokracii","CZ",2013 +"2013-12-24","Stedry den","CZ",2013 +"2013-12-25","1. svatek vanocni","CZ",2013 +"2013-12-26","2. svatek vanocni","CZ",2013 +"2014-01-01","Den obnovy samostatneho ceskeho statu","CZ",2014 +"2014-04-21","Velikonocni pondeli","CZ",2014 +"2014-05-01","Svatek prace","CZ",2014 +"2014-05-08","Den vitezstvi","CZ",2014 +"2014-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2014 +"2014-07-06","Den upaleni mistra Jana Husa","CZ",2014 +"2014-09-28","Den ceske statnosti","CZ",2014 +"2014-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2014 +"2014-11-17","Den boje za svobodu a demokracii","CZ",2014 +"2014-12-24","Stedry den","CZ",2014 +"2014-12-25","1. svatek vanocni","CZ",2014 +"2014-12-26","2. svatek vanocni","CZ",2014 +"2015-01-01","Den obnovy samostatneho ceskeho statu","CZ",2015 +"2015-04-06","Velikonocni pondeli","CZ",2015 +"2015-05-01","Svatek prace","CZ",2015 +"2015-05-08","Den vitezstvi","CZ",2015 +"2015-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2015 +"2015-07-06","Den upaleni mistra Jana Husa","CZ",2015 +"2015-09-28","Den ceske statnosti","CZ",2015 +"2015-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2015 +"2015-11-17","Den boje za svobodu a demokracii","CZ",2015 +"2015-12-24","Stedry den","CZ",2015 +"2015-12-25","1. svatek vanocni","CZ",2015 +"2015-12-26","2. svatek vanocni","CZ",2015 +"2016-01-01","Den obnovy samostatneho ceskeho statu","CZ",2016 +"2016-03-25","Velky patek","CZ",2016 +"2016-03-28","Velikonocni pondeli","CZ",2016 +"2016-05-01","Svatek prace","CZ",2016 +"2016-05-08","Den vitezstvi","CZ",2016 +"2016-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2016 +"2016-07-06","Den upaleni mistra Jana Husa","CZ",2016 +"2016-09-28","Den ceske statnosti","CZ",2016 +"2016-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2016 +"2016-11-17","Den boje za svobodu a demokracii","CZ",2016 +"2016-12-24","Stedry den","CZ",2016 +"2016-12-25","1. svatek vanocni","CZ",2016 +"2016-12-26","2. svatek vanocni","CZ",2016 +"2017-01-01","Den obnovy samostatneho ceskeho statu","CZ",2017 +"2017-04-14","Velky patek","CZ",2017 +"2017-04-17","Velikonocni pondeli","CZ",2017 +"2017-05-01","Svatek prace","CZ",2017 +"2017-05-08","Den vitezstvi","CZ",2017 +"2017-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2017 +"2017-07-06","Den upaleni mistra Jana Husa","CZ",2017 +"2017-09-28","Den ceske statnosti","CZ",2017 +"2017-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2017 +"2017-11-17","Den boje za svobodu a demokracii","CZ",2017 +"2017-12-24","Stedry den","CZ",2017 +"2017-12-25","1. svatek vanocni","CZ",2017 +"2017-12-26","2. svatek vanocni","CZ",2017 +"2018-01-01","Den obnovy samostatneho ceskeho statu","CZ",2018 +"2018-03-30","Velky patek","CZ",2018 +"2018-04-02","Velikonocni pondeli","CZ",2018 +"2018-05-01","Svatek prace","CZ",2018 +"2018-05-08","Den vitezstvi","CZ",2018 +"2018-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2018 +"2018-07-06","Den upaleni mistra Jana Husa","CZ",2018 +"2018-09-28","Den ceske statnosti","CZ",2018 +"2018-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2018 +"2018-11-17","Den boje za svobodu a demokracii","CZ",2018 +"2018-12-24","Stedry den","CZ",2018 +"2018-12-25","1. svatek vanocni","CZ",2018 +"2018-12-26","2. svatek vanocni","CZ",2018 +"2019-01-01","Den obnovy samostatneho ceskeho statu","CZ",2019 +"2019-04-19","Velky patek","CZ",2019 +"2019-04-22","Velikonocni pondeli","CZ",2019 +"2019-05-01","Svatek prace","CZ",2019 +"2019-05-08","Den vitezstvi","CZ",2019 +"2019-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2019 +"2019-07-06","Den upaleni mistra Jana Husa","CZ",2019 +"2019-09-28","Den ceske statnosti","CZ",2019 +"2019-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2019 +"2019-11-17","Den boje za svobodu a demokracii","CZ",2019 +"2019-12-24","Stedry den","CZ",2019 +"2019-12-25","1. svatek vanocni","CZ",2019 +"2019-12-26","2. svatek vanocni","CZ",2019 +"2020-01-01","Den obnovy samostatneho ceskeho statu","CZ",2020 +"2020-04-10","Velky patek","CZ",2020 +"2020-04-13","Velikonocni pondeli","CZ",2020 +"2020-05-01","Svatek prace","CZ",2020 +"2020-05-08","Den vitezstvi","CZ",2020 +"2020-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2020 +"2020-07-06","Den upaleni mistra Jana Husa","CZ",2020 +"2020-09-28","Den ceske statnosti","CZ",2020 +"2020-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2020 +"2020-11-17","Den boje za svobodu a demokracii","CZ",2020 +"2020-12-24","Stedry den","CZ",2020 +"2020-12-25","1. svatek vanocni","CZ",2020 +"2020-12-26","2. svatek vanocni","CZ",2020 +"2021-01-01","Den obnovy samostatneho ceskeho statu","CZ",2021 +"2021-04-02","Velky patek","CZ",2021 +"2021-04-05","Velikonocni pondeli","CZ",2021 +"2021-05-01","Svatek prace","CZ",2021 +"2021-05-08","Den vitezstvi","CZ",2021 +"2021-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2021 +"2021-07-06","Den upaleni mistra Jana Husa","CZ",2021 +"2021-09-28","Den ceske statnosti","CZ",2021 +"2021-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2021 +"2021-11-17","Den boje za svobodu a demokracii","CZ",2021 +"2021-12-24","Stedry den","CZ",2021 +"2021-12-25","1. svatek vanocni","CZ",2021 +"2021-12-26","2. svatek vanocni","CZ",2021 +"2022-01-01","Den obnovy samostatneho ceskeho statu","CZ",2022 +"2022-04-15","Velky patek","CZ",2022 +"2022-04-18","Velikonocni pondeli","CZ",2022 +"2022-05-01","Svatek prace","CZ",2022 +"2022-05-08","Den vitezstvi","CZ",2022 +"2022-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2022 +"2022-07-06","Den upaleni mistra Jana Husa","CZ",2022 +"2022-09-28","Den ceske statnosti","CZ",2022 +"2022-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2022 +"2022-11-17","Den boje za svobodu a demokracii","CZ",2022 +"2022-12-24","Stedry den","CZ",2022 +"2022-12-25","1. svatek vanocni","CZ",2022 +"2022-12-26","2. svatek vanocni","CZ",2022 +"2023-01-01","Den obnovy samostatneho ceskeho statu","CZ",2023 +"2023-04-07","Velky patek","CZ",2023 +"2023-04-10","Velikonocni pondeli","CZ",2023 +"2023-05-01","Svatek prace","CZ",2023 +"2023-05-08","Den vitezstvi","CZ",2023 +"2023-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2023 +"2023-07-06","Den upaleni mistra Jana Husa","CZ",2023 +"2023-09-28","Den ceske statnosti","CZ",2023 +"2023-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2023 +"2023-11-17","Den boje za svobodu a demokracii","CZ",2023 +"2023-12-24","Stedry den","CZ",2023 +"2023-12-25","1. svatek vanocni","CZ",2023 +"2023-12-26","2. svatek vanocni","CZ",2023 +"2024-01-01","Den obnovy samostatneho ceskeho statu","CZ",2024 +"2024-03-29","Velky patek","CZ",2024 +"2024-04-01","Velikonocni pondeli","CZ",2024 +"2024-05-01","Svatek prace","CZ",2024 +"2024-05-08","Den vitezstvi","CZ",2024 +"2024-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2024 +"2024-07-06","Den upaleni mistra Jana Husa","CZ",2024 +"2024-09-28","Den ceske statnosti","CZ",2024 +"2024-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2024 +"2024-11-17","Den boje za svobodu a demokracii","CZ",2024 +"2024-12-24","Stedry den","CZ",2024 +"2024-12-25","1. svatek vanocni","CZ",2024 +"2024-12-26","2. svatek vanocni","CZ",2024 +"2025-01-01","Den obnovy samostatneho ceskeho statu","CZ",2025 +"2025-04-18","Velky patek","CZ",2025 +"2025-04-21","Velikonocni pondeli","CZ",2025 +"2025-05-01","Svatek prace","CZ",2025 +"2025-05-08","Den vitezstvi","CZ",2025 +"2025-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2025 +"2025-07-06","Den upaleni mistra Jana Husa","CZ",2025 +"2025-09-28","Den ceske statnosti","CZ",2025 +"2025-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2025 +"2025-11-17","Den boje za svobodu a demokracii","CZ",2025 +"2025-12-24","Stedry den","CZ",2025 +"2025-12-25","1. svatek vanocni","CZ",2025 +"2025-12-26","2. svatek vanocni","CZ",2025 +"2026-01-01","Den obnovy samostatneho ceskeho statu","CZ",2026 +"2026-04-03","Velky patek","CZ",2026 +"2026-04-06","Velikonocni pondeli","CZ",2026 +"2026-05-01","Svatek prace","CZ",2026 +"2026-05-08","Den vitezstvi","CZ",2026 +"2026-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2026 +"2026-07-06","Den upaleni mistra Jana Husa","CZ",2026 +"2026-09-28","Den ceske statnosti","CZ",2026 +"2026-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2026 +"2026-11-17","Den boje za svobodu a demokracii","CZ",2026 +"2026-12-24","Stedry den","CZ",2026 +"2026-12-25","1. svatek vanocni","CZ",2026 +"2026-12-26","2. svatek vanocni","CZ",2026 +"2027-01-01","Den obnovy samostatneho ceskeho statu","CZ",2027 +"2027-03-26","Velky patek","CZ",2027 +"2027-03-29","Velikonocni pondeli","CZ",2027 +"2027-05-01","Svatek prace","CZ",2027 +"2027-05-08","Den vitezstvi","CZ",2027 +"2027-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2027 +"2027-07-06","Den upaleni mistra Jana Husa","CZ",2027 +"2027-09-28","Den ceske statnosti","CZ",2027 +"2027-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2027 +"2027-11-17","Den boje za svobodu a demokracii","CZ",2027 +"2027-12-24","Stedry den","CZ",2027 +"2027-12-25","1. svatek vanocni","CZ",2027 +"2027-12-26","2. svatek vanocni","CZ",2027 +"2028-01-01","Den obnovy samostatneho ceskeho statu","CZ",2028 +"2028-04-14","Velky patek","CZ",2028 +"2028-04-17","Velikonocni pondeli","CZ",2028 +"2028-05-01","Svatek prace","CZ",2028 +"2028-05-08","Den vitezstvi","CZ",2028 +"2028-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2028 +"2028-07-06","Den upaleni mistra Jana Husa","CZ",2028 +"2028-09-28","Den ceske statnosti","CZ",2028 +"2028-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2028 +"2028-11-17","Den boje za svobodu a demokracii","CZ",2028 +"2028-12-24","Stedry den","CZ",2028 +"2028-12-25","1. svatek vanocni","CZ",2028 +"2028-12-26","2. svatek vanocni","CZ",2028 +"2029-01-01","Den obnovy samostatneho ceskeho statu","CZ",2029 +"2029-03-30","Velky patek","CZ",2029 +"2029-04-02","Velikonocni pondeli","CZ",2029 +"2029-05-01","Svatek prace","CZ",2029 +"2029-05-08","Den vitezstvi","CZ",2029 +"2029-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2029 +"2029-07-06","Den upaleni mistra Jana Husa","CZ",2029 +"2029-09-28","Den ceske statnosti","CZ",2029 +"2029-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2029 +"2029-11-17","Den boje za svobodu a demokracii","CZ",2029 +"2029-12-24","Stedry den","CZ",2029 +"2029-12-25","1. svatek vanocni","CZ",2029 +"2029-12-26","2. svatek vanocni","CZ",2029 +"2030-01-01","Den obnovy samostatneho ceskeho statu","CZ",2030 +"2030-04-19","Velky patek","CZ",2030 +"2030-04-22","Velikonocni pondeli","CZ",2030 +"2030-05-01","Svatek prace","CZ",2030 +"2030-05-08","Den vitezstvi","CZ",2030 +"2030-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2030 +"2030-07-06","Den upaleni mistra Jana Husa","CZ",2030 +"2030-09-28","Den ceske statnosti","CZ",2030 +"2030-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2030 +"2030-11-17","Den boje za svobodu a demokracii","CZ",2030 +"2030-12-24","Stedry den","CZ",2030 +"2030-12-25","1. svatek vanocni","CZ",2030 +"2030-12-26","2. svatek vanocni","CZ",2030 +"2031-01-01","Den obnovy samostatneho ceskeho statu","CZ",2031 +"2031-04-11","Velky patek","CZ",2031 +"2031-04-14","Velikonocni pondeli","CZ",2031 +"2031-05-01","Svatek prace","CZ",2031 +"2031-05-08","Den vitezstvi","CZ",2031 +"2031-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2031 +"2031-07-06","Den upaleni mistra Jana Husa","CZ",2031 +"2031-09-28","Den ceske statnosti","CZ",2031 +"2031-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2031 +"2031-11-17","Den boje za svobodu a demokracii","CZ",2031 +"2031-12-24","Stedry den","CZ",2031 +"2031-12-25","1. svatek vanocni","CZ",2031 +"2031-12-26","2. svatek vanocni","CZ",2031 +"2032-01-01","Den obnovy samostatneho ceskeho statu","CZ",2032 +"2032-03-26","Velky patek","CZ",2032 +"2032-03-29","Velikonocni pondeli","CZ",2032 +"2032-05-01","Svatek prace","CZ",2032 +"2032-05-08","Den vitezstvi","CZ",2032 +"2032-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2032 +"2032-07-06","Den upaleni mistra Jana Husa","CZ",2032 +"2032-09-28","Den ceske statnosti","CZ",2032 +"2032-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2032 +"2032-11-17","Den boje za svobodu a demokracii","CZ",2032 +"2032-12-24","Stedry den","CZ",2032 +"2032-12-25","1. svatek vanocni","CZ",2032 +"2032-12-26","2. svatek vanocni","CZ",2032 +"2033-01-01","Den obnovy samostatneho ceskeho statu","CZ",2033 +"2033-04-15","Velky patek","CZ",2033 +"2033-04-18","Velikonocni pondeli","CZ",2033 +"2033-05-01","Svatek prace","CZ",2033 +"2033-05-08","Den vitezstvi","CZ",2033 +"2033-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2033 +"2033-07-06","Den upaleni mistra Jana Husa","CZ",2033 +"2033-09-28","Den ceske statnosti","CZ",2033 +"2033-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2033 +"2033-11-17","Den boje za svobodu a demokracii","CZ",2033 +"2033-12-24","Stedry den","CZ",2033 +"2033-12-25","1. svatek vanocni","CZ",2033 +"2033-12-26","2. svatek vanocni","CZ",2033 +"2034-01-01","Den obnovy samostatneho ceskeho statu","CZ",2034 +"2034-04-07","Velky patek","CZ",2034 +"2034-04-10","Velikonocni pondeli","CZ",2034 +"2034-05-01","Svatek prace","CZ",2034 +"2034-05-08","Den vitezstvi","CZ",2034 +"2034-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2034 +"2034-07-06","Den upaleni mistra Jana Husa","CZ",2034 +"2034-09-28","Den ceske statnosti","CZ",2034 +"2034-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2034 +"2034-11-17","Den boje za svobodu a demokracii","CZ",2034 +"2034-12-24","Stedry den","CZ",2034 +"2034-12-25","1. svatek vanocni","CZ",2034 +"2034-12-26","2. svatek vanocni","CZ",2034 +"2035-01-01","Den obnovy samostatneho ceskeho statu","CZ",2035 +"2035-03-23","Velky patek","CZ",2035 +"2035-03-26","Velikonocni pondeli","CZ",2035 +"2035-05-01","Svatek prace","CZ",2035 +"2035-05-08","Den vitezstvi","CZ",2035 +"2035-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2035 +"2035-07-06","Den upaleni mistra Jana Husa","CZ",2035 +"2035-09-28","Den ceske statnosti","CZ",2035 +"2035-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2035 +"2035-11-17","Den boje za svobodu a demokracii","CZ",2035 +"2035-12-24","Stedry den","CZ",2035 +"2035-12-25","1. svatek vanocni","CZ",2035 +"2035-12-26","2. svatek vanocni","CZ",2035 +"2036-01-01","Den obnovy samostatneho ceskeho statu","CZ",2036 +"2036-04-11","Velky patek","CZ",2036 +"2036-04-14","Velikonocni pondeli","CZ",2036 +"2036-05-01","Svatek prace","CZ",2036 +"2036-05-08","Den vitezstvi","CZ",2036 +"2036-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2036 +"2036-07-06","Den upaleni mistra Jana Husa","CZ",2036 +"2036-09-28","Den ceske statnosti","CZ",2036 +"2036-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2036 +"2036-11-17","Den boje za svobodu a demokracii","CZ",2036 +"2036-12-24","Stedry den","CZ",2036 +"2036-12-25","1. svatek vanocni","CZ",2036 +"2036-12-26","2. svatek vanocni","CZ",2036 +"2037-01-01","Den obnovy samostatneho ceskeho statu","CZ",2037 +"2037-04-03","Velky patek","CZ",2037 +"2037-04-06","Velikonocni pondeli","CZ",2037 +"2037-05-01","Svatek prace","CZ",2037 +"2037-05-08","Den vitezstvi","CZ",2037 +"2037-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2037 +"2037-07-06","Den upaleni mistra Jana Husa","CZ",2037 +"2037-09-28","Den ceske statnosti","CZ",2037 +"2037-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2037 +"2037-11-17","Den boje za svobodu a demokracii","CZ",2037 +"2037-12-24","Stedry den","CZ",2037 +"2037-12-25","1. svatek vanocni","CZ",2037 +"2037-12-26","2. svatek vanocni","CZ",2037 +"2038-01-01","Den obnovy samostatneho ceskeho statu","CZ",2038 +"2038-04-23","Velky patek","CZ",2038 +"2038-04-26","Velikonocni pondeli","CZ",2038 +"2038-05-01","Svatek prace","CZ",2038 +"2038-05-08","Den vitezstvi","CZ",2038 +"2038-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2038 +"2038-07-06","Den upaleni mistra Jana Husa","CZ",2038 +"2038-09-28","Den ceske statnosti","CZ",2038 +"2038-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2038 +"2038-11-17","Den boje za svobodu a demokracii","CZ",2038 +"2038-12-24","Stedry den","CZ",2038 +"2038-12-25","1. svatek vanocni","CZ",2038 +"2038-12-26","2. svatek vanocni","CZ",2038 +"2039-01-01","Den obnovy samostatneho ceskeho statu","CZ",2039 +"2039-04-08","Velky patek","CZ",2039 +"2039-04-11","Velikonocni pondeli","CZ",2039 +"2039-05-01","Svatek prace","CZ",2039 +"2039-05-08","Den vitezstvi","CZ",2039 +"2039-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2039 +"2039-07-06","Den upaleni mistra Jana Husa","CZ",2039 +"2039-09-28","Den ceske statnosti","CZ",2039 +"2039-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2039 +"2039-11-17","Den boje za svobodu a demokracii","CZ",2039 +"2039-12-24","Stedry den","CZ",2039 +"2039-12-25","1. svatek vanocni","CZ",2039 +"2039-12-26","2. svatek vanocni","CZ",2039 +"2040-01-01","Den obnovy samostatneho ceskeho statu","CZ",2040 +"2040-03-30","Velky patek","CZ",2040 +"2040-04-02","Velikonocni pondeli","CZ",2040 +"2040-05-01","Svatek prace","CZ",2040 +"2040-05-08","Den vitezstvi","CZ",2040 +"2040-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2040 +"2040-07-06","Den upaleni mistra Jana Husa","CZ",2040 +"2040-09-28","Den ceske statnosti","CZ",2040 +"2040-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2040 +"2040-11-17","Den boje za svobodu a demokracii","CZ",2040 +"2040-12-24","Stedry den","CZ",2040 +"2040-12-25","1. svatek vanocni","CZ",2040 +"2040-12-26","2. svatek vanocni","CZ",2040 +"2041-01-01","Den obnovy samostatneho ceskeho statu","CZ",2041 +"2041-04-19","Velky patek","CZ",2041 +"2041-04-22","Velikonocni pondeli","CZ",2041 +"2041-05-01","Svatek prace","CZ",2041 +"2041-05-08","Den vitezstvi","CZ",2041 +"2041-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2041 +"2041-07-06","Den upaleni mistra Jana Husa","CZ",2041 +"2041-09-28","Den ceske statnosti","CZ",2041 +"2041-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2041 +"2041-11-17","Den boje za svobodu a demokracii","CZ",2041 +"2041-12-24","Stedry den","CZ",2041 +"2041-12-25","1. svatek vanocni","CZ",2041 +"2041-12-26","2. svatek vanocni","CZ",2041 +"2042-01-01","Den obnovy samostatneho ceskeho statu","CZ",2042 +"2042-04-04","Velky patek","CZ",2042 +"2042-04-07","Velikonocni pondeli","CZ",2042 +"2042-05-01","Svatek prace","CZ",2042 +"2042-05-08","Den vitezstvi","CZ",2042 +"2042-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2042 +"2042-07-06","Den upaleni mistra Jana Husa","CZ",2042 +"2042-09-28","Den ceske statnosti","CZ",2042 +"2042-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2042 +"2042-11-17","Den boje za svobodu a demokracii","CZ",2042 +"2042-12-24","Stedry den","CZ",2042 +"2042-12-25","1. svatek vanocni","CZ",2042 +"2042-12-26","2. svatek vanocni","CZ",2042 +"2043-01-01","Den obnovy samostatneho ceskeho statu","CZ",2043 +"2043-03-27","Velky patek","CZ",2043 +"2043-03-30","Velikonocni pondeli","CZ",2043 +"2043-05-01","Svatek prace","CZ",2043 +"2043-05-08","Den vitezstvi","CZ",2043 +"2043-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2043 +"2043-07-06","Den upaleni mistra Jana Husa","CZ",2043 +"2043-09-28","Den ceske statnosti","CZ",2043 +"2043-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2043 +"2043-11-17","Den boje za svobodu a demokracii","CZ",2043 +"2043-12-24","Stedry den","CZ",2043 +"2043-12-25","1. svatek vanocni","CZ",2043 +"2043-12-26","2. svatek vanocni","CZ",2043 +"2044-01-01","Den obnovy samostatneho ceskeho statu","CZ",2044 +"2044-04-15","Velky patek","CZ",2044 +"2044-04-18","Velikonocni pondeli","CZ",2044 +"2044-05-01","Svatek prace","CZ",2044 +"2044-05-08","Den vitezstvi","CZ",2044 +"2044-07-05","Den slovanskych verozvestu Cyrila a Metodeje","CZ",2044 +"2044-07-06","Den upaleni mistra Jana Husa","CZ",2044 +"2044-09-28","Den ceske statnosti","CZ",2044 +"2044-10-28","Den vzniku samostatneho ceskoslovenskeho statu","CZ",2044 +"2044-11-17","Den boje za svobodu a demokracii","CZ",2044 +"2044-12-24","Stedry den","CZ",2044 +"2044-12-25","1. svatek vanocni","CZ",2044 +"2044-12-26","2. svatek vanocni","CZ",2044 +"1995-01-01","New Year's Day","DE",1995 +"1995-04-14","Good Friday","DE",1995 +"1995-04-17","Easter Monday","DE",1995 +"1995-05-01","Labor Day","DE",1995 +"1995-05-25","Ascension Day","DE",1995 +"1995-06-05","Whit Monday","DE",1995 +"1995-10-03","German Unity Day","DE",1995 +"1995-12-25","Christmas Day","DE",1995 +"1995-12-26","Second Day of Christmas","DE",1995 +"1996-01-01","New Year's Day","DE",1996 +"1996-04-05","Good Friday","DE",1996 +"1996-04-08","Easter Monday","DE",1996 +"1996-05-01","Labor Day","DE",1996 +"1996-05-16","Ascension Day","DE",1996 +"1996-05-27","Whit Monday","DE",1996 +"1996-10-03","German Unity Day","DE",1996 +"1996-12-25","Christmas Day","DE",1996 +"1996-12-26","Second Day of Christmas","DE",1996 +"1997-01-01","New Year's Day","DE",1997 +"1997-03-28","Good Friday","DE",1997 +"1997-03-31","Easter Monday","DE",1997 +"1997-05-01","Labor Day","DE",1997 +"1997-05-08","Ascension Day","DE",1997 +"1997-05-19","Whit Monday","DE",1997 +"1997-10-03","German Unity Day","DE",1997 +"1997-12-25","Christmas Day","DE",1997 +"1997-12-26","Second Day of Christmas","DE",1997 +"1998-01-01","New Year's Day","DE",1998 +"1998-04-10","Good Friday","DE",1998 +"1998-04-13","Easter Monday","DE",1998 +"1998-05-01","Labor Day","DE",1998 +"1998-05-21","Ascension Day","DE",1998 +"1998-06-01","Whit Monday","DE",1998 +"1998-10-03","German Unity Day","DE",1998 +"1998-12-25","Christmas Day","DE",1998 +"1998-12-26","Second Day of Christmas","DE",1998 +"1999-01-01","New Year's Day","DE",1999 +"1999-04-02","Good Friday","DE",1999 +"1999-04-05","Easter Monday","DE",1999 +"1999-05-01","Labor Day","DE",1999 +"1999-05-13","Ascension Day","DE",1999 +"1999-05-24","Whit Monday","DE",1999 +"1999-10-03","German Unity Day","DE",1999 +"1999-12-25","Christmas Day","DE",1999 +"1999-12-26","Second Day of Christmas","DE",1999 +"2000-01-01","New Year's Day","DE",2000 +"2000-04-21","Good Friday","DE",2000 +"2000-04-24","Easter Monday","DE",2000 +"2000-05-01","Labor Day","DE",2000 +"2000-06-01","Ascension Day","DE",2000 +"2000-06-12","Whit Monday","DE",2000 +"2000-10-03","German Unity Day","DE",2000 +"2000-12-25","Christmas Day","DE",2000 +"2000-12-26","Second Day of Christmas","DE",2000 +"2001-01-01","New Year's Day","DE",2001 +"2001-04-13","Good Friday","DE",2001 +"2001-04-16","Easter Monday","DE",2001 +"2001-05-01","Labor Day","DE",2001 +"2001-05-24","Ascension Day","DE",2001 +"2001-06-04","Whit Monday","DE",2001 +"2001-10-03","German Unity Day","DE",2001 +"2001-12-25","Christmas Day","DE",2001 +"2001-12-26","Second Day of Christmas","DE",2001 +"2002-01-01","New Year's Day","DE",2002 +"2002-03-29","Good Friday","DE",2002 +"2002-04-01","Easter Monday","DE",2002 +"2002-05-01","Labor Day","DE",2002 +"2002-05-09","Ascension Day","DE",2002 +"2002-05-20","Whit Monday","DE",2002 +"2002-10-03","German Unity Day","DE",2002 +"2002-12-25","Christmas Day","DE",2002 +"2002-12-26","Second Day of Christmas","DE",2002 +"2003-01-01","New Year's Day","DE",2003 +"2003-04-18","Good Friday","DE",2003 +"2003-04-21","Easter Monday","DE",2003 +"2003-05-01","Labor Day","DE",2003 +"2003-05-29","Ascension Day","DE",2003 +"2003-06-09","Whit Monday","DE",2003 +"2003-10-03","German Unity Day","DE",2003 +"2003-12-25","Christmas Day","DE",2003 +"2003-12-26","Second Day of Christmas","DE",2003 +"2004-01-01","New Year's Day","DE",2004 +"2004-04-09","Good Friday","DE",2004 +"2004-04-12","Easter Monday","DE",2004 +"2004-05-01","Labor Day","DE",2004 +"2004-05-20","Ascension Day","DE",2004 +"2004-05-31","Whit Monday","DE",2004 +"2004-10-03","German Unity Day","DE",2004 +"2004-12-25","Christmas Day","DE",2004 +"2004-12-26","Second Day of Christmas","DE",2004 +"2005-01-01","New Year's Day","DE",2005 +"2005-03-25","Good Friday","DE",2005 +"2005-03-28","Easter Monday","DE",2005 +"2005-05-01","Labor Day","DE",2005 +"2005-05-05","Ascension Day","DE",2005 +"2005-05-16","Whit Monday","DE",2005 +"2005-10-03","German Unity Day","DE",2005 +"2005-12-25","Christmas Day","DE",2005 +"2005-12-26","Second Day of Christmas","DE",2005 +"2006-01-01","New Year's Day","DE",2006 +"2006-04-14","Good Friday","DE",2006 +"2006-04-17","Easter Monday","DE",2006 +"2006-05-01","Labor Day","DE",2006 +"2006-05-25","Ascension Day","DE",2006 +"2006-06-05","Whit Monday","DE",2006 +"2006-10-03","German Unity Day","DE",2006 +"2006-12-25","Christmas Day","DE",2006 +"2006-12-26","Second Day of Christmas","DE",2006 +"2007-01-01","New Year's Day","DE",2007 +"2007-04-06","Good Friday","DE",2007 +"2007-04-09","Easter Monday","DE",2007 +"2007-05-01","Labor Day","DE",2007 +"2007-05-17","Ascension Day","DE",2007 +"2007-05-28","Whit Monday","DE",2007 +"2007-10-03","German Unity Day","DE",2007 +"2007-12-25","Christmas Day","DE",2007 +"2007-12-26","Second Day of Christmas","DE",2007 +"2008-01-01","New Year's Day","DE",2008 +"2008-03-21","Good Friday","DE",2008 +"2008-03-24","Easter Monday","DE",2008 +"2008-05-01","Ascension Day","DE",2008 +"2008-05-01","Labor Day","DE",2008 +"2008-05-12","Whit Monday","DE",2008 +"2008-10-03","German Unity Day","DE",2008 +"2008-12-25","Christmas Day","DE",2008 +"2008-12-26","Second Day of Christmas","DE",2008 +"2009-01-01","New Year's Day","DE",2009 +"2009-04-10","Good Friday","DE",2009 +"2009-04-13","Easter Monday","DE",2009 +"2009-05-01","Labor Day","DE",2009 +"2009-05-21","Ascension Day","DE",2009 +"2009-06-01","Whit Monday","DE",2009 +"2009-10-03","German Unity Day","DE",2009 +"2009-12-25","Christmas Day","DE",2009 +"2009-12-26","Second Day of Christmas","DE",2009 +"2010-01-01","New Year's Day","DE",2010 +"2010-04-02","Good Friday","DE",2010 +"2010-04-05","Easter Monday","DE",2010 +"2010-05-01","Labor Day","DE",2010 +"2010-05-13","Ascension Day","DE",2010 +"2010-05-24","Whit Monday","DE",2010 +"2010-10-03","German Unity Day","DE",2010 +"2010-12-25","Christmas Day","DE",2010 +"2010-12-26","Second Day of Christmas","DE",2010 +"2011-01-01","New Year's Day","DE",2011 +"2011-04-22","Good Friday","DE",2011 +"2011-04-25","Easter Monday","DE",2011 +"2011-05-01","Labor Day","DE",2011 +"2011-06-02","Ascension Day","DE",2011 +"2011-06-13","Whit Monday","DE",2011 +"2011-10-03","German Unity Day","DE",2011 +"2011-12-25","Christmas Day","DE",2011 +"2011-12-26","Second Day of Christmas","DE",2011 +"2012-01-01","New Year's Day","DE",2012 +"2012-04-06","Good Friday","DE",2012 +"2012-04-09","Easter Monday","DE",2012 +"2012-05-01","Labor Day","DE",2012 +"2012-05-17","Ascension Day","DE",2012 +"2012-05-28","Whit Monday","DE",2012 +"2012-10-03","German Unity Day","DE",2012 +"2012-12-25","Christmas Day","DE",2012 +"2012-12-26","Second Day of Christmas","DE",2012 +"2013-01-01","New Year's Day","DE",2013 +"2013-03-29","Good Friday","DE",2013 +"2013-04-01","Easter Monday","DE",2013 +"2013-05-01","Labor Day","DE",2013 +"2013-05-09","Ascension Day","DE",2013 +"2013-05-20","Whit Monday","DE",2013 +"2013-10-03","German Unity Day","DE",2013 +"2013-12-25","Christmas Day","DE",2013 +"2013-12-26","Second Day of Christmas","DE",2013 +"2014-01-01","New Year's Day","DE",2014 +"2014-04-18","Good Friday","DE",2014 +"2014-04-21","Easter Monday","DE",2014 +"2014-05-01","Labor Day","DE",2014 +"2014-05-29","Ascension Day","DE",2014 +"2014-06-09","Whit Monday","DE",2014 +"2014-10-03","German Unity Day","DE",2014 +"2014-12-25","Christmas Day","DE",2014 +"2014-12-26","Second Day of Christmas","DE",2014 +"2015-01-01","New Year's Day","DE",2015 +"2015-04-03","Good Friday","DE",2015 +"2015-04-06","Easter Monday","DE",2015 +"2015-05-01","Labor Day","DE",2015 +"2015-05-14","Ascension Day","DE",2015 +"2015-05-25","Whit Monday","DE",2015 +"2015-10-03","German Unity Day","DE",2015 +"2015-12-25","Christmas Day","DE",2015 +"2015-12-26","Second Day of Christmas","DE",2015 +"2016-01-01","New Year's Day","DE",2016 +"2016-03-25","Good Friday","DE",2016 +"2016-03-28","Easter Monday","DE",2016 +"2016-05-01","Labor Day","DE",2016 +"2016-05-05","Ascension Day","DE",2016 +"2016-05-16","Whit Monday","DE",2016 +"2016-10-03","German Unity Day","DE",2016 +"2016-12-25","Christmas Day","DE",2016 +"2016-12-26","Second Day of Christmas","DE",2016 +"2017-01-01","New Year's Day","DE",2017 +"2017-04-14","Good Friday","DE",2017 +"2017-04-17","Easter Monday","DE",2017 +"2017-05-01","Labor Day","DE",2017 +"2017-05-25","Ascension Day","DE",2017 +"2017-06-05","Whit Monday","DE",2017 +"2017-10-03","German Unity Day","DE",2017 +"2017-10-31","Reformation Day","DE",2017 +"2017-12-25","Christmas Day","DE",2017 +"2017-12-26","Second Day of Christmas","DE",2017 +"2018-01-01","New Year's Day","DE",2018 +"2018-03-30","Good Friday","DE",2018 +"2018-04-02","Easter Monday","DE",2018 +"2018-05-01","Labor Day","DE",2018 +"2018-05-10","Ascension Day","DE",2018 +"2018-05-21","Whit Monday","DE",2018 +"2018-10-03","German Unity Day","DE",2018 +"2018-12-25","Christmas Day","DE",2018 +"2018-12-26","Second Day of Christmas","DE",2018 +"2019-01-01","New Year's Day","DE",2019 +"2019-04-19","Good Friday","DE",2019 +"2019-04-22","Easter Monday","DE",2019 +"2019-05-01","Labor Day","DE",2019 +"2019-05-30","Ascension Day","DE",2019 +"2019-06-10","Whit Monday","DE",2019 +"2019-10-03","German Unity Day","DE",2019 +"2019-12-25","Christmas Day","DE",2019 +"2019-12-26","Second Day of Christmas","DE",2019 +"2020-01-01","New Year's Day","DE",2020 +"2020-04-10","Good Friday","DE",2020 +"2020-04-13","Easter Monday","DE",2020 +"2020-05-01","Labor Day","DE",2020 +"2020-05-21","Ascension Day","DE",2020 +"2020-06-01","Whit Monday","DE",2020 +"2020-10-03","German Unity Day","DE",2020 +"2020-12-25","Christmas Day","DE",2020 +"2020-12-26","Second Day of Christmas","DE",2020 +"2021-01-01","New Year's Day","DE",2021 +"2021-04-02","Good Friday","DE",2021 +"2021-04-05","Easter Monday","DE",2021 +"2021-05-01","Labor Day","DE",2021 +"2021-05-13","Ascension Day","DE",2021 +"2021-05-24","Whit Monday","DE",2021 +"2021-10-03","German Unity Day","DE",2021 +"2021-12-25","Christmas Day","DE",2021 +"2021-12-26","Second Day of Christmas","DE",2021 +"2022-01-01","New Year's Day","DE",2022 +"2022-04-15","Good Friday","DE",2022 +"2022-04-18","Easter Monday","DE",2022 +"2022-05-01","Labor Day","DE",2022 +"2022-05-26","Ascension Day","DE",2022 +"2022-06-06","Whit Monday","DE",2022 +"2022-10-03","German Unity Day","DE",2022 +"2022-12-25","Christmas Day","DE",2022 +"2022-12-26","Second Day of Christmas","DE",2022 +"2023-01-01","New Year's Day","DE",2023 +"2023-04-07","Good Friday","DE",2023 +"2023-04-10","Easter Monday","DE",2023 +"2023-05-01","Labor Day","DE",2023 +"2023-05-18","Ascension Day","DE",2023 +"2023-05-29","Whit Monday","DE",2023 +"2023-10-03","German Unity Day","DE",2023 +"2023-12-25","Christmas Day","DE",2023 +"2023-12-26","Second Day of Christmas","DE",2023 +"2024-01-01","New Year's Day","DE",2024 +"2024-03-29","Good Friday","DE",2024 +"2024-04-01","Easter Monday","DE",2024 +"2024-05-01","Labor Day","DE",2024 +"2024-05-09","Ascension Day","DE",2024 +"2024-05-20","Whit Monday","DE",2024 +"2024-10-03","German Unity Day","DE",2024 +"2024-12-25","Christmas Day","DE",2024 +"2024-12-26","Second Day of Christmas","DE",2024 +"2025-01-01","New Year's Day","DE",2025 +"2025-04-18","Good Friday","DE",2025 +"2025-04-21","Easter Monday","DE",2025 +"2025-05-01","Labor Day","DE",2025 +"2025-05-29","Ascension Day","DE",2025 +"2025-06-09","Whit Monday","DE",2025 +"2025-10-03","German Unity Day","DE",2025 +"2025-12-25","Christmas Day","DE",2025 +"2025-12-26","Second Day of Christmas","DE",2025 +"2026-01-01","New Year's Day","DE",2026 +"2026-04-03","Good Friday","DE",2026 +"2026-04-06","Easter Monday","DE",2026 +"2026-05-01","Labor Day","DE",2026 +"2026-05-14","Ascension Day","DE",2026 +"2026-05-25","Whit Monday","DE",2026 +"2026-10-03","German Unity Day","DE",2026 +"2026-12-25","Christmas Day","DE",2026 +"2026-12-26","Second Day of Christmas","DE",2026 +"2027-01-01","New Year's Day","DE",2027 +"2027-03-26","Good Friday","DE",2027 +"2027-03-29","Easter Monday","DE",2027 +"2027-05-01","Labor Day","DE",2027 +"2027-05-06","Ascension Day","DE",2027 +"2027-05-17","Whit Monday","DE",2027 +"2027-10-03","German Unity Day","DE",2027 +"2027-12-25","Christmas Day","DE",2027 +"2027-12-26","Second Day of Christmas","DE",2027 +"2028-01-01","New Year's Day","DE",2028 +"2028-04-14","Good Friday","DE",2028 +"2028-04-17","Easter Monday","DE",2028 +"2028-05-01","Labor Day","DE",2028 +"2028-05-25","Ascension Day","DE",2028 +"2028-06-05","Whit Monday","DE",2028 +"2028-10-03","German Unity Day","DE",2028 +"2028-12-25","Christmas Day","DE",2028 +"2028-12-26","Second Day of Christmas","DE",2028 +"2029-01-01","New Year's Day","DE",2029 +"2029-03-30","Good Friday","DE",2029 +"2029-04-02","Easter Monday","DE",2029 +"2029-05-01","Labor Day","DE",2029 +"2029-05-10","Ascension Day","DE",2029 +"2029-05-21","Whit Monday","DE",2029 +"2029-10-03","German Unity Day","DE",2029 +"2029-12-25","Christmas Day","DE",2029 +"2029-12-26","Second Day of Christmas","DE",2029 +"2030-01-01","New Year's Day","DE",2030 +"2030-04-19","Good Friday","DE",2030 +"2030-04-22","Easter Monday","DE",2030 +"2030-05-01","Labor Day","DE",2030 +"2030-05-30","Ascension Day","DE",2030 +"2030-06-10","Whit Monday","DE",2030 +"2030-10-03","German Unity Day","DE",2030 +"2030-12-25","Christmas Day","DE",2030 +"2030-12-26","Second Day of Christmas","DE",2030 +"2031-01-01","New Year's Day","DE",2031 +"2031-04-11","Good Friday","DE",2031 +"2031-04-14","Easter Monday","DE",2031 +"2031-05-01","Labor Day","DE",2031 +"2031-05-22","Ascension Day","DE",2031 +"2031-06-02","Whit Monday","DE",2031 +"2031-10-03","German Unity Day","DE",2031 +"2031-12-25","Christmas Day","DE",2031 +"2031-12-26","Second Day of Christmas","DE",2031 +"2032-01-01","New Year's Day","DE",2032 +"2032-03-26","Good Friday","DE",2032 +"2032-03-29","Easter Monday","DE",2032 +"2032-05-01","Labor Day","DE",2032 +"2032-05-06","Ascension Day","DE",2032 +"2032-05-17","Whit Monday","DE",2032 +"2032-10-03","German Unity Day","DE",2032 +"2032-12-25","Christmas Day","DE",2032 +"2032-12-26","Second Day of Christmas","DE",2032 +"2033-01-01","New Year's Day","DE",2033 +"2033-04-15","Good Friday","DE",2033 +"2033-04-18","Easter Monday","DE",2033 +"2033-05-01","Labor Day","DE",2033 +"2033-05-26","Ascension Day","DE",2033 +"2033-06-06","Whit Monday","DE",2033 +"2033-10-03","German Unity Day","DE",2033 +"2033-12-25","Christmas Day","DE",2033 +"2033-12-26","Second Day of Christmas","DE",2033 +"2034-01-01","New Year's Day","DE",2034 +"2034-04-07","Good Friday","DE",2034 +"2034-04-10","Easter Monday","DE",2034 +"2034-05-01","Labor Day","DE",2034 +"2034-05-18","Ascension Day","DE",2034 +"2034-05-29","Whit Monday","DE",2034 +"2034-10-03","German Unity Day","DE",2034 +"2034-12-25","Christmas Day","DE",2034 +"2034-12-26","Second Day of Christmas","DE",2034 +"2035-01-01","New Year's Day","DE",2035 +"2035-03-23","Good Friday","DE",2035 +"2035-03-26","Easter Monday","DE",2035 +"2035-05-01","Labor Day","DE",2035 +"2035-05-03","Ascension Day","DE",2035 +"2035-05-14","Whit Monday","DE",2035 +"2035-10-03","German Unity Day","DE",2035 +"2035-12-25","Christmas Day","DE",2035 +"2035-12-26","Second Day of Christmas","DE",2035 +"2036-01-01","New Year's Day","DE",2036 +"2036-04-11","Good Friday","DE",2036 +"2036-04-14","Easter Monday","DE",2036 +"2036-05-01","Labor Day","DE",2036 +"2036-05-22","Ascension Day","DE",2036 +"2036-06-02","Whit Monday","DE",2036 +"2036-10-03","German Unity Day","DE",2036 +"2036-12-25","Christmas Day","DE",2036 +"2036-12-26","Second Day of Christmas","DE",2036 +"2037-01-01","New Year's Day","DE",2037 +"2037-04-03","Good Friday","DE",2037 +"2037-04-06","Easter Monday","DE",2037 +"2037-05-01","Labor Day","DE",2037 +"2037-05-14","Ascension Day","DE",2037 +"2037-05-25","Whit Monday","DE",2037 +"2037-10-03","German Unity Day","DE",2037 +"2037-12-25","Christmas Day","DE",2037 +"2037-12-26","Second Day of Christmas","DE",2037 +"2038-01-01","New Year's Day","DE",2038 +"2038-04-23","Good Friday","DE",2038 +"2038-04-26","Easter Monday","DE",2038 +"2038-05-01","Labor Day","DE",2038 +"2038-06-03","Ascension Day","DE",2038 +"2038-06-14","Whit Monday","DE",2038 +"2038-10-03","German Unity Day","DE",2038 +"2038-12-25","Christmas Day","DE",2038 +"2038-12-26","Second Day of Christmas","DE",2038 +"2039-01-01","New Year's Day","DE",2039 +"2039-04-08","Good Friday","DE",2039 +"2039-04-11","Easter Monday","DE",2039 +"2039-05-01","Labor Day","DE",2039 +"2039-05-19","Ascension Day","DE",2039 +"2039-05-30","Whit Monday","DE",2039 +"2039-10-03","German Unity Day","DE",2039 +"2039-12-25","Christmas Day","DE",2039 +"2039-12-26","Second Day of Christmas","DE",2039 +"2040-01-01","New Year's Day","DE",2040 +"2040-03-30","Good Friday","DE",2040 +"2040-04-02","Easter Monday","DE",2040 +"2040-05-01","Labor Day","DE",2040 +"2040-05-10","Ascension Day","DE",2040 +"2040-05-21","Whit Monday","DE",2040 +"2040-10-03","German Unity Day","DE",2040 +"2040-12-25","Christmas Day","DE",2040 +"2040-12-26","Second Day of Christmas","DE",2040 +"2041-01-01","New Year's Day","DE",2041 +"2041-04-19","Good Friday","DE",2041 +"2041-04-22","Easter Monday","DE",2041 +"2041-05-01","Labor Day","DE",2041 +"2041-05-30","Ascension Day","DE",2041 +"2041-06-10","Whit Monday","DE",2041 +"2041-10-03","German Unity Day","DE",2041 +"2041-12-25","Christmas Day","DE",2041 +"2041-12-26","Second Day of Christmas","DE",2041 +"2042-01-01","New Year's Day","DE",2042 +"2042-04-04","Good Friday","DE",2042 +"2042-04-07","Easter Monday","DE",2042 +"2042-05-01","Labor Day","DE",2042 +"2042-05-15","Ascension Day","DE",2042 +"2042-05-26","Whit Monday","DE",2042 +"2042-10-03","German Unity Day","DE",2042 +"2042-12-25","Christmas Day","DE",2042 +"2042-12-26","Second Day of Christmas","DE",2042 +"2043-01-01","New Year's Day","DE",2043 +"2043-03-27","Good Friday","DE",2043 +"2043-03-30","Easter Monday","DE",2043 +"2043-05-01","Labor Day","DE",2043 +"2043-05-07","Ascension Day","DE",2043 +"2043-05-18","Whit Monday","DE",2043 +"2043-10-03","German Unity Day","DE",2043 +"2043-12-25","Christmas Day","DE",2043 +"2043-12-26","Second Day of Christmas","DE",2043 +"2044-01-01","New Year's Day","DE",2044 +"2044-04-15","Good Friday","DE",2044 +"2044-04-18","Easter Monday","DE",2044 +"2044-05-01","Labor Day","DE",2044 +"2044-05-26","Ascension Day","DE",2044 +"2044-06-06","Whit Monday","DE",2044 +"2044-10-03","German Unity Day","DE",2044 +"2044-12-25","Christmas Day","DE",2044 +"2044-12-26","Second Day of Christmas","DE",2044 +"1995-01-01","Nouvel an","DJ",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","DJ",1995 +"1995-03-03","Eid al-Fitr deuxieme jour* (*estimated)","DJ",1995 +"1995-05-01","Fete du travail","DJ",1995 +"1995-05-08","Arafat* (*estimated)","DJ",1995 +"1995-05-09","Eid al-Adha* (*estimated)","DJ",1995 +"1995-05-10","Eid al-Adha deuxieme jour* (*estimated)","DJ",1995 +"1995-05-30","Nouvel an musulman* (*estimated)","DJ",1995 +"1995-06-27","Fete de l'independance","DJ",1995 +"1995-06-28","Fete de l'independance","DJ",1995 +"1995-08-08","Naissance du prophet Muhammad* (*estimated)","DJ",1995 +"1995-12-19","Isra wal Miraj* (*estimated)","DJ",1995 +"1996-01-01","Nouvel an","DJ",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","DJ",1996 +"1996-02-20","Eid al-Fitr deuxieme jour* (*estimated)","DJ",1996 +"1996-04-26","Arafat* (*estimated)","DJ",1996 +"1996-04-27","Eid al-Adha* (*estimated)","DJ",1996 +"1996-04-28","Eid al-Adha deuxieme jour* (*estimated)","DJ",1996 +"1996-05-01","Fete du travail","DJ",1996 +"1996-05-18","Nouvel an musulman* (*estimated)","DJ",1996 +"1996-06-27","Fete de l'independance","DJ",1996 +"1996-06-28","Fete de l'independance","DJ",1996 +"1996-07-27","Naissance du prophet Muhammad* (*estimated)","DJ",1996 +"1996-12-08","Isra wal Miraj* (*estimated)","DJ",1996 +"1997-01-01","Nouvel an","DJ",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","DJ",1997 +"1997-02-09","Eid al-Fitr deuxieme jour* (*estimated)","DJ",1997 +"1997-04-16","Arafat* (*estimated)","DJ",1997 +"1997-04-17","Eid al-Adha* (*estimated)","DJ",1997 +"1997-04-18","Eid al-Adha deuxieme jour* (*estimated)","DJ",1997 +"1997-05-01","Fete du travail","DJ",1997 +"1997-05-07","Nouvel an musulman* (*estimated)","DJ",1997 +"1997-06-27","Fete de l'independance","DJ",1997 +"1997-06-28","Fete de l'independance","DJ",1997 +"1997-07-16","Naissance du prophet Muhammad* (*estimated)","DJ",1997 +"1997-11-27","Isra wal Miraj* (*estimated)","DJ",1997 +"1998-01-01","Nouvel an","DJ",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","DJ",1998 +"1998-01-30","Eid al-Fitr deuxieme jour* (*estimated)","DJ",1998 +"1998-04-06","Arafat* (*estimated)","DJ",1998 +"1998-04-07","Eid al-Adha* (*estimated)","DJ",1998 +"1998-04-08","Eid al-Adha deuxieme jour* (*estimated)","DJ",1998 +"1998-04-27","Nouvel an musulman* (*estimated)","DJ",1998 +"1998-05-01","Fete du travail","DJ",1998 +"1998-06-27","Fete de l'independance","DJ",1998 +"1998-06-28","Fete de l'independance","DJ",1998 +"1998-07-06","Naissance du prophet Muhammad* (*estimated)","DJ",1998 +"1998-11-16","Isra wal Miraj* (*estimated)","DJ",1998 +"1999-01-01","Nouvel an","DJ",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","DJ",1999 +"1999-01-19","Eid al-Fitr deuxieme jour* (*estimated)","DJ",1999 +"1999-03-26","Arafat* (*estimated)","DJ",1999 +"1999-03-27","Eid al-Adha* (*estimated)","DJ",1999 +"1999-03-28","Eid al-Adha deuxieme jour* (*estimated)","DJ",1999 +"1999-04-17","Nouvel an musulman* (*estimated)","DJ",1999 +"1999-05-01","Fete du travail","DJ",1999 +"1999-06-26","Naissance du prophet Muhammad* (*estimated)","DJ",1999 +"1999-06-27","Fete de l'independance","DJ",1999 +"1999-06-28","Fete de l'independance","DJ",1999 +"1999-11-05","Isra wal Miraj* (*estimated)","DJ",1999 +"2000-01-01","Nouvel an","DJ",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","DJ",2000 +"2000-01-09","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2000 +"2000-03-15","Arafat* (*estimated)","DJ",2000 +"2000-03-16","Eid al-Adha* (*estimated)","DJ",2000 +"2000-03-17","Eid al-Adha deuxieme jour* (*estimated)","DJ",2000 +"2000-04-06","Nouvel an musulman* (*estimated)","DJ",2000 +"2000-05-01","Fete du travail","DJ",2000 +"2000-06-14","Naissance du prophet Muhammad* (*estimated)","DJ",2000 +"2000-06-27","Fete de l'independance","DJ",2000 +"2000-06-28","Fete de l'independance","DJ",2000 +"2000-10-24","Isra wal Miraj* (*estimated)","DJ",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","DJ",2000 +"2000-12-28","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2000 +"2001-01-01","Nouvel an","DJ",2001 +"2001-03-04","Arafat* (*estimated)","DJ",2001 +"2001-03-05","Eid al-Adha* (*estimated)","DJ",2001 +"2001-03-06","Eid al-Adha deuxieme jour* (*estimated)","DJ",2001 +"2001-03-26","Nouvel an musulman* (*estimated)","DJ",2001 +"2001-05-01","Fete du travail","DJ",2001 +"2001-06-04","Naissance du prophet Muhammad* (*estimated)","DJ",2001 +"2001-06-27","Fete de l'independance","DJ",2001 +"2001-06-28","Fete de l'independance","DJ",2001 +"2001-10-14","Isra wal Miraj* (*estimated)","DJ",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","DJ",2001 +"2001-12-17","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2001 +"2002-01-01","Nouvel an","DJ",2002 +"2002-02-21","Arafat* (*estimated)","DJ",2002 +"2002-02-22","Eid al-Adha* (*estimated)","DJ",2002 +"2002-02-23","Eid al-Adha deuxieme jour* (*estimated)","DJ",2002 +"2002-03-15","Nouvel an musulman* (*estimated)","DJ",2002 +"2002-05-01","Fete du travail","DJ",2002 +"2002-05-24","Naissance du prophet Muhammad* (*estimated)","DJ",2002 +"2002-06-27","Fete de l'independance","DJ",2002 +"2002-06-28","Fete de l'independance","DJ",2002 +"2002-10-04","Isra wal Miraj* (*estimated)","DJ",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","DJ",2002 +"2002-12-06","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2002 +"2003-01-01","Nouvel an","DJ",2003 +"2003-02-10","Arafat* (*estimated)","DJ",2003 +"2003-02-11","Eid al-Adha* (*estimated)","DJ",2003 +"2003-02-12","Eid al-Adha deuxieme jour* (*estimated)","DJ",2003 +"2003-03-04","Nouvel an musulman* (*estimated)","DJ",2003 +"2003-05-01","Fete du travail","DJ",2003 +"2003-05-13","Naissance du prophet Muhammad* (*estimated)","DJ",2003 +"2003-06-27","Fete de l'independance","DJ",2003 +"2003-06-28","Fete de l'independance","DJ",2003 +"2003-09-24","Isra wal Miraj* (*estimated)","DJ",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","DJ",2003 +"2003-11-26","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2003 +"2004-01-01","Nouvel an","DJ",2004 +"2004-01-31","Arafat* (*estimated)","DJ",2004 +"2004-02-01","Eid al-Adha* (*estimated)","DJ",2004 +"2004-02-02","Eid al-Adha deuxieme jour* (*estimated)","DJ",2004 +"2004-02-21","Nouvel an musulman* (*estimated)","DJ",2004 +"2004-05-01","Fete du travail","DJ",2004 +"2004-05-01","Naissance du prophet Muhammad* (*estimated)","DJ",2004 +"2004-06-27","Fete de l'independance","DJ",2004 +"2004-06-28","Fete de l'independance","DJ",2004 +"2004-09-12","Isra wal Miraj* (*estimated)","DJ",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","DJ",2004 +"2004-11-15","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2004 +"2005-01-01","Nouvel an","DJ",2005 +"2005-01-20","Arafat* (*estimated)","DJ",2005 +"2005-01-21","Eid al-Adha* (*estimated)","DJ",2005 +"2005-01-22","Eid al-Adha deuxieme jour* (*estimated)","DJ",2005 +"2005-02-10","Nouvel an musulman* (*estimated)","DJ",2005 +"2005-04-21","Naissance du prophet Muhammad* (*estimated)","DJ",2005 +"2005-05-01","Fete du travail","DJ",2005 +"2005-06-27","Fete de l'independance","DJ",2005 +"2005-06-28","Fete de l'independance","DJ",2005 +"2005-09-01","Isra wal Miraj* (*estimated)","DJ",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","DJ",2005 +"2005-11-04","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2005 +"2006-01-01","Nouvel an","DJ",2006 +"2006-01-09","Arafat* (*estimated)","DJ",2006 +"2006-01-10","Eid al-Adha* (*estimated)","DJ",2006 +"2006-01-11","Eid al-Adha deuxieme jour* (*estimated)","DJ",2006 +"2006-01-31","Nouvel an musulman* (*estimated)","DJ",2006 +"2006-04-10","Naissance du prophet Muhammad* (*estimated)","DJ",2006 +"2006-05-01","Fete du travail","DJ",2006 +"2006-06-27","Fete de l'independance","DJ",2006 +"2006-06-28","Fete de l'independance","DJ",2006 +"2006-08-21","Isra wal Miraj* (*estimated)","DJ",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","DJ",2006 +"2006-10-24","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2006 +"2006-12-30","Arafat* (*estimated)","DJ",2006 +"2006-12-31","Eid al-Adha* (*estimated)","DJ",2006 +"2007-01-01","Eid al-Adha deuxieme jour* (*estimated)","DJ",2007 +"2007-01-01","Nouvel an","DJ",2007 +"2007-01-20","Nouvel an musulman* (*estimated)","DJ",2007 +"2007-03-31","Naissance du prophet Muhammad* (*estimated)","DJ",2007 +"2007-05-01","Fete du travail","DJ",2007 +"2007-06-27","Fete de l'independance","DJ",2007 +"2007-06-28","Fete de l'independance","DJ",2007 +"2007-08-10","Isra wal Miraj* (*estimated)","DJ",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","DJ",2007 +"2007-10-14","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2007 +"2007-12-19","Arafat* (*estimated)","DJ",2007 +"2007-12-20","Eid al-Adha* (*estimated)","DJ",2007 +"2007-12-21","Eid al-Adha deuxieme jour* (*estimated)","DJ",2007 +"2008-01-01","Nouvel an","DJ",2008 +"2008-01-10","Nouvel an musulman* (*estimated)","DJ",2008 +"2008-03-20","Naissance du prophet Muhammad* (*estimated)","DJ",2008 +"2008-05-01","Fete du travail","DJ",2008 +"2008-06-27","Fete de l'independance","DJ",2008 +"2008-06-28","Fete de l'independance","DJ",2008 +"2008-07-30","Isra wal Miraj* (*estimated)","DJ",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","DJ",2008 +"2008-10-02","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2008 +"2008-12-07","Arafat* (*estimated)","DJ",2008 +"2008-12-08","Eid al-Adha* (*estimated)","DJ",2008 +"2008-12-09","Eid al-Adha deuxieme jour* (*estimated)","DJ",2008 +"2008-12-29","Nouvel an musulman* (*estimated)","DJ",2008 +"2009-01-01","Nouvel an","DJ",2009 +"2009-03-09","Naissance du prophet Muhammad* (*estimated)","DJ",2009 +"2009-05-01","Fete du travail","DJ",2009 +"2009-06-27","Fete de l'independance","DJ",2009 +"2009-06-28","Fete de l'independance","DJ",2009 +"2009-07-20","Isra wal Miraj* (*estimated)","DJ",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","DJ",2009 +"2009-09-21","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2009 +"2009-11-26","Arafat* (*estimated)","DJ",2009 +"2009-11-27","Eid al-Adha* (*estimated)","DJ",2009 +"2009-11-28","Eid al-Adha deuxieme jour* (*estimated)","DJ",2009 +"2009-12-18","Nouvel an musulman* (*estimated)","DJ",2009 +"2010-01-01","Nouvel an","DJ",2010 +"2010-02-26","Naissance du prophet Muhammad* (*estimated)","DJ",2010 +"2010-05-01","Fete du travail","DJ",2010 +"2010-06-27","Fete de l'independance","DJ",2010 +"2010-06-28","Fete de l'independance","DJ",2010 +"2010-07-09","Isra wal Miraj* (*estimated)","DJ",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","DJ",2010 +"2010-09-11","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2010 +"2010-11-15","Arafat* (*estimated)","DJ",2010 +"2010-11-16","Eid al-Adha* (*estimated)","DJ",2010 +"2010-11-17","Eid al-Adha deuxieme jour* (*estimated)","DJ",2010 +"2010-12-07","Nouvel an musulman* (*estimated)","DJ",2010 +"2011-01-01","Nouvel an","DJ",2011 +"2011-02-15","Naissance du prophet Muhammad* (*estimated)","DJ",2011 +"2011-05-01","Fete du travail","DJ",2011 +"2011-06-27","Fete de l'independance","DJ",2011 +"2011-06-28","Fete de l'independance","DJ",2011 +"2011-06-29","Isra wal Miraj* (*estimated)","DJ",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","DJ",2011 +"2011-08-31","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2011 +"2011-11-05","Arafat* (*estimated)","DJ",2011 +"2011-11-06","Eid al-Adha* (*estimated)","DJ",2011 +"2011-11-07","Eid al-Adha deuxieme jour* (*estimated)","DJ",2011 +"2011-11-26","Nouvel an musulman* (*estimated)","DJ",2011 +"2012-01-01","Nouvel an","DJ",2012 +"2012-02-04","Naissance du prophet Muhammad* (*estimated)","DJ",2012 +"2012-05-01","Fete du travail","DJ",2012 +"2012-06-17","Isra wal Miraj* (*estimated)","DJ",2012 +"2012-06-27","Fete de l'independance","DJ",2012 +"2012-06-28","Fete de l'independance","DJ",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","DJ",2012 +"2012-08-20","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2012 +"2012-10-25","Arafat* (*estimated)","DJ",2012 +"2012-10-26","Eid al-Adha* (*estimated)","DJ",2012 +"2012-10-27","Eid al-Adha deuxieme jour* (*estimated)","DJ",2012 +"2012-11-15","Nouvel an musulman* (*estimated)","DJ",2012 +"2013-01-01","Nouvel an","DJ",2013 +"2013-01-24","Naissance du prophet Muhammad* (*estimated)","DJ",2013 +"2013-05-01","Fete du travail","DJ",2013 +"2013-06-06","Isra wal Miraj* (*estimated)","DJ",2013 +"2013-06-27","Fete de l'independance","DJ",2013 +"2013-06-28","Fete de l'independance","DJ",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","DJ",2013 +"2013-08-09","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2013 +"2013-10-14","Arafat* (*estimated)","DJ",2013 +"2013-10-15","Eid al-Adha* (*estimated)","DJ",2013 +"2013-10-16","Eid al-Adha deuxieme jour* (*estimated)","DJ",2013 +"2013-11-04","Nouvel an musulman* (*estimated)","DJ",2013 +"2014-01-01","Nouvel an","DJ",2014 +"2014-01-13","Naissance du prophet Muhammad* (*estimated)","DJ",2014 +"2014-05-01","Fete du travail","DJ",2014 +"2014-05-26","Isra wal Miraj* (*estimated)","DJ",2014 +"2014-06-27","Fete de l'independance","DJ",2014 +"2014-06-28","Fete de l'independance","DJ",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","DJ",2014 +"2014-07-29","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2014 +"2014-10-03","Arafat* (*estimated)","DJ",2014 +"2014-10-04","Eid al-Adha* (*estimated)","DJ",2014 +"2014-10-05","Eid al-Adha deuxieme jour* (*estimated)","DJ",2014 +"2014-10-25","Nouvel an musulman* (*estimated)","DJ",2014 +"2015-01-01","Nouvel an","DJ",2015 +"2015-01-03","Naissance du prophet Muhammad* (*estimated)","DJ",2015 +"2015-05-01","Fete du travail","DJ",2015 +"2015-05-16","Isra wal Miraj* (*estimated)","DJ",2015 +"2015-06-27","Fete de l'independance","DJ",2015 +"2015-06-28","Fete de l'independance","DJ",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","DJ",2015 +"2015-07-18","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2015 +"2015-09-22","Arafat* (*estimated)","DJ",2015 +"2015-09-23","Eid al-Adha* (*estimated)","DJ",2015 +"2015-09-24","Eid al-Adha deuxieme jour* (*estimated)","DJ",2015 +"2015-10-14","Nouvel an musulman* (*estimated)","DJ",2015 +"2015-12-23","Naissance du prophet Muhammad* (*estimated)","DJ",2015 +"2016-01-01","Nouvel an","DJ",2016 +"2016-05-01","Fete du travail","DJ",2016 +"2016-05-04","Isra wal Miraj* (*estimated)","DJ",2016 +"2016-06-27","Fete de l'independance","DJ",2016 +"2016-06-28","Fete de l'independance","DJ",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","DJ",2016 +"2016-07-07","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2016 +"2016-09-10","Arafat* (*estimated)","DJ",2016 +"2016-09-11","Eid al-Adha* (*estimated)","DJ",2016 +"2016-09-12","Eid al-Adha deuxieme jour* (*estimated)","DJ",2016 +"2016-10-02","Nouvel an musulman* (*estimated)","DJ",2016 +"2016-12-11","Naissance du prophet Muhammad* (*estimated)","DJ",2016 +"2017-01-01","Nouvel an","DJ",2017 +"2017-04-24","Isra wal Miraj* (*estimated)","DJ",2017 +"2017-05-01","Fete du travail","DJ",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","DJ",2017 +"2017-06-26","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2017 +"2017-06-27","Fete de l'independance","DJ",2017 +"2017-06-28","Fete de l'independance","DJ",2017 +"2017-08-31","Arafat* (*estimated)","DJ",2017 +"2017-09-01","Eid al-Adha* (*estimated)","DJ",2017 +"2017-09-02","Eid al-Adha deuxieme jour* (*estimated)","DJ",2017 +"2017-09-21","Nouvel an musulman* (*estimated)","DJ",2017 +"2017-11-30","Naissance du prophet Muhammad* (*estimated)","DJ",2017 +"2018-01-01","Nouvel an","DJ",2018 +"2018-04-13","Isra wal Miraj* (*estimated)","DJ",2018 +"2018-05-01","Fete du travail","DJ",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","DJ",2018 +"2018-06-16","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2018 +"2018-06-27","Fete de l'independance","DJ",2018 +"2018-06-28","Fete de l'independance","DJ",2018 +"2018-08-20","Arafat* (*estimated)","DJ",2018 +"2018-08-21","Eid al-Adha* (*estimated)","DJ",2018 +"2018-08-22","Eid al-Adha deuxieme jour* (*estimated)","DJ",2018 +"2018-09-11","Nouvel an musulman* (*estimated)","DJ",2018 +"2018-11-20","Naissance du prophet Muhammad* (*estimated)","DJ",2018 +"2019-01-01","Nouvel an","DJ",2019 +"2019-04-03","Isra wal Miraj* (*estimated)","DJ",2019 +"2019-05-01","Fete du travail","DJ",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","DJ",2019 +"2019-06-05","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2019 +"2019-06-27","Fete de l'independance","DJ",2019 +"2019-06-28","Fete de l'independance","DJ",2019 +"2019-08-10","Arafat* (*estimated)","DJ",2019 +"2019-08-11","Eid al-Adha* (*estimated)","DJ",2019 +"2019-08-12","Eid al-Adha deuxieme jour* (*estimated)","DJ",2019 +"2019-08-31","Nouvel an musulman* (*estimated)","DJ",2019 +"2019-11-09","Naissance du prophet Muhammad* (*estimated)","DJ",2019 +"2020-01-01","Nouvel an","DJ",2020 +"2020-03-22","Isra wal Miraj* (*estimated)","DJ",2020 +"2020-05-01","Fete du travail","DJ",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","DJ",2020 +"2020-05-25","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2020 +"2020-06-27","Fete de l'independance","DJ",2020 +"2020-06-28","Fete de l'independance","DJ",2020 +"2020-07-30","Arafat* (*estimated)","DJ",2020 +"2020-07-31","Eid al-Adha* (*estimated)","DJ",2020 +"2020-08-01","Eid al-Adha deuxieme jour* (*estimated)","DJ",2020 +"2020-08-20","Nouvel an musulman* (*estimated)","DJ",2020 +"2020-10-29","Naissance du prophet Muhammad* (*estimated)","DJ",2020 +"2021-01-01","Nouvel an","DJ",2021 +"2021-03-11","Isra wal Miraj* (*estimated)","DJ",2021 +"2021-05-01","Fete du travail","DJ",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","DJ",2021 +"2021-05-14","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2021 +"2021-06-27","Fete de l'independance","DJ",2021 +"2021-06-28","Fete de l'independance","DJ",2021 +"2021-07-19","Arafat* (*estimated)","DJ",2021 +"2021-07-20","Eid al-Adha* (*estimated)","DJ",2021 +"2021-07-21","Eid al-Adha deuxieme jour* (*estimated)","DJ",2021 +"2021-08-09","Nouvel an musulman* (*estimated)","DJ",2021 +"2021-10-18","Naissance du prophet Muhammad* (*estimated)","DJ",2021 +"2022-01-01","Nouvel an","DJ",2022 +"2022-02-28","Isra wal Miraj* (*estimated)","DJ",2022 +"2022-05-01","Fete du travail","DJ",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","DJ",2022 +"2022-05-03","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2022 +"2022-06-27","Fete de l'independance","DJ",2022 +"2022-06-28","Fete de l'independance","DJ",2022 +"2022-07-08","Arafat* (*estimated)","DJ",2022 +"2022-07-09","Eid al-Adha* (*estimated)","DJ",2022 +"2022-07-10","Eid al-Adha deuxieme jour* (*estimated)","DJ",2022 +"2022-07-30","Nouvel an musulman* (*estimated)","DJ",2022 +"2022-10-08","Naissance du prophet Muhammad* (*estimated)","DJ",2022 +"2023-01-01","Nouvel an","DJ",2023 +"2023-02-18","Isra wal Miraj* (*estimated)","DJ",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","DJ",2023 +"2023-04-22","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2023 +"2023-05-01","Fete du travail","DJ",2023 +"2023-06-27","Arafat* (*estimated)","DJ",2023 +"2023-06-27","Fete de l'independance","DJ",2023 +"2023-06-28","Eid al-Adha* (*estimated)","DJ",2023 +"2023-06-28","Fete de l'independance","DJ",2023 +"2023-06-29","Eid al-Adha deuxieme jour* (*estimated)","DJ",2023 +"2023-07-19","Nouvel an musulman* (*estimated)","DJ",2023 +"2023-09-27","Naissance du prophet Muhammad* (*estimated)","DJ",2023 +"2024-01-01","Nouvel an","DJ",2024 +"2024-02-08","Isra wal Miraj* (*estimated)","DJ",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","DJ",2024 +"2024-04-11","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2024 +"2024-05-01","Fete du travail","DJ",2024 +"2024-06-15","Arafat* (*estimated)","DJ",2024 +"2024-06-16","Eid al-Adha* (*estimated)","DJ",2024 +"2024-06-17","Eid al-Adha deuxieme jour* (*estimated)","DJ",2024 +"2024-06-27","Fete de l'independance","DJ",2024 +"2024-06-28","Fete de l'independance","DJ",2024 +"2024-07-07","Nouvel an musulman* (*estimated)","DJ",2024 +"2024-09-15","Naissance du prophet Muhammad* (*estimated)","DJ",2024 +"2025-01-01","Nouvel an","DJ",2025 +"2025-01-27","Isra wal Miraj* (*estimated)","DJ",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","DJ",2025 +"2025-03-31","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2025 +"2025-05-01","Fete du travail","DJ",2025 +"2025-06-05","Arafat* (*estimated)","DJ",2025 +"2025-06-06","Eid al-Adha* (*estimated)","DJ",2025 +"2025-06-07","Eid al-Adha deuxieme jour* (*estimated)","DJ",2025 +"2025-06-26","Nouvel an musulman* (*estimated)","DJ",2025 +"2025-06-27","Fete de l'independance","DJ",2025 +"2025-06-28","Fete de l'independance","DJ",2025 +"2025-09-04","Naissance du prophet Muhammad* (*estimated)","DJ",2025 +"2026-01-01","Nouvel an","DJ",2026 +"2026-01-16","Isra wal Miraj* (*estimated)","DJ",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","DJ",2026 +"2026-03-21","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2026 +"2026-05-01","Fete du travail","DJ",2026 +"2026-05-26","Arafat* (*estimated)","DJ",2026 +"2026-05-27","Eid al-Adha* (*estimated)","DJ",2026 +"2026-05-28","Eid al-Adha deuxieme jour* (*estimated)","DJ",2026 +"2026-06-16","Nouvel an musulman* (*estimated)","DJ",2026 +"2026-06-27","Fete de l'independance","DJ",2026 +"2026-06-28","Fete de l'independance","DJ",2026 +"2026-08-25","Naissance du prophet Muhammad* (*estimated)","DJ",2026 +"2027-01-01","Nouvel an","DJ",2027 +"2027-01-05","Isra wal Miraj* (*estimated)","DJ",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","DJ",2027 +"2027-03-10","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2027 +"2027-05-01","Fete du travail","DJ",2027 +"2027-05-15","Arafat* (*estimated)","DJ",2027 +"2027-05-16","Eid al-Adha* (*estimated)","DJ",2027 +"2027-05-17","Eid al-Adha deuxieme jour* (*estimated)","DJ",2027 +"2027-06-06","Nouvel an musulman* (*estimated)","DJ",2027 +"2027-06-27","Fete de l'independance","DJ",2027 +"2027-06-28","Fete de l'independance","DJ",2027 +"2027-08-14","Naissance du prophet Muhammad* (*estimated)","DJ",2027 +"2027-12-25","Isra wal Miraj* (*estimated)","DJ",2027 +"2028-01-01","Nouvel an","DJ",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","DJ",2028 +"2028-02-27","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2028 +"2028-05-01","Fete du travail","DJ",2028 +"2028-05-04","Arafat* (*estimated)","DJ",2028 +"2028-05-05","Eid al-Adha* (*estimated)","DJ",2028 +"2028-05-06","Eid al-Adha deuxieme jour* (*estimated)","DJ",2028 +"2028-05-25","Nouvel an musulman* (*estimated)","DJ",2028 +"2028-06-27","Fete de l'independance","DJ",2028 +"2028-06-28","Fete de l'independance","DJ",2028 +"2028-08-03","Naissance du prophet Muhammad* (*estimated)","DJ",2028 +"2028-12-14","Isra wal Miraj* (*estimated)","DJ",2028 +"2029-01-01","Nouvel an","DJ",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","DJ",2029 +"2029-02-15","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2029 +"2029-04-23","Arafat* (*estimated)","DJ",2029 +"2029-04-24","Eid al-Adha* (*estimated)","DJ",2029 +"2029-04-25","Eid al-Adha deuxieme jour* (*estimated)","DJ",2029 +"2029-05-01","Fete du travail","DJ",2029 +"2029-05-14","Nouvel an musulman* (*estimated)","DJ",2029 +"2029-06-27","Fete de l'independance","DJ",2029 +"2029-06-28","Fete de l'independance","DJ",2029 +"2029-07-24","Naissance du prophet Muhammad* (*estimated)","DJ",2029 +"2029-12-03","Isra wal Miraj* (*estimated)","DJ",2029 +"2030-01-01","Nouvel an","DJ",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","DJ",2030 +"2030-02-05","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2030 +"2030-04-12","Arafat* (*estimated)","DJ",2030 +"2030-04-13","Eid al-Adha* (*estimated)","DJ",2030 +"2030-04-14","Eid al-Adha deuxieme jour* (*estimated)","DJ",2030 +"2030-05-01","Fete du travail","DJ",2030 +"2030-05-03","Nouvel an musulman* (*estimated)","DJ",2030 +"2030-06-27","Fete de l'independance","DJ",2030 +"2030-06-28","Fete de l'independance","DJ",2030 +"2030-07-13","Naissance du prophet Muhammad* (*estimated)","DJ",2030 +"2030-11-23","Isra wal Miraj* (*estimated)","DJ",2030 +"2031-01-01","Nouvel an","DJ",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","DJ",2031 +"2031-01-25","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2031 +"2031-04-01","Arafat* (*estimated)","DJ",2031 +"2031-04-02","Eid al-Adha* (*estimated)","DJ",2031 +"2031-04-03","Eid al-Adha deuxieme jour* (*estimated)","DJ",2031 +"2031-04-23","Nouvel an musulman* (*estimated)","DJ",2031 +"2031-05-01","Fete du travail","DJ",2031 +"2031-06-27","Fete de l'independance","DJ",2031 +"2031-06-28","Fete de l'independance","DJ",2031 +"2031-07-02","Naissance du prophet Muhammad* (*estimated)","DJ",2031 +"2031-11-12","Isra wal Miraj* (*estimated)","DJ",2031 +"2032-01-01","Nouvel an","DJ",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","DJ",2032 +"2032-01-15","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2032 +"2032-03-21","Arafat* (*estimated)","DJ",2032 +"2032-03-22","Eid al-Adha* (*estimated)","DJ",2032 +"2032-03-23","Eid al-Adha deuxieme jour* (*estimated)","DJ",2032 +"2032-04-11","Nouvel an musulman* (*estimated)","DJ",2032 +"2032-05-01","Fete du travail","DJ",2032 +"2032-06-20","Naissance du prophet Muhammad* (*estimated)","DJ",2032 +"2032-06-27","Fete de l'independance","DJ",2032 +"2032-06-28","Fete de l'independance","DJ",2032 +"2032-11-01","Isra wal Miraj* (*estimated)","DJ",2032 +"2033-01-01","Nouvel an","DJ",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","DJ",2033 +"2033-01-03","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2033 +"2033-03-10","Arafat* (*estimated)","DJ",2033 +"2033-03-11","Eid al-Adha* (*estimated)","DJ",2033 +"2033-03-12","Eid al-Adha deuxieme jour* (*estimated)","DJ",2033 +"2033-04-01","Nouvel an musulman* (*estimated)","DJ",2033 +"2033-05-01","Fete du travail","DJ",2033 +"2033-06-09","Naissance du prophet Muhammad* (*estimated)","DJ",2033 +"2033-06-27","Fete de l'independance","DJ",2033 +"2033-06-28","Fete de l'independance","DJ",2033 +"2033-10-21","Isra wal Miraj* (*estimated)","DJ",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","DJ",2033 +"2033-12-24","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2033 +"2034-01-01","Nouvel an","DJ",2034 +"2034-02-28","Arafat* (*estimated)","DJ",2034 +"2034-03-01","Eid al-Adha* (*estimated)","DJ",2034 +"2034-03-02","Eid al-Adha deuxieme jour* (*estimated)","DJ",2034 +"2034-03-21","Nouvel an musulman* (*estimated)","DJ",2034 +"2034-05-01","Fete du travail","DJ",2034 +"2034-05-30","Naissance du prophet Muhammad* (*estimated)","DJ",2034 +"2034-06-27","Fete de l'independance","DJ",2034 +"2034-06-28","Fete de l'independance","DJ",2034 +"2034-10-10","Isra wal Miraj* (*estimated)","DJ",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","DJ",2034 +"2034-12-13","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2034 +"2035-01-01","Nouvel an","DJ",2035 +"2035-02-17","Arafat* (*estimated)","DJ",2035 +"2035-02-18","Eid al-Adha* (*estimated)","DJ",2035 +"2035-02-19","Eid al-Adha deuxieme jour* (*estimated)","DJ",2035 +"2035-03-11","Nouvel an musulman* (*estimated)","DJ",2035 +"2035-05-01","Fete du travail","DJ",2035 +"2035-05-20","Naissance du prophet Muhammad* (*estimated)","DJ",2035 +"2035-06-27","Fete de l'independance","DJ",2035 +"2035-06-28","Fete de l'independance","DJ",2035 +"2035-09-29","Isra wal Miraj* (*estimated)","DJ",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","DJ",2035 +"2035-12-02","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2035 +"2036-01-01","Nouvel an","DJ",2036 +"2036-02-06","Arafat* (*estimated)","DJ",2036 +"2036-02-07","Eid al-Adha* (*estimated)","DJ",2036 +"2036-02-08","Eid al-Adha deuxieme jour* (*estimated)","DJ",2036 +"2036-02-28","Nouvel an musulman* (*estimated)","DJ",2036 +"2036-05-01","Fete du travail","DJ",2036 +"2036-05-08","Naissance du prophet Muhammad* (*estimated)","DJ",2036 +"2036-06-27","Fete de l'independance","DJ",2036 +"2036-06-28","Fete de l'independance","DJ",2036 +"2036-09-18","Isra wal Miraj* (*estimated)","DJ",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","DJ",2036 +"2036-11-20","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2036 +"2037-01-01","Nouvel an","DJ",2037 +"2037-01-25","Arafat* (*estimated)","DJ",2037 +"2037-01-26","Eid al-Adha* (*estimated)","DJ",2037 +"2037-01-27","Eid al-Adha deuxieme jour* (*estimated)","DJ",2037 +"2037-02-16","Nouvel an musulman* (*estimated)","DJ",2037 +"2037-04-28","Naissance du prophet Muhammad* (*estimated)","DJ",2037 +"2037-05-01","Fete du travail","DJ",2037 +"2037-06-27","Fete de l'independance","DJ",2037 +"2037-06-28","Fete de l'independance","DJ",2037 +"2037-09-07","Isra wal Miraj* (*estimated)","DJ",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","DJ",2037 +"2037-11-09","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2037 +"2038-01-01","Nouvel an","DJ",2038 +"2038-01-15","Arafat* (*estimated)","DJ",2038 +"2038-01-16","Eid al-Adha* (*estimated)","DJ",2038 +"2038-01-17","Eid al-Adha deuxieme jour* (*estimated)","DJ",2038 +"2038-02-05","Nouvel an musulman* (*estimated)","DJ",2038 +"2038-04-17","Naissance du prophet Muhammad* (*estimated)","DJ",2038 +"2038-05-01","Fete du travail","DJ",2038 +"2038-06-27","Fete de l'independance","DJ",2038 +"2038-06-28","Fete de l'independance","DJ",2038 +"2038-08-28","Isra wal Miraj* (*estimated)","DJ",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","DJ",2038 +"2038-10-30","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2038 +"2039-01-01","Nouvel an","DJ",2039 +"2039-01-04","Arafat* (*estimated)","DJ",2039 +"2039-01-05","Eid al-Adha* (*estimated)","DJ",2039 +"2039-01-06","Eid al-Adha deuxieme jour* (*estimated)","DJ",2039 +"2039-01-26","Nouvel an musulman* (*estimated)","DJ",2039 +"2039-04-06","Naissance du prophet Muhammad* (*estimated)","DJ",2039 +"2039-05-01","Fete du travail","DJ",2039 +"2039-06-27","Fete de l'independance","DJ",2039 +"2039-06-28","Fete de l'independance","DJ",2039 +"2039-08-17","Isra wal Miraj* (*estimated)","DJ",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","DJ",2039 +"2039-10-20","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2039 +"2039-12-25","Arafat* (*estimated)","DJ",2039 +"2039-12-26","Eid al-Adha* (*estimated)","DJ",2039 +"2039-12-27","Eid al-Adha deuxieme jour* (*estimated)","DJ",2039 +"2040-01-01","Nouvel an","DJ",2040 +"2040-01-15","Nouvel an musulman* (*estimated)","DJ",2040 +"2040-03-25","Naissance du prophet Muhammad* (*estimated)","DJ",2040 +"2040-05-01","Fete du travail","DJ",2040 +"2040-06-27","Fete de l'independance","DJ",2040 +"2040-06-28","Fete de l'independance","DJ",2040 +"2040-08-05","Isra wal Miraj* (*estimated)","DJ",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","DJ",2040 +"2040-10-08","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2040 +"2040-12-13","Arafat* (*estimated)","DJ",2040 +"2040-12-14","Eid al-Adha* (*estimated)","DJ",2040 +"2040-12-15","Eid al-Adha deuxieme jour* (*estimated)","DJ",2040 +"2041-01-01","Nouvel an","DJ",2041 +"2041-01-04","Nouvel an musulman* (*estimated)","DJ",2041 +"2041-03-15","Naissance du prophet Muhammad* (*estimated)","DJ",2041 +"2041-05-01","Fete du travail","DJ",2041 +"2041-06-27","Fete de l'independance","DJ",2041 +"2041-06-28","Fete de l'independance","DJ",2041 +"2041-07-25","Isra wal Miraj* (*estimated)","DJ",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","DJ",2041 +"2041-09-27","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2041 +"2041-12-03","Arafat* (*estimated)","DJ",2041 +"2041-12-04","Eid al-Adha* (*estimated)","DJ",2041 +"2041-12-05","Eid al-Adha deuxieme jour* (*estimated)","DJ",2041 +"2041-12-24","Nouvel an musulman* (*estimated)","DJ",2041 +"2042-01-01","Nouvel an","DJ",2042 +"2042-03-04","Naissance du prophet Muhammad* (*estimated)","DJ",2042 +"2042-05-01","Fete du travail","DJ",2042 +"2042-06-27","Fete de l'independance","DJ",2042 +"2042-06-28","Fete de l'independance","DJ",2042 +"2042-07-15","Isra wal Miraj* (*estimated)","DJ",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","DJ",2042 +"2042-09-16","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2042 +"2042-11-22","Arafat* (*estimated)","DJ",2042 +"2042-11-23","Eid al-Adha* (*estimated)","DJ",2042 +"2042-11-24","Eid al-Adha deuxieme jour* (*estimated)","DJ",2042 +"2042-12-14","Nouvel an musulman* (*estimated)","DJ",2042 +"2043-01-01","Nouvel an","DJ",2043 +"2043-02-22","Naissance du prophet Muhammad* (*estimated)","DJ",2043 +"2043-05-01","Fete du travail","DJ",2043 +"2043-06-27","Fete de l'independance","DJ",2043 +"2043-06-28","Fete de l'independance","DJ",2043 +"2043-07-04","Isra wal Miraj* (*estimated)","DJ",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","DJ",2043 +"2043-09-05","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2043 +"2043-11-11","Arafat* (*estimated)","DJ",2043 +"2043-11-12","Eid al-Adha* (*estimated)","DJ",2043 +"2043-11-13","Eid al-Adha deuxieme jour* (*estimated)","DJ",2043 +"2043-12-03","Nouvel an musulman* (*estimated)","DJ",2043 +"2044-01-01","Nouvel an","DJ",2044 +"2044-02-11","Naissance du prophet Muhammad* (*estimated)","DJ",2044 +"2044-05-01","Fete du travail","DJ",2044 +"2044-06-23","Isra wal Miraj* (*estimated)","DJ",2044 +"2044-06-27","Fete de l'independance","DJ",2044 +"2044-06-28","Fete de l'independance","DJ",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","DJ",2044 +"2044-08-25","Eid al-Fitr deuxieme jour* (*estimated)","DJ",2044 +"2044-10-30","Arafat* (*estimated)","DJ",2044 +"2044-10-31","Eid al-Adha* (*estimated)","DJ",2044 +"2044-11-01","Eid al-Adha deuxieme jour* (*estimated)","DJ",2044 +"2044-11-21","Nouvel an musulman* (*estimated)","DJ",2044 +"1995-01-01","New Year's Day","DK",1995 +"1995-04-13","Maundy Thursday","DK",1995 +"1995-04-14","Good Friday","DK",1995 +"1995-04-16","Easter Sunday","DK",1995 +"1995-04-17","Easter Monday","DK",1995 +"1995-05-12","Great Prayer Day","DK",1995 +"1995-05-25","Ascension Day","DK",1995 +"1995-06-04","Whit Sunday","DK",1995 +"1995-06-05","Whit Monday","DK",1995 +"1995-12-25","Christmas Day","DK",1995 +"1995-12-26","Second Day of Christmas","DK",1995 +"1996-01-01","New Year's Day","DK",1996 +"1996-04-04","Maundy Thursday","DK",1996 +"1996-04-05","Good Friday","DK",1996 +"1996-04-07","Easter Sunday","DK",1996 +"1996-04-08","Easter Monday","DK",1996 +"1996-05-03","Great Prayer Day","DK",1996 +"1996-05-16","Ascension Day","DK",1996 +"1996-05-26","Whit Sunday","DK",1996 +"1996-05-27","Whit Monday","DK",1996 +"1996-12-25","Christmas Day","DK",1996 +"1996-12-26","Second Day of Christmas","DK",1996 +"1997-01-01","New Year's Day","DK",1997 +"1997-03-27","Maundy Thursday","DK",1997 +"1997-03-28","Good Friday","DK",1997 +"1997-03-30","Easter Sunday","DK",1997 +"1997-03-31","Easter Monday","DK",1997 +"1997-04-25","Great Prayer Day","DK",1997 +"1997-05-08","Ascension Day","DK",1997 +"1997-05-18","Whit Sunday","DK",1997 +"1997-05-19","Whit Monday","DK",1997 +"1997-12-25","Christmas Day","DK",1997 +"1997-12-26","Second Day of Christmas","DK",1997 +"1998-01-01","New Year's Day","DK",1998 +"1998-04-09","Maundy Thursday","DK",1998 +"1998-04-10","Good Friday","DK",1998 +"1998-04-12","Easter Sunday","DK",1998 +"1998-04-13","Easter Monday","DK",1998 +"1998-05-08","Great Prayer Day","DK",1998 +"1998-05-21","Ascension Day","DK",1998 +"1998-05-31","Whit Sunday","DK",1998 +"1998-06-01","Whit Monday","DK",1998 +"1998-12-25","Christmas Day","DK",1998 +"1998-12-26","Second Day of Christmas","DK",1998 +"1999-01-01","New Year's Day","DK",1999 +"1999-04-01","Maundy Thursday","DK",1999 +"1999-04-02","Good Friday","DK",1999 +"1999-04-04","Easter Sunday","DK",1999 +"1999-04-05","Easter Monday","DK",1999 +"1999-04-30","Great Prayer Day","DK",1999 +"1999-05-13","Ascension Day","DK",1999 +"1999-05-23","Whit Sunday","DK",1999 +"1999-05-24","Whit Monday","DK",1999 +"1999-12-25","Christmas Day","DK",1999 +"1999-12-26","Second Day of Christmas","DK",1999 +"2000-01-01","New Year's Day","DK",2000 +"2000-04-20","Maundy Thursday","DK",2000 +"2000-04-21","Good Friday","DK",2000 +"2000-04-23","Easter Sunday","DK",2000 +"2000-04-24","Easter Monday","DK",2000 +"2000-05-19","Great Prayer Day","DK",2000 +"2000-06-01","Ascension Day","DK",2000 +"2000-06-11","Whit Sunday","DK",2000 +"2000-06-12","Whit Monday","DK",2000 +"2000-12-25","Christmas Day","DK",2000 +"2000-12-26","Second Day of Christmas","DK",2000 +"2001-01-01","New Year's Day","DK",2001 +"2001-04-12","Maundy Thursday","DK",2001 +"2001-04-13","Good Friday","DK",2001 +"2001-04-15","Easter Sunday","DK",2001 +"2001-04-16","Easter Monday","DK",2001 +"2001-05-11","Great Prayer Day","DK",2001 +"2001-05-24","Ascension Day","DK",2001 +"2001-06-03","Whit Sunday","DK",2001 +"2001-06-04","Whit Monday","DK",2001 +"2001-12-25","Christmas Day","DK",2001 +"2001-12-26","Second Day of Christmas","DK",2001 +"2002-01-01","New Year's Day","DK",2002 +"2002-03-28","Maundy Thursday","DK",2002 +"2002-03-29","Good Friday","DK",2002 +"2002-03-31","Easter Sunday","DK",2002 +"2002-04-01","Easter Monday","DK",2002 +"2002-04-26","Great Prayer Day","DK",2002 +"2002-05-09","Ascension Day","DK",2002 +"2002-05-19","Whit Sunday","DK",2002 +"2002-05-20","Whit Monday","DK",2002 +"2002-12-25","Christmas Day","DK",2002 +"2002-12-26","Second Day of Christmas","DK",2002 +"2003-01-01","New Year's Day","DK",2003 +"2003-04-17","Maundy Thursday","DK",2003 +"2003-04-18","Good Friday","DK",2003 +"2003-04-20","Easter Sunday","DK",2003 +"2003-04-21","Easter Monday","DK",2003 +"2003-05-16","Great Prayer Day","DK",2003 +"2003-05-29","Ascension Day","DK",2003 +"2003-06-08","Whit Sunday","DK",2003 +"2003-06-09","Whit Monday","DK",2003 +"2003-12-25","Christmas Day","DK",2003 +"2003-12-26","Second Day of Christmas","DK",2003 +"2004-01-01","New Year's Day","DK",2004 +"2004-04-08","Maundy Thursday","DK",2004 +"2004-04-09","Good Friday","DK",2004 +"2004-04-11","Easter Sunday","DK",2004 +"2004-04-12","Easter Monday","DK",2004 +"2004-05-07","Great Prayer Day","DK",2004 +"2004-05-20","Ascension Day","DK",2004 +"2004-05-30","Whit Sunday","DK",2004 +"2004-05-31","Whit Monday","DK",2004 +"2004-12-25","Christmas Day","DK",2004 +"2004-12-26","Second Day of Christmas","DK",2004 +"2005-01-01","New Year's Day","DK",2005 +"2005-03-24","Maundy Thursday","DK",2005 +"2005-03-25","Good Friday","DK",2005 +"2005-03-27","Easter Sunday","DK",2005 +"2005-03-28","Easter Monday","DK",2005 +"2005-04-22","Great Prayer Day","DK",2005 +"2005-05-05","Ascension Day","DK",2005 +"2005-05-15","Whit Sunday","DK",2005 +"2005-05-16","Whit Monday","DK",2005 +"2005-12-25","Christmas Day","DK",2005 +"2005-12-26","Second Day of Christmas","DK",2005 +"2006-01-01","New Year's Day","DK",2006 +"2006-04-13","Maundy Thursday","DK",2006 +"2006-04-14","Good Friday","DK",2006 +"2006-04-16","Easter Sunday","DK",2006 +"2006-04-17","Easter Monday","DK",2006 +"2006-05-12","Great Prayer Day","DK",2006 +"2006-05-25","Ascension Day","DK",2006 +"2006-06-04","Whit Sunday","DK",2006 +"2006-06-05","Whit Monday","DK",2006 +"2006-12-25","Christmas Day","DK",2006 +"2006-12-26","Second Day of Christmas","DK",2006 +"2007-01-01","New Year's Day","DK",2007 +"2007-04-05","Maundy Thursday","DK",2007 +"2007-04-06","Good Friday","DK",2007 +"2007-04-08","Easter Sunday","DK",2007 +"2007-04-09","Easter Monday","DK",2007 +"2007-05-04","Great Prayer Day","DK",2007 +"2007-05-17","Ascension Day","DK",2007 +"2007-05-27","Whit Sunday","DK",2007 +"2007-05-28","Whit Monday","DK",2007 +"2007-12-25","Christmas Day","DK",2007 +"2007-12-26","Second Day of Christmas","DK",2007 +"2008-01-01","New Year's Day","DK",2008 +"2008-03-20","Maundy Thursday","DK",2008 +"2008-03-21","Good Friday","DK",2008 +"2008-03-23","Easter Sunday","DK",2008 +"2008-03-24","Easter Monday","DK",2008 +"2008-04-18","Great Prayer Day","DK",2008 +"2008-05-01","Ascension Day","DK",2008 +"2008-05-11","Whit Sunday","DK",2008 +"2008-05-12","Whit Monday","DK",2008 +"2008-12-25","Christmas Day","DK",2008 +"2008-12-26","Second Day of Christmas","DK",2008 +"2009-01-01","New Year's Day","DK",2009 +"2009-04-09","Maundy Thursday","DK",2009 +"2009-04-10","Good Friday","DK",2009 +"2009-04-12","Easter Sunday","DK",2009 +"2009-04-13","Easter Monday","DK",2009 +"2009-05-08","Great Prayer Day","DK",2009 +"2009-05-21","Ascension Day","DK",2009 +"2009-05-31","Whit Sunday","DK",2009 +"2009-06-01","Whit Monday","DK",2009 +"2009-12-25","Christmas Day","DK",2009 +"2009-12-26","Second Day of Christmas","DK",2009 +"2010-01-01","New Year's Day","DK",2010 +"2010-04-01","Maundy Thursday","DK",2010 +"2010-04-02","Good Friday","DK",2010 +"2010-04-04","Easter Sunday","DK",2010 +"2010-04-05","Easter Monday","DK",2010 +"2010-04-30","Great Prayer Day","DK",2010 +"2010-05-13","Ascension Day","DK",2010 +"2010-05-23","Whit Sunday","DK",2010 +"2010-05-24","Whit Monday","DK",2010 +"2010-12-25","Christmas Day","DK",2010 +"2010-12-26","Second Day of Christmas","DK",2010 +"2011-01-01","New Year's Day","DK",2011 +"2011-04-21","Maundy Thursday","DK",2011 +"2011-04-22","Good Friday","DK",2011 +"2011-04-24","Easter Sunday","DK",2011 +"2011-04-25","Easter Monday","DK",2011 +"2011-05-20","Great Prayer Day","DK",2011 +"2011-06-02","Ascension Day","DK",2011 +"2011-06-12","Whit Sunday","DK",2011 +"2011-06-13","Whit Monday","DK",2011 +"2011-12-25","Christmas Day","DK",2011 +"2011-12-26","Second Day of Christmas","DK",2011 +"2012-01-01","New Year's Day","DK",2012 +"2012-04-05","Maundy Thursday","DK",2012 +"2012-04-06","Good Friday","DK",2012 +"2012-04-08","Easter Sunday","DK",2012 +"2012-04-09","Easter Monday","DK",2012 +"2012-05-04","Great Prayer Day","DK",2012 +"2012-05-17","Ascension Day","DK",2012 +"2012-05-27","Whit Sunday","DK",2012 +"2012-05-28","Whit Monday","DK",2012 +"2012-12-25","Christmas Day","DK",2012 +"2012-12-26","Second Day of Christmas","DK",2012 +"2013-01-01","New Year's Day","DK",2013 +"2013-03-28","Maundy Thursday","DK",2013 +"2013-03-29","Good Friday","DK",2013 +"2013-03-31","Easter Sunday","DK",2013 +"2013-04-01","Easter Monday","DK",2013 +"2013-04-26","Great Prayer Day","DK",2013 +"2013-05-09","Ascension Day","DK",2013 +"2013-05-19","Whit Sunday","DK",2013 +"2013-05-20","Whit Monday","DK",2013 +"2013-12-25","Christmas Day","DK",2013 +"2013-12-26","Second Day of Christmas","DK",2013 +"2014-01-01","New Year's Day","DK",2014 +"2014-04-17","Maundy Thursday","DK",2014 +"2014-04-18","Good Friday","DK",2014 +"2014-04-20","Easter Sunday","DK",2014 +"2014-04-21","Easter Monday","DK",2014 +"2014-05-16","Great Prayer Day","DK",2014 +"2014-05-29","Ascension Day","DK",2014 +"2014-06-08","Whit Sunday","DK",2014 +"2014-06-09","Whit Monday","DK",2014 +"2014-12-25","Christmas Day","DK",2014 +"2014-12-26","Second Day of Christmas","DK",2014 +"2015-01-01","New Year's Day","DK",2015 +"2015-04-02","Maundy Thursday","DK",2015 +"2015-04-03","Good Friday","DK",2015 +"2015-04-05","Easter Sunday","DK",2015 +"2015-04-06","Easter Monday","DK",2015 +"2015-05-01","Great Prayer Day","DK",2015 +"2015-05-14","Ascension Day","DK",2015 +"2015-05-24","Whit Sunday","DK",2015 +"2015-05-25","Whit Monday","DK",2015 +"2015-12-25","Christmas Day","DK",2015 +"2015-12-26","Second Day of Christmas","DK",2015 +"2016-01-01","New Year's Day","DK",2016 +"2016-03-24","Maundy Thursday","DK",2016 +"2016-03-25","Good Friday","DK",2016 +"2016-03-27","Easter Sunday","DK",2016 +"2016-03-28","Easter Monday","DK",2016 +"2016-04-22","Great Prayer Day","DK",2016 +"2016-05-05","Ascension Day","DK",2016 +"2016-05-15","Whit Sunday","DK",2016 +"2016-05-16","Whit Monday","DK",2016 +"2016-12-25","Christmas Day","DK",2016 +"2016-12-26","Second Day of Christmas","DK",2016 +"2017-01-01","New Year's Day","DK",2017 +"2017-04-13","Maundy Thursday","DK",2017 +"2017-04-14","Good Friday","DK",2017 +"2017-04-16","Easter Sunday","DK",2017 +"2017-04-17","Easter Monday","DK",2017 +"2017-05-12","Great Prayer Day","DK",2017 +"2017-05-25","Ascension Day","DK",2017 +"2017-06-04","Whit Sunday","DK",2017 +"2017-06-05","Whit Monday","DK",2017 +"2017-12-25","Christmas Day","DK",2017 +"2017-12-26","Second Day of Christmas","DK",2017 +"2018-01-01","New Year's Day","DK",2018 +"2018-03-29","Maundy Thursday","DK",2018 +"2018-03-30","Good Friday","DK",2018 +"2018-04-01","Easter Sunday","DK",2018 +"2018-04-02","Easter Monday","DK",2018 +"2018-04-27","Great Prayer Day","DK",2018 +"2018-05-10","Ascension Day","DK",2018 +"2018-05-20","Whit Sunday","DK",2018 +"2018-05-21","Whit Monday","DK",2018 +"2018-12-25","Christmas Day","DK",2018 +"2018-12-26","Second Day of Christmas","DK",2018 +"2019-01-01","New Year's Day","DK",2019 +"2019-04-18","Maundy Thursday","DK",2019 +"2019-04-19","Good Friday","DK",2019 +"2019-04-21","Easter Sunday","DK",2019 +"2019-04-22","Easter Monday","DK",2019 +"2019-05-17","Great Prayer Day","DK",2019 +"2019-05-30","Ascension Day","DK",2019 +"2019-06-09","Whit Sunday","DK",2019 +"2019-06-10","Whit Monday","DK",2019 +"2019-12-25","Christmas Day","DK",2019 +"2019-12-26","Second Day of Christmas","DK",2019 +"2020-01-01","New Year's Day","DK",2020 +"2020-04-09","Maundy Thursday","DK",2020 +"2020-04-10","Good Friday","DK",2020 +"2020-04-12","Easter Sunday","DK",2020 +"2020-04-13","Easter Monday","DK",2020 +"2020-05-08","Great Prayer Day","DK",2020 +"2020-05-21","Ascension Day","DK",2020 +"2020-05-31","Whit Sunday","DK",2020 +"2020-06-01","Whit Monday","DK",2020 +"2020-12-25","Christmas Day","DK",2020 +"2020-12-26","Second Day of Christmas","DK",2020 +"2021-01-01","New Year's Day","DK",2021 +"2021-04-01","Maundy Thursday","DK",2021 +"2021-04-02","Good Friday","DK",2021 +"2021-04-04","Easter Sunday","DK",2021 +"2021-04-05","Easter Monday","DK",2021 +"2021-04-30","Great Prayer Day","DK",2021 +"2021-05-13","Ascension Day","DK",2021 +"2021-05-23","Whit Sunday","DK",2021 +"2021-05-24","Whit Monday","DK",2021 +"2021-12-25","Christmas Day","DK",2021 +"2021-12-26","Second Day of Christmas","DK",2021 +"2022-01-01","New Year's Day","DK",2022 +"2022-04-14","Maundy Thursday","DK",2022 +"2022-04-15","Good Friday","DK",2022 +"2022-04-17","Easter Sunday","DK",2022 +"2022-04-18","Easter Monday","DK",2022 +"2022-05-13","Great Prayer Day","DK",2022 +"2022-05-26","Ascension Day","DK",2022 +"2022-06-05","Whit Sunday","DK",2022 +"2022-06-06","Whit Monday","DK",2022 +"2022-12-25","Christmas Day","DK",2022 +"2022-12-26","Second Day of Christmas","DK",2022 +"2023-01-01","New Year's Day","DK",2023 +"2023-04-06","Maundy Thursday","DK",2023 +"2023-04-07","Good Friday","DK",2023 +"2023-04-09","Easter Sunday","DK",2023 +"2023-04-10","Easter Monday","DK",2023 +"2023-05-05","Great Prayer Day","DK",2023 +"2023-05-18","Ascension Day","DK",2023 +"2023-05-28","Whit Sunday","DK",2023 +"2023-05-29","Whit Monday","DK",2023 +"2023-12-25","Christmas Day","DK",2023 +"2023-12-26","Second Day of Christmas","DK",2023 +"2024-01-01","New Year's Day","DK",2024 +"2024-03-28","Maundy Thursday","DK",2024 +"2024-03-29","Good Friday","DK",2024 +"2024-03-31","Easter Sunday","DK",2024 +"2024-04-01","Easter Monday","DK",2024 +"2024-05-09","Ascension Day","DK",2024 +"2024-05-19","Whit Sunday","DK",2024 +"2024-05-20","Whit Monday","DK",2024 +"2024-12-25","Christmas Day","DK",2024 +"2024-12-26","Second Day of Christmas","DK",2024 +"2025-01-01","New Year's Day","DK",2025 +"2025-04-17","Maundy Thursday","DK",2025 +"2025-04-18","Good Friday","DK",2025 +"2025-04-20","Easter Sunday","DK",2025 +"2025-04-21","Easter Monday","DK",2025 +"2025-05-29","Ascension Day","DK",2025 +"2025-06-08","Whit Sunday","DK",2025 +"2025-06-09","Whit Monday","DK",2025 +"2025-12-25","Christmas Day","DK",2025 +"2025-12-26","Second Day of Christmas","DK",2025 +"2026-01-01","New Year's Day","DK",2026 +"2026-04-02","Maundy Thursday","DK",2026 +"2026-04-03","Good Friday","DK",2026 +"2026-04-05","Easter Sunday","DK",2026 +"2026-04-06","Easter Monday","DK",2026 +"2026-05-14","Ascension Day","DK",2026 +"2026-05-24","Whit Sunday","DK",2026 +"2026-05-25","Whit Monday","DK",2026 +"2026-12-25","Christmas Day","DK",2026 +"2026-12-26","Second Day of Christmas","DK",2026 +"2027-01-01","New Year's Day","DK",2027 +"2027-03-25","Maundy Thursday","DK",2027 +"2027-03-26","Good Friday","DK",2027 +"2027-03-28","Easter Sunday","DK",2027 +"2027-03-29","Easter Monday","DK",2027 +"2027-05-06","Ascension Day","DK",2027 +"2027-05-16","Whit Sunday","DK",2027 +"2027-05-17","Whit Monday","DK",2027 +"2027-12-25","Christmas Day","DK",2027 +"2027-12-26","Second Day of Christmas","DK",2027 +"2028-01-01","New Year's Day","DK",2028 +"2028-04-13","Maundy Thursday","DK",2028 +"2028-04-14","Good Friday","DK",2028 +"2028-04-16","Easter Sunday","DK",2028 +"2028-04-17","Easter Monday","DK",2028 +"2028-05-25","Ascension Day","DK",2028 +"2028-06-04","Whit Sunday","DK",2028 +"2028-06-05","Whit Monday","DK",2028 +"2028-12-25","Christmas Day","DK",2028 +"2028-12-26","Second Day of Christmas","DK",2028 +"2029-01-01","New Year's Day","DK",2029 +"2029-03-29","Maundy Thursday","DK",2029 +"2029-03-30","Good Friday","DK",2029 +"2029-04-01","Easter Sunday","DK",2029 +"2029-04-02","Easter Monday","DK",2029 +"2029-05-10","Ascension Day","DK",2029 +"2029-05-20","Whit Sunday","DK",2029 +"2029-05-21","Whit Monday","DK",2029 +"2029-12-25","Christmas Day","DK",2029 +"2029-12-26","Second Day of Christmas","DK",2029 +"2030-01-01","New Year's Day","DK",2030 +"2030-04-18","Maundy Thursday","DK",2030 +"2030-04-19","Good Friday","DK",2030 +"2030-04-21","Easter Sunday","DK",2030 +"2030-04-22","Easter Monday","DK",2030 +"2030-05-30","Ascension Day","DK",2030 +"2030-06-09","Whit Sunday","DK",2030 +"2030-06-10","Whit Monday","DK",2030 +"2030-12-25","Christmas Day","DK",2030 +"2030-12-26","Second Day of Christmas","DK",2030 +"2031-01-01","New Year's Day","DK",2031 +"2031-04-10","Maundy Thursday","DK",2031 +"2031-04-11","Good Friday","DK",2031 +"2031-04-13","Easter Sunday","DK",2031 +"2031-04-14","Easter Monday","DK",2031 +"2031-05-22","Ascension Day","DK",2031 +"2031-06-01","Whit Sunday","DK",2031 +"2031-06-02","Whit Monday","DK",2031 +"2031-12-25","Christmas Day","DK",2031 +"2031-12-26","Second Day of Christmas","DK",2031 +"2032-01-01","New Year's Day","DK",2032 +"2032-03-25","Maundy Thursday","DK",2032 +"2032-03-26","Good Friday","DK",2032 +"2032-03-28","Easter Sunday","DK",2032 +"2032-03-29","Easter Monday","DK",2032 +"2032-05-06","Ascension Day","DK",2032 +"2032-05-16","Whit Sunday","DK",2032 +"2032-05-17","Whit Monday","DK",2032 +"2032-12-25","Christmas Day","DK",2032 +"2032-12-26","Second Day of Christmas","DK",2032 +"2033-01-01","New Year's Day","DK",2033 +"2033-04-14","Maundy Thursday","DK",2033 +"2033-04-15","Good Friday","DK",2033 +"2033-04-17","Easter Sunday","DK",2033 +"2033-04-18","Easter Monday","DK",2033 +"2033-05-26","Ascension Day","DK",2033 +"2033-06-05","Whit Sunday","DK",2033 +"2033-06-06","Whit Monday","DK",2033 +"2033-12-25","Christmas Day","DK",2033 +"2033-12-26","Second Day of Christmas","DK",2033 +"2034-01-01","New Year's Day","DK",2034 +"2034-04-06","Maundy Thursday","DK",2034 +"2034-04-07","Good Friday","DK",2034 +"2034-04-09","Easter Sunday","DK",2034 +"2034-04-10","Easter Monday","DK",2034 +"2034-05-18","Ascension Day","DK",2034 +"2034-05-28","Whit Sunday","DK",2034 +"2034-05-29","Whit Monday","DK",2034 +"2034-12-25","Christmas Day","DK",2034 +"2034-12-26","Second Day of Christmas","DK",2034 +"2035-01-01","New Year's Day","DK",2035 +"2035-03-22","Maundy Thursday","DK",2035 +"2035-03-23","Good Friday","DK",2035 +"2035-03-25","Easter Sunday","DK",2035 +"2035-03-26","Easter Monday","DK",2035 +"2035-05-03","Ascension Day","DK",2035 +"2035-05-13","Whit Sunday","DK",2035 +"2035-05-14","Whit Monday","DK",2035 +"2035-12-25","Christmas Day","DK",2035 +"2035-12-26","Second Day of Christmas","DK",2035 +"2036-01-01","New Year's Day","DK",2036 +"2036-04-10","Maundy Thursday","DK",2036 +"2036-04-11","Good Friday","DK",2036 +"2036-04-13","Easter Sunday","DK",2036 +"2036-04-14","Easter Monday","DK",2036 +"2036-05-22","Ascension Day","DK",2036 +"2036-06-01","Whit Sunday","DK",2036 +"2036-06-02","Whit Monday","DK",2036 +"2036-12-25","Christmas Day","DK",2036 +"2036-12-26","Second Day of Christmas","DK",2036 +"2037-01-01","New Year's Day","DK",2037 +"2037-04-02","Maundy Thursday","DK",2037 +"2037-04-03","Good Friday","DK",2037 +"2037-04-05","Easter Sunday","DK",2037 +"2037-04-06","Easter Monday","DK",2037 +"2037-05-14","Ascension Day","DK",2037 +"2037-05-24","Whit Sunday","DK",2037 +"2037-05-25","Whit Monday","DK",2037 +"2037-12-25","Christmas Day","DK",2037 +"2037-12-26","Second Day of Christmas","DK",2037 +"2038-01-01","New Year's Day","DK",2038 +"2038-04-22","Maundy Thursday","DK",2038 +"2038-04-23","Good Friday","DK",2038 +"2038-04-25","Easter Sunday","DK",2038 +"2038-04-26","Easter Monday","DK",2038 +"2038-06-03","Ascension Day","DK",2038 +"2038-06-13","Whit Sunday","DK",2038 +"2038-06-14","Whit Monday","DK",2038 +"2038-12-25","Christmas Day","DK",2038 +"2038-12-26","Second Day of Christmas","DK",2038 +"2039-01-01","New Year's Day","DK",2039 +"2039-04-07","Maundy Thursday","DK",2039 +"2039-04-08","Good Friday","DK",2039 +"2039-04-10","Easter Sunday","DK",2039 +"2039-04-11","Easter Monday","DK",2039 +"2039-05-19","Ascension Day","DK",2039 +"2039-05-29","Whit Sunday","DK",2039 +"2039-05-30","Whit Monday","DK",2039 +"2039-12-25","Christmas Day","DK",2039 +"2039-12-26","Second Day of Christmas","DK",2039 +"2040-01-01","New Year's Day","DK",2040 +"2040-03-29","Maundy Thursday","DK",2040 +"2040-03-30","Good Friday","DK",2040 +"2040-04-01","Easter Sunday","DK",2040 +"2040-04-02","Easter Monday","DK",2040 +"2040-05-10","Ascension Day","DK",2040 +"2040-05-20","Whit Sunday","DK",2040 +"2040-05-21","Whit Monday","DK",2040 +"2040-12-25","Christmas Day","DK",2040 +"2040-12-26","Second Day of Christmas","DK",2040 +"2041-01-01","New Year's Day","DK",2041 +"2041-04-18","Maundy Thursday","DK",2041 +"2041-04-19","Good Friday","DK",2041 +"2041-04-21","Easter Sunday","DK",2041 +"2041-04-22","Easter Monday","DK",2041 +"2041-05-30","Ascension Day","DK",2041 +"2041-06-09","Whit Sunday","DK",2041 +"2041-06-10","Whit Monday","DK",2041 +"2041-12-25","Christmas Day","DK",2041 +"2041-12-26","Second Day of Christmas","DK",2041 +"2042-01-01","New Year's Day","DK",2042 +"2042-04-03","Maundy Thursday","DK",2042 +"2042-04-04","Good Friday","DK",2042 +"2042-04-06","Easter Sunday","DK",2042 +"2042-04-07","Easter Monday","DK",2042 +"2042-05-15","Ascension Day","DK",2042 +"2042-05-25","Whit Sunday","DK",2042 +"2042-05-26","Whit Monday","DK",2042 +"2042-12-25","Christmas Day","DK",2042 +"2042-12-26","Second Day of Christmas","DK",2042 +"2043-01-01","New Year's Day","DK",2043 +"2043-03-26","Maundy Thursday","DK",2043 +"2043-03-27","Good Friday","DK",2043 +"2043-03-29","Easter Sunday","DK",2043 +"2043-03-30","Easter Monday","DK",2043 +"2043-05-07","Ascension Day","DK",2043 +"2043-05-17","Whit Sunday","DK",2043 +"2043-05-18","Whit Monday","DK",2043 +"2043-12-25","Christmas Day","DK",2043 +"2043-12-26","Second Day of Christmas","DK",2043 +"2044-01-01","New Year's Day","DK",2044 +"2044-04-14","Maundy Thursday","DK",2044 +"2044-04-15","Good Friday","DK",2044 +"2044-04-17","Easter Sunday","DK",2044 +"2044-04-18","Easter Monday","DK",2044 +"2044-05-26","Ascension Day","DK",2044 +"2044-06-05","Whit Sunday","DK",2044 +"2044-06-06","Whit Monday","DK",2044 +"2044-12-25","Christmas Day","DK",2044 +"2044-12-26","Second Day of Christmas","DK",2044 +"1995-01-01","New Year's Day","DO",1995 +"1995-01-06","Epiphany","DO",1995 +"1995-01-21","Lady of Altagracia","DO",1995 +"1995-01-26","Juan Pablo Duarte Day","DO",1995 +"1995-02-27","Independence Day","DO",1995 +"1995-04-14","Good Friday","DO",1995 +"1995-05-01","Labor Day","DO",1995 +"1995-06-15","Feast of Corpus Christi","DO",1995 +"1995-08-16","Restoration Day","DO",1995 +"1995-09-24","Our Lady of Mercedes Day","DO",1995 +"1995-11-06","Constitution Day","DO",1995 +"1995-12-25","Christmas Day","DO",1995 +"1996-01-01","New Year's Day","DO",1996 +"1996-01-06","Epiphany","DO",1996 +"1996-01-21","Lady of Altagracia","DO",1996 +"1996-01-26","Juan Pablo Duarte Day","DO",1996 +"1996-02-27","Independence Day","DO",1996 +"1996-04-05","Good Friday","DO",1996 +"1996-05-01","Labor Day","DO",1996 +"1996-06-06","Feast of Corpus Christi","DO",1996 +"1996-08-16","Restoration Day","DO",1996 +"1996-09-24","Our Lady of Mercedes Day","DO",1996 +"1996-11-06","Constitution Day","DO",1996 +"1996-12-25","Christmas Day","DO",1996 +"1997-01-01","New Year's Day","DO",1997 +"1997-01-06","Epiphany","DO",1997 +"1997-01-21","Lady of Altagracia","DO",1997 +"1997-01-26","Juan Pablo Duarte Day","DO",1997 +"1997-02-27","Independence Day","DO",1997 +"1997-03-28","Good Friday","DO",1997 +"1997-05-01","Labor Day","DO",1997 +"1997-05-29","Feast of Corpus Christi","DO",1997 +"1997-08-16","Restoration Day","DO",1997 +"1997-09-24","Our Lady of Mercedes Day","DO",1997 +"1997-11-10","Constitution Day","DO",1997 +"1997-12-25","Christmas Day","DO",1997 +"1998-01-01","New Year's Day","DO",1998 +"1998-01-05","Epiphany","DO",1998 +"1998-01-21","Lady of Altagracia","DO",1998 +"1998-01-26","Juan Pablo Duarte Day","DO",1998 +"1998-02-27","Independence Day","DO",1998 +"1998-04-10","Good Friday","DO",1998 +"1998-05-04","Labor Day","DO",1998 +"1998-06-11","Feast of Corpus Christi","DO",1998 +"1998-08-16","Restoration Day","DO",1998 +"1998-09-24","Our Lady of Mercedes Day","DO",1998 +"1998-11-09","Constitution Day","DO",1998 +"1998-12-25","Christmas Day","DO",1998 +"1999-01-01","New Year's Day","DO",1999 +"1999-01-04","Epiphany","DO",1999 +"1999-01-21","Lady of Altagracia","DO",1999 +"1999-01-25","Juan Pablo Duarte Day","DO",1999 +"1999-02-27","Independence Day","DO",1999 +"1999-04-02","Good Friday","DO",1999 +"1999-05-01","Labor Day","DO",1999 +"1999-06-03","Feast of Corpus Christi","DO",1999 +"1999-08-16","Restoration Day","DO",1999 +"1999-09-24","Our Lady of Mercedes Day","DO",1999 +"1999-11-06","Constitution Day","DO",1999 +"1999-12-25","Christmas Day","DO",1999 +"2000-01-01","New Year's Day","DO",2000 +"2000-01-10","Epiphany","DO",2000 +"2000-01-21","Lady of Altagracia","DO",2000 +"2000-01-24","Juan Pablo Duarte Day","DO",2000 +"2000-02-27","Independence Day","DO",2000 +"2000-04-21","Good Friday","DO",2000 +"2000-05-01","Labor Day","DO",2000 +"2000-06-22","Feast of Corpus Christi","DO",2000 +"2000-08-16","Restoration Day","DO",2000 +"2000-09-24","Our Lady of Mercedes Day","DO",2000 +"2000-11-06","Constitution Day","DO",2000 +"2000-12-25","Christmas Day","DO",2000 +"2001-01-01","New Year's Day","DO",2001 +"2001-01-06","Epiphany","DO",2001 +"2001-01-21","Lady of Altagracia","DO",2001 +"2001-01-29","Juan Pablo Duarte Day","DO",2001 +"2001-02-27","Independence Day","DO",2001 +"2001-04-13","Good Friday","DO",2001 +"2001-04-30","Labor Day","DO",2001 +"2001-06-14","Feast of Corpus Christi","DO",2001 +"2001-08-20","Restoration Day","DO",2001 +"2001-09-24","Our Lady of Mercedes Day","DO",2001 +"2001-11-05","Constitution Day","DO",2001 +"2001-12-25","Christmas Day","DO",2001 +"2002-01-01","New Year's Day","DO",2002 +"2002-01-06","Epiphany","DO",2002 +"2002-01-21","Lady of Altagracia","DO",2002 +"2002-01-26","Juan Pablo Duarte Day","DO",2002 +"2002-02-27","Independence Day","DO",2002 +"2002-03-29","Good Friday","DO",2002 +"2002-04-29","Labor Day","DO",2002 +"2002-05-30","Feast of Corpus Christi","DO",2002 +"2002-08-19","Restoration Day","DO",2002 +"2002-09-24","Our Lady of Mercedes Day","DO",2002 +"2002-11-04","Constitution Day","DO",2002 +"2002-12-25","Christmas Day","DO",2002 +"2003-01-01","New Year's Day","DO",2003 +"2003-01-06","Epiphany","DO",2003 +"2003-01-21","Lady of Altagracia","DO",2003 +"2003-01-26","Juan Pablo Duarte Day","DO",2003 +"2003-02-27","Independence Day","DO",2003 +"2003-04-18","Good Friday","DO",2003 +"2003-05-05","Labor Day","DO",2003 +"2003-06-19","Feast of Corpus Christi","DO",2003 +"2003-08-16","Restoration Day","DO",2003 +"2003-09-24","Our Lady of Mercedes Day","DO",2003 +"2003-11-10","Constitution Day","DO",2003 +"2003-12-25","Christmas Day","DO",2003 +"2004-01-01","New Year's Day","DO",2004 +"2004-01-05","Epiphany","DO",2004 +"2004-01-21","Lady of Altagracia","DO",2004 +"2004-01-26","Juan Pablo Duarte Day","DO",2004 +"2004-02-27","Independence Day","DO",2004 +"2004-04-09","Good Friday","DO",2004 +"2004-05-01","Labor Day","DO",2004 +"2004-06-10","Feast of Corpus Christi","DO",2004 +"2004-08-16","Restoration Day","DO",2004 +"2004-09-24","Our Lady of Mercedes Day","DO",2004 +"2004-11-06","Constitution Day","DO",2004 +"2004-12-25","Christmas Day","DO",2004 +"2005-01-01","New Year's Day","DO",2005 +"2005-01-10","Epiphany","DO",2005 +"2005-01-21","Lady of Altagracia","DO",2005 +"2005-01-24","Juan Pablo Duarte Day","DO",2005 +"2005-02-27","Independence Day","DO",2005 +"2005-03-25","Good Friday","DO",2005 +"2005-05-02","Labor Day","DO",2005 +"2005-05-26","Feast of Corpus Christi","DO",2005 +"2005-08-15","Restoration Day","DO",2005 +"2005-09-24","Our Lady of Mercedes Day","DO",2005 +"2005-11-06","Constitution Day","DO",2005 +"2005-12-25","Christmas Day","DO",2005 +"2006-01-01","New Year's Day","DO",2006 +"2006-01-09","Epiphany","DO",2006 +"2006-01-21","Lady of Altagracia","DO",2006 +"2006-01-30","Juan Pablo Duarte Day","DO",2006 +"2006-02-27","Independence Day","DO",2006 +"2006-04-14","Good Friday","DO",2006 +"2006-05-01","Labor Day","DO",2006 +"2006-06-15","Feast of Corpus Christi","DO",2006 +"2006-08-14","Restoration Day","DO",2006 +"2006-09-24","Our Lady of Mercedes Day","DO",2006 +"2006-11-06","Constitution Day","DO",2006 +"2006-12-25","Christmas Day","DO",2006 +"2007-01-01","New Year's Day","DO",2007 +"2007-01-06","Epiphany","DO",2007 +"2007-01-21","Lady of Altagracia","DO",2007 +"2007-01-29","Juan Pablo Duarte Day","DO",2007 +"2007-02-27","Independence Day","DO",2007 +"2007-04-06","Good Friday","DO",2007 +"2007-04-30","Labor Day","DO",2007 +"2007-06-07","Feast of Corpus Christi","DO",2007 +"2007-08-20","Restoration Day","DO",2007 +"2007-09-24","Our Lady of Mercedes Day","DO",2007 +"2007-11-05","Constitution Day","DO",2007 +"2007-12-25","Christmas Day","DO",2007 +"2008-01-01","New Year's Day","DO",2008 +"2008-01-06","Epiphany","DO",2008 +"2008-01-21","Lady of Altagracia","DO",2008 +"2008-01-26","Juan Pablo Duarte Day","DO",2008 +"2008-02-27","Independence Day","DO",2008 +"2008-03-21","Good Friday","DO",2008 +"2008-05-05","Labor Day","DO",2008 +"2008-05-22","Feast of Corpus Christi","DO",2008 +"2008-08-16","Restoration Day","DO",2008 +"2008-09-24","Our Lady of Mercedes Day","DO",2008 +"2008-11-10","Constitution Day","DO",2008 +"2008-12-25","Christmas Day","DO",2008 +"2009-01-01","New Year's Day","DO",2009 +"2009-01-05","Epiphany","DO",2009 +"2009-01-21","Lady of Altagracia","DO",2009 +"2009-01-26","Juan Pablo Duarte Day","DO",2009 +"2009-02-27","Independence Day","DO",2009 +"2009-04-10","Good Friday","DO",2009 +"2009-05-04","Labor Day","DO",2009 +"2009-06-11","Feast of Corpus Christi","DO",2009 +"2009-08-16","Restoration Day","DO",2009 +"2009-09-24","Our Lady of Mercedes Day","DO",2009 +"2009-11-09","Constitution Day","DO",2009 +"2009-12-25","Christmas Day","DO",2009 +"2010-01-01","New Year's Day","DO",2010 +"2010-01-04","Epiphany","DO",2010 +"2010-01-21","Lady of Altagracia","DO",2010 +"2010-01-25","Juan Pablo Duarte Day","DO",2010 +"2010-02-27","Independence Day","DO",2010 +"2010-04-02","Good Friday","DO",2010 +"2010-05-01","Labor Day","DO",2010 +"2010-06-03","Feast of Corpus Christi","DO",2010 +"2010-08-16","Restoration Day","DO",2010 +"2010-09-24","Our Lady of Mercedes Day","DO",2010 +"2010-11-06","Constitution Day","DO",2010 +"2010-12-25","Christmas Day","DO",2010 +"2011-01-01","New Year's Day","DO",2011 +"2011-01-10","Epiphany","DO",2011 +"2011-01-21","Lady of Altagracia","DO",2011 +"2011-01-24","Juan Pablo Duarte Day","DO",2011 +"2011-02-27","Independence Day","DO",2011 +"2011-04-22","Good Friday","DO",2011 +"2011-05-02","Labor Day","DO",2011 +"2011-06-23","Feast of Corpus Christi","DO",2011 +"2011-08-15","Restoration Day","DO",2011 +"2011-09-24","Our Lady of Mercedes Day","DO",2011 +"2011-11-06","Constitution Day","DO",2011 +"2011-12-25","Christmas Day","DO",2011 +"2012-01-01","New Year's Day","DO",2012 +"2012-01-09","Epiphany","DO",2012 +"2012-01-21","Lady of Altagracia","DO",2012 +"2012-01-30","Juan Pablo Duarte Day","DO",2012 +"2012-02-27","Independence Day","DO",2012 +"2012-04-06","Good Friday","DO",2012 +"2012-04-30","Labor Day","DO",2012 +"2012-06-07","Feast of Corpus Christi","DO",2012 +"2012-08-20","Restoration Day","DO",2012 +"2012-09-24","Our Lady of Mercedes Day","DO",2012 +"2012-11-05","Constitution Day","DO",2012 +"2012-12-25","Christmas Day","DO",2012 +"2013-01-01","New Year's Day","DO",2013 +"2013-01-06","Epiphany","DO",2013 +"2013-01-21","Lady of Altagracia","DO",2013 +"2013-01-26","Juan Pablo Duarte Day","DO",2013 +"2013-02-27","Independence Day","DO",2013 +"2013-03-29","Good Friday","DO",2013 +"2013-04-29","Labor Day","DO",2013 +"2013-05-30","Feast of Corpus Christi","DO",2013 +"2013-08-19","Restoration Day","DO",2013 +"2013-09-24","Our Lady of Mercedes Day","DO",2013 +"2013-11-04","Constitution Day","DO",2013 +"2013-12-25","Christmas Day","DO",2013 +"2014-01-01","New Year's Day","DO",2014 +"2014-01-06","Epiphany","DO",2014 +"2014-01-21","Lady of Altagracia","DO",2014 +"2014-01-26","Juan Pablo Duarte Day","DO",2014 +"2014-02-27","Independence Day","DO",2014 +"2014-04-18","Good Friday","DO",2014 +"2014-05-05","Labor Day","DO",2014 +"2014-06-19","Feast of Corpus Christi","DO",2014 +"2014-08-16","Restoration Day","DO",2014 +"2014-09-24","Our Lady of Mercedes Day","DO",2014 +"2014-11-10","Constitution Day","DO",2014 +"2014-12-25","Christmas Day","DO",2014 +"2015-01-01","New Year's Day","DO",2015 +"2015-01-05","Epiphany","DO",2015 +"2015-01-21","Lady of Altagracia","DO",2015 +"2015-01-26","Juan Pablo Duarte Day","DO",2015 +"2015-02-27","Independence Day","DO",2015 +"2015-04-03","Good Friday","DO",2015 +"2015-05-04","Labor Day","DO",2015 +"2015-06-04","Feast of Corpus Christi","DO",2015 +"2015-08-16","Restoration Day","DO",2015 +"2015-09-24","Our Lady of Mercedes Day","DO",2015 +"2015-11-09","Constitution Day","DO",2015 +"2015-12-25","Christmas Day","DO",2015 +"2016-01-01","New Year's Day","DO",2016 +"2016-01-04","Epiphany","DO",2016 +"2016-01-21","Lady of Altagracia","DO",2016 +"2016-01-25","Juan Pablo Duarte Day","DO",2016 +"2016-02-27","Independence Day","DO",2016 +"2016-03-25","Good Friday","DO",2016 +"2016-05-02","Labor Day","DO",2016 +"2016-05-26","Feast of Corpus Christi","DO",2016 +"2016-08-15","Restoration Day","DO",2016 +"2016-09-24","Our Lady of Mercedes Day","DO",2016 +"2016-11-06","Constitution Day","DO",2016 +"2016-12-25","Christmas Day","DO",2016 +"2017-01-01","New Year's Day","DO",2017 +"2017-01-09","Epiphany","DO",2017 +"2017-01-21","Lady of Altagracia","DO",2017 +"2017-01-30","Juan Pablo Duarte Day","DO",2017 +"2017-02-27","Independence Day","DO",2017 +"2017-04-14","Good Friday","DO",2017 +"2017-05-01","Labor Day","DO",2017 +"2017-06-15","Feast of Corpus Christi","DO",2017 +"2017-08-14","Restoration Day","DO",2017 +"2017-09-24","Our Lady of Mercedes Day","DO",2017 +"2017-11-06","Constitution Day","DO",2017 +"2017-12-25","Christmas Day","DO",2017 +"2018-01-01","New Year's Day","DO",2018 +"2018-01-06","Epiphany","DO",2018 +"2018-01-21","Lady of Altagracia","DO",2018 +"2018-01-29","Juan Pablo Duarte Day","DO",2018 +"2018-02-27","Independence Day","DO",2018 +"2018-03-30","Good Friday","DO",2018 +"2018-04-30","Labor Day","DO",2018 +"2018-05-31","Feast of Corpus Christi","DO",2018 +"2018-08-20","Restoration Day","DO",2018 +"2018-09-24","Our Lady of Mercedes Day","DO",2018 +"2018-11-05","Constitution Day","DO",2018 +"2018-12-25","Christmas Day","DO",2018 +"2019-01-01","New Year's Day","DO",2019 +"2019-01-06","Epiphany","DO",2019 +"2019-01-21","Lady of Altagracia","DO",2019 +"2019-01-26","Juan Pablo Duarte Day","DO",2019 +"2019-02-27","Independence Day","DO",2019 +"2019-04-19","Good Friday","DO",2019 +"2019-04-29","Labor Day","DO",2019 +"2019-06-20","Feast of Corpus Christi","DO",2019 +"2019-08-19","Restoration Day","DO",2019 +"2019-09-24","Our Lady of Mercedes Day","DO",2019 +"2019-11-04","Constitution Day","DO",2019 +"2019-12-25","Christmas Day","DO",2019 +"2020-01-01","New Year's Day","DO",2020 +"2020-01-06","Epiphany","DO",2020 +"2020-01-21","Lady of Altagracia","DO",2020 +"2020-01-26","Juan Pablo Duarte Day","DO",2020 +"2020-02-27","Independence Day","DO",2020 +"2020-04-10","Good Friday","DO",2020 +"2020-05-04","Labor Day","DO",2020 +"2020-06-11","Feast of Corpus Christi","DO",2020 +"2020-08-16","Restoration Day","DO",2020 +"2020-09-24","Our Lady of Mercedes Day","DO",2020 +"2020-11-09","Constitution Day","DO",2020 +"2020-12-25","Christmas Day","DO",2020 +"2021-01-01","New Year's Day","DO",2021 +"2021-01-04","Epiphany","DO",2021 +"2021-01-21","Lady of Altagracia","DO",2021 +"2021-01-25","Juan Pablo Duarte Day","DO",2021 +"2021-02-27","Independence Day","DO",2021 +"2021-04-02","Good Friday","DO",2021 +"2021-05-01","Labor Day","DO",2021 +"2021-06-03","Feast of Corpus Christi","DO",2021 +"2021-08-16","Restoration Day","DO",2021 +"2021-09-24","Our Lady of Mercedes Day","DO",2021 +"2021-11-06","Constitution Day","DO",2021 +"2021-12-25","Christmas Day","DO",2021 +"2022-01-01","New Year's Day","DO",2022 +"2022-01-10","Epiphany","DO",2022 +"2022-01-21","Lady of Altagracia","DO",2022 +"2022-01-24","Juan Pablo Duarte Day","DO",2022 +"2022-02-27","Independence Day","DO",2022 +"2022-04-15","Good Friday","DO",2022 +"2022-05-02","Labor Day","DO",2022 +"2022-06-16","Feast of Corpus Christi","DO",2022 +"2022-08-15","Restoration Day","DO",2022 +"2022-09-24","Our Lady of Mercedes Day","DO",2022 +"2022-11-06","Constitution Day","DO",2022 +"2022-12-25","Christmas Day","DO",2022 +"2023-01-01","New Year's Day","DO",2023 +"2023-01-09","Epiphany","DO",2023 +"2023-01-21","Lady of Altagracia","DO",2023 +"2023-01-30","Juan Pablo Duarte Day","DO",2023 +"2023-02-27","Independence Day","DO",2023 +"2023-04-07","Good Friday","DO",2023 +"2023-05-01","Labor Day","DO",2023 +"2023-06-08","Feast of Corpus Christi","DO",2023 +"2023-08-14","Restoration Day","DO",2023 +"2023-09-24","Our Lady of Mercedes Day","DO",2023 +"2023-11-06","Constitution Day","DO",2023 +"2023-12-25","Christmas Day","DO",2023 +"2024-01-01","New Year's Day","DO",2024 +"2024-01-06","Epiphany","DO",2024 +"2024-01-21","Lady of Altagracia","DO",2024 +"2024-01-29","Juan Pablo Duarte Day","DO",2024 +"2024-02-27","Independence Day","DO",2024 +"2024-03-29","Good Friday","DO",2024 +"2024-04-29","Labor Day","DO",2024 +"2024-05-30","Feast of Corpus Christi","DO",2024 +"2024-08-19","Restoration Day","DO",2024 +"2024-09-24","Our Lady of Mercedes Day","DO",2024 +"2024-11-04","Constitution Day","DO",2024 +"2024-12-25","Christmas Day","DO",2024 +"2025-01-01","New Year's Day","DO",2025 +"2025-01-06","Epiphany","DO",2025 +"2025-01-21","Lady of Altagracia","DO",2025 +"2025-01-26","Juan Pablo Duarte Day","DO",2025 +"2025-02-27","Independence Day","DO",2025 +"2025-04-18","Good Friday","DO",2025 +"2025-05-05","Labor Day","DO",2025 +"2025-06-19","Feast of Corpus Christi","DO",2025 +"2025-08-16","Restoration Day","DO",2025 +"2025-09-24","Our Lady of Mercedes Day","DO",2025 +"2025-11-10","Constitution Day","DO",2025 +"2025-12-25","Christmas Day","DO",2025 +"2026-01-01","New Year's Day","DO",2026 +"2026-01-05","Epiphany","DO",2026 +"2026-01-21","Lady of Altagracia","DO",2026 +"2026-01-26","Juan Pablo Duarte Day","DO",2026 +"2026-02-27","Independence Day","DO",2026 +"2026-04-03","Good Friday","DO",2026 +"2026-05-04","Labor Day","DO",2026 +"2026-06-04","Feast of Corpus Christi","DO",2026 +"2026-08-16","Restoration Day","DO",2026 +"2026-09-24","Our Lady of Mercedes Day","DO",2026 +"2026-11-09","Constitution Day","DO",2026 +"2026-12-25","Christmas Day","DO",2026 +"2027-01-01","New Year's Day","DO",2027 +"2027-01-04","Epiphany","DO",2027 +"2027-01-21","Lady of Altagracia","DO",2027 +"2027-01-25","Juan Pablo Duarte Day","DO",2027 +"2027-02-27","Independence Day","DO",2027 +"2027-03-26","Good Friday","DO",2027 +"2027-05-01","Labor Day","DO",2027 +"2027-05-27","Feast of Corpus Christi","DO",2027 +"2027-08-16","Restoration Day","DO",2027 +"2027-09-24","Our Lady of Mercedes Day","DO",2027 +"2027-11-06","Constitution Day","DO",2027 +"2027-12-25","Christmas Day","DO",2027 +"2028-01-01","New Year's Day","DO",2028 +"2028-01-10","Epiphany","DO",2028 +"2028-01-21","Lady of Altagracia","DO",2028 +"2028-01-24","Juan Pablo Duarte Day","DO",2028 +"2028-02-27","Independence Day","DO",2028 +"2028-04-14","Good Friday","DO",2028 +"2028-05-01","Labor Day","DO",2028 +"2028-06-15","Feast of Corpus Christi","DO",2028 +"2028-08-14","Restoration Day","DO",2028 +"2028-09-24","Our Lady of Mercedes Day","DO",2028 +"2028-11-06","Constitution Day","DO",2028 +"2028-12-25","Christmas Day","DO",2028 +"2029-01-01","New Year's Day","DO",2029 +"2029-01-06","Epiphany","DO",2029 +"2029-01-21","Lady of Altagracia","DO",2029 +"2029-01-29","Juan Pablo Duarte Day","DO",2029 +"2029-02-27","Independence Day","DO",2029 +"2029-03-30","Good Friday","DO",2029 +"2029-04-30","Labor Day","DO",2029 +"2029-05-31","Feast of Corpus Christi","DO",2029 +"2029-08-20","Restoration Day","DO",2029 +"2029-09-24","Our Lady of Mercedes Day","DO",2029 +"2029-11-05","Constitution Day","DO",2029 +"2029-12-25","Christmas Day","DO",2029 +"2030-01-01","New Year's Day","DO",2030 +"2030-01-06","Epiphany","DO",2030 +"2030-01-21","Lady of Altagracia","DO",2030 +"2030-01-26","Juan Pablo Duarte Day","DO",2030 +"2030-02-27","Independence Day","DO",2030 +"2030-04-19","Good Friday","DO",2030 +"2030-04-29","Labor Day","DO",2030 +"2030-06-20","Feast of Corpus Christi","DO",2030 +"2030-08-19","Restoration Day","DO",2030 +"2030-09-24","Our Lady of Mercedes Day","DO",2030 +"2030-11-04","Constitution Day","DO",2030 +"2030-12-25","Christmas Day","DO",2030 +"2031-01-01","New Year's Day","DO",2031 +"2031-01-06","Epiphany","DO",2031 +"2031-01-21","Lady of Altagracia","DO",2031 +"2031-01-26","Juan Pablo Duarte Day","DO",2031 +"2031-02-27","Independence Day","DO",2031 +"2031-04-11","Good Friday","DO",2031 +"2031-05-05","Labor Day","DO",2031 +"2031-06-12","Feast of Corpus Christi","DO",2031 +"2031-08-16","Restoration Day","DO",2031 +"2031-09-24","Our Lady of Mercedes Day","DO",2031 +"2031-11-10","Constitution Day","DO",2031 +"2031-12-25","Christmas Day","DO",2031 +"2032-01-01","New Year's Day","DO",2032 +"2032-01-05","Epiphany","DO",2032 +"2032-01-21","Lady of Altagracia","DO",2032 +"2032-01-26","Juan Pablo Duarte Day","DO",2032 +"2032-02-27","Independence Day","DO",2032 +"2032-03-26","Good Friday","DO",2032 +"2032-05-01","Labor Day","DO",2032 +"2032-05-27","Feast of Corpus Christi","DO",2032 +"2032-08-16","Restoration Day","DO",2032 +"2032-09-24","Our Lady of Mercedes Day","DO",2032 +"2032-11-06","Constitution Day","DO",2032 +"2032-12-25","Christmas Day","DO",2032 +"2033-01-01","New Year's Day","DO",2033 +"2033-01-10","Epiphany","DO",2033 +"2033-01-21","Lady of Altagracia","DO",2033 +"2033-01-24","Juan Pablo Duarte Day","DO",2033 +"2033-02-27","Independence Day","DO",2033 +"2033-04-15","Good Friday","DO",2033 +"2033-05-02","Labor Day","DO",2033 +"2033-06-16","Feast of Corpus Christi","DO",2033 +"2033-08-15","Restoration Day","DO",2033 +"2033-09-24","Our Lady of Mercedes Day","DO",2033 +"2033-11-06","Constitution Day","DO",2033 +"2033-12-25","Christmas Day","DO",2033 +"2034-01-01","New Year's Day","DO",2034 +"2034-01-09","Epiphany","DO",2034 +"2034-01-21","Lady of Altagracia","DO",2034 +"2034-01-30","Juan Pablo Duarte Day","DO",2034 +"2034-02-27","Independence Day","DO",2034 +"2034-04-07","Good Friday","DO",2034 +"2034-05-01","Labor Day","DO",2034 +"2034-06-08","Feast of Corpus Christi","DO",2034 +"2034-08-14","Restoration Day","DO",2034 +"2034-09-24","Our Lady of Mercedes Day","DO",2034 +"2034-11-06","Constitution Day","DO",2034 +"2034-12-25","Christmas Day","DO",2034 +"2035-01-01","New Year's Day","DO",2035 +"2035-01-06","Epiphany","DO",2035 +"2035-01-21","Lady of Altagracia","DO",2035 +"2035-01-29","Juan Pablo Duarte Day","DO",2035 +"2035-02-27","Independence Day","DO",2035 +"2035-03-23","Good Friday","DO",2035 +"2035-04-30","Labor Day","DO",2035 +"2035-05-24","Feast of Corpus Christi","DO",2035 +"2035-08-20","Restoration Day","DO",2035 +"2035-09-24","Our Lady of Mercedes Day","DO",2035 +"2035-11-05","Constitution Day","DO",2035 +"2035-12-25","Christmas Day","DO",2035 +"2036-01-01","New Year's Day","DO",2036 +"2036-01-06","Epiphany","DO",2036 +"2036-01-21","Lady of Altagracia","DO",2036 +"2036-01-26","Juan Pablo Duarte Day","DO",2036 +"2036-02-27","Independence Day","DO",2036 +"2036-04-11","Good Friday","DO",2036 +"2036-05-05","Labor Day","DO",2036 +"2036-06-12","Feast of Corpus Christi","DO",2036 +"2036-08-16","Restoration Day","DO",2036 +"2036-09-24","Our Lady of Mercedes Day","DO",2036 +"2036-11-10","Constitution Day","DO",2036 +"2036-12-25","Christmas Day","DO",2036 +"2037-01-01","New Year's Day","DO",2037 +"2037-01-05","Epiphany","DO",2037 +"2037-01-21","Lady of Altagracia","DO",2037 +"2037-01-26","Juan Pablo Duarte Day","DO",2037 +"2037-02-27","Independence Day","DO",2037 +"2037-04-03","Good Friday","DO",2037 +"2037-05-04","Labor Day","DO",2037 +"2037-06-04","Feast of Corpus Christi","DO",2037 +"2037-08-16","Restoration Day","DO",2037 +"2037-09-24","Our Lady of Mercedes Day","DO",2037 +"2037-11-09","Constitution Day","DO",2037 +"2037-12-25","Christmas Day","DO",2037 +"2038-01-01","New Year's Day","DO",2038 +"2038-01-04","Epiphany","DO",2038 +"2038-01-21","Lady of Altagracia","DO",2038 +"2038-01-25","Juan Pablo Duarte Day","DO",2038 +"2038-02-27","Independence Day","DO",2038 +"2038-04-23","Good Friday","DO",2038 +"2038-05-01","Labor Day","DO",2038 +"2038-06-24","Feast of Corpus Christi","DO",2038 +"2038-08-16","Restoration Day","DO",2038 +"2038-09-24","Our Lady of Mercedes Day","DO",2038 +"2038-11-06","Constitution Day","DO",2038 +"2038-12-25","Christmas Day","DO",2038 +"2039-01-01","New Year's Day","DO",2039 +"2039-01-10","Epiphany","DO",2039 +"2039-01-21","Lady of Altagracia","DO",2039 +"2039-01-24","Juan Pablo Duarte Day","DO",2039 +"2039-02-27","Independence Day","DO",2039 +"2039-04-08","Good Friday","DO",2039 +"2039-05-02","Labor Day","DO",2039 +"2039-06-09","Feast of Corpus Christi","DO",2039 +"2039-08-15","Restoration Day","DO",2039 +"2039-09-24","Our Lady of Mercedes Day","DO",2039 +"2039-11-06","Constitution Day","DO",2039 +"2039-12-25","Christmas Day","DO",2039 +"2040-01-01","New Year's Day","DO",2040 +"2040-01-09","Epiphany","DO",2040 +"2040-01-21","Lady of Altagracia","DO",2040 +"2040-01-30","Juan Pablo Duarte Day","DO",2040 +"2040-02-27","Independence Day","DO",2040 +"2040-03-30","Good Friday","DO",2040 +"2040-04-30","Labor Day","DO",2040 +"2040-05-31","Feast of Corpus Christi","DO",2040 +"2040-08-20","Restoration Day","DO",2040 +"2040-09-24","Our Lady of Mercedes Day","DO",2040 +"2040-11-05","Constitution Day","DO",2040 +"2040-12-25","Christmas Day","DO",2040 +"2041-01-01","New Year's Day","DO",2041 +"2041-01-06","Epiphany","DO",2041 +"2041-01-21","Lady of Altagracia","DO",2041 +"2041-01-26","Juan Pablo Duarte Day","DO",2041 +"2041-02-27","Independence Day","DO",2041 +"2041-04-19","Good Friday","DO",2041 +"2041-04-29","Labor Day","DO",2041 +"2041-06-20","Feast of Corpus Christi","DO",2041 +"2041-08-19","Restoration Day","DO",2041 +"2041-09-24","Our Lady of Mercedes Day","DO",2041 +"2041-11-04","Constitution Day","DO",2041 +"2041-12-25","Christmas Day","DO",2041 +"2042-01-01","New Year's Day","DO",2042 +"2042-01-06","Epiphany","DO",2042 +"2042-01-21","Lady of Altagracia","DO",2042 +"2042-01-26","Juan Pablo Duarte Day","DO",2042 +"2042-02-27","Independence Day","DO",2042 +"2042-04-04","Good Friday","DO",2042 +"2042-05-05","Labor Day","DO",2042 +"2042-06-05","Feast of Corpus Christi","DO",2042 +"2042-08-16","Restoration Day","DO",2042 +"2042-09-24","Our Lady of Mercedes Day","DO",2042 +"2042-11-10","Constitution Day","DO",2042 +"2042-12-25","Christmas Day","DO",2042 +"2043-01-01","New Year's Day","DO",2043 +"2043-01-05","Epiphany","DO",2043 +"2043-01-21","Lady of Altagracia","DO",2043 +"2043-01-26","Juan Pablo Duarte Day","DO",2043 +"2043-02-27","Independence Day","DO",2043 +"2043-03-27","Good Friday","DO",2043 +"2043-05-04","Labor Day","DO",2043 +"2043-05-28","Feast of Corpus Christi","DO",2043 +"2043-08-16","Restoration Day","DO",2043 +"2043-09-24","Our Lady of Mercedes Day","DO",2043 +"2043-11-09","Constitution Day","DO",2043 +"2043-12-25","Christmas Day","DO",2043 +"2044-01-01","New Year's Day","DO",2044 +"2044-01-04","Epiphany","DO",2044 +"2044-01-21","Lady of Altagracia","DO",2044 +"2044-01-25","Juan Pablo Duarte Day","DO",2044 +"2044-02-27","Independence Day","DO",2044 +"2044-04-15","Good Friday","DO",2044 +"2044-05-02","Labor Day","DO",2044 +"2044-06-16","Feast of Corpus Christi","DO",2044 +"2044-08-15","Restoration Day","DO",2044 +"2044-09-24","Our Lady of Mercedes Day","DO",2044 +"2044-11-06","Constitution Day","DO",2044 +"2044-12-25","Christmas Day","DO",2044 +"1995-01-01","New Year's Day","DZ",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","DZ",1995 +"1995-03-03","Eid al-Fitr Holiday* (*estimated)","DZ",1995 +"1995-05-01","Labour Day","DZ",1995 +"1995-05-09","Eid al-Adha* (*estimated)","DZ",1995 +"1995-05-10","Eid al-Adha Holiday* (*estimated)","DZ",1995 +"1995-05-30","Islamic New Year* (*estimated)","DZ",1995 +"1995-06-08","Ashura Day* (*estimated)","DZ",1995 +"1995-07-05","Independence Day","DZ",1995 +"1995-08-08","Prophet's Birthday* (*estimated)","DZ",1995 +"1995-11-01","Revolution Day","DZ",1995 +"1996-01-01","New Year's Day","DZ",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","DZ",1996 +"1996-02-20","Eid al-Fitr Holiday* (*estimated)","DZ",1996 +"1996-04-27","Eid al-Adha* (*estimated)","DZ",1996 +"1996-04-28","Eid al-Adha Holiday* (*estimated)","DZ",1996 +"1996-05-01","Labour Day","DZ",1996 +"1996-05-18","Islamic New Year* (*estimated)","DZ",1996 +"1996-05-27","Ashura Day* (*estimated)","DZ",1996 +"1996-07-05","Independence Day","DZ",1996 +"1996-07-27","Prophet's Birthday* (*estimated)","DZ",1996 +"1996-11-01","Revolution Day","DZ",1996 +"1997-01-01","New Year's Day","DZ",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","DZ",1997 +"1997-02-09","Eid al-Fitr Holiday* (*estimated)","DZ",1997 +"1997-04-17","Eid al-Adha* (*estimated)","DZ",1997 +"1997-04-18","Eid al-Adha Holiday* (*estimated)","DZ",1997 +"1997-05-01","Labour Day","DZ",1997 +"1997-05-07","Islamic New Year* (*estimated)","DZ",1997 +"1997-05-16","Ashura Day* (*estimated)","DZ",1997 +"1997-07-05","Independence Day","DZ",1997 +"1997-07-16","Prophet's Birthday* (*estimated)","DZ",1997 +"1997-11-01","Revolution Day","DZ",1997 +"1998-01-01","New Year's Day","DZ",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","DZ",1998 +"1998-01-30","Eid al-Fitr Holiday* (*estimated)","DZ",1998 +"1998-04-07","Eid al-Adha* (*estimated)","DZ",1998 +"1998-04-08","Eid al-Adha Holiday* (*estimated)","DZ",1998 +"1998-04-27","Islamic New Year* (*estimated)","DZ",1998 +"1998-05-01","Labour Day","DZ",1998 +"1998-05-06","Ashura Day* (*estimated)","DZ",1998 +"1998-07-05","Independence Day","DZ",1998 +"1998-07-06","Prophet's Birthday* (*estimated)","DZ",1998 +"1998-11-01","Revolution Day","DZ",1998 +"1999-01-01","New Year's Day","DZ",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","DZ",1999 +"1999-01-19","Eid al-Fitr Holiday* (*estimated)","DZ",1999 +"1999-03-27","Eid al-Adha* (*estimated)","DZ",1999 +"1999-03-28","Eid al-Adha Holiday* (*estimated)","DZ",1999 +"1999-04-17","Islamic New Year* (*estimated)","DZ",1999 +"1999-04-26","Ashura Day* (*estimated)","DZ",1999 +"1999-05-01","Labour Day","DZ",1999 +"1999-06-26","Prophet's Birthday* (*estimated)","DZ",1999 +"1999-07-05","Independence Day","DZ",1999 +"1999-11-01","Revolution Day","DZ",1999 +"2000-01-01","New Year's Day","DZ",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","DZ",2000 +"2000-01-09","Eid al-Fitr Holiday* (*estimated)","DZ",2000 +"2000-03-16","Eid al-Adha* (*estimated)","DZ",2000 +"2000-03-17","Eid al-Adha Holiday* (*estimated)","DZ",2000 +"2000-04-06","Islamic New Year* (*estimated)","DZ",2000 +"2000-04-15","Ashura Day* (*estimated)","DZ",2000 +"2000-05-01","Labour Day","DZ",2000 +"2000-06-14","Prophet's Birthday* (*estimated)","DZ",2000 +"2000-07-05","Independence Day","DZ",2000 +"2000-11-01","Revolution Day","DZ",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","DZ",2000 +"2000-12-28","Eid al-Fitr Holiday* (*estimated)","DZ",2000 +"2001-01-01","New Year's Day","DZ",2001 +"2001-03-05","Eid al-Adha* (*estimated)","DZ",2001 +"2001-03-06","Eid al-Adha Holiday* (*estimated)","DZ",2001 +"2001-03-26","Islamic New Year* (*estimated)","DZ",2001 +"2001-04-04","Ashura Day* (*estimated)","DZ",2001 +"2001-05-01","Labour Day","DZ",2001 +"2001-06-04","Prophet's Birthday* (*estimated)","DZ",2001 +"2001-07-05","Independence Day","DZ",2001 +"2001-11-01","Revolution Day","DZ",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","DZ",2001 +"2001-12-17","Eid al-Fitr Holiday* (*estimated)","DZ",2001 +"2002-01-01","New Year's Day","DZ",2002 +"2002-02-22","Eid al-Adha* (*estimated)","DZ",2002 +"2002-02-23","Eid al-Adha Holiday* (*estimated)","DZ",2002 +"2002-03-15","Islamic New Year* (*estimated)","DZ",2002 +"2002-03-24","Ashura Day* (*estimated)","DZ",2002 +"2002-05-01","Labour Day","DZ",2002 +"2002-05-24","Prophet's Birthday* (*estimated)","DZ",2002 +"2002-07-05","Independence Day","DZ",2002 +"2002-11-01","Revolution Day","DZ",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","DZ",2002 +"2002-12-06","Eid al-Fitr Holiday* (*estimated)","DZ",2002 +"2003-01-01","New Year's Day","DZ",2003 +"2003-02-11","Eid al-Adha* (*estimated)","DZ",2003 +"2003-02-12","Eid al-Adha Holiday* (*estimated)","DZ",2003 +"2003-03-04","Islamic New Year* (*estimated)","DZ",2003 +"2003-03-13","Ashura Day* (*estimated)","DZ",2003 +"2003-05-01","Labour Day","DZ",2003 +"2003-05-13","Prophet's Birthday* (*estimated)","DZ",2003 +"2003-07-05","Independence Day","DZ",2003 +"2003-11-01","Revolution Day","DZ",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","DZ",2003 +"2003-11-26","Eid al-Fitr Holiday* (*estimated)","DZ",2003 +"2004-01-01","New Year's Day","DZ",2004 +"2004-02-01","Eid al-Adha* (*estimated)","DZ",2004 +"2004-02-02","Eid al-Adha Holiday* (*estimated)","DZ",2004 +"2004-02-21","Islamic New Year* (*estimated)","DZ",2004 +"2004-03-01","Ashura Day* (*estimated)","DZ",2004 +"2004-05-01","Labour Day","DZ",2004 +"2004-05-01","Prophet's Birthday* (*estimated)","DZ",2004 +"2004-07-05","Independence Day","DZ",2004 +"2004-11-01","Revolution Day","DZ",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","DZ",2004 +"2004-11-15","Eid al-Fitr Holiday* (*estimated)","DZ",2004 +"2005-01-01","New Year's Day","DZ",2005 +"2005-01-21","Eid al-Adha* (*estimated)","DZ",2005 +"2005-01-22","Eid al-Adha Holiday* (*estimated)","DZ",2005 +"2005-02-10","Islamic New Year* (*estimated)","DZ",2005 +"2005-02-19","Ashura Day* (*estimated)","DZ",2005 +"2005-04-21","Prophet's Birthday* (*estimated)","DZ",2005 +"2005-05-01","Labour Day","DZ",2005 +"2005-07-05","Independence Day","DZ",2005 +"2005-11-01","Revolution Day","DZ",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","DZ",2005 +"2005-11-04","Eid al-Fitr Holiday* (*estimated)","DZ",2005 +"2006-01-01","New Year's Day","DZ",2006 +"2006-01-10","Eid al-Adha* (*estimated)","DZ",2006 +"2006-01-11","Eid al-Adha Holiday* (*estimated)","DZ",2006 +"2006-01-31","Islamic New Year* (*estimated)","DZ",2006 +"2006-02-09","Ashura Day* (*estimated)","DZ",2006 +"2006-04-10","Prophet's Birthday* (*estimated)","DZ",2006 +"2006-05-01","Labour Day","DZ",2006 +"2006-07-05","Independence Day","DZ",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","DZ",2006 +"2006-10-24","Eid al-Fitr Holiday* (*estimated)","DZ",2006 +"2006-11-01","Revolution Day","DZ",2006 +"2006-12-31","Eid al-Adha* (*estimated)","DZ",2006 +"2007-01-01","Eid al-Adha Holiday* (*estimated)","DZ",2007 +"2007-01-01","New Year's Day","DZ",2007 +"2007-01-20","Islamic New Year* (*estimated)","DZ",2007 +"2007-01-29","Ashura Day* (*estimated)","DZ",2007 +"2007-03-31","Prophet's Birthday* (*estimated)","DZ",2007 +"2007-05-01","Labour Day","DZ",2007 +"2007-07-05","Independence Day","DZ",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","DZ",2007 +"2007-10-14","Eid al-Fitr Holiday* (*estimated)","DZ",2007 +"2007-11-01","Revolution Day","DZ",2007 +"2007-12-20","Eid al-Adha* (*estimated)","DZ",2007 +"2007-12-21","Eid al-Adha Holiday* (*estimated)","DZ",2007 +"2008-01-01","New Year's Day","DZ",2008 +"2008-01-10","Islamic New Year* (*estimated)","DZ",2008 +"2008-01-19","Ashura Day* (*estimated)","DZ",2008 +"2008-03-20","Prophet's Birthday* (*estimated)","DZ",2008 +"2008-05-01","Labour Day","DZ",2008 +"2008-07-05","Independence Day","DZ",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","DZ",2008 +"2008-10-02","Eid al-Fitr Holiday* (*estimated)","DZ",2008 +"2008-11-01","Revolution Day","DZ",2008 +"2008-12-08","Eid al-Adha* (*estimated)","DZ",2008 +"2008-12-09","Eid al-Adha Holiday* (*estimated)","DZ",2008 +"2008-12-29","Islamic New Year* (*estimated)","DZ",2008 +"2009-01-01","New Year's Day","DZ",2009 +"2009-01-07","Ashura Day* (*estimated)","DZ",2009 +"2009-03-09","Prophet's Birthday* (*estimated)","DZ",2009 +"2009-05-01","Labour Day","DZ",2009 +"2009-07-05","Independence Day","DZ",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","DZ",2009 +"2009-09-21","Eid al-Fitr Holiday* (*estimated)","DZ",2009 +"2009-11-01","Revolution Day","DZ",2009 +"2009-11-27","Eid al-Adha* (*estimated)","DZ",2009 +"2009-11-28","Eid al-Adha Holiday* (*estimated)","DZ",2009 +"2009-12-18","Islamic New Year* (*estimated)","DZ",2009 +"2009-12-27","Ashura Day* (*estimated)","DZ",2009 +"2010-01-01","New Year's Day","DZ",2010 +"2010-02-26","Prophet's Birthday* (*estimated)","DZ",2010 +"2010-05-01","Labour Day","DZ",2010 +"2010-07-05","Independence Day","DZ",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","DZ",2010 +"2010-09-11","Eid al-Fitr Holiday* (*estimated)","DZ",2010 +"2010-11-01","Revolution Day","DZ",2010 +"2010-11-16","Eid al-Adha* (*estimated)","DZ",2010 +"2010-11-17","Eid al-Adha Holiday* (*estimated)","DZ",2010 +"2010-12-07","Islamic New Year* (*estimated)","DZ",2010 +"2010-12-16","Ashura Day* (*estimated)","DZ",2010 +"2011-01-01","New Year's Day","DZ",2011 +"2011-02-15","Prophet's Birthday* (*estimated)","DZ",2011 +"2011-05-01","Labour Day","DZ",2011 +"2011-07-05","Independence Day","DZ",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","DZ",2011 +"2011-08-31","Eid al-Fitr Holiday* (*estimated)","DZ",2011 +"2011-11-01","Revolution Day","DZ",2011 +"2011-11-06","Eid al-Adha* (*estimated)","DZ",2011 +"2011-11-07","Eid al-Adha Holiday* (*estimated)","DZ",2011 +"2011-11-26","Islamic New Year* (*estimated)","DZ",2011 +"2011-12-05","Ashura Day* (*estimated)","DZ",2011 +"2012-01-01","New Year's Day","DZ",2012 +"2012-02-04","Prophet's Birthday* (*estimated)","DZ",2012 +"2012-05-01","Labour Day","DZ",2012 +"2012-07-05","Independence Day","DZ",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","DZ",2012 +"2012-08-20","Eid al-Fitr Holiday* (*estimated)","DZ",2012 +"2012-10-26","Eid al-Adha* (*estimated)","DZ",2012 +"2012-10-27","Eid al-Adha Holiday* (*estimated)","DZ",2012 +"2012-11-01","Revolution Day","DZ",2012 +"2012-11-15","Islamic New Year* (*estimated)","DZ",2012 +"2012-11-24","Ashura Day* (*estimated)","DZ",2012 +"2013-01-01","New Year's Day","DZ",2013 +"2013-01-24","Prophet's Birthday* (*estimated)","DZ",2013 +"2013-05-01","Labour Day","DZ",2013 +"2013-07-05","Independence Day","DZ",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","DZ",2013 +"2013-08-09","Eid al-Fitr Holiday* (*estimated)","DZ",2013 +"2013-10-15","Eid al-Adha* (*estimated)","DZ",2013 +"2013-10-16","Eid al-Adha Holiday* (*estimated)","DZ",2013 +"2013-11-01","Revolution Day","DZ",2013 +"2013-11-04","Islamic New Year* (*estimated)","DZ",2013 +"2013-11-13","Ashura Day* (*estimated)","DZ",2013 +"2014-01-01","New Year's Day","DZ",2014 +"2014-01-13","Prophet's Birthday* (*estimated)","DZ",2014 +"2014-05-01","Labour Day","DZ",2014 +"2014-07-05","Independence Day","DZ",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","DZ",2014 +"2014-07-29","Eid al-Fitr Holiday* (*estimated)","DZ",2014 +"2014-10-04","Eid al-Adha* (*estimated)","DZ",2014 +"2014-10-05","Eid al-Adha Holiday* (*estimated)","DZ",2014 +"2014-10-25","Islamic New Year* (*estimated)","DZ",2014 +"2014-11-01","Revolution Day","DZ",2014 +"2014-11-03","Ashura Day* (*estimated)","DZ",2014 +"2015-01-01","New Year's Day","DZ",2015 +"2015-01-03","Prophet's Birthday* (*estimated)","DZ",2015 +"2015-05-01","Labour Day","DZ",2015 +"2015-07-05","Independence Day","DZ",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","DZ",2015 +"2015-07-18","Eid al-Fitr Holiday* (*estimated)","DZ",2015 +"2015-09-23","Eid al-Adha* (*estimated)","DZ",2015 +"2015-09-24","Eid al-Adha Holiday* (*estimated)","DZ",2015 +"2015-10-14","Islamic New Year* (*estimated)","DZ",2015 +"2015-10-23","Ashura Day* (*estimated)","DZ",2015 +"2015-11-01","Revolution Day","DZ",2015 +"2015-12-23","Prophet's Birthday* (*estimated)","DZ",2015 +"2016-01-01","New Year's Day","DZ",2016 +"2016-05-01","Labour Day","DZ",2016 +"2016-07-05","Independence Day","DZ",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","DZ",2016 +"2016-07-07","Eid al-Fitr Holiday* (*estimated)","DZ",2016 +"2016-09-11","Eid al-Adha* (*estimated)","DZ",2016 +"2016-09-12","Eid al-Adha Holiday* (*estimated)","DZ",2016 +"2016-10-02","Islamic New Year* (*estimated)","DZ",2016 +"2016-10-11","Ashura Day* (*estimated)","DZ",2016 +"2016-11-01","Revolution Day","DZ",2016 +"2016-12-11","Prophet's Birthday* (*estimated)","DZ",2016 +"2017-01-01","New Year's Day","DZ",2017 +"2017-05-01","Labour Day","DZ",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","DZ",2017 +"2017-06-26","Eid al-Fitr Holiday* (*estimated)","DZ",2017 +"2017-07-05","Independence Day","DZ",2017 +"2017-09-01","Eid al-Adha* (*estimated)","DZ",2017 +"2017-09-02","Eid al-Adha Holiday* (*estimated)","DZ",2017 +"2017-09-21","Islamic New Year* (*estimated)","DZ",2017 +"2017-09-30","Ashura Day* (*estimated)","DZ",2017 +"2017-11-01","Revolution Day","DZ",2017 +"2017-11-30","Prophet's Birthday* (*estimated)","DZ",2017 +"2018-01-01","New Year's Day","DZ",2018 +"2018-01-12","Amazigh New Year","DZ",2018 +"2018-05-01","Labour Day","DZ",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","DZ",2018 +"2018-06-16","Eid al-Fitr Holiday* (*estimated)","DZ",2018 +"2018-07-05","Independence Day","DZ",2018 +"2018-08-21","Eid al-Adha* (*estimated)","DZ",2018 +"2018-08-22","Eid al-Adha Holiday* (*estimated)","DZ",2018 +"2018-09-11","Islamic New Year* (*estimated)","DZ",2018 +"2018-09-20","Ashura Day* (*estimated)","DZ",2018 +"2018-11-01","Revolution Day","DZ",2018 +"2018-11-20","Prophet's Birthday* (*estimated)","DZ",2018 +"2019-01-01","New Year's Day","DZ",2019 +"2019-01-12","Amazigh New Year","DZ",2019 +"2019-05-01","Labour Day","DZ",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","DZ",2019 +"2019-06-05","Eid al-Fitr Holiday* (*estimated)","DZ",2019 +"2019-07-05","Independence Day","DZ",2019 +"2019-08-11","Eid al-Adha* (*estimated)","DZ",2019 +"2019-08-12","Eid al-Adha Holiday* (*estimated)","DZ",2019 +"2019-08-31","Islamic New Year* (*estimated)","DZ",2019 +"2019-09-09","Ashura Day* (*estimated)","DZ",2019 +"2019-11-01","Revolution Day","DZ",2019 +"2019-11-09","Prophet's Birthday* (*estimated)","DZ",2019 +"2020-01-01","New Year's Day","DZ",2020 +"2020-01-12","Amazigh New Year","DZ",2020 +"2020-05-01","Labour Day","DZ",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","DZ",2020 +"2020-05-25","Eid al-Fitr Holiday* (*estimated)","DZ",2020 +"2020-07-05","Independence Day","DZ",2020 +"2020-07-31","Eid al-Adha* (*estimated)","DZ",2020 +"2020-08-01","Eid al-Adha Holiday* (*estimated)","DZ",2020 +"2020-08-20","Islamic New Year* (*estimated)","DZ",2020 +"2020-08-29","Ashura Day* (*estimated)","DZ",2020 +"2020-10-29","Prophet's Birthday* (*estimated)","DZ",2020 +"2020-11-01","Revolution Day","DZ",2020 +"2021-01-01","New Year's Day","DZ",2021 +"2021-01-12","Amazigh New Year","DZ",2021 +"2021-05-01","Labour Day","DZ",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","DZ",2021 +"2021-05-14","Eid al-Fitr Holiday* (*estimated)","DZ",2021 +"2021-07-05","Independence Day","DZ",2021 +"2021-07-20","Eid al-Adha* (*estimated)","DZ",2021 +"2021-07-21","Eid al-Adha Holiday* (*estimated)","DZ",2021 +"2021-08-09","Islamic New Year* (*estimated)","DZ",2021 +"2021-08-18","Ashura Day* (*estimated)","DZ",2021 +"2021-10-18","Prophet's Birthday* (*estimated)","DZ",2021 +"2021-11-01","Revolution Day","DZ",2021 +"2022-01-01","New Year's Day","DZ",2022 +"2022-01-12","Amazigh New Year","DZ",2022 +"2022-05-01","Labour Day","DZ",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","DZ",2022 +"2022-05-03","Eid al-Fitr Holiday* (*estimated)","DZ",2022 +"2022-07-05","Independence Day","DZ",2022 +"2022-07-09","Eid al-Adha* (*estimated)","DZ",2022 +"2022-07-10","Eid al-Adha Holiday* (*estimated)","DZ",2022 +"2022-07-30","Islamic New Year* (*estimated)","DZ",2022 +"2022-08-08","Ashura Day* (*estimated)","DZ",2022 +"2022-10-08","Prophet's Birthday* (*estimated)","DZ",2022 +"2022-11-01","Revolution Day","DZ",2022 +"2023-01-01","New Year's Day","DZ",2023 +"2023-01-12","Amazigh New Year","DZ",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","DZ",2023 +"2023-04-22","Eid al-Fitr Holiday* (*estimated)","DZ",2023 +"2023-05-01","Labour Day","DZ",2023 +"2023-06-28","Eid al-Adha* (*estimated)","DZ",2023 +"2023-06-29","Eid al-Adha Holiday* (*estimated)","DZ",2023 +"2023-06-30","Eid al-Adha Holiday* (*estimated)","DZ",2023 +"2023-07-05","Independence Day","DZ",2023 +"2023-07-19","Islamic New Year* (*estimated)","DZ",2023 +"2023-07-28","Ashura Day* (*estimated)","DZ",2023 +"2023-09-27","Prophet's Birthday* (*estimated)","DZ",2023 +"2023-11-01","Revolution Day","DZ",2023 +"2024-01-01","New Year's Day","DZ",2024 +"2024-01-12","Amazigh New Year","DZ",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","DZ",2024 +"2024-04-11","Eid al-Fitr Holiday* (*estimated)","DZ",2024 +"2024-04-12","Eid al-Fitr Holiday* (*estimated)","DZ",2024 +"2024-05-01","Labour Day","DZ",2024 +"2024-06-16","Eid al-Adha* (*estimated)","DZ",2024 +"2024-06-17","Eid al-Adha Holiday* (*estimated)","DZ",2024 +"2024-06-18","Eid al-Adha Holiday* (*estimated)","DZ",2024 +"2024-07-05","Independence Day","DZ",2024 +"2024-07-07","Islamic New Year* (*estimated)","DZ",2024 +"2024-07-16","Ashura Day* (*estimated)","DZ",2024 +"2024-09-15","Prophet's Birthday* (*estimated)","DZ",2024 +"2024-11-01","Revolution Day","DZ",2024 +"2025-01-01","New Year's Day","DZ",2025 +"2025-01-12","Amazigh New Year","DZ",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","DZ",2025 +"2025-03-31","Eid al-Fitr Holiday* (*estimated)","DZ",2025 +"2025-04-01","Eid al-Fitr Holiday* (*estimated)","DZ",2025 +"2025-05-01","Labour Day","DZ",2025 +"2025-06-06","Eid al-Adha* (*estimated)","DZ",2025 +"2025-06-07","Eid al-Adha Holiday* (*estimated)","DZ",2025 +"2025-06-08","Eid al-Adha Holiday* (*estimated)","DZ",2025 +"2025-06-26","Islamic New Year* (*estimated)","DZ",2025 +"2025-07-05","Ashura Day* (*estimated)","DZ",2025 +"2025-07-05","Independence Day","DZ",2025 +"2025-09-04","Prophet's Birthday* (*estimated)","DZ",2025 +"2025-11-01","Revolution Day","DZ",2025 +"2026-01-01","New Year's Day","DZ",2026 +"2026-01-12","Amazigh New Year","DZ",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","DZ",2026 +"2026-03-21","Eid al-Fitr Holiday* (*estimated)","DZ",2026 +"2026-03-22","Eid al-Fitr Holiday* (*estimated)","DZ",2026 +"2026-05-01","Labour Day","DZ",2026 +"2026-05-27","Eid al-Adha* (*estimated)","DZ",2026 +"2026-05-28","Eid al-Adha Holiday* (*estimated)","DZ",2026 +"2026-05-29","Eid al-Adha Holiday* (*estimated)","DZ",2026 +"2026-06-16","Islamic New Year* (*estimated)","DZ",2026 +"2026-06-25","Ashura Day* (*estimated)","DZ",2026 +"2026-07-05","Independence Day","DZ",2026 +"2026-08-25","Prophet's Birthday* (*estimated)","DZ",2026 +"2026-11-01","Revolution Day","DZ",2026 +"2027-01-01","New Year's Day","DZ",2027 +"2027-01-12","Amazigh New Year","DZ",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","DZ",2027 +"2027-03-10","Eid al-Fitr Holiday* (*estimated)","DZ",2027 +"2027-03-11","Eid al-Fitr Holiday* (*estimated)","DZ",2027 +"2027-05-01","Labour Day","DZ",2027 +"2027-05-16","Eid al-Adha* (*estimated)","DZ",2027 +"2027-05-17","Eid al-Adha Holiday* (*estimated)","DZ",2027 +"2027-05-18","Eid al-Adha Holiday* (*estimated)","DZ",2027 +"2027-06-06","Islamic New Year* (*estimated)","DZ",2027 +"2027-06-15","Ashura Day* (*estimated)","DZ",2027 +"2027-07-05","Independence Day","DZ",2027 +"2027-08-14","Prophet's Birthday* (*estimated)","DZ",2027 +"2027-11-01","Revolution Day","DZ",2027 +"2028-01-01","New Year's Day","DZ",2028 +"2028-01-12","Amazigh New Year","DZ",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","DZ",2028 +"2028-02-27","Eid al-Fitr Holiday* (*estimated)","DZ",2028 +"2028-02-28","Eid al-Fitr Holiday* (*estimated)","DZ",2028 +"2028-05-01","Labour Day","DZ",2028 +"2028-05-05","Eid al-Adha* (*estimated)","DZ",2028 +"2028-05-06","Eid al-Adha Holiday* (*estimated)","DZ",2028 +"2028-05-07","Eid al-Adha Holiday* (*estimated)","DZ",2028 +"2028-05-25","Islamic New Year* (*estimated)","DZ",2028 +"2028-06-03","Ashura Day* (*estimated)","DZ",2028 +"2028-07-05","Independence Day","DZ",2028 +"2028-08-03","Prophet's Birthday* (*estimated)","DZ",2028 +"2028-11-01","Revolution Day","DZ",2028 +"2029-01-01","New Year's Day","DZ",2029 +"2029-01-12","Amazigh New Year","DZ",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","DZ",2029 +"2029-02-15","Eid al-Fitr Holiday* (*estimated)","DZ",2029 +"2029-02-16","Eid al-Fitr Holiday* (*estimated)","DZ",2029 +"2029-04-24","Eid al-Adha* (*estimated)","DZ",2029 +"2029-04-25","Eid al-Adha Holiday* (*estimated)","DZ",2029 +"2029-04-26","Eid al-Adha Holiday* (*estimated)","DZ",2029 +"2029-05-01","Labour Day","DZ",2029 +"2029-05-14","Islamic New Year* (*estimated)","DZ",2029 +"2029-05-23","Ashura Day* (*estimated)","DZ",2029 +"2029-07-05","Independence Day","DZ",2029 +"2029-07-24","Prophet's Birthday* (*estimated)","DZ",2029 +"2029-11-01","Revolution Day","DZ",2029 +"2030-01-01","New Year's Day","DZ",2030 +"2030-01-12","Amazigh New Year","DZ",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","DZ",2030 +"2030-02-05","Eid al-Fitr Holiday* (*estimated)","DZ",2030 +"2030-02-06","Eid al-Fitr Holiday* (*estimated)","DZ",2030 +"2030-04-13","Eid al-Adha* (*estimated)","DZ",2030 +"2030-04-14","Eid al-Adha Holiday* (*estimated)","DZ",2030 +"2030-04-15","Eid al-Adha Holiday* (*estimated)","DZ",2030 +"2030-05-01","Labour Day","DZ",2030 +"2030-05-03","Islamic New Year* (*estimated)","DZ",2030 +"2030-05-12","Ashura Day* (*estimated)","DZ",2030 +"2030-07-05","Independence Day","DZ",2030 +"2030-07-13","Prophet's Birthday* (*estimated)","DZ",2030 +"2030-11-01","Revolution Day","DZ",2030 +"2031-01-01","New Year's Day","DZ",2031 +"2031-01-12","Amazigh New Year","DZ",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","DZ",2031 +"2031-01-25","Eid al-Fitr Holiday* (*estimated)","DZ",2031 +"2031-01-26","Eid al-Fitr Holiday* (*estimated)","DZ",2031 +"2031-04-02","Eid al-Adha* (*estimated)","DZ",2031 +"2031-04-03","Eid al-Adha Holiday* (*estimated)","DZ",2031 +"2031-04-04","Eid al-Adha Holiday* (*estimated)","DZ",2031 +"2031-04-23","Islamic New Year* (*estimated)","DZ",2031 +"2031-05-01","Labour Day","DZ",2031 +"2031-05-02","Ashura Day* (*estimated)","DZ",2031 +"2031-07-02","Prophet's Birthday* (*estimated)","DZ",2031 +"2031-07-05","Independence Day","DZ",2031 +"2031-11-01","Revolution Day","DZ",2031 +"2032-01-01","New Year's Day","DZ",2032 +"2032-01-12","Amazigh New Year","DZ",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","DZ",2032 +"2032-01-15","Eid al-Fitr Holiday* (*estimated)","DZ",2032 +"2032-01-16","Eid al-Fitr Holiday* (*estimated)","DZ",2032 +"2032-03-22","Eid al-Adha* (*estimated)","DZ",2032 +"2032-03-23","Eid al-Adha Holiday* (*estimated)","DZ",2032 +"2032-03-24","Eid al-Adha Holiday* (*estimated)","DZ",2032 +"2032-04-11","Islamic New Year* (*estimated)","DZ",2032 +"2032-04-20","Ashura Day* (*estimated)","DZ",2032 +"2032-05-01","Labour Day","DZ",2032 +"2032-06-20","Prophet's Birthday* (*estimated)","DZ",2032 +"2032-07-05","Independence Day","DZ",2032 +"2032-11-01","Revolution Day","DZ",2032 +"2033-01-01","New Year's Day","DZ",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","DZ",2033 +"2033-01-03","Eid al-Fitr Holiday* (*estimated)","DZ",2033 +"2033-01-04","Eid al-Fitr Holiday* (*estimated)","DZ",2033 +"2033-01-12","Amazigh New Year","DZ",2033 +"2033-03-11","Eid al-Adha* (*estimated)","DZ",2033 +"2033-03-12","Eid al-Adha Holiday* (*estimated)","DZ",2033 +"2033-03-13","Eid al-Adha Holiday* (*estimated)","DZ",2033 +"2033-04-01","Islamic New Year* (*estimated)","DZ",2033 +"2033-04-10","Ashura Day* (*estimated)","DZ",2033 +"2033-05-01","Labour Day","DZ",2033 +"2033-06-09","Prophet's Birthday* (*estimated)","DZ",2033 +"2033-07-05","Independence Day","DZ",2033 +"2033-11-01","Revolution Day","DZ",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","DZ",2033 +"2033-12-24","Eid al-Fitr Holiday* (*estimated)","DZ",2033 +"2033-12-25","Eid al-Fitr Holiday* (*estimated)","DZ",2033 +"2034-01-01","New Year's Day","DZ",2034 +"2034-01-12","Amazigh New Year","DZ",2034 +"2034-03-01","Eid al-Adha* (*estimated)","DZ",2034 +"2034-03-02","Eid al-Adha Holiday* (*estimated)","DZ",2034 +"2034-03-03","Eid al-Adha Holiday* (*estimated)","DZ",2034 +"2034-03-21","Islamic New Year* (*estimated)","DZ",2034 +"2034-03-30","Ashura Day* (*estimated)","DZ",2034 +"2034-05-01","Labour Day","DZ",2034 +"2034-05-30","Prophet's Birthday* (*estimated)","DZ",2034 +"2034-07-05","Independence Day","DZ",2034 +"2034-11-01","Revolution Day","DZ",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","DZ",2034 +"2034-12-13","Eid al-Fitr Holiday* (*estimated)","DZ",2034 +"2034-12-14","Eid al-Fitr Holiday* (*estimated)","DZ",2034 +"2035-01-01","New Year's Day","DZ",2035 +"2035-01-12","Amazigh New Year","DZ",2035 +"2035-02-18","Eid al-Adha* (*estimated)","DZ",2035 +"2035-02-19","Eid al-Adha Holiday* (*estimated)","DZ",2035 +"2035-02-20","Eid al-Adha Holiday* (*estimated)","DZ",2035 +"2035-03-11","Islamic New Year* (*estimated)","DZ",2035 +"2035-03-20","Ashura Day* (*estimated)","DZ",2035 +"2035-05-01","Labour Day","DZ",2035 +"2035-05-20","Prophet's Birthday* (*estimated)","DZ",2035 +"2035-07-05","Independence Day","DZ",2035 +"2035-11-01","Revolution Day","DZ",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","DZ",2035 +"2035-12-02","Eid al-Fitr Holiday* (*estimated)","DZ",2035 +"2035-12-03","Eid al-Fitr Holiday* (*estimated)","DZ",2035 +"2036-01-01","New Year's Day","DZ",2036 +"2036-01-12","Amazigh New Year","DZ",2036 +"2036-02-07","Eid al-Adha* (*estimated)","DZ",2036 +"2036-02-08","Eid al-Adha Holiday* (*estimated)","DZ",2036 +"2036-02-09","Eid al-Adha Holiday* (*estimated)","DZ",2036 +"2036-02-28","Islamic New Year* (*estimated)","DZ",2036 +"2036-03-08","Ashura Day* (*estimated)","DZ",2036 +"2036-05-01","Labour Day","DZ",2036 +"2036-05-08","Prophet's Birthday* (*estimated)","DZ",2036 +"2036-07-05","Independence Day","DZ",2036 +"2036-11-01","Revolution Day","DZ",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","DZ",2036 +"2036-11-20","Eid al-Fitr Holiday* (*estimated)","DZ",2036 +"2036-11-21","Eid al-Fitr Holiday* (*estimated)","DZ",2036 +"2037-01-01","New Year's Day","DZ",2037 +"2037-01-12","Amazigh New Year","DZ",2037 +"2037-01-26","Eid al-Adha* (*estimated)","DZ",2037 +"2037-01-27","Eid al-Adha Holiday* (*estimated)","DZ",2037 +"2037-01-28","Eid al-Adha Holiday* (*estimated)","DZ",2037 +"2037-02-16","Islamic New Year* (*estimated)","DZ",2037 +"2037-02-25","Ashura Day* (*estimated)","DZ",2037 +"2037-04-28","Prophet's Birthday* (*estimated)","DZ",2037 +"2037-05-01","Labour Day","DZ",2037 +"2037-07-05","Independence Day","DZ",2037 +"2037-11-01","Revolution Day","DZ",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","DZ",2037 +"2037-11-09","Eid al-Fitr Holiday* (*estimated)","DZ",2037 +"2037-11-10","Eid al-Fitr Holiday* (*estimated)","DZ",2037 +"2038-01-01","New Year's Day","DZ",2038 +"2038-01-12","Amazigh New Year","DZ",2038 +"2038-01-16","Eid al-Adha* (*estimated)","DZ",2038 +"2038-01-17","Eid al-Adha Holiday* (*estimated)","DZ",2038 +"2038-01-18","Eid al-Adha Holiday* (*estimated)","DZ",2038 +"2038-02-05","Islamic New Year* (*estimated)","DZ",2038 +"2038-02-14","Ashura Day* (*estimated)","DZ",2038 +"2038-04-17","Prophet's Birthday* (*estimated)","DZ",2038 +"2038-05-01","Labour Day","DZ",2038 +"2038-07-05","Independence Day","DZ",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","DZ",2038 +"2038-10-30","Eid al-Fitr Holiday* (*estimated)","DZ",2038 +"2038-10-31","Eid al-Fitr Holiday* (*estimated)","DZ",2038 +"2038-11-01","Revolution Day","DZ",2038 +"2039-01-01","New Year's Day","DZ",2039 +"2039-01-05","Eid al-Adha* (*estimated)","DZ",2039 +"2039-01-06","Eid al-Adha Holiday* (*estimated)","DZ",2039 +"2039-01-07","Eid al-Adha Holiday* (*estimated)","DZ",2039 +"2039-01-12","Amazigh New Year","DZ",2039 +"2039-01-26","Islamic New Year* (*estimated)","DZ",2039 +"2039-02-04","Ashura Day* (*estimated)","DZ",2039 +"2039-04-06","Prophet's Birthday* (*estimated)","DZ",2039 +"2039-05-01","Labour Day","DZ",2039 +"2039-07-05","Independence Day","DZ",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","DZ",2039 +"2039-10-20","Eid al-Fitr Holiday* (*estimated)","DZ",2039 +"2039-10-21","Eid al-Fitr Holiday* (*estimated)","DZ",2039 +"2039-11-01","Revolution Day","DZ",2039 +"2039-12-26","Eid al-Adha* (*estimated)","DZ",2039 +"2039-12-27","Eid al-Adha Holiday* (*estimated)","DZ",2039 +"2039-12-28","Eid al-Adha Holiday* (*estimated)","DZ",2039 +"2040-01-01","New Year's Day","DZ",2040 +"2040-01-12","Amazigh New Year","DZ",2040 +"2040-01-15","Islamic New Year* (*estimated)","DZ",2040 +"2040-01-24","Ashura Day* (*estimated)","DZ",2040 +"2040-03-25","Prophet's Birthday* (*estimated)","DZ",2040 +"2040-05-01","Labour Day","DZ",2040 +"2040-07-05","Independence Day","DZ",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","DZ",2040 +"2040-10-08","Eid al-Fitr Holiday* (*estimated)","DZ",2040 +"2040-10-09","Eid al-Fitr Holiday* (*estimated)","DZ",2040 +"2040-11-01","Revolution Day","DZ",2040 +"2040-12-14","Eid al-Adha* (*estimated)","DZ",2040 +"2040-12-15","Eid al-Adha Holiday* (*estimated)","DZ",2040 +"2040-12-16","Eid al-Adha Holiday* (*estimated)","DZ",2040 +"2041-01-01","New Year's Day","DZ",2041 +"2041-01-04","Islamic New Year* (*estimated)","DZ",2041 +"2041-01-12","Amazigh New Year","DZ",2041 +"2041-01-13","Ashura Day* (*estimated)","DZ",2041 +"2041-03-15","Prophet's Birthday* (*estimated)","DZ",2041 +"2041-05-01","Labour Day","DZ",2041 +"2041-07-05","Independence Day","DZ",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","DZ",2041 +"2041-09-27","Eid al-Fitr Holiday* (*estimated)","DZ",2041 +"2041-09-28","Eid al-Fitr Holiday* (*estimated)","DZ",2041 +"2041-11-01","Revolution Day","DZ",2041 +"2041-12-04","Eid al-Adha* (*estimated)","DZ",2041 +"2041-12-05","Eid al-Adha Holiday* (*estimated)","DZ",2041 +"2041-12-06","Eid al-Adha Holiday* (*estimated)","DZ",2041 +"2041-12-24","Islamic New Year* (*estimated)","DZ",2041 +"2042-01-01","New Year's Day","DZ",2042 +"2042-01-02","Ashura Day* (*estimated)","DZ",2042 +"2042-01-12","Amazigh New Year","DZ",2042 +"2042-03-04","Prophet's Birthday* (*estimated)","DZ",2042 +"2042-05-01","Labour Day","DZ",2042 +"2042-07-05","Independence Day","DZ",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","DZ",2042 +"2042-09-16","Eid al-Fitr Holiday* (*estimated)","DZ",2042 +"2042-09-17","Eid al-Fitr Holiday* (*estimated)","DZ",2042 +"2042-11-01","Revolution Day","DZ",2042 +"2042-11-23","Eid al-Adha* (*estimated)","DZ",2042 +"2042-11-24","Eid al-Adha Holiday* (*estimated)","DZ",2042 +"2042-11-25","Eid al-Adha Holiday* (*estimated)","DZ",2042 +"2042-12-14","Islamic New Year* (*estimated)","DZ",2042 +"2042-12-23","Ashura Day* (*estimated)","DZ",2042 +"2043-01-01","New Year's Day","DZ",2043 +"2043-01-12","Amazigh New Year","DZ",2043 +"2043-02-22","Prophet's Birthday* (*estimated)","DZ",2043 +"2043-05-01","Labour Day","DZ",2043 +"2043-07-05","Independence Day","DZ",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","DZ",2043 +"2043-09-05","Eid al-Fitr Holiday* (*estimated)","DZ",2043 +"2043-09-06","Eid al-Fitr Holiday* (*estimated)","DZ",2043 +"2043-11-01","Revolution Day","DZ",2043 +"2043-11-12","Eid al-Adha* (*estimated)","DZ",2043 +"2043-11-13","Eid al-Adha Holiday* (*estimated)","DZ",2043 +"2043-11-14","Eid al-Adha Holiday* (*estimated)","DZ",2043 +"2043-12-03","Islamic New Year* (*estimated)","DZ",2043 +"2043-12-12","Ashura Day* (*estimated)","DZ",2043 +"2044-01-01","New Year's Day","DZ",2044 +"2044-01-12","Amazigh New Year","DZ",2044 +"2044-02-11","Prophet's Birthday* (*estimated)","DZ",2044 +"2044-05-01","Labour Day","DZ",2044 +"2044-07-05","Independence Day","DZ",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","DZ",2044 +"2044-08-25","Eid al-Fitr Holiday* (*estimated)","DZ",2044 +"2044-08-26","Eid al-Fitr Holiday* (*estimated)","DZ",2044 +"2044-10-31","Eid al-Adha* (*estimated)","DZ",2044 +"2044-11-01","Eid al-Adha Holiday* (*estimated)","DZ",2044 +"2044-11-01","Revolution Day","DZ",2044 +"2044-11-02","Eid al-Adha Holiday* (*estimated)","DZ",2044 +"2044-11-21","Islamic New Year* (*estimated)","DZ",2044 +"2044-11-30","Ashura Day* (*estimated)","DZ",2044 +"1995-01-01","New Year's Day","EC",1995 +"1995-02-27","Carnival","EC",1995 +"1995-02-28","Carnival","EC",1995 +"1995-04-14","Good Friday","EC",1995 +"1995-05-01","Labour Day","EC",1995 +"1995-05-24","The Battle of Pichincha","EC",1995 +"1995-08-10","Declaration of Independence of Quito","EC",1995 +"1995-10-09","Independence of Guayaquil","EC",1995 +"1995-11-02","All Souls' Day","EC",1995 +"1995-11-03","Independence of Cuenca","EC",1995 +"1995-12-25","Christmas Day","EC",1995 +"1996-01-01","New Year's Day","EC",1996 +"1996-02-19","Carnival","EC",1996 +"1996-02-20","Carnival","EC",1996 +"1996-04-05","Good Friday","EC",1996 +"1996-05-01","Labour Day","EC",1996 +"1996-05-24","The Battle of Pichincha","EC",1996 +"1996-08-10","Declaration of Independence of Quito","EC",1996 +"1996-10-09","Independence of Guayaquil","EC",1996 +"1996-11-02","All Souls' Day","EC",1996 +"1996-11-03","Independence of Cuenca","EC",1996 +"1996-12-25","Christmas Day","EC",1996 +"1997-01-01","New Year's Day","EC",1997 +"1997-02-10","Carnival","EC",1997 +"1997-02-11","Carnival","EC",1997 +"1997-03-28","Good Friday","EC",1997 +"1997-05-01","Labour Day","EC",1997 +"1997-05-24","The Battle of Pichincha","EC",1997 +"1997-08-10","Declaration of Independence of Quito","EC",1997 +"1997-10-09","Independence of Guayaquil","EC",1997 +"1997-11-02","All Souls' Day","EC",1997 +"1997-11-03","Independence of Cuenca","EC",1997 +"1997-12-25","Christmas Day","EC",1997 +"1998-01-01","New Year's Day","EC",1998 +"1998-02-23","Carnival","EC",1998 +"1998-02-24","Carnival","EC",1998 +"1998-04-10","Good Friday","EC",1998 +"1998-05-01","Labour Day","EC",1998 +"1998-05-24","The Battle of Pichincha","EC",1998 +"1998-08-10","Declaration of Independence of Quito","EC",1998 +"1998-10-09","Independence of Guayaquil","EC",1998 +"1998-11-02","All Souls' Day","EC",1998 +"1998-11-03","Independence of Cuenca","EC",1998 +"1998-12-25","Christmas Day","EC",1998 +"1999-01-01","New Year's Day","EC",1999 +"1999-02-15","Carnival","EC",1999 +"1999-02-16","Carnival","EC",1999 +"1999-04-02","Good Friday","EC",1999 +"1999-05-01","Labour Day","EC",1999 +"1999-05-24","The Battle of Pichincha","EC",1999 +"1999-08-10","Declaration of Independence of Quito","EC",1999 +"1999-10-09","Independence of Guayaquil","EC",1999 +"1999-11-02","All Souls' Day","EC",1999 +"1999-11-03","Independence of Cuenca","EC",1999 +"1999-12-25","Christmas Day","EC",1999 +"2000-01-01","New Year's Day","EC",2000 +"2000-03-06","Carnival","EC",2000 +"2000-03-07","Carnival","EC",2000 +"2000-04-21","Good Friday","EC",2000 +"2000-05-01","Labour Day","EC",2000 +"2000-05-24","The Battle of Pichincha","EC",2000 +"2000-08-10","Declaration of Independence of Quito","EC",2000 +"2000-10-09","Independence of Guayaquil","EC",2000 +"2000-11-02","All Souls' Day","EC",2000 +"2000-11-03","Independence of Cuenca","EC",2000 +"2000-12-25","Christmas Day","EC",2000 +"2001-01-01","New Year's Day","EC",2001 +"2001-02-26","Carnival","EC",2001 +"2001-02-27","Carnival","EC",2001 +"2001-04-13","Good Friday","EC",2001 +"2001-05-01","Labour Day","EC",2001 +"2001-05-24","The Battle of Pichincha","EC",2001 +"2001-08-10","Declaration of Independence of Quito","EC",2001 +"2001-10-09","Independence of Guayaquil","EC",2001 +"2001-11-02","All Souls' Day","EC",2001 +"2001-11-03","Independence of Cuenca","EC",2001 +"2001-12-25","Christmas Day","EC",2001 +"2002-01-01","New Year's Day","EC",2002 +"2002-02-11","Carnival","EC",2002 +"2002-02-12","Carnival","EC",2002 +"2002-03-29","Good Friday","EC",2002 +"2002-05-01","Labour Day","EC",2002 +"2002-05-24","The Battle of Pichincha","EC",2002 +"2002-08-10","Declaration of Independence of Quito","EC",2002 +"2002-10-09","Independence of Guayaquil","EC",2002 +"2002-11-02","All Souls' Day","EC",2002 +"2002-11-03","Independence of Cuenca","EC",2002 +"2002-12-25","Christmas Day","EC",2002 +"2003-01-01","New Year's Day","EC",2003 +"2003-03-03","Carnival","EC",2003 +"2003-03-04","Carnival","EC",2003 +"2003-04-18","Good Friday","EC",2003 +"2003-05-01","Labour Day","EC",2003 +"2003-05-24","The Battle of Pichincha","EC",2003 +"2003-08-10","Declaration of Independence of Quito","EC",2003 +"2003-10-09","Independence of Guayaquil","EC",2003 +"2003-11-02","All Souls' Day","EC",2003 +"2003-11-03","Independence of Cuenca","EC",2003 +"2003-12-25","Christmas Day","EC",2003 +"2004-01-01","New Year's Day","EC",2004 +"2004-02-23","Carnival","EC",2004 +"2004-02-24","Carnival","EC",2004 +"2004-04-09","Good Friday","EC",2004 +"2004-05-01","Labour Day","EC",2004 +"2004-05-24","The Battle of Pichincha","EC",2004 +"2004-08-10","Declaration of Independence of Quito","EC",2004 +"2004-10-09","Independence of Guayaquil","EC",2004 +"2004-11-02","All Souls' Day","EC",2004 +"2004-11-03","Independence of Cuenca","EC",2004 +"2004-12-25","Christmas Day","EC",2004 +"2005-01-01","New Year's Day","EC",2005 +"2005-02-07","Carnival","EC",2005 +"2005-02-08","Carnival","EC",2005 +"2005-03-25","Good Friday","EC",2005 +"2005-05-01","Labour Day","EC",2005 +"2005-05-24","The Battle of Pichincha","EC",2005 +"2005-08-10","Declaration of Independence of Quito","EC",2005 +"2005-10-09","Independence of Guayaquil","EC",2005 +"2005-11-02","All Souls' Day","EC",2005 +"2005-11-03","Independence of Cuenca","EC",2005 +"2005-12-25","Christmas Day","EC",2005 +"2006-01-01","New Year's Day","EC",2006 +"2006-02-27","Carnival","EC",2006 +"2006-02-28","Carnival","EC",2006 +"2006-04-14","Good Friday","EC",2006 +"2006-05-01","Labour Day","EC",2006 +"2006-05-24","The Battle of Pichincha","EC",2006 +"2006-08-10","Declaration of Independence of Quito","EC",2006 +"2006-10-09","Independence of Guayaquil","EC",2006 +"2006-11-02","All Souls' Day","EC",2006 +"2006-11-03","Independence of Cuenca","EC",2006 +"2006-12-25","Christmas Day","EC",2006 +"2007-01-01","New Year's Day","EC",2007 +"2007-02-19","Carnival","EC",2007 +"2007-02-20","Carnival","EC",2007 +"2007-04-06","Good Friday","EC",2007 +"2007-05-01","Labour Day","EC",2007 +"2007-05-24","The Battle of Pichincha","EC",2007 +"2007-08-10","Declaration of Independence of Quito","EC",2007 +"2007-10-09","Independence of Guayaquil","EC",2007 +"2007-11-02","All Souls' Day","EC",2007 +"2007-11-03","Independence of Cuenca","EC",2007 +"2007-12-25","Christmas Day","EC",2007 +"2008-01-01","New Year's Day","EC",2008 +"2008-02-04","Carnival","EC",2008 +"2008-02-05","Carnival","EC",2008 +"2008-03-21","Good Friday","EC",2008 +"2008-05-01","Labour Day","EC",2008 +"2008-05-24","The Battle of Pichincha","EC",2008 +"2008-08-10","Declaration of Independence of Quito","EC",2008 +"2008-10-09","Independence of Guayaquil","EC",2008 +"2008-11-02","All Souls' Day","EC",2008 +"2008-11-03","Independence of Cuenca","EC",2008 +"2008-12-25","Christmas Day","EC",2008 +"2009-01-01","New Year's Day","EC",2009 +"2009-02-23","Carnival","EC",2009 +"2009-02-24","Carnival","EC",2009 +"2009-04-10","Good Friday","EC",2009 +"2009-05-01","Labour Day","EC",2009 +"2009-05-24","The Battle of Pichincha","EC",2009 +"2009-08-10","Declaration of Independence of Quito","EC",2009 +"2009-10-09","Independence of Guayaquil","EC",2009 +"2009-11-02","All Souls' Day","EC",2009 +"2009-11-03","Independence of Cuenca","EC",2009 +"2009-12-25","Christmas Day","EC",2009 +"2010-01-01","New Year's Day","EC",2010 +"2010-02-15","Carnival","EC",2010 +"2010-02-16","Carnival","EC",2010 +"2010-04-02","Good Friday","EC",2010 +"2010-05-01","Labour Day","EC",2010 +"2010-05-24","The Battle of Pichincha","EC",2010 +"2010-08-10","Declaration of Independence of Quito","EC",2010 +"2010-10-09","Independence of Guayaquil","EC",2010 +"2010-11-02","All Souls' Day","EC",2010 +"2010-11-03","Independence of Cuenca","EC",2010 +"2010-12-25","Christmas Day","EC",2010 +"2011-01-01","New Year's Day","EC",2011 +"2011-03-07","Carnival","EC",2011 +"2011-03-08","Carnival","EC",2011 +"2011-04-22","Good Friday","EC",2011 +"2011-05-01","Labour Day","EC",2011 +"2011-05-24","The Battle of Pichincha","EC",2011 +"2011-08-10","Declaration of Independence of Quito","EC",2011 +"2011-10-09","Independence of Guayaquil","EC",2011 +"2011-11-02","All Souls' Day","EC",2011 +"2011-11-03","Independence of Cuenca","EC",2011 +"2011-12-25","Christmas Day","EC",2011 +"2012-01-01","New Year's Day","EC",2012 +"2012-02-20","Carnival","EC",2012 +"2012-02-21","Carnival","EC",2012 +"2012-04-06","Good Friday","EC",2012 +"2012-05-01","Labour Day","EC",2012 +"2012-05-24","The Battle of Pichincha","EC",2012 +"2012-08-10","Declaration of Independence of Quito","EC",2012 +"2012-10-09","Independence of Guayaquil","EC",2012 +"2012-11-02","All Souls' Day","EC",2012 +"2012-11-03","Independence of Cuenca","EC",2012 +"2012-12-25","Christmas Day","EC",2012 +"2013-01-01","New Year's Day","EC",2013 +"2013-02-11","Carnival","EC",2013 +"2013-02-12","Carnival","EC",2013 +"2013-03-29","Good Friday","EC",2013 +"2013-05-01","Labour Day","EC",2013 +"2013-05-24","The Battle of Pichincha","EC",2013 +"2013-08-10","Declaration of Independence of Quito","EC",2013 +"2013-10-09","Independence of Guayaquil","EC",2013 +"2013-11-02","All Souls' Day","EC",2013 +"2013-11-03","Independence of Cuenca","EC",2013 +"2013-12-25","Christmas Day","EC",2013 +"2014-01-01","New Year's Day","EC",2014 +"2014-03-03","Carnival","EC",2014 +"2014-03-04","Carnival","EC",2014 +"2014-04-18","Good Friday","EC",2014 +"2014-05-01","Labour Day","EC",2014 +"2014-05-24","The Battle of Pichincha","EC",2014 +"2014-08-10","Declaration of Independence of Quito","EC",2014 +"2014-10-09","Independence of Guayaquil","EC",2014 +"2014-11-02","All Souls' Day","EC",2014 +"2014-11-03","Independence of Cuenca","EC",2014 +"2014-12-25","Christmas Day","EC",2014 +"2015-01-01","New Year's Day","EC",2015 +"2015-02-16","Carnival","EC",2015 +"2015-02-17","Carnival","EC",2015 +"2015-04-03","Good Friday","EC",2015 +"2015-05-01","Labour Day","EC",2015 +"2015-05-24","The Battle of Pichincha","EC",2015 +"2015-08-10","Declaration of Independence of Quito","EC",2015 +"2015-10-09","Independence of Guayaquil","EC",2015 +"2015-11-02","All Souls' Day","EC",2015 +"2015-11-03","Independence of Cuenca","EC",2015 +"2015-12-25","Christmas Day","EC",2015 +"2016-01-01","New Year's Day","EC",2016 +"2016-02-08","Carnival","EC",2016 +"2016-02-09","Carnival","EC",2016 +"2016-03-25","Good Friday","EC",2016 +"2016-05-01","Labour Day","EC",2016 +"2016-05-24","The Battle of Pichincha","EC",2016 +"2016-08-10","Declaration of Independence of Quito","EC",2016 +"2016-10-09","Independence of Guayaquil","EC",2016 +"2016-11-02","All Souls' Day","EC",2016 +"2016-11-03","Independence of Cuenca","EC",2016 +"2016-12-25","Christmas Day","EC",2016 +"2017-01-01","New Year's Day","EC",2017 +"2017-01-02","New Year's Day (Observed)","EC",2017 +"2017-02-27","Carnival","EC",2017 +"2017-02-28","Carnival","EC",2017 +"2017-04-14","Good Friday","EC",2017 +"2017-05-01","Labour Day","EC",2017 +"2017-05-24","The Battle of Pichincha","EC",2017 +"2017-05-26","The Battle of Pichincha (Observed)","EC",2017 +"2017-08-10","Declaration of Independence of Quito","EC",2017 +"2017-08-11","Declaration of Independence of Quito (Observed)","EC",2017 +"2017-10-09","Independence of Guayaquil","EC",2017 +"2017-11-02","All Souls' Day","EC",2017 +"2017-11-03","Independence of Cuenca","EC",2017 +"2017-12-25","Christmas Day","EC",2017 +"2018-01-01","New Year's Day","EC",2018 +"2018-02-12","Carnival","EC",2018 +"2018-02-13","Carnival","EC",2018 +"2018-03-30","Good Friday","EC",2018 +"2018-04-30","Labour Day (Observed)","EC",2018 +"2018-05-01","Labour Day","EC",2018 +"2018-05-24","The Battle of Pichincha","EC",2018 +"2018-05-25","The Battle of Pichincha (Observed)","EC",2018 +"2018-08-10","Declaration of Independence of Quito","EC",2018 +"2018-10-08","Independence of Guayaquil (Observed)","EC",2018 +"2018-10-09","Independence of Guayaquil","EC",2018 +"2018-11-02","All Souls' Day","EC",2018 +"2018-11-03","Independence of Cuenca","EC",2018 +"2018-12-25","Christmas Day","EC",2018 +"2019-01-01","New Year's Day","EC",2019 +"2019-03-04","Carnival","EC",2019 +"2019-03-05","Carnival","EC",2019 +"2019-04-19","Good Friday","EC",2019 +"2019-05-01","Labour Day","EC",2019 +"2019-05-03","Labour Day (Observed)","EC",2019 +"2019-05-24","The Battle of Pichincha","EC",2019 +"2019-08-09","Declaration of Independence of Quito (Observed)","EC",2019 +"2019-08-10","Declaration of Independence of Quito","EC",2019 +"2019-10-09","Independence of Guayaquil","EC",2019 +"2019-10-11","Independence of Guayaquil (Observed)","EC",2019 +"2019-11-01","All Souls' Day (Observed)","EC",2019 +"2019-11-02","All Souls' Day","EC",2019 +"2019-11-03","Independence of Cuenca","EC",2019 +"2019-11-04","Independence of Cuenca (Observed)","EC",2019 +"2019-12-25","Christmas Day","EC",2019 +"2020-01-01","New Year's Day","EC",2020 +"2020-02-24","Carnival","EC",2020 +"2020-02-25","Carnival","EC",2020 +"2020-04-10","Good Friday","EC",2020 +"2020-05-01","Labour Day","EC",2020 +"2020-05-24","The Battle of Pichincha","EC",2020 +"2020-05-25","The Battle of Pichincha (Observed)","EC",2020 +"2020-08-10","Declaration of Independence of Quito","EC",2020 +"2020-10-09","Independence of Guayaquil","EC",2020 +"2020-11-02","All Souls' Day","EC",2020 +"2020-11-03","Independence of Cuenca","EC",2020 +"2020-12-25","Christmas Day","EC",2020 +"2021-01-01","New Year's Day","EC",2021 +"2021-02-15","Carnival","EC",2021 +"2021-02-16","Carnival","EC",2021 +"2021-04-02","Good Friday","EC",2021 +"2021-04-30","Labour Day (Observed)","EC",2021 +"2021-05-01","Labour Day","EC",2021 +"2021-05-24","The Battle of Pichincha","EC",2021 +"2021-08-09","Declaration of Independence of Quito (Observed)","EC",2021 +"2021-08-10","Declaration of Independence of Quito","EC",2021 +"2021-10-08","Independence of Guayaquil (Observed)","EC",2021 +"2021-10-09","Independence of Guayaquil","EC",2021 +"2021-11-01","All Souls' Day (Observed)","EC",2021 +"2021-11-02","All Souls' Day","EC",2021 +"2021-11-03","Independence of Cuenca","EC",2021 +"2021-11-05","Independence of Cuenca (Observed)","EC",2021 +"2021-12-24","Christmas Day (Observed)","EC",2021 +"2021-12-25","Christmas Day","EC",2021 +"2021-12-31","New Year's Day (Observed)","EC",2021 +"2022-01-01","New Year's Day","EC",2022 +"2022-02-28","Carnival","EC",2022 +"2022-03-01","Carnival","EC",2022 +"2022-04-15","Good Friday","EC",2022 +"2022-05-01","Labour Day","EC",2022 +"2022-05-02","Labour Day (Observed)","EC",2022 +"2022-05-23","The Battle of Pichincha (Observed)","EC",2022 +"2022-05-24","The Battle of Pichincha","EC",2022 +"2022-08-10","Declaration of Independence of Quito","EC",2022 +"2022-08-12","Declaration of Independence of Quito (Observed)","EC",2022 +"2022-10-09","Independence of Guayaquil","EC",2022 +"2022-10-10","Independence of Guayaquil (Observed)","EC",2022 +"2022-11-02","All Souls' Day","EC",2022 +"2022-11-03","Independence of Cuenca","EC",2022 +"2022-11-04","All Souls' Day (Observed)","EC",2022 +"2022-11-04","Independence of Cuenca (Observed)","EC",2022 +"2022-12-25","Christmas Day","EC",2022 +"2022-12-26","Christmas Day (Observed)","EC",2022 +"2023-01-01","New Year's Day","EC",2023 +"2023-01-02","New Year's Day (Observed)","EC",2023 +"2023-02-20","Carnival","EC",2023 +"2023-02-21","Carnival","EC",2023 +"2023-04-07","Good Friday","EC",2023 +"2023-05-01","Labour Day","EC",2023 +"2023-05-24","The Battle of Pichincha","EC",2023 +"2023-05-26","The Battle of Pichincha (Observed)","EC",2023 +"2023-08-10","Declaration of Independence of Quito","EC",2023 +"2023-08-11","Declaration of Independence of Quito (Observed)","EC",2023 +"2023-10-09","Independence of Guayaquil","EC",2023 +"2023-11-02","All Souls' Day","EC",2023 +"2023-11-03","Independence of Cuenca","EC",2023 +"2023-12-25","Christmas Day","EC",2023 +"2024-01-01","New Year's Day","EC",2024 +"2024-02-12","Carnival","EC",2024 +"2024-02-13","Carnival","EC",2024 +"2024-03-29","Good Friday","EC",2024 +"2024-05-01","Labour Day","EC",2024 +"2024-05-03","Labour Day (Observed)","EC",2024 +"2024-05-24","The Battle of Pichincha","EC",2024 +"2024-08-09","Declaration of Independence of Quito (Observed)","EC",2024 +"2024-08-10","Declaration of Independence of Quito","EC",2024 +"2024-10-09","Independence of Guayaquil","EC",2024 +"2024-10-11","Independence of Guayaquil (Observed)","EC",2024 +"2024-11-01","All Souls' Day (Observed)","EC",2024 +"2024-11-02","All Souls' Day","EC",2024 +"2024-11-03","Independence of Cuenca","EC",2024 +"2024-11-04","Independence of Cuenca (Observed)","EC",2024 +"2024-12-25","Christmas Day","EC",2024 +"2025-01-01","New Year's Day","EC",2025 +"2025-03-03","Carnival","EC",2025 +"2025-03-04","Carnival","EC",2025 +"2025-04-18","Good Friday","EC",2025 +"2025-05-01","Labour Day","EC",2025 +"2025-05-02","Labour Day (Observed)","EC",2025 +"2025-05-23","The Battle of Pichincha (Observed)","EC",2025 +"2025-05-24","The Battle of Pichincha","EC",2025 +"2025-08-10","Declaration of Independence of Quito","EC",2025 +"2025-08-11","Declaration of Independence of Quito (Observed)","EC",2025 +"2025-10-09","Independence of Guayaquil","EC",2025 +"2025-10-10","Independence of Guayaquil (Observed)","EC",2025 +"2025-11-02","All Souls' Day","EC",2025 +"2025-11-03","Independence of Cuenca","EC",2025 +"2025-12-25","Christmas Day","EC",2025 +"2026-01-01","New Year's Day","EC",2026 +"2026-02-16","Carnival","EC",2026 +"2026-02-17","Carnival","EC",2026 +"2026-04-03","Good Friday","EC",2026 +"2026-05-01","Labour Day","EC",2026 +"2026-05-24","The Battle of Pichincha","EC",2026 +"2026-05-25","The Battle of Pichincha (Observed)","EC",2026 +"2026-08-10","Declaration of Independence of Quito","EC",2026 +"2026-10-09","Independence of Guayaquil","EC",2026 +"2026-11-02","All Souls' Day","EC",2026 +"2026-11-03","Independence of Cuenca","EC",2026 +"2026-12-25","Christmas Day","EC",2026 +"2027-01-01","New Year's Day","EC",2027 +"2027-02-08","Carnival","EC",2027 +"2027-02-09","Carnival","EC",2027 +"2027-03-26","Good Friday","EC",2027 +"2027-04-30","Labour Day (Observed)","EC",2027 +"2027-05-01","Labour Day","EC",2027 +"2027-05-24","The Battle of Pichincha","EC",2027 +"2027-08-09","Declaration of Independence of Quito (Observed)","EC",2027 +"2027-08-10","Declaration of Independence of Quito","EC",2027 +"2027-10-08","Independence of Guayaquil (Observed)","EC",2027 +"2027-10-09","Independence of Guayaquil","EC",2027 +"2027-11-01","All Souls' Day (Observed)","EC",2027 +"2027-11-02","All Souls' Day","EC",2027 +"2027-11-03","Independence of Cuenca","EC",2027 +"2027-11-05","Independence of Cuenca (Observed)","EC",2027 +"2027-12-24","Christmas Day (Observed)","EC",2027 +"2027-12-25","Christmas Day","EC",2027 +"2027-12-31","New Year's Day (Observed)","EC",2027 +"2028-01-01","New Year's Day","EC",2028 +"2028-02-28","Carnival","EC",2028 +"2028-02-29","Carnival","EC",2028 +"2028-04-14","Good Friday","EC",2028 +"2028-05-01","Labour Day","EC",2028 +"2028-05-24","The Battle of Pichincha","EC",2028 +"2028-05-26","The Battle of Pichincha (Observed)","EC",2028 +"2028-08-10","Declaration of Independence of Quito","EC",2028 +"2028-08-11","Declaration of Independence of Quito (Observed)","EC",2028 +"2028-10-09","Independence of Guayaquil","EC",2028 +"2028-11-02","All Souls' Day","EC",2028 +"2028-11-03","Independence of Cuenca","EC",2028 +"2028-12-25","Christmas Day","EC",2028 +"2029-01-01","New Year's Day","EC",2029 +"2029-02-12","Carnival","EC",2029 +"2029-02-13","Carnival","EC",2029 +"2029-03-30","Good Friday","EC",2029 +"2029-04-30","Labour Day (Observed)","EC",2029 +"2029-05-01","Labour Day","EC",2029 +"2029-05-24","The Battle of Pichincha","EC",2029 +"2029-05-25","The Battle of Pichincha (Observed)","EC",2029 +"2029-08-10","Declaration of Independence of Quito","EC",2029 +"2029-10-08","Independence of Guayaquil (Observed)","EC",2029 +"2029-10-09","Independence of Guayaquil","EC",2029 +"2029-11-02","All Souls' Day","EC",2029 +"2029-11-03","Independence of Cuenca","EC",2029 +"2029-12-25","Christmas Day","EC",2029 +"2030-01-01","New Year's Day","EC",2030 +"2030-03-04","Carnival","EC",2030 +"2030-03-05","Carnival","EC",2030 +"2030-04-19","Good Friday","EC",2030 +"2030-05-01","Labour Day","EC",2030 +"2030-05-03","Labour Day (Observed)","EC",2030 +"2030-05-24","The Battle of Pichincha","EC",2030 +"2030-08-09","Declaration of Independence of Quito (Observed)","EC",2030 +"2030-08-10","Declaration of Independence of Quito","EC",2030 +"2030-10-09","Independence of Guayaquil","EC",2030 +"2030-10-11","Independence of Guayaquil (Observed)","EC",2030 +"2030-11-01","All Souls' Day (Observed)","EC",2030 +"2030-11-02","All Souls' Day","EC",2030 +"2030-11-03","Independence of Cuenca","EC",2030 +"2030-11-04","Independence of Cuenca (Observed)","EC",2030 +"2030-12-25","Christmas Day","EC",2030 +"2031-01-01","New Year's Day","EC",2031 +"2031-02-24","Carnival","EC",2031 +"2031-02-25","Carnival","EC",2031 +"2031-04-11","Good Friday","EC",2031 +"2031-05-01","Labour Day","EC",2031 +"2031-05-02","Labour Day (Observed)","EC",2031 +"2031-05-23","The Battle of Pichincha (Observed)","EC",2031 +"2031-05-24","The Battle of Pichincha","EC",2031 +"2031-08-10","Declaration of Independence of Quito","EC",2031 +"2031-08-11","Declaration of Independence of Quito (Observed)","EC",2031 +"2031-10-09","Independence of Guayaquil","EC",2031 +"2031-10-10","Independence of Guayaquil (Observed)","EC",2031 +"2031-11-02","All Souls' Day","EC",2031 +"2031-11-03","Independence of Cuenca","EC",2031 +"2031-12-25","Christmas Day","EC",2031 +"2032-01-01","New Year's Day","EC",2032 +"2032-02-09","Carnival","EC",2032 +"2032-02-10","Carnival","EC",2032 +"2032-03-26","Good Friday","EC",2032 +"2032-04-30","Labour Day (Observed)","EC",2032 +"2032-05-01","Labour Day","EC",2032 +"2032-05-24","The Battle of Pichincha","EC",2032 +"2032-08-09","Declaration of Independence of Quito (Observed)","EC",2032 +"2032-08-10","Declaration of Independence of Quito","EC",2032 +"2032-10-08","Independence of Guayaquil (Observed)","EC",2032 +"2032-10-09","Independence of Guayaquil","EC",2032 +"2032-11-01","All Souls' Day (Observed)","EC",2032 +"2032-11-02","All Souls' Day","EC",2032 +"2032-11-03","Independence of Cuenca","EC",2032 +"2032-11-05","Independence of Cuenca (Observed)","EC",2032 +"2032-12-24","Christmas Day (Observed)","EC",2032 +"2032-12-25","Christmas Day","EC",2032 +"2032-12-31","New Year's Day (Observed)","EC",2032 +"2033-01-01","New Year's Day","EC",2033 +"2033-02-28","Carnival","EC",2033 +"2033-03-01","Carnival","EC",2033 +"2033-04-15","Good Friday","EC",2033 +"2033-05-01","Labour Day","EC",2033 +"2033-05-02","Labour Day (Observed)","EC",2033 +"2033-05-23","The Battle of Pichincha (Observed)","EC",2033 +"2033-05-24","The Battle of Pichincha","EC",2033 +"2033-08-10","Declaration of Independence of Quito","EC",2033 +"2033-08-12","Declaration of Independence of Quito (Observed)","EC",2033 +"2033-10-09","Independence of Guayaquil","EC",2033 +"2033-10-10","Independence of Guayaquil (Observed)","EC",2033 +"2033-11-02","All Souls' Day","EC",2033 +"2033-11-03","Independence of Cuenca","EC",2033 +"2033-11-04","All Souls' Day (Observed)","EC",2033 +"2033-11-04","Independence of Cuenca (Observed)","EC",2033 +"2033-12-25","Christmas Day","EC",2033 +"2033-12-26","Christmas Day (Observed)","EC",2033 +"2034-01-01","New Year's Day","EC",2034 +"2034-01-02","New Year's Day (Observed)","EC",2034 +"2034-02-20","Carnival","EC",2034 +"2034-02-21","Carnival","EC",2034 +"2034-04-07","Good Friday","EC",2034 +"2034-05-01","Labour Day","EC",2034 +"2034-05-24","The Battle of Pichincha","EC",2034 +"2034-05-26","The Battle of Pichincha (Observed)","EC",2034 +"2034-08-10","Declaration of Independence of Quito","EC",2034 +"2034-08-11","Declaration of Independence of Quito (Observed)","EC",2034 +"2034-10-09","Independence of Guayaquil","EC",2034 +"2034-11-02","All Souls' Day","EC",2034 +"2034-11-03","Independence of Cuenca","EC",2034 +"2034-12-25","Christmas Day","EC",2034 +"2035-01-01","New Year's Day","EC",2035 +"2035-02-05","Carnival","EC",2035 +"2035-02-06","Carnival","EC",2035 +"2035-03-23","Good Friday","EC",2035 +"2035-04-30","Labour Day (Observed)","EC",2035 +"2035-05-01","Labour Day","EC",2035 +"2035-05-24","The Battle of Pichincha","EC",2035 +"2035-05-25","The Battle of Pichincha (Observed)","EC",2035 +"2035-08-10","Declaration of Independence of Quito","EC",2035 +"2035-10-08","Independence of Guayaquil (Observed)","EC",2035 +"2035-10-09","Independence of Guayaquil","EC",2035 +"2035-11-02","All Souls' Day","EC",2035 +"2035-11-03","Independence of Cuenca","EC",2035 +"2035-12-25","Christmas Day","EC",2035 +"2036-01-01","New Year's Day","EC",2036 +"2036-02-25","Carnival","EC",2036 +"2036-02-26","Carnival","EC",2036 +"2036-04-11","Good Friday","EC",2036 +"2036-05-01","Labour Day","EC",2036 +"2036-05-02","Labour Day (Observed)","EC",2036 +"2036-05-23","The Battle of Pichincha (Observed)","EC",2036 +"2036-05-24","The Battle of Pichincha","EC",2036 +"2036-08-10","Declaration of Independence of Quito","EC",2036 +"2036-08-11","Declaration of Independence of Quito (Observed)","EC",2036 +"2036-10-09","Independence of Guayaquil","EC",2036 +"2036-10-10","Independence of Guayaquil (Observed)","EC",2036 +"2036-11-02","All Souls' Day","EC",2036 +"2036-11-03","Independence of Cuenca","EC",2036 +"2036-12-25","Christmas Day","EC",2036 +"2037-01-01","New Year's Day","EC",2037 +"2037-02-16","Carnival","EC",2037 +"2037-02-17","Carnival","EC",2037 +"2037-04-03","Good Friday","EC",2037 +"2037-05-01","Labour Day","EC",2037 +"2037-05-24","The Battle of Pichincha","EC",2037 +"2037-05-25","The Battle of Pichincha (Observed)","EC",2037 +"2037-08-10","Declaration of Independence of Quito","EC",2037 +"2037-10-09","Independence of Guayaquil","EC",2037 +"2037-11-02","All Souls' Day","EC",2037 +"2037-11-03","Independence of Cuenca","EC",2037 +"2037-12-25","Christmas Day","EC",2037 +"2038-01-01","New Year's Day","EC",2038 +"2038-03-08","Carnival","EC",2038 +"2038-03-09","Carnival","EC",2038 +"2038-04-23","Good Friday","EC",2038 +"2038-04-30","Labour Day (Observed)","EC",2038 +"2038-05-01","Labour Day","EC",2038 +"2038-05-24","The Battle of Pichincha","EC",2038 +"2038-08-09","Declaration of Independence of Quito (Observed)","EC",2038 +"2038-08-10","Declaration of Independence of Quito","EC",2038 +"2038-10-08","Independence of Guayaquil (Observed)","EC",2038 +"2038-10-09","Independence of Guayaquil","EC",2038 +"2038-11-01","All Souls' Day (Observed)","EC",2038 +"2038-11-02","All Souls' Day","EC",2038 +"2038-11-03","Independence of Cuenca","EC",2038 +"2038-11-05","Independence of Cuenca (Observed)","EC",2038 +"2038-12-24","Christmas Day (Observed)","EC",2038 +"2038-12-25","Christmas Day","EC",2038 +"2038-12-31","New Year's Day (Observed)","EC",2038 +"2039-01-01","New Year's Day","EC",2039 +"2039-02-21","Carnival","EC",2039 +"2039-02-22","Carnival","EC",2039 +"2039-04-08","Good Friday","EC",2039 +"2039-05-01","Labour Day","EC",2039 +"2039-05-02","Labour Day (Observed)","EC",2039 +"2039-05-23","The Battle of Pichincha (Observed)","EC",2039 +"2039-05-24","The Battle of Pichincha","EC",2039 +"2039-08-10","Declaration of Independence of Quito","EC",2039 +"2039-08-12","Declaration of Independence of Quito (Observed)","EC",2039 +"2039-10-09","Independence of Guayaquil","EC",2039 +"2039-10-10","Independence of Guayaquil (Observed)","EC",2039 +"2039-11-02","All Souls' Day","EC",2039 +"2039-11-03","Independence of Cuenca","EC",2039 +"2039-11-04","All Souls' Day (Observed)","EC",2039 +"2039-11-04","Independence of Cuenca (Observed)","EC",2039 +"2039-12-25","Christmas Day","EC",2039 +"2039-12-26","Christmas Day (Observed)","EC",2039 +"2040-01-01","New Year's Day","EC",2040 +"2040-01-02","New Year's Day (Observed)","EC",2040 +"2040-02-13","Carnival","EC",2040 +"2040-02-14","Carnival","EC",2040 +"2040-03-30","Good Friday","EC",2040 +"2040-04-30","Labour Day (Observed)","EC",2040 +"2040-05-01","Labour Day","EC",2040 +"2040-05-24","The Battle of Pichincha","EC",2040 +"2040-05-25","The Battle of Pichincha (Observed)","EC",2040 +"2040-08-10","Declaration of Independence of Quito","EC",2040 +"2040-10-08","Independence of Guayaquil (Observed)","EC",2040 +"2040-10-09","Independence of Guayaquil","EC",2040 +"2040-11-02","All Souls' Day","EC",2040 +"2040-11-03","Independence of Cuenca","EC",2040 +"2040-12-25","Christmas Day","EC",2040 +"2041-01-01","New Year's Day","EC",2041 +"2041-03-04","Carnival","EC",2041 +"2041-03-05","Carnival","EC",2041 +"2041-04-19","Good Friday","EC",2041 +"2041-05-01","Labour Day","EC",2041 +"2041-05-03","Labour Day (Observed)","EC",2041 +"2041-05-24","The Battle of Pichincha","EC",2041 +"2041-08-09","Declaration of Independence of Quito (Observed)","EC",2041 +"2041-08-10","Declaration of Independence of Quito","EC",2041 +"2041-10-09","Independence of Guayaquil","EC",2041 +"2041-10-11","Independence of Guayaquil (Observed)","EC",2041 +"2041-11-01","All Souls' Day (Observed)","EC",2041 +"2041-11-02","All Souls' Day","EC",2041 +"2041-11-03","Independence of Cuenca","EC",2041 +"2041-11-04","Independence of Cuenca (Observed)","EC",2041 +"2041-12-25","Christmas Day","EC",2041 +"2042-01-01","New Year's Day","EC",2042 +"2042-02-17","Carnival","EC",2042 +"2042-02-18","Carnival","EC",2042 +"2042-04-04","Good Friday","EC",2042 +"2042-05-01","Labour Day","EC",2042 +"2042-05-02","Labour Day (Observed)","EC",2042 +"2042-05-23","The Battle of 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Day","EC",2043 +"2044-01-01","New Year's Day","EC",2044 +"2044-02-29","Carnival","EC",2044 +"2044-03-01","Carnival","EC",2044 +"2044-04-15","Good Friday","EC",2044 +"2044-05-01","Labour Day","EC",2044 +"2044-05-02","Labour Day (Observed)","EC",2044 +"2044-05-23","The Battle of Pichincha (Observed)","EC",2044 +"2044-05-24","The Battle of Pichincha","EC",2044 +"2044-08-10","Declaration of Independence of Quito","EC",2044 +"2044-08-12","Declaration of Independence of Quito (Observed)","EC",2044 +"2044-10-09","Independence of Guayaquil","EC",2044 +"2044-10-10","Independence of Guayaquil (Observed)","EC",2044 +"2044-11-02","All Souls' Day","EC",2044 +"2044-11-03","Independence of Cuenca","EC",2044 +"2044-11-04","All Souls' Day (Observed)","EC",2044 +"2044-11-04","Independence of Cuenca (Observed)","EC",2044 +"2044-12-25","Christmas Day","EC",2044 +"2044-12-26","Christmas Day (Observed)","EC",2044 +"1995-01-01","uusaasta","EE",1995 +"1995-02-24","iseseisvuspaev","EE",1995 +"1995-04-14","suur reede","EE",1995 +"1995-04-16","ulestousmispuhade 1. puha","EE",1995 +"1995-05-01","kevadpuha","EE",1995 +"1995-06-04","nelipuhade 1. puha","EE",1995 +"1995-06-23","voidupuha","EE",1995 +"1995-06-24","jaanipaev","EE",1995 +"1995-08-20","taasiseseisvumispaev","EE",1995 +"1995-12-24","joululaupaev","EE",1995 +"1995-12-25","esimene joulupuha","EE",1995 +"1995-12-26","teine joulupuha","EE",1995 +"1996-01-01","uusaasta","EE",1996 +"1996-02-24","iseseisvuspaev","EE",1996 +"1996-04-05","suur reede","EE",1996 +"1996-04-07","ulestousmispuhade 1. puha","EE",1996 +"1996-05-01","kevadpuha","EE",1996 +"1996-05-26","nelipuhade 1. puha","EE",1996 +"1996-06-23","voidupuha","EE",1996 +"1996-06-24","jaanipaev","EE",1996 +"1996-08-20","taasiseseisvumispaev","EE",1996 +"1996-12-24","joululaupaev","EE",1996 +"1996-12-25","esimene joulupuha","EE",1996 +"1996-12-26","teine joulupuha","EE",1996 +"1997-01-01","uusaasta","EE",1997 +"1997-02-24","iseseisvuspaev","EE",1997 +"1997-03-28","suur reede","EE",1997 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+"2041-04-21","ulestousmispuhade 1. puha","EE",2041 +"2041-05-01","kevadpuha","EE",2041 +"2041-06-09","nelipuhade 1. puha","EE",2041 +"2041-06-23","voidupuha","EE",2041 +"2041-06-24","jaanipaev","EE",2041 +"2041-08-20","taasiseseisvumispaev","EE",2041 +"2041-12-24","joululaupaev","EE",2041 +"2041-12-25","esimene joulupuha","EE",2041 +"2041-12-26","teine joulupuha","EE",2041 +"2042-01-01","uusaasta","EE",2042 +"2042-02-24","iseseisvuspaev","EE",2042 +"2042-04-04","suur reede","EE",2042 +"2042-04-06","ulestousmispuhade 1. puha","EE",2042 +"2042-05-01","kevadpuha","EE",2042 +"2042-05-25","nelipuhade 1. puha","EE",2042 +"2042-06-23","voidupuha","EE",2042 +"2042-06-24","jaanipaev","EE",2042 +"2042-08-20","taasiseseisvumispaev","EE",2042 +"2042-12-24","joululaupaev","EE",2042 +"2042-12-25","esimene joulupuha","EE",2042 +"2042-12-26","teine joulupuha","EE",2042 +"2043-01-01","uusaasta","EE",2043 +"2043-02-24","iseseisvuspaev","EE",2043 +"2043-03-27","suur reede","EE",2043 +"2043-03-29","ulestousmispuhade 1. puha","EE",2043 +"2043-05-01","kevadpuha","EE",2043 +"2043-05-17","nelipuhade 1. puha","EE",2043 +"2043-06-23","voidupuha","EE",2043 +"2043-06-24","jaanipaev","EE",2043 +"2043-08-20","taasiseseisvumispaev","EE",2043 +"2043-12-24","joululaupaev","EE",2043 +"2043-12-25","esimene joulupuha","EE",2043 +"2043-12-26","teine joulupuha","EE",2043 +"2044-01-01","uusaasta","EE",2044 +"2044-02-24","iseseisvuspaev","EE",2044 +"2044-04-15","suur reede","EE",2044 +"2044-04-17","ulestousmispuhade 1. puha","EE",2044 +"2044-05-01","kevadpuha","EE",2044 +"2044-06-05","nelipuhade 1. puha","EE",2044 +"2044-06-23","voidupuha","EE",2044 +"2044-06-24","jaanipaev","EE",2044 +"2044-08-20","taasiseseisvumispaev","EE",2044 +"2044-12-24","joululaupaev","EE",2044 +"2044-12-25","esimene joulupuha","EE",2044 +"2044-12-26","teine joulupuha","EE",2044 +"1995-01-01","New Year's Day - Bank Holiday","EG",1995 +"1995-01-07","Coptic Christmas","EG",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","EG",1995 +"1995-03-03","Eid al-Fitr Holiday* (*estimated)","EG",1995 +"1995-03-04","Eid al-Fitr Holiday* (*estimated)","EG",1995 +"1995-04-23","Coptic Easter Sunday","EG",1995 +"1995-04-24","Sham El Nessim","EG",1995 +"1995-04-25","Sinai Liberation Day","EG",1995 +"1995-05-01","Labour Day","EG",1995 +"1995-05-08","Arafat Day* (*estimated)","EG",1995 +"1995-05-09","Eid al-Adha* (*estimated)","EG",1995 +"1995-05-10","Eid al-Adha Holiday* (*estimated)","EG",1995 +"1995-05-11","Eid al-Adha Holiday* (*estimated)","EG",1995 +"1995-05-30","Islamic New Year* (*estimated)","EG",1995 +"1995-07-23","Revolution Day","EG",1995 +"1995-08-08","Prophet Muhammad's Birthday* (*estimated)","EG",1995 +"1995-10-06","Armed Forces Day","EG",1995 +"1996-01-01","New Year's Day - Bank Holiday","EG",1996 +"1996-01-07","Coptic Christmas","EG",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","EG",1996 +"1996-02-20","Eid al-Fitr Holiday* (*estimated)","EG",1996 +"1996-02-21","Eid al-Fitr Holiday* (*estimated)","EG",1996 +"1996-04-14","Coptic Easter Sunday","EG",1996 +"1996-04-15","Sham El Nessim","EG",1996 +"1996-04-25","Sinai Liberation Day","EG",1996 +"1996-04-26","Arafat Day* (*estimated)","EG",1996 +"1996-04-27","Eid al-Adha* (*estimated)","EG",1996 +"1996-04-28","Eid al-Adha Holiday* (*estimated)","EG",1996 +"1996-04-29","Eid al-Adha Holiday* (*estimated)","EG",1996 +"1996-05-01","Labour Day","EG",1996 +"1996-05-18","Islamic New Year* (*estimated)","EG",1996 +"1996-07-23","Revolution Day","EG",1996 +"1996-07-27","Prophet Muhammad's Birthday* (*estimated)","EG",1996 +"1996-10-06","Armed Forces Day","EG",1996 +"1997-01-01","New Year's Day - Bank Holiday","EG",1997 +"1997-01-07","Coptic Christmas","EG",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","EG",1997 +"1997-02-09","Eid al-Fitr Holiday* (*estimated)","EG",1997 +"1997-02-10","Eid al-Fitr Holiday* (*estimated)","EG",1997 +"1997-04-16","Arafat Day* (*estimated)","EG",1997 +"1997-04-17","Eid al-Adha* (*estimated)","EG",1997 +"1997-04-18","Eid al-Adha Holiday* (*estimated)","EG",1997 +"1997-04-19","Eid al-Adha Holiday* (*estimated)","EG",1997 +"1997-04-25","Sinai Liberation Day","EG",1997 +"1997-04-27","Coptic Easter Sunday","EG",1997 +"1997-04-28","Sham El Nessim","EG",1997 +"1997-05-01","Labour Day","EG",1997 +"1997-05-07","Islamic New Year* (*estimated)","EG",1997 +"1997-07-16","Prophet Muhammad's Birthday* (*estimated)","EG",1997 +"1997-07-23","Revolution Day","EG",1997 +"1997-10-06","Armed Forces Day","EG",1997 +"1998-01-01","New Year's Day - Bank Holiday","EG",1998 +"1998-01-07","Coptic Christmas","EG",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","EG",1998 +"1998-01-30","Eid al-Fitr Holiday* (*estimated)","EG",1998 +"1998-01-31","Eid al-Fitr Holiday* (*estimated)","EG",1998 +"1998-04-06","Arafat Day* (*estimated)","EG",1998 +"1998-04-07","Eid al-Adha* (*estimated)","EG",1998 +"1998-04-08","Eid al-Adha Holiday* (*estimated)","EG",1998 +"1998-04-09","Eid al-Adha Holiday* (*estimated)","EG",1998 +"1998-04-19","Coptic Easter Sunday","EG",1998 +"1998-04-20","Sham El Nessim","EG",1998 +"1998-04-25","Sinai Liberation Day","EG",1998 +"1998-04-27","Islamic New Year* (*estimated)","EG",1998 +"1998-05-01","Labour Day","EG",1998 +"1998-07-06","Prophet Muhammad's Birthday* (*estimated)","EG",1998 +"1998-07-23","Revolution Day","EG",1998 +"1998-10-06","Armed Forces Day","EG",1998 +"1999-01-01","New Year's Day - Bank Holiday","EG",1999 +"1999-01-07","Coptic Christmas","EG",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","EG",1999 +"1999-01-19","Eid al-Fitr Holiday* (*estimated)","EG",1999 +"1999-01-20","Eid al-Fitr Holiday* (*estimated)","EG",1999 +"1999-03-26","Arafat Day* (*estimated)","EG",1999 +"1999-03-27","Eid al-Adha* (*estimated)","EG",1999 +"1999-03-28","Eid al-Adha Holiday* (*estimated)","EG",1999 +"1999-03-29","Eid al-Adha Holiday* (*estimated)","EG",1999 +"1999-04-11","Coptic Easter Sunday","EG",1999 +"1999-04-12","Sham El Nessim","EG",1999 +"1999-04-17","Islamic New Year* (*estimated)","EG",1999 +"1999-04-25","Sinai Liberation Day","EG",1999 +"1999-05-01","Labour Day","EG",1999 +"1999-06-26","Prophet Muhammad's Birthday* (*estimated)","EG",1999 +"1999-07-23","Revolution Day","EG",1999 +"1999-10-06","Armed Forces Day","EG",1999 +"2000-01-01","New Year's Day - Bank Holiday","EG",2000 +"2000-01-07","Coptic Christmas","EG",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","EG",2000 +"2000-01-09","Eid al-Fitr Holiday* (*estimated)","EG",2000 +"2000-01-10","Eid al-Fitr Holiday* (*estimated)","EG",2000 +"2000-03-15","Arafat Day* (*estimated)","EG",2000 +"2000-03-16","Eid al-Adha* (*estimated)","EG",2000 +"2000-03-17","Eid al-Adha Holiday* (*estimated)","EG",2000 +"2000-03-18","Eid al-Adha Holiday* (*estimated)","EG",2000 +"2000-04-06","Islamic New Year* (*estimated)","EG",2000 +"2000-04-25","Sinai Liberation Day","EG",2000 +"2000-04-30","Coptic Easter Sunday","EG",2000 +"2000-05-01","Labour Day","EG",2000 +"2000-05-01","Sham El Nessim","EG",2000 +"2000-06-14","Prophet Muhammad's Birthday* (*estimated)","EG",2000 +"2000-07-23","Revolution Day","EG",2000 +"2000-10-06","Armed Forces Day","EG",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","EG",2000 +"2000-12-28","Eid al-Fitr Holiday* (*estimated)","EG",2000 +"2000-12-29","Eid al-Fitr Holiday* (*estimated)","EG",2000 +"2001-01-01","New Year's Day - Bank Holiday","EG",2001 +"2001-01-07","Coptic Christmas","EG",2001 +"2001-03-04","Arafat Day* (*estimated)","EG",2001 +"2001-03-05","Eid al-Adha* (*estimated)","EG",2001 +"2001-03-06","Eid al-Adha Holiday* (*estimated)","EG",2001 +"2001-03-07","Eid al-Adha Holiday* (*estimated)","EG",2001 +"2001-03-26","Islamic New Year* (*estimated)","EG",2001 +"2001-04-15","Coptic Easter Sunday","EG",2001 +"2001-04-16","Sham El Nessim","EG",2001 +"2001-04-25","Sinai Liberation Day","EG",2001 +"2001-05-01","Labour Day","EG",2001 +"2001-06-04","Prophet Muhammad's Birthday* (*estimated)","EG",2001 +"2001-07-23","Revolution Day","EG",2001 +"2001-10-06","Armed Forces Day","EG",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","EG",2001 +"2001-12-17","Eid al-Fitr Holiday* (*estimated)","EG",2001 +"2001-12-18","Eid al-Fitr Holiday* (*estimated)","EG",2001 +"2002-01-01","New Year's Day - Bank Holiday","EG",2002 +"2002-01-07","Coptic Christmas","EG",2002 +"2002-02-21","Arafat Day* (*estimated)","EG",2002 +"2002-02-22","Eid al-Adha* (*estimated)","EG",2002 +"2002-02-23","Eid al-Adha Holiday* (*estimated)","EG",2002 +"2002-02-24","Eid al-Adha Holiday* (*estimated)","EG",2002 +"2002-03-15","Islamic New Year* (*estimated)","EG",2002 +"2002-04-25","Sinai Liberation Day","EG",2002 +"2002-05-01","Labour Day","EG",2002 +"2002-05-05","Coptic Easter Sunday","EG",2002 +"2002-05-06","Sham El Nessim","EG",2002 +"2002-05-24","Prophet Muhammad's Birthday* (*estimated)","EG",2002 +"2002-07-23","Revolution Day","EG",2002 +"2002-10-06","Armed Forces Day","EG",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","EG",2002 +"2002-12-06","Eid al-Fitr Holiday* (*estimated)","EG",2002 +"2002-12-07","Eid al-Fitr Holiday* (*estimated)","EG",2002 +"2003-01-01","New Year's Day - Bank Holiday","EG",2003 +"2003-01-07","Coptic Christmas","EG",2003 +"2003-02-10","Arafat Day* (*estimated)","EG",2003 +"2003-02-11","Eid al-Adha* (*estimated)","EG",2003 +"2003-02-12","Eid al-Adha Holiday* (*estimated)","EG",2003 +"2003-02-13","Eid al-Adha Holiday* (*estimated)","EG",2003 +"2003-03-04","Islamic New Year* (*estimated)","EG",2003 +"2003-04-25","Sinai Liberation Day","EG",2003 +"2003-04-27","Coptic Easter Sunday","EG",2003 +"2003-04-28","Sham El Nessim","EG",2003 +"2003-05-01","Labour Day","EG",2003 +"2003-05-13","Prophet Muhammad's Birthday* (*estimated)","EG",2003 +"2003-07-23","Revolution Day","EG",2003 +"2003-10-06","Armed Forces Day","EG",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","EG",2003 +"2003-11-26","Eid al-Fitr Holiday* (*estimated)","EG",2003 +"2003-11-27","Eid al-Fitr Holiday* (*estimated)","EG",2003 +"2004-01-01","New Year's Day - Bank Holiday","EG",2004 +"2004-01-07","Coptic Christmas","EG",2004 +"2004-01-31","Arafat Day* (*estimated)","EG",2004 +"2004-02-01","Eid al-Adha* (*estimated)","EG",2004 +"2004-02-02","Eid al-Adha Holiday* (*estimated)","EG",2004 +"2004-02-03","Eid al-Adha Holiday* (*estimated)","EG",2004 +"2004-02-21","Islamic New Year* (*estimated)","EG",2004 +"2004-04-11","Coptic Easter Sunday","EG",2004 +"2004-04-12","Sham El Nessim","EG",2004 +"2004-04-25","Sinai Liberation Day","EG",2004 +"2004-05-01","Labour Day","EG",2004 +"2004-05-01","Prophet Muhammad's Birthday* (*estimated)","EG",2004 +"2004-07-23","Revolution Day","EG",2004 +"2004-10-06","Armed Forces Day","EG",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","EG",2004 +"2004-11-15","Eid al-Fitr Holiday* (*estimated)","EG",2004 +"2004-11-16","Eid al-Fitr Holiday* (*estimated)","EG",2004 +"2005-01-01","New Year's Day - Bank Holiday","EG",2005 +"2005-01-07","Coptic Christmas","EG",2005 +"2005-01-20","Arafat Day* (*estimated)","EG",2005 +"2005-01-21","Eid al-Adha* (*estimated)","EG",2005 +"2005-01-22","Eid al-Adha Holiday* (*estimated)","EG",2005 +"2005-01-23","Eid al-Adha Holiday* (*estimated)","EG",2005 +"2005-02-10","Islamic New Year* (*estimated)","EG",2005 +"2005-04-21","Prophet Muhammad's Birthday* (*estimated)","EG",2005 +"2005-04-25","Sinai Liberation Day","EG",2005 +"2005-05-01","Coptic Easter Sunday","EG",2005 +"2005-05-01","Labour Day","EG",2005 +"2005-05-02","Sham El Nessim","EG",2005 +"2005-07-23","Revolution Day","EG",2005 +"2005-10-06","Armed Forces Day","EG",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","EG",2005 +"2005-11-04","Eid al-Fitr Holiday* (*estimated)","EG",2005 +"2005-11-05","Eid al-Fitr Holiday* (*estimated)","EG",2005 +"2006-01-01","New Year's Day - Bank Holiday","EG",2006 +"2006-01-07","Coptic Christmas","EG",2006 +"2006-01-09","Arafat Day* (*estimated)","EG",2006 +"2006-01-10","Eid al-Adha* (*estimated)","EG",2006 +"2006-01-11","Eid al-Adha Holiday* (*estimated)","EG",2006 +"2006-01-12","Eid al-Adha Holiday* (*estimated)","EG",2006 +"2006-01-31","Islamic New Year* (*estimated)","EG",2006 +"2006-04-10","Prophet Muhammad's Birthday* (*estimated)","EG",2006 +"2006-04-23","Coptic Easter Sunday","EG",2006 +"2006-04-24","Sham El Nessim","EG",2006 +"2006-04-25","Sinai Liberation Day","EG",2006 +"2006-05-01","Labour Day","EG",2006 +"2006-07-23","Revolution Day","EG",2006 +"2006-10-06","Armed Forces Day","EG",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","EG",2006 +"2006-10-24","Eid al-Fitr Holiday* (*estimated)","EG",2006 +"2006-10-25","Eid al-Fitr Holiday* (*estimated)","EG",2006 +"2006-12-30","Arafat Day* (*estimated)","EG",2006 +"2006-12-31","Eid al-Adha* (*estimated)","EG",2006 +"2007-01-01","Eid al-Adha Holiday* (*estimated)","EG",2007 +"2007-01-01","New Year's Day - Bank Holiday","EG",2007 +"2007-01-02","Eid al-Adha Holiday* (*estimated)","EG",2007 +"2007-01-07","Coptic Christmas","EG",2007 +"2007-01-20","Islamic New Year* (*estimated)","EG",2007 +"2007-03-31","Prophet Muhammad's Birthday* (*estimated)","EG",2007 +"2007-04-08","Coptic Easter Sunday","EG",2007 +"2007-04-09","Sham El Nessim","EG",2007 +"2007-04-25","Sinai Liberation Day","EG",2007 +"2007-05-01","Labour Day","EG",2007 +"2007-07-23","Revolution Day","EG",2007 +"2007-10-06","Armed Forces Day","EG",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","EG",2007 +"2007-10-14","Eid al-Fitr Holiday* (*estimated)","EG",2007 +"2007-10-15","Eid al-Fitr Holiday* (*estimated)","EG",2007 +"2007-12-19","Arafat Day* (*estimated)","EG",2007 +"2007-12-20","Eid al-Adha* (*estimated)","EG",2007 +"2007-12-21","Eid al-Adha Holiday* (*estimated)","EG",2007 +"2007-12-22","Eid al-Adha Holiday* (*estimated)","EG",2007 +"2008-01-01","New Year's Day - Bank Holiday","EG",2008 +"2008-01-07","Coptic Christmas","EG",2008 +"2008-01-10","Islamic New Year* (*estimated)","EG",2008 +"2008-03-20","Prophet Muhammad's Birthday* (*estimated)","EG",2008 +"2008-04-25","Sinai Liberation Day","EG",2008 +"2008-04-27","Coptic Easter Sunday","EG",2008 +"2008-04-28","Sham El Nessim","EG",2008 +"2008-05-01","Labour Day","EG",2008 +"2008-07-23","Revolution Day","EG",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","EG",2008 +"2008-10-02","Eid al-Fitr Holiday* (*estimated)","EG",2008 +"2008-10-03","Eid al-Fitr Holiday* (*estimated)","EG",2008 +"2008-10-06","Armed Forces Day","EG",2008 +"2008-12-07","Arafat Day* (*estimated)","EG",2008 +"2008-12-08","Eid al-Adha* (*estimated)","EG",2008 +"2008-12-09","Eid al-Adha Holiday* (*estimated)","EG",2008 +"2008-12-10","Eid al-Adha Holiday* (*estimated)","EG",2008 +"2008-12-29","Islamic New Year* (*estimated)","EG",2008 +"2009-01-01","New Year's Day - Bank Holiday","EG",2009 +"2009-01-07","Coptic Christmas","EG",2009 +"2009-01-25","Police Day","EG",2009 +"2009-03-09","Prophet Muhammad's Birthday* (*estimated)","EG",2009 +"2009-04-19","Coptic Easter Sunday","EG",2009 +"2009-04-20","Sham El Nessim","EG",2009 +"2009-04-25","Sinai Liberation Day","EG",2009 +"2009-05-01","Labour Day","EG",2009 +"2009-07-23","Revolution Day","EG",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","EG",2009 +"2009-09-21","Eid al-Fitr Holiday* (*estimated)","EG",2009 +"2009-09-22","Eid al-Fitr Holiday* (*estimated)","EG",2009 +"2009-10-06","Armed Forces Day","EG",2009 +"2009-11-26","Arafat Day* (*estimated)","EG",2009 +"2009-11-27","Eid al-Adha* (*estimated)","EG",2009 +"2009-11-28","Eid al-Adha Holiday* (*estimated)","EG",2009 +"2009-11-29","Eid al-Adha Holiday* (*estimated)","EG",2009 +"2009-12-18","Islamic New Year* (*estimated)","EG",2009 +"2010-01-01","New Year's Day - Bank Holiday","EG",2010 +"2010-01-07","Coptic Christmas","EG",2010 +"2010-01-25","Police Day","EG",2010 +"2010-02-26","Prophet Muhammad's Birthday* (*estimated)","EG",2010 +"2010-04-04","Coptic Easter Sunday","EG",2010 +"2010-04-05","Sham El Nessim","EG",2010 +"2010-04-25","Sinai Liberation Day","EG",2010 +"2010-05-01","Labour Day","EG",2010 +"2010-07-23","Revolution Day","EG",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","EG",2010 +"2010-09-11","Eid al-Fitr Holiday* (*estimated)","EG",2010 +"2010-09-12","Eid al-Fitr Holiday* (*estimated)","EG",2010 +"2010-10-06","Armed Forces Day","EG",2010 +"2010-11-15","Arafat Day* (*estimated)","EG",2010 +"2010-11-16","Eid al-Adha* (*estimated)","EG",2010 +"2010-11-17","Eid al-Adha Holiday* (*estimated)","EG",2010 +"2010-11-18","Eid al-Adha Holiday* (*estimated)","EG",2010 +"2010-12-07","Islamic New Year* (*estimated)","EG",2010 +"2011-01-01","New Year's Day - Bank Holiday","EG",2011 +"2011-01-07","Coptic Christmas","EG",2011 +"2011-01-25","Police Day","EG",2011 +"2011-02-15","Prophet Muhammad's Birthday* (*estimated)","EG",2011 +"2011-04-24","Coptic Easter Sunday","EG",2011 +"2011-04-25","Sham El Nessim","EG",2011 +"2011-04-25","Sinai Liberation Day","EG",2011 +"2011-05-01","Labour Day","EG",2011 +"2011-07-23","Revolution Day","EG",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","EG",2011 +"2011-08-31","Eid al-Fitr Holiday* (*estimated)","EG",2011 +"2011-09-01","Eid al-Fitr Holiday* (*estimated)","EG",2011 +"2011-10-06","Armed Forces Day","EG",2011 +"2011-11-05","Arafat Day* (*estimated)","EG",2011 +"2011-11-06","Eid al-Adha* (*estimated)","EG",2011 +"2011-11-07","Eid al-Adha Holiday* (*estimated)","EG",2011 +"2011-11-08","Eid al-Adha Holiday* (*estimated)","EG",2011 +"2011-11-26","Islamic New Year* (*estimated)","EG",2011 +"2012-01-01","New Year's Day - Bank Holiday","EG",2012 +"2012-01-07","Coptic Christmas","EG",2012 +"2012-01-25","Revolution Day - January 25","EG",2012 +"2012-02-04","Prophet Muhammad's Birthday* (*estimated)","EG",2012 +"2012-04-15","Coptic Easter Sunday","EG",2012 +"2012-04-16","Sham El Nessim","EG",2012 +"2012-04-25","Sinai Liberation Day","EG",2012 +"2012-05-01","Labour Day","EG",2012 +"2012-07-23","Revolution Day","EG",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","EG",2012 +"2012-08-20","Eid al-Fitr Holiday* (*estimated)","EG",2012 +"2012-08-21","Eid al-Fitr Holiday* (*estimated)","EG",2012 +"2012-10-06","Armed Forces Day","EG",2012 +"2012-10-25","Arafat Day* (*estimated)","EG",2012 +"2012-10-26","Eid al-Adha* (*estimated)","EG",2012 +"2012-10-27","Eid al-Adha Holiday* (*estimated)","EG",2012 +"2012-10-28","Eid al-Adha Holiday* (*estimated)","EG",2012 +"2012-11-15","Islamic New Year* (*estimated)","EG",2012 +"2013-01-01","New Year's Day - Bank Holiday","EG",2013 +"2013-01-07","Coptic Christmas","EG",2013 +"2013-01-24","Prophet Muhammad's Birthday* (*estimated)","EG",2013 +"2013-01-25","Revolution Day - January 25","EG",2013 +"2013-04-25","Sinai Liberation Day","EG",2013 +"2013-05-01","Labour Day","EG",2013 +"2013-05-05","Coptic Easter Sunday","EG",2013 +"2013-05-06","Sham El Nessim","EG",2013 +"2013-07-23","Revolution Day","EG",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","EG",2013 +"2013-08-09","Eid al-Fitr Holiday* (*estimated)","EG",2013 +"2013-08-10","Eid al-Fitr Holiday* (*estimated)","EG",2013 +"2013-10-06","Armed Forces Day","EG",2013 +"2013-10-14","Arafat Day* (*estimated)","EG",2013 +"2013-10-15","Eid al-Adha* (*estimated)","EG",2013 +"2013-10-16","Eid al-Adha Holiday* (*estimated)","EG",2013 +"2013-10-17","Eid al-Adha Holiday* (*estimated)","EG",2013 +"2013-11-04","Islamic New Year* (*estimated)","EG",2013 +"2014-01-01","New Year's Day - Bank Holiday","EG",2014 +"2014-01-07","Coptic Christmas","EG",2014 +"2014-01-13","Prophet Muhammad's Birthday* (*estimated)","EG",2014 +"2014-01-25","Revolution Day - January 25","EG",2014 +"2014-04-20","Coptic Easter Sunday","EG",2014 +"2014-04-21","Sham El Nessim","EG",2014 +"2014-04-25","Sinai Liberation Day","EG",2014 +"2014-05-01","Labour Day","EG",2014 +"2014-06-30","30 June Revolution Day","EG",2014 +"2014-07-23","Revolution Day","EG",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","EG",2014 +"2014-07-29","Eid al-Fitr Holiday* (*estimated)","EG",2014 +"2014-07-30","Eid al-Fitr Holiday* (*estimated)","EG",2014 +"2014-10-03","Arafat Day* (*estimated)","EG",2014 +"2014-10-04","Eid al-Adha* (*estimated)","EG",2014 +"2014-10-05","Eid al-Adha Holiday* (*estimated)","EG",2014 +"2014-10-06","Armed Forces Day","EG",2014 +"2014-10-06","Eid al-Adha Holiday* (*estimated)","EG",2014 +"2014-10-25","Islamic New Year* (*estimated)","EG",2014 +"2015-01-01","New Year's Day - Bank Holiday","EG",2015 +"2015-01-03","Prophet Muhammad's Birthday* (*estimated)","EG",2015 +"2015-01-07","Coptic Christmas","EG",2015 +"2015-01-25","Revolution Day - January 25","EG",2015 +"2015-04-12","Coptic Easter Sunday","EG",2015 +"2015-04-13","Sham El Nessim","EG",2015 +"2015-04-25","Sinai Liberation Day","EG",2015 +"2015-05-01","Labour Day","EG",2015 +"2015-06-30","30 June Revolution Day","EG",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","EG",2015 +"2015-07-18","Eid al-Fitr Holiday* (*estimated)","EG",2015 +"2015-07-19","Eid al-Fitr Holiday* (*estimated)","EG",2015 +"2015-07-23","Revolution Day","EG",2015 +"2015-09-22","Arafat Day* (*estimated)","EG",2015 +"2015-09-23","Eid al-Adha* (*estimated)","EG",2015 +"2015-09-24","Eid al-Adha Holiday* (*estimated)","EG",2015 +"2015-09-25","Eid al-Adha Holiday* (*estimated)","EG",2015 +"2015-10-06","Armed Forces Day","EG",2015 +"2015-10-14","Islamic New Year* (*estimated)","EG",2015 +"2015-12-23","Prophet Muhammad's Birthday* (*estimated)","EG",2015 +"2016-01-01","New Year's Day - Bank Holiday","EG",2016 +"2016-01-07","Coptic Christmas","EG",2016 +"2016-01-25","Revolution Day - January 25","EG",2016 +"2016-04-25","Sinai Liberation Day","EG",2016 +"2016-05-01","Coptic Easter Sunday","EG",2016 +"2016-05-01","Labour Day","EG",2016 +"2016-05-02","Sham El Nessim","EG",2016 +"2016-06-30","30 June Revolution Day","EG",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","EG",2016 +"2016-07-07","Eid al-Fitr Holiday* (*estimated)","EG",2016 +"2016-07-08","Eid al-Fitr Holiday* (*estimated)","EG",2016 +"2016-07-23","Revolution Day","EG",2016 +"2016-09-10","Arafat Day* (*estimated)","EG",2016 +"2016-09-11","Eid al-Adha* (*estimated)","EG",2016 +"2016-09-12","Eid al-Adha Holiday* (*estimated)","EG",2016 +"2016-09-13","Eid al-Adha Holiday* (*estimated)","EG",2016 +"2016-10-02","Islamic New Year* (*estimated)","EG",2016 +"2016-10-06","Armed Forces Day","EG",2016 +"2016-12-11","Prophet Muhammad's Birthday* (*estimated)","EG",2016 +"2017-01-01","New Year's Day - Bank Holiday","EG",2017 +"2017-01-07","Coptic Christmas","EG",2017 +"2017-01-25","Revolution Day - January 25","EG",2017 +"2017-04-16","Coptic Easter Sunday","EG",2017 +"2017-04-17","Sham El Nessim","EG",2017 +"2017-04-25","Sinai Liberation Day","EG",2017 +"2017-05-01","Labour Day","EG",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","EG",2017 +"2017-06-26","Eid al-Fitr Holiday* (*estimated)","EG",2017 +"2017-06-27","Eid al-Fitr Holiday* (*estimated)","EG",2017 +"2017-06-30","30 June Revolution Day","EG",2017 +"2017-07-23","Revolution Day","EG",2017 +"2017-08-31","Arafat Day* (*estimated)","EG",2017 +"2017-09-01","Eid al-Adha* (*estimated)","EG",2017 +"2017-09-02","Eid al-Adha Holiday* (*estimated)","EG",2017 +"2017-09-03","Eid al-Adha Holiday* (*estimated)","EG",2017 +"2017-09-21","Islamic New Year* (*estimated)","EG",2017 +"2017-10-06","Armed Forces Day","EG",2017 +"2017-11-30","Prophet Muhammad's Birthday* (*estimated)","EG",2017 +"2018-01-01","New Year's Day - Bank Holiday","EG",2018 +"2018-01-07","Coptic Christmas","EG",2018 +"2018-01-25","Revolution Day - January 25","EG",2018 +"2018-04-08","Coptic Easter Sunday","EG",2018 +"2018-04-09","Sham El Nessim","EG",2018 +"2018-04-25","Sinai Liberation Day","EG",2018 +"2018-05-01","Labour Day","EG",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","EG",2018 +"2018-06-16","Eid al-Fitr Holiday* (*estimated)","EG",2018 +"2018-06-17","Eid al-Fitr Holiday* (*estimated)","EG",2018 +"2018-06-30","30 June Revolution Day","EG",2018 +"2018-07-23","Revolution Day","EG",2018 +"2018-08-20","Arafat Day* (*estimated)","EG",2018 +"2018-08-21","Eid al-Adha* (*estimated)","EG",2018 +"2018-08-22","Eid al-Adha Holiday* (*estimated)","EG",2018 +"2018-08-23","Eid al-Adha Holiday* (*estimated)","EG",2018 +"2018-09-11","Islamic New Year* (*estimated)","EG",2018 +"2018-10-06","Armed Forces Day","EG",2018 +"2018-11-20","Prophet Muhammad's Birthday* (*estimated)","EG",2018 +"2019-01-01","New Year's Day - Bank Holiday","EG",2019 +"2019-01-07","Coptic Christmas","EG",2019 +"2019-01-25","Revolution Day - January 25","EG",2019 +"2019-04-25","Sinai Liberation Day","EG",2019 +"2019-04-28","Coptic Easter Sunday","EG",2019 +"2019-04-29","Sham El Nessim","EG",2019 +"2019-05-01","Labour Day","EG",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","EG",2019 +"2019-06-05","Eid al-Fitr Holiday* (*estimated)","EG",2019 +"2019-06-06","Eid al-Fitr Holiday* (*estimated)","EG",2019 +"2019-06-30","30 June Revolution Day","EG",2019 +"2019-07-23","Revolution Day","EG",2019 +"2019-08-10","Arafat Day* (*estimated)","EG",2019 +"2019-08-11","Eid al-Adha* (*estimated)","EG",2019 +"2019-08-12","Eid al-Adha Holiday* (*estimated)","EG",2019 +"2019-08-13","Eid al-Adha Holiday* (*estimated)","EG",2019 +"2019-08-31","Islamic New Year* (*estimated)","EG",2019 +"2019-10-06","Armed Forces Day","EG",2019 +"2019-11-09","Prophet Muhammad's Birthday* (*estimated)","EG",2019 +"2020-01-01","New Year's Day - Bank Holiday","EG",2020 +"2020-01-07","Coptic Christmas","EG",2020 +"2020-01-25","Revolution Day - January 25","EG",2020 +"2020-04-19","Coptic Easter Sunday","EG",2020 +"2020-04-20","Sham El Nessim","EG",2020 +"2020-04-25","Sinai Liberation Day","EG",2020 +"2020-05-01","Labour Day","EG",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","EG",2020 +"2020-05-25","Eid al-Fitr Holiday* (*estimated)","EG",2020 +"2020-05-26","Eid al-Fitr Holiday* (*estimated)","EG",2020 +"2020-06-30","30 June Revolution Day","EG",2020 +"2020-07-23","Revolution Day","EG",2020 +"2020-07-30","Arafat Day* (*estimated)","EG",2020 +"2020-07-31","Eid al-Adha* (*estimated)","EG",2020 +"2020-08-01","Eid al-Adha Holiday* (*estimated)","EG",2020 +"2020-08-02","Eid al-Adha Holiday* (*estimated)","EG",2020 +"2020-08-20","Islamic New Year* (*estimated)","EG",2020 +"2020-10-06","Armed Forces Day","EG",2020 +"2020-10-29","Prophet Muhammad's Birthday* (*estimated)","EG",2020 +"2021-01-01","New Year's Day - Bank Holiday","EG",2021 +"2021-01-07","Coptic Christmas","EG",2021 +"2021-01-25","Revolution Day - January 25","EG",2021 +"2021-04-25","Sinai Liberation Day","EG",2021 +"2021-05-01","Labour Day","EG",2021 +"2021-05-02","Coptic Easter Sunday","EG",2021 +"2021-05-03","Sham El Nessim","EG",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","EG",2021 +"2021-05-14","Eid al-Fitr Holiday* (*estimated)","EG",2021 +"2021-05-15","Eid al-Fitr Holiday* (*estimated)","EG",2021 +"2021-06-30","30 June Revolution Day","EG",2021 +"2021-07-19","Arafat Day* (*estimated)","EG",2021 +"2021-07-20","Eid al-Adha* (*estimated)","EG",2021 +"2021-07-21","Eid al-Adha Holiday* (*estimated)","EG",2021 +"2021-07-22","Eid al-Adha Holiday* (*estimated)","EG",2021 +"2021-07-23","Revolution Day","EG",2021 +"2021-08-09","Islamic New Year* (*estimated)","EG",2021 +"2021-10-06","Armed Forces Day","EG",2021 +"2021-10-18","Prophet Muhammad's Birthday* (*estimated)","EG",2021 +"2022-01-01","New Year's Day - Bank Holiday","EG",2022 +"2022-01-07","Coptic Christmas","EG",2022 +"2022-01-25","Revolution Day - January 25","EG",2022 +"2022-04-24","Coptic Easter Sunday","EG",2022 +"2022-04-25","Sham El Nessim","EG",2022 +"2022-04-25","Sinai Liberation Day","EG",2022 +"2022-05-01","Labour Day","EG",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","EG",2022 +"2022-05-03","Eid al-Fitr Holiday* (*estimated)","EG",2022 +"2022-05-04","Eid al-Fitr Holiday* (*estimated)","EG",2022 +"2022-06-30","30 June Revolution Day","EG",2022 +"2022-07-08","Arafat Day* (*estimated)","EG",2022 +"2022-07-09","Eid al-Adha* (*estimated)","EG",2022 +"2022-07-10","Eid al-Adha Holiday* (*estimated)","EG",2022 +"2022-07-11","Eid al-Adha Holiday* (*estimated)","EG",2022 +"2022-07-23","Revolution Day","EG",2022 +"2022-07-30","Islamic New Year* (*estimated)","EG",2022 +"2022-10-06","Armed Forces Day","EG",2022 +"2022-10-08","Prophet Muhammad's Birthday* (*estimated)","EG",2022 +"2023-01-01","New Year's Day - Bank Holiday","EG",2023 +"2023-01-07","Coptic Christmas","EG",2023 +"2023-01-25","Revolution Day - January 25","EG",2023 +"2023-04-16","Coptic Easter Sunday","EG",2023 +"2023-04-17","Sham El Nessim","EG",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","EG",2023 +"2023-04-22","Eid al-Fitr Holiday* (*estimated)","EG",2023 +"2023-04-23","Eid al-Fitr Holiday* (*estimated)","EG",2023 +"2023-04-25","Sinai Liberation Day","EG",2023 +"2023-05-01","Labour Day","EG",2023 +"2023-06-27","Arafat Day* (*estimated)","EG",2023 +"2023-06-28","Eid al-Adha* (*estimated)","EG",2023 +"2023-06-29","Eid al-Adha Holiday* (*estimated)","EG",2023 +"2023-06-30","30 June Revolution Day","EG",2023 +"2023-06-30","Eid al-Adha Holiday* (*estimated)","EG",2023 +"2023-07-19","Islamic New Year* (*estimated)","EG",2023 +"2023-07-23","Revolution Day","EG",2023 +"2023-09-27","Prophet Muhammad's Birthday* (*estimated)","EG",2023 +"2023-10-06","Armed Forces Day","EG",2023 +"2024-01-01","New Year's Day - Bank Holiday","EG",2024 +"2024-01-07","Coptic Christmas","EG",2024 +"2024-01-25","Revolution Day - January 25","EG",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","EG",2024 +"2024-04-11","Eid al-Fitr Holiday* (*estimated)","EG",2024 +"2024-04-12","Eid al-Fitr Holiday* (*estimated)","EG",2024 +"2024-04-25","Sinai Liberation Day","EG",2024 +"2024-05-01","Labour Day","EG",2024 +"2024-05-05","Coptic Easter Sunday","EG",2024 +"2024-05-06","Sham El Nessim","EG",2024 +"2024-06-15","Arafat Day* (*estimated)","EG",2024 +"2024-06-16","Eid al-Adha* (*estimated)","EG",2024 +"2024-06-17","Eid al-Adha Holiday* (*estimated)","EG",2024 +"2024-06-18","Eid al-Adha Holiday* (*estimated)","EG",2024 +"2024-06-30","30 June Revolution Day","EG",2024 +"2024-07-07","Islamic New Year* (*estimated)","EG",2024 +"2024-07-23","Revolution Day","EG",2024 +"2024-09-15","Prophet Muhammad's Birthday* (*estimated)","EG",2024 +"2024-10-06","Armed Forces Day","EG",2024 +"2025-01-01","New Year's Day - Bank Holiday","EG",2025 +"2025-01-07","Coptic Christmas","EG",2025 +"2025-01-25","Revolution Day - January 25","EG",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","EG",2025 +"2025-03-31","Eid al-Fitr Holiday* (*estimated)","EG",2025 +"2025-04-01","Eid al-Fitr Holiday* (*estimated)","EG",2025 +"2025-04-20","Coptic Easter Sunday","EG",2025 +"2025-04-21","Sham El Nessim","EG",2025 +"2025-04-25","Sinai Liberation Day","EG",2025 +"2025-05-01","Labour Day","EG",2025 +"2025-06-05","Arafat Day* (*estimated)","EG",2025 +"2025-06-06","Eid al-Adha* (*estimated)","EG",2025 +"2025-06-07","Eid al-Adha Holiday* (*estimated)","EG",2025 +"2025-06-08","Eid al-Adha Holiday* (*estimated)","EG",2025 +"2025-06-26","Islamic New Year* (*estimated)","EG",2025 +"2025-06-30","30 June Revolution Day","EG",2025 +"2025-07-23","Revolution Day","EG",2025 +"2025-09-04","Prophet Muhammad's Birthday* (*estimated)","EG",2025 +"2025-10-06","Armed Forces Day","EG",2025 +"2026-01-01","New Year's Day - Bank Holiday","EG",2026 +"2026-01-07","Coptic Christmas","EG",2026 +"2026-01-25","Revolution Day - January 25","EG",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","EG",2026 +"2026-03-21","Eid al-Fitr Holiday* (*estimated)","EG",2026 +"2026-03-22","Eid al-Fitr Holiday* (*estimated)","EG",2026 +"2026-04-12","Coptic Easter Sunday","EG",2026 +"2026-04-13","Sham El Nessim","EG",2026 +"2026-04-25","Sinai Liberation Day","EG",2026 +"2026-05-01","Labour Day","EG",2026 +"2026-05-26","Arafat Day* (*estimated)","EG",2026 +"2026-05-27","Eid al-Adha* (*estimated)","EG",2026 +"2026-05-28","Eid al-Adha Holiday* (*estimated)","EG",2026 +"2026-05-29","Eid al-Adha Holiday* (*estimated)","EG",2026 +"2026-06-16","Islamic New Year* (*estimated)","EG",2026 +"2026-06-30","30 June Revolution Day","EG",2026 +"2026-07-23","Revolution Day","EG",2026 +"2026-08-25","Prophet Muhammad's Birthday* (*estimated)","EG",2026 +"2026-10-06","Armed Forces Day","EG",2026 +"2027-01-01","New Year's Day - Bank Holiday","EG",2027 +"2027-01-07","Coptic Christmas","EG",2027 +"2027-01-25","Revolution Day - January 25","EG",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","EG",2027 +"2027-03-10","Eid al-Fitr Holiday* (*estimated)","EG",2027 +"2027-03-11","Eid al-Fitr Holiday* (*estimated)","EG",2027 +"2027-04-25","Sinai Liberation Day","EG",2027 +"2027-05-01","Labour Day","EG",2027 +"2027-05-02","Coptic Easter Sunday","EG",2027 +"2027-05-03","Sham El Nessim","EG",2027 +"2027-05-15","Arafat Day* (*estimated)","EG",2027 +"2027-05-16","Eid al-Adha* (*estimated)","EG",2027 +"2027-05-17","Eid al-Adha Holiday* (*estimated)","EG",2027 +"2027-05-18","Eid al-Adha Holiday* (*estimated)","EG",2027 +"2027-06-06","Islamic New Year* (*estimated)","EG",2027 +"2027-06-30","30 June Revolution Day","EG",2027 +"2027-07-23","Revolution Day","EG",2027 +"2027-08-14","Prophet Muhammad's Birthday* (*estimated)","EG",2027 +"2027-10-06","Armed Forces Day","EG",2027 +"2028-01-01","New Year's Day - Bank Holiday","EG",2028 +"2028-01-07","Coptic Christmas","EG",2028 +"2028-01-25","Revolution Day - January 25","EG",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","EG",2028 +"2028-02-27","Eid al-Fitr Holiday* (*estimated)","EG",2028 +"2028-02-28","Eid al-Fitr Holiday* (*estimated)","EG",2028 +"2028-04-16","Coptic Easter Sunday","EG",2028 +"2028-04-17","Sham El Nessim","EG",2028 +"2028-04-25","Sinai Liberation Day","EG",2028 +"2028-05-01","Labour Day","EG",2028 +"2028-05-04","Arafat Day* (*estimated)","EG",2028 +"2028-05-05","Eid al-Adha* (*estimated)","EG",2028 +"2028-05-06","Eid al-Adha Holiday* (*estimated)","EG",2028 +"2028-05-07","Eid al-Adha Holiday* (*estimated)","EG",2028 +"2028-05-25","Islamic New Year* (*estimated)","EG",2028 +"2028-06-30","30 June Revolution Day","EG",2028 +"2028-07-23","Revolution Day","EG",2028 +"2028-08-03","Prophet Muhammad's Birthday* (*estimated)","EG",2028 +"2028-10-06","Armed Forces Day","EG",2028 +"2029-01-01","New Year's Day - Bank Holiday","EG",2029 +"2029-01-07","Coptic Christmas","EG",2029 +"2029-01-25","Revolution Day - January 25","EG",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","EG",2029 +"2029-02-15","Eid al-Fitr Holiday* (*estimated)","EG",2029 +"2029-02-16","Eid al-Fitr Holiday* (*estimated)","EG",2029 +"2029-04-08","Coptic Easter Sunday","EG",2029 +"2029-04-09","Sham El Nessim","EG",2029 +"2029-04-23","Arafat Day* (*estimated)","EG",2029 +"2029-04-24","Eid al-Adha* (*estimated)","EG",2029 +"2029-04-25","Eid al-Adha Holiday* (*estimated)","EG",2029 +"2029-04-25","Sinai Liberation Day","EG",2029 +"2029-04-26","Eid al-Adha Holiday* (*estimated)","EG",2029 +"2029-05-01","Labour Day","EG",2029 +"2029-05-14","Islamic New Year* (*estimated)","EG",2029 +"2029-06-30","30 June Revolution Day","EG",2029 +"2029-07-23","Revolution Day","EG",2029 +"2029-07-24","Prophet Muhammad's Birthday* (*estimated)","EG",2029 +"2029-10-06","Armed Forces Day","EG",2029 +"2030-01-01","New Year's Day - Bank Holiday","EG",2030 +"2030-01-07","Coptic Christmas","EG",2030 +"2030-01-25","Revolution Day - January 25","EG",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","EG",2030 +"2030-02-05","Eid al-Fitr Holiday* (*estimated)","EG",2030 +"2030-02-06","Eid al-Fitr Holiday* (*estimated)","EG",2030 +"2030-04-12","Arafat Day* (*estimated)","EG",2030 +"2030-04-13","Eid al-Adha* (*estimated)","EG",2030 +"2030-04-14","Eid al-Adha Holiday* (*estimated)","EG",2030 +"2030-04-15","Eid al-Adha Holiday* (*estimated)","EG",2030 +"2030-04-25","Sinai Liberation Day","EG",2030 +"2030-04-28","Coptic Easter Sunday","EG",2030 +"2030-04-29","Sham El Nessim","EG",2030 +"2030-05-01","Labour Day","EG",2030 +"2030-05-03","Islamic New Year* (*estimated)","EG",2030 +"2030-06-30","30 June Revolution Day","EG",2030 +"2030-07-13","Prophet Muhammad's Birthday* (*estimated)","EG",2030 +"2030-07-23","Revolution Day","EG",2030 +"2030-10-06","Armed Forces Day","EG",2030 +"2031-01-01","New Year's Day - Bank Holiday","EG",2031 +"2031-01-07","Coptic Christmas","EG",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","EG",2031 +"2031-01-25","Eid al-Fitr Holiday* (*estimated)","EG",2031 +"2031-01-25","Revolution Day - January 25","EG",2031 +"2031-01-26","Eid al-Fitr Holiday* (*estimated)","EG",2031 +"2031-04-01","Arafat Day* (*estimated)","EG",2031 +"2031-04-02","Eid al-Adha* (*estimated)","EG",2031 +"2031-04-03","Eid al-Adha Holiday* (*estimated)","EG",2031 +"2031-04-04","Eid al-Adha Holiday* (*estimated)","EG",2031 +"2031-04-13","Coptic Easter Sunday","EG",2031 +"2031-04-14","Sham El Nessim","EG",2031 +"2031-04-23","Islamic New Year* (*estimated)","EG",2031 +"2031-04-25","Sinai Liberation Day","EG",2031 +"2031-05-01","Labour Day","EG",2031 +"2031-06-30","30 June Revolution Day","EG",2031 +"2031-07-02","Prophet Muhammad's Birthday* (*estimated)","EG",2031 +"2031-07-23","Revolution Day","EG",2031 +"2031-10-06","Armed Forces Day","EG",2031 +"2032-01-01","New Year's Day - Bank Holiday","EG",2032 +"2032-01-07","Coptic Christmas","EG",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","EG",2032 +"2032-01-15","Eid al-Fitr Holiday* (*estimated)","EG",2032 +"2032-01-16","Eid al-Fitr Holiday* (*estimated)","EG",2032 +"2032-01-25","Revolution Day - January 25","EG",2032 +"2032-03-21","Arafat Day* (*estimated)","EG",2032 +"2032-03-22","Eid al-Adha* (*estimated)","EG",2032 +"2032-03-23","Eid al-Adha Holiday* (*estimated)","EG",2032 +"2032-03-24","Eid al-Adha Holiday* (*estimated)","EG",2032 +"2032-04-11","Islamic New Year* (*estimated)","EG",2032 +"2032-04-25","Sinai Liberation Day","EG",2032 +"2032-05-01","Labour Day","EG",2032 +"2032-05-02","Coptic Easter Sunday","EG",2032 +"2032-05-03","Sham El Nessim","EG",2032 +"2032-06-20","Prophet Muhammad's Birthday* (*estimated)","EG",2032 +"2032-06-30","30 June Revolution Day","EG",2032 +"2032-07-23","Revolution Day","EG",2032 +"2032-10-06","Armed Forces Day","EG",2032 +"2033-01-01","New Year's Day - Bank Holiday","EG",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","EG",2033 +"2033-01-03","Eid al-Fitr Holiday* (*estimated)","EG",2033 +"2033-01-04","Eid al-Fitr Holiday* (*estimated)","EG",2033 +"2033-01-07","Coptic Christmas","EG",2033 +"2033-01-25","Revolution Day - January 25","EG",2033 +"2033-03-10","Arafat Day* (*estimated)","EG",2033 +"2033-03-11","Eid al-Adha* (*estimated)","EG",2033 +"2033-03-12","Eid al-Adha Holiday* (*estimated)","EG",2033 +"2033-03-13","Eid al-Adha Holiday* (*estimated)","EG",2033 +"2033-04-01","Islamic New Year* (*estimated)","EG",2033 +"2033-04-24","Coptic Easter Sunday","EG",2033 +"2033-04-25","Sham El Nessim","EG",2033 +"2033-04-25","Sinai Liberation Day","EG",2033 +"2033-05-01","Labour Day","EG",2033 +"2033-06-09","Prophet Muhammad's Birthday* (*estimated)","EG",2033 +"2033-06-30","30 June Revolution Day","EG",2033 +"2033-07-23","Revolution Day","EG",2033 +"2033-10-06","Armed Forces Day","EG",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","EG",2033 +"2033-12-24","Eid al-Fitr Holiday* (*estimated)","EG",2033 +"2033-12-25","Eid al-Fitr Holiday* (*estimated)","EG",2033 +"2034-01-01","New Year's Day - Bank Holiday","EG",2034 +"2034-01-07","Coptic Christmas","EG",2034 +"2034-01-25","Revolution Day - January 25","EG",2034 +"2034-02-28","Arafat Day* (*estimated)","EG",2034 +"2034-03-01","Eid al-Adha* (*estimated)","EG",2034 +"2034-03-02","Eid al-Adha Holiday* (*estimated)","EG",2034 +"2034-03-03","Eid al-Adha Holiday* (*estimated)","EG",2034 +"2034-03-21","Islamic New Year* (*estimated)","EG",2034 +"2034-04-09","Coptic Easter Sunday","EG",2034 +"2034-04-10","Sham El Nessim","EG",2034 +"2034-04-25","Sinai Liberation Day","EG",2034 +"2034-05-01","Labour Day","EG",2034 +"2034-05-30","Prophet Muhammad's Birthday* (*estimated)","EG",2034 +"2034-06-30","30 June Revolution Day","EG",2034 +"2034-07-23","Revolution Day","EG",2034 +"2034-10-06","Armed Forces Day","EG",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","EG",2034 +"2034-12-13","Eid al-Fitr Holiday* (*estimated)","EG",2034 +"2034-12-14","Eid al-Fitr Holiday* (*estimated)","EG",2034 +"2035-01-01","New Year's Day - Bank Holiday","EG",2035 +"2035-01-07","Coptic Christmas","EG",2035 +"2035-01-25","Revolution Day - January 25","EG",2035 +"2035-02-17","Arafat Day* (*estimated)","EG",2035 +"2035-02-18","Eid al-Adha* (*estimated)","EG",2035 +"2035-02-19","Eid al-Adha Holiday* (*estimated)","EG",2035 +"2035-02-20","Eid al-Adha Holiday* (*estimated)","EG",2035 +"2035-03-11","Islamic New Year* (*estimated)","EG",2035 +"2035-04-25","Sinai Liberation Day","EG",2035 +"2035-04-29","Coptic Easter Sunday","EG",2035 +"2035-04-30","Sham El Nessim","EG",2035 +"2035-05-01","Labour Day","EG",2035 +"2035-05-20","Prophet Muhammad's Birthday* (*estimated)","EG",2035 +"2035-06-30","30 June Revolution Day","EG",2035 +"2035-07-23","Revolution Day","EG",2035 +"2035-10-06","Armed Forces Day","EG",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","EG",2035 +"2035-12-02","Eid al-Fitr Holiday* (*estimated)","EG",2035 +"2035-12-03","Eid al-Fitr Holiday* (*estimated)","EG",2035 +"2036-01-01","New Year's Day - Bank Holiday","EG",2036 +"2036-01-07","Coptic Christmas","EG",2036 +"2036-01-25","Revolution Day - January 25","EG",2036 +"2036-02-06","Arafat Day* (*estimated)","EG",2036 +"2036-02-07","Eid al-Adha* (*estimated)","EG",2036 +"2036-02-08","Eid al-Adha Holiday* (*estimated)","EG",2036 +"2036-02-09","Eid al-Adha Holiday* (*estimated)","EG",2036 +"2036-02-28","Islamic New Year* (*estimated)","EG",2036 +"2036-04-20","Coptic Easter Sunday","EG",2036 +"2036-04-21","Sham El Nessim","EG",2036 +"2036-04-25","Sinai Liberation Day","EG",2036 +"2036-05-01","Labour Day","EG",2036 +"2036-05-08","Prophet Muhammad's Birthday* (*estimated)","EG",2036 +"2036-06-30","30 June Revolution Day","EG",2036 +"2036-07-23","Revolution Day","EG",2036 +"2036-10-06","Armed Forces Day","EG",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","EG",2036 +"2036-11-20","Eid al-Fitr Holiday* (*estimated)","EG",2036 +"2036-11-21","Eid al-Fitr Holiday* (*estimated)","EG",2036 +"2037-01-01","New Year's Day - Bank Holiday","EG",2037 +"2037-01-07","Coptic Christmas","EG",2037 +"2037-01-25","Arafat Day* (*estimated)","EG",2037 +"2037-01-25","Revolution Day - January 25","EG",2037 +"2037-01-26","Eid al-Adha* (*estimated)","EG",2037 +"2037-01-27","Eid al-Adha Holiday* (*estimated)","EG",2037 +"2037-01-28","Eid al-Adha Holiday* (*estimated)","EG",2037 +"2037-02-16","Islamic New Year* (*estimated)","EG",2037 +"2037-04-05","Coptic Easter Sunday","EG",2037 +"2037-04-06","Sham El Nessim","EG",2037 +"2037-04-25","Sinai Liberation Day","EG",2037 +"2037-04-28","Prophet Muhammad's Birthday* (*estimated)","EG",2037 +"2037-05-01","Labour Day","EG",2037 +"2037-06-30","30 June Revolution Day","EG",2037 +"2037-07-23","Revolution Day","EG",2037 +"2037-10-06","Armed Forces Day","EG",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","EG",2037 +"2037-11-09","Eid al-Fitr Holiday* (*estimated)","EG",2037 +"2037-11-10","Eid al-Fitr Holiday* (*estimated)","EG",2037 +"2038-01-01","New Year's Day - Bank Holiday","EG",2038 +"2038-01-07","Coptic Christmas","EG",2038 +"2038-01-15","Arafat Day* (*estimated)","EG",2038 +"2038-01-16","Eid al-Adha* (*estimated)","EG",2038 +"2038-01-17","Eid al-Adha Holiday* (*estimated)","EG",2038 +"2038-01-18","Eid al-Adha Holiday* (*estimated)","EG",2038 +"2038-01-25","Revolution Day - January 25","EG",2038 +"2038-02-05","Islamic New Year* (*estimated)","EG",2038 +"2038-04-17","Prophet Muhammad's Birthday* (*estimated)","EG",2038 +"2038-04-25","Coptic Easter Sunday","EG",2038 +"2038-04-25","Sinai Liberation Day","EG",2038 +"2038-04-26","Sham El Nessim","EG",2038 +"2038-05-01","Labour Day","EG",2038 +"2038-06-30","30 June Revolution Day","EG",2038 +"2038-07-23","Revolution Day","EG",2038 +"2038-10-06","Armed Forces Day","EG",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","EG",2038 +"2038-10-30","Eid al-Fitr Holiday* (*estimated)","EG",2038 +"2038-10-31","Eid al-Fitr Holiday* (*estimated)","EG",2038 +"2039-01-01","New Year's Day - Bank Holiday","EG",2039 +"2039-01-04","Arafat Day* (*estimated)","EG",2039 +"2039-01-05","Eid al-Adha* (*estimated)","EG",2039 +"2039-01-06","Eid al-Adha Holiday* (*estimated)","EG",2039 +"2039-01-07","Coptic Christmas","EG",2039 +"2039-01-07","Eid al-Adha Holiday* (*estimated)","EG",2039 +"2039-01-25","Revolution Day - January 25","EG",2039 +"2039-01-26","Islamic New Year* (*estimated)","EG",2039 +"2039-04-06","Prophet Muhammad's Birthday* (*estimated)","EG",2039 +"2039-04-17","Coptic Easter Sunday","EG",2039 +"2039-04-18","Sham El Nessim","EG",2039 +"2039-04-25","Sinai Liberation Day","EG",2039 +"2039-05-01","Labour Day","EG",2039 +"2039-06-30","30 June Revolution Day","EG",2039 +"2039-07-23","Revolution Day","EG",2039 +"2039-10-06","Armed Forces Day","EG",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","EG",2039 +"2039-10-20","Eid al-Fitr Holiday* (*estimated)","EG",2039 +"2039-10-21","Eid al-Fitr Holiday* (*estimated)","EG",2039 +"2039-12-25","Arafat Day* (*estimated)","EG",2039 +"2039-12-26","Eid al-Adha* (*estimated)","EG",2039 +"2039-12-27","Eid al-Adha Holiday* (*estimated)","EG",2039 +"2039-12-28","Eid al-Adha Holiday* (*estimated)","EG",2039 +"2040-01-01","New Year's Day - Bank Holiday","EG",2040 +"2040-01-07","Coptic Christmas","EG",2040 +"2040-01-15","Islamic New Year* (*estimated)","EG",2040 +"2040-01-25","Revolution Day - January 25","EG",2040 +"2040-03-25","Prophet Muhammad's Birthday* (*estimated)","EG",2040 +"2040-04-25","Sinai Liberation Day","EG",2040 +"2040-05-01","Labour Day","EG",2040 +"2040-05-06","Coptic Easter Sunday","EG",2040 +"2040-05-07","Sham El Nessim","EG",2040 +"2040-06-30","30 June Revolution Day","EG",2040 +"2040-07-23","Revolution Day","EG",2040 +"2040-10-06","Armed Forces Day","EG",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","EG",2040 +"2040-10-08","Eid al-Fitr Holiday* (*estimated)","EG",2040 +"2040-10-09","Eid al-Fitr Holiday* (*estimated)","EG",2040 +"2040-12-13","Arafat Day* (*estimated)","EG",2040 +"2040-12-14","Eid al-Adha* (*estimated)","EG",2040 +"2040-12-15","Eid al-Adha Holiday* (*estimated)","EG",2040 +"2040-12-16","Eid al-Adha Holiday* (*estimated)","EG",2040 +"2041-01-01","New Year's Day - Bank Holiday","EG",2041 +"2041-01-04","Islamic New Year* (*estimated)","EG",2041 +"2041-01-07","Coptic Christmas","EG",2041 +"2041-01-25","Revolution Day - January 25","EG",2041 +"2041-03-15","Prophet Muhammad's Birthday* (*estimated)","EG",2041 +"2041-04-21","Coptic Easter Sunday","EG",2041 +"2041-04-22","Sham El Nessim","EG",2041 +"2041-04-25","Sinai Liberation Day","EG",2041 +"2041-05-01","Labour Day","EG",2041 +"2041-06-30","30 June Revolution Day","EG",2041 +"2041-07-23","Revolution Day","EG",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","EG",2041 +"2041-09-27","Eid al-Fitr Holiday* (*estimated)","EG",2041 +"2041-09-28","Eid al-Fitr Holiday* (*estimated)","EG",2041 +"2041-10-06","Armed Forces Day","EG",2041 +"2041-12-03","Arafat Day* (*estimated)","EG",2041 +"2041-12-04","Eid al-Adha* (*estimated)","EG",2041 +"2041-12-05","Eid al-Adha Holiday* (*estimated)","EG",2041 +"2041-12-06","Eid al-Adha Holiday* (*estimated)","EG",2041 +"2041-12-24","Islamic New Year* (*estimated)","EG",2041 +"2042-01-01","New Year's Day - Bank Holiday","EG",2042 +"2042-01-07","Coptic Christmas","EG",2042 +"2042-01-25","Revolution Day - January 25","EG",2042 +"2042-03-04","Prophet Muhammad's Birthday* (*estimated)","EG",2042 +"2042-04-13","Coptic Easter Sunday","EG",2042 +"2042-04-14","Sham El Nessim","EG",2042 +"2042-04-25","Sinai Liberation Day","EG",2042 +"2042-05-01","Labour Day","EG",2042 +"2042-06-30","30 June Revolution Day","EG",2042 +"2042-07-23","Revolution Day","EG",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","EG",2042 +"2042-09-16","Eid al-Fitr Holiday* (*estimated)","EG",2042 +"2042-09-17","Eid al-Fitr Holiday* (*estimated)","EG",2042 +"2042-10-06","Armed Forces Day","EG",2042 +"2042-11-22","Arafat Day* (*estimated)","EG",2042 +"2042-11-23","Eid al-Adha* (*estimated)","EG",2042 +"2042-11-24","Eid al-Adha Holiday* (*estimated)","EG",2042 +"2042-11-25","Eid al-Adha Holiday* (*estimated)","EG",2042 +"2042-12-14","Islamic New Year* (*estimated)","EG",2042 +"2043-01-01","New Year's Day - Bank Holiday","EG",2043 +"2043-01-07","Coptic Christmas","EG",2043 +"2043-01-25","Revolution Day - January 25","EG",2043 +"2043-02-22","Prophet Muhammad's Birthday* (*estimated)","EG",2043 +"2043-04-25","Sinai Liberation Day","EG",2043 +"2043-05-01","Labour Day","EG",2043 +"2043-05-03","Coptic Easter Sunday","EG",2043 +"2043-05-04","Sham El Nessim","EG",2043 +"2043-06-30","30 June Revolution Day","EG",2043 +"2043-07-23","Revolution Day","EG",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","EG",2043 +"2043-09-05","Eid al-Fitr Holiday* (*estimated)","EG",2043 +"2043-09-06","Eid al-Fitr Holiday* (*estimated)","EG",2043 +"2043-10-06","Armed Forces Day","EG",2043 +"2043-11-11","Arafat Day* (*estimated)","EG",2043 +"2043-11-12","Eid al-Adha* (*estimated)","EG",2043 +"2043-11-13","Eid al-Adha Holiday* (*estimated)","EG",2043 +"2043-11-14","Eid al-Adha Holiday* (*estimated)","EG",2043 +"2043-12-03","Islamic New Year* (*estimated)","EG",2043 +"2044-01-01","New Year's Day - Bank Holiday","EG",2044 +"2044-01-07","Coptic Christmas","EG",2044 +"2044-01-25","Revolution Day - January 25","EG",2044 +"2044-02-11","Prophet Muhammad's Birthday* (*estimated)","EG",2044 +"2044-04-24","Coptic Easter Sunday","EG",2044 +"2044-04-25","Sham El Nessim","EG",2044 +"2044-04-25","Sinai Liberation Day","EG",2044 +"2044-05-01","Labour Day","EG",2044 +"2044-06-30","30 June Revolution Day","EG",2044 +"2044-07-23","Revolution Day","EG",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","EG",2044 +"2044-08-25","Eid al-Fitr Holiday* (*estimated)","EG",2044 +"2044-08-26","Eid al-Fitr Holiday* (*estimated)","EG",2044 +"2044-10-06","Armed Forces Day","EG",2044 +"2044-10-30","Arafat Day* (*estimated)","EG",2044 +"2044-10-31","Eid al-Adha* (*estimated)","EG",2044 +"2044-11-01","Eid al-Adha Holiday* (*estimated)","EG",2044 +"2044-11-02","Eid al-Adha Holiday* (*estimated)","EG",2044 +"2044-11-21","Islamic New Year* (*estimated)","EG",2044 +"1995-01-02","Ano nuevo (Trasladado)","ES",1995 +"1995-01-06","Epifania del Senor","ES",1995 +"1995-04-14","Viernes Santo","ES",1995 +"1995-05-01","Dia del Trabajador","ES",1995 +"1995-08-15","Asuncion de la Virgen","ES",1995 +"1995-10-12","Dia de la Hispanidad","ES",1995 +"1995-11-01","Todos los Santos","ES",1995 +"1995-12-06","Dia de la Constitucion Espanola","ES",1995 +"1995-12-08","La Inmaculada Concepcion","ES",1995 +"1995-12-25","Navidad","ES",1995 +"1996-01-01","Ano nuevo","ES",1996 +"1996-01-06","Epifania del Senor","ES",1996 +"1996-04-05","Viernes Santo","ES",1996 +"1996-05-01","Dia del Trabajador","ES",1996 +"1996-08-15","Asuncion de la Virgen","ES",1996 +"1996-10-12","Dia de la Hispanidad","ES",1996 +"1996-11-01","Todos los Santos","ES",1996 +"1996-12-06","Dia de la Constitucion Espanola","ES",1996 +"1996-12-09","La Inmaculada Concepcion (Trasladado)","ES",1996 +"1996-12-25","Navidad","ES",1996 +"1997-01-01","Ano nuevo","ES",1997 +"1997-01-06","Epifania del Senor","ES",1997 +"1997-03-28","Viernes Santo","ES",1997 +"1997-05-01","Dia del Trabajador","ES",1997 +"1997-08-15","Asuncion de la Virgen","ES",1997 +"1997-10-13","Dia de la Hispanidad (Trasladado)","ES",1997 +"1997-11-01","Todos los Santos","ES",1997 +"1997-12-06","Dia de la Constitucion Espanola","ES",1997 +"1997-12-08","La Inmaculada Concepcion","ES",1997 +"1997-12-25","Navidad","ES",1997 +"1998-01-01","Ano nuevo","ES",1998 +"1998-01-06","Epifania del Senor","ES",1998 +"1998-04-10","Viernes Santo","ES",1998 +"1998-05-01","Dia del Trabajador","ES",1998 +"1998-08-15","Asuncion de la Virgen","ES",1998 +"1998-10-12","Dia de la Hispanidad","ES",1998 +"1998-11-02","Todos los Santos (Trasladado)","ES",1998 +"1998-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",1998 +"1998-12-08","La Inmaculada Concepcion","ES",1998 +"1998-12-25","Navidad","ES",1998 +"1999-01-01","Ano nuevo","ES",1999 +"1999-01-06","Epifania del Senor","ES",1999 +"1999-04-02","Viernes Santo","ES",1999 +"1999-05-01","Dia del Trabajador","ES",1999 +"1999-08-16","Asuncion de la Virgen (Trasladado)","ES",1999 +"1999-10-12","Dia de la Hispanidad","ES",1999 +"1999-11-01","Todos los Santos","ES",1999 +"1999-12-06","Dia de la Constitucion Espanola","ES",1999 +"1999-12-08","La Inmaculada Concepcion","ES",1999 +"1999-12-25","Navidad","ES",1999 +"2000-01-01","Ano nuevo","ES",2000 +"2000-01-06","Epifania del Senor","ES",2000 +"2000-04-21","Viernes Santo","ES",2000 +"2000-05-01","Dia del Trabajador","ES",2000 +"2000-08-15","Asuncion de la Virgen","ES",2000 +"2000-10-12","Dia de la Hispanidad","ES",2000 +"2000-11-01","Todos los Santos","ES",2000 +"2000-12-06","Dia de la Constitucion Espanola","ES",2000 +"2000-12-08","La Inmaculada Concepcion","ES",2000 +"2000-12-25","Navidad","ES",2000 +"2001-01-01","Ano nuevo","ES",2001 +"2001-01-06","Epifania del Senor","ES",2001 +"2001-04-13","Viernes Santo","ES",2001 +"2001-05-01","Dia del Trabajador","ES",2001 +"2001-08-15","Asuncion de la Virgen","ES",2001 +"2001-10-12","Dia de la Hispanidad","ES",2001 +"2001-11-01","Todos los Santos","ES",2001 +"2001-12-06","Dia de la Constitucion Espanola","ES",2001 +"2001-12-08","La Inmaculada Concepcion","ES",2001 +"2001-12-25","Navidad","ES",2001 +"2002-01-01","Ano nuevo","ES",2002 +"2002-01-07","Epifania del Senor (Trasladado)","ES",2002 +"2002-03-29","Viernes Santo","ES",2002 +"2002-05-01","Dia del Trabajador","ES",2002 +"2002-08-15","Asuncion de la Virgen","ES",2002 +"2002-10-12","Dia de la Hispanidad","ES",2002 +"2002-11-01","Todos los Santos","ES",2002 +"2002-12-06","Dia de la Constitucion Espanola","ES",2002 +"2002-12-09","La Inmaculada Concepcion (Trasladado)","ES",2002 +"2002-12-25","Navidad","ES",2002 +"2003-01-01","Ano nuevo","ES",2003 +"2003-01-06","Epifania del Senor","ES",2003 +"2003-04-18","Viernes Santo","ES",2003 +"2003-05-01","Dia del Trabajador","ES",2003 +"2003-08-15","Asuncion de la Virgen","ES",2003 +"2003-10-13","Dia de la Hispanidad (Trasladado)","ES",2003 +"2003-11-01","Todos los Santos","ES",2003 +"2003-12-06","Dia de la Constitucion Espanola","ES",2003 +"2003-12-08","La Inmaculada Concepcion","ES",2003 +"2003-12-25","Navidad","ES",2003 +"2004-01-01","Ano nuevo","ES",2004 +"2004-01-06","Epifania del Senor","ES",2004 +"2004-04-09","Viernes Santo","ES",2004 +"2004-05-01","Dia del Trabajador","ES",2004 +"2004-08-16","Asuncion de la Virgen (Trasladado)","ES",2004 +"2004-10-12","Dia de la Hispanidad","ES",2004 +"2004-11-01","Todos los Santos","ES",2004 +"2004-12-06","Dia de la Constitucion Espanola","ES",2004 +"2004-12-08","La Inmaculada Concepcion","ES",2004 +"2004-12-25","Navidad","ES",2004 +"2005-01-01","Ano nuevo","ES",2005 +"2005-01-06","Epifania del Senor","ES",2005 +"2005-03-25","Viernes Santo","ES",2005 +"2005-05-02","Dia del Trabajador (Trasladado)","ES",2005 +"2005-08-15","Asuncion de la Virgen","ES",2005 +"2005-10-12","Dia de la Hispanidad","ES",2005 +"2005-11-01","Todos los Santos","ES",2005 +"2005-12-06","Dia de la Constitucion Espanola","ES",2005 +"2005-12-08","La Inmaculada Concepcion","ES",2005 +"2005-12-26","Navidad (Trasladado)","ES",2005 +"2006-01-02","Ano nuevo (Trasladado)","ES",2006 +"2006-01-06","Epifania del Senor","ES",2006 +"2006-04-14","Viernes Santo","ES",2006 +"2006-05-01","Dia del Trabajador","ES",2006 +"2006-08-15","Asuncion de la Virgen","ES",2006 +"2006-10-12","Dia de la Hispanidad","ES",2006 +"2006-11-01","Todos los Santos","ES",2006 +"2006-12-06","Dia de la Constitucion Espanola","ES",2006 +"2006-12-08","La Inmaculada Concepcion","ES",2006 +"2006-12-25","Navidad","ES",2006 +"2007-01-01","Ano nuevo","ES",2007 +"2007-01-06","Epifania del Senor","ES",2007 +"2007-04-06","Viernes Santo","ES",2007 +"2007-05-01","Dia del Trabajador","ES",2007 +"2007-08-15","Asuncion de la Virgen","ES",2007 +"2007-10-12","Dia de la Hispanidad","ES",2007 +"2007-11-01","Todos los Santos","ES",2007 +"2007-12-06","Dia de la Constitucion Espanola","ES",2007 +"2007-12-08","La Inmaculada Concepcion","ES",2007 +"2007-12-25","Navidad","ES",2007 +"2008-01-01","Ano nuevo","ES",2008 +"2008-01-07","Epifania del Senor (Trasladado)","ES",2008 +"2008-03-21","Viernes Santo","ES",2008 +"2008-05-01","Dia del Trabajador","ES",2008 +"2008-08-15","Asuncion de la Virgen","ES",2008 +"2008-10-13","Dia de la Hispanidad (Trasladado)","ES",2008 +"2008-11-01","Todos los Santos","ES",2008 +"2008-12-06","Dia de la Constitucion Espanola","ES",2008 +"2008-12-08","La Inmaculada Concepcion","ES",2008 +"2008-12-25","Navidad","ES",2008 +"2009-01-01","Ano nuevo","ES",2009 +"2009-01-06","Epifania del Senor","ES",2009 +"2009-04-10","Viernes Santo","ES",2009 +"2009-05-01","Dia del Trabajador","ES",2009 +"2009-08-15","Asuncion de la Virgen","ES",2009 +"2009-10-12","Dia de la Hispanidad","ES",2009 +"2009-11-02","Todos los Santos (Trasladado)","ES",2009 +"2009-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",2009 +"2009-12-08","La Inmaculada Concepcion","ES",2009 +"2009-12-25","Navidad","ES",2009 +"2010-01-01","Ano nuevo","ES",2010 +"2010-01-06","Epifania del Senor","ES",2010 +"2010-04-02","Viernes Santo","ES",2010 +"2010-05-01","Dia del Trabajador","ES",2010 +"2010-08-16","Asuncion de la Virgen (Trasladado)","ES",2010 +"2010-10-12","Dia de la Hispanidad","ES",2010 +"2010-11-01","Todos los Santos","ES",2010 +"2010-12-06","Dia de la Constitucion Espanola","ES",2010 +"2010-12-08","La Inmaculada Concepcion","ES",2010 +"2010-12-25","Navidad","ES",2010 +"2011-01-01","Ano nuevo","ES",2011 +"2011-01-06","Epifania del Senor","ES",2011 +"2011-04-22","Viernes Santo","ES",2011 +"2011-05-02","Dia del Trabajador (Trasladado)","ES",2011 +"2011-08-15","Asuncion de la Virgen","ES",2011 +"2011-10-12","Dia de la Hispanidad","ES",2011 +"2011-11-01","Todos los Santos","ES",2011 +"2011-12-06","Dia de la Constitucion Espanola","ES",2011 +"2011-12-08","La Inmaculada Concepcion","ES",2011 +"2011-12-26","Navidad (Trasladado)","ES",2011 +"2012-01-02","Ano nuevo (Trasladado)","ES",2012 +"2012-01-06","Epifania del Senor","ES",2012 +"2012-04-06","Viernes Santo","ES",2012 +"2012-05-01","Dia del Trabajador","ES",2012 +"2012-08-15","Asuncion de la Virgen","ES",2012 +"2012-10-12","Dia de la Hispanidad","ES",2012 +"2012-11-01","Todos los Santos","ES",2012 +"2012-12-06","Dia de la Constitucion Espanola","ES",2012 +"2012-12-08","La Inmaculada Concepcion","ES",2012 +"2012-12-25","Navidad","ES",2012 +"2013-01-01","Ano nuevo","ES",2013 +"2013-01-07","Epifania del Senor (Trasladado)","ES",2013 +"2013-03-29","Viernes Santo","ES",2013 +"2013-05-01","Dia del Trabajador","ES",2013 +"2013-08-15","Asuncion de la Virgen","ES",2013 +"2013-10-12","Dia de la Hispanidad","ES",2013 +"2013-11-01","Todos los Santos","ES",2013 +"2013-12-06","Dia de la Constitucion Espanola","ES",2013 +"2013-12-09","La Inmaculada Concepcion (Trasladado)","ES",2013 +"2013-12-25","Navidad","ES",2013 +"2014-01-01","Ano nuevo","ES",2014 +"2014-01-06","Epifania del Senor","ES",2014 +"2014-04-18","Viernes Santo","ES",2014 +"2014-05-01","Dia del Trabajador","ES",2014 +"2014-08-15","Asuncion de la Virgen","ES",2014 +"2014-10-13","Dia de la Hispanidad (Trasladado)","ES",2014 +"2014-11-01","Todos los Santos","ES",2014 +"2014-12-06","Dia de la Constitucion Espanola","ES",2014 +"2014-12-08","La Inmaculada Concepcion","ES",2014 +"2014-12-25","Navidad","ES",2014 +"2015-01-01","Ano nuevo","ES",2015 +"2015-01-06","Epifania del Senor","ES",2015 +"2015-04-03","Viernes Santo","ES",2015 +"2015-05-01","Dia del Trabajador","ES",2015 +"2015-08-15","Asuncion de la Virgen","ES",2015 +"2015-10-12","Dia de la Hispanidad","ES",2015 +"2015-11-02","Todos los Santos (Trasladado)","ES",2015 +"2015-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",2015 +"2015-12-08","La Inmaculada Concepcion","ES",2015 +"2015-12-25","Navidad","ES",2015 +"2016-01-01","Ano nuevo","ES",2016 +"2016-01-06","Epifania del Senor","ES",2016 +"2016-03-25","Viernes Santo","ES",2016 +"2016-05-02","Dia del Trabajador (Trasladado)","ES",2016 +"2016-08-15","Asuncion de la Virgen","ES",2016 +"2016-10-12","Dia de la Hispanidad","ES",2016 +"2016-11-01","Todos los Santos","ES",2016 +"2016-12-06","Dia de la Constitucion Espanola","ES",2016 +"2016-12-08","La Inmaculada Concepcion","ES",2016 +"2016-12-26","Navidad (Trasladado)","ES",2016 +"2017-01-02","Ano nuevo (Trasladado)","ES",2017 +"2017-01-06","Epifania del Senor","ES",2017 +"2017-04-14","Viernes Santo","ES",2017 +"2017-05-01","Dia del Trabajador","ES",2017 +"2017-08-15","Asuncion de la Virgen","ES",2017 +"2017-10-12","Dia de la Hispanidad","ES",2017 +"2017-11-01","Todos los Santos","ES",2017 +"2017-12-06","Dia de la Constitucion Espanola","ES",2017 +"2017-12-08","La Inmaculada Concepcion","ES",2017 +"2017-12-25","Navidad","ES",2017 +"2018-01-01","Ano nuevo","ES",2018 +"2018-01-06","Epifania del Senor","ES",2018 +"2018-03-30","Viernes Santo","ES",2018 +"2018-05-01","Dia del Trabajador","ES",2018 +"2018-08-15","Asuncion de la Virgen","ES",2018 +"2018-10-12","Dia de la Hispanidad","ES",2018 +"2018-11-01","Todos los Santos","ES",2018 +"2018-12-06","Dia de la Constitucion Espanola","ES",2018 +"2018-12-08","La Inmaculada Concepcion","ES",2018 +"2018-12-25","Navidad","ES",2018 +"2019-01-01","Ano nuevo","ES",2019 +"2019-01-07","Epifania del Senor (Trasladado)","ES",2019 +"2019-04-19","Viernes Santo","ES",2019 +"2019-05-01","Dia del Trabajador","ES",2019 +"2019-08-15","Asuncion de la Virgen","ES",2019 +"2019-10-12","Dia de la Hispanidad","ES",2019 +"2019-11-01","Todos los Santos","ES",2019 +"2019-12-06","Dia de la Constitucion Espanola","ES",2019 +"2019-12-09","La Inmaculada Concepcion (Trasladado)","ES",2019 +"2019-12-25","Navidad","ES",2019 +"2020-01-01","Ano nuevo","ES",2020 +"2020-01-06","Epifania del Senor","ES",2020 +"2020-04-10","Viernes Santo","ES",2020 +"2020-05-01","Dia del Trabajador","ES",2020 +"2020-08-15","Asuncion de la Virgen","ES",2020 +"2020-10-12","Dia de la Hispanidad","ES",2020 +"2020-11-02","Todos los Santos (Trasladado)","ES",2020 +"2020-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",2020 +"2020-12-08","La Inmaculada Concepcion","ES",2020 +"2020-12-25","Navidad","ES",2020 +"2021-01-01","Ano nuevo","ES",2021 +"2021-01-06","Epifania del Senor","ES",2021 +"2021-04-02","Viernes Santo","ES",2021 +"2021-05-01","Dia del Trabajador","ES",2021 +"2021-08-16","Asuncion de la Virgen (Trasladado)","ES",2021 +"2021-10-12","Dia de la Hispanidad","ES",2021 +"2021-11-01","Todos los Santos","ES",2021 +"2021-12-06","Dia de la Constitucion Espanola","ES",2021 +"2021-12-08","La Inmaculada Concepcion","ES",2021 +"2021-12-25","Navidad","ES",2021 +"2022-01-01","Ano nuevo","ES",2022 +"2022-01-06","Epifania del Senor","ES",2022 +"2022-04-15","Viernes Santo","ES",2022 +"2022-08-15","Asuncion de la Virgen","ES",2022 +"2022-10-12","Dia de la Hispanidad","ES",2022 +"2022-11-01","Todos los Santos","ES",2022 +"2022-12-06","Dia de la Constitucion Espanola","ES",2022 +"2022-12-08","La Inmaculada Concepcion","ES",2022 +"2023-01-06","Epifania del Senor","ES",2023 +"2023-04-06","Jueves Santo","ES",2023 +"2023-04-07","Viernes Santo","ES",2023 +"2023-05-01","Dia del Trabajador","ES",2023 +"2023-08-15","Asuncion de la Virgen","ES",2023 +"2023-10-12","Dia de la Hispanidad","ES",2023 +"2023-11-01","Todos los Santos","ES",2023 +"2023-12-06","Dia de la Constitucion Espanola","ES",2023 +"2023-12-08","La Inmaculada Concepcion","ES",2023 +"2023-12-25","Navidad","ES",2023 +"2024-01-01","Ano nuevo","ES",2024 +"2024-01-06","Epifania del Senor","ES",2024 +"2024-03-28","Jueves Santo","ES",2024 +"2024-03-29","Viernes Santo","ES",2024 +"2024-05-01","Dia del Trabajador","ES",2024 +"2024-08-15","Asuncion de la Virgen","ES",2024 +"2024-10-12","Dia de la Hispanidad","ES",2024 +"2024-11-01","Todos los Santos","ES",2024 +"2024-12-06","Dia de la Constitucion Espanola","ES",2024 +"2024-12-09","La Inmaculada Concepcion (Trasladado)","ES",2024 +"2024-12-25","Navidad","ES",2024 +"2025-01-01","Ano nuevo","ES",2025 +"2025-01-06","Epifania del Senor","ES",2025 +"2025-04-17","Jueves Santo","ES",2025 +"2025-04-18","Viernes Santo","ES",2025 +"2025-05-01","Dia del Trabajador","ES",2025 +"2025-08-15","Asuncion de la Virgen","ES",2025 +"2025-10-13","Dia de la Hispanidad (Trasladado)","ES",2025 +"2025-11-01","Todos los Santos","ES",2025 +"2025-12-06","Dia de la Constitucion Espanola","ES",2025 +"2025-12-08","La Inmaculada Concepcion","ES",2025 +"2025-12-25","Navidad","ES",2025 +"2026-01-01","Ano nuevo","ES",2026 +"2026-01-06","Epifania del Senor","ES",2026 +"2026-04-02","Jueves Santo","ES",2026 +"2026-04-03","Viernes Santo","ES",2026 +"2026-05-01","Dia del Trabajador","ES",2026 +"2026-08-15","Asuncion de la Virgen","ES",2026 +"2026-10-12","Dia de la Hispanidad","ES",2026 +"2026-11-02","Todos los Santos (Trasladado)","ES",2026 +"2026-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",2026 +"2026-12-08","La Inmaculada Concepcion","ES",2026 +"2026-12-25","Navidad","ES",2026 +"2027-01-01","Ano nuevo","ES",2027 +"2027-01-06","Epifania del Senor","ES",2027 +"2027-03-25","Jueves Santo","ES",2027 +"2027-03-26","Viernes Santo","ES",2027 +"2027-05-01","Dia del Trabajador","ES",2027 +"2027-08-16","Asuncion de la Virgen (Trasladado)","ES",2027 +"2027-10-12","Dia de la Hispanidad","ES",2027 +"2027-11-01","Todos los Santos","ES",2027 +"2027-12-06","Dia de la Constitucion Espanola","ES",2027 +"2027-12-08","La Inmaculada Concepcion","ES",2027 +"2027-12-25","Navidad","ES",2027 +"2028-01-01","Ano nuevo","ES",2028 +"2028-01-06","Epifania del Senor","ES",2028 +"2028-04-13","Jueves Santo","ES",2028 +"2028-04-14","Viernes Santo","ES",2028 +"2028-05-01","Dia del Trabajador","ES",2028 +"2028-08-15","Asuncion de la Virgen","ES",2028 +"2028-10-12","Dia de la Hispanidad","ES",2028 +"2028-11-01","Todos los Santos","ES",2028 +"2028-12-06","Dia de la Constitucion Espanola","ES",2028 +"2028-12-08","La Inmaculada Concepcion","ES",2028 +"2028-12-25","Navidad","ES",2028 +"2029-01-01","Ano nuevo","ES",2029 +"2029-01-06","Epifania del Senor","ES",2029 +"2029-03-29","Jueves Santo","ES",2029 +"2029-03-30","Viernes Santo","ES",2029 +"2029-05-01","Dia del Trabajador","ES",2029 +"2029-08-15","Asuncion de la Virgen","ES",2029 +"2029-10-12","Dia de la Hispanidad","ES",2029 +"2029-11-01","Todos los Santos","ES",2029 +"2029-12-06","Dia de la Constitucion Espanola","ES",2029 +"2029-12-08","La Inmaculada Concepcion","ES",2029 +"2029-12-25","Navidad","ES",2029 +"2030-01-01","Ano nuevo","ES",2030 +"2030-01-07","Epifania del Senor (Trasladado)","ES",2030 +"2030-04-18","Jueves Santo","ES",2030 +"2030-04-19","Viernes Santo","ES",2030 +"2030-05-01","Dia del Trabajador","ES",2030 +"2030-08-15","Asuncion de la Virgen","ES",2030 +"2030-10-12","Dia de la Hispanidad","ES",2030 +"2030-11-01","Todos los Santos","ES",2030 +"2030-12-06","Dia de la Constitucion Espanola","ES",2030 +"2030-12-09","La Inmaculada Concepcion (Trasladado)","ES",2030 +"2030-12-25","Navidad","ES",2030 +"2031-01-01","Ano nuevo","ES",2031 +"2031-01-06","Epifania del Senor","ES",2031 +"2031-04-10","Jueves Santo","ES",2031 +"2031-04-11","Viernes Santo","ES",2031 +"2031-05-01","Dia del Trabajador","ES",2031 +"2031-08-15","Asuncion de la Virgen","ES",2031 +"2031-10-13","Dia de la Hispanidad (Trasladado)","ES",2031 +"2031-11-01","Todos los Santos","ES",2031 +"2031-12-06","Dia de la Constitucion Espanola","ES",2031 +"2031-12-08","La Inmaculada Concepcion","ES",2031 +"2031-12-25","Navidad","ES",2031 +"2032-01-01","Ano nuevo","ES",2032 +"2032-01-06","Epifania del Senor","ES",2032 +"2032-03-25","Jueves Santo","ES",2032 +"2032-03-26","Viernes Santo","ES",2032 +"2032-05-01","Dia del Trabajador","ES",2032 +"2032-08-16","Asuncion de la Virgen (Trasladado)","ES",2032 +"2032-10-12","Dia de la Hispanidad","ES",2032 +"2032-11-01","Todos los Santos","ES",2032 +"2032-12-06","Dia de la Constitucion Espanola","ES",2032 +"2032-12-08","La Inmaculada Concepcion","ES",2032 +"2032-12-25","Navidad","ES",2032 +"2033-01-01","Ano nuevo","ES",2033 +"2033-01-06","Epifania del Senor","ES",2033 +"2033-04-14","Jueves Santo","ES",2033 +"2033-04-15","Viernes Santo","ES",2033 +"2033-05-02","Dia del Trabajador (Trasladado)","ES",2033 +"2033-08-15","Asuncion de la Virgen","ES",2033 +"2033-10-12","Dia de la Hispanidad","ES",2033 +"2033-11-01","Todos los Santos","ES",2033 +"2033-12-06","Dia de la Constitucion Espanola","ES",2033 +"2033-12-08","La Inmaculada Concepcion","ES",2033 +"2033-12-26","Navidad (Trasladado)","ES",2033 +"2034-01-02","Ano nuevo (Trasladado)","ES",2034 +"2034-01-06","Epifania del Senor","ES",2034 +"2034-04-06","Jueves Santo","ES",2034 +"2034-04-07","Viernes Santo","ES",2034 +"2034-05-01","Dia del Trabajador","ES",2034 +"2034-08-15","Asuncion de la Virgen","ES",2034 +"2034-10-12","Dia de la Hispanidad","ES",2034 +"2034-11-01","Todos los Santos","ES",2034 +"2034-12-06","Dia de la Constitucion Espanola","ES",2034 +"2034-12-08","La Inmaculada Concepcion","ES",2034 +"2034-12-25","Navidad","ES",2034 +"2035-01-01","Ano nuevo","ES",2035 +"2035-01-06","Epifania del Senor","ES",2035 +"2035-03-22","Jueves Santo","ES",2035 +"2035-03-23","Viernes Santo","ES",2035 +"2035-05-01","Dia del Trabajador","ES",2035 +"2035-08-15","Asuncion de la Virgen","ES",2035 +"2035-10-12","Dia de la Hispanidad","ES",2035 +"2035-11-01","Todos los Santos","ES",2035 +"2035-12-06","Dia de la Constitucion Espanola","ES",2035 +"2035-12-08","La Inmaculada Concepcion","ES",2035 +"2035-12-25","Navidad","ES",2035 +"2036-01-01","Ano nuevo","ES",2036 +"2036-01-07","Epifania del Senor (Trasladado)","ES",2036 +"2036-04-10","Jueves Santo","ES",2036 +"2036-04-11","Viernes Santo","ES",2036 +"2036-05-01","Dia del Trabajador","ES",2036 +"2036-08-15","Asuncion de la Virgen","ES",2036 +"2036-10-13","Dia de la Hispanidad (Trasladado)","ES",2036 +"2036-11-01","Todos los Santos","ES",2036 +"2036-12-06","Dia de la Constitucion Espanola","ES",2036 +"2036-12-08","La Inmaculada Concepcion","ES",2036 +"2036-12-25","Navidad","ES",2036 +"2037-01-01","Ano nuevo","ES",2037 +"2037-01-06","Epifania del Senor","ES",2037 +"2037-04-02","Jueves Santo","ES",2037 +"2037-04-03","Viernes Santo","ES",2037 +"2037-05-01","Dia del Trabajador","ES",2037 +"2037-08-15","Asuncion de la Virgen","ES",2037 +"2037-10-12","Dia de la Hispanidad","ES",2037 +"2037-11-02","Todos los Santos (Trasladado)","ES",2037 +"2037-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",2037 +"2037-12-08","La Inmaculada Concepcion","ES",2037 +"2037-12-25","Navidad","ES",2037 +"2038-01-01","Ano nuevo","ES",2038 +"2038-01-06","Epifania del Senor","ES",2038 +"2038-04-22","Jueves Santo","ES",2038 +"2038-04-23","Viernes Santo","ES",2038 +"2038-05-01","Dia del Trabajador","ES",2038 +"2038-08-16","Asuncion de la Virgen (Trasladado)","ES",2038 +"2038-10-12","Dia de la Hispanidad","ES",2038 +"2038-11-01","Todos los Santos","ES",2038 +"2038-12-06","Dia de la Constitucion Espanola","ES",2038 +"2038-12-08","La Inmaculada Concepcion","ES",2038 +"2038-12-25","Navidad","ES",2038 +"2039-01-01","Ano nuevo","ES",2039 +"2039-01-06","Epifania del Senor","ES",2039 +"2039-04-07","Jueves Santo","ES",2039 +"2039-04-08","Viernes Santo","ES",2039 +"2039-05-02","Dia del Trabajador (Trasladado)","ES",2039 +"2039-08-15","Asuncion de la Virgen","ES",2039 +"2039-10-12","Dia de la Hispanidad","ES",2039 +"2039-11-01","Todos los Santos","ES",2039 +"2039-12-06","Dia de la Constitucion Espanola","ES",2039 +"2039-12-08","La Inmaculada Concepcion","ES",2039 +"2039-12-26","Navidad (Trasladado)","ES",2039 +"2040-01-02","Ano nuevo (Trasladado)","ES",2040 +"2040-01-06","Epifania del Senor","ES",2040 +"2040-03-29","Jueves Santo","ES",2040 +"2040-03-30","Viernes Santo","ES",2040 +"2040-05-01","Dia del Trabajador","ES",2040 +"2040-08-15","Asuncion de la Virgen","ES",2040 +"2040-10-12","Dia de la Hispanidad","ES",2040 +"2040-11-01","Todos los Santos","ES",2040 +"2040-12-06","Dia de la Constitucion Espanola","ES",2040 +"2040-12-08","La Inmaculada Concepcion","ES",2040 +"2040-12-25","Navidad","ES",2040 +"2041-01-01","Ano nuevo","ES",2041 +"2041-01-07","Epifania del Senor (Trasladado)","ES",2041 +"2041-04-18","Jueves Santo","ES",2041 +"2041-04-19","Viernes Santo","ES",2041 +"2041-05-01","Dia del Trabajador","ES",2041 +"2041-08-15","Asuncion de la Virgen","ES",2041 +"2041-10-12","Dia de la Hispanidad","ES",2041 +"2041-11-01","Todos los Santos","ES",2041 +"2041-12-06","Dia de la Constitucion Espanola","ES",2041 +"2041-12-09","La Inmaculada Concepcion (Trasladado)","ES",2041 +"2041-12-25","Navidad","ES",2041 +"2042-01-01","Ano nuevo","ES",2042 +"2042-01-06","Epifania del Senor","ES",2042 +"2042-04-03","Jueves Santo","ES",2042 +"2042-04-04","Viernes Santo","ES",2042 +"2042-05-01","Dia del Trabajador","ES",2042 +"2042-08-15","Asuncion de la Virgen","ES",2042 +"2042-10-13","Dia de la Hispanidad (Trasladado)","ES",2042 +"2042-11-01","Todos los Santos","ES",2042 +"2042-12-06","Dia de la Constitucion Espanola","ES",2042 +"2042-12-08","La Inmaculada Concepcion","ES",2042 +"2042-12-25","Navidad","ES",2042 +"2043-01-01","Ano nuevo","ES",2043 +"2043-01-06","Epifania del Senor","ES",2043 +"2043-03-26","Jueves Santo","ES",2043 +"2043-03-27","Viernes Santo","ES",2043 +"2043-05-01","Dia del Trabajador","ES",2043 +"2043-08-15","Asuncion de la Virgen","ES",2043 +"2043-10-12","Dia de la Hispanidad","ES",2043 +"2043-11-02","Todos los Santos (Trasladado)","ES",2043 +"2043-12-07","Dia de la Constitucion Espanola (Trasladado)","ES",2043 +"2043-12-08","La Inmaculada Concepcion","ES",2043 +"2043-12-25","Navidad","ES",2043 +"2044-01-01","Ano nuevo","ES",2044 +"2044-01-06","Epifania del Senor","ES",2044 +"2044-04-14","Jueves Santo","ES",2044 +"2044-04-15","Viernes Santo","ES",2044 +"2044-05-02","Dia del Trabajador (Trasladado)","ES",2044 +"2044-08-15","Asuncion de la Virgen","ES",2044 +"2044-10-12","Dia de la Hispanidad","ES",2044 +"2044-11-01","Todos los Santos","ES",2044 +"2044-12-06","Dia de la Constitucion Espanola","ES",2044 +"2044-12-08","La Inmaculada Concepcion","ES",2044 +"2044-12-26","Navidad (Trasladado)","ES",2044 +"1995-01-07","Orthodox Christmas Day","ET",1995 +"1995-01-19","Orthodox Epiphany Day","ET",1995 +"1995-03-02","Adwa Victory Day","ET",1995 +"1995-03-02","* (*estimated)","ET",1995 +"1995-04-21","Orthodox Good Friday","ET",1995 +"1995-04-23","Orthodox Easter Sunday","ET",1995 +"1995-05-01","Labor Day","ET",1995 +"1995-05-05","Patriots Day","ET",1995 +"1995-05-09","* (*estimated)","ET",1995 +"1995-05-10","* (*estimated)","ET",1995 +"1995-05-28","Downfall of Dergue Regime Day","ET",1995 +"1995-08-08","* (*estimated)","ET",1995 +"1995-08-09","* (*estimated)","ET",1995 +"1995-09-12","Ethiopian New Year's Day","ET",1995 +"1995-09-28","Finding of True Cross","ET",1995 +"1996-01-07","Orthodox Christmas Day","ET",1996 +"1996-01-19","Orthodox Epiphany Day","ET",1996 +"1996-02-19","* (*estimated)","ET",1996 +"1996-03-02","Adwa Victory Day","ET",1996 +"1996-04-12","Orthodox Good Friday","ET",1996 +"1996-04-14","Orthodox Easter Sunday","ET",1996 +"1996-04-27","* (*estimated)","ET",1996 +"1996-04-28","* (*estimated)","ET",1996 +"1996-05-01","Labor Day","ET",1996 +"1996-05-05","Patriots Day","ET",1996 +"1996-05-28","Downfall of Dergue Regime Day","ET",1996 +"1996-07-27","* (*estimated)","ET",1996 +"1996-07-28","* (*estimated)","ET",1996 +"1996-09-11","Ethiopian New Year's Day","ET",1996 +"1996-09-27","Finding of True Cross","ET",1996 +"1997-01-07","Orthodox Christmas Day","ET",1997 +"1997-01-19","Orthodox Epiphany Day","ET",1997 +"1997-02-08","* (*estimated)","ET",1997 +"1997-03-02","Adwa Victory Day","ET",1997 +"1997-04-17","* (*estimated)","ET",1997 +"1997-04-18","* (*estimated)","ET",1997 +"1997-04-25","Orthodox Good Friday","ET",1997 +"1997-04-27","Orthodox Easter Sunday","ET",1997 +"1997-05-01","Labor Day","ET",1997 +"1997-05-05","Patriots Day","ET",1997 +"1997-05-28","Downfall of Dergue Regime Day","ET",1997 +"1997-07-16","* (*estimated)","ET",1997 +"1997-07-17","* (*estimated)","ET",1997 +"1997-09-11","Ethiopian New Year's Day","ET",1997 +"1997-09-27","Finding of True Cross","ET",1997 +"1998-01-07","Orthodox Christmas Day","ET",1998 +"1998-01-19","Orthodox Epiphany Day","ET",1998 +"1998-01-29","* (*estimated)","ET",1998 +"1998-03-02","Adwa Victory Day","ET",1998 +"1998-04-07","* (*estimated)","ET",1998 +"1998-04-08","* (*estimated)","ET",1998 +"1998-04-17","Orthodox Good Friday","ET",1998 +"1998-04-19","Orthodox Easter Sunday","ET",1998 +"1998-05-01","Labor Day","ET",1998 +"1998-05-05","Patriots Day","ET",1998 +"1998-05-28","Downfall of Dergue Regime Day","ET",1998 +"1998-07-06","* (*estimated)","ET",1998 +"1998-07-07","* (*estimated)","ET",1998 +"1998-09-11","Ethiopian New Year's Day","ET",1998 +"1998-09-27","Finding of True Cross","ET",1998 +"1999-01-07","Orthodox Christmas Day","ET",1999 +"1999-01-18","* (*estimated)","ET",1999 +"1999-01-19","Orthodox Epiphany Day","ET",1999 +"1999-03-02","Adwa Victory Day","ET",1999 +"1999-03-27","* (*estimated)","ET",1999 +"1999-03-28","* (*estimated)","ET",1999 +"1999-04-09","Orthodox Good Friday","ET",1999 +"1999-04-11","Orthodox Easter Sunday","ET",1999 +"1999-05-01","Labor Day","ET",1999 +"1999-05-05","Patriots Day","ET",1999 +"1999-05-28","Downfall of Dergue Regime Day","ET",1999 +"1999-06-26","* (*estimated)","ET",1999 +"1999-06-27","* (*estimated)","ET",1999 +"1999-09-12","Ethiopian New Year's Day","ET",1999 +"1999-09-28","Finding of True Cross","ET",1999 +"2000-01-07","Orthodox Christmas Day","ET",2000 +"2000-01-08","* (*estimated)","ET",2000 +"2000-01-19","Orthodox Epiphany Day","ET",2000 +"2000-03-02","Adwa Victory Day","ET",2000 +"2000-03-16","* (*estimated)","ET",2000 +"2000-03-17","* (*estimated)","ET",2000 +"2000-04-28","Orthodox Good Friday","ET",2000 +"2000-04-30","Orthodox Easter Sunday","ET",2000 +"2000-05-01","Labor Day","ET",2000 +"2000-05-05","Patriots Day","ET",2000 +"2000-05-28","Downfall of Dergue Regime Day","ET",2000 +"2000-06-14","* (*estimated)","ET",2000 +"2000-06-15","* (*estimated)","ET",2000 +"2000-09-11","Ethiopian New Year's Day","ET",2000 +"2000-09-27","Finding of True Cross","ET",2000 +"2000-12-27","* (*estimated)","ET",2000 +"2001-01-07","Orthodox Christmas Day","ET",2001 +"2001-01-19","Orthodox Epiphany Day","ET",2001 +"2001-03-02","Adwa Victory Day","ET",2001 +"2001-03-05","* (*estimated)","ET",2001 +"2001-03-06","* (*estimated)","ET",2001 +"2001-04-13","Orthodox Good Friday","ET",2001 +"2001-04-15","Orthodox Easter Sunday","ET",2001 +"2001-05-01","Labor Day","ET",2001 +"2001-05-05","Patriots Day","ET",2001 +"2001-05-28","Downfall of Dergue Regime Day","ET",2001 +"2001-06-04","* (*estimated)","ET",2001 +"2001-06-05","* (*estimated)","ET",2001 +"2001-09-11","Ethiopian New Year's Day","ET",2001 +"2001-09-27","Finding of True Cross","ET",2001 +"2001-12-16","* (*estimated)","ET",2001 +"2002-01-07","Orthodox Christmas Day","ET",2002 +"2002-01-19","Orthodox Epiphany Day","ET",2002 +"2002-02-22","* (*estimated)","ET",2002 +"2002-02-23","* (*estimated)","ET",2002 +"2002-03-02","Adwa Victory Day","ET",2002 +"2002-05-01","Labor Day","ET",2002 +"2002-05-03","Orthodox Good Friday","ET",2002 +"2002-05-05","Orthodox Easter Sunday","ET",2002 +"2002-05-05","Patriots Day","ET",2002 +"2002-05-24","* (*estimated)","ET",2002 +"2002-05-25","* (*estimated)","ET",2002 +"2002-05-28","Downfall of Dergue Regime Day","ET",2002 +"2002-09-11","Ethiopian New Year's Day","ET",2002 +"2002-09-27","Finding of True Cross","ET",2002 +"2002-12-05","* (*estimated)","ET",2002 +"2003-01-07","Orthodox Christmas Day","ET",2003 +"2003-01-19","Orthodox Epiphany Day","ET",2003 +"2003-02-11","* (*estimated)","ET",2003 +"2003-02-12","* (*estimated)","ET",2003 +"2003-03-02","Adwa Victory Day","ET",2003 +"2003-04-25","Orthodox Good Friday","ET",2003 +"2003-04-27","Orthodox Easter Sunday","ET",2003 +"2003-05-01","Labor Day","ET",2003 +"2003-05-05","Patriots Day","ET",2003 +"2003-05-13","* (*estimated)","ET",2003 +"2003-05-14","* (*estimated)","ET",2003 +"2003-05-28","Downfall of Dergue Regime Day","ET",2003 +"2003-09-12","Ethiopian New Year's Day","ET",2003 +"2003-09-28","Finding of True Cross","ET",2003 +"2003-11-25","* (*estimated)","ET",2003 +"2004-01-07","Orthodox Christmas Day","ET",2004 +"2004-01-19","Orthodox Epiphany Day","ET",2004 +"2004-02-01","* (*estimated)","ET",2004 +"2004-02-02","* (*estimated)","ET",2004 +"2004-03-02","Adwa Victory Day","ET",2004 +"2004-04-09","Orthodox Good Friday","ET",2004 +"2004-04-11","Orthodox Easter Sunday","ET",2004 +"2004-05-01","Labor Day","ET",2004 +"2004-05-01","* (*estimated)","ET",2004 +"2004-05-02","* (*estimated)","ET",2004 +"2004-05-05","Patriots Day","ET",2004 +"2004-05-28","Downfall of Dergue Regime Day","ET",2004 +"2004-09-11","Ethiopian New Year's Day","ET",2004 +"2004-09-27","Finding of True Cross","ET",2004 +"2004-11-14","* (*estimated)","ET",2004 +"2005-01-07","Orthodox Christmas Day","ET",2005 +"2005-01-19","Orthodox Epiphany Day","ET",2005 +"2005-01-21","* (*estimated)","ET",2005 +"2005-01-22","* (*estimated)","ET",2005 +"2005-03-02","Adwa Victory Day","ET",2005 +"2005-04-21","* (*estimated)","ET",2005 +"2005-04-22","* (*estimated)","ET",2005 +"2005-04-29","Orthodox Good Friday","ET",2005 +"2005-05-01","Labor Day","ET",2005 +"2005-05-01","Orthodox Easter Sunday","ET",2005 +"2005-05-05","Patriots Day","ET",2005 +"2005-05-28","Downfall of Dergue Regime Day","ET",2005 +"2005-09-11","Ethiopian New Year's Day","ET",2005 +"2005-09-27","Finding of True Cross","ET",2005 +"2005-11-03","* (*estimated)","ET",2005 +"2006-01-07","Orthodox Christmas Day","ET",2006 +"2006-01-10","* (*estimated)","ET",2006 +"2006-01-11","* (*estimated)","ET",2006 +"2006-01-19","Orthodox Epiphany Day","ET",2006 +"2006-03-02","Adwa Victory Day","ET",2006 +"2006-04-10","* (*estimated)","ET",2006 +"2006-04-11","* (*estimated)","ET",2006 +"2006-04-21","Orthodox Good Friday","ET",2006 +"2006-04-23","Orthodox Easter Sunday","ET",2006 +"2006-05-01","Labor Day","ET",2006 +"2006-05-05","Patriots Day","ET",2006 +"2006-05-28","Downfall of Dergue Regime Day","ET",2006 +"2006-09-11","Ethiopian New Year's Day","ET",2006 +"2006-09-27","Finding of True Cross","ET",2006 +"2006-10-23","* (*estimated)","ET",2006 +"2006-12-31","* (*estimated)","ET",2006 +"2007-01-01","* (*estimated)","ET",2007 +"2007-01-07","Orthodox Christmas Day","ET",2007 +"2007-01-19","Orthodox Epiphany Day","ET",2007 +"2007-03-02","Adwa Victory Day","ET",2007 +"2007-03-31","* (*estimated)","ET",2007 +"2007-04-01","* (*estimated)","ET",2007 +"2007-04-06","Orthodox Good Friday","ET",2007 +"2007-04-08","Orthodox Easter Sunday","ET",2007 +"2007-05-01","Labor Day","ET",2007 +"2007-05-05","Patriots Day","ET",2007 +"2007-05-28","Downfall of Dergue Regime Day","ET",2007 +"2007-09-12","Ethiopian New Year's Day","ET",2007 +"2007-09-28","Finding of True Cross","ET",2007 +"2007-10-13","* (*estimated)","ET",2007 +"2007-12-20","* (*estimated)","ET",2007 +"2007-12-21","* (*estimated)","ET",2007 +"2008-01-07","Orthodox Christmas Day","ET",2008 +"2008-01-19","Orthodox Epiphany Day","ET",2008 +"2008-03-02","Adwa Victory Day","ET",2008 +"2008-03-20","* (*estimated)","ET",2008 +"2008-03-21","* (*estimated)","ET",2008 +"2008-04-25","Orthodox Good Friday","ET",2008 +"2008-04-27","Orthodox Easter Sunday","ET",2008 +"2008-05-01","Labor Day","ET",2008 +"2008-05-05","Patriots Day","ET",2008 +"2008-05-28","Downfall of Dergue Regime Day","ET",2008 +"2008-09-11","Ethiopian New Year's Day","ET",2008 +"2008-09-27","Finding of True Cross","ET",2008 +"2008-10-01","* (*estimated)","ET",2008 +"2008-12-08","* (*estimated)","ET",2008 +"2008-12-09","* (*estimated)","ET",2008 +"2009-01-07","Orthodox Christmas Day","ET",2009 +"2009-01-19","Orthodox Epiphany Day","ET",2009 +"2009-03-02","Adwa Victory Day","ET",2009 +"2009-03-09","* (*estimated)","ET",2009 +"2009-03-10","* (*estimated)","ET",2009 +"2009-04-17","Orthodox Good Friday","ET",2009 +"2009-04-19","Orthodox Easter Sunday","ET",2009 +"2009-05-01","Labor Day","ET",2009 +"2009-05-05","Patriots Day","ET",2009 +"2009-05-28","Downfall of Dergue Regime Day","ET",2009 +"2009-09-11","Ethiopian New Year's Day","ET",2009 +"2009-09-20","* (*estimated)","ET",2009 +"2009-09-27","Finding of True Cross","ET",2009 +"2009-11-27","* (*estimated)","ET",2009 +"2009-11-28","* (*estimated)","ET",2009 +"2010-01-07","Orthodox Christmas Day","ET",2010 +"2010-01-19","Orthodox Epiphany Day","ET",2010 +"2010-02-26","* (*estimated)","ET",2010 +"2010-02-27","* (*estimated)","ET",2010 +"2010-03-02","Adwa Victory Day","ET",2010 +"2010-04-02","Orthodox Good Friday","ET",2010 +"2010-04-04","Orthodox Easter Sunday","ET",2010 +"2010-05-01","Labor Day","ET",2010 +"2010-05-05","Patriots Day","ET",2010 +"2010-05-28","Downfall of Dergue Regime Day","ET",2010 +"2010-09-10","* (*estimated)","ET",2010 +"2010-09-11","Ethiopian New Year's Day","ET",2010 +"2010-09-27","Finding of True Cross","ET",2010 +"2010-11-16","* (*estimated)","ET",2010 +"2010-11-17","* (*estimated)","ET",2010 +"2011-01-07","Orthodox Christmas Day","ET",2011 +"2011-01-19","Orthodox Epiphany Day","ET",2011 +"2011-02-15","* (*estimated)","ET",2011 +"2011-02-16","* (*estimated)","ET",2011 +"2011-03-02","Adwa Victory Day","ET",2011 +"2011-04-22","Orthodox Good Friday","ET",2011 +"2011-04-24","Orthodox Easter Sunday","ET",2011 +"2011-05-01","Labor Day","ET",2011 +"2011-05-05","Patriots Day","ET",2011 +"2011-05-28","Downfall of Dergue Regime Day","ET",2011 +"2011-08-30","* (*estimated)","ET",2011 +"2011-09-12","Ethiopian New Year's Day","ET",2011 +"2011-09-28","Finding of True Cross","ET",2011 +"2011-11-06","* (*estimated)","ET",2011 +"2011-11-07","* (*estimated)","ET",2011 +"2012-01-07","Orthodox Christmas Day","ET",2012 +"2012-01-19","Orthodox Epiphany Day","ET",2012 +"2012-02-04","* (*estimated)","ET",2012 +"2012-02-05","* (*estimated)","ET",2012 +"2012-03-02","Adwa Victory Day","ET",2012 +"2012-04-13","Orthodox Good Friday","ET",2012 +"2012-04-15","Orthodox Easter Sunday","ET",2012 +"2012-05-01","Labor Day","ET",2012 +"2012-05-05","Patriots Day","ET",2012 +"2012-05-28","Downfall of Dergue Regime Day","ET",2012 +"2012-08-19","* (*estimated)","ET",2012 +"2012-09-11","Ethiopian New Year's Day","ET",2012 +"2012-09-27","Finding of True Cross","ET",2012 +"2012-10-26","* (*estimated)","ET",2012 +"2012-10-27","* (*estimated)","ET",2012 +"2013-01-07","Orthodox Christmas Day","ET",2013 +"2013-01-19","Orthodox Epiphany Day","ET",2013 +"2013-01-24","* (*estimated)","ET",2013 +"2013-01-25","* (*estimated)","ET",2013 +"2013-03-02","Adwa Victory Day","ET",2013 +"2013-05-01","Labor Day","ET",2013 +"2013-05-03","Orthodox Good Friday","ET",2013 +"2013-05-05","Orthodox Easter Sunday","ET",2013 +"2013-05-05","Patriots Day","ET",2013 +"2013-05-28","Downfall of Dergue Regime Day","ET",2013 +"2013-08-08","* (*estimated)","ET",2013 +"2013-09-11","Ethiopian New Year's Day","ET",2013 +"2013-09-27","Finding of True Cross","ET",2013 +"2013-10-15","* (*estimated)","ET",2013 +"2013-10-16","* (*estimated)","ET",2013 +"2014-01-07","Orthodox Christmas Day","ET",2014 +"2014-01-13","* (*estimated)","ET",2014 +"2014-01-14","* (*estimated)","ET",2014 +"2014-01-19","Orthodox Epiphany Day","ET",2014 +"2014-03-02","Adwa Victory Day","ET",2014 +"2014-04-18","Orthodox Good Friday","ET",2014 +"2014-04-20","Orthodox Easter Sunday","ET",2014 +"2014-05-01","Labor Day","ET",2014 +"2014-05-05","Patriots Day","ET",2014 +"2014-05-28","Downfall of Dergue Regime Day","ET",2014 +"2014-07-28","* (*estimated)","ET",2014 +"2014-09-11","Ethiopian New Year's Day","ET",2014 +"2014-09-27","Finding of True Cross","ET",2014 +"2014-10-04","* (*estimated)","ET",2014 +"2014-10-05","* (*estimated)","ET",2014 +"2015-01-03","* (*estimated)","ET",2015 +"2015-01-04","* (*estimated)","ET",2015 +"2015-01-07","Orthodox Christmas Day","ET",2015 +"2015-01-19","Orthodox Epiphany Day","ET",2015 +"2015-03-02","Adwa Victory Day","ET",2015 +"2015-04-10","Orthodox Good Friday","ET",2015 +"2015-04-12","Orthodox Easter Sunday","ET",2015 +"2015-05-01","Labor Day","ET",2015 +"2015-05-05","Patriots Day","ET",2015 +"2015-05-28","Downfall of Dergue Regime Day","ET",2015 +"2015-07-17","* (*estimated)","ET",2015 +"2015-09-12","Ethiopian New Year's Day","ET",2015 +"2015-09-23","* (*estimated)","ET",2015 +"2015-09-24","* (*estimated)","ET",2015 +"2015-09-28","Finding of True Cross","ET",2015 +"2015-12-23","* (*estimated)","ET",2015 +"2015-12-24","* (*estimated)","ET",2015 +"2016-01-07","Orthodox Christmas Day","ET",2016 +"2016-01-19","Orthodox Epiphany Day","ET",2016 +"2016-03-02","Adwa Victory Day","ET",2016 +"2016-04-29","Orthodox Good Friday","ET",2016 +"2016-05-01","Labor Day","ET",2016 +"2016-05-01","Orthodox Easter Sunday","ET",2016 +"2016-05-05","Patriots Day","ET",2016 +"2016-05-28","Downfall of Dergue Regime Day","ET",2016 +"2016-07-06","* (*estimated)","ET",2016 +"2016-09-11","Ethiopian New Year's Day","ET",2016 +"2016-09-11","* (*estimated)","ET",2016 +"2016-09-12","* (*estimated)","ET",2016 +"2016-09-27","Finding of True Cross","ET",2016 +"2016-12-11","* (*estimated)","ET",2016 +"2016-12-12","* (*estimated)","ET",2016 +"2017-01-07","Orthodox Christmas Day","ET",2017 +"2017-01-19","Orthodox Epiphany Day","ET",2017 +"2017-03-02","Adwa Victory Day","ET",2017 +"2017-04-14","Orthodox Good Friday","ET",2017 +"2017-04-16","Orthodox Easter Sunday","ET",2017 +"2017-05-01","Labor Day","ET",2017 +"2017-05-05","Patriots Day","ET",2017 +"2017-05-28","Downfall of Dergue Regime Day","ET",2017 +"2017-06-25","* (*estimated)","ET",2017 +"2017-09-01","* (*estimated)","ET",2017 +"2017-09-02","* (*estimated)","ET",2017 +"2017-09-11","Ethiopian New Year's Day","ET",2017 +"2017-09-27","Finding of True Cross","ET",2017 +"2017-11-30","* (*estimated)","ET",2017 +"2017-12-01","* (*estimated)","ET",2017 +"2018-01-07","Orthodox Christmas Day","ET",2018 +"2018-01-19","Orthodox Epiphany Day","ET",2018 +"2018-03-02","Adwa Victory Day","ET",2018 +"2018-04-06","Orthodox Good Friday","ET",2018 +"2018-04-08","Orthodox Easter Sunday","ET",2018 +"2018-05-01","Labor Day","ET",2018 +"2018-05-05","Patriots Day","ET",2018 +"2018-05-28","Downfall of Dergue Regime Day","ET",2018 +"2018-06-15","* (*estimated)","ET",2018 +"2018-08-21","* (*estimated)","ET",2018 +"2018-08-22","* (*estimated)","ET",2018 +"2018-09-11","Ethiopian New Year's Day","ET",2018 +"2018-09-27","Finding of True Cross","ET",2018 +"2018-11-20","* (*estimated)","ET",2018 +"2018-11-21","* (*estimated)","ET",2018 +"2019-01-07","Orthodox Christmas Day","ET",2019 +"2019-01-19","Orthodox Epiphany Day","ET",2019 +"2019-03-02","Adwa Victory Day","ET",2019 +"2019-04-26","Orthodox Good Friday","ET",2019 +"2019-04-28","Orthodox Easter Sunday","ET",2019 +"2019-05-01","Labor Day","ET",2019 +"2019-05-05","Patriots Day","ET",2019 +"2019-05-28","Downfall of Dergue Regime Day","ET",2019 +"2019-06-04","* (*estimated)","ET",2019 +"2019-08-11","* (*estimated)","ET",2019 +"2019-08-12","* (*estimated)","ET",2019 +"2019-09-12","Ethiopian New Year's Day","ET",2019 +"2019-09-28","Finding of True Cross","ET",2019 +"2019-11-09","* (*estimated)","ET",2019 +"2019-11-10","* (*estimated)","ET",2019 +"2020-01-07","Orthodox Christmas Day","ET",2020 +"2020-01-19","Orthodox Epiphany Day","ET",2020 +"2020-03-02","Adwa Victory Day","ET",2020 +"2020-04-17","Orthodox Good Friday","ET",2020 +"2020-04-19","Orthodox Easter Sunday","ET",2020 +"2020-05-01","Labor Day","ET",2020 +"2020-05-05","Patriots Day","ET",2020 +"2020-05-24","* (*estimated)","ET",2020 +"2020-05-28","Downfall of Dergue Regime Day","ET",2020 +"2020-07-31","* (*estimated)","ET",2020 +"2020-08-01","* (*estimated)","ET",2020 +"2020-09-11","Ethiopian New Year's Day","ET",2020 +"2020-09-27","Finding of True Cross","ET",2020 +"2020-10-29","* (*estimated)","ET",2020 +"2020-10-30","* (*estimated)","ET",2020 +"2021-01-07","Orthodox Christmas Day","ET",2021 +"2021-01-19","Orthodox Epiphany Day","ET",2021 +"2021-03-02","Adwa Victory Day","ET",2021 +"2021-04-30","Orthodox Good Friday","ET",2021 +"2021-05-01","Labor Day","ET",2021 +"2021-05-02","Orthodox Easter Sunday","ET",2021 +"2021-05-05","Patriots Day","ET",2021 +"2021-05-13","* (*estimated)","ET",2021 +"2021-05-28","Downfall of Dergue Regime Day","ET",2021 +"2021-07-20","* (*estimated)","ET",2021 +"2021-07-21","* (*estimated)","ET",2021 +"2021-09-11","Ethiopian New Year's Day","ET",2021 +"2021-09-27","Finding of True Cross","ET",2021 +"2021-10-18","* (*estimated)","ET",2021 +"2021-10-19","* (*estimated)","ET",2021 +"2022-01-07","Orthodox Christmas Day","ET",2022 +"2022-01-19","Orthodox Epiphany Day","ET",2022 +"2022-03-02","Adwa Victory Day","ET",2022 +"2022-04-22","Orthodox Good Friday","ET",2022 +"2022-04-24","Orthodox Easter Sunday","ET",2022 +"2022-05-01","Labor Day","ET",2022 +"2022-05-02","* (*estimated)","ET",2022 +"2022-05-05","Patriots Day","ET",2022 +"2022-05-28","Downfall of Dergue Regime Day","ET",2022 +"2022-07-09","* (*estimated)","ET",2022 +"2022-07-10","* (*estimated)","ET",2022 +"2022-09-11","Ethiopian New Year's Day","ET",2022 +"2022-09-27","Finding of True Cross","ET",2022 +"2022-10-08","* (*estimated)","ET",2022 +"2022-10-09","* (*estimated)","ET",2022 +"2023-01-07","Orthodox Christmas Day","ET",2023 +"2023-01-19","Orthodox Epiphany Day","ET",2023 +"2023-03-02","Adwa Victory Day","ET",2023 +"2023-04-14","Orthodox Good Friday","ET",2023 +"2023-04-16","Orthodox Easter Sunday","ET",2023 +"2023-04-21","* (*estimated)","ET",2023 +"2023-05-01","Labor Day","ET",2023 +"2023-05-05","Patriots Day","ET",2023 +"2023-05-28","Downfall of Dergue Regime Day","ET",2023 +"2023-06-28","* (*estimated)","ET",2023 +"2023-06-29","* (*estimated)","ET",2023 +"2023-09-12","Ethiopian New Year's Day","ET",2023 +"2023-09-27","* (*estimated)","ET",2023 +"2023-09-28","Finding of True Cross","ET",2023 +"2023-09-28","* (*estimated)","ET",2023 +"2024-01-07","Orthodox Christmas Day","ET",2024 +"2024-01-19","Orthodox Epiphany Day","ET",2024 +"2024-03-02","Adwa Victory Day","ET",2024 +"2024-04-10","* (*estimated)","ET",2024 +"2024-05-01","Labor Day","ET",2024 +"2024-05-03","Orthodox Good Friday","ET",2024 +"2024-05-05","Orthodox Easter Sunday","ET",2024 +"2024-05-05","Patriots Day","ET",2024 +"2024-05-28","Downfall of Dergue Regime Day","ET",2024 +"2024-06-16","* (*estimated)","ET",2024 +"2024-06-17","* (*estimated)","ET",2024 +"2024-09-11","Ethiopian New Year's Day","ET",2024 +"2024-09-15","* (*estimated)","ET",2024 +"2024-09-16","* (*estimated)","ET",2024 +"2024-09-27","Finding of True Cross","ET",2024 +"2025-01-07","Orthodox Christmas Day","ET",2025 +"2025-01-19","Orthodox Epiphany Day","ET",2025 +"2025-03-02","Adwa Victory Day","ET",2025 +"2025-03-30","* (*estimated)","ET",2025 +"2025-04-18","Orthodox Good Friday","ET",2025 +"2025-04-20","Orthodox Easter Sunday","ET",2025 +"2025-05-01","Labor Day","ET",2025 +"2025-05-05","Patriots Day","ET",2025 +"2025-05-28","Downfall of Dergue Regime Day","ET",2025 +"2025-06-06","* (*estimated)","ET",2025 +"2025-06-07","* (*estimated)","ET",2025 +"2025-09-04","* (*estimated)","ET",2025 +"2025-09-05","* (*estimated)","ET",2025 +"2025-09-11","Ethiopian New Year's Day","ET",2025 +"2025-09-27","Finding of True Cross","ET",2025 +"2026-01-07","Orthodox Christmas Day","ET",2026 +"2026-01-19","Orthodox Epiphany Day","ET",2026 +"2026-03-02","Adwa Victory Day","ET",2026 +"2026-03-20","* (*estimated)","ET",2026 +"2026-04-10","Orthodox Good Friday","ET",2026 +"2026-04-12","Orthodox Easter Sunday","ET",2026 +"2026-05-01","Labor Day","ET",2026 +"2026-05-05","Patriots Day","ET",2026 +"2026-05-27","* (*estimated)","ET",2026 +"2026-05-28","Downfall of Dergue Regime Day","ET",2026 +"2026-05-28","* (*estimated)","ET",2026 +"2026-08-25","* (*estimated)","ET",2026 +"2026-08-26","* (*estimated)","ET",2026 +"2026-09-11","Ethiopian New Year's Day","ET",2026 +"2026-09-27","Finding of True Cross","ET",2026 +"2027-01-07","Orthodox Christmas Day","ET",2027 +"2027-01-19","Orthodox Epiphany Day","ET",2027 +"2027-03-02","Adwa Victory Day","ET",2027 +"2027-03-09","* (*estimated)","ET",2027 +"2027-04-30","Orthodox Good Friday","ET",2027 +"2027-05-01","Labor Day","ET",2027 +"2027-05-02","Orthodox Easter Sunday","ET",2027 +"2027-05-05","Patriots Day","ET",2027 +"2027-05-16","* (*estimated)","ET",2027 +"2027-05-17","* (*estimated)","ET",2027 +"2027-05-28","Downfall of Dergue Regime Day","ET",2027 +"2027-08-14","* (*estimated)","ET",2027 +"2027-08-15","* (*estimated)","ET",2027 +"2027-09-12","Ethiopian New Year's Day","ET",2027 +"2027-09-28","Finding of True Cross","ET",2027 +"2028-01-07","Orthodox Christmas Day","ET",2028 +"2028-01-19","Orthodox Epiphany Day","ET",2028 +"2028-02-26","* (*estimated)","ET",2028 +"2028-03-02","Adwa Victory Day","ET",2028 +"2028-04-14","Orthodox Good Friday","ET",2028 +"2028-04-16","Orthodox Easter Sunday","ET",2028 +"2028-05-01","Labor Day","ET",2028 +"2028-05-05","Patriots Day","ET",2028 +"2028-05-05","* (*estimated)","ET",2028 +"2028-05-06","* (*estimated)","ET",2028 +"2028-05-28","Downfall of Dergue Regime Day","ET",2028 +"2028-08-03","* (*estimated)","ET",2028 +"2028-08-04","* (*estimated)","ET",2028 +"2028-09-11","Ethiopian New Year's Day","ET",2028 +"2028-09-27","Finding of True Cross","ET",2028 +"2029-01-07","Orthodox Christmas Day","ET",2029 +"2029-01-19","Orthodox Epiphany Day","ET",2029 +"2029-02-14","* (*estimated)","ET",2029 +"2029-03-02","Adwa Victory Day","ET",2029 +"2029-04-06","Orthodox Good Friday","ET",2029 +"2029-04-08","Orthodox Easter Sunday","ET",2029 +"2029-04-24","* (*estimated)","ET",2029 +"2029-04-25","* (*estimated)","ET",2029 +"2029-05-01","Labor Day","ET",2029 +"2029-05-05","Patriots Day","ET",2029 +"2029-05-28","Downfall of Dergue Regime Day","ET",2029 +"2029-07-24","* (*estimated)","ET",2029 +"2029-07-25","* (*estimated)","ET",2029 +"2029-09-11","Ethiopian New Year's Day","ET",2029 +"2029-09-27","Finding of True Cross","ET",2029 +"2030-01-07","Orthodox Christmas Day","ET",2030 +"2030-01-19","Orthodox Epiphany Day","ET",2030 +"2030-02-04","* (*estimated)","ET",2030 +"2030-03-02","Adwa Victory Day","ET",2030 +"2030-04-13","* (*estimated)","ET",2030 +"2030-04-14","* (*estimated)","ET",2030 +"2030-04-26","Orthodox Good Friday","ET",2030 +"2030-04-28","Orthodox Easter Sunday","ET",2030 +"2030-05-01","Labor Day","ET",2030 +"2030-05-05","Patriots Day","ET",2030 +"2030-05-28","Downfall of Dergue Regime Day","ET",2030 +"2030-07-13","* (*estimated)","ET",2030 +"2030-07-14","* (*estimated)","ET",2030 +"2030-09-11","Ethiopian New Year's Day","ET",2030 +"2030-09-27","Finding of True Cross","ET",2030 +"2031-01-07","Orthodox Christmas Day","ET",2031 +"2031-01-19","Orthodox Epiphany Day","ET",2031 +"2031-01-24","* (*estimated)","ET",2031 +"2031-03-02","Adwa Victory Day","ET",2031 +"2031-04-02","* (*estimated)","ET",2031 +"2031-04-03","* (*estimated)","ET",2031 +"2031-04-11","Orthodox Good Friday","ET",2031 +"2031-04-13","Orthodox Easter Sunday","ET",2031 +"2031-05-01","Labor Day","ET",2031 +"2031-05-05","Patriots Day","ET",2031 +"2031-05-28","Downfall of Dergue Regime Day","ET",2031 +"2031-07-02","* (*estimated)","ET",2031 +"2031-07-03","* (*estimated)","ET",2031 +"2031-09-12","Ethiopian New Year's Day","ET",2031 +"2031-09-28","Finding of True Cross","ET",2031 +"2032-01-07","Orthodox Christmas Day","ET",2032 +"2032-01-14","* (*estimated)","ET",2032 +"2032-01-19","Orthodox Epiphany Day","ET",2032 +"2032-03-02","Adwa Victory Day","ET",2032 +"2032-03-22","* (*estimated)","ET",2032 +"2032-03-23","* (*estimated)","ET",2032 +"2032-04-30","Orthodox Good Friday","ET",2032 +"2032-05-01","Labor Day","ET",2032 +"2032-05-02","Orthodox Easter Sunday","ET",2032 +"2032-05-05","Patriots Day","ET",2032 +"2032-05-28","Downfall of Dergue Regime Day","ET",2032 +"2032-06-20","* (*estimated)","ET",2032 +"2032-06-21","* (*estimated)","ET",2032 +"2032-09-11","Ethiopian New Year's Day","ET",2032 +"2032-09-27","Finding of True Cross","ET",2032 +"2033-01-02","* (*estimated)","ET",2033 +"2033-01-07","Orthodox Christmas Day","ET",2033 +"2033-01-19","Orthodox Epiphany Day","ET",2033 +"2033-03-02","Adwa Victory Day","ET",2033 +"2033-03-11","* (*estimated)","ET",2033 +"2033-03-12","* (*estimated)","ET",2033 +"2033-04-22","Orthodox Good Friday","ET",2033 +"2033-04-24","Orthodox Easter Sunday","ET",2033 +"2033-05-01","Labor Day","ET",2033 +"2033-05-05","Patriots Day","ET",2033 +"2033-05-28","Downfall of Dergue Regime Day","ET",2033 +"2033-06-09","* (*estimated)","ET",2033 +"2033-06-10","* (*estimated)","ET",2033 +"2033-09-11","Ethiopian New Year's Day","ET",2033 +"2033-09-27","Finding of True Cross","ET",2033 +"2033-12-23","* (*estimated)","ET",2033 +"2034-01-07","Orthodox Christmas Day","ET",2034 +"2034-01-19","Orthodox Epiphany Day","ET",2034 +"2034-03-01","* (*estimated)","ET",2034 +"2034-03-02","Adwa Victory Day","ET",2034 +"2034-03-02","* (*estimated)","ET",2034 +"2034-04-07","Orthodox Good Friday","ET",2034 +"2034-04-09","Orthodox Easter Sunday","ET",2034 +"2034-05-01","Labor Day","ET",2034 +"2034-05-05","Patriots Day","ET",2034 +"2034-05-28","Downfall of Dergue Regime Day","ET",2034 +"2034-05-30","* (*estimated)","ET",2034 +"2034-05-31","* (*estimated)","ET",2034 +"2034-09-11","Ethiopian New Year's Day","ET",2034 +"2034-09-27","Finding of True Cross","ET",2034 +"2034-12-12","* (*estimated)","ET",2034 +"2035-01-07","Orthodox Christmas Day","ET",2035 +"2035-01-19","Orthodox Epiphany Day","ET",2035 +"2035-02-18","* (*estimated)","ET",2035 +"2035-02-19","* (*estimated)","ET",2035 +"2035-03-02","Adwa Victory Day","ET",2035 +"2035-04-27","Orthodox Good Friday","ET",2035 +"2035-04-29","Orthodox Easter Sunday","ET",2035 +"2035-05-01","Labor Day","ET",2035 +"2035-05-05","Patriots Day","ET",2035 +"2035-05-20","* (*estimated)","ET",2035 +"2035-05-21","* (*estimated)","ET",2035 +"2035-05-28","Downfall of Dergue Regime Day","ET",2035 +"2035-09-12","Ethiopian New Year's Day","ET",2035 +"2035-09-28","Finding of True Cross","ET",2035 +"2035-12-01","* (*estimated)","ET",2035 +"2036-01-07","Orthodox Christmas Day","ET",2036 +"2036-01-19","Orthodox Epiphany Day","ET",2036 +"2036-02-07","* (*estimated)","ET",2036 +"2036-02-08","* (*estimated)","ET",2036 +"2036-03-02","Adwa Victory Day","ET",2036 +"2036-04-18","Orthodox Good Friday","ET",2036 +"2036-04-20","Orthodox Easter Sunday","ET",2036 +"2036-05-01","Labor Day","ET",2036 +"2036-05-05","Patriots Day","ET",2036 +"2036-05-08","* (*estimated)","ET",2036 +"2036-05-09","* (*estimated)","ET",2036 +"2036-05-28","Downfall of Dergue Regime Day","ET",2036 +"2036-09-11","Ethiopian New Year's Day","ET",2036 +"2036-09-27","Finding of True Cross","ET",2036 +"2036-11-19","* (*estimated)","ET",2036 +"2037-01-07","Orthodox Christmas Day","ET",2037 +"2037-01-19","Orthodox Epiphany Day","ET",2037 +"2037-01-26","* (*estimated)","ET",2037 +"2037-01-27","* (*estimated)","ET",2037 +"2037-03-02","Adwa Victory Day","ET",2037 +"2037-04-03","Orthodox Good Friday","ET",2037 +"2037-04-05","Orthodox Easter Sunday","ET",2037 +"2037-04-28","* (*estimated)","ET",2037 +"2037-04-29","* (*estimated)","ET",2037 +"2037-05-01","Labor Day","ET",2037 +"2037-05-05","Patriots Day","ET",2037 +"2037-05-28","Downfall of Dergue Regime Day","ET",2037 +"2037-09-11","Ethiopian New Year's Day","ET",2037 +"2037-09-27","Finding of True Cross","ET",2037 +"2037-11-08","* (*estimated)","ET",2037 +"2038-01-07","Orthodox Christmas Day","ET",2038 +"2038-01-16","* (*estimated)","ET",2038 +"2038-01-17","* (*estimated)","ET",2038 +"2038-01-19","Orthodox Epiphany Day","ET",2038 +"2038-03-02","Adwa Victory Day","ET",2038 +"2038-04-17","* (*estimated)","ET",2038 +"2038-04-18","* (*estimated)","ET",2038 +"2038-04-23","Orthodox Good Friday","ET",2038 +"2038-04-25","Orthodox Easter Sunday","ET",2038 +"2038-05-01","Labor Day","ET",2038 +"2038-05-05","Patriots Day","ET",2038 +"2038-05-28","Downfall of Dergue Regime Day","ET",2038 +"2038-09-11","Ethiopian New Year's Day","ET",2038 +"2038-09-27","Finding of True Cross","ET",2038 +"2038-10-29","* (*estimated)","ET",2038 +"2039-01-05","* (*estimated)","ET",2039 +"2039-01-06","* (*estimated)","ET",2039 +"2039-01-07","Orthodox Christmas Day","ET",2039 +"2039-01-19","Orthodox Epiphany Day","ET",2039 +"2039-03-02","Adwa Victory Day","ET",2039 +"2039-04-06","* (*estimated)","ET",2039 +"2039-04-07","* (*estimated)","ET",2039 +"2039-04-15","Orthodox Good Friday","ET",2039 +"2039-04-17","Orthodox Easter Sunday","ET",2039 +"2039-05-01","Labor Day","ET",2039 +"2039-05-05","Patriots Day","ET",2039 +"2039-05-28","Downfall of Dergue Regime Day","ET",2039 +"2039-09-12","Ethiopian New Year's Day","ET",2039 +"2039-09-28","Finding of True Cross","ET",2039 +"2039-10-19","* (*estimated)","ET",2039 +"2039-12-26","* (*estimated)","ET",2039 +"2039-12-27","* (*estimated)","ET",2039 +"2040-01-07","Orthodox Christmas Day","ET",2040 +"2040-01-19","Orthodox Epiphany Day","ET",2040 +"2040-03-02","Adwa Victory Day","ET",2040 +"2040-03-25","* (*estimated)","ET",2040 +"2040-03-26","* (*estimated)","ET",2040 +"2040-05-01","Labor Day","ET",2040 +"2040-05-04","Orthodox Good Friday","ET",2040 +"2040-05-05","Patriots Day","ET",2040 +"2040-05-06","Orthodox Easter Sunday","ET",2040 +"2040-05-28","Downfall of Dergue Regime Day","ET",2040 +"2040-09-11","Ethiopian New Year's Day","ET",2040 +"2040-09-27","Finding of True Cross","ET",2040 +"2040-10-07","* (*estimated)","ET",2040 +"2040-12-14","* (*estimated)","ET",2040 +"2040-12-15","* (*estimated)","ET",2040 +"2041-01-07","Orthodox Christmas Day","ET",2041 +"2041-01-19","Orthodox Epiphany Day","ET",2041 +"2041-03-02","Adwa Victory Day","ET",2041 +"2041-03-15","* (*estimated)","ET",2041 +"2041-03-16","* (*estimated)","ET",2041 +"2041-04-19","Orthodox Good Friday","ET",2041 +"2041-04-21","Orthodox Easter Sunday","ET",2041 +"2041-05-01","Labor Day","ET",2041 +"2041-05-05","Patriots Day","ET",2041 +"2041-05-28","Downfall of Dergue Regime Day","ET",2041 +"2041-09-11","Ethiopian New Year's Day","ET",2041 +"2041-09-26","* (*estimated)","ET",2041 +"2041-09-27","Finding of True Cross","ET",2041 +"2041-12-04","* (*estimated)","ET",2041 +"2041-12-05","* (*estimated)","ET",2041 +"2042-01-07","Orthodox Christmas Day","ET",2042 +"2042-01-19","Orthodox Epiphany Day","ET",2042 +"2042-03-02","Adwa Victory Day","ET",2042 +"2042-03-04","* (*estimated)","ET",2042 +"2042-03-05","* (*estimated)","ET",2042 +"2042-04-11","Orthodox Good Friday","ET",2042 +"2042-04-13","Orthodox Easter Sunday","ET",2042 +"2042-05-01","Labor Day","ET",2042 +"2042-05-05","Patriots Day","ET",2042 +"2042-05-28","Downfall of Dergue Regime Day","ET",2042 +"2042-09-11","Ethiopian New Year's Day","ET",2042 +"2042-09-15","* (*estimated)","ET",2042 +"2042-09-27","Finding of True Cross","ET",2042 +"2042-11-23","* (*estimated)","ET",2042 +"2042-11-24","* (*estimated)","ET",2042 +"2043-01-07","Orthodox Christmas Day","ET",2043 +"2043-01-19","Orthodox Epiphany Day","ET",2043 +"2043-02-22","* (*estimated)","ET",2043 +"2043-02-23","* (*estimated)","ET",2043 +"2043-03-02","Adwa Victory Day","ET",2043 +"2043-05-01","Labor Day","ET",2043 +"2043-05-01","Orthodox Good Friday","ET",2043 +"2043-05-03","Orthodox Easter Sunday","ET",2043 +"2043-05-05","Patriots Day","ET",2043 +"2043-05-28","Downfall of Dergue Regime Day","ET",2043 +"2043-09-04","* (*estimated)","ET",2043 +"2043-09-12","Ethiopian New Year's Day","ET",2043 +"2043-09-28","Finding of True Cross","ET",2043 +"2043-11-12","* (*estimated)","ET",2043 +"2043-11-13","* (*estimated)","ET",2043 +"2044-01-07","Orthodox Christmas Day","ET",2044 +"2044-01-19","Orthodox Epiphany Day","ET",2044 +"2044-02-11","* (*estimated)","ET",2044 +"2044-02-12","* (*estimated)","ET",2044 +"2044-03-02","Adwa Victory Day","ET",2044 +"2044-04-22","Orthodox Good Friday","ET",2044 +"2044-04-24","Orthodox Easter Sunday","ET",2044 +"2044-05-01","Labor Day","ET",2044 +"2044-05-05","Patriots Day","ET",2044 +"2044-05-28","Downfall of Dergue Regime Day","ET",2044 +"2044-08-24","* (*estimated)","ET",2044 +"2044-09-11","Ethiopian New Year's Day","ET",2044 +"2044-09-27","Finding of True Cross","ET",2044 +"2044-10-31","* (*estimated)","ET",2044 +"2044-11-01","* (*estimated)","ET",2044 +"1995-01-01","New Year's Day","FI",1995 +"1995-01-06","Epiphany","FI",1995 +"1995-04-14","Good Friday","FI",1995 +"1995-04-16","Easter Sunday","FI",1995 +"1995-04-17","Easter Monday","FI",1995 +"1995-05-01","May Day","FI",1995 +"1995-05-25","Ascension Day","FI",1995 +"1995-06-04","Whit Sunday","FI",1995 +"1995-06-23","Midsummer Eve","FI",1995 +"1995-06-24","Midsummer Day","FI",1995 +"1995-11-04","All Saints' Day","FI",1995 +"1995-12-06","Independence Day","FI",1995 +"1995-12-24","Christmas Eve","FI",1995 +"1995-12-25","Christmas Day","FI",1995 +"1995-12-26","Second Day of Christmas","FI",1995 +"1996-01-01","New Year's Day","FI",1996 +"1996-01-06","Epiphany","FI",1996 +"1996-04-05","Good Friday","FI",1996 +"1996-04-07","Easter Sunday","FI",1996 +"1996-04-08","Easter Monday","FI",1996 +"1996-05-01","May Day","FI",1996 +"1996-05-16","Ascension Day","FI",1996 +"1996-05-26","Whit Sunday","FI",1996 +"1996-06-21","Midsummer Eve","FI",1996 +"1996-06-22","Midsummer Day","FI",1996 +"1996-11-02","All Saints' Day","FI",1996 +"1996-12-06","Independence Day","FI",1996 +"1996-12-24","Christmas Eve","FI",1996 +"1996-12-25","Christmas Day","FI",1996 +"1996-12-26","Second Day of Christmas","FI",1996 +"1997-01-01","New Year's Day","FI",1997 +"1997-01-06","Epiphany","FI",1997 +"1997-03-28","Good Friday","FI",1997 +"1997-03-30","Easter Sunday","FI",1997 +"1997-03-31","Easter Monday","FI",1997 +"1997-05-01","May Day","FI",1997 +"1997-05-08","Ascension Day","FI",1997 +"1997-05-18","Whit Sunday","FI",1997 +"1997-06-20","Midsummer Eve","FI",1997 +"1997-06-21","Midsummer Day","FI",1997 +"1997-11-01","All Saints' Day","FI",1997 +"1997-12-06","Independence Day","FI",1997 +"1997-12-24","Christmas Eve","FI",1997 +"1997-12-25","Christmas Day","FI",1997 +"1997-12-26","Second Day of Christmas","FI",1997 +"1998-01-01","New Year's Day","FI",1998 +"1998-01-06","Epiphany","FI",1998 +"1998-04-10","Good Friday","FI",1998 +"1998-04-12","Easter Sunday","FI",1998 +"1998-04-13","Easter Monday","FI",1998 +"1998-05-01","May Day","FI",1998 +"1998-05-21","Ascension Day","FI",1998 +"1998-05-31","Whit Sunday","FI",1998 +"1998-06-19","Midsummer Eve","FI",1998 +"1998-06-20","Midsummer Day","FI",1998 +"1998-10-31","All Saints' Day","FI",1998 +"1998-12-06","Independence Day","FI",1998 +"1998-12-24","Christmas Eve","FI",1998 +"1998-12-25","Christmas Day","FI",1998 +"1998-12-26","Second Day of Christmas","FI",1998 +"1999-01-01","New Year's Day","FI",1999 +"1999-01-06","Epiphany","FI",1999 +"1999-04-02","Good Friday","FI",1999 +"1999-04-04","Easter Sunday","FI",1999 +"1999-04-05","Easter Monday","FI",1999 +"1999-05-01","May Day","FI",1999 +"1999-05-13","Ascension Day","FI",1999 +"1999-05-23","Whit Sunday","FI",1999 +"1999-06-25","Midsummer Eve","FI",1999 +"1999-06-26","Midsummer Day","FI",1999 +"1999-11-06","All Saints' Day","FI",1999 +"1999-12-06","Independence Day","FI",1999 +"1999-12-24","Christmas Eve","FI",1999 +"1999-12-25","Christmas Day","FI",1999 +"1999-12-26","Second Day of Christmas","FI",1999 +"2000-01-01","New Year's Day","FI",2000 +"2000-01-06","Epiphany","FI",2000 +"2000-04-21","Good Friday","FI",2000 +"2000-04-23","Easter Sunday","FI",2000 +"2000-04-24","Easter Monday","FI",2000 +"2000-05-01","May Day","FI",2000 +"2000-06-01","Ascension Day","FI",2000 +"2000-06-11","Whit Sunday","FI",2000 +"2000-06-23","Midsummer Eve","FI",2000 +"2000-06-24","Midsummer Day","FI",2000 +"2000-11-04","All Saints' Day","FI",2000 +"2000-12-06","Independence Day","FI",2000 +"2000-12-24","Christmas Eve","FI",2000 +"2000-12-25","Christmas Day","FI",2000 +"2000-12-26","Second Day of Christmas","FI",2000 +"2001-01-01","New Year's Day","FI",2001 +"2001-01-06","Epiphany","FI",2001 +"2001-04-13","Good Friday","FI",2001 +"2001-04-15","Easter Sunday","FI",2001 +"2001-04-16","Easter Monday","FI",2001 +"2001-05-01","May Day","FI",2001 +"2001-05-24","Ascension Day","FI",2001 +"2001-06-03","Whit Sunday","FI",2001 +"2001-06-22","Midsummer Eve","FI",2001 +"2001-06-23","Midsummer Day","FI",2001 +"2001-11-03","All Saints' Day","FI",2001 +"2001-12-06","Independence Day","FI",2001 +"2001-12-24","Christmas Eve","FI",2001 +"2001-12-25","Christmas Day","FI",2001 +"2001-12-26","Second Day of Christmas","FI",2001 +"2002-01-01","New Year's Day","FI",2002 +"2002-01-06","Epiphany","FI",2002 +"2002-03-29","Good Friday","FI",2002 +"2002-03-31","Easter Sunday","FI",2002 +"2002-04-01","Easter Monday","FI",2002 +"2002-05-01","May Day","FI",2002 +"2002-05-09","Ascension Day","FI",2002 +"2002-05-19","Whit Sunday","FI",2002 +"2002-06-21","Midsummer Eve","FI",2002 +"2002-06-22","Midsummer Day","FI",2002 +"2002-11-02","All Saints' Day","FI",2002 +"2002-12-06","Independence Day","FI",2002 +"2002-12-24","Christmas Eve","FI",2002 +"2002-12-25","Christmas Day","FI",2002 +"2002-12-26","Second Day of Christmas","FI",2002 +"2003-01-01","New Year's Day","FI",2003 +"2003-01-06","Epiphany","FI",2003 +"2003-04-18","Good Friday","FI",2003 +"2003-04-20","Easter Sunday","FI",2003 +"2003-04-21","Easter Monday","FI",2003 +"2003-05-01","May Day","FI",2003 +"2003-05-29","Ascension Day","FI",2003 +"2003-06-08","Whit Sunday","FI",2003 +"2003-06-20","Midsummer Eve","FI",2003 +"2003-06-21","Midsummer Day","FI",2003 +"2003-11-01","All Saints' Day","FI",2003 +"2003-12-06","Independence Day","FI",2003 +"2003-12-24","Christmas Eve","FI",2003 +"2003-12-25","Christmas Day","FI",2003 +"2003-12-26","Second Day of Christmas","FI",2003 +"2004-01-01","New Year's Day","FI",2004 +"2004-01-06","Epiphany","FI",2004 +"2004-04-09","Good Friday","FI",2004 +"2004-04-11","Easter Sunday","FI",2004 +"2004-04-12","Easter Monday","FI",2004 +"2004-05-01","May Day","FI",2004 +"2004-05-20","Ascension Day","FI",2004 +"2004-05-30","Whit Sunday","FI",2004 +"2004-06-25","Midsummer Eve","FI",2004 +"2004-06-26","Midsummer Day","FI",2004 +"2004-11-06","All Saints' Day","FI",2004 +"2004-12-06","Independence Day","FI",2004 +"2004-12-24","Christmas Eve","FI",2004 +"2004-12-25","Christmas Day","FI",2004 +"2004-12-26","Second Day of Christmas","FI",2004 +"2005-01-01","New Year's Day","FI",2005 +"2005-01-06","Epiphany","FI",2005 +"2005-03-25","Good Friday","FI",2005 +"2005-03-27","Easter Sunday","FI",2005 +"2005-03-28","Easter Monday","FI",2005 +"2005-05-01","May Day","FI",2005 +"2005-05-05","Ascension Day","FI",2005 +"2005-05-15","Whit Sunday","FI",2005 +"2005-06-24","Midsummer Eve","FI",2005 +"2005-06-25","Midsummer Day","FI",2005 +"2005-11-05","All Saints' Day","FI",2005 +"2005-12-06","Independence Day","FI",2005 +"2005-12-24","Christmas Eve","FI",2005 +"2005-12-25","Christmas Day","FI",2005 +"2005-12-26","Second Day of Christmas","FI",2005 +"2006-01-01","New Year's Day","FI",2006 +"2006-01-06","Epiphany","FI",2006 +"2006-04-14","Good Friday","FI",2006 +"2006-04-16","Easter Sunday","FI",2006 +"2006-04-17","Easter Monday","FI",2006 +"2006-05-01","May Day","FI",2006 +"2006-05-25","Ascension Day","FI",2006 +"2006-06-04","Whit Sunday","FI",2006 +"2006-06-23","Midsummer Eve","FI",2006 +"2006-06-24","Midsummer Day","FI",2006 +"2006-11-04","All Saints' Day","FI",2006 +"2006-12-06","Independence Day","FI",2006 +"2006-12-24","Christmas Eve","FI",2006 +"2006-12-25","Christmas Day","FI",2006 +"2006-12-26","Second Day of Christmas","FI",2006 +"2007-01-01","New Year's Day","FI",2007 +"2007-01-06","Epiphany","FI",2007 +"2007-04-06","Good Friday","FI",2007 +"2007-04-08","Easter Sunday","FI",2007 +"2007-04-09","Easter Monday","FI",2007 +"2007-05-01","May Day","FI",2007 +"2007-05-17","Ascension Day","FI",2007 +"2007-05-27","Whit Sunday","FI",2007 +"2007-06-22","Midsummer Eve","FI",2007 +"2007-06-23","Midsummer Day","FI",2007 +"2007-11-03","All Saints' Day","FI",2007 +"2007-12-06","Independence Day","FI",2007 +"2007-12-24","Christmas Eve","FI",2007 +"2007-12-25","Christmas Day","FI",2007 +"2007-12-26","Second Day of Christmas","FI",2007 +"2008-01-01","New Year's Day","FI",2008 +"2008-01-06","Epiphany","FI",2008 +"2008-03-21","Good Friday","FI",2008 +"2008-03-23","Easter Sunday","FI",2008 +"2008-03-24","Easter Monday","FI",2008 +"2008-05-01","Ascension Day","FI",2008 +"2008-05-01","May Day","FI",2008 +"2008-05-11","Whit Sunday","FI",2008 +"2008-06-20","Midsummer Eve","FI",2008 +"2008-06-21","Midsummer Day","FI",2008 +"2008-11-01","All Saints' Day","FI",2008 +"2008-12-06","Independence Day","FI",2008 +"2008-12-24","Christmas Eve","FI",2008 +"2008-12-25","Christmas Day","FI",2008 +"2008-12-26","Second Day of Christmas","FI",2008 +"2009-01-01","New Year's Day","FI",2009 +"2009-01-06","Epiphany","FI",2009 +"2009-04-10","Good Friday","FI",2009 +"2009-04-12","Easter Sunday","FI",2009 +"2009-04-13","Easter Monday","FI",2009 +"2009-05-01","May Day","FI",2009 +"2009-05-21","Ascension Day","FI",2009 +"2009-05-31","Whit Sunday","FI",2009 +"2009-06-19","Midsummer Eve","FI",2009 +"2009-06-20","Midsummer Day","FI",2009 +"2009-10-31","All Saints' Day","FI",2009 +"2009-12-06","Independence Day","FI",2009 +"2009-12-24","Christmas Eve","FI",2009 +"2009-12-25","Christmas Day","FI",2009 +"2009-12-26","Second Day of Christmas","FI",2009 +"2010-01-01","New Year's Day","FI",2010 +"2010-01-06","Epiphany","FI",2010 +"2010-04-02","Good Friday","FI",2010 +"2010-04-04","Easter Sunday","FI",2010 +"2010-04-05","Easter Monday","FI",2010 +"2010-05-01","May Day","FI",2010 +"2010-05-13","Ascension Day","FI",2010 +"2010-05-23","Whit Sunday","FI",2010 +"2010-06-25","Midsummer Eve","FI",2010 +"2010-06-26","Midsummer Day","FI",2010 +"2010-11-06","All Saints' Day","FI",2010 +"2010-12-06","Independence Day","FI",2010 +"2010-12-24","Christmas Eve","FI",2010 +"2010-12-25","Christmas Day","FI",2010 +"2010-12-26","Second Day of Christmas","FI",2010 +"2011-01-01","New Year's Day","FI",2011 +"2011-01-06","Epiphany","FI",2011 +"2011-04-22","Good Friday","FI",2011 +"2011-04-24","Easter Sunday","FI",2011 +"2011-04-25","Easter Monday","FI",2011 +"2011-05-01","May Day","FI",2011 +"2011-06-02","Ascension Day","FI",2011 +"2011-06-12","Whit Sunday","FI",2011 +"2011-06-24","Midsummer Eve","FI",2011 +"2011-06-25","Midsummer Day","FI",2011 +"2011-11-05","All Saints' Day","FI",2011 +"2011-12-06","Independence Day","FI",2011 +"2011-12-24","Christmas Eve","FI",2011 +"2011-12-25","Christmas Day","FI",2011 +"2011-12-26","Second Day of Christmas","FI",2011 +"2012-01-01","New Year's Day","FI",2012 +"2012-01-06","Epiphany","FI",2012 +"2012-04-06","Good Friday","FI",2012 +"2012-04-08","Easter Sunday","FI",2012 +"2012-04-09","Easter Monday","FI",2012 +"2012-05-01","May Day","FI",2012 +"2012-05-17","Ascension Day","FI",2012 +"2012-05-27","Whit Sunday","FI",2012 +"2012-06-22","Midsummer Eve","FI",2012 +"2012-06-23","Midsummer Day","FI",2012 +"2012-11-03","All Saints' Day","FI",2012 +"2012-12-06","Independence Day","FI",2012 +"2012-12-24","Christmas Eve","FI",2012 +"2012-12-25","Christmas Day","FI",2012 +"2012-12-26","Second Day of Christmas","FI",2012 +"2013-01-01","New Year's Day","FI",2013 +"2013-01-06","Epiphany","FI",2013 +"2013-03-29","Good Friday","FI",2013 +"2013-03-31","Easter Sunday","FI",2013 +"2013-04-01","Easter Monday","FI",2013 +"2013-05-01","May Day","FI",2013 +"2013-05-09","Ascension Day","FI",2013 +"2013-05-19","Whit Sunday","FI",2013 +"2013-06-21","Midsummer Eve","FI",2013 +"2013-06-22","Midsummer Day","FI",2013 +"2013-11-02","All Saints' Day","FI",2013 +"2013-12-06","Independence Day","FI",2013 +"2013-12-24","Christmas Eve","FI",2013 +"2013-12-25","Christmas Day","FI",2013 +"2013-12-26","Second Day of Christmas","FI",2013 +"2014-01-01","New Year's Day","FI",2014 +"2014-01-06","Epiphany","FI",2014 +"2014-04-18","Good Friday","FI",2014 +"2014-04-20","Easter Sunday","FI",2014 +"2014-04-21","Easter Monday","FI",2014 +"2014-05-01","May Day","FI",2014 +"2014-05-29","Ascension Day","FI",2014 +"2014-06-08","Whit Sunday","FI",2014 +"2014-06-20","Midsummer Eve","FI",2014 +"2014-06-21","Midsummer Day","FI",2014 +"2014-11-01","All Saints' Day","FI",2014 +"2014-12-06","Independence Day","FI",2014 +"2014-12-24","Christmas Eve","FI",2014 +"2014-12-25","Christmas Day","FI",2014 +"2014-12-26","Second Day of Christmas","FI",2014 +"2015-01-01","New Year's Day","FI",2015 +"2015-01-06","Epiphany","FI",2015 +"2015-04-03","Good Friday","FI",2015 +"2015-04-05","Easter Sunday","FI",2015 +"2015-04-06","Easter Monday","FI",2015 +"2015-05-01","May Day","FI",2015 +"2015-05-14","Ascension Day","FI",2015 +"2015-05-24","Whit Sunday","FI",2015 +"2015-06-19","Midsummer Eve","FI",2015 +"2015-06-20","Midsummer Day","FI",2015 +"2015-10-31","All Saints' Day","FI",2015 +"2015-12-06","Independence Day","FI",2015 +"2015-12-24","Christmas Eve","FI",2015 +"2015-12-25","Christmas Day","FI",2015 +"2015-12-26","Second Day of Christmas","FI",2015 +"2016-01-01","New Year's Day","FI",2016 +"2016-01-06","Epiphany","FI",2016 +"2016-03-25","Good Friday","FI",2016 +"2016-03-27","Easter Sunday","FI",2016 +"2016-03-28","Easter Monday","FI",2016 +"2016-05-01","May Day","FI",2016 +"2016-05-05","Ascension Day","FI",2016 +"2016-05-15","Whit Sunday","FI",2016 +"2016-06-24","Midsummer Eve","FI",2016 +"2016-06-25","Midsummer Day","FI",2016 +"2016-11-05","All Saints' Day","FI",2016 +"2016-12-06","Independence Day","FI",2016 +"2016-12-24","Christmas Eve","FI",2016 +"2016-12-25","Christmas Day","FI",2016 +"2016-12-26","Second Day of Christmas","FI",2016 +"2017-01-01","New Year's Day","FI",2017 +"2017-01-06","Epiphany","FI",2017 +"2017-04-14","Good Friday","FI",2017 +"2017-04-16","Easter Sunday","FI",2017 +"2017-04-17","Easter Monday","FI",2017 +"2017-05-01","May Day","FI",2017 +"2017-05-25","Ascension Day","FI",2017 +"2017-06-04","Whit Sunday","FI",2017 +"2017-06-23","Midsummer Eve","FI",2017 +"2017-06-24","Midsummer Day","FI",2017 +"2017-11-04","All Saints' Day","FI",2017 +"2017-12-06","Independence Day","FI",2017 +"2017-12-24","Christmas Eve","FI",2017 +"2017-12-25","Christmas Day","FI",2017 +"2017-12-26","Second Day of Christmas","FI",2017 +"2018-01-01","New Year's Day","FI",2018 +"2018-01-06","Epiphany","FI",2018 +"2018-03-30","Good Friday","FI",2018 +"2018-04-01","Easter Sunday","FI",2018 +"2018-04-02","Easter Monday","FI",2018 +"2018-05-01","May Day","FI",2018 +"2018-05-10","Ascension Day","FI",2018 +"2018-05-20","Whit Sunday","FI",2018 +"2018-06-22","Midsummer Eve","FI",2018 +"2018-06-23","Midsummer Day","FI",2018 +"2018-11-03","All Saints' Day","FI",2018 +"2018-12-06","Independence Day","FI",2018 +"2018-12-24","Christmas Eve","FI",2018 +"2018-12-25","Christmas Day","FI",2018 +"2018-12-26","Second Day of Christmas","FI",2018 +"2019-01-01","New Year's Day","FI",2019 +"2019-01-06","Epiphany","FI",2019 +"2019-04-19","Good Friday","FI",2019 +"2019-04-21","Easter Sunday","FI",2019 +"2019-04-22","Easter Monday","FI",2019 +"2019-05-01","May Day","FI",2019 +"2019-05-30","Ascension Day","FI",2019 +"2019-06-09","Whit Sunday","FI",2019 +"2019-06-21","Midsummer Eve","FI",2019 +"2019-06-22","Midsummer Day","FI",2019 +"2019-11-02","All Saints' Day","FI",2019 +"2019-12-06","Independence Day","FI",2019 +"2019-12-24","Christmas Eve","FI",2019 +"2019-12-25","Christmas Day","FI",2019 +"2019-12-26","Second Day of Christmas","FI",2019 +"2020-01-01","New Year's Day","FI",2020 +"2020-01-06","Epiphany","FI",2020 +"2020-04-10","Good Friday","FI",2020 +"2020-04-12","Easter Sunday","FI",2020 +"2020-04-13","Easter Monday","FI",2020 +"2020-05-01","May Day","FI",2020 +"2020-05-21","Ascension Day","FI",2020 +"2020-05-31","Whit Sunday","FI",2020 +"2020-06-19","Midsummer Eve","FI",2020 +"2020-06-20","Midsummer Day","FI",2020 +"2020-10-31","All Saints' Day","FI",2020 +"2020-12-06","Independence Day","FI",2020 +"2020-12-24","Christmas Eve","FI",2020 +"2020-12-25","Christmas Day","FI",2020 +"2020-12-26","Second Day of Christmas","FI",2020 +"2021-01-01","New Year's Day","FI",2021 +"2021-01-06","Epiphany","FI",2021 +"2021-04-02","Good Friday","FI",2021 +"2021-04-04","Easter Sunday","FI",2021 +"2021-04-05","Easter Monday","FI",2021 +"2021-05-01","May Day","FI",2021 +"2021-05-13","Ascension Day","FI",2021 +"2021-05-23","Whit Sunday","FI",2021 +"2021-06-25","Midsummer Eve","FI",2021 +"2021-06-26","Midsummer Day","FI",2021 +"2021-11-06","All Saints' Day","FI",2021 +"2021-12-06","Independence Day","FI",2021 +"2021-12-24","Christmas Eve","FI",2021 +"2021-12-25","Christmas Day","FI",2021 +"2021-12-26","Second Day of Christmas","FI",2021 +"2022-01-01","New Year's Day","FI",2022 +"2022-01-06","Epiphany","FI",2022 +"2022-04-15","Good Friday","FI",2022 +"2022-04-17","Easter Sunday","FI",2022 +"2022-04-18","Easter Monday","FI",2022 +"2022-05-01","May Day","FI",2022 +"2022-05-26","Ascension Day","FI",2022 +"2022-06-05","Whit Sunday","FI",2022 +"2022-06-24","Midsummer Eve","FI",2022 +"2022-06-25","Midsummer Day","FI",2022 +"2022-11-05","All Saints' Day","FI",2022 +"2022-12-06","Independence Day","FI",2022 +"2022-12-24","Christmas Eve","FI",2022 +"2022-12-25","Christmas Day","FI",2022 +"2022-12-26","Second Day of Christmas","FI",2022 +"2023-01-01","New Year's Day","FI",2023 +"2023-01-06","Epiphany","FI",2023 +"2023-04-07","Good Friday","FI",2023 +"2023-04-09","Easter Sunday","FI",2023 +"2023-04-10","Easter Monday","FI",2023 +"2023-05-01","May Day","FI",2023 +"2023-05-18","Ascension Day","FI",2023 +"2023-05-28","Whit Sunday","FI",2023 +"2023-06-23","Midsummer Eve","FI",2023 +"2023-06-24","Midsummer Day","FI",2023 +"2023-11-04","All Saints' Day","FI",2023 +"2023-12-06","Independence Day","FI",2023 +"2023-12-24","Christmas Eve","FI",2023 +"2023-12-25","Christmas Day","FI",2023 +"2023-12-26","Second Day of Christmas","FI",2023 +"2024-01-01","New Year's Day","FI",2024 +"2024-01-06","Epiphany","FI",2024 +"2024-03-29","Good Friday","FI",2024 +"2024-03-31","Easter Sunday","FI",2024 +"2024-04-01","Easter Monday","FI",2024 +"2024-05-01","May Day","FI",2024 +"2024-05-09","Ascension Day","FI",2024 +"2024-05-19","Whit Sunday","FI",2024 +"2024-06-21","Midsummer Eve","FI",2024 +"2024-06-22","Midsummer Day","FI",2024 +"2024-11-02","All Saints' Day","FI",2024 +"2024-12-06","Independence Day","FI",2024 +"2024-12-24","Christmas Eve","FI",2024 +"2024-12-25","Christmas Day","FI",2024 +"2024-12-26","Second Day of Christmas","FI",2024 +"2025-01-01","New Year's Day","FI",2025 +"2025-01-06","Epiphany","FI",2025 +"2025-04-18","Good Friday","FI",2025 +"2025-04-20","Easter Sunday","FI",2025 +"2025-04-21","Easter Monday","FI",2025 +"2025-05-01","May Day","FI",2025 +"2025-05-29","Ascension Day","FI",2025 +"2025-06-08","Whit Sunday","FI",2025 +"2025-06-20","Midsummer Eve","FI",2025 +"2025-06-21","Midsummer Day","FI",2025 +"2025-11-01","All Saints' Day","FI",2025 +"2025-12-06","Independence Day","FI",2025 +"2025-12-24","Christmas Eve","FI",2025 +"2025-12-25","Christmas Day","FI",2025 +"2025-12-26","Second Day of Christmas","FI",2025 +"2026-01-01","New Year's Day","FI",2026 +"2026-01-06","Epiphany","FI",2026 +"2026-04-03","Good Friday","FI",2026 +"2026-04-05","Easter Sunday","FI",2026 +"2026-04-06","Easter Monday","FI",2026 +"2026-05-01","May Day","FI",2026 +"2026-05-14","Ascension Day","FI",2026 +"2026-05-24","Whit Sunday","FI",2026 +"2026-06-19","Midsummer Eve","FI",2026 +"2026-06-20","Midsummer Day","FI",2026 +"2026-10-31","All Saints' Day","FI",2026 +"2026-12-06","Independence Day","FI",2026 +"2026-12-24","Christmas Eve","FI",2026 +"2026-12-25","Christmas Day","FI",2026 +"2026-12-26","Second Day of Christmas","FI",2026 +"2027-01-01","New Year's Day","FI",2027 +"2027-01-06","Epiphany","FI",2027 +"2027-03-26","Good Friday","FI",2027 +"2027-03-28","Easter Sunday","FI",2027 +"2027-03-29","Easter Monday","FI",2027 +"2027-05-01","May Day","FI",2027 +"2027-05-06","Ascension Day","FI",2027 +"2027-05-16","Whit Sunday","FI",2027 +"2027-06-25","Midsummer Eve","FI",2027 +"2027-06-26","Midsummer Day","FI",2027 +"2027-11-06","All Saints' Day","FI",2027 +"2027-12-06","Independence Day","FI",2027 +"2027-12-24","Christmas Eve","FI",2027 +"2027-12-25","Christmas Day","FI",2027 +"2027-12-26","Second Day of Christmas","FI",2027 +"2028-01-01","New Year's Day","FI",2028 +"2028-01-06","Epiphany","FI",2028 +"2028-04-14","Good Friday","FI",2028 +"2028-04-16","Easter Sunday","FI",2028 +"2028-04-17","Easter Monday","FI",2028 +"2028-05-01","May Day","FI",2028 +"2028-05-25","Ascension Day","FI",2028 +"2028-06-04","Whit Sunday","FI",2028 +"2028-06-23","Midsummer Eve","FI",2028 +"2028-06-24","Midsummer Day","FI",2028 +"2028-11-04","All Saints' Day","FI",2028 +"2028-12-06","Independence Day","FI",2028 +"2028-12-24","Christmas Eve","FI",2028 +"2028-12-25","Christmas Day","FI",2028 +"2028-12-26","Second Day of Christmas","FI",2028 +"2029-01-01","New Year's Day","FI",2029 +"2029-01-06","Epiphany","FI",2029 +"2029-03-30","Good Friday","FI",2029 +"2029-04-01","Easter Sunday","FI",2029 +"2029-04-02","Easter Monday","FI",2029 +"2029-05-01","May Day","FI",2029 +"2029-05-10","Ascension Day","FI",2029 +"2029-05-20","Whit Sunday","FI",2029 +"2029-06-22","Midsummer Eve","FI",2029 +"2029-06-23","Midsummer Day","FI",2029 +"2029-11-03","All Saints' Day","FI",2029 +"2029-12-06","Independence Day","FI",2029 +"2029-12-24","Christmas Eve","FI",2029 +"2029-12-25","Christmas Day","FI",2029 +"2029-12-26","Second Day of Christmas","FI",2029 +"2030-01-01","New Year's Day","FI",2030 +"2030-01-06","Epiphany","FI",2030 +"2030-04-19","Good Friday","FI",2030 +"2030-04-21","Easter Sunday","FI",2030 +"2030-04-22","Easter Monday","FI",2030 +"2030-05-01","May Day","FI",2030 +"2030-05-30","Ascension Day","FI",2030 +"2030-06-09","Whit Sunday","FI",2030 +"2030-06-21","Midsummer Eve","FI",2030 +"2030-06-22","Midsummer Day","FI",2030 +"2030-11-02","All Saints' Day","FI",2030 +"2030-12-06","Independence Day","FI",2030 +"2030-12-24","Christmas Eve","FI",2030 +"2030-12-25","Christmas Day","FI",2030 +"2030-12-26","Second Day of Christmas","FI",2030 +"2031-01-01","New Year's Day","FI",2031 +"2031-01-06","Epiphany","FI",2031 +"2031-04-11","Good Friday","FI",2031 +"2031-04-13","Easter Sunday","FI",2031 +"2031-04-14","Easter Monday","FI",2031 +"2031-05-01","May Day","FI",2031 +"2031-05-22","Ascension Day","FI",2031 +"2031-06-01","Whit Sunday","FI",2031 +"2031-06-20","Midsummer Eve","FI",2031 +"2031-06-21","Midsummer Day","FI",2031 +"2031-11-01","All Saints' Day","FI",2031 +"2031-12-06","Independence Day","FI",2031 +"2031-12-24","Christmas Eve","FI",2031 +"2031-12-25","Christmas Day","FI",2031 +"2031-12-26","Second Day of Christmas","FI",2031 +"2032-01-01","New Year's Day","FI",2032 +"2032-01-06","Epiphany","FI",2032 +"2032-03-26","Good Friday","FI",2032 +"2032-03-28","Easter Sunday","FI",2032 +"2032-03-29","Easter Monday","FI",2032 +"2032-05-01","May Day","FI",2032 +"2032-05-06","Ascension Day","FI",2032 +"2032-05-16","Whit Sunday","FI",2032 +"2032-06-25","Midsummer Eve","FI",2032 +"2032-06-26","Midsummer Day","FI",2032 +"2032-11-06","All Saints' Day","FI",2032 +"2032-12-06","Independence Day","FI",2032 +"2032-12-24","Christmas Eve","FI",2032 +"2032-12-25","Christmas Day","FI",2032 +"2032-12-26","Second Day of Christmas","FI",2032 +"2033-01-01","New Year's Day","FI",2033 +"2033-01-06","Epiphany","FI",2033 +"2033-04-15","Good Friday","FI",2033 +"2033-04-17","Easter Sunday","FI",2033 +"2033-04-18","Easter Monday","FI",2033 +"2033-05-01","May Day","FI",2033 +"2033-05-26","Ascension Day","FI",2033 +"2033-06-05","Whit Sunday","FI",2033 +"2033-06-24","Midsummer Eve","FI",2033 +"2033-06-25","Midsummer Day","FI",2033 +"2033-11-05","All Saints' Day","FI",2033 +"2033-12-06","Independence Day","FI",2033 +"2033-12-24","Christmas Eve","FI",2033 +"2033-12-25","Christmas Day","FI",2033 +"2033-12-26","Second Day of Christmas","FI",2033 +"2034-01-01","New Year's Day","FI",2034 +"2034-01-06","Epiphany","FI",2034 +"2034-04-07","Good Friday","FI",2034 +"2034-04-09","Easter Sunday","FI",2034 +"2034-04-10","Easter Monday","FI",2034 +"2034-05-01","May Day","FI",2034 +"2034-05-18","Ascension Day","FI",2034 +"2034-05-28","Whit Sunday","FI",2034 +"2034-06-23","Midsummer Eve","FI",2034 +"2034-06-24","Midsummer Day","FI",2034 +"2034-11-04","All Saints' Day","FI",2034 +"2034-12-06","Independence Day","FI",2034 +"2034-12-24","Christmas Eve","FI",2034 +"2034-12-25","Christmas Day","FI",2034 +"2034-12-26","Second Day of Christmas","FI",2034 +"2035-01-01","New Year's Day","FI",2035 +"2035-01-06","Epiphany","FI",2035 +"2035-03-23","Good Friday","FI",2035 +"2035-03-25","Easter Sunday","FI",2035 +"2035-03-26","Easter Monday","FI",2035 +"2035-05-01","May Day","FI",2035 +"2035-05-03","Ascension Day","FI",2035 +"2035-05-13","Whit Sunday","FI",2035 +"2035-06-22","Midsummer Eve","FI",2035 +"2035-06-23","Midsummer Day","FI",2035 +"2035-11-03","All Saints' Day","FI",2035 +"2035-12-06","Independence Day","FI",2035 +"2035-12-24","Christmas Eve","FI",2035 +"2035-12-25","Christmas Day","FI",2035 +"2035-12-26","Second Day of Christmas","FI",2035 +"2036-01-01","New Year's Day","FI",2036 +"2036-01-06","Epiphany","FI",2036 +"2036-04-11","Good Friday","FI",2036 +"2036-04-13","Easter Sunday","FI",2036 +"2036-04-14","Easter Monday","FI",2036 +"2036-05-01","May Day","FI",2036 +"2036-05-22","Ascension Day","FI",2036 +"2036-06-01","Whit Sunday","FI",2036 +"2036-06-20","Midsummer Eve","FI",2036 +"2036-06-21","Midsummer Day","FI",2036 +"2036-11-01","All Saints' Day","FI",2036 +"2036-12-06","Independence Day","FI",2036 +"2036-12-24","Christmas Eve","FI",2036 +"2036-12-25","Christmas Day","FI",2036 +"2036-12-26","Second Day of Christmas","FI",2036 +"2037-01-01","New Year's Day","FI",2037 +"2037-01-06","Epiphany","FI",2037 +"2037-04-03","Good Friday","FI",2037 +"2037-04-05","Easter Sunday","FI",2037 +"2037-04-06","Easter Monday","FI",2037 +"2037-05-01","May Day","FI",2037 +"2037-05-14","Ascension Day","FI",2037 +"2037-05-24","Whit Sunday","FI",2037 +"2037-06-19","Midsummer Eve","FI",2037 +"2037-06-20","Midsummer Day","FI",2037 +"2037-10-31","All Saints' Day","FI",2037 +"2037-12-06","Independence Day","FI",2037 +"2037-12-24","Christmas Eve","FI",2037 +"2037-12-25","Christmas Day","FI",2037 +"2037-12-26","Second Day of Christmas","FI",2037 +"2038-01-01","New Year's Day","FI",2038 +"2038-01-06","Epiphany","FI",2038 +"2038-04-23","Good Friday","FI",2038 +"2038-04-25","Easter Sunday","FI",2038 +"2038-04-26","Easter Monday","FI",2038 +"2038-05-01","May Day","FI",2038 +"2038-06-03","Ascension Day","FI",2038 +"2038-06-13","Whit Sunday","FI",2038 +"2038-06-25","Midsummer Eve","FI",2038 +"2038-06-26","Midsummer Day","FI",2038 +"2038-11-06","All Saints' Day","FI",2038 +"2038-12-06","Independence Day","FI",2038 +"2038-12-24","Christmas Eve","FI",2038 +"2038-12-25","Christmas Day","FI",2038 +"2038-12-26","Second Day of Christmas","FI",2038 +"2039-01-01","New Year's Day","FI",2039 +"2039-01-06","Epiphany","FI",2039 +"2039-04-08","Good Friday","FI",2039 +"2039-04-10","Easter Sunday","FI",2039 +"2039-04-11","Easter Monday","FI",2039 +"2039-05-01","May Day","FI",2039 +"2039-05-19","Ascension Day","FI",2039 +"2039-05-29","Whit Sunday","FI",2039 +"2039-06-24","Midsummer Eve","FI",2039 +"2039-06-25","Midsummer Day","FI",2039 +"2039-11-05","All Saints' Day","FI",2039 +"2039-12-06","Independence Day","FI",2039 +"2039-12-24","Christmas Eve","FI",2039 +"2039-12-25","Christmas Day","FI",2039 +"2039-12-26","Second Day of Christmas","FI",2039 +"2040-01-01","New Year's Day","FI",2040 +"2040-01-06","Epiphany","FI",2040 +"2040-03-30","Good Friday","FI",2040 +"2040-04-01","Easter Sunday","FI",2040 +"2040-04-02","Easter Monday","FI",2040 +"2040-05-01","May Day","FI",2040 +"2040-05-10","Ascension Day","FI",2040 +"2040-05-20","Whit Sunday","FI",2040 +"2040-06-22","Midsummer Eve","FI",2040 +"2040-06-23","Midsummer Day","FI",2040 +"2040-11-03","All Saints' Day","FI",2040 +"2040-12-06","Independence Day","FI",2040 +"2040-12-24","Christmas Eve","FI",2040 +"2040-12-25","Christmas Day","FI",2040 +"2040-12-26","Second Day of Christmas","FI",2040 +"2041-01-01","New Year's Day","FI",2041 +"2041-01-06","Epiphany","FI",2041 +"2041-04-19","Good Friday","FI",2041 +"2041-04-21","Easter Sunday","FI",2041 +"2041-04-22","Easter Monday","FI",2041 +"2041-05-01","May Day","FI",2041 +"2041-05-30","Ascension Day","FI",2041 +"2041-06-09","Whit Sunday","FI",2041 +"2041-06-21","Midsummer Eve","FI",2041 +"2041-06-22","Midsummer Day","FI",2041 +"2041-11-02","All Saints' Day","FI",2041 +"2041-12-06","Independence Day","FI",2041 +"2041-12-24","Christmas Eve","FI",2041 +"2041-12-25","Christmas Day","FI",2041 +"2041-12-26","Second Day of Christmas","FI",2041 +"2042-01-01","New Year's Day","FI",2042 +"2042-01-06","Epiphany","FI",2042 +"2042-04-04","Good Friday","FI",2042 +"2042-04-06","Easter Sunday","FI",2042 +"2042-04-07","Easter Monday","FI",2042 +"2042-05-01","May Day","FI",2042 +"2042-05-15","Ascension Day","FI",2042 +"2042-05-25","Whit Sunday","FI",2042 +"2042-06-20","Midsummer Eve","FI",2042 +"2042-06-21","Midsummer Day","FI",2042 +"2042-11-01","All Saints' Day","FI",2042 +"2042-12-06","Independence Day","FI",2042 +"2042-12-24","Christmas Eve","FI",2042 +"2042-12-25","Christmas Day","FI",2042 +"2042-12-26","Second Day of Christmas","FI",2042 +"2043-01-01","New Year's Day","FI",2043 +"2043-01-06","Epiphany","FI",2043 +"2043-03-27","Good Friday","FI",2043 +"2043-03-29","Easter Sunday","FI",2043 +"2043-03-30","Easter Monday","FI",2043 +"2043-05-01","May Day","FI",2043 +"2043-05-07","Ascension Day","FI",2043 +"2043-05-17","Whit Sunday","FI",2043 +"2043-06-19","Midsummer Eve","FI",2043 +"2043-06-20","Midsummer Day","FI",2043 +"2043-10-31","All Saints' Day","FI",2043 +"2043-12-06","Independence Day","FI",2043 +"2043-12-24","Christmas Eve","FI",2043 +"2043-12-25","Christmas Day","FI",2043 +"2043-12-26","Second Day of Christmas","FI",2043 +"2044-01-01","New Year's Day","FI",2044 +"2044-01-06","Epiphany","FI",2044 +"2044-04-15","Good Friday","FI",2044 +"2044-04-17","Easter Sunday","FI",2044 +"2044-04-18","Easter Monday","FI",2044 +"2044-05-01","May Day","FI",2044 +"2044-05-26","Ascension Day","FI",2044 +"2044-06-05","Whit Sunday","FI",2044 +"2044-06-24","Midsummer Eve","FI",2044 +"2044-06-25","Midsummer Day","FI",2044 +"2044-11-05","All Saints' Day","FI",2044 +"2044-12-06","Independence Day","FI",2044 +"2044-12-24","Christmas Eve","FI",2044 +"2044-12-25","Christmas Day","FI",2044 +"2044-12-26","Second Day of Christmas","FI",2044 +"1995-01-01","New Year's Day","FR",1995 +"1995-04-17","Easter Monday","FR",1995 +"1995-05-01","Labor Day","FR",1995 +"1995-05-08","Victory Day","FR",1995 +"1995-05-25","Ascension Day","FR",1995 +"1995-06-05","Whit Monday","FR",1995 +"1995-07-14","National Day","FR",1995 +"1995-08-15","Assumption Day","FR",1995 +"1995-11-01","All Saints' Day","FR",1995 +"1995-11-11","Armistice Day","FR",1995 +"1995-12-25","Christmas Day","FR",1995 +"1996-01-01","New Year's Day","FR",1996 +"1996-04-08","Easter Monday","FR",1996 +"1996-05-01","Labor Day","FR",1996 +"1996-05-08","Victory Day","FR",1996 +"1996-05-16","Ascension Day","FR",1996 +"1996-05-27","Whit Monday","FR",1996 +"1996-07-14","National Day","FR",1996 +"1996-08-15","Assumption Day","FR",1996 +"1996-11-01","All Saints' Day","FR",1996 +"1996-11-11","Armistice Day","FR",1996 +"1996-12-25","Christmas Day","FR",1996 +"1997-01-01","New Year's Day","FR",1997 +"1997-03-31","Easter Monday","FR",1997 +"1997-05-01","Labor Day","FR",1997 +"1997-05-08","Ascension Day","FR",1997 +"1997-05-08","Victory Day","FR",1997 +"1997-05-19","Whit Monday","FR",1997 +"1997-07-14","National Day","FR",1997 +"1997-08-15","Assumption Day","FR",1997 +"1997-11-01","All Saints' Day","FR",1997 +"1997-11-11","Armistice Day","FR",1997 +"1997-12-25","Christmas Day","FR",1997 +"1998-01-01","New Year's Day","FR",1998 +"1998-04-13","Easter Monday","FR",1998 +"1998-05-01","Labor Day","FR",1998 +"1998-05-08","Victory Day","FR",1998 +"1998-05-21","Ascension Day","FR",1998 +"1998-06-01","Whit Monday","FR",1998 +"1998-07-14","National Day","FR",1998 +"1998-08-15","Assumption Day","FR",1998 +"1998-11-01","All Saints' Day","FR",1998 +"1998-11-11","Armistice Day","FR",1998 +"1998-12-25","Christmas Day","FR",1998 +"1999-01-01","New Year's Day","FR",1999 +"1999-04-05","Easter Monday","FR",1999 +"1999-05-01","Labor Day","FR",1999 +"1999-05-08","Victory Day","FR",1999 +"1999-05-13","Ascension Day","FR",1999 +"1999-05-24","Whit Monday","FR",1999 +"1999-07-14","National Day","FR",1999 +"1999-08-15","Assumption Day","FR",1999 +"1999-11-01","All Saints' Day","FR",1999 +"1999-11-11","Armistice Day","FR",1999 +"1999-12-25","Christmas Day","FR",1999 +"2000-01-01","New Year's Day","FR",2000 +"2000-04-24","Easter Monday","FR",2000 +"2000-05-01","Labor Day","FR",2000 +"2000-05-08","Victory Day","FR",2000 +"2000-06-01","Ascension Day","FR",2000 +"2000-06-12","Whit Monday","FR",2000 +"2000-07-14","National Day","FR",2000 +"2000-08-15","Assumption Day","FR",2000 +"2000-11-01","All Saints' Day","FR",2000 +"2000-11-11","Armistice Day","FR",2000 +"2000-12-25","Christmas Day","FR",2000 +"2001-01-01","New Year's Day","FR",2001 +"2001-04-16","Easter Monday","FR",2001 +"2001-05-01","Labor Day","FR",2001 +"2001-05-08","Victory Day","FR",2001 +"2001-05-24","Ascension Day","FR",2001 +"2001-06-04","Whit Monday","FR",2001 +"2001-07-14","National Day","FR",2001 +"2001-08-15","Assumption Day","FR",2001 +"2001-11-01","All Saints' Day","FR",2001 +"2001-11-11","Armistice Day","FR",2001 +"2001-12-25","Christmas Day","FR",2001 +"2002-01-01","New Year's Day","FR",2002 +"2002-04-01","Easter Monday","FR",2002 +"2002-05-01","Labor Day","FR",2002 +"2002-05-08","Victory Day","FR",2002 +"2002-05-09","Ascension Day","FR",2002 +"2002-05-20","Whit Monday","FR",2002 +"2002-07-14","National Day","FR",2002 +"2002-08-15","Assumption Day","FR",2002 +"2002-11-01","All Saints' Day","FR",2002 +"2002-11-11","Armistice Day","FR",2002 +"2002-12-25","Christmas Day","FR",2002 +"2003-01-01","New Year's Day","FR",2003 +"2003-04-21","Easter Monday","FR",2003 +"2003-05-01","Labor Day","FR",2003 +"2003-05-08","Victory Day","FR",2003 +"2003-05-29","Ascension Day","FR",2003 +"2003-06-09","Whit Monday","FR",2003 +"2003-07-14","National Day","FR",2003 +"2003-08-15","Assumption Day","FR",2003 +"2003-11-01","All Saints' Day","FR",2003 +"2003-11-11","Armistice Day","FR",2003 +"2003-12-25","Christmas Day","FR",2003 +"2004-01-01","New Year's Day","FR",2004 +"2004-04-12","Easter Monday","FR",2004 +"2004-05-01","Labor Day","FR",2004 +"2004-05-08","Victory Day","FR",2004 +"2004-05-20","Ascension Day","FR",2004 +"2004-05-31","Whit Monday","FR",2004 +"2004-07-14","National Day","FR",2004 +"2004-08-15","Assumption Day","FR",2004 +"2004-11-01","All Saints' Day","FR",2004 +"2004-11-11","Armistice Day","FR",2004 +"2004-12-25","Christmas Day","FR",2004 +"2005-01-01","New Year's Day","FR",2005 +"2005-03-28","Easter Monday","FR",2005 +"2005-05-01","Labor Day","FR",2005 +"2005-05-05","Ascension Day","FR",2005 +"2005-05-08","Victory Day","FR",2005 +"2005-07-14","National Day","FR",2005 +"2005-08-15","Assumption Day","FR",2005 +"2005-11-01","All Saints' Day","FR",2005 +"2005-11-11","Armistice Day","FR",2005 +"2005-12-25","Christmas Day","FR",2005 +"2006-01-01","New Year's Day","FR",2006 +"2006-04-17","Easter Monday","FR",2006 +"2006-05-01","Labor Day","FR",2006 +"2006-05-08","Victory Day","FR",2006 +"2006-05-25","Ascension Day","FR",2006 +"2006-07-14","National Day","FR",2006 +"2006-08-15","Assumption Day","FR",2006 +"2006-11-01","All Saints' Day","FR",2006 +"2006-11-11","Armistice Day","FR",2006 +"2006-12-25","Christmas Day","FR",2006 +"2007-01-01","New Year's Day","FR",2007 +"2007-04-09","Easter Monday","FR",2007 +"2007-05-01","Labor Day","FR",2007 +"2007-05-08","Victory Day","FR",2007 +"2007-05-17","Ascension Day","FR",2007 +"2007-07-14","National Day","FR",2007 +"2007-08-15","Assumption Day","FR",2007 +"2007-11-01","All Saints' Day","FR",2007 +"2007-11-11","Armistice Day","FR",2007 +"2007-12-25","Christmas Day","FR",2007 +"2008-01-01","New Year's Day","FR",2008 +"2008-03-24","Easter Monday","FR",2008 +"2008-05-01","Ascension Day","FR",2008 +"2008-05-01","Labor Day","FR",2008 +"2008-05-08","Victory Day","FR",2008 +"2008-05-12","Whit Monday","FR",2008 +"2008-07-14","National Day","FR",2008 +"2008-08-15","Assumption Day","FR",2008 +"2008-11-01","All Saints' Day","FR",2008 +"2008-11-11","Armistice Day","FR",2008 +"2008-12-25","Christmas Day","FR",2008 +"2009-01-01","New Year's Day","FR",2009 +"2009-04-13","Easter Monday","FR",2009 +"2009-05-01","Labor Day","FR",2009 +"2009-05-08","Victory Day","FR",2009 +"2009-05-21","Ascension Day","FR",2009 +"2009-06-01","Whit Monday","FR",2009 +"2009-07-14","National Day","FR",2009 +"2009-08-15","Assumption Day","FR",2009 +"2009-11-01","All Saints' Day","FR",2009 +"2009-11-11","Armistice Day","FR",2009 +"2009-12-25","Christmas Day","FR",2009 +"2010-01-01","New Year's Day","FR",2010 +"2010-04-05","Easter Monday","FR",2010 +"2010-05-01","Labor Day","FR",2010 +"2010-05-08","Victory Day","FR",2010 +"2010-05-13","Ascension Day","FR",2010 +"2010-05-24","Whit Monday","FR",2010 +"2010-07-14","National Day","FR",2010 +"2010-08-15","Assumption Day","FR",2010 +"2010-11-01","All Saints' Day","FR",2010 +"2010-11-11","Armistice Day","FR",2010 +"2010-12-25","Christmas Day","FR",2010 +"2011-01-01","New Year's Day","FR",2011 +"2011-04-25","Easter Monday","FR",2011 +"2011-05-01","Labor Day","FR",2011 +"2011-05-08","Victory Day","FR",2011 +"2011-06-02","Ascension Day","FR",2011 +"2011-06-13","Whit Monday","FR",2011 +"2011-07-14","National Day","FR",2011 +"2011-08-15","Assumption Day","FR",2011 +"2011-11-01","All Saints' Day","FR",2011 +"2011-11-11","Armistice Day","FR",2011 +"2011-12-25","Christmas Day","FR",2011 +"2012-01-01","New Year's Day","FR",2012 +"2012-04-09","Easter Monday","FR",2012 +"2012-05-01","Labor Day","FR",2012 +"2012-05-08","Victory Day","FR",2012 +"2012-05-17","Ascension Day","FR",2012 +"2012-05-28","Whit Monday","FR",2012 +"2012-07-14","National Day","FR",2012 +"2012-08-15","Assumption Day","FR",2012 +"2012-11-01","All Saints' Day","FR",2012 +"2012-11-11","Armistice Day","FR",2012 +"2012-12-25","Christmas Day","FR",2012 +"2013-01-01","New Year's Day","FR",2013 +"2013-04-01","Easter Monday","FR",2013 +"2013-05-01","Labor Day","FR",2013 +"2013-05-08","Victory Day","FR",2013 +"2013-05-09","Ascension Day","FR",2013 +"2013-05-20","Whit Monday","FR",2013 +"2013-07-14","National Day","FR",2013 +"2013-08-15","Assumption Day","FR",2013 +"2013-11-01","All Saints' Day","FR",2013 +"2013-11-11","Armistice Day","FR",2013 +"2013-12-25","Christmas Day","FR",2013 +"2014-01-01","New Year's Day","FR",2014 +"2014-04-21","Easter Monday","FR",2014 +"2014-05-01","Labor Day","FR",2014 +"2014-05-08","Victory Day","FR",2014 +"2014-05-29","Ascension Day","FR",2014 +"2014-06-09","Whit Monday","FR",2014 +"2014-07-14","National Day","FR",2014 +"2014-08-15","Assumption Day","FR",2014 +"2014-11-01","All Saints' Day","FR",2014 +"2014-11-11","Armistice Day","FR",2014 +"2014-12-25","Christmas Day","FR",2014 +"2015-01-01","New Year's Day","FR",2015 +"2015-04-06","Easter Monday","FR",2015 +"2015-05-01","Labor Day","FR",2015 +"2015-05-08","Victory Day","FR",2015 +"2015-05-14","Ascension Day","FR",2015 +"2015-05-25","Whit Monday","FR",2015 +"2015-07-14","National Day","FR",2015 +"2015-08-15","Assumption Day","FR",2015 +"2015-11-01","All Saints' Day","FR",2015 +"2015-11-11","Armistice Day","FR",2015 +"2015-12-25","Christmas Day","FR",2015 +"2016-01-01","New Year's Day","FR",2016 +"2016-03-28","Easter Monday","FR",2016 +"2016-05-01","Labor Day","FR",2016 +"2016-05-05","Ascension Day","FR",2016 +"2016-05-08","Victory Day","FR",2016 +"2016-05-16","Whit Monday","FR",2016 +"2016-07-14","National Day","FR",2016 +"2016-08-15","Assumption Day","FR",2016 +"2016-11-01","All Saints' Day","FR",2016 +"2016-11-11","Armistice Day","FR",2016 +"2016-12-25","Christmas Day","FR",2016 +"2017-01-01","New Year's Day","FR",2017 +"2017-04-17","Easter Monday","FR",2017 +"2017-05-01","Labor Day","FR",2017 +"2017-05-08","Victory Day","FR",2017 +"2017-05-25","Ascension Day","FR",2017 +"2017-06-05","Whit Monday","FR",2017 +"2017-07-14","National Day","FR",2017 +"2017-08-15","Assumption Day","FR",2017 +"2017-11-01","All Saints' Day","FR",2017 +"2017-11-11","Armistice Day","FR",2017 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+"2024-11-01","All Saints' Day","FR",2024 +"2024-11-11","Armistice Day","FR",2024 +"2024-12-25","Christmas Day","FR",2024 +"2025-01-01","New Year's Day","FR",2025 +"2025-04-21","Easter Monday","FR",2025 +"2025-05-01","Labor Day","FR",2025 +"2025-05-08","Victory Day","FR",2025 +"2025-05-29","Ascension Day","FR",2025 +"2025-06-09","Whit Monday","FR",2025 +"2025-07-14","National Day","FR",2025 +"2025-08-15","Assumption Day","FR",2025 +"2025-11-01","All Saints' Day","FR",2025 +"2025-11-11","Armistice Day","FR",2025 +"2025-12-25","Christmas Day","FR",2025 +"2026-01-01","New Year's Day","FR",2026 +"2026-04-06","Easter Monday","FR",2026 +"2026-05-01","Labor Day","FR",2026 +"2026-05-08","Victory Day","FR",2026 +"2026-05-14","Ascension Day","FR",2026 +"2026-05-25","Whit Monday","FR",2026 +"2026-07-14","National Day","FR",2026 +"2026-08-15","Assumption Day","FR",2026 +"2026-11-01","All Saints' Day","FR",2026 +"2026-11-11","Armistice Day","FR",2026 +"2026-12-25","Christmas Day","FR",2026 +"2027-01-01","New Year's Day","FR",2027 +"2027-03-29","Easter Monday","FR",2027 +"2027-05-01","Labor Day","FR",2027 +"2027-05-06","Ascension Day","FR",2027 +"2027-05-08","Victory Day","FR",2027 +"2027-05-17","Whit Monday","FR",2027 +"2027-07-14","National Day","FR",2027 +"2027-08-15","Assumption Day","FR",2027 +"2027-11-01","All Saints' Day","FR",2027 +"2027-11-11","Armistice Day","FR",2027 +"2027-12-25","Christmas Day","FR",2027 +"2028-01-01","New Year's Day","FR",2028 +"2028-04-17","Easter Monday","FR",2028 +"2028-05-01","Labor Day","FR",2028 +"2028-05-08","Victory Day","FR",2028 +"2028-05-25","Ascension Day","FR",2028 +"2028-06-05","Whit Monday","FR",2028 +"2028-07-14","National Day","FR",2028 +"2028-08-15","Assumption Day","FR",2028 +"2028-11-01","All Saints' Day","FR",2028 +"2028-11-11","Armistice Day","FR",2028 +"2028-12-25","Christmas Day","FR",2028 +"2029-01-01","New Year's Day","FR",2029 +"2029-04-02","Easter Monday","FR",2029 +"2029-05-01","Labor Day","FR",2029 +"2029-05-08","Victory Day","FR",2029 +"2029-05-10","Ascension Day","FR",2029 +"2029-05-21","Whit Monday","FR",2029 +"2029-07-14","National Day","FR",2029 +"2029-08-15","Assumption Day","FR",2029 +"2029-11-01","All Saints' Day","FR",2029 +"2029-11-11","Armistice Day","FR",2029 +"2029-12-25","Christmas Day","FR",2029 +"2030-01-01","New Year's Day","FR",2030 +"2030-04-22","Easter Monday","FR",2030 +"2030-05-01","Labor Day","FR",2030 +"2030-05-08","Victory Day","FR",2030 +"2030-05-30","Ascension Day","FR",2030 +"2030-06-10","Whit Monday","FR",2030 +"2030-07-14","National Day","FR",2030 +"2030-08-15","Assumption Day","FR",2030 +"2030-11-01","All Saints' Day","FR",2030 +"2030-11-11","Armistice Day","FR",2030 +"2030-12-25","Christmas Day","FR",2030 +"2031-01-01","New Year's Day","FR",2031 +"2031-04-14","Easter Monday","FR",2031 +"2031-05-01","Labor Day","FR",2031 +"2031-05-08","Victory Day","FR",2031 +"2031-05-22","Ascension Day","FR",2031 +"2031-06-02","Whit Monday","FR",2031 +"2031-07-14","National Day","FR",2031 +"2031-08-15","Assumption Day","FR",2031 +"2031-11-01","All Saints' Day","FR",2031 +"2031-11-11","Armistice Day","FR",2031 +"2031-12-25","Christmas Day","FR",2031 +"2032-01-01","New Year's Day","FR",2032 +"2032-03-29","Easter Monday","FR",2032 +"2032-05-01","Labor Day","FR",2032 +"2032-05-06","Ascension Day","FR",2032 +"2032-05-08","Victory Day","FR",2032 +"2032-05-17","Whit Monday","FR",2032 +"2032-07-14","National Day","FR",2032 +"2032-08-15","Assumption Day","FR",2032 +"2032-11-01","All Saints' Day","FR",2032 +"2032-11-11","Armistice Day","FR",2032 +"2032-12-25","Christmas Day","FR",2032 +"2033-01-01","New Year's Day","FR",2033 +"2033-04-18","Easter Monday","FR",2033 +"2033-05-01","Labor Day","FR",2033 +"2033-05-08","Victory Day","FR",2033 +"2033-05-26","Ascension Day","FR",2033 +"2033-06-06","Whit Monday","FR",2033 +"2033-07-14","National Day","FR",2033 +"2033-08-15","Assumption Day","FR",2033 +"2033-11-01","All Saints' Day","FR",2033 +"2033-11-11","Armistice Day","FR",2033 +"2033-12-25","Christmas Day","FR",2033 +"2034-01-01","New Year's Day","FR",2034 +"2034-04-10","Easter Monday","FR",2034 +"2034-05-01","Labor Day","FR",2034 +"2034-05-08","Victory Day","FR",2034 +"2034-05-18","Ascension Day","FR",2034 +"2034-05-29","Whit Monday","FR",2034 +"2034-07-14","National Day","FR",2034 +"2034-08-15","Assumption Day","FR",2034 +"2034-11-01","All Saints' Day","FR",2034 +"2034-11-11","Armistice Day","FR",2034 +"2034-12-25","Christmas Day","FR",2034 +"2035-01-01","New Year's Day","FR",2035 +"2035-03-26","Easter Monday","FR",2035 +"2035-05-01","Labor Day","FR",2035 +"2035-05-03","Ascension Day","FR",2035 +"2035-05-08","Victory Day","FR",2035 +"2035-05-14","Whit Monday","FR",2035 +"2035-07-14","National Day","FR",2035 +"2035-08-15","Assumption Day","FR",2035 +"2035-11-01","All Saints' Day","FR",2035 +"2035-11-11","Armistice Day","FR",2035 +"2035-12-25","Christmas Day","FR",2035 +"2036-01-01","New Year's Day","FR",2036 +"2036-04-14","Easter Monday","FR",2036 +"2036-05-01","Labor Day","FR",2036 +"2036-05-08","Victory Day","FR",2036 +"2036-05-22","Ascension Day","FR",2036 +"2036-06-02","Whit Monday","FR",2036 +"2036-07-14","National Day","FR",2036 +"2036-08-15","Assumption Day","FR",2036 +"2036-11-01","All Saints' Day","FR",2036 +"2036-11-11","Armistice Day","FR",2036 +"2036-12-25","Christmas Day","FR",2036 +"2037-01-01","New Year's Day","FR",2037 +"2037-04-06","Easter Monday","FR",2037 +"2037-05-01","Labor Day","FR",2037 +"2037-05-08","Victory Day","FR",2037 +"2037-05-14","Ascension Day","FR",2037 +"2037-05-25","Whit Monday","FR",2037 +"2037-07-14","National Day","FR",2037 +"2037-08-15","Assumption Day","FR",2037 +"2037-11-01","All Saints' Day","FR",2037 +"2037-11-11","Armistice Day","FR",2037 +"2037-12-25","Christmas Day","FR",2037 +"2038-01-01","New Year's Day","FR",2038 +"2038-04-26","Easter Monday","FR",2038 +"2038-05-01","Labor Day","FR",2038 +"2038-05-08","Victory Day","FR",2038 +"2038-06-03","Ascension Day","FR",2038 +"2038-06-14","Whit Monday","FR",2038 +"2038-07-14","National Day","FR",2038 +"2038-08-15","Assumption Day","FR",2038 +"2038-11-01","All Saints' Day","FR",2038 +"2038-11-11","Armistice Day","FR",2038 +"2038-12-25","Christmas Day","FR",2038 +"2039-01-01","New Year's Day","FR",2039 +"2039-04-11","Easter Monday","FR",2039 +"2039-05-01","Labor Day","FR",2039 +"2039-05-08","Victory Day","FR",2039 +"2039-05-19","Ascension Day","FR",2039 +"2039-05-30","Whit Monday","FR",2039 +"2039-07-14","National Day","FR",2039 +"2039-08-15","Assumption Day","FR",2039 +"2039-11-01","All Saints' Day","FR",2039 +"2039-11-11","Armistice Day","FR",2039 +"2039-12-25","Christmas Day","FR",2039 +"2040-01-01","New Year's Day","FR",2040 +"2040-04-02","Easter Monday","FR",2040 +"2040-05-01","Labor Day","FR",2040 +"2040-05-08","Victory Day","FR",2040 +"2040-05-10","Ascension Day","FR",2040 +"2040-05-21","Whit Monday","FR",2040 +"2040-07-14","National Day","FR",2040 +"2040-08-15","Assumption Day","FR",2040 +"2040-11-01","All Saints' Day","FR",2040 +"2040-11-11","Armistice Day","FR",2040 +"2040-12-25","Christmas Day","FR",2040 +"2041-01-01","New Year's Day","FR",2041 +"2041-04-22","Easter Monday","FR",2041 +"2041-05-01","Labor Day","FR",2041 +"2041-05-08","Victory Day","FR",2041 +"2041-05-30","Ascension Day","FR",2041 +"2041-06-10","Whit Monday","FR",2041 +"2041-07-14","National Day","FR",2041 +"2041-08-15","Assumption Day","FR",2041 +"2041-11-01","All Saints' Day","FR",2041 +"2041-11-11","Armistice Day","FR",2041 +"2041-12-25","Christmas Day","FR",2041 +"2042-01-01","New Year's Day","FR",2042 +"2042-04-07","Easter Monday","FR",2042 +"2042-05-01","Labor Day","FR",2042 +"2042-05-08","Victory Day","FR",2042 +"2042-05-15","Ascension Day","FR",2042 +"2042-05-26","Whit Monday","FR",2042 +"2042-07-14","National Day","FR",2042 +"2042-08-15","Assumption Day","FR",2042 +"2042-11-01","All Saints' Day","FR",2042 +"2042-11-11","Armistice Day","FR",2042 +"2042-12-25","Christmas Day","FR",2042 +"2043-01-01","New Year's Day","FR",2043 +"2043-03-30","Easter Monday","FR",2043 +"2043-05-01","Labor Day","FR",2043 +"2043-05-07","Ascension Day","FR",2043 +"2043-05-08","Victory Day","FR",2043 +"2043-05-18","Whit Monday","FR",2043 +"2043-07-14","National Day","FR",2043 +"2043-08-15","Assumption Day","FR",2043 +"2043-11-01","All Saints' Day","FR",2043 +"2043-11-11","Armistice Day","FR",2043 +"2043-12-25","Christmas Day","FR",2043 +"2044-01-01","New Year's Day","FR",2044 +"2044-04-18","Easter Monday","FR",2044 +"2044-05-01","Labor Day","FR",2044 +"2044-05-08","Victory Day","FR",2044 +"2044-05-26","Ascension Day","FR",2044 +"2044-06-06","Whit Monday","FR",2044 +"2044-07-14","National Day","FR",2044 +"2044-08-15","Assumption Day","FR",2044 +"2044-11-01","All Saints' Day","FR",2044 +"2044-11-11","Armistice Day","FR",2044 +"2044-12-25","Christmas Day","FR",2044 +"1995-01-01","New Year's Day","GB",1995 +"1995-01-02","New Year Holiday [Scotland]","GB",1995 +"1995-01-02","New Year's Day (Observed)","GB",1995 +"1995-01-03","New Year Holiday [Scotland] (Observed)","GB",1995 +"1995-03-17","St. Patrick's Day [Northern Ireland]","GB",1995 +"1995-04-14","Good Friday","GB",1995 +"1995-04-17","Easter Monday [England/Wales/Northern Ireland]","GB",1995 +"1995-05-08","May Day","GB",1995 +"1995-05-29","Spring Bank Holiday","GB",1995 +"1995-07-12","Battle of the Boyne [Northern Ireland]","GB",1995 +"1995-08-07","Summer Bank Holiday [Scotland]","GB",1995 +"1995-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",1995 +"1995-11-30","St. Andrew's Day [Scotland]","GB",1995 +"1995-12-25","Christmas Day","GB",1995 +"1995-12-26","Boxing Day","GB",1995 +"1996-01-01","New Year's Day","GB",1996 +"1996-01-02","New Year Holiday [Scotland]","GB",1996 +"1996-03-17","St. Patrick's Day [Northern Ireland]","GB",1996 +"1996-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",1996 +"1996-04-05","Good Friday","GB",1996 +"1996-04-08","Easter Monday [England/Wales/Northern Ireland]","GB",1996 +"1996-05-06","May Day","GB",1996 +"1996-05-27","Spring Bank Holiday","GB",1996 +"1996-07-12","Battle of the Boyne [Northern Ireland]","GB",1996 +"1996-08-05","Summer Bank Holiday [Scotland]","GB",1996 +"1996-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",1996 +"1996-11-30","St. Andrew's Day [Scotland]","GB",1996 +"1996-12-25","Christmas Day","GB",1996 +"1996-12-26","Boxing Day","GB",1996 +"1997-01-01","New Year's Day","GB",1997 +"1997-01-02","New Year Holiday [Scotland]","GB",1997 +"1997-03-17","St. Patrick's Day [Northern Ireland]","GB",1997 +"1997-03-28","Good Friday","GB",1997 +"1997-03-31","Easter Monday [England/Wales/Northern Ireland]","GB",1997 +"1997-05-05","May Day","GB",1997 +"1997-05-26","Spring Bank Holiday","GB",1997 +"1997-07-12","Battle of the Boyne [Northern Ireland]","GB",1997 +"1997-08-04","Summer Bank Holiday [Scotland]","GB",1997 +"1997-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",1997 +"1997-11-30","St. Andrew's Day [Scotland]","GB",1997 +"1997-12-25","Christmas Day","GB",1997 +"1997-12-26","Boxing Day","GB",1997 +"1998-01-01","New Year's Day","GB",1998 +"1998-01-02","New Year Holiday [Scotland]","GB",1998 +"1998-03-17","St. Patrick's Day [Northern Ireland]","GB",1998 +"1998-04-10","Good Friday","GB",1998 +"1998-04-13","Easter Monday [England/Wales/Northern Ireland]","GB",1998 +"1998-05-04","May Day","GB",1998 +"1998-05-25","Spring Bank Holiday","GB",1998 +"1998-07-12","Battle of the Boyne [Northern Ireland]","GB",1998 +"1998-08-03","Summer Bank Holiday [Scotland]","GB",1998 +"1998-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",1998 +"1998-11-30","St. Andrew's Day [Scotland]","GB",1998 +"1998-12-25","Christmas Day","GB",1998 +"1998-12-26","Boxing Day","GB",1998 +"1998-12-28","Boxing Day (Observed)","GB",1998 +"1999-01-01","New Year's Day","GB",1999 +"1999-01-02","New Year Holiday [Scotland]","GB",1999 +"1999-01-04","New Year Holiday [Scotland] (Observed)","GB",1999 +"1999-03-17","St. Patrick's Day [Northern Ireland]","GB",1999 +"1999-04-02","Good Friday","GB",1999 +"1999-04-05","Easter Monday [England/Wales/Northern Ireland]","GB",1999 +"1999-05-03","May Day","GB",1999 +"1999-05-31","Spring Bank Holiday","GB",1999 +"1999-07-12","Battle of the Boyne [Northern Ireland]","GB",1999 +"1999-08-02","Summer Bank Holiday [Scotland]","GB",1999 +"1999-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",1999 +"1999-11-30","St. Andrew's Day [Scotland]","GB",1999 +"1999-12-25","Christmas Day","GB",1999 +"1999-12-26","Boxing Day","GB",1999 +"1999-12-27","Christmas Day (Observed)","GB",1999 +"1999-12-28","Boxing Day (Observed)","GB",1999 +"1999-12-31","Millennium Celebrations","GB",1999 +"2000-01-01","New Year's Day","GB",2000 +"2000-01-02","New Year Holiday [Scotland]","GB",2000 +"2000-01-03","New Year's Day (Observed)","GB",2000 +"2000-01-04","New Year Holiday [Scotland] (Observed)","GB",2000 +"2000-03-17","St. Patrick's Day [Northern Ireland]","GB",2000 +"2000-04-21","Good Friday","GB",2000 +"2000-04-24","Easter Monday [England/Wales/Northern Ireland]","GB",2000 +"2000-05-01","May Day","GB",2000 +"2000-05-29","Spring Bank Holiday","GB",2000 +"2000-07-12","Battle of the Boyne [Northern Ireland]","GB",2000 +"2000-08-07","Summer Bank Holiday [Scotland]","GB",2000 +"2000-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2000 +"2000-11-30","St. Andrew's Day [Scotland]","GB",2000 +"2000-12-25","Christmas Day","GB",2000 +"2000-12-26","Boxing Day","GB",2000 +"2001-01-01","New Year's Day","GB",2001 +"2001-01-02","New Year Holiday [Scotland]","GB",2001 +"2001-03-17","St. Patrick's Day [Northern Ireland]","GB",2001 +"2001-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2001 +"2001-04-13","Good Friday","GB",2001 +"2001-04-16","Easter Monday [England/Wales/Northern Ireland]","GB",2001 +"2001-05-07","May Day","GB",2001 +"2001-05-28","Spring Bank Holiday","GB",2001 +"2001-07-12","Battle of the Boyne [Northern Ireland]","GB",2001 +"2001-08-06","Summer Bank Holiday [Scotland]","GB",2001 +"2001-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2001 +"2001-11-30","St. Andrew's Day [Scotland]","GB",2001 +"2001-12-25","Christmas Day","GB",2001 +"2001-12-26","Boxing Day","GB",2001 +"2002-01-01","New Year's Day","GB",2002 +"2002-01-02","New Year Holiday [Scotland]","GB",2002 +"2002-03-17","St. Patrick's Day [Northern Ireland]","GB",2002 +"2002-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",2002 +"2002-03-29","Good Friday","GB",2002 +"2002-04-01","Easter Monday [England/Wales/Northern Ireland]","GB",2002 +"2002-05-06","May Day","GB",2002 +"2002-05-27","Spring Bank Holiday","GB",2002 +"2002-06-03","Golden Jubilee of Elizabeth II","GB",2002 +"2002-07-12","Battle of the Boyne [Northern Ireland]","GB",2002 +"2002-08-05","Summer Bank Holiday [Scotland]","GB",2002 +"2002-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2002 +"2002-11-30","St. Andrew's Day [Scotland]","GB",2002 +"2002-12-25","Christmas Day","GB",2002 +"2002-12-26","Boxing Day","GB",2002 +"2003-01-01","New Year's Day","GB",2003 +"2003-01-02","New Year Holiday [Scotland]","GB",2003 +"2003-03-17","St. Patrick's Day [Northern Ireland]","GB",2003 +"2003-04-18","Good Friday","GB",2003 +"2003-04-21","Easter Monday [England/Wales/Northern Ireland]","GB",2003 +"2003-05-05","May Day","GB",2003 +"2003-05-26","Spring Bank Holiday","GB",2003 +"2003-07-12","Battle of the Boyne [Northern Ireland]","GB",2003 +"2003-08-04","Summer Bank Holiday [Scotland]","GB",2003 +"2003-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2003 +"2003-11-30","St. Andrew's Day [Scotland]","GB",2003 +"2003-12-25","Christmas Day","GB",2003 +"2003-12-26","Boxing Day","GB",2003 +"2004-01-01","New Year's Day","GB",2004 +"2004-01-02","New Year Holiday [Scotland]","GB",2004 +"2004-03-17","St. Patrick's Day [Northern Ireland]","GB",2004 +"2004-04-09","Good Friday","GB",2004 +"2004-04-12","Easter Monday [England/Wales/Northern Ireland]","GB",2004 +"2004-05-03","May Day","GB",2004 +"2004-05-31","Spring Bank Holiday","GB",2004 +"2004-07-12","Battle of the Boyne [Northern Ireland]","GB",2004 +"2004-08-02","Summer Bank Holiday [Scotland]","GB",2004 +"2004-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2004 +"2004-11-30","St. Andrew's Day [Scotland]","GB",2004 +"2004-12-25","Christmas Day","GB",2004 +"2004-12-26","Boxing Day","GB",2004 +"2004-12-27","Christmas Day (Observed)","GB",2004 +"2004-12-28","Boxing Day (Observed)","GB",2004 +"2005-01-01","New Year's Day","GB",2005 +"2005-01-02","New Year Holiday [Scotland]","GB",2005 +"2005-01-03","New Year's Day (Observed)","GB",2005 +"2005-01-04","New Year Holiday [Scotland] (Observed)","GB",2005 +"2005-03-17","St. Patrick's Day [Northern Ireland]","GB",2005 +"2005-03-25","Good Friday","GB",2005 +"2005-03-28","Easter Monday [England/Wales/Northern Ireland]","GB",2005 +"2005-05-02","May Day","GB",2005 +"2005-05-30","Spring Bank Holiday","GB",2005 +"2005-07-12","Battle of the Boyne [Northern Ireland]","GB",2005 +"2005-08-01","Summer Bank Holiday [Scotland]","GB",2005 +"2005-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2005 +"2005-11-30","St. Andrew's Day [Scotland]","GB",2005 +"2005-12-25","Christmas Day","GB",2005 +"2005-12-26","Boxing Day","GB",2005 +"2005-12-27","Christmas Day (Observed)","GB",2005 +"2006-01-01","New Year's Day","GB",2006 +"2006-01-02","New Year Holiday [Scotland]","GB",2006 +"2006-01-02","New Year's Day (Observed)","GB",2006 +"2006-01-03","New Year Holiday [Scotland] (Observed)","GB",2006 +"2006-03-17","St. Patrick's Day [Northern Ireland]","GB",2006 +"2006-04-14","Good Friday","GB",2006 +"2006-04-17","Easter Monday [England/Wales/Northern Ireland]","GB",2006 +"2006-05-01","May Day","GB",2006 +"2006-05-29","Spring Bank Holiday","GB",2006 +"2006-07-12","Battle of the Boyne [Northern Ireland]","GB",2006 +"2006-08-07","Summer Bank Holiday [Scotland]","GB",2006 +"2006-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2006 +"2006-11-30","St. Andrew's Day [Scotland]","GB",2006 +"2006-12-25","Christmas Day","GB",2006 +"2006-12-26","Boxing Day","GB",2006 +"2007-01-01","New Year's Day","GB",2007 +"2007-01-02","New Year Holiday [Scotland]","GB",2007 +"2007-03-17","St. Patrick's Day [Northern Ireland]","GB",2007 +"2007-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2007 +"2007-04-06","Good Friday","GB",2007 +"2007-04-09","Easter Monday [England/Wales/Northern Ireland]","GB",2007 +"2007-05-07","May Day","GB",2007 +"2007-05-28","Spring Bank Holiday","GB",2007 +"2007-07-12","Battle of the Boyne [Northern Ireland]","GB",2007 +"2007-08-06","Summer Bank Holiday [Scotland]","GB",2007 +"2007-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2007 +"2007-11-30","St. Andrew's Day [Scotland]","GB",2007 +"2007-12-25","Christmas Day","GB",2007 +"2007-12-26","Boxing Day","GB",2007 +"2008-01-01","New Year's Day","GB",2008 +"2008-01-02","New Year Holiday [Scotland]","GB",2008 +"2008-03-17","St. Patrick's Day [Northern Ireland]","GB",2008 +"2008-03-21","Good Friday","GB",2008 +"2008-03-24","Easter Monday [England/Wales/Northern Ireland]","GB",2008 +"2008-05-05","May Day","GB",2008 +"2008-05-26","Spring Bank Holiday","GB",2008 +"2008-07-12","Battle of the Boyne [Northern Ireland]","GB",2008 +"2008-08-04","Summer Bank Holiday [Scotland]","GB",2008 +"2008-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2008 +"2008-11-30","St. Andrew's Day [Scotland]","GB",2008 +"2008-12-25","Christmas Day","GB",2008 +"2008-12-26","Boxing Day","GB",2008 +"2009-01-01","New Year's Day","GB",2009 +"2009-01-02","New Year Holiday [Scotland]","GB",2009 +"2009-03-17","St. Patrick's Day [Northern Ireland]","GB",2009 +"2009-04-10","Good Friday","GB",2009 +"2009-04-13","Easter Monday [England/Wales/Northern Ireland]","GB",2009 +"2009-05-04","May Day","GB",2009 +"2009-05-25","Spring Bank Holiday","GB",2009 +"2009-07-12","Battle of the Boyne [Northern Ireland]","GB",2009 +"2009-08-03","Summer Bank Holiday [Scotland]","GB",2009 +"2009-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2009 +"2009-11-30","St. Andrew's Day [Scotland]","GB",2009 +"2009-12-25","Christmas Day","GB",2009 +"2009-12-26","Boxing Day","GB",2009 +"2009-12-28","Boxing Day (Observed)","GB",2009 +"2010-01-01","New Year's Day","GB",2010 +"2010-01-02","New Year Holiday [Scotland]","GB",2010 +"2010-01-04","New Year Holiday [Scotland] (Observed)","GB",2010 +"2010-03-17","St. Patrick's Day [Northern Ireland]","GB",2010 +"2010-04-02","Good Friday","GB",2010 +"2010-04-05","Easter Monday [England/Wales/Northern Ireland]","GB",2010 +"2010-05-03","May Day","GB",2010 +"2010-05-31","Spring Bank Holiday","GB",2010 +"2010-07-12","Battle of the Boyne [Northern Ireland]","GB",2010 +"2010-08-02","Summer Bank Holiday [Scotland]","GB",2010 +"2010-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2010 +"2010-11-30","St. Andrew's Day [Scotland]","GB",2010 +"2010-12-25","Christmas Day","GB",2010 +"2010-12-26","Boxing Day","GB",2010 +"2010-12-27","Christmas Day (Observed)","GB",2010 +"2010-12-28","Boxing Day (Observed)","GB",2010 +"2011-01-01","New Year's Day","GB",2011 +"2011-01-02","New Year Holiday [Scotland]","GB",2011 +"2011-01-03","New Year's Day (Observed)","GB",2011 +"2011-01-04","New Year Holiday [Scotland] (Observed)","GB",2011 +"2011-03-17","St. Patrick's Day [Northern Ireland]","GB",2011 +"2011-04-22","Good Friday","GB",2011 +"2011-04-25","Easter Monday [England/Wales/Northern Ireland]","GB",2011 +"2011-04-29","Wedding of William and Catherine","GB",2011 +"2011-05-02","May Day","GB",2011 +"2011-05-30","Spring Bank Holiday","GB",2011 +"2011-07-12","Battle of the Boyne [Northern Ireland]","GB",2011 +"2011-08-01","Summer Bank Holiday [Scotland]","GB",2011 +"2011-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2011 +"2011-11-30","St. Andrew's Day [Scotland]","GB",2011 +"2011-12-25","Christmas Day","GB",2011 +"2011-12-26","Boxing Day","GB",2011 +"2011-12-27","Christmas Day (Observed)","GB",2011 +"2012-01-01","New Year's Day","GB",2012 +"2012-01-02","New Year Holiday [Scotland]","GB",2012 +"2012-01-02","New Year's Day (Observed)","GB",2012 +"2012-01-03","New Year Holiday [Scotland] (Observed)","GB",2012 +"2012-03-17","St. Patrick's Day [Northern Ireland]","GB",2012 +"2012-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2012 +"2012-04-06","Good Friday","GB",2012 +"2012-04-09","Easter Monday [England/Wales/Northern Ireland]","GB",2012 +"2012-05-07","May Day","GB",2012 +"2012-06-04","Spring Bank Holiday","GB",2012 +"2012-06-05","Diamond Jubilee of Elizabeth II","GB",2012 +"2012-07-12","Battle of the Boyne [Northern Ireland]","GB",2012 +"2012-08-06","Summer Bank Holiday [Scotland]","GB",2012 +"2012-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2012 +"2012-11-30","St. Andrew's Day [Scotland]","GB",2012 +"2012-12-25","Christmas Day","GB",2012 +"2012-12-26","Boxing Day","GB",2012 +"2013-01-01","New Year's Day","GB",2013 +"2013-01-02","New Year Holiday [Scotland]","GB",2013 +"2013-03-17","St. Patrick's Day [Northern Ireland]","GB",2013 +"2013-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",2013 +"2013-03-29","Good Friday","GB",2013 +"2013-04-01","Easter Monday [England/Wales/Northern Ireland]","GB",2013 +"2013-05-06","May Day","GB",2013 +"2013-05-27","Spring Bank Holiday","GB",2013 +"2013-07-12","Battle of the Boyne [Northern Ireland]","GB",2013 +"2013-08-05","Summer Bank Holiday [Scotland]","GB",2013 +"2013-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2013 +"2013-11-30","St. Andrew's Day [Scotland]","GB",2013 +"2013-12-25","Christmas Day","GB",2013 +"2013-12-26","Boxing Day","GB",2013 +"2014-01-01","New Year's Day","GB",2014 +"2014-01-02","New Year Holiday [Scotland]","GB",2014 +"2014-03-17","St. Patrick's Day [Northern Ireland]","GB",2014 +"2014-04-18","Good Friday","GB",2014 +"2014-04-21","Easter Monday [England/Wales/Northern Ireland]","GB",2014 +"2014-05-05","May Day","GB",2014 +"2014-05-26","Spring Bank Holiday","GB",2014 +"2014-07-12","Battle of the Boyne [Northern Ireland]","GB",2014 +"2014-08-04","Summer Bank Holiday [Scotland]","GB",2014 +"2014-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2014 +"2014-11-30","St. Andrew's Day [Scotland]","GB",2014 +"2014-12-25","Christmas Day","GB",2014 +"2014-12-26","Boxing Day","GB",2014 +"2015-01-01","New Year's Day","GB",2015 +"2015-01-02","New Year Holiday [Scotland]","GB",2015 +"2015-03-17","St. Patrick's Day [Northern Ireland]","GB",2015 +"2015-04-03","Good Friday","GB",2015 +"2015-04-06","Easter Monday [England/Wales/Northern Ireland]","GB",2015 +"2015-05-04","May Day","GB",2015 +"2015-05-25","Spring Bank Holiday","GB",2015 +"2015-07-12","Battle of the Boyne [Northern Ireland]","GB",2015 +"2015-08-03","Summer Bank Holiday [Scotland]","GB",2015 +"2015-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2015 +"2015-11-30","St. Andrew's Day [Scotland]","GB",2015 +"2015-12-25","Christmas Day","GB",2015 +"2015-12-26","Boxing Day","GB",2015 +"2015-12-28","Boxing Day (Observed)","GB",2015 +"2016-01-01","New Year's Day","GB",2016 +"2016-01-02","New Year Holiday [Scotland]","GB",2016 +"2016-01-04","New Year Holiday [Scotland] (Observed)","GB",2016 +"2016-03-17","St. Patrick's Day [Northern Ireland]","GB",2016 +"2016-03-25","Good Friday","GB",2016 +"2016-03-28","Easter Monday [England/Wales/Northern Ireland]","GB",2016 +"2016-05-02","May Day","GB",2016 +"2016-05-30","Spring Bank Holiday","GB",2016 +"2016-07-12","Battle of the Boyne [Northern Ireland]","GB",2016 +"2016-08-01","Summer Bank Holiday [Scotland]","GB",2016 +"2016-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2016 +"2016-11-30","St. Andrew's Day [Scotland]","GB",2016 +"2016-12-25","Christmas Day","GB",2016 +"2016-12-26","Boxing Day","GB",2016 +"2016-12-27","Christmas Day (Observed)","GB",2016 +"2017-01-01","New Year's Day","GB",2017 +"2017-01-02","New Year Holiday [Scotland]","GB",2017 +"2017-01-02","New Year's Day (Observed)","GB",2017 +"2017-01-03","New Year Holiday [Scotland] (Observed)","GB",2017 +"2017-03-17","St. Patrick's Day [Northern Ireland]","GB",2017 +"2017-04-14","Good Friday","GB",2017 +"2017-04-17","Easter Monday [England/Wales/Northern Ireland]","GB",2017 +"2017-05-01","May Day","GB",2017 +"2017-05-29","Spring Bank Holiday","GB",2017 +"2017-07-12","Battle of the Boyne [Northern Ireland]","GB",2017 +"2017-08-07","Summer Bank Holiday [Scotland]","GB",2017 +"2017-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2017 +"2017-11-30","St. Andrew's Day [Scotland]","GB",2017 +"2017-12-25","Christmas Day","GB",2017 +"2017-12-26","Boxing Day","GB",2017 +"2018-01-01","New Year's Day","GB",2018 +"2018-01-02","New Year Holiday [Scotland]","GB",2018 +"2018-03-17","St. Patrick's Day [Northern Ireland]","GB",2018 +"2018-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2018 +"2018-03-30","Good Friday","GB",2018 +"2018-04-02","Easter Monday [England/Wales/Northern Ireland]","GB",2018 +"2018-05-07","May Day","GB",2018 +"2018-05-28","Spring Bank Holiday","GB",2018 +"2018-07-12","Battle of the Boyne [Northern Ireland]","GB",2018 +"2018-08-06","Summer Bank Holiday [Scotland]","GB",2018 +"2018-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2018 +"2018-11-30","St. Andrew's Day [Scotland]","GB",2018 +"2018-12-25","Christmas Day","GB",2018 +"2018-12-26","Boxing Day","GB",2018 +"2019-01-01","New Year's Day","GB",2019 +"2019-01-02","New Year Holiday [Scotland]","GB",2019 +"2019-03-17","St. Patrick's Day [Northern Ireland]","GB",2019 +"2019-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",2019 +"2019-04-19","Good Friday","GB",2019 +"2019-04-22","Easter Monday [England/Wales/Northern Ireland]","GB",2019 +"2019-05-06","May Day","GB",2019 +"2019-05-27","Spring Bank Holiday","GB",2019 +"2019-07-12","Battle of the Boyne [Northern Ireland]","GB",2019 +"2019-08-05","Summer Bank Holiday [Scotland]","GB",2019 +"2019-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2019 +"2019-11-30","St. Andrew's Day [Scotland]","GB",2019 +"2019-12-25","Christmas Day","GB",2019 +"2019-12-26","Boxing Day","GB",2019 +"2020-01-01","New Year's Day","GB",2020 +"2020-01-02","New Year Holiday [Scotland]","GB",2020 +"2020-03-17","St. Patrick's Day [Northern Ireland]","GB",2020 +"2020-04-10","Good Friday","GB",2020 +"2020-04-13","Easter Monday [England/Wales/Northern Ireland]","GB",2020 +"2020-05-08","May Day","GB",2020 +"2020-05-25","Spring Bank Holiday","GB",2020 +"2020-07-12","Battle of the Boyne [Northern Ireland]","GB",2020 +"2020-08-03","Summer Bank Holiday [Scotland]","GB",2020 +"2020-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2020 +"2020-11-30","St. Andrew's Day [Scotland]","GB",2020 +"2020-12-25","Christmas Day","GB",2020 +"2020-12-26","Boxing Day","GB",2020 +"2020-12-28","Boxing Day (Observed)","GB",2020 +"2021-01-01","New Year's Day","GB",2021 +"2021-01-02","New Year Holiday [Scotland]","GB",2021 +"2021-01-04","New Year Holiday [Scotland] (Observed)","GB",2021 +"2021-03-17","St. Patrick's Day [Northern Ireland]","GB",2021 +"2021-04-02","Good Friday","GB",2021 +"2021-04-05","Easter Monday [England/Wales/Northern Ireland]","GB",2021 +"2021-05-03","May Day","GB",2021 +"2021-05-31","Spring Bank Holiday","GB",2021 +"2021-07-12","Battle of the Boyne [Northern Ireland]","GB",2021 +"2021-08-02","Summer Bank Holiday [Scotland]","GB",2021 +"2021-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2021 +"2021-11-30","St. Andrew's Day [Scotland]","GB",2021 +"2021-12-25","Christmas Day","GB",2021 +"2021-12-26","Boxing Day","GB",2021 +"2021-12-27","Christmas Day (Observed)","GB",2021 +"2021-12-28","Boxing Day (Observed)","GB",2021 +"2022-01-01","New Year's Day","GB",2022 +"2022-01-02","New Year Holiday [Scotland]","GB",2022 +"2022-01-03","New Year's Day (Observed)","GB",2022 +"2022-01-04","New Year Holiday [Scotland] (Observed)","GB",2022 +"2022-03-17","St. Patrick's Day [Northern Ireland]","GB",2022 +"2022-04-15","Good Friday","GB",2022 +"2022-04-18","Easter Monday [England/Wales/Northern Ireland]","GB",2022 +"2022-05-02","May Day","GB",2022 +"2022-06-02","Spring Bank Holiday","GB",2022 +"2022-06-03","Platinum Jubilee of Elizabeth II","GB",2022 +"2022-07-12","Battle of the Boyne [Northern Ireland]","GB",2022 +"2022-08-01","Summer Bank Holiday [Scotland]","GB",2022 +"2022-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2022 +"2022-09-19","State Funeral of Queen Elizabeth II","GB",2022 +"2022-11-30","St. Andrew's Day [Scotland]","GB",2022 +"2022-12-25","Christmas Day","GB",2022 +"2022-12-26","Boxing Day","GB",2022 +"2022-12-27","Christmas Day (Observed)","GB",2022 +"2023-01-01","New Year's Day","GB",2023 +"2023-01-02","New Year Holiday [Scotland]","GB",2023 +"2023-01-02","New Year's Day (Observed)","GB",2023 +"2023-01-03","New Year Holiday [Scotland] (Observed)","GB",2023 +"2023-03-17","St. Patrick's Day [Northern Ireland]","GB",2023 +"2023-04-07","Good Friday","GB",2023 +"2023-04-10","Easter Monday [England/Wales/Northern Ireland]","GB",2023 +"2023-05-01","May Day","GB",2023 +"2023-05-08","Coronation of Charles III","GB",2023 +"2023-05-29","Spring Bank Holiday","GB",2023 +"2023-07-12","Battle of the Boyne [Northern Ireland]","GB",2023 +"2023-08-07","Summer Bank Holiday [Scotland]","GB",2023 +"2023-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2023 +"2023-11-30","St. Andrew's Day [Scotland]","GB",2023 +"2023-12-25","Christmas Day","GB",2023 +"2023-12-26","Boxing Day","GB",2023 +"2024-01-01","New Year's Day","GB",2024 +"2024-01-02","New Year Holiday [Scotland]","GB",2024 +"2024-03-17","St. Patrick's Day [Northern Ireland]","GB",2024 +"2024-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",2024 +"2024-03-29","Good Friday","GB",2024 +"2024-04-01","Easter Monday [England/Wales/Northern Ireland]","GB",2024 +"2024-05-06","May Day","GB",2024 +"2024-05-27","Spring Bank Holiday","GB",2024 +"2024-07-12","Battle of the Boyne [Northern Ireland]","GB",2024 +"2024-08-05","Summer Bank Holiday [Scotland]","GB",2024 +"2024-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2024 +"2024-11-30","St. Andrew's Day [Scotland]","GB",2024 +"2024-12-25","Christmas Day","GB",2024 +"2024-12-26","Boxing Day","GB",2024 +"2025-01-01","New Year's Day","GB",2025 +"2025-01-02","New Year Holiday [Scotland]","GB",2025 +"2025-03-17","St. Patrick's Day [Northern Ireland]","GB",2025 +"2025-04-18","Good Friday","GB",2025 +"2025-04-21","Easter Monday [England/Wales/Northern Ireland]","GB",2025 +"2025-05-05","May Day","GB",2025 +"2025-05-26","Spring Bank Holiday","GB",2025 +"2025-07-12","Battle of the Boyne [Northern Ireland]","GB",2025 +"2025-08-04","Summer Bank Holiday [Scotland]","GB",2025 +"2025-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2025 +"2025-11-30","St. Andrew's Day [Scotland]","GB",2025 +"2025-12-25","Christmas Day","GB",2025 +"2025-12-26","Boxing Day","GB",2025 +"2026-01-01","New Year's Day","GB",2026 +"2026-01-02","New Year Holiday [Scotland]","GB",2026 +"2026-03-17","St. Patrick's Day [Northern Ireland]","GB",2026 +"2026-04-03","Good Friday","GB",2026 +"2026-04-06","Easter Monday [England/Wales/Northern Ireland]","GB",2026 +"2026-05-04","May Day","GB",2026 +"2026-05-25","Spring Bank Holiday","GB",2026 +"2026-07-12","Battle of the Boyne [Northern Ireland]","GB",2026 +"2026-08-03","Summer Bank Holiday [Scotland]","GB",2026 +"2026-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2026 +"2026-11-30","St. Andrew's Day [Scotland]","GB",2026 +"2026-12-25","Christmas Day","GB",2026 +"2026-12-26","Boxing Day","GB",2026 +"2026-12-28","Boxing Day (Observed)","GB",2026 +"2027-01-01","New Year's Day","GB",2027 +"2027-01-02","New Year Holiday [Scotland]","GB",2027 +"2027-01-04","New Year Holiday [Scotland] (Observed)","GB",2027 +"2027-03-17","St. Patrick's Day [Northern Ireland]","GB",2027 +"2027-03-26","Good Friday","GB",2027 +"2027-03-29","Easter Monday [England/Wales/Northern Ireland]","GB",2027 +"2027-05-03","May Day","GB",2027 +"2027-05-31","Spring Bank Holiday","GB",2027 +"2027-07-12","Battle of the Boyne [Northern Ireland]","GB",2027 +"2027-08-02","Summer Bank Holiday [Scotland]","GB",2027 +"2027-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2027 +"2027-11-30","St. Andrew's Day [Scotland]","GB",2027 +"2027-12-25","Christmas Day","GB",2027 +"2027-12-26","Boxing Day","GB",2027 +"2027-12-27","Christmas Day (Observed)","GB",2027 +"2027-12-28","Boxing Day (Observed)","GB",2027 +"2028-01-01","New Year's Day","GB",2028 +"2028-01-02","New Year Holiday [Scotland]","GB",2028 +"2028-01-03","New Year's Day (Observed)","GB",2028 +"2028-01-04","New Year Holiday [Scotland] (Observed)","GB",2028 +"2028-03-17","St. Patrick's Day [Northern Ireland]","GB",2028 +"2028-04-14","Good Friday","GB",2028 +"2028-04-17","Easter Monday [England/Wales/Northern Ireland]","GB",2028 +"2028-05-01","May Day","GB",2028 +"2028-05-29","Spring Bank Holiday","GB",2028 +"2028-07-12","Battle of the Boyne [Northern Ireland]","GB",2028 +"2028-08-07","Summer Bank Holiday [Scotland]","GB",2028 +"2028-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2028 +"2028-11-30","St. Andrew's Day [Scotland]","GB",2028 +"2028-12-25","Christmas Day","GB",2028 +"2028-12-26","Boxing Day","GB",2028 +"2029-01-01","New Year's Day","GB",2029 +"2029-01-02","New Year Holiday [Scotland]","GB",2029 +"2029-03-17","St. Patrick's Day [Northern Ireland]","GB",2029 +"2029-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2029 +"2029-03-30","Good Friday","GB",2029 +"2029-04-02","Easter Monday [England/Wales/Northern Ireland]","GB",2029 +"2029-05-07","May Day","GB",2029 +"2029-05-28","Spring Bank Holiday","GB",2029 +"2029-07-12","Battle of the Boyne [Northern Ireland]","GB",2029 +"2029-08-06","Summer Bank Holiday [Scotland]","GB",2029 +"2029-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2029 +"2029-11-30","St. Andrew's Day [Scotland]","GB",2029 +"2029-12-25","Christmas Day","GB",2029 +"2029-12-26","Boxing Day","GB",2029 +"2030-01-01","New Year's Day","GB",2030 +"2030-01-02","New Year Holiday [Scotland]","GB",2030 +"2030-03-17","St. Patrick's Day [Northern Ireland]","GB",2030 +"2030-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",2030 +"2030-04-19","Good Friday","GB",2030 +"2030-04-22","Easter Monday [England/Wales/Northern Ireland]","GB",2030 +"2030-05-06","May Day","GB",2030 +"2030-05-27","Spring Bank Holiday","GB",2030 +"2030-07-12","Battle of the Boyne [Northern Ireland]","GB",2030 +"2030-08-05","Summer Bank Holiday [Scotland]","GB",2030 +"2030-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2030 +"2030-11-30","St. Andrew's Day [Scotland]","GB",2030 +"2030-12-25","Christmas Day","GB",2030 +"2030-12-26","Boxing Day","GB",2030 +"2031-01-01","New Year's Day","GB",2031 +"2031-01-02","New Year Holiday [Scotland]","GB",2031 +"2031-03-17","St. Patrick's Day [Northern Ireland]","GB",2031 +"2031-04-11","Good Friday","GB",2031 +"2031-04-14","Easter Monday [England/Wales/Northern Ireland]","GB",2031 +"2031-05-05","May Day","GB",2031 +"2031-05-26","Spring Bank Holiday","GB",2031 +"2031-07-12","Battle of the Boyne [Northern Ireland]","GB",2031 +"2031-08-04","Summer Bank Holiday [Scotland]","GB",2031 +"2031-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2031 +"2031-11-30","St. Andrew's Day [Scotland]","GB",2031 +"2031-12-25","Christmas Day","GB",2031 +"2031-12-26","Boxing Day","GB",2031 +"2032-01-01","New Year's Day","GB",2032 +"2032-01-02","New Year Holiday [Scotland]","GB",2032 +"2032-03-17","St. Patrick's Day [Northern Ireland]","GB",2032 +"2032-03-26","Good Friday","GB",2032 +"2032-03-29","Easter Monday [England/Wales/Northern Ireland]","GB",2032 +"2032-05-03","May Day","GB",2032 +"2032-05-31","Spring Bank Holiday","GB",2032 +"2032-07-12","Battle of the Boyne [Northern Ireland]","GB",2032 +"2032-08-02","Summer Bank Holiday [Scotland]","GB",2032 +"2032-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2032 +"2032-11-30","St. Andrew's Day [Scotland]","GB",2032 +"2032-12-25","Christmas Day","GB",2032 +"2032-12-26","Boxing Day","GB",2032 +"2032-12-27","Christmas Day (Observed)","GB",2032 +"2032-12-28","Boxing Day (Observed)","GB",2032 +"2033-01-01","New Year's Day","GB",2033 +"2033-01-02","New Year Holiday [Scotland]","GB",2033 +"2033-01-03","New Year's Day (Observed)","GB",2033 +"2033-01-04","New Year Holiday [Scotland] (Observed)","GB",2033 +"2033-03-17","St. Patrick's Day [Northern Ireland]","GB",2033 +"2033-04-15","Good Friday","GB",2033 +"2033-04-18","Easter Monday [England/Wales/Northern Ireland]","GB",2033 +"2033-05-02","May Day","GB",2033 +"2033-05-30","Spring Bank Holiday","GB",2033 +"2033-07-12","Battle of the Boyne [Northern Ireland]","GB",2033 +"2033-08-01","Summer Bank Holiday [Scotland]","GB",2033 +"2033-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2033 +"2033-11-30","St. Andrew's Day [Scotland]","GB",2033 +"2033-12-25","Christmas Day","GB",2033 +"2033-12-26","Boxing Day","GB",2033 +"2033-12-27","Christmas Day (Observed)","GB",2033 +"2034-01-01","New Year's Day","GB",2034 +"2034-01-02","New Year Holiday [Scotland]","GB",2034 +"2034-01-02","New Year's Day (Observed)","GB",2034 +"2034-01-03","New Year Holiday [Scotland] (Observed)","GB",2034 +"2034-03-17","St. Patrick's Day [Northern Ireland]","GB",2034 +"2034-04-07","Good Friday","GB",2034 +"2034-04-10","Easter Monday [England/Wales/Northern Ireland]","GB",2034 +"2034-05-01","May Day","GB",2034 +"2034-05-29","Spring Bank Holiday","GB",2034 +"2034-07-12","Battle of the Boyne [Northern Ireland]","GB",2034 +"2034-08-07","Summer Bank Holiday [Scotland]","GB",2034 +"2034-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2034 +"2034-11-30","St. Andrew's Day [Scotland]","GB",2034 +"2034-12-25","Christmas Day","GB",2034 +"2034-12-26","Boxing Day","GB",2034 +"2035-01-01","New Year's Day","GB",2035 +"2035-01-02","New Year Holiday [Scotland]","GB",2035 +"2035-03-17","St. Patrick's Day [Northern Ireland]","GB",2035 +"2035-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2035 +"2035-03-23","Good Friday","GB",2035 +"2035-03-26","Easter Monday [England/Wales/Northern Ireland]","GB",2035 +"2035-05-07","May Day","GB",2035 +"2035-05-28","Spring Bank Holiday","GB",2035 +"2035-07-12","Battle of the Boyne [Northern Ireland]","GB",2035 +"2035-08-06","Summer Bank Holiday [Scotland]","GB",2035 +"2035-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2035 +"2035-11-30","St. Andrew's Day [Scotland]","GB",2035 +"2035-12-25","Christmas Day","GB",2035 +"2035-12-26","Boxing Day","GB",2035 +"2036-01-01","New Year's Day","GB",2036 +"2036-01-02","New Year Holiday [Scotland]","GB",2036 +"2036-03-17","St. Patrick's Day [Northern Ireland]","GB",2036 +"2036-04-11","Good Friday","GB",2036 +"2036-04-14","Easter Monday [England/Wales/Northern Ireland]","GB",2036 +"2036-05-05","May Day","GB",2036 +"2036-05-26","Spring Bank Holiday","GB",2036 +"2036-07-12","Battle of the Boyne [Northern Ireland]","GB",2036 +"2036-08-04","Summer Bank Holiday [Scotland]","GB",2036 +"2036-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2036 +"2036-11-30","St. Andrew's Day [Scotland]","GB",2036 +"2036-12-25","Christmas Day","GB",2036 +"2036-12-26","Boxing Day","GB",2036 +"2037-01-01","New Year's Day","GB",2037 +"2037-01-02","New Year Holiday [Scotland]","GB",2037 +"2037-03-17","St. Patrick's Day [Northern Ireland]","GB",2037 +"2037-04-03","Good Friday","GB",2037 +"2037-04-06","Easter Monday [England/Wales/Northern Ireland]","GB",2037 +"2037-05-04","May Day","GB",2037 +"2037-05-25","Spring Bank Holiday","GB",2037 +"2037-07-12","Battle of the Boyne [Northern Ireland]","GB",2037 +"2037-08-03","Summer Bank Holiday [Scotland]","GB",2037 +"2037-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2037 +"2037-11-30","St. Andrew's Day [Scotland]","GB",2037 +"2037-12-25","Christmas Day","GB",2037 +"2037-12-26","Boxing Day","GB",2037 +"2037-12-28","Boxing Day (Observed)","GB",2037 +"2038-01-01","New Year's Day","GB",2038 +"2038-01-02","New Year Holiday [Scotland]","GB",2038 +"2038-01-04","New Year Holiday [Scotland] (Observed)","GB",2038 +"2038-03-17","St. Patrick's Day [Northern Ireland]","GB",2038 +"2038-04-23","Good Friday","GB",2038 +"2038-04-26","Easter Monday [England/Wales/Northern Ireland]","GB",2038 +"2038-05-03","May Day","GB",2038 +"2038-05-31","Spring Bank Holiday","GB",2038 +"2038-07-12","Battle of the Boyne [Northern Ireland]","GB",2038 +"2038-08-02","Summer Bank Holiday [Scotland]","GB",2038 +"2038-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2038 +"2038-11-30","St. Andrew's Day [Scotland]","GB",2038 +"2038-12-25","Christmas Day","GB",2038 +"2038-12-26","Boxing Day","GB",2038 +"2038-12-27","Christmas Day (Observed)","GB",2038 +"2038-12-28","Boxing Day (Observed)","GB",2038 +"2039-01-01","New Year's Day","GB",2039 +"2039-01-02","New Year Holiday [Scotland]","GB",2039 +"2039-01-03","New Year's Day (Observed)","GB",2039 +"2039-01-04","New Year Holiday [Scotland] (Observed)","GB",2039 +"2039-03-17","St. Patrick's Day [Northern Ireland]","GB",2039 +"2039-04-08","Good Friday","GB",2039 +"2039-04-11","Easter Monday [England/Wales/Northern Ireland]","GB",2039 +"2039-05-02","May Day","GB",2039 +"2039-05-30","Spring Bank Holiday","GB",2039 +"2039-07-12","Battle of the Boyne [Northern Ireland]","GB",2039 +"2039-08-01","Summer Bank Holiday [Scotland]","GB",2039 +"2039-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2039 +"2039-11-30","St. Andrew's Day [Scotland]","GB",2039 +"2039-12-25","Christmas Day","GB",2039 +"2039-12-26","Boxing Day","GB",2039 +"2039-12-27","Christmas Day (Observed)","GB",2039 +"2040-01-01","New Year's Day","GB",2040 +"2040-01-02","New Year Holiday [Scotland]","GB",2040 +"2040-01-02","New Year's Day (Observed)","GB",2040 +"2040-01-03","New Year Holiday [Scotland] (Observed)","GB",2040 +"2040-03-17","St. Patrick's Day [Northern Ireland]","GB",2040 +"2040-03-19","St. Patrick's Day [Northern Ireland] (Observed)","GB",2040 +"2040-03-30","Good Friday","GB",2040 +"2040-04-02","Easter Monday [England/Wales/Northern Ireland]","GB",2040 +"2040-05-07","May Day","GB",2040 +"2040-05-28","Spring Bank Holiday","GB",2040 +"2040-07-12","Battle of the Boyne [Northern Ireland]","GB",2040 +"2040-08-06","Summer Bank Holiday [Scotland]","GB",2040 +"2040-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2040 +"2040-11-30","St. Andrew's Day [Scotland]","GB",2040 +"2040-12-25","Christmas Day","GB",2040 +"2040-12-26","Boxing Day","GB",2040 +"2041-01-01","New Year's Day","GB",2041 +"2041-01-02","New Year Holiday [Scotland]","GB",2041 +"2041-03-17","St. Patrick's Day [Northern Ireland]","GB",2041 +"2041-03-18","St. Patrick's Day [Northern Ireland] (Observed)","GB",2041 +"2041-04-19","Good Friday","GB",2041 +"2041-04-22","Easter Monday [England/Wales/Northern Ireland]","GB",2041 +"2041-05-06","May Day","GB",2041 +"2041-05-27","Spring Bank Holiday","GB",2041 +"2041-07-12","Battle of the Boyne [Northern Ireland]","GB",2041 +"2041-08-05","Summer Bank Holiday [Scotland]","GB",2041 +"2041-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2041 +"2041-11-30","St. Andrew's Day [Scotland]","GB",2041 +"2041-12-25","Christmas Day","GB",2041 +"2041-12-26","Boxing Day","GB",2041 +"2042-01-01","New Year's Day","GB",2042 +"2042-01-02","New Year Holiday [Scotland]","GB",2042 +"2042-03-17","St. Patrick's Day [Northern Ireland]","GB",2042 +"2042-04-04","Good Friday","GB",2042 +"2042-04-07","Easter Monday [England/Wales/Northern Ireland]","GB",2042 +"2042-05-05","May Day","GB",2042 +"2042-05-26","Spring Bank Holiday","GB",2042 +"2042-07-12","Battle of the Boyne [Northern Ireland]","GB",2042 +"2042-08-04","Summer Bank Holiday [Scotland]","GB",2042 +"2042-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2042 +"2042-11-30","St. Andrew's Day [Scotland]","GB",2042 +"2042-12-25","Christmas Day","GB",2042 +"2042-12-26","Boxing Day","GB",2042 +"2043-01-01","New Year's Day","GB",2043 +"2043-01-02","New Year Holiday [Scotland]","GB",2043 +"2043-03-17","St. Patrick's Day [Northern Ireland]","GB",2043 +"2043-03-27","Good Friday","GB",2043 +"2043-03-30","Easter Monday [England/Wales/Northern Ireland]","GB",2043 +"2043-05-04","May Day","GB",2043 +"2043-05-25","Spring Bank Holiday","GB",2043 +"2043-07-12","Battle of the Boyne [Northern Ireland]","GB",2043 +"2043-08-03","Summer Bank Holiday [Scotland]","GB",2043 +"2043-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2043 +"2043-11-30","St. Andrew's Day [Scotland]","GB",2043 +"2043-12-25","Christmas Day","GB",2043 +"2043-12-26","Boxing Day","GB",2043 +"2043-12-28","Boxing Day (Observed)","GB",2043 +"2044-01-01","New Year's Day","GB",2044 +"2044-01-02","New Year Holiday [Scotland]","GB",2044 +"2044-01-04","New Year Holiday [Scotland] (Observed)","GB",2044 +"2044-03-17","St. Patrick's Day [Northern Ireland]","GB",2044 +"2044-04-15","Good Friday","GB",2044 +"2044-04-18","Easter Monday [England/Wales/Northern Ireland]","GB",2044 +"2044-05-02","May Day","GB",2044 +"2044-05-30","Spring Bank Holiday","GB",2044 +"2044-07-12","Battle of the Boyne [Northern Ireland]","GB",2044 +"2044-08-01","Summer Bank Holiday [Scotland]","GB",2044 +"2044-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","GB",2044 +"2044-11-30","St. Andrew's Day [Scotland]","GB",2044 +"2044-12-25","Christmas Day","GB",2044 +"2044-12-26","Boxing Day","GB",2044 +"2044-12-27","Christmas Day (Observed)","GB",2044 +"1995-01-01","New Year's Day","GE",1995 +"1995-01-02","New Year's Day","GE",1995 +"1995-01-07","Orthodox Christmas Day","GE",1995 +"1995-01-19","Epiphany Day","GE",1995 +"1995-03-03","Mother's Day","GE",1995 +"1995-03-08","International Women's ay","GE",1995 +"1995-04-09","National Unity Day","GE",1995 +"1995-04-21","Orthodox Good Friday","GE",1995 +"1995-04-22","Orthodox Holy Saturday","GE",1995 +"1995-04-23","Orthodox Easter Sunday","GE",1995 +"1995-04-24","Orthodox Easter Monday","GE",1995 +"1995-05-09","Day of Victory over Fascism","GE",1995 +"1995-05-12","St. Andrew's Day","GE",1995 +"1995-05-26","Independence Day","GE",1995 +"1995-08-28","Saint Mary's Day","GE",1995 +"1995-10-14","Day of Svetitskhoveli Cathedral","GE",1995 +"1995-11-23","Saint George's Day","GE",1995 +"1996-01-01","New Year's Day","GE",1996 +"1996-01-02","New Year's Day","GE",1996 +"1996-01-07","Orthodox Christmas Day","GE",1996 +"1996-01-19","Epiphany Day","GE",1996 +"1996-03-03","Mother's Day","GE",1996 +"1996-03-08","International Women's ay","GE",1996 +"1996-04-09","National Unity Day","GE",1996 +"1996-04-12","Orthodox Good Friday","GE",1996 +"1996-04-13","Orthodox Holy Saturday","GE",1996 +"1996-04-14","Orthodox Easter Sunday","GE",1996 +"1996-04-15","Orthodox Easter Monday","GE",1996 +"1996-05-09","Day of Victory over Fascism","GE",1996 +"1996-05-12","St. Andrew's Day","GE",1996 +"1996-05-26","Independence Day","GE",1996 +"1996-08-28","Saint Mary's Day","GE",1996 +"1996-10-14","Day of Svetitskhoveli Cathedral","GE",1996 +"1996-11-23","Saint George's Day","GE",1996 +"1997-01-01","New Year's Day","GE",1997 +"1997-01-02","New Year's Day","GE",1997 +"1997-01-07","Orthodox Christmas Day","GE",1997 +"1997-01-19","Epiphany Day","GE",1997 +"1997-03-03","Mother's Day","GE",1997 +"1997-03-08","International Women's ay","GE",1997 +"1997-04-09","National Unity Day","GE",1997 +"1997-04-25","Orthodox Good Friday","GE",1997 +"1997-04-26","Orthodox Holy Saturday","GE",1997 +"1997-04-27","Orthodox Easter Sunday","GE",1997 +"1997-04-28","Orthodox Easter Monday","GE",1997 +"1997-05-09","Day of Victory over Fascism","GE",1997 +"1997-05-12","St. Andrew's Day","GE",1997 +"1997-05-26","Independence Day","GE",1997 +"1997-08-28","Saint Mary's Day","GE",1997 +"1997-10-14","Day of Svetitskhoveli Cathedral","GE",1997 +"1997-11-23","Saint George's Day","GE",1997 +"1998-01-01","New Year's Day","GE",1998 +"1998-01-02","New Year's Day","GE",1998 +"1998-01-07","Orthodox Christmas Day","GE",1998 +"1998-01-19","Epiphany Day","GE",1998 +"1998-03-03","Mother's Day","GE",1998 +"1998-03-08","International Women's ay","GE",1998 +"1998-04-09","National Unity Day","GE",1998 +"1998-04-17","Orthodox Good Friday","GE",1998 +"1998-04-18","Orthodox Holy Saturday","GE",1998 +"1998-04-19","Orthodox Easter Sunday","GE",1998 +"1998-04-20","Orthodox Easter Monday","GE",1998 +"1998-05-09","Day of Victory over Fascism","GE",1998 +"1998-05-12","St. Andrew's Day","GE",1998 +"1998-05-26","Independence Day","GE",1998 +"1998-08-28","Saint Mary's Day","GE",1998 +"1998-10-14","Day of Svetitskhoveli Cathedral","GE",1998 +"1998-11-23","Saint George's Day","GE",1998 +"1999-01-01","New Year's Day","GE",1999 +"1999-01-02","New Year's Day","GE",1999 +"1999-01-07","Orthodox Christmas Day","GE",1999 +"1999-01-19","Epiphany Day","GE",1999 +"1999-03-03","Mother's Day","GE",1999 +"1999-03-08","International Women's ay","GE",1999 +"1999-04-09","National Unity Day","GE",1999 +"1999-04-09","Orthodox Good Friday","GE",1999 +"1999-04-10","Orthodox Holy Saturday","GE",1999 +"1999-04-11","Orthodox Easter Sunday","GE",1999 +"1999-04-12","Orthodox Easter Monday","GE",1999 +"1999-05-09","Day of Victory over Fascism","GE",1999 +"1999-05-12","St. Andrew's Day","GE",1999 +"1999-05-26","Independence Day","GE",1999 +"1999-08-28","Saint Mary's Day","GE",1999 +"1999-10-14","Day of Svetitskhoveli Cathedral","GE",1999 +"1999-11-23","Saint George's Day","GE",1999 +"2000-01-01","New Year's Day","GE",2000 +"2000-01-02","New Year's Day","GE",2000 +"2000-01-07","Orthodox Christmas Day","GE",2000 +"2000-01-19","Epiphany Day","GE",2000 +"2000-03-03","Mother's Day","GE",2000 +"2000-03-08","International Women's ay","GE",2000 +"2000-04-09","National Unity Day","GE",2000 +"2000-04-28","Orthodox Good Friday","GE",2000 +"2000-04-29","Orthodox Holy Saturday","GE",2000 +"2000-04-30","Orthodox Easter Sunday","GE",2000 +"2000-05-01","Orthodox Easter Monday","GE",2000 +"2000-05-09","Day of Victory over Fascism","GE",2000 +"2000-05-12","St. Andrew's Day","GE",2000 +"2000-05-26","Independence Day","GE",2000 +"2000-08-28","Saint Mary's Day","GE",2000 +"2000-10-14","Day of Svetitskhoveli Cathedral","GE",2000 +"2000-11-23","Saint George's Day","GE",2000 +"2001-01-01","New Year's Day","GE",2001 +"2001-01-02","New Year's Day","GE",2001 +"2001-01-07","Orthodox Christmas Day","GE",2001 +"2001-01-19","Epiphany Day","GE",2001 +"2001-03-03","Mother's Day","GE",2001 +"2001-03-08","International Women's ay","GE",2001 +"2001-04-09","National Unity Day","GE",2001 +"2001-04-13","Orthodox Good Friday","GE",2001 +"2001-04-14","Orthodox Holy Saturday","GE",2001 +"2001-04-15","Orthodox Easter Sunday","GE",2001 +"2001-04-16","Orthodox Easter Monday","GE",2001 +"2001-05-09","Day of Victory over Fascism","GE",2001 +"2001-05-12","St. Andrew's Day","GE",2001 +"2001-05-26","Independence Day","GE",2001 +"2001-08-28","Saint Mary's Day","GE",2001 +"2001-10-14","Day of Svetitskhoveli Cathedral","GE",2001 +"2001-11-23","Saint George's Day","GE",2001 +"2002-01-01","New Year's Day","GE",2002 +"2002-01-02","New Year's Day","GE",2002 +"2002-01-07","Orthodox Christmas Day","GE",2002 +"2002-01-19","Epiphany Day","GE",2002 +"2002-03-03","Mother's Day","GE",2002 +"2002-03-08","International Women's ay","GE",2002 +"2002-04-09","National Unity Day","GE",2002 +"2002-05-03","Orthodox Good Friday","GE",2002 +"2002-05-04","Orthodox Holy Saturday","GE",2002 +"2002-05-05","Orthodox Easter Sunday","GE",2002 +"2002-05-06","Orthodox Easter Monday","GE",2002 +"2002-05-09","Day of Victory over Fascism","GE",2002 +"2002-05-12","St. Andrew's Day","GE",2002 +"2002-05-26","Independence Day","GE",2002 +"2002-08-28","Saint Mary's Day","GE",2002 +"2002-10-14","Day of Svetitskhoveli Cathedral","GE",2002 +"2002-11-23","Saint George's Day","GE",2002 +"2003-01-01","New Year's Day","GE",2003 +"2003-01-02","New Year's Day","GE",2003 +"2003-01-07","Orthodox Christmas Day","GE",2003 +"2003-01-19","Epiphany Day","GE",2003 +"2003-03-03","Mother's Day","GE",2003 +"2003-03-08","International Women's ay","GE",2003 +"2003-04-09","National Unity Day","GE",2003 +"2003-04-25","Orthodox Good Friday","GE",2003 +"2003-04-26","Orthodox Holy Saturday","GE",2003 +"2003-04-27","Orthodox Easter Sunday","GE",2003 +"2003-04-28","Orthodox Easter Monday","GE",2003 +"2003-05-09","Day of Victory over Fascism","GE",2003 +"2003-05-12","St. Andrew's Day","GE",2003 +"2003-05-26","Independence Day","GE",2003 +"2003-08-28","Saint Mary's Day","GE",2003 +"2003-10-14","Day of Svetitskhoveli Cathedral","GE",2003 +"2003-11-23","Saint George's Day","GE",2003 +"2004-01-01","New Year's Day","GE",2004 +"2004-01-02","New Year's Day","GE",2004 +"2004-01-07","Orthodox Christmas Day","GE",2004 +"2004-01-19","Epiphany Day","GE",2004 +"2004-03-03","Mother's Day","GE",2004 +"2004-03-08","International Women's ay","GE",2004 +"2004-04-09","National Unity Day","GE",2004 +"2004-04-09","Orthodox Good Friday","GE",2004 +"2004-04-10","Orthodox Holy Saturday","GE",2004 +"2004-04-11","Orthodox Easter Sunday","GE",2004 +"2004-04-12","Orthodox Easter Monday","GE",2004 +"2004-05-09","Day of Victory over Fascism","GE",2004 +"2004-05-12","St. Andrew's Day","GE",2004 +"2004-05-26","Independence Day","GE",2004 +"2004-08-28","Saint Mary's Day","GE",2004 +"2004-10-14","Day of Svetitskhoveli Cathedral","GE",2004 +"2004-11-23","Saint George's Day","GE",2004 +"2005-01-01","New Year's Day","GE",2005 +"2005-01-02","New Year's Day","GE",2005 +"2005-01-07","Orthodox Christmas Day","GE",2005 +"2005-01-19","Epiphany Day","GE",2005 +"2005-03-03","Mother's Day","GE",2005 +"2005-03-08","International Women's ay","GE",2005 +"2005-04-09","National Unity Day","GE",2005 +"2005-04-29","Orthodox Good Friday","GE",2005 +"2005-04-30","Orthodox Holy Saturday","GE",2005 +"2005-05-01","Orthodox Easter Sunday","GE",2005 +"2005-05-02","Orthodox Easter Monday","GE",2005 +"2005-05-09","Day of Victory over Fascism","GE",2005 +"2005-05-12","St. Andrew's Day","GE",2005 +"2005-05-26","Independence Day","GE",2005 +"2005-08-28","Saint Mary's Day","GE",2005 +"2005-10-14","Day of Svetitskhoveli Cathedral","GE",2005 +"2005-11-23","Saint George's Day","GE",2005 +"2006-01-01","New Year's Day","GE",2006 +"2006-01-02","New Year's Day","GE",2006 +"2006-01-07","Orthodox Christmas Day","GE",2006 +"2006-01-19","Epiphany Day","GE",2006 +"2006-03-03","Mother's Day","GE",2006 +"2006-03-08","International Women's ay","GE",2006 +"2006-04-09","National Unity Day","GE",2006 +"2006-04-21","Orthodox Good Friday","GE",2006 +"2006-04-22","Orthodox Holy Saturday","GE",2006 +"2006-04-23","Orthodox Easter Sunday","GE",2006 +"2006-04-24","Orthodox Easter Monday","GE",2006 +"2006-05-09","Day of Victory over Fascism","GE",2006 +"2006-05-12","St. Andrew's Day","GE",2006 +"2006-05-26","Independence Day","GE",2006 +"2006-08-28","Saint Mary's Day","GE",2006 +"2006-10-14","Day of Svetitskhoveli Cathedral","GE",2006 +"2006-11-23","Saint George's Day","GE",2006 +"2007-01-01","New Year's Day","GE",2007 +"2007-01-02","New Year's Day","GE",2007 +"2007-01-07","Orthodox Christmas Day","GE",2007 +"2007-01-19","Epiphany Day","GE",2007 +"2007-03-03","Mother's Day","GE",2007 +"2007-03-08","International Women's ay","GE",2007 +"2007-04-06","Orthodox Good Friday","GE",2007 +"2007-04-07","Orthodox Holy Saturday","GE",2007 +"2007-04-08","Orthodox Easter Sunday","GE",2007 +"2007-04-09","National Unity Day","GE",2007 +"2007-04-09","Orthodox Easter Monday","GE",2007 +"2007-05-09","Day of Victory over Fascism","GE",2007 +"2007-05-12","St. Andrew's Day","GE",2007 +"2007-05-26","Independence Day","GE",2007 +"2007-08-28","Saint Mary's Day","GE",2007 +"2007-10-14","Day of Svetitskhoveli Cathedral","GE",2007 +"2007-11-23","Saint George's Day","GE",2007 +"2008-01-01","New Year's Day","GE",2008 +"2008-01-02","New Year's Day","GE",2008 +"2008-01-07","Orthodox Christmas Day","GE",2008 +"2008-01-19","Epiphany Day","GE",2008 +"2008-03-03","Mother's Day","GE",2008 +"2008-03-08","International Women's ay","GE",2008 +"2008-04-09","National Unity Day","GE",2008 +"2008-04-25","Orthodox Good Friday","GE",2008 +"2008-04-26","Orthodox Holy Saturday","GE",2008 +"2008-04-27","Orthodox Easter Sunday","GE",2008 +"2008-04-28","Orthodox Easter Monday","GE",2008 +"2008-05-09","Day of Victory over Fascism","GE",2008 +"2008-05-12","St. Andrew's Day","GE",2008 +"2008-05-26","Independence Day","GE",2008 +"2008-08-28","Saint Mary's Day","GE",2008 +"2008-10-14","Day of Svetitskhoveli Cathedral","GE",2008 +"2008-11-23","Saint George's Day","GE",2008 +"2009-01-01","New Year's Day","GE",2009 +"2009-01-02","New Year's Day","GE",2009 +"2009-01-07","Orthodox Christmas Day","GE",2009 +"2009-01-19","Epiphany Day","GE",2009 +"2009-03-03","Mother's Day","GE",2009 +"2009-03-08","International Women's ay","GE",2009 +"2009-04-09","National Unity Day","GE",2009 +"2009-04-17","Orthodox Good Friday","GE",2009 +"2009-04-18","Orthodox Holy Saturday","GE",2009 +"2009-04-19","Orthodox Easter Sunday","GE",2009 +"2009-04-20","Orthodox Easter Monday","GE",2009 +"2009-05-09","Day of Victory over Fascism","GE",2009 +"2009-05-12","St. Andrew's Day","GE",2009 +"2009-05-26","Independence Day","GE",2009 +"2009-08-28","Saint Mary's Day","GE",2009 +"2009-10-14","Day of Svetitskhoveli Cathedral","GE",2009 +"2009-11-23","Saint George's Day","GE",2009 +"2010-01-01","New Year's Day","GE",2010 +"2010-01-02","New Year's Day","GE",2010 +"2010-01-07","Orthodox Christmas Day","GE",2010 +"2010-01-19","Epiphany Day","GE",2010 +"2010-03-03","Mother's Day","GE",2010 +"2010-03-08","International Women's ay","GE",2010 +"2010-04-02","Orthodox Good Friday","GE",2010 +"2010-04-03","Orthodox Holy Saturday","GE",2010 +"2010-04-04","Orthodox Easter Sunday","GE",2010 +"2010-04-05","Orthodox Easter Monday","GE",2010 +"2010-04-09","National Unity Day","GE",2010 +"2010-05-09","Day of Victory over Fascism","GE",2010 +"2010-05-12","St. Andrew's Day","GE",2010 +"2010-05-26","Independence Day","GE",2010 +"2010-08-28","Saint Mary's Day","GE",2010 +"2010-10-14","Day of Svetitskhoveli Cathedral","GE",2010 +"2010-11-23","Saint George's Day","GE",2010 +"2011-01-01","New Year's Day","GE",2011 +"2011-01-02","New Year's Day","GE",2011 +"2011-01-07","Orthodox Christmas Day","GE",2011 +"2011-01-19","Epiphany Day","GE",2011 +"2011-03-03","Mother's Day","GE",2011 +"2011-03-08","International Women's ay","GE",2011 +"2011-04-09","National Unity Day","GE",2011 +"2011-04-22","Orthodox Good Friday","GE",2011 +"2011-04-23","Orthodox Holy Saturday","GE",2011 +"2011-04-24","Orthodox Easter Sunday","GE",2011 +"2011-04-25","Orthodox Easter Monday","GE",2011 +"2011-05-09","Day of Victory over Fascism","GE",2011 +"2011-05-12","St. Andrew's Day","GE",2011 +"2011-05-26","Independence Day","GE",2011 +"2011-08-28","Saint Mary's Day","GE",2011 +"2011-10-14","Day of Svetitskhoveli Cathedral","GE",2011 +"2011-11-23","Saint George's Day","GE",2011 +"2012-01-01","New Year's Day","GE",2012 +"2012-01-02","New Year's Day","GE",2012 +"2012-01-07","Orthodox Christmas Day","GE",2012 +"2012-01-19","Epiphany Day","GE",2012 +"2012-03-03","Mother's Day","GE",2012 +"2012-03-08","International Women's ay","GE",2012 +"2012-04-09","National Unity Day","GE",2012 +"2012-04-13","Orthodox Good Friday","GE",2012 +"2012-04-14","Orthodox Holy Saturday","GE",2012 +"2012-04-15","Orthodox Easter Sunday","GE",2012 +"2012-04-16","Orthodox Easter Monday","GE",2012 +"2012-05-09","Day of Victory over Fascism","GE",2012 +"2012-05-12","St. Andrew's Day","GE",2012 +"2012-05-26","Independence Day","GE",2012 +"2012-08-28","Saint Mary's Day","GE",2012 +"2012-10-14","Day of Svetitskhoveli Cathedral","GE",2012 +"2012-11-23","Saint George's Day","GE",2012 +"2013-01-01","New Year's Day","GE",2013 +"2013-01-02","New Year's Day","GE",2013 +"2013-01-07","Orthodox Christmas Day","GE",2013 +"2013-01-19","Epiphany Day","GE",2013 +"2013-03-03","Mother's Day","GE",2013 +"2013-03-08","International Women's ay","GE",2013 +"2013-04-09","National Unity Day","GE",2013 +"2013-05-03","Orthodox Good Friday","GE",2013 +"2013-05-04","Orthodox Holy Saturday","GE",2013 +"2013-05-05","Orthodox Easter Sunday","GE",2013 +"2013-05-06","Orthodox Easter Monday","GE",2013 +"2013-05-09","Day of Victory over Fascism","GE",2013 +"2013-05-12","St. Andrew's Day","GE",2013 +"2013-05-26","Independence Day","GE",2013 +"2013-08-28","Saint Mary's Day","GE",2013 +"2013-10-14","Day of Svetitskhoveli Cathedral","GE",2013 +"2013-11-23","Saint George's Day","GE",2013 +"2014-01-01","New Year's Day","GE",2014 +"2014-01-02","New Year's Day","GE",2014 +"2014-01-07","Orthodox Christmas Day","GE",2014 +"2014-01-19","Epiphany Day","GE",2014 +"2014-03-03","Mother's Day","GE",2014 +"2014-03-08","International Women's ay","GE",2014 +"2014-04-09","National Unity Day","GE",2014 +"2014-04-18","Orthodox Good Friday","GE",2014 +"2014-04-19","Orthodox Holy Saturday","GE",2014 +"2014-04-20","Orthodox Easter Sunday","GE",2014 +"2014-04-21","Orthodox Easter Monday","GE",2014 +"2014-05-09","Day of Victory over Fascism","GE",2014 +"2014-05-12","St. Andrew's Day","GE",2014 +"2014-05-26","Independence Day","GE",2014 +"2014-08-28","Saint Mary's Day","GE",2014 +"2014-10-14","Day of Svetitskhoveli Cathedral","GE",2014 +"2014-11-23","Saint George's Day","GE",2014 +"2015-01-01","New Year's Day","GE",2015 +"2015-01-02","New Year's Day","GE",2015 +"2015-01-07","Orthodox Christmas Day","GE",2015 +"2015-01-19","Epiphany Day","GE",2015 +"2015-03-03","Mother's Day","GE",2015 +"2015-03-08","International Women's ay","GE",2015 +"2015-04-09","National Unity Day","GE",2015 +"2015-04-10","Orthodox Good Friday","GE",2015 +"2015-04-11","Orthodox Holy Saturday","GE",2015 +"2015-04-12","Orthodox Easter Sunday","GE",2015 +"2015-04-13","Orthodox Easter Monday","GE",2015 +"2015-05-09","Day of Victory over Fascism","GE",2015 +"2015-05-12","St. Andrew's Day","GE",2015 +"2015-05-26","Independence Day","GE",2015 +"2015-08-28","Saint Mary's Day","GE",2015 +"2015-10-14","Day of Svetitskhoveli Cathedral","GE",2015 +"2015-11-23","Saint George's Day","GE",2015 +"2016-01-01","New Year's Day","GE",2016 +"2016-01-02","New Year's Day","GE",2016 +"2016-01-07","Orthodox Christmas Day","GE",2016 +"2016-01-19","Epiphany Day","GE",2016 +"2016-03-03","Mother's Day","GE",2016 +"2016-03-08","International Women's ay","GE",2016 +"2016-04-09","National Unity Day","GE",2016 +"2016-04-29","Orthodox Good Friday","GE",2016 +"2016-04-30","Orthodox Holy Saturday","GE",2016 +"2016-05-01","Orthodox Easter Sunday","GE",2016 +"2016-05-02","Orthodox Easter Monday","GE",2016 +"2016-05-09","Day of Victory over Fascism","GE",2016 +"2016-05-12","St. Andrew's Day","GE",2016 +"2016-05-26","Independence Day","GE",2016 +"2016-08-28","Saint Mary's Day","GE",2016 +"2016-10-14","Day of Svetitskhoveli Cathedral","GE",2016 +"2016-11-23","Saint George's Day","GE",2016 +"2017-01-01","New Year's Day","GE",2017 +"2017-01-02","New Year's Day","GE",2017 +"2017-01-07","Orthodox Christmas Day","GE",2017 +"2017-01-19","Epiphany Day","GE",2017 +"2017-03-03","Mother's Day","GE",2017 +"2017-03-08","International Women's ay","GE",2017 +"2017-04-09","National Unity Day","GE",2017 +"2017-04-14","Orthodox Good Friday","GE",2017 +"2017-04-15","Orthodox Holy Saturday","GE",2017 +"2017-04-16","Orthodox Easter Sunday","GE",2017 +"2017-04-17","Orthodox Easter Monday","GE",2017 +"2017-05-09","Day of Victory over Fascism","GE",2017 +"2017-05-12","St. Andrew's Day","GE",2017 +"2017-05-26","Independence Day","GE",2017 +"2017-08-28","Saint Mary's Day","GE",2017 +"2017-10-14","Day of Svetitskhoveli Cathedral","GE",2017 +"2017-11-23","Saint George's Day","GE",2017 +"2018-01-01","New Year's Day","GE",2018 +"2018-01-02","New Year's Day","GE",2018 +"2018-01-07","Orthodox Christmas Day","GE",2018 +"2018-01-19","Epiphany Day","GE",2018 +"2018-03-03","Mother's Day","GE",2018 +"2018-03-08","International Women's ay","GE",2018 +"2018-04-06","Orthodox Good Friday","GE",2018 +"2018-04-07","Orthodox Holy Saturday","GE",2018 +"2018-04-08","Orthodox Easter Sunday","GE",2018 +"2018-04-09","National Unity Day","GE",2018 +"2018-04-09","Orthodox Easter Monday","GE",2018 +"2018-05-09","Day of Victory over Fascism","GE",2018 +"2018-05-12","St. Andrew's Day","GE",2018 +"2018-05-26","Independence Day","GE",2018 +"2018-08-28","Saint Mary's Day","GE",2018 +"2018-10-14","Day of Svetitskhoveli Cathedral","GE",2018 +"2018-11-23","Saint George's Day","GE",2018 +"2019-01-01","New Year's Day","GE",2019 +"2019-01-02","New Year's Day","GE",2019 +"2019-01-07","Orthodox Christmas Day","GE",2019 +"2019-01-19","Epiphany Day","GE",2019 +"2019-03-03","Mother's Day","GE",2019 +"2019-03-08","International Women's ay","GE",2019 +"2019-04-09","National Unity Day","GE",2019 +"2019-04-26","Orthodox Good Friday","GE",2019 +"2019-04-27","Orthodox Holy Saturday","GE",2019 +"2019-04-28","Orthodox Easter Sunday","GE",2019 +"2019-04-29","Orthodox Easter Monday","GE",2019 +"2019-05-09","Day of Victory over Fascism","GE",2019 +"2019-05-12","St. Andrew's Day","GE",2019 +"2019-05-26","Independence Day","GE",2019 +"2019-08-28","Saint Mary's Day","GE",2019 +"2019-10-14","Day of Svetitskhoveli Cathedral","GE",2019 +"2019-11-23","Saint George's Day","GE",2019 +"2020-01-01","New Year's Day","GE",2020 +"2020-01-02","New Year's Day","GE",2020 +"2020-01-07","Orthodox Christmas Day","GE",2020 +"2020-01-19","Epiphany Day","GE",2020 +"2020-03-03","Mother's Day","GE",2020 +"2020-03-08","International Women's ay","GE",2020 +"2020-04-09","National Unity Day","GE",2020 +"2020-04-17","Orthodox Good Friday","GE",2020 +"2020-04-18","Orthodox Holy Saturday","GE",2020 +"2020-04-19","Orthodox Easter Sunday","GE",2020 +"2020-04-20","Orthodox Easter Monday","GE",2020 +"2020-05-09","Day of Victory over Fascism","GE",2020 +"2020-05-12","St. Andrew's Day","GE",2020 +"2020-05-26","Independence Day","GE",2020 +"2020-08-28","Saint Mary's Day","GE",2020 +"2020-10-14","Day of Svetitskhoveli Cathedral","GE",2020 +"2020-11-23","Saint George's Day","GE",2020 +"2021-01-01","New Year's Day","GE",2021 +"2021-01-02","New Year's Day","GE",2021 +"2021-01-07","Orthodox Christmas Day","GE",2021 +"2021-01-19","Epiphany Day","GE",2021 +"2021-03-03","Mother's Day","GE",2021 +"2021-03-08","International Women's ay","GE",2021 +"2021-04-09","National Unity Day","GE",2021 +"2021-04-30","Orthodox Good Friday","GE",2021 +"2021-05-01","Orthodox Holy Saturday","GE",2021 +"2021-05-02","Orthodox Easter Sunday","GE",2021 +"2021-05-03","Orthodox Easter Monday","GE",2021 +"2021-05-09","Day of Victory over Fascism","GE",2021 +"2021-05-12","St. Andrew's Day","GE",2021 +"2021-05-26","Independence Day","GE",2021 +"2021-08-28","Saint Mary's Day","GE",2021 +"2021-10-14","Day of Svetitskhoveli Cathedral","GE",2021 +"2021-11-23","Saint George's Day","GE",2021 +"2022-01-01","New Year's Day","GE",2022 +"2022-01-02","New Year's Day","GE",2022 +"2022-01-07","Orthodox Christmas Day","GE",2022 +"2022-01-19","Epiphany Day","GE",2022 +"2022-03-03","Mother's Day","GE",2022 +"2022-03-08","International Women's ay","GE",2022 +"2022-04-09","National Unity Day","GE",2022 +"2022-04-22","Orthodox Good Friday","GE",2022 +"2022-04-23","Orthodox Holy Saturday","GE",2022 +"2022-04-24","Orthodox Easter Sunday","GE",2022 +"2022-04-25","Orthodox Easter Monday","GE",2022 +"2022-05-09","Day of Victory over Fascism","GE",2022 +"2022-05-12","St. Andrew's Day","GE",2022 +"2022-05-26","Independence Day","GE",2022 +"2022-08-28","Saint Mary's Day","GE",2022 +"2022-10-14","Day of Svetitskhoveli Cathedral","GE",2022 +"2022-11-23","Saint George's Day","GE",2022 +"2023-01-01","New Year's Day","GE",2023 +"2023-01-02","New Year's Day","GE",2023 +"2023-01-07","Orthodox Christmas Day","GE",2023 +"2023-01-19","Epiphany Day","GE",2023 +"2023-03-03","Mother's Day","GE",2023 +"2023-03-08","International Women's ay","GE",2023 +"2023-04-09","National Unity Day","GE",2023 +"2023-04-14","Orthodox Good Friday","GE",2023 +"2023-04-15","Orthodox Holy Saturday","GE",2023 +"2023-04-16","Orthodox Easter Sunday","GE",2023 +"2023-04-17","Orthodox Easter Monday","GE",2023 +"2023-05-09","Day of Victory over Fascism","GE",2023 +"2023-05-12","St. Andrew's Day","GE",2023 +"2023-05-26","Independence Day","GE",2023 +"2023-08-28","Saint Mary's Day","GE",2023 +"2023-10-14","Day of Svetitskhoveli Cathedral","GE",2023 +"2023-11-23","Saint George's Day","GE",2023 +"2024-01-01","New Year's Day","GE",2024 +"2024-01-02","New Year's Day","GE",2024 +"2024-01-07","Orthodox Christmas Day","GE",2024 +"2024-01-19","Epiphany Day","GE",2024 +"2024-03-03","Mother's Day","GE",2024 +"2024-03-08","International Women's ay","GE",2024 +"2024-04-09","National Unity Day","GE",2024 +"2024-05-03","Orthodox Good Friday","GE",2024 +"2024-05-04","Orthodox Holy Saturday","GE",2024 +"2024-05-05","Orthodox Easter Sunday","GE",2024 +"2024-05-06","Orthodox Easter Monday","GE",2024 +"2024-05-09","Day of Victory over Fascism","GE",2024 +"2024-05-12","St. Andrew's Day","GE",2024 +"2024-05-26","Independence Day","GE",2024 +"2024-08-28","Saint Mary's Day","GE",2024 +"2024-10-14","Day of Svetitskhoveli Cathedral","GE",2024 +"2024-11-23","Saint George's Day","GE",2024 +"2025-01-01","New Year's Day","GE",2025 +"2025-01-02","New Year's Day","GE",2025 +"2025-01-07","Orthodox Christmas Day","GE",2025 +"2025-01-19","Epiphany Day","GE",2025 +"2025-03-03","Mother's Day","GE",2025 +"2025-03-08","International Women's ay","GE",2025 +"2025-04-09","National Unity Day","GE",2025 +"2025-04-18","Orthodox Good Friday","GE",2025 +"2025-04-19","Orthodox Holy Saturday","GE",2025 +"2025-04-20","Orthodox Easter Sunday","GE",2025 +"2025-04-21","Orthodox Easter Monday","GE",2025 +"2025-05-09","Day of Victory over Fascism","GE",2025 +"2025-05-12","St. Andrew's Day","GE",2025 +"2025-05-26","Independence Day","GE",2025 +"2025-08-28","Saint Mary's Day","GE",2025 +"2025-10-14","Day of Svetitskhoveli Cathedral","GE",2025 +"2025-11-23","Saint George's Day","GE",2025 +"2026-01-01","New Year's Day","GE",2026 +"2026-01-02","New Year's Day","GE",2026 +"2026-01-07","Orthodox Christmas Day","GE",2026 +"2026-01-19","Epiphany Day","GE",2026 +"2026-03-03","Mother's Day","GE",2026 +"2026-03-08","International Women's ay","GE",2026 +"2026-04-09","National Unity Day","GE",2026 +"2026-04-10","Orthodox Good Friday","GE",2026 +"2026-04-11","Orthodox Holy Saturday","GE",2026 +"2026-04-12","Orthodox Easter Sunday","GE",2026 +"2026-04-13","Orthodox Easter Monday","GE",2026 +"2026-05-09","Day of Victory over Fascism","GE",2026 +"2026-05-12","St. Andrew's Day","GE",2026 +"2026-05-26","Independence Day","GE",2026 +"2026-08-28","Saint Mary's Day","GE",2026 +"2026-10-14","Day of Svetitskhoveli Cathedral","GE",2026 +"2026-11-23","Saint George's Day","GE",2026 +"2027-01-01","New Year's Day","GE",2027 +"2027-01-02","New Year's Day","GE",2027 +"2027-01-07","Orthodox Christmas Day","GE",2027 +"2027-01-19","Epiphany Day","GE",2027 +"2027-03-03","Mother's Day","GE",2027 +"2027-03-08","International Women's ay","GE",2027 +"2027-04-09","National Unity Day","GE",2027 +"2027-04-30","Orthodox Good Friday","GE",2027 +"2027-05-01","Orthodox Holy Saturday","GE",2027 +"2027-05-02","Orthodox Easter Sunday","GE",2027 +"2027-05-03","Orthodox Easter Monday","GE",2027 +"2027-05-09","Day of Victory over Fascism","GE",2027 +"2027-05-12","St. Andrew's Day","GE",2027 +"2027-05-26","Independence Day","GE",2027 +"2027-08-28","Saint Mary's Day","GE",2027 +"2027-10-14","Day of Svetitskhoveli Cathedral","GE",2027 +"2027-11-23","Saint George's Day","GE",2027 +"2028-01-01","New Year's Day","GE",2028 +"2028-01-02","New Year's Day","GE",2028 +"2028-01-07","Orthodox Christmas Day","GE",2028 +"2028-01-19","Epiphany Day","GE",2028 +"2028-03-03","Mother's Day","GE",2028 +"2028-03-08","International Women's ay","GE",2028 +"2028-04-09","National Unity Day","GE",2028 +"2028-04-14","Orthodox Good Friday","GE",2028 +"2028-04-15","Orthodox Holy Saturday","GE",2028 +"2028-04-16","Orthodox Easter Sunday","GE",2028 +"2028-04-17","Orthodox Easter Monday","GE",2028 +"2028-05-09","Day of Victory over Fascism","GE",2028 +"2028-05-12","St. Andrew's Day","GE",2028 +"2028-05-26","Independence Day","GE",2028 +"2028-08-28","Saint Mary's Day","GE",2028 +"2028-10-14","Day of Svetitskhoveli Cathedral","GE",2028 +"2028-11-23","Saint George's Day","GE",2028 +"2029-01-01","New Year's Day","GE",2029 +"2029-01-02","New Year's Day","GE",2029 +"2029-01-07","Orthodox Christmas Day","GE",2029 +"2029-01-19","Epiphany Day","GE",2029 +"2029-03-03","Mother's Day","GE",2029 +"2029-03-08","International Women's ay","GE",2029 +"2029-04-06","Orthodox Good Friday","GE",2029 +"2029-04-07","Orthodox Holy Saturday","GE",2029 +"2029-04-08","Orthodox Easter Sunday","GE",2029 +"2029-04-09","National Unity Day","GE",2029 +"2029-04-09","Orthodox Easter Monday","GE",2029 +"2029-05-09","Day of Victory over Fascism","GE",2029 +"2029-05-12","St. Andrew's Day","GE",2029 +"2029-05-26","Independence Day","GE",2029 +"2029-08-28","Saint Mary's Day","GE",2029 +"2029-10-14","Day of Svetitskhoveli Cathedral","GE",2029 +"2029-11-23","Saint George's Day","GE",2029 +"2030-01-01","New Year's Day","GE",2030 +"2030-01-02","New Year's Day","GE",2030 +"2030-01-07","Orthodox Christmas Day","GE",2030 +"2030-01-19","Epiphany Day","GE",2030 +"2030-03-03","Mother's Day","GE",2030 +"2030-03-08","International Women's ay","GE",2030 +"2030-04-09","National Unity Day","GE",2030 +"2030-04-26","Orthodox Good Friday","GE",2030 +"2030-04-27","Orthodox Holy Saturday","GE",2030 +"2030-04-28","Orthodox Easter Sunday","GE",2030 +"2030-04-29","Orthodox Easter Monday","GE",2030 +"2030-05-09","Day of Victory over Fascism","GE",2030 +"2030-05-12","St. Andrew's Day","GE",2030 +"2030-05-26","Independence Day","GE",2030 +"2030-08-28","Saint Mary's Day","GE",2030 +"2030-10-14","Day of Svetitskhoveli Cathedral","GE",2030 +"2030-11-23","Saint George's Day","GE",2030 +"2031-01-01","New Year's Day","GE",2031 +"2031-01-02","New Year's Day","GE",2031 +"2031-01-07","Orthodox Christmas Day","GE",2031 +"2031-01-19","Epiphany Day","GE",2031 +"2031-03-03","Mother's Day","GE",2031 +"2031-03-08","International Women's ay","GE",2031 +"2031-04-09","National Unity Day","GE",2031 +"2031-04-11","Orthodox Good Friday","GE",2031 +"2031-04-12","Orthodox Holy Saturday","GE",2031 +"2031-04-13","Orthodox Easter Sunday","GE",2031 +"2031-04-14","Orthodox Easter Monday","GE",2031 +"2031-05-09","Day of Victory over Fascism","GE",2031 +"2031-05-12","St. Andrew's Day","GE",2031 +"2031-05-26","Independence Day","GE",2031 +"2031-08-28","Saint Mary's Day","GE",2031 +"2031-10-14","Day of Svetitskhoveli Cathedral","GE",2031 +"2031-11-23","Saint George's Day","GE",2031 +"2032-01-01","New Year's Day","GE",2032 +"2032-01-02","New Year's Day","GE",2032 +"2032-01-07","Orthodox Christmas Day","GE",2032 +"2032-01-19","Epiphany Day","GE",2032 +"2032-03-03","Mother's Day","GE",2032 +"2032-03-08","International Women's ay","GE",2032 +"2032-04-09","National Unity Day","GE",2032 +"2032-04-30","Orthodox Good Friday","GE",2032 +"2032-05-01","Orthodox Holy Saturday","GE",2032 +"2032-05-02","Orthodox Easter Sunday","GE",2032 +"2032-05-03","Orthodox Easter Monday","GE",2032 +"2032-05-09","Day of Victory over Fascism","GE",2032 +"2032-05-12","St. Andrew's Day","GE",2032 +"2032-05-26","Independence Day","GE",2032 +"2032-08-28","Saint Mary's Day","GE",2032 +"2032-10-14","Day of Svetitskhoveli Cathedral","GE",2032 +"2032-11-23","Saint George's Day","GE",2032 +"2033-01-01","New Year's Day","GE",2033 +"2033-01-02","New Year's Day","GE",2033 +"2033-01-07","Orthodox Christmas Day","GE",2033 +"2033-01-19","Epiphany Day","GE",2033 +"2033-03-03","Mother's Day","GE",2033 +"2033-03-08","International Women's ay","GE",2033 +"2033-04-09","National Unity Day","GE",2033 +"2033-04-22","Orthodox Good Friday","GE",2033 +"2033-04-23","Orthodox Holy Saturday","GE",2033 +"2033-04-24","Orthodox Easter Sunday","GE",2033 +"2033-04-25","Orthodox Easter Monday","GE",2033 +"2033-05-09","Day of Victory over Fascism","GE",2033 +"2033-05-12","St. Andrew's Day","GE",2033 +"2033-05-26","Independence Day","GE",2033 +"2033-08-28","Saint Mary's Day","GE",2033 +"2033-10-14","Day of Svetitskhoveli Cathedral","GE",2033 +"2033-11-23","Saint George's Day","GE",2033 +"2034-01-01","New Year's Day","GE",2034 +"2034-01-02","New Year's Day","GE",2034 +"2034-01-07","Orthodox Christmas Day","GE",2034 +"2034-01-19","Epiphany Day","GE",2034 +"2034-03-03","Mother's Day","GE",2034 +"2034-03-08","International Women's ay","GE",2034 +"2034-04-07","Orthodox Good Friday","GE",2034 +"2034-04-08","Orthodox Holy Saturday","GE",2034 +"2034-04-09","National Unity Day","GE",2034 +"2034-04-09","Orthodox Easter Sunday","GE",2034 +"2034-04-10","Orthodox Easter Monday","GE",2034 +"2034-05-09","Day of Victory over Fascism","GE",2034 +"2034-05-12","St. Andrew's Day","GE",2034 +"2034-05-26","Independence Day","GE",2034 +"2034-08-28","Saint Mary's Day","GE",2034 +"2034-10-14","Day of Svetitskhoveli Cathedral","GE",2034 +"2034-11-23","Saint George's Day","GE",2034 +"2035-01-01","New Year's Day","GE",2035 +"2035-01-02","New Year's Day","GE",2035 +"2035-01-07","Orthodox Christmas Day","GE",2035 +"2035-01-19","Epiphany Day","GE",2035 +"2035-03-03","Mother's Day","GE",2035 +"2035-03-08","International Women's ay","GE",2035 +"2035-04-09","National Unity Day","GE",2035 +"2035-04-27","Orthodox Good Friday","GE",2035 +"2035-04-28","Orthodox Holy Saturday","GE",2035 +"2035-04-29","Orthodox Easter Sunday","GE",2035 +"2035-04-30","Orthodox Easter Monday","GE",2035 +"2035-05-09","Day of Victory over Fascism","GE",2035 +"2035-05-12","St. Andrew's Day","GE",2035 +"2035-05-26","Independence Day","GE",2035 +"2035-08-28","Saint Mary's Day","GE",2035 +"2035-10-14","Day of Svetitskhoveli Cathedral","GE",2035 +"2035-11-23","Saint George's Day","GE",2035 +"2036-01-01","New Year's Day","GE",2036 +"2036-01-02","New Year's Day","GE",2036 +"2036-01-07","Orthodox Christmas Day","GE",2036 +"2036-01-19","Epiphany Day","GE",2036 +"2036-03-03","Mother's Day","GE",2036 +"2036-03-08","International Women's ay","GE",2036 +"2036-04-09","National Unity Day","GE",2036 +"2036-04-18","Orthodox Good Friday","GE",2036 +"2036-04-19","Orthodox Holy Saturday","GE",2036 +"2036-04-20","Orthodox Easter Sunday","GE",2036 +"2036-04-21","Orthodox Easter Monday","GE",2036 +"2036-05-09","Day of Victory over Fascism","GE",2036 +"2036-05-12","St. Andrew's Day","GE",2036 +"2036-05-26","Independence Day","GE",2036 +"2036-08-28","Saint Mary's Day","GE",2036 +"2036-10-14","Day of Svetitskhoveli Cathedral","GE",2036 +"2036-11-23","Saint George's Day","GE",2036 +"2037-01-01","New Year's Day","GE",2037 +"2037-01-02","New Year's Day","GE",2037 +"2037-01-07","Orthodox Christmas Day","GE",2037 +"2037-01-19","Epiphany Day","GE",2037 +"2037-03-03","Mother's Day","GE",2037 +"2037-03-08","International Women's ay","GE",2037 +"2037-04-03","Orthodox Good Friday","GE",2037 +"2037-04-04","Orthodox Holy Saturday","GE",2037 +"2037-04-05","Orthodox Easter Sunday","GE",2037 +"2037-04-06","Orthodox Easter Monday","GE",2037 +"2037-04-09","National Unity Day","GE",2037 +"2037-05-09","Day of Victory over Fascism","GE",2037 +"2037-05-12","St. Andrew's Day","GE",2037 +"2037-05-26","Independence Day","GE",2037 +"2037-08-28","Saint Mary's Day","GE",2037 +"2037-10-14","Day of Svetitskhoveli Cathedral","GE",2037 +"2037-11-23","Saint George's Day","GE",2037 +"2038-01-01","New Year's Day","GE",2038 +"2038-01-02","New Year's Day","GE",2038 +"2038-01-07","Orthodox Christmas Day","GE",2038 +"2038-01-19","Epiphany Day","GE",2038 +"2038-03-03","Mother's Day","GE",2038 +"2038-03-08","International Women's ay","GE",2038 +"2038-04-09","National Unity Day","GE",2038 +"2038-04-23","Orthodox Good Friday","GE",2038 +"2038-04-24","Orthodox Holy Saturday","GE",2038 +"2038-04-25","Orthodox Easter Sunday","GE",2038 +"2038-04-26","Orthodox Easter Monday","GE",2038 +"2038-05-09","Day of Victory over Fascism","GE",2038 +"2038-05-12","St. Andrew's Day","GE",2038 +"2038-05-26","Independence Day","GE",2038 +"2038-08-28","Saint Mary's Day","GE",2038 +"2038-10-14","Day of Svetitskhoveli Cathedral","GE",2038 +"2038-11-23","Saint George's Day","GE",2038 +"2039-01-01","New Year's Day","GE",2039 +"2039-01-02","New Year's Day","GE",2039 +"2039-01-07","Orthodox Christmas Day","GE",2039 +"2039-01-19","Epiphany Day","GE",2039 +"2039-03-03","Mother's Day","GE",2039 +"2039-03-08","International Women's ay","GE",2039 +"2039-04-09","National Unity Day","GE",2039 +"2039-04-15","Orthodox Good Friday","GE",2039 +"2039-04-16","Orthodox Holy Saturday","GE",2039 +"2039-04-17","Orthodox Easter Sunday","GE",2039 +"2039-04-18","Orthodox Easter Monday","GE",2039 +"2039-05-09","Day of Victory over Fascism","GE",2039 +"2039-05-12","St. Andrew's Day","GE",2039 +"2039-05-26","Independence Day","GE",2039 +"2039-08-28","Saint Mary's Day","GE",2039 +"2039-10-14","Day of Svetitskhoveli Cathedral","GE",2039 +"2039-11-23","Saint George's Day","GE",2039 +"2040-01-01","New Year's Day","GE",2040 +"2040-01-02","New Year's Day","GE",2040 +"2040-01-07","Orthodox Christmas Day","GE",2040 +"2040-01-19","Epiphany Day","GE",2040 +"2040-03-03","Mother's Day","GE",2040 +"2040-03-08","International Women's ay","GE",2040 +"2040-04-09","National Unity Day","GE",2040 +"2040-05-04","Orthodox Good Friday","GE",2040 +"2040-05-05","Orthodox Holy Saturday","GE",2040 +"2040-05-06","Orthodox Easter Sunday","GE",2040 +"2040-05-07","Orthodox Easter Monday","GE",2040 +"2040-05-09","Day of Victory over Fascism","GE",2040 +"2040-05-12","St. Andrew's Day","GE",2040 +"2040-05-26","Independence Day","GE",2040 +"2040-08-28","Saint Mary's Day","GE",2040 +"2040-10-14","Day of Svetitskhoveli Cathedral","GE",2040 +"2040-11-23","Saint George's Day","GE",2040 +"2041-01-01","New Year's Day","GE",2041 +"2041-01-02","New Year's Day","GE",2041 +"2041-01-07","Orthodox Christmas Day","GE",2041 +"2041-01-19","Epiphany Day","GE",2041 +"2041-03-03","Mother's Day","GE",2041 +"2041-03-08","International Women's ay","GE",2041 +"2041-04-09","National Unity Day","GE",2041 +"2041-04-19","Orthodox Good Friday","GE",2041 +"2041-04-20","Orthodox Holy Saturday","GE",2041 +"2041-04-21","Orthodox Easter Sunday","GE",2041 +"2041-04-22","Orthodox Easter Monday","GE",2041 +"2041-05-09","Day of Victory over Fascism","GE",2041 +"2041-05-12","St. Andrew's Day","GE",2041 +"2041-05-26","Independence Day","GE",2041 +"2041-08-28","Saint Mary's Day","GE",2041 +"2041-10-14","Day of Svetitskhoveli Cathedral","GE",2041 +"2041-11-23","Saint George's Day","GE",2041 +"2042-01-01","New Year's Day","GE",2042 +"2042-01-02","New Year's Day","GE",2042 +"2042-01-07","Orthodox Christmas Day","GE",2042 +"2042-01-19","Epiphany Day","GE",2042 +"2042-03-03","Mother's Day","GE",2042 +"2042-03-08","International Women's ay","GE",2042 +"2042-04-09","National Unity Day","GE",2042 +"2042-04-11","Orthodox Good Friday","GE",2042 +"2042-04-12","Orthodox Holy Saturday","GE",2042 +"2042-04-13","Orthodox Easter Sunday","GE",2042 +"2042-04-14","Orthodox Easter Monday","GE",2042 +"2042-05-09","Day of Victory over Fascism","GE",2042 +"2042-05-12","St. Andrew's Day","GE",2042 +"2042-05-26","Independence Day","GE",2042 +"2042-08-28","Saint Mary's Day","GE",2042 +"2042-10-14","Day of Svetitskhoveli Cathedral","GE",2042 +"2042-11-23","Saint George's Day","GE",2042 +"2043-01-01","New Year's Day","GE",2043 +"2043-01-02","New Year's Day","GE",2043 +"2043-01-07","Orthodox Christmas Day","GE",2043 +"2043-01-19","Epiphany Day","GE",2043 +"2043-03-03","Mother's Day","GE",2043 +"2043-03-08","International Women's ay","GE",2043 +"2043-04-09","National Unity Day","GE",2043 +"2043-05-01","Orthodox Good Friday","GE",2043 +"2043-05-02","Orthodox Holy Saturday","GE",2043 +"2043-05-03","Orthodox Easter Sunday","GE",2043 +"2043-05-04","Orthodox Easter Monday","GE",2043 +"2043-05-09","Day of Victory over Fascism","GE",2043 +"2043-05-12","St. Andrew's Day","GE",2043 +"2043-05-26","Independence Day","GE",2043 +"2043-08-28","Saint Mary's Day","GE",2043 +"2043-10-14","Day of Svetitskhoveli Cathedral","GE",2043 +"2043-11-23","Saint George's Day","GE",2043 +"2044-01-01","New Year's Day","GE",2044 +"2044-01-02","New Year's Day","GE",2044 +"2044-01-07","Orthodox Christmas Day","GE",2044 +"2044-01-19","Epiphany Day","GE",2044 +"2044-03-03","Mother's Day","GE",2044 +"2044-03-08","International Women's ay","GE",2044 +"2044-04-09","National Unity Day","GE",2044 +"2044-04-22","Orthodox Good Friday","GE",2044 +"2044-04-23","Orthodox Holy Saturday","GE",2044 +"2044-04-24","Orthodox Easter Sunday","GE",2044 +"2044-04-25","Orthodox Easter Monday","GE",2044 +"2044-05-09","Day of Victory over Fascism","GE",2044 +"2044-05-12","St. Andrew's Day","GE",2044 +"2044-05-26","Independence Day","GE",2044 +"2044-08-28","Saint Mary's Day","GE",2044 +"2044-10-14","Day of Svetitskhoveli Cathedral","GE",2044 +"2044-11-23","Saint George's Day","GE",2044 +"1995-01-01","New Years Day","GR",1995 +"1995-01-06","Epiphany","GR",1995 +"1995-03-06","Clean Monday","GR",1995 +"1995-03-25","Independence Day","GR",1995 +"1995-04-24","Easter Monday","GR",1995 +"1995-05-01","Labor Day","GR",1995 +"1995-06-12","Easter Monday","GR",1995 +"1995-08-15","Assumption of Mary Day","GR",1995 +"1995-10-28","Ochi Day","GR",1995 +"1995-12-25","Christmas Day","GR",1995 +"1995-12-26","Day After Christmas","GR",1995 +"1996-01-01","New Years Day","GR",1996 +"1996-01-06","Epiphany","GR",1996 +"1996-02-26","Clean Monday","GR",1996 +"1996-03-25","Independence Day","GR",1996 +"1996-04-15","Easter Monday","GR",1996 +"1996-05-01","Labor Day","GR",1996 +"1996-06-03","Easter Monday","GR",1996 +"1996-08-15","Assumption of Mary Day","GR",1996 +"1996-10-28","Ochi Day","GR",1996 +"1996-12-25","Christmas Day","GR",1996 +"1996-12-26","Day After Christmas","GR",1996 +"1997-01-01","New Years Day","GR",1997 +"1997-01-06","Epiphany","GR",1997 +"1997-03-10","Clean Monday","GR",1997 +"1997-03-25","Independence Day","GR",1997 +"1997-04-28","Easter Monday","GR",1997 +"1997-05-01","Labor Day","GR",1997 +"1997-06-16","Easter Monday","GR",1997 +"1997-08-15","Assumption of Mary Day","GR",1997 +"1997-10-28","Ochi Day","GR",1997 +"1997-12-25","Christmas Day","GR",1997 +"1997-12-26","Day After Christmas","GR",1997 +"1998-01-01","New Years Day","GR",1998 +"1998-01-06","Epiphany","GR",1998 +"1998-03-02","Clean Monday","GR",1998 +"1998-03-25","Independence Day","GR",1998 +"1998-04-20","Easter Monday","GR",1998 +"1998-05-01","Labor Day","GR",1998 +"1998-06-08","Easter Monday","GR",1998 +"1998-08-15","Assumption of Mary Day","GR",1998 +"1998-10-28","Ochi Day","GR",1998 +"1998-12-25","Christmas Day","GR",1998 +"1998-12-26","Day After Christmas","GR",1998 +"1999-01-01","New Years Day","GR",1999 +"1999-01-06","Epiphany","GR",1999 +"1999-02-22","Clean Monday","GR",1999 +"1999-03-25","Independence Day","GR",1999 +"1999-04-12","Easter Monday","GR",1999 +"1999-05-01","Labor Day","GR",1999 +"1999-05-03","Labor Day (Observed)","GR",1999 +"1999-05-31","Easter Monday","GR",1999 +"1999-08-15","Assumption of Mary Day","GR",1999 +"1999-10-28","Ochi Day","GR",1999 +"1999-12-25","Christmas Day","GR",1999 +"1999-12-26","Day After Christmas","GR",1999 +"2000-01-01","New Years Day","GR",2000 +"2000-01-06","Epiphany","GR",2000 +"2000-03-13","Clean Monday","GR",2000 +"2000-03-25","Independence Day","GR",2000 +"2000-05-01","Easter Monday","GR",2000 +"2000-05-01","Labor Day","GR",2000 +"2000-06-19","Easter Monday","GR",2000 +"2000-08-15","Assumption of Mary Day","GR",2000 +"2000-10-28","Ochi Day","GR",2000 +"2000-12-25","Christmas Day","GR",2000 +"2000-12-26","Day After Christmas","GR",2000 +"2001-01-01","New Years Day","GR",2001 +"2001-01-06","Epiphany","GR",2001 +"2001-02-26","Clean Monday","GR",2001 +"2001-03-25","Independence Day","GR",2001 +"2001-04-16","Easter Monday","GR",2001 +"2001-05-01","Labor Day","GR",2001 +"2001-06-04","Easter Monday","GR",2001 +"2001-08-15","Assumption of Mary Day","GR",2001 +"2001-10-28","Ochi Day","GR",2001 +"2001-12-25","Christmas Day","GR",2001 +"2001-12-26","Day After Christmas","GR",2001 +"2002-01-01","New Years Day","GR",2002 +"2002-01-06","Epiphany","GR",2002 +"2002-03-18","Clean Monday","GR",2002 +"2002-03-25","Independence Day","GR",2002 +"2002-05-01","Labor Day","GR",2002 +"2002-05-06","Easter Monday","GR",2002 +"2002-06-24","Easter Monday","GR",2002 +"2002-08-15","Assumption of Mary Day","GR",2002 +"2002-10-28","Ochi Day","GR",2002 +"2002-12-25","Christmas Day","GR",2002 +"2002-12-26","Day After Christmas","GR",2002 +"2003-01-01","New Years Day","GR",2003 +"2003-01-06","Epiphany","GR",2003 +"2003-03-10","Clean Monday","GR",2003 +"2003-03-25","Independence Day","GR",2003 +"2003-04-28","Easter Monday","GR",2003 +"2003-05-01","Labor Day","GR",2003 +"2003-06-16","Easter Monday","GR",2003 +"2003-08-15","Assumption of Mary Day","GR",2003 +"2003-10-28","Ochi Day","GR",2003 +"2003-12-25","Christmas Day","GR",2003 +"2003-12-26","Day After Christmas","GR",2003 +"2004-01-01","New Years Day","GR",2004 +"2004-01-06","Epiphany","GR",2004 +"2004-02-23","Clean Monday","GR",2004 +"2004-03-25","Independence Day","GR",2004 +"2004-04-12","Easter Monday","GR",2004 +"2004-05-01","Labor Day","GR",2004 +"2004-05-03","Labor Day (Observed)","GR",2004 +"2004-05-31","Easter Monday","GR",2004 +"2004-08-15","Assumption of Mary Day","GR",2004 +"2004-10-28","Ochi Day","GR",2004 +"2004-12-25","Christmas Day","GR",2004 +"2004-12-26","Day After Christmas","GR",2004 +"2005-01-01","New Years Day","GR",2005 +"2005-01-06","Epiphany","GR",2005 +"2005-03-14","Clean Monday","GR",2005 +"2005-03-25","Independence Day","GR",2005 +"2005-05-01","Labor Day","GR",2005 +"2005-05-02","Easter Monday","GR",2005 +"2005-05-03","Labor Day (Observed)","GR",2005 +"2005-06-20","Easter Monday","GR",2005 +"2005-08-15","Assumption of Mary Day","GR",2005 +"2005-10-28","Ochi Day","GR",2005 +"2005-12-25","Christmas Day","GR",2005 +"2005-12-26","Day After Christmas","GR",2005 +"2006-01-01","New Years Day","GR",2006 +"2006-01-06","Epiphany","GR",2006 +"2006-03-06","Clean Monday","GR",2006 +"2006-03-25","Independence Day","GR",2006 +"2006-04-24","Easter Monday","GR",2006 +"2006-05-01","Labor Day","GR",2006 +"2006-06-12","Easter Monday","GR",2006 +"2006-08-15","Assumption of Mary Day","GR",2006 +"2006-10-28","Ochi Day","GR",2006 +"2006-12-25","Christmas Day","GR",2006 +"2006-12-26","Day After Christmas","GR",2006 +"2007-01-01","New Years Day","GR",2007 +"2007-01-06","Epiphany","GR",2007 +"2007-02-19","Clean Monday","GR",2007 +"2007-03-25","Independence Day","GR",2007 +"2007-04-09","Easter Monday","GR",2007 +"2007-05-01","Labor Day","GR",2007 +"2007-05-28","Easter Monday","GR",2007 +"2007-08-15","Assumption of Mary Day","GR",2007 +"2007-10-28","Ochi Day","GR",2007 +"2007-12-25","Christmas Day","GR",2007 +"2007-12-26","Day After Christmas","GR",2007 +"2008-01-01","New Years Day","GR",2008 +"2008-01-06","Epiphany","GR",2008 +"2008-03-10","Clean Monday","GR",2008 +"2008-03-25","Independence Day","GR",2008 +"2008-04-28","Easter Monday","GR",2008 +"2008-05-01","Labor Day","GR",2008 +"2008-06-16","Easter Monday","GR",2008 +"2008-08-15","Assumption of Mary Day","GR",2008 +"2008-10-28","Ochi Day","GR",2008 +"2008-12-25","Christmas Day","GR",2008 +"2008-12-26","Day After Christmas","GR",2008 +"2009-01-01","New Years Day","GR",2009 +"2009-01-06","Epiphany","GR",2009 +"2009-03-02","Clean Monday","GR",2009 +"2009-03-25","Independence Day","GR",2009 +"2009-04-20","Easter Monday","GR",2009 +"2009-05-01","Labor Day","GR",2009 +"2009-06-08","Easter Monday","GR",2009 +"2009-08-15","Assumption of Mary Day","GR",2009 +"2009-10-28","Ochi Day","GR",2009 +"2009-12-25","Christmas Day","GR",2009 +"2009-12-26","Day After Christmas","GR",2009 +"2010-01-01","New Years Day","GR",2010 +"2010-01-06","Epiphany","GR",2010 +"2010-02-15","Clean Monday","GR",2010 +"2010-03-25","Independence Day","GR",2010 +"2010-04-05","Easter Monday","GR",2010 +"2010-05-01","Labor Day","GR",2010 +"2010-05-03","Labor Day (Observed)","GR",2010 +"2010-05-24","Easter Monday","GR",2010 +"2010-08-15","Assumption of Mary Day","GR",2010 +"2010-10-28","Ochi Day","GR",2010 +"2010-12-25","Christmas Day","GR",2010 +"2010-12-26","Day After Christmas","GR",2010 +"2011-01-01","New Years Day","GR",2011 +"2011-01-06","Epiphany","GR",2011 +"2011-03-07","Clean Monday","GR",2011 +"2011-03-25","Independence Day","GR",2011 +"2011-04-25","Easter Monday","GR",2011 +"2011-05-01","Labor Day","GR",2011 +"2011-05-02","Labor Day (Observed)","GR",2011 +"2011-06-13","Easter Monday","GR",2011 +"2011-08-15","Assumption of Mary Day","GR",2011 +"2011-10-28","Ochi Day","GR",2011 +"2011-12-25","Christmas Day","GR",2011 +"2011-12-26","Day After Christmas","GR",2011 +"2012-01-01","New Years Day","GR",2012 +"2012-01-06","Epiphany","GR",2012 +"2012-02-27","Clean Monday","GR",2012 +"2012-03-25","Independence Day","GR",2012 +"2012-04-16","Easter Monday","GR",2012 +"2012-05-01","Labor Day","GR",2012 +"2012-06-04","Easter Monday","GR",2012 +"2012-08-15","Assumption of Mary Day","GR",2012 +"2012-10-28","Ochi Day","GR",2012 +"2012-12-25","Christmas Day","GR",2012 +"2012-12-26","Day After Christmas","GR",2012 +"2013-01-01","New Years Day","GR",2013 +"2013-01-06","Epiphany","GR",2013 +"2013-03-18","Clean Monday","GR",2013 +"2013-03-25","Independence Day","GR",2013 +"2013-05-01","Labor Day","GR",2013 +"2013-05-06","Easter Monday","GR",2013 +"2013-06-24","Easter Monday","GR",2013 +"2013-08-15","Assumption of Mary Day","GR",2013 +"2013-10-28","Ochi Day","GR",2013 +"2013-12-25","Christmas Day","GR",2013 +"2013-12-26","Day After Christmas","GR",2013 +"2014-01-01","New Years Day","GR",2014 +"2014-01-06","Epiphany","GR",2014 +"2014-03-03","Clean Monday","GR",2014 +"2014-03-25","Independence Day","GR",2014 +"2014-04-21","Easter Monday","GR",2014 +"2014-05-01","Labor Day","GR",2014 +"2014-06-09","Easter Monday","GR",2014 +"2014-08-15","Assumption of Mary Day","GR",2014 +"2014-10-28","Ochi Day","GR",2014 +"2014-12-25","Christmas Day","GR",2014 +"2014-12-26","Day After Christmas","GR",2014 +"2015-01-01","New Years Day","GR",2015 +"2015-01-06","Epiphany","GR",2015 +"2015-02-23","Clean Monday","GR",2015 +"2015-03-25","Independence Day","GR",2015 +"2015-04-13","Easter Monday","GR",2015 +"2015-05-01","Labor Day","GR",2015 +"2015-06-01","Easter Monday","GR",2015 +"2015-08-15","Assumption of Mary Day","GR",2015 +"2015-10-28","Ochi Day","GR",2015 +"2015-12-25","Christmas Day","GR",2015 +"2015-12-26","Day After Christmas","GR",2015 +"2016-01-01","New Years Day","GR",2016 +"2016-01-06","Epiphany","GR",2016 +"2016-03-14","Clean Monday","GR",2016 +"2016-03-25","Independence Day","GR",2016 +"2016-05-01","Labor Day","GR",2016 +"2016-05-02","Easter Monday","GR",2016 +"2016-05-03","Labor Day (Observed)","GR",2016 +"2016-06-20","Easter Monday","GR",2016 +"2016-08-15","Assumption of Mary Day","GR",2016 +"2016-10-28","Ochi Day","GR",2016 +"2016-12-25","Christmas Day","GR",2016 +"2016-12-26","Day After Christmas","GR",2016 +"2017-01-01","New Years Day","GR",2017 +"2017-01-06","Epiphany","GR",2017 +"2017-02-27","Clean Monday","GR",2017 +"2017-03-25","Independence Day","GR",2017 +"2017-04-17","Easter Monday","GR",2017 +"2017-05-01","Labor Day","GR",2017 +"2017-06-05","Easter Monday","GR",2017 +"2017-08-15","Assumption of Mary Day","GR",2017 +"2017-10-28","Ochi Day","GR",2017 +"2017-12-25","Christmas Day","GR",2017 +"2017-12-26","Day After Christmas","GR",2017 +"2018-01-01","New Years Day","GR",2018 +"2018-01-06","Epiphany","GR",2018 +"2018-02-19","Clean Monday","GR",2018 +"2018-03-25","Independence Day","GR",2018 +"2018-04-09","Easter Monday","GR",2018 +"2018-05-01","Labor Day","GR",2018 +"2018-05-28","Easter Monday","GR",2018 +"2018-08-15","Assumption of Mary Day","GR",2018 +"2018-10-28","Ochi Day","GR",2018 +"2018-12-25","Christmas Day","GR",2018 +"2018-12-26","Day After Christmas","GR",2018 +"2019-01-01","New Years Day","GR",2019 +"2019-01-06","Epiphany","GR",2019 +"2019-03-11","Clean Monday","GR",2019 +"2019-03-25","Independence Day","GR",2019 +"2019-04-29","Easter Monday","GR",2019 +"2019-05-01","Labor Day","GR",2019 +"2019-06-17","Easter Monday","GR",2019 +"2019-08-15","Assumption of Mary Day","GR",2019 +"2019-10-28","Ochi Day","GR",2019 +"2019-12-25","Christmas Day","GR",2019 +"2019-12-26","Day After Christmas","GR",2019 +"2020-01-01","New Years Day","GR",2020 +"2020-01-06","Epiphany","GR",2020 +"2020-03-02","Clean Monday","GR",2020 +"2020-03-25","Independence Day","GR",2020 +"2020-04-20","Easter Monday","GR",2020 +"2020-05-01","Labor Day","GR",2020 +"2020-06-08","Easter Monday","GR",2020 +"2020-08-15","Assumption of Mary Day","GR",2020 +"2020-10-28","Ochi Day","GR",2020 +"2020-12-25","Christmas Day","GR",2020 +"2020-12-26","Day After Christmas","GR",2020 +"2021-01-01","New Years Day","GR",2021 +"2021-01-06","Epiphany","GR",2021 +"2021-03-15","Clean Monday","GR",2021 +"2021-03-25","Independence Day","GR",2021 +"2021-05-01","Labor Day","GR",2021 +"2021-05-03","Easter Monday","GR",2021 +"2021-05-04","Labor Day (Observed)","GR",2021 +"2021-06-21","Easter Monday","GR",2021 +"2021-08-15","Assumption of Mary Day","GR",2021 +"2021-10-28","Ochi Day","GR",2021 +"2021-12-25","Christmas Day","GR",2021 +"2021-12-26","Day After Christmas","GR",2021 +"2022-01-01","New Years Day","GR",2022 +"2022-01-06","Epiphany","GR",2022 +"2022-03-07","Clean Monday","GR",2022 +"2022-03-25","Independence Day","GR",2022 +"2022-04-25","Easter Monday","GR",2022 +"2022-05-01","Labor Day","GR",2022 +"2022-05-02","Labor Day (Observed)","GR",2022 +"2022-06-13","Easter Monday","GR",2022 +"2022-08-15","Assumption of Mary Day","GR",2022 +"2022-10-28","Ochi Day","GR",2022 +"2022-12-25","Christmas Day","GR",2022 +"2022-12-26","Day After Christmas","GR",2022 +"2023-01-01","New Years Day","GR",2023 +"2023-01-06","Epiphany","GR",2023 +"2023-02-27","Clean Monday","GR",2023 +"2023-03-25","Independence Day","GR",2023 +"2023-04-17","Easter Monday","GR",2023 +"2023-05-01","Labor Day","GR",2023 +"2023-06-05","Easter Monday","GR",2023 +"2023-08-15","Assumption of Mary Day","GR",2023 +"2023-10-28","Ochi Day","GR",2023 +"2023-12-25","Christmas Day","GR",2023 +"2023-12-26","Day After Christmas","GR",2023 +"2024-01-01","New Years Day","GR",2024 +"2024-01-06","Epiphany","GR",2024 +"2024-03-18","Clean Monday","GR",2024 +"2024-03-25","Independence Day","GR",2024 +"2024-05-01","Labor Day","GR",2024 +"2024-05-06","Easter Monday","GR",2024 +"2024-06-24","Easter Monday","GR",2024 +"2024-08-15","Assumption of Mary Day","GR",2024 +"2024-10-28","Ochi Day","GR",2024 +"2024-12-25","Christmas Day","GR",2024 +"2024-12-26","Day After Christmas","GR",2024 +"2025-01-01","New Years Day","GR",2025 +"2025-01-06","Epiphany","GR",2025 +"2025-03-03","Clean Monday","GR",2025 +"2025-03-25","Independence Day","GR",2025 +"2025-04-21","Easter Monday","GR",2025 +"2025-05-01","Labor Day","GR",2025 +"2025-06-09","Easter Monday","GR",2025 +"2025-08-15","Assumption of Mary Day","GR",2025 +"2025-10-28","Ochi Day","GR",2025 +"2025-12-25","Christmas Day","GR",2025 +"2025-12-26","Day After Christmas","GR",2025 +"2026-01-01","New Years Day","GR",2026 +"2026-01-06","Epiphany","GR",2026 +"2026-02-23","Clean Monday","GR",2026 +"2026-03-25","Independence Day","GR",2026 +"2026-04-13","Easter Monday","GR",2026 +"2026-05-01","Labor Day","GR",2026 +"2026-06-01","Easter Monday","GR",2026 +"2026-08-15","Assumption of Mary Day","GR",2026 +"2026-10-28","Ochi Day","GR",2026 +"2026-12-25","Christmas Day","GR",2026 +"2026-12-26","Day After Christmas","GR",2026 +"2027-01-01","New Years Day","GR",2027 +"2027-01-06","Epiphany","GR",2027 +"2027-03-15","Clean Monday","GR",2027 +"2027-03-25","Independence Day","GR",2027 +"2027-05-01","Labor Day","GR",2027 +"2027-05-03","Easter Monday","GR",2027 +"2027-05-04","Labor Day (Observed)","GR",2027 +"2027-06-21","Easter Monday","GR",2027 +"2027-08-15","Assumption of Mary Day","GR",2027 +"2027-10-28","Ochi Day","GR",2027 +"2027-12-25","Christmas Day","GR",2027 +"2027-12-26","Day After Christmas","GR",2027 +"2028-01-01","New Years Day","GR",2028 +"2028-01-06","Epiphany","GR",2028 +"2028-02-28","Clean Monday","GR",2028 +"2028-03-25","Independence Day","GR",2028 +"2028-04-17","Easter Monday","GR",2028 +"2028-05-01","Labor Day","GR",2028 +"2028-06-05","Easter Monday","GR",2028 +"2028-08-15","Assumption of Mary Day","GR",2028 +"2028-10-28","Ochi Day","GR",2028 +"2028-12-25","Christmas Day","GR",2028 +"2028-12-26","Day After Christmas","GR",2028 +"2029-01-01","New Years Day","GR",2029 +"2029-01-06","Epiphany","GR",2029 +"2029-02-19","Clean Monday","GR",2029 +"2029-03-25","Independence Day","GR",2029 +"2029-04-09","Easter Monday","GR",2029 +"2029-05-01","Labor Day","GR",2029 +"2029-05-28","Easter Monday","GR",2029 +"2029-08-15","Assumption of Mary Day","GR",2029 +"2029-10-28","Ochi Day","GR",2029 +"2029-12-25","Christmas Day","GR",2029 +"2029-12-26","Day After Christmas","GR",2029 +"2030-01-01","New Years Day","GR",2030 +"2030-01-06","Epiphany","GR",2030 +"2030-03-11","Clean Monday","GR",2030 +"2030-03-25","Independence Day","GR",2030 +"2030-04-29","Easter Monday","GR",2030 +"2030-05-01","Labor Day","GR",2030 +"2030-06-17","Easter Monday","GR",2030 +"2030-08-15","Assumption of Mary Day","GR",2030 +"2030-10-28","Ochi Day","GR",2030 +"2030-12-25","Christmas Day","GR",2030 +"2030-12-26","Day After Christmas","GR",2030 +"2031-01-01","New Years Day","GR",2031 +"2031-01-06","Epiphany","GR",2031 +"2031-02-24","Clean Monday","GR",2031 +"2031-03-25","Independence Day","GR",2031 +"2031-04-14","Easter Monday","GR",2031 +"2031-05-01","Labor Day","GR",2031 +"2031-06-02","Easter Monday","GR",2031 +"2031-08-15","Assumption of Mary Day","GR",2031 +"2031-10-28","Ochi Day","GR",2031 +"2031-12-25","Christmas Day","GR",2031 +"2031-12-26","Day After Christmas","GR",2031 +"2032-01-01","New Years Day","GR",2032 +"2032-01-06","Epiphany","GR",2032 +"2032-03-15","Clean Monday","GR",2032 +"2032-03-25","Independence Day","GR",2032 +"2032-05-01","Labor Day","GR",2032 +"2032-05-03","Easter Monday","GR",2032 +"2032-05-04","Labor Day (Observed)","GR",2032 +"2032-06-21","Easter Monday","GR",2032 +"2032-08-15","Assumption of Mary Day","GR",2032 +"2032-10-28","Ochi Day","GR",2032 +"2032-12-25","Christmas Day","GR",2032 +"2032-12-26","Day After Christmas","GR",2032 +"2033-01-01","New Years Day","GR",2033 +"2033-01-06","Epiphany","GR",2033 +"2033-03-07","Clean Monday","GR",2033 +"2033-03-25","Independence Day","GR",2033 +"2033-04-25","Easter Monday","GR",2033 +"2033-05-01","Labor Day","GR",2033 +"2033-05-02","Labor Day (Observed)","GR",2033 +"2033-06-13","Easter Monday","GR",2033 +"2033-08-15","Assumption of Mary Day","GR",2033 +"2033-10-28","Ochi Day","GR",2033 +"2033-12-25","Christmas Day","GR",2033 +"2033-12-26","Day After Christmas","GR",2033 +"2034-01-01","New Years Day","GR",2034 +"2034-01-06","Epiphany","GR",2034 +"2034-02-20","Clean Monday","GR",2034 +"2034-03-25","Independence Day","GR",2034 +"2034-04-10","Easter Monday","GR",2034 +"2034-05-01","Labor Day","GR",2034 +"2034-05-29","Easter Monday","GR",2034 +"2034-08-15","Assumption of Mary Day","GR",2034 +"2034-10-28","Ochi Day","GR",2034 +"2034-12-25","Christmas Day","GR",2034 +"2034-12-26","Day After Christmas","GR",2034 +"2035-01-01","New Years Day","GR",2035 +"2035-01-06","Epiphany","GR",2035 +"2035-03-12","Clean Monday","GR",2035 +"2035-03-25","Independence Day","GR",2035 +"2035-04-30","Easter Monday","GR",2035 +"2035-05-01","Labor Day","GR",2035 +"2035-06-18","Easter Monday","GR",2035 +"2035-08-15","Assumption of Mary Day","GR",2035 +"2035-10-28","Ochi Day","GR",2035 +"2035-12-25","Christmas Day","GR",2035 +"2035-12-26","Day After Christmas","GR",2035 +"2036-01-01","New Years Day","GR",2036 +"2036-01-06","Epiphany","GR",2036 +"2036-03-03","Clean Monday","GR",2036 +"2036-03-25","Independence Day","GR",2036 +"2036-04-21","Easter Monday","GR",2036 +"2036-05-01","Labor Day","GR",2036 +"2036-06-09","Easter Monday","GR",2036 +"2036-08-15","Assumption of Mary Day","GR",2036 +"2036-10-28","Ochi Day","GR",2036 +"2036-12-25","Christmas Day","GR",2036 +"2036-12-26","Day After Christmas","GR",2036 +"2037-01-01","New Years Day","GR",2037 +"2037-01-06","Epiphany","GR",2037 +"2037-02-16","Clean Monday","GR",2037 +"2037-03-25","Independence Day","GR",2037 +"2037-04-06","Easter Monday","GR",2037 +"2037-05-01","Labor Day","GR",2037 +"2037-05-25","Easter Monday","GR",2037 +"2037-08-15","Assumption of Mary Day","GR",2037 +"2037-10-28","Ochi Day","GR",2037 +"2037-12-25","Christmas Day","GR",2037 +"2037-12-26","Day After Christmas","GR",2037 +"2038-01-01","New Years Day","GR",2038 +"2038-01-06","Epiphany","GR",2038 +"2038-03-08","Clean Monday","GR",2038 +"2038-03-25","Independence Day","GR",2038 +"2038-04-26","Easter Monday","GR",2038 +"2038-05-01","Labor Day","GR",2038 +"2038-05-03","Labor Day (Observed)","GR",2038 +"2038-06-14","Easter Monday","GR",2038 +"2038-08-15","Assumption of Mary Day","GR",2038 +"2038-10-28","Ochi Day","GR",2038 +"2038-12-25","Christmas Day","GR",2038 +"2038-12-26","Day After Christmas","GR",2038 +"2039-01-01","New Years Day","GR",2039 +"2039-01-06","Epiphany","GR",2039 +"2039-02-28","Clean Monday","GR",2039 +"2039-03-25","Independence Day","GR",2039 +"2039-04-18","Easter Monday","GR",2039 +"2039-05-01","Labor Day","GR",2039 +"2039-05-02","Labor Day (Observed)","GR",2039 +"2039-06-06","Easter Monday","GR",2039 +"2039-08-15","Assumption of Mary Day","GR",2039 +"2039-10-28","Ochi Day","GR",2039 +"2039-12-25","Christmas Day","GR",2039 +"2039-12-26","Day After Christmas","GR",2039 +"2040-01-01","New Years Day","GR",2040 +"2040-01-06","Epiphany","GR",2040 +"2040-03-19","Clean Monday","GR",2040 +"2040-03-25","Independence Day","GR",2040 +"2040-05-01","Labor Day","GR",2040 +"2040-05-07","Easter Monday","GR",2040 +"2040-06-25","Easter Monday","GR",2040 +"2040-08-15","Assumption of Mary Day","GR",2040 +"2040-10-28","Ochi Day","GR",2040 +"2040-12-25","Christmas Day","GR",2040 +"2040-12-26","Day After Christmas","GR",2040 +"2041-01-01","New Years Day","GR",2041 +"2041-01-06","Epiphany","GR",2041 +"2041-03-04","Clean Monday","GR",2041 +"2041-03-25","Independence Day","GR",2041 +"2041-04-22","Easter Monday","GR",2041 +"2041-05-01","Labor Day","GR",2041 +"2041-06-10","Easter Monday","GR",2041 +"2041-08-15","Assumption of Mary Day","GR",2041 +"2041-10-28","Ochi Day","GR",2041 +"2041-12-25","Christmas Day","GR",2041 +"2041-12-26","Day After Christmas","GR",2041 +"2042-01-01","New Years Day","GR",2042 +"2042-01-06","Epiphany","GR",2042 +"2042-02-24","Clean Monday","GR",2042 +"2042-03-25","Independence Day","GR",2042 +"2042-04-14","Easter Monday","GR",2042 +"2042-05-01","Labor Day","GR",2042 +"2042-06-02","Easter Monday","GR",2042 +"2042-08-15","Assumption of Mary Day","GR",2042 +"2042-10-28","Ochi Day","GR",2042 +"2042-12-25","Christmas Day","GR",2042 +"2042-12-26","Day After Christmas","GR",2042 +"2043-01-01","New Years Day","GR",2043 +"2043-01-06","Epiphany","GR",2043 +"2043-03-16","Clean Monday","GR",2043 +"2043-03-25","Independence Day","GR",2043 +"2043-05-01","Labor Day","GR",2043 +"2043-05-04","Easter Monday","GR",2043 +"2043-06-22","Easter Monday","GR",2043 +"2043-08-15","Assumption of Mary Day","GR",2043 +"2043-10-28","Ochi Day","GR",2043 +"2043-12-25","Christmas Day","GR",2043 +"2043-12-26","Day After Christmas","GR",2043 +"2044-01-01","New Years Day","GR",2044 +"2044-01-06","Epiphany","GR",2044 +"2044-03-07","Clean Monday","GR",2044 +"2044-03-25","Independence Day","GR",2044 +"2044-04-25","Easter Monday","GR",2044 +"2044-05-01","Labor Day","GR",2044 +"2044-05-02","Labor Day (Observed)","GR",2044 +"2044-06-13","Easter Monday","GR",2044 +"2044-08-15","Assumption of Mary Day","GR",2044 +"2044-10-28","Ochi Day","GR",2044 +"2044-12-25","Christmas Day","GR",2044 +"2044-12-26","Day After Christmas","GR",2044 +"1995-01-01","New Year's Day","GU",1995 +"1995-01-02","New Year's Day (Observed)","GU",1995 +"1995-01-16","Martin Luther King Jr. Day","GU",1995 +"1995-02-20","Washington's Birthday","GU",1995 +"1995-03-06","Guam Discovery Day","GU",1995 +"1995-04-14","Good Friday","GU",1995 +"1995-05-29","Memorial Day","GU",1995 +"1995-07-04","Independence Day","GU",1995 +"1995-07-21","Liberation Day (Guam)","GU",1995 +"1995-09-04","Labor Day","GU",1995 +"1995-10-09","Columbus Day","GU",1995 +"1995-11-02","All Souls' Day","GU",1995 +"1995-11-10","Veterans Day (Observed)","GU",1995 +"1995-11-11","Veterans Day","GU",1995 +"1995-11-23","Thanksgiving","GU",1995 +"1995-12-08","Lady of Camarin Day","GU",1995 +"1995-12-25","Christmas Day","GU",1995 +"1996-01-01","New Year's Day","GU",1996 +"1996-01-15","Martin Luther King Jr. Day","GU",1996 +"1996-02-19","Washington's Birthday","GU",1996 +"1996-03-04","Guam Discovery Day","GU",1996 +"1996-04-05","Good Friday","GU",1996 +"1996-05-27","Memorial Day","GU",1996 +"1996-07-04","Independence Day","GU",1996 +"1996-07-21","Liberation Day (Guam)","GU",1996 +"1996-09-02","Labor Day","GU",1996 +"1996-10-14","Columbus Day","GU",1996 +"1996-11-02","All Souls' Day","GU",1996 +"1996-11-11","Veterans Day","GU",1996 +"1996-11-28","Thanksgiving","GU",1996 +"1996-12-08","Lady of Camarin Day","GU",1996 +"1996-12-25","Christmas Day","GU",1996 +"1997-01-01","New Year's Day","GU",1997 +"1997-01-20","Martin Luther King Jr. Day","GU",1997 +"1997-02-17","Washington's Birthday","GU",1997 +"1997-03-03","Guam Discovery Day","GU",1997 +"1997-03-28","Good Friday","GU",1997 +"1997-05-26","Memorial Day","GU",1997 +"1997-07-04","Independence Day","GU",1997 +"1997-07-21","Liberation Day (Guam)","GU",1997 +"1997-09-01","Labor Day","GU",1997 +"1997-10-13","Columbus Day","GU",1997 +"1997-11-02","All Souls' Day","GU",1997 +"1997-11-11","Veterans Day","GU",1997 +"1997-11-27","Thanksgiving","GU",1997 +"1997-12-08","Lady of Camarin Day","GU",1997 +"1997-12-25","Christmas Day","GU",1997 +"1998-01-01","New Year's Day","GU",1998 +"1998-01-19","Martin Luther King Jr. Day","GU",1998 +"1998-02-16","Washington's Birthday","GU",1998 +"1998-03-02","Guam Discovery Day","GU",1998 +"1998-04-10","Good Friday","GU",1998 +"1998-05-25","Memorial Day","GU",1998 +"1998-07-03","Independence Day (Observed)","GU",1998 +"1998-07-04","Independence Day","GU",1998 +"1998-07-21","Liberation Day (Guam)","GU",1998 +"1998-09-07","Labor Day","GU",1998 +"1998-10-12","Columbus Day","GU",1998 +"1998-11-02","All Souls' Day","GU",1998 +"1998-11-11","Veterans Day","GU",1998 +"1998-11-26","Thanksgiving","GU",1998 +"1998-12-08","Lady of Camarin Day","GU",1998 +"1998-12-25","Christmas Day","GU",1998 +"1999-01-01","New Year's Day","GU",1999 +"1999-01-18","Martin Luther King Jr. Day","GU",1999 +"1999-02-15","Washington's Birthday","GU",1999 +"1999-03-01","Guam Discovery Day","GU",1999 +"1999-04-02","Good Friday","GU",1999 +"1999-05-31","Memorial Day","GU",1999 +"1999-07-04","Independence Day","GU",1999 +"1999-07-05","Independence Day (Observed)","GU",1999 +"1999-07-21","Liberation Day (Guam)","GU",1999 +"1999-09-06","Labor Day","GU",1999 +"1999-10-11","Columbus Day","GU",1999 +"1999-11-02","All Souls' Day","GU",1999 +"1999-11-11","Veterans Day","GU",1999 +"1999-11-25","Thanksgiving","GU",1999 +"1999-12-08","Lady of Camarin Day","GU",1999 +"1999-12-24","Christmas Day (Observed)","GU",1999 +"1999-12-25","Christmas Day","GU",1999 +"1999-12-31","New Year's Day (Observed)","GU",1999 +"2000-01-01","New Year's Day","GU",2000 +"2000-01-17","Martin Luther King Jr. Day","GU",2000 +"2000-02-21","Washington's Birthday","GU",2000 +"2000-03-06","Guam Discovery Day","GU",2000 +"2000-04-21","Good Friday","GU",2000 +"2000-05-29","Memorial Day","GU",2000 +"2000-07-04","Independence Day","GU",2000 +"2000-07-21","Liberation Day (Guam)","GU",2000 +"2000-09-04","Labor Day","GU",2000 +"2000-10-09","Columbus Day","GU",2000 +"2000-11-02","All Souls' Day","GU",2000 +"2000-11-10","Veterans Day (Observed)","GU",2000 +"2000-11-11","Veterans Day","GU",2000 +"2000-11-23","Thanksgiving","GU",2000 +"2000-12-08","Lady of Camarin Day","GU",2000 +"2000-12-25","Christmas Day","GU",2000 +"2001-01-01","New Year's Day","GU",2001 +"2001-01-15","Martin Luther King Jr. Day","GU",2001 +"2001-02-19","Washington's Birthday","GU",2001 +"2001-03-05","Guam Discovery Day","GU",2001 +"2001-04-13","Good Friday","GU",2001 +"2001-05-28","Memorial Day","GU",2001 +"2001-07-04","Independence Day","GU",2001 +"2001-07-21","Liberation Day (Guam)","GU",2001 +"2001-09-03","Labor Day","GU",2001 +"2001-10-08","Columbus Day","GU",2001 +"2001-11-02","All Souls' Day","GU",2001 +"2001-11-11","Veterans Day","GU",2001 +"2001-11-12","Veterans Day (Observed)","GU",2001 +"2001-11-22","Thanksgiving","GU",2001 +"2001-12-08","Lady of Camarin Day","GU",2001 +"2001-12-25","Christmas Day","GU",2001 +"2002-01-01","New Year's Day","GU",2002 +"2002-01-21","Martin Luther King Jr. Day","GU",2002 +"2002-02-18","Washington's Birthday","GU",2002 +"2002-03-04","Guam Discovery Day","GU",2002 +"2002-03-29","Good Friday","GU",2002 +"2002-05-27","Memorial Day","GU",2002 +"2002-07-04","Independence Day","GU",2002 +"2002-07-21","Liberation Day (Guam)","GU",2002 +"2002-09-02","Labor Day","GU",2002 +"2002-10-14","Columbus Day","GU",2002 +"2002-11-02","All Souls' Day","GU",2002 +"2002-11-11","Veterans Day","GU",2002 +"2002-11-28","Thanksgiving","GU",2002 +"2002-12-08","Lady of Camarin Day","GU",2002 +"2002-12-25","Christmas Day","GU",2002 +"2003-01-01","New Year's Day","GU",2003 +"2003-01-20","Martin Luther King Jr. Day","GU",2003 +"2003-02-17","Washington's Birthday","GU",2003 +"2003-03-03","Guam Discovery Day","GU",2003 +"2003-04-18","Good Friday","GU",2003 +"2003-05-26","Memorial Day","GU",2003 +"2003-07-04","Independence Day","GU",2003 +"2003-07-21","Liberation Day (Guam)","GU",2003 +"2003-09-01","Labor Day","GU",2003 +"2003-10-13","Columbus Day","GU",2003 +"2003-11-02","All Souls' Day","GU",2003 +"2003-11-11","Veterans Day","GU",2003 +"2003-11-27","Thanksgiving","GU",2003 +"2003-12-08","Lady of Camarin Day","GU",2003 +"2003-12-25","Christmas Day","GU",2003 +"2004-01-01","New Year's Day","GU",2004 +"2004-01-19","Martin Luther King Jr. Day","GU",2004 +"2004-02-16","Washington's Birthday","GU",2004 +"2004-03-01","Guam Discovery Day","GU",2004 +"2004-04-09","Good Friday","GU",2004 +"2004-05-31","Memorial Day","GU",2004 +"2004-07-04","Independence Day","GU",2004 +"2004-07-05","Independence Day (Observed)","GU",2004 +"2004-07-21","Liberation Day (Guam)","GU",2004 +"2004-09-06","Labor Day","GU",2004 +"2004-10-11","Columbus Day","GU",2004 +"2004-11-02","All Souls' Day","GU",2004 +"2004-11-11","Veterans Day","GU",2004 +"2004-11-25","Thanksgiving","GU",2004 +"2004-12-08","Lady of Camarin Day","GU",2004 +"2004-12-24","Christmas Day (Observed)","GU",2004 +"2004-12-25","Christmas Day","GU",2004 +"2004-12-31","New Year's Day (Observed)","GU",2004 +"2005-01-01","New Year's Day","GU",2005 +"2005-01-17","Martin Luther King Jr. Day","GU",2005 +"2005-02-21","Washington's Birthday","GU",2005 +"2005-03-07","Guam Discovery Day","GU",2005 +"2005-03-25","Good Friday","GU",2005 +"2005-05-30","Memorial Day","GU",2005 +"2005-07-04","Independence Day","GU",2005 +"2005-07-21","Liberation Day (Guam)","GU",2005 +"2005-09-05","Labor Day","GU",2005 +"2005-10-10","Columbus Day","GU",2005 +"2005-11-02","All Souls' Day","GU",2005 +"2005-11-11","Veterans Day","GU",2005 +"2005-11-24","Thanksgiving","GU",2005 +"2005-12-08","Lady of Camarin Day","GU",2005 +"2005-12-25","Christmas Day","GU",2005 +"2005-12-26","Christmas Day (Observed)","GU",2005 +"2006-01-01","New Year's Day","GU",2006 +"2006-01-02","New Year's Day (Observed)","GU",2006 +"2006-01-16","Martin Luther King Jr. Day","GU",2006 +"2006-02-20","Washington's Birthday","GU",2006 +"2006-03-06","Guam Discovery Day","GU",2006 +"2006-04-14","Good Friday","GU",2006 +"2006-05-29","Memorial Day","GU",2006 +"2006-07-04","Independence Day","GU",2006 +"2006-07-21","Liberation Day (Guam)","GU",2006 +"2006-09-04","Labor Day","GU",2006 +"2006-10-09","Columbus Day","GU",2006 +"2006-11-02","All Souls' Day","GU",2006 +"2006-11-10","Veterans Day (Observed)","GU",2006 +"2006-11-11","Veterans Day","GU",2006 +"2006-11-23","Thanksgiving","GU",2006 +"2006-12-08","Lady of Camarin Day","GU",2006 +"2006-12-25","Christmas Day","GU",2006 +"2007-01-01","New Year's Day","GU",2007 +"2007-01-15","Martin Luther King Jr. Day","GU",2007 +"2007-02-19","Washington's Birthday","GU",2007 +"2007-03-05","Guam Discovery Day","GU",2007 +"2007-04-06","Good Friday","GU",2007 +"2007-05-28","Memorial Day","GU",2007 +"2007-07-04","Independence Day","GU",2007 +"2007-07-21","Liberation Day (Guam)","GU",2007 +"2007-09-03","Labor Day","GU",2007 +"2007-10-08","Columbus Day","GU",2007 +"2007-11-02","All Souls' Day","GU",2007 +"2007-11-11","Veterans Day","GU",2007 +"2007-11-12","Veterans Day (Observed)","GU",2007 +"2007-11-22","Thanksgiving","GU",2007 +"2007-12-08","Lady of Camarin Day","GU",2007 +"2007-12-25","Christmas Day","GU",2007 +"2008-01-01","New Year's Day","GU",2008 +"2008-01-21","Martin Luther King Jr. Day","GU",2008 +"2008-02-18","Washington's Birthday","GU",2008 +"2008-03-03","Guam Discovery Day","GU",2008 +"2008-03-21","Good Friday","GU",2008 +"2008-05-26","Memorial Day","GU",2008 +"2008-07-04","Independence Day","GU",2008 +"2008-07-21","Liberation Day (Guam)","GU",2008 +"2008-09-01","Labor Day","GU",2008 +"2008-10-13","Columbus Day","GU",2008 +"2008-11-02","All Souls' Day","GU",2008 +"2008-11-11","Veterans Day","GU",2008 +"2008-11-27","Thanksgiving","GU",2008 +"2008-12-08","Lady of Camarin Day","GU",2008 +"2008-12-25","Christmas Day","GU",2008 +"2009-01-01","New Year's Day","GU",2009 +"2009-01-19","Martin Luther King Jr. Day","GU",2009 +"2009-02-16","Washington's Birthday","GU",2009 +"2009-03-02","Guam Discovery Day","GU",2009 +"2009-04-10","Good Friday","GU",2009 +"2009-05-25","Memorial Day","GU",2009 +"2009-07-03","Independence Day (Observed)","GU",2009 +"2009-07-04","Independence Day","GU",2009 +"2009-07-21","Liberation Day (Guam)","GU",2009 +"2009-09-07","Labor Day","GU",2009 +"2009-10-12","Columbus Day","GU",2009 +"2009-11-02","All Souls' Day","GU",2009 +"2009-11-11","Veterans Day","GU",2009 +"2009-11-26","Thanksgiving","GU",2009 +"2009-12-08","Lady of Camarin Day","GU",2009 +"2009-12-25","Christmas Day","GU",2009 +"2010-01-01","New Year's Day","GU",2010 +"2010-01-18","Martin Luther King Jr. Day","GU",2010 +"2010-02-15","Washington's Birthday","GU",2010 +"2010-03-01","Guam Discovery Day","GU",2010 +"2010-04-02","Good Friday","GU",2010 +"2010-05-31","Memorial Day","GU",2010 +"2010-07-04","Independence Day","GU",2010 +"2010-07-05","Independence Day (Observed)","GU",2010 +"2010-07-21","Liberation Day (Guam)","GU",2010 +"2010-09-06","Labor Day","GU",2010 +"2010-10-11","Columbus Day","GU",2010 +"2010-11-02","All Souls' Day","GU",2010 +"2010-11-11","Veterans Day","GU",2010 +"2010-11-25","Thanksgiving","GU",2010 +"2010-12-08","Lady of Camarin Day","GU",2010 +"2010-12-24","Christmas Day (Observed)","GU",2010 +"2010-12-25","Christmas Day","GU",2010 +"2010-12-31","New Year's Day (Observed)","GU",2010 +"2011-01-01","New Year's Day","GU",2011 +"2011-01-17","Martin Luther King Jr. Day","GU",2011 +"2011-02-21","Washington's Birthday","GU",2011 +"2011-03-07","Guam Discovery Day","GU",2011 +"2011-04-22","Good Friday","GU",2011 +"2011-05-30","Memorial Day","GU",2011 +"2011-07-04","Independence Day","GU",2011 +"2011-07-21","Liberation Day (Guam)","GU",2011 +"2011-09-05","Labor Day","GU",2011 +"2011-10-10","Columbus Day","GU",2011 +"2011-11-02","All Souls' Day","GU",2011 +"2011-11-11","Veterans Day","GU",2011 +"2011-11-24","Thanksgiving","GU",2011 +"2011-12-08","Lady of Camarin Day","GU",2011 +"2011-12-25","Christmas Day","GU",2011 +"2011-12-26","Christmas Day (Observed)","GU",2011 +"2012-01-01","New Year's Day","GU",2012 +"2012-01-02","New Year's Day (Observed)","GU",2012 +"2012-01-16","Martin Luther King Jr. Day","GU",2012 +"2012-02-20","Washington's Birthday","GU",2012 +"2012-03-05","Guam Discovery Day","GU",2012 +"2012-04-06","Good Friday","GU",2012 +"2012-05-28","Memorial Day","GU",2012 +"2012-07-04","Independence Day","GU",2012 +"2012-07-21","Liberation Day (Guam)","GU",2012 +"2012-09-03","Labor Day","GU",2012 +"2012-10-08","Columbus Day","GU",2012 +"2012-11-02","All Souls' Day","GU",2012 +"2012-11-11","Veterans Day","GU",2012 +"2012-11-12","Veterans Day (Observed)","GU",2012 +"2012-11-22","Thanksgiving","GU",2012 +"2012-12-08","Lady of Camarin Day","GU",2012 +"2012-12-25","Christmas Day","GU",2012 +"2013-01-01","New Year's Day","GU",2013 +"2013-01-21","Martin Luther King Jr. Day","GU",2013 +"2013-02-18","Washington's Birthday","GU",2013 +"2013-03-04","Guam Discovery Day","GU",2013 +"2013-03-29","Good Friday","GU",2013 +"2013-05-27","Memorial Day","GU",2013 +"2013-07-04","Independence Day","GU",2013 +"2013-07-21","Liberation Day (Guam)","GU",2013 +"2013-09-02","Labor Day","GU",2013 +"2013-10-14","Columbus Day","GU",2013 +"2013-11-02","All Souls' Day","GU",2013 +"2013-11-11","Veterans Day","GU",2013 +"2013-11-28","Thanksgiving","GU",2013 +"2013-12-08","Lady of Camarin Day","GU",2013 +"2013-12-25","Christmas Day","GU",2013 +"2014-01-01","New Year's Day","GU",2014 +"2014-01-20","Martin Luther King Jr. Day","GU",2014 +"2014-02-17","Washington's Birthday","GU",2014 +"2014-03-03","Guam Discovery Day","GU",2014 +"2014-04-18","Good Friday","GU",2014 +"2014-05-26","Memorial Day","GU",2014 +"2014-07-04","Independence Day","GU",2014 +"2014-07-21","Liberation Day (Guam)","GU",2014 +"2014-09-01","Labor Day","GU",2014 +"2014-10-13","Columbus Day","GU",2014 +"2014-11-02","All Souls' Day","GU",2014 +"2014-11-11","Veterans Day","GU",2014 +"2014-11-27","Thanksgiving","GU",2014 +"2014-12-08","Lady of Camarin Day","GU",2014 +"2014-12-25","Christmas Day","GU",2014 +"2015-01-01","New Year's Day","GU",2015 +"2015-01-19","Martin Luther King Jr. Day","GU",2015 +"2015-02-16","Washington's Birthday","GU",2015 +"2015-03-02","Guam Discovery Day","GU",2015 +"2015-04-03","Good Friday","GU",2015 +"2015-05-25","Memorial Day","GU",2015 +"2015-07-03","Independence Day (Observed)","GU",2015 +"2015-07-04","Independence Day","GU",2015 +"2015-07-21","Liberation Day (Guam)","GU",2015 +"2015-09-07","Labor Day","GU",2015 +"2015-10-12","Columbus Day","GU",2015 +"2015-11-02","All Souls' Day","GU",2015 +"2015-11-11","Veterans Day","GU",2015 +"2015-11-26","Thanksgiving","GU",2015 +"2015-12-08","Lady of Camarin Day","GU",2015 +"2015-12-25","Christmas Day","GU",2015 +"2016-01-01","New Year's Day","GU",2016 +"2016-01-18","Martin Luther King Jr. Day","GU",2016 +"2016-02-15","Washington's Birthday","GU",2016 +"2016-03-07","Guam Discovery Day","GU",2016 +"2016-03-25","Good Friday","GU",2016 +"2016-05-30","Memorial Day","GU",2016 +"2016-07-04","Independence Day","GU",2016 +"2016-07-21","Liberation Day (Guam)","GU",2016 +"2016-09-05","Labor Day","GU",2016 +"2016-10-10","Columbus Day","GU",2016 +"2016-11-02","All Souls' Day","GU",2016 +"2016-11-11","Veterans Day","GU",2016 +"2016-11-24","Thanksgiving","GU",2016 +"2016-12-08","Lady of Camarin Day","GU",2016 +"2016-12-25","Christmas Day","GU",2016 +"2016-12-26","Christmas Day (Observed)","GU",2016 +"2017-01-01","New Year's Day","GU",2017 +"2017-01-02","New Year's Day (Observed)","GU",2017 +"2017-01-16","Martin Luther King Jr. Day","GU",2017 +"2017-02-20","Washington's Birthday","GU",2017 +"2017-03-06","Guam Discovery Day","GU",2017 +"2017-04-14","Good Friday","GU",2017 +"2017-05-29","Memorial Day","GU",2017 +"2017-07-04","Independence Day","GU",2017 +"2017-07-21","Liberation Day (Guam)","GU",2017 +"2017-09-04","Labor Day","GU",2017 +"2017-10-09","Columbus Day","GU",2017 +"2017-11-02","All Souls' Day","GU",2017 +"2017-11-10","Veterans Day (Observed)","GU",2017 +"2017-11-11","Veterans Day","GU",2017 +"2017-11-23","Thanksgiving","GU",2017 +"2017-12-08","Lady of Camarin Day","GU",2017 +"2017-12-25","Christmas Day","GU",2017 +"2018-01-01","New Year's Day","GU",2018 +"2018-01-15","Martin Luther King Jr. Day","GU",2018 +"2018-02-19","Washington's Birthday","GU",2018 +"2018-03-05","Guam Discovery Day","GU",2018 +"2018-03-30","Good Friday","GU",2018 +"2018-05-28","Memorial Day","GU",2018 +"2018-07-04","Independence Day","GU",2018 +"2018-07-21","Liberation Day (Guam)","GU",2018 +"2018-09-03","Labor Day","GU",2018 +"2018-10-08","Columbus Day","GU",2018 +"2018-11-02","All Souls' Day","GU",2018 +"2018-11-11","Veterans Day","GU",2018 +"2018-11-12","Veterans Day (Observed)","GU",2018 +"2018-11-22","Thanksgiving","GU",2018 +"2018-12-08","Lady of Camarin Day","GU",2018 +"2018-12-25","Christmas Day","GU",2018 +"2019-01-01","New Year's Day","GU",2019 +"2019-01-21","Martin Luther King Jr. Day","GU",2019 +"2019-02-18","Washington's Birthday","GU",2019 +"2019-03-04","Guam Discovery Day","GU",2019 +"2019-04-19","Good Friday","GU",2019 +"2019-05-27","Memorial Day","GU",2019 +"2019-07-04","Independence Day","GU",2019 +"2019-07-21","Liberation Day (Guam)","GU",2019 +"2019-09-02","Labor Day","GU",2019 +"2019-10-14","Columbus Day","GU",2019 +"2019-11-02","All Souls' Day","GU",2019 +"2019-11-11","Veterans Day","GU",2019 +"2019-11-28","Thanksgiving","GU",2019 +"2019-12-08","Lady of Camarin Day","GU",2019 +"2019-12-25","Christmas Day","GU",2019 +"2020-01-01","New Year's Day","GU",2020 +"2020-01-20","Martin Luther King Jr. Day","GU",2020 +"2020-02-17","Washington's Birthday","GU",2020 +"2020-03-02","Guam Discovery Day","GU",2020 +"2020-04-10","Good Friday","GU",2020 +"2020-05-25","Memorial Day","GU",2020 +"2020-07-03","Independence Day (Observed)","GU",2020 +"2020-07-04","Independence Day","GU",2020 +"2020-07-21","Liberation Day (Guam)","GU",2020 +"2020-09-07","Labor Day","GU",2020 +"2020-10-12","Columbus Day","GU",2020 +"2020-11-02","All Souls' Day","GU",2020 +"2020-11-11","Veterans Day","GU",2020 +"2020-11-26","Thanksgiving","GU",2020 +"2020-12-08","Lady of Camarin Day","GU",2020 +"2020-12-25","Christmas Day","GU",2020 +"2021-01-01","New Year's Day","GU",2021 +"2021-01-18","Martin Luther King Jr. Day","GU",2021 +"2021-02-15","Washington's Birthday","GU",2021 +"2021-03-01","Guam Discovery Day","GU",2021 +"2021-04-02","Good Friday","GU",2021 +"2021-05-31","Memorial Day","GU",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","GU",2021 +"2021-06-19","Juneteenth National Independence Day","GU",2021 +"2021-07-04","Independence Day","GU",2021 +"2021-07-05","Independence Day (Observed)","GU",2021 +"2021-07-21","Liberation Day (Guam)","GU",2021 +"2021-09-06","Labor Day","GU",2021 +"2021-10-11","Columbus Day","GU",2021 +"2021-11-02","All Souls' Day","GU",2021 +"2021-11-11","Veterans Day","GU",2021 +"2021-11-25","Thanksgiving","GU",2021 +"2021-12-08","Lady of Camarin Day","GU",2021 +"2021-12-24","Christmas Day (Observed)","GU",2021 +"2021-12-25","Christmas Day","GU",2021 +"2021-12-31","New Year's Day (Observed)","GU",2021 +"2022-01-01","New Year's Day","GU",2022 +"2022-01-17","Martin Luther King Jr. Day","GU",2022 +"2022-02-21","Washington's Birthday","GU",2022 +"2022-03-07","Guam Discovery Day","GU",2022 +"2022-04-15","Good Friday","GU",2022 +"2022-05-30","Memorial Day","GU",2022 +"2022-06-19","Juneteenth National Independence Day","GU",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","GU",2022 +"2022-07-04","Independence Day","GU",2022 +"2022-07-21","Liberation Day (Guam)","GU",2022 +"2022-09-05","Labor Day","GU",2022 +"2022-10-10","Columbus Day","GU",2022 +"2022-11-02","All Souls' Day","GU",2022 +"2022-11-11","Veterans Day","GU",2022 +"2022-11-24","Thanksgiving","GU",2022 +"2022-12-08","Lady of Camarin Day","GU",2022 +"2022-12-25","Christmas Day","GU",2022 +"2022-12-26","Christmas Day (Observed)","GU",2022 +"2023-01-01","New Year's Day","GU",2023 +"2023-01-02","New Year's Day (Observed)","GU",2023 +"2023-01-16","Martin Luther King Jr. Day","GU",2023 +"2023-02-20","Washington's Birthday","GU",2023 +"2023-03-06","Guam Discovery Day","GU",2023 +"2023-04-07","Good Friday","GU",2023 +"2023-05-29","Memorial Day","GU",2023 +"2023-06-19","Juneteenth National Independence Day","GU",2023 +"2023-07-04","Independence Day","GU",2023 +"2023-07-21","Liberation Day (Guam)","GU",2023 +"2023-09-04","Labor Day","GU",2023 +"2023-10-09","Columbus Day","GU",2023 +"2023-11-02","All Souls' Day","GU",2023 +"2023-11-10","Veterans Day (Observed)","GU",2023 +"2023-11-11","Veterans Day","GU",2023 +"2023-11-23","Thanksgiving","GU",2023 +"2023-12-08","Lady of Camarin Day","GU",2023 +"2023-12-25","Christmas Day","GU",2023 +"2024-01-01","New Year's Day","GU",2024 +"2024-01-15","Martin Luther King Jr. Day","GU",2024 +"2024-02-19","Washington's Birthday","GU",2024 +"2024-03-04","Guam Discovery Day","GU",2024 +"2024-03-29","Good Friday","GU",2024 +"2024-05-27","Memorial Day","GU",2024 +"2024-06-19","Juneteenth National Independence Day","GU",2024 +"2024-07-04","Independence Day","GU",2024 +"2024-07-21","Liberation Day (Guam)","GU",2024 +"2024-09-02","Labor Day","GU",2024 +"2024-10-14","Columbus Day","GU",2024 +"2024-11-02","All Souls' Day","GU",2024 +"2024-11-11","Veterans Day","GU",2024 +"2024-11-28","Thanksgiving","GU",2024 +"2024-12-08","Lady of Camarin Day","GU",2024 +"2024-12-25","Christmas Day","GU",2024 +"2025-01-01","New Year's Day","GU",2025 +"2025-01-20","Martin Luther King Jr. Day","GU",2025 +"2025-02-17","Washington's Birthday","GU",2025 +"2025-03-03","Guam Discovery Day","GU",2025 +"2025-04-18","Good Friday","GU",2025 +"2025-05-26","Memorial Day","GU",2025 +"2025-06-19","Juneteenth National Independence Day","GU",2025 +"2025-07-04","Independence Day","GU",2025 +"2025-07-21","Liberation Day (Guam)","GU",2025 +"2025-09-01","Labor Day","GU",2025 +"2025-10-13","Columbus Day","GU",2025 +"2025-11-02","All Souls' Day","GU",2025 +"2025-11-11","Veterans Day","GU",2025 +"2025-11-27","Thanksgiving","GU",2025 +"2025-12-08","Lady of Camarin Day","GU",2025 +"2025-12-25","Christmas Day","GU",2025 +"2026-01-01","New Year's Day","GU",2026 +"2026-01-19","Martin Luther King Jr. Day","GU",2026 +"2026-02-16","Washington's Birthday","GU",2026 +"2026-03-02","Guam Discovery Day","GU",2026 +"2026-04-03","Good Friday","GU",2026 +"2026-05-25","Memorial Day","GU",2026 +"2026-06-19","Juneteenth National Independence Day","GU",2026 +"2026-07-03","Independence Day (Observed)","GU",2026 +"2026-07-04","Independence Day","GU",2026 +"2026-07-21","Liberation Day (Guam)","GU",2026 +"2026-09-07","Labor Day","GU",2026 +"2026-10-12","Columbus Day","GU",2026 +"2026-11-02","All Souls' Day","GU",2026 +"2026-11-11","Veterans Day","GU",2026 +"2026-11-26","Thanksgiving","GU",2026 +"2026-12-08","Lady of Camarin Day","GU",2026 +"2026-12-25","Christmas Day","GU",2026 +"2027-01-01","New Year's Day","GU",2027 +"2027-01-18","Martin Luther King Jr. Day","GU",2027 +"2027-02-15","Washington's Birthday","GU",2027 +"2027-03-01","Guam Discovery Day","GU",2027 +"2027-03-26","Good Friday","GU",2027 +"2027-05-31","Memorial Day","GU",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","GU",2027 +"2027-06-19","Juneteenth National Independence Day","GU",2027 +"2027-07-04","Independence Day","GU",2027 +"2027-07-05","Independence Day (Observed)","GU",2027 +"2027-07-21","Liberation Day (Guam)","GU",2027 +"2027-09-06","Labor Day","GU",2027 +"2027-10-11","Columbus Day","GU",2027 +"2027-11-02","All Souls' Day","GU",2027 +"2027-11-11","Veterans Day","GU",2027 +"2027-11-25","Thanksgiving","GU",2027 +"2027-12-08","Lady of Camarin Day","GU",2027 +"2027-12-24","Christmas Day (Observed)","GU",2027 +"2027-12-25","Christmas Day","GU",2027 +"2027-12-31","New Year's Day (Observed)","GU",2027 +"2028-01-01","New Year's Day","GU",2028 +"2028-01-17","Martin Luther King Jr. Day","GU",2028 +"2028-02-21","Washington's Birthday","GU",2028 +"2028-03-06","Guam Discovery Day","GU",2028 +"2028-04-14","Good Friday","GU",2028 +"2028-05-29","Memorial Day","GU",2028 +"2028-06-19","Juneteenth National Independence Day","GU",2028 +"2028-07-04","Independence Day","GU",2028 +"2028-07-21","Liberation Day (Guam)","GU",2028 +"2028-09-04","Labor Day","GU",2028 +"2028-10-09","Columbus Day","GU",2028 +"2028-11-02","All Souls' Day","GU",2028 +"2028-11-10","Veterans Day (Observed)","GU",2028 +"2028-11-11","Veterans Day","GU",2028 +"2028-11-23","Thanksgiving","GU",2028 +"2028-12-08","Lady of Camarin Day","GU",2028 +"2028-12-25","Christmas Day","GU",2028 +"2029-01-01","New Year's Day","GU",2029 +"2029-01-15","Martin Luther King Jr. Day","GU",2029 +"2029-02-19","Washington's Birthday","GU",2029 +"2029-03-05","Guam Discovery Day","GU",2029 +"2029-03-30","Good Friday","GU",2029 +"2029-05-28","Memorial Day","GU",2029 +"2029-06-19","Juneteenth National Independence Day","GU",2029 +"2029-07-04","Independence Day","GU",2029 +"2029-07-21","Liberation Day (Guam)","GU",2029 +"2029-09-03","Labor Day","GU",2029 +"2029-10-08","Columbus Day","GU",2029 +"2029-11-02","All Souls' Day","GU",2029 +"2029-11-11","Veterans Day","GU",2029 +"2029-11-12","Veterans Day (Observed)","GU",2029 +"2029-11-22","Thanksgiving","GU",2029 +"2029-12-08","Lady of Camarin Day","GU",2029 +"2029-12-25","Christmas Day","GU",2029 +"2030-01-01","New Year's Day","GU",2030 +"2030-01-21","Martin Luther King Jr. Day","GU",2030 +"2030-02-18","Washington's Birthday","GU",2030 +"2030-03-04","Guam Discovery Day","GU",2030 +"2030-04-19","Good Friday","GU",2030 +"2030-05-27","Memorial Day","GU",2030 +"2030-06-19","Juneteenth National Independence Day","GU",2030 +"2030-07-04","Independence Day","GU",2030 +"2030-07-21","Liberation Day (Guam)","GU",2030 +"2030-09-02","Labor Day","GU",2030 +"2030-10-14","Columbus Day","GU",2030 +"2030-11-02","All Souls' Day","GU",2030 +"2030-11-11","Veterans Day","GU",2030 +"2030-11-28","Thanksgiving","GU",2030 +"2030-12-08","Lady of Camarin Day","GU",2030 +"2030-12-25","Christmas Day","GU",2030 +"2031-01-01","New Year's Day","GU",2031 +"2031-01-20","Martin Luther King Jr. Day","GU",2031 +"2031-02-17","Washington's Birthday","GU",2031 +"2031-03-03","Guam Discovery Day","GU",2031 +"2031-04-11","Good Friday","GU",2031 +"2031-05-26","Memorial Day","GU",2031 +"2031-06-19","Juneteenth National Independence Day","GU",2031 +"2031-07-04","Independence Day","GU",2031 +"2031-07-21","Liberation Day (Guam)","GU",2031 +"2031-09-01","Labor Day","GU",2031 +"2031-10-13","Columbus Day","GU",2031 +"2031-11-02","All Souls' Day","GU",2031 +"2031-11-11","Veterans Day","GU",2031 +"2031-11-27","Thanksgiving","GU",2031 +"2031-12-08","Lady of Camarin Day","GU",2031 +"2031-12-25","Christmas Day","GU",2031 +"2032-01-01","New Year's Day","GU",2032 +"2032-01-19","Martin Luther King Jr. Day","GU",2032 +"2032-02-16","Washington's Birthday","GU",2032 +"2032-03-01","Guam Discovery Day","GU",2032 +"2032-03-26","Good Friday","GU",2032 +"2032-05-31","Memorial Day","GU",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","GU",2032 +"2032-06-19","Juneteenth National Independence Day","GU",2032 +"2032-07-04","Independence Day","GU",2032 +"2032-07-05","Independence Day (Observed)","GU",2032 +"2032-07-21","Liberation Day (Guam)","GU",2032 +"2032-09-06","Labor Day","GU",2032 +"2032-10-11","Columbus Day","GU",2032 +"2032-11-02","All Souls' Day","GU",2032 +"2032-11-11","Veterans Day","GU",2032 +"2032-11-25","Thanksgiving","GU",2032 +"2032-12-08","Lady of Camarin Day","GU",2032 +"2032-12-24","Christmas Day (Observed)","GU",2032 +"2032-12-25","Christmas Day","GU",2032 +"2032-12-31","New Year's Day (Observed)","GU",2032 +"2033-01-01","New Year's Day","GU",2033 +"2033-01-17","Martin Luther King Jr. Day","GU",2033 +"2033-02-21","Washington's Birthday","GU",2033 +"2033-03-07","Guam Discovery Day","GU",2033 +"2033-04-15","Good Friday","GU",2033 +"2033-05-30","Memorial Day","GU",2033 +"2033-06-19","Juneteenth National Independence Day","GU",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","GU",2033 +"2033-07-04","Independence Day","GU",2033 +"2033-07-21","Liberation Day (Guam)","GU",2033 +"2033-09-05","Labor Day","GU",2033 +"2033-10-10","Columbus Day","GU",2033 +"2033-11-02","All Souls' Day","GU",2033 +"2033-11-11","Veterans Day","GU",2033 +"2033-11-24","Thanksgiving","GU",2033 +"2033-12-08","Lady of Camarin Day","GU",2033 +"2033-12-25","Christmas Day","GU",2033 +"2033-12-26","Christmas Day (Observed)","GU",2033 +"2034-01-01","New Year's Day","GU",2034 +"2034-01-02","New Year's Day (Observed)","GU",2034 +"2034-01-16","Martin Luther King Jr. Day","GU",2034 +"2034-02-20","Washington's Birthday","GU",2034 +"2034-03-06","Guam Discovery Day","GU",2034 +"2034-04-07","Good Friday","GU",2034 +"2034-05-29","Memorial Day","GU",2034 +"2034-06-19","Juneteenth National Independence Day","GU",2034 +"2034-07-04","Independence Day","GU",2034 +"2034-07-21","Liberation Day (Guam)","GU",2034 +"2034-09-04","Labor Day","GU",2034 +"2034-10-09","Columbus Day","GU",2034 +"2034-11-02","All Souls' Day","GU",2034 +"2034-11-10","Veterans Day (Observed)","GU",2034 +"2034-11-11","Veterans Day","GU",2034 +"2034-11-23","Thanksgiving","GU",2034 +"2034-12-08","Lady of Camarin Day","GU",2034 +"2034-12-25","Christmas Day","GU",2034 +"2035-01-01","New Year's Day","GU",2035 +"2035-01-15","Martin Luther King Jr. Day","GU",2035 +"2035-02-19","Washington's Birthday","GU",2035 +"2035-03-05","Guam Discovery Day","GU",2035 +"2035-03-23","Good Friday","GU",2035 +"2035-05-28","Memorial Day","GU",2035 +"2035-06-19","Juneteenth National Independence Day","GU",2035 +"2035-07-04","Independence Day","GU",2035 +"2035-07-21","Liberation Day (Guam)","GU",2035 +"2035-09-03","Labor Day","GU",2035 +"2035-10-08","Columbus Day","GU",2035 +"2035-11-02","All Souls' Day","GU",2035 +"2035-11-11","Veterans Day","GU",2035 +"2035-11-12","Veterans Day (Observed)","GU",2035 +"2035-11-22","Thanksgiving","GU",2035 +"2035-12-08","Lady of Camarin Day","GU",2035 +"2035-12-25","Christmas Day","GU",2035 +"2036-01-01","New Year's Day","GU",2036 +"2036-01-21","Martin Luther King Jr. Day","GU",2036 +"2036-02-18","Washington's Birthday","GU",2036 +"2036-03-03","Guam Discovery Day","GU",2036 +"2036-04-11","Good Friday","GU",2036 +"2036-05-26","Memorial Day","GU",2036 +"2036-06-19","Juneteenth National Independence Day","GU",2036 +"2036-07-04","Independence Day","GU",2036 +"2036-07-21","Liberation Day (Guam)","GU",2036 +"2036-09-01","Labor Day","GU",2036 +"2036-10-13","Columbus Day","GU",2036 +"2036-11-02","All Souls' Day","GU",2036 +"2036-11-11","Veterans Day","GU",2036 +"2036-11-27","Thanksgiving","GU",2036 +"2036-12-08","Lady of Camarin Day","GU",2036 +"2036-12-25","Christmas Day","GU",2036 +"2037-01-01","New Year's Day","GU",2037 +"2037-01-19","Martin Luther King Jr. Day","GU",2037 +"2037-02-16","Washington's Birthday","GU",2037 +"2037-03-02","Guam Discovery Day","GU",2037 +"2037-04-03","Good Friday","GU",2037 +"2037-05-25","Memorial Day","GU",2037 +"2037-06-19","Juneteenth National Independence Day","GU",2037 +"2037-07-03","Independence Day (Observed)","GU",2037 +"2037-07-04","Independence Day","GU",2037 +"2037-07-21","Liberation Day (Guam)","GU",2037 +"2037-09-07","Labor Day","GU",2037 +"2037-10-12","Columbus Day","GU",2037 +"2037-11-02","All Souls' Day","GU",2037 +"2037-11-11","Veterans Day","GU",2037 +"2037-11-26","Thanksgiving","GU",2037 +"2037-12-08","Lady of Camarin Day","GU",2037 +"2037-12-25","Christmas Day","GU",2037 +"2038-01-01","New Year's Day","GU",2038 +"2038-01-18","Martin Luther King Jr. Day","GU",2038 +"2038-02-15","Washington's Birthday","GU",2038 +"2038-03-01","Guam Discovery Day","GU",2038 +"2038-04-23","Good Friday","GU",2038 +"2038-05-31","Memorial Day","GU",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","GU",2038 +"2038-06-19","Juneteenth National Independence Day","GU",2038 +"2038-07-04","Independence Day","GU",2038 +"2038-07-05","Independence Day (Observed)","GU",2038 +"2038-07-21","Liberation Day (Guam)","GU",2038 +"2038-09-06","Labor Day","GU",2038 +"2038-10-11","Columbus Day","GU",2038 +"2038-11-02","All Souls' Day","GU",2038 +"2038-11-11","Veterans Day","GU",2038 +"2038-11-25","Thanksgiving","GU",2038 +"2038-12-08","Lady of Camarin Day","GU",2038 +"2038-12-24","Christmas Day (Observed)","GU",2038 +"2038-12-25","Christmas Day","GU",2038 +"2038-12-31","New Year's Day (Observed)","GU",2038 +"2039-01-01","New Year's Day","GU",2039 +"2039-01-17","Martin Luther King Jr. Day","GU",2039 +"2039-02-21","Washington's Birthday","GU",2039 +"2039-03-07","Guam Discovery Day","GU",2039 +"2039-04-08","Good Friday","GU",2039 +"2039-05-30","Memorial Day","GU",2039 +"2039-06-19","Juneteenth National Independence Day","GU",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","GU",2039 +"2039-07-04","Independence Day","GU",2039 +"2039-07-21","Liberation Day (Guam)","GU",2039 +"2039-09-05","Labor Day","GU",2039 +"2039-10-10","Columbus Day","GU",2039 +"2039-11-02","All Souls' Day","GU",2039 +"2039-11-11","Veterans Day","GU",2039 +"2039-11-24","Thanksgiving","GU",2039 +"2039-12-08","Lady of Camarin Day","GU",2039 +"2039-12-25","Christmas Day","GU",2039 +"2039-12-26","Christmas Day (Observed)","GU",2039 +"2040-01-01","New Year's Day","GU",2040 +"2040-01-02","New Year's Day (Observed)","GU",2040 +"2040-01-16","Martin Luther King Jr. Day","GU",2040 +"2040-02-20","Washington's Birthday","GU",2040 +"2040-03-05","Guam Discovery Day","GU",2040 +"2040-03-30","Good Friday","GU",2040 +"2040-05-28","Memorial Day","GU",2040 +"2040-06-19","Juneteenth National Independence Day","GU",2040 +"2040-07-04","Independence Day","GU",2040 +"2040-07-21","Liberation Day (Guam)","GU",2040 +"2040-09-03","Labor Day","GU",2040 +"2040-10-08","Columbus Day","GU",2040 +"2040-11-02","All Souls' Day","GU",2040 +"2040-11-11","Veterans Day","GU",2040 +"2040-11-12","Veterans Day (Observed)","GU",2040 +"2040-11-22","Thanksgiving","GU",2040 +"2040-12-08","Lady of Camarin Day","GU",2040 +"2040-12-25","Christmas Day","GU",2040 +"2041-01-01","New Year's Day","GU",2041 +"2041-01-21","Martin Luther King Jr. Day","GU",2041 +"2041-02-18","Washington's Birthday","GU",2041 +"2041-03-04","Guam Discovery Day","GU",2041 +"2041-04-19","Good Friday","GU",2041 +"2041-05-27","Memorial Day","GU",2041 +"2041-06-19","Juneteenth National Independence Day","GU",2041 +"2041-07-04","Independence Day","GU",2041 +"2041-07-21","Liberation Day (Guam)","GU",2041 +"2041-09-02","Labor Day","GU",2041 +"2041-10-14","Columbus Day","GU",2041 +"2041-11-02","All Souls' Day","GU",2041 +"2041-11-11","Veterans Day","GU",2041 +"2041-11-28","Thanksgiving","GU",2041 +"2041-12-08","Lady of Camarin Day","GU",2041 +"2041-12-25","Christmas Day","GU",2041 +"2042-01-01","New Year's Day","GU",2042 +"2042-01-20","Martin Luther King Jr. Day","GU",2042 +"2042-02-17","Washington's Birthday","GU",2042 +"2042-03-03","Guam Discovery Day","GU",2042 +"2042-04-04","Good Friday","GU",2042 +"2042-05-26","Memorial Day","GU",2042 +"2042-06-19","Juneteenth National Independence Day","GU",2042 +"2042-07-04","Independence Day","GU",2042 +"2042-07-21","Liberation Day (Guam)","GU",2042 +"2042-09-01","Labor Day","GU",2042 +"2042-10-13","Columbus Day","GU",2042 +"2042-11-02","All Souls' Day","GU",2042 +"2042-11-11","Veterans Day","GU",2042 +"2042-11-27","Thanksgiving","GU",2042 +"2042-12-08","Lady of Camarin Day","GU",2042 +"2042-12-25","Christmas Day","GU",2042 +"2043-01-01","New Year's Day","GU",2043 +"2043-01-19","Martin Luther King Jr. Day","GU",2043 +"2043-02-16","Washington's Birthday","GU",2043 +"2043-03-02","Guam Discovery Day","GU",2043 +"2043-03-27","Good Friday","GU",2043 +"2043-05-25","Memorial Day","GU",2043 +"2043-06-19","Juneteenth National Independence Day","GU",2043 +"2043-07-03","Independence Day (Observed)","GU",2043 +"2043-07-04","Independence Day","GU",2043 +"2043-07-21","Liberation Day (Guam)","GU",2043 +"2043-09-07","Labor Day","GU",2043 +"2043-10-12","Columbus Day","GU",2043 +"2043-11-02","All Souls' Day","GU",2043 +"2043-11-11","Veterans Day","GU",2043 +"2043-11-26","Thanksgiving","GU",2043 +"2043-12-08","Lady of Camarin Day","GU",2043 +"2043-12-25","Christmas Day","GU",2043 +"2044-01-01","New Year's Day","GU",2044 +"2044-01-18","Martin Luther King Jr. Day","GU",2044 +"2044-02-15","Washington's Birthday","GU",2044 +"2044-03-07","Guam Discovery Day","GU",2044 +"2044-04-15","Good Friday","GU",2044 +"2044-05-30","Memorial Day","GU",2044 +"2044-06-19","Juneteenth National Independence Day","GU",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","GU",2044 +"2044-07-04","Independence Day","GU",2044 +"2044-07-21","Liberation Day (Guam)","GU",2044 +"2044-09-05","Labor Day","GU",2044 +"2044-10-10","Columbus Day","GU",2044 +"2044-11-02","All Souls' Day","GU",2044 +"2044-11-11","Veterans Day","GU",2044 +"2044-11-24","Thanksgiving","GU",2044 +"2044-12-08","Lady of Camarin Day","GU",2044 +"2044-12-25","Christmas Day","GU",2044 +"2044-12-26","Christmas Day (Observed)","GU",2044 +"1995-01-02","The day following the first day of January","HK",1995 +"1995-01-31","Lunar New Year's Day","HK",1995 +"1995-02-01","The second day of Lunar New Year","HK",1995 +"1995-02-02","The third day of Lunar New Year","HK",1995 +"1995-04-05","Ching Ming Festival","HK",1995 +"1995-04-14","Good Friday","HK",1995 +"1995-04-15","The day following Good Friday","HK",1995 +"1995-04-17","Easter Monday","HK",1995 +"1995-06-02","Tuen Ng Festival","HK",1995 +"1995-06-12","Queen's Birthday","HK",1995 +"1995-08-27","Anniversary of the victory in the Second Sino-Japanese War","HK",1995 +"1995-08-28","Anniversary of the liberation of Hong Kong","HK",1995 +"1995-09-09","Chinese Mid-Autumn Festival","HK",1995 +"1995-11-01","Chung Yeung Festival","HK",1995 +"1995-12-25","Christmas Day","HK",1995 +"1995-12-26","The first weekday after Christmas Day","HK",1995 +"1996-01-01","The first day of January","HK",1996 +"1996-02-19","Lunar New Year's Day","HK",1996 +"1996-02-20","The second day of Lunar New Year","HK",1996 +"1996-02-21","The third day of Lunar New Year","HK",1996 +"1996-04-04","Ching Ming Festival","HK",1996 +"1996-04-05","Good Friday","HK",1996 +"1996-04-06","The day following Good Friday","HK",1996 +"1996-04-08","Easter Monday","HK",1996 +"1996-06-10","Queen's Birthday","HK",1996 +"1996-06-20","Tuen Ng Festival","HK",1996 +"1996-08-25","Anniversary of the victory in the Second Sino-Japanese War","HK",1996 +"1996-08-26","Anniversary of the liberation of Hong Kong","HK",1996 +"1996-09-28","The day following the Chinese Mid-Autumn Festival","HK",1996 +"1996-10-21","The day following Chung Yeung Festival","HK",1996 +"1996-12-25","Christmas Day","HK",1996 +"1996-12-26","The first weekday after Christmas Day","HK",1996 +"1997-01-01","The first day of January","HK",1997 +"1997-02-07","Lunar New Year's Day","HK",1997 +"1997-02-08","The second day of Lunar New Year","HK",1997 +"1997-02-10","The fourth day of Lunar New Year","HK",1997 +"1997-03-28","Good Friday","HK",1997 +"1997-03-29","The day following Good Friday","HK",1997 +"1997-03-31","Easter Monday","HK",1997 +"1997-04-05","Ching Ming Festival","HK",1997 +"1997-06-09","Queen's Birthday","HK",1997 +"1997-06-09","Tuen Ng Festival","HK",1997 +"1997-07-01","Hong Kong Special Administrative Region Establishment Day","HK",1997 +"1997-09-17","The day following the Chinese Mid-Autumn Festival","HK",1997 +"1997-10-01","National Day","HK",1997 +"1997-10-10","Chung Yeung Festival","HK",1997 +"1997-12-25","Christmas Day","HK",1997 +"1997-12-26","The first weekday after Christmas Day","HK",1997 +"1998-01-01","The first day of January","HK",1998 +"1998-01-28","Lunar New Year's Day","HK",1998 +"1998-01-29","The second day of Lunar New Year","HK",1998 +"1998-01-30","The third day of Lunar New Year","HK",1998 +"1998-04-06","The day following Ching Ming Festival","HK",1998 +"1998-04-10","Good Friday","HK",1998 +"1998-04-11","The day following Good Friday","HK",1998 +"1998-04-13","Easter Monday","HK",1998 +"1998-05-01","Labour Day","HK",1998 +"1998-05-04","The day following The Birthday of the Buddha","HK",1998 +"1998-05-30","Tuen Ng Festival","HK",1998 +"1998-07-01","Hong Kong Special Administrative Region Establishment Day","HK",1998 +"1998-10-01","National Day","HK",1998 +"1998-10-06","The day following the Chinese Mid-Autumn Festival","HK",1998 +"1998-10-28","Chung Yeung Festival","HK",1998 +"1998-12-25","Christmas Day","HK",1998 +"1998-12-26","The first weekday after Christmas Day","HK",1998 +"1999-01-01","The first day of January","HK",1999 +"1999-02-16","Lunar New Year's Day","HK",1999 +"1999-02-17","The second day of Lunar New Year","HK",1999 +"1999-02-18","The third day of Lunar New Year","HK",1999 +"1999-04-02","Good Friday","HK",1999 +"1999-04-03","The day following Good Friday","HK",1999 +"1999-04-05","Easter Monday","HK",1999 +"1999-04-06","The day following Ching Ming Festival","HK",1999 +"1999-05-01","Labour Day","HK",1999 +"1999-05-22","The Birthday of the Buddha","HK",1999 +"1999-06-18","Tuen Ng Festival","HK",1999 +"1999-07-01","Hong Kong Special Administrative Region Establishment Day","HK",1999 +"1999-09-25","The day following the Chinese Mid-Autumn Festival","HK",1999 +"1999-10-01","National Day","HK",1999 +"1999-10-18","The day following Chung Yeung Festival","HK",1999 +"1999-12-25","Christmas Day","HK",1999 +"1999-12-27","The first weekday after Christmas Day","HK",1999 +"2000-01-01","The first day of January","HK",2000 +"2000-02-05","Lunar New Year's Day","HK",2000 +"2000-02-07","The third day of Lunar New Year","HK",2000 +"2000-02-08","The fourth day of Lunar New Year","HK",2000 +"2000-04-04","Ching Ming Festival","HK",2000 +"2000-04-21","Good Friday","HK",2000 +"2000-04-22","The day following Good Friday","HK",2000 +"2000-04-24","Easter Monday","HK",2000 +"2000-05-01","Labour Day","HK",2000 +"2000-05-11","The Birthday of the Buddha","HK",2000 +"2000-06-06","Tuen Ng Festival","HK",2000 +"2000-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2000 +"2000-09-13","The day following the Chinese Mid-Autumn Festival","HK",2000 +"2000-10-02","The day following National Day","HK",2000 +"2000-10-06","Chung Yeung Festival","HK",2000 +"2000-12-25","Christmas Day","HK",2000 +"2000-12-26","The first weekday after Christmas Day","HK",2000 +"2001-01-01","The first day of January","HK",2001 +"2001-01-24","Lunar New Year's Day","HK",2001 +"2001-01-25","The second day of Lunar New Year","HK",2001 +"2001-01-26","The third day of Lunar New Year","HK",2001 +"2001-04-05","Ching Ming Festival","HK",2001 +"2001-04-13","Good Friday","HK",2001 +"2001-04-14","The day following Good Friday","HK",2001 +"2001-04-16","Easter Monday","HK",2001 +"2001-04-30","The Birthday of the Buddha","HK",2001 +"2001-05-01","Labour Day","HK",2001 +"2001-06-25","Tuen Ng Festival","HK",2001 +"2001-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2001 +"2001-10-01","National Day","HK",2001 +"2001-10-02","The day following the Chinese Mid-Autumn Festival","HK",2001 +"2001-10-25","Chung Yeung Festival","HK",2001 +"2001-12-25","Christmas Day","HK",2001 +"2001-12-26","The first weekday after Christmas Day","HK",2001 +"2002-01-01","The first day of January","HK",2002 +"2002-02-12","Lunar New Year's Day","HK",2002 +"2002-02-13","The second day of Lunar New Year","HK",2002 +"2002-02-14","The third day of Lunar New Year","HK",2002 +"2002-03-29","Good Friday","HK",2002 +"2002-03-30","The day following Good Friday","HK",2002 +"2002-04-01","Easter Monday","HK",2002 +"2002-04-05","Ching Ming Festival","HK",2002 +"2002-05-01","Labour Day","HK",2002 +"2002-05-20","The day following The Birthday of the Buddha","HK",2002 +"2002-06-15","Tuen Ng Festival","HK",2002 +"2002-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2002 +"2002-09-21","Chinese Mid-Autumn Festival","HK",2002 +"2002-10-01","National Day","HK",2002 +"2002-10-14","Chung Yeung Festival","HK",2002 +"2002-12-25","Christmas Day","HK",2002 +"2002-12-26","The first weekday after Christmas Day","HK",2002 +"2003-01-01","The first day of January","HK",2003 +"2003-02-01","Lunar New Year's Day","HK",2003 +"2003-02-03","The third day of Lunar New Year","HK",2003 +"2003-02-04","The fourth day of Lunar New Year","HK",2003 +"2003-04-05","Ching Ming Festival","HK",2003 +"2003-04-18","Good Friday","HK",2003 +"2003-04-19","The day following Good Friday","HK",2003 +"2003-04-21","Easter Monday","HK",2003 +"2003-05-01","Labour Day","HK",2003 +"2003-05-08","The Birthday of the Buddha","HK",2003 +"2003-06-04","Tuen Ng Festival","HK",2003 +"2003-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2003 +"2003-09-12","The day following the Chinese Mid-Autumn Festival","HK",2003 +"2003-10-01","National Day","HK",2003 +"2003-10-04","Chung Yeung Festival","HK",2003 +"2003-12-25","Christmas Day","HK",2003 +"2003-12-26","The first weekday after Christmas Day","HK",2003 +"2004-01-01","The first day of January","HK",2004 +"2004-01-22","Lunar New Year's Day","HK",2004 +"2004-01-23","The second day of Lunar New Year","HK",2004 +"2004-01-24","The third day of Lunar New Year","HK",2004 +"2004-04-05","The day following Ching Ming Festival","HK",2004 +"2004-04-09","Good Friday","HK",2004 +"2004-04-10","The day following Good Friday","HK",2004 +"2004-04-12","Easter Monday","HK",2004 +"2004-05-01","Labour Day","HK",2004 +"2004-05-26","The Birthday of the Buddha","HK",2004 +"2004-06-22","Tuen Ng Festival","HK",2004 +"2004-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2004 +"2004-09-29","The day following the Chinese Mid-Autumn Festival","HK",2004 +"2004-10-01","National Day","HK",2004 +"2004-10-22","Chung Yeung Festival","HK",2004 +"2004-12-25","Christmas Day","HK",2004 +"2004-12-27","The first weekday after Christmas Day","HK",2004 +"2005-01-01","The first day of January","HK",2005 +"2005-02-09","Lunar New Year's Day","HK",2005 +"2005-02-10","The second day of Lunar New Year","HK",2005 +"2005-02-11","The third day of Lunar New Year","HK",2005 +"2005-03-25","Good Friday","HK",2005 +"2005-03-26","The day following Good Friday","HK",2005 +"2005-03-28","Easter Monday","HK",2005 +"2005-04-05","Ching Ming Festival","HK",2005 +"2005-05-02","The day following Labour Day","HK",2005 +"2005-05-16","The day following The Birthday of the Buddha","HK",2005 +"2005-06-11","Tuen Ng Festival","HK",2005 +"2005-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2005 +"2005-09-19","The day following the Chinese Mid-Autumn Festival","HK",2005 +"2005-10-01","National Day","HK",2005 +"2005-10-11","Chung Yeung Festival","HK",2005 +"2005-12-26","The first weekday after Christmas Day","HK",2005 +"2005-12-27","The second weekday after Christmas Day","HK",2005 +"2006-01-02","The day following the first day of January","HK",2006 +"2006-01-28","The day preceding Lunar New Year's Day","HK",2006 +"2006-01-30","The second day of Lunar New Year","HK",2006 +"2006-01-31","The third day of Lunar New Year","HK",2006 +"2006-04-05","Ching Ming Festival","HK",2006 +"2006-04-14","Good Friday","HK",2006 +"2006-04-15","The day following Good Friday","HK",2006 +"2006-04-17","Easter Monday","HK",2006 +"2006-05-01","Labour Day","HK",2006 +"2006-05-05","The Birthday of the Buddha","HK",2006 +"2006-05-31","Tuen Ng Festival","HK",2006 +"2006-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2006 +"2006-10-02","The day following National Day","HK",2006 +"2006-10-07","The day following the Chinese Mid-Autumn Festival","HK",2006 +"2006-10-30","Chung Yeung Festival","HK",2006 +"2006-12-25","Christmas Day","HK",2006 +"2006-12-26","The first weekday after Christmas Day","HK",2006 +"2007-01-01","The first day of January","HK",2007 +"2007-02-17","The day preceding Lunar New Year's Day","HK",2007 +"2007-02-19","The second day of Lunar New Year","HK",2007 +"2007-02-20","The third day of Lunar New Year","HK",2007 +"2007-04-05","Ching Ming Festival","HK",2007 +"2007-04-06","Good Friday","HK",2007 +"2007-04-07","The day following Good Friday","HK",2007 +"2007-04-09","Easter Monday","HK",2007 +"2007-05-01","Labour Day","HK",2007 +"2007-05-24","The Birthday of the Buddha","HK",2007 +"2007-06-19","Tuen Ng Festival","HK",2007 +"2007-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2007 +"2007-09-26","The day following the Chinese Mid-Autumn Festival","HK",2007 +"2007-10-01","National Day","HK",2007 +"2007-10-19","Chung Yeung Festival","HK",2007 +"2007-12-25","Christmas Day","HK",2007 +"2007-12-26","The first weekday after Christmas Day","HK",2007 +"2008-01-01","The first day of January","HK",2008 +"2008-02-07","Lunar New Year's Day","HK",2008 +"2008-02-08","The second day of Lunar New Year","HK",2008 +"2008-02-09","The third day of Lunar New Year","HK",2008 +"2008-03-21","Good Friday","HK",2008 +"2008-03-22","The day following Good Friday","HK",2008 +"2008-03-24","Easter Monday","HK",2008 +"2008-04-04","Ching Ming Festival","HK",2008 +"2008-05-01","Labour Day","HK",2008 +"2008-05-12","The Birthday of the Buddha","HK",2008 +"2008-06-09","The day following Tuen Ng Festival","HK",2008 +"2008-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2008 +"2008-09-15","The day following the Chinese Mid-Autumn Festival","HK",2008 +"2008-10-01","National Day","HK",2008 +"2008-10-07","Chung Yeung Festival","HK",2008 +"2008-12-25","Christmas Day","HK",2008 +"2008-12-26","The first weekday after Christmas Day","HK",2008 +"2009-01-01","The first day of January","HK",2009 +"2009-01-26","Lunar New Year's Day","HK",2009 +"2009-01-27","The second day of Lunar New Year","HK",2009 +"2009-01-28","The third day of Lunar New Year","HK",2009 +"2009-04-04","Ching Ming Festival","HK",2009 +"2009-04-10","Good Friday","HK",2009 +"2009-04-11","The day following Good Friday","HK",2009 +"2009-04-13","Easter Monday","HK",2009 +"2009-05-01","Labour Day","HK",2009 +"2009-05-02","The Birthday of the Buddha","HK",2009 +"2009-05-28","Tuen Ng Festival","HK",2009 +"2009-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2009 +"2009-10-01","National Day","HK",2009 +"2009-10-03","Chinese Mid-Autumn Festival","HK",2009 +"2009-10-26","Chung Yeung Festival","HK",2009 +"2009-12-25","Christmas Day","HK",2009 +"2009-12-26","The first weekday after Christmas Day","HK",2009 +"2010-01-01","The first day of January","HK",2010 +"2010-02-13","The day preceding Lunar New Year's Day","HK",2010 +"2010-02-15","The second day of Lunar New Year","HK",2010 +"2010-02-16","The third day of Lunar New Year","HK",2010 +"2010-04-02","Good Friday","HK",2010 +"2010-04-03","The day following Good Friday","HK",2010 +"2010-04-05","Easter Monday","HK",2010 +"2010-04-06","The day following Ching Ming Festival","HK",2010 +"2010-05-01","Labour Day","HK",2010 +"2010-05-21","The Birthday of the Buddha","HK",2010 +"2010-06-16","Tuen Ng Festival","HK",2010 +"2010-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2010 +"2010-09-23","The day following the Chinese Mid-Autumn Festival","HK",2010 +"2010-10-01","National Day","HK",2010 +"2010-10-16","Chung Yeung Festival","HK",2010 +"2010-12-25","Christmas Day","HK",2010 +"2010-12-27","The first weekday after Christmas Day","HK",2010 +"2011-01-01","The first day of January","HK",2011 +"2011-02-03","Lunar New Year's Day","HK",2011 +"2011-02-04","The second day of Lunar New Year","HK",2011 +"2011-02-05","The third day of Lunar New Year","HK",2011 +"2011-04-05","Ching Ming Festival","HK",2011 +"2011-04-22","Good Friday","HK",2011 +"2011-04-23","The day following Good Friday","HK",2011 +"2011-04-25","Easter Monday","HK",2011 +"2011-05-02","The day following Labour Day","HK",2011 +"2011-05-10","The Birthday of the Buddha","HK",2011 +"2011-06-06","Tuen Ng Festival","HK",2011 +"2011-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2011 +"2011-09-13","The day following the Chinese Mid-Autumn Festival","HK",2011 +"2011-10-01","National Day","HK",2011 +"2011-10-05","Chung Yeung Festival","HK",2011 +"2011-12-26","The first weekday after Christmas Day","HK",2011 +"2011-12-27","The second weekday after Christmas Day","HK",2011 +"2012-01-02","The day following the first day of January","HK",2012 +"2012-01-23","Lunar New Year's Day","HK",2012 +"2012-01-24","The second day of Lunar New Year","HK",2012 +"2012-01-25","The third day of Lunar New Year","HK",2012 +"2012-04-04","Ching Ming Festival","HK",2012 +"2012-04-06","Good Friday","HK",2012 +"2012-04-07","The day following Good Friday","HK",2012 +"2012-04-09","Easter Monday","HK",2012 +"2012-04-28","The Birthday of the Buddha","HK",2012 +"2012-05-01","Labour Day","HK",2012 +"2012-06-23","Tuen Ng Festival","HK",2012 +"2012-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2012 +"2012-10-01","The day following the Chinese Mid-Autumn Festival","HK",2012 +"2012-10-02","The day following National Day","HK",2012 +"2012-10-23","Chung Yeung Festival","HK",2012 +"2012-12-25","Christmas Day","HK",2012 +"2012-12-26","The first weekday after Christmas Day","HK",2012 +"2013-01-01","The first day of January","HK",2013 +"2013-02-11","The second day of Lunar New Year","HK",2013 +"2013-02-12","The third day of Lunar New Year","HK",2013 +"2013-02-13","The fourth day of Lunar New Year","HK",2013 +"2013-03-29","Good Friday","HK",2013 +"2013-03-30","The day following Good Friday","HK",2013 +"2013-04-01","Easter Monday","HK",2013 +"2013-04-04","Ching Ming Festival","HK",2013 +"2013-05-01","Labour Day","HK",2013 +"2013-05-17","The Birthday of the Buddha","HK",2013 +"2013-06-12","Tuen Ng Festival","HK",2013 +"2013-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2013 +"2013-09-20","The day following the Chinese Mid-Autumn Festival","HK",2013 +"2013-10-01","National Day","HK",2013 +"2013-10-14","The day following Chung Yeung Festival","HK",2013 +"2013-12-25","Christmas Day","HK",2013 +"2013-12-26","The first weekday after Christmas Day","HK",2013 +"2014-01-01","The first day of January","HK",2014 +"2014-01-31","Lunar New Year's Day","HK",2014 +"2014-02-01","The second day of Lunar New Year","HK",2014 +"2014-02-03","The fourth day of Lunar New Year","HK",2014 +"2014-04-05","Ching Ming Festival","HK",2014 +"2014-04-18","Good Friday","HK",2014 +"2014-04-19","The day following Good Friday","HK",2014 +"2014-04-21","Easter Monday","HK",2014 +"2014-05-01","Labour Day","HK",2014 +"2014-05-06","The Birthday of the Buddha","HK",2014 +"2014-06-02","Tuen Ng Festival","HK",2014 +"2014-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2014 +"2014-09-09","The day following the Chinese Mid-Autumn Festival","HK",2014 +"2014-10-01","National Day","HK",2014 +"2014-10-02","Chung Yeung Festival","HK",2014 +"2014-12-25","Christmas Day","HK",2014 +"2014-12-26","The first weekday after Christmas Day","HK",2014 +"2015-01-01","The first day of January","HK",2015 +"2015-02-19","Lunar New Year's Day","HK",2015 +"2015-02-20","The second day of Lunar New Year","HK",2015 +"2015-02-21","The third day of Lunar New Year","HK",2015 +"2015-04-03","Good Friday","HK",2015 +"2015-04-04","The day following Good Friday","HK",2015 +"2015-04-06","The day following Ching Ming Festival","HK",2015 +"2015-04-07","The day following Easter Monday","HK",2015 +"2015-05-01","Labour Day","HK",2015 +"2015-05-25","The Birthday of the Buddha","HK",2015 +"2015-06-20","Tuen Ng Festival","HK",2015 +"2015-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2015 +"2015-09-03","The 70th anniversary day of the victory of the Chinese people's war of resistance against Japanese aggression","HK",2015 +"2015-09-28","The day following the Chinese Mid-Autumn Festival","HK",2015 +"2015-10-01","National Day","HK",2015 +"2015-10-21","Chung Yeung Festival","HK",2015 +"2015-12-25","Christmas Day","HK",2015 +"2015-12-26","The first weekday after Christmas Day","HK",2015 +"2016-01-01","The first day of January","HK",2016 +"2016-02-08","Lunar New Year's Day","HK",2016 +"2016-02-09","The second day of Lunar New Year","HK",2016 +"2016-02-10","The third day of Lunar New Year","HK",2016 +"2016-03-25","Good Friday","HK",2016 +"2016-03-26","The day following Good Friday","HK",2016 +"2016-03-28","Easter Monday","HK",2016 +"2016-04-04","Ching Ming Festival","HK",2016 +"2016-05-02","The day following Labour Day","HK",2016 +"2016-05-14","The Birthday of the Buddha","HK",2016 +"2016-06-09","Tuen Ng Festival","HK",2016 +"2016-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2016 +"2016-09-16","The day following the Chinese Mid-Autumn Festival","HK",2016 +"2016-10-01","National Day","HK",2016 +"2016-10-10","The day following Chung Yeung Festival","HK",2016 +"2016-12-26","The first weekday after Christmas Day","HK",2016 +"2016-12-27","The second weekday after Christmas Day","HK",2016 +"2017-01-02","The day following the first day of January","HK",2017 +"2017-01-28","Lunar New Year's Day","HK",2017 +"2017-01-30","The third day of Lunar New Year","HK",2017 +"2017-01-31","The fourth day of Lunar New Year","HK",2017 +"2017-04-04","Ching Ming Festival","HK",2017 +"2017-04-14","Good Friday","HK",2017 +"2017-04-15","The day following Good Friday","HK",2017 +"2017-04-17","Easter Monday","HK",2017 +"2017-05-01","Labour Day","HK",2017 +"2017-05-03","The Birthday of the Buddha","HK",2017 +"2017-05-30","Tuen Ng Festival","HK",2017 +"2017-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2017 +"2017-10-02","The day following National Day","HK",2017 +"2017-10-05","The day following the Chinese Mid-Autumn Festival","HK",2017 +"2017-10-28","Chung Yeung Festival","HK",2017 +"2017-12-25","Christmas Day","HK",2017 +"2017-12-26","The first weekday after Christmas Day","HK",2017 +"2018-01-01","The first day of January","HK",2018 +"2018-02-16","Lunar New Year's Day","HK",2018 +"2018-02-17","The second day of Lunar New Year","HK",2018 +"2018-02-19","The fourth day of Lunar New Year","HK",2018 +"2018-03-30","Good Friday","HK",2018 +"2018-03-31","The day following Good Friday","HK",2018 +"2018-04-02","Easter Monday","HK",2018 +"2018-04-05","Ching Ming Festival","HK",2018 +"2018-05-01","Labour Day","HK",2018 +"2018-05-22","The Birthday of the Buddha","HK",2018 +"2018-06-18","Tuen Ng Festival","HK",2018 +"2018-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2018 +"2018-09-25","The day following the Chinese Mid-Autumn Festival","HK",2018 +"2018-10-01","National Day","HK",2018 +"2018-10-17","Chung Yeung Festival","HK",2018 +"2018-12-25","Christmas Day","HK",2018 +"2018-12-26","The first weekday after Christmas Day","HK",2018 +"2019-01-01","The first day of January","HK",2019 +"2019-02-05","Lunar New Year's Day","HK",2019 +"2019-02-06","The second day of Lunar New Year","HK",2019 +"2019-02-07","The third day of Lunar New Year","HK",2019 +"2019-04-05","Ching Ming Festival","HK",2019 +"2019-04-19","Good Friday","HK",2019 +"2019-04-20","The day following Good Friday","HK",2019 +"2019-04-22","Easter Monday","HK",2019 +"2019-05-01","Labour Day","HK",2019 +"2019-05-13","The day following The Birthday of the Buddha","HK",2019 +"2019-06-07","Tuen Ng Festival","HK",2019 +"2019-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2019 +"2019-09-14","The day following the Chinese Mid-Autumn Festival","HK",2019 +"2019-10-01","National Day","HK",2019 +"2019-10-07","Chung Yeung Festival","HK",2019 +"2019-12-25","Christmas Day","HK",2019 +"2019-12-26","The first weekday after Christmas Day","HK",2019 +"2020-01-01","The first day of January","HK",2020 +"2020-01-25","Lunar New Year's Day","HK",2020 +"2020-01-27","The third day of Lunar New Year","HK",2020 +"2020-01-28","The fourth day of Lunar New Year","HK",2020 +"2020-04-04","Ching Ming Festival","HK",2020 +"2020-04-10","Good Friday","HK",2020 +"2020-04-11","The day following Good Friday","HK",2020 +"2020-04-13","Easter Monday","HK",2020 +"2020-04-30","The Birthday of the Buddha","HK",2020 +"2020-05-01","Labour Day","HK",2020 +"2020-06-25","Tuen Ng Festival","HK",2020 +"2020-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2020 +"2020-10-01","National Day","HK",2020 +"2020-10-02","The day following the Chinese Mid-Autumn Festival","HK",2020 +"2020-10-26","The day following Chung Yeung Festival","HK",2020 +"2020-12-25","Christmas Day","HK",2020 +"2020-12-26","The first weekday after Christmas Day","HK",2020 +"2021-01-01","The first day of January","HK",2021 +"2021-02-12","Lunar New Year's Day","HK",2021 +"2021-02-13","The second day of Lunar New Year","HK",2021 +"2021-02-15","The fourth day of Lunar New Year","HK",2021 +"2021-04-02","Good Friday","HK",2021 +"2021-04-03","The day following Good Friday","HK",2021 +"2021-04-05","The day following Ching Ming Festival","HK",2021 +"2021-04-06","The day following Easter Monday","HK",2021 +"2021-05-01","Labour Day","HK",2021 +"2021-05-19","The Birthday of the Buddha","HK",2021 +"2021-06-14","Tuen Ng Festival","HK",2021 +"2021-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2021 +"2021-09-22","The day following the Chinese Mid-Autumn Festival","HK",2021 +"2021-10-01","National Day","HK",2021 +"2021-10-14","Chung Yeung Festival","HK",2021 +"2021-12-25","Christmas Day","HK",2021 +"2021-12-27","The first weekday after Christmas Day","HK",2021 +"2022-01-01","The first day of January","HK",2022 +"2022-02-01","Lunar New Year's Day","HK",2022 +"2022-02-02","The second day of Lunar New Year","HK",2022 +"2022-02-03","The third day of Lunar New Year","HK",2022 +"2022-04-05","Ching Ming Festival","HK",2022 +"2022-04-15","Good Friday","HK",2022 +"2022-04-16","The day following Good Friday","HK",2022 +"2022-04-18","Easter Monday","HK",2022 +"2022-05-02","The day following Labour Day","HK",2022 +"2022-05-09","The day following The Birthday of the Buddha","HK",2022 +"2022-06-03","Tuen Ng Festival","HK",2022 +"2022-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2022 +"2022-09-12","The second day of the Chinese Mid-Autumn Festival (Monday)","HK",2022 +"2022-10-01","National Day","HK",2022 +"2022-10-04","Chung Yeung Festival","HK",2022 +"2022-12-26","The first weekday after Christmas Day","HK",2022 +"2022-12-27","The second weekday after Christmas Day","HK",2022 +"2023-01-02","The day following the first day of January","HK",2023 +"2023-01-23","The second day of Lunar New Year","HK",2023 +"2023-01-24","The third day of Lunar New Year","HK",2023 +"2023-01-25","The fourth day of Lunar New Year","HK",2023 +"2023-04-05","Ching Ming Festival","HK",2023 +"2023-04-07","Good Friday","HK",2023 +"2023-04-08","The day following Good Friday","HK",2023 +"2023-04-10","Easter Monday","HK",2023 +"2023-05-01","Labour Day","HK",2023 +"2023-05-26","The Birthday of the Buddha","HK",2023 +"2023-06-22","Tuen Ng Festival","HK",2023 +"2023-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2023 +"2023-09-30","The day following the Chinese Mid-Autumn Festival","HK",2023 +"2023-10-02","The day following National Day","HK",2023 +"2023-10-23","Chung Yeung Festival","HK",2023 +"2023-12-25","Christmas Day","HK",2023 +"2023-12-26","The first weekday after Christmas Day","HK",2023 +"2024-01-01","The first day of January","HK",2024 +"2024-02-10","Lunar New Year's Day","HK",2024 +"2024-02-12","The third day of Lunar New Year","HK",2024 +"2024-02-13","The fourth day of Lunar New Year","HK",2024 +"2024-03-29","Good Friday","HK",2024 +"2024-03-30","The day following Good Friday","HK",2024 +"2024-04-01","Easter Monday","HK",2024 +"2024-04-04","Ching Ming Festival","HK",2024 +"2024-05-01","Labour Day","HK",2024 +"2024-05-15","The Birthday of the Buddha","HK",2024 +"2024-06-10","Tuen Ng Festival","HK",2024 +"2024-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2024 +"2024-09-18","The day following the Chinese Mid-Autumn Festival","HK",2024 +"2024-10-01","National Day","HK",2024 +"2024-10-11","Chung Yeung Festival","HK",2024 +"2024-12-25","Christmas Day","HK",2024 +"2024-12-26","The first weekday after Christmas Day","HK",2024 +"2025-01-01","The first day of January","HK",2025 +"2025-01-29","Lunar New Year's Day","HK",2025 +"2025-01-30","The second day of Lunar New Year","HK",2025 +"2025-01-31","The third day of Lunar New Year","HK",2025 +"2025-04-04","Ching Ming Festival","HK",2025 +"2025-04-18","Good Friday","HK",2025 +"2025-04-19","The day following Good Friday","HK",2025 +"2025-04-21","Easter Monday","HK",2025 +"2025-05-01","Labour Day","HK",2025 +"2025-05-05","The day following The Birthday of the Buddha","HK",2025 +"2025-05-31","Tuen Ng Festival","HK",2025 +"2025-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2025 +"2025-10-01","National Day","HK",2025 +"2025-10-07","The day following the Chinese Mid-Autumn Festival","HK",2025 +"2025-10-29","Chung Yeung Festival","HK",2025 +"2025-12-25","Christmas Day","HK",2025 +"2025-12-26","The first weekday after Christmas Day","HK",2025 +"2026-01-01","The first day of January","HK",2026 +"2026-02-17","Lunar New Year's Day","HK",2026 +"2026-02-18","The second day of Lunar New Year","HK",2026 +"2026-02-19","The third day of Lunar New Year","HK",2026 +"2026-04-03","Good Friday","HK",2026 +"2026-04-04","The day following Good Friday","HK",2026 +"2026-04-06","The day following Ching Ming Festival","HK",2026 +"2026-04-07","The day following Easter Monday","HK",2026 +"2026-05-01","Labour Day","HK",2026 +"2026-05-25","The day following The Birthday of the Buddha","HK",2026 +"2026-06-19","Tuen Ng Festival","HK",2026 +"2026-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2026 +"2026-09-26","The day following the Chinese Mid-Autumn Festival","HK",2026 +"2026-10-01","National Day","HK",2026 +"2026-10-19","The day following Chung Yeung Festival","HK",2026 +"2026-12-25","Christmas Day","HK",2026 +"2026-12-26","The first weekday after Christmas Day","HK",2026 +"2027-01-01","The first day of January","HK",2027 +"2027-02-06","Lunar New Year's Day","HK",2027 +"2027-02-08","The third day of Lunar New Year","HK",2027 +"2027-02-09","The fourth day of Lunar New Year","HK",2027 +"2027-03-26","Good Friday","HK",2027 +"2027-03-27","The day following Good Friday","HK",2027 +"2027-03-29","Easter Monday","HK",2027 +"2027-04-05","Ching Ming Festival","HK",2027 +"2027-05-01","Labour Day","HK",2027 +"2027-05-13","The Birthday of the Buddha","HK",2027 +"2027-06-09","Tuen Ng Festival","HK",2027 +"2027-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2027 +"2027-09-16","The day following the Chinese Mid-Autumn Festival","HK",2027 +"2027-10-01","National Day","HK",2027 +"2027-10-08","Chung Yeung Festival","HK",2027 +"2027-12-25","Christmas Day","HK",2027 +"2027-12-27","The first weekday after Christmas Day","HK",2027 +"2028-01-01","The first day of January","HK",2028 +"2028-01-26","Lunar New Year's Day","HK",2028 +"2028-01-27","The second day of Lunar New Year","HK",2028 +"2028-01-28","The third day of Lunar New Year","HK",2028 +"2028-04-04","Ching Ming Festival","HK",2028 +"2028-04-14","Good Friday","HK",2028 +"2028-04-15","The day following Good Friday","HK",2028 +"2028-04-17","Easter Monday","HK",2028 +"2028-05-01","Labour Day","HK",2028 +"2028-05-02","The Birthday of the Buddha","HK",2028 +"2028-05-29","The day following Tuen Ng Festival","HK",2028 +"2028-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2028 +"2028-10-02","The day following National Day","HK",2028 +"2028-10-04","The day following the Chinese Mid-Autumn Festival","HK",2028 +"2028-10-26","Chung Yeung Festival","HK",2028 +"2028-12-25","Christmas Day","HK",2028 +"2028-12-26","The first weekday after Christmas Day","HK",2028 +"2029-01-01","The first day of January","HK",2029 +"2029-02-13","Lunar New Year's Day","HK",2029 +"2029-02-14","The second day of Lunar New Year","HK",2029 +"2029-02-15","The third day of Lunar New Year","HK",2029 +"2029-03-30","Good Friday","HK",2029 +"2029-03-31","The day following Good Friday","HK",2029 +"2029-04-02","Easter Monday","HK",2029 +"2029-04-04","Ching Ming Festival","HK",2029 +"2029-05-01","Labour Day","HK",2029 +"2029-05-21","The day following The Birthday of the Buddha","HK",2029 +"2029-06-16","Tuen Ng Festival","HK",2029 +"2029-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2029 +"2029-09-24","The second day of the Chinese Mid-Autumn Festival (Monday)","HK",2029 +"2029-10-01","National Day","HK",2029 +"2029-10-16","Chung Yeung Festival","HK",2029 +"2029-12-25","Christmas Day","HK",2029 +"2029-12-26","The first weekday after Christmas Day","HK",2029 +"2030-01-01","The first day of January","HK",2030 +"2030-02-04","The second day of Lunar New Year","HK",2030 +"2030-02-05","The third day of Lunar New Year","HK",2030 +"2030-02-06","The fourth day of Lunar New Year","HK",2030 +"2030-04-05","Ching Ming Festival","HK",2030 +"2030-04-19","Good Friday","HK",2030 +"2030-04-20","The day following Good Friday","HK",2030 +"2030-04-22","Easter Monday","HK",2030 +"2030-05-01","Labour Day","HK",2030 +"2030-05-09","The Birthday of the Buddha","HK",2030 +"2030-06-05","Tuen Ng Festival","HK",2030 +"2030-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2030 +"2030-09-13","The day following the Chinese Mid-Autumn Festival","HK",2030 +"2030-10-01","National Day","HK",2030 +"2030-10-05","Chung Yeung Festival","HK",2030 +"2030-12-25","Christmas Day","HK",2030 +"2030-12-26","The first weekday after Christmas Day","HK",2030 +"2031-01-01","The first day of January","HK",2031 +"2031-01-23","Lunar New Year's Day","HK",2031 +"2031-01-24","The second day of Lunar New Year","HK",2031 +"2031-01-25","The third day of Lunar New Year","HK",2031 +"2031-04-05","Ching Ming Festival","HK",2031 +"2031-04-11","Good Friday","HK",2031 +"2031-04-12","The day following Good Friday","HK",2031 +"2031-04-14","Easter Monday","HK",2031 +"2031-05-01","Labour Day","HK",2031 +"2031-05-28","The Birthday of the Buddha","HK",2031 +"2031-06-24","Tuen Ng Festival","HK",2031 +"2031-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2031 +"2031-10-01","National Day","HK",2031 +"2031-10-02","The day following the Chinese Mid-Autumn Festival","HK",2031 +"2031-10-24","Chung Yeung Festival","HK",2031 +"2031-12-25","Christmas Day","HK",2031 +"2031-12-26","The first weekday after Christmas Day","HK",2031 +"2032-01-01","The first day of January","HK",2032 +"2032-02-11","Lunar New Year's Day","HK",2032 +"2032-02-12","The second day of Lunar New Year","HK",2032 +"2032-02-13","The third day of Lunar New Year","HK",2032 +"2032-03-26","Good Friday","HK",2032 +"2032-03-27","The day following Good Friday","HK",2032 +"2032-03-29","Easter Monday","HK",2032 +"2032-04-05","The day following Ching Ming Festival","HK",2032 +"2032-05-01","Labour Day","HK",2032 +"2032-05-17","The day following The Birthday of the Buddha","HK",2032 +"2032-06-12","Tuen Ng Festival","HK",2032 +"2032-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2032 +"2032-09-20","The day following the Chinese Mid-Autumn Festival","HK",2032 +"2032-10-01","National Day","HK",2032 +"2032-10-12","Chung Yeung Festival","HK",2032 +"2032-12-25","Christmas Day","HK",2032 +"2032-12-27","The first weekday after Christmas Day","HK",2032 +"2033-01-01","The first day of January","HK",2033 +"2033-01-31","Lunar New Year's Day","HK",2033 +"2033-02-01","The second day of Lunar New Year","HK",2033 +"2033-02-02","The third day of Lunar New Year","HK",2033 +"2033-04-04","Ching Ming Festival","HK",2033 +"2033-04-15","Good Friday","HK",2033 +"2033-04-16","The day following Good Friday","HK",2033 +"2033-04-18","Easter Monday","HK",2033 +"2033-05-02","The day following Labour Day","HK",2033 +"2033-05-06","The Birthday of the Buddha","HK",2033 +"2033-06-01","Tuen Ng Festival","HK",2033 +"2033-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2033 +"2033-09-09","The day following the Chinese Mid-Autumn Festival","HK",2033 +"2033-10-01","Chung Yeung Festival","HK",2033 +"2033-10-01","National Day","HK",2033 +"2033-12-26","The first weekday after Christmas Day","HK",2033 +"2033-12-27","The second weekday after Christmas Day","HK",2033 +"2034-01-02","The day following the first day of January","HK",2034 +"2034-02-20","The second day of Lunar New Year","HK",2034 +"2034-02-21","The third day of Lunar New Year","HK",2034 +"2034-02-22","The fourth day of Lunar New Year","HK",2034 +"2034-04-05","Ching Ming Festival","HK",2034 +"2034-04-07","Good Friday","HK",2034 +"2034-04-08","The day following Good Friday","HK",2034 +"2034-04-10","Easter Monday","HK",2034 +"2034-05-01","Labour Day","HK",2034 +"2034-05-25","The Birthday of the Buddha","HK",2034 +"2034-06-20","Tuen Ng Festival","HK",2034 +"2034-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2034 +"2034-09-28","The day following the Chinese Mid-Autumn Festival","HK",2034 +"2034-10-02","The day following National Day","HK",2034 +"2034-10-20","Chung Yeung Festival","HK",2034 +"2034-12-25","Christmas Day","HK",2034 +"2034-12-26","The first weekday after Christmas Day","HK",2034 +"2035-01-01","The first day of January","HK",2035 +"2035-02-08","Lunar New Year's Day","HK",2035 +"2035-02-09","The second day of Lunar New Year","HK",2035 +"2035-02-10","The third day of Lunar New Year","HK",2035 +"2035-03-23","Good Friday","HK",2035 +"2035-03-24","The day following Good Friday","HK",2035 +"2035-03-26","Easter Monday","HK",2035 +"2035-04-05","Ching Ming Festival","HK",2035 +"2035-05-01","Labour Day","HK",2035 +"2035-05-15","The Birthday of the Buddha","HK",2035 +"2035-06-11","The day following Tuen Ng Festival","HK",2035 +"2035-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2035 +"2035-09-17","The day following the Chinese Mid-Autumn Festival","HK",2035 +"2035-10-01","National Day","HK",2035 +"2035-10-09","Chung Yeung Festival","HK",2035 +"2035-12-25","Christmas Day","HK",2035 +"2035-12-26","The first weekday after Christmas Day","HK",2035 +"2036-01-01","The first day of January","HK",2036 +"2036-01-28","Lunar New Year's Day","HK",2036 +"2036-01-29","The second day of Lunar New Year","HK",2036 +"2036-01-30","The third day of Lunar New Year","HK",2036 +"2036-04-04","Ching Ming Festival","HK",2036 +"2036-04-11","Good Friday","HK",2036 +"2036-04-12","The day following Good Friday","HK",2036 +"2036-04-14","Easter Monday","HK",2036 +"2036-05-01","Labour Day","HK",2036 +"2036-05-03","The Birthday of the Buddha","HK",2036 +"2036-05-30","Tuen Ng Festival","HK",2036 +"2036-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2036 +"2036-10-01","National Day","HK",2036 +"2036-10-06","The second day of the Chinese Mid-Autumn Festival (Monday)","HK",2036 +"2036-10-27","Chung Yeung Festival","HK",2036 +"2036-12-25","Christmas Day","HK",2036 +"2036-12-26","The first weekday after Christmas Day","HK",2036 +"2037-01-01","The first day of January","HK",2037 +"2037-02-16","The second day of Lunar New Year","HK",2037 +"2037-02-17","The third day of Lunar New Year","HK",2037 +"2037-02-18","The fourth day of Lunar New Year","HK",2037 +"2037-04-03","Good Friday","HK",2037 +"2037-04-04","Ching Ming Festival","HK",2037 +"2037-04-04","The day following Good Friday","HK",2037 +"2037-04-06","Easter Monday","HK",2037 +"2037-05-01","Labour Day","HK",2037 +"2037-05-22","The Birthday of the Buddha","HK",2037 +"2037-06-18","Tuen Ng Festival","HK",2037 +"2037-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2037 +"2037-09-25","The day following the Chinese Mid-Autumn Festival","HK",2037 +"2037-10-01","National Day","HK",2037 +"2037-10-17","Chung Yeung Festival","HK",2037 +"2037-12-25","Christmas Day","HK",2037 +"2037-12-26","The first weekday after Christmas Day","HK",2037 +"2038-01-01","The first day of January","HK",2038 +"2038-02-04","Lunar New Year's Day","HK",2038 +"2038-02-05","The second day of Lunar New Year","HK",2038 +"2038-02-06","The third day of Lunar New Year","HK",2038 +"2038-04-05","Ching Ming Festival","HK",2038 +"2038-04-23","Good Friday","HK",2038 +"2038-04-24","The day following Good Friday","HK",2038 +"2038-04-26","Easter Monday","HK",2038 +"2038-05-01","Labour Day","HK",2038 +"2038-05-11","The Birthday of the Buddha","HK",2038 +"2038-06-07","Tuen Ng Festival","HK",2038 +"2038-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2038 +"2038-09-14","The day following the Chinese Mid-Autumn Festival","HK",2038 +"2038-10-01","National Day","HK",2038 +"2038-10-07","Chung Yeung Festival","HK",2038 +"2038-12-25","Christmas Day","HK",2038 +"2038-12-27","The first weekday after Christmas Day","HK",2038 +"2039-01-01","The first day of January","HK",2039 +"2039-01-24","Lunar New Year's Day","HK",2039 +"2039-01-25","The second day of Lunar New Year","HK",2039 +"2039-01-26","The third day of Lunar New Year","HK",2039 +"2039-04-05","Ching Ming Festival","HK",2039 +"2039-04-08","Good Friday","HK",2039 +"2039-04-09","The day following Good Friday","HK",2039 +"2039-04-11","Easter Monday","HK",2039 +"2039-04-30","The Birthday of the Buddha","HK",2039 +"2039-05-02","The day following Labour Day","HK",2039 +"2039-05-27","Tuen Ng Festival","HK",2039 +"2039-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2039 +"2039-10-01","National Day","HK",2039 +"2039-10-03","The day following the Chinese Mid-Autumn Festival","HK",2039 +"2039-10-26","Chung Yeung Festival","HK",2039 +"2039-12-26","The first weekday after Christmas Day","HK",2039 +"2039-12-27","The second weekday after Christmas Day","HK",2039 +"2040-01-02","The day following the first day of January","HK",2040 +"2040-02-13","The second day of Lunar New Year","HK",2040 +"2040-02-14","The third day of Lunar New Year","HK",2040 +"2040-02-15","The fourth day of Lunar New Year","HK",2040 +"2040-03-30","Good Friday","HK",2040 +"2040-03-31","The day following Good Friday","HK",2040 +"2040-04-02","Easter Monday","HK",2040 +"2040-04-04","Ching Ming Festival","HK",2040 +"2040-05-01","Labour Day","HK",2040 +"2040-05-18","The Birthday of the Buddha","HK",2040 +"2040-06-14","Tuen Ng Festival","HK",2040 +"2040-07-02","The day following Hong Kong Special Administrative Region Establishment Day","HK",2040 +"2040-09-21","The day following the Chinese Mid-Autumn Festival","HK",2040 +"2040-10-01","National Day","HK",2040 +"2040-10-15","The day following Chung Yeung Festival","HK",2040 +"2040-12-25","Christmas Day","HK",2040 +"2040-12-26","The first weekday after Christmas Day","HK",2040 +"2041-01-01","The first day of January","HK",2041 +"2041-02-01","Lunar New Year's Day","HK",2041 +"2041-02-02","The second day of Lunar New Year","HK",2041 +"2041-02-04","The fourth day of Lunar New Year","HK",2041 +"2041-04-04","Ching Ming Festival","HK",2041 +"2041-04-19","Good Friday","HK",2041 +"2041-04-20","The day following Good Friday","HK",2041 +"2041-04-22","Easter Monday","HK",2041 +"2041-05-01","Labour Day","HK",2041 +"2041-05-07","The Birthday of the Buddha","HK",2041 +"2041-06-03","Tuen Ng Festival","HK",2041 +"2041-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2041 +"2041-09-11","The day following the Chinese Mid-Autumn Festival","HK",2041 +"2041-10-01","National Day","HK",2041 +"2041-10-03","Chung Yeung Festival","HK",2041 +"2041-12-25","Christmas Day","HK",2041 +"2041-12-26","The first weekday after Christmas Day","HK",2041 +"2042-01-01","The first day of January","HK",2042 +"2042-01-22","Lunar New Year's Day","HK",2042 +"2042-01-23","The second day of Lunar New Year","HK",2042 +"2042-01-24","The third day of Lunar New Year","HK",2042 +"2042-04-04","Good Friday","HK",2042 +"2042-04-05","Ching Ming Festival","HK",2042 +"2042-04-05","The day following Good Friday","HK",2042 +"2042-04-07","Easter Monday","HK",2042 +"2042-05-01","Labour Day","HK",2042 +"2042-05-26","The Birthday of the Buddha","HK",2042 +"2042-06-23","The day following Tuen Ng Festival","HK",2042 +"2042-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2042 +"2042-09-29","The day following the Chinese Mid-Autumn Festival","HK",2042 +"2042-10-01","National Day","HK",2042 +"2042-10-22","Chung Yeung Festival","HK",2042 +"2042-12-25","Christmas Day","HK",2042 +"2042-12-26","The first weekday after Christmas Day","HK",2042 +"2043-01-01","The first day of January","HK",2043 +"2043-02-10","Lunar New Year's Day","HK",2043 +"2043-02-11","The second day of Lunar New Year","HK",2043 +"2043-02-12","The third day of Lunar New Year","HK",2043 +"2043-03-27","Good Friday","HK",2043 +"2043-03-28","The day following Good Friday","HK",2043 +"2043-03-30","Easter Monday","HK",2043 +"2043-04-06","The day following Ching Ming Festival","HK",2043 +"2043-05-01","Labour Day","HK",2043 +"2043-05-16","The Birthday of the Buddha","HK",2043 +"2043-06-11","Tuen Ng Festival","HK",2043 +"2043-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2043 +"2043-09-18","The day following the Chinese Mid-Autumn Festival","HK",2043 +"2043-10-01","National Day","HK",2043 +"2043-10-12","The day following Chung Yeung Festival","HK",2043 +"2043-12-25","Christmas Day","HK",2043 +"2043-12-26","The first weekday after Christmas Day","HK",2043 +"2044-01-01","The first day of January","HK",2044 +"2044-01-30","Lunar New Year's Day","HK",2044 +"2044-02-01","The third day of Lunar New Year","HK",2044 +"2044-02-02","The fourth day of Lunar New Year","HK",2044 +"2044-04-04","Ching Ming Festival","HK",2044 +"2044-04-15","Good Friday","HK",2044 +"2044-04-16","The day following Good Friday","HK",2044 +"2044-04-18","Easter Monday","HK",2044 +"2044-05-02","The day following Labour Day","HK",2044 +"2044-05-05","The Birthday of the Buddha","HK",2044 +"2044-05-31","Tuen Ng Festival","HK",2044 +"2044-07-01","Hong Kong Special Administrative Region Establishment Day","HK",2044 +"2044-10-01","National Day","HK",2044 +"2044-10-06","The day following the Chinese Mid-Autumn Festival","HK",2044 +"2044-10-29","Chung Yeung Festival","HK",2044 +"2044-12-26","The first weekday after Christmas Day","HK",2044 +"2044-12-27","The second weekday after Christmas Day","HK",2044 +"1995-01-01","New Year's Day","HN",1995 +"1995-04-13","Maundy Thursday","HN",1995 +"1995-04-14","Good Friday","HN",1995 +"1995-04-14","Panamerican Day","HN",1995 +"1995-04-15","Holy Saturday","HN",1995 +"1995-05-01","Labor Day","HN",1995 +"1995-09-15","Dia de la Independencia","HN",1995 +"1995-10-03","Morazan's Day","HN",1995 +"1995-10-12","Columbus Day","HN",1995 +"1995-10-21","Army Day","HN",1995 +"1995-12-25","Christmas","HN",1995 +"1996-01-01","New Year's Day","HN",1996 +"1996-04-04","Maundy Thursday","HN",1996 +"1996-04-05","Good Friday","HN",1996 +"1996-04-06","Holy Saturday","HN",1996 +"1996-04-14","Panamerican Day","HN",1996 +"1996-05-01","Labor Day","HN",1996 +"1996-09-15","Dia de la Independencia","HN",1996 +"1996-10-03","Morazan's Day","HN",1996 +"1996-10-12","Columbus Day","HN",1996 +"1996-10-21","Army Day","HN",1996 +"1996-12-25","Christmas","HN",1996 +"1997-01-01","New Year's Day","HN",1997 +"1997-03-27","Maundy Thursday","HN",1997 +"1997-03-28","Good Friday","HN",1997 +"1997-03-29","Holy Saturday","HN",1997 +"1997-04-14","Panamerican Day","HN",1997 +"1997-05-01","Labor Day","HN",1997 +"1997-09-15","Dia de la Independencia","HN",1997 +"1997-10-03","Morazan's Day","HN",1997 +"1997-10-12","Columbus Day","HN",1997 +"1997-10-21","Army Day","HN",1997 +"1997-12-25","Christmas","HN",1997 +"1998-01-01","New Year's Day","HN",1998 +"1998-04-09","Maundy Thursday","HN",1998 +"1998-04-10","Good Friday","HN",1998 +"1998-04-11","Holy Saturday","HN",1998 +"1998-04-14","Panamerican Day","HN",1998 +"1998-05-01","Labor Day","HN",1998 +"1998-09-15","Dia de la Independencia","HN",1998 +"1998-10-03","Morazan's Day","HN",1998 +"1998-10-12","Columbus Day","HN",1998 +"1998-10-21","Army Day","HN",1998 +"1998-12-25","Christmas","HN",1998 +"1999-01-01","New Year's Day","HN",1999 +"1999-04-01","Maundy Thursday","HN",1999 +"1999-04-02","Good Friday","HN",1999 +"1999-04-03","Holy Saturday","HN",1999 +"1999-04-14","Panamerican Day","HN",1999 +"1999-05-01","Labor Day","HN",1999 +"1999-09-15","Dia de la Independencia","HN",1999 +"1999-10-03","Morazan's Day","HN",1999 +"1999-10-12","Columbus Day","HN",1999 +"1999-10-21","Army Day","HN",1999 +"1999-12-25","Christmas","HN",1999 +"2000-01-01","New Year's Day","HN",2000 +"2000-04-14","Panamerican Day","HN",2000 +"2000-04-20","Maundy Thursday","HN",2000 +"2000-04-21","Good Friday","HN",2000 +"2000-04-22","Holy Saturday","HN",2000 +"2000-05-01","Labor Day","HN",2000 +"2000-09-15","Dia de la Independencia","HN",2000 +"2000-10-03","Morazan's Day","HN",2000 +"2000-10-12","Columbus Day","HN",2000 +"2000-10-21","Army Day","HN",2000 +"2000-12-25","Christmas","HN",2000 +"2001-01-01","New Year's Day","HN",2001 +"2001-04-12","Maundy Thursday","HN",2001 +"2001-04-13","Good Friday","HN",2001 +"2001-04-14","Holy Saturday","HN",2001 +"2001-04-14","Panamerican Day","HN",2001 +"2001-05-01","Labor Day","HN",2001 +"2001-09-15","Dia de la Independencia","HN",2001 +"2001-10-03","Morazan's Day","HN",2001 +"2001-10-12","Columbus Day","HN",2001 +"2001-10-21","Army Day","HN",2001 +"2001-12-25","Christmas","HN",2001 +"2002-01-01","New Year's Day","HN",2002 +"2002-03-28","Maundy Thursday","HN",2002 +"2002-03-29","Good Friday","HN",2002 +"2002-03-30","Holy Saturday","HN",2002 +"2002-04-14","Panamerican Day","HN",2002 +"2002-05-01","Labor Day","HN",2002 +"2002-09-15","Dia de la Independencia","HN",2002 +"2002-10-03","Morazan's Day","HN",2002 +"2002-10-12","Columbus Day","HN",2002 +"2002-10-21","Army Day","HN",2002 +"2002-12-25","Christmas","HN",2002 +"2003-01-01","New Year's Day","HN",2003 +"2003-04-14","Panamerican Day","HN",2003 +"2003-04-17","Maundy Thursday","HN",2003 +"2003-04-18","Good Friday","HN",2003 +"2003-04-19","Holy Saturday","HN",2003 +"2003-05-01","Labor Day","HN",2003 +"2003-09-15","Dia de la Independencia","HN",2003 +"2003-10-03","Morazan's Day","HN",2003 +"2003-10-12","Columbus Day","HN",2003 +"2003-10-21","Army Day","HN",2003 +"2003-12-25","Christmas","HN",2003 +"2004-01-01","New Year's Day","HN",2004 +"2004-04-08","Maundy Thursday","HN",2004 +"2004-04-09","Good Friday","HN",2004 +"2004-04-10","Holy Saturday","HN",2004 +"2004-04-14","Panamerican Day","HN",2004 +"2004-05-01","Labor Day","HN",2004 +"2004-09-15","Dia de la Independencia","HN",2004 +"2004-10-03","Morazan's Day","HN",2004 +"2004-10-12","Columbus Day","HN",2004 +"2004-10-21","Army Day","HN",2004 +"2004-12-25","Christmas","HN",2004 +"2005-01-01","New Year's Day","HN",2005 +"2005-03-24","Maundy Thursday","HN",2005 +"2005-03-25","Good Friday","HN",2005 +"2005-03-26","Holy Saturday","HN",2005 +"2005-04-14","Panamerican Day","HN",2005 +"2005-05-01","Labor Day","HN",2005 +"2005-09-15","Dia de la Independencia","HN",2005 +"2005-10-03","Morazan's Day","HN",2005 +"2005-10-12","Columbus Day","HN",2005 +"2005-10-21","Army Day","HN",2005 +"2005-12-25","Christmas","HN",2005 +"2006-01-01","New Year's Day","HN",2006 +"2006-04-13","Maundy Thursday","HN",2006 +"2006-04-14","Good Friday","HN",2006 +"2006-04-14","Panamerican Day","HN",2006 +"2006-04-15","Holy Saturday","HN",2006 +"2006-05-01","Labor Day","HN",2006 +"2006-09-15","Dia de la Independencia","HN",2006 +"2006-10-03","Morazan's Day","HN",2006 +"2006-10-12","Columbus Day","HN",2006 +"2006-10-21","Army Day","HN",2006 +"2006-12-25","Christmas","HN",2006 +"2007-01-01","New Year's Day","HN",2007 +"2007-04-05","Maundy Thursday","HN",2007 +"2007-04-06","Good Friday","HN",2007 +"2007-04-07","Holy Saturday","HN",2007 +"2007-04-14","Panamerican Day","HN",2007 +"2007-05-01","Labor Day","HN",2007 +"2007-09-15","Dia de la Independencia","HN",2007 +"2007-10-03","Morazan's Day","HN",2007 +"2007-10-12","Columbus Day","HN",2007 +"2007-10-21","Army Day","HN",2007 +"2007-12-25","Christmas","HN",2007 +"2008-01-01","New Year's Day","HN",2008 +"2008-03-20","Maundy Thursday","HN",2008 +"2008-03-21","Good Friday","HN",2008 +"2008-03-22","Holy Saturday","HN",2008 +"2008-04-14","Panamerican Day","HN",2008 +"2008-05-01","Labor Day","HN",2008 +"2008-09-15","Dia de la Independencia","HN",2008 +"2008-10-03","Morazan's Day","HN",2008 +"2008-10-12","Columbus Day","HN",2008 +"2008-10-21","Army Day","HN",2008 +"2008-12-25","Christmas","HN",2008 +"2009-01-01","New Year's Day","HN",2009 +"2009-04-09","Maundy Thursday","HN",2009 +"2009-04-10","Good Friday","HN",2009 +"2009-04-11","Holy Saturday","HN",2009 +"2009-04-14","Panamerican Day","HN",2009 +"2009-05-01","Labor Day","HN",2009 +"2009-09-15","Dia de la Independencia","HN",2009 +"2009-10-03","Morazan's Day","HN",2009 +"2009-10-12","Columbus Day","HN",2009 +"2009-10-21","Army Day","HN",2009 +"2009-12-25","Christmas","HN",2009 +"2010-01-01","New Year's Day","HN",2010 +"2010-04-01","Maundy Thursday","HN",2010 +"2010-04-02","Good Friday","HN",2010 +"2010-04-03","Holy Saturday","HN",2010 +"2010-04-14","Panamerican Day","HN",2010 +"2010-05-01","Labor Day","HN",2010 +"2010-09-15","Dia de la Independencia","HN",2010 +"2010-10-03","Morazan's Day","HN",2010 +"2010-10-12","Columbus Day","HN",2010 +"2010-10-21","Army Day","HN",2010 +"2010-12-25","Christmas","HN",2010 +"2011-01-01","New Year's Day","HN",2011 +"2011-04-14","Panamerican Day","HN",2011 +"2011-04-21","Maundy Thursday","HN",2011 +"2011-04-22","Good Friday","HN",2011 +"2011-04-23","Holy Saturday","HN",2011 +"2011-05-01","Labor Day","HN",2011 +"2011-09-15","Dia de la Independencia","HN",2011 +"2011-10-03","Morazan's Day","HN",2011 +"2011-10-12","Columbus Day","HN",2011 +"2011-10-21","Army Day","HN",2011 +"2011-12-25","Christmas","HN",2011 +"2012-01-01","New Year's Day","HN",2012 +"2012-04-05","Maundy Thursday","HN",2012 +"2012-04-06","Good Friday","HN",2012 +"2012-04-07","Holy Saturday","HN",2012 +"2012-04-14","Panamerican Day","HN",2012 +"2012-05-01","Labor Day","HN",2012 +"2012-09-15","Dia de la Independencia","HN",2012 +"2012-10-03","Morazan's Day","HN",2012 +"2012-10-12","Columbus Day","HN",2012 +"2012-10-21","Army Day","HN",2012 +"2012-12-25","Christmas","HN",2012 +"2013-01-01","New Year's Day","HN",2013 +"2013-03-28","Maundy Thursday","HN",2013 +"2013-03-29","Good Friday","HN",2013 +"2013-03-30","Holy Saturday","HN",2013 +"2013-04-14","Panamerican Day","HN",2013 +"2013-05-01","Labor Day","HN",2013 +"2013-09-15","Dia de la Independencia","HN",2013 +"2013-10-03","Morazan's Day","HN",2013 +"2013-10-12","Columbus Day","HN",2013 +"2013-10-21","Army Day","HN",2013 +"2013-12-25","Christmas","HN",2013 +"2014-01-01","New Year's Day","HN",2014 +"2014-04-14","Panamerican Day","HN",2014 +"2014-04-17","Maundy Thursday","HN",2014 +"2014-04-18","Good Friday","HN",2014 +"2014-04-19","Holy Saturday","HN",2014 +"2014-05-01","Labor Day","HN",2014 +"2014-09-15","Dia de la Independencia","HN",2014 +"2014-10-03","Morazan's Day","HN",2014 +"2014-10-12","Columbus Day","HN",2014 +"2014-10-21","Army Day","HN",2014 +"2014-12-25","Christmas","HN",2014 +"2015-01-01","New Year's Day","HN",2015 +"2015-04-02","Maundy Thursday","HN",2015 +"2015-04-03","Good Friday","HN",2015 +"2015-04-04","Holy Saturday","HN",2015 +"2015-04-14","Panamerican Day","HN",2015 +"2015-05-01","Labor Day","HN",2015 +"2015-09-15","Dia de la Independencia","HN",2015 +"2015-10-07","Morazan Weekend","HN",2015 +"2015-10-08","Morazan Weekend","HN",2015 +"2015-10-09","Morazan Weekend","HN",2015 +"2015-12-25","Christmas","HN",2015 +"2016-01-01","New Year's Day","HN",2016 +"2016-03-24","Maundy Thursday","HN",2016 +"2016-03-25","Good Friday","HN",2016 +"2016-03-26","Holy Saturday","HN",2016 +"2016-04-14","Panamerican Day","HN",2016 +"2016-05-01","Labor Day","HN",2016 +"2016-09-15","Dia de la Independencia","HN",2016 +"2016-10-05","Morazan Weekend","HN",2016 +"2016-10-06","Morazan Weekend","HN",2016 +"2016-10-07","Morazan Weekend","HN",2016 +"2016-12-25","Christmas","HN",2016 +"2017-01-01","New Year's Day","HN",2017 +"2017-04-13","Maundy Thursday","HN",2017 +"2017-04-14","Good Friday","HN",2017 +"2017-04-14","Panamerican Day","HN",2017 +"2017-04-15","Holy Saturday","HN",2017 +"2017-05-01","Labor Day","HN",2017 +"2017-09-15","Dia de la Independencia","HN",2017 +"2017-10-04","Morazan Weekend","HN",2017 +"2017-10-05","Morazan Weekend","HN",2017 +"2017-10-06","Morazan Weekend","HN",2017 +"2017-12-25","Christmas","HN",2017 +"2018-01-01","New Year's Day","HN",2018 +"2018-03-29","Maundy Thursday","HN",2018 +"2018-03-30","Good Friday","HN",2018 +"2018-03-31","Holy Saturday","HN",2018 +"2018-04-14","Panamerican Day","HN",2018 +"2018-05-01","Labor Day","HN",2018 +"2018-09-15","Dia de la Independencia","HN",2018 +"2018-10-03","Morazan Weekend","HN",2018 +"2018-10-04","Morazan Weekend","HN",2018 +"2018-10-05","Morazan Weekend","HN",2018 +"2018-12-25","Christmas","HN",2018 +"2019-01-01","New Year's Day","HN",2019 +"2019-04-14","Panamerican Day","HN",2019 +"2019-04-18","Maundy Thursday","HN",2019 +"2019-04-19","Good Friday","HN",2019 +"2019-04-20","Holy Saturday","HN",2019 +"2019-05-01","Labor Day","HN",2019 +"2019-09-15","Dia de la Independencia","HN",2019 +"2019-10-02","Morazan Weekend","HN",2019 +"2019-10-03","Morazan Weekend","HN",2019 +"2019-10-04","Morazan Weekend","HN",2019 +"2019-12-25","Christmas","HN",2019 +"2020-01-01","New Year's Day","HN",2020 +"2020-04-09","Maundy Thursday","HN",2020 +"2020-04-10","Good Friday","HN",2020 +"2020-04-11","Holy Saturday","HN",2020 +"2020-04-14","Panamerican Day","HN",2020 +"2020-05-01","Labor Day","HN",2020 +"2020-09-15","Dia de la Independencia","HN",2020 +"2020-10-07","Morazan Weekend","HN",2020 +"2020-10-08","Morazan Weekend","HN",2020 +"2020-10-09","Morazan Weekend","HN",2020 +"2020-12-25","Christmas","HN",2020 +"2021-01-01","New Year's Day","HN",2021 +"2021-04-01","Maundy Thursday","HN",2021 +"2021-04-02","Good Friday","HN",2021 +"2021-04-03","Holy Saturday","HN",2021 +"2021-04-14","Panamerican Day","HN",2021 +"2021-05-01","Labor Day","HN",2021 +"2021-09-15","Dia de la Independencia","HN",2021 +"2021-10-06","Morazan Weekend","HN",2021 +"2021-10-07","Morazan Weekend","HN",2021 +"2021-10-08","Morazan Weekend","HN",2021 +"2021-12-25","Christmas","HN",2021 +"2022-01-01","New Year's Day","HN",2022 +"2022-04-14","Maundy Thursday","HN",2022 +"2022-04-14","Panamerican Day","HN",2022 +"2022-04-15","Good Friday","HN",2022 +"2022-04-16","Holy Saturday","HN",2022 +"2022-05-01","Labor Day","HN",2022 +"2022-09-15","Dia de la Independencia","HN",2022 +"2022-10-05","Morazan Weekend","HN",2022 +"2022-10-06","Morazan Weekend","HN",2022 +"2022-10-07","Morazan Weekend","HN",2022 +"2022-12-25","Christmas","HN",2022 +"2023-01-01","New Year's Day","HN",2023 +"2023-04-06","Maundy Thursday","HN",2023 +"2023-04-07","Good Friday","HN",2023 +"2023-04-08","Holy Saturday","HN",2023 +"2023-04-14","Panamerican Day","HN",2023 +"2023-05-01","Labor Day","HN",2023 +"2023-09-15","Dia de la Independencia","HN",2023 +"2023-10-04","Morazan Weekend","HN",2023 +"2023-10-05","Morazan Weekend","HN",2023 +"2023-10-06","Morazan Weekend","HN",2023 +"2023-12-25","Christmas","HN",2023 +"2024-01-01","New Year's Day","HN",2024 +"2024-03-28","Maundy Thursday","HN",2024 +"2024-03-29","Good Friday","HN",2024 +"2024-03-30","Holy Saturday","HN",2024 +"2024-04-14","Panamerican Day","HN",2024 +"2024-05-01","Labor Day","HN",2024 +"2024-09-15","Dia de la Independencia","HN",2024 +"2024-10-02","Morazan Weekend","HN",2024 +"2024-10-03","Morazan Weekend","HN",2024 +"2024-10-04","Morazan Weekend","HN",2024 +"2024-12-25","Christmas","HN",2024 +"2025-01-01","New Year's Day","HN",2025 +"2025-04-14","Panamerican Day","HN",2025 +"2025-04-17","Maundy Thursday","HN",2025 +"2025-04-18","Good Friday","HN",2025 +"2025-04-19","Holy Saturday","HN",2025 +"2025-05-01","Labor Day","HN",2025 +"2025-09-15","Dia de la Independencia","HN",2025 +"2025-10-01","Morazan Weekend","HN",2025 +"2025-10-02","Morazan Weekend","HN",2025 +"2025-10-03","Morazan Weekend","HN",2025 +"2025-12-25","Christmas","HN",2025 +"2026-01-01","New Year's Day","HN",2026 +"2026-04-02","Maundy Thursday","HN",2026 +"2026-04-03","Good Friday","HN",2026 +"2026-04-04","Holy Saturday","HN",2026 +"2026-04-14","Panamerican Day","HN",2026 +"2026-05-01","Labor Day","HN",2026 +"2026-09-15","Dia de la Independencia","HN",2026 +"2026-10-07","Morazan Weekend","HN",2026 +"2026-10-08","Morazan Weekend","HN",2026 +"2026-10-09","Morazan Weekend","HN",2026 +"2026-12-25","Christmas","HN",2026 +"2027-01-01","New Year's Day","HN",2027 +"2027-03-25","Maundy Thursday","HN",2027 +"2027-03-26","Good Friday","HN",2027 +"2027-03-27","Holy Saturday","HN",2027 +"2027-04-14","Panamerican Day","HN",2027 +"2027-05-01","Labor Day","HN",2027 +"2027-09-15","Dia de la Independencia","HN",2027 +"2027-10-06","Morazan Weekend","HN",2027 +"2027-10-07","Morazan Weekend","HN",2027 +"2027-10-08","Morazan Weekend","HN",2027 +"2027-12-25","Christmas","HN",2027 +"2028-01-01","New Year's Day","HN",2028 +"2028-04-13","Maundy Thursday","HN",2028 +"2028-04-14","Good Friday","HN",2028 +"2028-04-14","Panamerican Day","HN",2028 +"2028-04-15","Holy Saturday","HN",2028 +"2028-05-01","Labor Day","HN",2028 +"2028-09-15","Dia de la Independencia","HN",2028 +"2028-10-04","Morazan Weekend","HN",2028 +"2028-10-05","Morazan Weekend","HN",2028 +"2028-10-06","Morazan Weekend","HN",2028 +"2028-12-25","Christmas","HN",2028 +"2029-01-01","New Year's Day","HN",2029 +"2029-03-29","Maundy Thursday","HN",2029 +"2029-03-30","Good Friday","HN",2029 +"2029-03-31","Holy Saturday","HN",2029 +"2029-04-14","Panamerican Day","HN",2029 +"2029-05-01","Labor Day","HN",2029 +"2029-09-15","Dia de la Independencia","HN",2029 +"2029-10-03","Morazan Weekend","HN",2029 +"2029-10-04","Morazan Weekend","HN",2029 +"2029-10-05","Morazan Weekend","HN",2029 +"2029-12-25","Christmas","HN",2029 +"2030-01-01","New Year's Day","HN",2030 +"2030-04-14","Panamerican Day","HN",2030 +"2030-04-18","Maundy Thursday","HN",2030 +"2030-04-19","Good Friday","HN",2030 +"2030-04-20","Holy Saturday","HN",2030 +"2030-05-01","Labor Day","HN",2030 +"2030-09-15","Dia de la Independencia","HN",2030 +"2030-10-02","Morazan Weekend","HN",2030 +"2030-10-03","Morazan Weekend","HN",2030 +"2030-10-04","Morazan Weekend","HN",2030 +"2030-12-25","Christmas","HN",2030 +"2031-01-01","New Year's Day","HN",2031 +"2031-04-10","Maundy Thursday","HN",2031 +"2031-04-11","Good Friday","HN",2031 +"2031-04-12","Holy Saturday","HN",2031 +"2031-04-14","Panamerican Day","HN",2031 +"2031-05-01","Labor Day","HN",2031 +"2031-09-15","Dia de la Independencia","HN",2031 +"2031-10-01","Morazan Weekend","HN",2031 +"2031-10-02","Morazan Weekend","HN",2031 +"2031-10-03","Morazan Weekend","HN",2031 +"2031-12-25","Christmas","HN",2031 +"2032-01-01","New Year's Day","HN",2032 +"2032-03-25","Maundy Thursday","HN",2032 +"2032-03-26","Good Friday","HN",2032 +"2032-03-27","Holy Saturday","HN",2032 +"2032-04-14","Panamerican Day","HN",2032 +"2032-05-01","Labor Day","HN",2032 +"2032-09-15","Dia de la Independencia","HN",2032 +"2032-10-06","Morazan Weekend","HN",2032 +"2032-10-07","Morazan Weekend","HN",2032 +"2032-10-08","Morazan Weekend","HN",2032 +"2032-12-25","Christmas","HN",2032 +"2033-01-01","New Year's Day","HN",2033 +"2033-04-14","Maundy Thursday","HN",2033 +"2033-04-14","Panamerican Day","HN",2033 +"2033-04-15","Good Friday","HN",2033 +"2033-04-16","Holy Saturday","HN",2033 +"2033-05-01","Labor Day","HN",2033 +"2033-09-15","Dia de la Independencia","HN",2033 +"2033-10-05","Morazan Weekend","HN",2033 +"2033-10-06","Morazan Weekend","HN",2033 +"2033-10-07","Morazan Weekend","HN",2033 +"2033-12-25","Christmas","HN",2033 +"2034-01-01","New Year's Day","HN",2034 +"2034-04-06","Maundy Thursday","HN",2034 +"2034-04-07","Good Friday","HN",2034 +"2034-04-08","Holy Saturday","HN",2034 +"2034-04-14","Panamerican Day","HN",2034 +"2034-05-01","Labor Day","HN",2034 +"2034-09-15","Dia de la Independencia","HN",2034 +"2034-10-04","Morazan Weekend","HN",2034 +"2034-10-05","Morazan Weekend","HN",2034 +"2034-10-06","Morazan Weekend","HN",2034 +"2034-12-25","Christmas","HN",2034 +"2035-01-01","New Year's Day","HN",2035 +"2035-03-22","Maundy Thursday","HN",2035 +"2035-03-23","Good Friday","HN",2035 +"2035-03-24","Holy Saturday","HN",2035 +"2035-04-14","Panamerican Day","HN",2035 +"2035-05-01","Labor Day","HN",2035 +"2035-09-15","Dia de la Independencia","HN",2035 +"2035-10-03","Morazan Weekend","HN",2035 +"2035-10-04","Morazan Weekend","HN",2035 +"2035-10-05","Morazan Weekend","HN",2035 +"2035-12-25","Christmas","HN",2035 +"2036-01-01","New Year's Day","HN",2036 +"2036-04-10","Maundy Thursday","HN",2036 +"2036-04-11","Good Friday","HN",2036 +"2036-04-12","Holy Saturday","HN",2036 +"2036-04-14","Panamerican Day","HN",2036 +"2036-05-01","Labor Day","HN",2036 +"2036-09-15","Dia de la Independencia","HN",2036 +"2036-10-01","Morazan Weekend","HN",2036 +"2036-10-02","Morazan Weekend","HN",2036 +"2036-10-03","Morazan Weekend","HN",2036 +"2036-12-25","Christmas","HN",2036 +"2037-01-01","New Year's Day","HN",2037 +"2037-04-02","Maundy Thursday","HN",2037 +"2037-04-03","Good Friday","HN",2037 +"2037-04-04","Holy Saturday","HN",2037 +"2037-04-14","Panamerican Day","HN",2037 +"2037-05-01","Labor Day","HN",2037 +"2037-09-15","Dia de la Independencia","HN",2037 +"2037-10-07","Morazan Weekend","HN",2037 +"2037-10-08","Morazan Weekend","HN",2037 +"2037-10-09","Morazan Weekend","HN",2037 +"2037-12-25","Christmas","HN",2037 +"2038-01-01","New Year's Day","HN",2038 +"2038-04-14","Panamerican Day","HN",2038 +"2038-04-22","Maundy Thursday","HN",2038 +"2038-04-23","Good Friday","HN",2038 +"2038-04-24","Holy Saturday","HN",2038 +"2038-05-01","Labor Day","HN",2038 +"2038-09-15","Dia de la Independencia","HN",2038 +"2038-10-06","Morazan Weekend","HN",2038 +"2038-10-07","Morazan Weekend","HN",2038 +"2038-10-08","Morazan Weekend","HN",2038 +"2038-12-25","Christmas","HN",2038 +"2039-01-01","New Year's Day","HN",2039 +"2039-04-07","Maundy Thursday","HN",2039 +"2039-04-08","Good Friday","HN",2039 +"2039-04-09","Holy Saturday","HN",2039 +"2039-04-14","Panamerican Day","HN",2039 +"2039-05-01","Labor Day","HN",2039 +"2039-09-15","Dia de la Independencia","HN",2039 +"2039-10-05","Morazan Weekend","HN",2039 +"2039-10-06","Morazan Weekend","HN",2039 +"2039-10-07","Morazan Weekend","HN",2039 +"2039-12-25","Christmas","HN",2039 +"2040-01-01","New Year's Day","HN",2040 +"2040-03-29","Maundy Thursday","HN",2040 +"2040-03-30","Good Friday","HN",2040 +"2040-03-31","Holy Saturday","HN",2040 +"2040-04-14","Panamerican Day","HN",2040 +"2040-05-01","Labor Day","HN",2040 +"2040-09-15","Dia de la Independencia","HN",2040 +"2040-10-03","Morazan Weekend","HN",2040 +"2040-10-04","Morazan Weekend","HN",2040 +"2040-10-05","Morazan Weekend","HN",2040 +"2040-12-25","Christmas","HN",2040 +"2041-01-01","New Year's Day","HN",2041 +"2041-04-14","Panamerican Day","HN",2041 +"2041-04-18","Maundy Thursday","HN",2041 +"2041-04-19","Good Friday","HN",2041 +"2041-04-20","Holy Saturday","HN",2041 +"2041-05-01","Labor Day","HN",2041 +"2041-09-15","Dia de la Independencia","HN",2041 +"2041-10-02","Morazan Weekend","HN",2041 +"2041-10-03","Morazan Weekend","HN",2041 +"2041-10-04","Morazan Weekend","HN",2041 +"2041-12-25","Christmas","HN",2041 +"2042-01-01","New Year's Day","HN",2042 +"2042-04-03","Maundy Thursday","HN",2042 +"2042-04-04","Good Friday","HN",2042 +"2042-04-05","Holy Saturday","HN",2042 +"2042-04-14","Panamerican Day","HN",2042 +"2042-05-01","Labor Day","HN",2042 +"2042-09-15","Dia de la Independencia","HN",2042 +"2042-10-01","Morazan Weekend","HN",2042 +"2042-10-02","Morazan Weekend","HN",2042 +"2042-10-03","Morazan Weekend","HN",2042 +"2042-12-25","Christmas","HN",2042 +"2043-01-01","New Year's Day","HN",2043 +"2043-03-26","Maundy Thursday","HN",2043 +"2043-03-27","Good Friday","HN",2043 +"2043-03-28","Holy Saturday","HN",2043 +"2043-04-14","Panamerican Day","HN",2043 +"2043-05-01","Labor Day","HN",2043 +"2043-09-15","Dia de la Independencia","HN",2043 +"2043-10-07","Morazan Weekend","HN",2043 +"2043-10-08","Morazan Weekend","HN",2043 +"2043-10-09","Morazan Weekend","HN",2043 +"2043-12-25","Christmas","HN",2043 +"2044-01-01","New Year's Day","HN",2044 +"2044-04-14","Maundy Thursday","HN",2044 +"2044-04-14","Panamerican Day","HN",2044 +"2044-04-15","Good Friday","HN",2044 +"2044-04-16","Holy Saturday","HN",2044 +"2044-05-01","Labor Day","HN",2044 +"2044-09-15","Dia de la Independencia","HN",2044 +"2044-10-05","Morazan Weekend","HN",2044 +"2044-10-06","Morazan Weekend","HN",2044 +"2044-10-07","Morazan Weekend","HN",2044 +"2044-12-25","Christmas","HN",2044 +"1995-01-01","Nova Godina","HR",1995 +"1995-01-06","Sveta tri kralja","HR",1995 +"1995-04-16","Uskrs","HR",1995 +"1995-04-17","Uskrsni ponedjeljak","HR",1995 +"1995-05-01","Meunarodni praznik rada","HR",1995 +"1995-06-15","Tijelovo","HR",1995 +"1995-06-22","Dan antifasisticke borbe","HR",1995 +"1995-06-25","Dan drzavnosti","HR",1995 +"1995-08-05","Dan pobjede i domovinske zahvalnosti","HR",1995 +"1995-08-15","Velika Gospa","HR",1995 +"1995-10-08","Dan neovisnosti","HR",1995 +"1995-11-01","Svi sveti","HR",1995 +"1995-12-25","Bozic","HR",1995 +"1995-12-26","Sveti Stjepan","HR",1995 +"1996-01-01","Nova Godina","HR",1996 +"1996-01-06","Sveta tri kralja","HR",1996 +"1996-04-07","Uskrs","HR",1996 +"1996-04-08","Uskrsni ponedjeljak","HR",1996 +"1996-05-01","Meunarodni praznik rada","HR",1996 +"1996-06-06","Tijelovo","HR",1996 +"1996-06-22","Dan antifasisticke borbe","HR",1996 +"1996-06-25","Dan drzavnosti","HR",1996 +"1996-08-05","Dan pobjede i domovinske zahvalnosti","HR",1996 +"1996-08-15","Velika Gospa","HR",1996 +"1996-10-08","Dan neovisnosti","HR",1996 +"1996-11-01","Svi sveti","HR",1996 +"1996-12-25","Bozic","HR",1996 +"1996-12-26","Sveti Stjepan","HR",1996 +"1997-01-01","Nova Godina","HR",1997 +"1997-01-06","Sveta tri kralja","HR",1997 +"1997-03-30","Uskrs","HR",1997 +"1997-03-31","Uskrsni ponedjeljak","HR",1997 +"1997-05-01","Meunarodni praznik rada","HR",1997 +"1997-05-29","Tijelovo","HR",1997 +"1997-06-22","Dan antifasisticke borbe","HR",1997 +"1997-06-25","Dan drzavnosti","HR",1997 +"1997-08-05","Dan pobjede i domovinske zahvalnosti","HR",1997 +"1997-08-15","Velika Gospa","HR",1997 +"1997-10-08","Dan neovisnosti","HR",1997 +"1997-11-01","Svi sveti","HR",1997 +"1997-12-25","Bozic","HR",1997 +"1997-12-26","Sveti Stjepan","HR",1997 +"1998-01-01","Nova Godina","HR",1998 +"1998-01-06","Sveta tri kralja","HR",1998 +"1998-04-12","Uskrs","HR",1998 +"1998-04-13","Uskrsni ponedjeljak","HR",1998 +"1998-05-01","Meunarodni praznik rada","HR",1998 +"1998-06-11","Tijelovo","HR",1998 +"1998-06-22","Dan antifasisticke borbe","HR",1998 +"1998-06-25","Dan drzavnosti","HR",1998 +"1998-08-05","Dan pobjede i domovinske zahvalnosti","HR",1998 +"1998-08-15","Velika Gospa","HR",1998 +"1998-10-08","Dan neovisnosti","HR",1998 +"1998-11-01","Svi sveti","HR",1998 +"1998-12-25","Bozic","HR",1998 +"1998-12-26","Sveti Stjepan","HR",1998 +"1999-01-01","Nova Godina","HR",1999 +"1999-01-06","Sveta tri kralja","HR",1999 +"1999-04-04","Uskrs","HR",1999 +"1999-04-05","Uskrsni ponedjeljak","HR",1999 +"1999-05-01","Meunarodni praznik rada","HR",1999 +"1999-06-03","Tijelovo","HR",1999 +"1999-06-22","Dan antifasisticke borbe","HR",1999 +"1999-06-25","Dan drzavnosti","HR",1999 +"1999-08-05","Dan pobjede i domovinske zahvalnosti","HR",1999 +"1999-08-15","Velika Gospa","HR",1999 +"1999-10-08","Dan neovisnosti","HR",1999 +"1999-11-01","Svi sveti","HR",1999 +"1999-12-25","Bozic","HR",1999 +"1999-12-26","Sveti Stjepan","HR",1999 +"2000-01-01","Nova Godina","HR",2000 +"2000-01-06","Sveta tri kralja","HR",2000 +"2000-04-23","Uskrs","HR",2000 +"2000-04-24","Uskrsni ponedjeljak","HR",2000 +"2000-05-01","Meunarodni praznik rada","HR",2000 +"2000-06-22","Dan antifasisticke borbe","HR",2000 +"2000-06-22","Tijelovo","HR",2000 +"2000-06-25","Dan drzavnosti","HR",2000 +"2000-08-05","Dan pobjede i domovinske zahvalnosti","HR",2000 +"2000-08-15","Velika Gospa","HR",2000 +"2000-10-08","Dan neovisnosti","HR",2000 +"2000-11-01","Svi sveti","HR",2000 +"2000-12-25","Bozic","HR",2000 +"2000-12-26","Sveti Stjepan","HR",2000 +"2001-01-01","Nova Godina","HR",2001 +"2001-01-06","Sveta tri kralja","HR",2001 +"2001-04-15","Uskrs","HR",2001 +"2001-04-16","Uskrsni ponedjeljak","HR",2001 +"2001-05-01","Meunarodni praznik rada","HR",2001 +"2001-06-14","Tijelovo","HR",2001 +"2001-06-22","Dan antifasisticke borbe","HR",2001 +"2001-06-25","Dan drzavnosti","HR",2001 +"2001-08-05","Dan pobjede i domovinske zahvalnosti","HR",2001 +"2001-08-15","Velika Gospa","HR",2001 +"2001-10-08","Dan neovisnosti","HR",2001 +"2001-11-01","Svi sveti","HR",2001 +"2001-12-25","Bozic","HR",2001 +"2001-12-26","Sveti Stjepan","HR",2001 +"2002-01-01","Nova Godina","HR",2002 +"2002-01-06","Sveta tri kralja","HR",2002 +"2002-03-31","Uskrs","HR",2002 +"2002-04-01","Uskrsni ponedjeljak","HR",2002 +"2002-05-01","Meunarodni praznik rada","HR",2002 +"2002-05-30","Tijelovo","HR",2002 +"2002-06-22","Dan antifasisticke borbe","HR",2002 +"2002-06-25","Dan drzavnosti","HR",2002 +"2002-08-05","Dan pobjede i domovinske zahvalnosti","HR",2002 +"2002-08-15","Velika Gospa","HR",2002 +"2002-10-08","Dan neovisnosti","HR",2002 +"2002-11-01","Svi sveti","HR",2002 +"2002-12-25","Bozic","HR",2002 +"2002-12-26","Sveti Stjepan","HR",2002 +"2003-01-01","Nova Godina","HR",2003 +"2003-01-06","Sveta tri kralja","HR",2003 +"2003-04-20","Uskrs","HR",2003 +"2003-04-21","Uskrsni ponedjeljak","HR",2003 +"2003-05-01","Meunarodni praznik rada","HR",2003 +"2003-06-19","Tijelovo","HR",2003 +"2003-06-22","Dan antifasisticke borbe","HR",2003 +"2003-06-25","Dan drzavnosti","HR",2003 +"2003-08-05","Dan pobjede i domovinske zahvalnosti","HR",2003 +"2003-08-15","Velika Gospa","HR",2003 +"2003-10-08","Dan neovisnosti","HR",2003 +"2003-11-01","Svi sveti","HR",2003 +"2003-12-25","Bozic","HR",2003 +"2003-12-26","Sveti Stjepan","HR",2003 +"2004-01-01","Nova Godina","HR",2004 +"2004-01-06","Sveta tri kralja","HR",2004 +"2004-04-11","Uskrs","HR",2004 +"2004-04-12","Uskrsni ponedjeljak","HR",2004 +"2004-05-01","Meunarodni praznik rada","HR",2004 +"2004-06-10","Tijelovo","HR",2004 +"2004-06-22","Dan antifasisticke borbe","HR",2004 +"2004-06-25","Dan drzavnosti","HR",2004 +"2004-08-05","Dan pobjede i domovinske zahvalnosti","HR",2004 +"2004-08-15","Velika Gospa","HR",2004 +"2004-10-08","Dan neovisnosti","HR",2004 +"2004-11-01","Svi sveti","HR",2004 +"2004-12-25","Bozic","HR",2004 +"2004-12-26","Sveti Stjepan","HR",2004 +"2005-01-01","Nova Godina","HR",2005 +"2005-01-06","Sveta tri kralja","HR",2005 +"2005-03-27","Uskrs","HR",2005 +"2005-03-28","Uskrsni ponedjeljak","HR",2005 +"2005-05-01","Meunarodni praznik rada","HR",2005 +"2005-05-26","Tijelovo","HR",2005 +"2005-06-22","Dan antifasisticke borbe","HR",2005 +"2005-06-25","Dan drzavnosti","HR",2005 +"2005-08-05","Dan pobjede i domovinske zahvalnosti","HR",2005 +"2005-08-15","Velika Gospa","HR",2005 +"2005-10-08","Dan neovisnosti","HR",2005 +"2005-11-01","Svi sveti","HR",2005 +"2005-12-25","Bozic","HR",2005 +"2005-12-26","Sveti Stjepan","HR",2005 +"2006-01-01","Nova Godina","HR",2006 +"2006-01-06","Sveta tri kralja","HR",2006 +"2006-04-16","Uskrs","HR",2006 +"2006-04-17","Uskrsni ponedjeljak","HR",2006 +"2006-05-01","Meunarodni praznik rada","HR",2006 +"2006-06-15","Tijelovo","HR",2006 +"2006-06-22","Dan antifasisticke borbe","HR",2006 +"2006-06-25","Dan drzavnosti","HR",2006 +"2006-08-05","Dan pobjede i domovinske zahvalnosti","HR",2006 +"2006-08-15","Velika Gospa","HR",2006 +"2006-10-08","Dan neovisnosti","HR",2006 +"2006-11-01","Svi sveti","HR",2006 +"2006-12-25","Bozic","HR",2006 +"2006-12-26","Sveti Stjepan","HR",2006 +"2007-01-01","Nova Godina","HR",2007 +"2007-01-06","Sveta tri kralja","HR",2007 +"2007-04-08","Uskrs","HR",2007 +"2007-04-09","Uskrsni ponedjeljak","HR",2007 +"2007-05-01","Meunarodni praznik rada","HR",2007 +"2007-06-07","Tijelovo","HR",2007 +"2007-06-22","Dan antifasisticke borbe","HR",2007 +"2007-06-25","Dan drzavnosti","HR",2007 +"2007-08-05","Dan pobjede i domovinske zahvalnosti","HR",2007 +"2007-08-15","Velika Gospa","HR",2007 +"2007-10-08","Dan neovisnosti","HR",2007 +"2007-11-01","Svi sveti","HR",2007 +"2007-12-25","Bozic","HR",2007 +"2007-12-26","Sveti Stjepan","HR",2007 +"2008-01-01","Nova Godina","HR",2008 +"2008-01-06","Sveta tri kralja","HR",2008 +"2008-03-23","Uskrs","HR",2008 +"2008-03-24","Uskrsni ponedjeljak","HR",2008 +"2008-05-01","Meunarodni praznik rada","HR",2008 +"2008-05-22","Tijelovo","HR",2008 +"2008-06-22","Dan antifasisticke borbe","HR",2008 +"2008-06-25","Dan drzavnosti","HR",2008 +"2008-08-05","Dan pobjede i domovinske zahvalnosti","HR",2008 +"2008-08-15","Velika Gospa","HR",2008 +"2008-10-08","Dan neovisnosti","HR",2008 +"2008-11-01","Svi sveti","HR",2008 +"2008-12-25","Bozic","HR",2008 +"2008-12-26","Sveti Stjepan","HR",2008 +"2009-01-01","Nova Godina","HR",2009 +"2009-01-06","Sveta tri kralja","HR",2009 +"2009-04-12","Uskrs","HR",2009 +"2009-04-13","Uskrsni ponedjeljak","HR",2009 +"2009-05-01","Meunarodni praznik rada","HR",2009 +"2009-06-11","Tijelovo","HR",2009 +"2009-06-22","Dan antifasisticke borbe","HR",2009 +"2009-06-25","Dan drzavnosti","HR",2009 +"2009-08-05","Dan pobjede i domovinske zahvalnosti","HR",2009 +"2009-08-15","Velika Gospa","HR",2009 +"2009-10-08","Dan neovisnosti","HR",2009 +"2009-11-01","Svi sveti","HR",2009 +"2009-12-25","Bozic","HR",2009 +"2009-12-26","Sveti Stjepan","HR",2009 +"2010-01-01","Nova Godina","HR",2010 +"2010-01-06","Sveta tri kralja","HR",2010 +"2010-04-04","Uskrs","HR",2010 +"2010-04-05","Uskrsni ponedjeljak","HR",2010 +"2010-05-01","Meunarodni praznik rada","HR",2010 +"2010-06-03","Tijelovo","HR",2010 +"2010-06-22","Dan antifasisticke borbe","HR",2010 +"2010-06-25","Dan drzavnosti","HR",2010 +"2010-08-05","Dan pobjede i domovinske zahvalnosti","HR",2010 +"2010-08-15","Velika Gospa","HR",2010 +"2010-10-08","Dan neovisnosti","HR",2010 +"2010-11-01","Svi sveti","HR",2010 +"2010-12-25","Bozic","HR",2010 +"2010-12-26","Sveti Stjepan","HR",2010 +"2011-01-01","Nova Godina","HR",2011 +"2011-01-06","Sveta tri kralja","HR",2011 +"2011-04-24","Uskrs","HR",2011 +"2011-04-25","Uskrsni ponedjeljak","HR",2011 +"2011-05-01","Meunarodni praznik rada","HR",2011 +"2011-06-22","Dan antifasisticke borbe","HR",2011 +"2011-06-23","Tijelovo","HR",2011 +"2011-06-25","Dan drzavnosti","HR",2011 +"2011-08-05","Dan pobjede i domovinske zahvalnosti","HR",2011 +"2011-08-15","Velika Gospa","HR",2011 +"2011-10-08","Dan neovisnosti","HR",2011 +"2011-11-01","Svi sveti","HR",2011 +"2011-12-25","Bozic","HR",2011 +"2011-12-26","Sveti Stjepan","HR",2011 +"2012-01-01","Nova Godina","HR",2012 +"2012-01-06","Sveta tri kralja","HR",2012 +"2012-04-08","Uskrs","HR",2012 +"2012-04-09","Uskrsni ponedjeljak","HR",2012 +"2012-05-01","Meunarodni praznik rada","HR",2012 +"2012-06-07","Tijelovo","HR",2012 +"2012-06-22","Dan antifasisticke borbe","HR",2012 +"2012-06-25","Dan drzavnosti","HR",2012 +"2012-08-05","Dan pobjede i domovinske zahvalnosti","HR",2012 +"2012-08-15","Velika Gospa","HR",2012 +"2012-10-08","Dan neovisnosti","HR",2012 +"2012-11-01","Svi sveti","HR",2012 +"2012-12-25","Bozic","HR",2012 +"2012-12-26","Sveti Stjepan","HR",2012 +"2013-01-01","Nova Godina","HR",2013 +"2013-01-06","Sveta tri kralja","HR",2013 +"2013-03-31","Uskrs","HR",2013 +"2013-04-01","Uskrsni ponedjeljak","HR",2013 +"2013-05-01","Meunarodni praznik rada","HR",2013 +"2013-05-30","Tijelovo","HR",2013 +"2013-06-22","Dan antifasisticke borbe","HR",2013 +"2013-06-25","Dan drzavnosti","HR",2013 +"2013-08-05","Dan pobjede i domovinske zahvalnosti","HR",2013 +"2013-08-15","Velika Gospa","HR",2013 +"2013-10-08","Dan neovisnosti","HR",2013 +"2013-11-01","Svi sveti","HR",2013 +"2013-12-25","Bozic","HR",2013 +"2013-12-26","Sveti Stjepan","HR",2013 +"2014-01-01","Nova Godina","HR",2014 +"2014-01-06","Sveta tri kralja","HR",2014 +"2014-04-20","Uskrs","HR",2014 +"2014-04-21","Uskrsni ponedjeljak","HR",2014 +"2014-05-01","Meunarodni praznik rada","HR",2014 +"2014-06-19","Tijelovo","HR",2014 +"2014-06-22","Dan antifasisticke borbe","HR",2014 +"2014-06-25","Dan drzavnosti","HR",2014 +"2014-08-05","Dan pobjede i domovinske zahvalnosti","HR",2014 +"2014-08-15","Velika Gospa","HR",2014 +"2014-10-08","Dan neovisnosti","HR",2014 +"2014-11-01","Svi sveti","HR",2014 +"2014-12-25","Bozic","HR",2014 +"2014-12-26","Sveti Stjepan","HR",2014 +"2015-01-01","Nova Godina","HR",2015 +"2015-01-06","Sveta tri kralja","HR",2015 +"2015-04-05","Uskrs","HR",2015 +"2015-04-06","Uskrsni ponedjeljak","HR",2015 +"2015-05-01","Meunarodni praznik rada","HR",2015 +"2015-06-04","Tijelovo","HR",2015 +"2015-06-22","Dan antifasisticke borbe","HR",2015 +"2015-06-25","Dan drzavnosti","HR",2015 +"2015-08-05","Dan pobjede i domovinske zahvalnosti","HR",2015 +"2015-08-15","Velika Gospa","HR",2015 +"2015-10-08","Dan neovisnosti","HR",2015 +"2015-11-01","Svi sveti","HR",2015 +"2015-12-25","Bozic","HR",2015 +"2015-12-26","Sveti Stjepan","HR",2015 +"2016-01-01","Nova Godina","HR",2016 +"2016-01-06","Sveta tri kralja","HR",2016 +"2016-03-27","Uskrs","HR",2016 +"2016-03-28","Uskrsni ponedjeljak","HR",2016 +"2016-05-01","Meunarodni praznik rada","HR",2016 +"2016-05-26","Tijelovo","HR",2016 +"2016-06-22","Dan antifasisticke borbe","HR",2016 +"2016-06-25","Dan drzavnosti","HR",2016 +"2016-08-05","Dan pobjede i domovinske zahvalnosti","HR",2016 +"2016-08-15","Velika Gospa","HR",2016 +"2016-10-08","Dan neovisnosti","HR",2016 +"2016-11-01","Svi sveti","HR",2016 +"2016-12-25","Bozic","HR",2016 +"2016-12-26","Sveti Stjepan","HR",2016 +"2017-01-01","Nova Godina","HR",2017 +"2017-01-06","Sveta tri kralja","HR",2017 +"2017-04-16","Uskrs","HR",2017 +"2017-04-17","Uskrsni ponedjeljak","HR",2017 +"2017-05-01","Meunarodni praznik rada","HR",2017 +"2017-06-15","Tijelovo","HR",2017 +"2017-06-22","Dan antifasisticke borbe","HR",2017 +"2017-06-25","Dan drzavnosti","HR",2017 +"2017-08-05","Dan pobjede i domovinske zahvalnosti","HR",2017 +"2017-08-15","Velika Gospa","HR",2017 +"2017-10-08","Dan neovisnosti","HR",2017 +"2017-11-01","Svi sveti","HR",2017 +"2017-12-25","Bozic","HR",2017 +"2017-12-26","Sveti Stjepan","HR",2017 +"2018-01-01","Nova Godina","HR",2018 +"2018-01-06","Sveta tri kralja","HR",2018 +"2018-04-01","Uskrs","HR",2018 +"2018-04-02","Uskrsni ponedjeljak","HR",2018 +"2018-05-01","Meunarodni praznik rada","HR",2018 +"2018-05-31","Tijelovo","HR",2018 +"2018-06-22","Dan antifasisticke borbe","HR",2018 +"2018-06-25","Dan drzavnosti","HR",2018 +"2018-08-05","Dan pobjede i domovinske zahvalnosti","HR",2018 +"2018-08-15","Velika Gospa","HR",2018 +"2018-10-08","Dan neovisnosti","HR",2018 +"2018-11-01","Svi sveti","HR",2018 +"2018-12-25","Bozic","HR",2018 +"2018-12-26","Sveti Stjepan","HR",2018 +"2019-01-01","Nova Godina","HR",2019 +"2019-01-06","Sveta tri kralja","HR",2019 +"2019-04-21","Uskrs","HR",2019 +"2019-04-22","Uskrsni ponedjeljak","HR",2019 +"2019-05-01","Meunarodni praznik rada","HR",2019 +"2019-06-20","Tijelovo","HR",2019 +"2019-06-22","Dan antifasisticke borbe","HR",2019 +"2019-06-25","Dan drzavnosti","HR",2019 +"2019-08-05","Dan pobjede i domovinske zahvalnosti","HR",2019 +"2019-08-15","Velika Gospa","HR",2019 +"2019-10-08","Dan neovisnosti","HR",2019 +"2019-11-01","Svi sveti","HR",2019 +"2019-12-25","Bozic","HR",2019 +"2019-12-26","Sveti Stjepan","HR",2019 +"2020-01-01","Nova Godina","HR",2020 +"2020-01-06","Sveta tri kralja","HR",2020 +"2020-04-12","Uskrs","HR",2020 +"2020-04-13","Uskrsni ponedjeljak","HR",2020 +"2020-05-01","Meunarodni praznik rada","HR",2020 +"2020-05-30","Dan drzavnosti","HR",2020 +"2020-06-11","Tijelovo","HR",2020 +"2020-06-22","Dan antifasisticke borbe","HR",2020 +"2020-08-05","Dan pobjede i domovinske zahvalnosti","HR",2020 +"2020-08-15","Velika Gospa","HR",2020 +"2020-11-01","Svi sveti","HR",2020 +"2020-11-18","Dan sjecanja","HR",2020 +"2020-12-25","Bozic","HR",2020 +"2020-12-26","Sveti Stjepan","HR",2020 +"2021-01-01","Nova Godina","HR",2021 +"2021-01-06","Sveta tri kralja","HR",2021 +"2021-04-04","Uskrs","HR",2021 +"2021-04-05","Uskrsni ponedjeljak","HR",2021 +"2021-05-01","Meunarodni praznik rada","HR",2021 +"2021-05-30","Dan drzavnosti","HR",2021 +"2021-06-03","Tijelovo","HR",2021 +"2021-06-22","Dan antifasisticke borbe","HR",2021 +"2021-08-05","Dan pobjede i domovinske zahvalnosti","HR",2021 +"2021-08-15","Velika Gospa","HR",2021 +"2021-11-01","Svi sveti","HR",2021 +"2021-11-18","Dan sjecanja","HR",2021 +"2021-12-25","Bozic","HR",2021 +"2021-12-26","Sveti Stjepan","HR",2021 +"2022-01-01","Nova Godina","HR",2022 +"2022-01-06","Sveta tri kralja","HR",2022 +"2022-04-17","Uskrs","HR",2022 +"2022-04-18","Uskrsni ponedjeljak","HR",2022 +"2022-05-01","Meunarodni praznik rada","HR",2022 +"2022-05-30","Dan drzavnosti","HR",2022 +"2022-06-16","Tijelovo","HR",2022 +"2022-06-22","Dan antifasisticke borbe","HR",2022 +"2022-08-05","Dan pobjede i domovinske zahvalnosti","HR",2022 +"2022-08-15","Velika Gospa","HR",2022 +"2022-11-01","Svi sveti","HR",2022 +"2022-11-18","Dan sjecanja","HR",2022 +"2022-12-25","Bozic","HR",2022 +"2022-12-26","Sveti Stjepan","HR",2022 +"2023-01-01","Nova Godina","HR",2023 +"2023-01-06","Sveta tri kralja","HR",2023 +"2023-04-09","Uskrs","HR",2023 +"2023-04-10","Uskrsni ponedjeljak","HR",2023 +"2023-05-01","Meunarodni praznik rada","HR",2023 +"2023-05-30","Dan drzavnosti","HR",2023 +"2023-06-08","Tijelovo","HR",2023 +"2023-06-22","Dan antifasisticke borbe","HR",2023 +"2023-08-05","Dan pobjede i domovinske zahvalnosti","HR",2023 +"2023-08-15","Velika Gospa","HR",2023 +"2023-11-01","Svi sveti","HR",2023 +"2023-11-18","Dan sjecanja","HR",2023 +"2023-12-25","Bozic","HR",2023 +"2023-12-26","Sveti Stjepan","HR",2023 +"2024-01-01","Nova Godina","HR",2024 +"2024-01-06","Sveta tri kralja","HR",2024 +"2024-03-31","Uskrs","HR",2024 +"2024-04-01","Uskrsni ponedjeljak","HR",2024 +"2024-05-01","Meunarodni praznik rada","HR",2024 +"2024-05-30","Dan drzavnosti","HR",2024 +"2024-05-30","Tijelovo","HR",2024 +"2024-06-22","Dan antifasisticke borbe","HR",2024 +"2024-08-05","Dan pobjede i domovinske zahvalnosti","HR",2024 +"2024-08-15","Velika Gospa","HR",2024 +"2024-11-01","Svi sveti","HR",2024 +"2024-11-18","Dan sjecanja","HR",2024 +"2024-12-25","Bozic","HR",2024 +"2024-12-26","Sveti Stjepan","HR",2024 +"2025-01-01","Nova Godina","HR",2025 +"2025-01-06","Sveta tri kralja","HR",2025 +"2025-04-20","Uskrs","HR",2025 +"2025-04-21","Uskrsni ponedjeljak","HR",2025 +"2025-05-01","Meunarodni praznik rada","HR",2025 +"2025-05-30","Dan drzavnosti","HR",2025 +"2025-06-19","Tijelovo","HR",2025 +"2025-06-22","Dan antifasisticke borbe","HR",2025 +"2025-08-05","Dan pobjede i domovinske zahvalnosti","HR",2025 +"2025-08-15","Velika Gospa","HR",2025 +"2025-11-01","Svi sveti","HR",2025 +"2025-11-18","Dan sjecanja","HR",2025 +"2025-12-25","Bozic","HR",2025 +"2025-12-26","Sveti Stjepan","HR",2025 +"2026-01-01","Nova Godina","HR",2026 +"2026-01-06","Sveta tri kralja","HR",2026 +"2026-04-05","Uskrs","HR",2026 +"2026-04-06","Uskrsni ponedjeljak","HR",2026 +"2026-05-01","Meunarodni praznik rada","HR",2026 +"2026-05-30","Dan drzavnosti","HR",2026 +"2026-06-04","Tijelovo","HR",2026 +"2026-06-22","Dan antifasisticke borbe","HR",2026 +"2026-08-05","Dan pobjede i domovinske zahvalnosti","HR",2026 +"2026-08-15","Velika Gospa","HR",2026 +"2026-11-01","Svi sveti","HR",2026 +"2026-11-18","Dan sjecanja","HR",2026 +"2026-12-25","Bozic","HR",2026 +"2026-12-26","Sveti Stjepan","HR",2026 +"2027-01-01","Nova Godina","HR",2027 +"2027-01-06","Sveta tri kralja","HR",2027 +"2027-03-28","Uskrs","HR",2027 +"2027-03-29","Uskrsni ponedjeljak","HR",2027 +"2027-05-01","Meunarodni praznik rada","HR",2027 +"2027-05-27","Tijelovo","HR",2027 +"2027-05-30","Dan drzavnosti","HR",2027 +"2027-06-22","Dan antifasisticke borbe","HR",2027 +"2027-08-05","Dan pobjede i domovinske zahvalnosti","HR",2027 +"2027-08-15","Velika Gospa","HR",2027 +"2027-11-01","Svi sveti","HR",2027 +"2027-11-18","Dan sjecanja","HR",2027 +"2027-12-25","Bozic","HR",2027 +"2027-12-26","Sveti Stjepan","HR",2027 +"2028-01-01","Nova Godina","HR",2028 +"2028-01-06","Sveta tri kralja","HR",2028 +"2028-04-16","Uskrs","HR",2028 +"2028-04-17","Uskrsni ponedjeljak","HR",2028 +"2028-05-01","Meunarodni praznik rada","HR",2028 +"2028-05-30","Dan drzavnosti","HR",2028 +"2028-06-15","Tijelovo","HR",2028 +"2028-06-22","Dan antifasisticke borbe","HR",2028 +"2028-08-05","Dan pobjede i domovinske zahvalnosti","HR",2028 +"2028-08-15","Velika Gospa","HR",2028 +"2028-11-01","Svi sveti","HR",2028 +"2028-11-18","Dan sjecanja","HR",2028 +"2028-12-25","Bozic","HR",2028 +"2028-12-26","Sveti Stjepan","HR",2028 +"2029-01-01","Nova Godina","HR",2029 +"2029-01-06","Sveta tri kralja","HR",2029 +"2029-04-01","Uskrs","HR",2029 +"2029-04-02","Uskrsni ponedjeljak","HR",2029 +"2029-05-01","Meunarodni praznik rada","HR",2029 +"2029-05-30","Dan drzavnosti","HR",2029 +"2029-05-31","Tijelovo","HR",2029 +"2029-06-22","Dan antifasisticke borbe","HR",2029 +"2029-08-05","Dan pobjede i domovinske zahvalnosti","HR",2029 +"2029-08-15","Velika Gospa","HR",2029 +"2029-11-01","Svi sveti","HR",2029 +"2029-11-18","Dan sjecanja","HR",2029 +"2029-12-25","Bozic","HR",2029 +"2029-12-26","Sveti Stjepan","HR",2029 +"2030-01-01","Nova Godina","HR",2030 +"2030-01-06","Sveta tri kralja","HR",2030 +"2030-04-21","Uskrs","HR",2030 +"2030-04-22","Uskrsni ponedjeljak","HR",2030 +"2030-05-01","Meunarodni praznik rada","HR",2030 +"2030-05-30","Dan drzavnosti","HR",2030 +"2030-06-20","Tijelovo","HR",2030 +"2030-06-22","Dan antifasisticke borbe","HR",2030 +"2030-08-05","Dan pobjede i domovinske zahvalnosti","HR",2030 +"2030-08-15","Velika Gospa","HR",2030 +"2030-11-01","Svi sveti","HR",2030 +"2030-11-18","Dan sjecanja","HR",2030 +"2030-12-25","Bozic","HR",2030 +"2030-12-26","Sveti Stjepan","HR",2030 +"2031-01-01","Nova Godina","HR",2031 +"2031-01-06","Sveta tri kralja","HR",2031 +"2031-04-13","Uskrs","HR",2031 +"2031-04-14","Uskrsni ponedjeljak","HR",2031 +"2031-05-01","Meunarodni praznik rada","HR",2031 +"2031-05-30","Dan drzavnosti","HR",2031 +"2031-06-12","Tijelovo","HR",2031 +"2031-06-22","Dan antifasisticke borbe","HR",2031 +"2031-08-05","Dan pobjede i domovinske zahvalnosti","HR",2031 +"2031-08-15","Velika Gospa","HR",2031 +"2031-11-01","Svi sveti","HR",2031 +"2031-11-18","Dan sjecanja","HR",2031 +"2031-12-25","Bozic","HR",2031 +"2031-12-26","Sveti Stjepan","HR",2031 +"2032-01-01","Nova Godina","HR",2032 +"2032-01-06","Sveta tri kralja","HR",2032 +"2032-03-28","Uskrs","HR",2032 +"2032-03-29","Uskrsni ponedjeljak","HR",2032 +"2032-05-01","Meunarodni praznik rada","HR",2032 +"2032-05-27","Tijelovo","HR",2032 +"2032-05-30","Dan drzavnosti","HR",2032 +"2032-06-22","Dan antifasisticke borbe","HR",2032 +"2032-08-05","Dan pobjede i domovinske zahvalnosti","HR",2032 +"2032-08-15","Velika Gospa","HR",2032 +"2032-11-01","Svi sveti","HR",2032 +"2032-11-18","Dan sjecanja","HR",2032 +"2032-12-25","Bozic","HR",2032 +"2032-12-26","Sveti Stjepan","HR",2032 +"2033-01-01","Nova Godina","HR",2033 +"2033-01-06","Sveta tri kralja","HR",2033 +"2033-04-17","Uskrs","HR",2033 +"2033-04-18","Uskrsni ponedjeljak","HR",2033 +"2033-05-01","Meunarodni praznik rada","HR",2033 +"2033-05-30","Dan drzavnosti","HR",2033 +"2033-06-16","Tijelovo","HR",2033 +"2033-06-22","Dan antifasisticke borbe","HR",2033 +"2033-08-05","Dan pobjede i domovinske zahvalnosti","HR",2033 +"2033-08-15","Velika Gospa","HR",2033 +"2033-11-01","Svi sveti","HR",2033 +"2033-11-18","Dan sjecanja","HR",2033 +"2033-12-25","Bozic","HR",2033 +"2033-12-26","Sveti Stjepan","HR",2033 +"2034-01-01","Nova Godina","HR",2034 +"2034-01-06","Sveta tri kralja","HR",2034 +"2034-04-09","Uskrs","HR",2034 +"2034-04-10","Uskrsni ponedjeljak","HR",2034 +"2034-05-01","Meunarodni praznik rada","HR",2034 +"2034-05-30","Dan drzavnosti","HR",2034 +"2034-06-08","Tijelovo","HR",2034 +"2034-06-22","Dan antifasisticke borbe","HR",2034 +"2034-08-05","Dan pobjede i domovinske zahvalnosti","HR",2034 +"2034-08-15","Velika Gospa","HR",2034 +"2034-11-01","Svi sveti","HR",2034 +"2034-11-18","Dan sjecanja","HR",2034 +"2034-12-25","Bozic","HR",2034 +"2034-12-26","Sveti Stjepan","HR",2034 +"2035-01-01","Nova Godina","HR",2035 +"2035-01-06","Sveta tri kralja","HR",2035 +"2035-03-25","Uskrs","HR",2035 +"2035-03-26","Uskrsni ponedjeljak","HR",2035 +"2035-05-01","Meunarodni praznik rada","HR",2035 +"2035-05-24","Tijelovo","HR",2035 +"2035-05-30","Dan drzavnosti","HR",2035 +"2035-06-22","Dan antifasisticke borbe","HR",2035 +"2035-08-05","Dan pobjede i domovinske zahvalnosti","HR",2035 +"2035-08-15","Velika Gospa","HR",2035 +"2035-11-01","Svi sveti","HR",2035 +"2035-11-18","Dan sjecanja","HR",2035 +"2035-12-25","Bozic","HR",2035 +"2035-12-26","Sveti Stjepan","HR",2035 +"2036-01-01","Nova Godina","HR",2036 +"2036-01-06","Sveta tri kralja","HR",2036 +"2036-04-13","Uskrs","HR",2036 +"2036-04-14","Uskrsni ponedjeljak","HR",2036 +"2036-05-01","Meunarodni praznik rada","HR",2036 +"2036-05-30","Dan drzavnosti","HR",2036 +"2036-06-12","Tijelovo","HR",2036 +"2036-06-22","Dan antifasisticke borbe","HR",2036 +"2036-08-05","Dan pobjede i domovinske zahvalnosti","HR",2036 +"2036-08-15","Velika Gospa","HR",2036 +"2036-11-01","Svi sveti","HR",2036 +"2036-11-18","Dan sjecanja","HR",2036 +"2036-12-25","Bozic","HR",2036 +"2036-12-26","Sveti Stjepan","HR",2036 +"2037-01-01","Nova Godina","HR",2037 +"2037-01-06","Sveta tri kralja","HR",2037 +"2037-04-05","Uskrs","HR",2037 +"2037-04-06","Uskrsni ponedjeljak","HR",2037 +"2037-05-01","Meunarodni praznik rada","HR",2037 +"2037-05-30","Dan drzavnosti","HR",2037 +"2037-06-04","Tijelovo","HR",2037 +"2037-06-22","Dan antifasisticke borbe","HR",2037 +"2037-08-05","Dan pobjede i domovinske zahvalnosti","HR",2037 +"2037-08-15","Velika Gospa","HR",2037 +"2037-11-01","Svi sveti","HR",2037 +"2037-11-18","Dan sjecanja","HR",2037 +"2037-12-25","Bozic","HR",2037 +"2037-12-26","Sveti Stjepan","HR",2037 +"2038-01-01","Nova Godina","HR",2038 +"2038-01-06","Sveta tri kralja","HR",2038 +"2038-04-25","Uskrs","HR",2038 +"2038-04-26","Uskrsni ponedjeljak","HR",2038 +"2038-05-01","Meunarodni praznik rada","HR",2038 +"2038-05-30","Dan drzavnosti","HR",2038 +"2038-06-22","Dan antifasisticke borbe","HR",2038 +"2038-06-24","Tijelovo","HR",2038 +"2038-08-05","Dan pobjede i domovinske zahvalnosti","HR",2038 +"2038-08-15","Velika Gospa","HR",2038 +"2038-11-01","Svi sveti","HR",2038 +"2038-11-18","Dan sjecanja","HR",2038 +"2038-12-25","Bozic","HR",2038 +"2038-12-26","Sveti Stjepan","HR",2038 +"2039-01-01","Nova Godina","HR",2039 +"2039-01-06","Sveta tri kralja","HR",2039 +"2039-04-10","Uskrs","HR",2039 +"2039-04-11","Uskrsni ponedjeljak","HR",2039 +"2039-05-01","Meunarodni praznik rada","HR",2039 +"2039-05-30","Dan drzavnosti","HR",2039 +"2039-06-09","Tijelovo","HR",2039 +"2039-06-22","Dan antifasisticke borbe","HR",2039 +"2039-08-05","Dan pobjede i domovinske zahvalnosti","HR",2039 +"2039-08-15","Velika Gospa","HR",2039 +"2039-11-01","Svi sveti","HR",2039 +"2039-11-18","Dan sjecanja","HR",2039 +"2039-12-25","Bozic","HR",2039 +"2039-12-26","Sveti Stjepan","HR",2039 +"2040-01-01","Nova Godina","HR",2040 +"2040-01-06","Sveta tri kralja","HR",2040 +"2040-04-01","Uskrs","HR",2040 +"2040-04-02","Uskrsni ponedjeljak","HR",2040 +"2040-05-01","Meunarodni praznik rada","HR",2040 +"2040-05-30","Dan drzavnosti","HR",2040 +"2040-05-31","Tijelovo","HR",2040 +"2040-06-22","Dan antifasisticke borbe","HR",2040 +"2040-08-05","Dan pobjede i domovinske zahvalnosti","HR",2040 +"2040-08-15","Velika Gospa","HR",2040 +"2040-11-01","Svi sveti","HR",2040 +"2040-11-18","Dan sjecanja","HR",2040 +"2040-12-25","Bozic","HR",2040 +"2040-12-26","Sveti Stjepan","HR",2040 +"2041-01-01","Nova Godina","HR",2041 +"2041-01-06","Sveta tri kralja","HR",2041 +"2041-04-21","Uskrs","HR",2041 +"2041-04-22","Uskrsni ponedjeljak","HR",2041 +"2041-05-01","Meunarodni praznik rada","HR",2041 +"2041-05-30","Dan drzavnosti","HR",2041 +"2041-06-20","Tijelovo","HR",2041 +"2041-06-22","Dan antifasisticke borbe","HR",2041 +"2041-08-05","Dan pobjede i domovinske zahvalnosti","HR",2041 +"2041-08-15","Velika Gospa","HR",2041 +"2041-11-01","Svi sveti","HR",2041 +"2041-11-18","Dan sjecanja","HR",2041 +"2041-12-25","Bozic","HR",2041 +"2041-12-26","Sveti Stjepan","HR",2041 +"2042-01-01","Nova Godina","HR",2042 +"2042-01-06","Sveta tri kralja","HR",2042 +"2042-04-06","Uskrs","HR",2042 +"2042-04-07","Uskrsni ponedjeljak","HR",2042 +"2042-05-01","Meunarodni praznik rada","HR",2042 +"2042-05-30","Dan drzavnosti","HR",2042 +"2042-06-05","Tijelovo","HR",2042 +"2042-06-22","Dan antifasisticke borbe","HR",2042 +"2042-08-05","Dan pobjede i domovinske zahvalnosti","HR",2042 +"2042-08-15","Velika Gospa","HR",2042 +"2042-11-01","Svi sveti","HR",2042 +"2042-11-18","Dan sjecanja","HR",2042 +"2042-12-25","Bozic","HR",2042 +"2042-12-26","Sveti Stjepan","HR",2042 +"2043-01-01","Nova Godina","HR",2043 +"2043-01-06","Sveta tri kralja","HR",2043 +"2043-03-29","Uskrs","HR",2043 +"2043-03-30","Uskrsni ponedjeljak","HR",2043 +"2043-05-01","Meunarodni praznik rada","HR",2043 +"2043-05-28","Tijelovo","HR",2043 +"2043-05-30","Dan drzavnosti","HR",2043 +"2043-06-22","Dan antifasisticke borbe","HR",2043 +"2043-08-05","Dan pobjede i domovinske zahvalnosti","HR",2043 +"2043-08-15","Velika Gospa","HR",2043 +"2043-11-01","Svi sveti","HR",2043 +"2043-11-18","Dan sjecanja","HR",2043 +"2043-12-25","Bozic","HR",2043 +"2043-12-26","Sveti Stjepan","HR",2043 +"2044-01-01","Nova Godina","HR",2044 +"2044-01-06","Sveta tri kralja","HR",2044 +"2044-04-17","Uskrs","HR",2044 +"2044-04-18","Uskrsni ponedjeljak","HR",2044 +"2044-05-01","Meunarodni praznik rada","HR",2044 +"2044-05-30","Dan drzavnosti","HR",2044 +"2044-06-16","Tijelovo","HR",2044 +"2044-06-22","Dan antifasisticke borbe","HR",2044 +"2044-08-05","Dan pobjede i domovinske zahvalnosti","HR",2044 +"2044-08-15","Velika Gospa","HR",2044 +"2044-11-01","Svi sveti","HR",2044 +"2044-11-18","Dan sjecanja","HR",2044 +"2044-12-25","Bozic","HR",2044 +"2044-12-26","Sveti Stjepan","HR",2044 +"1995-01-01","Ujev","HU",1995 +"1995-03-15","Nemzeti unnep","HU",1995 +"1995-04-16","Husvet","HU",1995 +"1995-04-17","Husvet Hetfo","HU",1995 +"1995-05-01","A Munka unnepe","HU",1995 +"1995-06-04","Punkosd","HU",1995 +"1995-06-05","Punkosdhetfo","HU",1995 +"1995-08-20","Az allamalapitas unnepe","HU",1995 +"1995-10-23","Nemzeti unnep","HU",1995 +"1995-12-25","Karacsony","HU",1995 +"1995-12-26","Karacsony masnapja","HU",1995 +"1996-01-01","Ujev","HU",1996 +"1996-03-15","Nemzeti unnep","HU",1996 +"1996-04-07","Husvet","HU",1996 +"1996-04-08","Husvet Hetfo","HU",1996 +"1996-05-01","A Munka unnepe","HU",1996 +"1996-05-26","Punkosd","HU",1996 +"1996-05-27","Punkosdhetfo","HU",1996 +"1996-08-20","Az allamalapitas unnepe","HU",1996 +"1996-10-23","Nemzeti unnep","HU",1996 +"1996-12-25","Karacsony","HU",1996 +"1996-12-26","Karacsony masnapja","HU",1996 +"1997-01-01","Ujev","HU",1997 +"1997-03-15","Nemzeti unnep","HU",1997 +"1997-03-30","Husvet","HU",1997 +"1997-03-31","Husvet Hetfo","HU",1997 +"1997-05-01","A Munka unnepe","HU",1997 +"1997-05-18","Punkosd","HU",1997 +"1997-05-19","Punkosdhetfo","HU",1997 +"1997-08-20","Az allamalapitas unnepe","HU",1997 +"1997-10-23","Nemzeti unnep","HU",1997 +"1997-12-25","Karacsony","HU",1997 +"1997-12-26","Karacsony masnapja","HU",1997 +"1998-01-01","Ujev","HU",1998 +"1998-03-15","Nemzeti unnep","HU",1998 +"1998-04-12","Husvet","HU",1998 +"1998-04-13","Husvet Hetfo","HU",1998 +"1998-05-01","A Munka unnepe","HU",1998 +"1998-05-31","Punkosd","HU",1998 +"1998-06-01","Punkosdhetfo","HU",1998 +"1998-08-20","Az allamalapitas unnepe","HU",1998 +"1998-10-23","Nemzeti unnep","HU",1998 +"1998-12-25","Karacsony","HU",1998 +"1998-12-26","Karacsony masnapja","HU",1998 +"1999-01-01","Ujev","HU",1999 +"1999-03-15","Nemzeti unnep","HU",1999 +"1999-04-04","Husvet","HU",1999 +"1999-04-05","Husvet Hetfo","HU",1999 +"1999-05-01","A Munka unnepe","HU",1999 +"1999-05-23","Punkosd","HU",1999 +"1999-05-24","Punkosdhetfo","HU",1999 +"1999-08-20","Az allamalapitas unnepe","HU",1999 +"1999-10-23","Nemzeti unnep","HU",1999 +"1999-11-01","Mindenszentek","HU",1999 +"1999-12-25","Karacsony","HU",1999 +"1999-12-26","Karacsony masnapja","HU",1999 +"2000-01-01","Ujev","HU",2000 +"2000-03-15","Nemzeti unnep","HU",2000 +"2000-04-23","Husvet","HU",2000 +"2000-04-24","Husvet Hetfo","HU",2000 +"2000-05-01","A Munka unnepe","HU",2000 +"2000-06-11","Punkosd","HU",2000 +"2000-06-12","Punkosdhetfo","HU",2000 +"2000-08-20","Az allamalapitas unnepe","HU",2000 +"2000-10-23","Nemzeti unnep","HU",2000 +"2000-11-01","Mindenszentek","HU",2000 +"2000-12-25","Karacsony","HU",2000 +"2000-12-26","Karacsony masnapja","HU",2000 +"2001-01-01","Ujev","HU",2001 +"2001-03-15","Nemzeti unnep","HU",2001 +"2001-04-15","Husvet","HU",2001 +"2001-04-16","Husvet Hetfo","HU",2001 +"2001-05-01","A Munka unnepe","HU",2001 +"2001-06-03","Punkosd","HU",2001 +"2001-06-04","Punkosdhetfo","HU",2001 +"2001-08-20","Az allamalapitas unnepe","HU",2001 +"2001-10-23","Nemzeti unnep","HU",2001 +"2001-11-01","Mindenszentek","HU",2001 +"2001-12-25","Karacsony","HU",2001 +"2001-12-26","Karacsony masnapja","HU",2001 +"2002-01-01","Ujev","HU",2002 +"2002-03-15","Nemzeti unnep","HU",2002 +"2002-03-31","Husvet","HU",2002 +"2002-04-01","Husvet Hetfo","HU",2002 +"2002-05-01","A Munka unnepe","HU",2002 +"2002-05-19","Punkosd","HU",2002 +"2002-05-20","Punkosdhetfo","HU",2002 +"2002-08-20","Az allamalapitas unnepe","HU",2002 +"2002-10-23","Nemzeti unnep","HU",2002 +"2002-11-01","Mindenszentek","HU",2002 +"2002-12-25","Karacsony","HU",2002 +"2002-12-26","Karacsony masnapja","HU",2002 +"2003-01-01","Ujev","HU",2003 +"2003-03-15","Nemzeti unnep","HU",2003 +"2003-04-20","Husvet","HU",2003 +"2003-04-21","Husvet Hetfo","HU",2003 +"2003-05-01","A Munka unnepe","HU",2003 +"2003-06-08","Punkosd","HU",2003 +"2003-06-09","Punkosdhetfo","HU",2003 +"2003-08-20","Az allamalapitas unnepe","HU",2003 +"2003-10-23","Nemzeti unnep","HU",2003 +"2003-11-01","Mindenszentek","HU",2003 +"2003-12-25","Karacsony","HU",2003 +"2003-12-26","Karacsony masnapja","HU",2003 +"2004-01-01","Ujev","HU",2004 +"2004-03-15","Nemzeti unnep","HU",2004 +"2004-04-11","Husvet","HU",2004 +"2004-04-12","Husvet Hetfo","HU",2004 +"2004-05-01","A Munka unnepe","HU",2004 +"2004-05-30","Punkosd","HU",2004 +"2004-05-31","Punkosdhetfo","HU",2004 +"2004-08-20","Az allamalapitas unnepe","HU",2004 +"2004-10-23","Nemzeti unnep","HU",2004 +"2004-11-01","Mindenszentek","HU",2004 +"2004-12-25","Karacsony","HU",2004 +"2004-12-26","Karacsony masnapja","HU",2004 +"2005-01-01","Ujev","HU",2005 +"2005-03-15","Nemzeti unnep","HU",2005 +"2005-03-27","Husvet","HU",2005 +"2005-03-28","Husvet Hetfo","HU",2005 +"2005-05-01","A Munka unnepe","HU",2005 +"2005-05-15","Punkosd","HU",2005 +"2005-05-16","Punkosdhetfo","HU",2005 +"2005-08-20","Az allamalapitas unnepe","HU",2005 +"2005-10-23","Nemzeti unnep","HU",2005 +"2005-11-01","Mindenszentek","HU",2005 +"2005-12-25","Karacsony","HU",2005 +"2005-12-26","Karacsony masnapja","HU",2005 +"2006-01-01","Ujev","HU",2006 +"2006-03-15","Nemzeti unnep","HU",2006 +"2006-04-16","Husvet","HU",2006 +"2006-04-17","Husvet Hetfo","HU",2006 +"2006-05-01","A Munka unnepe","HU",2006 +"2006-06-04","Punkosd","HU",2006 +"2006-06-05","Punkosdhetfo","HU",2006 +"2006-08-20","Az allamalapitas unnepe","HU",2006 +"2006-10-23","Nemzeti unnep","HU",2006 +"2006-11-01","Mindenszentek","HU",2006 +"2006-12-25","Karacsony","HU",2006 +"2006-12-26","Karacsony masnapja","HU",2006 +"2007-01-01","Ujev","HU",2007 +"2007-03-15","Nemzeti unnep","HU",2007 +"2007-04-08","Husvet","HU",2007 +"2007-04-09","Husvet Hetfo","HU",2007 +"2007-05-01","A Munka unnepe","HU",2007 +"2007-05-27","Punkosd","HU",2007 +"2007-05-28","Punkosdhetfo","HU",2007 +"2007-08-20","Az allamalapitas unnepe","HU",2007 +"2007-10-23","Nemzeti unnep","HU",2007 +"2007-11-01","Mindenszentek","HU",2007 +"2007-12-25","Karacsony","HU",2007 +"2007-12-26","Karacsony masnapja","HU",2007 +"2008-01-01","Ujev","HU",2008 +"2008-03-15","Nemzeti unnep","HU",2008 +"2008-03-23","Husvet","HU",2008 +"2008-03-24","Husvet Hetfo","HU",2008 +"2008-05-01","A Munka unnepe","HU",2008 +"2008-05-11","Punkosd","HU",2008 +"2008-05-12","Punkosdhetfo","HU",2008 +"2008-08-20","Az allamalapitas unnepe","HU",2008 +"2008-10-23","Nemzeti unnep","HU",2008 +"2008-11-01","Mindenszentek","HU",2008 +"2008-12-25","Karacsony","HU",2008 +"2008-12-26","Karacsony masnapja","HU",2008 +"2009-01-01","Ujev","HU",2009 +"2009-03-15","Nemzeti unnep","HU",2009 +"2009-04-12","Husvet","HU",2009 +"2009-04-13","Husvet Hetfo","HU",2009 +"2009-05-01","A Munka unnepe","HU",2009 +"2009-05-31","Punkosd","HU",2009 +"2009-06-01","Punkosdhetfo","HU",2009 +"2009-08-20","Az allamalapitas unnepe","HU",2009 +"2009-10-23","Nemzeti unnep","HU",2009 +"2009-11-01","Mindenszentek","HU",2009 +"2009-12-25","Karacsony","HU",2009 +"2009-12-26","Karacsony masnapja","HU",2009 +"2010-01-01","Ujev","HU",2010 +"2010-03-15","Nemzeti unnep","HU",2010 +"2010-04-04","Husvet","HU",2010 +"2010-04-05","Husvet Hetfo","HU",2010 +"2010-05-01","A Munka unnepe","HU",2010 +"2010-05-23","Punkosd","HU",2010 +"2010-05-24","Punkosdhetfo","HU",2010 +"2010-08-20","Az allamalapitas unnepe","HU",2010 +"2010-10-23","Nemzeti unnep","HU",2010 +"2010-11-01","Mindenszentek","HU",2010 +"2010-12-24","Szenteste","HU",2010 +"2010-12-25","Karacsony","HU",2010 +"2010-12-26","Karacsony masnapja","HU",2010 +"2011-01-01","Ujev","HU",2011 +"2011-03-14","Nemzeti unnep elotti pihenonap","HU",2011 +"2011-03-15","Nemzeti unnep","HU",2011 +"2011-04-24","Husvet","HU",2011 +"2011-04-25","Husvet Hetfo","HU",2011 +"2011-05-01","A Munka unnepe","HU",2011 +"2011-06-12","Punkosd","HU",2011 +"2011-06-13","Punkosdhetfo","HU",2011 +"2011-08-20","Az allamalapitas unnepe","HU",2011 +"2011-10-23","Nemzeti unnep","HU",2011 +"2011-10-31","Mindenszentek elotti pihenonap","HU",2011 +"2011-11-01","Mindenszentek","HU",2011 +"2011-12-25","Karacsony","HU",2011 +"2011-12-26","Karacsony masnapja","HU",2011 +"2012-01-01","Ujev","HU",2012 +"2012-03-15","Nemzeti unnep","HU",2012 +"2012-03-16","Nemzeti unnep utani pihenonap","HU",2012 +"2012-04-08","Husvet","HU",2012 +"2012-04-09","Husvet Hetfo","HU",2012 +"2012-04-30","A Munka unnepe elotti pihenonap","HU",2012 +"2012-05-01","A Munka unnepe","HU",2012 +"2012-05-27","Punkosd","HU",2012 +"2012-05-28","Punkosdhetfo","HU",2012 +"2012-08-20","Az allamalapitas unnepe","HU",2012 +"2012-10-22","Nemzeti unnep elotti pihenonap","HU",2012 +"2012-10-23","Nemzeti unnep","HU",2012 +"2012-11-01","Mindenszentek","HU",2012 +"2012-11-02","Mindenszentek utani pihenonap","HU",2012 +"2012-12-24","Szenteste","HU",2012 +"2012-12-25","Karacsony","HU",2012 +"2012-12-26","Karacsony masnapja","HU",2012 +"2013-01-01","Ujev","HU",2013 +"2013-03-15","Nemzeti unnep","HU",2013 +"2013-03-31","Husvet","HU",2013 +"2013-04-01","Husvet Hetfo","HU",2013 +"2013-05-01","A Munka unnepe","HU",2013 +"2013-05-19","Punkosd","HU",2013 +"2013-05-20","Punkosdhetfo","HU",2013 +"2013-08-19","Az allamalapitas unnepe elotti pihenonap","HU",2013 +"2013-08-20","Az allamalapitas unnepe","HU",2013 +"2013-10-23","Nemzeti unnep","HU",2013 +"2013-11-01","Mindenszentek","HU",2013 +"2013-12-24","Szenteste","HU",2013 +"2013-12-25","Karacsony","HU",2013 +"2013-12-26","Karacsony masnapja","HU",2013 +"2013-12-27","Karacsony masnapja utani pihenonap","HU",2013 +"2014-01-01","Ujev","HU",2014 +"2014-03-15","Nemzeti unnep","HU",2014 +"2014-04-20","Husvet","HU",2014 +"2014-04-21","Husvet Hetfo","HU",2014 +"2014-05-01","A Munka unnepe","HU",2014 +"2014-05-02","A Munka unnepe utani pihenonap","HU",2014 +"2014-06-08","Punkosd","HU",2014 +"2014-06-09","Punkosdhetfo","HU",2014 +"2014-08-20","Az allamalapitas unnepe","HU",2014 +"2014-10-23","Nemzeti unnep","HU",2014 +"2014-10-24","Nemzeti unnep utani pihenonap","HU",2014 +"2014-11-01","Mindenszentek","HU",2014 +"2014-12-24","Szenteste","HU",2014 +"2014-12-25","Karacsony","HU",2014 +"2014-12-26","Karacsony masnapja","HU",2014 +"2015-01-01","Ujev","HU",2015 +"2015-01-02","Ujev utani pihenonap","HU",2015 +"2015-03-15","Nemzeti unnep","HU",2015 +"2015-04-05","Husvet","HU",2015 +"2015-04-06","Husvet Hetfo","HU",2015 +"2015-05-01","A Munka unnepe","HU",2015 +"2015-05-24","Punkosd","HU",2015 +"2015-05-25","Punkosdhetfo","HU",2015 +"2015-08-20","Az allamalapitas unnepe","HU",2015 +"2015-08-21","Az allamalapitas unnepe utani pihenonap","HU",2015 +"2015-10-23","Nemzeti unnep","HU",2015 +"2015-11-01","Mindenszentek","HU",2015 +"2015-12-24","Szenteste","HU",2015 +"2015-12-25","Karacsony","HU",2015 +"2015-12-26","Karacsony masnapja","HU",2015 +"2016-01-01","Ujev","HU",2016 +"2016-03-14","Nemzeti unnep elotti pihenonap","HU",2016 +"2016-03-15","Nemzeti unnep","HU",2016 +"2016-03-27","Husvet","HU",2016 +"2016-03-28","Husvet Hetfo","HU",2016 +"2016-05-01","A Munka unnepe","HU",2016 +"2016-05-15","Punkosd","HU",2016 +"2016-05-16","Punkosdhetfo","HU",2016 +"2016-08-20","Az allamalapitas unnepe","HU",2016 +"2016-10-23","Nemzeti unnep","HU",2016 +"2016-10-31","Mindenszentek elotti pihenonap","HU",2016 +"2016-11-01","Mindenszentek","HU",2016 +"2016-12-25","Karacsony","HU",2016 +"2016-12-26","Karacsony masnapja","HU",2016 +"2017-01-01","Ujev","HU",2017 +"2017-03-15","Nemzeti unnep","HU",2017 +"2017-04-14","Nagypentek","HU",2017 +"2017-04-16","Husvet","HU",2017 +"2017-04-17","Husvet Hetfo","HU",2017 +"2017-05-01","A Munka unnepe","HU",2017 +"2017-06-04","Punkosd","HU",2017 +"2017-06-05","Punkosdhetfo","HU",2017 +"2017-08-20","Az allamalapitas unnepe","HU",2017 +"2017-10-23","Nemzeti unnep","HU",2017 +"2017-11-01","Mindenszentek","HU",2017 +"2017-12-25","Karacsony","HU",2017 +"2017-12-26","Karacsony masnapja","HU",2017 +"2018-01-01","Ujev","HU",2018 +"2018-03-15","Nemzeti unnep","HU",2018 +"2018-03-16","Nemzeti unnep utani pihenonap","HU",2018 +"2018-03-30","Nagypentek","HU",2018 +"2018-04-01","Husvet","HU",2018 +"2018-04-02","Husvet Hetfo","HU",2018 +"2018-04-30","A Munka unnepe elotti pihenonap","HU",2018 +"2018-05-01","A Munka unnepe","HU",2018 +"2018-05-20","Punkosd","HU",2018 +"2018-05-21","Punkosdhetfo","HU",2018 +"2018-08-20","Az allamalapitas unnepe","HU",2018 +"2018-10-22","Nemzeti unnep elotti pihenonap","HU",2018 +"2018-10-23","Nemzeti unnep","HU",2018 +"2018-11-01","Mindenszentek","HU",2018 +"2018-11-02","Mindenszentek utani pihenonap","HU",2018 +"2018-12-24","Szenteste","HU",2018 +"2018-12-25","Karacsony","HU",2018 +"2018-12-26","Karacsony masnapja","HU",2018 +"2018-12-31","Szilveszter","HU",2018 +"2019-01-01","Ujev","HU",2019 +"2019-03-15","Nemzeti unnep","HU",2019 +"2019-04-19","Nagypentek","HU",2019 +"2019-04-21","Husvet","HU",2019 +"2019-04-22","Husvet Hetfo","HU",2019 +"2019-05-01","A Munka unnepe","HU",2019 +"2019-06-09","Punkosd","HU",2019 +"2019-06-10","Punkosdhetfo","HU",2019 +"2019-08-19","Az allamalapitas unnepe elotti pihenonap","HU",2019 +"2019-08-20","Az allamalapitas unnepe","HU",2019 +"2019-10-23","Nemzeti unnep","HU",2019 +"2019-11-01","Mindenszentek","HU",2019 +"2019-12-24","Szenteste","HU",2019 +"2019-12-25","Karacsony","HU",2019 +"2019-12-26","Karacsony masnapja","HU",2019 +"2019-12-27","Karacsony masnapja utani pihenonap","HU",2019 +"2020-01-01","Ujev","HU",2020 +"2020-03-15","Nemzeti unnep","HU",2020 +"2020-04-10","Nagypentek","HU",2020 +"2020-04-12","Husvet","HU",2020 +"2020-04-13","Husvet Hetfo","HU",2020 +"2020-05-01","A Munka unnepe","HU",2020 +"2020-05-31","Punkosd","HU",2020 +"2020-06-01","Punkosdhetfo","HU",2020 +"2020-08-20","Az allamalapitas unnepe","HU",2020 +"2020-08-21","Az allamalapitas unnepe utani pihenonap","HU",2020 +"2020-10-23","Nemzeti unnep","HU",2020 +"2020-11-01","Mindenszentek","HU",2020 +"2020-12-24","Szenteste","HU",2020 +"2020-12-25","Karacsony","HU",2020 +"2020-12-26","Karacsony masnapja","HU",2020 +"2021-01-01","Ujev","HU",2021 +"2021-03-15","Nemzeti unnep","HU",2021 +"2021-04-02","Nagypentek","HU",2021 +"2021-04-04","Husvet","HU",2021 +"2021-04-05","Husvet Hetfo","HU",2021 +"2021-05-01","A Munka unnepe","HU",2021 +"2021-05-23","Punkosd","HU",2021 +"2021-05-24","Punkosdhetfo","HU",2021 +"2021-08-20","Az allamalapitas unnepe","HU",2021 +"2021-10-23","Nemzeti unnep","HU",2021 +"2021-11-01","Mindenszentek","HU",2021 +"2021-12-24","Szenteste","HU",2021 +"2021-12-25","Karacsony","HU",2021 +"2021-12-26","Karacsony masnapja","HU",2021 +"2022-01-01","Ujev","HU",2022 +"2022-03-14","Nemzeti unnep elotti pihenonap","HU",2022 +"2022-03-15","Nemzeti unnep","HU",2022 +"2022-04-15","Nagypentek","HU",2022 +"2022-04-17","Husvet","HU",2022 +"2022-04-18","Husvet Hetfo","HU",2022 +"2022-05-01","A Munka unnepe","HU",2022 +"2022-06-05","Punkosd","HU",2022 +"2022-06-06","Punkosdhetfo","HU",2022 +"2022-08-20","Az allamalapitas unnepe","HU",2022 +"2022-10-23","Nemzeti unnep","HU",2022 +"2022-10-31","Mindenszentek elotti pihenonap","HU",2022 +"2022-11-01","Mindenszentek","HU",2022 +"2022-12-25","Karacsony","HU",2022 +"2022-12-26","Karacsony masnapja","HU",2022 +"2023-01-01","Ujev","HU",2023 +"2023-03-15","Nemzeti unnep","HU",2023 +"2023-04-07","Nagypentek","HU",2023 +"2023-04-09","Husvet","HU",2023 +"2023-04-10","Husvet Hetfo","HU",2023 +"2023-05-01","A Munka unnepe","HU",2023 +"2023-05-28","Punkosd","HU",2023 +"2023-05-29","Punkosdhetfo","HU",2023 +"2023-08-20","Az allamalapitas unnepe","HU",2023 +"2023-10-23","Nemzeti unnep","HU",2023 +"2023-11-01","Mindenszentek","HU",2023 +"2023-12-25","Karacsony","HU",2023 +"2023-12-26","Karacsony masnapja","HU",2023 +"2024-01-01","Ujev","HU",2024 +"2024-03-15","Nemzeti unnep","HU",2024 +"2024-03-29","Nagypentek","HU",2024 +"2024-03-31","Husvet","HU",2024 +"2024-04-01","Husvet Hetfo","HU",2024 +"2024-05-01","A Munka unnepe","HU",2024 +"2024-05-19","Punkosd","HU",2024 +"2024-05-20","Punkosdhetfo","HU",2024 +"2024-08-19","Az allamalapitas unnepe elotti pihenonap","HU",2024 +"2024-08-20","Az allamalapitas unnepe","HU",2024 +"2024-10-23","Nemzeti unnep","HU",2024 +"2024-11-01","Mindenszentek","HU",2024 +"2024-12-24","Szenteste","HU",2024 +"2024-12-25","Karacsony","HU",2024 +"2024-12-26","Karacsony masnapja","HU",2024 +"2024-12-27","Karacsony masnapja utani pihenonap","HU",2024 +"2025-01-01","Ujev","HU",2025 +"2025-03-15","Nemzeti unnep","HU",2025 +"2025-04-18","Nagypentek","HU",2025 +"2025-04-20","Husvet","HU",2025 +"2025-04-21","Husvet Hetfo","HU",2025 +"2025-05-01","A Munka unnepe","HU",2025 +"2025-05-02","A Munka unnepe utani pihenonap","HU",2025 +"2025-06-08","Punkosd","HU",2025 +"2025-06-09","Punkosdhetfo","HU",2025 +"2025-08-20","Az allamalapitas unnepe","HU",2025 +"2025-10-23","Nemzeti unnep","HU",2025 +"2025-10-24","Nemzeti unnep utani pihenonap","HU",2025 +"2025-11-01","Mindenszentek","HU",2025 +"2025-12-24","Szenteste","HU",2025 +"2025-12-25","Karacsony","HU",2025 +"2025-12-26","Karacsony masnapja","HU",2025 +"2026-01-01","Ujev","HU",2026 +"2026-01-02","Ujev utani pihenonap","HU",2026 +"2026-03-15","Nemzeti unnep","HU",2026 +"2026-04-03","Nagypentek","HU",2026 +"2026-04-05","Husvet","HU",2026 +"2026-04-06","Husvet Hetfo","HU",2026 +"2026-05-01","A Munka unnepe","HU",2026 +"2026-05-24","Punkosd","HU",2026 +"2026-05-25","Punkosdhetfo","HU",2026 +"2026-08-20","Az allamalapitas unnepe","HU",2026 +"2026-08-21","Az allamalapitas unnepe utani pihenonap","HU",2026 +"2026-10-23","Nemzeti unnep","HU",2026 +"2026-11-01","Mindenszentek","HU",2026 +"2026-12-24","Szenteste","HU",2026 +"2026-12-25","Karacsony","HU",2026 +"2026-12-26","Karacsony masnapja","HU",2026 +"2027-01-01","Ujev","HU",2027 +"2027-03-15","Nemzeti unnep","HU",2027 +"2027-03-26","Nagypentek","HU",2027 +"2027-03-28","Husvet","HU",2027 +"2027-03-29","Husvet Hetfo","HU",2027 +"2027-05-01","A Munka unnepe","HU",2027 +"2027-05-16","Punkosd","HU",2027 +"2027-05-17","Punkosdhetfo","HU",2027 +"2027-08-20","Az allamalapitas unnepe","HU",2027 +"2027-10-23","Nemzeti unnep","HU",2027 +"2027-11-01","Mindenszentek","HU",2027 +"2027-12-24","Szenteste","HU",2027 +"2027-12-25","Karacsony","HU",2027 +"2027-12-26","Karacsony masnapja","HU",2027 +"2028-01-01","Ujev","HU",2028 +"2028-03-15","Nemzeti unnep","HU",2028 +"2028-04-14","Nagypentek","HU",2028 +"2028-04-16","Husvet","HU",2028 +"2028-04-17","Husvet Hetfo","HU",2028 +"2028-05-01","A Munka unnepe","HU",2028 +"2028-06-04","Punkosd","HU",2028 +"2028-06-05","Punkosdhetfo","HU",2028 +"2028-08-20","Az allamalapitas unnepe","HU",2028 +"2028-10-23","Nemzeti unnep","HU",2028 +"2028-11-01","Mindenszentek","HU",2028 +"2028-12-25","Karacsony","HU",2028 +"2028-12-26","Karacsony masnapja","HU",2028 +"2029-01-01","Ujev","HU",2029 +"2029-03-15","Nemzeti unnep","HU",2029 +"2029-03-16","Nemzeti unnep utani pihenonap","HU",2029 +"2029-03-30","Nagypentek","HU",2029 +"2029-04-01","Husvet","HU",2029 +"2029-04-02","Husvet Hetfo","HU",2029 +"2029-04-30","A Munka unnepe elotti pihenonap","HU",2029 +"2029-05-01","A Munka unnepe","HU",2029 +"2029-05-20","Punkosd","HU",2029 +"2029-05-21","Punkosdhetfo","HU",2029 +"2029-08-20","Az allamalapitas unnepe","HU",2029 +"2029-10-22","Nemzeti unnep elotti pihenonap","HU",2029 +"2029-10-23","Nemzeti unnep","HU",2029 +"2029-11-01","Mindenszentek","HU",2029 +"2029-11-02","Mindenszentek utani pihenonap","HU",2029 +"2029-12-24","Szenteste","HU",2029 +"2029-12-25","Karacsony","HU",2029 +"2029-12-26","Karacsony masnapja","HU",2029 +"2029-12-31","Szilveszter","HU",2029 +"2030-01-01","Ujev","HU",2030 +"2030-03-15","Nemzeti unnep","HU",2030 +"2030-04-19","Nagypentek","HU",2030 +"2030-04-21","Husvet","HU",2030 +"2030-04-22","Husvet Hetfo","HU",2030 +"2030-05-01","A Munka unnepe","HU",2030 +"2030-06-09","Punkosd","HU",2030 +"2030-06-10","Punkosdhetfo","HU",2030 +"2030-08-19","Az allamalapitas unnepe elotti pihenonap","HU",2030 +"2030-08-20","Az allamalapitas unnepe","HU",2030 +"2030-10-23","Nemzeti unnep","HU",2030 +"2030-11-01","Mindenszentek","HU",2030 +"2030-12-24","Szenteste","HU",2030 +"2030-12-25","Karacsony","HU",2030 +"2030-12-26","Karacsony masnapja","HU",2030 +"2030-12-27","Karacsony masnapja utani pihenonap","HU",2030 +"2031-01-01","Ujev","HU",2031 +"2031-03-15","Nemzeti unnep","HU",2031 +"2031-04-11","Nagypentek","HU",2031 +"2031-04-13","Husvet","HU",2031 +"2031-04-14","Husvet Hetfo","HU",2031 +"2031-05-01","A Munka unnepe","HU",2031 +"2031-05-02","A Munka unnepe utani pihenonap","HU",2031 +"2031-06-01","Punkosd","HU",2031 +"2031-06-02","Punkosdhetfo","HU",2031 +"2031-08-20","Az allamalapitas unnepe","HU",2031 +"2031-10-23","Nemzeti unnep","HU",2031 +"2031-10-24","Nemzeti unnep utani pihenonap","HU",2031 +"2031-11-01","Mindenszentek","HU",2031 +"2031-12-24","Szenteste","HU",2031 +"2031-12-25","Karacsony","HU",2031 +"2031-12-26","Karacsony masnapja","HU",2031 +"2032-01-01","Ujev","HU",2032 +"2032-01-02","Ujev utani pihenonap","HU",2032 +"2032-03-15","Nemzeti unnep","HU",2032 +"2032-03-26","Nagypentek","HU",2032 +"2032-03-28","Husvet","HU",2032 +"2032-03-29","Husvet Hetfo","HU",2032 +"2032-05-01","A Munka unnepe","HU",2032 +"2032-05-16","Punkosd","HU",2032 +"2032-05-17","Punkosdhetfo","HU",2032 +"2032-08-20","Az allamalapitas unnepe","HU",2032 +"2032-10-23","Nemzeti unnep","HU",2032 +"2032-11-01","Mindenszentek","HU",2032 +"2032-12-24","Szenteste","HU",2032 +"2032-12-25","Karacsony","HU",2032 +"2032-12-26","Karacsony masnapja","HU",2032 +"2033-01-01","Ujev","HU",2033 +"2033-03-14","Nemzeti unnep elotti pihenonap","HU",2033 +"2033-03-15","Nemzeti unnep","HU",2033 +"2033-04-15","Nagypentek","HU",2033 +"2033-04-17","Husvet","HU",2033 +"2033-04-18","Husvet Hetfo","HU",2033 +"2033-05-01","A Munka unnepe","HU",2033 +"2033-06-05","Punkosd","HU",2033 +"2033-06-06","Punkosdhetfo","HU",2033 +"2033-08-20","Az allamalapitas unnepe","HU",2033 +"2033-10-23","Nemzeti unnep","HU",2033 +"2033-10-31","Mindenszentek elotti pihenonap","HU",2033 +"2033-11-01","Mindenszentek","HU",2033 +"2033-12-25","Karacsony","HU",2033 +"2033-12-26","Karacsony masnapja","HU",2033 +"2034-01-01","Ujev","HU",2034 +"2034-03-15","Nemzeti unnep","HU",2034 +"2034-04-07","Nagypentek","HU",2034 +"2034-04-09","Husvet","HU",2034 +"2034-04-10","Husvet Hetfo","HU",2034 +"2034-05-01","A Munka unnepe","HU",2034 +"2034-05-28","Punkosd","HU",2034 +"2034-05-29","Punkosdhetfo","HU",2034 +"2034-08-20","Az allamalapitas unnepe","HU",2034 +"2034-10-23","Nemzeti unnep","HU",2034 +"2034-11-01","Mindenszentek","HU",2034 +"2034-12-25","Karacsony","HU",2034 +"2034-12-26","Karacsony masnapja","HU",2034 +"2035-01-01","Ujev","HU",2035 +"2035-03-15","Nemzeti unnep","HU",2035 +"2035-03-16","Nemzeti unnep utani pihenonap","HU",2035 +"2035-03-23","Nagypentek","HU",2035 +"2035-03-25","Husvet","HU",2035 +"2035-03-26","Husvet Hetfo","HU",2035 +"2035-04-30","A Munka unnepe elotti pihenonap","HU",2035 +"2035-05-01","A Munka unnepe","HU",2035 +"2035-05-13","Punkosd","HU",2035 +"2035-05-14","Punkosdhetfo","HU",2035 +"2035-08-20","Az allamalapitas unnepe","HU",2035 +"2035-10-22","Nemzeti unnep elotti pihenonap","HU",2035 +"2035-10-23","Nemzeti unnep","HU",2035 +"2035-11-01","Mindenszentek","HU",2035 +"2035-11-02","Mindenszentek utani pihenonap","HU",2035 +"2035-12-24","Szenteste","HU",2035 +"2035-12-25","Karacsony","HU",2035 +"2035-12-26","Karacsony masnapja","HU",2035 +"2035-12-31","Szilveszter","HU",2035 +"2036-01-01","Ujev","HU",2036 +"2036-03-15","Nemzeti unnep","HU",2036 +"2036-04-11","Nagypentek","HU",2036 +"2036-04-13","Husvet","HU",2036 +"2036-04-14","Husvet Hetfo","HU",2036 +"2036-05-01","A Munka unnepe","HU",2036 +"2036-05-02","A Munka unnepe utani pihenonap","HU",2036 +"2036-06-01","Punkosd","HU",2036 +"2036-06-02","Punkosdhetfo","HU",2036 +"2036-08-20","Az allamalapitas unnepe","HU",2036 +"2036-10-23","Nemzeti unnep","HU",2036 +"2036-10-24","Nemzeti unnep utani pihenonap","HU",2036 +"2036-11-01","Mindenszentek","HU",2036 +"2036-12-24","Szenteste","HU",2036 +"2036-12-25","Karacsony","HU",2036 +"2036-12-26","Karacsony masnapja","HU",2036 +"2037-01-01","Ujev","HU",2037 +"2037-01-02","Ujev utani pihenonap","HU",2037 +"2037-03-15","Nemzeti unnep","HU",2037 +"2037-04-03","Nagypentek","HU",2037 +"2037-04-05","Husvet","HU",2037 +"2037-04-06","Husvet Hetfo","HU",2037 +"2037-05-01","A Munka unnepe","HU",2037 +"2037-05-24","Punkosd","HU",2037 +"2037-05-25","Punkosdhetfo","HU",2037 +"2037-08-20","Az allamalapitas unnepe","HU",2037 +"2037-08-21","Az allamalapitas unnepe utani pihenonap","HU",2037 +"2037-10-23","Nemzeti unnep","HU",2037 +"2037-11-01","Mindenszentek","HU",2037 +"2037-12-24","Szenteste","HU",2037 +"2037-12-25","Karacsony","HU",2037 +"2037-12-26","Karacsony masnapja","HU",2037 +"2038-01-01","Ujev","HU",2038 +"2038-03-15","Nemzeti unnep","HU",2038 +"2038-04-23","Nagypentek","HU",2038 +"2038-04-25","Husvet","HU",2038 +"2038-04-26","Husvet Hetfo","HU",2038 +"2038-05-01","A Munka unnepe","HU",2038 +"2038-06-13","Punkosd","HU",2038 +"2038-06-14","Punkosdhetfo","HU",2038 +"2038-08-20","Az allamalapitas unnepe","HU",2038 +"2038-10-23","Nemzeti unnep","HU",2038 +"2038-11-01","Mindenszentek","HU",2038 +"2038-12-24","Szenteste","HU",2038 +"2038-12-25","Karacsony","HU",2038 +"2038-12-26","Karacsony masnapja","HU",2038 +"2039-01-01","Ujev","HU",2039 +"2039-03-14","Nemzeti unnep elotti pihenonap","HU",2039 +"2039-03-15","Nemzeti unnep","HU",2039 +"2039-04-08","Nagypentek","HU",2039 +"2039-04-10","Husvet","HU",2039 +"2039-04-11","Husvet Hetfo","HU",2039 +"2039-05-01","A Munka unnepe","HU",2039 +"2039-05-29","Punkosd","HU",2039 +"2039-05-30","Punkosdhetfo","HU",2039 +"2039-08-20","Az allamalapitas unnepe","HU",2039 +"2039-10-23","Nemzeti unnep","HU",2039 +"2039-10-31","Mindenszentek elotti pihenonap","HU",2039 +"2039-11-01","Mindenszentek","HU",2039 +"2039-12-25","Karacsony","HU",2039 +"2039-12-26","Karacsony masnapja","HU",2039 +"2040-01-01","Ujev","HU",2040 +"2040-03-15","Nemzeti unnep","HU",2040 +"2040-03-16","Nemzeti unnep utani pihenonap","HU",2040 +"2040-03-30","Nagypentek","HU",2040 +"2040-04-01","Husvet","HU",2040 +"2040-04-02","Husvet Hetfo","HU",2040 +"2040-04-30","A Munka unnepe elotti pihenonap","HU",2040 +"2040-05-01","A Munka unnepe","HU",2040 +"2040-05-20","Punkosd","HU",2040 +"2040-05-21","Punkosdhetfo","HU",2040 +"2040-08-20","Az allamalapitas unnepe","HU",2040 +"2040-10-22","Nemzeti unnep elotti pihenonap","HU",2040 +"2040-10-23","Nemzeti unnep","HU",2040 +"2040-11-01","Mindenszentek","HU",2040 +"2040-11-02","Mindenszentek utani pihenonap","HU",2040 +"2040-12-24","Szenteste","HU",2040 +"2040-12-25","Karacsony","HU",2040 +"2040-12-26","Karacsony masnapja","HU",2040 +"2040-12-31","Szilveszter","HU",2040 +"2041-01-01","Ujev","HU",2041 +"2041-03-15","Nemzeti unnep","HU",2041 +"2041-04-19","Nagypentek","HU",2041 +"2041-04-21","Husvet","HU",2041 +"2041-04-22","Husvet Hetfo","HU",2041 +"2041-05-01","A Munka unnepe","HU",2041 +"2041-06-09","Punkosd","HU",2041 +"2041-06-10","Punkosdhetfo","HU",2041 +"2041-08-19","Az allamalapitas unnepe elotti pihenonap","HU",2041 +"2041-08-20","Az allamalapitas unnepe","HU",2041 +"2041-10-23","Nemzeti unnep","HU",2041 +"2041-11-01","Mindenszentek","HU",2041 +"2041-12-24","Szenteste","HU",2041 +"2041-12-25","Karacsony","HU",2041 +"2041-12-26","Karacsony masnapja","HU",2041 +"2041-12-27","Karacsony masnapja utani pihenonap","HU",2041 +"2042-01-01","Ujev","HU",2042 +"2042-03-15","Nemzeti unnep","HU",2042 +"2042-04-04","Nagypentek","HU",2042 +"2042-04-06","Husvet","HU",2042 +"2042-04-07","Husvet Hetfo","HU",2042 +"2042-05-01","A Munka unnepe","HU",2042 +"2042-05-02","A Munka unnepe utani pihenonap","HU",2042 +"2042-05-25","Punkosd","HU",2042 +"2042-05-26","Punkosdhetfo","HU",2042 +"2042-08-20","Az allamalapitas unnepe","HU",2042 +"2042-10-23","Nemzeti unnep","HU",2042 +"2042-10-24","Nemzeti unnep utani pihenonap","HU",2042 +"2042-11-01","Mindenszentek","HU",2042 +"2042-12-24","Szenteste","HU",2042 +"2042-12-25","Karacsony","HU",2042 +"2042-12-26","Karacsony masnapja","HU",2042 +"2043-01-01","Ujev","HU",2043 +"2043-01-02","Ujev utani pihenonap","HU",2043 +"2043-03-15","Nemzeti unnep","HU",2043 +"2043-03-27","Nagypentek","HU",2043 +"2043-03-29","Husvet","HU",2043 +"2043-03-30","Husvet Hetfo","HU",2043 +"2043-05-01","A Munka unnepe","HU",2043 +"2043-05-17","Punkosd","HU",2043 +"2043-05-18","Punkosdhetfo","HU",2043 +"2043-08-20","Az allamalapitas unnepe","HU",2043 +"2043-08-21","Az allamalapitas unnepe utani pihenonap","HU",2043 +"2043-10-23","Nemzeti unnep","HU",2043 +"2043-11-01","Mindenszentek","HU",2043 +"2043-12-24","Szenteste","HU",2043 +"2043-12-25","Karacsony","HU",2043 +"2043-12-26","Karacsony masnapja","HU",2043 +"2044-01-01","Ujev","HU",2044 +"2044-03-14","Nemzeti unnep elotti pihenonap","HU",2044 +"2044-03-15","Nemzeti unnep","HU",2044 +"2044-04-15","Nagypentek","HU",2044 +"2044-04-17","Husvet","HU",2044 +"2044-04-18","Husvet Hetfo","HU",2044 +"2044-05-01","A Munka unnepe","HU",2044 +"2044-06-05","Punkosd","HU",2044 +"2044-06-06","Punkosdhetfo","HU",2044 +"2044-08-20","Az allamalapitas unnepe","HU",2044 +"2044-10-23","Nemzeti unnep","HU",2044 +"2044-10-31","Mindenszentek elotti pihenonap","HU",2044 +"2044-11-01","Mindenszentek","HU",2044 +"2044-12-25","Karacsony","HU",2044 +"2044-12-26","Karacsony masnapja","HU",2044 +"1995-01-01","Tahun Baru Masehi","ID",1995 +"1995-03-02","Hari Raya Idul Fitri* (*estimated)","ID",1995 +"1995-03-03","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",1995 +"1995-04-14","Wafat Yesus Kristus","ID",1995 +"1995-05-09","Hari Raya Idul Adha* (*estimated)","ID",1995 +"1995-05-14","Hari Raya Waisak* (*estimated)","ID",1995 +"1995-05-25","Kenaikan Yesus Kristus","ID",1995 +"1995-05-30","Tahun Baru Islam* (*estimated)","ID",1995 +"1995-08-08","Maulid Nabi Muhammad* (*estimated)","ID",1995 +"1995-08-17","Hari Kemerdekaan Republik Indonesia","ID",1995 +"1995-12-19","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",1995 +"1995-12-25","Hari Raya Natal","ID",1995 +"1996-01-01","Tahun Baru Masehi","ID",1996 +"1996-02-19","Hari Raya Idul Fitri* (*estimated)","ID",1996 +"1996-02-20","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",1996 +"1996-04-05","Wafat Yesus Kristus","ID",1996 +"1996-04-27","Hari Raya Idul Adha* (*estimated)","ID",1996 +"1996-05-16","Kenaikan Yesus Kristus","ID",1996 +"1996-05-18","Tahun Baru Islam* (*estimated)","ID",1996 +"1996-05-31","Hari Raya Waisak* (*estimated)","ID",1996 +"1996-07-27","Maulid Nabi Muhammad* (*estimated)","ID",1996 +"1996-08-17","Hari Kemerdekaan Republik Indonesia","ID",1996 +"1996-12-08","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",1996 +"1996-12-25","Hari Raya Natal","ID",1996 +"1997-01-01","Tahun Baru Masehi","ID",1997 +"1997-02-08","Hari Raya Idul Fitri* (*estimated)","ID",1997 +"1997-02-09","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",1997 +"1997-03-28","Wafat Yesus Kristus","ID",1997 +"1997-04-17","Hari Raya Idul Adha* (*estimated)","ID",1997 +"1997-05-07","Tahun Baru Islam* (*estimated)","ID",1997 +"1997-05-08","Kenaikan Yesus Kristus","ID",1997 +"1997-05-21","Hari Raya Waisak* (*estimated)","ID",1997 +"1997-07-16","Maulid Nabi Muhammad* (*estimated)","ID",1997 +"1997-08-17","Hari Kemerdekaan Republik Indonesia","ID",1997 +"1997-11-27","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",1997 +"1997-12-25","Hari Raya Natal","ID",1997 +"1998-01-01","Tahun Baru Masehi","ID",1998 +"1998-01-29","Hari Raya Idul Fitri* (*estimated)","ID",1998 +"1998-01-30","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",1998 +"1998-04-07","Hari Raya Idul Adha* (*estimated)","ID",1998 +"1998-04-10","Wafat Yesus Kristus","ID",1998 +"1998-04-27","Tahun Baru Islam* (*estimated)","ID",1998 +"1998-05-10","Hari Raya Waisak* (*estimated)","ID",1998 +"1998-05-21","Kenaikan Yesus Kristus","ID",1998 +"1998-07-06","Maulid Nabi Muhammad* (*estimated)","ID",1998 +"1998-08-17","Hari Kemerdekaan Republik Indonesia","ID",1998 +"1998-11-16","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",1998 +"1998-12-25","Hari Raya Natal","ID",1998 +"1999-01-01","Tahun Baru Masehi","ID",1999 +"1999-01-18","Hari Raya Idul Fitri* (*estimated)","ID",1999 +"1999-01-19","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",1999 +"1999-03-27","Hari Raya Idul Adha* (*estimated)","ID",1999 +"1999-04-02","Wafat Yesus Kristus","ID",1999 +"1999-04-17","Tahun Baru Islam* (*estimated)","ID",1999 +"1999-05-13","Kenaikan Yesus Kristus","ID",1999 +"1999-05-29","Hari Raya Waisak* (*estimated)","ID",1999 +"1999-06-26","Maulid Nabi Muhammad* (*estimated)","ID",1999 +"1999-08-17","Hari Kemerdekaan Republik Indonesia","ID",1999 +"1999-11-05","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",1999 +"1999-12-25","Hari Raya Natal","ID",1999 +"2000-01-01","Tahun Baru Masehi","ID",2000 +"2000-01-08","Hari Raya Idul Fitri* (*estimated)","ID",2000 +"2000-01-09","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2000 +"2000-03-16","Hari Raya Idul Adha* (*estimated)","ID",2000 +"2000-04-06","Tahun Baru Islam* (*estimated)","ID",2000 +"2000-04-21","Wafat Yesus Kristus","ID",2000 +"2000-05-18","Hari Raya Waisak* (*estimated)","ID",2000 +"2000-06-01","Kenaikan Yesus Kristus","ID",2000 +"2000-06-14","Maulid Nabi Muhammad* (*estimated)","ID",2000 +"2000-08-17","Hari Kemerdekaan Republik Indonesia","ID",2000 +"2000-10-24","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2000 +"2000-12-25","Hari Raya Natal","ID",2000 +"2000-12-27","Hari Raya Idul Fitri* (*estimated)","ID",2000 +"2000-12-28","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2000 +"2001-01-01","Tahun Baru Masehi","ID",2001 +"2001-03-06","Hari Raya Idul Adha","ID",2001 +"2001-03-26","Tahun Baru Islam","ID",2001 +"2001-04-13","Wafat Yesus Kristus","ID",2001 +"2001-05-07","Hari Raya Waisak* (*estimated)","ID",2001 +"2001-05-24","Kenaikan Yesus Kristus","ID",2001 +"2001-06-04","Maulid Nabi Muhammad* (*estimated)","ID",2001 +"2001-08-17","Hari Kemerdekaan Republik Indonesia","ID",2001 +"2001-10-15","Isra' Mi'raj Nabi Muhammad","ID",2001 +"2001-12-16","Hari Raya Idul Fitri","ID",2001 +"2001-12-17","Hari kedua dari Hari Raya Idul Fitri","ID",2001 +"2001-12-25","Hari Raya Natal","ID",2001 +"2002-01-01","Tahun Baru Masehi","ID",2002 +"2002-02-23","Hari Raya Idul Adha","ID",2002 +"2002-03-15","Tahun Baru Islam","ID",2002 +"2002-03-29","Wafat Yesus Kristus","ID",2002 +"2002-05-09","Kenaikan Yesus Kristus","ID",2002 +"2002-05-24","Maulid Nabi Muhammad* (*estimated)","ID",2002 +"2002-05-26","Hari Raya Waisak* (*estimated)","ID",2002 +"2002-08-17","Hari Kemerdekaan Republik Indonesia","ID",2002 +"2002-10-04","Isra' Mi'raj Nabi Muhammad","ID",2002 +"2002-12-06","Hari Raya Idul Fitri","ID",2002 +"2002-12-07","Hari kedua dari Hari Raya Idul Fitri","ID",2002 +"2002-12-25","Hari Raya Natal","ID",2002 +"2003-01-01","Tahun Baru Masehi","ID",2003 +"2003-02-01","Tahun Baru Imlek","ID",2003 +"2003-02-12","Hari Raya Idul Adha","ID",2003 +"2003-03-05","Tahun Baru Islam","ID",2003 +"2003-04-18","Wafat Yesus Kristus","ID",2003 +"2003-05-13","Maulid Nabi Muhammad* (*estimated)","ID",2003 +"2003-05-15","Hari Raya Waisak* (*estimated)","ID",2003 +"2003-05-29","Kenaikan Yesus Kristus","ID",2003 +"2003-08-17","Hari Kemerdekaan Republik Indonesia","ID",2003 +"2003-09-24","Isra' Mi'raj Nabi Muhammad","ID",2003 +"2003-11-25","Hari Raya Idul Fitri","ID",2003 +"2003-11-26","Hari kedua dari Hari Raya Idul Fitri","ID",2003 +"2003-12-25","Hari Raya Natal","ID",2003 +"2004-01-01","Tahun Baru Masehi","ID",2004 +"2004-01-22","Tahun Baru Imlek","ID",2004 +"2004-02-02","Hari Raya Idul Adha","ID",2004 +"2004-02-22","Tahun Baru Islam","ID",2004 +"2004-04-09","Wafat Yesus Kristus","ID",2004 +"2004-05-01","Maulid Nabi Muhammad* (*estimated)","ID",2004 +"2004-05-20","Kenaikan Yesus Kristus","ID",2004 +"2004-06-02","Hari Raya Waisak* (*estimated)","ID",2004 +"2004-08-17","Hari Kemerdekaan Republik Indonesia","ID",2004 +"2004-09-12","Isra' Mi'raj Nabi Muhammad","ID",2004 +"2004-11-14","Hari Raya Idul Fitri","ID",2004 +"2004-11-15","Hari kedua dari Hari Raya Idul Fitri","ID",2004 +"2004-12-25","Hari Raya Natal","ID",2004 +"2005-01-01","Tahun Baru Masehi","ID",2005 +"2005-01-21","Hari Raya Idul Adha","ID",2005 +"2005-02-09","Tahun Baru Imlek","ID",2005 +"2005-02-10","Tahun Baru Islam","ID",2005 +"2005-03-25","Wafat Yesus Kristus","ID",2005 +"2005-04-21","Maulid Nabi Muhammad* (*estimated)","ID",2005 +"2005-05-05","Kenaikan Yesus Kristus","ID",2005 +"2005-05-22","Hari Raya Waisak* (*estimated)","ID",2005 +"2005-08-17","Hari Kemerdekaan Republik Indonesia","ID",2005 +"2005-09-01","Isra' Mi'raj Nabi Muhammad","ID",2005 +"2005-11-03","Hari Raya Idul Fitri","ID",2005 +"2005-11-04","Hari kedua dari Hari Raya Idul Fitri","ID",2005 +"2005-12-25","Hari Raya Natal","ID",2005 +"2006-01-01","Tahun Baru Masehi","ID",2006 +"2006-01-10","Hari Raya Idul Adha","ID",2006 +"2006-01-29","Tahun Baru Imlek","ID",2006 +"2006-01-31","Tahun Baru Islam","ID",2006 +"2006-04-10","Maulid Nabi Muhammad","ID",2006 +"2006-04-14","Wafat Yesus Kristus","ID",2006 +"2006-05-12","Hari Raya Waisak* (*estimated)","ID",2006 +"2006-05-25","Kenaikan Yesus Kristus","ID",2006 +"2006-08-17","Hari Kemerdekaan Republik Indonesia","ID",2006 +"2006-08-22","Isra' Mi'raj Nabi Muhammad","ID",2006 +"2006-10-24","Hari Raya Idul Fitri","ID",2006 +"2006-10-25","Hari kedua dari Hari Raya Idul Fitri","ID",2006 +"2006-12-25","Hari Raya Natal","ID",2006 +"2006-12-31","Hari Raya Idul Adha","ID",2006 +"2007-01-01","Tahun Baru Masehi","ID",2007 +"2007-01-20","Tahun Baru Islam","ID",2007 +"2007-02-18","Tahun Baru Imlek","ID",2007 +"2007-03-31","Maulid Nabi Muhammad","ID",2007 +"2007-04-06","Wafat Yesus Kristus","ID",2007 +"2007-05-17","Kenaikan Yesus Kristus","ID",2007 +"2007-06-01","Hari Raya Waisak","ID",2007 +"2007-08-11","Isra' Mi'raj Nabi Muhammad","ID",2007 +"2007-08-17","Hari Kemerdekaan Republik Indonesia","ID",2007 +"2007-10-13","Hari Raya Idul Fitri","ID",2007 +"2007-10-14","Hari kedua dari Hari Raya Idul Fitri","ID",2007 +"2007-12-20","Hari Raya Idul Adha","ID",2007 +"2007-12-25","Hari Raya Natal","ID",2007 +"2008-01-01","Tahun Baru Masehi","ID",2008 +"2008-01-10","Tahun Baru Islam","ID",2008 +"2008-02-07","Tahun Baru Imlek","ID",2008 +"2008-03-20","Maulid Nabi Muhammad","ID",2008 +"2008-03-21","Wafat Yesus Kristus","ID",2008 +"2008-05-01","Kenaikan Yesus Kristus","ID",2008 +"2008-05-20","Hari Raya Waisak","ID",2008 +"2008-07-31","Isra' Mi'raj Nabi Muhammad","ID",2008 +"2008-08-17","Hari Kemerdekaan Republik Indonesia","ID",2008 +"2008-10-01","Hari Raya Idul Fitri","ID",2008 +"2008-10-02","Hari kedua dari Hari Raya Idul Fitri","ID",2008 +"2008-12-08","Hari Raya Idul Adha","ID",2008 +"2008-12-25","Hari Raya Natal","ID",2008 +"2008-12-29","Tahun Baru Islam","ID",2008 +"2009-01-01","Tahun Baru Masehi","ID",2009 +"2009-01-26","Tahun Baru Imlek","ID",2009 +"2009-03-09","Maulid Nabi Muhammad","ID",2009 +"2009-03-26","Hari Suci Nyepi","ID",2009 +"2009-04-10","Wafat Yesus Kristus","ID",2009 +"2009-05-09","Hari Raya Waisak","ID",2009 +"2009-05-21","Kenaikan Yesus Kristus","ID",2009 +"2009-07-20","Isra' Mi'raj Nabi Muhammad","ID",2009 +"2009-08-17","Hari Kemerdekaan Republik Indonesia","ID",2009 +"2009-09-20","Hari Raya Idul Fitri","ID",2009 +"2009-09-21","Hari kedua dari Hari Raya Idul Fitri","ID",2009 +"2009-11-27","Hari Raya Idul Adha","ID",2009 +"2009-12-18","Tahun Baru Islam","ID",2009 +"2009-12-25","Hari Raya Natal","ID",2009 +"2010-01-01","Tahun Baru Masehi","ID",2010 +"2010-02-14","Tahun Baru Imlek","ID",2010 +"2010-02-26","Maulid Nabi Muhammad","ID",2010 +"2010-03-16","Hari Suci Nyepi","ID",2010 +"2010-04-02","Wafat Yesus Kristus","ID",2010 +"2010-05-13","Kenaikan Yesus Kristus","ID",2010 +"2010-05-28","Hari Raya Waisak","ID",2010 +"2010-07-09","Isra' Mi'raj Nabi Muhammad","ID",2010 +"2010-08-17","Hari Kemerdekaan Republik Indonesia","ID",2010 +"2010-09-10","Hari Raya Idul Fitri","ID",2010 +"2010-09-11","Hari kedua dari Hari Raya Idul Fitri","ID",2010 +"2010-11-17","Hari Raya Idul Adha","ID",2010 +"2010-12-07","Tahun Baru Islam","ID",2010 +"2010-12-25","Hari Raya Natal","ID",2010 +"2011-01-01","Tahun Baru Masehi","ID",2011 +"2011-02-03","Tahun Baru Imlek","ID",2011 +"2011-02-15","Maulid Nabi Muhammad","ID",2011 +"2011-03-05","Hari Suci Nyepi","ID",2011 +"2011-04-22","Wafat Yesus Kristus","ID",2011 +"2011-05-17","Hari Raya Waisak","ID",2011 +"2011-06-02","Kenaikan Yesus Kristus","ID",2011 +"2011-06-29","Isra' Mi'raj Nabi Muhammad","ID",2011 +"2011-08-17","Hari Kemerdekaan Republik Indonesia","ID",2011 +"2011-08-30","Hari Raya Idul Fitri","ID",2011 +"2011-08-31","Hari kedua dari Hari Raya Idul Fitri","ID",2011 +"2011-11-06","Hari Raya Idul Adha","ID",2011 +"2011-11-27","Tahun Baru Islam","ID",2011 +"2011-12-25","Hari Raya Natal","ID",2011 +"2012-01-01","Tahun Baru Masehi","ID",2012 +"2012-01-23","Tahun Baru Imlek","ID",2012 +"2012-02-05","Maulid Nabi Muhammad","ID",2012 +"2012-03-23","Hari Suci Nyepi","ID",2012 +"2012-04-06","Wafat Yesus Kristus","ID",2012 +"2012-05-06","Hari Raya Waisak","ID",2012 +"2012-05-17","Kenaikan Yesus Kristus","ID",2012 +"2012-06-17","Isra' Mi'raj Nabi Muhammad","ID",2012 +"2012-08-17","Hari Kemerdekaan Republik Indonesia","ID",2012 +"2012-08-19","Hari Raya Idul Fitri","ID",2012 +"2012-08-20","Hari kedua dari Hari Raya Idul Fitri","ID",2012 +"2012-10-26","Hari Raya Idul Adha","ID",2012 +"2012-11-15","Tahun Baru Islam","ID",2012 +"2012-12-25","Hari Raya Natal","ID",2012 +"2013-01-01","Tahun Baru Masehi","ID",2013 +"2013-01-24","Maulid Nabi Muhammad","ID",2013 +"2013-02-10","Tahun Baru Imlek","ID",2013 +"2013-03-12","Hari Suci Nyepi","ID",2013 +"2013-03-29","Wafat Yesus Kristus","ID",2013 +"2013-05-09","Kenaikan Yesus Kristus","ID",2013 +"2013-05-25","Hari Raya Waisak","ID",2013 +"2013-06-06","Isra' Mi'raj Nabi Muhammad","ID",2013 +"2013-08-08","Hari Raya Idul Fitri","ID",2013 +"2013-08-09","Hari kedua dari Hari Raya Idul Fitri","ID",2013 +"2013-08-17","Hari Kemerdekaan Republik Indonesia","ID",2013 +"2013-10-15","Hari Raya Idul Adha","ID",2013 +"2013-11-05","Tahun Baru Islam","ID",2013 +"2013-12-25","Hari Raya Natal","ID",2013 +"2014-01-01","Tahun Baru Masehi","ID",2014 +"2014-01-14","Maulid Nabi Muhammad","ID",2014 +"2014-01-31","Tahun Baru Imlek","ID",2014 +"2014-03-31","Hari Suci Nyepi","ID",2014 +"2014-04-18","Wafat Yesus Kristus","ID",2014 +"2014-05-01","Hari Buruh Internasional","ID",2014 +"2014-05-15","Hari Raya Waisak","ID",2014 +"2014-05-27","Isra' Mi'raj Nabi Muhammad","ID",2014 +"2014-05-29","Kenaikan Yesus Kristus","ID",2014 +"2014-07-28","Hari Raya Idul Fitri","ID",2014 +"2014-07-29","Hari kedua dari Hari Raya Idul Fitri","ID",2014 +"2014-08-17","Hari Kemerdekaan Republik Indonesia","ID",2014 +"2014-10-05","Hari Raya Idul Adha","ID",2014 +"2014-10-25","Tahun Baru Islam","ID",2014 +"2014-12-25","Hari Raya Natal","ID",2014 +"2015-01-01","Tahun Baru Masehi","ID",2015 +"2015-01-03","Maulid Nabi Muhammad","ID",2015 +"2015-02-19","Tahun Baru Imlek","ID",2015 +"2015-03-21","Hari Suci Nyepi","ID",2015 +"2015-04-03","Wafat Yesus Kristus","ID",2015 +"2015-05-01","Hari Buruh Internasional","ID",2015 +"2015-05-14","Kenaikan Yesus Kristus","ID",2015 +"2015-05-16","Isra' Mi'raj Nabi Muhammad","ID",2015 +"2015-06-02","Hari Raya Waisak","ID",2015 +"2015-07-17","Hari Raya Idul Fitri","ID",2015 +"2015-07-18","Hari kedua dari Hari Raya Idul Fitri","ID",2015 +"2015-08-17","Hari Kemerdekaan Republik Indonesia","ID",2015 +"2015-09-24","Hari Raya Idul Adha","ID",2015 +"2015-10-14","Tahun Baru Islam","ID",2015 +"2015-12-24","Maulid Nabi Muhammad","ID",2015 +"2015-12-25","Hari Raya Natal","ID",2015 +"2016-01-01","Tahun Baru Masehi","ID",2016 +"2016-02-08","Tahun Baru Imlek","ID",2016 +"2016-03-09","Hari Suci Nyepi","ID",2016 +"2016-03-25","Wafat Yesus Kristus","ID",2016 +"2016-05-01","Hari Buruh Internasional","ID",2016 +"2016-05-05","Kenaikan Yesus Kristus","ID",2016 +"2016-05-06","Isra' Mi'raj Nabi Muhammad","ID",2016 +"2016-05-22","Hari Raya Waisak","ID",2016 +"2016-07-06","Hari Raya Idul Fitri","ID",2016 +"2016-07-07","Hari kedua dari Hari Raya Idul Fitri","ID",2016 +"2016-08-17","Hari Kemerdekaan Republik Indonesia","ID",2016 +"2016-09-12","Hari Raya Idul Adha","ID",2016 +"2016-10-02","Tahun Baru Islam","ID",2016 +"2016-12-12","Maulid Nabi Muhammad","ID",2016 +"2016-12-25","Hari Raya Natal","ID",2016 +"2017-01-01","Tahun Baru Masehi","ID",2017 +"2017-01-28","Tahun Baru Imlek","ID",2017 +"2017-03-28","Hari Suci Nyepi","ID",2017 +"2017-04-14","Wafat Yesus Kristus","ID",2017 +"2017-04-24","Isra' Mi'raj Nabi Muhammad","ID",2017 +"2017-05-01","Hari Buruh Internasional","ID",2017 +"2017-05-11","Hari Raya Waisak","ID",2017 +"2017-05-25","Kenaikan Yesus Kristus","ID",2017 +"2017-06-01","Hari Lahir Pancasila","ID",2017 +"2017-06-25","Hari Raya Idul Fitri","ID",2017 +"2017-06-26","Hari kedua dari Hari Raya Idul Fitri","ID",2017 +"2017-08-17","Hari Kemerdekaan Republik Indonesia","ID",2017 +"2017-09-01","Hari Raya Idul Adha","ID",2017 +"2017-09-21","Tahun Baru Islam","ID",2017 +"2017-12-01","Maulid Nabi Muhammad","ID",2017 +"2017-12-25","Hari Raya Natal","ID",2017 +"2018-01-01","Tahun Baru Masehi","ID",2018 +"2018-02-16","Tahun Baru Imlek","ID",2018 +"2018-03-17","Hari Suci Nyepi","ID",2018 +"2018-03-30","Wafat Yesus Kristus","ID",2018 +"2018-04-14","Isra' Mi'raj Nabi Muhammad","ID",2018 +"2018-05-01","Hari Buruh Internasional","ID",2018 +"2018-05-10","Kenaikan Yesus Kristus","ID",2018 +"2018-05-29","Hari Raya Waisak","ID",2018 +"2018-06-01","Hari Lahir Pancasila","ID",2018 +"2018-06-15","Hari Raya Idul Fitri","ID",2018 +"2018-06-16","Hari kedua dari Hari Raya Idul Fitri","ID",2018 +"2018-06-27","Hari Pemilihan","ID",2018 +"2018-08-17","Hari Kemerdekaan Republik Indonesia","ID",2018 +"2018-08-22","Hari Raya Idul Adha","ID",2018 +"2018-09-11","Tahun Baru Islam","ID",2018 +"2018-11-20","Maulid Nabi Muhammad","ID",2018 +"2018-12-25","Hari Raya Natal","ID",2018 +"2019-01-01","Tahun Baru Masehi","ID",2019 +"2019-02-05","Tahun Baru Imlek","ID",2019 +"2019-03-07","Hari Suci Nyepi","ID",2019 +"2019-04-03","Isra' Mi'raj Nabi Muhammad","ID",2019 +"2019-04-17","Hari Pemilihan","ID",2019 +"2019-04-19","Wafat Yesus Kristus","ID",2019 +"2019-05-01","Hari Buruh Internasional","ID",2019 +"2019-05-19","Hari Raya Waisak","ID",2019 +"2019-05-30","Kenaikan Yesus Kristus","ID",2019 +"2019-06-01","Hari Lahir Pancasila","ID",2019 +"2019-06-05","Hari Raya Idul Fitri","ID",2019 +"2019-06-06","Hari kedua dari Hari Raya Idul Fitri","ID",2019 +"2019-08-11","Hari Raya Idul Adha","ID",2019 +"2019-08-17","Hari Kemerdekaan Republik Indonesia","ID",2019 +"2019-09-01","Tahun Baru Islam","ID",2019 +"2019-11-09","Maulid Nabi Muhammad","ID",2019 +"2019-12-25","Hari Raya Natal","ID",2019 +"2020-01-01","Tahun Baru Masehi","ID",2020 +"2020-01-25","Tahun Baru Imlek","ID",2020 +"2020-03-22","Isra' Mi'raj Nabi Muhammad","ID",2020 +"2020-03-25","Hari Suci Nyepi","ID",2020 +"2020-04-10","Wafat Yesus Kristus","ID",2020 +"2020-05-01","Hari Buruh Internasional","ID",2020 +"2020-05-07","Hari Raya Waisak","ID",2020 +"2020-05-21","Kenaikan Yesus Kristus","ID",2020 +"2020-05-24","Hari Raya Idul Fitri","ID",2020 +"2020-05-25","Hari kedua dari Hari Raya Idul Fitri","ID",2020 +"2020-06-01","Hari Lahir Pancasila","ID",2020 +"2020-07-31","Hari Raya Idul Adha","ID",2020 +"2020-08-17","Hari Kemerdekaan Republik Indonesia","ID",2020 +"2020-08-20","Tahun Baru Islam","ID",2020 +"2020-10-29","Maulid Nabi Muhammad","ID",2020 +"2020-12-09","Hari Pemilihan","ID",2020 +"2020-12-25","Hari Raya Natal","ID",2020 +"2021-01-01","Tahun Baru Masehi","ID",2021 +"2021-02-12","Tahun Baru Imlek","ID",2021 +"2021-03-11","Isra' Mi'raj Nabi Muhammad","ID",2021 +"2021-03-14","Hari Suci Nyepi","ID",2021 +"2021-04-02","Wafat Yesus Kristus","ID",2021 +"2021-05-01","Hari Buruh Internasional","ID",2021 +"2021-05-13","Hari Raya Idul Fitri","ID",2021 +"2021-05-13","Kenaikan Yesus Kristus","ID",2021 +"2021-05-14","Hari kedua dari Hari Raya Idul Fitri","ID",2021 +"2021-05-26","Hari Raya Waisak","ID",2021 +"2021-06-01","Hari Lahir Pancasila","ID",2021 +"2021-07-20","Hari Raya Idul Adha","ID",2021 +"2021-08-11","Tahun Baru Islam","ID",2021 +"2021-08-17","Hari Kemerdekaan Republik Indonesia","ID",2021 +"2021-10-19","Maulid Nabi Muhammad","ID",2021 +"2021-12-25","Hari Raya Natal","ID",2021 +"2022-01-01","Tahun Baru Masehi","ID",2022 +"2022-02-01","Tahun Baru Imlek","ID",2022 +"2022-02-28","Isra' Mi'raj Nabi Muhammad","ID",2022 +"2022-03-03","Hari Suci Nyepi","ID",2022 +"2022-04-15","Wafat Yesus Kristus","ID",2022 +"2022-05-01","Hari Buruh Internasional","ID",2022 +"2022-05-02","Hari Raya Idul Fitri","ID",2022 +"2022-05-03","Hari kedua dari Hari Raya Idul Fitri","ID",2022 +"2022-05-16","Hari Raya Waisak","ID",2022 +"2022-05-26","Kenaikan Yesus Kristus","ID",2022 +"2022-06-01","Hari Lahir Pancasila","ID",2022 +"2022-07-10","Hari Raya Idul Adha","ID",2022 +"2022-07-30","Tahun Baru Islam","ID",2022 +"2022-08-17","Hari Kemerdekaan Republik Indonesia","ID",2022 +"2022-10-08","Maulid Nabi Muhammad","ID",2022 +"2022-12-25","Hari Raya Natal","ID",2022 +"2023-01-01","Tahun Baru Masehi","ID",2023 +"2023-01-22","Tahun Baru Imlek","ID",2023 +"2023-02-18","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2023 +"2023-03-22","Hari Suci Nyepi","ID",2023 +"2023-04-07","Wafat Yesus Kristus","ID",2023 +"2023-04-22","Hari Raya Idul Fitri","ID",2023 +"2023-04-23","Hari kedua dari Hari Raya Idul Fitri","ID",2023 +"2023-05-01","Hari Buruh Internasional","ID",2023 +"2023-05-18","Kenaikan Yesus Kristus","ID",2023 +"2023-06-01","Hari Lahir Pancasila","ID",2023 +"2023-06-04","Hari Raya Waisak","ID",2023 +"2023-06-29","Hari Raya Idul Adha","ID",2023 +"2023-07-19","Tahun Baru Islam* (*estimated)","ID",2023 +"2023-08-17","Hari Kemerdekaan Republik Indonesia","ID",2023 +"2023-09-27","Maulid Nabi Muhammad* (*estimated)","ID",2023 +"2023-12-25","Hari Raya Natal","ID",2023 +"2024-01-01","Tahun Baru Masehi","ID",2024 +"2024-02-08","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2024 +"2024-02-10","Tahun Baru Imlek","ID",2024 +"2024-03-11","Hari Suci Nyepi","ID",2024 +"2024-03-29","Wafat Yesus Kristus","ID",2024 +"2024-04-10","Hari Raya Idul Fitri* (*estimated)","ID",2024 +"2024-04-11","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2024 +"2024-05-01","Hari Buruh Internasional","ID",2024 +"2024-05-09","Kenaikan Yesus Kristus","ID",2024 +"2024-05-22","Hari Raya Waisak* (*estimated)","ID",2024 +"2024-06-01","Hari Lahir Pancasila","ID",2024 +"2024-06-16","Hari Raya Idul Adha* (*estimated)","ID",2024 +"2024-07-07","Tahun Baru Islam* (*estimated)","ID",2024 +"2024-08-17","Hari Kemerdekaan Republik Indonesia","ID",2024 +"2024-09-15","Maulid Nabi Muhammad* (*estimated)","ID",2024 +"2024-12-25","Hari Raya Natal","ID",2024 +"2025-01-01","Tahun Baru Masehi","ID",2025 +"2025-01-27","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2025 +"2025-01-29","Tahun Baru Imlek","ID",2025 +"2025-03-29","Hari Suci Nyepi","ID",2025 +"2025-03-30","Hari Raya Idul Fitri* (*estimated)","ID",2025 +"2025-03-31","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2025 +"2025-04-18","Wafat Yesus Kristus","ID",2025 +"2025-05-01","Hari Buruh Internasional","ID",2025 +"2025-05-11","Hari Raya Waisak* (*estimated)","ID",2025 +"2025-05-29","Kenaikan Yesus Kristus","ID",2025 +"2025-06-01","Hari Lahir Pancasila","ID",2025 +"2025-06-06","Hari Raya Idul Adha* (*estimated)","ID",2025 +"2025-06-26","Tahun Baru Islam* (*estimated)","ID",2025 +"2025-08-17","Hari Kemerdekaan Republik Indonesia","ID",2025 +"2025-09-04","Maulid Nabi Muhammad* (*estimated)","ID",2025 +"2025-12-25","Hari Raya Natal","ID",2025 +"2026-01-01","Tahun Baru Masehi","ID",2026 +"2026-01-16","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2026 +"2026-02-17","Tahun Baru Imlek","ID",2026 +"2026-03-19","Hari Suci Nyepi","ID",2026 +"2026-03-20","Hari Raya Idul Fitri* (*estimated)","ID",2026 +"2026-03-21","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2026 +"2026-04-03","Wafat Yesus Kristus","ID",2026 +"2026-05-01","Hari Buruh Internasional","ID",2026 +"2026-05-14","Kenaikan Yesus Kristus","ID",2026 +"2026-05-27","Hari Raya Idul Adha* (*estimated)","ID",2026 +"2026-05-31","Hari Raya Waisak* (*estimated)","ID",2026 +"2026-06-01","Hari Lahir Pancasila","ID",2026 +"2026-06-16","Tahun Baru Islam* (*estimated)","ID",2026 +"2026-08-17","Hari Kemerdekaan Republik Indonesia","ID",2026 +"2026-08-25","Maulid Nabi Muhammad* (*estimated)","ID",2026 +"2026-12-25","Hari Raya Natal","ID",2026 +"2027-01-01","Tahun Baru Masehi","ID",2027 +"2027-01-05","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2027 +"2027-02-06","Tahun Baru Imlek","ID",2027 +"2027-03-09","Hari Raya Idul Fitri* (*estimated)","ID",2027 +"2027-03-10","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2027 +"2027-03-26","Wafat Yesus Kristus","ID",2027 +"2027-05-01","Hari Buruh Internasional","ID",2027 +"2027-05-06","Kenaikan Yesus Kristus","ID",2027 +"2027-05-16","Hari Raya Idul Adha* (*estimated)","ID",2027 +"2027-05-20","Hari Raya Waisak* (*estimated)","ID",2027 +"2027-06-01","Hari Lahir Pancasila","ID",2027 +"2027-06-06","Tahun Baru Islam* (*estimated)","ID",2027 +"2027-08-14","Maulid Nabi Muhammad* (*estimated)","ID",2027 +"2027-08-17","Hari Kemerdekaan Republik Indonesia","ID",2027 +"2027-12-25","Hari Raya Natal","ID",2027 +"2027-12-25","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2027 +"2028-01-01","Tahun Baru Masehi","ID",2028 +"2028-01-26","Tahun Baru Imlek","ID",2028 +"2028-02-26","Hari Raya Idul Fitri* (*estimated)","ID",2028 +"2028-02-27","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2028 +"2028-04-14","Wafat Yesus Kristus","ID",2028 +"2028-05-01","Hari Buruh Internasional","ID",2028 +"2028-05-05","Hari Raya Idul Adha* (*estimated)","ID",2028 +"2028-05-09","Hari Raya Waisak* (*estimated)","ID",2028 +"2028-05-25","Kenaikan Yesus Kristus","ID",2028 +"2028-05-25","Tahun Baru Islam* (*estimated)","ID",2028 +"2028-06-01","Hari Lahir Pancasila","ID",2028 +"2028-08-03","Maulid Nabi Muhammad* (*estimated)","ID",2028 +"2028-08-17","Hari Kemerdekaan Republik Indonesia","ID",2028 +"2028-12-14","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2028 +"2028-12-25","Hari Raya Natal","ID",2028 +"2029-01-01","Tahun Baru Masehi","ID",2029 +"2029-02-13","Tahun Baru Imlek","ID",2029 +"2029-02-14","Hari Raya Idul Fitri* (*estimated)","ID",2029 +"2029-02-15","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2029 +"2029-03-30","Wafat Yesus Kristus","ID",2029 +"2029-04-24","Hari Raya Idul Adha* (*estimated)","ID",2029 +"2029-05-01","Hari Buruh Internasional","ID",2029 +"2029-05-10","Kenaikan Yesus Kristus","ID",2029 +"2029-05-14","Tahun Baru Islam* (*estimated)","ID",2029 +"2029-05-27","Hari Raya Waisak* (*estimated)","ID",2029 +"2029-06-01","Hari Lahir Pancasila","ID",2029 +"2029-07-24","Maulid Nabi Muhammad* (*estimated)","ID",2029 +"2029-08-17","Hari Kemerdekaan Republik Indonesia","ID",2029 +"2029-12-03","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2029 +"2029-12-25","Hari Raya Natal","ID",2029 +"2030-01-01","Tahun Baru Masehi","ID",2030 +"2030-02-03","Tahun Baru Imlek","ID",2030 +"2030-02-04","Hari Raya Idul Fitri* (*estimated)","ID",2030 +"2030-02-05","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2030 +"2030-04-13","Hari Raya Idul Adha* (*estimated)","ID",2030 +"2030-04-19","Wafat Yesus Kristus","ID",2030 +"2030-05-01","Hari Buruh Internasional","ID",2030 +"2030-05-03","Tahun Baru Islam* (*estimated)","ID",2030 +"2030-05-16","Hari Raya Waisak* (*estimated)","ID",2030 +"2030-05-30","Kenaikan Yesus Kristus","ID",2030 +"2030-06-01","Hari Lahir Pancasila","ID",2030 +"2030-07-13","Maulid Nabi Muhammad* (*estimated)","ID",2030 +"2030-08-17","Hari Kemerdekaan Republik Indonesia","ID",2030 +"2030-11-23","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2030 +"2030-12-25","Hari Raya Natal","ID",2030 +"2031-01-01","Tahun Baru Masehi","ID",2031 +"2031-01-23","Tahun Baru Imlek","ID",2031 +"2031-01-24","Hari Raya Idul Fitri* (*estimated)","ID",2031 +"2031-01-25","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2031 +"2031-04-02","Hari Raya Idul Adha* (*estimated)","ID",2031 +"2031-04-11","Wafat Yesus Kristus","ID",2031 +"2031-04-23","Tahun Baru Islam* (*estimated)","ID",2031 +"2031-05-01","Hari Buruh Internasional","ID",2031 +"2031-05-22","Kenaikan Yesus Kristus","ID",2031 +"2031-06-01","Hari Lahir Pancasila","ID",2031 +"2031-06-04","Hari Raya Waisak* (*estimated)","ID",2031 +"2031-07-02","Maulid Nabi Muhammad* (*estimated)","ID",2031 +"2031-08-17","Hari Kemerdekaan Republik Indonesia","ID",2031 +"2031-11-12","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2031 +"2031-12-25","Hari Raya Natal","ID",2031 +"2032-01-01","Tahun Baru Masehi","ID",2032 +"2032-01-14","Hari Raya Idul Fitri* (*estimated)","ID",2032 +"2032-01-15","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2032 +"2032-02-11","Tahun Baru Imlek","ID",2032 +"2032-03-22","Hari Raya Idul Adha* (*estimated)","ID",2032 +"2032-03-26","Wafat Yesus Kristus","ID",2032 +"2032-04-11","Tahun Baru Islam* (*estimated)","ID",2032 +"2032-05-01","Hari Buruh Internasional","ID",2032 +"2032-05-06","Kenaikan Yesus Kristus","ID",2032 +"2032-05-23","Hari Raya Waisak* (*estimated)","ID",2032 +"2032-06-01","Hari Lahir Pancasila","ID",2032 +"2032-06-20","Maulid Nabi Muhammad* (*estimated)","ID",2032 +"2032-08-17","Hari Kemerdekaan Republik Indonesia","ID",2032 +"2032-11-01","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2032 +"2032-12-25","Hari Raya Natal","ID",2032 +"2033-01-01","Tahun Baru Masehi","ID",2033 +"2033-01-02","Hari Raya Idul Fitri* (*estimated)","ID",2033 +"2033-01-03","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2033 +"2033-01-31","Tahun Baru Imlek","ID",2033 +"2033-03-11","Hari Raya Idul Adha* (*estimated)","ID",2033 +"2033-04-01","Tahun Baru Islam* (*estimated)","ID",2033 +"2033-04-15","Wafat Yesus Kristus","ID",2033 +"2033-05-01","Hari Buruh Internasional","ID",2033 +"2033-05-13","Hari Raya Waisak* (*estimated)","ID",2033 +"2033-05-26","Kenaikan Yesus Kristus","ID",2033 +"2033-06-01","Hari Lahir Pancasila","ID",2033 +"2033-06-09","Maulid Nabi Muhammad* (*estimated)","ID",2033 +"2033-08-17","Hari Kemerdekaan Republik Indonesia","ID",2033 +"2033-10-21","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2033 +"2033-12-23","Hari Raya Idul Fitri* (*estimated)","ID",2033 +"2033-12-24","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2033 +"2033-12-25","Hari Raya Natal","ID",2033 +"2034-01-01","Tahun Baru Masehi","ID",2034 +"2034-02-19","Tahun Baru Imlek","ID",2034 +"2034-03-01","Hari Raya Idul Adha* (*estimated)","ID",2034 +"2034-03-21","Tahun Baru Islam* (*estimated)","ID",2034 +"2034-04-07","Wafat Yesus Kristus","ID",2034 +"2034-05-01","Hari Buruh Internasional","ID",2034 +"2034-05-18","Kenaikan Yesus Kristus","ID",2034 +"2034-05-30","Maulid Nabi Muhammad* (*estimated)","ID",2034 +"2034-06-01","Hari Lahir Pancasila","ID",2034 +"2034-06-01","Hari Raya Waisak* (*estimated)","ID",2034 +"2034-08-17","Hari Kemerdekaan Republik Indonesia","ID",2034 +"2034-10-10","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2034 +"2034-12-12","Hari Raya Idul Fitri* (*estimated)","ID",2034 +"2034-12-13","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2034 +"2034-12-25","Hari Raya Natal","ID",2034 +"2035-01-01","Tahun Baru Masehi","ID",2035 +"2035-02-08","Tahun Baru Imlek","ID",2035 +"2035-02-18","Hari Raya Idul Adha* (*estimated)","ID",2035 +"2035-03-11","Tahun Baru Islam* (*estimated)","ID",2035 +"2035-03-23","Wafat Yesus Kristus","ID",2035 +"2035-05-01","Hari Buruh Internasional","ID",2035 +"2035-05-03","Kenaikan Yesus Kristus","ID",2035 +"2035-05-20","Maulid Nabi Muhammad* (*estimated)","ID",2035 +"2035-05-22","Hari Raya Waisak* (*estimated)","ID",2035 +"2035-06-01","Hari Lahir Pancasila","ID",2035 +"2035-08-17","Hari Kemerdekaan Republik Indonesia","ID",2035 +"2035-09-29","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2035 +"2035-12-01","Hari Raya Idul Fitri* (*estimated)","ID",2035 +"2035-12-02","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2035 +"2035-12-25","Hari Raya Natal","ID",2035 +"2036-01-01","Tahun Baru Masehi","ID",2036 +"2036-01-28","Tahun Baru Imlek","ID",2036 +"2036-02-07","Hari Raya Idul Adha* (*estimated)","ID",2036 +"2036-02-28","Tahun Baru Islam* (*estimated)","ID",2036 +"2036-04-11","Wafat Yesus Kristus","ID",2036 +"2036-05-01","Hari Buruh Internasional","ID",2036 +"2036-05-08","Maulid Nabi Muhammad* (*estimated)","ID",2036 +"2036-05-10","Hari Raya Waisak* (*estimated)","ID",2036 +"2036-05-22","Kenaikan Yesus Kristus","ID",2036 +"2036-06-01","Hari Lahir Pancasila","ID",2036 +"2036-08-17","Hari Kemerdekaan Republik Indonesia","ID",2036 +"2036-09-18","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2036 +"2036-11-19","Hari Raya Idul Fitri* (*estimated)","ID",2036 +"2036-11-20","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2036 +"2036-12-25","Hari Raya Natal","ID",2036 +"2037-01-01","Tahun Baru Masehi","ID",2037 +"2037-01-26","Hari Raya Idul Adha* (*estimated)","ID",2037 +"2037-02-15","Tahun Baru Imlek","ID",2037 +"2037-02-16","Tahun Baru Islam* (*estimated)","ID",2037 +"2037-04-03","Wafat Yesus Kristus","ID",2037 +"2037-04-28","Maulid Nabi Muhammad* (*estimated)","ID",2037 +"2037-05-01","Hari Buruh Internasional","ID",2037 +"2037-05-14","Kenaikan Yesus Kristus","ID",2037 +"2037-05-29","Hari Raya Waisak* (*estimated)","ID",2037 +"2037-06-01","Hari Lahir Pancasila","ID",2037 +"2037-08-17","Hari Kemerdekaan Republik Indonesia","ID",2037 +"2037-09-07","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2037 +"2037-11-08","Hari Raya Idul Fitri* (*estimated)","ID",2037 +"2037-11-09","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2037 +"2037-12-25","Hari Raya Natal","ID",2037 +"2038-01-01","Tahun Baru Masehi","ID",2038 +"2038-01-16","Hari Raya Idul Adha* (*estimated)","ID",2038 +"2038-02-04","Tahun Baru Imlek","ID",2038 +"2038-02-05","Tahun Baru Islam* (*estimated)","ID",2038 +"2038-04-17","Maulid Nabi Muhammad* (*estimated)","ID",2038 +"2038-04-23","Wafat Yesus Kristus","ID",2038 +"2038-05-01","Hari Buruh Internasional","ID",2038 +"2038-05-18","Hari Raya Waisak* (*estimated)","ID",2038 +"2038-06-01","Hari Lahir Pancasila","ID",2038 +"2038-06-03","Kenaikan Yesus Kristus","ID",2038 +"2038-08-17","Hari Kemerdekaan Republik Indonesia","ID",2038 +"2038-08-28","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2038 +"2038-10-29","Hari Raya Idul Fitri* (*estimated)","ID",2038 +"2038-10-30","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2038 +"2038-12-25","Hari Raya Natal","ID",2038 +"2039-01-01","Tahun Baru Masehi","ID",2039 +"2039-01-05","Hari Raya Idul Adha* (*estimated)","ID",2039 +"2039-01-24","Tahun Baru Imlek","ID",2039 +"2039-01-26","Tahun Baru Islam* (*estimated)","ID",2039 +"2039-04-06","Maulid Nabi Muhammad* (*estimated)","ID",2039 +"2039-04-08","Wafat Yesus Kristus","ID",2039 +"2039-05-01","Hari Buruh Internasional","ID",2039 +"2039-05-07","Hari Raya Waisak* (*estimated)","ID",2039 +"2039-05-19","Kenaikan Yesus Kristus","ID",2039 +"2039-06-01","Hari Lahir Pancasila","ID",2039 +"2039-08-17","Hari Kemerdekaan Republik Indonesia","ID",2039 +"2039-08-17","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2039 +"2039-10-19","Hari Raya Idul Fitri* (*estimated)","ID",2039 +"2039-10-20","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2039 +"2039-12-25","Hari Raya Natal","ID",2039 +"2039-12-26","Hari Raya Idul Adha* (*estimated)","ID",2039 +"2040-01-01","Tahun Baru Masehi","ID",2040 +"2040-01-15","Tahun Baru Islam* (*estimated)","ID",2040 +"2040-02-12","Tahun Baru Imlek","ID",2040 +"2040-03-25","Maulid Nabi Muhammad* (*estimated)","ID",2040 +"2040-03-30","Wafat Yesus Kristus","ID",2040 +"2040-05-01","Hari Buruh Internasional","ID",2040 +"2040-05-10","Kenaikan Yesus Kristus","ID",2040 +"2040-05-25","Hari Raya Waisak* (*estimated)","ID",2040 +"2040-06-01","Hari Lahir Pancasila","ID",2040 +"2040-08-05","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2040 +"2040-08-17","Hari Kemerdekaan Republik Indonesia","ID",2040 +"2040-10-07","Hari Raya Idul Fitri* (*estimated)","ID",2040 +"2040-10-08","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2040 +"2040-12-14","Hari Raya Idul Adha* (*estimated)","ID",2040 +"2040-12-25","Hari Raya Natal","ID",2040 +"2041-01-01","Tahun Baru Masehi","ID",2041 +"2041-01-04","Tahun Baru Islam* (*estimated)","ID",2041 +"2041-02-01","Tahun Baru Imlek","ID",2041 +"2041-03-15","Maulid Nabi Muhammad* (*estimated)","ID",2041 +"2041-04-19","Wafat Yesus Kristus","ID",2041 +"2041-05-01","Hari Buruh Internasional","ID",2041 +"2041-05-14","Hari Raya Waisak* (*estimated)","ID",2041 +"2041-05-30","Kenaikan Yesus Kristus","ID",2041 +"2041-06-01","Hari Lahir Pancasila","ID",2041 +"2041-07-25","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2041 +"2041-08-17","Hari Kemerdekaan Republik Indonesia","ID",2041 +"2041-09-26","Hari Raya Idul Fitri* (*estimated)","ID",2041 +"2041-09-27","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2041 +"2041-12-04","Hari Raya Idul Adha* (*estimated)","ID",2041 +"2041-12-24","Tahun Baru Islam* (*estimated)","ID",2041 +"2041-12-25","Hari Raya Natal","ID",2041 +"2042-01-01","Tahun Baru Masehi","ID",2042 +"2042-01-22","Tahun Baru Imlek","ID",2042 +"2042-03-04","Maulid Nabi Muhammad* (*estimated)","ID",2042 +"2042-04-04","Wafat Yesus Kristus","ID",2042 +"2042-05-01","Hari Buruh Internasional","ID",2042 +"2042-05-15","Kenaikan Yesus Kristus","ID",2042 +"2042-06-01","Hari Lahir Pancasila","ID",2042 +"2042-06-02","Hari Raya Waisak* (*estimated)","ID",2042 +"2042-07-15","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2042 +"2042-08-17","Hari Kemerdekaan Republik Indonesia","ID",2042 +"2042-09-15","Hari Raya Idul Fitri* (*estimated)","ID",2042 +"2042-09-16","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2042 +"2042-11-23","Hari Raya Idul Adha* (*estimated)","ID",2042 +"2042-12-14","Tahun Baru Islam* (*estimated)","ID",2042 +"2042-12-25","Hari Raya Natal","ID",2042 +"2043-01-01","Tahun Baru Masehi","ID",2043 +"2043-02-10","Tahun Baru Imlek","ID",2043 +"2043-02-22","Maulid Nabi Muhammad* (*estimated)","ID",2043 +"2043-03-27","Wafat Yesus Kristus","ID",2043 +"2043-05-01","Hari Buruh Internasional","ID",2043 +"2043-05-07","Kenaikan Yesus Kristus","ID",2043 +"2043-05-23","Hari Raya Waisak* (*estimated)","ID",2043 +"2043-06-01","Hari Lahir Pancasila","ID",2043 +"2043-07-04","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2043 +"2043-08-17","Hari Kemerdekaan Republik Indonesia","ID",2043 +"2043-09-04","Hari Raya Idul Fitri* (*estimated)","ID",2043 +"2043-09-05","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2043 +"2043-11-12","Hari Raya Idul Adha* (*estimated)","ID",2043 +"2043-12-03","Tahun Baru Islam* (*estimated)","ID",2043 +"2043-12-25","Hari Raya Natal","ID",2043 +"2044-01-01","Tahun Baru Masehi","ID",2044 +"2044-01-30","Tahun Baru Imlek","ID",2044 +"2044-02-11","Maulid Nabi Muhammad* (*estimated)","ID",2044 +"2044-04-15","Wafat Yesus Kristus","ID",2044 +"2044-05-01","Hari Buruh Internasional","ID",2044 +"2044-05-12","Hari Raya Waisak* (*estimated)","ID",2044 +"2044-05-26","Kenaikan Yesus Kristus","ID",2044 +"2044-06-01","Hari Lahir Pancasila","ID",2044 +"2044-06-23","Isra' Mi'raj Nabi Muhammad* (*estimated)","ID",2044 +"2044-08-17","Hari Kemerdekaan Republik Indonesia","ID",2044 +"2044-08-24","Hari Raya Idul Fitri* (*estimated)","ID",2044 +"2044-08-25","Hari kedua dari Hari Raya Idul Fitri* (*estimated)","ID",2044 +"2044-10-31","Hari Raya Idul Adha* (*estimated)","ID",2044 +"2044-11-21","Tahun Baru Islam* (*estimated)","ID",2044 +"2044-12-25","Hari Raya Natal","ID",2044 +"1995-01-01","New Year's Day","IE",1995 +"1995-03-17","St. Patrick's Day","IE",1995 +"1995-04-17","Easter Monday","IE",1995 +"1995-05-08","May Day","IE",1995 +"1995-06-05","June Bank Holiday","IE",1995 +"1995-08-07","August Bank Holiday","IE",1995 +"1995-10-30","October Bank Holiday","IE",1995 +"1995-12-25","Christmas Day","IE",1995 +"1995-12-26","St. Stephen's Day","IE",1995 +"1996-01-01","New Year's Day","IE",1996 +"1996-03-17","St. Patrick's Day","IE",1996 +"1996-03-18","St. Patrick's Day (Observed)","IE",1996 +"1996-04-08","Easter Monday","IE",1996 +"1996-05-06","May Day","IE",1996 +"1996-06-03","June Bank Holiday","IE",1996 +"1996-08-05","August Bank Holiday","IE",1996 +"1996-10-28","October Bank Holiday","IE",1996 +"1996-12-25","Christmas Day","IE",1996 +"1996-12-26","St. Stephen's Day","IE",1996 +"1997-01-01","New Year's Day","IE",1997 +"1997-03-17","St. Patrick's Day","IE",1997 +"1997-03-31","Easter Monday","IE",1997 +"1997-05-05","May Day","IE",1997 +"1997-06-02","June Bank Holiday","IE",1997 +"1997-08-04","August Bank Holiday","IE",1997 +"1997-10-27","October Bank Holiday","IE",1997 +"1997-12-25","Christmas Day","IE",1997 +"1997-12-26","St. Stephen's Day","IE",1997 +"1998-01-01","New Year's Day","IE",1998 +"1998-03-17","St. Patrick's Day","IE",1998 +"1998-04-13","Easter Monday","IE",1998 +"1998-05-04","May Day","IE",1998 +"1998-06-01","June Bank Holiday","IE",1998 +"1998-08-03","August Bank Holiday","IE",1998 +"1998-10-26","October Bank Holiday","IE",1998 +"1998-12-25","Christmas Day","IE",1998 +"1998-12-26","St. Stephen's Day","IE",1998 +"1998-12-28","St. Stephen's Day (Observed)","IE",1998 +"1999-01-01","New Year's Day","IE",1999 +"1999-03-17","St. Patrick's Day","IE",1999 +"1999-04-05","Easter Monday","IE",1999 +"1999-05-03","May Day","IE",1999 +"1999-06-07","June Bank Holiday","IE",1999 +"1999-08-02","August Bank Holiday","IE",1999 +"1999-10-25","October Bank Holiday","IE",1999 +"1999-12-25","Christmas Day","IE",1999 +"1999-12-26","St. Stephen's Day","IE",1999 +"1999-12-27","Christmas Day (Observed)","IE",1999 +"1999-12-28","St. Stephen's Day (Observed)","IE",1999 +"2000-01-01","New Year's Day","IE",2000 +"2000-03-17","St. Patrick's Day","IE",2000 +"2000-04-24","Easter Monday","IE",2000 +"2000-05-01","May Day","IE",2000 +"2000-06-05","June Bank Holiday","IE",2000 +"2000-08-07","August Bank Holiday","IE",2000 +"2000-10-30","October Bank Holiday","IE",2000 +"2000-12-25","Christmas Day","IE",2000 +"2000-12-26","St. Stephen's Day","IE",2000 +"2001-01-01","New Year's Day","IE",2001 +"2001-03-17","St. Patrick's Day","IE",2001 +"2001-03-19","St. Patrick's Day (Observed)","IE",2001 +"2001-04-16","Easter Monday","IE",2001 +"2001-05-07","May Day","IE",2001 +"2001-06-04","June Bank Holiday","IE",2001 +"2001-08-06","August Bank Holiday","IE",2001 +"2001-10-29","October Bank Holiday","IE",2001 +"2001-12-25","Christmas Day","IE",2001 +"2001-12-26","St. Stephen's Day","IE",2001 +"2002-01-01","New Year's Day","IE",2002 +"2002-03-17","St. Patrick's Day","IE",2002 +"2002-03-18","St. Patrick's Day (Observed)","IE",2002 +"2002-04-01","Easter Monday","IE",2002 +"2002-05-06","May Day","IE",2002 +"2002-06-03","June Bank Holiday","IE",2002 +"2002-08-05","August Bank Holiday","IE",2002 +"2002-10-28","October Bank Holiday","IE",2002 +"2002-12-25","Christmas Day","IE",2002 +"2002-12-26","St. Stephen's Day","IE",2002 +"2003-01-01","New Year's Day","IE",2003 +"2003-03-17","St. Patrick's Day","IE",2003 +"2003-04-21","Easter Monday","IE",2003 +"2003-05-05","May Day","IE",2003 +"2003-06-02","June Bank Holiday","IE",2003 +"2003-08-04","August Bank Holiday","IE",2003 +"2003-10-27","October Bank Holiday","IE",2003 +"2003-12-25","Christmas Day","IE",2003 +"2003-12-26","St. Stephen's Day","IE",2003 +"2004-01-01","New Year's Day","IE",2004 +"2004-03-17","St. Patrick's Day","IE",2004 +"2004-04-12","Easter Monday","IE",2004 +"2004-05-03","May Day","IE",2004 +"2004-06-07","June Bank Holiday","IE",2004 +"2004-08-02","August Bank Holiday","IE",2004 +"2004-10-25","October Bank Holiday","IE",2004 +"2004-12-25","Christmas Day","IE",2004 +"2004-12-26","St. Stephen's Day","IE",2004 +"2004-12-27","Christmas Day (Observed)","IE",2004 +"2004-12-28","St. Stephen's Day (Observed)","IE",2004 +"2005-01-01","New Year's Day","IE",2005 +"2005-03-17","St. Patrick's Day","IE",2005 +"2005-03-28","Easter Monday","IE",2005 +"2005-05-02","May Day","IE",2005 +"2005-06-06","June Bank Holiday","IE",2005 +"2005-08-01","August Bank Holiday","IE",2005 +"2005-10-31","October Bank Holiday","IE",2005 +"2005-12-25","Christmas Day","IE",2005 +"2005-12-26","Christmas Day (Observed)","IE",2005 +"2005-12-26","St. Stephen's Day","IE",2005 +"2006-01-01","New Year's Day","IE",2006 +"2006-03-17","St. Patrick's Day","IE",2006 +"2006-04-17","Easter Monday","IE",2006 +"2006-05-01","May Day","IE",2006 +"2006-06-05","June Bank Holiday","IE",2006 +"2006-08-07","August Bank Holiday","IE",2006 +"2006-10-30","October Bank Holiday","IE",2006 +"2006-12-25","Christmas Day","IE",2006 +"2006-12-26","St. Stephen's Day","IE",2006 +"2007-01-01","New Year's Day","IE",2007 +"2007-03-17","St. Patrick's Day","IE",2007 +"2007-03-19","St. Patrick's Day (Observed)","IE",2007 +"2007-04-09","Easter Monday","IE",2007 +"2007-05-07","May Day","IE",2007 +"2007-06-04","June Bank Holiday","IE",2007 +"2007-08-06","August Bank Holiday","IE",2007 +"2007-10-29","October Bank Holiday","IE",2007 +"2007-12-25","Christmas Day","IE",2007 +"2007-12-26","St. Stephen's Day","IE",2007 +"2008-01-01","New Year's Day","IE",2008 +"2008-03-17","St. Patrick's Day","IE",2008 +"2008-03-24","Easter Monday","IE",2008 +"2008-05-05","May Day","IE",2008 +"2008-06-02","June Bank Holiday","IE",2008 +"2008-08-04","August Bank Holiday","IE",2008 +"2008-10-27","October Bank Holiday","IE",2008 +"2008-12-25","Christmas Day","IE",2008 +"2008-12-26","St. Stephen's Day","IE",2008 +"2009-01-01","New Year's Day","IE",2009 +"2009-03-17","St. Patrick's Day","IE",2009 +"2009-04-13","Easter Monday","IE",2009 +"2009-05-04","May Day","IE",2009 +"2009-06-01","June Bank Holiday","IE",2009 +"2009-08-03","August Bank Holiday","IE",2009 +"2009-10-26","October Bank Holiday","IE",2009 +"2009-12-25","Christmas Day","IE",2009 +"2009-12-26","St. Stephen's Day","IE",2009 +"2009-12-28","St. Stephen's Day (Observed)","IE",2009 +"2010-01-01","New Year's Day","IE",2010 +"2010-03-17","St. Patrick's Day","IE",2010 +"2010-04-05","Easter Monday","IE",2010 +"2010-05-03","May Day","IE",2010 +"2010-06-07","June Bank Holiday","IE",2010 +"2010-08-02","August Bank Holiday","IE",2010 +"2010-10-25","October Bank Holiday","IE",2010 +"2010-12-25","Christmas Day","IE",2010 +"2010-12-26","St. Stephen's Day","IE",2010 +"2010-12-27","Christmas Day (Observed)","IE",2010 +"2010-12-28","St. Stephen's Day (Observed)","IE",2010 +"2011-01-01","New Year's Day","IE",2011 +"2011-03-17","St. Patrick's Day","IE",2011 +"2011-04-25","Easter Monday","IE",2011 +"2011-05-02","May Day","IE",2011 +"2011-06-06","June Bank Holiday","IE",2011 +"2011-08-01","August Bank Holiday","IE",2011 +"2011-10-31","October Bank Holiday","IE",2011 +"2011-12-25","Christmas Day","IE",2011 +"2011-12-26","Christmas Day (Observed)","IE",2011 +"2011-12-26","St. Stephen's Day","IE",2011 +"2012-01-01","New Year's Day","IE",2012 +"2012-03-17","St. Patrick's Day","IE",2012 +"2012-03-19","St. Patrick's Day (Observed)","IE",2012 +"2012-04-09","Easter Monday","IE",2012 +"2012-05-07","May Day","IE",2012 +"2012-06-04","June Bank Holiday","IE",2012 +"2012-08-06","August Bank Holiday","IE",2012 +"2012-10-29","October Bank Holiday","IE",2012 +"2012-12-25","Christmas Day","IE",2012 +"2012-12-26","St. Stephen's Day","IE",2012 +"2013-01-01","New Year's Day","IE",2013 +"2013-03-17","St. Patrick's Day","IE",2013 +"2013-03-18","St. Patrick's Day (Observed)","IE",2013 +"2013-04-01","Easter Monday","IE",2013 +"2013-05-06","May Day","IE",2013 +"2013-06-03","June Bank Holiday","IE",2013 +"2013-08-05","August Bank Holiday","IE",2013 +"2013-10-28","October Bank Holiday","IE",2013 +"2013-12-25","Christmas Day","IE",2013 +"2013-12-26","St. Stephen's Day","IE",2013 +"2014-01-01","New Year's Day","IE",2014 +"2014-03-17","St. Patrick's Day","IE",2014 +"2014-04-21","Easter Monday","IE",2014 +"2014-05-05","May Day","IE",2014 +"2014-06-02","June Bank Holiday","IE",2014 +"2014-08-04","August Bank Holiday","IE",2014 +"2014-10-27","October Bank Holiday","IE",2014 +"2014-12-25","Christmas Day","IE",2014 +"2014-12-26","St. Stephen's Day","IE",2014 +"2015-01-01","New Year's Day","IE",2015 +"2015-03-17","St. Patrick's Day","IE",2015 +"2015-04-06","Easter Monday","IE",2015 +"2015-05-04","May Day","IE",2015 +"2015-06-01","June Bank Holiday","IE",2015 +"2015-08-03","August Bank Holiday","IE",2015 +"2015-10-26","October Bank Holiday","IE",2015 +"2015-12-25","Christmas Day","IE",2015 +"2015-12-26","St. Stephen's Day","IE",2015 +"2015-12-28","St. Stephen's Day (Observed)","IE",2015 +"2016-01-01","New Year's Day","IE",2016 +"2016-03-17","St. Patrick's Day","IE",2016 +"2016-03-28","Easter Monday","IE",2016 +"2016-05-02","May Day","IE",2016 +"2016-06-06","June Bank Holiday","IE",2016 +"2016-08-01","August Bank Holiday","IE",2016 +"2016-10-31","October Bank Holiday","IE",2016 +"2016-12-25","Christmas Day","IE",2016 +"2016-12-26","Christmas Day (Observed)","IE",2016 +"2016-12-26","St. Stephen's Day","IE",2016 +"2017-01-01","New Year's Day","IE",2017 +"2017-03-17","St. Patrick's Day","IE",2017 +"2017-04-17","Easter Monday","IE",2017 +"2017-05-01","May Day","IE",2017 +"2017-06-05","June Bank Holiday","IE",2017 +"2017-08-07","August Bank Holiday","IE",2017 +"2017-10-30","October Bank Holiday","IE",2017 +"2017-12-25","Christmas Day","IE",2017 +"2017-12-26","St. Stephen's Day","IE",2017 +"2018-01-01","New Year's Day","IE",2018 +"2018-03-17","St. Patrick's Day","IE",2018 +"2018-03-19","St. Patrick's Day (Observed)","IE",2018 +"2018-04-02","Easter Monday","IE",2018 +"2018-05-07","May Day","IE",2018 +"2018-06-04","June Bank Holiday","IE",2018 +"2018-08-06","August Bank Holiday","IE",2018 +"2018-10-29","October Bank Holiday","IE",2018 +"2018-12-25","Christmas Day","IE",2018 +"2018-12-26","St. Stephen's Day","IE",2018 +"2019-01-01","New Year's Day","IE",2019 +"2019-03-17","St. Patrick's Day","IE",2019 +"2019-03-18","St. Patrick's Day (Observed)","IE",2019 +"2019-04-22","Easter Monday","IE",2019 +"2019-05-06","May Day","IE",2019 +"2019-06-03","June Bank Holiday","IE",2019 +"2019-08-05","August Bank Holiday","IE",2019 +"2019-10-28","October Bank Holiday","IE",2019 +"2019-12-25","Christmas Day","IE",2019 +"2019-12-26","St. Stephen's Day","IE",2019 +"2020-01-01","New Year's Day","IE",2020 +"2020-03-17","St. Patrick's Day","IE",2020 +"2020-04-13","Easter Monday","IE",2020 +"2020-05-04","May Day","IE",2020 +"2020-06-01","June Bank Holiday","IE",2020 +"2020-08-03","August Bank Holiday","IE",2020 +"2020-10-26","October Bank Holiday","IE",2020 +"2020-12-25","Christmas Day","IE",2020 +"2020-12-26","St. Stephen's Day","IE",2020 +"2020-12-28","St. Stephen's Day (Observed)","IE",2020 +"2021-01-01","New Year's Day","IE",2021 +"2021-03-17","St. Patrick's Day","IE",2021 +"2021-04-05","Easter Monday","IE",2021 +"2021-05-03","May Day","IE",2021 +"2021-06-07","June Bank Holiday","IE",2021 +"2021-08-02","August Bank Holiday","IE",2021 +"2021-10-25","October Bank Holiday","IE",2021 +"2021-12-25","Christmas Day","IE",2021 +"2021-12-26","St. Stephen's Day","IE",2021 +"2021-12-27","Christmas Day (Observed)","IE",2021 +"2021-12-28","St. Stephen's Day (Observed)","IE",2021 +"2022-01-01","New Year's Day","IE",2022 +"2022-03-17","St. Patrick's Day","IE",2022 +"2022-03-18","Day of Remembrance and Recognition","IE",2022 +"2022-04-18","Easter Monday","IE",2022 +"2022-05-02","May Day","IE",2022 +"2022-06-06","June Bank Holiday","IE",2022 +"2022-08-01","August Bank Holiday","IE",2022 +"2022-10-31","October Bank Holiday","IE",2022 +"2022-12-25","Christmas Day","IE",2022 +"2022-12-26","Christmas Day (Observed)","IE",2022 +"2022-12-26","St. Stephen's Day","IE",2022 +"2023-01-01","New Year's Day","IE",2023 +"2023-02-06","St. Brigid's Day","IE",2023 +"2023-03-17","St. Patrick's Day","IE",2023 +"2023-04-10","Easter Monday","IE",2023 +"2023-05-01","May Day","IE",2023 +"2023-06-05","June Bank Holiday","IE",2023 +"2023-08-07","August Bank Holiday","IE",2023 +"2023-10-30","October Bank Holiday","IE",2023 +"2023-12-25","Christmas Day","IE",2023 +"2023-12-26","St. Stephen's Day","IE",2023 +"2024-01-01","New Year's Day","IE",2024 +"2024-02-05","St. Brigid's Day","IE",2024 +"2024-03-17","St. Patrick's Day","IE",2024 +"2024-03-18","St. Patrick's Day (Observed)","IE",2024 +"2024-04-01","Easter Monday","IE",2024 +"2024-05-06","May Day","IE",2024 +"2024-06-03","June Bank Holiday","IE",2024 +"2024-08-05","August Bank Holiday","IE",2024 +"2024-10-28","October Bank Holiday","IE",2024 +"2024-12-25","Christmas Day","IE",2024 +"2024-12-26","St. Stephen's Day","IE",2024 +"2025-01-01","New Year's Day","IE",2025 +"2025-02-03","St. Brigid's Day","IE",2025 +"2025-03-17","St. Patrick's Day","IE",2025 +"2025-04-21","Easter Monday","IE",2025 +"2025-05-05","May Day","IE",2025 +"2025-06-02","June Bank Holiday","IE",2025 +"2025-08-04","August Bank Holiday","IE",2025 +"2025-10-27","October Bank Holiday","IE",2025 +"2025-12-25","Christmas Day","IE",2025 +"2025-12-26","St. Stephen's Day","IE",2025 +"2026-01-01","New Year's Day","IE",2026 +"2026-02-02","St. Brigid's Day","IE",2026 +"2026-03-17","St. Patrick's Day","IE",2026 +"2026-04-06","Easter Monday","IE",2026 +"2026-05-04","May Day","IE",2026 +"2026-06-01","June Bank Holiday","IE",2026 +"2026-08-03","August Bank Holiday","IE",2026 +"2026-10-26","October Bank Holiday","IE",2026 +"2026-12-25","Christmas Day","IE",2026 +"2026-12-26","St. Stephen's Day","IE",2026 +"2026-12-28","St. Stephen's Day (Observed)","IE",2026 +"2027-01-01","New Year's Day","IE",2027 +"2027-02-01","St. Brigid's Day","IE",2027 +"2027-03-17","St. Patrick's Day","IE",2027 +"2027-03-29","Easter Monday","IE",2027 +"2027-05-03","May Day","IE",2027 +"2027-06-07","June Bank Holiday","IE",2027 +"2027-08-02","August Bank Holiday","IE",2027 +"2027-10-25","October Bank Holiday","IE",2027 +"2027-12-25","Christmas Day","IE",2027 +"2027-12-26","St. Stephen's Day","IE",2027 +"2027-12-27","Christmas Day (Observed)","IE",2027 +"2027-12-28","St. Stephen's Day (Observed)","IE",2027 +"2028-01-01","New Year's Day","IE",2028 +"2028-02-07","St. Brigid's Day","IE",2028 +"2028-03-17","St. Patrick's Day","IE",2028 +"2028-04-17","Easter Monday","IE",2028 +"2028-05-01","May Day","IE",2028 +"2028-06-05","June Bank Holiday","IE",2028 +"2028-08-07","August Bank Holiday","IE",2028 +"2028-10-30","October Bank Holiday","IE",2028 +"2028-12-25","Christmas Day","IE",2028 +"2028-12-26","St. Stephen's Day","IE",2028 +"2029-01-01","New Year's Day","IE",2029 +"2029-02-05","St. Brigid's Day","IE",2029 +"2029-03-17","St. Patrick's Day","IE",2029 +"2029-03-19","St. Patrick's Day (Observed)","IE",2029 +"2029-04-02","Easter Monday","IE",2029 +"2029-05-07","May Day","IE",2029 +"2029-06-04","June Bank Holiday","IE",2029 +"2029-08-06","August Bank Holiday","IE",2029 +"2029-10-29","October Bank Holiday","IE",2029 +"2029-12-25","Christmas Day","IE",2029 +"2029-12-26","St. Stephen's Day","IE",2029 +"2030-01-01","New Year's Day","IE",2030 +"2030-02-01","St. Brigid's Day","IE",2030 +"2030-03-17","St. Patrick's Day","IE",2030 +"2030-03-18","St. Patrick's Day (Observed)","IE",2030 +"2030-04-22","Easter Monday","IE",2030 +"2030-05-06","May Day","IE",2030 +"2030-06-03","June Bank Holiday","IE",2030 +"2030-08-05","August Bank Holiday","IE",2030 +"2030-10-28","October Bank Holiday","IE",2030 +"2030-12-25","Christmas Day","IE",2030 +"2030-12-26","St. Stephen's Day","IE",2030 +"2031-01-01","New Year's Day","IE",2031 +"2031-02-03","St. Brigid's Day","IE",2031 +"2031-03-17","St. Patrick's Day","IE",2031 +"2031-04-14","Easter Monday","IE",2031 +"2031-05-05","May Day","IE",2031 +"2031-06-02","June Bank Holiday","IE",2031 +"2031-08-04","August Bank Holiday","IE",2031 +"2031-10-27","October Bank Holiday","IE",2031 +"2031-12-25","Christmas Day","IE",2031 +"2031-12-26","St. Stephen's Day","IE",2031 +"2032-01-01","New Year's Day","IE",2032 +"2032-02-02","St. Brigid's Day","IE",2032 +"2032-03-17","St. Patrick's Day","IE",2032 +"2032-03-29","Easter Monday","IE",2032 +"2032-05-03","May Day","IE",2032 +"2032-06-07","June Bank Holiday","IE",2032 +"2032-08-02","August Bank Holiday","IE",2032 +"2032-10-25","October Bank Holiday","IE",2032 +"2032-12-25","Christmas Day","IE",2032 +"2032-12-26","St. Stephen's Day","IE",2032 +"2032-12-27","Christmas Day (Observed)","IE",2032 +"2032-12-28","St. Stephen's Day (Observed)","IE",2032 +"2033-01-01","New Year's Day","IE",2033 +"2033-02-07","St. Brigid's Day","IE",2033 +"2033-03-17","St. Patrick's Day","IE",2033 +"2033-04-18","Easter Monday","IE",2033 +"2033-05-02","May Day","IE",2033 +"2033-06-06","June Bank Holiday","IE",2033 +"2033-08-01","August Bank Holiday","IE",2033 +"2033-10-31","October Bank Holiday","IE",2033 +"2033-12-25","Christmas Day","IE",2033 +"2033-12-26","Christmas Day (Observed)","IE",2033 +"2033-12-26","St. Stephen's Day","IE",2033 +"2034-01-01","New Year's Day","IE",2034 +"2034-02-06","St. Brigid's Day","IE",2034 +"2034-03-17","St. Patrick's Day","IE",2034 +"2034-04-10","Easter Monday","IE",2034 +"2034-05-01","May Day","IE",2034 +"2034-06-05","June Bank Holiday","IE",2034 +"2034-08-07","August Bank Holiday","IE",2034 +"2034-10-30","October Bank Holiday","IE",2034 +"2034-12-25","Christmas Day","IE",2034 +"2034-12-26","St. Stephen's Day","IE",2034 +"2035-01-01","New Year's Day","IE",2035 +"2035-02-05","St. Brigid's Day","IE",2035 +"2035-03-17","St. Patrick's Day","IE",2035 +"2035-03-19","St. Patrick's Day (Observed)","IE",2035 +"2035-03-26","Easter Monday","IE",2035 +"2035-05-07","May Day","IE",2035 +"2035-06-04","June Bank Holiday","IE",2035 +"2035-08-06","August Bank Holiday","IE",2035 +"2035-10-29","October Bank Holiday","IE",2035 +"2035-12-25","Christmas Day","IE",2035 +"2035-12-26","St. Stephen's Day","IE",2035 +"2036-01-01","New Year's Day","IE",2036 +"2036-02-01","St. Brigid's Day","IE",2036 +"2036-03-17","St. Patrick's Day","IE",2036 +"2036-04-14","Easter Monday","IE",2036 +"2036-05-05","May Day","IE",2036 +"2036-06-02","June Bank Holiday","IE",2036 +"2036-08-04","August Bank Holiday","IE",2036 +"2036-10-27","October Bank Holiday","IE",2036 +"2036-12-25","Christmas Day","IE",2036 +"2036-12-26","St. Stephen's Day","IE",2036 +"2037-01-01","New Year's Day","IE",2037 +"2037-02-02","St. Brigid's Day","IE",2037 +"2037-03-17","St. Patrick's Day","IE",2037 +"2037-04-06","Easter Monday","IE",2037 +"2037-05-04","May Day","IE",2037 +"2037-06-01","June Bank Holiday","IE",2037 +"2037-08-03","August Bank Holiday","IE",2037 +"2037-10-26","October Bank Holiday","IE",2037 +"2037-12-25","Christmas Day","IE",2037 +"2037-12-26","St. Stephen's Day","IE",2037 +"2037-12-28","St. Stephen's Day (Observed)","IE",2037 +"2038-01-01","New Year's Day","IE",2038 +"2038-02-01","St. Brigid's Day","IE",2038 +"2038-03-17","St. Patrick's Day","IE",2038 +"2038-04-26","Easter Monday","IE",2038 +"2038-05-03","May Day","IE",2038 +"2038-06-07","June Bank Holiday","IE",2038 +"2038-08-02","August Bank Holiday","IE",2038 +"2038-10-25","October Bank Holiday","IE",2038 +"2038-12-25","Christmas Day","IE",2038 +"2038-12-26","St. Stephen's Day","IE",2038 +"2038-12-27","Christmas Day (Observed)","IE",2038 +"2038-12-28","St. Stephen's Day (Observed)","IE",2038 +"2039-01-01","New Year's Day","IE",2039 +"2039-02-07","St. Brigid's Day","IE",2039 +"2039-03-17","St. Patrick's Day","IE",2039 +"2039-04-11","Easter Monday","IE",2039 +"2039-05-02","May Day","IE",2039 +"2039-06-06","June Bank Holiday","IE",2039 +"2039-08-01","August Bank Holiday","IE",2039 +"2039-10-31","October Bank Holiday","IE",2039 +"2039-12-25","Christmas Day","IE",2039 +"2039-12-26","Christmas Day (Observed)","IE",2039 +"2039-12-26","St. Stephen's Day","IE",2039 +"2040-01-01","New Year's Day","IE",2040 +"2040-02-06","St. Brigid's Day","IE",2040 +"2040-03-17","St. Patrick's Day","IE",2040 +"2040-03-19","St. Patrick's Day (Observed)","IE",2040 +"2040-04-02","Easter Monday","IE",2040 +"2040-05-07","May Day","IE",2040 +"2040-06-04","June Bank Holiday","IE",2040 +"2040-08-06","August Bank Holiday","IE",2040 +"2040-10-29","October Bank Holiday","IE",2040 +"2040-12-25","Christmas Day","IE",2040 +"2040-12-26","St. Stephen's Day","IE",2040 +"2041-01-01","New Year's Day","IE",2041 +"2041-02-01","St. Brigid's Day","IE",2041 +"2041-03-17","St. Patrick's Day","IE",2041 +"2041-03-18","St. Patrick's Day (Observed)","IE",2041 +"2041-04-22","Easter Monday","IE",2041 +"2041-05-06","May Day","IE",2041 +"2041-06-03","June Bank Holiday","IE",2041 +"2041-08-05","August Bank Holiday","IE",2041 +"2041-10-28","October Bank Holiday","IE",2041 +"2041-12-25","Christmas Day","IE",2041 +"2041-12-26","St. Stephen's Day","IE",2041 +"2042-01-01","New Year's Day","IE",2042 +"2042-02-03","St. Brigid's Day","IE",2042 +"2042-03-17","St. Patrick's Day","IE",2042 +"2042-04-07","Easter Monday","IE",2042 +"2042-05-05","May Day","IE",2042 +"2042-06-02","June Bank Holiday","IE",2042 +"2042-08-04","August Bank Holiday","IE",2042 +"2042-10-27","October Bank Holiday","IE",2042 +"2042-12-25","Christmas Day","IE",2042 +"2042-12-26","St. Stephen's Day","IE",2042 +"2043-01-01","New Year's Day","IE",2043 +"2043-02-02","St. Brigid's Day","IE",2043 +"2043-03-17","St. Patrick's Day","IE",2043 +"2043-03-30","Easter Monday","IE",2043 +"2043-05-04","May Day","IE",2043 +"2043-06-01","June Bank Holiday","IE",2043 +"2043-08-03","August Bank Holiday","IE",2043 +"2043-10-26","October Bank Holiday","IE",2043 +"2043-12-25","Christmas Day","IE",2043 +"2043-12-26","St. Stephen's Day","IE",2043 +"2043-12-28","St. Stephen's Day (Observed)","IE",2043 +"2044-01-01","New Year's Day","IE",2044 +"2044-02-01","St. Brigid's Day","IE",2044 +"2044-03-17","St. Patrick's Day","IE",2044 +"2044-04-18","Easter Monday","IE",2044 +"2044-05-02","May Day","IE",2044 +"2044-06-06","June Bank Holiday","IE",2044 +"2044-08-01","August Bank Holiday","IE",2044 +"2044-10-31","October Bank Holiday","IE",2044 +"2044-12-25","Christmas Day","IE",2044 +"2044-12-26","Christmas Day (Observed)","IE",2044 +"2044-12-26","St. Stephen's Day","IE",2044 +"1995-03-15","Purim - Eve","IL",1995 +"1995-03-16","Purim","IL",1995 +"1995-03-17","Shushan Purim","IL",1995 +"1995-04-14","Passover I - Eve","IL",1995 +"1995-04-15","Passover I","IL",1995 +"1995-04-16","Passover - Chol HaMoed","IL",1995 +"1995-04-17","Passover - Chol HaMoed","IL",1995 +"1995-04-18","Passover - Chol HaMoed","IL",1995 +"1995-04-19","Passover - Chol HaMoed","IL",1995 +"1995-04-20","Passover VII - Eve","IL",1995 +"1995-04-21","Passover VII","IL",1995 +"1995-05-03","Memorial Day (Observed)","IL",1995 +"1995-05-04","Independence Day (Observed)","IL",1995 +"1995-05-18","Lag B'Omer","IL",1995 +"1995-06-03","Shavuot - Eve","IL",1995 +"1995-06-04","Shavuot","IL",1995 +"1995-09-24","Rosh Hashanah - Eve","IL",1995 +"1995-09-25","Rosh Hashanah","IL",1995 +"1995-09-26","Rosh Hashanah","IL",1995 +"1995-10-03","Yom Kippur - Eve","IL",1995 +"1995-10-04","Yom Kippur","IL",1995 +"1995-10-08","Sukkot I - Eve","IL",1995 +"1995-10-09","Sukkot I","IL",1995 +"1995-10-10","Sukkot - Chol HaMoed","IL",1995 +"1995-10-11","Sukkot - Chol HaMoed","IL",1995 +"1995-10-12","Sukkot - Chol HaMoed","IL",1995 +"1995-10-13","Sukkot - Chol HaMoed","IL",1995 +"1995-10-14","Sukkot - Chol HaMoed","IL",1995 +"1995-10-15","Sukkot VII - Eve","IL",1995 +"1995-10-16","Sukkot VII","IL",1995 +"1995-12-18","Hanukkah","IL",1995 +"1995-12-19","Hanukkah","IL",1995 +"1995-12-20","Hanukkah","IL",1995 +"1995-12-21","Hanukkah","IL",1995 +"1995-12-22","Hanukkah","IL",1995 +"1995-12-23","Hanukkah","IL",1995 +"1995-12-24","Hanukkah","IL",1995 +"1995-12-25","Hanukkah","IL",1995 +"1996-03-04","Purim - Eve","IL",1996 +"1996-03-05","Purim","IL",1996 +"1996-03-06","Shushan Purim","IL",1996 +"1996-04-03","Passover I - Eve","IL",1996 +"1996-04-04","Passover I","IL",1996 +"1996-04-05","Passover - Chol HaMoed","IL",1996 +"1996-04-06","Passover - Chol HaMoed","IL",1996 +"1996-04-07","Passover - Chol HaMoed","IL",1996 +"1996-04-08","Passover - Chol HaMoed","IL",1996 +"1996-04-09","Passover VII - Eve","IL",1996 +"1996-04-10","Passover VII","IL",1996 +"1996-04-23","Memorial Day","IL",1996 +"1996-04-24","Independence Day","IL",1996 +"1996-05-07","Lag B'Omer","IL",1996 +"1996-05-23","Shavuot - Eve","IL",1996 +"1996-05-24","Shavuot","IL",1996 +"1996-09-13","Rosh Hashanah - Eve","IL",1996 +"1996-09-14","Rosh Hashanah","IL",1996 +"1996-09-15","Rosh Hashanah","IL",1996 +"1996-09-22","Yom Kippur - Eve","IL",1996 +"1996-09-23","Yom Kippur","IL",1996 +"1996-09-27","Sukkot I - Eve","IL",1996 +"1996-09-28","Sukkot I","IL",1996 +"1996-09-29","Sukkot - Chol HaMoed","IL",1996 +"1996-09-30","Sukkot - Chol HaMoed","IL",1996 +"1996-10-01","Sukkot - Chol HaMoed","IL",1996 +"1996-10-02","Sukkot - Chol HaMoed","IL",1996 +"1996-10-03","Sukkot - Chol HaMoed","IL",1996 +"1996-10-04","Sukkot VII - Eve","IL",1996 +"1996-10-05","Sukkot VII","IL",1996 +"1996-12-06","Hanukkah","IL",1996 +"1996-12-07","Hanukkah","IL",1996 +"1996-12-08","Hanukkah","IL",1996 +"1996-12-09","Hanukkah","IL",1996 +"1996-12-10","Hanukkah","IL",1996 +"1996-12-11","Hanukkah","IL",1996 +"1996-12-12","Hanukkah","IL",1996 +"1996-12-13","Hanukkah","IL",1996 +"1997-03-22","Purim - Eve","IL",1997 +"1997-03-23","Purim","IL",1997 +"1997-03-24","Shushan Purim","IL",1997 +"1997-04-21","Passover I - Eve","IL",1997 +"1997-04-22","Passover I","IL",1997 +"1997-04-23","Passover - Chol HaMoed","IL",1997 +"1997-04-24","Passover - Chol HaMoed","IL",1997 +"1997-04-25","Passover - Chol HaMoed","IL",1997 +"1997-04-26","Passover - Chol HaMoed","IL",1997 +"1997-04-27","Passover VII - Eve","IL",1997 +"1997-04-28","Passover VII","IL",1997 +"1997-05-11","Memorial Day","IL",1997 +"1997-05-12","Independence Day","IL",1997 +"1997-05-25","Lag B'Omer","IL",1997 +"1997-06-10","Shavuot - Eve","IL",1997 +"1997-06-11","Shavuot","IL",1997 +"1997-10-01","Rosh Hashanah - Eve","IL",1997 +"1997-10-02","Rosh Hashanah","IL",1997 +"1997-10-03","Rosh Hashanah","IL",1997 +"1997-10-10","Yom Kippur - Eve","IL",1997 +"1997-10-11","Yom Kippur","IL",1997 +"1997-10-15","Sukkot I - Eve","IL",1997 +"1997-10-16","Sukkot I","IL",1997 +"1997-10-17","Sukkot - Chol HaMoed","IL",1997 +"1997-10-18","Sukkot - Chol HaMoed","IL",1997 +"1997-10-19","Sukkot - Chol HaMoed","IL",1997 +"1997-10-20","Sukkot - Chol HaMoed","IL",1997 +"1997-10-21","Sukkot - Chol HaMoed","IL",1997 +"1997-10-22","Sukkot VII - Eve","IL",1997 +"1997-10-23","Sukkot VII","IL",1997 +"1997-12-24","Hanukkah","IL",1997 +"1997-12-25","Hanukkah","IL",1997 +"1997-12-26","Hanukkah","IL",1997 +"1997-12-27","Hanukkah","IL",1997 +"1997-12-28","Hanukkah","IL",1997 +"1997-12-29","Hanukkah","IL",1997 +"1997-12-30","Hanukkah","IL",1997 +"1997-12-31","Hanukkah","IL",1997 +"1998-03-11","Purim - Eve","IL",1998 +"1998-03-12","Purim","IL",1998 +"1998-03-13","Shushan Purim","IL",1998 +"1998-04-10","Passover I - Eve","IL",1998 +"1998-04-11","Passover I","IL",1998 +"1998-04-12","Passover - Chol HaMoed","IL",1998 +"1998-04-13","Passover - Chol HaMoed","IL",1998 +"1998-04-14","Passover - Chol HaMoed","IL",1998 +"1998-04-15","Passover - Chol HaMoed","IL",1998 +"1998-04-16","Passover VII - Eve","IL",1998 +"1998-04-17","Passover VII","IL",1998 +"1998-04-29","Memorial Day (Observed)","IL",1998 +"1998-04-30","Independence Day (Observed)","IL",1998 +"1998-05-14","Lag B'Omer","IL",1998 +"1998-05-30","Shavuot - Eve","IL",1998 +"1998-05-31","Shavuot","IL",1998 +"1998-09-20","Rosh Hashanah - Eve","IL",1998 +"1998-09-21","Rosh Hashanah","IL",1998 +"1998-09-22","Rosh Hashanah","IL",1998 +"1998-09-29","Yom Kippur - Eve","IL",1998 +"1998-09-30","Yom Kippur","IL",1998 +"1998-10-04","Sukkot I - Eve","IL",1998 +"1998-10-05","Sukkot I","IL",1998 +"1998-10-06","Sukkot - Chol HaMoed","IL",1998 +"1998-10-07","Sukkot - Chol HaMoed","IL",1998 +"1998-10-08","Sukkot - Chol HaMoed","IL",1998 +"1998-10-09","Sukkot - Chol HaMoed","IL",1998 +"1998-10-10","Sukkot - Chol HaMoed","IL",1998 +"1998-10-11","Sukkot VII - Eve","IL",1998 +"1998-10-12","Sukkot VII","IL",1998 +"1998-12-14","Hanukkah","IL",1998 +"1998-12-15","Hanukkah","IL",1998 +"1998-12-16","Hanukkah","IL",1998 +"1998-12-17","Hanukkah","IL",1998 +"1998-12-18","Hanukkah","IL",1998 +"1998-12-19","Hanukkah","IL",1998 +"1998-12-20","Hanukkah","IL",1998 +"1998-12-21","Hanukkah","IL",1998 +"1999-03-01","Purim - Eve","IL",1999 +"1999-03-02","Purim","IL",1999 +"1999-03-03","Shushan Purim","IL",1999 +"1999-03-31","Passover I - Eve","IL",1999 +"1999-04-01","Passover I","IL",1999 +"1999-04-02","Passover - Chol HaMoed","IL",1999 +"1999-04-03","Passover - Chol HaMoed","IL",1999 +"1999-04-04","Passover - Chol HaMoed","IL",1999 +"1999-04-05","Passover - Chol HaMoed","IL",1999 +"1999-04-06","Passover VII - Eve","IL",1999 +"1999-04-07","Passover VII","IL",1999 +"1999-04-20","Memorial Day","IL",1999 +"1999-04-21","Independence Day","IL",1999 +"1999-05-04","Lag B'Omer","IL",1999 +"1999-05-20","Shavuot - Eve","IL",1999 +"1999-05-21","Shavuot","IL",1999 +"1999-09-10","Rosh Hashanah - Eve","IL",1999 +"1999-09-11","Rosh Hashanah","IL",1999 +"1999-09-12","Rosh Hashanah","IL",1999 +"1999-09-19","Yom Kippur - Eve","IL",1999 +"1999-09-20","Yom Kippur","IL",1999 +"1999-09-24","Sukkot I - Eve","IL",1999 +"1999-09-25","Sukkot I","IL",1999 +"1999-09-26","Sukkot - Chol HaMoed","IL",1999 +"1999-09-27","Sukkot - Chol HaMoed","IL",1999 +"1999-09-28","Sukkot - Chol HaMoed","IL",1999 +"1999-09-29","Sukkot - Chol HaMoed","IL",1999 +"1999-09-30","Sukkot - Chol HaMoed","IL",1999 +"1999-10-01","Sukkot VII - Eve","IL",1999 +"1999-10-02","Sukkot VII","IL",1999 +"1999-12-04","Hanukkah","IL",1999 +"1999-12-05","Hanukkah","IL",1999 +"1999-12-06","Hanukkah","IL",1999 +"1999-12-07","Hanukkah","IL",1999 +"1999-12-08","Hanukkah","IL",1999 +"1999-12-09","Hanukkah","IL",1999 +"1999-12-10","Hanukkah","IL",1999 +"1999-12-11","Hanukkah","IL",1999 +"2000-03-20","Purim - Eve","IL",2000 +"2000-03-21","Purim","IL",2000 +"2000-03-22","Shushan Purim","IL",2000 +"2000-04-19","Passover I - Eve","IL",2000 +"2000-04-20","Passover I","IL",2000 +"2000-04-21","Passover - Chol HaMoed","IL",2000 +"2000-04-22","Passover - Chol HaMoed","IL",2000 +"2000-04-23","Passover - Chol HaMoed","IL",2000 +"2000-04-24","Passover - Chol HaMoed","IL",2000 +"2000-04-25","Passover VII - Eve","IL",2000 +"2000-04-26","Passover VII","IL",2000 +"2000-05-09","Memorial Day","IL",2000 +"2000-05-10","Independence Day","IL",2000 +"2000-05-23","Lag B'Omer","IL",2000 +"2000-06-08","Shavuot - Eve","IL",2000 +"2000-06-09","Shavuot","IL",2000 +"2000-09-29","Rosh Hashanah - Eve","IL",2000 +"2000-09-30","Rosh Hashanah","IL",2000 +"2000-10-01","Rosh Hashanah","IL",2000 +"2000-10-08","Yom Kippur - Eve","IL",2000 +"2000-10-09","Yom Kippur","IL",2000 +"2000-10-13","Sukkot I - Eve","IL",2000 +"2000-10-14","Sukkot I","IL",2000 +"2000-10-15","Sukkot - Chol HaMoed","IL",2000 +"2000-10-16","Sukkot - Chol HaMoed","IL",2000 +"2000-10-17","Sukkot - Chol HaMoed","IL",2000 +"2000-10-18","Sukkot - Chol HaMoed","IL",2000 +"2000-10-19","Sukkot - Chol HaMoed","IL",2000 +"2000-10-20","Sukkot VII - Eve","IL",2000 +"2000-10-21","Sukkot VII","IL",2000 +"2000-12-22","Hanukkah","IL",2000 +"2000-12-23","Hanukkah","IL",2000 +"2000-12-24","Hanukkah","IL",2000 +"2000-12-25","Hanukkah","IL",2000 +"2000-12-26","Hanukkah","IL",2000 +"2000-12-27","Hanukkah","IL",2000 +"2000-12-28","Hanukkah","IL",2000 +"2000-12-29","Hanukkah","IL",2000 +"2001-03-08","Purim - Eve","IL",2001 +"2001-03-09","Purim","IL",2001 +"2001-03-10","Shushan Purim","IL",2001 +"2001-04-07","Passover I - Eve","IL",2001 +"2001-04-08","Passover I","IL",2001 +"2001-04-09","Passover - Chol HaMoed","IL",2001 +"2001-04-10","Passover - Chol HaMoed","IL",2001 +"2001-04-11","Passover - Chol HaMoed","IL",2001 +"2001-04-12","Passover - Chol HaMoed","IL",2001 +"2001-04-13","Passover VII - Eve","IL",2001 +"2001-04-14","Passover VII","IL",2001 +"2001-04-25","Memorial Day (Observed)","IL",2001 +"2001-04-26","Independence Day (Observed)","IL",2001 +"2001-05-11","Lag B'Omer","IL",2001 +"2001-05-27","Shavuot - Eve","IL",2001 +"2001-05-28","Shavuot","IL",2001 +"2001-09-17","Rosh Hashanah - Eve","IL",2001 +"2001-09-18","Rosh Hashanah","IL",2001 +"2001-09-19","Rosh Hashanah","IL",2001 +"2001-09-26","Yom Kippur - Eve","IL",2001 +"2001-09-27","Yom Kippur","IL",2001 +"2001-10-01","Sukkot I - Eve","IL",2001 +"2001-10-02","Sukkot I","IL",2001 +"2001-10-03","Sukkot - Chol HaMoed","IL",2001 +"2001-10-04","Sukkot - Chol HaMoed","IL",2001 +"2001-10-05","Sukkot - Chol HaMoed","IL",2001 +"2001-10-06","Sukkot - Chol HaMoed","IL",2001 +"2001-10-07","Sukkot - Chol HaMoed","IL",2001 +"2001-10-08","Sukkot VII - Eve","IL",2001 +"2001-10-09","Sukkot VII","IL",2001 +"2001-12-10","Hanukkah","IL",2001 +"2001-12-11","Hanukkah","IL",2001 +"2001-12-12","Hanukkah","IL",2001 +"2001-12-13","Hanukkah","IL",2001 +"2001-12-14","Hanukkah","IL",2001 +"2001-12-15","Hanukkah","IL",2001 +"2001-12-16","Hanukkah","IL",2001 +"2001-12-17","Hanukkah","IL",2001 +"2002-02-25","Purim - Eve","IL",2002 +"2002-02-26","Purim","IL",2002 +"2002-02-27","Shushan Purim","IL",2002 +"2002-03-27","Passover I - Eve","IL",2002 +"2002-03-28","Passover I","IL",2002 +"2002-03-29","Passover - Chol HaMoed","IL",2002 +"2002-03-30","Passover - Chol HaMoed","IL",2002 +"2002-03-31","Passover - Chol HaMoed","IL",2002 +"2002-04-01","Passover - Chol HaMoed","IL",2002 +"2002-04-02","Passover VII - Eve","IL",2002 +"2002-04-03","Passover VII","IL",2002 +"2002-04-16","Memorial Day","IL",2002 +"2002-04-17","Independence Day","IL",2002 +"2002-04-30","Lag B'Omer","IL",2002 +"2002-05-16","Shavuot - Eve","IL",2002 +"2002-05-17","Shavuot","IL",2002 +"2002-09-06","Rosh Hashanah - Eve","IL",2002 +"2002-09-07","Rosh Hashanah","IL",2002 +"2002-09-08","Rosh Hashanah","IL",2002 +"2002-09-15","Yom Kippur - Eve","IL",2002 +"2002-09-16","Yom Kippur","IL",2002 +"2002-09-20","Sukkot I - Eve","IL",2002 +"2002-09-21","Sukkot I","IL",2002 +"2002-09-22","Sukkot - Chol HaMoed","IL",2002 +"2002-09-23","Sukkot - Chol HaMoed","IL",2002 +"2002-09-24","Sukkot - Chol HaMoed","IL",2002 +"2002-09-25","Sukkot - Chol HaMoed","IL",2002 +"2002-09-26","Sukkot - Chol HaMoed","IL",2002 +"2002-09-27","Sukkot VII - Eve","IL",2002 +"2002-09-28","Sukkot VII","IL",2002 +"2002-11-30","Hanukkah","IL",2002 +"2002-12-01","Hanukkah","IL",2002 +"2002-12-02","Hanukkah","IL",2002 +"2002-12-03","Hanukkah","IL",2002 +"2002-12-04","Hanukkah","IL",2002 +"2002-12-05","Hanukkah","IL",2002 +"2002-12-06","Hanukkah","IL",2002 +"2002-12-07","Hanukkah","IL",2002 +"2003-03-17","Purim - Eve","IL",2003 +"2003-03-18","Purim","IL",2003 +"2003-03-19","Shushan Purim","IL",2003 +"2003-04-16","Passover I - Eve","IL",2003 +"2003-04-17","Passover I","IL",2003 +"2003-04-18","Passover - Chol HaMoed","IL",2003 +"2003-04-19","Passover - Chol HaMoed","IL",2003 +"2003-04-20","Passover - Chol HaMoed","IL",2003 +"2003-04-21","Passover - Chol HaMoed","IL",2003 +"2003-04-22","Passover VII - Eve","IL",2003 +"2003-04-23","Passover VII","IL",2003 +"2003-05-06","Memorial Day","IL",2003 +"2003-05-07","Independence Day","IL",2003 +"2003-05-20","Lag B'Omer","IL",2003 +"2003-06-05","Shavuot - Eve","IL",2003 +"2003-06-06","Shavuot","IL",2003 +"2003-09-26","Rosh Hashanah - Eve","IL",2003 +"2003-09-27","Rosh Hashanah","IL",2003 +"2003-09-28","Rosh Hashanah","IL",2003 +"2003-10-05","Yom Kippur - Eve","IL",2003 +"2003-10-06","Yom Kippur","IL",2003 +"2003-10-10","Sukkot I - Eve","IL",2003 +"2003-10-11","Sukkot I","IL",2003 +"2003-10-12","Sukkot - Chol HaMoed","IL",2003 +"2003-10-13","Sukkot - Chol HaMoed","IL",2003 +"2003-10-14","Sukkot - Chol HaMoed","IL",2003 +"2003-10-15","Sukkot - Chol HaMoed","IL",2003 +"2003-10-16","Sukkot - Chol HaMoed","IL",2003 +"2003-10-17","Sukkot VII - Eve","IL",2003 +"2003-10-18","Sukkot VII","IL",2003 +"2003-12-20","Hanukkah","IL",2003 +"2003-12-21","Hanukkah","IL",2003 +"2003-12-22","Hanukkah","IL",2003 +"2003-12-23","Hanukkah","IL",2003 +"2003-12-24","Hanukkah","IL",2003 +"2003-12-25","Hanukkah","IL",2003 +"2003-12-26","Hanukkah","IL",2003 +"2003-12-27","Hanukkah","IL",2003 +"2004-03-06","Purim - Eve","IL",2004 +"2004-03-07","Purim","IL",2004 +"2004-03-08","Shushan Purim","IL",2004 +"2004-04-05","Passover I - Eve","IL",2004 +"2004-04-06","Passover I","IL",2004 +"2004-04-07","Passover - Chol HaMoed","IL",2004 +"2004-04-08","Passover - Chol HaMoed","IL",2004 +"2004-04-09","Passover - Chol HaMoed","IL",2004 +"2004-04-10","Passover - Chol HaMoed","IL",2004 +"2004-04-11","Passover VII - Eve","IL",2004 +"2004-04-12","Passover VII","IL",2004 +"2004-04-26","Memorial Day (Observed)","IL",2004 +"2004-04-27","Independence Day (Observed)","IL",2004 +"2004-05-09","Lag B'Omer","IL",2004 +"2004-05-25","Shavuot - Eve","IL",2004 +"2004-05-26","Shavuot","IL",2004 +"2004-09-15","Rosh Hashanah - Eve","IL",2004 +"2004-09-16","Rosh Hashanah","IL",2004 +"2004-09-17","Rosh Hashanah","IL",2004 +"2004-09-24","Yom Kippur - Eve","IL",2004 +"2004-09-25","Yom Kippur","IL",2004 +"2004-09-29","Sukkot I - Eve","IL",2004 +"2004-09-30","Sukkot I","IL",2004 +"2004-10-01","Sukkot - Chol HaMoed","IL",2004 +"2004-10-02","Sukkot - Chol HaMoed","IL",2004 +"2004-10-03","Sukkot - Chol HaMoed","IL",2004 +"2004-10-04","Sukkot - Chol HaMoed","IL",2004 +"2004-10-05","Sukkot - Chol HaMoed","IL",2004 +"2004-10-06","Sukkot VII - Eve","IL",2004 +"2004-10-07","Sukkot VII","IL",2004 +"2004-12-08","Hanukkah","IL",2004 +"2004-12-09","Hanukkah","IL",2004 +"2004-12-10","Hanukkah","IL",2004 +"2004-12-11","Hanukkah","IL",2004 +"2004-12-12","Hanukkah","IL",2004 +"2004-12-13","Hanukkah","IL",2004 +"2004-12-14","Hanukkah","IL",2004 +"2004-12-15","Hanukkah","IL",2004 +"2005-03-24","Purim - Eve","IL",2005 +"2005-03-25","Purim","IL",2005 +"2005-03-26","Shushan Purim","IL",2005 +"2005-04-23","Passover I - Eve","IL",2005 +"2005-04-24","Passover I","IL",2005 +"2005-04-25","Passover - Chol HaMoed","IL",2005 +"2005-04-26","Passover - Chol HaMoed","IL",2005 +"2005-04-27","Passover - Chol HaMoed","IL",2005 +"2005-04-28","Passover - Chol HaMoed","IL",2005 +"2005-04-29","Passover VII - Eve","IL",2005 +"2005-04-30","Passover VII","IL",2005 +"2005-05-11","Memorial Day (Observed)","IL",2005 +"2005-05-12","Independence Day (Observed)","IL",2005 +"2005-05-27","Lag B'Omer","IL",2005 +"2005-06-12","Shavuot - Eve","IL",2005 +"2005-06-13","Shavuot","IL",2005 +"2005-10-03","Rosh Hashanah - Eve","IL",2005 +"2005-10-04","Rosh Hashanah","IL",2005 +"2005-10-05","Rosh Hashanah","IL",2005 +"2005-10-12","Yom Kippur - Eve","IL",2005 +"2005-10-13","Yom Kippur","IL",2005 +"2005-10-17","Sukkot I - Eve","IL",2005 +"2005-10-18","Sukkot I","IL",2005 +"2005-10-19","Sukkot - Chol HaMoed","IL",2005 +"2005-10-20","Sukkot - Chol HaMoed","IL",2005 +"2005-10-21","Sukkot - Chol HaMoed","IL",2005 +"2005-10-22","Sukkot - Chol HaMoed","IL",2005 +"2005-10-23","Sukkot - Chol HaMoed","IL",2005 +"2005-10-24","Sukkot VII - Eve","IL",2005 +"2005-10-25","Sukkot VII","IL",2005 +"2005-12-26","Hanukkah","IL",2005 +"2005-12-27","Hanukkah","IL",2005 +"2005-12-28","Hanukkah","IL",2005 +"2005-12-29","Hanukkah","IL",2005 +"2005-12-30","Hanukkah","IL",2005 +"2005-12-31","Hanukkah","IL",2005 +"2006-01-01","Hanukkah","IL",2006 +"2006-01-02","Hanukkah","IL",2006 +"2006-03-13","Purim - Eve","IL",2006 +"2006-03-14","Purim","IL",2006 +"2006-03-15","Shushan Purim","IL",2006 +"2006-04-12","Passover I - Eve","IL",2006 +"2006-04-13","Passover I","IL",2006 +"2006-04-14","Passover - Chol HaMoed","IL",2006 +"2006-04-15","Passover - Chol HaMoed","IL",2006 +"2006-04-16","Passover - Chol HaMoed","IL",2006 +"2006-04-17","Passover - Chol HaMoed","IL",2006 +"2006-04-18","Passover VII - Eve","IL",2006 +"2006-04-19","Passover VII","IL",2006 +"2006-05-02","Memorial Day","IL",2006 +"2006-05-03","Independence Day","IL",2006 +"2006-05-16","Lag B'Omer","IL",2006 +"2006-06-01","Shavuot - Eve","IL",2006 +"2006-06-02","Shavuot","IL",2006 +"2006-09-22","Rosh Hashanah - Eve","IL",2006 +"2006-09-23","Rosh Hashanah","IL",2006 +"2006-09-24","Rosh Hashanah","IL",2006 +"2006-10-01","Yom Kippur - Eve","IL",2006 +"2006-10-02","Yom Kippur","IL",2006 +"2006-10-06","Sukkot I - Eve","IL",2006 +"2006-10-07","Sukkot I","IL",2006 +"2006-10-08","Sukkot - Chol HaMoed","IL",2006 +"2006-10-09","Sukkot - Chol HaMoed","IL",2006 +"2006-10-10","Sukkot - Chol HaMoed","IL",2006 +"2006-10-11","Sukkot - Chol HaMoed","IL",2006 +"2006-10-12","Sukkot - Chol HaMoed","IL",2006 +"2006-10-13","Sukkot VII - Eve","IL",2006 +"2006-10-14","Sukkot VII","IL",2006 +"2006-12-16","Hanukkah","IL",2006 +"2006-12-17","Hanukkah","IL",2006 +"2006-12-18","Hanukkah","IL",2006 +"2006-12-19","Hanukkah","IL",2006 +"2006-12-20","Hanukkah","IL",2006 +"2006-12-21","Hanukkah","IL",2006 +"2006-12-22","Hanukkah","IL",2006 +"2006-12-23","Hanukkah","IL",2006 +"2007-03-03","Purim - Eve","IL",2007 +"2007-03-04","Purim","IL",2007 +"2007-03-05","Shushan Purim","IL",2007 +"2007-04-02","Passover I - Eve","IL",2007 +"2007-04-03","Passover I","IL",2007 +"2007-04-04","Passover - Chol HaMoed","IL",2007 +"2007-04-05","Passover - Chol HaMoed","IL",2007 +"2007-04-06","Passover - Chol HaMoed","IL",2007 +"2007-04-07","Passover - Chol HaMoed","IL",2007 +"2007-04-08","Passover VII - Eve","IL",2007 +"2007-04-09","Passover VII","IL",2007 +"2007-04-23","Memorial Day (Observed)","IL",2007 +"2007-04-24","Independence Day (Observed)","IL",2007 +"2007-05-06","Lag B'Omer","IL",2007 +"2007-05-22","Shavuot - Eve","IL",2007 +"2007-05-23","Shavuot","IL",2007 +"2007-09-12","Rosh Hashanah - Eve","IL",2007 +"2007-09-13","Rosh Hashanah","IL",2007 +"2007-09-14","Rosh Hashanah","IL",2007 +"2007-09-21","Yom Kippur - Eve","IL",2007 +"2007-09-22","Yom Kippur","IL",2007 +"2007-09-26","Sukkot I - Eve","IL",2007 +"2007-09-27","Sukkot I","IL",2007 +"2007-09-28","Sukkot - Chol HaMoed","IL",2007 +"2007-09-29","Sukkot - Chol HaMoed","IL",2007 +"2007-09-30","Sukkot - Chol HaMoed","IL",2007 +"2007-10-01","Sukkot - Chol HaMoed","IL",2007 +"2007-10-02","Sukkot - Chol HaMoed","IL",2007 +"2007-10-03","Sukkot VII - Eve","IL",2007 +"2007-10-04","Sukkot VII","IL",2007 +"2007-12-05","Hanukkah","IL",2007 +"2007-12-06","Hanukkah","IL",2007 +"2007-12-07","Hanukkah","IL",2007 +"2007-12-08","Hanukkah","IL",2007 +"2007-12-09","Hanukkah","IL",2007 +"2007-12-10","Hanukkah","IL",2007 +"2007-12-11","Hanukkah","IL",2007 +"2007-12-12","Hanukkah","IL",2007 +"2008-03-20","Purim - Eve","IL",2008 +"2008-03-21","Purim","IL",2008 +"2008-03-22","Shushan Purim","IL",2008 +"2008-04-19","Passover I - Eve","IL",2008 +"2008-04-20","Passover I","IL",2008 +"2008-04-21","Passover - Chol HaMoed","IL",2008 +"2008-04-22","Passover - Chol HaMoed","IL",2008 +"2008-04-23","Passover - Chol HaMoed","IL",2008 +"2008-04-24","Passover - Chol HaMoed","IL",2008 +"2008-04-25","Passover VII - Eve","IL",2008 +"2008-04-26","Passover VII","IL",2008 +"2008-05-07","Memorial Day (Observed)","IL",2008 +"2008-05-08","Independence Day (Observed)","IL",2008 +"2008-05-23","Lag B'Omer","IL",2008 +"2008-06-08","Shavuot - Eve","IL",2008 +"2008-06-09","Shavuot","IL",2008 +"2008-09-29","Rosh Hashanah - Eve","IL",2008 +"2008-09-30","Rosh Hashanah","IL",2008 +"2008-10-01","Rosh Hashanah","IL",2008 +"2008-10-08","Yom Kippur - Eve","IL",2008 +"2008-10-09","Yom Kippur","IL",2008 +"2008-10-13","Sukkot I - Eve","IL",2008 +"2008-10-14","Sukkot I","IL",2008 +"2008-10-15","Sukkot - Chol HaMoed","IL",2008 +"2008-10-16","Sukkot - Chol HaMoed","IL",2008 +"2008-10-17","Sukkot - Chol HaMoed","IL",2008 +"2008-10-18","Sukkot - Chol HaMoed","IL",2008 +"2008-10-19","Sukkot - Chol HaMoed","IL",2008 +"2008-10-20","Sukkot VII - Eve","IL",2008 +"2008-10-21","Sukkot VII","IL",2008 +"2008-12-22","Hanukkah","IL",2008 +"2008-12-23","Hanukkah","IL",2008 +"2008-12-24","Hanukkah","IL",2008 +"2008-12-25","Hanukkah","IL",2008 +"2008-12-26","Hanukkah","IL",2008 +"2008-12-27","Hanukkah","IL",2008 +"2008-12-28","Hanukkah","IL",2008 +"2008-12-29","Hanukkah","IL",2008 +"2009-03-09","Purim - Eve","IL",2009 +"2009-03-10","Purim","IL",2009 +"2009-03-11","Shushan Purim","IL",2009 +"2009-04-08","Passover I - Eve","IL",2009 +"2009-04-09","Passover I","IL",2009 +"2009-04-10","Passover - Chol HaMoed","IL",2009 +"2009-04-11","Passover - Chol HaMoed","IL",2009 +"2009-04-12","Passover - Chol HaMoed","IL",2009 +"2009-04-13","Passover - Chol HaMoed","IL",2009 +"2009-04-14","Passover VII - Eve","IL",2009 +"2009-04-15","Passover VII","IL",2009 +"2009-04-28","Memorial Day","IL",2009 +"2009-04-29","Independence Day","IL",2009 +"2009-05-12","Lag B'Omer","IL",2009 +"2009-05-28","Shavuot - Eve","IL",2009 +"2009-05-29","Shavuot","IL",2009 +"2009-09-18","Rosh Hashanah - Eve","IL",2009 +"2009-09-19","Rosh Hashanah","IL",2009 +"2009-09-20","Rosh Hashanah","IL",2009 +"2009-09-27","Yom Kippur - Eve","IL",2009 +"2009-09-28","Yom Kippur","IL",2009 +"2009-10-02","Sukkot I - Eve","IL",2009 +"2009-10-03","Sukkot I","IL",2009 +"2009-10-04","Sukkot - Chol HaMoed","IL",2009 +"2009-10-05","Sukkot - Chol HaMoed","IL",2009 +"2009-10-06","Sukkot - Chol HaMoed","IL",2009 +"2009-10-07","Sukkot - Chol HaMoed","IL",2009 +"2009-10-08","Sukkot - Chol HaMoed","IL",2009 +"2009-10-09","Sukkot VII - Eve","IL",2009 +"2009-10-10","Sukkot VII","IL",2009 +"2009-12-12","Hanukkah","IL",2009 +"2009-12-13","Hanukkah","IL",2009 +"2009-12-14","Hanukkah","IL",2009 +"2009-12-15","Hanukkah","IL",2009 +"2009-12-16","Hanukkah","IL",2009 +"2009-12-17","Hanukkah","IL",2009 +"2009-12-18","Hanukkah","IL",2009 +"2009-12-19","Hanukkah","IL",2009 +"2010-02-27","Purim - Eve","IL",2010 +"2010-02-28","Purim","IL",2010 +"2010-03-01","Shushan Purim","IL",2010 +"2010-03-29","Passover I - Eve","IL",2010 +"2010-03-30","Passover I","IL",2010 +"2010-03-31","Passover - Chol HaMoed","IL",2010 +"2010-04-01","Passover - Chol HaMoed","IL",2010 +"2010-04-02","Passover - Chol HaMoed","IL",2010 +"2010-04-03","Passover - Chol HaMoed","IL",2010 +"2010-04-04","Passover VII - Eve","IL",2010 +"2010-04-05","Passover VII","IL",2010 +"2010-04-19","Memorial Day (Observed)","IL",2010 +"2010-04-20","Independence Day (Observed)","IL",2010 +"2010-05-02","Lag B'Omer","IL",2010 +"2010-05-18","Shavuot - Eve","IL",2010 +"2010-05-19","Shavuot","IL",2010 +"2010-09-08","Rosh Hashanah - Eve","IL",2010 +"2010-09-09","Rosh Hashanah","IL",2010 +"2010-09-10","Rosh Hashanah","IL",2010 +"2010-09-17","Yom Kippur - Eve","IL",2010 +"2010-09-18","Yom Kippur","IL",2010 +"2010-09-22","Sukkot I - Eve","IL",2010 +"2010-09-23","Sukkot I","IL",2010 +"2010-09-24","Sukkot - Chol HaMoed","IL",2010 +"2010-09-25","Sukkot - Chol HaMoed","IL",2010 +"2010-09-26","Sukkot - Chol HaMoed","IL",2010 +"2010-09-27","Sukkot - Chol HaMoed","IL",2010 +"2010-09-28","Sukkot - Chol HaMoed","IL",2010 +"2010-09-29","Sukkot VII - Eve","IL",2010 +"2010-09-30","Sukkot VII","IL",2010 +"2010-12-02","Hanukkah","IL",2010 +"2010-12-03","Hanukkah","IL",2010 +"2010-12-04","Hanukkah","IL",2010 +"2010-12-05","Hanukkah","IL",2010 +"2010-12-06","Hanukkah","IL",2010 +"2010-12-07","Hanukkah","IL",2010 +"2010-12-08","Hanukkah","IL",2010 +"2010-12-09","Hanukkah","IL",2010 +"2011-03-19","Purim - Eve","IL",2011 +"2011-03-20","Purim","IL",2011 +"2011-03-21","Shushan Purim","IL",2011 +"2011-04-18","Passover I - Eve","IL",2011 +"2011-04-19","Passover I","IL",2011 +"2011-04-20","Passover - Chol HaMoed","IL",2011 +"2011-04-21","Passover - Chol HaMoed","IL",2011 +"2011-04-22","Passover - Chol HaMoed","IL",2011 +"2011-04-23","Passover - Chol HaMoed","IL",2011 +"2011-04-24","Passover VII - Eve","IL",2011 +"2011-04-25","Passover VII","IL",2011 +"2011-05-09","Memorial Day (Observed)","IL",2011 +"2011-05-10","Independence Day (Observed)","IL",2011 +"2011-05-22","Lag B'Omer","IL",2011 +"2011-06-07","Shavuot - Eve","IL",2011 +"2011-06-08","Shavuot","IL",2011 +"2011-09-28","Rosh Hashanah - Eve","IL",2011 +"2011-09-29","Rosh Hashanah","IL",2011 +"2011-09-30","Rosh Hashanah","IL",2011 +"2011-10-07","Yom Kippur - Eve","IL",2011 +"2011-10-08","Yom Kippur","IL",2011 +"2011-10-12","Sukkot I - Eve","IL",2011 +"2011-10-13","Sukkot I","IL",2011 +"2011-10-14","Sukkot - Chol HaMoed","IL",2011 +"2011-10-15","Sukkot - Chol HaMoed","IL",2011 +"2011-10-16","Sukkot - Chol HaMoed","IL",2011 +"2011-10-17","Sukkot - Chol HaMoed","IL",2011 +"2011-10-18","Sukkot - Chol HaMoed","IL",2011 +"2011-10-19","Sukkot VII - Eve","IL",2011 +"2011-10-20","Sukkot VII","IL",2011 +"2011-12-21","Hanukkah","IL",2011 +"2011-12-22","Hanukkah","IL",2011 +"2011-12-23","Hanukkah","IL",2011 +"2011-12-24","Hanukkah","IL",2011 +"2011-12-25","Hanukkah","IL",2011 +"2011-12-26","Hanukkah","IL",2011 +"2011-12-27","Hanukkah","IL",2011 +"2011-12-28","Hanukkah","IL",2011 +"2012-03-07","Purim - Eve","IL",2012 +"2012-03-08","Purim","IL",2012 +"2012-03-09","Shushan Purim","IL",2012 +"2012-04-06","Passover I - Eve","IL",2012 +"2012-04-07","Passover I","IL",2012 +"2012-04-08","Passover - Chol HaMoed","IL",2012 +"2012-04-09","Passover - Chol HaMoed","IL",2012 +"2012-04-10","Passover - Chol HaMoed","IL",2012 +"2012-04-11","Passover - Chol HaMoed","IL",2012 +"2012-04-12","Passover VII - Eve","IL",2012 +"2012-04-13","Passover VII","IL",2012 +"2012-04-25","Memorial Day (Observed)","IL",2012 +"2012-04-26","Independence Day (Observed)","IL",2012 +"2012-05-10","Lag B'Omer","IL",2012 +"2012-05-26","Shavuot - Eve","IL",2012 +"2012-05-27","Shavuot","IL",2012 +"2012-09-16","Rosh Hashanah - Eve","IL",2012 +"2012-09-17","Rosh Hashanah","IL",2012 +"2012-09-18","Rosh Hashanah","IL",2012 +"2012-09-25","Yom Kippur - Eve","IL",2012 +"2012-09-26","Yom Kippur","IL",2012 +"2012-09-30","Sukkot I - Eve","IL",2012 +"2012-10-01","Sukkot I","IL",2012 +"2012-10-02","Sukkot - Chol HaMoed","IL",2012 +"2012-10-03","Sukkot - Chol HaMoed","IL",2012 +"2012-10-04","Sukkot - Chol HaMoed","IL",2012 +"2012-10-05","Sukkot - Chol HaMoed","IL",2012 +"2012-10-06","Sukkot - Chol HaMoed","IL",2012 +"2012-10-07","Sukkot VII - Eve","IL",2012 +"2012-10-08","Sukkot VII","IL",2012 +"2012-12-09","Hanukkah","IL",2012 +"2012-12-10","Hanukkah","IL",2012 +"2012-12-11","Hanukkah","IL",2012 +"2012-12-12","Hanukkah","IL",2012 +"2012-12-13","Hanukkah","IL",2012 +"2012-12-14","Hanukkah","IL",2012 +"2012-12-15","Hanukkah","IL",2012 +"2012-12-16","Hanukkah","IL",2012 +"2013-02-23","Purim - Eve","IL",2013 +"2013-02-24","Purim","IL",2013 +"2013-02-25","Shushan Purim","IL",2013 +"2013-03-25","Passover I - Eve","IL",2013 +"2013-03-26","Passover I","IL",2013 +"2013-03-27","Passover - Chol HaMoed","IL",2013 +"2013-03-28","Passover - Chol HaMoed","IL",2013 +"2013-03-29","Passover - Chol HaMoed","IL",2013 +"2013-03-30","Passover - Chol HaMoed","IL",2013 +"2013-03-31","Passover VII - Eve","IL",2013 +"2013-04-01","Passover VII","IL",2013 +"2013-04-15","Memorial Day (Observed)","IL",2013 +"2013-04-16","Independence Day (Observed)","IL",2013 +"2013-04-28","Lag B'Omer","IL",2013 +"2013-05-14","Shavuot - Eve","IL",2013 +"2013-05-15","Shavuot","IL",2013 +"2013-09-04","Rosh Hashanah - Eve","IL",2013 +"2013-09-05","Rosh Hashanah","IL",2013 +"2013-09-06","Rosh Hashanah","IL",2013 +"2013-09-13","Yom Kippur - Eve","IL",2013 +"2013-09-14","Yom Kippur","IL",2013 +"2013-09-18","Sukkot I - Eve","IL",2013 +"2013-09-19","Sukkot I","IL",2013 +"2013-09-20","Sukkot - Chol HaMoed","IL",2013 +"2013-09-21","Sukkot - Chol HaMoed","IL",2013 +"2013-09-22","Sukkot - Chol HaMoed","IL",2013 +"2013-09-23","Sukkot - Chol HaMoed","IL",2013 +"2013-09-24","Sukkot - Chol HaMoed","IL",2013 +"2013-09-25","Sukkot VII - Eve","IL",2013 +"2013-09-26","Sukkot VII","IL",2013 +"2013-11-28","Hanukkah","IL",2013 +"2013-11-29","Hanukkah","IL",2013 +"2013-11-30","Hanukkah","IL",2013 +"2013-12-01","Hanukkah","IL",2013 +"2013-12-02","Hanukkah","IL",2013 +"2013-12-03","Hanukkah","IL",2013 +"2013-12-04","Hanukkah","IL",2013 +"2013-12-05","Hanukkah","IL",2013 +"2014-03-15","Purim - Eve","IL",2014 +"2014-03-16","Purim","IL",2014 +"2014-03-17","Shushan Purim","IL",2014 +"2014-04-14","Passover I - Eve","IL",2014 +"2014-04-15","Passover I","IL",2014 +"2014-04-16","Passover - Chol HaMoed","IL",2014 +"2014-04-17","Passover - Chol HaMoed","IL",2014 +"2014-04-18","Passover - Chol HaMoed","IL",2014 +"2014-04-19","Passover - Chol HaMoed","IL",2014 +"2014-04-20","Passover VII - Eve","IL",2014 +"2014-04-21","Passover VII","IL",2014 +"2014-05-05","Memorial Day (Observed)","IL",2014 +"2014-05-06","Independence Day (Observed)","IL",2014 +"2014-05-18","Lag B'Omer","IL",2014 +"2014-06-03","Shavuot - Eve","IL",2014 +"2014-06-04","Shavuot","IL",2014 +"2014-09-24","Rosh Hashanah - Eve","IL",2014 +"2014-09-25","Rosh Hashanah","IL",2014 +"2014-09-26","Rosh Hashanah","IL",2014 +"2014-10-03","Yom Kippur - Eve","IL",2014 +"2014-10-04","Yom Kippur","IL",2014 +"2014-10-08","Sukkot I - Eve","IL",2014 +"2014-10-09","Sukkot I","IL",2014 +"2014-10-10","Sukkot - Chol HaMoed","IL",2014 +"2014-10-11","Sukkot - Chol HaMoed","IL",2014 +"2014-10-12","Sukkot - Chol HaMoed","IL",2014 +"2014-10-13","Sukkot - Chol HaMoed","IL",2014 +"2014-10-14","Sukkot - Chol HaMoed","IL",2014 +"2014-10-15","Sukkot VII - Eve","IL",2014 +"2014-10-16","Sukkot VII","IL",2014 +"2014-12-17","Hanukkah","IL",2014 +"2014-12-18","Hanukkah","IL",2014 +"2014-12-19","Hanukkah","IL",2014 +"2014-12-20","Hanukkah","IL",2014 +"2014-12-21","Hanukkah","IL",2014 +"2014-12-22","Hanukkah","IL",2014 +"2014-12-23","Hanukkah","IL",2014 +"2014-12-24","Hanukkah","IL",2014 +"2015-03-04","Purim - Eve","IL",2015 +"2015-03-05","Purim","IL",2015 +"2015-03-06","Shushan Purim","IL",2015 +"2015-04-03","Passover I - Eve","IL",2015 +"2015-04-04","Passover I","IL",2015 +"2015-04-05","Passover - Chol HaMoed","IL",2015 +"2015-04-06","Passover - Chol HaMoed","IL",2015 +"2015-04-07","Passover - Chol HaMoed","IL",2015 +"2015-04-08","Passover - Chol HaMoed","IL",2015 +"2015-04-09","Passover VII - Eve","IL",2015 +"2015-04-10","Passover VII","IL",2015 +"2015-04-22","Memorial Day (Observed)","IL",2015 +"2015-04-23","Independence Day (Observed)","IL",2015 +"2015-05-07","Lag B'Omer","IL",2015 +"2015-05-23","Shavuot - Eve","IL",2015 +"2015-05-24","Shavuot","IL",2015 +"2015-09-13","Rosh Hashanah - Eve","IL",2015 +"2015-09-14","Rosh Hashanah","IL",2015 +"2015-09-15","Rosh Hashanah","IL",2015 +"2015-09-22","Yom Kippur - Eve","IL",2015 +"2015-09-23","Yom Kippur","IL",2015 +"2015-09-27","Sukkot I - Eve","IL",2015 +"2015-09-28","Sukkot I","IL",2015 +"2015-09-29","Sukkot - Chol HaMoed","IL",2015 +"2015-09-30","Sukkot - Chol HaMoed","IL",2015 +"2015-10-01","Sukkot - Chol HaMoed","IL",2015 +"2015-10-02","Sukkot - Chol HaMoed","IL",2015 +"2015-10-03","Sukkot - Chol HaMoed","IL",2015 +"2015-10-04","Sukkot VII - Eve","IL",2015 +"2015-10-05","Sukkot VII","IL",2015 +"2015-12-07","Hanukkah","IL",2015 +"2015-12-08","Hanukkah","IL",2015 +"2015-12-09","Hanukkah","IL",2015 +"2015-12-10","Hanukkah","IL",2015 +"2015-12-11","Hanukkah","IL",2015 +"2015-12-12","Hanukkah","IL",2015 +"2015-12-13","Hanukkah","IL",2015 +"2015-12-14","Hanukkah","IL",2015 +"2016-03-23","Purim - Eve","IL",2016 +"2016-03-24","Purim","IL",2016 +"2016-03-25","Shushan Purim","IL",2016 +"2016-04-22","Passover I - Eve","IL",2016 +"2016-04-23","Passover I","IL",2016 +"2016-04-24","Passover - Chol HaMoed","IL",2016 +"2016-04-25","Passover - Chol HaMoed","IL",2016 +"2016-04-26","Passover - Chol HaMoed","IL",2016 +"2016-04-27","Passover - Chol HaMoed","IL",2016 +"2016-04-28","Passover VII - Eve","IL",2016 +"2016-04-29","Passover VII","IL",2016 +"2016-05-11","Memorial Day (Observed)","IL",2016 +"2016-05-12","Independence Day (Observed)","IL",2016 +"2016-05-26","Lag B'Omer","IL",2016 +"2016-06-11","Shavuot - Eve","IL",2016 +"2016-06-12","Shavuot","IL",2016 +"2016-10-02","Rosh Hashanah - Eve","IL",2016 +"2016-10-03","Rosh Hashanah","IL",2016 +"2016-10-04","Rosh Hashanah","IL",2016 +"2016-10-11","Yom Kippur - Eve","IL",2016 +"2016-10-12","Yom Kippur","IL",2016 +"2016-10-16","Sukkot I - Eve","IL",2016 +"2016-10-17","Sukkot I","IL",2016 +"2016-10-18","Sukkot - Chol HaMoed","IL",2016 +"2016-10-19","Sukkot - Chol HaMoed","IL",2016 +"2016-10-20","Sukkot - Chol HaMoed","IL",2016 +"2016-10-21","Sukkot - Chol HaMoed","IL",2016 +"2016-10-22","Sukkot - Chol HaMoed","IL",2016 +"2016-10-23","Sukkot VII - Eve","IL",2016 +"2016-10-24","Sukkot VII","IL",2016 +"2016-12-25","Hanukkah","IL",2016 +"2016-12-26","Hanukkah","IL",2016 +"2016-12-27","Hanukkah","IL",2016 +"2016-12-28","Hanukkah","IL",2016 +"2016-12-29","Hanukkah","IL",2016 +"2016-12-30","Hanukkah","IL",2016 +"2016-12-31","Hanukkah","IL",2016 +"2017-01-01","Hanukkah","IL",2017 +"2017-03-11","Purim - Eve","IL",2017 +"2017-03-12","Purim","IL",2017 +"2017-03-13","Shushan Purim","IL",2017 +"2017-04-10","Passover I - Eve","IL",2017 +"2017-04-11","Passover I","IL",2017 +"2017-04-12","Passover - Chol HaMoed","IL",2017 +"2017-04-13","Passover - Chol HaMoed","IL",2017 +"2017-04-14","Passover - Chol HaMoed","IL",2017 +"2017-04-15","Passover - Chol HaMoed","IL",2017 +"2017-04-16","Passover VII - Eve","IL",2017 +"2017-04-17","Passover VII","IL",2017 +"2017-05-01","Memorial Day (Observed)","IL",2017 +"2017-05-02","Independence Day (Observed)","IL",2017 +"2017-05-14","Lag B'Omer","IL",2017 +"2017-05-30","Shavuot - Eve","IL",2017 +"2017-05-31","Shavuot","IL",2017 +"2017-09-20","Rosh Hashanah - Eve","IL",2017 +"2017-09-21","Rosh Hashanah","IL",2017 +"2017-09-22","Rosh Hashanah","IL",2017 +"2017-09-29","Yom Kippur - Eve","IL",2017 +"2017-09-30","Yom Kippur","IL",2017 +"2017-10-04","Sukkot I - Eve","IL",2017 +"2017-10-05","Sukkot I","IL",2017 +"2017-10-06","Sukkot - Chol HaMoed","IL",2017 +"2017-10-07","Sukkot - Chol HaMoed","IL",2017 +"2017-10-08","Sukkot - Chol HaMoed","IL",2017 +"2017-10-09","Sukkot - Chol HaMoed","IL",2017 +"2017-10-10","Sukkot - Chol HaMoed","IL",2017 +"2017-10-11","Sukkot VII - Eve","IL",2017 +"2017-10-12","Sukkot VII","IL",2017 +"2017-12-13","Hanukkah","IL",2017 +"2017-12-14","Hanukkah","IL",2017 +"2017-12-15","Hanukkah","IL",2017 +"2017-12-16","Hanukkah","IL",2017 +"2017-12-17","Hanukkah","IL",2017 +"2017-12-18","Hanukkah","IL",2017 +"2017-12-19","Hanukkah","IL",2017 +"2017-12-20","Hanukkah","IL",2017 +"2018-02-28","Purim - Eve","IL",2018 +"2018-03-01","Purim","IL",2018 +"2018-03-02","Shushan Purim","IL",2018 +"2018-03-30","Passover I - Eve","IL",2018 +"2018-03-31","Passover I","IL",2018 +"2018-04-01","Passover - Chol HaMoed","IL",2018 +"2018-04-02","Passover - Chol HaMoed","IL",2018 +"2018-04-03","Passover - Chol HaMoed","IL",2018 +"2018-04-04","Passover - Chol HaMoed","IL",2018 +"2018-04-05","Passover VII - Eve","IL",2018 +"2018-04-06","Passover VII","IL",2018 +"2018-04-18","Memorial Day (Observed)","IL",2018 +"2018-04-19","Independence Day (Observed)","IL",2018 +"2018-05-03","Lag B'Omer","IL",2018 +"2018-05-19","Shavuot - Eve","IL",2018 +"2018-05-20","Shavuot","IL",2018 +"2018-09-09","Rosh Hashanah - Eve","IL",2018 +"2018-09-10","Rosh Hashanah","IL",2018 +"2018-09-11","Rosh Hashanah","IL",2018 +"2018-09-18","Yom Kippur - Eve","IL",2018 +"2018-09-19","Yom Kippur","IL",2018 +"2018-09-23","Sukkot I - Eve","IL",2018 +"2018-09-24","Sukkot I","IL",2018 +"2018-09-25","Sukkot - Chol HaMoed","IL",2018 +"2018-09-26","Sukkot - Chol HaMoed","IL",2018 +"2018-09-27","Sukkot - Chol HaMoed","IL",2018 +"2018-09-28","Sukkot - Chol HaMoed","IL",2018 +"2018-09-29","Sukkot - Chol HaMoed","IL",2018 +"2018-09-30","Sukkot VII - Eve","IL",2018 +"2018-10-01","Sukkot VII","IL",2018 +"2018-12-03","Hanukkah","IL",2018 +"2018-12-04","Hanukkah","IL",2018 +"2018-12-05","Hanukkah","IL",2018 +"2018-12-06","Hanukkah","IL",2018 +"2018-12-07","Hanukkah","IL",2018 +"2018-12-08","Hanukkah","IL",2018 +"2018-12-09","Hanukkah","IL",2018 +"2018-12-10","Hanukkah","IL",2018 +"2019-03-20","Purim - Eve","IL",2019 +"2019-03-21","Purim","IL",2019 +"2019-03-22","Shushan Purim","IL",2019 +"2019-04-19","Passover I - Eve","IL",2019 +"2019-04-20","Passover I","IL",2019 +"2019-04-21","Passover - Chol HaMoed","IL",2019 +"2019-04-22","Passover - Chol HaMoed","IL",2019 +"2019-04-23","Passover - Chol HaMoed","IL",2019 +"2019-04-24","Passover - Chol HaMoed","IL",2019 +"2019-04-25","Passover VII - Eve","IL",2019 +"2019-04-26","Passover VII","IL",2019 +"2019-05-08","Memorial Day (Observed)","IL",2019 +"2019-05-09","Independence Day (Observed)","IL",2019 +"2019-05-23","Lag B'Omer","IL",2019 +"2019-06-08","Shavuot - Eve","IL",2019 +"2019-06-09","Shavuot","IL",2019 +"2019-09-29","Rosh Hashanah - Eve","IL",2019 +"2019-09-30","Rosh Hashanah","IL",2019 +"2019-10-01","Rosh Hashanah","IL",2019 +"2019-10-08","Yom Kippur - Eve","IL",2019 +"2019-10-09","Yom Kippur","IL",2019 +"2019-10-13","Sukkot I - Eve","IL",2019 +"2019-10-14","Sukkot I","IL",2019 +"2019-10-15","Sukkot - Chol HaMoed","IL",2019 +"2019-10-16","Sukkot - Chol HaMoed","IL",2019 +"2019-10-17","Sukkot - Chol HaMoed","IL",2019 +"2019-10-18","Sukkot - Chol HaMoed","IL",2019 +"2019-10-19","Sukkot - Chol HaMoed","IL",2019 +"2019-10-20","Sukkot VII - Eve","IL",2019 +"2019-10-21","Sukkot VII","IL",2019 +"2019-12-23","Hanukkah","IL",2019 +"2019-12-24","Hanukkah","IL",2019 +"2019-12-25","Hanukkah","IL",2019 +"2019-12-26","Hanukkah","IL",2019 +"2019-12-27","Hanukkah","IL",2019 +"2019-12-28","Hanukkah","IL",2019 +"2019-12-29","Hanukkah","IL",2019 +"2019-12-30","Hanukkah","IL",2019 +"2020-03-09","Purim - Eve","IL",2020 +"2020-03-10","Purim","IL",2020 +"2020-03-11","Shushan Purim","IL",2020 +"2020-04-08","Passover I - Eve","IL",2020 +"2020-04-09","Passover I","IL",2020 +"2020-04-10","Passover - Chol HaMoed","IL",2020 +"2020-04-11","Passover - Chol HaMoed","IL",2020 +"2020-04-12","Passover - Chol HaMoed","IL",2020 +"2020-04-13","Passover - Chol HaMoed","IL",2020 +"2020-04-14","Passover VII - Eve","IL",2020 +"2020-04-15","Passover VII","IL",2020 +"2020-04-28","Memorial Day","IL",2020 +"2020-04-29","Independence Day","IL",2020 +"2020-05-12","Lag B'Omer","IL",2020 +"2020-05-28","Shavuot - Eve","IL",2020 +"2020-05-29","Shavuot","IL",2020 +"2020-09-18","Rosh Hashanah - Eve","IL",2020 +"2020-09-19","Rosh Hashanah","IL",2020 +"2020-09-20","Rosh Hashanah","IL",2020 +"2020-09-27","Yom Kippur - Eve","IL",2020 +"2020-09-28","Yom Kippur","IL",2020 +"2020-10-02","Sukkot I - Eve","IL",2020 +"2020-10-03","Sukkot I","IL",2020 +"2020-10-04","Sukkot - Chol HaMoed","IL",2020 +"2020-10-05","Sukkot - Chol HaMoed","IL",2020 +"2020-10-06","Sukkot - Chol HaMoed","IL",2020 +"2020-10-07","Sukkot - Chol HaMoed","IL",2020 +"2020-10-08","Sukkot - Chol HaMoed","IL",2020 +"2020-10-09","Sukkot VII - Eve","IL",2020 +"2020-10-10","Sukkot VII","IL",2020 +"2020-12-11","Hanukkah","IL",2020 +"2020-12-12","Hanukkah","IL",2020 +"2020-12-13","Hanukkah","IL",2020 +"2020-12-14","Hanukkah","IL",2020 +"2020-12-15","Hanukkah","IL",2020 +"2020-12-16","Hanukkah","IL",2020 +"2020-12-17","Hanukkah","IL",2020 +"2020-12-18","Hanukkah","IL",2020 +"2021-02-25","Purim - Eve","IL",2021 +"2021-02-26","Purim","IL",2021 +"2021-02-27","Shushan Purim","IL",2021 +"2021-03-27","Passover I - Eve","IL",2021 +"2021-03-28","Passover I","IL",2021 +"2021-03-29","Passover - Chol HaMoed","IL",2021 +"2021-03-30","Passover - Chol HaMoed","IL",2021 +"2021-03-31","Passover - Chol HaMoed","IL",2021 +"2021-04-01","Passover - Chol HaMoed","IL",2021 +"2021-04-02","Passover VII - Eve","IL",2021 +"2021-04-03","Passover VII","IL",2021 +"2021-04-14","Memorial Day (Observed)","IL",2021 +"2021-04-15","Independence Day (Observed)","IL",2021 +"2021-04-30","Lag B'Omer","IL",2021 +"2021-05-16","Shavuot - Eve","IL",2021 +"2021-05-17","Shavuot","IL",2021 +"2021-09-06","Rosh Hashanah - Eve","IL",2021 +"2021-09-07","Rosh Hashanah","IL",2021 +"2021-09-08","Rosh Hashanah","IL",2021 +"2021-09-15","Yom Kippur - Eve","IL",2021 +"2021-09-16","Yom Kippur","IL",2021 +"2021-09-20","Sukkot I - Eve","IL",2021 +"2021-09-21","Sukkot I","IL",2021 +"2021-09-22","Sukkot - Chol HaMoed","IL",2021 +"2021-09-23","Sukkot - Chol HaMoed","IL",2021 +"2021-09-24","Sukkot - Chol HaMoed","IL",2021 +"2021-09-25","Sukkot - Chol HaMoed","IL",2021 +"2021-09-26","Sukkot - Chol HaMoed","IL",2021 +"2021-09-27","Sukkot VII - Eve","IL",2021 +"2021-09-28","Sukkot VII","IL",2021 +"2021-11-29","Hanukkah","IL",2021 +"2021-11-30","Hanukkah","IL",2021 +"2021-12-01","Hanukkah","IL",2021 +"2021-12-02","Hanukkah","IL",2021 +"2021-12-03","Hanukkah","IL",2021 +"2021-12-04","Hanukkah","IL",2021 +"2021-12-05","Hanukkah","IL",2021 +"2021-12-06","Hanukkah","IL",2021 +"2022-03-16","Purim - Eve","IL",2022 +"2022-03-17","Purim","IL",2022 +"2022-03-18","Shushan Purim","IL",2022 +"2022-04-15","Passover I - Eve","IL",2022 +"2022-04-16","Passover I","IL",2022 +"2022-04-17","Passover - Chol HaMoed","IL",2022 +"2022-04-18","Passover - Chol HaMoed","IL",2022 +"2022-04-19","Passover - Chol HaMoed","IL",2022 +"2022-04-20","Passover - Chol HaMoed","IL",2022 +"2022-04-21","Passover VII - Eve","IL",2022 +"2022-04-22","Passover VII","IL",2022 +"2022-05-04","Memorial Day (Observed)","IL",2022 +"2022-05-05","Independence Day (Observed)","IL",2022 +"2022-05-19","Lag B'Omer","IL",2022 +"2022-06-04","Shavuot - Eve","IL",2022 +"2022-06-05","Shavuot","IL",2022 +"2022-09-25","Rosh Hashanah - Eve","IL",2022 +"2022-09-26","Rosh Hashanah","IL",2022 +"2022-09-27","Rosh Hashanah","IL",2022 +"2022-10-04","Yom Kippur - Eve","IL",2022 +"2022-10-05","Yom Kippur","IL",2022 +"2022-10-09","Sukkot I - Eve","IL",2022 +"2022-10-10","Sukkot I","IL",2022 +"2022-10-11","Sukkot - Chol HaMoed","IL",2022 +"2022-10-12","Sukkot - Chol HaMoed","IL",2022 +"2022-10-13","Sukkot - Chol HaMoed","IL",2022 +"2022-10-14","Sukkot - Chol HaMoed","IL",2022 +"2022-10-15","Sukkot - Chol HaMoed","IL",2022 +"2022-10-16","Sukkot VII - Eve","IL",2022 +"2022-10-17","Sukkot VII","IL",2022 +"2022-12-19","Hanukkah","IL",2022 +"2022-12-20","Hanukkah","IL",2022 +"2022-12-21","Hanukkah","IL",2022 +"2022-12-22","Hanukkah","IL",2022 +"2022-12-23","Hanukkah","IL",2022 +"2022-12-24","Hanukkah","IL",2022 +"2022-12-25","Hanukkah","IL",2022 +"2022-12-26","Hanukkah","IL",2022 +"2023-03-06","Purim - Eve","IL",2023 +"2023-03-07","Purim","IL",2023 +"2023-03-08","Shushan Purim","IL",2023 +"2023-04-05","Passover I - Eve","IL",2023 +"2023-04-06","Passover I","IL",2023 +"2023-04-07","Passover - Chol HaMoed","IL",2023 +"2023-04-08","Passover - Chol HaMoed","IL",2023 +"2023-04-09","Passover - Chol HaMoed","IL",2023 +"2023-04-10","Passover - Chol HaMoed","IL",2023 +"2023-04-11","Passover VII - Eve","IL",2023 +"2023-04-12","Passover VII","IL",2023 +"2023-04-25","Memorial Day","IL",2023 +"2023-04-26","Independence Day","IL",2023 +"2023-05-09","Lag B'Omer","IL",2023 +"2023-05-25","Shavuot - Eve","IL",2023 +"2023-05-26","Shavuot","IL",2023 +"2023-09-15","Rosh Hashanah - Eve","IL",2023 +"2023-09-16","Rosh Hashanah","IL",2023 +"2023-09-17","Rosh Hashanah","IL",2023 +"2023-09-24","Yom Kippur - Eve","IL",2023 +"2023-09-25","Yom Kippur","IL",2023 +"2023-09-29","Sukkot I - Eve","IL",2023 +"2023-09-30","Sukkot I","IL",2023 +"2023-10-01","Sukkot - Chol HaMoed","IL",2023 +"2023-10-02","Sukkot - Chol HaMoed","IL",2023 +"2023-10-03","Sukkot - Chol HaMoed","IL",2023 +"2023-10-04","Sukkot - Chol HaMoed","IL",2023 +"2023-10-05","Sukkot - Chol HaMoed","IL",2023 +"2023-10-06","Sukkot VII - Eve","IL",2023 +"2023-10-07","Sukkot VII","IL",2023 +"2023-12-08","Hanukkah","IL",2023 +"2023-12-09","Hanukkah","IL",2023 +"2023-12-10","Hanukkah","IL",2023 +"2023-12-11","Hanukkah","IL",2023 +"2023-12-12","Hanukkah","IL",2023 +"2023-12-13","Hanukkah","IL",2023 +"2023-12-14","Hanukkah","IL",2023 +"2023-12-15","Hanukkah","IL",2023 +"2024-03-23","Purim - Eve","IL",2024 +"2024-03-24","Purim","IL",2024 +"2024-03-25","Shushan Purim","IL",2024 +"2024-04-22","Passover I - Eve","IL",2024 +"2024-04-23","Passover I","IL",2024 +"2024-04-24","Passover - Chol HaMoed","IL",2024 +"2024-04-25","Passover - Chol HaMoed","IL",2024 +"2024-04-26","Passover - Chol HaMoed","IL",2024 +"2024-04-27","Passover - Chol HaMoed","IL",2024 +"2024-04-28","Passover VII - Eve","IL",2024 +"2024-04-29","Passover VII","IL",2024 +"2024-05-13","Memorial Day (Observed)","IL",2024 +"2024-05-14","Independence Day (Observed)","IL",2024 +"2024-05-26","Lag B'Omer","IL",2024 +"2024-06-11","Shavuot - Eve","IL",2024 +"2024-06-12","Shavuot","IL",2024 +"2024-10-02","Rosh Hashanah - Eve","IL",2024 +"2024-10-03","Rosh Hashanah","IL",2024 +"2024-10-04","Rosh Hashanah","IL",2024 +"2024-10-11","Yom Kippur - Eve","IL",2024 +"2024-10-12","Yom Kippur","IL",2024 +"2024-10-16","Sukkot I - Eve","IL",2024 +"2024-10-17","Sukkot I","IL",2024 +"2024-10-18","Sukkot - Chol HaMoed","IL",2024 +"2024-10-19","Sukkot - Chol HaMoed","IL",2024 +"2024-10-20","Sukkot - Chol HaMoed","IL",2024 +"2024-10-21","Sukkot - Chol HaMoed","IL",2024 +"2024-10-22","Sukkot - Chol HaMoed","IL",2024 +"2024-10-23","Sukkot VII - Eve","IL",2024 +"2024-10-24","Sukkot VII","IL",2024 +"2024-12-26","Hanukkah","IL",2024 +"2024-12-27","Hanukkah","IL",2024 +"2024-12-28","Hanukkah","IL",2024 +"2024-12-29","Hanukkah","IL",2024 +"2024-12-30","Hanukkah","IL",2024 +"2024-12-31","Hanukkah","IL",2024 +"2025-01-01","Hanukkah","IL",2025 +"2025-01-02","Hanukkah","IL",2025 +"2025-03-13","Purim - Eve","IL",2025 +"2025-03-14","Purim","IL",2025 +"2025-03-15","Shushan Purim","IL",2025 +"2025-04-12","Passover I - Eve","IL",2025 +"2025-04-13","Passover I","IL",2025 +"2025-04-14","Passover - Chol HaMoed","IL",2025 +"2025-04-15","Passover - Chol HaMoed","IL",2025 +"2025-04-16","Passover - Chol HaMoed","IL",2025 +"2025-04-17","Passover - Chol HaMoed","IL",2025 +"2025-04-18","Passover VII - Eve","IL",2025 +"2025-04-19","Passover VII","IL",2025 +"2025-04-30","Memorial Day (Observed)","IL",2025 +"2025-05-01","Independence Day (Observed)","IL",2025 +"2025-05-16","Lag B'Omer","IL",2025 +"2025-06-01","Shavuot - Eve","IL",2025 +"2025-06-02","Shavuot","IL",2025 +"2025-09-22","Rosh Hashanah - Eve","IL",2025 +"2025-09-23","Rosh Hashanah","IL",2025 +"2025-09-24","Rosh Hashanah","IL",2025 +"2025-10-01","Yom Kippur - Eve","IL",2025 +"2025-10-02","Yom Kippur","IL",2025 +"2025-10-06","Sukkot I - Eve","IL",2025 +"2025-10-07","Sukkot I","IL",2025 +"2025-10-08","Sukkot - Chol HaMoed","IL",2025 +"2025-10-09","Sukkot - Chol HaMoed","IL",2025 +"2025-10-10","Sukkot - Chol HaMoed","IL",2025 +"2025-10-11","Sukkot - Chol HaMoed","IL",2025 +"2025-10-12","Sukkot - Chol HaMoed","IL",2025 +"2025-10-13","Sukkot VII - Eve","IL",2025 +"2025-10-14","Sukkot VII","IL",2025 +"2025-12-15","Hanukkah","IL",2025 +"2025-12-16","Hanukkah","IL",2025 +"2025-12-17","Hanukkah","IL",2025 +"2025-12-18","Hanukkah","IL",2025 +"2025-12-19","Hanukkah","IL",2025 +"2025-12-20","Hanukkah","IL",2025 +"2025-12-21","Hanukkah","IL",2025 +"2025-12-22","Hanukkah","IL",2025 +"2026-03-02","Purim - Eve","IL",2026 +"2026-03-03","Purim","IL",2026 +"2026-03-04","Shushan Purim","IL",2026 +"2026-04-01","Passover I - Eve","IL",2026 +"2026-04-02","Passover I","IL",2026 +"2026-04-03","Passover - Chol HaMoed","IL",2026 +"2026-04-04","Passover - Chol HaMoed","IL",2026 +"2026-04-05","Passover - Chol HaMoed","IL",2026 +"2026-04-06","Passover - Chol HaMoed","IL",2026 +"2026-04-07","Passover VII - Eve","IL",2026 +"2026-04-08","Passover VII","IL",2026 +"2026-04-21","Memorial Day","IL",2026 +"2026-04-22","Independence Day","IL",2026 +"2026-05-05","Lag B'Omer","IL",2026 +"2026-05-21","Shavuot - Eve","IL",2026 +"2026-05-22","Shavuot","IL",2026 +"2026-09-11","Rosh Hashanah - Eve","IL",2026 +"2026-09-12","Rosh Hashanah","IL",2026 +"2026-09-13","Rosh Hashanah","IL",2026 +"2026-09-20","Yom Kippur - Eve","IL",2026 +"2026-09-21","Yom Kippur","IL",2026 +"2026-09-25","Sukkot I - Eve","IL",2026 +"2026-09-26","Sukkot I","IL",2026 +"2026-09-27","Sukkot - Chol HaMoed","IL",2026 +"2026-09-28","Sukkot - Chol HaMoed","IL",2026 +"2026-09-29","Sukkot - Chol HaMoed","IL",2026 +"2026-09-30","Sukkot - Chol HaMoed","IL",2026 +"2026-10-01","Sukkot - Chol HaMoed","IL",2026 +"2026-10-02","Sukkot VII - Eve","IL",2026 +"2026-10-03","Sukkot VII","IL",2026 +"2026-12-05","Hanukkah","IL",2026 +"2026-12-06","Hanukkah","IL",2026 +"2026-12-07","Hanukkah","IL",2026 +"2026-12-08","Hanukkah","IL",2026 +"2026-12-09","Hanukkah","IL",2026 +"2026-12-10","Hanukkah","IL",2026 +"2026-12-11","Hanukkah","IL",2026 +"2026-12-12","Hanukkah","IL",2026 +"2027-03-22","Purim - Eve","IL",2027 +"2027-03-23","Purim","IL",2027 +"2027-03-24","Shushan Purim","IL",2027 +"2027-04-21","Passover I - Eve","IL",2027 +"2027-04-22","Passover I","IL",2027 +"2027-04-23","Passover - Chol HaMoed","IL",2027 +"2027-04-24","Passover - Chol HaMoed","IL",2027 +"2027-04-25","Passover - Chol HaMoed","IL",2027 +"2027-04-26","Passover - Chol HaMoed","IL",2027 +"2027-04-27","Passover VII - Eve","IL",2027 +"2027-04-28","Passover VII","IL",2027 +"2027-05-11","Memorial Day","IL",2027 +"2027-05-12","Independence Day","IL",2027 +"2027-05-25","Lag B'Omer","IL",2027 +"2027-06-10","Shavuot - Eve","IL",2027 +"2027-06-11","Shavuot","IL",2027 +"2027-10-01","Rosh Hashanah - Eve","IL",2027 +"2027-10-02","Rosh Hashanah","IL",2027 +"2027-10-03","Rosh Hashanah","IL",2027 +"2027-10-10","Yom Kippur - Eve","IL",2027 +"2027-10-11","Yom Kippur","IL",2027 +"2027-10-15","Sukkot I - Eve","IL",2027 +"2027-10-16","Sukkot I","IL",2027 +"2027-10-17","Sukkot - Chol HaMoed","IL",2027 +"2027-10-18","Sukkot - Chol HaMoed","IL",2027 +"2027-10-19","Sukkot - Chol HaMoed","IL",2027 +"2027-10-20","Sukkot - Chol HaMoed","IL",2027 +"2027-10-21","Sukkot - Chol HaMoed","IL",2027 +"2027-10-22","Sukkot VII - Eve","IL",2027 +"2027-10-23","Sukkot VII","IL",2027 +"2027-12-25","Hanukkah","IL",2027 +"2027-12-26","Hanukkah","IL",2027 +"2027-12-27","Hanukkah","IL",2027 +"2027-12-28","Hanukkah","IL",2027 +"2027-12-29","Hanukkah","IL",2027 +"2027-12-30","Hanukkah","IL",2027 +"2027-12-31","Hanukkah","IL",2027 +"2028-01-01","Hanukkah","IL",2028 +"2028-03-11","Purim - Eve","IL",2028 +"2028-03-12","Purim","IL",2028 +"2028-03-13","Shushan Purim","IL",2028 +"2028-04-10","Passover I - Eve","IL",2028 +"2028-04-11","Passover I","IL",2028 +"2028-04-12","Passover - Chol HaMoed","IL",2028 +"2028-04-13","Passover - Chol HaMoed","IL",2028 +"2028-04-14","Passover - Chol HaMoed","IL",2028 +"2028-04-15","Passover - Chol HaMoed","IL",2028 +"2028-04-16","Passover VII - Eve","IL",2028 +"2028-04-17","Passover VII","IL",2028 +"2028-05-01","Memorial Day (Observed)","IL",2028 +"2028-05-02","Independence Day (Observed)","IL",2028 +"2028-05-14","Lag B'Omer","IL",2028 +"2028-05-30","Shavuot - Eve","IL",2028 +"2028-05-31","Shavuot","IL",2028 +"2028-09-20","Rosh Hashanah - Eve","IL",2028 +"2028-09-21","Rosh Hashanah","IL",2028 +"2028-09-22","Rosh Hashanah","IL",2028 +"2028-09-29","Yom Kippur - Eve","IL",2028 +"2028-09-30","Yom Kippur","IL",2028 +"2028-10-04","Sukkot I - Eve","IL",2028 +"2028-10-05","Sukkot I","IL",2028 +"2028-10-06","Sukkot - Chol HaMoed","IL",2028 +"2028-10-07","Sukkot - Chol HaMoed","IL",2028 +"2028-10-08","Sukkot - Chol HaMoed","IL",2028 +"2028-10-09","Sukkot - Chol HaMoed","IL",2028 +"2028-10-10","Sukkot - Chol HaMoed","IL",2028 +"2028-10-11","Sukkot VII - Eve","IL",2028 +"2028-10-12","Sukkot VII","IL",2028 +"2028-12-13","Hanukkah","IL",2028 +"2028-12-14","Hanukkah","IL",2028 +"2028-12-15","Hanukkah","IL",2028 +"2028-12-16","Hanukkah","IL",2028 +"2028-12-17","Hanukkah","IL",2028 +"2028-12-18","Hanukkah","IL",2028 +"2028-12-19","Hanukkah","IL",2028 +"2028-12-20","Hanukkah","IL",2028 +"2029-02-28","Purim - Eve","IL",2029 +"2029-03-01","Purim","IL",2029 +"2029-03-02","Shushan Purim","IL",2029 +"2029-03-30","Passover I - Eve","IL",2029 +"2029-03-31","Passover I","IL",2029 +"2029-04-01","Passover - Chol HaMoed","IL",2029 +"2029-04-02","Passover - Chol HaMoed","IL",2029 +"2029-04-03","Passover - Chol HaMoed","IL",2029 +"2029-04-04","Passover - Chol HaMoed","IL",2029 +"2029-04-05","Passover VII - Eve","IL",2029 +"2029-04-06","Passover VII","IL",2029 +"2029-04-18","Memorial Day (Observed)","IL",2029 +"2029-04-19","Independence Day (Observed)","IL",2029 +"2029-05-03","Lag B'Omer","IL",2029 +"2029-05-19","Shavuot - Eve","IL",2029 +"2029-05-20","Shavuot","IL",2029 +"2029-09-09","Rosh Hashanah - Eve","IL",2029 +"2029-09-10","Rosh Hashanah","IL",2029 +"2029-09-11","Rosh Hashanah","IL",2029 +"2029-09-18","Yom Kippur - Eve","IL",2029 +"2029-09-19","Yom Kippur","IL",2029 +"2029-09-23","Sukkot I - Eve","IL",2029 +"2029-09-24","Sukkot I","IL",2029 +"2029-09-25","Sukkot - Chol HaMoed","IL",2029 +"2029-09-26","Sukkot - Chol HaMoed","IL",2029 +"2029-09-27","Sukkot - Chol HaMoed","IL",2029 +"2029-09-28","Sukkot - Chol HaMoed","IL",2029 +"2029-09-29","Sukkot - Chol HaMoed","IL",2029 +"2029-09-30","Sukkot VII - Eve","IL",2029 +"2029-10-01","Sukkot VII","IL",2029 +"2029-12-02","Hanukkah","IL",2029 +"2029-12-03","Hanukkah","IL",2029 +"2029-12-04","Hanukkah","IL",2029 +"2029-12-05","Hanukkah","IL",2029 +"2029-12-06","Hanukkah","IL",2029 +"2029-12-07","Hanukkah","IL",2029 +"2029-12-08","Hanukkah","IL",2029 +"2029-12-09","Hanukkah","IL",2029 +"2030-03-18","Purim - Eve","IL",2030 +"2030-03-19","Purim","IL",2030 +"2030-03-20","Shushan Purim","IL",2030 +"2030-04-17","Passover I - Eve","IL",2030 +"2030-04-18","Passover I","IL",2030 +"2030-04-19","Passover - Chol HaMoed","IL",2030 +"2030-04-20","Passover - Chol HaMoed","IL",2030 +"2030-04-21","Passover - Chol HaMoed","IL",2030 +"2030-04-22","Passover - Chol HaMoed","IL",2030 +"2030-04-23","Passover VII - Eve","IL",2030 +"2030-04-24","Passover VII","IL",2030 +"2030-05-07","Memorial Day","IL",2030 +"2030-05-08","Independence Day","IL",2030 +"2030-05-21","Lag B'Omer","IL",2030 +"2030-06-06","Shavuot - Eve","IL",2030 +"2030-06-07","Shavuot","IL",2030 +"2030-09-27","Rosh Hashanah - Eve","IL",2030 +"2030-09-28","Rosh Hashanah","IL",2030 +"2030-09-29","Rosh Hashanah","IL",2030 +"2030-10-06","Yom Kippur - Eve","IL",2030 +"2030-10-07","Yom Kippur","IL",2030 +"2030-10-11","Sukkot I - Eve","IL",2030 +"2030-10-12","Sukkot I","IL",2030 +"2030-10-13","Sukkot - Chol HaMoed","IL",2030 +"2030-10-14","Sukkot - Chol HaMoed","IL",2030 +"2030-10-15","Sukkot - Chol HaMoed","IL",2030 +"2030-10-16","Sukkot - Chol HaMoed","IL",2030 +"2030-10-17","Sukkot - Chol HaMoed","IL",2030 +"2030-10-18","Sukkot VII - Eve","IL",2030 +"2030-10-19","Sukkot VII","IL",2030 +"2030-12-21","Hanukkah","IL",2030 +"2030-12-22","Hanukkah","IL",2030 +"2030-12-23","Hanukkah","IL",2030 +"2030-12-24","Hanukkah","IL",2030 +"2030-12-25","Hanukkah","IL",2030 +"2030-12-26","Hanukkah","IL",2030 +"2030-12-27","Hanukkah","IL",2030 +"2030-12-28","Hanukkah","IL",2030 +"2031-03-08","Purim - Eve","IL",2031 +"2031-03-09","Purim","IL",2031 +"2031-03-10","Shushan Purim","IL",2031 +"2031-04-07","Passover I - Eve","IL",2031 +"2031-04-08","Passover I","IL",2031 +"2031-04-09","Passover - Chol HaMoed","IL",2031 +"2031-04-10","Passover - Chol HaMoed","IL",2031 +"2031-04-11","Passover - Chol HaMoed","IL",2031 +"2031-04-12","Passover - Chol HaMoed","IL",2031 +"2031-04-13","Passover VII - Eve","IL",2031 +"2031-04-14","Passover VII","IL",2031 +"2031-04-28","Memorial Day (Observed)","IL",2031 +"2031-04-29","Independence Day (Observed)","IL",2031 +"2031-05-11","Lag B'Omer","IL",2031 +"2031-05-27","Shavuot - Eve","IL",2031 +"2031-05-28","Shavuot","IL",2031 +"2031-09-17","Rosh Hashanah - Eve","IL",2031 +"2031-09-18","Rosh Hashanah","IL",2031 +"2031-09-19","Rosh Hashanah","IL",2031 +"2031-09-26","Yom Kippur - Eve","IL",2031 +"2031-09-27","Yom Kippur","IL",2031 +"2031-10-01","Sukkot I - Eve","IL",2031 +"2031-10-02","Sukkot I","IL",2031 +"2031-10-03","Sukkot - Chol HaMoed","IL",2031 +"2031-10-04","Sukkot - Chol HaMoed","IL",2031 +"2031-10-05","Sukkot - Chol HaMoed","IL",2031 +"2031-10-06","Sukkot - Chol HaMoed","IL",2031 +"2031-10-07","Sukkot - Chol HaMoed","IL",2031 +"2031-10-08","Sukkot VII - Eve","IL",2031 +"2031-10-09","Sukkot VII","IL",2031 +"2031-12-10","Hanukkah","IL",2031 +"2031-12-11","Hanukkah","IL",2031 +"2031-12-12","Hanukkah","IL",2031 +"2031-12-13","Hanukkah","IL",2031 +"2031-12-14","Hanukkah","IL",2031 +"2031-12-15","Hanukkah","IL",2031 +"2031-12-16","Hanukkah","IL",2031 +"2031-12-17","Hanukkah","IL",2031 +"2032-02-25","Purim - Eve","IL",2032 +"2032-02-26","Purim","IL",2032 +"2032-02-27","Shushan Purim","IL",2032 +"2032-03-26","Passover I - Eve","IL",2032 +"2032-03-27","Passover I","IL",2032 +"2032-03-28","Passover - Chol HaMoed","IL",2032 +"2032-03-29","Passover - Chol HaMoed","IL",2032 +"2032-03-30","Passover - Chol HaMoed","IL",2032 +"2032-03-31","Passover - Chol HaMoed","IL",2032 +"2032-04-01","Passover VII - Eve","IL",2032 +"2032-04-02","Passover VII","IL",2032 +"2032-04-14","Memorial Day (Observed)","IL",2032 +"2032-04-15","Independence Day (Observed)","IL",2032 +"2032-04-29","Lag B'Omer","IL",2032 +"2032-05-15","Shavuot - Eve","IL",2032 +"2032-05-16","Shavuot","IL",2032 +"2032-09-05","Rosh Hashanah - Eve","IL",2032 +"2032-09-06","Rosh Hashanah","IL",2032 +"2032-09-07","Rosh Hashanah","IL",2032 +"2032-09-14","Yom Kippur - Eve","IL",2032 +"2032-09-15","Yom Kippur","IL",2032 +"2032-09-19","Sukkot I - Eve","IL",2032 +"2032-09-20","Sukkot I","IL",2032 +"2032-09-21","Sukkot - Chol HaMoed","IL",2032 +"2032-09-22","Sukkot - Chol HaMoed","IL",2032 +"2032-09-23","Sukkot - Chol HaMoed","IL",2032 +"2032-09-24","Sukkot - Chol HaMoed","IL",2032 +"2032-09-25","Sukkot - Chol HaMoed","IL",2032 +"2032-09-26","Sukkot VII - Eve","IL",2032 +"2032-09-27","Sukkot VII","IL",2032 +"2032-11-28","Hanukkah","IL",2032 +"2032-11-29","Hanukkah","IL",2032 +"2032-11-30","Hanukkah","IL",2032 +"2032-12-01","Hanukkah","IL",2032 +"2032-12-02","Hanukkah","IL",2032 +"2032-12-03","Hanukkah","IL",2032 +"2032-12-04","Hanukkah","IL",2032 +"2032-12-05","Hanukkah","IL",2032 +"2033-03-14","Purim - Eve","IL",2033 +"2033-03-15","Purim","IL",2033 +"2033-03-16","Shushan Purim","IL",2033 +"2033-04-13","Passover I - Eve","IL",2033 +"2033-04-14","Passover I","IL",2033 +"2033-04-15","Passover - Chol HaMoed","IL",2033 +"2033-04-16","Passover - Chol HaMoed","IL",2033 +"2033-04-17","Passover - Chol HaMoed","IL",2033 +"2033-04-18","Passover - Chol HaMoed","IL",2033 +"2033-04-19","Passover VII - Eve","IL",2033 +"2033-04-20","Passover VII","IL",2033 +"2033-05-03","Memorial Day","IL",2033 +"2033-05-04","Independence Day","IL",2033 +"2033-05-17","Lag B'Omer","IL",2033 +"2033-06-02","Shavuot - Eve","IL",2033 +"2033-06-03","Shavuot","IL",2033 +"2033-09-23","Rosh Hashanah - Eve","IL",2033 +"2033-09-24","Rosh Hashanah","IL",2033 +"2033-09-25","Rosh Hashanah","IL",2033 +"2033-10-02","Yom Kippur - Eve","IL",2033 +"2033-10-03","Yom Kippur","IL",2033 +"2033-10-07","Sukkot I - Eve","IL",2033 +"2033-10-08","Sukkot I","IL",2033 +"2033-10-09","Sukkot - Chol HaMoed","IL",2033 +"2033-10-10","Sukkot - Chol HaMoed","IL",2033 +"2033-10-11","Sukkot - Chol HaMoed","IL",2033 +"2033-10-12","Sukkot - Chol HaMoed","IL",2033 +"2033-10-13","Sukkot - Chol HaMoed","IL",2033 +"2033-10-14","Sukkot VII - Eve","IL",2033 +"2033-10-15","Sukkot VII","IL",2033 +"2033-12-17","Hanukkah","IL",2033 +"2033-12-18","Hanukkah","IL",2033 +"2033-12-19","Hanukkah","IL",2033 +"2033-12-20","Hanukkah","IL",2033 +"2033-12-21","Hanukkah","IL",2033 +"2033-12-22","Hanukkah","IL",2033 +"2033-12-23","Hanukkah","IL",2033 +"2033-12-24","Hanukkah","IL",2033 +"2034-03-04","Purim - Eve","IL",2034 +"2034-03-05","Purim","IL",2034 +"2034-03-06","Shushan Purim","IL",2034 +"2034-04-03","Passover I - Eve","IL",2034 +"2034-04-04","Passover I","IL",2034 +"2034-04-05","Passover - Chol HaMoed","IL",2034 +"2034-04-06","Passover - Chol HaMoed","IL",2034 +"2034-04-07","Passover - Chol HaMoed","IL",2034 +"2034-04-08","Passover - Chol HaMoed","IL",2034 +"2034-04-09","Passover VII - Eve","IL",2034 +"2034-04-10","Passover VII","IL",2034 +"2034-04-24","Memorial Day (Observed)","IL",2034 +"2034-04-25","Independence Day (Observed)","IL",2034 +"2034-05-07","Lag B'Omer","IL",2034 +"2034-05-23","Shavuot - Eve","IL",2034 +"2034-05-24","Shavuot","IL",2034 +"2034-09-13","Rosh Hashanah - Eve","IL",2034 +"2034-09-14","Rosh Hashanah","IL",2034 +"2034-09-15","Rosh Hashanah","IL",2034 +"2034-09-22","Yom Kippur - Eve","IL",2034 +"2034-09-23","Yom Kippur","IL",2034 +"2034-09-27","Sukkot I - Eve","IL",2034 +"2034-09-28","Sukkot I","IL",2034 +"2034-09-29","Sukkot - Chol HaMoed","IL",2034 +"2034-09-30","Sukkot - Chol HaMoed","IL",2034 +"2034-10-01","Sukkot - Chol HaMoed","IL",2034 +"2034-10-02","Sukkot - Chol HaMoed","IL",2034 +"2034-10-03","Sukkot - Chol HaMoed","IL",2034 +"2034-10-04","Sukkot VII - Eve","IL",2034 +"2034-10-05","Sukkot VII","IL",2034 +"2034-12-07","Hanukkah","IL",2034 +"2034-12-08","Hanukkah","IL",2034 +"2034-12-09","Hanukkah","IL",2034 +"2034-12-10","Hanukkah","IL",2034 +"2034-12-11","Hanukkah","IL",2034 +"2034-12-12","Hanukkah","IL",2034 +"2034-12-13","Hanukkah","IL",2034 +"2034-12-14","Hanukkah","IL",2034 +"2035-03-24","Purim - Eve","IL",2035 +"2035-03-25","Purim","IL",2035 +"2035-03-26","Shushan Purim","IL",2035 +"2035-04-23","Passover I - Eve","IL",2035 +"2035-04-24","Passover I","IL",2035 +"2035-04-25","Passover - Chol HaMoed","IL",2035 +"2035-04-26","Passover - Chol HaMoed","IL",2035 +"2035-04-27","Passover - Chol HaMoed","IL",2035 +"2035-04-28","Passover - Chol HaMoed","IL",2035 +"2035-04-29","Passover VII - Eve","IL",2035 +"2035-04-30","Passover VII","IL",2035 +"2035-05-14","Memorial Day (Observed)","IL",2035 +"2035-05-15","Independence Day (Observed)","IL",2035 +"2035-05-27","Lag B'Omer","IL",2035 +"2035-06-12","Shavuot - Eve","IL",2035 +"2035-06-13","Shavuot","IL",2035 +"2035-10-03","Rosh Hashanah - Eve","IL",2035 +"2035-10-04","Rosh Hashanah","IL",2035 +"2035-10-05","Rosh Hashanah","IL",2035 +"2035-10-12","Yom Kippur - Eve","IL",2035 +"2035-10-13","Yom Kippur","IL",2035 +"2035-10-17","Sukkot I - Eve","IL",2035 +"2035-10-18","Sukkot I","IL",2035 +"2035-10-19","Sukkot - Chol HaMoed","IL",2035 +"2035-10-20","Sukkot - Chol HaMoed","IL",2035 +"2035-10-21","Sukkot - Chol HaMoed","IL",2035 +"2035-10-22","Sukkot - Chol HaMoed","IL",2035 +"2035-10-23","Sukkot - Chol HaMoed","IL",2035 +"2035-10-24","Sukkot VII - Eve","IL",2035 +"2035-10-25","Sukkot VII","IL",2035 +"2035-12-26","Hanukkah","IL",2035 +"2035-12-27","Hanukkah","IL",2035 +"2035-12-28","Hanukkah","IL",2035 +"2035-12-29","Hanukkah","IL",2035 +"2035-12-30","Hanukkah","IL",2035 +"2035-12-31","Hanukkah","IL",2035 +"2036-01-01","Hanukkah","IL",2036 +"2036-01-02","Hanukkah","IL",2036 +"2036-03-12","Purim - Eve","IL",2036 +"2036-03-13","Purim","IL",2036 +"2036-03-14","Shushan Purim","IL",2036 +"2036-04-11","Passover I - Eve","IL",2036 +"2036-04-12","Passover I","IL",2036 +"2036-04-13","Passover - Chol HaMoed","IL",2036 +"2036-04-14","Passover - Chol HaMoed","IL",2036 +"2036-04-15","Passover - Chol HaMoed","IL",2036 +"2036-04-16","Passover - Chol HaMoed","IL",2036 +"2036-04-17","Passover VII - Eve","IL",2036 +"2036-04-18","Passover VII","IL",2036 +"2036-04-30","Memorial Day (Observed)","IL",2036 +"2036-05-01","Independence Day (Observed)","IL",2036 +"2036-05-15","Lag B'Omer","IL",2036 +"2036-05-31","Shavuot - Eve","IL",2036 +"2036-06-01","Shavuot","IL",2036 +"2036-09-21","Rosh Hashanah - Eve","IL",2036 +"2036-09-22","Rosh Hashanah","IL",2036 +"2036-09-23","Rosh Hashanah","IL",2036 +"2036-09-30","Yom Kippur - Eve","IL",2036 +"2036-10-01","Yom Kippur","IL",2036 +"2036-10-05","Sukkot I - Eve","IL",2036 +"2036-10-06","Sukkot I","IL",2036 +"2036-10-07","Sukkot - Chol HaMoed","IL",2036 +"2036-10-08","Sukkot - Chol HaMoed","IL",2036 +"2036-10-09","Sukkot - Chol HaMoed","IL",2036 +"2036-10-10","Sukkot - Chol HaMoed","IL",2036 +"2036-10-11","Sukkot - Chol HaMoed","IL",2036 +"2036-10-12","Sukkot VII - Eve","IL",2036 +"2036-10-13","Sukkot VII","IL",2036 +"2036-12-14","Hanukkah","IL",2036 +"2036-12-15","Hanukkah","IL",2036 +"2036-12-16","Hanukkah","IL",2036 +"2036-12-17","Hanukkah","IL",2036 +"2036-12-18","Hanukkah","IL",2036 +"2036-12-19","Hanukkah","IL",2036 +"2036-12-20","Hanukkah","IL",2036 +"2036-12-21","Hanukkah","IL",2036 +"2037-02-28","Purim - Eve","IL",2037 +"2037-03-01","Purim","IL",2037 +"2037-03-02","Shushan Purim","IL",2037 +"2037-03-30","Passover I - Eve","IL",2037 +"2037-03-31","Passover I","IL",2037 +"2037-04-01","Passover - Chol HaMoed","IL",2037 +"2037-04-02","Passover - Chol HaMoed","IL",2037 +"2037-04-03","Passover - Chol HaMoed","IL",2037 +"2037-04-04","Passover - Chol HaMoed","IL",2037 +"2037-04-05","Passover VII - Eve","IL",2037 +"2037-04-06","Passover VII","IL",2037 +"2037-04-20","Memorial Day (Observed)","IL",2037 +"2037-04-21","Independence Day (Observed)","IL",2037 +"2037-05-03","Lag B'Omer","IL",2037 +"2037-05-19","Shavuot - Eve","IL",2037 +"2037-05-20","Shavuot","IL",2037 +"2037-09-09","Rosh Hashanah - Eve","IL",2037 +"2037-09-10","Rosh Hashanah","IL",2037 +"2037-09-11","Rosh Hashanah","IL",2037 +"2037-09-18","Yom Kippur - Eve","IL",2037 +"2037-09-19","Yom Kippur","IL",2037 +"2037-09-23","Sukkot I - Eve","IL",2037 +"2037-09-24","Sukkot I","IL",2037 +"2037-09-25","Sukkot - Chol HaMoed","IL",2037 +"2037-09-26","Sukkot - Chol HaMoed","IL",2037 +"2037-09-27","Sukkot - Chol HaMoed","IL",2037 +"2037-09-28","Sukkot - Chol HaMoed","IL",2037 +"2037-09-29","Sukkot - Chol HaMoed","IL",2037 +"2037-09-30","Sukkot VII - Eve","IL",2037 +"2037-10-01","Sukkot VII","IL",2037 +"2037-12-03","Hanukkah","IL",2037 +"2037-12-04","Hanukkah","IL",2037 +"2037-12-05","Hanukkah","IL",2037 +"2037-12-06","Hanukkah","IL",2037 +"2037-12-07","Hanukkah","IL",2037 +"2037-12-08","Hanukkah","IL",2037 +"2037-12-09","Hanukkah","IL",2037 +"2037-12-10","Hanukkah","IL",2037 +"2038-03-20","Purim - Eve","IL",2038 +"2038-03-21","Purim","IL",2038 +"2038-03-22","Shushan Purim","IL",2038 +"2038-04-19","Passover I - Eve","IL",2038 +"2038-04-20","Passover I","IL",2038 +"2038-04-21","Passover - Chol HaMoed","IL",2038 +"2038-04-22","Passover - Chol HaMoed","IL",2038 +"2038-04-23","Passover - Chol HaMoed","IL",2038 +"2038-04-24","Passover - Chol HaMoed","IL",2038 +"2038-04-25","Passover VII - Eve","IL",2038 +"2038-04-26","Passover VII","IL",2038 +"2038-05-10","Memorial Day (Observed)","IL",2038 +"2038-05-11","Independence Day (Observed)","IL",2038 +"2038-05-23","Lag B'Omer","IL",2038 +"2038-06-08","Shavuot - Eve","IL",2038 +"2038-06-09","Shavuot","IL",2038 +"2038-09-29","Rosh Hashanah - Eve","IL",2038 +"2038-09-30","Rosh Hashanah","IL",2038 +"2038-10-01","Rosh Hashanah","IL",2038 +"2038-10-08","Yom Kippur - Eve","IL",2038 +"2038-10-09","Yom Kippur","IL",2038 +"2038-10-13","Sukkot I - Eve","IL",2038 +"2038-10-14","Sukkot I","IL",2038 +"2038-10-15","Sukkot - Chol HaMoed","IL",2038 +"2038-10-16","Sukkot - Chol HaMoed","IL",2038 +"2038-10-17","Sukkot - Chol HaMoed","IL",2038 +"2038-10-18","Sukkot - Chol HaMoed","IL",2038 +"2038-10-19","Sukkot - Chol HaMoed","IL",2038 +"2038-10-20","Sukkot VII - Eve","IL",2038 +"2038-10-21","Sukkot VII","IL",2038 +"2038-12-22","Hanukkah","IL",2038 +"2038-12-23","Hanukkah","IL",2038 +"2038-12-24","Hanukkah","IL",2038 +"2038-12-25","Hanukkah","IL",2038 +"2038-12-26","Hanukkah","IL",2038 +"2038-12-27","Hanukkah","IL",2038 +"2038-12-28","Hanukkah","IL",2038 +"2038-12-29","Hanukkah","IL",2038 +"2039-03-09","Purim - Eve","IL",2039 +"2039-03-10","Purim","IL",2039 +"2039-03-11","Shushan Purim","IL",2039 +"2039-04-08","Passover I - Eve","IL",2039 +"2039-04-09","Passover I","IL",2039 +"2039-04-10","Passover - Chol HaMoed","IL",2039 +"2039-04-11","Passover - Chol HaMoed","IL",2039 +"2039-04-12","Passover - Chol HaMoed","IL",2039 +"2039-04-13","Passover - Chol HaMoed","IL",2039 +"2039-04-14","Passover VII - Eve","IL",2039 +"2039-04-15","Passover VII","IL",2039 +"2039-04-27","Memorial Day (Observed)","IL",2039 +"2039-04-28","Independence Day (Observed)","IL",2039 +"2039-05-12","Lag B'Omer","IL",2039 +"2039-05-28","Shavuot - Eve","IL",2039 +"2039-05-29","Shavuot","IL",2039 +"2039-09-18","Rosh Hashanah - Eve","IL",2039 +"2039-09-19","Rosh Hashanah","IL",2039 +"2039-09-20","Rosh Hashanah","IL",2039 +"2039-09-27","Yom Kippur - Eve","IL",2039 +"2039-09-28","Yom Kippur","IL",2039 +"2039-10-02","Sukkot I - Eve","IL",2039 +"2039-10-03","Sukkot I","IL",2039 +"2039-10-04","Sukkot - Chol HaMoed","IL",2039 +"2039-10-05","Sukkot - Chol HaMoed","IL",2039 +"2039-10-06","Sukkot - Chol HaMoed","IL",2039 +"2039-10-07","Sukkot - Chol HaMoed","IL",2039 +"2039-10-08","Sukkot - Chol HaMoed","IL",2039 +"2039-10-09","Sukkot VII - Eve","IL",2039 +"2039-10-10","Sukkot VII","IL",2039 +"2039-12-12","Hanukkah","IL",2039 +"2039-12-13","Hanukkah","IL",2039 +"2039-12-14","Hanukkah","IL",2039 +"2039-12-15","Hanukkah","IL",2039 +"2039-12-16","Hanukkah","IL",2039 +"2039-12-17","Hanukkah","IL",2039 +"2039-12-18","Hanukkah","IL",2039 +"2039-12-19","Hanukkah","IL",2039 +"2040-02-27","Purim - Eve","IL",2040 +"2040-02-28","Purim","IL",2040 +"2040-02-29","Shushan Purim","IL",2040 +"2040-03-28","Passover I - Eve","IL",2040 +"2040-03-29","Passover I","IL",2040 +"2040-03-30","Passover - Chol HaMoed","IL",2040 +"2040-03-31","Passover - Chol HaMoed","IL",2040 +"2040-04-01","Passover - Chol HaMoed","IL",2040 +"2040-04-02","Passover - Chol HaMoed","IL",2040 +"2040-04-03","Passover VII - Eve","IL",2040 +"2040-04-04","Passover VII","IL",2040 +"2040-04-17","Memorial Day","IL",2040 +"2040-04-18","Independence Day","IL",2040 +"2040-05-01","Lag B'Omer","IL",2040 +"2040-05-17","Shavuot - Eve","IL",2040 +"2040-05-18","Shavuot","IL",2040 +"2040-09-07","Rosh Hashanah - Eve","IL",2040 +"2040-09-08","Rosh Hashanah","IL",2040 +"2040-09-09","Rosh Hashanah","IL",2040 +"2040-09-16","Yom Kippur - Eve","IL",2040 +"2040-09-17","Yom Kippur","IL",2040 +"2040-09-21","Sukkot I - Eve","IL",2040 +"2040-09-22","Sukkot I","IL",2040 +"2040-09-23","Sukkot - Chol HaMoed","IL",2040 +"2040-09-24","Sukkot - Chol HaMoed","IL",2040 +"2040-09-25","Sukkot - Chol HaMoed","IL",2040 +"2040-09-26","Sukkot - Chol HaMoed","IL",2040 +"2040-09-27","Sukkot - Chol HaMoed","IL",2040 +"2040-09-28","Sukkot VII - Eve","IL",2040 +"2040-09-29","Sukkot VII","IL",2040 +"2040-11-30","Hanukkah","IL",2040 +"2040-12-01","Hanukkah","IL",2040 +"2040-12-02","Hanukkah","IL",2040 +"2040-12-03","Hanukkah","IL",2040 +"2040-12-04","Hanukkah","IL",2040 +"2040-12-05","Hanukkah","IL",2040 +"2040-12-06","Hanukkah","IL",2040 +"2040-12-07","Hanukkah","IL",2040 +"2041-03-16","Purim - Eve","IL",2041 +"2041-03-17","Purim","IL",2041 +"2041-03-18","Shushan Purim","IL",2041 +"2041-04-15","Passover I - Eve","IL",2041 +"2041-04-16","Passover I","IL",2041 +"2041-04-17","Passover - Chol HaMoed","IL",2041 +"2041-04-18","Passover - Chol HaMoed","IL",2041 +"2041-04-19","Passover - Chol HaMoed","IL",2041 +"2041-04-20","Passover - Chol HaMoed","IL",2041 +"2041-04-21","Passover VII - Eve","IL",2041 +"2041-04-22","Passover VII","IL",2041 +"2041-05-06","Memorial Day (Observed)","IL",2041 +"2041-05-07","Independence Day (Observed)","IL",2041 +"2041-05-19","Lag B'Omer","IL",2041 +"2041-06-04","Shavuot - Eve","IL",2041 +"2041-06-05","Shavuot","IL",2041 +"2041-09-25","Rosh Hashanah - Eve","IL",2041 +"2041-09-26","Rosh Hashanah","IL",2041 +"2041-09-27","Rosh Hashanah","IL",2041 +"2041-10-04","Yom Kippur - Eve","IL",2041 +"2041-10-05","Yom Kippur","IL",2041 +"2041-10-09","Sukkot I - Eve","IL",2041 +"2041-10-10","Sukkot I","IL",2041 +"2041-10-11","Sukkot - Chol HaMoed","IL",2041 +"2041-10-12","Sukkot - Chol HaMoed","IL",2041 +"2041-10-13","Sukkot - Chol HaMoed","IL",2041 +"2041-10-14","Sukkot - Chol HaMoed","IL",2041 +"2041-10-15","Sukkot - Chol HaMoed","IL",2041 +"2041-10-16","Sukkot VII - Eve","IL",2041 +"2041-10-17","Sukkot VII","IL",2041 +"2041-12-18","Hanukkah","IL",2041 +"2041-12-19","Hanukkah","IL",2041 +"2041-12-20","Hanukkah","IL",2041 +"2041-12-21","Hanukkah","IL",2041 +"2041-12-22","Hanukkah","IL",2041 +"2041-12-23","Hanukkah","IL",2041 +"2041-12-24","Hanukkah","IL",2041 +"2041-12-25","Hanukkah","IL",2041 +"2042-03-05","Purim - Eve","IL",2042 +"2042-03-06","Purim","IL",2042 +"2042-03-07","Shushan Purim","IL",2042 +"2042-04-04","Passover I - Eve","IL",2042 +"2042-04-05","Passover I","IL",2042 +"2042-04-06","Passover - Chol HaMoed","IL",2042 +"2042-04-07","Passover - Chol HaMoed","IL",2042 +"2042-04-08","Passover - Chol HaMoed","IL",2042 +"2042-04-09","Passover - Chol HaMoed","IL",2042 +"2042-04-10","Passover VII - Eve","IL",2042 +"2042-04-11","Passover VII","IL",2042 +"2042-04-23","Memorial Day (Observed)","IL",2042 +"2042-04-24","Independence Day (Observed)","IL",2042 +"2042-05-08","Lag B'Omer","IL",2042 +"2042-05-24","Shavuot - Eve","IL",2042 +"2042-05-25","Shavuot","IL",2042 +"2042-09-14","Rosh Hashanah - Eve","IL",2042 +"2042-09-15","Rosh Hashanah","IL",2042 +"2042-09-16","Rosh Hashanah","IL",2042 +"2042-09-23","Yom Kippur - Eve","IL",2042 +"2042-09-24","Yom Kippur","IL",2042 +"2042-09-28","Sukkot I - Eve","IL",2042 +"2042-09-29","Sukkot I","IL",2042 +"2042-09-30","Sukkot - Chol HaMoed","IL",2042 +"2042-10-01","Sukkot - Chol HaMoed","IL",2042 +"2042-10-02","Sukkot - Chol HaMoed","IL",2042 +"2042-10-03","Sukkot - Chol HaMoed","IL",2042 +"2042-10-04","Sukkot - Chol HaMoed","IL",2042 +"2042-10-05","Sukkot VII - Eve","IL",2042 +"2042-10-06","Sukkot VII","IL",2042 +"2042-12-08","Hanukkah","IL",2042 +"2042-12-09","Hanukkah","IL",2042 +"2042-12-10","Hanukkah","IL",2042 +"2042-12-11","Hanukkah","IL",2042 +"2042-12-12","Hanukkah","IL",2042 +"2042-12-13","Hanukkah","IL",2042 +"2042-12-14","Hanukkah","IL",2042 +"2042-12-15","Hanukkah","IL",2042 +"2043-03-25","Purim - Eve","IL",2043 +"2043-03-26","Purim","IL",2043 +"2043-03-27","Shushan Purim","IL",2043 +"2043-04-24","Passover I - Eve","IL",2043 +"2043-04-25","Passover I","IL",2043 +"2043-04-26","Passover - Chol HaMoed","IL",2043 +"2043-04-27","Passover - Chol HaMoed","IL",2043 +"2043-04-28","Passover - Chol HaMoed","IL",2043 +"2043-04-29","Passover - Chol HaMoed","IL",2043 +"2043-04-30","Passover VII - Eve","IL",2043 +"2043-05-01","Passover VII","IL",2043 +"2043-05-13","Memorial Day (Observed)","IL",2043 +"2043-05-14","Independence Day (Observed)","IL",2043 +"2043-05-28","Lag B'Omer","IL",2043 +"2043-06-13","Shavuot - Eve","IL",2043 +"2043-06-14","Shavuot","IL",2043 +"2043-10-04","Rosh Hashanah - Eve","IL",2043 +"2043-10-05","Rosh Hashanah","IL",2043 +"2043-10-06","Rosh Hashanah","IL",2043 +"2043-10-13","Yom Kippur - Eve","IL",2043 +"2043-10-14","Yom Kippur","IL",2043 +"2043-10-18","Sukkot I - Eve","IL",2043 +"2043-10-19","Sukkot I","IL",2043 +"2043-10-20","Sukkot - Chol HaMoed","IL",2043 +"2043-10-21","Sukkot - Chol HaMoed","IL",2043 +"2043-10-22","Sukkot - Chol HaMoed","IL",2043 +"2043-10-23","Sukkot - Chol HaMoed","IL",2043 +"2043-10-24","Sukkot - Chol HaMoed","IL",2043 +"2043-10-25","Sukkot VII - Eve","IL",2043 +"2043-10-26","Sukkot VII","IL",2043 +"2043-12-27","Hanukkah","IL",2043 +"2043-12-28","Hanukkah","IL",2043 +"2043-12-29","Hanukkah","IL",2043 +"2043-12-30","Hanukkah","IL",2043 +"2043-12-31","Hanukkah","IL",2043 +"2044-01-01","Hanukkah","IL",2044 +"2044-01-02","Hanukkah","IL",2044 +"2044-01-03","Hanukkah","IL",2044 +"2044-03-12","Purim - Eve","IL",2044 +"2044-03-13","Purim","IL",2044 +"2044-03-14","Shushan Purim","IL",2044 +"2044-04-11","Passover I - Eve","IL",2044 +"2044-04-12","Passover I","IL",2044 +"2044-04-13","Passover - Chol HaMoed","IL",2044 +"2044-04-14","Passover - Chol HaMoed","IL",2044 +"2044-04-15","Passover - Chol HaMoed","IL",2044 +"2044-04-16","Passover - Chol HaMoed","IL",2044 +"2044-04-17","Passover VII - Eve","IL",2044 +"2044-04-18","Passover VII","IL",2044 +"2044-05-02","Memorial Day (Observed)","IL",2044 +"2044-05-03","Independence Day (Observed)","IL",2044 +"2044-05-15","Lag B'Omer","IL",2044 +"2044-05-31","Shavuot - Eve","IL",2044 +"2044-06-01","Shavuot","IL",2044 +"2044-09-21","Rosh Hashanah - Eve","IL",2044 +"2044-09-22","Rosh Hashanah","IL",2044 +"2044-09-23","Rosh Hashanah","IL",2044 +"2044-09-30","Yom Kippur - Eve","IL",2044 +"2044-10-01","Yom Kippur","IL",2044 +"2044-10-05","Sukkot I - Eve","IL",2044 +"2044-10-06","Sukkot I","IL",2044 +"2044-10-07","Sukkot - Chol HaMoed","IL",2044 +"2044-10-08","Sukkot - Chol HaMoed","IL",2044 +"2044-10-09","Sukkot - Chol HaMoed","IL",2044 +"2044-10-10","Sukkot - Chol HaMoed","IL",2044 +"2044-10-11","Sukkot - Chol HaMoed","IL",2044 +"2044-10-12","Sukkot VII - Eve","IL",2044 +"2044-10-13","Sukkot VII","IL",2044 +"2044-12-15","Hanukkah","IL",2044 +"2044-12-16","Hanukkah","IL",2044 +"2044-12-17","Hanukkah","IL",2044 +"2044-12-18","Hanukkah","IL",2044 +"2044-12-19","Hanukkah","IL",2044 +"2044-12-20","Hanukkah","IL",2044 +"2044-12-21","Hanukkah","IL",2044 +"2044-12-22","Hanukkah","IL",2044 +"1995-01-01","New Year's Day","IM",1995 +"1995-01-02","New Year's Day (Observed)","IM",1995 +"1995-04-14","Good Friday","IM",1995 +"1995-04-17","Easter Monday","IM",1995 +"1995-05-08","May Day","IM",1995 +"1995-05-29","Spring Bank Holiday","IM",1995 +"1995-06-02","TT Bank Holiday","IM",1995 +"1995-07-05","Tynwald Day","IM",1995 +"1995-08-28","Late Summer Bank Holiday","IM",1995 +"1995-12-25","Christmas Day","IM",1995 +"1995-12-26","Boxing Day","IM",1995 +"1996-01-01","New Year's Day","IM",1996 +"1996-04-05","Good Friday","IM",1996 +"1996-04-08","Easter Monday","IM",1996 +"1996-05-06","May Day","IM",1996 +"1996-05-27","Spring Bank Holiday","IM",1996 +"1996-06-07","TT Bank Holiday","IM",1996 +"1996-07-05","Tynwald Day","IM",1996 +"1996-08-26","Late Summer Bank Holiday","IM",1996 +"1996-12-25","Christmas Day","IM",1996 +"1996-12-26","Boxing Day","IM",1996 +"1997-01-01","New Year's Day","IM",1997 +"1997-03-28","Good Friday","IM",1997 +"1997-03-31","Easter Monday","IM",1997 +"1997-05-05","May Day","IM",1997 +"1997-05-26","Spring Bank Holiday","IM",1997 +"1997-06-06","TT Bank Holiday","IM",1997 +"1997-07-05","Tynwald Day","IM",1997 +"1997-08-25","Late Summer Bank Holiday","IM",1997 +"1997-12-25","Christmas Day","IM",1997 +"1997-12-26","Boxing Day","IM",1997 +"1998-01-01","New Year's Day","IM",1998 +"1998-04-10","Good Friday","IM",1998 +"1998-04-13","Easter Monday","IM",1998 +"1998-05-04","May Day","IM",1998 +"1998-05-25","Spring Bank Holiday","IM",1998 +"1998-06-05","TT Bank Holiday","IM",1998 +"1998-07-05","Tynwald Day","IM",1998 +"1998-08-31","Late Summer Bank Holiday","IM",1998 +"1998-12-25","Christmas Day","IM",1998 +"1998-12-26","Boxing Day","IM",1998 +"1998-12-28","Boxing Day (Observed)","IM",1998 +"1999-01-01","New Year's Day","IM",1999 +"1999-04-02","Good Friday","IM",1999 +"1999-04-05","Easter Monday","IM",1999 +"1999-05-03","May Day","IM",1999 +"1999-05-31","Spring Bank Holiday","IM",1999 +"1999-06-04","TT Bank Holiday","IM",1999 +"1999-07-05","Tynwald Day","IM",1999 +"1999-08-30","Late Summer Bank Holiday","IM",1999 +"1999-12-25","Christmas Day","IM",1999 +"1999-12-26","Boxing Day","IM",1999 +"1999-12-27","Christmas Day (Observed)","IM",1999 +"1999-12-28","Boxing Day (Observed)","IM",1999 +"1999-12-31","Millennium Celebrations","IM",1999 +"2000-01-01","New Year's Day","IM",2000 +"2000-01-03","New Year's Day (Observed)","IM",2000 +"2000-04-21","Good Friday","IM",2000 +"2000-04-24","Easter Monday","IM",2000 +"2000-05-01","May Day","IM",2000 +"2000-05-29","Spring Bank Holiday","IM",2000 +"2000-06-02","TT Bank Holiday","IM",2000 +"2000-07-05","Tynwald Day","IM",2000 +"2000-08-28","Late Summer Bank Holiday","IM",2000 +"2000-12-25","Christmas Day","IM",2000 +"2000-12-26","Boxing Day","IM",2000 +"2001-01-01","New Year's Day","IM",2001 +"2001-04-13","Good Friday","IM",2001 +"2001-04-16","Easter Monday","IM",2001 +"2001-05-07","May Day","IM",2001 +"2001-05-28","Spring Bank Holiday","IM",2001 +"2001-06-01","TT Bank Holiday","IM",2001 +"2001-07-05","Tynwald Day","IM",2001 +"2001-08-27","Late Summer Bank Holiday","IM",2001 +"2001-12-25","Christmas Day","IM",2001 +"2001-12-26","Boxing Day","IM",2001 +"2002-01-01","New Year's Day","IM",2002 +"2002-03-29","Good Friday","IM",2002 +"2002-04-01","Easter Monday","IM",2002 +"2002-05-06","May Day","IM",2002 +"2002-05-27","Spring Bank Holiday","IM",2002 +"2002-06-03","Golden Jubilee of Elizabeth II","IM",2002 +"2002-06-07","TT Bank Holiday","IM",2002 +"2002-07-05","Tynwald Day","IM",2002 +"2002-08-26","Late Summer Bank Holiday","IM",2002 +"2002-12-25","Christmas Day","IM",2002 +"2002-12-26","Boxing Day","IM",2002 +"2003-01-01","New Year's Day","IM",2003 +"2003-04-18","Good Friday","IM",2003 +"2003-04-21","Easter Monday","IM",2003 +"2003-05-05","May Day","IM",2003 +"2003-05-26","Spring Bank Holiday","IM",2003 +"2003-06-06","TT Bank Holiday","IM",2003 +"2003-07-05","Tynwald Day","IM",2003 +"2003-08-25","Late Summer Bank Holiday","IM",2003 +"2003-12-25","Christmas Day","IM",2003 +"2003-12-26","Boxing Day","IM",2003 +"2004-01-01","New Year's Day","IM",2004 +"2004-04-09","Good Friday","IM",2004 +"2004-04-12","Easter Monday","IM",2004 +"2004-05-03","May Day","IM",2004 +"2004-05-31","Spring Bank Holiday","IM",2004 +"2004-06-04","TT Bank Holiday","IM",2004 +"2004-07-05","Tynwald Day","IM",2004 +"2004-08-30","Late Summer Bank Holiday","IM",2004 +"2004-12-25","Christmas Day","IM",2004 +"2004-12-26","Boxing Day","IM",2004 +"2004-12-27","Christmas Day (Observed)","IM",2004 +"2004-12-28","Boxing Day (Observed)","IM",2004 +"2005-01-01","New Year's Day","IM",2005 +"2005-01-03","New Year's Day (Observed)","IM",2005 +"2005-03-25","Good Friday","IM",2005 +"2005-03-28","Easter Monday","IM",2005 +"2005-05-02","May Day","IM",2005 +"2005-05-30","Spring Bank Holiday","IM",2005 +"2005-06-03","TT Bank Holiday","IM",2005 +"2005-07-05","Tynwald Day","IM",2005 +"2005-08-29","Late Summer Bank Holiday","IM",2005 +"2005-12-25","Christmas Day","IM",2005 +"2005-12-26","Boxing Day","IM",2005 +"2005-12-27","Christmas Day (Observed)","IM",2005 +"2006-01-01","New Year's Day","IM",2006 +"2006-01-02","New Year's Day (Observed)","IM",2006 +"2006-04-14","Good Friday","IM",2006 +"2006-04-17","Easter Monday","IM",2006 +"2006-05-01","May Day","IM",2006 +"2006-05-29","Spring Bank Holiday","IM",2006 +"2006-06-02","TT Bank Holiday","IM",2006 +"2006-07-05","Tynwald Day","IM",2006 +"2006-08-28","Late Summer Bank Holiday","IM",2006 +"2006-12-25","Christmas Day","IM",2006 +"2006-12-26","Boxing Day","IM",2006 +"2007-01-01","New Year's Day","IM",2007 +"2007-04-06","Good Friday","IM",2007 +"2007-04-09","Easter Monday","IM",2007 +"2007-05-07","May Day","IM",2007 +"2007-05-28","Spring Bank Holiday","IM",2007 +"2007-06-01","TT Bank Holiday","IM",2007 +"2007-07-05","Tynwald Day","IM",2007 +"2007-08-27","Late Summer Bank Holiday","IM",2007 +"2007-12-25","Christmas Day","IM",2007 +"2007-12-26","Boxing Day","IM",2007 +"2008-01-01","New Year's Day","IM",2008 +"2008-03-21","Good Friday","IM",2008 +"2008-03-24","Easter Monday","IM",2008 +"2008-05-05","May Day","IM",2008 +"2008-05-26","Spring Bank Holiday","IM",2008 +"2008-06-06","TT Bank Holiday","IM",2008 +"2008-07-05","Tynwald Day","IM",2008 +"2008-08-25","Late Summer Bank Holiday","IM",2008 +"2008-12-25","Christmas Day","IM",2008 +"2008-12-26","Boxing Day","IM",2008 +"2009-01-01","New Year's Day","IM",2009 +"2009-04-10","Good Friday","IM",2009 +"2009-04-13","Easter Monday","IM",2009 +"2009-05-04","May Day","IM",2009 +"2009-05-25","Spring Bank Holiday","IM",2009 +"2009-06-05","TT Bank Holiday","IM",2009 +"2009-07-05","Tynwald Day","IM",2009 +"2009-08-31","Late Summer Bank Holiday","IM",2009 +"2009-12-25","Christmas Day","IM",2009 +"2009-12-26","Boxing Day","IM",2009 +"2009-12-28","Boxing Day (Observed)","IM",2009 +"2010-01-01","New Year's Day","IM",2010 +"2010-04-02","Good Friday","IM",2010 +"2010-04-05","Easter Monday","IM",2010 +"2010-05-03","May Day","IM",2010 +"2010-05-31","Spring Bank Holiday","IM",2010 +"2010-06-04","TT Bank Holiday","IM",2010 +"2010-07-05","Tynwald Day","IM",2010 +"2010-08-30","Late Summer Bank Holiday","IM",2010 +"2010-12-25","Christmas Day","IM",2010 +"2010-12-26","Boxing Day","IM",2010 +"2010-12-27","Christmas Day (Observed)","IM",2010 +"2010-12-28","Boxing Day (Observed)","IM",2010 +"2011-01-01","New Year's Day","IM",2011 +"2011-01-03","New Year's Day (Observed)","IM",2011 +"2011-04-22","Good Friday","IM",2011 +"2011-04-25","Easter Monday","IM",2011 +"2011-04-29","Wedding of William and Catherine","IM",2011 +"2011-05-02","May Day","IM",2011 +"2011-05-30","Spring Bank Holiday","IM",2011 +"2011-06-03","TT Bank Holiday","IM",2011 +"2011-07-05","Tynwald Day","IM",2011 +"2011-08-29","Late Summer Bank Holiday","IM",2011 +"2011-12-25","Christmas Day","IM",2011 +"2011-12-26","Boxing Day","IM",2011 +"2011-12-27","Christmas Day (Observed)","IM",2011 +"2012-01-01","New Year's Day","IM",2012 +"2012-01-02","New Year's Day (Observed)","IM",2012 +"2012-04-06","Good Friday","IM",2012 +"2012-04-09","Easter Monday","IM",2012 +"2012-05-07","May Day","IM",2012 +"2012-06-01","TT Bank Holiday","IM",2012 +"2012-06-04","Spring Bank Holiday","IM",2012 +"2012-06-05","Diamond Jubilee of Elizabeth II","IM",2012 +"2012-07-05","Tynwald Day","IM",2012 +"2012-08-27","Late Summer Bank Holiday","IM",2012 +"2012-12-25","Christmas Day","IM",2012 +"2012-12-26","Boxing Day","IM",2012 +"2013-01-01","New Year's Day","IM",2013 +"2013-03-29","Good Friday","IM",2013 +"2013-04-01","Easter Monday","IM",2013 +"2013-05-06","May Day","IM",2013 +"2013-05-27","Spring Bank Holiday","IM",2013 +"2013-06-07","TT Bank Holiday","IM",2013 +"2013-07-05","Tynwald Day","IM",2013 +"2013-08-26","Late Summer Bank Holiday","IM",2013 +"2013-12-25","Christmas Day","IM",2013 +"2013-12-26","Boxing Day","IM",2013 +"2014-01-01","New Year's Day","IM",2014 +"2014-04-18","Good Friday","IM",2014 +"2014-04-21","Easter Monday","IM",2014 +"2014-05-05","May Day","IM",2014 +"2014-05-26","Spring Bank Holiday","IM",2014 +"2014-06-06","TT Bank Holiday","IM",2014 +"2014-07-05","Tynwald Day","IM",2014 +"2014-08-25","Late Summer Bank Holiday","IM",2014 +"2014-12-25","Christmas Day","IM",2014 +"2014-12-26","Boxing Day","IM",2014 +"2015-01-01","New Year's Day","IM",2015 +"2015-04-03","Good Friday","IM",2015 +"2015-04-06","Easter Monday","IM",2015 +"2015-05-04","May Day","IM",2015 +"2015-05-25","Spring Bank Holiday","IM",2015 +"2015-06-05","TT Bank Holiday","IM",2015 +"2015-07-05","Tynwald Day","IM",2015 +"2015-08-31","Late Summer Bank Holiday","IM",2015 +"2015-12-25","Christmas Day","IM",2015 +"2015-12-26","Boxing Day","IM",2015 +"2015-12-28","Boxing Day (Observed)","IM",2015 +"2016-01-01","New Year's Day","IM",2016 +"2016-03-25","Good Friday","IM",2016 +"2016-03-28","Easter Monday","IM",2016 +"2016-05-02","May Day","IM",2016 +"2016-05-30","Spring Bank Holiday","IM",2016 +"2016-06-03","TT Bank Holiday","IM",2016 +"2016-07-05","Tynwald Day","IM",2016 +"2016-08-29","Late Summer Bank Holiday","IM",2016 +"2016-12-25","Christmas Day","IM",2016 +"2016-12-26","Boxing Day","IM",2016 +"2016-12-27","Christmas Day (Observed)","IM",2016 +"2017-01-01","New Year's Day","IM",2017 +"2017-01-02","New Year's Day (Observed)","IM",2017 +"2017-04-14","Good Friday","IM",2017 +"2017-04-17","Easter Monday","IM",2017 +"2017-05-01","May Day","IM",2017 +"2017-05-29","Spring Bank Holiday","IM",2017 +"2017-06-02","TT Bank Holiday","IM",2017 +"2017-07-05","Tynwald Day","IM",2017 +"2017-08-28","Late Summer Bank Holiday","IM",2017 +"2017-12-25","Christmas Day","IM",2017 +"2017-12-26","Boxing Day","IM",2017 +"2018-01-01","New Year's Day","IM",2018 +"2018-03-30","Good Friday","IM",2018 +"2018-04-02","Easter Monday","IM",2018 +"2018-05-07","May Day","IM",2018 +"2018-05-28","Spring Bank Holiday","IM",2018 +"2018-06-01","TT Bank Holiday","IM",2018 +"2018-07-05","Tynwald Day","IM",2018 +"2018-08-27","Late Summer Bank Holiday","IM",2018 +"2018-12-25","Christmas Day","IM",2018 +"2018-12-26","Boxing Day","IM",2018 +"2019-01-01","New Year's Day","IM",2019 +"2019-04-19","Good Friday","IM",2019 +"2019-04-22","Easter Monday","IM",2019 +"2019-05-06","May Day","IM",2019 +"2019-05-27","Spring Bank Holiday","IM",2019 +"2019-06-07","TT Bank Holiday","IM",2019 +"2019-07-05","Tynwald Day","IM",2019 +"2019-08-26","Late Summer Bank Holiday","IM",2019 +"2019-12-25","Christmas Day","IM",2019 +"2019-12-26","Boxing Day","IM",2019 +"2020-01-01","New Year's Day","IM",2020 +"2020-04-10","Good Friday","IM",2020 +"2020-04-13","Easter Monday","IM",2020 +"2020-05-08","May Day","IM",2020 +"2020-05-25","Spring Bank Holiday","IM",2020 +"2020-06-05","TT Bank Holiday","IM",2020 +"2020-07-05","Tynwald Day","IM",2020 +"2020-08-31","Late Summer Bank Holiday","IM",2020 +"2020-12-25","Christmas Day","IM",2020 +"2020-12-26","Boxing Day","IM",2020 +"2020-12-28","Boxing Day (Observed)","IM",2020 +"2021-01-01","New Year's Day","IM",2021 +"2021-04-02","Good Friday","IM",2021 +"2021-04-05","Easter Monday","IM",2021 +"2021-05-03","May Day","IM",2021 +"2021-05-31","Spring Bank Holiday","IM",2021 +"2021-06-04","TT Bank Holiday","IM",2021 +"2021-07-05","Tynwald Day","IM",2021 +"2021-08-30","Late Summer Bank Holiday","IM",2021 +"2021-12-25","Christmas Day","IM",2021 +"2021-12-26","Boxing Day","IM",2021 +"2021-12-27","Christmas Day (Observed)","IM",2021 +"2021-12-28","Boxing Day (Observed)","IM",2021 +"2022-01-01","New Year's Day","IM",2022 +"2022-01-03","New Year's Day (Observed)","IM",2022 +"2022-04-15","Good Friday","IM",2022 +"2022-04-18","Easter Monday","IM",2022 +"2022-05-02","May Day","IM",2022 +"2022-06-02","Spring Bank Holiday","IM",2022 +"2022-06-03","Platinum Jubilee of Elizabeth II","IM",2022 +"2022-06-03","TT Bank Holiday","IM",2022 +"2022-07-05","Tynwald Day","IM",2022 +"2022-08-29","Late Summer Bank Holiday","IM",2022 +"2022-09-19","State Funeral of Queen Elizabeth II","IM",2022 +"2022-12-25","Christmas Day","IM",2022 +"2022-12-26","Boxing Day","IM",2022 +"2022-12-27","Christmas Day (Observed)","IM",2022 +"2023-01-01","New Year's Day","IM",2023 +"2023-01-02","New Year's Day (Observed)","IM",2023 +"2023-04-07","Good Friday","IM",2023 +"2023-04-10","Easter Monday","IM",2023 +"2023-05-01","May Day","IM",2023 +"2023-05-08","Coronation of Charles III","IM",2023 +"2023-05-29","Spring Bank Holiday","IM",2023 +"2023-06-02","TT Bank Holiday","IM",2023 +"2023-07-05","Tynwald Day","IM",2023 +"2023-08-28","Late Summer Bank Holiday","IM",2023 +"2023-12-25","Christmas Day","IM",2023 +"2023-12-26","Boxing Day","IM",2023 +"2024-01-01","New Year's Day","IM",2024 +"2024-03-29","Good Friday","IM",2024 +"2024-04-01","Easter Monday","IM",2024 +"2024-05-06","May Day","IM",2024 +"2024-05-27","Spring Bank Holiday","IM",2024 +"2024-06-07","TT Bank Holiday","IM",2024 +"2024-07-05","Tynwald Day","IM",2024 +"2024-08-26","Late Summer Bank Holiday","IM",2024 +"2024-12-25","Christmas Day","IM",2024 +"2024-12-26","Boxing Day","IM",2024 +"2025-01-01","New Year's Day","IM",2025 +"2025-04-18","Good Friday","IM",2025 +"2025-04-21","Easter Monday","IM",2025 +"2025-05-05","May Day","IM",2025 +"2025-05-26","Spring Bank Holiday","IM",2025 +"2025-06-06","TT Bank Holiday","IM",2025 +"2025-07-05","Tynwald Day","IM",2025 +"2025-08-25","Late Summer Bank Holiday","IM",2025 +"2025-12-25","Christmas Day","IM",2025 +"2025-12-26","Boxing Day","IM",2025 +"2026-01-01","New Year's Day","IM",2026 +"2026-04-03","Good Friday","IM",2026 +"2026-04-06","Easter Monday","IM",2026 +"2026-05-04","May Day","IM",2026 +"2026-05-25","Spring Bank Holiday","IM",2026 +"2026-06-05","TT Bank Holiday","IM",2026 +"2026-07-05","Tynwald Day","IM",2026 +"2026-08-31","Late Summer Bank Holiday","IM",2026 +"2026-12-25","Christmas Day","IM",2026 +"2026-12-26","Boxing Day","IM",2026 +"2026-12-28","Boxing Day (Observed)","IM",2026 +"2027-01-01","New Year's Day","IM",2027 +"2027-03-26","Good Friday","IM",2027 +"2027-03-29","Easter Monday","IM",2027 +"2027-05-03","May Day","IM",2027 +"2027-05-31","Spring Bank Holiday","IM",2027 +"2027-06-04","TT Bank Holiday","IM",2027 +"2027-07-05","Tynwald Day","IM",2027 +"2027-08-30","Late Summer Bank Holiday","IM",2027 +"2027-12-25","Christmas Day","IM",2027 +"2027-12-26","Boxing Day","IM",2027 +"2027-12-27","Christmas Day (Observed)","IM",2027 +"2027-12-28","Boxing Day (Observed)","IM",2027 +"2028-01-01","New Year's Day","IM",2028 +"2028-01-03","New Year's Day (Observed)","IM",2028 +"2028-04-14","Good Friday","IM",2028 +"2028-04-17","Easter Monday","IM",2028 +"2028-05-01","May Day","IM",2028 +"2028-05-29","Spring Bank Holiday","IM",2028 +"2028-06-02","TT Bank Holiday","IM",2028 +"2028-07-05","Tynwald Day","IM",2028 +"2028-08-28","Late Summer Bank Holiday","IM",2028 +"2028-12-25","Christmas Day","IM",2028 +"2028-12-26","Boxing Day","IM",2028 +"2029-01-01","New Year's Day","IM",2029 +"2029-03-30","Good Friday","IM",2029 +"2029-04-02","Easter Monday","IM",2029 +"2029-05-07","May Day","IM",2029 +"2029-05-28","Spring Bank Holiday","IM",2029 +"2029-06-01","TT Bank Holiday","IM",2029 +"2029-07-05","Tynwald Day","IM",2029 +"2029-08-27","Late Summer Bank Holiday","IM",2029 +"2029-12-25","Christmas Day","IM",2029 +"2029-12-26","Boxing Day","IM",2029 +"2030-01-01","New Year's Day","IM",2030 +"2030-04-19","Good Friday","IM",2030 +"2030-04-22","Easter Monday","IM",2030 +"2030-05-06","May Day","IM",2030 +"2030-05-27","Spring Bank Holiday","IM",2030 +"2030-06-07","TT Bank Holiday","IM",2030 +"2030-07-05","Tynwald Day","IM",2030 +"2030-08-26","Late Summer Bank Holiday","IM",2030 +"2030-12-25","Christmas Day","IM",2030 +"2030-12-26","Boxing Day","IM",2030 +"2031-01-01","New Year's Day","IM",2031 +"2031-04-11","Good Friday","IM",2031 +"2031-04-14","Easter Monday","IM",2031 +"2031-05-05","May Day","IM",2031 +"2031-05-26","Spring Bank Holiday","IM",2031 +"2031-06-06","TT Bank Holiday","IM",2031 +"2031-07-05","Tynwald Day","IM",2031 +"2031-08-25","Late Summer Bank Holiday","IM",2031 +"2031-12-25","Christmas Day","IM",2031 +"2031-12-26","Boxing Day","IM",2031 +"2032-01-01","New Year's Day","IM",2032 +"2032-03-26","Good Friday","IM",2032 +"2032-03-29","Easter Monday","IM",2032 +"2032-05-03","May Day","IM",2032 +"2032-05-31","Spring Bank Holiday","IM",2032 +"2032-06-04","TT Bank Holiday","IM",2032 +"2032-07-05","Tynwald Day","IM",2032 +"2032-08-30","Late Summer Bank Holiday","IM",2032 +"2032-12-25","Christmas Day","IM",2032 +"2032-12-26","Boxing Day","IM",2032 +"2032-12-27","Christmas Day (Observed)","IM",2032 +"2032-12-28","Boxing Day (Observed)","IM",2032 +"2033-01-01","New Year's Day","IM",2033 +"2033-01-03","New Year's Day (Observed)","IM",2033 +"2033-04-15","Good Friday","IM",2033 +"2033-04-18","Easter Monday","IM",2033 +"2033-05-02","May Day","IM",2033 +"2033-05-30","Spring Bank Holiday","IM",2033 +"2033-06-03","TT Bank Holiday","IM",2033 +"2033-07-05","Tynwald Day","IM",2033 +"2033-08-29","Late Summer Bank Holiday","IM",2033 +"2033-12-25","Christmas Day","IM",2033 +"2033-12-26","Boxing Day","IM",2033 +"2033-12-27","Christmas Day (Observed)","IM",2033 +"2034-01-01","New Year's Day","IM",2034 +"2034-01-02","New Year's Day (Observed)","IM",2034 +"2034-04-07","Good Friday","IM",2034 +"2034-04-10","Easter Monday","IM",2034 +"2034-05-01","May Day","IM",2034 +"2034-05-29","Spring Bank Holiday","IM",2034 +"2034-06-02","TT Bank Holiday","IM",2034 +"2034-07-05","Tynwald Day","IM",2034 +"2034-08-28","Late Summer Bank Holiday","IM",2034 +"2034-12-25","Christmas Day","IM",2034 +"2034-12-26","Boxing Day","IM",2034 +"2035-01-01","New Year's Day","IM",2035 +"2035-03-23","Good Friday","IM",2035 +"2035-03-26","Easter Monday","IM",2035 +"2035-05-07","May Day","IM",2035 +"2035-05-28","Spring Bank Holiday","IM",2035 +"2035-06-01","TT Bank Holiday","IM",2035 +"2035-07-05","Tynwald Day","IM",2035 +"2035-08-27","Late Summer Bank Holiday","IM",2035 +"2035-12-25","Christmas Day","IM",2035 +"2035-12-26","Boxing Day","IM",2035 +"2036-01-01","New Year's Day","IM",2036 +"2036-04-11","Good Friday","IM",2036 +"2036-04-14","Easter Monday","IM",2036 +"2036-05-05","May Day","IM",2036 +"2036-05-26","Spring Bank Holiday","IM",2036 +"2036-06-06","TT Bank Holiday","IM",2036 +"2036-07-05","Tynwald Day","IM",2036 +"2036-08-25","Late Summer Bank Holiday","IM",2036 +"2036-12-25","Christmas Day","IM",2036 +"2036-12-26","Boxing Day","IM",2036 +"2037-01-01","New Year's Day","IM",2037 +"2037-04-03","Good Friday","IM",2037 +"2037-04-06","Easter Monday","IM",2037 +"2037-05-04","May Day","IM",2037 +"2037-05-25","Spring Bank Holiday","IM",2037 +"2037-06-05","TT Bank Holiday","IM",2037 +"2037-07-05","Tynwald Day","IM",2037 +"2037-08-31","Late Summer Bank Holiday","IM",2037 +"2037-12-25","Christmas Day","IM",2037 +"2037-12-26","Boxing Day","IM",2037 +"2037-12-28","Boxing Day (Observed)","IM",2037 +"2038-01-01","New Year's Day","IM",2038 +"2038-04-23","Good Friday","IM",2038 +"2038-04-26","Easter Monday","IM",2038 +"2038-05-03","May Day","IM",2038 +"2038-05-31","Spring Bank Holiday","IM",2038 +"2038-06-04","TT Bank Holiday","IM",2038 +"2038-07-05","Tynwald Day","IM",2038 +"2038-08-30","Late Summer Bank Holiday","IM",2038 +"2038-12-25","Christmas Day","IM",2038 +"2038-12-26","Boxing Day","IM",2038 +"2038-12-27","Christmas Day (Observed)","IM",2038 +"2038-12-28","Boxing Day (Observed)","IM",2038 +"2039-01-01","New Year's Day","IM",2039 +"2039-01-03","New Year's Day (Observed)","IM",2039 +"2039-04-08","Good Friday","IM",2039 +"2039-04-11","Easter Monday","IM",2039 +"2039-05-02","May Day","IM",2039 +"2039-05-30","Spring Bank Holiday","IM",2039 +"2039-06-03","TT Bank Holiday","IM",2039 +"2039-07-05","Tynwald Day","IM",2039 +"2039-08-29","Late Summer Bank Holiday","IM",2039 +"2039-12-25","Christmas Day","IM",2039 +"2039-12-26","Boxing Day","IM",2039 +"2039-12-27","Christmas Day (Observed)","IM",2039 +"2040-01-01","New Year's Day","IM",2040 +"2040-01-02","New Year's Day (Observed)","IM",2040 +"2040-03-30","Good Friday","IM",2040 +"2040-04-02","Easter Monday","IM",2040 +"2040-05-07","May Day","IM",2040 +"2040-05-28","Spring Bank Holiday","IM",2040 +"2040-06-01","TT Bank Holiday","IM",2040 +"2040-07-05","Tynwald Day","IM",2040 +"2040-08-27","Late Summer Bank Holiday","IM",2040 +"2040-12-25","Christmas Day","IM",2040 +"2040-12-26","Boxing Day","IM",2040 +"2041-01-01","New Year's Day","IM",2041 +"2041-04-19","Good Friday","IM",2041 +"2041-04-22","Easter Monday","IM",2041 +"2041-05-06","May Day","IM",2041 +"2041-05-27","Spring Bank Holiday","IM",2041 +"2041-06-07","TT Bank Holiday","IM",2041 +"2041-07-05","Tynwald Day","IM",2041 +"2041-08-26","Late Summer Bank Holiday","IM",2041 +"2041-12-25","Christmas Day","IM",2041 +"2041-12-26","Boxing Day","IM",2041 +"2042-01-01","New Year's Day","IM",2042 +"2042-04-04","Good Friday","IM",2042 +"2042-04-07","Easter Monday","IM",2042 +"2042-05-05","May Day","IM",2042 +"2042-05-26","Spring Bank Holiday","IM",2042 +"2042-06-06","TT Bank Holiday","IM",2042 +"2042-07-05","Tynwald Day","IM",2042 +"2042-08-25","Late Summer Bank Holiday","IM",2042 +"2042-12-25","Christmas Day","IM",2042 +"2042-12-26","Boxing Day","IM",2042 +"2043-01-01","New Year's Day","IM",2043 +"2043-03-27","Good Friday","IM",2043 +"2043-03-30","Easter Monday","IM",2043 +"2043-05-04","May Day","IM",2043 +"2043-05-25","Spring Bank Holiday","IM",2043 +"2043-06-05","TT Bank Holiday","IM",2043 +"2043-07-05","Tynwald Day","IM",2043 +"2043-08-31","Late Summer Bank Holiday","IM",2043 +"2043-12-25","Christmas Day","IM",2043 +"2043-12-26","Boxing Day","IM",2043 +"2043-12-28","Boxing Day (Observed)","IM",2043 +"2044-01-01","New Year's Day","IM",2044 +"2044-04-15","Good Friday","IM",2044 +"2044-04-18","Easter Monday","IM",2044 +"2044-05-02","May Day","IM",2044 +"2044-05-30","Spring Bank Holiday","IM",2044 +"2044-06-03","TT Bank Holiday","IM",2044 +"2044-07-05","Tynwald Day","IM",2044 +"2044-08-29","Late Summer Bank Holiday","IM",2044 +"2044-12-25","Christmas Day","IM",2044 +"2044-12-26","Boxing Day","IM",2044 +"2044-12-27","Christmas Day (Observed)","IM",2044 +"1995-01-14","Makar Sankranti / Pongal","IN",1995 +"1995-01-26","Republic Day","IN",1995 +"1995-03-02","Eid ul-Fitr* (*estimated)","IN",1995 +"1995-03-03","Eid ul-Fitr* (*estimated)","IN",1995 +"1995-04-09","Palm Sunday","IN",1995 +"1995-04-14","Good Friday","IN",1995 +"1995-04-16","Easter Sunday","IN",1995 +"1995-05-01","Labour Day","IN",1995 +"1995-05-09","Eid al-Adha* (*estimated)","IN",1995 +"1995-05-10","Eid al-Adha* (*estimated)","IN",1995 +"1995-06-04","Feast of Pentecost","IN",1995 +"1995-06-08","Day of Ashura* (*estimated)","IN",1995 +"1995-08-08","Mawlid* (*estimated)","IN",1995 +"1995-08-15","Independence Day","IN",1995 +"1995-10-02","Gandhi Jayanti","IN",1995 +"1995-12-25","Christmas Day","IN",1995 +"1996-01-14","Makar Sankranti / Pongal","IN",1996 +"1996-01-26","Republic Day","IN",1996 +"1996-02-19","Eid ul-Fitr* (*estimated)","IN",1996 +"1996-02-20","Eid ul-Fitr* (*estimated)","IN",1996 +"1996-03-31","Palm Sunday","IN",1996 +"1996-04-05","Good Friday","IN",1996 +"1996-04-07","Easter Sunday","IN",1996 +"1996-04-27","Eid al-Adha* (*estimated)","IN",1996 +"1996-04-28","Eid al-Adha* (*estimated)","IN",1996 +"1996-05-01","Labour Day","IN",1996 +"1996-05-26","Feast of Pentecost","IN",1996 +"1996-05-27","Day of Ashura* (*estimated)","IN",1996 +"1996-07-27","Mawlid* (*estimated)","IN",1996 +"1996-08-15","Independence Day","IN",1996 +"1996-10-02","Gandhi Jayanti","IN",1996 +"1996-12-25","Christmas Day","IN",1996 +"1997-01-14","Makar Sankranti / Pongal","IN",1997 +"1997-01-26","Republic Day","IN",1997 +"1997-02-08","Eid ul-Fitr* (*estimated)","IN",1997 +"1997-02-09","Eid ul-Fitr* (*estimated)","IN",1997 +"1997-03-23","Palm Sunday","IN",1997 +"1997-03-28","Good Friday","IN",1997 +"1997-03-30","Easter Sunday","IN",1997 +"1997-04-17","Eid al-Adha* (*estimated)","IN",1997 +"1997-04-18","Eid al-Adha* (*estimated)","IN",1997 +"1997-05-01","Labour Day","IN",1997 +"1997-05-16","Day of Ashura* (*estimated)","IN",1997 +"1997-05-18","Feast of Pentecost","IN",1997 +"1997-07-16","Mawlid* (*estimated)","IN",1997 +"1997-08-15","Independence Day","IN",1997 +"1997-10-02","Gandhi Jayanti","IN",1997 +"1997-12-25","Christmas Day","IN",1997 +"1998-01-14","Makar Sankranti / Pongal","IN",1998 +"1998-01-26","Republic Day","IN",1998 +"1998-01-29","Eid ul-Fitr* (*estimated)","IN",1998 +"1998-01-30","Eid ul-Fitr* (*estimated)","IN",1998 +"1998-04-05","Palm Sunday","IN",1998 +"1998-04-07","Eid al-Adha* (*estimated)","IN",1998 +"1998-04-08","Eid al-Adha* (*estimated)","IN",1998 +"1998-04-10","Good Friday","IN",1998 +"1998-04-12","Easter Sunday","IN",1998 +"1998-05-01","Labour Day","IN",1998 +"1998-05-06","Day of Ashura* (*estimated)","IN",1998 +"1998-05-31","Feast of Pentecost","IN",1998 +"1998-07-06","Mawlid* (*estimated)","IN",1998 +"1998-08-15","Independence Day","IN",1998 +"1998-10-02","Gandhi Jayanti","IN",1998 +"1998-12-25","Christmas Day","IN",1998 +"1999-01-14","Makar Sankranti / Pongal","IN",1999 +"1999-01-18","Eid ul-Fitr* (*estimated)","IN",1999 +"1999-01-19","Eid ul-Fitr* (*estimated)","IN",1999 +"1999-01-26","Republic Day","IN",1999 +"1999-03-27","Eid al-Adha* (*estimated)","IN",1999 +"1999-03-28","Eid al-Adha* (*estimated)","IN",1999 +"1999-03-28","Palm Sunday","IN",1999 +"1999-04-02","Good Friday","IN",1999 +"1999-04-04","Easter Sunday","IN",1999 +"1999-04-26","Day of Ashura* (*estimated)","IN",1999 +"1999-05-01","Labour Day","IN",1999 +"1999-05-23","Feast of Pentecost","IN",1999 +"1999-06-26","Mawlid* (*estimated)","IN",1999 +"1999-08-15","Independence Day","IN",1999 +"1999-10-02","Gandhi Jayanti","IN",1999 +"1999-12-25","Christmas Day","IN",1999 +"2000-01-08","Eid ul-Fitr* (*estimated)","IN",2000 +"2000-01-09","Eid ul-Fitr* (*estimated)","IN",2000 +"2000-01-14","Makar Sankranti / Pongal","IN",2000 +"2000-01-26","Republic Day","IN",2000 +"2000-03-16","Eid al-Adha* (*estimated)","IN",2000 +"2000-03-17","Eid al-Adha* (*estimated)","IN",2000 +"2000-04-15","Day of Ashura* (*estimated)","IN",2000 +"2000-04-16","Palm Sunday","IN",2000 +"2000-04-21","Good Friday","IN",2000 +"2000-04-23","Easter Sunday","IN",2000 +"2000-05-01","Labour Day","IN",2000 +"2000-06-11","Feast of Pentecost","IN",2000 +"2000-06-14","Mawlid* (*estimated)","IN",2000 +"2000-08-15","Independence Day","IN",2000 +"2000-10-02","Gandhi Jayanti","IN",2000 +"2000-12-25","Christmas Day","IN",2000 +"2000-12-27","Eid ul-Fitr* (*estimated)","IN",2000 +"2000-12-28","Eid ul-Fitr* (*estimated)","IN",2000 +"2001-01-14","Makar Sankranti / Pongal","IN",2001 +"2001-01-26","Republic Day","IN",2001 +"2001-03-05","Eid al-Adha* (*estimated)","IN",2001 +"2001-03-06","Eid al-Adha* (*estimated)","IN",2001 +"2001-03-10","Holi","IN",2001 +"2001-04-04","Day of Ashura* (*estimated)","IN",2001 +"2001-04-08","Palm Sunday","IN",2001 +"2001-04-13","Good Friday","IN",2001 +"2001-04-15","Easter Sunday","IN",2001 +"2001-05-01","Labour Day","IN",2001 +"2001-06-03","Feast of Pentecost","IN",2001 +"2001-06-04","Mawlid* (*estimated)","IN",2001 +"2001-08-15","Independence Day","IN",2001 +"2001-10-02","Gandhi Jayanti","IN",2001 +"2001-11-14","Diwali","IN",2001 +"2001-12-16","Eid ul-Fitr* (*estimated)","IN",2001 +"2001-12-17","Eid ul-Fitr* (*estimated)","IN",2001 +"2001-12-25","Christmas Day","IN",2001 +"2002-01-14","Makar Sankranti / Pongal","IN",2002 +"2002-01-26","Republic Day","IN",2002 +"2002-02-22","Eid al-Adha* (*estimated)","IN",2002 +"2002-02-23","Eid al-Adha* (*estimated)","IN",2002 +"2002-03-24","Day of Ashura* (*estimated)","IN",2002 +"2002-03-24","Palm Sunday","IN",2002 +"2002-03-29","Good Friday","IN",2002 +"2002-03-29","Holi","IN",2002 +"2002-03-31","Easter Sunday","IN",2002 +"2002-05-01","Labour Day","IN",2002 +"2002-05-19","Feast of Pentecost","IN",2002 +"2002-05-24","Mawlid* (*estimated)","IN",2002 +"2002-08-15","Independence Day","IN",2002 +"2002-10-02","Gandhi Jayanti","IN",2002 +"2002-11-04","Diwali","IN",2002 +"2002-12-05","Eid ul-Fitr* (*estimated)","IN",2002 +"2002-12-06","Eid ul-Fitr* (*estimated)","IN",2002 +"2002-12-25","Christmas Day","IN",2002 +"2003-01-14","Makar Sankranti / Pongal","IN",2003 +"2003-01-26","Republic Day","IN",2003 +"2003-02-11","Eid al-Adha* (*estimated)","IN",2003 +"2003-02-12","Eid al-Adha* (*estimated)","IN",2003 +"2003-03-13","Day of Ashura* (*estimated)","IN",2003 +"2003-03-18","Holi","IN",2003 +"2003-04-13","Palm Sunday","IN",2003 +"2003-04-18","Good Friday","IN",2003 +"2003-04-20","Easter Sunday","IN",2003 +"2003-05-01","Labour Day","IN",2003 +"2003-05-13","Mawlid* (*estimated)","IN",2003 +"2003-06-08","Feast of Pentecost","IN",2003 +"2003-08-15","Independence Day","IN",2003 +"2003-10-02","Gandhi Jayanti","IN",2003 +"2003-10-25","Diwali","IN",2003 +"2003-11-25","Eid ul-Fitr* (*estimated)","IN",2003 +"2003-11-26","Eid ul-Fitr* (*estimated)","IN",2003 +"2003-12-25","Christmas Day","IN",2003 +"2004-01-14","Makar Sankranti / Pongal","IN",2004 +"2004-01-26","Republic Day","IN",2004 +"2004-02-01","Eid al-Adha* (*estimated)","IN",2004 +"2004-02-02","Eid al-Adha* (*estimated)","IN",2004 +"2004-03-01","Day of Ashura* (*estimated)","IN",2004 +"2004-03-07","Holi","IN",2004 +"2004-04-04","Palm Sunday","IN",2004 +"2004-04-09","Good Friday","IN",2004 +"2004-04-11","Easter Sunday","IN",2004 +"2004-05-01","Labour Day","IN",2004 +"2004-05-01","Mawlid* (*estimated)","IN",2004 +"2004-05-30","Feast of Pentecost","IN",2004 +"2004-08-15","Independence Day","IN",2004 +"2004-10-02","Gandhi Jayanti","IN",2004 +"2004-11-12","Diwali","IN",2004 +"2004-11-14","Eid ul-Fitr* (*estimated)","IN",2004 +"2004-11-15","Eid ul-Fitr* (*estimated)","IN",2004 +"2004-12-25","Christmas Day","IN",2004 +"2005-01-14","Makar Sankranti / Pongal","IN",2005 +"2005-01-21","Eid al-Adha* (*estimated)","IN",2005 +"2005-01-22","Eid al-Adha* (*estimated)","IN",2005 +"2005-01-26","Republic Day","IN",2005 +"2005-02-19","Day of Ashura* (*estimated)","IN",2005 +"2005-03-20","Palm Sunday","IN",2005 +"2005-03-25","Good Friday","IN",2005 +"2005-03-26","Holi","IN",2005 +"2005-03-27","Easter Sunday","IN",2005 +"2005-04-21","Mawlid* (*estimated)","IN",2005 +"2005-05-01","Labour Day","IN",2005 +"2005-05-15","Feast of Pentecost","IN",2005 +"2005-08-15","Independence Day","IN",2005 +"2005-10-02","Gandhi Jayanti","IN",2005 +"2005-11-01","Diwali","IN",2005 +"2005-11-03","Eid ul-Fitr* (*estimated)","IN",2005 +"2005-11-04","Eid ul-Fitr* (*estimated)","IN",2005 +"2005-12-25","Christmas Day","IN",2005 +"2006-01-10","Eid al-Adha* (*estimated)","IN",2006 +"2006-01-11","Eid al-Adha* (*estimated)","IN",2006 +"2006-01-14","Makar Sankranti / Pongal","IN",2006 +"2006-01-26","Republic Day","IN",2006 +"2006-02-09","Day of Ashura* (*estimated)","IN",2006 +"2006-03-15","Holi","IN",2006 +"2006-04-09","Palm Sunday","IN",2006 +"2006-04-10","Mawlid* (*estimated)","IN",2006 +"2006-04-14","Good Friday","IN",2006 +"2006-04-16","Easter Sunday","IN",2006 +"2006-05-01","Labour Day","IN",2006 +"2006-06-04","Feast of Pentecost","IN",2006 +"2006-08-15","Independence Day","IN",2006 +"2006-10-02","Gandhi Jayanti","IN",2006 +"2006-10-21","Diwali","IN",2006 +"2006-10-23","Eid ul-Fitr* (*estimated)","IN",2006 +"2006-10-24","Eid ul-Fitr* (*estimated)","IN",2006 +"2006-12-25","Christmas Day","IN",2006 +"2006-12-31","Eid al-Adha* (*estimated)","IN",2006 +"2007-01-01","Eid al-Adha* (*estimated)","IN",2007 +"2007-01-14","Makar Sankranti / Pongal","IN",2007 +"2007-01-26","Republic Day","IN",2007 +"2007-01-29","Day of Ashura* (*estimated)","IN",2007 +"2007-03-04","Holi","IN",2007 +"2007-03-31","Mawlid* (*estimated)","IN",2007 +"2007-04-01","Palm Sunday","IN",2007 +"2007-04-06","Good Friday","IN",2007 +"2007-04-08","Easter Sunday","IN",2007 +"2007-05-01","Labour Day","IN",2007 +"2007-05-27","Feast of Pentecost","IN",2007 +"2007-08-15","Independence Day","IN",2007 +"2007-10-02","Gandhi Jayanti","IN",2007 +"2007-10-13","Eid ul-Fitr* (*estimated)","IN",2007 +"2007-10-14","Eid ul-Fitr* (*estimated)","IN",2007 +"2007-11-09","Diwali","IN",2007 +"2007-12-20","Eid al-Adha* (*estimated)","IN",2007 +"2007-12-21","Eid al-Adha* (*estimated)","IN",2007 +"2007-12-25","Christmas Day","IN",2007 +"2008-01-14","Makar Sankranti / Pongal","IN",2008 +"2008-01-19","Day of Ashura* (*estimated)","IN",2008 +"2008-01-26","Republic Day","IN",2008 +"2008-03-16","Palm Sunday","IN",2008 +"2008-03-20","Mawlid* (*estimated)","IN",2008 +"2008-03-21","Good Friday","IN",2008 +"2008-03-22","Holi","IN",2008 +"2008-03-23","Easter Sunday","IN",2008 +"2008-05-01","Labour Day","IN",2008 +"2008-05-11","Feast of Pentecost","IN",2008 +"2008-08-15","Independence Day","IN",2008 +"2008-10-01","Eid ul-Fitr* (*estimated)","IN",2008 +"2008-10-02","Eid ul-Fitr* (*estimated)","IN",2008 +"2008-10-02","Gandhi Jayanti","IN",2008 +"2008-10-28","Diwali","IN",2008 +"2008-12-08","Eid al-Adha* (*estimated)","IN",2008 +"2008-12-09","Eid al-Adha* (*estimated)","IN",2008 +"2008-12-25","Christmas Day","IN",2008 +"2009-01-07","Day of Ashura* (*estimated)","IN",2009 +"2009-01-14","Makar Sankranti / Pongal","IN",2009 +"2009-01-26","Republic Day","IN",2009 +"2009-03-09","Mawlid* (*estimated)","IN",2009 +"2009-03-11","Holi","IN",2009 +"2009-04-05","Palm Sunday","IN",2009 +"2009-04-10","Good Friday","IN",2009 +"2009-04-12","Easter Sunday","IN",2009 +"2009-05-01","Labour Day","IN",2009 +"2009-05-31","Feast of Pentecost","IN",2009 +"2009-08-15","Independence Day","IN",2009 +"2009-09-20","Eid ul-Fitr* (*estimated)","IN",2009 +"2009-09-21","Eid ul-Fitr* (*estimated)","IN",2009 +"2009-10-02","Gandhi Jayanti","IN",2009 +"2009-10-17","Diwali","IN",2009 +"2009-11-27","Eid al-Adha* (*estimated)","IN",2009 +"2009-11-28","Eid al-Adha* (*estimated)","IN",2009 +"2009-12-25","Christmas Day","IN",2009 +"2009-12-27","Day of Ashura* (*estimated)","IN",2009 +"2010-01-14","Makar Sankranti / Pongal","IN",2010 +"2010-01-26","Republic Day","IN",2010 +"2010-02-26","Mawlid* (*estimated)","IN",2010 +"2010-03-01","Holi","IN",2010 +"2010-03-28","Palm Sunday","IN",2010 +"2010-04-02","Good Friday","IN",2010 +"2010-04-04","Easter Sunday","IN",2010 +"2010-05-01","Labour Day","IN",2010 +"2010-05-23","Feast of Pentecost","IN",2010 +"2010-08-15","Independence Day","IN",2010 +"2010-09-10","Eid ul-Fitr* (*estimated)","IN",2010 +"2010-09-11","Eid ul-Fitr* (*estimated)","IN",2010 +"2010-10-02","Gandhi Jayanti","IN",2010 +"2010-11-05","Diwali","IN",2010 +"2010-11-16","Eid al-Adha* (*estimated)","IN",2010 +"2010-11-17","Eid al-Adha* (*estimated)","IN",2010 +"2010-12-16","Day of Ashura* (*estimated)","IN",2010 +"2010-12-25","Christmas Day","IN",2010 +"2011-01-14","Makar Sankranti / Pongal","IN",2011 +"2011-01-26","Republic Day","IN",2011 +"2011-02-15","Mawlid* (*estimated)","IN",2011 +"2011-03-20","Holi","IN",2011 +"2011-04-17","Palm Sunday","IN",2011 +"2011-04-22","Good Friday","IN",2011 +"2011-04-24","Easter Sunday","IN",2011 +"2011-05-01","Labour Day","IN",2011 +"2011-06-12","Feast of Pentecost","IN",2011 +"2011-08-15","Independence Day","IN",2011 +"2011-08-30","Eid ul-Fitr* (*estimated)","IN",2011 +"2011-08-31","Eid ul-Fitr* (*estimated)","IN",2011 +"2011-10-02","Gandhi Jayanti","IN",2011 +"2011-10-26","Diwali","IN",2011 +"2011-11-06","Eid al-Adha* (*estimated)","IN",2011 +"2011-11-07","Eid al-Adha* (*estimated)","IN",2011 +"2011-12-05","Day of Ashura* (*estimated)","IN",2011 +"2011-12-25","Christmas Day","IN",2011 +"2012-01-14","Makar Sankranti / Pongal","IN",2012 +"2012-01-26","Republic Day","IN",2012 +"2012-02-04","Mawlid* (*estimated)","IN",2012 +"2012-03-08","Holi","IN",2012 +"2012-04-01","Palm Sunday","IN",2012 +"2012-04-06","Good Friday","IN",2012 +"2012-04-08","Easter Sunday","IN",2012 +"2012-05-01","Labour Day","IN",2012 +"2012-05-27","Feast of Pentecost","IN",2012 +"2012-08-15","Independence Day","IN",2012 +"2012-08-19","Eid ul-Fitr* (*estimated)","IN",2012 +"2012-08-20","Eid ul-Fitr* (*estimated)","IN",2012 +"2012-10-02","Gandhi Jayanti","IN",2012 +"2012-10-26","Eid al-Adha* (*estimated)","IN",2012 +"2012-10-27","Eid al-Adha* (*estimated)","IN",2012 +"2012-11-13","Diwali","IN",2012 +"2012-11-24","Day of Ashura* (*estimated)","IN",2012 +"2012-12-25","Christmas Day","IN",2012 +"2013-01-14","Makar Sankranti / Pongal","IN",2013 +"2013-01-24","Mawlid* (*estimated)","IN",2013 +"2013-01-26","Republic Day","IN",2013 +"2013-03-24","Palm Sunday","IN",2013 +"2013-03-27","Holi","IN",2013 +"2013-03-29","Good Friday","IN",2013 +"2013-03-31","Easter Sunday","IN",2013 +"2013-05-01","Labour Day","IN",2013 +"2013-05-19","Feast of Pentecost","IN",2013 +"2013-08-08","Eid ul-Fitr* (*estimated)","IN",2013 +"2013-08-09","Eid ul-Fitr* (*estimated)","IN",2013 +"2013-08-15","Independence Day","IN",2013 +"2013-10-02","Gandhi Jayanti","IN",2013 +"2013-10-15","Eid al-Adha* (*estimated)","IN",2013 +"2013-10-16","Eid al-Adha* (*estimated)","IN",2013 +"2013-11-03","Diwali","IN",2013 +"2013-11-13","Day of Ashura* (*estimated)","IN",2013 +"2013-12-25","Christmas Day","IN",2013 +"2014-01-13","Mawlid* (*estimated)","IN",2014 +"2014-01-14","Makar Sankranti / Pongal","IN",2014 +"2014-01-26","Republic Day","IN",2014 +"2014-03-17","Holi","IN",2014 +"2014-04-13","Palm Sunday","IN",2014 +"2014-04-18","Good Friday","IN",2014 +"2014-04-20","Easter Sunday","IN",2014 +"2014-05-01","Labour Day","IN",2014 +"2014-06-08","Feast of Pentecost","IN",2014 +"2014-07-28","Eid ul-Fitr* (*estimated)","IN",2014 +"2014-07-29","Eid ul-Fitr* (*estimated)","IN",2014 +"2014-08-15","Independence Day","IN",2014 +"2014-10-02","Gandhi Jayanti","IN",2014 +"2014-10-04","Eid al-Adha* (*estimated)","IN",2014 +"2014-10-05","Eid al-Adha* (*estimated)","IN",2014 +"2014-10-23","Diwali","IN",2014 +"2014-11-03","Day of Ashura* (*estimated)","IN",2014 +"2014-12-25","Christmas Day","IN",2014 +"2015-01-03","Mawlid* (*estimated)","IN",2015 +"2015-01-14","Makar Sankranti / Pongal","IN",2015 +"2015-01-26","Republic Day","IN",2015 +"2015-03-06","Holi","IN",2015 +"2015-03-29","Palm Sunday","IN",2015 +"2015-04-03","Good Friday","IN",2015 +"2015-04-05","Easter Sunday","IN",2015 +"2015-05-01","Labour Day","IN",2015 +"2015-05-24","Feast of Pentecost","IN",2015 +"2015-07-17","Eid ul-Fitr* (*estimated)","IN",2015 +"2015-07-18","Eid ul-Fitr* (*estimated)","IN",2015 +"2015-08-15","Independence Day","IN",2015 +"2015-09-23","Eid al-Adha* (*estimated)","IN",2015 +"2015-09-24","Eid al-Adha* (*estimated)","IN",2015 +"2015-10-02","Gandhi Jayanti","IN",2015 +"2015-10-23","Day of Ashura* (*estimated)","IN",2015 +"2015-11-11","Diwali","IN",2015 +"2015-12-23","Mawlid* (*estimated)","IN",2015 +"2015-12-25","Christmas Day","IN",2015 +"2016-01-14","Makar Sankranti / Pongal","IN",2016 +"2016-01-26","Republic Day","IN",2016 +"2016-03-20","Palm Sunday","IN",2016 +"2016-03-24","Holi","IN",2016 +"2016-03-25","Good Friday","IN",2016 +"2016-03-27","Easter Sunday","IN",2016 +"2016-05-01","Labour Day","IN",2016 +"2016-05-15","Feast of Pentecost","IN",2016 +"2016-07-06","Eid ul-Fitr* (*estimated)","IN",2016 +"2016-07-07","Eid ul-Fitr* (*estimated)","IN",2016 +"2016-08-15","Independence Day","IN",2016 +"2016-09-11","Eid al-Adha* (*estimated)","IN",2016 +"2016-09-12","Eid al-Adha* (*estimated)","IN",2016 +"2016-10-02","Gandhi Jayanti","IN",2016 +"2016-10-11","Day of Ashura* (*estimated)","IN",2016 +"2016-10-30","Diwali","IN",2016 +"2016-12-11","Mawlid* (*estimated)","IN",2016 +"2016-12-25","Christmas Day","IN",2016 +"2017-01-14","Makar Sankranti / Pongal","IN",2017 +"2017-01-26","Republic Day","IN",2017 +"2017-03-13","Holi","IN",2017 +"2017-04-09","Palm Sunday","IN",2017 +"2017-04-14","Good Friday","IN",2017 +"2017-04-16","Easter Sunday","IN",2017 +"2017-05-01","Labour Day","IN",2017 +"2017-06-04","Feast of Pentecost","IN",2017 +"2017-06-25","Eid ul-Fitr* (*estimated)","IN",2017 +"2017-06-26","Eid ul-Fitr* (*estimated)","IN",2017 +"2017-08-15","Independence Day","IN",2017 +"2017-09-01","Eid al-Adha* (*estimated)","IN",2017 +"2017-09-02","Eid al-Adha* (*estimated)","IN",2017 +"2017-09-30","Day of Ashura* (*estimated)","IN",2017 +"2017-10-02","Gandhi Jayanti","IN",2017 +"2017-10-19","Diwali","IN",2017 +"2017-11-30","Mawlid* (*estimated)","IN",2017 +"2017-12-25","Christmas Day","IN",2017 +"2018-01-14","Makar Sankranti / Pongal","IN",2018 +"2018-01-26","Republic Day","IN",2018 +"2018-03-02","Holi","IN",2018 +"2018-03-25","Palm Sunday","IN",2018 +"2018-03-30","Good Friday","IN",2018 +"2018-04-01","Easter Sunday","IN",2018 +"2018-05-01","Labour Day","IN",2018 +"2018-05-20","Feast of Pentecost","IN",2018 +"2018-06-15","Eid ul-Fitr* (*estimated)","IN",2018 +"2018-06-16","Eid ul-Fitr* (*estimated)","IN",2018 +"2018-08-15","Independence Day","IN",2018 +"2018-08-21","Eid al-Adha* (*estimated)","IN",2018 +"2018-08-22","Eid al-Adha* (*estimated)","IN",2018 +"2018-09-20","Day of Ashura* (*estimated)","IN",2018 +"2018-10-02","Gandhi Jayanti","IN",2018 +"2018-11-07","Diwali","IN",2018 +"2018-11-20","Mawlid* (*estimated)","IN",2018 +"2018-12-25","Christmas Day","IN",2018 +"2019-01-14","Makar Sankranti / Pongal","IN",2019 +"2019-01-26","Republic Day","IN",2019 +"2019-03-21","Holi","IN",2019 +"2019-04-14","Palm Sunday","IN",2019 +"2019-04-19","Good Friday","IN",2019 +"2019-04-21","Easter Sunday","IN",2019 +"2019-05-01","Labour Day","IN",2019 +"2019-06-04","Eid ul-Fitr* (*estimated)","IN",2019 +"2019-06-05","Eid ul-Fitr* (*estimated)","IN",2019 +"2019-06-09","Feast of Pentecost","IN",2019 +"2019-08-11","Eid al-Adha* (*estimated)","IN",2019 +"2019-08-12","Eid al-Adha* (*estimated)","IN",2019 +"2019-08-15","Independence Day","IN",2019 +"2019-09-09","Day of Ashura* (*estimated)","IN",2019 +"2019-10-02","Gandhi Jayanti","IN",2019 +"2019-10-27","Diwali","IN",2019 +"2019-11-09","Mawlid* (*estimated)","IN",2019 +"2019-12-25","Christmas Day","IN",2019 +"2020-01-14","Makar Sankranti / Pongal","IN",2020 +"2020-01-26","Republic Day","IN",2020 +"2020-03-10","Holi","IN",2020 +"2020-04-05","Palm Sunday","IN",2020 +"2020-04-10","Good Friday","IN",2020 +"2020-04-12","Easter Sunday","IN",2020 +"2020-05-01","Labour Day","IN",2020 +"2020-05-24","Eid ul-Fitr* (*estimated)","IN",2020 +"2020-05-25","Eid ul-Fitr* (*estimated)","IN",2020 +"2020-05-31","Feast of Pentecost","IN",2020 +"2020-07-31","Eid al-Adha* (*estimated)","IN",2020 +"2020-08-01","Eid al-Adha* (*estimated)","IN",2020 +"2020-08-15","Independence Day","IN",2020 +"2020-08-29","Day of Ashura* (*estimated)","IN",2020 +"2020-10-02","Gandhi Jayanti","IN",2020 +"2020-10-29","Mawlid* (*estimated)","IN",2020 +"2020-11-14","Diwali","IN",2020 +"2020-12-25","Christmas Day","IN",2020 +"2021-01-14","Makar Sankranti / Pongal","IN",2021 +"2021-01-26","Republic Day","IN",2021 +"2021-03-28","Palm Sunday","IN",2021 +"2021-03-29","Holi","IN",2021 +"2021-04-02","Good Friday","IN",2021 +"2021-04-04","Easter Sunday","IN",2021 +"2021-05-01","Labour Day","IN",2021 +"2021-05-13","Eid ul-Fitr* (*estimated)","IN",2021 +"2021-05-14","Eid ul-Fitr* (*estimated)","IN",2021 +"2021-05-23","Feast of Pentecost","IN",2021 +"2021-07-20","Eid al-Adha* (*estimated)","IN",2021 +"2021-07-21","Eid al-Adha* (*estimated)","IN",2021 +"2021-08-15","Independence Day","IN",2021 +"2021-08-18","Day of Ashura* (*estimated)","IN",2021 +"2021-10-02","Gandhi Jayanti","IN",2021 +"2021-10-18","Mawlid* (*estimated)","IN",2021 +"2021-11-04","Diwali","IN",2021 +"2021-12-25","Christmas Day","IN",2021 +"2022-01-14","Makar Sankranti / Pongal","IN",2022 +"2022-01-26","Republic Day","IN",2022 +"2022-03-18","Holi","IN",2022 +"2022-04-10","Palm Sunday","IN",2022 +"2022-04-15","Good Friday","IN",2022 +"2022-04-17","Easter Sunday","IN",2022 +"2022-05-01","Labour Day","IN",2022 +"2022-05-02","Eid ul-Fitr* (*estimated)","IN",2022 +"2022-05-03","Eid ul-Fitr* (*estimated)","IN",2022 +"2022-06-05","Feast of Pentecost","IN",2022 +"2022-07-09","Eid al-Adha* (*estimated)","IN",2022 +"2022-07-10","Eid al-Adha* (*estimated)","IN",2022 +"2022-08-08","Day of Ashura* (*estimated)","IN",2022 +"2022-08-15","Independence Day","IN",2022 +"2022-10-02","Gandhi Jayanti","IN",2022 +"2022-10-08","Mawlid* (*estimated)","IN",2022 +"2022-10-24","Diwali","IN",2022 +"2022-12-25","Christmas Day","IN",2022 +"2023-01-14","Makar Sankranti / Pongal","IN",2023 +"2023-01-26","Republic Day","IN",2023 +"2023-03-08","Holi","IN",2023 +"2023-04-02","Palm Sunday","IN",2023 +"2023-04-07","Good Friday","IN",2023 +"2023-04-09","Easter Sunday","IN",2023 +"2023-04-21","Eid ul-Fitr* (*estimated)","IN",2023 +"2023-04-22","Eid ul-Fitr* (*estimated)","IN",2023 +"2023-05-01","Labour Day","IN",2023 +"2023-05-28","Feast of Pentecost","IN",2023 +"2023-06-28","Eid al-Adha* (*estimated)","IN",2023 +"2023-06-29","Eid al-Adha* (*estimated)","IN",2023 +"2023-07-28","Day of Ashura* (*estimated)","IN",2023 +"2023-08-15","Independence Day","IN",2023 +"2023-09-27","Mawlid* (*estimated)","IN",2023 +"2023-10-02","Gandhi Jayanti","IN",2023 +"2023-11-12","Diwali","IN",2023 +"2023-12-25","Christmas Day","IN",2023 +"2024-01-14","Makar Sankranti / Pongal","IN",2024 +"2024-01-26","Republic Day","IN",2024 +"2024-03-24","Palm Sunday","IN",2024 +"2024-03-25","Holi","IN",2024 +"2024-03-29","Good Friday","IN",2024 +"2024-03-31","Easter Sunday","IN",2024 +"2024-04-10","Eid ul-Fitr* (*estimated)","IN",2024 +"2024-04-11","Eid ul-Fitr* (*estimated)","IN",2024 +"2024-05-01","Labour Day","IN",2024 +"2024-05-19","Feast of Pentecost","IN",2024 +"2024-06-16","Eid al-Adha* (*estimated)","IN",2024 +"2024-06-17","Eid al-Adha* (*estimated)","IN",2024 +"2024-07-16","Day of Ashura* (*estimated)","IN",2024 +"2024-08-15","Independence Day","IN",2024 +"2024-09-15","Mawlid* (*estimated)","IN",2024 +"2024-10-02","Gandhi Jayanti","IN",2024 +"2024-11-01","Diwali","IN",2024 +"2024-12-25","Christmas Day","IN",2024 +"2025-01-14","Makar Sankranti / Pongal","IN",2025 +"2025-01-26","Republic Day","IN",2025 +"2025-03-14","Holi","IN",2025 +"2025-03-30","Eid ul-Fitr* (*estimated)","IN",2025 +"2025-03-31","Eid ul-Fitr* (*estimated)","IN",2025 +"2025-04-13","Palm Sunday","IN",2025 +"2025-04-18","Good Friday","IN",2025 +"2025-04-20","Easter Sunday","IN",2025 +"2025-05-01","Labour Day","IN",2025 +"2025-06-06","Eid al-Adha* (*estimated)","IN",2025 +"2025-06-07","Eid al-Adha* (*estimated)","IN",2025 +"2025-06-08","Feast of Pentecost","IN",2025 +"2025-07-05","Day of Ashura* (*estimated)","IN",2025 +"2025-08-15","Independence Day","IN",2025 +"2025-09-04","Mawlid* (*estimated)","IN",2025 +"2025-10-02","Gandhi Jayanti","IN",2025 +"2025-10-20","Diwali","IN",2025 +"2025-12-25","Christmas Day","IN",2025 +"2026-01-14","Makar Sankranti / Pongal","IN",2026 +"2026-01-26","Republic Day","IN",2026 +"2026-03-04","Holi","IN",2026 +"2026-03-20","Eid ul-Fitr* (*estimated)","IN",2026 +"2026-03-21","Eid ul-Fitr* (*estimated)","IN",2026 +"2026-03-29","Palm Sunday","IN",2026 +"2026-04-03","Good Friday","IN",2026 +"2026-04-05","Easter Sunday","IN",2026 +"2026-05-01","Labour Day","IN",2026 +"2026-05-24","Feast of Pentecost","IN",2026 +"2026-05-27","Eid al-Adha* (*estimated)","IN",2026 +"2026-05-28","Eid al-Adha* (*estimated)","IN",2026 +"2026-06-25","Day of Ashura* (*estimated)","IN",2026 +"2026-08-15","Independence Day","IN",2026 +"2026-08-25","Mawlid* (*estimated)","IN",2026 +"2026-10-02","Gandhi Jayanti","IN",2026 +"2026-11-08","Diwali","IN",2026 +"2026-12-25","Christmas Day","IN",2026 +"2027-01-14","Makar Sankranti / Pongal","IN",2027 +"2027-01-26","Republic Day","IN",2027 +"2027-03-09","Eid ul-Fitr* (*estimated)","IN",2027 +"2027-03-10","Eid ul-Fitr* (*estimated)","IN",2027 +"2027-03-21","Palm Sunday","IN",2027 +"2027-03-22","Holi","IN",2027 +"2027-03-26","Good Friday","IN",2027 +"2027-03-28","Easter Sunday","IN",2027 +"2027-05-01","Labour Day","IN",2027 +"2027-05-16","Eid al-Adha* (*estimated)","IN",2027 +"2027-05-16","Feast of Pentecost","IN",2027 +"2027-05-17","Eid al-Adha* (*estimated)","IN",2027 +"2027-06-15","Day of Ashura* (*estimated)","IN",2027 +"2027-08-14","Mawlid* (*estimated)","IN",2027 +"2027-08-15","Independence Day","IN",2027 +"2027-10-02","Gandhi Jayanti","IN",2027 +"2027-10-29","Diwali","IN",2027 +"2027-12-25","Christmas Day","IN",2027 +"2028-01-14","Makar Sankranti / Pongal","IN",2028 +"2028-01-26","Republic Day","IN",2028 +"2028-02-26","Eid ul-Fitr* (*estimated)","IN",2028 +"2028-02-27","Eid ul-Fitr* (*estimated)","IN",2028 +"2028-03-11","Holi","IN",2028 +"2028-04-09","Palm Sunday","IN",2028 +"2028-04-14","Good Friday","IN",2028 +"2028-04-16","Easter Sunday","IN",2028 +"2028-05-01","Labour Day","IN",2028 +"2028-05-05","Eid al-Adha* (*estimated)","IN",2028 +"2028-05-06","Eid al-Adha* (*estimated)","IN",2028 +"2028-06-03","Day of Ashura* (*estimated)","IN",2028 +"2028-06-04","Feast of Pentecost","IN",2028 +"2028-08-03","Mawlid* (*estimated)","IN",2028 +"2028-08-15","Independence Day","IN",2028 +"2028-10-02","Gandhi Jayanti","IN",2028 +"2028-10-17","Diwali","IN",2028 +"2028-12-25","Christmas Day","IN",2028 +"2029-01-14","Makar Sankranti / Pongal","IN",2029 +"2029-01-26","Republic Day","IN",2029 +"2029-02-14","Eid ul-Fitr* (*estimated)","IN",2029 +"2029-02-15","Eid ul-Fitr* (*estimated)","IN",2029 +"2029-03-01","Holi","IN",2029 +"2029-03-25","Palm Sunday","IN",2029 +"2029-03-30","Good Friday","IN",2029 +"2029-04-01","Easter Sunday","IN",2029 +"2029-04-24","Eid al-Adha* (*estimated)","IN",2029 +"2029-04-25","Eid al-Adha* (*estimated)","IN",2029 +"2029-05-01","Labour Day","IN",2029 +"2029-05-20","Feast of Pentecost","IN",2029 +"2029-05-23","Day of Ashura* (*estimated)","IN",2029 +"2029-07-24","Mawlid* (*estimated)","IN",2029 +"2029-08-15","Independence Day","IN",2029 +"2029-10-02","Gandhi Jayanti","IN",2029 +"2029-11-05","Diwali","IN",2029 +"2029-12-25","Christmas Day","IN",2029 +"2030-01-14","Makar Sankranti / Pongal","IN",2030 +"2030-01-26","Republic Day","IN",2030 +"2030-02-04","Eid ul-Fitr* (*estimated)","IN",2030 +"2030-02-05","Eid ul-Fitr* (*estimated)","IN",2030 +"2030-03-20","Holi","IN",2030 +"2030-04-13","Eid al-Adha* (*estimated)","IN",2030 +"2030-04-14","Eid al-Adha* (*estimated)","IN",2030 +"2030-04-14","Palm Sunday","IN",2030 +"2030-04-19","Good Friday","IN",2030 +"2030-04-21","Easter Sunday","IN",2030 +"2030-05-01","Labour Day","IN",2030 +"2030-05-12","Day of Ashura* (*estimated)","IN",2030 +"2030-06-09","Feast of Pentecost","IN",2030 +"2030-07-13","Mawlid* (*estimated)","IN",2030 +"2030-08-15","Independence Day","IN",2030 +"2030-10-02","Gandhi Jayanti","IN",2030 +"2030-10-26","Diwali","IN",2030 +"2030-12-25","Christmas Day","IN",2030 +"2031-01-14","Makar Sankranti / Pongal","IN",2031 +"2031-01-24","Eid ul-Fitr* (*estimated)","IN",2031 +"2031-01-25","Eid ul-Fitr* (*estimated)","IN",2031 +"2031-01-26","Republic Day","IN",2031 +"2031-04-02","Eid al-Adha* (*estimated)","IN",2031 +"2031-04-03","Eid al-Adha* (*estimated)","IN",2031 +"2031-04-06","Palm Sunday","IN",2031 +"2031-04-11","Good Friday","IN",2031 +"2031-04-13","Easter Sunday","IN",2031 +"2031-05-01","Labour Day","IN",2031 +"2031-05-02","Day of Ashura* (*estimated)","IN",2031 +"2031-06-01","Feast of Pentecost","IN",2031 +"2031-07-02","Mawlid* (*estimated)","IN",2031 +"2031-08-15","Independence Day","IN",2031 +"2031-10-02","Gandhi Jayanti","IN",2031 +"2031-12-25","Christmas Day","IN",2031 +"2032-01-14","Eid ul-Fitr* (*estimated)","IN",2032 +"2032-01-14","Makar Sankranti / Pongal","IN",2032 +"2032-01-15","Eid ul-Fitr* (*estimated)","IN",2032 +"2032-01-26","Republic Day","IN",2032 +"2032-03-21","Palm Sunday","IN",2032 +"2032-03-22","Eid al-Adha* (*estimated)","IN",2032 +"2032-03-23","Eid al-Adha* (*estimated)","IN",2032 +"2032-03-26","Good Friday","IN",2032 +"2032-03-28","Easter Sunday","IN",2032 +"2032-04-20","Day of Ashura* (*estimated)","IN",2032 +"2032-05-01","Labour Day","IN",2032 +"2032-05-16","Feast of Pentecost","IN",2032 +"2032-06-20","Mawlid* (*estimated)","IN",2032 +"2032-08-15","Independence Day","IN",2032 +"2032-10-02","Gandhi Jayanti","IN",2032 +"2032-12-25","Christmas Day","IN",2032 +"2033-01-02","Eid ul-Fitr* (*estimated)","IN",2033 +"2033-01-03","Eid ul-Fitr* (*estimated)","IN",2033 +"2033-01-14","Makar Sankranti / Pongal","IN",2033 +"2033-01-26","Republic Day","IN",2033 +"2033-03-11","Eid al-Adha* (*estimated)","IN",2033 +"2033-03-12","Eid al-Adha* (*estimated)","IN",2033 +"2033-04-10","Day of Ashura* (*estimated)","IN",2033 +"2033-04-10","Palm Sunday","IN",2033 +"2033-04-15","Good Friday","IN",2033 +"2033-04-17","Easter Sunday","IN",2033 +"2033-05-01","Labour Day","IN",2033 +"2033-06-05","Feast of Pentecost","IN",2033 +"2033-06-09","Mawlid* (*estimated)","IN",2033 +"2033-08-15","Independence Day","IN",2033 +"2033-10-02","Gandhi Jayanti","IN",2033 +"2033-12-23","Eid ul-Fitr* (*estimated)","IN",2033 +"2033-12-24","Eid ul-Fitr* (*estimated)","IN",2033 +"2033-12-25","Christmas Day","IN",2033 +"2034-01-14","Makar Sankranti / Pongal","IN",2034 +"2034-01-26","Republic Day","IN",2034 +"2034-03-01","Eid al-Adha* (*estimated)","IN",2034 +"2034-03-02","Eid al-Adha* (*estimated)","IN",2034 +"2034-03-30","Day of Ashura* (*estimated)","IN",2034 +"2034-04-02","Palm Sunday","IN",2034 +"2034-04-07","Good Friday","IN",2034 +"2034-04-09","Easter Sunday","IN",2034 +"2034-05-01","Labour Day","IN",2034 +"2034-05-28","Feast of Pentecost","IN",2034 +"2034-05-30","Mawlid* (*estimated)","IN",2034 +"2034-08-15","Independence Day","IN",2034 +"2034-10-02","Gandhi Jayanti","IN",2034 +"2034-12-12","Eid ul-Fitr* (*estimated)","IN",2034 +"2034-12-13","Eid ul-Fitr* (*estimated)","IN",2034 +"2034-12-25","Christmas Day","IN",2034 +"2035-01-14","Makar Sankranti / Pongal","IN",2035 +"2035-01-26","Republic Day","IN",2035 +"2035-02-18","Eid al-Adha* (*estimated)","IN",2035 +"2035-02-19","Eid al-Adha* (*estimated)","IN",2035 +"2035-03-18","Palm Sunday","IN",2035 +"2035-03-20","Day of Ashura* (*estimated)","IN",2035 +"2035-03-23","Good Friday","IN",2035 +"2035-03-25","Easter Sunday","IN",2035 +"2035-05-01","Labour Day","IN",2035 +"2035-05-13","Feast of Pentecost","IN",2035 +"2035-05-20","Mawlid* (*estimated)","IN",2035 +"2035-08-15","Independence Day","IN",2035 +"2035-10-02","Gandhi Jayanti","IN",2035 +"2035-12-01","Eid ul-Fitr* (*estimated)","IN",2035 +"2035-12-02","Eid ul-Fitr* (*estimated)","IN",2035 +"2035-12-25","Christmas Day","IN",2035 +"2036-01-14","Makar Sankranti / Pongal","IN",2036 +"2036-01-26","Republic Day","IN",2036 +"2036-02-07","Eid al-Adha* (*estimated)","IN",2036 +"2036-02-08","Eid al-Adha* (*estimated)","IN",2036 +"2036-03-08","Day of Ashura* (*estimated)","IN",2036 +"2036-04-06","Palm Sunday","IN",2036 +"2036-04-11","Good Friday","IN",2036 +"2036-04-13","Easter Sunday","IN",2036 +"2036-05-01","Labour Day","IN",2036 +"2036-05-08","Mawlid* (*estimated)","IN",2036 +"2036-06-01","Feast of Pentecost","IN",2036 +"2036-08-15","Independence Day","IN",2036 +"2036-10-02","Gandhi Jayanti","IN",2036 +"2036-11-19","Eid ul-Fitr* (*estimated)","IN",2036 +"2036-11-20","Eid ul-Fitr* (*estimated)","IN",2036 +"2036-12-25","Christmas Day","IN",2036 +"2037-01-14","Makar Sankranti / Pongal","IN",2037 +"2037-01-26","Eid al-Adha* (*estimated)","IN",2037 +"2037-01-26","Republic Day","IN",2037 +"2037-01-27","Eid al-Adha* (*estimated)","IN",2037 +"2037-02-25","Day of Ashura* (*estimated)","IN",2037 +"2037-03-29","Palm Sunday","IN",2037 +"2037-04-03","Good Friday","IN",2037 +"2037-04-05","Easter Sunday","IN",2037 +"2037-04-28","Mawlid* (*estimated)","IN",2037 +"2037-05-01","Labour Day","IN",2037 +"2037-05-24","Feast of Pentecost","IN",2037 +"2037-08-15","Independence Day","IN",2037 +"2037-10-02","Gandhi Jayanti","IN",2037 +"2037-11-08","Eid ul-Fitr* (*estimated)","IN",2037 +"2037-11-09","Eid ul-Fitr* (*estimated)","IN",2037 +"2037-12-25","Christmas Day","IN",2037 +"2038-01-14","Makar Sankranti / Pongal","IN",2038 +"2038-01-16","Eid al-Adha* (*estimated)","IN",2038 +"2038-01-17","Eid al-Adha* (*estimated)","IN",2038 +"2038-01-26","Republic Day","IN",2038 +"2038-02-14","Day of Ashura* (*estimated)","IN",2038 +"2038-04-17","Mawlid* (*estimated)","IN",2038 +"2038-04-18","Palm Sunday","IN",2038 +"2038-04-23","Good Friday","IN",2038 +"2038-04-25","Easter Sunday","IN",2038 +"2038-05-01","Labour Day","IN",2038 +"2038-06-13","Feast of Pentecost","IN",2038 +"2038-08-15","Independence Day","IN",2038 +"2038-10-02","Gandhi Jayanti","IN",2038 +"2038-10-29","Eid ul-Fitr* (*estimated)","IN",2038 +"2038-10-30","Eid ul-Fitr* (*estimated)","IN",2038 +"2038-12-25","Christmas Day","IN",2038 +"2039-01-05","Eid al-Adha* (*estimated)","IN",2039 +"2039-01-06","Eid al-Adha* (*estimated)","IN",2039 +"2039-01-14","Makar Sankranti / Pongal","IN",2039 +"2039-01-26","Republic Day","IN",2039 +"2039-02-04","Day of Ashura* (*estimated)","IN",2039 +"2039-04-03","Palm Sunday","IN",2039 +"2039-04-06","Mawlid* (*estimated)","IN",2039 +"2039-04-08","Good Friday","IN",2039 +"2039-04-10","Easter Sunday","IN",2039 +"2039-05-01","Labour Day","IN",2039 +"2039-05-29","Feast of Pentecost","IN",2039 +"2039-08-15","Independence Day","IN",2039 +"2039-10-02","Gandhi Jayanti","IN",2039 +"2039-10-19","Eid ul-Fitr* (*estimated)","IN",2039 +"2039-10-20","Eid ul-Fitr* (*estimated)","IN",2039 +"2039-12-25","Christmas Day","IN",2039 +"2039-12-26","Eid al-Adha* (*estimated)","IN",2039 +"2039-12-27","Eid al-Adha* (*estimated)","IN",2039 +"2040-01-14","Makar Sankranti / Pongal","IN",2040 +"2040-01-24","Day of Ashura* (*estimated)","IN",2040 +"2040-01-26","Republic Day","IN",2040 +"2040-03-25","Mawlid* (*estimated)","IN",2040 +"2040-03-25","Palm Sunday","IN",2040 +"2040-03-30","Good Friday","IN",2040 +"2040-04-01","Easter Sunday","IN",2040 +"2040-05-01","Labour Day","IN",2040 +"2040-05-20","Feast of Pentecost","IN",2040 +"2040-08-15","Independence Day","IN",2040 +"2040-10-02","Gandhi Jayanti","IN",2040 +"2040-10-07","Eid ul-Fitr* (*estimated)","IN",2040 +"2040-10-08","Eid ul-Fitr* (*estimated)","IN",2040 +"2040-12-14","Eid al-Adha* (*estimated)","IN",2040 +"2040-12-15","Eid al-Adha* (*estimated)","IN",2040 +"2040-12-25","Christmas Day","IN",2040 +"2041-01-13","Day of Ashura* (*estimated)","IN",2041 +"2041-01-14","Makar Sankranti / Pongal","IN",2041 +"2041-01-26","Republic Day","IN",2041 +"2041-03-15","Mawlid* (*estimated)","IN",2041 +"2041-04-14","Palm Sunday","IN",2041 +"2041-04-19","Good Friday","IN",2041 +"2041-04-21","Easter Sunday","IN",2041 +"2041-05-01","Labour Day","IN",2041 +"2041-06-09","Feast of Pentecost","IN",2041 +"2041-08-15","Independence Day","IN",2041 +"2041-09-26","Eid ul-Fitr* (*estimated)","IN",2041 +"2041-09-27","Eid ul-Fitr* (*estimated)","IN",2041 +"2041-10-02","Gandhi Jayanti","IN",2041 +"2041-12-04","Eid al-Adha* (*estimated)","IN",2041 +"2041-12-05","Eid al-Adha* (*estimated)","IN",2041 +"2041-12-25","Christmas Day","IN",2041 +"2042-01-02","Day of Ashura* (*estimated)","IN",2042 +"2042-01-14","Makar Sankranti / Pongal","IN",2042 +"2042-01-26","Republic Day","IN",2042 +"2042-03-04","Mawlid* (*estimated)","IN",2042 +"2042-03-30","Palm Sunday","IN",2042 +"2042-04-04","Good Friday","IN",2042 +"2042-04-06","Easter Sunday","IN",2042 +"2042-05-01","Labour Day","IN",2042 +"2042-05-25","Feast of Pentecost","IN",2042 +"2042-08-15","Independence Day","IN",2042 +"2042-09-15","Eid ul-Fitr* (*estimated)","IN",2042 +"2042-09-16","Eid ul-Fitr* (*estimated)","IN",2042 +"2042-10-02","Gandhi Jayanti","IN",2042 +"2042-11-23","Eid al-Adha* (*estimated)","IN",2042 +"2042-11-24","Eid al-Adha* (*estimated)","IN",2042 +"2042-12-23","Day of Ashura* (*estimated)","IN",2042 +"2042-12-25","Christmas Day","IN",2042 +"2043-01-14","Makar Sankranti / Pongal","IN",2043 +"2043-01-26","Republic Day","IN",2043 +"2043-02-22","Mawlid* (*estimated)","IN",2043 +"2043-03-22","Palm Sunday","IN",2043 +"2043-03-27","Good Friday","IN",2043 +"2043-03-29","Easter Sunday","IN",2043 +"2043-05-01","Labour Day","IN",2043 +"2043-05-17","Feast of Pentecost","IN",2043 +"2043-08-15","Independence Day","IN",2043 +"2043-09-04","Eid ul-Fitr* (*estimated)","IN",2043 +"2043-09-05","Eid ul-Fitr* (*estimated)","IN",2043 +"2043-10-02","Gandhi Jayanti","IN",2043 +"2043-11-12","Eid al-Adha* (*estimated)","IN",2043 +"2043-11-13","Eid al-Adha* (*estimated)","IN",2043 +"2043-12-12","Day of Ashura* (*estimated)","IN",2043 +"2043-12-25","Christmas Day","IN",2043 +"2044-01-14","Makar Sankranti / Pongal","IN",2044 +"2044-01-26","Republic Day","IN",2044 +"2044-02-11","Mawlid* (*estimated)","IN",2044 +"2044-04-10","Palm Sunday","IN",2044 +"2044-04-15","Good Friday","IN",2044 +"2044-04-17","Easter Sunday","IN",2044 +"2044-05-01","Labour Day","IN",2044 +"2044-06-05","Feast of Pentecost","IN",2044 +"2044-08-15","Independence Day","IN",2044 +"2044-08-24","Eid ul-Fitr* (*estimated)","IN",2044 +"2044-08-25","Eid ul-Fitr* (*estimated)","IN",2044 +"2044-10-02","Gandhi Jayanti","IN",2044 +"2044-10-31","Eid al-Adha* (*estimated)","IN",2044 +"2044-11-01","Eid al-Adha* (*estimated)","IN",2044 +"2044-11-30","Day of Ashura* (*estimated)","IN",2044 +"2044-12-25","Christmas Day","IN",2044 +"1995-01-01","New Year's Day","IS",1995 +"1995-04-13","Maundy Thursday","IS",1995 +"1995-04-14","Good Friday","IS",1995 +"1995-04-16","Easter Sunday","IS",1995 +"1995-04-17","Easter Monday","IS",1995 +"1995-04-20","First Day of Summer","IS",1995 +"1995-05-01","Labor Day","IS",1995 +"1995-05-25","Ascension Day","IS",1995 +"1995-06-04","Whit Sunday","IS",1995 +"1995-06-05","Whit Monday","IS",1995 +"1995-06-17","National Day","IS",1995 +"1995-08-07","Commerce Day","IS",1995 +"1995-12-24","Christmas Eve","IS",1995 +"1995-12-25","Christmas Day","IS",1995 +"1995-12-26","Second Day of Christmas","IS",1995 +"1995-12-31","New Year's Eve","IS",1995 +"1996-01-01","New Year's Day","IS",1996 +"1996-04-04","Maundy Thursday","IS",1996 +"1996-04-05","Good Friday","IS",1996 +"1996-04-07","Easter Sunday","IS",1996 +"1996-04-08","Easter Monday","IS",1996 +"1996-04-25","First Day of Summer","IS",1996 +"1996-05-01","Labor Day","IS",1996 +"1996-05-16","Ascension Day","IS",1996 +"1996-05-26","Whit Sunday","IS",1996 +"1996-05-27","Whit Monday","IS",1996 +"1996-06-17","National Day","IS",1996 +"1996-08-05","Commerce Day","IS",1996 +"1996-12-24","Christmas Eve","IS",1996 +"1996-12-25","Christmas Day","IS",1996 +"1996-12-26","Second Day of Christmas","IS",1996 +"1996-12-31","New Year's Eve","IS",1996 +"1997-01-01","New Year's Day","IS",1997 +"1997-03-27","Maundy Thursday","IS",1997 +"1997-03-28","Good Friday","IS",1997 +"1997-03-30","Easter Sunday","IS",1997 +"1997-03-31","Easter Monday","IS",1997 +"1997-04-24","First Day of Summer","IS",1997 +"1997-05-01","Labor Day","IS",1997 +"1997-05-08","Ascension Day","IS",1997 +"1997-05-18","Whit Sunday","IS",1997 +"1997-05-19","Whit Monday","IS",1997 +"1997-06-17","National Day","IS",1997 +"1997-08-04","Commerce Day","IS",1997 +"1997-12-24","Christmas Eve","IS",1997 +"1997-12-25","Christmas Day","IS",1997 +"1997-12-26","Second Day of Christmas","IS",1997 +"1997-12-31","New Year's Eve","IS",1997 +"1998-01-01","New Year's Day","IS",1998 +"1998-04-09","Maundy Thursday","IS",1998 +"1998-04-10","Good Friday","IS",1998 +"1998-04-12","Easter Sunday","IS",1998 +"1998-04-13","Easter Monday","IS",1998 +"1998-04-23","First Day of Summer","IS",1998 +"1998-05-01","Labor Day","IS",1998 +"1998-05-21","Ascension Day","IS",1998 +"1998-05-31","Whit Sunday","IS",1998 +"1998-06-01","Whit Monday","IS",1998 +"1998-06-17","National Day","IS",1998 +"1998-08-03","Commerce Day","IS",1998 +"1998-12-24","Christmas Eve","IS",1998 +"1998-12-25","Christmas Day","IS",1998 +"1998-12-26","Second Day of Christmas","IS",1998 +"1998-12-31","New Year's Eve","IS",1998 +"1999-01-01","New Year's Day","IS",1999 +"1999-04-01","Maundy Thursday","IS",1999 +"1999-04-02","Good Friday","IS",1999 +"1999-04-04","Easter Sunday","IS",1999 +"1999-04-05","Easter Monday","IS",1999 +"1999-04-22","First Day of Summer","IS",1999 +"1999-05-01","Labor Day","IS",1999 +"1999-05-13","Ascension Day","IS",1999 +"1999-05-23","Whit Sunday","IS",1999 +"1999-05-24","Whit Monday","IS",1999 +"1999-06-17","National Day","IS",1999 +"1999-08-02","Commerce Day","IS",1999 +"1999-12-24","Christmas Eve","IS",1999 +"1999-12-25","Christmas Day","IS",1999 +"1999-12-26","Second Day of Christmas","IS",1999 +"1999-12-31","New Year's Eve","IS",1999 +"2000-01-01","New Year's Day","IS",2000 +"2000-04-20","First Day of Summer","IS",2000 +"2000-04-20","Maundy Thursday","IS",2000 +"2000-04-21","Good Friday","IS",2000 +"2000-04-23","Easter Sunday","IS",2000 +"2000-04-24","Easter Monday","IS",2000 +"2000-05-01","Labor Day","IS",2000 +"2000-06-01","Ascension Day","IS",2000 +"2000-06-11","Whit Sunday","IS",2000 +"2000-06-12","Whit Monday","IS",2000 +"2000-06-17","National Day","IS",2000 +"2000-08-07","Commerce Day","IS",2000 +"2000-12-24","Christmas Eve","IS",2000 +"2000-12-25","Christmas Day","IS",2000 +"2000-12-26","Second Day of Christmas","IS",2000 +"2000-12-31","New Year's Eve","IS",2000 +"2001-01-01","New Year's Day","IS",2001 +"2001-04-12","Maundy Thursday","IS",2001 +"2001-04-13","Good Friday","IS",2001 +"2001-04-15","Easter Sunday","IS",2001 +"2001-04-16","Easter Monday","IS",2001 +"2001-04-19","First Day of Summer","IS",2001 +"2001-05-01","Labor Day","IS",2001 +"2001-05-24","Ascension Day","IS",2001 +"2001-06-03","Whit Sunday","IS",2001 +"2001-06-04","Whit Monday","IS",2001 +"2001-06-17","National Day","IS",2001 +"2001-08-06","Commerce Day","IS",2001 +"2001-12-24","Christmas Eve","IS",2001 +"2001-12-25","Christmas Day","IS",2001 +"2001-12-26","Second Day of Christmas","IS",2001 +"2001-12-31","New Year's Eve","IS",2001 +"2002-01-01","New Year's Day","IS",2002 +"2002-03-28","Maundy Thursday","IS",2002 +"2002-03-29","Good Friday","IS",2002 +"2002-03-31","Easter Sunday","IS",2002 +"2002-04-01","Easter Monday","IS",2002 +"2002-04-25","First Day of Summer","IS",2002 +"2002-05-01","Labor Day","IS",2002 +"2002-05-09","Ascension Day","IS",2002 +"2002-05-19","Whit Sunday","IS",2002 +"2002-05-20","Whit Monday","IS",2002 +"2002-06-17","National Day","IS",2002 +"2002-08-05","Commerce Day","IS",2002 +"2002-12-24","Christmas Eve","IS",2002 +"2002-12-25","Christmas Day","IS",2002 +"2002-12-26","Second Day of Christmas","IS",2002 +"2002-12-31","New Year's Eve","IS",2002 +"2003-01-01","New Year's Day","IS",2003 +"2003-04-17","Maundy Thursday","IS",2003 +"2003-04-18","Good Friday","IS",2003 +"2003-04-20","Easter Sunday","IS",2003 +"2003-04-21","Easter Monday","IS",2003 +"2003-04-24","First Day of Summer","IS",2003 +"2003-05-01","Labor Day","IS",2003 +"2003-05-29","Ascension Day","IS",2003 +"2003-06-08","Whit Sunday","IS",2003 +"2003-06-09","Whit Monday","IS",2003 +"2003-06-17","National Day","IS",2003 +"2003-08-04","Commerce Day","IS",2003 +"2003-12-24","Christmas Eve","IS",2003 +"2003-12-25","Christmas Day","IS",2003 +"2003-12-26","Second Day of Christmas","IS",2003 +"2003-12-31","New Year's Eve","IS",2003 +"2004-01-01","New Year's Day","IS",2004 +"2004-04-08","Maundy Thursday","IS",2004 +"2004-04-09","Good Friday","IS",2004 +"2004-04-11","Easter Sunday","IS",2004 +"2004-04-12","Easter Monday","IS",2004 +"2004-04-22","First Day of Summer","IS",2004 +"2004-05-01","Labor Day","IS",2004 +"2004-05-20","Ascension Day","IS",2004 +"2004-05-30","Whit Sunday","IS",2004 +"2004-05-31","Whit Monday","IS",2004 +"2004-06-17","National Day","IS",2004 +"2004-08-02","Commerce Day","IS",2004 +"2004-12-24","Christmas Eve","IS",2004 +"2004-12-25","Christmas Day","IS",2004 +"2004-12-26","Second Day of Christmas","IS",2004 +"2004-12-31","New Year's Eve","IS",2004 +"2005-01-01","New Year's Day","IS",2005 +"2005-03-24","Maundy Thursday","IS",2005 +"2005-03-25","Good Friday","IS",2005 +"2005-03-27","Easter Sunday","IS",2005 +"2005-03-28","Easter Monday","IS",2005 +"2005-04-21","First Day of Summer","IS",2005 +"2005-05-01","Labor Day","IS",2005 +"2005-05-05","Ascension Day","IS",2005 +"2005-05-15","Whit Sunday","IS",2005 +"2005-05-16","Whit Monday","IS",2005 +"2005-06-17","National Day","IS",2005 +"2005-08-01","Commerce Day","IS",2005 +"2005-12-24","Christmas Eve","IS",2005 +"2005-12-25","Christmas Day","IS",2005 +"2005-12-26","Second Day of Christmas","IS",2005 +"2005-12-31","New Year's Eve","IS",2005 +"2006-01-01","New Year's Day","IS",2006 +"2006-04-13","Maundy Thursday","IS",2006 +"2006-04-14","Good Friday","IS",2006 +"2006-04-16","Easter Sunday","IS",2006 +"2006-04-17","Easter Monday","IS",2006 +"2006-04-20","First Day of Summer","IS",2006 +"2006-05-01","Labor Day","IS",2006 +"2006-05-25","Ascension Day","IS",2006 +"2006-06-04","Whit Sunday","IS",2006 +"2006-06-05","Whit Monday","IS",2006 +"2006-06-17","National Day","IS",2006 +"2006-08-07","Commerce Day","IS",2006 +"2006-12-24","Christmas Eve","IS",2006 +"2006-12-25","Christmas Day","IS",2006 +"2006-12-26","Second Day of Christmas","IS",2006 +"2006-12-31","New Year's Eve","IS",2006 +"2007-01-01","New Year's Day","IS",2007 +"2007-04-05","Maundy Thursday","IS",2007 +"2007-04-06","Good Friday","IS",2007 +"2007-04-08","Easter Sunday","IS",2007 +"2007-04-09","Easter Monday","IS",2007 +"2007-04-19","First Day of Summer","IS",2007 +"2007-05-01","Labor Day","IS",2007 +"2007-05-17","Ascension Day","IS",2007 +"2007-05-27","Whit Sunday","IS",2007 +"2007-05-28","Whit Monday","IS",2007 +"2007-06-17","National Day","IS",2007 +"2007-08-06","Commerce Day","IS",2007 +"2007-12-24","Christmas Eve","IS",2007 +"2007-12-25","Christmas Day","IS",2007 +"2007-12-26","Second Day of Christmas","IS",2007 +"2007-12-31","New Year's Eve","IS",2007 +"2008-01-01","New Year's Day","IS",2008 +"2008-03-20","Maundy Thursday","IS",2008 +"2008-03-21","Good Friday","IS",2008 +"2008-03-23","Easter Sunday","IS",2008 +"2008-03-24","Easter Monday","IS",2008 +"2008-04-24","First Day of Summer","IS",2008 +"2008-05-01","Ascension Day","IS",2008 +"2008-05-01","Labor Day","IS",2008 +"2008-05-11","Whit Sunday","IS",2008 +"2008-05-12","Whit Monday","IS",2008 +"2008-06-17","National Day","IS",2008 +"2008-08-04","Commerce Day","IS",2008 +"2008-12-24","Christmas Eve","IS",2008 +"2008-12-25","Christmas Day","IS",2008 +"2008-12-26","Second Day of Christmas","IS",2008 +"2008-12-31","New Year's Eve","IS",2008 +"2009-01-01","New Year's Day","IS",2009 +"2009-04-09","Maundy Thursday","IS",2009 +"2009-04-10","Good Friday","IS",2009 +"2009-04-12","Easter Sunday","IS",2009 +"2009-04-13","Easter Monday","IS",2009 +"2009-04-23","First Day of Summer","IS",2009 +"2009-05-01","Labor Day","IS",2009 +"2009-05-21","Ascension Day","IS",2009 +"2009-05-31","Whit Sunday","IS",2009 +"2009-06-01","Whit Monday","IS",2009 +"2009-06-17","National Day","IS",2009 +"2009-08-03","Commerce Day","IS",2009 +"2009-12-24","Christmas Eve","IS",2009 +"2009-12-25","Christmas Day","IS",2009 +"2009-12-26","Second Day of Christmas","IS",2009 +"2009-12-31","New Year's Eve","IS",2009 +"2010-01-01","New Year's Day","IS",2010 +"2010-04-01","Maundy Thursday","IS",2010 +"2010-04-02","Good Friday","IS",2010 +"2010-04-04","Easter Sunday","IS",2010 +"2010-04-05","Easter Monday","IS",2010 +"2010-04-22","First Day of Summer","IS",2010 +"2010-05-01","Labor Day","IS",2010 +"2010-05-13","Ascension Day","IS",2010 +"2010-05-23","Whit Sunday","IS",2010 +"2010-05-24","Whit Monday","IS",2010 +"2010-06-17","National Day","IS",2010 +"2010-08-02","Commerce Day","IS",2010 +"2010-12-24","Christmas Eve","IS",2010 +"2010-12-25","Christmas Day","IS",2010 +"2010-12-26","Second Day of Christmas","IS",2010 +"2010-12-31","New Year's Eve","IS",2010 +"2011-01-01","New Year's Day","IS",2011 +"2011-04-21","First Day of Summer","IS",2011 +"2011-04-21","Maundy Thursday","IS",2011 +"2011-04-22","Good Friday","IS",2011 +"2011-04-24","Easter Sunday","IS",2011 +"2011-04-25","Easter Monday","IS",2011 +"2011-05-01","Labor Day","IS",2011 +"2011-06-02","Ascension Day","IS",2011 +"2011-06-12","Whit Sunday","IS",2011 +"2011-06-13","Whit Monday","IS",2011 +"2011-06-17","National Day","IS",2011 +"2011-08-01","Commerce Day","IS",2011 +"2011-12-24","Christmas Eve","IS",2011 +"2011-12-25","Christmas Day","IS",2011 +"2011-12-26","Second Day of Christmas","IS",2011 +"2011-12-31","New Year's Eve","IS",2011 +"2012-01-01","New Year's Day","IS",2012 +"2012-04-05","Maundy Thursday","IS",2012 +"2012-04-06","Good Friday","IS",2012 +"2012-04-08","Easter Sunday","IS",2012 +"2012-04-09","Easter Monday","IS",2012 +"2012-04-19","First Day of Summer","IS",2012 +"2012-05-01","Labor Day","IS",2012 +"2012-05-17","Ascension Day","IS",2012 +"2012-05-27","Whit Sunday","IS",2012 +"2012-05-28","Whit Monday","IS",2012 +"2012-06-17","National Day","IS",2012 +"2012-08-06","Commerce Day","IS",2012 +"2012-12-24","Christmas Eve","IS",2012 +"2012-12-25","Christmas Day","IS",2012 +"2012-12-26","Second Day of Christmas","IS",2012 +"2012-12-31","New Year's Eve","IS",2012 +"2013-01-01","New Year's Day","IS",2013 +"2013-03-28","Maundy Thursday","IS",2013 +"2013-03-29","Good Friday","IS",2013 +"2013-03-31","Easter Sunday","IS",2013 +"2013-04-01","Easter Monday","IS",2013 +"2013-04-25","First Day of Summer","IS",2013 +"2013-05-01","Labor Day","IS",2013 +"2013-05-09","Ascension Day","IS",2013 +"2013-05-19","Whit Sunday","IS",2013 +"2013-05-20","Whit Monday","IS",2013 +"2013-06-17","National Day","IS",2013 +"2013-08-05","Commerce Day","IS",2013 +"2013-12-24","Christmas Eve","IS",2013 +"2013-12-25","Christmas Day","IS",2013 +"2013-12-26","Second Day of Christmas","IS",2013 +"2013-12-31","New Year's Eve","IS",2013 +"2014-01-01","New Year's Day","IS",2014 +"2014-04-17","Maundy Thursday","IS",2014 +"2014-04-18","Good Friday","IS",2014 +"2014-04-20","Easter Sunday","IS",2014 +"2014-04-21","Easter Monday","IS",2014 +"2014-04-24","First Day of Summer","IS",2014 +"2014-05-01","Labor Day","IS",2014 +"2014-05-29","Ascension Day","IS",2014 +"2014-06-08","Whit Sunday","IS",2014 +"2014-06-09","Whit Monday","IS",2014 +"2014-06-17","National Day","IS",2014 +"2014-08-04","Commerce Day","IS",2014 +"2014-12-24","Christmas Eve","IS",2014 +"2014-12-25","Christmas Day","IS",2014 +"2014-12-26","Second Day of Christmas","IS",2014 +"2014-12-31","New Year's Eve","IS",2014 +"2015-01-01","New Year's Day","IS",2015 +"2015-04-02","Maundy Thursday","IS",2015 +"2015-04-03","Good Friday","IS",2015 +"2015-04-05","Easter Sunday","IS",2015 +"2015-04-06","Easter Monday","IS",2015 +"2015-04-23","First Day of Summer","IS",2015 +"2015-05-01","Labor Day","IS",2015 +"2015-05-14","Ascension Day","IS",2015 +"2015-05-24","Whit Sunday","IS",2015 +"2015-05-25","Whit Monday","IS",2015 +"2015-06-17","National Day","IS",2015 +"2015-08-03","Commerce Day","IS",2015 +"2015-12-24","Christmas Eve","IS",2015 +"2015-12-25","Christmas Day","IS",2015 +"2015-12-26","Second Day of Christmas","IS",2015 +"2015-12-31","New Year's Eve","IS",2015 +"2016-01-01","New Year's Day","IS",2016 +"2016-03-24","Maundy Thursday","IS",2016 +"2016-03-25","Good Friday","IS",2016 +"2016-03-27","Easter Sunday","IS",2016 +"2016-03-28","Easter Monday","IS",2016 +"2016-04-21","First Day of Summer","IS",2016 +"2016-05-01","Labor Day","IS",2016 +"2016-05-05","Ascension Day","IS",2016 +"2016-05-15","Whit Sunday","IS",2016 +"2016-05-16","Whit Monday","IS",2016 +"2016-06-17","National Day","IS",2016 +"2016-08-01","Commerce Day","IS",2016 +"2016-12-24","Christmas Eve","IS",2016 +"2016-12-25","Christmas Day","IS",2016 +"2016-12-26","Second Day of Christmas","IS",2016 +"2016-12-31","New Year's Eve","IS",2016 +"2017-01-01","New Year's Day","IS",2017 +"2017-04-13","Maundy Thursday","IS",2017 +"2017-04-14","Good Friday","IS",2017 +"2017-04-16","Easter Sunday","IS",2017 +"2017-04-17","Easter Monday","IS",2017 +"2017-04-20","First Day of Summer","IS",2017 +"2017-05-01","Labor Day","IS",2017 +"2017-05-25","Ascension Day","IS",2017 +"2017-06-04","Whit Sunday","IS",2017 +"2017-06-05","Whit Monday","IS",2017 +"2017-06-17","National Day","IS",2017 +"2017-08-07","Commerce Day","IS",2017 +"2017-12-24","Christmas Eve","IS",2017 +"2017-12-25","Christmas Day","IS",2017 +"2017-12-26","Second Day of Christmas","IS",2017 +"2017-12-31","New Year's Eve","IS",2017 +"2018-01-01","New Year's Day","IS",2018 +"2018-03-29","Maundy Thursday","IS",2018 +"2018-03-30","Good Friday","IS",2018 +"2018-04-01","Easter Sunday","IS",2018 +"2018-04-02","Easter Monday","IS",2018 +"2018-04-19","First Day of Summer","IS",2018 +"2018-05-01","Labor Day","IS",2018 +"2018-05-10","Ascension Day","IS",2018 +"2018-05-20","Whit Sunday","IS",2018 +"2018-05-21","Whit Monday","IS",2018 +"2018-06-17","National Day","IS",2018 +"2018-08-06","Commerce Day","IS",2018 +"2018-12-24","Christmas Eve","IS",2018 +"2018-12-25","Christmas Day","IS",2018 +"2018-12-26","Second Day of Christmas","IS",2018 +"2018-12-31","New Year's Eve","IS",2018 +"2019-01-01","New Year's Day","IS",2019 +"2019-04-18","Maundy Thursday","IS",2019 +"2019-04-19","Good Friday","IS",2019 +"2019-04-21","Easter Sunday","IS",2019 +"2019-04-22","Easter Monday","IS",2019 +"2019-04-25","First Day of Summer","IS",2019 +"2019-05-01","Labor Day","IS",2019 +"2019-05-30","Ascension Day","IS",2019 +"2019-06-09","Whit Sunday","IS",2019 +"2019-06-10","Whit Monday","IS",2019 +"2019-06-17","National Day","IS",2019 +"2019-08-05","Commerce Day","IS",2019 +"2019-12-24","Christmas Eve","IS",2019 +"2019-12-25","Christmas Day","IS",2019 +"2019-12-26","Second Day of Christmas","IS",2019 +"2019-12-31","New Year's Eve","IS",2019 +"2020-01-01","New Year's Day","IS",2020 +"2020-04-09","Maundy Thursday","IS",2020 +"2020-04-10","Good Friday","IS",2020 +"2020-04-12","Easter Sunday","IS",2020 +"2020-04-13","Easter Monday","IS",2020 +"2020-04-23","First Day of Summer","IS",2020 +"2020-05-01","Labor Day","IS",2020 +"2020-05-21","Ascension Day","IS",2020 +"2020-05-31","Whit Sunday","IS",2020 +"2020-06-01","Whit Monday","IS",2020 +"2020-06-17","National Day","IS",2020 +"2020-08-03","Commerce Day","IS",2020 +"2020-12-24","Christmas Eve","IS",2020 +"2020-12-25","Christmas Day","IS",2020 +"2020-12-26","Second Day of Christmas","IS",2020 +"2020-12-31","New Year's Eve","IS",2020 +"2021-01-01","New Year's Day","IS",2021 +"2021-04-01","Maundy Thursday","IS",2021 +"2021-04-02","Good Friday","IS",2021 +"2021-04-04","Easter Sunday","IS",2021 +"2021-04-05","Easter Monday","IS",2021 +"2021-04-22","First Day of Summer","IS",2021 +"2021-05-01","Labor Day","IS",2021 +"2021-05-13","Ascension Day","IS",2021 +"2021-05-23","Whit Sunday","IS",2021 +"2021-05-24","Whit Monday","IS",2021 +"2021-06-17","National Day","IS",2021 +"2021-08-02","Commerce Day","IS",2021 +"2021-12-24","Christmas Eve","IS",2021 +"2021-12-25","Christmas Day","IS",2021 +"2021-12-26","Second Day of Christmas","IS",2021 +"2021-12-31","New Year's Eve","IS",2021 +"2022-01-01","New Year's Day","IS",2022 +"2022-04-14","Maundy Thursday","IS",2022 +"2022-04-15","Good Friday","IS",2022 +"2022-04-17","Easter Sunday","IS",2022 +"2022-04-18","Easter Monday","IS",2022 +"2022-04-21","First Day of Summer","IS",2022 +"2022-05-01","Labor Day","IS",2022 +"2022-05-26","Ascension Day","IS",2022 +"2022-06-05","Whit Sunday","IS",2022 +"2022-06-06","Whit Monday","IS",2022 +"2022-06-17","National Day","IS",2022 +"2022-08-01","Commerce Day","IS",2022 +"2022-12-24","Christmas Eve","IS",2022 +"2022-12-25","Christmas Day","IS",2022 +"2022-12-26","Second Day of Christmas","IS",2022 +"2022-12-31","New Year's Eve","IS",2022 +"2023-01-01","New Year's Day","IS",2023 +"2023-04-06","Maundy Thursday","IS",2023 +"2023-04-07","Good Friday","IS",2023 +"2023-04-09","Easter Sunday","IS",2023 +"2023-04-10","Easter Monday","IS",2023 +"2023-04-20","First Day of Summer","IS",2023 +"2023-05-01","Labor Day","IS",2023 +"2023-05-18","Ascension Day","IS",2023 +"2023-05-28","Whit Sunday","IS",2023 +"2023-05-29","Whit Monday","IS",2023 +"2023-06-17","National Day","IS",2023 +"2023-08-07","Commerce Day","IS",2023 +"2023-12-24","Christmas Eve","IS",2023 +"2023-12-25","Christmas Day","IS",2023 +"2023-12-26","Second Day of Christmas","IS",2023 +"2023-12-31","New Year's Eve","IS",2023 +"2024-01-01","New Year's Day","IS",2024 +"2024-03-28","Maundy Thursday","IS",2024 +"2024-03-29","Good Friday","IS",2024 +"2024-03-31","Easter Sunday","IS",2024 +"2024-04-01","Easter Monday","IS",2024 +"2024-04-25","First Day of Summer","IS",2024 +"2024-05-01","Labor Day","IS",2024 +"2024-05-09","Ascension Day","IS",2024 +"2024-05-19","Whit Sunday","IS",2024 +"2024-05-20","Whit Monday","IS",2024 +"2024-06-17","National Day","IS",2024 +"2024-08-05","Commerce Day","IS",2024 +"2024-12-24","Christmas Eve","IS",2024 +"2024-12-25","Christmas Day","IS",2024 +"2024-12-26","Second Day of Christmas","IS",2024 +"2024-12-31","New Year's Eve","IS",2024 +"2025-01-01","New Year's Day","IS",2025 +"2025-04-17","Maundy Thursday","IS",2025 +"2025-04-18","Good Friday","IS",2025 +"2025-04-20","Easter Sunday","IS",2025 +"2025-04-21","Easter Monday","IS",2025 +"2025-04-24","First Day of Summer","IS",2025 +"2025-05-01","Labor Day","IS",2025 +"2025-05-29","Ascension Day","IS",2025 +"2025-06-08","Whit Sunday","IS",2025 +"2025-06-09","Whit Monday","IS",2025 +"2025-06-17","National Day","IS",2025 +"2025-08-04","Commerce Day","IS",2025 +"2025-12-24","Christmas Eve","IS",2025 +"2025-12-25","Christmas Day","IS",2025 +"2025-12-26","Second Day of Christmas","IS",2025 +"2025-12-31","New Year's Eve","IS",2025 +"2026-01-01","New Year's Day","IS",2026 +"2026-04-02","Maundy Thursday","IS",2026 +"2026-04-03","Good Friday","IS",2026 +"2026-04-05","Easter Sunday","IS",2026 +"2026-04-06","Easter Monday","IS",2026 +"2026-04-23","First Day of Summer","IS",2026 +"2026-05-01","Labor Day","IS",2026 +"2026-05-14","Ascension Day","IS",2026 +"2026-05-24","Whit Sunday","IS",2026 +"2026-05-25","Whit Monday","IS",2026 +"2026-06-17","National Day","IS",2026 +"2026-08-03","Commerce Day","IS",2026 +"2026-12-24","Christmas Eve","IS",2026 +"2026-12-25","Christmas Day","IS",2026 +"2026-12-26","Second Day of Christmas","IS",2026 +"2026-12-31","New Year's Eve","IS",2026 +"2027-01-01","New Year's Day","IS",2027 +"2027-03-25","Maundy Thursday","IS",2027 +"2027-03-26","Good Friday","IS",2027 +"2027-03-28","Easter Sunday","IS",2027 +"2027-03-29","Easter Monday","IS",2027 +"2027-04-22","First Day of Summer","IS",2027 +"2027-05-01","Labor Day","IS",2027 +"2027-05-06","Ascension Day","IS",2027 +"2027-05-16","Whit Sunday","IS",2027 +"2027-05-17","Whit Monday","IS",2027 +"2027-06-17","National Day","IS",2027 +"2027-08-02","Commerce Day","IS",2027 +"2027-12-24","Christmas Eve","IS",2027 +"2027-12-25","Christmas Day","IS",2027 +"2027-12-26","Second Day of Christmas","IS",2027 +"2027-12-31","New Year's Eve","IS",2027 +"2028-01-01","New Year's Day","IS",2028 +"2028-04-13","Maundy Thursday","IS",2028 +"2028-04-14","Good Friday","IS",2028 +"2028-04-16","Easter Sunday","IS",2028 +"2028-04-17","Easter Monday","IS",2028 +"2028-04-20","First Day of Summer","IS",2028 +"2028-05-01","Labor Day","IS",2028 +"2028-05-25","Ascension Day","IS",2028 +"2028-06-04","Whit Sunday","IS",2028 +"2028-06-05","Whit Monday","IS",2028 +"2028-06-17","National Day","IS",2028 +"2028-08-07","Commerce Day","IS",2028 +"2028-12-24","Christmas Eve","IS",2028 +"2028-12-25","Christmas Day","IS",2028 +"2028-12-26","Second Day of Christmas","IS",2028 +"2028-12-31","New Year's Eve","IS",2028 +"2029-01-01","New Year's Day","IS",2029 +"2029-03-29","Maundy Thursday","IS",2029 +"2029-03-30","Good Friday","IS",2029 +"2029-04-01","Easter Sunday","IS",2029 +"2029-04-02","Easter Monday","IS",2029 +"2029-04-19","First Day of Summer","IS",2029 +"2029-05-01","Labor Day","IS",2029 +"2029-05-10","Ascension Day","IS",2029 +"2029-05-20","Whit Sunday","IS",2029 +"2029-05-21","Whit Monday","IS",2029 +"2029-06-17","National Day","IS",2029 +"2029-08-06","Commerce Day","IS",2029 +"2029-12-24","Christmas Eve","IS",2029 +"2029-12-25","Christmas Day","IS",2029 +"2029-12-26","Second Day of Christmas","IS",2029 +"2029-12-31","New Year's Eve","IS",2029 +"2030-01-01","New Year's Day","IS",2030 +"2030-04-18","Maundy Thursday","IS",2030 +"2030-04-19","Good Friday","IS",2030 +"2030-04-21","Easter Sunday","IS",2030 +"2030-04-22","Easter Monday","IS",2030 +"2030-04-25","First Day of Summer","IS",2030 +"2030-05-01","Labor Day","IS",2030 +"2030-05-30","Ascension Day","IS",2030 +"2030-06-09","Whit Sunday","IS",2030 +"2030-06-10","Whit Monday","IS",2030 +"2030-06-17","National Day","IS",2030 +"2030-08-05","Commerce Day","IS",2030 +"2030-12-24","Christmas Eve","IS",2030 +"2030-12-25","Christmas Day","IS",2030 +"2030-12-26","Second Day of Christmas","IS",2030 +"2030-12-31","New Year's Eve","IS",2030 +"2031-01-01","New Year's Day","IS",2031 +"2031-04-10","Maundy Thursday","IS",2031 +"2031-04-11","Good Friday","IS",2031 +"2031-04-13","Easter Sunday","IS",2031 +"2031-04-14","Easter Monday","IS",2031 +"2031-04-24","First Day of Summer","IS",2031 +"2031-05-01","Labor Day","IS",2031 +"2031-05-22","Ascension Day","IS",2031 +"2031-06-01","Whit Sunday","IS",2031 +"2031-06-02","Whit Monday","IS",2031 +"2031-06-17","National Day","IS",2031 +"2031-08-04","Commerce Day","IS",2031 +"2031-12-24","Christmas Eve","IS",2031 +"2031-12-25","Christmas Day","IS",2031 +"2031-12-26","Second Day of Christmas","IS",2031 +"2031-12-31","New Year's Eve","IS",2031 +"2032-01-01","New Year's Day","IS",2032 +"2032-03-25","Maundy Thursday","IS",2032 +"2032-03-26","Good Friday","IS",2032 +"2032-03-28","Easter Sunday","IS",2032 +"2032-03-29","Easter Monday","IS",2032 +"2032-04-22","First Day of Summer","IS",2032 +"2032-05-01","Labor Day","IS",2032 +"2032-05-06","Ascension Day","IS",2032 +"2032-05-16","Whit Sunday","IS",2032 +"2032-05-17","Whit Monday","IS",2032 +"2032-06-17","National Day","IS",2032 +"2032-08-02","Commerce Day","IS",2032 +"2032-12-24","Christmas Eve","IS",2032 +"2032-12-25","Christmas Day","IS",2032 +"2032-12-26","Second Day of Christmas","IS",2032 +"2032-12-31","New Year's Eve","IS",2032 +"2033-01-01","New Year's Day","IS",2033 +"2033-04-14","Maundy Thursday","IS",2033 +"2033-04-15","Good Friday","IS",2033 +"2033-04-17","Easter Sunday","IS",2033 +"2033-04-18","Easter Monday","IS",2033 +"2033-04-21","First Day of Summer","IS",2033 +"2033-05-01","Labor Day","IS",2033 +"2033-05-26","Ascension Day","IS",2033 +"2033-06-05","Whit Sunday","IS",2033 +"2033-06-06","Whit Monday","IS",2033 +"2033-06-17","National Day","IS",2033 +"2033-08-01","Commerce Day","IS",2033 +"2033-12-24","Christmas Eve","IS",2033 +"2033-12-25","Christmas Day","IS",2033 +"2033-12-26","Second Day of Christmas","IS",2033 +"2033-12-31","New Year's Eve","IS",2033 +"2034-01-01","New Year's Day","IS",2034 +"2034-04-06","Maundy Thursday","IS",2034 +"2034-04-07","Good Friday","IS",2034 +"2034-04-09","Easter Sunday","IS",2034 +"2034-04-10","Easter Monday","IS",2034 +"2034-04-20","First Day of Summer","IS",2034 +"2034-05-01","Labor Day","IS",2034 +"2034-05-18","Ascension Day","IS",2034 +"2034-05-28","Whit Sunday","IS",2034 +"2034-05-29","Whit Monday","IS",2034 +"2034-06-17","National Day","IS",2034 +"2034-08-07","Commerce Day","IS",2034 +"2034-12-24","Christmas Eve","IS",2034 +"2034-12-25","Christmas Day","IS",2034 +"2034-12-26","Second Day of Christmas","IS",2034 +"2034-12-31","New Year's Eve","IS",2034 +"2035-01-01","New Year's Day","IS",2035 +"2035-03-22","Maundy Thursday","IS",2035 +"2035-03-23","Good Friday","IS",2035 +"2035-03-25","Easter Sunday","IS",2035 +"2035-03-26","Easter Monday","IS",2035 +"2035-04-19","First Day of Summer","IS",2035 +"2035-05-01","Labor Day","IS",2035 +"2035-05-03","Ascension Day","IS",2035 +"2035-05-13","Whit Sunday","IS",2035 +"2035-05-14","Whit Monday","IS",2035 +"2035-06-17","National Day","IS",2035 +"2035-08-06","Commerce Day","IS",2035 +"2035-12-24","Christmas Eve","IS",2035 +"2035-12-25","Christmas Day","IS",2035 +"2035-12-26","Second Day of Christmas","IS",2035 +"2035-12-31","New Year's Eve","IS",2035 +"2036-01-01","New Year's Day","IS",2036 +"2036-04-10","Maundy Thursday","IS",2036 +"2036-04-11","Good Friday","IS",2036 +"2036-04-13","Easter Sunday","IS",2036 +"2036-04-14","Easter Monday","IS",2036 +"2036-04-24","First Day of Summer","IS",2036 +"2036-05-01","Labor Day","IS",2036 +"2036-05-22","Ascension Day","IS",2036 +"2036-06-01","Whit Sunday","IS",2036 +"2036-06-02","Whit Monday","IS",2036 +"2036-06-17","National Day","IS",2036 +"2036-08-04","Commerce Day","IS",2036 +"2036-12-24","Christmas Eve","IS",2036 +"2036-12-25","Christmas Day","IS",2036 +"2036-12-26","Second Day of Christmas","IS",2036 +"2036-12-31","New Year's Eve","IS",2036 +"2037-01-01","New Year's Day","IS",2037 +"2037-04-02","Maundy Thursday","IS",2037 +"2037-04-03","Good Friday","IS",2037 +"2037-04-05","Easter Sunday","IS",2037 +"2037-04-06","Easter Monday","IS",2037 +"2037-04-23","First Day of Summer","IS",2037 +"2037-05-01","Labor Day","IS",2037 +"2037-05-14","Ascension Day","IS",2037 +"2037-05-24","Whit Sunday","IS",2037 +"2037-05-25","Whit Monday","IS",2037 +"2037-06-17","National Day","IS",2037 +"2037-08-03","Commerce Day","IS",2037 +"2037-12-24","Christmas Eve","IS",2037 +"2037-12-25","Christmas Day","IS",2037 +"2037-12-26","Second Day of Christmas","IS",2037 +"2037-12-31","New Year's Eve","IS",2037 +"2038-01-01","New Year's Day","IS",2038 +"2038-04-22","First Day of Summer","IS",2038 +"2038-04-22","Maundy Thursday","IS",2038 +"2038-04-23","Good Friday","IS",2038 +"2038-04-25","Easter Sunday","IS",2038 +"2038-04-26","Easter Monday","IS",2038 +"2038-05-01","Labor Day","IS",2038 +"2038-06-03","Ascension Day","IS",2038 +"2038-06-13","Whit Sunday","IS",2038 +"2038-06-14","Whit Monday","IS",2038 +"2038-06-17","National Day","IS",2038 +"2038-08-02","Commerce Day","IS",2038 +"2038-12-24","Christmas Eve","IS",2038 +"2038-12-25","Christmas Day","IS",2038 +"2038-12-26","Second Day of Christmas","IS",2038 +"2038-12-31","New Year's Eve","IS",2038 +"2039-01-01","New Year's Day","IS",2039 +"2039-04-07","Maundy Thursday","IS",2039 +"2039-04-08","Good Friday","IS",2039 +"2039-04-10","Easter Sunday","IS",2039 +"2039-04-11","Easter Monday","IS",2039 +"2039-04-21","First Day of Summer","IS",2039 +"2039-05-01","Labor Day","IS",2039 +"2039-05-19","Ascension Day","IS",2039 +"2039-05-29","Whit Sunday","IS",2039 +"2039-05-30","Whit Monday","IS",2039 +"2039-06-17","National Day","IS",2039 +"2039-08-01","Commerce Day","IS",2039 +"2039-12-24","Christmas Eve","IS",2039 +"2039-12-25","Christmas Day","IS",2039 +"2039-12-26","Second Day of Christmas","IS",2039 +"2039-12-31","New Year's Eve","IS",2039 +"2040-01-01","New Year's Day","IS",2040 +"2040-03-29","Maundy Thursday","IS",2040 +"2040-03-30","Good Friday","IS",2040 +"2040-04-01","Easter Sunday","IS",2040 +"2040-04-02","Easter Monday","IS",2040 +"2040-04-19","First Day of Summer","IS",2040 +"2040-05-01","Labor Day","IS",2040 +"2040-05-10","Ascension Day","IS",2040 +"2040-05-20","Whit Sunday","IS",2040 +"2040-05-21","Whit Monday","IS",2040 +"2040-06-17","National Day","IS",2040 +"2040-08-06","Commerce Day","IS",2040 +"2040-12-24","Christmas Eve","IS",2040 +"2040-12-25","Christmas Day","IS",2040 +"2040-12-26","Second Day of Christmas","IS",2040 +"2040-12-31","New Year's Eve","IS",2040 +"2041-01-01","New Year's Day","IS",2041 +"2041-04-18","Maundy Thursday","IS",2041 +"2041-04-19","Good Friday","IS",2041 +"2041-04-21","Easter Sunday","IS",2041 +"2041-04-22","Easter Monday","IS",2041 +"2041-04-25","First Day of Summer","IS",2041 +"2041-05-01","Labor Day","IS",2041 +"2041-05-30","Ascension Day","IS",2041 +"2041-06-09","Whit Sunday","IS",2041 +"2041-06-10","Whit Monday","IS",2041 +"2041-06-17","National Day","IS",2041 +"2041-08-05","Commerce Day","IS",2041 +"2041-12-24","Christmas Eve","IS",2041 +"2041-12-25","Christmas Day","IS",2041 +"2041-12-26","Second Day of Christmas","IS",2041 +"2041-12-31","New Year's Eve","IS",2041 +"2042-01-01","New Year's Day","IS",2042 +"2042-04-03","Maundy Thursday","IS",2042 +"2042-04-04","Good Friday","IS",2042 +"2042-04-06","Easter Sunday","IS",2042 +"2042-04-07","Easter Monday","IS",2042 +"2042-04-24","First Day of Summer","IS",2042 +"2042-05-01","Labor Day","IS",2042 +"2042-05-15","Ascension Day","IS",2042 +"2042-05-25","Whit Sunday","IS",2042 +"2042-05-26","Whit Monday","IS",2042 +"2042-06-17","National Day","IS",2042 +"2042-08-04","Commerce Day","IS",2042 +"2042-12-24","Christmas Eve","IS",2042 +"2042-12-25","Christmas Day","IS",2042 +"2042-12-26","Second Day of Christmas","IS",2042 +"2042-12-31","New Year's Eve","IS",2042 +"2043-01-01","New Year's Day","IS",2043 +"2043-03-26","Maundy Thursday","IS",2043 +"2043-03-27","Good Friday","IS",2043 +"2043-03-29","Easter Sunday","IS",2043 +"2043-03-30","Easter Monday","IS",2043 +"2043-04-23","First Day of Summer","IS",2043 +"2043-05-01","Labor Day","IS",2043 +"2043-05-07","Ascension Day","IS",2043 +"2043-05-17","Whit Sunday","IS",2043 +"2043-05-18","Whit Monday","IS",2043 +"2043-06-17","National Day","IS",2043 +"2043-08-03","Commerce Day","IS",2043 +"2043-12-24","Christmas Eve","IS",2043 +"2043-12-25","Christmas Day","IS",2043 +"2043-12-26","Second Day of Christmas","IS",2043 +"2043-12-31","New Year's Eve","IS",2043 +"2044-01-01","New Year's Day","IS",2044 +"2044-04-14","Maundy Thursday","IS",2044 +"2044-04-15","Good Friday","IS",2044 +"2044-04-17","Easter Sunday","IS",2044 +"2044-04-18","Easter Monday","IS",2044 +"2044-04-21","First Day of Summer","IS",2044 +"2044-05-01","Labor Day","IS",2044 +"2044-05-26","Ascension Day","IS",2044 +"2044-06-05","Whit Sunday","IS",2044 +"2044-06-06","Whit Monday","IS",2044 +"2044-06-17","National Day","IS",2044 +"2044-08-01","Commerce Day","IS",2044 +"2044-12-24","Christmas Eve","IS",2044 +"2044-12-25","Christmas Day","IS",2044 +"2044-12-26","Second Day of Christmas","IS",2044 +"2044-12-31","New Year's Eve","IS",2044 +"1995-01-01","Capodanno","IT",1995 +"1995-01-06","Epifania del Signore","IT",1995 +"1995-04-16","Pasqua di Resurrezione","IT",1995 +"1995-04-17","Lunedi dell'Angelo","IT",1995 +"1995-04-25","Festa della Liberazione","IT",1995 +"1995-05-01","Festa dei Lavoratori","IT",1995 +"1995-06-02","Festa della Repubblica","IT",1995 +"1995-08-15","Assunzione della Vergine","IT",1995 +"1995-11-01","Tutti i Santi","IT",1995 +"1995-12-08","Immacolata Concezione","IT",1995 +"1995-12-25","Natale","IT",1995 +"1995-12-26","Santo Stefano","IT",1995 +"1996-01-01","Capodanno","IT",1996 +"1996-01-06","Epifania del Signore","IT",1996 +"1996-04-07","Pasqua di Resurrezione","IT",1996 +"1996-04-08","Lunedi dell'Angelo","IT",1996 +"1996-04-25","Festa della Liberazione","IT",1996 +"1996-05-01","Festa dei Lavoratori","IT",1996 +"1996-06-02","Festa della Repubblica","IT",1996 +"1996-08-15","Assunzione della Vergine","IT",1996 +"1996-11-01","Tutti i Santi","IT",1996 +"1996-12-08","Immacolata Concezione","IT",1996 +"1996-12-25","Natale","IT",1996 +"1996-12-26","Santo Stefano","IT",1996 +"1997-01-01","Capodanno","IT",1997 +"1997-01-06","Epifania del Signore","IT",1997 +"1997-03-30","Pasqua di Resurrezione","IT",1997 +"1997-03-31","Lunedi dell'Angelo","IT",1997 +"1997-04-25","Festa della Liberazione","IT",1997 +"1997-05-01","Festa dei Lavoratori","IT",1997 +"1997-06-02","Festa della Repubblica","IT",1997 +"1997-08-15","Assunzione della Vergine","IT",1997 +"1997-11-01","Tutti i Santi","IT",1997 +"1997-12-08","Immacolata Concezione","IT",1997 +"1997-12-25","Natale","IT",1997 +"1997-12-26","Santo Stefano","IT",1997 +"1998-01-01","Capodanno","IT",1998 +"1998-01-06","Epifania del Signore","IT",1998 +"1998-04-12","Pasqua di Resurrezione","IT",1998 +"1998-04-13","Lunedi dell'Angelo","IT",1998 +"1998-04-25","Festa della Liberazione","IT",1998 +"1998-05-01","Festa dei Lavoratori","IT",1998 +"1998-06-02","Festa della Repubblica","IT",1998 +"1998-08-15","Assunzione della Vergine","IT",1998 +"1998-11-01","Tutti i Santi","IT",1998 +"1998-12-08","Immacolata Concezione","IT",1998 +"1998-12-25","Natale","IT",1998 +"1998-12-26","Santo Stefano","IT",1998 +"1999-01-01","Capodanno","IT",1999 +"1999-01-06","Epifania del Signore","IT",1999 +"1999-04-04","Pasqua di Resurrezione","IT",1999 +"1999-04-05","Lunedi dell'Angelo","IT",1999 +"1999-04-25","Festa della Liberazione","IT",1999 +"1999-05-01","Festa dei Lavoratori","IT",1999 +"1999-06-02","Festa della Repubblica","IT",1999 +"1999-08-15","Assunzione della Vergine","IT",1999 +"1999-11-01","Tutti i Santi","IT",1999 +"1999-12-08","Immacolata Concezione","IT",1999 +"1999-12-25","Natale","IT",1999 +"1999-12-26","Santo Stefano","IT",1999 +"2000-01-01","Capodanno","IT",2000 +"2000-01-06","Epifania del Signore","IT",2000 +"2000-04-23","Pasqua di Resurrezione","IT",2000 +"2000-04-24","Lunedi dell'Angelo","IT",2000 +"2000-04-25","Festa della Liberazione","IT",2000 +"2000-05-01","Festa dei Lavoratori","IT",2000 +"2000-06-02","Festa della Repubblica","IT",2000 +"2000-08-15","Assunzione della Vergine","IT",2000 +"2000-11-01","Tutti i Santi","IT",2000 +"2000-12-08","Immacolata Concezione","IT",2000 +"2000-12-25","Natale","IT",2000 +"2000-12-26","Santo Stefano","IT",2000 +"2001-01-01","Capodanno","IT",2001 +"2001-01-06","Epifania del Signore","IT",2001 +"2001-04-15","Pasqua di Resurrezione","IT",2001 +"2001-04-16","Lunedi dell'Angelo","IT",2001 +"2001-04-25","Festa della Liberazione","IT",2001 +"2001-05-01","Festa dei Lavoratori","IT",2001 +"2001-06-02","Festa della Repubblica","IT",2001 +"2001-08-15","Assunzione della Vergine","IT",2001 +"2001-11-01","Tutti i Santi","IT",2001 +"2001-12-08","Immacolata Concezione","IT",2001 +"2001-12-25","Natale","IT",2001 +"2001-12-26","Santo Stefano","IT",2001 +"2002-01-01","Capodanno","IT",2002 +"2002-01-06","Epifania del Signore","IT",2002 +"2002-03-31","Pasqua di Resurrezione","IT",2002 +"2002-04-01","Lunedi dell'Angelo","IT",2002 +"2002-04-25","Festa della Liberazione","IT",2002 +"2002-05-01","Festa dei Lavoratori","IT",2002 +"2002-06-02","Festa della Repubblica","IT",2002 +"2002-08-15","Assunzione della Vergine","IT",2002 +"2002-11-01","Tutti i Santi","IT",2002 +"2002-12-08","Immacolata Concezione","IT",2002 +"2002-12-25","Natale","IT",2002 +"2002-12-26","Santo Stefano","IT",2002 +"2003-01-01","Capodanno","IT",2003 +"2003-01-06","Epifania del Signore","IT",2003 +"2003-04-20","Pasqua di Resurrezione","IT",2003 +"2003-04-21","Lunedi dell'Angelo","IT",2003 +"2003-04-25","Festa della Liberazione","IT",2003 +"2003-05-01","Festa dei Lavoratori","IT",2003 +"2003-06-02","Festa della Repubblica","IT",2003 +"2003-08-15","Assunzione della Vergine","IT",2003 +"2003-11-01","Tutti i Santi","IT",2003 +"2003-12-08","Immacolata Concezione","IT",2003 +"2003-12-25","Natale","IT",2003 +"2003-12-26","Santo Stefano","IT",2003 +"2004-01-01","Capodanno","IT",2004 +"2004-01-06","Epifania del Signore","IT",2004 +"2004-04-11","Pasqua di Resurrezione","IT",2004 +"2004-04-12","Lunedi dell'Angelo","IT",2004 +"2004-04-25","Festa della Liberazione","IT",2004 +"2004-05-01","Festa dei Lavoratori","IT",2004 +"2004-06-02","Festa della Repubblica","IT",2004 +"2004-08-15","Assunzione della Vergine","IT",2004 +"2004-11-01","Tutti i Santi","IT",2004 +"2004-12-08","Immacolata Concezione","IT",2004 +"2004-12-25","Natale","IT",2004 +"2004-12-26","Santo Stefano","IT",2004 +"2005-01-01","Capodanno","IT",2005 +"2005-01-06","Epifania del Signore","IT",2005 +"2005-03-27","Pasqua di Resurrezione","IT",2005 +"2005-03-28","Lunedi dell'Angelo","IT",2005 +"2005-04-25","Festa della Liberazione","IT",2005 +"2005-05-01","Festa dei Lavoratori","IT",2005 +"2005-06-02","Festa della Repubblica","IT",2005 +"2005-08-15","Assunzione della Vergine","IT",2005 +"2005-11-01","Tutti i Santi","IT",2005 +"2005-12-08","Immacolata Concezione","IT",2005 +"2005-12-25","Natale","IT",2005 +"2005-12-26","Santo Stefano","IT",2005 +"2006-01-01","Capodanno","IT",2006 +"2006-01-06","Epifania del Signore","IT",2006 +"2006-04-16","Pasqua di Resurrezione","IT",2006 +"2006-04-17","Lunedi dell'Angelo","IT",2006 +"2006-04-25","Festa della Liberazione","IT",2006 +"2006-05-01","Festa dei Lavoratori","IT",2006 +"2006-06-02","Festa della Repubblica","IT",2006 +"2006-08-15","Assunzione della Vergine","IT",2006 +"2006-11-01","Tutti i Santi","IT",2006 +"2006-12-08","Immacolata Concezione","IT",2006 +"2006-12-25","Natale","IT",2006 +"2006-12-26","Santo Stefano","IT",2006 +"2007-01-01","Capodanno","IT",2007 +"2007-01-06","Epifania del Signore","IT",2007 +"2007-04-08","Pasqua di Resurrezione","IT",2007 +"2007-04-09","Lunedi dell'Angelo","IT",2007 +"2007-04-25","Festa della Liberazione","IT",2007 +"2007-05-01","Festa dei Lavoratori","IT",2007 +"2007-06-02","Festa della Repubblica","IT",2007 +"2007-08-15","Assunzione della Vergine","IT",2007 +"2007-11-01","Tutti i Santi","IT",2007 +"2007-12-08","Immacolata Concezione","IT",2007 +"2007-12-25","Natale","IT",2007 +"2007-12-26","Santo Stefano","IT",2007 +"2008-01-01","Capodanno","IT",2008 +"2008-01-06","Epifania del Signore","IT",2008 +"2008-03-23","Pasqua di Resurrezione","IT",2008 +"2008-03-24","Lunedi dell'Angelo","IT",2008 +"2008-04-25","Festa della Liberazione","IT",2008 +"2008-05-01","Festa dei Lavoratori","IT",2008 +"2008-06-02","Festa della Repubblica","IT",2008 +"2008-08-15","Assunzione della Vergine","IT",2008 +"2008-11-01","Tutti i Santi","IT",2008 +"2008-12-08","Immacolata Concezione","IT",2008 +"2008-12-25","Natale","IT",2008 +"2008-12-26","Santo Stefano","IT",2008 +"2009-01-01","Capodanno","IT",2009 +"2009-01-06","Epifania del Signore","IT",2009 +"2009-04-12","Pasqua di Resurrezione","IT",2009 +"2009-04-13","Lunedi dell'Angelo","IT",2009 +"2009-04-25","Festa della Liberazione","IT",2009 +"2009-05-01","Festa dei Lavoratori","IT",2009 +"2009-06-02","Festa della Repubblica","IT",2009 +"2009-08-15","Assunzione della Vergine","IT",2009 +"2009-11-01","Tutti i Santi","IT",2009 +"2009-12-08","Immacolata Concezione","IT",2009 +"2009-12-25","Natale","IT",2009 +"2009-12-26","Santo Stefano","IT",2009 +"2010-01-01","Capodanno","IT",2010 +"2010-01-06","Epifania del Signore","IT",2010 +"2010-04-04","Pasqua di Resurrezione","IT",2010 +"2010-04-05","Lunedi dell'Angelo","IT",2010 +"2010-04-25","Festa della Liberazione","IT",2010 +"2010-05-01","Festa dei Lavoratori","IT",2010 +"2010-06-02","Festa della Repubblica","IT",2010 +"2010-08-15","Assunzione della Vergine","IT",2010 +"2010-11-01","Tutti i Santi","IT",2010 +"2010-12-08","Immacolata Concezione","IT",2010 +"2010-12-25","Natale","IT",2010 +"2010-12-26","Santo Stefano","IT",2010 +"2011-01-01","Capodanno","IT",2011 +"2011-01-06","Epifania del Signore","IT",2011 +"2011-04-24","Pasqua di Resurrezione","IT",2011 +"2011-04-25","Festa della Liberazione","IT",2011 +"2011-04-25","Lunedi dell'Angelo","IT",2011 +"2011-05-01","Festa dei Lavoratori","IT",2011 +"2011-06-02","Festa della Repubblica","IT",2011 +"2011-08-15","Assunzione della Vergine","IT",2011 +"2011-11-01","Tutti i Santi","IT",2011 +"2011-12-08","Immacolata Concezione","IT",2011 +"2011-12-25","Natale","IT",2011 +"2011-12-26","Santo Stefano","IT",2011 +"2012-01-01","Capodanno","IT",2012 +"2012-01-06","Epifania del Signore","IT",2012 +"2012-04-08","Pasqua di Resurrezione","IT",2012 +"2012-04-09","Lunedi dell'Angelo","IT",2012 +"2012-04-25","Festa della Liberazione","IT",2012 +"2012-05-01","Festa dei Lavoratori","IT",2012 +"2012-06-02","Festa della Repubblica","IT",2012 +"2012-08-15","Assunzione della Vergine","IT",2012 +"2012-11-01","Tutti i Santi","IT",2012 +"2012-12-08","Immacolata Concezione","IT",2012 +"2012-12-25","Natale","IT",2012 +"2012-12-26","Santo Stefano","IT",2012 +"2013-01-01","Capodanno","IT",2013 +"2013-01-06","Epifania del Signore","IT",2013 +"2013-03-31","Pasqua di Resurrezione","IT",2013 +"2013-04-01","Lunedi dell'Angelo","IT",2013 +"2013-04-25","Festa della Liberazione","IT",2013 +"2013-05-01","Festa dei Lavoratori","IT",2013 +"2013-06-02","Festa della Repubblica","IT",2013 +"2013-08-15","Assunzione della Vergine","IT",2013 +"2013-11-01","Tutti i Santi","IT",2013 +"2013-12-08","Immacolata Concezione","IT",2013 +"2013-12-25","Natale","IT",2013 +"2013-12-26","Santo Stefano","IT",2013 +"2014-01-01","Capodanno","IT",2014 +"2014-01-06","Epifania del Signore","IT",2014 +"2014-04-20","Pasqua di Resurrezione","IT",2014 +"2014-04-21","Lunedi dell'Angelo","IT",2014 +"2014-04-25","Festa della Liberazione","IT",2014 +"2014-05-01","Festa dei Lavoratori","IT",2014 +"2014-06-02","Festa della Repubblica","IT",2014 +"2014-08-15","Assunzione della Vergine","IT",2014 +"2014-11-01","Tutti i Santi","IT",2014 +"2014-12-08","Immacolata Concezione","IT",2014 +"2014-12-25","Natale","IT",2014 +"2014-12-26","Santo Stefano","IT",2014 +"2015-01-01","Capodanno","IT",2015 +"2015-01-06","Epifania del Signore","IT",2015 +"2015-04-05","Pasqua di Resurrezione","IT",2015 +"2015-04-06","Lunedi dell'Angelo","IT",2015 +"2015-04-25","Festa della Liberazione","IT",2015 +"2015-05-01","Festa dei Lavoratori","IT",2015 +"2015-06-02","Festa della Repubblica","IT",2015 +"2015-08-15","Assunzione della Vergine","IT",2015 +"2015-11-01","Tutti i Santi","IT",2015 +"2015-12-08","Immacolata Concezione","IT",2015 +"2015-12-25","Natale","IT",2015 +"2015-12-26","Santo Stefano","IT",2015 +"2016-01-01","Capodanno","IT",2016 +"2016-01-06","Epifania del Signore","IT",2016 +"2016-03-27","Pasqua di Resurrezione","IT",2016 +"2016-03-28","Lunedi dell'Angelo","IT",2016 +"2016-04-25","Festa della Liberazione","IT",2016 +"2016-05-01","Festa dei Lavoratori","IT",2016 +"2016-06-02","Festa della Repubblica","IT",2016 +"2016-08-15","Assunzione della Vergine","IT",2016 +"2016-11-01","Tutti i Santi","IT",2016 +"2016-12-08","Immacolata Concezione","IT",2016 +"2016-12-25","Natale","IT",2016 +"2016-12-26","Santo Stefano","IT",2016 +"2017-01-01","Capodanno","IT",2017 +"2017-01-06","Epifania del Signore","IT",2017 +"2017-04-16","Pasqua di Resurrezione","IT",2017 +"2017-04-17","Lunedi dell'Angelo","IT",2017 +"2017-04-25","Festa della Liberazione","IT",2017 +"2017-05-01","Festa dei Lavoratori","IT",2017 +"2017-06-02","Festa della Repubblica","IT",2017 +"2017-08-15","Assunzione della Vergine","IT",2017 +"2017-11-01","Tutti i Santi","IT",2017 +"2017-12-08","Immacolata Concezione","IT",2017 +"2017-12-25","Natale","IT",2017 +"2017-12-26","Santo Stefano","IT",2017 +"2018-01-01","Capodanno","IT",2018 +"2018-01-06","Epifania del Signore","IT",2018 +"2018-04-01","Pasqua di Resurrezione","IT",2018 +"2018-04-02","Lunedi dell'Angelo","IT",2018 +"2018-04-25","Festa della Liberazione","IT",2018 +"2018-05-01","Festa dei Lavoratori","IT",2018 +"2018-06-02","Festa della Repubblica","IT",2018 +"2018-08-15","Assunzione della Vergine","IT",2018 +"2018-11-01","Tutti i Santi","IT",2018 +"2018-12-08","Immacolata Concezione","IT",2018 +"2018-12-25","Natale","IT",2018 +"2018-12-26","Santo Stefano","IT",2018 +"2019-01-01","Capodanno","IT",2019 +"2019-01-06","Epifania del Signore","IT",2019 +"2019-04-21","Pasqua di Resurrezione","IT",2019 +"2019-04-22","Lunedi dell'Angelo","IT",2019 +"2019-04-25","Festa della Liberazione","IT",2019 +"2019-05-01","Festa dei Lavoratori","IT",2019 +"2019-06-02","Festa della Repubblica","IT",2019 +"2019-08-15","Assunzione della Vergine","IT",2019 +"2019-11-01","Tutti i Santi","IT",2019 +"2019-12-08","Immacolata Concezione","IT",2019 +"2019-12-25","Natale","IT",2019 +"2019-12-26","Santo Stefano","IT",2019 +"2020-01-01","Capodanno","IT",2020 +"2020-01-06","Epifania del Signore","IT",2020 +"2020-04-12","Pasqua di Resurrezione","IT",2020 +"2020-04-13","Lunedi dell'Angelo","IT",2020 +"2020-04-25","Festa della Liberazione","IT",2020 +"2020-05-01","Festa dei Lavoratori","IT",2020 +"2020-06-02","Festa della Repubblica","IT",2020 +"2020-08-15","Assunzione della Vergine","IT",2020 +"2020-11-01","Tutti i Santi","IT",2020 +"2020-12-08","Immacolata Concezione","IT",2020 +"2020-12-25","Natale","IT",2020 +"2020-12-26","Santo Stefano","IT",2020 +"2021-01-01","Capodanno","IT",2021 +"2021-01-06","Epifania del Signore","IT",2021 +"2021-04-04","Pasqua di Resurrezione","IT",2021 +"2021-04-05","Lunedi dell'Angelo","IT",2021 +"2021-04-25","Festa della Liberazione","IT",2021 +"2021-05-01","Festa dei Lavoratori","IT",2021 +"2021-06-02","Festa della Repubblica","IT",2021 +"2021-08-15","Assunzione della Vergine","IT",2021 +"2021-11-01","Tutti i Santi","IT",2021 +"2021-12-08","Immacolata Concezione","IT",2021 +"2021-12-25","Natale","IT",2021 +"2021-12-26","Santo Stefano","IT",2021 +"2022-01-01","Capodanno","IT",2022 +"2022-01-06","Epifania del Signore","IT",2022 +"2022-04-17","Pasqua di Resurrezione","IT",2022 +"2022-04-18","Lunedi dell'Angelo","IT",2022 +"2022-04-25","Festa della Liberazione","IT",2022 +"2022-05-01","Festa dei Lavoratori","IT",2022 +"2022-06-02","Festa della Repubblica","IT",2022 +"2022-08-15","Assunzione della Vergine","IT",2022 +"2022-11-01","Tutti i Santi","IT",2022 +"2022-12-08","Immacolata Concezione","IT",2022 +"2022-12-25","Natale","IT",2022 +"2022-12-26","Santo Stefano","IT",2022 +"2023-01-01","Capodanno","IT",2023 +"2023-01-06","Epifania del Signore","IT",2023 +"2023-04-09","Pasqua di Resurrezione","IT",2023 +"2023-04-10","Lunedi dell'Angelo","IT",2023 +"2023-04-25","Festa della Liberazione","IT",2023 +"2023-05-01","Festa dei Lavoratori","IT",2023 +"2023-06-02","Festa della Repubblica","IT",2023 +"2023-08-15","Assunzione della Vergine","IT",2023 +"2023-11-01","Tutti i Santi","IT",2023 +"2023-12-08","Immacolata Concezione","IT",2023 +"2023-12-25","Natale","IT",2023 +"2023-12-26","Santo Stefano","IT",2023 +"2024-01-01","Capodanno","IT",2024 +"2024-01-06","Epifania del Signore","IT",2024 +"2024-03-31","Pasqua di Resurrezione","IT",2024 +"2024-04-01","Lunedi dell'Angelo","IT",2024 +"2024-04-25","Festa della Liberazione","IT",2024 +"2024-05-01","Festa dei Lavoratori","IT",2024 +"2024-06-02","Festa della Repubblica","IT",2024 +"2024-08-15","Assunzione della Vergine","IT",2024 +"2024-11-01","Tutti i Santi","IT",2024 +"2024-12-08","Immacolata Concezione","IT",2024 +"2024-12-25","Natale","IT",2024 +"2024-12-26","Santo Stefano","IT",2024 +"2025-01-01","Capodanno","IT",2025 +"2025-01-06","Epifania del Signore","IT",2025 +"2025-04-20","Pasqua di Resurrezione","IT",2025 +"2025-04-21","Lunedi dell'Angelo","IT",2025 +"2025-04-25","Festa della Liberazione","IT",2025 +"2025-05-01","Festa dei Lavoratori","IT",2025 +"2025-06-02","Festa della Repubblica","IT",2025 +"2025-08-15","Assunzione della Vergine","IT",2025 +"2025-11-01","Tutti i Santi","IT",2025 +"2025-12-08","Immacolata Concezione","IT",2025 +"2025-12-25","Natale","IT",2025 +"2025-12-26","Santo Stefano","IT",2025 +"2026-01-01","Capodanno","IT",2026 +"2026-01-06","Epifania del Signore","IT",2026 +"2026-04-05","Pasqua di Resurrezione","IT",2026 +"2026-04-06","Lunedi dell'Angelo","IT",2026 +"2026-04-25","Festa della Liberazione","IT",2026 +"2026-05-01","Festa dei Lavoratori","IT",2026 +"2026-06-02","Festa della Repubblica","IT",2026 +"2026-08-15","Assunzione della Vergine","IT",2026 +"2026-11-01","Tutti i Santi","IT",2026 +"2026-12-08","Immacolata Concezione","IT",2026 +"2026-12-25","Natale","IT",2026 +"2026-12-26","Santo Stefano","IT",2026 +"2027-01-01","Capodanno","IT",2027 +"2027-01-06","Epifania del Signore","IT",2027 +"2027-03-28","Pasqua di Resurrezione","IT",2027 +"2027-03-29","Lunedi dell'Angelo","IT",2027 +"2027-04-25","Festa della Liberazione","IT",2027 +"2027-05-01","Festa dei Lavoratori","IT",2027 +"2027-06-02","Festa della Repubblica","IT",2027 +"2027-08-15","Assunzione della Vergine","IT",2027 +"2027-11-01","Tutti i Santi","IT",2027 +"2027-12-08","Immacolata Concezione","IT",2027 +"2027-12-25","Natale","IT",2027 +"2027-12-26","Santo Stefano","IT",2027 +"2028-01-01","Capodanno","IT",2028 +"2028-01-06","Epifania del Signore","IT",2028 +"2028-04-16","Pasqua di Resurrezione","IT",2028 +"2028-04-17","Lunedi dell'Angelo","IT",2028 +"2028-04-25","Festa della Liberazione","IT",2028 +"2028-05-01","Festa dei Lavoratori","IT",2028 +"2028-06-02","Festa della Repubblica","IT",2028 +"2028-08-15","Assunzione della Vergine","IT",2028 +"2028-11-01","Tutti i Santi","IT",2028 +"2028-12-08","Immacolata Concezione","IT",2028 +"2028-12-25","Natale","IT",2028 +"2028-12-26","Santo Stefano","IT",2028 +"2029-01-01","Capodanno","IT",2029 +"2029-01-06","Epifania del Signore","IT",2029 +"2029-04-01","Pasqua di Resurrezione","IT",2029 +"2029-04-02","Lunedi dell'Angelo","IT",2029 +"2029-04-25","Festa della Liberazione","IT",2029 +"2029-05-01","Festa dei Lavoratori","IT",2029 +"2029-06-02","Festa della Repubblica","IT",2029 +"2029-08-15","Assunzione della Vergine","IT",2029 +"2029-11-01","Tutti i Santi","IT",2029 +"2029-12-08","Immacolata Concezione","IT",2029 +"2029-12-25","Natale","IT",2029 +"2029-12-26","Santo Stefano","IT",2029 +"2030-01-01","Capodanno","IT",2030 +"2030-01-06","Epifania del Signore","IT",2030 +"2030-04-21","Pasqua di Resurrezione","IT",2030 +"2030-04-22","Lunedi dell'Angelo","IT",2030 +"2030-04-25","Festa della Liberazione","IT",2030 +"2030-05-01","Festa dei Lavoratori","IT",2030 +"2030-06-02","Festa della Repubblica","IT",2030 +"2030-08-15","Assunzione della Vergine","IT",2030 +"2030-11-01","Tutti i Santi","IT",2030 +"2030-12-08","Immacolata Concezione","IT",2030 +"2030-12-25","Natale","IT",2030 +"2030-12-26","Santo Stefano","IT",2030 +"2031-01-01","Capodanno","IT",2031 +"2031-01-06","Epifania del Signore","IT",2031 +"2031-04-13","Pasqua di Resurrezione","IT",2031 +"2031-04-14","Lunedi dell'Angelo","IT",2031 +"2031-04-25","Festa della Liberazione","IT",2031 +"2031-05-01","Festa dei Lavoratori","IT",2031 +"2031-06-02","Festa della Repubblica","IT",2031 +"2031-08-15","Assunzione della Vergine","IT",2031 +"2031-11-01","Tutti i Santi","IT",2031 +"2031-12-08","Immacolata Concezione","IT",2031 +"2031-12-25","Natale","IT",2031 +"2031-12-26","Santo Stefano","IT",2031 +"2032-01-01","Capodanno","IT",2032 +"2032-01-06","Epifania del Signore","IT",2032 +"2032-03-28","Pasqua di Resurrezione","IT",2032 +"2032-03-29","Lunedi dell'Angelo","IT",2032 +"2032-04-25","Festa della Liberazione","IT",2032 +"2032-05-01","Festa dei Lavoratori","IT",2032 +"2032-06-02","Festa della Repubblica","IT",2032 +"2032-08-15","Assunzione della Vergine","IT",2032 +"2032-11-01","Tutti i Santi","IT",2032 +"2032-12-08","Immacolata Concezione","IT",2032 +"2032-12-25","Natale","IT",2032 +"2032-12-26","Santo Stefano","IT",2032 +"2033-01-01","Capodanno","IT",2033 +"2033-01-06","Epifania del Signore","IT",2033 +"2033-04-17","Pasqua di Resurrezione","IT",2033 +"2033-04-18","Lunedi dell'Angelo","IT",2033 +"2033-04-25","Festa della Liberazione","IT",2033 +"2033-05-01","Festa dei Lavoratori","IT",2033 +"2033-06-02","Festa della Repubblica","IT",2033 +"2033-08-15","Assunzione della Vergine","IT",2033 +"2033-11-01","Tutti i Santi","IT",2033 +"2033-12-08","Immacolata Concezione","IT",2033 +"2033-12-25","Natale","IT",2033 +"2033-12-26","Santo Stefano","IT",2033 +"2034-01-01","Capodanno","IT",2034 +"2034-01-06","Epifania del Signore","IT",2034 +"2034-04-09","Pasqua di Resurrezione","IT",2034 +"2034-04-10","Lunedi dell'Angelo","IT",2034 +"2034-04-25","Festa della Liberazione","IT",2034 +"2034-05-01","Festa dei Lavoratori","IT",2034 +"2034-06-02","Festa della Repubblica","IT",2034 +"2034-08-15","Assunzione della Vergine","IT",2034 +"2034-11-01","Tutti i Santi","IT",2034 +"2034-12-08","Immacolata Concezione","IT",2034 +"2034-12-25","Natale","IT",2034 +"2034-12-26","Santo Stefano","IT",2034 +"2035-01-01","Capodanno","IT",2035 +"2035-01-06","Epifania del Signore","IT",2035 +"2035-03-25","Pasqua di Resurrezione","IT",2035 +"2035-03-26","Lunedi dell'Angelo","IT",2035 +"2035-04-25","Festa della Liberazione","IT",2035 +"2035-05-01","Festa dei Lavoratori","IT",2035 +"2035-06-02","Festa della Repubblica","IT",2035 +"2035-08-15","Assunzione della Vergine","IT",2035 +"2035-11-01","Tutti i Santi","IT",2035 +"2035-12-08","Immacolata Concezione","IT",2035 +"2035-12-25","Natale","IT",2035 +"2035-12-26","Santo Stefano","IT",2035 +"2036-01-01","Capodanno","IT",2036 +"2036-01-06","Epifania del Signore","IT",2036 +"2036-04-13","Pasqua di Resurrezione","IT",2036 +"2036-04-14","Lunedi dell'Angelo","IT",2036 +"2036-04-25","Festa della Liberazione","IT",2036 +"2036-05-01","Festa dei Lavoratori","IT",2036 +"2036-06-02","Festa della Repubblica","IT",2036 +"2036-08-15","Assunzione della Vergine","IT",2036 +"2036-11-01","Tutti i Santi","IT",2036 +"2036-12-08","Immacolata Concezione","IT",2036 +"2036-12-25","Natale","IT",2036 +"2036-12-26","Santo Stefano","IT",2036 +"2037-01-01","Capodanno","IT",2037 +"2037-01-06","Epifania del Signore","IT",2037 +"2037-04-05","Pasqua di Resurrezione","IT",2037 +"2037-04-06","Lunedi dell'Angelo","IT",2037 +"2037-04-25","Festa della Liberazione","IT",2037 +"2037-05-01","Festa dei Lavoratori","IT",2037 +"2037-06-02","Festa della Repubblica","IT",2037 +"2037-08-15","Assunzione della Vergine","IT",2037 +"2037-11-01","Tutti i Santi","IT",2037 +"2037-12-08","Immacolata Concezione","IT",2037 +"2037-12-25","Natale","IT",2037 +"2037-12-26","Santo Stefano","IT",2037 +"2038-01-01","Capodanno","IT",2038 +"2038-01-06","Epifania del Signore","IT",2038 +"2038-04-25","Festa della Liberazione","IT",2038 +"2038-04-25","Pasqua di Resurrezione","IT",2038 +"2038-04-26","Lunedi dell'Angelo","IT",2038 +"2038-05-01","Festa dei Lavoratori","IT",2038 +"2038-06-02","Festa della Repubblica","IT",2038 +"2038-08-15","Assunzione della Vergine","IT",2038 +"2038-11-01","Tutti i Santi","IT",2038 +"2038-12-08","Immacolata Concezione","IT",2038 +"2038-12-25","Natale","IT",2038 +"2038-12-26","Santo Stefano","IT",2038 +"2039-01-01","Capodanno","IT",2039 +"2039-01-06","Epifania del Signore","IT",2039 +"2039-04-10","Pasqua di Resurrezione","IT",2039 +"2039-04-11","Lunedi dell'Angelo","IT",2039 +"2039-04-25","Festa della Liberazione","IT",2039 +"2039-05-01","Festa dei Lavoratori","IT",2039 +"2039-06-02","Festa della Repubblica","IT",2039 +"2039-08-15","Assunzione della Vergine","IT",2039 +"2039-11-01","Tutti i Santi","IT",2039 +"2039-12-08","Immacolata Concezione","IT",2039 +"2039-12-25","Natale","IT",2039 +"2039-12-26","Santo Stefano","IT",2039 +"2040-01-01","Capodanno","IT",2040 +"2040-01-06","Epifania del Signore","IT",2040 +"2040-04-01","Pasqua di Resurrezione","IT",2040 +"2040-04-02","Lunedi dell'Angelo","IT",2040 +"2040-04-25","Festa della Liberazione","IT",2040 +"2040-05-01","Festa dei Lavoratori","IT",2040 +"2040-06-02","Festa della Repubblica","IT",2040 +"2040-08-15","Assunzione della Vergine","IT",2040 +"2040-11-01","Tutti i Santi","IT",2040 +"2040-12-08","Immacolata Concezione","IT",2040 +"2040-12-25","Natale","IT",2040 +"2040-12-26","Santo Stefano","IT",2040 +"2041-01-01","Capodanno","IT",2041 +"2041-01-06","Epifania del Signore","IT",2041 +"2041-04-21","Pasqua di Resurrezione","IT",2041 +"2041-04-22","Lunedi dell'Angelo","IT",2041 +"2041-04-25","Festa della Liberazione","IT",2041 +"2041-05-01","Festa dei Lavoratori","IT",2041 +"2041-06-02","Festa della Repubblica","IT",2041 +"2041-08-15","Assunzione della Vergine","IT",2041 +"2041-11-01","Tutti i Santi","IT",2041 +"2041-12-08","Immacolata Concezione","IT",2041 +"2041-12-25","Natale","IT",2041 +"2041-12-26","Santo Stefano","IT",2041 +"2042-01-01","Capodanno","IT",2042 +"2042-01-06","Epifania del Signore","IT",2042 +"2042-04-06","Pasqua di Resurrezione","IT",2042 +"2042-04-07","Lunedi dell'Angelo","IT",2042 +"2042-04-25","Festa della Liberazione","IT",2042 +"2042-05-01","Festa dei Lavoratori","IT",2042 +"2042-06-02","Festa della Repubblica","IT",2042 +"2042-08-15","Assunzione della Vergine","IT",2042 +"2042-11-01","Tutti i Santi","IT",2042 +"2042-12-08","Immacolata Concezione","IT",2042 +"2042-12-25","Natale","IT",2042 +"2042-12-26","Santo Stefano","IT",2042 +"2043-01-01","Capodanno","IT",2043 +"2043-01-06","Epifania del Signore","IT",2043 +"2043-03-29","Pasqua di Resurrezione","IT",2043 +"2043-03-30","Lunedi dell'Angelo","IT",2043 +"2043-04-25","Festa della Liberazione","IT",2043 +"2043-05-01","Festa dei Lavoratori","IT",2043 +"2043-06-02","Festa della Repubblica","IT",2043 +"2043-08-15","Assunzione della Vergine","IT",2043 +"2043-11-01","Tutti i Santi","IT",2043 +"2043-12-08","Immacolata Concezione","IT",2043 +"2043-12-25","Natale","IT",2043 +"2043-12-26","Santo Stefano","IT",2043 +"2044-01-01","Capodanno","IT",2044 +"2044-01-06","Epifania del Signore","IT",2044 +"2044-04-17","Pasqua di Resurrezione","IT",2044 +"2044-04-18","Lunedi dell'Angelo","IT",2044 +"2044-04-25","Festa della Liberazione","IT",2044 +"2044-05-01","Festa dei Lavoratori","IT",2044 +"2044-06-02","Festa della Repubblica","IT",2044 +"2044-08-15","Assunzione della Vergine","IT",2044 +"2044-11-01","Tutti i Santi","IT",2044 +"2044-12-08","Immacolata Concezione","IT",2044 +"2044-12-25","Natale","IT",2044 +"2044-12-26","Santo Stefano","IT",2044 +"1995-01-01","New Year's Day","JM",1995 +"1995-01-02","New Year's Day (Observed)","JM",1995 +"1995-03-01","Ash Wednesday","JM",1995 +"1995-04-14","Good Friday","JM",1995 +"1995-04-17","Easter Monday","JM",1995 +"1995-05-23","National Labour Day","JM",1995 +"1995-08-06","Independence Day","JM",1995 +"1995-08-07","Independence Day (Observed)","JM",1995 +"1995-10-16","National Heroes Day","JM",1995 +"1995-12-25","Christmas Day","JM",1995 +"1995-12-26","Boxing Day","JM",1995 +"1996-01-01","New Year's Day","JM",1996 +"1996-02-21","Ash Wednesday","JM",1996 +"1996-04-05","Good Friday","JM",1996 +"1996-04-08","Easter Monday","JM",1996 +"1996-05-23","National Labour Day","JM",1996 +"1996-08-06","Independence Day","JM",1996 +"1996-10-21","National Heroes Day","JM",1996 +"1996-12-25","Christmas Day","JM",1996 +"1996-12-26","Boxing Day","JM",1996 +"1997-01-01","New Year's Day","JM",1997 +"1997-02-12","Ash Wednesday","JM",1997 +"1997-03-28","Good Friday","JM",1997 +"1997-03-31","Easter Monday","JM",1997 +"1997-05-23","National Labour Day","JM",1997 +"1997-08-06","Independence Day","JM",1997 +"1997-10-20","National Heroes Day","JM",1997 +"1997-12-25","Christmas Day","JM",1997 +"1997-12-26","Boxing Day","JM",1997 +"1998-01-01","New Year's Day","JM",1998 +"1998-02-25","Ash Wednesday","JM",1998 +"1998-04-10","Good Friday","JM",1998 +"1998-04-13","Easter Monday","JM",1998 +"1998-05-23","National Labour Day","JM",1998 +"1998-05-25","National Labour Day (Observed)","JM",1998 +"1998-08-01","Emancipation Day","JM",1998 +"1998-08-06","Independence Day","JM",1998 +"1998-10-19","National Heroes Day","JM",1998 +"1998-12-25","Christmas Day","JM",1998 +"1998-12-26","Boxing Day","JM",1998 +"1999-01-01","New Year's Day","JM",1999 +"1999-02-17","Ash Wednesday","JM",1999 +"1999-04-02","Good Friday","JM",1999 +"1999-04-05","Easter Monday","JM",1999 +"1999-05-23","National Labour Day","JM",1999 +"1999-05-24","National Labour Day (Observed)","JM",1999 +"1999-08-01","Emancipation Day","JM",1999 +"1999-08-02","Emancipation Day (Observed)","JM",1999 +"1999-08-06","Independence Day","JM",1999 +"1999-10-18","National Heroes Day","JM",1999 +"1999-12-25","Christmas Day","JM",1999 +"1999-12-26","Boxing Day","JM",1999 +"1999-12-27","Boxing Day (Observed)","JM",1999 +"2000-01-01","New Year's Day","JM",2000 +"2000-03-08","Ash Wednesday","JM",2000 +"2000-04-21","Good Friday","JM",2000 +"2000-04-24","Easter Monday","JM",2000 +"2000-05-23","National Labour Day","JM",2000 +"2000-08-01","Emancipation Day","JM",2000 +"2000-08-06","Independence Day","JM",2000 +"2000-08-07","Independence Day (Observed)","JM",2000 +"2000-10-16","National Heroes Day","JM",2000 +"2000-12-25","Christmas Day","JM",2000 +"2000-12-26","Boxing Day","JM",2000 +"2001-01-01","New Year's Day","JM",2001 +"2001-02-28","Ash Wednesday","JM",2001 +"2001-04-13","Good Friday","JM",2001 +"2001-04-16","Easter Monday","JM",2001 +"2001-05-23","National Labour Day","JM",2001 +"2001-08-01","Emancipation Day","JM",2001 +"2001-08-06","Independence Day","JM",2001 +"2001-10-15","National Heroes Day","JM",2001 +"2001-12-25","Christmas Day","JM",2001 +"2001-12-26","Boxing Day","JM",2001 +"2002-01-01","New Year's Day","JM",2002 +"2002-02-13","Ash Wednesday","JM",2002 +"2002-03-29","Good Friday","JM",2002 +"2002-04-01","Easter Monday","JM",2002 +"2002-05-23","National Labour Day","JM",2002 +"2002-08-01","Emancipation Day","JM",2002 +"2002-08-06","Independence Day","JM",2002 +"2002-10-21","National Heroes Day","JM",2002 +"2002-12-25","Christmas Day","JM",2002 +"2002-12-26","Boxing Day","JM",2002 +"2003-01-01","New Year's Day","JM",2003 +"2003-03-05","Ash Wednesday","JM",2003 +"2003-04-18","Good Friday","JM",2003 +"2003-04-21","Easter Monday","JM",2003 +"2003-05-23","National Labour Day","JM",2003 +"2003-08-01","Emancipation Day","JM",2003 +"2003-08-06","Independence Day","JM",2003 +"2003-10-20","National Heroes Day","JM",2003 +"2003-12-25","Christmas Day","JM",2003 +"2003-12-26","Boxing Day","JM",2003 +"2004-01-01","New Year's Day","JM",2004 +"2004-02-25","Ash Wednesday","JM",2004 +"2004-04-09","Good Friday","JM",2004 +"2004-04-12","Easter Monday","JM",2004 +"2004-05-23","National Labour Day","JM",2004 +"2004-05-24","National Labour Day (Observed)","JM",2004 +"2004-08-01","Emancipation Day","JM",2004 +"2004-08-02","Emancipation Day (Observed)","JM",2004 +"2004-08-06","Independence Day","JM",2004 +"2004-10-18","National Heroes Day","JM",2004 +"2004-12-25","Christmas Day","JM",2004 +"2004-12-26","Boxing Day","JM",2004 +"2004-12-27","Boxing Day (Observed)","JM",2004 +"2005-01-01","New Year's Day","JM",2005 +"2005-02-09","Ash Wednesday","JM",2005 +"2005-03-25","Good Friday","JM",2005 +"2005-03-28","Easter Monday","JM",2005 +"2005-05-23","National Labour Day","JM",2005 +"2005-08-01","Emancipation Day","JM",2005 +"2005-08-06","Independence Day","JM",2005 +"2005-10-17","National Heroes Day","JM",2005 +"2005-12-25","Christmas Day","JM",2005 +"2005-12-26","Boxing Day","JM",2005 +"2005-12-27","Christmas Day (Observed)","JM",2005 +"2006-01-01","New Year's Day","JM",2006 +"2006-01-02","New Year's Day (Observed)","JM",2006 +"2006-03-01","Ash Wednesday","JM",2006 +"2006-04-14","Good Friday","JM",2006 +"2006-04-17","Easter Monday","JM",2006 +"2006-05-23","National Labour Day","JM",2006 +"2006-08-01","Emancipation Day","JM",2006 +"2006-08-06","Independence Day","JM",2006 +"2006-08-07","Independence Day (Observed)","JM",2006 +"2006-10-16","National Heroes Day","JM",2006 +"2006-12-25","Christmas Day","JM",2006 +"2006-12-26","Boxing Day","JM",2006 +"2007-01-01","New Year's Day","JM",2007 +"2007-02-21","Ash Wednesday","JM",2007 +"2007-04-06","Good Friday","JM",2007 +"2007-04-09","Easter Monday","JM",2007 +"2007-05-23","National Labour Day","JM",2007 +"2007-08-01","Emancipation Day","JM",2007 +"2007-08-06","Independence Day","JM",2007 +"2007-10-15","National Heroes Day","JM",2007 +"2007-12-25","Christmas Day","JM",2007 +"2007-12-26","Boxing Day","JM",2007 +"2008-01-01","New Year's Day","JM",2008 +"2008-02-06","Ash Wednesday","JM",2008 +"2008-03-21","Good Friday","JM",2008 +"2008-03-24","Easter Monday","JM",2008 +"2008-05-23","National Labour Day","JM",2008 +"2008-08-01","Emancipation Day","JM",2008 +"2008-08-06","Independence Day","JM",2008 +"2008-10-20","National Heroes Day","JM",2008 +"2008-12-25","Christmas Day","JM",2008 +"2008-12-26","Boxing Day","JM",2008 +"2009-01-01","New Year's Day","JM",2009 +"2009-02-25","Ash Wednesday","JM",2009 +"2009-04-10","Good Friday","JM",2009 +"2009-04-13","Easter Monday","JM",2009 +"2009-05-23","National Labour Day","JM",2009 +"2009-05-25","National Labour Day (Observed)","JM",2009 +"2009-08-01","Emancipation Day","JM",2009 +"2009-08-06","Independence Day","JM",2009 +"2009-10-19","National Heroes Day","JM",2009 +"2009-12-25","Christmas Day","JM",2009 +"2009-12-26","Boxing Day","JM",2009 +"2010-01-01","New Year's Day","JM",2010 +"2010-02-17","Ash Wednesday","JM",2010 +"2010-04-02","Good Friday","JM",2010 +"2010-04-05","Easter Monday","JM",2010 +"2010-05-23","National Labour Day","JM",2010 +"2010-05-24","National Labour Day (Observed)","JM",2010 +"2010-08-01","Emancipation Day","JM",2010 +"2010-08-02","Emancipation Day (Observed)","JM",2010 +"2010-08-06","Independence Day","JM",2010 +"2010-10-18","National Heroes Day","JM",2010 +"2010-12-25","Christmas Day","JM",2010 +"2010-12-26","Boxing Day","JM",2010 +"2010-12-27","Boxing Day (Observed)","JM",2010 +"2011-01-01","New Year's Day","JM",2011 +"2011-03-09","Ash Wednesday","JM",2011 +"2011-04-22","Good Friday","JM",2011 +"2011-04-25","Easter Monday","JM",2011 +"2011-05-23","National Labour Day","JM",2011 +"2011-08-01","Emancipation Day","JM",2011 +"2011-08-06","Independence Day","JM",2011 +"2011-10-17","National Heroes Day","JM",2011 +"2011-12-25","Christmas Day","JM",2011 +"2011-12-26","Boxing Day","JM",2011 +"2011-12-27","Christmas Day (Observed)","JM",2011 +"2012-01-01","New Year's Day","JM",2012 +"2012-01-02","New Year's Day (Observed)","JM",2012 +"2012-02-22","Ash Wednesday","JM",2012 +"2012-04-06","Good Friday","JM",2012 +"2012-04-09","Easter Monday","JM",2012 +"2012-05-23","National Labour Day","JM",2012 +"2012-08-01","Emancipation Day","JM",2012 +"2012-08-06","Independence Day","JM",2012 +"2012-10-15","National Heroes Day","JM",2012 +"2012-12-25","Christmas Day","JM",2012 +"2012-12-26","Boxing Day","JM",2012 +"2013-01-01","New Year's Day","JM",2013 +"2013-02-13","Ash Wednesday","JM",2013 +"2013-03-29","Good Friday","JM",2013 +"2013-04-01","Easter Monday","JM",2013 +"2013-05-23","National Labour Day","JM",2013 +"2013-08-01","Emancipation Day","JM",2013 +"2013-08-06","Independence Day","JM",2013 +"2013-10-21","National Heroes Day","JM",2013 +"2013-12-25","Christmas Day","JM",2013 +"2013-12-26","Boxing Day","JM",2013 +"2014-01-01","New Year's Day","JM",2014 +"2014-03-05","Ash Wednesday","JM",2014 +"2014-04-18","Good Friday","JM",2014 +"2014-04-21","Easter Monday","JM",2014 +"2014-05-23","National Labour Day","JM",2014 +"2014-08-01","Emancipation Day","JM",2014 +"2014-08-06","Independence Day","JM",2014 +"2014-10-20","National Heroes Day","JM",2014 +"2014-12-25","Christmas Day","JM",2014 +"2014-12-26","Boxing Day","JM",2014 +"2015-01-01","New Year's Day","JM",2015 +"2015-02-18","Ash Wednesday","JM",2015 +"2015-04-03","Good Friday","JM",2015 +"2015-04-06","Easter Monday","JM",2015 +"2015-05-23","National Labour Day","JM",2015 +"2015-05-25","National Labour Day (Observed)","JM",2015 +"2015-08-01","Emancipation Day","JM",2015 +"2015-08-06","Independence Day","JM",2015 +"2015-10-19","National Heroes Day","JM",2015 +"2015-12-25","Christmas Day","JM",2015 +"2015-12-26","Boxing Day","JM",2015 +"2016-01-01","New Year's Day","JM",2016 +"2016-02-10","Ash Wednesday","JM",2016 +"2016-03-25","Good Friday","JM",2016 +"2016-03-28","Easter Monday","JM",2016 +"2016-05-23","National Labour Day","JM",2016 +"2016-08-01","Emancipation Day","JM",2016 +"2016-08-06","Independence Day","JM",2016 +"2016-10-17","National Heroes Day","JM",2016 +"2016-12-25","Christmas Day","JM",2016 +"2016-12-26","Boxing Day","JM",2016 +"2016-12-27","Christmas Day (Observed)","JM",2016 +"2017-01-01","New Year's Day","JM",2017 +"2017-01-02","New Year's Day (Observed)","JM",2017 +"2017-03-01","Ash Wednesday","JM",2017 +"2017-04-14","Good Friday","JM",2017 +"2017-04-17","Easter Monday","JM",2017 +"2017-05-23","National Labour Day","JM",2017 +"2017-08-01","Emancipation Day","JM",2017 +"2017-08-06","Independence Day","JM",2017 +"2017-08-07","Independence Day (Observed)","JM",2017 +"2017-10-16","National Heroes Day","JM",2017 +"2017-12-25","Christmas Day","JM",2017 +"2017-12-26","Boxing Day","JM",2017 +"2018-01-01","New Year's Day","JM",2018 +"2018-02-14","Ash Wednesday","JM",2018 +"2018-03-30","Good Friday","JM",2018 +"2018-04-02","Easter Monday","JM",2018 +"2018-05-23","National Labour Day","JM",2018 +"2018-08-01","Emancipation Day","JM",2018 +"2018-08-06","Independence Day","JM",2018 +"2018-10-15","National Heroes Day","JM",2018 +"2018-12-25","Christmas Day","JM",2018 +"2018-12-26","Boxing Day","JM",2018 +"2019-01-01","New Year's Day","JM",2019 +"2019-03-06","Ash Wednesday","JM",2019 +"2019-04-19","Good Friday","JM",2019 +"2019-04-22","Easter Monday","JM",2019 +"2019-05-23","National Labour Day","JM",2019 +"2019-08-01","Emancipation Day","JM",2019 +"2019-08-06","Independence Day","JM",2019 +"2019-10-21","National Heroes Day","JM",2019 +"2019-12-25","Christmas Day","JM",2019 +"2019-12-26","Boxing Day","JM",2019 +"2020-01-01","New Year's Day","JM",2020 +"2020-02-26","Ash Wednesday","JM",2020 +"2020-04-10","Good Friday","JM",2020 +"2020-04-13","Easter Monday","JM",2020 +"2020-05-23","National Labour Day","JM",2020 +"2020-05-25","National Labour Day (Observed)","JM",2020 +"2020-08-01","Emancipation Day","JM",2020 +"2020-08-06","Independence Day","JM",2020 +"2020-10-19","National Heroes Day","JM",2020 +"2020-12-25","Christmas Day","JM",2020 +"2020-12-26","Boxing Day","JM",2020 +"2021-01-01","New Year's Day","JM",2021 +"2021-02-17","Ash Wednesday","JM",2021 +"2021-04-02","Good Friday","JM",2021 +"2021-04-05","Easter Monday","JM",2021 +"2021-05-23","National Labour Day","JM",2021 +"2021-05-24","National Labour Day (Observed)","JM",2021 +"2021-08-01","Emancipation Day","JM",2021 +"2021-08-02","Emancipation Day (Observed)","JM",2021 +"2021-08-06","Independence Day","JM",2021 +"2021-10-18","National Heroes Day","JM",2021 +"2021-12-25","Christmas Day","JM",2021 +"2021-12-26","Boxing Day","JM",2021 +"2021-12-27","Boxing Day (Observed)","JM",2021 +"2022-01-01","New Year's Day","JM",2022 +"2022-03-02","Ash Wednesday","JM",2022 +"2022-04-15","Good Friday","JM",2022 +"2022-04-18","Easter Monday","JM",2022 +"2022-05-23","National Labour Day","JM",2022 +"2022-08-01","Emancipation Day","JM",2022 +"2022-08-06","Independence Day","JM",2022 +"2022-10-17","National Heroes Day","JM",2022 +"2022-12-25","Christmas Day","JM",2022 +"2022-12-26","Boxing Day","JM",2022 +"2022-12-27","Christmas Day (Observed)","JM",2022 +"2023-01-01","New Year's Day","JM",2023 +"2023-01-02","New Year's Day (Observed)","JM",2023 +"2023-02-22","Ash Wednesday","JM",2023 +"2023-04-07","Good Friday","JM",2023 +"2023-04-10","Easter Monday","JM",2023 +"2023-05-23","National Labour Day","JM",2023 +"2023-08-01","Emancipation Day","JM",2023 +"2023-08-06","Independence Day","JM",2023 +"2023-08-07","Independence Day (Observed)","JM",2023 +"2023-10-16","National Heroes Day","JM",2023 +"2023-12-25","Christmas Day","JM",2023 +"2023-12-26","Boxing Day","JM",2023 +"2024-01-01","New Year's Day","JM",2024 +"2024-02-14","Ash Wednesday","JM",2024 +"2024-03-29","Good Friday","JM",2024 +"2024-04-01","Easter Monday","JM",2024 +"2024-05-23","National Labour Day","JM",2024 +"2024-08-01","Emancipation Day","JM",2024 +"2024-08-06","Independence Day","JM",2024 +"2024-10-21","National Heroes Day","JM",2024 +"2024-12-25","Christmas Day","JM",2024 +"2024-12-26","Boxing Day","JM",2024 +"2025-01-01","New Year's Day","JM",2025 +"2025-03-05","Ash Wednesday","JM",2025 +"2025-04-18","Good Friday","JM",2025 +"2025-04-21","Easter Monday","JM",2025 +"2025-05-23","National Labour Day","JM",2025 +"2025-08-01","Emancipation Day","JM",2025 +"2025-08-06","Independence Day","JM",2025 +"2025-10-20","National Heroes Day","JM",2025 +"2025-12-25","Christmas Day","JM",2025 +"2025-12-26","Boxing Day","JM",2025 +"2026-01-01","New Year's Day","JM",2026 +"2026-02-18","Ash Wednesday","JM",2026 +"2026-04-03","Good Friday","JM",2026 +"2026-04-06","Easter Monday","JM",2026 +"2026-05-23","National Labour Day","JM",2026 +"2026-05-25","National Labour Day (Observed)","JM",2026 +"2026-08-01","Emancipation Day","JM",2026 +"2026-08-06","Independence Day","JM",2026 +"2026-10-19","National Heroes Day","JM",2026 +"2026-12-25","Christmas Day","JM",2026 +"2026-12-26","Boxing Day","JM",2026 +"2027-01-01","New Year's Day","JM",2027 +"2027-02-10","Ash Wednesday","JM",2027 +"2027-03-26","Good Friday","JM",2027 +"2027-03-29","Easter Monday","JM",2027 +"2027-05-23","National Labour Day","JM",2027 +"2027-05-24","National Labour Day (Observed)","JM",2027 +"2027-08-01","Emancipation Day","JM",2027 +"2027-08-02","Emancipation Day (Observed)","JM",2027 +"2027-08-06","Independence Day","JM",2027 +"2027-10-18","National Heroes Day","JM",2027 +"2027-12-25","Christmas Day","JM",2027 +"2027-12-26","Boxing Day","JM",2027 +"2027-12-27","Boxing Day (Observed)","JM",2027 +"2028-01-01","New Year's Day","JM",2028 +"2028-03-01","Ash Wednesday","JM",2028 +"2028-04-14","Good Friday","JM",2028 +"2028-04-17","Easter Monday","JM",2028 +"2028-05-23","National Labour Day","JM",2028 +"2028-08-01","Emancipation Day","JM",2028 +"2028-08-06","Independence Day","JM",2028 +"2028-08-07","Independence Day (Observed)","JM",2028 +"2028-10-16","National Heroes Day","JM",2028 +"2028-12-25","Christmas Day","JM",2028 +"2028-12-26","Boxing Day","JM",2028 +"2029-01-01","New Year's Day","JM",2029 +"2029-02-14","Ash Wednesday","JM",2029 +"2029-03-30","Good Friday","JM",2029 +"2029-04-02","Easter Monday","JM",2029 +"2029-05-23","National Labour Day","JM",2029 +"2029-08-01","Emancipation Day","JM",2029 +"2029-08-06","Independence Day","JM",2029 +"2029-10-15","National Heroes Day","JM",2029 +"2029-12-25","Christmas Day","JM",2029 +"2029-12-26","Boxing Day","JM",2029 +"2030-01-01","New Year's Day","JM",2030 +"2030-03-06","Ash Wednesday","JM",2030 +"2030-04-19","Good Friday","JM",2030 +"2030-04-22","Easter Monday","JM",2030 +"2030-05-23","National Labour Day","JM",2030 +"2030-08-01","Emancipation Day","JM",2030 +"2030-08-06","Independence Day","JM",2030 +"2030-10-21","National Heroes Day","JM",2030 +"2030-12-25","Christmas Day","JM",2030 +"2030-12-26","Boxing Day","JM",2030 +"2031-01-01","New Year's Day","JM",2031 +"2031-02-26","Ash Wednesday","JM",2031 +"2031-04-11","Good Friday","JM",2031 +"2031-04-14","Easter Monday","JM",2031 +"2031-05-23","National Labour Day","JM",2031 +"2031-08-01","Emancipation Day","JM",2031 +"2031-08-06","Independence Day","JM",2031 +"2031-10-20","National Heroes Day","JM",2031 +"2031-12-25","Christmas Day","JM",2031 +"2031-12-26","Boxing Day","JM",2031 +"2032-01-01","New Year's Day","JM",2032 +"2032-02-11","Ash Wednesday","JM",2032 +"2032-03-26","Good Friday","JM",2032 +"2032-03-29","Easter Monday","JM",2032 +"2032-05-23","National Labour Day","JM",2032 +"2032-05-24","National Labour Day (Observed)","JM",2032 +"2032-08-01","Emancipation Day","JM",2032 +"2032-08-02","Emancipation Day (Observed)","JM",2032 +"2032-08-06","Independence Day","JM",2032 +"2032-10-18","National Heroes Day","JM",2032 +"2032-12-25","Christmas Day","JM",2032 +"2032-12-26","Boxing Day","JM",2032 +"2032-12-27","Boxing Day (Observed)","JM",2032 +"2033-01-01","New Year's Day","JM",2033 +"2033-03-02","Ash Wednesday","JM",2033 +"2033-04-15","Good Friday","JM",2033 +"2033-04-18","Easter Monday","JM",2033 +"2033-05-23","National Labour Day","JM",2033 +"2033-08-01","Emancipation Day","JM",2033 +"2033-08-06","Independence Day","JM",2033 +"2033-10-17","National Heroes Day","JM",2033 +"2033-12-25","Christmas Day","JM",2033 +"2033-12-26","Boxing Day","JM",2033 +"2033-12-27","Christmas Day (Observed)","JM",2033 +"2034-01-01","New Year's Day","JM",2034 +"2034-01-02","New Year's Day (Observed)","JM",2034 +"2034-02-22","Ash Wednesday","JM",2034 +"2034-04-07","Good Friday","JM",2034 +"2034-04-10","Easter Monday","JM",2034 +"2034-05-23","National Labour Day","JM",2034 +"2034-08-01","Emancipation Day","JM",2034 +"2034-08-06","Independence Day","JM",2034 +"2034-08-07","Independence Day (Observed)","JM",2034 +"2034-10-16","National Heroes Day","JM",2034 +"2034-12-25","Christmas Day","JM",2034 +"2034-12-26","Boxing Day","JM",2034 +"2035-01-01","New Year's Day","JM",2035 +"2035-02-07","Ash Wednesday","JM",2035 +"2035-03-23","Good Friday","JM",2035 +"2035-03-26","Easter Monday","JM",2035 +"2035-05-23","National Labour Day","JM",2035 +"2035-08-01","Emancipation Day","JM",2035 +"2035-08-06","Independence Day","JM",2035 +"2035-10-15","National Heroes Day","JM",2035 +"2035-12-25","Christmas Day","JM",2035 +"2035-12-26","Boxing Day","JM",2035 +"2036-01-01","New Year's Day","JM",2036 +"2036-02-27","Ash Wednesday","JM",2036 +"2036-04-11","Good Friday","JM",2036 +"2036-04-14","Easter Monday","JM",2036 +"2036-05-23","National Labour Day","JM",2036 +"2036-08-01","Emancipation Day","JM",2036 +"2036-08-06","Independence Day","JM",2036 +"2036-10-20","National Heroes Day","JM",2036 +"2036-12-25","Christmas Day","JM",2036 +"2036-12-26","Boxing Day","JM",2036 +"2037-01-01","New Year's Day","JM",2037 +"2037-02-18","Ash Wednesday","JM",2037 +"2037-04-03","Good Friday","JM",2037 +"2037-04-06","Easter Monday","JM",2037 +"2037-05-23","National Labour Day","JM",2037 +"2037-05-25","National Labour Day (Observed)","JM",2037 +"2037-08-01","Emancipation Day","JM",2037 +"2037-08-06","Independence Day","JM",2037 +"2037-10-19","National Heroes Day","JM",2037 +"2037-12-25","Christmas Day","JM",2037 +"2037-12-26","Boxing Day","JM",2037 +"2038-01-01","New Year's Day","JM",2038 +"2038-03-10","Ash Wednesday","JM",2038 +"2038-04-23","Good Friday","JM",2038 +"2038-04-26","Easter Monday","JM",2038 +"2038-05-23","National Labour Day","JM",2038 +"2038-05-24","National Labour Day (Observed)","JM",2038 +"2038-08-01","Emancipation Day","JM",2038 +"2038-08-02","Emancipation Day (Observed)","JM",2038 +"2038-08-06","Independence Day","JM",2038 +"2038-10-18","National Heroes Day","JM",2038 +"2038-12-25","Christmas Day","JM",2038 +"2038-12-26","Boxing Day","JM",2038 +"2038-12-27","Boxing Day (Observed)","JM",2038 +"2039-01-01","New Year's Day","JM",2039 +"2039-02-23","Ash Wednesday","JM",2039 +"2039-04-08","Good Friday","JM",2039 +"2039-04-11","Easter Monday","JM",2039 +"2039-05-23","National Labour Day","JM",2039 +"2039-08-01","Emancipation Day","JM",2039 +"2039-08-06","Independence Day","JM",2039 +"2039-10-17","National Heroes Day","JM",2039 +"2039-12-25","Christmas Day","JM",2039 +"2039-12-26","Boxing Day","JM",2039 +"2039-12-27","Christmas Day (Observed)","JM",2039 +"2040-01-01","New Year's Day","JM",2040 +"2040-01-02","New Year's Day (Observed)","JM",2040 +"2040-02-15","Ash Wednesday","JM",2040 +"2040-03-30","Good Friday","JM",2040 +"2040-04-02","Easter Monday","JM",2040 +"2040-05-23","National Labour Day","JM",2040 +"2040-08-01","Emancipation Day","JM",2040 +"2040-08-06","Independence Day","JM",2040 +"2040-10-15","National Heroes Day","JM",2040 +"2040-12-25","Christmas Day","JM",2040 +"2040-12-26","Boxing Day","JM",2040 +"2041-01-01","New Year's Day","JM",2041 +"2041-03-06","Ash Wednesday","JM",2041 +"2041-04-19","Good Friday","JM",2041 +"2041-04-22","Easter Monday","JM",2041 +"2041-05-23","National Labour Day","JM",2041 +"2041-08-01","Emancipation Day","JM",2041 +"2041-08-06","Independence Day","JM",2041 +"2041-10-21","National Heroes Day","JM",2041 +"2041-12-25","Christmas Day","JM",2041 +"2041-12-26","Boxing Day","JM",2041 +"2042-01-01","New Year's Day","JM",2042 +"2042-02-19","Ash Wednesday","JM",2042 +"2042-04-04","Good Friday","JM",2042 +"2042-04-07","Easter Monday","JM",2042 +"2042-05-23","National Labour Day","JM",2042 +"2042-08-01","Emancipation Day","JM",2042 +"2042-08-06","Independence Day","JM",2042 +"2042-10-20","National Heroes Day","JM",2042 +"2042-12-25","Christmas Day","JM",2042 +"2042-12-26","Boxing Day","JM",2042 +"2043-01-01","New Year's Day","JM",2043 +"2043-02-11","Ash Wednesday","JM",2043 +"2043-03-27","Good Friday","JM",2043 +"2043-03-30","Easter Monday","JM",2043 +"2043-05-23","National Labour Day","JM",2043 +"2043-05-25","National Labour Day (Observed)","JM",2043 +"2043-08-01","Emancipation Day","JM",2043 +"2043-08-06","Independence Day","JM",2043 +"2043-10-19","National Heroes Day","JM",2043 +"2043-12-25","Christmas Day","JM",2043 +"2043-12-26","Boxing Day","JM",2043 +"2044-01-01","New Year's Day","JM",2044 +"2044-03-02","Ash Wednesday","JM",2044 +"2044-04-15","Good Friday","JM",2044 +"2044-04-18","Easter Monday","JM",2044 +"2044-05-23","National Labour Day","JM",2044 +"2044-08-01","Emancipation Day","JM",2044 +"2044-08-06","Independence Day","JM",2044 +"2044-10-17","National Heroes Day","JM",2044 +"2044-12-25","Christmas Day","JM",2044 +"2044-12-26","Boxing Day","JM",2044 +"2044-12-27","Christmas Day (Observed)","JM",2044 +"1995-01-01","New Year's Day","JP",1995 +"1995-01-02","Substitute Holiday","JP",1995 +"1995-01-15","Coming of Age Day","JP",1995 +"1995-01-16","Substitute Holiday","JP",1995 +"1995-02-11","Foundation Day","JP",1995 +"1995-03-21","Vernal Equinox Day","JP",1995 +"1995-04-29","Greenery Day","JP",1995 +"1995-05-03","Constitution Day","JP",1995 +"1995-05-04","National Holiday","JP",1995 +"1995-05-05","Children's Day","JP",1995 +"1995-09-15","Respect for the Aged Day","JP",1995 +"1995-09-23","Autumnal Equinox","JP",1995 +"1995-10-10","Physical Education Day","JP",1995 +"1995-11-03","Culture Day","JP",1995 +"1995-11-23","Labor Thanksgiving Day","JP",1995 +"1995-12-23","Emperor's Birthday","JP",1995 +"1996-01-01","New Year's Day","JP",1996 +"1996-01-15","Coming of Age Day","JP",1996 +"1996-02-11","Foundation Day","JP",1996 +"1996-02-12","Substitute Holiday","JP",1996 +"1996-03-20","Vernal Equinox Day","JP",1996 +"1996-04-29","Greenery Day","JP",1996 +"1996-05-03","Constitution Day","JP",1996 +"1996-05-04","National Holiday","JP",1996 +"1996-05-05","Children's Day","JP",1996 +"1996-05-06","Substitute Holiday","JP",1996 +"1996-07-20","Marine Day","JP",1996 +"1996-09-15","Respect for the Aged Day","JP",1996 +"1996-09-16","Substitute Holiday","JP",1996 +"1996-09-23","Autumnal Equinox","JP",1996 +"1996-10-10","Physical Education Day","JP",1996 +"1996-11-03","Culture Day","JP",1996 +"1996-11-04","Substitute Holiday","JP",1996 +"1996-11-23","Labor Thanksgiving Day","JP",1996 +"1996-12-23","Emperor's Birthday","JP",1996 +"1997-01-01","New Year's Day","JP",1997 +"1997-01-15","Coming of Age Day","JP",1997 +"1997-02-11","Foundation Day","JP",1997 +"1997-03-20","Vernal Equinox Day","JP",1997 +"1997-04-29","Greenery Day","JP",1997 +"1997-05-03","Constitution Day","JP",1997 +"1997-05-05","Children's Day","JP",1997 +"1997-07-20","Marine Day","JP",1997 +"1997-07-21","Substitute Holiday","JP",1997 +"1997-09-15","Respect for the Aged Day","JP",1997 +"1997-09-23","Autumnal Equinox","JP",1997 +"1997-10-10","Physical Education Day","JP",1997 +"1997-11-03","Culture Day","JP",1997 +"1997-11-23","Labor Thanksgiving Day","JP",1997 +"1997-11-24","Substitute Holiday","JP",1997 +"1997-12-23","Emperor's Birthday","JP",1997 +"1998-01-01","New Year's Day","JP",1998 +"1998-01-15","Coming of Age Day","JP",1998 +"1998-02-11","Foundation Day","JP",1998 +"1998-03-21","Vernal Equinox Day","JP",1998 +"1998-04-29","Greenery Day","JP",1998 +"1998-05-03","Constitution Day","JP",1998 +"1998-05-04","Substitute Holiday","JP",1998 +"1998-05-05","Children's Day","JP",1998 +"1998-07-20","Marine Day","JP",1998 +"1998-09-15","Respect for the Aged Day","JP",1998 +"1998-09-23","Autumnal Equinox","JP",1998 +"1998-10-10","Physical Education Day","JP",1998 +"1998-11-03","Culture Day","JP",1998 +"1998-11-23","Labor Thanksgiving Day","JP",1998 +"1998-12-23","Emperor's Birthday","JP",1998 +"1999-01-01","New Year's Day","JP",1999 +"1999-01-15","Coming of Age Day","JP",1999 +"1999-02-11","Foundation Day","JP",1999 +"1999-03-21","Vernal Equinox Day","JP",1999 +"1999-03-22","Substitute Holiday","JP",1999 +"1999-04-29","Greenery Day","JP",1999 +"1999-05-03","Constitution Day","JP",1999 +"1999-05-04","National Holiday","JP",1999 +"1999-05-05","Children's Day","JP",1999 +"1999-07-20","Marine Day","JP",1999 +"1999-09-15","Respect for the Aged Day","JP",1999 +"1999-09-23","Autumnal Equinox","JP",1999 +"1999-10-10","Physical Education Day","JP",1999 +"1999-10-11","Substitute Holiday","JP",1999 +"1999-11-03","Culture Day","JP",1999 +"1999-11-23","Labor Thanksgiving Day","JP",1999 +"1999-12-23","Emperor's Birthday","JP",1999 +"2000-01-01","New Year's Day","JP",2000 +"2000-01-10","Coming of Age Day","JP",2000 +"2000-02-11","Foundation Day","JP",2000 +"2000-03-20","Vernal Equinox Day","JP",2000 +"2000-04-29","Greenery Day","JP",2000 +"2000-05-03","Constitution Day","JP",2000 +"2000-05-04","National Holiday","JP",2000 +"2000-05-05","Children's Day","JP",2000 +"2000-07-20","Marine Day","JP",2000 +"2000-09-15","Respect for the Aged Day","JP",2000 +"2000-09-23","Autumnal Equinox","JP",2000 +"2000-10-09","Physical Education Day","JP",2000 +"2000-11-03","Culture Day","JP",2000 +"2000-11-23","Labor Thanksgiving Day","JP",2000 +"2000-12-23","Emperor's Birthday","JP",2000 +"2001-01-01","New Year's Day","JP",2001 +"2001-01-08","Coming of Age Day","JP",2001 +"2001-02-11","Foundation Day","JP",2001 +"2001-02-12","Substitute Holiday","JP",2001 +"2001-03-20","Vernal Equinox Day","JP",2001 +"2001-04-29","Greenery Day","JP",2001 +"2001-04-30","Substitute Holiday","JP",2001 +"2001-05-03","Constitution Day","JP",2001 +"2001-05-04","National Holiday","JP",2001 +"2001-05-05","Children's Day","JP",2001 +"2001-07-20","Marine Day","JP",2001 +"2001-09-15","Respect for the Aged Day","JP",2001 +"2001-09-23","Autumnal Equinox","JP",2001 +"2001-09-24","Substitute Holiday","JP",2001 +"2001-10-08","Physical Education Day","JP",2001 +"2001-11-03","Culture Day","JP",2001 +"2001-11-23","Labor Thanksgiving Day","JP",2001 +"2001-12-23","Emperor's Birthday","JP",2001 +"2001-12-24","Substitute Holiday","JP",2001 +"2002-01-01","New Year's Day","JP",2002 +"2002-01-14","Coming of Age Day","JP",2002 +"2002-02-11","Foundation Day","JP",2002 +"2002-03-21","Vernal Equinox Day","JP",2002 +"2002-04-29","Greenery Day","JP",2002 +"2002-05-03","Constitution Day","JP",2002 +"2002-05-04","National Holiday","JP",2002 +"2002-05-05","Children's Day","JP",2002 +"2002-05-06","Substitute Holiday","JP",2002 +"2002-07-20","Marine Day","JP",2002 +"2002-09-15","Respect for the Aged Day","JP",2002 +"2002-09-16","Substitute Holiday","JP",2002 +"2002-09-23","Autumnal Equinox","JP",2002 +"2002-10-14","Physical Education Day","JP",2002 +"2002-11-03","Culture Day","JP",2002 +"2002-11-04","Substitute Holiday","JP",2002 +"2002-11-23","Labor Thanksgiving Day","JP",2002 +"2002-12-23","Emperor's Birthday","JP",2002 +"2003-01-01","New Year's Day","JP",2003 +"2003-01-13","Coming of Age Day","JP",2003 +"2003-02-11","Foundation Day","JP",2003 +"2003-03-21","Vernal Equinox Day","JP",2003 +"2003-04-29","Greenery Day","JP",2003 +"2003-05-03","Constitution Day","JP",2003 +"2003-05-05","Children's Day","JP",2003 +"2003-07-21","Marine Day","JP",2003 +"2003-09-15","Respect for the Aged Day","JP",2003 +"2003-09-23","Autumnal Equinox","JP",2003 +"2003-10-13","Physical Education Day","JP",2003 +"2003-11-03","Culture Day","JP",2003 +"2003-11-23","Labor Thanksgiving Day","JP",2003 +"2003-11-24","Substitute Holiday","JP",2003 +"2003-12-23","Emperor's Birthday","JP",2003 +"2004-01-01","New Year's Day","JP",2004 +"2004-01-12","Coming of Age Day","JP",2004 +"2004-02-11","Foundation Day","JP",2004 +"2004-03-20","Vernal Equinox Day","JP",2004 +"2004-04-29","Greenery Day","JP",2004 +"2004-05-03","Constitution Day","JP",2004 +"2004-05-04","National Holiday","JP",2004 +"2004-05-05","Children's Day","JP",2004 +"2004-07-19","Marine Day","JP",2004 +"2004-09-20","Respect for the Aged Day","JP",2004 +"2004-09-23","Autumnal Equinox","JP",2004 +"2004-10-11","Physical Education Day","JP",2004 +"2004-11-03","Culture Day","JP",2004 +"2004-11-23","Labor Thanksgiving Day","JP",2004 +"2004-12-23","Emperor's Birthday","JP",2004 +"2005-01-01","New Year's Day","JP",2005 +"2005-01-10","Coming of Age Day","JP",2005 +"2005-02-11","Foundation Day","JP",2005 +"2005-03-20","Vernal Equinox Day","JP",2005 +"2005-03-21","Substitute Holiday","JP",2005 +"2005-04-29","Greenery Day","JP",2005 +"2005-05-03","Constitution Day","JP",2005 +"2005-05-04","National Holiday","JP",2005 +"2005-05-05","Children's Day","JP",2005 +"2005-07-18","Marine Day","JP",2005 +"2005-09-19","Respect for the Aged Day","JP",2005 +"2005-09-23","Autumnal Equinox","JP",2005 +"2005-10-10","Physical Education Day","JP",2005 +"2005-11-03","Culture Day","JP",2005 +"2005-11-23","Labor Thanksgiving Day","JP",2005 +"2005-12-23","Emperor's Birthday","JP",2005 +"2006-01-01","New Year's Day","JP",2006 +"2006-01-02","Substitute Holiday","JP",2006 +"2006-01-09","Coming of Age Day","JP",2006 +"2006-02-11","Foundation Day","JP",2006 +"2006-03-21","Vernal Equinox Day","JP",2006 +"2006-04-29","Greenery Day","JP",2006 +"2006-05-03","Constitution Day","JP",2006 +"2006-05-04","National Holiday","JP",2006 +"2006-05-05","Children's Day","JP",2006 +"2006-07-17","Marine Day","JP",2006 +"2006-09-18","Respect for the Aged Day","JP",2006 +"2006-09-23","Autumnal Equinox","JP",2006 +"2006-10-09","Physical Education Day","JP",2006 +"2006-11-03","Culture Day","JP",2006 +"2006-11-23","Labor Thanksgiving Day","JP",2006 +"2006-12-23","Emperor's Birthday","JP",2006 +"2007-01-01","New Year's Day","JP",2007 +"2007-01-08","Coming of Age Day","JP",2007 +"2007-02-11","Foundation Day","JP",2007 +"2007-02-12","Substitute Holiday","JP",2007 +"2007-03-21","Vernal Equinox Day","JP",2007 +"2007-04-29","Showa Day","JP",2007 +"2007-04-30","Substitute Holiday","JP",2007 +"2007-05-03","Constitution Day","JP",2007 +"2007-05-04","Greenery Day","JP",2007 +"2007-05-05","Children's Day","JP",2007 +"2007-07-16","Marine Day","JP",2007 +"2007-09-17","Respect for the Aged Day","JP",2007 +"2007-09-23","Autumnal Equinox","JP",2007 +"2007-09-24","Substitute Holiday","JP",2007 +"2007-10-08","Physical Education Day","JP",2007 +"2007-11-03","Culture Day","JP",2007 +"2007-11-23","Labor Thanksgiving Day","JP",2007 +"2007-12-23","Emperor's Birthday","JP",2007 +"2007-12-24","Substitute Holiday","JP",2007 +"2008-01-01","New Year's Day","JP",2008 +"2008-01-14","Coming of Age Day","JP",2008 +"2008-02-11","Foundation Day","JP",2008 +"2008-03-20","Vernal Equinox Day","JP",2008 +"2008-04-29","Showa Day","JP",2008 +"2008-05-03","Constitution Day","JP",2008 +"2008-05-04","Greenery Day","JP",2008 +"2008-05-05","Children's Day","JP",2008 +"2008-05-06","Substitute Holiday","JP",2008 +"2008-07-21","Marine Day","JP",2008 +"2008-09-15","Respect for the Aged Day","JP",2008 +"2008-09-23","Autumnal Equinox","JP",2008 +"2008-10-13","Physical Education Day","JP",2008 +"2008-11-03","Culture Day","JP",2008 +"2008-11-23","Labor Thanksgiving Day","JP",2008 +"2008-11-24","Substitute Holiday","JP",2008 +"2008-12-23","Emperor's Birthday","JP",2008 +"2009-01-01","New Year's Day","JP",2009 +"2009-01-12","Coming of Age Day","JP",2009 +"2009-02-11","Foundation Day","JP",2009 +"2009-03-20","Vernal Equinox Day","JP",2009 +"2009-04-29","Showa Day","JP",2009 +"2009-05-03","Constitution Day","JP",2009 +"2009-05-04","Greenery Day","JP",2009 +"2009-05-05","Children's Day","JP",2009 +"2009-05-06","Substitute Holiday","JP",2009 +"2009-07-20","Marine Day","JP",2009 +"2009-09-21","Respect for the Aged Day","JP",2009 +"2009-09-22","National Holiday","JP",2009 +"2009-09-23","Autumnal Equinox","JP",2009 +"2009-10-12","Physical Education Day","JP",2009 +"2009-11-03","Culture Day","JP",2009 +"2009-11-23","Labor Thanksgiving Day","JP",2009 +"2009-12-23","Emperor's Birthday","JP",2009 +"2010-01-01","New Year's Day","JP",2010 +"2010-01-11","Coming of Age Day","JP",2010 +"2010-02-11","Foundation Day","JP",2010 +"2010-03-21","Vernal Equinox Day","JP",2010 +"2010-03-22","Substitute Holiday","JP",2010 +"2010-04-29","Showa Day","JP",2010 +"2010-05-03","Constitution Day","JP",2010 +"2010-05-04","Greenery Day","JP",2010 +"2010-05-05","Children's Day","JP",2010 +"2010-07-19","Marine Day","JP",2010 +"2010-09-20","Respect for the Aged Day","JP",2010 +"2010-09-23","Autumnal Equinox","JP",2010 +"2010-10-11","Physical Education Day","JP",2010 +"2010-11-03","Culture Day","JP",2010 +"2010-11-23","Labor Thanksgiving Day","JP",2010 +"2010-12-23","Emperor's Birthday","JP",2010 +"2011-01-01","New Year's Day","JP",2011 +"2011-01-10","Coming of Age Day","JP",2011 +"2011-02-11","Foundation Day","JP",2011 +"2011-03-21","Vernal Equinox Day","JP",2011 +"2011-04-29","Showa Day","JP",2011 +"2011-05-03","Constitution Day","JP",2011 +"2011-05-04","Greenery Day","JP",2011 +"2011-05-05","Children's Day","JP",2011 +"2011-07-18","Marine Day","JP",2011 +"2011-09-19","Respect for the Aged Day","JP",2011 +"2011-09-23","Autumnal Equinox","JP",2011 +"2011-10-10","Physical Education Day","JP",2011 +"2011-11-03","Culture Day","JP",2011 +"2011-11-23","Labor Thanksgiving Day","JP",2011 +"2011-12-23","Emperor's Birthday","JP",2011 +"2012-01-01","New Year's Day","JP",2012 +"2012-01-02","Substitute Holiday","JP",2012 +"2012-01-09","Coming of Age Day","JP",2012 +"2012-02-11","Foundation Day","JP",2012 +"2012-03-20","Vernal Equinox Day","JP",2012 +"2012-04-29","Showa Day","JP",2012 +"2012-04-30","Substitute Holiday","JP",2012 +"2012-05-03","Constitution Day","JP",2012 +"2012-05-04","Greenery Day","JP",2012 +"2012-05-05","Children's Day","JP",2012 +"2012-07-16","Marine Day","JP",2012 +"2012-09-17","Respect for the Aged Day","JP",2012 +"2012-09-22","Autumnal Equinox","JP",2012 +"2012-10-08","Physical Education Day","JP",2012 +"2012-11-03","Culture Day","JP",2012 +"2012-11-23","Labor Thanksgiving Day","JP",2012 +"2012-12-23","Emperor's Birthday","JP",2012 +"2012-12-24","Substitute Holiday","JP",2012 +"2013-01-01","New Year's Day","JP",2013 +"2013-01-14","Coming of Age Day","JP",2013 +"2013-02-11","Foundation Day","JP",2013 +"2013-03-20","Vernal Equinox Day","JP",2013 +"2013-04-29","Showa Day","JP",2013 +"2013-05-03","Constitution Day","JP",2013 +"2013-05-04","Greenery Day","JP",2013 +"2013-05-05","Children's Day","JP",2013 +"2013-05-06","Substitute Holiday","JP",2013 +"2013-07-15","Marine Day","JP",2013 +"2013-09-16","Respect for the Aged Day","JP",2013 +"2013-09-23","Autumnal Equinox","JP",2013 +"2013-10-14","Physical Education Day","JP",2013 +"2013-11-03","Culture Day","JP",2013 +"2013-11-04","Substitute Holiday","JP",2013 +"2013-11-23","Labor Thanksgiving Day","JP",2013 +"2013-12-23","Emperor's Birthday","JP",2013 +"2014-01-01","New Year's Day","JP",2014 +"2014-01-13","Coming of Age Day","JP",2014 +"2014-02-11","Foundation Day","JP",2014 +"2014-03-21","Vernal Equinox Day","JP",2014 +"2014-04-29","Showa Day","JP",2014 +"2014-05-03","Constitution Day","JP",2014 +"2014-05-04","Greenery Day","JP",2014 +"2014-05-05","Children's Day","JP",2014 +"2014-05-06","Substitute Holiday","JP",2014 +"2014-07-21","Marine Day","JP",2014 +"2014-09-15","Respect for the Aged Day","JP",2014 +"2014-09-23","Autumnal Equinox","JP",2014 +"2014-10-13","Physical Education Day","JP",2014 +"2014-11-03","Culture Day","JP",2014 +"2014-11-23","Labor Thanksgiving Day","JP",2014 +"2014-11-24","Substitute Holiday","JP",2014 +"2014-12-23","Emperor's Birthday","JP",2014 +"2015-01-01","New Year's Day","JP",2015 +"2015-01-12","Coming of Age Day","JP",2015 +"2015-02-11","Foundation Day","JP",2015 +"2015-03-21","Vernal Equinox Day","JP",2015 +"2015-04-29","Showa Day","JP",2015 +"2015-05-03","Constitution Day","JP",2015 +"2015-05-04","Greenery Day","JP",2015 +"2015-05-05","Children's Day","JP",2015 +"2015-05-06","Substitute Holiday","JP",2015 +"2015-07-20","Marine Day","JP",2015 +"2015-09-21","Respect for the Aged Day","JP",2015 +"2015-09-22","National Holiday","JP",2015 +"2015-09-23","Autumnal Equinox","JP",2015 +"2015-10-12","Physical Education Day","JP",2015 +"2015-11-03","Culture Day","JP",2015 +"2015-11-23","Labor Thanksgiving Day","JP",2015 +"2015-12-23","Emperor's Birthday","JP",2015 +"2016-01-01","New Year's Day","JP",2016 +"2016-01-11","Coming of Age Day","JP",2016 +"2016-02-11","Foundation Day","JP",2016 +"2016-03-20","Vernal Equinox Day","JP",2016 +"2016-03-21","Substitute Holiday","JP",2016 +"2016-04-29","Showa Day","JP",2016 +"2016-05-03","Constitution Day","JP",2016 +"2016-05-04","Greenery Day","JP",2016 +"2016-05-05","Children's Day","JP",2016 +"2016-07-18","Marine Day","JP",2016 +"2016-08-11","Mountain Day","JP",2016 +"2016-09-19","Respect for the Aged Day","JP",2016 +"2016-09-22","Autumnal Equinox","JP",2016 +"2016-10-10","Physical Education Day","JP",2016 +"2016-11-03","Culture Day","JP",2016 +"2016-11-23","Labor Thanksgiving Day","JP",2016 +"2016-12-23","Emperor's Birthday","JP",2016 +"2017-01-01","New Year's Day","JP",2017 +"2017-01-02","Substitute Holiday","JP",2017 +"2017-01-09","Coming of Age Day","JP",2017 +"2017-02-11","Foundation Day","JP",2017 +"2017-03-20","Vernal Equinox Day","JP",2017 +"2017-04-29","Showa Day","JP",2017 +"2017-05-03","Constitution Day","JP",2017 +"2017-05-04","Greenery Day","JP",2017 +"2017-05-05","Children's Day","JP",2017 +"2017-07-17","Marine Day","JP",2017 +"2017-08-11","Mountain Day","JP",2017 +"2017-09-18","Respect for the Aged Day","JP",2017 +"2017-09-23","Autumnal Equinox","JP",2017 +"2017-10-09","Physical Education Day","JP",2017 +"2017-11-03","Culture Day","JP",2017 +"2017-11-23","Labor Thanksgiving Day","JP",2017 +"2017-12-23","Emperor's Birthday","JP",2017 +"2018-01-01","New Year's Day","JP",2018 +"2018-01-08","Coming of Age Day","JP",2018 +"2018-02-11","Foundation Day","JP",2018 +"2018-02-12","Substitute Holiday","JP",2018 +"2018-03-21","Vernal Equinox Day","JP",2018 +"2018-04-29","Showa Day","JP",2018 +"2018-04-30","Substitute Holiday","JP",2018 +"2018-05-03","Constitution Day","JP",2018 +"2018-05-04","Greenery Day","JP",2018 +"2018-05-05","Children's Day","JP",2018 +"2018-07-16","Marine Day","JP",2018 +"2018-08-11","Mountain Day","JP",2018 +"2018-09-17","Respect for the Aged Day","JP",2018 +"2018-09-23","Autumnal Equinox","JP",2018 +"2018-09-24","Substitute Holiday","JP",2018 +"2018-10-08","Physical Education Day","JP",2018 +"2018-11-03","Culture Day","JP",2018 +"2018-11-23","Labor Thanksgiving Day","JP",2018 +"2018-12-23","Emperor's Birthday","JP",2018 +"2018-12-24","Substitute Holiday","JP",2018 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Day","JP",2020 +"2020-01-13","Coming of Age Day","JP",2020 +"2020-02-11","Foundation Day","JP",2020 +"2020-02-23","Emperor's Birthday","JP",2020 +"2020-02-24","Substitute Holiday","JP",2020 +"2020-03-20","Vernal Equinox Day","JP",2020 +"2020-04-29","Showa Day","JP",2020 +"2020-05-03","Constitution Day","JP",2020 +"2020-05-04","Greenery Day","JP",2020 +"2020-05-05","Children's Day","JP",2020 +"2020-05-06","Substitute Holiday","JP",2020 +"2020-07-23","Marine Day","JP",2020 +"2020-07-24","Sports Day","JP",2020 +"2020-08-10","Mountain Day","JP",2020 +"2020-09-21","Respect for the Aged Day","JP",2020 +"2020-09-22","Autumnal Equinox","JP",2020 +"2020-11-03","Culture Day","JP",2020 +"2020-11-23","Labor Thanksgiving Day","JP",2020 +"2021-01-01","New Year's Day","JP",2021 +"2021-01-11","Coming of Age Day","JP",2021 +"2021-02-11","Foundation Day","JP",2021 +"2021-02-23","Emperor's Birthday","JP",2021 +"2021-03-20","Vernal Equinox Day","JP",2021 +"2021-04-29","Showa Day","JP",2021 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Equinox","JP",2022 +"2022-10-10","Sports Day","JP",2022 +"2022-11-03","Culture Day","JP",2022 +"2022-11-23","Labor Thanksgiving Day","JP",2022 +"2023-01-01","New Year's Day","JP",2023 +"2023-01-02","Substitute Holiday","JP",2023 +"2023-01-09","Coming of Age Day","JP",2023 +"2023-02-11","Foundation Day","JP",2023 +"2023-02-23","Emperor's Birthday","JP",2023 +"2023-03-21","Vernal Equinox Day","JP",2023 +"2023-04-29","Showa Day","JP",2023 +"2023-05-03","Constitution Day","JP",2023 +"2023-05-04","Greenery Day","JP",2023 +"2023-05-05","Children's Day","JP",2023 +"2023-07-17","Marine Day","JP",2023 +"2023-08-11","Mountain Day","JP",2023 +"2023-09-18","Respect for the Aged Day","JP",2023 +"2023-09-23","Autumnal Equinox","JP",2023 +"2023-10-09","Sports Day","JP",2023 +"2023-11-03","Culture Day","JP",2023 +"2023-11-23","Labor Thanksgiving Day","JP",2023 +"2024-01-01","New Year's Day","JP",2024 +"2024-01-08","Coming of Age Day","JP",2024 +"2024-02-11","Foundation Day","JP",2024 +"2024-02-12","Substitute Holiday","JP",2024 +"2024-02-23","Emperor's Birthday","JP",2024 +"2024-03-20","Vernal Equinox Day","JP",2024 +"2024-04-29","Showa Day","JP",2024 +"2024-05-03","Constitution Day","JP",2024 +"2024-05-04","Greenery Day","JP",2024 +"2024-05-05","Children's Day","JP",2024 +"2024-05-06","Substitute Holiday","JP",2024 +"2024-07-15","Marine Day","JP",2024 +"2024-08-11","Mountain Day","JP",2024 +"2024-08-12","Substitute Holiday","JP",2024 +"2024-09-16","Respect for the Aged Day","JP",2024 +"2024-09-22","Autumnal Equinox","JP",2024 +"2024-09-23","Substitute Holiday","JP",2024 +"2024-10-14","Sports Day","JP",2024 +"2024-11-03","Culture Day","JP",2024 +"2024-11-04","Substitute Holiday","JP",2024 +"2024-11-23","Labor Thanksgiving Day","JP",2024 +"2025-01-01","New Year's Day","JP",2025 +"2025-01-13","Coming of Age Day","JP",2025 +"2025-02-11","Foundation Day","JP",2025 +"2025-02-23","Emperor's Birthday","JP",2025 +"2025-02-24","Substitute Holiday","JP",2025 +"2025-03-20","Vernal Equinox Day","JP",2025 +"2025-04-29","Showa Day","JP",2025 +"2025-05-03","Constitution Day","JP",2025 +"2025-05-04","Greenery Day","JP",2025 +"2025-05-05","Children's Day","JP",2025 +"2025-05-06","Substitute Holiday","JP",2025 +"2025-07-21","Marine Day","JP",2025 +"2025-08-11","Mountain Day","JP",2025 +"2025-09-15","Respect for the Aged Day","JP",2025 +"2025-09-23","Autumnal Equinox","JP",2025 +"2025-10-13","Sports Day","JP",2025 +"2025-11-03","Culture Day","JP",2025 +"2025-11-23","Labor Thanksgiving Day","JP",2025 +"2025-11-24","Substitute Holiday","JP",2025 +"2026-01-01","New Year's Day","JP",2026 +"2026-01-12","Coming of Age Day","JP",2026 +"2026-02-11","Foundation Day","JP",2026 +"2026-02-23","Emperor's Birthday","JP",2026 +"2026-03-20","Vernal Equinox Day","JP",2026 +"2026-04-29","Showa Day","JP",2026 +"2026-05-03","Constitution Day","JP",2026 +"2026-05-04","Greenery Day","JP",2026 +"2026-05-05","Children's Day","JP",2026 +"2026-05-06","Substitute Holiday","JP",2026 +"2026-07-20","Marine Day","JP",2026 +"2026-08-11","Mountain Day","JP",2026 +"2026-09-21","Respect for the Aged Day","JP",2026 +"2026-09-22","National Holiday","JP",2026 +"2026-09-23","Autumnal Equinox","JP",2026 +"2026-10-12","Sports Day","JP",2026 +"2026-11-03","Culture Day","JP",2026 +"2026-11-23","Labor Thanksgiving Day","JP",2026 +"2027-01-01","New Year's Day","JP",2027 +"2027-01-11","Coming of Age Day","JP",2027 +"2027-02-11","Foundation Day","JP",2027 +"2027-02-23","Emperor's Birthday","JP",2027 +"2027-03-21","Vernal Equinox Day","JP",2027 +"2027-03-22","Substitute Holiday","JP",2027 +"2027-04-29","Showa Day","JP",2027 +"2027-05-03","Constitution Day","JP",2027 +"2027-05-04","Greenery Day","JP",2027 +"2027-05-05","Children's Day","JP",2027 +"2027-07-19","Marine Day","JP",2027 +"2027-08-11","Mountain Day","JP",2027 +"2027-09-20","Respect for the Aged Day","JP",2027 +"2027-09-23","Autumnal Equinox","JP",2027 +"2027-10-11","Sports Day","JP",2027 +"2027-11-03","Culture Day","JP",2027 +"2027-11-23","Labor Thanksgiving Day","JP",2027 +"2028-01-01","New Year's Day","JP",2028 +"2028-01-10","Coming of Age Day","JP",2028 +"2028-02-11","Foundation Day","JP",2028 +"2028-02-23","Emperor's Birthday","JP",2028 +"2028-03-20","Vernal Equinox Day","JP",2028 +"2028-04-29","Showa Day","JP",2028 +"2028-05-03","Constitution Day","JP",2028 +"2028-05-04","Greenery Day","JP",2028 +"2028-05-05","Children's Day","JP",2028 +"2028-07-17","Marine Day","JP",2028 +"2028-08-11","Mountain Day","JP",2028 +"2028-09-18","Respect for the Aged Day","JP",2028 +"2028-09-22","Autumnal Equinox","JP",2028 +"2028-10-09","Sports Day","JP",2028 +"2028-11-03","Culture Day","JP",2028 +"2028-11-23","Labor Thanksgiving Day","JP",2028 +"2029-01-01","New Year's Day","JP",2029 +"2029-01-08","Coming of Age Day","JP",2029 +"2029-02-11","Foundation Day","JP",2029 +"2029-02-12","Substitute Holiday","JP",2029 +"2029-02-23","Emperor's Birthday","JP",2029 +"2029-03-20","Vernal Equinox Day","JP",2029 +"2029-04-29","Showa Day","JP",2029 +"2029-04-30","Substitute Holiday","JP",2029 +"2029-05-03","Constitution Day","JP",2029 +"2029-05-04","Greenery Day","JP",2029 +"2029-05-05","Children's Day","JP",2029 +"2029-07-16","Marine Day","JP",2029 +"2029-08-11","Mountain Day","JP",2029 +"2029-09-17","Respect for the Aged Day","JP",2029 +"2029-09-23","Autumnal Equinox","JP",2029 +"2029-09-24","Substitute Holiday","JP",2029 +"2029-10-08","Sports Day","JP",2029 +"2029-11-03","Culture Day","JP",2029 +"2029-11-23","Labor Thanksgiving Day","JP",2029 +"2030-01-01","New Year's Day","JP",2030 +"2030-01-14","Coming of Age Day","JP",2030 +"2030-02-11","Foundation Day","JP",2030 +"2030-02-23","Emperor's Birthday","JP",2030 +"2030-03-20","Vernal Equinox Day","JP",2030 +"2030-04-29","Showa Day","JP",2030 +"2030-05-03","Constitution Day","JP",2030 +"2030-05-04","Greenery Day","JP",2030 +"2030-05-05","Children's Day","JP",2030 +"2030-05-06","Substitute Holiday","JP",2030 +"2030-07-15","Marine Day","JP",2030 +"2030-08-11","Mountain Day","JP",2030 +"2030-08-12","Substitute Holiday","JP",2030 +"2030-09-16","Respect for the Aged Day","JP",2030 +"2030-09-23","Autumnal Equinox","JP",2030 +"2030-10-14","Sports Day","JP",2030 +"2030-11-03","Culture Day","JP",2030 +"2030-11-04","Substitute Holiday","JP",2030 +"2030-11-23","Labor Thanksgiving Day","JP",2030 +"2031-01-01","New Year's Day","JP",2031 +"2031-01-13","Coming of Age Day","JP",2031 +"2031-02-11","Foundation Day","JP",2031 +"2031-02-23","Emperor's Birthday","JP",2031 +"2031-02-24","Substitute Holiday","JP",2031 +"2031-03-21","Vernal Equinox Day","JP",2031 +"2031-04-29","Showa Day","JP",2031 +"2031-05-03","Constitution Day","JP",2031 +"2031-05-04","Greenery Day","JP",2031 +"2031-05-05","Children's Day","JP",2031 +"2031-05-06","Substitute Holiday","JP",2031 +"2031-07-21","Marine Day","JP",2031 +"2031-08-11","Mountain Day","JP",2031 +"2031-09-15","Respect for the Aged Day","JP",2031 +"2031-09-23","Autumnal Equinox","JP",2031 +"2031-10-13","Sports Day","JP",2031 +"2031-11-03","Culture Day","JP",2031 +"2031-11-23","Labor Thanksgiving Day","JP",2031 +"2031-11-24","Substitute Holiday","JP",2031 +"2032-01-01","New Year's Day","JP",2032 +"2032-01-12","Coming of Age Day","JP",2032 +"2032-02-11","Foundation Day","JP",2032 +"2032-02-23","Emperor's Birthday","JP",2032 +"2032-03-20","Vernal Equinox Day","JP",2032 +"2032-04-29","Showa Day","JP",2032 +"2032-05-03","Constitution Day","JP",2032 +"2032-05-04","Greenery Day","JP",2032 +"2032-05-05","Children's Day","JP",2032 +"2032-07-19","Marine Day","JP",2032 +"2032-08-11","Mountain Day","JP",2032 +"2032-09-20","Respect for the Aged Day","JP",2032 +"2032-09-21","National Holiday","JP",2032 +"2032-09-22","Autumnal Equinox","JP",2032 +"2032-10-11","Sports Day","JP",2032 +"2032-11-03","Culture Day","JP",2032 +"2032-11-23","Labor Thanksgiving Day","JP",2032 +"2033-01-01","New Year's Day","JP",2033 +"2033-01-10","Coming of Age Day","JP",2033 +"2033-02-11","Foundation Day","JP",2033 +"2033-02-23","Emperor's Birthday","JP",2033 +"2033-03-20","Vernal Equinox Day","JP",2033 +"2033-03-21","Substitute Holiday","JP",2033 +"2033-04-29","Showa Day","JP",2033 +"2033-05-03","Constitution Day","JP",2033 +"2033-05-04","Greenery Day","JP",2033 +"2033-05-05","Children's Day","JP",2033 +"2033-07-18","Marine Day","JP",2033 +"2033-08-11","Mountain Day","JP",2033 +"2033-09-19","Respect for the Aged Day","JP",2033 +"2033-09-23","Autumnal Equinox","JP",2033 +"2033-10-10","Sports Day","JP",2033 +"2033-11-03","Culture Day","JP",2033 +"2033-11-23","Labor Thanksgiving Day","JP",2033 +"2034-01-01","New Year's Day","JP",2034 +"2034-01-02","Substitute Holiday","JP",2034 +"2034-01-09","Coming of Age Day","JP",2034 +"2034-02-11","Foundation Day","JP",2034 +"2034-02-23","Emperor's Birthday","JP",2034 +"2034-03-20","Vernal Equinox Day","JP",2034 +"2034-04-29","Showa Day","JP",2034 +"2034-05-03","Constitution Day","JP",2034 +"2034-05-04","Greenery Day","JP",2034 +"2034-05-05","Children's Day","JP",2034 +"2034-07-17","Marine Day","JP",2034 +"2034-08-11","Mountain Day","JP",2034 +"2034-09-18","Respect for the Aged Day","JP",2034 +"2034-09-23","Autumnal Equinox","JP",2034 +"2034-10-09","Sports Day","JP",2034 +"2034-11-03","Culture Day","JP",2034 +"2034-11-23","Labor Thanksgiving Day","JP",2034 +"2035-01-01","New Year's Day","JP",2035 +"2035-01-08","Coming of Age Day","JP",2035 +"2035-02-11","Foundation Day","JP",2035 +"2035-02-12","Substitute Holiday","JP",2035 +"2035-02-23","Emperor's Birthday","JP",2035 +"2035-03-21","Vernal Equinox Day","JP",2035 +"2035-04-29","Showa Day","JP",2035 +"2035-04-30","Substitute Holiday","JP",2035 +"2035-05-03","Constitution Day","JP",2035 +"2035-05-04","Greenery Day","JP",2035 +"2035-05-05","Children's Day","JP",2035 +"2035-07-16","Marine Day","JP",2035 +"2035-08-11","Mountain Day","JP",2035 +"2035-09-17","Respect for the Aged Day","JP",2035 +"2035-09-23","Autumnal Equinox","JP",2035 +"2035-09-24","Substitute Holiday","JP",2035 +"2035-10-08","Sports Day","JP",2035 +"2035-11-03","Culture Day","JP",2035 +"2035-11-23","Labor Thanksgiving Day","JP",2035 +"2036-01-01","New Year's Day","JP",2036 +"2036-01-14","Coming of Age Day","JP",2036 +"2036-02-11","Foundation Day","JP",2036 +"2036-02-23","Emperor's Birthday","JP",2036 +"2036-03-20","Vernal Equinox Day","JP",2036 +"2036-04-29","Showa Day","JP",2036 +"2036-05-03","Constitution Day","JP",2036 +"2036-05-04","Greenery Day","JP",2036 +"2036-05-05","Children's Day","JP",2036 +"2036-05-06","Substitute Holiday","JP",2036 +"2036-07-21","Marine Day","JP",2036 +"2036-08-11","Mountain Day","JP",2036 +"2036-09-15","Respect for the Aged Day","JP",2036 +"2036-09-22","Autumnal Equinox","JP",2036 +"2036-10-13","Sports Day","JP",2036 +"2036-11-03","Culture Day","JP",2036 +"2036-11-23","Labor Thanksgiving Day","JP",2036 +"2036-11-24","Substitute Holiday","JP",2036 +"2037-01-01","New Year's Day","JP",2037 +"2037-01-12","Coming of Age Day","JP",2037 +"2037-02-11","Foundation Day","JP",2037 +"2037-02-23","Emperor's Birthday","JP",2037 +"2037-03-20","Vernal Equinox Day","JP",2037 +"2037-04-29","Showa Day","JP",2037 +"2037-05-03","Constitution Day","JP",2037 +"2037-05-04","Greenery Day","JP",2037 +"2037-05-05","Children's Day","JP",2037 +"2037-05-06","Substitute Holiday","JP",2037 +"2037-07-20","Marine Day","JP",2037 +"2037-08-11","Mountain Day","JP",2037 +"2037-09-21","Respect for the Aged Day","JP",2037 +"2037-09-22","National Holiday","JP",2037 +"2037-09-23","Autumnal Equinox","JP",2037 +"2037-10-12","Sports Day","JP",2037 +"2037-11-03","Culture Day","JP",2037 +"2037-11-23","Labor Thanksgiving Day","JP",2037 +"2038-01-01","New Year's Day","JP",2038 +"2038-01-11","Coming of Age Day","JP",2038 +"2038-02-11","Foundation Day","JP",2038 +"2038-02-23","Emperor's Birthday","JP",2038 +"2038-03-20","Vernal Equinox Day","JP",2038 +"2038-04-29","Showa Day","JP",2038 +"2038-05-03","Constitution Day","JP",2038 +"2038-05-04","Greenery Day","JP",2038 +"2038-05-05","Children's Day","JP",2038 +"2038-07-19","Marine Day","JP",2038 +"2038-08-11","Mountain Day","JP",2038 +"2038-09-20","Respect for the Aged Day","JP",2038 +"2038-09-23","Autumnal Equinox","JP",2038 +"2038-10-11","Sports Day","JP",2038 +"2038-11-03","Culture Day","JP",2038 +"2038-11-23","Labor Thanksgiving Day","JP",2038 +"2039-01-01","New Year's Day","JP",2039 +"2039-01-10","Coming of Age Day","JP",2039 +"2039-02-11","Foundation Day","JP",2039 +"2039-02-23","Emperor's Birthday","JP",2039 +"2039-03-21","Vernal Equinox Day","JP",2039 +"2039-04-29","Showa Day","JP",2039 +"2039-05-03","Constitution Day","JP",2039 +"2039-05-04","Greenery Day","JP",2039 +"2039-05-05","Children's Day","JP",2039 +"2039-07-18","Marine Day","JP",2039 +"2039-08-11","Mountain Day","JP",2039 +"2039-09-19","Respect for the Aged Day","JP",2039 +"2039-09-23","Autumnal Equinox","JP",2039 +"2039-10-10","Sports Day","JP",2039 +"2039-11-03","Culture Day","JP",2039 +"2039-11-23","Labor Thanksgiving Day","JP",2039 +"2040-01-01","New Year's Day","JP",2040 +"2040-01-02","Substitute Holiday","JP",2040 +"2040-01-09","Coming of Age Day","JP",2040 +"2040-02-11","Foundation Day","JP",2040 +"2040-02-23","Emperor's Birthday","JP",2040 +"2040-03-20","Vernal Equinox Day","JP",2040 +"2040-04-29","Showa Day","JP",2040 +"2040-04-30","Substitute Holiday","JP",2040 +"2040-05-03","Constitution Day","JP",2040 +"2040-05-04","Greenery Day","JP",2040 +"2040-05-05","Children's Day","JP",2040 +"2040-07-16","Marine Day","JP",2040 +"2040-08-11","Mountain Day","JP",2040 +"2040-09-17","Respect for the Aged Day","JP",2040 +"2040-09-22","Autumnal Equinox","JP",2040 +"2040-10-08","Sports Day","JP",2040 +"2040-11-03","Culture Day","JP",2040 +"2040-11-23","Labor Thanksgiving Day","JP",2040 +"2041-01-01","New Year's Day","JP",2041 +"2041-01-14","Coming of Age Day","JP",2041 +"2041-02-11","Foundation Day","JP",2041 +"2041-02-23","Emperor's Birthday","JP",2041 +"2041-03-20","Vernal Equinox Day","JP",2041 +"2041-04-29","Showa Day","JP",2041 +"2041-05-03","Constitution Day","JP",2041 +"2041-05-04","Greenery Day","JP",2041 +"2041-05-05","Children's Day","JP",2041 +"2041-05-06","Substitute Holiday","JP",2041 +"2041-07-15","Marine Day","JP",2041 +"2041-08-11","Mountain Day","JP",2041 +"2041-08-12","Substitute Holiday","JP",2041 +"2041-09-16","Respect for the Aged Day","JP",2041 +"2041-09-23","Autumnal Equinox","JP",2041 +"2041-10-14","Sports Day","JP",2041 +"2041-11-03","Culture Day","JP",2041 +"2041-11-04","Substitute Holiday","JP",2041 +"2041-11-23","Labor Thanksgiving Day","JP",2041 +"2042-01-01","New Year's Day","JP",2042 +"2042-01-13","Coming of Age Day","JP",2042 +"2042-02-11","Foundation Day","JP",2042 +"2042-02-23","Emperor's Birthday","JP",2042 +"2042-02-24","Substitute Holiday","JP",2042 +"2042-03-20","Vernal Equinox Day","JP",2042 +"2042-04-29","Showa Day","JP",2042 +"2042-05-03","Constitution Day","JP",2042 +"2042-05-04","Greenery Day","JP",2042 +"2042-05-05","Children's Day","JP",2042 +"2042-05-06","Substitute Holiday","JP",2042 +"2042-07-21","Marine Day","JP",2042 +"2042-08-11","Mountain Day","JP",2042 +"2042-09-15","Respect for the Aged Day","JP",2042 +"2042-09-23","Autumnal Equinox","JP",2042 +"2042-10-13","Sports Day","JP",2042 +"2042-11-03","Culture Day","JP",2042 +"2042-11-23","Labor Thanksgiving Day","JP",2042 +"2042-11-24","Substitute Holiday","JP",2042 +"2043-01-01","New Year's Day","JP",2043 +"2043-01-12","Coming of Age Day","JP",2043 +"2043-02-11","Foundation Day","JP",2043 +"2043-02-23","Emperor's Birthday","JP",2043 +"2043-03-21","Vernal Equinox Day","JP",2043 +"2043-04-29","Showa Day","JP",2043 +"2043-05-03","Constitution Day","JP",2043 +"2043-05-04","Greenery Day","JP",2043 +"2043-05-05","Children's Day","JP",2043 +"2043-05-06","Substitute Holiday","JP",2043 +"2043-07-20","Marine Day","JP",2043 +"2043-08-11","Mountain Day","JP",2043 +"2043-09-21","Respect for the Aged Day","JP",2043 +"2043-09-22","National Holiday","JP",2043 +"2043-09-23","Autumnal Equinox","JP",2043 +"2043-10-12","Sports Day","JP",2043 +"2043-11-03","Culture Day","JP",2043 +"2043-11-23","Labor Thanksgiving Day","JP",2043 +"2044-01-01","New Year's Day","JP",2044 +"2044-01-11","Coming of Age Day","JP",2044 +"2044-02-11","Foundation Day","JP",2044 +"2044-02-23","Emperor's Birthday","JP",2044 +"2044-03-20","Vernal Equinox Day","JP",2044 +"2044-03-21","Substitute Holiday","JP",2044 +"2044-04-29","Showa Day","JP",2044 +"2044-05-03","Constitution Day","JP",2044 +"2044-05-04","Greenery Day","JP",2044 +"2044-05-05","Children's Day","JP",2044 +"2044-07-18","Marine Day","JP",2044 +"2044-08-11","Mountain Day","JP",2044 +"2044-09-19","Respect for the Aged Day","JP",2044 +"2044-09-22","Autumnal Equinox","JP",2044 +"2044-10-10","Sports Day","JP",2044 +"2044-11-03","Culture Day","JP",2044 +"2044-11-23","Labor Thanksgiving Day","JP",2044 +"1995-01-01","New Year's Day","KE",1995 +"1995-01-02","New Year's Day (Observed)","KE",1995 +"1995-04-14","Good Friday","KE",1995 +"1995-04-17","Easter Monday","KE",1995 +"1995-05-01","Labour Day","KE",1995 +"1995-10-20","Kenyatta Day","KE",1995 +"1995-12-12","Jamhuri Day","KE",1995 +"1995-12-25","Christmas Day","KE",1995 +"1995-12-26","Boxing Day","KE",1995 +"1996-01-01","New Year's Day","KE",1996 +"1996-04-05","Good Friday","KE",1996 +"1996-04-08","Easter Monday","KE",1996 +"1996-05-01","Labour Day","KE",1996 +"1996-10-20","Kenyatta Day","KE",1996 +"1996-10-21","Kenyatta Day (Observed)","KE",1996 +"1996-12-12","Jamhuri Day","KE",1996 +"1996-12-25","Christmas Day","KE",1996 +"1996-12-26","Boxing Day","KE",1996 +"1997-01-01","New Year's Day","KE",1997 +"1997-03-28","Good Friday","KE",1997 +"1997-03-31","Easter Monday","KE",1997 +"1997-05-01","Labour Day","KE",1997 +"1997-10-20","Kenyatta Day","KE",1997 +"1997-12-12","Jamhuri Day","KE",1997 +"1997-12-25","Christmas Day","KE",1997 +"1997-12-26","Boxing Day","KE",1997 +"1998-01-01","New Year's Day","KE",1998 +"1998-04-10","Good Friday","KE",1998 +"1998-04-13","Easter Monday","KE",1998 +"1998-05-01","Labour Day","KE",1998 +"1998-10-20","Kenyatta Day","KE",1998 +"1998-12-12","Jamhuri Day","KE",1998 +"1998-12-25","Christmas Day","KE",1998 +"1998-12-26","Boxing Day","KE",1998 +"1999-01-01","New Year's Day","KE",1999 +"1999-04-02","Good Friday","KE",1999 +"1999-04-05","Easter Monday","KE",1999 +"1999-05-01","Labour Day","KE",1999 +"1999-10-20","Kenyatta Day","KE",1999 +"1999-12-12","Jamhuri Day","KE",1999 +"1999-12-13","Jamhuri Day (Observed)","KE",1999 +"1999-12-25","Christmas Day","KE",1999 +"1999-12-26","Boxing Day","KE",1999 +"1999-12-27","Boxing Day (Observed)","KE",1999 +"2000-01-01","New Year's Day","KE",2000 +"2000-04-21","Good Friday","KE",2000 +"2000-04-24","Easter Monday","KE",2000 +"2000-05-01","Labour Day","KE",2000 +"2000-10-20","Kenyatta Day","KE",2000 +"2000-12-12","Jamhuri Day","KE",2000 +"2000-12-25","Christmas Day","KE",2000 +"2000-12-26","Boxing Day","KE",2000 +"2001-01-01","New Year's Day","KE",2001 +"2001-04-13","Good Friday","KE",2001 +"2001-04-16","Easter Monday","KE",2001 +"2001-05-01","Labour Day","KE",2001 +"2001-10-20","Kenyatta Day","KE",2001 +"2001-12-12","Jamhuri Day","KE",2001 +"2001-12-25","Christmas Day","KE",2001 +"2001-12-26","Boxing Day","KE",2001 +"2002-01-01","New Year's Day","KE",2002 +"2002-03-29","Good Friday","KE",2002 +"2002-04-01","Easter Monday","KE",2002 +"2002-05-01","Labour Day","KE",2002 +"2002-10-10","Moi Day","KE",2002 +"2002-10-20","Kenyatta Day","KE",2002 +"2002-10-21","Kenyatta Day (Observed)","KE",2002 +"2002-12-12","Jamhuri Day","KE",2002 +"2002-12-25","Christmas Day","KE",2002 +"2002-12-26","Boxing Day","KE",2002 +"2003-01-01","New Year's Day","KE",2003 +"2003-04-18","Good Friday","KE",2003 +"2003-04-21","Easter Monday","KE",2003 +"2003-05-01","Labour Day","KE",2003 +"2003-10-10","Moi Day","KE",2003 +"2003-10-20","Kenyatta Day","KE",2003 +"2003-12-12","Jamhuri Day","KE",2003 +"2003-12-25","Christmas Day","KE",2003 +"2003-12-26","Boxing Day","KE",2003 +"2004-01-01","New Year's Day","KE",2004 +"2004-04-09","Good Friday","KE",2004 +"2004-04-12","Easter Monday","KE",2004 +"2004-05-01","Labour Day","KE",2004 +"2004-10-10","Moi Day","KE",2004 +"2004-10-11","Moi Day (Observed)","KE",2004 +"2004-10-20","Kenyatta Day","KE",2004 +"2004-12-12","Jamhuri Day","KE",2004 +"2004-12-13","Jamhuri Day (Observed)","KE",2004 +"2004-12-25","Christmas Day","KE",2004 +"2004-12-26","Boxing Day","KE",2004 +"2004-12-27","Boxing Day (Observed)","KE",2004 +"2005-01-01","New Year's Day","KE",2005 +"2005-03-25","Good Friday","KE",2005 +"2005-03-28","Easter Monday","KE",2005 +"2005-05-01","Labour Day","KE",2005 +"2005-05-02","Labour Day (Observed)","KE",2005 +"2005-10-10","Moi Day","KE",2005 +"2005-10-20","Kenyatta Day","KE",2005 +"2005-12-12","Jamhuri Day","KE",2005 +"2005-12-25","Christmas Day","KE",2005 +"2005-12-26","Boxing Day","KE",2005 +"2005-12-27","Christmas Day (Observed)","KE",2005 +"2006-01-01","New Year's Day","KE",2006 +"2006-01-02","New Year's Day (Observed)","KE",2006 +"2006-04-14","Good Friday","KE",2006 +"2006-04-17","Easter Monday","KE",2006 +"2006-05-01","Labour Day","KE",2006 +"2006-10-10","Moi Day","KE",2006 +"2006-10-20","Kenyatta Day","KE",2006 +"2006-12-12","Jamhuri Day","KE",2006 +"2006-12-25","Christmas Day","KE",2006 +"2006-12-26","Boxing Day","KE",2006 +"2007-01-01","New Year's Day","KE",2007 +"2007-04-06","Good Friday","KE",2007 +"2007-04-09","Easter Monday","KE",2007 +"2007-05-01","Labour Day","KE",2007 +"2007-10-10","Moi Day","KE",2007 +"2007-10-20","Kenyatta Day","KE",2007 +"2007-12-12","Jamhuri Day","KE",2007 +"2007-12-25","Christmas Day","KE",2007 +"2007-12-26","Boxing Day","KE",2007 +"2008-01-01","New Year's Day","KE",2008 +"2008-03-21","Good Friday","KE",2008 +"2008-03-24","Easter Monday","KE",2008 +"2008-05-01","Labour Day","KE",2008 +"2008-10-10","Moi Day","KE",2008 +"2008-10-20","Kenyatta Day","KE",2008 +"2008-12-12","Jamhuri Day","KE",2008 +"2008-12-25","Christmas Day","KE",2008 +"2008-12-26","Boxing Day","KE",2008 +"2009-01-01","New Year's Day","KE",2009 +"2009-04-10","Good Friday","KE",2009 +"2009-04-13","Easter Monday","KE",2009 +"2009-05-01","Labour Day","KE",2009 +"2009-10-10","Moi Day","KE",2009 +"2009-10-20","Kenyatta Day","KE",2009 +"2009-12-12","Jamhuri Day","KE",2009 +"2009-12-25","Christmas Day","KE",2009 +"2009-12-26","Boxing Day","KE",2009 +"2010-01-01","New Year's Day","KE",2010 +"2010-04-02","Good Friday","KE",2010 +"2010-04-05","Easter Monday","KE",2010 +"2010-05-01","Labour Day","KE",2010 +"2010-06-01","Madaraka Day","KE",2010 +"2010-10-20","Mashujaa Day","KE",2010 +"2010-12-12","Jamhuri Day","KE",2010 +"2010-12-13","Jamhuri Day (Observed)","KE",2010 +"2010-12-25","Christmas Day","KE",2010 +"2010-12-26","Boxing Day","KE",2010 +"2010-12-27","Boxing Day (Observed)","KE",2010 +"2011-01-01","New Year's Day","KE",2011 +"2011-04-22","Good Friday","KE",2011 +"2011-04-25","Easter Monday","KE",2011 +"2011-05-01","Labour Day","KE",2011 +"2011-05-02","Labour Day (Observed)","KE",2011 +"2011-06-01","Madaraka Day","KE",2011 +"2011-10-20","Mashujaa Day","KE",2011 +"2011-12-12","Jamhuri Day","KE",2011 +"2011-12-25","Christmas Day","KE",2011 +"2011-12-26","Boxing Day","KE",2011 +"2011-12-27","Christmas Day (Observed)","KE",2011 +"2012-01-01","New Year's Day","KE",2012 +"2012-01-02","New Year's Day (Observed)","KE",2012 +"2012-04-06","Good Friday","KE",2012 +"2012-04-09","Easter Monday","KE",2012 +"2012-05-01","Labour Day","KE",2012 +"2012-06-01","Madaraka Day","KE",2012 +"2012-10-20","Mashujaa Day","KE",2012 +"2012-12-12","Jamhuri Day","KE",2012 +"2012-12-25","Christmas Day","KE",2012 +"2012-12-26","Boxing Day","KE",2012 +"2013-01-01","New Year's Day","KE",2013 +"2013-03-29","Good Friday","KE",2013 +"2013-04-01","Easter Monday","KE",2013 +"2013-05-01","Labour Day","KE",2013 +"2013-06-01","Madaraka Day","KE",2013 +"2013-10-20","Mashujaa Day","KE",2013 +"2013-10-21","Mashujaa Day (Observed)","KE",2013 +"2013-12-12","Jamhuri Day","KE",2013 +"2013-12-25","Christmas Day","KE",2013 +"2013-12-26","Boxing Day","KE",2013 +"2014-01-01","New Year's Day","KE",2014 +"2014-04-18","Good Friday","KE",2014 +"2014-04-21","Easter Monday","KE",2014 +"2014-05-01","Labour Day","KE",2014 +"2014-06-01","Madaraka Day","KE",2014 +"2014-06-02","Madaraka Day (Observed)","KE",2014 +"2014-10-20","Mashujaa Day","KE",2014 +"2014-12-12","Jamhuri Day","KE",2014 +"2014-12-25","Christmas Day","KE",2014 +"2014-12-26","Boxing Day","KE",2014 +"2015-01-01","New Year's Day","KE",2015 +"2015-04-03","Good Friday","KE",2015 +"2015-04-06","Easter Monday","KE",2015 +"2015-05-01","Labour Day","KE",2015 +"2015-06-01","Madaraka Day","KE",2015 +"2015-10-20","Mashujaa Day","KE",2015 +"2015-12-12","Jamhuri Day","KE",2015 +"2015-12-25","Christmas Day","KE",2015 +"2015-12-26","Boxing Day","KE",2015 +"2016-01-01","New Year's Day","KE",2016 +"2016-03-25","Good Friday","KE",2016 +"2016-03-28","Easter Monday","KE",2016 +"2016-05-01","Labour Day","KE",2016 +"2016-05-02","Labour Day (Observed)","KE",2016 +"2016-06-01","Madaraka Day","KE",2016 +"2016-10-20","Mashujaa Day","KE",2016 +"2016-12-12","Jamhuri Day","KE",2016 +"2016-12-25","Christmas Day","KE",2016 +"2016-12-26","Boxing Day","KE",2016 +"2016-12-27","Christmas Day (Observed)","KE",2016 +"2017-01-01","New Year's Day","KE",2017 +"2017-01-02","New Year's Day (Observed)","KE",2017 +"2017-04-14","Good Friday","KE",2017 +"2017-04-17","Easter Monday","KE",2017 +"2017-05-01","Labour Day","KE",2017 +"2017-06-01","Madaraka Day","KE",2017 +"2017-10-20","Mashujaa Day","KE",2017 +"2017-12-12","Jamhuri Day","KE",2017 +"2017-12-25","Christmas Day","KE",2017 +"2017-12-26","Boxing Day","KE",2017 +"2018-01-01","New Year's Day","KE",2018 +"2018-03-30","Good Friday","KE",2018 +"2018-04-02","Easter Monday","KE",2018 +"2018-05-01","Labour Day","KE",2018 +"2018-06-01","Madaraka Day","KE",2018 +"2018-10-10","Moi Day","KE",2018 +"2018-10-20","Mashujaa Day","KE",2018 +"2018-12-12","Jamhuri Day","KE",2018 +"2018-12-25","Christmas Day","KE",2018 +"2018-12-26","Boxing Day","KE",2018 +"2019-01-01","New Year's Day","KE",2019 +"2019-04-19","Good Friday","KE",2019 +"2019-04-22","Easter Monday","KE",2019 +"2019-05-01","Labour Day","KE",2019 +"2019-06-01","Madaraka Day","KE",2019 +"2019-10-10","Moi Day","KE",2019 +"2019-10-20","Mashujaa Day","KE",2019 +"2019-10-21","Mashujaa Day (Observed)","KE",2019 +"2019-12-12","Jamhuri Day","KE",2019 +"2019-12-25","Christmas Day","KE",2019 +"2019-12-26","Boxing Day","KE",2019 +"2020-01-01","New Year's Day","KE",2020 +"2020-02-11","President Moi Celebration of Life Day","KE",2020 +"2020-04-10","Good Friday","KE",2020 +"2020-04-13","Easter Monday","KE",2020 +"2020-05-01","Labour Day","KE",2020 +"2020-06-01","Madaraka Day","KE",2020 +"2020-10-10","Moi Day","KE",2020 +"2020-10-20","Mashujaa Day","KE",2020 +"2020-12-12","Jamhuri Day","KE",2020 +"2020-12-25","Christmas Day","KE",2020 +"2020-12-26","Boxing Day","KE",2020 +"2021-01-01","New Year's Day","KE",2021 +"2021-04-02","Good Friday","KE",2021 +"2021-04-05","Easter Monday","KE",2021 +"2021-05-01","Labour Day","KE",2021 +"2021-06-01","Madaraka Day","KE",2021 +"2021-10-10","Utamaduni Day","KE",2021 +"2021-10-11","Utamaduni Day (Observed)","KE",2021 +"2021-10-20","Mashujaa Day","KE",2021 +"2021-12-12","Jamhuri Day","KE",2021 +"2021-12-13","Jamhuri Day (Observed)","KE",2021 +"2021-12-25","Christmas Day","KE",2021 +"2021-12-26","Boxing Day","KE",2021 +"2021-12-27","Boxing Day (Observed)","KE",2021 +"2022-01-01","New Year's Day","KE",2022 +"2022-04-15","Good Friday","KE",2022 +"2022-04-18","Easter Monday","KE",2022 +"2022-04-29","State Funeral for Former President Mwai Kibaki","KE",2022 +"2022-05-01","Labour Day","KE",2022 +"2022-05-02","Labour Day (Observed)","KE",2022 +"2022-06-01","Madaraka Day","KE",2022 +"2022-08-09","Election Day","KE",2022 +"2022-09-10","Day of Mourning for Queen Elizabeth II","KE",2022 +"2022-09-11","Day of Mourning for Queen Elizabeth II","KE",2022 +"2022-09-12","Day of Mourning for Queen Elizabeth II","KE",2022 +"2022-09-13","Inauguration Day","KE",2022 +"2022-10-10","Utamaduni Day","KE",2022 +"2022-10-20","Mashujaa Day","KE",2022 +"2022-12-12","Jamhuri Day","KE",2022 +"2022-12-25","Christmas Day","KE",2022 +"2022-12-26","Boxing Day","KE",2022 +"2022-12-27","Christmas Day (Observed)","KE",2022 +"2023-01-01","New Year's Day","KE",2023 +"2023-01-02","New Year's Day (Observed)","KE",2023 +"2023-04-07","Good Friday","KE",2023 +"2023-04-10","Easter Monday","KE",2023 +"2023-05-01","Labour Day","KE",2023 +"2023-06-01","Madaraka Day","KE",2023 +"2023-10-10","Utamaduni Day","KE",2023 +"2023-10-20","Mashujaa Day","KE",2023 +"2023-12-12","Jamhuri Day","KE",2023 +"2023-12-25","Christmas Day","KE",2023 +"2023-12-26","Boxing Day","KE",2023 +"2024-01-01","New Year's Day","KE",2024 +"2024-03-29","Good Friday","KE",2024 +"2024-04-01","Easter Monday","KE",2024 +"2024-05-01","Labour Day","KE",2024 +"2024-06-01","Madaraka Day","KE",2024 +"2024-10-10","Utamaduni Day","KE",2024 +"2024-10-20","Mashujaa Day","KE",2024 +"2024-10-21","Mashujaa Day (Observed)","KE",2024 +"2024-12-12","Jamhuri Day","KE",2024 +"2024-12-25","Christmas Day","KE",2024 +"2024-12-26","Boxing Day","KE",2024 +"2025-01-01","New Year's Day","KE",2025 +"2025-04-18","Good Friday","KE",2025 +"2025-04-21","Easter Monday","KE",2025 +"2025-05-01","Labour Day","KE",2025 +"2025-06-01","Madaraka Day","KE",2025 +"2025-06-02","Madaraka Day (Observed)","KE",2025 +"2025-10-10","Utamaduni Day","KE",2025 +"2025-10-20","Mashujaa Day","KE",2025 +"2025-12-12","Jamhuri Day","KE",2025 +"2025-12-25","Christmas Day","KE",2025 +"2025-12-26","Boxing Day","KE",2025 +"2026-01-01","New Year's Day","KE",2026 +"2026-04-03","Good Friday","KE",2026 +"2026-04-06","Easter Monday","KE",2026 +"2026-05-01","Labour Day","KE",2026 +"2026-06-01","Madaraka Day","KE",2026 +"2026-10-10","Utamaduni Day","KE",2026 +"2026-10-20","Mashujaa Day","KE",2026 +"2026-12-12","Jamhuri Day","KE",2026 +"2026-12-25","Christmas Day","KE",2026 +"2026-12-26","Boxing Day","KE",2026 +"2027-01-01","New Year's Day","KE",2027 +"2027-03-26","Good Friday","KE",2027 +"2027-03-29","Easter Monday","KE",2027 +"2027-05-01","Labour Day","KE",2027 +"2027-06-01","Madaraka Day","KE",2027 +"2027-10-10","Utamaduni Day","KE",2027 +"2027-10-11","Utamaduni Day (Observed)","KE",2027 +"2027-10-20","Mashujaa Day","KE",2027 +"2027-12-12","Jamhuri Day","KE",2027 +"2027-12-13","Jamhuri Day (Observed)","KE",2027 +"2027-12-25","Christmas Day","KE",2027 +"2027-12-26","Boxing Day","KE",2027 +"2027-12-27","Boxing Day (Observed)","KE",2027 +"2028-01-01","New Year's Day","KE",2028 +"2028-04-14","Good Friday","KE",2028 +"2028-04-17","Easter Monday","KE",2028 +"2028-05-01","Labour Day","KE",2028 +"2028-06-01","Madaraka Day","KE",2028 +"2028-10-10","Utamaduni Day","KE",2028 +"2028-10-20","Mashujaa Day","KE",2028 +"2028-12-12","Jamhuri Day","KE",2028 +"2028-12-25","Christmas Day","KE",2028 +"2028-12-26","Boxing Day","KE",2028 +"2029-01-01","New Year's Day","KE",2029 +"2029-03-30","Good Friday","KE",2029 +"2029-04-02","Easter Monday","KE",2029 +"2029-05-01","Labour Day","KE",2029 +"2029-06-01","Madaraka Day","KE",2029 +"2029-10-10","Utamaduni Day","KE",2029 +"2029-10-20","Mashujaa Day","KE",2029 +"2029-12-12","Jamhuri Day","KE",2029 +"2029-12-25","Christmas Day","KE",2029 +"2029-12-26","Boxing Day","KE",2029 +"2030-01-01","New Year's Day","KE",2030 +"2030-04-19","Good Friday","KE",2030 +"2030-04-22","Easter Monday","KE",2030 +"2030-05-01","Labour Day","KE",2030 +"2030-06-01","Madaraka Day","KE",2030 +"2030-10-10","Utamaduni Day","KE",2030 +"2030-10-20","Mashujaa Day","KE",2030 +"2030-10-21","Mashujaa Day (Observed)","KE",2030 +"2030-12-12","Jamhuri Day","KE",2030 +"2030-12-25","Christmas Day","KE",2030 +"2030-12-26","Boxing Day","KE",2030 +"2031-01-01","New Year's Day","KE",2031 +"2031-04-11","Good Friday","KE",2031 +"2031-04-14","Easter Monday","KE",2031 +"2031-05-01","Labour Day","KE",2031 +"2031-06-01","Madaraka Day","KE",2031 +"2031-06-02","Madaraka Day (Observed)","KE",2031 +"2031-10-10","Utamaduni Day","KE",2031 +"2031-10-20","Mashujaa Day","KE",2031 +"2031-12-12","Jamhuri Day","KE",2031 +"2031-12-25","Christmas Day","KE",2031 +"2031-12-26","Boxing Day","KE",2031 +"2032-01-01","New Year's Day","KE",2032 +"2032-03-26","Good Friday","KE",2032 +"2032-03-29","Easter Monday","KE",2032 +"2032-05-01","Labour Day","KE",2032 +"2032-06-01","Madaraka Day","KE",2032 +"2032-10-10","Utamaduni Day","KE",2032 +"2032-10-11","Utamaduni Day (Observed)","KE",2032 +"2032-10-20","Mashujaa Day","KE",2032 +"2032-12-12","Jamhuri Day","KE",2032 +"2032-12-13","Jamhuri Day (Observed)","KE",2032 +"2032-12-25","Christmas Day","KE",2032 +"2032-12-26","Boxing Day","KE",2032 +"2032-12-27","Boxing Day (Observed)","KE",2032 +"2033-01-01","New Year's Day","KE",2033 +"2033-04-15","Good Friday","KE",2033 +"2033-04-18","Easter Monday","KE",2033 +"2033-05-01","Labour Day","KE",2033 +"2033-05-02","Labour Day (Observed)","KE",2033 +"2033-06-01","Madaraka Day","KE",2033 +"2033-10-10","Utamaduni Day","KE",2033 +"2033-10-20","Mashujaa Day","KE",2033 +"2033-12-12","Jamhuri Day","KE",2033 +"2033-12-25","Christmas Day","KE",2033 +"2033-12-26","Boxing Day","KE",2033 +"2033-12-27","Christmas Day (Observed)","KE",2033 +"2034-01-01","New Year's Day","KE",2034 +"2034-01-02","New Year's Day (Observed)","KE",2034 +"2034-04-07","Good Friday","KE",2034 +"2034-04-10","Easter Monday","KE",2034 +"2034-05-01","Labour Day","KE",2034 +"2034-06-01","Madaraka Day","KE",2034 +"2034-10-10","Utamaduni Day","KE",2034 +"2034-10-20","Mashujaa Day","KE",2034 +"2034-12-12","Jamhuri Day","KE",2034 +"2034-12-25","Christmas Day","KE",2034 +"2034-12-26","Boxing Day","KE",2034 +"2035-01-01","New Year's Day","KE",2035 +"2035-03-23","Good Friday","KE",2035 +"2035-03-26","Easter Monday","KE",2035 +"2035-05-01","Labour Day","KE",2035 +"2035-06-01","Madaraka Day","KE",2035 +"2035-10-10","Utamaduni Day","KE",2035 +"2035-10-20","Mashujaa Day","KE",2035 +"2035-12-12","Jamhuri Day","KE",2035 +"2035-12-25","Christmas Day","KE",2035 +"2035-12-26","Boxing Day","KE",2035 +"2036-01-01","New Year's Day","KE",2036 +"2036-04-11","Good Friday","KE",2036 +"2036-04-14","Easter Monday","KE",2036 +"2036-05-01","Labour Day","KE",2036 +"2036-06-01","Madaraka Day","KE",2036 +"2036-06-02","Madaraka Day (Observed)","KE",2036 +"2036-10-10","Utamaduni Day","KE",2036 +"2036-10-20","Mashujaa Day","KE",2036 +"2036-12-12","Jamhuri Day","KE",2036 +"2036-12-25","Christmas Day","KE",2036 +"2036-12-26","Boxing Day","KE",2036 +"2037-01-01","New Year's Day","KE",2037 +"2037-04-03","Good Friday","KE",2037 +"2037-04-06","Easter Monday","KE",2037 +"2037-05-01","Labour Day","KE",2037 +"2037-06-01","Madaraka Day","KE",2037 +"2037-10-10","Utamaduni Day","KE",2037 +"2037-10-20","Mashujaa Day","KE",2037 +"2037-12-12","Jamhuri Day","KE",2037 +"2037-12-25","Christmas Day","KE",2037 +"2037-12-26","Boxing Day","KE",2037 +"2038-01-01","New Year's Day","KE",2038 +"2038-04-23","Good Friday","KE",2038 +"2038-04-26","Easter Monday","KE",2038 +"2038-05-01","Labour Day","KE",2038 +"2038-06-01","Madaraka Day","KE",2038 +"2038-10-10","Utamaduni Day","KE",2038 +"2038-10-11","Utamaduni Day (Observed)","KE",2038 +"2038-10-20","Mashujaa Day","KE",2038 +"2038-12-12","Jamhuri Day","KE",2038 +"2038-12-13","Jamhuri Day (Observed)","KE",2038 +"2038-12-25","Christmas Day","KE",2038 +"2038-12-26","Boxing Day","KE",2038 +"2038-12-27","Boxing Day (Observed)","KE",2038 +"2039-01-01","New Year's Day","KE",2039 +"2039-04-08","Good Friday","KE",2039 +"2039-04-11","Easter Monday","KE",2039 +"2039-05-01","Labour Day","KE",2039 +"2039-05-02","Labour Day (Observed)","KE",2039 +"2039-06-01","Madaraka Day","KE",2039 +"2039-10-10","Utamaduni Day","KE",2039 +"2039-10-20","Mashujaa Day","KE",2039 +"2039-12-12","Jamhuri Day","KE",2039 +"2039-12-25","Christmas Day","KE",2039 +"2039-12-26","Boxing Day","KE",2039 +"2039-12-27","Christmas Day (Observed)","KE",2039 +"2040-01-01","New Year's Day","KE",2040 +"2040-01-02","New Year's Day (Observed)","KE",2040 +"2040-03-30","Good Friday","KE",2040 +"2040-04-02","Easter Monday","KE",2040 +"2040-05-01","Labour Day","KE",2040 +"2040-06-01","Madaraka Day","KE",2040 +"2040-10-10","Utamaduni Day","KE",2040 +"2040-10-20","Mashujaa Day","KE",2040 +"2040-12-12","Jamhuri Day","KE",2040 +"2040-12-25","Christmas Day","KE",2040 +"2040-12-26","Boxing Day","KE",2040 +"2041-01-01","New Year's Day","KE",2041 +"2041-04-19","Good Friday","KE",2041 +"2041-04-22","Easter Monday","KE",2041 +"2041-05-01","Labour Day","KE",2041 +"2041-06-01","Madaraka Day","KE",2041 +"2041-10-10","Utamaduni Day","KE",2041 +"2041-10-20","Mashujaa Day","KE",2041 +"2041-10-21","Mashujaa Day (Observed)","KE",2041 +"2041-12-12","Jamhuri Day","KE",2041 +"2041-12-25","Christmas Day","KE",2041 +"2041-12-26","Boxing Day","KE",2041 +"2042-01-01","New Year's Day","KE",2042 +"2042-04-04","Good Friday","KE",2042 +"2042-04-07","Easter Monday","KE",2042 +"2042-05-01","Labour Day","KE",2042 +"2042-06-01","Madaraka Day","KE",2042 +"2042-06-02","Madaraka Day (Observed)","KE",2042 +"2042-10-10","Utamaduni Day","KE",2042 +"2042-10-20","Mashujaa Day","KE",2042 +"2042-12-12","Jamhuri Day","KE",2042 +"2042-12-25","Christmas Day","KE",2042 +"2042-12-26","Boxing Day","KE",2042 +"2043-01-01","New Year's Day","KE",2043 +"2043-03-27","Good Friday","KE",2043 +"2043-03-30","Easter Monday","KE",2043 +"2043-05-01","Labour Day","KE",2043 +"2043-06-01","Madaraka Day","KE",2043 +"2043-10-10","Utamaduni Day","KE",2043 +"2043-10-20","Mashujaa Day","KE",2043 +"2043-12-12","Jamhuri Day","KE",2043 +"2043-12-25","Christmas Day","KE",2043 +"2043-12-26","Boxing Day","KE",2043 +"2044-01-01","New Year's Day","KE",2044 +"2044-04-15","Good Friday","KE",2044 +"2044-04-18","Easter Monday","KE",2044 +"2044-05-01","Labour Day","KE",2044 +"2044-05-02","Labour Day (Observed)","KE",2044 +"2044-06-01","Madaraka Day","KE",2044 +"2044-10-10","Utamaduni Day","KE",2044 +"2044-10-20","Mashujaa Day","KE",2044 +"2044-12-12","Jamhuri Day","KE",2044 +"2044-12-25","Christmas Day","KE",2044 +"2044-12-26","Boxing Day","KE",2044 +"2044-12-27","Christmas Day (Observed)","KE",2044 +"1995-01-01","New Year's Day","KG",1995 +"1995-01-07","Christmas Day","KG",1995 +"1995-02-23","Fatherland Defender's Day","KG",1995 +"1995-03-02","Orozo Ait* (*estimated)","KG",1995 +"1995-03-03","Orozo Ait* (*estimated)","KG",1995 +"1995-03-08","International Women's Day","KG",1995 +"1995-03-21","Nooruz Mairamy","KG",1995 +"1995-05-01","International Workers' Day","KG",1995 +"1995-05-05","Constitution Day","KG",1995 +"1995-05-09","Kurman Ait* (*estimated)","KG",1995 +"1995-05-09","Victory Day","KG",1995 +"1995-08-31","Independence Day","KG",1995 +"1995-11-07","Days of History and Commemoration of Ancestors","KG",1995 +"1995-11-08","Days of History and Commemoration of Ancestors","KG",1995 +"1995-12-31","New Year's Eve","KG",1995 +"1996-01-01","New Year's Day","KG",1996 +"1996-01-07","Christmas Day","KG",1996 +"1996-02-19","Orozo Ait* (*estimated)","KG",1996 +"1996-02-20","Orozo Ait* (*estimated)","KG",1996 +"1996-02-23","Fatherland Defender's Day","KG",1996 +"1996-03-08","International Women's Day","KG",1996 +"1996-03-21","Nooruz Mairamy","KG",1996 +"1996-04-27","Kurman Ait* (*estimated)","KG",1996 +"1996-05-01","International Workers' Day","KG",1996 +"1996-05-05","Constitution Day","KG",1996 +"1996-05-09","Victory Day","KG",1996 +"1996-08-31","Independence Day","KG",1996 +"1996-11-07","Days of History and Commemoration of Ancestors","KG",1996 +"1996-11-08","Days of History and Commemoration of Ancestors","KG",1996 +"1996-12-31","New Year's Eve","KG",1996 +"1997-01-01","New Year's Day","KG",1997 +"1997-01-07","Christmas Day","KG",1997 +"1997-02-08","Orozo Ait* (*estimated)","KG",1997 +"1997-02-09","Orozo Ait* (*estimated)","KG",1997 +"1997-02-23","Fatherland Defender's Day","KG",1997 +"1997-03-08","International Women's Day","KG",1997 +"1997-03-21","Nooruz Mairamy","KG",1997 +"1997-04-17","Kurman Ait* (*estimated)","KG",1997 +"1997-05-01","International Workers' Day","KG",1997 +"1997-05-05","Constitution Day","KG",1997 +"1997-05-09","Victory Day","KG",1997 +"1997-08-31","Independence Day","KG",1997 +"1997-11-07","Days of History and Commemoration of Ancestors","KG",1997 +"1997-11-08","Days of History and Commemoration of Ancestors","KG",1997 +"1997-12-31","New Year's Eve","KG",1997 +"1998-01-01","New Year's Day","KG",1998 +"1998-01-07","Christmas Day","KG",1998 +"1998-01-29","Orozo Ait* (*estimated)","KG",1998 +"1998-01-30","Orozo Ait* (*estimated)","KG",1998 +"1998-02-23","Fatherland Defender's Day","KG",1998 +"1998-03-08","International Women's Day","KG",1998 +"1998-03-21","Nooruz Mairamy","KG",1998 +"1998-04-07","Kurman Ait* (*estimated)","KG",1998 +"1998-05-01","International Workers' Day","KG",1998 +"1998-05-05","Constitution Day","KG",1998 +"1998-05-09","Victory Day","KG",1998 +"1998-08-31","Independence Day","KG",1998 +"1998-11-07","Days of History and Commemoration of Ancestors","KG",1998 +"1998-11-08","Days of History and Commemoration of Ancestors","KG",1998 +"1998-12-31","New Year's Eve","KG",1998 +"1999-01-01","New Year's Day","KG",1999 +"1999-01-07","Christmas Day","KG",1999 +"1999-01-18","Orozo Ait* (*estimated)","KG",1999 +"1999-01-19","Orozo Ait* (*estimated)","KG",1999 +"1999-02-23","Fatherland Defender's Day","KG",1999 +"1999-03-08","International Women's Day","KG",1999 +"1999-03-21","Nooruz Mairamy","KG",1999 +"1999-03-27","Kurman Ait* (*estimated)","KG",1999 +"1999-05-01","International Workers' Day","KG",1999 +"1999-05-05","Constitution Day","KG",1999 +"1999-05-09","Victory Day","KG",1999 +"1999-08-31","Independence Day","KG",1999 +"1999-11-07","Days of History and Commemoration of Ancestors","KG",1999 +"1999-11-08","Days of History and Commemoration of Ancestors","KG",1999 +"1999-12-31","New Year's Eve","KG",1999 +"2000-01-01","New Year's Day","KG",2000 +"2000-01-07","Christmas Day","KG",2000 +"2000-01-08","Orozo Ait* (*estimated)","KG",2000 +"2000-01-09","Orozo Ait* (*estimated)","KG",2000 +"2000-02-23","Fatherland Defender's Day","KG",2000 +"2000-03-08","International Women's Day","KG",2000 +"2000-03-16","Kurman Ait* (*estimated)","KG",2000 +"2000-03-21","Nooruz Mairamy","KG",2000 +"2000-05-01","International Workers' Day","KG",2000 +"2000-05-05","Constitution Day","KG",2000 +"2000-05-09","Victory Day","KG",2000 +"2000-08-31","Independence Day","KG",2000 +"2000-11-07","Days of History and Commemoration of Ancestors","KG",2000 +"2000-11-08","Days of History and Commemoration of Ancestors","KG",2000 +"2000-12-27","Orozo Ait* (*estimated)","KG",2000 +"2000-12-28","Orozo Ait* (*estimated)","KG",2000 +"2000-12-31","New Year's Eve","KG",2000 +"2001-01-01","New Year's Day","KG",2001 +"2001-01-07","Christmas Day","KG",2001 +"2001-02-23","Fatherland Defender's Day","KG",2001 +"2001-03-05","Kurman Ait* (*estimated)","KG",2001 +"2001-03-08","International Women's Day","KG",2001 +"2001-03-21","Nooruz Mairamy","KG",2001 +"2001-05-01","International Workers' Day","KG",2001 +"2001-05-05","Constitution Day","KG",2001 +"2001-05-09","Victory Day","KG",2001 +"2001-08-31","Independence Day","KG",2001 +"2001-11-07","Days of History and Commemoration of Ancestors","KG",2001 +"2001-11-08","Days of History and Commemoration of Ancestors","KG",2001 +"2001-12-16","Orozo Ait* (*estimated)","KG",2001 +"2001-12-17","Orozo Ait* (*estimated)","KG",2001 +"2001-12-31","New Year's Eve","KG",2001 +"2002-01-01","New Year's Day","KG",2002 +"2002-01-07","Christmas Day","KG",2002 +"2002-02-22","Kurman Ait* (*estimated)","KG",2002 +"2002-02-23","Fatherland Defender's Day","KG",2002 +"2002-03-08","International Women's Day","KG",2002 +"2002-03-21","Nooruz Mairamy","KG",2002 +"2002-05-01","International Workers' Day","KG",2002 +"2002-05-05","Constitution Day","KG",2002 +"2002-05-09","Victory Day","KG",2002 +"2002-08-31","Independence Day","KG",2002 +"2002-11-07","Days of History and Commemoration of Ancestors","KG",2002 +"2002-11-08","Days of History and Commemoration of Ancestors","KG",2002 +"2002-12-05","Orozo Ait* (*estimated)","KG",2002 +"2002-12-06","Orozo Ait* (*estimated)","KG",2002 +"2002-12-31","New Year's Eve","KG",2002 +"2003-01-01","New Year's Day","KG",2003 +"2003-01-07","Christmas Day","KG",2003 +"2003-02-11","Kurman Ait* (*estimated)","KG",2003 +"2003-02-23","Fatherland Defender's Day","KG",2003 +"2003-03-08","International Women's Day","KG",2003 +"2003-03-21","Nooruz Mairamy","KG",2003 +"2003-05-01","International Workers' Day","KG",2003 +"2003-05-05","Constitution Day","KG",2003 +"2003-05-09","Victory Day","KG",2003 +"2003-08-31","Independence Day","KG",2003 +"2003-11-07","Days of History and Commemoration of Ancestors","KG",2003 +"2003-11-08","Days of History and Commemoration of Ancestors","KG",2003 +"2003-11-25","Orozo Ait* (*estimated)","KG",2003 +"2003-11-26","Orozo Ait* (*estimated)","KG",2003 +"2003-12-31","New Year's Eve","KG",2003 +"2004-01-01","New Year's Day","KG",2004 +"2004-01-07","Christmas Day","KG",2004 +"2004-02-01","Kurman Ait* (*estimated)","KG",2004 +"2004-02-23","Fatherland Defender's Day","KG",2004 +"2004-03-08","International Women's Day","KG",2004 +"2004-03-21","Nooruz Mairamy","KG",2004 +"2004-05-01","International Workers' Day","KG",2004 +"2004-05-05","Constitution Day","KG",2004 +"2004-05-09","Victory Day","KG",2004 +"2004-08-31","Independence Day","KG",2004 +"2004-11-07","Days of History and Commemoration of Ancestors","KG",2004 +"2004-11-08","Days of History and Commemoration of Ancestors","KG",2004 +"2004-11-14","Orozo Ait* (*estimated)","KG",2004 +"2004-11-15","Orozo Ait* (*estimated)","KG",2004 +"2004-12-31","New Year's Eve","KG",2004 +"2005-01-01","New Year's Day","KG",2005 +"2005-01-07","Christmas Day","KG",2005 +"2005-01-21","Kurman Ait* (*estimated)","KG",2005 +"2005-02-23","Fatherland Defender's Day","KG",2005 +"2005-03-08","International Women's Day","KG",2005 +"2005-03-21","Nooruz Mairamy","KG",2005 +"2005-05-01","International Workers' Day","KG",2005 +"2005-05-05","Constitution Day","KG",2005 +"2005-05-09","Victory Day","KG",2005 +"2005-08-31","Independence Day","KG",2005 +"2005-11-03","Orozo Ait* (*estimated)","KG",2005 +"2005-11-04","Orozo Ait* (*estimated)","KG",2005 +"2005-11-07","Days of History and Commemoration of Ancestors","KG",2005 +"2005-11-08","Days of History and Commemoration of Ancestors","KG",2005 +"2005-12-31","New Year's Eve","KG",2005 +"2006-01-01","New Year's Day","KG",2006 +"2006-01-07","Christmas Day","KG",2006 +"2006-01-10","Kurman Ait* (*estimated)","KG",2006 +"2006-02-23","Fatherland Defender's Day","KG",2006 +"2006-03-08","International Women's Day","KG",2006 +"2006-03-21","Nooruz Mairamy","KG",2006 +"2006-05-01","International Workers' Day","KG",2006 +"2006-05-05","Constitution Day","KG",2006 +"2006-05-09","Victory Day","KG",2006 +"2006-08-31","Independence Day","KG",2006 +"2006-10-23","Orozo Ait* (*estimated)","KG",2006 +"2006-10-24","Orozo Ait* (*estimated)","KG",2006 +"2006-11-07","Days of History and Commemoration of Ancestors","KG",2006 +"2006-11-08","Days of History and Commemoration of Ancestors","KG",2006 +"2006-12-31","Kurman Ait* (*estimated)","KG",2006 +"2006-12-31","New Year's Eve","KG",2006 +"2007-01-01","New Year's Day","KG",2007 +"2007-01-07","Christmas Day","KG",2007 +"2007-02-23","Fatherland Defender's Day","KG",2007 +"2007-03-08","International Women's Day","KG",2007 +"2007-03-21","Nooruz Mairamy","KG",2007 +"2007-05-01","International Workers' Day","KG",2007 +"2007-05-05","Constitution Day","KG",2007 +"2007-05-09","Victory Day","KG",2007 +"2007-08-31","Independence Day","KG",2007 +"2007-10-13","Orozo Ait* (*estimated)","KG",2007 +"2007-10-14","Orozo Ait* (*estimated)","KG",2007 +"2007-11-07","Days of History and Commemoration of Ancestors","KG",2007 +"2007-11-08","Days of History and Commemoration of Ancestors","KG",2007 +"2007-12-20","Kurman Ait* (*estimated)","KG",2007 +"2007-12-31","New Year's Eve","KG",2007 +"2008-01-01","New Year's Day","KG",2008 +"2008-01-07","Christmas Day","KG",2008 +"2008-02-23","Fatherland Defender's Day","KG",2008 +"2008-03-08","International Women's Day","KG",2008 +"2008-03-21","Nooruz Mairamy","KG",2008 +"2008-05-01","International Workers' Day","KG",2008 +"2008-05-05","Constitution Day","KG",2008 +"2008-05-09","Victory Day","KG",2008 +"2008-08-31","Independence Day","KG",2008 +"2008-10-01","Orozo Ait* (*estimated)","KG",2008 +"2008-10-02","Orozo Ait* (*estimated)","KG",2008 +"2008-11-07","Days of History and Commemoration of Ancestors","KG",2008 +"2008-11-08","Days of History and Commemoration of Ancestors","KG",2008 +"2008-12-08","Kurman Ait* (*estimated)","KG",2008 +"2008-12-31","New Year's Eve","KG",2008 +"2009-01-01","New Year's Day","KG",2009 +"2009-01-07","Christmas Day","KG",2009 +"2009-02-23","Fatherland Defender's Day","KG",2009 +"2009-03-08","International Women's Day","KG",2009 +"2009-03-21","Nooruz Mairamy","KG",2009 +"2009-05-01","International Workers' Day","KG",2009 +"2009-05-05","Constitution Day","KG",2009 +"2009-05-09","Victory Day","KG",2009 +"2009-08-31","Independence Day","KG",2009 +"2009-09-20","Orozo Ait* (*estimated)","KG",2009 +"2009-09-21","Orozo Ait* (*estimated)","KG",2009 +"2009-11-07","Days of History and Commemoration of Ancestors","KG",2009 +"2009-11-08","Days of History and Commemoration of Ancestors","KG",2009 +"2009-11-27","Kurman Ait* (*estimated)","KG",2009 +"2009-12-31","New Year's Eve","KG",2009 +"2010-01-01","New Year's Day","KG",2010 +"2010-01-07","Christmas Day","KG",2010 +"2010-02-23","Fatherland Defender's Day","KG",2010 +"2010-03-08","International Women's Day","KG",2010 +"2010-03-21","Nooruz Mairamy","KG",2010 +"2010-05-01","International Workers' Day","KG",2010 +"2010-05-05","Constitution Day","KG",2010 +"2010-05-09","Victory Day","KG",2010 +"2010-08-31","Independence Day","KG",2010 +"2010-09-10","Orozo Ait* (*estimated)","KG",2010 +"2010-09-11","Orozo Ait* (*estimated)","KG",2010 +"2010-11-07","Days of History and Commemoration of Ancestors","KG",2010 +"2010-11-08","Days of History and Commemoration of Ancestors","KG",2010 +"2010-11-16","Kurman Ait* (*estimated)","KG",2010 +"2010-12-31","New Year's Eve","KG",2010 +"2011-01-01","New Year's Day","KG",2011 +"2011-01-07","Christmas Day","KG",2011 +"2011-02-23","Fatherland Defender's Day","KG",2011 +"2011-03-08","International Women's Day","KG",2011 +"2011-03-21","Nooruz Mairamy","KG",2011 +"2011-05-01","International Workers' Day","KG",2011 +"2011-05-05","Constitution Day","KG",2011 +"2011-05-09","Victory Day","KG",2011 +"2011-08-30","Orozo Ait* (*estimated)","KG",2011 +"2011-08-31","Independence Day","KG",2011 +"2011-08-31","Orozo Ait* (*estimated)","KG",2011 +"2011-11-06","Kurman Ait* (*estimated)","KG",2011 +"2011-11-07","Days of History and Commemoration of Ancestors","KG",2011 +"2011-11-08","Days of History and Commemoration of Ancestors","KG",2011 +"2011-12-31","New Year's Eve","KG",2011 +"2012-01-01","New Year's Day","KG",2012 +"2012-01-07","Christmas Day","KG",2012 +"2012-02-23","Fatherland Defender's Day","KG",2012 +"2012-03-08","International Women's Day","KG",2012 +"2012-03-21","Nooruz Mairamy","KG",2012 +"2012-05-01","International Workers' Day","KG",2012 +"2012-05-05","Constitution Day","KG",2012 +"2012-05-09","Victory Day","KG",2012 +"2012-08-19","Orozo Ait* (*estimated)","KG",2012 +"2012-08-20","Orozo Ait* (*estimated)","KG",2012 +"2012-08-31","Independence Day","KG",2012 +"2012-10-26","Kurman Ait* (*estimated)","KG",2012 +"2012-11-07","Days of History and Commemoration of Ancestors","KG",2012 +"2012-11-08","Days of History and Commemoration of Ancestors","KG",2012 +"2012-12-31","New Year's Eve","KG",2012 +"2013-01-01","New Year's Day","KG",2013 +"2013-01-07","Christmas Day","KG",2013 +"2013-02-23","Fatherland Defender's Day","KG",2013 +"2013-03-08","International Women's Day","KG",2013 +"2013-03-21","Nooruz Mairamy","KG",2013 +"2013-05-01","International Workers' Day","KG",2013 +"2013-05-05","Constitution Day","KG",2013 +"2013-05-09","Victory Day","KG",2013 +"2013-08-08","Orozo Ait* (*estimated)","KG",2013 +"2013-08-09","Orozo Ait* (*estimated)","KG",2013 +"2013-08-31","Independence Day","KG",2013 +"2013-10-15","Kurman Ait* (*estimated)","KG",2013 +"2013-11-07","Days of History and Commemoration of Ancestors","KG",2013 +"2013-11-08","Days of History and Commemoration of Ancestors","KG",2013 +"2013-12-31","New Year's Eve","KG",2013 +"2014-01-01","New Year's Day","KG",2014 +"2014-01-07","Christmas Day","KG",2014 +"2014-02-23","Fatherland Defender's Day","KG",2014 +"2014-03-08","International Women's Day","KG",2014 +"2014-03-21","Nooruz Mairamy","KG",2014 +"2014-05-01","International Workers' Day","KG",2014 +"2014-05-05","Constitution Day","KG",2014 +"2014-05-09","Victory Day","KG",2014 +"2014-07-28","Orozo Ait* (*estimated)","KG",2014 +"2014-07-29","Orozo Ait* (*estimated)","KG",2014 +"2014-08-31","Independence Day","KG",2014 +"2014-10-04","Kurman Ait* (*estimated)","KG",2014 +"2014-11-07","Days of History and Commemoration of Ancestors","KG",2014 +"2014-11-08","Days of History and Commemoration of Ancestors","KG",2014 +"2014-12-31","New Year's Eve","KG",2014 +"2015-01-01","New Year's Day","KG",2015 +"2015-01-07","Christmas Day","KG",2015 +"2015-02-23","Fatherland Defender's Day","KG",2015 +"2015-03-08","International Women's Day","KG",2015 +"2015-03-21","Nooruz Mairamy","KG",2015 +"2015-05-01","International Workers' Day","KG",2015 +"2015-05-05","Constitution Day","KG",2015 +"2015-05-09","Victory Day","KG",2015 +"2015-07-17","Orozo Ait* (*estimated)","KG",2015 +"2015-07-18","Orozo Ait* (*estimated)","KG",2015 +"2015-08-31","Independence Day","KG",2015 +"2015-09-23","Kurman Ait* (*estimated)","KG",2015 +"2015-11-07","Days of History and Commemoration of Ancestors","KG",2015 +"2015-11-08","Days of History and Commemoration of Ancestors","KG",2015 +"2015-12-31","New Year's Eve","KG",2015 +"2016-01-01","New Year's Day","KG",2016 +"2016-01-07","Christmas Day","KG",2016 +"2016-02-23","Fatherland Defender's Day","KG",2016 +"2016-03-08","International Women's Day","KG",2016 +"2016-03-21","Nooruz Mairamy","KG",2016 +"2016-04-07","Day of the People's April Revolution","KG",2016 +"2016-05-01","International Workers' Day","KG",2016 +"2016-05-05","Constitution Day","KG",2016 +"2016-05-09","Victory Day","KG",2016 +"2016-07-06","Orozo Ait* (*estimated)","KG",2016 +"2016-07-07","Orozo Ait* (*estimated)","KG",2016 +"2016-08-31","Independence Day","KG",2016 +"2016-09-11","Kurman Ait* (*estimated)","KG",2016 +"2016-11-07","Days of History and Commemoration of Ancestors","KG",2016 +"2016-11-08","Days of History and Commemoration of Ancestors","KG",2016 +"2016-12-31","New Year's Eve","KG",2016 +"2017-01-01","New Year's Day","KG",2017 +"2017-01-07","Christmas Day","KG",2017 +"2017-02-23","Fatherland Defender's Day","KG",2017 +"2017-03-08","International Women's Day","KG",2017 +"2017-03-21","Nooruz Mairamy","KG",2017 +"2017-04-07","Day of the People's April Revolution","KG",2017 +"2017-05-01","International Workers' Day","KG",2017 +"2017-05-05","Constitution Day","KG",2017 +"2017-05-09","Victory Day","KG",2017 +"2017-06-25","Orozo Ait* (*estimated)","KG",2017 +"2017-06-26","Orozo Ait* (*estimated)","KG",2017 +"2017-08-31","Independence Day","KG",2017 +"2017-09-01","Kurman Ait* (*estimated)","KG",2017 +"2017-11-07","Days of History and Commemoration of Ancestors","KG",2017 +"2017-11-08","Days of History and Commemoration of Ancestors","KG",2017 +"2017-12-31","New Year's Eve","KG",2017 +"2018-01-01","New Year's Day","KG",2018 +"2018-01-07","Christmas Day","KG",2018 +"2018-02-23","Fatherland Defender's Day","KG",2018 +"2018-03-08","International Women's Day","KG",2018 +"2018-03-21","Nooruz Mairamy","KG",2018 +"2018-04-07","Day of the People's April Revolution","KG",2018 +"2018-05-01","International Workers' Day","KG",2018 +"2018-05-05","Constitution Day","KG",2018 +"2018-05-09","Victory Day","KG",2018 +"2018-06-15","Orozo Ait* (*estimated)","KG",2018 +"2018-06-16","Orozo Ait* (*estimated)","KG",2018 +"2018-08-21","Kurman Ait* (*estimated)","KG",2018 +"2018-08-31","Independence Day","KG",2018 +"2018-11-07","Days of History and Commemoration of Ancestors","KG",2018 +"2018-11-08","Days of History and Commemoration of Ancestors","KG",2018 +"2018-12-31","New Year's Eve","KG",2018 +"2019-01-01","New Year's Day","KG",2019 +"2019-01-07","Christmas Day","KG",2019 +"2019-02-23","Fatherland Defender's Day","KG",2019 +"2019-03-08","International Women's Day","KG",2019 +"2019-03-21","Nooruz Mairamy","KG",2019 +"2019-04-07","Day of the People's April Revolution","KG",2019 +"2019-05-01","International Workers' Day","KG",2019 +"2019-05-05","Constitution Day","KG",2019 +"2019-05-09","Victory Day","KG",2019 +"2019-06-04","Orozo Ait* (*estimated)","KG",2019 +"2019-06-05","Orozo Ait* (*estimated)","KG",2019 +"2019-08-11","Kurman Ait* (*estimated)","KG",2019 +"2019-08-31","Independence Day","KG",2019 +"2019-11-07","Days of History and Commemoration of Ancestors","KG",2019 +"2019-11-08","Days of History and Commemoration of Ancestors","KG",2019 +"2019-12-31","New Year's Eve","KG",2019 +"2020-01-01","New Year's Day","KG",2020 +"2020-01-07","Christmas Day","KG",2020 +"2020-02-23","Fatherland Defender's Day","KG",2020 +"2020-03-08","International Women's Day","KG",2020 +"2020-03-21","Nooruz Mairamy","KG",2020 +"2020-04-07","Day of the People's April Revolution","KG",2020 +"2020-05-01","International Workers' Day","KG",2020 +"2020-05-05","Constitution Day","KG",2020 +"2020-05-09","Victory Day","KG",2020 +"2020-05-24","Orozo Ait* (*estimated)","KG",2020 +"2020-05-25","Orozo Ait* (*estimated)","KG",2020 +"2020-07-31","Kurman Ait* (*estimated)","KG",2020 +"2020-08-31","Independence Day","KG",2020 +"2020-11-07","Days of History and Commemoration of Ancestors","KG",2020 +"2020-11-08","Days of History and Commemoration of Ancestors","KG",2020 +"2020-12-31","New Year's Eve","KG",2020 +"2021-01-01","New Year's Day","KG",2021 +"2021-01-07","Christmas Day","KG",2021 +"2021-02-23","Fatherland Defender's Day","KG",2021 +"2021-03-08","International Women's Day","KG",2021 +"2021-03-21","Nooruz Mairamy","KG",2021 +"2021-04-07","Day of the People's April Revolution","KG",2021 +"2021-05-01","International Workers' Day","KG",2021 +"2021-05-05","Constitution Day","KG",2021 +"2021-05-09","Victory Day","KG",2021 +"2021-05-13","Orozo Ait* (*estimated)","KG",2021 +"2021-05-14","Orozo Ait* (*estimated)","KG",2021 +"2021-07-20","Kurman Ait* (*estimated)","KG",2021 +"2021-08-31","Independence Day","KG",2021 +"2021-11-07","Days of History and Commemoration of Ancestors","KG",2021 +"2021-11-08","Days of History and Commemoration of Ancestors","KG",2021 +"2021-12-31","New Year's Eve","KG",2021 +"2022-01-01","New Year's Day","KG",2022 +"2022-01-07","Christmas Day","KG",2022 +"2022-02-23","Fatherland Defender's Day","KG",2022 +"2022-03-08","International Women's Day","KG",2022 +"2022-03-21","Nooruz Mairamy","KG",2022 +"2022-04-07","Day of the People's April Revolution","KG",2022 +"2022-05-01","International Workers' Day","KG",2022 +"2022-05-02","Orozo Ait* (*estimated)","KG",2022 +"2022-05-03","Orozo Ait* (*estimated)","KG",2022 +"2022-05-05","Constitution Day","KG",2022 +"2022-05-09","Victory Day","KG",2022 +"2022-07-09","Kurman Ait* (*estimated)","KG",2022 +"2022-08-31","Independence Day","KG",2022 +"2022-11-07","Days of History and Commemoration of Ancestors","KG",2022 +"2022-11-08","Days of History and Commemoration of Ancestors","KG",2022 +"2022-12-31","New Year's Eve","KG",2022 +"2023-01-01","New Year's Day","KG",2023 +"2023-01-07","Christmas Day","KG",2023 +"2023-02-23","Fatherland Defender's Day","KG",2023 +"2023-03-08","International Women's Day","KG",2023 +"2023-03-21","Nooruz Mairamy","KG",2023 +"2023-04-07","Day of the People's April Revolution","KG",2023 +"2023-04-21","Orozo Ait* (*estimated)","KG",2023 +"2023-04-22","Orozo Ait* (*estimated)","KG",2023 +"2023-05-01","International Workers' Day","KG",2023 +"2023-05-05","Constitution Day","KG",2023 +"2023-05-09","Victory Day","KG",2023 +"2023-06-28","Kurman Ait* (*estimated)","KG",2023 +"2023-08-31","Independence Day","KG",2023 +"2023-11-07","Days of History and Commemoration of Ancestors","KG",2023 +"2023-11-08","Days of History and Commemoration of Ancestors","KG",2023 +"2023-12-31","New Year's Eve","KG",2023 +"2024-01-01","New Year's Day","KG",2024 +"2024-01-07","Christmas Day","KG",2024 +"2024-02-23","Fatherland Defender's Day","KG",2024 +"2024-03-08","International Women's Day","KG",2024 +"2024-03-21","Nooruz Mairamy","KG",2024 +"2024-04-07","Day of the People's April Revolution","KG",2024 +"2024-04-10","Orozo Ait* (*estimated)","KG",2024 +"2024-04-11","Orozo Ait* (*estimated)","KG",2024 +"2024-05-01","International Workers' Day","KG",2024 +"2024-05-05","Constitution Day","KG",2024 +"2024-05-09","Victory Day","KG",2024 +"2024-06-16","Kurman Ait* (*estimated)","KG",2024 +"2024-08-31","Independence Day","KG",2024 +"2024-11-07","Days of History and Commemoration of Ancestors","KG",2024 +"2024-11-08","Days of History and Commemoration of Ancestors","KG",2024 +"2024-12-31","New Year's Eve","KG",2024 +"2025-01-01","New Year's Day","KG",2025 +"2025-01-07","Christmas Day","KG",2025 +"2025-02-23","Fatherland Defender's Day","KG",2025 +"2025-03-08","International Women's Day","KG",2025 +"2025-03-21","Nooruz Mairamy","KG",2025 +"2025-03-30","Orozo Ait* (*estimated)","KG",2025 +"2025-03-31","Orozo Ait* (*estimated)","KG",2025 +"2025-04-07","Day of the People's April Revolution","KG",2025 +"2025-05-01","International Workers' Day","KG",2025 +"2025-05-05","Constitution Day","KG",2025 +"2025-05-09","Victory Day","KG",2025 +"2025-06-06","Kurman Ait* (*estimated)","KG",2025 +"2025-08-31","Independence Day","KG",2025 +"2025-11-07","Days of History and Commemoration of Ancestors","KG",2025 +"2025-11-08","Days of History and Commemoration of Ancestors","KG",2025 +"2025-12-31","New Year's Eve","KG",2025 +"2026-01-01","New Year's Day","KG",2026 +"2026-01-07","Christmas Day","KG",2026 +"2026-02-23","Fatherland Defender's Day","KG",2026 +"2026-03-08","International Women's Day","KG",2026 +"2026-03-20","Orozo Ait* (*estimated)","KG",2026 +"2026-03-21","Nooruz Mairamy","KG",2026 +"2026-03-21","Orozo Ait* (*estimated)","KG",2026 +"2026-04-07","Day of the People's April Revolution","KG",2026 +"2026-05-01","International Workers' Day","KG",2026 +"2026-05-05","Constitution Day","KG",2026 +"2026-05-09","Victory Day","KG",2026 +"2026-05-27","Kurman Ait* (*estimated)","KG",2026 +"2026-08-31","Independence Day","KG",2026 +"2026-11-07","Days of History and Commemoration of Ancestors","KG",2026 +"2026-11-08","Days of History and Commemoration of Ancestors","KG",2026 +"2026-12-31","New Year's Eve","KG",2026 +"2027-01-01","New Year's Day","KG",2027 +"2027-01-07","Christmas Day","KG",2027 +"2027-02-23","Fatherland Defender's Day","KG",2027 +"2027-03-08","International Women's Day","KG",2027 +"2027-03-09","Orozo Ait* (*estimated)","KG",2027 +"2027-03-10","Orozo Ait* (*estimated)","KG",2027 +"2027-03-21","Nooruz Mairamy","KG",2027 +"2027-04-07","Day of the People's April Revolution","KG",2027 +"2027-05-01","International Workers' Day","KG",2027 +"2027-05-05","Constitution Day","KG",2027 +"2027-05-09","Victory Day","KG",2027 +"2027-05-16","Kurman Ait* (*estimated)","KG",2027 +"2027-08-31","Independence Day","KG",2027 +"2027-11-07","Days of History and Commemoration of Ancestors","KG",2027 +"2027-11-08","Days of History and Commemoration of Ancestors","KG",2027 +"2027-12-31","New Year's Eve","KG",2027 +"2028-01-01","New Year's Day","KG",2028 +"2028-01-07","Christmas Day","KG",2028 +"2028-02-23","Fatherland Defender's Day","KG",2028 +"2028-02-26","Orozo Ait* (*estimated)","KG",2028 +"2028-02-27","Orozo Ait* (*estimated)","KG",2028 +"2028-03-08","International Women's Day","KG",2028 +"2028-03-21","Nooruz Mairamy","KG",2028 +"2028-04-07","Day of the People's April Revolution","KG",2028 +"2028-05-01","International Workers' Day","KG",2028 +"2028-05-05","Constitution Day","KG",2028 +"2028-05-05","Kurman Ait* (*estimated)","KG",2028 +"2028-05-09","Victory Day","KG",2028 +"2028-08-31","Independence Day","KG",2028 +"2028-11-07","Days of History and Commemoration of Ancestors","KG",2028 +"2028-11-08","Days of History and Commemoration of Ancestors","KG",2028 +"2028-12-31","New Year's Eve","KG",2028 +"2029-01-01","New Year's Day","KG",2029 +"2029-01-07","Christmas Day","KG",2029 +"2029-02-14","Orozo Ait* (*estimated)","KG",2029 +"2029-02-15","Orozo Ait* (*estimated)","KG",2029 +"2029-02-23","Fatherland Defender's Day","KG",2029 +"2029-03-08","International Women's Day","KG",2029 +"2029-03-21","Nooruz Mairamy","KG",2029 +"2029-04-07","Day of the People's April Revolution","KG",2029 +"2029-04-24","Kurman Ait* (*estimated)","KG",2029 +"2029-05-01","International Workers' Day","KG",2029 +"2029-05-05","Constitution Day","KG",2029 +"2029-05-09","Victory Day","KG",2029 +"2029-08-31","Independence Day","KG",2029 +"2029-11-07","Days of History and Commemoration of Ancestors","KG",2029 +"2029-11-08","Days of History and Commemoration of Ancestors","KG",2029 +"2029-12-31","New Year's Eve","KG",2029 +"2030-01-01","New Year's Day","KG",2030 +"2030-01-07","Christmas Day","KG",2030 +"2030-02-04","Orozo Ait* (*estimated)","KG",2030 +"2030-02-05","Orozo Ait* (*estimated)","KG",2030 +"2030-02-23","Fatherland Defender's Day","KG",2030 +"2030-03-08","International Women's Day","KG",2030 +"2030-03-21","Nooruz Mairamy","KG",2030 +"2030-04-07","Day of the People's April Revolution","KG",2030 +"2030-04-13","Kurman Ait* (*estimated)","KG",2030 +"2030-05-01","International Workers' Day","KG",2030 +"2030-05-05","Constitution Day","KG",2030 +"2030-05-09","Victory Day","KG",2030 +"2030-08-31","Independence Day","KG",2030 +"2030-11-07","Days of History and Commemoration of Ancestors","KG",2030 +"2030-11-08","Days of History and Commemoration of Ancestors","KG",2030 +"2030-12-31","New Year's Eve","KG",2030 +"2031-01-01","New Year's Day","KG",2031 +"2031-01-07","Christmas Day","KG",2031 +"2031-01-24","Orozo Ait* (*estimated)","KG",2031 +"2031-01-25","Orozo Ait* (*estimated)","KG",2031 +"2031-02-23","Fatherland Defender's Day","KG",2031 +"2031-03-08","International Women's Day","KG",2031 +"2031-03-21","Nooruz Mairamy","KG",2031 +"2031-04-02","Kurman Ait* (*estimated)","KG",2031 +"2031-04-07","Day of the People's April Revolution","KG",2031 +"2031-05-01","International Workers' Day","KG",2031 +"2031-05-05","Constitution Day","KG",2031 +"2031-05-09","Victory Day","KG",2031 +"2031-08-31","Independence Day","KG",2031 +"2031-11-07","Days of History and Commemoration of Ancestors","KG",2031 +"2031-11-08","Days of History and Commemoration of Ancestors","KG",2031 +"2031-12-31","New Year's Eve","KG",2031 +"2032-01-01","New Year's Day","KG",2032 +"2032-01-07","Christmas Day","KG",2032 +"2032-01-14","Orozo Ait* (*estimated)","KG",2032 +"2032-01-15","Orozo Ait* (*estimated)","KG",2032 +"2032-02-23","Fatherland Defender's Day","KG",2032 +"2032-03-08","International Women's Day","KG",2032 +"2032-03-21","Nooruz Mairamy","KG",2032 +"2032-03-22","Kurman Ait* (*estimated)","KG",2032 +"2032-04-07","Day of the People's April Revolution","KG",2032 +"2032-05-01","International Workers' Day","KG",2032 +"2032-05-05","Constitution Day","KG",2032 +"2032-05-09","Victory Day","KG",2032 +"2032-08-31","Independence Day","KG",2032 +"2032-11-07","Days of History and Commemoration of Ancestors","KG",2032 +"2032-11-08","Days of History and Commemoration of Ancestors","KG",2032 +"2032-12-31","New Year's Eve","KG",2032 +"2033-01-01","New Year's Day","KG",2033 +"2033-01-02","Orozo Ait* (*estimated)","KG",2033 +"2033-01-03","Orozo Ait* (*estimated)","KG",2033 +"2033-01-07","Christmas Day","KG",2033 +"2033-02-23","Fatherland Defender's Day","KG",2033 +"2033-03-08","International Women's Day","KG",2033 +"2033-03-11","Kurman Ait* (*estimated)","KG",2033 +"2033-03-21","Nooruz Mairamy","KG",2033 +"2033-04-07","Day of the People's April Revolution","KG",2033 +"2033-05-01","International Workers' Day","KG",2033 +"2033-05-05","Constitution Day","KG",2033 +"2033-05-09","Victory Day","KG",2033 +"2033-08-31","Independence Day","KG",2033 +"2033-11-07","Days of History and Commemoration of Ancestors","KG",2033 +"2033-11-08","Days of History and Commemoration of Ancestors","KG",2033 +"2033-12-23","Orozo Ait* (*estimated)","KG",2033 +"2033-12-24","Orozo Ait* (*estimated)","KG",2033 +"2033-12-31","New Year's Eve","KG",2033 +"2034-01-01","New Year's Day","KG",2034 +"2034-01-07","Christmas Day","KG",2034 +"2034-02-23","Fatherland Defender's Day","KG",2034 +"2034-03-01","Kurman Ait* (*estimated)","KG",2034 +"2034-03-08","International Women's Day","KG",2034 +"2034-03-21","Nooruz Mairamy","KG",2034 +"2034-04-07","Day of the People's April Revolution","KG",2034 +"2034-05-01","International Workers' Day","KG",2034 +"2034-05-05","Constitution Day","KG",2034 +"2034-05-09","Victory Day","KG",2034 +"2034-08-31","Independence Day","KG",2034 +"2034-11-07","Days of History and Commemoration of Ancestors","KG",2034 +"2034-11-08","Days of History and Commemoration of Ancestors","KG",2034 +"2034-12-12","Orozo Ait* (*estimated)","KG",2034 +"2034-12-13","Orozo Ait* (*estimated)","KG",2034 +"2034-12-31","New Year's Eve","KG",2034 +"2035-01-01","New Year's Day","KG",2035 +"2035-01-07","Christmas Day","KG",2035 +"2035-02-18","Kurman Ait* (*estimated)","KG",2035 +"2035-02-23","Fatherland Defender's Day","KG",2035 +"2035-03-08","International Women's Day","KG",2035 +"2035-03-21","Nooruz Mairamy","KG",2035 +"2035-04-07","Day of the People's April Revolution","KG",2035 +"2035-05-01","International Workers' Day","KG",2035 +"2035-05-05","Constitution Day","KG",2035 +"2035-05-09","Victory Day","KG",2035 +"2035-08-31","Independence Day","KG",2035 +"2035-11-07","Days of History and Commemoration of Ancestors","KG",2035 +"2035-11-08","Days of History and Commemoration of Ancestors","KG",2035 +"2035-12-01","Orozo Ait* (*estimated)","KG",2035 +"2035-12-02","Orozo Ait* (*estimated)","KG",2035 +"2035-12-31","New Year's Eve","KG",2035 +"2036-01-01","New Year's Day","KG",2036 +"2036-01-07","Christmas Day","KG",2036 +"2036-02-07","Kurman Ait* (*estimated)","KG",2036 +"2036-02-23","Fatherland Defender's Day","KG",2036 +"2036-03-08","International Women's Day","KG",2036 +"2036-03-21","Nooruz Mairamy","KG",2036 +"2036-04-07","Day of the People's April Revolution","KG",2036 +"2036-05-01","International Workers' Day","KG",2036 +"2036-05-05","Constitution Day","KG",2036 +"2036-05-09","Victory Day","KG",2036 +"2036-08-31","Independence Day","KG",2036 +"2036-11-07","Days of History and Commemoration of Ancestors","KG",2036 +"2036-11-08","Days of History and Commemoration of Ancestors","KG",2036 +"2036-11-19","Orozo Ait* (*estimated)","KG",2036 +"2036-11-20","Orozo Ait* (*estimated)","KG",2036 +"2036-12-31","New Year's Eve","KG",2036 +"2037-01-01","New Year's Day","KG",2037 +"2037-01-07","Christmas Day","KG",2037 +"2037-01-26","Kurman Ait* (*estimated)","KG",2037 +"2037-02-23","Fatherland Defender's Day","KG",2037 +"2037-03-08","International Women's Day","KG",2037 +"2037-03-21","Nooruz Mairamy","KG",2037 +"2037-04-07","Day of the People's April Revolution","KG",2037 +"2037-05-01","International Workers' Day","KG",2037 +"2037-05-05","Constitution Day","KG",2037 +"2037-05-09","Victory Day","KG",2037 +"2037-08-31","Independence Day","KG",2037 +"2037-11-07","Days of History and Commemoration of Ancestors","KG",2037 +"2037-11-08","Days of History and Commemoration of Ancestors","KG",2037 +"2037-11-08","Orozo Ait* (*estimated)","KG",2037 +"2037-11-09","Orozo Ait* (*estimated)","KG",2037 +"2037-12-31","New Year's Eve","KG",2037 +"2038-01-01","New Year's Day","KG",2038 +"2038-01-07","Christmas Day","KG",2038 +"2038-01-16","Kurman Ait* (*estimated)","KG",2038 +"2038-02-23","Fatherland Defender's Day","KG",2038 +"2038-03-08","International Women's Day","KG",2038 +"2038-03-21","Nooruz Mairamy","KG",2038 +"2038-04-07","Day of the People's April Revolution","KG",2038 +"2038-05-01","International Workers' Day","KG",2038 +"2038-05-05","Constitution Day","KG",2038 +"2038-05-09","Victory Day","KG",2038 +"2038-08-31","Independence Day","KG",2038 +"2038-10-29","Orozo Ait* (*estimated)","KG",2038 +"2038-10-30","Orozo Ait* (*estimated)","KG",2038 +"2038-11-07","Days of History and Commemoration of Ancestors","KG",2038 +"2038-11-08","Days of History and Commemoration of Ancestors","KG",2038 +"2038-12-31","New Year's Eve","KG",2038 +"2039-01-01","New Year's Day","KG",2039 +"2039-01-05","Kurman Ait* (*estimated)","KG",2039 +"2039-01-07","Christmas Day","KG",2039 +"2039-02-23","Fatherland Defender's Day","KG",2039 +"2039-03-08","International Women's Day","KG",2039 +"2039-03-21","Nooruz Mairamy","KG",2039 +"2039-04-07","Day of the People's April Revolution","KG",2039 +"2039-05-01","International Workers' Day","KG",2039 +"2039-05-05","Constitution Day","KG",2039 +"2039-05-09","Victory Day","KG",2039 +"2039-08-31","Independence Day","KG",2039 +"2039-10-19","Orozo Ait* (*estimated)","KG",2039 +"2039-10-20","Orozo Ait* (*estimated)","KG",2039 +"2039-11-07","Days of History and Commemoration of Ancestors","KG",2039 +"2039-11-08","Days of History and Commemoration of Ancestors","KG",2039 +"2039-12-26","Kurman Ait* (*estimated)","KG",2039 +"2039-12-31","New Year's Eve","KG",2039 +"2040-01-01","New Year's Day","KG",2040 +"2040-01-07","Christmas Day","KG",2040 +"2040-02-23","Fatherland Defender's Day","KG",2040 +"2040-03-08","International Women's Day","KG",2040 +"2040-03-21","Nooruz Mairamy","KG",2040 +"2040-04-07","Day of the People's April Revolution","KG",2040 +"2040-05-01","International Workers' Day","KG",2040 +"2040-05-05","Constitution Day","KG",2040 +"2040-05-09","Victory Day","KG",2040 +"2040-08-31","Independence Day","KG",2040 +"2040-10-07","Orozo Ait* (*estimated)","KG",2040 +"2040-10-08","Orozo Ait* (*estimated)","KG",2040 +"2040-11-07","Days of History and Commemoration of Ancestors","KG",2040 +"2040-11-08","Days of History and Commemoration of Ancestors","KG",2040 +"2040-12-14","Kurman Ait* (*estimated)","KG",2040 +"2040-12-31","New Year's Eve","KG",2040 +"2041-01-01","New Year's Day","KG",2041 +"2041-01-07","Christmas Day","KG",2041 +"2041-02-23","Fatherland Defender's Day","KG",2041 +"2041-03-08","International Women's Day","KG",2041 +"2041-03-21","Nooruz Mairamy","KG",2041 +"2041-04-07","Day of the People's April Revolution","KG",2041 +"2041-05-01","International Workers' Day","KG",2041 +"2041-05-05","Constitution Day","KG",2041 +"2041-05-09","Victory Day","KG",2041 +"2041-08-31","Independence Day","KG",2041 +"2041-09-26","Orozo Ait* (*estimated)","KG",2041 +"2041-09-27","Orozo Ait* (*estimated)","KG",2041 +"2041-11-07","Days of History and Commemoration of Ancestors","KG",2041 +"2041-11-08","Days of History and Commemoration of Ancestors","KG",2041 +"2041-12-04","Kurman Ait* (*estimated)","KG",2041 +"2041-12-31","New Year's Eve","KG",2041 +"2042-01-01","New Year's Day","KG",2042 +"2042-01-07","Christmas Day","KG",2042 +"2042-02-23","Fatherland Defender's Day","KG",2042 +"2042-03-08","International Women's Day","KG",2042 +"2042-03-21","Nooruz Mairamy","KG",2042 +"2042-04-07","Day of the People's April Revolution","KG",2042 +"2042-05-01","International Workers' Day","KG",2042 +"2042-05-05","Constitution Day","KG",2042 +"2042-05-09","Victory Day","KG",2042 +"2042-08-31","Independence Day","KG",2042 +"2042-09-15","Orozo Ait* (*estimated)","KG",2042 +"2042-09-16","Orozo Ait* (*estimated)","KG",2042 +"2042-11-07","Days of History and Commemoration of Ancestors","KG",2042 +"2042-11-08","Days of History and Commemoration of Ancestors","KG",2042 +"2042-11-23","Kurman Ait* (*estimated)","KG",2042 +"2042-12-31","New Year's Eve","KG",2042 +"2043-01-01","New Year's Day","KG",2043 +"2043-01-07","Christmas Day","KG",2043 +"2043-02-23","Fatherland Defender's Day","KG",2043 +"2043-03-08","International Women's Day","KG",2043 +"2043-03-21","Nooruz Mairamy","KG",2043 +"2043-04-07","Day of the People's April Revolution","KG",2043 +"2043-05-01","International Workers' Day","KG",2043 +"2043-05-05","Constitution Day","KG",2043 +"2043-05-09","Victory Day","KG",2043 +"2043-08-31","Independence Day","KG",2043 +"2043-09-04","Orozo Ait* (*estimated)","KG",2043 +"2043-09-05","Orozo Ait* (*estimated)","KG",2043 +"2043-11-07","Days of History and Commemoration of Ancestors","KG",2043 +"2043-11-08","Days of History and Commemoration of Ancestors","KG",2043 +"2043-11-12","Kurman Ait* (*estimated)","KG",2043 +"2043-12-31","New Year's Eve","KG",2043 +"2044-01-01","New Year's Day","KG",2044 +"2044-01-07","Christmas Day","KG",2044 +"2044-02-23","Fatherland Defender's Day","KG",2044 +"2044-03-08","International Women's Day","KG",2044 +"2044-03-21","Nooruz Mairamy","KG",2044 +"2044-04-07","Day of the People's April Revolution","KG",2044 +"2044-05-01","International Workers' Day","KG",2044 +"2044-05-05","Constitution Day","KG",2044 +"2044-05-09","Victory Day","KG",2044 +"2044-08-24","Orozo Ait* (*estimated)","KG",2044 +"2044-08-25","Orozo Ait* (*estimated)","KG",2044 +"2044-08-31","Independence Day","KG",2044 +"2044-10-31","Kurman Ait* (*estimated)","KG",2044 +"2044-11-07","Days of History and Commemoration of Ancestors","KG",2044 +"2044-11-08","Days of History and Commemoration of Ancestors","KG",2044 +"2044-12-31","New Year's Eve","KG",2044 +"1995-01-01","New Year's Day","KR",1995 +"1995-01-30","The day preceding of Lunar New Year's Day","KR",1995 +"1995-01-31","Lunar New Year's Day","KR",1995 +"1995-02-01","The second day of Lunar New Year's Day","KR",1995 +"1995-03-01","Independence Movement Day","KR",1995 +"1995-04-05","Tree Planting Day","KR",1995 +"1995-05-01","Labour Day","KR",1995 +"1995-05-05","Children's Day","KR",1995 +"1995-05-07","Birthday of the Buddha","KR",1995 +"1995-06-06","Memorial Day","KR",1995 +"1995-07-17","Constitution Day","KR",1995 +"1995-08-15","Liberation Day","KR",1995 +"1995-09-08","The day preceding of Chuseok","KR",1995 +"1995-09-09","Chuseok","KR",1995 +"1995-09-10","The second day of Chuseok","KR",1995 +"1995-10-03","National Foundation Day","KR",1995 +"1995-12-25","Christmas Day","KR",1995 +"1996-01-01","New Year's Day","KR",1996 +"1996-02-18","The day preceding of Lunar New Year's Day","KR",1996 +"1996-02-19","Lunar New Year's Day","KR",1996 +"1996-02-20","The second day of Lunar New Year's Day","KR",1996 +"1996-03-01","Independence Movement Day","KR",1996 +"1996-04-05","Tree Planting Day","KR",1996 +"1996-05-01","Labour Day","KR",1996 +"1996-05-05","Children's Day","KR",1996 +"1996-05-24","Birthday of the Buddha","KR",1996 +"1996-06-06","Memorial Day","KR",1996 +"1996-07-17","Constitution Day","KR",1996 +"1996-08-15","Liberation Day","KR",1996 +"1996-09-26","The day preceding of Chuseok","KR",1996 +"1996-09-27","Chuseok","KR",1996 +"1996-09-28","The second day of Chuseok","KR",1996 +"1996-10-03","National Foundation Day","KR",1996 +"1996-12-25","Christmas Day","KR",1996 +"1997-01-01","New Year's Day","KR",1997 +"1997-02-07","The day preceding of Lunar New Year's Day","KR",1997 +"1997-02-08","Lunar New Year's Day","KR",1997 +"1997-02-09","The second day of Lunar New Year's Day","KR",1997 +"1997-03-01","Independence Movement Day","KR",1997 +"1997-04-05","Tree Planting Day","KR",1997 +"1997-05-01","Labour Day","KR",1997 +"1997-05-05","Children's Day","KR",1997 +"1997-05-14","Birthday of the Buddha","KR",1997 +"1997-06-06","Memorial Day","KR",1997 +"1997-07-17","Constitution Day","KR",1997 +"1997-08-15","Liberation Day","KR",1997 +"1997-09-15","The day preceding of Chuseok","KR",1997 +"1997-09-16","Chuseok","KR",1997 +"1997-09-17","The second day of Chuseok","KR",1997 +"1997-10-03","National Foundation Day","KR",1997 +"1997-12-25","Christmas Day","KR",1997 +"1998-01-01","New Year's Day","KR",1998 +"1998-01-27","The day preceding of Lunar New Year's Day","KR",1998 +"1998-01-28","Lunar New Year's Day","KR",1998 +"1998-01-29","The second day of Lunar New Year's Day","KR",1998 +"1998-03-01","Independence Movement Day","KR",1998 +"1998-04-05","Tree Planting Day","KR",1998 +"1998-05-01","Labour Day","KR",1998 +"1998-05-03","Birthday of the Buddha","KR",1998 +"1998-05-05","Children's Day","KR",1998 +"1998-06-06","Memorial Day","KR",1998 +"1998-07-17","Constitution Day","KR",1998 +"1998-08-15","Liberation Day","KR",1998 +"1998-10-03","National Foundation Day","KR",1998 +"1998-10-04","The day preceding of Chuseok","KR",1998 +"1998-10-05","Chuseok","KR",1998 +"1998-10-06","The second day of Chuseok","KR",1998 +"1998-12-25","Christmas Day","KR",1998 +"1999-01-01","New Year's Day","KR",1999 +"1999-02-15","The day preceding of Lunar New Year's Day","KR",1999 +"1999-02-16","Lunar New Year's Day","KR",1999 +"1999-02-17","The second day of Lunar New Year's Day","KR",1999 +"1999-03-01","Independence Movement Day","KR",1999 +"1999-04-05","Tree Planting Day","KR",1999 +"1999-05-01","Labour Day","KR",1999 +"1999-05-05","Children's Day","KR",1999 +"1999-05-22","Birthday of the Buddha","KR",1999 +"1999-06-06","Memorial Day","KR",1999 +"1999-07-17","Constitution Day","KR",1999 +"1999-08-15","Liberation Day","KR",1999 +"1999-09-23","The day preceding of Chuseok","KR",1999 +"1999-09-24","Chuseok","KR",1999 +"1999-09-25","The second day of Chuseok","KR",1999 +"1999-10-03","National Foundation Day","KR",1999 +"1999-12-25","Christmas Day","KR",1999 +"2000-01-01","New Year's Day","KR",2000 +"2000-02-04","The day preceding of Lunar New Year's Day","KR",2000 +"2000-02-05","Lunar New Year's Day","KR",2000 +"2000-02-06","The second day of Lunar New Year's Day","KR",2000 +"2000-03-01","Independence Movement Day","KR",2000 +"2000-04-05","Tree Planting Day","KR",2000 +"2000-05-01","Labour Day","KR",2000 +"2000-05-05","Children's Day","KR",2000 +"2000-05-11","Birthday of the Buddha","KR",2000 +"2000-06-06","Memorial Day","KR",2000 +"2000-07-17","Constitution Day","KR",2000 +"2000-08-15","Liberation Day","KR",2000 +"2000-09-11","The day preceding of Chuseok","KR",2000 +"2000-09-12","Chuseok","KR",2000 +"2000-09-13","The second day of Chuseok","KR",2000 +"2000-10-03","National Foundation Day","KR",2000 +"2000-12-25","Christmas Day","KR",2000 +"2001-01-01","New Year's Day","KR",2001 +"2001-01-23","The day preceding of Lunar New Year's Day","KR",2001 +"2001-01-24","Lunar New Year's Day","KR",2001 +"2001-01-25","The second day of Lunar New Year's Day","KR",2001 +"2001-03-01","Independence Movement Day","KR",2001 +"2001-04-05","Tree Planting Day","KR",2001 +"2001-05-01","Birthday of the Buddha","KR",2001 +"2001-05-01","Labour Day","KR",2001 +"2001-05-05","Children's Day","KR",2001 +"2001-06-06","Memorial Day","KR",2001 +"2001-07-17","Constitution Day","KR",2001 +"2001-08-15","Liberation Day","KR",2001 +"2001-09-30","The day preceding of Chuseok","KR",2001 +"2001-10-01","Chuseok","KR",2001 +"2001-10-02","The second day of Chuseok","KR",2001 +"2001-10-03","National Foundation Day","KR",2001 +"2001-12-25","Christmas Day","KR",2001 +"2002-01-01","New Year's Day","KR",2002 +"2002-02-11","The day preceding of Lunar New Year's Day","KR",2002 +"2002-02-12","Lunar New Year's Day","KR",2002 +"2002-02-13","The second day of Lunar New Year's Day","KR",2002 +"2002-03-01","Independence Movement Day","KR",2002 +"2002-04-05","Tree Planting Day","KR",2002 +"2002-05-01","Labour Day","KR",2002 +"2002-05-05","Children's Day","KR",2002 +"2002-05-19","Birthday of the Buddha","KR",2002 +"2002-06-06","Memorial Day","KR",2002 +"2002-07-17","Constitution Day","KR",2002 +"2002-08-15","Liberation Day","KR",2002 +"2002-09-20","The day preceding of Chuseok","KR",2002 +"2002-09-21","Chuseok","KR",2002 +"2002-09-22","The second day of Chuseok","KR",2002 +"2002-10-03","National Foundation Day","KR",2002 +"2002-12-25","Christmas Day","KR",2002 +"2003-01-01","New Year's Day","KR",2003 +"2003-01-31","The day preceding of Lunar New Year's Day","KR",2003 +"2003-02-01","Lunar New Year's Day","KR",2003 +"2003-02-02","The second day of Lunar New Year's Day","KR",2003 +"2003-03-01","Independence Movement Day","KR",2003 +"2003-04-05","Tree Planting Day","KR",2003 +"2003-05-01","Labour Day","KR",2003 +"2003-05-05","Children's Day","KR",2003 +"2003-05-08","Birthday of the Buddha","KR",2003 +"2003-06-06","Memorial Day","KR",2003 +"2003-07-17","Constitution Day","KR",2003 +"2003-08-15","Liberation Day","KR",2003 +"2003-09-10","The day preceding of Chuseok","KR",2003 +"2003-09-11","Chuseok","KR",2003 +"2003-09-12","The second day of Chuseok","KR",2003 +"2003-10-03","National Foundation Day","KR",2003 +"2003-12-25","Christmas Day","KR",2003 +"2004-01-01","New Year's Day","KR",2004 +"2004-01-21","The day preceding of Lunar New Year's Day","KR",2004 +"2004-01-22","Lunar New Year's Day","KR",2004 +"2004-01-23","The second day of Lunar New Year's Day","KR",2004 +"2004-03-01","Independence Movement Day","KR",2004 +"2004-04-05","Tree Planting Day","KR",2004 +"2004-05-01","Labour Day","KR",2004 +"2004-05-05","Children's Day","KR",2004 +"2004-05-26","Birthday of the Buddha","KR",2004 +"2004-06-06","Memorial Day","KR",2004 +"2004-07-17","Constitution Day","KR",2004 +"2004-08-15","Liberation Day","KR",2004 +"2004-09-27","The day preceding of Chuseok","KR",2004 +"2004-09-28","Chuseok","KR",2004 +"2004-09-29","The second day of Chuseok","KR",2004 +"2004-10-03","National Foundation Day","KR",2004 +"2004-12-25","Christmas Day","KR",2004 +"2005-01-01","New Year's Day","KR",2005 +"2005-02-08","The day preceding of Lunar New Year's Day","KR",2005 +"2005-02-09","Lunar New Year's Day","KR",2005 +"2005-02-10","The second day of Lunar New Year's Day","KR",2005 +"2005-03-01","Independence Movement Day","KR",2005 +"2005-04-05","Tree Planting Day","KR",2005 +"2005-05-01","Labour Day","KR",2005 +"2005-05-05","Children's Day","KR",2005 +"2005-05-15","Birthday of the Buddha","KR",2005 +"2005-06-06","Memorial Day","KR",2005 +"2005-07-17","Constitution Day","KR",2005 +"2005-08-15","Liberation Day","KR",2005 +"2005-09-17","The day preceding of Chuseok","KR",2005 +"2005-09-18","Chuseok","KR",2005 +"2005-09-19","The second day of Chuseok","KR",2005 +"2005-10-03","National Foundation Day","KR",2005 +"2005-12-25","Christmas Day","KR",2005 +"2006-01-01","New Year's Day","KR",2006 +"2006-01-28","The day preceding of Lunar New Year's Day","KR",2006 +"2006-01-29","Lunar New Year's Day","KR",2006 +"2006-01-30","The second day of Lunar New Year's Day","KR",2006 +"2006-03-01","Independence Movement Day","KR",2006 +"2006-05-01","Labour Day","KR",2006 +"2006-05-05","Birthday of the Buddha","KR",2006 +"2006-05-05","Children's Day","KR",2006 +"2006-06-06","Memorial Day","KR",2006 +"2006-07-17","Constitution Day","KR",2006 +"2006-08-15","Liberation Day","KR",2006 +"2006-10-03","National Foundation Day","KR",2006 +"2006-10-05","The day preceding of Chuseok","KR",2006 +"2006-10-06","Chuseok","KR",2006 +"2006-10-07","The second day of Chuseok","KR",2006 +"2006-12-25","Christmas Day","KR",2006 +"2007-01-01","New Year's Day","KR",2007 +"2007-02-17","The day preceding of Lunar New Year's Day","KR",2007 +"2007-02-18","Lunar New Year's Day","KR",2007 +"2007-02-19","The second day of Lunar New Year's Day","KR",2007 +"2007-03-01","Independence Movement Day","KR",2007 +"2007-05-01","Labour Day","KR",2007 +"2007-05-05","Children's Day","KR",2007 +"2007-05-24","Birthday of the Buddha","KR",2007 +"2007-06-06","Memorial Day","KR",2007 +"2007-07-17","Constitution Day","KR",2007 +"2007-08-15","Liberation Day","KR",2007 +"2007-09-24","The day preceding of Chuseok","KR",2007 +"2007-09-25","Chuseok","KR",2007 +"2007-09-26","The second day of Chuseok","KR",2007 +"2007-10-03","National Foundation Day","KR",2007 +"2007-12-25","Christmas Day","KR",2007 +"2008-01-01","New Year's Day","KR",2008 +"2008-02-06","The day preceding of Lunar New Year's Day","KR",2008 +"2008-02-07","Lunar New Year's Day","KR",2008 +"2008-02-08","The second day of Lunar New Year's Day","KR",2008 +"2008-03-01","Independence Movement Day","KR",2008 +"2008-05-01","Labour Day","KR",2008 +"2008-05-05","Children's Day","KR",2008 +"2008-05-12","Birthday of the Buddha","KR",2008 +"2008-06-06","Memorial Day","KR",2008 +"2008-08-15","Liberation Day","KR",2008 +"2008-09-13","The day preceding of Chuseok","KR",2008 +"2008-09-14","Chuseok","KR",2008 +"2008-09-15","The second day of Chuseok","KR",2008 +"2008-10-03","National Foundation Day","KR",2008 +"2008-12-25","Christmas Day","KR",2008 +"2009-01-01","New Year's Day","KR",2009 +"2009-01-25","The day preceding of Lunar New Year's Day","KR",2009 +"2009-01-26","Lunar New Year's Day","KR",2009 +"2009-01-27","The second day of Lunar New Year's Day","KR",2009 +"2009-03-01","Independence Movement Day","KR",2009 +"2009-05-01","Labour Day","KR",2009 +"2009-05-02","Birthday of the Buddha","KR",2009 +"2009-05-05","Children's Day","KR",2009 +"2009-06-06","Memorial Day","KR",2009 +"2009-08-15","Liberation Day","KR",2009 +"2009-10-02","The day preceding of Chuseok","KR",2009 +"2009-10-03","Chuseok","KR",2009 +"2009-10-03","National Foundation Day","KR",2009 +"2009-10-04","The second day of Chuseok","KR",2009 +"2009-12-25","Christmas Day","KR",2009 +"2010-01-01","New Year's Day","KR",2010 +"2010-02-13","The day preceding of Lunar New Year's Day","KR",2010 +"2010-02-14","Lunar New Year's Day","KR",2010 +"2010-02-15","The second day of Lunar New Year's Day","KR",2010 +"2010-03-01","Independence Movement Day","KR",2010 +"2010-05-01","Labour Day","KR",2010 +"2010-05-05","Children's Day","KR",2010 +"2010-05-21","Birthday of the Buddha","KR",2010 +"2010-06-06","Memorial Day","KR",2010 +"2010-08-15","Liberation Day","KR",2010 +"2010-09-21","The day preceding of Chuseok","KR",2010 +"2010-09-22","Chuseok","KR",2010 +"2010-09-23","The second day of Chuseok","KR",2010 +"2010-10-03","National Foundation Day","KR",2010 +"2010-12-25","Christmas Day","KR",2010 +"2011-01-01","New Year's Day","KR",2011 +"2011-02-02","The day preceding of Lunar New Year's Day","KR",2011 +"2011-02-03","Lunar New Year's Day","KR",2011 +"2011-02-04","The second day of Lunar New Year's Day","KR",2011 +"2011-03-01","Independence Movement Day","KR",2011 +"2011-05-01","Labour Day","KR",2011 +"2011-05-05","Children's Day","KR",2011 +"2011-05-10","Birthday of the Buddha","KR",2011 +"2011-06-06","Memorial Day","KR",2011 +"2011-08-15","Liberation Day","KR",2011 +"2011-09-11","The day preceding of Chuseok","KR",2011 +"2011-09-12","Chuseok","KR",2011 +"2011-09-13","The second day of Chuseok","KR",2011 +"2011-10-03","National Foundation Day","KR",2011 +"2011-12-25","Christmas Day","KR",2011 +"2012-01-01","New Year's Day","KR",2012 +"2012-01-22","The day preceding of Lunar New Year's Day","KR",2012 +"2012-01-23","Lunar New Year's Day","KR",2012 +"2012-01-24","The second day of Lunar New Year's Day","KR",2012 +"2012-03-01","Independence Movement Day","KR",2012 +"2012-05-01","Labour Day","KR",2012 +"2012-05-05","Children's Day","KR",2012 +"2012-05-28","Birthday of the Buddha","KR",2012 +"2012-06-06","Memorial Day","KR",2012 +"2012-08-15","Liberation Day","KR",2012 +"2012-09-29","The day preceding of Chuseok","KR",2012 +"2012-09-30","Chuseok","KR",2012 +"2012-10-01","The second day of Chuseok","KR",2012 +"2012-10-03","National Foundation Day","KR",2012 +"2012-12-25","Christmas Day","KR",2012 +"2013-01-01","New Year's Day","KR",2013 +"2013-02-09","The day preceding of Lunar New Year's Day","KR",2013 +"2013-02-10","Lunar New Year's Day","KR",2013 +"2013-02-11","The second day of Lunar New Year's Day","KR",2013 +"2013-03-01","Independence Movement Day","KR",2013 +"2013-05-01","Labour Day","KR",2013 +"2013-05-05","Children's Day","KR",2013 +"2013-05-17","Birthday of the Buddha","KR",2013 +"2013-06-06","Memorial Day","KR",2013 +"2013-08-15","Liberation Day","KR",2013 +"2013-09-18","The day preceding of Chuseok","KR",2013 +"2013-09-19","Chuseok","KR",2013 +"2013-09-20","The second day of Chuseok","KR",2013 +"2013-10-03","National Foundation Day","KR",2013 +"2013-10-09","Hangeul Day","KR",2013 +"2013-12-25","Christmas Day","KR",2013 +"2014-01-01","New Year's Day","KR",2014 +"2014-01-30","The day preceding of Lunar New Year's Day","KR",2014 +"2014-01-31","Lunar New Year's Day","KR",2014 +"2014-02-01","The second day of Lunar New Year's Day","KR",2014 +"2014-03-01","Independence Movement Day","KR",2014 +"2014-05-01","Labour Day","KR",2014 +"2014-05-05","Children's Day","KR",2014 +"2014-05-06","Birthday of the Buddha","KR",2014 +"2014-06-06","Memorial Day","KR",2014 +"2014-08-15","Liberation Day","KR",2014 +"2014-09-07","The day preceding of Chuseok","KR",2014 +"2014-09-08","Chuseok","KR",2014 +"2014-09-09","The second day of Chuseok","KR",2014 +"2014-09-10","Alternative holiday of Chuseok","KR",2014 +"2014-10-03","National Foundation Day","KR",2014 +"2014-10-09","Hangeul Day","KR",2014 +"2014-12-25","Christmas Day","KR",2014 +"2015-01-01","New Year's Day","KR",2015 +"2015-02-18","The day preceding of Lunar New Year's Day","KR",2015 +"2015-02-19","Lunar New Year's Day","KR",2015 +"2015-02-20","The second day of Lunar New Year's Day","KR",2015 +"2015-03-01","Independence Movement Day","KR",2015 +"2015-05-01","Labour Day","KR",2015 +"2015-05-05","Children's Day","KR",2015 +"2015-05-25","Birthday of the Buddha","KR",2015 +"2015-06-06","Memorial Day","KR",2015 +"2015-08-15","Liberation Day","KR",2015 +"2015-09-26","The day preceding of Chuseok","KR",2015 +"2015-09-27","Chuseok","KR",2015 +"2015-09-28","The second day of Chuseok","KR",2015 +"2015-09-29","Alternative holiday of Chuseok","KR",2015 +"2015-10-03","National Foundation Day","KR",2015 +"2015-10-09","Hangeul Day","KR",2015 +"2015-12-25","Christmas Day","KR",2015 +"2016-01-01","New Year's Day","KR",2016 +"2016-02-07","The day preceding of Lunar New Year's Day","KR",2016 +"2016-02-08","Lunar New Year's Day","KR",2016 +"2016-02-09","The second day of Lunar New Year's Day","KR",2016 +"2016-02-10","Alternative holiday of Lunar New Year's Day","KR",2016 +"2016-03-01","Independence Movement Day","KR",2016 +"2016-05-01","Labour Day","KR",2016 +"2016-05-05","Children's Day","KR",2016 +"2016-05-14","Birthday of the Buddha","KR",2016 +"2016-06-06","Memorial Day","KR",2016 +"2016-08-15","Liberation Day","KR",2016 +"2016-09-14","The day preceding of Chuseok","KR",2016 +"2016-09-15","Chuseok","KR",2016 +"2016-09-16","The second day of Chuseok","KR",2016 +"2016-10-03","National Foundation Day","KR",2016 +"2016-10-09","Hangeul Day","KR",2016 +"2016-12-25","Christmas Day","KR",2016 +"2017-01-01","New Year's Day","KR",2017 +"2017-01-27","The day preceding of Lunar New Year's Day","KR",2017 +"2017-01-28","Lunar New Year's Day","KR",2017 +"2017-01-29","The second day of Lunar New Year's Day","KR",2017 +"2017-01-30","Alternative holiday of Lunar New Year's Day","KR",2017 +"2017-03-01","Independence Movement Day","KR",2017 +"2017-05-01","Labour Day","KR",2017 +"2017-05-03","Birthday of the Buddha","KR",2017 +"2017-05-05","Children's Day","KR",2017 +"2017-06-06","Memorial Day","KR",2017 +"2017-08-15","Liberation Day","KR",2017 +"2017-10-03","National Foundation Day","KR",2017 +"2017-10-03","The day preceding of Chuseok","KR",2017 +"2017-10-04","Chuseok","KR",2017 +"2017-10-05","The second day of Chuseok","KR",2017 +"2017-10-09","Hangeul Day","KR",2017 +"2017-12-25","Christmas Day","KR",2017 +"2018-01-01","New Year's Day","KR",2018 +"2018-02-15","The day preceding of Lunar New Year's Day","KR",2018 +"2018-02-16","Lunar New Year's Day","KR",2018 +"2018-02-17","The second day of Lunar New Year's Day","KR",2018 +"2018-03-01","Independence Movement Day","KR",2018 +"2018-05-01","Labour Day","KR",2018 +"2018-05-05","Children's Day","KR",2018 +"2018-05-07","Alternative holiday of Children's Day","KR",2018 +"2018-05-22","Birthday of the Buddha","KR",2018 +"2018-06-06","Memorial Day","KR",2018 +"2018-08-15","Liberation Day","KR",2018 +"2018-09-23","The day preceding of Chuseok","KR",2018 +"2018-09-24","Chuseok","KR",2018 +"2018-09-25","The second day of Chuseok","KR",2018 +"2018-09-26","Alternative holiday of Chuseok","KR",2018 +"2018-10-03","National Foundation Day","KR",2018 +"2018-10-09","Hangeul Day","KR",2018 +"2018-12-25","Christmas Day","KR",2018 +"2019-01-01","New Year's Day","KR",2019 +"2019-02-04","The day preceding of Lunar New Year's Day","KR",2019 +"2019-02-05","Lunar New Year's Day","KR",2019 +"2019-02-06","The second day of Lunar New Year's Day","KR",2019 +"2019-03-01","Independence Movement Day","KR",2019 +"2019-05-01","Labour Day","KR",2019 +"2019-05-05","Children's Day","KR",2019 +"2019-05-06","Alternative holiday of Children's Day","KR",2019 +"2019-05-12","Birthday of the Buddha","KR",2019 +"2019-06-06","Memorial Day","KR",2019 +"2019-08-15","Liberation Day","KR",2019 +"2019-09-12","The day preceding of Chuseok","KR",2019 +"2019-09-13","Chuseok","KR",2019 +"2019-09-14","The second day of Chuseok","KR",2019 +"2019-10-03","National Foundation Day","KR",2019 +"2019-10-09","Hangeul Day","KR",2019 +"2019-12-25","Christmas Day","KR",2019 +"2020-01-01","New Year's Day","KR",2020 +"2020-01-24","The day preceding of Lunar New Year's Day","KR",2020 +"2020-01-25","Lunar New Year's Day","KR",2020 +"2020-01-26","The second day of Lunar New Year's Day","KR",2020 +"2020-01-27","Alternative holiday of Lunar New Year's Day","KR",2020 +"2020-03-01","Independence Movement Day","KR",2020 +"2020-04-30","Birthday of the Buddha","KR",2020 +"2020-05-01","Labour Day","KR",2020 +"2020-05-05","Children's Day","KR",2020 +"2020-06-06","Memorial Day","KR",2020 +"2020-08-15","Liberation Day","KR",2020 +"2020-08-17","Alternative public holiday","KR",2020 +"2020-09-30","The day preceding of Chuseok","KR",2020 +"2020-10-01","Chuseok","KR",2020 +"2020-10-02","The second day of Chuseok","KR",2020 +"2020-10-03","National Foundation Day","KR",2020 +"2020-10-09","Hangeul Day","KR",2020 +"2020-12-25","Christmas Day","KR",2020 +"2021-01-01","New Year's Day","KR",2021 +"2021-02-11","The day preceding of Lunar New Year's Day","KR",2021 +"2021-02-12","Lunar New Year's Day","KR",2021 +"2021-02-13","The second day of Lunar New Year's Day","KR",2021 +"2021-03-01","Independence Movement Day","KR",2021 +"2021-05-01","Labour Day","KR",2021 +"2021-05-05","Children's Day","KR",2021 +"2021-05-19","Birthday of the Buddha","KR",2021 +"2021-06-06","Memorial Day","KR",2021 +"2021-08-15","Liberation Day","KR",2021 +"2021-08-16","Alternative holiday of Liberation Day","KR",2021 +"2021-09-20","The day preceding of Chuseok","KR",2021 +"2021-09-21","Chuseok","KR",2021 +"2021-09-22","The second day of Chuseok","KR",2021 +"2021-10-03","National Foundation Day","KR",2021 +"2021-10-04","Alternative holiday of National Foundation Day","KR",2021 +"2021-10-09","Hangeul Day","KR",2021 +"2021-10-11","Alternative holiday of Hangeul Day","KR",2021 +"2021-12-25","Christmas Day","KR",2021 +"2022-01-01","New Year's Day","KR",2022 +"2022-01-31","The day preceding of Lunar New Year's Day","KR",2022 +"2022-02-01","Lunar New Year's Day","KR",2022 +"2022-02-02","The second day of Lunar New Year's Day","KR",2022 +"2022-03-01","Independence Movement Day","KR",2022 +"2022-05-01","Labour Day","KR",2022 +"2022-05-05","Children's Day","KR",2022 +"2022-05-08","Birthday of the Buddha","KR",2022 +"2022-06-06","Memorial Day","KR",2022 +"2022-08-15","Liberation Day","KR",2022 +"2022-09-09","The day preceding of Chuseok","KR",2022 +"2022-09-10","Chuseok","KR",2022 +"2022-09-11","The second day of Chuseok","KR",2022 +"2022-09-12","Alternative holiday of Chuseok","KR",2022 +"2022-10-03","National Foundation Day","KR",2022 +"2022-10-09","Hangeul Day","KR",2022 +"2022-10-10","Alternative holiday of Hangeul Day","KR",2022 +"2022-12-25","Christmas Day","KR",2022 +"2023-01-01","New Year's Day","KR",2023 +"2023-01-21","The day preceding of Lunar New Year's Day","KR",2023 +"2023-01-22","Lunar New Year's Day","KR",2023 +"2023-01-23","The second day of Lunar New Year's Day","KR",2023 +"2023-01-24","Alternative holiday of Lunar New Year's Day","KR",2023 +"2023-03-01","Independence Movement Day","KR",2023 +"2023-05-01","Labour Day","KR",2023 +"2023-05-05","Children's Day","KR",2023 +"2023-05-27","Birthday of the Buddha","KR",2023 +"2023-06-06","Memorial Day","KR",2023 +"2023-08-15","Liberation Day","KR",2023 +"2023-09-28","The day preceding of Chuseok","KR",2023 +"2023-09-29","Chuseok","KR",2023 +"2023-09-30","The second day of Chuseok","KR",2023 +"2023-10-03","National Foundation Day","KR",2023 +"2023-10-09","Hangeul Day","KR",2023 +"2023-12-25","Christmas Day","KR",2023 +"2024-01-01","New Year's Day","KR",2024 +"2024-02-09","The day preceding of Lunar New Year's Day","KR",2024 +"2024-02-10","Lunar New Year's Day","KR",2024 +"2024-02-11","The second day of Lunar New Year's Day","KR",2024 +"2024-02-12","Alternative holiday of Lunar New Year's Day","KR",2024 +"2024-03-01","Independence Movement Day","KR",2024 +"2024-05-01","Labour Day","KR",2024 +"2024-05-05","Children's Day","KR",2024 +"2024-05-06","Alternative holiday of Children's Day","KR",2024 +"2024-05-15","Birthday of the Buddha","KR",2024 +"2024-06-06","Memorial Day","KR",2024 +"2024-08-15","Liberation Day","KR",2024 +"2024-09-16","The day preceding of Chuseok","KR",2024 +"2024-09-17","Chuseok","KR",2024 +"2024-09-18","The second day of Chuseok","KR",2024 +"2024-10-03","National Foundation Day","KR",2024 +"2024-10-09","Hangeul Day","KR",2024 +"2024-12-25","Christmas Day","KR",2024 +"2025-01-01","New Year's Day","KR",2025 +"2025-01-28","The day preceding of Lunar New Year's Day","KR",2025 +"2025-01-29","Lunar New Year's Day","KR",2025 +"2025-01-30","The second day of Lunar New Year's Day","KR",2025 +"2025-03-01","Independence Movement Day","KR",2025 +"2025-03-03","Alternative holiday of Independence Movement Day","KR",2025 +"2025-05-01","Labour Day","KR",2025 +"2025-05-05","Birthday of the Buddha","KR",2025 +"2025-05-05","Children's Day","KR",2025 +"2025-05-06","Alternative holiday of Children's Day","KR",2025 +"2025-06-06","Memorial Day","KR",2025 +"2025-08-15","Liberation Day","KR",2025 +"2025-10-03","National Foundation Day","KR",2025 +"2025-10-05","The day preceding of Chuseok","KR",2025 +"2025-10-06","Chuseok","KR",2025 +"2025-10-07","The second day of Chuseok","KR",2025 +"2025-10-08","Alternative holiday of Chuseok","KR",2025 +"2025-10-09","Hangeul Day","KR",2025 +"2025-12-25","Christmas Day","KR",2025 +"2026-01-01","New Year's Day","KR",2026 +"2026-02-16","The day preceding of Lunar New Year's Day","KR",2026 +"2026-02-17","Lunar New Year's Day","KR",2026 +"2026-02-18","The second day of Lunar New Year's Day","KR",2026 +"2026-03-01","Independence Movement Day","KR",2026 +"2026-03-02","Alternative holiday of Independence Movement Day","KR",2026 +"2026-05-01","Labour Day","KR",2026 +"2026-05-05","Children's Day","KR",2026 +"2026-05-24","Birthday of the Buddha","KR",2026 +"2026-06-06","Memorial Day","KR",2026 +"2026-08-15","Liberation Day","KR",2026 +"2026-08-17","Alternative holiday of Liberation Day","KR",2026 +"2026-09-24","The day preceding of Chuseok","KR",2026 +"2026-09-25","Chuseok","KR",2026 +"2026-09-26","The second day of Chuseok","KR",2026 +"2026-10-03","National Foundation Day","KR",2026 +"2026-10-05","Alternative holiday of National Foundation Day","KR",2026 +"2026-10-09","Hangeul Day","KR",2026 +"2026-12-25","Christmas Day","KR",2026 +"2027-01-01","New Year's Day","KR",2027 +"2027-02-06","The day preceding of Lunar New Year's Day","KR",2027 +"2027-02-07","Lunar New Year's Day","KR",2027 +"2027-02-08","The second day of Lunar New Year's Day","KR",2027 +"2027-02-09","Alternative holiday of Lunar New Year's Day","KR",2027 +"2027-03-01","Independence Movement Day","KR",2027 +"2027-05-01","Labour Day","KR",2027 +"2027-05-05","Children's Day","KR",2027 +"2027-05-13","Birthday of the Buddha","KR",2027 +"2027-06-06","Memorial Day","KR",2027 +"2027-08-15","Liberation Day","KR",2027 +"2027-08-16","Alternative holiday of Liberation Day","KR",2027 +"2027-09-14","The day preceding of Chuseok","KR",2027 +"2027-09-15","Chuseok","KR",2027 +"2027-09-16","The second day of Chuseok","KR",2027 +"2027-10-03","National Foundation Day","KR",2027 +"2027-10-04","Alternative holiday of National Foundation Day","KR",2027 +"2027-10-09","Hangeul Day","KR",2027 +"2027-10-11","Alternative holiday of Hangeul Day","KR",2027 +"2027-12-25","Christmas Day","KR",2027 +"2028-01-01","New Year's Day","KR",2028 +"2028-01-26","The day preceding of Lunar New Year's Day","KR",2028 +"2028-01-27","Lunar New Year's Day","KR",2028 +"2028-01-28","The second day of Lunar New Year's Day","KR",2028 +"2028-03-01","Independence Movement Day","KR",2028 +"2028-05-01","Labour Day","KR",2028 +"2028-05-02","Birthday of the Buddha","KR",2028 +"2028-05-05","Children's Day","KR",2028 +"2028-06-06","Memorial Day","KR",2028 +"2028-08-15","Liberation Day","KR",2028 +"2028-10-02","The day preceding of Chuseok","KR",2028 +"2028-10-03","Chuseok","KR",2028 +"2028-10-03","National Foundation Day","KR",2028 +"2028-10-04","The second day of Chuseok","KR",2028 +"2028-10-05","Alternative holiday of National Foundation Day","KR",2028 +"2028-10-09","Hangeul Day","KR",2028 +"2028-12-25","Christmas Day","KR",2028 +"2029-01-01","New Year's Day","KR",2029 +"2029-02-12","The day preceding of Lunar New Year's Day","KR",2029 +"2029-02-13","Lunar New Year's Day","KR",2029 +"2029-02-14","The second day of Lunar New Year's Day","KR",2029 +"2029-03-01","Independence Movement Day","KR",2029 +"2029-05-01","Labour Day","KR",2029 +"2029-05-05","Children's Day","KR",2029 +"2029-05-07","Alternative holiday of Children's Day","KR",2029 +"2029-05-20","Birthday of the Buddha","KR",2029 +"2029-06-06","Memorial Day","KR",2029 +"2029-08-15","Liberation Day","KR",2029 +"2029-09-21","The day preceding of Chuseok","KR",2029 +"2029-09-22","Chuseok","KR",2029 +"2029-09-23","The second day of Chuseok","KR",2029 +"2029-09-24","Alternative holiday of Chuseok","KR",2029 +"2029-10-03","National Foundation Day","KR",2029 +"2029-10-09","Hangeul Day","KR",2029 +"2029-12-25","Christmas Day","KR",2029 +"2030-01-01","New Year's Day","KR",2030 +"2030-02-02","The day preceding of Lunar New Year's Day","KR",2030 +"2030-02-03","Lunar New Year's Day","KR",2030 +"2030-02-04","The second day of Lunar New Year's Day","KR",2030 +"2030-02-05","Alternative holiday of Lunar New Year's Day","KR",2030 +"2030-03-01","Independence Movement Day","KR",2030 +"2030-05-01","Labour Day","KR",2030 +"2030-05-05","Children's Day","KR",2030 +"2030-05-06","Alternative holiday of Children's Day","KR",2030 +"2030-05-09","Birthday of the Buddha","KR",2030 +"2030-06-06","Memorial Day","KR",2030 +"2030-08-15","Liberation Day","KR",2030 +"2030-09-11","The day preceding of Chuseok","KR",2030 +"2030-09-12","Chuseok","KR",2030 +"2030-09-13","The second day of Chuseok","KR",2030 +"2030-10-03","National Foundation Day","KR",2030 +"2030-10-09","Hangeul Day","KR",2030 +"2030-12-25","Christmas Day","KR",2030 +"2031-01-01","New Year's Day","KR",2031 +"2031-01-22","The day preceding of Lunar New Year's Day","KR",2031 +"2031-01-23","Lunar New Year's Day","KR",2031 +"2031-01-24","The second day of Lunar New Year's Day","KR",2031 +"2031-03-01","Independence Movement Day","KR",2031 +"2031-03-03","Alternative holiday of Independence Movement Day","KR",2031 +"2031-05-01","Labour Day","KR",2031 +"2031-05-05","Children's Day","KR",2031 +"2031-05-28","Birthday of the Buddha","KR",2031 +"2031-06-06","Memorial Day","KR",2031 +"2031-08-15","Liberation Day","KR",2031 +"2031-09-30","The day preceding of Chuseok","KR",2031 +"2031-10-01","Chuseok","KR",2031 +"2031-10-02","The second day of Chuseok","KR",2031 +"2031-10-03","National Foundation Day","KR",2031 +"2031-10-09","Hangeul Day","KR",2031 +"2031-12-25","Christmas Day","KR",2031 +"2032-01-01","New Year's Day","KR",2032 +"2032-02-10","The day preceding of Lunar New Year's Day","KR",2032 +"2032-02-11","Lunar New Year's Day","KR",2032 +"2032-02-12","The second day of Lunar New Year's Day","KR",2032 +"2032-03-01","Independence Movement Day","KR",2032 +"2032-05-01","Labour Day","KR",2032 +"2032-05-05","Children's Day","KR",2032 +"2032-05-16","Birthday of the Buddha","KR",2032 +"2032-06-06","Memorial Day","KR",2032 +"2032-08-15","Liberation Day","KR",2032 +"2032-08-16","Alternative holiday of Liberation Day","KR",2032 +"2032-09-18","The day preceding of Chuseok","KR",2032 +"2032-09-19","Chuseok","KR",2032 +"2032-09-20","The second day of Chuseok","KR",2032 +"2032-09-21","Alternative holiday of Chuseok","KR",2032 +"2032-10-03","National Foundation Day","KR",2032 +"2032-10-04","Alternative holiday of National Foundation Day","KR",2032 +"2032-10-09","Hangeul Day","KR",2032 +"2032-10-11","Alternative holiday of Hangeul Day","KR",2032 +"2032-12-25","Christmas Day","KR",2032 +"2033-01-01","New Year's Day","KR",2033 +"2033-01-30","The day preceding of Lunar New Year's Day","KR",2033 +"2033-01-31","Lunar New Year's Day","KR",2033 +"2033-02-01","The second day of Lunar New Year's Day","KR",2033 +"2033-02-02","Alternative holiday of Lunar New Year's Day","KR",2033 +"2033-03-01","Independence Movement Day","KR",2033 +"2033-05-01","Labour Day","KR",2033 +"2033-05-05","Children's Day","KR",2033 +"2033-05-06","Birthday of the Buddha","KR",2033 +"2033-06-06","Memorial Day","KR",2033 +"2033-08-15","Liberation Day","KR",2033 +"2033-09-07","The day preceding of Chuseok","KR",2033 +"2033-09-08","Chuseok","KR",2033 +"2033-09-09","The second day of Chuseok","KR",2033 +"2033-10-03","National Foundation Day","KR",2033 +"2033-10-09","Hangeul Day","KR",2033 +"2033-10-10","Alternative holiday of Hangeul Day","KR",2033 +"2033-12-25","Christmas Day","KR",2033 +"2034-01-01","New Year's Day","KR",2034 +"2034-02-18","The day preceding of Lunar New Year's Day","KR",2034 +"2034-02-19","Lunar New Year's Day","KR",2034 +"2034-02-20","The second day of Lunar New Year's Day","KR",2034 +"2034-02-21","Alternative holiday of Lunar New Year's Day","KR",2034 +"2034-03-01","Independence Movement Day","KR",2034 +"2034-05-01","Labour Day","KR",2034 +"2034-05-05","Children's Day","KR",2034 +"2034-05-25","Birthday of the Buddha","KR",2034 +"2034-06-06","Memorial Day","KR",2034 +"2034-08-15","Liberation Day","KR",2034 +"2034-09-26","The day preceding of Chuseok","KR",2034 +"2034-09-27","Chuseok","KR",2034 +"2034-09-28","The second day of Chuseok","KR",2034 +"2034-10-03","National Foundation Day","KR",2034 +"2034-10-09","Hangeul Day","KR",2034 +"2034-12-25","Christmas Day","KR",2034 +"2035-01-01","New Year's Day","KR",2035 +"2035-02-07","The day preceding of Lunar New Year's Day","KR",2035 +"2035-02-08","Lunar New Year's Day","KR",2035 +"2035-02-09","The second day of Lunar New Year's Day","KR",2035 +"2035-03-01","Independence Movement Day","KR",2035 +"2035-05-01","Labour Day","KR",2035 +"2035-05-05","Children's Day","KR",2035 +"2035-05-07","Alternative holiday of Children's Day","KR",2035 +"2035-05-15","Birthday of the Buddha","KR",2035 +"2035-06-06","Memorial Day","KR",2035 +"2035-08-15","Liberation Day","KR",2035 +"2035-09-15","The day preceding of Chuseok","KR",2035 +"2035-09-16","Chuseok","KR",2035 +"2035-09-17","The second day of Chuseok","KR",2035 +"2035-09-18","Alternative holiday of Chuseok","KR",2035 +"2035-10-03","National Foundation Day","KR",2035 +"2035-10-09","Hangeul Day","KR",2035 +"2035-12-25","Christmas Day","KR",2035 +"2036-01-01","New Year's Day","KR",2036 +"2036-01-27","The day preceding of Lunar New Year's Day","KR",2036 +"2036-01-28","Lunar New Year's Day","KR",2036 +"2036-01-29","The second day of Lunar New Year's Day","KR",2036 +"2036-01-30","Alternative holiday of Lunar New Year's Day","KR",2036 +"2036-03-01","Independence Movement Day","KR",2036 +"2036-03-03","Alternative holiday of Independence Movement Day","KR",2036 +"2036-05-01","Labour Day","KR",2036 +"2036-05-03","Birthday of the Buddha","KR",2036 +"2036-05-05","Children's Day","KR",2036 +"2036-06-06","Memorial Day","KR",2036 +"2036-08-15","Liberation Day","KR",2036 +"2036-10-03","National Foundation Day","KR",2036 +"2036-10-03","The day preceding of Chuseok","KR",2036 +"2036-10-04","Chuseok","KR",2036 +"2036-10-05","The second day of Chuseok","KR",2036 +"2036-10-06","Alternative holiday of Chuseok","KR",2036 +"2036-10-07","Alternative holiday of National Foundation Day","KR",2036 +"2036-10-09","Hangeul Day","KR",2036 +"2036-12-25","Christmas Day","KR",2036 +"2037-01-01","New Year's Day","KR",2037 +"2037-02-14","The day preceding of Lunar New Year's Day","KR",2037 +"2037-02-15","Lunar New Year's Day","KR",2037 +"2037-02-16","The second day of Lunar New Year's Day","KR",2037 +"2037-02-17","Alternative holiday of Lunar New Year's Day","KR",2037 +"2037-03-01","Independence Movement Day","KR",2037 +"2037-03-02","Alternative holiday of Independence Movement Day","KR",2037 +"2037-05-01","Labour Day","KR",2037 +"2037-05-05","Children's Day","KR",2037 +"2037-05-22","Birthday of the Buddha","KR",2037 +"2037-06-06","Memorial Day","KR",2037 +"2037-08-15","Liberation Day","KR",2037 +"2037-08-17","Alternative holiday of Liberation Day","KR",2037 +"2037-09-23","The day preceding of Chuseok","KR",2037 +"2037-09-24","Chuseok","KR",2037 +"2037-09-25","The second day of Chuseok","KR",2037 +"2037-10-03","National Foundation Day","KR",2037 +"2037-10-05","Alternative holiday of National Foundation Day","KR",2037 +"2037-10-09","Hangeul Day","KR",2037 +"2037-12-25","Christmas Day","KR",2037 +"2038-01-01","New Year's Day","KR",2038 +"2038-02-03","The day preceding of Lunar New Year's Day","KR",2038 +"2038-02-04","Lunar New Year's Day","KR",2038 +"2038-02-05","The second day of Lunar New Year's Day","KR",2038 +"2038-03-01","Independence Movement Day","KR",2038 +"2038-05-01","Labour Day","KR",2038 +"2038-05-05","Children's Day","KR",2038 +"2038-05-11","Birthday of the Buddha","KR",2038 +"2038-06-06","Memorial Day","KR",2038 +"2038-08-15","Liberation Day","KR",2038 +"2038-08-16","Alternative holiday of Liberation Day","KR",2038 +"2038-09-12","The day preceding of Chuseok","KR",2038 +"2038-09-13","Chuseok","KR",2038 +"2038-09-14","The second day of Chuseok","KR",2038 +"2038-09-15","Alternative holiday of Chuseok","KR",2038 +"2038-10-03","National Foundation Day","KR",2038 +"2038-10-04","Alternative holiday of National Foundation Day","KR",2038 +"2038-10-09","Hangeul Day","KR",2038 +"2038-10-11","Alternative holiday of Hangeul Day","KR",2038 +"2038-12-25","Christmas Day","KR",2038 +"2039-01-01","New Year's Day","KR",2039 +"2039-01-23","The day preceding of Lunar New Year's Day","KR",2039 +"2039-01-24","Lunar New Year's Day","KR",2039 +"2039-01-25","The second day of Lunar New Year's Day","KR",2039 +"2039-01-26","Alternative holiday of Lunar New Year's Day","KR",2039 +"2039-03-01","Independence Movement Day","KR",2039 +"2039-04-30","Birthday of the Buddha","KR",2039 +"2039-05-01","Labour Day","KR",2039 +"2039-05-05","Children's Day","KR",2039 +"2039-06-06","Memorial Day","KR",2039 +"2039-08-15","Liberation Day","KR",2039 +"2039-10-01","The day preceding of Chuseok","KR",2039 +"2039-10-02","Chuseok","KR",2039 +"2039-10-03","National Foundation Day","KR",2039 +"2039-10-03","The second day of Chuseok","KR",2039 +"2039-10-04","Alternative holiday of Chuseok","KR",2039 +"2039-10-05","Alternative holiday of National Foundation Day","KR",2039 +"2039-10-09","Hangeul Day","KR",2039 +"2039-10-10","Alternative holiday of Hangeul Day","KR",2039 +"2039-12-25","Christmas Day","KR",2039 +"2040-01-01","New Year's Day","KR",2040 +"2040-02-11","The day preceding of Lunar New Year's Day","KR",2040 +"2040-02-12","Lunar New Year's Day","KR",2040 +"2040-02-13","The second day of Lunar New Year's Day","KR",2040 +"2040-02-14","Alternative holiday of Lunar New Year's Day","KR",2040 +"2040-03-01","Independence Movement Day","KR",2040 +"2040-05-01","Labour Day","KR",2040 +"2040-05-05","Children's Day","KR",2040 +"2040-05-07","Alternative holiday of Children's Day","KR",2040 +"2040-05-18","Birthday of the Buddha","KR",2040 +"2040-06-06","Memorial Day","KR",2040 +"2040-08-15","Liberation Day","KR",2040 +"2040-09-20","The day preceding of Chuseok","KR",2040 +"2040-09-21","Chuseok","KR",2040 +"2040-09-22","The second day of Chuseok","KR",2040 +"2040-10-03","National Foundation Day","KR",2040 +"2040-10-09","Hangeul Day","KR",2040 +"2040-12-25","Christmas Day","KR",2040 +"2041-01-01","New Year's Day","KR",2041 +"2041-01-31","The day preceding of Lunar New Year's Day","KR",2041 +"2041-02-01","Lunar New Year's Day","KR",2041 +"2041-02-02","The second day of Lunar New Year's Day","KR",2041 +"2041-03-01","Independence Movement Day","KR",2041 +"2041-05-01","Labour Day","KR",2041 +"2041-05-05","Children's Day","KR",2041 +"2041-05-06","Alternative holiday of Children's Day","KR",2041 +"2041-05-07","Birthday of the Buddha","KR",2041 +"2041-06-06","Memorial Day","KR",2041 +"2041-08-15","Liberation Day","KR",2041 +"2041-09-09","The day preceding of Chuseok","KR",2041 +"2041-09-10","Chuseok","KR",2041 +"2041-09-11","The second day of Chuseok","KR",2041 +"2041-10-03","National Foundation Day","KR",2041 +"2041-10-09","Hangeul Day","KR",2041 +"2041-12-25","Christmas Day","KR",2041 +"2042-01-01","New Year's Day","KR",2042 +"2042-01-21","The day preceding of Lunar New Year's Day","KR",2042 +"2042-01-22","Lunar New Year's Day","KR",2042 +"2042-01-23","The second day of Lunar New Year's Day","KR",2042 +"2042-03-01","Independence Movement Day","KR",2042 +"2042-03-03","Alternative holiday of Independence Movement Day","KR",2042 +"2042-05-01","Labour Day","KR",2042 +"2042-05-05","Children's Day","KR",2042 +"2042-05-26","Birthday of the Buddha","KR",2042 +"2042-06-06","Memorial Day","KR",2042 +"2042-08-15","Liberation Day","KR",2042 +"2042-09-27","The day preceding of Chuseok","KR",2042 +"2042-09-28","Chuseok","KR",2042 +"2042-09-29","The second day of Chuseok","KR",2042 +"2042-09-30","Alternative holiday of Chuseok","KR",2042 +"2042-10-03","National Foundation Day","KR",2042 +"2042-10-09","Hangeul Day","KR",2042 +"2042-12-25","Christmas Day","KR",2042 +"2043-01-01","New Year's Day","KR",2043 +"2043-02-09","The day preceding of Lunar New Year's Day","KR",2043 +"2043-02-10","Lunar New Year's Day","KR",2043 +"2043-02-11","The second day of Lunar New Year's Day","KR",2043 +"2043-03-01","Independence Movement Day","KR",2043 +"2043-03-02","Alternative holiday of Independence Movement Day","KR",2043 +"2043-05-01","Labour Day","KR",2043 +"2043-05-05","Children's Day","KR",2043 +"2043-05-16","Birthday of the Buddha","KR",2043 +"2043-06-06","Memorial Day","KR",2043 +"2043-08-15","Liberation Day","KR",2043 +"2043-08-17","Alternative holiday of Liberation Day","KR",2043 +"2043-09-16","The day preceding of Chuseok","KR",2043 +"2043-09-17","Chuseok","KR",2043 +"2043-09-18","The second day of Chuseok","KR",2043 +"2043-10-03","National Foundation Day","KR",2043 +"2043-10-05","Alternative holiday of National Foundation Day","KR",2043 +"2043-10-09","Hangeul Day","KR",2043 +"2043-12-25","Christmas Day","KR",2043 +"2044-01-01","New Year's Day","KR",2044 +"2044-01-29","The day preceding of Lunar New Year's Day","KR",2044 +"2044-01-30","Lunar New Year's Day","KR",2044 +"2044-01-31","The second day of Lunar New Year's Day","KR",2044 +"2044-02-01","Alternative holiday of Lunar New Year's Day","KR",2044 +"2044-03-01","Independence Movement Day","KR",2044 +"2044-05-01","Labour Day","KR",2044 +"2044-05-05","Birthday of the Buddha","KR",2044 +"2044-05-05","Children's Day","KR",2044 +"2044-05-06","Alternative holiday of Children's Day","KR",2044 +"2044-06-06","Memorial Day","KR",2044 +"2044-08-15","Liberation Day","KR",2044 +"2044-10-03","National Foundation Day","KR",2044 +"2044-10-04","The day preceding of Chuseok","KR",2044 +"2044-10-05","Chuseok","KR",2044 +"2044-10-06","The second day of Chuseok","KR",2044 +"2044-10-09","Hangeul Day","KR",2044 +"2044-10-10","Alternative holiday of Hangeul Day","KR",2044 +"2044-12-25","Christmas Day","KR",2044 +"1995-01-01","New Year","KZ",1995 +"1995-01-02","New Year","KZ",1995 +"1995-03-08","International Women's Day","KZ",1995 +"1995-05-01","Kazakhstan People Solidarity Holiday","KZ",1995 +"1995-05-09","Victory Day","KZ",1995 +"1995-10-25","Republic Day","KZ",1995 +"1995-12-16","Kazakhstan Independence Day","KZ",1995 +"1996-01-01","New Year","KZ",1996 +"1996-01-02","New Year","KZ",1996 +"1996-03-08","International Women's Day","KZ",1996 +"1996-05-01","Kazakhstan People Solidarity Holiday","KZ",1996 +"1996-05-09","Victory Day","KZ",1996 +"1996-08-30","Constitution Day of the Republic of Kazakhstan","KZ",1996 +"1996-10-25","Republic Day","KZ",1996 +"1996-12-16","Kazakhstan Independence Day","KZ",1996 +"1997-01-01","New Year","KZ",1997 +"1997-01-02","New Year","KZ",1997 +"1997-03-08","International Women's Day","KZ",1997 +"1997-05-01","Kazakhstan People Solidarity Holiday","KZ",1997 +"1997-05-09","Victory Day","KZ",1997 +"1997-08-30","Constitution Day of the Republic of Kazakhstan","KZ",1997 +"1997-10-25","Republic Day","KZ",1997 +"1997-12-16","Kazakhstan Independence Day","KZ",1997 +"1998-01-01","New Year","KZ",1998 +"1998-01-02","New Year","KZ",1998 +"1998-03-08","International Women's Day","KZ",1998 +"1998-05-01","Kazakhstan People Solidarity Holiday","KZ",1998 +"1998-05-09","Victory Day","KZ",1998 +"1998-08-30","Constitution Day of the Republic of Kazakhstan","KZ",1998 +"1998-10-25","Republic Day","KZ",1998 +"1998-12-16","Kazakhstan Independence Day","KZ",1998 +"1999-01-01","New Year","KZ",1999 +"1999-01-02","New Year","KZ",1999 +"1999-03-08","International Women's Day","KZ",1999 +"1999-05-01","Kazakhstan People Solidarity Holiday","KZ",1999 +"1999-05-09","Victory Day","KZ",1999 +"1999-08-30","Constitution Day of the Republic of Kazakhstan","KZ",1999 +"1999-10-25","Republic Day","KZ",1999 +"1999-12-16","Kazakhstan Independence Day","KZ",1999 +"2000-01-01","New Year","KZ",2000 +"2000-01-02","New Year","KZ",2000 +"2000-03-08","International Women's Day","KZ",2000 +"2000-05-01","Kazakhstan People Solidarity Holiday","KZ",2000 +"2000-05-09","Victory Day","KZ",2000 +"2000-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2000 +"2000-10-25","Republic Day","KZ",2000 +"2000-12-16","Kazakhstan Independence Day","KZ",2000 +"2001-01-01","New Year","KZ",2001 +"2001-01-02","New Year","KZ",2001 +"2001-03-08","International Women's Day","KZ",2001 +"2001-05-01","Kazakhstan People Solidarity Holiday","KZ",2001 +"2001-05-09","Victory Day","KZ",2001 +"2001-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2001 +"2001-10-25","Republic Day","KZ",2001 +"2001-12-16","Kazakhstan Independence Day","KZ",2001 +"2002-01-01","New Year","KZ",2002 +"2002-01-02","New Year","KZ",2002 +"2002-03-08","International Women's Day","KZ",2002 +"2002-03-22","Nauryz holiday","KZ",2002 +"2002-05-01","Kazakhstan People Solidarity Holiday","KZ",2002 +"2002-05-09","Victory Day","KZ",2002 +"2002-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2002 +"2002-10-25","Republic Day","KZ",2002 +"2002-12-16","Kazakhstan Independence Day","KZ",2002 +"2002-12-17","Kazakhstan Independence Day","KZ",2002 +"2003-01-01","New Year","KZ",2003 +"2003-01-02","New Year","KZ",2003 +"2003-03-08","International Women's Day","KZ",2003 +"2003-03-10","International Women's Day (Observed)","KZ",2003 +"2003-03-22","Nauryz holiday","KZ",2003 +"2003-03-24","Nauryz holiday (Observed)","KZ",2003 +"2003-05-01","Kazakhstan People Solidarity Holiday","KZ",2003 +"2003-05-09","Victory Day","KZ",2003 +"2003-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2003 +"2003-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2003 +"2003-10-25","Republic Day","KZ",2003 +"2003-10-27","Republic Day (Observed)","KZ",2003 +"2003-12-16","Kazakhstan Independence Day","KZ",2003 +"2003-12-17","Kazakhstan Independence Day","KZ",2003 +"2004-01-01","New Year","KZ",2004 +"2004-01-02","New Year","KZ",2004 +"2004-03-08","International Women's Day","KZ",2004 +"2004-03-22","Nauryz holiday","KZ",2004 +"2004-05-01","Kazakhstan People Solidarity Holiday","KZ",2004 +"2004-05-03","Kazakhstan People Solidarity Holiday (Observed)","KZ",2004 +"2004-05-09","Victory Day","KZ",2004 +"2004-05-10","Victory Day (Observed)","KZ",2004 +"2004-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2004 +"2004-10-25","Republic Day","KZ",2004 +"2004-12-16","Kazakhstan Independence Day","KZ",2004 +"2004-12-17","Kazakhstan Independence Day","KZ",2004 +"2005-01-01","New Year","KZ",2005 +"2005-01-02","New Year","KZ",2005 +"2005-01-03","New Year (Observed)","KZ",2005 +"2005-01-04","New Year (Observed)","KZ",2005 +"2005-03-08","International Women's Day","KZ",2005 +"2005-03-22","Nauryz holiday","KZ",2005 +"2005-05-01","Kazakhstan People Solidarity Holiday","KZ",2005 +"2005-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2005 +"2005-05-09","Victory Day","KZ",2005 +"2005-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2005 +"2005-10-25","Republic Day","KZ",2005 +"2005-12-16","Kazakhstan Independence Day","KZ",2005 +"2005-12-17","Kazakhstan Independence Day","KZ",2005 +"2005-12-19","Kazakhstan Independence Day (Observed)","KZ",2005 +"2006-01-01","New Year","KZ",2006 +"2006-01-02","New Year","KZ",2006 +"2006-01-03","New Year (Observed)","KZ",2006 +"2006-01-07","Orthodox Christmas","KZ",2006 +"2006-01-10","Kurban Ait* (*estimated)","KZ",2006 +"2006-03-08","International Women's Day","KZ",2006 +"2006-03-22","Nauryz holiday","KZ",2006 +"2006-05-01","Kazakhstan People Solidarity Holiday","KZ",2006 +"2006-05-09","Victory Day","KZ",2006 +"2006-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2006 +"2006-10-25","Republic Day","KZ",2006 +"2006-12-16","Kazakhstan Independence Day","KZ",2006 +"2006-12-17","Kazakhstan Independence Day","KZ",2006 +"2006-12-18","Kazakhstan Independence Day (Observed)","KZ",2006 +"2006-12-19","Kazakhstan Independence Day (Observed)","KZ",2006 +"2006-12-31","Kurban Ait* (*estimated)","KZ",2006 +"2007-01-01","New Year","KZ",2007 +"2007-01-02","New Year","KZ",2007 +"2007-01-07","Orthodox Christmas","KZ",2007 +"2007-03-08","International Women's Day","KZ",2007 +"2007-03-22","Nauryz holiday","KZ",2007 +"2007-05-01","Kazakhstan People Solidarity Holiday","KZ",2007 +"2007-05-09","Victory Day","KZ",2007 +"2007-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2007 +"2007-10-25","Republic Day","KZ",2007 +"2007-12-16","Kazakhstan Independence Day","KZ",2007 +"2007-12-17","Kazakhstan Independence Day","KZ",2007 +"2007-12-18","Kazakhstan Independence Day (Observed)","KZ",2007 +"2007-12-20","Kurban Ait* (*estimated)","KZ",2007 +"2008-01-01","New Year","KZ",2008 +"2008-01-02","New Year","KZ",2008 +"2008-01-07","Orthodox Christmas","KZ",2008 +"2008-03-08","International Women's Day","KZ",2008 +"2008-03-10","International Women's Day (Observed)","KZ",2008 +"2008-03-22","Nauryz holiday","KZ",2008 +"2008-03-24","Nauryz holiday (Observed)","KZ",2008 +"2008-05-01","Kazakhstan People Solidarity Holiday","KZ",2008 +"2008-05-09","Victory Day","KZ",2008 +"2008-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2008 +"2008-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2008 +"2008-10-25","Republic Day","KZ",2008 +"2008-10-27","Republic Day (Observed)","KZ",2008 +"2008-12-08","Kurban Ait* (*estimated)","KZ",2008 +"2008-12-16","Kazakhstan Independence Day","KZ",2008 +"2008-12-17","Kazakhstan Independence Day","KZ",2008 +"2009-01-01","New Year","KZ",2009 +"2009-01-02","New Year","KZ",2009 +"2009-01-07","Orthodox Christmas","KZ",2009 +"2009-03-08","International Women's Day","KZ",2009 +"2009-03-09","International Women's Day (Observed)","KZ",2009 +"2009-03-22","Nauryz holiday","KZ",2009 +"2009-03-23","Nauryz holiday (Observed)","KZ",2009 +"2009-05-01","Kazakhstan People Solidarity Holiday","KZ",2009 +"2009-05-09","Victory Day","KZ",2009 +"2009-05-11","Victory Day (Observed)","KZ",2009 +"2009-07-06","Capital Day","KZ",2009 +"2009-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2009 +"2009-08-31","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2009 +"2009-11-27","Kurban Ait* (*estimated)","KZ",2009 +"2009-12-16","Kazakhstan Independence Day","KZ",2009 +"2009-12-17","Kazakhstan Independence Day","KZ",2009 +"2010-01-01","New Year","KZ",2010 +"2010-01-02","New Year","KZ",2010 +"2010-01-04","New Year (Observed)","KZ",2010 +"2010-01-07","Orthodox Christmas","KZ",2010 +"2010-03-08","International Women's Day","KZ",2010 +"2010-03-21","Nauryz holiday","KZ",2010 +"2010-03-22","Nauryz holiday","KZ",2010 +"2010-03-23","Nauryz holiday","KZ",2010 +"2010-03-24","Nauryz holiday (Observed)","KZ",2010 +"2010-05-01","Kazakhstan People Solidarity Holiday","KZ",2010 +"2010-05-03","Kazakhstan People Solidarity Holiday (Observed)","KZ",2010 +"2010-05-09","Victory Day","KZ",2010 +"2010-05-10","Victory Day (Observed)","KZ",2010 +"2010-07-06","Capital Day","KZ",2010 +"2010-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2010 +"2010-11-16","Kurban Ait* (*estimated)","KZ",2010 +"2010-12-16","Kazakhstan Independence Day","KZ",2010 +"2010-12-17","Kazakhstan Independence Day","KZ",2010 +"2011-01-01","New Year","KZ",2011 +"2011-01-02","New Year","KZ",2011 +"2011-01-03","New Year (Observed)","KZ",2011 +"2011-01-04","New Year (Observed)","KZ",2011 +"2011-01-07","Orthodox Christmas","KZ",2011 +"2011-03-08","International Women's Day","KZ",2011 +"2011-03-21","Nauryz holiday","KZ",2011 +"2011-03-22","Nauryz holiday","KZ",2011 +"2011-03-23","Nauryz holiday","KZ",2011 +"2011-05-01","Kazakhstan People Solidarity Holiday","KZ",2011 +"2011-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2011 +"2011-05-09","Victory Day","KZ",2011 +"2011-07-06","Capital Day","KZ",2011 +"2011-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2011 +"2011-11-06","Kurban Ait* (*estimated)","KZ",2011 +"2011-12-16","Kazakhstan Independence Day","KZ",2011 +"2011-12-17","Kazakhstan Independence Day","KZ",2011 +"2011-12-19","Kazakhstan Independence Day (Observed)","KZ",2011 +"2012-01-01","New Year","KZ",2012 +"2012-01-02","New Year","KZ",2012 +"2012-01-03","New Year (Observed)","KZ",2012 +"2012-01-07","Orthodox Christmas","KZ",2012 +"2012-03-08","International Women's Day","KZ",2012 +"2012-03-21","Nauryz holiday","KZ",2012 +"2012-03-22","Nauryz holiday","KZ",2012 +"2012-03-23","Nauryz holiday","KZ",2012 +"2012-05-01","Kazakhstan People Solidarity Holiday","KZ",2012 +"2012-05-09","Victory Day","KZ",2012 +"2012-07-06","Capital Day","KZ",2012 +"2012-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2012 +"2012-10-26","Kurban Ait* (*estimated)","KZ",2012 +"2012-12-01","First President Day","KZ",2012 +"2012-12-03","First President Day (Observed)","KZ",2012 +"2012-12-16","Kazakhstan Independence Day","KZ",2012 +"2012-12-17","Kazakhstan Independence Day","KZ",2012 +"2012-12-18","Kazakhstan Independence Day (Observed)","KZ",2012 +"2013-01-01","New Year","KZ",2013 +"2013-01-02","New Year","KZ",2013 +"2013-01-07","Orthodox Christmas","KZ",2013 +"2013-03-08","International Women's Day","KZ",2013 +"2013-03-21","Nauryz holiday","KZ",2013 +"2013-03-22","Nauryz holiday","KZ",2013 +"2013-03-23","Nauryz holiday","KZ",2013 +"2013-03-25","Nauryz holiday (Observed)","KZ",2013 +"2013-05-01","Kazakhstan People Solidarity Holiday","KZ",2013 +"2013-05-07","Defender of the Fatherland Day","KZ",2013 +"2013-05-09","Victory Day","KZ",2013 +"2013-07-06","Capital Day","KZ",2013 +"2013-07-08","Capital Day (Observed)","KZ",2013 +"2013-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2013 +"2013-10-15","Kurban Ait* (*estimated)","KZ",2013 +"2013-12-01","First President Day","KZ",2013 +"2013-12-02","First President Day (Observed)","KZ",2013 +"2013-12-16","Kazakhstan Independence Day","KZ",2013 +"2013-12-17","Kazakhstan Independence Day","KZ",2013 +"2014-01-01","New Year","KZ",2014 +"2014-01-02","New Year","KZ",2014 +"2014-01-07","Orthodox Christmas","KZ",2014 +"2014-03-08","International Women's Day","KZ",2014 +"2014-03-10","International Women's Day (Observed)","KZ",2014 +"2014-03-21","Nauryz holiday","KZ",2014 +"2014-03-22","Nauryz holiday","KZ",2014 +"2014-03-23","Nauryz holiday","KZ",2014 +"2014-03-24","Nauryz holiday (Observed)","KZ",2014 +"2014-03-25","Nauryz holiday (Observed)","KZ",2014 +"2014-05-01","Kazakhstan People Solidarity Holiday","KZ",2014 +"2014-05-07","Defender of the Fatherland Day","KZ",2014 +"2014-05-09","Victory Day","KZ",2014 +"2014-07-06","Capital Day","KZ",2014 +"2014-07-07","Capital Day (Observed)","KZ",2014 +"2014-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2014 +"2014-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2014 +"2014-10-04","Kurban Ait* (*estimated)","KZ",2014 +"2014-12-01","First President Day","KZ",2014 +"2014-12-16","Kazakhstan Independence Day","KZ",2014 +"2014-12-17","Kazakhstan Independence Day","KZ",2014 +"2015-01-01","New Year","KZ",2015 +"2015-01-02","New Year","KZ",2015 +"2015-01-07","Orthodox Christmas","KZ",2015 +"2015-03-08","International Women's Day","KZ",2015 +"2015-03-09","International Women's Day (Observed)","KZ",2015 +"2015-03-21","Nauryz holiday","KZ",2015 +"2015-03-22","Nauryz holiday","KZ",2015 +"2015-03-23","Nauryz holiday","KZ",2015 +"2015-03-24","Nauryz holiday (Observed)","KZ",2015 +"2015-03-25","Nauryz holiday (Observed)","KZ",2015 +"2015-05-01","Kazakhstan People Solidarity Holiday","KZ",2015 +"2015-05-07","Defender of the Fatherland Day","KZ",2015 +"2015-05-09","Victory Day","KZ",2015 +"2015-05-11","Victory Day (Observed)","KZ",2015 +"2015-07-06","Capital Day","KZ",2015 +"2015-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2015 +"2015-08-31","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2015 +"2015-09-23","Kurban Ait* (*estimated)","KZ",2015 +"2015-12-01","First President Day","KZ",2015 +"2015-12-16","Kazakhstan Independence Day","KZ",2015 +"2015-12-17","Kazakhstan Independence Day","KZ",2015 +"2016-01-01","New Year","KZ",2016 +"2016-01-02","New Year","KZ",2016 +"2016-01-04","New Year (Observed)","KZ",2016 +"2016-01-07","Orthodox Christmas","KZ",2016 +"2016-03-08","International Women's Day","KZ",2016 +"2016-03-21","Nauryz holiday","KZ",2016 +"2016-03-22","Nauryz holiday","KZ",2016 +"2016-03-23","Nauryz holiday","KZ",2016 +"2016-05-01","Kazakhstan People Solidarity Holiday","KZ",2016 +"2016-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2016 +"2016-05-07","Defender of the Fatherland Day","KZ",2016 +"2016-05-09","Victory Day","KZ",2016 +"2016-05-10","Defender of the Fatherland Day (Observed)","KZ",2016 +"2016-07-06","Capital Day","KZ",2016 +"2016-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2016 +"2016-09-11","Kurban Ait* (*estimated)","KZ",2016 +"2016-12-01","First President Day","KZ",2016 +"2016-12-16","Kazakhstan Independence Day","KZ",2016 +"2016-12-17","Kazakhstan Independence Day","KZ",2016 +"2016-12-19","Kazakhstan Independence Day (Observed)","KZ",2016 +"2017-01-01","New Year","KZ",2017 +"2017-01-02","New Year","KZ",2017 +"2017-01-03","New Year (Observed)","KZ",2017 +"2017-01-07","Orthodox Christmas","KZ",2017 +"2017-03-08","International Women's Day","KZ",2017 +"2017-03-21","Nauryz holiday","KZ",2017 +"2017-03-22","Nauryz holiday","KZ",2017 +"2017-03-23","Nauryz holiday","KZ",2017 +"2017-05-01","Kazakhstan People Solidarity Holiday","KZ",2017 +"2017-05-07","Defender of the Fatherland Day","KZ",2017 +"2017-05-08","Defender of the Fatherland Day (Observed)","KZ",2017 +"2017-05-09","Victory Day","KZ",2017 +"2017-07-06","Capital Day","KZ",2017 +"2017-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2017 +"2017-09-01","Kurban Ait* (*estimated)","KZ",2017 +"2017-12-01","First President Day","KZ",2017 +"2017-12-16","Kazakhstan Independence Day","KZ",2017 +"2017-12-17","Kazakhstan Independence Day","KZ",2017 +"2017-12-18","Kazakhstan Independence Day (Observed)","KZ",2017 +"2017-12-19","Kazakhstan Independence Day (Observed)","KZ",2017 +"2018-01-01","New Year","KZ",2018 +"2018-01-02","New Year","KZ",2018 +"2018-01-07","Orthodox Christmas","KZ",2018 +"2018-03-08","International Women's Day","KZ",2018 +"2018-03-21","Nauryz holiday","KZ",2018 +"2018-03-22","Nauryz holiday","KZ",2018 +"2018-03-23","Nauryz holiday","KZ",2018 +"2018-05-01","Kazakhstan People Solidarity Holiday","KZ",2018 +"2018-05-07","Defender of the Fatherland Day","KZ",2018 +"2018-05-09","Victory Day","KZ",2018 +"2018-07-06","Capital Day","KZ",2018 +"2018-08-21","Kurban Ait* (*estimated)","KZ",2018 +"2018-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2018 +"2018-12-01","First President Day","KZ",2018 +"2018-12-03","First President Day (Observed)","KZ",2018 +"2018-12-16","Kazakhstan Independence Day","KZ",2018 +"2018-12-17","Kazakhstan Independence Day","KZ",2018 +"2018-12-18","Kazakhstan Independence Day (Observed)","KZ",2018 +"2019-01-01","New Year","KZ",2019 +"2019-01-02","New Year","KZ",2019 +"2019-01-07","Orthodox Christmas","KZ",2019 +"2019-03-08","International Women's Day","KZ",2019 +"2019-03-21","Nauryz holiday","KZ",2019 +"2019-03-22","Nauryz holiday","KZ",2019 +"2019-03-23","Nauryz holiday","KZ",2019 +"2019-03-25","Nauryz holiday (Observed)","KZ",2019 +"2019-05-01","Kazakhstan People Solidarity Holiday","KZ",2019 +"2019-05-07","Defender of the Fatherland Day","KZ",2019 +"2019-05-09","Victory Day","KZ",2019 +"2019-07-06","Capital Day","KZ",2019 +"2019-07-08","Capital Day (Observed)","KZ",2019 +"2019-08-11","Kurban Ait* (*estimated)","KZ",2019 +"2019-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2019 +"2019-12-01","First President Day","KZ",2019 +"2019-12-02","First President Day (Observed)","KZ",2019 +"2019-12-16","Kazakhstan Independence Day","KZ",2019 +"2019-12-17","Kazakhstan Independence Day","KZ",2019 +"2020-01-01","New Year","KZ",2020 +"2020-01-02","New Year","KZ",2020 +"2020-01-07","Orthodox Christmas","KZ",2020 +"2020-03-08","International Women's Day","KZ",2020 +"2020-03-09","International Women's Day (Observed)","KZ",2020 +"2020-03-21","Nauryz holiday","KZ",2020 +"2020-03-22","Nauryz holiday","KZ",2020 +"2020-03-23","Nauryz holiday","KZ",2020 +"2020-03-24","Nauryz holiday (Observed)","KZ",2020 +"2020-03-25","Nauryz holiday (Observed)","KZ",2020 +"2020-05-01","Kazakhstan People Solidarity Holiday","KZ",2020 +"2020-05-07","Defender of the Fatherland Day","KZ",2020 +"2020-05-09","Victory Day","KZ",2020 +"2020-05-11","Victory Day (Observed)","KZ",2020 +"2020-07-06","Capital Day","KZ",2020 +"2020-07-31","Kurban Ait* (*estimated)","KZ",2020 +"2020-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2020 +"2020-08-31","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2020 +"2020-12-01","First President Day","KZ",2020 +"2020-12-16","Kazakhstan Independence Day","KZ",2020 +"2020-12-17","Kazakhstan Independence Day","KZ",2020 +"2021-01-01","New Year","KZ",2021 +"2021-01-02","New Year","KZ",2021 +"2021-01-04","New Year (Observed)","KZ",2021 +"2021-01-07","Orthodox Christmas","KZ",2021 +"2021-03-08","International Women's Day","KZ",2021 +"2021-03-21","Nauryz holiday","KZ",2021 +"2021-03-22","Nauryz holiday","KZ",2021 +"2021-03-23","Nauryz holiday","KZ",2021 +"2021-03-24","Nauryz holiday (Observed)","KZ",2021 +"2021-05-01","Kazakhstan People Solidarity Holiday","KZ",2021 +"2021-05-03","Kazakhstan People Solidarity Holiday (Observed)","KZ",2021 +"2021-05-07","Defender of the Fatherland Day","KZ",2021 +"2021-05-09","Victory Day","KZ",2021 +"2021-05-10","Victory Day (Observed)","KZ",2021 +"2021-07-06","Capital Day","KZ",2021 +"2021-07-20","Kurban Ait* (*estimated)","KZ",2021 +"2021-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2021 +"2021-12-01","First President Day","KZ",2021 +"2021-12-16","Kazakhstan Independence Day","KZ",2021 +"2021-12-17","Kazakhstan Independence Day","KZ",2021 +"2022-01-01","New Year","KZ",2022 +"2022-01-02","New Year","KZ",2022 +"2022-01-03","New Year (Observed)","KZ",2022 +"2022-01-04","New Year (Observed)","KZ",2022 +"2022-01-07","Orthodox Christmas","KZ",2022 +"2022-03-08","International Women's Day","KZ",2022 +"2022-03-21","Nauryz holiday","KZ",2022 +"2022-03-22","Nauryz holiday","KZ",2022 +"2022-03-23","Nauryz holiday","KZ",2022 +"2022-05-01","Kazakhstan People Solidarity Holiday","KZ",2022 +"2022-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2022 +"2022-05-07","Defender of the Fatherland Day","KZ",2022 +"2022-05-09","Victory Day","KZ",2022 +"2022-05-10","Defender of the Fatherland Day (Observed)","KZ",2022 +"2022-07-06","Capital Day","KZ",2022 +"2022-07-09","Kurban Ait* (*estimated)","KZ",2022 +"2022-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2022 +"2022-10-25","Republic Day","KZ",2022 +"2022-12-16","Kazakhstan Independence Day","KZ",2022 +"2023-01-01","New Year","KZ",2023 +"2023-01-02","New Year","KZ",2023 +"2023-01-03","New Year (Observed)","KZ",2023 +"2023-01-07","Orthodox Christmas","KZ",2023 +"2023-03-08","International Women's Day","KZ",2023 +"2023-03-21","Nauryz holiday","KZ",2023 +"2023-03-22","Nauryz holiday","KZ",2023 +"2023-03-23","Nauryz holiday","KZ",2023 +"2023-05-01","Kazakhstan People Solidarity Holiday","KZ",2023 +"2023-05-07","Defender of the Fatherland Day","KZ",2023 +"2023-05-08","Defender of the Fatherland Day (Observed)","KZ",2023 +"2023-05-09","Victory Day","KZ",2023 +"2023-06-28","Kurban Ait* (*estimated)","KZ",2023 +"2023-07-06","Capital Day","KZ",2023 +"2023-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2023 +"2023-10-25","Republic Day","KZ",2023 +"2023-12-16","Kazakhstan Independence Day","KZ",2023 +"2023-12-18","Kazakhstan Independence Day (Observed)","KZ",2023 +"2024-01-01","New Year","KZ",2024 +"2024-01-02","New Year","KZ",2024 +"2024-01-07","Orthodox Christmas","KZ",2024 +"2024-03-08","International Women's Day","KZ",2024 +"2024-03-21","Nauryz holiday","KZ",2024 +"2024-03-22","Nauryz holiday","KZ",2024 +"2024-03-23","Nauryz holiday","KZ",2024 +"2024-03-25","Nauryz holiday (Observed)","KZ",2024 +"2024-05-01","Kazakhstan People Solidarity Holiday","KZ",2024 +"2024-05-07","Defender of the Fatherland Day","KZ",2024 +"2024-05-09","Victory Day","KZ",2024 +"2024-06-16","Kurban Ait* (*estimated)","KZ",2024 +"2024-07-06","Capital Day","KZ",2024 +"2024-07-08","Capital Day (Observed)","KZ",2024 +"2024-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2024 +"2024-10-25","Republic Day","KZ",2024 +"2024-12-16","Kazakhstan Independence Day","KZ",2024 +"2025-01-01","New Year","KZ",2025 +"2025-01-02","New Year","KZ",2025 +"2025-01-07","Orthodox Christmas","KZ",2025 +"2025-03-08","International Women's Day","KZ",2025 +"2025-03-10","International Women's Day (Observed)","KZ",2025 +"2025-03-21","Nauryz holiday","KZ",2025 +"2025-03-22","Nauryz holiday","KZ",2025 +"2025-03-23","Nauryz holiday","KZ",2025 +"2025-03-24","Nauryz holiday (Observed)","KZ",2025 +"2025-03-25","Nauryz holiday (Observed)","KZ",2025 +"2025-05-01","Kazakhstan People Solidarity Holiday","KZ",2025 +"2025-05-07","Defender of the Fatherland Day","KZ",2025 +"2025-05-09","Victory Day","KZ",2025 +"2025-06-06","Kurban Ait* (*estimated)","KZ",2025 +"2025-07-06","Capital Day","KZ",2025 +"2025-07-07","Capital Day (Observed)","KZ",2025 +"2025-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2025 +"2025-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2025 +"2025-10-25","Republic Day","KZ",2025 +"2025-10-27","Republic Day (Observed)","KZ",2025 +"2025-12-16","Kazakhstan Independence Day","KZ",2025 +"2026-01-01","New Year","KZ",2026 +"2026-01-02","New Year","KZ",2026 +"2026-01-07","Orthodox Christmas","KZ",2026 +"2026-03-08","International Women's Day","KZ",2026 +"2026-03-09","International Women's Day (Observed)","KZ",2026 +"2026-03-21","Nauryz holiday","KZ",2026 +"2026-03-22","Nauryz holiday","KZ",2026 +"2026-03-23","Nauryz holiday","KZ",2026 +"2026-03-24","Nauryz holiday (Observed)","KZ",2026 +"2026-03-25","Nauryz holiday (Observed)","KZ",2026 +"2026-05-01","Kazakhstan People Solidarity Holiday","KZ",2026 +"2026-05-07","Defender of the Fatherland Day","KZ",2026 +"2026-05-09","Victory Day","KZ",2026 +"2026-05-11","Victory Day (Observed)","KZ",2026 +"2026-05-27","Kurban Ait* (*estimated)","KZ",2026 +"2026-07-06","Capital Day","KZ",2026 +"2026-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2026 +"2026-08-31","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2026 +"2026-10-25","Republic Day","KZ",2026 +"2026-10-26","Republic Day (Observed)","KZ",2026 +"2026-12-16","Kazakhstan Independence Day","KZ",2026 +"2027-01-01","New Year","KZ",2027 +"2027-01-02","New Year","KZ",2027 +"2027-01-04","New Year (Observed)","KZ",2027 +"2027-01-07","Orthodox Christmas","KZ",2027 +"2027-03-08","International Women's Day","KZ",2027 +"2027-03-21","Nauryz holiday","KZ",2027 +"2027-03-22","Nauryz holiday","KZ",2027 +"2027-03-23","Nauryz holiday","KZ",2027 +"2027-03-24","Nauryz holiday (Observed)","KZ",2027 +"2027-05-01","Kazakhstan People Solidarity Holiday","KZ",2027 +"2027-05-03","Kazakhstan People Solidarity Holiday (Observed)","KZ",2027 +"2027-05-07","Defender of the Fatherland Day","KZ",2027 +"2027-05-09","Victory Day","KZ",2027 +"2027-05-10","Victory Day (Observed)","KZ",2027 +"2027-05-16","Kurban Ait* (*estimated)","KZ",2027 +"2027-07-06","Capital Day","KZ",2027 +"2027-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2027 +"2027-10-25","Republic Day","KZ",2027 +"2027-12-16","Kazakhstan Independence Day","KZ",2027 +"2028-01-01","New Year","KZ",2028 +"2028-01-02","New Year","KZ",2028 +"2028-01-03","New Year (Observed)","KZ",2028 +"2028-01-04","New Year (Observed)","KZ",2028 +"2028-01-07","Orthodox Christmas","KZ",2028 +"2028-03-08","International Women's Day","KZ",2028 +"2028-03-21","Nauryz holiday","KZ",2028 +"2028-03-22","Nauryz holiday","KZ",2028 +"2028-03-23","Nauryz holiday","KZ",2028 +"2028-05-01","Kazakhstan People Solidarity Holiday","KZ",2028 +"2028-05-05","Kurban Ait* (*estimated)","KZ",2028 +"2028-05-07","Defender of the Fatherland Day","KZ",2028 +"2028-05-08","Defender of the Fatherland Day (Observed)","KZ",2028 +"2028-05-09","Victory Day","KZ",2028 +"2028-07-06","Capital Day","KZ",2028 +"2028-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2028 +"2028-10-25","Republic Day","KZ",2028 +"2028-12-16","Kazakhstan Independence Day","KZ",2028 +"2028-12-18","Kazakhstan Independence Day (Observed)","KZ",2028 +"2029-01-01","New Year","KZ",2029 +"2029-01-02","New Year","KZ",2029 +"2029-01-07","Orthodox Christmas","KZ",2029 +"2029-03-08","International Women's Day","KZ",2029 +"2029-03-21","Nauryz holiday","KZ",2029 +"2029-03-22","Nauryz holiday","KZ",2029 +"2029-03-23","Nauryz holiday","KZ",2029 +"2029-04-24","Kurban Ait* (*estimated)","KZ",2029 +"2029-05-01","Kazakhstan People Solidarity Holiday","KZ",2029 +"2029-05-07","Defender of the Fatherland Day","KZ",2029 +"2029-05-09","Victory Day","KZ",2029 +"2029-07-06","Capital Day","KZ",2029 +"2029-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2029 +"2029-10-25","Republic Day","KZ",2029 +"2029-12-16","Kazakhstan Independence Day","KZ",2029 +"2029-12-17","Kazakhstan Independence Day (Observed)","KZ",2029 +"2030-01-01","New Year","KZ",2030 +"2030-01-02","New Year","KZ",2030 +"2030-01-07","Orthodox Christmas","KZ",2030 +"2030-03-08","International Women's Day","KZ",2030 +"2030-03-21","Nauryz holiday","KZ",2030 +"2030-03-22","Nauryz holiday","KZ",2030 +"2030-03-23","Nauryz holiday","KZ",2030 +"2030-03-25","Nauryz holiday (Observed)","KZ",2030 +"2030-04-13","Kurban Ait* (*estimated)","KZ",2030 +"2030-05-01","Kazakhstan People Solidarity Holiday","KZ",2030 +"2030-05-07","Defender of the Fatherland Day","KZ",2030 +"2030-05-09","Victory Day","KZ",2030 +"2030-07-06","Capital Day","KZ",2030 +"2030-07-08","Capital Day (Observed)","KZ",2030 +"2030-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2030 +"2030-10-25","Republic Day","KZ",2030 +"2030-12-16","Kazakhstan Independence Day","KZ",2030 +"2031-01-01","New Year","KZ",2031 +"2031-01-02","New Year","KZ",2031 +"2031-01-07","Orthodox Christmas","KZ",2031 +"2031-03-08","International Women's Day","KZ",2031 +"2031-03-10","International Women's Day (Observed)","KZ",2031 +"2031-03-21","Nauryz holiday","KZ",2031 +"2031-03-22","Nauryz holiday","KZ",2031 +"2031-03-23","Nauryz holiday","KZ",2031 +"2031-03-24","Nauryz holiday (Observed)","KZ",2031 +"2031-03-25","Nauryz holiday (Observed)","KZ",2031 +"2031-04-02","Kurban Ait* (*estimated)","KZ",2031 +"2031-05-01","Kazakhstan People Solidarity Holiday","KZ",2031 +"2031-05-07","Defender of the Fatherland Day","KZ",2031 +"2031-05-09","Victory Day","KZ",2031 +"2031-07-06","Capital Day","KZ",2031 +"2031-07-07","Capital Day (Observed)","KZ",2031 +"2031-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2031 +"2031-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2031 +"2031-10-25","Republic Day","KZ",2031 +"2031-10-27","Republic Day (Observed)","KZ",2031 +"2031-12-16","Kazakhstan Independence Day","KZ",2031 +"2032-01-01","New Year","KZ",2032 +"2032-01-02","New Year","KZ",2032 +"2032-01-07","Orthodox Christmas","KZ",2032 +"2032-03-08","International Women's Day","KZ",2032 +"2032-03-21","Nauryz holiday","KZ",2032 +"2032-03-22","Kurban Ait* (*estimated)","KZ",2032 +"2032-03-22","Nauryz holiday","KZ",2032 +"2032-03-23","Nauryz holiday","KZ",2032 +"2032-03-24","Nauryz holiday (Observed)","KZ",2032 +"2032-05-01","Kazakhstan People Solidarity Holiday","KZ",2032 +"2032-05-03","Kazakhstan People Solidarity Holiday (Observed)","KZ",2032 +"2032-05-07","Defender of the Fatherland Day","KZ",2032 +"2032-05-09","Victory Day","KZ",2032 +"2032-05-10","Victory Day (Observed)","KZ",2032 +"2032-07-06","Capital Day","KZ",2032 +"2032-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2032 +"2032-10-25","Republic Day","KZ",2032 +"2032-12-16","Kazakhstan Independence Day","KZ",2032 +"2033-01-01","New Year","KZ",2033 +"2033-01-02","New Year","KZ",2033 +"2033-01-03","New Year (Observed)","KZ",2033 +"2033-01-04","New Year (Observed)","KZ",2033 +"2033-01-07","Orthodox Christmas","KZ",2033 +"2033-03-08","International Women's Day","KZ",2033 +"2033-03-11","Kurban Ait* (*estimated)","KZ",2033 +"2033-03-21","Nauryz holiday","KZ",2033 +"2033-03-22","Nauryz holiday","KZ",2033 +"2033-03-23","Nauryz holiday","KZ",2033 +"2033-05-01","Kazakhstan People Solidarity Holiday","KZ",2033 +"2033-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2033 +"2033-05-07","Defender of the Fatherland Day","KZ",2033 +"2033-05-09","Victory Day","KZ",2033 +"2033-05-10","Defender of the Fatherland Day (Observed)","KZ",2033 +"2033-07-06","Capital Day","KZ",2033 +"2033-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2033 +"2033-10-25","Republic Day","KZ",2033 +"2033-12-16","Kazakhstan Independence Day","KZ",2033 +"2034-01-01","New Year","KZ",2034 +"2034-01-02","New Year","KZ",2034 +"2034-01-03","New Year (Observed)","KZ",2034 +"2034-01-07","Orthodox Christmas","KZ",2034 +"2034-03-01","Kurban Ait* (*estimated)","KZ",2034 +"2034-03-08","International Women's Day","KZ",2034 +"2034-03-21","Nauryz holiday","KZ",2034 +"2034-03-22","Nauryz holiday","KZ",2034 +"2034-03-23","Nauryz holiday","KZ",2034 +"2034-05-01","Kazakhstan People Solidarity Holiday","KZ",2034 +"2034-05-07","Defender of the Fatherland Day","KZ",2034 +"2034-05-08","Defender of the Fatherland Day (Observed)","KZ",2034 +"2034-05-09","Victory Day","KZ",2034 +"2034-07-06","Capital Day","KZ",2034 +"2034-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2034 +"2034-10-25","Republic Day","KZ",2034 +"2034-12-16","Kazakhstan Independence Day","KZ",2034 +"2034-12-18","Kazakhstan Independence Day (Observed)","KZ",2034 +"2035-01-01","New Year","KZ",2035 +"2035-01-02","New Year","KZ",2035 +"2035-01-07","Orthodox Christmas","KZ",2035 +"2035-02-18","Kurban Ait* (*estimated)","KZ",2035 +"2035-03-08","International Women's Day","KZ",2035 +"2035-03-21","Nauryz holiday","KZ",2035 +"2035-03-22","Nauryz holiday","KZ",2035 +"2035-03-23","Nauryz holiday","KZ",2035 +"2035-05-01","Kazakhstan People Solidarity Holiday","KZ",2035 +"2035-05-07","Defender of the Fatherland Day","KZ",2035 +"2035-05-09","Victory Day","KZ",2035 +"2035-07-06","Capital Day","KZ",2035 +"2035-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2035 +"2035-10-25","Republic Day","KZ",2035 +"2035-12-16","Kazakhstan Independence Day","KZ",2035 +"2035-12-17","Kazakhstan Independence Day (Observed)","KZ",2035 +"2036-01-01","New Year","KZ",2036 +"2036-01-02","New Year","KZ",2036 +"2036-01-07","Orthodox Christmas","KZ",2036 +"2036-02-07","Kurban Ait* (*estimated)","KZ",2036 +"2036-03-08","International Women's Day","KZ",2036 +"2036-03-10","International Women's Day (Observed)","KZ",2036 +"2036-03-21","Nauryz holiday","KZ",2036 +"2036-03-22","Nauryz holiday","KZ",2036 +"2036-03-23","Nauryz holiday","KZ",2036 +"2036-03-24","Nauryz holiday (Observed)","KZ",2036 +"2036-03-25","Nauryz holiday (Observed)","KZ",2036 +"2036-05-01","Kazakhstan People Solidarity Holiday","KZ",2036 +"2036-05-07","Defender of the Fatherland Day","KZ",2036 +"2036-05-09","Victory Day","KZ",2036 +"2036-07-06","Capital Day","KZ",2036 +"2036-07-07","Capital Day (Observed)","KZ",2036 +"2036-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2036 +"2036-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2036 +"2036-10-25","Republic Day","KZ",2036 +"2036-10-27","Republic Day (Observed)","KZ",2036 +"2036-12-16","Kazakhstan Independence Day","KZ",2036 +"2037-01-01","New Year","KZ",2037 +"2037-01-02","New Year","KZ",2037 +"2037-01-07","Orthodox Christmas","KZ",2037 +"2037-01-26","Kurban Ait* (*estimated)","KZ",2037 +"2037-03-08","International Women's Day","KZ",2037 +"2037-03-09","International Women's Day (Observed)","KZ",2037 +"2037-03-21","Nauryz holiday","KZ",2037 +"2037-03-22","Nauryz holiday","KZ",2037 +"2037-03-23","Nauryz holiday","KZ",2037 +"2037-03-24","Nauryz holiday (Observed)","KZ",2037 +"2037-03-25","Nauryz holiday (Observed)","KZ",2037 +"2037-05-01","Kazakhstan People Solidarity Holiday","KZ",2037 +"2037-05-07","Defender of the Fatherland Day","KZ",2037 +"2037-05-09","Victory Day","KZ",2037 +"2037-05-11","Victory Day (Observed)","KZ",2037 +"2037-07-06","Capital Day","KZ",2037 +"2037-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2037 +"2037-08-31","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2037 +"2037-10-25","Republic Day","KZ",2037 +"2037-10-26","Republic Day (Observed)","KZ",2037 +"2037-12-16","Kazakhstan Independence Day","KZ",2037 +"2038-01-01","New Year","KZ",2038 +"2038-01-02","New Year","KZ",2038 +"2038-01-04","New Year (Observed)","KZ",2038 +"2038-01-07","Orthodox Christmas","KZ",2038 +"2038-01-16","Kurban Ait* (*estimated)","KZ",2038 +"2038-03-08","International Women's Day","KZ",2038 +"2038-03-21","Nauryz holiday","KZ",2038 +"2038-03-22","Nauryz holiday","KZ",2038 +"2038-03-23","Nauryz holiday","KZ",2038 +"2038-03-24","Nauryz holiday (Observed)","KZ",2038 +"2038-05-01","Kazakhstan People Solidarity Holiday","KZ",2038 +"2038-05-03","Kazakhstan People Solidarity Holiday (Observed)","KZ",2038 +"2038-05-07","Defender of the Fatherland Day","KZ",2038 +"2038-05-09","Victory Day","KZ",2038 +"2038-05-10","Victory Day (Observed)","KZ",2038 +"2038-07-06","Capital Day","KZ",2038 +"2038-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2038 +"2038-10-25","Republic Day","KZ",2038 +"2038-12-16","Kazakhstan Independence Day","KZ",2038 +"2039-01-01","New Year","KZ",2039 +"2039-01-02","New Year","KZ",2039 +"2039-01-03","New Year (Observed)","KZ",2039 +"2039-01-04","New Year (Observed)","KZ",2039 +"2039-01-05","Kurban Ait* (*estimated)","KZ",2039 +"2039-01-07","Orthodox Christmas","KZ",2039 +"2039-03-08","International Women's Day","KZ",2039 +"2039-03-21","Nauryz holiday","KZ",2039 +"2039-03-22","Nauryz holiday","KZ",2039 +"2039-03-23","Nauryz holiday","KZ",2039 +"2039-05-01","Kazakhstan People Solidarity Holiday","KZ",2039 +"2039-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2039 +"2039-05-07","Defender of the Fatherland Day","KZ",2039 +"2039-05-09","Victory Day","KZ",2039 +"2039-05-10","Defender of the Fatherland Day (Observed)","KZ",2039 +"2039-07-06","Capital Day","KZ",2039 +"2039-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2039 +"2039-10-25","Republic Day","KZ",2039 +"2039-12-16","Kazakhstan Independence Day","KZ",2039 +"2039-12-26","Kurban Ait* (*estimated)","KZ",2039 +"2040-01-01","New Year","KZ",2040 +"2040-01-02","New Year","KZ",2040 +"2040-01-03","New Year (Observed)","KZ",2040 +"2040-01-07","Orthodox Christmas","KZ",2040 +"2040-03-08","International Women's Day","KZ",2040 +"2040-03-21","Nauryz holiday","KZ",2040 +"2040-03-22","Nauryz holiday","KZ",2040 +"2040-03-23","Nauryz holiday","KZ",2040 +"2040-05-01","Kazakhstan People Solidarity Holiday","KZ",2040 +"2040-05-07","Defender of the Fatherland Day","KZ",2040 +"2040-05-09","Victory Day","KZ",2040 +"2040-07-06","Capital Day","KZ",2040 +"2040-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2040 +"2040-10-25","Republic Day","KZ",2040 +"2040-12-14","Kurban Ait* (*estimated)","KZ",2040 +"2040-12-16","Kazakhstan Independence Day","KZ",2040 +"2040-12-17","Kazakhstan Independence Day (Observed)","KZ",2040 +"2041-01-01","New Year","KZ",2041 +"2041-01-02","New Year","KZ",2041 +"2041-01-07","Orthodox Christmas","KZ",2041 +"2041-03-08","International Women's Day","KZ",2041 +"2041-03-21","Nauryz holiday","KZ",2041 +"2041-03-22","Nauryz holiday","KZ",2041 +"2041-03-23","Nauryz holiday","KZ",2041 +"2041-03-25","Nauryz holiday (Observed)","KZ",2041 +"2041-05-01","Kazakhstan People Solidarity Holiday","KZ",2041 +"2041-05-07","Defender of the Fatherland Day","KZ",2041 +"2041-05-09","Victory Day","KZ",2041 +"2041-07-06","Capital Day","KZ",2041 +"2041-07-08","Capital Day (Observed)","KZ",2041 +"2041-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2041 +"2041-10-25","Republic Day","KZ",2041 +"2041-12-04","Kurban Ait* (*estimated)","KZ",2041 +"2041-12-16","Kazakhstan Independence Day","KZ",2041 +"2042-01-01","New Year","KZ",2042 +"2042-01-02","New Year","KZ",2042 +"2042-01-07","Orthodox Christmas","KZ",2042 +"2042-03-08","International Women's Day","KZ",2042 +"2042-03-10","International Women's Day (Observed)","KZ",2042 +"2042-03-21","Nauryz holiday","KZ",2042 +"2042-03-22","Nauryz holiday","KZ",2042 +"2042-03-23","Nauryz holiday","KZ",2042 +"2042-03-24","Nauryz holiday (Observed)","KZ",2042 +"2042-03-25","Nauryz holiday (Observed)","KZ",2042 +"2042-05-01","Kazakhstan People Solidarity Holiday","KZ",2042 +"2042-05-07","Defender of the Fatherland Day","KZ",2042 +"2042-05-09","Victory Day","KZ",2042 +"2042-07-06","Capital Day","KZ",2042 +"2042-07-07","Capital Day (Observed)","KZ",2042 +"2042-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2042 +"2042-09-01","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2042 +"2042-10-25","Republic Day","KZ",2042 +"2042-10-27","Republic Day (Observed)","KZ",2042 +"2042-11-23","Kurban Ait* (*estimated)","KZ",2042 +"2042-12-16","Kazakhstan Independence Day","KZ",2042 +"2043-01-01","New Year","KZ",2043 +"2043-01-02","New Year","KZ",2043 +"2043-01-07","Orthodox Christmas","KZ",2043 +"2043-03-08","International Women's Day","KZ",2043 +"2043-03-09","International Women's Day (Observed)","KZ",2043 +"2043-03-21","Nauryz holiday","KZ",2043 +"2043-03-22","Nauryz holiday","KZ",2043 +"2043-03-23","Nauryz holiday","KZ",2043 +"2043-03-24","Nauryz holiday (Observed)","KZ",2043 +"2043-03-25","Nauryz holiday (Observed)","KZ",2043 +"2043-05-01","Kazakhstan People Solidarity Holiday","KZ",2043 +"2043-05-07","Defender of the Fatherland Day","KZ",2043 +"2043-05-09","Victory Day","KZ",2043 +"2043-05-11","Victory Day (Observed)","KZ",2043 +"2043-07-06","Capital Day","KZ",2043 +"2043-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2043 +"2043-08-31","Constitution Day of the Republic of Kazakhstan (Observed)","KZ",2043 +"2043-10-25","Republic Day","KZ",2043 +"2043-10-26","Republic Day (Observed)","KZ",2043 +"2043-11-12","Kurban Ait* (*estimated)","KZ",2043 +"2043-12-16","Kazakhstan Independence Day","KZ",2043 +"2044-01-01","New Year","KZ",2044 +"2044-01-02","New Year","KZ",2044 +"2044-01-04","New Year (Observed)","KZ",2044 +"2044-01-07","Orthodox Christmas","KZ",2044 +"2044-03-08","International Women's Day","KZ",2044 +"2044-03-21","Nauryz holiday","KZ",2044 +"2044-03-22","Nauryz holiday","KZ",2044 +"2044-03-23","Nauryz holiday","KZ",2044 +"2044-05-01","Kazakhstan People Solidarity Holiday","KZ",2044 +"2044-05-02","Kazakhstan People Solidarity Holiday (Observed)","KZ",2044 +"2044-05-07","Defender of the Fatherland Day","KZ",2044 +"2044-05-09","Victory Day","KZ",2044 +"2044-05-10","Defender of the Fatherland Day (Observed)","KZ",2044 +"2044-07-06","Capital Day","KZ",2044 +"2044-08-30","Constitution Day of the Republic of Kazakhstan","KZ",2044 +"2044-10-25","Republic Day","KZ",2044 +"2044-10-31","Kurban Ait* (*estimated)","KZ",2044 +"2044-12-16","Kazakhstan Independence Day","KZ",2044 +"1995-01-01","New Year's Day","LI",1995 +"1995-01-02","Saint Berchtold's Day","LI",1995 +"1995-01-06","Epiphany","LI",1995 +"1995-02-02","Candlemas","LI",1995 +"1995-02-28","Shrove Tuesday","LI",1995 +"1995-03-19","Saint Joseph's Day","LI",1995 +"1995-04-14","Good Friday","LI",1995 +"1995-04-16","Easter Sunday","LI",1995 +"1995-04-17","Easter Monday","LI",1995 +"1995-05-01","Labor Day","LI",1995 +"1995-05-25","Ascension Day","LI",1995 +"1995-06-04","Whit Sunday","LI",1995 +"1995-06-05","Whit Monday","LI",1995 +"1995-06-15","Corpus Christi","LI",1995 +"1995-08-15","National Day","LI",1995 +"1995-09-08","Nativity of Mary","LI",1995 +"1995-11-01","All Saints' Day","LI",1995 +"1995-12-08","Immaculate Conception","LI",1995 +"1995-12-24","Christmas Eve","LI",1995 +"1995-12-25","Christmas Day","LI",1995 +"1995-12-26","St. Stephen's Day","LI",1995 +"1995-12-31","New Year's Eve","LI",1995 +"1996-01-01","New Year's Day","LI",1996 +"1996-01-02","Saint Berchtold's Day","LI",1996 +"1996-01-06","Epiphany","LI",1996 +"1996-02-02","Candlemas","LI",1996 +"1996-02-20","Shrove Tuesday","LI",1996 +"1996-03-19","Saint Joseph's Day","LI",1996 +"1996-04-05","Good Friday","LI",1996 +"1996-04-07","Easter Sunday","LI",1996 +"1996-04-08","Easter Monday","LI",1996 +"1996-05-01","Labor Day","LI",1996 +"1996-05-16","Ascension Day","LI",1996 +"1996-05-26","Whit Sunday","LI",1996 +"1996-05-27","Whit Monday","LI",1996 +"1996-06-06","Corpus Christi","LI",1996 +"1996-08-15","National Day","LI",1996 +"1996-09-08","Nativity of Mary","LI",1996 +"1996-11-01","All Saints' Day","LI",1996 +"1996-12-08","Immaculate Conception","LI",1996 +"1996-12-24","Christmas Eve","LI",1996 +"1996-12-25","Christmas Day","LI",1996 +"1996-12-26","St. Stephen's Day","LI",1996 +"1996-12-31","New Year's Eve","LI",1996 +"1997-01-01","New Year's Day","LI",1997 +"1997-01-02","Saint Berchtold's Day","LI",1997 +"1997-01-06","Epiphany","LI",1997 +"1997-02-02","Candlemas","LI",1997 +"1997-02-11","Shrove Tuesday","LI",1997 +"1997-03-19","Saint Joseph's Day","LI",1997 +"1997-03-28","Good Friday","LI",1997 +"1997-03-30","Easter Sunday","LI",1997 +"1997-03-31","Easter Monday","LI",1997 +"1997-05-01","Labor Day","LI",1997 +"1997-05-08","Ascension Day","LI",1997 +"1997-05-18","Whit Sunday","LI",1997 +"1997-05-19","Whit Monday","LI",1997 +"1997-05-29","Corpus Christi","LI",1997 +"1997-08-15","National Day","LI",1997 +"1997-09-08","Nativity of Mary","LI",1997 +"1997-11-01","All Saints' Day","LI",1997 +"1997-12-08","Immaculate Conception","LI",1997 +"1997-12-24","Christmas Eve","LI",1997 +"1997-12-25","Christmas Day","LI",1997 +"1997-12-26","St. Stephen's Day","LI",1997 +"1997-12-31","New Year's Eve","LI",1997 +"1998-01-01","New Year's Day","LI",1998 +"1998-01-02","Saint Berchtold's Day","LI",1998 +"1998-01-06","Epiphany","LI",1998 +"1998-02-02","Candlemas","LI",1998 +"1998-02-24","Shrove Tuesday","LI",1998 +"1998-03-19","Saint Joseph's Day","LI",1998 +"1998-04-10","Good Friday","LI",1998 +"1998-04-12","Easter Sunday","LI",1998 +"1998-04-13","Easter Monday","LI",1998 +"1998-05-01","Labor Day","LI",1998 +"1998-05-21","Ascension Day","LI",1998 +"1998-05-31","Whit Sunday","LI",1998 +"1998-06-01","Whit Monday","LI",1998 +"1998-06-11","Corpus Christi","LI",1998 +"1998-08-15","National Day","LI",1998 +"1998-09-08","Nativity of Mary","LI",1998 +"1998-11-01","All Saints' Day","LI",1998 +"1998-12-08","Immaculate Conception","LI",1998 +"1998-12-24","Christmas Eve","LI",1998 +"1998-12-25","Christmas Day","LI",1998 +"1998-12-26","St. Stephen's Day","LI",1998 +"1998-12-31","New Year's Eve","LI",1998 +"1999-01-01","New Year's Day","LI",1999 +"1999-01-02","Saint Berchtold's Day","LI",1999 +"1999-01-06","Epiphany","LI",1999 +"1999-02-02","Candlemas","LI",1999 +"1999-02-16","Shrove Tuesday","LI",1999 +"1999-03-19","Saint Joseph's Day","LI",1999 +"1999-04-02","Good Friday","LI",1999 +"1999-04-04","Easter Sunday","LI",1999 +"1999-04-05","Easter Monday","LI",1999 +"1999-05-01","Labor Day","LI",1999 +"1999-05-13","Ascension Day","LI",1999 +"1999-05-23","Whit Sunday","LI",1999 +"1999-05-24","Whit Monday","LI",1999 +"1999-06-03","Corpus Christi","LI",1999 +"1999-08-15","National Day","LI",1999 +"1999-09-08","Nativity of Mary","LI",1999 +"1999-11-01","All Saints' Day","LI",1999 +"1999-12-08","Immaculate Conception","LI",1999 +"1999-12-24","Christmas Eve","LI",1999 +"1999-12-25","Christmas Day","LI",1999 +"1999-12-26","St. Stephen's Day","LI",1999 +"1999-12-31","New Year's Eve","LI",1999 +"2000-01-01","New Year's Day","LI",2000 +"2000-01-02","Saint Berchtold's Day","LI",2000 +"2000-01-06","Epiphany","LI",2000 +"2000-02-02","Candlemas","LI",2000 +"2000-03-07","Shrove Tuesday","LI",2000 +"2000-03-19","Saint Joseph's Day","LI",2000 +"2000-04-21","Good Friday","LI",2000 +"2000-04-23","Easter Sunday","LI",2000 +"2000-04-24","Easter Monday","LI",2000 +"2000-05-01","Labor Day","LI",2000 +"2000-06-01","Ascension Day","LI",2000 +"2000-06-11","Whit Sunday","LI",2000 +"2000-06-12","Whit Monday","LI",2000 +"2000-06-22","Corpus Christi","LI",2000 +"2000-08-15","National Day","LI",2000 +"2000-09-08","Nativity of Mary","LI",2000 +"2000-11-01","All Saints' Day","LI",2000 +"2000-12-08","Immaculate Conception","LI",2000 +"2000-12-24","Christmas Eve","LI",2000 +"2000-12-25","Christmas Day","LI",2000 +"2000-12-26","St. Stephen's Day","LI",2000 +"2000-12-31","New Year's Eve","LI",2000 +"2001-01-01","New Year's Day","LI",2001 +"2001-01-02","Saint Berchtold's Day","LI",2001 +"2001-01-06","Epiphany","LI",2001 +"2001-02-02","Candlemas","LI",2001 +"2001-02-27","Shrove Tuesday","LI",2001 +"2001-03-19","Saint Joseph's Day","LI",2001 +"2001-04-13","Good Friday","LI",2001 +"2001-04-15","Easter Sunday","LI",2001 +"2001-04-16","Easter Monday","LI",2001 +"2001-05-01","Labor Day","LI",2001 +"2001-05-24","Ascension Day","LI",2001 +"2001-06-03","Whit Sunday","LI",2001 +"2001-06-04","Whit Monday","LI",2001 +"2001-06-14","Corpus Christi","LI",2001 +"2001-08-15","National Day","LI",2001 +"2001-09-08","Nativity of Mary","LI",2001 +"2001-11-01","All Saints' Day","LI",2001 +"2001-12-08","Immaculate Conception","LI",2001 +"2001-12-24","Christmas Eve","LI",2001 +"2001-12-25","Christmas Day","LI",2001 +"2001-12-26","St. Stephen's Day","LI",2001 +"2001-12-31","New Year's Eve","LI",2001 +"2002-01-01","New Year's Day","LI",2002 +"2002-01-02","Saint Berchtold's Day","LI",2002 +"2002-01-06","Epiphany","LI",2002 +"2002-02-02","Candlemas","LI",2002 +"2002-02-12","Shrove Tuesday","LI",2002 +"2002-03-19","Saint Joseph's Day","LI",2002 +"2002-03-29","Good Friday","LI",2002 +"2002-03-31","Easter Sunday","LI",2002 +"2002-04-01","Easter Monday","LI",2002 +"2002-05-01","Labor Day","LI",2002 +"2002-05-09","Ascension Day","LI",2002 +"2002-05-19","Whit Sunday","LI",2002 +"2002-05-20","Whit Monday","LI",2002 +"2002-05-30","Corpus Christi","LI",2002 +"2002-08-15","National Day","LI",2002 +"2002-09-08","Nativity of Mary","LI",2002 +"2002-11-01","All Saints' Day","LI",2002 +"2002-12-08","Immaculate Conception","LI",2002 +"2002-12-24","Christmas Eve","LI",2002 +"2002-12-25","Christmas Day","LI",2002 +"2002-12-26","St. Stephen's Day","LI",2002 +"2002-12-31","New Year's Eve","LI",2002 +"2003-01-01","New Year's Day","LI",2003 +"2003-01-02","Saint Berchtold's Day","LI",2003 +"2003-01-06","Epiphany","LI",2003 +"2003-02-02","Candlemas","LI",2003 +"2003-03-04","Shrove Tuesday","LI",2003 +"2003-03-19","Saint Joseph's Day","LI",2003 +"2003-04-18","Good Friday","LI",2003 +"2003-04-20","Easter Sunday","LI",2003 +"2003-04-21","Easter Monday","LI",2003 +"2003-05-01","Labor Day","LI",2003 +"2003-05-29","Ascension Day","LI",2003 +"2003-06-08","Whit Sunday","LI",2003 +"2003-06-09","Whit Monday","LI",2003 +"2003-06-19","Corpus Christi","LI",2003 +"2003-08-15","National Day","LI",2003 +"2003-09-08","Nativity of Mary","LI",2003 +"2003-11-01","All Saints' Day","LI",2003 +"2003-12-08","Immaculate Conception","LI",2003 +"2003-12-24","Christmas Eve","LI",2003 +"2003-12-25","Christmas Day","LI",2003 +"2003-12-26","St. Stephen's Day","LI",2003 +"2003-12-31","New Year's Eve","LI",2003 +"2004-01-01","New Year's Day","LI",2004 +"2004-01-02","Saint Berchtold's Day","LI",2004 +"2004-01-06","Epiphany","LI",2004 +"2004-02-02","Candlemas","LI",2004 +"2004-02-24","Shrove Tuesday","LI",2004 +"2004-03-19","Saint Joseph's Day","LI",2004 +"2004-04-09","Good Friday","LI",2004 +"2004-04-11","Easter Sunday","LI",2004 +"2004-04-12","Easter Monday","LI",2004 +"2004-05-01","Labor Day","LI",2004 +"2004-05-20","Ascension Day","LI",2004 +"2004-05-30","Whit Sunday","LI",2004 +"2004-05-31","Whit Monday","LI",2004 +"2004-06-10","Corpus Christi","LI",2004 +"2004-08-15","National Day","LI",2004 +"2004-09-08","Nativity of Mary","LI",2004 +"2004-11-01","All Saints' Day","LI",2004 +"2004-12-08","Immaculate Conception","LI",2004 +"2004-12-24","Christmas Eve","LI",2004 +"2004-12-25","Christmas Day","LI",2004 +"2004-12-26","St. Stephen's Day","LI",2004 +"2004-12-31","New Year's Eve","LI",2004 +"2005-01-01","New Year's Day","LI",2005 +"2005-01-02","Saint Berchtold's Day","LI",2005 +"2005-01-06","Epiphany","LI",2005 +"2005-02-02","Candlemas","LI",2005 +"2005-02-08","Shrove Tuesday","LI",2005 +"2005-03-19","Saint Joseph's Day","LI",2005 +"2005-03-25","Good Friday","LI",2005 +"2005-03-27","Easter Sunday","LI",2005 +"2005-03-28","Easter Monday","LI",2005 +"2005-05-01","Labor Day","LI",2005 +"2005-05-05","Ascension Day","LI",2005 +"2005-05-15","Whit Sunday","LI",2005 +"2005-05-16","Whit Monday","LI",2005 +"2005-05-26","Corpus Christi","LI",2005 +"2005-08-15","National Day","LI",2005 +"2005-09-08","Nativity of Mary","LI",2005 +"2005-11-01","All Saints' Day","LI",2005 +"2005-12-08","Immaculate Conception","LI",2005 +"2005-12-24","Christmas Eve","LI",2005 +"2005-12-25","Christmas Day","LI",2005 +"2005-12-26","St. Stephen's Day","LI",2005 +"2005-12-31","New Year's Eve","LI",2005 +"2006-01-01","New Year's Day","LI",2006 +"2006-01-02","Saint Berchtold's Day","LI",2006 +"2006-01-06","Epiphany","LI",2006 +"2006-02-02","Candlemas","LI",2006 +"2006-02-28","Shrove Tuesday","LI",2006 +"2006-03-19","Saint Joseph's Day","LI",2006 +"2006-04-14","Good Friday","LI",2006 +"2006-04-16","Easter Sunday","LI",2006 +"2006-04-17","Easter Monday","LI",2006 +"2006-05-01","Labor Day","LI",2006 +"2006-05-25","Ascension Day","LI",2006 +"2006-06-04","Whit Sunday","LI",2006 +"2006-06-05","Whit Monday","LI",2006 +"2006-06-15","Corpus Christi","LI",2006 +"2006-08-15","National Day","LI",2006 +"2006-09-08","Nativity of Mary","LI",2006 +"2006-11-01","All Saints' Day","LI",2006 +"2006-12-08","Immaculate Conception","LI",2006 +"2006-12-24","Christmas Eve","LI",2006 +"2006-12-25","Christmas Day","LI",2006 +"2006-12-26","St. Stephen's Day","LI",2006 +"2006-12-31","New Year's Eve","LI",2006 +"2007-01-01","New Year's Day","LI",2007 +"2007-01-02","Saint Berchtold's Day","LI",2007 +"2007-01-06","Epiphany","LI",2007 +"2007-02-02","Candlemas","LI",2007 +"2007-02-20","Shrove Tuesday","LI",2007 +"2007-03-19","Saint Joseph's Day","LI",2007 +"2007-04-06","Good Friday","LI",2007 +"2007-04-08","Easter Sunday","LI",2007 +"2007-04-09","Easter Monday","LI",2007 +"2007-05-01","Labor Day","LI",2007 +"2007-05-17","Ascension Day","LI",2007 +"2007-05-27","Whit Sunday","LI",2007 +"2007-05-28","Whit Monday","LI",2007 +"2007-06-07","Corpus Christi","LI",2007 +"2007-08-15","National Day","LI",2007 +"2007-09-08","Nativity of Mary","LI",2007 +"2007-11-01","All Saints' Day","LI",2007 +"2007-12-08","Immaculate Conception","LI",2007 +"2007-12-24","Christmas Eve","LI",2007 +"2007-12-25","Christmas Day","LI",2007 +"2007-12-26","St. Stephen's Day","LI",2007 +"2007-12-31","New Year's Eve","LI",2007 +"2008-01-01","New Year's Day","LI",2008 +"2008-01-02","Saint Berchtold's Day","LI",2008 +"2008-01-06","Epiphany","LI",2008 +"2008-02-02","Candlemas","LI",2008 +"2008-02-05","Shrove Tuesday","LI",2008 +"2008-03-19","Saint Joseph's Day","LI",2008 +"2008-03-21","Good Friday","LI",2008 +"2008-03-23","Easter Sunday","LI",2008 +"2008-03-24","Easter Monday","LI",2008 +"2008-05-01","Ascension Day","LI",2008 +"2008-05-01","Labor Day","LI",2008 +"2008-05-11","Whit Sunday","LI",2008 +"2008-05-12","Whit Monday","LI",2008 +"2008-05-22","Corpus Christi","LI",2008 +"2008-08-15","National Day","LI",2008 +"2008-09-08","Nativity of Mary","LI",2008 +"2008-11-01","All Saints' Day","LI",2008 +"2008-12-08","Immaculate Conception","LI",2008 +"2008-12-24","Christmas Eve","LI",2008 +"2008-12-25","Christmas Day","LI",2008 +"2008-12-26","St. Stephen's Day","LI",2008 +"2008-12-31","New Year's Eve","LI",2008 +"2009-01-01","New Year's Day","LI",2009 +"2009-01-02","Saint Berchtold's Day","LI",2009 +"2009-01-06","Epiphany","LI",2009 +"2009-02-02","Candlemas","LI",2009 +"2009-02-24","Shrove Tuesday","LI",2009 +"2009-03-19","Saint Joseph's Day","LI",2009 +"2009-04-10","Good Friday","LI",2009 +"2009-04-12","Easter Sunday","LI",2009 +"2009-04-13","Easter Monday","LI",2009 +"2009-05-01","Labor Day","LI",2009 +"2009-05-21","Ascension Day","LI",2009 +"2009-05-31","Whit Sunday","LI",2009 +"2009-06-01","Whit Monday","LI",2009 +"2009-06-11","Corpus Christi","LI",2009 +"2009-08-15","National Day","LI",2009 +"2009-09-08","Nativity of Mary","LI",2009 +"2009-11-01","All Saints' Day","LI",2009 +"2009-12-08","Immaculate Conception","LI",2009 +"2009-12-24","Christmas Eve","LI",2009 +"2009-12-25","Christmas Day","LI",2009 +"2009-12-26","St. Stephen's Day","LI",2009 +"2009-12-31","New Year's Eve","LI",2009 +"2010-01-01","New Year's Day","LI",2010 +"2010-01-02","Saint Berchtold's Day","LI",2010 +"2010-01-06","Epiphany","LI",2010 +"2010-02-02","Candlemas","LI",2010 +"2010-02-16","Shrove Tuesday","LI",2010 +"2010-03-19","Saint Joseph's Day","LI",2010 +"2010-04-02","Good Friday","LI",2010 +"2010-04-04","Easter Sunday","LI",2010 +"2010-04-05","Easter Monday","LI",2010 +"2010-05-01","Labor Day","LI",2010 +"2010-05-13","Ascension Day","LI",2010 +"2010-05-23","Whit Sunday","LI",2010 +"2010-05-24","Whit Monday","LI",2010 +"2010-06-03","Corpus Christi","LI",2010 +"2010-08-15","National Day","LI",2010 +"2010-09-08","Nativity of Mary","LI",2010 +"2010-11-01","All Saints' Day","LI",2010 +"2010-12-08","Immaculate Conception","LI",2010 +"2010-12-24","Christmas Eve","LI",2010 +"2010-12-25","Christmas Day","LI",2010 +"2010-12-26","St. Stephen's Day","LI",2010 +"2010-12-31","New Year's Eve","LI",2010 +"2011-01-01","New Year's Day","LI",2011 +"2011-01-02","Saint Berchtold's Day","LI",2011 +"2011-01-06","Epiphany","LI",2011 +"2011-02-02","Candlemas","LI",2011 +"2011-03-08","Shrove Tuesday","LI",2011 +"2011-03-19","Saint Joseph's Day","LI",2011 +"2011-04-22","Good Friday","LI",2011 +"2011-04-24","Easter Sunday","LI",2011 +"2011-04-25","Easter Monday","LI",2011 +"2011-05-01","Labor Day","LI",2011 +"2011-06-02","Ascension Day","LI",2011 +"2011-06-12","Whit Sunday","LI",2011 +"2011-06-13","Whit Monday","LI",2011 +"2011-06-23","Corpus Christi","LI",2011 +"2011-08-15","National Day","LI",2011 +"2011-09-08","Nativity of Mary","LI",2011 +"2011-11-01","All Saints' Day","LI",2011 +"2011-12-08","Immaculate Conception","LI",2011 +"2011-12-24","Christmas Eve","LI",2011 +"2011-12-25","Christmas Day","LI",2011 +"2011-12-26","St. Stephen's Day","LI",2011 +"2011-12-31","New Year's Eve","LI",2011 +"2012-01-01","New Year's Day","LI",2012 +"2012-01-02","Saint Berchtold's Day","LI",2012 +"2012-01-06","Epiphany","LI",2012 +"2012-02-02","Candlemas","LI",2012 +"2012-02-21","Shrove Tuesday","LI",2012 +"2012-03-19","Saint Joseph's Day","LI",2012 +"2012-04-06","Good Friday","LI",2012 +"2012-04-08","Easter Sunday","LI",2012 +"2012-04-09","Easter Monday","LI",2012 +"2012-05-01","Labor Day","LI",2012 +"2012-05-17","Ascension Day","LI",2012 +"2012-05-27","Whit Sunday","LI",2012 +"2012-05-28","Whit Monday","LI",2012 +"2012-06-07","Corpus Christi","LI",2012 +"2012-08-15","National Day","LI",2012 +"2012-09-08","Nativity of Mary","LI",2012 +"2012-11-01","All Saints' Day","LI",2012 +"2012-12-08","Immaculate Conception","LI",2012 +"2012-12-24","Christmas Eve","LI",2012 +"2012-12-25","Christmas Day","LI",2012 +"2012-12-26","St. Stephen's Day","LI",2012 +"2012-12-31","New Year's Eve","LI",2012 +"2013-01-01","New Year's Day","LI",2013 +"2013-01-02","Saint Berchtold's Day","LI",2013 +"2013-01-06","Epiphany","LI",2013 +"2013-02-02","Candlemas","LI",2013 +"2013-02-12","Shrove Tuesday","LI",2013 +"2013-03-19","Saint Joseph's Day","LI",2013 +"2013-03-29","Good Friday","LI",2013 +"2013-03-31","Easter Sunday","LI",2013 +"2013-04-01","Easter Monday","LI",2013 +"2013-05-01","Labor Day","LI",2013 +"2013-05-09","Ascension Day","LI",2013 +"2013-05-19","Whit Sunday","LI",2013 +"2013-05-20","Whit Monday","LI",2013 +"2013-05-30","Corpus Christi","LI",2013 +"2013-08-15","National Day","LI",2013 +"2013-09-08","Nativity of Mary","LI",2013 +"2013-11-01","All Saints' Day","LI",2013 +"2013-12-08","Immaculate Conception","LI",2013 +"2013-12-24","Christmas Eve","LI",2013 +"2013-12-25","Christmas Day","LI",2013 +"2013-12-26","St. Stephen's Day","LI",2013 +"2013-12-31","New Year's Eve","LI",2013 +"2014-01-01","New Year's Day","LI",2014 +"2014-01-02","Saint Berchtold's Day","LI",2014 +"2014-01-06","Epiphany","LI",2014 +"2014-02-02","Candlemas","LI",2014 +"2014-03-04","Shrove Tuesday","LI",2014 +"2014-03-19","Saint Joseph's Day","LI",2014 +"2014-04-18","Good Friday","LI",2014 +"2014-04-20","Easter Sunday","LI",2014 +"2014-04-21","Easter Monday","LI",2014 +"2014-05-01","Labor Day","LI",2014 +"2014-05-29","Ascension Day","LI",2014 +"2014-06-08","Whit Sunday","LI",2014 +"2014-06-09","Whit Monday","LI",2014 +"2014-06-19","Corpus Christi","LI",2014 +"2014-08-15","National Day","LI",2014 +"2014-09-08","Nativity of Mary","LI",2014 +"2014-11-01","All Saints' Day","LI",2014 +"2014-12-08","Immaculate Conception","LI",2014 +"2014-12-24","Christmas Eve","LI",2014 +"2014-12-25","Christmas Day","LI",2014 +"2014-12-26","St. Stephen's Day","LI",2014 +"2014-12-31","New Year's Eve","LI",2014 +"2015-01-01","New Year's Day","LI",2015 +"2015-01-02","Saint Berchtold's Day","LI",2015 +"2015-01-06","Epiphany","LI",2015 +"2015-02-02","Candlemas","LI",2015 +"2015-02-17","Shrove Tuesday","LI",2015 +"2015-03-19","Saint Joseph's Day","LI",2015 +"2015-04-03","Good Friday","LI",2015 +"2015-04-05","Easter Sunday","LI",2015 +"2015-04-06","Easter Monday","LI",2015 +"2015-05-01","Labor Day","LI",2015 +"2015-05-14","Ascension Day","LI",2015 +"2015-05-24","Whit Sunday","LI",2015 +"2015-05-25","Whit Monday","LI",2015 +"2015-06-04","Corpus Christi","LI",2015 +"2015-08-15","National Day","LI",2015 +"2015-09-08","Nativity of Mary","LI",2015 +"2015-11-01","All Saints' Day","LI",2015 +"2015-12-08","Immaculate Conception","LI",2015 +"2015-12-24","Christmas Eve","LI",2015 +"2015-12-25","Christmas Day","LI",2015 +"2015-12-26","St. Stephen's Day","LI",2015 +"2015-12-31","New Year's Eve","LI",2015 +"2016-01-01","New Year's Day","LI",2016 +"2016-01-02","Saint Berchtold's Day","LI",2016 +"2016-01-06","Epiphany","LI",2016 +"2016-02-02","Candlemas","LI",2016 +"2016-02-09","Shrove Tuesday","LI",2016 +"2016-03-19","Saint Joseph's Day","LI",2016 +"2016-03-25","Good Friday","LI",2016 +"2016-03-27","Easter Sunday","LI",2016 +"2016-03-28","Easter Monday","LI",2016 +"2016-05-01","Labor Day","LI",2016 +"2016-05-05","Ascension Day","LI",2016 +"2016-05-15","Whit Sunday","LI",2016 +"2016-05-16","Whit Monday","LI",2016 +"2016-05-26","Corpus Christi","LI",2016 +"2016-08-15","National Day","LI",2016 +"2016-09-08","Nativity of Mary","LI",2016 +"2016-11-01","All Saints' Day","LI",2016 +"2016-12-08","Immaculate Conception","LI",2016 +"2016-12-24","Christmas Eve","LI",2016 +"2016-12-25","Christmas Day","LI",2016 +"2016-12-26","St. Stephen's Day","LI",2016 +"2016-12-31","New Year's Eve","LI",2016 +"2017-01-01","New Year's Day","LI",2017 +"2017-01-02","Saint Berchtold's Day","LI",2017 +"2017-01-06","Epiphany","LI",2017 +"2017-02-02","Candlemas","LI",2017 +"2017-02-28","Shrove Tuesday","LI",2017 +"2017-03-19","Saint Joseph's Day","LI",2017 +"2017-04-14","Good Friday","LI",2017 +"2017-04-16","Easter Sunday","LI",2017 +"2017-04-17","Easter Monday","LI",2017 +"2017-05-01","Labor Day","LI",2017 +"2017-05-25","Ascension Day","LI",2017 +"2017-06-04","Whit Sunday","LI",2017 +"2017-06-05","Whit Monday","LI",2017 +"2017-06-15","Corpus Christi","LI",2017 +"2017-08-15","National Day","LI",2017 +"2017-09-08","Nativity of Mary","LI",2017 +"2017-11-01","All Saints' Day","LI",2017 +"2017-12-08","Immaculate Conception","LI",2017 +"2017-12-24","Christmas Eve","LI",2017 +"2017-12-25","Christmas Day","LI",2017 +"2017-12-26","St. Stephen's Day","LI",2017 +"2017-12-31","New Year's Eve","LI",2017 +"2018-01-01","New Year's Day","LI",2018 +"2018-01-02","Saint Berchtold's Day","LI",2018 +"2018-01-06","Epiphany","LI",2018 +"2018-02-02","Candlemas","LI",2018 +"2018-02-13","Shrove Tuesday","LI",2018 +"2018-03-19","Saint Joseph's Day","LI",2018 +"2018-03-30","Good Friday","LI",2018 +"2018-04-01","Easter Sunday","LI",2018 +"2018-04-02","Easter Monday","LI",2018 +"2018-05-01","Labor Day","LI",2018 +"2018-05-10","Ascension Day","LI",2018 +"2018-05-20","Whit Sunday","LI",2018 +"2018-05-21","Whit Monday","LI",2018 +"2018-05-31","Corpus Christi","LI",2018 +"2018-08-15","National Day","LI",2018 +"2018-09-08","Nativity of Mary","LI",2018 +"2018-11-01","All Saints' Day","LI",2018 +"2018-12-08","Immaculate Conception","LI",2018 +"2018-12-24","Christmas Eve","LI",2018 +"2018-12-25","Christmas Day","LI",2018 +"2018-12-26","St. Stephen's Day","LI",2018 +"2018-12-31","New Year's Eve","LI",2018 +"2019-01-01","New Year's Day","LI",2019 +"2019-01-02","Saint Berchtold's Day","LI",2019 +"2019-01-06","Epiphany","LI",2019 +"2019-02-02","Candlemas","LI",2019 +"2019-03-05","Shrove Tuesday","LI",2019 +"2019-03-19","Saint Joseph's Day","LI",2019 +"2019-04-19","Good Friday","LI",2019 +"2019-04-21","Easter Sunday","LI",2019 +"2019-04-22","Easter Monday","LI",2019 +"2019-05-01","Labor Day","LI",2019 +"2019-05-30","Ascension Day","LI",2019 +"2019-06-09","Whit Sunday","LI",2019 +"2019-06-10","Whit Monday","LI",2019 +"2019-06-20","Corpus Christi","LI",2019 +"2019-08-15","National Day","LI",2019 +"2019-09-08","Nativity of Mary","LI",2019 +"2019-11-01","All Saints' Day","LI",2019 +"2019-12-08","Immaculate Conception","LI",2019 +"2019-12-24","Christmas Eve","LI",2019 +"2019-12-25","Christmas Day","LI",2019 +"2019-12-26","St. Stephen's Day","LI",2019 +"2019-12-31","New Year's Eve","LI",2019 +"2020-01-01","New Year's Day","LI",2020 +"2020-01-02","Saint Berchtold's Day","LI",2020 +"2020-01-06","Epiphany","LI",2020 +"2020-02-02","Candlemas","LI",2020 +"2020-02-25","Shrove Tuesday","LI",2020 +"2020-03-19","Saint Joseph's Day","LI",2020 +"2020-04-10","Good Friday","LI",2020 +"2020-04-12","Easter Sunday","LI",2020 +"2020-04-13","Easter Monday","LI",2020 +"2020-05-01","Labor Day","LI",2020 +"2020-05-21","Ascension Day","LI",2020 +"2020-05-31","Whit Sunday","LI",2020 +"2020-06-01","Whit Monday","LI",2020 +"2020-06-11","Corpus Christi","LI",2020 +"2020-08-15","National Day","LI",2020 +"2020-09-08","Nativity of Mary","LI",2020 +"2020-11-01","All Saints' Day","LI",2020 +"2020-12-08","Immaculate Conception","LI",2020 +"2020-12-24","Christmas Eve","LI",2020 +"2020-12-25","Christmas Day","LI",2020 +"2020-12-26","St. Stephen's Day","LI",2020 +"2020-12-31","New Year's Eve","LI",2020 +"2021-01-01","New Year's Day","LI",2021 +"2021-01-02","Saint Berchtold's Day","LI",2021 +"2021-01-06","Epiphany","LI",2021 +"2021-02-02","Candlemas","LI",2021 +"2021-02-16","Shrove Tuesday","LI",2021 +"2021-03-19","Saint Joseph's Day","LI",2021 +"2021-04-02","Good Friday","LI",2021 +"2021-04-04","Easter Sunday","LI",2021 +"2021-04-05","Easter Monday","LI",2021 +"2021-05-01","Labor Day","LI",2021 +"2021-05-13","Ascension Day","LI",2021 +"2021-05-23","Whit Sunday","LI",2021 +"2021-05-24","Whit Monday","LI",2021 +"2021-06-03","Corpus Christi","LI",2021 +"2021-08-15","National Day","LI",2021 +"2021-09-08","Nativity of Mary","LI",2021 +"2021-11-01","All Saints' Day","LI",2021 +"2021-12-08","Immaculate Conception","LI",2021 +"2021-12-24","Christmas Eve","LI",2021 +"2021-12-25","Christmas Day","LI",2021 +"2021-12-26","St. Stephen's Day","LI",2021 +"2021-12-31","New Year's Eve","LI",2021 +"2022-01-01","New Year's Day","LI",2022 +"2022-01-02","Saint Berchtold's Day","LI",2022 +"2022-01-06","Epiphany","LI",2022 +"2022-02-02","Candlemas","LI",2022 +"2022-03-01","Shrove Tuesday","LI",2022 +"2022-03-19","Saint Joseph's Day","LI",2022 +"2022-04-15","Good Friday","LI",2022 +"2022-04-17","Easter Sunday","LI",2022 +"2022-04-18","Easter Monday","LI",2022 +"2022-05-01","Labor Day","LI",2022 +"2022-05-26","Ascension Day","LI",2022 +"2022-06-05","Whit Sunday","LI",2022 +"2022-06-06","Whit Monday","LI",2022 +"2022-06-16","Corpus Christi","LI",2022 +"2022-08-15","National Day","LI",2022 +"2022-09-08","Nativity of Mary","LI",2022 +"2022-11-01","All Saints' Day","LI",2022 +"2022-12-08","Immaculate Conception","LI",2022 +"2022-12-24","Christmas Eve","LI",2022 +"2022-12-25","Christmas Day","LI",2022 +"2022-12-26","St. Stephen's Day","LI",2022 +"2022-12-31","New Year's Eve","LI",2022 +"2023-01-01","New Year's Day","LI",2023 +"2023-01-02","Saint Berchtold's Day","LI",2023 +"2023-01-06","Epiphany","LI",2023 +"2023-02-02","Candlemas","LI",2023 +"2023-02-21","Shrove Tuesday","LI",2023 +"2023-03-19","Saint Joseph's Day","LI",2023 +"2023-04-07","Good Friday","LI",2023 +"2023-04-09","Easter Sunday","LI",2023 +"2023-04-10","Easter Monday","LI",2023 +"2023-05-01","Labor Day","LI",2023 +"2023-05-18","Ascension Day","LI",2023 +"2023-05-28","Whit Sunday","LI",2023 +"2023-05-29","Whit Monday","LI",2023 +"2023-06-08","Corpus Christi","LI",2023 +"2023-08-15","National Day","LI",2023 +"2023-09-08","Nativity of Mary","LI",2023 +"2023-11-01","All Saints' Day","LI",2023 +"2023-12-08","Immaculate Conception","LI",2023 +"2023-12-24","Christmas Eve","LI",2023 +"2023-12-25","Christmas Day","LI",2023 +"2023-12-26","St. Stephen's Day","LI",2023 +"2023-12-31","New Year's Eve","LI",2023 +"2024-01-01","New Year's Day","LI",2024 +"2024-01-02","Saint Berchtold's Day","LI",2024 +"2024-01-06","Epiphany","LI",2024 +"2024-02-02","Candlemas","LI",2024 +"2024-02-13","Shrove Tuesday","LI",2024 +"2024-03-19","Saint Joseph's Day","LI",2024 +"2024-03-29","Good Friday","LI",2024 +"2024-03-31","Easter Sunday","LI",2024 +"2024-04-01","Easter Monday","LI",2024 +"2024-05-01","Labor Day","LI",2024 +"2024-05-09","Ascension Day","LI",2024 +"2024-05-19","Whit Sunday","LI",2024 +"2024-05-20","Whit Monday","LI",2024 +"2024-05-30","Corpus Christi","LI",2024 +"2024-08-15","National Day","LI",2024 +"2024-09-08","Nativity of Mary","LI",2024 +"2024-11-01","All Saints' Day","LI",2024 +"2024-12-08","Immaculate Conception","LI",2024 +"2024-12-24","Christmas Eve","LI",2024 +"2024-12-25","Christmas Day","LI",2024 +"2024-12-26","St. Stephen's Day","LI",2024 +"2024-12-31","New Year's Eve","LI",2024 +"2025-01-01","New Year's Day","LI",2025 +"2025-01-02","Saint Berchtold's Day","LI",2025 +"2025-01-06","Epiphany","LI",2025 +"2025-02-02","Candlemas","LI",2025 +"2025-03-04","Shrove Tuesday","LI",2025 +"2025-03-19","Saint Joseph's Day","LI",2025 +"2025-04-18","Good Friday","LI",2025 +"2025-04-20","Easter Sunday","LI",2025 +"2025-04-21","Easter Monday","LI",2025 +"2025-05-01","Labor Day","LI",2025 +"2025-05-29","Ascension Day","LI",2025 +"2025-06-08","Whit Sunday","LI",2025 +"2025-06-09","Whit Monday","LI",2025 +"2025-06-19","Corpus Christi","LI",2025 +"2025-08-15","National Day","LI",2025 +"2025-09-08","Nativity of Mary","LI",2025 +"2025-11-01","All Saints' Day","LI",2025 +"2025-12-08","Immaculate Conception","LI",2025 +"2025-12-24","Christmas Eve","LI",2025 +"2025-12-25","Christmas Day","LI",2025 +"2025-12-26","St. Stephen's Day","LI",2025 +"2025-12-31","New Year's Eve","LI",2025 +"2026-01-01","New Year's Day","LI",2026 +"2026-01-02","Saint Berchtold's Day","LI",2026 +"2026-01-06","Epiphany","LI",2026 +"2026-02-02","Candlemas","LI",2026 +"2026-02-17","Shrove Tuesday","LI",2026 +"2026-03-19","Saint Joseph's Day","LI",2026 +"2026-04-03","Good Friday","LI",2026 +"2026-04-05","Easter Sunday","LI",2026 +"2026-04-06","Easter Monday","LI",2026 +"2026-05-01","Labor Day","LI",2026 +"2026-05-14","Ascension Day","LI",2026 +"2026-05-24","Whit Sunday","LI",2026 +"2026-05-25","Whit Monday","LI",2026 +"2026-06-04","Corpus Christi","LI",2026 +"2026-08-15","National Day","LI",2026 +"2026-09-08","Nativity of Mary","LI",2026 +"2026-11-01","All Saints' Day","LI",2026 +"2026-12-08","Immaculate Conception","LI",2026 +"2026-12-24","Christmas Eve","LI",2026 +"2026-12-25","Christmas Day","LI",2026 +"2026-12-26","St. Stephen's Day","LI",2026 +"2026-12-31","New Year's Eve","LI",2026 +"2027-01-01","New Year's Day","LI",2027 +"2027-01-02","Saint Berchtold's Day","LI",2027 +"2027-01-06","Epiphany","LI",2027 +"2027-02-02","Candlemas","LI",2027 +"2027-02-09","Shrove Tuesday","LI",2027 +"2027-03-19","Saint Joseph's Day","LI",2027 +"2027-03-26","Good Friday","LI",2027 +"2027-03-28","Easter Sunday","LI",2027 +"2027-03-29","Easter Monday","LI",2027 +"2027-05-01","Labor Day","LI",2027 +"2027-05-06","Ascension Day","LI",2027 +"2027-05-16","Whit Sunday","LI",2027 +"2027-05-17","Whit Monday","LI",2027 +"2027-05-27","Corpus Christi","LI",2027 +"2027-08-15","National Day","LI",2027 +"2027-09-08","Nativity of Mary","LI",2027 +"2027-11-01","All Saints' Day","LI",2027 +"2027-12-08","Immaculate Conception","LI",2027 +"2027-12-24","Christmas Eve","LI",2027 +"2027-12-25","Christmas Day","LI",2027 +"2027-12-26","St. Stephen's Day","LI",2027 +"2027-12-31","New Year's Eve","LI",2027 +"2028-01-01","New Year's Day","LI",2028 +"2028-01-02","Saint Berchtold's Day","LI",2028 +"2028-01-06","Epiphany","LI",2028 +"2028-02-02","Candlemas","LI",2028 +"2028-02-29","Shrove Tuesday","LI",2028 +"2028-03-19","Saint Joseph's Day","LI",2028 +"2028-04-14","Good Friday","LI",2028 +"2028-04-16","Easter Sunday","LI",2028 +"2028-04-17","Easter Monday","LI",2028 +"2028-05-01","Labor Day","LI",2028 +"2028-05-25","Ascension Day","LI",2028 +"2028-06-04","Whit Sunday","LI",2028 +"2028-06-05","Whit Monday","LI",2028 +"2028-06-15","Corpus Christi","LI",2028 +"2028-08-15","National Day","LI",2028 +"2028-09-08","Nativity of Mary","LI",2028 +"2028-11-01","All Saints' Day","LI",2028 +"2028-12-08","Immaculate Conception","LI",2028 +"2028-12-24","Christmas Eve","LI",2028 +"2028-12-25","Christmas Day","LI",2028 +"2028-12-26","St. Stephen's Day","LI",2028 +"2028-12-31","New Year's Eve","LI",2028 +"2029-01-01","New Year's Day","LI",2029 +"2029-01-02","Saint Berchtold's Day","LI",2029 +"2029-01-06","Epiphany","LI",2029 +"2029-02-02","Candlemas","LI",2029 +"2029-02-13","Shrove Tuesday","LI",2029 +"2029-03-19","Saint Joseph's Day","LI",2029 +"2029-03-30","Good Friday","LI",2029 +"2029-04-01","Easter Sunday","LI",2029 +"2029-04-02","Easter Monday","LI",2029 +"2029-05-01","Labor Day","LI",2029 +"2029-05-10","Ascension Day","LI",2029 +"2029-05-20","Whit Sunday","LI",2029 +"2029-05-21","Whit Monday","LI",2029 +"2029-05-31","Corpus Christi","LI",2029 +"2029-08-15","National Day","LI",2029 +"2029-09-08","Nativity of Mary","LI",2029 +"2029-11-01","All Saints' Day","LI",2029 +"2029-12-08","Immaculate Conception","LI",2029 +"2029-12-24","Christmas Eve","LI",2029 +"2029-12-25","Christmas Day","LI",2029 +"2029-12-26","St. Stephen's Day","LI",2029 +"2029-12-31","New Year's Eve","LI",2029 +"2030-01-01","New Year's Day","LI",2030 +"2030-01-02","Saint Berchtold's Day","LI",2030 +"2030-01-06","Epiphany","LI",2030 +"2030-02-02","Candlemas","LI",2030 +"2030-03-05","Shrove Tuesday","LI",2030 +"2030-03-19","Saint Joseph's Day","LI",2030 +"2030-04-19","Good Friday","LI",2030 +"2030-04-21","Easter Sunday","LI",2030 +"2030-04-22","Easter Monday","LI",2030 +"2030-05-01","Labor Day","LI",2030 +"2030-05-30","Ascension Day","LI",2030 +"2030-06-09","Whit Sunday","LI",2030 +"2030-06-10","Whit Monday","LI",2030 +"2030-06-20","Corpus Christi","LI",2030 +"2030-08-15","National Day","LI",2030 +"2030-09-08","Nativity of Mary","LI",2030 +"2030-11-01","All Saints' Day","LI",2030 +"2030-12-08","Immaculate Conception","LI",2030 +"2030-12-24","Christmas Eve","LI",2030 +"2030-12-25","Christmas Day","LI",2030 +"2030-12-26","St. Stephen's Day","LI",2030 +"2030-12-31","New Year's Eve","LI",2030 +"2031-01-01","New Year's Day","LI",2031 +"2031-01-02","Saint Berchtold's Day","LI",2031 +"2031-01-06","Epiphany","LI",2031 +"2031-02-02","Candlemas","LI",2031 +"2031-02-25","Shrove Tuesday","LI",2031 +"2031-03-19","Saint Joseph's Day","LI",2031 +"2031-04-11","Good Friday","LI",2031 +"2031-04-13","Easter Sunday","LI",2031 +"2031-04-14","Easter Monday","LI",2031 +"2031-05-01","Labor Day","LI",2031 +"2031-05-22","Ascension Day","LI",2031 +"2031-06-01","Whit Sunday","LI",2031 +"2031-06-02","Whit Monday","LI",2031 +"2031-06-12","Corpus Christi","LI",2031 +"2031-08-15","National Day","LI",2031 +"2031-09-08","Nativity of Mary","LI",2031 +"2031-11-01","All Saints' Day","LI",2031 +"2031-12-08","Immaculate Conception","LI",2031 +"2031-12-24","Christmas Eve","LI",2031 +"2031-12-25","Christmas Day","LI",2031 +"2031-12-26","St. Stephen's Day","LI",2031 +"2031-12-31","New Year's Eve","LI",2031 +"2032-01-01","New Year's Day","LI",2032 +"2032-01-02","Saint Berchtold's Day","LI",2032 +"2032-01-06","Epiphany","LI",2032 +"2032-02-02","Candlemas","LI",2032 +"2032-02-10","Shrove Tuesday","LI",2032 +"2032-03-19","Saint Joseph's Day","LI",2032 +"2032-03-26","Good Friday","LI",2032 +"2032-03-28","Easter Sunday","LI",2032 +"2032-03-29","Easter Monday","LI",2032 +"2032-05-01","Labor Day","LI",2032 +"2032-05-06","Ascension Day","LI",2032 +"2032-05-16","Whit Sunday","LI",2032 +"2032-05-17","Whit Monday","LI",2032 +"2032-05-27","Corpus Christi","LI",2032 +"2032-08-15","National Day","LI",2032 +"2032-09-08","Nativity of Mary","LI",2032 +"2032-11-01","All Saints' Day","LI",2032 +"2032-12-08","Immaculate Conception","LI",2032 +"2032-12-24","Christmas Eve","LI",2032 +"2032-12-25","Christmas Day","LI",2032 +"2032-12-26","St. Stephen's Day","LI",2032 +"2032-12-31","New Year's Eve","LI",2032 +"2033-01-01","New Year's Day","LI",2033 +"2033-01-02","Saint Berchtold's Day","LI",2033 +"2033-01-06","Epiphany","LI",2033 +"2033-02-02","Candlemas","LI",2033 +"2033-03-01","Shrove Tuesday","LI",2033 +"2033-03-19","Saint Joseph's Day","LI",2033 +"2033-04-15","Good Friday","LI",2033 +"2033-04-17","Easter Sunday","LI",2033 +"2033-04-18","Easter Monday","LI",2033 +"2033-05-01","Labor Day","LI",2033 +"2033-05-26","Ascension Day","LI",2033 +"2033-06-05","Whit Sunday","LI",2033 +"2033-06-06","Whit Monday","LI",2033 +"2033-06-16","Corpus Christi","LI",2033 +"2033-08-15","National Day","LI",2033 +"2033-09-08","Nativity of Mary","LI",2033 +"2033-11-01","All Saints' Day","LI",2033 +"2033-12-08","Immaculate Conception","LI",2033 +"2033-12-24","Christmas Eve","LI",2033 +"2033-12-25","Christmas Day","LI",2033 +"2033-12-26","St. Stephen's Day","LI",2033 +"2033-12-31","New Year's Eve","LI",2033 +"2034-01-01","New Year's Day","LI",2034 +"2034-01-02","Saint Berchtold's Day","LI",2034 +"2034-01-06","Epiphany","LI",2034 +"2034-02-02","Candlemas","LI",2034 +"2034-02-21","Shrove Tuesday","LI",2034 +"2034-03-19","Saint Joseph's Day","LI",2034 +"2034-04-07","Good Friday","LI",2034 +"2034-04-09","Easter Sunday","LI",2034 +"2034-04-10","Easter Monday","LI",2034 +"2034-05-01","Labor Day","LI",2034 +"2034-05-18","Ascension Day","LI",2034 +"2034-05-28","Whit Sunday","LI",2034 +"2034-05-29","Whit Monday","LI",2034 +"2034-06-08","Corpus Christi","LI",2034 +"2034-08-15","National Day","LI",2034 +"2034-09-08","Nativity of Mary","LI",2034 +"2034-11-01","All Saints' Day","LI",2034 +"2034-12-08","Immaculate Conception","LI",2034 +"2034-12-24","Christmas Eve","LI",2034 +"2034-12-25","Christmas Day","LI",2034 +"2034-12-26","St. Stephen's Day","LI",2034 +"2034-12-31","New Year's Eve","LI",2034 +"2035-01-01","New Year's Day","LI",2035 +"2035-01-02","Saint Berchtold's Day","LI",2035 +"2035-01-06","Epiphany","LI",2035 +"2035-02-02","Candlemas","LI",2035 +"2035-02-06","Shrove Tuesday","LI",2035 +"2035-03-19","Saint Joseph's Day","LI",2035 +"2035-03-23","Good Friday","LI",2035 +"2035-03-25","Easter Sunday","LI",2035 +"2035-03-26","Easter Monday","LI",2035 +"2035-05-01","Labor Day","LI",2035 +"2035-05-03","Ascension Day","LI",2035 +"2035-05-13","Whit Sunday","LI",2035 +"2035-05-14","Whit Monday","LI",2035 +"2035-05-24","Corpus Christi","LI",2035 +"2035-08-15","National Day","LI",2035 +"2035-09-08","Nativity of Mary","LI",2035 +"2035-11-01","All Saints' Day","LI",2035 +"2035-12-08","Immaculate Conception","LI",2035 +"2035-12-24","Christmas Eve","LI",2035 +"2035-12-25","Christmas Day","LI",2035 +"2035-12-26","St. Stephen's Day","LI",2035 +"2035-12-31","New Year's Eve","LI",2035 +"2036-01-01","New Year's Day","LI",2036 +"2036-01-02","Saint Berchtold's Day","LI",2036 +"2036-01-06","Epiphany","LI",2036 +"2036-02-02","Candlemas","LI",2036 +"2036-02-26","Shrove Tuesday","LI",2036 +"2036-03-19","Saint Joseph's Day","LI",2036 +"2036-04-11","Good Friday","LI",2036 +"2036-04-13","Easter Sunday","LI",2036 +"2036-04-14","Easter Monday","LI",2036 +"2036-05-01","Labor Day","LI",2036 +"2036-05-22","Ascension Day","LI",2036 +"2036-06-01","Whit Sunday","LI",2036 +"2036-06-02","Whit Monday","LI",2036 +"2036-06-12","Corpus Christi","LI",2036 +"2036-08-15","National Day","LI",2036 +"2036-09-08","Nativity of Mary","LI",2036 +"2036-11-01","All Saints' Day","LI",2036 +"2036-12-08","Immaculate Conception","LI",2036 +"2036-12-24","Christmas Eve","LI",2036 +"2036-12-25","Christmas Day","LI",2036 +"2036-12-26","St. Stephen's Day","LI",2036 +"2036-12-31","New Year's Eve","LI",2036 +"2037-01-01","New Year's Day","LI",2037 +"2037-01-02","Saint Berchtold's Day","LI",2037 +"2037-01-06","Epiphany","LI",2037 +"2037-02-02","Candlemas","LI",2037 +"2037-02-17","Shrove Tuesday","LI",2037 +"2037-03-19","Saint Joseph's Day","LI",2037 +"2037-04-03","Good Friday","LI",2037 +"2037-04-05","Easter Sunday","LI",2037 +"2037-04-06","Easter Monday","LI",2037 +"2037-05-01","Labor Day","LI",2037 +"2037-05-14","Ascension Day","LI",2037 +"2037-05-24","Whit Sunday","LI",2037 +"2037-05-25","Whit Monday","LI",2037 +"2037-06-04","Corpus Christi","LI",2037 +"2037-08-15","National Day","LI",2037 +"2037-09-08","Nativity of Mary","LI",2037 +"2037-11-01","All Saints' Day","LI",2037 +"2037-12-08","Immaculate Conception","LI",2037 +"2037-12-24","Christmas Eve","LI",2037 +"2037-12-25","Christmas Day","LI",2037 +"2037-12-26","St. Stephen's Day","LI",2037 +"2037-12-31","New Year's Eve","LI",2037 +"2038-01-01","New Year's Day","LI",2038 +"2038-01-02","Saint Berchtold's Day","LI",2038 +"2038-01-06","Epiphany","LI",2038 +"2038-02-02","Candlemas","LI",2038 +"2038-03-09","Shrove Tuesday","LI",2038 +"2038-03-19","Saint Joseph's Day","LI",2038 +"2038-04-23","Good Friday","LI",2038 +"2038-04-25","Easter Sunday","LI",2038 +"2038-04-26","Easter Monday","LI",2038 +"2038-05-01","Labor Day","LI",2038 +"2038-06-03","Ascension Day","LI",2038 +"2038-06-13","Whit Sunday","LI",2038 +"2038-06-14","Whit Monday","LI",2038 +"2038-06-24","Corpus Christi","LI",2038 +"2038-08-15","National Day","LI",2038 +"2038-09-08","Nativity of Mary","LI",2038 +"2038-11-01","All Saints' Day","LI",2038 +"2038-12-08","Immaculate Conception","LI",2038 +"2038-12-24","Christmas Eve","LI",2038 +"2038-12-25","Christmas Day","LI",2038 +"2038-12-26","St. Stephen's Day","LI",2038 +"2038-12-31","New Year's Eve","LI",2038 +"2039-01-01","New Year's Day","LI",2039 +"2039-01-02","Saint Berchtold's Day","LI",2039 +"2039-01-06","Epiphany","LI",2039 +"2039-02-02","Candlemas","LI",2039 +"2039-02-22","Shrove Tuesday","LI",2039 +"2039-03-19","Saint Joseph's Day","LI",2039 +"2039-04-08","Good Friday","LI",2039 +"2039-04-10","Easter Sunday","LI",2039 +"2039-04-11","Easter Monday","LI",2039 +"2039-05-01","Labor Day","LI",2039 +"2039-05-19","Ascension Day","LI",2039 +"2039-05-29","Whit Sunday","LI",2039 +"2039-05-30","Whit Monday","LI",2039 +"2039-06-09","Corpus Christi","LI",2039 +"2039-08-15","National Day","LI",2039 +"2039-09-08","Nativity of Mary","LI",2039 +"2039-11-01","All Saints' Day","LI",2039 +"2039-12-08","Immaculate Conception","LI",2039 +"2039-12-24","Christmas Eve","LI",2039 +"2039-12-25","Christmas Day","LI",2039 +"2039-12-26","St. Stephen's Day","LI",2039 +"2039-12-31","New Year's Eve","LI",2039 +"2040-01-01","New Year's Day","LI",2040 +"2040-01-02","Saint Berchtold's Day","LI",2040 +"2040-01-06","Epiphany","LI",2040 +"2040-02-02","Candlemas","LI",2040 +"2040-02-14","Shrove Tuesday","LI",2040 +"2040-03-19","Saint Joseph's Day","LI",2040 +"2040-03-30","Good Friday","LI",2040 +"2040-04-01","Easter Sunday","LI",2040 +"2040-04-02","Easter Monday","LI",2040 +"2040-05-01","Labor Day","LI",2040 +"2040-05-10","Ascension Day","LI",2040 +"2040-05-20","Whit Sunday","LI",2040 +"2040-05-21","Whit Monday","LI",2040 +"2040-05-31","Corpus Christi","LI",2040 +"2040-08-15","National Day","LI",2040 +"2040-09-08","Nativity of Mary","LI",2040 +"2040-11-01","All Saints' Day","LI",2040 +"2040-12-08","Immaculate Conception","LI",2040 +"2040-12-24","Christmas Eve","LI",2040 +"2040-12-25","Christmas Day","LI",2040 +"2040-12-26","St. Stephen's Day","LI",2040 +"2040-12-31","New Year's Eve","LI",2040 +"2041-01-01","New Year's Day","LI",2041 +"2041-01-02","Saint Berchtold's Day","LI",2041 +"2041-01-06","Epiphany","LI",2041 +"2041-02-02","Candlemas","LI",2041 +"2041-03-05","Shrove Tuesday","LI",2041 +"2041-03-19","Saint Joseph's Day","LI",2041 +"2041-04-19","Good Friday","LI",2041 +"2041-04-21","Easter Sunday","LI",2041 +"2041-04-22","Easter Monday","LI",2041 +"2041-05-01","Labor Day","LI",2041 +"2041-05-30","Ascension Day","LI",2041 +"2041-06-09","Whit Sunday","LI",2041 +"2041-06-10","Whit Monday","LI",2041 +"2041-06-20","Corpus Christi","LI",2041 +"2041-08-15","National Day","LI",2041 +"2041-09-08","Nativity of Mary","LI",2041 +"2041-11-01","All Saints' Day","LI",2041 +"2041-12-08","Immaculate Conception","LI",2041 +"2041-12-24","Christmas Eve","LI",2041 +"2041-12-25","Christmas Day","LI",2041 +"2041-12-26","St. Stephen's Day","LI",2041 +"2041-12-31","New Year's Eve","LI",2041 +"2042-01-01","New Year's Day","LI",2042 +"2042-01-02","Saint Berchtold's Day","LI",2042 +"2042-01-06","Epiphany","LI",2042 +"2042-02-02","Candlemas","LI",2042 +"2042-02-18","Shrove Tuesday","LI",2042 +"2042-03-19","Saint Joseph's Day","LI",2042 +"2042-04-04","Good Friday","LI",2042 +"2042-04-06","Easter Sunday","LI",2042 +"2042-04-07","Easter Monday","LI",2042 +"2042-05-01","Labor Day","LI",2042 +"2042-05-15","Ascension Day","LI",2042 +"2042-05-25","Whit Sunday","LI",2042 +"2042-05-26","Whit Monday","LI",2042 +"2042-06-05","Corpus Christi","LI",2042 +"2042-08-15","National Day","LI",2042 +"2042-09-08","Nativity of Mary","LI",2042 +"2042-11-01","All Saints' Day","LI",2042 +"2042-12-08","Immaculate Conception","LI",2042 +"2042-12-24","Christmas Eve","LI",2042 +"2042-12-25","Christmas Day","LI",2042 +"2042-12-26","St. Stephen's Day","LI",2042 +"2042-12-31","New Year's Eve","LI",2042 +"2043-01-01","New Year's Day","LI",2043 +"2043-01-02","Saint Berchtold's Day","LI",2043 +"2043-01-06","Epiphany","LI",2043 +"2043-02-02","Candlemas","LI",2043 +"2043-02-10","Shrove Tuesday","LI",2043 +"2043-03-19","Saint Joseph's Day","LI",2043 +"2043-03-27","Good Friday","LI",2043 +"2043-03-29","Easter Sunday","LI",2043 +"2043-03-30","Easter Monday","LI",2043 +"2043-05-01","Labor Day","LI",2043 +"2043-05-07","Ascension Day","LI",2043 +"2043-05-17","Whit Sunday","LI",2043 +"2043-05-18","Whit Monday","LI",2043 +"2043-05-28","Corpus Christi","LI",2043 +"2043-08-15","National Day","LI",2043 +"2043-09-08","Nativity of Mary","LI",2043 +"2043-11-01","All Saints' Day","LI",2043 +"2043-12-08","Immaculate Conception","LI",2043 +"2043-12-24","Christmas Eve","LI",2043 +"2043-12-25","Christmas Day","LI",2043 +"2043-12-26","St. Stephen's Day","LI",2043 +"2043-12-31","New Year's Eve","LI",2043 +"2044-01-01","New Year's Day","LI",2044 +"2044-01-02","Saint Berchtold's Day","LI",2044 +"2044-01-06","Epiphany","LI",2044 +"2044-02-02","Candlemas","LI",2044 +"2044-03-01","Shrove Tuesday","LI",2044 +"2044-03-19","Saint Joseph's Day","LI",2044 +"2044-04-15","Good Friday","LI",2044 +"2044-04-17","Easter Sunday","LI",2044 +"2044-04-18","Easter Monday","LI",2044 +"2044-05-01","Labor Day","LI",2044 +"2044-05-26","Ascension Day","LI",2044 +"2044-06-05","Whit Sunday","LI",2044 +"2044-06-06","Whit Monday","LI",2044 +"2044-06-16","Corpus Christi","LI",2044 +"2044-08-15","National Day","LI",2044 +"2044-09-08","Nativity of Mary","LI",2044 +"2044-11-01","All Saints' Day","LI",2044 +"2044-12-08","Immaculate Conception","LI",2044 +"2044-12-24","Christmas Eve","LI",2044 +"2044-12-25","Christmas Day","LI",2044 +"2044-12-26","St. Stephen's Day","LI",2044 +"2044-12-31","New Year's Eve","LI",2044 +"1996-01-01","New Year's Day","LS",1996 +"1996-03-11","Moshoeshoe's Day","LS",1996 +"1996-04-04","Heroes Day","LS",1996 +"1996-04-05","Good Friday","LS",1996 +"1996-04-08","Easter Monday","LS",1996 +"1996-05-01","Workers' Day","LS",1996 +"1996-05-02","King's Birthday","LS",1996 +"1996-05-16","Ascension Day","LS",1996 +"1996-10-04","National Independence Day","LS",1996 +"1996-12-25","Christmas Day","LS",1996 +"1996-12-26","Boxing Day","LS",1996 +"1997-01-01","New Year's Day","LS",1997 +"1997-03-11","Moshoeshoe's Day","LS",1997 +"1997-03-28","Good Friday","LS",1997 +"1997-03-31","Easter Monday","LS",1997 +"1997-04-04","Heroes Day","LS",1997 +"1997-05-01","Workers' Day","LS",1997 +"1997-05-02","King's Birthday","LS",1997 +"1997-05-08","Ascension Day","LS",1997 +"1997-10-04","National Independence Day","LS",1997 +"1997-12-25","Christmas Day","LS",1997 +"1997-12-26","Boxing Day","LS",1997 +"1998-01-01","New Year's Day","LS",1998 +"1998-03-11","Moshoeshoe's Day","LS",1998 +"1998-04-04","Heroes Day","LS",1998 +"1998-04-10","Good Friday","LS",1998 +"1998-04-13","Easter Monday","LS",1998 +"1998-05-01","Workers' Day","LS",1998 +"1998-05-21","Ascension Day","LS",1998 +"1998-07-17","King's Birthday","LS",1998 +"1998-10-04","National Independence Day","LS",1998 +"1998-12-25","Christmas Day","LS",1998 +"1998-12-26","Boxing Day","LS",1998 +"1999-01-01","New Year's Day","LS",1999 +"1999-03-11","Moshoeshoe's Day","LS",1999 +"1999-04-02","Good Friday","LS",1999 +"1999-04-04","Heroes Day","LS",1999 +"1999-04-05","Easter Monday","LS",1999 +"1999-05-01","Workers' Day","LS",1999 +"1999-05-13","Ascension Day","LS",1999 +"1999-07-17","King's Birthday","LS",1999 +"1999-10-04","National Independence Day","LS",1999 +"1999-12-25","Christmas Day","LS",1999 +"1999-12-26","Boxing Day","LS",1999 +"2000-01-01","New Year's Day","LS",2000 +"2000-03-11","Moshoeshoe's Day","LS",2000 +"2000-04-04","Heroes Day","LS",2000 +"2000-04-21","Good Friday","LS",2000 +"2000-04-24","Easter Monday","LS",2000 +"2000-05-01","Workers' Day","LS",2000 +"2000-06-01","Ascension Day","LS",2000 +"2000-07-17","King's Birthday","LS",2000 +"2000-10-04","National Independence Day","LS",2000 +"2000-12-25","Christmas Day","LS",2000 +"2000-12-26","Boxing Day","LS",2000 +"2001-01-01","New Year's Day","LS",2001 +"2001-03-11","Moshoeshoe's Day","LS",2001 +"2001-04-04","Heroes Day","LS",2001 +"2001-04-13","Good Friday","LS",2001 +"2001-04-16","Easter Monday","LS",2001 +"2001-05-01","Workers' Day","LS",2001 +"2001-05-24","Ascension Day","LS",2001 +"2001-07-17","King's Birthday","LS",2001 +"2001-10-04","National Independence Day","LS",2001 +"2001-12-25","Christmas Day","LS",2001 +"2001-12-26","Boxing Day","LS",2001 +"2002-01-01","New Year's Day","LS",2002 +"2002-03-11","Moshoeshoe's Day","LS",2002 +"2002-03-29","Good Friday","LS",2002 +"2002-04-01","Easter Monday","LS",2002 +"2002-04-04","Heroes Day","LS",2002 +"2002-05-01","Workers' Day","LS",2002 +"2002-05-09","Ascension Day","LS",2002 +"2002-05-25","Africa Day","LS",2002 +"2002-07-17","King's Birthday","LS",2002 +"2002-10-04","National Independence Day","LS",2002 +"2002-12-25","Christmas Day","LS",2002 +"2002-12-26","Boxing Day","LS",2002 +"2003-01-01","New Year's Day","LS",2003 +"2003-03-11","Moshoeshoe's Day","LS",2003 +"2003-04-18","Good Friday","LS",2003 +"2003-04-21","Easter Monday","LS",2003 +"2003-05-01","Workers' Day","LS",2003 +"2003-05-25","Africa/Heroes Day","LS",2003 +"2003-05-29","Ascension Day","LS",2003 +"2003-07-17","King's Birthday","LS",2003 +"2003-10-04","National Independence Day","LS",2003 +"2003-12-25","Christmas Day","LS",2003 +"2003-12-26","Boxing Day","LS",2003 +"2004-01-01","New Year's Day","LS",2004 +"2004-03-11","Moshoeshoe's Day","LS",2004 +"2004-04-09","Good Friday","LS",2004 +"2004-04-12","Easter Monday","LS",2004 +"2004-05-01","Workers' Day","LS",2004 +"2004-05-20","Ascension Day","LS",2004 +"2004-05-25","Africa/Heroes Day","LS",2004 +"2004-07-17","King's Birthday","LS",2004 +"2004-10-04","National Independence Day","LS",2004 +"2004-12-25","Christmas Day","LS",2004 +"2004-12-26","Boxing Day","LS",2004 +"2005-01-01","New Year's Day","LS",2005 +"2005-03-11","Moshoeshoe's Day","LS",2005 +"2005-03-25","Good Friday","LS",2005 +"2005-03-28","Easter Monday","LS",2005 +"2005-05-01","Workers' Day","LS",2005 +"2005-05-05","Ascension Day","LS",2005 +"2005-05-25","Africa/Heroes Day","LS",2005 +"2005-07-17","King's Birthday","LS",2005 +"2005-10-04","National Independence Day","LS",2005 +"2005-12-25","Christmas Day","LS",2005 +"2005-12-26","Boxing Day","LS",2005 +"2006-01-01","New Year's Day","LS",2006 +"2006-03-11","Moshoeshoe's Day","LS",2006 +"2006-04-14","Good Friday","LS",2006 +"2006-04-17","Easter Monday","LS",2006 +"2006-05-01","Workers' Day","LS",2006 +"2006-05-25","Africa/Heroes Day","LS",2006 +"2006-05-25","Ascension Day","LS",2006 +"2006-07-17","King's Birthday","LS",2006 +"2006-10-04","National Independence Day","LS",2006 +"2006-12-25","Christmas Day","LS",2006 +"2006-12-26","Boxing Day","LS",2006 +"2007-01-01","New Year's Day","LS",2007 +"2007-03-11","Moshoeshoe's Day","LS",2007 +"2007-04-06","Good Friday","LS",2007 +"2007-04-09","Easter Monday","LS",2007 +"2007-05-01","Workers' Day","LS",2007 +"2007-05-17","Ascension Day","LS",2007 +"2007-05-25","Africa/Heroes Day","LS",2007 +"2007-07-17","King's Birthday","LS",2007 +"2007-10-04","National Independence Day","LS",2007 +"2007-12-25","Christmas Day","LS",2007 +"2007-12-26","Boxing Day","LS",2007 +"2008-01-01","New Year's Day","LS",2008 +"2008-03-11","Moshoeshoe's Day","LS",2008 +"2008-03-21","Good Friday","LS",2008 +"2008-03-24","Easter Monday","LS",2008 +"2008-05-01","Ascension Day","LS",2008 +"2008-05-01","Workers' Day","LS",2008 +"2008-05-25","Africa/Heroes Day","LS",2008 +"2008-07-17","King's Birthday","LS",2008 +"2008-10-04","National Independence Day","LS",2008 +"2008-12-25","Christmas Day","LS",2008 +"2008-12-26","Boxing Day","LS",2008 +"2009-01-01","New Year's Day","LS",2009 +"2009-03-11","Moshoeshoe's Day","LS",2009 +"2009-04-10","Good Friday","LS",2009 +"2009-04-13","Easter Monday","LS",2009 +"2009-05-01","Workers' Day","LS",2009 +"2009-05-21","Ascension Day","LS",2009 +"2009-05-25","Africa/Heroes Day","LS",2009 +"2009-07-17","King's Birthday","LS",2009 +"2009-10-04","National Independence Day","LS",2009 +"2009-12-25","Christmas Day","LS",2009 +"2009-12-26","Boxing Day","LS",2009 +"2010-01-01","New Year's Day","LS",2010 +"2010-03-11","Moshoeshoe's Day","LS",2010 +"2010-04-02","Good Friday","LS",2010 +"2010-04-05","Easter Monday","LS",2010 +"2010-05-01","Workers' Day","LS",2010 +"2010-05-13","Ascension Day","LS",2010 +"2010-05-25","Africa/Heroes Day","LS",2010 +"2010-07-17","King's Birthday","LS",2010 +"2010-10-04","National Independence Day","LS",2010 +"2010-12-25","Christmas Day","LS",2010 +"2010-12-26","Boxing Day","LS",2010 +"2011-01-01","New Year's Day","LS",2011 +"2011-03-11","Moshoeshoe's Day","LS",2011 +"2011-04-22","Good Friday","LS",2011 +"2011-04-25","Easter Monday","LS",2011 +"2011-05-01","Workers' Day","LS",2011 +"2011-05-25","Africa/Heroes Day","LS",2011 +"2011-06-02","Ascension Day","LS",2011 +"2011-07-17","King's Birthday","LS",2011 +"2011-10-04","National Independence Day","LS",2011 +"2011-12-25","Christmas Day","LS",2011 +"2011-12-26","Boxing Day","LS",2011 +"2012-01-01","New Year's Day","LS",2012 +"2012-03-11","Moshoeshoe's Day","LS",2012 +"2012-04-06","Good Friday","LS",2012 +"2012-04-09","Easter Monday","LS",2012 +"2012-05-01","Workers' Day","LS",2012 +"2012-05-17","Ascension Day","LS",2012 +"2012-05-25","Africa/Heroes Day","LS",2012 +"2012-07-17","King's Birthday","LS",2012 +"2012-10-04","National Independence Day","LS",2012 +"2012-12-25","Christmas Day","LS",2012 +"2012-12-26","Boxing Day","LS",2012 +"2013-01-01","New Year's Day","LS",2013 +"2013-03-11","Moshoeshoe's Day","LS",2013 +"2013-03-29","Good Friday","LS",2013 +"2013-04-01","Easter Monday","LS",2013 +"2013-05-01","Workers' Day","LS",2013 +"2013-05-09","Ascension Day","LS",2013 +"2013-05-25","Africa/Heroes Day","LS",2013 +"2013-07-17","King's Birthday","LS",2013 +"2013-10-04","National Independence Day","LS",2013 +"2013-12-25","Christmas Day","LS",2013 +"2013-12-26","Boxing Day","LS",2013 +"2014-01-01","New Year's Day","LS",2014 +"2014-03-11","Moshoeshoe's Day","LS",2014 +"2014-04-18","Good Friday","LS",2014 +"2014-04-21","Easter Monday","LS",2014 +"2014-05-01","Workers' Day","LS",2014 +"2014-05-25","Africa/Heroes Day","LS",2014 +"2014-05-29","Ascension Day","LS",2014 +"2014-07-17","King's Birthday","LS",2014 +"2014-10-04","National Independence Day","LS",2014 +"2014-12-25","Christmas Day","LS",2014 +"2014-12-26","Boxing Day","LS",2014 +"2015-01-01","New Year's Day","LS",2015 +"2015-03-11","Moshoeshoe's Day","LS",2015 +"2015-04-03","Good Friday","LS",2015 +"2015-04-06","Easter Monday","LS",2015 +"2015-05-01","Workers' Day","LS",2015 +"2015-05-14","Ascension Day","LS",2015 +"2015-05-25","Africa/Heroes Day","LS",2015 +"2015-07-17","King's Birthday","LS",2015 +"2015-10-04","National Independence Day","LS",2015 +"2015-12-25","Christmas Day","LS",2015 +"2015-12-26","Boxing Day","LS",2015 +"2016-01-01","New Year's Day","LS",2016 +"2016-03-11","Moshoeshoe's Day","LS",2016 +"2016-03-25","Good Friday","LS",2016 +"2016-03-28","Easter Monday","LS",2016 +"2016-05-01","Workers' Day","LS",2016 +"2016-05-05","Ascension Day","LS",2016 +"2016-05-25","Africa/Heroes Day","LS",2016 +"2016-07-17","King's Birthday","LS",2016 +"2016-10-04","National Independence Day","LS",2016 +"2016-12-25","Christmas Day","LS",2016 +"2016-12-26","Boxing Day","LS",2016 +"2017-01-01","New Year's Day","LS",2017 +"2017-03-11","Moshoeshoe's Day","LS",2017 +"2017-04-14","Good Friday","LS",2017 +"2017-04-17","Easter Monday","LS",2017 +"2017-05-01","Workers' Day","LS",2017 +"2017-05-25","Africa/Heroes Day","LS",2017 +"2017-05-25","Ascension Day","LS",2017 +"2017-07-17","King's Birthday","LS",2017 +"2017-10-04","National Independence Day","LS",2017 +"2017-12-25","Christmas Day","LS",2017 +"2017-12-26","Boxing Day","LS",2017 +"2018-01-01","New Year's Day","LS",2018 +"2018-03-11","Moshoeshoe's Day","LS",2018 +"2018-03-30","Good Friday","LS",2018 +"2018-04-02","Easter Monday","LS",2018 +"2018-05-01","Workers' Day","LS",2018 +"2018-05-10","Ascension Day","LS",2018 +"2018-05-25","Africa/Heroes Day","LS",2018 +"2018-07-17","King's Birthday","LS",2018 +"2018-10-04","National Independence Day","LS",2018 +"2018-12-25","Christmas Day","LS",2018 +"2018-12-26","Boxing Day","LS",2018 +"2019-01-01","New Year's Day","LS",2019 +"2019-03-11","Moshoeshoe's Day","LS",2019 +"2019-04-19","Good Friday","LS",2019 +"2019-04-22","Easter Monday","LS",2019 +"2019-05-01","Workers' Day","LS",2019 +"2019-05-25","Africa/Heroes Day","LS",2019 +"2019-05-30","Ascension Day","LS",2019 +"2019-07-17","King's Birthday","LS",2019 +"2019-10-04","National Independence Day","LS",2019 +"2019-12-25","Christmas Day","LS",2019 +"2019-12-26","Boxing Day","LS",2019 +"2020-01-01","New Year's Day","LS",2020 +"2020-03-11","Moshoeshoe's Day","LS",2020 +"2020-04-10","Good Friday","LS",2020 +"2020-04-13","Easter Monday","LS",2020 +"2020-05-01","Workers' Day","LS",2020 +"2020-05-21","Ascension Day","LS",2020 +"2020-05-25","Africa/Heroes Day","LS",2020 +"2020-07-17","King's Birthday","LS",2020 +"2020-10-04","National Independence Day","LS",2020 +"2020-12-25","Christmas Day","LS",2020 +"2020-12-26","Boxing Day","LS",2020 +"2021-01-01","New Year's Day","LS",2021 +"2021-03-11","Moshoeshoe's Day","LS",2021 +"2021-04-02","Good Friday","LS",2021 +"2021-04-05","Easter Monday","LS",2021 +"2021-05-01","Workers' Day","LS",2021 +"2021-05-13","Ascension Day","LS",2021 +"2021-05-25","Africa/Heroes Day","LS",2021 +"2021-07-17","King's Birthday","LS",2021 +"2021-10-04","National Independence Day","LS",2021 +"2021-12-25","Christmas Day","LS",2021 +"2021-12-26","Boxing Day","LS",2021 +"2022-01-01","New Year's Day","LS",2022 +"2022-03-11","Moshoeshoe's Day","LS",2022 +"2022-04-15","Good Friday","LS",2022 +"2022-04-18","Easter Monday","LS",2022 +"2022-05-01","Workers' Day","LS",2022 +"2022-05-25","Africa/Heroes Day","LS",2022 +"2022-05-26","Ascension Day","LS",2022 +"2022-07-17","King's Birthday","LS",2022 +"2022-10-04","National Independence Day","LS",2022 +"2022-12-25","Christmas Day","LS",2022 +"2022-12-26","Boxing Day","LS",2022 +"2023-01-01","New Year's Day","LS",2023 +"2023-03-11","Moshoeshoe's Day","LS",2023 +"2023-04-07","Good Friday","LS",2023 +"2023-04-10","Easter Monday","LS",2023 +"2023-05-01","Workers' Day","LS",2023 +"2023-05-18","Ascension Day","LS",2023 +"2023-05-25","Africa/Heroes Day","LS",2023 +"2023-07-17","King's Birthday","LS",2023 +"2023-10-04","National Independence Day","LS",2023 +"2023-12-25","Christmas Day","LS",2023 +"2023-12-26","Boxing Day","LS",2023 +"2024-01-01","New Year's Day","LS",2024 +"2024-03-11","Moshoeshoe's Day","LS",2024 +"2024-03-29","Good Friday","LS",2024 +"2024-04-01","Easter Monday","LS",2024 +"2024-05-01","Workers' Day","LS",2024 +"2024-05-09","Ascension Day","LS",2024 +"2024-05-25","Africa/Heroes Day","LS",2024 +"2024-07-17","King's Birthday","LS",2024 +"2024-10-04","National Independence Day","LS",2024 +"2024-12-25","Christmas Day","LS",2024 +"2024-12-26","Boxing Day","LS",2024 +"2025-01-01","New Year's Day","LS",2025 +"2025-03-11","Moshoeshoe's Day","LS",2025 +"2025-04-18","Good Friday","LS",2025 +"2025-04-21","Easter Monday","LS",2025 +"2025-05-01","Workers' Day","LS",2025 +"2025-05-25","Africa/Heroes Day","LS",2025 +"2025-05-29","Ascension Day","LS",2025 +"2025-07-17","King's Birthday","LS",2025 +"2025-10-04","National Independence Day","LS",2025 +"2025-12-25","Christmas Day","LS",2025 +"2025-12-26","Boxing Day","LS",2025 +"2026-01-01","New Year's Day","LS",2026 +"2026-03-11","Moshoeshoe's Day","LS",2026 +"2026-04-03","Good Friday","LS",2026 +"2026-04-06","Easter Monday","LS",2026 +"2026-05-01","Workers' Day","LS",2026 +"2026-05-14","Ascension Day","LS",2026 +"2026-05-25","Africa/Heroes Day","LS",2026 +"2026-07-17","King's Birthday","LS",2026 +"2026-10-04","National Independence Day","LS",2026 +"2026-12-25","Christmas Day","LS",2026 +"2026-12-26","Boxing Day","LS",2026 +"2027-01-01","New Year's Day","LS",2027 +"2027-03-11","Moshoeshoe's Day","LS",2027 +"2027-03-26","Good Friday","LS",2027 +"2027-03-29","Easter Monday","LS",2027 +"2027-05-01","Workers' Day","LS",2027 +"2027-05-06","Ascension Day","LS",2027 +"2027-05-25","Africa/Heroes Day","LS",2027 +"2027-07-17","King's Birthday","LS",2027 +"2027-10-04","National Independence Day","LS",2027 +"2027-12-25","Christmas Day","LS",2027 +"2027-12-26","Boxing Day","LS",2027 +"2028-01-01","New Year's Day","LS",2028 +"2028-03-11","Moshoeshoe's Day","LS",2028 +"2028-04-14","Good Friday","LS",2028 +"2028-04-17","Easter Monday","LS",2028 +"2028-05-01","Workers' Day","LS",2028 +"2028-05-25","Africa/Heroes Day","LS",2028 +"2028-05-25","Ascension Day","LS",2028 +"2028-07-17","King's Birthday","LS",2028 +"2028-10-04","National Independence Day","LS",2028 +"2028-12-25","Christmas Day","LS",2028 +"2028-12-26","Boxing Day","LS",2028 +"2029-01-01","New Year's Day","LS",2029 +"2029-03-11","Moshoeshoe's Day","LS",2029 +"2029-03-30","Good Friday","LS",2029 +"2029-04-02","Easter Monday","LS",2029 +"2029-05-01","Workers' Day","LS",2029 +"2029-05-10","Ascension Day","LS",2029 +"2029-05-25","Africa/Heroes Day","LS",2029 +"2029-07-17","King's Birthday","LS",2029 +"2029-10-04","National Independence Day","LS",2029 +"2029-12-25","Christmas Day","LS",2029 +"2029-12-26","Boxing Day","LS",2029 +"2030-01-01","New Year's Day","LS",2030 +"2030-03-11","Moshoeshoe's Day","LS",2030 +"2030-04-19","Good Friday","LS",2030 +"2030-04-22","Easter Monday","LS",2030 +"2030-05-01","Workers' Day","LS",2030 +"2030-05-25","Africa/Heroes Day","LS",2030 +"2030-05-30","Ascension Day","LS",2030 +"2030-07-17","King's Birthday","LS",2030 +"2030-10-04","National Independence Day","LS",2030 +"2030-12-25","Christmas Day","LS",2030 +"2030-12-26","Boxing Day","LS",2030 +"2031-01-01","New Year's Day","LS",2031 +"2031-03-11","Moshoeshoe's Day","LS",2031 +"2031-04-11","Good Friday","LS",2031 +"2031-04-14","Easter Monday","LS",2031 +"2031-05-01","Workers' Day","LS",2031 +"2031-05-22","Ascension Day","LS",2031 +"2031-05-25","Africa/Heroes Day","LS",2031 +"2031-07-17","King's Birthday","LS",2031 +"2031-10-04","National Independence Day","LS",2031 +"2031-12-25","Christmas Day","LS",2031 +"2031-12-26","Boxing Day","LS",2031 +"2032-01-01","New Year's Day","LS",2032 +"2032-03-11","Moshoeshoe's Day","LS",2032 +"2032-03-26","Good Friday","LS",2032 +"2032-03-29","Easter Monday","LS",2032 +"2032-05-01","Workers' Day","LS",2032 +"2032-05-06","Ascension Day","LS",2032 +"2032-05-25","Africa/Heroes Day","LS",2032 +"2032-07-17","King's Birthday","LS",2032 +"2032-10-04","National Independence Day","LS",2032 +"2032-12-25","Christmas Day","LS",2032 +"2032-12-26","Boxing Day","LS",2032 +"2033-01-01","New Year's Day","LS",2033 +"2033-03-11","Moshoeshoe's Day","LS",2033 +"2033-04-15","Good Friday","LS",2033 +"2033-04-18","Easter Monday","LS",2033 +"2033-05-01","Workers' Day","LS",2033 +"2033-05-25","Africa/Heroes Day","LS",2033 +"2033-05-26","Ascension Day","LS",2033 +"2033-07-17","King's Birthday","LS",2033 +"2033-10-04","National Independence Day","LS",2033 +"2033-12-25","Christmas Day","LS",2033 +"2033-12-26","Boxing Day","LS",2033 +"2034-01-01","New Year's Day","LS",2034 +"2034-03-11","Moshoeshoe's Day","LS",2034 +"2034-04-07","Good Friday","LS",2034 +"2034-04-10","Easter Monday","LS",2034 +"2034-05-01","Workers' Day","LS",2034 +"2034-05-18","Ascension Day","LS",2034 +"2034-05-25","Africa/Heroes Day","LS",2034 +"2034-07-17","King's Birthday","LS",2034 +"2034-10-04","National Independence Day","LS",2034 +"2034-12-25","Christmas Day","LS",2034 +"2034-12-26","Boxing Day","LS",2034 +"2035-01-01","New Year's Day","LS",2035 +"2035-03-11","Moshoeshoe's Day","LS",2035 +"2035-03-23","Good Friday","LS",2035 +"2035-03-26","Easter Monday","LS",2035 +"2035-05-01","Workers' Day","LS",2035 +"2035-05-03","Ascension Day","LS",2035 +"2035-05-25","Africa/Heroes Day","LS",2035 +"2035-07-17","King's Birthday","LS",2035 +"2035-10-04","National Independence Day","LS",2035 +"2035-12-25","Christmas Day","LS",2035 +"2035-12-26","Boxing Day","LS",2035 +"2036-01-01","New Year's Day","LS",2036 +"2036-03-11","Moshoeshoe's Day","LS",2036 +"2036-04-11","Good Friday","LS",2036 +"2036-04-14","Easter Monday","LS",2036 +"2036-05-01","Workers' Day","LS",2036 +"2036-05-22","Ascension Day","LS",2036 +"2036-05-25","Africa/Heroes Day","LS",2036 +"2036-07-17","King's Birthday","LS",2036 +"2036-10-04","National Independence Day","LS",2036 +"2036-12-25","Christmas Day","LS",2036 +"2036-12-26","Boxing Day","LS",2036 +"2037-01-01","New Year's Day","LS",2037 +"2037-03-11","Moshoeshoe's Day","LS",2037 +"2037-04-03","Good Friday","LS",2037 +"2037-04-06","Easter Monday","LS",2037 +"2037-05-01","Workers' Day","LS",2037 +"2037-05-14","Ascension Day","LS",2037 +"2037-05-25","Africa/Heroes Day","LS",2037 +"2037-07-17","King's Birthday","LS",2037 +"2037-10-04","National Independence Day","LS",2037 +"2037-12-25","Christmas Day","LS",2037 +"2037-12-26","Boxing Day","LS",2037 +"2038-01-01","New Year's Day","LS",2038 +"2038-03-11","Moshoeshoe's Day","LS",2038 +"2038-04-23","Good Friday","LS",2038 +"2038-04-26","Easter Monday","LS",2038 +"2038-05-01","Workers' Day","LS",2038 +"2038-05-25","Africa/Heroes Day","LS",2038 +"2038-06-03","Ascension Day","LS",2038 +"2038-07-17","King's Birthday","LS",2038 +"2038-10-04","National Independence Day","LS",2038 +"2038-12-25","Christmas Day","LS",2038 +"2038-12-26","Boxing Day","LS",2038 +"2039-01-01","New Year's Day","LS",2039 +"2039-03-11","Moshoeshoe's Day","LS",2039 +"2039-04-08","Good Friday","LS",2039 +"2039-04-11","Easter Monday","LS",2039 +"2039-05-01","Workers' Day","LS",2039 +"2039-05-19","Ascension Day","LS",2039 +"2039-05-25","Africa/Heroes Day","LS",2039 +"2039-07-17","King's Birthday","LS",2039 +"2039-10-04","National Independence Day","LS",2039 +"2039-12-25","Christmas Day","LS",2039 +"2039-12-26","Boxing Day","LS",2039 +"2040-01-01","New Year's Day","LS",2040 +"2040-03-11","Moshoeshoe's Day","LS",2040 +"2040-03-30","Good Friday","LS",2040 +"2040-04-02","Easter Monday","LS",2040 +"2040-05-01","Workers' Day","LS",2040 +"2040-05-10","Ascension Day","LS",2040 +"2040-05-25","Africa/Heroes Day","LS",2040 +"2040-07-17","King's Birthday","LS",2040 +"2040-10-04","National Independence Day","LS",2040 +"2040-12-25","Christmas Day","LS",2040 +"2040-12-26","Boxing Day","LS",2040 +"2041-01-01","New Year's Day","LS",2041 +"2041-03-11","Moshoeshoe's Day","LS",2041 +"2041-04-19","Good Friday","LS",2041 +"2041-04-22","Easter Monday","LS",2041 +"2041-05-01","Workers' Day","LS",2041 +"2041-05-25","Africa/Heroes Day","LS",2041 +"2041-05-30","Ascension Day","LS",2041 +"2041-07-17","King's Birthday","LS",2041 +"2041-10-04","National Independence Day","LS",2041 +"2041-12-25","Christmas Day","LS",2041 +"2041-12-26","Boxing Day","LS",2041 +"2042-01-01","New Year's Day","LS",2042 +"2042-03-11","Moshoeshoe's Day","LS",2042 +"2042-04-04","Good Friday","LS",2042 +"2042-04-07","Easter Monday","LS",2042 +"2042-05-01","Workers' Day","LS",2042 +"2042-05-15","Ascension Day","LS",2042 +"2042-05-25","Africa/Heroes Day","LS",2042 +"2042-07-17","King's Birthday","LS",2042 +"2042-10-04","National Independence Day","LS",2042 +"2042-12-25","Christmas Day","LS",2042 +"2042-12-26","Boxing Day","LS",2042 +"2043-01-01","New Year's Day","LS",2043 +"2043-03-11","Moshoeshoe's Day","LS",2043 +"2043-03-27","Good Friday","LS",2043 +"2043-03-30","Easter Monday","LS",2043 +"2043-05-01","Workers' Day","LS",2043 +"2043-05-07","Ascension Day","LS",2043 +"2043-05-25","Africa/Heroes Day","LS",2043 +"2043-07-17","King's Birthday","LS",2043 +"2043-10-04","National Independence Day","LS",2043 +"2043-12-25","Christmas Day","LS",2043 +"2043-12-26","Boxing Day","LS",2043 +"2044-01-01","New Year's Day","LS",2044 +"2044-03-11","Moshoeshoe's Day","LS",2044 +"2044-04-15","Good Friday","LS",2044 +"2044-04-18","Easter Monday","LS",2044 +"2044-05-01","Workers' Day","LS",2044 +"2044-05-25","Africa/Heroes Day","LS",2044 +"2044-05-26","Ascension Day","LS",2044 +"2044-07-17","King's Birthday","LS",2044 +"2044-10-04","National Independence Day","LS",2044 +"2044-12-25","Christmas Day","LS",2044 +"2044-12-26","Boxing Day","LS",2044 +"1995-01-01","Naujieji metai","LT",1995 +"1995-02-16","Lietuvos valstybes atkurimo diena","LT",1995 +"1995-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",1995 +"1995-04-16","Velykos","LT",1995 +"1995-04-17","Velyku antroji diena","LT",1995 +"1995-05-01","Tarptautine darbo diena","LT",1995 +"1995-05-07","Motinos diena","LT",1995 +"1995-06-04","Tevo diena","LT",1995 +"1995-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",1995 +"1995-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",1995 +"1995-11-01","Visu sventuju diena (Velines)","LT",1995 +"1995-12-24","Sv. Kucios","LT",1995 +"1995-12-25","Sv. Kaledu pirma diena","LT",1995 +"1995-12-26","Sv. Kaledu antra diena","LT",1995 +"1996-01-01","Naujieji metai","LT",1996 +"1996-02-16","Lietuvos valstybes atkurimo diena","LT",1996 +"1996-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",1996 +"1996-04-07","Velykos","LT",1996 +"1996-04-08","Velyku antroji diena","LT",1996 +"1996-05-01","Tarptautine darbo diena","LT",1996 +"1996-05-05","Motinos diena","LT",1996 +"1996-06-02","Tevo diena","LT",1996 +"1996-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",1996 +"1996-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",1996 +"1996-11-01","Visu sventuju diena (Velines)","LT",1996 +"1996-12-24","Sv. Kucios","LT",1996 +"1996-12-25","Sv. Kaledu pirma diena","LT",1996 +"1996-12-26","Sv. Kaledu antra diena","LT",1996 +"1997-01-01","Naujieji metai","LT",1997 +"1997-02-16","Lietuvos valstybes atkurimo diena","LT",1997 +"1997-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",1997 +"1997-03-30","Velykos","LT",1997 +"1997-03-31","Velyku antroji diena","LT",1997 +"1997-05-01","Tarptautine darbo diena","LT",1997 +"1997-05-04","Motinos diena","LT",1997 +"1997-06-01","Tevo diena","LT",1997 +"1997-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",1997 +"1997-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",1997 +"1997-11-01","Visu sventuju diena (Velines)","LT",1997 +"1997-12-24","Sv. Kucios","LT",1997 +"1997-12-25","Sv. Kaledu pirma diena","LT",1997 +"1997-12-26","Sv. Kaledu antra diena","LT",1997 +"1998-01-01","Naujieji metai","LT",1998 +"1998-02-16","Lietuvos valstybes atkurimo diena","LT",1998 +"1998-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",1998 +"1998-04-12","Velykos","LT",1998 +"1998-04-13","Velyku antroji diena","LT",1998 +"1998-05-01","Tarptautine darbo diena","LT",1998 +"1998-05-03","Motinos diena","LT",1998 +"1998-06-07","Tevo diena","LT",1998 +"1998-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",1998 +"1998-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",1998 +"1998-11-01","Visu sventuju diena (Velines)","LT",1998 +"1998-12-24","Sv. Kucios","LT",1998 +"1998-12-25","Sv. Kaledu pirma diena","LT",1998 +"1998-12-26","Sv. Kaledu antra diena","LT",1998 +"1999-01-01","Naujieji metai","LT",1999 +"1999-02-16","Lietuvos valstybes atkurimo diena","LT",1999 +"1999-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",1999 +"1999-04-04","Velykos","LT",1999 +"1999-04-05","Velyku antroji diena","LT",1999 +"1999-05-01","Tarptautine darbo diena","LT",1999 +"1999-05-02","Motinos diena","LT",1999 +"1999-06-06","Tevo diena","LT",1999 +"1999-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",1999 +"1999-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",1999 +"1999-11-01","Visu sventuju diena (Velines)","LT",1999 +"1999-12-24","Sv. Kucios","LT",1999 +"1999-12-25","Sv. Kaledu pirma diena","LT",1999 +"1999-12-26","Sv. Kaledu antra diena","LT",1999 +"2000-01-01","Naujieji metai","LT",2000 +"2000-02-16","Lietuvos valstybes atkurimo diena","LT",2000 +"2000-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2000 +"2000-04-23","Velykos","LT",2000 +"2000-04-24","Velyku antroji diena","LT",2000 +"2000-05-01","Tarptautine darbo diena","LT",2000 +"2000-05-07","Motinos diena","LT",2000 +"2000-06-04","Tevo diena","LT",2000 +"2000-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2000 +"2000-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2000 +"2000-11-01","Visu sventuju diena (Velines)","LT",2000 +"2000-12-24","Sv. Kucios","LT",2000 +"2000-12-25","Sv. Kaledu pirma diena","LT",2000 +"2000-12-26","Sv. Kaledu antra diena","LT",2000 +"2001-01-01","Naujieji metai","LT",2001 +"2001-02-16","Lietuvos valstybes atkurimo diena","LT",2001 +"2001-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2001 +"2001-04-15","Velykos","LT",2001 +"2001-04-16","Velyku antroji diena","LT",2001 +"2001-05-01","Tarptautine darbo diena","LT",2001 +"2001-05-06","Motinos diena","LT",2001 +"2001-06-03","Tevo diena","LT",2001 +"2001-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2001 +"2001-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2001 +"2001-11-01","Visu sventuju diena (Velines)","LT",2001 +"2001-12-24","Sv. Kucios","LT",2001 +"2001-12-25","Sv. Kaledu pirma diena","LT",2001 +"2001-12-26","Sv. Kaledu antra diena","LT",2001 +"2002-01-01","Naujieji metai","LT",2002 +"2002-02-16","Lietuvos valstybes atkurimo diena","LT",2002 +"2002-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2002 +"2002-03-31","Velykos","LT",2002 +"2002-04-01","Velyku antroji diena","LT",2002 +"2002-05-01","Tarptautine darbo diena","LT",2002 +"2002-05-05","Motinos diena","LT",2002 +"2002-06-02","Tevo diena","LT",2002 +"2002-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2002 +"2002-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2002 +"2002-11-01","Visu sventuju diena (Velines)","LT",2002 +"2002-12-24","Sv. Kucios","LT",2002 +"2002-12-25","Sv. Kaledu pirma diena","LT",2002 +"2002-12-26","Sv. Kaledu antra diena","LT",2002 +"2003-01-01","Naujieji metai","LT",2003 +"2003-02-16","Lietuvos valstybes atkurimo diena","LT",2003 +"2003-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2003 +"2003-04-20","Velykos","LT",2003 +"2003-04-21","Velyku antroji diena","LT",2003 +"2003-05-01","Tarptautine darbo diena","LT",2003 +"2003-05-04","Motinos diena","LT",2003 +"2003-06-01","Tevo diena","LT",2003 +"2003-06-24","Jonines, Rasos","LT",2003 +"2003-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2003 +"2003-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2003 +"2003-11-01","Visu sventuju diena (Velines)","LT",2003 +"2003-12-24","Sv. Kucios","LT",2003 +"2003-12-25","Sv. Kaledu pirma diena","LT",2003 +"2003-12-26","Sv. Kaledu antra diena","LT",2003 +"2004-01-01","Naujieji metai","LT",2004 +"2004-02-16","Lietuvos valstybes atkurimo diena","LT",2004 +"2004-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2004 +"2004-04-11","Velykos","LT",2004 +"2004-04-12","Velyku antroji diena","LT",2004 +"2004-05-01","Tarptautine darbo diena","LT",2004 +"2004-05-02","Motinos diena","LT",2004 +"2004-06-06","Tevo diena","LT",2004 +"2004-06-24","Jonines, Rasos","LT",2004 +"2004-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2004 +"2004-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2004 +"2004-11-01","Visu sventuju diena (Velines)","LT",2004 +"2004-12-24","Sv. Kucios","LT",2004 +"2004-12-25","Sv. Kaledu pirma diena","LT",2004 +"2004-12-26","Sv. Kaledu antra diena","LT",2004 +"2005-01-01","Naujieji metai","LT",2005 +"2005-02-16","Lietuvos valstybes atkurimo diena","LT",2005 +"2005-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2005 +"2005-03-27","Velykos","LT",2005 +"2005-03-28","Velyku antroji diena","LT",2005 +"2005-05-01","Motinos diena","LT",2005 +"2005-05-01","Tarptautine darbo diena","LT",2005 +"2005-06-05","Tevo diena","LT",2005 +"2005-06-24","Jonines, Rasos","LT",2005 +"2005-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2005 +"2005-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2005 +"2005-11-01","Visu sventuju diena (Velines)","LT",2005 +"2005-12-24","Sv. Kucios","LT",2005 +"2005-12-25","Sv. Kaledu pirma diena","LT",2005 +"2005-12-26","Sv. Kaledu antra diena","LT",2005 +"2006-01-01","Naujieji metai","LT",2006 +"2006-02-16","Lietuvos valstybes atkurimo diena","LT",2006 +"2006-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2006 +"2006-04-16","Velykos","LT",2006 +"2006-04-17","Velyku antroji diena","LT",2006 +"2006-05-01","Tarptautine darbo diena","LT",2006 +"2006-05-07","Motinos diena","LT",2006 +"2006-06-04","Tevo diena","LT",2006 +"2006-06-24","Jonines, Rasos","LT",2006 +"2006-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2006 +"2006-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2006 +"2006-11-01","Visu sventuju diena (Velines)","LT",2006 +"2006-12-24","Sv. Kucios","LT",2006 +"2006-12-25","Sv. Kaledu pirma diena","LT",2006 +"2006-12-26","Sv. Kaledu antra diena","LT",2006 +"2007-01-01","Naujieji metai","LT",2007 +"2007-02-16","Lietuvos valstybes atkurimo diena","LT",2007 +"2007-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2007 +"2007-04-08","Velykos","LT",2007 +"2007-04-09","Velyku antroji diena","LT",2007 +"2007-05-01","Tarptautine darbo diena","LT",2007 +"2007-05-06","Motinos diena","LT",2007 +"2007-06-03","Tevo diena","LT",2007 +"2007-06-24","Jonines, Rasos","LT",2007 +"2007-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2007 +"2007-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2007 +"2007-11-01","Visu sventuju diena (Velines)","LT",2007 +"2007-12-24","Sv. Kucios","LT",2007 +"2007-12-25","Sv. Kaledu pirma diena","LT",2007 +"2007-12-26","Sv. Kaledu antra diena","LT",2007 +"2008-01-01","Naujieji metai","LT",2008 +"2008-02-16","Lietuvos valstybes atkurimo diena","LT",2008 +"2008-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2008 +"2008-03-23","Velykos","LT",2008 +"2008-03-24","Velyku antroji diena","LT",2008 +"2008-05-01","Tarptautine darbo diena","LT",2008 +"2008-05-04","Motinos diena","LT",2008 +"2008-06-01","Tevo diena","LT",2008 +"2008-06-24","Jonines, Rasos","LT",2008 +"2008-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2008 +"2008-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2008 +"2008-11-01","Visu sventuju diena (Velines)","LT",2008 +"2008-12-24","Sv. Kucios","LT",2008 +"2008-12-25","Sv. Kaledu pirma diena","LT",2008 +"2008-12-26","Sv. Kaledu antra diena","LT",2008 +"2009-01-01","Naujieji metai","LT",2009 +"2009-02-16","Lietuvos valstybes atkurimo diena","LT",2009 +"2009-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2009 +"2009-04-12","Velykos","LT",2009 +"2009-04-13","Velyku antroji diena","LT",2009 +"2009-05-01","Tarptautine darbo diena","LT",2009 +"2009-05-03","Motinos diena","LT",2009 +"2009-06-07","Tevo diena","LT",2009 +"2009-06-24","Jonines, Rasos","LT",2009 +"2009-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2009 +"2009-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2009 +"2009-11-01","Visu sventuju diena (Velines)","LT",2009 +"2009-12-24","Sv. Kucios","LT",2009 +"2009-12-25","Sv. Kaledu pirma diena","LT",2009 +"2009-12-26","Sv. Kaledu antra diena","LT",2009 +"2010-01-01","Naujieji metai","LT",2010 +"2010-02-16","Lietuvos valstybes atkurimo diena","LT",2010 +"2010-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2010 +"2010-04-04","Velykos","LT",2010 +"2010-04-05","Velyku antroji diena","LT",2010 +"2010-05-01","Tarptautine darbo diena","LT",2010 +"2010-05-02","Motinos diena","LT",2010 +"2010-06-06","Tevo diena","LT",2010 +"2010-06-24","Jonines, Rasos","LT",2010 +"2010-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2010 +"2010-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2010 +"2010-11-01","Visu sventuju diena (Velines)","LT",2010 +"2010-12-24","Sv. Kucios","LT",2010 +"2010-12-25","Sv. Kaledu pirma diena","LT",2010 +"2010-12-26","Sv. Kaledu antra diena","LT",2010 +"2011-01-01","Naujieji metai","LT",2011 +"2011-02-16","Lietuvos valstybes atkurimo diena","LT",2011 +"2011-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2011 +"2011-04-24","Velykos","LT",2011 +"2011-04-25","Velyku antroji diena","LT",2011 +"2011-05-01","Motinos diena","LT",2011 +"2011-05-01","Tarptautine darbo diena","LT",2011 +"2011-06-05","Tevo diena","LT",2011 +"2011-06-24","Jonines, Rasos","LT",2011 +"2011-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2011 +"2011-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2011 +"2011-11-01","Visu sventuju diena (Velines)","LT",2011 +"2011-12-24","Sv. Kucios","LT",2011 +"2011-12-25","Sv. Kaledu pirma diena","LT",2011 +"2011-12-26","Sv. Kaledu antra diena","LT",2011 +"2012-01-01","Naujieji metai","LT",2012 +"2012-02-16","Lietuvos valstybes atkurimo diena","LT",2012 +"2012-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2012 +"2012-04-08","Velykos","LT",2012 +"2012-04-09","Velyku antroji diena","LT",2012 +"2012-05-01","Tarptautine darbo diena","LT",2012 +"2012-05-06","Motinos diena","LT",2012 +"2012-06-03","Tevo diena","LT",2012 +"2012-06-24","Jonines, Rasos","LT",2012 +"2012-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2012 +"2012-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2012 +"2012-11-01","Visu sventuju diena (Velines)","LT",2012 +"2012-12-24","Sv. Kucios","LT",2012 +"2012-12-25","Sv. Kaledu pirma diena","LT",2012 +"2012-12-26","Sv. Kaledu antra diena","LT",2012 +"2013-01-01","Naujieji metai","LT",2013 +"2013-02-16","Lietuvos valstybes atkurimo diena","LT",2013 +"2013-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2013 +"2013-03-31","Velykos","LT",2013 +"2013-04-01","Velyku antroji diena","LT",2013 +"2013-05-01","Tarptautine darbo diena","LT",2013 +"2013-05-05","Motinos diena","LT",2013 +"2013-06-02","Tevo diena","LT",2013 +"2013-06-24","Jonines, Rasos","LT",2013 +"2013-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2013 +"2013-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2013 +"2013-11-01","Visu sventuju diena (Velines)","LT",2013 +"2013-12-24","Sv. Kucios","LT",2013 +"2013-12-25","Sv. Kaledu pirma diena","LT",2013 +"2013-12-26","Sv. Kaledu antra diena","LT",2013 +"2014-01-01","Naujieji metai","LT",2014 +"2014-02-16","Lietuvos valstybes atkurimo diena","LT",2014 +"2014-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2014 +"2014-04-20","Velykos","LT",2014 +"2014-04-21","Velyku antroji diena","LT",2014 +"2014-05-01","Tarptautine darbo diena","LT",2014 +"2014-05-04","Motinos diena","LT",2014 +"2014-06-01","Tevo diena","LT",2014 +"2014-06-24","Jonines, Rasos","LT",2014 +"2014-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2014 +"2014-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2014 +"2014-11-01","Visu sventuju diena (Velines)","LT",2014 +"2014-12-24","Sv. Kucios","LT",2014 +"2014-12-25","Sv. Kaledu pirma diena","LT",2014 +"2014-12-26","Sv. Kaledu antra diena","LT",2014 +"2015-01-01","Naujieji metai","LT",2015 +"2015-02-16","Lietuvos valstybes atkurimo diena","LT",2015 +"2015-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2015 +"2015-04-05","Velykos","LT",2015 +"2015-04-06","Velyku antroji diena","LT",2015 +"2015-05-01","Tarptautine darbo diena","LT",2015 +"2015-05-03","Motinos diena","LT",2015 +"2015-06-07","Tevo diena","LT",2015 +"2015-06-24","Jonines, Rasos","LT",2015 +"2015-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2015 +"2015-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2015 +"2015-11-01","Visu sventuju diena (Velines)","LT",2015 +"2015-12-24","Sv. Kucios","LT",2015 +"2015-12-25","Sv. Kaledu pirma diena","LT",2015 +"2015-12-26","Sv. Kaledu antra diena","LT",2015 +"2016-01-01","Naujieji metai","LT",2016 +"2016-02-16","Lietuvos valstybes atkurimo diena","LT",2016 +"2016-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2016 +"2016-03-27","Velykos","LT",2016 +"2016-03-28","Velyku antroji diena","LT",2016 +"2016-05-01","Motinos diena","LT",2016 +"2016-05-01","Tarptautine darbo diena","LT",2016 +"2016-06-05","Tevo diena","LT",2016 +"2016-06-24","Jonines, Rasos","LT",2016 +"2016-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2016 +"2016-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2016 +"2016-11-01","Visu sventuju diena (Velines)","LT",2016 +"2016-12-24","Sv. Kucios","LT",2016 +"2016-12-25","Sv. Kaledu pirma diena","LT",2016 +"2016-12-26","Sv. Kaledu antra diena","LT",2016 +"2017-01-01","Naujieji metai","LT",2017 +"2017-02-16","Lietuvos valstybes atkurimo diena","LT",2017 +"2017-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2017 +"2017-04-16","Velykos","LT",2017 +"2017-04-17","Velyku antroji diena","LT",2017 +"2017-05-01","Tarptautine darbo diena","LT",2017 +"2017-05-07","Motinos diena","LT",2017 +"2017-06-04","Tevo diena","LT",2017 +"2017-06-24","Jonines, Rasos","LT",2017 +"2017-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2017 +"2017-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2017 +"2017-11-01","Visu sventuju diena (Velines)","LT",2017 +"2017-12-24","Sv. Kucios","LT",2017 +"2017-12-25","Sv. Kaledu pirma diena","LT",2017 +"2017-12-26","Sv. Kaledu antra diena","LT",2017 +"2018-01-01","Naujieji metai","LT",2018 +"2018-02-16","Lietuvos valstybes atkurimo diena","LT",2018 +"2018-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2018 +"2018-04-01","Velykos","LT",2018 +"2018-04-02","Velyku antroji diena","LT",2018 +"2018-05-01","Tarptautine darbo diena","LT",2018 +"2018-05-06","Motinos diena","LT",2018 +"2018-06-03","Tevo diena","LT",2018 +"2018-06-24","Jonines, Rasos","LT",2018 +"2018-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2018 +"2018-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2018 +"2018-11-01","Visu sventuju diena (Velines)","LT",2018 +"2018-12-24","Sv. Kucios","LT",2018 +"2018-12-25","Sv. Kaledu pirma diena","LT",2018 +"2018-12-26","Sv. Kaledu antra diena","LT",2018 +"2019-01-01","Naujieji metai","LT",2019 +"2019-02-16","Lietuvos valstybes atkurimo diena","LT",2019 +"2019-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2019 +"2019-04-21","Velykos","LT",2019 +"2019-04-22","Velyku antroji diena","LT",2019 +"2019-05-01","Tarptautine darbo diena","LT",2019 +"2019-05-05","Motinos diena","LT",2019 +"2019-06-02","Tevo diena","LT",2019 +"2019-06-24","Jonines, Rasos","LT",2019 +"2019-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2019 +"2019-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2019 +"2019-11-01","Visu sventuju diena (Velines)","LT",2019 +"2019-12-24","Sv. Kucios","LT",2019 +"2019-12-25","Sv. Kaledu pirma diena","LT",2019 +"2019-12-26","Sv. Kaledu antra diena","LT",2019 +"2020-01-01","Naujieji metai","LT",2020 +"2020-02-16","Lietuvos valstybes atkurimo diena","LT",2020 +"2020-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2020 +"2020-04-12","Velykos","LT",2020 +"2020-04-13","Velyku antroji diena","LT",2020 +"2020-05-01","Tarptautine darbo diena","LT",2020 +"2020-05-03","Motinos diena","LT",2020 +"2020-06-07","Tevo diena","LT",2020 +"2020-06-24","Jonines, Rasos","LT",2020 +"2020-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2020 +"2020-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2020 +"2020-11-01","Visu sventuju diena (Velines)","LT",2020 +"2020-11-02","Mirusiuju atminimo diena (Velines)","LT",2020 +"2020-12-24","Sv. Kucios","LT",2020 +"2020-12-25","Sv. Kaledu pirma diena","LT",2020 +"2020-12-26","Sv. Kaledu antra diena","LT",2020 +"2021-01-01","Naujieji metai","LT",2021 +"2021-02-16","Lietuvos valstybes atkurimo diena","LT",2021 +"2021-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2021 +"2021-04-04","Velykos","LT",2021 +"2021-04-05","Velyku antroji diena","LT",2021 +"2021-05-01","Tarptautine darbo diena","LT",2021 +"2021-05-02","Motinos diena","LT",2021 +"2021-06-06","Tevo diena","LT",2021 +"2021-06-24","Jonines, Rasos","LT",2021 +"2021-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2021 +"2021-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2021 +"2021-11-01","Visu sventuju diena (Velines)","LT",2021 +"2021-11-02","Mirusiuju atminimo diena (Velines)","LT",2021 +"2021-12-24","Sv. Kucios","LT",2021 +"2021-12-25","Sv. Kaledu pirma diena","LT",2021 +"2021-12-26","Sv. Kaledu antra diena","LT",2021 +"2022-01-01","Naujieji metai","LT",2022 +"2022-02-16","Lietuvos valstybes atkurimo diena","LT",2022 +"2022-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2022 +"2022-04-17","Velykos","LT",2022 +"2022-04-18","Velyku antroji diena","LT",2022 +"2022-05-01","Motinos diena","LT",2022 +"2022-05-01","Tarptautine darbo diena","LT",2022 +"2022-06-05","Tevo diena","LT",2022 +"2022-06-24","Jonines, Rasos","LT",2022 +"2022-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2022 +"2022-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2022 +"2022-11-01","Visu sventuju diena (Velines)","LT",2022 +"2022-11-02","Mirusiuju atminimo diena (Velines)","LT",2022 +"2022-12-24","Sv. Kucios","LT",2022 +"2022-12-25","Sv. Kaledu pirma diena","LT",2022 +"2022-12-26","Sv. Kaledu antra diena","LT",2022 +"2023-01-01","Naujieji metai","LT",2023 +"2023-02-16","Lietuvos valstybes atkurimo diena","LT",2023 +"2023-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2023 +"2023-04-09","Velykos","LT",2023 +"2023-04-10","Velyku antroji diena","LT",2023 +"2023-05-01","Tarptautine darbo diena","LT",2023 +"2023-05-07","Motinos diena","LT",2023 +"2023-06-04","Tevo diena","LT",2023 +"2023-06-24","Jonines, Rasos","LT",2023 +"2023-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2023 +"2023-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2023 +"2023-11-01","Visu sventuju diena (Velines)","LT",2023 +"2023-11-02","Mirusiuju atminimo diena (Velines)","LT",2023 +"2023-12-24","Sv. Kucios","LT",2023 +"2023-12-25","Sv. Kaledu pirma diena","LT",2023 +"2023-12-26","Sv. Kaledu antra diena","LT",2023 +"2024-01-01","Naujieji metai","LT",2024 +"2024-02-16","Lietuvos valstybes atkurimo diena","LT",2024 +"2024-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2024 +"2024-03-31","Velykos","LT",2024 +"2024-04-01","Velyku antroji diena","LT",2024 +"2024-05-01","Tarptautine darbo diena","LT",2024 +"2024-05-05","Motinos diena","LT",2024 +"2024-06-02","Tevo diena","LT",2024 +"2024-06-24","Jonines, Rasos","LT",2024 +"2024-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2024 +"2024-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2024 +"2024-11-01","Visu sventuju diena (Velines)","LT",2024 +"2024-11-02","Mirusiuju atminimo diena (Velines)","LT",2024 +"2024-12-24","Sv. Kucios","LT",2024 +"2024-12-25","Sv. Kaledu pirma diena","LT",2024 +"2024-12-26","Sv. Kaledu antra diena","LT",2024 +"2025-01-01","Naujieji metai","LT",2025 +"2025-02-16","Lietuvos valstybes atkurimo diena","LT",2025 +"2025-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2025 +"2025-04-20","Velykos","LT",2025 +"2025-04-21","Velyku antroji diena","LT",2025 +"2025-05-01","Tarptautine darbo diena","LT",2025 +"2025-05-04","Motinos diena","LT",2025 +"2025-06-01","Tevo diena","LT",2025 +"2025-06-24","Jonines, Rasos","LT",2025 +"2025-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2025 +"2025-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2025 +"2025-11-01","Visu sventuju diena (Velines)","LT",2025 +"2025-11-02","Mirusiuju atminimo diena (Velines)","LT",2025 +"2025-12-24","Sv. Kucios","LT",2025 +"2025-12-25","Sv. Kaledu pirma diena","LT",2025 +"2025-12-26","Sv. Kaledu antra diena","LT",2025 +"2026-01-01","Naujieji metai","LT",2026 +"2026-02-16","Lietuvos valstybes atkurimo diena","LT",2026 +"2026-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2026 +"2026-04-05","Velykos","LT",2026 +"2026-04-06","Velyku antroji diena","LT",2026 +"2026-05-01","Tarptautine darbo diena","LT",2026 +"2026-05-03","Motinos diena","LT",2026 +"2026-06-07","Tevo diena","LT",2026 +"2026-06-24","Jonines, Rasos","LT",2026 +"2026-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2026 +"2026-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2026 +"2026-11-01","Visu sventuju diena (Velines)","LT",2026 +"2026-11-02","Mirusiuju atminimo diena (Velines)","LT",2026 +"2026-12-24","Sv. Kucios","LT",2026 +"2026-12-25","Sv. Kaledu pirma diena","LT",2026 +"2026-12-26","Sv. Kaledu antra diena","LT",2026 +"2027-01-01","Naujieji metai","LT",2027 +"2027-02-16","Lietuvos valstybes atkurimo diena","LT",2027 +"2027-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2027 +"2027-03-28","Velykos","LT",2027 +"2027-03-29","Velyku antroji diena","LT",2027 +"2027-05-01","Tarptautine darbo diena","LT",2027 +"2027-05-02","Motinos diena","LT",2027 +"2027-06-06","Tevo diena","LT",2027 +"2027-06-24","Jonines, Rasos","LT",2027 +"2027-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2027 +"2027-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2027 +"2027-11-01","Visu sventuju diena (Velines)","LT",2027 +"2027-11-02","Mirusiuju atminimo diena (Velines)","LT",2027 +"2027-12-24","Sv. Kucios","LT",2027 +"2027-12-25","Sv. Kaledu pirma diena","LT",2027 +"2027-12-26","Sv. Kaledu antra diena","LT",2027 +"2028-01-01","Naujieji metai","LT",2028 +"2028-02-16","Lietuvos valstybes atkurimo diena","LT",2028 +"2028-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2028 +"2028-04-16","Velykos","LT",2028 +"2028-04-17","Velyku antroji diena","LT",2028 +"2028-05-01","Tarptautine darbo diena","LT",2028 +"2028-05-07","Motinos diena","LT",2028 +"2028-06-04","Tevo diena","LT",2028 +"2028-06-24","Jonines, Rasos","LT",2028 +"2028-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2028 +"2028-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2028 +"2028-11-01","Visu sventuju diena (Velines)","LT",2028 +"2028-11-02","Mirusiuju atminimo diena (Velines)","LT",2028 +"2028-12-24","Sv. Kucios","LT",2028 +"2028-12-25","Sv. Kaledu pirma diena","LT",2028 +"2028-12-26","Sv. Kaledu antra diena","LT",2028 +"2029-01-01","Naujieji metai","LT",2029 +"2029-02-16","Lietuvos valstybes atkurimo diena","LT",2029 +"2029-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2029 +"2029-04-01","Velykos","LT",2029 +"2029-04-02","Velyku antroji diena","LT",2029 +"2029-05-01","Tarptautine darbo diena","LT",2029 +"2029-05-06","Motinos diena","LT",2029 +"2029-06-03","Tevo diena","LT",2029 +"2029-06-24","Jonines, Rasos","LT",2029 +"2029-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2029 +"2029-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2029 +"2029-11-01","Visu sventuju diena (Velines)","LT",2029 +"2029-11-02","Mirusiuju atminimo diena (Velines)","LT",2029 +"2029-12-24","Sv. Kucios","LT",2029 +"2029-12-25","Sv. Kaledu pirma diena","LT",2029 +"2029-12-26","Sv. Kaledu antra diena","LT",2029 +"2030-01-01","Naujieji metai","LT",2030 +"2030-02-16","Lietuvos valstybes atkurimo diena","LT",2030 +"2030-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2030 +"2030-04-21","Velykos","LT",2030 +"2030-04-22","Velyku antroji diena","LT",2030 +"2030-05-01","Tarptautine darbo diena","LT",2030 +"2030-05-05","Motinos diena","LT",2030 +"2030-06-02","Tevo diena","LT",2030 +"2030-06-24","Jonines, Rasos","LT",2030 +"2030-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2030 +"2030-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2030 +"2030-11-01","Visu sventuju diena (Velines)","LT",2030 +"2030-11-02","Mirusiuju atminimo diena (Velines)","LT",2030 +"2030-12-24","Sv. Kucios","LT",2030 +"2030-12-25","Sv. Kaledu pirma diena","LT",2030 +"2030-12-26","Sv. Kaledu antra diena","LT",2030 +"2031-01-01","Naujieji metai","LT",2031 +"2031-02-16","Lietuvos valstybes atkurimo diena","LT",2031 +"2031-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2031 +"2031-04-13","Velykos","LT",2031 +"2031-04-14","Velyku antroji diena","LT",2031 +"2031-05-01","Tarptautine darbo diena","LT",2031 +"2031-05-04","Motinos diena","LT",2031 +"2031-06-01","Tevo diena","LT",2031 +"2031-06-24","Jonines, Rasos","LT",2031 +"2031-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2031 +"2031-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2031 +"2031-11-01","Visu sventuju diena (Velines)","LT",2031 +"2031-11-02","Mirusiuju atminimo diena (Velines)","LT",2031 +"2031-12-24","Sv. Kucios","LT",2031 +"2031-12-25","Sv. Kaledu pirma diena","LT",2031 +"2031-12-26","Sv. Kaledu antra diena","LT",2031 +"2032-01-01","Naujieji metai","LT",2032 +"2032-02-16","Lietuvos valstybes atkurimo diena","LT",2032 +"2032-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2032 +"2032-03-28","Velykos","LT",2032 +"2032-03-29","Velyku antroji diena","LT",2032 +"2032-05-01","Tarptautine darbo diena","LT",2032 +"2032-05-02","Motinos diena","LT",2032 +"2032-06-06","Tevo diena","LT",2032 +"2032-06-24","Jonines, Rasos","LT",2032 +"2032-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2032 +"2032-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2032 +"2032-11-01","Visu sventuju diena (Velines)","LT",2032 +"2032-11-02","Mirusiuju atminimo diena (Velines)","LT",2032 +"2032-12-24","Sv. Kucios","LT",2032 +"2032-12-25","Sv. Kaledu pirma diena","LT",2032 +"2032-12-26","Sv. Kaledu antra diena","LT",2032 +"2033-01-01","Naujieji metai","LT",2033 +"2033-02-16","Lietuvos valstybes atkurimo diena","LT",2033 +"2033-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2033 +"2033-04-17","Velykos","LT",2033 +"2033-04-18","Velyku antroji diena","LT",2033 +"2033-05-01","Motinos diena","LT",2033 +"2033-05-01","Tarptautine darbo diena","LT",2033 +"2033-06-05","Tevo diena","LT",2033 +"2033-06-24","Jonines, Rasos","LT",2033 +"2033-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2033 +"2033-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2033 +"2033-11-01","Visu sventuju diena (Velines)","LT",2033 +"2033-11-02","Mirusiuju atminimo diena (Velines)","LT",2033 +"2033-12-24","Sv. Kucios","LT",2033 +"2033-12-25","Sv. Kaledu pirma diena","LT",2033 +"2033-12-26","Sv. Kaledu antra diena","LT",2033 +"2034-01-01","Naujieji metai","LT",2034 +"2034-02-16","Lietuvos valstybes atkurimo diena","LT",2034 +"2034-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2034 +"2034-04-09","Velykos","LT",2034 +"2034-04-10","Velyku antroji diena","LT",2034 +"2034-05-01","Tarptautine darbo diena","LT",2034 +"2034-05-07","Motinos diena","LT",2034 +"2034-06-04","Tevo diena","LT",2034 +"2034-06-24","Jonines, Rasos","LT",2034 +"2034-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2034 +"2034-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2034 +"2034-11-01","Visu sventuju diena (Velines)","LT",2034 +"2034-11-02","Mirusiuju atminimo diena (Velines)","LT",2034 +"2034-12-24","Sv. Kucios","LT",2034 +"2034-12-25","Sv. Kaledu pirma diena","LT",2034 +"2034-12-26","Sv. Kaledu antra diena","LT",2034 +"2035-01-01","Naujieji metai","LT",2035 +"2035-02-16","Lietuvos valstybes atkurimo diena","LT",2035 +"2035-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2035 +"2035-03-25","Velykos","LT",2035 +"2035-03-26","Velyku antroji diena","LT",2035 +"2035-05-01","Tarptautine darbo diena","LT",2035 +"2035-05-06","Motinos diena","LT",2035 +"2035-06-03","Tevo diena","LT",2035 +"2035-06-24","Jonines, Rasos","LT",2035 +"2035-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2035 +"2035-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2035 +"2035-11-01","Visu sventuju diena (Velines)","LT",2035 +"2035-11-02","Mirusiuju atminimo diena (Velines)","LT",2035 +"2035-12-24","Sv. Kucios","LT",2035 +"2035-12-25","Sv. Kaledu pirma diena","LT",2035 +"2035-12-26","Sv. Kaledu antra diena","LT",2035 +"2036-01-01","Naujieji metai","LT",2036 +"2036-02-16","Lietuvos valstybes atkurimo diena","LT",2036 +"2036-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2036 +"2036-04-13","Velykos","LT",2036 +"2036-04-14","Velyku antroji diena","LT",2036 +"2036-05-01","Tarptautine darbo diena","LT",2036 +"2036-05-04","Motinos diena","LT",2036 +"2036-06-01","Tevo diena","LT",2036 +"2036-06-24","Jonines, Rasos","LT",2036 +"2036-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2036 +"2036-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2036 +"2036-11-01","Visu sventuju diena (Velines)","LT",2036 +"2036-11-02","Mirusiuju atminimo diena (Velines)","LT",2036 +"2036-12-24","Sv. Kucios","LT",2036 +"2036-12-25","Sv. Kaledu pirma diena","LT",2036 +"2036-12-26","Sv. Kaledu antra diena","LT",2036 +"2037-01-01","Naujieji metai","LT",2037 +"2037-02-16","Lietuvos valstybes atkurimo diena","LT",2037 +"2037-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2037 +"2037-04-05","Velykos","LT",2037 +"2037-04-06","Velyku antroji diena","LT",2037 +"2037-05-01","Tarptautine darbo diena","LT",2037 +"2037-05-03","Motinos diena","LT",2037 +"2037-06-07","Tevo diena","LT",2037 +"2037-06-24","Jonines, Rasos","LT",2037 +"2037-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2037 +"2037-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2037 +"2037-11-01","Visu sventuju diena (Velines)","LT",2037 +"2037-11-02","Mirusiuju atminimo diena (Velines)","LT",2037 +"2037-12-24","Sv. Kucios","LT",2037 +"2037-12-25","Sv. Kaledu pirma diena","LT",2037 +"2037-12-26","Sv. Kaledu antra diena","LT",2037 +"2038-01-01","Naujieji metai","LT",2038 +"2038-02-16","Lietuvos valstybes atkurimo diena","LT",2038 +"2038-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2038 +"2038-04-25","Velykos","LT",2038 +"2038-04-26","Velyku antroji diena","LT",2038 +"2038-05-01","Tarptautine darbo diena","LT",2038 +"2038-05-02","Motinos diena","LT",2038 +"2038-06-06","Tevo diena","LT",2038 +"2038-06-24","Jonines, Rasos","LT",2038 +"2038-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2038 +"2038-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2038 +"2038-11-01","Visu sventuju diena (Velines)","LT",2038 +"2038-11-02","Mirusiuju atminimo diena (Velines)","LT",2038 +"2038-12-24","Sv. Kucios","LT",2038 +"2038-12-25","Sv. Kaledu pirma diena","LT",2038 +"2038-12-26","Sv. Kaledu antra diena","LT",2038 +"2039-01-01","Naujieji metai","LT",2039 +"2039-02-16","Lietuvos valstybes atkurimo diena","LT",2039 +"2039-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2039 +"2039-04-10","Velykos","LT",2039 +"2039-04-11","Velyku antroji diena","LT",2039 +"2039-05-01","Motinos diena","LT",2039 +"2039-05-01","Tarptautine darbo diena","LT",2039 +"2039-06-05","Tevo diena","LT",2039 +"2039-06-24","Jonines, Rasos","LT",2039 +"2039-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2039 +"2039-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2039 +"2039-11-01","Visu sventuju diena (Velines)","LT",2039 +"2039-11-02","Mirusiuju atminimo diena (Velines)","LT",2039 +"2039-12-24","Sv. Kucios","LT",2039 +"2039-12-25","Sv. Kaledu pirma diena","LT",2039 +"2039-12-26","Sv. Kaledu antra diena","LT",2039 +"2040-01-01","Naujieji metai","LT",2040 +"2040-02-16","Lietuvos valstybes atkurimo diena","LT",2040 +"2040-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2040 +"2040-04-01","Velykos","LT",2040 +"2040-04-02","Velyku antroji diena","LT",2040 +"2040-05-01","Tarptautine darbo diena","LT",2040 +"2040-05-06","Motinos diena","LT",2040 +"2040-06-03","Tevo diena","LT",2040 +"2040-06-24","Jonines, Rasos","LT",2040 +"2040-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2040 +"2040-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2040 +"2040-11-01","Visu sventuju diena (Velines)","LT",2040 +"2040-11-02","Mirusiuju atminimo diena (Velines)","LT",2040 +"2040-12-24","Sv. Kucios","LT",2040 +"2040-12-25","Sv. Kaledu pirma diena","LT",2040 +"2040-12-26","Sv. Kaledu antra diena","LT",2040 +"2041-01-01","Naujieji metai","LT",2041 +"2041-02-16","Lietuvos valstybes atkurimo diena","LT",2041 +"2041-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2041 +"2041-04-21","Velykos","LT",2041 +"2041-04-22","Velyku antroji diena","LT",2041 +"2041-05-01","Tarptautine darbo diena","LT",2041 +"2041-05-05","Motinos diena","LT",2041 +"2041-06-02","Tevo diena","LT",2041 +"2041-06-24","Jonines, Rasos","LT",2041 +"2041-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2041 +"2041-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2041 +"2041-11-01","Visu sventuju diena (Velines)","LT",2041 +"2041-11-02","Mirusiuju atminimo diena (Velines)","LT",2041 +"2041-12-24","Sv. Kucios","LT",2041 +"2041-12-25","Sv. Kaledu pirma diena","LT",2041 +"2041-12-26","Sv. Kaledu antra diena","LT",2041 +"2042-01-01","Naujieji metai","LT",2042 +"2042-02-16","Lietuvos valstybes atkurimo diena","LT",2042 +"2042-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2042 +"2042-04-06","Velykos","LT",2042 +"2042-04-07","Velyku antroji diena","LT",2042 +"2042-05-01","Tarptautine darbo diena","LT",2042 +"2042-05-04","Motinos diena","LT",2042 +"2042-06-01","Tevo diena","LT",2042 +"2042-06-24","Jonines, Rasos","LT",2042 +"2042-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2042 +"2042-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2042 +"2042-11-01","Visu sventuju diena (Velines)","LT",2042 +"2042-11-02","Mirusiuju atminimo diena (Velines)","LT",2042 +"2042-12-24","Sv. Kucios","LT",2042 +"2042-12-25","Sv. Kaledu pirma diena","LT",2042 +"2042-12-26","Sv. Kaledu antra diena","LT",2042 +"2043-01-01","Naujieji metai","LT",2043 +"2043-02-16","Lietuvos valstybes atkurimo diena","LT",2043 +"2043-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2043 +"2043-03-29","Velykos","LT",2043 +"2043-03-30","Velyku antroji diena","LT",2043 +"2043-05-01","Tarptautine darbo diena","LT",2043 +"2043-05-03","Motinos diena","LT",2043 +"2043-06-07","Tevo diena","LT",2043 +"2043-06-24","Jonines, Rasos","LT",2043 +"2043-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2043 +"2043-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2043 +"2043-11-01","Visu sventuju diena (Velines)","LT",2043 +"2043-11-02","Mirusiuju atminimo diena (Velines)","LT",2043 +"2043-12-24","Sv. Kucios","LT",2043 +"2043-12-25","Sv. Kaledu pirma diena","LT",2043 +"2043-12-26","Sv. Kaledu antra diena","LT",2043 +"2044-01-01","Naujieji metai","LT",2044 +"2044-02-16","Lietuvos valstybes atkurimo diena","LT",2044 +"2044-03-11","Lietuvos nepriklausomybes atkurimo diena","LT",2044 +"2044-04-17","Velykos","LT",2044 +"2044-04-18","Velyku antroji diena","LT",2044 +"2044-05-01","Motinos diena","LT",2044 +"2044-05-01","Tarptautine darbo diena","LT",2044 +"2044-06-05","Tevo diena","LT",2044 +"2044-06-24","Jonines, Rasos","LT",2044 +"2044-07-06","Valstybes (Lietuvos karaliaus Mindaugo karunavimo) diena","LT",2044 +"2044-08-15","Zoline (Svc. Mergeles Marijos emimo i dangu diena)","LT",2044 +"2044-11-01","Visu sventuju diena (Velines)","LT",2044 +"2044-11-02","Mirusiuju atminimo diena (Velines)","LT",2044 +"2044-12-24","Sv. Kucios","LT",2044 +"2044-12-25","Sv. Kaledu pirma diena","LT",2044 +"2044-12-26","Sv. Kaledu antra diena","LT",2044 +"1995-01-01","Neijoerschdag","LU",1995 +"1995-04-17","Ouschtermeindeg","LU",1995 +"1995-05-01","Dag vun der Aarbecht","LU",1995 +"1995-05-25","Christi Himmelfaart","LU",1995 +"1995-06-05","Pengschtmeindeg","LU",1995 +"1995-06-23","Nationalfeierdag","LU",1995 +"1995-08-15","Leiffraweschdag","LU",1995 +"1995-11-01","Allerhellgen","LU",1995 +"1995-12-25","Chreschtdag","LU",1995 +"1995-12-26","Stiefesdag","LU",1995 +"1996-01-01","Neijoerschdag","LU",1996 +"1996-04-08","Ouschtermeindeg","LU",1996 +"1996-05-01","Dag vun der Aarbecht","LU",1996 +"1996-05-16","Christi Himmelfaart","LU",1996 +"1996-05-27","Pengschtmeindeg","LU",1996 +"1996-06-23","Nationalfeierdag","LU",1996 +"1996-08-15","Leiffraweschdag","LU",1996 +"1996-11-01","Allerhellgen","LU",1996 +"1996-12-25","Chreschtdag","LU",1996 +"1996-12-26","Stiefesdag","LU",1996 +"1997-01-01","Neijoerschdag","LU",1997 +"1997-03-31","Ouschtermeindeg","LU",1997 +"1997-05-01","Dag vun der Aarbecht","LU",1997 +"1997-05-08","Christi Himmelfaart","LU",1997 +"1997-05-19","Pengschtmeindeg","LU",1997 +"1997-06-23","Nationalfeierdag","LU",1997 +"1997-08-15","Leiffraweschdag","LU",1997 +"1997-11-01","Allerhellgen","LU",1997 +"1997-12-25","Chreschtdag","LU",1997 +"1997-12-26","Stiefesdag","LU",1997 +"1998-01-01","Neijoerschdag","LU",1998 +"1998-04-13","Ouschtermeindeg","LU",1998 +"1998-05-01","Dag vun der Aarbecht","LU",1998 +"1998-05-21","Christi Himmelfaart","LU",1998 +"1998-06-01","Pengschtmeindeg","LU",1998 +"1998-06-23","Nationalfeierdag","LU",1998 +"1998-08-15","Leiffraweschdag","LU",1998 +"1998-11-01","Allerhellgen","LU",1998 +"1998-12-25","Chreschtdag","LU",1998 +"1998-12-26","Stiefesdag","LU",1998 +"1999-01-01","Neijoerschdag","LU",1999 +"1999-04-05","Ouschtermeindeg","LU",1999 +"1999-05-01","Dag vun der Aarbecht","LU",1999 +"1999-05-13","Christi Himmelfaart","LU",1999 +"1999-05-24","Pengschtmeindeg","LU",1999 +"1999-06-23","Nationalfeierdag","LU",1999 +"1999-08-15","Leiffraweschdag","LU",1999 +"1999-11-01","Allerhellgen","LU",1999 +"1999-12-25","Chreschtdag","LU",1999 +"1999-12-26","Stiefesdag","LU",1999 +"2000-01-01","Neijoerschdag","LU",2000 +"2000-04-24","Ouschtermeindeg","LU",2000 +"2000-05-01","Dag vun der Aarbecht","LU",2000 +"2000-06-01","Christi Himmelfaart","LU",2000 +"2000-06-12","Pengschtmeindeg","LU",2000 +"2000-06-23","Nationalfeierdag","LU",2000 +"2000-08-15","Leiffraweschdag","LU",2000 +"2000-11-01","Allerhellgen","LU",2000 +"2000-12-25","Chreschtdag","LU",2000 +"2000-12-26","Stiefesdag","LU",2000 +"2001-01-01","Neijoerschdag","LU",2001 +"2001-04-16","Ouschtermeindeg","LU",2001 +"2001-05-01","Dag vun der Aarbecht","LU",2001 +"2001-05-24","Christi Himmelfaart","LU",2001 +"2001-06-04","Pengschtmeindeg","LU",2001 +"2001-06-23","Nationalfeierdag","LU",2001 +"2001-08-15","Leiffraweschdag","LU",2001 +"2001-11-01","Allerhellgen","LU",2001 +"2001-12-25","Chreschtdag","LU",2001 +"2001-12-26","Stiefesdag","LU",2001 +"2002-01-01","Neijoerschdag","LU",2002 +"2002-04-01","Ouschtermeindeg","LU",2002 +"2002-05-01","Dag vun der Aarbecht","LU",2002 +"2002-05-09","Christi Himmelfaart","LU",2002 +"2002-05-20","Pengschtmeindeg","LU",2002 +"2002-06-23","Nationalfeierdag","LU",2002 +"2002-08-15","Leiffraweschdag","LU",2002 +"2002-11-01","Allerhellgen","LU",2002 +"2002-12-25","Chreschtdag","LU",2002 +"2002-12-26","Stiefesdag","LU",2002 +"2003-01-01","Neijoerschdag","LU",2003 +"2003-04-21","Ouschtermeindeg","LU",2003 +"2003-05-01","Dag vun der Aarbecht","LU",2003 +"2003-05-29","Christi Himmelfaart","LU",2003 +"2003-06-09","Pengschtmeindeg","LU",2003 +"2003-06-23","Nationalfeierdag","LU",2003 +"2003-08-15","Leiffraweschdag","LU",2003 +"2003-11-01","Allerhellgen","LU",2003 +"2003-12-25","Chreschtdag","LU",2003 +"2003-12-26","Stiefesdag","LU",2003 +"2004-01-01","Neijoerschdag","LU",2004 +"2004-04-12","Ouschtermeindeg","LU",2004 +"2004-05-01","Dag vun der Aarbecht","LU",2004 +"2004-05-20","Christi Himmelfaart","LU",2004 +"2004-05-31","Pengschtmeindeg","LU",2004 +"2004-06-23","Nationalfeierdag","LU",2004 +"2004-08-15","Leiffraweschdag","LU",2004 +"2004-11-01","Allerhellgen","LU",2004 +"2004-12-25","Chreschtdag","LU",2004 +"2004-12-26","Stiefesdag","LU",2004 +"2005-01-01","Neijoerschdag","LU",2005 +"2005-03-28","Ouschtermeindeg","LU",2005 +"2005-05-01","Dag vun der Aarbecht","LU",2005 +"2005-05-05","Christi Himmelfaart","LU",2005 +"2005-05-16","Pengschtmeindeg","LU",2005 +"2005-06-23","Nationalfeierdag","LU",2005 +"2005-08-15","Leiffraweschdag","LU",2005 +"2005-11-01","Allerhellgen","LU",2005 +"2005-12-25","Chreschtdag","LU",2005 +"2005-12-26","Stiefesdag","LU",2005 +"2006-01-01","Neijoerschdag","LU",2006 +"2006-04-17","Ouschtermeindeg","LU",2006 +"2006-05-01","Dag vun der Aarbecht","LU",2006 +"2006-05-25","Christi Himmelfaart","LU",2006 +"2006-06-05","Pengschtmeindeg","LU",2006 +"2006-06-23","Nationalfeierdag","LU",2006 +"2006-08-15","Leiffraweschdag","LU",2006 +"2006-11-01","Allerhellgen","LU",2006 +"2006-12-25","Chreschtdag","LU",2006 +"2006-12-26","Stiefesdag","LU",2006 +"2007-01-01","Neijoerschdag","LU",2007 +"2007-04-09","Ouschtermeindeg","LU",2007 +"2007-05-01","Dag vun der Aarbecht","LU",2007 +"2007-05-17","Christi Himmelfaart","LU",2007 +"2007-05-28","Pengschtmeindeg","LU",2007 +"2007-06-23","Nationalfeierdag","LU",2007 +"2007-08-15","Leiffraweschdag","LU",2007 +"2007-11-01","Allerhellgen","LU",2007 +"2007-12-25","Chreschtdag","LU",2007 +"2007-12-26","Stiefesdag","LU",2007 +"2008-01-01","Neijoerschdag","LU",2008 +"2008-03-24","Ouschtermeindeg","LU",2008 +"2008-05-01","Christi Himmelfaart","LU",2008 +"2008-05-01","Dag vun der Aarbecht","LU",2008 +"2008-05-12","Pengschtmeindeg","LU",2008 +"2008-06-23","Nationalfeierdag","LU",2008 +"2008-08-15","Leiffraweschdag","LU",2008 +"2008-11-01","Allerhellgen","LU",2008 +"2008-12-25","Chreschtdag","LU",2008 +"2008-12-26","Stiefesdag","LU",2008 +"2009-01-01","Neijoerschdag","LU",2009 +"2009-04-13","Ouschtermeindeg","LU",2009 +"2009-05-01","Dag vun der Aarbecht","LU",2009 +"2009-05-21","Christi Himmelfaart","LU",2009 +"2009-06-01","Pengschtmeindeg","LU",2009 +"2009-06-23","Nationalfeierdag","LU",2009 +"2009-08-15","Leiffraweschdag","LU",2009 +"2009-11-01","Allerhellgen","LU",2009 +"2009-12-25","Chreschtdag","LU",2009 +"2009-12-26","Stiefesdag","LU",2009 +"2010-01-01","Neijoerschdag","LU",2010 +"2010-04-05","Ouschtermeindeg","LU",2010 +"2010-05-01","Dag vun der Aarbecht","LU",2010 +"2010-05-13","Christi Himmelfaart","LU",2010 +"2010-05-24","Pengschtmeindeg","LU",2010 +"2010-06-23","Nationalfeierdag","LU",2010 +"2010-08-15","Leiffraweschdag","LU",2010 +"2010-11-01","Allerhellgen","LU",2010 +"2010-12-25","Chreschtdag","LU",2010 +"2010-12-26","Stiefesdag","LU",2010 +"2011-01-01","Neijoerschdag","LU",2011 +"2011-04-25","Ouschtermeindeg","LU",2011 +"2011-05-01","Dag vun der Aarbecht","LU",2011 +"2011-06-02","Christi Himmelfaart","LU",2011 +"2011-06-13","Pengschtmeindeg","LU",2011 +"2011-06-23","Nationalfeierdag","LU",2011 +"2011-08-15","Leiffraweschdag","LU",2011 +"2011-11-01","Allerhellgen","LU",2011 +"2011-12-25","Chreschtdag","LU",2011 +"2011-12-26","Stiefesdag","LU",2011 +"2012-01-01","Neijoerschdag","LU",2012 +"2012-04-09","Ouschtermeindeg","LU",2012 +"2012-05-01","Dag vun der Aarbecht","LU",2012 +"2012-05-17","Christi Himmelfaart","LU",2012 +"2012-05-28","Pengschtmeindeg","LU",2012 +"2012-06-23","Nationalfeierdag","LU",2012 +"2012-08-15","Leiffraweschdag","LU",2012 +"2012-11-01","Allerhellgen","LU",2012 +"2012-12-25","Chreschtdag","LU",2012 +"2012-12-26","Stiefesdag","LU",2012 +"2013-01-01","Neijoerschdag","LU",2013 +"2013-04-01","Ouschtermeindeg","LU",2013 +"2013-05-01","Dag vun der Aarbecht","LU",2013 +"2013-05-09","Christi Himmelfaart","LU",2013 +"2013-05-20","Pengschtmeindeg","LU",2013 +"2013-06-23","Nationalfeierdag","LU",2013 +"2013-08-15","Leiffraweschdag","LU",2013 +"2013-11-01","Allerhellgen","LU",2013 +"2013-12-25","Chreschtdag","LU",2013 +"2013-12-26","Stiefesdag","LU",2013 +"2014-01-01","Neijoerschdag","LU",2014 +"2014-04-21","Ouschtermeindeg","LU",2014 +"2014-05-01","Dag vun der Aarbecht","LU",2014 +"2014-05-29","Christi Himmelfaart","LU",2014 +"2014-06-09","Pengschtmeindeg","LU",2014 +"2014-06-23","Nationalfeierdag","LU",2014 +"2014-08-15","Leiffraweschdag","LU",2014 +"2014-11-01","Allerhellgen","LU",2014 +"2014-12-25","Chreschtdag","LU",2014 +"2014-12-26","Stiefesdag","LU",2014 +"2015-01-01","Neijoerschdag","LU",2015 +"2015-04-06","Ouschtermeindeg","LU",2015 +"2015-05-01","Dag vun der Aarbecht","LU",2015 +"2015-05-14","Christi Himmelfaart","LU",2015 +"2015-05-25","Pengschtmeindeg","LU",2015 +"2015-06-23","Nationalfeierdag","LU",2015 +"2015-08-15","Leiffraweschdag","LU",2015 +"2015-11-01","Allerhellgen","LU",2015 +"2015-12-25","Chreschtdag","LU",2015 +"2015-12-26","Stiefesdag","LU",2015 +"2016-01-01","Neijoerschdag","LU",2016 +"2016-03-28","Ouschtermeindeg","LU",2016 +"2016-05-01","Dag vun der Aarbecht","LU",2016 +"2016-05-05","Christi Himmelfaart","LU",2016 +"2016-05-16","Pengschtmeindeg","LU",2016 +"2016-06-23","Nationalfeierdag","LU",2016 +"2016-08-15","Leiffraweschdag","LU",2016 +"2016-11-01","Allerhellgen","LU",2016 +"2016-12-25","Chreschtdag","LU",2016 +"2016-12-26","Stiefesdag","LU",2016 +"2017-01-01","Neijoerschdag","LU",2017 +"2017-04-17","Ouschtermeindeg","LU",2017 +"2017-05-01","Dag vun der Aarbecht","LU",2017 +"2017-05-25","Christi Himmelfaart","LU",2017 +"2017-06-05","Pengschtmeindeg","LU",2017 +"2017-06-23","Nationalfeierdag","LU",2017 +"2017-08-15","Leiffraweschdag","LU",2017 +"2017-11-01","Allerhellgen","LU",2017 +"2017-12-25","Chreschtdag","LU",2017 +"2017-12-26","Stiefesdag","LU",2017 +"2018-01-01","Neijoerschdag","LU",2018 +"2018-04-02","Ouschtermeindeg","LU",2018 +"2018-05-01","Dag vun der Aarbecht","LU",2018 +"2018-05-10","Christi Himmelfaart","LU",2018 +"2018-05-21","Pengschtmeindeg","LU",2018 +"2018-06-23","Nationalfeierdag","LU",2018 +"2018-08-15","Leiffraweschdag","LU",2018 +"2018-11-01","Allerhellgen","LU",2018 +"2018-12-25","Chreschtdag","LU",2018 +"2018-12-26","Stiefesdag","LU",2018 +"2019-01-01","Neijoerschdag","LU",2019 +"2019-04-22","Ouschtermeindeg","LU",2019 +"2019-05-01","Dag vun der Aarbecht","LU",2019 +"2019-05-09","Europadag","LU",2019 +"2019-05-30","Christi Himmelfaart","LU",2019 +"2019-06-10","Pengschtmeindeg","LU",2019 +"2019-06-23","Nationalfeierdag","LU",2019 +"2019-08-15","Leiffraweschdag","LU",2019 +"2019-11-01","Allerhellgen","LU",2019 +"2019-12-25","Chreschtdag","LU",2019 +"2019-12-26","Stiefesdag","LU",2019 +"2020-01-01","Neijoerschdag","LU",2020 +"2020-04-13","Ouschtermeindeg","LU",2020 +"2020-05-01","Dag vun der Aarbecht","LU",2020 +"2020-05-09","Europadag","LU",2020 +"2020-05-21","Christi Himmelfaart","LU",2020 +"2020-06-01","Pengschtmeindeg","LU",2020 +"2020-06-23","Nationalfeierdag","LU",2020 +"2020-08-15","Leiffraweschdag","LU",2020 +"2020-11-01","Allerhellgen","LU",2020 +"2020-12-25","Chreschtdag","LU",2020 +"2020-12-26","Stiefesdag","LU",2020 +"2021-01-01","Neijoerschdag","LU",2021 +"2021-04-05","Ouschtermeindeg","LU",2021 +"2021-05-01","Dag vun der Aarbecht","LU",2021 +"2021-05-09","Europadag","LU",2021 +"2021-05-13","Christi Himmelfaart","LU",2021 +"2021-05-24","Pengschtmeindeg","LU",2021 +"2021-06-23","Nationalfeierdag","LU",2021 +"2021-08-15","Leiffraweschdag","LU",2021 +"2021-11-01","Allerhellgen","LU",2021 +"2021-12-25","Chreschtdag","LU",2021 +"2021-12-26","Stiefesdag","LU",2021 +"2022-01-01","Neijoerschdag","LU",2022 +"2022-04-18","Ouschtermeindeg","LU",2022 +"2022-05-01","Dag vun der Aarbecht","LU",2022 +"2022-05-09","Europadag","LU",2022 +"2022-05-26","Christi Himmelfaart","LU",2022 +"2022-06-06","Pengschtmeindeg","LU",2022 +"2022-06-23","Nationalfeierdag","LU",2022 +"2022-08-15","Leiffraweschdag","LU",2022 +"2022-11-01","Allerhellgen","LU",2022 +"2022-12-25","Chreschtdag","LU",2022 +"2022-12-26","Stiefesdag","LU",2022 +"2023-01-01","Neijoerschdag","LU",2023 +"2023-04-10","Ouschtermeindeg","LU",2023 +"2023-05-01","Dag vun der Aarbecht","LU",2023 +"2023-05-09","Europadag","LU",2023 +"2023-05-18","Christi Himmelfaart","LU",2023 +"2023-05-29","Pengschtmeindeg","LU",2023 +"2023-06-23","Nationalfeierdag","LU",2023 +"2023-08-15","Leiffraweschdag","LU",2023 +"2023-11-01","Allerhellgen","LU",2023 +"2023-12-25","Chreschtdag","LU",2023 +"2023-12-26","Stiefesdag","LU",2023 +"2024-01-01","Neijoerschdag","LU",2024 +"2024-04-01","Ouschtermeindeg","LU",2024 +"2024-05-01","Dag vun der Aarbecht","LU",2024 +"2024-05-09","Christi Himmelfaart","LU",2024 +"2024-05-09","Europadag","LU",2024 +"2024-05-20","Pengschtmeindeg","LU",2024 +"2024-06-23","Nationalfeierdag","LU",2024 +"2024-08-15","Leiffraweschdag","LU",2024 +"2024-11-01","Allerhellgen","LU",2024 +"2024-12-25","Chreschtdag","LU",2024 +"2024-12-26","Stiefesdag","LU",2024 +"2025-01-01","Neijoerschdag","LU",2025 +"2025-04-21","Ouschtermeindeg","LU",2025 +"2025-05-01","Dag vun der Aarbecht","LU",2025 +"2025-05-09","Europadag","LU",2025 +"2025-05-29","Christi Himmelfaart","LU",2025 +"2025-06-09","Pengschtmeindeg","LU",2025 +"2025-06-23","Nationalfeierdag","LU",2025 +"2025-08-15","Leiffraweschdag","LU",2025 +"2025-11-01","Allerhellgen","LU",2025 +"2025-12-25","Chreschtdag","LU",2025 +"2025-12-26","Stiefesdag","LU",2025 +"2026-01-01","Neijoerschdag","LU",2026 +"2026-04-06","Ouschtermeindeg","LU",2026 +"2026-05-01","Dag vun der Aarbecht","LU",2026 +"2026-05-09","Europadag","LU",2026 +"2026-05-14","Christi Himmelfaart","LU",2026 +"2026-05-25","Pengschtmeindeg","LU",2026 +"2026-06-23","Nationalfeierdag","LU",2026 +"2026-08-15","Leiffraweschdag","LU",2026 +"2026-11-01","Allerhellgen","LU",2026 +"2026-12-25","Chreschtdag","LU",2026 +"2026-12-26","Stiefesdag","LU",2026 +"2027-01-01","Neijoerschdag","LU",2027 +"2027-03-29","Ouschtermeindeg","LU",2027 +"2027-05-01","Dag vun der Aarbecht","LU",2027 +"2027-05-06","Christi Himmelfaart","LU",2027 +"2027-05-09","Europadag","LU",2027 +"2027-05-17","Pengschtmeindeg","LU",2027 +"2027-06-23","Nationalfeierdag","LU",2027 +"2027-08-15","Leiffraweschdag","LU",2027 +"2027-11-01","Allerhellgen","LU",2027 +"2027-12-25","Chreschtdag","LU",2027 +"2027-12-26","Stiefesdag","LU",2027 +"2028-01-01","Neijoerschdag","LU",2028 +"2028-04-17","Ouschtermeindeg","LU",2028 +"2028-05-01","Dag vun der Aarbecht","LU",2028 +"2028-05-09","Europadag","LU",2028 +"2028-05-25","Christi Himmelfaart","LU",2028 +"2028-06-05","Pengschtmeindeg","LU",2028 +"2028-06-23","Nationalfeierdag","LU",2028 +"2028-08-15","Leiffraweschdag","LU",2028 +"2028-11-01","Allerhellgen","LU",2028 +"2028-12-25","Chreschtdag","LU",2028 +"2028-12-26","Stiefesdag","LU",2028 +"2029-01-01","Neijoerschdag","LU",2029 +"2029-04-02","Ouschtermeindeg","LU",2029 +"2029-05-01","Dag vun der Aarbecht","LU",2029 +"2029-05-09","Europadag","LU",2029 +"2029-05-10","Christi Himmelfaart","LU",2029 +"2029-05-21","Pengschtmeindeg","LU",2029 +"2029-06-23","Nationalfeierdag","LU",2029 +"2029-08-15","Leiffraweschdag","LU",2029 +"2029-11-01","Allerhellgen","LU",2029 +"2029-12-25","Chreschtdag","LU",2029 +"2029-12-26","Stiefesdag","LU",2029 +"2030-01-01","Neijoerschdag","LU",2030 +"2030-04-22","Ouschtermeindeg","LU",2030 +"2030-05-01","Dag vun der Aarbecht","LU",2030 +"2030-05-09","Europadag","LU",2030 +"2030-05-30","Christi Himmelfaart","LU",2030 +"2030-06-10","Pengschtmeindeg","LU",2030 +"2030-06-23","Nationalfeierdag","LU",2030 +"2030-08-15","Leiffraweschdag","LU",2030 +"2030-11-01","Allerhellgen","LU",2030 +"2030-12-25","Chreschtdag","LU",2030 +"2030-12-26","Stiefesdag","LU",2030 +"2031-01-01","Neijoerschdag","LU",2031 +"2031-04-14","Ouschtermeindeg","LU",2031 +"2031-05-01","Dag vun der Aarbecht","LU",2031 +"2031-05-09","Europadag","LU",2031 +"2031-05-22","Christi Himmelfaart","LU",2031 +"2031-06-02","Pengschtmeindeg","LU",2031 +"2031-06-23","Nationalfeierdag","LU",2031 +"2031-08-15","Leiffraweschdag","LU",2031 +"2031-11-01","Allerhellgen","LU",2031 +"2031-12-25","Chreschtdag","LU",2031 +"2031-12-26","Stiefesdag","LU",2031 +"2032-01-01","Neijoerschdag","LU",2032 +"2032-03-29","Ouschtermeindeg","LU",2032 +"2032-05-01","Dag vun der Aarbecht","LU",2032 +"2032-05-06","Christi Himmelfaart","LU",2032 +"2032-05-09","Europadag","LU",2032 +"2032-05-17","Pengschtmeindeg","LU",2032 +"2032-06-23","Nationalfeierdag","LU",2032 +"2032-08-15","Leiffraweschdag","LU",2032 +"2032-11-01","Allerhellgen","LU",2032 +"2032-12-25","Chreschtdag","LU",2032 +"2032-12-26","Stiefesdag","LU",2032 +"2033-01-01","Neijoerschdag","LU",2033 +"2033-04-18","Ouschtermeindeg","LU",2033 +"2033-05-01","Dag vun der Aarbecht","LU",2033 +"2033-05-09","Europadag","LU",2033 +"2033-05-26","Christi Himmelfaart","LU",2033 +"2033-06-06","Pengschtmeindeg","LU",2033 +"2033-06-23","Nationalfeierdag","LU",2033 +"2033-08-15","Leiffraweschdag","LU",2033 +"2033-11-01","Allerhellgen","LU",2033 +"2033-12-25","Chreschtdag","LU",2033 +"2033-12-26","Stiefesdag","LU",2033 +"2034-01-01","Neijoerschdag","LU",2034 +"2034-04-10","Ouschtermeindeg","LU",2034 +"2034-05-01","Dag vun der Aarbecht","LU",2034 +"2034-05-09","Europadag","LU",2034 +"2034-05-18","Christi Himmelfaart","LU",2034 +"2034-05-29","Pengschtmeindeg","LU",2034 +"2034-06-23","Nationalfeierdag","LU",2034 +"2034-08-15","Leiffraweschdag","LU",2034 +"2034-11-01","Allerhellgen","LU",2034 +"2034-12-25","Chreschtdag","LU",2034 +"2034-12-26","Stiefesdag","LU",2034 +"2035-01-01","Neijoerschdag","LU",2035 +"2035-03-26","Ouschtermeindeg","LU",2035 +"2035-05-01","Dag vun der Aarbecht","LU",2035 +"2035-05-03","Christi Himmelfaart","LU",2035 +"2035-05-09","Europadag","LU",2035 +"2035-05-14","Pengschtmeindeg","LU",2035 +"2035-06-23","Nationalfeierdag","LU",2035 +"2035-08-15","Leiffraweschdag","LU",2035 +"2035-11-01","Allerhellgen","LU",2035 +"2035-12-25","Chreschtdag","LU",2035 +"2035-12-26","Stiefesdag","LU",2035 +"2036-01-01","Neijoerschdag","LU",2036 +"2036-04-14","Ouschtermeindeg","LU",2036 +"2036-05-01","Dag vun der Aarbecht","LU",2036 +"2036-05-09","Europadag","LU",2036 +"2036-05-22","Christi Himmelfaart","LU",2036 +"2036-06-02","Pengschtmeindeg","LU",2036 +"2036-06-23","Nationalfeierdag","LU",2036 +"2036-08-15","Leiffraweschdag","LU",2036 +"2036-11-01","Allerhellgen","LU",2036 +"2036-12-25","Chreschtdag","LU",2036 +"2036-12-26","Stiefesdag","LU",2036 +"2037-01-01","Neijoerschdag","LU",2037 +"2037-04-06","Ouschtermeindeg","LU",2037 +"2037-05-01","Dag vun der Aarbecht","LU",2037 +"2037-05-09","Europadag","LU",2037 +"2037-05-14","Christi Himmelfaart","LU",2037 +"2037-05-25","Pengschtmeindeg","LU",2037 +"2037-06-23","Nationalfeierdag","LU",2037 +"2037-08-15","Leiffraweschdag","LU",2037 +"2037-11-01","Allerhellgen","LU",2037 +"2037-12-25","Chreschtdag","LU",2037 +"2037-12-26","Stiefesdag","LU",2037 +"2038-01-01","Neijoerschdag","LU",2038 +"2038-04-26","Ouschtermeindeg","LU",2038 +"2038-05-01","Dag vun der Aarbecht","LU",2038 +"2038-05-09","Europadag","LU",2038 +"2038-06-03","Christi Himmelfaart","LU",2038 +"2038-06-14","Pengschtmeindeg","LU",2038 +"2038-06-23","Nationalfeierdag","LU",2038 +"2038-08-15","Leiffraweschdag","LU",2038 +"2038-11-01","Allerhellgen","LU",2038 +"2038-12-25","Chreschtdag","LU",2038 +"2038-12-26","Stiefesdag","LU",2038 +"2039-01-01","Neijoerschdag","LU",2039 +"2039-04-11","Ouschtermeindeg","LU",2039 +"2039-05-01","Dag vun der Aarbecht","LU",2039 +"2039-05-09","Europadag","LU",2039 +"2039-05-19","Christi Himmelfaart","LU",2039 +"2039-05-30","Pengschtmeindeg","LU",2039 +"2039-06-23","Nationalfeierdag","LU",2039 +"2039-08-15","Leiffraweschdag","LU",2039 +"2039-11-01","Allerhellgen","LU",2039 +"2039-12-25","Chreschtdag","LU",2039 +"2039-12-26","Stiefesdag","LU",2039 +"2040-01-01","Neijoerschdag","LU",2040 +"2040-04-02","Ouschtermeindeg","LU",2040 +"2040-05-01","Dag vun der Aarbecht","LU",2040 +"2040-05-09","Europadag","LU",2040 +"2040-05-10","Christi Himmelfaart","LU",2040 +"2040-05-21","Pengschtmeindeg","LU",2040 +"2040-06-23","Nationalfeierdag","LU",2040 +"2040-08-15","Leiffraweschdag","LU",2040 +"2040-11-01","Allerhellgen","LU",2040 +"2040-12-25","Chreschtdag","LU",2040 +"2040-12-26","Stiefesdag","LU",2040 +"2041-01-01","Neijoerschdag","LU",2041 +"2041-04-22","Ouschtermeindeg","LU",2041 +"2041-05-01","Dag vun der Aarbecht","LU",2041 +"2041-05-09","Europadag","LU",2041 +"2041-05-30","Christi Himmelfaart","LU",2041 +"2041-06-10","Pengschtmeindeg","LU",2041 +"2041-06-23","Nationalfeierdag","LU",2041 +"2041-08-15","Leiffraweschdag","LU",2041 +"2041-11-01","Allerhellgen","LU",2041 +"2041-12-25","Chreschtdag","LU",2041 +"2041-12-26","Stiefesdag","LU",2041 +"2042-01-01","Neijoerschdag","LU",2042 +"2042-04-07","Ouschtermeindeg","LU",2042 +"2042-05-01","Dag vun der Aarbecht","LU",2042 +"2042-05-09","Europadag","LU",2042 +"2042-05-15","Christi Himmelfaart","LU",2042 +"2042-05-26","Pengschtmeindeg","LU",2042 +"2042-06-23","Nationalfeierdag","LU",2042 +"2042-08-15","Leiffraweschdag","LU",2042 +"2042-11-01","Allerhellgen","LU",2042 +"2042-12-25","Chreschtdag","LU",2042 +"2042-12-26","Stiefesdag","LU",2042 +"2043-01-01","Neijoerschdag","LU",2043 +"2043-03-30","Ouschtermeindeg","LU",2043 +"2043-05-01","Dag vun der Aarbecht","LU",2043 +"2043-05-07","Christi Himmelfaart","LU",2043 +"2043-05-09","Europadag","LU",2043 +"2043-05-18","Pengschtmeindeg","LU",2043 +"2043-06-23","Nationalfeierdag","LU",2043 +"2043-08-15","Leiffraweschdag","LU",2043 +"2043-11-01","Allerhellgen","LU",2043 +"2043-12-25","Chreschtdag","LU",2043 +"2043-12-26","Stiefesdag","LU",2043 +"2044-01-01","Neijoerschdag","LU",2044 +"2044-04-18","Ouschtermeindeg","LU",2044 +"2044-05-01","Dag vun der Aarbecht","LU",2044 +"2044-05-09","Europadag","LU",2044 +"2044-05-26","Christi Himmelfaart","LU",2044 +"2044-06-06","Pengschtmeindeg","LU",2044 +"2044-06-23","Nationalfeierdag","LU",2044 +"2044-08-15","Leiffraweschdag","LU",2044 +"2044-11-01","Allerhellgen","LU",2044 +"2044-12-25","Chreschtdag","LU",2044 +"2044-12-26","Stiefesdag","LU",2044 +"1995-01-01","Jaunais gads","LV",1995 +"1995-04-14","Liela Piektdiena","LV",1995 +"1995-04-16","Lieldienas","LV",1995 +"1995-04-17","Otras Lieldienas","LV",1995 +"1995-05-01","Darba svetki","LV",1995 +"1995-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",1995 +"1995-06-23","Ligo diena","LV",1995 +"1995-06-24","Janu dienu","LV",1995 +"1995-11-18","Latvijas Republikas proklamesanas diena","LV",1995 +"1995-12-24","Ziemassvetku vakars","LV",1995 +"1995-12-25","Ziemassvetki","LV",1995 +"1995-12-26","Otrie Ziemassvetki","LV",1995 +"1995-12-31","Vecgada vakars","LV",1995 +"1996-01-01","Jaunais gads","LV",1996 +"1996-04-05","Liela Piektdiena","LV",1996 +"1996-04-07","Lieldienas","LV",1996 +"1996-04-08","Otras Lieldienas","LV",1996 +"1996-05-01","Darba svetki","LV",1996 +"1996-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",1996 +"1996-06-23","Ligo diena","LV",1996 +"1996-06-24","Janu dienu","LV",1996 +"1996-11-18","Latvijas Republikas proklamesanas diena","LV",1996 +"1996-12-24","Ziemassvetku vakars","LV",1996 +"1996-12-25","Ziemassvetki","LV",1996 +"1996-12-26","Otrie Ziemassvetki","LV",1996 +"1996-12-31","Vecgada vakars","LV",1996 +"1997-01-01","Jaunais gads","LV",1997 +"1997-03-28","Liela Piektdiena","LV",1997 +"1997-03-30","Lieldienas","LV",1997 +"1997-03-31","Otras Lieldienas","LV",1997 +"1997-05-01","Darba svetki","LV",1997 +"1997-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",1997 +"1997-06-23","Ligo diena","LV",1997 +"1997-06-24","Janu dienu","LV",1997 +"1997-11-18","Latvijas Republikas proklamesanas diena","LV",1997 +"1997-12-24","Ziemassvetku vakars","LV",1997 +"1997-12-25","Ziemassvetki","LV",1997 +"1997-12-26","Otrie Ziemassvetki","LV",1997 +"1997-12-31","Vecgada vakars","LV",1997 +"1998-01-01","Jaunais gads","LV",1998 +"1998-04-10","Liela Piektdiena","LV",1998 +"1998-04-12","Lieldienas","LV",1998 +"1998-04-13","Otras Lieldienas","LV",1998 +"1998-05-01","Darba svetki","LV",1998 +"1998-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",1998 +"1998-06-23","Ligo diena","LV",1998 +"1998-06-24","Janu dienu","LV",1998 +"1998-11-18","Latvijas Republikas proklamesanas diena","LV",1998 +"1998-12-24","Ziemassvetku vakars","LV",1998 +"1998-12-25","Ziemassvetki","LV",1998 +"1998-12-26","Otrie Ziemassvetki","LV",1998 +"1998-12-31","Vecgada vakars","LV",1998 +"1999-01-01","Jaunais gads","LV",1999 +"1999-04-02","Liela Piektdiena","LV",1999 +"1999-04-04","Lieldienas","LV",1999 +"1999-04-05","Otras Lieldienas","LV",1999 +"1999-05-01","Darba svetki","LV",1999 +"1999-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",1999 +"1999-06-23","Ligo diena","LV",1999 +"1999-06-24","Janu dienu","LV",1999 +"1999-11-18","Latvijas Republikas proklamesanas diena","LV",1999 +"1999-12-24","Ziemassvetku vakars","LV",1999 +"1999-12-25","Ziemassvetki","LV",1999 +"1999-12-26","Otrie Ziemassvetki","LV",1999 +"1999-12-31","Vecgada vakars","LV",1999 +"2000-01-01","Jaunais gads","LV",2000 +"2000-04-21","Liela Piektdiena","LV",2000 +"2000-04-23","Lieldienas","LV",2000 +"2000-04-24","Otras Lieldienas","LV",2000 +"2000-05-01","Darba svetki","LV",2000 +"2000-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2000 +"2000-06-23","Ligo diena","LV",2000 +"2000-06-24","Janu dienu","LV",2000 +"2000-11-18","Latvijas Republikas proklamesanas diena","LV",2000 +"2000-12-24","Ziemassvetku vakars","LV",2000 +"2000-12-25","Ziemassvetki","LV",2000 +"2000-12-26","Otrie Ziemassvetki","LV",2000 +"2000-12-31","Vecgada vakars","LV",2000 +"2001-01-01","Jaunais gads","LV",2001 +"2001-04-13","Liela Piektdiena","LV",2001 +"2001-04-15","Lieldienas","LV",2001 +"2001-04-16","Otras Lieldienas","LV",2001 +"2001-05-01","Darba svetki","LV",2001 +"2001-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2001 +"2001-06-23","Ligo diena","LV",2001 +"2001-06-24","Janu dienu","LV",2001 +"2001-11-18","Latvijas Republikas proklamesanas diena","LV",2001 +"2001-12-24","Ziemassvetku vakars","LV",2001 +"2001-12-25","Ziemassvetki","LV",2001 +"2001-12-26","Otrie Ziemassvetki","LV",2001 +"2001-12-31","Vecgada vakars","LV",2001 +"2002-01-01","Jaunais gads","LV",2002 +"2002-03-29","Liela Piektdiena","LV",2002 +"2002-03-31","Lieldienas","LV",2002 +"2002-04-01","Otras Lieldienas","LV",2002 +"2002-05-01","Darba svetki","LV",2002 +"2002-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2002 +"2002-06-23","Ligo diena","LV",2002 +"2002-06-24","Janu dienu","LV",2002 +"2002-11-18","Latvijas Republikas proklamesanas diena","LV",2002 +"2002-12-24","Ziemassvetku vakars","LV",2002 +"2002-12-25","Ziemassvetki","LV",2002 +"2002-12-26","Otrie Ziemassvetki","LV",2002 +"2002-12-31","Vecgada vakars","LV",2002 +"2003-01-01","Jaunais gads","LV",2003 +"2003-04-18","Liela Piektdiena","LV",2003 +"2003-04-20","Lieldienas","LV",2003 +"2003-04-21","Otras Lieldienas","LV",2003 +"2003-05-01","Darba svetki","LV",2003 +"2003-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2003 +"2003-06-23","Ligo diena","LV",2003 +"2003-06-24","Janu dienu","LV",2003 +"2003-11-18","Latvijas Republikas proklamesanas diena","LV",2003 +"2003-12-24","Ziemassvetku vakars","LV",2003 +"2003-12-25","Ziemassvetki","LV",2003 +"2003-12-26","Otrie Ziemassvetki","LV",2003 +"2003-12-31","Vecgada vakars","LV",2003 +"2004-01-01","Jaunais gads","LV",2004 +"2004-04-09","Liela Piektdiena","LV",2004 +"2004-04-11","Lieldienas","LV",2004 +"2004-04-12","Otras Lieldienas","LV",2004 +"2004-05-01","Darba svetki","LV",2004 +"2004-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2004 +"2004-06-23","Ligo diena","LV",2004 +"2004-06-24","Janu dienu","LV",2004 +"2004-11-18","Latvijas Republikas proklamesanas diena","LV",2004 +"2004-12-24","Ziemassvetku vakars","LV",2004 +"2004-12-25","Ziemassvetki","LV",2004 +"2004-12-26","Otrie Ziemassvetki","LV",2004 +"2004-12-31","Vecgada vakars","LV",2004 +"2005-01-01","Jaunais gads","LV",2005 +"2005-03-25","Liela Piektdiena","LV",2005 +"2005-03-27","Lieldienas","LV",2005 +"2005-03-28","Otras Lieldienas","LV",2005 +"2005-05-01","Darba svetki","LV",2005 +"2005-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2005 +"2005-06-23","Ligo diena","LV",2005 +"2005-06-24","Janu dienu","LV",2005 +"2005-11-18","Latvijas Republikas proklamesanas diena","LV",2005 +"2005-12-24","Ziemassvetku vakars","LV",2005 +"2005-12-25","Ziemassvetki","LV",2005 +"2005-12-26","Otrie Ziemassvetki","LV",2005 +"2005-12-31","Vecgada vakars","LV",2005 +"2006-01-01","Jaunais gads","LV",2006 +"2006-04-14","Liela Piektdiena","LV",2006 +"2006-04-16","Lieldienas","LV",2006 +"2006-04-17","Otras Lieldienas","LV",2006 +"2006-05-01","Darba svetki","LV",2006 +"2006-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2006 +"2006-06-23","Ligo diena","LV",2006 +"2006-06-24","Janu dienu","LV",2006 +"2006-11-18","Latvijas Republikas proklamesanas diena","LV",2006 +"2006-12-24","Ziemassvetku vakars","LV",2006 +"2006-12-25","Ziemassvetki","LV",2006 +"2006-12-26","Otrie Ziemassvetki","LV",2006 +"2006-12-31","Vecgada vakars","LV",2006 +"2007-01-01","Jaunais gads","LV",2007 +"2007-04-06","Liela Piektdiena","LV",2007 +"2007-04-08","Lieldienas","LV",2007 +"2007-04-09","Otras Lieldienas","LV",2007 +"2007-05-01","Darba svetki","LV",2007 +"2007-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2007 +"2007-06-23","Ligo diena","LV",2007 +"2007-06-24","Janu dienu","LV",2007 +"2007-11-18","Latvijas Republikas proklamesanas diena","LV",2007 +"2007-12-24","Ziemassvetku vakars","LV",2007 +"2007-12-25","Ziemassvetki","LV",2007 +"2007-12-26","Otrie Ziemassvetki","LV",2007 +"2007-12-31","Vecgada vakars","LV",2007 +"2008-01-01","Jaunais gads","LV",2008 +"2008-03-21","Liela Piektdiena","LV",2008 +"2008-03-23","Lieldienas","LV",2008 +"2008-03-24","Otras Lieldienas","LV",2008 +"2008-05-01","Darba svetki","LV",2008 +"2008-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2008 +"2008-06-23","Ligo diena","LV",2008 +"2008-06-24","Janu dienu","LV",2008 +"2008-11-18","Latvijas Republikas proklamesanas diena","LV",2008 +"2008-12-24","Ziemassvetku vakars","LV",2008 +"2008-12-25","Ziemassvetki","LV",2008 +"2008-12-26","Otrie Ziemassvetki","LV",2008 +"2008-12-31","Vecgada vakars","LV",2008 +"2009-01-01","Jaunais gads","LV",2009 +"2009-04-10","Liela Piektdiena","LV",2009 +"2009-04-12","Lieldienas","LV",2009 +"2009-04-13","Otras Lieldienas","LV",2009 +"2009-05-01","Darba svetki","LV",2009 +"2009-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2009 +"2009-06-23","Ligo diena","LV",2009 +"2009-06-24","Janu dienu","LV",2009 +"2009-11-18","Latvijas Republikas proklamesanas diena","LV",2009 +"2009-12-24","Ziemassvetku vakars","LV",2009 +"2009-12-25","Ziemassvetki","LV",2009 +"2009-12-26","Otrie Ziemassvetki","LV",2009 +"2009-12-31","Vecgada vakars","LV",2009 +"2010-01-01","Jaunais gads","LV",2010 +"2010-04-02","Liela Piektdiena","LV",2010 +"2010-04-04","Lieldienas","LV",2010 +"2010-04-05","Otras Lieldienas","LV",2010 +"2010-05-01","Darba svetki","LV",2010 +"2010-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2010 +"2010-06-23","Ligo diena","LV",2010 +"2010-06-24","Janu dienu","LV",2010 +"2010-11-18","Latvijas Republikas proklamesanas diena","LV",2010 +"2010-12-24","Ziemassvetku vakars","LV",2010 +"2010-12-25","Ziemassvetki","LV",2010 +"2010-12-26","Otrie Ziemassvetki","LV",2010 +"2010-12-31","Vecgada vakars","LV",2010 +"2011-01-01","Jaunais gads","LV",2011 +"2011-04-22","Liela Piektdiena","LV",2011 +"2011-04-24","Lieldienas","LV",2011 +"2011-04-25","Otras Lieldienas","LV",2011 +"2011-05-01","Darba svetki","LV",2011 +"2011-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2011 +"2011-06-23","Ligo diena","LV",2011 +"2011-06-24","Janu dienu","LV",2011 +"2011-11-18","Latvijas Republikas proklamesanas diena","LV",2011 +"2011-12-24","Ziemassvetku vakars","LV",2011 +"2011-12-25","Ziemassvetki","LV",2011 +"2011-12-26","Otrie Ziemassvetki","LV",2011 +"2011-12-31","Vecgada vakars","LV",2011 +"2012-01-01","Jaunais gads","LV",2012 +"2012-04-06","Liela Piektdiena","LV",2012 +"2012-04-08","Lieldienas","LV",2012 +"2012-04-09","Otras Lieldienas","LV",2012 +"2012-05-01","Darba svetki","LV",2012 +"2012-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2012 +"2012-06-23","Ligo diena","LV",2012 +"2012-06-24","Janu dienu","LV",2012 +"2012-11-18","Latvijas Republikas proklamesanas diena","LV",2012 +"2012-12-24","Ziemassvetku vakars","LV",2012 +"2012-12-25","Ziemassvetki","LV",2012 +"2012-12-26","Otrie Ziemassvetki","LV",2012 +"2012-12-31","Vecgada vakars","LV",2012 +"2013-01-01","Jaunais gads","LV",2013 +"2013-03-29","Liela Piektdiena","LV",2013 +"2013-03-31","Lieldienas","LV",2013 +"2013-04-01","Otras Lieldienas","LV",2013 +"2013-05-01","Darba svetki","LV",2013 +"2013-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2013 +"2013-06-23","Ligo diena","LV",2013 +"2013-06-24","Janu dienu","LV",2013 +"2013-11-18","Latvijas Republikas proklamesanas diena","LV",2013 +"2013-12-24","Ziemassvetku vakars","LV",2013 +"2013-12-25","Ziemassvetki","LV",2013 +"2013-12-26","Otrie Ziemassvetki","LV",2013 +"2013-12-31","Vecgada vakars","LV",2013 +"2014-01-01","Jaunais gads","LV",2014 +"2014-04-18","Liela Piektdiena","LV",2014 +"2014-04-20","Lieldienas","LV",2014 +"2014-04-21","Otras Lieldienas","LV",2014 +"2014-05-01","Darba svetki","LV",2014 +"2014-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2014 +"2014-06-23","Ligo diena","LV",2014 +"2014-06-24","Janu dienu","LV",2014 +"2014-11-18","Latvijas Republikas proklamesanas diena","LV",2014 +"2014-12-24","Ziemassvetku vakars","LV",2014 +"2014-12-25","Ziemassvetki","LV",2014 +"2014-12-26","Otrie Ziemassvetki","LV",2014 +"2014-12-31","Vecgada vakars","LV",2014 +"2015-01-01","Jaunais gads","LV",2015 +"2015-04-03","Liela Piektdiena","LV",2015 +"2015-04-05","Lieldienas","LV",2015 +"2015-04-06","Otras Lieldienas","LV",2015 +"2015-05-01","Darba svetki","LV",2015 +"2015-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2015 +"2015-06-23","Ligo diena","LV",2015 +"2015-06-24","Janu dienu","LV",2015 +"2015-11-18","Latvijas Republikas proklamesanas diena","LV",2015 +"2015-12-24","Ziemassvetku vakars","LV",2015 +"2015-12-25","Ziemassvetki","LV",2015 +"2015-12-26","Otrie Ziemassvetki","LV",2015 +"2015-12-31","Vecgada vakars","LV",2015 +"2016-01-01","Jaunais gads","LV",2016 +"2016-03-25","Liela Piektdiena","LV",2016 +"2016-03-27","Lieldienas","LV",2016 +"2016-03-28","Otras Lieldienas","LV",2016 +"2016-05-01","Darba svetki","LV",2016 +"2016-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2016 +"2016-06-23","Ligo diena","LV",2016 +"2016-06-24","Janu dienu","LV",2016 +"2016-11-18","Latvijas Republikas proklamesanas diena","LV",2016 +"2016-12-24","Ziemassvetku vakars","LV",2016 +"2016-12-25","Ziemassvetki","LV",2016 +"2016-12-26","Otrie Ziemassvetki","LV",2016 +"2016-12-31","Vecgada vakars","LV",2016 +"2017-01-01","Jaunais gads","LV",2017 +"2017-04-14","Liela Piektdiena","LV",2017 +"2017-04-16","Lieldienas","LV",2017 +"2017-04-17","Otras Lieldienas","LV",2017 +"2017-05-01","Darba svetki","LV",2017 +"2017-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2017 +"2017-06-23","Ligo diena","LV",2017 +"2017-06-24","Janu dienu","LV",2017 +"2017-11-18","Latvijas Republikas proklamesanas diena","LV",2017 +"2017-12-24","Ziemassvetku vakars","LV",2017 +"2017-12-25","Ziemassvetki","LV",2017 +"2017-12-26","Otrie Ziemassvetki","LV",2017 +"2017-12-31","Vecgada vakars","LV",2017 +"2018-01-01","Jaunais gads","LV",2018 +"2018-03-30","Liela Piektdiena","LV",2018 +"2018-04-01","Lieldienas","LV",2018 +"2018-04-02","Otras Lieldienas","LV",2018 +"2018-05-01","Darba svetki","LV",2018 +"2018-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2018 +"2018-06-23","Ligo diena","LV",2018 +"2018-06-24","Janu dienu","LV",2018 +"2018-11-18","Latvijas Republikas proklamesanas diena","LV",2018 +"2018-12-24","Ziemassvetku vakars","LV",2018 +"2018-12-25","Ziemassvetki","LV",2018 +"2018-12-26","Otrie Ziemassvetki","LV",2018 +"2018-12-31","Vecgada vakars","LV",2018 +"2019-01-01","Jaunais gads","LV",2019 +"2019-04-19","Liela Piektdiena","LV",2019 +"2019-04-21","Lieldienas","LV",2019 +"2019-04-22","Otras Lieldienas","LV",2019 +"2019-05-01","Darba svetki","LV",2019 +"2019-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2019 +"2019-06-23","Ligo diena","LV",2019 +"2019-06-24","Janu dienu","LV",2019 +"2019-11-18","Latvijas Republikas proklamesanas diena","LV",2019 +"2019-12-24","Ziemassvetku vakars","LV",2019 +"2019-12-25","Ziemassvetki","LV",2019 +"2019-12-26","Otrie Ziemassvetki","LV",2019 +"2019-12-31","Vecgada vakars","LV",2019 +"2020-01-01","Jaunais gads","LV",2020 +"2020-04-10","Liela Piektdiena","LV",2020 +"2020-04-12","Lieldienas","LV",2020 +"2020-04-13","Otras Lieldienas","LV",2020 +"2020-05-01","Darba svetki","LV",2020 +"2020-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2020 +"2020-06-23","Ligo diena","LV",2020 +"2020-06-24","Janu dienu","LV",2020 +"2020-11-18","Latvijas Republikas proklamesanas diena","LV",2020 +"2020-12-24","Ziemassvetku vakars","LV",2020 +"2020-12-25","Ziemassvetki","LV",2020 +"2020-12-26","Otrie Ziemassvetki","LV",2020 +"2020-12-31","Vecgada vakars","LV",2020 +"2021-01-01","Jaunais gads","LV",2021 +"2021-04-02","Liela Piektdiena","LV",2021 +"2021-04-04","Lieldienas","LV",2021 +"2021-04-05","Otras Lieldienas","LV",2021 +"2021-05-01","Darba svetki","LV",2021 +"2021-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2021 +"2021-06-23","Ligo diena","LV",2021 +"2021-06-24","Janu dienu","LV",2021 +"2021-11-18","Latvijas Republikas proklamesanas diena","LV",2021 +"2021-12-24","Ziemassvetku vakars","LV",2021 +"2021-12-25","Ziemassvetki","LV",2021 +"2021-12-26","Otrie Ziemassvetki","LV",2021 +"2021-12-31","Vecgada vakars","LV",2021 +"2022-01-01","Jaunais gads","LV",2022 +"2022-04-15","Liela Piektdiena","LV",2022 +"2022-04-17","Lieldienas","LV",2022 +"2022-04-18","Otras Lieldienas","LV",2022 +"2022-05-01","Darba svetki","LV",2022 +"2022-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2022 +"2022-06-23","Ligo diena","LV",2022 +"2022-06-24","Janu dienu","LV",2022 +"2022-11-18","Latvijas Republikas proklamesanas diena","LV",2022 +"2022-12-24","Ziemassvetku vakars","LV",2022 +"2022-12-25","Ziemassvetki","LV",2022 +"2022-12-26","Otrie Ziemassvetki","LV",2022 +"2022-12-31","Vecgada vakars","LV",2022 +"2023-01-01","Jaunais gads","LV",2023 +"2023-04-07","Liela Piektdiena","LV",2023 +"2023-04-09","Lieldienas","LV",2023 +"2023-04-10","Otras Lieldienas","LV",2023 +"2023-05-01","Darba svetki","LV",2023 +"2023-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2023 +"2023-06-23","Ligo diena","LV",2023 +"2023-06-24","Janu dienu","LV",2023 +"2023-11-18","Latvijas Republikas proklamesanas diena","LV",2023 +"2023-12-24","Ziemassvetku vakars","LV",2023 +"2023-12-25","Ziemassvetki","LV",2023 +"2023-12-26","Otrie Ziemassvetki","LV",2023 +"2023-12-31","Vecgada vakars","LV",2023 +"2024-01-01","Jaunais gads","LV",2024 +"2024-03-29","Liela Piektdiena","LV",2024 +"2024-03-31","Lieldienas","LV",2024 +"2024-04-01","Otras Lieldienas","LV",2024 +"2024-05-01","Darba svetki","LV",2024 +"2024-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2024 +"2024-06-23","Ligo diena","LV",2024 +"2024-06-24","Janu dienu","LV",2024 +"2024-11-18","Latvijas Republikas proklamesanas diena","LV",2024 +"2024-12-24","Ziemassvetku vakars","LV",2024 +"2024-12-25","Ziemassvetki","LV",2024 +"2024-12-26","Otrie Ziemassvetki","LV",2024 +"2024-12-31","Vecgada vakars","LV",2024 +"2025-01-01","Jaunais gads","LV",2025 +"2025-04-18","Liela Piektdiena","LV",2025 +"2025-04-20","Lieldienas","LV",2025 +"2025-04-21","Otras Lieldienas","LV",2025 +"2025-05-01","Darba svetki","LV",2025 +"2025-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2025 +"2025-06-23","Ligo diena","LV",2025 +"2025-06-24","Janu dienu","LV",2025 +"2025-11-18","Latvijas Republikas proklamesanas diena","LV",2025 +"2025-12-24","Ziemassvetku vakars","LV",2025 +"2025-12-25","Ziemassvetki","LV",2025 +"2025-12-26","Otrie Ziemassvetki","LV",2025 +"2025-12-31","Vecgada vakars","LV",2025 +"2026-01-01","Jaunais gads","LV",2026 +"2026-04-03","Liela Piektdiena","LV",2026 +"2026-04-05","Lieldienas","LV",2026 +"2026-04-06","Otras Lieldienas","LV",2026 +"2026-05-01","Darba svetki","LV",2026 +"2026-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2026 +"2026-06-23","Ligo diena","LV",2026 +"2026-06-24","Janu dienu","LV",2026 +"2026-11-18","Latvijas Republikas proklamesanas diena","LV",2026 +"2026-12-24","Ziemassvetku vakars","LV",2026 +"2026-12-25","Ziemassvetki","LV",2026 +"2026-12-26","Otrie Ziemassvetki","LV",2026 +"2026-12-31","Vecgada vakars","LV",2026 +"2027-01-01","Jaunais gads","LV",2027 +"2027-03-26","Liela Piektdiena","LV",2027 +"2027-03-28","Lieldienas","LV",2027 +"2027-03-29","Otras Lieldienas","LV",2027 +"2027-05-01","Darba svetki","LV",2027 +"2027-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2027 +"2027-06-23","Ligo diena","LV",2027 +"2027-06-24","Janu dienu","LV",2027 +"2027-11-18","Latvijas Republikas proklamesanas diena","LV",2027 +"2027-12-24","Ziemassvetku vakars","LV",2027 +"2027-12-25","Ziemassvetki","LV",2027 +"2027-12-26","Otrie Ziemassvetki","LV",2027 +"2027-12-31","Vecgada vakars","LV",2027 +"2028-01-01","Jaunais gads","LV",2028 +"2028-04-14","Liela Piektdiena","LV",2028 +"2028-04-16","Lieldienas","LV",2028 +"2028-04-17","Otras Lieldienas","LV",2028 +"2028-05-01","Darba svetki","LV",2028 +"2028-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2028 +"2028-06-23","Ligo diena","LV",2028 +"2028-06-24","Janu dienu","LV",2028 +"2028-11-18","Latvijas Republikas proklamesanas diena","LV",2028 +"2028-12-24","Ziemassvetku vakars","LV",2028 +"2028-12-25","Ziemassvetki","LV",2028 +"2028-12-26","Otrie Ziemassvetki","LV",2028 +"2028-12-31","Vecgada vakars","LV",2028 +"2029-01-01","Jaunais gads","LV",2029 +"2029-03-30","Liela Piektdiena","LV",2029 +"2029-04-01","Lieldienas","LV",2029 +"2029-04-02","Otras Lieldienas","LV",2029 +"2029-05-01","Darba svetki","LV",2029 +"2029-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2029 +"2029-06-23","Ligo diena","LV",2029 +"2029-06-24","Janu dienu","LV",2029 +"2029-11-18","Latvijas Republikas proklamesanas diena","LV",2029 +"2029-12-24","Ziemassvetku vakars","LV",2029 +"2029-12-25","Ziemassvetki","LV",2029 +"2029-12-26","Otrie Ziemassvetki","LV",2029 +"2029-12-31","Vecgada vakars","LV",2029 +"2030-01-01","Jaunais gads","LV",2030 +"2030-04-19","Liela Piektdiena","LV",2030 +"2030-04-21","Lieldienas","LV",2030 +"2030-04-22","Otras Lieldienas","LV",2030 +"2030-05-01","Darba svetki","LV",2030 +"2030-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2030 +"2030-06-23","Ligo diena","LV",2030 +"2030-06-24","Janu dienu","LV",2030 +"2030-11-18","Latvijas Republikas proklamesanas diena","LV",2030 +"2030-12-24","Ziemassvetku vakars","LV",2030 +"2030-12-25","Ziemassvetki","LV",2030 +"2030-12-26","Otrie Ziemassvetki","LV",2030 +"2030-12-31","Vecgada vakars","LV",2030 +"2031-01-01","Jaunais gads","LV",2031 +"2031-04-11","Liela Piektdiena","LV",2031 +"2031-04-13","Lieldienas","LV",2031 +"2031-04-14","Otras Lieldienas","LV",2031 +"2031-05-01","Darba svetki","LV",2031 +"2031-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2031 +"2031-06-23","Ligo diena","LV",2031 +"2031-06-24","Janu dienu","LV",2031 +"2031-11-18","Latvijas Republikas proklamesanas diena","LV",2031 +"2031-12-24","Ziemassvetku vakars","LV",2031 +"2031-12-25","Ziemassvetki","LV",2031 +"2031-12-26","Otrie Ziemassvetki","LV",2031 +"2031-12-31","Vecgada vakars","LV",2031 +"2032-01-01","Jaunais gads","LV",2032 +"2032-03-26","Liela Piektdiena","LV",2032 +"2032-03-28","Lieldienas","LV",2032 +"2032-03-29","Otras Lieldienas","LV",2032 +"2032-05-01","Darba svetki","LV",2032 +"2032-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2032 +"2032-06-23","Ligo diena","LV",2032 +"2032-06-24","Janu dienu","LV",2032 +"2032-11-18","Latvijas Republikas proklamesanas diena","LV",2032 +"2032-12-24","Ziemassvetku vakars","LV",2032 +"2032-12-25","Ziemassvetki","LV",2032 +"2032-12-26","Otrie Ziemassvetki","LV",2032 +"2032-12-31","Vecgada vakars","LV",2032 +"2033-01-01","Jaunais gads","LV",2033 +"2033-04-15","Liela Piektdiena","LV",2033 +"2033-04-17","Lieldienas","LV",2033 +"2033-04-18","Otras Lieldienas","LV",2033 +"2033-05-01","Darba svetki","LV",2033 +"2033-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2033 +"2033-06-23","Ligo diena","LV",2033 +"2033-06-24","Janu dienu","LV",2033 +"2033-11-18","Latvijas Republikas proklamesanas diena","LV",2033 +"2033-12-24","Ziemassvetku vakars","LV",2033 +"2033-12-25","Ziemassvetki","LV",2033 +"2033-12-26","Otrie Ziemassvetki","LV",2033 +"2033-12-31","Vecgada vakars","LV",2033 +"2034-01-01","Jaunais gads","LV",2034 +"2034-04-07","Liela Piektdiena","LV",2034 +"2034-04-09","Lieldienas","LV",2034 +"2034-04-10","Otras Lieldienas","LV",2034 +"2034-05-01","Darba svetki","LV",2034 +"2034-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2034 +"2034-06-23","Ligo diena","LV",2034 +"2034-06-24","Janu dienu","LV",2034 +"2034-11-18","Latvijas Republikas proklamesanas diena","LV",2034 +"2034-12-24","Ziemassvetku vakars","LV",2034 +"2034-12-25","Ziemassvetki","LV",2034 +"2034-12-26","Otrie Ziemassvetki","LV",2034 +"2034-12-31","Vecgada vakars","LV",2034 +"2035-01-01","Jaunais gads","LV",2035 +"2035-03-23","Liela Piektdiena","LV",2035 +"2035-03-25","Lieldienas","LV",2035 +"2035-03-26","Otras Lieldienas","LV",2035 +"2035-05-01","Darba svetki","LV",2035 +"2035-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2035 +"2035-06-23","Ligo diena","LV",2035 +"2035-06-24","Janu dienu","LV",2035 +"2035-11-18","Latvijas Republikas proklamesanas diena","LV",2035 +"2035-12-24","Ziemassvetku vakars","LV",2035 +"2035-12-25","Ziemassvetki","LV",2035 +"2035-12-26","Otrie Ziemassvetki","LV",2035 +"2035-12-31","Vecgada vakars","LV",2035 +"2036-01-01","Jaunais gads","LV",2036 +"2036-04-11","Liela Piektdiena","LV",2036 +"2036-04-13","Lieldienas","LV",2036 +"2036-04-14","Otras Lieldienas","LV",2036 +"2036-05-01","Darba svetki","LV",2036 +"2036-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2036 +"2036-06-23","Ligo diena","LV",2036 +"2036-06-24","Janu dienu","LV",2036 +"2036-11-18","Latvijas Republikas proklamesanas diena","LV",2036 +"2036-12-24","Ziemassvetku vakars","LV",2036 +"2036-12-25","Ziemassvetki","LV",2036 +"2036-12-26","Otrie Ziemassvetki","LV",2036 +"2036-12-31","Vecgada vakars","LV",2036 +"2037-01-01","Jaunais gads","LV",2037 +"2037-04-03","Liela Piektdiena","LV",2037 +"2037-04-05","Lieldienas","LV",2037 +"2037-04-06","Otras Lieldienas","LV",2037 +"2037-05-01","Darba svetki","LV",2037 +"2037-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2037 +"2037-06-23","Ligo diena","LV",2037 +"2037-06-24","Janu dienu","LV",2037 +"2037-11-18","Latvijas Republikas proklamesanas diena","LV",2037 +"2037-12-24","Ziemassvetku vakars","LV",2037 +"2037-12-25","Ziemassvetki","LV",2037 +"2037-12-26","Otrie Ziemassvetki","LV",2037 +"2037-12-31","Vecgada vakars","LV",2037 +"2038-01-01","Jaunais gads","LV",2038 +"2038-04-23","Liela Piektdiena","LV",2038 +"2038-04-25","Lieldienas","LV",2038 +"2038-04-26","Otras Lieldienas","LV",2038 +"2038-05-01","Darba svetki","LV",2038 +"2038-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2038 +"2038-06-23","Ligo diena","LV",2038 +"2038-06-24","Janu dienu","LV",2038 +"2038-11-18","Latvijas Republikas proklamesanas diena","LV",2038 +"2038-12-24","Ziemassvetku vakars","LV",2038 +"2038-12-25","Ziemassvetki","LV",2038 +"2038-12-26","Otrie Ziemassvetki","LV",2038 +"2038-12-31","Vecgada vakars","LV",2038 +"2039-01-01","Jaunais gads","LV",2039 +"2039-04-08","Liela Piektdiena","LV",2039 +"2039-04-10","Lieldienas","LV",2039 +"2039-04-11","Otras Lieldienas","LV",2039 +"2039-05-01","Darba svetki","LV",2039 +"2039-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2039 +"2039-06-23","Ligo diena","LV",2039 +"2039-06-24","Janu dienu","LV",2039 +"2039-11-18","Latvijas Republikas proklamesanas diena","LV",2039 +"2039-12-24","Ziemassvetku vakars","LV",2039 +"2039-12-25","Ziemassvetki","LV",2039 +"2039-12-26","Otrie Ziemassvetki","LV",2039 +"2039-12-31","Vecgada vakars","LV",2039 +"2040-01-01","Jaunais gads","LV",2040 +"2040-03-30","Liela Piektdiena","LV",2040 +"2040-04-01","Lieldienas","LV",2040 +"2040-04-02","Otras Lieldienas","LV",2040 +"2040-05-01","Darba svetki","LV",2040 +"2040-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2040 +"2040-06-23","Ligo diena","LV",2040 +"2040-06-24","Janu dienu","LV",2040 +"2040-11-18","Latvijas Republikas proklamesanas diena","LV",2040 +"2040-12-24","Ziemassvetku vakars","LV",2040 +"2040-12-25","Ziemassvetki","LV",2040 +"2040-12-26","Otrie Ziemassvetki","LV",2040 +"2040-12-31","Vecgada vakars","LV",2040 +"2041-01-01","Jaunais gads","LV",2041 +"2041-04-19","Liela Piektdiena","LV",2041 +"2041-04-21","Lieldienas","LV",2041 +"2041-04-22","Otras Lieldienas","LV",2041 +"2041-05-01","Darba svetki","LV",2041 +"2041-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2041 +"2041-06-23","Ligo diena","LV",2041 +"2041-06-24","Janu dienu","LV",2041 +"2041-11-18","Latvijas Republikas proklamesanas diena","LV",2041 +"2041-12-24","Ziemassvetku vakars","LV",2041 +"2041-12-25","Ziemassvetki","LV",2041 +"2041-12-26","Otrie Ziemassvetki","LV",2041 +"2041-12-31","Vecgada vakars","LV",2041 +"2042-01-01","Jaunais gads","LV",2042 +"2042-04-04","Liela Piektdiena","LV",2042 +"2042-04-06","Lieldienas","LV",2042 +"2042-04-07","Otras Lieldienas","LV",2042 +"2042-05-01","Darba svetki","LV",2042 +"2042-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2042 +"2042-06-23","Ligo diena","LV",2042 +"2042-06-24","Janu dienu","LV",2042 +"2042-11-18","Latvijas Republikas proklamesanas diena","LV",2042 +"2042-12-24","Ziemassvetku vakars","LV",2042 +"2042-12-25","Ziemassvetki","LV",2042 +"2042-12-26","Otrie Ziemassvetki","LV",2042 +"2042-12-31","Vecgada vakars","LV",2042 +"2043-01-01","Jaunais gads","LV",2043 +"2043-03-27","Liela Piektdiena","LV",2043 +"2043-03-29","Lieldienas","LV",2043 +"2043-03-30","Otras Lieldienas","LV",2043 +"2043-05-01","Darba svetki","LV",2043 +"2043-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2043 +"2043-06-23","Ligo diena","LV",2043 +"2043-06-24","Janu dienu","LV",2043 +"2043-11-18","Latvijas Republikas proklamesanas diena","LV",2043 +"2043-12-24","Ziemassvetku vakars","LV",2043 +"2043-12-25","Ziemassvetki","LV",2043 +"2043-12-26","Otrie Ziemassvetki","LV",2043 +"2043-12-31","Vecgada vakars","LV",2043 +"2044-01-01","Jaunais gads","LV",2044 +"2044-04-15","Liela Piektdiena","LV",2044 +"2044-04-17","Lieldienas","LV",2044 +"2044-04-18","Otras Lieldienas","LV",2044 +"2044-05-01","Darba svetki","LV",2044 +"2044-05-04","Latvijas Republikas Neatkaribas atjaunosanas diena","LV",2044 +"2044-06-23","Ligo diena","LV",2044 +"2044-06-24","Janu dienu","LV",2044 +"2044-11-18","Latvijas Republikas proklamesanas diena","LV",2044 +"2044-12-24","Ziemassvetku vakars","LV",2044 +"2044-12-25","Ziemassvetki","LV",2044 +"2044-12-26","Otrie Ziemassvetki","LV",2044 +"2044-12-31","Vecgada vakars","LV",2044 +"1995-01-01","Nouvel an - Premier janvier","MA",1995 +"1995-01-11","Commemoration de la presentation du manifeste de l'independance","MA",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","MA",1995 +"1995-03-03","Eid al-Fitr* (*estimated)","MA",1995 +"1995-03-03","Fete du Trone","MA",1995 +"1995-05-01","Fete du Travail","MA",1995 +"1995-05-09","Eid al-Adha* (*estimated)","MA",1995 +"1995-05-10","Eid al-Adha* (*estimated)","MA",1995 +"1995-05-30","1er Moharram* (*estimated)","MA",1995 +"1995-07-09","Fete du Trone","MA",1995 +"1995-08-08","Aid al Mawlid Annabawi* (*estimated)","MA",1995 +"1995-08-09","Aid al Mawlid Annabawi* (*estimated)","MA",1995 +"1995-08-14","Journee de Oued Ed-Dahab","MA",1995 +"1995-08-20","Commemoration de la revolution du Roi et du peuple","MA",1995 +"1995-11-06","Marche verte","MA",1995 +"1995-11-18","Fete de l'independance","MA",1995 +"1996-01-01","Nouvel an - Premier janvier","MA",1996 +"1996-01-11","Commemoration de la presentation du manifeste de l'independance","MA",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","MA",1996 +"1996-02-20","Eid al-Fitr* (*estimated)","MA",1996 +"1996-03-03","Fete du Trone","MA",1996 +"1996-04-27","Eid al-Adha* (*estimated)","MA",1996 +"1996-04-28","Eid al-Adha* (*estimated)","MA",1996 +"1996-05-01","Fete du Travail","MA",1996 +"1996-05-18","1er Moharram* (*estimated)","MA",1996 +"1996-07-09","Fete du Trone","MA",1996 +"1996-07-27","Aid al Mawlid Annabawi* (*estimated)","MA",1996 +"1996-07-28","Aid al Mawlid Annabawi* (*estimated)","MA",1996 +"1996-08-14","Journee de Oued Ed-Dahab","MA",1996 +"1996-08-20","Commemoration de la revolution du Roi et du peuple","MA",1996 +"1996-11-06","Marche verte","MA",1996 +"1996-11-18","Fete de l'independance","MA",1996 +"1997-01-01","Nouvel an - Premier janvier","MA",1997 +"1997-01-11","Commemoration de la presentation du manifeste de l'independance","MA",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","MA",1997 +"1997-02-09","Eid al-Fitr* (*estimated)","MA",1997 +"1997-03-03","Fete du Trone","MA",1997 +"1997-04-17","Eid al-Adha* (*estimated)","MA",1997 +"1997-04-18","Eid al-Adha* (*estimated)","MA",1997 +"1997-05-01","Fete du Travail","MA",1997 +"1997-05-07","1er Moharram* (*estimated)","MA",1997 +"1997-07-09","Fete du Trone","MA",1997 +"1997-07-16","Aid al Mawlid Annabawi* (*estimated)","MA",1997 +"1997-07-17","Aid al Mawlid Annabawi* (*estimated)","MA",1997 +"1997-08-14","Journee de Oued Ed-Dahab","MA",1997 +"1997-08-20","Commemoration de la revolution du Roi et du peuple","MA",1997 +"1997-11-06","Marche verte","MA",1997 +"1997-11-18","Fete de l'independance","MA",1997 +"1998-01-01","Nouvel an - Premier janvier","MA",1998 +"1998-01-11","Commemoration de la presentation du manifeste de l'independance","MA",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","MA",1998 +"1998-01-30","Eid al-Fitr* (*estimated)","MA",1998 +"1998-03-03","Fete du Trone","MA",1998 +"1998-04-07","Eid al-Adha* (*estimated)","MA",1998 +"1998-04-08","Eid al-Adha* (*estimated)","MA",1998 +"1998-04-27","1er Moharram* (*estimated)","MA",1998 +"1998-05-01","Fete du Travail","MA",1998 +"1998-07-06","Aid al Mawlid Annabawi* (*estimated)","MA",1998 +"1998-07-07","Aid al Mawlid Annabawi* (*estimated)","MA",1998 +"1998-07-09","Fete du Trone","MA",1998 +"1998-08-14","Journee de Oued Ed-Dahab","MA",1998 +"1998-08-20","Commemoration de la revolution du Roi et du peuple","MA",1998 +"1998-11-06","Marche verte","MA",1998 +"1998-11-18","Fete de l'independance","MA",1998 +"1999-01-01","Nouvel an - Premier janvier","MA",1999 +"1999-01-11","Commemoration de la presentation du manifeste de l'independance","MA",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","MA",1999 +"1999-01-19","Eid al-Fitr* (*estimated)","MA",1999 +"1999-03-03","Fete du Trone","MA",1999 +"1999-03-27","Eid al-Adha* (*estimated)","MA",1999 +"1999-03-28","Eid al-Adha* (*estimated)","MA",1999 +"1999-04-17","1er Moharram* (*estimated)","MA",1999 +"1999-05-01","Fete du Travail","MA",1999 +"1999-06-26","Aid al Mawlid Annabawi* (*estimated)","MA",1999 +"1999-06-27","Aid al Mawlid Annabawi* (*estimated)","MA",1999 +"1999-07-09","Fete du Trone","MA",1999 +"1999-08-14","Journee de Oued Ed-Dahab","MA",1999 +"1999-08-20","Commemoration de la revolution du Roi et du peuple","MA",1999 +"1999-11-06","Marche verte","MA",1999 +"1999-11-18","Fete de l'independance","MA",1999 +"2000-01-01","Nouvel an - Premier janvier","MA",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","MA",2000 +"2000-01-09","Eid al-Fitr* (*estimated)","MA",2000 +"2000-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2000 +"2000-03-03","Fete du Trone","MA",2000 +"2000-03-16","Eid al-Adha* (*estimated)","MA",2000 +"2000-03-17","Eid al-Adha* (*estimated)","MA",2000 +"2000-04-06","1er Moharram* (*estimated)","MA",2000 +"2000-05-01","Fete du Travail","MA",2000 +"2000-06-14","Aid al Mawlid Annabawi* (*estimated)","MA",2000 +"2000-06-15","Aid al Mawlid Annabawi* (*estimated)","MA",2000 +"2000-07-09","Fete du Trone","MA",2000 +"2000-08-14","Journee de Oued Ed-Dahab","MA",2000 +"2000-08-20","Commemoration de la revolution du Roi et du peuple","MA",2000 +"2000-11-06","Marche verte","MA",2000 +"2000-11-18","Fete de l'independance","MA",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","MA",2000 +"2000-12-28","Eid al-Fitr* (*estimated)","MA",2000 +"2001-01-01","Nouvel an - Premier janvier","MA",2001 +"2001-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2001 +"2001-03-05","Eid al-Adha* (*estimated)","MA",2001 +"2001-03-06","Eid al-Adha* (*estimated)","MA",2001 +"2001-03-26","1er Moharram* (*estimated)","MA",2001 +"2001-05-01","Fete du Travail","MA",2001 +"2001-06-04","Aid al Mawlid Annabawi* (*estimated)","MA",2001 +"2001-06-05","Aid al Mawlid Annabawi* (*estimated)","MA",2001 +"2001-07-30","Fete du Trone","MA",2001 +"2001-08-14","Journee de Oued Ed-Dahab","MA",2001 +"2001-08-20","Commemoration de la revolution du Roi et du peuple","MA",2001 +"2001-08-21","Fete de la jeunesse","MA",2001 +"2001-11-06","Marche verte","MA",2001 +"2001-11-18","Fete de l'independance","MA",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","MA",2001 +"2001-12-17","Eid al-Fitr* (*estimated)","MA",2001 +"2002-01-01","Nouvel an - Premier janvier","MA",2002 +"2002-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2002 +"2002-02-22","Eid al-Adha* (*estimated)","MA",2002 +"2002-02-23","Eid al-Adha* (*estimated)","MA",2002 +"2002-03-15","1er Moharram* (*estimated)","MA",2002 +"2002-05-01","Fete du Travail","MA",2002 +"2002-05-24","Aid al Mawlid Annabawi* (*estimated)","MA",2002 +"2002-05-25","Aid al Mawlid Annabawi* (*estimated)","MA",2002 +"2002-07-30","Fete du Trone","MA",2002 +"2002-08-14","Journee de Oued Ed-Dahab","MA",2002 +"2002-08-20","Commemoration de la revolution du Roi et du peuple","MA",2002 +"2002-08-21","Fete de la jeunesse","MA",2002 +"2002-11-06","Marche verte","MA",2002 +"2002-11-18","Fete de l'independance","MA",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","MA",2002 +"2002-12-06","Eid al-Fitr* (*estimated)","MA",2002 +"2003-01-01","Nouvel an - Premier janvier","MA",2003 +"2003-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2003 +"2003-02-11","Eid al-Adha* (*estimated)","MA",2003 +"2003-02-12","Eid al-Adha* (*estimated)","MA",2003 +"2003-03-04","1er Moharram* (*estimated)","MA",2003 +"2003-05-01","Fete du Travail","MA",2003 +"2003-05-13","Aid al Mawlid Annabawi* (*estimated)","MA",2003 +"2003-05-14","Aid al Mawlid Annabawi* (*estimated)","MA",2003 +"2003-07-30","Fete du Trone","MA",2003 +"2003-08-14","Journee de Oued Ed-Dahab","MA",2003 +"2003-08-20","Commemoration de la revolution du Roi et du peuple","MA",2003 +"2003-08-21","Fete de la jeunesse","MA",2003 +"2003-11-06","Marche verte","MA",2003 +"2003-11-18","Fete de l'independance","MA",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","MA",2003 +"2003-11-26","Eid al-Fitr* (*estimated)","MA",2003 +"2004-01-01","Nouvel an - Premier janvier","MA",2004 +"2004-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2004 +"2004-02-01","Eid al-Adha* (*estimated)","MA",2004 +"2004-02-02","Eid al-Adha* (*estimated)","MA",2004 +"2004-02-21","1er Moharram* (*estimated)","MA",2004 +"2004-05-01","Aid al Mawlid Annabawi* (*estimated)","MA",2004 +"2004-05-01","Fete du Travail","MA",2004 +"2004-05-02","Aid al Mawlid Annabawi* (*estimated)","MA",2004 +"2004-07-30","Fete du Trone","MA",2004 +"2004-08-14","Journee de Oued Ed-Dahab","MA",2004 +"2004-08-20","Commemoration de la revolution du Roi et du peuple","MA",2004 +"2004-08-21","Fete de la jeunesse","MA",2004 +"2004-11-06","Marche verte","MA",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","MA",2004 +"2004-11-15","Eid al-Fitr* (*estimated)","MA",2004 +"2004-11-18","Fete de l'independance","MA",2004 +"2005-01-01","Nouvel an - Premier janvier","MA",2005 +"2005-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2005 +"2005-01-21","Eid al-Adha* (*estimated)","MA",2005 +"2005-01-22","Eid al-Adha* (*estimated)","MA",2005 +"2005-02-10","1er Moharram* (*estimated)","MA",2005 +"2005-04-21","Aid al Mawlid Annabawi* (*estimated)","MA",2005 +"2005-04-22","Aid al Mawlid Annabawi* (*estimated)","MA",2005 +"2005-05-01","Fete du Travail","MA",2005 +"2005-07-30","Fete du Trone","MA",2005 +"2005-08-14","Journee de Oued Ed-Dahab","MA",2005 +"2005-08-20","Commemoration de la revolution du Roi et du peuple","MA",2005 +"2005-08-21","Fete de la jeunesse","MA",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","MA",2005 +"2005-11-04","Eid al-Fitr* (*estimated)","MA",2005 +"2005-11-06","Marche verte","MA",2005 +"2005-11-18","Fete de l'independance","MA",2005 +"2006-01-01","Nouvel an - Premier janvier","MA",2006 +"2006-01-10","Eid al-Adha* (*estimated)","MA",2006 +"2006-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2006 +"2006-01-11","Eid al-Adha* (*estimated)","MA",2006 +"2006-01-31","1er Moharram* (*estimated)","MA",2006 +"2006-04-10","Aid al Mawlid Annabawi* (*estimated)","MA",2006 +"2006-04-11","Aid al Mawlid Annabawi* (*estimated)","MA",2006 +"2006-05-01","Fete du Travail","MA",2006 +"2006-07-30","Fete du Trone","MA",2006 +"2006-08-14","Journee de Oued Ed-Dahab","MA",2006 +"2006-08-20","Commemoration de la revolution du Roi et du peuple","MA",2006 +"2006-08-21","Fete de la jeunesse","MA",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","MA",2006 +"2006-10-24","Eid al-Fitr* (*estimated)","MA",2006 +"2006-11-06","Marche verte","MA",2006 +"2006-11-18","Fete de l'independance","MA",2006 +"2006-12-31","Eid al-Adha* (*estimated)","MA",2006 +"2007-01-01","Eid al-Adha* (*estimated)","MA",2007 +"2007-01-01","Nouvel an - Premier janvier","MA",2007 +"2007-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2007 +"2007-01-20","1er Moharram* (*estimated)","MA",2007 +"2007-03-31","Aid al Mawlid Annabawi* (*estimated)","MA",2007 +"2007-04-01","Aid al Mawlid Annabawi* (*estimated)","MA",2007 +"2007-05-01","Fete du Travail","MA",2007 +"2007-07-30","Fete du Trone","MA",2007 +"2007-08-14","Journee de Oued Ed-Dahab","MA",2007 +"2007-08-20","Commemoration de la revolution du Roi et du peuple","MA",2007 +"2007-08-21","Fete de la jeunesse","MA",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","MA",2007 +"2007-10-14","Eid al-Fitr* (*estimated)","MA",2007 +"2007-11-06","Marche verte","MA",2007 +"2007-11-18","Fete de l'independance","MA",2007 +"2007-12-20","Eid al-Adha* (*estimated)","MA",2007 +"2007-12-21","Eid al-Adha* (*estimated)","MA",2007 +"2008-01-01","Nouvel an - Premier janvier","MA",2008 +"2008-01-10","1er Moharram* (*estimated)","MA",2008 +"2008-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2008 +"2008-03-20","Aid al Mawlid Annabawi* (*estimated)","MA",2008 +"2008-03-21","Aid al Mawlid Annabawi* (*estimated)","MA",2008 +"2008-05-01","Fete du Travail","MA",2008 +"2008-07-30","Fete du Trone","MA",2008 +"2008-08-14","Journee de Oued Ed-Dahab","MA",2008 +"2008-08-20","Commemoration de la revolution du Roi et du peuple","MA",2008 +"2008-08-21","Fete de la jeunesse","MA",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","MA",2008 +"2008-10-02","Eid al-Fitr* (*estimated)","MA",2008 +"2008-11-06","Marche verte","MA",2008 +"2008-11-18","Fete de l'independance","MA",2008 +"2008-12-08","Eid al-Adha* (*estimated)","MA",2008 +"2008-12-09","Eid al-Adha* (*estimated)","MA",2008 +"2008-12-29","1er Moharram* (*estimated)","MA",2008 +"2009-01-01","Nouvel an - Premier janvier","MA",2009 +"2009-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2009 +"2009-03-09","Aid al Mawlid Annabawi* (*estimated)","MA",2009 +"2009-03-10","Aid al Mawlid Annabawi* (*estimated)","MA",2009 +"2009-05-01","Fete du Travail","MA",2009 +"2009-07-30","Fete du Trone","MA",2009 +"2009-08-14","Journee de Oued Ed-Dahab","MA",2009 +"2009-08-20","Commemoration de la revolution du Roi et du peuple","MA",2009 +"2009-08-21","Fete de la jeunesse","MA",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","MA",2009 +"2009-09-21","Eid al-Fitr* (*estimated)","MA",2009 +"2009-11-06","Marche verte","MA",2009 +"2009-11-18","Fete de l'independance","MA",2009 +"2009-11-27","Eid al-Adha* (*estimated)","MA",2009 +"2009-11-28","Eid al-Adha* (*estimated)","MA",2009 +"2009-12-18","1er Moharram* (*estimated)","MA",2009 +"2010-01-01","Nouvel an - Premier janvier","MA",2010 +"2010-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2010 +"2010-02-26","Aid al Mawlid Annabawi* (*estimated)","MA",2010 +"2010-02-27","Aid al Mawlid Annabawi* (*estimated)","MA",2010 +"2010-05-01","Fete du Travail","MA",2010 +"2010-07-30","Fete du Trone","MA",2010 +"2010-08-14","Journee de Oued Ed-Dahab","MA",2010 +"2010-08-20","Commemoration de la revolution du Roi et du peuple","MA",2010 +"2010-08-21","Fete de la jeunesse","MA",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","MA",2010 +"2010-09-11","Eid al-Fitr* (*estimated)","MA",2010 +"2010-11-06","Marche verte","MA",2010 +"2010-11-16","Eid al-Adha* (*estimated)","MA",2010 +"2010-11-17","Eid al-Adha* (*estimated)","MA",2010 +"2010-11-18","Fete de l'independance","MA",2010 +"2010-12-07","1er Moharram* (*estimated)","MA",2010 +"2011-01-01","Nouvel an - Premier janvier","MA",2011 +"2011-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2011 +"2011-02-15","Aid al Mawlid Annabawi* (*estimated)","MA",2011 +"2011-02-16","Aid al Mawlid Annabawi* (*estimated)","MA",2011 +"2011-05-01","Fete du Travail","MA",2011 +"2011-07-30","Fete du Trone","MA",2011 +"2011-08-14","Journee de Oued Ed-Dahab","MA",2011 +"2011-08-20","Commemoration de la revolution du Roi et du peuple","MA",2011 +"2011-08-21","Fete de la jeunesse","MA",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","MA",2011 +"2011-08-31","Eid al-Fitr* (*estimated)","MA",2011 +"2011-11-06","Eid al-Adha* (*estimated)","MA",2011 +"2011-11-06","Marche verte","MA",2011 +"2011-11-07","Eid al-Adha* (*estimated)","MA",2011 +"2011-11-18","Fete de l'independance","MA",2011 +"2011-11-26","1er Moharram* (*estimated)","MA",2011 +"2012-01-01","Nouvel an - Premier janvier","MA",2012 +"2012-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2012 +"2012-02-04","Aid al Mawlid Annabawi* (*estimated)","MA",2012 +"2012-02-05","Aid al Mawlid Annabawi* (*estimated)","MA",2012 +"2012-05-01","Fete du Travail","MA",2012 +"2012-07-30","Fete du Trone","MA",2012 +"2012-08-14","Journee de Oued Ed-Dahab","MA",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","MA",2012 +"2012-08-20","Commemoration de la revolution du Roi et du peuple","MA",2012 +"2012-08-20","Eid al-Fitr* (*estimated)","MA",2012 +"2012-08-21","Fete de la jeunesse","MA",2012 +"2012-10-26","Eid al-Adha* (*estimated)","MA",2012 +"2012-10-27","Eid al-Adha* (*estimated)","MA",2012 +"2012-11-06","Marche verte","MA",2012 +"2012-11-15","1er Moharram* (*estimated)","MA",2012 +"2012-11-18","Fete de l'independance","MA",2012 +"2013-01-01","Nouvel an - Premier janvier","MA",2013 +"2013-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2013 +"2013-01-24","Aid al Mawlid Annabawi* (*estimated)","MA",2013 +"2013-01-25","Aid al Mawlid Annabawi* (*estimated)","MA",2013 +"2013-05-01","Fete du Travail","MA",2013 +"2013-07-30","Fete du Trone","MA",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","MA",2013 +"2013-08-09","Eid al-Fitr* (*estimated)","MA",2013 +"2013-08-14","Journee de Oued Ed-Dahab","MA",2013 +"2013-08-20","Commemoration de la revolution du Roi et du peuple","MA",2013 +"2013-08-21","Fete de la jeunesse","MA",2013 +"2013-10-15","Eid al-Adha* (*estimated)","MA",2013 +"2013-10-16","Eid al-Adha* (*estimated)","MA",2013 +"2013-11-04","1er Moharram* (*estimated)","MA",2013 +"2013-11-06","Marche verte","MA",2013 +"2013-11-18","Fete de l'independance","MA",2013 +"2014-01-01","Nouvel an - Premier janvier","MA",2014 +"2014-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2014 +"2014-01-13","Aid al Mawlid Annabawi* (*estimated)","MA",2014 +"2014-01-14","Aid al Mawlid Annabawi* (*estimated)","MA",2014 +"2014-05-01","Fete du Travail","MA",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","MA",2014 +"2014-07-29","Eid al-Fitr* (*estimated)","MA",2014 +"2014-07-30","Fete du Trone","MA",2014 +"2014-08-14","Journee de Oued Ed-Dahab","MA",2014 +"2014-08-20","Commemoration de la revolution du Roi et du peuple","MA",2014 +"2014-08-21","Fete de la jeunesse","MA",2014 +"2014-10-04","Eid al-Adha* (*estimated)","MA",2014 +"2014-10-05","Eid al-Adha* (*estimated)","MA",2014 +"2014-10-25","1er Moharram* (*estimated)","MA",2014 +"2014-11-06","Marche verte","MA",2014 +"2014-11-18","Fete de l'independance","MA",2014 +"2015-01-01","Nouvel an - Premier janvier","MA",2015 +"2015-01-03","Aid al Mawlid Annabawi* (*estimated)","MA",2015 +"2015-01-04","Aid al Mawlid Annabawi* (*estimated)","MA",2015 +"2015-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2015 +"2015-05-01","Fete du Travail","MA",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","MA",2015 +"2015-07-18","Eid al-Fitr* (*estimated)","MA",2015 +"2015-07-30","Fete du Trone","MA",2015 +"2015-08-14","Journee de Oued Ed-Dahab","MA",2015 +"2015-08-20","Commemoration de la revolution du Roi et du peuple","MA",2015 +"2015-08-21","Fete de la jeunesse","MA",2015 +"2015-09-23","Eid al-Adha* (*estimated)","MA",2015 +"2015-09-24","Eid al-Adha* (*estimated)","MA",2015 +"2015-10-14","1er Moharram* (*estimated)","MA",2015 +"2015-11-06","Marche verte","MA",2015 +"2015-11-18","Fete de l'independance","MA",2015 +"2015-12-23","Aid al Mawlid Annabawi* (*estimated)","MA",2015 +"2015-12-24","Aid al Mawlid Annabawi* (*estimated)","MA",2015 +"2016-01-01","Nouvel an - Premier janvier","MA",2016 +"2016-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2016 +"2016-05-01","Fete du Travail","MA",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","MA",2016 +"2016-07-07","Eid al-Fitr* (*estimated)","MA",2016 +"2016-07-30","Fete du Trone","MA",2016 +"2016-08-14","Journee de Oued Ed-Dahab","MA",2016 +"2016-08-20","Commemoration de la revolution du Roi et du peuple","MA",2016 +"2016-08-21","Fete de la jeunesse","MA",2016 +"2016-09-11","Eid al-Adha* (*estimated)","MA",2016 +"2016-09-12","Eid al-Adha* (*estimated)","MA",2016 +"2016-10-02","1er Moharram* (*estimated)","MA",2016 +"2016-11-06","Marche verte","MA",2016 +"2016-11-18","Fete de l'independance","MA",2016 +"2016-12-11","Aid al Mawlid Annabawi* (*estimated)","MA",2016 +"2016-12-12","Aid al Mawlid Annabawi* (*estimated)","MA",2016 +"2017-01-01","Nouvel an - Premier janvier","MA",2017 +"2017-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2017 +"2017-05-01","Fete du Travail","MA",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","MA",2017 +"2017-06-26","Eid al-Fitr* (*estimated)","MA",2017 +"2017-07-30","Fete du Trone","MA",2017 +"2017-08-14","Journee de Oued Ed-Dahab","MA",2017 +"2017-08-20","Commemoration de la revolution du Roi et du peuple","MA",2017 +"2017-08-21","Fete de la jeunesse","MA",2017 +"2017-09-01","Eid al-Adha* (*estimated)","MA",2017 +"2017-09-02","Eid al-Adha* (*estimated)","MA",2017 +"2017-09-21","1er Moharram* (*estimated)","MA",2017 +"2017-11-06","Marche verte","MA",2017 +"2017-11-18","Fete de l'independance","MA",2017 +"2017-11-30","Aid al Mawlid Annabawi* (*estimated)","MA",2017 +"2017-12-01","Aid al Mawlid Annabawi* (*estimated)","MA",2017 +"2018-01-01","Nouvel an - Premier janvier","MA",2018 +"2018-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2018 +"2018-05-01","Fete du Travail","MA",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","MA",2018 +"2018-06-16","Eid al-Fitr* (*estimated)","MA",2018 +"2018-07-30","Fete du Trone","MA",2018 +"2018-08-14","Journee de Oued Ed-Dahab","MA",2018 +"2018-08-20","Commemoration de la revolution du Roi et du peuple","MA",2018 +"2018-08-21","Eid al-Adha* (*estimated)","MA",2018 +"2018-08-21","Fete de la jeunesse","MA",2018 +"2018-08-22","Eid al-Adha* (*estimated)","MA",2018 +"2018-09-11","1er Moharram* (*estimated)","MA",2018 +"2018-11-06","Marche verte","MA",2018 +"2018-11-18","Fete de l'independance","MA",2018 +"2018-11-20","Aid al Mawlid Annabawi* (*estimated)","MA",2018 +"2018-11-21","Aid al Mawlid Annabawi* (*estimated)","MA",2018 +"2019-01-01","Nouvel an - Premier janvier","MA",2019 +"2019-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2019 +"2019-05-01","Fete du Travail","MA",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","MA",2019 +"2019-06-05","Eid al-Fitr* (*estimated)","MA",2019 +"2019-07-30","Fete du Trone","MA",2019 +"2019-08-11","Eid al-Adha* (*estimated)","MA",2019 +"2019-08-12","Eid al-Adha* (*estimated)","MA",2019 +"2019-08-14","Journee de Oued Ed-Dahab","MA",2019 +"2019-08-20","Commemoration de la revolution du Roi et du peuple","MA",2019 +"2019-08-21","Fete de la jeunesse","MA",2019 +"2019-08-31","1er Moharram* (*estimated)","MA",2019 +"2019-11-06","Marche verte","MA",2019 +"2019-11-09","Aid al Mawlid Annabawi* (*estimated)","MA",2019 +"2019-11-10","Aid al Mawlid Annabawi* (*estimated)","MA",2019 +"2019-11-18","Fete de l'independance","MA",2019 +"2020-01-01","Nouvel an - Premier janvier","MA",2020 +"2020-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2020 +"2020-05-01","Fete du Travail","MA",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","MA",2020 +"2020-05-25","Eid al-Fitr* (*estimated)","MA",2020 +"2020-07-30","Fete du Trone","MA",2020 +"2020-07-31","Eid al-Adha* (*estimated)","MA",2020 +"2020-08-01","Eid al-Adha* (*estimated)","MA",2020 +"2020-08-14","Journee de Oued Ed-Dahab","MA",2020 +"2020-08-20","1er Moharram* (*estimated)","MA",2020 +"2020-08-20","Commemoration de la revolution du Roi et du peuple","MA",2020 +"2020-08-21","Fete de la jeunesse","MA",2020 +"2020-10-29","Aid al Mawlid Annabawi* (*estimated)","MA",2020 +"2020-10-30","Aid al Mawlid Annabawi* (*estimated)","MA",2020 +"2020-11-06","Marche verte","MA",2020 +"2020-11-18","Fete de l'independance","MA",2020 +"2021-01-01","Nouvel an - Premier janvier","MA",2021 +"2021-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2021 +"2021-05-01","Fete du Travail","MA",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","MA",2021 +"2021-05-14","Eid al-Fitr* (*estimated)","MA",2021 +"2021-07-20","Eid al-Adha* (*estimated)","MA",2021 +"2021-07-21","Eid al-Adha* (*estimated)","MA",2021 +"2021-07-30","Fete du Trone","MA",2021 +"2021-08-09","1er Moharram* (*estimated)","MA",2021 +"2021-08-14","Journee de Oued Ed-Dahab","MA",2021 +"2021-08-20","Commemoration de la revolution du Roi et du peuple","MA",2021 +"2021-08-21","Fete de la jeunesse","MA",2021 +"2021-10-18","Aid al Mawlid Annabawi* (*estimated)","MA",2021 +"2021-10-19","Aid al Mawlid Annabawi* (*estimated)","MA",2021 +"2021-11-06","Marche verte","MA",2021 +"2021-11-18","Fete de l'independance","MA",2021 +"2022-01-01","Nouvel an - Premier janvier","MA",2022 +"2022-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2022 +"2022-05-01","Fete du Travail","MA",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","MA",2022 +"2022-05-03","Eid al-Fitr* (*estimated)","MA",2022 +"2022-07-09","Eid al-Adha* (*estimated)","MA",2022 +"2022-07-10","Eid al-Adha* (*estimated)","MA",2022 +"2022-07-30","1er Moharram* (*estimated)","MA",2022 +"2022-07-30","Fete du Trone","MA",2022 +"2022-08-14","Journee de Oued Ed-Dahab","MA",2022 +"2022-08-20","Commemoration de la revolution du Roi et du peuple","MA",2022 +"2022-08-21","Fete de la jeunesse","MA",2022 +"2022-10-08","Aid al Mawlid Annabawi* (*estimated)","MA",2022 +"2022-10-09","Aid al Mawlid Annabawi* (*estimated)","MA",2022 +"2022-11-06","Marche verte","MA",2022 +"2022-11-18","Fete de l'independance","MA",2022 +"2023-01-01","Nouvel an - Premier janvier","MA",2023 +"2023-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","MA",2023 +"2023-04-22","Eid al-Fitr* (*estimated)","MA",2023 +"2023-05-01","Fete du Travail","MA",2023 +"2023-06-28","Eid al-Adha* (*estimated)","MA",2023 +"2023-06-29","Eid al-Adha* (*estimated)","MA",2023 +"2023-07-19","1er Moharram* (*estimated)","MA",2023 +"2023-07-30","Fete du Trone","MA",2023 +"2023-08-14","Journee de Oued Ed-Dahab","MA",2023 +"2023-08-20","Commemoration de la revolution du Roi et du peuple","MA",2023 +"2023-08-21","Fete de la jeunesse","MA",2023 +"2023-09-27","Aid al Mawlid Annabawi* (*estimated)","MA",2023 +"2023-09-28","Aid al Mawlid Annabawi* (*estimated)","MA",2023 +"2023-11-06","Marche verte","MA",2023 +"2023-11-18","Fete de l'independance","MA",2023 +"2024-01-01","Nouvel an - Premier janvier","MA",2024 +"2024-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","MA",2024 +"2024-04-11","Eid al-Fitr* (*estimated)","MA",2024 +"2024-05-01","Fete du Travail","MA",2024 +"2024-06-16","Eid al-Adha* (*estimated)","MA",2024 +"2024-06-17","Eid al-Adha* (*estimated)","MA",2024 +"2024-07-07","1er Moharram* (*estimated)","MA",2024 +"2024-07-30","Fete du Trone","MA",2024 +"2024-08-14","Journee de Oued Ed-Dahab","MA",2024 +"2024-08-20","Commemoration de la revolution du Roi et du peuple","MA",2024 +"2024-08-21","Fete de la jeunesse","MA",2024 +"2024-09-15","Aid al Mawlid Annabawi* (*estimated)","MA",2024 +"2024-09-16","Aid al Mawlid Annabawi* (*estimated)","MA",2024 +"2024-11-06","Marche verte","MA",2024 +"2024-11-18","Fete de l'independance","MA",2024 +"2025-01-01","Nouvel an - Premier janvier","MA",2025 +"2025-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","MA",2025 +"2025-03-31","Eid al-Fitr* (*estimated)","MA",2025 +"2025-05-01","Fete du Travail","MA",2025 +"2025-06-06","Eid al-Adha* (*estimated)","MA",2025 +"2025-06-07","Eid al-Adha* (*estimated)","MA",2025 +"2025-06-26","1er Moharram* (*estimated)","MA",2025 +"2025-07-30","Fete du Trone","MA",2025 +"2025-08-14","Journee de Oued Ed-Dahab","MA",2025 +"2025-08-20","Commemoration de la revolution du Roi et du peuple","MA",2025 +"2025-08-21","Fete de la jeunesse","MA",2025 +"2025-09-04","Aid al Mawlid Annabawi* (*estimated)","MA",2025 +"2025-09-05","Aid al Mawlid Annabawi* (*estimated)","MA",2025 +"2025-11-06","Marche verte","MA",2025 +"2025-11-18","Fete de l'independance","MA",2025 +"2026-01-01","Nouvel an - Premier janvier","MA",2026 +"2026-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","MA",2026 +"2026-03-21","Eid al-Fitr* (*estimated)","MA",2026 +"2026-05-01","Fete du Travail","MA",2026 +"2026-05-27","Eid al-Adha* (*estimated)","MA",2026 +"2026-05-28","Eid al-Adha* (*estimated)","MA",2026 +"2026-06-16","1er Moharram* (*estimated)","MA",2026 +"2026-07-30","Fete du Trone","MA",2026 +"2026-08-14","Journee de Oued Ed-Dahab","MA",2026 +"2026-08-20","Commemoration de la revolution du Roi et du peuple","MA",2026 +"2026-08-21","Fete de la jeunesse","MA",2026 +"2026-08-25","Aid al Mawlid Annabawi* (*estimated)","MA",2026 +"2026-08-26","Aid al Mawlid Annabawi* (*estimated)","MA",2026 +"2026-11-06","Marche verte","MA",2026 +"2026-11-18","Fete de l'independance","MA",2026 +"2027-01-01","Nouvel an - Premier janvier","MA",2027 +"2027-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","MA",2027 +"2027-03-10","Eid al-Fitr* (*estimated)","MA",2027 +"2027-05-01","Fete du Travail","MA",2027 +"2027-05-16","Eid al-Adha* (*estimated)","MA",2027 +"2027-05-17","Eid al-Adha* (*estimated)","MA",2027 +"2027-06-06","1er Moharram* (*estimated)","MA",2027 +"2027-07-30","Fete du Trone","MA",2027 +"2027-08-14","Aid al Mawlid Annabawi* (*estimated)","MA",2027 +"2027-08-14","Journee de Oued Ed-Dahab","MA",2027 +"2027-08-15","Aid al Mawlid Annabawi* (*estimated)","MA",2027 +"2027-08-20","Commemoration de la revolution du Roi et du peuple","MA",2027 +"2027-08-21","Fete de la jeunesse","MA",2027 +"2027-11-06","Marche verte","MA",2027 +"2027-11-18","Fete de l'independance","MA",2027 +"2028-01-01","Nouvel an - Premier janvier","MA",2028 +"2028-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","MA",2028 +"2028-02-27","Eid al-Fitr* (*estimated)","MA",2028 +"2028-05-01","Fete du Travail","MA",2028 +"2028-05-05","Eid al-Adha* (*estimated)","MA",2028 +"2028-05-06","Eid al-Adha* (*estimated)","MA",2028 +"2028-05-25","1er Moharram* (*estimated)","MA",2028 +"2028-07-30","Fete du Trone","MA",2028 +"2028-08-03","Aid al Mawlid Annabawi* (*estimated)","MA",2028 +"2028-08-04","Aid al Mawlid Annabawi* (*estimated)","MA",2028 +"2028-08-14","Journee de Oued Ed-Dahab","MA",2028 +"2028-08-20","Commemoration de la revolution du Roi et du peuple","MA",2028 +"2028-08-21","Fete de la jeunesse","MA",2028 +"2028-11-06","Marche verte","MA",2028 +"2028-11-18","Fete de l'independance","MA",2028 +"2029-01-01","Nouvel an - Premier janvier","MA",2029 +"2029-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","MA",2029 +"2029-02-15","Eid al-Fitr* (*estimated)","MA",2029 +"2029-04-24","Eid al-Adha* (*estimated)","MA",2029 +"2029-04-25","Eid al-Adha* (*estimated)","MA",2029 +"2029-05-01","Fete du Travail","MA",2029 +"2029-05-14","1er Moharram* (*estimated)","MA",2029 +"2029-07-24","Aid al Mawlid Annabawi* (*estimated)","MA",2029 +"2029-07-25","Aid al Mawlid Annabawi* (*estimated)","MA",2029 +"2029-07-30","Fete du Trone","MA",2029 +"2029-08-14","Journee de Oued Ed-Dahab","MA",2029 +"2029-08-20","Commemoration de la revolution du Roi et du peuple","MA",2029 +"2029-08-21","Fete de la jeunesse","MA",2029 +"2029-11-06","Marche verte","MA",2029 +"2029-11-18","Fete de l'independance","MA",2029 +"2030-01-01","Nouvel an - Premier janvier","MA",2030 +"2030-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","MA",2030 +"2030-02-05","Eid al-Fitr* (*estimated)","MA",2030 +"2030-04-13","Eid al-Adha* (*estimated)","MA",2030 +"2030-04-14","Eid al-Adha* (*estimated)","MA",2030 +"2030-05-01","Fete du Travail","MA",2030 +"2030-05-03","1er Moharram* (*estimated)","MA",2030 +"2030-07-13","Aid al Mawlid Annabawi* (*estimated)","MA",2030 +"2030-07-14","Aid al Mawlid Annabawi* (*estimated)","MA",2030 +"2030-07-30","Fete du Trone","MA",2030 +"2030-08-14","Journee de Oued Ed-Dahab","MA",2030 +"2030-08-20","Commemoration de la revolution du Roi et du peuple","MA",2030 +"2030-08-21","Fete de la jeunesse","MA",2030 +"2030-11-06","Marche verte","MA",2030 +"2030-11-18","Fete de l'independance","MA",2030 +"2031-01-01","Nouvel an - Premier janvier","MA",2031 +"2031-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","MA",2031 +"2031-01-25","Eid al-Fitr* (*estimated)","MA",2031 +"2031-04-02","Eid al-Adha* (*estimated)","MA",2031 +"2031-04-03","Eid al-Adha* (*estimated)","MA",2031 +"2031-04-23","1er Moharram* (*estimated)","MA",2031 +"2031-05-01","Fete du Travail","MA",2031 +"2031-07-02","Aid al Mawlid Annabawi* (*estimated)","MA",2031 +"2031-07-03","Aid al Mawlid Annabawi* (*estimated)","MA",2031 +"2031-07-30","Fete du Trone","MA",2031 +"2031-08-14","Journee de Oued Ed-Dahab","MA",2031 +"2031-08-20","Commemoration de la revolution du Roi et du peuple","MA",2031 +"2031-08-21","Fete de la jeunesse","MA",2031 +"2031-11-06","Marche verte","MA",2031 +"2031-11-18","Fete de l'independance","MA",2031 +"2032-01-01","Nouvel an - Premier janvier","MA",2032 +"2032-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","MA",2032 +"2032-01-15","Eid al-Fitr* (*estimated)","MA",2032 +"2032-03-22","Eid al-Adha* (*estimated)","MA",2032 +"2032-03-23","Eid al-Adha* (*estimated)","MA",2032 +"2032-04-11","1er Moharram* (*estimated)","MA",2032 +"2032-05-01","Fete du Travail","MA",2032 +"2032-06-20","Aid al Mawlid Annabawi* (*estimated)","MA",2032 +"2032-06-21","Aid al Mawlid Annabawi* (*estimated)","MA",2032 +"2032-07-30","Fete du Trone","MA",2032 +"2032-08-14","Journee de Oued Ed-Dahab","MA",2032 +"2032-08-20","Commemoration de la revolution du Roi et du peuple","MA",2032 +"2032-08-21","Fete de la jeunesse","MA",2032 +"2032-11-06","Marche verte","MA",2032 +"2032-11-18","Fete de l'independance","MA",2032 +"2033-01-01","Nouvel an - Premier janvier","MA",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","MA",2033 +"2033-01-03","Eid al-Fitr* (*estimated)","MA",2033 +"2033-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2033 +"2033-03-11","Eid al-Adha* (*estimated)","MA",2033 +"2033-03-12","Eid al-Adha* (*estimated)","MA",2033 +"2033-04-01","1er Moharram* (*estimated)","MA",2033 +"2033-05-01","Fete du Travail","MA",2033 +"2033-06-09","Aid al Mawlid Annabawi* (*estimated)","MA",2033 +"2033-06-10","Aid al Mawlid Annabawi* (*estimated)","MA",2033 +"2033-07-30","Fete du Trone","MA",2033 +"2033-08-14","Journee de Oued Ed-Dahab","MA",2033 +"2033-08-20","Commemoration de la revolution du Roi et du peuple","MA",2033 +"2033-08-21","Fete de la jeunesse","MA",2033 +"2033-11-06","Marche verte","MA",2033 +"2033-11-18","Fete de l'independance","MA",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","MA",2033 +"2033-12-24","Eid al-Fitr* (*estimated)","MA",2033 +"2034-01-01","Nouvel an - Premier janvier","MA",2034 +"2034-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2034 +"2034-03-01","Eid al-Adha* (*estimated)","MA",2034 +"2034-03-02","Eid al-Adha* (*estimated)","MA",2034 +"2034-03-21","1er Moharram* (*estimated)","MA",2034 +"2034-05-01","Fete du Travail","MA",2034 +"2034-05-30","Aid al Mawlid Annabawi* (*estimated)","MA",2034 +"2034-05-31","Aid al Mawlid Annabawi* (*estimated)","MA",2034 +"2034-07-30","Fete du Trone","MA",2034 +"2034-08-14","Journee de Oued Ed-Dahab","MA",2034 +"2034-08-20","Commemoration de la revolution du Roi et du peuple","MA",2034 +"2034-08-21","Fete de la jeunesse","MA",2034 +"2034-11-06","Marche verte","MA",2034 +"2034-11-18","Fete de l'independance","MA",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","MA",2034 +"2034-12-13","Eid al-Fitr* (*estimated)","MA",2034 +"2035-01-01","Nouvel an - Premier janvier","MA",2035 +"2035-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2035 +"2035-02-18","Eid al-Adha* (*estimated)","MA",2035 +"2035-02-19","Eid al-Adha* (*estimated)","MA",2035 +"2035-03-11","1er Moharram* (*estimated)","MA",2035 +"2035-05-01","Fete du Travail","MA",2035 +"2035-05-20","Aid al Mawlid Annabawi* (*estimated)","MA",2035 +"2035-05-21","Aid al Mawlid Annabawi* (*estimated)","MA",2035 +"2035-07-30","Fete du Trone","MA",2035 +"2035-08-14","Journee de Oued Ed-Dahab","MA",2035 +"2035-08-20","Commemoration de la revolution du Roi et du peuple","MA",2035 +"2035-08-21","Fete de la jeunesse","MA",2035 +"2035-11-06","Marche verte","MA",2035 +"2035-11-18","Fete de l'independance","MA",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","MA",2035 +"2035-12-02","Eid al-Fitr* (*estimated)","MA",2035 +"2036-01-01","Nouvel an - Premier janvier","MA",2036 +"2036-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2036 +"2036-02-07","Eid al-Adha* (*estimated)","MA",2036 +"2036-02-08","Eid al-Adha* (*estimated)","MA",2036 +"2036-02-28","1er Moharram* (*estimated)","MA",2036 +"2036-05-01","Fete du Travail","MA",2036 +"2036-05-08","Aid al Mawlid Annabawi* (*estimated)","MA",2036 +"2036-05-09","Aid al Mawlid Annabawi* (*estimated)","MA",2036 +"2036-07-30","Fete du Trone","MA",2036 +"2036-08-14","Journee de Oued Ed-Dahab","MA",2036 +"2036-08-20","Commemoration de la revolution du Roi et du peuple","MA",2036 +"2036-08-21","Fete de la jeunesse","MA",2036 +"2036-11-06","Marche verte","MA",2036 +"2036-11-18","Fete de l'independance","MA",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","MA",2036 +"2036-11-20","Eid al-Fitr* (*estimated)","MA",2036 +"2037-01-01","Nouvel an - Premier janvier","MA",2037 +"2037-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2037 +"2037-01-26","Eid al-Adha* (*estimated)","MA",2037 +"2037-01-27","Eid al-Adha* (*estimated)","MA",2037 +"2037-02-16","1er Moharram* (*estimated)","MA",2037 +"2037-04-28","Aid al Mawlid Annabawi* (*estimated)","MA",2037 +"2037-04-29","Aid al Mawlid Annabawi* (*estimated)","MA",2037 +"2037-05-01","Fete du Travail","MA",2037 +"2037-07-30","Fete du Trone","MA",2037 +"2037-08-14","Journee de Oued Ed-Dahab","MA",2037 +"2037-08-20","Commemoration de la revolution du Roi et du peuple","MA",2037 +"2037-08-21","Fete de la jeunesse","MA",2037 +"2037-11-06","Marche verte","MA",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","MA",2037 +"2037-11-09","Eid al-Fitr* (*estimated)","MA",2037 +"2037-11-18","Fete de l'independance","MA",2037 +"2038-01-01","Nouvel an - Premier janvier","MA",2038 +"2038-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2038 +"2038-01-16","Eid al-Adha* (*estimated)","MA",2038 +"2038-01-17","Eid al-Adha* (*estimated)","MA",2038 +"2038-02-05","1er Moharram* (*estimated)","MA",2038 +"2038-04-17","Aid al Mawlid Annabawi* (*estimated)","MA",2038 +"2038-04-18","Aid al Mawlid Annabawi* (*estimated)","MA",2038 +"2038-05-01","Fete du Travail","MA",2038 +"2038-07-30","Fete du Trone","MA",2038 +"2038-08-14","Journee de Oued Ed-Dahab","MA",2038 +"2038-08-20","Commemoration de la revolution du Roi et du peuple","MA",2038 +"2038-08-21","Fete de la jeunesse","MA",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","MA",2038 +"2038-10-30","Eid al-Fitr* (*estimated)","MA",2038 +"2038-11-06","Marche verte","MA",2038 +"2038-11-18","Fete de l'independance","MA",2038 +"2039-01-01","Nouvel an - Premier janvier","MA",2039 +"2039-01-05","Eid al-Adha* (*estimated)","MA",2039 +"2039-01-06","Eid al-Adha* (*estimated)","MA",2039 +"2039-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2039 +"2039-01-26","1er Moharram* (*estimated)","MA",2039 +"2039-04-06","Aid al Mawlid Annabawi* (*estimated)","MA",2039 +"2039-04-07","Aid al Mawlid Annabawi* (*estimated)","MA",2039 +"2039-05-01","Fete du Travail","MA",2039 +"2039-07-30","Fete du Trone","MA",2039 +"2039-08-14","Journee de Oued Ed-Dahab","MA",2039 +"2039-08-20","Commemoration de la revolution du Roi et du peuple","MA",2039 +"2039-08-21","Fete de la jeunesse","MA",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","MA",2039 +"2039-10-20","Eid al-Fitr* (*estimated)","MA",2039 +"2039-11-06","Marche verte","MA",2039 +"2039-11-18","Fete de l'independance","MA",2039 +"2039-12-26","Eid al-Adha* (*estimated)","MA",2039 +"2039-12-27","Eid al-Adha* (*estimated)","MA",2039 +"2040-01-01","Nouvel an - Premier janvier","MA",2040 +"2040-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2040 +"2040-01-15","1er Moharram* (*estimated)","MA",2040 +"2040-03-25","Aid al Mawlid Annabawi* (*estimated)","MA",2040 +"2040-03-26","Aid al Mawlid Annabawi* (*estimated)","MA",2040 +"2040-05-01","Fete du Travail","MA",2040 +"2040-07-30","Fete du Trone","MA",2040 +"2040-08-14","Journee de Oued Ed-Dahab","MA",2040 +"2040-08-20","Commemoration de la revolution du Roi et du peuple","MA",2040 +"2040-08-21","Fete de la jeunesse","MA",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","MA",2040 +"2040-10-08","Eid al-Fitr* (*estimated)","MA",2040 +"2040-11-06","Marche verte","MA",2040 +"2040-11-18","Fete de l'independance","MA",2040 +"2040-12-14","Eid al-Adha* (*estimated)","MA",2040 +"2040-12-15","Eid al-Adha* (*estimated)","MA",2040 +"2041-01-01","Nouvel an - Premier janvier","MA",2041 +"2041-01-04","1er Moharram* (*estimated)","MA",2041 +"2041-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2041 +"2041-03-15","Aid al Mawlid Annabawi* (*estimated)","MA",2041 +"2041-03-16","Aid al Mawlid Annabawi* (*estimated)","MA",2041 +"2041-05-01","Fete du Travail","MA",2041 +"2041-07-30","Fete du Trone","MA",2041 +"2041-08-14","Journee de Oued Ed-Dahab","MA",2041 +"2041-08-20","Commemoration de la revolution du Roi et du peuple","MA",2041 +"2041-08-21","Fete de la jeunesse","MA",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","MA",2041 +"2041-09-27","Eid al-Fitr* (*estimated)","MA",2041 +"2041-11-06","Marche verte","MA",2041 +"2041-11-18","Fete de l'independance","MA",2041 +"2041-12-04","Eid al-Adha* (*estimated)","MA",2041 +"2041-12-05","Eid al-Adha* (*estimated)","MA",2041 +"2041-12-24","1er Moharram* (*estimated)","MA",2041 +"2042-01-01","Nouvel an - Premier janvier","MA",2042 +"2042-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2042 +"2042-03-04","Aid al Mawlid Annabawi* (*estimated)","MA",2042 +"2042-03-05","Aid al Mawlid Annabawi* (*estimated)","MA",2042 +"2042-05-01","Fete du Travail","MA",2042 +"2042-07-30","Fete du Trone","MA",2042 +"2042-08-14","Journee de Oued Ed-Dahab","MA",2042 +"2042-08-20","Commemoration de la revolution du Roi et du peuple","MA",2042 +"2042-08-21","Fete de la jeunesse","MA",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","MA",2042 +"2042-09-16","Eid al-Fitr* (*estimated)","MA",2042 +"2042-11-06","Marche verte","MA",2042 +"2042-11-18","Fete de l'independance","MA",2042 +"2042-11-23","Eid al-Adha* (*estimated)","MA",2042 +"2042-11-24","Eid al-Adha* (*estimated)","MA",2042 +"2042-12-14","1er Moharram* (*estimated)","MA",2042 +"2043-01-01","Nouvel an - Premier janvier","MA",2043 +"2043-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2043 +"2043-02-22","Aid al Mawlid Annabawi* (*estimated)","MA",2043 +"2043-02-23","Aid al Mawlid Annabawi* (*estimated)","MA",2043 +"2043-05-01","Fete du Travail","MA",2043 +"2043-07-30","Fete du Trone","MA",2043 +"2043-08-14","Journee de Oued Ed-Dahab","MA",2043 +"2043-08-20","Commemoration de la revolution du Roi et du peuple","MA",2043 +"2043-08-21","Fete de la jeunesse","MA",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","MA",2043 +"2043-09-05","Eid al-Fitr* (*estimated)","MA",2043 +"2043-11-06","Marche verte","MA",2043 +"2043-11-12","Eid al-Adha* (*estimated)","MA",2043 +"2043-11-13","Eid al-Adha* (*estimated)","MA",2043 +"2043-11-18","Fete de l'independance","MA",2043 +"2043-12-03","1er Moharram* (*estimated)","MA",2043 +"2044-01-01","Nouvel an - Premier janvier","MA",2044 +"2044-01-11","Commemoration de la presentation du manifeste de l'independance","MA",2044 +"2044-02-11","Aid al Mawlid Annabawi* (*estimated)","MA",2044 +"2044-02-12","Aid al Mawlid Annabawi* (*estimated)","MA",2044 +"2044-05-01","Fete du Travail","MA",2044 +"2044-07-30","Fete du Trone","MA",2044 +"2044-08-14","Journee de Oued Ed-Dahab","MA",2044 +"2044-08-20","Commemoration de la revolution du Roi et du peuple","MA",2044 +"2044-08-21","Fete de la jeunesse","MA",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","MA",2044 +"2044-08-25","Eid al-Fitr* (*estimated)","MA",2044 +"2044-10-31","Eid al-Adha* (*estimated)","MA",2044 +"2044-11-01","Eid al-Adha* (*estimated)","MA",2044 +"2044-11-06","Marche verte","MA",2044 +"2044-11-18","Fete de l'independance","MA",2044 +"2044-11-21","1er Moharram* (*estimated)","MA",2044 +"1995-01-01","New Year's Day","MC",1995 +"1995-01-02","New Year's Day (Observed)","MC",1995 +"1995-01-27","Saint Devote's Day","MC",1995 +"1995-04-17","Easter Monday","MC",1995 +"1995-05-01","Labour Day","MC",1995 +"1995-05-25","Ascension's Day","MC",1995 +"1995-06-05","Whit Monday","MC",1995 +"1995-06-15","Corpus Christi","MC",1995 +"1995-08-15","Assumption's Day","MC",1995 +"1995-11-01","All Saints' Day","MC",1995 +"1995-11-19","Prince's Day","MC",1995 +"1995-11-20","Prince's Day (Observed)","MC",1995 +"1995-12-08","Immaculate Conception's Day","MC",1995 +"1995-12-25","Christmas Day","MC",1995 +"1996-01-01","New Year's Day","MC",1996 +"1996-01-27","Saint Devote's Day","MC",1996 +"1996-04-08","Easter Monday","MC",1996 +"1996-05-01","Labour Day","MC",1996 +"1996-05-16","Ascension's Day","MC",1996 +"1996-05-27","Whit Monday","MC",1996 +"1996-06-06","Corpus Christi","MC",1996 +"1996-08-15","Assumption's Day","MC",1996 +"1996-11-01","All Saints' Day","MC",1996 +"1996-11-19","Prince's Day","MC",1996 +"1996-12-08","Immaculate Conception's Day","MC",1996 +"1996-12-25","Christmas Day","MC",1996 +"1997-01-01","New Year's Day","MC",1997 +"1997-01-27","Saint Devote's Day","MC",1997 +"1997-03-31","Easter Monday","MC",1997 +"1997-05-01","Labour Day","MC",1997 +"1997-05-08","Ascension's Day","MC",1997 +"1997-05-19","Whit Monday","MC",1997 +"1997-05-29","Corpus Christi","MC",1997 +"1997-08-15","Assumption's Day","MC",1997 +"1997-11-01","All Saints' Day","MC",1997 +"1997-11-19","Prince's Day","MC",1997 +"1997-12-08","Immaculate Conception's Day","MC",1997 +"1997-12-25","Christmas Day","MC",1997 +"1998-01-01","New Year's Day","MC",1998 +"1998-01-27","Saint Devote's Day","MC",1998 +"1998-04-13","Easter Monday","MC",1998 +"1998-05-01","Labour Day","MC",1998 +"1998-05-21","Ascension's Day","MC",1998 +"1998-06-01","Whit Monday","MC",1998 +"1998-06-11","Corpus Christi","MC",1998 +"1998-08-15","Assumption's Day","MC",1998 +"1998-11-01","All Saints' Day","MC",1998 +"1998-11-02","All Saints' Day (Observed)","MC",1998 +"1998-11-19","Prince's Day","MC",1998 +"1998-12-08","Immaculate Conception's Day","MC",1998 +"1998-12-25","Christmas Day","MC",1998 +"1999-01-01","New Year's Day","MC",1999 +"1999-01-27","Saint Devote's Day","MC",1999 +"1999-04-05","Easter Monday","MC",1999 +"1999-05-01","Labour Day","MC",1999 +"1999-05-13","Ascension's Day","MC",1999 +"1999-05-24","Whit Monday","MC",1999 +"1999-06-03","Corpus Christi","MC",1999 +"1999-08-15","Assumption's Day","MC",1999 +"1999-08-16","Assumption's Day (Observed)","MC",1999 +"1999-11-01","All Saints' Day","MC",1999 +"1999-11-19","Prince's Day","MC",1999 +"1999-12-08","Immaculate Conception's Day","MC",1999 +"1999-12-25","Christmas Day","MC",1999 +"2000-01-01","New Year's Day","MC",2000 +"2000-01-27","Saint Devote's Day","MC",2000 +"2000-04-24","Easter Monday","MC",2000 +"2000-05-01","Labour Day","MC",2000 +"2000-06-01","Ascension's Day","MC",2000 +"2000-06-12","Whit Monday","MC",2000 +"2000-06-22","Corpus Christi","MC",2000 +"2000-08-15","Assumption's Day","MC",2000 +"2000-11-01","All Saints' Day","MC",2000 +"2000-11-19","Prince's Day","MC",2000 +"2000-11-20","Prince's Day (Observed)","MC",2000 +"2000-12-08","Immaculate Conception's Day","MC",2000 +"2000-12-25","Christmas Day","MC",2000 +"2001-01-01","New Year's Day","MC",2001 +"2001-01-27","Saint Devote's Day","MC",2001 +"2001-04-16","Easter Monday","MC",2001 +"2001-05-01","Labour Day","MC",2001 +"2001-05-24","Ascension's Day","MC",2001 +"2001-06-04","Whit Monday","MC",2001 +"2001-06-14","Corpus Christi","MC",2001 +"2001-08-15","Assumption's Day","MC",2001 +"2001-11-01","All Saints' Day","MC",2001 +"2001-11-19","Prince's Day","MC",2001 +"2001-12-08","Immaculate Conception's Day","MC",2001 +"2001-12-25","Christmas Day","MC",2001 +"2002-01-01","New Year's Day","MC",2002 +"2002-01-27","Saint Devote's Day","MC",2002 +"2002-04-01","Easter Monday","MC",2002 +"2002-05-01","Labour Day","MC",2002 +"2002-05-09","Ascension's Day","MC",2002 +"2002-05-20","Whit Monday","MC",2002 +"2002-05-30","Corpus Christi","MC",2002 +"2002-08-15","Assumption's Day","MC",2002 +"2002-11-01","All Saints' Day","MC",2002 +"2002-11-19","Prince's Day","MC",2002 +"2002-12-08","Immaculate Conception's Day","MC",2002 +"2002-12-25","Christmas Day","MC",2002 +"2003-01-01","New Year's Day","MC",2003 +"2003-01-27","Saint Devote's Day","MC",2003 +"2003-04-21","Easter Monday","MC",2003 +"2003-05-01","Labour Day","MC",2003 +"2003-05-29","Ascension's Day","MC",2003 +"2003-06-09","Whit Monday","MC",2003 +"2003-06-19","Corpus Christi","MC",2003 +"2003-08-15","Assumption's Day","MC",2003 +"2003-11-01","All Saints' Day","MC",2003 +"2003-11-19","Prince's Day","MC",2003 +"2003-12-08","Immaculate Conception's Day","MC",2003 +"2003-12-25","Christmas Day","MC",2003 +"2004-01-01","New Year's Day","MC",2004 +"2004-01-27","Saint Devote's Day","MC",2004 +"2004-04-12","Easter Monday","MC",2004 +"2004-05-01","Labour Day","MC",2004 +"2004-05-20","Ascension's Day","MC",2004 +"2004-05-31","Whit Monday","MC",2004 +"2004-06-10","Corpus Christi","MC",2004 +"2004-08-15","Assumption's Day","MC",2004 +"2004-08-16","Assumption's Day (Observed)","MC",2004 +"2004-11-01","All Saints' Day","MC",2004 +"2004-11-19","Prince's Day","MC",2004 +"2004-12-08","Immaculate Conception's Day","MC",2004 +"2004-12-25","Christmas Day","MC",2004 +"2005-01-01","New Year's Day","MC",2005 +"2005-01-27","Saint Devote's Day","MC",2005 +"2005-03-28","Easter Monday","MC",2005 +"2005-05-01","Labour Day","MC",2005 +"2005-05-02","Labour Day (Observed)","MC",2005 +"2005-05-05","Ascension's Day","MC",2005 +"2005-05-16","Whit Monday","MC",2005 +"2005-05-26","Corpus Christi","MC",2005 +"2005-08-15","Assumption's Day","MC",2005 +"2005-11-01","All Saints' Day","MC",2005 +"2005-11-19","Prince's Day","MC",2005 +"2005-12-08","Immaculate Conception's Day","MC",2005 +"2005-12-25","Christmas Day","MC",2005 +"2005-12-26","Christmas Day (Observed)","MC",2005 +"2006-01-01","New Year's Day","MC",2006 +"2006-01-02","New Year's Day (Observed)","MC",2006 +"2006-01-27","Saint Devote's Day","MC",2006 +"2006-04-17","Easter Monday","MC",2006 +"2006-05-01","Labour Day","MC",2006 +"2006-05-25","Ascension's Day","MC",2006 +"2006-06-05","Whit Monday","MC",2006 +"2006-06-15","Corpus Christi","MC",2006 +"2006-08-15","Assumption's Day","MC",2006 +"2006-11-01","All Saints' Day","MC",2006 +"2006-11-19","Prince's Day","MC",2006 +"2006-11-20","Prince's Day (Observed)","MC",2006 +"2006-12-08","Immaculate Conception's Day","MC",2006 +"2006-12-25","Christmas Day","MC",2006 +"2007-01-01","New Year's Day","MC",2007 +"2007-01-27","Saint Devote's Day","MC",2007 +"2007-04-09","Easter Monday","MC",2007 +"2007-05-01","Labour Day","MC",2007 +"2007-05-17","Ascension's Day","MC",2007 +"2007-05-28","Whit Monday","MC",2007 +"2007-06-07","Corpus Christi","MC",2007 +"2007-08-15","Assumption's Day","MC",2007 +"2007-11-01","All Saints' Day","MC",2007 +"2007-11-19","Prince's Day","MC",2007 +"2007-12-08","Immaculate Conception's Day","MC",2007 +"2007-12-25","Christmas Day","MC",2007 +"2008-01-01","New Year's Day","MC",2008 +"2008-01-27","Saint Devote's Day","MC",2008 +"2008-03-24","Easter Monday","MC",2008 +"2008-05-01","Ascension's Day","MC",2008 +"2008-05-01","Labour Day","MC",2008 +"2008-05-12","Whit Monday","MC",2008 +"2008-05-22","Corpus Christi","MC",2008 +"2008-08-15","Assumption's Day","MC",2008 +"2008-11-01","All Saints' Day","MC",2008 +"2008-11-19","Prince's Day","MC",2008 +"2008-12-08","Immaculate Conception's Day","MC",2008 +"2008-12-25","Christmas Day","MC",2008 +"2009-01-01","New Year's Day","MC",2009 +"2009-01-27","Saint Devote's Day","MC",2009 +"2009-04-13","Easter Monday","MC",2009 +"2009-05-01","Labour Day","MC",2009 +"2009-05-21","Ascension's Day","MC",2009 +"2009-06-01","Whit Monday","MC",2009 +"2009-06-11","Corpus Christi","MC",2009 +"2009-08-15","Assumption's Day","MC",2009 +"2009-11-01","All Saints' Day","MC",2009 +"2009-11-02","All Saints' Day (Observed)","MC",2009 +"2009-11-19","Prince's Day","MC",2009 +"2009-12-08","Immaculate Conception's Day","MC",2009 +"2009-12-25","Christmas Day","MC",2009 +"2010-01-01","New Year's Day","MC",2010 +"2010-01-27","Saint Devote's Day","MC",2010 +"2010-04-05","Easter Monday","MC",2010 +"2010-05-01","Labour Day","MC",2010 +"2010-05-13","Ascension's Day","MC",2010 +"2010-05-24","Whit Monday","MC",2010 +"2010-06-03","Corpus Christi","MC",2010 +"2010-08-15","Assumption's Day","MC",2010 +"2010-08-16","Assumption's Day (Observed)","MC",2010 +"2010-11-01","All Saints' Day","MC",2010 +"2010-11-19","Prince's Day","MC",2010 +"2010-12-08","Immaculate Conception's Day","MC",2010 +"2010-12-25","Christmas Day","MC",2010 +"2011-01-01","New Year's Day","MC",2011 +"2011-01-27","Saint Devote's Day","MC",2011 +"2011-04-25","Easter Monday","MC",2011 +"2011-05-01","Labour Day","MC",2011 +"2011-05-02","Labour Day (Observed)","MC",2011 +"2011-06-02","Ascension's Day","MC",2011 +"2011-06-13","Whit Monday","MC",2011 +"2011-06-23","Corpus Christi","MC",2011 +"2011-08-15","Assumption's Day","MC",2011 +"2011-11-01","All Saints' Day","MC",2011 +"2011-11-19","Prince's Day","MC",2011 +"2011-12-08","Immaculate Conception's Day","MC",2011 +"2011-12-25","Christmas Day","MC",2011 +"2011-12-26","Christmas Day (Observed)","MC",2011 +"2012-01-01","New Year's Day","MC",2012 +"2012-01-02","New Year's Day (Observed)","MC",2012 +"2012-01-27","Saint Devote's Day","MC",2012 +"2012-04-09","Easter Monday","MC",2012 +"2012-05-01","Labour Day","MC",2012 +"2012-05-17","Ascension's Day","MC",2012 +"2012-05-28","Whit Monday","MC",2012 +"2012-06-07","Corpus Christi","MC",2012 +"2012-08-15","Assumption's Day","MC",2012 +"2012-11-01","All Saints' Day","MC",2012 +"2012-11-19","Prince's Day","MC",2012 +"2012-12-08","Immaculate Conception's Day","MC",2012 +"2012-12-25","Christmas Day","MC",2012 +"2013-01-01","New Year's Day","MC",2013 +"2013-01-27","Saint Devote's Day","MC",2013 +"2013-04-01","Easter Monday","MC",2013 +"2013-05-01","Labour Day","MC",2013 +"2013-05-09","Ascension's Day","MC",2013 +"2013-05-20","Whit Monday","MC",2013 +"2013-05-30","Corpus Christi","MC",2013 +"2013-08-15","Assumption's Day","MC",2013 +"2013-11-01","All Saints' Day","MC",2013 +"2013-11-19","Prince's Day","MC",2013 +"2013-12-08","Immaculate Conception's Day","MC",2013 +"2013-12-25","Christmas Day","MC",2013 +"2014-01-01","New Year's Day","MC",2014 +"2014-01-27","Saint Devote's Day","MC",2014 +"2014-04-21","Easter Monday","MC",2014 +"2014-05-01","Labour Day","MC",2014 +"2014-05-29","Ascension's Day","MC",2014 +"2014-06-09","Whit Monday","MC",2014 +"2014-06-19","Corpus Christi","MC",2014 +"2014-08-15","Assumption's Day","MC",2014 +"2014-11-01","All Saints' Day","MC",2014 +"2014-11-19","Prince's Day","MC",2014 +"2014-12-08","Immaculate Conception's Day","MC",2014 +"2014-12-25","Christmas Day","MC",2014 +"2015-01-01","New Year's Day","MC",2015 +"2015-01-07","Public holiday","MC",2015 +"2015-01-27","Saint Devote's Day","MC",2015 +"2015-04-06","Easter Monday","MC",2015 +"2015-05-01","Labour Day","MC",2015 +"2015-05-14","Ascension's Day","MC",2015 +"2015-05-25","Whit Monday","MC",2015 +"2015-06-04","Corpus Christi","MC",2015 +"2015-08-15","Assumption's Day","MC",2015 +"2015-11-01","All Saints' Day","MC",2015 +"2015-11-02","All Saints' Day (Observed)","MC",2015 +"2015-11-19","Prince's Day","MC",2015 +"2015-12-08","Immaculate Conception's Day","MC",2015 +"2015-12-25","Christmas Day","MC",2015 +"2016-01-01","New Year's Day","MC",2016 +"2016-01-27","Saint Devote's Day","MC",2016 +"2016-03-28","Easter Monday","MC",2016 +"2016-05-01","Labour Day","MC",2016 +"2016-05-02","Labour Day (Observed)","MC",2016 +"2016-05-05","Ascension's Day","MC",2016 +"2016-05-16","Whit Monday","MC",2016 +"2016-05-26","Corpus Christi","MC",2016 +"2016-08-15","Assumption's Day","MC",2016 +"2016-11-01","All Saints' Day","MC",2016 +"2016-11-19","Prince's Day","MC",2016 +"2016-12-08","Immaculate Conception's Day","MC",2016 +"2016-12-25","Christmas Day","MC",2016 +"2016-12-26","Christmas Day (Observed)","MC",2016 +"2017-01-01","New Year's Day","MC",2017 +"2017-01-02","New Year's Day (Observed)","MC",2017 +"2017-01-27","Saint Devote's Day","MC",2017 +"2017-04-17","Easter Monday","MC",2017 +"2017-05-01","Labour Day","MC",2017 +"2017-05-25","Ascension's Day","MC",2017 +"2017-06-05","Whit Monday","MC",2017 +"2017-06-15","Corpus Christi","MC",2017 +"2017-08-15","Assumption's Day","MC",2017 +"2017-11-01","All Saints' Day","MC",2017 +"2017-11-19","Prince's Day","MC",2017 +"2017-11-20","Prince's Day (Observed)","MC",2017 +"2017-12-08","Immaculate Conception's Day","MC",2017 +"2017-12-25","Christmas Day","MC",2017 +"2018-01-01","New Year's Day","MC",2018 +"2018-01-27","Saint Devote's Day","MC",2018 +"2018-04-02","Easter Monday","MC",2018 +"2018-05-01","Labour Day","MC",2018 +"2018-05-10","Ascension's Day","MC",2018 +"2018-05-21","Whit Monday","MC",2018 +"2018-05-31","Corpus Christi","MC",2018 +"2018-08-15","Assumption's Day","MC",2018 +"2018-11-01","All Saints' Day","MC",2018 +"2018-11-19","Prince's Day","MC",2018 +"2018-12-08","Immaculate Conception's Day","MC",2018 +"2018-12-25","Christmas Day","MC",2018 +"2019-01-01","New Year's Day","MC",2019 +"2019-01-27","Saint Devote's Day","MC",2019 +"2019-04-22","Easter Monday","MC",2019 +"2019-05-01","Labour Day","MC",2019 +"2019-05-30","Ascension's Day","MC",2019 +"2019-06-10","Whit Monday","MC",2019 +"2019-06-20","Corpus Christi","MC",2019 +"2019-08-15","Assumption's Day","MC",2019 +"2019-11-01","All Saints' Day","MC",2019 +"2019-11-19","Prince's Day","MC",2019 +"2019-12-09","Immaculate Conception's Day","MC",2019 +"2019-12-25","Christmas Day","MC",2019 +"2020-01-01","New Year's Day","MC",2020 +"2020-01-27","Saint Devote's Day","MC",2020 +"2020-04-13","Easter Monday","MC",2020 +"2020-05-01","Labour Day","MC",2020 +"2020-05-21","Ascension's Day","MC",2020 +"2020-06-01","Whit Monday","MC",2020 +"2020-06-11","Corpus Christi","MC",2020 +"2020-08-15","Assumption's Day","MC",2020 +"2020-11-01","All Saints' Day","MC",2020 +"2020-11-02","All Saints' Day (Observed)","MC",2020 +"2020-11-19","Prince's Day","MC",2020 +"2020-12-08","Immaculate Conception's Day","MC",2020 +"2020-12-25","Christmas Day","MC",2020 +"2021-01-01","New Year's Day","MC",2021 +"2021-01-27","Saint Devote's Day","MC",2021 +"2021-04-05","Easter Monday","MC",2021 +"2021-05-01","Labour Day","MC",2021 +"2021-05-13","Ascension's Day","MC",2021 +"2021-05-24","Whit Monday","MC",2021 +"2021-06-03","Corpus Christi","MC",2021 +"2021-08-15","Assumption's Day","MC",2021 +"2021-08-16","Assumption's Day (Observed)","MC",2021 +"2021-11-01","All Saints' Day","MC",2021 +"2021-11-19","Prince's Day","MC",2021 +"2021-12-08","Immaculate Conception's Day","MC",2021 +"2021-12-25","Christmas Day","MC",2021 +"2022-01-01","New Year's Day","MC",2022 +"2022-01-27","Saint Devote's Day","MC",2022 +"2022-04-18","Easter Monday","MC",2022 +"2022-05-01","Labour Day","MC",2022 +"2022-05-02","Labour Day (Observed)","MC",2022 +"2022-05-26","Ascension's Day","MC",2022 +"2022-06-06","Whit Monday","MC",2022 +"2022-06-16","Corpus Christi","MC",2022 +"2022-08-15","Assumption's Day","MC",2022 +"2022-11-01","All Saints' Day","MC",2022 +"2022-11-19","Prince's Day","MC",2022 +"2022-12-08","Immaculate Conception's Day","MC",2022 +"2022-12-25","Christmas Day","MC",2022 +"2022-12-26","Christmas Day (Observed)","MC",2022 +"2023-01-01","New Year's Day","MC",2023 +"2023-01-02","New Year's Day (Observed)","MC",2023 +"2023-01-27","Saint Devote's Day","MC",2023 +"2023-04-10","Easter Monday","MC",2023 +"2023-05-01","Labour Day","MC",2023 +"2023-05-18","Ascension's Day","MC",2023 +"2023-05-29","Whit Monday","MC",2023 +"2023-06-08","Corpus Christi","MC",2023 +"2023-08-15","Assumption's Day","MC",2023 +"2023-11-01","All Saints' Day","MC",2023 +"2023-11-19","Prince's Day","MC",2023 +"2023-11-20","Prince's Day (Observed)","MC",2023 +"2023-12-08","Immaculate Conception's Day","MC",2023 +"2023-12-25","Christmas Day","MC",2023 +"2024-01-01","New Year's Day","MC",2024 +"2024-01-27","Saint Devote's Day","MC",2024 +"2024-04-01","Easter Monday","MC",2024 +"2024-05-01","Labour Day","MC",2024 +"2024-05-09","Ascension's Day","MC",2024 +"2024-05-20","Whit Monday","MC",2024 +"2024-05-30","Corpus Christi","MC",2024 +"2024-08-15","Assumption's Day","MC",2024 +"2024-11-01","All Saints' Day","MC",2024 +"2024-11-19","Prince's Day","MC",2024 +"2024-12-09","Immaculate Conception's Day","MC",2024 +"2024-12-25","Christmas Day","MC",2024 +"2025-01-01","New Year's Day","MC",2025 +"2025-01-27","Saint Devote's Day","MC",2025 +"2025-04-21","Easter Monday","MC",2025 +"2025-05-01","Labour Day","MC",2025 +"2025-05-29","Ascension's Day","MC",2025 +"2025-06-09","Whit Monday","MC",2025 +"2025-06-19","Corpus Christi","MC",2025 +"2025-08-15","Assumption's Day","MC",2025 +"2025-11-01","All Saints' Day","MC",2025 +"2025-11-19","Prince's Day","MC",2025 +"2025-12-08","Immaculate Conception's Day","MC",2025 +"2025-12-25","Christmas Day","MC",2025 +"2026-01-01","New Year's Day","MC",2026 +"2026-01-27","Saint Devote's Day","MC",2026 +"2026-04-06","Easter Monday","MC",2026 +"2026-05-01","Labour Day","MC",2026 +"2026-05-14","Ascension's Day","MC",2026 +"2026-05-25","Whit Monday","MC",2026 +"2026-06-04","Corpus Christi","MC",2026 +"2026-08-15","Assumption's Day","MC",2026 +"2026-11-01","All Saints' Day","MC",2026 +"2026-11-02","All Saints' Day (Observed)","MC",2026 +"2026-11-19","Prince's Day","MC",2026 +"2026-12-08","Immaculate Conception's Day","MC",2026 +"2026-12-25","Christmas Day","MC",2026 +"2027-01-01","New Year's Day","MC",2027 +"2027-01-27","Saint Devote's Day","MC",2027 +"2027-03-29","Easter Monday","MC",2027 +"2027-05-01","Labour Day","MC",2027 +"2027-05-06","Ascension's Day","MC",2027 +"2027-05-17","Whit Monday","MC",2027 +"2027-05-27","Corpus Christi","MC",2027 +"2027-08-15","Assumption's Day","MC",2027 +"2027-08-16","Assumption's Day (Observed)","MC",2027 +"2027-11-01","All Saints' Day","MC",2027 +"2027-11-19","Prince's Day","MC",2027 +"2027-12-08","Immaculate Conception's Day","MC",2027 +"2027-12-25","Christmas Day","MC",2027 +"2028-01-01","New Year's Day","MC",2028 +"2028-01-27","Saint Devote's Day","MC",2028 +"2028-04-17","Easter Monday","MC",2028 +"2028-05-01","Labour Day","MC",2028 +"2028-05-25","Ascension's Day","MC",2028 +"2028-06-05","Whit Monday","MC",2028 +"2028-06-15","Corpus Christi","MC",2028 +"2028-08-15","Assumption's Day","MC",2028 +"2028-11-01","All Saints' Day","MC",2028 +"2028-11-19","Prince's Day","MC",2028 +"2028-11-20","Prince's Day (Observed)","MC",2028 +"2028-12-08","Immaculate Conception's Day","MC",2028 +"2028-12-25","Christmas Day","MC",2028 +"2029-01-01","New Year's Day","MC",2029 +"2029-01-27","Saint Devote's Day","MC",2029 +"2029-04-02","Easter Monday","MC",2029 +"2029-05-01","Labour Day","MC",2029 +"2029-05-10","Ascension's Day","MC",2029 +"2029-05-21","Whit Monday","MC",2029 +"2029-05-31","Corpus Christi","MC",2029 +"2029-08-15","Assumption's Day","MC",2029 +"2029-11-01","All Saints' Day","MC",2029 +"2029-11-19","Prince's Day","MC",2029 +"2029-12-08","Immaculate Conception's Day","MC",2029 +"2029-12-25","Christmas Day","MC",2029 +"2030-01-01","New Year's Day","MC",2030 +"2030-01-27","Saint Devote's Day","MC",2030 +"2030-04-22","Easter Monday","MC",2030 +"2030-05-01","Labour Day","MC",2030 +"2030-05-30","Ascension's Day","MC",2030 +"2030-06-10","Whit Monday","MC",2030 +"2030-06-20","Corpus Christi","MC",2030 +"2030-08-15","Assumption's Day","MC",2030 +"2030-11-01","All Saints' Day","MC",2030 +"2030-11-19","Prince's Day","MC",2030 +"2030-12-09","Immaculate Conception's Day","MC",2030 +"2030-12-25","Christmas Day","MC",2030 +"2031-01-01","New Year's Day","MC",2031 +"2031-01-27","Saint Devote's Day","MC",2031 +"2031-04-14","Easter Monday","MC",2031 +"2031-05-01","Labour Day","MC",2031 +"2031-05-22","Ascension's Day","MC",2031 +"2031-06-02","Whit Monday","MC",2031 +"2031-06-12","Corpus Christi","MC",2031 +"2031-08-15","Assumption's Day","MC",2031 +"2031-11-01","All Saints' Day","MC",2031 +"2031-11-19","Prince's Day","MC",2031 +"2031-12-08","Immaculate Conception's Day","MC",2031 +"2031-12-25","Christmas Day","MC",2031 +"2032-01-01","New Year's Day","MC",2032 +"2032-01-27","Saint Devote's Day","MC",2032 +"2032-03-29","Easter Monday","MC",2032 +"2032-05-01","Labour Day","MC",2032 +"2032-05-06","Ascension's Day","MC",2032 +"2032-05-17","Whit Monday","MC",2032 +"2032-05-27","Corpus Christi","MC",2032 +"2032-08-15","Assumption's Day","MC",2032 +"2032-08-16","Assumption's Day (Observed)","MC",2032 +"2032-11-01","All Saints' Day","MC",2032 +"2032-11-19","Prince's Day","MC",2032 +"2032-12-08","Immaculate Conception's Day","MC",2032 +"2032-12-25","Christmas Day","MC",2032 +"2033-01-01","New Year's Day","MC",2033 +"2033-01-27","Saint Devote's Day","MC",2033 +"2033-04-18","Easter Monday","MC",2033 +"2033-05-01","Labour Day","MC",2033 +"2033-05-02","Labour Day (Observed)","MC",2033 +"2033-05-26","Ascension's Day","MC",2033 +"2033-06-06","Whit Monday","MC",2033 +"2033-06-16","Corpus Christi","MC",2033 +"2033-08-15","Assumption's Day","MC",2033 +"2033-11-01","All Saints' Day","MC",2033 +"2033-11-19","Prince's Day","MC",2033 +"2033-12-08","Immaculate Conception's Day","MC",2033 +"2033-12-25","Christmas Day","MC",2033 +"2033-12-26","Christmas Day (Observed)","MC",2033 +"2034-01-01","New Year's Day","MC",2034 +"2034-01-02","New Year's Day (Observed)","MC",2034 +"2034-01-27","Saint Devote's Day","MC",2034 +"2034-04-10","Easter Monday","MC",2034 +"2034-05-01","Labour Day","MC",2034 +"2034-05-18","Ascension's Day","MC",2034 +"2034-05-29","Whit Monday","MC",2034 +"2034-06-08","Corpus Christi","MC",2034 +"2034-08-15","Assumption's Day","MC",2034 +"2034-11-01","All Saints' Day","MC",2034 +"2034-11-19","Prince's Day","MC",2034 +"2034-11-20","Prince's Day (Observed)","MC",2034 +"2034-12-08","Immaculate Conception's Day","MC",2034 +"2034-12-25","Christmas Day","MC",2034 +"2035-01-01","New Year's Day","MC",2035 +"2035-01-27","Saint Devote's Day","MC",2035 +"2035-03-26","Easter Monday","MC",2035 +"2035-05-01","Labour Day","MC",2035 +"2035-05-03","Ascension's Day","MC",2035 +"2035-05-14","Whit Monday","MC",2035 +"2035-05-24","Corpus Christi","MC",2035 +"2035-08-15","Assumption's Day","MC",2035 +"2035-11-01","All Saints' Day","MC",2035 +"2035-11-19","Prince's Day","MC",2035 +"2035-12-08","Immaculate Conception's Day","MC",2035 +"2035-12-25","Christmas Day","MC",2035 +"2036-01-01","New Year's Day","MC",2036 +"2036-01-27","Saint Devote's Day","MC",2036 +"2036-04-14","Easter Monday","MC",2036 +"2036-05-01","Labour Day","MC",2036 +"2036-05-22","Ascension's Day","MC",2036 +"2036-06-02","Whit Monday","MC",2036 +"2036-06-12","Corpus Christi","MC",2036 +"2036-08-15","Assumption's Day","MC",2036 +"2036-11-01","All Saints' Day","MC",2036 +"2036-11-19","Prince's Day","MC",2036 +"2036-12-08","Immaculate Conception's Day","MC",2036 +"2036-12-25","Christmas Day","MC",2036 +"2037-01-01","New Year's Day","MC",2037 +"2037-01-27","Saint Devote's Day","MC",2037 +"2037-04-06","Easter Monday","MC",2037 +"2037-05-01","Labour Day","MC",2037 +"2037-05-14","Ascension's Day","MC",2037 +"2037-05-25","Whit Monday","MC",2037 +"2037-06-04","Corpus Christi","MC",2037 +"2037-08-15","Assumption's Day","MC",2037 +"2037-11-01","All Saints' Day","MC",2037 +"2037-11-02","All Saints' Day (Observed)","MC",2037 +"2037-11-19","Prince's Day","MC",2037 +"2037-12-08","Immaculate Conception's Day","MC",2037 +"2037-12-25","Christmas Day","MC",2037 +"2038-01-01","New Year's Day","MC",2038 +"2038-01-27","Saint Devote's Day","MC",2038 +"2038-04-26","Easter Monday","MC",2038 +"2038-05-01","Labour Day","MC",2038 +"2038-06-03","Ascension's Day","MC",2038 +"2038-06-14","Whit Monday","MC",2038 +"2038-06-24","Corpus Christi","MC",2038 +"2038-08-15","Assumption's Day","MC",2038 +"2038-08-16","Assumption's Day (Observed)","MC",2038 +"2038-11-01","All Saints' Day","MC",2038 +"2038-11-19","Prince's Day","MC",2038 +"2038-12-08","Immaculate Conception's Day","MC",2038 +"2038-12-25","Christmas Day","MC",2038 +"2039-01-01","New Year's Day","MC",2039 +"2039-01-27","Saint Devote's Day","MC",2039 +"2039-04-11","Easter Monday","MC",2039 +"2039-05-01","Labour Day","MC",2039 +"2039-05-02","Labour Day (Observed)","MC",2039 +"2039-05-19","Ascension's Day","MC",2039 +"2039-05-30","Whit Monday","MC",2039 +"2039-06-09","Corpus Christi","MC",2039 +"2039-08-15","Assumption's Day","MC",2039 +"2039-11-01","All Saints' Day","MC",2039 +"2039-11-19","Prince's Day","MC",2039 +"2039-12-08","Immaculate Conception's Day","MC",2039 +"2039-12-25","Christmas Day","MC",2039 +"2039-12-26","Christmas Day (Observed)","MC",2039 +"2040-01-01","New Year's Day","MC",2040 +"2040-01-02","New Year's Day (Observed)","MC",2040 +"2040-01-27","Saint Devote's Day","MC",2040 +"2040-04-02","Easter Monday","MC",2040 +"2040-05-01","Labour Day","MC",2040 +"2040-05-10","Ascension's Day","MC",2040 +"2040-05-21","Whit Monday","MC",2040 +"2040-05-31","Corpus Christi","MC",2040 +"2040-08-15","Assumption's Day","MC",2040 +"2040-11-01","All Saints' Day","MC",2040 +"2040-11-19","Prince's Day","MC",2040 +"2040-12-08","Immaculate Conception's Day","MC",2040 +"2040-12-25","Christmas Day","MC",2040 +"2041-01-01","New Year's Day","MC",2041 +"2041-01-27","Saint Devote's Day","MC",2041 +"2041-04-22","Easter Monday","MC",2041 +"2041-05-01","Labour Day","MC",2041 +"2041-05-30","Ascension's Day","MC",2041 +"2041-06-10","Whit Monday","MC",2041 +"2041-06-20","Corpus Christi","MC",2041 +"2041-08-15","Assumption's Day","MC",2041 +"2041-11-01","All Saints' Day","MC",2041 +"2041-11-19","Prince's Day","MC",2041 +"2041-12-09","Immaculate Conception's Day","MC",2041 +"2041-12-25","Christmas Day","MC",2041 +"2042-01-01","New Year's Day","MC",2042 +"2042-01-27","Saint Devote's Day","MC",2042 +"2042-04-07","Easter Monday","MC",2042 +"2042-05-01","Labour Day","MC",2042 +"2042-05-15","Ascension's Day","MC",2042 +"2042-05-26","Whit Monday","MC",2042 +"2042-06-05","Corpus Christi","MC",2042 +"2042-08-15","Assumption's Day","MC",2042 +"2042-11-01","All Saints' Day","MC",2042 +"2042-11-19","Prince's Day","MC",2042 +"2042-12-08","Immaculate Conception's Day","MC",2042 +"2042-12-25","Christmas Day","MC",2042 +"2043-01-01","New Year's Day","MC",2043 +"2043-01-27","Saint Devote's Day","MC",2043 +"2043-03-30","Easter Monday","MC",2043 +"2043-05-01","Labour Day","MC",2043 +"2043-05-07","Ascension's Day","MC",2043 +"2043-05-18","Whit Monday","MC",2043 +"2043-05-28","Corpus Christi","MC",2043 +"2043-08-15","Assumption's Day","MC",2043 +"2043-11-01","All Saints' Day","MC",2043 +"2043-11-02","All Saints' Day (Observed)","MC",2043 +"2043-11-19","Prince's Day","MC",2043 +"2043-12-08","Immaculate Conception's Day","MC",2043 +"2043-12-25","Christmas Day","MC",2043 +"2044-01-01","New Year's Day","MC",2044 +"2044-01-27","Saint Devote's Day","MC",2044 +"2044-04-18","Easter Monday","MC",2044 +"2044-05-01","Labour Day","MC",2044 +"2044-05-02","Labour Day (Observed)","MC",2044 +"2044-05-26","Ascension's Day","MC",2044 +"2044-06-06","Whit Monday","MC",2044 +"2044-06-16","Corpus Christi","MC",2044 +"2044-08-15","Assumption's Day","MC",2044 +"2044-11-01","All Saints' Day","MC",2044 +"2044-11-19","Prince's Day","MC",2044 +"2044-12-08","Immaculate Conception's Day","MC",2044 +"2044-12-25","Christmas Day","MC",2044 +"2044-12-26","Christmas Day (Observed)","MC",2044 +"1995-01-01","New Year's Day","MD",1995 +"1995-01-07","Christmas","MD",1995 +"1995-01-08","Christmas","MD",1995 +"1995-03-08","International Women's Day","MD",1995 +"1995-04-23","Easter","MD",1995 +"1995-04-24","Easter","MD",1995 +"1995-05-01","Day of Rejoicing","MD",1995 +"1995-05-01","International Workers' Solidarity Day","MD",1995 +"1995-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",1995 +"1995-08-27","Republic of Moldova Independence Day","MD",1995 +"1995-08-31","National Language Day","MD",1995 +"1996-01-01","New Year's Day","MD",1996 +"1996-01-07","Christmas","MD",1996 +"1996-01-08","Christmas","MD",1996 +"1996-03-08","International Women's Day","MD",1996 +"1996-04-14","Easter","MD",1996 +"1996-04-15","Easter","MD",1996 +"1996-04-22","Day of Rejoicing","MD",1996 +"1996-05-01","International Workers' Solidarity Day","MD",1996 +"1996-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",1996 +"1996-08-27","Republic of Moldova Independence Day","MD",1996 +"1996-08-31","National Language Day","MD",1996 +"1997-01-01","New Year's Day","MD",1997 +"1997-01-07","Christmas","MD",1997 +"1997-01-08","Christmas","MD",1997 +"1997-03-08","International Women's Day","MD",1997 +"1997-04-27","Easter","MD",1997 +"1997-04-28","Easter","MD",1997 +"1997-05-01","International Workers' Solidarity Day","MD",1997 +"1997-05-05","Day of Rejoicing","MD",1997 +"1997-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",1997 +"1997-08-27","Republic of Moldova Independence Day","MD",1997 +"1997-08-31","National Language Day","MD",1997 +"1998-01-01","New Year's Day","MD",1998 +"1998-01-07","Christmas","MD",1998 +"1998-01-08","Christmas","MD",1998 +"1998-03-08","International Women's Day","MD",1998 +"1998-04-19","Easter","MD",1998 +"1998-04-20","Easter","MD",1998 +"1998-04-27","Day of Rejoicing","MD",1998 +"1998-05-01","International Workers' Solidarity Day","MD",1998 +"1998-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",1998 +"1998-08-27","Republic of Moldova Independence Day","MD",1998 +"1998-08-31","National Language Day","MD",1998 +"1999-01-01","New Year's Day","MD",1999 +"1999-01-07","Christmas","MD",1999 +"1999-01-08","Christmas","MD",1999 +"1999-03-08","International Women's Day","MD",1999 +"1999-04-11","Easter","MD",1999 +"1999-04-12","Easter","MD",1999 +"1999-04-19","Day of Rejoicing","MD",1999 +"1999-05-01","International Workers' Solidarity Day","MD",1999 +"1999-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",1999 +"1999-08-27","Republic of Moldova Independence Day","MD",1999 +"1999-08-31","National Language Day","MD",1999 +"2000-01-01","New Year's Day","MD",2000 +"2000-01-07","Christmas","MD",2000 +"2000-01-08","Christmas","MD",2000 +"2000-03-08","International Women's Day","MD",2000 +"2000-04-30","Easter","MD",2000 +"2000-05-01","Easter","MD",2000 +"2000-05-01","International Workers' Solidarity Day","MD",2000 +"2000-05-08","Day of Rejoicing","MD",2000 +"2000-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2000 +"2000-08-27","Republic of Moldova Independence Day","MD",2000 +"2000-08-31","National Language Day","MD",2000 +"2001-01-01","New Year's Day","MD",2001 +"2001-01-07","Christmas","MD",2001 +"2001-01-08","Christmas","MD",2001 +"2001-03-08","International Women's Day","MD",2001 +"2001-04-15","Easter","MD",2001 +"2001-04-16","Easter","MD",2001 +"2001-04-23","Day of Rejoicing","MD",2001 +"2001-05-01","International Workers' Solidarity Day","MD",2001 +"2001-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2001 +"2001-08-27","Republic of Moldova Independence Day","MD",2001 +"2001-08-31","National Language Day","MD",2001 +"2002-01-01","New Year's Day","MD",2002 +"2002-01-07","Christmas","MD",2002 +"2002-01-08","Christmas","MD",2002 +"2002-03-08","International Women's Day","MD",2002 +"2002-05-01","International Workers' Solidarity Day","MD",2002 +"2002-05-05","Easter","MD",2002 +"2002-05-06","Easter","MD",2002 +"2002-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2002 +"2002-05-13","Day of Rejoicing","MD",2002 +"2002-08-27","Republic of Moldova Independence Day","MD",2002 +"2002-08-31","National Language Day","MD",2002 +"2003-01-01","New Year's Day","MD",2003 +"2003-01-07","Christmas","MD",2003 +"2003-01-08","Christmas","MD",2003 +"2003-03-08","International Women's Day","MD",2003 +"2003-04-27","Easter","MD",2003 +"2003-04-28","Easter","MD",2003 +"2003-05-01","International Workers' Solidarity Day","MD",2003 +"2003-05-05","Day of Rejoicing","MD",2003 +"2003-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2003 +"2003-08-27","Republic of Moldova Independence Day","MD",2003 +"2003-08-31","National Language Day","MD",2003 +"2004-01-01","New Year's Day","MD",2004 +"2004-01-07","Christmas","MD",2004 +"2004-01-08","Christmas","MD",2004 +"2004-03-08","International Women's Day","MD",2004 +"2004-04-11","Easter","MD",2004 +"2004-04-12","Easter","MD",2004 +"2004-04-19","Day of Rejoicing","MD",2004 +"2004-05-01","International Workers' Solidarity Day","MD",2004 +"2004-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2004 +"2004-08-27","Republic of Moldova Independence Day","MD",2004 +"2004-08-31","National Language Day","MD",2004 +"2005-01-01","New Year's Day","MD",2005 +"2005-01-07","Christmas","MD",2005 +"2005-01-08","Christmas","MD",2005 +"2005-03-08","International Women's Day","MD",2005 +"2005-05-01","Easter","MD",2005 +"2005-05-01","International Workers' Solidarity Day","MD",2005 +"2005-05-02","Easter","MD",2005 +"2005-05-09","Day of Rejoicing","MD",2005 +"2005-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2005 +"2005-08-27","Republic of Moldova Independence Day","MD",2005 +"2005-08-31","National Language Day","MD",2005 +"2006-01-01","New Year's Day","MD",2006 +"2006-01-07","Christmas","MD",2006 +"2006-01-08","Christmas","MD",2006 +"2006-03-08","International Women's Day","MD",2006 +"2006-04-23","Easter","MD",2006 +"2006-04-24","Easter","MD",2006 +"2006-05-01","Day of Rejoicing","MD",2006 +"2006-05-01","International Workers' Solidarity Day","MD",2006 +"2006-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2006 +"2006-08-27","Republic of Moldova Independence Day","MD",2006 +"2006-08-31","National Language Day","MD",2006 +"2007-01-01","New Year's Day","MD",2007 +"2007-01-07","Christmas","MD",2007 +"2007-01-08","Christmas","MD",2007 +"2007-03-08","International Women's Day","MD",2007 +"2007-04-08","Easter","MD",2007 +"2007-04-09","Easter","MD",2007 +"2007-04-16","Day of Rejoicing","MD",2007 +"2007-05-01","International Workers' Solidarity Day","MD",2007 +"2007-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2007 +"2007-08-27","Republic of Moldova Independence Day","MD",2007 +"2007-08-31","National Language Day","MD",2007 +"2008-01-01","New Year's Day","MD",2008 +"2008-01-07","Christmas","MD",2008 +"2008-01-08","Christmas","MD",2008 +"2008-03-08","International Women's Day","MD",2008 +"2008-04-27","Easter","MD",2008 +"2008-04-28","Easter","MD",2008 +"2008-05-01","International Workers' Solidarity Day","MD",2008 +"2008-05-05","Day of Rejoicing","MD",2008 +"2008-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2008 +"2008-08-27","Republic of Moldova Independence Day","MD",2008 +"2008-08-31","National Language Day","MD",2008 +"2009-01-01","New Year's Day","MD",2009 +"2009-01-07","Christmas","MD",2009 +"2009-01-08","Christmas","MD",2009 +"2009-03-08","International Women's Day","MD",2009 +"2009-04-19","Easter","MD",2009 +"2009-04-20","Easter","MD",2009 +"2009-04-27","Day of Rejoicing","MD",2009 +"2009-05-01","International Workers' Solidarity Day","MD",2009 +"2009-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2009 +"2009-08-27","Republic of Moldova Independence Day","MD",2009 +"2009-08-31","National Language Day","MD",2009 +"2010-01-01","New Year's Day","MD",2010 +"2010-01-07","Christmas","MD",2010 +"2010-01-08","Christmas","MD",2010 +"2010-03-08","International Women's Day","MD",2010 +"2010-04-04","Easter","MD",2010 +"2010-04-05","Easter","MD",2010 +"2010-04-12","Day of Rejoicing","MD",2010 +"2010-05-01","International Workers' Solidarity Day","MD",2010 +"2010-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2010 +"2010-08-27","Republic of Moldova Independence Day","MD",2010 +"2010-08-31","National Language Day","MD",2010 +"2011-01-01","New Year's Day","MD",2011 +"2011-01-07","Christmas","MD",2011 +"2011-01-08","Christmas","MD",2011 +"2011-03-08","International Women's Day","MD",2011 +"2011-04-24","Easter","MD",2011 +"2011-04-25","Easter","MD",2011 +"2011-05-01","International Workers' Solidarity Day","MD",2011 +"2011-05-02","Day of Rejoicing","MD",2011 +"2011-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2011 +"2011-08-27","Republic of Moldova Independence Day","MD",2011 +"2011-08-31","National Language Day","MD",2011 +"2012-01-01","New Year's Day","MD",2012 +"2012-01-07","Christmas","MD",2012 +"2012-01-08","Christmas","MD",2012 +"2012-03-08","International Women's Day","MD",2012 +"2012-04-15","Easter","MD",2012 +"2012-04-16","Easter","MD",2012 +"2012-04-23","Day of Rejoicing","MD",2012 +"2012-05-01","International Workers' Solidarity Day","MD",2012 +"2012-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2012 +"2012-08-27","Republic of Moldova Independence Day","MD",2012 +"2012-08-31","National Language Day","MD",2012 +"2013-01-01","New Year's Day","MD",2013 +"2013-01-07","Christmas","MD",2013 +"2013-01-08","Christmas","MD",2013 +"2013-03-08","International Women's Day","MD",2013 +"2013-05-01","International Workers' Solidarity Day","MD",2013 +"2013-05-05","Easter","MD",2013 +"2013-05-06","Easter","MD",2013 +"2013-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2013 +"2013-05-13","Day of Rejoicing","MD",2013 +"2013-08-27","Republic of Moldova Independence Day","MD",2013 +"2013-08-31","National Language Day","MD",2013 +"2013-12-25","Christmas (by new style)","MD",2013 +"2014-01-01","New Year's Day","MD",2014 +"2014-01-07","Christmas (by old style)","MD",2014 +"2014-01-08","Christmas (by old style)","MD",2014 +"2014-03-08","International Women's Day","MD",2014 +"2014-04-20","Easter","MD",2014 +"2014-04-21","Easter","MD",2014 +"2014-04-28","Day of Rejoicing","MD",2014 +"2014-05-01","International Workers' Solidarity Day","MD",2014 +"2014-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2014 +"2014-08-27","Republic of Moldova Independence Day","MD",2014 +"2014-08-31","National Language Day","MD",2014 +"2014-12-25","Christmas (by new style)","MD",2014 +"2015-01-01","New Year's Day","MD",2015 +"2015-01-07","Christmas (by old style)","MD",2015 +"2015-01-08","Christmas (by old style)","MD",2015 +"2015-03-08","International Women's Day","MD",2015 +"2015-04-12","Easter","MD",2015 +"2015-04-13","Easter","MD",2015 +"2015-04-20","Day of Rejoicing","MD",2015 +"2015-05-01","International Workers' Solidarity Day","MD",2015 +"2015-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2015 +"2015-08-27","Republic of Moldova Independence Day","MD",2015 +"2015-08-31","National Language Day","MD",2015 +"2015-12-25","Christmas (by new style)","MD",2015 +"2016-01-01","New Year's Day","MD",2016 +"2016-01-07","Christmas (by old style)","MD",2016 +"2016-01-08","Christmas (by old style)","MD",2016 +"2016-03-08","International Women's Day","MD",2016 +"2016-05-01","Easter","MD",2016 +"2016-05-01","International Workers' Solidarity Day","MD",2016 +"2016-05-02","Easter","MD",2016 +"2016-05-09","Day of Rejoicing","MD",2016 +"2016-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2016 +"2016-06-01","International Children's Day","MD",2016 +"2016-08-27","Republic of Moldova Independence Day","MD",2016 +"2016-08-31","National Language Day","MD",2016 +"2016-12-25","Christmas (by new style)","MD",2016 +"2017-01-01","New Year's Day","MD",2017 +"2017-01-07","Christmas (by old style)","MD",2017 +"2017-01-08","Christmas (by old style)","MD",2017 +"2017-03-08","International Women's Day","MD",2017 +"2017-04-16","Easter","MD",2017 +"2017-04-17","Easter","MD",2017 +"2017-04-24","Day of Rejoicing","MD",2017 +"2017-05-01","International Workers' Solidarity Day","MD",2017 +"2017-05-09","Europe Day","MD",2017 +"2017-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2017 +"2017-06-01","International Children's Day","MD",2017 +"2017-08-27","Republic of Moldova Independence Day","MD",2017 +"2017-08-31","National Language Day","MD",2017 +"2017-12-25","Christmas (by new style)","MD",2017 +"2018-01-01","New Year's Day","MD",2018 +"2018-01-07","Christmas (by old style)","MD",2018 +"2018-01-08","Christmas (by old style)","MD",2018 +"2018-03-08","International Women's Day","MD",2018 +"2018-04-08","Easter","MD",2018 +"2018-04-09","Easter","MD",2018 +"2018-04-16","Day of Rejoicing","MD",2018 +"2018-05-01","International Workers' Solidarity Day","MD",2018 +"2018-05-09","Europe Day","MD",2018 +"2018-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2018 +"2018-06-01","International Children's Day","MD",2018 +"2018-08-27","Republic of Moldova Independence Day","MD",2018 +"2018-08-31","National Language Day","MD",2018 +"2018-12-25","Christmas (by new style)","MD",2018 +"2019-01-01","New Year's Day","MD",2019 +"2019-01-07","Christmas (by old style)","MD",2019 +"2019-01-08","Christmas (by old style)","MD",2019 +"2019-03-08","International Women's Day","MD",2019 +"2019-04-28","Easter","MD",2019 +"2019-04-29","Easter","MD",2019 +"2019-05-01","International Workers' Solidarity Day","MD",2019 +"2019-05-06","Day of Rejoicing","MD",2019 +"2019-05-09","Europe Day","MD",2019 +"2019-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2019 +"2019-06-01","International Children's Day","MD",2019 +"2019-08-27","Republic of Moldova Independence Day","MD",2019 +"2019-08-31","National Language Day","MD",2019 +"2019-12-25","Christmas (by new style)","MD",2019 +"2020-01-01","New Year's Day","MD",2020 +"2020-01-07","Christmas (by old style)","MD",2020 +"2020-01-08","Christmas (by old style)","MD",2020 +"2020-03-08","International Women's Day","MD",2020 +"2020-04-19","Easter","MD",2020 +"2020-04-20","Easter","MD",2020 +"2020-04-27","Day of Rejoicing","MD",2020 +"2020-05-01","International Workers' Solidarity Day","MD",2020 +"2020-05-09","Europe Day","MD",2020 +"2020-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2020 +"2020-06-01","International Children's Day","MD",2020 +"2020-08-27","Republic of Moldova Independence Day","MD",2020 +"2020-08-31","National Language Day","MD",2020 +"2020-12-25","Christmas (by new style)","MD",2020 +"2021-01-01","New Year's Day","MD",2021 +"2021-01-07","Christmas (by old style)","MD",2021 +"2021-01-08","Christmas (by old style)","MD",2021 +"2021-03-08","International Women's Day","MD",2021 +"2021-05-01","International Workers' Solidarity Day","MD",2021 +"2021-05-02","Easter","MD",2021 +"2021-05-03","Easter","MD",2021 +"2021-05-09","Europe Day","MD",2021 +"2021-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2021 +"2021-05-10","Day of Rejoicing","MD",2021 +"2021-06-01","International Children's Day","MD",2021 +"2021-08-27","Republic of Moldova Independence Day","MD",2021 +"2021-08-31","National Language Day","MD",2021 +"2021-12-25","Christmas (by new style)","MD",2021 +"2022-01-01","New Year's Day","MD",2022 +"2022-01-07","Christmas (by old style)","MD",2022 +"2022-01-08","Christmas (by old style)","MD",2022 +"2022-03-08","International Women's Day","MD",2022 +"2022-04-24","Easter","MD",2022 +"2022-04-25","Easter","MD",2022 +"2022-05-01","International Workers' Solidarity Day","MD",2022 +"2022-05-02","Day of Rejoicing","MD",2022 +"2022-05-09","Europe Day","MD",2022 +"2022-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2022 +"2022-06-01","International Children's Day","MD",2022 +"2022-08-27","Republic of Moldova Independence Day","MD",2022 +"2022-08-31","National Language Day","MD",2022 +"2022-12-25","Christmas (by new style)","MD",2022 +"2023-01-01","New Year's Day","MD",2023 +"2023-01-07","Christmas (by old style)","MD",2023 +"2023-01-08","Christmas (by old style)","MD",2023 +"2023-03-08","International Women's Day","MD",2023 +"2023-04-16","Easter","MD",2023 +"2023-04-17","Easter","MD",2023 +"2023-04-24","Day of Rejoicing","MD",2023 +"2023-05-01","International Workers' Solidarity Day","MD",2023 +"2023-05-09","Europe Day","MD",2023 +"2023-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2023 +"2023-06-01","International Children's Day","MD",2023 +"2023-08-27","Republic of Moldova Independence Day","MD",2023 +"2023-08-31","National Language Day","MD",2023 +"2023-12-25","Christmas (by new style)","MD",2023 +"2024-01-01","New Year's Day","MD",2024 +"2024-01-07","Christmas (by old style)","MD",2024 +"2024-01-08","Christmas (by old style)","MD",2024 +"2024-03-08","International Women's Day","MD",2024 +"2024-05-01","International Workers' Solidarity Day","MD",2024 +"2024-05-05","Easter","MD",2024 +"2024-05-06","Easter","MD",2024 +"2024-05-09","Europe Day","MD",2024 +"2024-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2024 +"2024-05-13","Day of Rejoicing","MD",2024 +"2024-06-01","International Children's Day","MD",2024 +"2024-08-27","Republic of Moldova Independence Day","MD",2024 +"2024-08-31","National Language Day","MD",2024 +"2024-12-25","Christmas (by new style)","MD",2024 +"2025-01-01","New Year's Day","MD",2025 +"2025-01-07","Christmas (by old style)","MD",2025 +"2025-01-08","Christmas (by old style)","MD",2025 +"2025-03-08","International Women's Day","MD",2025 +"2025-04-20","Easter","MD",2025 +"2025-04-21","Easter","MD",2025 +"2025-04-28","Day of Rejoicing","MD",2025 +"2025-05-01","International Workers' Solidarity Day","MD",2025 +"2025-05-09","Europe Day","MD",2025 +"2025-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2025 +"2025-06-01","International Children's Day","MD",2025 +"2025-08-27","Republic of Moldova Independence Day","MD",2025 +"2025-08-31","National Language Day","MD",2025 +"2025-12-25","Christmas (by new style)","MD",2025 +"2026-01-01","New Year's Day","MD",2026 +"2026-01-07","Christmas (by old style)","MD",2026 +"2026-01-08","Christmas (by old style)","MD",2026 +"2026-03-08","International Women's Day","MD",2026 +"2026-04-12","Easter","MD",2026 +"2026-04-13","Easter","MD",2026 +"2026-04-20","Day of Rejoicing","MD",2026 +"2026-05-01","International Workers' Solidarity Day","MD",2026 +"2026-05-09","Europe Day","MD",2026 +"2026-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2026 +"2026-06-01","International Children's Day","MD",2026 +"2026-08-27","Republic of Moldova Independence Day","MD",2026 +"2026-08-31","National Language Day","MD",2026 +"2026-12-25","Christmas (by new style)","MD",2026 +"2027-01-01","New Year's Day","MD",2027 +"2027-01-07","Christmas (by old style)","MD",2027 +"2027-01-08","Christmas (by old style)","MD",2027 +"2027-03-08","International Women's Day","MD",2027 +"2027-05-01","International Workers' Solidarity Day","MD",2027 +"2027-05-02","Easter","MD",2027 +"2027-05-03","Easter","MD",2027 +"2027-05-09","Europe Day","MD",2027 +"2027-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2027 +"2027-05-10","Day of Rejoicing","MD",2027 +"2027-06-01","International Children's Day","MD",2027 +"2027-08-27","Republic of Moldova Independence Day","MD",2027 +"2027-08-31","National Language Day","MD",2027 +"2027-12-25","Christmas (by new style)","MD",2027 +"2028-01-01","New Year's Day","MD",2028 +"2028-01-07","Christmas (by old style)","MD",2028 +"2028-01-08","Christmas (by old style)","MD",2028 +"2028-03-08","International Women's Day","MD",2028 +"2028-04-16","Easter","MD",2028 +"2028-04-17","Easter","MD",2028 +"2028-04-24","Day of Rejoicing","MD",2028 +"2028-05-01","International Workers' Solidarity Day","MD",2028 +"2028-05-09","Europe Day","MD",2028 +"2028-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2028 +"2028-06-01","International Children's Day","MD",2028 +"2028-08-27","Republic of Moldova Independence Day","MD",2028 +"2028-08-31","National Language Day","MD",2028 +"2028-12-25","Christmas (by new style)","MD",2028 +"2029-01-01","New Year's Day","MD",2029 +"2029-01-07","Christmas (by old style)","MD",2029 +"2029-01-08","Christmas (by old style)","MD",2029 +"2029-03-08","International Women's Day","MD",2029 +"2029-04-08","Easter","MD",2029 +"2029-04-09","Easter","MD",2029 +"2029-04-16","Day of Rejoicing","MD",2029 +"2029-05-01","International Workers' Solidarity Day","MD",2029 +"2029-05-09","Europe Day","MD",2029 +"2029-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2029 +"2029-06-01","International Children's Day","MD",2029 +"2029-08-27","Republic of Moldova Independence Day","MD",2029 +"2029-08-31","National Language Day","MD",2029 +"2029-12-25","Christmas (by new style)","MD",2029 +"2030-01-01","New Year's Day","MD",2030 +"2030-01-07","Christmas (by old style)","MD",2030 +"2030-01-08","Christmas (by old style)","MD",2030 +"2030-03-08","International Women's Day","MD",2030 +"2030-04-28","Easter","MD",2030 +"2030-04-29","Easter","MD",2030 +"2030-05-01","International Workers' Solidarity Day","MD",2030 +"2030-05-06","Day of Rejoicing","MD",2030 +"2030-05-09","Europe Day","MD",2030 +"2030-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2030 +"2030-06-01","International Children's Day","MD",2030 +"2030-08-27","Republic of Moldova Independence Day","MD",2030 +"2030-08-31","National Language Day","MD",2030 +"2030-12-25","Christmas (by new style)","MD",2030 +"2031-01-01","New Year's Day","MD",2031 +"2031-01-07","Christmas (by old style)","MD",2031 +"2031-01-08","Christmas (by old style)","MD",2031 +"2031-03-08","International Women's Day","MD",2031 +"2031-04-13","Easter","MD",2031 +"2031-04-14","Easter","MD",2031 +"2031-04-21","Day of Rejoicing","MD",2031 +"2031-05-01","International Workers' Solidarity Day","MD",2031 +"2031-05-09","Europe Day","MD",2031 +"2031-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2031 +"2031-06-01","International Children's Day","MD",2031 +"2031-08-27","Republic of Moldova Independence Day","MD",2031 +"2031-08-31","National Language Day","MD",2031 +"2031-12-25","Christmas (by new style)","MD",2031 +"2032-01-01","New Year's Day","MD",2032 +"2032-01-07","Christmas (by old style)","MD",2032 +"2032-01-08","Christmas (by old style)","MD",2032 +"2032-03-08","International Women's Day","MD",2032 +"2032-05-01","International Workers' Solidarity Day","MD",2032 +"2032-05-02","Easter","MD",2032 +"2032-05-03","Easter","MD",2032 +"2032-05-09","Europe Day","MD",2032 +"2032-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2032 +"2032-05-10","Day of Rejoicing","MD",2032 +"2032-06-01","International Children's Day","MD",2032 +"2032-08-27","Republic of Moldova Independence Day","MD",2032 +"2032-08-31","National Language Day","MD",2032 +"2032-12-25","Christmas (by new style)","MD",2032 +"2033-01-01","New Year's Day","MD",2033 +"2033-01-07","Christmas (by old style)","MD",2033 +"2033-01-08","Christmas (by old style)","MD",2033 +"2033-03-08","International Women's Day","MD",2033 +"2033-04-24","Easter","MD",2033 +"2033-04-25","Easter","MD",2033 +"2033-05-01","International Workers' Solidarity Day","MD",2033 +"2033-05-02","Day of Rejoicing","MD",2033 +"2033-05-09","Europe Day","MD",2033 +"2033-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2033 +"2033-06-01","International Children's Day","MD",2033 +"2033-08-27","Republic of Moldova Independence Day","MD",2033 +"2033-08-31","National Language Day","MD",2033 +"2033-12-25","Christmas (by new style)","MD",2033 +"2034-01-01","New Year's Day","MD",2034 +"2034-01-07","Christmas (by old style)","MD",2034 +"2034-01-08","Christmas (by old style)","MD",2034 +"2034-03-08","International Women's Day","MD",2034 +"2034-04-09","Easter","MD",2034 +"2034-04-10","Easter","MD",2034 +"2034-04-17","Day of Rejoicing","MD",2034 +"2034-05-01","International Workers' Solidarity Day","MD",2034 +"2034-05-09","Europe Day","MD",2034 +"2034-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2034 +"2034-06-01","International Children's Day","MD",2034 +"2034-08-27","Republic of Moldova Independence Day","MD",2034 +"2034-08-31","National Language Day","MD",2034 +"2034-12-25","Christmas (by new style)","MD",2034 +"2035-01-01","New Year's Day","MD",2035 +"2035-01-07","Christmas (by old style)","MD",2035 +"2035-01-08","Christmas (by old style)","MD",2035 +"2035-03-08","International Women's Day","MD",2035 +"2035-04-29","Easter","MD",2035 +"2035-04-30","Easter","MD",2035 +"2035-05-01","International Workers' Solidarity Day","MD",2035 +"2035-05-07","Day of Rejoicing","MD",2035 +"2035-05-09","Europe Day","MD",2035 +"2035-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2035 +"2035-06-01","International Children's Day","MD",2035 +"2035-08-27","Republic of Moldova Independence Day","MD",2035 +"2035-08-31","National Language Day","MD",2035 +"2035-12-25","Christmas (by new style)","MD",2035 +"2036-01-01","New Year's Day","MD",2036 +"2036-01-07","Christmas (by old style)","MD",2036 +"2036-01-08","Christmas (by old style)","MD",2036 +"2036-03-08","International Women's Day","MD",2036 +"2036-04-20","Easter","MD",2036 +"2036-04-21","Easter","MD",2036 +"2036-04-28","Day of Rejoicing","MD",2036 +"2036-05-01","International Workers' Solidarity Day","MD",2036 +"2036-05-09","Europe Day","MD",2036 +"2036-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2036 +"2036-06-01","International Children's Day","MD",2036 +"2036-08-27","Republic of Moldova Independence Day","MD",2036 +"2036-08-31","National Language Day","MD",2036 +"2036-12-25","Christmas (by new style)","MD",2036 +"2037-01-01","New Year's Day","MD",2037 +"2037-01-07","Christmas (by old style)","MD",2037 +"2037-01-08","Christmas (by old style)","MD",2037 +"2037-03-08","International Women's Day","MD",2037 +"2037-04-05","Easter","MD",2037 +"2037-04-06","Easter","MD",2037 +"2037-04-13","Day of Rejoicing","MD",2037 +"2037-05-01","International Workers' Solidarity Day","MD",2037 +"2037-05-09","Europe Day","MD",2037 +"2037-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2037 +"2037-06-01","International Children's Day","MD",2037 +"2037-08-27","Republic of Moldova Independence Day","MD",2037 +"2037-08-31","National Language Day","MD",2037 +"2037-12-25","Christmas (by new style)","MD",2037 +"2038-01-01","New Year's Day","MD",2038 +"2038-01-07","Christmas (by old style)","MD",2038 +"2038-01-08","Christmas (by old style)","MD",2038 +"2038-03-08","International Women's Day","MD",2038 +"2038-04-25","Easter","MD",2038 +"2038-04-26","Easter","MD",2038 +"2038-05-01","International Workers' Solidarity Day","MD",2038 +"2038-05-03","Day of Rejoicing","MD",2038 +"2038-05-09","Europe Day","MD",2038 +"2038-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2038 +"2038-06-01","International Children's Day","MD",2038 +"2038-08-27","Republic of Moldova Independence Day","MD",2038 +"2038-08-31","National Language Day","MD",2038 +"2038-12-25","Christmas (by new style)","MD",2038 +"2039-01-01","New Year's Day","MD",2039 +"2039-01-07","Christmas (by old style)","MD",2039 +"2039-01-08","Christmas (by old style)","MD",2039 +"2039-03-08","International Women's Day","MD",2039 +"2039-04-17","Easter","MD",2039 +"2039-04-18","Easter","MD",2039 +"2039-04-25","Day of Rejoicing","MD",2039 +"2039-05-01","International Workers' Solidarity Day","MD",2039 +"2039-05-09","Europe Day","MD",2039 +"2039-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2039 +"2039-06-01","International Children's Day","MD",2039 +"2039-08-27","Republic of Moldova Independence Day","MD",2039 +"2039-08-31","National Language Day","MD",2039 +"2039-12-25","Christmas (by new style)","MD",2039 +"2040-01-01","New Year's Day","MD",2040 +"2040-01-07","Christmas (by old style)","MD",2040 +"2040-01-08","Christmas (by old style)","MD",2040 +"2040-03-08","International Women's Day","MD",2040 +"2040-05-01","International Workers' Solidarity Day","MD",2040 +"2040-05-06","Easter","MD",2040 +"2040-05-07","Easter","MD",2040 +"2040-05-09","Europe Day","MD",2040 +"2040-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2040 +"2040-05-14","Day of Rejoicing","MD",2040 +"2040-06-01","International Children's Day","MD",2040 +"2040-08-27","Republic of Moldova Independence Day","MD",2040 +"2040-08-31","National Language Day","MD",2040 +"2040-12-25","Christmas (by new style)","MD",2040 +"2041-01-01","New Year's Day","MD",2041 +"2041-01-07","Christmas (by old style)","MD",2041 +"2041-01-08","Christmas (by old style)","MD",2041 +"2041-03-08","International Women's Day","MD",2041 +"2041-04-21","Easter","MD",2041 +"2041-04-22","Easter","MD",2041 +"2041-04-29","Day of Rejoicing","MD",2041 +"2041-05-01","International Workers' Solidarity Day","MD",2041 +"2041-05-09","Europe Day","MD",2041 +"2041-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2041 +"2041-06-01","International Children's Day","MD",2041 +"2041-08-27","Republic of Moldova Independence Day","MD",2041 +"2041-08-31","National Language Day","MD",2041 +"2041-12-25","Christmas (by new style)","MD",2041 +"2042-01-01","New Year's Day","MD",2042 +"2042-01-07","Christmas (by old style)","MD",2042 +"2042-01-08","Christmas (by old style)","MD",2042 +"2042-03-08","International Women's Day","MD",2042 +"2042-04-13","Easter","MD",2042 +"2042-04-14","Easter","MD",2042 +"2042-04-21","Day of Rejoicing","MD",2042 +"2042-05-01","International Workers' Solidarity Day","MD",2042 +"2042-05-09","Europe Day","MD",2042 +"2042-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2042 +"2042-06-01","International Children's Day","MD",2042 +"2042-08-27","Republic of Moldova Independence Day","MD",2042 +"2042-08-31","National Language Day","MD",2042 +"2042-12-25","Christmas (by new style)","MD",2042 +"2043-01-01","New Year's Day","MD",2043 +"2043-01-07","Christmas (by old style)","MD",2043 +"2043-01-08","Christmas (by old style)","MD",2043 +"2043-03-08","International Women's Day","MD",2043 +"2043-05-01","International Workers' Solidarity Day","MD",2043 +"2043-05-03","Easter","MD",2043 +"2043-05-04","Easter","MD",2043 +"2043-05-09","Europe Day","MD",2043 +"2043-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2043 +"2043-05-11","Day of Rejoicing","MD",2043 +"2043-06-01","International Children's Day","MD",2043 +"2043-08-27","Republic of Moldova Independence Day","MD",2043 +"2043-08-31","National Language Day","MD",2043 +"2043-12-25","Christmas (by new style)","MD",2043 +"2044-01-01","New Year's Day","MD",2044 +"2044-01-07","Christmas (by old style)","MD",2044 +"2044-01-08","Christmas (by old style)","MD",2044 +"2044-03-08","International Women's Day","MD",2044 +"2044-04-24","Easter","MD",2044 +"2044-04-25","Easter","MD",2044 +"2044-05-01","International Workers' Solidarity Day","MD",2044 +"2044-05-02","Day of Rejoicing","MD",2044 +"2044-05-09","Europe Day","MD",2044 +"2044-05-09","Victory Day and Commemoration of the heroes fallen for Independence of Fatherland","MD",2044 +"2044-06-01","International Children's Day","MD",2044 +"2044-08-27","Republic of Moldova Independence Day","MD",2044 +"2044-08-31","National Language Day","MD",2044 +"2044-12-25","Christmas (by new style)","MD",2044 +"1995-01-01","New Year's Day","ME",1995 +"1995-01-02","New Year's Day (Observed)","ME",1995 +"1995-01-03","New Year's Day (Observed)","ME",1995 +"1995-01-06","Orthodox Christmas Eve","ME",1995 +"1995-01-07","Orthodox Christmas","ME",1995 +"1995-04-21","Orthodox Good Friday","ME",1995 +"1995-04-23","Orthodox Easter Sunday","ME",1995 +"1995-04-24","Orthodox Easter Monday","ME",1995 +"1995-05-01","Labour Day","ME",1995 +"1995-05-02","Labour Day","ME",1995 +"1995-05-21","Independence Day","ME",1995 +"1995-05-22","Independence Day (Observed)","ME",1995 +"1995-05-23","Independence Day (Observed)","ME",1995 +"1995-07-13","Statehood Day","ME",1995 +"1995-07-14","Statehood Day","ME",1995 +"1996-01-01","New Year's Day","ME",1996 +"1996-01-02","New Year's Day","ME",1996 +"1996-01-06","Orthodox Christmas Eve","ME",1996 +"1996-01-07","Orthodox Christmas","ME",1996 +"1996-04-12","Orthodox Good Friday","ME",1996 +"1996-04-14","Orthodox Easter Sunday","ME",1996 +"1996-04-15","Orthodox Easter Monday","ME",1996 +"1996-05-01","Labour Day","ME",1996 +"1996-05-02","Labour Day","ME",1996 +"1996-05-21","Independence Day","ME",1996 +"1996-05-22","Independence Day","ME",1996 +"1996-07-13","Statehood Day","ME",1996 +"1996-07-14","Statehood Day","ME",1996 +"1996-07-15","Statehood Day (Observed)","ME",1996 +"1997-01-01","New Year's Day","ME",1997 +"1997-01-02","New Year's Day","ME",1997 +"1997-01-06","Orthodox Christmas Eve","ME",1997 +"1997-01-07","Orthodox Christmas","ME",1997 +"1997-04-25","Orthodox Good Friday","ME",1997 +"1997-04-27","Orthodox Easter Sunday","ME",1997 +"1997-04-28","Orthodox Easter Monday","ME",1997 +"1997-05-01","Labour Day","ME",1997 +"1997-05-02","Labour Day","ME",1997 +"1997-05-21","Independence Day","ME",1997 +"1997-05-22","Independence Day","ME",1997 +"1997-07-13","Statehood Day","ME",1997 +"1997-07-14","Statehood Day (Observed)","ME",1997 +"1997-07-15","Statehood Day (Observed)","ME",1997 +"1998-01-01","New Year's Day","ME",1998 +"1998-01-02","New Year's Day","ME",1998 +"1998-01-06","Orthodox Christmas Eve","ME",1998 +"1998-01-07","Orthodox Christmas","ME",1998 +"1998-04-17","Orthodox Good Friday","ME",1998 +"1998-04-19","Orthodox Easter Sunday","ME",1998 +"1998-04-20","Orthodox Easter Monday","ME",1998 +"1998-05-01","Labour Day","ME",1998 +"1998-05-02","Labour Day","ME",1998 +"1998-05-21","Independence Day","ME",1998 +"1998-05-22","Independence Day","ME",1998 +"1998-07-13","Statehood Day","ME",1998 +"1998-07-14","Statehood Day","ME",1998 +"1999-01-01","New Year's Day","ME",1999 +"1999-01-02","New Year's Day","ME",1999 +"1999-01-06","Orthodox Christmas Eve","ME",1999 +"1999-01-07","Orthodox Christmas","ME",1999 +"1999-04-09","Orthodox Good Friday","ME",1999 +"1999-04-11","Orthodox Easter Sunday","ME",1999 +"1999-04-12","Orthodox Easter Monday","ME",1999 +"1999-05-01","Labour Day","ME",1999 +"1999-05-02","Labour Day","ME",1999 +"1999-05-03","Labour Day (Observed)","ME",1999 +"1999-05-21","Independence Day","ME",1999 +"1999-05-22","Independence Day","ME",1999 +"1999-07-13","Statehood Day","ME",1999 +"1999-07-14","Statehood Day","ME",1999 +"2000-01-01","New Year's Day","ME",2000 +"2000-01-02","New Year's Day","ME",2000 +"2000-01-03","New Year's Day (Observed)","ME",2000 +"2000-01-06","Orthodox Christmas Eve","ME",2000 +"2000-01-07","Orthodox Christmas","ME",2000 +"2000-04-28","Orthodox Good Friday","ME",2000 +"2000-04-30","Orthodox Easter Sunday","ME",2000 +"2000-05-01","Labour Day","ME",2000 +"2000-05-01","Orthodox Easter Monday","ME",2000 +"2000-05-02","Labour Day","ME",2000 +"2000-05-21","Independence Day","ME",2000 +"2000-05-22","Independence Day (Observed)","ME",2000 +"2000-05-23","Independence Day (Observed)","ME",2000 +"2000-07-13","Statehood Day","ME",2000 +"2000-07-14","Statehood Day","ME",2000 +"2001-01-01","New Year's Day","ME",2001 +"2001-01-02","New Year's Day","ME",2001 +"2001-01-06","Orthodox Christmas Eve","ME",2001 +"2001-01-07","Orthodox Christmas","ME",2001 +"2001-04-13","Orthodox Good Friday","ME",2001 +"2001-04-15","Orthodox Easter Sunday","ME",2001 +"2001-04-16","Orthodox Easter Monday","ME",2001 +"2001-05-01","Labour Day","ME",2001 +"2001-05-02","Labour Day","ME",2001 +"2001-05-21","Independence Day","ME",2001 +"2001-05-22","Independence Day","ME",2001 +"2001-07-13","Statehood Day","ME",2001 +"2001-07-14","Statehood Day","ME",2001 +"2002-01-01","New Year's Day","ME",2002 +"2002-01-02","New Year's Day","ME",2002 +"2002-01-06","Orthodox Christmas Eve","ME",2002 +"2002-01-07","Orthodox Christmas","ME",2002 +"2002-05-01","Labour Day","ME",2002 +"2002-05-02","Labour Day","ME",2002 +"2002-05-03","Orthodox Good Friday","ME",2002 +"2002-05-05","Orthodox Easter Sunday","ME",2002 +"2002-05-06","Orthodox Easter Monday","ME",2002 +"2002-05-21","Independence Day","ME",2002 +"2002-05-22","Independence Day","ME",2002 +"2002-07-13","Statehood Day","ME",2002 +"2002-07-14","Statehood Day","ME",2002 +"2002-07-15","Statehood Day (Observed)","ME",2002 +"2003-01-01","New Year's Day","ME",2003 +"2003-01-02","New Year's Day","ME",2003 +"2003-01-06","Orthodox Christmas Eve","ME",2003 +"2003-01-07","Orthodox Christmas","ME",2003 +"2003-04-25","Orthodox Good Friday","ME",2003 +"2003-04-27","Orthodox Easter Sunday","ME",2003 +"2003-04-28","Orthodox Easter Monday","ME",2003 +"2003-05-01","Labour Day","ME",2003 +"2003-05-02","Labour Day","ME",2003 +"2003-05-21","Independence Day","ME",2003 +"2003-05-22","Independence Day","ME",2003 +"2003-07-13","Statehood Day","ME",2003 +"2003-07-14","Statehood Day (Observed)","ME",2003 +"2003-07-15","Statehood Day (Observed)","ME",2003 +"2004-01-01","New Year's Day","ME",2004 +"2004-01-02","New Year's Day","ME",2004 +"2004-01-06","Orthodox Christmas Eve","ME",2004 +"2004-01-07","Orthodox Christmas","ME",2004 +"2004-04-09","Orthodox Good Friday","ME",2004 +"2004-04-11","Orthodox Easter Sunday","ME",2004 +"2004-04-12","Orthodox Easter Monday","ME",2004 +"2004-05-01","Labour Day","ME",2004 +"2004-05-02","Labour Day","ME",2004 +"2004-05-03","Labour Day (Observed)","ME",2004 +"2004-05-21","Independence Day","ME",2004 +"2004-05-22","Independence Day","ME",2004 +"2004-07-13","Statehood Day","ME",2004 +"2004-07-14","Statehood Day","ME",2004 +"2005-01-01","New Year's Day","ME",2005 +"2005-01-02","New Year's Day","ME",2005 +"2005-01-03","New Year's Day (Observed)","ME",2005 +"2005-01-06","Orthodox Christmas Eve","ME",2005 +"2005-01-07","Orthodox Christmas","ME",2005 +"2005-04-29","Orthodox Good Friday","ME",2005 +"2005-05-01","Labour Day","ME",2005 +"2005-05-01","Orthodox Easter Sunday","ME",2005 +"2005-05-02","Labour Day (Observed)","ME",2005 +"2005-05-02","Orthodox Easter Monday","ME",2005 +"2005-05-03","Labour Day (Observed)","ME",2005 +"2005-05-21","Independence Day","ME",2005 +"2005-05-22","Independence Day","ME",2005 +"2005-05-23","Independence Day (Observed)","ME",2005 +"2005-07-13","Statehood Day","ME",2005 +"2005-07-14","Statehood Day","ME",2005 +"2006-01-01","New Year's Day","ME",2006 +"2006-01-02","New Year's Day (Observed)","ME",2006 +"2006-01-03","New Year's Day (Observed)","ME",2006 +"2006-01-06","Orthodox Christmas Eve","ME",2006 +"2006-01-07","Orthodox Christmas","ME",2006 +"2006-04-21","Orthodox Good Friday","ME",2006 +"2006-04-23","Orthodox Easter Sunday","ME",2006 +"2006-04-24","Orthodox Easter Monday","ME",2006 +"2006-05-01","Labour Day","ME",2006 +"2006-05-02","Labour Day","ME",2006 +"2006-05-21","Independence Day","ME",2006 +"2006-05-22","Independence Day (Observed)","ME",2006 +"2006-05-23","Independence Day (Observed)","ME",2006 +"2006-07-13","Statehood Day","ME",2006 +"2006-07-14","Statehood Day","ME",2006 +"2007-01-01","New Year's Day","ME",2007 +"2007-01-02","New Year's Day","ME",2007 +"2007-01-06","Orthodox Christmas Eve","ME",2007 +"2007-01-07","Orthodox Christmas","ME",2007 +"2007-04-06","Orthodox Good Friday","ME",2007 +"2007-04-08","Orthodox Easter Sunday","ME",2007 +"2007-04-09","Orthodox Easter Monday","ME",2007 +"2007-05-01","Labour Day","ME",2007 +"2007-05-02","Labour Day","ME",2007 +"2007-05-21","Independence Day","ME",2007 +"2007-05-22","Independence Day","ME",2007 +"2007-07-13","Statehood Day","ME",2007 +"2007-07-14","Statehood Day","ME",2007 +"2008-01-01","New Year's Day","ME",2008 +"2008-01-02","New Year's Day","ME",2008 +"2008-01-06","Orthodox Christmas Eve","ME",2008 +"2008-01-07","Orthodox Christmas","ME",2008 +"2008-04-25","Orthodox Good Friday","ME",2008 +"2008-04-27","Orthodox Easter Sunday","ME",2008 +"2008-04-28","Orthodox Easter Monday","ME",2008 +"2008-05-01","Labour Day","ME",2008 +"2008-05-02","Labour Day","ME",2008 +"2008-05-21","Independence Day","ME",2008 +"2008-05-22","Independence Day","ME",2008 +"2008-07-13","Statehood Day","ME",2008 +"2008-07-14","Statehood Day (Observed)","ME",2008 +"2008-07-15","Statehood Day (Observed)","ME",2008 +"2009-01-01","New Year's Day","ME",2009 +"2009-01-02","New Year's Day","ME",2009 +"2009-01-06","Orthodox Christmas Eve","ME",2009 +"2009-01-07","Orthodox Christmas","ME",2009 +"2009-04-17","Orthodox Good Friday","ME",2009 +"2009-04-19","Orthodox Easter Sunday","ME",2009 +"2009-04-20","Orthodox Easter Monday","ME",2009 +"2009-05-01","Labour Day","ME",2009 +"2009-05-02","Labour Day","ME",2009 +"2009-05-21","Independence Day","ME",2009 +"2009-05-22","Independence Day","ME",2009 +"2009-07-13","Statehood Day","ME",2009 +"2009-07-14","Statehood Day","ME",2009 +"2010-01-01","New Year's Day","ME",2010 +"2010-01-02","New Year's Day","ME",2010 +"2010-01-06","Orthodox Christmas Eve","ME",2010 +"2010-01-07","Orthodox Christmas","ME",2010 +"2010-04-02","Orthodox Good Friday","ME",2010 +"2010-04-04","Orthodox Easter Sunday","ME",2010 +"2010-04-05","Orthodox Easter Monday","ME",2010 +"2010-05-01","Labour Day","ME",2010 +"2010-05-02","Labour Day","ME",2010 +"2010-05-03","Labour Day (Observed)","ME",2010 +"2010-05-21","Independence Day","ME",2010 +"2010-05-22","Independence Day","ME",2010 +"2010-07-13","Statehood Day","ME",2010 +"2010-07-14","Statehood Day","ME",2010 +"2011-01-01","New Year's Day","ME",2011 +"2011-01-02","New Year's Day","ME",2011 +"2011-01-03","New Year's Day (Observed)","ME",2011 +"2011-01-06","Orthodox Christmas Eve","ME",2011 +"2011-01-07","Orthodox Christmas","ME",2011 +"2011-04-22","Orthodox Good Friday","ME",2011 +"2011-04-24","Orthodox Easter Sunday","ME",2011 +"2011-04-25","Orthodox Easter Monday","ME",2011 +"2011-05-01","Labour Day","ME",2011 +"2011-05-02","Labour Day (Observed)","ME",2011 +"2011-05-03","Labour Day (Observed)","ME",2011 +"2011-05-21","Independence Day","ME",2011 +"2011-05-22","Independence Day","ME",2011 +"2011-05-23","Independence Day (Observed)","ME",2011 +"2011-07-13","Statehood Day","ME",2011 +"2011-07-14","Statehood Day","ME",2011 +"2012-01-01","New Year's Day","ME",2012 +"2012-01-02","New Year's Day (Observed)","ME",2012 +"2012-01-03","New Year's Day (Observed)","ME",2012 +"2012-01-06","Orthodox Christmas Eve","ME",2012 +"2012-01-07","Orthodox Christmas","ME",2012 +"2012-04-13","Orthodox Good Friday","ME",2012 +"2012-04-15","Orthodox Easter Sunday","ME",2012 +"2012-04-16","Orthodox Easter Monday","ME",2012 +"2012-05-01","Labour Day","ME",2012 +"2012-05-02","Labour Day","ME",2012 +"2012-05-21","Independence Day","ME",2012 +"2012-05-22","Independence Day","ME",2012 +"2012-07-13","Statehood Day","ME",2012 +"2012-07-14","Statehood Day","ME",2012 +"2013-01-01","New Year's Day","ME",2013 +"2013-01-02","New Year's Day","ME",2013 +"2013-01-06","Orthodox Christmas Eve","ME",2013 +"2013-01-07","Orthodox Christmas","ME",2013 +"2013-05-01","Labour Day","ME",2013 +"2013-05-02","Labour Day","ME",2013 +"2013-05-03","Orthodox Good Friday","ME",2013 +"2013-05-05","Orthodox Easter Sunday","ME",2013 +"2013-05-06","Orthodox Easter Monday","ME",2013 +"2013-05-21","Independence Day","ME",2013 +"2013-05-22","Independence Day","ME",2013 +"2013-07-13","Statehood Day","ME",2013 +"2013-07-14","Statehood Day","ME",2013 +"2013-07-15","Statehood Day (Observed)","ME",2013 +"2014-01-01","New Year's Day","ME",2014 +"2014-01-02","New Year's Day","ME",2014 +"2014-01-06","Orthodox Christmas Eve","ME",2014 +"2014-01-07","Orthodox Christmas","ME",2014 +"2014-04-18","Orthodox Good Friday","ME",2014 +"2014-04-20","Orthodox Easter Sunday","ME",2014 +"2014-04-21","Orthodox Easter Monday","ME",2014 +"2014-05-01","Labour Day","ME",2014 +"2014-05-02","Labour Day","ME",2014 +"2014-05-21","Independence Day","ME",2014 +"2014-05-22","Independence Day","ME",2014 +"2014-07-13","Statehood Day","ME",2014 +"2014-07-14","Statehood Day (Observed)","ME",2014 +"2014-07-15","Statehood Day (Observed)","ME",2014 +"2015-01-01","New Year's Day","ME",2015 +"2015-01-02","New Year's Day","ME",2015 +"2015-01-06","Orthodox Christmas Eve","ME",2015 +"2015-01-07","Orthodox Christmas","ME",2015 +"2015-04-10","Orthodox Good Friday","ME",2015 +"2015-04-12","Orthodox Easter Sunday","ME",2015 +"2015-04-13","Orthodox Easter Monday","ME",2015 +"2015-05-01","Labour Day","ME",2015 +"2015-05-02","Labour Day","ME",2015 +"2015-05-21","Independence Day","ME",2015 +"2015-05-22","Independence Day","ME",2015 +"2015-07-13","Statehood Day","ME",2015 +"2015-07-14","Statehood Day","ME",2015 +"2016-01-01","New Year's Day","ME",2016 +"2016-01-02","New Year's Day","ME",2016 +"2016-01-06","Orthodox Christmas Eve","ME",2016 +"2016-01-07","Orthodox Christmas","ME",2016 +"2016-04-29","Orthodox Good Friday","ME",2016 +"2016-05-01","Labour Day","ME",2016 +"2016-05-01","Orthodox Easter Sunday","ME",2016 +"2016-05-02","Labour Day (Observed)","ME",2016 +"2016-05-02","Orthodox Easter Monday","ME",2016 +"2016-05-03","Labour Day (Observed)","ME",2016 +"2016-05-21","Independence Day","ME",2016 +"2016-05-22","Independence Day","ME",2016 +"2016-05-23","Independence Day (Observed)","ME",2016 +"2016-07-13","Statehood Day","ME",2016 +"2016-07-14","Statehood Day","ME",2016 +"2017-01-01","New Year's Day","ME",2017 +"2017-01-02","New Year's Day (Observed)","ME",2017 +"2017-01-03","New Year's Day (Observed)","ME",2017 +"2017-01-06","Orthodox Christmas Eve","ME",2017 +"2017-01-07","Orthodox Christmas","ME",2017 +"2017-04-14","Orthodox Good Friday","ME",2017 +"2017-04-16","Orthodox Easter Sunday","ME",2017 +"2017-04-17","Orthodox Easter Monday","ME",2017 +"2017-05-01","Labour Day","ME",2017 +"2017-05-02","Labour Day","ME",2017 +"2017-05-21","Independence Day","ME",2017 +"2017-05-22","Independence Day (Observed)","ME",2017 +"2017-05-23","Independence Day (Observed)","ME",2017 +"2017-07-13","Statehood Day","ME",2017 +"2017-07-14","Statehood Day","ME",2017 +"2018-01-01","New Year's Day","ME",2018 +"2018-01-02","New Year's Day","ME",2018 +"2018-01-06","Orthodox Christmas Eve","ME",2018 +"2018-01-07","Orthodox Christmas","ME",2018 +"2018-04-06","Orthodox Good Friday","ME",2018 +"2018-04-08","Orthodox Easter Sunday","ME",2018 +"2018-04-09","Orthodox Easter Monday","ME",2018 +"2018-05-01","Labour Day","ME",2018 +"2018-05-02","Labour Day","ME",2018 +"2018-05-21","Independence Day","ME",2018 +"2018-05-22","Independence Day","ME",2018 +"2018-07-13","Statehood Day","ME",2018 +"2018-07-14","Statehood Day","ME",2018 +"2019-01-01","New Year's Day","ME",2019 +"2019-01-02","New Year's Day","ME",2019 +"2019-01-06","Orthodox Christmas Eve","ME",2019 +"2019-01-07","Orthodox Christmas","ME",2019 +"2019-04-26","Orthodox Good Friday","ME",2019 +"2019-04-28","Orthodox Easter Sunday","ME",2019 +"2019-04-29","Orthodox Easter Monday","ME",2019 +"2019-05-01","Labour Day","ME",2019 +"2019-05-02","Labour Day","ME",2019 +"2019-05-21","Independence Day","ME",2019 +"2019-05-22","Independence Day","ME",2019 +"2019-07-13","Statehood Day","ME",2019 +"2019-07-14","Statehood Day","ME",2019 +"2019-07-15","Statehood Day (Observed)","ME",2019 +"2020-01-01","New Year's Day","ME",2020 +"2020-01-02","New Year's Day","ME",2020 +"2020-01-06","Orthodox Christmas Eve","ME",2020 +"2020-01-07","Orthodox Christmas","ME",2020 +"2020-04-17","Orthodox Good Friday","ME",2020 +"2020-04-19","Orthodox Easter Sunday","ME",2020 +"2020-04-20","Orthodox Easter Monday","ME",2020 +"2020-05-01","Labour Day","ME",2020 +"2020-05-02","Labour Day","ME",2020 +"2020-05-21","Independence Day","ME",2020 +"2020-05-22","Independence Day","ME",2020 +"2020-07-13","Statehood Day","ME",2020 +"2020-07-14","Statehood Day","ME",2020 +"2021-01-01","New Year's Day","ME",2021 +"2021-01-02","New Year's Day","ME",2021 +"2021-01-06","Orthodox Christmas Eve","ME",2021 +"2021-01-07","Orthodox Christmas","ME",2021 +"2021-04-30","Orthodox Good Friday","ME",2021 +"2021-05-01","Labour Day","ME",2021 +"2021-05-02","Labour Day","ME",2021 +"2021-05-02","Orthodox Easter Sunday","ME",2021 +"2021-05-03","Labour Day (Observed)","ME",2021 +"2021-05-03","Orthodox Easter Monday","ME",2021 +"2021-05-21","Independence Day","ME",2021 +"2021-05-22","Independence Day","ME",2021 +"2021-07-13","Statehood Day","ME",2021 +"2021-07-14","Statehood Day","ME",2021 +"2022-01-01","New Year's Day","ME",2022 +"2022-01-02","New Year's Day","ME",2022 +"2022-01-03","New Year's Day (Observed)","ME",2022 +"2022-01-06","Orthodox Christmas Eve","ME",2022 +"2022-01-07","Orthodox Christmas","ME",2022 +"2022-04-22","Orthodox Good Friday","ME",2022 +"2022-04-24","Orthodox Easter Sunday","ME",2022 +"2022-04-25","Orthodox Easter Monday","ME",2022 +"2022-05-01","Labour Day","ME",2022 +"2022-05-02","Labour Day (Observed)","ME",2022 +"2022-05-03","Labour Day (Observed)","ME",2022 +"2022-05-21","Independence Day","ME",2022 +"2022-05-22","Independence Day","ME",2022 +"2022-05-23","Independence Day (Observed)","ME",2022 +"2022-07-13","Statehood Day","ME",2022 +"2022-07-14","Statehood Day","ME",2022 +"2023-01-01","New Year's Day","ME",2023 +"2023-01-02","New Year's Day (Observed)","ME",2023 +"2023-01-03","New Year's Day (Observed)","ME",2023 +"2023-01-06","Orthodox Christmas Eve","ME",2023 +"2023-01-07","Orthodox Christmas","ME",2023 +"2023-04-14","Orthodox Good Friday","ME",2023 +"2023-04-16","Orthodox Easter Sunday","ME",2023 +"2023-04-17","Orthodox Easter Monday","ME",2023 +"2023-05-01","Labour Day","ME",2023 +"2023-05-02","Labour Day","ME",2023 +"2023-05-21","Independence Day","ME",2023 +"2023-05-22","Independence Day (Observed)","ME",2023 +"2023-05-23","Independence Day (Observed)","ME",2023 +"2023-07-13","Statehood Day","ME",2023 +"2023-07-14","Statehood Day","ME",2023 +"2024-01-01","New Year's Day","ME",2024 +"2024-01-02","New Year's Day","ME",2024 +"2024-01-06","Orthodox Christmas Eve","ME",2024 +"2024-01-07","Orthodox Christmas","ME",2024 +"2024-05-01","Labour Day","ME",2024 +"2024-05-02","Labour Day","ME",2024 +"2024-05-03","Orthodox Good Friday","ME",2024 +"2024-05-05","Orthodox Easter Sunday","ME",2024 +"2024-05-06","Orthodox Easter Monday","ME",2024 +"2024-05-21","Independence Day","ME",2024 +"2024-05-22","Independence Day","ME",2024 +"2024-07-13","Statehood Day","ME",2024 +"2024-07-14","Statehood Day","ME",2024 +"2024-07-15","Statehood Day (Observed)","ME",2024 +"2025-01-01","New Year's Day","ME",2025 +"2025-01-02","New Year's Day","ME",2025 +"2025-01-06","Orthodox Christmas Eve","ME",2025 +"2025-01-07","Orthodox Christmas","ME",2025 +"2025-04-18","Orthodox Good Friday","ME",2025 +"2025-04-20","Orthodox Easter Sunday","ME",2025 +"2025-04-21","Orthodox Easter Monday","ME",2025 +"2025-05-01","Labour Day","ME",2025 +"2025-05-02","Labour Day","ME",2025 +"2025-05-21","Independence Day","ME",2025 +"2025-05-22","Independence Day","ME",2025 +"2025-07-13","Statehood Day","ME",2025 +"2025-07-14","Statehood Day (Observed)","ME",2025 +"2025-07-15","Statehood Day (Observed)","ME",2025 +"2026-01-01","New Year's Day","ME",2026 +"2026-01-02","New Year's Day","ME",2026 +"2026-01-06","Orthodox Christmas Eve","ME",2026 +"2026-01-07","Orthodox Christmas","ME",2026 +"2026-04-10","Orthodox Good Friday","ME",2026 +"2026-04-12","Orthodox Easter Sunday","ME",2026 +"2026-04-13","Orthodox Easter Monday","ME",2026 +"2026-05-01","Labour Day","ME",2026 +"2026-05-02","Labour Day","ME",2026 +"2026-05-21","Independence Day","ME",2026 +"2026-05-22","Independence Day","ME",2026 +"2026-07-13","Statehood Day","ME",2026 +"2026-07-14","Statehood Day","ME",2026 +"2027-01-01","New Year's Day","ME",2027 +"2027-01-02","New Year's Day","ME",2027 +"2027-01-06","Orthodox Christmas Eve","ME",2027 +"2027-01-07","Orthodox Christmas","ME",2027 +"2027-04-30","Orthodox Good Friday","ME",2027 +"2027-05-01","Labour Day","ME",2027 +"2027-05-02","Labour Day","ME",2027 +"2027-05-02","Orthodox Easter Sunday","ME",2027 +"2027-05-03","Labour Day (Observed)","ME",2027 +"2027-05-03","Orthodox Easter Monday","ME",2027 +"2027-05-21","Independence Day","ME",2027 +"2027-05-22","Independence Day","ME",2027 +"2027-07-13","Statehood Day","ME",2027 +"2027-07-14","Statehood Day","ME",2027 +"2028-01-01","New Year's Day","ME",2028 +"2028-01-02","New Year's Day","ME",2028 +"2028-01-03","New Year's Day (Observed)","ME",2028 +"2028-01-06","Orthodox Christmas Eve","ME",2028 +"2028-01-07","Orthodox Christmas","ME",2028 +"2028-04-14","Orthodox Good Friday","ME",2028 +"2028-04-16","Orthodox Easter Sunday","ME",2028 +"2028-04-17","Orthodox Easter Monday","ME",2028 +"2028-05-01","Labour Day","ME",2028 +"2028-05-02","Labour Day","ME",2028 +"2028-05-21","Independence Day","ME",2028 +"2028-05-22","Independence Day (Observed)","ME",2028 +"2028-05-23","Independence Day (Observed)","ME",2028 +"2028-07-13","Statehood Day","ME",2028 +"2028-07-14","Statehood Day","ME",2028 +"2029-01-01","New Year's Day","ME",2029 +"2029-01-02","New Year's Day","ME",2029 +"2029-01-06","Orthodox Christmas Eve","ME",2029 +"2029-01-07","Orthodox Christmas","ME",2029 +"2029-04-06","Orthodox Good Friday","ME",2029 +"2029-04-08","Orthodox Easter Sunday","ME",2029 +"2029-04-09","Orthodox Easter Monday","ME",2029 +"2029-05-01","Labour Day","ME",2029 +"2029-05-02","Labour Day","ME",2029 +"2029-05-21","Independence Day","ME",2029 +"2029-05-22","Independence Day","ME",2029 +"2029-07-13","Statehood Day","ME",2029 +"2029-07-14","Statehood Day","ME",2029 +"2030-01-01","New Year's Day","ME",2030 +"2030-01-02","New Year's Day","ME",2030 +"2030-01-06","Orthodox Christmas Eve","ME",2030 +"2030-01-07","Orthodox Christmas","ME",2030 +"2030-04-26","Orthodox Good Friday","ME",2030 +"2030-04-28","Orthodox Easter Sunday","ME",2030 +"2030-04-29","Orthodox Easter Monday","ME",2030 +"2030-05-01","Labour Day","ME",2030 +"2030-05-02","Labour Day","ME",2030 +"2030-05-21","Independence Day","ME",2030 +"2030-05-22","Independence Day","ME",2030 +"2030-07-13","Statehood Day","ME",2030 +"2030-07-14","Statehood Day","ME",2030 +"2030-07-15","Statehood Day (Observed)","ME",2030 +"2031-01-01","New Year's Day","ME",2031 +"2031-01-02","New Year's Day","ME",2031 +"2031-01-06","Orthodox Christmas Eve","ME",2031 +"2031-01-07","Orthodox Christmas","ME",2031 +"2031-04-11","Orthodox Good Friday","ME",2031 +"2031-04-13","Orthodox Easter Sunday","ME",2031 +"2031-04-14","Orthodox Easter Monday","ME",2031 +"2031-05-01","Labour Day","ME",2031 +"2031-05-02","Labour Day","ME",2031 +"2031-05-21","Independence Day","ME",2031 +"2031-05-22","Independence Day","ME",2031 +"2031-07-13","Statehood Day","ME",2031 +"2031-07-14","Statehood Day (Observed)","ME",2031 +"2031-07-15","Statehood Day (Observed)","ME",2031 +"2032-01-01","New Year's Day","ME",2032 +"2032-01-02","New Year's Day","ME",2032 +"2032-01-06","Orthodox Christmas Eve","ME",2032 +"2032-01-07","Orthodox Christmas","ME",2032 +"2032-04-30","Orthodox Good Friday","ME",2032 +"2032-05-01","Labour Day","ME",2032 +"2032-05-02","Labour Day","ME",2032 +"2032-05-02","Orthodox Easter Sunday","ME",2032 +"2032-05-03","Labour Day (Observed)","ME",2032 +"2032-05-03","Orthodox Easter Monday","ME",2032 +"2032-05-21","Independence Day","ME",2032 +"2032-05-22","Independence Day","ME",2032 +"2032-07-13","Statehood Day","ME",2032 +"2032-07-14","Statehood Day","ME",2032 +"2033-01-01","New Year's Day","ME",2033 +"2033-01-02","New Year's Day","ME",2033 +"2033-01-03","New Year's Day (Observed)","ME",2033 +"2033-01-06","Orthodox Christmas Eve","ME",2033 +"2033-01-07","Orthodox Christmas","ME",2033 +"2033-04-22","Orthodox Good Friday","ME",2033 +"2033-04-24","Orthodox Easter Sunday","ME",2033 +"2033-04-25","Orthodox Easter Monday","ME",2033 +"2033-05-01","Labour Day","ME",2033 +"2033-05-02","Labour Day (Observed)","ME",2033 +"2033-05-03","Labour Day (Observed)","ME",2033 +"2033-05-21","Independence Day","ME",2033 +"2033-05-22","Independence Day","ME",2033 +"2033-05-23","Independence Day (Observed)","ME",2033 +"2033-07-13","Statehood Day","ME",2033 +"2033-07-14","Statehood Day","ME",2033 +"2034-01-01","New Year's Day","ME",2034 +"2034-01-02","New Year's Day (Observed)","ME",2034 +"2034-01-03","New Year's Day (Observed)","ME",2034 +"2034-01-06","Orthodox Christmas Eve","ME",2034 +"2034-01-07","Orthodox Christmas","ME",2034 +"2034-04-07","Orthodox Good Friday","ME",2034 +"2034-04-09","Orthodox Easter Sunday","ME",2034 +"2034-04-10","Orthodox Easter Monday","ME",2034 +"2034-05-01","Labour Day","ME",2034 +"2034-05-02","Labour Day","ME",2034 +"2034-05-21","Independence Day","ME",2034 +"2034-05-22","Independence Day (Observed)","ME",2034 +"2034-05-23","Independence Day (Observed)","ME",2034 +"2034-07-13","Statehood Day","ME",2034 +"2034-07-14","Statehood Day","ME",2034 +"2035-01-01","New Year's Day","ME",2035 +"2035-01-02","New Year's Day","ME",2035 +"2035-01-06","Orthodox Christmas Eve","ME",2035 +"2035-01-07","Orthodox Christmas","ME",2035 +"2035-04-27","Orthodox Good Friday","ME",2035 +"2035-04-29","Orthodox Easter Sunday","ME",2035 +"2035-04-30","Orthodox Easter Monday","ME",2035 +"2035-05-01","Labour Day","ME",2035 +"2035-05-02","Labour Day","ME",2035 +"2035-05-21","Independence Day","ME",2035 +"2035-05-22","Independence Day","ME",2035 +"2035-07-13","Statehood Day","ME",2035 +"2035-07-14","Statehood Day","ME",2035 +"2036-01-01","New Year's Day","ME",2036 +"2036-01-02","New Year's Day","ME",2036 +"2036-01-06","Orthodox Christmas Eve","ME",2036 +"2036-01-07","Orthodox Christmas","ME",2036 +"2036-04-18","Orthodox Good Friday","ME",2036 +"2036-04-20","Orthodox Easter Sunday","ME",2036 +"2036-04-21","Orthodox Easter Monday","ME",2036 +"2036-05-01","Labour Day","ME",2036 +"2036-05-02","Labour Day","ME",2036 +"2036-05-21","Independence Day","ME",2036 +"2036-05-22","Independence Day","ME",2036 +"2036-07-13","Statehood Day","ME",2036 +"2036-07-14","Statehood Day (Observed)","ME",2036 +"2036-07-15","Statehood Day (Observed)","ME",2036 +"2037-01-01","New Year's Day","ME",2037 +"2037-01-02","New Year's Day","ME",2037 +"2037-01-06","Orthodox Christmas Eve","ME",2037 +"2037-01-07","Orthodox Christmas","ME",2037 +"2037-04-03","Orthodox Good Friday","ME",2037 +"2037-04-05","Orthodox Easter Sunday","ME",2037 +"2037-04-06","Orthodox Easter Monday","ME",2037 +"2037-05-01","Labour Day","ME",2037 +"2037-05-02","Labour Day","ME",2037 +"2037-05-21","Independence Day","ME",2037 +"2037-05-22","Independence Day","ME",2037 +"2037-07-13","Statehood Day","ME",2037 +"2037-07-14","Statehood Day","ME",2037 +"2038-01-01","New Year's Day","ME",2038 +"2038-01-02","New Year's Day","ME",2038 +"2038-01-06","Orthodox Christmas Eve","ME",2038 +"2038-01-07","Orthodox Christmas","ME",2038 +"2038-04-23","Orthodox Good Friday","ME",2038 +"2038-04-25","Orthodox Easter Sunday","ME",2038 +"2038-04-26","Orthodox Easter Monday","ME",2038 +"2038-05-01","Labour Day","ME",2038 +"2038-05-02","Labour Day","ME",2038 +"2038-05-03","Labour Day (Observed)","ME",2038 +"2038-05-21","Independence Day","ME",2038 +"2038-05-22","Independence Day","ME",2038 +"2038-07-13","Statehood Day","ME",2038 +"2038-07-14","Statehood Day","ME",2038 +"2039-01-01","New Year's Day","ME",2039 +"2039-01-02","New Year's Day","ME",2039 +"2039-01-03","New Year's Day (Observed)","ME",2039 +"2039-01-06","Orthodox Christmas Eve","ME",2039 +"2039-01-07","Orthodox Christmas","ME",2039 +"2039-04-15","Orthodox Good Friday","ME",2039 +"2039-04-17","Orthodox Easter Sunday","ME",2039 +"2039-04-18","Orthodox Easter Monday","ME",2039 +"2039-05-01","Labour Day","ME",2039 +"2039-05-02","Labour Day (Observed)","ME",2039 +"2039-05-03","Labour Day (Observed)","ME",2039 +"2039-05-21","Independence Day","ME",2039 +"2039-05-22","Independence Day","ME",2039 +"2039-05-23","Independence Day (Observed)","ME",2039 +"2039-07-13","Statehood Day","ME",2039 +"2039-07-14","Statehood Day","ME",2039 +"2040-01-01","New Year's Day","ME",2040 +"2040-01-02","New Year's Day (Observed)","ME",2040 +"2040-01-03","New Year's Day (Observed)","ME",2040 +"2040-01-06","Orthodox Christmas Eve","ME",2040 +"2040-01-07","Orthodox Christmas","ME",2040 +"2040-05-01","Labour Day","ME",2040 +"2040-05-02","Labour Day","ME",2040 +"2040-05-04","Orthodox Good Friday","ME",2040 +"2040-05-06","Orthodox Easter Sunday","ME",2040 +"2040-05-07","Orthodox Easter Monday","ME",2040 +"2040-05-21","Independence Day","ME",2040 +"2040-05-22","Independence Day","ME",2040 +"2040-07-13","Statehood Day","ME",2040 +"2040-07-14","Statehood Day","ME",2040 +"2041-01-01","New Year's Day","ME",2041 +"2041-01-02","New Year's Day","ME",2041 +"2041-01-06","Orthodox Christmas Eve","ME",2041 +"2041-01-07","Orthodox Christmas","ME",2041 +"2041-04-19","Orthodox Good Friday","ME",2041 +"2041-04-21","Orthodox Easter Sunday","ME",2041 +"2041-04-22","Orthodox Easter Monday","ME",2041 +"2041-05-01","Labour Day","ME",2041 +"2041-05-02","Labour Day","ME",2041 +"2041-05-21","Independence Day","ME",2041 +"2041-05-22","Independence Day","ME",2041 +"2041-07-13","Statehood Day","ME",2041 +"2041-07-14","Statehood Day","ME",2041 +"2041-07-15","Statehood Day (Observed)","ME",2041 +"2042-01-01","New Year's Day","ME",2042 +"2042-01-02","New Year's Day","ME",2042 +"2042-01-06","Orthodox Christmas Eve","ME",2042 +"2042-01-07","Orthodox Christmas","ME",2042 +"2042-04-11","Orthodox Good Friday","ME",2042 +"2042-04-13","Orthodox Easter Sunday","ME",2042 +"2042-04-14","Orthodox Easter Monday","ME",2042 +"2042-05-01","Labour Day","ME",2042 +"2042-05-02","Labour Day","ME",2042 +"2042-05-21","Independence Day","ME",2042 +"2042-05-22","Independence Day","ME",2042 +"2042-07-13","Statehood Day","ME",2042 +"2042-07-14","Statehood Day (Observed)","ME",2042 +"2042-07-15","Statehood Day (Observed)","ME",2042 +"2043-01-01","New Year's Day","ME",2043 +"2043-01-02","New Year's Day","ME",2043 +"2043-01-06","Orthodox Christmas Eve","ME",2043 +"2043-01-07","Orthodox Christmas","ME",2043 +"2043-05-01","Labour Day","ME",2043 +"2043-05-01","Orthodox Good Friday","ME",2043 +"2043-05-02","Labour Day","ME",2043 +"2043-05-03","Orthodox Easter Sunday","ME",2043 +"2043-05-04","Orthodox Easter Monday","ME",2043 +"2043-05-21","Independence Day","ME",2043 +"2043-05-22","Independence Day","ME",2043 +"2043-07-13","Statehood Day","ME",2043 +"2043-07-14","Statehood Day","ME",2043 +"2044-01-01","New Year's Day","ME",2044 +"2044-01-02","New Year's Day","ME",2044 +"2044-01-06","Orthodox Christmas Eve","ME",2044 +"2044-01-07","Orthodox Christmas","ME",2044 +"2044-04-22","Orthodox Good Friday","ME",2044 +"2044-04-24","Orthodox Easter Sunday","ME",2044 +"2044-04-25","Orthodox Easter Monday","ME",2044 +"2044-05-01","Labour Day","ME",2044 +"2044-05-02","Labour Day (Observed)","ME",2044 +"2044-05-03","Labour Day (Observed)","ME",2044 +"2044-05-21","Independence Day","ME",2044 +"2044-05-22","Independence Day","ME",2044 +"2044-05-23","Independence Day (Observed)","ME",2044 +"2044-07-13","Statehood Day","ME",2044 +"2044-07-14","Statehood Day","ME",2044 +"1995-01-01","Taom-baovao / New Year's Day","MG",1995 +"1995-03-08","Fetin'ny vehivavy / Women's Day","MG",1995 +"1995-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",1995 +"1995-04-16","Fetin'ny paska / Easter Sunday","MG",1995 +"1995-04-17","Alatsinain'ny paska / Easter Monday","MG",1995 +"1995-05-01","Labour Day","MG",1995 +"1995-05-25","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",1995 +"1995-05-28","Fetin'ny Reny / Mother's Day","MG",1995 +"1995-06-04","Pentekosta / Whit Sunday","MG",1995 +"1995-06-05","Alatsinain'ny pentekosta / Whit Monday","MG",1995 +"1995-06-18","Fetin'ny ray / Father's Day","MG",1995 +"1995-06-26","Independence Day","MG",1995 +"1995-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",1995 +"1995-11-01","Fetin'ny olo-masina / All Saints' Day","MG",1995 +"1995-12-25","Fetin'ny noely / Christmas Day","MG",1995 +"1996-01-01","Taom-baovao / New Year's Day","MG",1996 +"1996-03-08","Fetin'ny vehivavy / Women's Day","MG",1996 +"1996-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",1996 +"1996-04-07","Fetin'ny paska / Easter Sunday","MG",1996 +"1996-04-08","Alatsinain'ny paska / Easter Monday","MG",1996 +"1996-05-01","Labour Day","MG",1996 +"1996-05-16","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",1996 +"1996-05-26","Pentekosta / Whit Sunday","MG",1996 +"1996-05-27","Alatsinain'ny pentekosta / Whit Monday","MG",1996 +"1996-06-02","Fetin'ny Reny / Mother's Day","MG",1996 +"1996-06-16","Fetin'ny ray / Father's Day","MG",1996 +"1996-06-26","Independence Day","MG",1996 +"1996-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",1996 +"1996-11-01","Fetin'ny olo-masina / All Saints' Day","MG",1996 +"1996-12-25","Fetin'ny noely / Christmas Day","MG",1996 +"1997-01-01","Taom-baovao / New Year's Day","MG",1997 +"1997-03-08","Fetin'ny vehivavy / Women's Day","MG",1997 +"1997-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",1997 +"1997-03-30","Fetin'ny paska / Easter Sunday","MG",1997 +"1997-03-31","Alatsinain'ny paska / Easter Monday","MG",1997 +"1997-05-01","Labour Day","MG",1997 +"1997-05-08","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",1997 +"1997-05-18","Pentekosta / Whit Sunday","MG",1997 +"1997-05-19","Alatsinain'ny pentekosta / Whit Monday","MG",1997 +"1997-05-25","Fetin'ny Reny / Mother's Day","MG",1997 +"1997-06-15","Fetin'ny ray / Father's Day","MG",1997 +"1997-06-26","Independence Day","MG",1997 +"1997-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",1997 +"1997-11-01","Fetin'ny olo-masina / All Saints' Day","MG",1997 +"1997-12-25","Fetin'ny noely / Christmas Day","MG",1997 +"1998-01-01","Taom-baovao / New Year's Day","MG",1998 +"1998-03-08","Fetin'ny vehivavy / Women's Day","MG",1998 +"1998-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",1998 +"1998-04-12","Fetin'ny paska / Easter Sunday","MG",1998 +"1998-04-13","Alatsinain'ny paska / Easter Monday","MG",1998 +"1998-05-01","Labour Day","MG",1998 +"1998-05-21","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",1998 +"1998-05-31","Pentekosta / Whit Sunday","MG",1998 +"1998-06-01","Alatsinain'ny pentekosta / Whit Monday","MG",1998 +"1998-06-07","Fetin'ny Reny / Mother's Day","MG",1998 +"1998-06-21","Fetin'ny ray / Father's Day","MG",1998 +"1998-06-26","Independence Day","MG",1998 +"1998-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",1998 +"1998-11-01","Fetin'ny olo-masina / All Saints' Day","MG",1998 +"1998-12-25","Fetin'ny noely / Christmas Day","MG",1998 +"1999-01-01","Taom-baovao / New Year's Day","MG",1999 +"1999-03-08","Fetin'ny vehivavy / Women's Day","MG",1999 +"1999-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",1999 +"1999-04-04","Fetin'ny paska / Easter Sunday","MG",1999 +"1999-04-05","Alatsinain'ny paska / Easter Monday","MG",1999 +"1999-05-01","Labour Day","MG",1999 +"1999-05-13","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",1999 +"1999-05-23","Pentekosta / Whit Sunday","MG",1999 +"1999-05-24","Alatsinain'ny pentekosta / Whit Monday","MG",1999 +"1999-05-30","Fetin'ny Reny / Mother's Day","MG",1999 +"1999-06-20","Fetin'ny ray / Father's Day","MG",1999 +"1999-06-26","Independence Day","MG",1999 +"1999-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",1999 +"1999-11-01","Fetin'ny olo-masina / All Saints' Day","MG",1999 +"1999-12-25","Fetin'ny noely / Christmas Day","MG",1999 +"2000-01-01","Taom-baovao / New Year's Day","MG",2000 +"2000-03-08","Fetin'ny vehivavy / Women's Day","MG",2000 +"2000-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2000 +"2000-04-23","Fetin'ny paska / Easter Sunday","MG",2000 +"2000-04-24","Alatsinain'ny paska / Easter Monday","MG",2000 +"2000-05-01","Labour Day","MG",2000 +"2000-05-28","Fetin'ny Reny / Mother's Day","MG",2000 +"2000-06-01","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2000 +"2000-06-11","Pentekosta / Whit Sunday","MG",2000 +"2000-06-12","Alatsinain'ny pentekosta / Whit Monday","MG",2000 +"2000-06-18","Fetin'ny ray / Father's Day","MG",2000 +"2000-06-26","Independence Day","MG",2000 +"2000-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2000 +"2000-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2000 +"2000-12-25","Fetin'ny noely / Christmas Day","MG",2000 +"2001-01-01","Taom-baovao / New Year's Day","MG",2001 +"2001-03-08","Fetin'ny vehivavy / Women's Day","MG",2001 +"2001-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2001 +"2001-04-15","Fetin'ny paska / Easter Sunday","MG",2001 +"2001-04-16","Alatsinain'ny paska / Easter Monday","MG",2001 +"2001-05-01","Labour Day","MG",2001 +"2001-05-24","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2001 +"2001-05-27","Fetin'ny Reny / Mother's Day","MG",2001 +"2001-06-03","Pentekosta / Whit Sunday","MG",2001 +"2001-06-04","Alatsinain'ny pentekosta / Whit Monday","MG",2001 +"2001-06-17","Fetin'ny ray / Father's Day","MG",2001 +"2001-06-26","Independence Day","MG",2001 +"2001-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2001 +"2001-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2001 +"2001-12-25","Fetin'ny noely / Christmas Day","MG",2001 +"2002-01-01","Taom-baovao / New Year's Day","MG",2002 +"2002-03-08","Fetin'ny vehivavy / Women's Day","MG",2002 +"2002-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2002 +"2002-03-31","Fetin'ny paska / Easter Sunday","MG",2002 +"2002-04-01","Alatsinain'ny paska / Easter Monday","MG",2002 +"2002-05-01","Labour Day","MG",2002 +"2002-05-09","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2002 +"2002-05-19","Pentekosta / Whit Sunday","MG",2002 +"2002-05-20","Alatsinain'ny pentekosta / Whit Monday","MG",2002 +"2002-05-26","Fetin'ny Reny / Mother's Day","MG",2002 +"2002-06-16","Fetin'ny ray / Father's Day","MG",2002 +"2002-06-26","Independence Day","MG",2002 +"2002-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2002 +"2002-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2002 +"2002-12-25","Fetin'ny noely / Christmas Day","MG",2002 +"2003-01-01","Taom-baovao / New Year's Day","MG",2003 +"2003-03-08","Fetin'ny vehivavy / Women's Day","MG",2003 +"2003-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2003 +"2003-04-20","Fetin'ny paska / Easter Sunday","MG",2003 +"2003-04-21","Alatsinain'ny paska / Easter Monday","MG",2003 +"2003-05-01","Labour Day","MG",2003 +"2003-05-25","Fetin'ny Reny / Mother's Day","MG",2003 +"2003-05-29","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2003 +"2003-06-08","Pentekosta / Whit Sunday","MG",2003 +"2003-06-09","Alatsinain'ny pentekosta / Whit Monday","MG",2003 +"2003-06-15","Fetin'ny ray / Father's Day","MG",2003 +"2003-06-26","Independence Day","MG",2003 +"2003-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2003 +"2003-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2003 +"2003-12-25","Fetin'ny noely / Christmas Day","MG",2003 +"2004-01-01","Taom-baovao / New Year's Day","MG",2004 +"2004-03-08","Fetin'ny vehivavy / Women's Day","MG",2004 +"2004-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2004 +"2004-04-11","Fetin'ny paska / Easter Sunday","MG",2004 +"2004-04-12","Alatsinain'ny paska / Easter Monday","MG",2004 +"2004-05-01","Labour Day","MG",2004 +"2004-05-20","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2004 +"2004-05-30","Pentekosta / Whit Sunday","MG",2004 +"2004-05-31","Alatsinain'ny pentekosta / Whit Monday","MG",2004 +"2004-06-06","Fetin'ny Reny / Mother's Day","MG",2004 +"2004-06-20","Fetin'ny ray / Father's Day","MG",2004 +"2004-06-26","Independence Day","MG",2004 +"2004-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2004 +"2004-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2004 +"2004-12-25","Fetin'ny noely / Christmas Day","MG",2004 +"2005-01-01","Taom-baovao / New Year's Day","MG",2005 +"2005-03-08","Fetin'ny vehivavy / Women's Day","MG",2005 +"2005-03-27","Fetin'ny paska / Easter Sunday","MG",2005 +"2005-03-28","Alatsinain'ny paska / Easter Monday","MG",2005 +"2005-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2005 +"2005-05-01","Labour Day","MG",2005 +"2005-05-05","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2005 +"2005-05-15","Pentekosta / Whit Sunday","MG",2005 +"2005-05-16","Alatsinain'ny pentekosta / Whit Monday","MG",2005 +"2005-05-29","Fetin'ny Reny / Mother's Day","MG",2005 +"2005-06-19","Fetin'ny ray / Father's Day","MG",2005 +"2005-06-26","Independence Day","MG",2005 +"2005-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2005 +"2005-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2005 +"2005-12-25","Fetin'ny noely / Christmas Day","MG",2005 +"2006-01-01","Taom-baovao / New Year's Day","MG",2006 +"2006-03-08","Fetin'ny vehivavy / Women's Day","MG",2006 +"2006-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2006 +"2006-04-16","Fetin'ny paska / Easter Sunday","MG",2006 +"2006-04-17","Alatsinain'ny paska / Easter Monday","MG",2006 +"2006-05-01","Labour Day","MG",2006 +"2006-05-25","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2006 +"2006-05-28","Fetin'ny Reny / Mother's Day","MG",2006 +"2006-06-04","Pentekosta / Whit Sunday","MG",2006 +"2006-06-05","Alatsinain'ny pentekosta / Whit Monday","MG",2006 +"2006-06-18","Fetin'ny ray / Father's Day","MG",2006 +"2006-06-26","Independence Day","MG",2006 +"2006-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2006 +"2006-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2006 +"2006-12-25","Fetin'ny noely / Christmas Day","MG",2006 +"2007-01-01","Taom-baovao / New Year's Day","MG",2007 +"2007-03-08","Fetin'ny vehivavy / Women's Day","MG",2007 +"2007-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2007 +"2007-04-08","Fetin'ny paska / Easter Sunday","MG",2007 +"2007-04-09","Alatsinain'ny paska / Easter Monday","MG",2007 +"2007-05-01","Labour Day","MG",2007 +"2007-05-17","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2007 +"2007-05-27","Pentekosta / Whit Sunday","MG",2007 +"2007-05-28","Alatsinain'ny pentekosta / Whit Monday","MG",2007 +"2007-06-03","Fetin'ny Reny / Mother's Day","MG",2007 +"2007-06-17","Fetin'ny ray / Father's Day","MG",2007 +"2007-06-26","Independence Day","MG",2007 +"2007-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2007 +"2007-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2007 +"2007-12-25","Fetin'ny noely / Christmas Day","MG",2007 +"2008-01-01","Taom-baovao / New Year's Day","MG",2008 +"2008-03-08","Fetin'ny vehivavy / Women's Day","MG",2008 +"2008-03-23","Fetin'ny paska / Easter Sunday","MG",2008 +"2008-03-24","Alatsinain'ny paska / Easter Monday","MG",2008 +"2008-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2008 +"2008-05-01","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2008 +"2008-05-01","Labour Day","MG",2008 +"2008-05-11","Pentekosta / Whit Sunday","MG",2008 +"2008-05-12","Alatsinain'ny pentekosta / Whit Monday","MG",2008 +"2008-05-25","Fetin'ny Reny / Mother's Day","MG",2008 +"2008-06-15","Fetin'ny ray / Father's Day","MG",2008 +"2008-06-26","Independence Day","MG",2008 +"2008-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2008 +"2008-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2008 +"2008-12-25","Fetin'ny noely / Christmas Day","MG",2008 +"2009-01-01","Taom-baovao / New Year's Day","MG",2009 +"2009-03-08","Fetin'ny vehivavy / Women's Day","MG",2009 +"2009-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2009 +"2009-04-12","Fetin'ny paska / Easter Sunday","MG",2009 +"2009-04-13","Alatsinain'ny paska / Easter Monday","MG",2009 +"2009-05-01","Labour Day","MG",2009 +"2009-05-21","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2009 +"2009-05-31","Pentekosta / Whit Sunday","MG",2009 +"2009-06-01","Alatsinain'ny pentekosta / Whit Monday","MG",2009 +"2009-06-07","Fetin'ny Reny / Mother's Day","MG",2009 +"2009-06-21","Fetin'ny ray / Father's Day","MG",2009 +"2009-06-26","Independence Day","MG",2009 +"2009-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2009 +"2009-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2009 +"2009-12-25","Fetin'ny noely / Christmas Day","MG",2009 +"2010-01-01","Taom-baovao / New Year's Day","MG",2010 +"2010-03-08","Fetin'ny vehivavy / Women's Day","MG",2010 +"2010-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2010 +"2010-04-04","Fetin'ny paska / Easter Sunday","MG",2010 +"2010-04-05","Alatsinain'ny paska / Easter Monday","MG",2010 +"2010-05-01","Labour Day","MG",2010 +"2010-05-13","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2010 +"2010-05-23","Pentekosta / Whit Sunday","MG",2010 +"2010-05-24","Alatsinain'ny pentekosta / Whit Monday","MG",2010 +"2010-05-30","Fetin'ny Reny / Mother's Day","MG",2010 +"2010-06-20","Fetin'ny ray / Father's Day","MG",2010 +"2010-06-26","Independence Day","MG",2010 +"2010-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2010 +"2010-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2010 +"2010-12-25","Fetin'ny noely / Christmas Day","MG",2010 +"2011-01-01","Taom-baovao / New Year's Day","MG",2011 +"2011-03-08","Fetin'ny vehivavy / Women's Day","MG",2011 +"2011-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2011 +"2011-04-24","Fetin'ny paska / Easter Sunday","MG",2011 +"2011-04-25","Alatsinain'ny paska / Easter Monday","MG",2011 +"2011-05-01","Labour Day","MG",2011 +"2011-05-29","Fetin'ny Reny / Mother's Day","MG",2011 +"2011-06-02","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2011 +"2011-06-12","Pentekosta / Whit Sunday","MG",2011 +"2011-06-13","Alatsinain'ny pentekosta / Whit Monday","MG",2011 +"2011-06-19","Fetin'ny ray / Father's Day","MG",2011 +"2011-06-26","Independence Day","MG",2011 +"2011-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2011 +"2011-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2011 +"2011-12-11","Republic Day","MG",2011 +"2011-12-25","Fetin'ny noely / Christmas Day","MG",2011 +"2012-01-01","Taom-baovao / New Year's Day","MG",2012 +"2012-03-08","Fetin'ny vehivavy / Women's Day","MG",2012 +"2012-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2012 +"2012-04-08","Fetin'ny paska / Easter Sunday","MG",2012 +"2012-04-09","Alatsinain'ny paska / Easter Monday","MG",2012 +"2012-05-01","Labour Day","MG",2012 +"2012-05-17","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2012 +"2012-05-27","Pentekosta / Whit Sunday","MG",2012 +"2012-05-28","Alatsinain'ny pentekosta / Whit Monday","MG",2012 +"2012-06-03","Fetin'ny Reny / Mother's Day","MG",2012 +"2012-06-17","Fetin'ny ray / Father's Day","MG",2012 +"2012-06-26","Independence Day","MG",2012 +"2012-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2012 +"2012-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2012 +"2012-12-11","Republic Day","MG",2012 +"2012-12-25","Fetin'ny noely / Christmas Day","MG",2012 +"2013-01-01","Taom-baovao / New Year's Day","MG",2013 +"2013-03-08","Fetin'ny vehivavy / Women's Day","MG",2013 +"2013-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2013 +"2013-03-31","Fetin'ny paska / Easter Sunday","MG",2013 +"2013-04-01","Alatsinain'ny paska / Easter Monday","MG",2013 +"2013-05-01","Labour Day","MG",2013 +"2013-05-09","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2013 +"2013-05-19","Pentekosta / Whit Sunday","MG",2013 +"2013-05-20","Alatsinain'ny pentekosta / Whit Monday","MG",2013 +"2013-05-26","Fetin'ny Reny / Mother's Day","MG",2013 +"2013-06-16","Fetin'ny ray / Father's Day","MG",2013 +"2013-06-26","Independence Day","MG",2013 +"2013-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2013 +"2013-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2013 +"2013-12-11","Republic Day","MG",2013 +"2013-12-25","Fetin'ny noely / Christmas Day","MG",2013 +"2014-01-01","Taom-baovao / New Year's Day","MG",2014 +"2014-03-08","Fetin'ny vehivavy / Women's Day","MG",2014 +"2014-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2014 +"2014-04-20","Fetin'ny paska / Easter Sunday","MG",2014 +"2014-04-21","Alatsinain'ny paska / Easter Monday","MG",2014 +"2014-05-01","Labour Day","MG",2014 +"2014-05-25","Fetin'ny Reny / Mother's Day","MG",2014 +"2014-05-29","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2014 +"2014-06-08","Pentekosta / Whit Sunday","MG",2014 +"2014-06-09","Alatsinain'ny pentekosta / Whit Monday","MG",2014 +"2014-06-15","Fetin'ny ray / Father's Day","MG",2014 +"2014-06-26","Independence Day","MG",2014 +"2014-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2014 +"2014-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2014 +"2014-12-11","Republic Day","MG",2014 +"2014-12-25","Fetin'ny noely / Christmas Day","MG",2014 +"2015-01-01","Taom-baovao / New Year's Day","MG",2015 +"2015-03-08","Fetin'ny vehivavy / Women's Day","MG",2015 +"2015-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2015 +"2015-04-05","Fetin'ny paska / Easter Sunday","MG",2015 +"2015-04-06","Alatsinain'ny paska / Easter Monday","MG",2015 +"2015-05-01","Labour Day","MG",2015 +"2015-05-14","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2015 +"2015-05-24","Pentekosta / Whit Sunday","MG",2015 +"2015-05-25","Alatsinain'ny pentekosta / Whit Monday","MG",2015 +"2015-05-31","Fetin'ny Reny / Mother's Day","MG",2015 +"2015-06-21","Fetin'ny ray / Father's Day","MG",2015 +"2015-06-26","Independence Day","MG",2015 +"2015-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2015 +"2015-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2015 +"2015-12-11","Republic Day","MG",2015 +"2015-12-25","Fetin'ny noely / Christmas Day","MG",2015 +"2016-01-01","Taom-baovao / New Year's Day","MG",2016 +"2016-03-08","Fetin'ny vehivavy / Women's Day","MG",2016 +"2016-03-27","Fetin'ny paska / Easter Sunday","MG",2016 +"2016-03-28","Alatsinain'ny paska / Easter Monday","MG",2016 +"2016-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2016 +"2016-05-01","Labour Day","MG",2016 +"2016-05-05","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2016 +"2016-05-15","Pentekosta / Whit Sunday","MG",2016 +"2016-05-16","Alatsinain'ny pentekosta / Whit Monday","MG",2016 +"2016-05-29","Fetin'ny Reny / Mother's Day","MG",2016 +"2016-06-19","Fetin'ny ray / Father's Day","MG",2016 +"2016-06-26","Independence Day","MG",2016 +"2016-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2016 +"2016-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2016 +"2016-12-11","Republic Day","MG",2016 +"2016-12-25","Fetin'ny noely / Christmas Day","MG",2016 +"2017-01-01","Taom-baovao / New Year's Day","MG",2017 +"2017-03-08","Fetin'ny vehivavy / Women's Day","MG",2017 +"2017-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2017 +"2017-04-16","Fetin'ny paska / Easter Sunday","MG",2017 +"2017-04-17","Alatsinain'ny paska / Easter Monday","MG",2017 +"2017-05-01","Labour Day","MG",2017 +"2017-05-25","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2017 +"2017-05-28","Fetin'ny Reny / Mother's Day","MG",2017 +"2017-06-04","Pentekosta / Whit Sunday","MG",2017 +"2017-06-05","Alatsinain'ny pentekosta / Whit Monday","MG",2017 +"2017-06-18","Fetin'ny ray / Father's Day","MG",2017 +"2017-06-26","Independence Day","MG",2017 +"2017-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2017 +"2017-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2017 +"2017-12-11","Republic Day","MG",2017 +"2017-12-25","Fetin'ny noely / Christmas Day","MG",2017 +"2018-01-01","Taom-baovao / New Year's Day","MG",2018 +"2018-03-08","Fetin'ny vehivavy / Women's Day","MG",2018 +"2018-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2018 +"2018-04-01","Fetin'ny paska / Easter Sunday","MG",2018 +"2018-04-02","Alatsinain'ny paska / Easter Monday","MG",2018 +"2018-05-01","Labour Day","MG",2018 +"2018-05-10","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2018 +"2018-05-20","Pentekosta / Whit Sunday","MG",2018 +"2018-05-21","Alatsinain'ny pentekosta / Whit Monday","MG",2018 +"2018-05-27","Fetin'ny Reny / Mother's Day","MG",2018 +"2018-06-17","Fetin'ny ray / Father's Day","MG",2018 +"2018-06-26","Independence Day","MG",2018 +"2018-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2018 +"2018-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2018 +"2018-12-11","Republic Day","MG",2018 +"2018-12-25","Fetin'ny noely / Christmas Day","MG",2018 +"2019-01-01","Taom-baovao / New Year's Day","MG",2019 +"2019-03-08","Fetin'ny vehivavy / Women's Day","MG",2019 +"2019-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2019 +"2019-04-21","Fetin'ny paska / Easter Sunday","MG",2019 +"2019-04-22","Alatsinain'ny paska / Easter Monday","MG",2019 +"2019-05-01","Labour Day","MG",2019 +"2019-05-26","Fetin'ny Reny / Mother's Day","MG",2019 +"2019-05-30","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2019 +"2019-06-09","Pentekosta / Whit Sunday","MG",2019 +"2019-06-10","Alatsinain'ny pentekosta / Whit Monday","MG",2019 +"2019-06-16","Fetin'ny ray / Father's Day","MG",2019 +"2019-06-26","Independence Day","MG",2019 +"2019-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2019 +"2019-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2019 +"2019-12-11","Republic Day","MG",2019 +"2019-12-25","Fetin'ny noely / Christmas Day","MG",2019 +"2020-01-01","Taom-baovao / New Year's Day","MG",2020 +"2020-03-08","Fetin'ny vehivavy / Women's Day","MG",2020 +"2020-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2020 +"2020-04-12","Fetin'ny paska / Easter Sunday","MG",2020 +"2020-04-13","Alatsinain'ny paska / Easter Monday","MG",2020 +"2020-05-01","Labour Day","MG",2020 +"2020-05-21","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2020 +"2020-05-31","Pentekosta / Whit Sunday","MG",2020 +"2020-06-01","Alatsinain'ny pentekosta / Whit Monday","MG",2020 +"2020-06-07","Fetin'ny Reny / Mother's Day","MG",2020 +"2020-06-21","Fetin'ny ray / Father's Day","MG",2020 +"2020-06-26","Independence Day","MG",2020 +"2020-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2020 +"2020-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2020 +"2020-12-11","Republic Day","MG",2020 +"2020-12-25","Fetin'ny noely / Christmas Day","MG",2020 +"2021-01-01","Taom-baovao / New Year's Day","MG",2021 +"2021-03-08","Fetin'ny vehivavy / Women's Day","MG",2021 +"2021-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2021 +"2021-04-04","Fetin'ny paska / Easter Sunday","MG",2021 +"2021-04-05","Alatsinain'ny paska / Easter Monday","MG",2021 +"2021-05-01","Labour Day","MG",2021 +"2021-05-13","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2021 +"2021-05-23","Pentekosta / Whit Sunday","MG",2021 +"2021-05-24","Alatsinain'ny pentekosta / Whit Monday","MG",2021 +"2021-05-30","Fetin'ny Reny / Mother's Day","MG",2021 +"2021-06-20","Fetin'ny ray / Father's Day","MG",2021 +"2021-06-26","Independence Day","MG",2021 +"2021-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2021 +"2021-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2021 +"2021-12-11","Republic Day","MG",2021 +"2021-12-25","Fetin'ny noely / Christmas Day","MG",2021 +"2022-01-01","Taom-baovao / New Year's Day","MG",2022 +"2022-03-08","Fetin'ny vehivavy / Women's Day","MG",2022 +"2022-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2022 +"2022-04-17","Fetin'ny paska / Easter Sunday","MG",2022 +"2022-04-18","Alatsinain'ny paska / Easter Monday","MG",2022 +"2022-05-01","Labour Day","MG",2022 +"2022-05-26","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2022 +"2022-05-29","Fetin'ny Reny / Mother's Day","MG",2022 +"2022-06-05","Pentekosta / Whit Sunday","MG",2022 +"2022-06-06","Alatsinain'ny pentekosta / Whit Monday","MG",2022 +"2022-06-19","Fetin'ny ray / Father's Day","MG",2022 +"2022-06-26","Independence Day","MG",2022 +"2022-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2022 +"2022-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2022 +"2022-12-11","Republic Day","MG",2022 +"2022-12-25","Fetin'ny noely / Christmas Day","MG",2022 +"2023-01-01","Taom-baovao / New Year's Day","MG",2023 +"2023-03-08","Fetin'ny vehivavy / Women's Day","MG",2023 +"2023-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2023 +"2023-04-09","Fetin'ny paska / Easter Sunday","MG",2023 +"2023-04-10","Alatsinain'ny paska / Easter Monday","MG",2023 +"2023-05-01","Labour Day","MG",2023 +"2023-05-18","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2023 +"2023-05-28","Pentekosta / Whit Sunday","MG",2023 +"2023-05-29","Alatsinain'ny pentekosta / Whit Monday","MG",2023 +"2023-06-04","Fetin'ny Reny / Mother's Day","MG",2023 +"2023-06-18","Fetin'ny ray / Father's Day","MG",2023 +"2023-06-26","Independence Day","MG",2023 +"2023-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2023 +"2023-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2023 +"2023-12-11","Republic Day","MG",2023 +"2023-12-25","Fetin'ny noely / Christmas Day","MG",2023 +"2024-01-01","Taom-baovao / New Year's Day","MG",2024 +"2024-03-08","Fetin'ny vehivavy / Women's Day","MG",2024 +"2024-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2024 +"2024-03-31","Fetin'ny paska / Easter Sunday","MG",2024 +"2024-04-01","Alatsinain'ny paska / Easter Monday","MG",2024 +"2024-05-01","Labour Day","MG",2024 +"2024-05-09","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2024 +"2024-05-19","Pentekosta / Whit Sunday","MG",2024 +"2024-05-20","Alatsinain'ny pentekosta / Whit Monday","MG",2024 +"2024-05-26","Fetin'ny Reny / Mother's Day","MG",2024 +"2024-06-16","Fetin'ny ray / Father's Day","MG",2024 +"2024-06-26","Independence Day","MG",2024 +"2024-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2024 +"2024-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2024 +"2024-12-11","Republic Day","MG",2024 +"2024-12-25","Fetin'ny noely / Christmas Day","MG",2024 +"2025-01-01","Taom-baovao / New Year's Day","MG",2025 +"2025-03-08","Fetin'ny vehivavy / Women's Day","MG",2025 +"2025-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2025 +"2025-04-20","Fetin'ny paska / Easter Sunday","MG",2025 +"2025-04-21","Alatsinain'ny paska / Easter Monday","MG",2025 +"2025-05-01","Labour Day","MG",2025 +"2025-05-25","Fetin'ny Reny / Mother's Day","MG",2025 +"2025-05-29","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2025 +"2025-06-08","Pentekosta / Whit Sunday","MG",2025 +"2025-06-09","Alatsinain'ny pentekosta / Whit Monday","MG",2025 +"2025-06-15","Fetin'ny ray / Father's Day","MG",2025 +"2025-06-26","Independence Day","MG",2025 +"2025-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2025 +"2025-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2025 +"2025-12-11","Republic Day","MG",2025 +"2025-12-25","Fetin'ny noely / Christmas Day","MG",2025 +"2026-01-01","Taom-baovao / New Year's Day","MG",2026 +"2026-03-08","Fetin'ny vehivavy / Women's Day","MG",2026 +"2026-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2026 +"2026-04-05","Fetin'ny paska / Easter Sunday","MG",2026 +"2026-04-06","Alatsinain'ny paska / Easter Monday","MG",2026 +"2026-05-01","Labour Day","MG",2026 +"2026-05-14","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2026 +"2026-05-24","Pentekosta / Whit Sunday","MG",2026 +"2026-05-25","Alatsinain'ny pentekosta / Whit Monday","MG",2026 +"2026-05-31","Fetin'ny Reny / Mother's Day","MG",2026 +"2026-06-21","Fetin'ny ray / Father's Day","MG",2026 +"2026-06-26","Independence Day","MG",2026 +"2026-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2026 +"2026-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2026 +"2026-12-11","Republic Day","MG",2026 +"2026-12-25","Fetin'ny noely / Christmas Day","MG",2026 +"2027-01-01","Taom-baovao / New Year's Day","MG",2027 +"2027-03-08","Fetin'ny vehivavy / Women's Day","MG",2027 +"2027-03-28","Fetin'ny paska / Easter Sunday","MG",2027 +"2027-03-29","Alatsinain'ny paska / Easter Monday","MG",2027 +"2027-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2027 +"2027-05-01","Labour Day","MG",2027 +"2027-05-06","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2027 +"2027-05-16","Pentekosta / Whit Sunday","MG",2027 +"2027-05-17","Alatsinain'ny pentekosta / Whit Monday","MG",2027 +"2027-05-30","Fetin'ny Reny / Mother's Day","MG",2027 +"2027-06-20","Fetin'ny ray / Father's Day","MG",2027 +"2027-06-26","Independence Day","MG",2027 +"2027-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2027 +"2027-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2027 +"2027-12-11","Republic Day","MG",2027 +"2027-12-25","Fetin'ny noely / Christmas Day","MG",2027 +"2028-01-01","Taom-baovao / New Year's Day","MG",2028 +"2028-03-08","Fetin'ny vehivavy / Women's Day","MG",2028 +"2028-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2028 +"2028-04-16","Fetin'ny paska / Easter Sunday","MG",2028 +"2028-04-17","Alatsinain'ny paska / Easter Monday","MG",2028 +"2028-05-01","Labour Day","MG",2028 +"2028-05-25","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2028 +"2028-05-28","Fetin'ny Reny / Mother's Day","MG",2028 +"2028-06-04","Pentekosta / Whit Sunday","MG",2028 +"2028-06-05","Alatsinain'ny pentekosta / Whit Monday","MG",2028 +"2028-06-18","Fetin'ny ray / Father's Day","MG",2028 +"2028-06-26","Independence Day","MG",2028 +"2028-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2028 +"2028-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2028 +"2028-12-11","Republic Day","MG",2028 +"2028-12-25","Fetin'ny noely / Christmas Day","MG",2028 +"2029-01-01","Taom-baovao / New Year's Day","MG",2029 +"2029-03-08","Fetin'ny vehivavy / Women's Day","MG",2029 +"2029-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2029 +"2029-04-01","Fetin'ny paska / Easter Sunday","MG",2029 +"2029-04-02","Alatsinain'ny paska / Easter Monday","MG",2029 +"2029-05-01","Labour Day","MG",2029 +"2029-05-10","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2029 +"2029-05-20","Pentekosta / Whit Sunday","MG",2029 +"2029-05-21","Alatsinain'ny pentekosta / Whit Monday","MG",2029 +"2029-05-27","Fetin'ny Reny / Mother's Day","MG",2029 +"2029-06-17","Fetin'ny ray / Father's Day","MG",2029 +"2029-06-26","Independence Day","MG",2029 +"2029-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2029 +"2029-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2029 +"2029-12-11","Republic Day","MG",2029 +"2029-12-25","Fetin'ny noely / Christmas Day","MG",2029 +"2030-01-01","Taom-baovao / New Year's Day","MG",2030 +"2030-03-08","Fetin'ny vehivavy / Women's Day","MG",2030 +"2030-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2030 +"2030-04-21","Fetin'ny paska / Easter Sunday","MG",2030 +"2030-04-22","Alatsinain'ny paska / Easter Monday","MG",2030 +"2030-05-01","Labour Day","MG",2030 +"2030-05-26","Fetin'ny Reny / Mother's Day","MG",2030 +"2030-05-30","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2030 +"2030-06-09","Pentekosta / Whit Sunday","MG",2030 +"2030-06-10","Alatsinain'ny pentekosta / Whit Monday","MG",2030 +"2030-06-16","Fetin'ny ray / Father's Day","MG",2030 +"2030-06-26","Independence Day","MG",2030 +"2030-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2030 +"2030-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2030 +"2030-12-11","Republic Day","MG",2030 +"2030-12-25","Fetin'ny noely / Christmas Day","MG",2030 +"2031-01-01","Taom-baovao / New Year's Day","MG",2031 +"2031-03-08","Fetin'ny vehivavy / Women's Day","MG",2031 +"2031-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2031 +"2031-04-13","Fetin'ny paska / Easter Sunday","MG",2031 +"2031-04-14","Alatsinain'ny paska / Easter Monday","MG",2031 +"2031-05-01","Labour Day","MG",2031 +"2031-05-22","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2031 +"2031-05-25","Fetin'ny Reny / Mother's Day","MG",2031 +"2031-06-01","Pentekosta / Whit Sunday","MG",2031 +"2031-06-02","Alatsinain'ny pentekosta / Whit Monday","MG",2031 +"2031-06-15","Fetin'ny ray / Father's Day","MG",2031 +"2031-06-26","Independence Day","MG",2031 +"2031-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2031 +"2031-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2031 +"2031-12-11","Republic Day","MG",2031 +"2031-12-25","Fetin'ny noely / Christmas Day","MG",2031 +"2032-01-01","Taom-baovao / New Year's Day","MG",2032 +"2032-03-08","Fetin'ny vehivavy / Women's Day","MG",2032 +"2032-03-28","Fetin'ny paska / Easter Sunday","MG",2032 +"2032-03-29","Alatsinain'ny paska / Easter Monday","MG",2032 +"2032-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2032 +"2032-05-01","Labour Day","MG",2032 +"2032-05-06","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2032 +"2032-05-16","Pentekosta / Whit Sunday","MG",2032 +"2032-05-17","Alatsinain'ny pentekosta / Whit Monday","MG",2032 +"2032-05-30","Fetin'ny Reny / Mother's Day","MG",2032 +"2032-06-20","Fetin'ny ray / Father's Day","MG",2032 +"2032-06-26","Independence Day","MG",2032 +"2032-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2032 +"2032-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2032 +"2032-12-11","Republic Day","MG",2032 +"2032-12-25","Fetin'ny noely / Christmas Day","MG",2032 +"2033-01-01","Taom-baovao / New Year's Day","MG",2033 +"2033-03-08","Fetin'ny vehivavy / Women's Day","MG",2033 +"2033-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2033 +"2033-04-17","Fetin'ny paska / Easter Sunday","MG",2033 +"2033-04-18","Alatsinain'ny paska / Easter Monday","MG",2033 +"2033-05-01","Labour Day","MG",2033 +"2033-05-26","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2033 +"2033-05-29","Fetin'ny Reny / Mother's Day","MG",2033 +"2033-06-05","Pentekosta / Whit Sunday","MG",2033 +"2033-06-06","Alatsinain'ny pentekosta / Whit Monday","MG",2033 +"2033-06-19","Fetin'ny ray / Father's Day","MG",2033 +"2033-06-26","Independence Day","MG",2033 +"2033-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2033 +"2033-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2033 +"2033-12-11","Republic Day","MG",2033 +"2033-12-25","Fetin'ny noely / Christmas Day","MG",2033 +"2034-01-01","Taom-baovao / New Year's Day","MG",2034 +"2034-03-08","Fetin'ny vehivavy / Women's Day","MG",2034 +"2034-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2034 +"2034-04-09","Fetin'ny paska / Easter Sunday","MG",2034 +"2034-04-10","Alatsinain'ny paska / Easter Monday","MG",2034 +"2034-05-01","Labour Day","MG",2034 +"2034-05-18","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2034 +"2034-05-28","Pentekosta / Whit Sunday","MG",2034 +"2034-05-29","Alatsinain'ny pentekosta / Whit Monday","MG",2034 +"2034-06-04","Fetin'ny Reny / Mother's Day","MG",2034 +"2034-06-18","Fetin'ny ray / Father's Day","MG",2034 +"2034-06-26","Independence Day","MG",2034 +"2034-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2034 +"2034-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2034 +"2034-12-11","Republic Day","MG",2034 +"2034-12-25","Fetin'ny noely / Christmas Day","MG",2034 +"2035-01-01","Taom-baovao / New Year's Day","MG",2035 +"2035-03-08","Fetin'ny vehivavy / Women's Day","MG",2035 +"2035-03-25","Fetin'ny paska / Easter Sunday","MG",2035 +"2035-03-26","Alatsinain'ny paska / Easter Monday","MG",2035 +"2035-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2035 +"2035-05-01","Labour Day","MG",2035 +"2035-05-03","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2035 +"2035-05-13","Pentekosta / Whit Sunday","MG",2035 +"2035-05-14","Alatsinain'ny pentekosta / Whit Monday","MG",2035 +"2035-05-27","Fetin'ny Reny / Mother's Day","MG",2035 +"2035-06-17","Fetin'ny ray / Father's Day","MG",2035 +"2035-06-26","Independence Day","MG",2035 +"2035-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2035 +"2035-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2035 +"2035-12-11","Republic Day","MG",2035 +"2035-12-25","Fetin'ny noely / Christmas Day","MG",2035 +"2036-01-01","Taom-baovao / New Year's Day","MG",2036 +"2036-03-08","Fetin'ny vehivavy / Women's Day","MG",2036 +"2036-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2036 +"2036-04-13","Fetin'ny paska / Easter Sunday","MG",2036 +"2036-04-14","Alatsinain'ny paska / Easter Monday","MG",2036 +"2036-05-01","Labour Day","MG",2036 +"2036-05-22","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2036 +"2036-05-25","Fetin'ny Reny / Mother's Day","MG",2036 +"2036-06-01","Pentekosta / Whit Sunday","MG",2036 +"2036-06-02","Alatsinain'ny pentekosta / Whit Monday","MG",2036 +"2036-06-15","Fetin'ny ray / Father's Day","MG",2036 +"2036-06-26","Independence Day","MG",2036 +"2036-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2036 +"2036-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2036 +"2036-12-11","Republic Day","MG",2036 +"2036-12-25","Fetin'ny noely / Christmas Day","MG",2036 +"2037-01-01","Taom-baovao / New Year's Day","MG",2037 +"2037-03-08","Fetin'ny vehivavy / Women's Day","MG",2037 +"2037-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2037 +"2037-04-05","Fetin'ny paska / Easter Sunday","MG",2037 +"2037-04-06","Alatsinain'ny paska / Easter Monday","MG",2037 +"2037-05-01","Labour Day","MG",2037 +"2037-05-14","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2037 +"2037-05-24","Pentekosta / Whit Sunday","MG",2037 +"2037-05-25","Alatsinain'ny pentekosta / Whit Monday","MG",2037 +"2037-05-31","Fetin'ny Reny / Mother's Day","MG",2037 +"2037-06-21","Fetin'ny ray / Father's Day","MG",2037 +"2037-06-26","Independence Day","MG",2037 +"2037-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2037 +"2037-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2037 +"2037-12-11","Republic Day","MG",2037 +"2037-12-25","Fetin'ny noely / Christmas Day","MG",2037 +"2038-01-01","Taom-baovao / New Year's Day","MG",2038 +"2038-03-08","Fetin'ny vehivavy / Women's Day","MG",2038 +"2038-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2038 +"2038-04-25","Fetin'ny paska / Easter Sunday","MG",2038 +"2038-04-26","Alatsinain'ny paska / Easter Monday","MG",2038 +"2038-05-01","Labour Day","MG",2038 +"2038-05-30","Fetin'ny Reny / Mother's Day","MG",2038 +"2038-06-03","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2038 +"2038-06-13","Pentekosta / Whit Sunday","MG",2038 +"2038-06-14","Alatsinain'ny pentekosta / Whit Monday","MG",2038 +"2038-06-20","Fetin'ny ray / Father's Day","MG",2038 +"2038-06-26","Independence Day","MG",2038 +"2038-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2038 +"2038-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2038 +"2038-12-11","Republic Day","MG",2038 +"2038-12-25","Fetin'ny noely / Christmas Day","MG",2038 +"2039-01-01","Taom-baovao / New Year's Day","MG",2039 +"2039-03-08","Fetin'ny vehivavy / Women's Day","MG",2039 +"2039-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2039 +"2039-04-10","Fetin'ny paska / Easter Sunday","MG",2039 +"2039-04-11","Alatsinain'ny paska / Easter Monday","MG",2039 +"2039-05-01","Labour Day","MG",2039 +"2039-05-19","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2039 +"2039-05-29","Pentekosta / Whit Sunday","MG",2039 +"2039-05-30","Alatsinain'ny pentekosta / Whit Monday","MG",2039 +"2039-06-05","Fetin'ny Reny / Mother's Day","MG",2039 +"2039-06-19","Fetin'ny ray / Father's Day","MG",2039 +"2039-06-26","Independence Day","MG",2039 +"2039-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2039 +"2039-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2039 +"2039-12-11","Republic Day","MG",2039 +"2039-12-25","Fetin'ny noely / Christmas Day","MG",2039 +"2040-01-01","Taom-baovao / New Year's Day","MG",2040 +"2040-03-08","Fetin'ny vehivavy / Women's Day","MG",2040 +"2040-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2040 +"2040-04-01","Fetin'ny paska / Easter Sunday","MG",2040 +"2040-04-02","Alatsinain'ny paska / Easter Monday","MG",2040 +"2040-05-01","Labour Day","MG",2040 +"2040-05-10","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2040 +"2040-05-20","Pentekosta / Whit Sunday","MG",2040 +"2040-05-21","Alatsinain'ny pentekosta / Whit Monday","MG",2040 +"2040-05-27","Fetin'ny Reny / Mother's Day","MG",2040 +"2040-06-17","Fetin'ny ray / Father's Day","MG",2040 +"2040-06-26","Independence Day","MG",2040 +"2040-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2040 +"2040-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2040 +"2040-12-11","Republic Day","MG",2040 +"2040-12-25","Fetin'ny noely / Christmas Day","MG",2040 +"2041-01-01","Taom-baovao / New Year's Day","MG",2041 +"2041-03-08","Fetin'ny vehivavy / Women's Day","MG",2041 +"2041-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2041 +"2041-04-21","Fetin'ny paska / Easter Sunday","MG",2041 +"2041-04-22","Alatsinain'ny paska / Easter Monday","MG",2041 +"2041-05-01","Labour Day","MG",2041 +"2041-05-26","Fetin'ny Reny / Mother's Day","MG",2041 +"2041-05-30","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2041 +"2041-06-09","Pentekosta / Whit Sunday","MG",2041 +"2041-06-10","Alatsinain'ny pentekosta / Whit Monday","MG",2041 +"2041-06-16","Fetin'ny ray / Father's Day","MG",2041 +"2041-06-26","Independence Day","MG",2041 +"2041-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2041 +"2041-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2041 +"2041-12-11","Republic Day","MG",2041 +"2041-12-25","Fetin'ny noely / Christmas Day","MG",2041 +"2042-01-01","Taom-baovao / New Year's Day","MG",2042 +"2042-03-08","Fetin'ny vehivavy / Women's Day","MG",2042 +"2042-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2042 +"2042-04-06","Fetin'ny paska / Easter Sunday","MG",2042 +"2042-04-07","Alatsinain'ny paska / Easter Monday","MG",2042 +"2042-05-01","Labour Day","MG",2042 +"2042-05-15","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2042 +"2042-05-25","Pentekosta / Whit Sunday","MG",2042 +"2042-05-26","Alatsinain'ny pentekosta / Whit Monday","MG",2042 +"2042-06-01","Fetin'ny Reny / Mother's Day","MG",2042 +"2042-06-15","Fetin'ny ray / Father's Day","MG",2042 +"2042-06-26","Independence Day","MG",2042 +"2042-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2042 +"2042-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2042 +"2042-12-11","Republic Day","MG",2042 +"2042-12-25","Fetin'ny noely / Christmas Day","MG",2042 +"2043-01-01","Taom-baovao / New Year's Day","MG",2043 +"2043-03-08","Fetin'ny vehivavy / Women's Day","MG",2043 +"2043-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2043 +"2043-03-29","Fetin'ny paska / Easter Sunday","MG",2043 +"2043-03-30","Alatsinain'ny paska / Easter Monday","MG",2043 +"2043-05-01","Labour Day","MG",2043 +"2043-05-07","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2043 +"2043-05-17","Pentekosta / Whit Sunday","MG",2043 +"2043-05-18","Alatsinain'ny pentekosta / Whit Monday","MG",2043 +"2043-05-31","Fetin'ny Reny / Mother's Day","MG",2043 +"2043-06-21","Fetin'ny ray / Father's Day","MG",2043 +"2043-06-26","Independence Day","MG",2043 +"2043-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2043 +"2043-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2043 +"2043-12-11","Republic Day","MG",2043 +"2043-12-25","Fetin'ny noely / Christmas Day","MG",2043 +"2044-01-01","Taom-baovao / New Year's Day","MG",2044 +"2044-03-08","Fetin'ny vehivavy / Women's Day","MG",2044 +"2044-03-29","Fetin'ny mahery fo / Martyrs' Day","MG",2044 +"2044-04-17","Fetin'ny paska / Easter Sunday","MG",2044 +"2044-04-18","Alatsinain'ny paska / Easter Monday","MG",2044 +"2044-05-01","Labour Day","MG",2044 +"2044-05-26","Fiakaran'ny Jesosy kristy tany an-danitra / Ascension Day","MG",2044 +"2044-05-29","Fetin'ny Reny / Mother's Day","MG",2044 +"2044-06-05","Pentekosta / Whit Sunday","MG",2044 +"2044-06-06","Alatsinain'ny pentekosta / Whit Monday","MG",2044 +"2044-06-19","Fetin'ny ray / Father's Day","MG",2044 +"2044-06-26","Independence Day","MG",2044 +"2044-08-15","Fiakaran'ny Masina Maria tany an-danitra / Assumption Day","MG",2044 +"2044-11-01","Fetin'ny olo-masina / All Saints' Day","MG",2044 +"2044-12-11","Republic Day","MG",2044 +"2044-12-25","Fetin'ny noely / Christmas Day","MG",2044 +"1995-01-01","New Year's Day","MH",1995 +"1995-01-02","New Year's Day (Holiday)","MH",1995 +"1995-03-01","Nuclear Victims Remembrance Day","MH",1995 +"1995-04-14","Good Friday","MH",1995 +"1995-05-01","Constitution Day","MH",1995 +"1995-07-07","Fisherman's Day","MH",1995 +"1995-09-01","Dri-jerbal Day","MH",1995 +"1995-09-29","Manit Day","MH",1995 +"1995-11-17","President's Day","MH",1995 +"1995-12-01","Gospel Day","MH",1995 +"1995-12-25","Christmas Day","MH",1995 +"1996-01-01","New Year's Day","MH",1996 +"1996-03-01","Nuclear Victims Remembrance Day","MH",1996 +"1996-04-05","Good Friday","MH",1996 +"1996-05-01","Constitution Day","MH",1996 +"1996-07-05","Fisherman's Day","MH",1996 +"1996-09-06","Dri-jerbal Day","MH",1996 +"1996-09-27","Manit Day","MH",1996 +"1996-11-17","President's Day","MH",1996 +"1996-11-18","President's Day (Holiday)","MH",1996 +"1996-12-06","Gospel Day","MH",1996 +"1996-12-25","Christmas Day","MH",1996 +"1997-01-01","New Year's Day","MH",1997 +"1997-03-01","Nuclear Victims Remembrance Day","MH",1997 +"1997-03-28","Good Friday","MH",1997 +"1997-05-01","Constitution Day","MH",1997 +"1997-07-04","Fisherman's Day","MH",1997 +"1997-09-05","Dri-jerbal Day","MH",1997 +"1997-09-26","Manit Day","MH",1997 +"1997-11-17","President's Day","MH",1997 +"1997-12-05","Gospel Day","MH",1997 +"1997-12-25","Christmas Day","MH",1997 +"1998-01-01","New Year's Day","MH",1998 +"1998-03-01","Nuclear Victims Remembrance Day","MH",1998 +"1998-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",1998 +"1998-04-10","Good Friday","MH",1998 +"1998-05-01","Constitution Day","MH",1998 +"1998-07-03","Fisherman's Day","MH",1998 +"1998-09-04","Dri-jerbal Day","MH",1998 +"1998-09-25","Manit Day","MH",1998 +"1998-11-17","President's Day","MH",1998 +"1998-12-04","Gospel Day","MH",1998 +"1998-12-25","Christmas Day","MH",1998 +"1999-01-01","New Year's Day","MH",1999 +"1999-03-01","Nuclear Victims Remembrance Day","MH",1999 +"1999-04-02","Good Friday","MH",1999 +"1999-05-01","Constitution Day","MH",1999 +"1999-07-02","Fisherman's Day","MH",1999 +"1999-09-03","Dri-jerbal Day","MH",1999 +"1999-09-24","Manit Day","MH",1999 +"1999-11-17","President's Day","MH",1999 +"1999-12-03","Gospel Day","MH",1999 +"1999-12-25","Christmas Day","MH",1999 +"2000-01-01","New Year's Day","MH",2000 +"2000-01-03","New Year's Day (Holiday)","MH",2000 +"2000-03-01","Nuclear Victims Remembrance Day","MH",2000 +"2000-04-21","Good Friday","MH",2000 +"2000-05-01","Constitution Day","MH",2000 +"2000-07-07","Fisherman's Day","MH",2000 +"2000-09-01","Dri-jerbal Day","MH",2000 +"2000-09-29","Manit Day","MH",2000 +"2000-11-17","President's Day","MH",2000 +"2000-12-01","Gospel Day","MH",2000 +"2000-12-25","Christmas Day","MH",2000 +"2001-01-01","New Year's Day","MH",2001 +"2001-03-01","Nuclear Victims Remembrance Day","MH",2001 +"2001-04-13","Good Friday","MH",2001 +"2001-05-01","Constitution Day","MH",2001 +"2001-07-06","Fisherman's Day","MH",2001 +"2001-09-07","Dri-jerbal Day","MH",2001 +"2001-09-28","Manit Day","MH",2001 +"2001-11-17","President's Day","MH",2001 +"2001-12-07","Gospel Day","MH",2001 +"2001-12-25","Christmas Day","MH",2001 +"2002-01-01","New Year's Day","MH",2002 +"2002-03-01","Nuclear Victims Remembrance Day","MH",2002 +"2002-03-29","Good Friday","MH",2002 +"2002-05-01","Constitution Day","MH",2002 +"2002-07-05","Fisherman's Day","MH",2002 +"2002-09-06","Dri-jerbal Day","MH",2002 +"2002-09-27","Manit Day","MH",2002 +"2002-11-17","President's Day","MH",2002 +"2002-11-18","President's Day (Holiday)","MH",2002 +"2002-12-06","Gospel Day","MH",2002 +"2002-12-25","Christmas Day","MH",2002 +"2003-01-01","New Year's Day","MH",2003 +"2003-03-01","Nuclear Victims Remembrance Day","MH",2003 +"2003-04-18","Good Friday","MH",2003 +"2003-05-01","Constitution Day","MH",2003 +"2003-07-04","Fisherman's Day","MH",2003 +"2003-09-05","Dri-jerbal Day","MH",2003 +"2003-09-26","Manit Day","MH",2003 +"2003-11-17","President's Day","MH",2003 +"2003-12-05","Gospel Day","MH",2003 +"2003-12-25","Christmas Day","MH",2003 +"2004-01-01","New Year's Day","MH",2004 +"2004-03-01","Nuclear Victims Remembrance Day","MH",2004 +"2004-04-09","Good Friday","MH",2004 +"2004-05-01","Constitution Day","MH",2004 +"2004-07-02","Fisherman's Day","MH",2004 +"2004-09-03","Dri-jerbal Day","MH",2004 +"2004-09-24","Manit Day","MH",2004 +"2004-11-17","President's Day","MH",2004 +"2004-12-03","Gospel Day","MH",2004 +"2004-12-25","Christmas Day","MH",2004 +"2005-01-01","New Year's Day","MH",2005 +"2005-01-03","New Year's Day (Holiday)","MH",2005 +"2005-03-01","Nuclear Victims Remembrance Day","MH",2005 +"2005-03-25","Good Friday","MH",2005 +"2005-05-01","Constitution Day","MH",2005 +"2005-07-01","Fisherman's Day","MH",2005 +"2005-09-02","Dri-jerbal Day","MH",2005 +"2005-09-30","Manit Day","MH",2005 +"2005-11-17","President's Day","MH",2005 +"2005-12-02","Gospel Day","MH",2005 +"2005-12-25","Christmas Day","MH",2005 +"2005-12-26","Christmas Day (Holiday)","MH",2005 +"2006-01-01","New Year's Day","MH",2006 +"2006-01-02","New Year's Day (Holiday)","MH",2006 +"2006-03-01","Nuclear Victims Remembrance Day","MH",2006 +"2006-04-14","Good Friday","MH",2006 +"2006-05-01","Constitution Day","MH",2006 +"2006-07-07","Fisherman's Day","MH",2006 +"2006-09-01","Dri-jerbal Day","MH",2006 +"2006-09-29","Manit Day","MH",2006 +"2006-11-17","President's Day","MH",2006 +"2006-12-01","Gospel Day","MH",2006 +"2006-12-25","Christmas Day","MH",2006 +"2007-01-01","New Year's Day","MH",2007 +"2007-03-01","Nuclear Victims Remembrance Day","MH",2007 +"2007-04-06","Good Friday","MH",2007 +"2007-05-01","Constitution Day","MH",2007 +"2007-07-06","Fisherman's Day","MH",2007 +"2007-09-07","Dri-jerbal Day","MH",2007 +"2007-09-28","Manit Day","MH",2007 +"2007-11-17","President's Day","MH",2007 +"2007-12-07","Gospel Day","MH",2007 +"2007-12-25","Christmas Day","MH",2007 +"2008-01-01","New Year's Day","MH",2008 +"2008-03-01","Nuclear Victims Remembrance Day","MH",2008 +"2008-03-21","Good Friday","MH",2008 +"2008-05-01","Constitution Day","MH",2008 +"2008-07-04","Fisherman's Day","MH",2008 +"2008-09-05","Dri-jerbal Day","MH",2008 +"2008-09-26","Manit Day","MH",2008 +"2008-11-17","President's Day","MH",2008 +"2008-12-05","Gospel Day","MH",2008 +"2008-12-25","Christmas Day","MH",2008 +"2009-01-01","New Year's Day","MH",2009 +"2009-03-01","Nuclear Victims Remembrance Day","MH",2009 +"2009-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",2009 +"2009-04-10","Good Friday","MH",2009 +"2009-05-01","Constitution Day","MH",2009 +"2009-07-03","Fisherman's Day","MH",2009 +"2009-09-04","Dri-jerbal Day","MH",2009 +"2009-09-25","Manit Day","MH",2009 +"2009-11-17","President's Day","MH",2009 +"2009-12-04","Gospel Day","MH",2009 +"2009-12-25","Christmas Day","MH",2009 +"2010-01-01","New Year's Day","MH",2010 +"2010-03-01","Nuclear Victims Remembrance Day","MH",2010 +"2010-04-02","Good Friday","MH",2010 +"2010-05-01","Constitution Day","MH",2010 +"2010-07-02","Fisherman's Day","MH",2010 +"2010-09-03","Dri-jerbal Day","MH",2010 +"2010-09-24","Manit Day","MH",2010 +"2010-11-17","President's Day","MH",2010 +"2010-12-03","Gospel Day","MH",2010 +"2010-12-25","Christmas Day","MH",2010 +"2011-01-01","New Year's Day","MH",2011 +"2011-01-03","New Year's Day (Holiday)","MH",2011 +"2011-03-01","Nuclear Victims Remembrance Day","MH",2011 +"2011-04-22","Good Friday","MH",2011 +"2011-05-01","Constitution Day","MH",2011 +"2011-07-01","Fisherman's Day","MH",2011 +"2011-09-02","Dri-jerbal Day","MH",2011 +"2011-09-30","Manit Day","MH",2011 +"2011-11-17","President's Day","MH",2011 +"2011-12-02","Gospel Day","MH",2011 +"2011-12-25","Christmas Day","MH",2011 +"2011-12-26","Christmas Day (Holiday)","MH",2011 +"2012-01-01","New Year's Day","MH",2012 +"2012-01-02","New Year's Day (Holiday)","MH",2012 +"2012-03-01","Nuclear Victims Remembrance Day","MH",2012 +"2012-04-06","Good Friday","MH",2012 +"2012-05-01","Constitution Day","MH",2012 +"2012-07-06","Fisherman's Day","MH",2012 +"2012-09-07","Dri-jerbal Day","MH",2012 +"2012-09-28","Manit Day","MH",2012 +"2012-11-17","President's Day","MH",2012 +"2012-12-07","Gospel Day","MH",2012 +"2012-12-25","Christmas Day","MH",2012 +"2013-01-01","New Year's Day","MH",2013 +"2013-03-01","Nuclear Victims Remembrance Day","MH",2013 +"2013-03-29","Good Friday","MH",2013 +"2013-05-01","Constitution Day","MH",2013 +"2013-07-05","Fisherman's Day","MH",2013 +"2013-09-06","Dri-jerbal Day","MH",2013 +"2013-09-27","Manit Day","MH",2013 +"2013-11-17","President's Day","MH",2013 +"2013-11-18","President's Day (Holiday)","MH",2013 +"2013-12-06","Gospel Day","MH",2013 +"2013-12-25","Christmas Day","MH",2013 +"2014-01-01","New Year's Day","MH",2014 +"2014-03-01","Nuclear Victims Remembrance Day","MH",2014 +"2014-04-18","Good Friday","MH",2014 +"2014-05-01","Constitution Day","MH",2014 +"2014-07-04","Fisherman's Day","MH",2014 +"2014-09-05","Dri-jerbal Day","MH",2014 +"2014-09-26","Manit Day","MH",2014 +"2014-11-17","President's Day","MH",2014 +"2014-12-05","Gospel Day","MH",2014 +"2014-12-25","Christmas Day","MH",2014 +"2015-01-01","New Year's Day","MH",2015 +"2015-03-01","Nuclear Victims Remembrance Day","MH",2015 +"2015-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",2015 +"2015-04-03","Good Friday","MH",2015 +"2015-05-01","Constitution Day","MH",2015 +"2015-07-03","Fisherman's Day","MH",2015 +"2015-09-04","Dri-jerbal Day","MH",2015 +"2015-09-25","Manit Day","MH",2015 +"2015-11-17","President's Day","MH",2015 +"2015-12-04","Gospel Day","MH",2015 +"2015-12-25","Christmas Day","MH",2015 +"2016-01-01","New Year's Day","MH",2016 +"2016-03-01","Nuclear Victims Remembrance Day","MH",2016 +"2016-03-25","Good Friday","MH",2016 +"2016-05-01","Constitution Day","MH",2016 +"2016-07-01","Fisherman's Day","MH",2016 +"2016-09-02","Dri-jerbal Day","MH",2016 +"2016-09-30","Manit Day","MH",2016 +"2016-11-17","President's Day","MH",2016 +"2016-12-02","Gospel Day","MH",2016 +"2016-12-25","Christmas Day","MH",2016 +"2016-12-26","Christmas Day (Holiday)","MH",2016 +"2017-01-01","New Year's Day","MH",2017 +"2017-01-02","New Year's Day (Holiday)","MH",2017 +"2017-03-01","Nuclear Victims Remembrance Day","MH",2017 +"2017-04-14","Good Friday","MH",2017 +"2017-05-01","Constitution Day","MH",2017 +"2017-07-07","Fisherman's Day","MH",2017 +"2017-09-01","Dri-jerbal Day","MH",2017 +"2017-09-29","Manit Day","MH",2017 +"2017-11-17","President's Day","MH",2017 +"2017-12-01","Gospel Day","MH",2017 +"2017-12-25","Christmas Day","MH",2017 +"2018-01-01","New Year's Day","MH",2018 +"2018-03-01","Nuclear Victims Remembrance Day","MH",2018 +"2018-03-30","Good Friday","MH",2018 +"2018-05-01","Constitution Day","MH",2018 +"2018-07-06","Fisherman's Day","MH",2018 +"2018-09-07","Dri-jerbal Day","MH",2018 +"2018-09-28","Manit Day","MH",2018 +"2018-11-17","President's Day","MH",2018 +"2018-12-07","Gospel Day","MH",2018 +"2018-12-25","Christmas Day","MH",2018 +"2019-01-01","New Year's Day","MH",2019 +"2019-03-01","Nuclear Victims Remembrance Day","MH",2019 +"2019-04-19","Good Friday","MH",2019 +"2019-05-01","Constitution Day","MH",2019 +"2019-07-05","Fisherman's Day","MH",2019 +"2019-09-06","Dri-jerbal Day","MH",2019 +"2019-09-27","Manit Day","MH",2019 +"2019-11-17","President's Day","MH",2019 +"2019-11-18","General Election Day","MH",2019 +"2019-11-18","President's Day (Holiday)","MH",2019 +"2019-12-06","Gospel Day","MH",2019 +"2019-12-25","Christmas Day","MH",2019 +"2020-01-01","New Year's Day","MH",2020 +"2020-03-01","Nuclear Victims Remembrance Day","MH",2020 +"2020-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",2020 +"2020-04-10","Good Friday","MH",2020 +"2020-05-01","Constitution Day","MH",2020 +"2020-07-03","Fisherman's Day","MH",2020 +"2020-09-04","Dri-jerbal Day","MH",2020 +"2020-09-25","Manit Day","MH",2020 +"2020-11-17","President's Day","MH",2020 +"2020-12-04","Gospel Day","MH",2020 +"2020-12-25","Christmas Day","MH",2020 +"2021-01-01","New Year's Day","MH",2021 +"2021-03-01","Nuclear Victims Remembrance Day","MH",2021 +"2021-04-02","Good Friday","MH",2021 +"2021-05-01","Constitution Day","MH",2021 +"2021-07-02","Fisherman's Day","MH",2021 +"2021-09-03","Dri-jerbal Day","MH",2021 +"2021-09-24","Manit Day","MH",2021 +"2021-11-17","President's Day","MH",2021 +"2021-12-03","Gospel Day","MH",2021 +"2021-12-25","Christmas Day","MH",2021 +"2022-01-01","New Year's Day","MH",2022 +"2022-01-03","New Year's Day (Holiday)","MH",2022 +"2022-03-01","Nuclear Victims Remembrance Day","MH",2022 +"2022-04-15","Good Friday","MH",2022 +"2022-05-01","Constitution Day","MH",2022 +"2022-07-01","Fisherman's Day","MH",2022 +"2022-09-02","Dri-jerbal Day","MH",2022 +"2022-09-30","Manit Day","MH",2022 +"2022-11-17","President's Day","MH",2022 +"2022-12-02","Gospel Day","MH",2022 +"2022-12-25","Christmas Day","MH",2022 +"2022-12-26","Christmas Day (Holiday)","MH",2022 +"2023-01-01","New Year's Day","MH",2023 +"2023-01-02","New Year's Day (Holiday)","MH",2023 +"2023-03-01","Nuclear Victims Remembrance Day","MH",2023 +"2023-04-07","Good Friday","MH",2023 +"2023-05-01","Constitution Day","MH",2023 +"2023-07-07","Fisherman's Day","MH",2023 +"2023-09-01","Dri-jerbal Day","MH",2023 +"2023-09-29","Manit Day","MH",2023 +"2023-11-17","President's Day","MH",2023 +"2023-12-01","Gospel Day","MH",2023 +"2023-12-25","Christmas Day","MH",2023 +"2024-01-01","New Year's Day","MH",2024 +"2024-03-01","Nuclear Victims Remembrance Day","MH",2024 +"2024-03-29","Good Friday","MH",2024 +"2024-05-01","Constitution Day","MH",2024 +"2024-07-05","Fisherman's Day","MH",2024 +"2024-09-06","Dri-jerbal Day","MH",2024 +"2024-09-27","Manit Day","MH",2024 +"2024-11-17","President's Day","MH",2024 +"2024-11-18","President's Day (Holiday)","MH",2024 +"2024-12-06","Gospel Day","MH",2024 +"2024-12-25","Christmas Day","MH",2024 +"2025-01-01","New Year's Day","MH",2025 +"2025-03-01","Nuclear Victims Remembrance Day","MH",2025 +"2025-04-18","Good Friday","MH",2025 +"2025-05-01","Constitution Day","MH",2025 +"2025-07-04","Fisherman's Day","MH",2025 +"2025-09-05","Dri-jerbal Day","MH",2025 +"2025-09-26","Manit Day","MH",2025 +"2025-11-17","President's Day","MH",2025 +"2025-12-05","Gospel Day","MH",2025 +"2025-12-25","Christmas Day","MH",2025 +"2026-01-01","New Year's Day","MH",2026 +"2026-03-01","Nuclear Victims Remembrance Day","MH",2026 +"2026-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",2026 +"2026-04-03","Good Friday","MH",2026 +"2026-05-01","Constitution Day","MH",2026 +"2026-07-03","Fisherman's Day","MH",2026 +"2026-09-04","Dri-jerbal Day","MH",2026 +"2026-09-25","Manit Day","MH",2026 +"2026-11-17","President's Day","MH",2026 +"2026-12-04","Gospel Day","MH",2026 +"2026-12-25","Christmas Day","MH",2026 +"2027-01-01","New Year's Day","MH",2027 +"2027-03-01","Nuclear Victims Remembrance Day","MH",2027 +"2027-03-26","Good Friday","MH",2027 +"2027-05-01","Constitution Day","MH",2027 +"2027-07-02","Fisherman's Day","MH",2027 +"2027-09-03","Dri-jerbal Day","MH",2027 +"2027-09-24","Manit Day","MH",2027 +"2027-11-17","President's Day","MH",2027 +"2027-12-03","Gospel Day","MH",2027 +"2027-12-25","Christmas Day","MH",2027 +"2028-01-01","New Year's Day","MH",2028 +"2028-01-03","New Year's Day (Holiday)","MH",2028 +"2028-03-01","Nuclear Victims Remembrance Day","MH",2028 +"2028-04-14","Good Friday","MH",2028 +"2028-05-01","Constitution Day","MH",2028 +"2028-07-07","Fisherman's Day","MH",2028 +"2028-09-01","Dri-jerbal Day","MH",2028 +"2028-09-29","Manit Day","MH",2028 +"2028-11-17","President's Day","MH",2028 +"2028-12-01","Gospel Day","MH",2028 +"2028-12-25","Christmas Day","MH",2028 +"2029-01-01","New Year's Day","MH",2029 +"2029-03-01","Nuclear Victims Remembrance Day","MH",2029 +"2029-03-30","Good Friday","MH",2029 +"2029-05-01","Constitution Day","MH",2029 +"2029-07-06","Fisherman's Day","MH",2029 +"2029-09-07","Dri-jerbal Day","MH",2029 +"2029-09-28","Manit Day","MH",2029 +"2029-11-17","President's Day","MH",2029 +"2029-12-07","Gospel Day","MH",2029 +"2029-12-25","Christmas Day","MH",2029 +"2030-01-01","New Year's Day","MH",2030 +"2030-03-01","Nuclear Victims Remembrance Day","MH",2030 +"2030-04-19","Good Friday","MH",2030 +"2030-05-01","Constitution Day","MH",2030 +"2030-07-05","Fisherman's Day","MH",2030 +"2030-09-06","Dri-jerbal Day","MH",2030 +"2030-09-27","Manit Day","MH",2030 +"2030-11-17","President's Day","MH",2030 +"2030-11-18","President's Day (Holiday)","MH",2030 +"2030-12-06","Gospel Day","MH",2030 +"2030-12-25","Christmas Day","MH",2030 +"2031-01-01","New Year's Day","MH",2031 +"2031-03-01","Nuclear Victims Remembrance Day","MH",2031 +"2031-04-11","Good Friday","MH",2031 +"2031-05-01","Constitution Day","MH",2031 +"2031-07-04","Fisherman's Day","MH",2031 +"2031-09-05","Dri-jerbal Day","MH",2031 +"2031-09-26","Manit Day","MH",2031 +"2031-11-17","President's Day","MH",2031 +"2031-12-05","Gospel Day","MH",2031 +"2031-12-25","Christmas Day","MH",2031 +"2032-01-01","New Year's Day","MH",2032 +"2032-03-01","Nuclear Victims Remembrance Day","MH",2032 +"2032-03-26","Good Friday","MH",2032 +"2032-05-01","Constitution Day","MH",2032 +"2032-07-02","Fisherman's Day","MH",2032 +"2032-09-03","Dri-jerbal Day","MH",2032 +"2032-09-24","Manit Day","MH",2032 +"2032-11-17","President's Day","MH",2032 +"2032-12-03","Gospel Day","MH",2032 +"2032-12-25","Christmas Day","MH",2032 +"2033-01-01","New Year's Day","MH",2033 +"2033-01-03","New Year's Day (Holiday)","MH",2033 +"2033-03-01","Nuclear Victims Remembrance Day","MH",2033 +"2033-04-15","Good Friday","MH",2033 +"2033-05-01","Constitution Day","MH",2033 +"2033-07-01","Fisherman's Day","MH",2033 +"2033-09-02","Dri-jerbal Day","MH",2033 +"2033-09-30","Manit Day","MH",2033 +"2033-11-17","President's Day","MH",2033 +"2033-12-02","Gospel Day","MH",2033 +"2033-12-25","Christmas Day","MH",2033 +"2033-12-26","Christmas Day (Holiday)","MH",2033 +"2034-01-01","New Year's Day","MH",2034 +"2034-01-02","New Year's Day (Holiday)","MH",2034 +"2034-03-01","Nuclear Victims Remembrance Day","MH",2034 +"2034-04-07","Good Friday","MH",2034 +"2034-05-01","Constitution Day","MH",2034 +"2034-07-07","Fisherman's Day","MH",2034 +"2034-09-01","Dri-jerbal Day","MH",2034 +"2034-09-29","Manit Day","MH",2034 +"2034-11-17","President's Day","MH",2034 +"2034-12-01","Gospel Day","MH",2034 +"2034-12-25","Christmas Day","MH",2034 +"2035-01-01","New Year's Day","MH",2035 +"2035-03-01","Nuclear Victims Remembrance Day","MH",2035 +"2035-03-23","Good Friday","MH",2035 +"2035-05-01","Constitution Day","MH",2035 +"2035-07-06","Fisherman's Day","MH",2035 +"2035-09-07","Dri-jerbal Day","MH",2035 +"2035-09-28","Manit Day","MH",2035 +"2035-11-17","President's Day","MH",2035 +"2035-12-07","Gospel Day","MH",2035 +"2035-12-25","Christmas Day","MH",2035 +"2036-01-01","New Year's Day","MH",2036 +"2036-03-01","Nuclear Victims Remembrance Day","MH",2036 +"2036-04-11","Good Friday","MH",2036 +"2036-05-01","Constitution Day","MH",2036 +"2036-07-04","Fisherman's Day","MH",2036 +"2036-09-05","Dri-jerbal Day","MH",2036 +"2036-09-26","Manit Day","MH",2036 +"2036-11-17","President's Day","MH",2036 +"2036-12-05","Gospel Day","MH",2036 +"2036-12-25","Christmas Day","MH",2036 +"2037-01-01","New Year's Day","MH",2037 +"2037-03-01","Nuclear Victims Remembrance Day","MH",2037 +"2037-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",2037 +"2037-04-03","Good Friday","MH",2037 +"2037-05-01","Constitution Day","MH",2037 +"2037-07-03","Fisherman's Day","MH",2037 +"2037-09-04","Dri-jerbal Day","MH",2037 +"2037-09-25","Manit Day","MH",2037 +"2037-11-17","President's Day","MH",2037 +"2037-12-04","Gospel Day","MH",2037 +"2037-12-25","Christmas Day","MH",2037 +"2038-01-01","New Year's Day","MH",2038 +"2038-03-01","Nuclear Victims Remembrance Day","MH",2038 +"2038-04-23","Good Friday","MH",2038 +"2038-05-01","Constitution Day","MH",2038 +"2038-07-02","Fisherman's Day","MH",2038 +"2038-09-03","Dri-jerbal Day","MH",2038 +"2038-09-24","Manit Day","MH",2038 +"2038-11-17","President's Day","MH",2038 +"2038-12-03","Gospel Day","MH",2038 +"2038-12-25","Christmas Day","MH",2038 +"2039-01-01","New Year's Day","MH",2039 +"2039-01-03","New Year's Day (Holiday)","MH",2039 +"2039-03-01","Nuclear Victims Remembrance Day","MH",2039 +"2039-04-08","Good Friday","MH",2039 +"2039-05-01","Constitution Day","MH",2039 +"2039-07-01","Fisherman's Day","MH",2039 +"2039-09-02","Dri-jerbal Day","MH",2039 +"2039-09-30","Manit Day","MH",2039 +"2039-11-17","President's Day","MH",2039 +"2039-12-02","Gospel Day","MH",2039 +"2039-12-25","Christmas Day","MH",2039 +"2039-12-26","Christmas Day (Holiday)","MH",2039 +"2040-01-01","New Year's Day","MH",2040 +"2040-01-02","New Year's Day (Holiday)","MH",2040 +"2040-03-01","Nuclear Victims Remembrance Day","MH",2040 +"2040-03-30","Good Friday","MH",2040 +"2040-05-01","Constitution Day","MH",2040 +"2040-07-06","Fisherman's Day","MH",2040 +"2040-09-07","Dri-jerbal Day","MH",2040 +"2040-09-28","Manit Day","MH",2040 +"2040-11-17","President's Day","MH",2040 +"2040-12-07","Gospel Day","MH",2040 +"2040-12-25","Christmas Day","MH",2040 +"2041-01-01","New Year's Day","MH",2041 +"2041-03-01","Nuclear Victims Remembrance Day","MH",2041 +"2041-04-19","Good Friday","MH",2041 +"2041-05-01","Constitution Day","MH",2041 +"2041-07-05","Fisherman's Day","MH",2041 +"2041-09-06","Dri-jerbal Day","MH",2041 +"2041-09-27","Manit Day","MH",2041 +"2041-11-17","President's Day","MH",2041 +"2041-11-18","President's Day (Holiday)","MH",2041 +"2041-12-06","Gospel Day","MH",2041 +"2041-12-25","Christmas Day","MH",2041 +"2042-01-01","New Year's Day","MH",2042 +"2042-03-01","Nuclear Victims Remembrance Day","MH",2042 +"2042-04-04","Good Friday","MH",2042 +"2042-05-01","Constitution Day","MH",2042 +"2042-07-04","Fisherman's Day","MH",2042 +"2042-09-05","Dri-jerbal Day","MH",2042 +"2042-09-26","Manit Day","MH",2042 +"2042-11-17","President's Day","MH",2042 +"2042-12-05","Gospel Day","MH",2042 +"2042-12-25","Christmas Day","MH",2042 +"2043-01-01","New Year's Day","MH",2043 +"2043-03-01","Nuclear Victims Remembrance Day","MH",2043 +"2043-03-02","Nuclear Victims Remembrance Day (Holiday)","MH",2043 +"2043-03-27","Good Friday","MH",2043 +"2043-05-01","Constitution Day","MH",2043 +"2043-07-03","Fisherman's Day","MH",2043 +"2043-09-04","Dri-jerbal Day","MH",2043 +"2043-09-25","Manit Day","MH",2043 +"2043-11-17","President's Day","MH",2043 +"2043-12-04","Gospel Day","MH",2043 +"2043-12-25","Christmas Day","MH",2043 +"2044-01-01","New Year's Day","MH",2044 +"2044-03-01","Nuclear Victims Remembrance Day","MH",2044 +"2044-04-15","Good Friday","MH",2044 +"2044-05-01","Constitution Day","MH",2044 +"2044-07-01","Fisherman's Day","MH",2044 +"2044-09-02","Dri-jerbal Day","MH",2044 +"2044-09-30","Manit Day","MH",2044 +"2044-11-17","President's Day","MH",2044 +"2044-12-02","Gospel Day","MH",2044 +"2044-12-25","Christmas Day","MH",2044 +"2044-12-26","Christmas Day (Holiday)","MH",2044 +"1995-01-01","New Year's Day","MK",1995 +"1995-01-07","Christmas Day (Orthodox)","MK",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","MK",1995 +"1995-04-24","Easter Monday (Orthodox)","MK",1995 +"1995-05-01","Labour Day","MK",1995 +"1995-05-24","Saints Cyril and Methodius Day","MK",1995 +"1995-08-02","Republic Day","MK",1995 +"1995-09-08","Independence Day","MK",1995 +"1995-10-11","Day of Macedonian Uprising in 1941","MK",1995 +"1995-10-23","Day of the Macedonian Revolutionary Struggle","MK",1995 +"1995-12-08","Saint Clement of Ohrid Day","MK",1995 +"1996-01-01","New Year's Day","MK",1996 +"1996-01-07","Christmas Day (Orthodox)","MK",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","MK",1996 +"1996-04-15","Easter Monday (Orthodox)","MK",1996 +"1996-05-01","Labour Day","MK",1996 +"1996-05-24","Saints Cyril and Methodius Day","MK",1996 +"1996-08-02","Republic Day","MK",1996 +"1996-09-08","Independence Day","MK",1996 +"1996-10-11","Day of Macedonian Uprising in 1941","MK",1996 +"1996-10-23","Day of the Macedonian Revolutionary Struggle","MK",1996 +"1996-12-08","Saint Clement of Ohrid Day","MK",1996 +"1997-01-01","New Year's Day","MK",1997 +"1997-01-07","Christmas Day (Orthodox)","MK",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","MK",1997 +"1997-04-28","Easter Monday (Orthodox)","MK",1997 +"1997-05-01","Labour Day","MK",1997 +"1997-05-24","Saints Cyril and Methodius Day","MK",1997 +"1997-08-02","Republic Day","MK",1997 +"1997-09-08","Independence Day","MK",1997 +"1997-10-11","Day of Macedonian Uprising in 1941","MK",1997 +"1997-10-23","Day of the Macedonian Revolutionary Struggle","MK",1997 +"1997-12-08","Saint Clement of Ohrid Day","MK",1997 +"1998-01-01","New Year's Day","MK",1998 +"1998-01-07","Christmas Day (Orthodox)","MK",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","MK",1998 +"1998-04-20","Easter Monday (Orthodox)","MK",1998 +"1998-05-01","Labour Day","MK",1998 +"1998-05-24","Saints Cyril and Methodius Day","MK",1998 +"1998-08-02","Republic Day","MK",1998 +"1998-09-08","Independence Day","MK",1998 +"1998-10-11","Day of Macedonian Uprising in 1941","MK",1998 +"1998-10-23","Day of the Macedonian Revolutionary Struggle","MK",1998 +"1998-12-08","Saint Clement of Ohrid Day","MK",1998 +"1999-01-01","New Year's Day","MK",1999 +"1999-01-07","Christmas Day (Orthodox)","MK",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","MK",1999 +"1999-04-12","Easter Monday (Orthodox)","MK",1999 +"1999-05-01","Labour Day","MK",1999 +"1999-05-24","Saints Cyril and Methodius Day","MK",1999 +"1999-08-02","Republic Day","MK",1999 +"1999-09-08","Independence Day","MK",1999 +"1999-10-11","Day of Macedonian Uprising in 1941","MK",1999 +"1999-10-23","Day of the Macedonian Revolutionary Struggle","MK",1999 +"1999-12-08","Saint Clement of Ohrid Day","MK",1999 +"2000-01-01","New Year's Day","MK",2000 +"2000-01-07","Christmas Day (Orthodox)","MK",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","MK",2000 +"2000-05-01","Easter Monday (Orthodox)","MK",2000 +"2000-05-01","Labour Day","MK",2000 +"2000-05-24","Saints Cyril and Methodius Day","MK",2000 +"2000-08-02","Republic Day","MK",2000 +"2000-09-08","Independence Day","MK",2000 +"2000-10-11","Day of Macedonian Uprising in 1941","MK",2000 +"2000-10-23","Day of the Macedonian Revolutionary Struggle","MK",2000 +"2000-12-08","Saint Clement of Ohrid Day","MK",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","MK",2000 +"2001-01-01","New Year's Day","MK",2001 +"2001-01-07","Christmas Day (Orthodox)","MK",2001 +"2001-04-16","Easter Monday (Orthodox)","MK",2001 +"2001-05-01","Labour Day","MK",2001 +"2001-05-24","Saints Cyril and Methodius Day","MK",2001 +"2001-08-02","Republic Day","MK",2001 +"2001-09-08","Independence Day","MK",2001 +"2001-10-11","Day of Macedonian Uprising in 1941","MK",2001 +"2001-10-23","Day of the Macedonian Revolutionary Struggle","MK",2001 +"2001-12-08","Saint Clement of Ohrid Day","MK",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","MK",2001 +"2002-01-01","New Year's Day","MK",2002 +"2002-01-07","Christmas Day (Orthodox)","MK",2002 +"2002-05-01","Labour Day","MK",2002 +"2002-05-06","Easter Monday (Orthodox)","MK",2002 +"2002-05-24","Saints Cyril and Methodius Day","MK",2002 +"2002-08-02","Republic Day","MK",2002 +"2002-09-08","Independence Day","MK",2002 +"2002-10-11","Day of Macedonian Uprising in 1941","MK",2002 +"2002-10-23","Day of the Macedonian Revolutionary Struggle","MK",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","MK",2002 +"2002-12-08","Saint Clement of Ohrid Day","MK",2002 +"2003-01-01","New Year's Day","MK",2003 +"2003-01-07","Christmas Day (Orthodox)","MK",2003 +"2003-04-28","Easter Monday (Orthodox)","MK",2003 +"2003-05-01","Labour Day","MK",2003 +"2003-05-24","Saints Cyril and Methodius Day","MK",2003 +"2003-08-02","Republic Day","MK",2003 +"2003-09-08","Independence Day","MK",2003 +"2003-10-11","Day of Macedonian Uprising in 1941","MK",2003 +"2003-10-23","Day of the Macedonian Revolutionary Struggle","MK",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","MK",2003 +"2003-12-08","Saint Clement of Ohrid Day","MK",2003 +"2004-01-01","New Year's Day","MK",2004 +"2004-01-07","Christmas Day (Orthodox)","MK",2004 +"2004-04-12","Easter Monday (Orthodox)","MK",2004 +"2004-05-01","Labour Day","MK",2004 +"2004-05-24","Saints Cyril and Methodius Day","MK",2004 +"2004-08-02","Republic Day","MK",2004 +"2004-09-08","Independence Day","MK",2004 +"2004-10-11","Day of Macedonian Uprising in 1941","MK",2004 +"2004-10-23","Day of the Macedonian Revolutionary Struggle","MK",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","MK",2004 +"2004-12-08","Saint Clement of Ohrid Day","MK",2004 +"2005-01-01","New Year's Day","MK",2005 +"2005-01-07","Christmas Day (Orthodox)","MK",2005 +"2005-05-01","Labour Day","MK",2005 +"2005-05-02","Easter Monday (Orthodox)","MK",2005 +"2005-05-24","Saints Cyril and Methodius Day","MK",2005 +"2005-08-02","Republic Day","MK",2005 +"2005-09-08","Independence Day","MK",2005 +"2005-10-11","Day of Macedonian Uprising in 1941","MK",2005 +"2005-10-23","Day of the Macedonian Revolutionary Struggle","MK",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","MK",2005 +"2005-12-08","Saint Clement of Ohrid Day","MK",2005 +"2006-01-01","New Year's Day","MK",2006 +"2006-01-07","Christmas Day (Orthodox)","MK",2006 +"2006-04-24","Easter Monday (Orthodox)","MK",2006 +"2006-05-01","Labour Day","MK",2006 +"2006-05-24","Saints Cyril and Methodius Day","MK",2006 +"2006-08-02","Republic Day","MK",2006 +"2006-09-08","Independence Day","MK",2006 +"2006-10-11","Day of Macedonian Uprising in 1941","MK",2006 +"2006-10-23","Day of the Macedonian Revolutionary Struggle","MK",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","MK",2006 +"2006-12-08","Saint Clement of Ohrid Day","MK",2006 +"2007-01-01","New Year's Day","MK",2007 +"2007-01-07","Christmas Day (Orthodox)","MK",2007 +"2007-04-09","Easter Monday (Orthodox)","MK",2007 +"2007-05-01","Labour Day","MK",2007 +"2007-05-24","Saints Cyril and Methodius Day","MK",2007 +"2007-08-02","Republic Day","MK",2007 +"2007-09-08","Independence Day","MK",2007 +"2007-10-11","Day of Macedonian Uprising in 1941","MK",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","MK",2007 +"2007-10-23","Day of the Macedonian Revolutionary Struggle","MK",2007 +"2007-12-08","Saint Clement of Ohrid Day","MK",2007 +"2008-01-01","New Year's Day","MK",2008 +"2008-01-07","Christmas Day (Orthodox)","MK",2008 +"2008-04-28","Easter Monday (Orthodox)","MK",2008 +"2008-05-01","Labour Day","MK",2008 +"2008-05-24","Saints Cyril and Methodius Day","MK",2008 +"2008-08-02","Republic Day","MK",2008 +"2008-09-08","Independence Day","MK",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","MK",2008 +"2008-10-11","Day of Macedonian Uprising in 1941","MK",2008 +"2008-10-23","Day of the Macedonian Revolutionary Struggle","MK",2008 +"2008-12-08","Saint Clement of Ohrid Day","MK",2008 +"2009-01-01","New Year's Day","MK",2009 +"2009-01-07","Christmas Day (Orthodox)","MK",2009 +"2009-04-20","Easter Monday (Orthodox)","MK",2009 +"2009-05-01","Labour Day","MK",2009 +"2009-05-24","Saints Cyril and Methodius Day","MK",2009 +"2009-08-02","Republic Day","MK",2009 +"2009-09-08","Independence Day","MK",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","MK",2009 +"2009-10-11","Day of Macedonian Uprising in 1941","MK",2009 +"2009-10-23","Day of the Macedonian Revolutionary Struggle","MK",2009 +"2009-12-08","Saint Clement of Ohrid Day","MK",2009 +"2010-01-01","New Year's Day","MK",2010 +"2010-01-07","Christmas Day (Orthodox)","MK",2010 +"2010-04-05","Easter Monday (Orthodox)","MK",2010 +"2010-05-01","Labour Day","MK",2010 +"2010-05-24","Saints Cyril and Methodius Day","MK",2010 +"2010-08-02","Republic Day","MK",2010 +"2010-09-08","Independence Day","MK",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","MK",2010 +"2010-10-11","Day of Macedonian Uprising in 1941","MK",2010 +"2010-10-23","Day of the Macedonian Revolutionary Struggle","MK",2010 +"2010-12-08","Saint Clement of Ohrid Day","MK",2010 +"2011-01-01","New Year's Day","MK",2011 +"2011-01-07","Christmas Day (Orthodox)","MK",2011 +"2011-04-25","Easter Monday (Orthodox)","MK",2011 +"2011-05-01","Labour Day","MK",2011 +"2011-05-24","Saints Cyril and Methodius Day","MK",2011 +"2011-08-02","Republic Day","MK",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","MK",2011 +"2011-09-08","Independence Day","MK",2011 +"2011-10-11","Day of Macedonian Uprising in 1941","MK",2011 +"2011-10-23","Day of the Macedonian Revolutionary Struggle","MK",2011 +"2011-12-08","Saint Clement of Ohrid Day","MK",2011 +"2012-01-01","New Year's Day","MK",2012 +"2012-01-07","Christmas Day (Orthodox)","MK",2012 +"2012-04-16","Easter Monday (Orthodox)","MK",2012 +"2012-05-01","Labour Day","MK",2012 +"2012-05-24","Saints Cyril and Methodius Day","MK",2012 +"2012-08-02","Republic Day","MK",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","MK",2012 +"2012-09-08","Independence Day","MK",2012 +"2012-10-11","Day of Macedonian Uprising in 1941","MK",2012 +"2012-10-23","Day of the Macedonian Revolutionary Struggle","MK",2012 +"2012-12-08","Saint Clement of Ohrid Day","MK",2012 +"2013-01-01","New Year's Day","MK",2013 +"2013-01-07","Christmas Day (Orthodox)","MK",2013 +"2013-05-01","Labour Day","MK",2013 +"2013-05-06","Easter Monday (Orthodox)","MK",2013 +"2013-05-24","Saints Cyril and Methodius Day","MK",2013 +"2013-08-02","Republic Day","MK",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","MK",2013 +"2013-09-08","Independence Day","MK",2013 +"2013-10-11","Day of Macedonian Uprising in 1941","MK",2013 +"2013-10-23","Day of the Macedonian Revolutionary Struggle","MK",2013 +"2013-12-08","Saint Clement of Ohrid Day","MK",2013 +"2014-01-01","New Year's Day","MK",2014 +"2014-01-07","Christmas Day (Orthodox)","MK",2014 +"2014-04-21","Easter Monday (Orthodox)","MK",2014 +"2014-05-01","Labour Day","MK",2014 +"2014-05-24","Saints Cyril and Methodius Day","MK",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","MK",2014 +"2014-08-02","Republic Day","MK",2014 +"2014-09-08","Independence Day","MK",2014 +"2014-10-11","Day of Macedonian Uprising in 1941","MK",2014 +"2014-10-23","Day of the Macedonian Revolutionary Struggle","MK",2014 +"2014-12-08","Saint Clement of Ohrid Day","MK",2014 +"2015-01-01","New Year's Day","MK",2015 +"2015-01-07","Christmas Day (Orthodox)","MK",2015 +"2015-04-13","Easter Monday (Orthodox)","MK",2015 +"2015-05-01","Labour Day","MK",2015 +"2015-05-24","Saints Cyril and Methodius Day","MK",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","MK",2015 +"2015-08-02","Republic Day","MK",2015 +"2015-09-08","Independence Day","MK",2015 +"2015-10-11","Day of Macedonian Uprising in 1941","MK",2015 +"2015-10-23","Day of the Macedonian Revolutionary Struggle","MK",2015 +"2015-12-08","Saint Clement of Ohrid Day","MK",2015 +"2016-01-01","New Year's Day","MK",2016 +"2016-01-07","Christmas Day (Orthodox)","MK",2016 +"2016-05-01","Labour Day","MK",2016 +"2016-05-02","Easter Monday (Orthodox)","MK",2016 +"2016-05-24","Saints Cyril and Methodius Day","MK",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","MK",2016 +"2016-08-02","Republic Day","MK",2016 +"2016-09-08","Independence Day","MK",2016 +"2016-10-11","Day of Macedonian Uprising in 1941","MK",2016 +"2016-10-23","Day of the Macedonian Revolutionary Struggle","MK",2016 +"2016-12-08","Saint Clement of Ohrid Day","MK",2016 +"2017-01-01","New Year's Day","MK",2017 +"2017-01-07","Christmas Day (Orthodox)","MK",2017 +"2017-04-17","Easter Monday (Orthodox)","MK",2017 +"2017-05-01","Labour Day","MK",2017 +"2017-05-24","Saints Cyril and Methodius Day","MK",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","MK",2017 +"2017-08-02","Republic Day","MK",2017 +"2017-09-08","Independence Day","MK",2017 +"2017-10-11","Day of Macedonian Uprising in 1941","MK",2017 +"2017-10-23","Day of the Macedonian Revolutionary Struggle","MK",2017 +"2017-12-08","Saint Clement of Ohrid Day","MK",2017 +"2018-01-01","New Year's Day","MK",2018 +"2018-01-07","Christmas Day (Orthodox)","MK",2018 +"2018-04-09","Easter Monday (Orthodox)","MK",2018 +"2018-05-01","Labour Day","MK",2018 +"2018-05-24","Saints Cyril and Methodius Day","MK",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","MK",2018 +"2018-08-02","Republic Day","MK",2018 +"2018-09-08","Independence Day","MK",2018 +"2018-10-11","Day of Macedonian Uprising in 1941","MK",2018 +"2018-10-23","Day of the Macedonian Revolutionary Struggle","MK",2018 +"2018-12-08","Saint Clement of Ohrid Day","MK",2018 +"2019-01-01","New Year's Day","MK",2019 +"2019-01-07","Christmas Day (Orthodox)","MK",2019 +"2019-04-29","Easter Monday (Orthodox)","MK",2019 +"2019-05-01","Labour Day","MK",2019 +"2019-05-24","Saints Cyril and Methodius Day","MK",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","MK",2019 +"2019-08-02","Republic Day","MK",2019 +"2019-09-08","Independence Day","MK",2019 +"2019-10-11","Day of Macedonian Uprising in 1941","MK",2019 +"2019-10-23","Day of the Macedonian Revolutionary Struggle","MK",2019 +"2019-12-08","Saint Clement of Ohrid Day","MK",2019 +"2020-01-01","New Year's Day","MK",2020 +"2020-01-07","Christmas Day (Orthodox)","MK",2020 +"2020-04-20","Easter Monday (Orthodox)","MK",2020 +"2020-05-01","Labour Day","MK",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","MK",2020 +"2020-05-24","Saints Cyril and Methodius Day","MK",2020 +"2020-08-02","Republic Day","MK",2020 +"2020-09-08","Independence Day","MK",2020 +"2020-10-11","Day of Macedonian Uprising in 1941","MK",2020 +"2020-10-23","Day of the Macedonian Revolutionary Struggle","MK",2020 +"2020-12-08","Saint Clement of Ohrid Day","MK",2020 +"2021-01-01","New Year's Day","MK",2021 +"2021-01-07","Christmas Day (Orthodox)","MK",2021 +"2021-05-01","Labour Day","MK",2021 +"2021-05-03","Easter Monday (Orthodox)","MK",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","MK",2021 +"2021-05-24","Saints Cyril and Methodius Day","MK",2021 +"2021-08-02","Republic Day","MK",2021 +"2021-09-08","Independence Day","MK",2021 +"2021-10-11","Day of Macedonian Uprising in 1941","MK",2021 +"2021-10-23","Day of the Macedonian Revolutionary Struggle","MK",2021 +"2021-12-08","Saint Clement of Ohrid Day","MK",2021 +"2022-01-01","New Year's Day","MK",2022 +"2022-01-07","Christmas Day (Orthodox)","MK",2022 +"2022-04-25","Easter Monday (Orthodox)","MK",2022 +"2022-05-01","Labour Day","MK",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","MK",2022 +"2022-05-24","Saints Cyril and Methodius Day","MK",2022 +"2022-08-02","Republic Day","MK",2022 +"2022-09-08","Independence Day","MK",2022 +"2022-10-11","Day of Macedonian Uprising in 1941","MK",2022 +"2022-10-23","Day of the Macedonian Revolutionary Struggle","MK",2022 +"2022-12-08","Saint Clement of Ohrid Day","MK",2022 +"2023-01-01","New Year's Day","MK",2023 +"2023-01-07","Christmas Day (Orthodox)","MK",2023 +"2023-04-17","Easter Monday (Orthodox)","MK",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","MK",2023 +"2023-05-01","Labour Day","MK",2023 +"2023-05-24","Saints Cyril and Methodius Day","MK",2023 +"2023-08-02","Republic Day","MK",2023 +"2023-09-08","Independence Day","MK",2023 +"2023-10-11","Day of Macedonian Uprising in 1941","MK",2023 +"2023-10-23","Day of the Macedonian Revolutionary Struggle","MK",2023 +"2023-12-08","Saint Clement of Ohrid Day","MK",2023 +"2024-01-01","New Year's Day","MK",2024 +"2024-01-07","Christmas Day (Orthodox)","MK",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","MK",2024 +"2024-05-01","Labour Day","MK",2024 +"2024-05-06","Easter Monday (Orthodox)","MK",2024 +"2024-05-24","Saints Cyril and Methodius Day","MK",2024 +"2024-08-02","Republic Day","MK",2024 +"2024-09-08","Independence Day","MK",2024 +"2024-10-11","Day of Macedonian Uprising in 1941","MK",2024 +"2024-10-23","Day of the Macedonian Revolutionary Struggle","MK",2024 +"2024-12-08","Saint Clement of Ohrid Day","MK",2024 +"2025-01-01","New Year's Day","MK",2025 +"2025-01-07","Christmas Day (Orthodox)","MK",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","MK",2025 +"2025-04-21","Easter Monday (Orthodox)","MK",2025 +"2025-05-01","Labour Day","MK",2025 +"2025-05-24","Saints Cyril and Methodius Day","MK",2025 +"2025-08-02","Republic Day","MK",2025 +"2025-09-08","Independence Day","MK",2025 +"2025-10-11","Day of Macedonian Uprising in 1941","MK",2025 +"2025-10-23","Day of the Macedonian Revolutionary Struggle","MK",2025 +"2025-12-08","Saint Clement of Ohrid Day","MK",2025 +"2026-01-01","New Year's Day","MK",2026 +"2026-01-07","Christmas Day (Orthodox)","MK",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","MK",2026 +"2026-04-13","Easter Monday (Orthodox)","MK",2026 +"2026-05-01","Labour Day","MK",2026 +"2026-05-24","Saints Cyril and Methodius Day","MK",2026 +"2026-08-02","Republic Day","MK",2026 +"2026-09-08","Independence Day","MK",2026 +"2026-10-11","Day of Macedonian Uprising in 1941","MK",2026 +"2026-10-23","Day of the Macedonian Revolutionary Struggle","MK",2026 +"2026-12-08","Saint Clement of Ohrid Day","MK",2026 +"2027-01-01","New Year's Day","MK",2027 +"2027-01-07","Christmas Day (Orthodox)","MK",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","MK",2027 +"2027-05-01","Labour Day","MK",2027 +"2027-05-03","Easter Monday (Orthodox)","MK",2027 +"2027-05-24","Saints Cyril and Methodius Day","MK",2027 +"2027-08-02","Republic Day","MK",2027 +"2027-09-08","Independence Day","MK",2027 +"2027-10-11","Day of Macedonian Uprising in 1941","MK",2027 +"2027-10-23","Day of the Macedonian Revolutionary Struggle","MK",2027 +"2027-12-08","Saint Clement of Ohrid Day","MK",2027 +"2028-01-01","New Year's Day","MK",2028 +"2028-01-07","Christmas Day (Orthodox)","MK",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","MK",2028 +"2028-04-17","Easter Monday (Orthodox)","MK",2028 +"2028-05-01","Labour Day","MK",2028 +"2028-05-24","Saints Cyril and Methodius Day","MK",2028 +"2028-08-02","Republic Day","MK",2028 +"2028-09-08","Independence Day","MK",2028 +"2028-10-11","Day of Macedonian Uprising in 1941","MK",2028 +"2028-10-23","Day of the Macedonian Revolutionary Struggle","MK",2028 +"2028-12-08","Saint Clement of Ohrid Day","MK",2028 +"2029-01-01","New Year's Day","MK",2029 +"2029-01-07","Christmas Day (Orthodox)","MK",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","MK",2029 +"2029-04-09","Easter Monday (Orthodox)","MK",2029 +"2029-05-01","Labour Day","MK",2029 +"2029-05-24","Saints Cyril and Methodius Day","MK",2029 +"2029-08-02","Republic Day","MK",2029 +"2029-09-08","Independence Day","MK",2029 +"2029-10-11","Day of Macedonian Uprising in 1941","MK",2029 +"2029-10-23","Day of the Macedonian Revolutionary Struggle","MK",2029 +"2029-12-08","Saint Clement of Ohrid Day","MK",2029 +"2030-01-01","New Year's Day","MK",2030 +"2030-01-07","Christmas Day (Orthodox)","MK",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","MK",2030 +"2030-04-29","Easter Monday (Orthodox)","MK",2030 +"2030-05-01","Labour Day","MK",2030 +"2030-05-24","Saints Cyril and Methodius Day","MK",2030 +"2030-08-02","Republic Day","MK",2030 +"2030-09-08","Independence Day","MK",2030 +"2030-10-11","Day of Macedonian Uprising in 1941","MK",2030 +"2030-10-23","Day of the Macedonian Revolutionary Struggle","MK",2030 +"2030-12-08","Saint Clement of Ohrid Day","MK",2030 +"2031-01-01","New Year's Day","MK",2031 +"2031-01-07","Christmas Day (Orthodox)","MK",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","MK",2031 +"2031-04-14","Easter Monday (Orthodox)","MK",2031 +"2031-05-01","Labour Day","MK",2031 +"2031-05-24","Saints Cyril and Methodius Day","MK",2031 +"2031-08-02","Republic Day","MK",2031 +"2031-09-08","Independence Day","MK",2031 +"2031-10-11","Day of Macedonian Uprising in 1941","MK",2031 +"2031-10-23","Day of the Macedonian Revolutionary Struggle","MK",2031 +"2031-12-08","Saint Clement of Ohrid Day","MK",2031 +"2032-01-01","New Year's Day","MK",2032 +"2032-01-07","Christmas Day (Orthodox)","MK",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","MK",2032 +"2032-05-01","Labour Day","MK",2032 +"2032-05-03","Easter Monday (Orthodox)","MK",2032 +"2032-05-24","Saints Cyril and Methodius Day","MK",2032 +"2032-08-02","Republic Day","MK",2032 +"2032-09-08","Independence Day","MK",2032 +"2032-10-11","Day of Macedonian Uprising in 1941","MK",2032 +"2032-10-23","Day of the Macedonian Revolutionary Struggle","MK",2032 +"2032-12-08","Saint Clement of Ohrid Day","MK",2032 +"2033-01-01","New Year's Day","MK",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","MK",2033 +"2033-01-07","Christmas Day (Orthodox)","MK",2033 +"2033-04-25","Easter Monday (Orthodox)","MK",2033 +"2033-05-01","Labour Day","MK",2033 +"2033-05-24","Saints Cyril and Methodius Day","MK",2033 +"2033-08-02","Republic Day","MK",2033 +"2033-09-08","Independence Day","MK",2033 +"2033-10-11","Day of Macedonian Uprising in 1941","MK",2033 +"2033-10-23","Day of the Macedonian Revolutionary Struggle","MK",2033 +"2033-12-08","Saint Clement of Ohrid Day","MK",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","MK",2033 +"2034-01-01","New Year's Day","MK",2034 +"2034-01-07","Christmas Day (Orthodox)","MK",2034 +"2034-04-10","Easter Monday (Orthodox)","MK",2034 +"2034-05-01","Labour Day","MK",2034 +"2034-05-24","Saints Cyril and Methodius Day","MK",2034 +"2034-08-02","Republic Day","MK",2034 +"2034-09-08","Independence Day","MK",2034 +"2034-10-11","Day of Macedonian Uprising in 1941","MK",2034 +"2034-10-23","Day of the Macedonian Revolutionary Struggle","MK",2034 +"2034-12-08","Saint Clement of Ohrid Day","MK",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","MK",2034 +"2035-01-01","New Year's Day","MK",2035 +"2035-01-07","Christmas Day (Orthodox)","MK",2035 +"2035-04-30","Easter Monday (Orthodox)","MK",2035 +"2035-05-01","Labour Day","MK",2035 +"2035-05-24","Saints Cyril and Methodius Day","MK",2035 +"2035-08-02","Republic Day","MK",2035 +"2035-09-08","Independence Day","MK",2035 +"2035-10-11","Day of Macedonian Uprising in 1941","MK",2035 +"2035-10-23","Day of the Macedonian Revolutionary Struggle","MK",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","MK",2035 +"2035-12-08","Saint Clement of Ohrid Day","MK",2035 +"2036-01-01","New Year's Day","MK",2036 +"2036-01-07","Christmas Day (Orthodox)","MK",2036 +"2036-04-21","Easter Monday (Orthodox)","MK",2036 +"2036-05-01","Labour Day","MK",2036 +"2036-05-24","Saints Cyril and Methodius Day","MK",2036 +"2036-08-02","Republic Day","MK",2036 +"2036-09-08","Independence Day","MK",2036 +"2036-10-11","Day of Macedonian Uprising in 1941","MK",2036 +"2036-10-23","Day of the Macedonian Revolutionary Struggle","MK",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","MK",2036 +"2036-12-08","Saint Clement of Ohrid Day","MK",2036 +"2037-01-01","New Year's Day","MK",2037 +"2037-01-07","Christmas Day (Orthodox)","MK",2037 +"2037-04-06","Easter Monday (Orthodox)","MK",2037 +"2037-05-01","Labour Day","MK",2037 +"2037-05-24","Saints Cyril and Methodius Day","MK",2037 +"2037-08-02","Republic Day","MK",2037 +"2037-09-08","Independence Day","MK",2037 +"2037-10-11","Day of Macedonian Uprising in 1941","MK",2037 +"2037-10-23","Day of the Macedonian Revolutionary Struggle","MK",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","MK",2037 +"2037-12-08","Saint Clement of Ohrid Day","MK",2037 +"2038-01-01","New Year's Day","MK",2038 +"2038-01-07","Christmas Day (Orthodox)","MK",2038 +"2038-04-26","Easter Monday (Orthodox)","MK",2038 +"2038-05-01","Labour Day","MK",2038 +"2038-05-24","Saints Cyril and Methodius Day","MK",2038 +"2038-08-02","Republic Day","MK",2038 +"2038-09-08","Independence Day","MK",2038 +"2038-10-11","Day of Macedonian Uprising in 1941","MK",2038 +"2038-10-23","Day of the Macedonian Revolutionary Struggle","MK",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","MK",2038 +"2038-12-08","Saint Clement of Ohrid Day","MK",2038 +"2039-01-01","New Year's Day","MK",2039 +"2039-01-07","Christmas Day (Orthodox)","MK",2039 +"2039-04-18","Easter Monday (Orthodox)","MK",2039 +"2039-05-01","Labour Day","MK",2039 +"2039-05-24","Saints Cyril and Methodius Day","MK",2039 +"2039-08-02","Republic Day","MK",2039 +"2039-09-08","Independence Day","MK",2039 +"2039-10-11","Day of Macedonian Uprising in 1941","MK",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","MK",2039 +"2039-10-23","Day of the Macedonian Revolutionary Struggle","MK",2039 +"2039-12-08","Saint Clement of Ohrid Day","MK",2039 +"2040-01-01","New Year's Day","MK",2040 +"2040-01-07","Christmas Day (Orthodox)","MK",2040 +"2040-05-01","Labour Day","MK",2040 +"2040-05-07","Easter Monday (Orthodox)","MK",2040 +"2040-05-24","Saints Cyril and Methodius Day","MK",2040 +"2040-08-02","Republic Day","MK",2040 +"2040-09-08","Independence Day","MK",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","MK",2040 +"2040-10-11","Day of Macedonian Uprising in 1941","MK",2040 +"2040-10-23","Day of the Macedonian Revolutionary Struggle","MK",2040 +"2040-12-08","Saint Clement of Ohrid Day","MK",2040 +"2041-01-01","New Year's Day","MK",2041 +"2041-01-07","Christmas Day (Orthodox)","MK",2041 +"2041-04-22","Easter Monday (Orthodox)","MK",2041 +"2041-05-01","Labour Day","MK",2041 +"2041-05-24","Saints Cyril and Methodius Day","MK",2041 +"2041-08-02","Republic Day","MK",2041 +"2041-09-08","Independence Day","MK",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","MK",2041 +"2041-10-11","Day of Macedonian Uprising in 1941","MK",2041 +"2041-10-23","Day of the Macedonian Revolutionary Struggle","MK",2041 +"2041-12-08","Saint Clement of Ohrid Day","MK",2041 +"2042-01-01","New Year's Day","MK",2042 +"2042-01-07","Christmas Day (Orthodox)","MK",2042 +"2042-04-14","Easter Monday (Orthodox)","MK",2042 +"2042-05-01","Labour Day","MK",2042 +"2042-05-24","Saints Cyril and Methodius Day","MK",2042 +"2042-08-02","Republic Day","MK",2042 +"2042-09-08","Independence Day","MK",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","MK",2042 +"2042-10-11","Day of Macedonian Uprising in 1941","MK",2042 +"2042-10-23","Day of the Macedonian Revolutionary Struggle","MK",2042 +"2042-12-08","Saint Clement of Ohrid Day","MK",2042 +"2043-01-01","New Year's Day","MK",2043 +"2043-01-07","Christmas Day (Orthodox)","MK",2043 +"2043-05-01","Labour Day","MK",2043 +"2043-05-04","Easter Monday (Orthodox)","MK",2043 +"2043-05-24","Saints Cyril and Methodius Day","MK",2043 +"2043-08-02","Republic Day","MK",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","MK",2043 +"2043-09-08","Independence Day","MK",2043 +"2043-10-11","Day of Macedonian Uprising in 1941","MK",2043 +"2043-10-23","Day of the Macedonian Revolutionary Struggle","MK",2043 +"2043-12-08","Saint Clement of Ohrid Day","MK",2043 +"2044-01-01","New Year's Day","MK",2044 +"2044-01-07","Christmas Day (Orthodox)","MK",2044 +"2044-04-25","Easter Monday (Orthodox)","MK",2044 +"2044-05-01","Labour Day","MK",2044 +"2044-05-24","Saints Cyril and Methodius Day","MK",2044 +"2044-08-02","Republic Day","MK",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","MK",2044 +"2044-09-08","Independence Day","MK",2044 +"2044-10-11","Day of Macedonian Uprising in 1941","MK",2044 +"2044-10-23","Day of the Macedonian Revolutionary Struggle","MK",2044 +"2044-12-08","Saint Clement of Ohrid Day","MK",2044 +"1995-01-01","New Year's Day","MP",1995 +"1995-01-02","New Year's Day (Observed)","MP",1995 +"1995-01-16","Martin Luther King Jr. Day","MP",1995 +"1995-02-20","Washington's Birthday","MP",1995 +"1995-03-24","Commonwealth Covenant Day","MP",1995 +"1995-04-14","Good Friday","MP",1995 +"1995-05-29","Memorial Day","MP",1995 +"1995-07-04","Independence Day","MP",1995 +"1995-09-04","Labor Day","MP",1995 +"1995-10-09","Columbus Day","MP",1995 +"1995-10-09","Commonwealth Cultural Day","MP",1995 +"1995-11-03","Citizenship Day (Observed)","MP",1995 +"1995-11-04","Citizenship Day","MP",1995 +"1995-11-10","Veterans Day (Observed)","MP",1995 +"1995-11-11","Veterans Day","MP",1995 +"1995-11-23","Thanksgiving","MP",1995 +"1995-12-08","Constitution Day","MP",1995 +"1995-12-25","Christmas Day","MP",1995 +"1996-01-01","New Year's Day","MP",1996 +"1996-01-15","Martin Luther King Jr. Day","MP",1996 +"1996-02-19","Washington's Birthday","MP",1996 +"1996-03-24","Commonwealth Covenant Day","MP",1996 +"1996-03-25","Commonwealth Covenant Day (Observed)","MP",1996 +"1996-04-05","Good Friday","MP",1996 +"1996-05-27","Memorial Day","MP",1996 +"1996-07-04","Independence Day","MP",1996 +"1996-09-02","Labor Day","MP",1996 +"1996-10-14","Columbus Day","MP",1996 +"1996-10-14","Commonwealth Cultural Day","MP",1996 +"1996-11-04","Citizenship Day","MP",1996 +"1996-11-11","Veterans Day","MP",1996 +"1996-11-28","Thanksgiving","MP",1996 +"1996-12-08","Constitution Day","MP",1996 +"1996-12-09","Constitution Day (Observed)","MP",1996 +"1996-12-25","Christmas Day","MP",1996 +"1997-01-01","New Year's Day","MP",1997 +"1997-01-20","Martin Luther King Jr. Day","MP",1997 +"1997-02-17","Washington's Birthday","MP",1997 +"1997-03-24","Commonwealth Covenant Day","MP",1997 +"1997-03-28","Good Friday","MP",1997 +"1997-05-26","Memorial Day","MP",1997 +"1997-07-04","Independence Day","MP",1997 +"1997-09-01","Labor Day","MP",1997 +"1997-10-13","Columbus Day","MP",1997 +"1997-10-13","Commonwealth Cultural Day","MP",1997 +"1997-11-04","Citizenship Day","MP",1997 +"1997-11-11","Veterans Day","MP",1997 +"1997-11-27","Thanksgiving","MP",1997 +"1997-12-08","Constitution Day","MP",1997 +"1997-12-25","Christmas Day","MP",1997 +"1998-01-01","New Year's Day","MP",1998 +"1998-01-19","Martin Luther King Jr. Day","MP",1998 +"1998-02-16","Washington's Birthday","MP",1998 +"1998-03-24","Commonwealth Covenant Day","MP",1998 +"1998-04-10","Good Friday","MP",1998 +"1998-05-25","Memorial Day","MP",1998 +"1998-07-03","Independence Day (Observed)","MP",1998 +"1998-07-04","Independence Day","MP",1998 +"1998-09-07","Labor Day","MP",1998 +"1998-10-12","Columbus Day","MP",1998 +"1998-10-12","Commonwealth Cultural Day","MP",1998 +"1998-11-04","Citizenship Day","MP",1998 +"1998-11-11","Veterans Day","MP",1998 +"1998-11-26","Thanksgiving","MP",1998 +"1998-12-08","Constitution Day","MP",1998 +"1998-12-25","Christmas Day","MP",1998 +"1999-01-01","New Year's Day","MP",1999 +"1999-01-18","Martin Luther King Jr. Day","MP",1999 +"1999-02-15","Washington's Birthday","MP",1999 +"1999-03-24","Commonwealth Covenant Day","MP",1999 +"1999-04-02","Good Friday","MP",1999 +"1999-05-31","Memorial Day","MP",1999 +"1999-07-04","Independence Day","MP",1999 +"1999-07-05","Independence Day (Observed)","MP",1999 +"1999-09-06","Labor Day","MP",1999 +"1999-10-11","Columbus Day","MP",1999 +"1999-10-11","Commonwealth Cultural Day","MP",1999 +"1999-11-04","Citizenship Day","MP",1999 +"1999-11-11","Veterans Day","MP",1999 +"1999-11-25","Thanksgiving","MP",1999 +"1999-12-08","Constitution Day","MP",1999 +"1999-12-24","Christmas Day (Observed)","MP",1999 +"1999-12-25","Christmas Day","MP",1999 +"1999-12-31","New Year's Day (Observed)","MP",1999 +"2000-01-01","New Year's Day","MP",2000 +"2000-01-17","Martin Luther King Jr. Day","MP",2000 +"2000-02-21","Washington's Birthday","MP",2000 +"2000-03-24","Commonwealth Covenant Day","MP",2000 +"2000-04-21","Good Friday","MP",2000 +"2000-05-29","Memorial Day","MP",2000 +"2000-07-04","Independence Day","MP",2000 +"2000-09-04","Labor Day","MP",2000 +"2000-10-09","Columbus Day","MP",2000 +"2000-10-09","Commonwealth Cultural Day","MP",2000 +"2000-11-03","Citizenship Day (Observed)","MP",2000 +"2000-11-04","Citizenship Day","MP",2000 +"2000-11-10","Veterans Day (Observed)","MP",2000 +"2000-11-11","Veterans Day","MP",2000 +"2000-11-23","Thanksgiving","MP",2000 +"2000-12-08","Constitution Day","MP",2000 +"2000-12-25","Christmas Day","MP",2000 +"2001-01-01","New Year's Day","MP",2001 +"2001-01-15","Martin Luther King Jr. Day","MP",2001 +"2001-02-19","Washington's Birthday","MP",2001 +"2001-03-23","Commonwealth Covenant Day (Observed)","MP",2001 +"2001-03-24","Commonwealth Covenant Day","MP",2001 +"2001-04-13","Good Friday","MP",2001 +"2001-05-28","Memorial Day","MP",2001 +"2001-07-04","Independence Day","MP",2001 +"2001-09-03","Labor Day","MP",2001 +"2001-10-08","Columbus Day","MP",2001 +"2001-10-08","Commonwealth Cultural Day","MP",2001 +"2001-11-04","Citizenship Day","MP",2001 +"2001-11-05","Citizenship Day (Observed)","MP",2001 +"2001-11-11","Veterans Day","MP",2001 +"2001-11-12","Veterans Day (Observed)","MP",2001 +"2001-11-22","Thanksgiving","MP",2001 +"2001-12-07","Constitution Day (Observed)","MP",2001 +"2001-12-08","Constitution Day","MP",2001 +"2001-12-25","Christmas Day","MP",2001 +"2002-01-01","New Year's Day","MP",2002 +"2002-01-21","Martin Luther King Jr. Day","MP",2002 +"2002-02-18","Washington's Birthday","MP",2002 +"2002-03-24","Commonwealth Covenant Day","MP",2002 +"2002-03-25","Commonwealth Covenant Day (Observed)","MP",2002 +"2002-03-29","Good Friday","MP",2002 +"2002-05-27","Memorial Day","MP",2002 +"2002-07-04","Independence Day","MP",2002 +"2002-09-02","Labor Day","MP",2002 +"2002-10-14","Columbus Day","MP",2002 +"2002-10-14","Commonwealth Cultural Day","MP",2002 +"2002-11-04","Citizenship Day","MP",2002 +"2002-11-11","Veterans Day","MP",2002 +"2002-11-28","Thanksgiving","MP",2002 +"2002-12-08","Constitution Day","MP",2002 +"2002-12-09","Constitution Day (Observed)","MP",2002 +"2002-12-25","Christmas Day","MP",2002 +"2003-01-01","New Year's Day","MP",2003 +"2003-01-20","Martin Luther King Jr. Day","MP",2003 +"2003-02-17","Washington's Birthday","MP",2003 +"2003-03-24","Commonwealth Covenant Day","MP",2003 +"2003-04-18","Good Friday","MP",2003 +"2003-05-26","Memorial Day","MP",2003 +"2003-07-04","Independence Day","MP",2003 +"2003-09-01","Labor Day","MP",2003 +"2003-10-13","Columbus Day","MP",2003 +"2003-10-13","Commonwealth Cultural Day","MP",2003 +"2003-11-04","Citizenship Day","MP",2003 +"2003-11-11","Veterans Day","MP",2003 +"2003-11-27","Thanksgiving","MP",2003 +"2003-12-08","Constitution Day","MP",2003 +"2003-12-25","Christmas Day","MP",2003 +"2004-01-01","New Year's Day","MP",2004 +"2004-01-19","Martin Luther King Jr. Day","MP",2004 +"2004-02-16","Washington's Birthday","MP",2004 +"2004-03-24","Commonwealth Covenant Day","MP",2004 +"2004-04-09","Good Friday","MP",2004 +"2004-05-31","Memorial Day","MP",2004 +"2004-07-04","Independence Day","MP",2004 +"2004-07-05","Independence Day (Observed)","MP",2004 +"2004-09-06","Labor Day","MP",2004 +"2004-10-11","Columbus Day","MP",2004 +"2004-10-11","Commonwealth Cultural Day","MP",2004 +"2004-11-04","Citizenship Day","MP",2004 +"2004-11-11","Veterans Day","MP",2004 +"2004-11-25","Thanksgiving","MP",2004 +"2004-12-08","Constitution Day","MP",2004 +"2004-12-24","Christmas Day (Observed)","MP",2004 +"2004-12-25","Christmas Day","MP",2004 +"2004-12-31","New Year's Day (Observed)","MP",2004 +"2005-01-01","New Year's Day","MP",2005 +"2005-01-17","Martin Luther King Jr. Day","MP",2005 +"2005-02-21","Washington's Birthday","MP",2005 +"2005-03-24","Commonwealth Covenant Day","MP",2005 +"2005-03-25","Good Friday","MP",2005 +"2005-05-30","Memorial Day","MP",2005 +"2005-07-04","Independence Day","MP",2005 +"2005-09-05","Labor Day","MP",2005 +"2005-10-10","Columbus Day","MP",2005 +"2005-10-10","Commonwealth Cultural Day","MP",2005 +"2005-11-04","Citizenship Day","MP",2005 +"2005-11-11","Veterans Day","MP",2005 +"2005-11-24","Thanksgiving","MP",2005 +"2005-12-08","Constitution Day","MP",2005 +"2005-12-25","Christmas Day","MP",2005 +"2005-12-26","Christmas Day (Observed)","MP",2005 +"2006-01-01","New Year's Day","MP",2006 +"2006-01-02","New Year's Day (Observed)","MP",2006 +"2006-01-16","Martin Luther King Jr. Day","MP",2006 +"2006-02-20","Washington's Birthday","MP",2006 +"2006-03-24","Commonwealth Covenant Day","MP",2006 +"2006-04-14","Good Friday","MP",2006 +"2006-05-29","Memorial Day","MP",2006 +"2006-07-04","Independence Day","MP",2006 +"2006-09-04","Labor Day","MP",2006 +"2006-10-09","Columbus Day","MP",2006 +"2006-10-09","Commonwealth Cultural Day","MP",2006 +"2006-11-03","Citizenship Day (Observed)","MP",2006 +"2006-11-04","Citizenship Day","MP",2006 +"2006-11-10","Veterans Day (Observed)","MP",2006 +"2006-11-11","Veterans Day","MP",2006 +"2006-11-23","Thanksgiving","MP",2006 +"2006-12-08","Constitution Day","MP",2006 +"2006-12-25","Christmas Day","MP",2006 +"2007-01-01","New Year's Day","MP",2007 +"2007-01-15","Martin Luther King Jr. Day","MP",2007 +"2007-02-19","Washington's Birthday","MP",2007 +"2007-03-23","Commonwealth Covenant Day (Observed)","MP",2007 +"2007-03-24","Commonwealth Covenant Day","MP",2007 +"2007-04-06","Good Friday","MP",2007 +"2007-05-28","Memorial Day","MP",2007 +"2007-07-04","Independence Day","MP",2007 +"2007-09-03","Labor Day","MP",2007 +"2007-10-08","Columbus Day","MP",2007 +"2007-10-08","Commonwealth Cultural Day","MP",2007 +"2007-11-04","Citizenship Day","MP",2007 +"2007-11-05","Citizenship Day (Observed)","MP",2007 +"2007-11-11","Veterans Day","MP",2007 +"2007-11-12","Veterans Day (Observed)","MP",2007 +"2007-11-22","Thanksgiving","MP",2007 +"2007-12-07","Constitution Day (Observed)","MP",2007 +"2007-12-08","Constitution Day","MP",2007 +"2007-12-25","Christmas Day","MP",2007 +"2008-01-01","New Year's Day","MP",2008 +"2008-01-21","Martin Luther King Jr. Day","MP",2008 +"2008-02-18","Washington's Birthday","MP",2008 +"2008-03-21","Good Friday","MP",2008 +"2008-03-24","Commonwealth Covenant Day","MP",2008 +"2008-05-26","Memorial Day","MP",2008 +"2008-07-04","Independence Day","MP",2008 +"2008-09-01","Labor Day","MP",2008 +"2008-10-13","Columbus Day","MP",2008 +"2008-10-13","Commonwealth Cultural Day","MP",2008 +"2008-11-04","Citizenship Day","MP",2008 +"2008-11-04","Election Day","MP",2008 +"2008-11-11","Veterans Day","MP",2008 +"2008-11-27","Thanksgiving","MP",2008 +"2008-12-08","Constitution Day","MP",2008 +"2008-12-25","Christmas Day","MP",2008 +"2009-01-01","New Year's Day","MP",2009 +"2009-01-19","Martin Luther King Jr. Day","MP",2009 +"2009-02-16","Washington's Birthday","MP",2009 +"2009-03-24","Commonwealth Covenant Day","MP",2009 +"2009-04-10","Good Friday","MP",2009 +"2009-05-25","Memorial Day","MP",2009 +"2009-07-03","Independence Day (Observed)","MP",2009 +"2009-07-04","Independence Day","MP",2009 +"2009-09-07","Labor Day","MP",2009 +"2009-10-12","Columbus Day","MP",2009 +"2009-10-12","Commonwealth Cultural Day","MP",2009 +"2009-11-04","Citizenship Day","MP",2009 +"2009-11-11","Veterans Day","MP",2009 +"2009-11-26","Thanksgiving","MP",2009 +"2009-12-08","Constitution Day","MP",2009 +"2009-12-25","Christmas Day","MP",2009 +"2010-01-01","New Year's Day","MP",2010 +"2010-01-18","Martin Luther King Jr. Day","MP",2010 +"2010-02-15","Washington's Birthday","MP",2010 +"2010-03-24","Commonwealth Covenant Day","MP",2010 +"2010-04-02","Good Friday","MP",2010 +"2010-05-31","Memorial Day","MP",2010 +"2010-07-04","Independence Day","MP",2010 +"2010-07-05","Independence Day (Observed)","MP",2010 +"2010-09-06","Labor Day","MP",2010 +"2010-10-11","Columbus Day","MP",2010 +"2010-10-11","Commonwealth Cultural Day","MP",2010 +"2010-11-02","Election Day","MP",2010 +"2010-11-04","Citizenship Day","MP",2010 +"2010-11-11","Veterans Day","MP",2010 +"2010-11-25","Thanksgiving","MP",2010 +"2010-12-08","Constitution Day","MP",2010 +"2010-12-24","Christmas Day (Observed)","MP",2010 +"2010-12-25","Christmas Day","MP",2010 +"2010-12-31","New Year's Day (Observed)","MP",2010 +"2011-01-01","New Year's Day","MP",2011 +"2011-01-17","Martin Luther King Jr. Day","MP",2011 +"2011-02-21","Washington's Birthday","MP",2011 +"2011-03-24","Commonwealth Covenant Day","MP",2011 +"2011-04-22","Good Friday","MP",2011 +"2011-05-30","Memorial Day","MP",2011 +"2011-07-04","Independence Day","MP",2011 +"2011-09-05","Labor Day","MP",2011 +"2011-10-10","Columbus Day","MP",2011 +"2011-10-10","Commonwealth Cultural Day","MP",2011 +"2011-11-04","Citizenship Day","MP",2011 +"2011-11-11","Veterans Day","MP",2011 +"2011-11-24","Thanksgiving","MP",2011 +"2011-12-08","Constitution Day","MP",2011 +"2011-12-25","Christmas Day","MP",2011 +"2011-12-26","Christmas Day (Observed)","MP",2011 +"2012-01-01","New Year's Day","MP",2012 +"2012-01-02","New Year's Day (Observed)","MP",2012 +"2012-01-16","Martin Luther King Jr. Day","MP",2012 +"2012-02-20","Washington's Birthday","MP",2012 +"2012-03-23","Commonwealth Covenant Day (Observed)","MP",2012 +"2012-03-24","Commonwealth Covenant Day","MP",2012 +"2012-04-06","Good Friday","MP",2012 +"2012-05-28","Memorial Day","MP",2012 +"2012-07-04","Independence Day","MP",2012 +"2012-09-03","Labor Day","MP",2012 +"2012-10-08","Columbus Day","MP",2012 +"2012-10-08","Commonwealth Cultural Day","MP",2012 +"2012-11-04","Citizenship Day","MP",2012 +"2012-11-05","Citizenship Day (Observed)","MP",2012 +"2012-11-06","Election Day","MP",2012 +"2012-11-11","Veterans Day","MP",2012 +"2012-11-12","Veterans Day (Observed)","MP",2012 +"2012-11-22","Thanksgiving","MP",2012 +"2012-12-07","Constitution Day (Observed)","MP",2012 +"2012-12-08","Constitution Day","MP",2012 +"2012-12-25","Christmas Day","MP",2012 +"2013-01-01","New Year's Day","MP",2013 +"2013-01-21","Martin Luther King Jr. Day","MP",2013 +"2013-02-18","Washington's Birthday","MP",2013 +"2013-03-24","Commonwealth Covenant Day","MP",2013 +"2013-03-25","Commonwealth Covenant Day (Observed)","MP",2013 +"2013-03-29","Good Friday","MP",2013 +"2013-05-27","Memorial Day","MP",2013 +"2013-07-04","Independence Day","MP",2013 +"2013-09-02","Labor Day","MP",2013 +"2013-10-14","Columbus Day","MP",2013 +"2013-10-14","Commonwealth Cultural Day","MP",2013 +"2013-11-04","Citizenship Day","MP",2013 +"2013-11-11","Veterans Day","MP",2013 +"2013-11-28","Thanksgiving","MP",2013 +"2013-12-08","Constitution Day","MP",2013 +"2013-12-09","Constitution Day (Observed)","MP",2013 +"2013-12-25","Christmas Day","MP",2013 +"2014-01-01","New Year's Day","MP",2014 +"2014-01-20","Martin Luther King Jr. Day","MP",2014 +"2014-02-17","Washington's Birthday","MP",2014 +"2014-03-24","Commonwealth Covenant Day","MP",2014 +"2014-04-18","Good Friday","MP",2014 +"2014-05-26","Memorial Day","MP",2014 +"2014-07-04","Independence Day","MP",2014 +"2014-09-01","Labor Day","MP",2014 +"2014-10-13","Columbus Day","MP",2014 +"2014-10-13","Commonwealth Cultural Day","MP",2014 +"2014-11-04","Citizenship Day","MP",2014 +"2014-11-04","Election Day","MP",2014 +"2014-11-11","Veterans Day","MP",2014 +"2014-11-27","Thanksgiving","MP",2014 +"2014-12-08","Constitution Day","MP",2014 +"2014-12-25","Christmas Day","MP",2014 +"2015-01-01","New Year's Day","MP",2015 +"2015-01-19","Martin Luther King Jr. Day","MP",2015 +"2015-02-16","Washington's Birthday","MP",2015 +"2015-03-24","Commonwealth Covenant Day","MP",2015 +"2015-04-03","Good Friday","MP",2015 +"2015-05-25","Memorial Day","MP",2015 +"2015-07-03","Independence Day (Observed)","MP",2015 +"2015-07-04","Independence Day","MP",2015 +"2015-09-07","Labor Day","MP",2015 +"2015-10-12","Columbus Day","MP",2015 +"2015-10-12","Commonwealth Cultural Day","MP",2015 +"2015-11-04","Citizenship Day","MP",2015 +"2015-11-11","Veterans Day","MP",2015 +"2015-11-26","Thanksgiving","MP",2015 +"2015-12-08","Constitution Day","MP",2015 +"2015-12-25","Christmas Day","MP",2015 +"2016-01-01","New Year's Day","MP",2016 +"2016-01-18","Martin Luther King Jr. Day","MP",2016 +"2016-02-15","Washington's Birthday","MP",2016 +"2016-03-24","Commonwealth Covenant Day","MP",2016 +"2016-03-25","Good Friday","MP",2016 +"2016-05-30","Memorial Day","MP",2016 +"2016-07-04","Independence Day","MP",2016 +"2016-09-05","Labor Day","MP",2016 +"2016-10-10","Columbus Day","MP",2016 +"2016-10-10","Commonwealth Cultural Day","MP",2016 +"2016-11-04","Citizenship Day","MP",2016 +"2016-11-08","Election Day","MP",2016 +"2016-11-11","Veterans Day","MP",2016 +"2016-11-24","Thanksgiving","MP",2016 +"2016-12-08","Constitution Day","MP",2016 +"2016-12-25","Christmas Day","MP",2016 +"2016-12-26","Christmas Day (Observed)","MP",2016 +"2017-01-01","New Year's Day","MP",2017 +"2017-01-02","New Year's Day (Observed)","MP",2017 +"2017-01-16","Martin Luther King Jr. Day","MP",2017 +"2017-02-20","Washington's Birthday","MP",2017 +"2017-03-24","Commonwealth Covenant Day","MP",2017 +"2017-04-14","Good Friday","MP",2017 +"2017-05-29","Memorial Day","MP",2017 +"2017-07-04","Independence Day","MP",2017 +"2017-09-04","Labor Day","MP",2017 +"2017-10-09","Columbus Day","MP",2017 +"2017-10-09","Commonwealth Cultural Day","MP",2017 +"2017-11-03","Citizenship Day (Observed)","MP",2017 +"2017-11-04","Citizenship Day","MP",2017 +"2017-11-10","Veterans Day (Observed)","MP",2017 +"2017-11-11","Veterans Day","MP",2017 +"2017-11-23","Thanksgiving","MP",2017 +"2017-12-08","Constitution Day","MP",2017 +"2017-12-25","Christmas Day","MP",2017 +"2018-01-01","New Year's Day","MP",2018 +"2018-01-15","Martin Luther King Jr. Day","MP",2018 +"2018-02-19","Washington's Birthday","MP",2018 +"2018-03-23","Commonwealth Covenant Day (Observed)","MP",2018 +"2018-03-24","Commonwealth Covenant Day","MP",2018 +"2018-03-30","Good Friday","MP",2018 +"2018-05-28","Memorial Day","MP",2018 +"2018-07-04","Independence Day","MP",2018 +"2018-09-03","Labor Day","MP",2018 +"2018-10-08","Columbus Day","MP",2018 +"2018-10-08","Commonwealth Cultural Day","MP",2018 +"2018-11-04","Citizenship Day","MP",2018 +"2018-11-05","Citizenship Day (Observed)","MP",2018 +"2018-11-06","Election Day","MP",2018 +"2018-11-11","Veterans Day","MP",2018 +"2018-11-12","Veterans Day (Observed)","MP",2018 +"2018-11-22","Thanksgiving","MP",2018 +"2018-12-07","Constitution Day (Observed)","MP",2018 +"2018-12-08","Constitution Day","MP",2018 +"2018-12-25","Christmas Day","MP",2018 +"2019-01-01","New Year's Day","MP",2019 +"2019-01-21","Martin Luther King Jr. Day","MP",2019 +"2019-02-18","Washington's Birthday","MP",2019 +"2019-03-24","Commonwealth Covenant Day","MP",2019 +"2019-03-25","Commonwealth Covenant Day (Observed)","MP",2019 +"2019-04-19","Good Friday","MP",2019 +"2019-05-27","Memorial Day","MP",2019 +"2019-07-04","Independence Day","MP",2019 +"2019-09-02","Labor Day","MP",2019 +"2019-10-14","Columbus Day","MP",2019 +"2019-10-14","Commonwealth Cultural Day","MP",2019 +"2019-11-04","Citizenship Day","MP",2019 +"2019-11-11","Veterans Day","MP",2019 +"2019-11-28","Thanksgiving","MP",2019 +"2019-12-08","Constitution Day","MP",2019 +"2019-12-09","Constitution Day (Observed)","MP",2019 +"2019-12-25","Christmas Day","MP",2019 +"2020-01-01","New Year's Day","MP",2020 +"2020-01-20","Martin Luther King Jr. Day","MP",2020 +"2020-02-17","Washington's Birthday","MP",2020 +"2020-03-24","Commonwealth Covenant Day","MP",2020 +"2020-04-10","Good Friday","MP",2020 +"2020-05-25","Memorial Day","MP",2020 +"2020-07-03","Independence Day (Observed)","MP",2020 +"2020-07-04","Independence Day","MP",2020 +"2020-09-07","Labor Day","MP",2020 +"2020-10-12","Columbus Day","MP",2020 +"2020-10-12","Commonwealth Cultural Day","MP",2020 +"2020-11-03","Election Day","MP",2020 +"2020-11-04","Citizenship Day","MP",2020 +"2020-11-11","Veterans Day","MP",2020 +"2020-11-26","Thanksgiving","MP",2020 +"2020-12-08","Constitution Day","MP",2020 +"2020-12-25","Christmas Day","MP",2020 +"2021-01-01","New Year's Day","MP",2021 +"2021-01-18","Martin Luther King Jr. Day","MP",2021 +"2021-02-15","Washington's Birthday","MP",2021 +"2021-03-24","Commonwealth Covenant Day","MP",2021 +"2021-04-02","Good Friday","MP",2021 +"2021-05-31","Memorial Day","MP",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","MP",2021 +"2021-06-19","Juneteenth National Independence Day","MP",2021 +"2021-07-04","Independence Day","MP",2021 +"2021-07-05","Independence Day (Observed)","MP",2021 +"2021-09-06","Labor Day","MP",2021 +"2021-10-11","Columbus Day","MP",2021 +"2021-10-11","Commonwealth Cultural Day","MP",2021 +"2021-11-04","Citizenship Day","MP",2021 +"2021-11-11","Veterans Day","MP",2021 +"2021-11-25","Thanksgiving","MP",2021 +"2021-12-08","Constitution Day","MP",2021 +"2021-12-24","Christmas Day (Observed)","MP",2021 +"2021-12-25","Christmas Day","MP",2021 +"2021-12-31","New Year's Day (Observed)","MP",2021 +"2022-01-01","New Year's Day","MP",2022 +"2022-01-17","Martin Luther King Jr. Day","MP",2022 +"2022-02-21","Washington's Birthday","MP",2022 +"2022-03-24","Commonwealth Covenant Day","MP",2022 +"2022-04-15","Good Friday","MP",2022 +"2022-05-30","Memorial Day","MP",2022 +"2022-06-19","Juneteenth National Independence Day","MP",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","MP",2022 +"2022-07-04","Independence Day","MP",2022 +"2022-09-05","Labor Day","MP",2022 +"2022-10-10","Columbus Day","MP",2022 +"2022-10-10","Commonwealth Cultural Day","MP",2022 +"2022-11-04","Citizenship Day","MP",2022 +"2022-11-08","Election Day","MP",2022 +"2022-11-11","Veterans Day","MP",2022 +"2022-11-24","Thanksgiving","MP",2022 +"2022-12-08","Constitution Day","MP",2022 +"2022-12-25","Christmas Day","MP",2022 +"2022-12-26","Christmas Day (Observed)","MP",2022 +"2023-01-01","New Year's Day","MP",2023 +"2023-01-02","New Year's Day (Observed)","MP",2023 +"2023-01-16","Martin Luther King Jr. Day","MP",2023 +"2023-02-20","Washington's Birthday","MP",2023 +"2023-03-24","Commonwealth Covenant Day","MP",2023 +"2023-04-07","Good Friday","MP",2023 +"2023-05-29","Memorial Day","MP",2023 +"2023-06-19","Juneteenth National Independence Day","MP",2023 +"2023-07-04","Independence Day","MP",2023 +"2023-09-04","Labor Day","MP",2023 +"2023-10-09","Columbus Day","MP",2023 +"2023-10-09","Commonwealth Cultural Day","MP",2023 +"2023-11-03","Citizenship Day (Observed)","MP",2023 +"2023-11-04","Citizenship Day","MP",2023 +"2023-11-10","Veterans Day (Observed)","MP",2023 +"2023-11-11","Veterans Day","MP",2023 +"2023-11-23","Thanksgiving","MP",2023 +"2023-12-08","Constitution Day","MP",2023 +"2023-12-25","Christmas Day","MP",2023 +"2024-01-01","New Year's Day","MP",2024 +"2024-01-15","Martin Luther King Jr. Day","MP",2024 +"2024-02-19","Washington's Birthday","MP",2024 +"2024-03-24","Commonwealth Covenant Day","MP",2024 +"2024-03-25","Commonwealth Covenant Day (Observed)","MP",2024 +"2024-03-29","Good Friday","MP",2024 +"2024-05-27","Memorial Day","MP",2024 +"2024-06-19","Juneteenth National Independence Day","MP",2024 +"2024-07-04","Independence Day","MP",2024 +"2024-09-02","Labor Day","MP",2024 +"2024-10-14","Columbus Day","MP",2024 +"2024-10-14","Commonwealth Cultural Day","MP",2024 +"2024-11-04","Citizenship Day","MP",2024 +"2024-11-05","Election Day","MP",2024 +"2024-11-11","Veterans Day","MP",2024 +"2024-11-28","Thanksgiving","MP",2024 +"2024-12-08","Constitution Day","MP",2024 +"2024-12-09","Constitution Day (Observed)","MP",2024 +"2024-12-25","Christmas Day","MP",2024 +"2025-01-01","New Year's Day","MP",2025 +"2025-01-20","Martin Luther King Jr. Day","MP",2025 +"2025-02-17","Washington's Birthday","MP",2025 +"2025-03-24","Commonwealth Covenant Day","MP",2025 +"2025-04-18","Good Friday","MP",2025 +"2025-05-26","Memorial Day","MP",2025 +"2025-06-19","Juneteenth National Independence Day","MP",2025 +"2025-07-04","Independence Day","MP",2025 +"2025-09-01","Labor Day","MP",2025 +"2025-10-13","Columbus Day","MP",2025 +"2025-10-13","Commonwealth Cultural Day","MP",2025 +"2025-11-04","Citizenship Day","MP",2025 +"2025-11-11","Veterans Day","MP",2025 +"2025-11-27","Thanksgiving","MP",2025 +"2025-12-08","Constitution Day","MP",2025 +"2025-12-25","Christmas Day","MP",2025 +"2026-01-01","New Year's Day","MP",2026 +"2026-01-19","Martin Luther King Jr. Day","MP",2026 +"2026-02-16","Washington's Birthday","MP",2026 +"2026-03-24","Commonwealth Covenant Day","MP",2026 +"2026-04-03","Good Friday","MP",2026 +"2026-05-25","Memorial Day","MP",2026 +"2026-06-19","Juneteenth National Independence Day","MP",2026 +"2026-07-03","Independence Day (Observed)","MP",2026 +"2026-07-04","Independence Day","MP",2026 +"2026-09-07","Labor Day","MP",2026 +"2026-10-12","Columbus Day","MP",2026 +"2026-10-12","Commonwealth Cultural Day","MP",2026 +"2026-11-03","Election Day","MP",2026 +"2026-11-04","Citizenship Day","MP",2026 +"2026-11-11","Veterans Day","MP",2026 +"2026-11-26","Thanksgiving","MP",2026 +"2026-12-08","Constitution Day","MP",2026 +"2026-12-25","Christmas Day","MP",2026 +"2027-01-01","New Year's Day","MP",2027 +"2027-01-18","Martin Luther King Jr. Day","MP",2027 +"2027-02-15","Washington's Birthday","MP",2027 +"2027-03-24","Commonwealth Covenant Day","MP",2027 +"2027-03-26","Good Friday","MP",2027 +"2027-05-31","Memorial Day","MP",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","MP",2027 +"2027-06-19","Juneteenth National Independence Day","MP",2027 +"2027-07-04","Independence Day","MP",2027 +"2027-07-05","Independence Day (Observed)","MP",2027 +"2027-09-06","Labor Day","MP",2027 +"2027-10-11","Columbus Day","MP",2027 +"2027-10-11","Commonwealth Cultural Day","MP",2027 +"2027-11-04","Citizenship Day","MP",2027 +"2027-11-11","Veterans Day","MP",2027 +"2027-11-25","Thanksgiving","MP",2027 +"2027-12-08","Constitution Day","MP",2027 +"2027-12-24","Christmas Day (Observed)","MP",2027 +"2027-12-25","Christmas Day","MP",2027 +"2027-12-31","New Year's Day (Observed)","MP",2027 +"2028-01-01","New Year's Day","MP",2028 +"2028-01-17","Martin Luther King Jr. Day","MP",2028 +"2028-02-21","Washington's Birthday","MP",2028 +"2028-03-24","Commonwealth Covenant Day","MP",2028 +"2028-04-14","Good Friday","MP",2028 +"2028-05-29","Memorial Day","MP",2028 +"2028-06-19","Juneteenth National Independence Day","MP",2028 +"2028-07-04","Independence Day","MP",2028 +"2028-09-04","Labor Day","MP",2028 +"2028-10-09","Columbus Day","MP",2028 +"2028-10-09","Commonwealth Cultural Day","MP",2028 +"2028-11-03","Citizenship Day (Observed)","MP",2028 +"2028-11-04","Citizenship Day","MP",2028 +"2028-11-07","Election Day","MP",2028 +"2028-11-10","Veterans Day (Observed)","MP",2028 +"2028-11-11","Veterans Day","MP",2028 +"2028-11-23","Thanksgiving","MP",2028 +"2028-12-08","Constitution Day","MP",2028 +"2028-12-25","Christmas Day","MP",2028 +"2029-01-01","New Year's Day","MP",2029 +"2029-01-15","Martin Luther King Jr. Day","MP",2029 +"2029-02-19","Washington's Birthday","MP",2029 +"2029-03-23","Commonwealth Covenant Day (Observed)","MP",2029 +"2029-03-24","Commonwealth Covenant Day","MP",2029 +"2029-03-30","Good Friday","MP",2029 +"2029-05-28","Memorial Day","MP",2029 +"2029-06-19","Juneteenth National Independence Day","MP",2029 +"2029-07-04","Independence Day","MP",2029 +"2029-09-03","Labor Day","MP",2029 +"2029-10-08","Columbus Day","MP",2029 +"2029-10-08","Commonwealth Cultural Day","MP",2029 +"2029-11-04","Citizenship Day","MP",2029 +"2029-11-05","Citizenship Day (Observed)","MP",2029 +"2029-11-11","Veterans Day","MP",2029 +"2029-11-12","Veterans Day (Observed)","MP",2029 +"2029-11-22","Thanksgiving","MP",2029 +"2029-12-07","Constitution Day (Observed)","MP",2029 +"2029-12-08","Constitution Day","MP",2029 +"2029-12-25","Christmas Day","MP",2029 +"2030-01-01","New Year's Day","MP",2030 +"2030-01-21","Martin Luther King Jr. Day","MP",2030 +"2030-02-18","Washington's Birthday","MP",2030 +"2030-03-24","Commonwealth Covenant Day","MP",2030 +"2030-03-25","Commonwealth Covenant Day (Observed)","MP",2030 +"2030-04-19","Good Friday","MP",2030 +"2030-05-27","Memorial Day","MP",2030 +"2030-06-19","Juneteenth National Independence Day","MP",2030 +"2030-07-04","Independence Day","MP",2030 +"2030-09-02","Labor Day","MP",2030 +"2030-10-14","Columbus Day","MP",2030 +"2030-10-14","Commonwealth Cultural Day","MP",2030 +"2030-11-04","Citizenship Day","MP",2030 +"2030-11-05","Election Day","MP",2030 +"2030-11-11","Veterans Day","MP",2030 +"2030-11-28","Thanksgiving","MP",2030 +"2030-12-08","Constitution Day","MP",2030 +"2030-12-09","Constitution Day (Observed)","MP",2030 +"2030-12-25","Christmas Day","MP",2030 +"2031-01-01","New Year's Day","MP",2031 +"2031-01-20","Martin Luther King Jr. Day","MP",2031 +"2031-02-17","Washington's Birthday","MP",2031 +"2031-03-24","Commonwealth Covenant Day","MP",2031 +"2031-04-11","Good Friday","MP",2031 +"2031-05-26","Memorial Day","MP",2031 +"2031-06-19","Juneteenth National Independence Day","MP",2031 +"2031-07-04","Independence Day","MP",2031 +"2031-09-01","Labor Day","MP",2031 +"2031-10-13","Columbus Day","MP",2031 +"2031-10-13","Commonwealth Cultural Day","MP",2031 +"2031-11-04","Citizenship Day","MP",2031 +"2031-11-11","Veterans Day","MP",2031 +"2031-11-27","Thanksgiving","MP",2031 +"2031-12-08","Constitution Day","MP",2031 +"2031-12-25","Christmas Day","MP",2031 +"2032-01-01","New Year's Day","MP",2032 +"2032-01-19","Martin Luther King Jr. Day","MP",2032 +"2032-02-16","Washington's Birthday","MP",2032 +"2032-03-24","Commonwealth Covenant Day","MP",2032 +"2032-03-26","Good Friday","MP",2032 +"2032-05-31","Memorial Day","MP",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","MP",2032 +"2032-06-19","Juneteenth National Independence Day","MP",2032 +"2032-07-04","Independence Day","MP",2032 +"2032-07-05","Independence Day (Observed)","MP",2032 +"2032-09-06","Labor Day","MP",2032 +"2032-10-11","Columbus Day","MP",2032 +"2032-10-11","Commonwealth Cultural Day","MP",2032 +"2032-11-02","Election Day","MP",2032 +"2032-11-04","Citizenship Day","MP",2032 +"2032-11-11","Veterans Day","MP",2032 +"2032-11-25","Thanksgiving","MP",2032 +"2032-12-08","Constitution Day","MP",2032 +"2032-12-24","Christmas Day (Observed)","MP",2032 +"2032-12-25","Christmas Day","MP",2032 +"2032-12-31","New Year's Day (Observed)","MP",2032 +"2033-01-01","New Year's Day","MP",2033 +"2033-01-17","Martin Luther King Jr. Day","MP",2033 +"2033-02-21","Washington's Birthday","MP",2033 +"2033-03-24","Commonwealth Covenant Day","MP",2033 +"2033-04-15","Good Friday","MP",2033 +"2033-05-30","Memorial Day","MP",2033 +"2033-06-19","Juneteenth National Independence Day","MP",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","MP",2033 +"2033-07-04","Independence Day","MP",2033 +"2033-09-05","Labor Day","MP",2033 +"2033-10-10","Columbus Day","MP",2033 +"2033-10-10","Commonwealth Cultural Day","MP",2033 +"2033-11-04","Citizenship Day","MP",2033 +"2033-11-11","Veterans Day","MP",2033 +"2033-11-24","Thanksgiving","MP",2033 +"2033-12-08","Constitution Day","MP",2033 +"2033-12-25","Christmas Day","MP",2033 +"2033-12-26","Christmas Day (Observed)","MP",2033 +"2034-01-01","New Year's Day","MP",2034 +"2034-01-02","New Year's Day (Observed)","MP",2034 +"2034-01-16","Martin Luther King Jr. Day","MP",2034 +"2034-02-20","Washington's Birthday","MP",2034 +"2034-03-24","Commonwealth Covenant Day","MP",2034 +"2034-04-07","Good Friday","MP",2034 +"2034-05-29","Memorial Day","MP",2034 +"2034-06-19","Juneteenth National Independence Day","MP",2034 +"2034-07-04","Independence Day","MP",2034 +"2034-09-04","Labor Day","MP",2034 +"2034-10-09","Columbus Day","MP",2034 +"2034-10-09","Commonwealth Cultural Day","MP",2034 +"2034-11-03","Citizenship Day (Observed)","MP",2034 +"2034-11-04","Citizenship Day","MP",2034 +"2034-11-07","Election Day","MP",2034 +"2034-11-10","Veterans Day (Observed)","MP",2034 +"2034-11-11","Veterans Day","MP",2034 +"2034-11-23","Thanksgiving","MP",2034 +"2034-12-08","Constitution Day","MP",2034 +"2034-12-25","Christmas Day","MP",2034 +"2035-01-01","New Year's Day","MP",2035 +"2035-01-15","Martin Luther King Jr. Day","MP",2035 +"2035-02-19","Washington's Birthday","MP",2035 +"2035-03-23","Commonwealth Covenant Day (Observed)","MP",2035 +"2035-03-23","Good Friday","MP",2035 +"2035-03-24","Commonwealth Covenant Day","MP",2035 +"2035-05-28","Memorial Day","MP",2035 +"2035-06-19","Juneteenth National Independence Day","MP",2035 +"2035-07-04","Independence Day","MP",2035 +"2035-09-03","Labor Day","MP",2035 +"2035-10-08","Columbus Day","MP",2035 +"2035-10-08","Commonwealth Cultural Day","MP",2035 +"2035-11-04","Citizenship Day","MP",2035 +"2035-11-05","Citizenship Day (Observed)","MP",2035 +"2035-11-11","Veterans Day","MP",2035 +"2035-11-12","Veterans Day (Observed)","MP",2035 +"2035-11-22","Thanksgiving","MP",2035 +"2035-12-07","Constitution Day (Observed)","MP",2035 +"2035-12-08","Constitution Day","MP",2035 +"2035-12-25","Christmas Day","MP",2035 +"2036-01-01","New Year's Day","MP",2036 +"2036-01-21","Martin Luther King Jr. Day","MP",2036 +"2036-02-18","Washington's Birthday","MP",2036 +"2036-03-24","Commonwealth Covenant Day","MP",2036 +"2036-04-11","Good Friday","MP",2036 +"2036-05-26","Memorial Day","MP",2036 +"2036-06-19","Juneteenth National Independence Day","MP",2036 +"2036-07-04","Independence Day","MP",2036 +"2036-09-01","Labor Day","MP",2036 +"2036-10-13","Columbus Day","MP",2036 +"2036-10-13","Commonwealth Cultural Day","MP",2036 +"2036-11-04","Citizenship Day","MP",2036 +"2036-11-04","Election Day","MP",2036 +"2036-11-11","Veterans Day","MP",2036 +"2036-11-27","Thanksgiving","MP",2036 +"2036-12-08","Constitution Day","MP",2036 +"2036-12-25","Christmas Day","MP",2036 +"2037-01-01","New Year's Day","MP",2037 +"2037-01-19","Martin Luther King Jr. Day","MP",2037 +"2037-02-16","Washington's Birthday","MP",2037 +"2037-03-24","Commonwealth Covenant Day","MP",2037 +"2037-04-03","Good Friday","MP",2037 +"2037-05-25","Memorial Day","MP",2037 +"2037-06-19","Juneteenth National Independence Day","MP",2037 +"2037-07-03","Independence Day (Observed)","MP",2037 +"2037-07-04","Independence Day","MP",2037 +"2037-09-07","Labor Day","MP",2037 +"2037-10-12","Columbus Day","MP",2037 +"2037-10-12","Commonwealth Cultural Day","MP",2037 +"2037-11-04","Citizenship Day","MP",2037 +"2037-11-11","Veterans Day","MP",2037 +"2037-11-26","Thanksgiving","MP",2037 +"2037-12-08","Constitution Day","MP",2037 +"2037-12-25","Christmas Day","MP",2037 +"2038-01-01","New Year's Day","MP",2038 +"2038-01-18","Martin Luther King Jr. Day","MP",2038 +"2038-02-15","Washington's Birthday","MP",2038 +"2038-03-24","Commonwealth Covenant Day","MP",2038 +"2038-04-23","Good Friday","MP",2038 +"2038-05-31","Memorial Day","MP",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","MP",2038 +"2038-06-19","Juneteenth National Independence Day","MP",2038 +"2038-07-04","Independence Day","MP",2038 +"2038-07-05","Independence Day (Observed)","MP",2038 +"2038-09-06","Labor Day","MP",2038 +"2038-10-11","Columbus Day","MP",2038 +"2038-10-11","Commonwealth Cultural Day","MP",2038 +"2038-11-02","Election Day","MP",2038 +"2038-11-04","Citizenship Day","MP",2038 +"2038-11-11","Veterans Day","MP",2038 +"2038-11-25","Thanksgiving","MP",2038 +"2038-12-08","Constitution Day","MP",2038 +"2038-12-24","Christmas Day (Observed)","MP",2038 +"2038-12-25","Christmas Day","MP",2038 +"2038-12-31","New Year's Day (Observed)","MP",2038 +"2039-01-01","New Year's Day","MP",2039 +"2039-01-17","Martin Luther King Jr. Day","MP",2039 +"2039-02-21","Washington's Birthday","MP",2039 +"2039-03-24","Commonwealth Covenant Day","MP",2039 +"2039-04-08","Good Friday","MP",2039 +"2039-05-30","Memorial Day","MP",2039 +"2039-06-19","Juneteenth National Independence Day","MP",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","MP",2039 +"2039-07-04","Independence Day","MP",2039 +"2039-09-05","Labor Day","MP",2039 +"2039-10-10","Columbus Day","MP",2039 +"2039-10-10","Commonwealth Cultural Day","MP",2039 +"2039-11-04","Citizenship Day","MP",2039 +"2039-11-11","Veterans Day","MP",2039 +"2039-11-24","Thanksgiving","MP",2039 +"2039-12-08","Constitution Day","MP",2039 +"2039-12-25","Christmas Day","MP",2039 +"2039-12-26","Christmas Day (Observed)","MP",2039 +"2040-01-01","New Year's Day","MP",2040 +"2040-01-02","New Year's Day (Observed)","MP",2040 +"2040-01-16","Martin Luther King Jr. Day","MP",2040 +"2040-02-20","Washington's Birthday","MP",2040 +"2040-03-23","Commonwealth Covenant Day (Observed)","MP",2040 +"2040-03-24","Commonwealth Covenant Day","MP",2040 +"2040-03-30","Good Friday","MP",2040 +"2040-05-28","Memorial Day","MP",2040 +"2040-06-19","Juneteenth National Independence Day","MP",2040 +"2040-07-04","Independence Day","MP",2040 +"2040-09-03","Labor Day","MP",2040 +"2040-10-08","Columbus Day","MP",2040 +"2040-10-08","Commonwealth Cultural Day","MP",2040 +"2040-11-04","Citizenship Day","MP",2040 +"2040-11-05","Citizenship Day (Observed)","MP",2040 +"2040-11-06","Election Day","MP",2040 +"2040-11-11","Veterans Day","MP",2040 +"2040-11-12","Veterans Day (Observed)","MP",2040 +"2040-11-22","Thanksgiving","MP",2040 +"2040-12-07","Constitution Day (Observed)","MP",2040 +"2040-12-08","Constitution Day","MP",2040 +"2040-12-25","Christmas Day","MP",2040 +"2041-01-01","New Year's Day","MP",2041 +"2041-01-21","Martin Luther King Jr. Day","MP",2041 +"2041-02-18","Washington's Birthday","MP",2041 +"2041-03-24","Commonwealth Covenant Day","MP",2041 +"2041-03-25","Commonwealth Covenant Day (Observed)","MP",2041 +"2041-04-19","Good Friday","MP",2041 +"2041-05-27","Memorial Day","MP",2041 +"2041-06-19","Juneteenth National Independence Day","MP",2041 +"2041-07-04","Independence Day","MP",2041 +"2041-09-02","Labor Day","MP",2041 +"2041-10-14","Columbus Day","MP",2041 +"2041-10-14","Commonwealth Cultural Day","MP",2041 +"2041-11-04","Citizenship Day","MP",2041 +"2041-11-11","Veterans Day","MP",2041 +"2041-11-28","Thanksgiving","MP",2041 +"2041-12-08","Constitution Day","MP",2041 +"2041-12-09","Constitution Day (Observed)","MP",2041 +"2041-12-25","Christmas Day","MP",2041 +"2042-01-01","New Year's Day","MP",2042 +"2042-01-20","Martin Luther King Jr. Day","MP",2042 +"2042-02-17","Washington's Birthday","MP",2042 +"2042-03-24","Commonwealth Covenant Day","MP",2042 +"2042-04-04","Good Friday","MP",2042 +"2042-05-26","Memorial Day","MP",2042 +"2042-06-19","Juneteenth National Independence Day","MP",2042 +"2042-07-04","Independence Day","MP",2042 +"2042-09-01","Labor Day","MP",2042 +"2042-10-13","Columbus Day","MP",2042 +"2042-10-13","Commonwealth Cultural Day","MP",2042 +"2042-11-04","Citizenship Day","MP",2042 +"2042-11-04","Election Day","MP",2042 +"2042-11-11","Veterans Day","MP",2042 +"2042-11-27","Thanksgiving","MP",2042 +"2042-12-08","Constitution Day","MP",2042 +"2042-12-25","Christmas Day","MP",2042 +"2043-01-01","New Year's Day","MP",2043 +"2043-01-19","Martin Luther King Jr. Day","MP",2043 +"2043-02-16","Washington's Birthday","MP",2043 +"2043-03-24","Commonwealth Covenant Day","MP",2043 +"2043-03-27","Good Friday","MP",2043 +"2043-05-25","Memorial Day","MP",2043 +"2043-06-19","Juneteenth National Independence Day","MP",2043 +"2043-07-03","Independence Day (Observed)","MP",2043 +"2043-07-04","Independence Day","MP",2043 +"2043-09-07","Labor Day","MP",2043 +"2043-10-12","Columbus Day","MP",2043 +"2043-10-12","Commonwealth Cultural Day","MP",2043 +"2043-11-04","Citizenship Day","MP",2043 +"2043-11-11","Veterans Day","MP",2043 +"2043-11-26","Thanksgiving","MP",2043 +"2043-12-08","Constitution Day","MP",2043 +"2043-12-25","Christmas Day","MP",2043 +"2044-01-01","New Year's Day","MP",2044 +"2044-01-18","Martin Luther King Jr. Day","MP",2044 +"2044-02-15","Washington's Birthday","MP",2044 +"2044-03-24","Commonwealth Covenant Day","MP",2044 +"2044-04-15","Good Friday","MP",2044 +"2044-05-30","Memorial Day","MP",2044 +"2044-06-19","Juneteenth National Independence Day","MP",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","MP",2044 +"2044-07-04","Independence Day","MP",2044 +"2044-09-05","Labor Day","MP",2044 +"2044-10-10","Columbus Day","MP",2044 +"2044-10-10","Commonwealth Cultural Day","MP",2044 +"2044-11-04","Citizenship Day","MP",2044 +"2044-11-08","Election Day","MP",2044 +"2044-11-11","Veterans Day","MP",2044 +"2044-11-24","Thanksgiving","MP",2044 +"2044-12-08","Constitution Day","MP",2044 +"2044-12-25","Christmas Day","MP",2044 +"2044-12-26","Christmas Day (Observed)","MP",2044 +"1995-01-01","New Year","MT",1995 +"1995-02-10","Feast of St. Paul's Shipwreck","MT",1995 +"1995-03-19","Feast of St. Joseph","MT",1995 +"1995-03-31","Freedom Day","MT",1995 +"1995-04-14","Good Friday","MT",1995 +"1995-05-01","Worker's Day","MT",1995 +"1995-06-07","Sette Giugno","MT",1995 +"1995-06-29","Feast of St. Peter and St. Paul","MT",1995 +"1995-08-15","Feast of the Assumption","MT",1995 +"1995-09-08","Feast of Our Lady of Victories","MT",1995 +"1995-09-21","Independence Day","MT",1995 +"1995-12-08","Feast of the Immaculate Conception","MT",1995 +"1995-12-13","Republic Day","MT",1995 +"1995-12-25","Christmas Day","MT",1995 +"1996-01-01","New Year","MT",1996 +"1996-02-10","Feast of St. Paul's Shipwreck","MT",1996 +"1996-03-19","Feast of St. Joseph","MT",1996 +"1996-03-31","Freedom Day","MT",1996 +"1996-04-05","Good Friday","MT",1996 +"1996-05-01","Worker's Day","MT",1996 +"1996-06-07","Sette Giugno","MT",1996 +"1996-06-29","Feast of St. Peter and St. Paul","MT",1996 +"1996-08-15","Feast of the Assumption","MT",1996 +"1996-09-08","Feast of Our Lady of Victories","MT",1996 +"1996-09-21","Independence Day","MT",1996 +"1996-12-08","Feast of the Immaculate Conception","MT",1996 +"1996-12-13","Republic Day","MT",1996 +"1996-12-25","Christmas Day","MT",1996 +"1997-01-01","New Year","MT",1997 +"1997-02-10","Feast of St. Paul's Shipwreck","MT",1997 +"1997-03-19","Feast of St. Joseph","MT",1997 +"1997-03-28","Good Friday","MT",1997 +"1997-03-31","Freedom Day","MT",1997 +"1997-05-01","Worker's Day","MT",1997 +"1997-06-07","Sette Giugno","MT",1997 +"1997-06-29","Feast of St. Peter and St. Paul","MT",1997 +"1997-08-15","Feast of the Assumption","MT",1997 +"1997-09-08","Feast of Our Lady of Victories","MT",1997 +"1997-09-21","Independence Day","MT",1997 +"1997-12-08","Feast of the Immaculate Conception","MT",1997 +"1997-12-13","Republic Day","MT",1997 +"1997-12-25","Christmas Day","MT",1997 +"1998-01-01","New Year","MT",1998 +"1998-02-10","Feast of St. Paul's Shipwreck","MT",1998 +"1998-03-19","Feast of St. Joseph","MT",1998 +"1998-03-31","Freedom Day","MT",1998 +"1998-04-10","Good Friday","MT",1998 +"1998-05-01","Worker's Day","MT",1998 +"1998-06-07","Sette Giugno","MT",1998 +"1998-06-29","Feast of St. Peter and St. Paul","MT",1998 +"1998-08-15","Feast of the Assumption","MT",1998 +"1998-09-08","Feast of Our Lady of Victories","MT",1998 +"1998-09-21","Independence Day","MT",1998 +"1998-12-08","Feast of the Immaculate Conception","MT",1998 +"1998-12-13","Republic Day","MT",1998 +"1998-12-25","Christmas Day","MT",1998 +"1999-01-01","New Year","MT",1999 +"1999-02-10","Feast of St. Paul's Shipwreck","MT",1999 +"1999-03-19","Feast of St. Joseph","MT",1999 +"1999-03-31","Freedom Day","MT",1999 +"1999-04-02","Good Friday","MT",1999 +"1999-05-01","Worker's Day","MT",1999 +"1999-06-07","Sette Giugno","MT",1999 +"1999-06-29","Feast of St. Peter and St. Paul","MT",1999 +"1999-08-15","Feast of the Assumption","MT",1999 +"1999-09-08","Feast of Our Lady of Victories","MT",1999 +"1999-09-21","Independence Day","MT",1999 +"1999-12-08","Feast of the Immaculate Conception","MT",1999 +"1999-12-13","Republic Day","MT",1999 +"1999-12-25","Christmas Day","MT",1999 +"2000-01-01","New Year","MT",2000 +"2000-02-10","Feast of St. Paul's Shipwreck","MT",2000 +"2000-03-19","Feast of St. Joseph","MT",2000 +"2000-03-31","Freedom Day","MT",2000 +"2000-04-21","Good Friday","MT",2000 +"2000-05-01","Worker's Day","MT",2000 +"2000-06-07","Sette Giugno","MT",2000 +"2000-06-29","Feast of St. Peter and St. Paul","MT",2000 +"2000-08-15","Feast of the Assumption","MT",2000 +"2000-09-08","Feast of Our Lady of Victories","MT",2000 +"2000-09-21","Independence Day","MT",2000 +"2000-12-08","Feast of the Immaculate Conception","MT",2000 +"2000-12-13","Republic Day","MT",2000 +"2000-12-25","Christmas Day","MT",2000 +"2001-01-01","New Year","MT",2001 +"2001-02-10","Feast of St. Paul's Shipwreck","MT",2001 +"2001-03-19","Feast of St. Joseph","MT",2001 +"2001-03-31","Freedom Day","MT",2001 +"2001-04-13","Good Friday","MT",2001 +"2001-05-01","Worker's Day","MT",2001 +"2001-06-07","Sette Giugno","MT",2001 +"2001-06-29","Feast of St. Peter and St. Paul","MT",2001 +"2001-08-15","Feast of the Assumption","MT",2001 +"2001-09-08","Feast of Our Lady of Victories","MT",2001 +"2001-09-21","Independence Day","MT",2001 +"2001-12-08","Feast of the Immaculate Conception","MT",2001 +"2001-12-13","Republic Day","MT",2001 +"2001-12-25","Christmas Day","MT",2001 +"2002-01-01","New Year","MT",2002 +"2002-02-10","Feast of St. Paul's Shipwreck","MT",2002 +"2002-03-19","Feast of St. Joseph","MT",2002 +"2002-03-29","Good Friday","MT",2002 +"2002-03-31","Freedom Day","MT",2002 +"2002-05-01","Worker's Day","MT",2002 +"2002-06-07","Sette Giugno","MT",2002 +"2002-06-29","Feast of St. Peter and St. Paul","MT",2002 +"2002-08-15","Feast of the Assumption","MT",2002 +"2002-09-08","Feast of Our Lady of Victories","MT",2002 +"2002-09-21","Independence Day","MT",2002 +"2002-12-08","Feast of the Immaculate Conception","MT",2002 +"2002-12-13","Republic Day","MT",2002 +"2002-12-25","Christmas Day","MT",2002 +"2003-01-01","New Year","MT",2003 +"2003-02-10","Feast of St. Paul's Shipwreck","MT",2003 +"2003-03-19","Feast of St. Joseph","MT",2003 +"2003-03-31","Freedom Day","MT",2003 +"2003-04-18","Good Friday","MT",2003 +"2003-05-01","Worker's Day","MT",2003 +"2003-06-07","Sette Giugno","MT",2003 +"2003-06-29","Feast of St. Peter and St. Paul","MT",2003 +"2003-08-15","Feast of the Assumption","MT",2003 +"2003-09-08","Feast of Our Lady of Victories","MT",2003 +"2003-09-21","Independence Day","MT",2003 +"2003-12-08","Feast of the Immaculate Conception","MT",2003 +"2003-12-13","Republic Day","MT",2003 +"2003-12-25","Christmas Day","MT",2003 +"2004-01-01","New Year","MT",2004 +"2004-02-10","Feast of St. Paul's Shipwreck","MT",2004 +"2004-03-19","Feast of St. Joseph","MT",2004 +"2004-03-31","Freedom Day","MT",2004 +"2004-04-09","Good Friday","MT",2004 +"2004-05-01","Worker's Day","MT",2004 +"2004-06-07","Sette Giugno","MT",2004 +"2004-06-29","Feast of St. Peter and St. Paul","MT",2004 +"2004-08-15","Feast of the Assumption","MT",2004 +"2004-09-08","Feast of Our Lady of Victories","MT",2004 +"2004-09-21","Independence Day","MT",2004 +"2004-12-08","Feast of the Immaculate Conception","MT",2004 +"2004-12-13","Republic Day","MT",2004 +"2004-12-25","Christmas Day","MT",2004 +"2005-01-01","New Year","MT",2005 +"2005-02-10","Feast of St. Paul's Shipwreck","MT",2005 +"2005-03-19","Feast of St. Joseph","MT",2005 +"2005-03-25","Good Friday","MT",2005 +"2005-03-31","Freedom Day","MT",2005 +"2005-05-01","Worker's Day","MT",2005 +"2005-06-07","Sette Giugno","MT",2005 +"2005-06-29","Feast of St. Peter and St. Paul","MT",2005 +"2005-08-15","Feast of the Assumption","MT",2005 +"2005-09-08","Feast of Our Lady of Victories","MT",2005 +"2005-09-21","Independence Day","MT",2005 +"2005-12-08","Feast of the Immaculate Conception","MT",2005 +"2005-12-13","Republic Day","MT",2005 +"2005-12-25","Christmas Day","MT",2005 +"2006-01-01","New Year","MT",2006 +"2006-02-10","Feast of St. Paul's Shipwreck","MT",2006 +"2006-03-19","Feast of St. Joseph","MT",2006 +"2006-03-31","Freedom Day","MT",2006 +"2006-04-14","Good Friday","MT",2006 +"2006-05-01","Worker's Day","MT",2006 +"2006-06-07","Sette Giugno","MT",2006 +"2006-06-29","Feast of St. Peter and St. Paul","MT",2006 +"2006-08-15","Feast of the Assumption","MT",2006 +"2006-09-08","Feast of Our Lady of Victories","MT",2006 +"2006-09-21","Independence Day","MT",2006 +"2006-12-08","Feast of the Immaculate Conception","MT",2006 +"2006-12-13","Republic Day","MT",2006 +"2006-12-25","Christmas Day","MT",2006 +"2007-01-01","New Year","MT",2007 +"2007-02-10","Feast of St. Paul's Shipwreck","MT",2007 +"2007-03-19","Feast of St. Joseph","MT",2007 +"2007-03-31","Freedom Day","MT",2007 +"2007-04-06","Good Friday","MT",2007 +"2007-05-01","Worker's Day","MT",2007 +"2007-06-07","Sette Giugno","MT",2007 +"2007-06-29","Feast of St. Peter and St. Paul","MT",2007 +"2007-08-15","Feast of the Assumption","MT",2007 +"2007-09-08","Feast of Our Lady of Victories","MT",2007 +"2007-09-21","Independence Day","MT",2007 +"2007-12-08","Feast of the Immaculate Conception","MT",2007 +"2007-12-13","Republic Day","MT",2007 +"2007-12-25","Christmas Day","MT",2007 +"2008-01-01","New Year","MT",2008 +"2008-02-10","Feast of St. Paul's Shipwreck","MT",2008 +"2008-03-19","Feast of St. Joseph","MT",2008 +"2008-03-21","Good Friday","MT",2008 +"2008-03-31","Freedom Day","MT",2008 +"2008-05-01","Worker's Day","MT",2008 +"2008-06-07","Sette Giugno","MT",2008 +"2008-06-29","Feast of St. Peter and St. Paul","MT",2008 +"2008-08-15","Feast of the Assumption","MT",2008 +"2008-09-08","Feast of Our Lady of Victories","MT",2008 +"2008-09-21","Independence Day","MT",2008 +"2008-12-08","Feast of the Immaculate Conception","MT",2008 +"2008-12-13","Republic Day","MT",2008 +"2008-12-25","Christmas Day","MT",2008 +"2009-01-01","New Year","MT",2009 +"2009-02-10","Feast of St. Paul's Shipwreck","MT",2009 +"2009-03-19","Feast of St. Joseph","MT",2009 +"2009-03-31","Freedom Day","MT",2009 +"2009-04-10","Good Friday","MT",2009 +"2009-05-01","Worker's Day","MT",2009 +"2009-06-07","Sette Giugno","MT",2009 +"2009-06-29","Feast of St. Peter and St. Paul","MT",2009 +"2009-08-15","Feast of the Assumption","MT",2009 +"2009-09-08","Feast of Our Lady of Victories","MT",2009 +"2009-09-21","Independence Day","MT",2009 +"2009-12-08","Feast of the Immaculate Conception","MT",2009 +"2009-12-13","Republic Day","MT",2009 +"2009-12-25","Christmas Day","MT",2009 +"2010-01-01","New Year","MT",2010 +"2010-02-10","Feast of St. Paul's Shipwreck","MT",2010 +"2010-03-19","Feast of St. Joseph","MT",2010 +"2010-03-31","Freedom Day","MT",2010 +"2010-04-02","Good Friday","MT",2010 +"2010-05-01","Worker's Day","MT",2010 +"2010-06-07","Sette Giugno","MT",2010 +"2010-06-29","Feast of St. Peter and St. Paul","MT",2010 +"2010-08-15","Feast of the Assumption","MT",2010 +"2010-09-08","Feast of Our Lady of Victories","MT",2010 +"2010-09-21","Independence Day","MT",2010 +"2010-12-08","Feast of the Immaculate Conception","MT",2010 +"2010-12-13","Republic Day","MT",2010 +"2010-12-25","Christmas Day","MT",2010 +"2011-01-01","New Year","MT",2011 +"2011-02-10","Feast of St. Paul's Shipwreck","MT",2011 +"2011-03-19","Feast of St. Joseph","MT",2011 +"2011-03-31","Freedom Day","MT",2011 +"2011-04-22","Good Friday","MT",2011 +"2011-05-01","Worker's Day","MT",2011 +"2011-06-07","Sette Giugno","MT",2011 +"2011-06-29","Feast of St. Peter and St. Paul","MT",2011 +"2011-08-15","Feast of the Assumption","MT",2011 +"2011-09-08","Feast of Our Lady of Victories","MT",2011 +"2011-09-21","Independence Day","MT",2011 +"2011-12-08","Feast of the Immaculate Conception","MT",2011 +"2011-12-13","Republic Day","MT",2011 +"2011-12-25","Christmas Day","MT",2011 +"2012-01-01","New Year","MT",2012 +"2012-02-10","Feast of St. Paul's Shipwreck","MT",2012 +"2012-03-19","Feast of St. Joseph","MT",2012 +"2012-03-31","Freedom Day","MT",2012 +"2012-04-06","Good Friday","MT",2012 +"2012-05-01","Worker's Day","MT",2012 +"2012-06-07","Sette Giugno","MT",2012 +"2012-06-29","Feast of St. Peter and St. Paul","MT",2012 +"2012-08-15","Feast of the Assumption","MT",2012 +"2012-09-08","Feast of Our Lady of Victories","MT",2012 +"2012-09-21","Independence Day","MT",2012 +"2012-12-08","Feast of the Immaculate Conception","MT",2012 +"2012-12-13","Republic Day","MT",2012 +"2012-12-25","Christmas Day","MT",2012 +"2013-01-01","New Year","MT",2013 +"2013-02-10","Feast of St. Paul's Shipwreck","MT",2013 +"2013-03-19","Feast of St. Joseph","MT",2013 +"2013-03-29","Good Friday","MT",2013 +"2013-03-31","Freedom Day","MT",2013 +"2013-05-01","Worker's Day","MT",2013 +"2013-06-07","Sette Giugno","MT",2013 +"2013-06-29","Feast of St. Peter and St. Paul","MT",2013 +"2013-08-15","Feast of the Assumption","MT",2013 +"2013-09-08","Feast of Our Lady of Victories","MT",2013 +"2013-09-21","Independence Day","MT",2013 +"2013-12-08","Feast of the Immaculate Conception","MT",2013 +"2013-12-13","Republic Day","MT",2013 +"2013-12-25","Christmas Day","MT",2013 +"2014-01-01","New Year","MT",2014 +"2014-02-10","Feast of St. Paul's Shipwreck","MT",2014 +"2014-03-19","Feast of St. Joseph","MT",2014 +"2014-03-31","Freedom Day","MT",2014 +"2014-04-18","Good Friday","MT",2014 +"2014-05-01","Worker's Day","MT",2014 +"2014-06-07","Sette Giugno","MT",2014 +"2014-06-29","Feast of St. Peter and St. Paul","MT",2014 +"2014-08-15","Feast of the Assumption","MT",2014 +"2014-09-08","Feast of Our Lady of Victories","MT",2014 +"2014-09-21","Independence Day","MT",2014 +"2014-12-08","Feast of the Immaculate Conception","MT",2014 +"2014-12-13","Republic Day","MT",2014 +"2014-12-25","Christmas Day","MT",2014 +"2015-01-01","New Year","MT",2015 +"2015-02-10","Feast of St. Paul's Shipwreck","MT",2015 +"2015-03-19","Feast of St. Joseph","MT",2015 +"2015-03-31","Freedom Day","MT",2015 +"2015-04-03","Good Friday","MT",2015 +"2015-05-01","Worker's Day","MT",2015 +"2015-06-07","Sette Giugno","MT",2015 +"2015-06-29","Feast of St. Peter and St. Paul","MT",2015 +"2015-08-15","Feast of the Assumption","MT",2015 +"2015-09-08","Feast of Our Lady of Victories","MT",2015 +"2015-09-21","Independence Day","MT",2015 +"2015-12-08","Feast of the Immaculate Conception","MT",2015 +"2015-12-13","Republic Day","MT",2015 +"2015-12-25","Christmas Day","MT",2015 +"2016-01-01","New Year","MT",2016 +"2016-02-10","Feast of St. Paul's Shipwreck","MT",2016 +"2016-03-19","Feast of St. Joseph","MT",2016 +"2016-03-25","Good Friday","MT",2016 +"2016-03-31","Freedom Day","MT",2016 +"2016-05-01","Worker's Day","MT",2016 +"2016-06-07","Sette Giugno","MT",2016 +"2016-06-29","Feast of St. Peter and St. Paul","MT",2016 +"2016-08-15","Feast of the Assumption","MT",2016 +"2016-09-08","Feast of Our Lady of Victories","MT",2016 +"2016-09-21","Independence Day","MT",2016 +"2016-12-08","Feast of the Immaculate Conception","MT",2016 +"2016-12-13","Republic Day","MT",2016 +"2016-12-25","Christmas Day","MT",2016 +"2017-01-01","New Year","MT",2017 +"2017-02-10","Feast of St. Paul's Shipwreck","MT",2017 +"2017-03-19","Feast of St. Joseph","MT",2017 +"2017-03-31","Freedom Day","MT",2017 +"2017-04-14","Good Friday","MT",2017 +"2017-05-01","Worker's Day","MT",2017 +"2017-06-07","Sette Giugno","MT",2017 +"2017-06-29","Feast of St. Peter and St. Paul","MT",2017 +"2017-08-15","Feast of the Assumption","MT",2017 +"2017-09-08","Feast of Our Lady of Victories","MT",2017 +"2017-09-21","Independence Day","MT",2017 +"2017-12-08","Feast of the Immaculate Conception","MT",2017 +"2017-12-13","Republic Day","MT",2017 +"2017-12-25","Christmas Day","MT",2017 +"2018-01-01","New Year","MT",2018 +"2018-02-10","Feast of St. Paul's Shipwreck","MT",2018 +"2018-03-19","Feast of St. Joseph","MT",2018 +"2018-03-30","Good Friday","MT",2018 +"2018-03-31","Freedom Day","MT",2018 +"2018-05-01","Worker's Day","MT",2018 +"2018-06-07","Sette Giugno","MT",2018 +"2018-06-29","Feast of St. Peter and St. Paul","MT",2018 +"2018-08-15","Feast of the Assumption","MT",2018 +"2018-09-08","Feast of Our Lady of Victories","MT",2018 +"2018-09-21","Independence Day","MT",2018 +"2018-12-08","Feast of the Immaculate Conception","MT",2018 +"2018-12-13","Republic Day","MT",2018 +"2018-12-25","Christmas Day","MT",2018 +"2019-01-01","New Year","MT",2019 +"2019-02-10","Feast of St. Paul's Shipwreck","MT",2019 +"2019-03-19","Feast of St. Joseph","MT",2019 +"2019-03-31","Freedom Day","MT",2019 +"2019-04-19","Good Friday","MT",2019 +"2019-05-01","Worker's Day","MT",2019 +"2019-06-07","Sette Giugno","MT",2019 +"2019-06-29","Feast of St. Peter and St. Paul","MT",2019 +"2019-08-15","Feast of the Assumption","MT",2019 +"2019-09-08","Feast of Our Lady of Victories","MT",2019 +"2019-09-21","Independence Day","MT",2019 +"2019-12-08","Feast of the Immaculate Conception","MT",2019 +"2019-12-13","Republic Day","MT",2019 +"2019-12-25","Christmas Day","MT",2019 +"2020-01-01","New Year","MT",2020 +"2020-02-10","Feast of St. Paul's Shipwreck","MT",2020 +"2020-03-19","Feast of St. Joseph","MT",2020 +"2020-03-31","Freedom Day","MT",2020 +"2020-04-10","Good Friday","MT",2020 +"2020-05-01","Worker's Day","MT",2020 +"2020-06-07","Sette Giugno","MT",2020 +"2020-06-29","Feast of St. Peter and St. Paul","MT",2020 +"2020-08-15","Feast of the Assumption","MT",2020 +"2020-09-08","Feast of Our Lady of Victories","MT",2020 +"2020-09-21","Independence Day","MT",2020 +"2020-12-08","Feast of the Immaculate Conception","MT",2020 +"2020-12-13","Republic Day","MT",2020 +"2020-12-25","Christmas Day","MT",2020 +"2021-01-01","New Year","MT",2021 +"2021-02-10","Feast of St. Paul's Shipwreck","MT",2021 +"2021-03-19","Feast of St. Joseph","MT",2021 +"2021-03-31","Freedom Day","MT",2021 +"2021-04-02","Good Friday","MT",2021 +"2021-05-01","Worker's Day","MT",2021 +"2021-06-07","Sette Giugno","MT",2021 +"2021-06-29","Feast of St. Peter and St. Paul","MT",2021 +"2021-08-15","Feast of the Assumption","MT",2021 +"2021-09-08","Feast of Our Lady of Victories","MT",2021 +"2021-09-21","Independence Day","MT",2021 +"2021-12-08","Feast of the Immaculate Conception","MT",2021 +"2021-12-13","Republic Day","MT",2021 +"2021-12-25","Christmas Day","MT",2021 +"2022-01-01","New Year","MT",2022 +"2022-02-10","Feast of St. Paul's Shipwreck","MT",2022 +"2022-03-19","Feast of St. Joseph","MT",2022 +"2022-03-31","Freedom Day","MT",2022 +"2022-04-15","Good Friday","MT",2022 +"2022-05-01","Worker's Day","MT",2022 +"2022-06-07","Sette Giugno","MT",2022 +"2022-06-29","Feast of St. Peter and St. Paul","MT",2022 +"2022-08-15","Feast of the Assumption","MT",2022 +"2022-09-08","Feast of Our Lady of Victories","MT",2022 +"2022-09-21","Independence Day","MT",2022 +"2022-12-08","Feast of the Immaculate Conception","MT",2022 +"2022-12-13","Republic Day","MT",2022 +"2022-12-25","Christmas Day","MT",2022 +"2023-01-01","New Year","MT",2023 +"2023-02-10","Feast of St. Paul's Shipwreck","MT",2023 +"2023-03-19","Feast of St. Joseph","MT",2023 +"2023-03-31","Freedom Day","MT",2023 +"2023-04-07","Good Friday","MT",2023 +"2023-05-01","Worker's Day","MT",2023 +"2023-06-07","Sette Giugno","MT",2023 +"2023-06-29","Feast of St. Peter and St. Paul","MT",2023 +"2023-08-15","Feast of the Assumption","MT",2023 +"2023-09-08","Feast of Our Lady of Victories","MT",2023 +"2023-09-21","Independence Day","MT",2023 +"2023-12-08","Feast of the Immaculate Conception","MT",2023 +"2023-12-13","Republic Day","MT",2023 +"2023-12-25","Christmas Day","MT",2023 +"2024-01-01","New Year","MT",2024 +"2024-02-10","Feast of St. Paul's Shipwreck","MT",2024 +"2024-03-19","Feast of St. Joseph","MT",2024 +"2024-03-29","Good Friday","MT",2024 +"2024-03-31","Freedom Day","MT",2024 +"2024-05-01","Worker's Day","MT",2024 +"2024-06-07","Sette Giugno","MT",2024 +"2024-06-29","Feast of St. Peter and St. Paul","MT",2024 +"2024-08-15","Feast of the Assumption","MT",2024 +"2024-09-08","Feast of Our Lady of Victories","MT",2024 +"2024-09-21","Independence Day","MT",2024 +"2024-12-08","Feast of the Immaculate Conception","MT",2024 +"2024-12-13","Republic Day","MT",2024 +"2024-12-25","Christmas Day","MT",2024 +"2025-01-01","New Year","MT",2025 +"2025-02-10","Feast of St. Paul's Shipwreck","MT",2025 +"2025-03-19","Feast of St. Joseph","MT",2025 +"2025-03-31","Freedom Day","MT",2025 +"2025-04-18","Good Friday","MT",2025 +"2025-05-01","Worker's Day","MT",2025 +"2025-06-07","Sette Giugno","MT",2025 +"2025-06-29","Feast of St. Peter and St. Paul","MT",2025 +"2025-08-15","Feast of the Assumption","MT",2025 +"2025-09-08","Feast of Our Lady of Victories","MT",2025 +"2025-09-21","Independence Day","MT",2025 +"2025-12-08","Feast of the Immaculate Conception","MT",2025 +"2025-12-13","Republic Day","MT",2025 +"2025-12-25","Christmas Day","MT",2025 +"2026-01-01","New Year","MT",2026 +"2026-02-10","Feast of St. Paul's Shipwreck","MT",2026 +"2026-03-19","Feast of St. Joseph","MT",2026 +"2026-03-31","Freedom Day","MT",2026 +"2026-04-03","Good Friday","MT",2026 +"2026-05-01","Worker's Day","MT",2026 +"2026-06-07","Sette Giugno","MT",2026 +"2026-06-29","Feast of St. Peter and St. Paul","MT",2026 +"2026-08-15","Feast of the Assumption","MT",2026 +"2026-09-08","Feast of Our Lady of Victories","MT",2026 +"2026-09-21","Independence Day","MT",2026 +"2026-12-08","Feast of the Immaculate Conception","MT",2026 +"2026-12-13","Republic Day","MT",2026 +"2026-12-25","Christmas Day","MT",2026 +"2027-01-01","New Year","MT",2027 +"2027-02-10","Feast of St. Paul's Shipwreck","MT",2027 +"2027-03-19","Feast of St. Joseph","MT",2027 +"2027-03-26","Good Friday","MT",2027 +"2027-03-31","Freedom Day","MT",2027 +"2027-05-01","Worker's Day","MT",2027 +"2027-06-07","Sette Giugno","MT",2027 +"2027-06-29","Feast of St. Peter and St. Paul","MT",2027 +"2027-08-15","Feast of the Assumption","MT",2027 +"2027-09-08","Feast of Our Lady of Victories","MT",2027 +"2027-09-21","Independence Day","MT",2027 +"2027-12-08","Feast of the Immaculate Conception","MT",2027 +"2027-12-13","Republic Day","MT",2027 +"2027-12-25","Christmas Day","MT",2027 +"2028-01-01","New Year","MT",2028 +"2028-02-10","Feast of St. Paul's Shipwreck","MT",2028 +"2028-03-19","Feast of St. Joseph","MT",2028 +"2028-03-31","Freedom Day","MT",2028 +"2028-04-14","Good Friday","MT",2028 +"2028-05-01","Worker's Day","MT",2028 +"2028-06-07","Sette Giugno","MT",2028 +"2028-06-29","Feast of St. Peter and St. Paul","MT",2028 +"2028-08-15","Feast of the Assumption","MT",2028 +"2028-09-08","Feast of Our Lady of Victories","MT",2028 +"2028-09-21","Independence Day","MT",2028 +"2028-12-08","Feast of the Immaculate Conception","MT",2028 +"2028-12-13","Republic Day","MT",2028 +"2028-12-25","Christmas Day","MT",2028 +"2029-01-01","New Year","MT",2029 +"2029-02-10","Feast of St. Paul's Shipwreck","MT",2029 +"2029-03-19","Feast of St. Joseph","MT",2029 +"2029-03-30","Good Friday","MT",2029 +"2029-03-31","Freedom Day","MT",2029 +"2029-05-01","Worker's Day","MT",2029 +"2029-06-07","Sette Giugno","MT",2029 +"2029-06-29","Feast of St. Peter and St. Paul","MT",2029 +"2029-08-15","Feast of the Assumption","MT",2029 +"2029-09-08","Feast of Our Lady of Victories","MT",2029 +"2029-09-21","Independence Day","MT",2029 +"2029-12-08","Feast of the Immaculate Conception","MT",2029 +"2029-12-13","Republic Day","MT",2029 +"2029-12-25","Christmas Day","MT",2029 +"2030-01-01","New Year","MT",2030 +"2030-02-10","Feast of St. Paul's Shipwreck","MT",2030 +"2030-03-19","Feast of St. Joseph","MT",2030 +"2030-03-31","Freedom Day","MT",2030 +"2030-04-19","Good Friday","MT",2030 +"2030-05-01","Worker's Day","MT",2030 +"2030-06-07","Sette Giugno","MT",2030 +"2030-06-29","Feast of St. Peter and St. Paul","MT",2030 +"2030-08-15","Feast of the Assumption","MT",2030 +"2030-09-08","Feast of Our Lady of Victories","MT",2030 +"2030-09-21","Independence Day","MT",2030 +"2030-12-08","Feast of the Immaculate Conception","MT",2030 +"2030-12-13","Republic Day","MT",2030 +"2030-12-25","Christmas Day","MT",2030 +"2031-01-01","New Year","MT",2031 +"2031-02-10","Feast of St. Paul's Shipwreck","MT",2031 +"2031-03-19","Feast of St. Joseph","MT",2031 +"2031-03-31","Freedom Day","MT",2031 +"2031-04-11","Good Friday","MT",2031 +"2031-05-01","Worker's Day","MT",2031 +"2031-06-07","Sette Giugno","MT",2031 +"2031-06-29","Feast of St. Peter and St. Paul","MT",2031 +"2031-08-15","Feast of the Assumption","MT",2031 +"2031-09-08","Feast of Our Lady of Victories","MT",2031 +"2031-09-21","Independence Day","MT",2031 +"2031-12-08","Feast of the Immaculate Conception","MT",2031 +"2031-12-13","Republic Day","MT",2031 +"2031-12-25","Christmas Day","MT",2031 +"2032-01-01","New Year","MT",2032 +"2032-02-10","Feast of St. Paul's Shipwreck","MT",2032 +"2032-03-19","Feast of St. Joseph","MT",2032 +"2032-03-26","Good Friday","MT",2032 +"2032-03-31","Freedom Day","MT",2032 +"2032-05-01","Worker's Day","MT",2032 +"2032-06-07","Sette Giugno","MT",2032 +"2032-06-29","Feast of St. Peter and St. Paul","MT",2032 +"2032-08-15","Feast of the Assumption","MT",2032 +"2032-09-08","Feast of Our Lady of Victories","MT",2032 +"2032-09-21","Independence Day","MT",2032 +"2032-12-08","Feast of the Immaculate Conception","MT",2032 +"2032-12-13","Republic Day","MT",2032 +"2032-12-25","Christmas Day","MT",2032 +"2033-01-01","New Year","MT",2033 +"2033-02-10","Feast of St. Paul's Shipwreck","MT",2033 +"2033-03-19","Feast of St. Joseph","MT",2033 +"2033-03-31","Freedom Day","MT",2033 +"2033-04-15","Good Friday","MT",2033 +"2033-05-01","Worker's Day","MT",2033 +"2033-06-07","Sette Giugno","MT",2033 +"2033-06-29","Feast of St. Peter and St. Paul","MT",2033 +"2033-08-15","Feast of the Assumption","MT",2033 +"2033-09-08","Feast of Our Lady of Victories","MT",2033 +"2033-09-21","Independence Day","MT",2033 +"2033-12-08","Feast of the Immaculate Conception","MT",2033 +"2033-12-13","Republic Day","MT",2033 +"2033-12-25","Christmas Day","MT",2033 +"2034-01-01","New Year","MT",2034 +"2034-02-10","Feast of St. Paul's Shipwreck","MT",2034 +"2034-03-19","Feast of St. Joseph","MT",2034 +"2034-03-31","Freedom Day","MT",2034 +"2034-04-07","Good Friday","MT",2034 +"2034-05-01","Worker's Day","MT",2034 +"2034-06-07","Sette Giugno","MT",2034 +"2034-06-29","Feast of St. Peter and St. Paul","MT",2034 +"2034-08-15","Feast of the Assumption","MT",2034 +"2034-09-08","Feast of Our Lady of Victories","MT",2034 +"2034-09-21","Independence Day","MT",2034 +"2034-12-08","Feast of the Immaculate Conception","MT",2034 +"2034-12-13","Republic Day","MT",2034 +"2034-12-25","Christmas Day","MT",2034 +"2035-01-01","New Year","MT",2035 +"2035-02-10","Feast of St. Paul's Shipwreck","MT",2035 +"2035-03-19","Feast of St. Joseph","MT",2035 +"2035-03-23","Good Friday","MT",2035 +"2035-03-31","Freedom Day","MT",2035 +"2035-05-01","Worker's Day","MT",2035 +"2035-06-07","Sette Giugno","MT",2035 +"2035-06-29","Feast of St. Peter and St. Paul","MT",2035 +"2035-08-15","Feast of the Assumption","MT",2035 +"2035-09-08","Feast of Our Lady of Victories","MT",2035 +"2035-09-21","Independence Day","MT",2035 +"2035-12-08","Feast of the Immaculate Conception","MT",2035 +"2035-12-13","Republic Day","MT",2035 +"2035-12-25","Christmas Day","MT",2035 +"2036-01-01","New Year","MT",2036 +"2036-02-10","Feast of St. Paul's Shipwreck","MT",2036 +"2036-03-19","Feast of St. Joseph","MT",2036 +"2036-03-31","Freedom Day","MT",2036 +"2036-04-11","Good Friday","MT",2036 +"2036-05-01","Worker's Day","MT",2036 +"2036-06-07","Sette Giugno","MT",2036 +"2036-06-29","Feast of St. Peter and St. Paul","MT",2036 +"2036-08-15","Feast of the Assumption","MT",2036 +"2036-09-08","Feast of Our Lady of Victories","MT",2036 +"2036-09-21","Independence Day","MT",2036 +"2036-12-08","Feast of the Immaculate Conception","MT",2036 +"2036-12-13","Republic Day","MT",2036 +"2036-12-25","Christmas Day","MT",2036 +"2037-01-01","New Year","MT",2037 +"2037-02-10","Feast of St. Paul's Shipwreck","MT",2037 +"2037-03-19","Feast of St. Joseph","MT",2037 +"2037-03-31","Freedom Day","MT",2037 +"2037-04-03","Good Friday","MT",2037 +"2037-05-01","Worker's Day","MT",2037 +"2037-06-07","Sette Giugno","MT",2037 +"2037-06-29","Feast of St. Peter and St. Paul","MT",2037 +"2037-08-15","Feast of the Assumption","MT",2037 +"2037-09-08","Feast of Our Lady of Victories","MT",2037 +"2037-09-21","Independence Day","MT",2037 +"2037-12-08","Feast of the Immaculate Conception","MT",2037 +"2037-12-13","Republic Day","MT",2037 +"2037-12-25","Christmas Day","MT",2037 +"2038-01-01","New Year","MT",2038 +"2038-02-10","Feast of St. Paul's Shipwreck","MT",2038 +"2038-03-19","Feast of St. Joseph","MT",2038 +"2038-03-31","Freedom Day","MT",2038 +"2038-04-23","Good Friday","MT",2038 +"2038-05-01","Worker's Day","MT",2038 +"2038-06-07","Sette Giugno","MT",2038 +"2038-06-29","Feast of St. Peter and St. Paul","MT",2038 +"2038-08-15","Feast of the Assumption","MT",2038 +"2038-09-08","Feast of Our Lady of Victories","MT",2038 +"2038-09-21","Independence Day","MT",2038 +"2038-12-08","Feast of the Immaculate Conception","MT",2038 +"2038-12-13","Republic Day","MT",2038 +"2038-12-25","Christmas Day","MT",2038 +"2039-01-01","New Year","MT",2039 +"2039-02-10","Feast of St. Paul's Shipwreck","MT",2039 +"2039-03-19","Feast of St. Joseph","MT",2039 +"2039-03-31","Freedom Day","MT",2039 +"2039-04-08","Good Friday","MT",2039 +"2039-05-01","Worker's Day","MT",2039 +"2039-06-07","Sette Giugno","MT",2039 +"2039-06-29","Feast of St. Peter and St. Paul","MT",2039 +"2039-08-15","Feast of the Assumption","MT",2039 +"2039-09-08","Feast of Our Lady of Victories","MT",2039 +"2039-09-21","Independence Day","MT",2039 +"2039-12-08","Feast of the Immaculate Conception","MT",2039 +"2039-12-13","Republic Day","MT",2039 +"2039-12-25","Christmas Day","MT",2039 +"2040-01-01","New Year","MT",2040 +"2040-02-10","Feast of St. Paul's Shipwreck","MT",2040 +"2040-03-19","Feast of St. Joseph","MT",2040 +"2040-03-30","Good Friday","MT",2040 +"2040-03-31","Freedom Day","MT",2040 +"2040-05-01","Worker's Day","MT",2040 +"2040-06-07","Sette Giugno","MT",2040 +"2040-06-29","Feast of St. Peter and St. Paul","MT",2040 +"2040-08-15","Feast of the Assumption","MT",2040 +"2040-09-08","Feast of Our Lady of Victories","MT",2040 +"2040-09-21","Independence Day","MT",2040 +"2040-12-08","Feast of the Immaculate Conception","MT",2040 +"2040-12-13","Republic Day","MT",2040 +"2040-12-25","Christmas Day","MT",2040 +"2041-01-01","New Year","MT",2041 +"2041-02-10","Feast of St. Paul's Shipwreck","MT",2041 +"2041-03-19","Feast of St. Joseph","MT",2041 +"2041-03-31","Freedom Day","MT",2041 +"2041-04-19","Good Friday","MT",2041 +"2041-05-01","Worker's Day","MT",2041 +"2041-06-07","Sette Giugno","MT",2041 +"2041-06-29","Feast of St. Peter and St. Paul","MT",2041 +"2041-08-15","Feast of the Assumption","MT",2041 +"2041-09-08","Feast of Our Lady of Victories","MT",2041 +"2041-09-21","Independence Day","MT",2041 +"2041-12-08","Feast of the Immaculate Conception","MT",2041 +"2041-12-13","Republic Day","MT",2041 +"2041-12-25","Christmas Day","MT",2041 +"2042-01-01","New Year","MT",2042 +"2042-02-10","Feast of St. Paul's Shipwreck","MT",2042 +"2042-03-19","Feast of St. Joseph","MT",2042 +"2042-03-31","Freedom Day","MT",2042 +"2042-04-04","Good Friday","MT",2042 +"2042-05-01","Worker's Day","MT",2042 +"2042-06-07","Sette Giugno","MT",2042 +"2042-06-29","Feast of St. Peter and St. Paul","MT",2042 +"2042-08-15","Feast of the Assumption","MT",2042 +"2042-09-08","Feast of Our Lady of Victories","MT",2042 +"2042-09-21","Independence Day","MT",2042 +"2042-12-08","Feast of the Immaculate Conception","MT",2042 +"2042-12-13","Republic Day","MT",2042 +"2042-12-25","Christmas Day","MT",2042 +"2043-01-01","New Year","MT",2043 +"2043-02-10","Feast of St. Paul's Shipwreck","MT",2043 +"2043-03-19","Feast of St. Joseph","MT",2043 +"2043-03-27","Good Friday","MT",2043 +"2043-03-31","Freedom Day","MT",2043 +"2043-05-01","Worker's Day","MT",2043 +"2043-06-07","Sette Giugno","MT",2043 +"2043-06-29","Feast of St. Peter and St. Paul","MT",2043 +"2043-08-15","Feast of the Assumption","MT",2043 +"2043-09-08","Feast of Our Lady of Victories","MT",2043 +"2043-09-21","Independence Day","MT",2043 +"2043-12-08","Feast of the Immaculate Conception","MT",2043 +"2043-12-13","Republic Day","MT",2043 +"2043-12-25","Christmas Day","MT",2043 +"2044-01-01","New Year","MT",2044 +"2044-02-10","Feast of St. Paul's Shipwreck","MT",2044 +"2044-03-19","Feast of St. Joseph","MT",2044 +"2044-03-31","Freedom Day","MT",2044 +"2044-04-15","Good Friday","MT",2044 +"2044-05-01","Worker's Day","MT",2044 +"2044-06-07","Sette Giugno","MT",2044 +"2044-06-29","Feast of St. Peter and St. Paul","MT",2044 +"2044-08-15","Feast of the Assumption","MT",2044 +"2044-09-08","Feast of Our Lady of Victories","MT",2044 +"2044-09-21","Independence Day","MT",2044 +"2044-12-08","Feast of the Immaculate Conception","MT",2044 +"2044-12-13","Republic Day","MT",2044 +"2044-12-25","Christmas Day","MT",2044 +"2000-01-01","New Year's Day","MW",2000 +"2000-01-03","New Year's Day (Observed)","MW",2000 +"2000-01-15","John Chilembwe Day","MW",2000 +"2000-01-17","John Chilembwe Day (Observed)","MW",2000 +"2000-03-03","Martyrs Day","MW",2000 +"2000-04-21","Good Friday","MW",2000 +"2000-04-24","Easter Monday","MW",2000 +"2000-05-01","Labour Day","MW",2000 +"2000-05-14","Kamuzu Day","MW",2000 +"2000-05-15","Kamuzu Day (Observed)","MW",2000 +"2000-07-06","Independence Day","MW",2000 +"2000-10-15","Mother's Day","MW",2000 +"2000-10-16","Mother's Day (Observed)","MW",2000 +"2000-12-25","Christmas Day","MW",2000 +"2000-12-26","Boxing Day","MW",2000 +"2001-01-01","New Year's Day","MW",2001 +"2001-01-15","John Chilembwe Day","MW",2001 +"2001-03-03","Martyrs Day","MW",2001 +"2001-03-05","Martyrs Day (Observed)","MW",2001 +"2001-04-13","Good Friday","MW",2001 +"2001-04-16","Easter Monday","MW",2001 +"2001-05-01","Labour Day","MW",2001 +"2001-05-14","Kamuzu Day","MW",2001 +"2001-07-06","Independence Day","MW",2001 +"2001-10-15","Mother's Day","MW",2001 +"2001-12-25","Christmas Day","MW",2001 +"2001-12-26","Boxing Day","MW",2001 +"2002-01-01","New Year's Day","MW",2002 +"2002-01-15","John Chilembwe Day","MW",2002 +"2002-03-03","Martyrs Day","MW",2002 +"2002-03-04","Martyrs Day (Observed)","MW",2002 +"2002-03-29","Good Friday","MW",2002 +"2002-04-01","Easter Monday","MW",2002 +"2002-05-01","Labour Day","MW",2002 +"2002-05-14","Kamuzu Day","MW",2002 +"2002-07-06","Independence Day","MW",2002 +"2002-07-08","Independence Day (Observed)","MW",2002 +"2002-10-15","Mother's Day","MW",2002 +"2002-12-25","Christmas Day","MW",2002 +"2002-12-26","Boxing Day","MW",2002 +"2003-01-01","New Year's Day","MW",2003 +"2003-01-15","John Chilembwe Day","MW",2003 +"2003-03-03","Martyrs Day","MW",2003 +"2003-04-18","Good Friday","MW",2003 +"2003-04-21","Easter Monday","MW",2003 +"2003-05-01","Labour Day","MW",2003 +"2003-05-14","Kamuzu Day","MW",2003 +"2003-07-06","Independence Day","MW",2003 +"2003-07-07","Independence Day (Observed)","MW",2003 +"2003-10-15","Mother's Day","MW",2003 +"2003-12-25","Christmas Day","MW",2003 +"2003-12-26","Boxing Day","MW",2003 +"2004-01-01","New Year's Day","MW",2004 +"2004-01-15","John Chilembwe Day","MW",2004 +"2004-03-03","Martyrs Day","MW",2004 +"2004-04-09","Good Friday","MW",2004 +"2004-04-12","Easter Monday","MW",2004 +"2004-05-01","Labour Day","MW",2004 +"2004-05-03","Labour Day (Observed)","MW",2004 +"2004-05-14","Kamuzu Day","MW",2004 +"2004-07-06","Independence Day","MW",2004 +"2004-10-15","Mother's Day","MW",2004 +"2004-12-25","Christmas Day","MW",2004 +"2004-12-26","Boxing Day","MW",2004 +"2004-12-27","Christmas Day (Observed)","MW",2004 +"2004-12-28","Boxing Day (Observed)","MW",2004 +"2005-01-01","New Year's Day","MW",2005 +"2005-01-03","New Year's Day (Observed)","MW",2005 +"2005-01-15","John Chilembwe Day","MW",2005 +"2005-01-17","John Chilembwe Day (Observed)","MW",2005 +"2005-03-03","Martyrs Day","MW",2005 +"2005-03-25","Good Friday","MW",2005 +"2005-03-28","Easter Monday","MW",2005 +"2005-05-01","Labour Day","MW",2005 +"2005-05-02","Labour Day (Observed)","MW",2005 +"2005-05-14","Kamuzu Day","MW",2005 +"2005-05-16","Kamuzu Day (Observed)","MW",2005 +"2005-07-06","Independence Day","MW",2005 +"2005-10-15","Mother's Day","MW",2005 +"2005-10-17","Mother's Day (Observed)","MW",2005 +"2005-12-25","Christmas Day","MW",2005 +"2005-12-26","Boxing Day","MW",2005 +"2005-12-27","Christmas Day (Observed)","MW",2005 +"2006-01-01","New Year's Day","MW",2006 +"2006-01-02","New Year's Day (Observed)","MW",2006 +"2006-01-15","John Chilembwe Day","MW",2006 +"2006-01-16","John Chilembwe Day (Observed)","MW",2006 +"2006-03-03","Martyrs Day","MW",2006 +"2006-04-14","Good Friday","MW",2006 +"2006-04-17","Easter Monday","MW",2006 +"2006-05-01","Labour Day","MW",2006 +"2006-05-14","Kamuzu Day","MW",2006 +"2006-05-15","Kamuzu Day (Observed)","MW",2006 +"2006-07-06","Independence Day","MW",2006 +"2006-10-15","Mother's Day","MW",2006 +"2006-10-16","Mother's Day (Observed)","MW",2006 +"2006-12-25","Christmas Day","MW",2006 +"2006-12-26","Boxing Day","MW",2006 +"2007-01-01","New Year's Day","MW",2007 +"2007-01-15","John Chilembwe Day","MW",2007 +"2007-03-03","Martyrs Day","MW",2007 +"2007-03-05","Martyrs Day (Observed)","MW",2007 +"2007-04-06","Good Friday","MW",2007 +"2007-04-09","Easter Monday","MW",2007 +"2007-05-01","Labour Day","MW",2007 +"2007-05-14","Kamuzu Day","MW",2007 +"2007-07-06","Independence Day","MW",2007 +"2007-10-15","Mother's Day","MW",2007 +"2007-12-25","Christmas Day","MW",2007 +"2007-12-26","Boxing Day","MW",2007 +"2008-01-01","New Year's Day","MW",2008 +"2008-01-15","John Chilembwe Day","MW",2008 +"2008-03-03","Martyrs Day","MW",2008 +"2008-03-21","Good Friday","MW",2008 +"2008-03-24","Easter Monday","MW",2008 +"2008-05-01","Labour Day","MW",2008 +"2008-05-14","Kamuzu Day","MW",2008 +"2008-07-06","Independence Day","MW",2008 +"2008-07-07","Independence Day (Observed)","MW",2008 +"2008-10-15","Mother's Day","MW",2008 +"2008-12-25","Christmas Day","MW",2008 +"2008-12-26","Boxing Day","MW",2008 +"2009-01-01","New Year's Day","MW",2009 +"2009-01-15","John Chilembwe Day","MW",2009 +"2009-03-03","Martyrs Day","MW",2009 +"2009-04-10","Good Friday","MW",2009 +"2009-04-13","Easter Monday","MW",2009 +"2009-05-01","Labour Day","MW",2009 +"2009-05-14","Kamuzu Day","MW",2009 +"2009-07-06","Independence Day","MW",2009 +"2009-10-15","Mother's Day","MW",2009 +"2009-12-25","Christmas Day","MW",2009 +"2009-12-26","Boxing Day","MW",2009 +"2009-12-28","Boxing Day (Observed)","MW",2009 +"2010-01-01","New Year's Day","MW",2010 +"2010-01-15","John Chilembwe Day","MW",2010 +"2010-03-03","Martyrs Day","MW",2010 +"2010-04-02","Good Friday","MW",2010 +"2010-04-05","Easter Monday","MW",2010 +"2010-05-01","Labour Day","MW",2010 +"2010-05-03","Labour Day (Observed)","MW",2010 +"2010-05-14","Kamuzu Day","MW",2010 +"2010-07-06","Independence Day","MW",2010 +"2010-10-15","Mother's Day","MW",2010 +"2010-12-25","Christmas Day","MW",2010 +"2010-12-26","Boxing Day","MW",2010 +"2010-12-27","Christmas Day (Observed)","MW",2010 +"2010-12-28","Boxing Day (Observed)","MW",2010 +"2011-01-01","New Year's Day","MW",2011 +"2011-01-03","New Year's Day (Observed)","MW",2011 +"2011-01-15","John Chilembwe Day","MW",2011 +"2011-01-17","John Chilembwe Day (Observed)","MW",2011 +"2011-03-03","Martyrs Day","MW",2011 +"2011-04-22","Good Friday","MW",2011 +"2011-04-25","Easter Monday","MW",2011 +"2011-05-01","Labour Day","MW",2011 +"2011-05-02","Labour Day (Observed)","MW",2011 +"2011-05-14","Kamuzu Day","MW",2011 +"2011-05-16","Kamuzu Day (Observed)","MW",2011 +"2011-07-06","Independence Day","MW",2011 +"2011-10-15","Mother's Day","MW",2011 +"2011-10-17","Mother's Day (Observed)","MW",2011 +"2011-12-25","Christmas Day","MW",2011 +"2011-12-26","Boxing Day","MW",2011 +"2011-12-27","Christmas Day (Observed)","MW",2011 +"2012-01-01","New Year's Day","MW",2012 +"2012-01-02","New Year's Day (Observed)","MW",2012 +"2012-01-15","John Chilembwe Day","MW",2012 +"2012-01-16","John Chilembwe Day (Observed)","MW",2012 +"2012-03-03","Martyrs Day","MW",2012 +"2012-03-05","Martyrs Day (Observed)","MW",2012 +"2012-04-06","Good Friday","MW",2012 +"2012-04-09","Easter Monday","MW",2012 +"2012-05-01","Labour Day","MW",2012 +"2012-05-14","Kamuzu Day","MW",2012 +"2012-07-06","Independence Day","MW",2012 +"2012-10-15","Mother's Day","MW",2012 +"2012-12-25","Christmas Day","MW",2012 +"2012-12-26","Boxing Day","MW",2012 +"2013-01-01","New Year's Day","MW",2013 +"2013-01-15","John Chilembwe Day","MW",2013 +"2013-03-03","Martyrs Day","MW",2013 +"2013-03-04","Martyrs Day (Observed)","MW",2013 +"2013-03-29","Good Friday","MW",2013 +"2013-04-01","Easter Monday","MW",2013 +"2013-05-01","Labour Day","MW",2013 +"2013-05-14","Kamuzu Day","MW",2013 +"2013-07-06","Independence Day","MW",2013 +"2013-07-08","Independence Day (Observed)","MW",2013 +"2013-10-15","Mother's Day","MW",2013 +"2013-12-25","Christmas Day","MW",2013 +"2013-12-26","Boxing Day","MW",2013 +"2014-01-01","New Year's Day","MW",2014 +"2014-01-15","John Chilembwe Day","MW",2014 +"2014-03-03","Martyrs Day","MW",2014 +"2014-04-18","Good Friday","MW",2014 +"2014-04-21","Easter Monday","MW",2014 +"2014-05-01","Labour Day","MW",2014 +"2014-05-14","Kamuzu Day","MW",2014 +"2014-07-06","Independence Day","MW",2014 +"2014-07-07","Independence Day (Observed)","MW",2014 +"2014-10-15","Mother's Day","MW",2014 +"2014-12-25","Christmas Day","MW",2014 +"2014-12-26","Boxing Day","MW",2014 +"2015-01-01","New Year's Day","MW",2015 +"2015-01-15","John Chilembwe Day","MW",2015 +"2015-03-03","Martyrs Day","MW",2015 +"2015-04-03","Good Friday","MW",2015 +"2015-04-06","Easter Monday","MW",2015 +"2015-05-01","Labour Day","MW",2015 +"2015-05-14","Kamuzu Day","MW",2015 +"2015-07-06","Independence Day","MW",2015 +"2015-10-15","Mother's Day","MW",2015 +"2015-12-25","Christmas Day","MW",2015 +"2015-12-26","Boxing Day","MW",2015 +"2015-12-28","Boxing Day (Observed)","MW",2015 +"2016-01-01","New Year's Day","MW",2016 +"2016-01-15","John Chilembwe Day","MW",2016 +"2016-03-03","Martyrs Day","MW",2016 +"2016-03-25","Good Friday","MW",2016 +"2016-03-28","Easter Monday","MW",2016 +"2016-05-01","Labour Day","MW",2016 +"2016-05-02","Labour Day (Observed)","MW",2016 +"2016-05-14","Kamuzu Day","MW",2016 +"2016-05-16","Kamuzu Day (Observed)","MW",2016 +"2016-07-06","Independence Day","MW",2016 +"2016-10-15","Mother's Day","MW",2016 +"2016-10-17","Mother's Day (Observed)","MW",2016 +"2016-12-25","Christmas Day","MW",2016 +"2016-12-26","Boxing Day","MW",2016 +"2016-12-27","Christmas Day (Observed)","MW",2016 +"2017-01-01","New Year's Day","MW",2017 +"2017-01-02","New Year's Day (Observed)","MW",2017 +"2017-01-15","John Chilembwe Day","MW",2017 +"2017-01-16","John Chilembwe Day (Observed)","MW",2017 +"2017-03-03","Martyrs Day","MW",2017 +"2017-04-14","Good Friday","MW",2017 +"2017-04-17","Easter Monday","MW",2017 +"2017-05-01","Labour Day","MW",2017 +"2017-05-14","Kamuzu Day","MW",2017 +"2017-05-15","Kamuzu Day (Observed)","MW",2017 +"2017-07-06","Independence Day","MW",2017 +"2017-10-15","Mother's Day","MW",2017 +"2017-10-16","Mother's Day (Observed)","MW",2017 +"2017-12-25","Christmas Day","MW",2017 +"2017-12-26","Boxing Day","MW",2017 +"2018-01-01","New Year's Day","MW",2018 +"2018-01-15","John Chilembwe Day","MW",2018 +"2018-03-03","Martyrs Day","MW",2018 +"2018-03-05","Martyrs Day (Observed)","MW",2018 +"2018-03-30","Good Friday","MW",2018 +"2018-04-02","Easter Monday","MW",2018 +"2018-05-01","Labour Day","MW",2018 +"2018-05-14","Kamuzu Day","MW",2018 +"2018-07-06","Independence Day","MW",2018 +"2018-10-15","Mother's Day","MW",2018 +"2018-12-25","Christmas Day","MW",2018 +"2018-12-26","Boxing Day","MW",2018 +"2019-01-01","New Year's Day","MW",2019 +"2019-01-15","John Chilembwe Day","MW",2019 +"2019-03-03","Martyrs Day","MW",2019 +"2019-03-04","Martyrs Day (Observed)","MW",2019 +"2019-04-19","Good Friday","MW",2019 +"2019-04-22","Easter Monday","MW",2019 +"2019-05-01","Labour Day","MW",2019 +"2019-05-14","Kamuzu Day","MW",2019 +"2019-07-06","Independence Day","MW",2019 +"2019-07-08","Independence Day (Observed)","MW",2019 +"2019-10-15","Mother's Day","MW",2019 +"2019-12-25","Christmas Day","MW",2019 +"2019-12-26","Boxing Day","MW",2019 +"2020-01-01","New Year's Day","MW",2020 +"2020-01-15","John Chilembwe Day","MW",2020 +"2020-03-03","Martyrs Day","MW",2020 +"2020-04-10","Good Friday","MW",2020 +"2020-04-13","Easter Monday","MW",2020 +"2020-05-01","Labour Day","MW",2020 +"2020-05-14","Kamuzu Day","MW",2020 +"2020-07-06","Independence Day","MW",2020 +"2020-10-15","Mother's Day","MW",2020 +"2020-12-25","Christmas Day","MW",2020 +"2020-12-26","Boxing Day","MW",2020 +"2020-12-28","Boxing Day (Observed)","MW",2020 +"2021-01-01","New Year's Day","MW",2021 +"2021-01-15","John Chilembwe Day","MW",2021 +"2021-03-03","Martyrs Day","MW",2021 +"2021-04-02","Good Friday","MW",2021 +"2021-04-05","Easter Monday","MW",2021 +"2021-05-01","Labour Day","MW",2021 +"2021-05-03","Labour Day (Observed)","MW",2021 +"2021-05-14","Kamuzu Day","MW",2021 +"2021-07-06","Independence Day","MW",2021 +"2021-10-15","Mother's Day","MW",2021 +"2021-12-25","Christmas Day","MW",2021 +"2021-12-26","Boxing Day","MW",2021 +"2021-12-27","Christmas Day (Observed)","MW",2021 +"2021-12-28","Boxing Day (Observed)","MW",2021 +"2022-01-01","New Year's Day","MW",2022 +"2022-01-03","New Year's Day (Observed)","MW",2022 +"2022-01-15","John Chilembwe Day","MW",2022 +"2022-01-17","John Chilembwe Day (Observed)","MW",2022 +"2022-03-03","Martyrs Day","MW",2022 +"2022-04-15","Good Friday","MW",2022 +"2022-04-18","Easter Monday","MW",2022 +"2022-05-01","Labour Day","MW",2022 +"2022-05-02","Labour Day (Observed)","MW",2022 +"2022-05-14","Kamuzu Day","MW",2022 +"2022-05-16","Kamuzu Day (Observed)","MW",2022 +"2022-07-06","Independence Day","MW",2022 +"2022-10-15","Mother's Day","MW",2022 +"2022-10-17","Mother's Day (Observed)","MW",2022 +"2022-12-25","Christmas Day","MW",2022 +"2022-12-26","Boxing Day","MW",2022 +"2022-12-27","Christmas Day (Observed)","MW",2022 +"2023-01-01","New Year's Day","MW",2023 +"2023-01-02","New Year's Day (Observed)","MW",2023 +"2023-01-15","John Chilembwe Day","MW",2023 +"2023-01-16","John Chilembwe Day (Observed)","MW",2023 +"2023-03-03","Martyrs Day","MW",2023 +"2023-04-07","Good Friday","MW",2023 +"2023-04-10","Easter Monday","MW",2023 +"2023-05-01","Labour Day","MW",2023 +"2023-05-14","Kamuzu Day","MW",2023 +"2023-05-15","Kamuzu Day (Observed)","MW",2023 +"2023-07-06","Independence Day","MW",2023 +"2023-10-15","Mother's Day","MW",2023 +"2023-10-16","Mother's Day (Observed)","MW",2023 +"2023-12-25","Christmas Day","MW",2023 +"2023-12-26","Boxing Day","MW",2023 +"2024-01-01","New Year's Day","MW",2024 +"2024-01-15","John Chilembwe Day","MW",2024 +"2024-03-03","Martyrs Day","MW",2024 +"2024-03-04","Martyrs Day (Observed)","MW",2024 +"2024-03-29","Good Friday","MW",2024 +"2024-04-01","Easter Monday","MW",2024 +"2024-05-01","Labour Day","MW",2024 +"2024-05-14","Kamuzu Day","MW",2024 +"2024-07-06","Independence Day","MW",2024 +"2024-07-08","Independence Day (Observed)","MW",2024 +"2024-10-15","Mother's Day","MW",2024 +"2024-12-25","Christmas Day","MW",2024 +"2024-12-26","Boxing Day","MW",2024 +"2025-01-01","New Year's Day","MW",2025 +"2025-01-15","John Chilembwe Day","MW",2025 +"2025-03-03","Martyrs Day","MW",2025 +"2025-04-18","Good Friday","MW",2025 +"2025-04-21","Easter Monday","MW",2025 +"2025-05-01","Labour Day","MW",2025 +"2025-05-14","Kamuzu Day","MW",2025 +"2025-07-06","Independence Day","MW",2025 +"2025-07-07","Independence Day (Observed)","MW",2025 +"2025-10-15","Mother's Day","MW",2025 +"2025-12-25","Christmas Day","MW",2025 +"2025-12-26","Boxing Day","MW",2025 +"2026-01-01","New Year's Day","MW",2026 +"2026-01-15","John Chilembwe Day","MW",2026 +"2026-03-03","Martyrs Day","MW",2026 +"2026-04-03","Good Friday","MW",2026 +"2026-04-06","Easter Monday","MW",2026 +"2026-05-01","Labour Day","MW",2026 +"2026-05-14","Kamuzu Day","MW",2026 +"2026-07-06","Independence Day","MW",2026 +"2026-10-15","Mother's Day","MW",2026 +"2026-12-25","Christmas Day","MW",2026 +"2026-12-26","Boxing Day","MW",2026 +"2026-12-28","Boxing Day (Observed)","MW",2026 +"2027-01-01","New Year's Day","MW",2027 +"2027-01-15","John Chilembwe Day","MW",2027 +"2027-03-03","Martyrs Day","MW",2027 +"2027-03-26","Good Friday","MW",2027 +"2027-03-29","Easter Monday","MW",2027 +"2027-05-01","Labour Day","MW",2027 +"2027-05-03","Labour Day (Observed)","MW",2027 +"2027-05-14","Kamuzu Day","MW",2027 +"2027-07-06","Independence Day","MW",2027 +"2027-10-15","Mother's Day","MW",2027 +"2027-12-25","Christmas Day","MW",2027 +"2027-12-26","Boxing Day","MW",2027 +"2027-12-27","Christmas Day (Observed)","MW",2027 +"2027-12-28","Boxing Day (Observed)","MW",2027 +"2028-01-01","New Year's Day","MW",2028 +"2028-01-03","New Year's Day (Observed)","MW",2028 +"2028-01-15","John Chilembwe Day","MW",2028 +"2028-01-17","John Chilembwe Day (Observed)","MW",2028 +"2028-03-03","Martyrs Day","MW",2028 +"2028-04-14","Good Friday","MW",2028 +"2028-04-17","Easter Monday","MW",2028 +"2028-05-01","Labour Day","MW",2028 +"2028-05-14","Kamuzu Day","MW",2028 +"2028-05-15","Kamuzu Day (Observed)","MW",2028 +"2028-07-06","Independence Day","MW",2028 +"2028-10-15","Mother's Day","MW",2028 +"2028-10-16","Mother's Day (Observed)","MW",2028 +"2028-12-25","Christmas Day","MW",2028 +"2028-12-26","Boxing Day","MW",2028 +"2029-01-01","New Year's Day","MW",2029 +"2029-01-15","John Chilembwe Day","MW",2029 +"2029-03-03","Martyrs Day","MW",2029 +"2029-03-05","Martyrs Day (Observed)","MW",2029 +"2029-03-30","Good Friday","MW",2029 +"2029-04-02","Easter Monday","MW",2029 +"2029-05-01","Labour Day","MW",2029 +"2029-05-14","Kamuzu Day","MW",2029 +"2029-07-06","Independence Day","MW",2029 +"2029-10-15","Mother's Day","MW",2029 +"2029-12-25","Christmas Day","MW",2029 +"2029-12-26","Boxing Day","MW",2029 +"2030-01-01","New Year's Day","MW",2030 +"2030-01-15","John Chilembwe Day","MW",2030 +"2030-03-03","Martyrs Day","MW",2030 +"2030-03-04","Martyrs Day (Observed)","MW",2030 +"2030-04-19","Good Friday","MW",2030 +"2030-04-22","Easter Monday","MW",2030 +"2030-05-01","Labour Day","MW",2030 +"2030-05-14","Kamuzu Day","MW",2030 +"2030-07-06","Independence Day","MW",2030 +"2030-07-08","Independence Day (Observed)","MW",2030 +"2030-10-15","Mother's Day","MW",2030 +"2030-12-25","Christmas Day","MW",2030 +"2030-12-26","Boxing Day","MW",2030 +"2031-01-01","New Year's Day","MW",2031 +"2031-01-15","John Chilembwe Day","MW",2031 +"2031-03-03","Martyrs Day","MW",2031 +"2031-04-11","Good Friday","MW",2031 +"2031-04-14","Easter Monday","MW",2031 +"2031-05-01","Labour Day","MW",2031 +"2031-05-14","Kamuzu Day","MW",2031 +"2031-07-06","Independence Day","MW",2031 +"2031-07-07","Independence Day (Observed)","MW",2031 +"2031-10-15","Mother's Day","MW",2031 +"2031-12-25","Christmas Day","MW",2031 +"2031-12-26","Boxing Day","MW",2031 +"2032-01-01","New Year's Day","MW",2032 +"2032-01-15","John Chilembwe Day","MW",2032 +"2032-03-03","Martyrs Day","MW",2032 +"2032-03-26","Good Friday","MW",2032 +"2032-03-29","Easter Monday","MW",2032 +"2032-05-01","Labour Day","MW",2032 +"2032-05-03","Labour Day (Observed)","MW",2032 +"2032-05-14","Kamuzu Day","MW",2032 +"2032-07-06","Independence Day","MW",2032 +"2032-10-15","Mother's Day","MW",2032 +"2032-12-25","Christmas Day","MW",2032 +"2032-12-26","Boxing Day","MW",2032 +"2032-12-27","Christmas Day (Observed)","MW",2032 +"2032-12-28","Boxing Day (Observed)","MW",2032 +"2033-01-01","New Year's Day","MW",2033 +"2033-01-03","New Year's Day (Observed)","MW",2033 +"2033-01-15","John Chilembwe Day","MW",2033 +"2033-01-17","John Chilembwe Day (Observed)","MW",2033 +"2033-03-03","Martyrs Day","MW",2033 +"2033-04-15","Good Friday","MW",2033 +"2033-04-18","Easter Monday","MW",2033 +"2033-05-01","Labour Day","MW",2033 +"2033-05-02","Labour Day (Observed)","MW",2033 +"2033-05-14","Kamuzu Day","MW",2033 +"2033-05-16","Kamuzu Day (Observed)","MW",2033 +"2033-07-06","Independence Day","MW",2033 +"2033-10-15","Mother's Day","MW",2033 +"2033-10-17","Mother's Day (Observed)","MW",2033 +"2033-12-25","Christmas Day","MW",2033 +"2033-12-26","Boxing Day","MW",2033 +"2033-12-27","Christmas Day (Observed)","MW",2033 +"2034-01-01","New Year's Day","MW",2034 +"2034-01-02","New Year's Day (Observed)","MW",2034 +"2034-01-15","John Chilembwe Day","MW",2034 +"2034-01-16","John Chilembwe Day (Observed)","MW",2034 +"2034-03-03","Martyrs Day","MW",2034 +"2034-04-07","Good Friday","MW",2034 +"2034-04-10","Easter Monday","MW",2034 +"2034-05-01","Labour Day","MW",2034 +"2034-05-14","Kamuzu Day","MW",2034 +"2034-05-15","Kamuzu Day (Observed)","MW",2034 +"2034-07-06","Independence Day","MW",2034 +"2034-10-15","Mother's Day","MW",2034 +"2034-10-16","Mother's Day (Observed)","MW",2034 +"2034-12-25","Christmas Day","MW",2034 +"2034-12-26","Boxing Day","MW",2034 +"2035-01-01","New Year's Day","MW",2035 +"2035-01-15","John Chilembwe Day","MW",2035 +"2035-03-03","Martyrs Day","MW",2035 +"2035-03-05","Martyrs Day (Observed)","MW",2035 +"2035-03-23","Good Friday","MW",2035 +"2035-03-26","Easter Monday","MW",2035 +"2035-05-01","Labour Day","MW",2035 +"2035-05-14","Kamuzu Day","MW",2035 +"2035-07-06","Independence Day","MW",2035 +"2035-10-15","Mother's Day","MW",2035 +"2035-12-25","Christmas Day","MW",2035 +"2035-12-26","Boxing Day","MW",2035 +"2036-01-01","New Year's Day","MW",2036 +"2036-01-15","John Chilembwe Day","MW",2036 +"2036-03-03","Martyrs Day","MW",2036 +"2036-04-11","Good Friday","MW",2036 +"2036-04-14","Easter Monday","MW",2036 +"2036-05-01","Labour Day","MW",2036 +"2036-05-14","Kamuzu Day","MW",2036 +"2036-07-06","Independence Day","MW",2036 +"2036-07-07","Independence Day (Observed)","MW",2036 +"2036-10-15","Mother's Day","MW",2036 +"2036-12-25","Christmas Day","MW",2036 +"2036-12-26","Boxing Day","MW",2036 +"2037-01-01","New Year's Day","MW",2037 +"2037-01-15","John Chilembwe Day","MW",2037 +"2037-03-03","Martyrs Day","MW",2037 +"2037-04-03","Good Friday","MW",2037 +"2037-04-06","Easter Monday","MW",2037 +"2037-05-01","Labour Day","MW",2037 +"2037-05-14","Kamuzu Day","MW",2037 +"2037-07-06","Independence Day","MW",2037 +"2037-10-15","Mother's Day","MW",2037 +"2037-12-25","Christmas Day","MW",2037 +"2037-12-26","Boxing Day","MW",2037 +"2037-12-28","Boxing Day (Observed)","MW",2037 +"2038-01-01","New Year's Day","MW",2038 +"2038-01-15","John Chilembwe Day","MW",2038 +"2038-03-03","Martyrs Day","MW",2038 +"2038-04-23","Good Friday","MW",2038 +"2038-04-26","Easter Monday","MW",2038 +"2038-05-01","Labour Day","MW",2038 +"2038-05-03","Labour Day (Observed)","MW",2038 +"2038-05-14","Kamuzu Day","MW",2038 +"2038-07-06","Independence Day","MW",2038 +"2038-10-15","Mother's Day","MW",2038 +"2038-12-25","Christmas Day","MW",2038 +"2038-12-26","Boxing Day","MW",2038 +"2038-12-27","Christmas Day (Observed)","MW",2038 +"2038-12-28","Boxing Day (Observed)","MW",2038 +"2039-01-01","New Year's Day","MW",2039 +"2039-01-03","New Year's Day (Observed)","MW",2039 +"2039-01-15","John Chilembwe Day","MW",2039 +"2039-01-17","John Chilembwe Day (Observed)","MW",2039 +"2039-03-03","Martyrs Day","MW",2039 +"2039-04-08","Good Friday","MW",2039 +"2039-04-11","Easter Monday","MW",2039 +"2039-05-01","Labour Day","MW",2039 +"2039-05-02","Labour Day (Observed)","MW",2039 +"2039-05-14","Kamuzu Day","MW",2039 +"2039-05-16","Kamuzu Day (Observed)","MW",2039 +"2039-07-06","Independence Day","MW",2039 +"2039-10-15","Mother's Day","MW",2039 +"2039-10-17","Mother's Day (Observed)","MW",2039 +"2039-12-25","Christmas Day","MW",2039 +"2039-12-26","Boxing Day","MW",2039 +"2039-12-27","Christmas Day (Observed)","MW",2039 +"2040-01-01","New Year's Day","MW",2040 +"2040-01-02","New Year's Day (Observed)","MW",2040 +"2040-01-15","John Chilembwe Day","MW",2040 +"2040-01-16","John Chilembwe Day (Observed)","MW",2040 +"2040-03-03","Martyrs Day","MW",2040 +"2040-03-05","Martyrs Day (Observed)","MW",2040 +"2040-03-30","Good Friday","MW",2040 +"2040-04-02","Easter Monday","MW",2040 +"2040-05-01","Labour Day","MW",2040 +"2040-05-14","Kamuzu Day","MW",2040 +"2040-07-06","Independence Day","MW",2040 +"2040-10-15","Mother's Day","MW",2040 +"2040-12-25","Christmas Day","MW",2040 +"2040-12-26","Boxing Day","MW",2040 +"2041-01-01","New Year's Day","MW",2041 +"2041-01-15","John Chilembwe Day","MW",2041 +"2041-03-03","Martyrs Day","MW",2041 +"2041-03-04","Martyrs Day (Observed)","MW",2041 +"2041-04-19","Good Friday","MW",2041 +"2041-04-22","Easter Monday","MW",2041 +"2041-05-01","Labour Day","MW",2041 +"2041-05-14","Kamuzu Day","MW",2041 +"2041-07-06","Independence Day","MW",2041 +"2041-07-08","Independence Day (Observed)","MW",2041 +"2041-10-15","Mother's Day","MW",2041 +"2041-12-25","Christmas Day","MW",2041 +"2041-12-26","Boxing Day","MW",2041 +"2042-01-01","New Year's Day","MW",2042 +"2042-01-15","John Chilembwe Day","MW",2042 +"2042-03-03","Martyrs Day","MW",2042 +"2042-04-04","Good Friday","MW",2042 +"2042-04-07","Easter Monday","MW",2042 +"2042-05-01","Labour Day","MW",2042 +"2042-05-14","Kamuzu Day","MW",2042 +"2042-07-06","Independence Day","MW",2042 +"2042-07-07","Independence Day (Observed)","MW",2042 +"2042-10-15","Mother's Day","MW",2042 +"2042-12-25","Christmas Day","MW",2042 +"2042-12-26","Boxing Day","MW",2042 +"2043-01-01","New Year's Day","MW",2043 +"2043-01-15","John Chilembwe Day","MW",2043 +"2043-03-03","Martyrs Day","MW",2043 +"2043-03-27","Good Friday","MW",2043 +"2043-03-30","Easter Monday","MW",2043 +"2043-05-01","Labour Day","MW",2043 +"2043-05-14","Kamuzu Day","MW",2043 +"2043-07-06","Independence Day","MW",2043 +"2043-10-15","Mother's Day","MW",2043 +"2043-12-25","Christmas Day","MW",2043 +"2043-12-26","Boxing Day","MW",2043 +"2043-12-28","Boxing Day (Observed)","MW",2043 +"2044-01-01","New Year's Day","MW",2044 +"2044-01-15","John Chilembwe Day","MW",2044 +"2044-03-03","Martyrs Day","MW",2044 +"2044-04-15","Good Friday","MW",2044 +"2044-04-18","Easter Monday","MW",2044 +"2044-05-01","Labour Day","MW",2044 +"2044-05-02","Labour Day (Observed)","MW",2044 +"2044-05-14","Kamuzu Day","MW",2044 +"2044-05-16","Kamuzu Day (Observed)","MW",2044 +"2044-07-06","Independence Day","MW",2044 +"2044-10-15","Mother's Day","MW",2044 +"2044-10-17","Mother's Day (Observed)","MW",2044 +"2044-12-25","Christmas Day","MW",2044 +"2044-12-26","Boxing Day","MW",2044 +"2044-12-27","Christmas Day (Observed)","MW",2044 +"1995-01-01","New Year's Day","MX",1995 +"1995-02-05","Constitution Day","MX",1995 +"1995-03-21","Benito Juarez's birthday","MX",1995 +"1995-05-01","Labour Day","MX",1995 +"1995-09-16","Independence Day","MX",1995 +"1995-11-20","Revolution Day","MX",1995 +"1995-12-25","Christmas Day","MX",1995 +"1996-01-01","New Year's Day","MX",1996 +"1996-02-05","Constitution Day","MX",1996 +"1996-03-21","Benito Juarez's birthday","MX",1996 +"1996-05-01","Labour Day","MX",1996 +"1996-09-16","Independence Day","MX",1996 +"1996-11-20","Revolution Day","MX",1996 +"1996-12-25","Christmas Day","MX",1996 +"1997-01-01","New Year's Day","MX",1997 +"1997-02-05","Constitution Day","MX",1997 +"1997-03-21","Benito Juarez's birthday","MX",1997 +"1997-05-01","Labour Day","MX",1997 +"1997-09-16","Independence Day","MX",1997 +"1997-11-20","Revolution Day","MX",1997 +"1997-12-25","Christmas Day","MX",1997 +"1998-01-01","New Year's Day","MX",1998 +"1998-02-05","Constitution Day","MX",1998 +"1998-03-21","Benito Juarez's birthday","MX",1998 +"1998-05-01","Labour Day","MX",1998 +"1998-09-16","Independence Day","MX",1998 +"1998-11-20","Revolution Day","MX",1998 +"1998-12-25","Christmas Day","MX",1998 +"1999-01-01","New Year's Day","MX",1999 +"1999-02-05","Constitution Day","MX",1999 +"1999-03-21","Benito Juarez's birthday","MX",1999 +"1999-05-01","Labour Day","MX",1999 +"1999-09-16","Independence Day","MX",1999 +"1999-11-20","Revolution Day","MX",1999 +"1999-12-25","Christmas Day","MX",1999 +"2000-01-01","New Year's Day","MX",2000 +"2000-02-05","Constitution Day","MX",2000 +"2000-03-21","Benito Juarez's birthday","MX",2000 +"2000-05-01","Labour Day","MX",2000 +"2000-09-16","Independence Day","MX",2000 +"2000-11-20","Revolution Day","MX",2000 +"2000-12-01","Change of Federal Government","MX",2000 +"2000-12-25","Christmas Day","MX",2000 +"2001-01-01","New Year's Day","MX",2001 +"2001-02-05","Constitution Day","MX",2001 +"2001-03-21","Benito Juarez's birthday","MX",2001 +"2001-05-01","Labour Day","MX",2001 +"2001-09-16","Independence Day","MX",2001 +"2001-11-20","Revolution Day","MX",2001 +"2001-12-25","Christmas Day","MX",2001 +"2002-01-01","New Year's Day","MX",2002 +"2002-02-05","Constitution Day","MX",2002 +"2002-03-21","Benito Juarez's birthday","MX",2002 +"2002-05-01","Labour Day","MX",2002 +"2002-09-16","Independence Day","MX",2002 +"2002-11-20","Revolution Day","MX",2002 +"2002-12-25","Christmas Day","MX",2002 +"2003-01-01","New Year's Day","MX",2003 +"2003-02-05","Constitution Day","MX",2003 +"2003-03-21","Benito Juarez's birthday","MX",2003 +"2003-05-01","Labour Day","MX",2003 +"2003-09-16","Independence Day","MX",2003 +"2003-11-20","Revolution Day","MX",2003 +"2003-12-25","Christmas Day","MX",2003 +"2004-01-01","New Year's Day","MX",2004 +"2004-02-05","Constitution Day","MX",2004 +"2004-03-21","Benito Juarez's birthday","MX",2004 +"2004-05-01","Labour Day","MX",2004 +"2004-09-16","Independence Day","MX",2004 +"2004-11-20","Revolution Day","MX",2004 +"2004-12-25","Christmas Day","MX",2004 +"2005-01-01","New Year's Day","MX",2005 +"2005-02-05","Constitution Day","MX",2005 +"2005-03-21","Benito Juarez's birthday","MX",2005 +"2005-05-01","Labour Day","MX",2005 +"2005-09-16","Independence Day","MX",2005 +"2005-11-20","Revolution Day","MX",2005 +"2005-12-25","Christmas Day","MX",2005 +"2006-01-01","New Year's Day","MX",2006 +"2006-02-06","Constitution Day","MX",2006 +"2006-03-21","Benito Juarez's birthday","MX",2006 +"2006-05-01","Labour Day","MX",2006 +"2006-09-16","Independence Day","MX",2006 +"2006-11-20","Revolution Day","MX",2006 +"2006-12-01","Change of Federal Government","MX",2006 +"2006-12-25","Christmas Day","MX",2006 +"2007-01-01","New Year's Day","MX",2007 +"2007-02-05","Constitution Day","MX",2007 +"2007-03-19","Benito Juarez's birthday","MX",2007 +"2007-05-01","Labour Day","MX",2007 +"2007-09-16","Independence Day","MX",2007 +"2007-11-19","Revolution Day","MX",2007 +"2007-12-25","Christmas Day","MX",2007 +"2008-01-01","New Year's Day","MX",2008 +"2008-02-04","Constitution Day","MX",2008 +"2008-03-17","Benito Juarez's birthday","MX",2008 +"2008-05-01","Labour Day","MX",2008 +"2008-09-16","Independence Day","MX",2008 +"2008-11-17","Revolution Day","MX",2008 +"2008-12-25","Christmas Day","MX",2008 +"2009-01-01","New Year's Day","MX",2009 +"2009-02-02","Constitution Day","MX",2009 +"2009-03-16","Benito Juarez's birthday","MX",2009 +"2009-05-01","Labour Day","MX",2009 +"2009-09-16","Independence Day","MX",2009 +"2009-11-16","Revolution Day","MX",2009 +"2009-12-25","Christmas Day","MX",2009 +"2010-01-01","New Year's Day","MX",2010 +"2010-02-01","Constitution Day","MX",2010 +"2010-03-15","Benito Juarez's birthday","MX",2010 +"2010-05-01","Labour Day","MX",2010 +"2010-09-16","Independence Day","MX",2010 +"2010-11-15","Revolution Day","MX",2010 +"2010-12-25","Christmas Day","MX",2010 +"2011-01-01","New Year's Day","MX",2011 +"2011-02-07","Constitution Day","MX",2011 +"2011-03-21","Benito Juarez's birthday","MX",2011 +"2011-05-01","Labour Day","MX",2011 +"2011-09-16","Independence Day","MX",2011 +"2011-11-21","Revolution Day","MX",2011 +"2011-12-25","Christmas Day","MX",2011 +"2012-01-01","New Year's Day","MX",2012 +"2012-02-06","Constitution Day","MX",2012 +"2012-03-19","Benito Juarez's birthday","MX",2012 +"2012-05-01","Labour Day","MX",2012 +"2012-09-16","Independence Day","MX",2012 +"2012-11-19","Revolution Day","MX",2012 +"2012-12-01","Change of Federal Government","MX",2012 +"2012-12-25","Christmas Day","MX",2012 +"2013-01-01","New Year's Day","MX",2013 +"2013-02-04","Constitution Day","MX",2013 +"2013-03-18","Benito Juarez's birthday","MX",2013 +"2013-05-01","Labour Day","MX",2013 +"2013-09-16","Independence Day","MX",2013 +"2013-11-18","Revolution Day","MX",2013 +"2013-12-25","Christmas Day","MX",2013 +"2014-01-01","New Year's Day","MX",2014 +"2014-02-03","Constitution Day","MX",2014 +"2014-03-17","Benito Juarez's birthday","MX",2014 +"2014-05-01","Labour Day","MX",2014 +"2014-09-16","Independence Day","MX",2014 +"2014-11-17","Revolution Day","MX",2014 +"2014-12-25","Christmas Day","MX",2014 +"2015-01-01","New Year's Day","MX",2015 +"2015-02-02","Constitution Day","MX",2015 +"2015-03-16","Benito Juarez's birthday","MX",2015 +"2015-05-01","Labour Day","MX",2015 +"2015-09-16","Independence Day","MX",2015 +"2015-11-16","Revolution Day","MX",2015 +"2015-12-25","Christmas Day","MX",2015 +"2016-01-01","New Year's Day","MX",2016 +"2016-02-01","Constitution Day","MX",2016 +"2016-03-21","Benito Juarez's birthday","MX",2016 +"2016-05-01","Labour Day","MX",2016 +"2016-09-16","Independence Day","MX",2016 +"2016-11-21","Revolution Day","MX",2016 +"2016-12-25","Christmas Day","MX",2016 +"2017-01-01","New Year's Day","MX",2017 +"2017-02-06","Constitution Day","MX",2017 +"2017-03-20","Benito Juarez's birthday","MX",2017 +"2017-05-01","Labour Day","MX",2017 +"2017-09-16","Independence Day","MX",2017 +"2017-11-20","Revolution Day","MX",2017 +"2017-12-25","Christmas Day","MX",2017 +"2018-01-01","New Year's Day","MX",2018 +"2018-02-05","Constitution Day","MX",2018 +"2018-03-19","Benito Juarez's birthday","MX",2018 +"2018-05-01","Labour Day","MX",2018 +"2018-09-16","Independence Day","MX",2018 +"2018-11-19","Revolution Day","MX",2018 +"2018-12-01","Change of Federal Government","MX",2018 +"2018-12-25","Christmas Day","MX",2018 +"2019-01-01","New Year's Day","MX",2019 +"2019-02-04","Constitution Day","MX",2019 +"2019-03-18","Benito Juarez's birthday","MX",2019 +"2019-05-01","Labour Day","MX",2019 +"2019-09-16","Independence Day","MX",2019 +"2019-11-18","Revolution Day","MX",2019 +"2019-12-25","Christmas Day","MX",2019 +"2020-01-01","New Year's Day","MX",2020 +"2020-02-03","Constitution Day","MX",2020 +"2020-03-16","Benito Juarez's birthday","MX",2020 +"2020-05-01","Labour Day","MX",2020 +"2020-09-16","Independence Day","MX",2020 +"2020-11-16","Revolution Day","MX",2020 +"2020-12-25","Christmas Day","MX",2020 +"2021-01-01","New Year's Day","MX",2021 +"2021-02-01","Constitution Day","MX",2021 +"2021-03-15","Benito Juarez's birthday","MX",2021 +"2021-05-01","Labour Day","MX",2021 +"2021-09-16","Independence Day","MX",2021 +"2021-11-15","Revolution Day","MX",2021 +"2021-12-25","Christmas Day","MX",2021 +"2022-01-01","New Year's Day","MX",2022 +"2022-02-07","Constitution Day","MX",2022 +"2022-03-21","Benito Juarez's birthday","MX",2022 +"2022-05-01","Labour Day","MX",2022 +"2022-09-16","Independence Day","MX",2022 +"2022-11-21","Revolution Day","MX",2022 +"2022-12-25","Christmas Day","MX",2022 +"2023-01-01","New Year's Day","MX",2023 +"2023-02-06","Constitution Day","MX",2023 +"2023-03-20","Benito Juarez's birthday","MX",2023 +"2023-05-01","Labour Day","MX",2023 +"2023-09-16","Independence Day","MX",2023 +"2023-11-20","Revolution Day","MX",2023 +"2023-12-25","Christmas Day","MX",2023 +"2024-01-01","New Year's Day","MX",2024 +"2024-02-05","Constitution Day","MX",2024 +"2024-03-18","Benito Juarez's birthday","MX",2024 +"2024-05-01","Labour Day","MX",2024 +"2024-09-16","Independence Day","MX",2024 +"2024-11-18","Revolution Day","MX",2024 +"2024-12-01","Change of Federal Government","MX",2024 +"2024-12-25","Christmas Day","MX",2024 +"2025-01-01","New Year's Day","MX",2025 +"2025-02-03","Constitution Day","MX",2025 +"2025-03-17","Benito Juarez's birthday","MX",2025 +"2025-05-01","Labour Day","MX",2025 +"2025-09-16","Independence Day","MX",2025 +"2025-11-17","Revolution Day","MX",2025 +"2025-12-25","Christmas Day","MX",2025 +"2026-01-01","New Year's Day","MX",2026 +"2026-02-02","Constitution Day","MX",2026 +"2026-03-16","Benito Juarez's birthday","MX",2026 +"2026-05-01","Labour Day","MX",2026 +"2026-09-16","Independence Day","MX",2026 +"2026-11-16","Revolution Day","MX",2026 +"2026-12-25","Christmas Day","MX",2026 +"2027-01-01","New Year's Day","MX",2027 +"2027-02-01","Constitution Day","MX",2027 +"2027-03-15","Benito Juarez's birthday","MX",2027 +"2027-05-01","Labour Day","MX",2027 +"2027-09-16","Independence Day","MX",2027 +"2027-11-15","Revolution Day","MX",2027 +"2027-12-25","Christmas Day","MX",2027 +"2028-01-01","New Year's Day","MX",2028 +"2028-02-07","Constitution Day","MX",2028 +"2028-03-20","Benito Juarez's birthday","MX",2028 +"2028-05-01","Labour Day","MX",2028 +"2028-09-16","Independence Day","MX",2028 +"2028-11-20","Revolution Day","MX",2028 +"2028-12-25","Christmas Day","MX",2028 +"2029-01-01","New Year's Day","MX",2029 +"2029-02-05","Constitution Day","MX",2029 +"2029-03-19","Benito Juarez's birthday","MX",2029 +"2029-05-01","Labour Day","MX",2029 +"2029-09-16","Independence Day","MX",2029 +"2029-11-19","Revolution Day","MX",2029 +"2029-12-25","Christmas Day","MX",2029 +"2030-01-01","New Year's Day","MX",2030 +"2030-02-04","Constitution Day","MX",2030 +"2030-03-18","Benito Juarez's birthday","MX",2030 +"2030-05-01","Labour Day","MX",2030 +"2030-09-16","Independence Day","MX",2030 +"2030-11-18","Revolution Day","MX",2030 +"2030-12-01","Change of Federal Government","MX",2030 +"2030-12-25","Christmas Day","MX",2030 +"2031-01-01","New Year's Day","MX",2031 +"2031-02-03","Constitution Day","MX",2031 +"2031-03-17","Benito Juarez's birthday","MX",2031 +"2031-05-01","Labour Day","MX",2031 +"2031-09-16","Independence Day","MX",2031 +"2031-11-17","Revolution Day","MX",2031 +"2031-12-25","Christmas Day","MX",2031 +"2032-01-01","New Year's Day","MX",2032 +"2032-02-02","Constitution Day","MX",2032 +"2032-03-15","Benito Juarez's birthday","MX",2032 +"2032-05-01","Labour Day","MX",2032 +"2032-09-16","Independence Day","MX",2032 +"2032-11-15","Revolution Day","MX",2032 +"2032-12-25","Christmas Day","MX",2032 +"2033-01-01","New Year's Day","MX",2033 +"2033-02-07","Constitution Day","MX",2033 +"2033-03-21","Benito Juarez's birthday","MX",2033 +"2033-05-01","Labour Day","MX",2033 +"2033-09-16","Independence Day","MX",2033 +"2033-11-21","Revolution Day","MX",2033 +"2033-12-25","Christmas Day","MX",2033 +"2034-01-01","New Year's Day","MX",2034 +"2034-02-06","Constitution Day","MX",2034 +"2034-03-20","Benito Juarez's birthday","MX",2034 +"2034-05-01","Labour Day","MX",2034 +"2034-09-16","Independence Day","MX",2034 +"2034-11-20","Revolution Day","MX",2034 +"2034-12-25","Christmas Day","MX",2034 +"2035-01-01","New Year's Day","MX",2035 +"2035-02-05","Constitution Day","MX",2035 +"2035-03-19","Benito Juarez's birthday","MX",2035 +"2035-05-01","Labour Day","MX",2035 +"2035-09-16","Independence Day","MX",2035 +"2035-11-19","Revolution Day","MX",2035 +"2035-12-25","Christmas Day","MX",2035 +"2036-01-01","New Year's Day","MX",2036 +"2036-02-04","Constitution Day","MX",2036 +"2036-03-17","Benito Juarez's birthday","MX",2036 +"2036-05-01","Labour Day","MX",2036 +"2036-09-16","Independence Day","MX",2036 +"2036-11-17","Revolution Day","MX",2036 +"2036-12-01","Change of Federal Government","MX",2036 +"2036-12-25","Christmas Day","MX",2036 +"2037-01-01","New Year's Day","MX",2037 +"2037-02-02","Constitution Day","MX",2037 +"2037-03-16","Benito Juarez's birthday","MX",2037 +"2037-05-01","Labour Day","MX",2037 +"2037-09-16","Independence Day","MX",2037 +"2037-11-16","Revolution Day","MX",2037 +"2037-12-25","Christmas Day","MX",2037 +"2038-01-01","New Year's Day","MX",2038 +"2038-02-01","Constitution Day","MX",2038 +"2038-03-15","Benito Juarez's birthday","MX",2038 +"2038-05-01","Labour Day","MX",2038 +"2038-09-16","Independence Day","MX",2038 +"2038-11-15","Revolution Day","MX",2038 +"2038-12-25","Christmas Day","MX",2038 +"2039-01-01","New Year's Day","MX",2039 +"2039-02-07","Constitution Day","MX",2039 +"2039-03-21","Benito Juarez's birthday","MX",2039 +"2039-05-01","Labour Day","MX",2039 +"2039-09-16","Independence Day","MX",2039 +"2039-11-21","Revolution Day","MX",2039 +"2039-12-25","Christmas Day","MX",2039 +"2040-01-01","New Year's Day","MX",2040 +"2040-02-06","Constitution Day","MX",2040 +"2040-03-19","Benito Juarez's birthday","MX",2040 +"2040-05-01","Labour Day","MX",2040 +"2040-09-16","Independence Day","MX",2040 +"2040-11-19","Revolution Day","MX",2040 +"2040-12-25","Christmas Day","MX",2040 +"2041-01-01","New Year's Day","MX",2041 +"2041-02-04","Constitution Day","MX",2041 +"2041-03-18","Benito Juarez's birthday","MX",2041 +"2041-05-01","Labour Day","MX",2041 +"2041-09-16","Independence Day","MX",2041 +"2041-11-18","Revolution Day","MX",2041 +"2041-12-25","Christmas Day","MX",2041 +"2042-01-01","New Year's Day","MX",2042 +"2042-02-03","Constitution Day","MX",2042 +"2042-03-17","Benito Juarez's birthday","MX",2042 +"2042-05-01","Labour Day","MX",2042 +"2042-09-16","Independence Day","MX",2042 +"2042-11-17","Revolution Day","MX",2042 +"2042-12-01","Change of Federal Government","MX",2042 +"2042-12-25","Christmas Day","MX",2042 +"2043-01-01","New Year's Day","MX",2043 +"2043-02-02","Constitution Day","MX",2043 +"2043-03-16","Benito Juarez's birthday","MX",2043 +"2043-05-01","Labour Day","MX",2043 +"2043-09-16","Independence Day","MX",2043 +"2043-11-16","Revolution Day","MX",2043 +"2043-12-25","Christmas Day","MX",2043 +"2044-01-01","New Year's Day","MX",2044 +"2044-02-01","Constitution Day","MX",2044 +"2044-03-21","Benito Juarez's birthday","MX",2044 +"2044-05-01","Labour Day","MX",2044 +"2044-09-16","Independence Day","MX",2044 +"2044-11-21","Revolution Day","MX",2044 +"2044-12-25","Christmas Day","MX",2044 +"1995-01-31","Chinese New Year","MY",1995 +"1995-02-01","Chinese New Year Holiday","MY",1995 +"1995-03-02","Hari Raya Puasa* (*estimated)","MY",1995 +"1995-03-03","Second day of Hari Raya Puasa* (*estimated)","MY",1995 +"1995-05-01","Labour Day","MY",1995 +"1995-05-09","Hari Raya Haji* (*estimated)","MY",1995 +"1995-05-14","Vesak Day* (*estimated)","MY",1995 +"1995-05-15","Vesak Day* (*estimated) [In lieu]","MY",1995 +"1995-05-30","Awal Muharram (Hijri New Year)* (*estimated)","MY",1995 +"1995-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",1995 +"1995-08-08","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",1995 +"1995-08-31","National Day","MY",1995 +"1995-11-20","Deepavali* (*estimated)","MY",1995 +"1995-12-25","Christmas Day","MY",1995 +"1996-02-19","Chinese New Year","MY",1996 +"1996-02-19","Hari Raya Puasa* (*estimated)","MY",1996 +"1996-02-20","Chinese New Year Holiday","MY",1996 +"1996-02-20","Second day of Hari Raya Puasa* (*estimated)","MY",1996 +"1996-04-27","Hari Raya Haji* (*estimated)","MY",1996 +"1996-05-01","Labour Day","MY",1996 +"1996-05-02","Vesak Day* (*estimated)","MY",1996 +"1996-05-18","Awal Muharram (Hijri New Year)* (*estimated)","MY",1996 +"1996-06-01","Birthday of SPB Yang di-Pertuan Agong","MY",1996 +"1996-07-27","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",1996 +"1996-08-31","National Day","MY",1996 +"1996-11-09","Deepavali* (*estimated)","MY",1996 +"1996-12-25","Christmas Day","MY",1996 +"1997-02-07","Chinese New Year","MY",1997 +"1997-02-08","Chinese New Year Holiday","MY",1997 +"1997-02-08","Hari Raya Puasa* (*estimated)","MY",1997 +"1997-02-09","Second day of Hari Raya Puasa* (*estimated)","MY",1997 +"1997-02-10","Second day of Hari Raya Puasa* (*estimated) [In lieu]","MY",1997 +"1997-04-17","Hari Raya Haji* (*estimated)","MY",1997 +"1997-05-01","Labour Day","MY",1997 +"1997-05-07","Awal Muharram (Hijri New Year)* (*estimated)","MY",1997 +"1997-05-21","Vesak Day* (*estimated)","MY",1997 +"1997-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",1997 +"1997-07-16","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",1997 +"1997-08-31","National Day","MY",1997 +"1997-09-01","National Day [In lieu]","MY",1997 +"1997-10-29","Deepavali* (*estimated)","MY",1997 +"1997-12-25","Christmas Day","MY",1997 +"1998-01-28","Chinese New Year","MY",1998 +"1998-01-29","Chinese New Year Holiday","MY",1998 +"1998-01-29","Hari Raya Puasa* (*estimated)","MY",1998 +"1998-01-30","Second day of Hari Raya Puasa* (*estimated)","MY",1998 +"1998-04-07","Hari Raya Haji* (*estimated)","MY",1998 +"1998-04-27","Awal Muharram (Hijri New Year)* (*estimated)","MY",1998 +"1998-05-01","Labour Day","MY",1998 +"1998-05-10","Vesak Day* (*estimated)","MY",1998 +"1998-05-11","Vesak Day* (*estimated) [In lieu]","MY",1998 +"1998-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",1998 +"1998-07-06","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",1998 +"1998-08-31","National Day","MY",1998 +"1998-11-17","Deepavali* (*estimated)","MY",1998 +"1998-12-25","Christmas Day","MY",1998 +"1999-01-18","Hari Raya Puasa* (*estimated)","MY",1999 +"1999-01-19","Second day of Hari Raya Puasa* (*estimated)","MY",1999 +"1999-02-16","Chinese New Year","MY",1999 +"1999-02-17","Chinese New Year Holiday","MY",1999 +"1999-03-27","Hari Raya Haji* (*estimated)","MY",1999 +"1999-04-17","Awal Muharram (Hijri New Year)* (*estimated)","MY",1999 +"1999-05-01","Labour Day","MY",1999 +"1999-05-29","Vesak Day* (*estimated)","MY",1999 +"1999-06-05","Birthday of SPB Yang di-Pertuan Agong","MY",1999 +"1999-06-26","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",1999 +"1999-08-31","National Day","MY",1999 +"1999-11-06","Deepavali* (*estimated)","MY",1999 +"1999-11-29","Malaysia General Election Holiday","MY",1999 +"1999-12-25","Christmas Day","MY",1999 +"2000-01-08","Hari Raya Puasa* (*estimated)","MY",2000 +"2000-01-09","Second day of Hari Raya Puasa* (*estimated)","MY",2000 +"2000-01-10","Second day of Hari Raya Puasa* (*estimated) [In lieu]","MY",2000 +"2000-02-05","Chinese New Year","MY",2000 +"2000-02-06","Chinese New Year Holiday","MY",2000 +"2000-02-07","Chinese New Year Holiday [In lieu]","MY",2000 +"2000-03-16","Hari Raya Haji* (*estimated)","MY",2000 +"2000-04-06","Awal Muharram (Hijri New Year)* (*estimated)","MY",2000 +"2000-05-01","Labour Day","MY",2000 +"2000-05-18","Vesak Day* (*estimated)","MY",2000 +"2000-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2000 +"2000-06-14","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2000 +"2000-08-31","National Day","MY",2000 +"2000-10-25","Deepavali* (*estimated)","MY",2000 +"2000-12-25","Christmas Day","MY",2000 +"2000-12-27","Hari Raya Puasa* (*estimated)","MY",2000 +"2000-12-28","Second day of Hari Raya Puasa* (*estimated)","MY",2000 +"2001-01-24","Chinese New Year","MY",2001 +"2001-01-25","Chinese New Year Holiday","MY",2001 +"2001-03-06","Hari Raya Haji","MY",2001 +"2001-03-26","Awal Muharram (Hijri New Year)","MY",2001 +"2001-05-01","Labour Day","MY",2001 +"2001-05-07","Vesak Day","MY",2001 +"2001-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2001 +"2001-06-04","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2001 +"2001-08-31","National Day","MY",2001 +"2001-11-14","Deepavali","MY",2001 +"2001-12-17","Hari Raya Puasa","MY",2001 +"2001-12-18","Second day of Hari Raya Puasa","MY",2001 +"2001-12-25","Christmas Day","MY",2001 +"2002-02-12","Chinese New Year","MY",2002 +"2002-02-13","Chinese New Year Holiday","MY",2002 +"2002-02-23","Hari Raya Haji","MY",2002 +"2002-03-15","Awal Muharram (Hijri New Year)","MY",2002 +"2002-05-01","Labour Day","MY",2002 +"2002-05-24","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2002 +"2002-05-27","Vesak Day","MY",2002 +"2002-06-01","Birthday of SPB Yang di-Pertuan Agong","MY",2002 +"2002-08-31","National Day","MY",2002 +"2002-11-03","Deepavali","MY",2002 +"2002-11-04","Deepavali [In lieu]","MY",2002 +"2002-12-06","Hari Raya Puasa","MY",2002 +"2002-12-07","Second day of Hari Raya Puasa","MY",2002 +"2002-12-25","Christmas Day","MY",2002 +"2003-02-01","Chinese New Year","MY",2003 +"2003-02-02","Chinese New Year Holiday","MY",2003 +"2003-02-03","Chinese New Year Holiday [In lieu]","MY",2003 +"2003-02-12","Hari Raya Haji","MY",2003 +"2003-03-05","Awal Muharram (Hijri New Year)","MY",2003 +"2003-05-01","Labour Day","MY",2003 +"2003-05-14","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2003 +"2003-05-15","Vesak Day","MY",2003 +"2003-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2003 +"2003-08-31","National Day","MY",2003 +"2003-09-01","National Day [In lieu]","MY",2003 +"2003-10-23","Deepavali","MY",2003 +"2003-11-26","Hari Raya Puasa","MY",2003 +"2003-11-27","Second day of Hari Raya Puasa","MY",2003 +"2003-12-25","Christmas Day","MY",2003 +"2004-01-22","Chinese New Year","MY",2004 +"2004-01-23","Chinese New Year Holiday","MY",2004 +"2004-02-02","Hari Raya Haji","MY",2004 +"2004-02-22","Awal Muharram (Hijri New Year)","MY",2004 +"2004-05-01","Labour Day","MY",2004 +"2004-05-02","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2004 +"2004-05-03","Vesak Day","MY",2004 +"2004-05-04","Maulidur Rasul (Birthday of the Prophet Muhammad) [In lieu]","MY",2004 +"2004-06-05","Birthday of SPB Yang di-Pertuan Agong","MY",2004 +"2004-08-31","National Day","MY",2004 +"2004-11-11","Deepavali","MY",2004 +"2004-11-14","Hari Raya Puasa","MY",2004 +"2004-11-15","Second day of Hari Raya Puasa","MY",2004 +"2004-11-16","Hari Raya Puasa [In lieu]","MY",2004 +"2004-12-25","Christmas Day","MY",2004 +"2005-01-21","Hari Raya Haji","MY",2005 +"2005-02-09","Chinese New Year","MY",2005 +"2005-02-10","Awal Muharram (Hijri New Year)","MY",2005 +"2005-02-10","Chinese New Year Holiday","MY",2005 +"2005-04-21","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2005 +"2005-05-01","Labour Day","MY",2005 +"2005-05-02","Labour Day [In lieu]","MY",2005 +"2005-05-23","Vesak Day","MY",2005 +"2005-06-04","Birthday of SPB Yang di-Pertuan Agong","MY",2005 +"2005-08-31","National Day","MY",2005 +"2005-11-01","Deepavali","MY",2005 +"2005-11-03","Hari Raya Puasa","MY",2005 +"2005-11-04","Second day of Hari Raya Puasa","MY",2005 +"2005-12-25","Christmas Day","MY",2005 +"2005-12-26","Christmas Day [In lieu]","MY",2005 +"2006-01-10","Hari Raya Haji","MY",2006 +"2006-01-29","Chinese New Year","MY",2006 +"2006-01-30","Chinese New Year Holiday","MY",2006 +"2006-01-31","Awal Muharram (Hijri New Year)","MY",2006 +"2006-01-31","Chinese New Year [In lieu]","MY",2006 +"2006-04-11","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2006 +"2006-05-01","Labour Day","MY",2006 +"2006-05-12","Vesak Day","MY",2006 +"2006-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2006 +"2006-08-31","National Day","MY",2006 +"2006-10-21","Deepavali","MY",2006 +"2006-10-24","Hari Raya Puasa","MY",2006 +"2006-10-25","Second day of Hari Raya Puasa","MY",2006 +"2006-12-25","Christmas Day","MY",2006 +"2006-12-31","Hari Raya Haji","MY",2006 +"2007-01-02","Hari Raya Haji [In lieu]","MY",2007 +"2007-01-20","Awal Muharram (Hijri New Year)","MY",2007 +"2007-02-18","Chinese New Year","MY",2007 +"2007-02-19","Chinese New Year Holiday","MY",2007 +"2007-02-20","Chinese New Year [In lieu]","MY",2007 +"2007-03-31","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2007 +"2007-05-01","Labour Day","MY",2007 +"2007-05-01","Vesak Day","MY",2007 +"2007-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2007 +"2007-08-31","National Day","MY",2007 +"2007-10-13","Hari Raya Puasa","MY",2007 +"2007-10-14","Second day of Hari Raya Puasa","MY",2007 +"2007-10-15","Second day of Hari Raya Puasa [In lieu]","MY",2007 +"2007-11-08","Deepavali","MY",2007 +"2007-12-20","Hari Raya Haji","MY",2007 +"2007-12-25","Christmas Day","MY",2007 +"2008-01-10","Awal Muharram (Hijri New Year)","MY",2008 +"2008-02-07","Chinese New Year","MY",2008 +"2008-02-08","Chinese New Year Holiday","MY",2008 +"2008-03-20","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2008 +"2008-05-01","Labour Day","MY",2008 +"2008-05-19","Vesak Day","MY",2008 +"2008-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2008 +"2008-08-31","National Day","MY",2008 +"2008-09-01","National Day [In lieu]","MY",2008 +"2008-10-01","Hari Raya Puasa","MY",2008 +"2008-10-02","Second day of Hari Raya Puasa","MY",2008 +"2008-10-27","Deepavali","MY",2008 +"2008-12-09","Hari Raya Haji","MY",2008 +"2008-12-25","Christmas Day","MY",2008 +"2008-12-29","Awal Muharram (Hijri New Year)","MY",2008 +"2009-01-26","Chinese New Year","MY",2009 +"2009-01-27","Chinese New Year Holiday","MY",2009 +"2009-03-09","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2009 +"2009-05-01","Labour Day","MY",2009 +"2009-05-09","Vesak Day","MY",2009 +"2009-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",2009 +"2009-08-31","National Day","MY",2009 +"2009-09-20","Hari Raya Puasa","MY",2009 +"2009-09-21","Second day of Hari Raya Puasa","MY",2009 +"2009-09-22","Hari Raya Puasa [In lieu]","MY",2009 +"2009-10-17","Deepavali","MY",2009 +"2009-11-28","Hari Raya Haji","MY",2009 +"2009-12-18","Awal Muharram (Hijri New Year)","MY",2009 +"2009-12-25","Christmas Day","MY",2009 +"2010-02-14","Chinese New Year","MY",2010 +"2010-02-15","Chinese New Year Holiday","MY",2010 +"2010-02-16","Chinese New Year [In lieu]","MY",2010 +"2010-02-26","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2010 +"2010-05-01","Labour Day","MY",2010 +"2010-05-28","Vesak Day","MY",2010 +"2010-06-05","Birthday of SPB Yang di-Pertuan Agong","MY",2010 +"2010-08-31","National Day","MY",2010 +"2010-09-10","Hari Raya Puasa","MY",2010 +"2010-09-11","Second day of Hari Raya Puasa","MY",2010 +"2010-09-16","Malaysia Day","MY",2010 +"2010-11-05","Deepavali","MY",2010 +"2010-11-17","Hari Raya Haji","MY",2010 +"2010-12-08","Awal Muharram (Hijri New Year)","MY",2010 +"2010-12-25","Christmas Day","MY",2010 +"2011-02-03","Chinese New Year","MY",2011 +"2011-02-04","Chinese New Year Holiday","MY",2011 +"2011-02-16","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2011 +"2011-05-01","Labour Day","MY",2011 +"2011-05-02","Labour Day [In lieu]","MY",2011 +"2011-05-17","Vesak Day","MY",2011 +"2011-06-04","Birthday of SPB Yang di-Pertuan Agong","MY",2011 +"2011-08-31","Hari Raya Puasa","MY",2011 +"2011-08-31","National Day","MY",2011 +"2011-09-01","Second day of Hari Raya Puasa","MY",2011 +"2011-09-16","Malaysia Day","MY",2011 +"2011-10-26","Deepavali","MY",2011 +"2011-11-07","Hari Raya Haji","MY",2011 +"2011-11-27","Awal Muharram (Hijri New Year)","MY",2011 +"2011-12-25","Christmas Day","MY",2011 +"2011-12-26","Christmas Day [In lieu]","MY",2011 +"2012-01-23","Chinese New Year","MY",2012 +"2012-01-24","Chinese New Year Holiday","MY",2012 +"2012-02-05","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2012 +"2012-02-06","Maulidur Rasul (Birthday of the Prophet Muhammad) [In lieu]","MY",2012 +"2012-05-01","Labour Day","MY",2012 +"2012-05-05","Vesak Day","MY",2012 +"2012-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2012 +"2012-08-19","Hari Raya Puasa","MY",2012 +"2012-08-20","Second day of Hari Raya Puasa","MY",2012 +"2012-08-21","Hari Raya Puasa [In lieu]","MY",2012 +"2012-08-31","National Day","MY",2012 +"2012-09-16","Malaysia Day","MY",2012 +"2012-09-17","Malaysia Day [In lieu]","MY",2012 +"2012-10-26","Hari Raya Haji","MY",2012 +"2012-11-13","Deepavali","MY",2012 +"2012-11-15","Awal Muharram (Hijri New Year)","MY",2012 +"2012-12-25","Christmas Day","MY",2012 +"2013-01-24","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2013 +"2013-02-10","Chinese New Year","MY",2013 +"2013-02-11","Chinese New Year Holiday","MY",2013 +"2013-02-12","Chinese New Year [In lieu]","MY",2013 +"2013-05-01","Labour Day","MY",2013 +"2013-05-24","Vesak Day","MY",2013 +"2013-06-01","Birthday of SPB Yang di-Pertuan Agong","MY",2013 +"2013-08-08","Hari Raya Puasa","MY",2013 +"2013-08-09","Second day of Hari Raya Puasa","MY",2013 +"2013-08-31","National Day","MY",2013 +"2013-09-16","Malaysia Day","MY",2013 +"2013-10-15","Hari Raya Haji","MY",2013 +"2013-11-02","Deepavali","MY",2013 +"2013-11-05","Awal Muharram (Hijri New Year)","MY",2013 +"2013-12-25","Christmas Day","MY",2013 +"2014-01-14","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2014 +"2014-01-31","Chinese New Year","MY",2014 +"2014-02-01","Chinese New Year Holiday","MY",2014 +"2014-05-01","Labour Day","MY",2014 +"2014-05-13","Vesak Day","MY",2014 +"2014-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2014 +"2014-07-28","Hari Raya Puasa","MY",2014 +"2014-07-29","Second day of Hari Raya Puasa","MY",2014 +"2014-08-31","National Day","MY",2014 +"2014-09-01","National Day [In lieu]","MY",2014 +"2014-09-16","Malaysia Day","MY",2014 +"2014-10-05","Hari Raya Haji","MY",2014 +"2014-10-06","Hari Raya Haji [In lieu]","MY",2014 +"2014-10-22","Deepavali","MY",2014 +"2014-10-25","Awal Muharram (Hijri New Year)","MY",2014 +"2014-12-25","Christmas Day","MY",2014 +"2015-01-03","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2015 +"2015-02-19","Chinese New Year","MY",2015 +"2015-02-20","Chinese New Year Holiday","MY",2015 +"2015-05-01","Labour Day","MY",2015 +"2015-05-03","Vesak Day","MY",2015 +"2015-05-04","Vesak Day [In lieu]","MY",2015 +"2015-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",2015 +"2015-07-17","Hari Raya Puasa","MY",2015 +"2015-07-18","Second day of Hari Raya Puasa","MY",2015 +"2015-08-31","National Day","MY",2015 +"2015-09-16","Malaysia Day","MY",2015 +"2015-09-24","Hari Raya Haji","MY",2015 +"2015-10-14","Awal Muharram (Hijri New Year)","MY",2015 +"2015-11-10","Deepavali","MY",2015 +"2015-12-24","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2015 +"2015-12-25","Christmas Day","MY",2015 +"2016-02-08","Chinese New Year","MY",2016 +"2016-02-09","Chinese New Year Holiday","MY",2016 +"2016-05-01","Labour Day","MY",2016 +"2016-05-02","Labour Day [In lieu]","MY",2016 +"2016-05-21","Vesak Day","MY",2016 +"2016-06-04","Birthday of SPB Yang di-Pertuan Agong","MY",2016 +"2016-07-06","Hari Raya Puasa","MY",2016 +"2016-07-07","Second day of Hari Raya Puasa","MY",2016 +"2016-08-31","National Day","MY",2016 +"2016-09-12","Hari Raya Haji","MY",2016 +"2016-09-16","Malaysia Day","MY",2016 +"2016-10-02","Awal Muharram (Hijri New Year)","MY",2016 +"2016-10-29","Deepavali","MY",2016 +"2016-12-12","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2016 +"2016-12-25","Christmas Day","MY",2016 +"2016-12-26","Christmas Day [In lieu]","MY",2016 +"2017-01-28","Chinese New Year","MY",2017 +"2017-01-29","Chinese New Year Holiday","MY",2017 +"2017-01-30","Chinese New Year Holiday [In lieu]","MY",2017 +"2017-05-01","Labour Day","MY",2017 +"2017-05-10","Vesak Day","MY",2017 +"2017-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2017 +"2017-06-25","Hari Raya Puasa","MY",2017 +"2017-06-26","Second day of Hari Raya Puasa","MY",2017 +"2017-06-27","Hari Raya Puasa [In lieu]","MY",2017 +"2017-08-31","National Day","MY",2017 +"2017-09-01","Hari Raya Haji","MY",2017 +"2017-09-16","Malaysia Day","MY",2017 +"2017-09-22","Awal Muharram (Hijri New Year)","MY",2017 +"2017-10-18","Deepavali","MY",2017 +"2017-12-01","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2017 +"2017-12-25","Christmas Day","MY",2017 +"2018-02-16","Chinese New Year","MY",2018 +"2018-02-17","Chinese New Year Holiday","MY",2018 +"2018-05-01","Labour Day","MY",2018 +"2018-05-09","Malaysia General Election Holiday","MY",2018 +"2018-05-29","Vesak Day","MY",2018 +"2018-06-15","Hari Raya Puasa","MY",2018 +"2018-06-16","Second day of Hari Raya Puasa","MY",2018 +"2018-08-22","Hari Raya Haji","MY",2018 +"2018-08-31","National Day","MY",2018 +"2018-09-09","Birthday of SPB Yang di-Pertuan Agong","MY",2018 +"2018-09-10","Birthday of SPB Yang di-Pertuan Agong [In lieu]","MY",2018 +"2018-09-11","Awal Muharram (Hijri New Year)","MY",2018 +"2018-09-16","Malaysia Day","MY",2018 +"2018-09-17","Malaysia Day [In lieu]","MY",2018 +"2018-11-06","Deepavali","MY",2018 +"2018-11-20","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2018 +"2018-12-25","Christmas Day","MY",2018 +"2019-02-05","Chinese New Year","MY",2019 +"2019-02-06","Chinese New Year Holiday","MY",2019 +"2019-05-01","Labour Day","MY",2019 +"2019-05-19","Vesak Day","MY",2019 +"2019-05-20","Vesak Day [In lieu]","MY",2019 +"2019-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2019 +"2019-06-05","Hari Raya Puasa","MY",2019 +"2019-06-06","Second day of Hari Raya Puasa","MY",2019 +"2019-07-30","Installation of New King","MY",2019 +"2019-08-11","Hari Raya Haji","MY",2019 +"2019-08-12","Hari Raya Haji [In lieu]","MY",2019 +"2019-08-31","National Day","MY",2019 +"2019-09-01","Awal Muharram (Hijri New Year)","MY",2019 +"2019-09-16","Malaysia Day","MY",2019 +"2019-10-27","Deepavali","MY",2019 +"2019-10-28","Deepavali [In lieu]","MY",2019 +"2019-11-09","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2019 +"2019-12-25","Christmas Day","MY",2019 +"2020-01-25","Chinese New Year","MY",2020 +"2020-01-26","Chinese New Year Holiday","MY",2020 +"2020-01-27","Chinese New Year Holiday [In lieu]","MY",2020 +"2020-05-01","Labour Day","MY",2020 +"2020-05-07","Vesak Day","MY",2020 +"2020-05-24","Hari Raya Puasa","MY",2020 +"2020-05-25","Second day of Hari Raya Puasa","MY",2020 +"2020-05-26","Hari Raya Puasa [In lieu]","MY",2020 +"2020-06-08","Birthday of SPB Yang di-Pertuan Agong","MY",2020 +"2020-07-31","Hari Raya Haji","MY",2020 +"2020-08-20","Awal Muharram (Hijri New Year)","MY",2020 +"2020-08-31","National Day","MY",2020 +"2020-09-16","Malaysia Day","MY",2020 +"2020-10-29","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2020 +"2020-11-14","Deepavali","MY",2020 +"2020-12-25","Christmas Day","MY",2020 +"2021-02-12","Chinese New Year","MY",2021 +"2021-02-13","Chinese New Year Holiday","MY",2021 +"2021-05-01","Labour Day","MY",2021 +"2021-05-13","Hari Raya Puasa","MY",2021 +"2021-05-14","Second day of Hari Raya Puasa","MY",2021 +"2021-05-26","Vesak Day","MY",2021 +"2021-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2021 +"2021-07-20","Hari Raya Haji","MY",2021 +"2021-08-10","Awal Muharram (Hijri New Year)","MY",2021 +"2021-08-31","National Day","MY",2021 +"2021-09-16","Malaysia Day","MY",2021 +"2021-10-19","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2021 +"2021-11-04","Deepavali","MY",2021 +"2021-12-25","Christmas Day","MY",2021 +"2022-02-01","Chinese New Year","MY",2022 +"2022-02-02","Chinese New Year Holiday","MY",2022 +"2022-05-01","Labour Day","MY",2022 +"2022-05-02","Hari Raya Puasa","MY",2022 +"2022-05-03","Second day of Hari Raya Puasa","MY",2022 +"2022-05-04","Labour Day [In lieu]","MY",2022 +"2022-05-15","Vesak Day","MY",2022 +"2022-05-16","Vesak Day [In lieu]","MY",2022 +"2022-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",2022 +"2022-07-10","Hari Raya Haji","MY",2022 +"2022-07-11","Hari Raya Haji [In lieu]","MY",2022 +"2022-07-30","Awal Muharram (Hijri New Year)","MY",2022 +"2022-08-31","National Day","MY",2022 +"2022-09-16","Malaysia Day","MY",2022 +"2022-10-10","Maulidur Rasul (Birthday of the Prophet Muhammad)","MY",2022 +"2022-10-24","Deepavali","MY",2022 +"2022-12-25","Christmas Day","MY",2022 +"2022-12-26","Christmas Day [In lieu]","MY",2022 +"2023-01-22","Chinese New Year","MY",2023 +"2023-01-23","Chinese New Year Holiday","MY",2023 +"2023-01-24","Chinese New Year [In lieu]","MY",2023 +"2023-04-21","Hari Raya Puasa* (*estimated)","MY",2023 +"2023-04-22","Second day of Hari Raya Puasa* (*estimated)","MY",2023 +"2023-05-01","Labour Day","MY",2023 +"2023-05-04","Vesak Day* (*estimated)","MY",2023 +"2023-06-05","Birthday of SPB Yang di-Pertuan Agong","MY",2023 +"2023-06-28","Hari Raya Haji* (*estimated)","MY",2023 +"2023-07-19","Awal Muharram (Hijri New Year)* (*estimated)","MY",2023 +"2023-08-31","National Day","MY",2023 +"2023-09-16","Malaysia Day","MY",2023 +"2023-09-27","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2023 +"2023-11-11","Deepavali* (*estimated)","MY",2023 +"2023-12-25","Christmas Day","MY",2023 +"2024-02-10","Chinese New Year","MY",2024 +"2024-02-11","Chinese New Year Holiday","MY",2024 +"2024-02-12","Chinese New Year Holiday [In lieu]","MY",2024 +"2024-04-10","Hari Raya Puasa* (*estimated)","MY",2024 +"2024-04-11","Second day of Hari Raya Puasa* (*estimated)","MY",2024 +"2024-05-01","Labour Day","MY",2024 +"2024-05-22","Vesak Day* (*estimated)","MY",2024 +"2024-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2024 +"2024-06-16","Hari Raya Haji* (*estimated)","MY",2024 +"2024-06-17","Hari Raya Haji* (*estimated) [In lieu]","MY",2024 +"2024-07-07","Awal Muharram (Hijri New Year)* (*estimated)","MY",2024 +"2024-08-31","National Day","MY",2024 +"2024-09-15","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2024 +"2024-09-16","Malaysia Day","MY",2024 +"2024-09-17","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated) [In lieu]","MY",2024 +"2024-10-30","Deepavali* (*estimated)","MY",2024 +"2024-12-25","Christmas Day","MY",2024 +"2025-01-29","Chinese New Year","MY",2025 +"2025-01-30","Chinese New Year Holiday","MY",2025 +"2025-03-30","Hari Raya Puasa* (*estimated)","MY",2025 +"2025-03-31","Second day of Hari Raya Puasa* (*estimated)","MY",2025 +"2025-04-01","Hari Raya Puasa* (*estimated) [In lieu]","MY",2025 +"2025-05-01","Labour Day","MY",2025 +"2025-05-11","Vesak Day* (*estimated)","MY",2025 +"2025-05-12","Vesak Day* (*estimated) [In lieu]","MY",2025 +"2025-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2025 +"2025-06-06","Hari Raya Haji* (*estimated)","MY",2025 +"2025-06-26","Awal Muharram (Hijri New Year)* (*estimated)","MY",2025 +"2025-08-31","National Day","MY",2025 +"2025-09-01","National Day [In lieu]","MY",2025 +"2025-09-04","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2025 +"2025-09-16","Malaysia Day","MY",2025 +"2025-11-18","Deepavali* (*estimated)","MY",2025 +"2025-12-25","Christmas Day","MY",2025 +"2026-02-17","Chinese New Year","MY",2026 +"2026-02-18","Chinese New Year Holiday","MY",2026 +"2026-03-20","Hari Raya Puasa* (*estimated)","MY",2026 +"2026-03-21","Second day of Hari Raya Puasa* (*estimated)","MY",2026 +"2026-05-01","Labour Day","MY",2026 +"2026-05-01","Vesak Day* (*estimated)","MY",2026 +"2026-05-27","Hari Raya Haji* (*estimated)","MY",2026 +"2026-06-01","Birthday of SPB Yang di-Pertuan Agong","MY",2026 +"2026-06-16","Awal Muharram (Hijri New Year)* (*estimated)","MY",2026 +"2026-08-25","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2026 +"2026-08-31","National Day","MY",2026 +"2026-09-16","Malaysia Day","MY",2026 +"2026-11-07","Deepavali* (*estimated)","MY",2026 +"2026-12-25","Christmas Day","MY",2026 +"2027-02-06","Chinese New Year","MY",2027 +"2027-02-07","Chinese New Year Holiday","MY",2027 +"2027-02-08","Chinese New Year Holiday [In lieu]","MY",2027 +"2027-03-09","Hari Raya Puasa* (*estimated)","MY",2027 +"2027-03-10","Second day of Hari Raya Puasa* (*estimated)","MY",2027 +"2027-05-01","Labour Day","MY",2027 +"2027-05-16","Hari Raya Haji* (*estimated)","MY",2027 +"2027-05-17","Hari Raya Haji* (*estimated) [In lieu]","MY",2027 +"2027-05-20","Vesak Day* (*estimated)","MY",2027 +"2027-06-06","Awal Muharram (Hijri New Year)* (*estimated)","MY",2027 +"2027-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2027 +"2027-08-14","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2027 +"2027-08-31","National Day","MY",2027 +"2027-09-16","Malaysia Day","MY",2027 +"2027-10-27","Deepavali* (*estimated)","MY",2027 +"2027-12-25","Christmas Day","MY",2027 +"2028-01-26","Chinese New Year","MY",2028 +"2028-01-27","Chinese New Year Holiday","MY",2028 +"2028-02-26","Hari Raya Puasa* (*estimated)","MY",2028 +"2028-02-27","Second day of Hari Raya Puasa* (*estimated)","MY",2028 +"2028-02-28","Second day of Hari Raya Puasa* (*estimated) [In lieu]","MY",2028 +"2028-05-01","Labour Day","MY",2028 +"2028-05-05","Hari Raya Haji* (*estimated)","MY",2028 +"2028-05-09","Vesak Day* (*estimated)","MY",2028 +"2028-05-25","Awal Muharram (Hijri New Year)* (*estimated)","MY",2028 +"2028-06-05","Birthday of SPB Yang di-Pertuan Agong","MY",2028 +"2028-08-03","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2028 +"2028-08-31","National Day","MY",2028 +"2028-09-16","Malaysia Day","MY",2028 +"2028-11-14","Deepavali* (*estimated)","MY",2028 +"2028-12-25","Christmas Day","MY",2028 +"2029-02-13","Chinese New Year","MY",2029 +"2029-02-14","Chinese New Year Holiday","MY",2029 +"2029-02-14","Hari Raya Puasa* (*estimated)","MY",2029 +"2029-02-15","Second day of Hari Raya Puasa* (*estimated)","MY",2029 +"2029-04-24","Hari Raya Haji* (*estimated)","MY",2029 +"2029-05-01","Labour Day","MY",2029 +"2029-05-14","Awal Muharram (Hijri New Year)* (*estimated)","MY",2029 +"2029-05-27","Vesak Day* (*estimated)","MY",2029 +"2029-05-28","Vesak Day* (*estimated) [In lieu]","MY",2029 +"2029-06-04","Birthday of SPB Yang di-Pertuan Agong","MY",2029 +"2029-07-24","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2029 +"2029-08-31","National Day","MY",2029 +"2029-09-16","Malaysia Day","MY",2029 +"2029-09-17","Malaysia Day [In lieu]","MY",2029 +"2029-11-04","Deepavali* (*estimated)","MY",2029 +"2029-11-05","Deepavali* (*estimated) [In lieu]","MY",2029 +"2029-12-25","Christmas Day","MY",2029 +"2030-02-03","Chinese New Year","MY",2030 +"2030-02-04","Chinese New Year Holiday","MY",2030 +"2030-02-04","Hari Raya Puasa* (*estimated)","MY",2030 +"2030-02-05","Second day of Hari Raya Puasa* (*estimated)","MY",2030 +"2030-02-06","Chinese New Year [In lieu]","MY",2030 +"2030-04-13","Hari Raya Haji* (*estimated)","MY",2030 +"2030-05-01","Labour Day","MY",2030 +"2030-05-03","Awal Muharram (Hijri New Year)* (*estimated)","MY",2030 +"2030-05-16","Vesak Day* (*estimated)","MY",2030 +"2030-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2030 +"2030-07-13","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2030 +"2030-08-31","National Day","MY",2030 +"2030-09-16","Malaysia Day","MY",2030 +"2030-10-25","Deepavali* (*estimated)","MY",2030 +"2030-12-25","Christmas Day","MY",2030 +"2031-01-23","Chinese New Year","MY",2031 +"2031-01-24","Chinese New Year Holiday","MY",2031 +"2031-01-24","Hari Raya Puasa* (*estimated)","MY",2031 +"2031-01-25","Second day of Hari Raya Puasa* (*estimated)","MY",2031 +"2031-04-02","Hari Raya Haji* (*estimated)","MY",2031 +"2031-04-23","Awal Muharram (Hijri New Year)* (*estimated)","MY",2031 +"2031-05-01","Labour Day","MY",2031 +"2031-05-06","Vesak Day* (*estimated)","MY",2031 +"2031-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2031 +"2031-07-02","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2031 +"2031-08-31","National Day","MY",2031 +"2031-09-01","National Day [In lieu]","MY",2031 +"2031-09-16","Malaysia Day","MY",2031 +"2031-11-13","Deepavali* (*estimated)","MY",2031 +"2031-12-25","Christmas Day","MY",2031 +"2032-01-14","Hari Raya Puasa* (*estimated)","MY",2032 +"2032-01-15","Second day of Hari Raya Puasa* (*estimated)","MY",2032 +"2032-02-11","Chinese New Year","MY",2032 +"2032-02-12","Chinese New Year Holiday","MY",2032 +"2032-03-22","Hari Raya Haji* (*estimated)","MY",2032 +"2032-04-11","Awal Muharram (Hijri New Year)* (*estimated)","MY",2032 +"2032-05-01","Labour Day","MY",2032 +"2032-05-23","Vesak Day* (*estimated)","MY",2032 +"2032-05-24","Vesak Day* (*estimated) [In lieu]","MY",2032 +"2032-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2032 +"2032-06-20","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2032 +"2032-06-21","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated) [In lieu]","MY",2032 +"2032-08-31","National Day","MY",2032 +"2032-09-16","Malaysia Day","MY",2032 +"2032-11-01","Deepavali* (*estimated)","MY",2032 +"2032-12-25","Christmas Day","MY",2032 +"2033-01-02","Hari Raya Puasa* (*estimated)","MY",2033 +"2033-01-03","Second day of Hari Raya Puasa* (*estimated)","MY",2033 +"2033-01-04","Hari Raya Puasa* (*estimated) [In lieu]","MY",2033 +"2033-01-31","Chinese New Year","MY",2033 +"2033-02-01","Chinese New Year Holiday","MY",2033 +"2033-03-11","Hari Raya Haji* (*estimated)","MY",2033 +"2033-04-01","Awal Muharram (Hijri New Year)* (*estimated)","MY",2033 +"2033-05-01","Labour Day","MY",2033 +"2033-05-02","Labour Day [In lieu]","MY",2033 +"2033-05-13","Vesak Day* (*estimated)","MY",2033 +"2033-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",2033 +"2033-06-09","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2033 +"2033-08-31","National Day","MY",2033 +"2033-09-16","Malaysia Day","MY",2033 +"2033-10-21","Deepavali* (*estimated)","MY",2033 +"2033-12-23","Hari Raya Puasa* (*estimated)","MY",2033 +"2033-12-24","Second day of Hari Raya Puasa* (*estimated)","MY",2033 +"2033-12-25","Christmas Day","MY",2033 +"2033-12-26","Christmas Day [In lieu]","MY",2033 +"2034-02-19","Chinese New Year","MY",2034 +"2034-02-20","Chinese New Year Holiday","MY",2034 +"2034-02-21","Chinese New Year [In lieu]","MY",2034 +"2034-03-01","Hari Raya Haji* (*estimated)","MY",2034 +"2034-03-21","Awal Muharram (Hijri New Year)* (*estimated)","MY",2034 +"2034-05-01","Labour Day","MY",2034 +"2034-05-03","Vesak Day* (*estimated)","MY",2034 +"2034-05-30","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2034 +"2034-06-05","Birthday of SPB Yang di-Pertuan Agong","MY",2034 +"2034-08-31","National Day","MY",2034 +"2034-09-16","Malaysia Day","MY",2034 +"2034-11-09","Deepavali* (*estimated)","MY",2034 +"2034-12-12","Hari Raya Puasa* (*estimated)","MY",2034 +"2034-12-13","Second day of Hari Raya Puasa* (*estimated)","MY",2034 +"2034-12-25","Christmas Day","MY",2034 +"2035-02-08","Chinese New Year","MY",2035 +"2035-02-09","Chinese New Year Holiday","MY",2035 +"2035-02-18","Hari Raya Haji* (*estimated)","MY",2035 +"2035-02-19","Hari Raya Haji* (*estimated) [In lieu]","MY",2035 +"2035-03-11","Awal Muharram (Hijri New Year)* (*estimated)","MY",2035 +"2035-05-01","Labour Day","MY",2035 +"2035-05-20","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2035 +"2035-05-21","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated) [In lieu]","MY",2035 +"2035-05-22","Vesak Day* (*estimated)","MY",2035 +"2035-06-04","Birthday of SPB Yang di-Pertuan Agong","MY",2035 +"2035-08-31","National Day","MY",2035 +"2035-09-16","Malaysia Day","MY",2035 +"2035-09-17","Malaysia Day [In lieu]","MY",2035 +"2035-10-29","Deepavali* (*estimated)","MY",2035 +"2035-12-01","Hari Raya Puasa* (*estimated)","MY",2035 +"2035-12-02","Second day of Hari Raya Puasa* (*estimated)","MY",2035 +"2035-12-03","Second day of Hari Raya Puasa* (*estimated) [In lieu]","MY",2035 +"2035-12-25","Christmas Day","MY",2035 +"2036-01-28","Chinese New Year","MY",2036 +"2036-01-29","Chinese New Year Holiday","MY",2036 +"2036-02-07","Hari Raya Haji* (*estimated)","MY",2036 +"2036-02-28","Awal Muharram (Hijri New Year)* (*estimated)","MY",2036 +"2036-05-01","Labour Day","MY",2036 +"2036-05-08","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2036 +"2036-05-10","Vesak Day* (*estimated)","MY",2036 +"2036-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2036 +"2036-08-31","National Day","MY",2036 +"2036-09-01","National Day [In lieu]","MY",2036 +"2036-09-16","Malaysia Day","MY",2036 +"2036-11-16","Deepavali* (*estimated)","MY",2036 +"2036-11-17","Deepavali* (*estimated) [In lieu]","MY",2036 +"2036-11-19","Hari Raya Puasa* (*estimated)","MY",2036 +"2036-11-20","Second day of Hari Raya Puasa* (*estimated)","MY",2036 +"2036-12-25","Christmas Day","MY",2036 +"2037-01-26","Hari Raya Haji* (*estimated)","MY",2037 +"2037-02-15","Chinese New Year","MY",2037 +"2037-02-16","Awal Muharram (Hijri New Year)* (*estimated)","MY",2037 +"2037-02-16","Chinese New Year Holiday","MY",2037 +"2037-02-17","Chinese New Year [In lieu]","MY",2037 +"2037-04-28","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2037 +"2037-05-01","Labour Day","MY",2037 +"2037-05-29","Vesak Day* (*estimated)","MY",2037 +"2037-06-01","Birthday of SPB Yang di-Pertuan Agong","MY",2037 +"2037-08-31","National Day","MY",2037 +"2037-09-16","Malaysia Day","MY",2037 +"2037-11-05","Deepavali* (*estimated)","MY",2037 +"2037-11-08","Hari Raya Puasa* (*estimated)","MY",2037 +"2037-11-09","Second day of Hari Raya Puasa* (*estimated)","MY",2037 +"2037-11-10","Hari Raya Puasa* (*estimated) [In lieu]","MY",2037 +"2037-12-25","Christmas Day","MY",2037 +"2038-01-16","Hari Raya Haji* (*estimated)","MY",2038 +"2038-02-04","Chinese New Year","MY",2038 +"2038-02-05","Awal Muharram (Hijri New Year)* (*estimated)","MY",2038 +"2038-02-05","Chinese New Year Holiday","MY",2038 +"2038-04-17","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2038 +"2038-05-01","Labour Day","MY",2038 +"2038-05-18","Vesak Day* (*estimated)","MY",2038 +"2038-06-07","Birthday of SPB Yang di-Pertuan Agong","MY",2038 +"2038-08-31","National Day","MY",2038 +"2038-09-16","Malaysia Day","MY",2038 +"2038-10-26","Deepavali* (*estimated)","MY",2038 +"2038-10-29","Hari Raya Puasa* (*estimated)","MY",2038 +"2038-10-30","Second day of Hari Raya Puasa* (*estimated)","MY",2038 +"2038-12-25","Christmas Day","MY",2038 +"2039-01-05","Hari Raya Haji* (*estimated)","MY",2039 +"2039-01-24","Chinese New Year","MY",2039 +"2039-01-25","Chinese New Year Holiday","MY",2039 +"2039-01-26","Awal Muharram (Hijri New Year)* (*estimated)","MY",2039 +"2039-04-06","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2039 +"2039-05-01","Labour Day","MY",2039 +"2039-05-02","Labour Day [In lieu]","MY",2039 +"2039-05-07","Vesak Day* (*estimated)","MY",2039 +"2039-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",2039 +"2039-08-31","National Day","MY",2039 +"2039-09-16","Malaysia Day","MY",2039 +"2039-10-19","Hari Raya Puasa* (*estimated)","MY",2039 +"2039-10-20","Second day of Hari Raya Puasa* (*estimated)","MY",2039 +"2039-11-14","Deepavali* (*estimated)","MY",2039 +"2039-12-25","Christmas Day","MY",2039 +"2039-12-26","Hari Raya Haji* (*estimated)","MY",2039 +"2039-12-27","Christmas Day [In lieu]","MY",2039 +"2040-01-15","Awal Muharram (Hijri New Year)* (*estimated)","MY",2040 +"2040-02-12","Chinese New Year","MY",2040 +"2040-02-13","Chinese New Year Holiday","MY",2040 +"2040-02-14","Chinese New Year [In lieu]","MY",2040 +"2040-03-25","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2040 +"2040-03-26","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated) [In lieu]","MY",2040 +"2040-05-01","Labour Day","MY",2040 +"2040-05-25","Vesak Day* (*estimated)","MY",2040 +"2040-06-04","Birthday of SPB Yang di-Pertuan Agong","MY",2040 +"2040-08-31","National Day","MY",2040 +"2040-09-16","Malaysia Day","MY",2040 +"2040-09-17","Malaysia Day [In lieu]","MY",2040 +"2040-10-07","Hari Raya Puasa* (*estimated)","MY",2040 +"2040-10-08","Second day of Hari Raya Puasa* (*estimated)","MY",2040 +"2040-10-09","Hari Raya Puasa* (*estimated) [In lieu]","MY",2040 +"2040-11-03","Deepavali* (*estimated)","MY",2040 +"2040-12-14","Hari Raya Haji* (*estimated)","MY",2040 +"2040-12-25","Christmas Day","MY",2040 +"2041-01-04","Awal Muharram (Hijri New Year)* (*estimated)","MY",2041 +"2041-02-01","Chinese New Year","MY",2041 +"2041-02-02","Chinese New Year Holiday","MY",2041 +"2041-03-15","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2041 +"2041-05-01","Labour Day","MY",2041 +"2041-05-14","Vesak Day* (*estimated)","MY",2041 +"2041-06-03","Birthday of SPB Yang di-Pertuan Agong","MY",2041 +"2041-08-31","National Day","MY",2041 +"2041-09-16","Malaysia Day","MY",2041 +"2041-09-26","Hari Raya Puasa* (*estimated)","MY",2041 +"2041-09-27","Second day of Hari Raya Puasa* (*estimated)","MY",2041 +"2041-10-23","Deepavali* (*estimated)","MY",2041 +"2041-12-04","Hari Raya Haji* (*estimated)","MY",2041 +"2041-12-24","Awal Muharram (Hijri New Year)* (*estimated)","MY",2041 +"2041-12-25","Christmas Day","MY",2041 +"2042-01-22","Chinese New Year","MY",2042 +"2042-01-23","Chinese New Year Holiday","MY",2042 +"2042-03-04","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2042 +"2042-05-01","Labour Day","MY",2042 +"2042-05-04","Vesak Day* (*estimated)","MY",2042 +"2042-05-05","Vesak Day* (*estimated) [In lieu]","MY",2042 +"2042-06-02","Birthday of SPB Yang di-Pertuan Agong","MY",2042 +"2042-08-31","National Day","MY",2042 +"2042-09-01","National Day [In lieu]","MY",2042 +"2042-09-15","Hari Raya Puasa* (*estimated)","MY",2042 +"2042-09-16","Malaysia Day","MY",2042 +"2042-09-16","Second day of Hari Raya Puasa* (*estimated)","MY",2042 +"2042-11-11","Deepavali* (*estimated)","MY",2042 +"2042-11-23","Hari Raya Haji* (*estimated)","MY",2042 +"2042-11-24","Hari Raya Haji* (*estimated) [In lieu]","MY",2042 +"2042-12-14","Awal Muharram (Hijri New Year)* (*estimated)","MY",2042 +"2042-12-25","Christmas Day","MY",2042 +"2043-02-10","Chinese New Year","MY",2043 +"2043-02-11","Chinese New Year Holiday","MY",2043 +"2043-02-22","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2043 +"2043-02-23","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated) [In lieu]","MY",2043 +"2043-05-01","Labour Day","MY",2043 +"2043-05-23","Vesak Day* (*estimated)","MY",2043 +"2043-06-01","Birthday of SPB Yang di-Pertuan Agong","MY",2043 +"2043-08-31","National Day","MY",2043 +"2043-09-04","Hari Raya Puasa* (*estimated)","MY",2043 +"2043-09-05","Second day of Hari Raya Puasa* (*estimated)","MY",2043 +"2043-09-16","Malaysia Day","MY",2043 +"2043-10-31","Deepavali* (*estimated)","MY",2043 +"2043-11-12","Hari Raya Haji* (*estimated)","MY",2043 +"2043-12-03","Awal Muharram (Hijri New Year)* (*estimated)","MY",2043 +"2043-12-25","Christmas Day","MY",2043 +"2044-01-30","Chinese New Year","MY",2044 +"2044-01-31","Chinese New Year Holiday","MY",2044 +"2044-02-01","Chinese New Year Holiday [In lieu]","MY",2044 +"2044-02-11","Maulidur Rasul (Birthday of the Prophet Muhammad)* (*estimated)","MY",2044 +"2044-05-01","Labour Day","MY",2044 +"2044-05-02","Labour Day [In lieu]","MY",2044 +"2044-05-12","Vesak Day* (*estimated)","MY",2044 +"2044-06-06","Birthday of SPB Yang di-Pertuan Agong","MY",2044 +"2044-08-24","Hari Raya Puasa* (*estimated)","MY",2044 +"2044-08-25","Second day of Hari Raya Puasa* (*estimated)","MY",2044 +"2044-08-31","National Day","MY",2044 +"2044-09-16","Malaysia Day","MY",2044 +"2044-10-31","Hari Raya Haji* (*estimated)","MY",2044 +"2044-11-17","Deepavali* (*estimated)","MY",2044 +"2044-11-21","Awal Muharram (Hijri New Year)* (*estimated)","MY",2044 +"2044-12-25","Christmas Day","MY",2044 +"2044-12-26","Christmas Day [In lieu]","MY",2044 +"1995-01-01","Ano novo","MZ",1995 +"1995-01-02","Ano novo (PONTE)","MZ",1995 +"1995-02-03","Dia dos Herois Mocambicanos","MZ",1995 +"1995-02-28","Carnaval","MZ",1995 +"1995-04-07","Dia da Mulher Mocambicana","MZ",1995 +"1995-04-14","Sexta-feira Santa","MZ",1995 +"1995-05-01","Dia Mundial do Trabalho","MZ",1995 +"1995-06-25","Dia da Independencia Nacional","MZ",1995 +"1995-06-26","Dia da Independencia Nacional (PONTE)","MZ",1995 +"1995-09-07","Dia da Vitoria","MZ",1995 +"1995-09-25","Dia das Forcas Armadas","MZ",1995 +"1995-10-04","Dia da Paz e Reconciliacao","MZ",1995 +"1995-12-25","Dia de Natal e da Familia","MZ",1995 +"1996-01-01","Ano novo","MZ",1996 +"1996-02-03","Dia dos Herois Mocambicanos","MZ",1996 +"1996-02-20","Carnaval","MZ",1996 +"1996-04-05","Sexta-feira Santa","MZ",1996 +"1996-04-07","Dia da Mulher Mocambicana","MZ",1996 +"1996-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",1996 +"1996-05-01","Dia Mundial do Trabalho","MZ",1996 +"1996-06-25","Dia da Independencia Nacional","MZ",1996 +"1996-09-07","Dia da Vitoria","MZ",1996 +"1996-09-25","Dia das Forcas Armadas","MZ",1996 +"1996-10-04","Dia da Paz e Reconciliacao","MZ",1996 +"1996-12-25","Dia de Natal e da Familia","MZ",1996 +"1997-01-01","Ano novo","MZ",1997 +"1997-02-03","Dia dos Herois Mocambicanos","MZ",1997 +"1997-02-11","Carnaval","MZ",1997 +"1997-03-28","Sexta-feira Santa","MZ",1997 +"1997-04-07","Dia da Mulher Mocambicana","MZ",1997 +"1997-05-01","Dia Mundial do Trabalho","MZ",1997 +"1997-06-25","Dia da Independencia Nacional","MZ",1997 +"1997-09-07","Dia da Vitoria","MZ",1997 +"1997-09-08","Dia da Vitoria (PONTE)","MZ",1997 +"1997-09-25","Dia das Forcas Armadas","MZ",1997 +"1997-10-04","Dia da Paz e Reconciliacao","MZ",1997 +"1997-12-25","Dia de Natal e da Familia","MZ",1997 +"1998-01-01","Ano novo","MZ",1998 +"1998-02-03","Dia dos Herois Mocambicanos","MZ",1998 +"1998-02-24","Carnaval","MZ",1998 +"1998-04-07","Dia da Mulher Mocambicana","MZ",1998 +"1998-04-10","Sexta-feira Santa","MZ",1998 +"1998-05-01","Dia Mundial do Trabalho","MZ",1998 +"1998-06-25","Dia da Independencia Nacional","MZ",1998 +"1998-09-07","Dia da Vitoria","MZ",1998 +"1998-09-25","Dia das Forcas Armadas","MZ",1998 +"1998-10-04","Dia da Paz e Reconciliacao","MZ",1998 +"1998-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",1998 +"1998-12-25","Dia de Natal e da Familia","MZ",1998 +"1999-01-01","Ano novo","MZ",1999 +"1999-02-03","Dia dos Herois Mocambicanos","MZ",1999 +"1999-02-16","Carnaval","MZ",1999 +"1999-04-02","Sexta-feira Santa","MZ",1999 +"1999-04-07","Dia da Mulher Mocambicana","MZ",1999 +"1999-05-01","Dia Mundial do Trabalho","MZ",1999 +"1999-06-25","Dia da Independencia Nacional","MZ",1999 +"1999-09-07","Dia da Vitoria","MZ",1999 +"1999-09-25","Dia das Forcas Armadas","MZ",1999 +"1999-10-04","Dia da Paz e Reconciliacao","MZ",1999 +"1999-12-25","Dia de Natal e da Familia","MZ",1999 +"2000-01-01","Ano novo","MZ",2000 +"2000-02-03","Dia dos Herois Mocambicanos","MZ",2000 +"2000-03-07","Carnaval","MZ",2000 +"2000-04-07","Dia da Mulher Mocambicana","MZ",2000 +"2000-04-21","Sexta-feira Santa","MZ",2000 +"2000-05-01","Dia Mundial do Trabalho","MZ",2000 +"2000-06-25","Dia da Independencia Nacional","MZ",2000 +"2000-06-26","Dia da Independencia Nacional (PONTE)","MZ",2000 +"2000-09-07","Dia da Vitoria","MZ",2000 +"2000-09-25","Dia das Forcas Armadas","MZ",2000 +"2000-10-04","Dia da Paz e Reconciliacao","MZ",2000 +"2000-12-25","Dia de Natal e da Familia","MZ",2000 +"2001-01-01","Ano novo","MZ",2001 +"2001-02-03","Dia dos Herois Mocambicanos","MZ",2001 +"2001-02-27","Carnaval","MZ",2001 +"2001-04-07","Dia da Mulher Mocambicana","MZ",2001 +"2001-04-13","Sexta-feira Santa","MZ",2001 +"2001-05-01","Dia Mundial do Trabalho","MZ",2001 +"2001-06-25","Dia da Independencia Nacional","MZ",2001 +"2001-09-07","Dia da Vitoria","MZ",2001 +"2001-09-25","Dia das Forcas Armadas","MZ",2001 +"2001-10-04","Dia da Paz e Reconciliacao","MZ",2001 +"2001-12-25","Dia de Natal e da Familia","MZ",2001 +"2002-01-01","Ano novo","MZ",2002 +"2002-02-03","Dia dos Herois Mocambicanos","MZ",2002 +"2002-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2002 +"2002-02-12","Carnaval","MZ",2002 +"2002-03-29","Sexta-feira Santa","MZ",2002 +"2002-04-07","Dia da Mulher Mocambicana","MZ",2002 +"2002-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",2002 +"2002-05-01","Dia Mundial do Trabalho","MZ",2002 +"2002-06-25","Dia da Independencia Nacional","MZ",2002 +"2002-09-07","Dia da Vitoria","MZ",2002 +"2002-09-25","Dia das Forcas Armadas","MZ",2002 +"2002-10-04","Dia da Paz e Reconciliacao","MZ",2002 +"2002-12-25","Dia de Natal e da Familia","MZ",2002 +"2003-01-01","Ano novo","MZ",2003 +"2003-02-03","Dia dos Herois Mocambicanos","MZ",2003 +"2003-03-04","Carnaval","MZ",2003 +"2003-04-07","Dia da Mulher Mocambicana","MZ",2003 +"2003-04-18","Sexta-feira Santa","MZ",2003 +"2003-05-01","Dia Mundial do Trabalho","MZ",2003 +"2003-06-25","Dia da Independencia Nacional","MZ",2003 +"2003-09-07","Dia da Vitoria","MZ",2003 +"2003-09-08","Dia da Vitoria (PONTE)","MZ",2003 +"2003-09-25","Dia das Forcas Armadas","MZ",2003 +"2003-10-04","Dia da Paz e Reconciliacao","MZ",2003 +"2003-12-25","Dia de Natal e da Familia","MZ",2003 +"2004-01-01","Ano novo","MZ",2004 +"2004-02-03","Dia dos Herois Mocambicanos","MZ",2004 +"2004-02-24","Carnaval","MZ",2004 +"2004-04-07","Dia da Mulher Mocambicana","MZ",2004 +"2004-04-09","Sexta-feira Santa","MZ",2004 +"2004-05-01","Dia Mundial do Trabalho","MZ",2004 +"2004-06-25","Dia da Independencia Nacional","MZ",2004 +"2004-09-07","Dia da Vitoria","MZ",2004 +"2004-09-25","Dia das Forcas Armadas","MZ",2004 +"2004-10-04","Dia da Paz e Reconciliacao","MZ",2004 +"2004-12-25","Dia de Natal e da Familia","MZ",2004 +"2005-01-01","Ano novo","MZ",2005 +"2005-02-03","Dia dos Herois Mocambicanos","MZ",2005 +"2005-02-08","Carnaval","MZ",2005 +"2005-03-25","Sexta-feira Santa","MZ",2005 +"2005-04-07","Dia da Mulher Mocambicana","MZ",2005 +"2005-05-01","Dia Mundial do Trabalho","MZ",2005 +"2005-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2005 +"2005-06-25","Dia da Independencia Nacional","MZ",2005 +"2005-09-07","Dia da Vitoria","MZ",2005 +"2005-09-25","Dia das Forcas Armadas","MZ",2005 +"2005-09-26","Dia das Forcas Armadas (PONTE)","MZ",2005 +"2005-10-04","Dia da Paz e Reconciliacao","MZ",2005 +"2005-12-25","Dia de Natal e da Familia","MZ",2005 +"2005-12-26","Dia de Natal e da Familia (PONTE)","MZ",2005 +"2006-01-01","Ano novo","MZ",2006 +"2006-01-02","Ano novo (PONTE)","MZ",2006 +"2006-02-03","Dia dos Herois Mocambicanos","MZ",2006 +"2006-02-28","Carnaval","MZ",2006 +"2006-04-07","Dia da Mulher Mocambicana","MZ",2006 +"2006-04-14","Sexta-feira Santa","MZ",2006 +"2006-05-01","Dia Mundial do Trabalho","MZ",2006 +"2006-06-25","Dia da Independencia Nacional","MZ",2006 +"2006-06-26","Dia da Independencia Nacional (PONTE)","MZ",2006 +"2006-09-07","Dia da Vitoria","MZ",2006 +"2006-09-25","Dia das Forcas Armadas","MZ",2006 +"2006-10-04","Dia da Paz e Reconciliacao","MZ",2006 +"2006-12-25","Dia de Natal e da Familia","MZ",2006 +"2007-01-01","Ano novo","MZ",2007 +"2007-02-03","Dia dos Herois Mocambicanos","MZ",2007 +"2007-02-20","Carnaval","MZ",2007 +"2007-04-06","Sexta-feira Santa","MZ",2007 +"2007-04-07","Dia da Mulher Mocambicana","MZ",2007 +"2007-05-01","Dia Mundial do Trabalho","MZ",2007 +"2007-06-25","Dia da Independencia Nacional","MZ",2007 +"2007-09-07","Dia da Vitoria","MZ",2007 +"2007-09-25","Dia das Forcas Armadas","MZ",2007 +"2007-10-04","Dia da Paz e Reconciliacao","MZ",2007 +"2007-12-25","Dia de Natal e da Familia","MZ",2007 +"2008-01-01","Ano novo","MZ",2008 +"2008-02-03","Dia dos Herois Mocambicanos","MZ",2008 +"2008-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2008 +"2008-02-05","Carnaval","MZ",2008 +"2008-03-21","Sexta-feira Santa","MZ",2008 +"2008-04-07","Dia da Mulher Mocambicana","MZ",2008 +"2008-05-01","Dia Mundial do Trabalho","MZ",2008 +"2008-06-25","Dia da Independencia Nacional","MZ",2008 +"2008-09-07","Dia da Vitoria","MZ",2008 +"2008-09-08","Dia da Vitoria (PONTE)","MZ",2008 +"2008-09-25","Dia das Forcas Armadas","MZ",2008 +"2008-10-04","Dia da Paz e Reconciliacao","MZ",2008 +"2008-12-25","Dia de Natal e da Familia","MZ",2008 +"2009-01-01","Ano novo","MZ",2009 +"2009-02-03","Dia dos Herois Mocambicanos","MZ",2009 +"2009-02-24","Carnaval","MZ",2009 +"2009-04-07","Dia da Mulher Mocambicana","MZ",2009 +"2009-04-10","Sexta-feira Santa","MZ",2009 +"2009-05-01","Dia Mundial do Trabalho","MZ",2009 +"2009-06-25","Dia da Independencia Nacional","MZ",2009 +"2009-09-07","Dia da Vitoria","MZ",2009 +"2009-09-25","Dia das Forcas Armadas","MZ",2009 +"2009-10-04","Dia da Paz e Reconciliacao","MZ",2009 +"2009-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",2009 +"2009-12-25","Dia de Natal e da Familia","MZ",2009 +"2010-01-01","Ano novo","MZ",2010 +"2010-02-03","Dia dos Herois Mocambicanos","MZ",2010 +"2010-02-16","Carnaval","MZ",2010 +"2010-04-02","Sexta-feira Santa","MZ",2010 +"2010-04-07","Dia da Mulher Mocambicana","MZ",2010 +"2010-05-01","Dia Mundial do Trabalho","MZ",2010 +"2010-06-25","Dia da Independencia Nacional","MZ",2010 +"2010-09-07","Dia da Vitoria","MZ",2010 +"2010-09-25","Dia das Forcas Armadas","MZ",2010 +"2010-10-04","Dia da Paz e Reconciliacao","MZ",2010 +"2010-12-25","Dia de Natal e da Familia","MZ",2010 +"2011-01-01","Ano novo","MZ",2011 +"2011-02-03","Dia dos Herois Mocambicanos","MZ",2011 +"2011-03-08","Carnaval","MZ",2011 +"2011-04-07","Dia da Mulher Mocambicana","MZ",2011 +"2011-04-22","Sexta-feira Santa","MZ",2011 +"2011-05-01","Dia Mundial do Trabalho","MZ",2011 +"2011-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2011 +"2011-06-25","Dia da Independencia Nacional","MZ",2011 +"2011-09-07","Dia da Vitoria","MZ",2011 +"2011-09-25","Dia das Forcas Armadas","MZ",2011 +"2011-09-26","Dia das Forcas Armadas (PONTE)","MZ",2011 +"2011-10-04","Dia da Paz e Reconciliacao","MZ",2011 +"2011-12-25","Dia de Natal e da Familia","MZ",2011 +"2011-12-26","Dia de Natal e da Familia (PONTE)","MZ",2011 +"2012-01-01","Ano novo","MZ",2012 +"2012-01-02","Ano novo (PONTE)","MZ",2012 +"2012-02-03","Dia dos Herois Mocambicanos","MZ",2012 +"2012-02-21","Carnaval","MZ",2012 +"2012-04-06","Sexta-feira Santa","MZ",2012 +"2012-04-07","Dia da Mulher Mocambicana","MZ",2012 +"2012-05-01","Dia Mundial do Trabalho","MZ",2012 +"2012-06-25","Dia da Independencia Nacional","MZ",2012 +"2012-09-07","Dia da Vitoria","MZ",2012 +"2012-09-25","Dia das Forcas Armadas","MZ",2012 +"2012-10-04","Dia da Paz e Reconciliacao","MZ",2012 +"2012-12-25","Dia de Natal e da Familia","MZ",2012 +"2013-01-01","Ano novo","MZ",2013 +"2013-02-03","Dia dos Herois Mocambicanos","MZ",2013 +"2013-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2013 +"2013-02-12","Carnaval","MZ",2013 +"2013-03-29","Sexta-feira Santa","MZ",2013 +"2013-04-07","Dia da Mulher Mocambicana","MZ",2013 +"2013-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",2013 +"2013-05-01","Dia Mundial do Trabalho","MZ",2013 +"2013-06-25","Dia da Independencia Nacional","MZ",2013 +"2013-09-07","Dia da Vitoria","MZ",2013 +"2013-09-25","Dia das Forcas Armadas","MZ",2013 +"2013-10-04","Dia da Paz e Reconciliacao","MZ",2013 +"2013-12-25","Dia de Natal e da Familia","MZ",2013 +"2014-01-01","Ano novo","MZ",2014 +"2014-02-03","Dia dos Herois Mocambicanos","MZ",2014 +"2014-03-04","Carnaval","MZ",2014 +"2014-04-07","Dia da Mulher Mocambicana","MZ",2014 +"2014-04-18","Sexta-feira Santa","MZ",2014 +"2014-05-01","Dia Mundial do Trabalho","MZ",2014 +"2014-06-25","Dia da Independencia Nacional","MZ",2014 +"2014-09-07","Dia da Vitoria","MZ",2014 +"2014-09-08","Dia da Vitoria (PONTE)","MZ",2014 +"2014-09-25","Dia das Forcas Armadas","MZ",2014 +"2014-10-04","Dia da Paz e Reconciliacao","MZ",2014 +"2014-12-25","Dia de Natal e da Familia","MZ",2014 +"2015-01-01","Ano novo","MZ",2015 +"2015-02-03","Dia dos Herois Mocambicanos","MZ",2015 +"2015-02-17","Carnaval","MZ",2015 +"2015-04-03","Sexta-feira Santa","MZ",2015 +"2015-04-07","Dia da Mulher Mocambicana","MZ",2015 +"2015-05-01","Dia Mundial do Trabalho","MZ",2015 +"2015-06-25","Dia da Independencia Nacional","MZ",2015 +"2015-09-07","Dia da Vitoria","MZ",2015 +"2015-09-25","Dia das Forcas Armadas","MZ",2015 +"2015-10-04","Dia da Paz e Reconciliacao","MZ",2015 +"2015-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",2015 +"2015-12-25","Dia de Natal e da Familia","MZ",2015 +"2016-01-01","Ano novo","MZ",2016 +"2016-02-03","Dia dos Herois Mocambicanos","MZ",2016 +"2016-02-09","Carnaval","MZ",2016 +"2016-03-25","Sexta-feira Santa","MZ",2016 +"2016-04-07","Dia da Mulher Mocambicana","MZ",2016 +"2016-05-01","Dia Mundial do Trabalho","MZ",2016 +"2016-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2016 +"2016-06-25","Dia da Independencia Nacional","MZ",2016 +"2016-09-07","Dia da Vitoria","MZ",2016 +"2016-09-25","Dia das Forcas Armadas","MZ",2016 +"2016-09-26","Dia das Forcas Armadas (PONTE)","MZ",2016 +"2016-10-04","Dia da Paz e Reconciliacao","MZ",2016 +"2016-12-25","Dia de Natal e da Familia","MZ",2016 +"2016-12-26","Dia de Natal e da Familia (PONTE)","MZ",2016 +"2017-01-01","Ano novo","MZ",2017 +"2017-01-02","Ano novo (PONTE)","MZ",2017 +"2017-02-03","Dia dos Herois Mocambicanos","MZ",2017 +"2017-02-28","Carnaval","MZ",2017 +"2017-04-07","Dia da Mulher Mocambicana","MZ",2017 +"2017-04-14","Sexta-feira Santa","MZ",2017 +"2017-05-01","Dia Mundial do Trabalho","MZ",2017 +"2017-06-25","Dia da Independencia Nacional","MZ",2017 +"2017-06-26","Dia da Independencia Nacional (PONTE)","MZ",2017 +"2017-09-07","Dia da Vitoria","MZ",2017 +"2017-09-25","Dia das Forcas Armadas","MZ",2017 +"2017-10-04","Dia da Paz e Reconciliacao","MZ",2017 +"2017-12-25","Dia de Natal e da Familia","MZ",2017 +"2018-01-01","Ano novo","MZ",2018 +"2018-02-03","Dia dos Herois Mocambicanos","MZ",2018 +"2018-02-13","Carnaval","MZ",2018 +"2018-03-30","Sexta-feira Santa","MZ",2018 +"2018-04-07","Dia da Mulher Mocambicana","MZ",2018 +"2018-05-01","Dia Mundial do Trabalho","MZ",2018 +"2018-06-25","Dia da Independencia Nacional","MZ",2018 +"2018-09-07","Dia da Vitoria","MZ",2018 +"2018-09-25","Dia das Forcas Armadas","MZ",2018 +"2018-10-04","Dia da Paz e Reconciliacao","MZ",2018 +"2018-12-25","Dia de Natal e da Familia","MZ",2018 +"2019-01-01","Ano novo","MZ",2019 +"2019-02-03","Dia dos Herois Mocambicanos","MZ",2019 +"2019-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2019 +"2019-03-05","Carnaval","MZ",2019 +"2019-04-07","Dia da Mulher Mocambicana","MZ",2019 +"2019-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",2019 +"2019-04-19","Sexta-feira Santa","MZ",2019 +"2019-05-01","Dia Mundial do Trabalho","MZ",2019 +"2019-06-25","Dia da Independencia Nacional","MZ",2019 +"2019-09-07","Dia da Vitoria","MZ",2019 +"2019-09-25","Dia das Forcas Armadas","MZ",2019 +"2019-10-04","Dia da Paz e Reconciliacao","MZ",2019 +"2019-12-25","Dia de Natal e da Familia","MZ",2019 +"2020-01-01","Ano novo","MZ",2020 +"2020-02-03","Dia dos Herois Mocambicanos","MZ",2020 +"2020-02-25","Carnaval","MZ",2020 +"2020-04-07","Dia da Mulher Mocambicana","MZ",2020 +"2020-04-10","Sexta-feira Santa","MZ",2020 +"2020-05-01","Dia Mundial do Trabalho","MZ",2020 +"2020-06-25","Dia da Independencia Nacional","MZ",2020 +"2020-09-07","Dia da Vitoria","MZ",2020 +"2020-09-25","Dia das Forcas Armadas","MZ",2020 +"2020-10-04","Dia da Paz e Reconciliacao","MZ",2020 +"2020-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",2020 +"2020-12-25","Dia de Natal e da Familia","MZ",2020 +"2021-01-01","Ano novo","MZ",2021 +"2021-02-03","Dia dos Herois Mocambicanos","MZ",2021 +"2021-02-16","Carnaval","MZ",2021 +"2021-04-02","Sexta-feira Santa","MZ",2021 +"2021-04-07","Dia da Mulher Mocambicana","MZ",2021 +"2021-05-01","Dia Mundial do Trabalho","MZ",2021 +"2021-06-25","Dia da Independencia Nacional","MZ",2021 +"2021-09-07","Dia da Vitoria","MZ",2021 +"2021-09-25","Dia das Forcas Armadas","MZ",2021 +"2021-10-04","Dia da Paz e Reconciliacao","MZ",2021 +"2021-12-25","Dia de Natal e da Familia","MZ",2021 +"2022-01-01","Ano novo","MZ",2022 +"2022-02-03","Dia dos Herois Mocambicanos","MZ",2022 +"2022-03-01","Carnaval","MZ",2022 +"2022-04-07","Dia da Mulher Mocambicana","MZ",2022 +"2022-04-15","Sexta-feira Santa","MZ",2022 +"2022-05-01","Dia Mundial do Trabalho","MZ",2022 +"2022-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2022 +"2022-06-25","Dia da Independencia Nacional","MZ",2022 +"2022-09-07","Dia da Vitoria","MZ",2022 +"2022-09-25","Dia das Forcas Armadas","MZ",2022 +"2022-09-26","Dia das Forcas Armadas (PONTE)","MZ",2022 +"2022-10-04","Dia da Paz e Reconciliacao","MZ",2022 +"2022-12-25","Dia de Natal e da Familia","MZ",2022 +"2022-12-26","Dia de Natal e da Familia (PONTE)","MZ",2022 +"2023-01-01","Ano novo","MZ",2023 +"2023-01-02","Ano novo (PONTE)","MZ",2023 +"2023-02-03","Dia dos Herois Mocambicanos","MZ",2023 +"2023-02-21","Carnaval","MZ",2023 +"2023-04-07","Dia da Mulher Mocambicana","MZ",2023 +"2023-04-07","Sexta-feira Santa","MZ",2023 +"2023-05-01","Dia Mundial do Trabalho","MZ",2023 +"2023-06-25","Dia da Independencia Nacional","MZ",2023 +"2023-06-26","Dia da Independencia Nacional (PONTE)","MZ",2023 +"2023-09-07","Dia da Vitoria","MZ",2023 +"2023-09-25","Dia das Forcas Armadas","MZ",2023 +"2023-10-04","Dia da Paz e Reconciliacao","MZ",2023 +"2023-12-25","Dia de Natal e da Familia","MZ",2023 +"2024-01-01","Ano novo","MZ",2024 +"2024-02-03","Dia dos Herois Mocambicanos","MZ",2024 +"2024-02-13","Carnaval","MZ",2024 +"2024-03-29","Sexta-feira Santa","MZ",2024 +"2024-04-07","Dia da Mulher Mocambicana","MZ",2024 +"2024-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",2024 +"2024-05-01","Dia Mundial do Trabalho","MZ",2024 +"2024-06-25","Dia da Independencia Nacional","MZ",2024 +"2024-09-07","Dia da Vitoria","MZ",2024 +"2024-09-25","Dia das Forcas Armadas","MZ",2024 +"2024-10-04","Dia da Paz e Reconciliacao","MZ",2024 +"2024-12-25","Dia de Natal e da Familia","MZ",2024 +"2025-01-01","Ano novo","MZ",2025 +"2025-02-03","Dia dos Herois Mocambicanos","MZ",2025 +"2025-03-04","Carnaval","MZ",2025 +"2025-04-07","Dia da Mulher Mocambicana","MZ",2025 +"2025-04-18","Sexta-feira Santa","MZ",2025 +"2025-05-01","Dia Mundial do Trabalho","MZ",2025 +"2025-06-25","Dia da Independencia Nacional","MZ",2025 +"2025-09-07","Dia da Vitoria","MZ",2025 +"2025-09-08","Dia da Vitoria (PONTE)","MZ",2025 +"2025-09-25","Dia das Forcas Armadas","MZ",2025 +"2025-10-04","Dia da Paz e Reconciliacao","MZ",2025 +"2025-12-25","Dia de Natal e da Familia","MZ",2025 +"2026-01-01","Ano novo","MZ",2026 +"2026-02-03","Dia dos Herois Mocambicanos","MZ",2026 +"2026-02-17","Carnaval","MZ",2026 +"2026-04-03","Sexta-feira Santa","MZ",2026 +"2026-04-07","Dia da Mulher Mocambicana","MZ",2026 +"2026-05-01","Dia Mundial do Trabalho","MZ",2026 +"2026-06-25","Dia da Independencia Nacional","MZ",2026 +"2026-09-07","Dia da Vitoria","MZ",2026 +"2026-09-25","Dia das Forcas Armadas","MZ",2026 +"2026-10-04","Dia da Paz e Reconciliacao","MZ",2026 +"2026-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",2026 +"2026-12-25","Dia de Natal e da Familia","MZ",2026 +"2027-01-01","Ano novo","MZ",2027 +"2027-02-03","Dia dos Herois Mocambicanos","MZ",2027 +"2027-02-09","Carnaval","MZ",2027 +"2027-03-26","Sexta-feira Santa","MZ",2027 +"2027-04-07","Dia da Mulher Mocambicana","MZ",2027 +"2027-05-01","Dia Mundial do Trabalho","MZ",2027 +"2027-06-25","Dia da Independencia Nacional","MZ",2027 +"2027-09-07","Dia da Vitoria","MZ",2027 +"2027-09-25","Dia das Forcas Armadas","MZ",2027 +"2027-10-04","Dia da Paz e Reconciliacao","MZ",2027 +"2027-12-25","Dia de Natal e da Familia","MZ",2027 +"2028-01-01","Ano novo","MZ",2028 +"2028-02-03","Dia dos Herois Mocambicanos","MZ",2028 +"2028-02-29","Carnaval","MZ",2028 +"2028-04-07","Dia da Mulher Mocambicana","MZ",2028 +"2028-04-14","Sexta-feira Santa","MZ",2028 +"2028-05-01","Dia Mundial do Trabalho","MZ",2028 +"2028-06-25","Dia da Independencia Nacional","MZ",2028 +"2028-06-26","Dia da Independencia Nacional (PONTE)","MZ",2028 +"2028-09-07","Dia da Vitoria","MZ",2028 +"2028-09-25","Dia das Forcas Armadas","MZ",2028 +"2028-10-04","Dia da Paz e Reconciliacao","MZ",2028 +"2028-12-25","Dia de Natal e da Familia","MZ",2028 +"2029-01-01","Ano novo","MZ",2029 +"2029-02-03","Dia dos Herois Mocambicanos","MZ",2029 +"2029-02-13","Carnaval","MZ",2029 +"2029-03-30","Sexta-feira Santa","MZ",2029 +"2029-04-07","Dia da Mulher Mocambicana","MZ",2029 +"2029-05-01","Dia Mundial do Trabalho","MZ",2029 +"2029-06-25","Dia da Independencia Nacional","MZ",2029 +"2029-09-07","Dia da Vitoria","MZ",2029 +"2029-09-25","Dia das Forcas Armadas","MZ",2029 +"2029-10-04","Dia da Paz e Reconciliacao","MZ",2029 +"2029-12-25","Dia de Natal e da Familia","MZ",2029 +"2030-01-01","Ano novo","MZ",2030 +"2030-02-03","Dia dos Herois Mocambicanos","MZ",2030 +"2030-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2030 +"2030-03-05","Carnaval","MZ",2030 +"2030-04-07","Dia da Mulher Mocambicana","MZ",2030 +"2030-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",2030 +"2030-04-19","Sexta-feira Santa","MZ",2030 +"2030-05-01","Dia Mundial do Trabalho","MZ",2030 +"2030-06-25","Dia da Independencia Nacional","MZ",2030 +"2030-09-07","Dia da Vitoria","MZ",2030 +"2030-09-25","Dia das Forcas Armadas","MZ",2030 +"2030-10-04","Dia da Paz e Reconciliacao","MZ",2030 +"2030-12-25","Dia de Natal e da Familia","MZ",2030 +"2031-01-01","Ano novo","MZ",2031 +"2031-02-03","Dia dos Herois Mocambicanos","MZ",2031 +"2031-02-25","Carnaval","MZ",2031 +"2031-04-07","Dia da Mulher Mocambicana","MZ",2031 +"2031-04-11","Sexta-feira Santa","MZ",2031 +"2031-05-01","Dia Mundial do Trabalho","MZ",2031 +"2031-06-25","Dia da Independencia Nacional","MZ",2031 +"2031-09-07","Dia da Vitoria","MZ",2031 +"2031-09-08","Dia da Vitoria (PONTE)","MZ",2031 +"2031-09-25","Dia das Forcas Armadas","MZ",2031 +"2031-10-04","Dia da Paz e Reconciliacao","MZ",2031 +"2031-12-25","Dia de Natal e da Familia","MZ",2031 +"2032-01-01","Ano novo","MZ",2032 +"2032-02-03","Dia dos Herois Mocambicanos","MZ",2032 +"2032-02-10","Carnaval","MZ",2032 +"2032-03-26","Sexta-feira Santa","MZ",2032 +"2032-04-07","Dia da Mulher Mocambicana","MZ",2032 +"2032-05-01","Dia Mundial do Trabalho","MZ",2032 +"2032-06-25","Dia da Independencia Nacional","MZ",2032 +"2032-09-07","Dia da Vitoria","MZ",2032 +"2032-09-25","Dia das Forcas Armadas","MZ",2032 +"2032-10-04","Dia da Paz e Reconciliacao","MZ",2032 +"2032-12-25","Dia de Natal e da Familia","MZ",2032 +"2033-01-01","Ano novo","MZ",2033 +"2033-02-03","Dia dos Herois Mocambicanos","MZ",2033 +"2033-03-01","Carnaval","MZ",2033 +"2033-04-07","Dia da Mulher Mocambicana","MZ",2033 +"2033-04-15","Sexta-feira Santa","MZ",2033 +"2033-05-01","Dia Mundial do Trabalho","MZ",2033 +"2033-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2033 +"2033-06-25","Dia da Independencia Nacional","MZ",2033 +"2033-09-07","Dia da Vitoria","MZ",2033 +"2033-09-25","Dia das Forcas Armadas","MZ",2033 +"2033-09-26","Dia das Forcas Armadas (PONTE)","MZ",2033 +"2033-10-04","Dia da Paz e Reconciliacao","MZ",2033 +"2033-12-25","Dia de Natal e da Familia","MZ",2033 +"2033-12-26","Dia de Natal e da Familia (PONTE)","MZ",2033 +"2034-01-01","Ano novo","MZ",2034 +"2034-01-02","Ano novo (PONTE)","MZ",2034 +"2034-02-03","Dia dos Herois Mocambicanos","MZ",2034 +"2034-02-21","Carnaval","MZ",2034 +"2034-04-07","Dia da Mulher Mocambicana","MZ",2034 +"2034-04-07","Sexta-feira Santa","MZ",2034 +"2034-05-01","Dia Mundial do Trabalho","MZ",2034 +"2034-06-25","Dia da Independencia Nacional","MZ",2034 +"2034-06-26","Dia da Independencia Nacional (PONTE)","MZ",2034 +"2034-09-07","Dia da Vitoria","MZ",2034 +"2034-09-25","Dia das Forcas Armadas","MZ",2034 +"2034-10-04","Dia da Paz e Reconciliacao","MZ",2034 +"2034-12-25","Dia de Natal e da Familia","MZ",2034 +"2035-01-01","Ano novo","MZ",2035 +"2035-02-03","Dia dos Herois Mocambicanos","MZ",2035 +"2035-02-06","Carnaval","MZ",2035 +"2035-03-23","Sexta-feira Santa","MZ",2035 +"2035-04-07","Dia da Mulher Mocambicana","MZ",2035 +"2035-05-01","Dia Mundial do Trabalho","MZ",2035 +"2035-06-25","Dia da Independencia Nacional","MZ",2035 +"2035-09-07","Dia da Vitoria","MZ",2035 +"2035-09-25","Dia das Forcas Armadas","MZ",2035 +"2035-10-04","Dia da Paz e Reconciliacao","MZ",2035 +"2035-12-25","Dia de Natal e da Familia","MZ",2035 +"2036-01-01","Ano novo","MZ",2036 +"2036-02-03","Dia dos Herois Mocambicanos","MZ",2036 +"2036-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2036 +"2036-02-26","Carnaval","MZ",2036 +"2036-04-07","Dia da Mulher Mocambicana","MZ",2036 +"2036-04-11","Sexta-feira Santa","MZ",2036 +"2036-05-01","Dia Mundial do Trabalho","MZ",2036 +"2036-06-25","Dia da Independencia Nacional","MZ",2036 +"2036-09-07","Dia da Vitoria","MZ",2036 +"2036-09-08","Dia da Vitoria (PONTE)","MZ",2036 +"2036-09-25","Dia das Forcas Armadas","MZ",2036 +"2036-10-04","Dia da Paz e Reconciliacao","MZ",2036 +"2036-12-25","Dia de Natal e da Familia","MZ",2036 +"2037-01-01","Ano novo","MZ",2037 +"2037-02-03","Dia dos Herois Mocambicanos","MZ",2037 +"2037-02-17","Carnaval","MZ",2037 +"2037-04-03","Sexta-feira Santa","MZ",2037 +"2037-04-07","Dia da Mulher Mocambicana","MZ",2037 +"2037-05-01","Dia Mundial do Trabalho","MZ",2037 +"2037-06-25","Dia da Independencia Nacional","MZ",2037 +"2037-09-07","Dia da Vitoria","MZ",2037 +"2037-09-25","Dia das Forcas Armadas","MZ",2037 +"2037-10-04","Dia da Paz e Reconciliacao","MZ",2037 +"2037-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",2037 +"2037-12-25","Dia de Natal e da Familia","MZ",2037 +"2038-01-01","Ano novo","MZ",2038 +"2038-02-03","Dia dos Herois Mocambicanos","MZ",2038 +"2038-03-09","Carnaval","MZ",2038 +"2038-04-07","Dia da Mulher Mocambicana","MZ",2038 +"2038-04-23","Sexta-feira Santa","MZ",2038 +"2038-05-01","Dia Mundial do Trabalho","MZ",2038 +"2038-06-25","Dia da Independencia Nacional","MZ",2038 +"2038-09-07","Dia da Vitoria","MZ",2038 +"2038-09-25","Dia das Forcas Armadas","MZ",2038 +"2038-10-04","Dia da Paz e Reconciliacao","MZ",2038 +"2038-12-25","Dia de Natal e da Familia","MZ",2038 +"2039-01-01","Ano novo","MZ",2039 +"2039-02-03","Dia dos Herois Mocambicanos","MZ",2039 +"2039-02-22","Carnaval","MZ",2039 +"2039-04-07","Dia da Mulher Mocambicana","MZ",2039 +"2039-04-08","Sexta-feira Santa","MZ",2039 +"2039-05-01","Dia Mundial do Trabalho","MZ",2039 +"2039-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2039 +"2039-06-25","Dia da Independencia Nacional","MZ",2039 +"2039-09-07","Dia da Vitoria","MZ",2039 +"2039-09-25","Dia das Forcas Armadas","MZ",2039 +"2039-09-26","Dia das Forcas Armadas (PONTE)","MZ",2039 +"2039-10-04","Dia da Paz e Reconciliacao","MZ",2039 +"2039-12-25","Dia de Natal e da Familia","MZ",2039 +"2039-12-26","Dia de Natal e da Familia (PONTE)","MZ",2039 +"2040-01-01","Ano novo","MZ",2040 +"2040-01-02","Ano novo (PONTE)","MZ",2040 +"2040-02-03","Dia dos Herois Mocambicanos","MZ",2040 +"2040-02-14","Carnaval","MZ",2040 +"2040-03-30","Sexta-feira Santa","MZ",2040 +"2040-04-07","Dia da Mulher Mocambicana","MZ",2040 +"2040-05-01","Dia Mundial do Trabalho","MZ",2040 +"2040-06-25","Dia da Independencia Nacional","MZ",2040 +"2040-09-07","Dia da Vitoria","MZ",2040 +"2040-09-25","Dia das Forcas Armadas","MZ",2040 +"2040-10-04","Dia da Paz e Reconciliacao","MZ",2040 +"2040-12-25","Dia de Natal e da Familia","MZ",2040 +"2041-01-01","Ano novo","MZ",2041 +"2041-02-03","Dia dos Herois Mocambicanos","MZ",2041 +"2041-02-04","Dia dos Herois Mocambicanos (PONTE)","MZ",2041 +"2041-03-05","Carnaval","MZ",2041 +"2041-04-07","Dia da Mulher Mocambicana","MZ",2041 +"2041-04-08","Dia da Mulher Mocambicana (PONTE)","MZ",2041 +"2041-04-19","Sexta-feira Santa","MZ",2041 +"2041-05-01","Dia Mundial do Trabalho","MZ",2041 +"2041-06-25","Dia da Independencia Nacional","MZ",2041 +"2041-09-07","Dia da Vitoria","MZ",2041 +"2041-09-25","Dia das Forcas Armadas","MZ",2041 +"2041-10-04","Dia da Paz e Reconciliacao","MZ",2041 +"2041-12-25","Dia de Natal e da Familia","MZ",2041 +"2042-01-01","Ano novo","MZ",2042 +"2042-02-03","Dia dos Herois Mocambicanos","MZ",2042 +"2042-02-18","Carnaval","MZ",2042 +"2042-04-04","Sexta-feira Santa","MZ",2042 +"2042-04-07","Dia da Mulher Mocambicana","MZ",2042 +"2042-05-01","Dia Mundial do Trabalho","MZ",2042 +"2042-06-25","Dia da Independencia Nacional","MZ",2042 +"2042-09-07","Dia da Vitoria","MZ",2042 +"2042-09-08","Dia da Vitoria (PONTE)","MZ",2042 +"2042-09-25","Dia das Forcas Armadas","MZ",2042 +"2042-10-04","Dia da Paz e Reconciliacao","MZ",2042 +"2042-12-25","Dia de Natal e da Familia","MZ",2042 +"2043-01-01","Ano novo","MZ",2043 +"2043-02-03","Dia dos Herois Mocambicanos","MZ",2043 +"2043-02-10","Carnaval","MZ",2043 +"2043-03-27","Sexta-feira Santa","MZ",2043 +"2043-04-07","Dia da Mulher Mocambicana","MZ",2043 +"2043-05-01","Dia Mundial do Trabalho","MZ",2043 +"2043-06-25","Dia da Independencia Nacional","MZ",2043 +"2043-09-07","Dia da Vitoria","MZ",2043 +"2043-09-25","Dia das Forcas Armadas","MZ",2043 +"2043-10-04","Dia da Paz e Reconciliacao","MZ",2043 +"2043-10-05","Dia da Paz e Reconciliacao (PONTE)","MZ",2043 +"2043-12-25","Dia de Natal e da Familia","MZ",2043 +"2044-01-01","Ano novo","MZ",2044 +"2044-02-03","Dia dos Herois Mocambicanos","MZ",2044 +"2044-03-01","Carnaval","MZ",2044 +"2044-04-07","Dia da Mulher Mocambicana","MZ",2044 +"2044-04-15","Sexta-feira Santa","MZ",2044 +"2044-05-01","Dia Mundial do Trabalho","MZ",2044 +"2044-05-02","Dia Mundial do Trabalho (PONTE)","MZ",2044 +"2044-06-25","Dia da Independencia Nacional","MZ",2044 +"2044-09-07","Dia da Vitoria","MZ",2044 +"2044-09-25","Dia das Forcas Armadas","MZ",2044 +"2044-09-26","Dia das Forcas Armadas (PONTE)","MZ",2044 +"2044-10-04","Dia da Paz e Reconciliacao","MZ",2044 +"2044-12-25","Dia de Natal e da Familia","MZ",2044 +"2044-12-26","Dia de Natal e da Familia (PONTE)","MZ",2044 +"1995-01-01","New Year's Day","NG",1995 +"1995-03-02","Eid-el-Fitr* (*estimated)","NG",1995 +"1995-03-03","Eid-el-Fitr Holiday* (*estimated)","NG",1995 +"1995-04-14","Good Friday","NG",1995 +"1995-04-17","Easter Monday","NG",1995 +"1995-05-01","Workers' Day","NG",1995 +"1995-05-09","Eid-el-Kabir* (*estimated)","NG",1995 +"1995-05-10","Eid-el-Kabir Holiday* (*estimated)","NG",1995 +"1995-08-08","Eid-el-Mawlid* (*estimated)","NG",1995 +"1995-10-01","Independence Day","NG",1995 +"1995-12-25","Christmas Day","NG",1995 +"1995-12-26","Boxing Day","NG",1995 +"1996-01-01","New Year's Day","NG",1996 +"1996-02-19","Eid-el-Fitr* (*estimated)","NG",1996 +"1996-02-20","Eid-el-Fitr Holiday* (*estimated)","NG",1996 +"1996-04-05","Good Friday","NG",1996 +"1996-04-08","Easter Monday","NG",1996 +"1996-04-27","Eid-el-Kabir* (*estimated)","NG",1996 +"1996-04-28","Eid-el-Kabir Holiday* (*estimated)","NG",1996 +"1996-05-01","Workers' Day","NG",1996 +"1996-07-27","Eid-el-Mawlid* (*estimated)","NG",1996 +"1996-10-01","Independence Day","NG",1996 +"1996-12-25","Christmas Day","NG",1996 +"1996-12-26","Boxing Day","NG",1996 +"1997-01-01","New Year's Day","NG",1997 +"1997-02-08","Eid-el-Fitr* (*estimated)","NG",1997 +"1997-02-09","Eid-el-Fitr Holiday* (*estimated)","NG",1997 +"1997-03-28","Good Friday","NG",1997 +"1997-03-31","Easter Monday","NG",1997 +"1997-04-17","Eid-el-Kabir* (*estimated)","NG",1997 +"1997-04-18","Eid-el-Kabir Holiday* (*estimated)","NG",1997 +"1997-05-01","Workers' Day","NG",1997 +"1997-07-16","Eid-el-Mawlid* (*estimated)","NG",1997 +"1997-10-01","Independence Day","NG",1997 +"1997-12-25","Christmas Day","NG",1997 +"1997-12-26","Boxing Day","NG",1997 +"1998-01-01","New Year's Day","NG",1998 +"1998-01-29","Eid-el-Fitr* (*estimated)","NG",1998 +"1998-01-30","Eid-el-Fitr Holiday* (*estimated)","NG",1998 +"1998-04-07","Eid-el-Kabir* (*estimated)","NG",1998 +"1998-04-08","Eid-el-Kabir Holiday* (*estimated)","NG",1998 +"1998-04-10","Good Friday","NG",1998 +"1998-04-13","Easter Monday","NG",1998 +"1998-05-01","Workers' Day","NG",1998 +"1998-07-06","Eid-el-Mawlid* (*estimated)","NG",1998 +"1998-10-01","Independence Day","NG",1998 +"1998-12-25","Christmas Day","NG",1998 +"1998-12-26","Boxing Day","NG",1998 +"1999-01-01","New Year's Day","NG",1999 +"1999-01-18","Eid-el-Fitr* (*estimated)","NG",1999 +"1999-01-19","Eid-el-Fitr Holiday* (*estimated)","NG",1999 +"1999-03-27","Eid-el-Kabir* (*estimated)","NG",1999 +"1999-03-28","Eid-el-Kabir Holiday* (*estimated)","NG",1999 +"1999-04-02","Good Friday","NG",1999 +"1999-04-05","Easter Monday","NG",1999 +"1999-05-01","Workers' Day","NG",1999 +"1999-06-26","Eid-el-Mawlid* (*estimated)","NG",1999 +"1999-10-01","Independence Day","NG",1999 +"1999-12-25","Christmas Day","NG",1999 +"1999-12-26","Boxing Day","NG",1999 +"2000-01-01","New Year's Day","NG",2000 +"2000-01-08","Eid-el-Fitr* (*estimated)","NG",2000 +"2000-01-09","Eid-el-Fitr Holiday* (*estimated)","NG",2000 +"2000-03-16","Eid-el-Kabir* (*estimated)","NG",2000 +"2000-03-17","Eid-el-Kabir Holiday* (*estimated)","NG",2000 +"2000-04-21","Good Friday","NG",2000 +"2000-04-24","Easter Monday","NG",2000 +"2000-05-01","Workers' Day","NG",2000 +"2000-05-29","Democracy Day","NG",2000 +"2000-06-14","Eid-el-Mawlid* (*estimated)","NG",2000 +"2000-10-01","Independence Day","NG",2000 +"2000-12-25","Christmas Day","NG",2000 +"2000-12-26","Boxing Day","NG",2000 +"2000-12-27","Eid-el-Fitr* (*estimated)","NG",2000 +"2000-12-28","Eid-el-Fitr Holiday* (*estimated)","NG",2000 +"2001-01-01","New Year's Day","NG",2001 +"2001-03-05","Eid-el-Kabir* (*estimated)","NG",2001 +"2001-03-06","Eid-el-Kabir Holiday* (*estimated)","NG",2001 +"2001-04-13","Good Friday","NG",2001 +"2001-04-16","Easter Monday","NG",2001 +"2001-05-01","Workers' Day","NG",2001 +"2001-05-29","Democracy Day","NG",2001 +"2001-06-04","Eid-el-Mawlid* (*estimated)","NG",2001 +"2001-10-01","Independence Day","NG",2001 +"2001-12-16","Eid-el-Fitr* (*estimated)","NG",2001 +"2001-12-17","Eid-el-Fitr Holiday* (*estimated)","NG",2001 +"2001-12-25","Christmas Day","NG",2001 +"2001-12-26","Boxing Day","NG",2001 +"2002-01-01","New Year's Day","NG",2002 +"2002-02-22","Eid-el-Kabir* (*estimated)","NG",2002 +"2002-02-23","Eid-el-Kabir Holiday* (*estimated)","NG",2002 +"2002-03-29","Good Friday","NG",2002 +"2002-04-01","Easter Monday","NG",2002 +"2002-05-01","Workers' Day","NG",2002 +"2002-05-24","Eid-el-Mawlid* (*estimated)","NG",2002 +"2002-05-29","Democracy Day","NG",2002 +"2002-10-01","Independence Day","NG",2002 +"2002-12-05","Eid-el-Fitr* (*estimated)","NG",2002 +"2002-12-06","Eid-el-Fitr Holiday* (*estimated)","NG",2002 +"2002-12-25","Christmas Day","NG",2002 +"2002-12-26","Boxing Day","NG",2002 +"2003-01-01","New Year's Day","NG",2003 +"2003-02-11","Eid-el-Kabir* (*estimated)","NG",2003 +"2003-02-12","Eid-el-Kabir Holiday* (*estimated)","NG",2003 +"2003-04-18","Good Friday","NG",2003 +"2003-04-21","Easter Monday","NG",2003 +"2003-05-01","Workers' Day","NG",2003 +"2003-05-13","Eid-el-Mawlid* (*estimated)","NG",2003 +"2003-05-29","Democracy Day","NG",2003 +"2003-10-01","Independence Day","NG",2003 +"2003-11-25","Eid-el-Fitr* (*estimated)","NG",2003 +"2003-11-26","Eid-el-Fitr Holiday* (*estimated)","NG",2003 +"2003-12-25","Christmas Day","NG",2003 +"2003-12-26","Boxing Day","NG",2003 +"2004-01-01","New Year's Day","NG",2004 +"2004-02-01","Eid-el-Kabir* (*estimated)","NG",2004 +"2004-02-02","Eid-el-Kabir Holiday* (*estimated)","NG",2004 +"2004-04-09","Good Friday","NG",2004 +"2004-04-12","Easter Monday","NG",2004 +"2004-05-01","Eid-el-Mawlid* (*estimated)","NG",2004 +"2004-05-01","Workers' Day","NG",2004 +"2004-05-29","Democracy Day","NG",2004 +"2004-10-01","Independence Day","NG",2004 +"2004-11-14","Eid-el-Fitr* (*estimated)","NG",2004 +"2004-11-15","Eid-el-Fitr Holiday* (*estimated)","NG",2004 +"2004-12-25","Christmas Day","NG",2004 +"2004-12-26","Boxing Day","NG",2004 +"2005-01-01","New Year's Day","NG",2005 +"2005-01-21","Eid-el-Kabir* (*estimated)","NG",2005 +"2005-01-22","Eid-el-Kabir Holiday* (*estimated)","NG",2005 +"2005-03-25","Good Friday","NG",2005 +"2005-03-28","Easter Monday","NG",2005 +"2005-04-21","Eid-el-Mawlid* (*estimated)","NG",2005 +"2005-05-01","Workers' Day","NG",2005 +"2005-05-29","Democracy Day","NG",2005 +"2005-10-01","Independence Day","NG",2005 +"2005-11-03","Eid-el-Fitr* (*estimated)","NG",2005 +"2005-11-04","Eid-el-Fitr Holiday* (*estimated)","NG",2005 +"2005-12-25","Christmas Day","NG",2005 +"2005-12-26","Boxing Day","NG",2005 +"2006-01-01","New Year's Day","NG",2006 +"2006-01-10","Eid-el-Kabir* (*estimated)","NG",2006 +"2006-01-11","Eid-el-Kabir Holiday* (*estimated)","NG",2006 +"2006-04-10","Eid-el-Mawlid* (*estimated)","NG",2006 +"2006-04-14","Good Friday","NG",2006 +"2006-04-17","Easter Monday","NG",2006 +"2006-05-01","Workers' Day","NG",2006 +"2006-05-29","Democracy Day","NG",2006 +"2006-10-01","Independence Day","NG",2006 +"2006-10-23","Eid-el-Fitr* (*estimated)","NG",2006 +"2006-10-24","Eid-el-Fitr Holiday* (*estimated)","NG",2006 +"2006-12-25","Christmas Day","NG",2006 +"2006-12-26","Boxing Day","NG",2006 +"2006-12-31","Eid-el-Kabir* (*estimated)","NG",2006 +"2007-01-01","Eid-el-Kabir Holiday* (*estimated)","NG",2007 +"2007-01-01","New Year's Day","NG",2007 +"2007-03-31","Eid-el-Mawlid* (*estimated)","NG",2007 +"2007-04-06","Good Friday","NG",2007 +"2007-04-09","Easter Monday","NG",2007 +"2007-05-01","Workers' Day","NG",2007 +"2007-05-29","Democracy Day","NG",2007 +"2007-10-01","Independence Day","NG",2007 +"2007-10-13","Eid-el-Fitr* (*estimated)","NG",2007 +"2007-10-14","Eid-el-Fitr Holiday* (*estimated)","NG",2007 +"2007-12-20","Eid-el-Kabir* (*estimated)","NG",2007 +"2007-12-21","Eid-el-Kabir Holiday* (*estimated)","NG",2007 +"2007-12-25","Christmas Day","NG",2007 +"2007-12-26","Boxing Day","NG",2007 +"2008-01-01","New Year's Day","NG",2008 +"2008-03-20","Eid-el-Mawlid* (*estimated)","NG",2008 +"2008-03-21","Good Friday","NG",2008 +"2008-03-24","Easter Monday","NG",2008 +"2008-05-01","Workers' Day","NG",2008 +"2008-05-29","Democracy Day","NG",2008 +"2008-10-01","Eid-el-Fitr* (*estimated)","NG",2008 +"2008-10-01","Independence Day","NG",2008 +"2008-10-02","Eid-el-Fitr Holiday* (*estimated)","NG",2008 +"2008-12-08","Eid-el-Kabir* (*estimated)","NG",2008 +"2008-12-09","Eid-el-Kabir Holiday* (*estimated)","NG",2008 +"2008-12-25","Christmas Day","NG",2008 +"2008-12-26","Boxing Day","NG",2008 +"2009-01-01","New Year's Day","NG",2009 +"2009-03-09","Eid-el-Mawlid* (*estimated)","NG",2009 +"2009-04-10","Good Friday","NG",2009 +"2009-04-13","Easter Monday","NG",2009 +"2009-05-01","Workers' Day","NG",2009 +"2009-05-29","Democracy Day","NG",2009 +"2009-09-20","Eid-el-Fitr* (*estimated)","NG",2009 +"2009-09-21","Eid-el-Fitr Holiday* (*estimated)","NG",2009 +"2009-10-01","Independence Day","NG",2009 +"2009-11-27","Eid-el-Kabir* (*estimated)","NG",2009 +"2009-11-28","Eid-el-Kabir Holiday* (*estimated)","NG",2009 +"2009-12-25","Christmas Day","NG",2009 +"2009-12-26","Boxing Day","NG",2009 +"2010-01-01","New Year's Day","NG",2010 +"2010-02-26","Eid-el-Mawlid* (*estimated)","NG",2010 +"2010-04-02","Good Friday","NG",2010 +"2010-04-05","Easter Monday","NG",2010 +"2010-05-01","Workers' Day","NG",2010 +"2010-05-29","Democracy Day","NG",2010 +"2010-09-10","Eid-el-Fitr* (*estimated)","NG",2010 +"2010-09-11","Eid-el-Fitr Holiday* (*estimated)","NG",2010 +"2010-10-01","Independence Day","NG",2010 +"2010-11-16","Eid-el-Kabir* (*estimated)","NG",2010 +"2010-11-17","Eid-el-Kabir Holiday* (*estimated)","NG",2010 +"2010-12-25","Christmas Day","NG",2010 +"2010-12-26","Boxing Day","NG",2010 +"2011-01-01","New Year's Day","NG",2011 +"2011-02-15","Eid-el-Mawlid* (*estimated)","NG",2011 +"2011-04-22","Good Friday","NG",2011 +"2011-04-25","Easter Monday","NG",2011 +"2011-05-01","Workers' Day","NG",2011 +"2011-05-29","Democracy Day","NG",2011 +"2011-08-30","Eid-el-Fitr* (*estimated)","NG",2011 +"2011-08-31","Eid-el-Fitr Holiday* (*estimated)","NG",2011 +"2011-10-01","Independence Day","NG",2011 +"2011-11-06","Eid-el-Kabir* (*estimated)","NG",2011 +"2011-11-07","Eid-el-Kabir Holiday* (*estimated)","NG",2011 +"2011-12-25","Christmas Day","NG",2011 +"2011-12-26","Boxing Day","NG",2011 +"2012-01-01","New Year's Day","NG",2012 +"2012-02-04","Eid-el-Mawlid* (*estimated)","NG",2012 +"2012-04-06","Good Friday","NG",2012 +"2012-04-09","Easter Monday","NG",2012 +"2012-05-01","Workers' Day","NG",2012 +"2012-05-29","Democracy Day","NG",2012 +"2012-08-19","Eid-el-Fitr* (*estimated)","NG",2012 +"2012-08-20","Eid-el-Fitr Holiday* (*estimated)","NG",2012 +"2012-10-01","Independence Day","NG",2012 +"2012-10-26","Eid-el-Kabir* (*estimated)","NG",2012 +"2012-10-27","Eid-el-Kabir Holiday* (*estimated)","NG",2012 +"2012-12-25","Christmas Day","NG",2012 +"2012-12-26","Boxing Day","NG",2012 +"2013-01-01","New Year's Day","NG",2013 +"2013-01-24","Eid-el-Mawlid* (*estimated)","NG",2013 +"2013-03-29","Good Friday","NG",2013 +"2013-04-01","Easter Monday","NG",2013 +"2013-05-01","Workers' Day","NG",2013 +"2013-05-29","Democracy Day","NG",2013 +"2013-08-08","Eid-el-Fitr* (*estimated)","NG",2013 +"2013-08-09","Eid-el-Fitr Holiday* (*estimated)","NG",2013 +"2013-10-01","Independence Day","NG",2013 +"2013-10-15","Eid-el-Kabir* (*estimated)","NG",2013 +"2013-10-16","Eid-el-Kabir Holiday* (*estimated)","NG",2013 +"2013-12-25","Christmas Day","NG",2013 +"2013-12-26","Boxing Day","NG",2013 +"2014-01-01","New Year's Day","NG",2014 +"2014-01-13","Eid-el-Mawlid* (*estimated)","NG",2014 +"2014-04-18","Good Friday","NG",2014 +"2014-04-21","Easter Monday","NG",2014 +"2014-05-01","Workers' Day","NG",2014 +"2014-05-29","Democracy Day","NG",2014 +"2014-07-28","Eid-el-Fitr* (*estimated)","NG",2014 +"2014-07-29","Eid-el-Fitr Holiday* (*estimated)","NG",2014 +"2014-10-01","Independence Day","NG",2014 +"2014-10-04","Eid-el-Kabir* (*estimated)","NG",2014 +"2014-10-05","Eid-el-Kabir Holiday* (*estimated)","NG",2014 +"2014-12-25","Christmas Day","NG",2014 +"2014-12-26","Boxing Day","NG",2014 +"2015-01-01","New Year's Day","NG",2015 +"2015-01-03","Eid-el-Mawlid* (*estimated)","NG",2015 +"2015-04-03","Good Friday","NG",2015 +"2015-04-06","Easter Monday","NG",2015 +"2015-05-01","Workers' Day","NG",2015 +"2015-05-29","Democracy Day","NG",2015 +"2015-07-17","Eid-el-Fitr* (*estimated)","NG",2015 +"2015-07-18","Eid-el-Fitr Holiday* (*estimated)","NG",2015 +"2015-09-23","Eid-el-Kabir* (*estimated)","NG",2015 +"2015-09-24","Eid-el-Kabir Holiday* (*estimated)","NG",2015 +"2015-10-01","Independence Day","NG",2015 +"2015-12-23","Eid-el-Mawlid* (*estimated)","NG",2015 +"2015-12-25","Christmas Day","NG",2015 +"2015-12-26","Boxing Day","NG",2015 +"2016-01-01","New Year's Day","NG",2016 +"2016-03-25","Good Friday","NG",2016 +"2016-03-28","Easter Monday","NG",2016 +"2016-05-01","Workers' Day","NG",2016 +"2016-05-02","Workers' Day (Observed)","NG",2016 +"2016-05-29","Democracy Day","NG",2016 +"2016-05-30","Democracy Day (Observed)","NG",2016 +"2016-07-06","Eid-el-Fitr* (*estimated)","NG",2016 +"2016-07-07","Eid-el-Fitr Holiday* (*estimated)","NG",2016 +"2016-09-11","Eid-el-Kabir* (*estimated)","NG",2016 +"2016-09-12","Eid-el-Kabir Holiday* (*estimated)","NG",2016 +"2016-09-13","Eid-el-Kabir* (*estimated) (Observed)","NG",2016 +"2016-10-01","Independence Day","NG",2016 +"2016-10-03","Independence Day (Observed)","NG",2016 +"2016-12-11","Eid-el-Mawlid* (*estimated)","NG",2016 +"2016-12-12","Eid-el-Mawlid* (*estimated) (Observed)","NG",2016 +"2016-12-25","Christmas Day","NG",2016 +"2016-12-26","Boxing Day","NG",2016 +"2016-12-27","Christmas Day (Observed)","NG",2016 +"2017-01-01","New Year's Day","NG",2017 +"2017-01-02","New Year's Day (Observed)","NG",2017 +"2017-04-14","Good Friday","NG",2017 +"2017-04-17","Easter Monday","NG",2017 +"2017-05-01","Workers' Day","NG",2017 +"2017-05-29","Democracy Day","NG",2017 +"2017-06-25","Eid-el-Fitr* (*estimated)","NG",2017 +"2017-06-26","Eid-el-Fitr Holiday* (*estimated)","NG",2017 +"2017-06-27","Eid-el-Fitr* (*estimated) (Observed)","NG",2017 +"2017-09-01","Eid-el-Kabir* (*estimated)","NG",2017 +"2017-09-02","Eid-el-Kabir Holiday* (*estimated)","NG",2017 +"2017-09-04","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2017 +"2017-10-01","Independence Day","NG",2017 +"2017-10-02","Independence Day (Observed)","NG",2017 +"2017-11-30","Eid-el-Mawlid* (*estimated)","NG",2017 +"2017-12-25","Christmas Day","NG",2017 +"2017-12-26","Boxing Day","NG",2017 +"2018-01-01","New Year's Day","NG",2018 +"2018-03-30","Good Friday","NG",2018 +"2018-04-02","Easter Monday","NG",2018 +"2018-05-01","Workers' Day","NG",2018 +"2018-05-29","Democracy Day","NG",2018 +"2018-06-15","Eid-el-Fitr* (*estimated)","NG",2018 +"2018-06-16","Eid-el-Fitr Holiday* (*estimated)","NG",2018 +"2018-06-18","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2018 +"2018-08-21","Eid-el-Kabir* (*estimated)","NG",2018 +"2018-08-22","Eid-el-Kabir Holiday* (*estimated)","NG",2018 +"2018-10-01","Independence Day","NG",2018 +"2018-11-20","Eid-el-Mawlid* (*estimated)","NG",2018 +"2018-12-25","Christmas Day","NG",2018 +"2018-12-26","Boxing Day","NG",2018 +"2019-01-01","New Year's Day","NG",2019 +"2019-02-22","Public Holiday for Elections","NG",2019 +"2019-04-19","Good Friday","NG",2019 +"2019-04-22","Easter Monday","NG",2019 +"2019-05-01","Workers' Day","NG",2019 +"2019-05-29","Presidential Inauguration Day","NG",2019 +"2019-06-04","Eid-el-Fitr* (*estimated)","NG",2019 +"2019-06-05","Eid-el-Fitr Holiday* (*estimated)","NG",2019 +"2019-06-12","Democracy Day","NG",2019 +"2019-08-11","Eid-el-Kabir* (*estimated)","NG",2019 +"2019-08-12","Eid-el-Kabir Holiday* (*estimated)","NG",2019 +"2019-08-13","Eid-el-Kabir* (*estimated) (Observed)","NG",2019 +"2019-10-01","Independence Day","NG",2019 +"2019-11-09","Eid-el-Mawlid* (*estimated)","NG",2019 +"2019-11-11","Eid-el-Mawlid* (*estimated) (Observed)","NG",2019 +"2019-12-25","Christmas Day","NG",2019 +"2019-12-26","Boxing Day","NG",2019 +"2020-01-01","New Year's Day","NG",2020 +"2020-04-10","Good Friday","NG",2020 +"2020-04-13","Easter Monday","NG",2020 +"2020-05-01","Workers' Day","NG",2020 +"2020-05-24","Eid-el-Fitr* (*estimated)","NG",2020 +"2020-05-25","Eid-el-Fitr Holiday* (*estimated)","NG",2020 +"2020-05-26","Eid-el-Fitr* (*estimated) (Observed)","NG",2020 +"2020-06-12","Democracy Day","NG",2020 +"2020-07-31","Eid-el-Kabir* (*estimated)","NG",2020 +"2020-08-01","Eid-el-Kabir Holiday* (*estimated)","NG",2020 +"2020-08-03","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2020 +"2020-10-01","Independence Day","NG",2020 +"2020-10-29","Eid-el-Mawlid* (*estimated)","NG",2020 +"2020-12-25","Christmas Day","NG",2020 +"2020-12-26","Boxing Day","NG",2020 +"2020-12-28","Boxing Day (Observed)","NG",2020 +"2021-01-01","New Year's Day","NG",2021 +"2021-04-02","Good Friday","NG",2021 +"2021-04-05","Easter Monday","NG",2021 +"2021-05-01","Workers' Day","NG",2021 +"2021-05-03","Workers' Day (Observed)","NG",2021 +"2021-05-13","Eid-el-Fitr* (*estimated)","NG",2021 +"2021-05-14","Eid-el-Fitr Holiday* (*estimated)","NG",2021 +"2021-06-12","Democracy Day","NG",2021 +"2021-06-14","Democracy Day (Observed)","NG",2021 +"2021-07-20","Eid-el-Kabir* (*estimated)","NG",2021 +"2021-07-21","Eid-el-Kabir Holiday* (*estimated)","NG",2021 +"2021-10-01","Independence Day","NG",2021 +"2021-10-18","Eid-el-Mawlid* (*estimated)","NG",2021 +"2021-12-25","Christmas Day","NG",2021 +"2021-12-26","Boxing Day","NG",2021 +"2021-12-27","Christmas Day (Observed)","NG",2021 +"2021-12-28","Boxing Day (Observed)","NG",2021 +"2022-01-01","New Year's Day","NG",2022 +"2022-01-03","New Year's Day (Observed)","NG",2022 +"2022-04-15","Good Friday","NG",2022 +"2022-04-18","Easter Monday","NG",2022 +"2022-05-01","Workers' Day","NG",2022 +"2022-05-02","Eid-el-Fitr* (*estimated)","NG",2022 +"2022-05-03","Eid-el-Fitr Holiday* (*estimated)","NG",2022 +"2022-05-04","Workers' Day (Observed)","NG",2022 +"2022-06-12","Democracy Day","NG",2022 +"2022-06-13","Democracy Day (Observed)","NG",2022 +"2022-07-09","Eid-el-Kabir* (*estimated)","NG",2022 +"2022-07-10","Eid-el-Kabir Holiday* (*estimated)","NG",2022 +"2022-07-11","Eid-el-Kabir* (*estimated) (Observed)","NG",2022 +"2022-07-12","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2022 +"2022-10-01","Independence Day","NG",2022 +"2022-10-03","Independence Day (Observed)","NG",2022 +"2022-10-08","Eid-el-Mawlid* (*estimated)","NG",2022 +"2022-10-10","Eid-el-Mawlid* (*estimated) (Observed)","NG",2022 +"2022-12-25","Christmas Day","NG",2022 +"2022-12-26","Boxing Day","NG",2022 +"2022-12-27","Christmas Day (Observed)","NG",2022 +"2023-01-01","New Year's Day","NG",2023 +"2023-01-02","New Year's Day (Observed)","NG",2023 +"2023-04-07","Good Friday","NG",2023 +"2023-04-10","Easter Monday","NG",2023 +"2023-04-21","Eid-el-Fitr* (*estimated)","NG",2023 +"2023-04-22","Eid-el-Fitr Holiday* (*estimated)","NG",2023 +"2023-04-24","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2023 +"2023-05-01","Workers' Day","NG",2023 +"2023-06-12","Democracy Day","NG",2023 +"2023-06-28","Eid-el-Kabir* (*estimated)","NG",2023 +"2023-06-29","Eid-el-Kabir Holiday* (*estimated)","NG",2023 +"2023-09-27","Eid-el-Mawlid* (*estimated)","NG",2023 +"2023-10-01","Independence Day","NG",2023 +"2023-10-02","Independence Day (Observed)","NG",2023 +"2023-12-25","Christmas Day","NG",2023 +"2023-12-26","Boxing Day","NG",2023 +"2024-01-01","New Year's Day","NG",2024 +"2024-03-29","Good Friday","NG",2024 +"2024-04-01","Easter Monday","NG",2024 +"2024-04-10","Eid-el-Fitr* (*estimated)","NG",2024 +"2024-04-11","Eid-el-Fitr Holiday* (*estimated)","NG",2024 +"2024-05-01","Workers' Day","NG",2024 +"2024-06-12","Democracy Day","NG",2024 +"2024-06-16","Eid-el-Kabir* (*estimated)","NG",2024 +"2024-06-17","Eid-el-Kabir Holiday* (*estimated)","NG",2024 +"2024-06-18","Eid-el-Kabir* (*estimated) (Observed)","NG",2024 +"2024-09-15","Eid-el-Mawlid* (*estimated)","NG",2024 +"2024-09-16","Eid-el-Mawlid* (*estimated) (Observed)","NG",2024 +"2024-10-01","Independence Day","NG",2024 +"2024-12-25","Christmas Day","NG",2024 +"2024-12-26","Boxing Day","NG",2024 +"2025-01-01","New Year's Day","NG",2025 +"2025-03-30","Eid-el-Fitr* (*estimated)","NG",2025 +"2025-03-31","Eid-el-Fitr Holiday* (*estimated)","NG",2025 +"2025-04-01","Eid-el-Fitr* (*estimated) (Observed)","NG",2025 +"2025-04-18","Good Friday","NG",2025 +"2025-04-21","Easter Monday","NG",2025 +"2025-05-01","Workers' Day","NG",2025 +"2025-06-06","Eid-el-Kabir* (*estimated)","NG",2025 +"2025-06-07","Eid-el-Kabir Holiday* (*estimated)","NG",2025 +"2025-06-09","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2025 +"2025-06-12","Democracy Day","NG",2025 +"2025-09-04","Eid-el-Mawlid* (*estimated)","NG",2025 +"2025-10-01","Independence Day","NG",2025 +"2025-12-25","Christmas Day","NG",2025 +"2025-12-26","Boxing Day","NG",2025 +"2026-01-01","New Year's Day","NG",2026 +"2026-03-20","Eid-el-Fitr* (*estimated)","NG",2026 +"2026-03-21","Eid-el-Fitr Holiday* (*estimated)","NG",2026 +"2026-03-23","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2026 +"2026-04-03","Good Friday","NG",2026 +"2026-04-06","Easter Monday","NG",2026 +"2026-05-01","Workers' Day","NG",2026 +"2026-05-27","Eid-el-Kabir* (*estimated)","NG",2026 +"2026-05-28","Eid-el-Kabir Holiday* (*estimated)","NG",2026 +"2026-06-12","Democracy Day","NG",2026 +"2026-08-25","Eid-el-Mawlid* (*estimated)","NG",2026 +"2026-10-01","Independence Day","NG",2026 +"2026-12-25","Christmas Day","NG",2026 +"2026-12-26","Boxing Day","NG",2026 +"2026-12-28","Boxing Day (Observed)","NG",2026 +"2027-01-01","New Year's Day","NG",2027 +"2027-03-09","Eid-el-Fitr* (*estimated)","NG",2027 +"2027-03-10","Eid-el-Fitr Holiday* (*estimated)","NG",2027 +"2027-03-26","Good Friday","NG",2027 +"2027-03-29","Easter Monday","NG",2027 +"2027-05-01","Workers' Day","NG",2027 +"2027-05-03","Workers' Day (Observed)","NG",2027 +"2027-05-16","Eid-el-Kabir* (*estimated)","NG",2027 +"2027-05-17","Eid-el-Kabir Holiday* (*estimated)","NG",2027 +"2027-05-18","Eid-el-Kabir* (*estimated) (Observed)","NG",2027 +"2027-06-12","Democracy Day","NG",2027 +"2027-06-14","Democracy Day (Observed)","NG",2027 +"2027-08-14","Eid-el-Mawlid* (*estimated)","NG",2027 +"2027-08-16","Eid-el-Mawlid* (*estimated) (Observed)","NG",2027 +"2027-10-01","Independence Day","NG",2027 +"2027-12-25","Christmas Day","NG",2027 +"2027-12-26","Boxing Day","NG",2027 +"2027-12-27","Christmas Day (Observed)","NG",2027 +"2027-12-28","Boxing Day (Observed)","NG",2027 +"2028-01-01","New Year's Day","NG",2028 +"2028-01-03","New Year's Day (Observed)","NG",2028 +"2028-02-26","Eid-el-Fitr* (*estimated)","NG",2028 +"2028-02-27","Eid-el-Fitr Holiday* (*estimated)","NG",2028 +"2028-02-28","Eid-el-Fitr* (*estimated) (Observed)","NG",2028 +"2028-02-29","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2028 +"2028-04-14","Good Friday","NG",2028 +"2028-04-17","Easter Monday","NG",2028 +"2028-05-01","Workers' Day","NG",2028 +"2028-05-05","Eid-el-Kabir* (*estimated)","NG",2028 +"2028-05-06","Eid-el-Kabir Holiday* (*estimated)","NG",2028 +"2028-05-08","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2028 +"2028-06-12","Democracy Day","NG",2028 +"2028-08-03","Eid-el-Mawlid* (*estimated)","NG",2028 +"2028-10-01","Independence Day","NG",2028 +"2028-10-02","Independence Day (Observed)","NG",2028 +"2028-12-25","Christmas Day","NG",2028 +"2028-12-26","Boxing Day","NG",2028 +"2029-01-01","New Year's Day","NG",2029 +"2029-02-14","Eid-el-Fitr* (*estimated)","NG",2029 +"2029-02-15","Eid-el-Fitr Holiday* (*estimated)","NG",2029 +"2029-03-30","Good Friday","NG",2029 +"2029-04-02","Easter Monday","NG",2029 +"2029-04-24","Eid-el-Kabir* (*estimated)","NG",2029 +"2029-04-25","Eid-el-Kabir Holiday* (*estimated)","NG",2029 +"2029-05-01","Workers' Day","NG",2029 +"2029-06-12","Democracy Day","NG",2029 +"2029-07-24","Eid-el-Mawlid* (*estimated)","NG",2029 +"2029-10-01","Independence Day","NG",2029 +"2029-12-25","Christmas Day","NG",2029 +"2029-12-26","Boxing Day","NG",2029 +"2030-01-01","New Year's Day","NG",2030 +"2030-02-04","Eid-el-Fitr* (*estimated)","NG",2030 +"2030-02-05","Eid-el-Fitr Holiday* (*estimated)","NG",2030 +"2030-04-13","Eid-el-Kabir* (*estimated)","NG",2030 +"2030-04-14","Eid-el-Kabir Holiday* (*estimated)","NG",2030 +"2030-04-15","Eid-el-Kabir* (*estimated) (Observed)","NG",2030 +"2030-04-16","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2030 +"2030-04-19","Good Friday","NG",2030 +"2030-04-22","Easter Monday","NG",2030 +"2030-05-01","Workers' Day","NG",2030 +"2030-06-12","Democracy Day","NG",2030 +"2030-07-13","Eid-el-Mawlid* (*estimated)","NG",2030 +"2030-07-15","Eid-el-Mawlid* (*estimated) (Observed)","NG",2030 +"2030-10-01","Independence Day","NG",2030 +"2030-12-25","Christmas Day","NG",2030 +"2030-12-26","Boxing Day","NG",2030 +"2031-01-01","New Year's Day","NG",2031 +"2031-01-24","Eid-el-Fitr* (*estimated)","NG",2031 +"2031-01-25","Eid-el-Fitr Holiday* (*estimated)","NG",2031 +"2031-01-27","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2031 +"2031-04-02","Eid-el-Kabir* (*estimated)","NG",2031 +"2031-04-03","Eid-el-Kabir Holiday* (*estimated)","NG",2031 +"2031-04-11","Good Friday","NG",2031 +"2031-04-14","Easter Monday","NG",2031 +"2031-05-01","Workers' Day","NG",2031 +"2031-06-12","Democracy Day","NG",2031 +"2031-07-02","Eid-el-Mawlid* (*estimated)","NG",2031 +"2031-10-01","Independence Day","NG",2031 +"2031-12-25","Christmas Day","NG",2031 +"2031-12-26","Boxing Day","NG",2031 +"2032-01-01","New Year's Day","NG",2032 +"2032-01-14","Eid-el-Fitr* (*estimated)","NG",2032 +"2032-01-15","Eid-el-Fitr Holiday* (*estimated)","NG",2032 +"2032-03-22","Eid-el-Kabir* (*estimated)","NG",2032 +"2032-03-23","Eid-el-Kabir Holiday* (*estimated)","NG",2032 +"2032-03-26","Good Friday","NG",2032 +"2032-03-29","Easter Monday","NG",2032 +"2032-05-01","Workers' Day","NG",2032 +"2032-05-03","Workers' Day (Observed)","NG",2032 +"2032-06-12","Democracy Day","NG",2032 +"2032-06-14","Democracy Day (Observed)","NG",2032 +"2032-06-20","Eid-el-Mawlid* (*estimated)","NG",2032 +"2032-06-21","Eid-el-Mawlid* (*estimated) (Observed)","NG",2032 +"2032-10-01","Independence Day","NG",2032 +"2032-12-25","Christmas Day","NG",2032 +"2032-12-26","Boxing Day","NG",2032 +"2032-12-27","Christmas Day (Observed)","NG",2032 +"2032-12-28","Boxing Day (Observed)","NG",2032 +"2033-01-01","New Year's Day","NG",2033 +"2033-01-02","Eid-el-Fitr* (*estimated)","NG",2033 +"2033-01-03","Eid-el-Fitr Holiday* (*estimated)","NG",2033 +"2033-01-04","New Year's Day (Observed)","NG",2033 +"2033-01-05","Eid-el-Fitr* (*estimated) (Observed)","NG",2033 +"2033-03-11","Eid-el-Kabir* (*estimated)","NG",2033 +"2033-03-12","Eid-el-Kabir Holiday* (*estimated)","NG",2033 +"2033-03-14","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2033 +"2033-04-15","Good Friday","NG",2033 +"2033-04-18","Easter Monday","NG",2033 +"2033-05-01","Workers' Day","NG",2033 +"2033-05-02","Workers' Day (Observed)","NG",2033 +"2033-06-09","Eid-el-Mawlid* (*estimated)","NG",2033 +"2033-06-12","Democracy Day","NG",2033 +"2033-06-13","Democracy Day (Observed)","NG",2033 +"2033-10-01","Independence Day","NG",2033 +"2033-10-03","Independence Day (Observed)","NG",2033 +"2033-12-23","Eid-el-Fitr* (*estimated)","NG",2033 +"2033-12-24","Eid-el-Fitr Holiday* (*estimated)","NG",2033 +"2033-12-25","Christmas Day","NG",2033 +"2033-12-26","Boxing Day","NG",2033 +"2033-12-27","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2033 +"2033-12-28","Christmas Day (Observed)","NG",2033 +"2034-01-01","New Year's Day","NG",2034 +"2034-01-02","New Year's Day (Observed)","NG",2034 +"2034-03-01","Eid-el-Kabir* (*estimated)","NG",2034 +"2034-03-02","Eid-el-Kabir Holiday* (*estimated)","NG",2034 +"2034-04-07","Good Friday","NG",2034 +"2034-04-10","Easter Monday","NG",2034 +"2034-05-01","Workers' Day","NG",2034 +"2034-05-30","Eid-el-Mawlid* (*estimated)","NG",2034 +"2034-06-12","Democracy Day","NG",2034 +"2034-10-01","Independence Day","NG",2034 +"2034-10-02","Independence Day (Observed)","NG",2034 +"2034-12-12","Eid-el-Fitr* (*estimated)","NG",2034 +"2034-12-13","Eid-el-Fitr Holiday* (*estimated)","NG",2034 +"2034-12-25","Christmas Day","NG",2034 +"2034-12-26","Boxing Day","NG",2034 +"2035-01-01","New Year's Day","NG",2035 +"2035-02-18","Eid-el-Kabir* (*estimated)","NG",2035 +"2035-02-19","Eid-el-Kabir Holiday* (*estimated)","NG",2035 +"2035-02-20","Eid-el-Kabir* (*estimated) (Observed)","NG",2035 +"2035-03-23","Good Friday","NG",2035 +"2035-03-26","Easter Monday","NG",2035 +"2035-05-01","Workers' Day","NG",2035 +"2035-05-20","Eid-el-Mawlid* (*estimated)","NG",2035 +"2035-05-21","Eid-el-Mawlid* (*estimated) (Observed)","NG",2035 +"2035-06-12","Democracy Day","NG",2035 +"2035-10-01","Independence Day","NG",2035 +"2035-12-01","Eid-el-Fitr* (*estimated)","NG",2035 +"2035-12-02","Eid-el-Fitr Holiday* (*estimated)","NG",2035 +"2035-12-03","Eid-el-Fitr* (*estimated) (Observed)","NG",2035 +"2035-12-04","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2035 +"2035-12-25","Christmas Day","NG",2035 +"2035-12-26","Boxing Day","NG",2035 +"2036-01-01","New Year's Day","NG",2036 +"2036-02-07","Eid-el-Kabir* (*estimated)","NG",2036 +"2036-02-08","Eid-el-Kabir Holiday* (*estimated)","NG",2036 +"2036-04-11","Good Friday","NG",2036 +"2036-04-14","Easter Monday","NG",2036 +"2036-05-01","Workers' Day","NG",2036 +"2036-05-08","Eid-el-Mawlid* (*estimated)","NG",2036 +"2036-06-12","Democracy Day","NG",2036 +"2036-10-01","Independence Day","NG",2036 +"2036-11-19","Eid-el-Fitr* (*estimated)","NG",2036 +"2036-11-20","Eid-el-Fitr Holiday* (*estimated)","NG",2036 +"2036-12-25","Christmas Day","NG",2036 +"2036-12-26","Boxing Day","NG",2036 +"2037-01-01","New Year's Day","NG",2037 +"2037-01-26","Eid-el-Kabir* (*estimated)","NG",2037 +"2037-01-27","Eid-el-Kabir Holiday* (*estimated)","NG",2037 +"2037-04-03","Good Friday","NG",2037 +"2037-04-06","Easter Monday","NG",2037 +"2037-04-28","Eid-el-Mawlid* (*estimated)","NG",2037 +"2037-05-01","Workers' Day","NG",2037 +"2037-06-12","Democracy Day","NG",2037 +"2037-10-01","Independence Day","NG",2037 +"2037-11-08","Eid-el-Fitr* (*estimated)","NG",2037 +"2037-11-09","Eid-el-Fitr Holiday* (*estimated)","NG",2037 +"2037-11-10","Eid-el-Fitr* (*estimated) (Observed)","NG",2037 +"2037-12-25","Christmas Day","NG",2037 +"2037-12-26","Boxing Day","NG",2037 +"2037-12-28","Boxing Day (Observed)","NG",2037 +"2038-01-01","New Year's Day","NG",2038 +"2038-01-16","Eid-el-Kabir* (*estimated)","NG",2038 +"2038-01-17","Eid-el-Kabir Holiday* (*estimated)","NG",2038 +"2038-01-18","Eid-el-Kabir* (*estimated) (Observed)","NG",2038 +"2038-01-19","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2038 +"2038-04-17","Eid-el-Mawlid* (*estimated)","NG",2038 +"2038-04-19","Eid-el-Mawlid* (*estimated) (Observed)","NG",2038 +"2038-04-23","Good Friday","NG",2038 +"2038-04-26","Easter Monday","NG",2038 +"2038-05-01","Workers' Day","NG",2038 +"2038-05-03","Workers' Day (Observed)","NG",2038 +"2038-06-12","Democracy Day","NG",2038 +"2038-06-14","Democracy Day (Observed)","NG",2038 +"2038-10-01","Independence Day","NG",2038 +"2038-10-29","Eid-el-Fitr* (*estimated)","NG",2038 +"2038-10-30","Eid-el-Fitr Holiday* (*estimated)","NG",2038 +"2038-11-01","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2038 +"2038-12-25","Christmas Day","NG",2038 +"2038-12-26","Boxing Day","NG",2038 +"2038-12-27","Christmas Day (Observed)","NG",2038 +"2038-12-28","Boxing Day (Observed)","NG",2038 +"2039-01-01","New Year's Day","NG",2039 +"2039-01-03","New Year's Day (Observed)","NG",2039 +"2039-01-05","Eid-el-Kabir* (*estimated)","NG",2039 +"2039-01-06","Eid-el-Kabir Holiday* (*estimated)","NG",2039 +"2039-04-06","Eid-el-Mawlid* (*estimated)","NG",2039 +"2039-04-08","Good Friday","NG",2039 +"2039-04-11","Easter Monday","NG",2039 +"2039-05-01","Workers' Day","NG",2039 +"2039-05-02","Workers' Day (Observed)","NG",2039 +"2039-06-12","Democracy Day","NG",2039 +"2039-06-13","Democracy Day (Observed)","NG",2039 +"2039-10-01","Independence Day","NG",2039 +"2039-10-03","Independence Day (Observed)","NG",2039 +"2039-10-19","Eid-el-Fitr* (*estimated)","NG",2039 +"2039-10-20","Eid-el-Fitr Holiday* (*estimated)","NG",2039 +"2039-12-25","Christmas Day","NG",2039 +"2039-12-26","Boxing Day","NG",2039 +"2039-12-26","Eid-el-Kabir* (*estimated)","NG",2039 +"2039-12-27","Eid-el-Kabir Holiday* (*estimated)","NG",2039 +"2039-12-28","Christmas Day (Observed)","NG",2039 +"2040-01-01","New Year's Day","NG",2040 +"2040-01-02","New Year's Day (Observed)","NG",2040 +"2040-03-25","Eid-el-Mawlid* (*estimated)","NG",2040 +"2040-03-26","Eid-el-Mawlid* (*estimated) (Observed)","NG",2040 +"2040-03-30","Good Friday","NG",2040 +"2040-04-02","Easter Monday","NG",2040 +"2040-05-01","Workers' Day","NG",2040 +"2040-06-12","Democracy Day","NG",2040 +"2040-10-01","Independence Day","NG",2040 +"2040-10-07","Eid-el-Fitr* (*estimated)","NG",2040 +"2040-10-08","Eid-el-Fitr Holiday* (*estimated)","NG",2040 +"2040-10-09","Eid-el-Fitr* (*estimated) (Observed)","NG",2040 +"2040-12-14","Eid-el-Kabir* (*estimated)","NG",2040 +"2040-12-15","Eid-el-Kabir Holiday* (*estimated)","NG",2040 +"2040-12-17","Eid-el-Kabir Holiday* (*estimated) (Observed)","NG",2040 +"2040-12-25","Christmas Day","NG",2040 +"2040-12-26","Boxing Day","NG",2040 +"2041-01-01","New Year's Day","NG",2041 +"2041-03-15","Eid-el-Mawlid* (*estimated)","NG",2041 +"2041-04-19","Good Friday","NG",2041 +"2041-04-22","Easter Monday","NG",2041 +"2041-05-01","Workers' Day","NG",2041 +"2041-06-12","Democracy Day","NG",2041 +"2041-09-26","Eid-el-Fitr* (*estimated)","NG",2041 +"2041-09-27","Eid-el-Fitr Holiday* (*estimated)","NG",2041 +"2041-10-01","Independence Day","NG",2041 +"2041-12-04","Eid-el-Kabir* (*estimated)","NG",2041 +"2041-12-05","Eid-el-Kabir Holiday* (*estimated)","NG",2041 +"2041-12-25","Christmas Day","NG",2041 +"2041-12-26","Boxing Day","NG",2041 +"2042-01-01","New Year's Day","NG",2042 +"2042-03-04","Eid-el-Mawlid* (*estimated)","NG",2042 +"2042-04-04","Good Friday","NG",2042 +"2042-04-07","Easter Monday","NG",2042 +"2042-05-01","Workers' Day","NG",2042 +"2042-06-12","Democracy Day","NG",2042 +"2042-09-15","Eid-el-Fitr* (*estimated)","NG",2042 +"2042-09-16","Eid-el-Fitr Holiday* (*estimated)","NG",2042 +"2042-10-01","Independence Day","NG",2042 +"2042-11-23","Eid-el-Kabir* (*estimated)","NG",2042 +"2042-11-24","Eid-el-Kabir Holiday* (*estimated)","NG",2042 +"2042-11-25","Eid-el-Kabir* (*estimated) (Observed)","NG",2042 +"2042-12-25","Christmas Day","NG",2042 +"2042-12-26","Boxing Day","NG",2042 +"2043-01-01","New Year's Day","NG",2043 +"2043-02-22","Eid-el-Mawlid* (*estimated)","NG",2043 +"2043-02-23","Eid-el-Mawlid* (*estimated) (Observed)","NG",2043 +"2043-03-27","Good Friday","NG",2043 +"2043-03-30","Easter Monday","NG",2043 +"2043-05-01","Workers' Day","NG",2043 +"2043-06-12","Democracy Day","NG",2043 +"2043-09-04","Eid-el-Fitr* (*estimated)","NG",2043 +"2043-09-05","Eid-el-Fitr Holiday* (*estimated)","NG",2043 +"2043-09-07","Eid-el-Fitr Holiday* (*estimated) (Observed)","NG",2043 +"2043-10-01","Independence Day","NG",2043 +"2043-11-12","Eid-el-Kabir* (*estimated)","NG",2043 +"2043-11-13","Eid-el-Kabir Holiday* (*estimated)","NG",2043 +"2043-12-25","Christmas Day","NG",2043 +"2043-12-26","Boxing Day","NG",2043 +"2043-12-28","Boxing Day (Observed)","NG",2043 +"2044-01-01","New Year's Day","NG",2044 +"2044-02-11","Eid-el-Mawlid* (*estimated)","NG",2044 +"2044-04-15","Good Friday","NG",2044 +"2044-04-18","Easter Monday","NG",2044 +"2044-05-01","Workers' Day","NG",2044 +"2044-05-02","Workers' Day (Observed)","NG",2044 +"2044-06-12","Democracy Day","NG",2044 +"2044-06-13","Democracy Day (Observed)","NG",2044 +"2044-08-24","Eid-el-Fitr* (*estimated)","NG",2044 +"2044-08-25","Eid-el-Fitr Holiday* (*estimated)","NG",2044 +"2044-10-01","Independence Day","NG",2044 +"2044-10-03","Independence Day (Observed)","NG",2044 +"2044-10-31","Eid-el-Kabir* (*estimated)","NG",2044 +"2044-11-01","Eid-el-Kabir Holiday* (*estimated)","NG",2044 +"2044-12-25","Christmas Day","NG",2044 +"2044-12-26","Boxing Day","NG",2044 +"2044-12-27","Christmas Day (Observed)","NG",2044 +"1995-01-01","New Year's Day","NI",1995 +"1995-04-13","Maundy Thursday","NI",1995 +"1995-04-14","Good Friday","NI",1995 +"1995-05-01","Labour Day","NI",1995 +"1995-07-19","Revolution Day","NI",1995 +"1995-08-01","Descent of Saint Dominic","NI",1995 +"1995-08-10","Ascent of Saint Dominic","NI",1995 +"1995-09-14","Battle of San Jacinto Day","NI",1995 +"1995-09-15","Independence Day","NI",1995 +"1995-12-08","Virgin's Day","NI",1995 +"1995-12-25","Christmas","NI",1995 +"1996-01-01","New Year's Day","NI",1996 +"1996-04-04","Maundy Thursday","NI",1996 +"1996-04-05","Good Friday","NI",1996 +"1996-05-01","Labour Day","NI",1996 +"1996-07-19","Revolution Day","NI",1996 +"1996-08-01","Descent of Saint Dominic","NI",1996 +"1996-08-10","Ascent of Saint Dominic","NI",1996 +"1996-09-14","Battle of San Jacinto Day","NI",1996 +"1996-09-15","Independence Day","NI",1996 +"1996-12-08","Virgin's Day","NI",1996 +"1996-12-25","Christmas","NI",1996 +"1997-01-01","New Year's Day","NI",1997 +"1997-03-27","Maundy Thursday","NI",1997 +"1997-03-28","Good Friday","NI",1997 +"1997-05-01","Labour Day","NI",1997 +"1997-07-19","Revolution Day","NI",1997 +"1997-08-01","Descent of Saint Dominic","NI",1997 +"1997-08-10","Ascent of Saint Dominic","NI",1997 +"1997-09-14","Battle of San Jacinto Day","NI",1997 +"1997-09-15","Independence Day","NI",1997 +"1997-12-08","Virgin's Day","NI",1997 +"1997-12-25","Christmas","NI",1997 +"1998-01-01","New Year's Day","NI",1998 +"1998-04-09","Maundy Thursday","NI",1998 +"1998-04-10","Good Friday","NI",1998 +"1998-05-01","Labour Day","NI",1998 +"1998-07-19","Revolution Day","NI",1998 +"1998-08-01","Descent of Saint Dominic","NI",1998 +"1998-08-10","Ascent of Saint Dominic","NI",1998 +"1998-09-14","Battle of San Jacinto Day","NI",1998 +"1998-09-15","Independence Day","NI",1998 +"1998-12-08","Virgin's Day","NI",1998 +"1998-12-25","Christmas","NI",1998 +"1999-01-01","New Year's Day","NI",1999 +"1999-04-01","Maundy Thursday","NI",1999 +"1999-04-02","Good Friday","NI",1999 +"1999-05-01","Labour Day","NI",1999 +"1999-07-19","Revolution Day","NI",1999 +"1999-08-01","Descent of Saint Dominic","NI",1999 +"1999-08-10","Ascent of Saint Dominic","NI",1999 +"1999-09-14","Battle of San Jacinto Day","NI",1999 +"1999-09-15","Independence Day","NI",1999 +"1999-12-08","Virgin's Day","NI",1999 +"1999-12-25","Christmas","NI",1999 +"2000-01-01","New Year's Day","NI",2000 +"2000-04-20","Maundy Thursday","NI",2000 +"2000-04-21","Good Friday","NI",2000 +"2000-05-01","Labour Day","NI",2000 +"2000-07-19","Revolution Day","NI",2000 +"2000-08-01","Descent of Saint Dominic","NI",2000 +"2000-08-10","Ascent of Saint Dominic","NI",2000 +"2000-09-14","Battle of San Jacinto Day","NI",2000 +"2000-09-15","Independence Day","NI",2000 +"2000-12-08","Virgin's Day","NI",2000 +"2000-12-25","Christmas","NI",2000 +"2001-01-01","New Year's Day","NI",2001 +"2001-04-12","Maundy Thursday","NI",2001 +"2001-04-13","Good Friday","NI",2001 +"2001-05-01","Labour Day","NI",2001 +"2001-07-19","Revolution Day","NI",2001 +"2001-08-01","Descent of Saint Dominic","NI",2001 +"2001-08-10","Ascent of Saint Dominic","NI",2001 +"2001-09-14","Battle of San Jacinto Day","NI",2001 +"2001-09-15","Independence Day","NI",2001 +"2001-12-08","Virgin's Day","NI",2001 +"2001-12-25","Christmas","NI",2001 +"2002-01-01","New Year's Day","NI",2002 +"2002-03-28","Maundy Thursday","NI",2002 +"2002-03-29","Good Friday","NI",2002 +"2002-05-01","Labour Day","NI",2002 +"2002-07-19","Revolution Day","NI",2002 +"2002-08-01","Descent of Saint Dominic","NI",2002 +"2002-08-10","Ascent of Saint Dominic","NI",2002 +"2002-09-14","Battle of San Jacinto Day","NI",2002 +"2002-09-15","Independence Day","NI",2002 +"2002-12-08","Virgin's Day","NI",2002 +"2002-12-25","Christmas","NI",2002 +"2003-01-01","New Year's Day","NI",2003 +"2003-04-17","Maundy Thursday","NI",2003 +"2003-04-18","Good Friday","NI",2003 +"2003-05-01","Labour Day","NI",2003 +"2003-07-19","Revolution Day","NI",2003 +"2003-08-01","Descent of Saint Dominic","NI",2003 +"2003-08-10","Ascent of Saint Dominic","NI",2003 +"2003-09-14","Battle of San Jacinto Day","NI",2003 +"2003-09-15","Independence Day","NI",2003 +"2003-12-08","Virgin's Day","NI",2003 +"2003-12-25","Christmas","NI",2003 +"2004-01-01","New Year's Day","NI",2004 +"2004-04-08","Maundy Thursday","NI",2004 +"2004-04-09","Good Friday","NI",2004 +"2004-05-01","Labour Day","NI",2004 +"2004-07-19","Revolution Day","NI",2004 +"2004-08-01","Descent of Saint Dominic","NI",2004 +"2004-08-10","Ascent of Saint Dominic","NI",2004 +"2004-09-14","Battle of San Jacinto Day","NI",2004 +"2004-09-15","Independence Day","NI",2004 +"2004-12-08","Virgin's Day","NI",2004 +"2004-12-25","Christmas","NI",2004 +"2005-01-01","New Year's Day","NI",2005 +"2005-03-24","Maundy Thursday","NI",2005 +"2005-03-25","Good Friday","NI",2005 +"2005-05-01","Labour Day","NI",2005 +"2005-07-19","Revolution Day","NI",2005 +"2005-08-01","Descent of Saint Dominic","NI",2005 +"2005-08-10","Ascent of Saint Dominic","NI",2005 +"2005-09-14","Battle of San Jacinto Day","NI",2005 +"2005-09-15","Independence Day","NI",2005 +"2005-12-08","Virgin's Day","NI",2005 +"2005-12-25","Christmas","NI",2005 +"2006-01-01","New Year's Day","NI",2006 +"2006-04-13","Maundy Thursday","NI",2006 +"2006-04-14","Good Friday","NI",2006 +"2006-05-01","Labour Day","NI",2006 +"2006-07-19","Revolution Day","NI",2006 +"2006-08-01","Descent of Saint Dominic","NI",2006 +"2006-08-10","Ascent of Saint Dominic","NI",2006 +"2006-09-14","Battle of San Jacinto Day","NI",2006 +"2006-09-15","Independence Day","NI",2006 +"2006-12-08","Virgin's Day","NI",2006 +"2006-12-25","Christmas","NI",2006 +"2007-01-01","New Year's Day","NI",2007 +"2007-04-05","Maundy Thursday","NI",2007 +"2007-04-06","Good Friday","NI",2007 +"2007-05-01","Labour Day","NI",2007 +"2007-07-19","Revolution Day","NI",2007 +"2007-08-01","Descent of Saint Dominic","NI",2007 +"2007-08-10","Ascent of Saint Dominic","NI",2007 +"2007-09-14","Battle of San Jacinto Day","NI",2007 +"2007-09-15","Independence Day","NI",2007 +"2007-12-08","Virgin's Day","NI",2007 +"2007-12-25","Christmas","NI",2007 +"2008-01-01","New Year's Day","NI",2008 +"2008-03-20","Maundy Thursday","NI",2008 +"2008-03-21","Good Friday","NI",2008 +"2008-05-01","Labour Day","NI",2008 +"2008-07-19","Revolution Day","NI",2008 +"2008-08-01","Descent of Saint Dominic","NI",2008 +"2008-08-10","Ascent of Saint Dominic","NI",2008 +"2008-09-14","Battle of San Jacinto Day","NI",2008 +"2008-09-15","Independence Day","NI",2008 +"2008-12-08","Virgin's Day","NI",2008 +"2008-12-25","Christmas","NI",2008 +"2009-01-01","New Year's Day","NI",2009 +"2009-04-09","Maundy Thursday","NI",2009 +"2009-04-10","Good Friday","NI",2009 +"2009-05-01","Labour Day","NI",2009 +"2009-07-19","Revolution Day","NI",2009 +"2009-08-01","Descent of Saint Dominic","NI",2009 +"2009-08-10","Ascent of Saint Dominic","NI",2009 +"2009-09-14","Battle of San Jacinto Day","NI",2009 +"2009-09-15","Independence Day","NI",2009 +"2009-12-08","Virgin's Day","NI",2009 +"2009-12-25","Christmas","NI",2009 +"2010-01-01","New Year's Day","NI",2010 +"2010-04-01","Maundy Thursday","NI",2010 +"2010-04-02","Good Friday","NI",2010 +"2010-05-01","Labour Day","NI",2010 +"2010-07-19","Revolution Day","NI",2010 +"2010-08-01","Descent of Saint Dominic","NI",2010 +"2010-08-10","Ascent of Saint Dominic","NI",2010 +"2010-09-14","Battle of San Jacinto Day","NI",2010 +"2010-09-15","Independence Day","NI",2010 +"2010-12-08","Virgin's Day","NI",2010 +"2010-12-25","Christmas","NI",2010 +"2011-01-01","New Year's Day","NI",2011 +"2011-04-21","Maundy Thursday","NI",2011 +"2011-04-22","Good Friday","NI",2011 +"2011-05-01","Labour Day","NI",2011 +"2011-07-19","Revolution Day","NI",2011 +"2011-08-01","Descent of Saint Dominic","NI",2011 +"2011-08-10","Ascent of Saint Dominic","NI",2011 +"2011-09-14","Battle of San Jacinto Day","NI",2011 +"2011-09-15","Independence Day","NI",2011 +"2011-12-08","Virgin's Day","NI",2011 +"2011-12-25","Christmas","NI",2011 +"2012-01-01","New Year's Day","NI",2012 +"2012-04-05","Maundy Thursday","NI",2012 +"2012-04-06","Good Friday","NI",2012 +"2012-05-01","Labour Day","NI",2012 +"2012-07-19","Revolution Day","NI",2012 +"2012-08-01","Descent of Saint Dominic","NI",2012 +"2012-08-10","Ascent of Saint Dominic","NI",2012 +"2012-09-14","Battle of San Jacinto Day","NI",2012 +"2012-09-15","Independence Day","NI",2012 +"2012-12-08","Virgin's Day","NI",2012 +"2012-12-25","Christmas","NI",2012 +"2013-01-01","New Year's Day","NI",2013 +"2013-03-28","Maundy Thursday","NI",2013 +"2013-03-29","Good Friday","NI",2013 +"2013-05-01","Labour Day","NI",2013 +"2013-07-19","Revolution Day","NI",2013 +"2013-08-01","Descent of Saint Dominic","NI",2013 +"2013-08-10","Ascent of Saint Dominic","NI",2013 +"2013-09-14","Battle of San Jacinto Day","NI",2013 +"2013-09-15","Independence Day","NI",2013 +"2013-12-08","Virgin's Day","NI",2013 +"2013-12-25","Christmas","NI",2013 +"2014-01-01","New Year's Day","NI",2014 +"2014-04-17","Maundy Thursday","NI",2014 +"2014-04-18","Good Friday","NI",2014 +"2014-05-01","Labour Day","NI",2014 +"2014-07-19","Revolution Day","NI",2014 +"2014-08-01","Descent of Saint Dominic","NI",2014 +"2014-08-10","Ascent of Saint Dominic","NI",2014 +"2014-09-14","Battle of San Jacinto Day","NI",2014 +"2014-09-15","Independence Day","NI",2014 +"2014-12-08","Virgin's Day","NI",2014 +"2014-12-25","Christmas","NI",2014 +"2015-01-01","New Year's Day","NI",2015 +"2015-04-02","Maundy Thursday","NI",2015 +"2015-04-03","Good Friday","NI",2015 +"2015-05-01","Labour Day","NI",2015 +"2015-07-19","Revolution Day","NI",2015 +"2015-08-01","Descent of Saint Dominic","NI",2015 +"2015-08-10","Ascent of Saint Dominic","NI",2015 +"2015-09-14","Battle of San Jacinto Day","NI",2015 +"2015-09-15","Independence Day","NI",2015 +"2015-12-08","Virgin's Day","NI",2015 +"2015-12-25","Christmas","NI",2015 +"2016-01-01","New Year's Day","NI",2016 +"2016-03-24","Maundy Thursday","NI",2016 +"2016-03-25","Good Friday","NI",2016 +"2016-05-01","Labour Day","NI",2016 +"2016-07-19","Revolution Day","NI",2016 +"2016-08-01","Descent of Saint Dominic","NI",2016 +"2016-08-10","Ascent of Saint Dominic","NI",2016 +"2016-09-14","Battle of San Jacinto Day","NI",2016 +"2016-09-15","Independence Day","NI",2016 +"2016-12-08","Virgin's Day","NI",2016 +"2016-12-25","Christmas","NI",2016 +"2017-01-01","New Year's Day","NI",2017 +"2017-04-13","Maundy Thursday","NI",2017 +"2017-04-14","Good Friday","NI",2017 +"2017-05-01","Labour Day","NI",2017 +"2017-07-19","Revolution Day","NI",2017 +"2017-08-01","Descent of Saint Dominic","NI",2017 +"2017-08-10","Ascent of Saint Dominic","NI",2017 +"2017-09-14","Battle of San Jacinto Day","NI",2017 +"2017-09-15","Independence Day","NI",2017 +"2017-12-08","Virgin's Day","NI",2017 +"2017-12-25","Christmas","NI",2017 +"2018-01-01","New Year's Day","NI",2018 +"2018-03-29","Maundy Thursday","NI",2018 +"2018-03-30","Good Friday","NI",2018 +"2018-05-01","Labour Day","NI",2018 +"2018-07-19","Revolution Day","NI",2018 +"2018-08-01","Descent of Saint Dominic","NI",2018 +"2018-08-10","Ascent of Saint Dominic","NI",2018 +"2018-09-14","Battle of San Jacinto Day","NI",2018 +"2018-09-15","Independence Day","NI",2018 +"2018-12-08","Virgin's Day","NI",2018 +"2018-12-25","Christmas","NI",2018 +"2019-01-01","New Year's Day","NI",2019 +"2019-04-18","Maundy Thursday","NI",2019 +"2019-04-19","Good Friday","NI",2019 +"2019-05-01","Labour Day","NI",2019 +"2019-07-19","Revolution Day","NI",2019 +"2019-08-01","Descent of Saint Dominic","NI",2019 +"2019-08-10","Ascent of Saint Dominic","NI",2019 +"2019-09-14","Battle of San Jacinto Day","NI",2019 +"2019-09-15","Independence Day","NI",2019 +"2019-12-08","Virgin's Day","NI",2019 +"2019-12-25","Christmas","NI",2019 +"2020-01-01","New Year's Day","NI",2020 +"2020-04-09","Maundy Thursday","NI",2020 +"2020-04-10","Good Friday","NI",2020 +"2020-05-01","Labour Day","NI",2020 +"2020-07-19","Revolution Day","NI",2020 +"2020-08-01","Descent of Saint Dominic","NI",2020 +"2020-08-10","Ascent of Saint Dominic","NI",2020 +"2020-09-14","Battle of San Jacinto Day","NI",2020 +"2020-09-15","Independence Day","NI",2020 +"2020-12-08","Virgin's Day","NI",2020 +"2020-12-25","Christmas","NI",2020 +"2021-01-01","New Year's Day","NI",2021 +"2021-04-01","Maundy Thursday","NI",2021 +"2021-04-02","Good Friday","NI",2021 +"2021-05-01","Labour Day","NI",2021 +"2021-07-19","Revolution Day","NI",2021 +"2021-08-01","Descent of Saint Dominic","NI",2021 +"2021-08-10","Ascent of Saint Dominic","NI",2021 +"2021-09-14","Battle of San Jacinto Day","NI",2021 +"2021-09-15","Independence Day","NI",2021 +"2021-12-08","Virgin's Day","NI",2021 +"2021-12-25","Christmas","NI",2021 +"2022-01-01","New Year's Day","NI",2022 +"2022-04-14","Maundy Thursday","NI",2022 +"2022-04-15","Good Friday","NI",2022 +"2022-05-01","Labour Day","NI",2022 +"2022-07-19","Revolution Day","NI",2022 +"2022-08-01","Descent of Saint Dominic","NI",2022 +"2022-08-10","Ascent of Saint Dominic","NI",2022 +"2022-09-14","Battle of San Jacinto Day","NI",2022 +"2022-09-15","Independence Day","NI",2022 +"2022-12-08","Virgin's Day","NI",2022 +"2022-12-25","Christmas","NI",2022 +"2023-01-01","New Year's Day","NI",2023 +"2023-04-06","Maundy Thursday","NI",2023 +"2023-04-07","Good Friday","NI",2023 +"2023-05-01","Labour Day","NI",2023 +"2023-07-19","Revolution Day","NI",2023 +"2023-08-01","Descent of Saint Dominic","NI",2023 +"2023-08-10","Ascent of Saint Dominic","NI",2023 +"2023-09-14","Battle of San Jacinto Day","NI",2023 +"2023-09-15","Independence Day","NI",2023 +"2023-12-08","Virgin's Day","NI",2023 +"2023-12-25","Christmas","NI",2023 +"2024-01-01","New Year's Day","NI",2024 +"2024-03-28","Maundy Thursday","NI",2024 +"2024-03-29","Good Friday","NI",2024 +"2024-05-01","Labour Day","NI",2024 +"2024-07-19","Revolution Day","NI",2024 +"2024-08-01","Descent of Saint Dominic","NI",2024 +"2024-08-10","Ascent of Saint Dominic","NI",2024 +"2024-09-14","Battle of San Jacinto Day","NI",2024 +"2024-09-15","Independence Day","NI",2024 +"2024-12-08","Virgin's Day","NI",2024 +"2024-12-25","Christmas","NI",2024 +"2025-01-01","New Year's Day","NI",2025 +"2025-04-17","Maundy Thursday","NI",2025 +"2025-04-18","Good Friday","NI",2025 +"2025-05-01","Labour Day","NI",2025 +"2025-07-19","Revolution Day","NI",2025 +"2025-08-01","Descent of Saint Dominic","NI",2025 +"2025-08-10","Ascent of Saint Dominic","NI",2025 +"2025-09-14","Battle of San Jacinto Day","NI",2025 +"2025-09-15","Independence Day","NI",2025 +"2025-12-08","Virgin's Day","NI",2025 +"2025-12-25","Christmas","NI",2025 +"2026-01-01","New Year's Day","NI",2026 +"2026-04-02","Maundy Thursday","NI",2026 +"2026-04-03","Good Friday","NI",2026 +"2026-05-01","Labour Day","NI",2026 +"2026-07-19","Revolution Day","NI",2026 +"2026-08-01","Descent of Saint Dominic","NI",2026 +"2026-08-10","Ascent of Saint Dominic","NI",2026 +"2026-09-14","Battle of San Jacinto Day","NI",2026 +"2026-09-15","Independence Day","NI",2026 +"2026-12-08","Virgin's Day","NI",2026 +"2026-12-25","Christmas","NI",2026 +"2027-01-01","New Year's Day","NI",2027 +"2027-03-25","Maundy Thursday","NI",2027 +"2027-03-26","Good Friday","NI",2027 +"2027-05-01","Labour Day","NI",2027 +"2027-07-19","Revolution Day","NI",2027 +"2027-08-01","Descent of Saint Dominic","NI",2027 +"2027-08-10","Ascent of Saint Dominic","NI",2027 +"2027-09-14","Battle of San Jacinto Day","NI",2027 +"2027-09-15","Independence Day","NI",2027 +"2027-12-08","Virgin's Day","NI",2027 +"2027-12-25","Christmas","NI",2027 +"2028-01-01","New Year's Day","NI",2028 +"2028-04-13","Maundy Thursday","NI",2028 +"2028-04-14","Good Friday","NI",2028 +"2028-05-01","Labour Day","NI",2028 +"2028-07-19","Revolution Day","NI",2028 +"2028-08-01","Descent of Saint Dominic","NI",2028 +"2028-08-10","Ascent of Saint Dominic","NI",2028 +"2028-09-14","Battle of San Jacinto Day","NI",2028 +"2028-09-15","Independence Day","NI",2028 +"2028-12-08","Virgin's Day","NI",2028 +"2028-12-25","Christmas","NI",2028 +"2029-01-01","New Year's Day","NI",2029 +"2029-03-29","Maundy Thursday","NI",2029 +"2029-03-30","Good Friday","NI",2029 +"2029-05-01","Labour Day","NI",2029 +"2029-07-19","Revolution Day","NI",2029 +"2029-08-01","Descent of Saint Dominic","NI",2029 +"2029-08-10","Ascent of Saint Dominic","NI",2029 +"2029-09-14","Battle of San Jacinto Day","NI",2029 +"2029-09-15","Independence Day","NI",2029 +"2029-12-08","Virgin's Day","NI",2029 +"2029-12-25","Christmas","NI",2029 +"2030-01-01","New Year's Day","NI",2030 +"2030-04-18","Maundy Thursday","NI",2030 +"2030-04-19","Good Friday","NI",2030 +"2030-05-01","Labour Day","NI",2030 +"2030-07-19","Revolution Day","NI",2030 +"2030-08-01","Descent of Saint Dominic","NI",2030 +"2030-08-10","Ascent of Saint Dominic","NI",2030 +"2030-09-14","Battle of San Jacinto Day","NI",2030 +"2030-09-15","Independence Day","NI",2030 +"2030-12-08","Virgin's Day","NI",2030 +"2030-12-25","Christmas","NI",2030 +"2031-01-01","New Year's Day","NI",2031 +"2031-04-10","Maundy Thursday","NI",2031 +"2031-04-11","Good Friday","NI",2031 +"2031-05-01","Labour Day","NI",2031 +"2031-07-19","Revolution Day","NI",2031 +"2031-08-01","Descent of Saint Dominic","NI",2031 +"2031-08-10","Ascent of Saint Dominic","NI",2031 +"2031-09-14","Battle of San Jacinto Day","NI",2031 +"2031-09-15","Independence Day","NI",2031 +"2031-12-08","Virgin's Day","NI",2031 +"2031-12-25","Christmas","NI",2031 +"2032-01-01","New Year's Day","NI",2032 +"2032-03-25","Maundy Thursday","NI",2032 +"2032-03-26","Good Friday","NI",2032 +"2032-05-01","Labour Day","NI",2032 +"2032-07-19","Revolution Day","NI",2032 +"2032-08-01","Descent of Saint Dominic","NI",2032 +"2032-08-10","Ascent of Saint Dominic","NI",2032 +"2032-09-14","Battle of San Jacinto Day","NI",2032 +"2032-09-15","Independence Day","NI",2032 +"2032-12-08","Virgin's Day","NI",2032 +"2032-12-25","Christmas","NI",2032 +"2033-01-01","New Year's Day","NI",2033 +"2033-04-14","Maundy Thursday","NI",2033 +"2033-04-15","Good Friday","NI",2033 +"2033-05-01","Labour Day","NI",2033 +"2033-07-19","Revolution Day","NI",2033 +"2033-08-01","Descent of Saint Dominic","NI",2033 +"2033-08-10","Ascent of Saint Dominic","NI",2033 +"2033-09-14","Battle of San Jacinto Day","NI",2033 +"2033-09-15","Independence Day","NI",2033 +"2033-12-08","Virgin's Day","NI",2033 +"2033-12-25","Christmas","NI",2033 +"2034-01-01","New Year's Day","NI",2034 +"2034-04-06","Maundy Thursday","NI",2034 +"2034-04-07","Good Friday","NI",2034 +"2034-05-01","Labour Day","NI",2034 +"2034-07-19","Revolution Day","NI",2034 +"2034-08-01","Descent of Saint Dominic","NI",2034 +"2034-08-10","Ascent of Saint Dominic","NI",2034 +"2034-09-14","Battle of San Jacinto Day","NI",2034 +"2034-09-15","Independence Day","NI",2034 +"2034-12-08","Virgin's Day","NI",2034 +"2034-12-25","Christmas","NI",2034 +"2035-01-01","New Year's Day","NI",2035 +"2035-03-22","Maundy Thursday","NI",2035 +"2035-03-23","Good Friday","NI",2035 +"2035-05-01","Labour Day","NI",2035 +"2035-07-19","Revolution Day","NI",2035 +"2035-08-01","Descent of Saint Dominic","NI",2035 +"2035-08-10","Ascent of Saint Dominic","NI",2035 +"2035-09-14","Battle of San Jacinto Day","NI",2035 +"2035-09-15","Independence Day","NI",2035 +"2035-12-08","Virgin's Day","NI",2035 +"2035-12-25","Christmas","NI",2035 +"2036-01-01","New Year's Day","NI",2036 +"2036-04-10","Maundy Thursday","NI",2036 +"2036-04-11","Good Friday","NI",2036 +"2036-05-01","Labour Day","NI",2036 +"2036-07-19","Revolution Day","NI",2036 +"2036-08-01","Descent of Saint Dominic","NI",2036 +"2036-08-10","Ascent of Saint Dominic","NI",2036 +"2036-09-14","Battle of San Jacinto Day","NI",2036 +"2036-09-15","Independence Day","NI",2036 +"2036-12-08","Virgin's Day","NI",2036 +"2036-12-25","Christmas","NI",2036 +"2037-01-01","New Year's Day","NI",2037 +"2037-04-02","Maundy Thursday","NI",2037 +"2037-04-03","Good Friday","NI",2037 +"2037-05-01","Labour Day","NI",2037 +"2037-07-19","Revolution Day","NI",2037 +"2037-08-01","Descent of Saint Dominic","NI",2037 +"2037-08-10","Ascent of Saint Dominic","NI",2037 +"2037-09-14","Battle of San Jacinto Day","NI",2037 +"2037-09-15","Independence Day","NI",2037 +"2037-12-08","Virgin's Day","NI",2037 +"2037-12-25","Christmas","NI",2037 +"2038-01-01","New Year's Day","NI",2038 +"2038-04-22","Maundy Thursday","NI",2038 +"2038-04-23","Good Friday","NI",2038 +"2038-05-01","Labour Day","NI",2038 +"2038-07-19","Revolution Day","NI",2038 +"2038-08-01","Descent of Saint Dominic","NI",2038 +"2038-08-10","Ascent of Saint Dominic","NI",2038 +"2038-09-14","Battle of San Jacinto Day","NI",2038 +"2038-09-15","Independence Day","NI",2038 +"2038-12-08","Virgin's Day","NI",2038 +"2038-12-25","Christmas","NI",2038 +"2039-01-01","New Year's Day","NI",2039 +"2039-04-07","Maundy Thursday","NI",2039 +"2039-04-08","Good Friday","NI",2039 +"2039-05-01","Labour Day","NI",2039 +"2039-07-19","Revolution Day","NI",2039 +"2039-08-01","Descent of Saint Dominic","NI",2039 +"2039-08-10","Ascent of Saint Dominic","NI",2039 +"2039-09-14","Battle of San Jacinto Day","NI",2039 +"2039-09-15","Independence Day","NI",2039 +"2039-12-08","Virgin's Day","NI",2039 +"2039-12-25","Christmas","NI",2039 +"2040-01-01","New Year's Day","NI",2040 +"2040-03-29","Maundy Thursday","NI",2040 +"2040-03-30","Good Friday","NI",2040 +"2040-05-01","Labour Day","NI",2040 +"2040-07-19","Revolution Day","NI",2040 +"2040-08-01","Descent of Saint Dominic","NI",2040 +"2040-08-10","Ascent of Saint Dominic","NI",2040 +"2040-09-14","Battle of San Jacinto Day","NI",2040 +"2040-09-15","Independence Day","NI",2040 +"2040-12-08","Virgin's Day","NI",2040 +"2040-12-25","Christmas","NI",2040 +"2041-01-01","New Year's Day","NI",2041 +"2041-04-18","Maundy Thursday","NI",2041 +"2041-04-19","Good Friday","NI",2041 +"2041-05-01","Labour Day","NI",2041 +"2041-07-19","Revolution Day","NI",2041 +"2041-08-01","Descent of Saint Dominic","NI",2041 +"2041-08-10","Ascent of Saint Dominic","NI",2041 +"2041-09-14","Battle of San Jacinto Day","NI",2041 +"2041-09-15","Independence Day","NI",2041 +"2041-12-08","Virgin's Day","NI",2041 +"2041-12-25","Christmas","NI",2041 +"2042-01-01","New Year's Day","NI",2042 +"2042-04-03","Maundy Thursday","NI",2042 +"2042-04-04","Good Friday","NI",2042 +"2042-05-01","Labour Day","NI",2042 +"2042-07-19","Revolution Day","NI",2042 +"2042-08-01","Descent of Saint Dominic","NI",2042 +"2042-08-10","Ascent of Saint Dominic","NI",2042 +"2042-09-14","Battle of San Jacinto Day","NI",2042 +"2042-09-15","Independence Day","NI",2042 +"2042-12-08","Virgin's Day","NI",2042 +"2042-12-25","Christmas","NI",2042 +"2043-01-01","New Year's Day","NI",2043 +"2043-03-26","Maundy Thursday","NI",2043 +"2043-03-27","Good Friday","NI",2043 +"2043-05-01","Labour Day","NI",2043 +"2043-07-19","Revolution Day","NI",2043 +"2043-08-01","Descent of Saint Dominic","NI",2043 +"2043-08-10","Ascent of Saint Dominic","NI",2043 +"2043-09-14","Battle of San Jacinto Day","NI",2043 +"2043-09-15","Independence Day","NI",2043 +"2043-12-08","Virgin's Day","NI",2043 +"2043-12-25","Christmas","NI",2043 +"2044-01-01","New Year's Day","NI",2044 +"2044-04-14","Maundy Thursday","NI",2044 +"2044-04-15","Good Friday","NI",2044 +"2044-05-01","Labour Day","NI",2044 +"2044-07-19","Revolution Day","NI",2044 +"2044-08-01","Descent of Saint Dominic","NI",2044 +"2044-08-10","Ascent of Saint Dominic","NI",2044 +"2044-09-14","Battle of San Jacinto Day","NI",2044 +"2044-09-15","Independence Day","NI",2044 +"2044-12-08","Virgin's Day","NI",2044 +"2044-12-25","Christmas","NI",2044 +"1995-01-01","New Year's Day","NL",1995 +"1995-04-14","Good Friday","NL",1995 +"1995-04-16","Easter Sunday","NL",1995 +"1995-04-17","Easter Monday","NL",1995 +"1995-04-29","Queen's Day","NL",1995 +"1995-05-05","Liberation Day","NL",1995 +"1995-05-25","Ascension Day","NL",1995 +"1995-06-04","Whit Sunday","NL",1995 +"1995-06-05","Whit Monday","NL",1995 +"1995-12-25","Christmas Day","NL",1995 +"1995-12-26","Second Day of Christmas","NL",1995 +"1996-01-01","New Year's Day","NL",1996 +"1996-04-05","Good Friday","NL",1996 +"1996-04-07","Easter Sunday","NL",1996 +"1996-04-08","Easter Monday","NL",1996 +"1996-04-30","Queen's Day","NL",1996 +"1996-05-16","Ascension Day","NL",1996 +"1996-05-26","Whit Sunday","NL",1996 +"1996-05-27","Whit Monday","NL",1996 +"1996-12-25","Christmas Day","NL",1996 +"1996-12-26","Second Day of Christmas","NL",1996 +"1997-01-01","New Year's Day","NL",1997 +"1997-03-28","Good Friday","NL",1997 +"1997-03-30","Easter Sunday","NL",1997 +"1997-03-31","Easter Monday","NL",1997 +"1997-04-30","Queen's Day","NL",1997 +"1997-05-08","Ascension Day","NL",1997 +"1997-05-18","Whit Sunday","NL",1997 +"1997-05-19","Whit Monday","NL",1997 +"1997-12-25","Christmas Day","NL",1997 +"1997-12-26","Second Day of Christmas","NL",1997 +"1998-01-01","New Year's Day","NL",1998 +"1998-04-10","Good Friday","NL",1998 +"1998-04-12","Easter Sunday","NL",1998 +"1998-04-13","Easter Monday","NL",1998 +"1998-04-30","Queen's Day","NL",1998 +"1998-05-21","Ascension Day","NL",1998 +"1998-05-31","Whit Sunday","NL",1998 +"1998-06-01","Whit Monday","NL",1998 +"1998-12-25","Christmas Day","NL",1998 +"1998-12-26","Second Day of Christmas","NL",1998 +"1999-01-01","New Year's Day","NL",1999 +"1999-04-02","Good Friday","NL",1999 +"1999-04-04","Easter Sunday","NL",1999 +"1999-04-05","Easter Monday","NL",1999 +"1999-04-30","Queen's Day","NL",1999 +"1999-05-13","Ascension Day","NL",1999 +"1999-05-23","Whit Sunday","NL",1999 +"1999-05-24","Whit Monday","NL",1999 +"1999-12-25","Christmas Day","NL",1999 +"1999-12-26","Second Day of Christmas","NL",1999 +"2000-01-01","New Year's Day","NL",2000 +"2000-04-21","Good Friday","NL",2000 +"2000-04-23","Easter Sunday","NL",2000 +"2000-04-24","Easter Monday","NL",2000 +"2000-04-29","Queen's Day","NL",2000 +"2000-05-05","Liberation Day","NL",2000 +"2000-06-01","Ascension Day","NL",2000 +"2000-06-11","Whit Sunday","NL",2000 +"2000-06-12","Whit Monday","NL",2000 +"2000-12-25","Christmas Day","NL",2000 +"2000-12-26","Second Day of Christmas","NL",2000 +"2001-01-01","New Year's Day","NL",2001 +"2001-04-13","Good Friday","NL",2001 +"2001-04-15","Easter Sunday","NL",2001 +"2001-04-16","Easter Monday","NL",2001 +"2001-04-30","Queen's Day","NL",2001 +"2001-05-24","Ascension Day","NL",2001 +"2001-06-03","Whit Sunday","NL",2001 +"2001-06-04","Whit Monday","NL",2001 +"2001-12-25","Christmas Day","NL",2001 +"2001-12-26","Second Day of Christmas","NL",2001 +"2002-01-01","New Year's Day","NL",2002 +"2002-03-29","Good Friday","NL",2002 +"2002-03-31","Easter Sunday","NL",2002 +"2002-04-01","Easter Monday","NL",2002 +"2002-04-30","Queen's Day","NL",2002 +"2002-05-09","Ascension Day","NL",2002 +"2002-05-19","Whit Sunday","NL",2002 +"2002-05-20","Whit Monday","NL",2002 +"2002-12-25","Christmas Day","NL",2002 +"2002-12-26","Second Day of Christmas","NL",2002 +"2003-01-01","New Year's Day","NL",2003 +"2003-04-18","Good Friday","NL",2003 +"2003-04-20","Easter Sunday","NL",2003 +"2003-04-21","Easter Monday","NL",2003 +"2003-04-30","Queen's Day","NL",2003 +"2003-05-29","Ascension Day","NL",2003 +"2003-06-08","Whit Sunday","NL",2003 +"2003-06-09","Whit Monday","NL",2003 +"2003-12-25","Christmas Day","NL",2003 +"2003-12-26","Second Day of Christmas","NL",2003 +"2004-01-01","New Year's Day","NL",2004 +"2004-04-09","Good Friday","NL",2004 +"2004-04-11","Easter Sunday","NL",2004 +"2004-04-12","Easter Monday","NL",2004 +"2004-04-30","Queen's Day","NL",2004 +"2004-05-20","Ascension Day","NL",2004 +"2004-05-30","Whit Sunday","NL",2004 +"2004-05-31","Whit Monday","NL",2004 +"2004-12-25","Christmas Day","NL",2004 +"2004-12-26","Second Day of Christmas","NL",2004 +"2005-01-01","New Year's Day","NL",2005 +"2005-03-25","Good Friday","NL",2005 +"2005-03-27","Easter Sunday","NL",2005 +"2005-03-28","Easter Monday","NL",2005 +"2005-04-30","Queen's Day","NL",2005 +"2005-05-05","Ascension Day","NL",2005 +"2005-05-05","Liberation Day","NL",2005 +"2005-05-15","Whit Sunday","NL",2005 +"2005-05-16","Whit Monday","NL",2005 +"2005-12-25","Christmas Day","NL",2005 +"2005-12-26","Second Day of Christmas","NL",2005 +"2006-01-01","New Year's Day","NL",2006 +"2006-04-14","Good Friday","NL",2006 +"2006-04-16","Easter Sunday","NL",2006 +"2006-04-17","Easter Monday","NL",2006 +"2006-04-29","Queen's Day","NL",2006 +"2006-05-25","Ascension Day","NL",2006 +"2006-06-04","Whit Sunday","NL",2006 +"2006-06-05","Whit Monday","NL",2006 +"2006-12-25","Christmas Day","NL",2006 +"2006-12-26","Second Day of Christmas","NL",2006 +"2007-01-01","New Year's Day","NL",2007 +"2007-04-06","Good Friday","NL",2007 +"2007-04-08","Easter Sunday","NL",2007 +"2007-04-09","Easter Monday","NL",2007 +"2007-04-30","Queen's Day","NL",2007 +"2007-05-17","Ascension Day","NL",2007 +"2007-05-27","Whit Sunday","NL",2007 +"2007-05-28","Whit Monday","NL",2007 +"2007-12-25","Christmas Day","NL",2007 +"2007-12-26","Second Day of Christmas","NL",2007 +"2008-01-01","New Year's Day","NL",2008 +"2008-03-21","Good Friday","NL",2008 +"2008-03-23","Easter Sunday","NL",2008 +"2008-03-24","Easter Monday","NL",2008 +"2008-04-30","Queen's Day","NL",2008 +"2008-05-01","Ascension Day","NL",2008 +"2008-05-11","Whit Sunday","NL",2008 +"2008-05-12","Whit Monday","NL",2008 +"2008-12-25","Christmas Day","NL",2008 +"2008-12-26","Second Day of Christmas","NL",2008 +"2009-01-01","New Year's Day","NL",2009 +"2009-04-10","Good Friday","NL",2009 +"2009-04-12","Easter Sunday","NL",2009 +"2009-04-13","Easter Monday","NL",2009 +"2009-04-30","Queen's Day","NL",2009 +"2009-05-21","Ascension Day","NL",2009 +"2009-05-31","Whit Sunday","NL",2009 +"2009-06-01","Whit Monday","NL",2009 +"2009-12-25","Christmas Day","NL",2009 +"2009-12-26","Second Day of Christmas","NL",2009 +"2010-01-01","New Year's Day","NL",2010 +"2010-04-02","Good Friday","NL",2010 +"2010-04-04","Easter Sunday","NL",2010 +"2010-04-05","Easter Monday","NL",2010 +"2010-04-30","Queen's Day","NL",2010 +"2010-05-05","Liberation Day","NL",2010 +"2010-05-13","Ascension Day","NL",2010 +"2010-05-23","Whit Sunday","NL",2010 +"2010-05-24","Whit Monday","NL",2010 +"2010-12-25","Christmas Day","NL",2010 +"2010-12-26","Second Day of Christmas","NL",2010 +"2011-01-01","New Year's Day","NL",2011 +"2011-04-22","Good Friday","NL",2011 +"2011-04-24","Easter Sunday","NL",2011 +"2011-04-25","Easter Monday","NL",2011 +"2011-04-30","Queen's Day","NL",2011 +"2011-06-02","Ascension Day","NL",2011 +"2011-06-12","Whit Sunday","NL",2011 +"2011-06-13","Whit Monday","NL",2011 +"2011-12-25","Christmas Day","NL",2011 +"2011-12-26","Second Day of Christmas","NL",2011 +"2012-01-01","New Year's Day","NL",2012 +"2012-04-06","Good Friday","NL",2012 +"2012-04-08","Easter Sunday","NL",2012 +"2012-04-09","Easter Monday","NL",2012 +"2012-04-30","Queen's Day","NL",2012 +"2012-05-17","Ascension Day","NL",2012 +"2012-05-27","Whit Sunday","NL",2012 +"2012-05-28","Whit Monday","NL",2012 +"2012-12-25","Christmas Day","NL",2012 +"2012-12-26","Second Day of Christmas","NL",2012 +"2013-01-01","New Year's Day","NL",2013 +"2013-03-29","Good Friday","NL",2013 +"2013-03-31","Easter Sunday","NL",2013 +"2013-04-01","Easter Monday","NL",2013 +"2013-04-30","Queen's Day","NL",2013 +"2013-05-09","Ascension Day","NL",2013 +"2013-05-19","Whit Sunday","NL",2013 +"2013-05-20","Whit Monday","NL",2013 +"2013-12-25","Christmas Day","NL",2013 +"2013-12-26","Second Day of Christmas","NL",2013 +"2014-01-01","New Year's Day","NL",2014 +"2014-04-18","Good Friday","NL",2014 +"2014-04-20","Easter Sunday","NL",2014 +"2014-04-21","Easter Monday","NL",2014 +"2014-04-26","King's Day","NL",2014 +"2014-05-29","Ascension Day","NL",2014 +"2014-06-08","Whit Sunday","NL",2014 +"2014-06-09","Whit Monday","NL",2014 +"2014-12-25","Christmas Day","NL",2014 +"2014-12-26","Second Day of Christmas","NL",2014 +"2015-01-01","New Year's Day","NL",2015 +"2015-04-03","Good Friday","NL",2015 +"2015-04-05","Easter Sunday","NL",2015 +"2015-04-06","Easter Monday","NL",2015 +"2015-04-27","King's Day","NL",2015 +"2015-05-05","Liberation Day","NL",2015 +"2015-05-14","Ascension Day","NL",2015 +"2015-05-24","Whit Sunday","NL",2015 +"2015-05-25","Whit Monday","NL",2015 +"2015-12-25","Christmas Day","NL",2015 +"2015-12-26","Second Day of Christmas","NL",2015 +"2016-01-01","New Year's Day","NL",2016 +"2016-03-25","Good Friday","NL",2016 +"2016-03-27","Easter Sunday","NL",2016 +"2016-03-28","Easter Monday","NL",2016 +"2016-04-27","King's Day","NL",2016 +"2016-05-05","Ascension Day","NL",2016 +"2016-05-15","Whit Sunday","NL",2016 +"2016-05-16","Whit Monday","NL",2016 +"2016-12-25","Christmas Day","NL",2016 +"2016-12-26","Second Day of Christmas","NL",2016 +"2017-01-01","New Year's Day","NL",2017 +"2017-04-14","Good Friday","NL",2017 +"2017-04-16","Easter Sunday","NL",2017 +"2017-04-17","Easter Monday","NL",2017 +"2017-04-27","King's Day","NL",2017 +"2017-05-25","Ascension Day","NL",2017 +"2017-06-04","Whit Sunday","NL",2017 +"2017-06-05","Whit Monday","NL",2017 +"2017-12-25","Christmas Day","NL",2017 +"2017-12-26","Second Day of Christmas","NL",2017 +"2018-01-01","New Year's Day","NL",2018 +"2018-03-30","Good Friday","NL",2018 +"2018-04-01","Easter Sunday","NL",2018 +"2018-04-02","Easter Monday","NL",2018 +"2018-04-27","King's Day","NL",2018 +"2018-05-10","Ascension Day","NL",2018 +"2018-05-20","Whit Sunday","NL",2018 +"2018-05-21","Whit Monday","NL",2018 +"2018-12-25","Christmas Day","NL",2018 +"2018-12-26","Second Day of Christmas","NL",2018 +"2019-01-01","New Year's Day","NL",2019 +"2019-04-19","Good Friday","NL",2019 +"2019-04-21","Easter Sunday","NL",2019 +"2019-04-22","Easter Monday","NL",2019 +"2019-04-27","King's Day","NL",2019 +"2019-05-30","Ascension Day","NL",2019 +"2019-06-09","Whit Sunday","NL",2019 +"2019-06-10","Whit Monday","NL",2019 +"2019-12-25","Christmas Day","NL",2019 +"2019-12-26","Second Day of Christmas","NL",2019 +"2020-01-01","New Year's Day","NL",2020 +"2020-04-10","Good Friday","NL",2020 +"2020-04-12","Easter Sunday","NL",2020 +"2020-04-13","Easter Monday","NL",2020 +"2020-04-27","King's Day","NL",2020 +"2020-05-05","Liberation Day","NL",2020 +"2020-05-21","Ascension Day","NL",2020 +"2020-05-31","Whit Sunday","NL",2020 +"2020-06-01","Whit Monday","NL",2020 +"2020-12-25","Christmas Day","NL",2020 +"2020-12-26","Second Day of Christmas","NL",2020 +"2021-01-01","New Year's Day","NL",2021 +"2021-04-02","Good Friday","NL",2021 +"2021-04-04","Easter Sunday","NL",2021 +"2021-04-05","Easter Monday","NL",2021 +"2021-04-27","King's Day","NL",2021 +"2021-05-13","Ascension Day","NL",2021 +"2021-05-23","Whit Sunday","NL",2021 +"2021-05-24","Whit Monday","NL",2021 +"2021-12-25","Christmas Day","NL",2021 +"2021-12-26","Second Day of Christmas","NL",2021 +"2022-01-01","New Year's Day","NL",2022 +"2022-04-15","Good Friday","NL",2022 +"2022-04-17","Easter Sunday","NL",2022 +"2022-04-18","Easter Monday","NL",2022 +"2022-04-27","King's Day","NL",2022 +"2022-05-26","Ascension Day","NL",2022 +"2022-06-05","Whit Sunday","NL",2022 +"2022-06-06","Whit Monday","NL",2022 +"2022-12-25","Christmas Day","NL",2022 +"2022-12-26","Second Day of Christmas","NL",2022 +"2023-01-01","New Year's Day","NL",2023 +"2023-04-07","Good Friday","NL",2023 +"2023-04-09","Easter Sunday","NL",2023 +"2023-04-10","Easter Monday","NL",2023 +"2023-04-27","King's Day","NL",2023 +"2023-05-18","Ascension Day","NL",2023 +"2023-05-28","Whit Sunday","NL",2023 +"2023-05-29","Whit Monday","NL",2023 +"2023-12-25","Christmas Day","NL",2023 +"2023-12-26","Second Day of Christmas","NL",2023 +"2024-01-01","New Year's Day","NL",2024 +"2024-03-29","Good Friday","NL",2024 +"2024-03-31","Easter Sunday","NL",2024 +"2024-04-01","Easter Monday","NL",2024 +"2024-04-27","King's Day","NL",2024 +"2024-05-09","Ascension Day","NL",2024 +"2024-05-19","Whit Sunday","NL",2024 +"2024-05-20","Whit Monday","NL",2024 +"2024-12-25","Christmas Day","NL",2024 +"2024-12-26","Second Day of Christmas","NL",2024 +"2025-01-01","New Year's Day","NL",2025 +"2025-04-18","Good Friday","NL",2025 +"2025-04-20","Easter Sunday","NL",2025 +"2025-04-21","Easter Monday","NL",2025 +"2025-04-26","King's Day","NL",2025 +"2025-05-05","Liberation Day","NL",2025 +"2025-05-29","Ascension Day","NL",2025 +"2025-06-08","Whit Sunday","NL",2025 +"2025-06-09","Whit Monday","NL",2025 +"2025-12-25","Christmas Day","NL",2025 +"2025-12-26","Second Day of Christmas","NL",2025 +"2026-01-01","New Year's Day","NL",2026 +"2026-04-03","Good Friday","NL",2026 +"2026-04-05","Easter Sunday","NL",2026 +"2026-04-06","Easter Monday","NL",2026 +"2026-04-27","King's Day","NL",2026 +"2026-05-14","Ascension Day","NL",2026 +"2026-05-24","Whit Sunday","NL",2026 +"2026-05-25","Whit Monday","NL",2026 +"2026-12-25","Christmas Day","NL",2026 +"2026-12-26","Second Day of Christmas","NL",2026 +"2027-01-01","New Year's Day","NL",2027 +"2027-03-26","Good Friday","NL",2027 +"2027-03-28","Easter Sunday","NL",2027 +"2027-03-29","Easter Monday","NL",2027 +"2027-04-27","King's Day","NL",2027 +"2027-05-06","Ascension Day","NL",2027 +"2027-05-16","Whit Sunday","NL",2027 +"2027-05-17","Whit Monday","NL",2027 +"2027-12-25","Christmas Day","NL",2027 +"2027-12-26","Second Day of Christmas","NL",2027 +"2028-01-01","New Year's Day","NL",2028 +"2028-04-14","Good Friday","NL",2028 +"2028-04-16","Easter Sunday","NL",2028 +"2028-04-17","Easter Monday","NL",2028 +"2028-04-27","King's Day","NL",2028 +"2028-05-25","Ascension Day","NL",2028 +"2028-06-04","Whit Sunday","NL",2028 +"2028-06-05","Whit Monday","NL",2028 +"2028-12-25","Christmas Day","NL",2028 +"2028-12-26","Second Day of Christmas","NL",2028 +"2029-01-01","New Year's Day","NL",2029 +"2029-03-30","Good Friday","NL",2029 +"2029-04-01","Easter Sunday","NL",2029 +"2029-04-02","Easter Monday","NL",2029 +"2029-04-27","King's Day","NL",2029 +"2029-05-10","Ascension Day","NL",2029 +"2029-05-20","Whit Sunday","NL",2029 +"2029-05-21","Whit Monday","NL",2029 +"2029-12-25","Christmas Day","NL",2029 +"2029-12-26","Second Day of Christmas","NL",2029 +"2030-01-01","New Year's Day","NL",2030 +"2030-04-19","Good Friday","NL",2030 +"2030-04-21","Easter Sunday","NL",2030 +"2030-04-22","Easter Monday","NL",2030 +"2030-04-27","King's Day","NL",2030 +"2030-05-05","Liberation Day","NL",2030 +"2030-05-30","Ascension Day","NL",2030 +"2030-06-09","Whit Sunday","NL",2030 +"2030-06-10","Whit Monday","NL",2030 +"2030-12-25","Christmas Day","NL",2030 +"2030-12-26","Second Day of Christmas","NL",2030 +"2031-01-01","New Year's Day","NL",2031 +"2031-04-11","Good Friday","NL",2031 +"2031-04-13","Easter Sunday","NL",2031 +"2031-04-14","Easter Monday","NL",2031 +"2031-04-26","King's Day","NL",2031 +"2031-05-22","Ascension Day","NL",2031 +"2031-06-01","Whit Sunday","NL",2031 +"2031-06-02","Whit Monday","NL",2031 +"2031-12-25","Christmas Day","NL",2031 +"2031-12-26","Second Day of Christmas","NL",2031 +"2032-01-01","New Year's Day","NL",2032 +"2032-03-26","Good Friday","NL",2032 +"2032-03-28","Easter Sunday","NL",2032 +"2032-03-29","Easter Monday","NL",2032 +"2032-04-27","King's Day","NL",2032 +"2032-05-06","Ascension Day","NL",2032 +"2032-05-16","Whit Sunday","NL",2032 +"2032-05-17","Whit Monday","NL",2032 +"2032-12-25","Christmas Day","NL",2032 +"2032-12-26","Second Day of Christmas","NL",2032 +"2033-01-01","New Year's Day","NL",2033 +"2033-04-15","Good Friday","NL",2033 +"2033-04-17","Easter Sunday","NL",2033 +"2033-04-18","Easter Monday","NL",2033 +"2033-04-27","King's Day","NL",2033 +"2033-05-26","Ascension Day","NL",2033 +"2033-06-05","Whit Sunday","NL",2033 +"2033-06-06","Whit Monday","NL",2033 +"2033-12-25","Christmas Day","NL",2033 +"2033-12-26","Second Day of Christmas","NL",2033 +"2034-01-01","New Year's Day","NL",2034 +"2034-04-07","Good Friday","NL",2034 +"2034-04-09","Easter Sunday","NL",2034 +"2034-04-10","Easter Monday","NL",2034 +"2034-04-27","King's Day","NL",2034 +"2034-05-18","Ascension Day","NL",2034 +"2034-05-28","Whit Sunday","NL",2034 +"2034-05-29","Whit Monday","NL",2034 +"2034-12-25","Christmas Day","NL",2034 +"2034-12-26","Second Day of Christmas","NL",2034 +"2035-01-01","New Year's Day","NL",2035 +"2035-03-23","Good Friday","NL",2035 +"2035-03-25","Easter Sunday","NL",2035 +"2035-03-26","Easter Monday","NL",2035 +"2035-04-27","King's Day","NL",2035 +"2035-05-03","Ascension Day","NL",2035 +"2035-05-05","Liberation Day","NL",2035 +"2035-05-13","Whit Sunday","NL",2035 +"2035-05-14","Whit Monday","NL",2035 +"2035-12-25","Christmas Day","NL",2035 +"2035-12-26","Second Day of Christmas","NL",2035 +"2036-01-01","New Year's Day","NL",2036 +"2036-04-11","Good Friday","NL",2036 +"2036-04-13","Easter Sunday","NL",2036 +"2036-04-14","Easter Monday","NL",2036 +"2036-04-26","King's Day","NL",2036 +"2036-05-22","Ascension Day","NL",2036 +"2036-06-01","Whit Sunday","NL",2036 +"2036-06-02","Whit Monday","NL",2036 +"2036-12-25","Christmas Day","NL",2036 +"2036-12-26","Second Day of Christmas","NL",2036 +"2037-01-01","New Year's Day","NL",2037 +"2037-04-03","Good Friday","NL",2037 +"2037-04-05","Easter Sunday","NL",2037 +"2037-04-06","Easter Monday","NL",2037 +"2037-04-27","King's Day","NL",2037 +"2037-05-14","Ascension Day","NL",2037 +"2037-05-24","Whit Sunday","NL",2037 +"2037-05-25","Whit Monday","NL",2037 +"2037-12-25","Christmas Day","NL",2037 +"2037-12-26","Second Day of Christmas","NL",2037 +"2038-01-01","New Year's Day","NL",2038 +"2038-04-23","Good Friday","NL",2038 +"2038-04-25","Easter Sunday","NL",2038 +"2038-04-26","Easter Monday","NL",2038 +"2038-04-27","King's Day","NL",2038 +"2038-06-03","Ascension Day","NL",2038 +"2038-06-13","Whit Sunday","NL",2038 +"2038-06-14","Whit Monday","NL",2038 +"2038-12-25","Christmas Day","NL",2038 +"2038-12-26","Second Day of Christmas","NL",2038 +"2039-01-01","New Year's Day","NL",2039 +"2039-04-08","Good Friday","NL",2039 +"2039-04-10","Easter Sunday","NL",2039 +"2039-04-11","Easter Monday","NL",2039 +"2039-04-27","King's Day","NL",2039 +"2039-05-19","Ascension Day","NL",2039 +"2039-05-29","Whit Sunday","NL",2039 +"2039-05-30","Whit Monday","NL",2039 +"2039-12-25","Christmas Day","NL",2039 +"2039-12-26","Second Day of Christmas","NL",2039 +"2040-01-01","New Year's Day","NL",2040 +"2040-03-30","Good Friday","NL",2040 +"2040-04-01","Easter Sunday","NL",2040 +"2040-04-02","Easter Monday","NL",2040 +"2040-04-27","King's Day","NL",2040 +"2040-05-05","Liberation Day","NL",2040 +"2040-05-10","Ascension Day","NL",2040 +"2040-05-20","Whit Sunday","NL",2040 +"2040-05-21","Whit Monday","NL",2040 +"2040-12-25","Christmas Day","NL",2040 +"2040-12-26","Second Day of Christmas","NL",2040 +"2041-01-01","New Year's Day","NL",2041 +"2041-04-19","Good Friday","NL",2041 +"2041-04-21","Easter Sunday","NL",2041 +"2041-04-22","Easter Monday","NL",2041 +"2041-04-27","King's Day","NL",2041 +"2041-05-30","Ascension Day","NL",2041 +"2041-06-09","Whit Sunday","NL",2041 +"2041-06-10","Whit Monday","NL",2041 +"2041-12-25","Christmas Day","NL",2041 +"2041-12-26","Second Day of Christmas","NL",2041 +"2042-01-01","New Year's Day","NL",2042 +"2042-04-04","Good Friday","NL",2042 +"2042-04-06","Easter Sunday","NL",2042 +"2042-04-07","Easter Monday","NL",2042 +"2042-04-26","King's Day","NL",2042 +"2042-05-15","Ascension Day","NL",2042 +"2042-05-25","Whit Sunday","NL",2042 +"2042-05-26","Whit Monday","NL",2042 +"2042-12-25","Christmas Day","NL",2042 +"2042-12-26","Second Day of Christmas","NL",2042 +"2043-01-01","New Year's Day","NL",2043 +"2043-03-27","Good Friday","NL",2043 +"2043-03-29","Easter Sunday","NL",2043 +"2043-03-30","Easter Monday","NL",2043 +"2043-04-27","King's Day","NL",2043 +"2043-05-07","Ascension Day","NL",2043 +"2043-05-17","Whit Sunday","NL",2043 +"2043-05-18","Whit Monday","NL",2043 +"2043-12-25","Christmas Day","NL",2043 +"2043-12-26","Second Day of Christmas","NL",2043 +"2044-01-01","New Year's Day","NL",2044 +"2044-04-15","Good Friday","NL",2044 +"2044-04-17","Easter Sunday","NL",2044 +"2044-04-18","Easter Monday","NL",2044 +"2044-04-27","King's Day","NL",2044 +"2044-05-26","Ascension Day","NL",2044 +"2044-06-05","Whit Sunday","NL",2044 +"2044-06-06","Whit Monday","NL",2044 +"2044-12-25","Christmas Day","NL",2044 +"2044-12-26","Second Day of Christmas","NL",2044 +"1995-01-01","New Year's Day","NO",1995 +"1995-04-13","Maundy Thursday","NO",1995 +"1995-04-14","Good Friday","NO",1995 +"1995-04-16","Easter Sunday","NO",1995 +"1995-04-17","Easter Monday","NO",1995 +"1995-05-01","Labor Day","NO",1995 +"1995-05-17","Constitution Day","NO",1995 +"1995-05-25","Ascension Day","NO",1995 +"1995-06-04","Whit Sunday","NO",1995 +"1995-06-05","Whit Monday","NO",1995 +"1995-12-25","Christmas Day","NO",1995 +"1995-12-26","Second Day of Christmas","NO",1995 +"1996-01-01","New Year's Day","NO",1996 +"1996-04-04","Maundy Thursday","NO",1996 +"1996-04-05","Good Friday","NO",1996 +"1996-04-07","Easter Sunday","NO",1996 +"1996-04-08","Easter Monday","NO",1996 +"1996-05-01","Labor Day","NO",1996 +"1996-05-16","Ascension Day","NO",1996 +"1996-05-17","Constitution Day","NO",1996 +"1996-05-26","Whit Sunday","NO",1996 +"1996-05-27","Whit Monday","NO",1996 +"1996-12-25","Christmas Day","NO",1996 +"1996-12-26","Second Day of Christmas","NO",1996 +"1997-01-01","New Year's Day","NO",1997 +"1997-03-27","Maundy Thursday","NO",1997 +"1997-03-28","Good Friday","NO",1997 +"1997-03-30","Easter Sunday","NO",1997 +"1997-03-31","Easter Monday","NO",1997 +"1997-05-01","Labor Day","NO",1997 +"1997-05-08","Ascension Day","NO",1997 +"1997-05-17","Constitution Day","NO",1997 +"1997-05-18","Whit Sunday","NO",1997 +"1997-05-19","Whit Monday","NO",1997 +"1997-12-25","Christmas Day","NO",1997 +"1997-12-26","Second Day of Christmas","NO",1997 +"1998-01-01","New Year's Day","NO",1998 +"1998-04-09","Maundy Thursday","NO",1998 +"1998-04-10","Good Friday","NO",1998 +"1998-04-12","Easter Sunday","NO",1998 +"1998-04-13","Easter Monday","NO",1998 +"1998-05-01","Labor Day","NO",1998 +"1998-05-17","Constitution Day","NO",1998 +"1998-05-21","Ascension Day","NO",1998 +"1998-05-31","Whit Sunday","NO",1998 +"1998-06-01","Whit Monday","NO",1998 +"1998-12-25","Christmas Day","NO",1998 +"1998-12-26","Second Day of Christmas","NO",1998 +"1999-01-01","New Year's Day","NO",1999 +"1999-04-01","Maundy Thursday","NO",1999 +"1999-04-02","Good Friday","NO",1999 +"1999-04-04","Easter Sunday","NO",1999 +"1999-04-05","Easter Monday","NO",1999 +"1999-05-01","Labor Day","NO",1999 +"1999-05-13","Ascension Day","NO",1999 +"1999-05-17","Constitution Day","NO",1999 +"1999-05-23","Whit Sunday","NO",1999 +"1999-05-24","Whit Monday","NO",1999 +"1999-12-25","Christmas Day","NO",1999 +"1999-12-26","Second Day of Christmas","NO",1999 +"2000-01-01","New Year's Day","NO",2000 +"2000-04-20","Maundy Thursday","NO",2000 +"2000-04-21","Good Friday","NO",2000 +"2000-04-23","Easter Sunday","NO",2000 +"2000-04-24","Easter Monday","NO",2000 +"2000-05-01","Labor Day","NO",2000 +"2000-05-17","Constitution Day","NO",2000 +"2000-06-01","Ascension Day","NO",2000 +"2000-06-11","Whit Sunday","NO",2000 +"2000-06-12","Whit Monday","NO",2000 +"2000-12-25","Christmas Day","NO",2000 +"2000-12-26","Second Day of Christmas","NO",2000 +"2001-01-01","New Year's Day","NO",2001 +"2001-04-12","Maundy Thursday","NO",2001 +"2001-04-13","Good Friday","NO",2001 +"2001-04-15","Easter Sunday","NO",2001 +"2001-04-16","Easter Monday","NO",2001 +"2001-05-01","Labor Day","NO",2001 +"2001-05-17","Constitution Day","NO",2001 +"2001-05-24","Ascension Day","NO",2001 +"2001-06-03","Whit Sunday","NO",2001 +"2001-06-04","Whit Monday","NO",2001 +"2001-12-25","Christmas Day","NO",2001 +"2001-12-26","Second Day of Christmas","NO",2001 +"2002-01-01","New Year's Day","NO",2002 +"2002-03-28","Maundy Thursday","NO",2002 +"2002-03-29","Good Friday","NO",2002 +"2002-03-31","Easter Sunday","NO",2002 +"2002-04-01","Easter Monday","NO",2002 +"2002-05-01","Labor Day","NO",2002 +"2002-05-09","Ascension Day","NO",2002 +"2002-05-17","Constitution Day","NO",2002 +"2002-05-19","Whit Sunday","NO",2002 +"2002-05-20","Whit Monday","NO",2002 +"2002-12-25","Christmas Day","NO",2002 +"2002-12-26","Second Day of Christmas","NO",2002 +"2003-01-01","New Year's Day","NO",2003 +"2003-04-17","Maundy Thursday","NO",2003 +"2003-04-18","Good Friday","NO",2003 +"2003-04-20","Easter Sunday","NO",2003 +"2003-04-21","Easter Monday","NO",2003 +"2003-05-01","Labor Day","NO",2003 +"2003-05-17","Constitution Day","NO",2003 +"2003-05-29","Ascension Day","NO",2003 +"2003-06-08","Whit Sunday","NO",2003 +"2003-06-09","Whit Monday","NO",2003 +"2003-12-25","Christmas Day","NO",2003 +"2003-12-26","Second Day of Christmas","NO",2003 +"2004-01-01","New Year's Day","NO",2004 +"2004-04-08","Maundy Thursday","NO",2004 +"2004-04-09","Good Friday","NO",2004 +"2004-04-11","Easter Sunday","NO",2004 +"2004-04-12","Easter Monday","NO",2004 +"2004-05-01","Labor Day","NO",2004 +"2004-05-17","Constitution Day","NO",2004 +"2004-05-20","Ascension Day","NO",2004 +"2004-05-30","Whit Sunday","NO",2004 +"2004-05-31","Whit Monday","NO",2004 +"2004-12-25","Christmas Day","NO",2004 +"2004-12-26","Second Day of Christmas","NO",2004 +"2005-01-01","New Year's Day","NO",2005 +"2005-03-24","Maundy Thursday","NO",2005 +"2005-03-25","Good Friday","NO",2005 +"2005-03-27","Easter Sunday","NO",2005 +"2005-03-28","Easter Monday","NO",2005 +"2005-05-01","Labor Day","NO",2005 +"2005-05-05","Ascension Day","NO",2005 +"2005-05-15","Whit Sunday","NO",2005 +"2005-05-16","Whit Monday","NO",2005 +"2005-05-17","Constitution Day","NO",2005 +"2005-12-25","Christmas Day","NO",2005 +"2005-12-26","Second Day of Christmas","NO",2005 +"2006-01-01","New Year's Day","NO",2006 +"2006-04-13","Maundy Thursday","NO",2006 +"2006-04-14","Good Friday","NO",2006 +"2006-04-16","Easter Sunday","NO",2006 +"2006-04-17","Easter Monday","NO",2006 +"2006-05-01","Labor Day","NO",2006 +"2006-05-17","Constitution Day","NO",2006 +"2006-05-25","Ascension Day","NO",2006 +"2006-06-04","Whit Sunday","NO",2006 +"2006-06-05","Whit Monday","NO",2006 +"2006-12-25","Christmas Day","NO",2006 +"2006-12-26","Second Day of Christmas","NO",2006 +"2007-01-01","New Year's Day","NO",2007 +"2007-04-05","Maundy Thursday","NO",2007 +"2007-04-06","Good Friday","NO",2007 +"2007-04-08","Easter Sunday","NO",2007 +"2007-04-09","Easter Monday","NO",2007 +"2007-05-01","Labor Day","NO",2007 +"2007-05-17","Ascension Day","NO",2007 +"2007-05-17","Constitution Day","NO",2007 +"2007-05-27","Whit Sunday","NO",2007 +"2007-05-28","Whit Monday","NO",2007 +"2007-12-25","Christmas Day","NO",2007 +"2007-12-26","Second Day of Christmas","NO",2007 +"2008-01-01","New Year's Day","NO",2008 +"2008-03-20","Maundy Thursday","NO",2008 +"2008-03-21","Good Friday","NO",2008 +"2008-03-23","Easter Sunday","NO",2008 +"2008-03-24","Easter Monday","NO",2008 +"2008-05-01","Ascension Day","NO",2008 +"2008-05-01","Labor Day","NO",2008 +"2008-05-11","Whit Sunday","NO",2008 +"2008-05-12","Whit Monday","NO",2008 +"2008-05-17","Constitution Day","NO",2008 +"2008-12-25","Christmas Day","NO",2008 +"2008-12-26","Second Day of Christmas","NO",2008 +"2009-01-01","New Year's Day","NO",2009 +"2009-04-09","Maundy Thursday","NO",2009 +"2009-04-10","Good Friday","NO",2009 +"2009-04-12","Easter Sunday","NO",2009 +"2009-04-13","Easter Monday","NO",2009 +"2009-05-01","Labor Day","NO",2009 +"2009-05-17","Constitution Day","NO",2009 +"2009-05-21","Ascension Day","NO",2009 +"2009-05-31","Whit Sunday","NO",2009 +"2009-06-01","Whit Monday","NO",2009 +"2009-12-25","Christmas Day","NO",2009 +"2009-12-26","Second Day of Christmas","NO",2009 +"2010-01-01","New Year's Day","NO",2010 +"2010-04-01","Maundy Thursday","NO",2010 +"2010-04-02","Good Friday","NO",2010 +"2010-04-04","Easter Sunday","NO",2010 +"2010-04-05","Easter Monday","NO",2010 +"2010-05-01","Labor Day","NO",2010 +"2010-05-13","Ascension Day","NO",2010 +"2010-05-17","Constitution Day","NO",2010 +"2010-05-23","Whit Sunday","NO",2010 +"2010-05-24","Whit Monday","NO",2010 +"2010-12-25","Christmas Day","NO",2010 +"2010-12-26","Second Day of Christmas","NO",2010 +"2011-01-01","New Year's Day","NO",2011 +"2011-04-21","Maundy Thursday","NO",2011 +"2011-04-22","Good Friday","NO",2011 +"2011-04-24","Easter Sunday","NO",2011 +"2011-04-25","Easter Monday","NO",2011 +"2011-05-01","Labor Day","NO",2011 +"2011-05-17","Constitution Day","NO",2011 +"2011-06-02","Ascension Day","NO",2011 +"2011-06-12","Whit Sunday","NO",2011 +"2011-06-13","Whit Monday","NO",2011 +"2011-12-25","Christmas Day","NO",2011 +"2011-12-26","Second Day of Christmas","NO",2011 +"2012-01-01","New Year's Day","NO",2012 +"2012-04-05","Maundy Thursday","NO",2012 +"2012-04-06","Good Friday","NO",2012 +"2012-04-08","Easter Sunday","NO",2012 +"2012-04-09","Easter Monday","NO",2012 +"2012-05-01","Labor Day","NO",2012 +"2012-05-17","Ascension Day","NO",2012 +"2012-05-17","Constitution Day","NO",2012 +"2012-05-27","Whit Sunday","NO",2012 +"2012-05-28","Whit Monday","NO",2012 +"2012-12-25","Christmas Day","NO",2012 +"2012-12-26","Second Day of Christmas","NO",2012 +"2013-01-01","New Year's Day","NO",2013 +"2013-03-28","Maundy Thursday","NO",2013 +"2013-03-29","Good Friday","NO",2013 +"2013-03-31","Easter Sunday","NO",2013 +"2013-04-01","Easter Monday","NO",2013 +"2013-05-01","Labor Day","NO",2013 +"2013-05-09","Ascension Day","NO",2013 +"2013-05-17","Constitution Day","NO",2013 +"2013-05-19","Whit Sunday","NO",2013 +"2013-05-20","Whit Monday","NO",2013 +"2013-12-25","Christmas Day","NO",2013 +"2013-12-26","Second Day of Christmas","NO",2013 +"2014-01-01","New Year's Day","NO",2014 +"2014-04-17","Maundy Thursday","NO",2014 +"2014-04-18","Good Friday","NO",2014 +"2014-04-20","Easter Sunday","NO",2014 +"2014-04-21","Easter Monday","NO",2014 +"2014-05-01","Labor Day","NO",2014 +"2014-05-17","Constitution Day","NO",2014 +"2014-05-29","Ascension Day","NO",2014 +"2014-06-08","Whit Sunday","NO",2014 +"2014-06-09","Whit Monday","NO",2014 +"2014-12-25","Christmas Day","NO",2014 +"2014-12-26","Second Day of Christmas","NO",2014 +"2015-01-01","New Year's Day","NO",2015 +"2015-04-02","Maundy Thursday","NO",2015 +"2015-04-03","Good Friday","NO",2015 +"2015-04-05","Easter Sunday","NO",2015 +"2015-04-06","Easter Monday","NO",2015 +"2015-05-01","Labor Day","NO",2015 +"2015-05-14","Ascension Day","NO",2015 +"2015-05-17","Constitution Day","NO",2015 +"2015-05-24","Whit Sunday","NO",2015 +"2015-05-25","Whit Monday","NO",2015 +"2015-12-25","Christmas Day","NO",2015 +"2015-12-26","Second Day of Christmas","NO",2015 +"2016-01-01","New Year's Day","NO",2016 +"2016-03-24","Maundy Thursday","NO",2016 +"2016-03-25","Good Friday","NO",2016 +"2016-03-27","Easter Sunday","NO",2016 +"2016-03-28","Easter Monday","NO",2016 +"2016-05-01","Labor Day","NO",2016 +"2016-05-05","Ascension Day","NO",2016 +"2016-05-15","Whit Sunday","NO",2016 +"2016-05-16","Whit Monday","NO",2016 +"2016-05-17","Constitution Day","NO",2016 +"2016-12-25","Christmas Day","NO",2016 +"2016-12-26","Second Day of Christmas","NO",2016 +"2017-01-01","New Year's Day","NO",2017 +"2017-04-13","Maundy Thursday","NO",2017 +"2017-04-14","Good Friday","NO",2017 +"2017-04-16","Easter Sunday","NO",2017 +"2017-04-17","Easter Monday","NO",2017 +"2017-05-01","Labor Day","NO",2017 +"2017-05-17","Constitution Day","NO",2017 +"2017-05-25","Ascension Day","NO",2017 +"2017-06-04","Whit Sunday","NO",2017 +"2017-06-05","Whit Monday","NO",2017 +"2017-12-25","Christmas Day","NO",2017 +"2017-12-26","Second Day of Christmas","NO",2017 +"2018-01-01","New Year's Day","NO",2018 +"2018-03-29","Maundy Thursday","NO",2018 +"2018-03-30","Good Friday","NO",2018 +"2018-04-01","Easter Sunday","NO",2018 +"2018-04-02","Easter Monday","NO",2018 +"2018-05-01","Labor Day","NO",2018 +"2018-05-10","Ascension Day","NO",2018 +"2018-05-17","Constitution Day","NO",2018 +"2018-05-20","Whit Sunday","NO",2018 +"2018-05-21","Whit Monday","NO",2018 +"2018-12-25","Christmas Day","NO",2018 +"2018-12-26","Second Day of Christmas","NO",2018 +"2019-01-01","New Year's Day","NO",2019 +"2019-04-18","Maundy Thursday","NO",2019 +"2019-04-19","Good Friday","NO",2019 +"2019-04-21","Easter Sunday","NO",2019 +"2019-04-22","Easter Monday","NO",2019 +"2019-05-01","Labor Day","NO",2019 +"2019-05-17","Constitution Day","NO",2019 +"2019-05-30","Ascension Day","NO",2019 +"2019-06-09","Whit Sunday","NO",2019 +"2019-06-10","Whit Monday","NO",2019 +"2019-12-25","Christmas Day","NO",2019 +"2019-12-26","Second Day of Christmas","NO",2019 +"2020-01-01","New Year's Day","NO",2020 +"2020-04-09","Maundy Thursday","NO",2020 +"2020-04-10","Good Friday","NO",2020 +"2020-04-12","Easter Sunday","NO",2020 +"2020-04-13","Easter Monday","NO",2020 +"2020-05-01","Labor Day","NO",2020 +"2020-05-17","Constitution Day","NO",2020 +"2020-05-21","Ascension Day","NO",2020 +"2020-05-31","Whit Sunday","NO",2020 +"2020-06-01","Whit Monday","NO",2020 +"2020-12-25","Christmas Day","NO",2020 +"2020-12-26","Second Day of Christmas","NO",2020 +"2021-01-01","New Year's Day","NO",2021 +"2021-04-01","Maundy Thursday","NO",2021 +"2021-04-02","Good Friday","NO",2021 +"2021-04-04","Easter Sunday","NO",2021 +"2021-04-05","Easter Monday","NO",2021 +"2021-05-01","Labor Day","NO",2021 +"2021-05-13","Ascension Day","NO",2021 +"2021-05-17","Constitution Day","NO",2021 +"2021-05-23","Whit Sunday","NO",2021 +"2021-05-24","Whit Monday","NO",2021 +"2021-12-25","Christmas Day","NO",2021 +"2021-12-26","Second Day of Christmas","NO",2021 +"2022-01-01","New Year's Day","NO",2022 +"2022-04-14","Maundy Thursday","NO",2022 +"2022-04-15","Good Friday","NO",2022 +"2022-04-17","Easter Sunday","NO",2022 +"2022-04-18","Easter Monday","NO",2022 +"2022-05-01","Labor Day","NO",2022 +"2022-05-17","Constitution Day","NO",2022 +"2022-05-26","Ascension Day","NO",2022 +"2022-06-05","Whit Sunday","NO",2022 +"2022-06-06","Whit Monday","NO",2022 +"2022-12-25","Christmas Day","NO",2022 +"2022-12-26","Second Day of Christmas","NO",2022 +"2023-01-01","New Year's Day","NO",2023 +"2023-04-06","Maundy Thursday","NO",2023 +"2023-04-07","Good Friday","NO",2023 +"2023-04-09","Easter Sunday","NO",2023 +"2023-04-10","Easter Monday","NO",2023 +"2023-05-01","Labor Day","NO",2023 +"2023-05-17","Constitution Day","NO",2023 +"2023-05-18","Ascension Day","NO",2023 +"2023-05-28","Whit Sunday","NO",2023 +"2023-05-29","Whit Monday","NO",2023 +"2023-12-25","Christmas Day","NO",2023 +"2023-12-26","Second Day of Christmas","NO",2023 +"2024-01-01","New Year's Day","NO",2024 +"2024-03-28","Maundy Thursday","NO",2024 +"2024-03-29","Good Friday","NO",2024 +"2024-03-31","Easter Sunday","NO",2024 +"2024-04-01","Easter Monday","NO",2024 +"2024-05-01","Labor Day","NO",2024 +"2024-05-09","Ascension Day","NO",2024 +"2024-05-17","Constitution Day","NO",2024 +"2024-05-19","Whit Sunday","NO",2024 +"2024-05-20","Whit Monday","NO",2024 +"2024-12-25","Christmas Day","NO",2024 +"2024-12-26","Second Day of Christmas","NO",2024 +"2025-01-01","New Year's Day","NO",2025 +"2025-04-17","Maundy Thursday","NO",2025 +"2025-04-18","Good Friday","NO",2025 +"2025-04-20","Easter Sunday","NO",2025 +"2025-04-21","Easter Monday","NO",2025 +"2025-05-01","Labor Day","NO",2025 +"2025-05-17","Constitution Day","NO",2025 +"2025-05-29","Ascension Day","NO",2025 +"2025-06-08","Whit Sunday","NO",2025 +"2025-06-09","Whit Monday","NO",2025 +"2025-12-25","Christmas Day","NO",2025 +"2025-12-26","Second Day of Christmas","NO",2025 +"2026-01-01","New Year's Day","NO",2026 +"2026-04-02","Maundy Thursday","NO",2026 +"2026-04-03","Good Friday","NO",2026 +"2026-04-05","Easter Sunday","NO",2026 +"2026-04-06","Easter Monday","NO",2026 +"2026-05-01","Labor Day","NO",2026 +"2026-05-14","Ascension Day","NO",2026 +"2026-05-17","Constitution Day","NO",2026 +"2026-05-24","Whit Sunday","NO",2026 +"2026-05-25","Whit Monday","NO",2026 +"2026-12-25","Christmas Day","NO",2026 +"2026-12-26","Second Day of Christmas","NO",2026 +"2027-01-01","New Year's Day","NO",2027 +"2027-03-25","Maundy Thursday","NO",2027 +"2027-03-26","Good Friday","NO",2027 +"2027-03-28","Easter Sunday","NO",2027 +"2027-03-29","Easter Monday","NO",2027 +"2027-05-01","Labor Day","NO",2027 +"2027-05-06","Ascension Day","NO",2027 +"2027-05-16","Whit Sunday","NO",2027 +"2027-05-17","Constitution Day","NO",2027 +"2027-05-17","Whit Monday","NO",2027 +"2027-12-25","Christmas Day","NO",2027 +"2027-12-26","Second Day of Christmas","NO",2027 +"2028-01-01","New Year's Day","NO",2028 +"2028-04-13","Maundy Thursday","NO",2028 +"2028-04-14","Good Friday","NO",2028 +"2028-04-16","Easter Sunday","NO",2028 +"2028-04-17","Easter Monday","NO",2028 +"2028-05-01","Labor Day","NO",2028 +"2028-05-17","Constitution Day","NO",2028 +"2028-05-25","Ascension Day","NO",2028 +"2028-06-04","Whit Sunday","NO",2028 +"2028-06-05","Whit Monday","NO",2028 +"2028-12-25","Christmas Day","NO",2028 +"2028-12-26","Second Day of Christmas","NO",2028 +"2029-01-01","New Year's Day","NO",2029 +"2029-03-29","Maundy Thursday","NO",2029 +"2029-03-30","Good Friday","NO",2029 +"2029-04-01","Easter Sunday","NO",2029 +"2029-04-02","Easter Monday","NO",2029 +"2029-05-01","Labor Day","NO",2029 +"2029-05-10","Ascension Day","NO",2029 +"2029-05-17","Constitution Day","NO",2029 +"2029-05-20","Whit Sunday","NO",2029 +"2029-05-21","Whit Monday","NO",2029 +"2029-12-25","Christmas Day","NO",2029 +"2029-12-26","Second Day of Christmas","NO",2029 +"2030-01-01","New Year's Day","NO",2030 +"2030-04-18","Maundy Thursday","NO",2030 +"2030-04-19","Good Friday","NO",2030 +"2030-04-21","Easter Sunday","NO",2030 +"2030-04-22","Easter Monday","NO",2030 +"2030-05-01","Labor Day","NO",2030 +"2030-05-17","Constitution Day","NO",2030 +"2030-05-30","Ascension Day","NO",2030 +"2030-06-09","Whit Sunday","NO",2030 +"2030-06-10","Whit Monday","NO",2030 +"2030-12-25","Christmas Day","NO",2030 +"2030-12-26","Second Day of Christmas","NO",2030 +"2031-01-01","New Year's Day","NO",2031 +"2031-04-10","Maundy Thursday","NO",2031 +"2031-04-11","Good Friday","NO",2031 +"2031-04-13","Easter Sunday","NO",2031 +"2031-04-14","Easter Monday","NO",2031 +"2031-05-01","Labor Day","NO",2031 +"2031-05-17","Constitution Day","NO",2031 +"2031-05-22","Ascension Day","NO",2031 +"2031-06-01","Whit Sunday","NO",2031 +"2031-06-02","Whit Monday","NO",2031 +"2031-12-25","Christmas Day","NO",2031 +"2031-12-26","Second Day of Christmas","NO",2031 +"2032-01-01","New Year's Day","NO",2032 +"2032-03-25","Maundy Thursday","NO",2032 +"2032-03-26","Good Friday","NO",2032 +"2032-03-28","Easter Sunday","NO",2032 +"2032-03-29","Easter Monday","NO",2032 +"2032-05-01","Labor Day","NO",2032 +"2032-05-06","Ascension Day","NO",2032 +"2032-05-16","Whit Sunday","NO",2032 +"2032-05-17","Constitution Day","NO",2032 +"2032-05-17","Whit Monday","NO",2032 +"2032-12-25","Christmas Day","NO",2032 +"2032-12-26","Second Day of Christmas","NO",2032 +"2033-01-01","New Year's Day","NO",2033 +"2033-04-14","Maundy Thursday","NO",2033 +"2033-04-15","Good Friday","NO",2033 +"2033-04-17","Easter Sunday","NO",2033 +"2033-04-18","Easter Monday","NO",2033 +"2033-05-01","Labor Day","NO",2033 +"2033-05-17","Constitution Day","NO",2033 +"2033-05-26","Ascension Day","NO",2033 +"2033-06-05","Whit Sunday","NO",2033 +"2033-06-06","Whit Monday","NO",2033 +"2033-12-25","Christmas Day","NO",2033 +"2033-12-26","Second Day of Christmas","NO",2033 +"2034-01-01","New Year's Day","NO",2034 +"2034-04-06","Maundy Thursday","NO",2034 +"2034-04-07","Good Friday","NO",2034 +"2034-04-09","Easter Sunday","NO",2034 +"2034-04-10","Easter Monday","NO",2034 +"2034-05-01","Labor Day","NO",2034 +"2034-05-17","Constitution Day","NO",2034 +"2034-05-18","Ascension Day","NO",2034 +"2034-05-28","Whit Sunday","NO",2034 +"2034-05-29","Whit Monday","NO",2034 +"2034-12-25","Christmas Day","NO",2034 +"2034-12-26","Second Day of Christmas","NO",2034 +"2035-01-01","New Year's Day","NO",2035 +"2035-03-22","Maundy Thursday","NO",2035 +"2035-03-23","Good Friday","NO",2035 +"2035-03-25","Easter Sunday","NO",2035 +"2035-03-26","Easter Monday","NO",2035 +"2035-05-01","Labor Day","NO",2035 +"2035-05-03","Ascension Day","NO",2035 +"2035-05-13","Whit Sunday","NO",2035 +"2035-05-14","Whit Monday","NO",2035 +"2035-05-17","Constitution Day","NO",2035 +"2035-12-25","Christmas Day","NO",2035 +"2035-12-26","Second Day of Christmas","NO",2035 +"2036-01-01","New Year's Day","NO",2036 +"2036-04-10","Maundy Thursday","NO",2036 +"2036-04-11","Good Friday","NO",2036 +"2036-04-13","Easter Sunday","NO",2036 +"2036-04-14","Easter Monday","NO",2036 +"2036-05-01","Labor Day","NO",2036 +"2036-05-17","Constitution Day","NO",2036 +"2036-05-22","Ascension Day","NO",2036 +"2036-06-01","Whit Sunday","NO",2036 +"2036-06-02","Whit Monday","NO",2036 +"2036-12-25","Christmas Day","NO",2036 +"2036-12-26","Second Day of Christmas","NO",2036 +"2037-01-01","New Year's Day","NO",2037 +"2037-04-02","Maundy Thursday","NO",2037 +"2037-04-03","Good Friday","NO",2037 +"2037-04-05","Easter Sunday","NO",2037 +"2037-04-06","Easter Monday","NO",2037 +"2037-05-01","Labor Day","NO",2037 +"2037-05-14","Ascension Day","NO",2037 +"2037-05-17","Constitution Day","NO",2037 +"2037-05-24","Whit Sunday","NO",2037 +"2037-05-25","Whit Monday","NO",2037 +"2037-12-25","Christmas Day","NO",2037 +"2037-12-26","Second Day of Christmas","NO",2037 +"2038-01-01","New Year's Day","NO",2038 +"2038-04-22","Maundy Thursday","NO",2038 +"2038-04-23","Good Friday","NO",2038 +"2038-04-25","Easter Sunday","NO",2038 +"2038-04-26","Easter Monday","NO",2038 +"2038-05-01","Labor Day","NO",2038 +"2038-05-17","Constitution Day","NO",2038 +"2038-06-03","Ascension Day","NO",2038 +"2038-06-13","Whit Sunday","NO",2038 +"2038-06-14","Whit Monday","NO",2038 +"2038-12-25","Christmas Day","NO",2038 +"2038-12-26","Second Day of Christmas","NO",2038 +"2039-01-01","New Year's Day","NO",2039 +"2039-04-07","Maundy Thursday","NO",2039 +"2039-04-08","Good Friday","NO",2039 +"2039-04-10","Easter Sunday","NO",2039 +"2039-04-11","Easter Monday","NO",2039 +"2039-05-01","Labor Day","NO",2039 +"2039-05-17","Constitution Day","NO",2039 +"2039-05-19","Ascension Day","NO",2039 +"2039-05-29","Whit Sunday","NO",2039 +"2039-05-30","Whit Monday","NO",2039 +"2039-12-25","Christmas Day","NO",2039 +"2039-12-26","Second Day of Christmas","NO",2039 +"2040-01-01","New Year's Day","NO",2040 +"2040-03-29","Maundy Thursday","NO",2040 +"2040-03-30","Good Friday","NO",2040 +"2040-04-01","Easter Sunday","NO",2040 +"2040-04-02","Easter Monday","NO",2040 +"2040-05-01","Labor Day","NO",2040 +"2040-05-10","Ascension Day","NO",2040 +"2040-05-17","Constitution Day","NO",2040 +"2040-05-20","Whit Sunday","NO",2040 +"2040-05-21","Whit Monday","NO",2040 +"2040-12-25","Christmas Day","NO",2040 +"2040-12-26","Second Day of Christmas","NO",2040 +"2041-01-01","New Year's Day","NO",2041 +"2041-04-18","Maundy Thursday","NO",2041 +"2041-04-19","Good Friday","NO",2041 +"2041-04-21","Easter Sunday","NO",2041 +"2041-04-22","Easter Monday","NO",2041 +"2041-05-01","Labor Day","NO",2041 +"2041-05-17","Constitution Day","NO",2041 +"2041-05-30","Ascension Day","NO",2041 +"2041-06-09","Whit Sunday","NO",2041 +"2041-06-10","Whit Monday","NO",2041 +"2041-12-25","Christmas Day","NO",2041 +"2041-12-26","Second Day of Christmas","NO",2041 +"2042-01-01","New Year's Day","NO",2042 +"2042-04-03","Maundy Thursday","NO",2042 +"2042-04-04","Good Friday","NO",2042 +"2042-04-06","Easter Sunday","NO",2042 +"2042-04-07","Easter Monday","NO",2042 +"2042-05-01","Labor Day","NO",2042 +"2042-05-15","Ascension Day","NO",2042 +"2042-05-17","Constitution Day","NO",2042 +"2042-05-25","Whit Sunday","NO",2042 +"2042-05-26","Whit Monday","NO",2042 +"2042-12-25","Christmas Day","NO",2042 +"2042-12-26","Second Day of Christmas","NO",2042 +"2043-01-01","New Year's Day","NO",2043 +"2043-03-26","Maundy Thursday","NO",2043 +"2043-03-27","Good Friday","NO",2043 +"2043-03-29","Easter Sunday","NO",2043 +"2043-03-30","Easter Monday","NO",2043 +"2043-05-01","Labor Day","NO",2043 +"2043-05-07","Ascension Day","NO",2043 +"2043-05-17","Constitution Day","NO",2043 +"2043-05-17","Whit Sunday","NO",2043 +"2043-05-18","Whit Monday","NO",2043 +"2043-12-25","Christmas Day","NO",2043 +"2043-12-26","Second Day of Christmas","NO",2043 +"2044-01-01","New Year's Day","NO",2044 +"2044-04-14","Maundy Thursday","NO",2044 +"2044-04-15","Good Friday","NO",2044 +"2044-04-17","Easter Sunday","NO",2044 +"2044-04-18","Easter Monday","NO",2044 +"2044-05-01","Labor Day","NO",2044 +"2044-05-17","Constitution Day","NO",2044 +"2044-05-26","Ascension Day","NO",2044 +"2044-06-05","Whit Sunday","NO",2044 +"2044-06-06","Whit Monday","NO",2044 +"2044-12-25","Christmas Day","NO",2044 +"2044-12-26","Second Day of Christmas","NO",2044 +"1995-01-01","New Year's Day","NZ",1995 +"1995-01-02","Day after New Year's Day","NZ",1995 +"1995-01-03","New Year's Day (Observed)","NZ",1995 +"1995-02-06","Waitangi Day","NZ",1995 +"1995-04-14","Good Friday","NZ",1995 +"1995-04-17","Easter Monday","NZ",1995 +"1995-04-25","Anzac Day","NZ",1995 +"1995-06-05","Queen's Birthday","NZ",1995 +"1995-10-23","Labour Day","NZ",1995 +"1995-12-25","Christmas Day","NZ",1995 +"1995-12-26","Boxing Day","NZ",1995 +"1996-01-01","New Year's Day","NZ",1996 +"1996-01-02","Day after New Year's Day","NZ",1996 +"1996-02-06","Waitangi Day","NZ",1996 +"1996-04-05","Good Friday","NZ",1996 +"1996-04-08","Easter Monday","NZ",1996 +"1996-04-25","Anzac Day","NZ",1996 +"1996-06-03","Queen's Birthday","NZ",1996 +"1996-10-28","Labour Day","NZ",1996 +"1996-12-25","Christmas Day","NZ",1996 +"1996-12-26","Boxing Day","NZ",1996 +"1997-01-01","New Year's Day","NZ",1997 +"1997-01-02","Day after New Year's Day","NZ",1997 +"1997-02-06","Waitangi Day","NZ",1997 +"1997-03-28","Good Friday","NZ",1997 +"1997-03-31","Easter Monday","NZ",1997 +"1997-04-25","Anzac Day","NZ",1997 +"1997-06-02","Queen's Birthday","NZ",1997 +"1997-10-27","Labour Day","NZ",1997 +"1997-12-25","Christmas Day","NZ",1997 +"1997-12-26","Boxing Day","NZ",1997 +"1998-01-01","New Year's Day","NZ",1998 +"1998-01-02","Day after New Year's Day","NZ",1998 +"1998-02-06","Waitangi Day","NZ",1998 +"1998-04-10","Good Friday","NZ",1998 +"1998-04-13","Easter Monday","NZ",1998 +"1998-04-25","Anzac Day","NZ",1998 +"1998-06-01","Queen's Birthday","NZ",1998 +"1998-10-26","Labour Day","NZ",1998 +"1998-12-25","Christmas Day","NZ",1998 +"1998-12-26","Boxing Day","NZ",1998 +"1998-12-28","Boxing Day (Observed)","NZ",1998 +"1999-01-01","New Year's Day","NZ",1999 +"1999-01-02","Day after New Year's Day","NZ",1999 +"1999-01-04","Day after New Year's Day (Observed)","NZ",1999 +"1999-02-06","Waitangi Day","NZ",1999 +"1999-04-02","Good Friday","NZ",1999 +"1999-04-05","Easter Monday","NZ",1999 +"1999-04-25","Anzac Day","NZ",1999 +"1999-06-07","Queen's Birthday","NZ",1999 +"1999-10-25","Labour Day","NZ",1999 +"1999-12-25","Christmas Day","NZ",1999 +"1999-12-26","Boxing Day","NZ",1999 +"1999-12-27","Christmas Day (Observed)","NZ",1999 +"1999-12-28","Boxing Day (Observed)","NZ",1999 +"2000-01-01","New Year's Day","NZ",2000 +"2000-01-02","Day after New Year's Day","NZ",2000 +"2000-01-03","New Year's Day (Observed)","NZ",2000 +"2000-01-04","Day after New Year's Day (Observed)","NZ",2000 +"2000-02-06","Waitangi Day","NZ",2000 +"2000-04-21","Good Friday","NZ",2000 +"2000-04-24","Easter Monday","NZ",2000 +"2000-04-25","Anzac Day","NZ",2000 +"2000-06-05","Queen's Birthday","NZ",2000 +"2000-10-23","Labour Day","NZ",2000 +"2000-12-25","Christmas Day","NZ",2000 +"2000-12-26","Boxing Day","NZ",2000 +"2001-01-01","New Year's Day","NZ",2001 +"2001-01-02","Day after New Year's Day","NZ",2001 +"2001-02-06","Waitangi Day","NZ",2001 +"2001-04-13","Good Friday","NZ",2001 +"2001-04-16","Easter Monday","NZ",2001 +"2001-04-25","Anzac Day","NZ",2001 +"2001-06-04","Queen's Birthday","NZ",2001 +"2001-10-22","Labour Day","NZ",2001 +"2001-12-25","Christmas Day","NZ",2001 +"2001-12-26","Boxing Day","NZ",2001 +"2002-01-01","New Year's Day","NZ",2002 +"2002-01-02","Day after New Year's Day","NZ",2002 +"2002-02-06","Waitangi Day","NZ",2002 +"2002-03-29","Good Friday","NZ",2002 +"2002-04-01","Easter Monday","NZ",2002 +"2002-04-25","Anzac Day","NZ",2002 +"2002-06-03","Queen's Birthday","NZ",2002 +"2002-10-28","Labour Day","NZ",2002 +"2002-12-25","Christmas Day","NZ",2002 +"2002-12-26","Boxing Day","NZ",2002 +"2003-01-01","New Year's Day","NZ",2003 +"2003-01-02","Day after New Year's Day","NZ",2003 +"2003-02-06","Waitangi Day","NZ",2003 +"2003-04-18","Good Friday","NZ",2003 +"2003-04-21","Easter Monday","NZ",2003 +"2003-04-25","Anzac Day","NZ",2003 +"2003-06-02","Queen's Birthday","NZ",2003 +"2003-10-27","Labour Day","NZ",2003 +"2003-12-25","Christmas Day","NZ",2003 +"2003-12-26","Boxing Day","NZ",2003 +"2004-01-01","New Year's Day","NZ",2004 +"2004-01-02","Day after New Year's Day","NZ",2004 +"2004-02-06","Waitangi Day","NZ",2004 +"2004-04-09","Good Friday","NZ",2004 +"2004-04-12","Easter Monday","NZ",2004 +"2004-04-25","Anzac Day","NZ",2004 +"2004-06-07","Queen's Birthday","NZ",2004 +"2004-10-25","Labour Day","NZ",2004 +"2004-12-25","Christmas Day","NZ",2004 +"2004-12-26","Boxing Day","NZ",2004 +"2004-12-27","Christmas Day (Observed)","NZ",2004 +"2004-12-28","Boxing Day (Observed)","NZ",2004 +"2005-01-01","New Year's Day","NZ",2005 +"2005-01-02","Day after New Year's Day","NZ",2005 +"2005-01-03","New Year's Day (Observed)","NZ",2005 +"2005-01-04","Day after New Year's Day (Observed)","NZ",2005 +"2005-02-06","Waitangi Day","NZ",2005 +"2005-03-25","Good Friday","NZ",2005 +"2005-03-28","Easter Monday","NZ",2005 +"2005-04-25","Anzac Day","NZ",2005 +"2005-06-06","Queen's Birthday","NZ",2005 +"2005-10-24","Labour Day","NZ",2005 +"2005-12-25","Christmas Day","NZ",2005 +"2005-12-26","Boxing Day","NZ",2005 +"2005-12-27","Christmas Day (Observed)","NZ",2005 +"2006-01-01","New Year's Day","NZ",2006 +"2006-01-02","Day after New Year's Day","NZ",2006 +"2006-01-03","New Year's Day (Observed)","NZ",2006 +"2006-02-06","Waitangi Day","NZ",2006 +"2006-04-14","Good Friday","NZ",2006 +"2006-04-17","Easter Monday","NZ",2006 +"2006-04-25","Anzac Day","NZ",2006 +"2006-06-05","Queen's Birthday","NZ",2006 +"2006-10-23","Labour Day","NZ",2006 +"2006-12-25","Christmas Day","NZ",2006 +"2006-12-26","Boxing Day","NZ",2006 +"2007-01-01","New Year's Day","NZ",2007 +"2007-01-02","Day after New Year's Day","NZ",2007 +"2007-02-06","Waitangi Day","NZ",2007 +"2007-04-06","Good Friday","NZ",2007 +"2007-04-09","Easter Monday","NZ",2007 +"2007-04-25","Anzac Day","NZ",2007 +"2007-06-04","Queen's Birthday","NZ",2007 +"2007-10-22","Labour Day","NZ",2007 +"2007-12-25","Christmas Day","NZ",2007 +"2007-12-26","Boxing Day","NZ",2007 +"2008-01-01","New Year's Day","NZ",2008 +"2008-01-02","Day after New Year's Day","NZ",2008 +"2008-02-06","Waitangi Day","NZ",2008 +"2008-03-21","Good Friday","NZ",2008 +"2008-03-24","Easter Monday","NZ",2008 +"2008-04-25","Anzac Day","NZ",2008 +"2008-06-02","Queen's Birthday","NZ",2008 +"2008-10-27","Labour Day","NZ",2008 +"2008-12-25","Christmas Day","NZ",2008 +"2008-12-26","Boxing Day","NZ",2008 +"2009-01-01","New Year's Day","NZ",2009 +"2009-01-02","Day after New Year's Day","NZ",2009 +"2009-02-06","Waitangi Day","NZ",2009 +"2009-04-10","Good Friday","NZ",2009 +"2009-04-13","Easter Monday","NZ",2009 +"2009-04-25","Anzac Day","NZ",2009 +"2009-06-01","Queen's Birthday","NZ",2009 +"2009-10-26","Labour Day","NZ",2009 +"2009-12-25","Christmas Day","NZ",2009 +"2009-12-26","Boxing Day","NZ",2009 +"2009-12-28","Boxing Day (Observed)","NZ",2009 +"2010-01-01","New Year's Day","NZ",2010 +"2010-01-02","Day after New Year's Day","NZ",2010 +"2010-01-04","Day after New Year's Day (Observed)","NZ",2010 +"2010-02-06","Waitangi Day","NZ",2010 +"2010-04-02","Good Friday","NZ",2010 +"2010-04-05","Easter Monday","NZ",2010 +"2010-04-25","Anzac Day","NZ",2010 +"2010-06-07","Queen's Birthday","NZ",2010 +"2010-10-25","Labour Day","NZ",2010 +"2010-12-25","Christmas Day","NZ",2010 +"2010-12-26","Boxing Day","NZ",2010 +"2010-12-27","Christmas Day (Observed)","NZ",2010 +"2010-12-28","Boxing Day (Observed)","NZ",2010 +"2011-01-01","New Year's Day","NZ",2011 +"2011-01-02","Day after New Year's Day","NZ",2011 +"2011-01-03","New Year's Day (Observed)","NZ",2011 +"2011-01-04","Day after New Year's Day (Observed)","NZ",2011 +"2011-02-06","Waitangi Day","NZ",2011 +"2011-04-22","Good Friday","NZ",2011 +"2011-04-25","Anzac Day","NZ",2011 +"2011-04-25","Easter Monday","NZ",2011 +"2011-06-06","Queen's Birthday","NZ",2011 +"2011-10-24","Labour Day","NZ",2011 +"2011-12-25","Christmas Day","NZ",2011 +"2011-12-26","Boxing Day","NZ",2011 +"2011-12-27","Christmas Day (Observed)","NZ",2011 +"2012-01-01","New Year's Day","NZ",2012 +"2012-01-02","Day after New Year's Day","NZ",2012 +"2012-01-03","New Year's Day (Observed)","NZ",2012 +"2012-02-06","Waitangi Day","NZ",2012 +"2012-04-06","Good Friday","NZ",2012 +"2012-04-09","Easter Monday","NZ",2012 +"2012-04-25","Anzac Day","NZ",2012 +"2012-06-04","Queen's Birthday","NZ",2012 +"2012-10-22","Labour Day","NZ",2012 +"2012-12-25","Christmas Day","NZ",2012 +"2012-12-26","Boxing Day","NZ",2012 +"2013-01-01","New Year's Day","NZ",2013 +"2013-01-02","Day after New Year's Day","NZ",2013 +"2013-02-06","Waitangi Day","NZ",2013 +"2013-03-29","Good Friday","NZ",2013 +"2013-04-01","Easter Monday","NZ",2013 +"2013-04-25","Anzac Day","NZ",2013 +"2013-06-03","Queen's Birthday","NZ",2013 +"2013-10-28","Labour Day","NZ",2013 +"2013-12-25","Christmas Day","NZ",2013 +"2013-12-26","Boxing Day","NZ",2013 +"2014-01-01","New Year's Day","NZ",2014 +"2014-01-02","Day after New Year's Day","NZ",2014 +"2014-02-06","Waitangi Day","NZ",2014 +"2014-04-18","Good Friday","NZ",2014 +"2014-04-21","Easter Monday","NZ",2014 +"2014-04-25","Anzac Day","NZ",2014 +"2014-06-02","Queen's Birthday","NZ",2014 +"2014-10-27","Labour Day","NZ",2014 +"2014-12-25","Christmas Day","NZ",2014 +"2014-12-26","Boxing Day","NZ",2014 +"2015-01-01","New Year's Day","NZ",2015 +"2015-01-02","Day after New Year's Day","NZ",2015 +"2015-02-06","Waitangi Day","NZ",2015 +"2015-04-03","Good Friday","NZ",2015 +"2015-04-06","Easter Monday","NZ",2015 +"2015-04-25","Anzac Day","NZ",2015 +"2015-04-27","Anzac Day (Observed)","NZ",2015 +"2015-06-01","Queen's Birthday","NZ",2015 +"2015-10-26","Labour Day","NZ",2015 +"2015-12-25","Christmas Day","NZ",2015 +"2015-12-26","Boxing Day","NZ",2015 +"2015-12-28","Boxing Day (Observed)","NZ",2015 +"2016-01-01","New Year's Day","NZ",2016 +"2016-01-02","Day after New Year's Day","NZ",2016 +"2016-01-04","Day after New Year's Day (Observed)","NZ",2016 +"2016-02-06","Waitangi Day","NZ",2016 +"2016-02-08","Waitangi Day (Observed)","NZ",2016 +"2016-03-25","Good Friday","NZ",2016 +"2016-03-28","Easter Monday","NZ",2016 +"2016-04-25","Anzac Day","NZ",2016 +"2016-06-06","Queen's Birthday","NZ",2016 +"2016-10-24","Labour Day","NZ",2016 +"2016-12-25","Christmas Day","NZ",2016 +"2016-12-26","Boxing Day","NZ",2016 +"2016-12-27","Christmas Day (Observed)","NZ",2016 +"2017-01-01","New Year's Day","NZ",2017 +"2017-01-02","Day after New Year's Day","NZ",2017 +"2017-01-03","New Year's Day (Observed)","NZ",2017 +"2017-02-06","Waitangi Day","NZ",2017 +"2017-04-14","Good Friday","NZ",2017 +"2017-04-17","Easter Monday","NZ",2017 +"2017-04-25","Anzac Day","NZ",2017 +"2017-06-05","Queen's Birthday","NZ",2017 +"2017-10-23","Labour Day","NZ",2017 +"2017-12-25","Christmas Day","NZ",2017 +"2017-12-26","Boxing Day","NZ",2017 +"2018-01-01","New Year's Day","NZ",2018 +"2018-01-02","Day after New Year's Day","NZ",2018 +"2018-02-06","Waitangi Day","NZ",2018 +"2018-03-30","Good Friday","NZ",2018 +"2018-04-02","Easter Monday","NZ",2018 +"2018-04-25","Anzac Day","NZ",2018 +"2018-06-04","Queen's Birthday","NZ",2018 +"2018-10-22","Labour Day","NZ",2018 +"2018-12-25","Christmas Day","NZ",2018 +"2018-12-26","Boxing Day","NZ",2018 +"2019-01-01","New Year's Day","NZ",2019 +"2019-01-02","Day after New Year's Day","NZ",2019 +"2019-02-06","Waitangi Day","NZ",2019 +"2019-04-19","Good Friday","NZ",2019 +"2019-04-22","Easter Monday","NZ",2019 +"2019-04-25","Anzac Day","NZ",2019 +"2019-06-03","Queen's Birthday","NZ",2019 +"2019-10-28","Labour Day","NZ",2019 +"2019-12-25","Christmas Day","NZ",2019 +"2019-12-26","Boxing Day","NZ",2019 +"2020-01-01","New Year's Day","NZ",2020 +"2020-01-02","Day after New Year's Day","NZ",2020 +"2020-02-06","Waitangi Day","NZ",2020 +"2020-04-10","Good Friday","NZ",2020 +"2020-04-13","Easter Monday","NZ",2020 +"2020-04-25","Anzac Day","NZ",2020 +"2020-04-27","Anzac Day (Observed)","NZ",2020 +"2020-06-01","Queen's Birthday","NZ",2020 +"2020-10-26","Labour Day","NZ",2020 +"2020-12-25","Christmas Day","NZ",2020 +"2020-12-26","Boxing Day","NZ",2020 +"2020-12-28","Boxing Day (Observed)","NZ",2020 +"2021-01-01","New Year's Day","NZ",2021 +"2021-01-02","Day after New Year's Day","NZ",2021 +"2021-01-04","Day after New Year's Day (Observed)","NZ",2021 +"2021-02-06","Waitangi Day","NZ",2021 +"2021-02-08","Waitangi Day (Observed)","NZ",2021 +"2021-04-02","Good Friday","NZ",2021 +"2021-04-05","Easter Monday","NZ",2021 +"2021-04-25","Anzac Day","NZ",2021 +"2021-04-26","Anzac Day (Observed)","NZ",2021 +"2021-06-07","Queen's Birthday","NZ",2021 +"2021-10-25","Labour Day","NZ",2021 +"2021-12-25","Christmas Day","NZ",2021 +"2021-12-26","Boxing Day","NZ",2021 +"2021-12-27","Christmas Day (Observed)","NZ",2021 +"2021-12-28","Boxing Day (Observed)","NZ",2021 +"2022-01-01","New Year's Day","NZ",2022 +"2022-01-02","Day after New Year's Day","NZ",2022 +"2022-01-03","New Year's Day (Observed)","NZ",2022 +"2022-01-04","Day after New Year's Day (Observed)","NZ",2022 +"2022-02-06","Waitangi Day","NZ",2022 +"2022-02-07","Waitangi Day (Observed)","NZ",2022 +"2022-04-15","Good Friday","NZ",2022 +"2022-04-18","Easter Monday","NZ",2022 +"2022-04-25","Anzac Day","NZ",2022 +"2022-06-06","Queen's Birthday","NZ",2022 +"2022-06-24","Matariki","NZ",2022 +"2022-09-26","Queen Elizabeth II Memorial Day","NZ",2022 +"2022-10-24","Labour Day","NZ",2022 +"2022-12-25","Christmas Day","NZ",2022 +"2022-12-26","Boxing Day","NZ",2022 +"2022-12-27","Christmas Day (Observed)","NZ",2022 +"2023-01-01","New Year's Day","NZ",2023 +"2023-01-02","Day after New Year's Day","NZ",2023 +"2023-01-03","New Year's Day (Observed)","NZ",2023 +"2023-02-06","Waitangi Day","NZ",2023 +"2023-04-07","Good Friday","NZ",2023 +"2023-04-10","Easter Monday","NZ",2023 +"2023-04-25","Anzac Day","NZ",2023 +"2023-06-05","King's Birthday","NZ",2023 +"2023-07-14","Matariki","NZ",2023 +"2023-10-23","Labour Day","NZ",2023 +"2023-12-25","Christmas Day","NZ",2023 +"2023-12-26","Boxing Day","NZ",2023 +"2024-01-01","New Year's Day","NZ",2024 +"2024-01-02","Day after New Year's Day","NZ",2024 +"2024-02-06","Waitangi Day","NZ",2024 +"2024-03-29","Good Friday","NZ",2024 +"2024-04-01","Easter Monday","NZ",2024 +"2024-04-25","Anzac Day","NZ",2024 +"2024-06-03","King's Birthday","NZ",2024 +"2024-06-28","Matariki","NZ",2024 +"2024-10-28","Labour Day","NZ",2024 +"2024-12-25","Christmas Day","NZ",2024 +"2024-12-26","Boxing Day","NZ",2024 +"2025-01-01","New Year's Day","NZ",2025 +"2025-01-02","Day after New Year's Day","NZ",2025 +"2025-02-06","Waitangi Day","NZ",2025 +"2025-04-18","Good Friday","NZ",2025 +"2025-04-21","Easter Monday","NZ",2025 +"2025-04-25","Anzac Day","NZ",2025 +"2025-06-02","King's Birthday","NZ",2025 +"2025-06-20","Matariki","NZ",2025 +"2025-10-27","Labour Day","NZ",2025 +"2025-12-25","Christmas Day","NZ",2025 +"2025-12-26","Boxing Day","NZ",2025 +"2026-01-01","New Year's Day","NZ",2026 +"2026-01-02","Day after New Year's Day","NZ",2026 +"2026-02-06","Waitangi Day","NZ",2026 +"2026-04-03","Good Friday","NZ",2026 +"2026-04-06","Easter Monday","NZ",2026 +"2026-04-25","Anzac Day","NZ",2026 +"2026-04-27","Anzac Day (Observed)","NZ",2026 +"2026-06-01","King's Birthday","NZ",2026 +"2026-07-10","Matariki","NZ",2026 +"2026-10-26","Labour Day","NZ",2026 +"2026-12-25","Christmas Day","NZ",2026 +"2026-12-26","Boxing Day","NZ",2026 +"2026-12-28","Boxing Day (Observed)","NZ",2026 +"2027-01-01","New Year's Day","NZ",2027 +"2027-01-02","Day after New Year's Day","NZ",2027 +"2027-01-04","Day after New Year's Day (Observed)","NZ",2027 +"2027-02-06","Waitangi Day","NZ",2027 +"2027-02-08","Waitangi Day (Observed)","NZ",2027 +"2027-03-26","Good Friday","NZ",2027 +"2027-03-29","Easter Monday","NZ",2027 +"2027-04-25","Anzac Day","NZ",2027 +"2027-04-26","Anzac Day (Observed)","NZ",2027 +"2027-06-07","King's Birthday","NZ",2027 +"2027-06-25","Matariki","NZ",2027 +"2027-10-25","Labour Day","NZ",2027 +"2027-12-25","Christmas Day","NZ",2027 +"2027-12-26","Boxing Day","NZ",2027 +"2027-12-27","Christmas Day (Observed)","NZ",2027 +"2027-12-28","Boxing Day (Observed)","NZ",2027 +"2028-01-01","New Year's Day","NZ",2028 +"2028-01-02","Day after New Year's Day","NZ",2028 +"2028-01-03","New Year's Day (Observed)","NZ",2028 +"2028-01-04","Day after New Year's Day (Observed)","NZ",2028 +"2028-02-06","Waitangi Day","NZ",2028 +"2028-02-07","Waitangi Day (Observed)","NZ",2028 +"2028-04-14","Good Friday","NZ",2028 +"2028-04-17","Easter Monday","NZ",2028 +"2028-04-25","Anzac Day","NZ",2028 +"2028-06-05","King's Birthday","NZ",2028 +"2028-07-14","Matariki","NZ",2028 +"2028-10-23","Labour Day","NZ",2028 +"2028-12-25","Christmas Day","NZ",2028 +"2028-12-26","Boxing Day","NZ",2028 +"2029-01-01","New Year's Day","NZ",2029 +"2029-01-02","Day after New Year's Day","NZ",2029 +"2029-02-06","Waitangi Day","NZ",2029 +"2029-03-30","Good Friday","NZ",2029 +"2029-04-02","Easter Monday","NZ",2029 +"2029-04-25","Anzac Day","NZ",2029 +"2029-06-04","King's Birthday","NZ",2029 +"2029-07-06","Matariki","NZ",2029 +"2029-10-22","Labour Day","NZ",2029 +"2029-12-25","Christmas Day","NZ",2029 +"2029-12-26","Boxing Day","NZ",2029 +"2030-01-01","New Year's Day","NZ",2030 +"2030-01-02","Day after New Year's Day","NZ",2030 +"2030-02-06","Waitangi Day","NZ",2030 +"2030-04-19","Good Friday","NZ",2030 +"2030-04-22","Easter Monday","NZ",2030 +"2030-04-25","Anzac Day","NZ",2030 +"2030-06-03","King's Birthday","NZ",2030 +"2030-06-21","Matariki","NZ",2030 +"2030-10-28","Labour Day","NZ",2030 +"2030-12-25","Christmas Day","NZ",2030 +"2030-12-26","Boxing Day","NZ",2030 +"2031-01-01","New Year's Day","NZ",2031 +"2031-01-02","Day after New Year's Day","NZ",2031 +"2031-02-06","Waitangi Day","NZ",2031 +"2031-04-11","Good Friday","NZ",2031 +"2031-04-14","Easter Monday","NZ",2031 +"2031-04-25","Anzac Day","NZ",2031 +"2031-06-02","King's Birthday","NZ",2031 +"2031-07-11","Matariki","NZ",2031 +"2031-10-27","Labour Day","NZ",2031 +"2031-12-25","Christmas Day","NZ",2031 +"2031-12-26","Boxing Day","NZ",2031 +"2032-01-01","New Year's Day","NZ",2032 +"2032-01-02","Day after New Year's Day","NZ",2032 +"2032-02-06","Waitangi Day","NZ",2032 +"2032-03-26","Good Friday","NZ",2032 +"2032-03-29","Easter Monday","NZ",2032 +"2032-04-25","Anzac Day","NZ",2032 +"2032-04-26","Anzac Day (Observed)","NZ",2032 +"2032-06-07","King's Birthday","NZ",2032 +"2032-07-02","Matariki","NZ",2032 +"2032-10-25","Labour Day","NZ",2032 +"2032-12-25","Christmas Day","NZ",2032 +"2032-12-26","Boxing Day","NZ",2032 +"2032-12-27","Christmas Day (Observed)","NZ",2032 +"2032-12-28","Boxing Day (Observed)","NZ",2032 +"2033-01-01","New Year's Day","NZ",2033 +"2033-01-02","Day after New Year's Day","NZ",2033 +"2033-01-03","New Year's Day (Observed)","NZ",2033 +"2033-01-04","Day after New Year's Day (Observed)","NZ",2033 +"2033-02-06","Waitangi Day","NZ",2033 +"2033-02-07","Waitangi Day (Observed)","NZ",2033 +"2033-04-15","Good Friday","NZ",2033 +"2033-04-18","Easter Monday","NZ",2033 +"2033-04-25","Anzac Day","NZ",2033 +"2033-06-06","King's Birthday","NZ",2033 +"2033-06-24","Matariki","NZ",2033 +"2033-10-24","Labour Day","NZ",2033 +"2033-12-25","Christmas Day","NZ",2033 +"2033-12-26","Boxing Day","NZ",2033 +"2033-12-27","Christmas Day (Observed)","NZ",2033 +"2034-01-01","New Year's Day","NZ",2034 +"2034-01-02","Day after New Year's Day","NZ",2034 +"2034-01-03","New Year's Day (Observed)","NZ",2034 +"2034-02-06","Waitangi Day","NZ",2034 +"2034-04-07","Good Friday","NZ",2034 +"2034-04-10","Easter Monday","NZ",2034 +"2034-04-25","Anzac Day","NZ",2034 +"2034-06-05","King's Birthday","NZ",2034 +"2034-07-07","Matariki","NZ",2034 +"2034-10-23","Labour Day","NZ",2034 +"2034-12-25","Christmas Day","NZ",2034 +"2034-12-26","Boxing Day","NZ",2034 +"2035-01-01","New Year's Day","NZ",2035 +"2035-01-02","Day after New Year's Day","NZ",2035 +"2035-02-06","Waitangi Day","NZ",2035 +"2035-03-23","Good Friday","NZ",2035 +"2035-03-26","Easter Monday","NZ",2035 +"2035-04-25","Anzac Day","NZ",2035 +"2035-06-04","King's Birthday","NZ",2035 +"2035-06-29","Matariki","NZ",2035 +"2035-10-22","Labour Day","NZ",2035 +"2035-12-25","Christmas Day","NZ",2035 +"2035-12-26","Boxing Day","NZ",2035 +"2036-01-01","New Year's Day","NZ",2036 +"2036-01-02","Day after New Year's Day","NZ",2036 +"2036-02-06","Waitangi Day","NZ",2036 +"2036-04-11","Good Friday","NZ",2036 +"2036-04-14","Easter Monday","NZ",2036 +"2036-04-25","Anzac Day","NZ",2036 +"2036-06-02","King's Birthday","NZ",2036 +"2036-07-18","Matariki","NZ",2036 +"2036-10-27","Labour Day","NZ",2036 +"2036-12-25","Christmas Day","NZ",2036 +"2036-12-26","Boxing Day","NZ",2036 +"2037-01-01","New Year's Day","NZ",2037 +"2037-01-02","Day after New Year's Day","NZ",2037 +"2037-02-06","Waitangi Day","NZ",2037 +"2037-04-03","Good Friday","NZ",2037 +"2037-04-06","Easter Monday","NZ",2037 +"2037-04-25","Anzac Day","NZ",2037 +"2037-04-27","Anzac Day (Observed)","NZ",2037 +"2037-06-01","King's Birthday","NZ",2037 +"2037-07-10","Matariki","NZ",2037 +"2037-10-26","Labour Day","NZ",2037 +"2037-12-25","Christmas Day","NZ",2037 +"2037-12-26","Boxing Day","NZ",2037 +"2037-12-28","Boxing Day (Observed)","NZ",2037 +"2038-01-01","New Year's Day","NZ",2038 +"2038-01-02","Day after New Year's Day","NZ",2038 +"2038-01-04","Day after New Year's Day (Observed)","NZ",2038 +"2038-02-06","Waitangi Day","NZ",2038 +"2038-02-08","Waitangi Day (Observed)","NZ",2038 +"2038-04-23","Good Friday","NZ",2038 +"2038-04-25","Anzac Day","NZ",2038 +"2038-04-26","Anzac Day (Observed)","NZ",2038 +"2038-04-26","Easter Monday","NZ",2038 +"2038-06-07","King's Birthday","NZ",2038 +"2038-06-25","Matariki","NZ",2038 +"2038-10-25","Labour Day","NZ",2038 +"2038-12-25","Christmas Day","NZ",2038 +"2038-12-26","Boxing Day","NZ",2038 +"2038-12-27","Christmas Day (Observed)","NZ",2038 +"2038-12-28","Boxing Day (Observed)","NZ",2038 +"2039-01-01","New Year's Day","NZ",2039 +"2039-01-02","Day after New Year's Day","NZ",2039 +"2039-01-03","New Year's Day (Observed)","NZ",2039 +"2039-01-04","Day after New Year's Day (Observed)","NZ",2039 +"2039-02-06","Waitangi Day","NZ",2039 +"2039-02-07","Waitangi Day (Observed)","NZ",2039 +"2039-04-08","Good Friday","NZ",2039 +"2039-04-11","Easter Monday","NZ",2039 +"2039-04-25","Anzac Day","NZ",2039 +"2039-06-06","King's Birthday","NZ",2039 +"2039-07-15","Matariki","NZ",2039 +"2039-10-24","Labour Day","NZ",2039 +"2039-12-25","Christmas Day","NZ",2039 +"2039-12-26","Boxing Day","NZ",2039 +"2039-12-27","Christmas Day (Observed)","NZ",2039 +"2040-01-01","New Year's Day","NZ",2040 +"2040-01-02","Day after New Year's Day","NZ",2040 +"2040-01-03","New Year's Day (Observed)","NZ",2040 +"2040-02-06","Waitangi Day","NZ",2040 +"2040-03-30","Good Friday","NZ",2040 +"2040-04-02","Easter Monday","NZ",2040 +"2040-04-25","Anzac Day","NZ",2040 +"2040-06-04","King's Birthday","NZ",2040 +"2040-07-06","Matariki","NZ",2040 +"2040-10-22","Labour Day","NZ",2040 +"2040-12-25","Christmas Day","NZ",2040 +"2040-12-26","Boxing Day","NZ",2040 +"2041-01-01","New Year's Day","NZ",2041 +"2041-01-02","Day after New Year's Day","NZ",2041 +"2041-02-06","Waitangi Day","NZ",2041 +"2041-04-19","Good Friday","NZ",2041 +"2041-04-22","Easter Monday","NZ",2041 +"2041-04-25","Anzac Day","NZ",2041 +"2041-06-03","King's Birthday","NZ",2041 +"2041-07-19","Matariki","NZ",2041 +"2041-10-28","Labour Day","NZ",2041 +"2041-12-25","Christmas Day","NZ",2041 +"2041-12-26","Boxing Day","NZ",2041 +"2042-01-01","New Year's Day","NZ",2042 +"2042-01-02","Day after New Year's Day","NZ",2042 +"2042-02-06","Waitangi Day","NZ",2042 +"2042-04-04","Good Friday","NZ",2042 +"2042-04-07","Easter Monday","NZ",2042 +"2042-04-25","Anzac Day","NZ",2042 +"2042-06-02","King's Birthday","NZ",2042 +"2042-07-11","Matariki","NZ",2042 +"2042-10-27","Labour Day","NZ",2042 +"2042-12-25","Christmas Day","NZ",2042 +"2042-12-26","Boxing Day","NZ",2042 +"2043-01-01","New Year's Day","NZ",2043 +"2043-01-02","Day after New Year's Day","NZ",2043 +"2043-02-06","Waitangi Day","NZ",2043 +"2043-03-27","Good Friday","NZ",2043 +"2043-03-30","Easter Monday","NZ",2043 +"2043-04-25","Anzac Day","NZ",2043 +"2043-04-27","Anzac Day (Observed)","NZ",2043 +"2043-06-01","King's Birthday","NZ",2043 +"2043-07-03","Matariki","NZ",2043 +"2043-10-26","Labour Day","NZ",2043 +"2043-12-25","Christmas Day","NZ",2043 +"2043-12-26","Boxing Day","NZ",2043 +"2043-12-28","Boxing Day (Observed)","NZ",2043 +"2044-01-01","New Year's Day","NZ",2044 +"2044-01-02","Day after New Year's Day","NZ",2044 +"2044-01-04","Day after New Year's Day (Observed)","NZ",2044 +"2044-02-06","Waitangi Day","NZ",2044 +"2044-02-08","Waitangi Day (Observed)","NZ",2044 +"2044-04-15","Good Friday","NZ",2044 +"2044-04-18","Easter Monday","NZ",2044 +"2044-04-25","Anzac Day","NZ",2044 +"2044-06-06","King's Birthday","NZ",2044 +"2044-06-24","Matariki","NZ",2044 +"2044-10-24","Labour Day","NZ",2044 +"2044-12-25","Christmas Day","NZ",2044 +"2044-12-26","Boxing Day","NZ",2044 +"2044-12-27","Christmas Day (Observed)","NZ",2044 +"1995-01-01","New Year's Day","PA",1995 +"1995-01-02","New Year's Day (Observed)","PA",1995 +"1995-01-09","Martyrs' Day","PA",1995 +"1995-02-28","Carnival","PA",1995 +"1995-04-14","Good Friday","PA",1995 +"1995-05-01","Labour Day","PA",1995 +"1995-11-03","Separation Day","PA",1995 +"1995-11-04","National Symbols Day","PA",1995 +"1995-11-05","Colon Day","PA",1995 +"1995-11-10","Los Santos Uprising Day","PA",1995 +"1995-11-28","Independence Day","PA",1995 +"1995-12-08","Mother's Day","PA",1995 +"1995-12-25","Christmas Day","PA",1995 +"1996-01-01","New Year's Day","PA",1996 +"1996-01-09","Martyrs' Day","PA",1996 +"1996-02-20","Carnival","PA",1996 +"1996-04-05","Good Friday","PA",1996 +"1996-05-01","Labour Day","PA",1996 +"1996-11-03","Separation Day","PA",1996 +"1996-11-04","National Symbols Day","PA",1996 +"1996-11-05","Colon Day","PA",1996 +"1996-11-10","Los Santos Uprising Day","PA",1996 +"1996-11-28","Independence Day","PA",1996 +"1996-12-08","Mother's Day","PA",1996 +"1996-12-09","Mother's Day (Observed)","PA",1996 +"1996-12-25","Christmas Day","PA",1996 +"1997-01-01","New Year's Day","PA",1997 +"1997-01-09","Martyrs' Day","PA",1997 +"1997-02-11","Carnival","PA",1997 +"1997-03-28","Good Friday","PA",1997 +"1997-05-01","Labour Day","PA",1997 +"1997-11-03","Separation Day","PA",1997 +"1997-11-04","National Symbols Day","PA",1997 +"1997-11-05","Colon Day","PA",1997 +"1997-11-10","Los Santos Uprising Day","PA",1997 +"1997-11-28","Independence Day","PA",1997 +"1997-12-08","Mother's Day","PA",1997 +"1997-12-25","Christmas Day","PA",1997 +"1998-01-01","New Year's Day","PA",1998 +"1998-01-09","Martyrs' Day","PA",1998 +"1998-02-24","Carnival","PA",1998 +"1998-04-10","Good Friday","PA",1998 +"1998-05-01","Labour Day","PA",1998 +"1998-11-03","Separation Day","PA",1998 +"1998-11-04","National Symbols Day","PA",1998 +"1998-11-05","Colon Day","PA",1998 +"1998-11-10","Los Santos Uprising Day","PA",1998 +"1998-11-28","Independence Day","PA",1998 +"1998-12-08","Mother's Day","PA",1998 +"1998-12-25","Christmas Day","PA",1998 +"1999-01-01","New Year's Day","PA",1999 +"1999-01-09","Martyrs' Day","PA",1999 +"1999-02-16","Carnival","PA",1999 +"1999-04-02","Good Friday","PA",1999 +"1999-05-01","Labour Day","PA",1999 +"1999-11-03","Separation Day","PA",1999 +"1999-11-04","National Symbols Day","PA",1999 +"1999-11-05","Colon Day","PA",1999 +"1999-11-10","Los Santos Uprising Day","PA",1999 +"1999-11-28","Independence Day","PA",1999 +"1999-11-29","Independence Day (Observed)","PA",1999 +"1999-12-08","Mother's Day","PA",1999 +"1999-12-25","Christmas Day","PA",1999 +"2000-01-01","New Year's Day","PA",2000 +"2000-01-09","Martyrs' Day","PA",2000 +"2000-01-10","Martyrs' Day (Observed)","PA",2000 +"2000-03-07","Carnival","PA",2000 +"2000-04-21","Good Friday","PA",2000 +"2000-05-01","Labour Day","PA",2000 +"2000-11-03","Separation Day","PA",2000 +"2000-11-04","National Symbols Day","PA",2000 +"2000-11-05","Colon Day","PA",2000 +"2000-11-10","Los Santos Uprising Day","PA",2000 +"2000-11-28","Independence Day","PA",2000 +"2000-12-08","Mother's Day","PA",2000 +"2000-12-25","Christmas Day","PA",2000 +"2001-01-01","New Year's Day","PA",2001 +"2001-01-09","Martyrs' Day","PA",2001 +"2001-02-27","Carnival","PA",2001 +"2001-04-13","Good Friday","PA",2001 +"2001-05-01","Labour Day","PA",2001 +"2001-11-03","Separation Day","PA",2001 +"2001-11-04","National Symbols Day","PA",2001 +"2001-11-05","Colon Day","PA",2001 +"2001-11-10","Los Santos Uprising Day","PA",2001 +"2001-11-28","Independence Day","PA",2001 +"2001-12-08","Mother's Day","PA",2001 +"2001-12-25","Christmas Day","PA",2001 +"2002-01-01","New Year's Day","PA",2002 +"2002-01-09","Martyrs' Day","PA",2002 +"2002-02-12","Carnival","PA",2002 +"2002-03-29","Good Friday","PA",2002 +"2002-05-01","Labour Day","PA",2002 +"2002-11-03","Separation Day","PA",2002 +"2002-11-04","National Symbols Day","PA",2002 +"2002-11-05","Colon Day","PA",2002 +"2002-11-10","Los Santos Uprising Day","PA",2002 +"2002-11-28","Independence Day","PA",2002 +"2002-12-08","Mother's Day","PA",2002 +"2002-12-09","Mother's Day (Observed)","PA",2002 +"2002-12-25","Christmas Day","PA",2002 +"2003-01-01","New Year's Day","PA",2003 +"2003-01-09","Martyrs' Day","PA",2003 +"2003-03-04","Carnival","PA",2003 +"2003-04-18","Good Friday","PA",2003 +"2003-05-01","Labour Day","PA",2003 +"2003-11-03","Separation Day","PA",2003 +"2003-11-04","National Symbols Day","PA",2003 +"2003-11-05","Colon Day","PA",2003 +"2003-11-10","Los Santos Uprising Day","PA",2003 +"2003-11-28","Independence Day","PA",2003 +"2003-12-08","Mother's Day","PA",2003 +"2003-12-25","Christmas Day","PA",2003 +"2004-01-01","New Year's Day","PA",2004 +"2004-01-09","Martyrs' Day","PA",2004 +"2004-02-24","Carnival","PA",2004 +"2004-04-09","Good Friday","PA",2004 +"2004-05-01","Labour Day","PA",2004 +"2004-11-03","Separation Day","PA",2004 +"2004-11-04","National Symbols Day","PA",2004 +"2004-11-05","Colon Day","PA",2004 +"2004-11-10","Los Santos Uprising Day","PA",2004 +"2004-11-28","Independence Day","PA",2004 +"2004-11-29","Independence Day (Observed)","PA",2004 +"2004-12-08","Mother's Day","PA",2004 +"2004-12-25","Christmas Day","PA",2004 +"2005-01-01","New Year's Day","PA",2005 +"2005-01-09","Martyrs' Day","PA",2005 +"2005-01-10","Martyrs' Day (Observed)","PA",2005 +"2005-02-08","Carnival","PA",2005 +"2005-03-25","Good Friday","PA",2005 +"2005-05-01","Labour Day","PA",2005 +"2005-05-02","Labour Day (Observed)","PA",2005 +"2005-11-03","Separation Day","PA",2005 +"2005-11-04","National Symbols Day","PA",2005 +"2005-11-05","Colon Day","PA",2005 +"2005-11-10","Los Santos Uprising Day","PA",2005 +"2005-11-28","Independence Day","PA",2005 +"2005-12-08","Mother's Day","PA",2005 +"2005-12-25","Christmas Day","PA",2005 +"2005-12-26","Christmas Day (Observed)","PA",2005 +"2006-01-01","New Year's Day","PA",2006 +"2006-01-02","New Year's Day (Observed)","PA",2006 +"2006-01-09","Martyrs' Day","PA",2006 +"2006-02-28","Carnival","PA",2006 +"2006-04-14","Good Friday","PA",2006 +"2006-05-01","Labour Day","PA",2006 +"2006-11-03","Separation Day","PA",2006 +"2006-11-04","National Symbols Day","PA",2006 +"2006-11-05","Colon Day","PA",2006 +"2006-11-10","Los Santos Uprising Day","PA",2006 +"2006-11-28","Independence Day","PA",2006 +"2006-12-08","Mother's Day","PA",2006 +"2006-12-25","Christmas Day","PA",2006 +"2007-01-01","New Year's Day","PA",2007 +"2007-01-09","Martyrs' Day","PA",2007 +"2007-02-20","Carnival","PA",2007 +"2007-04-06","Good Friday","PA",2007 +"2007-05-01","Labour Day","PA",2007 +"2007-11-03","Separation Day","PA",2007 +"2007-11-04","National Symbols Day","PA",2007 +"2007-11-05","Colon Day","PA",2007 +"2007-11-10","Los Santos Uprising Day","PA",2007 +"2007-11-28","Independence Day","PA",2007 +"2007-12-08","Mother's Day","PA",2007 +"2007-12-25","Christmas Day","PA",2007 +"2008-01-01","New Year's Day","PA",2008 +"2008-01-09","Martyrs' Day","PA",2008 +"2008-02-05","Carnival","PA",2008 +"2008-03-21","Good Friday","PA",2008 +"2008-05-01","Labour Day","PA",2008 +"2008-11-03","Separation Day","PA",2008 +"2008-11-04","National Symbols Day","PA",2008 +"2008-11-05","Colon Day","PA",2008 +"2008-11-10","Los Santos Uprising Day","PA",2008 +"2008-11-28","Independence Day","PA",2008 +"2008-12-08","Mother's Day","PA",2008 +"2008-12-25","Christmas Day","PA",2008 +"2009-01-01","New Year's Day","PA",2009 +"2009-01-09","Martyrs' Day","PA",2009 +"2009-02-24","Carnival","PA",2009 +"2009-04-10","Good Friday","PA",2009 +"2009-05-01","Labour Day","PA",2009 +"2009-11-03","Separation Day","PA",2009 +"2009-11-04","National Symbols Day","PA",2009 +"2009-11-05","Colon Day","PA",2009 +"2009-11-10","Los Santos Uprising Day","PA",2009 +"2009-11-28","Independence Day","PA",2009 +"2009-12-08","Mother's Day","PA",2009 +"2009-12-25","Christmas Day","PA",2009 +"2010-01-01","New Year's Day","PA",2010 +"2010-01-09","Martyrs' Day","PA",2010 +"2010-02-16","Carnival","PA",2010 +"2010-04-02","Good Friday","PA",2010 +"2010-05-01","Labour Day","PA",2010 +"2010-11-03","Separation Day","PA",2010 +"2010-11-04","National Symbols Day","PA",2010 +"2010-11-05","Colon Day","PA",2010 +"2010-11-10","Los Santos Uprising Day","PA",2010 +"2010-11-28","Independence Day","PA",2010 +"2010-11-29","Independence Day (Observed)","PA",2010 +"2010-12-08","Mother's Day","PA",2010 +"2010-12-25","Christmas Day","PA",2010 +"2011-01-01","New Year's Day","PA",2011 +"2011-01-09","Martyrs' Day","PA",2011 +"2011-01-10","Martyrs' Day (Observed)","PA",2011 +"2011-03-08","Carnival","PA",2011 +"2011-04-22","Good Friday","PA",2011 +"2011-05-01","Labour Day","PA",2011 +"2011-05-02","Labour Day (Observed)","PA",2011 +"2011-11-03","Separation Day","PA",2011 +"2011-11-04","National Symbols Day","PA",2011 +"2011-11-05","Colon Day","PA",2011 +"2011-11-10","Los Santos Uprising Day","PA",2011 +"2011-11-28","Independence Day","PA",2011 +"2011-12-08","Mother's Day","PA",2011 +"2011-12-25","Christmas Day","PA",2011 +"2011-12-26","Christmas Day (Observed)","PA",2011 +"2012-01-01","New Year's Day","PA",2012 +"2012-01-02","New Year's Day (Observed)","PA",2012 +"2012-01-09","Martyrs' Day","PA",2012 +"2012-02-21","Carnival","PA",2012 +"2012-04-06","Good Friday","PA",2012 +"2012-05-01","Labour Day","PA",2012 +"2012-11-03","Separation Day","PA",2012 +"2012-11-04","National Symbols Day","PA",2012 +"2012-11-05","Colon Day","PA",2012 +"2012-11-10","Los Santos Uprising Day","PA",2012 +"2012-11-28","Independence Day","PA",2012 +"2012-12-08","Mother's Day","PA",2012 +"2012-12-25","Christmas Day","PA",2012 +"2013-01-01","New Year's Day","PA",2013 +"2013-01-09","Martyrs' Day","PA",2013 +"2013-02-12","Carnival","PA",2013 +"2013-03-29","Good Friday","PA",2013 +"2013-05-01","Labour Day","PA",2013 +"2013-11-03","Separation Day","PA",2013 +"2013-11-04","National Symbols Day","PA",2013 +"2013-11-05","Colon Day","PA",2013 +"2013-11-10","Los Santos Uprising Day","PA",2013 +"2013-11-28","Independence Day","PA",2013 +"2013-12-08","Mother's Day","PA",2013 +"2013-12-09","Mother's Day (Observed)","PA",2013 +"2013-12-25","Christmas Day","PA",2013 +"2014-01-01","New Year's Day","PA",2014 +"2014-01-09","Martyrs' Day","PA",2014 +"2014-03-04","Carnival","PA",2014 +"2014-04-18","Good Friday","PA",2014 +"2014-05-01","Labour Day","PA",2014 +"2014-11-03","Separation Day","PA",2014 +"2014-11-04","National Symbols Day","PA",2014 +"2014-11-05","Colon Day","PA",2014 +"2014-11-10","Los Santos Uprising Day","PA",2014 +"2014-11-28","Independence Day","PA",2014 +"2014-12-08","Mother's Day","PA",2014 +"2014-12-25","Christmas Day","PA",2014 +"2015-01-01","New Year's Day","PA",2015 +"2015-01-09","Martyrs' Day","PA",2015 +"2015-02-17","Carnival","PA",2015 +"2015-04-03","Good Friday","PA",2015 +"2015-05-01","Labour Day","PA",2015 +"2015-11-03","Separation Day","PA",2015 +"2015-11-04","National Symbols Day","PA",2015 +"2015-11-05","Colon Day","PA",2015 +"2015-11-10","Los Santos Uprising Day","PA",2015 +"2015-11-28","Independence Day","PA",2015 +"2015-12-08","Mother's Day","PA",2015 +"2015-12-25","Christmas Day","PA",2015 +"2016-01-01","New Year's Day","PA",2016 +"2016-01-09","Martyrs' Day","PA",2016 +"2016-02-09","Carnival","PA",2016 +"2016-03-25","Good Friday","PA",2016 +"2016-05-01","Labour Day","PA",2016 +"2016-05-02","Labour Day (Observed)","PA",2016 +"2016-11-03","Separation Day","PA",2016 +"2016-11-04","National Symbols Day","PA",2016 +"2016-11-05","Colon Day","PA",2016 +"2016-11-10","Los Santos Uprising Day","PA",2016 +"2016-11-28","Independence Day","PA",2016 +"2016-12-08","Mother's Day","PA",2016 +"2016-12-25","Christmas Day","PA",2016 +"2016-12-26","Christmas Day (Observed)","PA",2016 +"2017-01-01","New Year's Day","PA",2017 +"2017-01-02","New Year's Day (Observed)","PA",2017 +"2017-01-09","Martyrs' Day","PA",2017 +"2017-02-28","Carnival","PA",2017 +"2017-04-14","Good Friday","PA",2017 +"2017-05-01","Labour Day","PA",2017 +"2017-11-03","Separation Day","PA",2017 +"2017-11-04","National Symbols Day","PA",2017 +"2017-11-05","Colon Day","PA",2017 +"2017-11-10","Los Santos Uprising Day","PA",2017 +"2017-11-28","Independence Day","PA",2017 +"2017-12-08","Mother's Day","PA",2017 +"2017-12-25","Christmas Day","PA",2017 +"2018-01-01","New Year's Day","PA",2018 +"2018-01-09","Martyrs' Day","PA",2018 +"2018-02-13","Carnival","PA",2018 +"2018-03-30","Good Friday","PA",2018 +"2018-05-01","Labour Day","PA",2018 +"2018-11-03","Separation Day","PA",2018 +"2018-11-04","National Symbols Day","PA",2018 +"2018-11-05","Colon Day","PA",2018 +"2018-11-10","Los Santos Uprising Day","PA",2018 +"2018-11-28","Independence Day","PA",2018 +"2018-12-08","Mother's Day","PA",2018 +"2018-12-25","Christmas Day","PA",2018 +"2019-01-01","New Year's Day","PA",2019 +"2019-01-09","Martyrs' Day","PA",2019 +"2019-03-05","Carnival","PA",2019 +"2019-04-19","Good Friday","PA",2019 +"2019-05-01","Labour Day","PA",2019 +"2019-11-03","Separation Day","PA",2019 +"2019-11-04","National Symbols Day","PA",2019 +"2019-11-05","Colon Day","PA",2019 +"2019-11-10","Los Santos Uprising Day","PA",2019 +"2019-11-28","Independence Day","PA",2019 +"2019-12-08","Mother's Day","PA",2019 +"2019-12-09","Mother's Day (Observed)","PA",2019 +"2019-12-25","Christmas Day","PA",2019 +"2020-01-01","New Year's Day","PA",2020 +"2020-01-09","Martyrs' Day","PA",2020 +"2020-02-25","Carnival","PA",2020 +"2020-04-10","Good Friday","PA",2020 +"2020-05-01","Labour Day","PA",2020 +"2020-11-03","Separation Day","PA",2020 +"2020-11-04","National Symbols Day","PA",2020 +"2020-11-05","Colon Day","PA",2020 +"2020-11-10","Los Santos Uprising Day","PA",2020 +"2020-11-28","Independence Day","PA",2020 +"2020-12-08","Mother's Day","PA",2020 +"2020-12-25","Christmas Day","PA",2020 +"2021-01-01","New Year's Day","PA",2021 +"2021-01-09","Martyrs' Day","PA",2021 +"2021-02-16","Carnival","PA",2021 +"2021-04-02","Good Friday","PA",2021 +"2021-05-01","Labour Day","PA",2021 +"2021-11-03","Separation Day","PA",2021 +"2021-11-04","National Symbols Day","PA",2021 +"2021-11-05","Colon Day","PA",2021 +"2021-11-10","Los Santos Uprising Day","PA",2021 +"2021-11-28","Independence Day","PA",2021 +"2021-11-29","Independence Day (Observed)","PA",2021 +"2021-12-08","Mother's Day","PA",2021 +"2021-12-25","Christmas Day","PA",2021 +"2022-01-01","New Year's Day","PA",2022 +"2022-01-09","Martyrs' Day","PA",2022 +"2022-01-10","Martyrs' Day (Observed)","PA",2022 +"2022-03-01","Carnival","PA",2022 +"2022-04-15","Good Friday","PA",2022 +"2022-05-01","Labour Day","PA",2022 +"2022-05-02","Labour Day (Observed)","PA",2022 +"2022-11-03","Separation Day","PA",2022 +"2022-11-04","National Symbols Day","PA",2022 +"2022-11-05","Colon Day","PA",2022 +"2022-11-10","Los Santos Uprising Day","PA",2022 +"2022-11-28","Independence Day","PA",2022 +"2022-12-08","Mother's Day","PA",2022 +"2022-12-20","National Mourning Day","PA",2022 +"2022-12-25","Christmas Day","PA",2022 +"2022-12-26","Christmas Day (Observed)","PA",2022 +"2023-01-01","New Year's Day","PA",2023 +"2023-01-02","New Year's Day (Observed)","PA",2023 +"2023-01-09","Martyrs' Day","PA",2023 +"2023-02-21","Carnival","PA",2023 +"2023-04-07","Good Friday","PA",2023 +"2023-05-01","Labour Day","PA",2023 +"2023-11-03","Separation Day","PA",2023 +"2023-11-04","National Symbols Day","PA",2023 +"2023-11-05","Colon Day","PA",2023 +"2023-11-10","Los Santos Uprising Day","PA",2023 +"2023-11-28","Independence Day","PA",2023 +"2023-12-08","Mother's Day","PA",2023 +"2023-12-20","National Mourning Day","PA",2023 +"2023-12-25","Christmas Day","PA",2023 +"2024-01-01","New Year's Day","PA",2024 +"2024-01-09","Martyrs' Day","PA",2024 +"2024-02-13","Carnival","PA",2024 +"2024-03-29","Good Friday","PA",2024 +"2024-05-01","Labour Day","PA",2024 +"2024-11-03","Separation Day","PA",2024 +"2024-11-04","National Symbols Day","PA",2024 +"2024-11-05","Colon Day","PA",2024 +"2024-11-10","Los Santos Uprising Day","PA",2024 +"2024-11-28","Independence Day","PA",2024 +"2024-12-08","Mother's Day","PA",2024 +"2024-12-09","Mother's Day (Observed)","PA",2024 +"2024-12-20","National Mourning Day","PA",2024 +"2024-12-25","Christmas Day","PA",2024 +"2025-01-01","New Year's Day","PA",2025 +"2025-01-09","Martyrs' Day","PA",2025 +"2025-03-04","Carnival","PA",2025 +"2025-04-18","Good Friday","PA",2025 +"2025-05-01","Labour Day","PA",2025 +"2025-11-03","Separation Day","PA",2025 +"2025-11-04","National Symbols Day","PA",2025 +"2025-11-05","Colon Day","PA",2025 +"2025-11-10","Los Santos Uprising Day","PA",2025 +"2025-11-28","Independence Day","PA",2025 +"2025-12-08","Mother's Day","PA",2025 +"2025-12-20","National Mourning Day","PA",2025 +"2025-12-25","Christmas Day","PA",2025 +"2026-01-01","New Year's Day","PA",2026 +"2026-01-09","Martyrs' Day","PA",2026 +"2026-02-17","Carnival","PA",2026 +"2026-04-03","Good Friday","PA",2026 +"2026-05-01","Labour Day","PA",2026 +"2026-11-03","Separation Day","PA",2026 +"2026-11-04","National Symbols Day","PA",2026 +"2026-11-05","Colon Day","PA",2026 +"2026-11-10","Los Santos Uprising Day","PA",2026 +"2026-11-28","Independence Day","PA",2026 +"2026-12-08","Mother's Day","PA",2026 +"2026-12-20","National Mourning Day","PA",2026 +"2026-12-21","National Mourning Day (Observed)","PA",2026 +"2026-12-25","Christmas Day","PA",2026 +"2027-01-01","New Year's Day","PA",2027 +"2027-01-09","Martyrs' Day","PA",2027 +"2027-02-09","Carnival","PA",2027 +"2027-03-26","Good Friday","PA",2027 +"2027-05-01","Labour Day","PA",2027 +"2027-11-03","Separation Day","PA",2027 +"2027-11-04","National Symbols Day","PA",2027 +"2027-11-05","Colon Day","PA",2027 +"2027-11-10","Los Santos Uprising Day","PA",2027 +"2027-11-28","Independence Day","PA",2027 +"2027-11-29","Independence Day (Observed)","PA",2027 +"2027-12-08","Mother's Day","PA",2027 +"2027-12-20","National Mourning Day","PA",2027 +"2027-12-25","Christmas Day","PA",2027 +"2028-01-01","New Year's Day","PA",2028 +"2028-01-09","Martyrs' Day","PA",2028 +"2028-01-10","Martyrs' Day (Observed)","PA",2028 +"2028-02-29","Carnival","PA",2028 +"2028-04-14","Good Friday","PA",2028 +"2028-05-01","Labour Day","PA",2028 +"2028-11-03","Separation Day","PA",2028 +"2028-11-04","National Symbols Day","PA",2028 +"2028-11-05","Colon Day","PA",2028 +"2028-11-10","Los Santos Uprising Day","PA",2028 +"2028-11-28","Independence Day","PA",2028 +"2028-12-08","Mother's Day","PA",2028 +"2028-12-20","National Mourning Day","PA",2028 +"2028-12-25","Christmas Day","PA",2028 +"2029-01-01","New Year's Day","PA",2029 +"2029-01-09","Martyrs' Day","PA",2029 +"2029-02-13","Carnival","PA",2029 +"2029-03-30","Good Friday","PA",2029 +"2029-05-01","Labour Day","PA",2029 +"2029-11-03","Separation Day","PA",2029 +"2029-11-04","National Symbols Day","PA",2029 +"2029-11-05","Colon Day","PA",2029 +"2029-11-10","Los Santos Uprising Day","PA",2029 +"2029-11-28","Independence Day","PA",2029 +"2029-12-08","Mother's Day","PA",2029 +"2029-12-20","National Mourning Day","PA",2029 +"2029-12-25","Christmas Day","PA",2029 +"2030-01-01","New Year's Day","PA",2030 +"2030-01-09","Martyrs' Day","PA",2030 +"2030-03-05","Carnival","PA",2030 +"2030-04-19","Good Friday","PA",2030 +"2030-05-01","Labour Day","PA",2030 +"2030-11-03","Separation Day","PA",2030 +"2030-11-04","National Symbols Day","PA",2030 +"2030-11-05","Colon Day","PA",2030 +"2030-11-10","Los Santos Uprising Day","PA",2030 +"2030-11-28","Independence Day","PA",2030 +"2030-12-08","Mother's Day","PA",2030 +"2030-12-09","Mother's Day (Observed)","PA",2030 +"2030-12-20","National Mourning Day","PA",2030 +"2030-12-25","Christmas Day","PA",2030 +"2031-01-01","New Year's Day","PA",2031 +"2031-01-09","Martyrs' Day","PA",2031 +"2031-02-25","Carnival","PA",2031 +"2031-04-11","Good Friday","PA",2031 +"2031-05-01","Labour Day","PA",2031 +"2031-11-03","Separation Day","PA",2031 +"2031-11-04","National Symbols Day","PA",2031 +"2031-11-05","Colon Day","PA",2031 +"2031-11-10","Los Santos Uprising Day","PA",2031 +"2031-11-28","Independence Day","PA",2031 +"2031-12-08","Mother's Day","PA",2031 +"2031-12-20","National Mourning Day","PA",2031 +"2031-12-25","Christmas Day","PA",2031 +"2032-01-01","New Year's Day","PA",2032 +"2032-01-09","Martyrs' Day","PA",2032 +"2032-02-10","Carnival","PA",2032 +"2032-03-26","Good Friday","PA",2032 +"2032-05-01","Labour Day","PA",2032 +"2032-11-03","Separation Day","PA",2032 +"2032-11-04","National Symbols Day","PA",2032 +"2032-11-05","Colon Day","PA",2032 +"2032-11-10","Los Santos Uprising Day","PA",2032 +"2032-11-28","Independence Day","PA",2032 +"2032-11-29","Independence Day (Observed)","PA",2032 +"2032-12-08","Mother's Day","PA",2032 +"2032-12-20","National Mourning Day","PA",2032 +"2032-12-25","Christmas Day","PA",2032 +"2033-01-01","New Year's Day","PA",2033 +"2033-01-09","Martyrs' Day","PA",2033 +"2033-01-10","Martyrs' Day (Observed)","PA",2033 +"2033-03-01","Carnival","PA",2033 +"2033-04-15","Good Friday","PA",2033 +"2033-05-01","Labour Day","PA",2033 +"2033-05-02","Labour Day (Observed)","PA",2033 +"2033-11-03","Separation Day","PA",2033 +"2033-11-04","National Symbols Day","PA",2033 +"2033-11-05","Colon Day","PA",2033 +"2033-11-10","Los Santos Uprising Day","PA",2033 +"2033-11-28","Independence Day","PA",2033 +"2033-12-08","Mother's Day","PA",2033 +"2033-12-20","National Mourning Day","PA",2033 +"2033-12-25","Christmas Day","PA",2033 +"2033-12-26","Christmas Day (Observed)","PA",2033 +"2034-01-01","New Year's Day","PA",2034 +"2034-01-02","New Year's Day (Observed)","PA",2034 +"2034-01-09","Martyrs' Day","PA",2034 +"2034-02-21","Carnival","PA",2034 +"2034-04-07","Good Friday","PA",2034 +"2034-05-01","Labour Day","PA",2034 +"2034-11-03","Separation Day","PA",2034 +"2034-11-04","National Symbols Day","PA",2034 +"2034-11-05","Colon Day","PA",2034 +"2034-11-10","Los Santos Uprising Day","PA",2034 +"2034-11-28","Independence Day","PA",2034 +"2034-12-08","Mother's Day","PA",2034 +"2034-12-20","National Mourning Day","PA",2034 +"2034-12-25","Christmas Day","PA",2034 +"2035-01-01","New Year's Day","PA",2035 +"2035-01-09","Martyrs' Day","PA",2035 +"2035-02-06","Carnival","PA",2035 +"2035-03-23","Good Friday","PA",2035 +"2035-05-01","Labour Day","PA",2035 +"2035-11-03","Separation Day","PA",2035 +"2035-11-04","National Symbols Day","PA",2035 +"2035-11-05","Colon Day","PA",2035 +"2035-11-10","Los Santos Uprising Day","PA",2035 +"2035-11-28","Independence Day","PA",2035 +"2035-12-08","Mother's Day","PA",2035 +"2035-12-20","National Mourning Day","PA",2035 +"2035-12-25","Christmas Day","PA",2035 +"2036-01-01","New Year's Day","PA",2036 +"2036-01-09","Martyrs' Day","PA",2036 +"2036-02-26","Carnival","PA",2036 +"2036-04-11","Good Friday","PA",2036 +"2036-05-01","Labour Day","PA",2036 +"2036-11-03","Separation Day","PA",2036 +"2036-11-04","National Symbols Day","PA",2036 +"2036-11-05","Colon Day","PA",2036 +"2036-11-10","Los Santos Uprising Day","PA",2036 +"2036-11-28","Independence Day","PA",2036 +"2036-12-08","Mother's Day","PA",2036 +"2036-12-20","National Mourning Day","PA",2036 +"2036-12-25","Christmas Day","PA",2036 +"2037-01-01","New Year's Day","PA",2037 +"2037-01-09","Martyrs' Day","PA",2037 +"2037-02-17","Carnival","PA",2037 +"2037-04-03","Good Friday","PA",2037 +"2037-05-01","Labour Day","PA",2037 +"2037-11-03","Separation Day","PA",2037 +"2037-11-04","National Symbols Day","PA",2037 +"2037-11-05","Colon Day","PA",2037 +"2037-11-10","Los Santos Uprising Day","PA",2037 +"2037-11-28","Independence Day","PA",2037 +"2037-12-08","Mother's Day","PA",2037 +"2037-12-20","National Mourning Day","PA",2037 +"2037-12-21","National Mourning Day (Observed)","PA",2037 +"2037-12-25","Christmas Day","PA",2037 +"2038-01-01","New Year's Day","PA",2038 +"2038-01-09","Martyrs' Day","PA",2038 +"2038-03-09","Carnival","PA",2038 +"2038-04-23","Good Friday","PA",2038 +"2038-05-01","Labour Day","PA",2038 +"2038-11-03","Separation Day","PA",2038 +"2038-11-04","National Symbols Day","PA",2038 +"2038-11-05","Colon Day","PA",2038 +"2038-11-10","Los Santos Uprising Day","PA",2038 +"2038-11-28","Independence Day","PA",2038 +"2038-11-29","Independence Day (Observed)","PA",2038 +"2038-12-08","Mother's Day","PA",2038 +"2038-12-20","National Mourning Day","PA",2038 +"2038-12-25","Christmas Day","PA",2038 +"2039-01-01","New Year's Day","PA",2039 +"2039-01-09","Martyrs' Day","PA",2039 +"2039-01-10","Martyrs' Day (Observed)","PA",2039 +"2039-02-22","Carnival","PA",2039 +"2039-04-08","Good Friday","PA",2039 +"2039-05-01","Labour Day","PA",2039 +"2039-05-02","Labour Day (Observed)","PA",2039 +"2039-11-03","Separation Day","PA",2039 +"2039-11-04","National Symbols Day","PA",2039 +"2039-11-05","Colon Day","PA",2039 +"2039-11-10","Los Santos Uprising Day","PA",2039 +"2039-11-28","Independence Day","PA",2039 +"2039-12-08","Mother's Day","PA",2039 +"2039-12-20","National Mourning Day","PA",2039 +"2039-12-25","Christmas Day","PA",2039 +"2039-12-26","Christmas Day (Observed)","PA",2039 +"2040-01-01","New Year's Day","PA",2040 +"2040-01-02","New Year's Day (Observed)","PA",2040 +"2040-01-09","Martyrs' Day","PA",2040 +"2040-02-14","Carnival","PA",2040 +"2040-03-30","Good Friday","PA",2040 +"2040-05-01","Labour Day","PA",2040 +"2040-11-03","Separation Day","PA",2040 +"2040-11-04","National Symbols Day","PA",2040 +"2040-11-05","Colon Day","PA",2040 +"2040-11-10","Los Santos Uprising Day","PA",2040 +"2040-11-28","Independence Day","PA",2040 +"2040-12-08","Mother's Day","PA",2040 +"2040-12-20","National Mourning Day","PA",2040 +"2040-12-25","Christmas Day","PA",2040 +"2041-01-01","New Year's Day","PA",2041 +"2041-01-09","Martyrs' Day","PA",2041 +"2041-03-05","Carnival","PA",2041 +"2041-04-19","Good Friday","PA",2041 +"2041-05-01","Labour Day","PA",2041 +"2041-11-03","Separation Day","PA",2041 +"2041-11-04","National Symbols Day","PA",2041 +"2041-11-05","Colon Day","PA",2041 +"2041-11-10","Los Santos Uprising Day","PA",2041 +"2041-11-28","Independence Day","PA",2041 +"2041-12-08","Mother's Day","PA",2041 +"2041-12-09","Mother's Day (Observed)","PA",2041 +"2041-12-20","National Mourning Day","PA",2041 +"2041-12-25","Christmas Day","PA",2041 +"2042-01-01","New Year's Day","PA",2042 +"2042-01-09","Martyrs' Day","PA",2042 +"2042-02-18","Carnival","PA",2042 +"2042-04-04","Good Friday","PA",2042 +"2042-05-01","Labour Day","PA",2042 +"2042-11-03","Separation Day","PA",2042 +"2042-11-04","National Symbols Day","PA",2042 +"2042-11-05","Colon Day","PA",2042 +"2042-11-10","Los Santos Uprising Day","PA",2042 +"2042-11-28","Independence Day","PA",2042 +"2042-12-08","Mother's Day","PA",2042 +"2042-12-20","National Mourning Day","PA",2042 +"2042-12-25","Christmas Day","PA",2042 +"2043-01-01","New Year's Day","PA",2043 +"2043-01-09","Martyrs' Day","PA",2043 +"2043-02-10","Carnival","PA",2043 +"2043-03-27","Good Friday","PA",2043 +"2043-05-01","Labour Day","PA",2043 +"2043-11-03","Separation Day","PA",2043 +"2043-11-04","National Symbols Day","PA",2043 +"2043-11-05","Colon Day","PA",2043 +"2043-11-10","Los Santos Uprising Day","PA",2043 +"2043-11-28","Independence Day","PA",2043 +"2043-12-08","Mother's Day","PA",2043 +"2043-12-20","National Mourning Day","PA",2043 +"2043-12-21","National Mourning Day (Observed)","PA",2043 +"2043-12-25","Christmas Day","PA",2043 +"2044-01-01","New Year's Day","PA",2044 +"2044-01-09","Martyrs' Day","PA",2044 +"2044-03-01","Carnival","PA",2044 +"2044-04-15","Good Friday","PA",2044 +"2044-05-01","Labour Day","PA",2044 +"2044-05-02","Labour Day (Observed)","PA",2044 +"2044-11-03","Separation Day","PA",2044 +"2044-11-04","National Symbols Day","PA",2044 +"2044-11-05","Colon Day","PA",2044 +"2044-11-10","Los Santos Uprising Day","PA",2044 +"2044-11-28","Independence Day","PA",2044 +"2044-12-08","Mother's Day","PA",2044 +"2044-12-20","National Mourning Day","PA",2044 +"2044-12-25","Christmas Day","PA",2044 +"2044-12-26","Christmas Day (Observed)","PA",2044 +"1995-01-01","New Year's Day","PE",1995 +"1995-04-13","Maundy Thursday","PE",1995 +"1995-04-14","Good Friday","PE",1995 +"1995-04-16","Easter Sunday","PE",1995 +"1995-05-01","Labour Day","PE",1995 +"1995-06-29","Saint Peter and Saint Paul","PE",1995 +"1995-07-28","Independence Day","PE",1995 +"1995-07-29","Great Military Parade Day","PE",1995 +"1995-08-30","Rose of Lima Day","PE",1995 +"1995-10-08","Battle of Angamos Day","PE",1995 +"1995-11-01","All Saints' Day","PE",1995 +"1995-12-08","Immaculate Conception Day","PE",1995 +"1995-12-25","Christmas Day","PE",1995 +"1996-01-01","New Year's Day","PE",1996 +"1996-04-04","Maundy Thursday","PE",1996 +"1996-04-05","Good Friday","PE",1996 +"1996-04-07","Easter Sunday","PE",1996 +"1996-05-01","Labour Day","PE",1996 +"1996-06-29","Saint Peter and Saint Paul","PE",1996 +"1996-07-28","Independence Day","PE",1996 +"1996-07-29","Great Military Parade Day","PE",1996 +"1996-08-30","Rose of Lima Day","PE",1996 +"1996-10-08","Battle of Angamos Day","PE",1996 +"1996-11-01","All Saints' Day","PE",1996 +"1996-12-08","Immaculate Conception Day","PE",1996 +"1996-12-25","Christmas Day","PE",1996 +"1997-01-01","New Year's Day","PE",1997 +"1997-03-27","Maundy Thursday","PE",1997 +"1997-03-28","Good Friday","PE",1997 +"1997-03-30","Easter Sunday","PE",1997 +"1997-05-01","Labour Day","PE",1997 +"1997-06-29","Saint Peter and Saint Paul","PE",1997 +"1997-07-28","Independence Day","PE",1997 +"1997-07-29","Great Military Parade Day","PE",1997 +"1997-08-30","Rose of Lima Day","PE",1997 +"1997-10-08","Battle of Angamos Day","PE",1997 +"1997-11-01","All Saints' Day","PE",1997 +"1997-12-08","Immaculate Conception Day","PE",1997 +"1997-12-25","Christmas Day","PE",1997 +"1998-01-01","New Year's Day","PE",1998 +"1998-04-09","Maundy Thursday","PE",1998 +"1998-04-10","Good Friday","PE",1998 +"1998-04-12","Easter Sunday","PE",1998 +"1998-05-01","Labour Day","PE",1998 +"1998-06-29","Saint Peter and Saint Paul","PE",1998 +"1998-07-28","Independence Day","PE",1998 +"1998-07-29","Great Military Parade Day","PE",1998 +"1998-08-30","Rose of Lima Day","PE",1998 +"1998-10-08","Battle of Angamos Day","PE",1998 +"1998-11-01","All Saints' Day","PE",1998 +"1998-12-08","Immaculate Conception Day","PE",1998 +"1998-12-25","Christmas Day","PE",1998 +"1999-01-01","New Year's Day","PE",1999 +"1999-04-01","Maundy Thursday","PE",1999 +"1999-04-02","Good Friday","PE",1999 +"1999-04-04","Easter Sunday","PE",1999 +"1999-05-01","Labour Day","PE",1999 +"1999-06-29","Saint Peter and Saint Paul","PE",1999 +"1999-07-28","Independence Day","PE",1999 +"1999-07-29","Great Military Parade Day","PE",1999 +"1999-08-30","Rose of Lima Day","PE",1999 +"1999-10-08","Battle of Angamos Day","PE",1999 +"1999-11-01","All Saints' Day","PE",1999 +"1999-12-08","Immaculate Conception Day","PE",1999 +"1999-12-25","Christmas Day","PE",1999 +"2000-01-01","New Year's Day","PE",2000 +"2000-04-20","Maundy Thursday","PE",2000 +"2000-04-21","Good Friday","PE",2000 +"2000-04-23","Easter Sunday","PE",2000 +"2000-05-01","Labour Day","PE",2000 +"2000-06-29","Saint Peter and Saint Paul","PE",2000 +"2000-07-28","Independence Day","PE",2000 +"2000-07-29","Great Military Parade Day","PE",2000 +"2000-08-30","Rose of Lima Day","PE",2000 +"2000-10-08","Battle of Angamos Day","PE",2000 +"2000-11-01","All Saints' Day","PE",2000 +"2000-12-08","Immaculate Conception Day","PE",2000 +"2000-12-25","Christmas Day","PE",2000 +"2001-01-01","New Year's Day","PE",2001 +"2001-04-12","Maundy Thursday","PE",2001 +"2001-04-13","Good Friday","PE",2001 +"2001-04-15","Easter Sunday","PE",2001 +"2001-05-01","Labour Day","PE",2001 +"2001-06-29","Saint Peter and Saint Paul","PE",2001 +"2001-07-28","Independence Day","PE",2001 +"2001-07-29","Great Military Parade Day","PE",2001 +"2001-08-30","Rose of Lima Day","PE",2001 +"2001-10-08","Battle of Angamos Day","PE",2001 +"2001-11-01","All Saints' Day","PE",2001 +"2001-12-08","Immaculate Conception Day","PE",2001 +"2001-12-25","Christmas Day","PE",2001 +"2002-01-01","New Year's Day","PE",2002 +"2002-03-28","Maundy Thursday","PE",2002 +"2002-03-29","Good Friday","PE",2002 +"2002-03-31","Easter Sunday","PE",2002 +"2002-05-01","Labour Day","PE",2002 +"2002-06-29","Saint Peter and Saint Paul","PE",2002 +"2002-07-28","Independence Day","PE",2002 +"2002-07-29","Great Military Parade Day","PE",2002 +"2002-08-30","Rose of Lima Day","PE",2002 +"2002-10-08","Battle of Angamos Day","PE",2002 +"2002-11-01","All Saints' Day","PE",2002 +"2002-12-08","Immaculate Conception Day","PE",2002 +"2002-12-25","Christmas Day","PE",2002 +"2003-01-01","New Year's Day","PE",2003 +"2003-04-17","Maundy Thursday","PE",2003 +"2003-04-18","Good Friday","PE",2003 +"2003-04-20","Easter Sunday","PE",2003 +"2003-05-01","Labour Day","PE",2003 +"2003-06-29","Saint Peter and Saint Paul","PE",2003 +"2003-07-28","Independence Day","PE",2003 +"2003-07-29","Great Military Parade Day","PE",2003 +"2003-08-30","Rose of Lima Day","PE",2003 +"2003-10-08","Battle of Angamos Day","PE",2003 +"2003-11-01","All Saints' Day","PE",2003 +"2003-12-08","Immaculate Conception Day","PE",2003 +"2003-12-25","Christmas Day","PE",2003 +"2004-01-01","New Year's Day","PE",2004 +"2004-04-08","Maundy Thursday","PE",2004 +"2004-04-09","Good Friday","PE",2004 +"2004-04-11","Easter Sunday","PE",2004 +"2004-05-01","Labour Day","PE",2004 +"2004-06-29","Saint Peter and Saint Paul","PE",2004 +"2004-07-28","Independence Day","PE",2004 +"2004-07-29","Great Military Parade Day","PE",2004 +"2004-08-30","Rose of Lima Day","PE",2004 +"2004-10-08","Battle of Angamos Day","PE",2004 +"2004-11-01","All Saints' Day","PE",2004 +"2004-12-08","Immaculate Conception Day","PE",2004 +"2004-12-25","Christmas Day","PE",2004 +"2005-01-01","New Year's Day","PE",2005 +"2005-03-24","Maundy Thursday","PE",2005 +"2005-03-25","Good Friday","PE",2005 +"2005-03-27","Easter Sunday","PE",2005 +"2005-05-01","Labour Day","PE",2005 +"2005-06-29","Saint Peter and Saint Paul","PE",2005 +"2005-07-28","Independence Day","PE",2005 +"2005-07-29","Great Military Parade Day","PE",2005 +"2005-08-30","Rose of Lima Day","PE",2005 +"2005-10-08","Battle of Angamos Day","PE",2005 +"2005-11-01","All Saints' Day","PE",2005 +"2005-12-08","Immaculate Conception Day","PE",2005 +"2005-12-25","Christmas Day","PE",2005 +"2006-01-01","New Year's Day","PE",2006 +"2006-04-13","Maundy Thursday","PE",2006 +"2006-04-14","Good Friday","PE",2006 +"2006-04-16","Easter Sunday","PE",2006 +"2006-05-01","Labour Day","PE",2006 +"2006-06-29","Saint Peter and Saint Paul","PE",2006 +"2006-07-28","Independence Day","PE",2006 +"2006-07-29","Great Military Parade Day","PE",2006 +"2006-08-30","Rose of Lima Day","PE",2006 +"2006-10-08","Battle of Angamos Day","PE",2006 +"2006-11-01","All Saints' Day","PE",2006 +"2006-12-08","Immaculate Conception Day","PE",2006 +"2006-12-25","Christmas Day","PE",2006 +"2007-01-01","New Year's Day","PE",2007 +"2007-04-05","Maundy Thursday","PE",2007 +"2007-04-06","Good Friday","PE",2007 +"2007-04-08","Easter Sunday","PE",2007 +"2007-05-01","Labour Day","PE",2007 +"2007-06-29","Saint Peter and Saint Paul","PE",2007 +"2007-07-28","Independence Day","PE",2007 +"2007-07-29","Great Military Parade Day","PE",2007 +"2007-08-30","Rose of Lima Day","PE",2007 +"2007-10-08","Battle of Angamos Day","PE",2007 +"2007-11-01","All Saints' Day","PE",2007 +"2007-12-08","Immaculate Conception Day","PE",2007 +"2007-12-25","Christmas Day","PE",2007 +"2008-01-01","New Year's Day","PE",2008 +"2008-03-20","Maundy Thursday","PE",2008 +"2008-03-21","Good Friday","PE",2008 +"2008-03-23","Easter Sunday","PE",2008 +"2008-05-01","Labour Day","PE",2008 +"2008-06-29","Saint Peter and Saint Paul","PE",2008 +"2008-07-28","Independence Day","PE",2008 +"2008-07-29","Great Military Parade Day","PE",2008 +"2008-08-30","Rose of Lima Day","PE",2008 +"2008-10-08","Battle of Angamos Day","PE",2008 +"2008-11-01","All Saints' Day","PE",2008 +"2008-12-08","Immaculate Conception Day","PE",2008 +"2008-12-25","Christmas Day","PE",2008 +"2009-01-01","New Year's Day","PE",2009 +"2009-04-09","Maundy Thursday","PE",2009 +"2009-04-10","Good Friday","PE",2009 +"2009-04-12","Easter Sunday","PE",2009 +"2009-05-01","Labour Day","PE",2009 +"2009-06-29","Saint Peter and Saint Paul","PE",2009 +"2009-07-28","Independence Day","PE",2009 +"2009-07-29","Great Military Parade Day","PE",2009 +"2009-08-30","Rose of Lima Day","PE",2009 +"2009-10-08","Battle of Angamos Day","PE",2009 +"2009-11-01","All Saints' Day","PE",2009 +"2009-12-08","Immaculate Conception Day","PE",2009 +"2009-12-25","Christmas Day","PE",2009 +"2010-01-01","New Year's Day","PE",2010 +"2010-04-01","Maundy Thursday","PE",2010 +"2010-04-02","Good Friday","PE",2010 +"2010-04-04","Easter Sunday","PE",2010 +"2010-05-01","Labour Day","PE",2010 +"2010-06-29","Saint Peter and Saint Paul","PE",2010 +"2010-07-28","Independence Day","PE",2010 +"2010-07-29","Great Military Parade Day","PE",2010 +"2010-08-30","Rose of Lima Day","PE",2010 +"2010-10-08","Battle of Angamos Day","PE",2010 +"2010-11-01","All Saints' Day","PE",2010 +"2010-12-08","Immaculate Conception Day","PE",2010 +"2010-12-25","Christmas Day","PE",2010 +"2011-01-01","New Year's Day","PE",2011 +"2011-04-21","Maundy Thursday","PE",2011 +"2011-04-22","Good Friday","PE",2011 +"2011-04-24","Easter Sunday","PE",2011 +"2011-05-01","Labour Day","PE",2011 +"2011-06-29","Saint Peter and Saint Paul","PE",2011 +"2011-07-28","Independence Day","PE",2011 +"2011-07-29","Great Military Parade Day","PE",2011 +"2011-08-30","Rose of Lima Day","PE",2011 +"2011-10-08","Battle of Angamos Day","PE",2011 +"2011-11-01","All Saints' Day","PE",2011 +"2011-12-08","Immaculate Conception Day","PE",2011 +"2011-12-25","Christmas Day","PE",2011 +"2012-01-01","New Year's Day","PE",2012 +"2012-04-05","Maundy Thursday","PE",2012 +"2012-04-06","Good Friday","PE",2012 +"2012-04-08","Easter Sunday","PE",2012 +"2012-05-01","Labour Day","PE",2012 +"2012-06-29","Saint Peter and Saint Paul","PE",2012 +"2012-07-28","Independence Day","PE",2012 +"2012-07-29","Great Military Parade Day","PE",2012 +"2012-08-30","Rose of Lima Day","PE",2012 +"2012-10-08","Battle of Angamos Day","PE",2012 +"2012-11-01","All Saints' Day","PE",2012 +"2012-12-08","Immaculate Conception Day","PE",2012 +"2012-12-25","Christmas Day","PE",2012 +"2013-01-01","New Year's Day","PE",2013 +"2013-03-28","Maundy Thursday","PE",2013 +"2013-03-29","Good Friday","PE",2013 +"2013-03-31","Easter Sunday","PE",2013 +"2013-05-01","Labour Day","PE",2013 +"2013-06-29","Saint Peter and Saint Paul","PE",2013 +"2013-07-28","Independence Day","PE",2013 +"2013-07-29","Great Military Parade Day","PE",2013 +"2013-08-30","Rose of Lima Day","PE",2013 +"2013-10-08","Battle of Angamos Day","PE",2013 +"2013-11-01","All Saints' Day","PE",2013 +"2013-12-08","Immaculate Conception Day","PE",2013 +"2013-12-25","Christmas Day","PE",2013 +"2014-01-01","New Year's Day","PE",2014 +"2014-04-17","Maundy Thursday","PE",2014 +"2014-04-18","Good Friday","PE",2014 +"2014-04-20","Easter Sunday","PE",2014 +"2014-05-01","Labour Day","PE",2014 +"2014-06-29","Saint Peter and Saint Paul","PE",2014 +"2014-07-28","Independence Day","PE",2014 +"2014-07-29","Great Military Parade Day","PE",2014 +"2014-08-30","Rose of Lima Day","PE",2014 +"2014-10-08","Battle of Angamos Day","PE",2014 +"2014-11-01","All Saints' Day","PE",2014 +"2014-12-08","Immaculate Conception Day","PE",2014 +"2014-12-25","Christmas Day","PE",2014 +"2015-01-01","New Year's Day","PE",2015 +"2015-04-02","Maundy Thursday","PE",2015 +"2015-04-03","Good Friday","PE",2015 +"2015-04-05","Easter Sunday","PE",2015 +"2015-05-01","Labour Day","PE",2015 +"2015-06-29","Saint Peter and Saint Paul","PE",2015 +"2015-07-28","Independence Day","PE",2015 +"2015-07-29","Great Military Parade Day","PE",2015 +"2015-08-30","Rose of Lima Day","PE",2015 +"2015-10-08","Battle of Angamos Day","PE",2015 +"2015-11-01","All Saints' Day","PE",2015 +"2015-12-08","Immaculate Conception Day","PE",2015 +"2015-12-25","Christmas Day","PE",2015 +"2016-01-01","New Year's Day","PE",2016 +"2016-03-24","Maundy Thursday","PE",2016 +"2016-03-25","Good Friday","PE",2016 +"2016-03-27","Easter Sunday","PE",2016 +"2016-05-01","Labour Day","PE",2016 +"2016-06-29","Saint Peter and Saint Paul","PE",2016 +"2016-07-28","Independence Day","PE",2016 +"2016-07-29","Great Military Parade Day","PE",2016 +"2016-08-30","Rose of Lima Day","PE",2016 +"2016-10-08","Battle of Angamos Day","PE",2016 +"2016-11-01","All Saints' Day","PE",2016 +"2016-12-08","Immaculate Conception Day","PE",2016 +"2016-12-25","Christmas Day","PE",2016 +"2017-01-01","New Year's Day","PE",2017 +"2017-04-13","Maundy Thursday","PE",2017 +"2017-04-14","Good Friday","PE",2017 +"2017-04-16","Easter Sunday","PE",2017 +"2017-05-01","Labour Day","PE",2017 +"2017-06-29","Saint Peter and Saint Paul","PE",2017 +"2017-07-28","Independence Day","PE",2017 +"2017-07-29","Great Military Parade Day","PE",2017 +"2017-08-30","Rose of Lima Day","PE",2017 +"2017-10-08","Battle of Angamos Day","PE",2017 +"2017-11-01","All Saints' Day","PE",2017 +"2017-12-08","Immaculate Conception Day","PE",2017 +"2017-12-25","Christmas Day","PE",2017 +"2018-01-01","New Year's Day","PE",2018 +"2018-03-29","Maundy Thursday","PE",2018 +"2018-03-30","Good Friday","PE",2018 +"2018-04-01","Easter Sunday","PE",2018 +"2018-05-01","Labour Day","PE",2018 +"2018-06-29","Saint Peter and Saint Paul","PE",2018 +"2018-07-28","Independence Day","PE",2018 +"2018-07-29","Great Military Parade Day","PE",2018 +"2018-08-30","Rose of Lima Day","PE",2018 +"2018-10-08","Battle of Angamos Day","PE",2018 +"2018-11-01","All Saints' Day","PE",2018 +"2018-12-08","Immaculate Conception Day","PE",2018 +"2018-12-25","Christmas Day","PE",2018 +"2019-01-01","New Year's Day","PE",2019 +"2019-04-18","Maundy Thursday","PE",2019 +"2019-04-19","Good Friday","PE",2019 +"2019-04-21","Easter Sunday","PE",2019 +"2019-05-01","Labour Day","PE",2019 +"2019-06-29","Saint Peter and Saint Paul","PE",2019 +"2019-07-28","Independence Day","PE",2019 +"2019-07-29","Great Military Parade Day","PE",2019 +"2019-08-30","Rose of Lima Day","PE",2019 +"2019-10-08","Battle of Angamos Day","PE",2019 +"2019-11-01","All Saints' Day","PE",2019 +"2019-12-08","Immaculate Conception Day","PE",2019 +"2019-12-25","Christmas Day","PE",2019 +"2020-01-01","New Year's Day","PE",2020 +"2020-04-09","Maundy Thursday","PE",2020 +"2020-04-10","Good Friday","PE",2020 +"2020-04-12","Easter Sunday","PE",2020 +"2020-05-01","Labour Day","PE",2020 +"2020-06-29","Saint Peter and Saint Paul","PE",2020 +"2020-07-28","Independence Day","PE",2020 +"2020-07-29","Great Military Parade Day","PE",2020 +"2020-08-30","Rose of Lima Day","PE",2020 +"2020-10-08","Battle of Angamos Day","PE",2020 +"2020-11-01","All Saints' Day","PE",2020 +"2020-12-08","Immaculate Conception Day","PE",2020 +"2020-12-25","Christmas Day","PE",2020 +"2021-01-01","New Year's Day","PE",2021 +"2021-04-01","Maundy Thursday","PE",2021 +"2021-04-02","Good Friday","PE",2021 +"2021-04-04","Easter Sunday","PE",2021 +"2021-05-01","Labour Day","PE",2021 +"2021-06-29","Saint Peter and Saint Paul","PE",2021 +"2021-07-28","Independence Day","PE",2021 +"2021-07-29","Great Military Parade Day","PE",2021 +"2021-08-30","Rose of Lima Day","PE",2021 +"2021-10-08","Battle of Angamos Day","PE",2021 +"2021-11-01","All Saints' Day","PE",2021 +"2021-12-08","Immaculate Conception Day","PE",2021 +"2021-12-25","Christmas Day","PE",2021 +"2022-01-01","New Year's Day","PE",2022 +"2022-04-14","Maundy Thursday","PE",2022 +"2022-04-15","Good Friday","PE",2022 +"2022-04-17","Easter Sunday","PE",2022 +"2022-05-01","Labour Day","PE",2022 +"2022-06-29","Saint Peter and Saint Paul","PE",2022 +"2022-07-28","Independence Day","PE",2022 +"2022-07-29","Great Military Parade Day","PE",2022 +"2022-08-06","Battle of Junin Day","PE",2022 +"2022-08-30","Rose of Lima Day","PE",2022 +"2022-10-08","Battle of Angamos Day","PE",2022 +"2022-11-01","All Saints' Day","PE",2022 +"2022-12-08","Immaculate Conception Day","PE",2022 +"2022-12-09","Battle of Ayacucho Day","PE",2022 +"2022-12-25","Christmas Day","PE",2022 +"2023-01-01","New Year's Day","PE",2023 +"2023-04-06","Maundy Thursday","PE",2023 +"2023-04-07","Good Friday","PE",2023 +"2023-04-09","Easter Sunday","PE",2023 +"2023-05-01","Labour Day","PE",2023 +"2023-06-29","Saint Peter and Saint Paul","PE",2023 +"2023-07-28","Independence Day","PE",2023 +"2023-07-29","Great Military Parade Day","PE",2023 +"2023-08-06","Battle of Junin Day","PE",2023 +"2023-08-30","Rose of Lima Day","PE",2023 +"2023-10-08","Battle of Angamos Day","PE",2023 +"2023-11-01","All Saints' Day","PE",2023 +"2023-12-08","Immaculate Conception Day","PE",2023 +"2023-12-09","Battle of Ayacucho Day","PE",2023 +"2023-12-25","Christmas Day","PE",2023 +"2024-01-01","New Year's Day","PE",2024 +"2024-03-28","Maundy Thursday","PE",2024 +"2024-03-29","Good Friday","PE",2024 +"2024-03-31","Easter Sunday","PE",2024 +"2024-05-01","Labour Day","PE",2024 +"2024-06-29","Saint Peter and Saint Paul","PE",2024 +"2024-07-28","Independence Day","PE",2024 +"2024-07-29","Great Military Parade Day","PE",2024 +"2024-08-06","Battle of Junin Day","PE",2024 +"2024-08-30","Rose of Lima Day","PE",2024 +"2024-10-08","Battle of Angamos Day","PE",2024 +"2024-11-01","All Saints' Day","PE",2024 +"2024-12-08","Immaculate Conception Day","PE",2024 +"2024-12-09","Battle of Ayacucho Day","PE",2024 +"2024-12-25","Christmas Day","PE",2024 +"2025-01-01","New Year's Day","PE",2025 +"2025-04-17","Maundy Thursday","PE",2025 +"2025-04-18","Good Friday","PE",2025 +"2025-04-20","Easter Sunday","PE",2025 +"2025-05-01","Labour Day","PE",2025 +"2025-06-29","Saint Peter and Saint Paul","PE",2025 +"2025-07-28","Independence Day","PE",2025 +"2025-07-29","Great Military Parade Day","PE",2025 +"2025-08-06","Battle of Junin Day","PE",2025 +"2025-08-30","Rose of Lima Day","PE",2025 +"2025-10-08","Battle of Angamos Day","PE",2025 +"2025-11-01","All Saints' Day","PE",2025 +"2025-12-08","Immaculate Conception Day","PE",2025 +"2025-12-09","Battle of Ayacucho Day","PE",2025 +"2025-12-25","Christmas Day","PE",2025 +"2026-01-01","New Year's Day","PE",2026 +"2026-04-02","Maundy Thursday","PE",2026 +"2026-04-03","Good Friday","PE",2026 +"2026-04-05","Easter Sunday","PE",2026 +"2026-05-01","Labour Day","PE",2026 +"2026-06-29","Saint Peter and Saint Paul","PE",2026 +"2026-07-28","Independence Day","PE",2026 +"2026-07-29","Great Military Parade Day","PE",2026 +"2026-08-06","Battle of Junin Day","PE",2026 +"2026-08-30","Rose of Lima Day","PE",2026 +"2026-10-08","Battle of Angamos Day","PE",2026 +"2026-11-01","All Saints' Day","PE",2026 +"2026-12-08","Immaculate Conception Day","PE",2026 +"2026-12-09","Battle of Ayacucho Day","PE",2026 +"2026-12-25","Christmas Day","PE",2026 +"2027-01-01","New Year's Day","PE",2027 +"2027-03-25","Maundy Thursday","PE",2027 +"2027-03-26","Good Friday","PE",2027 +"2027-03-28","Easter Sunday","PE",2027 +"2027-05-01","Labour Day","PE",2027 +"2027-06-29","Saint Peter and Saint Paul","PE",2027 +"2027-07-28","Independence Day","PE",2027 +"2027-07-29","Great Military Parade Day","PE",2027 +"2027-08-06","Battle of Junin Day","PE",2027 +"2027-08-30","Rose of Lima Day","PE",2027 +"2027-10-08","Battle of Angamos Day","PE",2027 +"2027-11-01","All Saints' Day","PE",2027 +"2027-12-08","Immaculate Conception Day","PE",2027 +"2027-12-09","Battle of Ayacucho Day","PE",2027 +"2027-12-25","Christmas Day","PE",2027 +"2028-01-01","New Year's Day","PE",2028 +"2028-04-13","Maundy Thursday","PE",2028 +"2028-04-14","Good Friday","PE",2028 +"2028-04-16","Easter Sunday","PE",2028 +"2028-05-01","Labour Day","PE",2028 +"2028-06-29","Saint Peter and Saint Paul","PE",2028 +"2028-07-28","Independence Day","PE",2028 +"2028-07-29","Great Military Parade Day","PE",2028 +"2028-08-06","Battle of Junin Day","PE",2028 +"2028-08-30","Rose of Lima Day","PE",2028 +"2028-10-08","Battle of Angamos Day","PE",2028 +"2028-11-01","All Saints' Day","PE",2028 +"2028-12-08","Immaculate Conception Day","PE",2028 +"2028-12-09","Battle of Ayacucho Day","PE",2028 +"2028-12-25","Christmas Day","PE",2028 +"2029-01-01","New Year's Day","PE",2029 +"2029-03-29","Maundy Thursday","PE",2029 +"2029-03-30","Good Friday","PE",2029 +"2029-04-01","Easter Sunday","PE",2029 +"2029-05-01","Labour Day","PE",2029 +"2029-06-29","Saint Peter and Saint Paul","PE",2029 +"2029-07-28","Independence Day","PE",2029 +"2029-07-29","Great Military Parade Day","PE",2029 +"2029-08-06","Battle of Junin Day","PE",2029 +"2029-08-30","Rose of Lima Day","PE",2029 +"2029-10-08","Battle of Angamos Day","PE",2029 +"2029-11-01","All Saints' Day","PE",2029 +"2029-12-08","Immaculate Conception Day","PE",2029 +"2029-12-09","Battle of Ayacucho Day","PE",2029 +"2029-12-25","Christmas Day","PE",2029 +"2030-01-01","New Year's Day","PE",2030 +"2030-04-18","Maundy Thursday","PE",2030 +"2030-04-19","Good Friday","PE",2030 +"2030-04-21","Easter Sunday","PE",2030 +"2030-05-01","Labour Day","PE",2030 +"2030-06-29","Saint Peter and Saint Paul","PE",2030 +"2030-07-28","Independence Day","PE",2030 +"2030-07-29","Great Military Parade Day","PE",2030 +"2030-08-06","Battle of Junin Day","PE",2030 +"2030-08-30","Rose of Lima Day","PE",2030 +"2030-10-08","Battle of Angamos Day","PE",2030 +"2030-11-01","All Saints' Day","PE",2030 +"2030-12-08","Immaculate Conception Day","PE",2030 +"2030-12-09","Battle of Ayacucho Day","PE",2030 +"2030-12-25","Christmas Day","PE",2030 +"2031-01-01","New Year's Day","PE",2031 +"2031-04-10","Maundy Thursday","PE",2031 +"2031-04-11","Good Friday","PE",2031 +"2031-04-13","Easter Sunday","PE",2031 +"2031-05-01","Labour Day","PE",2031 +"2031-06-29","Saint Peter and Saint Paul","PE",2031 +"2031-07-28","Independence Day","PE",2031 +"2031-07-29","Great Military Parade Day","PE",2031 +"2031-08-06","Battle of Junin Day","PE",2031 +"2031-08-30","Rose of Lima Day","PE",2031 +"2031-10-08","Battle of Angamos Day","PE",2031 +"2031-11-01","All Saints' Day","PE",2031 +"2031-12-08","Immaculate Conception Day","PE",2031 +"2031-12-09","Battle of Ayacucho Day","PE",2031 +"2031-12-25","Christmas Day","PE",2031 +"2032-01-01","New Year's Day","PE",2032 +"2032-03-25","Maundy Thursday","PE",2032 +"2032-03-26","Good Friday","PE",2032 +"2032-03-28","Easter Sunday","PE",2032 +"2032-05-01","Labour Day","PE",2032 +"2032-06-29","Saint Peter and Saint Paul","PE",2032 +"2032-07-28","Independence Day","PE",2032 +"2032-07-29","Great Military Parade Day","PE",2032 +"2032-08-06","Battle of Junin Day","PE",2032 +"2032-08-30","Rose of Lima Day","PE",2032 +"2032-10-08","Battle of Angamos Day","PE",2032 +"2032-11-01","All Saints' Day","PE",2032 +"2032-12-08","Immaculate Conception Day","PE",2032 +"2032-12-09","Battle of Ayacucho Day","PE",2032 +"2032-12-25","Christmas Day","PE",2032 +"2033-01-01","New Year's Day","PE",2033 +"2033-04-14","Maundy Thursday","PE",2033 +"2033-04-15","Good Friday","PE",2033 +"2033-04-17","Easter Sunday","PE",2033 +"2033-05-01","Labour Day","PE",2033 +"2033-06-29","Saint Peter and Saint Paul","PE",2033 +"2033-07-28","Independence Day","PE",2033 +"2033-07-29","Great Military Parade Day","PE",2033 +"2033-08-06","Battle of Junin Day","PE",2033 +"2033-08-30","Rose of Lima Day","PE",2033 +"2033-10-08","Battle of Angamos Day","PE",2033 +"2033-11-01","All Saints' Day","PE",2033 +"2033-12-08","Immaculate Conception Day","PE",2033 +"2033-12-09","Battle of Ayacucho Day","PE",2033 +"2033-12-25","Christmas Day","PE",2033 +"2034-01-01","New Year's Day","PE",2034 +"2034-04-06","Maundy Thursday","PE",2034 +"2034-04-07","Good Friday","PE",2034 +"2034-04-09","Easter Sunday","PE",2034 +"2034-05-01","Labour Day","PE",2034 +"2034-06-29","Saint Peter and Saint Paul","PE",2034 +"2034-07-28","Independence Day","PE",2034 +"2034-07-29","Great Military Parade Day","PE",2034 +"2034-08-06","Battle of Junin Day","PE",2034 +"2034-08-30","Rose of Lima Day","PE",2034 +"2034-10-08","Battle of Angamos Day","PE",2034 +"2034-11-01","All Saints' Day","PE",2034 +"2034-12-08","Immaculate Conception Day","PE",2034 +"2034-12-09","Battle of Ayacucho Day","PE",2034 +"2034-12-25","Christmas Day","PE",2034 +"2035-01-01","New Year's Day","PE",2035 +"2035-03-22","Maundy Thursday","PE",2035 +"2035-03-23","Good Friday","PE",2035 +"2035-03-25","Easter Sunday","PE",2035 +"2035-05-01","Labour Day","PE",2035 +"2035-06-29","Saint Peter and Saint Paul","PE",2035 +"2035-07-28","Independence Day","PE",2035 +"2035-07-29","Great Military Parade Day","PE",2035 +"2035-08-06","Battle of Junin Day","PE",2035 +"2035-08-30","Rose of Lima Day","PE",2035 +"2035-10-08","Battle of Angamos Day","PE",2035 +"2035-11-01","All Saints' Day","PE",2035 +"2035-12-08","Immaculate Conception Day","PE",2035 +"2035-12-09","Battle of Ayacucho Day","PE",2035 +"2035-12-25","Christmas Day","PE",2035 +"2036-01-01","New Year's Day","PE",2036 +"2036-04-10","Maundy Thursday","PE",2036 +"2036-04-11","Good Friday","PE",2036 +"2036-04-13","Easter Sunday","PE",2036 +"2036-05-01","Labour Day","PE",2036 +"2036-06-29","Saint Peter and Saint Paul","PE",2036 +"2036-07-28","Independence Day","PE",2036 +"2036-07-29","Great Military Parade Day","PE",2036 +"2036-08-06","Battle of Junin Day","PE",2036 +"2036-08-30","Rose of Lima Day","PE",2036 +"2036-10-08","Battle of Angamos Day","PE",2036 +"2036-11-01","All Saints' Day","PE",2036 +"2036-12-08","Immaculate Conception Day","PE",2036 +"2036-12-09","Battle of Ayacucho Day","PE",2036 +"2036-12-25","Christmas Day","PE",2036 +"2037-01-01","New Year's Day","PE",2037 +"2037-04-02","Maundy Thursday","PE",2037 +"2037-04-03","Good Friday","PE",2037 +"2037-04-05","Easter Sunday","PE",2037 +"2037-05-01","Labour Day","PE",2037 +"2037-06-29","Saint Peter and Saint Paul","PE",2037 +"2037-07-28","Independence Day","PE",2037 +"2037-07-29","Great Military Parade Day","PE",2037 +"2037-08-06","Battle of Junin Day","PE",2037 +"2037-08-30","Rose of Lima Day","PE",2037 +"2037-10-08","Battle of Angamos Day","PE",2037 +"2037-11-01","All Saints' Day","PE",2037 +"2037-12-08","Immaculate Conception Day","PE",2037 +"2037-12-09","Battle of Ayacucho Day","PE",2037 +"2037-12-25","Christmas Day","PE",2037 +"2038-01-01","New Year's Day","PE",2038 +"2038-04-22","Maundy Thursday","PE",2038 +"2038-04-23","Good Friday","PE",2038 +"2038-04-25","Easter Sunday","PE",2038 +"2038-05-01","Labour Day","PE",2038 +"2038-06-29","Saint Peter and Saint Paul","PE",2038 +"2038-07-28","Independence Day","PE",2038 +"2038-07-29","Great Military Parade Day","PE",2038 +"2038-08-06","Battle of Junin Day","PE",2038 +"2038-08-30","Rose of Lima Day","PE",2038 +"2038-10-08","Battle of Angamos Day","PE",2038 +"2038-11-01","All Saints' Day","PE",2038 +"2038-12-08","Immaculate Conception Day","PE",2038 +"2038-12-09","Battle of Ayacucho Day","PE",2038 +"2038-12-25","Christmas Day","PE",2038 +"2039-01-01","New Year's Day","PE",2039 +"2039-04-07","Maundy Thursday","PE",2039 +"2039-04-08","Good Friday","PE",2039 +"2039-04-10","Easter Sunday","PE",2039 +"2039-05-01","Labour Day","PE",2039 +"2039-06-29","Saint Peter and Saint Paul","PE",2039 +"2039-07-28","Independence Day","PE",2039 +"2039-07-29","Great Military Parade Day","PE",2039 +"2039-08-06","Battle of Junin Day","PE",2039 +"2039-08-30","Rose of Lima Day","PE",2039 +"2039-10-08","Battle of Angamos Day","PE",2039 +"2039-11-01","All Saints' Day","PE",2039 +"2039-12-08","Immaculate Conception Day","PE",2039 +"2039-12-09","Battle of Ayacucho Day","PE",2039 +"2039-12-25","Christmas Day","PE",2039 +"2040-01-01","New Year's Day","PE",2040 +"2040-03-29","Maundy Thursday","PE",2040 +"2040-03-30","Good Friday","PE",2040 +"2040-04-01","Easter Sunday","PE",2040 +"2040-05-01","Labour Day","PE",2040 +"2040-06-29","Saint Peter and Saint Paul","PE",2040 +"2040-07-28","Independence Day","PE",2040 +"2040-07-29","Great Military Parade Day","PE",2040 +"2040-08-06","Battle of Junin Day","PE",2040 +"2040-08-30","Rose of Lima Day","PE",2040 +"2040-10-08","Battle of Angamos Day","PE",2040 +"2040-11-01","All Saints' Day","PE",2040 +"2040-12-08","Immaculate Conception Day","PE",2040 +"2040-12-09","Battle of Ayacucho Day","PE",2040 +"2040-12-25","Christmas Day","PE",2040 +"2041-01-01","New Year's Day","PE",2041 +"2041-04-18","Maundy Thursday","PE",2041 +"2041-04-19","Good Friday","PE",2041 +"2041-04-21","Easter Sunday","PE",2041 +"2041-05-01","Labour Day","PE",2041 +"2041-06-29","Saint Peter and Saint Paul","PE",2041 +"2041-07-28","Independence Day","PE",2041 +"2041-07-29","Great Military Parade Day","PE",2041 +"2041-08-06","Battle of Junin Day","PE",2041 +"2041-08-30","Rose of Lima Day","PE",2041 +"2041-10-08","Battle of Angamos Day","PE",2041 +"2041-11-01","All Saints' Day","PE",2041 +"2041-12-08","Immaculate Conception Day","PE",2041 +"2041-12-09","Battle of Ayacucho Day","PE",2041 +"2041-12-25","Christmas Day","PE",2041 +"2042-01-01","New Year's Day","PE",2042 +"2042-04-03","Maundy Thursday","PE",2042 +"2042-04-04","Good Friday","PE",2042 +"2042-04-06","Easter Sunday","PE",2042 +"2042-05-01","Labour Day","PE",2042 +"2042-06-29","Saint Peter and Saint Paul","PE",2042 +"2042-07-28","Independence Day","PE",2042 +"2042-07-29","Great Military Parade Day","PE",2042 +"2042-08-06","Battle of Junin Day","PE",2042 +"2042-08-30","Rose of Lima Day","PE",2042 +"2042-10-08","Battle of Angamos Day","PE",2042 +"2042-11-01","All Saints' Day","PE",2042 +"2042-12-08","Immaculate Conception Day","PE",2042 +"2042-12-09","Battle of Ayacucho Day","PE",2042 +"2042-12-25","Christmas Day","PE",2042 +"2043-01-01","New Year's Day","PE",2043 +"2043-03-26","Maundy Thursday","PE",2043 +"2043-03-27","Good Friday","PE",2043 +"2043-03-29","Easter Sunday","PE",2043 +"2043-05-01","Labour Day","PE",2043 +"2043-06-29","Saint Peter and Saint Paul","PE",2043 +"2043-07-28","Independence Day","PE",2043 +"2043-07-29","Great Military Parade Day","PE",2043 +"2043-08-06","Battle of Junin Day","PE",2043 +"2043-08-30","Rose of Lima Day","PE",2043 +"2043-10-08","Battle of Angamos Day","PE",2043 +"2043-11-01","All Saints' Day","PE",2043 +"2043-12-08","Immaculate Conception Day","PE",2043 +"2043-12-09","Battle of Ayacucho Day","PE",2043 +"2043-12-25","Christmas Day","PE",2043 +"2044-01-01","New Year's Day","PE",2044 +"2044-04-14","Maundy Thursday","PE",2044 +"2044-04-15","Good Friday","PE",2044 +"2044-04-17","Easter Sunday","PE",2044 +"2044-05-01","Labour Day","PE",2044 +"2044-06-29","Saint Peter and Saint Paul","PE",2044 +"2044-07-28","Independence Day","PE",2044 +"2044-07-29","Great Military Parade Day","PE",2044 +"2044-08-06","Battle of Junin Day","PE",2044 +"2044-08-30","Rose of Lima Day","PE",2044 +"2044-10-08","Battle of Angamos Day","PE",2044 +"2044-11-01","All Saints' Day","PE",2044 +"2044-12-08","Immaculate Conception Day","PE",2044 +"2044-12-09","Battle of Ayacucho Day","PE",2044 +"2044-12-25","Christmas Day","PE",2044 +"1995-01-01","New Year's Day","PH",1995 +"1995-01-31","Chinese New Year","PH",1995 +"1995-02-25","EDSA Revolution Anniversary","PH",1995 +"1995-03-02","Eid'l Fitr* (*estimated)","PH",1995 +"1995-04-09","Day of Valor","PH",1995 +"1995-04-13","Maundy Thursday","PH",1995 +"1995-04-14","Good Friday","PH",1995 +"1995-04-15","Black Saturday","PH",1995 +"1995-05-01","Labour Day","PH",1995 +"1995-05-09","Eid'l Adha* (*estimated)","PH",1995 +"1995-06-12","Independence Day","PH",1995 +"1995-08-21","Ninoy Aquino Day","PH",1995 +"1995-08-28","National Heroes Day","PH",1995 +"1995-11-01","All Saints' Day","PH",1995 +"1995-11-30","Bonifacio Day","PH",1995 +"1995-12-08","Immaculate Conception Day","PH",1995 +"1995-12-25","Christmas Day","PH",1995 +"1995-12-30","Rizal Day","PH",1995 +"1995-12-31","New Year's Eve","PH",1995 +"1996-01-01","New Year's Day","PH",1996 +"1996-02-19","Chinese New Year","PH",1996 +"1996-02-19","Eid'l Fitr* (*estimated)","PH",1996 +"1996-02-25","EDSA Revolution Anniversary","PH",1996 +"1996-04-04","Maundy Thursday","PH",1996 +"1996-04-05","Good Friday","PH",1996 +"1996-04-06","Black Saturday","PH",1996 +"1996-04-09","Day of Valor","PH",1996 +"1996-04-27","Eid'l Adha* (*estimated)","PH",1996 +"1996-05-01","Labour Day","PH",1996 +"1996-06-12","Independence Day","PH",1996 +"1996-08-21","Ninoy Aquino Day","PH",1996 +"1996-08-26","National Heroes Day","PH",1996 +"1996-11-01","All Saints' Day","PH",1996 +"1996-11-30","Bonifacio Day","PH",1996 +"1996-12-08","Immaculate Conception Day","PH",1996 +"1996-12-25","Christmas Day","PH",1996 +"1996-12-30","Rizal Day","PH",1996 +"1996-12-31","New Year's Eve","PH",1996 +"1997-01-01","New Year's Day","PH",1997 +"1997-02-07","Chinese New Year","PH",1997 +"1997-02-08","Eid'l Fitr* (*estimated)","PH",1997 +"1997-02-25","EDSA Revolution Anniversary","PH",1997 +"1997-03-27","Maundy Thursday","PH",1997 +"1997-03-28","Good Friday","PH",1997 +"1997-03-29","Black Saturday","PH",1997 +"1997-04-09","Day of Valor","PH",1997 +"1997-04-17","Eid'l Adha* (*estimated)","PH",1997 +"1997-05-01","Labour Day","PH",1997 +"1997-06-12","Independence Day","PH",1997 +"1997-08-21","Ninoy Aquino Day","PH",1997 +"1997-08-25","National Heroes Day","PH",1997 +"1997-11-01","All Saints' Day","PH",1997 +"1997-11-30","Bonifacio Day","PH",1997 +"1997-12-08","Immaculate Conception Day","PH",1997 +"1997-12-25","Christmas Day","PH",1997 +"1997-12-30","Rizal Day","PH",1997 +"1997-12-31","New Year's Eve","PH",1997 +"1998-01-01","New Year's Day","PH",1998 +"1998-01-28","Chinese New Year","PH",1998 +"1998-01-29","Eid'l Fitr* (*estimated)","PH",1998 +"1998-02-25","EDSA Revolution Anniversary","PH",1998 +"1998-04-07","Eid'l Adha* (*estimated)","PH",1998 +"1998-04-09","Day of Valor","PH",1998 +"1998-04-09","Maundy Thursday","PH",1998 +"1998-04-10","Good Friday","PH",1998 +"1998-04-11","Black Saturday","PH",1998 +"1998-05-01","Labour Day","PH",1998 +"1998-06-12","Independence Day","PH",1998 +"1998-08-21","Ninoy Aquino Day","PH",1998 +"1998-08-31","National Heroes Day","PH",1998 +"1998-11-01","All Saints' Day","PH",1998 +"1998-11-30","Bonifacio Day","PH",1998 +"1998-12-08","Immaculate Conception Day","PH",1998 +"1998-12-25","Christmas Day","PH",1998 +"1998-12-30","Rizal Day","PH",1998 +"1998-12-31","New Year's Eve","PH",1998 +"1999-01-01","New Year's Day","PH",1999 +"1999-01-18","Eid'l Fitr* (*estimated)","PH",1999 +"1999-02-16","Chinese New Year","PH",1999 +"1999-02-25","EDSA Revolution Anniversary","PH",1999 +"1999-03-27","Eid'l Adha* (*estimated)","PH",1999 +"1999-04-01","Maundy Thursday","PH",1999 +"1999-04-02","Good Friday","PH",1999 +"1999-04-03","Black Saturday","PH",1999 +"1999-04-09","Day of Valor","PH",1999 +"1999-05-01","Labour Day","PH",1999 +"1999-06-12","Independence Day","PH",1999 +"1999-08-21","Ninoy Aquino Day","PH",1999 +"1999-08-30","National Heroes Day","PH",1999 +"1999-11-01","All Saints' Day","PH",1999 +"1999-11-30","Bonifacio Day","PH",1999 +"1999-12-08","Immaculate Conception Day","PH",1999 +"1999-12-25","Christmas Day","PH",1999 +"1999-12-30","Rizal Day","PH",1999 +"1999-12-31","New Year's Eve","PH",1999 +"2000-01-01","New Year's Day","PH",2000 +"2000-01-08","Eid'l Fitr* (*estimated)","PH",2000 +"2000-02-05","Chinese New Year","PH",2000 +"2000-02-25","EDSA Revolution Anniversary","PH",2000 +"2000-03-16","Eid'l Adha* (*estimated)","PH",2000 +"2000-04-09","Day of Valor","PH",2000 +"2000-04-20","Maundy Thursday","PH",2000 +"2000-04-21","Good Friday","PH",2000 +"2000-04-22","Black Saturday","PH",2000 +"2000-05-01","Labour Day","PH",2000 +"2000-06-12","Independence Day","PH",2000 +"2000-08-21","Ninoy Aquino Day","PH",2000 +"2000-08-28","National Heroes Day","PH",2000 +"2000-11-01","All Saints' Day","PH",2000 +"2000-11-30","Bonifacio Day","PH",2000 +"2000-12-08","Immaculate Conception Day","PH",2000 +"2000-12-25","Christmas Day","PH",2000 +"2000-12-27","Eid'l Fitr* (*estimated)","PH",2000 +"2000-12-30","Rizal Day","PH",2000 +"2000-12-31","New Year's Eve","PH",2000 +"2001-01-01","New Year's Day","PH",2001 +"2001-01-24","Chinese New Year","PH",2001 +"2001-02-25","EDSA Revolution Anniversary","PH",2001 +"2001-03-05","Eid'l Adha* (*estimated)","PH",2001 +"2001-04-09","Day of Valor","PH",2001 +"2001-04-12","Maundy Thursday","PH",2001 +"2001-04-13","Good Friday","PH",2001 +"2001-04-14","Black Saturday","PH",2001 +"2001-05-01","Labour Day","PH",2001 +"2001-06-12","Independence Day","PH",2001 +"2001-08-21","Ninoy Aquino Day","PH",2001 +"2001-08-27","National Heroes Day","PH",2001 +"2001-11-01","All Saints' Day","PH",2001 +"2001-11-30","Bonifacio Day","PH",2001 +"2001-12-08","Immaculate Conception Day","PH",2001 +"2001-12-16","Eid'l Fitr* (*estimated)","PH",2001 +"2001-12-25","Christmas Day","PH",2001 +"2001-12-30","Rizal Day","PH",2001 +"2001-12-31","New Year's Eve","PH",2001 +"2002-01-01","New Year's Day","PH",2002 +"2002-02-12","Chinese New Year","PH",2002 +"2002-02-22","Eid'l Adha* (*estimated)","PH",2002 +"2002-02-25","EDSA Revolution Anniversary","PH",2002 +"2002-03-28","Maundy Thursday","PH",2002 +"2002-03-29","Good Friday","PH",2002 +"2002-03-30","Black Saturday","PH",2002 +"2002-04-09","Day of Valor","PH",2002 +"2002-05-01","Labour Day","PH",2002 +"2002-06-12","Independence Day","PH",2002 +"2002-08-21","Ninoy Aquino Day","PH",2002 +"2002-08-26","National Heroes Day","PH",2002 +"2002-11-01","All Saints' Day","PH",2002 +"2002-11-30","Bonifacio Day","PH",2002 +"2002-12-05","Eid'l Fitr* (*estimated)","PH",2002 +"2002-12-08","Immaculate Conception Day","PH",2002 +"2002-12-25","Christmas Day","PH",2002 +"2002-12-30","Rizal Day","PH",2002 +"2002-12-31","New Year's Eve","PH",2002 +"2003-01-01","New Year's Day","PH",2003 +"2003-02-01","Chinese New Year","PH",2003 +"2003-02-11","Eid'l Adha* (*estimated)","PH",2003 +"2003-02-25","EDSA Revolution Anniversary","PH",2003 +"2003-04-09","Day of Valor","PH",2003 +"2003-04-17","Maundy Thursday","PH",2003 +"2003-04-18","Good Friday","PH",2003 +"2003-04-19","Black Saturday","PH",2003 +"2003-05-01","Labour Day","PH",2003 +"2003-06-12","Independence Day","PH",2003 +"2003-08-21","Ninoy Aquino Day","PH",2003 +"2003-08-25","National Heroes Day","PH",2003 +"2003-11-01","All Saints' Day","PH",2003 +"2003-11-25","Eid'l Fitr* (*estimated)","PH",2003 +"2003-11-30","Bonifacio Day","PH",2003 +"2003-12-08","Immaculate Conception Day","PH",2003 +"2003-12-25","Christmas Day","PH",2003 +"2003-12-30","Rizal Day","PH",2003 +"2003-12-31","New Year's Eve","PH",2003 +"2004-01-01","New Year's Day","PH",2004 +"2004-01-22","Chinese New Year","PH",2004 +"2004-02-01","Eid'l Adha* (*estimated)","PH",2004 +"2004-02-25","EDSA Revolution Anniversary","PH",2004 +"2004-04-08","Maundy Thursday","PH",2004 +"2004-04-09","Day of Valor","PH",2004 +"2004-04-09","Good Friday","PH",2004 +"2004-04-10","Black Saturday","PH",2004 +"2004-05-01","Labour Day","PH",2004 +"2004-06-12","Independence Day","PH",2004 +"2004-08-21","Ninoy Aquino Day","PH",2004 +"2004-08-30","National Heroes Day","PH",2004 +"2004-11-01","All Saints' Day","PH",2004 +"2004-11-14","Eid'l Fitr* (*estimated)","PH",2004 +"2004-11-30","Bonifacio Day","PH",2004 +"2004-12-08","Immaculate Conception Day","PH",2004 +"2004-12-25","Christmas Day","PH",2004 +"2004-12-30","Rizal Day","PH",2004 +"2004-12-31","New Year's Eve","PH",2004 +"2005-01-01","New Year's Day","PH",2005 +"2005-01-21","Eid'l Adha* (*estimated)","PH",2005 +"2005-02-09","Chinese New Year","PH",2005 +"2005-02-25","EDSA Revolution Anniversary","PH",2005 +"2005-03-24","Maundy Thursday","PH",2005 +"2005-03-25","Good Friday","PH",2005 +"2005-03-26","Black Saturday","PH",2005 +"2005-04-09","Day of Valor","PH",2005 +"2005-05-01","Labour Day","PH",2005 +"2005-06-12","Independence Day","PH",2005 +"2005-08-21","Ninoy Aquino Day","PH",2005 +"2005-08-29","National Heroes Day","PH",2005 +"2005-11-01","All Saints' Day","PH",2005 +"2005-11-03","Eid'l Fitr* (*estimated)","PH",2005 +"2005-11-30","Bonifacio Day","PH",2005 +"2005-12-08","Immaculate Conception Day","PH",2005 +"2005-12-25","Christmas Day","PH",2005 +"2005-12-30","Rizal Day","PH",2005 +"2005-12-31","New Year's Eve","PH",2005 +"2006-01-01","New Year's Day","PH",2006 +"2006-01-10","Eid'l Adha* (*estimated)","PH",2006 +"2006-01-29","Chinese New Year","PH",2006 +"2006-02-25","EDSA Revolution Anniversary","PH",2006 +"2006-04-09","Day of Valor","PH",2006 +"2006-04-13","Maundy Thursday","PH",2006 +"2006-04-14","Good Friday","PH",2006 +"2006-04-15","Black Saturday","PH",2006 +"2006-05-01","Labour Day","PH",2006 +"2006-06-12","Independence Day","PH",2006 +"2006-08-21","Ninoy Aquino Day","PH",2006 +"2006-08-28","National Heroes Day","PH",2006 +"2006-10-23","Eid'l Fitr* (*estimated)","PH",2006 +"2006-11-01","All Saints' Day","PH",2006 +"2006-11-30","Bonifacio Day","PH",2006 +"2006-12-08","Immaculate Conception Day","PH",2006 +"2006-12-25","Christmas Day","PH",2006 +"2006-12-30","Rizal Day","PH",2006 +"2006-12-31","Eid'l Adha* (*estimated)","PH",2006 +"2006-12-31","New Year's Eve","PH",2006 +"2007-01-01","New Year's Day","PH",2007 +"2007-02-18","Chinese New Year","PH",2007 +"2007-02-25","EDSA Revolution Anniversary","PH",2007 +"2007-04-05","Maundy Thursday","PH",2007 +"2007-04-06","Good Friday","PH",2007 +"2007-04-07","Black Saturday","PH",2007 +"2007-04-09","Day of Valor","PH",2007 +"2007-05-01","Labour Day","PH",2007 +"2007-06-12","Independence Day","PH",2007 +"2007-08-21","Ninoy Aquino Day","PH",2007 +"2007-08-27","National Heroes Day","PH",2007 +"2007-10-13","Eid'l Fitr* (*estimated)","PH",2007 +"2007-11-01","All Saints' Day","PH",2007 +"2007-11-30","Bonifacio Day","PH",2007 +"2007-12-08","Immaculate Conception Day","PH",2007 +"2007-12-20","Eid'l Adha* (*estimated)","PH",2007 +"2007-12-25","Christmas Day","PH",2007 +"2007-12-30","Rizal Day","PH",2007 +"2007-12-31","New Year's Eve","PH",2007 +"2008-01-01","New Year's Day","PH",2008 +"2008-02-07","Chinese New Year","PH",2008 +"2008-02-25","EDSA Revolution Anniversary","PH",2008 +"2008-03-20","Maundy Thursday","PH",2008 +"2008-03-21","Good Friday","PH",2008 +"2008-03-22","Black Saturday","PH",2008 +"2008-04-09","Day of Valor","PH",2008 +"2008-05-01","Labour Day","PH",2008 +"2008-06-12","Independence Day","PH",2008 +"2008-08-21","Ninoy Aquino Day","PH",2008 +"2008-08-25","National Heroes Day","PH",2008 +"2008-10-01","Eid'l Fitr* (*estimated)","PH",2008 +"2008-11-01","All Saints' Day","PH",2008 +"2008-11-30","Bonifacio Day","PH",2008 +"2008-12-08","Eid'l Adha* (*estimated)","PH",2008 +"2008-12-08","Immaculate Conception Day","PH",2008 +"2008-12-25","Christmas Day","PH",2008 +"2008-12-30","Rizal Day","PH",2008 +"2008-12-31","New Year's Eve","PH",2008 +"2009-01-01","New Year's Day","PH",2009 +"2009-01-26","Chinese New Year","PH",2009 +"2009-02-25","EDSA Revolution Anniversary","PH",2009 +"2009-04-09","Day of Valor","PH",2009 +"2009-04-09","Maundy Thursday","PH",2009 +"2009-04-10","Good Friday","PH",2009 +"2009-04-11","Black Saturday","PH",2009 +"2009-05-01","Labour Day","PH",2009 +"2009-06-12","Independence Day","PH",2009 +"2009-08-21","Ninoy Aquino Day","PH",2009 +"2009-08-31","National Heroes Day","PH",2009 +"2009-09-20","Eid'l Fitr* (*estimated)","PH",2009 +"2009-11-01","All Saints' Day","PH",2009 +"2009-11-27","Eid'l Adha* (*estimated)","PH",2009 +"2009-11-30","Bonifacio Day","PH",2009 +"2009-12-08","Immaculate Conception Day","PH",2009 +"2009-12-25","Christmas Day","PH",2009 +"2009-12-30","Rizal Day","PH",2009 +"2009-12-31","New Year's Eve","PH",2009 +"2010-01-01","New Year's Day","PH",2010 +"2010-02-14","Chinese New Year","PH",2010 +"2010-02-25","EDSA Revolution Anniversary","PH",2010 +"2010-04-01","Maundy Thursday","PH",2010 +"2010-04-02","Good Friday","PH",2010 +"2010-04-03","Black Saturday","PH",2010 +"2010-04-09","Day of Valor","PH",2010 +"2010-05-01","Labour Day","PH",2010 +"2010-06-12","Independence Day","PH",2010 +"2010-08-21","Ninoy Aquino Day","PH",2010 +"2010-08-30","National Heroes Day","PH",2010 +"2010-09-10","Eid'l Fitr* (*estimated)","PH",2010 +"2010-11-01","All Saints' Day","PH",2010 +"2010-11-16","Eid'l Adha* (*estimated)","PH",2010 +"2010-11-30","Bonifacio Day","PH",2010 +"2010-12-08","Immaculate Conception Day","PH",2010 +"2010-12-25","Christmas Day","PH",2010 +"2010-12-30","Rizal Day","PH",2010 +"2010-12-31","New Year's Eve","PH",2010 +"2011-01-01","New Year's Day","PH",2011 +"2011-02-03","Chinese New Year","PH",2011 +"2011-02-25","EDSA Revolution Anniversary","PH",2011 +"2011-04-09","Day of Valor","PH",2011 +"2011-04-21","Maundy Thursday","PH",2011 +"2011-04-22","Good Friday","PH",2011 +"2011-04-23","Black Saturday","PH",2011 +"2011-05-01","Labour Day","PH",2011 +"2011-06-12","Independence Day","PH",2011 +"2011-08-21","Ninoy Aquino Day","PH",2011 +"2011-08-29","National Heroes Day","PH",2011 +"2011-08-30","Eid'l Fitr* (*estimated)","PH",2011 +"2011-11-01","All Saints' Day","PH",2011 +"2011-11-06","Eid'l Adha* (*estimated)","PH",2011 +"2011-11-30","Bonifacio Day","PH",2011 +"2011-12-08","Immaculate Conception Day","PH",2011 +"2011-12-25","Christmas Day","PH",2011 +"2011-12-30","Rizal Day","PH",2011 +"2011-12-31","New Year's Eve","PH",2011 +"2012-01-01","New Year's Day","PH",2012 +"2012-01-23","Chinese New Year","PH",2012 +"2012-02-25","EDSA Revolution Anniversary","PH",2012 +"2012-04-05","Maundy Thursday","PH",2012 +"2012-04-06","Good Friday","PH",2012 +"2012-04-07","Black Saturday","PH",2012 +"2012-04-09","Day of Valor","PH",2012 +"2012-05-01","Labour Day","PH",2012 +"2012-06-12","Independence Day","PH",2012 +"2012-08-19","Eid'l Fitr* (*estimated)","PH",2012 +"2012-08-21","Ninoy Aquino Day","PH",2012 +"2012-08-27","National Heroes Day","PH",2012 +"2012-10-26","Eid'l Adha* (*estimated)","PH",2012 +"2012-11-01","All Saints' Day","PH",2012 +"2012-11-30","Bonifacio Day","PH",2012 +"2012-12-08","Immaculate Conception Day","PH",2012 +"2012-12-25","Christmas Day","PH",2012 +"2012-12-30","Rizal Day","PH",2012 +"2012-12-31","New Year's Eve","PH",2012 +"2013-01-01","New Year's Day","PH",2013 +"2013-02-10","Chinese New Year","PH",2013 +"2013-02-25","EDSA Revolution Anniversary","PH",2013 +"2013-03-28","Maundy Thursday","PH",2013 +"2013-03-29","Good Friday","PH",2013 +"2013-03-30","Black Saturday","PH",2013 +"2013-04-09","Day of Valor","PH",2013 +"2013-05-01","Labour Day","PH",2013 +"2013-06-12","Independence Day","PH",2013 +"2013-08-08","Eid'l Fitr* (*estimated)","PH",2013 +"2013-08-21","Ninoy Aquino Day","PH",2013 +"2013-08-26","National Heroes Day","PH",2013 +"2013-10-15","Eid'l Adha* (*estimated)","PH",2013 +"2013-11-01","All Saints' Day","PH",2013 +"2013-11-30","Bonifacio Day","PH",2013 +"2013-12-08","Immaculate Conception Day","PH",2013 +"2013-12-25","Christmas Day","PH",2013 +"2013-12-30","Rizal Day","PH",2013 +"2013-12-31","New Year's Eve","PH",2013 +"2014-01-01","New Year's Day","PH",2014 +"2014-01-31","Chinese New Year","PH",2014 +"2014-02-25","EDSA Revolution Anniversary","PH",2014 +"2014-04-09","Day of Valor","PH",2014 +"2014-04-17","Maundy Thursday","PH",2014 +"2014-04-18","Good Friday","PH",2014 +"2014-04-19","Black Saturday","PH",2014 +"2014-05-01","Labour Day","PH",2014 +"2014-06-12","Independence Day","PH",2014 +"2014-07-28","Eid'l Fitr* (*estimated)","PH",2014 +"2014-08-21","Ninoy Aquino Day","PH",2014 +"2014-08-25","National Heroes Day","PH",2014 +"2014-10-04","Eid'l Adha* (*estimated)","PH",2014 +"2014-11-01","All Saints' Day","PH",2014 +"2014-11-30","Bonifacio Day","PH",2014 +"2014-12-08","Immaculate Conception Day","PH",2014 +"2014-12-25","Christmas Day","PH",2014 +"2014-12-30","Rizal Day","PH",2014 +"2014-12-31","New Year's Eve","PH",2014 +"2015-01-01","New Year's Day","PH",2015 +"2015-02-19","Chinese New Year","PH",2015 +"2015-02-25","EDSA Revolution Anniversary","PH",2015 +"2015-04-02","Maundy Thursday","PH",2015 +"2015-04-03","Good Friday","PH",2015 +"2015-04-04","Black Saturday","PH",2015 +"2015-04-09","Day of Valor","PH",2015 +"2015-05-01","Labour Day","PH",2015 +"2015-06-12","Independence Day","PH",2015 +"2015-07-17","Eid'l Fitr* (*estimated)","PH",2015 +"2015-08-21","Ninoy Aquino Day","PH",2015 +"2015-08-31","National Heroes Day","PH",2015 +"2015-09-23","Eid'l Adha* (*estimated)","PH",2015 +"2015-11-01","All Saints' Day","PH",2015 +"2015-11-30","Bonifacio Day","PH",2015 +"2015-12-08","Immaculate Conception Day","PH",2015 +"2015-12-25","Christmas Day","PH",2015 +"2015-12-30","Rizal Day","PH",2015 +"2015-12-31","New Year's Eve","PH",2015 +"2016-01-01","New Year's Day","PH",2016 +"2016-02-08","Chinese New Year","PH",2016 +"2016-02-25","EDSA Revolution Anniversary","PH",2016 +"2016-03-24","Maundy Thursday","PH",2016 +"2016-03-25","Good Friday","PH",2016 +"2016-03-26","Black Saturday","PH",2016 +"2016-04-09","Day of Valor","PH",2016 +"2016-05-01","Labour Day","PH",2016 +"2016-06-12","Independence Day","PH",2016 +"2016-07-06","Eid'l Fitr* (*estimated)","PH",2016 +"2016-08-21","Ninoy Aquino Day","PH",2016 +"2016-08-29","National Heroes Day","PH",2016 +"2016-09-11","Eid'l Adha* (*estimated)","PH",2016 +"2016-11-01","All Saints' Day","PH",2016 +"2016-11-30","Bonifacio Day","PH",2016 +"2016-12-08","Immaculate Conception Day","PH",2016 +"2016-12-25","Christmas Day","PH",2016 +"2016-12-30","Rizal Day","PH",2016 +"2016-12-31","New Year's Eve","PH",2016 +"2017-01-01","New Year's Day","PH",2017 +"2017-01-28","Chinese New Year","PH",2017 +"2017-02-25","EDSA Revolution Anniversary","PH",2017 +"2017-04-09","Day of Valor","PH",2017 +"2017-04-13","Maundy Thursday","PH",2017 +"2017-04-14","Good Friday","PH",2017 +"2017-04-15","Black Saturday","PH",2017 +"2017-05-01","Labour Day","PH",2017 +"2017-06-12","Independence Day","PH",2017 +"2017-06-25","Eid'l Fitr* (*estimated)","PH",2017 +"2017-08-21","Ninoy Aquino Day","PH",2017 +"2017-08-28","National Heroes Day","PH",2017 +"2017-09-01","Eid'l Adha* (*estimated)","PH",2017 +"2017-11-01","All Saints' Day","PH",2017 +"2017-11-30","Bonifacio Day","PH",2017 +"2017-12-08","Immaculate Conception Day","PH",2017 +"2017-12-25","Christmas Day","PH",2017 +"2017-12-30","Rizal Day","PH",2017 +"2017-12-31","New Year's Eve","PH",2017 +"2018-01-01","New Year's Day","PH",2018 +"2018-02-16","Chinese New Year","PH",2018 +"2018-02-25","EDSA Revolution Anniversary","PH",2018 +"2018-03-29","Maundy Thursday","PH",2018 +"2018-03-30","Good Friday","PH",2018 +"2018-03-31","Black Saturday","PH",2018 +"2018-04-09","Day of Valor","PH",2018 +"2018-05-01","Labour Day","PH",2018 +"2018-06-12","Independence Day","PH",2018 +"2018-06-15","Eid'l Fitr* (*estimated)","PH",2018 +"2018-08-21","Eid'l Adha* (*estimated)","PH",2018 +"2018-08-21","Ninoy Aquino Day","PH",2018 +"2018-08-27","National Heroes Day","PH",2018 +"2018-11-01","All Saints' Day","PH",2018 +"2018-11-30","Bonifacio Day","PH",2018 +"2018-12-08","Immaculate Conception Day","PH",2018 +"2018-12-25","Christmas Day","PH",2018 +"2018-12-30","Rizal Day","PH",2018 +"2018-12-31","New Year's Eve","PH",2018 +"2019-01-01","New Year's Day","PH",2019 +"2019-02-05","Chinese New Year","PH",2019 +"2019-02-25","EDSA Revolution Anniversary","PH",2019 +"2019-04-09","Day of Valor","PH",2019 +"2019-04-18","Maundy Thursday","PH",2019 +"2019-04-19","Good Friday","PH",2019 +"2019-04-20","Black Saturday","PH",2019 +"2019-05-01","Labour Day","PH",2019 +"2019-06-04","Eid'l Fitr* (*estimated)","PH",2019 +"2019-06-12","Independence Day","PH",2019 +"2019-08-11","Eid'l Adha* (*estimated)","PH",2019 +"2019-08-21","Ninoy Aquino Day","PH",2019 +"2019-08-26","National Heroes Day","PH",2019 +"2019-11-01","All Saints' Day","PH",2019 +"2019-11-30","Bonifacio Day","PH",2019 +"2019-12-08","Immaculate Conception Day","PH",2019 +"2019-12-25","Christmas Day","PH",2019 +"2019-12-30","Rizal Day","PH",2019 +"2019-12-31","New Year's Eve","PH",2019 +"2020-01-01","New Year's Day","PH",2020 +"2020-01-25","Chinese New Year","PH",2020 +"2020-02-25","EDSA Revolution Anniversary","PH",2020 +"2020-04-09","Day of Valor","PH",2020 +"2020-04-09","Maundy Thursday","PH",2020 +"2020-04-10","Good Friday","PH",2020 +"2020-04-11","Black Saturday","PH",2020 +"2020-05-01","Labour Day","PH",2020 +"2020-05-24","Eid'l Fitr* (*estimated)","PH",2020 +"2020-06-12","Independence Day","PH",2020 +"2020-07-31","Eid'l Adha* (*estimated)","PH",2020 +"2020-08-21","Ninoy Aquino Day","PH",2020 +"2020-08-31","National Heroes Day","PH",2020 +"2020-11-01","All Saints' Day","PH",2020 +"2020-11-30","Bonifacio Day","PH",2020 +"2020-12-08","Immaculate Conception Day","PH",2020 +"2020-12-25","Christmas Day","PH",2020 +"2020-12-30","Rizal Day","PH",2020 +"2020-12-31","New Year's Eve","PH",2020 +"2021-01-01","New Year's Day","PH",2021 +"2021-02-12","Chinese New Year","PH",2021 +"2021-02-25","EDSA Revolution Anniversary","PH",2021 +"2021-04-01","Maundy Thursday","PH",2021 +"2021-04-02","Good Friday","PH",2021 +"2021-04-03","Black Saturday","PH",2021 +"2021-04-09","Day of Valor","PH",2021 +"2021-05-01","Labour Day","PH",2021 +"2021-05-13","Eid'l Fitr* (*estimated)","PH",2021 +"2021-06-12","Independence Day","PH",2021 +"2021-07-20","Eid'l Adha* (*estimated)","PH",2021 +"2021-08-21","Ninoy Aquino Day","PH",2021 +"2021-08-30","National Heroes Day","PH",2021 +"2021-11-01","All Saints' Day","PH",2021 +"2021-11-30","Bonifacio Day","PH",2021 +"2021-12-08","Immaculate Conception Day","PH",2021 +"2021-12-25","Christmas Day","PH",2021 +"2021-12-30","Rizal Day","PH",2021 +"2021-12-31","New Year's Eve","PH",2021 +"2022-01-01","New Year's Day","PH",2022 +"2022-02-01","Chinese New Year","PH",2022 +"2022-02-25","EDSA Revolution Anniversary","PH",2022 +"2022-04-09","Day of Valor","PH",2022 +"2022-04-14","Maundy Thursday","PH",2022 +"2022-04-15","Good Friday","PH",2022 +"2022-04-16","Black Saturday","PH",2022 +"2022-05-01","Labour Day","PH",2022 +"2022-05-02","Eid'l Fitr* (*estimated)","PH",2022 +"2022-06-12","Independence Day","PH",2022 +"2022-07-09","Eid'l Adha* (*estimated)","PH",2022 +"2022-08-21","Ninoy Aquino Day","PH",2022 +"2022-08-29","National Heroes Day","PH",2022 +"2022-11-01","All Saints' Day","PH",2022 +"2022-11-30","Bonifacio Day","PH",2022 +"2022-12-08","Immaculate Conception Day","PH",2022 +"2022-12-25","Christmas Day","PH",2022 +"2022-12-30","Rizal Day","PH",2022 +"2022-12-31","New Year's Eve","PH",2022 +"2023-01-01","New Year's Day","PH",2023 +"2023-01-22","Chinese New Year","PH",2023 +"2023-02-25","EDSA Revolution Anniversary","PH",2023 +"2023-04-06","Maundy Thursday","PH",2023 +"2023-04-07","Good Friday","PH",2023 +"2023-04-08","Black Saturday","PH",2023 +"2023-04-09","Day of Valor","PH",2023 +"2023-04-21","Eid'l Fitr* (*estimated)","PH",2023 +"2023-05-01","Labour Day","PH",2023 +"2023-06-12","Independence Day","PH",2023 +"2023-06-28","Eid'l Adha* (*estimated)","PH",2023 +"2023-08-21","Ninoy Aquino Day","PH",2023 +"2023-08-28","National Heroes Day","PH",2023 +"2023-11-01","All Saints' Day","PH",2023 +"2023-11-30","Bonifacio Day","PH",2023 +"2023-12-08","Immaculate Conception Day","PH",2023 +"2023-12-25","Christmas Day","PH",2023 +"2023-12-30","Rizal Day","PH",2023 +"2023-12-31","New Year's Eve","PH",2023 +"2024-01-01","New Year's Day","PH",2024 +"2024-02-10","Chinese New Year","PH",2024 +"2024-02-25","EDSA Revolution Anniversary","PH",2024 +"2024-03-28","Maundy Thursday","PH",2024 +"2024-03-29","Good Friday","PH",2024 +"2024-03-30","Black Saturday","PH",2024 +"2024-04-09","Day of Valor","PH",2024 +"2024-04-10","Eid'l Fitr* (*estimated)","PH",2024 +"2024-05-01","Labour Day","PH",2024 +"2024-06-12","Independence Day","PH",2024 +"2024-06-16","Eid'l Adha* (*estimated)","PH",2024 +"2024-08-21","Ninoy Aquino Day","PH",2024 +"2024-08-26","National Heroes Day","PH",2024 +"2024-11-01","All Saints' Day","PH",2024 +"2024-11-30","Bonifacio Day","PH",2024 +"2024-12-08","Immaculate Conception Day","PH",2024 +"2024-12-25","Christmas Day","PH",2024 +"2024-12-30","Rizal Day","PH",2024 +"2024-12-31","New Year's Eve","PH",2024 +"2025-01-01","New Year's Day","PH",2025 +"2025-01-29","Chinese New Year","PH",2025 +"2025-02-25","EDSA Revolution Anniversary","PH",2025 +"2025-03-30","Eid'l Fitr* (*estimated)","PH",2025 +"2025-04-09","Day of Valor","PH",2025 +"2025-04-17","Maundy Thursday","PH",2025 +"2025-04-18","Good Friday","PH",2025 +"2025-04-19","Black Saturday","PH",2025 +"2025-05-01","Labour Day","PH",2025 +"2025-06-06","Eid'l Adha* (*estimated)","PH",2025 +"2025-06-12","Independence Day","PH",2025 +"2025-08-21","Ninoy Aquino Day","PH",2025 +"2025-08-25","National Heroes Day","PH",2025 +"2025-11-01","All Saints' Day","PH",2025 +"2025-11-30","Bonifacio Day","PH",2025 +"2025-12-08","Immaculate Conception Day","PH",2025 +"2025-12-25","Christmas Day","PH",2025 +"2025-12-30","Rizal Day","PH",2025 +"2025-12-31","New Year's Eve","PH",2025 +"2026-01-01","New Year's Day","PH",2026 +"2026-02-17","Chinese New Year","PH",2026 +"2026-02-25","EDSA Revolution Anniversary","PH",2026 +"2026-03-20","Eid'l Fitr* (*estimated)","PH",2026 +"2026-04-02","Maundy Thursday","PH",2026 +"2026-04-03","Good Friday","PH",2026 +"2026-04-04","Black Saturday","PH",2026 +"2026-04-09","Day of Valor","PH",2026 +"2026-05-01","Labour Day","PH",2026 +"2026-05-27","Eid'l Adha* (*estimated)","PH",2026 +"2026-06-12","Independence Day","PH",2026 +"2026-08-21","Ninoy Aquino Day","PH",2026 +"2026-08-31","National Heroes Day","PH",2026 +"2026-11-01","All Saints' Day","PH",2026 +"2026-11-30","Bonifacio Day","PH",2026 +"2026-12-08","Immaculate Conception Day","PH",2026 +"2026-12-25","Christmas Day","PH",2026 +"2026-12-30","Rizal Day","PH",2026 +"2026-12-31","New Year's Eve","PH",2026 +"2027-01-01","New Year's Day","PH",2027 +"2027-02-06","Chinese New Year","PH",2027 +"2027-02-25","EDSA Revolution Anniversary","PH",2027 +"2027-03-09","Eid'l Fitr* (*estimated)","PH",2027 +"2027-03-25","Maundy Thursday","PH",2027 +"2027-03-26","Good Friday","PH",2027 +"2027-03-27","Black Saturday","PH",2027 +"2027-04-09","Day of Valor","PH",2027 +"2027-05-01","Labour Day","PH",2027 +"2027-05-16","Eid'l Adha* (*estimated)","PH",2027 +"2027-06-12","Independence Day","PH",2027 +"2027-08-21","Ninoy Aquino Day","PH",2027 +"2027-08-30","National Heroes Day","PH",2027 +"2027-11-01","All Saints' Day","PH",2027 +"2027-11-30","Bonifacio Day","PH",2027 +"2027-12-08","Immaculate Conception Day","PH",2027 +"2027-12-25","Christmas Day","PH",2027 +"2027-12-30","Rizal Day","PH",2027 +"2027-12-31","New Year's Eve","PH",2027 +"2028-01-01","New Year's Day","PH",2028 +"2028-01-26","Chinese New Year","PH",2028 +"2028-02-25","EDSA Revolution Anniversary","PH",2028 +"2028-02-26","Eid'l Fitr* (*estimated)","PH",2028 +"2028-04-09","Day of Valor","PH",2028 +"2028-04-13","Maundy Thursday","PH",2028 +"2028-04-14","Good Friday","PH",2028 +"2028-04-15","Black Saturday","PH",2028 +"2028-05-01","Labour Day","PH",2028 +"2028-05-05","Eid'l Adha* (*estimated)","PH",2028 +"2028-06-12","Independence Day","PH",2028 +"2028-08-21","Ninoy Aquino Day","PH",2028 +"2028-08-28","National Heroes Day","PH",2028 +"2028-11-01","All Saints' Day","PH",2028 +"2028-11-30","Bonifacio Day","PH",2028 +"2028-12-08","Immaculate Conception Day","PH",2028 +"2028-12-25","Christmas Day","PH",2028 +"2028-12-30","Rizal Day","PH",2028 +"2028-12-31","New Year's Eve","PH",2028 +"2029-01-01","New Year's Day","PH",2029 +"2029-02-13","Chinese New Year","PH",2029 +"2029-02-14","Eid'l Fitr* (*estimated)","PH",2029 +"2029-02-25","EDSA Revolution Anniversary","PH",2029 +"2029-03-29","Maundy Thursday","PH",2029 +"2029-03-30","Good Friday","PH",2029 +"2029-03-31","Black Saturday","PH",2029 +"2029-04-09","Day of Valor","PH",2029 +"2029-04-24","Eid'l Adha* (*estimated)","PH",2029 +"2029-05-01","Labour Day","PH",2029 +"2029-06-12","Independence Day","PH",2029 +"2029-08-21","Ninoy Aquino Day","PH",2029 +"2029-08-27","National Heroes Day","PH",2029 +"2029-11-01","All Saints' Day","PH",2029 +"2029-11-30","Bonifacio Day","PH",2029 +"2029-12-08","Immaculate Conception Day","PH",2029 +"2029-12-25","Christmas Day","PH",2029 +"2029-12-30","Rizal Day","PH",2029 +"2029-12-31","New Year's Eve","PH",2029 +"2030-01-01","New Year's Day","PH",2030 +"2030-02-03","Chinese New Year","PH",2030 +"2030-02-04","Eid'l Fitr* (*estimated)","PH",2030 +"2030-02-25","EDSA Revolution Anniversary","PH",2030 +"2030-04-09","Day of Valor","PH",2030 +"2030-04-13","Eid'l Adha* (*estimated)","PH",2030 +"2030-04-18","Maundy Thursday","PH",2030 +"2030-04-19","Good Friday","PH",2030 +"2030-04-20","Black Saturday","PH",2030 +"2030-05-01","Labour Day","PH",2030 +"2030-06-12","Independence Day","PH",2030 +"2030-08-21","Ninoy Aquino Day","PH",2030 +"2030-08-26","National Heroes Day","PH",2030 +"2030-11-01","All Saints' Day","PH",2030 +"2030-11-30","Bonifacio Day","PH",2030 +"2030-12-08","Immaculate Conception Day","PH",2030 +"2030-12-25","Christmas Day","PH",2030 +"2030-12-30","Rizal Day","PH",2030 +"2030-12-31","New Year's Eve","PH",2030 +"2031-01-01","New Year's Day","PH",2031 +"2031-01-23","Chinese New Year","PH",2031 +"2031-01-24","Eid'l Fitr* (*estimated)","PH",2031 +"2031-02-25","EDSA Revolution Anniversary","PH",2031 +"2031-04-02","Eid'l Adha* (*estimated)","PH",2031 +"2031-04-09","Day of Valor","PH",2031 +"2031-04-10","Maundy Thursday","PH",2031 +"2031-04-11","Good Friday","PH",2031 +"2031-04-12","Black Saturday","PH",2031 +"2031-05-01","Labour Day","PH",2031 +"2031-06-12","Independence Day","PH",2031 +"2031-08-21","Ninoy Aquino Day","PH",2031 +"2031-08-25","National Heroes Day","PH",2031 +"2031-11-01","All Saints' Day","PH",2031 +"2031-11-30","Bonifacio Day","PH",2031 +"2031-12-08","Immaculate Conception Day","PH",2031 +"2031-12-25","Christmas Day","PH",2031 +"2031-12-30","Rizal Day","PH",2031 +"2031-12-31","New Year's Eve","PH",2031 +"2032-01-01","New Year's Day","PH",2032 +"2032-01-14","Eid'l Fitr* (*estimated)","PH",2032 +"2032-02-11","Chinese New Year","PH",2032 +"2032-02-25","EDSA Revolution Anniversary","PH",2032 +"2032-03-22","Eid'l Adha* (*estimated)","PH",2032 +"2032-03-25","Maundy Thursday","PH",2032 +"2032-03-26","Good Friday","PH",2032 +"2032-03-27","Black Saturday","PH",2032 +"2032-04-09","Day of Valor","PH",2032 +"2032-05-01","Labour Day","PH",2032 +"2032-06-12","Independence Day","PH",2032 +"2032-08-21","Ninoy Aquino Day","PH",2032 +"2032-08-30","National Heroes Day","PH",2032 +"2032-11-01","All Saints' Day","PH",2032 +"2032-11-30","Bonifacio Day","PH",2032 +"2032-12-08","Immaculate Conception Day","PH",2032 +"2032-12-25","Christmas Day","PH",2032 +"2032-12-30","Rizal Day","PH",2032 +"2032-12-31","New Year's Eve","PH",2032 +"2033-01-01","New Year's Day","PH",2033 +"2033-01-02","Eid'l Fitr* (*estimated)","PH",2033 +"2033-01-31","Chinese New Year","PH",2033 +"2033-02-25","EDSA Revolution Anniversary","PH",2033 +"2033-03-11","Eid'l Adha* (*estimated)","PH",2033 +"2033-04-09","Day of Valor","PH",2033 +"2033-04-14","Maundy Thursday","PH",2033 +"2033-04-15","Good Friday","PH",2033 +"2033-04-16","Black Saturday","PH",2033 +"2033-05-01","Labour Day","PH",2033 +"2033-06-12","Independence Day","PH",2033 +"2033-08-21","Ninoy Aquino Day","PH",2033 +"2033-08-29","National Heroes Day","PH",2033 +"2033-11-01","All Saints' Day","PH",2033 +"2033-11-30","Bonifacio Day","PH",2033 +"2033-12-08","Immaculate Conception Day","PH",2033 +"2033-12-23","Eid'l Fitr* (*estimated)","PH",2033 +"2033-12-25","Christmas Day","PH",2033 +"2033-12-30","Rizal Day","PH",2033 +"2033-12-31","New Year's Eve","PH",2033 +"2034-01-01","New Year's Day","PH",2034 +"2034-02-19","Chinese New Year","PH",2034 +"2034-02-25","EDSA Revolution Anniversary","PH",2034 +"2034-03-01","Eid'l Adha* (*estimated)","PH",2034 +"2034-04-06","Maundy Thursday","PH",2034 +"2034-04-07","Good Friday","PH",2034 +"2034-04-08","Black Saturday","PH",2034 +"2034-04-09","Day of Valor","PH",2034 +"2034-05-01","Labour Day","PH",2034 +"2034-06-12","Independence Day","PH",2034 +"2034-08-21","Ninoy Aquino Day","PH",2034 +"2034-08-28","National Heroes Day","PH",2034 +"2034-11-01","All Saints' Day","PH",2034 +"2034-11-30","Bonifacio Day","PH",2034 +"2034-12-08","Immaculate Conception Day","PH",2034 +"2034-12-12","Eid'l Fitr* (*estimated)","PH",2034 +"2034-12-25","Christmas Day","PH",2034 +"2034-12-30","Rizal Day","PH",2034 +"2034-12-31","New Year's Eve","PH",2034 +"2035-01-01","New Year's Day","PH",2035 +"2035-02-08","Chinese New Year","PH",2035 +"2035-02-18","Eid'l Adha* (*estimated)","PH",2035 +"2035-02-25","EDSA Revolution Anniversary","PH",2035 +"2035-03-22","Maundy Thursday","PH",2035 +"2035-03-23","Good Friday","PH",2035 +"2035-03-24","Black Saturday","PH",2035 +"2035-04-09","Day of Valor","PH",2035 +"2035-05-01","Labour Day","PH",2035 +"2035-06-12","Independence Day","PH",2035 +"2035-08-21","Ninoy Aquino Day","PH",2035 +"2035-08-27","National Heroes Day","PH",2035 +"2035-11-01","All Saints' Day","PH",2035 +"2035-11-30","Bonifacio Day","PH",2035 +"2035-12-01","Eid'l Fitr* (*estimated)","PH",2035 +"2035-12-08","Immaculate Conception Day","PH",2035 +"2035-12-25","Christmas Day","PH",2035 +"2035-12-30","Rizal Day","PH",2035 +"2035-12-31","New Year's Eve","PH",2035 +"2036-01-01","New Year's Day","PH",2036 +"2036-01-28","Chinese New Year","PH",2036 +"2036-02-07","Eid'l Adha* (*estimated)","PH",2036 +"2036-02-25","EDSA Revolution Anniversary","PH",2036 +"2036-04-09","Day of Valor","PH",2036 +"2036-04-10","Maundy Thursday","PH",2036 +"2036-04-11","Good Friday","PH",2036 +"2036-04-12","Black Saturday","PH",2036 +"2036-05-01","Labour Day","PH",2036 +"2036-06-12","Independence Day","PH",2036 +"2036-08-21","Ninoy Aquino Day","PH",2036 +"2036-08-25","National Heroes Day","PH",2036 +"2036-11-01","All Saints' Day","PH",2036 +"2036-11-19","Eid'l Fitr* (*estimated)","PH",2036 +"2036-11-30","Bonifacio Day","PH",2036 +"2036-12-08","Immaculate Conception Day","PH",2036 +"2036-12-25","Christmas Day","PH",2036 +"2036-12-30","Rizal Day","PH",2036 +"2036-12-31","New Year's Eve","PH",2036 +"2037-01-01","New Year's Day","PH",2037 +"2037-01-26","Eid'l Adha* (*estimated)","PH",2037 +"2037-02-15","Chinese New Year","PH",2037 +"2037-02-25","EDSA Revolution Anniversary","PH",2037 +"2037-04-02","Maundy Thursday","PH",2037 +"2037-04-03","Good Friday","PH",2037 +"2037-04-04","Black Saturday","PH",2037 +"2037-04-09","Day of Valor","PH",2037 +"2037-05-01","Labour Day","PH",2037 +"2037-06-12","Independence Day","PH",2037 +"2037-08-21","Ninoy Aquino Day","PH",2037 +"2037-08-31","National Heroes Day","PH",2037 +"2037-11-01","All Saints' Day","PH",2037 +"2037-11-08","Eid'l Fitr* (*estimated)","PH",2037 +"2037-11-30","Bonifacio Day","PH",2037 +"2037-12-08","Immaculate Conception Day","PH",2037 +"2037-12-25","Christmas Day","PH",2037 +"2037-12-30","Rizal Day","PH",2037 +"2037-12-31","New Year's Eve","PH",2037 +"2038-01-01","New Year's Day","PH",2038 +"2038-01-16","Eid'l Adha* (*estimated)","PH",2038 +"2038-02-04","Chinese New Year","PH",2038 +"2038-02-25","EDSA Revolution Anniversary","PH",2038 +"2038-04-09","Day of Valor","PH",2038 +"2038-04-22","Maundy Thursday","PH",2038 +"2038-04-23","Good Friday","PH",2038 +"2038-04-24","Black Saturday","PH",2038 +"2038-05-01","Labour Day","PH",2038 +"2038-06-12","Independence Day","PH",2038 +"2038-08-21","Ninoy Aquino Day","PH",2038 +"2038-08-30","National Heroes Day","PH",2038 +"2038-10-29","Eid'l Fitr* (*estimated)","PH",2038 +"2038-11-01","All Saints' Day","PH",2038 +"2038-11-30","Bonifacio Day","PH",2038 +"2038-12-08","Immaculate Conception Day","PH",2038 +"2038-12-25","Christmas Day","PH",2038 +"2038-12-30","Rizal Day","PH",2038 +"2038-12-31","New Year's Eve","PH",2038 +"2039-01-01","New Year's Day","PH",2039 +"2039-01-05","Eid'l Adha* (*estimated)","PH",2039 +"2039-01-24","Chinese New Year","PH",2039 +"2039-02-25","EDSA Revolution Anniversary","PH",2039 +"2039-04-07","Maundy Thursday","PH",2039 +"2039-04-08","Good Friday","PH",2039 +"2039-04-09","Black Saturday","PH",2039 +"2039-04-09","Day of Valor","PH",2039 +"2039-05-01","Labour Day","PH",2039 +"2039-06-12","Independence Day","PH",2039 +"2039-08-21","Ninoy Aquino Day","PH",2039 +"2039-08-29","National Heroes Day","PH",2039 +"2039-10-19","Eid'l Fitr* (*estimated)","PH",2039 +"2039-11-01","All Saints' Day","PH",2039 +"2039-11-30","Bonifacio Day","PH",2039 +"2039-12-08","Immaculate Conception Day","PH",2039 +"2039-12-25","Christmas Day","PH",2039 +"2039-12-26","Eid'l Adha* (*estimated)","PH",2039 +"2039-12-30","Rizal Day","PH",2039 +"2039-12-31","New Year's Eve","PH",2039 +"2040-01-01","New Year's Day","PH",2040 +"2040-02-12","Chinese New Year","PH",2040 +"2040-02-25","EDSA Revolution Anniversary","PH",2040 +"2040-03-29","Maundy Thursday","PH",2040 +"2040-03-30","Good Friday","PH",2040 +"2040-03-31","Black Saturday","PH",2040 +"2040-04-09","Day of Valor","PH",2040 +"2040-05-01","Labour Day","PH",2040 +"2040-06-12","Independence Day","PH",2040 +"2040-08-21","Ninoy Aquino Day","PH",2040 +"2040-08-27","National Heroes Day","PH",2040 +"2040-10-07","Eid'l Fitr* (*estimated)","PH",2040 +"2040-11-01","All Saints' Day","PH",2040 +"2040-11-30","Bonifacio Day","PH",2040 +"2040-12-08","Immaculate Conception Day","PH",2040 +"2040-12-14","Eid'l Adha* (*estimated)","PH",2040 +"2040-12-25","Christmas Day","PH",2040 +"2040-12-30","Rizal Day","PH",2040 +"2040-12-31","New Year's Eve","PH",2040 +"2041-01-01","New Year's Day","PH",2041 +"2041-02-01","Chinese New Year","PH",2041 +"2041-02-25","EDSA Revolution Anniversary","PH",2041 +"2041-04-09","Day of Valor","PH",2041 +"2041-04-18","Maundy Thursday","PH",2041 +"2041-04-19","Good Friday","PH",2041 +"2041-04-20","Black Saturday","PH",2041 +"2041-05-01","Labour Day","PH",2041 +"2041-06-12","Independence Day","PH",2041 +"2041-08-21","Ninoy Aquino Day","PH",2041 +"2041-08-26","National Heroes Day","PH",2041 +"2041-09-26","Eid'l Fitr* (*estimated)","PH",2041 +"2041-11-01","All Saints' Day","PH",2041 +"2041-11-30","Bonifacio Day","PH",2041 +"2041-12-04","Eid'l Adha* (*estimated)","PH",2041 +"2041-12-08","Immaculate Conception Day","PH",2041 +"2041-12-25","Christmas Day","PH",2041 +"2041-12-30","Rizal Day","PH",2041 +"2041-12-31","New Year's Eve","PH",2041 +"2042-01-01","New Year's Day","PH",2042 +"2042-01-22","Chinese New Year","PH",2042 +"2042-02-25","EDSA Revolution Anniversary","PH",2042 +"2042-04-03","Maundy Thursday","PH",2042 +"2042-04-04","Good Friday","PH",2042 +"2042-04-05","Black Saturday","PH",2042 +"2042-04-09","Day of Valor","PH",2042 +"2042-05-01","Labour Day","PH",2042 +"2042-06-12","Independence Day","PH",2042 +"2042-08-21","Ninoy Aquino Day","PH",2042 +"2042-08-25","National Heroes Day","PH",2042 +"2042-09-15","Eid'l Fitr* (*estimated)","PH",2042 +"2042-11-01","All Saints' Day","PH",2042 +"2042-11-23","Eid'l Adha* (*estimated)","PH",2042 +"2042-11-30","Bonifacio Day","PH",2042 +"2042-12-08","Immaculate Conception Day","PH",2042 +"2042-12-25","Christmas Day","PH",2042 +"2042-12-30","Rizal Day","PH",2042 +"2042-12-31","New Year's Eve","PH",2042 +"2043-01-01","New Year's Day","PH",2043 +"2043-02-10","Chinese New Year","PH",2043 +"2043-02-25","EDSA Revolution Anniversary","PH",2043 +"2043-03-26","Maundy Thursday","PH",2043 +"2043-03-27","Good Friday","PH",2043 +"2043-03-28","Black Saturday","PH",2043 +"2043-04-09","Day of Valor","PH",2043 +"2043-05-01","Labour Day","PH",2043 +"2043-06-12","Independence Day","PH",2043 +"2043-08-21","Ninoy Aquino Day","PH",2043 +"2043-08-31","National Heroes Day","PH",2043 +"2043-09-04","Eid'l Fitr* (*estimated)","PH",2043 +"2043-11-01","All Saints' Day","PH",2043 +"2043-11-12","Eid'l Adha* (*estimated)","PH",2043 +"2043-11-30","Bonifacio Day","PH",2043 +"2043-12-08","Immaculate Conception Day","PH",2043 +"2043-12-25","Christmas Day","PH",2043 +"2043-12-30","Rizal Day","PH",2043 +"2043-12-31","New Year's Eve","PH",2043 +"2044-01-01","New Year's Day","PH",2044 +"2044-01-30","Chinese New Year","PH",2044 +"2044-02-25","EDSA Revolution Anniversary","PH",2044 +"2044-04-09","Day of Valor","PH",2044 +"2044-04-14","Maundy Thursday","PH",2044 +"2044-04-15","Good Friday","PH",2044 +"2044-04-16","Black Saturday","PH",2044 +"2044-05-01","Labour Day","PH",2044 +"2044-06-12","Independence Day","PH",2044 +"2044-08-21","Ninoy Aquino Day","PH",2044 +"2044-08-24","Eid'l Fitr* (*estimated)","PH",2044 +"2044-08-29","National Heroes Day","PH",2044 +"2044-10-31","Eid'l Adha* (*estimated)","PH",2044 +"2044-11-01","All Saints' Day","PH",2044 +"2044-11-30","Bonifacio Day","PH",2044 +"2044-12-08","Immaculate Conception Day","PH",2044 +"2044-12-25","Christmas Day","PH",2044 +"2044-12-30","Rizal Day","PH",2044 +"2044-12-31","New Year's Eve","PH",2044 +"1995-02-05","Kashmir Solidarity Day","PK",1995 +"1995-03-02","Eid-ul-Fitr* (*estimated)","PK",1995 +"1995-03-03","Eid-ul-Fitr* (*estimated)","PK",1995 +"1995-03-04","Eid-ul-Fitr* (*estimated)","PK",1995 +"1995-03-23","Pakistan Day","PK",1995 +"1995-05-01","Labour Day","PK",1995 +"1995-05-09","Eid-ul-Adha* (*estimated)","PK",1995 +"1995-05-10","Eid-ul-Adha* (*estimated)","PK",1995 +"1995-05-11","Eid-ul-Adha* (*estimated)","PK",1995 +"1995-06-07","Ashura* (*estimated)","PK",1995 +"1995-06-08","Ashura* (*estimated)","PK",1995 +"1995-08-08","Eid Milad-un-Nabi* (*estimated)","PK",1995 +"1995-08-14","Independence Day","PK",1995 +"1995-11-09","Iqbal Day","PK",1995 +"1995-12-25","Quaid-e-Azam Day","PK",1995 +"1996-02-05","Kashmir Solidarity Day","PK",1996 +"1996-02-19","Eid-ul-Fitr* (*estimated)","PK",1996 +"1996-02-20","Eid-ul-Fitr* (*estimated)","PK",1996 +"1996-02-21","Eid-ul-Fitr* (*estimated)","PK",1996 +"1996-03-23","Pakistan Day","PK",1996 +"1996-04-27","Eid-ul-Adha* (*estimated)","PK",1996 +"1996-04-28","Eid-ul-Adha* (*estimated)","PK",1996 +"1996-04-29","Eid-ul-Adha* (*estimated)","PK",1996 +"1996-05-01","Labour Day","PK",1996 +"1996-05-26","Ashura* (*estimated)","PK",1996 +"1996-05-27","Ashura* (*estimated)","PK",1996 +"1996-07-27","Eid Milad-un-Nabi* (*estimated)","PK",1996 +"1996-08-14","Independence Day","PK",1996 +"1996-11-09","Iqbal Day","PK",1996 +"1996-12-25","Quaid-e-Azam Day","PK",1996 +"1997-02-05","Kashmir Solidarity Day","PK",1997 +"1997-02-08","Eid-ul-Fitr* (*estimated)","PK",1997 +"1997-02-09","Eid-ul-Fitr* (*estimated)","PK",1997 +"1997-02-10","Eid-ul-Fitr* (*estimated)","PK",1997 +"1997-03-23","Pakistan Day","PK",1997 +"1997-04-17","Eid-ul-Adha* (*estimated)","PK",1997 +"1997-04-18","Eid-ul-Adha* (*estimated)","PK",1997 +"1997-04-19","Eid-ul-Adha* (*estimated)","PK",1997 +"1997-05-01","Labour Day","PK",1997 +"1997-05-15","Ashura* (*estimated)","PK",1997 +"1997-05-16","Ashura* (*estimated)","PK",1997 +"1997-07-16","Eid Milad-un-Nabi* (*estimated)","PK",1997 +"1997-08-14","Independence Day","PK",1997 +"1997-11-09","Iqbal Day","PK",1997 +"1997-12-25","Quaid-e-Azam Day","PK",1997 +"1998-01-29","Eid-ul-Fitr* (*estimated)","PK",1998 +"1998-01-30","Eid-ul-Fitr* (*estimated)","PK",1998 +"1998-01-31","Eid-ul-Fitr* (*estimated)","PK",1998 +"1998-02-05","Kashmir Solidarity Day","PK",1998 +"1998-03-23","Pakistan Day","PK",1998 +"1998-04-07","Eid-ul-Adha* (*estimated)","PK",1998 +"1998-04-08","Eid-ul-Adha* (*estimated)","PK",1998 +"1998-04-09","Eid-ul-Adha* (*estimated)","PK",1998 +"1998-05-01","Labour Day","PK",1998 +"1998-05-05","Ashura* (*estimated)","PK",1998 +"1998-05-06","Ashura* (*estimated)","PK",1998 +"1998-07-06","Eid Milad-un-Nabi* (*estimated)","PK",1998 +"1998-08-14","Independence Day","PK",1998 +"1998-11-09","Iqbal Day","PK",1998 +"1998-12-25","Quaid-e-Azam Day","PK",1998 +"1999-01-18","Eid-ul-Fitr* (*estimated)","PK",1999 +"1999-01-19","Eid-ul-Fitr* (*estimated)","PK",1999 +"1999-01-20","Eid-ul-Fitr* (*estimated)","PK",1999 +"1999-02-05","Kashmir Solidarity Day","PK",1999 +"1999-03-23","Pakistan Day","PK",1999 +"1999-03-27","Eid-ul-Adha* (*estimated)","PK",1999 +"1999-03-28","Eid-ul-Adha* (*estimated)","PK",1999 +"1999-03-29","Eid-ul-Adha* (*estimated)","PK",1999 +"1999-04-25","Ashura* (*estimated)","PK",1999 +"1999-04-26","Ashura* (*estimated)","PK",1999 +"1999-05-01","Labour Day","PK",1999 +"1999-06-26","Eid Milad-un-Nabi* (*estimated)","PK",1999 +"1999-08-14","Independence Day","PK",1999 +"1999-11-09","Iqbal Day","PK",1999 +"1999-12-25","Quaid-e-Azam Day","PK",1999 +"2000-01-08","Eid-ul-Fitr* (*estimated)","PK",2000 +"2000-01-09","Eid-ul-Fitr* (*estimated)","PK",2000 +"2000-01-10","Eid-ul-Fitr* (*estimated)","PK",2000 +"2000-02-05","Kashmir Solidarity Day","PK",2000 +"2000-03-16","Eid-ul-Adha* (*estimated)","PK",2000 +"2000-03-17","Eid-ul-Adha* (*estimated)","PK",2000 +"2000-03-18","Eid-ul-Adha* (*estimated)","PK",2000 +"2000-03-23","Pakistan Day","PK",2000 +"2000-04-14","Ashura* (*estimated)","PK",2000 +"2000-04-15","Ashura* (*estimated)","PK",2000 +"2000-05-01","Labour Day","PK",2000 +"2000-06-14","Eid Milad-un-Nabi* (*estimated)","PK",2000 +"2000-08-14","Independence Day","PK",2000 +"2000-11-09","Iqbal Day","PK",2000 +"2000-12-25","Quaid-e-Azam Day","PK",2000 +"2000-12-27","Eid-ul-Fitr* (*estimated)","PK",2000 +"2000-12-28","Eid-ul-Fitr* (*estimated)","PK",2000 +"2000-12-29","Eid-ul-Fitr* (*estimated)","PK",2000 +"2001-02-05","Kashmir Solidarity Day","PK",2001 +"2001-03-05","Eid-ul-Adha* (*estimated)","PK",2001 +"2001-03-06","Eid-ul-Adha* (*estimated)","PK",2001 +"2001-03-07","Eid-ul-Adha* (*estimated)","PK",2001 +"2001-03-23","Pakistan Day","PK",2001 +"2001-04-03","Ashura* (*estimated)","PK",2001 +"2001-04-04","Ashura* (*estimated)","PK",2001 +"2001-05-01","Labour Day","PK",2001 +"2001-06-04","Eid Milad-un-Nabi* (*estimated)","PK",2001 +"2001-08-14","Independence Day","PK",2001 +"2001-11-09","Iqbal Day","PK",2001 +"2001-12-16","Eid-ul-Fitr* (*estimated)","PK",2001 +"2001-12-17","Eid-ul-Fitr* (*estimated)","PK",2001 +"2001-12-18","Eid-ul-Fitr* (*estimated)","PK",2001 +"2001-12-25","Quaid-e-Azam Day","PK",2001 +"2002-02-05","Kashmir Solidarity Day","PK",2002 +"2002-02-22","Eid-ul-Adha* (*estimated)","PK",2002 +"2002-02-23","Eid-ul-Adha* (*estimated)","PK",2002 +"2002-02-24","Eid-ul-Adha* (*estimated)","PK",2002 +"2002-03-23","Ashura* (*estimated)","PK",2002 +"2002-03-23","Pakistan Day","PK",2002 +"2002-03-24","Ashura* (*estimated)","PK",2002 +"2002-05-01","Labour Day","PK",2002 +"2002-05-24","Eid Milad-un-Nabi* (*estimated)","PK",2002 +"2002-08-14","Independence Day","PK",2002 +"2002-11-09","Iqbal Day","PK",2002 +"2002-12-05","Eid-ul-Fitr* (*estimated)","PK",2002 +"2002-12-06","Eid-ul-Fitr* (*estimated)","PK",2002 +"2002-12-07","Eid-ul-Fitr* (*estimated)","PK",2002 +"2002-12-25","Quaid-e-Azam Day","PK",2002 +"2003-02-05","Kashmir Solidarity Day","PK",2003 +"2003-02-11","Eid-ul-Adha* (*estimated)","PK",2003 +"2003-02-12","Eid-ul-Adha* (*estimated)","PK",2003 +"2003-02-13","Eid-ul-Adha* (*estimated)","PK",2003 +"2003-03-12","Ashura* (*estimated)","PK",2003 +"2003-03-13","Ashura* (*estimated)","PK",2003 +"2003-03-23","Pakistan Day","PK",2003 +"2003-05-01","Labour Day","PK",2003 +"2003-05-13","Eid Milad-un-Nabi* (*estimated)","PK",2003 +"2003-08-14","Independence Day","PK",2003 +"2003-11-09","Iqbal Day","PK",2003 +"2003-11-25","Eid-ul-Fitr* (*estimated)","PK",2003 +"2003-11-26","Eid-ul-Fitr* (*estimated)","PK",2003 +"2003-11-27","Eid-ul-Fitr* (*estimated)","PK",2003 +"2003-12-25","Quaid-e-Azam Day","PK",2003 +"2004-02-01","Eid-ul-Adha* (*estimated)","PK",2004 +"2004-02-02","Eid-ul-Adha* (*estimated)","PK",2004 +"2004-02-03","Eid-ul-Adha* (*estimated)","PK",2004 +"2004-02-05","Kashmir Solidarity Day","PK",2004 +"2004-02-29","Ashura* (*estimated)","PK",2004 +"2004-03-01","Ashura* (*estimated)","PK",2004 +"2004-03-23","Pakistan Day","PK",2004 +"2004-05-01","Eid Milad-un-Nabi* (*estimated)","PK",2004 +"2004-05-01","Labour Day","PK",2004 +"2004-08-14","Independence Day","PK",2004 +"2004-11-09","Iqbal Day","PK",2004 +"2004-11-14","Eid-ul-Fitr* (*estimated)","PK",2004 +"2004-11-15","Eid-ul-Fitr* (*estimated)","PK",2004 +"2004-11-16","Eid-ul-Fitr* (*estimated)","PK",2004 +"2004-12-25","Quaid-e-Azam Day","PK",2004 +"2005-01-21","Eid-ul-Adha","PK",2005 +"2005-01-22","Eid-ul-Adha","PK",2005 +"2005-01-23","Eid-ul-Adha","PK",2005 +"2005-02-05","Kashmir Solidarity Day","PK",2005 +"2005-02-17","Ashura","PK",2005 +"2005-02-18","Ashura","PK",2005 +"2005-03-23","Pakistan Day","PK",2005 +"2005-04-22","Eid Milad-un-Nabi","PK",2005 +"2005-05-01","Labour Day","PK",2005 +"2005-08-14","Independence Day","PK",2005 +"2005-11-04","Eid-ul-Fitr","PK",2005 +"2005-11-05","Eid-ul-Fitr","PK",2005 +"2005-11-06","Eid-ul-Fitr","PK",2005 +"2005-11-09","Iqbal Day","PK",2005 +"2005-12-25","Quaid-e-Azam Day","PK",2005 +"2006-01-10","Eid-ul-Adha","PK",2006 +"2006-01-11","Eid-ul-Adha","PK",2006 +"2006-01-12","Eid-ul-Adha","PK",2006 +"2006-02-05","Kashmir Solidarity Day","PK",2006 +"2006-02-07","Ashura","PK",2006 +"2006-02-08","Ashura","PK",2006 +"2006-03-23","Pakistan Day","PK",2006 +"2006-04-11","Eid Milad-un-Nabi","PK",2006 +"2006-05-01","Labour Day","PK",2006 +"2006-08-14","Independence Day","PK",2006 +"2006-10-24","Eid-ul-Fitr","PK",2006 +"2006-10-25","Eid-ul-Fitr","PK",2006 +"2006-10-26","Eid-ul-Fitr","PK",2006 +"2006-11-09","Iqbal Day","PK",2006 +"2006-12-25","Quaid-e-Azam Day","PK",2006 +"2006-12-31","Eid-ul-Adha","PK",2006 +"2007-01-01","Eid-ul-Adha","PK",2007 +"2007-01-02","Eid-ul-Adha","PK",2007 +"2007-01-27","Ashura","PK",2007 +"2007-01-28","Ashura","PK",2007 +"2007-02-05","Kashmir Solidarity Day","PK",2007 +"2007-03-23","Pakistan Day","PK",2007 +"2007-03-31","Eid Milad-un-Nabi","PK",2007 +"2007-05-01","Labour Day","PK",2007 +"2007-08-14","Independence Day","PK",2007 +"2007-10-13","Eid-ul-Fitr","PK",2007 +"2007-10-14","Eid-ul-Fitr","PK",2007 +"2007-10-15","Eid-ul-Fitr","PK",2007 +"2007-11-09","Iqbal Day","PK",2007 +"2007-12-20","Eid-ul-Adha","PK",2007 +"2007-12-21","Eid-ul-Adha","PK",2007 +"2007-12-22","Eid-ul-Adha","PK",2007 +"2007-12-25","Quaid-e-Azam Day","PK",2007 +"2008-01-17","Ashura","PK",2008 +"2008-01-18","Ashura","PK",2008 +"2008-02-05","Kashmir Solidarity Day","PK",2008 +"2008-03-21","Eid Milad-un-Nabi","PK",2008 +"2008-03-23","Pakistan Day","PK",2008 +"2008-05-01","Labour Day","PK",2008 +"2008-08-14","Independence Day","PK",2008 +"2008-10-02","Eid-ul-Fitr","PK",2008 +"2008-10-03","Eid-ul-Fitr","PK",2008 +"2008-10-04","Eid-ul-Fitr","PK",2008 +"2008-11-09","Iqbal Day","PK",2008 +"2008-12-09","Eid-ul-Adha","PK",2008 +"2008-12-10","Eid-ul-Adha","PK",2008 +"2008-12-11","Eid-ul-Adha","PK",2008 +"2008-12-25","Quaid-e-Azam Day","PK",2008 +"2009-01-05","Ashura","PK",2009 +"2009-01-06","Ashura","PK",2009 +"2009-02-05","Kashmir Solidarity Day","PK",2009 +"2009-03-09","Eid Milad-un-Nabi","PK",2009 +"2009-03-23","Pakistan Day","PK",2009 +"2009-05-01","Labour Day","PK",2009 +"2009-08-14","Independence Day","PK",2009 +"2009-09-21","Eid-ul-Fitr","PK",2009 +"2009-09-22","Eid-ul-Fitr","PK",2009 +"2009-09-23","Eid-ul-Fitr","PK",2009 +"2009-11-09","Iqbal Day","PK",2009 +"2009-11-28","Eid-ul-Adha","PK",2009 +"2009-11-29","Eid-ul-Adha","PK",2009 +"2009-11-30","Eid-ul-Adha","PK",2009 +"2009-12-25","Ashura","PK",2009 +"2009-12-25","Quaid-e-Azam Day","PK",2009 +"2009-12-26","Ashura","PK",2009 +"2010-02-05","Kashmir Solidarity Day","PK",2010 +"2010-03-01","Eid Milad-un-Nabi","PK",2010 +"2010-03-23","Pakistan Day","PK",2010 +"2010-05-01","Labour Day","PK",2010 +"2010-08-14","Independence Day","PK",2010 +"2010-09-10","Eid-ul-Fitr","PK",2010 +"2010-09-11","Eid-ul-Fitr","PK",2010 +"2010-09-12","Eid-ul-Fitr","PK",2010 +"2010-11-09","Iqbal Day","PK",2010 +"2010-11-17","Eid-ul-Adha","PK",2010 +"2010-11-18","Eid-ul-Adha","PK",2010 +"2010-11-19","Eid-ul-Adha","PK",2010 +"2010-12-15","Ashura","PK",2010 +"2010-12-16","Ashura","PK",2010 +"2010-12-25","Quaid-e-Azam Day","PK",2010 +"2011-02-05","Kashmir Solidarity Day","PK",2011 +"2011-02-17","Eid Milad-un-Nabi","PK",2011 +"2011-03-23","Pakistan Day","PK",2011 +"2011-05-01","Labour Day","PK",2011 +"2011-08-14","Independence Day","PK",2011 +"2011-08-31","Eid-ul-Fitr","PK",2011 +"2011-09-01","Eid-ul-Fitr","PK",2011 +"2011-09-02","Eid-ul-Fitr","PK",2011 +"2011-11-07","Eid-ul-Adha","PK",2011 +"2011-11-08","Eid-ul-Adha","PK",2011 +"2011-11-09","Eid-ul-Adha","PK",2011 +"2011-11-09","Iqbal Day","PK",2011 +"2011-12-04","Ashura","PK",2011 +"2011-12-05","Ashura","PK",2011 +"2011-12-25","Quaid-e-Azam Day","PK",2011 +"2012-02-05","Eid Milad-un-Nabi","PK",2012 +"2012-02-05","Kashmir Solidarity Day","PK",2012 +"2012-03-23","Pakistan Day","PK",2012 +"2012-05-01","Labour Day","PK",2012 +"2012-08-14","Independence Day","PK",2012 +"2012-08-19","Eid-ul-Fitr","PK",2012 +"2012-08-20","Eid-ul-Fitr","PK",2012 +"2012-08-21","Eid-ul-Fitr","PK",2012 +"2012-10-26","Eid-ul-Adha","PK",2012 +"2012-10-27","Eid-ul-Adha","PK",2012 +"2012-10-28","Eid-ul-Adha","PK",2012 +"2012-11-09","Iqbal Day","PK",2012 +"2012-11-22","Ashura","PK",2012 +"2012-11-23","Ashura","PK",2012 +"2012-12-25","Quaid-e-Azam Day","PK",2012 +"2013-01-24","Eid Milad-un-Nabi","PK",2013 +"2013-02-05","Kashmir Solidarity Day","PK",2013 +"2013-03-23","Pakistan Day","PK",2013 +"2013-05-01","Labour Day","PK",2013 +"2013-08-08","Eid-ul-Fitr","PK",2013 +"2013-08-09","Eid-ul-Fitr","PK",2013 +"2013-08-10","Eid-ul-Fitr","PK",2013 +"2013-08-14","Independence Day","PK",2013 +"2013-10-15","Eid-ul-Adha","PK",2013 +"2013-10-16","Eid-ul-Adha","PK",2013 +"2013-10-17","Eid-ul-Adha","PK",2013 +"2013-11-09","Iqbal Day","PK",2013 +"2013-11-12","Ashura","PK",2013 +"2013-11-13","Ashura","PK",2013 +"2013-12-25","Quaid-e-Azam Day","PK",2013 +"2014-01-14","Eid Milad-un-Nabi","PK",2014 +"2014-02-05","Kashmir Solidarity Day","PK",2014 +"2014-03-23","Pakistan Day","PK",2014 +"2014-05-01","Labour Day","PK",2014 +"2014-07-29","Eid-ul-Fitr","PK",2014 +"2014-07-30","Eid-ul-Fitr","PK",2014 +"2014-07-31","Eid-ul-Fitr","PK",2014 +"2014-08-14","Independence Day","PK",2014 +"2014-10-06","Eid-ul-Adha","PK",2014 +"2014-10-07","Eid-ul-Adha","PK",2014 +"2014-10-08","Eid-ul-Adha","PK",2014 +"2014-11-02","Ashura","PK",2014 +"2014-11-03","Ashura","PK",2014 +"2014-11-09","Iqbal Day","PK",2014 +"2014-12-25","Quaid-e-Azam Day","PK",2014 +"2015-01-04","Eid Milad-un-Nabi","PK",2015 +"2015-02-05","Kashmir Solidarity Day","PK",2015 +"2015-03-23","Pakistan Day","PK",2015 +"2015-05-01","Labour Day","PK",2015 +"2015-07-17","Eid-ul-Fitr","PK",2015 +"2015-07-18","Eid-ul-Fitr","PK",2015 +"2015-07-19","Eid-ul-Fitr","PK",2015 +"2015-08-14","Independence Day","PK",2015 +"2015-09-24","Eid-ul-Adha","PK",2015 +"2015-09-25","Eid-ul-Adha","PK",2015 +"2015-09-26","Eid-ul-Adha","PK",2015 +"2015-10-22","Ashura","PK",2015 +"2015-10-23","Ashura","PK",2015 +"2015-12-25","Quaid-e-Azam Day","PK",2015 +"2016-02-05","Kashmir Solidarity Day","PK",2016 +"2016-03-23","Pakistan Day","PK",2016 +"2016-05-01","Labour Day","PK",2016 +"2016-07-06","Eid-ul-Fitr","PK",2016 +"2016-07-07","Eid-ul-Fitr","PK",2016 +"2016-07-08","Eid-ul-Fitr","PK",2016 +"2016-08-14","Independence Day","PK",2016 +"2016-09-12","Eid-ul-Adha","PK",2016 +"2016-09-13","Eid-ul-Adha","PK",2016 +"2016-09-14","Eid-ul-Adha","PK",2016 +"2016-10-10","Ashura","PK",2016 +"2016-10-11","Ashura","PK",2016 +"2016-12-12","Eid Milad-un-Nabi","PK",2016 +"2016-12-25","Quaid-e-Azam Day","PK",2016 +"2017-02-05","Kashmir Solidarity Day","PK",2017 +"2017-03-23","Pakistan Day","PK",2017 +"2017-05-01","Labour Day","PK",2017 +"2017-06-26","Eid-ul-Fitr","PK",2017 +"2017-06-27","Eid-ul-Fitr","PK",2017 +"2017-06-28","Eid-ul-Fitr","PK",2017 +"2017-08-14","Independence Day","PK",2017 +"2017-09-02","Eid-ul-Adha","PK",2017 +"2017-09-03","Eid-ul-Adha","PK",2017 +"2017-09-04","Eid-ul-Adha","PK",2017 +"2017-09-29","Ashura","PK",2017 +"2017-09-30","Ashura","PK",2017 +"2017-12-01","Eid Milad-un-Nabi","PK",2017 +"2017-12-25","Quaid-e-Azam Day","PK",2017 +"2018-02-05","Kashmir Solidarity Day","PK",2018 +"2018-03-23","Pakistan Day","PK",2018 +"2018-05-01","Labour Day","PK",2018 +"2018-06-16","Eid-ul-Fitr","PK",2018 +"2018-06-17","Eid-ul-Fitr","PK",2018 +"2018-06-18","Eid-ul-Fitr","PK",2018 +"2018-08-14","Independence Day","PK",2018 +"2018-08-22","Eid-ul-Adha","PK",2018 +"2018-08-23","Eid-ul-Adha","PK",2018 +"2018-08-24","Eid-ul-Adha","PK",2018 +"2018-09-20","Ashura","PK",2018 +"2018-09-21","Ashura","PK",2018 +"2018-11-21","Eid Milad-un-Nabi","PK",2018 +"2018-12-25","Quaid-e-Azam Day","PK",2018 +"2019-02-05","Kashmir Solidarity Day","PK",2019 +"2019-03-23","Pakistan Day","PK",2019 +"2019-05-01","Labour Day","PK",2019 +"2019-06-05","Eid-ul-Fitr","PK",2019 +"2019-06-06","Eid-ul-Fitr","PK",2019 +"2019-06-07","Eid-ul-Fitr","PK",2019 +"2019-08-12","Eid-ul-Adha","PK",2019 +"2019-08-13","Eid-ul-Adha","PK",2019 +"2019-08-14","Eid-ul-Adha","PK",2019 +"2019-08-14","Independence Day","PK",2019 +"2019-09-08","Ashura","PK",2019 +"2019-09-09","Ashura","PK",2019 +"2019-11-10","Eid Milad-un-Nabi","PK",2019 +"2019-12-25","Quaid-e-Azam Day","PK",2019 +"2020-02-05","Kashmir Solidarity Day","PK",2020 +"2020-03-23","Pakistan Day","PK",2020 +"2020-05-01","Labour Day","PK",2020 +"2020-05-24","Eid-ul-Fitr","PK",2020 +"2020-05-25","Eid-ul-Fitr","PK",2020 +"2020-05-26","Eid-ul-Fitr","PK",2020 +"2020-07-31","Eid-ul-Adha","PK",2020 +"2020-08-01","Eid-ul-Adha","PK",2020 +"2020-08-02","Eid-ul-Adha","PK",2020 +"2020-08-14","Independence Day","PK",2020 +"2020-08-28","Ashura","PK",2020 +"2020-08-29","Ashura","PK",2020 +"2020-10-30","Eid Milad-un-Nabi","PK",2020 +"2020-12-25","Quaid-e-Azam Day","PK",2020 +"2021-02-05","Kashmir Solidarity Day","PK",2021 +"2021-03-23","Pakistan Day","PK",2021 +"2021-05-01","Labour Day","PK",2021 +"2021-05-13","Eid-ul-Fitr","PK",2021 +"2021-05-14","Eid-ul-Fitr","PK",2021 +"2021-05-15","Eid-ul-Fitr","PK",2021 +"2021-07-21","Eid-ul-Adha","PK",2021 +"2021-07-22","Eid-ul-Adha","PK",2021 +"2021-07-23","Eid-ul-Adha","PK",2021 +"2021-08-14","Independence Day","PK",2021 +"2021-08-17","Ashura","PK",2021 +"2021-08-18","Ashura","PK",2021 +"2021-10-19","Eid Milad-un-Nabi","PK",2021 +"2021-12-25","Quaid-e-Azam Day","PK",2021 +"2022-02-05","Kashmir Solidarity Day","PK",2022 +"2022-03-23","Pakistan Day","PK",2022 +"2022-05-01","Labour Day","PK",2022 +"2022-05-03","Eid-ul-Fitr","PK",2022 +"2022-05-04","Eid-ul-Fitr","PK",2022 +"2022-05-05","Eid-ul-Fitr","PK",2022 +"2022-07-10","Eid-ul-Adha","PK",2022 +"2022-07-11","Eid-ul-Adha","PK",2022 +"2022-07-12","Eid-ul-Adha","PK",2022 +"2022-08-08","Ashura","PK",2022 +"2022-08-09","Ashura","PK",2022 +"2022-08-14","Independence Day","PK",2022 +"2022-10-09","Eid Milad-un-Nabi","PK",2022 +"2022-11-09","Iqbal Day","PK",2022 +"2022-12-25","Quaid-e-Azam Day","PK",2022 +"2023-02-05","Kashmir Solidarity Day","PK",2023 +"2023-03-23","Pakistan Day","PK",2023 +"2023-04-21","Eid-ul-Fitr* (*estimated)","PK",2023 +"2023-04-22","Eid-ul-Fitr* (*estimated)","PK",2023 +"2023-04-23","Eid-ul-Fitr* (*estimated)","PK",2023 +"2023-05-01","Labour Day","PK",2023 +"2023-06-28","Eid-ul-Adha* (*estimated)","PK",2023 +"2023-06-29","Eid-ul-Adha* (*estimated)","PK",2023 +"2023-06-30","Eid-ul-Adha* (*estimated)","PK",2023 +"2023-07-27","Ashura* (*estimated)","PK",2023 +"2023-07-28","Ashura* (*estimated)","PK",2023 +"2023-08-14","Independence Day","PK",2023 +"2023-09-27","Eid Milad-un-Nabi* (*estimated)","PK",2023 +"2023-11-09","Iqbal Day","PK",2023 +"2023-12-25","Quaid-e-Azam Day","PK",2023 +"2024-02-05","Kashmir Solidarity Day","PK",2024 +"2024-03-23","Pakistan Day","PK",2024 +"2024-04-10","Eid-ul-Fitr* (*estimated)","PK",2024 +"2024-04-11","Eid-ul-Fitr* (*estimated)","PK",2024 +"2024-04-12","Eid-ul-Fitr* (*estimated)","PK",2024 +"2024-05-01","Labour Day","PK",2024 +"2024-06-16","Eid-ul-Adha* (*estimated)","PK",2024 +"2024-06-17","Eid-ul-Adha* (*estimated)","PK",2024 +"2024-06-18","Eid-ul-Adha* (*estimated)","PK",2024 +"2024-07-15","Ashura* (*estimated)","PK",2024 +"2024-07-16","Ashura* (*estimated)","PK",2024 +"2024-08-14","Independence Day","PK",2024 +"2024-09-15","Eid Milad-un-Nabi* (*estimated)","PK",2024 +"2024-11-09","Iqbal Day","PK",2024 +"2024-12-25","Quaid-e-Azam Day","PK",2024 +"2025-02-05","Kashmir Solidarity Day","PK",2025 +"2025-03-23","Pakistan Day","PK",2025 +"2025-03-30","Eid-ul-Fitr* (*estimated)","PK",2025 +"2025-03-31","Eid-ul-Fitr* (*estimated)","PK",2025 +"2025-04-01","Eid-ul-Fitr* (*estimated)","PK",2025 +"2025-05-01","Labour Day","PK",2025 +"2025-06-06","Eid-ul-Adha* (*estimated)","PK",2025 +"2025-06-07","Eid-ul-Adha* (*estimated)","PK",2025 +"2025-06-08","Eid-ul-Adha* (*estimated)","PK",2025 +"2025-07-04","Ashura* (*estimated)","PK",2025 +"2025-07-05","Ashura* (*estimated)","PK",2025 +"2025-08-14","Independence Day","PK",2025 +"2025-09-04","Eid Milad-un-Nabi* (*estimated)","PK",2025 +"2025-11-09","Iqbal Day","PK",2025 +"2025-12-25","Quaid-e-Azam Day","PK",2025 +"2026-02-05","Kashmir Solidarity Day","PK",2026 +"2026-03-20","Eid-ul-Fitr* (*estimated)","PK",2026 +"2026-03-21","Eid-ul-Fitr* (*estimated)","PK",2026 +"2026-03-22","Eid-ul-Fitr* (*estimated)","PK",2026 +"2026-03-23","Pakistan Day","PK",2026 +"2026-05-01","Labour Day","PK",2026 +"2026-05-27","Eid-ul-Adha* (*estimated)","PK",2026 +"2026-05-28","Eid-ul-Adha* (*estimated)","PK",2026 +"2026-05-29","Eid-ul-Adha* (*estimated)","PK",2026 +"2026-06-24","Ashura* (*estimated)","PK",2026 +"2026-06-25","Ashura* (*estimated)","PK",2026 +"2026-08-14","Independence Day","PK",2026 +"2026-08-25","Eid Milad-un-Nabi* (*estimated)","PK",2026 +"2026-11-09","Iqbal Day","PK",2026 +"2026-12-25","Quaid-e-Azam Day","PK",2026 +"2027-02-05","Kashmir Solidarity Day","PK",2027 +"2027-03-09","Eid-ul-Fitr* (*estimated)","PK",2027 +"2027-03-10","Eid-ul-Fitr* (*estimated)","PK",2027 +"2027-03-11","Eid-ul-Fitr* (*estimated)","PK",2027 +"2027-03-23","Pakistan Day","PK",2027 +"2027-05-01","Labour Day","PK",2027 +"2027-05-16","Eid-ul-Adha* (*estimated)","PK",2027 +"2027-05-17","Eid-ul-Adha* (*estimated)","PK",2027 +"2027-05-18","Eid-ul-Adha* (*estimated)","PK",2027 +"2027-06-14","Ashura* (*estimated)","PK",2027 +"2027-06-15","Ashura* (*estimated)","PK",2027 +"2027-08-14","Eid Milad-un-Nabi* (*estimated)","PK",2027 +"2027-08-14","Independence Day","PK",2027 +"2027-11-09","Iqbal Day","PK",2027 +"2027-12-25","Quaid-e-Azam Day","PK",2027 +"2028-02-05","Kashmir Solidarity Day","PK",2028 +"2028-02-26","Eid-ul-Fitr* (*estimated)","PK",2028 +"2028-02-27","Eid-ul-Fitr* (*estimated)","PK",2028 +"2028-02-28","Eid-ul-Fitr* (*estimated)","PK",2028 +"2028-03-23","Pakistan Day","PK",2028 +"2028-05-01","Labour Day","PK",2028 +"2028-05-05","Eid-ul-Adha* (*estimated)","PK",2028 +"2028-05-06","Eid-ul-Adha* (*estimated)","PK",2028 +"2028-05-07","Eid-ul-Adha* (*estimated)","PK",2028 +"2028-06-02","Ashura* (*estimated)","PK",2028 +"2028-06-03","Ashura* (*estimated)","PK",2028 +"2028-08-03","Eid Milad-un-Nabi* (*estimated)","PK",2028 +"2028-08-14","Independence Day","PK",2028 +"2028-11-09","Iqbal Day","PK",2028 +"2028-12-25","Quaid-e-Azam Day","PK",2028 +"2029-02-05","Kashmir Solidarity Day","PK",2029 +"2029-02-14","Eid-ul-Fitr* (*estimated)","PK",2029 +"2029-02-15","Eid-ul-Fitr* (*estimated)","PK",2029 +"2029-02-16","Eid-ul-Fitr* (*estimated)","PK",2029 +"2029-03-23","Pakistan Day","PK",2029 +"2029-04-24","Eid-ul-Adha* (*estimated)","PK",2029 +"2029-04-25","Eid-ul-Adha* (*estimated)","PK",2029 +"2029-04-26","Eid-ul-Adha* (*estimated)","PK",2029 +"2029-05-01","Labour Day","PK",2029 +"2029-05-22","Ashura* (*estimated)","PK",2029 +"2029-05-23","Ashura* (*estimated)","PK",2029 +"2029-07-24","Eid Milad-un-Nabi* (*estimated)","PK",2029 +"2029-08-14","Independence Day","PK",2029 +"2029-11-09","Iqbal Day","PK",2029 +"2029-12-25","Quaid-e-Azam Day","PK",2029 +"2030-02-04","Eid-ul-Fitr* (*estimated)","PK",2030 +"2030-02-05","Eid-ul-Fitr* (*estimated)","PK",2030 +"2030-02-05","Kashmir Solidarity Day","PK",2030 +"2030-02-06","Eid-ul-Fitr* (*estimated)","PK",2030 +"2030-03-23","Pakistan Day","PK",2030 +"2030-04-13","Eid-ul-Adha* (*estimated)","PK",2030 +"2030-04-14","Eid-ul-Adha* (*estimated)","PK",2030 +"2030-04-15","Eid-ul-Adha* (*estimated)","PK",2030 +"2030-05-01","Labour Day","PK",2030 +"2030-05-11","Ashura* (*estimated)","PK",2030 +"2030-05-12","Ashura* (*estimated)","PK",2030 +"2030-07-13","Eid Milad-un-Nabi* (*estimated)","PK",2030 +"2030-08-14","Independence Day","PK",2030 +"2030-11-09","Iqbal Day","PK",2030 +"2030-12-25","Quaid-e-Azam Day","PK",2030 +"2031-01-24","Eid-ul-Fitr* (*estimated)","PK",2031 +"2031-01-25","Eid-ul-Fitr* (*estimated)","PK",2031 +"2031-01-26","Eid-ul-Fitr* (*estimated)","PK",2031 +"2031-02-05","Kashmir Solidarity Day","PK",2031 +"2031-03-23","Pakistan Day","PK",2031 +"2031-04-02","Eid-ul-Adha* (*estimated)","PK",2031 +"2031-04-03","Eid-ul-Adha* (*estimated)","PK",2031 +"2031-04-04","Eid-ul-Adha* (*estimated)","PK",2031 +"2031-05-01","Ashura* (*estimated)","PK",2031 +"2031-05-01","Labour Day","PK",2031 +"2031-05-02","Ashura* (*estimated)","PK",2031 +"2031-07-02","Eid Milad-un-Nabi* (*estimated)","PK",2031 +"2031-08-14","Independence Day","PK",2031 +"2031-11-09","Iqbal Day","PK",2031 +"2031-12-25","Quaid-e-Azam Day","PK",2031 +"2032-01-14","Eid-ul-Fitr* (*estimated)","PK",2032 +"2032-01-15","Eid-ul-Fitr* (*estimated)","PK",2032 +"2032-01-16","Eid-ul-Fitr* (*estimated)","PK",2032 +"2032-02-05","Kashmir Solidarity Day","PK",2032 +"2032-03-22","Eid-ul-Adha* (*estimated)","PK",2032 +"2032-03-23","Eid-ul-Adha* (*estimated)","PK",2032 +"2032-03-23","Pakistan Day","PK",2032 +"2032-03-24","Eid-ul-Adha* (*estimated)","PK",2032 +"2032-04-19","Ashura* (*estimated)","PK",2032 +"2032-04-20","Ashura* (*estimated)","PK",2032 +"2032-05-01","Labour Day","PK",2032 +"2032-06-20","Eid Milad-un-Nabi* (*estimated)","PK",2032 +"2032-08-14","Independence Day","PK",2032 +"2032-11-09","Iqbal Day","PK",2032 +"2032-12-25","Quaid-e-Azam Day","PK",2032 +"2033-01-02","Eid-ul-Fitr* (*estimated)","PK",2033 +"2033-01-03","Eid-ul-Fitr* (*estimated)","PK",2033 +"2033-01-04","Eid-ul-Fitr* (*estimated)","PK",2033 +"2033-02-05","Kashmir Solidarity Day","PK",2033 +"2033-03-11","Eid-ul-Adha* (*estimated)","PK",2033 +"2033-03-12","Eid-ul-Adha* (*estimated)","PK",2033 +"2033-03-13","Eid-ul-Adha* (*estimated)","PK",2033 +"2033-03-23","Pakistan Day","PK",2033 +"2033-04-09","Ashura* (*estimated)","PK",2033 +"2033-04-10","Ashura* (*estimated)","PK",2033 +"2033-05-01","Labour Day","PK",2033 +"2033-06-09","Eid Milad-un-Nabi* (*estimated)","PK",2033 +"2033-08-14","Independence Day","PK",2033 +"2033-11-09","Iqbal Day","PK",2033 +"2033-12-23","Eid-ul-Fitr* (*estimated)","PK",2033 +"2033-12-24","Eid-ul-Fitr* (*estimated)","PK",2033 +"2033-12-25","Eid-ul-Fitr* (*estimated)","PK",2033 +"2033-12-25","Quaid-e-Azam Day","PK",2033 +"2034-02-05","Kashmir Solidarity Day","PK",2034 +"2034-03-01","Eid-ul-Adha* (*estimated)","PK",2034 +"2034-03-02","Eid-ul-Adha* (*estimated)","PK",2034 +"2034-03-03","Eid-ul-Adha* (*estimated)","PK",2034 +"2034-03-23","Pakistan Day","PK",2034 +"2034-03-29","Ashura* (*estimated)","PK",2034 +"2034-03-30","Ashura* (*estimated)","PK",2034 +"2034-05-01","Labour Day","PK",2034 +"2034-05-30","Eid Milad-un-Nabi* (*estimated)","PK",2034 +"2034-08-14","Independence Day","PK",2034 +"2034-11-09","Iqbal Day","PK",2034 +"2034-12-12","Eid-ul-Fitr* (*estimated)","PK",2034 +"2034-12-13","Eid-ul-Fitr* (*estimated)","PK",2034 +"2034-12-14","Eid-ul-Fitr* (*estimated)","PK",2034 +"2034-12-25","Quaid-e-Azam Day","PK",2034 +"2035-02-05","Kashmir Solidarity Day","PK",2035 +"2035-02-18","Eid-ul-Adha* (*estimated)","PK",2035 +"2035-02-19","Eid-ul-Adha* (*estimated)","PK",2035 +"2035-02-20","Eid-ul-Adha* (*estimated)","PK",2035 +"2035-03-19","Ashura* (*estimated)","PK",2035 +"2035-03-20","Ashura* (*estimated)","PK",2035 +"2035-03-23","Pakistan Day","PK",2035 +"2035-05-01","Labour Day","PK",2035 +"2035-05-20","Eid Milad-un-Nabi* (*estimated)","PK",2035 +"2035-08-14","Independence Day","PK",2035 +"2035-11-09","Iqbal Day","PK",2035 +"2035-12-01","Eid-ul-Fitr* (*estimated)","PK",2035 +"2035-12-02","Eid-ul-Fitr* (*estimated)","PK",2035 +"2035-12-03","Eid-ul-Fitr* (*estimated)","PK",2035 +"2035-12-25","Quaid-e-Azam Day","PK",2035 +"2036-02-05","Kashmir Solidarity Day","PK",2036 +"2036-02-07","Eid-ul-Adha* (*estimated)","PK",2036 +"2036-02-08","Eid-ul-Adha* (*estimated)","PK",2036 +"2036-02-09","Eid-ul-Adha* (*estimated)","PK",2036 +"2036-03-07","Ashura* (*estimated)","PK",2036 +"2036-03-08","Ashura* (*estimated)","PK",2036 +"2036-03-23","Pakistan Day","PK",2036 +"2036-05-01","Labour Day","PK",2036 +"2036-05-08","Eid Milad-un-Nabi* (*estimated)","PK",2036 +"2036-08-14","Independence Day","PK",2036 +"2036-11-09","Iqbal Day","PK",2036 +"2036-11-19","Eid-ul-Fitr* (*estimated)","PK",2036 +"2036-11-20","Eid-ul-Fitr* (*estimated)","PK",2036 +"2036-11-21","Eid-ul-Fitr* (*estimated)","PK",2036 +"2036-12-25","Quaid-e-Azam Day","PK",2036 +"2037-01-26","Eid-ul-Adha* (*estimated)","PK",2037 +"2037-01-27","Eid-ul-Adha* (*estimated)","PK",2037 +"2037-01-28","Eid-ul-Adha* (*estimated)","PK",2037 +"2037-02-05","Kashmir Solidarity Day","PK",2037 +"2037-02-24","Ashura* (*estimated)","PK",2037 +"2037-02-25","Ashura* (*estimated)","PK",2037 +"2037-03-23","Pakistan Day","PK",2037 +"2037-04-28","Eid Milad-un-Nabi* (*estimated)","PK",2037 +"2037-05-01","Labour Day","PK",2037 +"2037-08-14","Independence Day","PK",2037 +"2037-11-08","Eid-ul-Fitr* (*estimated)","PK",2037 +"2037-11-09","Eid-ul-Fitr* (*estimated)","PK",2037 +"2037-11-09","Iqbal Day","PK",2037 +"2037-11-10","Eid-ul-Fitr* (*estimated)","PK",2037 +"2037-12-25","Quaid-e-Azam Day","PK",2037 +"2038-01-16","Eid-ul-Adha* (*estimated)","PK",2038 +"2038-01-17","Eid-ul-Adha* (*estimated)","PK",2038 +"2038-01-18","Eid-ul-Adha* (*estimated)","PK",2038 +"2038-02-05","Kashmir Solidarity Day","PK",2038 +"2038-02-13","Ashura* (*estimated)","PK",2038 +"2038-02-14","Ashura* (*estimated)","PK",2038 +"2038-03-23","Pakistan Day","PK",2038 +"2038-04-17","Eid Milad-un-Nabi* (*estimated)","PK",2038 +"2038-05-01","Labour Day","PK",2038 +"2038-08-14","Independence Day","PK",2038 +"2038-10-29","Eid-ul-Fitr* (*estimated)","PK",2038 +"2038-10-30","Eid-ul-Fitr* (*estimated)","PK",2038 +"2038-10-31","Eid-ul-Fitr* (*estimated)","PK",2038 +"2038-11-09","Iqbal Day","PK",2038 +"2038-12-25","Quaid-e-Azam Day","PK",2038 +"2039-01-05","Eid-ul-Adha* (*estimated)","PK",2039 +"2039-01-06","Eid-ul-Adha* (*estimated)","PK",2039 +"2039-01-07","Eid-ul-Adha* (*estimated)","PK",2039 +"2039-02-03","Ashura* (*estimated)","PK",2039 +"2039-02-04","Ashura* (*estimated)","PK",2039 +"2039-02-05","Kashmir Solidarity Day","PK",2039 +"2039-03-23","Pakistan Day","PK",2039 +"2039-04-06","Eid Milad-un-Nabi* (*estimated)","PK",2039 +"2039-05-01","Labour Day","PK",2039 +"2039-08-14","Independence Day","PK",2039 +"2039-10-19","Eid-ul-Fitr* (*estimated)","PK",2039 +"2039-10-20","Eid-ul-Fitr* (*estimated)","PK",2039 +"2039-10-21","Eid-ul-Fitr* (*estimated)","PK",2039 +"2039-11-09","Iqbal Day","PK",2039 +"2039-12-25","Quaid-e-Azam Day","PK",2039 +"2039-12-26","Eid-ul-Adha* (*estimated)","PK",2039 +"2039-12-27","Eid-ul-Adha* (*estimated)","PK",2039 +"2039-12-28","Eid-ul-Adha* (*estimated)","PK",2039 +"2040-01-23","Ashura* (*estimated)","PK",2040 +"2040-01-24","Ashura* (*estimated)","PK",2040 +"2040-02-05","Kashmir Solidarity Day","PK",2040 +"2040-03-23","Pakistan Day","PK",2040 +"2040-03-25","Eid Milad-un-Nabi* (*estimated)","PK",2040 +"2040-05-01","Labour Day","PK",2040 +"2040-08-14","Independence Day","PK",2040 +"2040-10-07","Eid-ul-Fitr* (*estimated)","PK",2040 +"2040-10-08","Eid-ul-Fitr* (*estimated)","PK",2040 +"2040-10-09","Eid-ul-Fitr* (*estimated)","PK",2040 +"2040-11-09","Iqbal Day","PK",2040 +"2040-12-14","Eid-ul-Adha* (*estimated)","PK",2040 +"2040-12-15","Eid-ul-Adha* (*estimated)","PK",2040 +"2040-12-16","Eid-ul-Adha* (*estimated)","PK",2040 +"2040-12-25","Quaid-e-Azam Day","PK",2040 +"2041-01-12","Ashura* (*estimated)","PK",2041 +"2041-01-13","Ashura* (*estimated)","PK",2041 +"2041-02-05","Kashmir Solidarity Day","PK",2041 +"2041-03-15","Eid Milad-un-Nabi* (*estimated)","PK",2041 +"2041-03-23","Pakistan Day","PK",2041 +"2041-05-01","Labour Day","PK",2041 +"2041-08-14","Independence Day","PK",2041 +"2041-09-26","Eid-ul-Fitr* (*estimated)","PK",2041 +"2041-09-27","Eid-ul-Fitr* (*estimated)","PK",2041 +"2041-09-28","Eid-ul-Fitr* (*estimated)","PK",2041 +"2041-11-09","Iqbal Day","PK",2041 +"2041-12-04","Eid-ul-Adha* (*estimated)","PK",2041 +"2041-12-05","Eid-ul-Adha* (*estimated)","PK",2041 +"2041-12-06","Eid-ul-Adha* (*estimated)","PK",2041 +"2041-12-25","Quaid-e-Azam Day","PK",2041 +"2042-01-01","Ashura* (*estimated)","PK",2042 +"2042-01-02","Ashura* (*estimated)","PK",2042 +"2042-02-05","Kashmir Solidarity Day","PK",2042 +"2042-03-04","Eid Milad-un-Nabi* (*estimated)","PK",2042 +"2042-03-23","Pakistan Day","PK",2042 +"2042-05-01","Labour Day","PK",2042 +"2042-08-14","Independence Day","PK",2042 +"2042-09-15","Eid-ul-Fitr* (*estimated)","PK",2042 +"2042-09-16","Eid-ul-Fitr* (*estimated)","PK",2042 +"2042-09-17","Eid-ul-Fitr* (*estimated)","PK",2042 +"2042-11-09","Iqbal Day","PK",2042 +"2042-11-23","Eid-ul-Adha* (*estimated)","PK",2042 +"2042-11-24","Eid-ul-Adha* (*estimated)","PK",2042 +"2042-11-25","Eid-ul-Adha* (*estimated)","PK",2042 +"2042-12-22","Ashura* (*estimated)","PK",2042 +"2042-12-23","Ashura* (*estimated)","PK",2042 +"2042-12-25","Quaid-e-Azam Day","PK",2042 +"2043-02-05","Kashmir Solidarity Day","PK",2043 +"2043-02-22","Eid Milad-un-Nabi* (*estimated)","PK",2043 +"2043-03-23","Pakistan Day","PK",2043 +"2043-05-01","Labour Day","PK",2043 +"2043-08-14","Independence Day","PK",2043 +"2043-09-04","Eid-ul-Fitr* (*estimated)","PK",2043 +"2043-09-05","Eid-ul-Fitr* (*estimated)","PK",2043 +"2043-09-06","Eid-ul-Fitr* (*estimated)","PK",2043 +"2043-11-09","Iqbal Day","PK",2043 +"2043-11-12","Eid-ul-Adha* (*estimated)","PK",2043 +"2043-11-13","Eid-ul-Adha* (*estimated)","PK",2043 +"2043-11-14","Eid-ul-Adha* (*estimated)","PK",2043 +"2043-12-11","Ashura* (*estimated)","PK",2043 +"2043-12-12","Ashura* (*estimated)","PK",2043 +"2043-12-25","Quaid-e-Azam Day","PK",2043 +"2044-02-05","Kashmir Solidarity Day","PK",2044 +"2044-02-11","Eid Milad-un-Nabi* (*estimated)","PK",2044 +"2044-03-23","Pakistan Day","PK",2044 +"2044-05-01","Labour Day","PK",2044 +"2044-08-14","Independence Day","PK",2044 +"2044-08-24","Eid-ul-Fitr* (*estimated)","PK",2044 +"2044-08-25","Eid-ul-Fitr* (*estimated)","PK",2044 +"2044-08-26","Eid-ul-Fitr* (*estimated)","PK",2044 +"2044-10-31","Eid-ul-Adha* (*estimated)","PK",2044 +"2044-11-01","Eid-ul-Adha* (*estimated)","PK",2044 +"2044-11-02","Eid-ul-Adha* (*estimated)","PK",2044 +"2044-11-09","Iqbal Day","PK",2044 +"2044-11-29","Ashura* (*estimated)","PK",2044 +"2044-11-30","Ashura* (*estimated)","PK",2044 +"2044-12-25","Quaid-e-Azam Day","PK",2044 +"1995-01-01","New Year's Day","PL",1995 +"1995-04-16","Easter Sunday","PL",1995 +"1995-04-17","Easter Monday","PL",1995 +"1995-05-01","National Day","PL",1995 +"1995-05-03","National Day of the Third of May","PL",1995 +"1995-06-04","Pentecost","PL",1995 +"1995-06-15","Corpus Christi","PL",1995 +"1995-08-15","Assumption of the Virgin Mary","PL",1995 +"1995-11-01","All Saints' Day","PL",1995 +"1995-11-11","National Independence Day","PL",1995 +"1995-12-25","Christmas (Day 1)","PL",1995 +"1995-12-26","Christmas (Day 2)","PL",1995 +"1996-01-01","New Year's Day","PL",1996 +"1996-04-07","Easter Sunday","PL",1996 +"1996-04-08","Easter Monday","PL",1996 +"1996-05-01","National Day","PL",1996 +"1996-05-03","National Day of the Third of May","PL",1996 +"1996-05-26","Pentecost","PL",1996 +"1996-06-06","Corpus Christi","PL",1996 +"1996-08-15","Assumption of the Virgin Mary","PL",1996 +"1996-11-01","All Saints' Day","PL",1996 +"1996-11-11","National Independence Day","PL",1996 +"1996-12-25","Christmas (Day 1)","PL",1996 +"1996-12-26","Christmas (Day 2)","PL",1996 +"1997-01-01","New Year's Day","PL",1997 +"1997-03-30","Easter Sunday","PL",1997 +"1997-03-31","Easter Monday","PL",1997 +"1997-05-01","National Day","PL",1997 +"1997-05-03","National Day of the Third of May","PL",1997 +"1997-05-18","Pentecost","PL",1997 +"1997-05-29","Corpus Christi","PL",1997 +"1997-08-15","Assumption of the Virgin Mary","PL",1997 +"1997-11-01","All Saints' Day","PL",1997 +"1997-11-11","National Independence Day","PL",1997 +"1997-12-25","Christmas (Day 1)","PL",1997 +"1997-12-26","Christmas (Day 2)","PL",1997 +"1998-01-01","New Year's Day","PL",1998 +"1998-04-12","Easter Sunday","PL",1998 +"1998-04-13","Easter Monday","PL",1998 +"1998-05-01","National Day","PL",1998 +"1998-05-03","National Day of the Third of May","PL",1998 +"1998-05-31","Pentecost","PL",1998 +"1998-06-11","Corpus Christi","PL",1998 +"1998-08-15","Assumption of the Virgin Mary","PL",1998 +"1998-11-01","All Saints' Day","PL",1998 +"1998-11-11","National Independence Day","PL",1998 +"1998-12-25","Christmas (Day 1)","PL",1998 +"1998-12-26","Christmas (Day 2)","PL",1998 +"1999-01-01","New Year's Day","PL",1999 +"1999-04-04","Easter Sunday","PL",1999 +"1999-04-05","Easter Monday","PL",1999 +"1999-05-01","National Day","PL",1999 +"1999-05-03","National Day of the Third of May","PL",1999 +"1999-05-23","Pentecost","PL",1999 +"1999-06-03","Corpus Christi","PL",1999 +"1999-08-15","Assumption of the Virgin Mary","PL",1999 +"1999-11-01","All Saints' Day","PL",1999 +"1999-11-11","National Independence Day","PL",1999 +"1999-12-25","Christmas (Day 1)","PL",1999 +"1999-12-26","Christmas (Day 2)","PL",1999 +"2000-01-01","New Year's Day","PL",2000 +"2000-04-23","Easter Sunday","PL",2000 +"2000-04-24","Easter Monday","PL",2000 +"2000-05-01","National Day","PL",2000 +"2000-05-03","National Day of the Third of May","PL",2000 +"2000-06-11","Pentecost","PL",2000 +"2000-06-22","Corpus Christi","PL",2000 +"2000-08-15","Assumption of the Virgin Mary","PL",2000 +"2000-11-01","All Saints' Day","PL",2000 +"2000-11-11","National Independence Day","PL",2000 +"2000-12-25","Christmas (Day 1)","PL",2000 +"2000-12-26","Christmas (Day 2)","PL",2000 +"2001-01-01","New Year's Day","PL",2001 +"2001-04-15","Easter Sunday","PL",2001 +"2001-04-16","Easter Monday","PL",2001 +"2001-05-01","National Day","PL",2001 +"2001-05-03","National Day of the Third of May","PL",2001 +"2001-06-03","Pentecost","PL",2001 +"2001-06-14","Corpus Christi","PL",2001 +"2001-08-15","Assumption of the Virgin Mary","PL",2001 +"2001-11-01","All Saints' Day","PL",2001 +"2001-11-11","National Independence Day","PL",2001 +"2001-12-25","Christmas (Day 1)","PL",2001 +"2001-12-26","Christmas (Day 2)","PL",2001 +"2002-01-01","New Year's Day","PL",2002 +"2002-03-31","Easter Sunday","PL",2002 +"2002-04-01","Easter Monday","PL",2002 +"2002-05-01","National Day","PL",2002 +"2002-05-03","National Day of the Third of May","PL",2002 +"2002-05-19","Pentecost","PL",2002 +"2002-05-30","Corpus Christi","PL",2002 +"2002-08-15","Assumption of the Virgin Mary","PL",2002 +"2002-11-01","All Saints' Day","PL",2002 +"2002-11-11","National Independence Day","PL",2002 +"2002-12-25","Christmas (Day 1)","PL",2002 +"2002-12-26","Christmas (Day 2)","PL",2002 +"2003-01-01","New Year's Day","PL",2003 +"2003-04-20","Easter Sunday","PL",2003 +"2003-04-21","Easter Monday","PL",2003 +"2003-05-01","National Day","PL",2003 +"2003-05-03","National Day of the Third of May","PL",2003 +"2003-06-08","Pentecost","PL",2003 +"2003-06-19","Corpus Christi","PL",2003 +"2003-08-15","Assumption of the Virgin Mary","PL",2003 +"2003-11-01","All Saints' Day","PL",2003 +"2003-11-11","National Independence Day","PL",2003 +"2003-12-25","Christmas (Day 1)","PL",2003 +"2003-12-26","Christmas (Day 2)","PL",2003 +"2004-01-01","New Year's Day","PL",2004 +"2004-04-11","Easter Sunday","PL",2004 +"2004-04-12","Easter Monday","PL",2004 +"2004-05-01","National Day","PL",2004 +"2004-05-03","National Day of the Third of May","PL",2004 +"2004-05-30","Pentecost","PL",2004 +"2004-06-10","Corpus Christi","PL",2004 +"2004-08-15","Assumption of the Virgin Mary","PL",2004 +"2004-11-01","All Saints' Day","PL",2004 +"2004-11-11","National Independence Day","PL",2004 +"2004-12-25","Christmas (Day 1)","PL",2004 +"2004-12-26","Christmas (Day 2)","PL",2004 +"2005-01-01","New Year's Day","PL",2005 +"2005-03-27","Easter Sunday","PL",2005 +"2005-03-28","Easter Monday","PL",2005 +"2005-05-01","National Day","PL",2005 +"2005-05-03","National Day of the Third of May","PL",2005 +"2005-05-15","Pentecost","PL",2005 +"2005-05-26","Corpus Christi","PL",2005 +"2005-08-15","Assumption of the Virgin Mary","PL",2005 +"2005-11-01","All Saints' Day","PL",2005 +"2005-11-11","National Independence Day","PL",2005 +"2005-12-25","Christmas (Day 1)","PL",2005 +"2005-12-26","Christmas (Day 2)","PL",2005 +"2006-01-01","New Year's Day","PL",2006 +"2006-04-16","Easter Sunday","PL",2006 +"2006-04-17","Easter Monday","PL",2006 +"2006-05-01","National Day","PL",2006 +"2006-05-03","National Day of the Third of May","PL",2006 +"2006-06-04","Pentecost","PL",2006 +"2006-06-15","Corpus Christi","PL",2006 +"2006-08-15","Assumption of the Virgin Mary","PL",2006 +"2006-11-01","All Saints' Day","PL",2006 +"2006-11-11","National Independence Day","PL",2006 +"2006-12-25","Christmas (Day 1)","PL",2006 +"2006-12-26","Christmas (Day 2)","PL",2006 +"2007-01-01","New Year's Day","PL",2007 +"2007-04-08","Easter Sunday","PL",2007 +"2007-04-09","Easter Monday","PL",2007 +"2007-05-01","National Day","PL",2007 +"2007-05-03","National Day of the Third of May","PL",2007 +"2007-05-27","Pentecost","PL",2007 +"2007-06-07","Corpus Christi","PL",2007 +"2007-08-15","Assumption of the Virgin Mary","PL",2007 +"2007-11-01","All Saints' Day","PL",2007 +"2007-11-11","National Independence Day","PL",2007 +"2007-12-25","Christmas (Day 1)","PL",2007 +"2007-12-26","Christmas (Day 2)","PL",2007 +"2008-01-01","New Year's Day","PL",2008 +"2008-03-23","Easter Sunday","PL",2008 +"2008-03-24","Easter Monday","PL",2008 +"2008-05-01","National Day","PL",2008 +"2008-05-03","National Day of the Third of May","PL",2008 +"2008-05-11","Pentecost","PL",2008 +"2008-05-22","Corpus Christi","PL",2008 +"2008-08-15","Assumption of the Virgin Mary","PL",2008 +"2008-11-01","All Saints' Day","PL",2008 +"2008-11-11","National Independence Day","PL",2008 +"2008-12-25","Christmas (Day 1)","PL",2008 +"2008-12-26","Christmas (Day 2)","PL",2008 +"2009-01-01","New Year's Day","PL",2009 +"2009-04-12","Easter Sunday","PL",2009 +"2009-04-13","Easter Monday","PL",2009 +"2009-05-01","National Day","PL",2009 +"2009-05-03","National Day of the Third of May","PL",2009 +"2009-05-31","Pentecost","PL",2009 +"2009-06-11","Corpus Christi","PL",2009 +"2009-08-15","Assumption of the Virgin Mary","PL",2009 +"2009-11-01","All Saints' Day","PL",2009 +"2009-11-11","National Independence Day","PL",2009 +"2009-12-25","Christmas (Day 1)","PL",2009 +"2009-12-26","Christmas (Day 2)","PL",2009 +"2010-01-01","New Year's Day","PL",2010 +"2010-04-04","Easter Sunday","PL",2010 +"2010-04-05","Easter Monday","PL",2010 +"2010-05-01","National Day","PL",2010 +"2010-05-03","National Day of the Third of May","PL",2010 +"2010-05-23","Pentecost","PL",2010 +"2010-06-03","Corpus Christi","PL",2010 +"2010-08-15","Assumption of the Virgin Mary","PL",2010 +"2010-11-01","All Saints' Day","PL",2010 +"2010-11-11","National Independence Day","PL",2010 +"2010-12-25","Christmas (Day 1)","PL",2010 +"2010-12-26","Christmas (Day 2)","PL",2010 +"2011-01-01","New Year's Day","PL",2011 +"2011-01-06","Epiphany","PL",2011 +"2011-04-24","Easter Sunday","PL",2011 +"2011-04-25","Easter Monday","PL",2011 +"2011-05-01","National Day","PL",2011 +"2011-05-03","National Day of the Third of May","PL",2011 +"2011-06-12","Pentecost","PL",2011 +"2011-06-23","Corpus Christi","PL",2011 +"2011-08-15","Assumption of the Virgin Mary","PL",2011 +"2011-11-01","All Saints' Day","PL",2011 +"2011-11-11","National Independence Day","PL",2011 +"2011-12-25","Christmas (Day 1)","PL",2011 +"2011-12-26","Christmas (Day 2)","PL",2011 +"2012-01-01","New Year's Day","PL",2012 +"2012-01-06","Epiphany","PL",2012 +"2012-04-08","Easter Sunday","PL",2012 +"2012-04-09","Easter Monday","PL",2012 +"2012-05-01","National Day","PL",2012 +"2012-05-03","National Day of the Third of May","PL",2012 +"2012-05-27","Pentecost","PL",2012 +"2012-06-07","Corpus Christi","PL",2012 +"2012-08-15","Assumption of the Virgin Mary","PL",2012 +"2012-11-01","All Saints' Day","PL",2012 +"2012-11-11","National Independence Day","PL",2012 +"2012-12-25","Christmas (Day 1)","PL",2012 +"2012-12-26","Christmas (Day 2)","PL",2012 +"2013-01-01","New Year's Day","PL",2013 +"2013-01-06","Epiphany","PL",2013 +"2013-03-31","Easter Sunday","PL",2013 +"2013-04-01","Easter Monday","PL",2013 +"2013-05-01","National Day","PL",2013 +"2013-05-03","National Day of the Third of May","PL",2013 +"2013-05-19","Pentecost","PL",2013 +"2013-05-30","Corpus Christi","PL",2013 +"2013-08-15","Assumption of the Virgin Mary","PL",2013 +"2013-11-01","All Saints' Day","PL",2013 +"2013-11-11","National Independence Day","PL",2013 +"2013-12-25","Christmas (Day 1)","PL",2013 +"2013-12-26","Christmas (Day 2)","PL",2013 +"2014-01-01","New Year's Day","PL",2014 +"2014-01-06","Epiphany","PL",2014 +"2014-04-20","Easter Sunday","PL",2014 +"2014-04-21","Easter Monday","PL",2014 +"2014-05-01","National Day","PL",2014 +"2014-05-03","National Day of the Third of May","PL",2014 +"2014-06-08","Pentecost","PL",2014 +"2014-06-19","Corpus Christi","PL",2014 +"2014-08-15","Assumption of the Virgin Mary","PL",2014 +"2014-11-01","All Saints' Day","PL",2014 +"2014-11-11","National Independence Day","PL",2014 +"2014-12-25","Christmas (Day 1)","PL",2014 +"2014-12-26","Christmas (Day 2)","PL",2014 +"2015-01-01","New Year's Day","PL",2015 +"2015-01-06","Epiphany","PL",2015 +"2015-04-05","Easter Sunday","PL",2015 +"2015-04-06","Easter Monday","PL",2015 +"2015-05-01","National Day","PL",2015 +"2015-05-03","National Day of the Third of May","PL",2015 +"2015-05-24","Pentecost","PL",2015 +"2015-06-04","Corpus Christi","PL",2015 +"2015-08-15","Assumption of the Virgin Mary","PL",2015 +"2015-11-01","All Saints' Day","PL",2015 +"2015-11-11","National Independence Day","PL",2015 +"2015-12-25","Christmas (Day 1)","PL",2015 +"2015-12-26","Christmas (Day 2)","PL",2015 +"2016-01-01","New Year's Day","PL",2016 +"2016-01-06","Epiphany","PL",2016 +"2016-03-27","Easter Sunday","PL",2016 +"2016-03-28","Easter Monday","PL",2016 +"2016-05-01","National Day","PL",2016 +"2016-05-03","National Day of the Third of May","PL",2016 +"2016-05-15","Pentecost","PL",2016 +"2016-05-26","Corpus Christi","PL",2016 +"2016-08-15","Assumption of the Virgin Mary","PL",2016 +"2016-11-01","All Saints' Day","PL",2016 +"2016-11-11","National Independence Day","PL",2016 +"2016-12-25","Christmas (Day 1)","PL",2016 +"2016-12-26","Christmas (Day 2)","PL",2016 +"2017-01-01","New Year's Day","PL",2017 +"2017-01-06","Epiphany","PL",2017 +"2017-04-16","Easter Sunday","PL",2017 +"2017-04-17","Easter Monday","PL",2017 +"2017-05-01","National Day","PL",2017 +"2017-05-03","National Day of the Third of May","PL",2017 +"2017-06-04","Pentecost","PL",2017 +"2017-06-15","Corpus Christi","PL",2017 +"2017-08-15","Assumption of the Virgin Mary","PL",2017 +"2017-11-01","All Saints' Day","PL",2017 +"2017-11-11","National Independence Day","PL",2017 +"2017-12-25","Christmas (Day 1)","PL",2017 +"2017-12-26","Christmas (Day 2)","PL",2017 +"2018-01-01","New Year's Day","PL",2018 +"2018-01-06","Epiphany","PL",2018 +"2018-04-01","Easter Sunday","PL",2018 +"2018-04-02","Easter Monday","PL",2018 +"2018-05-01","National Day","PL",2018 +"2018-05-03","National Day of the Third of May","PL",2018 +"2018-05-20","Pentecost","PL",2018 +"2018-05-31","Corpus Christi","PL",2018 +"2018-08-15","Assumption of the Virgin Mary","PL",2018 +"2018-11-01","All Saints' Day","PL",2018 +"2018-11-11","National Independence Day","PL",2018 +"2018-11-12","National Independence Day - 100th anniversary","PL",2018 +"2018-12-25","Christmas (Day 1)","PL",2018 +"2018-12-26","Christmas (Day 2)","PL",2018 +"2019-01-01","New Year's Day","PL",2019 +"2019-01-06","Epiphany","PL",2019 +"2019-04-21","Easter Sunday","PL",2019 +"2019-04-22","Easter Monday","PL",2019 +"2019-05-01","National Day","PL",2019 +"2019-05-03","National Day of the Third of May","PL",2019 +"2019-06-09","Pentecost","PL",2019 +"2019-06-20","Corpus Christi","PL",2019 +"2019-08-15","Assumption of the Virgin Mary","PL",2019 +"2019-11-01","All Saints' Day","PL",2019 +"2019-11-11","National Independence Day","PL",2019 +"2019-12-25","Christmas (Day 1)","PL",2019 +"2019-12-26","Christmas (Day 2)","PL",2019 +"2020-01-01","New Year's Day","PL",2020 +"2020-01-06","Epiphany","PL",2020 +"2020-04-12","Easter Sunday","PL",2020 +"2020-04-13","Easter Monday","PL",2020 +"2020-05-01","National Day","PL",2020 +"2020-05-03","National Day of the Third of May","PL",2020 +"2020-05-31","Pentecost","PL",2020 +"2020-06-11","Corpus Christi","PL",2020 +"2020-08-15","Assumption of the Virgin Mary","PL",2020 +"2020-11-01","All Saints' Day","PL",2020 +"2020-11-11","National Independence Day","PL",2020 +"2020-12-25","Christmas (Day 1)","PL",2020 +"2020-12-26","Christmas (Day 2)","PL",2020 +"2021-01-01","New Year's Day","PL",2021 +"2021-01-06","Epiphany","PL",2021 +"2021-04-04","Easter Sunday","PL",2021 +"2021-04-05","Easter Monday","PL",2021 +"2021-05-01","National Day","PL",2021 +"2021-05-03","National Day of the Third of May","PL",2021 +"2021-05-23","Pentecost","PL",2021 +"2021-06-03","Corpus Christi","PL",2021 +"2021-08-15","Assumption of the Virgin Mary","PL",2021 +"2021-11-01","All Saints' Day","PL",2021 +"2021-11-11","National Independence Day","PL",2021 +"2021-12-25","Christmas (Day 1)","PL",2021 +"2021-12-26","Christmas (Day 2)","PL",2021 +"2022-01-01","New Year's Day","PL",2022 +"2022-01-06","Epiphany","PL",2022 +"2022-04-17","Easter Sunday","PL",2022 +"2022-04-18","Easter Monday","PL",2022 +"2022-05-01","National Day","PL",2022 +"2022-05-03","National Day of the Third of May","PL",2022 +"2022-06-05","Pentecost","PL",2022 +"2022-06-16","Corpus Christi","PL",2022 +"2022-08-15","Assumption of the Virgin Mary","PL",2022 +"2022-11-01","All Saints' Day","PL",2022 +"2022-11-11","National Independence Day","PL",2022 +"2022-12-25","Christmas (Day 1)","PL",2022 +"2022-12-26","Christmas (Day 2)","PL",2022 +"2023-01-01","New Year's Day","PL",2023 +"2023-01-06","Epiphany","PL",2023 +"2023-04-09","Easter Sunday","PL",2023 +"2023-04-10","Easter Monday","PL",2023 +"2023-05-01","National Day","PL",2023 +"2023-05-03","National Day of the Third of May","PL",2023 +"2023-05-28","Pentecost","PL",2023 +"2023-06-08","Corpus Christi","PL",2023 +"2023-08-15","Assumption of the Virgin Mary","PL",2023 +"2023-11-01","All Saints' Day","PL",2023 +"2023-11-11","National Independence Day","PL",2023 +"2023-12-25","Christmas (Day 1)","PL",2023 +"2023-12-26","Christmas (Day 2)","PL",2023 +"2024-01-01","New Year's Day","PL",2024 +"2024-01-06","Epiphany","PL",2024 +"2024-03-31","Easter Sunday","PL",2024 +"2024-04-01","Easter Monday","PL",2024 +"2024-05-01","National Day","PL",2024 +"2024-05-03","National Day of the Third of May","PL",2024 +"2024-05-19","Pentecost","PL",2024 +"2024-05-30","Corpus Christi","PL",2024 +"2024-08-15","Assumption of the Virgin Mary","PL",2024 +"2024-11-01","All Saints' Day","PL",2024 +"2024-11-11","National Independence Day","PL",2024 +"2024-12-25","Christmas (Day 1)","PL",2024 +"2024-12-26","Christmas (Day 2)","PL",2024 +"2025-01-01","New Year's Day","PL",2025 +"2025-01-06","Epiphany","PL",2025 +"2025-04-20","Easter Sunday","PL",2025 +"2025-04-21","Easter Monday","PL",2025 +"2025-05-01","National Day","PL",2025 +"2025-05-03","National Day of the Third of May","PL",2025 +"2025-06-08","Pentecost","PL",2025 +"2025-06-19","Corpus Christi","PL",2025 +"2025-08-15","Assumption of the Virgin Mary","PL",2025 +"2025-11-01","All Saints' Day","PL",2025 +"2025-11-11","National Independence Day","PL",2025 +"2025-12-25","Christmas (Day 1)","PL",2025 +"2025-12-26","Christmas (Day 2)","PL",2025 +"2026-01-01","New Year's Day","PL",2026 +"2026-01-06","Epiphany","PL",2026 +"2026-04-05","Easter Sunday","PL",2026 +"2026-04-06","Easter Monday","PL",2026 +"2026-05-01","National Day","PL",2026 +"2026-05-03","National Day of the Third of May","PL",2026 +"2026-05-24","Pentecost","PL",2026 +"2026-06-04","Corpus Christi","PL",2026 +"2026-08-15","Assumption of the Virgin Mary","PL",2026 +"2026-11-01","All Saints' Day","PL",2026 +"2026-11-11","National Independence Day","PL",2026 +"2026-12-25","Christmas (Day 1)","PL",2026 +"2026-12-26","Christmas (Day 2)","PL",2026 +"2027-01-01","New Year's Day","PL",2027 +"2027-01-06","Epiphany","PL",2027 +"2027-03-28","Easter Sunday","PL",2027 +"2027-03-29","Easter Monday","PL",2027 +"2027-05-01","National Day","PL",2027 +"2027-05-03","National Day of the Third of May","PL",2027 +"2027-05-16","Pentecost","PL",2027 +"2027-05-27","Corpus Christi","PL",2027 +"2027-08-15","Assumption of the Virgin Mary","PL",2027 +"2027-11-01","All Saints' Day","PL",2027 +"2027-11-11","National Independence Day","PL",2027 +"2027-12-25","Christmas (Day 1)","PL",2027 +"2027-12-26","Christmas (Day 2)","PL",2027 +"2028-01-01","New Year's Day","PL",2028 +"2028-01-06","Epiphany","PL",2028 +"2028-04-16","Easter Sunday","PL",2028 +"2028-04-17","Easter Monday","PL",2028 +"2028-05-01","National Day","PL",2028 +"2028-05-03","National Day of the Third of May","PL",2028 +"2028-06-04","Pentecost","PL",2028 +"2028-06-15","Corpus Christi","PL",2028 +"2028-08-15","Assumption of the Virgin Mary","PL",2028 +"2028-11-01","All Saints' Day","PL",2028 +"2028-11-11","National Independence Day","PL",2028 +"2028-12-25","Christmas (Day 1)","PL",2028 +"2028-12-26","Christmas (Day 2)","PL",2028 +"2029-01-01","New Year's Day","PL",2029 +"2029-01-06","Epiphany","PL",2029 +"2029-04-01","Easter Sunday","PL",2029 +"2029-04-02","Easter Monday","PL",2029 +"2029-05-01","National Day","PL",2029 +"2029-05-03","National Day of the Third of May","PL",2029 +"2029-05-20","Pentecost","PL",2029 +"2029-05-31","Corpus Christi","PL",2029 +"2029-08-15","Assumption of the Virgin Mary","PL",2029 +"2029-11-01","All Saints' Day","PL",2029 +"2029-11-11","National Independence Day","PL",2029 +"2029-12-25","Christmas (Day 1)","PL",2029 +"2029-12-26","Christmas (Day 2)","PL",2029 +"2030-01-01","New Year's Day","PL",2030 +"2030-01-06","Epiphany","PL",2030 +"2030-04-21","Easter Sunday","PL",2030 +"2030-04-22","Easter Monday","PL",2030 +"2030-05-01","National Day","PL",2030 +"2030-05-03","National Day of the Third of May","PL",2030 +"2030-06-09","Pentecost","PL",2030 +"2030-06-20","Corpus Christi","PL",2030 +"2030-08-15","Assumption of the Virgin Mary","PL",2030 +"2030-11-01","All Saints' Day","PL",2030 +"2030-11-11","National Independence Day","PL",2030 +"2030-12-25","Christmas (Day 1)","PL",2030 +"2030-12-26","Christmas (Day 2)","PL",2030 +"2031-01-01","New Year's Day","PL",2031 +"2031-01-06","Epiphany","PL",2031 +"2031-04-13","Easter Sunday","PL",2031 +"2031-04-14","Easter Monday","PL",2031 +"2031-05-01","National Day","PL",2031 +"2031-05-03","National Day of the Third of May","PL",2031 +"2031-06-01","Pentecost","PL",2031 +"2031-06-12","Corpus Christi","PL",2031 +"2031-08-15","Assumption of the Virgin Mary","PL",2031 +"2031-11-01","All Saints' Day","PL",2031 +"2031-11-11","National Independence Day","PL",2031 +"2031-12-25","Christmas (Day 1)","PL",2031 +"2031-12-26","Christmas (Day 2)","PL",2031 +"2032-01-01","New Year's Day","PL",2032 +"2032-01-06","Epiphany","PL",2032 +"2032-03-28","Easter Sunday","PL",2032 +"2032-03-29","Easter Monday","PL",2032 +"2032-05-01","National Day","PL",2032 +"2032-05-03","National Day of the Third of May","PL",2032 +"2032-05-16","Pentecost","PL",2032 +"2032-05-27","Corpus Christi","PL",2032 +"2032-08-15","Assumption of the Virgin Mary","PL",2032 +"2032-11-01","All Saints' Day","PL",2032 +"2032-11-11","National Independence Day","PL",2032 +"2032-12-25","Christmas (Day 1)","PL",2032 +"2032-12-26","Christmas (Day 2)","PL",2032 +"2033-01-01","New Year's Day","PL",2033 +"2033-01-06","Epiphany","PL",2033 +"2033-04-17","Easter Sunday","PL",2033 +"2033-04-18","Easter Monday","PL",2033 +"2033-05-01","National Day","PL",2033 +"2033-05-03","National Day of the Third of May","PL",2033 +"2033-06-05","Pentecost","PL",2033 +"2033-06-16","Corpus Christi","PL",2033 +"2033-08-15","Assumption of the Virgin Mary","PL",2033 +"2033-11-01","All Saints' Day","PL",2033 +"2033-11-11","National Independence Day","PL",2033 +"2033-12-25","Christmas (Day 1)","PL",2033 +"2033-12-26","Christmas (Day 2)","PL",2033 +"2034-01-01","New Year's Day","PL",2034 +"2034-01-06","Epiphany","PL",2034 +"2034-04-09","Easter Sunday","PL",2034 +"2034-04-10","Easter Monday","PL",2034 +"2034-05-01","National Day","PL",2034 +"2034-05-03","National Day of the Third of May","PL",2034 +"2034-05-28","Pentecost","PL",2034 +"2034-06-08","Corpus Christi","PL",2034 +"2034-08-15","Assumption of the Virgin Mary","PL",2034 +"2034-11-01","All Saints' Day","PL",2034 +"2034-11-11","National Independence Day","PL",2034 +"2034-12-25","Christmas (Day 1)","PL",2034 +"2034-12-26","Christmas (Day 2)","PL",2034 +"2035-01-01","New Year's Day","PL",2035 +"2035-01-06","Epiphany","PL",2035 +"2035-03-25","Easter Sunday","PL",2035 +"2035-03-26","Easter Monday","PL",2035 +"2035-05-01","National Day","PL",2035 +"2035-05-03","National Day of the Third of May","PL",2035 +"2035-05-13","Pentecost","PL",2035 +"2035-05-24","Corpus Christi","PL",2035 +"2035-08-15","Assumption of the Virgin Mary","PL",2035 +"2035-11-01","All Saints' Day","PL",2035 +"2035-11-11","National Independence Day","PL",2035 +"2035-12-25","Christmas (Day 1)","PL",2035 +"2035-12-26","Christmas (Day 2)","PL",2035 +"2036-01-01","New Year's Day","PL",2036 +"2036-01-06","Epiphany","PL",2036 +"2036-04-13","Easter Sunday","PL",2036 +"2036-04-14","Easter Monday","PL",2036 +"2036-05-01","National Day","PL",2036 +"2036-05-03","National Day of the Third of May","PL",2036 +"2036-06-01","Pentecost","PL",2036 +"2036-06-12","Corpus Christi","PL",2036 +"2036-08-15","Assumption of the Virgin Mary","PL",2036 +"2036-11-01","All Saints' Day","PL",2036 +"2036-11-11","National Independence Day","PL",2036 +"2036-12-25","Christmas (Day 1)","PL",2036 +"2036-12-26","Christmas (Day 2)","PL",2036 +"2037-01-01","New Year's Day","PL",2037 +"2037-01-06","Epiphany","PL",2037 +"2037-04-05","Easter Sunday","PL",2037 +"2037-04-06","Easter Monday","PL",2037 +"2037-05-01","National Day","PL",2037 +"2037-05-03","National Day of the Third of May","PL",2037 +"2037-05-24","Pentecost","PL",2037 +"2037-06-04","Corpus Christi","PL",2037 +"2037-08-15","Assumption of the Virgin Mary","PL",2037 +"2037-11-01","All Saints' Day","PL",2037 +"2037-11-11","National Independence Day","PL",2037 +"2037-12-25","Christmas (Day 1)","PL",2037 +"2037-12-26","Christmas (Day 2)","PL",2037 +"2038-01-01","New Year's Day","PL",2038 +"2038-01-06","Epiphany","PL",2038 +"2038-04-25","Easter Sunday","PL",2038 +"2038-04-26","Easter Monday","PL",2038 +"2038-05-01","National Day","PL",2038 +"2038-05-03","National Day of the Third of May","PL",2038 +"2038-06-13","Pentecost","PL",2038 +"2038-06-24","Corpus Christi","PL",2038 +"2038-08-15","Assumption of the Virgin Mary","PL",2038 +"2038-11-01","All Saints' Day","PL",2038 +"2038-11-11","National Independence Day","PL",2038 +"2038-12-25","Christmas (Day 1)","PL",2038 +"2038-12-26","Christmas (Day 2)","PL",2038 +"2039-01-01","New Year's Day","PL",2039 +"2039-01-06","Epiphany","PL",2039 +"2039-04-10","Easter Sunday","PL",2039 +"2039-04-11","Easter Monday","PL",2039 +"2039-05-01","National Day","PL",2039 +"2039-05-03","National Day of the Third of May","PL",2039 +"2039-05-29","Pentecost","PL",2039 +"2039-06-09","Corpus Christi","PL",2039 +"2039-08-15","Assumption of the Virgin Mary","PL",2039 +"2039-11-01","All Saints' Day","PL",2039 +"2039-11-11","National Independence Day","PL",2039 +"2039-12-25","Christmas (Day 1)","PL",2039 +"2039-12-26","Christmas (Day 2)","PL",2039 +"2040-01-01","New Year's Day","PL",2040 +"2040-01-06","Epiphany","PL",2040 +"2040-04-01","Easter Sunday","PL",2040 +"2040-04-02","Easter Monday","PL",2040 +"2040-05-01","National Day","PL",2040 +"2040-05-03","National Day of the Third of May","PL",2040 +"2040-05-20","Pentecost","PL",2040 +"2040-05-31","Corpus Christi","PL",2040 +"2040-08-15","Assumption of the Virgin Mary","PL",2040 +"2040-11-01","All Saints' Day","PL",2040 +"2040-11-11","National Independence Day","PL",2040 +"2040-12-25","Christmas (Day 1)","PL",2040 +"2040-12-26","Christmas (Day 2)","PL",2040 +"2041-01-01","New Year's Day","PL",2041 +"2041-01-06","Epiphany","PL",2041 +"2041-04-21","Easter Sunday","PL",2041 +"2041-04-22","Easter Monday","PL",2041 +"2041-05-01","National Day","PL",2041 +"2041-05-03","National Day of the Third of May","PL",2041 +"2041-06-09","Pentecost","PL",2041 +"2041-06-20","Corpus Christi","PL",2041 +"2041-08-15","Assumption of the Virgin Mary","PL",2041 +"2041-11-01","All Saints' Day","PL",2041 +"2041-11-11","National Independence Day","PL",2041 +"2041-12-25","Christmas (Day 1)","PL",2041 +"2041-12-26","Christmas (Day 2)","PL",2041 +"2042-01-01","New Year's Day","PL",2042 +"2042-01-06","Epiphany","PL",2042 +"2042-04-06","Easter Sunday","PL",2042 +"2042-04-07","Easter Monday","PL",2042 +"2042-05-01","National Day","PL",2042 +"2042-05-03","National Day of the Third of May","PL",2042 +"2042-05-25","Pentecost","PL",2042 +"2042-06-05","Corpus Christi","PL",2042 +"2042-08-15","Assumption of the Virgin Mary","PL",2042 +"2042-11-01","All Saints' Day","PL",2042 +"2042-11-11","National Independence Day","PL",2042 +"2042-12-25","Christmas (Day 1)","PL",2042 +"2042-12-26","Christmas (Day 2)","PL",2042 +"2043-01-01","New Year's Day","PL",2043 +"2043-01-06","Epiphany","PL",2043 +"2043-03-29","Easter Sunday","PL",2043 +"2043-03-30","Easter Monday","PL",2043 +"2043-05-01","National Day","PL",2043 +"2043-05-03","National Day of the Third of May","PL",2043 +"2043-05-17","Pentecost","PL",2043 +"2043-05-28","Corpus Christi","PL",2043 +"2043-08-15","Assumption of the Virgin Mary","PL",2043 +"2043-11-01","All Saints' Day","PL",2043 +"2043-11-11","National Independence Day","PL",2043 +"2043-12-25","Christmas (Day 1)","PL",2043 +"2043-12-26","Christmas (Day 2)","PL",2043 +"2044-01-01","New Year's Day","PL",2044 +"2044-01-06","Epiphany","PL",2044 +"2044-04-17","Easter Sunday","PL",2044 +"2044-04-18","Easter Monday","PL",2044 +"2044-05-01","National Day","PL",2044 +"2044-05-03","National Day of the Third of May","PL",2044 +"2044-06-05","Pentecost","PL",2044 +"2044-06-16","Corpus Christi","PL",2044 +"2044-08-15","Assumption of the Virgin Mary","PL",2044 +"2044-11-01","All Saints' Day","PL",2044 +"2044-11-11","National Independence Day","PL",2044 +"2044-12-25","Christmas (Day 1)","PL",2044 +"2044-12-26","Christmas (Day 2)","PL",2044 +"1995-01-01","New Year's Day","PR",1995 +"1995-01-02","New Year's Day (Observed)","PR",1995 +"1995-01-06","Epiphany","PR",1995 +"1995-01-16","Martin Luther King Jr. Day","PR",1995 +"1995-02-20","Presidents' Day","PR",1995 +"1995-03-22","Emancipation Day","PR",1995 +"1995-04-14","Good Friday","PR",1995 +"1995-05-29","Memorial Day","PR",1995 +"1995-07-04","Independence Day","PR",1995 +"1995-07-25","Constitution Day","PR",1995 +"1995-09-04","Labor Day","PR",1995 +"1995-10-09","Columbus Day","PR",1995 +"1995-11-10","Veterans Day (Observed)","PR",1995 +"1995-11-11","Veterans Day","PR",1995 +"1995-11-19","Discovery Day","PR",1995 +"1995-11-20","Discovery Day (Observed)","PR",1995 +"1995-11-23","Thanksgiving","PR",1995 +"1995-12-25","Christmas Day","PR",1995 +"1996-01-01","New Year's Day","PR",1996 +"1996-01-06","Epiphany","PR",1996 +"1996-01-15","Martin Luther King Jr. Day","PR",1996 +"1996-02-19","Presidents' Day","PR",1996 +"1996-03-22","Emancipation Day","PR",1996 +"1996-04-05","Good Friday","PR",1996 +"1996-05-27","Memorial Day","PR",1996 +"1996-07-04","Independence Day","PR",1996 +"1996-07-25","Constitution Day","PR",1996 +"1996-09-02","Labor Day","PR",1996 +"1996-10-14","Columbus Day","PR",1996 +"1996-11-11","Veterans Day","PR",1996 +"1996-11-19","Discovery Day","PR",1996 +"1996-11-28","Thanksgiving","PR",1996 +"1996-12-25","Christmas Day","PR",1996 +"1997-01-01","New Year's Day","PR",1997 +"1997-01-06","Epiphany","PR",1997 +"1997-01-20","Martin Luther King Jr. Day","PR",1997 +"1997-02-17","Presidents' Day","PR",1997 +"1997-03-22","Emancipation Day","PR",1997 +"1997-03-28","Good Friday","PR",1997 +"1997-05-26","Memorial Day","PR",1997 +"1997-07-04","Independence Day","PR",1997 +"1997-07-25","Constitution Day","PR",1997 +"1997-09-01","Labor Day","PR",1997 +"1997-10-13","Columbus Day","PR",1997 +"1997-11-11","Veterans Day","PR",1997 +"1997-11-19","Discovery Day","PR",1997 +"1997-11-27","Thanksgiving","PR",1997 +"1997-12-25","Christmas Day","PR",1997 +"1998-01-01","New Year's Day","PR",1998 +"1998-01-06","Epiphany","PR",1998 +"1998-01-19","Martin Luther King Jr. Day","PR",1998 +"1998-02-16","Presidents' Day","PR",1998 +"1998-03-22","Emancipation Day","PR",1998 +"1998-03-23","Emancipation Day (Observed)","PR",1998 +"1998-04-10","Good Friday","PR",1998 +"1998-05-25","Memorial Day","PR",1998 +"1998-07-03","Independence Day (Observed)","PR",1998 +"1998-07-04","Independence Day","PR",1998 +"1998-07-25","Constitution Day","PR",1998 +"1998-09-07","Labor Day","PR",1998 +"1998-10-12","Columbus Day","PR",1998 +"1998-11-11","Veterans Day","PR",1998 +"1998-11-19","Discovery Day","PR",1998 +"1998-11-26","Thanksgiving","PR",1998 +"1998-12-25","Christmas Day","PR",1998 +"1999-01-01","New Year's Day","PR",1999 +"1999-01-06","Epiphany","PR",1999 +"1999-01-18","Martin Luther King Jr. Day","PR",1999 +"1999-02-15","Presidents' Day","PR",1999 +"1999-03-22","Emancipation Day","PR",1999 +"1999-04-02","Good Friday","PR",1999 +"1999-05-31","Memorial Day","PR",1999 +"1999-07-04","Independence Day","PR",1999 +"1999-07-05","Independence Day (Observed)","PR",1999 +"1999-07-25","Constitution Day","PR",1999 +"1999-07-26","Constitution Day (Observed)","PR",1999 +"1999-09-06","Labor Day","PR",1999 +"1999-10-11","Columbus Day","PR",1999 +"1999-11-11","Veterans Day","PR",1999 +"1999-11-19","Discovery Day","PR",1999 +"1999-11-25","Thanksgiving","PR",1999 +"1999-12-24","Christmas Day (Observed)","PR",1999 +"1999-12-25","Christmas Day","PR",1999 +"1999-12-31","New Year's Day (Observed)","PR",1999 +"2000-01-01","New Year's Day","PR",2000 +"2000-01-06","Epiphany","PR",2000 +"2000-01-17","Martin Luther King Jr. Day","PR",2000 +"2000-02-21","Presidents' Day","PR",2000 +"2000-03-22","Emancipation Day","PR",2000 +"2000-04-21","Good Friday","PR",2000 +"2000-05-29","Memorial Day","PR",2000 +"2000-07-04","Independence Day","PR",2000 +"2000-07-25","Constitution Day","PR",2000 +"2000-09-04","Labor Day","PR",2000 +"2000-10-09","Columbus Day","PR",2000 +"2000-11-10","Veterans Day (Observed)","PR",2000 +"2000-11-11","Veterans Day","PR",2000 +"2000-11-19","Discovery Day","PR",2000 +"2000-11-20","Discovery Day (Observed)","PR",2000 +"2000-11-23","Thanksgiving","PR",2000 +"2000-12-25","Christmas Day","PR",2000 +"2001-01-01","New Year's Day","PR",2001 +"2001-01-06","Epiphany","PR",2001 +"2001-01-15","Martin Luther King Jr. Day","PR",2001 +"2001-02-19","Presidents' Day","PR",2001 +"2001-03-22","Emancipation Day","PR",2001 +"2001-04-13","Good Friday","PR",2001 +"2001-05-28","Memorial Day","PR",2001 +"2001-07-04","Independence Day","PR",2001 +"2001-07-25","Constitution Day","PR",2001 +"2001-09-03","Labor Day","PR",2001 +"2001-10-08","Columbus Day","PR",2001 +"2001-11-11","Veterans Day","PR",2001 +"2001-11-12","Veterans Day (Observed)","PR",2001 +"2001-11-19","Discovery Day","PR",2001 +"2001-11-22","Thanksgiving","PR",2001 +"2001-12-25","Christmas Day","PR",2001 +"2002-01-01","New Year's Day","PR",2002 +"2002-01-06","Epiphany","PR",2002 +"2002-01-21","Martin Luther King Jr. Day","PR",2002 +"2002-02-18","Presidents' Day","PR",2002 +"2002-03-22","Emancipation Day","PR",2002 +"2002-03-29","Good Friday","PR",2002 +"2002-05-27","Memorial Day","PR",2002 +"2002-07-04","Independence Day","PR",2002 +"2002-07-25","Constitution Day","PR",2002 +"2002-09-02","Labor Day","PR",2002 +"2002-10-14","Columbus Day","PR",2002 +"2002-11-11","Veterans Day","PR",2002 +"2002-11-19","Discovery Day","PR",2002 +"2002-11-28","Thanksgiving","PR",2002 +"2002-12-25","Christmas Day","PR",2002 +"2003-01-01","New Year's Day","PR",2003 +"2003-01-06","Epiphany","PR",2003 +"2003-01-20","Martin Luther King Jr. Day","PR",2003 +"2003-02-17","Presidents' Day","PR",2003 +"2003-03-22","Emancipation Day","PR",2003 +"2003-04-18","Good Friday","PR",2003 +"2003-05-26","Memorial Day","PR",2003 +"2003-07-04","Independence Day","PR",2003 +"2003-07-25","Constitution Day","PR",2003 +"2003-09-01","Labor Day","PR",2003 +"2003-10-13","Columbus Day","PR",2003 +"2003-11-11","Veterans Day","PR",2003 +"2003-11-19","Discovery Day","PR",2003 +"2003-11-27","Thanksgiving","PR",2003 +"2003-12-25","Christmas Day","PR",2003 +"2004-01-01","New Year's Day","PR",2004 +"2004-01-06","Epiphany","PR",2004 +"2004-01-19","Martin Luther King Jr. Day","PR",2004 +"2004-02-16","Presidents' Day","PR",2004 +"2004-03-22","Emancipation Day","PR",2004 +"2004-04-09","Good Friday","PR",2004 +"2004-05-31","Memorial Day","PR",2004 +"2004-07-04","Independence Day","PR",2004 +"2004-07-05","Independence Day (Observed)","PR",2004 +"2004-07-25","Constitution Day","PR",2004 +"2004-07-26","Constitution Day (Observed)","PR",2004 +"2004-09-06","Labor Day","PR",2004 +"2004-10-11","Columbus Day","PR",2004 +"2004-11-11","Veterans Day","PR",2004 +"2004-11-19","Discovery Day","PR",2004 +"2004-11-25","Thanksgiving","PR",2004 +"2004-12-24","Christmas Day (Observed)","PR",2004 +"2004-12-25","Christmas Day","PR",2004 +"2004-12-31","New Year's Day (Observed)","PR",2004 +"2005-01-01","New Year's Day","PR",2005 +"2005-01-06","Epiphany","PR",2005 +"2005-01-17","Martin Luther King Jr. Day","PR",2005 +"2005-02-21","Presidents' Day","PR",2005 +"2005-03-22","Emancipation Day","PR",2005 +"2005-03-25","Good Friday","PR",2005 +"2005-05-30","Memorial Day","PR",2005 +"2005-07-04","Independence Day","PR",2005 +"2005-07-25","Constitution Day","PR",2005 +"2005-09-05","Labor Day","PR",2005 +"2005-10-10","Columbus Day","PR",2005 +"2005-11-11","Veterans Day","PR",2005 +"2005-11-19","Discovery Day","PR",2005 +"2005-11-24","Thanksgiving","PR",2005 +"2005-12-25","Christmas Day","PR",2005 +"2005-12-26","Christmas Day (Observed)","PR",2005 +"2006-01-01","New Year's Day","PR",2006 +"2006-01-02","New Year's Day (Observed)","PR",2006 +"2006-01-06","Epiphany","PR",2006 +"2006-01-16","Martin Luther King Jr. Day","PR",2006 +"2006-02-20","Presidents' Day","PR",2006 +"2006-03-22","Emancipation Day","PR",2006 +"2006-04-14","Good Friday","PR",2006 +"2006-05-29","Memorial Day","PR",2006 +"2006-07-04","Independence Day","PR",2006 +"2006-07-25","Constitution Day","PR",2006 +"2006-09-04","Labor Day","PR",2006 +"2006-10-09","Columbus Day","PR",2006 +"2006-11-10","Veterans Day (Observed)","PR",2006 +"2006-11-11","Veterans Day","PR",2006 +"2006-11-19","Discovery Day","PR",2006 +"2006-11-20","Discovery Day (Observed)","PR",2006 +"2006-11-23","Thanksgiving","PR",2006 +"2006-12-25","Christmas Day","PR",2006 +"2007-01-01","New Year's Day","PR",2007 +"2007-01-06","Epiphany","PR",2007 +"2007-01-15","Martin Luther King Jr. Day","PR",2007 +"2007-02-19","Presidents' Day","PR",2007 +"2007-03-22","Emancipation Day","PR",2007 +"2007-04-06","Good Friday","PR",2007 +"2007-05-28","Memorial Day","PR",2007 +"2007-07-04","Independence Day","PR",2007 +"2007-07-25","Constitution Day","PR",2007 +"2007-09-03","Labor Day","PR",2007 +"2007-10-08","Columbus Day","PR",2007 +"2007-11-11","Veterans Day","PR",2007 +"2007-11-12","Veterans Day (Observed)","PR",2007 +"2007-11-19","Discovery Day","PR",2007 +"2007-11-22","Thanksgiving","PR",2007 +"2007-12-25","Christmas Day","PR",2007 +"2008-01-01","New Year's Day","PR",2008 +"2008-01-06","Epiphany","PR",2008 +"2008-01-21","Martin Luther King Jr. Day","PR",2008 +"2008-02-18","Presidents' Day","PR",2008 +"2008-03-21","Good Friday","PR",2008 +"2008-03-22","Emancipation Day","PR",2008 +"2008-05-26","Memorial Day","PR",2008 +"2008-07-04","Independence Day","PR",2008 +"2008-07-25","Constitution Day","PR",2008 +"2008-09-01","Labor Day","PR",2008 +"2008-10-13","Columbus Day","PR",2008 +"2008-11-11","Veterans Day","PR",2008 +"2008-11-19","Discovery Day","PR",2008 +"2008-11-27","Thanksgiving","PR",2008 +"2008-12-25","Christmas Day","PR",2008 +"2009-01-01","New Year's Day","PR",2009 +"2009-01-06","Epiphany","PR",2009 +"2009-01-19","Martin Luther King Jr. Day","PR",2009 +"2009-02-16","Presidents' Day","PR",2009 +"2009-03-22","Emancipation Day","PR",2009 +"2009-03-23","Emancipation Day (Observed)","PR",2009 +"2009-04-10","Good Friday","PR",2009 +"2009-05-25","Memorial Day","PR",2009 +"2009-07-03","Independence Day (Observed)","PR",2009 +"2009-07-04","Independence Day","PR",2009 +"2009-07-25","Constitution Day","PR",2009 +"2009-09-07","Labor Day","PR",2009 +"2009-10-12","Columbus Day","PR",2009 +"2009-11-11","Veterans Day","PR",2009 +"2009-11-19","Discovery Day","PR",2009 +"2009-11-26","Thanksgiving","PR",2009 +"2009-12-25","Christmas Day","PR",2009 +"2010-01-01","New Year's Day","PR",2010 +"2010-01-06","Epiphany","PR",2010 +"2010-01-18","Martin Luther King Jr. Day","PR",2010 +"2010-02-15","Presidents' Day","PR",2010 +"2010-03-22","Emancipation Day","PR",2010 +"2010-04-02","Good Friday","PR",2010 +"2010-05-31","Memorial Day","PR",2010 +"2010-07-04","Independence Day","PR",2010 +"2010-07-05","Independence Day (Observed)","PR",2010 +"2010-07-25","Constitution Day","PR",2010 +"2010-07-26","Constitution Day (Observed)","PR",2010 +"2010-09-06","Labor Day","PR",2010 +"2010-10-11","Columbus Day","PR",2010 +"2010-11-11","Veterans Day","PR",2010 +"2010-11-19","Discovery Day","PR",2010 +"2010-11-25","Thanksgiving","PR",2010 +"2010-12-24","Christmas Day (Observed)","PR",2010 +"2010-12-25","Christmas Day","PR",2010 +"2010-12-31","New Year's Day (Observed)","PR",2010 +"2011-01-01","New Year's Day","PR",2011 +"2011-01-06","Epiphany","PR",2011 +"2011-01-17","Martin Luther King Jr. Day","PR",2011 +"2011-02-21","Presidents' Day","PR",2011 +"2011-03-22","Emancipation Day","PR",2011 +"2011-04-22","Good Friday","PR",2011 +"2011-05-30","Memorial Day","PR",2011 +"2011-07-04","Independence Day","PR",2011 +"2011-07-25","Constitution Day","PR",2011 +"2011-09-05","Labor Day","PR",2011 +"2011-10-10","Columbus Day","PR",2011 +"2011-11-11","Veterans Day","PR",2011 +"2011-11-19","Discovery Day","PR",2011 +"2011-11-24","Thanksgiving","PR",2011 +"2011-12-25","Christmas Day","PR",2011 +"2011-12-26","Christmas Day (Observed)","PR",2011 +"2012-01-01","New Year's Day","PR",2012 +"2012-01-02","New Year's Day (Observed)","PR",2012 +"2012-01-06","Epiphany","PR",2012 +"2012-01-16","Martin Luther King Jr. Day","PR",2012 +"2012-02-20","Presidents' Day","PR",2012 +"2012-03-22","Emancipation Day","PR",2012 +"2012-04-06","Good Friday","PR",2012 +"2012-05-28","Memorial Day","PR",2012 +"2012-07-04","Independence Day","PR",2012 +"2012-07-25","Constitution Day","PR",2012 +"2012-09-03","Labor Day","PR",2012 +"2012-10-08","Columbus Day","PR",2012 +"2012-11-11","Veterans Day","PR",2012 +"2012-11-12","Veterans Day (Observed)","PR",2012 +"2012-11-19","Discovery Day","PR",2012 +"2012-11-22","Thanksgiving","PR",2012 +"2012-12-25","Christmas Day","PR",2012 +"2013-01-01","New Year's Day","PR",2013 +"2013-01-06","Epiphany","PR",2013 +"2013-01-21","Martin Luther King Jr. Day","PR",2013 +"2013-02-18","Presidents' Day","PR",2013 +"2013-03-22","Emancipation Day","PR",2013 +"2013-03-29","Good Friday","PR",2013 +"2013-05-27","Memorial Day","PR",2013 +"2013-07-04","Independence Day","PR",2013 +"2013-07-25","Constitution Day","PR",2013 +"2013-09-02","Labor Day","PR",2013 +"2013-10-14","Columbus Day","PR",2013 +"2013-11-11","Veterans Day","PR",2013 +"2013-11-19","Discovery Day","PR",2013 +"2013-11-28","Thanksgiving","PR",2013 +"2013-12-25","Christmas Day","PR",2013 +"2014-01-01","New Year's Day","PR",2014 +"2014-01-06","Epiphany","PR",2014 +"2014-01-20","Martin Luther King Jr. Day","PR",2014 +"2014-02-17","Presidents' Day","PR",2014 +"2014-03-22","Emancipation Day","PR",2014 +"2014-04-18","Good Friday","PR",2014 +"2014-05-26","Memorial Day","PR",2014 +"2014-07-04","Independence Day","PR",2014 +"2014-07-25","Constitution Day","PR",2014 +"2014-09-01","Labor Day","PR",2014 +"2014-10-13","Columbus Day","PR",2014 +"2014-11-11","Veterans Day","PR",2014 +"2014-11-19","Discovery Day","PR",2014 +"2014-11-27","Thanksgiving","PR",2014 +"2014-12-25","Christmas Day","PR",2014 +"2015-01-01","New Year's Day","PR",2015 +"2015-01-06","Epiphany","PR",2015 +"2015-01-19","Martin Luther King Jr. Day","PR",2015 +"2015-02-16","Presidents' Day","PR",2015 +"2015-03-22","Emancipation Day","PR",2015 +"2015-03-23","Emancipation Day (Observed)","PR",2015 +"2015-04-03","Good Friday","PR",2015 +"2015-05-25","Memorial Day","PR",2015 +"2015-07-03","Independence Day (Observed)","PR",2015 +"2015-07-04","Independence Day","PR",2015 +"2015-07-25","Constitution Day","PR",2015 +"2015-09-07","Labor Day","PR",2015 +"2015-10-12","Columbus Day","PR",2015 +"2015-11-11","Veterans Day","PR",2015 +"2015-11-19","Discovery Day","PR",2015 +"2015-11-26","Thanksgiving","PR",2015 +"2015-12-25","Christmas Day","PR",2015 +"2016-01-01","New Year's Day","PR",2016 +"2016-01-06","Epiphany","PR",2016 +"2016-01-18","Martin Luther King Jr. Day","PR",2016 +"2016-02-15","Presidents' Day","PR",2016 +"2016-03-22","Emancipation Day","PR",2016 +"2016-03-25","Good Friday","PR",2016 +"2016-05-30","Memorial Day","PR",2016 +"2016-07-04","Independence Day","PR",2016 +"2016-07-25","Constitution Day","PR",2016 +"2016-09-05","Labor Day","PR",2016 +"2016-10-10","Columbus Day","PR",2016 +"2016-11-11","Veterans Day","PR",2016 +"2016-11-19","Discovery Day","PR",2016 +"2016-11-24","Thanksgiving","PR",2016 +"2016-12-25","Christmas Day","PR",2016 +"2016-12-26","Christmas Day (Observed)","PR",2016 +"2017-01-01","New Year's Day","PR",2017 +"2017-01-02","New Year's Day (Observed)","PR",2017 +"2017-01-06","Epiphany","PR",2017 +"2017-01-16","Martin Luther King Jr. Day","PR",2017 +"2017-02-20","Presidents' Day","PR",2017 +"2017-03-22","Emancipation Day","PR",2017 +"2017-04-14","Good Friday","PR",2017 +"2017-05-29","Memorial Day","PR",2017 +"2017-07-04","Independence Day","PR",2017 +"2017-07-25","Constitution Day","PR",2017 +"2017-09-04","Labor Day","PR",2017 +"2017-10-09","Columbus Day","PR",2017 +"2017-11-10","Veterans Day (Observed)","PR",2017 +"2017-11-11","Veterans Day","PR",2017 +"2017-11-19","Discovery Day","PR",2017 +"2017-11-20","Discovery Day (Observed)","PR",2017 +"2017-11-23","Thanksgiving","PR",2017 +"2017-12-25","Christmas Day","PR",2017 +"2018-01-01","New Year's Day","PR",2018 +"2018-01-06","Epiphany","PR",2018 +"2018-01-15","Martin Luther King Jr. Day","PR",2018 +"2018-02-19","Presidents' Day","PR",2018 +"2018-03-22","Emancipation Day","PR",2018 +"2018-03-30","Good Friday","PR",2018 +"2018-05-28","Memorial Day","PR",2018 +"2018-07-04","Independence Day","PR",2018 +"2018-07-25","Constitution Day","PR",2018 +"2018-09-03","Labor Day","PR",2018 +"2018-10-08","Columbus Day","PR",2018 +"2018-11-11","Veterans Day","PR",2018 +"2018-11-12","Veterans Day (Observed)","PR",2018 +"2018-11-19","Discovery Day","PR",2018 +"2018-11-22","Thanksgiving","PR",2018 +"2018-12-25","Christmas Day","PR",2018 +"2019-01-01","New Year's Day","PR",2019 +"2019-01-06","Epiphany","PR",2019 +"2019-01-21","Martin Luther King Jr. Day","PR",2019 +"2019-02-18","Presidents' Day","PR",2019 +"2019-03-22","Emancipation Day","PR",2019 +"2019-04-19","Good Friday","PR",2019 +"2019-05-27","Memorial Day","PR",2019 +"2019-07-04","Independence Day","PR",2019 +"2019-07-25","Constitution Day","PR",2019 +"2019-09-02","Labor Day","PR",2019 +"2019-10-14","Columbus Day","PR",2019 +"2019-11-11","Veterans Day","PR",2019 +"2019-11-19","Discovery Day","PR",2019 +"2019-11-28","Thanksgiving","PR",2019 +"2019-12-25","Christmas Day","PR",2019 +"2020-01-01","New Year's Day","PR",2020 +"2020-01-06","Epiphany","PR",2020 +"2020-01-20","Martin Luther King Jr. Day","PR",2020 +"2020-02-17","Presidents' Day","PR",2020 +"2020-03-22","Emancipation Day","PR",2020 +"2020-03-23","Emancipation Day (Observed)","PR",2020 +"2020-04-10","Good Friday","PR",2020 +"2020-05-25","Memorial Day","PR",2020 +"2020-07-03","Independence Day (Observed)","PR",2020 +"2020-07-04","Independence Day","PR",2020 +"2020-07-25","Constitution Day","PR",2020 +"2020-09-07","Labor Day","PR",2020 +"2020-10-12","Columbus Day","PR",2020 +"2020-11-11","Veterans Day","PR",2020 +"2020-11-19","Discovery Day","PR",2020 +"2020-11-26","Thanksgiving","PR",2020 +"2020-12-25","Christmas Day","PR",2020 +"2021-01-01","New Year's Day","PR",2021 +"2021-01-06","Epiphany","PR",2021 +"2021-01-18","Martin Luther King Jr. Day","PR",2021 +"2021-02-15","Presidents' Day","PR",2021 +"2021-03-22","Emancipation Day","PR",2021 +"2021-04-02","Good Friday","PR",2021 +"2021-05-31","Memorial Day","PR",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","PR",2021 +"2021-06-19","Juneteenth National Independence Day","PR",2021 +"2021-07-04","Independence Day","PR",2021 +"2021-07-05","Independence Day (Observed)","PR",2021 +"2021-07-25","Constitution Day","PR",2021 +"2021-07-26","Constitution Day (Observed)","PR",2021 +"2021-09-06","Labor Day","PR",2021 +"2021-10-11","Columbus Day","PR",2021 +"2021-11-11","Veterans Day","PR",2021 +"2021-11-19","Discovery Day","PR",2021 +"2021-11-25","Thanksgiving","PR",2021 +"2021-12-24","Christmas Day (Observed)","PR",2021 +"2021-12-25","Christmas Day","PR",2021 +"2021-12-31","New Year's Day (Observed)","PR",2021 +"2022-01-01","New Year's Day","PR",2022 +"2022-01-06","Epiphany","PR",2022 +"2022-01-17","Martin Luther King Jr. Day","PR",2022 +"2022-02-21","Presidents' Day","PR",2022 +"2022-03-22","Emancipation Day","PR",2022 +"2022-04-15","Good Friday","PR",2022 +"2022-05-30","Memorial Day","PR",2022 +"2022-06-19","Juneteenth National Independence Day","PR",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","PR",2022 +"2022-07-04","Independence Day","PR",2022 +"2022-07-25","Constitution Day","PR",2022 +"2022-09-05","Labor Day","PR",2022 +"2022-10-10","Columbus Day","PR",2022 +"2022-11-11","Veterans Day","PR",2022 +"2022-11-19","Discovery Day","PR",2022 +"2022-11-24","Thanksgiving","PR",2022 +"2022-12-25","Christmas Day","PR",2022 +"2022-12-26","Christmas Day (Observed)","PR",2022 +"2023-01-01","New Year's Day","PR",2023 +"2023-01-02","New Year's Day (Observed)","PR",2023 +"2023-01-06","Epiphany","PR",2023 +"2023-01-16","Martin Luther King Jr. Day","PR",2023 +"2023-02-20","Presidents' Day","PR",2023 +"2023-03-22","Emancipation Day","PR",2023 +"2023-04-07","Good Friday","PR",2023 +"2023-05-29","Memorial Day","PR",2023 +"2023-06-19","Juneteenth National Independence Day","PR",2023 +"2023-07-04","Independence Day","PR",2023 +"2023-07-25","Constitution Day","PR",2023 +"2023-09-04","Labor Day","PR",2023 +"2023-10-09","Columbus Day","PR",2023 +"2023-11-10","Veterans Day (Observed)","PR",2023 +"2023-11-11","Veterans Day","PR",2023 +"2023-11-19","Discovery Day","PR",2023 +"2023-11-20","Discovery Day (Observed)","PR",2023 +"2023-11-23","Thanksgiving","PR",2023 +"2023-12-25","Christmas Day","PR",2023 +"2024-01-01","New Year's Day","PR",2024 +"2024-01-06","Epiphany","PR",2024 +"2024-01-15","Martin Luther King Jr. Day","PR",2024 +"2024-02-19","Presidents' Day","PR",2024 +"2024-03-22","Emancipation Day","PR",2024 +"2024-03-29","Good Friday","PR",2024 +"2024-05-27","Memorial Day","PR",2024 +"2024-06-19","Juneteenth National Independence Day","PR",2024 +"2024-07-04","Independence Day","PR",2024 +"2024-07-25","Constitution Day","PR",2024 +"2024-09-02","Labor Day","PR",2024 +"2024-10-14","Columbus Day","PR",2024 +"2024-11-11","Veterans Day","PR",2024 +"2024-11-19","Discovery Day","PR",2024 +"2024-11-28","Thanksgiving","PR",2024 +"2024-12-25","Christmas Day","PR",2024 +"2025-01-01","New Year's Day","PR",2025 +"2025-01-06","Epiphany","PR",2025 +"2025-01-20","Martin Luther King Jr. Day","PR",2025 +"2025-02-17","Presidents' Day","PR",2025 +"2025-03-22","Emancipation Day","PR",2025 +"2025-04-18","Good Friday","PR",2025 +"2025-05-26","Memorial Day","PR",2025 +"2025-06-19","Juneteenth National Independence Day","PR",2025 +"2025-07-04","Independence Day","PR",2025 +"2025-07-25","Constitution Day","PR",2025 +"2025-09-01","Labor Day","PR",2025 +"2025-10-13","Columbus Day","PR",2025 +"2025-11-11","Veterans Day","PR",2025 +"2025-11-19","Discovery Day","PR",2025 +"2025-11-27","Thanksgiving","PR",2025 +"2025-12-25","Christmas Day","PR",2025 +"2026-01-01","New Year's Day","PR",2026 +"2026-01-06","Epiphany","PR",2026 +"2026-01-19","Martin Luther King Jr. Day","PR",2026 +"2026-02-16","Presidents' Day","PR",2026 +"2026-03-22","Emancipation Day","PR",2026 +"2026-03-23","Emancipation Day (Observed)","PR",2026 +"2026-04-03","Good Friday","PR",2026 +"2026-05-25","Memorial Day","PR",2026 +"2026-06-19","Juneteenth National Independence Day","PR",2026 +"2026-07-03","Independence Day (Observed)","PR",2026 +"2026-07-04","Independence Day","PR",2026 +"2026-07-25","Constitution Day","PR",2026 +"2026-09-07","Labor Day","PR",2026 +"2026-10-12","Columbus Day","PR",2026 +"2026-11-11","Veterans Day","PR",2026 +"2026-11-19","Discovery Day","PR",2026 +"2026-11-26","Thanksgiving","PR",2026 +"2026-12-25","Christmas Day","PR",2026 +"2027-01-01","New Year's Day","PR",2027 +"2027-01-06","Epiphany","PR",2027 +"2027-01-18","Martin Luther King Jr. Day","PR",2027 +"2027-02-15","Presidents' Day","PR",2027 +"2027-03-22","Emancipation Day","PR",2027 +"2027-03-26","Good Friday","PR",2027 +"2027-05-31","Memorial Day","PR",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","PR",2027 +"2027-06-19","Juneteenth National Independence Day","PR",2027 +"2027-07-04","Independence Day","PR",2027 +"2027-07-05","Independence Day (Observed)","PR",2027 +"2027-07-25","Constitution Day","PR",2027 +"2027-07-26","Constitution Day (Observed)","PR",2027 +"2027-09-06","Labor Day","PR",2027 +"2027-10-11","Columbus Day","PR",2027 +"2027-11-11","Veterans Day","PR",2027 +"2027-11-19","Discovery Day","PR",2027 +"2027-11-25","Thanksgiving","PR",2027 +"2027-12-24","Christmas Day (Observed)","PR",2027 +"2027-12-25","Christmas Day","PR",2027 +"2027-12-31","New Year's Day (Observed)","PR",2027 +"2028-01-01","New Year's Day","PR",2028 +"2028-01-06","Epiphany","PR",2028 +"2028-01-17","Martin Luther King Jr. Day","PR",2028 +"2028-02-21","Presidents' Day","PR",2028 +"2028-03-22","Emancipation Day","PR",2028 +"2028-04-14","Good Friday","PR",2028 +"2028-05-29","Memorial Day","PR",2028 +"2028-06-19","Juneteenth National Independence Day","PR",2028 +"2028-07-04","Independence Day","PR",2028 +"2028-07-25","Constitution Day","PR",2028 +"2028-09-04","Labor Day","PR",2028 +"2028-10-09","Columbus Day","PR",2028 +"2028-11-10","Veterans Day (Observed)","PR",2028 +"2028-11-11","Veterans Day","PR",2028 +"2028-11-19","Discovery Day","PR",2028 +"2028-11-20","Discovery Day (Observed)","PR",2028 +"2028-11-23","Thanksgiving","PR",2028 +"2028-12-25","Christmas Day","PR",2028 +"2029-01-01","New Year's Day","PR",2029 +"2029-01-06","Epiphany","PR",2029 +"2029-01-15","Martin Luther King Jr. Day","PR",2029 +"2029-02-19","Presidents' Day","PR",2029 +"2029-03-22","Emancipation Day","PR",2029 +"2029-03-30","Good Friday","PR",2029 +"2029-05-28","Memorial Day","PR",2029 +"2029-06-19","Juneteenth National Independence Day","PR",2029 +"2029-07-04","Independence Day","PR",2029 +"2029-07-25","Constitution Day","PR",2029 +"2029-09-03","Labor Day","PR",2029 +"2029-10-08","Columbus Day","PR",2029 +"2029-11-11","Veterans Day","PR",2029 +"2029-11-12","Veterans Day (Observed)","PR",2029 +"2029-11-19","Discovery Day","PR",2029 +"2029-11-22","Thanksgiving","PR",2029 +"2029-12-25","Christmas Day","PR",2029 +"2030-01-01","New Year's Day","PR",2030 +"2030-01-06","Epiphany","PR",2030 +"2030-01-21","Martin Luther King Jr. Day","PR",2030 +"2030-02-18","Presidents' Day","PR",2030 +"2030-03-22","Emancipation Day","PR",2030 +"2030-04-19","Good Friday","PR",2030 +"2030-05-27","Memorial Day","PR",2030 +"2030-06-19","Juneteenth National Independence Day","PR",2030 +"2030-07-04","Independence Day","PR",2030 +"2030-07-25","Constitution Day","PR",2030 +"2030-09-02","Labor Day","PR",2030 +"2030-10-14","Columbus Day","PR",2030 +"2030-11-11","Veterans Day","PR",2030 +"2030-11-19","Discovery Day","PR",2030 +"2030-11-28","Thanksgiving","PR",2030 +"2030-12-25","Christmas Day","PR",2030 +"2031-01-01","New Year's Day","PR",2031 +"2031-01-06","Epiphany","PR",2031 +"2031-01-20","Martin Luther King Jr. Day","PR",2031 +"2031-02-17","Presidents' Day","PR",2031 +"2031-03-22","Emancipation Day","PR",2031 +"2031-04-11","Good Friday","PR",2031 +"2031-05-26","Memorial Day","PR",2031 +"2031-06-19","Juneteenth National Independence Day","PR",2031 +"2031-07-04","Independence Day","PR",2031 +"2031-07-25","Constitution Day","PR",2031 +"2031-09-01","Labor Day","PR",2031 +"2031-10-13","Columbus Day","PR",2031 +"2031-11-11","Veterans Day","PR",2031 +"2031-11-19","Discovery Day","PR",2031 +"2031-11-27","Thanksgiving","PR",2031 +"2031-12-25","Christmas Day","PR",2031 +"2032-01-01","New Year's Day","PR",2032 +"2032-01-06","Epiphany","PR",2032 +"2032-01-19","Martin Luther King Jr. Day","PR",2032 +"2032-02-16","Presidents' Day","PR",2032 +"2032-03-22","Emancipation Day","PR",2032 +"2032-03-26","Good Friday","PR",2032 +"2032-05-31","Memorial Day","PR",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","PR",2032 +"2032-06-19","Juneteenth National Independence Day","PR",2032 +"2032-07-04","Independence Day","PR",2032 +"2032-07-05","Independence Day (Observed)","PR",2032 +"2032-07-25","Constitution Day","PR",2032 +"2032-07-26","Constitution Day (Observed)","PR",2032 +"2032-09-06","Labor Day","PR",2032 +"2032-10-11","Columbus Day","PR",2032 +"2032-11-11","Veterans Day","PR",2032 +"2032-11-19","Discovery Day","PR",2032 +"2032-11-25","Thanksgiving","PR",2032 +"2032-12-24","Christmas Day (Observed)","PR",2032 +"2032-12-25","Christmas Day","PR",2032 +"2032-12-31","New Year's Day (Observed)","PR",2032 +"2033-01-01","New Year's Day","PR",2033 +"2033-01-06","Epiphany","PR",2033 +"2033-01-17","Martin Luther King Jr. Day","PR",2033 +"2033-02-21","Presidents' Day","PR",2033 +"2033-03-22","Emancipation Day","PR",2033 +"2033-04-15","Good Friday","PR",2033 +"2033-05-30","Memorial Day","PR",2033 +"2033-06-19","Juneteenth National Independence Day","PR",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","PR",2033 +"2033-07-04","Independence Day","PR",2033 +"2033-07-25","Constitution Day","PR",2033 +"2033-09-05","Labor Day","PR",2033 +"2033-10-10","Columbus Day","PR",2033 +"2033-11-11","Veterans Day","PR",2033 +"2033-11-19","Discovery Day","PR",2033 +"2033-11-24","Thanksgiving","PR",2033 +"2033-12-25","Christmas Day","PR",2033 +"2033-12-26","Christmas Day (Observed)","PR",2033 +"2034-01-01","New Year's Day","PR",2034 +"2034-01-02","New Year's Day (Observed)","PR",2034 +"2034-01-06","Epiphany","PR",2034 +"2034-01-16","Martin Luther King Jr. Day","PR",2034 +"2034-02-20","Presidents' Day","PR",2034 +"2034-03-22","Emancipation Day","PR",2034 +"2034-04-07","Good Friday","PR",2034 +"2034-05-29","Memorial Day","PR",2034 +"2034-06-19","Juneteenth National Independence Day","PR",2034 +"2034-07-04","Independence Day","PR",2034 +"2034-07-25","Constitution Day","PR",2034 +"2034-09-04","Labor Day","PR",2034 +"2034-10-09","Columbus Day","PR",2034 +"2034-11-10","Veterans Day (Observed)","PR",2034 +"2034-11-11","Veterans Day","PR",2034 +"2034-11-19","Discovery Day","PR",2034 +"2034-11-20","Discovery Day (Observed)","PR",2034 +"2034-11-23","Thanksgiving","PR",2034 +"2034-12-25","Christmas Day","PR",2034 +"2035-01-01","New Year's Day","PR",2035 +"2035-01-06","Epiphany","PR",2035 +"2035-01-15","Martin Luther King Jr. Day","PR",2035 +"2035-02-19","Presidents' Day","PR",2035 +"2035-03-22","Emancipation Day","PR",2035 +"2035-03-23","Good Friday","PR",2035 +"2035-05-28","Memorial Day","PR",2035 +"2035-06-19","Juneteenth National Independence Day","PR",2035 +"2035-07-04","Independence Day","PR",2035 +"2035-07-25","Constitution Day","PR",2035 +"2035-09-03","Labor Day","PR",2035 +"2035-10-08","Columbus Day","PR",2035 +"2035-11-11","Veterans Day","PR",2035 +"2035-11-12","Veterans Day (Observed)","PR",2035 +"2035-11-19","Discovery Day","PR",2035 +"2035-11-22","Thanksgiving","PR",2035 +"2035-12-25","Christmas Day","PR",2035 +"2036-01-01","New Year's Day","PR",2036 +"2036-01-06","Epiphany","PR",2036 +"2036-01-21","Martin Luther King Jr. Day","PR",2036 +"2036-02-18","Presidents' Day","PR",2036 +"2036-03-22","Emancipation Day","PR",2036 +"2036-04-11","Good Friday","PR",2036 +"2036-05-26","Memorial Day","PR",2036 +"2036-06-19","Juneteenth National Independence Day","PR",2036 +"2036-07-04","Independence Day","PR",2036 +"2036-07-25","Constitution Day","PR",2036 +"2036-09-01","Labor Day","PR",2036 +"2036-10-13","Columbus Day","PR",2036 +"2036-11-11","Veterans Day","PR",2036 +"2036-11-19","Discovery Day","PR",2036 +"2036-11-27","Thanksgiving","PR",2036 +"2036-12-25","Christmas Day","PR",2036 +"2037-01-01","New Year's Day","PR",2037 +"2037-01-06","Epiphany","PR",2037 +"2037-01-19","Martin Luther King Jr. Day","PR",2037 +"2037-02-16","Presidents' Day","PR",2037 +"2037-03-22","Emancipation Day","PR",2037 +"2037-03-23","Emancipation Day (Observed)","PR",2037 +"2037-04-03","Good Friday","PR",2037 +"2037-05-25","Memorial Day","PR",2037 +"2037-06-19","Juneteenth National Independence Day","PR",2037 +"2037-07-03","Independence Day (Observed)","PR",2037 +"2037-07-04","Independence Day","PR",2037 +"2037-07-25","Constitution Day","PR",2037 +"2037-09-07","Labor Day","PR",2037 +"2037-10-12","Columbus Day","PR",2037 +"2037-11-11","Veterans Day","PR",2037 +"2037-11-19","Discovery Day","PR",2037 +"2037-11-26","Thanksgiving","PR",2037 +"2037-12-25","Christmas Day","PR",2037 +"2038-01-01","New Year's Day","PR",2038 +"2038-01-06","Epiphany","PR",2038 +"2038-01-18","Martin Luther King Jr. Day","PR",2038 +"2038-02-15","Presidents' Day","PR",2038 +"2038-03-22","Emancipation Day","PR",2038 +"2038-04-23","Good Friday","PR",2038 +"2038-05-31","Memorial Day","PR",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","PR",2038 +"2038-06-19","Juneteenth National Independence Day","PR",2038 +"2038-07-04","Independence Day","PR",2038 +"2038-07-05","Independence Day (Observed)","PR",2038 +"2038-07-25","Constitution Day","PR",2038 +"2038-07-26","Constitution Day (Observed)","PR",2038 +"2038-09-06","Labor Day","PR",2038 +"2038-10-11","Columbus Day","PR",2038 +"2038-11-11","Veterans Day","PR",2038 +"2038-11-19","Discovery Day","PR",2038 +"2038-11-25","Thanksgiving","PR",2038 +"2038-12-24","Christmas Day (Observed)","PR",2038 +"2038-12-25","Christmas Day","PR",2038 +"2038-12-31","New Year's Day (Observed)","PR",2038 +"2039-01-01","New Year's Day","PR",2039 +"2039-01-06","Epiphany","PR",2039 +"2039-01-17","Martin Luther King Jr. Day","PR",2039 +"2039-02-21","Presidents' Day","PR",2039 +"2039-03-22","Emancipation Day","PR",2039 +"2039-04-08","Good Friday","PR",2039 +"2039-05-30","Memorial Day","PR",2039 +"2039-06-19","Juneteenth National Independence Day","PR",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","PR",2039 +"2039-07-04","Independence Day","PR",2039 +"2039-07-25","Constitution Day","PR",2039 +"2039-09-05","Labor Day","PR",2039 +"2039-10-10","Columbus Day","PR",2039 +"2039-11-11","Veterans Day","PR",2039 +"2039-11-19","Discovery Day","PR",2039 +"2039-11-24","Thanksgiving","PR",2039 +"2039-12-25","Christmas Day","PR",2039 +"2039-12-26","Christmas Day (Observed)","PR",2039 +"2040-01-01","New Year's Day","PR",2040 +"2040-01-02","New Year's Day (Observed)","PR",2040 +"2040-01-06","Epiphany","PR",2040 +"2040-01-16","Martin Luther King Jr. Day","PR",2040 +"2040-02-20","Presidents' Day","PR",2040 +"2040-03-22","Emancipation Day","PR",2040 +"2040-03-30","Good Friday","PR",2040 +"2040-05-28","Memorial Day","PR",2040 +"2040-06-19","Juneteenth National Independence Day","PR",2040 +"2040-07-04","Independence Day","PR",2040 +"2040-07-25","Constitution Day","PR",2040 +"2040-09-03","Labor Day","PR",2040 +"2040-10-08","Columbus Day","PR",2040 +"2040-11-11","Veterans Day","PR",2040 +"2040-11-12","Veterans Day (Observed)","PR",2040 +"2040-11-19","Discovery Day","PR",2040 +"2040-11-22","Thanksgiving","PR",2040 +"2040-12-25","Christmas Day","PR",2040 +"2041-01-01","New Year's Day","PR",2041 +"2041-01-06","Epiphany","PR",2041 +"2041-01-21","Martin Luther King Jr. Day","PR",2041 +"2041-02-18","Presidents' Day","PR",2041 +"2041-03-22","Emancipation Day","PR",2041 +"2041-04-19","Good Friday","PR",2041 +"2041-05-27","Memorial Day","PR",2041 +"2041-06-19","Juneteenth National Independence Day","PR",2041 +"2041-07-04","Independence Day","PR",2041 +"2041-07-25","Constitution Day","PR",2041 +"2041-09-02","Labor Day","PR",2041 +"2041-10-14","Columbus Day","PR",2041 +"2041-11-11","Veterans Day","PR",2041 +"2041-11-19","Discovery Day","PR",2041 +"2041-11-28","Thanksgiving","PR",2041 +"2041-12-25","Christmas Day","PR",2041 +"2042-01-01","New Year's Day","PR",2042 +"2042-01-06","Epiphany","PR",2042 +"2042-01-20","Martin Luther King Jr. Day","PR",2042 +"2042-02-17","Presidents' Day","PR",2042 +"2042-03-22","Emancipation Day","PR",2042 +"2042-04-04","Good Friday","PR",2042 +"2042-05-26","Memorial Day","PR",2042 +"2042-06-19","Juneteenth National Independence Day","PR",2042 +"2042-07-04","Independence Day","PR",2042 +"2042-07-25","Constitution Day","PR",2042 +"2042-09-01","Labor Day","PR",2042 +"2042-10-13","Columbus Day","PR",2042 +"2042-11-11","Veterans Day","PR",2042 +"2042-11-19","Discovery Day","PR",2042 +"2042-11-27","Thanksgiving","PR",2042 +"2042-12-25","Christmas Day","PR",2042 +"2043-01-01","New Year's Day","PR",2043 +"2043-01-06","Epiphany","PR",2043 +"2043-01-19","Martin Luther King Jr. Day","PR",2043 +"2043-02-16","Presidents' Day","PR",2043 +"2043-03-22","Emancipation Day","PR",2043 +"2043-03-23","Emancipation Day (Observed)","PR",2043 +"2043-03-27","Good Friday","PR",2043 +"2043-05-25","Memorial Day","PR",2043 +"2043-06-19","Juneteenth National Independence Day","PR",2043 +"2043-07-03","Independence Day (Observed)","PR",2043 +"2043-07-04","Independence Day","PR",2043 +"2043-07-25","Constitution Day","PR",2043 +"2043-09-07","Labor Day","PR",2043 +"2043-10-12","Columbus Day","PR",2043 +"2043-11-11","Veterans Day","PR",2043 +"2043-11-19","Discovery Day","PR",2043 +"2043-11-26","Thanksgiving","PR",2043 +"2043-12-25","Christmas Day","PR",2043 +"2044-01-01","New Year's Day","PR",2044 +"2044-01-06","Epiphany","PR",2044 +"2044-01-18","Martin Luther King Jr. Day","PR",2044 +"2044-02-15","Presidents' Day","PR",2044 +"2044-03-22","Emancipation Day","PR",2044 +"2044-04-15","Good Friday","PR",2044 +"2044-05-30","Memorial Day","PR",2044 +"2044-06-19","Juneteenth National Independence Day","PR",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","PR",2044 +"2044-07-04","Independence Day","PR",2044 +"2044-07-25","Constitution Day","PR",2044 +"2044-09-05","Labor Day","PR",2044 +"2044-10-10","Columbus Day","PR",2044 +"2044-11-11","Veterans Day","PR",2044 +"2044-11-19","Discovery Day","PR",2044 +"2044-11-24","Thanksgiving","PR",2044 +"2044-12-25","Christmas Day","PR",2044 +"2044-12-26","Christmas Day (Observed)","PR",2044 +"1995-01-01","New Year's Day","PT",1995 +"1995-04-14","Good Friday","PT",1995 +"1995-04-16","Easter Sunday","PT",1995 +"1995-04-25","Freedom Day","PT",1995 +"1995-05-01","Labour Day","PT",1995 +"1995-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",1995 +"1995-06-15","Corpus Christi","PT",1995 +"1995-08-15","Assumption Day","PT",1995 +"1995-10-05","Republic Day","PT",1995 +"1995-11-01","All Saints Day","PT",1995 +"1995-12-01","Restoration of Independence Day","PT",1995 +"1995-12-08","Immaculate Conception","PT",1995 +"1995-12-25","Christmas","PT",1995 +"1996-01-01","New Year's Day","PT",1996 +"1996-04-05","Good Friday","PT",1996 +"1996-04-07","Easter Sunday","PT",1996 +"1996-04-25","Freedom Day","PT",1996 +"1996-05-01","Labour Day","PT",1996 +"1996-06-06","Corpus Christi","PT",1996 +"1996-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",1996 +"1996-08-15","Assumption Day","PT",1996 +"1996-10-05","Republic Day","PT",1996 +"1996-11-01","All Saints Day","PT",1996 +"1996-12-01","Restoration of Independence Day","PT",1996 +"1996-12-08","Immaculate Conception","PT",1996 +"1996-12-25","Christmas","PT",1996 +"1997-01-01","New Year's Day","PT",1997 +"1997-03-28","Good Friday","PT",1997 +"1997-03-30","Easter Sunday","PT",1997 +"1997-04-25","Freedom Day","PT",1997 +"1997-05-01","Labour Day","PT",1997 +"1997-05-29","Corpus Christi","PT",1997 +"1997-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",1997 +"1997-08-15","Assumption Day","PT",1997 +"1997-10-05","Republic Day","PT",1997 +"1997-11-01","All Saints Day","PT",1997 +"1997-12-01","Restoration of Independence Day","PT",1997 +"1997-12-08","Immaculate Conception","PT",1997 +"1997-12-25","Christmas","PT",1997 +"1998-01-01","New Year's Day","PT",1998 +"1998-04-10","Good Friday","PT",1998 +"1998-04-12","Easter Sunday","PT",1998 +"1998-04-25","Freedom Day","PT",1998 +"1998-05-01","Labour Day","PT",1998 +"1998-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",1998 +"1998-06-11","Corpus Christi","PT",1998 +"1998-08-15","Assumption Day","PT",1998 +"1998-10-05","Republic Day","PT",1998 +"1998-11-01","All Saints Day","PT",1998 +"1998-12-01","Restoration of Independence Day","PT",1998 +"1998-12-08","Immaculate Conception","PT",1998 +"1998-12-25","Christmas","PT",1998 +"1999-01-01","New Year's Day","PT",1999 +"1999-04-02","Good Friday","PT",1999 +"1999-04-04","Easter Sunday","PT",1999 +"1999-04-25","Freedom Day","PT",1999 +"1999-05-01","Labour Day","PT",1999 +"1999-06-03","Corpus Christi","PT",1999 +"1999-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",1999 +"1999-08-15","Assumption Day","PT",1999 +"1999-10-05","Republic Day","PT",1999 +"1999-11-01","All Saints Day","PT",1999 +"1999-12-01","Restoration of Independence Day","PT",1999 +"1999-12-08","Immaculate Conception","PT",1999 +"1999-12-25","Christmas","PT",1999 +"2000-01-01","New Year's Day","PT",2000 +"2000-04-21","Good Friday","PT",2000 +"2000-04-23","Easter Sunday","PT",2000 +"2000-04-25","Freedom Day","PT",2000 +"2000-05-01","Labour Day","PT",2000 +"2000-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2000 +"2000-06-22","Corpus Christi","PT",2000 +"2000-08-15","Assumption Day","PT",2000 +"2000-10-05","Republic Day","PT",2000 +"2000-11-01","All Saints Day","PT",2000 +"2000-12-01","Restoration of Independence Day","PT",2000 +"2000-12-08","Immaculate Conception","PT",2000 +"2000-12-25","Christmas","PT",2000 +"2001-01-01","New Year's Day","PT",2001 +"2001-04-13","Good Friday","PT",2001 +"2001-04-15","Easter Sunday","PT",2001 +"2001-04-25","Freedom Day","PT",2001 +"2001-05-01","Labour Day","PT",2001 +"2001-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2001 +"2001-06-14","Corpus Christi","PT",2001 +"2001-08-15","Assumption Day","PT",2001 +"2001-10-05","Republic Day","PT",2001 +"2001-11-01","All Saints Day","PT",2001 +"2001-12-01","Restoration of Independence Day","PT",2001 +"2001-12-08","Immaculate Conception","PT",2001 +"2001-12-25","Christmas","PT",2001 +"2002-01-01","New Year's Day","PT",2002 +"2002-03-29","Good Friday","PT",2002 +"2002-03-31","Easter Sunday","PT",2002 +"2002-04-25","Freedom Day","PT",2002 +"2002-05-01","Labour Day","PT",2002 +"2002-05-30","Corpus Christi","PT",2002 +"2002-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2002 +"2002-08-15","Assumption Day","PT",2002 +"2002-10-05","Republic Day","PT",2002 +"2002-11-01","All Saints Day","PT",2002 +"2002-12-01","Restoration of Independence Day","PT",2002 +"2002-12-08","Immaculate Conception","PT",2002 +"2002-12-25","Christmas","PT",2002 +"2003-01-01","New Year's Day","PT",2003 +"2003-04-18","Good Friday","PT",2003 +"2003-04-20","Easter Sunday","PT",2003 +"2003-04-25","Freedom Day","PT",2003 +"2003-05-01","Labour Day","PT",2003 +"2003-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2003 +"2003-06-19","Corpus Christi","PT",2003 +"2003-08-15","Assumption Day","PT",2003 +"2003-10-05","Republic Day","PT",2003 +"2003-11-01","All Saints Day","PT",2003 +"2003-12-01","Restoration of Independence Day","PT",2003 +"2003-12-08","Immaculate Conception","PT",2003 +"2003-12-25","Christmas","PT",2003 +"2004-01-01","New Year's Day","PT",2004 +"2004-04-09","Good Friday","PT",2004 +"2004-04-11","Easter Sunday","PT",2004 +"2004-04-25","Freedom Day","PT",2004 +"2004-05-01","Labour Day","PT",2004 +"2004-06-10","Corpus Christi","PT",2004 +"2004-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2004 +"2004-08-15","Assumption Day","PT",2004 +"2004-10-05","Republic Day","PT",2004 +"2004-11-01","All Saints Day","PT",2004 +"2004-12-01","Restoration of Independence Day","PT",2004 +"2004-12-08","Immaculate Conception","PT",2004 +"2004-12-25","Christmas","PT",2004 +"2005-01-01","New Year's Day","PT",2005 +"2005-03-25","Good Friday","PT",2005 +"2005-03-27","Easter Sunday","PT",2005 +"2005-04-25","Freedom Day","PT",2005 +"2005-05-01","Labour Day","PT",2005 +"2005-05-26","Corpus Christi","PT",2005 +"2005-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2005 +"2005-08-15","Assumption Day","PT",2005 +"2005-10-05","Republic Day","PT",2005 +"2005-11-01","All Saints Day","PT",2005 +"2005-12-01","Restoration of Independence Day","PT",2005 +"2005-12-08","Immaculate Conception","PT",2005 +"2005-12-25","Christmas","PT",2005 +"2006-01-01","New Year's Day","PT",2006 +"2006-04-14","Good Friday","PT",2006 +"2006-04-16","Easter Sunday","PT",2006 +"2006-04-25","Freedom Day","PT",2006 +"2006-05-01","Labour Day","PT",2006 +"2006-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2006 +"2006-06-15","Corpus Christi","PT",2006 +"2006-08-15","Assumption Day","PT",2006 +"2006-10-05","Republic Day","PT",2006 +"2006-11-01","All Saints Day","PT",2006 +"2006-12-01","Restoration of Independence Day","PT",2006 +"2006-12-08","Immaculate Conception","PT",2006 +"2006-12-25","Christmas","PT",2006 +"2007-01-01","New Year's Day","PT",2007 +"2007-04-06","Good Friday","PT",2007 +"2007-04-08","Easter Sunday","PT",2007 +"2007-04-25","Freedom Day","PT",2007 +"2007-05-01","Labour Day","PT",2007 +"2007-06-07","Corpus Christi","PT",2007 +"2007-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2007 +"2007-08-15","Assumption Day","PT",2007 +"2007-10-05","Republic Day","PT",2007 +"2007-11-01","All Saints Day","PT",2007 +"2007-12-01","Restoration of Independence Day","PT",2007 +"2007-12-08","Immaculate Conception","PT",2007 +"2007-12-25","Christmas","PT",2007 +"2008-01-01","New Year's Day","PT",2008 +"2008-03-21","Good Friday","PT",2008 +"2008-03-23","Easter Sunday","PT",2008 +"2008-04-25","Freedom Day","PT",2008 +"2008-05-01","Labour Day","PT",2008 +"2008-05-22","Corpus Christi","PT",2008 +"2008-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2008 +"2008-08-15","Assumption Day","PT",2008 +"2008-10-05","Republic Day","PT",2008 +"2008-11-01","All Saints Day","PT",2008 +"2008-12-01","Restoration of Independence Day","PT",2008 +"2008-12-08","Immaculate Conception","PT",2008 +"2008-12-25","Christmas","PT",2008 +"2009-01-01","New Year's Day","PT",2009 +"2009-04-10","Good Friday","PT",2009 +"2009-04-12","Easter Sunday","PT",2009 +"2009-04-25","Freedom Day","PT",2009 +"2009-05-01","Labour Day","PT",2009 +"2009-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2009 +"2009-06-11","Corpus Christi","PT",2009 +"2009-08-15","Assumption Day","PT",2009 +"2009-10-05","Republic Day","PT",2009 +"2009-11-01","All Saints Day","PT",2009 +"2009-12-01","Restoration of Independence Day","PT",2009 +"2009-12-08","Immaculate Conception","PT",2009 +"2009-12-25","Christmas","PT",2009 +"2010-01-01","New Year's Day","PT",2010 +"2010-04-02","Good Friday","PT",2010 +"2010-04-04","Easter Sunday","PT",2010 +"2010-04-25","Freedom Day","PT",2010 +"2010-05-01","Labour Day","PT",2010 +"2010-06-03","Corpus Christi","PT",2010 +"2010-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2010 +"2010-08-15","Assumption Day","PT",2010 +"2010-10-05","Republic Day","PT",2010 +"2010-11-01","All Saints Day","PT",2010 +"2010-12-01","Restoration of Independence Day","PT",2010 +"2010-12-08","Immaculate Conception","PT",2010 +"2010-12-25","Christmas","PT",2010 +"2011-01-01","New Year's Day","PT",2011 +"2011-04-22","Good Friday","PT",2011 +"2011-04-24","Easter Sunday","PT",2011 +"2011-04-25","Freedom Day","PT",2011 +"2011-05-01","Labour Day","PT",2011 +"2011-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2011 +"2011-06-23","Corpus Christi","PT",2011 +"2011-08-15","Assumption Day","PT",2011 +"2011-10-05","Republic Day","PT",2011 +"2011-11-01","All Saints Day","PT",2011 +"2011-12-01","Restoration of Independence Day","PT",2011 +"2011-12-08","Immaculate Conception","PT",2011 +"2011-12-25","Christmas","PT",2011 +"2012-01-01","New Year's Day","PT",2012 +"2012-04-06","Good Friday","PT",2012 +"2012-04-08","Easter Sunday","PT",2012 +"2012-04-25","Freedom Day","PT",2012 +"2012-05-01","Labour Day","PT",2012 +"2012-06-07","Corpus Christi","PT",2012 +"2012-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2012 +"2012-08-15","Assumption Day","PT",2012 +"2012-10-05","Republic Day","PT",2012 +"2012-11-01","All Saints Day","PT",2012 +"2012-12-01","Restoration of Independence Day","PT",2012 +"2012-12-08","Immaculate Conception","PT",2012 +"2012-12-25","Christmas","PT",2012 +"2013-01-01","New Year's Day","PT",2013 +"2013-03-29","Good Friday","PT",2013 +"2013-03-31","Easter Sunday","PT",2013 +"2013-04-25","Freedom Day","PT",2013 +"2013-05-01","Labour Day","PT",2013 +"2013-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2013 +"2013-08-15","Assumption Day","PT",2013 +"2013-12-08","Immaculate Conception","PT",2013 +"2013-12-25","Christmas","PT",2013 +"2014-01-01","New Year's Day","PT",2014 +"2014-04-18","Good Friday","PT",2014 +"2014-04-20","Easter Sunday","PT",2014 +"2014-04-25","Freedom Day","PT",2014 +"2014-05-01","Labour Day","PT",2014 +"2014-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2014 +"2014-08-15","Assumption Day","PT",2014 +"2014-12-08","Immaculate Conception","PT",2014 +"2014-12-25","Christmas","PT",2014 +"2015-01-01","New Year's Day","PT",2015 +"2015-04-03","Good Friday","PT",2015 +"2015-04-05","Easter Sunday","PT",2015 +"2015-04-25","Freedom Day","PT",2015 +"2015-05-01","Labour Day","PT",2015 +"2015-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2015 +"2015-08-15","Assumption Day","PT",2015 +"2015-12-08","Immaculate Conception","PT",2015 +"2015-12-25","Christmas","PT",2015 +"2016-01-01","New Year's Day","PT",2016 +"2016-03-25","Good Friday","PT",2016 +"2016-03-27","Easter Sunday","PT",2016 +"2016-04-25","Freedom Day","PT",2016 +"2016-05-01","Labour Day","PT",2016 +"2016-05-26","Corpus Christi","PT",2016 +"2016-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2016 +"2016-08-15","Assumption Day","PT",2016 +"2016-10-05","Republic Day","PT",2016 +"2016-11-01","All Saints Day","PT",2016 +"2016-12-01","Restoration of Independence Day","PT",2016 +"2016-12-08","Immaculate Conception","PT",2016 +"2016-12-25","Christmas","PT",2016 +"2017-01-01","New Year's Day","PT",2017 +"2017-04-14","Good Friday","PT",2017 +"2017-04-16","Easter Sunday","PT",2017 +"2017-04-25","Freedom Day","PT",2017 +"2017-05-01","Labour Day","PT",2017 +"2017-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2017 +"2017-06-15","Corpus Christi","PT",2017 +"2017-08-15","Assumption Day","PT",2017 +"2017-10-05","Republic Day","PT",2017 +"2017-11-01","All Saints Day","PT",2017 +"2017-12-01","Restoration of Independence Day","PT",2017 +"2017-12-08","Immaculate Conception","PT",2017 +"2017-12-25","Christmas","PT",2017 +"2018-01-01","New Year's Day","PT",2018 +"2018-03-30","Good Friday","PT",2018 +"2018-04-01","Easter Sunday","PT",2018 +"2018-04-25","Freedom Day","PT",2018 +"2018-05-01","Labour Day","PT",2018 +"2018-05-31","Corpus Christi","PT",2018 +"2018-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2018 +"2018-08-15","Assumption Day","PT",2018 +"2018-10-05","Republic Day","PT",2018 +"2018-11-01","All Saints Day","PT",2018 +"2018-12-01","Restoration of Independence Day","PT",2018 +"2018-12-08","Immaculate Conception","PT",2018 +"2018-12-25","Christmas","PT",2018 +"2019-01-01","New Year's Day","PT",2019 +"2019-04-19","Good Friday","PT",2019 +"2019-04-21","Easter Sunday","PT",2019 +"2019-04-25","Freedom Day","PT",2019 +"2019-05-01","Labour Day","PT",2019 +"2019-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2019 +"2019-06-20","Corpus Christi","PT",2019 +"2019-08-15","Assumption Day","PT",2019 +"2019-10-05","Republic Day","PT",2019 +"2019-11-01","All Saints Day","PT",2019 +"2019-12-01","Restoration of Independence Day","PT",2019 +"2019-12-08","Immaculate Conception","PT",2019 +"2019-12-25","Christmas","PT",2019 +"2020-01-01","New Year's Day","PT",2020 +"2020-04-10","Good Friday","PT",2020 +"2020-04-12","Easter Sunday","PT",2020 +"2020-04-25","Freedom Day","PT",2020 +"2020-05-01","Labour Day","PT",2020 +"2020-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2020 +"2020-06-11","Corpus Christi","PT",2020 +"2020-08-15","Assumption Day","PT",2020 +"2020-10-05","Republic Day","PT",2020 +"2020-11-01","All Saints Day","PT",2020 +"2020-12-01","Restoration of Independence Day","PT",2020 +"2020-12-08","Immaculate Conception","PT",2020 +"2020-12-25","Christmas","PT",2020 +"2021-01-01","New Year's Day","PT",2021 +"2021-04-02","Good Friday","PT",2021 +"2021-04-04","Easter Sunday","PT",2021 +"2021-04-25","Freedom Day","PT",2021 +"2021-05-01","Labour Day","PT",2021 +"2021-06-03","Corpus Christi","PT",2021 +"2021-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2021 +"2021-08-15","Assumption Day","PT",2021 +"2021-10-05","Republic Day","PT",2021 +"2021-11-01","All Saints Day","PT",2021 +"2021-12-01","Restoration of Independence Day","PT",2021 +"2021-12-08","Immaculate Conception","PT",2021 +"2021-12-25","Christmas","PT",2021 +"2022-01-01","New Year's Day","PT",2022 +"2022-04-15","Good Friday","PT",2022 +"2022-04-17","Easter Sunday","PT",2022 +"2022-04-25","Freedom Day","PT",2022 +"2022-05-01","Labour Day","PT",2022 +"2022-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2022 +"2022-06-16","Corpus Christi","PT",2022 +"2022-08-15","Assumption Day","PT",2022 +"2022-10-05","Republic Day","PT",2022 +"2022-11-01","All Saints Day","PT",2022 +"2022-12-01","Restoration of Independence Day","PT",2022 +"2022-12-08","Immaculate Conception","PT",2022 +"2022-12-25","Christmas","PT",2022 +"2023-01-01","New Year's Day","PT",2023 +"2023-04-07","Good Friday","PT",2023 +"2023-04-09","Easter Sunday","PT",2023 +"2023-04-25","Freedom Day","PT",2023 +"2023-05-01","Labour Day","PT",2023 +"2023-06-08","Corpus Christi","PT",2023 +"2023-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2023 +"2023-08-15","Assumption Day","PT",2023 +"2023-10-05","Republic Day","PT",2023 +"2023-11-01","All Saints Day","PT",2023 +"2023-12-01","Restoration of Independence Day","PT",2023 +"2023-12-08","Immaculate Conception","PT",2023 +"2023-12-25","Christmas","PT",2023 +"2024-01-01","New Year's Day","PT",2024 +"2024-03-29","Good Friday","PT",2024 +"2024-03-31","Easter Sunday","PT",2024 +"2024-04-25","Freedom Day","PT",2024 +"2024-05-01","Labour Day","PT",2024 +"2024-05-30","Corpus Christi","PT",2024 +"2024-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2024 +"2024-08-15","Assumption Day","PT",2024 +"2024-10-05","Republic Day","PT",2024 +"2024-11-01","All Saints Day","PT",2024 +"2024-12-01","Restoration of Independence Day","PT",2024 +"2024-12-08","Immaculate Conception","PT",2024 +"2024-12-25","Christmas","PT",2024 +"2025-01-01","New Year's Day","PT",2025 +"2025-04-18","Good Friday","PT",2025 +"2025-04-20","Easter Sunday","PT",2025 +"2025-04-25","Freedom Day","PT",2025 +"2025-05-01","Labour Day","PT",2025 +"2025-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2025 +"2025-06-19","Corpus Christi","PT",2025 +"2025-08-15","Assumption Day","PT",2025 +"2025-10-05","Republic Day","PT",2025 +"2025-11-01","All Saints Day","PT",2025 +"2025-12-01","Restoration of Independence Day","PT",2025 +"2025-12-08","Immaculate Conception","PT",2025 +"2025-12-25","Christmas","PT",2025 +"2026-01-01","New Year's Day","PT",2026 +"2026-04-03","Good Friday","PT",2026 +"2026-04-05","Easter Sunday","PT",2026 +"2026-04-25","Freedom Day","PT",2026 +"2026-05-01","Labour Day","PT",2026 +"2026-06-04","Corpus Christi","PT",2026 +"2026-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2026 +"2026-08-15","Assumption Day","PT",2026 +"2026-10-05","Republic Day","PT",2026 +"2026-11-01","All Saints Day","PT",2026 +"2026-12-01","Restoration of Independence Day","PT",2026 +"2026-12-08","Immaculate Conception","PT",2026 +"2026-12-25","Christmas","PT",2026 +"2027-01-01","New Year's Day","PT",2027 +"2027-03-26","Good Friday","PT",2027 +"2027-03-28","Easter Sunday","PT",2027 +"2027-04-25","Freedom Day","PT",2027 +"2027-05-01","Labour Day","PT",2027 +"2027-05-27","Corpus Christi","PT",2027 +"2027-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2027 +"2027-08-15","Assumption Day","PT",2027 +"2027-10-05","Republic Day","PT",2027 +"2027-11-01","All Saints Day","PT",2027 +"2027-12-01","Restoration of Independence Day","PT",2027 +"2027-12-08","Immaculate Conception","PT",2027 +"2027-12-25","Christmas","PT",2027 +"2028-01-01","New Year's Day","PT",2028 +"2028-04-14","Good Friday","PT",2028 +"2028-04-16","Easter Sunday","PT",2028 +"2028-04-25","Freedom Day","PT",2028 +"2028-05-01","Labour Day","PT",2028 +"2028-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2028 +"2028-06-15","Corpus Christi","PT",2028 +"2028-08-15","Assumption Day","PT",2028 +"2028-10-05","Republic Day","PT",2028 +"2028-11-01","All Saints Day","PT",2028 +"2028-12-01","Restoration of Independence Day","PT",2028 +"2028-12-08","Immaculate Conception","PT",2028 +"2028-12-25","Christmas","PT",2028 +"2029-01-01","New Year's Day","PT",2029 +"2029-03-30","Good Friday","PT",2029 +"2029-04-01","Easter Sunday","PT",2029 +"2029-04-25","Freedom Day","PT",2029 +"2029-05-01","Labour Day","PT",2029 +"2029-05-31","Corpus Christi","PT",2029 +"2029-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2029 +"2029-08-15","Assumption Day","PT",2029 +"2029-10-05","Republic Day","PT",2029 +"2029-11-01","All Saints Day","PT",2029 +"2029-12-01","Restoration of Independence Day","PT",2029 +"2029-12-08","Immaculate Conception","PT",2029 +"2029-12-25","Christmas","PT",2029 +"2030-01-01","New Year's Day","PT",2030 +"2030-04-19","Good Friday","PT",2030 +"2030-04-21","Easter Sunday","PT",2030 +"2030-04-25","Freedom Day","PT",2030 +"2030-05-01","Labour Day","PT",2030 +"2030-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2030 +"2030-06-20","Corpus Christi","PT",2030 +"2030-08-15","Assumption Day","PT",2030 +"2030-10-05","Republic Day","PT",2030 +"2030-11-01","All Saints Day","PT",2030 +"2030-12-01","Restoration of Independence Day","PT",2030 +"2030-12-08","Immaculate Conception","PT",2030 +"2030-12-25","Christmas","PT",2030 +"2031-01-01","New Year's Day","PT",2031 +"2031-04-11","Good Friday","PT",2031 +"2031-04-13","Easter Sunday","PT",2031 +"2031-04-25","Freedom Day","PT",2031 +"2031-05-01","Labour Day","PT",2031 +"2031-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2031 +"2031-06-12","Corpus Christi","PT",2031 +"2031-08-15","Assumption Day","PT",2031 +"2031-10-05","Republic Day","PT",2031 +"2031-11-01","All Saints Day","PT",2031 +"2031-12-01","Restoration of Independence Day","PT",2031 +"2031-12-08","Immaculate Conception","PT",2031 +"2031-12-25","Christmas","PT",2031 +"2032-01-01","New Year's Day","PT",2032 +"2032-03-26","Good Friday","PT",2032 +"2032-03-28","Easter Sunday","PT",2032 +"2032-04-25","Freedom Day","PT",2032 +"2032-05-01","Labour Day","PT",2032 +"2032-05-27","Corpus Christi","PT",2032 +"2032-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2032 +"2032-08-15","Assumption Day","PT",2032 +"2032-10-05","Republic Day","PT",2032 +"2032-11-01","All Saints Day","PT",2032 +"2032-12-01","Restoration of Independence Day","PT",2032 +"2032-12-08","Immaculate Conception","PT",2032 +"2032-12-25","Christmas","PT",2032 +"2033-01-01","New Year's Day","PT",2033 +"2033-04-15","Good Friday","PT",2033 +"2033-04-17","Easter Sunday","PT",2033 +"2033-04-25","Freedom Day","PT",2033 +"2033-05-01","Labour Day","PT",2033 +"2033-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2033 +"2033-06-16","Corpus Christi","PT",2033 +"2033-08-15","Assumption Day","PT",2033 +"2033-10-05","Republic Day","PT",2033 +"2033-11-01","All Saints Day","PT",2033 +"2033-12-01","Restoration of Independence Day","PT",2033 +"2033-12-08","Immaculate Conception","PT",2033 +"2033-12-25","Christmas","PT",2033 +"2034-01-01","New Year's Day","PT",2034 +"2034-04-07","Good Friday","PT",2034 +"2034-04-09","Easter Sunday","PT",2034 +"2034-04-25","Freedom Day","PT",2034 +"2034-05-01","Labour Day","PT",2034 +"2034-06-08","Corpus Christi","PT",2034 +"2034-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2034 +"2034-08-15","Assumption Day","PT",2034 +"2034-10-05","Republic Day","PT",2034 +"2034-11-01","All Saints Day","PT",2034 +"2034-12-01","Restoration of Independence Day","PT",2034 +"2034-12-08","Immaculate Conception","PT",2034 +"2034-12-25","Christmas","PT",2034 +"2035-01-01","New Year's Day","PT",2035 +"2035-03-23","Good Friday","PT",2035 +"2035-03-25","Easter Sunday","PT",2035 +"2035-04-25","Freedom Day","PT",2035 +"2035-05-01","Labour Day","PT",2035 +"2035-05-24","Corpus Christi","PT",2035 +"2035-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2035 +"2035-08-15","Assumption Day","PT",2035 +"2035-10-05","Republic Day","PT",2035 +"2035-11-01","All Saints Day","PT",2035 +"2035-12-01","Restoration of Independence Day","PT",2035 +"2035-12-08","Immaculate Conception","PT",2035 +"2035-12-25","Christmas","PT",2035 +"2036-01-01","New Year's Day","PT",2036 +"2036-04-11","Good Friday","PT",2036 +"2036-04-13","Easter Sunday","PT",2036 +"2036-04-25","Freedom Day","PT",2036 +"2036-05-01","Labour Day","PT",2036 +"2036-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2036 +"2036-06-12","Corpus Christi","PT",2036 +"2036-08-15","Assumption Day","PT",2036 +"2036-10-05","Republic Day","PT",2036 +"2036-11-01","All Saints Day","PT",2036 +"2036-12-01","Restoration of Independence Day","PT",2036 +"2036-12-08","Immaculate Conception","PT",2036 +"2036-12-25","Christmas","PT",2036 +"2037-01-01","New Year's Day","PT",2037 +"2037-04-03","Good Friday","PT",2037 +"2037-04-05","Easter Sunday","PT",2037 +"2037-04-25","Freedom Day","PT",2037 +"2037-05-01","Labour Day","PT",2037 +"2037-06-04","Corpus Christi","PT",2037 +"2037-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2037 +"2037-08-15","Assumption Day","PT",2037 +"2037-10-05","Republic Day","PT",2037 +"2037-11-01","All Saints Day","PT",2037 +"2037-12-01","Restoration of Independence Day","PT",2037 +"2037-12-08","Immaculate Conception","PT",2037 +"2037-12-25","Christmas","PT",2037 +"2038-01-01","New Year's Day","PT",2038 +"2038-04-23","Good Friday","PT",2038 +"2038-04-25","Easter Sunday","PT",2038 +"2038-04-25","Freedom Day","PT",2038 +"2038-05-01","Labour Day","PT",2038 +"2038-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2038 +"2038-06-24","Corpus Christi","PT",2038 +"2038-08-15","Assumption Day","PT",2038 +"2038-10-05","Republic Day","PT",2038 +"2038-11-01","All Saints Day","PT",2038 +"2038-12-01","Restoration of Independence Day","PT",2038 +"2038-12-08","Immaculate Conception","PT",2038 +"2038-12-25","Christmas","PT",2038 +"2039-01-01","New Year's Day","PT",2039 +"2039-04-08","Good Friday","PT",2039 +"2039-04-10","Easter Sunday","PT",2039 +"2039-04-25","Freedom Day","PT",2039 +"2039-05-01","Labour Day","PT",2039 +"2039-06-09","Corpus Christi","PT",2039 +"2039-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2039 +"2039-08-15","Assumption Day","PT",2039 +"2039-10-05","Republic Day","PT",2039 +"2039-11-01","All Saints Day","PT",2039 +"2039-12-01","Restoration of Independence Day","PT",2039 +"2039-12-08","Immaculate Conception","PT",2039 +"2039-12-25","Christmas","PT",2039 +"2040-01-01","New Year's Day","PT",2040 +"2040-03-30","Good Friday","PT",2040 +"2040-04-01","Easter Sunday","PT",2040 +"2040-04-25","Freedom Day","PT",2040 +"2040-05-01","Labour Day","PT",2040 +"2040-05-31","Corpus Christi","PT",2040 +"2040-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2040 +"2040-08-15","Assumption Day","PT",2040 +"2040-10-05","Republic Day","PT",2040 +"2040-11-01","All Saints Day","PT",2040 +"2040-12-01","Restoration of Independence Day","PT",2040 +"2040-12-08","Immaculate Conception","PT",2040 +"2040-12-25","Christmas","PT",2040 +"2041-01-01","New Year's Day","PT",2041 +"2041-04-19","Good Friday","PT",2041 +"2041-04-21","Easter Sunday","PT",2041 +"2041-04-25","Freedom Day","PT",2041 +"2041-05-01","Labour Day","PT",2041 +"2041-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2041 +"2041-06-20","Corpus Christi","PT",2041 +"2041-08-15","Assumption Day","PT",2041 +"2041-10-05","Republic Day","PT",2041 +"2041-11-01","All Saints Day","PT",2041 +"2041-12-01","Restoration of Independence Day","PT",2041 +"2041-12-08","Immaculate Conception","PT",2041 +"2041-12-25","Christmas","PT",2041 +"2042-01-01","New Year's Day","PT",2042 +"2042-04-04","Good Friday","PT",2042 +"2042-04-06","Easter Sunday","PT",2042 +"2042-04-25","Freedom Day","PT",2042 +"2042-05-01","Labour Day","PT",2042 +"2042-06-05","Corpus Christi","PT",2042 +"2042-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2042 +"2042-08-15","Assumption Day","PT",2042 +"2042-10-05","Republic Day","PT",2042 +"2042-11-01","All Saints Day","PT",2042 +"2042-12-01","Restoration of Independence Day","PT",2042 +"2042-12-08","Immaculate Conception","PT",2042 +"2042-12-25","Christmas","PT",2042 +"2043-01-01","New Year's Day","PT",2043 +"2043-03-27","Good Friday","PT",2043 +"2043-03-29","Easter Sunday","PT",2043 +"2043-04-25","Freedom Day","PT",2043 +"2043-05-01","Labour Day","PT",2043 +"2043-05-28","Corpus Christi","PT",2043 +"2043-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2043 +"2043-08-15","Assumption Day","PT",2043 +"2043-10-05","Republic Day","PT",2043 +"2043-11-01","All Saints Day","PT",2043 +"2043-12-01","Restoration of Independence Day","PT",2043 +"2043-12-08","Immaculate Conception","PT",2043 +"2043-12-25","Christmas","PT",2043 +"2044-01-01","New Year's Day","PT",2044 +"2044-04-15","Good Friday","PT",2044 +"2044-04-17","Easter Sunday","PT",2044 +"2044-04-25","Freedom Day","PT",2044 +"2044-05-01","Labour Day","PT",2044 +"2044-06-10","Day of Portugal, Camoes, and the Portuguese Communities","PT",2044 +"2044-06-16","Corpus Christi","PT",2044 +"2044-08-15","Assumption Day","PT",2044 +"2044-10-05","Republic Day","PT",2044 +"2044-11-01","All Saints Day","PT",2044 +"2044-12-01","Restoration of Independence Day","PT",2044 +"2044-12-08","Immaculate Conception","PT",2044 +"2044-12-25","Christmas","PT",2044 +"1995-01-01","New Year's Day","PY",1995 +"1995-03-01","Patriots Day","PY",1995 +"1995-04-13","Maundy Thursday","PY",1995 +"1995-04-14","Good Friday","PY",1995 +"1995-04-16","Easter Day","PY",1995 +"1995-05-01","Labour Day","PY",1995 +"1995-05-15","Independence Day","PY",1995 +"1995-06-12","Chaco Armistice Day","PY",1995 +"1995-08-15","Asuncion Foundation's Day","PY",1995 +"1995-12-08","Caacupe Virgin Day","PY",1995 +"1995-12-25","Christmas","PY",1995 +"1996-01-01","New Year's Day","PY",1996 +"1996-03-01","Patriots Day","PY",1996 +"1996-04-04","Maundy Thursday","PY",1996 +"1996-04-05","Good Friday","PY",1996 +"1996-04-07","Easter Day","PY",1996 +"1996-05-01","Labour Day","PY",1996 +"1996-05-15","Independence Day","PY",1996 +"1996-06-12","Chaco Armistice Day","PY",1996 +"1996-08-15","Asuncion Foundation's Day","PY",1996 +"1996-12-08","Caacupe Virgin Day","PY",1996 +"1996-12-25","Christmas","PY",1996 +"1997-01-01","New Year's Day","PY",1997 +"1997-03-01","Patriots Day","PY",1997 +"1997-03-27","Maundy Thursday","PY",1997 +"1997-03-28","Good Friday","PY",1997 +"1997-03-30","Easter Day","PY",1997 +"1997-05-01","Labour Day","PY",1997 +"1997-05-15","Independence Day","PY",1997 +"1997-06-12","Chaco Armistice Day","PY",1997 +"1997-08-15","Asuncion Foundation's Day","PY",1997 +"1997-12-08","Caacupe Virgin Day","PY",1997 +"1997-12-25","Christmas","PY",1997 +"1998-01-01","New Year's Day","PY",1998 +"1998-03-01","Patriots Day","PY",1998 +"1998-04-09","Maundy Thursday","PY",1998 +"1998-04-10","Good Friday","PY",1998 +"1998-04-12","Easter Day","PY",1998 +"1998-05-01","Labour Day","PY",1998 +"1998-05-15","Independence Day","PY",1998 +"1998-06-12","Chaco Armistice Day","PY",1998 +"1998-08-15","Asuncion Foundation's Day","PY",1998 +"1998-12-08","Caacupe Virgin Day","PY",1998 +"1998-12-25","Christmas","PY",1998 +"1999-01-01","New Year's Day","PY",1999 +"1999-03-01","Patriots Day","PY",1999 +"1999-04-01","Maundy Thursday","PY",1999 +"1999-04-02","Good Friday","PY",1999 +"1999-04-04","Easter Day","PY",1999 +"1999-05-01","Labour Day","PY",1999 +"1999-05-15","Independence Day","PY",1999 +"1999-06-12","Chaco Armistice Day","PY",1999 +"1999-08-15","Asuncion Foundation's Day","PY",1999 +"1999-12-08","Caacupe Virgin Day","PY",1999 +"1999-12-25","Christmas","PY",1999 +"2000-01-01","New Year's Day","PY",2000 +"2000-03-01","Patriots Day","PY",2000 +"2000-04-20","Maundy Thursday","PY",2000 +"2000-04-21","Good Friday","PY",2000 +"2000-04-23","Easter Day","PY",2000 +"2000-05-01","Labour Day","PY",2000 +"2000-05-15","Independence Day","PY",2000 +"2000-06-12","Chaco Armistice Day","PY",2000 +"2000-08-15","Asuncion Foundation's Day","PY",2000 +"2000-09-29","Boqueron Battle Day","PY",2000 +"2000-12-08","Caacupe Virgin Day","PY",2000 +"2000-12-25","Christmas","PY",2000 +"2001-01-01","New Year's Day","PY",2001 +"2001-03-01","Patriots Day","PY",2001 +"2001-04-12","Maundy Thursday","PY",2001 +"2001-04-13","Good Friday","PY",2001 +"2001-04-15","Easter Day","PY",2001 +"2001-05-01","Labour Day","PY",2001 +"2001-05-15","Independence Day","PY",2001 +"2001-06-12","Chaco Armistice Day","PY",2001 +"2001-08-15","Asuncion Foundation's Day","PY",2001 +"2001-09-29","Boqueron Battle Day","PY",2001 +"2001-12-08","Caacupe Virgin Day","PY",2001 +"2001-12-25","Christmas","PY",2001 +"2002-01-01","New Year's Day","PY",2002 +"2002-03-01","Patriots Day","PY",2002 +"2002-03-28","Maundy Thursday","PY",2002 +"2002-03-29","Good Friday","PY",2002 +"2002-03-31","Easter Day","PY",2002 +"2002-05-01","Labour Day","PY",2002 +"2002-05-15","Independence Day","PY",2002 +"2002-06-12","Chaco Armistice Day","PY",2002 +"2002-08-15","Asuncion Foundation's Day","PY",2002 +"2002-09-29","Boqueron Battle Day","PY",2002 +"2002-12-08","Caacupe Virgin Day","PY",2002 +"2002-12-25","Christmas","PY",2002 +"2003-01-01","New Year's Day","PY",2003 +"2003-03-01","Patriots Day","PY",2003 +"2003-04-17","Maundy Thursday","PY",2003 +"2003-04-18","Good Friday","PY",2003 +"2003-04-20","Easter Day","PY",2003 +"2003-05-01","Labour Day","PY",2003 +"2003-05-15","Independence Day","PY",2003 +"2003-06-12","Chaco Armistice Day","PY",2003 +"2003-08-15","Asuncion Foundation's Day","PY",2003 +"2003-09-29","Boqueron Battle Day","PY",2003 +"2003-12-08","Caacupe Virgin Day","PY",2003 +"2003-12-25","Christmas","PY",2003 +"2004-01-01","New Year's Day","PY",2004 +"2004-03-01","Patriots Day","PY",2004 +"2004-04-08","Maundy Thursday","PY",2004 +"2004-04-09","Good Friday","PY",2004 +"2004-04-11","Easter Day","PY",2004 +"2004-05-01","Labour Day","PY",2004 +"2004-05-15","Independence Day","PY",2004 +"2004-06-12","Chaco Armistice Day","PY",2004 +"2004-08-15","Asuncion Foundation's Day","PY",2004 +"2004-09-29","Boqueron Battle Day","PY",2004 +"2004-12-08","Caacupe Virgin Day","PY",2004 +"2004-12-25","Christmas","PY",2004 +"2005-01-01","New Year's Day","PY",2005 +"2005-03-01","Patriots Day","PY",2005 +"2005-03-24","Maundy Thursday","PY",2005 +"2005-03-25","Good Friday","PY",2005 +"2005-03-27","Easter Day","PY",2005 +"2005-05-01","Labour Day","PY",2005 +"2005-05-15","Independence Day","PY",2005 +"2005-06-12","Chaco Armistice Day","PY",2005 +"2005-08-15","Asuncion Foundation's Day","PY",2005 +"2005-09-29","Boqueron Battle Day","PY",2005 +"2005-12-08","Caacupe Virgin Day","PY",2005 +"2005-12-25","Christmas","PY",2005 +"2006-01-01","New Year's Day","PY",2006 +"2006-03-01","Patriots Day","PY",2006 +"2006-04-13","Maundy Thursday","PY",2006 +"2006-04-14","Good Friday","PY",2006 +"2006-04-16","Easter Day","PY",2006 +"2006-05-01","Labour Day","PY",2006 +"2006-05-15","Independence Day","PY",2006 +"2006-06-12","Chaco Armistice Day","PY",2006 +"2006-08-15","Asuncion Foundation's Day","PY",2006 +"2006-09-29","Boqueron Battle Day","PY",2006 +"2006-12-08","Caacupe Virgin Day","PY",2006 +"2006-12-25","Christmas","PY",2006 +"2007-01-01","New Year's Day","PY",2007 +"2007-01-29","Public holiday","PY",2007 +"2007-03-01","Patriots Day","PY",2007 +"2007-04-05","Maundy Thursday","PY",2007 +"2007-04-06","Good Friday","PY",2007 +"2007-04-08","Easter Day","PY",2007 +"2007-05-01","Labour Day","PY",2007 +"2007-05-15","Independence Day","PY",2007 +"2007-06-12","Chaco Armistice Day","PY",2007 +"2007-08-15","Asuncion Foundation's Day","PY",2007 +"2007-09-29","Boqueron Battle Day","PY",2007 +"2007-12-08","Caacupe Virgin Day","PY",2007 +"2007-12-25","Christmas","PY",2007 +"2008-01-01","New Year's Day","PY",2008 +"2008-03-01","Patriots Day","PY",2008 +"2008-03-20","Maundy Thursday","PY",2008 +"2008-03-21","Good Friday","PY",2008 +"2008-03-23","Easter Day","PY",2008 +"2008-05-01","Labour Day","PY",2008 +"2008-05-15","Independence Day","PY",2008 +"2008-06-12","Chaco Armistice Day","PY",2008 +"2008-08-15","Asuncion Foundation's Day","PY",2008 +"2008-09-29","Boqueron Battle Day","PY",2008 +"2008-12-08","Caacupe Virgin Day","PY",2008 +"2008-12-25","Christmas","PY",2008 +"2009-01-01","New Year's Day","PY",2009 +"2009-03-01","Patriots Day","PY",2009 +"2009-04-09","Maundy Thursday","PY",2009 +"2009-04-10","Good Friday","PY",2009 +"2009-04-12","Easter Day","PY",2009 +"2009-05-01","Labour Day","PY",2009 +"2009-05-15","Independence Day","PY",2009 +"2009-06-12","Chaco Armistice Day","PY",2009 +"2009-08-15","Asuncion Foundation's Day","PY",2009 +"2009-09-10","Public holiday","PY",2009 +"2009-09-29","Boqueron Battle Day","PY",2009 +"2009-12-08","Caacupe Virgin Day","PY",2009 +"2009-12-25","Christmas","PY",2009 +"2010-01-01","New Year's Day","PY",2010 +"2010-03-01","Patriots Day","PY",2010 +"2010-04-01","Maundy Thursday","PY",2010 +"2010-04-02","Good Friday","PY",2010 +"2010-04-04","Easter Day","PY",2010 +"2010-05-01","Labour Day","PY",2010 +"2010-05-15","Independence Day","PY",2010 +"2010-06-12","Chaco Armistice Day","PY",2010 +"2010-06-14","Public holiday","PY",2010 +"2010-08-15","Asuncion Foundation's Day","PY",2010 +"2010-09-29","Boqueron Battle Day","PY",2010 +"2010-12-08","Caacupe Virgin Day","PY",2010 +"2010-12-24","Public sector holiday","PY",2010 +"2010-12-25","Christmas","PY",2010 +"2010-12-31","Public sector holiday","PY",2010 +"2011-01-01","New Year's Day","PY",2011 +"2011-03-01","Patriots Day","PY",2011 +"2011-04-19","Public holiday","PY",2011 +"2011-04-20","Public sector holiday","PY",2011 +"2011-04-21","Maundy Thursday","PY",2011 +"2011-04-22","Good Friday","PY",2011 +"2011-04-24","Easter Day","PY",2011 +"2011-05-01","Labour Day","PY",2011 +"2011-05-14","Public holiday","PY",2011 +"2011-05-15","Independence Day","PY",2011 +"2011-05-16","Public holiday","PY",2011 +"2011-06-12","Chaco Armistice Day","PY",2011 +"2011-08-15","Asuncion Foundation's Day","PY",2011 +"2011-09-29","Boqueron Battle Day","PY",2011 +"2011-12-08","Caacupe Virgin Day","PY",2011 +"2011-12-23","Public sector holiday","PY",2011 +"2011-12-25","Christmas","PY",2011 +"2011-12-30","Public sector holiday","PY",2011 +"2012-01-01","New Year's Day","PY",2012 +"2012-03-01","Patriots Day","PY",2012 +"2012-04-04","Public sector holiday","PY",2012 +"2012-04-05","Maundy Thursday","PY",2012 +"2012-04-06","Good Friday","PY",2012 +"2012-04-08","Easter Day","PY",2012 +"2012-05-01","Labour Day","PY",2012 +"2012-05-14","Independence Day","PY",2012 +"2012-05-15","Independence Day","PY",2012 +"2012-06-12","Chaco Armistice Day","PY",2012 +"2012-08-15","Asuncion Foundation's Day","PY",2012 +"2012-09-29","Boqueron Battle Day","PY",2012 +"2012-12-08","Caacupe Virgin Day","PY",2012 +"2012-12-24","Public sector holiday","PY",2012 +"2012-12-25","Christmas","PY",2012 +"2012-12-31","Public sector holiday","PY",2012 +"2013-01-01","New Year's Day","PY",2013 +"2013-03-04","Patriots Day","PY",2013 +"2013-03-27","Public sector holiday","PY",2013 +"2013-03-28","Maundy Thursday","PY",2013 +"2013-03-29","Good Friday","PY",2013 +"2013-03-31","Easter Day","PY",2013 +"2013-05-01","Labour Day","PY",2013 +"2013-05-14","Independence Day","PY",2013 +"2013-05-15","Independence Day","PY",2013 +"2013-06-12","Chaco Armistice Day","PY",2013 +"2013-08-14","Public holiday","PY",2013 +"2013-08-15","Asuncion Foundation's Day","PY",2013 +"2013-09-29","Boqueron Battle Day","PY",2013 +"2013-12-08","Caacupe Virgin Day","PY",2013 +"2013-12-25","Christmas","PY",2013 +"2014-01-01","New Year's Day","PY",2014 +"2014-03-01","Patriots Day","PY",2014 +"2014-04-16","Public sector holiday","PY",2014 +"2014-04-17","Maundy Thursday","PY",2014 +"2014-04-18","Good Friday","PY",2014 +"2014-04-20","Easter Day","PY",2014 +"2014-05-01","Labour Day","PY",2014 +"2014-05-14","Independence Day","PY",2014 +"2014-05-15","Independence Day","PY",2014 +"2014-06-16","Chaco Armistice Day","PY",2014 +"2014-08-15","Asuncion Foundation's Day","PY",2014 +"2014-09-29","Boqueron Battle Day","PY",2014 +"2014-12-08","Caacupe Virgin Day","PY",2014 +"2014-12-24","Public sector holiday","PY",2014 +"2014-12-25","Christmas","PY",2014 +"2014-12-31","Public sector holiday","PY",2014 +"2015-01-01","New Year's Day","PY",2015 +"2015-03-01","Patriots Day","PY",2015 +"2015-04-01","Public sector holiday","PY",2015 +"2015-04-02","Maundy Thursday","PY",2015 +"2015-04-03","Good Friday","PY",2015 +"2015-04-05","Easter Day","PY",2015 +"2015-05-01","Labour Day","PY",2015 +"2015-05-14","Independence Day","PY",2015 +"2015-05-15","Independence Day","PY",2015 +"2015-06-12","Chaco Armistice Day","PY",2015 +"2015-07-10","Public holiday","PY",2015 +"2015-07-11","Public holiday","PY",2015 +"2015-08-15","Asuncion Foundation's Day","PY",2015 +"2015-09-28","Boqueron Battle Day","PY",2015 +"2015-12-08","Caacupe Virgin Day","PY",2015 +"2015-12-24","Public sector holiday","PY",2015 +"2015-12-25","Christmas","PY",2015 +"2015-12-31","Public sector holiday","PY",2015 +"2016-01-01","New Year's Day","PY",2016 +"2016-02-29","Patriots Day","PY",2016 +"2016-03-23","Public sector holiday","PY",2016 +"2016-03-24","Maundy Thursday","PY",2016 +"2016-03-25","Good Friday","PY",2016 +"2016-03-27","Easter Day","PY",2016 +"2016-05-01","Labour Day","PY",2016 +"2016-05-14","Independence Day","PY",2016 +"2016-05-15","Independence Day","PY",2016 +"2016-06-12","Chaco Armistice Day","PY",2016 +"2016-08-15","Asuncion Foundation's Day","PY",2016 +"2016-10-03","Boqueron Battle Day","PY",2016 +"2016-12-08","Caacupe Virgin Day","PY",2016 +"2016-12-25","Christmas","PY",2016 +"2017-01-01","New Year's Day","PY",2017 +"2017-03-01","Patriots Day","PY",2017 +"2017-03-28","Public sector holiday","PY",2017 +"2017-04-13","Maundy Thursday","PY",2017 +"2017-04-14","Good Friday","PY",2017 +"2017-04-16","Easter Day","PY",2017 +"2017-05-01","Labour Day","PY",2017 +"2017-05-14","Independence Day","PY",2017 +"2017-05-15","Independence Day","PY",2017 +"2017-06-12","Chaco Armistice Day","PY",2017 +"2017-08-15","Asuncion Foundation's Day","PY",2017 +"2017-10-02","Boqueron Battle Day","PY",2017 +"2017-12-08","Caacupe Virgin Day","PY",2017 +"2017-12-25","Christmas","PY",2017 +"2018-01-01","New Year's Day","PY",2018 +"2018-02-26","Patriots Day","PY",2018 +"2018-03-29","Maundy Thursday","PY",2018 +"2018-03-30","Good Friday","PY",2018 +"2018-04-01","Easter Day","PY",2018 +"2018-05-01","Labour Day","PY",2018 +"2018-05-14","Independence Day","PY",2018 +"2018-05-15","Independence Day","PY",2018 +"2018-06-11","Chaco Armistice Day","PY",2018 +"2018-08-15","Asuncion Foundation's Day","PY",2018 +"2018-09-29","Boqueron Battle Day","PY",2018 +"2018-12-08","Caacupe Virgin Day","PY",2018 +"2018-12-24","Public sector holiday","PY",2018 +"2018-12-25","Christmas","PY",2018 +"2018-12-31","Public sector holiday","PY",2018 +"2019-01-01","New Year's Day","PY",2019 +"2019-03-01","Patriots Day","PY",2019 +"2019-04-17","Public sector holiday","PY",2019 +"2019-04-18","Maundy Thursday","PY",2019 +"2019-04-19","Good Friday","PY",2019 +"2019-04-21","Easter Day","PY",2019 +"2019-05-01","Labour Day","PY",2019 +"2019-05-14","Independence Day","PY",2019 +"2019-05-15","Independence Day","PY",2019 +"2019-06-12","Chaco Armistice Day","PY",2019 +"2019-08-15","Asuncion Foundation's Day","PY",2019 +"2019-09-29","Boqueron Battle Day","PY",2019 +"2019-12-08","Caacupe Virgin Day","PY",2019 +"2019-12-24","Public sector holiday","PY",2019 +"2019-12-25","Christmas","PY",2019 +"2019-12-31","Public sector holiday","PY",2019 +"2020-01-01","New Year's Day","PY",2020 +"2020-03-01","Patriots Day","PY",2020 +"2020-04-08","Public sector holiday","PY",2020 +"2020-04-09","Maundy Thursday","PY",2020 +"2020-04-10","Good Friday","PY",2020 +"2020-04-12","Easter Day","PY",2020 +"2020-05-01","Labour Day","PY",2020 +"2020-05-14","Independence Day","PY",2020 +"2020-05-15","Independence Day","PY",2020 +"2020-06-12","Chaco Armistice Day","PY",2020 +"2020-08-15","Asuncion Foundation's Day","PY",2020 +"2020-09-29","Boqueron Battle Day","PY",2020 +"2020-12-08","Caacupe Virgin Day","PY",2020 +"2020-12-25","Christmas","PY",2020 +"2021-01-01","New Year's Day","PY",2021 +"2021-03-01","Patriots Day","PY",2021 +"2021-04-01","Maundy Thursday","PY",2021 +"2021-04-02","Good Friday","PY",2021 +"2021-04-04","Easter Day","PY",2021 +"2021-05-01","Labour Day","PY",2021 +"2021-05-14","Independence Day","PY",2021 +"2021-05-15","Independence Day","PY",2021 +"2021-06-12","Chaco Armistice Day","PY",2021 +"2021-08-15","Asuncion Foundation's Day","PY",2021 +"2021-09-27","Boqueron Battle Day","PY",2021 +"2021-12-08","Caacupe Virgin Day","PY",2021 +"2021-12-24","Public sector holiday","PY",2021 +"2021-12-25","Christmas","PY",2021 +"2021-12-31","Public sector holiday","PY",2021 +"2022-01-01","New Year's Day","PY",2022 +"2022-02-28","Patriots Day","PY",2022 +"2022-04-13","Public sector holiday","PY",2022 +"2022-04-14","Maundy Thursday","PY",2022 +"2022-04-15","Good Friday","PY",2022 +"2022-04-17","Easter Day","PY",2022 +"2022-05-01","Labour Day","PY",2022 +"2022-05-02","Public sector holiday","PY",2022 +"2022-05-14","Independence Day","PY",2022 +"2022-05-15","Independence Day","PY",2022 +"2022-06-12","Chaco Armistice Day","PY",2022 +"2022-08-15","Asuncion Foundation's Day","PY",2022 +"2022-10-03","Boqueron Battle Day","PY",2022 +"2022-12-08","Caacupe Virgin Day","PY",2022 +"2022-12-25","Christmas","PY",2022 +"2023-01-01","New Year's Day","PY",2023 +"2023-03-01","Patriots Day","PY",2023 +"2023-04-06","Maundy Thursday","PY",2023 +"2023-04-07","Good Friday","PY",2023 +"2023-04-09","Easter Day","PY",2023 +"2023-05-01","Labour Day","PY",2023 +"2023-05-14","Independence Day","PY",2023 +"2023-05-15","Independence Day","PY",2023 +"2023-06-12","Chaco Armistice Day","PY",2023 +"2023-08-15","Asuncion Foundation's Day","PY",2023 +"2023-09-29","Boqueron Battle Day","PY",2023 +"2023-12-08","Caacupe Virgin Day","PY",2023 +"2023-12-25","Christmas","PY",2023 +"2024-01-01","New Year's Day","PY",2024 +"2024-03-01","Patriots Day","PY",2024 +"2024-03-28","Maundy Thursday","PY",2024 +"2024-03-29","Good Friday","PY",2024 +"2024-03-31","Easter Day","PY",2024 +"2024-05-01","Labour Day","PY",2024 +"2024-05-14","Independence Day","PY",2024 +"2024-05-15","Independence Day","PY",2024 +"2024-06-12","Chaco Armistice Day","PY",2024 +"2024-08-15","Asuncion Foundation's Day","PY",2024 +"2024-09-29","Boqueron Battle Day","PY",2024 +"2024-12-08","Caacupe Virgin Day","PY",2024 +"2024-12-25","Christmas","PY",2024 +"2025-01-01","New Year's Day","PY",2025 +"2025-03-01","Patriots Day","PY",2025 +"2025-04-17","Maundy Thursday","PY",2025 +"2025-04-18","Good Friday","PY",2025 +"2025-04-20","Easter Day","PY",2025 +"2025-05-01","Labour Day","PY",2025 +"2025-05-14","Independence Day","PY",2025 +"2025-05-15","Independence Day","PY",2025 +"2025-06-12","Chaco Armistice Day","PY",2025 +"2025-08-15","Asuncion Foundation's Day","PY",2025 +"2025-09-29","Boqueron Battle Day","PY",2025 +"2025-12-08","Caacupe Virgin Day","PY",2025 +"2025-12-25","Christmas","PY",2025 +"2026-01-01","New Year's Day","PY",2026 +"2026-03-01","Patriots Day","PY",2026 +"2026-04-02","Maundy Thursday","PY",2026 +"2026-04-03","Good Friday","PY",2026 +"2026-04-05","Easter Day","PY",2026 +"2026-05-01","Labour Day","PY",2026 +"2026-05-14","Independence Day","PY",2026 +"2026-05-15","Independence Day","PY",2026 +"2026-06-12","Chaco Armistice Day","PY",2026 +"2026-08-15","Asuncion Foundation's Day","PY",2026 +"2026-09-29","Boqueron Battle Day","PY",2026 +"2026-12-08","Caacupe Virgin Day","PY",2026 +"2026-12-25","Christmas","PY",2026 +"2027-01-01","New Year's Day","PY",2027 +"2027-03-01","Patriots Day","PY",2027 +"2027-03-25","Maundy Thursday","PY",2027 +"2027-03-26","Good Friday","PY",2027 +"2027-03-28","Easter Day","PY",2027 +"2027-05-01","Labour Day","PY",2027 +"2027-05-14","Independence Day","PY",2027 +"2027-05-15","Independence Day","PY",2027 +"2027-06-12","Chaco Armistice Day","PY",2027 +"2027-08-15","Asuncion Foundation's Day","PY",2027 +"2027-09-29","Boqueron Battle Day","PY",2027 +"2027-12-08","Caacupe Virgin Day","PY",2027 +"2027-12-25","Christmas","PY",2027 +"2028-01-01","New Year's Day","PY",2028 +"2028-03-01","Patriots Day","PY",2028 +"2028-04-13","Maundy Thursday","PY",2028 +"2028-04-14","Good Friday","PY",2028 +"2028-04-16","Easter Day","PY",2028 +"2028-05-01","Labour Day","PY",2028 +"2028-05-14","Independence Day","PY",2028 +"2028-05-15","Independence Day","PY",2028 +"2028-06-12","Chaco Armistice Day","PY",2028 +"2028-08-15","Asuncion Foundation's Day","PY",2028 +"2028-09-29","Boqueron Battle Day","PY",2028 +"2028-12-08","Caacupe Virgin Day","PY",2028 +"2028-12-25","Christmas","PY",2028 +"2029-01-01","New Year's Day","PY",2029 +"2029-03-01","Patriots Day","PY",2029 +"2029-03-29","Maundy Thursday","PY",2029 +"2029-03-30","Good Friday","PY",2029 +"2029-04-01","Easter Day","PY",2029 +"2029-05-01","Labour Day","PY",2029 +"2029-05-14","Independence Day","PY",2029 +"2029-05-15","Independence Day","PY",2029 +"2029-06-12","Chaco Armistice Day","PY",2029 +"2029-08-15","Asuncion Foundation's Day","PY",2029 +"2029-09-29","Boqueron Battle Day","PY",2029 +"2029-12-08","Caacupe Virgin Day","PY",2029 +"2029-12-25","Christmas","PY",2029 +"2030-01-01","New Year's Day","PY",2030 +"2030-03-01","Patriots Day","PY",2030 +"2030-04-18","Maundy Thursday","PY",2030 +"2030-04-19","Good Friday","PY",2030 +"2030-04-21","Easter Day","PY",2030 +"2030-05-01","Labour Day","PY",2030 +"2030-05-14","Independence Day","PY",2030 +"2030-05-15","Independence Day","PY",2030 +"2030-06-12","Chaco Armistice Day","PY",2030 +"2030-08-15","Asuncion Foundation's Day","PY",2030 +"2030-09-29","Boqueron Battle Day","PY",2030 +"2030-12-08","Caacupe Virgin Day","PY",2030 +"2030-12-25","Christmas","PY",2030 +"2031-01-01","New Year's Day","PY",2031 +"2031-03-01","Patriots Day","PY",2031 +"2031-04-10","Maundy Thursday","PY",2031 +"2031-04-11","Good Friday","PY",2031 +"2031-04-13","Easter Day","PY",2031 +"2031-05-01","Labour Day","PY",2031 +"2031-05-14","Independence Day","PY",2031 +"2031-05-15","Independence Day","PY",2031 +"2031-06-12","Chaco Armistice Day","PY",2031 +"2031-08-15","Asuncion Foundation's Day","PY",2031 +"2031-09-29","Boqueron Battle Day","PY",2031 +"2031-12-08","Caacupe Virgin Day","PY",2031 +"2031-12-25","Christmas","PY",2031 +"2032-01-01","New Year's Day","PY",2032 +"2032-03-01","Patriots Day","PY",2032 +"2032-03-25","Maundy Thursday","PY",2032 +"2032-03-26","Good Friday","PY",2032 +"2032-03-28","Easter Day","PY",2032 +"2032-05-01","Labour Day","PY",2032 +"2032-05-14","Independence Day","PY",2032 +"2032-05-15","Independence Day","PY",2032 +"2032-06-12","Chaco Armistice Day","PY",2032 +"2032-08-15","Asuncion Foundation's Day","PY",2032 +"2032-09-29","Boqueron Battle Day","PY",2032 +"2032-12-08","Caacupe Virgin Day","PY",2032 +"2032-12-25","Christmas","PY",2032 +"2033-01-01","New Year's Day","PY",2033 +"2033-03-01","Patriots Day","PY",2033 +"2033-04-14","Maundy Thursday","PY",2033 +"2033-04-15","Good Friday","PY",2033 +"2033-04-17","Easter Day","PY",2033 +"2033-05-01","Labour Day","PY",2033 +"2033-05-14","Independence Day","PY",2033 +"2033-05-15","Independence Day","PY",2033 +"2033-06-12","Chaco Armistice Day","PY",2033 +"2033-08-15","Asuncion Foundation's Day","PY",2033 +"2033-09-29","Boqueron Battle Day","PY",2033 +"2033-12-08","Caacupe Virgin Day","PY",2033 +"2033-12-25","Christmas","PY",2033 +"2034-01-01","New Year's Day","PY",2034 +"2034-03-01","Patriots Day","PY",2034 +"2034-04-06","Maundy Thursday","PY",2034 +"2034-04-07","Good Friday","PY",2034 +"2034-04-09","Easter Day","PY",2034 +"2034-05-01","Labour Day","PY",2034 +"2034-05-14","Independence Day","PY",2034 +"2034-05-15","Independence Day","PY",2034 +"2034-06-12","Chaco Armistice Day","PY",2034 +"2034-08-15","Asuncion Foundation's Day","PY",2034 +"2034-09-29","Boqueron Battle Day","PY",2034 +"2034-12-08","Caacupe Virgin Day","PY",2034 +"2034-12-25","Christmas","PY",2034 +"2035-01-01","New Year's Day","PY",2035 +"2035-03-01","Patriots Day","PY",2035 +"2035-03-22","Maundy Thursday","PY",2035 +"2035-03-23","Good Friday","PY",2035 +"2035-03-25","Easter Day","PY",2035 +"2035-05-01","Labour Day","PY",2035 +"2035-05-14","Independence Day","PY",2035 +"2035-05-15","Independence Day","PY",2035 +"2035-06-12","Chaco Armistice Day","PY",2035 +"2035-08-15","Asuncion Foundation's Day","PY",2035 +"2035-09-29","Boqueron Battle Day","PY",2035 +"2035-12-08","Caacupe Virgin Day","PY",2035 +"2035-12-25","Christmas","PY",2035 +"2036-01-01","New Year's Day","PY",2036 +"2036-03-01","Patriots Day","PY",2036 +"2036-04-10","Maundy Thursday","PY",2036 +"2036-04-11","Good Friday","PY",2036 +"2036-04-13","Easter Day","PY",2036 +"2036-05-01","Labour Day","PY",2036 +"2036-05-14","Independence Day","PY",2036 +"2036-05-15","Independence Day","PY",2036 +"2036-06-12","Chaco Armistice Day","PY",2036 +"2036-08-15","Asuncion Foundation's Day","PY",2036 +"2036-09-29","Boqueron Battle Day","PY",2036 +"2036-12-08","Caacupe Virgin Day","PY",2036 +"2036-12-25","Christmas","PY",2036 +"2037-01-01","New Year's Day","PY",2037 +"2037-03-01","Patriots Day","PY",2037 +"2037-04-02","Maundy Thursday","PY",2037 +"2037-04-03","Good Friday","PY",2037 +"2037-04-05","Easter Day","PY",2037 +"2037-05-01","Labour Day","PY",2037 +"2037-05-14","Independence Day","PY",2037 +"2037-05-15","Independence Day","PY",2037 +"2037-06-12","Chaco Armistice Day","PY",2037 +"2037-08-15","Asuncion Foundation's Day","PY",2037 +"2037-09-29","Boqueron Battle Day","PY",2037 +"2037-12-08","Caacupe Virgin Day","PY",2037 +"2037-12-25","Christmas","PY",2037 +"2038-01-01","New Year's Day","PY",2038 +"2038-03-01","Patriots Day","PY",2038 +"2038-04-22","Maundy Thursday","PY",2038 +"2038-04-23","Good Friday","PY",2038 +"2038-04-25","Easter Day","PY",2038 +"2038-05-01","Labour Day","PY",2038 +"2038-05-14","Independence Day","PY",2038 +"2038-05-15","Independence Day","PY",2038 +"2038-06-12","Chaco Armistice Day","PY",2038 +"2038-08-15","Asuncion Foundation's Day","PY",2038 +"2038-09-29","Boqueron Battle Day","PY",2038 +"2038-12-08","Caacupe Virgin Day","PY",2038 +"2038-12-25","Christmas","PY",2038 +"2039-01-01","New Year's Day","PY",2039 +"2039-03-01","Patriots Day","PY",2039 +"2039-04-07","Maundy Thursday","PY",2039 +"2039-04-08","Good Friday","PY",2039 +"2039-04-10","Easter Day","PY",2039 +"2039-05-01","Labour Day","PY",2039 +"2039-05-14","Independence Day","PY",2039 +"2039-05-15","Independence Day","PY",2039 +"2039-06-12","Chaco Armistice Day","PY",2039 +"2039-08-15","Asuncion Foundation's Day","PY",2039 +"2039-09-29","Boqueron Battle Day","PY",2039 +"2039-12-08","Caacupe Virgin Day","PY",2039 +"2039-12-25","Christmas","PY",2039 +"2040-01-01","New Year's Day","PY",2040 +"2040-03-01","Patriots Day","PY",2040 +"2040-03-29","Maundy Thursday","PY",2040 +"2040-03-30","Good Friday","PY",2040 +"2040-04-01","Easter Day","PY",2040 +"2040-05-01","Labour Day","PY",2040 +"2040-05-14","Independence Day","PY",2040 +"2040-05-15","Independence Day","PY",2040 +"2040-06-12","Chaco Armistice Day","PY",2040 +"2040-08-15","Asuncion Foundation's Day","PY",2040 +"2040-09-29","Boqueron Battle Day","PY",2040 +"2040-12-08","Caacupe Virgin Day","PY",2040 +"2040-12-25","Christmas","PY",2040 +"2041-01-01","New Year's Day","PY",2041 +"2041-03-01","Patriots Day","PY",2041 +"2041-04-18","Maundy Thursday","PY",2041 +"2041-04-19","Good Friday","PY",2041 +"2041-04-21","Easter Day","PY",2041 +"2041-05-01","Labour Day","PY",2041 +"2041-05-14","Independence Day","PY",2041 +"2041-05-15","Independence Day","PY",2041 +"2041-06-12","Chaco Armistice Day","PY",2041 +"2041-08-15","Asuncion Foundation's Day","PY",2041 +"2041-09-29","Boqueron Battle Day","PY",2041 +"2041-12-08","Caacupe Virgin Day","PY",2041 +"2041-12-25","Christmas","PY",2041 +"2042-01-01","New Year's Day","PY",2042 +"2042-03-01","Patriots Day","PY",2042 +"2042-04-03","Maundy Thursday","PY",2042 +"2042-04-04","Good Friday","PY",2042 +"2042-04-06","Easter Day","PY",2042 +"2042-05-01","Labour Day","PY",2042 +"2042-05-14","Independence Day","PY",2042 +"2042-05-15","Independence Day","PY",2042 +"2042-06-12","Chaco Armistice Day","PY",2042 +"2042-08-15","Asuncion Foundation's Day","PY",2042 +"2042-09-29","Boqueron Battle Day","PY",2042 +"2042-12-08","Caacupe Virgin Day","PY",2042 +"2042-12-25","Christmas","PY",2042 +"2043-01-01","New Year's Day","PY",2043 +"2043-03-01","Patriots Day","PY",2043 +"2043-03-26","Maundy Thursday","PY",2043 +"2043-03-27","Good Friday","PY",2043 +"2043-03-29","Easter Day","PY",2043 +"2043-05-01","Labour Day","PY",2043 +"2043-05-14","Independence Day","PY",2043 +"2043-05-15","Independence Day","PY",2043 +"2043-06-12","Chaco Armistice Day","PY",2043 +"2043-08-15","Asuncion Foundation's Day","PY",2043 +"2043-09-29","Boqueron Battle Day","PY",2043 +"2043-12-08","Caacupe Virgin Day","PY",2043 +"2043-12-25","Christmas","PY",2043 +"2044-01-01","New Year's Day","PY",2044 +"2044-03-01","Patriots Day","PY",2044 +"2044-04-14","Maundy Thursday","PY",2044 +"2044-04-15","Good Friday","PY",2044 +"2044-04-17","Easter Day","PY",2044 +"2044-05-01","Labour Day","PY",2044 +"2044-05-14","Independence Day","PY",2044 +"2044-05-15","Independence Day","PY",2044 +"2044-06-12","Chaco Armistice Day","PY",2044 +"2044-08-15","Asuncion Foundation's Day","PY",2044 +"2044-09-29","Boqueron Battle Day","PY",2044 +"2044-12-08","Caacupe Virgin Day","PY",2044 +"2044-12-25","Christmas","PY",2044 +"1995-01-01","New Year's Day","RO",1995 +"1995-01-02","New Year's Day","RO",1995 +"1995-04-23","Easter","RO",1995 +"1995-04-24","Easter","RO",1995 +"1995-05-01","Labour Day","RO",1995 +"1995-06-11","Pentecost","RO",1995 +"1995-06-12","Pentecost","RO",1995 +"1995-12-01","National Day","RO",1995 +"1995-12-25","Christmas Day","RO",1995 +"1995-12-26","Christmas Day","RO",1995 +"1996-01-01","New Year's Day","RO",1996 +"1996-01-02","New Year's Day","RO",1996 +"1996-04-14","Easter","RO",1996 +"1996-04-15","Easter","RO",1996 +"1996-05-01","Labour Day","RO",1996 +"1996-06-02","Pentecost","RO",1996 +"1996-06-03","Pentecost","RO",1996 +"1996-12-01","National Day","RO",1996 +"1996-12-25","Christmas Day","RO",1996 +"1996-12-26","Christmas Day","RO",1996 +"1997-01-01","New Year's Day","RO",1997 +"1997-01-02","New Year's Day","RO",1997 +"1997-04-27","Easter","RO",1997 +"1997-04-28","Easter","RO",1997 +"1997-05-01","Labour Day","RO",1997 +"1997-06-15","Pentecost","RO",1997 +"1997-06-16","Pentecost","RO",1997 +"1997-12-01","National Day","RO",1997 +"1997-12-25","Christmas Day","RO",1997 +"1997-12-26","Christmas Day","RO",1997 +"1998-01-01","New Year's Day","RO",1998 +"1998-01-02","New Year's Day","RO",1998 +"1998-04-19","Easter","RO",1998 +"1998-04-20","Easter","RO",1998 +"1998-05-01","Labour Day","RO",1998 +"1998-06-07","Pentecost","RO",1998 +"1998-06-08","Pentecost","RO",1998 +"1998-12-01","National Day","RO",1998 +"1998-12-25","Christmas Day","RO",1998 +"1998-12-26","Christmas Day","RO",1998 +"1999-01-01","New Year's Day","RO",1999 +"1999-01-02","New Year's Day","RO",1999 +"1999-04-11","Easter","RO",1999 +"1999-04-12","Easter","RO",1999 +"1999-05-01","Labour Day","RO",1999 +"1999-05-30","Pentecost","RO",1999 +"1999-05-31","Pentecost","RO",1999 +"1999-12-01","National Day","RO",1999 +"1999-12-25","Christmas Day","RO",1999 +"1999-12-26","Christmas Day","RO",1999 +"2000-01-01","New Year's Day","RO",2000 +"2000-01-02","New Year's Day","RO",2000 +"2000-04-30","Easter","RO",2000 +"2000-05-01","Easter","RO",2000 +"2000-05-01","Labour Day","RO",2000 +"2000-06-18","Pentecost","RO",2000 +"2000-06-19","Pentecost","RO",2000 +"2000-12-01","National Day","RO",2000 +"2000-12-25","Christmas Day","RO",2000 +"2000-12-26","Christmas Day","RO",2000 +"2001-01-01","New Year's Day","RO",2001 +"2001-01-02","New Year's Day","RO",2001 +"2001-04-15","Easter","RO",2001 +"2001-04-16","Easter","RO",2001 +"2001-05-01","Labour Day","RO",2001 +"2001-06-03","Pentecost","RO",2001 +"2001-06-04","Pentecost","RO",2001 +"2001-12-01","National Day","RO",2001 +"2001-12-25","Christmas Day","RO",2001 +"2001-12-26","Christmas Day","RO",2001 +"2002-01-01","New Year's Day","RO",2002 +"2002-01-02","New Year's Day","RO",2002 +"2002-05-01","Labour Day","RO",2002 +"2002-05-05","Easter","RO",2002 +"2002-05-06","Easter","RO",2002 +"2002-06-23","Pentecost","RO",2002 +"2002-06-24","Pentecost","RO",2002 +"2002-12-01","National Day","RO",2002 +"2002-12-25","Christmas Day","RO",2002 +"2002-12-26","Christmas Day","RO",2002 +"2003-01-01","New Year's Day","RO",2003 +"2003-01-02","New Year's Day","RO",2003 +"2003-04-27","Easter","RO",2003 +"2003-04-28","Easter","RO",2003 +"2003-05-01","Labour Day","RO",2003 +"2003-06-15","Pentecost","RO",2003 +"2003-06-16","Pentecost","RO",2003 +"2003-12-01","National Day","RO",2003 +"2003-12-25","Christmas Day","RO",2003 +"2003-12-26","Christmas Day","RO",2003 +"2004-01-01","New Year's Day","RO",2004 +"2004-01-02","New Year's Day","RO",2004 +"2004-04-11","Easter","RO",2004 +"2004-04-12","Easter","RO",2004 +"2004-05-01","Labour Day","RO",2004 +"2004-05-30","Pentecost","RO",2004 +"2004-05-31","Pentecost","RO",2004 +"2004-12-01","National Day","RO",2004 +"2004-12-25","Christmas Day","RO",2004 +"2004-12-26","Christmas Day","RO",2004 +"2005-01-01","New Year's Day","RO",2005 +"2005-01-02","New Year's Day","RO",2005 +"2005-05-01","Easter","RO",2005 +"2005-05-01","Labour Day","RO",2005 +"2005-05-02","Easter","RO",2005 +"2005-06-19","Pentecost","RO",2005 +"2005-06-20","Pentecost","RO",2005 +"2005-12-01","National Day","RO",2005 +"2005-12-25","Christmas Day","RO",2005 +"2005-12-26","Christmas Day","RO",2005 +"2006-01-01","New Year's Day","RO",2006 +"2006-01-02","New Year's Day","RO",2006 +"2006-04-23","Easter","RO",2006 +"2006-04-24","Easter","RO",2006 +"2006-05-01","Labour Day","RO",2006 +"2006-06-11","Pentecost","RO",2006 +"2006-06-12","Pentecost","RO",2006 +"2006-12-01","National Day","RO",2006 +"2006-12-25","Christmas Day","RO",2006 +"2006-12-26","Christmas Day","RO",2006 +"2007-01-01","New Year's Day","RO",2007 +"2007-01-02","New Year's Day","RO",2007 +"2007-04-08","Easter","RO",2007 +"2007-04-09","Easter","RO",2007 +"2007-05-01","Labour Day","RO",2007 +"2007-05-27","Pentecost","RO",2007 +"2007-05-28","Pentecost","RO",2007 +"2007-12-01","National Day","RO",2007 +"2007-12-25","Christmas Day","RO",2007 +"2007-12-26","Christmas Day","RO",2007 +"2008-01-01","New Year's Day","RO",2008 +"2008-01-02","New Year's Day","RO",2008 +"2008-04-27","Easter","RO",2008 +"2008-04-28","Easter","RO",2008 +"2008-05-01","Labour Day","RO",2008 +"2008-06-15","Pentecost","RO",2008 +"2008-06-16","Pentecost","RO",2008 +"2008-12-01","National Day","RO",2008 +"2008-12-25","Christmas Day","RO",2008 +"2008-12-26","Christmas Day","RO",2008 +"2009-01-01","New Year's Day","RO",2009 +"2009-01-02","New Year's Day","RO",2009 +"2009-04-19","Easter","RO",2009 +"2009-04-20","Easter","RO",2009 +"2009-05-01","Labour Day","RO",2009 +"2009-06-07","Pentecost","RO",2009 +"2009-06-08","Pentecost","RO",2009 +"2009-08-15","Dormition of the Mother of God","RO",2009 +"2009-12-01","National Day","RO",2009 +"2009-12-25","Christmas Day","RO",2009 +"2009-12-26","Christmas Day","RO",2009 +"2010-01-01","New Year's Day","RO",2010 +"2010-01-02","New Year's Day","RO",2010 +"2010-04-04","Easter","RO",2010 +"2010-04-05","Easter","RO",2010 +"2010-05-01","Labour Day","RO",2010 +"2010-05-23","Pentecost","RO",2010 +"2010-05-24","Pentecost","RO",2010 +"2010-08-15","Dormition of the Mother of God","RO",2010 +"2010-12-01","National Day","RO",2010 +"2010-12-25","Christmas Day","RO",2010 +"2010-12-26","Christmas Day","RO",2010 +"2011-01-01","New Year's Day","RO",2011 +"2011-01-02","New Year's Day","RO",2011 +"2011-04-24","Easter","RO",2011 +"2011-04-25","Easter","RO",2011 +"2011-05-01","Labour Day","RO",2011 +"2011-06-12","Pentecost","RO",2011 +"2011-06-13","Pentecost","RO",2011 +"2011-08-15","Dormition of the Mother of God","RO",2011 +"2011-12-01","National Day","RO",2011 +"2011-12-25","Christmas Day","RO",2011 +"2011-12-26","Christmas Day","RO",2011 +"2012-01-01","New Year's Day","RO",2012 +"2012-01-02","New Year's Day","RO",2012 +"2012-04-15","Easter","RO",2012 +"2012-04-16","Easter","RO",2012 +"2012-05-01","Labour Day","RO",2012 +"2012-06-03","Pentecost","RO",2012 +"2012-06-04","Pentecost","RO",2012 +"2012-08-15","Dormition of the Mother of God","RO",2012 +"2012-11-30","Saint Andrew's Day","RO",2012 +"2012-12-01","National Day","RO",2012 +"2012-12-25","Christmas Day","RO",2012 +"2012-12-26","Christmas Day","RO",2012 +"2013-01-01","New Year's Day","RO",2013 +"2013-01-02","New Year's Day","RO",2013 +"2013-05-01","Labour Day","RO",2013 +"2013-05-05","Easter","RO",2013 +"2013-05-06","Easter","RO",2013 +"2013-06-23","Pentecost","RO",2013 +"2013-06-24","Pentecost","RO",2013 +"2013-08-15","Dormition of the Mother of God","RO",2013 +"2013-11-30","Saint Andrew's Day","RO",2013 +"2013-12-01","National Day","RO",2013 +"2013-12-25","Christmas Day","RO",2013 +"2013-12-26","Christmas Day","RO",2013 +"2014-01-01","New Year's Day","RO",2014 +"2014-01-02","New Year's Day","RO",2014 +"2014-04-20","Easter","RO",2014 +"2014-04-21","Easter","RO",2014 +"2014-05-01","Labour Day","RO",2014 +"2014-06-08","Pentecost","RO",2014 +"2014-06-09","Pentecost","RO",2014 +"2014-08-15","Dormition of the Mother of God","RO",2014 +"2014-11-30","Saint Andrew's Day","RO",2014 +"2014-12-01","National Day","RO",2014 +"2014-12-25","Christmas Day","RO",2014 +"2014-12-26","Christmas Day","RO",2014 +"2015-01-01","New Year's Day","RO",2015 +"2015-01-02","New Year's Day","RO",2015 +"2015-04-12","Easter","RO",2015 +"2015-04-13","Easter","RO",2015 +"2015-05-01","Labour Day","RO",2015 +"2015-05-31","Pentecost","RO",2015 +"2015-06-01","Pentecost","RO",2015 +"2015-08-15","Dormition of the Mother of God","RO",2015 +"2015-11-30","Saint Andrew's Day","RO",2015 +"2015-12-01","National Day","RO",2015 +"2015-12-25","Christmas Day","RO",2015 +"2015-12-26","Christmas Day","RO",2015 +"2016-01-01","New Year's Day","RO",2016 +"2016-01-02","New Year's Day","RO",2016 +"2016-01-24","Unification of the Romanian Principalities Day","RO",2016 +"2016-05-01","Easter","RO",2016 +"2016-05-01","Labour Day","RO",2016 +"2016-05-02","Easter","RO",2016 +"2016-06-19","Pentecost","RO",2016 +"2016-06-20","Pentecost","RO",2016 +"2016-08-15","Dormition of the Mother of God","RO",2016 +"2016-11-30","Saint Andrew's Day","RO",2016 +"2016-12-01","National Day","RO",2016 +"2016-12-25","Christmas Day","RO",2016 +"2016-12-26","Christmas Day","RO",2016 +"2017-01-01","New Year's Day","RO",2017 +"2017-01-02","New Year's Day","RO",2017 +"2017-01-24","Unification of the Romanian Principalities Day","RO",2017 +"2017-04-16","Easter","RO",2017 +"2017-04-17","Easter","RO",2017 +"2017-05-01","Labour Day","RO",2017 +"2017-06-01","Children's Day","RO",2017 +"2017-06-04","Pentecost","RO",2017 +"2017-06-05","Pentecost","RO",2017 +"2017-08-15","Dormition of the Mother of God","RO",2017 +"2017-11-30","Saint Andrew's Day","RO",2017 +"2017-12-01","National Day","RO",2017 +"2017-12-25","Christmas Day","RO",2017 +"2017-12-26","Christmas Day","RO",2017 +"2018-01-01","New Year's Day","RO",2018 +"2018-01-02","New Year's Day","RO",2018 +"2018-01-24","Unification of the Romanian Principalities Day","RO",2018 +"2018-04-06","Easter","RO",2018 +"2018-04-08","Easter","RO",2018 +"2018-04-09","Easter","RO",2018 +"2018-05-01","Labour Day","RO",2018 +"2018-05-27","Pentecost","RO",2018 +"2018-05-28","Pentecost","RO",2018 +"2018-06-01","Children's Day","RO",2018 +"2018-08-15","Dormition of the Mother of God","RO",2018 +"2018-11-30","Saint Andrew's Day","RO",2018 +"2018-12-01","National Day","RO",2018 +"2018-12-25","Christmas Day","RO",2018 +"2018-12-26","Christmas Day","RO",2018 +"2019-01-01","New Year's Day","RO",2019 +"2019-01-02","New Year's Day","RO",2019 +"2019-01-24","Unification of the Romanian Principalities Day","RO",2019 +"2019-04-26","Easter","RO",2019 +"2019-04-28","Easter","RO",2019 +"2019-04-29","Easter","RO",2019 +"2019-05-01","Labour Day","RO",2019 +"2019-06-01","Children's Day","RO",2019 +"2019-06-16","Pentecost","RO",2019 +"2019-06-17","Pentecost","RO",2019 +"2019-08-15","Dormition of the Mother of God","RO",2019 +"2019-11-30","Saint Andrew's Day","RO",2019 +"2019-12-01","National Day","RO",2019 +"2019-12-25","Christmas Day","RO",2019 +"2019-12-26","Christmas Day","RO",2019 +"2020-01-01","New Year's Day","RO",2020 +"2020-01-02","New Year's Day","RO",2020 +"2020-01-24","Unification of the Romanian Principalities Day","RO",2020 +"2020-04-17","Easter","RO",2020 +"2020-04-19","Easter","RO",2020 +"2020-04-20","Easter","RO",2020 +"2020-05-01","Labour Day","RO",2020 +"2020-06-01","Children's Day","RO",2020 +"2020-06-07","Pentecost","RO",2020 +"2020-06-08","Pentecost","RO",2020 +"2020-08-15","Dormition of the Mother of God","RO",2020 +"2020-11-30","Saint Andrew's Day","RO",2020 +"2020-12-01","National Day","RO",2020 +"2020-12-25","Christmas Day","RO",2020 +"2020-12-26","Christmas Day","RO",2020 +"2021-01-01","New Year's Day","RO",2021 +"2021-01-02","New Year's Day","RO",2021 +"2021-01-24","Unification of the Romanian Principalities Day","RO",2021 +"2021-04-30","Easter","RO",2021 +"2021-05-01","Labour Day","RO",2021 +"2021-05-02","Easter","RO",2021 +"2021-05-03","Easter","RO",2021 +"2021-06-01","Children's Day","RO",2021 +"2021-06-20","Pentecost","RO",2021 +"2021-06-21","Pentecost","RO",2021 +"2021-08-15","Dormition of the Mother of God","RO",2021 +"2021-11-30","Saint Andrew's Day","RO",2021 +"2021-12-01","National Day","RO",2021 +"2021-12-25","Christmas Day","RO",2021 +"2021-12-26","Christmas Day","RO",2021 +"2022-01-01","New Year's Day","RO",2022 +"2022-01-02","New Year's Day","RO",2022 +"2022-01-24","Unification of the Romanian Principalities Day","RO",2022 +"2022-04-22","Easter","RO",2022 +"2022-04-24","Easter","RO",2022 +"2022-04-25","Easter","RO",2022 +"2022-05-01","Labour Day","RO",2022 +"2022-06-01","Children's Day","RO",2022 +"2022-06-12","Pentecost","RO",2022 +"2022-06-13","Pentecost","RO",2022 +"2022-08-15","Dormition of the Mother of God","RO",2022 +"2022-11-30","Saint Andrew's Day","RO",2022 +"2022-12-01","National Day","RO",2022 +"2022-12-25","Christmas Day","RO",2022 +"2022-12-26","Christmas Day","RO",2022 +"2023-01-01","New Year's Day","RO",2023 +"2023-01-02","New Year's Day","RO",2023 +"2023-01-24","Unification of the Romanian Principalities Day","RO",2023 +"2023-04-14","Easter","RO",2023 +"2023-04-16","Easter","RO",2023 +"2023-04-17","Easter","RO",2023 +"2023-05-01","Labour Day","RO",2023 +"2023-06-01","Children's Day","RO",2023 +"2023-06-04","Pentecost","RO",2023 +"2023-06-05","Pentecost","RO",2023 +"2023-08-15","Dormition of the Mother of God","RO",2023 +"2023-11-30","Saint Andrew's Day","RO",2023 +"2023-12-01","National Day","RO",2023 +"2023-12-25","Christmas Day","RO",2023 +"2023-12-26","Christmas Day","RO",2023 +"2024-01-01","New Year's Day","RO",2024 +"2024-01-02","New Year's Day","RO",2024 +"2024-01-06","Epiphany","RO",2024 +"2024-01-07","Saint John the Baptist","RO",2024 +"2024-01-24","Unification of the Romanian Principalities Day","RO",2024 +"2024-05-01","Labour Day","RO",2024 +"2024-05-03","Easter","RO",2024 +"2024-05-05","Easter","RO",2024 +"2024-05-06","Easter","RO",2024 +"2024-06-01","Children's Day","RO",2024 +"2024-06-23","Pentecost","RO",2024 +"2024-06-24","Pentecost","RO",2024 +"2024-08-15","Dormition of the Mother of God","RO",2024 +"2024-11-30","Saint Andrew's Day","RO",2024 +"2024-12-01","National Day","RO",2024 +"2024-12-25","Christmas Day","RO",2024 +"2024-12-26","Christmas Day","RO",2024 +"2025-01-01","New Year's Day","RO",2025 +"2025-01-02","New Year's Day","RO",2025 +"2025-01-06","Epiphany","RO",2025 +"2025-01-07","Saint John the Baptist","RO",2025 +"2025-01-24","Unification of the Romanian Principalities Day","RO",2025 +"2025-04-18","Easter","RO",2025 +"2025-04-20","Easter","RO",2025 +"2025-04-21","Easter","RO",2025 +"2025-05-01","Labour Day","RO",2025 +"2025-06-01","Children's Day","RO",2025 +"2025-06-08","Pentecost","RO",2025 +"2025-06-09","Pentecost","RO",2025 +"2025-08-15","Dormition of the Mother of God","RO",2025 +"2025-11-30","Saint Andrew's Day","RO",2025 +"2025-12-01","National Day","RO",2025 +"2025-12-25","Christmas Day","RO",2025 +"2025-12-26","Christmas Day","RO",2025 +"2026-01-01","New Year's Day","RO",2026 +"2026-01-02","New Year's Day","RO",2026 +"2026-01-06","Epiphany","RO",2026 +"2026-01-07","Saint John the Baptist","RO",2026 +"2026-01-24","Unification of the Romanian Principalities Day","RO",2026 +"2026-04-10","Easter","RO",2026 +"2026-04-12","Easter","RO",2026 +"2026-04-13","Easter","RO",2026 +"2026-05-01","Labour Day","RO",2026 +"2026-05-31","Pentecost","RO",2026 +"2026-06-01","Children's Day","RO",2026 +"2026-06-01","Pentecost","RO",2026 +"2026-08-15","Dormition of the Mother of God","RO",2026 +"2026-11-30","Saint Andrew's Day","RO",2026 +"2026-12-01","National Day","RO",2026 +"2026-12-25","Christmas Day","RO",2026 +"2026-12-26","Christmas Day","RO",2026 +"2027-01-01","New Year's Day","RO",2027 +"2027-01-02","New Year's Day","RO",2027 +"2027-01-06","Epiphany","RO",2027 +"2027-01-07","Saint John the Baptist","RO",2027 +"2027-01-24","Unification of the Romanian Principalities Day","RO",2027 +"2027-04-30","Easter","RO",2027 +"2027-05-01","Labour Day","RO",2027 +"2027-05-02","Easter","RO",2027 +"2027-05-03","Easter","RO",2027 +"2027-06-01","Children's Day","RO",2027 +"2027-06-20","Pentecost","RO",2027 +"2027-06-21","Pentecost","RO",2027 +"2027-08-15","Dormition of the Mother of God","RO",2027 +"2027-11-30","Saint Andrew's Day","RO",2027 +"2027-12-01","National Day","RO",2027 +"2027-12-25","Christmas Day","RO",2027 +"2027-12-26","Christmas Day","RO",2027 +"2028-01-01","New Year's Day","RO",2028 +"2028-01-02","New Year's Day","RO",2028 +"2028-01-06","Epiphany","RO",2028 +"2028-01-07","Saint John the Baptist","RO",2028 +"2028-01-24","Unification of the Romanian Principalities Day","RO",2028 +"2028-04-14","Easter","RO",2028 +"2028-04-16","Easter","RO",2028 +"2028-04-17","Easter","RO",2028 +"2028-05-01","Labour Day","RO",2028 +"2028-06-01","Children's Day","RO",2028 +"2028-06-04","Pentecost","RO",2028 +"2028-06-05","Pentecost","RO",2028 +"2028-08-15","Dormition of the Mother of God","RO",2028 +"2028-11-30","Saint Andrew's Day","RO",2028 +"2028-12-01","National Day","RO",2028 +"2028-12-25","Christmas Day","RO",2028 +"2028-12-26","Christmas Day","RO",2028 +"2029-01-01","New Year's Day","RO",2029 +"2029-01-02","New Year's Day","RO",2029 +"2029-01-06","Epiphany","RO",2029 +"2029-01-07","Saint John the Baptist","RO",2029 +"2029-01-24","Unification of the Romanian Principalities Day","RO",2029 +"2029-04-06","Easter","RO",2029 +"2029-04-08","Easter","RO",2029 +"2029-04-09","Easter","RO",2029 +"2029-05-01","Labour Day","RO",2029 +"2029-05-27","Pentecost","RO",2029 +"2029-05-28","Pentecost","RO",2029 +"2029-06-01","Children's Day","RO",2029 +"2029-08-15","Dormition of the Mother of God","RO",2029 +"2029-11-30","Saint Andrew's Day","RO",2029 +"2029-12-01","National Day","RO",2029 +"2029-12-25","Christmas Day","RO",2029 +"2029-12-26","Christmas Day","RO",2029 +"2030-01-01","New Year's Day","RO",2030 +"2030-01-02","New Year's Day","RO",2030 +"2030-01-06","Epiphany","RO",2030 +"2030-01-07","Saint John the Baptist","RO",2030 +"2030-01-24","Unification of the Romanian Principalities Day","RO",2030 +"2030-04-26","Easter","RO",2030 +"2030-04-28","Easter","RO",2030 +"2030-04-29","Easter","RO",2030 +"2030-05-01","Labour Day","RO",2030 +"2030-06-01","Children's Day","RO",2030 +"2030-06-16","Pentecost","RO",2030 +"2030-06-17","Pentecost","RO",2030 +"2030-08-15","Dormition of the Mother of God","RO",2030 +"2030-11-30","Saint Andrew's Day","RO",2030 +"2030-12-01","National Day","RO",2030 +"2030-12-25","Christmas Day","RO",2030 +"2030-12-26","Christmas Day","RO",2030 +"2031-01-01","New Year's Day","RO",2031 +"2031-01-02","New Year's Day","RO",2031 +"2031-01-06","Epiphany","RO",2031 +"2031-01-07","Saint John the Baptist","RO",2031 +"2031-01-24","Unification of the Romanian Principalities Day","RO",2031 +"2031-04-11","Easter","RO",2031 +"2031-04-13","Easter","RO",2031 +"2031-04-14","Easter","RO",2031 +"2031-05-01","Labour Day","RO",2031 +"2031-06-01","Children's Day","RO",2031 +"2031-06-01","Pentecost","RO",2031 +"2031-06-02","Pentecost","RO",2031 +"2031-08-15","Dormition of the Mother of God","RO",2031 +"2031-11-30","Saint Andrew's Day","RO",2031 +"2031-12-01","National Day","RO",2031 +"2031-12-25","Christmas Day","RO",2031 +"2031-12-26","Christmas Day","RO",2031 +"2032-01-01","New Year's Day","RO",2032 +"2032-01-02","New Year's Day","RO",2032 +"2032-01-06","Epiphany","RO",2032 +"2032-01-07","Saint John the Baptist","RO",2032 +"2032-01-24","Unification of the Romanian Principalities Day","RO",2032 +"2032-04-30","Easter","RO",2032 +"2032-05-01","Labour Day","RO",2032 +"2032-05-02","Easter","RO",2032 +"2032-05-03","Easter","RO",2032 +"2032-06-01","Children's Day","RO",2032 +"2032-06-20","Pentecost","RO",2032 +"2032-06-21","Pentecost","RO",2032 +"2032-08-15","Dormition of the Mother of God","RO",2032 +"2032-11-30","Saint Andrew's Day","RO",2032 +"2032-12-01","National Day","RO",2032 +"2032-12-25","Christmas Day","RO",2032 +"2032-12-26","Christmas Day","RO",2032 +"2033-01-01","New Year's Day","RO",2033 +"2033-01-02","New Year's Day","RO",2033 +"2033-01-06","Epiphany","RO",2033 +"2033-01-07","Saint John the Baptist","RO",2033 +"2033-01-24","Unification of the Romanian Principalities Day","RO",2033 +"2033-04-22","Easter","RO",2033 +"2033-04-24","Easter","RO",2033 +"2033-04-25","Easter","RO",2033 +"2033-05-01","Labour Day","RO",2033 +"2033-06-01","Children's Day","RO",2033 +"2033-06-12","Pentecost","RO",2033 +"2033-06-13","Pentecost","RO",2033 +"2033-08-15","Dormition of the Mother of God","RO",2033 +"2033-11-30","Saint Andrew's Day","RO",2033 +"2033-12-01","National Day","RO",2033 +"2033-12-25","Christmas Day","RO",2033 +"2033-12-26","Christmas Day","RO",2033 +"2034-01-01","New Year's Day","RO",2034 +"2034-01-02","New Year's Day","RO",2034 +"2034-01-06","Epiphany","RO",2034 +"2034-01-07","Saint John the Baptist","RO",2034 +"2034-01-24","Unification of the Romanian Principalities Day","RO",2034 +"2034-04-07","Easter","RO",2034 +"2034-04-09","Easter","RO",2034 +"2034-04-10","Easter","RO",2034 +"2034-05-01","Labour Day","RO",2034 +"2034-05-28","Pentecost","RO",2034 +"2034-05-29","Pentecost","RO",2034 +"2034-06-01","Children's Day","RO",2034 +"2034-08-15","Dormition of the Mother of God","RO",2034 +"2034-11-30","Saint Andrew's Day","RO",2034 +"2034-12-01","National Day","RO",2034 +"2034-12-25","Christmas Day","RO",2034 +"2034-12-26","Christmas Day","RO",2034 +"2035-01-01","New Year's Day","RO",2035 +"2035-01-02","New Year's Day","RO",2035 +"2035-01-06","Epiphany","RO",2035 +"2035-01-07","Saint John the Baptist","RO",2035 +"2035-01-24","Unification of the Romanian Principalities Day","RO",2035 +"2035-04-27","Easter","RO",2035 +"2035-04-29","Easter","RO",2035 +"2035-04-30","Easter","RO",2035 +"2035-05-01","Labour Day","RO",2035 +"2035-06-01","Children's Day","RO",2035 +"2035-06-17","Pentecost","RO",2035 +"2035-06-18","Pentecost","RO",2035 +"2035-08-15","Dormition of the Mother of God","RO",2035 +"2035-11-30","Saint Andrew's Day","RO",2035 +"2035-12-01","National Day","RO",2035 +"2035-12-25","Christmas Day","RO",2035 +"2035-12-26","Christmas Day","RO",2035 +"2036-01-01","New Year's Day","RO",2036 +"2036-01-02","New Year's Day","RO",2036 +"2036-01-06","Epiphany","RO",2036 +"2036-01-07","Saint John the Baptist","RO",2036 +"2036-01-24","Unification of the Romanian Principalities Day","RO",2036 +"2036-04-18","Easter","RO",2036 +"2036-04-20","Easter","RO",2036 +"2036-04-21","Easter","RO",2036 +"2036-05-01","Labour Day","RO",2036 +"2036-06-01","Children's Day","RO",2036 +"2036-06-08","Pentecost","RO",2036 +"2036-06-09","Pentecost","RO",2036 +"2036-08-15","Dormition of the Mother of God","RO",2036 +"2036-11-30","Saint Andrew's Day","RO",2036 +"2036-12-01","National Day","RO",2036 +"2036-12-25","Christmas Day","RO",2036 +"2036-12-26","Christmas Day","RO",2036 +"2037-01-01","New Year's Day","RO",2037 +"2037-01-02","New Year's Day","RO",2037 +"2037-01-06","Epiphany","RO",2037 +"2037-01-07","Saint John the Baptist","RO",2037 +"2037-01-24","Unification of the Romanian Principalities Day","RO",2037 +"2037-04-03","Easter","RO",2037 +"2037-04-05","Easter","RO",2037 +"2037-04-06","Easter","RO",2037 +"2037-05-01","Labour Day","RO",2037 +"2037-05-24","Pentecost","RO",2037 +"2037-05-25","Pentecost","RO",2037 +"2037-06-01","Children's Day","RO",2037 +"2037-08-15","Dormition of the Mother of God","RO",2037 +"2037-11-30","Saint Andrew's Day","RO",2037 +"2037-12-01","National Day","RO",2037 +"2037-12-25","Christmas Day","RO",2037 +"2037-12-26","Christmas Day","RO",2037 +"2038-01-01","New Year's Day","RO",2038 +"2038-01-02","New Year's Day","RO",2038 +"2038-01-06","Epiphany","RO",2038 +"2038-01-07","Saint John the Baptist","RO",2038 +"2038-01-24","Unification of the Romanian Principalities Day","RO",2038 +"2038-04-23","Easter","RO",2038 +"2038-04-25","Easter","RO",2038 +"2038-04-26","Easter","RO",2038 +"2038-05-01","Labour Day","RO",2038 +"2038-06-01","Children's Day","RO",2038 +"2038-06-13","Pentecost","RO",2038 +"2038-06-14","Pentecost","RO",2038 +"2038-08-15","Dormition of the Mother of God","RO",2038 +"2038-11-30","Saint Andrew's Day","RO",2038 +"2038-12-01","National Day","RO",2038 +"2038-12-25","Christmas Day","RO",2038 +"2038-12-26","Christmas Day","RO",2038 +"2039-01-01","New Year's Day","RO",2039 +"2039-01-02","New Year's Day","RO",2039 +"2039-01-06","Epiphany","RO",2039 +"2039-01-07","Saint John the Baptist","RO",2039 +"2039-01-24","Unification of the Romanian Principalities Day","RO",2039 +"2039-04-15","Easter","RO",2039 +"2039-04-17","Easter","RO",2039 +"2039-04-18","Easter","RO",2039 +"2039-05-01","Labour Day","RO",2039 +"2039-06-01","Children's Day","RO",2039 +"2039-06-05","Pentecost","RO",2039 +"2039-06-06","Pentecost","RO",2039 +"2039-08-15","Dormition of the Mother of God","RO",2039 +"2039-11-30","Saint Andrew's Day","RO",2039 +"2039-12-01","National Day","RO",2039 +"2039-12-25","Christmas Day","RO",2039 +"2039-12-26","Christmas Day","RO",2039 +"2040-01-01","New Year's Day","RO",2040 +"2040-01-02","New Year's Day","RO",2040 +"2040-01-06","Epiphany","RO",2040 +"2040-01-07","Saint John the Baptist","RO",2040 +"2040-01-24","Unification of the Romanian Principalities Day","RO",2040 +"2040-05-01","Labour Day","RO",2040 +"2040-05-04","Easter","RO",2040 +"2040-05-06","Easter","RO",2040 +"2040-05-07","Easter","RO",2040 +"2040-06-01","Children's Day","RO",2040 +"2040-06-24","Pentecost","RO",2040 +"2040-06-25","Pentecost","RO",2040 +"2040-08-15","Dormition of the Mother of God","RO",2040 +"2040-11-30","Saint Andrew's Day","RO",2040 +"2040-12-01","National Day","RO",2040 +"2040-12-25","Christmas Day","RO",2040 +"2040-12-26","Christmas Day","RO",2040 +"2041-01-01","New Year's Day","RO",2041 +"2041-01-02","New Year's Day","RO",2041 +"2041-01-06","Epiphany","RO",2041 +"2041-01-07","Saint John the Baptist","RO",2041 +"2041-01-24","Unification of the Romanian Principalities Day","RO",2041 +"2041-04-19","Easter","RO",2041 +"2041-04-21","Easter","RO",2041 +"2041-04-22","Easter","RO",2041 +"2041-05-01","Labour Day","RO",2041 +"2041-06-01","Children's Day","RO",2041 +"2041-06-09","Pentecost","RO",2041 +"2041-06-10","Pentecost","RO",2041 +"2041-08-15","Dormition of the Mother of God","RO",2041 +"2041-11-30","Saint Andrew's Day","RO",2041 +"2041-12-01","National Day","RO",2041 +"2041-12-25","Christmas Day","RO",2041 +"2041-12-26","Christmas Day","RO",2041 +"2042-01-01","New Year's Day","RO",2042 +"2042-01-02","New Year's Day","RO",2042 +"2042-01-06","Epiphany","RO",2042 +"2042-01-07","Saint John the Baptist","RO",2042 +"2042-01-24","Unification of the Romanian Principalities Day","RO",2042 +"2042-04-11","Easter","RO",2042 +"2042-04-13","Easter","RO",2042 +"2042-04-14","Easter","RO",2042 +"2042-05-01","Labour Day","RO",2042 +"2042-06-01","Children's Day","RO",2042 +"2042-06-01","Pentecost","RO",2042 +"2042-06-02","Pentecost","RO",2042 +"2042-08-15","Dormition of the Mother of God","RO",2042 +"2042-11-30","Saint Andrew's Day","RO",2042 +"2042-12-01","National Day","RO",2042 +"2042-12-25","Christmas Day","RO",2042 +"2042-12-26","Christmas Day","RO",2042 +"2043-01-01","New Year's Day","RO",2043 +"2043-01-02","New Year's Day","RO",2043 +"2043-01-06","Epiphany","RO",2043 +"2043-01-07","Saint John the Baptist","RO",2043 +"2043-01-24","Unification of the Romanian Principalities Day","RO",2043 +"2043-05-01","Easter","RO",2043 +"2043-05-01","Labour Day","RO",2043 +"2043-05-03","Easter","RO",2043 +"2043-05-04","Easter","RO",2043 +"2043-06-01","Children's Day","RO",2043 +"2043-06-21","Pentecost","RO",2043 +"2043-06-22","Pentecost","RO",2043 +"2043-08-15","Dormition of the Mother of God","RO",2043 +"2043-11-30","Saint Andrew's Day","RO",2043 +"2043-12-01","National Day","RO",2043 +"2043-12-25","Christmas Day","RO",2043 +"2043-12-26","Christmas Day","RO",2043 +"2044-01-01","New Year's Day","RO",2044 +"2044-01-02","New Year's Day","RO",2044 +"2044-01-06","Epiphany","RO",2044 +"2044-01-07","Saint John the Baptist","RO",2044 +"2044-01-24","Unification of the Romanian Principalities Day","RO",2044 +"2044-04-22","Easter","RO",2044 +"2044-04-24","Easter","RO",2044 +"2044-04-25","Easter","RO",2044 +"2044-05-01","Labour Day","RO",2044 +"2044-06-01","Children's Day","RO",2044 +"2044-06-12","Pentecost","RO",2044 +"2044-06-13","Pentecost","RO",2044 +"2044-08-15","Dormition of the Mother of God","RO",2044 +"2044-11-30","Saint Andrew's Day","RO",2044 +"2044-12-01","National Day","RO",2044 +"2044-12-25","Christmas Day","RO",2044 +"2044-12-26","Christmas Day","RO",2044 +"1995-01-01","New Year's Day","RS",1995 +"1995-01-02","New Year's Day","RS",1995 +"1995-01-03","New Year's Day (Observed)","RS",1995 +"1995-01-07","Orthodox Christmas Day","RS",1995 +"1995-02-15","Statehood Day","RS",1995 +"1995-02-16","Statehood Day","RS",1995 +"1995-04-21","Good Friday","RS",1995 +"1995-04-22","Easter Saturday","RS",1995 +"1995-04-23","Easter Sunday","RS",1995 +"1995-04-24","Easter Monday","RS",1995 +"1995-05-01","International Workers' Day","RS",1995 +"1995-05-02","International Workers' Day","RS",1995 +"1995-11-11","Armistice Day","RS",1995 +"1996-01-01","New Year's Day","RS",1996 +"1996-01-02","New Year's Day","RS",1996 +"1996-01-07","Orthodox Christmas Day","RS",1996 +"1996-02-15","Statehood Day","RS",1996 +"1996-02-16","Statehood Day","RS",1996 +"1996-04-12","Good Friday","RS",1996 +"1996-04-13","Easter Saturday","RS",1996 +"1996-04-14","Easter Sunday","RS",1996 +"1996-04-15","Easter Monday","RS",1996 +"1996-05-01","International Workers' Day","RS",1996 +"1996-05-02","International Workers' Day","RS",1996 +"1996-11-11","Armistice Day","RS",1996 +"1997-01-01","New Year's Day","RS",1997 +"1997-01-02","New Year's Day","RS",1997 +"1997-01-07","Orthodox Christmas Day","RS",1997 +"1997-02-15","Statehood Day","RS",1997 +"1997-02-16","Statehood Day","RS",1997 +"1997-02-17","Statehood Day (Observed)","RS",1997 +"1997-04-25","Good Friday","RS",1997 +"1997-04-26","Easter Saturday","RS",1997 +"1997-04-27","Easter Sunday","RS",1997 +"1997-04-28","Easter Monday","RS",1997 +"1997-05-01","International Workers' Day","RS",1997 +"1997-05-02","International Workers' Day","RS",1997 +"1997-11-11","Armistice Day","RS",1997 +"1998-01-01","New Year's Day","RS",1998 +"1998-01-02","New Year's Day","RS",1998 +"1998-01-07","Orthodox Christmas Day","RS",1998 +"1998-02-15","Statehood Day","RS",1998 +"1998-02-16","Statehood Day","RS",1998 +"1998-02-17","Statehood Day (Observed)","RS",1998 +"1998-04-17","Good Friday","RS",1998 +"1998-04-18","Easter Saturday","RS",1998 +"1998-04-19","Easter Sunday","RS",1998 +"1998-04-20","Easter Monday","RS",1998 +"1998-05-01","International Workers' Day","RS",1998 +"1998-05-02","International Workers' Day","RS",1998 +"1998-11-11","Armistice Day","RS",1998 +"1999-01-01","New Year's Day","RS",1999 +"1999-01-02","New Year's Day","RS",1999 +"1999-01-07","Orthodox Christmas Day","RS",1999 +"1999-02-15","Statehood Day","RS",1999 +"1999-02-16","Statehood Day","RS",1999 +"1999-04-09","Good Friday","RS",1999 +"1999-04-10","Easter Saturday","RS",1999 +"1999-04-11","Easter Sunday","RS",1999 +"1999-04-12","Easter Monday","RS",1999 +"1999-05-01","International Workers' Day","RS",1999 +"1999-05-02","International Workers' Day","RS",1999 +"1999-05-03","International Workers' Day (Observed)","RS",1999 +"1999-11-11","Armistice Day","RS",1999 +"2000-01-01","New Year's Day","RS",2000 +"2000-01-02","New Year's Day","RS",2000 +"2000-01-03","New Year's Day (Observed)","RS",2000 +"2000-01-07","Orthodox Christmas Day","RS",2000 +"2000-02-15","Statehood Day","RS",2000 +"2000-02-16","Statehood Day","RS",2000 +"2000-04-28","Good Friday","RS",2000 +"2000-04-29","Easter Saturday","RS",2000 +"2000-04-30","Easter Sunday","RS",2000 +"2000-05-01","Easter Monday","RS",2000 +"2000-05-01","International Workers' Day","RS",2000 +"2000-05-02","International Workers' Day","RS",2000 +"2000-11-11","Armistice Day","RS",2000 +"2001-01-01","New Year's Day","RS",2001 +"2001-01-02","New Year's Day","RS",2001 +"2001-01-07","Orthodox Christmas Day","RS",2001 +"2001-02-15","Statehood Day","RS",2001 +"2001-02-16","Statehood Day","RS",2001 +"2001-04-13","Good Friday","RS",2001 +"2001-04-14","Easter Saturday","RS",2001 +"2001-04-15","Easter Sunday","RS",2001 +"2001-04-16","Easter Monday","RS",2001 +"2001-05-01","International Workers' Day","RS",2001 +"2001-05-02","International Workers' Day","RS",2001 +"2001-11-11","Armistice Day","RS",2001 +"2001-11-12","Armistice Day","RS",2001 +"2002-01-01","New Year's Day","RS",2002 +"2002-01-02","New Year's Day","RS",2002 +"2002-01-07","Orthodox Christmas Day","RS",2002 +"2002-02-15","Statehood Day","RS",2002 +"2002-02-16","Statehood Day","RS",2002 +"2002-05-01","International Workers' Day","RS",2002 +"2002-05-02","International Workers' Day","RS",2002 +"2002-05-03","Good Friday","RS",2002 +"2002-05-04","Easter Saturday","RS",2002 +"2002-05-05","Easter Sunday","RS",2002 +"2002-05-06","Easter Monday","RS",2002 +"2002-11-11","Armistice Day","RS",2002 +"2003-01-01","New Year's Day","RS",2003 +"2003-01-02","New Year's Day","RS",2003 +"2003-01-07","Orthodox Christmas Day","RS",2003 +"2003-02-15","Statehood Day","RS",2003 +"2003-02-16","Statehood Day","RS",2003 +"2003-02-17","Statehood Day (Observed)","RS",2003 +"2003-04-25","Good Friday","RS",2003 +"2003-04-26","Easter Saturday","RS",2003 +"2003-04-27","Easter Sunday","RS",2003 +"2003-04-28","Easter Monday","RS",2003 +"2003-05-01","International Workers' Day","RS",2003 +"2003-05-02","International Workers' Day","RS",2003 +"2003-11-11","Armistice Day","RS",2003 +"2004-01-01","New Year's Day","RS",2004 +"2004-01-02","New Year's Day","RS",2004 +"2004-01-07","Orthodox Christmas Day","RS",2004 +"2004-02-15","Statehood Day","RS",2004 +"2004-02-16","Statehood Day","RS",2004 +"2004-02-17","Statehood Day (Observed)","RS",2004 +"2004-04-09","Good Friday","RS",2004 +"2004-04-10","Easter Saturday","RS",2004 +"2004-04-11","Easter Sunday","RS",2004 +"2004-04-12","Easter Monday","RS",2004 +"2004-05-01","International Workers' Day","RS",2004 +"2004-05-02","International Workers' Day","RS",2004 +"2004-05-03","International Workers' Day (Observed)","RS",2004 +"2004-11-11","Armistice Day","RS",2004 +"2005-01-01","New Year's Day","RS",2005 +"2005-01-02","New Year's Day","RS",2005 +"2005-01-03","New Year's Day (Observed)","RS",2005 +"2005-01-07","Orthodox Christmas Day","RS",2005 +"2005-02-15","Statehood Day","RS",2005 +"2005-02-16","Statehood Day","RS",2005 +"2005-04-29","Good Friday","RS",2005 +"2005-04-30","Easter Saturday","RS",2005 +"2005-05-01","Easter Sunday","RS",2005 +"2005-05-01","International Workers' Day","RS",2005 +"2005-05-02","Easter Monday","RS",2005 +"2005-05-02","International Workers' Day","RS",2005 +"2005-05-03","International Workers' Day (Observed)","RS",2005 +"2005-11-11","Armistice Day","RS",2005 +"2006-01-01","New Year's Day","RS",2006 +"2006-01-02","New Year's Day","RS",2006 +"2006-01-03","New Year's Day (Observed)","RS",2006 +"2006-01-07","Orthodox Christmas Day","RS",2006 +"2006-02-15","Statehood Day","RS",2006 +"2006-02-16","Statehood Day","RS",2006 +"2006-04-21","Good Friday","RS",2006 +"2006-04-22","Easter Saturday","RS",2006 +"2006-04-23","Easter Sunday","RS",2006 +"2006-04-24","Easter Monday","RS",2006 +"2006-05-01","International Workers' Day","RS",2006 +"2006-05-02","International Workers' Day","RS",2006 +"2006-11-11","Armistice Day","RS",2006 +"2007-01-01","New Year's Day","RS",2007 +"2007-01-02","New Year's Day","RS",2007 +"2007-01-07","Orthodox Christmas Day","RS",2007 +"2007-02-15","Statehood Day","RS",2007 +"2007-02-16","Statehood Day","RS",2007 +"2007-04-06","Good Friday","RS",2007 +"2007-04-07","Easter Saturday","RS",2007 +"2007-04-08","Easter Sunday","RS",2007 +"2007-04-09","Easter Monday","RS",2007 +"2007-05-01","International Workers' Day","RS",2007 +"2007-05-02","International Workers' Day","RS",2007 +"2007-11-11","Armistice Day","RS",2007 +"2007-11-12","Armistice Day","RS",2007 +"2008-01-01","New Year's Day","RS",2008 +"2008-01-02","New Year's Day","RS",2008 +"2008-01-07","Orthodox Christmas Day","RS",2008 +"2008-02-15","Statehood Day","RS",2008 +"2008-02-16","Statehood Day","RS",2008 +"2008-04-25","Good Friday","RS",2008 +"2008-04-26","Easter Saturday","RS",2008 +"2008-04-27","Easter Sunday","RS",2008 +"2008-04-28","Easter Monday","RS",2008 +"2008-05-01","International Workers' Day","RS",2008 +"2008-05-02","International Workers' Day","RS",2008 +"2008-11-11","Armistice Day","RS",2008 +"2009-01-01","New Year's Day","RS",2009 +"2009-01-02","New Year's Day","RS",2009 +"2009-01-07","Orthodox Christmas Day","RS",2009 +"2009-02-15","Statehood Day","RS",2009 +"2009-02-16","Statehood Day","RS",2009 +"2009-02-17","Statehood Day (Observed)","RS",2009 +"2009-04-17","Good Friday","RS",2009 +"2009-04-18","Easter Saturday","RS",2009 +"2009-04-19","Easter Sunday","RS",2009 +"2009-04-20","Easter Monday","RS",2009 +"2009-05-01","International Workers' Day","RS",2009 +"2009-05-02","International Workers' Day","RS",2009 +"2009-11-11","Armistice Day","RS",2009 +"2010-01-01","New Year's Day","RS",2010 +"2010-01-02","New Year's Day","RS",2010 +"2010-01-07","Orthodox Christmas Day","RS",2010 +"2010-02-15","Statehood Day","RS",2010 +"2010-02-16","Statehood Day","RS",2010 +"2010-04-02","Good Friday","RS",2010 +"2010-04-03","Easter Saturday","RS",2010 +"2010-04-04","Easter Sunday","RS",2010 +"2010-04-05","Easter Monday","RS",2010 +"2010-05-01","International Workers' Day","RS",2010 +"2010-05-02","International Workers' Day","RS",2010 +"2010-05-03","International Workers' Day (Observed)","RS",2010 +"2010-11-11","Armistice Day","RS",2010 +"2011-01-01","New Year's Day","RS",2011 +"2011-01-02","New Year's Day","RS",2011 +"2011-01-03","New Year's Day (Observed)","RS",2011 +"2011-01-07","Orthodox Christmas Day","RS",2011 +"2011-02-15","Statehood Day","RS",2011 +"2011-02-16","Statehood Day","RS",2011 +"2011-04-22","Good Friday","RS",2011 +"2011-04-23","Easter Saturday","RS",2011 +"2011-04-24","Easter Sunday","RS",2011 +"2011-04-25","Easter Monday","RS",2011 +"2011-05-01","International Workers' Day","RS",2011 +"2011-05-02","International Workers' Day","RS",2011 +"2011-05-03","International Workers' Day (Observed)","RS",2011 +"2011-11-11","Armistice Day","RS",2011 +"2012-01-01","New Year's Day","RS",2012 +"2012-01-02","New Year's Day","RS",2012 +"2012-01-03","New Year's Day (Observed)","RS",2012 +"2012-01-07","Orthodox Christmas Day","RS",2012 +"2012-02-15","Statehood Day","RS",2012 +"2012-02-16","Statehood Day","RS",2012 +"2012-04-13","Good Friday","RS",2012 +"2012-04-14","Easter Saturday","RS",2012 +"2012-04-15","Easter Sunday","RS",2012 +"2012-04-16","Easter Monday","RS",2012 +"2012-05-01","International Workers' Day","RS",2012 +"2012-05-02","International Workers' Day","RS",2012 +"2012-11-11","Armistice Day","RS",2012 +"2012-11-12","Armistice Day","RS",2012 +"2013-01-01","New Year's Day","RS",2013 +"2013-01-02","New Year's Day","RS",2013 +"2013-01-07","Orthodox Christmas Day","RS",2013 +"2013-02-15","Statehood Day","RS",2013 +"2013-02-16","Statehood Day","RS",2013 +"2013-05-01","International Workers' Day","RS",2013 +"2013-05-02","International Workers' Day","RS",2013 +"2013-05-03","Good Friday","RS",2013 +"2013-05-04","Easter Saturday","RS",2013 +"2013-05-05","Easter Sunday","RS",2013 +"2013-05-06","Easter Monday","RS",2013 +"2013-11-11","Armistice Day","RS",2013 +"2014-01-01","New Year's Day","RS",2014 +"2014-01-02","New Year's Day","RS",2014 +"2014-01-07","Orthodox Christmas Day","RS",2014 +"2014-02-15","Statehood Day","RS",2014 +"2014-02-16","Statehood Day","RS",2014 +"2014-02-17","Statehood Day (Observed)","RS",2014 +"2014-04-18","Good Friday","RS",2014 +"2014-04-19","Easter Saturday","RS",2014 +"2014-04-20","Easter Sunday","RS",2014 +"2014-04-21","Easter Monday","RS",2014 +"2014-05-01","International Workers' Day","RS",2014 +"2014-05-02","International Workers' Day","RS",2014 +"2014-11-11","Armistice Day","RS",2014 +"2015-01-01","New Year's Day","RS",2015 +"2015-01-02","New Year's Day","RS",2015 +"2015-01-07","Orthodox Christmas Day","RS",2015 +"2015-02-15","Statehood Day","RS",2015 +"2015-02-16","Statehood Day","RS",2015 +"2015-02-17","Statehood Day (Observed)","RS",2015 +"2015-04-10","Good Friday","RS",2015 +"2015-04-11","Easter Saturday","RS",2015 +"2015-04-12","Easter Sunday","RS",2015 +"2015-04-13","Easter Monday","RS",2015 +"2015-05-01","International Workers' Day","RS",2015 +"2015-05-02","International Workers' Day","RS",2015 +"2015-11-11","Armistice Day","RS",2015 +"2016-01-01","New Year's Day","RS",2016 +"2016-01-02","New Year's Day","RS",2016 +"2016-01-07","Orthodox Christmas Day","RS",2016 +"2016-02-15","Statehood Day","RS",2016 +"2016-02-16","Statehood Day","RS",2016 +"2016-04-29","Good Friday","RS",2016 +"2016-04-30","Easter Saturday","RS",2016 +"2016-05-01","Easter Sunday","RS",2016 +"2016-05-01","International Workers' Day","RS",2016 +"2016-05-02","Easter Monday","RS",2016 +"2016-05-02","International Workers' Day","RS",2016 +"2016-05-03","International Workers' Day (Observed)","RS",2016 +"2016-11-11","Armistice Day","RS",2016 +"2017-01-01","New Year's Day","RS",2017 +"2017-01-02","New Year's Day","RS",2017 +"2017-01-03","New Year's Day (Observed)","RS",2017 +"2017-01-07","Orthodox Christmas Day","RS",2017 +"2017-02-15","Statehood Day","RS",2017 +"2017-02-16","Statehood Day","RS",2017 +"2017-04-14","Good Friday","RS",2017 +"2017-04-15","Easter Saturday","RS",2017 +"2017-04-16","Easter Sunday","RS",2017 +"2017-04-17","Easter Monday","RS",2017 +"2017-05-01","International Workers' Day","RS",2017 +"2017-05-02","International Workers' Day","RS",2017 +"2017-11-11","Armistice Day","RS",2017 +"2018-01-01","New Year's Day","RS",2018 +"2018-01-02","New Year's Day","RS",2018 +"2018-01-07","Orthodox Christmas Day","RS",2018 +"2018-02-15","Statehood Day","RS",2018 +"2018-02-16","Statehood Day","RS",2018 +"2018-04-06","Good Friday","RS",2018 +"2018-04-07","Easter Saturday","RS",2018 +"2018-04-08","Easter Sunday","RS",2018 +"2018-04-09","Easter Monday","RS",2018 +"2018-05-01","International Workers' Day","RS",2018 +"2018-05-02","International Workers' Day","RS",2018 +"2018-11-11","Armistice Day","RS",2018 +"2018-11-12","Armistice Day","RS",2018 +"2019-01-01","New Year's Day","RS",2019 +"2019-01-02","New Year's Day","RS",2019 +"2019-01-07","Orthodox Christmas Day","RS",2019 +"2019-02-15","Statehood Day","RS",2019 +"2019-02-16","Statehood Day","RS",2019 +"2019-04-26","Good Friday","RS",2019 +"2019-04-27","Easter Saturday","RS",2019 +"2019-04-28","Easter Sunday","RS",2019 +"2019-04-29","Easter Monday","RS",2019 +"2019-05-01","International Workers' Day","RS",2019 +"2019-05-02","International Workers' Day","RS",2019 +"2019-11-11","Armistice Day","RS",2019 +"2020-01-01","New Year's Day","RS",2020 +"2020-01-02","New Year's Day","RS",2020 +"2020-01-07","Orthodox Christmas Day","RS",2020 +"2020-02-15","Statehood Day","RS",2020 +"2020-02-16","Statehood Day","RS",2020 +"2020-02-17","Statehood Day (Observed)","RS",2020 +"2020-04-17","Good Friday","RS",2020 +"2020-04-18","Easter Saturday","RS",2020 +"2020-04-19","Easter Sunday","RS",2020 +"2020-04-20","Easter Monday","RS",2020 +"2020-05-01","International Workers' Day","RS",2020 +"2020-05-02","International Workers' Day","RS",2020 +"2020-11-11","Armistice Day","RS",2020 +"2021-01-01","New Year's Day","RS",2021 +"2021-01-02","New Year's Day","RS",2021 +"2021-01-07","Orthodox Christmas Day","RS",2021 +"2021-02-15","Statehood Day","RS",2021 +"2021-02-16","Statehood Day","RS",2021 +"2021-04-30","Good Friday","RS",2021 +"2021-05-01","Easter Saturday","RS",2021 +"2021-05-01","International Workers' Day","RS",2021 +"2021-05-02","Easter Sunday","RS",2021 +"2021-05-02","International Workers' Day","RS",2021 +"2021-05-03","Easter Monday","RS",2021 +"2021-05-04","International Workers' Day (Observed)","RS",2021 +"2021-11-11","Armistice Day","RS",2021 +"2022-01-01","New Year's Day","RS",2022 +"2022-01-02","New Year's Day","RS",2022 +"2022-01-03","New Year's Day (Observed)","RS",2022 +"2022-01-07","Orthodox Christmas Day","RS",2022 +"2022-02-15","Statehood Day","RS",2022 +"2022-02-16","Statehood Day","RS",2022 +"2022-04-22","Good Friday","RS",2022 +"2022-04-23","Easter Saturday","RS",2022 +"2022-04-24","Easter Sunday","RS",2022 +"2022-04-25","Easter Monday","RS",2022 +"2022-05-01","International Workers' Day","RS",2022 +"2022-05-02","International Workers' Day","RS",2022 +"2022-05-03","International Workers' Day (Observed)","RS",2022 +"2022-11-11","Armistice Day","RS",2022 +"2023-01-01","New Year's Day","RS",2023 +"2023-01-02","New Year's Day","RS",2023 +"2023-01-03","New Year's Day (Observed)","RS",2023 +"2023-01-07","Orthodox Christmas Day","RS",2023 +"2023-02-15","Statehood Day","RS",2023 +"2023-02-16","Statehood Day","RS",2023 +"2023-04-14","Good Friday","RS",2023 +"2023-04-15","Easter Saturday","RS",2023 +"2023-04-16","Easter Sunday","RS",2023 +"2023-04-17","Easter Monday","RS",2023 +"2023-05-01","International Workers' Day","RS",2023 +"2023-05-02","International Workers' Day","RS",2023 +"2023-11-11","Armistice Day","RS",2023 +"2024-01-01","New Year's Day","RS",2024 +"2024-01-02","New Year's Day","RS",2024 +"2024-01-07","Orthodox Christmas Day","RS",2024 +"2024-02-15","Statehood Day","RS",2024 +"2024-02-16","Statehood Day","RS",2024 +"2024-05-01","International Workers' Day","RS",2024 +"2024-05-02","International Workers' Day","RS",2024 +"2024-05-03","Good Friday","RS",2024 +"2024-05-04","Easter Saturday","RS",2024 +"2024-05-05","Easter Sunday","RS",2024 +"2024-05-06","Easter Monday","RS",2024 +"2024-11-11","Armistice Day","RS",2024 +"2025-01-01","New Year's Day","RS",2025 +"2025-01-02","New Year's Day","RS",2025 +"2025-01-07","Orthodox Christmas Day","RS",2025 +"2025-02-15","Statehood Day","RS",2025 +"2025-02-16","Statehood Day","RS",2025 +"2025-02-17","Statehood Day (Observed)","RS",2025 +"2025-04-18","Good Friday","RS",2025 +"2025-04-19","Easter Saturday","RS",2025 +"2025-04-20","Easter Sunday","RS",2025 +"2025-04-21","Easter Monday","RS",2025 +"2025-05-01","International Workers' Day","RS",2025 +"2025-05-02","International Workers' Day","RS",2025 +"2025-11-11","Armistice Day","RS",2025 +"2026-01-01","New Year's Day","RS",2026 +"2026-01-02","New Year's Day","RS",2026 +"2026-01-07","Orthodox Christmas Day","RS",2026 +"2026-02-15","Statehood Day","RS",2026 +"2026-02-16","Statehood Day","RS",2026 +"2026-02-17","Statehood Day (Observed)","RS",2026 +"2026-04-10","Good Friday","RS",2026 +"2026-04-11","Easter Saturday","RS",2026 +"2026-04-12","Easter Sunday","RS",2026 +"2026-04-13","Easter Monday","RS",2026 +"2026-05-01","International Workers' Day","RS",2026 +"2026-05-02","International Workers' Day","RS",2026 +"2026-11-11","Armistice Day","RS",2026 +"2027-01-01","New Year's Day","RS",2027 +"2027-01-02","New Year's Day","RS",2027 +"2027-01-07","Orthodox Christmas Day","RS",2027 +"2027-02-15","Statehood Day","RS",2027 +"2027-02-16","Statehood Day","RS",2027 +"2027-04-30","Good Friday","RS",2027 +"2027-05-01","Easter Saturday","RS",2027 +"2027-05-01","International Workers' Day","RS",2027 +"2027-05-02","Easter Sunday","RS",2027 +"2027-05-02","International Workers' Day","RS",2027 +"2027-05-03","Easter Monday","RS",2027 +"2027-05-04","International Workers' Day (Observed)","RS",2027 +"2027-11-11","Armistice Day","RS",2027 +"2028-01-01","New Year's Day","RS",2028 +"2028-01-02","New Year's Day","RS",2028 +"2028-01-03","New Year's Day (Observed)","RS",2028 +"2028-01-07","Orthodox Christmas Day","RS",2028 +"2028-02-15","Statehood Day","RS",2028 +"2028-02-16","Statehood Day","RS",2028 +"2028-04-14","Good Friday","RS",2028 +"2028-04-15","Easter Saturday","RS",2028 +"2028-04-16","Easter Sunday","RS",2028 +"2028-04-17","Easter Monday","RS",2028 +"2028-05-01","International Workers' Day","RS",2028 +"2028-05-02","International Workers' Day","RS",2028 +"2028-11-11","Armistice Day","RS",2028 +"2029-01-01","New Year's Day","RS",2029 +"2029-01-02","New Year's Day","RS",2029 +"2029-01-07","Orthodox Christmas Day","RS",2029 +"2029-02-15","Statehood Day","RS",2029 +"2029-02-16","Statehood Day","RS",2029 +"2029-04-06","Good Friday","RS",2029 +"2029-04-07","Easter Saturday","RS",2029 +"2029-04-08","Easter Sunday","RS",2029 +"2029-04-09","Easter Monday","RS",2029 +"2029-05-01","International Workers' Day","RS",2029 +"2029-05-02","International Workers' Day","RS",2029 +"2029-11-11","Armistice Day","RS",2029 +"2029-11-12","Armistice Day","RS",2029 +"2030-01-01","New Year's Day","RS",2030 +"2030-01-02","New Year's Day","RS",2030 +"2030-01-07","Orthodox Christmas Day","RS",2030 +"2030-02-15","Statehood Day","RS",2030 +"2030-02-16","Statehood Day","RS",2030 +"2030-04-26","Good Friday","RS",2030 +"2030-04-27","Easter Saturday","RS",2030 +"2030-04-28","Easter Sunday","RS",2030 +"2030-04-29","Easter Monday","RS",2030 +"2030-05-01","International Workers' Day","RS",2030 +"2030-05-02","International Workers' Day","RS",2030 +"2030-11-11","Armistice Day","RS",2030 +"2031-01-01","New Year's Day","RS",2031 +"2031-01-02","New Year's Day","RS",2031 +"2031-01-07","Orthodox Christmas Day","RS",2031 +"2031-02-15","Statehood Day","RS",2031 +"2031-02-16","Statehood Day","RS",2031 +"2031-02-17","Statehood Day (Observed)","RS",2031 +"2031-04-11","Good Friday","RS",2031 +"2031-04-12","Easter Saturday","RS",2031 +"2031-04-13","Easter Sunday","RS",2031 +"2031-04-14","Easter Monday","RS",2031 +"2031-05-01","International Workers' Day","RS",2031 +"2031-05-02","International Workers' Day","RS",2031 +"2031-11-11","Armistice Day","RS",2031 +"2032-01-01","New Year's Day","RS",2032 +"2032-01-02","New Year's Day","RS",2032 +"2032-01-07","Orthodox Christmas Day","RS",2032 +"2032-02-15","Statehood Day","RS",2032 +"2032-02-16","Statehood Day","RS",2032 +"2032-02-17","Statehood Day (Observed)","RS",2032 +"2032-04-30","Good Friday","RS",2032 +"2032-05-01","Easter Saturday","RS",2032 +"2032-05-01","International Workers' Day","RS",2032 +"2032-05-02","Easter Sunday","RS",2032 +"2032-05-02","International Workers' Day","RS",2032 +"2032-05-03","Easter Monday","RS",2032 +"2032-05-04","International Workers' Day (Observed)","RS",2032 +"2032-11-11","Armistice Day","RS",2032 +"2033-01-01","New Year's Day","RS",2033 +"2033-01-02","New Year's Day","RS",2033 +"2033-01-03","New Year's Day (Observed)","RS",2033 +"2033-01-07","Orthodox Christmas Day","RS",2033 +"2033-02-15","Statehood Day","RS",2033 +"2033-02-16","Statehood Day","RS",2033 +"2033-04-22","Good Friday","RS",2033 +"2033-04-23","Easter Saturday","RS",2033 +"2033-04-24","Easter Sunday","RS",2033 +"2033-04-25","Easter Monday","RS",2033 +"2033-05-01","International Workers' Day","RS",2033 +"2033-05-02","International Workers' Day","RS",2033 +"2033-05-03","International Workers' Day (Observed)","RS",2033 +"2033-11-11","Armistice Day","RS",2033 +"2034-01-01","New Year's Day","RS",2034 +"2034-01-02","New Year's Day","RS",2034 +"2034-01-03","New Year's Day (Observed)","RS",2034 +"2034-01-07","Orthodox Christmas Day","RS",2034 +"2034-02-15","Statehood Day","RS",2034 +"2034-02-16","Statehood Day","RS",2034 +"2034-04-07","Good Friday","RS",2034 +"2034-04-08","Easter Saturday","RS",2034 +"2034-04-09","Easter Sunday","RS",2034 +"2034-04-10","Easter Monday","RS",2034 +"2034-05-01","International Workers' Day","RS",2034 +"2034-05-02","International Workers' Day","RS",2034 +"2034-11-11","Armistice Day","RS",2034 +"2035-01-01","New Year's Day","RS",2035 +"2035-01-02","New Year's Day","RS",2035 +"2035-01-07","Orthodox Christmas Day","RS",2035 +"2035-02-15","Statehood Day","RS",2035 +"2035-02-16","Statehood Day","RS",2035 +"2035-04-27","Good Friday","RS",2035 +"2035-04-28","Easter Saturday","RS",2035 +"2035-04-29","Easter Sunday","RS",2035 +"2035-04-30","Easter Monday","RS",2035 +"2035-05-01","International Workers' Day","RS",2035 +"2035-05-02","International Workers' Day","RS",2035 +"2035-11-11","Armistice Day","RS",2035 +"2035-11-12","Armistice Day","RS",2035 +"2036-01-01","New Year's Day","RS",2036 +"2036-01-02","New Year's Day","RS",2036 +"2036-01-07","Orthodox Christmas Day","RS",2036 +"2036-02-15","Statehood Day","RS",2036 +"2036-02-16","Statehood Day","RS",2036 +"2036-04-18","Good Friday","RS",2036 +"2036-04-19","Easter Saturday","RS",2036 +"2036-04-20","Easter Sunday","RS",2036 +"2036-04-21","Easter Monday","RS",2036 +"2036-05-01","International Workers' Day","RS",2036 +"2036-05-02","International Workers' Day","RS",2036 +"2036-11-11","Armistice Day","RS",2036 +"2037-01-01","New Year's Day","RS",2037 +"2037-01-02","New Year's Day","RS",2037 +"2037-01-07","Orthodox Christmas Day","RS",2037 +"2037-02-15","Statehood Day","RS",2037 +"2037-02-16","Statehood Day","RS",2037 +"2037-02-17","Statehood Day (Observed)","RS",2037 +"2037-04-03","Good Friday","RS",2037 +"2037-04-04","Easter Saturday","RS",2037 +"2037-04-05","Easter Sunday","RS",2037 +"2037-04-06","Easter Monday","RS",2037 +"2037-05-01","International Workers' Day","RS",2037 +"2037-05-02","International Workers' Day","RS",2037 +"2037-11-11","Armistice Day","RS",2037 +"2038-01-01","New Year's Day","RS",2038 +"2038-01-02","New Year's Day","RS",2038 +"2038-01-07","Orthodox Christmas Day","RS",2038 +"2038-02-15","Statehood Day","RS",2038 +"2038-02-16","Statehood Day","RS",2038 +"2038-04-23","Good Friday","RS",2038 +"2038-04-24","Easter Saturday","RS",2038 +"2038-04-25","Easter Sunday","RS",2038 +"2038-04-26","Easter Monday","RS",2038 +"2038-05-01","International Workers' Day","RS",2038 +"2038-05-02","International Workers' Day","RS",2038 +"2038-05-03","International Workers' Day (Observed)","RS",2038 +"2038-11-11","Armistice Day","RS",2038 +"2039-01-01","New Year's Day","RS",2039 +"2039-01-02","New Year's Day","RS",2039 +"2039-01-03","New Year's Day (Observed)","RS",2039 +"2039-01-07","Orthodox Christmas Day","RS",2039 +"2039-02-15","Statehood Day","RS",2039 +"2039-02-16","Statehood Day","RS",2039 +"2039-04-15","Good Friday","RS",2039 +"2039-04-16","Easter Saturday","RS",2039 +"2039-04-17","Easter Sunday","RS",2039 +"2039-04-18","Easter Monday","RS",2039 +"2039-05-01","International Workers' Day","RS",2039 +"2039-05-02","International Workers' Day","RS",2039 +"2039-05-03","International Workers' Day (Observed)","RS",2039 +"2039-11-11","Armistice Day","RS",2039 +"2040-01-01","New Year's Day","RS",2040 +"2040-01-02","New Year's Day","RS",2040 +"2040-01-03","New Year's Day (Observed)","RS",2040 +"2040-01-07","Orthodox Christmas Day","RS",2040 +"2040-02-15","Statehood Day","RS",2040 +"2040-02-16","Statehood Day","RS",2040 +"2040-05-01","International Workers' Day","RS",2040 +"2040-05-02","International Workers' Day","RS",2040 +"2040-05-04","Good Friday","RS",2040 +"2040-05-05","Easter Saturday","RS",2040 +"2040-05-06","Easter Sunday","RS",2040 +"2040-05-07","Easter Monday","RS",2040 +"2040-11-11","Armistice Day","RS",2040 +"2040-11-12","Armistice Day","RS",2040 +"2041-01-01","New Year's Day","RS",2041 +"2041-01-02","New Year's Day","RS",2041 +"2041-01-07","Orthodox Christmas Day","RS",2041 +"2041-02-15","Statehood Day","RS",2041 +"2041-02-16","Statehood Day","RS",2041 +"2041-04-19","Good Friday","RS",2041 +"2041-04-20","Easter Saturday","RS",2041 +"2041-04-21","Easter Sunday","RS",2041 +"2041-04-22","Easter Monday","RS",2041 +"2041-05-01","International Workers' Day","RS",2041 +"2041-05-02","International Workers' Day","RS",2041 +"2041-11-11","Armistice Day","RS",2041 +"2042-01-01","New Year's Day","RS",2042 +"2042-01-02","New Year's Day","RS",2042 +"2042-01-07","Orthodox Christmas Day","RS",2042 +"2042-02-15","Statehood Day","RS",2042 +"2042-02-16","Statehood Day","RS",2042 +"2042-02-17","Statehood Day (Observed)","RS",2042 +"2042-04-11","Good Friday","RS",2042 +"2042-04-12","Easter Saturday","RS",2042 +"2042-04-13","Easter Sunday","RS",2042 +"2042-04-14","Easter Monday","RS",2042 +"2042-05-01","International Workers' Day","RS",2042 +"2042-05-02","International Workers' Day","RS",2042 +"2042-11-11","Armistice Day","RS",2042 +"2043-01-01","New Year's Day","RS",2043 +"2043-01-02","New Year's Day","RS",2043 +"2043-01-07","Orthodox Christmas Day","RS",2043 +"2043-02-15","Statehood Day","RS",2043 +"2043-02-16","Statehood Day","RS",2043 +"2043-02-17","Statehood Day (Observed)","RS",2043 +"2043-05-01","Good Friday","RS",2043 +"2043-05-01","International Workers' Day","RS",2043 +"2043-05-02","Easter Saturday","RS",2043 +"2043-05-02","International Workers' Day","RS",2043 +"2043-05-03","Easter Sunday","RS",2043 +"2043-05-04","Easter Monday","RS",2043 +"2043-11-11","Armistice Day","RS",2043 +"2044-01-01","New Year's Day","RS",2044 +"2044-01-02","New Year's Day","RS",2044 +"2044-01-07","Orthodox Christmas Day","RS",2044 +"2044-02-15","Statehood Day","RS",2044 +"2044-02-16","Statehood Day","RS",2044 +"2044-04-22","Good Friday","RS",2044 +"2044-04-23","Easter Saturday","RS",2044 +"2044-04-24","Easter Sunday","RS",2044 +"2044-04-25","Easter Monday","RS",2044 +"2044-05-01","International Workers' Day","RS",2044 +"2044-05-02","International Workers' Day","RS",2044 +"2044-05-03","International Workers' Day (Observed)","RS",2044 +"2044-11-11","Armistice Day","RS",2044 +"1995-01-01","New Year Holidays","RU",1995 +"1995-01-02","New Year Holidays","RU",1995 +"1995-01-03","New Year Holidays","RU",1995 +"1995-01-04","New Year Holidays","RU",1995 +"1995-01-05","New Year Holidays","RU",1995 +"1995-01-06","New Year Holidays","RU",1995 +"1995-01-07","Orthodox Christmas Day","RU",1995 +"1995-01-08","New Year Holidays","RU",1995 +"1995-02-23","Fatherland Defender's Day","RU",1995 +"1995-03-08","International Women's Day","RU",1995 +"1995-05-01","Holiday of Spring and Labor","RU",1995 +"1995-05-09","Victory Day","RU",1995 +"1995-06-12","Russia's Day","RU",1995 +"1995-11-07","October Revolution Day","RU",1995 +"1996-01-01","New Year Holidays","RU",1996 +"1996-01-02","New Year Holidays","RU",1996 +"1996-01-03","New Year Holidays","RU",1996 +"1996-01-04","New Year Holidays","RU",1996 +"1996-01-05","New Year Holidays","RU",1996 +"1996-01-06","New Year Holidays","RU",1996 +"1996-01-07","Orthodox Christmas Day","RU",1996 +"1996-01-08","New Year Holidays","RU",1996 +"1996-02-23","Fatherland Defender's Day","RU",1996 +"1996-03-08","International Women's Day","RU",1996 +"1996-05-01","Holiday of Spring and Labor","RU",1996 +"1996-05-09","Victory Day","RU",1996 +"1996-06-12","Russia's Day","RU",1996 +"1996-11-07","October Revolution Day","RU",1996 +"1997-01-01","New Year Holidays","RU",1997 +"1997-01-02","New Year Holidays","RU",1997 +"1997-01-03","New Year Holidays","RU",1997 +"1997-01-04","New Year Holidays","RU",1997 +"1997-01-05","New Year Holidays","RU",1997 +"1997-01-06","New Year Holidays","RU",1997 +"1997-01-07","Orthodox Christmas Day","RU",1997 +"1997-01-08","New Year Holidays","RU",1997 +"1997-02-23","Fatherland Defender's Day","RU",1997 +"1997-03-08","International Women's Day","RU",1997 +"1997-05-01","Holiday of Spring and Labor","RU",1997 +"1997-05-09","Victory Day","RU",1997 +"1997-06-12","Russia's Day","RU",1997 +"1997-11-07","October Revolution Day","RU",1997 +"1998-01-01","New Year Holidays","RU",1998 +"1998-01-02","New Year Holidays","RU",1998 +"1998-01-03","New Year Holidays","RU",1998 +"1998-01-04","New Year Holidays","RU",1998 +"1998-01-05","New Year Holidays","RU",1998 +"1998-01-06","New Year Holidays","RU",1998 +"1998-01-07","Orthodox Christmas Day","RU",1998 +"1998-01-08","New Year Holidays","RU",1998 +"1998-02-23","Fatherland Defender's Day","RU",1998 +"1998-03-08","International Women's Day","RU",1998 +"1998-05-01","Holiday of Spring and Labor","RU",1998 +"1998-05-09","Victory Day","RU",1998 +"1998-06-12","Russia's Day","RU",1998 +"1998-11-07","October Revolution Day","RU",1998 +"1999-01-01","New Year Holidays","RU",1999 +"1999-01-02","New Year Holidays","RU",1999 +"1999-01-03","New Year Holidays","RU",1999 +"1999-01-04","New Year Holidays","RU",1999 +"1999-01-05","New Year Holidays","RU",1999 +"1999-01-06","New Year Holidays","RU",1999 +"1999-01-07","Orthodox Christmas Day","RU",1999 +"1999-01-08","New Year Holidays","RU",1999 +"1999-02-23","Fatherland Defender's Day","RU",1999 +"1999-03-08","International Women's Day","RU",1999 +"1999-05-01","Holiday of Spring and Labor","RU",1999 +"1999-05-09","Victory Day","RU",1999 +"1999-06-12","Russia's Day","RU",1999 +"1999-11-07","October Revolution Day","RU",1999 +"2000-01-01","New Year Holidays","RU",2000 +"2000-01-02","New Year Holidays","RU",2000 +"2000-01-03","New Year Holidays","RU",2000 +"2000-01-04","New Year Holidays","RU",2000 +"2000-01-05","New Year Holidays","RU",2000 +"2000-01-06","New Year Holidays","RU",2000 +"2000-01-07","Orthodox Christmas Day","RU",2000 +"2000-01-08","New Year Holidays","RU",2000 +"2000-02-23","Fatherland Defender's Day","RU",2000 +"2000-03-08","International Women's Day","RU",2000 +"2000-05-01","Holiday of Spring and Labor","RU",2000 +"2000-05-09","Victory Day","RU",2000 +"2000-06-12","Russia's Day","RU",2000 +"2000-11-07","October Revolution Day","RU",2000 +"2001-01-01","New Year Holidays","RU",2001 +"2001-01-02","New Year Holidays","RU",2001 +"2001-01-03","New Year Holidays","RU",2001 +"2001-01-04","New Year Holidays","RU",2001 +"2001-01-05","New Year Holidays","RU",2001 +"2001-01-06","New Year Holidays","RU",2001 +"2001-01-07","Orthodox Christmas Day","RU",2001 +"2001-01-08","New Year Holidays","RU",2001 +"2001-02-23","Fatherland Defender's Day","RU",2001 +"2001-03-08","International Women's Day","RU",2001 +"2001-05-01","Holiday of Spring and Labor","RU",2001 +"2001-05-09","Victory Day","RU",2001 +"2001-06-12","Russia's Day","RU",2001 +"2001-11-07","October Revolution Day","RU",2001 +"2002-01-01","New Year Holidays","RU",2002 +"2002-01-02","New Year Holidays","RU",2002 +"2002-01-03","New Year Holidays","RU",2002 +"2002-01-04","New Year Holidays","RU",2002 +"2002-01-05","New Year Holidays","RU",2002 +"2002-01-06","New Year Holidays","RU",2002 +"2002-01-07","Orthodox Christmas Day","RU",2002 +"2002-01-08","New Year Holidays","RU",2002 +"2002-02-23","Fatherland Defender's Day","RU",2002 +"2002-03-08","International Women's Day","RU",2002 +"2002-05-01","Holiday of Spring and Labor","RU",2002 +"2002-05-09","Victory Day","RU",2002 +"2002-06-12","Russia's Day","RU",2002 +"2002-11-07","October Revolution Day","RU",2002 +"2003-01-01","New Year Holidays","RU",2003 +"2003-01-02","New Year Holidays","RU",2003 +"2003-01-03","New Year Holidays","RU",2003 +"2003-01-04","New Year Holidays","RU",2003 +"2003-01-05","New Year Holidays","RU",2003 +"2003-01-06","New Year Holidays","RU",2003 +"2003-01-07","Orthodox Christmas Day","RU",2003 +"2003-01-08","New Year Holidays","RU",2003 +"2003-02-23","Fatherland Defender's Day","RU",2003 +"2003-03-08","International Women's Day","RU",2003 +"2003-05-01","Holiday of Spring and Labor","RU",2003 +"2003-05-09","Victory Day","RU",2003 +"2003-06-12","Russia's Day","RU",2003 +"2003-11-07","October Revolution Day","RU",2003 +"2004-01-01","New Year Holidays","RU",2004 +"2004-01-02","New Year Holidays","RU",2004 +"2004-01-03","New Year Holidays","RU",2004 +"2004-01-04","New Year Holidays","RU",2004 +"2004-01-05","New Year Holidays","RU",2004 +"2004-01-06","New Year Holidays","RU",2004 +"2004-01-07","Orthodox Christmas Day","RU",2004 +"2004-01-08","New Year Holidays","RU",2004 +"2004-02-23","Fatherland Defender's Day","RU",2004 +"2004-03-08","International Women's Day","RU",2004 +"2004-05-01","Holiday of Spring and Labor","RU",2004 +"2004-05-09","Victory Day","RU",2004 +"2004-06-12","Russia's Day","RU",2004 +"2004-11-07","October Revolution Day","RU",2004 +"2005-01-01","New Year Holidays","RU",2005 +"2005-01-02","New Year Holidays","RU",2005 +"2005-01-03","New Year Holidays","RU",2005 +"2005-01-04","New Year Holidays","RU",2005 +"2005-01-05","New Year Holidays","RU",2005 +"2005-01-06","New Year Holidays","RU",2005 +"2005-01-07","Orthodox Christmas Day","RU",2005 +"2005-01-08","New Year Holidays","RU",2005 +"2005-02-23","Fatherland Defender's Day","RU",2005 +"2005-03-08","International Women's Day","RU",2005 +"2005-05-01","Holiday of Spring and Labor","RU",2005 +"2005-05-09","Victory Day","RU",2005 +"2005-06-12","Russia's Day","RU",2005 +"2005-11-04","Unity Day","RU",2005 +"2006-01-01","New Year Holidays","RU",2006 +"2006-01-02","New Year Holidays","RU",2006 +"2006-01-03","New Year Holidays","RU",2006 +"2006-01-04","New Year Holidays","RU",2006 +"2006-01-05","New Year Holidays","RU",2006 +"2006-01-06","New Year Holidays","RU",2006 +"2006-01-07","Orthodox Christmas Day","RU",2006 +"2006-01-08","New Year Holidays","RU",2006 +"2006-02-23","Fatherland Defender's Day","RU",2006 +"2006-03-08","International Women's Day","RU",2006 +"2006-05-01","Holiday of Spring and Labor","RU",2006 +"2006-05-09","Victory Day","RU",2006 +"2006-06-12","Russia's Day","RU",2006 +"2006-11-04","Unity Day","RU",2006 +"2007-01-01","New Year Holidays","RU",2007 +"2007-01-02","New Year Holidays","RU",2007 +"2007-01-03","New Year Holidays","RU",2007 +"2007-01-04","New Year Holidays","RU",2007 +"2007-01-05","New Year Holidays","RU",2007 +"2007-01-06","New Year Holidays","RU",2007 +"2007-01-07","Orthodox Christmas Day","RU",2007 +"2007-01-08","New Year Holidays","RU",2007 +"2007-02-23","Fatherland Defender's Day","RU",2007 +"2007-03-08","International Women's Day","RU",2007 +"2007-05-01","Holiday of Spring and Labor","RU",2007 +"2007-05-09","Victory Day","RU",2007 +"2007-06-12","Russia's Day","RU",2007 +"2007-11-04","Unity Day","RU",2007 +"2008-01-01","New Year Holidays","RU",2008 +"2008-01-02","New Year Holidays","RU",2008 +"2008-01-03","New Year Holidays","RU",2008 +"2008-01-04","New Year Holidays","RU",2008 +"2008-01-05","New Year Holidays","RU",2008 +"2008-01-06","New Year Holidays","RU",2008 +"2008-01-07","Orthodox Christmas Day","RU",2008 +"2008-01-08","New Year Holidays","RU",2008 +"2008-02-23","Fatherland Defender's Day","RU",2008 +"2008-03-08","International Women's Day","RU",2008 +"2008-05-01","Holiday of Spring and Labor","RU",2008 +"2008-05-09","Victory Day","RU",2008 +"2008-06-12","Russia's Day","RU",2008 +"2008-11-04","Unity Day","RU",2008 +"2009-01-01","New Year Holidays","RU",2009 +"2009-01-02","New Year Holidays","RU",2009 +"2009-01-03","New Year Holidays","RU",2009 +"2009-01-04","New Year Holidays","RU",2009 +"2009-01-05","New Year Holidays","RU",2009 +"2009-01-06","New Year Holidays","RU",2009 +"2009-01-07","Orthodox Christmas Day","RU",2009 +"2009-01-08","New Year Holidays","RU",2009 +"2009-02-23","Fatherland Defender's Day","RU",2009 +"2009-03-08","International Women's Day","RU",2009 +"2009-05-01","Holiday of Spring and Labor","RU",2009 +"2009-05-09","Victory Day","RU",2009 +"2009-06-12","Russia's Day","RU",2009 +"2009-11-04","Unity Day","RU",2009 +"2010-01-01","New Year Holidays","RU",2010 +"2010-01-02","New Year Holidays","RU",2010 +"2010-01-03","New Year Holidays","RU",2010 +"2010-01-04","New Year Holidays","RU",2010 +"2010-01-05","New Year Holidays","RU",2010 +"2010-01-06","New Year Holidays","RU",2010 +"2010-01-07","Orthodox Christmas Day","RU",2010 +"2010-01-08","New Year Holidays","RU",2010 +"2010-02-23","Fatherland Defender's Day","RU",2010 +"2010-03-08","International Women's Day","RU",2010 +"2010-05-01","Holiday of Spring and Labor","RU",2010 +"2010-05-09","Victory Day","RU",2010 +"2010-06-12","Russia's Day","RU",2010 +"2010-11-04","Unity Day","RU",2010 +"2011-01-01","New Year Holidays","RU",2011 +"2011-01-02","New Year Holidays","RU",2011 +"2011-01-03","New Year Holidays","RU",2011 +"2011-01-04","New Year Holidays","RU",2011 +"2011-01-05","New Year Holidays","RU",2011 +"2011-01-06","New Year Holidays","RU",2011 +"2011-01-07","Orthodox Christmas Day","RU",2011 +"2011-01-08","New Year Holidays","RU",2011 +"2011-02-23","Fatherland Defender's Day","RU",2011 +"2011-03-08","International Women's Day","RU",2011 +"2011-05-01","Holiday of Spring and Labor","RU",2011 +"2011-05-09","Victory Day","RU",2011 +"2011-06-12","Russia's Day","RU",2011 +"2011-11-04","Unity Day","RU",2011 +"2012-01-01","New Year Holidays","RU",2012 +"2012-01-02","New Year Holidays","RU",2012 +"2012-01-03","New Year Holidays","RU",2012 +"2012-01-04","New Year Holidays","RU",2012 +"2012-01-05","New Year Holidays","RU",2012 +"2012-01-06","New Year Holidays","RU",2012 +"2012-01-07","Orthodox Christmas Day","RU",2012 +"2012-01-08","New Year Holidays","RU",2012 +"2012-02-23","Fatherland Defender's Day","RU",2012 +"2012-03-08","International Women's Day","RU",2012 +"2012-05-01","Holiday of Spring and Labor","RU",2012 +"2012-05-09","Victory Day","RU",2012 +"2012-06-12","Russia's Day","RU",2012 +"2012-11-04","Unity Day","RU",2012 +"2013-01-01","New Year Holidays","RU",2013 +"2013-01-02","New Year Holidays","RU",2013 +"2013-01-03","New Year Holidays","RU",2013 +"2013-01-04","New Year Holidays","RU",2013 +"2013-01-05","New Year Holidays","RU",2013 +"2013-01-06","New Year Holidays","RU",2013 +"2013-01-07","Orthodox Christmas Day","RU",2013 +"2013-01-08","New Year Holidays","RU",2013 +"2013-02-23","Fatherland Defender's Day","RU",2013 +"2013-03-08","International Women's Day","RU",2013 +"2013-05-01","Holiday of Spring and Labor","RU",2013 +"2013-05-09","Victory Day","RU",2013 +"2013-06-12","Russia's Day","RU",2013 +"2013-11-04","Unity Day","RU",2013 +"2014-01-01","New Year Holidays","RU",2014 +"2014-01-02","New Year Holidays","RU",2014 +"2014-01-03","New Year Holidays","RU",2014 +"2014-01-04","New Year Holidays","RU",2014 +"2014-01-05","New Year Holidays","RU",2014 +"2014-01-06","New Year Holidays","RU",2014 +"2014-01-07","Orthodox Christmas Day","RU",2014 +"2014-01-08","New Year Holidays","RU",2014 +"2014-02-23","Fatherland Defender's Day","RU",2014 +"2014-03-08","International Women's Day","RU",2014 +"2014-05-01","Holiday of Spring and Labor","RU",2014 +"2014-05-09","Victory Day","RU",2014 +"2014-06-12","Russia's Day","RU",2014 +"2014-11-04","Unity Day","RU",2014 +"2015-01-01","New Year Holidays","RU",2015 +"2015-01-02","New Year Holidays","RU",2015 +"2015-01-03","New Year Holidays","RU",2015 +"2015-01-04","New Year Holidays","RU",2015 +"2015-01-05","New Year Holidays","RU",2015 +"2015-01-06","New Year Holidays","RU",2015 +"2015-01-07","Orthodox Christmas Day","RU",2015 +"2015-01-08","New Year Holidays","RU",2015 +"2015-02-23","Fatherland Defender's Day","RU",2015 +"2015-03-08","International Women's Day","RU",2015 +"2015-05-01","Holiday of Spring and Labor","RU",2015 +"2015-05-09","Victory Day","RU",2015 +"2015-06-12","Russia's Day","RU",2015 +"2015-11-04","Unity Day","RU",2015 +"2016-01-01","New Year Holidays","RU",2016 +"2016-01-02","New Year Holidays","RU",2016 +"2016-01-03","New Year Holidays","RU",2016 +"2016-01-04","New Year Holidays","RU",2016 +"2016-01-05","New Year Holidays","RU",2016 +"2016-01-06","New Year Holidays","RU",2016 +"2016-01-07","Orthodox Christmas Day","RU",2016 +"2016-01-08","New Year Holidays","RU",2016 +"2016-02-23","Fatherland Defender's Day","RU",2016 +"2016-03-08","International Women's Day","RU",2016 +"2016-05-01","Holiday of Spring and Labor","RU",2016 +"2016-05-09","Victory Day","RU",2016 +"2016-06-12","Russia's Day","RU",2016 +"2016-11-04","Unity Day","RU",2016 +"2017-01-01","New Year Holidays","RU",2017 +"2017-01-02","New Year Holidays","RU",2017 +"2017-01-03","New Year Holidays","RU",2017 +"2017-01-04","New Year Holidays","RU",2017 +"2017-01-05","New Year Holidays","RU",2017 +"2017-01-06","New Year Holidays","RU",2017 +"2017-01-07","Orthodox Christmas Day","RU",2017 +"2017-01-08","New Year Holidays","RU",2017 +"2017-02-23","Fatherland Defender's Day","RU",2017 +"2017-03-08","International Women's Day","RU",2017 +"2017-05-01","Holiday of Spring and Labor","RU",2017 +"2017-05-09","Victory Day","RU",2017 +"2017-06-12","Russia's Day","RU",2017 +"2017-11-04","Unity Day","RU",2017 +"2018-01-01","New Year Holidays","RU",2018 +"2018-01-02","New Year Holidays","RU",2018 +"2018-01-03","New Year Holidays","RU",2018 +"2018-01-04","New Year Holidays","RU",2018 +"2018-01-05","New Year Holidays","RU",2018 +"2018-01-06","New Year Holidays","RU",2018 +"2018-01-07","Orthodox Christmas Day","RU",2018 +"2018-01-08","New Year Holidays","RU",2018 +"2018-02-23","Fatherland Defender's Day","RU",2018 +"2018-03-08","International Women's Day","RU",2018 +"2018-05-01","Holiday of Spring and Labor","RU",2018 +"2018-05-09","Victory Day","RU",2018 +"2018-06-12","Russia's Day","RU",2018 +"2018-11-04","Unity Day","RU",2018 +"2019-01-01","New Year Holidays","RU",2019 +"2019-01-02","New Year Holidays","RU",2019 +"2019-01-03","New Year Holidays","RU",2019 +"2019-01-04","New Year Holidays","RU",2019 +"2019-01-05","New Year Holidays","RU",2019 +"2019-01-06","New Year Holidays","RU",2019 +"2019-01-07","Orthodox Christmas Day","RU",2019 +"2019-01-08","New Year Holidays","RU",2019 +"2019-02-23","Fatherland Defender's Day","RU",2019 +"2019-03-08","International Women's Day","RU",2019 +"2019-05-01","Holiday of Spring and Labor","RU",2019 +"2019-05-09","Victory Day","RU",2019 +"2019-06-12","Russia's Day","RU",2019 +"2019-11-04","Unity Day","RU",2019 +"2020-01-01","New Year Holidays","RU",2020 +"2020-01-02","New Year Holidays","RU",2020 +"2020-01-03","New Year Holidays","RU",2020 +"2020-01-04","New Year Holidays","RU",2020 +"2020-01-05","New Year Holidays","RU",2020 +"2020-01-06","New Year Holidays","RU",2020 +"2020-01-07","Orthodox Christmas Day","RU",2020 +"2020-01-08","New Year Holidays","RU",2020 +"2020-02-23","Fatherland Defender's Day","RU",2020 +"2020-03-08","International Women's Day","RU",2020 +"2020-05-01","Holiday of Spring and Labor","RU",2020 +"2020-05-09","Victory Day","RU",2020 +"2020-06-12","Russia's Day","RU",2020 +"2020-11-04","Unity Day","RU",2020 +"2021-01-01","New Year Holidays","RU",2021 +"2021-01-02","New Year Holidays","RU",2021 +"2021-01-03","New Year Holidays","RU",2021 +"2021-01-04","New Year Holidays","RU",2021 +"2021-01-05","New Year Holidays","RU",2021 +"2021-01-06","New Year Holidays","RU",2021 +"2021-01-07","Orthodox Christmas Day","RU",2021 +"2021-01-08","New Year Holidays","RU",2021 +"2021-02-23","Fatherland Defender's Day","RU",2021 +"2021-03-08","International Women's Day","RU",2021 +"2021-05-01","Holiday of Spring and Labor","RU",2021 +"2021-05-09","Victory Day","RU",2021 +"2021-06-12","Russia's Day","RU",2021 +"2021-11-04","Unity Day","RU",2021 +"2022-01-01","New Year Holidays","RU",2022 +"2022-01-02","New Year Holidays","RU",2022 +"2022-01-03","New Year Holidays","RU",2022 +"2022-01-04","New Year Holidays","RU",2022 +"2022-01-05","New Year Holidays","RU",2022 +"2022-01-06","New Year Holidays","RU",2022 +"2022-01-07","Orthodox Christmas Day","RU",2022 +"2022-01-08","New Year Holidays","RU",2022 +"2022-02-23","Fatherland Defender's Day","RU",2022 +"2022-03-08","International Women's Day","RU",2022 +"2022-05-01","Holiday of Spring and Labor","RU",2022 +"2022-05-09","Victory Day","RU",2022 +"2022-06-12","Russia's Day","RU",2022 +"2022-11-04","Unity Day","RU",2022 +"2023-01-01","New Year Holidays","RU",2023 +"2023-01-02","New Year Holidays","RU",2023 +"2023-01-03","New Year Holidays","RU",2023 +"2023-01-04","New Year Holidays","RU",2023 +"2023-01-05","New Year Holidays","RU",2023 +"2023-01-06","New Year Holidays","RU",2023 +"2023-01-07","Orthodox Christmas Day","RU",2023 +"2023-01-08","New Year Holidays","RU",2023 +"2023-02-23","Fatherland Defender's Day","RU",2023 +"2023-02-24","Fatherland Defender's Day","RU",2023 +"2023-03-08","International Women's Day","RU",2023 +"2023-05-01","Holiday of Spring and Labor","RU",2023 +"2023-05-08","Victory Day","RU",2023 +"2023-05-09","Victory Day","RU",2023 +"2023-06-12","Russia's Day","RU",2023 +"2023-11-04","Unity Day","RU",2023 +"2024-01-01","New Year Holidays","RU",2024 +"2024-01-02","New Year Holidays","RU",2024 +"2024-01-03","New Year Holidays","RU",2024 +"2024-01-04","New Year Holidays","RU",2024 +"2024-01-05","New Year Holidays","RU",2024 +"2024-01-06","New Year Holidays","RU",2024 +"2024-01-07","Orthodox Christmas Day","RU",2024 +"2024-01-08","New Year Holidays","RU",2024 +"2024-02-23","Fatherland Defender's Day","RU",2024 +"2024-03-08","International Women's Day","RU",2024 +"2024-05-01","Holiday of Spring and Labor","RU",2024 +"2024-05-09","Victory Day","RU",2024 +"2024-06-12","Russia's Day","RU",2024 +"2024-11-04","Unity Day","RU",2024 +"2025-01-01","New Year Holidays","RU",2025 +"2025-01-02","New Year Holidays","RU",2025 +"2025-01-03","New Year Holidays","RU",2025 +"2025-01-04","New Year Holidays","RU",2025 +"2025-01-05","New Year Holidays","RU",2025 +"2025-01-06","New Year Holidays","RU",2025 +"2025-01-07","Orthodox Christmas Day","RU",2025 +"2025-01-08","New Year Holidays","RU",2025 +"2025-02-23","Fatherland Defender's Day","RU",2025 +"2025-03-08","International Women's Day","RU",2025 +"2025-05-01","Holiday of Spring and Labor","RU",2025 +"2025-05-09","Victory Day","RU",2025 +"2025-06-12","Russia's Day","RU",2025 +"2025-11-04","Unity Day","RU",2025 +"2026-01-01","New Year Holidays","RU",2026 +"2026-01-02","New Year Holidays","RU",2026 +"2026-01-03","New Year Holidays","RU",2026 +"2026-01-04","New Year Holidays","RU",2026 +"2026-01-05","New Year Holidays","RU",2026 +"2026-01-06","New Year Holidays","RU",2026 +"2026-01-07","Orthodox Christmas Day","RU",2026 +"2026-01-08","New Year Holidays","RU",2026 +"2026-02-23","Fatherland Defender's Day","RU",2026 +"2026-03-08","International Women's Day","RU",2026 +"2026-05-01","Holiday of Spring and Labor","RU",2026 +"2026-05-09","Victory Day","RU",2026 +"2026-06-12","Russia's Day","RU",2026 +"2026-11-04","Unity Day","RU",2026 +"2027-01-01","New Year Holidays","RU",2027 +"2027-01-02","New Year Holidays","RU",2027 +"2027-01-03","New Year Holidays","RU",2027 +"2027-01-04","New Year Holidays","RU",2027 +"2027-01-05","New Year Holidays","RU",2027 +"2027-01-06","New Year Holidays","RU",2027 +"2027-01-07","Orthodox Christmas Day","RU",2027 +"2027-01-08","New Year Holidays","RU",2027 +"2027-02-23","Fatherland Defender's Day","RU",2027 +"2027-03-08","International Women's Day","RU",2027 +"2027-05-01","Holiday of Spring and Labor","RU",2027 +"2027-05-09","Victory Day","RU",2027 +"2027-06-12","Russia's Day","RU",2027 +"2027-11-04","Unity Day","RU",2027 +"2028-01-01","New Year Holidays","RU",2028 +"2028-01-02","New Year Holidays","RU",2028 +"2028-01-03","New Year Holidays","RU",2028 +"2028-01-04","New Year Holidays","RU",2028 +"2028-01-05","New Year Holidays","RU",2028 +"2028-01-06","New Year Holidays","RU",2028 +"2028-01-07","Orthodox Christmas Day","RU",2028 +"2028-01-08","New Year Holidays","RU",2028 +"2028-02-23","Fatherland Defender's Day","RU",2028 +"2028-03-08","International Women's Day","RU",2028 +"2028-05-01","Holiday of Spring and Labor","RU",2028 +"2028-05-09","Victory Day","RU",2028 +"2028-06-12","Russia's Day","RU",2028 +"2028-11-04","Unity Day","RU",2028 +"2029-01-01","New Year Holidays","RU",2029 +"2029-01-02","New Year Holidays","RU",2029 +"2029-01-03","New Year Holidays","RU",2029 +"2029-01-04","New Year Holidays","RU",2029 +"2029-01-05","New Year Holidays","RU",2029 +"2029-01-06","New Year Holidays","RU",2029 +"2029-01-07","Orthodox Christmas Day","RU",2029 +"2029-01-08","New Year Holidays","RU",2029 +"2029-02-23","Fatherland Defender's Day","RU",2029 +"2029-03-08","International Women's Day","RU",2029 +"2029-05-01","Holiday of Spring and Labor","RU",2029 +"2029-05-09","Victory Day","RU",2029 +"2029-06-12","Russia's Day","RU",2029 +"2029-11-04","Unity Day","RU",2029 +"2030-01-01","New Year Holidays","RU",2030 +"2030-01-02","New Year Holidays","RU",2030 +"2030-01-03","New Year Holidays","RU",2030 +"2030-01-04","New Year Holidays","RU",2030 +"2030-01-05","New Year Holidays","RU",2030 +"2030-01-06","New Year Holidays","RU",2030 +"2030-01-07","Orthodox Christmas Day","RU",2030 +"2030-01-08","New Year Holidays","RU",2030 +"2030-02-23","Fatherland Defender's Day","RU",2030 +"2030-03-08","International Women's Day","RU",2030 +"2030-05-01","Holiday of Spring and Labor","RU",2030 +"2030-05-09","Victory Day","RU",2030 +"2030-06-12","Russia's Day","RU",2030 +"2030-11-04","Unity Day","RU",2030 +"2031-01-01","New Year Holidays","RU",2031 +"2031-01-02","New Year Holidays","RU",2031 +"2031-01-03","New Year Holidays","RU",2031 +"2031-01-04","New Year Holidays","RU",2031 +"2031-01-05","New Year Holidays","RU",2031 +"2031-01-06","New Year Holidays","RU",2031 +"2031-01-07","Orthodox Christmas Day","RU",2031 +"2031-01-08","New Year Holidays","RU",2031 +"2031-02-23","Fatherland Defender's Day","RU",2031 +"2031-03-08","International Women's Day","RU",2031 +"2031-05-01","Holiday of Spring and Labor","RU",2031 +"2031-05-09","Victory Day","RU",2031 +"2031-06-12","Russia's Day","RU",2031 +"2031-11-04","Unity Day","RU",2031 +"2032-01-01","New Year Holidays","RU",2032 +"2032-01-02","New Year Holidays","RU",2032 +"2032-01-03","New Year Holidays","RU",2032 +"2032-01-04","New Year Holidays","RU",2032 +"2032-01-05","New Year Holidays","RU",2032 +"2032-01-06","New Year Holidays","RU",2032 +"2032-01-07","Orthodox Christmas Day","RU",2032 +"2032-01-08","New Year Holidays","RU",2032 +"2032-02-23","Fatherland Defender's Day","RU",2032 +"2032-03-08","International Women's Day","RU",2032 +"2032-05-01","Holiday of Spring and Labor","RU",2032 +"2032-05-09","Victory Day","RU",2032 +"2032-06-12","Russia's Day","RU",2032 +"2032-11-04","Unity Day","RU",2032 +"2033-01-01","New Year Holidays","RU",2033 +"2033-01-02","New Year Holidays","RU",2033 +"2033-01-03","New Year Holidays","RU",2033 +"2033-01-04","New Year Holidays","RU",2033 +"2033-01-05","New Year Holidays","RU",2033 +"2033-01-06","New Year Holidays","RU",2033 +"2033-01-07","Orthodox Christmas Day","RU",2033 +"2033-01-08","New Year Holidays","RU",2033 +"2033-02-23","Fatherland Defender's Day","RU",2033 +"2033-03-08","International Women's Day","RU",2033 +"2033-05-01","Holiday of Spring and Labor","RU",2033 +"2033-05-09","Victory Day","RU",2033 +"2033-06-12","Russia's Day","RU",2033 +"2033-11-04","Unity Day","RU",2033 +"2034-01-01","New Year Holidays","RU",2034 +"2034-01-02","New Year Holidays","RU",2034 +"2034-01-03","New Year Holidays","RU",2034 +"2034-01-04","New Year Holidays","RU",2034 +"2034-01-05","New Year Holidays","RU",2034 +"2034-01-06","New Year Holidays","RU",2034 +"2034-01-07","Orthodox Christmas Day","RU",2034 +"2034-01-08","New Year Holidays","RU",2034 +"2034-02-23","Fatherland Defender's Day","RU",2034 +"2034-03-08","International Women's Day","RU",2034 +"2034-05-01","Holiday of Spring and Labor","RU",2034 +"2034-05-09","Victory Day","RU",2034 +"2034-06-12","Russia's Day","RU",2034 +"2034-11-04","Unity Day","RU",2034 +"2035-01-01","New Year Holidays","RU",2035 +"2035-01-02","New Year Holidays","RU",2035 +"2035-01-03","New Year Holidays","RU",2035 +"2035-01-04","New Year Holidays","RU",2035 +"2035-01-05","New Year Holidays","RU",2035 +"2035-01-06","New Year Holidays","RU",2035 +"2035-01-07","Orthodox Christmas Day","RU",2035 +"2035-01-08","New Year Holidays","RU",2035 +"2035-02-23","Fatherland Defender's Day","RU",2035 +"2035-03-08","International Women's Day","RU",2035 +"2035-05-01","Holiday of Spring and Labor","RU",2035 +"2035-05-09","Victory Day","RU",2035 +"2035-06-12","Russia's Day","RU",2035 +"2035-11-04","Unity Day","RU",2035 +"2036-01-01","New Year Holidays","RU",2036 +"2036-01-02","New Year Holidays","RU",2036 +"2036-01-03","New Year Holidays","RU",2036 +"2036-01-04","New Year Holidays","RU",2036 +"2036-01-05","New Year Holidays","RU",2036 +"2036-01-06","New Year Holidays","RU",2036 +"2036-01-07","Orthodox Christmas Day","RU",2036 +"2036-01-08","New Year Holidays","RU",2036 +"2036-02-23","Fatherland Defender's Day","RU",2036 +"2036-03-08","International Women's Day","RU",2036 +"2036-05-01","Holiday of Spring and Labor","RU",2036 +"2036-05-09","Victory Day","RU",2036 +"2036-06-12","Russia's Day","RU",2036 +"2036-11-04","Unity Day","RU",2036 +"2037-01-01","New Year Holidays","RU",2037 +"2037-01-02","New Year Holidays","RU",2037 +"2037-01-03","New Year Holidays","RU",2037 +"2037-01-04","New Year Holidays","RU",2037 +"2037-01-05","New Year Holidays","RU",2037 +"2037-01-06","New Year Holidays","RU",2037 +"2037-01-07","Orthodox Christmas Day","RU",2037 +"2037-01-08","New Year Holidays","RU",2037 +"2037-02-23","Fatherland Defender's Day","RU",2037 +"2037-03-08","International Women's Day","RU",2037 +"2037-05-01","Holiday of Spring and Labor","RU",2037 +"2037-05-09","Victory Day","RU",2037 +"2037-06-12","Russia's Day","RU",2037 +"2037-11-04","Unity Day","RU",2037 +"2038-01-01","New Year Holidays","RU",2038 +"2038-01-02","New Year Holidays","RU",2038 +"2038-01-03","New Year Holidays","RU",2038 +"2038-01-04","New Year Holidays","RU",2038 +"2038-01-05","New Year Holidays","RU",2038 +"2038-01-06","New Year Holidays","RU",2038 +"2038-01-07","Orthodox Christmas Day","RU",2038 +"2038-01-08","New Year Holidays","RU",2038 +"2038-02-23","Fatherland Defender's Day","RU",2038 +"2038-03-08","International Women's Day","RU",2038 +"2038-05-01","Holiday of Spring and Labor","RU",2038 +"2038-05-09","Victory Day","RU",2038 +"2038-06-12","Russia's Day","RU",2038 +"2038-11-04","Unity Day","RU",2038 +"2039-01-01","New Year Holidays","RU",2039 +"2039-01-02","New Year Holidays","RU",2039 +"2039-01-03","New Year Holidays","RU",2039 +"2039-01-04","New Year Holidays","RU",2039 +"2039-01-05","New Year Holidays","RU",2039 +"2039-01-06","New Year Holidays","RU",2039 +"2039-01-07","Orthodox Christmas Day","RU",2039 +"2039-01-08","New Year Holidays","RU",2039 +"2039-02-23","Fatherland Defender's Day","RU",2039 +"2039-03-08","International Women's Day","RU",2039 +"2039-05-01","Holiday of Spring and Labor","RU",2039 +"2039-05-09","Victory Day","RU",2039 +"2039-06-12","Russia's Day","RU",2039 +"2039-11-04","Unity Day","RU",2039 +"2040-01-01","New Year Holidays","RU",2040 +"2040-01-02","New Year Holidays","RU",2040 +"2040-01-03","New Year Holidays","RU",2040 +"2040-01-04","New Year Holidays","RU",2040 +"2040-01-05","New Year Holidays","RU",2040 +"2040-01-06","New Year Holidays","RU",2040 +"2040-01-07","Orthodox Christmas Day","RU",2040 +"2040-01-08","New Year Holidays","RU",2040 +"2040-02-23","Fatherland Defender's Day","RU",2040 +"2040-03-08","International Women's Day","RU",2040 +"2040-05-01","Holiday of Spring and Labor","RU",2040 +"2040-05-09","Victory Day","RU",2040 +"2040-06-12","Russia's Day","RU",2040 +"2040-11-04","Unity Day","RU",2040 +"2041-01-01","New Year Holidays","RU",2041 +"2041-01-02","New Year Holidays","RU",2041 +"2041-01-03","New Year Holidays","RU",2041 +"2041-01-04","New Year Holidays","RU",2041 +"2041-01-05","New Year Holidays","RU",2041 +"2041-01-06","New Year Holidays","RU",2041 +"2041-01-07","Orthodox Christmas Day","RU",2041 +"2041-01-08","New Year Holidays","RU",2041 +"2041-02-23","Fatherland Defender's Day","RU",2041 +"2041-03-08","International Women's Day","RU",2041 +"2041-05-01","Holiday of Spring and Labor","RU",2041 +"2041-05-09","Victory Day","RU",2041 +"2041-06-12","Russia's Day","RU",2041 +"2041-11-04","Unity Day","RU",2041 +"2042-01-01","New Year Holidays","RU",2042 +"2042-01-02","New Year Holidays","RU",2042 +"2042-01-03","New Year Holidays","RU",2042 +"2042-01-04","New Year Holidays","RU",2042 +"2042-01-05","New Year Holidays","RU",2042 +"2042-01-06","New Year Holidays","RU",2042 +"2042-01-07","Orthodox Christmas Day","RU",2042 +"2042-01-08","New Year Holidays","RU",2042 +"2042-02-23","Fatherland Defender's Day","RU",2042 +"2042-03-08","International Women's Day","RU",2042 +"2042-05-01","Holiday of Spring and Labor","RU",2042 +"2042-05-09","Victory Day","RU",2042 +"2042-06-12","Russia's Day","RU",2042 +"2042-11-04","Unity Day","RU",2042 +"2043-01-01","New Year Holidays","RU",2043 +"2043-01-02","New Year Holidays","RU",2043 +"2043-01-03","New Year Holidays","RU",2043 +"2043-01-04","New Year Holidays","RU",2043 +"2043-01-05","New Year Holidays","RU",2043 +"2043-01-06","New Year Holidays","RU",2043 +"2043-01-07","Orthodox Christmas Day","RU",2043 +"2043-01-08","New Year Holidays","RU",2043 +"2043-02-23","Fatherland Defender's Day","RU",2043 +"2043-03-08","International Women's Day","RU",2043 +"2043-05-01","Holiday of Spring and Labor","RU",2043 +"2043-05-09","Victory Day","RU",2043 +"2043-06-12","Russia's Day","RU",2043 +"2043-11-04","Unity Day","RU",2043 +"2044-01-01","New Year Holidays","RU",2044 +"2044-01-02","New Year Holidays","RU",2044 +"2044-01-03","New Year Holidays","RU",2044 +"2044-01-04","New Year Holidays","RU",2044 +"2044-01-05","New Year Holidays","RU",2044 +"2044-01-06","New Year Holidays","RU",2044 +"2044-01-07","Orthodox Christmas Day","RU",2044 +"2044-01-08","New Year Holidays","RU",2044 +"2044-02-23","Fatherland Defender's Day","RU",2044 +"2044-03-08","International Women's Day","RU",2044 +"2044-05-01","Holiday of Spring and Labor","RU",2044 +"2044-05-09","Victory Day","RU",2044 +"2044-06-12","Russia's Day","RU",2044 +"2044-11-04","Unity Day","RU",2044 +"1995-03-02","Eid al-Fitr Holiday* (*estimated)","SA",1995 +"1995-03-03","Eid al-Fitr Holiday* (*estimated)","SA",1995 +"1995-03-04","Eid al-Fitr Holiday* (*estimated)","SA",1995 +"1995-03-05","Eid al-Fitr Holiday* (*estimated)","SA",1995 +"1995-03-06","Eid al-Fitr Holiday (Observed)","SA",1995 +"1995-03-07","Eid al-Fitr Holiday (Observed)","SA",1995 +"1995-05-08","Arafat Day Holiday* (*estimated)","SA",1995 +"1995-05-09","Eid al-Adha Holiday* (*estimated)","SA",1995 +"1995-05-10","Eid al-Adha Holiday* (*estimated)","SA",1995 +"1995-05-11","Eid al-Adha Holiday* (*estimated)","SA",1995 +"1995-05-12","Eid al-Adha Holiday (Observed)","SA",1995 +"1996-02-19","Eid al-Fitr Holiday* (*estimated)","SA",1996 +"1996-02-20","Eid al-Fitr Holiday* (*estimated)","SA",1996 +"1996-02-21","Eid al-Fitr Holiday* (*estimated)","SA",1996 +"1996-02-22","Eid al-Fitr Holiday* (*estimated)","SA",1996 +"1996-02-23","Eid al-Fitr Holiday (Observed)","SA",1996 +"1996-04-26","Arafat Day Holiday* (*estimated)","SA",1996 +"1996-04-27","Eid al-Adha Holiday* (*estimated)","SA",1996 +"1996-04-28","Eid al-Adha Holiday* (*estimated)","SA",1996 +"1996-04-29","Eid al-Adha Holiday* (*estimated)","SA",1996 +"1996-04-30","Eid al-Adha Holiday (Observed)","SA",1996 +"1997-02-08","Eid al-Fitr Holiday* (*estimated)","SA",1997 +"1997-02-09","Eid al-Fitr Holiday* (*estimated)","SA",1997 +"1997-02-10","Eid al-Fitr Holiday* (*estimated)","SA",1997 +"1997-02-11","Eid al-Fitr Holiday* (*estimated)","SA",1997 +"1997-04-16","Arafat Day Holiday* (*estimated)","SA",1997 +"1997-04-17","Eid al-Adha Holiday* (*estimated)","SA",1997 +"1997-04-18","Eid al-Adha Holiday* (*estimated)","SA",1997 +"1997-04-19","Eid al-Adha Holiday* (*estimated)","SA",1997 +"1997-04-20","Eid al-Adha Holiday (Observed)","SA",1997 +"1997-04-21","Eid al-Adha Holiday (Observed)","SA",1997 +"1998-01-29","Eid al-Fitr Holiday* (*estimated)","SA",1998 +"1998-01-30","Eid al-Fitr Holiday* (*estimated)","SA",1998 +"1998-01-31","Eid al-Fitr Holiday* (*estimated)","SA",1998 +"1998-02-01","Eid al-Fitr Holiday* (*estimated)","SA",1998 +"1998-02-02","Eid al-Fitr Holiday (Observed)","SA",1998 +"1998-02-03","Eid al-Fitr Holiday (Observed)","SA",1998 +"1998-04-06","Arafat Day Holiday* (*estimated)","SA",1998 +"1998-04-07","Eid al-Adha Holiday* (*estimated)","SA",1998 +"1998-04-08","Eid al-Adha Holiday* (*estimated)","SA",1998 +"1998-04-09","Eid al-Adha Holiday* (*estimated)","SA",1998 +"1998-04-10","Eid al-Adha Holiday (Observed)","SA",1998 +"1999-01-18","Eid al-Fitr Holiday* (*estimated)","SA",1999 +"1999-01-19","Eid al-Fitr Holiday* (*estimated)","SA",1999 +"1999-01-20","Eid al-Fitr Holiday* (*estimated)","SA",1999 +"1999-01-21","Eid al-Fitr Holiday* (*estimated)","SA",1999 +"1999-01-22","Eid al-Fitr Holiday (Observed)","SA",1999 +"1999-03-26","Arafat Day Holiday* (*estimated)","SA",1999 +"1999-03-27","Eid al-Adha Holiday* (*estimated)","SA",1999 +"1999-03-28","Eid al-Adha Holiday* (*estimated)","SA",1999 +"1999-03-29","Eid al-Adha Holiday* (*estimated)","SA",1999 +"1999-03-30","Eid al-Adha Holiday (Observed)","SA",1999 +"2000-01-08","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-01-09","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-01-10","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-01-11","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-03-15","Arafat Day Holiday* (*estimated)","SA",2000 +"2000-03-16","Eid al-Adha Holiday* (*estimated)","SA",2000 +"2000-03-17","Eid al-Adha Holiday* (*estimated)","SA",2000 +"2000-03-18","Eid al-Adha Holiday* (*estimated)","SA",2000 +"2000-03-19","Eid al-Adha Holiday (Observed)","SA",2000 +"2000-03-20","Eid al-Adha Holiday (Observed)","SA",2000 +"2000-12-27","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-12-28","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-12-29","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-12-30","Eid al-Fitr Holiday* (*estimated)","SA",2000 +"2000-12-31","Eid al-Fitr Holiday (Observed)","SA",2000 +"2001-01-01","Eid al-Fitr Holiday (Observed)","SA",2001 +"2001-03-04","Arafat Day Holiday* (*estimated)","SA",2001 +"2001-03-05","Eid al-Adha Holiday* (*estimated)","SA",2001 +"2001-03-06","Eid al-Adha Holiday* (*estimated)","SA",2001 +"2001-03-07","Eid al-Adha Holiday* (*estimated)","SA",2001 +"2001-12-16","Eid al-Fitr Holiday* (*estimated)","SA",2001 +"2001-12-17","Eid al-Fitr Holiday* (*estimated)","SA",2001 +"2001-12-18","Eid al-Fitr Holiday* (*estimated)","SA",2001 +"2001-12-19","Eid al-Fitr Holiday* (*estimated)","SA",2001 +"2002-02-21","Arafat Day Holiday* (*estimated)","SA",2002 +"2002-02-22","Eid al-Adha Holiday* (*estimated)","SA",2002 +"2002-02-23","Eid al-Adha Holiday* (*estimated)","SA",2002 +"2002-02-24","Eid al-Adha Holiday* (*estimated)","SA",2002 +"2002-02-25","Eid al-Adha Holiday (Observed)","SA",2002 +"2002-02-26","Eid al-Adha Holiday (Observed)","SA",2002 +"2002-12-05","Eid al-Fitr Holiday* (*estimated)","SA",2002 +"2002-12-06","Eid al-Fitr Holiday* (*estimated)","SA",2002 +"2002-12-07","Eid al-Fitr Holiday* (*estimated)","SA",2002 +"2002-12-08","Eid al-Fitr Holiday* (*estimated)","SA",2002 +"2002-12-09","Eid al-Fitr Holiday (Observed)","SA",2002 +"2002-12-10","Eid al-Fitr Holiday (Observed)","SA",2002 +"2003-02-10","Arafat Day Holiday* (*estimated)","SA",2003 +"2003-02-11","Eid al-Adha Holiday* (*estimated)","SA",2003 +"2003-02-12","Eid al-Adha Holiday* (*estimated)","SA",2003 +"2003-02-13","Eid al-Adha Holiday* (*estimated)","SA",2003 +"2003-02-14","Eid al-Adha Holiday (Observed)","SA",2003 +"2003-11-25","Eid al-Fitr Holiday* (*estimated)","SA",2003 +"2003-11-26","Eid al-Fitr Holiday* (*estimated)","SA",2003 +"2003-11-27","Eid al-Fitr Holiday* (*estimated)","SA",2003 +"2003-11-28","Eid al-Fitr Holiday* (*estimated)","SA",2003 +"2003-11-29","Eid al-Fitr Holiday (Observed)","SA",2003 +"2003-11-30","Eid al-Fitr Holiday (Observed)","SA",2003 +"2004-01-31","Arafat Day Holiday* (*estimated)","SA",2004 +"2004-02-01","Eid al-Adha Holiday* (*estimated)","SA",2004 +"2004-02-02","Eid al-Adha Holiday* (*estimated)","SA",2004 +"2004-02-03","Eid al-Adha Holiday* (*estimated)","SA",2004 +"2004-11-14","Eid al-Fitr Holiday* (*estimated)","SA",2004 +"2004-11-15","Eid al-Fitr Holiday* (*estimated)","SA",2004 +"2004-11-16","Eid al-Fitr Holiday* (*estimated)","SA",2004 +"2004-11-17","Eid al-Fitr Holiday* (*estimated)","SA",2004 +"2005-01-20","Arafat Day Holiday* (*estimated)","SA",2005 +"2005-01-21","Eid al-Adha Holiday* (*estimated)","SA",2005 +"2005-01-22","Eid al-Adha Holiday* (*estimated)","SA",2005 +"2005-01-23","Eid al-Adha Holiday* (*estimated)","SA",2005 +"2005-01-24","Eid al-Adha Holiday (Observed)","SA",2005 +"2005-01-25","Eid al-Adha Holiday (Observed)","SA",2005 +"2005-09-23","National Day Holiday","SA",2005 +"2005-09-24","National Day Holiday (Observed)","SA",2005 +"2005-11-03","Eid al-Fitr Holiday* (*estimated)","SA",2005 +"2005-11-04","Eid al-Fitr Holiday* (*estimated)","SA",2005 +"2005-11-05","Eid al-Fitr Holiday* (*estimated)","SA",2005 +"2005-11-06","Eid al-Fitr Holiday* (*estimated)","SA",2005 +"2005-11-07","Eid al-Fitr Holiday (Observed)","SA",2005 +"2005-11-08","Eid al-Fitr Holiday (Observed)","SA",2005 +"2006-01-09","Arafat Day Holiday* (*estimated)","SA",2006 +"2006-01-10","Eid al-Adha Holiday* (*estimated)","SA",2006 +"2006-01-11","Eid al-Adha Holiday* (*estimated)","SA",2006 +"2006-01-12","Eid al-Adha Holiday* (*estimated)","SA",2006 +"2006-01-13","Eid al-Adha Holiday (Observed)","SA",2006 +"2006-09-23","National Day Holiday","SA",2006 +"2006-10-23","Eid al-Fitr Holiday* (*estimated)","SA",2006 +"2006-10-24","Eid al-Fitr Holiday* (*estimated)","SA",2006 +"2006-10-25","Eid al-Fitr Holiday* (*estimated)","SA",2006 +"2006-10-26","Eid al-Fitr Holiday* (*estimated)","SA",2006 +"2006-10-27","Eid al-Fitr Holiday (Observed)","SA",2006 +"2006-12-30","Arafat Day Holiday* (*estimated)","SA",2006 +"2006-12-31","Eid al-Adha Holiday* (*estimated)","SA",2006 +"2007-01-01","Eid al-Adha Holiday* (*estimated)","SA",2007 +"2007-01-02","Eid al-Adha Holiday* (*estimated)","SA",2007 +"2007-09-23","National Day Holiday","SA",2007 +"2007-10-13","Eid al-Fitr Holiday* (*estimated)","SA",2007 +"2007-10-14","Eid al-Fitr Holiday* (*estimated)","SA",2007 +"2007-10-15","Eid al-Fitr Holiday* (*estimated)","SA",2007 +"2007-10-16","Eid al-Fitr Holiday* (*estimated)","SA",2007 +"2007-12-19","Arafat Day Holiday* (*estimated)","SA",2007 +"2007-12-20","Eid al-Adha Holiday* (*estimated)","SA",2007 +"2007-12-21","Eid al-Adha Holiday* (*estimated)","SA",2007 +"2007-12-22","Eid al-Adha Holiday* (*estimated)","SA",2007 +"2007-12-23","Eid al-Adha Holiday (Observed)","SA",2007 +"2007-12-24","Eid al-Adha Holiday (Observed)","SA",2007 +"2008-09-23","National Day Holiday","SA",2008 +"2008-10-01","Eid al-Fitr Holiday* (*estimated)","SA",2008 +"2008-10-02","Eid al-Fitr Holiday* (*estimated)","SA",2008 +"2008-10-03","Eid al-Fitr Holiday* (*estimated)","SA",2008 +"2008-10-04","Eid al-Fitr Holiday* (*estimated)","SA",2008 +"2008-10-05","Eid al-Fitr Holiday (Observed)","SA",2008 +"2008-10-06","Eid al-Fitr Holiday (Observed)","SA",2008 +"2008-12-07","Arafat Day Holiday* (*estimated)","SA",2008 +"2008-12-08","Eid al-Adha Holiday* (*estimated)","SA",2008 +"2008-12-09","Eid al-Adha Holiday* (*estimated)","SA",2008 +"2008-12-10","Eid al-Adha Holiday* (*estimated)","SA",2008 +"2009-09-20","Eid al-Fitr Holiday* (*estimated)","SA",2009 +"2009-09-21","Eid al-Fitr Holiday* (*estimated)","SA",2009 +"2009-09-22","Eid al-Fitr Holiday* (*estimated)","SA",2009 +"2009-09-23","Eid al-Fitr Holiday* (*estimated)","SA",2009 +"2009-11-26","Arafat Day Holiday* (*estimated)","SA",2009 +"2009-11-27","Eid al-Adha Holiday* (*estimated)","SA",2009 +"2009-11-28","Eid al-Adha Holiday* (*estimated)","SA",2009 +"2009-11-29","Eid al-Adha Holiday* (*estimated)","SA",2009 +"2009-11-30","Eid al-Adha Holiday (Observed)","SA",2009 +"2009-12-01","Eid al-Adha Holiday (Observed)","SA",2009 +"2010-09-10","Eid al-Fitr Holiday* (*estimated)","SA",2010 +"2010-09-11","Eid al-Fitr Holiday* (*estimated)","SA",2010 +"2010-09-12","Eid al-Fitr Holiday* (*estimated)","SA",2010 +"2010-09-13","Eid al-Fitr Holiday* (*estimated)","SA",2010 +"2010-09-14","Eid al-Fitr Holiday (Observed)","SA",2010 +"2010-09-22","National Day Holiday (Observed)","SA",2010 +"2010-09-23","National Day Holiday","SA",2010 +"2010-11-15","Arafat Day Holiday* (*estimated)","SA",2010 +"2010-11-16","Eid al-Adha Holiday* (*estimated)","SA",2010 +"2010-11-17","Eid al-Adha Holiday* (*estimated)","SA",2010 +"2010-11-18","Eid al-Adha Holiday* (*estimated)","SA",2010 +"2010-11-19","Eid al-Adha Holiday (Observed)","SA",2010 +"2011-08-30","Eid al-Fitr Holiday* (*estimated)","SA",2011 +"2011-08-31","Eid al-Fitr Holiday* (*estimated)","SA",2011 +"2011-09-01","Eid al-Fitr Holiday* (*estimated)","SA",2011 +"2011-09-02","Eid al-Fitr Holiday* (*estimated)","SA",2011 +"2011-09-03","Eid al-Fitr Holiday (Observed)","SA",2011 +"2011-09-04","Eid al-Fitr Holiday (Observed)","SA",2011 +"2011-09-23","National Day Holiday","SA",2011 +"2011-09-24","National Day Holiday (Observed)","SA",2011 +"2011-11-05","Arafat Day Holiday* (*estimated)","SA",2011 +"2011-11-06","Eid al-Adha Holiday* (*estimated)","SA",2011 +"2011-11-07","Eid al-Adha Holiday* (*estimated)","SA",2011 +"2011-11-08","Eid al-Adha Holiday* (*estimated)","SA",2011 +"2012-08-19","Eid al-Fitr Holiday* (*estimated)","SA",2012 +"2012-08-20","Eid al-Fitr Holiday* (*estimated)","SA",2012 +"2012-08-21","Eid al-Fitr Holiday* (*estimated)","SA",2012 +"2012-08-22","Eid al-Fitr Holiday* (*estimated)","SA",2012 +"2012-09-23","National Day Holiday","SA",2012 +"2012-10-25","Arafat Day Holiday* (*estimated)","SA",2012 +"2012-10-26","Eid al-Adha Holiday* (*estimated)","SA",2012 +"2012-10-27","Eid al-Adha Holiday* (*estimated)","SA",2012 +"2012-10-28","Eid al-Adha Holiday* (*estimated)","SA",2012 +"2012-10-29","Eid al-Adha Holiday (Observed)","SA",2012 +"2012-10-30","Eid al-Adha Holiday (Observed)","SA",2012 +"2013-08-08","Eid al-Fitr Holiday* (*estimated)","SA",2013 +"2013-08-09","Eid al-Fitr Holiday* (*estimated)","SA",2013 +"2013-08-10","Eid al-Fitr Holiday* (*estimated)","SA",2013 +"2013-08-11","Eid al-Fitr Holiday* (*estimated)","SA",2013 +"2013-08-12","Eid al-Fitr Holiday (Observed)","SA",2013 +"2013-08-13","Eid al-Fitr Holiday (Observed)","SA",2013 +"2013-09-23","National Day Holiday","SA",2013 +"2013-10-14","Arafat Day Holiday* (*estimated)","SA",2013 +"2013-10-15","Eid al-Adha Holiday* (*estimated)","SA",2013 +"2013-10-16","Eid al-Adha Holiday* (*estimated)","SA",2013 +"2013-10-17","Eid al-Adha Holiday* (*estimated)","SA",2013 +"2014-07-28","Eid al-Fitr Holiday* (*estimated)","SA",2014 +"2014-07-29","Eid al-Fitr Holiday* (*estimated)","SA",2014 +"2014-07-30","Eid al-Fitr Holiday* (*estimated)","SA",2014 +"2014-07-31","Eid al-Fitr Holiday* (*estimated)","SA",2014 +"2014-09-23","National Day Holiday","SA",2014 +"2014-10-03","Arafat Day Holiday* (*estimated)","SA",2014 +"2014-10-04","Eid al-Adha Holiday* (*estimated)","SA",2014 +"2014-10-05","Eid al-Adha Holiday* (*estimated)","SA",2014 +"2014-10-06","Eid al-Adha Holiday* (*estimated)","SA",2014 +"2014-10-07","Eid al-Adha Holiday (Observed)","SA",2014 +"2014-10-08","Eid al-Adha Holiday (Observed)","SA",2014 +"2015-07-17","Eid al-Fitr Holiday* (*estimated)","SA",2015 +"2015-07-18","Eid al-Fitr Holiday* (*estimated)","SA",2015 +"2015-07-19","Eid al-Fitr Holiday* (*estimated)","SA",2015 +"2015-07-20","Eid al-Fitr Holiday* (*estimated)","SA",2015 +"2015-07-21","Eid al-Fitr Holiday (Observed)","SA",2015 +"2015-07-22","Eid al-Fitr Holiday (Observed)","SA",2015 +"2015-09-22","Arafat Day Holiday* (*estimated)","SA",2015 +"2015-09-23","Eid al-Adha Holiday* (*estimated)","SA",2015 +"2015-09-24","Eid al-Adha Holiday* (*estimated)","SA",2015 +"2015-09-25","Eid al-Adha Holiday* (*estimated)","SA",2015 +"2015-09-26","Eid al-Adha Holiday (Observed)","SA",2015 +"2016-07-06","Eid al-Fitr Holiday* (*estimated)","SA",2016 +"2016-07-07","Eid al-Fitr Holiday* (*estimated)","SA",2016 +"2016-07-08","Eid al-Fitr Holiday* (*estimated)","SA",2016 +"2016-07-09","Eid al-Fitr Holiday* (*estimated)","SA",2016 +"2016-07-10","Eid al-Fitr Holiday (Observed)","SA",2016 +"2016-07-11","Eid al-Fitr Holiday (Observed)","SA",2016 +"2016-09-10","Arafat Day Holiday* (*estimated)","SA",2016 +"2016-09-11","Eid al-Adha Holiday* (*estimated)","SA",2016 +"2016-09-12","Eid al-Adha Holiday* (*estimated)","SA",2016 +"2016-09-13","Eid al-Adha Holiday* (*estimated)","SA",2016 +"2016-09-14","Eid al-Adha Holiday (Observed)","SA",2016 +"2016-09-22","National Day Holiday (Observed)","SA",2016 +"2016-09-23","National Day Holiday","SA",2016 +"2017-06-25","Eid al-Fitr Holiday* (*estimated)","SA",2017 +"2017-06-26","Eid al-Fitr Holiday* (*estimated)","SA",2017 +"2017-06-27","Eid al-Fitr Holiday* (*estimated)","SA",2017 +"2017-06-28","Eid al-Fitr Holiday* (*estimated)","SA",2017 +"2017-08-31","Arafat Day Holiday* (*estimated)","SA",2017 +"2017-09-01","Eid al-Adha Holiday* (*estimated)","SA",2017 +"2017-09-02","Eid al-Adha Holiday* (*estimated)","SA",2017 +"2017-09-03","Eid al-Adha Holiday* (*estimated)","SA",2017 +"2017-09-04","Eid al-Adha Holiday (Observed)","SA",2017 +"2017-09-05","Eid al-Adha Holiday (Observed)","SA",2017 +"2017-09-23","National Day Holiday","SA",2017 +"2017-09-24","National Day Holiday (Observed)","SA",2017 +"2018-06-15","Eid al-Fitr Holiday* (*estimated)","SA",2018 +"2018-06-16","Eid al-Fitr Holiday* (*estimated)","SA",2018 +"2018-06-17","Eid al-Fitr Holiday* (*estimated)","SA",2018 +"2018-06-18","Eid al-Fitr Holiday* (*estimated)","SA",2018 +"2018-06-19","Eid al-Fitr Holiday (Observed)","SA",2018 +"2018-06-20","Eid al-Fitr Holiday (Observed)","SA",2018 +"2018-08-20","Arafat Day Holiday* (*estimated)","SA",2018 +"2018-08-21","Eid al-Adha Holiday* (*estimated)","SA",2018 +"2018-08-22","Eid al-Adha Holiday* (*estimated)","SA",2018 +"2018-08-23","Eid al-Adha Holiday* (*estimated)","SA",2018 +"2018-09-23","National Day Holiday","SA",2018 +"2019-06-04","Eid al-Fitr Holiday* (*estimated)","SA",2019 +"2019-06-05","Eid al-Fitr Holiday* (*estimated)","SA",2019 +"2019-06-06","Eid al-Fitr Holiday* (*estimated)","SA",2019 +"2019-06-07","Eid al-Fitr Holiday* (*estimated)","SA",2019 +"2019-06-08","Eid al-Fitr Holiday (Observed)","SA",2019 +"2019-08-10","Arafat Day Holiday* (*estimated)","SA",2019 +"2019-08-11","Eid al-Adha Holiday* (*estimated)","SA",2019 +"2019-08-12","Eid al-Adha Holiday* (*estimated)","SA",2019 +"2019-08-13","Eid al-Adha Holiday* (*estimated)","SA",2019 +"2019-08-14","Eid al-Adha Holiday (Observed)","SA",2019 +"2019-09-23","National Day Holiday","SA",2019 +"2020-05-24","Eid al-Fitr Holiday* (*estimated)","SA",2020 +"2020-05-25","Eid al-Fitr Holiday* (*estimated)","SA",2020 +"2020-05-26","Eid al-Fitr Holiday* (*estimated)","SA",2020 +"2020-05-27","Eid al-Fitr Holiday* (*estimated)","SA",2020 +"2020-07-30","Arafat Day Holiday* (*estimated)","SA",2020 +"2020-07-31","Eid al-Adha Holiday* (*estimated)","SA",2020 +"2020-08-01","Eid al-Adha Holiday* (*estimated)","SA",2020 +"2020-08-02","Eid al-Adha Holiday* (*estimated)","SA",2020 +"2020-08-03","Eid al-Adha Holiday (Observed)","SA",2020 +"2020-08-04","Eid al-Adha Holiday (Observed)","SA",2020 +"2020-09-23","National Day Holiday","SA",2020 +"2021-05-13","Eid al-Fitr Holiday* (*estimated)","SA",2021 +"2021-05-14","Eid al-Fitr Holiday* (*estimated)","SA",2021 +"2021-05-15","Eid al-Fitr Holiday* (*estimated)","SA",2021 +"2021-05-16","Eid al-Fitr Holiday* (*estimated)","SA",2021 +"2021-05-17","Eid al-Fitr Holiday (Observed)","SA",2021 +"2021-05-18","Eid al-Fitr Holiday (Observed)","SA",2021 +"2021-07-19","Arafat Day Holiday* (*estimated)","SA",2021 +"2021-07-20","Eid al-Adha Holiday* (*estimated)","SA",2021 +"2021-07-21","Eid al-Adha Holiday* (*estimated)","SA",2021 +"2021-07-22","Eid al-Adha Holiday* (*estimated)","SA",2021 +"2021-09-23","National Day Holiday","SA",2021 +"2022-02-22","Founding Day Holiday","SA",2022 +"2022-05-02","Eid al-Fitr Holiday* (*estimated)","SA",2022 +"2022-05-03","Eid al-Fitr Holiday* (*estimated)","SA",2022 +"2022-05-04","Eid al-Fitr Holiday* (*estimated)","SA",2022 +"2022-05-05","Eid al-Fitr Holiday* (*estimated)","SA",2022 +"2022-07-08","Arafat Day Holiday* (*estimated)","SA",2022 +"2022-07-09","Eid al-Adha Holiday* (*estimated)","SA",2022 +"2022-07-10","Eid al-Adha Holiday* (*estimated)","SA",2022 +"2022-07-11","Eid al-Adha Holiday* (*estimated)","SA",2022 +"2022-07-12","Eid al-Adha Holiday (Observed)","SA",2022 +"2022-07-13","Eid al-Adha Holiday (Observed)","SA",2022 +"2022-09-22","National Day Holiday (Observed)","SA",2022 +"2022-09-23","National Day Holiday","SA",2022 +"2022-11-23","National Holiday","SA",2022 +"2023-02-22","Founding Day Holiday","SA",2023 +"2023-04-21","Eid al-Fitr Holiday* (*estimated)","SA",2023 +"2023-04-22","Eid al-Fitr Holiday* (*estimated)","SA",2023 +"2023-04-23","Eid al-Fitr Holiday* (*estimated)","SA",2023 +"2023-04-24","Eid al-Fitr Holiday* (*estimated)","SA",2023 +"2023-04-25","Eid al-Fitr Holiday (Observed)","SA",2023 +"2023-04-26","Eid al-Fitr Holiday (Observed)","SA",2023 +"2023-06-27","Arafat Day Holiday* (*estimated)","SA",2023 +"2023-06-28","Eid al-Adha Holiday* (*estimated)","SA",2023 +"2023-06-29","Eid al-Adha Holiday* (*estimated)","SA",2023 +"2023-06-30","Eid al-Adha Holiday* (*estimated)","SA",2023 +"2023-07-01","Eid al-Adha Holiday (Observed)","SA",2023 +"2023-09-23","National Day Holiday","SA",2023 +"2023-09-24","National Day Holiday (Observed)","SA",2023 +"2024-02-22","Founding Day Holiday","SA",2024 +"2024-04-10","Eid al-Fitr Holiday* (*estimated)","SA",2024 +"2024-04-11","Eid al-Fitr Holiday* (*estimated)","SA",2024 +"2024-04-12","Eid al-Fitr Holiday* (*estimated)","SA",2024 +"2024-04-13","Eid al-Fitr Holiday* (*estimated)","SA",2024 +"2024-04-14","Eid al-Fitr Holiday (Observed)","SA",2024 +"2024-04-15","Eid al-Fitr Holiday (Observed)","SA",2024 +"2024-06-15","Arafat Day Holiday* (*estimated)","SA",2024 +"2024-06-16","Eid al-Adha Holiday* (*estimated)","SA",2024 +"2024-06-17","Eid al-Adha Holiday* (*estimated)","SA",2024 +"2024-06-18","Eid al-Adha Holiday* (*estimated)","SA",2024 +"2024-06-19","Eid al-Adha Holiday (Observed)","SA",2024 +"2024-09-23","National Day Holiday","SA",2024 +"2025-02-22","Founding Day Holiday","SA",2025 +"2025-02-23","Founding Day Holiday (Observed)","SA",2025 +"2025-03-30","Eid al-Fitr Holiday* (*estimated)","SA",2025 +"2025-03-31","Eid al-Fitr Holiday* (*estimated)","SA",2025 +"2025-04-01","Eid al-Fitr Holiday* (*estimated)","SA",2025 +"2025-04-02","Eid al-Fitr Holiday* (*estimated)","SA",2025 +"2025-06-05","Arafat Day Holiday* (*estimated)","SA",2025 +"2025-06-06","Eid al-Adha Holiday* (*estimated)","SA",2025 +"2025-06-07","Eid al-Adha Holiday* (*estimated)","SA",2025 +"2025-06-08","Eid al-Adha Holiday* (*estimated)","SA",2025 +"2025-06-09","Eid al-Adha Holiday (Observed)","SA",2025 +"2025-06-10","Eid al-Adha Holiday (Observed)","SA",2025 +"2025-09-23","National Day Holiday","SA",2025 +"2026-02-22","Founding Day Holiday","SA",2026 +"2026-03-20","Eid al-Fitr Holiday* (*estimated)","SA",2026 +"2026-03-21","Eid al-Fitr Holiday* (*estimated)","SA",2026 +"2026-03-22","Eid al-Fitr Holiday* (*estimated)","SA",2026 +"2026-03-23","Eid al-Fitr Holiday* (*estimated)","SA",2026 +"2026-03-24","Eid al-Fitr Holiday (Observed)","SA",2026 +"2026-03-25","Eid al-Fitr Holiday (Observed)","SA",2026 +"2026-05-26","Arafat Day Holiday* (*estimated)","SA",2026 +"2026-05-27","Eid al-Adha Holiday* (*estimated)","SA",2026 +"2026-05-28","Eid al-Adha Holiday* (*estimated)","SA",2026 +"2026-05-29","Eid al-Adha Holiday* (*estimated)","SA",2026 +"2026-05-30","Eid al-Adha Holiday (Observed)","SA",2026 +"2026-09-23","National Day Holiday","SA",2026 +"2027-02-22","Founding Day Holiday","SA",2027 +"2027-03-09","Eid al-Fitr Holiday* (*estimated)","SA",2027 +"2027-03-10","Eid al-Fitr Holiday* (*estimated)","SA",2027 +"2027-03-11","Eid al-Fitr Holiday* (*estimated)","SA",2027 +"2027-03-12","Eid al-Fitr Holiday* (*estimated)","SA",2027 +"2027-03-13","Eid al-Fitr Holiday (Observed)","SA",2027 +"2027-05-15","Arafat Day Holiday* (*estimated)","SA",2027 +"2027-05-16","Eid al-Adha Holiday* (*estimated)","SA",2027 +"2027-05-17","Eid al-Adha Holiday* (*estimated)","SA",2027 +"2027-05-18","Eid al-Adha Holiday* (*estimated)","SA",2027 +"2027-05-19","Eid al-Adha Holiday (Observed)","SA",2027 +"2027-09-23","National Day Holiday","SA",2027 +"2028-02-22","Founding Day Holiday","SA",2028 +"2028-02-26","Eid al-Fitr Holiday* (*estimated)","SA",2028 +"2028-02-27","Eid al-Fitr Holiday* (*estimated)","SA",2028 +"2028-02-28","Eid al-Fitr Holiday* (*estimated)","SA",2028 +"2028-02-29","Eid al-Fitr Holiday* (*estimated)","SA",2028 +"2028-03-01","Eid al-Fitr Holiday (Observed)","SA",2028 +"2028-05-04","Arafat Day Holiday* (*estimated)","SA",2028 +"2028-05-05","Eid al-Adha Holiday* (*estimated)","SA",2028 +"2028-05-06","Eid al-Adha Holiday* (*estimated)","SA",2028 +"2028-05-07","Eid al-Adha Holiday* (*estimated)","SA",2028 +"2028-05-08","Eid al-Adha Holiday (Observed)","SA",2028 +"2028-05-09","Eid al-Adha Holiday (Observed)","SA",2028 +"2028-09-23","National Day Holiday","SA",2028 +"2028-09-24","National Day Holiday (Observed)","SA",2028 +"2029-02-14","Eid al-Fitr Holiday* (*estimated)","SA",2029 +"2029-02-15","Eid al-Fitr Holiday* (*estimated)","SA",2029 +"2029-02-16","Eid al-Fitr Holiday* (*estimated)","SA",2029 +"2029-02-17","Eid al-Fitr Holiday* (*estimated)","SA",2029 +"2029-02-18","Eid al-Fitr Holiday (Observed)","SA",2029 +"2029-02-19","Eid al-Fitr Holiday (Observed)","SA",2029 +"2029-02-22","Founding Day Holiday","SA",2029 +"2029-04-23","Arafat Day Holiday* (*estimated)","SA",2029 +"2029-04-24","Eid al-Adha Holiday* (*estimated)","SA",2029 +"2029-04-25","Eid al-Adha Holiday* (*estimated)","SA",2029 +"2029-04-26","Eid al-Adha Holiday* (*estimated)","SA",2029 +"2029-09-23","National Day Holiday","SA",2029 +"2030-02-04","Eid al-Fitr Holiday* (*estimated)","SA",2030 +"2030-02-05","Eid al-Fitr Holiday* (*estimated)","SA",2030 +"2030-02-06","Eid al-Fitr Holiday* (*estimated)","SA",2030 +"2030-02-07","Eid al-Fitr Holiday* (*estimated)","SA",2030 +"2030-02-21","Founding Day Holiday (Observed)","SA",2030 +"2030-02-22","Founding Day Holiday","SA",2030 +"2030-04-12","Arafat Day Holiday* (*estimated)","SA",2030 +"2030-04-13","Eid al-Adha Holiday* (*estimated)","SA",2030 +"2030-04-14","Eid al-Adha Holiday* (*estimated)","SA",2030 +"2030-04-15","Eid al-Adha Holiday* (*estimated)","SA",2030 +"2030-04-16","Eid al-Adha Holiday (Observed)","SA",2030 +"2030-04-17","Eid al-Adha Holiday (Observed)","SA",2030 +"2030-09-23","National Day Holiday","SA",2030 +"2031-01-24","Eid al-Fitr Holiday* (*estimated)","SA",2031 +"2031-01-25","Eid al-Fitr Holiday* (*estimated)","SA",2031 +"2031-01-26","Eid al-Fitr Holiday* (*estimated)","SA",2031 +"2031-01-27","Eid al-Fitr Holiday* (*estimated)","SA",2031 +"2031-01-28","Eid al-Fitr Holiday (Observed)","SA",2031 +"2031-01-29","Eid al-Fitr Holiday (Observed)","SA",2031 +"2031-02-22","Founding Day Holiday","SA",2031 +"2031-02-23","Founding Day Holiday (Observed)","SA",2031 +"2031-04-01","Arafat Day Holiday* (*estimated)","SA",2031 +"2031-04-02","Eid al-Adha Holiday* (*estimated)","SA",2031 +"2031-04-03","Eid al-Adha Holiday* (*estimated)","SA",2031 +"2031-04-04","Eid al-Adha Holiday* (*estimated)","SA",2031 +"2031-04-05","Eid al-Adha Holiday (Observed)","SA",2031 +"2031-09-23","National Day Holiday","SA",2031 +"2032-01-14","Eid al-Fitr Holiday* (*estimated)","SA",2032 +"2032-01-15","Eid al-Fitr Holiday* (*estimated)","SA",2032 +"2032-01-16","Eid al-Fitr Holiday* (*estimated)","SA",2032 +"2032-01-17","Eid al-Fitr Holiday* (*estimated)","SA",2032 +"2032-01-18","Eid al-Fitr Holiday (Observed)","SA",2032 +"2032-01-19","Eid al-Fitr Holiday (Observed)","SA",2032 +"2032-02-22","Founding Day Holiday","SA",2032 +"2032-03-21","Arafat Day Holiday* (*estimated)","SA",2032 +"2032-03-22","Eid al-Adha Holiday* (*estimated)","SA",2032 +"2032-03-23","Eid al-Adha Holiday* (*estimated)","SA",2032 +"2032-03-24","Eid al-Adha Holiday* (*estimated)","SA",2032 +"2032-09-23","National Day Holiday","SA",2032 +"2033-01-02","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-01-03","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-01-04","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-01-05","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-02-22","Founding Day Holiday","SA",2033 +"2033-03-10","Arafat Day Holiday* (*estimated)","SA",2033 +"2033-03-11","Eid al-Adha Holiday* (*estimated)","SA",2033 +"2033-03-12","Eid al-Adha Holiday* (*estimated)","SA",2033 +"2033-03-13","Eid al-Adha Holiday* (*estimated)","SA",2033 +"2033-03-14","Eid al-Adha Holiday (Observed)","SA",2033 +"2033-03-15","Eid al-Adha Holiday (Observed)","SA",2033 +"2033-09-22","National Day Holiday (Observed)","SA",2033 +"2033-09-23","National Day Holiday","SA",2033 +"2033-12-23","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-12-24","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-12-25","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-12-26","Eid al-Fitr Holiday* (*estimated)","SA",2033 +"2033-12-27","Eid al-Fitr Holiday (Observed)","SA",2033 +"2033-12-28","Eid al-Fitr Holiday (Observed)","SA",2033 +"2034-02-22","Founding Day Holiday","SA",2034 +"2034-02-28","Arafat Day Holiday* (*estimated)","SA",2034 +"2034-03-01","Eid al-Adha Holiday* (*estimated)","SA",2034 +"2034-03-02","Eid al-Adha Holiday* (*estimated)","SA",2034 +"2034-03-03","Eid al-Adha Holiday* (*estimated)","SA",2034 +"2034-03-04","Eid al-Adha Holiday (Observed)","SA",2034 +"2034-09-23","National Day Holiday","SA",2034 +"2034-09-24","National Day Holiday (Observed)","SA",2034 +"2034-12-12","Eid al-Fitr Holiday* (*estimated)","SA",2034 +"2034-12-13","Eid al-Fitr Holiday* (*estimated)","SA",2034 +"2034-12-14","Eid al-Fitr Holiday* (*estimated)","SA",2034 +"2034-12-15","Eid al-Fitr Holiday* (*estimated)","SA",2034 +"2034-12-16","Eid al-Fitr Holiday (Observed)","SA",2034 +"2035-02-17","Arafat Day Holiday* (*estimated)","SA",2035 +"2035-02-18","Eid al-Adha Holiday* (*estimated)","SA",2035 +"2035-02-19","Eid al-Adha Holiday* (*estimated)","SA",2035 +"2035-02-20","Eid al-Adha Holiday* (*estimated)","SA",2035 +"2035-02-21","Eid al-Adha Holiday (Observed)","SA",2035 +"2035-02-22","Founding Day Holiday","SA",2035 +"2035-09-23","National Day Holiday","SA",2035 +"2035-12-01","Eid al-Fitr Holiday* (*estimated)","SA",2035 +"2035-12-02","Eid al-Fitr Holiday* (*estimated)","SA",2035 +"2035-12-03","Eid al-Fitr Holiday* (*estimated)","SA",2035 +"2035-12-04","Eid al-Fitr Holiday* (*estimated)","SA",2035 +"2035-12-05","Eid al-Fitr Holiday (Observed)","SA",2035 +"2036-02-06","Arafat Day Holiday* (*estimated)","SA",2036 +"2036-02-07","Eid al-Adha Holiday* (*estimated)","SA",2036 +"2036-02-08","Eid al-Adha Holiday* (*estimated)","SA",2036 +"2036-02-09","Eid al-Adha Holiday* (*estimated)","SA",2036 +"2036-02-10","Eid al-Adha Holiday (Observed)","SA",2036 +"2036-02-11","Eid al-Adha Holiday (Observed)","SA",2036 +"2036-02-21","Founding Day Holiday (Observed)","SA",2036 +"2036-02-22","Founding Day Holiday","SA",2036 +"2036-09-23","National Day Holiday","SA",2036 +"2036-11-19","Eid al-Fitr Holiday* (*estimated)","SA",2036 +"2036-11-20","Eid al-Fitr Holiday* (*estimated)","SA",2036 +"2036-11-21","Eid al-Fitr Holiday* (*estimated)","SA",2036 +"2036-11-22","Eid al-Fitr Holiday* (*estimated)","SA",2036 +"2036-11-23","Eid al-Fitr Holiday (Observed)","SA",2036 +"2036-11-24","Eid al-Fitr Holiday (Observed)","SA",2036 +"2037-01-25","Arafat Day Holiday* (*estimated)","SA",2037 +"2037-01-26","Eid al-Adha Holiday* (*estimated)","SA",2037 +"2037-01-27","Eid al-Adha Holiday* (*estimated)","SA",2037 +"2037-01-28","Eid al-Adha Holiday* (*estimated)","SA",2037 +"2037-02-22","Founding Day Holiday","SA",2037 +"2037-09-23","National Day Holiday","SA",2037 +"2037-11-08","Eid al-Fitr Holiday* (*estimated)","SA",2037 +"2037-11-09","Eid al-Fitr Holiday* (*estimated)","SA",2037 +"2037-11-10","Eid al-Fitr Holiday* (*estimated)","SA",2037 +"2037-11-11","Eid al-Fitr Holiday* (*estimated)","SA",2037 +"2038-01-15","Arafat Day Holiday* (*estimated)","SA",2038 +"2038-01-16","Eid al-Adha Holiday* (*estimated)","SA",2038 +"2038-01-17","Eid al-Adha Holiday* (*estimated)","SA",2038 +"2038-01-18","Eid al-Adha Holiday* (*estimated)","SA",2038 +"2038-01-19","Eid al-Adha Holiday (Observed)","SA",2038 +"2038-01-20","Eid al-Adha Holiday (Observed)","SA",2038 +"2038-02-22","Founding Day Holiday","SA",2038 +"2038-09-23","National Day Holiday","SA",2038 +"2038-10-29","Eid al-Fitr Holiday* (*estimated)","SA",2038 +"2038-10-30","Eid al-Fitr Holiday* (*estimated)","SA",2038 +"2038-10-31","Eid al-Fitr Holiday* (*estimated)","SA",2038 +"2038-11-01","Eid al-Fitr Holiday* (*estimated)","SA",2038 +"2038-11-02","Eid al-Fitr Holiday (Observed)","SA",2038 +"2038-11-03","Eid al-Fitr Holiday (Observed)","SA",2038 +"2039-01-04","Arafat Day Holiday* (*estimated)","SA",2039 +"2039-01-05","Eid al-Adha Holiday* (*estimated)","SA",2039 +"2039-01-06","Eid al-Adha Holiday* (*estimated)","SA",2039 +"2039-01-07","Eid al-Adha Holiday* (*estimated)","SA",2039 +"2039-01-08","Eid al-Adha Holiday (Observed)","SA",2039 +"2039-02-22","Founding Day Holiday","SA",2039 +"2039-09-22","National Day Holiday (Observed)","SA",2039 +"2039-09-23","National Day Holiday","SA",2039 +"2039-10-19","Eid al-Fitr Holiday* (*estimated)","SA",2039 +"2039-10-20","Eid al-Fitr Holiday* (*estimated)","SA",2039 +"2039-10-21","Eid al-Fitr Holiday* (*estimated)","SA",2039 +"2039-10-22","Eid al-Fitr Holiday* (*estimated)","SA",2039 +"2039-10-23","Eid al-Fitr Holiday (Observed)","SA",2039 +"2039-10-24","Eid al-Fitr Holiday (Observed)","SA",2039 +"2039-12-25","Arafat Day Holiday* (*estimated)","SA",2039 +"2039-12-26","Eid al-Adha Holiday* (*estimated)","SA",2039 +"2039-12-27","Eid al-Adha Holiday* (*estimated)","SA",2039 +"2039-12-28","Eid al-Adha Holiday* (*estimated)","SA",2039 +"2040-02-22","Founding Day Holiday","SA",2040 +"2040-09-23","National Day Holiday","SA",2040 +"2040-10-07","Eid al-Fitr Holiday* (*estimated)","SA",2040 +"2040-10-08","Eid al-Fitr Holiday* (*estimated)","SA",2040 +"2040-10-09","Eid al-Fitr Holiday* (*estimated)","SA",2040 +"2040-10-10","Eid al-Fitr Holiday* (*estimated)","SA",2040 +"2040-12-13","Arafat Day Holiday* (*estimated)","SA",2040 +"2040-12-14","Eid al-Adha Holiday* (*estimated)","SA",2040 +"2040-12-15","Eid al-Adha Holiday* (*estimated)","SA",2040 +"2040-12-16","Eid al-Adha Holiday* (*estimated)","SA",2040 +"2040-12-17","Eid al-Adha Holiday (Observed)","SA",2040 +"2040-12-18","Eid al-Adha Holiday (Observed)","SA",2040 +"2041-02-21","Founding Day Holiday (Observed)","SA",2041 +"2041-02-22","Founding Day Holiday","SA",2041 +"2041-09-23","National Day Holiday","SA",2041 +"2041-09-26","Eid al-Fitr Holiday* (*estimated)","SA",2041 +"2041-09-27","Eid al-Fitr Holiday* (*estimated)","SA",2041 +"2041-09-28","Eid al-Fitr Holiday* (*estimated)","SA",2041 +"2041-09-29","Eid al-Fitr Holiday* (*estimated)","SA",2041 +"2041-09-30","Eid al-Fitr Holiday (Observed)","SA",2041 +"2041-10-01","Eid al-Fitr Holiday (Observed)","SA",2041 +"2041-12-03","Arafat Day Holiday* (*estimated)","SA",2041 +"2041-12-04","Eid al-Adha Holiday* (*estimated)","SA",2041 +"2041-12-05","Eid al-Adha Holiday* (*estimated)","SA",2041 +"2041-12-06","Eid al-Adha Holiday* (*estimated)","SA",2041 +"2041-12-07","Eid al-Adha Holiday (Observed)","SA",2041 +"2042-02-22","Founding Day Holiday","SA",2042 +"2042-02-23","Founding Day Holiday (Observed)","SA",2042 +"2042-09-15","Eid al-Fitr Holiday* (*estimated)","SA",2042 +"2042-09-16","Eid al-Fitr Holiday* (*estimated)","SA",2042 +"2042-09-17","Eid al-Fitr Holiday* (*estimated)","SA",2042 +"2042-09-18","Eid al-Fitr Holiday* (*estimated)","SA",2042 +"2042-09-23","National Day Holiday","SA",2042 +"2042-11-22","Arafat Day Holiday* (*estimated)","SA",2042 +"2042-11-23","Eid al-Adha Holiday* (*estimated)","SA",2042 +"2042-11-24","Eid al-Adha Holiday* (*estimated)","SA",2042 +"2042-11-25","Eid al-Adha Holiday* (*estimated)","SA",2042 +"2042-11-26","Eid al-Adha Holiday (Observed)","SA",2042 +"2043-02-22","Founding Day Holiday","SA",2043 +"2043-09-04","Eid al-Fitr Holiday* (*estimated)","SA",2043 +"2043-09-05","Eid al-Fitr Holiday* (*estimated)","SA",2043 +"2043-09-06","Eid al-Fitr Holiday* (*estimated)","SA",2043 +"2043-09-07","Eid al-Fitr Holiday* (*estimated)","SA",2043 +"2043-09-08","Eid al-Fitr Holiday (Observed)","SA",2043 +"2043-09-09","Eid al-Fitr Holiday (Observed)","SA",2043 +"2043-09-23","National Day Holiday","SA",2043 +"2043-11-11","Arafat Day Holiday* (*estimated)","SA",2043 +"2043-11-12","Eid al-Adha Holiday* (*estimated)","SA",2043 +"2043-11-13","Eid al-Adha Holiday* (*estimated)","SA",2043 +"2043-11-14","Eid al-Adha Holiday* (*estimated)","SA",2043 +"2043-11-15","Eid al-Adha Holiday (Observed)","SA",2043 +"2043-11-16","Eid al-Adha Holiday (Observed)","SA",2043 +"2044-02-22","Founding Day Holiday","SA",2044 +"2044-08-24","Eid al-Fitr Holiday* (*estimated)","SA",2044 +"2044-08-25","Eid al-Fitr Holiday* (*estimated)","SA",2044 +"2044-08-26","Eid al-Fitr Holiday* (*estimated)","SA",2044 +"2044-08-27","Eid al-Fitr Holiday* (*estimated)","SA",2044 +"2044-08-28","Eid al-Fitr Holiday (Observed)","SA",2044 +"2044-08-29","Eid al-Fitr Holiday (Observed)","SA",2044 +"2044-09-22","National Day Holiday (Observed)","SA",2044 +"2044-09-23","National Day Holiday","SA",2044 +"2044-10-30","Arafat Day Holiday* (*estimated)","SA",2044 +"2044-10-31","Eid al-Adha Holiday* (*estimated)","SA",2044 +"2044-11-01","Eid al-Adha Holiday* (*estimated)","SA",2044 +"2044-11-02","Eid al-Adha Holiday* (*estimated)","SA",2044 +"1995-01-01","New Year's Day","SE",1995 +"1995-01-01","Sunday","SE",1995 +"1995-01-06","Epiphany","SE",1995 +"1995-01-08","Sunday","SE",1995 +"1995-01-15","Sunday","SE",1995 +"1995-01-22","Sunday","SE",1995 +"1995-01-29","Sunday","SE",1995 +"1995-02-05","Sunday","SE",1995 +"1995-02-12","Sunday","SE",1995 +"1995-02-19","Sunday","SE",1995 +"1995-02-26","Sunday","SE",1995 +"1995-03-05","Sunday","SE",1995 +"1995-03-12","Sunday","SE",1995 +"1995-03-19","Sunday","SE",1995 +"1995-03-26","Sunday","SE",1995 +"1995-04-02","Sunday","SE",1995 +"1995-04-09","Sunday","SE",1995 +"1995-04-14","Good Friday","SE",1995 +"1995-04-16","Easter Sunday","SE",1995 +"1995-04-16","Sunday","SE",1995 +"1995-04-17","Easter Monday","SE",1995 +"1995-04-23","Sunday","SE",1995 +"1995-04-30","Sunday","SE",1995 +"1995-05-01","May Day","SE",1995 +"1995-05-07","Sunday","SE",1995 +"1995-05-14","Sunday","SE",1995 +"1995-05-21","Sunday","SE",1995 +"1995-05-25","Ascension Day","SE",1995 +"1995-05-28","Sunday","SE",1995 +"1995-06-04","Sunday","SE",1995 +"1995-06-04","Whit Sunday","SE",1995 +"1995-06-05","Whit Monday","SE",1995 +"1995-06-11","Sunday","SE",1995 +"1995-06-18","Sunday","SE",1995 +"1995-06-23","Midsummer Eve","SE",1995 +"1995-06-24","Midsummer Day","SE",1995 +"1995-06-25","Sunday","SE",1995 +"1995-07-02","Sunday","SE",1995 +"1995-07-09","Sunday","SE",1995 +"1995-07-16","Sunday","SE",1995 +"1995-07-23","Sunday","SE",1995 +"1995-07-30","Sunday","SE",1995 +"1995-08-06","Sunday","SE",1995 +"1995-08-13","Sunday","SE",1995 +"1995-08-20","Sunday","SE",1995 +"1995-08-27","Sunday","SE",1995 +"1995-09-03","Sunday","SE",1995 +"1995-09-10","Sunday","SE",1995 +"1995-09-17","Sunday","SE",1995 +"1995-09-24","Sunday","SE",1995 +"1995-10-01","Sunday","SE",1995 +"1995-10-08","Sunday","SE",1995 +"1995-10-15","Sunday","SE",1995 +"1995-10-22","Sunday","SE",1995 +"1995-10-29","Sunday","SE",1995 +"1995-11-04","All Saints' Day","SE",1995 +"1995-11-05","Sunday","SE",1995 +"1995-11-12","Sunday","SE",1995 +"1995-11-19","Sunday","SE",1995 +"1995-11-26","Sunday","SE",1995 +"1995-12-03","Sunday","SE",1995 +"1995-12-10","Sunday","SE",1995 +"1995-12-17","Sunday","SE",1995 +"1995-12-24","Christmas Eve","SE",1995 +"1995-12-24","Sunday","SE",1995 +"1995-12-25","Christmas Day","SE",1995 +"1995-12-26","Second Day of Christmas","SE",1995 +"1995-12-31","New Year's Eve","SE",1995 +"1995-12-31","Sunday","SE",1995 +"1996-01-01","New Year's Day","SE",1996 +"1996-01-06","Epiphany","SE",1996 +"1996-01-07","Sunday","SE",1996 +"1996-01-14","Sunday","SE",1996 +"1996-01-21","Sunday","SE",1996 +"1996-01-28","Sunday","SE",1996 +"1996-02-04","Sunday","SE",1996 +"1996-02-11","Sunday","SE",1996 +"1996-02-18","Sunday","SE",1996 +"1996-02-25","Sunday","SE",1996 +"1996-03-03","Sunday","SE",1996 +"1996-03-10","Sunday","SE",1996 +"1996-03-17","Sunday","SE",1996 +"1996-03-24","Sunday","SE",1996 +"1996-03-31","Sunday","SE",1996 +"1996-04-05","Good Friday","SE",1996 +"1996-04-07","Easter Sunday","SE",1996 +"1996-04-07","Sunday","SE",1996 +"1996-04-08","Easter Monday","SE",1996 +"1996-04-14","Sunday","SE",1996 +"1996-04-21","Sunday","SE",1996 +"1996-04-28","Sunday","SE",1996 +"1996-05-01","May Day","SE",1996 +"1996-05-05","Sunday","SE",1996 +"1996-05-12","Sunday","SE",1996 +"1996-05-16","Ascension Day","SE",1996 +"1996-05-19","Sunday","SE",1996 +"1996-05-26","Sunday","SE",1996 +"1996-05-26","Whit Sunday","SE",1996 +"1996-05-27","Whit Monday","SE",1996 +"1996-06-02","Sunday","SE",1996 +"1996-06-09","Sunday","SE",1996 +"1996-06-16","Sunday","SE",1996 +"1996-06-21","Midsummer Eve","SE",1996 +"1996-06-22","Midsummer Day","SE",1996 +"1996-06-23","Sunday","SE",1996 +"1996-06-30","Sunday","SE",1996 +"1996-07-07","Sunday","SE",1996 +"1996-07-14","Sunday","SE",1996 +"1996-07-21","Sunday","SE",1996 +"1996-07-28","Sunday","SE",1996 +"1996-08-04","Sunday","SE",1996 +"1996-08-11","Sunday","SE",1996 +"1996-08-18","Sunday","SE",1996 +"1996-08-25","Sunday","SE",1996 +"1996-09-01","Sunday","SE",1996 +"1996-09-08","Sunday","SE",1996 +"1996-09-15","Sunday","SE",1996 +"1996-09-22","Sunday","SE",1996 +"1996-09-29","Sunday","SE",1996 +"1996-10-06","Sunday","SE",1996 +"1996-10-13","Sunday","SE",1996 +"1996-10-20","Sunday","SE",1996 +"1996-10-27","Sunday","SE",1996 +"1996-11-02","All Saints' Day","SE",1996 +"1996-11-03","Sunday","SE",1996 +"1996-11-10","Sunday","SE",1996 +"1996-11-17","Sunday","SE",1996 +"1996-11-24","Sunday","SE",1996 +"1996-12-01","Sunday","SE",1996 +"1996-12-08","Sunday","SE",1996 +"1996-12-15","Sunday","SE",1996 +"1996-12-22","Sunday","SE",1996 +"1996-12-24","Christmas Eve","SE",1996 +"1996-12-25","Christmas Day","SE",1996 +"1996-12-26","Second Day of Christmas","SE",1996 +"1996-12-29","Sunday","SE",1996 +"1996-12-31","New Year's Eve","SE",1996 +"1997-01-01","New Year's Day","SE",1997 +"1997-01-05","Sunday","SE",1997 +"1997-01-06","Epiphany","SE",1997 +"1997-01-12","Sunday","SE",1997 +"1997-01-19","Sunday","SE",1997 +"1997-01-26","Sunday","SE",1997 +"1997-02-02","Sunday","SE",1997 +"1997-02-09","Sunday","SE",1997 +"1997-02-16","Sunday","SE",1997 +"1997-02-23","Sunday","SE",1997 +"1997-03-02","Sunday","SE",1997 +"1997-03-09","Sunday","SE",1997 +"1997-03-16","Sunday","SE",1997 +"1997-03-23","Sunday","SE",1997 +"1997-03-28","Good Friday","SE",1997 +"1997-03-30","Easter Sunday","SE",1997 +"1997-03-30","Sunday","SE",1997 +"1997-03-31","Easter Monday","SE",1997 +"1997-04-06","Sunday","SE",1997 +"1997-04-13","Sunday","SE",1997 +"1997-04-20","Sunday","SE",1997 +"1997-04-27","Sunday","SE",1997 +"1997-05-01","May Day","SE",1997 +"1997-05-04","Sunday","SE",1997 +"1997-05-08","Ascension Day","SE",1997 +"1997-05-11","Sunday","SE",1997 +"1997-05-18","Sunday","SE",1997 +"1997-05-18","Whit Sunday","SE",1997 +"1997-05-19","Whit Monday","SE",1997 +"1997-05-25","Sunday","SE",1997 +"1997-06-01","Sunday","SE",1997 +"1997-06-08","Sunday","SE",1997 +"1997-06-15","Sunday","SE",1997 +"1997-06-20","Midsummer Eve","SE",1997 +"1997-06-21","Midsummer Day","SE",1997 +"1997-06-22","Sunday","SE",1997 +"1997-06-29","Sunday","SE",1997 +"1997-07-06","Sunday","SE",1997 +"1997-07-13","Sunday","SE",1997 +"1997-07-20","Sunday","SE",1997 +"1997-07-27","Sunday","SE",1997 +"1997-08-03","Sunday","SE",1997 +"1997-08-10","Sunday","SE",1997 +"1997-08-17","Sunday","SE",1997 +"1997-08-24","Sunday","SE",1997 +"1997-08-31","Sunday","SE",1997 +"1997-09-07","Sunday","SE",1997 +"1997-09-14","Sunday","SE",1997 +"1997-09-21","Sunday","SE",1997 +"1997-09-28","Sunday","SE",1997 +"1997-10-05","Sunday","SE",1997 +"1997-10-12","Sunday","SE",1997 +"1997-10-19","Sunday","SE",1997 +"1997-10-26","Sunday","SE",1997 +"1997-11-01","All Saints' Day","SE",1997 +"1997-11-02","Sunday","SE",1997 +"1997-11-09","Sunday","SE",1997 +"1997-11-16","Sunday","SE",1997 +"1997-11-23","Sunday","SE",1997 +"1997-11-30","Sunday","SE",1997 +"1997-12-07","Sunday","SE",1997 +"1997-12-14","Sunday","SE",1997 +"1997-12-21","Sunday","SE",1997 +"1997-12-24","Christmas Eve","SE",1997 +"1997-12-25","Christmas Day","SE",1997 +"1997-12-26","Second Day of Christmas","SE",1997 +"1997-12-28","Sunday","SE",1997 +"1997-12-31","New Year's Eve","SE",1997 +"1998-01-01","New Year's Day","SE",1998 +"1998-01-04","Sunday","SE",1998 +"1998-01-06","Epiphany","SE",1998 +"1998-01-11","Sunday","SE",1998 +"1998-01-18","Sunday","SE",1998 +"1998-01-25","Sunday","SE",1998 +"1998-02-01","Sunday","SE",1998 +"1998-02-08","Sunday","SE",1998 +"1998-02-15","Sunday","SE",1998 +"1998-02-22","Sunday","SE",1998 +"1998-03-01","Sunday","SE",1998 +"1998-03-08","Sunday","SE",1998 +"1998-03-15","Sunday","SE",1998 +"1998-03-22","Sunday","SE",1998 +"1998-03-29","Sunday","SE",1998 +"1998-04-05","Sunday","SE",1998 +"1998-04-10","Good Friday","SE",1998 +"1998-04-12","Easter Sunday","SE",1998 +"1998-04-12","Sunday","SE",1998 +"1998-04-13","Easter Monday","SE",1998 +"1998-04-19","Sunday","SE",1998 +"1998-04-26","Sunday","SE",1998 +"1998-05-01","May Day","SE",1998 +"1998-05-03","Sunday","SE",1998 +"1998-05-10","Sunday","SE",1998 +"1998-05-17","Sunday","SE",1998 +"1998-05-21","Ascension Day","SE",1998 +"1998-05-24","Sunday","SE",1998 +"1998-05-31","Sunday","SE",1998 +"1998-05-31","Whit Sunday","SE",1998 +"1998-06-01","Whit Monday","SE",1998 +"1998-06-07","Sunday","SE",1998 +"1998-06-14","Sunday","SE",1998 +"1998-06-19","Midsummer Eve","SE",1998 +"1998-06-20","Midsummer Day","SE",1998 +"1998-06-21","Sunday","SE",1998 +"1998-06-28","Sunday","SE",1998 +"1998-07-05","Sunday","SE",1998 +"1998-07-12","Sunday","SE",1998 +"1998-07-19","Sunday","SE",1998 +"1998-07-26","Sunday","SE",1998 +"1998-08-02","Sunday","SE",1998 +"1998-08-09","Sunday","SE",1998 +"1998-08-16","Sunday","SE",1998 +"1998-08-23","Sunday","SE",1998 +"1998-08-30","Sunday","SE",1998 +"1998-09-06","Sunday","SE",1998 +"1998-09-13","Sunday","SE",1998 +"1998-09-20","Sunday","SE",1998 +"1998-09-27","Sunday","SE",1998 +"1998-10-04","Sunday","SE",1998 +"1998-10-11","Sunday","SE",1998 +"1998-10-18","Sunday","SE",1998 +"1998-10-25","Sunday","SE",1998 +"1998-10-31","All Saints' Day","SE",1998 +"1998-11-01","Sunday","SE",1998 +"1998-11-08","Sunday","SE",1998 +"1998-11-15","Sunday","SE",1998 +"1998-11-22","Sunday","SE",1998 +"1998-11-29","Sunday","SE",1998 +"1998-12-06","Sunday","SE",1998 +"1998-12-13","Sunday","SE",1998 +"1998-12-20","Sunday","SE",1998 +"1998-12-24","Christmas Eve","SE",1998 +"1998-12-25","Christmas Day","SE",1998 +"1998-12-26","Second Day of Christmas","SE",1998 +"1998-12-27","Sunday","SE",1998 +"1998-12-31","New Year's Eve","SE",1998 +"1999-01-01","New Year's Day","SE",1999 +"1999-01-03","Sunday","SE",1999 +"1999-01-06","Epiphany","SE",1999 +"1999-01-10","Sunday","SE",1999 +"1999-01-17","Sunday","SE",1999 +"1999-01-24","Sunday","SE",1999 +"1999-01-31","Sunday","SE",1999 +"1999-02-07","Sunday","SE",1999 +"1999-02-14","Sunday","SE",1999 +"1999-02-21","Sunday","SE",1999 +"1999-02-28","Sunday","SE",1999 +"1999-03-07","Sunday","SE",1999 +"1999-03-14","Sunday","SE",1999 +"1999-03-21","Sunday","SE",1999 +"1999-03-28","Sunday","SE",1999 +"1999-04-02","Good Friday","SE",1999 +"1999-04-04","Easter Sunday","SE",1999 +"1999-04-04","Sunday","SE",1999 +"1999-04-05","Easter Monday","SE",1999 +"1999-04-11","Sunday","SE",1999 +"1999-04-18","Sunday","SE",1999 +"1999-04-25","Sunday","SE",1999 +"1999-05-01","May Day","SE",1999 +"1999-05-02","Sunday","SE",1999 +"1999-05-09","Sunday","SE",1999 +"1999-05-13","Ascension Day","SE",1999 +"1999-05-16","Sunday","SE",1999 +"1999-05-23","Sunday","SE",1999 +"1999-05-23","Whit Sunday","SE",1999 +"1999-05-24","Whit Monday","SE",1999 +"1999-05-30","Sunday","SE",1999 +"1999-06-06","Sunday","SE",1999 +"1999-06-13","Sunday","SE",1999 +"1999-06-20","Sunday","SE",1999 +"1999-06-25","Midsummer Eve","SE",1999 +"1999-06-26","Midsummer Day","SE",1999 +"1999-06-27","Sunday","SE",1999 +"1999-07-04","Sunday","SE",1999 +"1999-07-11","Sunday","SE",1999 +"1999-07-18","Sunday","SE",1999 +"1999-07-25","Sunday","SE",1999 +"1999-08-01","Sunday","SE",1999 +"1999-08-08","Sunday","SE",1999 +"1999-08-15","Sunday","SE",1999 +"1999-08-22","Sunday","SE",1999 +"1999-08-29","Sunday","SE",1999 +"1999-09-05","Sunday","SE",1999 +"1999-09-12","Sunday","SE",1999 +"1999-09-19","Sunday","SE",1999 +"1999-09-26","Sunday","SE",1999 +"1999-10-03","Sunday","SE",1999 +"1999-10-10","Sunday","SE",1999 +"1999-10-17","Sunday","SE",1999 +"1999-10-24","Sunday","SE",1999 +"1999-10-31","Sunday","SE",1999 +"1999-11-06","All Saints' Day","SE",1999 +"1999-11-07","Sunday","SE",1999 +"1999-11-14","Sunday","SE",1999 +"1999-11-21","Sunday","SE",1999 +"1999-11-28","Sunday","SE",1999 +"1999-12-05","Sunday","SE",1999 +"1999-12-12","Sunday","SE",1999 +"1999-12-19","Sunday","SE",1999 +"1999-12-24","Christmas Eve","SE",1999 +"1999-12-25","Christmas Day","SE",1999 +"1999-12-26","Second Day of Christmas","SE",1999 +"1999-12-26","Sunday","SE",1999 +"1999-12-31","New Year's Eve","SE",1999 +"2000-01-01","New Year's Day","SE",2000 +"2000-01-02","Sunday","SE",2000 +"2000-01-06","Epiphany","SE",2000 +"2000-01-09","Sunday","SE",2000 +"2000-01-16","Sunday","SE",2000 +"2000-01-23","Sunday","SE",2000 +"2000-01-30","Sunday","SE",2000 +"2000-02-06","Sunday","SE",2000 +"2000-02-13","Sunday","SE",2000 +"2000-02-20","Sunday","SE",2000 +"2000-02-27","Sunday","SE",2000 +"2000-03-05","Sunday","SE",2000 +"2000-03-12","Sunday","SE",2000 +"2000-03-19","Sunday","SE",2000 +"2000-03-26","Sunday","SE",2000 +"2000-04-02","Sunday","SE",2000 +"2000-04-09","Sunday","SE",2000 +"2000-04-16","Sunday","SE",2000 +"2000-04-21","Good Friday","SE",2000 +"2000-04-23","Easter Sunday","SE",2000 +"2000-04-23","Sunday","SE",2000 +"2000-04-24","Easter Monday","SE",2000 +"2000-04-30","Sunday","SE",2000 +"2000-05-01","May Day","SE",2000 +"2000-05-07","Sunday","SE",2000 +"2000-05-14","Sunday","SE",2000 +"2000-05-21","Sunday","SE",2000 +"2000-05-28","Sunday","SE",2000 +"2000-06-01","Ascension Day","SE",2000 +"2000-06-04","Sunday","SE",2000 +"2000-06-11","Sunday","SE",2000 +"2000-06-11","Whit Sunday","SE",2000 +"2000-06-12","Whit Monday","SE",2000 +"2000-06-18","Sunday","SE",2000 +"2000-06-23","Midsummer Eve","SE",2000 +"2000-06-24","Midsummer Day","SE",2000 +"2000-06-25","Sunday","SE",2000 +"2000-07-02","Sunday","SE",2000 +"2000-07-09","Sunday","SE",2000 +"2000-07-16","Sunday","SE",2000 +"2000-07-23","Sunday","SE",2000 +"2000-07-30","Sunday","SE",2000 +"2000-08-06","Sunday","SE",2000 +"2000-08-13","Sunday","SE",2000 +"2000-08-20","Sunday","SE",2000 +"2000-08-27","Sunday","SE",2000 +"2000-09-03","Sunday","SE",2000 +"2000-09-10","Sunday","SE",2000 +"2000-09-17","Sunday","SE",2000 +"2000-09-24","Sunday","SE",2000 +"2000-10-01","Sunday","SE",2000 +"2000-10-08","Sunday","SE",2000 +"2000-10-15","Sunday","SE",2000 +"2000-10-22","Sunday","SE",2000 +"2000-10-29","Sunday","SE",2000 +"2000-11-04","All Saints' Day","SE",2000 +"2000-11-05","Sunday","SE",2000 +"2000-11-12","Sunday","SE",2000 +"2000-11-19","Sunday","SE",2000 +"2000-11-26","Sunday","SE",2000 +"2000-12-03","Sunday","SE",2000 +"2000-12-10","Sunday","SE",2000 +"2000-12-17","Sunday","SE",2000 +"2000-12-24","Christmas Eve","SE",2000 +"2000-12-24","Sunday","SE",2000 +"2000-12-25","Christmas Day","SE",2000 +"2000-12-26","Second Day of Christmas","SE",2000 +"2000-12-31","New Year's Eve","SE",2000 +"2000-12-31","Sunday","SE",2000 +"2001-01-01","New Year's Day","SE",2001 +"2001-01-06","Epiphany","SE",2001 +"2001-01-07","Sunday","SE",2001 +"2001-01-14","Sunday","SE",2001 +"2001-01-21","Sunday","SE",2001 +"2001-01-28","Sunday","SE",2001 +"2001-02-04","Sunday","SE",2001 +"2001-02-11","Sunday","SE",2001 +"2001-02-18","Sunday","SE",2001 +"2001-02-25","Sunday","SE",2001 +"2001-03-04","Sunday","SE",2001 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Sweden","SE",2027 +"2027-06-06","Sunday","SE",2027 +"2027-06-13","Sunday","SE",2027 +"2027-06-20","Sunday","SE",2027 +"2027-06-25","Midsummer Eve","SE",2027 +"2027-06-26","Midsummer Day","SE",2027 +"2027-06-27","Sunday","SE",2027 +"2027-07-04","Sunday","SE",2027 +"2027-07-11","Sunday","SE",2027 +"2027-07-18","Sunday","SE",2027 +"2027-07-25","Sunday","SE",2027 +"2027-08-01","Sunday","SE",2027 +"2027-08-08","Sunday","SE",2027 +"2027-08-15","Sunday","SE",2027 +"2027-08-22","Sunday","SE",2027 +"2027-08-29","Sunday","SE",2027 +"2027-09-05","Sunday","SE",2027 +"2027-09-12","Sunday","SE",2027 +"2027-09-19","Sunday","SE",2027 +"2027-09-26","Sunday","SE",2027 +"2027-10-03","Sunday","SE",2027 +"2027-10-10","Sunday","SE",2027 +"2027-10-17","Sunday","SE",2027 +"2027-10-24","Sunday","SE",2027 +"2027-10-31","Sunday","SE",2027 +"2027-11-06","All Saints' Day","SE",2027 +"2027-11-07","Sunday","SE",2027 +"2027-11-14","Sunday","SE",2027 +"2027-11-21","Sunday","SE",2027 +"2027-11-28","Sunday","SE",2027 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Day","SE",2029 +"2029-12-26","Second Day of Christmas","SE",2029 +"2029-12-30","Sunday","SE",2029 +"2029-12-31","New Year's Eve","SE",2029 +"2030-01-01","New Year's Day","SE",2030 +"2030-01-06","Epiphany","SE",2030 +"2030-01-06","Sunday","SE",2030 +"2030-01-13","Sunday","SE",2030 +"2030-01-20","Sunday","SE",2030 +"2030-01-27","Sunday","SE",2030 +"2030-02-03","Sunday","SE",2030 +"2030-02-10","Sunday","SE",2030 +"2030-02-17","Sunday","SE",2030 +"2030-02-24","Sunday","SE",2030 +"2030-03-03","Sunday","SE",2030 +"2030-03-10","Sunday","SE",2030 +"2030-03-17","Sunday","SE",2030 +"2030-03-24","Sunday","SE",2030 +"2030-03-31","Sunday","SE",2030 +"2030-04-07","Sunday","SE",2030 +"2030-04-14","Sunday","SE",2030 +"2030-04-19","Good Friday","SE",2030 +"2030-04-21","Easter Sunday","SE",2030 +"2030-04-21","Sunday","SE",2030 +"2030-04-22","Easter Monday","SE",2030 +"2030-04-28","Sunday","SE",2030 +"2030-05-01","May Day","SE",2030 +"2030-05-05","Sunday","SE",2030 +"2030-05-12","Sunday","SE",2030 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Day","SE",2034 +"2034-12-26","Second Day of Christmas","SE",2034 +"2034-12-31","New Year's Eve","SE",2034 +"2034-12-31","Sunday","SE",2034 +"2035-01-01","New Year's Day","SE",2035 +"2035-01-06","Epiphany","SE",2035 +"2035-01-07","Sunday","SE",2035 +"2035-01-14","Sunday","SE",2035 +"2035-01-21","Sunday","SE",2035 +"2035-01-28","Sunday","SE",2035 +"2035-02-04","Sunday","SE",2035 +"2035-02-11","Sunday","SE",2035 +"2035-02-18","Sunday","SE",2035 +"2035-02-25","Sunday","SE",2035 +"2035-03-04","Sunday","SE",2035 +"2035-03-11","Sunday","SE",2035 +"2035-03-18","Sunday","SE",2035 +"2035-03-23","Good Friday","SE",2035 +"2035-03-25","Easter Sunday","SE",2035 +"2035-03-25","Sunday","SE",2035 +"2035-03-26","Easter Monday","SE",2035 +"2035-04-01","Sunday","SE",2035 +"2035-04-08","Sunday","SE",2035 +"2035-04-15","Sunday","SE",2035 +"2035-04-22","Sunday","SE",2035 +"2035-04-29","Sunday","SE",2035 +"2035-05-01","May Day","SE",2035 +"2035-05-03","Ascension Day","SE",2035 +"2035-05-06","Sunday","SE",2035 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+"2043-09-20","Sunday","SE",2043 +"2043-09-27","Sunday","SE",2043 +"2043-10-04","Sunday","SE",2043 +"2043-10-11","Sunday","SE",2043 +"2043-10-18","Sunday","SE",2043 +"2043-10-25","Sunday","SE",2043 +"2043-10-31","All Saints' Day","SE",2043 +"2043-11-01","Sunday","SE",2043 +"2043-11-08","Sunday","SE",2043 +"2043-11-15","Sunday","SE",2043 +"2043-11-22","Sunday","SE",2043 +"2043-11-29","Sunday","SE",2043 +"2043-12-06","Sunday","SE",2043 +"2043-12-13","Sunday","SE",2043 +"2043-12-20","Sunday","SE",2043 +"2043-12-24","Christmas Eve","SE",2043 +"2043-12-25","Christmas Day","SE",2043 +"2043-12-26","Second Day of Christmas","SE",2043 +"2043-12-27","Sunday","SE",2043 +"2043-12-31","New Year's Eve","SE",2043 +"2044-01-01","New Year's Day","SE",2044 +"2044-01-03","Sunday","SE",2044 +"2044-01-06","Epiphany","SE",2044 +"2044-01-10","Sunday","SE",2044 +"2044-01-17","Sunday","SE",2044 +"2044-01-24","Sunday","SE",2044 +"2044-01-31","Sunday","SE",2044 +"2044-02-07","Sunday","SE",2044 +"2044-02-14","Sunday","SE",2044 +"2044-02-21","Sunday","SE",2044 +"2044-02-28","Sunday","SE",2044 +"2044-03-06","Sunday","SE",2044 +"2044-03-13","Sunday","SE",2044 +"2044-03-20","Sunday","SE",2044 +"2044-03-27","Sunday","SE",2044 +"2044-04-03","Sunday","SE",2044 +"2044-04-10","Sunday","SE",2044 +"2044-04-15","Good Friday","SE",2044 +"2044-04-17","Easter Sunday","SE",2044 +"2044-04-17","Sunday","SE",2044 +"2044-04-18","Easter Monday","SE",2044 +"2044-04-24","Sunday","SE",2044 +"2044-05-01","May Day","SE",2044 +"2044-05-01","Sunday","SE",2044 +"2044-05-08","Sunday","SE",2044 +"2044-05-15","Sunday","SE",2044 +"2044-05-22","Sunday","SE",2044 +"2044-05-26","Ascension Day","SE",2044 +"2044-05-29","Sunday","SE",2044 +"2044-06-05","Sunday","SE",2044 +"2044-06-05","Whit Sunday","SE",2044 +"2044-06-06","National Day of Sweden","SE",2044 +"2044-06-12","Sunday","SE",2044 +"2044-06-19","Sunday","SE",2044 +"2044-06-24","Midsummer Eve","SE",2044 +"2044-06-25","Midsummer Day","SE",2044 +"2044-06-26","Sunday","SE",2044 +"2044-07-03","Sunday","SE",2044 +"2044-07-10","Sunday","SE",2044 +"2044-07-17","Sunday","SE",2044 +"2044-07-24","Sunday","SE",2044 +"2044-07-31","Sunday","SE",2044 +"2044-08-07","Sunday","SE",2044 +"2044-08-14","Sunday","SE",2044 +"2044-08-21","Sunday","SE",2044 +"2044-08-28","Sunday","SE",2044 +"2044-09-04","Sunday","SE",2044 +"2044-09-11","Sunday","SE",2044 +"2044-09-18","Sunday","SE",2044 +"2044-09-25","Sunday","SE",2044 +"2044-10-02","Sunday","SE",2044 +"2044-10-09","Sunday","SE",2044 +"2044-10-16","Sunday","SE",2044 +"2044-10-23","Sunday","SE",2044 +"2044-10-30","Sunday","SE",2044 +"2044-11-05","All Saints' Day","SE",2044 +"2044-11-06","Sunday","SE",2044 +"2044-11-13","Sunday","SE",2044 +"2044-11-20","Sunday","SE",2044 +"2044-11-27","Sunday","SE",2044 +"2044-12-04","Sunday","SE",2044 +"2044-12-11","Sunday","SE",2044 +"2044-12-18","Sunday","SE",2044 +"2044-12-24","Christmas Eve","SE",2044 +"2044-12-25","Christmas Day","SE",2044 +"2044-12-25","Sunday","SE",2044 +"2044-12-26","Second Day of Christmas","SE",2044 +"2044-12-31","New Year's Eve","SE",2044 +"1995-01-01","New Year's Day","SG",1995 +"1995-01-31","Chinese New Year","SG",1995 +"1995-02-01","Chinese New Year","SG",1995 +"1995-03-02","Hari Raya Puasa* (*estimated)* (*estimated)","SG",1995 +"1995-04-14","Good Friday","SG",1995 +"1995-05-01","Labour Day","SG",1995 +"1995-05-09","Hari Raya Haji* (*estimated)* (*estimated)","SG",1995 +"1995-05-14","Vesak Day* (*estimated)","SG",1995 +"1995-08-09","National Day","SG",1995 +"1995-11-20","Deepavali* (*estimated)","SG",1995 +"1995-12-25","Christmas Day","SG",1995 +"1996-01-01","New Year's Day","SG",1996 +"1996-02-19","Chinese New Year","SG",1996 +"1996-02-19","Hari Raya Puasa* (*estimated)* (*estimated)","SG",1996 +"1996-02-20","Chinese New Year","SG",1996 +"1996-04-05","Good Friday","SG",1996 +"1996-04-27","Hari Raya Haji* (*estimated)* (*estimated)","SG",1996 +"1996-05-01","Labour Day","SG",1996 +"1996-05-31","Vesak Day* (*estimated)","SG",1996 +"1996-08-09","National Day","SG",1996 +"1996-11-09","Deepavali* (*estimated)","SG",1996 +"1996-12-25","Christmas Day","SG",1996 +"1997-01-01","New Year's Day","SG",1997 +"1997-02-07","Chinese New Year","SG",1997 +"1997-02-08","Chinese New Year","SG",1997 +"1997-02-08","Hari Raya Puasa* (*estimated)* (*estimated)","SG",1997 +"1997-03-28","Good Friday","SG",1997 +"1997-04-17","Hari Raya Haji* (*estimated)* (*estimated)","SG",1997 +"1997-05-01","Labour Day","SG",1997 +"1997-05-21","Vesak Day* (*estimated)","SG",1997 +"1997-08-09","National Day","SG",1997 +"1997-10-29","Deepavali* (*estimated)","SG",1997 +"1997-12-25","Christmas Day","SG",1997 +"1998-01-01","New Year's Day","SG",1998 +"1998-01-28","Chinese New Year","SG",1998 +"1998-01-29","Chinese New Year","SG",1998 +"1998-01-29","Hari Raya Puasa* (*estimated)* (*estimated)","SG",1998 +"1998-04-07","Hari Raya Haji* (*estimated)* (*estimated)","SG",1998 +"1998-04-10","Good Friday","SG",1998 +"1998-05-01","Labour Day","SG",1998 +"1998-05-10","Vesak Day* (*estimated)","SG",1998 +"1998-05-11","Vesak Day* (*estimated) (Observed)","SG",1998 +"1998-08-09","National Day","SG",1998 +"1998-08-10","National Day (Observed)","SG",1998 +"1998-11-17","Deepavali* (*estimated)","SG",1998 +"1998-12-25","Christmas Day","SG",1998 +"1999-01-01","New Year's Day","SG",1999 +"1999-01-18","Hari Raya Puasa* (*estimated)* (*estimated)","SG",1999 +"1999-02-16","Chinese New Year","SG",1999 +"1999-02-17","Chinese New Year","SG",1999 +"1999-03-27","Hari Raya Haji* (*estimated)* (*estimated)","SG",1999 +"1999-04-02","Good Friday","SG",1999 +"1999-05-01","Labour Day","SG",1999 +"1999-05-29","Vesak Day* (*estimated)","SG",1999 +"1999-08-09","National Day","SG",1999 +"1999-11-06","Deepavali* (*estimated)","SG",1999 +"1999-12-25","Christmas Day","SG",1999 +"2000-01-01","New Year's Day","SG",2000 +"2000-01-08","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2000 +"2000-02-05","Chinese New Year","SG",2000 +"2000-02-06","Chinese New Year","SG",2000 +"2000-02-07","Chinese New Year (Observed)","SG",2000 +"2000-03-16","Hari Raya Haji* (*estimated)* (*estimated)","SG",2000 +"2000-04-21","Good Friday","SG",2000 +"2000-05-01","Labour Day","SG",2000 +"2000-05-18","Vesak Day* (*estimated)","SG",2000 +"2000-08-09","National Day","SG",2000 +"2000-10-25","Deepavali* (*estimated)","SG",2000 +"2000-12-25","Christmas Day","SG",2000 +"2000-12-27","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2000 +"2001-01-01","New Year's Day","SG",2001 +"2001-01-24","Chinese New Year","SG",2001 +"2001-01-25","Chinese New Year","SG",2001 +"2001-03-06","Hari Raya Haji","SG",2001 +"2001-04-13","Good Friday","SG",2001 +"2001-05-01","Labour Day","SG",2001 +"2001-05-07","Vesak Day","SG",2001 +"2001-08-09","National Day","SG",2001 +"2001-11-03","Polling Day","SG",2001 +"2001-11-14","Deepavali","SG",2001 +"2001-12-16","Hari Raya Puasa","SG",2001 +"2001-12-17","Hari Raya Puasa (Observed)","SG",2001 +"2001-12-25","Christmas Day","SG",2001 +"2002-01-01","New Year's Day","SG",2002 +"2002-02-12","Chinese New Year","SG",2002 +"2002-02-13","Chinese New Year","SG",2002 +"2002-02-23","Hari Raya Haji","SG",2002 +"2002-03-29","Good Friday","SG",2002 +"2002-05-01","Labour Day","SG",2002 +"2002-05-26","Vesak Day","SG",2002 +"2002-05-27","Vesak Day (Observed)","SG",2002 +"2002-08-09","National Day","SG",2002 +"2002-11-03","Deepavali","SG",2002 +"2002-11-04","Deepavali (Observed)","SG",2002 +"2002-12-06","Hari Raya Puasa","SG",2002 +"2002-12-25","Christmas Day","SG",2002 +"2003-01-01","New Year's Day","SG",2003 +"2003-02-01","Chinese New Year","SG",2003 +"2003-02-02","Chinese New Year","SG",2003 +"2003-02-03","Chinese New Year (Observed)","SG",2003 +"2003-02-12","Hari Raya Haji","SG",2003 +"2003-04-18","Good Friday","SG",2003 +"2003-05-01","Labour Day","SG",2003 +"2003-05-15","Vesak Day","SG",2003 +"2003-08-09","National Day","SG",2003 +"2003-10-23","Deepavali","SG",2003 +"2003-11-25","Hari Raya Puasa","SG",2003 +"2003-12-25","Christmas Day","SG",2003 +"2004-01-01","New Year's Day","SG",2004 +"2004-01-22","Chinese New Year","SG",2004 +"2004-01-23","Chinese New Year","SG",2004 +"2004-02-01","Hari Raya Haji","SG",2004 +"2004-02-02","Hari Raya Haji (Observed)","SG",2004 +"2004-04-09","Good Friday","SG",2004 +"2004-05-01","Labour Day","SG",2004 +"2004-06-02","Vesak Day","SG",2004 +"2004-08-09","National Day","SG",2004 +"2004-11-11","Deepavali","SG",2004 +"2004-11-14","Hari Raya Puasa","SG",2004 +"2004-11-15","Hari Raya Puasa (Observed)","SG",2004 +"2004-12-25","Christmas Day","SG",2004 +"2005-01-01","New Year's Day","SG",2005 +"2005-01-21","Hari Raya Haji","SG",2005 +"2005-02-09","Chinese New Year","SG",2005 +"2005-02-10","Chinese New Year","SG",2005 +"2005-03-25","Good Friday","SG",2005 +"2005-05-01","Labour Day","SG",2005 +"2005-05-02","Labour Day (Observed)","SG",2005 +"2005-05-22","Vesak Day","SG",2005 +"2005-05-23","Vesak Day (Observed)","SG",2005 +"2005-08-09","National Day","SG",2005 +"2005-11-01","Deepavali","SG",2005 +"2005-11-03","Hari Raya Puasa","SG",2005 +"2005-12-25","Christmas Day","SG",2005 +"2005-12-26","Christmas Day (Observed)","SG",2005 +"2006-01-01","New Year's Day","SG",2006 +"2006-01-02","New Year's Day (Observed)","SG",2006 +"2006-01-10","Hari Raya Haji","SG",2006 +"2006-01-29","Chinese New Year","SG",2006 +"2006-01-30","Chinese New Year","SG",2006 +"2006-01-31","Chinese New Year (Observed)","SG",2006 +"2006-04-14","Good Friday","SG",2006 +"2006-05-01","Labour Day","SG",2006 +"2006-05-06","Polling Day","SG",2006 +"2006-05-12","Vesak Day","SG",2006 +"2006-08-09","National Day","SG",2006 +"2006-10-21","Deepavali","SG",2006 +"2006-10-24","Hari Raya Puasa","SG",2006 +"2006-12-25","Christmas Day","SG",2006 +"2006-12-31","Hari Raya Haji","SG",2006 +"2007-01-01","New Year's Day","SG",2007 +"2007-01-02","Hari Raya Haji (Observed)","SG",2007 +"2007-02-18","Chinese New Year","SG",2007 +"2007-02-19","Chinese New Year","SG",2007 +"2007-02-20","Chinese New Year (Observed)","SG",2007 +"2007-04-06","Good Friday","SG",2007 +"2007-05-01","Labour Day","SG",2007 +"2007-05-31","Vesak Day","SG",2007 +"2007-08-09","National Day","SG",2007 +"2007-10-13","Hari Raya Puasa","SG",2007 +"2007-11-08","Deepavali","SG",2007 +"2007-12-20","Hari Raya Haji","SG",2007 +"2007-12-25","Christmas Day","SG",2007 +"2008-01-01","New Year's Day","SG",2008 +"2008-02-07","Chinese New Year","SG",2008 +"2008-02-08","Chinese New Year","SG",2008 +"2008-03-21","Good Friday","SG",2008 +"2008-05-01","Labour Day","SG",2008 +"2008-05-19","Vesak Day","SG",2008 +"2008-08-09","National Day","SG",2008 +"2008-10-01","Hari Raya Puasa","SG",2008 +"2008-10-27","Deepavali","SG",2008 +"2008-12-08","Hari Raya Haji","SG",2008 +"2008-12-25","Christmas Day","SG",2008 +"2009-01-01","New Year's Day","SG",2009 +"2009-01-26","Chinese New Year","SG",2009 +"2009-01-27","Chinese New Year","SG",2009 +"2009-04-10","Good Friday","SG",2009 +"2009-05-01","Labour Day","SG",2009 +"2009-05-09","Vesak Day","SG",2009 +"2009-08-09","National Day","SG",2009 +"2009-08-10","National Day (Observed)","SG",2009 +"2009-09-20","Hari Raya Puasa","SG",2009 +"2009-09-21","Hari Raya Puasa (Observed)","SG",2009 +"2009-11-15","Deepavali","SG",2009 +"2009-11-16","Deepavali (Observed)","SG",2009 +"2009-11-27","Hari Raya Haji","SG",2009 +"2009-12-25","Christmas Day","SG",2009 +"2010-01-01","New Year's Day","SG",2010 +"2010-02-14","Chinese New Year","SG",2010 +"2010-02-15","Chinese New Year","SG",2010 +"2010-02-16","Chinese New Year (Observed)","SG",2010 +"2010-04-02","Good Friday","SG",2010 +"2010-05-01","Labour Day","SG",2010 +"2010-05-28","Vesak Day","SG",2010 +"2010-08-09","National Day","SG",2010 +"2010-09-10","Hari Raya Puasa","SG",2010 +"2010-11-05","Deepavali","SG",2010 +"2010-11-17","Hari Raya Haji","SG",2010 +"2010-12-25","Christmas Day","SG",2010 +"2011-01-01","New Year's Day","SG",2011 +"2011-02-03","Chinese New Year","SG",2011 +"2011-02-04","Chinese New Year","SG",2011 +"2011-04-22","Good Friday","SG",2011 +"2011-05-01","Labour Day","SG",2011 +"2011-05-02","Labour Day (Observed)","SG",2011 +"2011-05-07","Polling Day","SG",2011 +"2011-05-17","Vesak Day","SG",2011 +"2011-08-09","National Day","SG",2011 +"2011-08-30","Hari Raya Puasa","SG",2011 +"2011-10-26","Deepavali","SG",2011 +"2011-11-06","Hari Raya Haji","SG",2011 +"2011-11-07","Hari Raya Haji (Observed)","SG",2011 +"2011-12-25","Christmas Day","SG",2011 +"2011-12-26","Christmas Day (Observed)","SG",2011 +"2012-01-01","New Year's Day","SG",2012 +"2012-01-02","New Year's Day (Observed)","SG",2012 +"2012-01-23","Chinese New Year","SG",2012 +"2012-01-24","Chinese New Year","SG",2012 +"2012-04-06","Good Friday","SG",2012 +"2012-05-01","Labour Day","SG",2012 +"2012-05-05","Vesak Day","SG",2012 +"2012-08-09","National Day","SG",2012 +"2012-08-19","Hari Raya Puasa","SG",2012 +"2012-08-20","Hari Raya Puasa (Observed)","SG",2012 +"2012-10-26","Hari Raya Haji","SG",2012 +"2012-11-13","Deepavali","SG",2012 +"2012-12-25","Christmas Day","SG",2012 +"2013-01-01","New Year's Day","SG",2013 +"2013-02-10","Chinese New Year","SG",2013 +"2013-02-11","Chinese New Year","SG",2013 +"2013-02-12","Chinese New Year (Observed)","SG",2013 +"2013-03-29","Good Friday","SG",2013 +"2013-05-01","Labour Day","SG",2013 +"2013-05-24","Vesak Day","SG",2013 +"2013-08-08","Hari Raya Puasa","SG",2013 +"2013-08-09","National Day","SG",2013 +"2013-10-15","Hari Raya Haji","SG",2013 +"2013-11-02","Deepavali","SG",2013 +"2013-12-25","Christmas Day","SG",2013 +"2014-01-01","New Year's Day","SG",2014 +"2014-01-31","Chinese New Year","SG",2014 +"2014-02-01","Chinese New Year","SG",2014 +"2014-04-18","Good Friday","SG",2014 +"2014-05-01","Labour Day","SG",2014 +"2014-05-13","Vesak Day","SG",2014 +"2014-07-28","Hari Raya Puasa","SG",2014 +"2014-08-09","National Day","SG",2014 +"2014-10-05","Hari Raya Haji","SG",2014 +"2014-10-06","Hari Raya Haji (Observed)","SG",2014 +"2014-10-22","Deepavali","SG",2014 +"2014-12-25","Christmas Day","SG",2014 +"2015-01-01","New Year's Day","SG",2015 +"2015-02-19","Chinese New Year","SG",2015 +"2015-02-20","Chinese New Year","SG",2015 +"2015-04-03","Good Friday","SG",2015 +"2015-05-01","Labour Day","SG",2015 +"2015-06-01","Vesak Day","SG",2015 +"2015-07-17","Hari Raya Puasa","SG",2015 +"2015-08-07","SG50 Public Holiday","SG",2015 +"2015-08-09","National Day","SG",2015 +"2015-08-10","National Day (Observed)","SG",2015 +"2015-09-11","Polling Day","SG",2015 +"2015-09-24","Hari Raya Haji","SG",2015 +"2015-11-10","Deepavali","SG",2015 +"2015-12-25","Christmas Day","SG",2015 +"2016-01-01","New Year's Day","SG",2016 +"2016-02-08","Chinese New Year","SG",2016 +"2016-02-09","Chinese New Year","SG",2016 +"2016-03-25","Good Friday","SG",2016 +"2016-05-01","Labour Day","SG",2016 +"2016-05-02","Labour Day (Observed)","SG",2016 +"2016-05-21","Vesak Day","SG",2016 +"2016-07-06","Hari Raya Puasa","SG",2016 +"2016-08-09","National Day","SG",2016 +"2016-09-12","Hari Raya Haji","SG",2016 +"2016-10-29","Deepavali","SG",2016 +"2016-12-25","Christmas Day","SG",2016 +"2016-12-26","Christmas Day (Observed)","SG",2016 +"2017-01-01","New Year's Day","SG",2017 +"2017-01-02","New Year's Day (Observed)","SG",2017 +"2017-01-28","Chinese New Year","SG",2017 +"2017-01-29","Chinese New Year","SG",2017 +"2017-01-30","Chinese New Year (Observed)","SG",2017 +"2017-04-14","Good Friday","SG",2017 +"2017-05-01","Labour Day","SG",2017 +"2017-05-10","Vesak Day","SG",2017 +"2017-06-25","Hari Raya Puasa","SG",2017 +"2017-06-26","Hari Raya Puasa (Observed)","SG",2017 +"2017-08-09","National Day","SG",2017 +"2017-09-01","Hari Raya Haji","SG",2017 +"2017-10-18","Deepavali","SG",2017 +"2017-12-25","Christmas Day","SG",2017 +"2018-01-01","New Year's Day","SG",2018 +"2018-02-16","Chinese New Year","SG",2018 +"2018-02-17","Chinese New Year","SG",2018 +"2018-03-30","Good Friday","SG",2018 +"2018-05-01","Labour Day","SG",2018 +"2018-05-29","Vesak Day","SG",2018 +"2018-06-15","Hari Raya Puasa","SG",2018 +"2018-08-09","National Day","SG",2018 +"2018-08-22","Hari Raya Haji","SG",2018 +"2018-11-06","Deepavali","SG",2018 +"2018-12-25","Christmas Day","SG",2018 +"2019-01-01","New Year's Day","SG",2019 +"2019-02-05","Chinese New Year","SG",2019 +"2019-02-06","Chinese New Year","SG",2019 +"2019-04-19","Good Friday","SG",2019 +"2019-05-01","Labour Day","SG",2019 +"2019-05-19","Vesak Day","SG",2019 +"2019-05-20","Vesak Day (Observed)","SG",2019 +"2019-06-05","Hari Raya Puasa","SG",2019 +"2019-08-09","National Day","SG",2019 +"2019-08-11","Hari Raya Haji","SG",2019 +"2019-08-12","Hari Raya Haji (Observed)","SG",2019 +"2019-10-27","Deepavali","SG",2019 +"2019-10-28","Deepavali (Observed)","SG",2019 +"2019-12-25","Christmas Day","SG",2019 +"2020-01-01","New Year's Day","SG",2020 +"2020-01-25","Chinese New Year","SG",2020 +"2020-01-26","Chinese New Year","SG",2020 +"2020-01-27","Chinese New Year (Observed)","SG",2020 +"2020-04-10","Good Friday","SG",2020 +"2020-05-01","Labour Day","SG",2020 +"2020-05-07","Vesak Day","SG",2020 +"2020-05-24","Hari Raya Puasa","SG",2020 +"2020-05-25","Hari Raya Puasa (Observed)","SG",2020 +"2020-07-10","Polling Day","SG",2020 +"2020-07-31","Hari Raya Haji","SG",2020 +"2020-08-09","National Day","SG",2020 +"2020-08-10","National Day (Observed)","SG",2020 +"2020-11-14","Deepavali","SG",2020 +"2020-12-25","Christmas Day","SG",2020 +"2021-01-01","New Year's Day","SG",2021 +"2021-02-12","Chinese New Year","SG",2021 +"2021-02-13","Chinese New Year","SG",2021 +"2021-04-02","Good Friday","SG",2021 +"2021-05-01","Labour Day","SG",2021 +"2021-05-13","Hari Raya Puasa","SG",2021 +"2021-05-26","Vesak Day","SG",2021 +"2021-07-20","Hari Raya Haji","SG",2021 +"2021-08-09","National Day","SG",2021 +"2021-11-04","Deepavali","SG",2021 +"2021-12-25","Christmas Day","SG",2021 +"2022-01-01","New Year's Day","SG",2022 +"2022-02-01","Chinese New Year","SG",2022 +"2022-02-02","Chinese New Year","SG",2022 +"2022-04-15","Good Friday","SG",2022 +"2022-05-01","Labour Day","SG",2022 +"2022-05-02","Labour Day (Observed)","SG",2022 +"2022-05-03","Hari Raya Puasa","SG",2022 +"2022-05-15","Vesak Day","SG",2022 +"2022-05-16","Vesak Day (Observed)","SG",2022 +"2022-07-10","Hari Raya Haji","SG",2022 +"2022-07-11","Hari Raya Haji (Observed)","SG",2022 +"2022-08-09","National Day","SG",2022 +"2022-10-24","Deepavali","SG",2022 +"2022-12-25","Christmas Day","SG",2022 +"2022-12-26","Christmas Day (Observed)","SG",2022 +"2023-01-01","New Year's Day","SG",2023 +"2023-01-02","New Year's Day (Observed)","SG",2023 +"2023-01-22","Chinese New Year","SG",2023 +"2023-01-23","Chinese New Year","SG",2023 +"2023-01-24","Chinese New Year (Observed)","SG",2023 +"2023-04-07","Good Friday","SG",2023 +"2023-04-22","Hari Raya Puasa","SG",2023 +"2023-05-01","Labour Day","SG",2023 +"2023-06-02","Vesak Day","SG",2023 +"2023-06-29","Hari Raya Haji","SG",2023 +"2023-08-09","National Day","SG",2023 +"2023-11-12","Deepavali","SG",2023 +"2023-11-13","Deepavali (Observed)","SG",2023 +"2023-12-25","Christmas Day","SG",2023 +"2024-01-01","New Year's Day","SG",2024 +"2024-02-10","Chinese New Year","SG",2024 +"2024-02-11","Chinese New Year","SG",2024 +"2024-02-12","Chinese New Year (Observed)","SG",2024 +"2024-03-29","Good Friday","SG",2024 +"2024-04-10","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2024 +"2024-05-01","Labour Day","SG",2024 +"2024-05-22","Vesak Day* (*estimated)","SG",2024 +"2024-06-16","Hari Raya Haji* (*estimated)* (*estimated)","SG",2024 +"2024-06-17","Hari Raya Haji* (*estimated)* (*estimated) (Observed)","SG",2024 +"2024-08-09","National Day","SG",2024 +"2024-10-30","Deepavali* (*estimated)","SG",2024 +"2024-12-25","Christmas Day","SG",2024 +"2025-01-01","New Year's Day","SG",2025 +"2025-01-29","Chinese New Year","SG",2025 +"2025-01-30","Chinese New Year","SG",2025 +"2025-03-30","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2025 +"2025-03-31","Hari Raya Puasa* (*estimated)* (*estimated) (Observed)","SG",2025 +"2025-04-18","Good Friday","SG",2025 +"2025-05-01","Labour Day","SG",2025 +"2025-05-11","Vesak Day* (*estimated)","SG",2025 +"2025-05-12","Vesak Day* (*estimated) (Observed)","SG",2025 +"2025-06-06","Hari Raya Haji* (*estimated)* (*estimated)","SG",2025 +"2025-08-09","National Day","SG",2025 +"2025-11-18","Deepavali* (*estimated)","SG",2025 +"2025-12-25","Christmas Day","SG",2025 +"2026-01-01","New Year's Day","SG",2026 +"2026-02-17","Chinese New Year","SG",2026 +"2026-02-18","Chinese New Year","SG",2026 +"2026-03-20","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2026 +"2026-04-03","Good Friday","SG",2026 +"2026-05-01","Labour Day","SG",2026 +"2026-05-27","Hari Raya Haji* (*estimated)* (*estimated)","SG",2026 +"2026-05-31","Vesak Day* (*estimated)","SG",2026 +"2026-06-01","Vesak Day* (*estimated) (Observed)","SG",2026 +"2026-08-09","National Day","SG",2026 +"2026-08-10","National Day (Observed)","SG",2026 +"2026-11-07","Deepavali* (*estimated)","SG",2026 +"2026-12-25","Christmas Day","SG",2026 +"2027-01-01","New Year's Day","SG",2027 +"2027-02-06","Chinese New Year","SG",2027 +"2027-02-07","Chinese New Year","SG",2027 +"2027-02-08","Chinese New Year (Observed)","SG",2027 +"2027-03-09","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2027 +"2027-03-26","Good Friday","SG",2027 +"2027-05-01","Labour Day","SG",2027 +"2027-05-16","Hari Raya Haji* (*estimated)* (*estimated)","SG",2027 +"2027-05-17","Hari Raya Haji* (*estimated)* (*estimated) (Observed)","SG",2027 +"2027-05-20","Vesak Day* (*estimated)","SG",2027 +"2027-08-09","National Day","SG",2027 +"2027-10-27","Deepavali* (*estimated)","SG",2027 +"2027-12-25","Christmas Day","SG",2027 +"2028-01-01","New Year's Day","SG",2028 +"2028-01-26","Chinese New Year","SG",2028 +"2028-01-27","Chinese New Year","SG",2028 +"2028-02-26","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2028 +"2028-04-14","Good Friday","SG",2028 +"2028-05-01","Labour Day","SG",2028 +"2028-05-05","Hari Raya Haji* (*estimated)* (*estimated)","SG",2028 +"2028-05-09","Vesak Day* (*estimated)","SG",2028 +"2028-08-09","National Day","SG",2028 +"2028-11-14","Deepavali* (*estimated)","SG",2028 +"2028-12-25","Christmas Day","SG",2028 +"2029-01-01","New Year's Day","SG",2029 +"2029-02-13","Chinese New Year","SG",2029 +"2029-02-14","Chinese New Year","SG",2029 +"2029-02-14","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2029 +"2029-03-30","Good Friday","SG",2029 +"2029-04-24","Hari Raya Haji* (*estimated)* (*estimated)","SG",2029 +"2029-05-01","Labour Day","SG",2029 +"2029-05-27","Vesak Day* (*estimated)","SG",2029 +"2029-05-28","Vesak Day* (*estimated) (Observed)","SG",2029 +"2029-08-09","National Day","SG",2029 +"2029-11-04","Deepavali* (*estimated)","SG",2029 +"2029-11-05","Deepavali* (*estimated) (Observed)","SG",2029 +"2029-12-25","Christmas Day","SG",2029 +"2030-01-01","New Year's Day","SG",2030 +"2030-02-03","Chinese New Year","SG",2030 +"2030-02-04","Chinese New Year","SG",2030 +"2030-02-04","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2030 +"2030-02-05","Chinese New Year (Observed)","SG",2030 +"2030-04-13","Hari Raya Haji* (*estimated)* (*estimated)","SG",2030 +"2030-04-19","Good Friday","SG",2030 +"2030-05-01","Labour Day","SG",2030 +"2030-05-16","Vesak Day* (*estimated)","SG",2030 +"2030-08-09","National Day","SG",2030 +"2030-10-25","Deepavali* (*estimated)","SG",2030 +"2030-12-25","Christmas Day","SG",2030 +"2031-01-01","New Year's Day","SG",2031 +"2031-01-23","Chinese New Year","SG",2031 +"2031-01-24","Chinese New Year","SG",2031 +"2031-01-24","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2031 +"2031-04-02","Hari Raya Haji* (*estimated)* (*estimated)","SG",2031 +"2031-04-11","Good Friday","SG",2031 +"2031-05-01","Labour Day","SG",2031 +"2031-06-04","Vesak Day* (*estimated)","SG",2031 +"2031-08-09","National Day","SG",2031 +"2031-11-13","Deepavali* (*estimated)","SG",2031 +"2031-12-25","Christmas Day","SG",2031 +"2032-01-01","New Year's Day","SG",2032 +"2032-01-14","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2032 +"2032-02-11","Chinese New Year","SG",2032 +"2032-02-12","Chinese New Year","SG",2032 +"2032-03-22","Hari Raya Haji* (*estimated)* (*estimated)","SG",2032 +"2032-03-26","Good Friday","SG",2032 +"2032-05-01","Labour Day","SG",2032 +"2032-05-23","Vesak Day* (*estimated)","SG",2032 +"2032-05-24","Vesak Day* (*estimated) (Observed)","SG",2032 +"2032-08-09","National Day","SG",2032 +"2032-11-01","Deepavali* (*estimated)","SG",2032 +"2032-12-25","Christmas Day","SG",2032 +"2033-01-01","New Year's Day","SG",2033 +"2033-01-02","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2033 +"2033-01-03","Hari Raya Puasa* (*estimated)* (*estimated) (Observed)","SG",2033 +"2033-01-31","Chinese New Year","SG",2033 +"2033-02-01","Chinese New Year","SG",2033 +"2033-03-11","Hari Raya Haji* (*estimated)* (*estimated)","SG",2033 +"2033-04-15","Good Friday","SG",2033 +"2033-05-01","Labour Day","SG",2033 +"2033-05-02","Labour Day (Observed)","SG",2033 +"2033-05-13","Vesak Day* (*estimated)","SG",2033 +"2033-08-09","National Day","SG",2033 +"2033-10-21","Deepavali* (*estimated)","SG",2033 +"2033-12-23","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2033 +"2033-12-25","Christmas Day","SG",2033 +"2033-12-26","Christmas Day (Observed)","SG",2033 +"2034-01-01","New Year's Day","SG",2034 +"2034-01-02","New Year's Day (Observed)","SG",2034 +"2034-02-19","Chinese New Year","SG",2034 +"2034-02-20","Chinese New Year","SG",2034 +"2034-02-21","Chinese New Year (Observed)","SG",2034 +"2034-03-01","Hari Raya Haji* (*estimated)* (*estimated)","SG",2034 +"2034-04-07","Good Friday","SG",2034 +"2034-05-01","Labour Day","SG",2034 +"2034-06-01","Vesak Day* (*estimated)","SG",2034 +"2034-08-09","National Day","SG",2034 +"2034-11-09","Deepavali* (*estimated)","SG",2034 +"2034-12-12","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2034 +"2034-12-25","Christmas Day","SG",2034 +"2035-01-01","New Year's Day","SG",2035 +"2035-02-08","Chinese New Year","SG",2035 +"2035-02-09","Chinese New Year","SG",2035 +"2035-02-18","Hari Raya Haji* (*estimated)* (*estimated)","SG",2035 +"2035-02-19","Hari Raya Haji* (*estimated)* (*estimated) (Observed)","SG",2035 +"2035-03-23","Good Friday","SG",2035 +"2035-05-01","Labour Day","SG",2035 +"2035-05-22","Vesak Day* (*estimated)","SG",2035 +"2035-08-09","National Day","SG",2035 +"2035-10-29","Deepavali* (*estimated)","SG",2035 +"2035-12-01","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2035 +"2035-12-25","Christmas Day","SG",2035 +"2036-01-01","New Year's Day","SG",2036 +"2036-01-28","Chinese New Year","SG",2036 +"2036-01-29","Chinese New Year","SG",2036 +"2036-02-07","Hari Raya Haji* (*estimated)* (*estimated)","SG",2036 +"2036-04-11","Good Friday","SG",2036 +"2036-05-01","Labour Day","SG",2036 +"2036-05-10","Vesak Day* (*estimated)","SG",2036 +"2036-08-09","National Day","SG",2036 +"2036-11-16","Deepavali* (*estimated)","SG",2036 +"2036-11-17","Deepavali* (*estimated) (Observed)","SG",2036 +"2036-11-19","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2036 +"2036-12-25","Christmas Day","SG",2036 +"2037-01-01","New Year's Day","SG",2037 +"2037-01-26","Hari Raya Haji* (*estimated)* (*estimated)","SG",2037 +"2037-02-15","Chinese New Year","SG",2037 +"2037-02-16","Chinese New Year","SG",2037 +"2037-02-17","Chinese New Year (Observed)","SG",2037 +"2037-04-03","Good Friday","SG",2037 +"2037-05-01","Labour Day","SG",2037 +"2037-05-29","Vesak Day* (*estimated)","SG",2037 +"2037-08-09","National Day","SG",2037 +"2037-08-10","National Day (Observed)","SG",2037 +"2037-11-05","Deepavali* (*estimated)","SG",2037 +"2037-11-08","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2037 +"2037-11-09","Hari Raya Puasa* (*estimated)* (*estimated) (Observed)","SG",2037 +"2037-12-25","Christmas Day","SG",2037 +"2038-01-01","New Year's Day","SG",2038 +"2038-01-16","Hari Raya Haji* (*estimated)* (*estimated)","SG",2038 +"2038-02-04","Chinese New Year","SG",2038 +"2038-02-05","Chinese New Year","SG",2038 +"2038-04-23","Good Friday","SG",2038 +"2038-05-01","Labour Day","SG",2038 +"2038-05-18","Vesak Day* (*estimated)","SG",2038 +"2038-08-09","National Day","SG",2038 +"2038-10-26","Deepavali* (*estimated)","SG",2038 +"2038-10-29","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2038 +"2038-12-25","Christmas Day","SG",2038 +"2039-01-01","New Year's Day","SG",2039 +"2039-01-05","Hari Raya Haji* (*estimated)* (*estimated)","SG",2039 +"2039-01-24","Chinese New Year","SG",2039 +"2039-01-25","Chinese New Year","SG",2039 +"2039-04-08","Good Friday","SG",2039 +"2039-05-01","Labour Day","SG",2039 +"2039-05-02","Labour Day (Observed)","SG",2039 +"2039-05-07","Vesak Day* (*estimated)","SG",2039 +"2039-08-09","National Day","SG",2039 +"2039-10-19","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2039 +"2039-11-14","Deepavali* (*estimated)","SG",2039 +"2039-12-25","Christmas Day","SG",2039 +"2039-12-26","Hari Raya Haji* (*estimated)* (*estimated)","SG",2039 +"2039-12-27","Christmas Day (Observed)","SG",2039 +"2040-01-01","New Year's Day","SG",2040 +"2040-01-02","New Year's Day (Observed)","SG",2040 +"2040-02-12","Chinese New Year","SG",2040 +"2040-02-13","Chinese New Year","SG",2040 +"2040-02-14","Chinese New Year (Observed)","SG",2040 +"2040-03-30","Good Friday","SG",2040 +"2040-05-01","Labour Day","SG",2040 +"2040-05-25","Vesak Day* (*estimated)","SG",2040 +"2040-08-09","National Day","SG",2040 +"2040-10-07","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2040 +"2040-10-08","Hari Raya Puasa* (*estimated)* (*estimated) (Observed)","SG",2040 +"2040-11-03","Deepavali* (*estimated)","SG",2040 +"2040-12-14","Hari Raya Haji* (*estimated)* (*estimated)","SG",2040 +"2040-12-25","Christmas Day","SG",2040 +"2041-01-01","New Year's Day","SG",2041 +"2041-02-01","Chinese New Year","SG",2041 +"2041-02-02","Chinese New Year","SG",2041 +"2041-04-19","Good Friday","SG",2041 +"2041-05-01","Labour Day","SG",2041 +"2041-05-14","Vesak Day* (*estimated)","SG",2041 +"2041-08-09","National Day","SG",2041 +"2041-09-26","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2041 +"2041-10-23","Deepavali* (*estimated)","SG",2041 +"2041-12-04","Hari Raya Haji* (*estimated)* (*estimated)","SG",2041 +"2041-12-25","Christmas Day","SG",2041 +"2042-01-01","New Year's Day","SG",2042 +"2042-01-22","Chinese New Year","SG",2042 +"2042-01-23","Chinese New Year","SG",2042 +"2042-04-04","Good Friday","SG",2042 +"2042-05-01","Labour Day","SG",2042 +"2042-06-02","Vesak Day* (*estimated)","SG",2042 +"2042-08-09","National Day","SG",2042 +"2042-09-15","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2042 +"2042-11-11","Deepavali* (*estimated)","SG",2042 +"2042-11-23","Hari Raya Haji* (*estimated)* (*estimated)","SG",2042 +"2042-11-24","Hari Raya Haji* (*estimated)* (*estimated) (Observed)","SG",2042 +"2042-12-25","Christmas Day","SG",2042 +"2043-01-01","New Year's Day","SG",2043 +"2043-02-10","Chinese New Year","SG",2043 +"2043-02-11","Chinese New Year","SG",2043 +"2043-03-27","Good Friday","SG",2043 +"2043-05-01","Labour Day","SG",2043 +"2043-05-23","Vesak Day* (*estimated)","SG",2043 +"2043-08-09","National Day","SG",2043 +"2043-08-10","National Day (Observed)","SG",2043 +"2043-09-04","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2043 +"2043-10-31","Deepavali* (*estimated)","SG",2043 +"2043-11-12","Hari Raya Haji* (*estimated)* (*estimated)","SG",2043 +"2043-12-25","Christmas Day","SG",2043 +"2044-01-01","New Year's Day","SG",2044 +"2044-01-30","Chinese New Year","SG",2044 +"2044-01-31","Chinese New Year","SG",2044 +"2044-02-01","Chinese New Year (Observed)","SG",2044 +"2044-04-15","Good Friday","SG",2044 +"2044-05-01","Labour Day","SG",2044 +"2044-05-02","Labour Day (Observed)","SG",2044 +"2044-05-12","Vesak Day* (*estimated)","SG",2044 +"2044-08-09","National Day","SG",2044 +"2044-08-24","Hari Raya Puasa* (*estimated)* (*estimated)","SG",2044 +"2044-10-31","Hari Raya Haji* (*estimated)* (*estimated)","SG",2044 +"2044-11-17","Deepavali* (*estimated)","SG",2044 +"2044-12-25","Christmas Day","SG",2044 +"2044-12-26","Christmas Day (Observed)","SG",2044 +"1995-01-01","novo leto","SI",1995 +"1995-01-02","novo leto","SI",1995 +"1995-02-08","Presernov dan","SI",1995 +"1995-04-17","Velikonocni ponedeljek","SI",1995 +"1995-04-27","dan upora proti okupatorju","SI",1995 +"1995-05-01","praznik dela","SI",1995 +"1995-05-02","praznik dela","SI",1995 +"1995-06-25","dan drzavnosti","SI",1995 +"1995-08-15","Marijino vnebovzetje","SI",1995 +"1995-10-31","dan reformacije","SI",1995 +"1995-11-01","dan spomina na mrtve","SI",1995 +"1995-12-25","Bozic","SI",1995 +"1995-12-26","dan samostojnosti in enotnosti","SI",1995 +"1996-01-01","novo leto","SI",1996 +"1996-01-02","novo leto","SI",1996 +"1996-02-08","Presernov dan","SI",1996 +"1996-04-08","Velikonocni ponedeljek","SI",1996 +"1996-04-27","dan upora proti okupatorju","SI",1996 +"1996-05-01","praznik dela","SI",1996 +"1996-05-02","praznik dela","SI",1996 +"1996-06-25","dan drzavnosti","SI",1996 +"1996-08-15","Marijino vnebovzetje","SI",1996 +"1996-10-31","dan reformacije","SI",1996 +"1996-11-01","dan spomina na mrtve","SI",1996 +"1996-12-25","Bozic","SI",1996 +"1996-12-26","dan samostojnosti in enotnosti","SI",1996 +"1997-01-01","novo leto","SI",1997 +"1997-01-02","novo leto","SI",1997 +"1997-02-08","Presernov dan","SI",1997 +"1997-03-31","Velikonocni ponedeljek","SI",1997 +"1997-04-27","dan upora proti okupatorju","SI",1997 +"1997-05-01","praznik dela","SI",1997 +"1997-05-02","praznik dela","SI",1997 +"1997-06-25","dan drzavnosti","SI",1997 +"1997-08-15","Marijino vnebovzetje","SI",1997 +"1997-10-31","dan reformacije","SI",1997 +"1997-11-01","dan spomina na mrtve","SI",1997 +"1997-12-25","Bozic","SI",1997 +"1997-12-26","dan samostojnosti in enotnosti","SI",1997 +"1998-01-01","novo leto","SI",1998 +"1998-01-02","novo leto","SI",1998 +"1998-02-08","Presernov dan","SI",1998 +"1998-04-13","Velikonocni ponedeljek","SI",1998 +"1998-04-27","dan upora proti okupatorju","SI",1998 +"1998-05-01","praznik dela","SI",1998 +"1998-05-02","praznik dela","SI",1998 +"1998-06-25","dan drzavnosti","SI",1998 +"1998-08-15","Marijino vnebovzetje","SI",1998 +"1998-10-31","dan reformacije","SI",1998 +"1998-11-01","dan spomina na mrtve","SI",1998 +"1998-12-25","Bozic","SI",1998 +"1998-12-26","dan samostojnosti in enotnosti","SI",1998 +"1999-01-01","novo leto","SI",1999 +"1999-01-02","novo leto","SI",1999 +"1999-02-08","Presernov dan","SI",1999 +"1999-04-05","Velikonocni ponedeljek","SI",1999 +"1999-04-27","dan upora proti okupatorju","SI",1999 +"1999-05-01","praznik dela","SI",1999 +"1999-05-02","praznik dela","SI",1999 +"1999-06-25","dan drzavnosti","SI",1999 +"1999-08-15","Marijino vnebovzetje","SI",1999 +"1999-10-31","dan reformacije","SI",1999 +"1999-11-01","dan spomina na mrtve","SI",1999 +"1999-12-25","Bozic","SI",1999 +"1999-12-26","dan samostojnosti in enotnosti","SI",1999 +"2000-01-01","novo leto","SI",2000 +"2000-01-02","novo leto","SI",2000 +"2000-02-08","Presernov dan","SI",2000 +"2000-04-24","Velikonocni ponedeljek","SI",2000 +"2000-04-27","dan upora proti okupatorju","SI",2000 +"2000-05-01","praznik dela","SI",2000 +"2000-05-02","praznik dela","SI",2000 +"2000-06-25","dan drzavnosti","SI",2000 +"2000-08-15","Marijino vnebovzetje","SI",2000 +"2000-10-31","dan reformacije","SI",2000 +"2000-11-01","dan spomina na mrtve","SI",2000 +"2000-12-25","Bozic","SI",2000 +"2000-12-26","dan samostojnosti in enotnosti","SI",2000 +"2001-01-01","novo leto","SI",2001 +"2001-01-02","novo leto","SI",2001 +"2001-02-08","Presernov dan","SI",2001 +"2001-04-16","Velikonocni ponedeljek","SI",2001 +"2001-04-27","dan upora proti okupatorju","SI",2001 +"2001-05-01","praznik dela","SI",2001 +"2001-05-02","praznik dela","SI",2001 +"2001-06-25","dan drzavnosti","SI",2001 +"2001-08-15","Marijino vnebovzetje","SI",2001 +"2001-10-31","dan reformacije","SI",2001 +"2001-11-01","dan spomina na mrtve","SI",2001 +"2001-12-25","Bozic","SI",2001 +"2001-12-26","dan samostojnosti in enotnosti","SI",2001 +"2002-01-01","novo leto","SI",2002 +"2002-01-02","novo leto","SI",2002 +"2002-02-08","Presernov dan","SI",2002 +"2002-04-01","Velikonocni ponedeljek","SI",2002 +"2002-04-27","dan upora proti okupatorju","SI",2002 +"2002-05-01","praznik dela","SI",2002 +"2002-05-02","praznik dela","SI",2002 +"2002-06-25","dan drzavnosti","SI",2002 +"2002-08-15","Marijino vnebovzetje","SI",2002 +"2002-10-31","dan reformacije","SI",2002 +"2002-11-01","dan spomina na mrtve","SI",2002 +"2002-12-25","Bozic","SI",2002 +"2002-12-26","dan samostojnosti in enotnosti","SI",2002 +"2003-01-01","novo leto","SI",2003 +"2003-01-02","novo leto","SI",2003 +"2003-02-08","Presernov dan","SI",2003 +"2003-04-21","Velikonocni ponedeljek","SI",2003 +"2003-04-27","dan upora proti okupatorju","SI",2003 +"2003-05-01","praznik dela","SI",2003 +"2003-05-02","praznik dela","SI",2003 +"2003-06-25","dan drzavnosti","SI",2003 +"2003-08-15","Marijino vnebovzetje","SI",2003 +"2003-10-31","dan reformacije","SI",2003 +"2003-11-01","dan spomina na mrtve","SI",2003 +"2003-12-25","Bozic","SI",2003 +"2003-12-26","dan samostojnosti in enotnosti","SI",2003 +"2004-01-01","novo leto","SI",2004 +"2004-01-02","novo leto","SI",2004 +"2004-02-08","Presernov dan","SI",2004 +"2004-04-12","Velikonocni ponedeljek","SI",2004 +"2004-04-27","dan upora proti okupatorju","SI",2004 +"2004-05-01","praznik dela","SI",2004 +"2004-05-02","praznik dela","SI",2004 +"2004-06-25","dan drzavnosti","SI",2004 +"2004-08-15","Marijino vnebovzetje","SI",2004 +"2004-10-31","dan reformacije","SI",2004 +"2004-11-01","dan spomina na mrtve","SI",2004 +"2004-12-25","Bozic","SI",2004 +"2004-12-26","dan samostojnosti in enotnosti","SI",2004 +"2005-01-01","novo leto","SI",2005 +"2005-01-02","novo leto","SI",2005 +"2005-02-08","Presernov dan","SI",2005 +"2005-03-28","Velikonocni ponedeljek","SI",2005 +"2005-04-27","dan upora proti okupatorju","SI",2005 +"2005-05-01","praznik dela","SI",2005 +"2005-05-02","praznik dela","SI",2005 +"2005-06-25","dan drzavnosti","SI",2005 +"2005-08-15","Marijino vnebovzetje","SI",2005 +"2005-10-31","dan reformacije","SI",2005 +"2005-11-01","dan spomina na mrtve","SI",2005 +"2005-12-25","Bozic","SI",2005 +"2005-12-26","dan samostojnosti in enotnosti","SI",2005 +"2006-01-01","novo leto","SI",2006 +"2006-01-02","novo leto","SI",2006 +"2006-02-08","Presernov dan","SI",2006 +"2006-04-17","Velikonocni ponedeljek","SI",2006 +"2006-04-27","dan upora proti okupatorju","SI",2006 +"2006-05-01","praznik dela","SI",2006 +"2006-05-02","praznik dela","SI",2006 +"2006-06-25","dan drzavnosti","SI",2006 +"2006-08-15","Marijino vnebovzetje","SI",2006 +"2006-10-31","dan reformacije","SI",2006 +"2006-11-01","dan spomina na mrtve","SI",2006 +"2006-12-25","Bozic","SI",2006 +"2006-12-26","dan samostojnosti in enotnosti","SI",2006 +"2007-01-01","novo leto","SI",2007 +"2007-01-02","novo leto","SI",2007 +"2007-02-08","Presernov dan","SI",2007 +"2007-04-09","Velikonocni ponedeljek","SI",2007 +"2007-04-27","dan upora proti okupatorju","SI",2007 +"2007-05-01","praznik dela","SI",2007 +"2007-05-02","praznik dela","SI",2007 +"2007-06-25","dan drzavnosti","SI",2007 +"2007-08-15","Marijino vnebovzetje","SI",2007 +"2007-10-31","dan reformacije","SI",2007 +"2007-11-01","dan spomina na mrtve","SI",2007 +"2007-12-25","Bozic","SI",2007 +"2007-12-26","dan samostojnosti in enotnosti","SI",2007 +"2008-01-01","novo leto","SI",2008 +"2008-01-02","novo leto","SI",2008 +"2008-02-08","Presernov dan","SI",2008 +"2008-03-24","Velikonocni ponedeljek","SI",2008 +"2008-04-27","dan upora proti okupatorju","SI",2008 +"2008-05-01","praznik dela","SI",2008 +"2008-05-02","praznik dela","SI",2008 +"2008-06-25","dan drzavnosti","SI",2008 +"2008-08-15","Marijino vnebovzetje","SI",2008 +"2008-10-31","dan reformacije","SI",2008 +"2008-11-01","dan spomina na mrtve","SI",2008 +"2008-12-25","Bozic","SI",2008 +"2008-12-26","dan samostojnosti in enotnosti","SI",2008 +"2009-01-01","novo leto","SI",2009 +"2009-01-02","novo leto","SI",2009 +"2009-02-08","Presernov dan","SI",2009 +"2009-04-13","Velikonocni ponedeljek","SI",2009 +"2009-04-27","dan upora proti okupatorju","SI",2009 +"2009-05-01","praznik dela","SI",2009 +"2009-05-02","praznik dela","SI",2009 +"2009-06-25","dan drzavnosti","SI",2009 +"2009-08-15","Marijino vnebovzetje","SI",2009 +"2009-10-31","dan reformacije","SI",2009 +"2009-11-01","dan spomina na mrtve","SI",2009 +"2009-12-25","Bozic","SI",2009 +"2009-12-26","dan samostojnosti in enotnosti","SI",2009 +"2010-01-01","novo leto","SI",2010 +"2010-01-02","novo leto","SI",2010 +"2010-02-08","Presernov dan","SI",2010 +"2010-04-05","Velikonocni ponedeljek","SI",2010 +"2010-04-27","dan upora proti okupatorju","SI",2010 +"2010-05-01","praznik dela","SI",2010 +"2010-05-02","praznik dela","SI",2010 +"2010-06-25","dan drzavnosti","SI",2010 +"2010-08-15","Marijino vnebovzetje","SI",2010 +"2010-10-31","dan reformacije","SI",2010 +"2010-11-01","dan spomina na mrtve","SI",2010 +"2010-12-25","Bozic","SI",2010 +"2010-12-26","dan samostojnosti in enotnosti","SI",2010 +"2011-01-01","novo leto","SI",2011 +"2011-01-02","novo leto","SI",2011 +"2011-02-08","Presernov dan","SI",2011 +"2011-04-25","Velikonocni ponedeljek","SI",2011 +"2011-04-27","dan upora proti okupatorju","SI",2011 +"2011-05-01","praznik dela","SI",2011 +"2011-05-02","praznik dela","SI",2011 +"2011-06-25","dan drzavnosti","SI",2011 +"2011-08-15","Marijino vnebovzetje","SI",2011 +"2011-10-31","dan reformacije","SI",2011 +"2011-11-01","dan spomina na mrtve","SI",2011 +"2011-12-25","Bozic","SI",2011 +"2011-12-26","dan samostojnosti in enotnosti","SI",2011 +"2012-01-01","novo leto","SI",2012 +"2012-01-02","novo leto","SI",2012 +"2012-02-08","Presernov dan","SI",2012 +"2012-04-09","Velikonocni ponedeljek","SI",2012 +"2012-04-27","dan upora proti okupatorju","SI",2012 +"2012-05-01","praznik dela","SI",2012 +"2012-05-02","praznik dela","SI",2012 +"2012-06-25","dan drzavnosti","SI",2012 +"2012-08-15","Marijino vnebovzetje","SI",2012 +"2012-10-31","dan reformacije","SI",2012 +"2012-11-01","dan spomina na mrtve","SI",2012 +"2012-12-25","Bozic","SI",2012 +"2012-12-26","dan samostojnosti in enotnosti","SI",2012 +"2013-01-01","novo leto","SI",2013 +"2013-02-08","Presernov dan","SI",2013 +"2013-04-01","Velikonocni ponedeljek","SI",2013 +"2013-04-27","dan upora proti okupatorju","SI",2013 +"2013-05-01","praznik dela","SI",2013 +"2013-05-02","praznik dela","SI",2013 +"2013-06-25","dan drzavnosti","SI",2013 +"2013-08-15","Marijino vnebovzetje","SI",2013 +"2013-10-31","dan reformacije","SI",2013 +"2013-11-01","dan spomina na mrtve","SI",2013 +"2013-12-25","Bozic","SI",2013 +"2013-12-26","dan samostojnosti in enotnosti","SI",2013 +"2014-01-01","novo leto","SI",2014 +"2014-02-08","Presernov dan","SI",2014 +"2014-04-21","Velikonocni ponedeljek","SI",2014 +"2014-04-27","dan upora proti okupatorju","SI",2014 +"2014-05-01","praznik dela","SI",2014 +"2014-05-02","praznik dela","SI",2014 +"2014-06-25","dan drzavnosti","SI",2014 +"2014-08-15","Marijino vnebovzetje","SI",2014 +"2014-10-31","dan reformacije","SI",2014 +"2014-11-01","dan spomina na mrtve","SI",2014 +"2014-12-25","Bozic","SI",2014 +"2014-12-26","dan samostojnosti in enotnosti","SI",2014 +"2015-01-01","novo leto","SI",2015 +"2015-02-08","Presernov dan","SI",2015 +"2015-04-06","Velikonocni ponedeljek","SI",2015 +"2015-04-27","dan upora proti okupatorju","SI",2015 +"2015-05-01","praznik dela","SI",2015 +"2015-05-02","praznik dela","SI",2015 +"2015-06-25","dan drzavnosti","SI",2015 +"2015-08-15","Marijino vnebovzetje","SI",2015 +"2015-10-31","dan reformacije","SI",2015 +"2015-11-01","dan spomina na mrtve","SI",2015 +"2015-12-25","Bozic","SI",2015 +"2015-12-26","dan samostojnosti in enotnosti","SI",2015 +"2016-01-01","novo leto","SI",2016 +"2016-02-08","Presernov dan","SI",2016 +"2016-03-28","Velikonocni ponedeljek","SI",2016 +"2016-04-27","dan upora proti okupatorju","SI",2016 +"2016-05-01","praznik dela","SI",2016 +"2016-05-02","praznik dela","SI",2016 +"2016-06-25","dan drzavnosti","SI",2016 +"2016-08-15","Marijino vnebovzetje","SI",2016 +"2016-10-31","dan reformacije","SI",2016 +"2016-11-01","dan spomina na mrtve","SI",2016 +"2016-12-25","Bozic","SI",2016 +"2016-12-26","dan samostojnosti in enotnosti","SI",2016 +"2017-01-01","novo leto","SI",2017 +"2017-01-02","novo leto","SI",2017 +"2017-02-08","Presernov dan","SI",2017 +"2017-04-17","Velikonocni ponedeljek","SI",2017 +"2017-04-27","dan upora proti okupatorju","SI",2017 +"2017-05-01","praznik dela","SI",2017 +"2017-05-02","praznik dela","SI",2017 +"2017-06-25","dan drzavnosti","SI",2017 +"2017-08-15","Marijino vnebovzetje","SI",2017 +"2017-10-31","dan reformacije","SI",2017 +"2017-11-01","dan spomina na mrtve","SI",2017 +"2017-12-25","Bozic","SI",2017 +"2017-12-26","dan samostojnosti in enotnosti","SI",2017 +"2018-01-01","novo leto","SI",2018 +"2018-01-02","novo leto","SI",2018 +"2018-02-08","Presernov dan","SI",2018 +"2018-04-02","Velikonocni ponedeljek","SI",2018 +"2018-04-27","dan upora proti okupatorju","SI",2018 +"2018-05-01","praznik dela","SI",2018 +"2018-05-02","praznik dela","SI",2018 +"2018-06-25","dan drzavnosti","SI",2018 +"2018-08-15","Marijino vnebovzetje","SI",2018 +"2018-10-31","dan reformacije","SI",2018 +"2018-11-01","dan spomina na mrtve","SI",2018 +"2018-12-25","Bozic","SI",2018 +"2018-12-26","dan samostojnosti in enotnosti","SI",2018 +"2019-01-01","novo leto","SI",2019 +"2019-01-02","novo leto","SI",2019 +"2019-02-08","Presernov dan","SI",2019 +"2019-04-22","Velikonocni ponedeljek","SI",2019 +"2019-04-27","dan upora proti okupatorju","SI",2019 +"2019-05-01","praznik dela","SI",2019 +"2019-05-02","praznik dela","SI",2019 +"2019-06-25","dan drzavnosti","SI",2019 +"2019-08-15","Marijino vnebovzetje","SI",2019 +"2019-10-31","dan reformacije","SI",2019 +"2019-11-01","dan spomina na mrtve","SI",2019 +"2019-12-25","Bozic","SI",2019 +"2019-12-26","dan samostojnosti in enotnosti","SI",2019 +"2020-01-01","novo leto","SI",2020 +"2020-01-02","novo leto","SI",2020 +"2020-02-08","Presernov dan","SI",2020 +"2020-04-13","Velikonocni ponedeljek","SI",2020 +"2020-04-27","dan upora proti okupatorju","SI",2020 +"2020-05-01","praznik dela","SI",2020 +"2020-05-02","praznik dela","SI",2020 +"2020-06-25","dan drzavnosti","SI",2020 +"2020-08-15","Marijino vnebovzetje","SI",2020 +"2020-10-31","dan reformacije","SI",2020 +"2020-11-01","dan spomina na mrtve","SI",2020 +"2020-12-25","Bozic","SI",2020 +"2020-12-26","dan samostojnosti in enotnosti","SI",2020 +"2021-01-01","novo leto","SI",2021 +"2021-01-02","novo leto","SI",2021 +"2021-02-08","Presernov dan","SI",2021 +"2021-04-05","Velikonocni ponedeljek","SI",2021 +"2021-04-27","dan upora proti okupatorju","SI",2021 +"2021-05-01","praznik dela","SI",2021 +"2021-05-02","praznik dela","SI",2021 +"2021-06-25","dan drzavnosti","SI",2021 +"2021-08-15","Marijino vnebovzetje","SI",2021 +"2021-10-31","dan reformacije","SI",2021 +"2021-11-01","dan spomina na mrtve","SI",2021 +"2021-12-25","Bozic","SI",2021 +"2021-12-26","dan samostojnosti in enotnosti","SI",2021 +"2022-01-01","novo leto","SI",2022 +"2022-01-02","novo leto","SI",2022 +"2022-02-08","Presernov dan","SI",2022 +"2022-04-18","Velikonocni ponedeljek","SI",2022 +"2022-04-27","dan upora proti okupatorju","SI",2022 +"2022-05-01","praznik dela","SI",2022 +"2022-05-02","praznik dela","SI",2022 +"2022-06-25","dan drzavnosti","SI",2022 +"2022-08-15","Marijino vnebovzetje","SI",2022 +"2022-10-31","dan reformacije","SI",2022 +"2022-11-01","dan spomina na mrtve","SI",2022 +"2022-12-25","Bozic","SI",2022 +"2022-12-26","dan samostojnosti in enotnosti","SI",2022 +"2023-01-01","novo leto","SI",2023 +"2023-01-02","novo leto","SI",2023 +"2023-02-08","Presernov dan","SI",2023 +"2023-04-10","Velikonocni ponedeljek","SI",2023 +"2023-04-27","dan upora proti okupatorju","SI",2023 +"2023-05-01","praznik dela","SI",2023 +"2023-05-02","praznik dela","SI",2023 +"2023-06-25","dan drzavnosti","SI",2023 +"2023-08-15","Marijino vnebovzetje","SI",2023 +"2023-10-31","dan reformacije","SI",2023 +"2023-11-01","dan spomina na mrtve","SI",2023 +"2023-12-25","Bozic","SI",2023 +"2023-12-26","dan samostojnosti in enotnosti","SI",2023 +"2024-01-01","novo leto","SI",2024 +"2024-01-02","novo leto","SI",2024 +"2024-02-08","Presernov dan","SI",2024 +"2024-04-01","Velikonocni ponedeljek","SI",2024 +"2024-04-27","dan upora proti okupatorju","SI",2024 +"2024-05-01","praznik dela","SI",2024 +"2024-05-02","praznik dela","SI",2024 +"2024-06-25","dan drzavnosti","SI",2024 +"2024-08-15","Marijino vnebovzetje","SI",2024 +"2024-10-31","dan reformacije","SI",2024 +"2024-11-01","dan spomina na mrtve","SI",2024 +"2024-12-25","Bozic","SI",2024 +"2024-12-26","dan samostojnosti in enotnosti","SI",2024 +"2025-01-01","novo leto","SI",2025 +"2025-01-02","novo leto","SI",2025 +"2025-02-08","Presernov dan","SI",2025 +"2025-04-21","Velikonocni ponedeljek","SI",2025 +"2025-04-27","dan upora proti okupatorju","SI",2025 +"2025-05-01","praznik dela","SI",2025 +"2025-05-02","praznik dela","SI",2025 +"2025-06-25","dan drzavnosti","SI",2025 +"2025-08-15","Marijino vnebovzetje","SI",2025 +"2025-10-31","dan reformacije","SI",2025 +"2025-11-01","dan spomina na mrtve","SI",2025 +"2025-12-25","Bozic","SI",2025 +"2025-12-26","dan samostojnosti in enotnosti","SI",2025 +"2026-01-01","novo leto","SI",2026 +"2026-01-02","novo leto","SI",2026 +"2026-02-08","Presernov dan","SI",2026 +"2026-04-06","Velikonocni ponedeljek","SI",2026 +"2026-04-27","dan upora proti okupatorju","SI",2026 +"2026-05-01","praznik dela","SI",2026 +"2026-05-02","praznik dela","SI",2026 +"2026-06-25","dan drzavnosti","SI",2026 +"2026-08-15","Marijino vnebovzetje","SI",2026 +"2026-10-31","dan reformacije","SI",2026 +"2026-11-01","dan spomina na mrtve","SI",2026 +"2026-12-25","Bozic","SI",2026 +"2026-12-26","dan samostojnosti in enotnosti","SI",2026 +"2027-01-01","novo leto","SI",2027 +"2027-01-02","novo leto","SI",2027 +"2027-02-08","Presernov dan","SI",2027 +"2027-03-29","Velikonocni ponedeljek","SI",2027 +"2027-04-27","dan upora proti okupatorju","SI",2027 +"2027-05-01","praznik dela","SI",2027 +"2027-05-02","praznik dela","SI",2027 +"2027-06-25","dan drzavnosti","SI",2027 +"2027-08-15","Marijino vnebovzetje","SI",2027 +"2027-10-31","dan reformacije","SI",2027 +"2027-11-01","dan spomina na mrtve","SI",2027 +"2027-12-25","Bozic","SI",2027 +"2027-12-26","dan samostojnosti in enotnosti","SI",2027 +"2028-01-01","novo leto","SI",2028 +"2028-01-02","novo leto","SI",2028 +"2028-02-08","Presernov dan","SI",2028 +"2028-04-17","Velikonocni ponedeljek","SI",2028 +"2028-04-27","dan upora proti okupatorju","SI",2028 +"2028-05-01","praznik dela","SI",2028 +"2028-05-02","praznik dela","SI",2028 +"2028-06-25","dan drzavnosti","SI",2028 +"2028-08-15","Marijino vnebovzetje","SI",2028 +"2028-10-31","dan reformacije","SI",2028 +"2028-11-01","dan spomina na mrtve","SI",2028 +"2028-12-25","Bozic","SI",2028 +"2028-12-26","dan samostojnosti in enotnosti","SI",2028 +"2029-01-01","novo leto","SI",2029 +"2029-01-02","novo leto","SI",2029 +"2029-02-08","Presernov dan","SI",2029 +"2029-04-02","Velikonocni ponedeljek","SI",2029 +"2029-04-27","dan upora proti okupatorju","SI",2029 +"2029-05-01","praznik dela","SI",2029 +"2029-05-02","praznik dela","SI",2029 +"2029-06-25","dan drzavnosti","SI",2029 +"2029-08-15","Marijino vnebovzetje","SI",2029 +"2029-10-31","dan reformacije","SI",2029 +"2029-11-01","dan spomina na mrtve","SI",2029 +"2029-12-25","Bozic","SI",2029 +"2029-12-26","dan samostojnosti in enotnosti","SI",2029 +"2030-01-01","novo leto","SI",2030 +"2030-01-02","novo leto","SI",2030 +"2030-02-08","Presernov dan","SI",2030 +"2030-04-22","Velikonocni ponedeljek","SI",2030 +"2030-04-27","dan upora proti okupatorju","SI",2030 +"2030-05-01","praznik dela","SI",2030 +"2030-05-02","praznik dela","SI",2030 +"2030-06-25","dan drzavnosti","SI",2030 +"2030-08-15","Marijino vnebovzetje","SI",2030 +"2030-10-31","dan reformacije","SI",2030 +"2030-11-01","dan spomina na mrtve","SI",2030 +"2030-12-25","Bozic","SI",2030 +"2030-12-26","dan samostojnosti in enotnosti","SI",2030 +"2031-01-01","novo leto","SI",2031 +"2031-01-02","novo leto","SI",2031 +"2031-02-08","Presernov dan","SI",2031 +"2031-04-14","Velikonocni ponedeljek","SI",2031 +"2031-04-27","dan upora proti okupatorju","SI",2031 +"2031-05-01","praznik dela","SI",2031 +"2031-05-02","praznik dela","SI",2031 +"2031-06-25","dan drzavnosti","SI",2031 +"2031-08-15","Marijino vnebovzetje","SI",2031 +"2031-10-31","dan reformacije","SI",2031 +"2031-11-01","dan spomina na mrtve","SI",2031 +"2031-12-25","Bozic","SI",2031 +"2031-12-26","dan samostojnosti in enotnosti","SI",2031 +"2032-01-01","novo leto","SI",2032 +"2032-01-02","novo leto","SI",2032 +"2032-02-08","Presernov dan","SI",2032 +"2032-03-29","Velikonocni ponedeljek","SI",2032 +"2032-04-27","dan upora proti okupatorju","SI",2032 +"2032-05-01","praznik dela","SI",2032 +"2032-05-02","praznik dela","SI",2032 +"2032-06-25","dan drzavnosti","SI",2032 +"2032-08-15","Marijino vnebovzetje","SI",2032 +"2032-10-31","dan reformacije","SI",2032 +"2032-11-01","dan spomina na mrtve","SI",2032 +"2032-12-25","Bozic","SI",2032 +"2032-12-26","dan samostojnosti in enotnosti","SI",2032 +"2033-01-01","novo leto","SI",2033 +"2033-01-02","novo leto","SI",2033 +"2033-02-08","Presernov dan","SI",2033 +"2033-04-18","Velikonocni ponedeljek","SI",2033 +"2033-04-27","dan upora proti okupatorju","SI",2033 +"2033-05-01","praznik dela","SI",2033 +"2033-05-02","praznik dela","SI",2033 +"2033-06-25","dan drzavnosti","SI",2033 +"2033-08-15","Marijino vnebovzetje","SI",2033 +"2033-10-31","dan reformacije","SI",2033 +"2033-11-01","dan spomina na mrtve","SI",2033 +"2033-12-25","Bozic","SI",2033 +"2033-12-26","dan samostojnosti in enotnosti","SI",2033 +"2034-01-01","novo leto","SI",2034 +"2034-01-02","novo leto","SI",2034 +"2034-02-08","Presernov dan","SI",2034 +"2034-04-10","Velikonocni ponedeljek","SI",2034 +"2034-04-27","dan upora proti okupatorju","SI",2034 +"2034-05-01","praznik dela","SI",2034 +"2034-05-02","praznik dela","SI",2034 +"2034-06-25","dan drzavnosti","SI",2034 +"2034-08-15","Marijino vnebovzetje","SI",2034 +"2034-10-31","dan reformacije","SI",2034 +"2034-11-01","dan spomina na mrtve","SI",2034 +"2034-12-25","Bozic","SI",2034 +"2034-12-26","dan samostojnosti in enotnosti","SI",2034 +"2035-01-01","novo leto","SI",2035 +"2035-01-02","novo leto","SI",2035 +"2035-02-08","Presernov dan","SI",2035 +"2035-03-26","Velikonocni ponedeljek","SI",2035 +"2035-04-27","dan upora proti okupatorju","SI",2035 +"2035-05-01","praznik dela","SI",2035 +"2035-05-02","praznik dela","SI",2035 +"2035-06-25","dan drzavnosti","SI",2035 +"2035-08-15","Marijino vnebovzetje","SI",2035 +"2035-10-31","dan reformacije","SI",2035 +"2035-11-01","dan spomina na mrtve","SI",2035 +"2035-12-25","Bozic","SI",2035 +"2035-12-26","dan samostojnosti in enotnosti","SI",2035 +"2036-01-01","novo leto","SI",2036 +"2036-01-02","novo leto","SI",2036 +"2036-02-08","Presernov dan","SI",2036 +"2036-04-14","Velikonocni ponedeljek","SI",2036 +"2036-04-27","dan upora proti okupatorju","SI",2036 +"2036-05-01","praznik dela","SI",2036 +"2036-05-02","praznik dela","SI",2036 +"2036-06-25","dan drzavnosti","SI",2036 +"2036-08-15","Marijino vnebovzetje","SI",2036 +"2036-10-31","dan reformacije","SI",2036 +"2036-11-01","dan spomina na mrtve","SI",2036 +"2036-12-25","Bozic","SI",2036 +"2036-12-26","dan samostojnosti in enotnosti","SI",2036 +"2037-01-01","novo leto","SI",2037 +"2037-01-02","novo leto","SI",2037 +"2037-02-08","Presernov dan","SI",2037 +"2037-04-06","Velikonocni ponedeljek","SI",2037 +"2037-04-27","dan upora proti okupatorju","SI",2037 +"2037-05-01","praznik dela","SI",2037 +"2037-05-02","praznik dela","SI",2037 +"2037-06-25","dan drzavnosti","SI",2037 +"2037-08-15","Marijino vnebovzetje","SI",2037 +"2037-10-31","dan reformacije","SI",2037 +"2037-11-01","dan spomina na mrtve","SI",2037 +"2037-12-25","Bozic","SI",2037 +"2037-12-26","dan samostojnosti in enotnosti","SI",2037 +"2038-01-01","novo leto","SI",2038 +"2038-01-02","novo leto","SI",2038 +"2038-02-08","Presernov dan","SI",2038 +"2038-04-26","Velikonocni ponedeljek","SI",2038 +"2038-04-27","dan upora proti okupatorju","SI",2038 +"2038-05-01","praznik dela","SI",2038 +"2038-05-02","praznik dela","SI",2038 +"2038-06-25","dan drzavnosti","SI",2038 +"2038-08-15","Marijino vnebovzetje","SI",2038 +"2038-10-31","dan reformacije","SI",2038 +"2038-11-01","dan spomina na mrtve","SI",2038 +"2038-12-25","Bozic","SI",2038 +"2038-12-26","dan samostojnosti in enotnosti","SI",2038 +"2039-01-01","novo leto","SI",2039 +"2039-01-02","novo leto","SI",2039 +"2039-02-08","Presernov dan","SI",2039 +"2039-04-11","Velikonocni ponedeljek","SI",2039 +"2039-04-27","dan upora proti okupatorju","SI",2039 +"2039-05-01","praznik dela","SI",2039 +"2039-05-02","praznik dela","SI",2039 +"2039-06-25","dan drzavnosti","SI",2039 +"2039-08-15","Marijino vnebovzetje","SI",2039 +"2039-10-31","dan reformacije","SI",2039 +"2039-11-01","dan spomina na mrtve","SI",2039 +"2039-12-25","Bozic","SI",2039 +"2039-12-26","dan samostojnosti in enotnosti","SI",2039 +"2040-01-01","novo leto","SI",2040 +"2040-01-02","novo leto","SI",2040 +"2040-02-08","Presernov dan","SI",2040 +"2040-04-02","Velikonocni ponedeljek","SI",2040 +"2040-04-27","dan upora proti okupatorju","SI",2040 +"2040-05-01","praznik dela","SI",2040 +"2040-05-02","praznik dela","SI",2040 +"2040-06-25","dan drzavnosti","SI",2040 +"2040-08-15","Marijino vnebovzetje","SI",2040 +"2040-10-31","dan reformacije","SI",2040 +"2040-11-01","dan spomina na mrtve","SI",2040 +"2040-12-25","Bozic","SI",2040 +"2040-12-26","dan samostojnosti in enotnosti","SI",2040 +"2041-01-01","novo leto","SI",2041 +"2041-01-02","novo leto","SI",2041 +"2041-02-08","Presernov dan","SI",2041 +"2041-04-22","Velikonocni ponedeljek","SI",2041 +"2041-04-27","dan upora proti okupatorju","SI",2041 +"2041-05-01","praznik dela","SI",2041 +"2041-05-02","praznik dela","SI",2041 +"2041-06-25","dan drzavnosti","SI",2041 +"2041-08-15","Marijino vnebovzetje","SI",2041 +"2041-10-31","dan reformacije","SI",2041 +"2041-11-01","dan spomina na mrtve","SI",2041 +"2041-12-25","Bozic","SI",2041 +"2041-12-26","dan samostojnosti in enotnosti","SI",2041 +"2042-01-01","novo leto","SI",2042 +"2042-01-02","novo leto","SI",2042 +"2042-02-08","Presernov dan","SI",2042 +"2042-04-07","Velikonocni ponedeljek","SI",2042 +"2042-04-27","dan upora proti okupatorju","SI",2042 +"2042-05-01","praznik dela","SI",2042 +"2042-05-02","praznik dela","SI",2042 +"2042-06-25","dan drzavnosti","SI",2042 +"2042-08-15","Marijino vnebovzetje","SI",2042 +"2042-10-31","dan reformacije","SI",2042 +"2042-11-01","dan spomina na mrtve","SI",2042 +"2042-12-25","Bozic","SI",2042 +"2042-12-26","dan samostojnosti in enotnosti","SI",2042 +"2043-01-01","novo leto","SI",2043 +"2043-01-02","novo leto","SI",2043 +"2043-02-08","Presernov dan","SI",2043 +"2043-03-30","Velikonocni ponedeljek","SI",2043 +"2043-04-27","dan upora proti okupatorju","SI",2043 +"2043-05-01","praznik dela","SI",2043 +"2043-05-02","praznik dela","SI",2043 +"2043-06-25","dan drzavnosti","SI",2043 +"2043-08-15","Marijino vnebovzetje","SI",2043 +"2043-10-31","dan reformacije","SI",2043 +"2043-11-01","dan spomina na mrtve","SI",2043 +"2043-12-25","Bozic","SI",2043 +"2043-12-26","dan samostojnosti in enotnosti","SI",2043 +"2044-01-01","novo leto","SI",2044 +"2044-01-02","novo leto","SI",2044 +"2044-02-08","Presernov dan","SI",2044 +"2044-04-18","Velikonocni ponedeljek","SI",2044 +"2044-04-27","dan upora proti okupatorju","SI",2044 +"2044-05-01","praznik dela","SI",2044 +"2044-05-02","praznik dela","SI",2044 +"2044-06-25","dan drzavnosti","SI",2044 +"2044-08-15","Marijino vnebovzetje","SI",2044 +"2044-10-31","dan reformacije","SI",2044 +"2044-11-01","dan spomina na mrtve","SI",2044 +"2044-12-25","Bozic","SI",2044 +"2044-12-26","dan samostojnosti in enotnosti","SI",2044 +"1995-01-01","Day of the Establishment of the Slovak Republic","SK",1995 +"1995-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",1995 +"1995-04-14","Good Friday","SK",1995 +"1995-04-17","Easter Monday","SK",1995 +"1995-05-01","Labor Day","SK",1995 +"1995-07-05","St. Cyril and Methodius Day","SK",1995 +"1995-08-29","Slovak National Uprising Anniversary","SK",1995 +"1995-09-01","Constitution Day","SK",1995 +"1995-09-15","Day of Our Lady of the Seven Sorrows","SK",1995 +"1995-11-01","All Saints' Day","SK",1995 +"1995-12-24","Christmas Eve","SK",1995 +"1995-12-25","Christmas Day","SK",1995 +"1995-12-26","Second Day of Christmas","SK",1995 +"1996-01-01","Day of the Establishment of the Slovak Republic","SK",1996 +"1996-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",1996 +"1996-04-05","Good Friday","SK",1996 +"1996-04-08","Easter Monday","SK",1996 +"1996-05-01","Labor Day","SK",1996 +"1996-07-05","St. Cyril and Methodius Day","SK",1996 +"1996-08-29","Slovak National Uprising Anniversary","SK",1996 +"1996-09-01","Constitution Day","SK",1996 +"1996-09-15","Day of Our Lady of the Seven Sorrows","SK",1996 +"1996-11-01","All Saints' Day","SK",1996 +"1996-12-24","Christmas Eve","SK",1996 +"1996-12-25","Christmas Day","SK",1996 +"1996-12-26","Second Day of Christmas","SK",1996 +"1997-01-01","Day of the Establishment of the Slovak Republic","SK",1997 +"1997-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",1997 +"1997-03-28","Good Friday","SK",1997 +"1997-03-31","Easter Monday","SK",1997 +"1997-05-01","Labor Day","SK",1997 +"1997-05-08","Day of Victory over Fascism","SK",1997 +"1997-07-05","St. Cyril and Methodius Day","SK",1997 +"1997-08-29","Slovak National Uprising Anniversary","SK",1997 +"1997-09-01","Constitution Day","SK",1997 +"1997-09-15","Day of Our Lady of the Seven Sorrows","SK",1997 +"1997-11-01","All Saints' Day","SK",1997 +"1997-12-24","Christmas Eve","SK",1997 +"1997-12-25","Christmas Day","SK",1997 +"1997-12-26","Second Day of Christmas","SK",1997 +"1998-01-01","Day of the Establishment of the Slovak Republic","SK",1998 +"1998-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",1998 +"1998-04-10","Good Friday","SK",1998 +"1998-04-13","Easter Monday","SK",1998 +"1998-05-01","Labor Day","SK",1998 +"1998-05-08","Day of Victory over Fascism","SK",1998 +"1998-07-05","St. Cyril and Methodius Day","SK",1998 +"1998-08-29","Slovak National Uprising Anniversary","SK",1998 +"1998-09-01","Constitution Day","SK",1998 +"1998-09-15","Day of Our Lady of the Seven Sorrows","SK",1998 +"1998-11-01","All Saints' Day","SK",1998 +"1998-12-24","Christmas Eve","SK",1998 +"1998-12-25","Christmas Day","SK",1998 +"1998-12-26","Second Day of Christmas","SK",1998 +"1999-01-01","Day of the Establishment of the Slovak Republic","SK",1999 +"1999-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",1999 +"1999-04-02","Good Friday","SK",1999 +"1999-04-05","Easter Monday","SK",1999 +"1999-05-01","Labor Day","SK",1999 +"1999-05-08","Day of Victory over Fascism","SK",1999 +"1999-07-05","St. Cyril and Methodius Day","SK",1999 +"1999-08-29","Slovak National Uprising Anniversary","SK",1999 +"1999-09-01","Constitution Day","SK",1999 +"1999-09-15","Day of Our Lady of the Seven Sorrows","SK",1999 +"1999-11-01","All Saints' Day","SK",1999 +"1999-12-24","Christmas Eve","SK",1999 +"1999-12-25","Christmas Day","SK",1999 +"1999-12-26","Second Day of Christmas","SK",1999 +"2000-01-01","Day of the Establishment of the Slovak Republic","SK",2000 +"2000-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2000 +"2000-04-21","Good Friday","SK",2000 +"2000-04-24","Easter Monday","SK",2000 +"2000-05-01","Labor Day","SK",2000 +"2000-05-08","Day of Victory over Fascism","SK",2000 +"2000-07-05","St. Cyril and Methodius Day","SK",2000 +"2000-08-29","Slovak National Uprising Anniversary","SK",2000 +"2000-09-01","Constitution Day","SK",2000 +"2000-09-15","Day of Our Lady of the Seven Sorrows","SK",2000 +"2000-11-01","All Saints' Day","SK",2000 +"2000-12-24","Christmas Eve","SK",2000 +"2000-12-25","Christmas Day","SK",2000 +"2000-12-26","Second Day of Christmas","SK",2000 +"2001-01-01","Day of the Establishment of the Slovak Republic","SK",2001 +"2001-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2001 +"2001-04-13","Good Friday","SK",2001 +"2001-04-16","Easter Monday","SK",2001 +"2001-05-01","Labor Day","SK",2001 +"2001-05-08","Day of Victory over Fascism","SK",2001 +"2001-07-05","St. Cyril and Methodius Day","SK",2001 +"2001-08-29","Slovak National Uprising Anniversary","SK",2001 +"2001-09-01","Constitution Day","SK",2001 +"2001-09-15","Day of Our Lady of the Seven Sorrows","SK",2001 +"2001-11-01","All Saints' Day","SK",2001 +"2001-11-17","Struggle for Freedom and Democracy Day","SK",2001 +"2001-12-24","Christmas Eve","SK",2001 +"2001-12-25","Christmas Day","SK",2001 +"2001-12-26","Second Day of Christmas","SK",2001 +"2002-01-01","Day of the Establishment of the Slovak Republic","SK",2002 +"2002-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2002 +"2002-03-29","Good Friday","SK",2002 +"2002-04-01","Easter Monday","SK",2002 +"2002-05-01","Labor Day","SK",2002 +"2002-05-08","Day of Victory over Fascism","SK",2002 +"2002-07-05","St. Cyril and Methodius Day","SK",2002 +"2002-08-29","Slovak National Uprising Anniversary","SK",2002 +"2002-09-01","Constitution Day","SK",2002 +"2002-09-15","Day of Our Lady of the Seven Sorrows","SK",2002 +"2002-11-01","All Saints' Day","SK",2002 +"2002-11-17","Struggle for Freedom and Democracy Day","SK",2002 +"2002-12-24","Christmas Eve","SK",2002 +"2002-12-25","Christmas Day","SK",2002 +"2002-12-26","Second Day of Christmas","SK",2002 +"2003-01-01","Day of the Establishment of the Slovak Republic","SK",2003 +"2003-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2003 +"2003-04-18","Good Friday","SK",2003 +"2003-04-21","Easter Monday","SK",2003 +"2003-05-01","Labor Day","SK",2003 +"2003-05-08","Day of Victory over Fascism","SK",2003 +"2003-07-05","St. Cyril and Methodius Day","SK",2003 +"2003-08-29","Slovak National Uprising Anniversary","SK",2003 +"2003-09-01","Constitution Day","SK",2003 +"2003-09-15","Day of Our Lady of the Seven Sorrows","SK",2003 +"2003-11-01","All Saints' Day","SK",2003 +"2003-11-17","Struggle for Freedom and Democracy Day","SK",2003 +"2003-12-24","Christmas Eve","SK",2003 +"2003-12-25","Christmas Day","SK",2003 +"2003-12-26","Second Day of Christmas","SK",2003 +"2004-01-01","Day of the Establishment of the Slovak Republic","SK",2004 +"2004-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2004 +"2004-04-09","Good Friday","SK",2004 +"2004-04-12","Easter Monday","SK",2004 +"2004-05-01","Labor Day","SK",2004 +"2004-05-08","Day of Victory over Fascism","SK",2004 +"2004-07-05","St. Cyril and Methodius Day","SK",2004 +"2004-08-29","Slovak National Uprising Anniversary","SK",2004 +"2004-09-01","Constitution Day","SK",2004 +"2004-09-15","Day of Our Lady of the Seven Sorrows","SK",2004 +"2004-11-01","All Saints' Day","SK",2004 +"2004-11-17","Struggle for Freedom and Democracy Day","SK",2004 +"2004-12-24","Christmas Eve","SK",2004 +"2004-12-25","Christmas Day","SK",2004 +"2004-12-26","Second Day of Christmas","SK",2004 +"2005-01-01","Day of the Establishment of the Slovak Republic","SK",2005 +"2005-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2005 +"2005-03-25","Good Friday","SK",2005 +"2005-03-28","Easter Monday","SK",2005 +"2005-05-01","Labor Day","SK",2005 +"2005-05-08","Day of Victory over Fascism","SK",2005 +"2005-07-05","St. Cyril and Methodius Day","SK",2005 +"2005-08-29","Slovak National Uprising Anniversary","SK",2005 +"2005-09-01","Constitution Day","SK",2005 +"2005-09-15","Day of Our Lady of the Seven Sorrows","SK",2005 +"2005-11-01","All Saints' Day","SK",2005 +"2005-11-17","Struggle for Freedom and Democracy Day","SK",2005 +"2005-12-24","Christmas Eve","SK",2005 +"2005-12-25","Christmas Day","SK",2005 +"2005-12-26","Second Day of Christmas","SK",2005 +"2006-01-01","Day of the Establishment of the Slovak Republic","SK",2006 +"2006-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2006 +"2006-04-14","Good Friday","SK",2006 +"2006-04-17","Easter Monday","SK",2006 +"2006-05-01","Labor Day","SK",2006 +"2006-05-08","Day of Victory over Fascism","SK",2006 +"2006-07-05","St. Cyril and Methodius Day","SK",2006 +"2006-08-29","Slovak National Uprising Anniversary","SK",2006 +"2006-09-01","Constitution Day","SK",2006 +"2006-09-15","Day of Our Lady of the Seven Sorrows","SK",2006 +"2006-11-01","All Saints' Day","SK",2006 +"2006-11-17","Struggle for Freedom and Democracy Day","SK",2006 +"2006-12-24","Christmas Eve","SK",2006 +"2006-12-25","Christmas Day","SK",2006 +"2006-12-26","Second Day of Christmas","SK",2006 +"2007-01-01","Day of the Establishment of the Slovak Republic","SK",2007 +"2007-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2007 +"2007-04-06","Good Friday","SK",2007 +"2007-04-09","Easter Monday","SK",2007 +"2007-05-01","Labor Day","SK",2007 +"2007-05-08","Day of Victory over Fascism","SK",2007 +"2007-07-05","St. Cyril and Methodius Day","SK",2007 +"2007-08-29","Slovak National Uprising Anniversary","SK",2007 +"2007-09-01","Constitution Day","SK",2007 +"2007-09-15","Day of Our Lady of the Seven Sorrows","SK",2007 +"2007-11-01","All Saints' Day","SK",2007 +"2007-11-17","Struggle for Freedom and Democracy Day","SK",2007 +"2007-12-24","Christmas Eve","SK",2007 +"2007-12-25","Christmas Day","SK",2007 +"2007-12-26","Second Day of Christmas","SK",2007 +"2008-01-01","Day of the Establishment of the Slovak Republic","SK",2008 +"2008-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2008 +"2008-03-21","Good Friday","SK",2008 +"2008-03-24","Easter Monday","SK",2008 +"2008-05-01","Labor Day","SK",2008 +"2008-05-08","Day of Victory over Fascism","SK",2008 +"2008-07-05","St. Cyril and Methodius Day","SK",2008 +"2008-08-29","Slovak National Uprising Anniversary","SK",2008 +"2008-09-01","Constitution Day","SK",2008 +"2008-09-15","Day of Our Lady of the Seven Sorrows","SK",2008 +"2008-11-01","All Saints' Day","SK",2008 +"2008-11-17","Struggle for Freedom and Democracy Day","SK",2008 +"2008-12-24","Christmas Eve","SK",2008 +"2008-12-25","Christmas Day","SK",2008 +"2008-12-26","Second Day of Christmas","SK",2008 +"2009-01-01","Day of the Establishment of the Slovak Republic","SK",2009 +"2009-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2009 +"2009-04-10","Good Friday","SK",2009 +"2009-04-13","Easter Monday","SK",2009 +"2009-05-01","Labor Day","SK",2009 +"2009-05-08","Day of Victory over Fascism","SK",2009 +"2009-07-05","St. Cyril and Methodius Day","SK",2009 +"2009-08-29","Slovak National Uprising Anniversary","SK",2009 +"2009-09-01","Constitution Day","SK",2009 +"2009-09-15","Day of Our Lady of the Seven Sorrows","SK",2009 +"2009-11-01","All Saints' Day","SK",2009 +"2009-11-17","Struggle for Freedom and Democracy Day","SK",2009 +"2009-12-24","Christmas Eve","SK",2009 +"2009-12-25","Christmas Day","SK",2009 +"2009-12-26","Second Day of Christmas","SK",2009 +"2010-01-01","Day of the Establishment of the Slovak Republic","SK",2010 +"2010-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2010 +"2010-04-02","Good Friday","SK",2010 +"2010-04-05","Easter Monday","SK",2010 +"2010-05-01","Labor Day","SK",2010 +"2010-05-08","Day of Victory over Fascism","SK",2010 +"2010-07-05","St. Cyril and Methodius Day","SK",2010 +"2010-08-29","Slovak National Uprising Anniversary","SK",2010 +"2010-09-01","Constitution Day","SK",2010 +"2010-09-15","Day of Our Lady of the Seven Sorrows","SK",2010 +"2010-11-01","All Saints' Day","SK",2010 +"2010-11-17","Struggle for Freedom and Democracy Day","SK",2010 +"2010-12-24","Christmas Eve","SK",2010 +"2010-12-25","Christmas Day","SK",2010 +"2010-12-26","Second Day of Christmas","SK",2010 +"2011-01-01","Day of the Establishment of the Slovak Republic","SK",2011 +"2011-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2011 +"2011-04-22","Good Friday","SK",2011 +"2011-04-25","Easter Monday","SK",2011 +"2011-05-01","Labor Day","SK",2011 +"2011-05-08","Day of Victory over Fascism","SK",2011 +"2011-07-05","St. Cyril and Methodius Day","SK",2011 +"2011-08-29","Slovak National Uprising Anniversary","SK",2011 +"2011-09-01","Constitution Day","SK",2011 +"2011-09-15","Day of Our Lady of the Seven Sorrows","SK",2011 +"2011-11-01","All Saints' Day","SK",2011 +"2011-11-17","Struggle for Freedom and Democracy Day","SK",2011 +"2011-12-24","Christmas Eve","SK",2011 +"2011-12-25","Christmas Day","SK",2011 +"2011-12-26","Second Day of Christmas","SK",2011 +"2012-01-01","Day of the Establishment of the Slovak Republic","SK",2012 +"2012-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2012 +"2012-04-06","Good Friday","SK",2012 +"2012-04-09","Easter Monday","SK",2012 +"2012-05-01","Labor Day","SK",2012 +"2012-05-08","Day of Victory over Fascism","SK",2012 +"2012-07-05","St. Cyril and Methodius Day","SK",2012 +"2012-08-29","Slovak National Uprising Anniversary","SK",2012 +"2012-09-01","Constitution Day","SK",2012 +"2012-09-15","Day of Our Lady of the Seven Sorrows","SK",2012 +"2012-11-01","All Saints' Day","SK",2012 +"2012-11-17","Struggle for Freedom and Democracy Day","SK",2012 +"2012-12-24","Christmas Eve","SK",2012 +"2012-12-25","Christmas Day","SK",2012 +"2012-12-26","Second Day of Christmas","SK",2012 +"2013-01-01","Day of the Establishment of the Slovak Republic","SK",2013 +"2013-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2013 +"2013-03-29","Good Friday","SK",2013 +"2013-04-01","Easter Monday","SK",2013 +"2013-05-01","Labor Day","SK",2013 +"2013-05-08","Day of Victory over Fascism","SK",2013 +"2013-07-05","St. Cyril and Methodius Day","SK",2013 +"2013-08-29","Slovak National Uprising Anniversary","SK",2013 +"2013-09-01","Constitution Day","SK",2013 +"2013-09-15","Day of Our Lady of the Seven Sorrows","SK",2013 +"2013-11-01","All Saints' Day","SK",2013 +"2013-11-17","Struggle for Freedom and Democracy Day","SK",2013 +"2013-12-24","Christmas Eve","SK",2013 +"2013-12-25","Christmas Day","SK",2013 +"2013-12-26","Second Day of Christmas","SK",2013 +"2014-01-01","Day of the Establishment of the Slovak Republic","SK",2014 +"2014-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2014 +"2014-04-18","Good Friday","SK",2014 +"2014-04-21","Easter Monday","SK",2014 +"2014-05-01","Labor Day","SK",2014 +"2014-05-08","Day of Victory over Fascism","SK",2014 +"2014-07-05","St. Cyril and Methodius Day","SK",2014 +"2014-08-29","Slovak National Uprising Anniversary","SK",2014 +"2014-09-01","Constitution Day","SK",2014 +"2014-09-15","Day of Our Lady of the Seven Sorrows","SK",2014 +"2014-11-01","All Saints' Day","SK",2014 +"2014-11-17","Struggle for Freedom and Democracy Day","SK",2014 +"2014-12-24","Christmas Eve","SK",2014 +"2014-12-25","Christmas Day","SK",2014 +"2014-12-26","Second Day of Christmas","SK",2014 +"2015-01-01","Day of the Establishment of the Slovak Republic","SK",2015 +"2015-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2015 +"2015-04-03","Good Friday","SK",2015 +"2015-04-06","Easter Monday","SK",2015 +"2015-05-01","Labor Day","SK",2015 +"2015-05-08","Day of Victory over Fascism","SK",2015 +"2015-07-05","St. Cyril and Methodius Day","SK",2015 +"2015-08-29","Slovak National Uprising Anniversary","SK",2015 +"2015-09-01","Constitution Day","SK",2015 +"2015-09-15","Day of Our Lady of the Seven Sorrows","SK",2015 +"2015-11-01","All Saints' Day","SK",2015 +"2015-11-17","Struggle for Freedom and Democracy Day","SK",2015 +"2015-12-24","Christmas Eve","SK",2015 +"2015-12-25","Christmas Day","SK",2015 +"2015-12-26","Second Day of Christmas","SK",2015 +"2016-01-01","Day of the Establishment of the Slovak Republic","SK",2016 +"2016-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2016 +"2016-03-25","Good Friday","SK",2016 +"2016-03-28","Easter Monday","SK",2016 +"2016-05-01","Labor Day","SK",2016 +"2016-05-08","Day of Victory over Fascism","SK",2016 +"2016-07-05","St. Cyril and Methodius Day","SK",2016 +"2016-08-29","Slovak National Uprising Anniversary","SK",2016 +"2016-09-01","Constitution Day","SK",2016 +"2016-09-15","Day of Our Lady of the Seven Sorrows","SK",2016 +"2016-11-01","All Saints' Day","SK",2016 +"2016-11-17","Struggle for Freedom and Democracy Day","SK",2016 +"2016-12-24","Christmas Eve","SK",2016 +"2016-12-25","Christmas Day","SK",2016 +"2016-12-26","Second Day of Christmas","SK",2016 +"2017-01-01","Day of the Establishment of the Slovak Republic","SK",2017 +"2017-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2017 +"2017-04-14","Good Friday","SK",2017 +"2017-04-17","Easter Monday","SK",2017 +"2017-05-01","Labor Day","SK",2017 +"2017-05-08","Day of Victory over Fascism","SK",2017 +"2017-07-05","St. Cyril and Methodius Day","SK",2017 +"2017-08-29","Slovak National Uprising Anniversary","SK",2017 +"2017-09-01","Constitution Day","SK",2017 +"2017-09-15","Day of Our Lady of the Seven Sorrows","SK",2017 +"2017-11-01","All Saints' Day","SK",2017 +"2017-11-17","Struggle for Freedom and Democracy Day","SK",2017 +"2017-12-24","Christmas Eve","SK",2017 +"2017-12-25","Christmas Day","SK",2017 +"2017-12-26","Second Day of Christmas","SK",2017 +"2018-01-01","Day of the Establishment of the Slovak Republic","SK",2018 +"2018-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2018 +"2018-03-30","Good Friday","SK",2018 +"2018-04-02","Easter Monday","SK",2018 +"2018-05-01","Labor Day","SK",2018 +"2018-05-08","Day of Victory over Fascism","SK",2018 +"2018-07-05","St. Cyril and Methodius Day","SK",2018 +"2018-08-29","Slovak National Uprising Anniversary","SK",2018 +"2018-09-01","Constitution Day","SK",2018 +"2018-09-15","Day of Our Lady of the Seven Sorrows","SK",2018 +"2018-10-30","100th anniversary of the adoption of the Declaration of the Slovak Nation","SK",2018 +"2018-11-01","All Saints' Day","SK",2018 +"2018-11-17","Struggle for Freedom and Democracy Day","SK",2018 +"2018-12-24","Christmas Eve","SK",2018 +"2018-12-25","Christmas Day","SK",2018 +"2018-12-26","Second Day of Christmas","SK",2018 +"2019-01-01","Day of the Establishment of the Slovak Republic","SK",2019 +"2019-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2019 +"2019-04-19","Good Friday","SK",2019 +"2019-04-22","Easter Monday","SK",2019 +"2019-05-01","Labor Day","SK",2019 +"2019-05-08","Day of Victory over Fascism","SK",2019 +"2019-07-05","St. Cyril and Methodius Day","SK",2019 +"2019-08-29","Slovak National Uprising Anniversary","SK",2019 +"2019-09-01","Constitution Day","SK",2019 +"2019-09-15","Day of Our Lady of the Seven Sorrows","SK",2019 +"2019-11-01","All Saints' Day","SK",2019 +"2019-11-17","Struggle for Freedom and Democracy Day","SK",2019 +"2019-12-24","Christmas Eve","SK",2019 +"2019-12-25","Christmas Day","SK",2019 +"2019-12-26","Second Day of Christmas","SK",2019 +"2020-01-01","Day of the Establishment of the Slovak Republic","SK",2020 +"2020-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2020 +"2020-04-10","Good Friday","SK",2020 +"2020-04-13","Easter Monday","SK",2020 +"2020-05-01","Labor Day","SK",2020 +"2020-05-08","Day of Victory over Fascism","SK",2020 +"2020-07-05","St. Cyril and Methodius Day","SK",2020 +"2020-08-29","Slovak National Uprising Anniversary","SK",2020 +"2020-09-01","Constitution Day","SK",2020 +"2020-09-15","Day of Our Lady of the Seven Sorrows","SK",2020 +"2020-11-01","All Saints' Day","SK",2020 +"2020-11-17","Struggle for Freedom and Democracy Day","SK",2020 +"2020-12-24","Christmas Eve","SK",2020 +"2020-12-25","Christmas Day","SK",2020 +"2020-12-26","Second Day of Christmas","SK",2020 +"2021-01-01","Day of the Establishment of the Slovak Republic","SK",2021 +"2021-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2021 +"2021-04-02","Good Friday","SK",2021 +"2021-04-05","Easter Monday","SK",2021 +"2021-05-01","Labor Day","SK",2021 +"2021-05-08","Day of Victory over Fascism","SK",2021 +"2021-07-05","St. Cyril and Methodius Day","SK",2021 +"2021-08-29","Slovak National Uprising Anniversary","SK",2021 +"2021-09-01","Constitution Day","SK",2021 +"2021-09-15","Day of Our Lady of the Seven Sorrows","SK",2021 +"2021-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2021 +"2021-11-01","All Saints' Day","SK",2021 +"2021-11-17","Struggle for Freedom and Democracy Day","SK",2021 +"2021-12-24","Christmas Eve","SK",2021 +"2021-12-25","Christmas Day","SK",2021 +"2021-12-26","Second Day of Christmas","SK",2021 +"2022-01-01","Day of the Establishment of the Slovak Republic","SK",2022 +"2022-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2022 +"2022-04-15","Good Friday","SK",2022 +"2022-04-18","Easter Monday","SK",2022 +"2022-05-01","Labor Day","SK",2022 +"2022-05-08","Day of Victory over Fascism","SK",2022 +"2022-07-05","St. Cyril and Methodius Day","SK",2022 +"2022-08-29","Slovak National Uprising Anniversary","SK",2022 +"2022-09-01","Constitution Day","SK",2022 +"2022-09-15","Day of Our Lady of the Seven Sorrows","SK",2022 +"2022-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2022 +"2022-11-01","All Saints' Day","SK",2022 +"2022-11-17","Struggle for Freedom and Democracy Day","SK",2022 +"2022-12-24","Christmas Eve","SK",2022 +"2022-12-25","Christmas Day","SK",2022 +"2022-12-26","Second Day of Christmas","SK",2022 +"2023-01-01","Day of the Establishment of the Slovak Republic","SK",2023 +"2023-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2023 +"2023-04-07","Good Friday","SK",2023 +"2023-04-10","Easter Monday","SK",2023 +"2023-05-01","Labor Day","SK",2023 +"2023-05-08","Day of Victory over Fascism","SK",2023 +"2023-07-05","St. Cyril and Methodius Day","SK",2023 +"2023-08-29","Slovak National Uprising Anniversary","SK",2023 +"2023-09-01","Constitution Day","SK",2023 +"2023-09-15","Day of Our Lady of the Seven Sorrows","SK",2023 +"2023-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2023 +"2023-11-01","All Saints' Day","SK",2023 +"2023-11-17","Struggle for Freedom and Democracy Day","SK",2023 +"2023-12-24","Christmas Eve","SK",2023 +"2023-12-25","Christmas Day","SK",2023 +"2023-12-26","Second Day of Christmas","SK",2023 +"2024-01-01","Day of the Establishment of the Slovak Republic","SK",2024 +"2024-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2024 +"2024-03-29","Good Friday","SK",2024 +"2024-04-01","Easter Monday","SK",2024 +"2024-05-01","Labor Day","SK",2024 +"2024-05-08","Day of Victory over Fascism","SK",2024 +"2024-07-05","St. Cyril and Methodius Day","SK",2024 +"2024-08-29","Slovak National Uprising Anniversary","SK",2024 +"2024-09-01","Constitution Day","SK",2024 +"2024-09-15","Day of Our Lady of the Seven Sorrows","SK",2024 +"2024-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2024 +"2024-11-01","All Saints' Day","SK",2024 +"2024-11-17","Struggle for Freedom and Democracy Day","SK",2024 +"2024-12-24","Christmas Eve","SK",2024 +"2024-12-25","Christmas Day","SK",2024 +"2024-12-26","Second Day of Christmas","SK",2024 +"2025-01-01","Day of the Establishment of the Slovak Republic","SK",2025 +"2025-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2025 +"2025-04-18","Good Friday","SK",2025 +"2025-04-21","Easter Monday","SK",2025 +"2025-05-01","Labor Day","SK",2025 +"2025-05-08","Day of Victory over Fascism","SK",2025 +"2025-07-05","St. Cyril and Methodius Day","SK",2025 +"2025-08-29","Slovak National Uprising Anniversary","SK",2025 +"2025-09-01","Constitution Day","SK",2025 +"2025-09-15","Day of Our Lady of the Seven Sorrows","SK",2025 +"2025-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2025 +"2025-11-01","All Saints' Day","SK",2025 +"2025-11-17","Struggle for Freedom and Democracy Day","SK",2025 +"2025-12-24","Christmas Eve","SK",2025 +"2025-12-25","Christmas Day","SK",2025 +"2025-12-26","Second Day of Christmas","SK",2025 +"2026-01-01","Day of the Establishment of the Slovak Republic","SK",2026 +"2026-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2026 +"2026-04-03","Good Friday","SK",2026 +"2026-04-06","Easter Monday","SK",2026 +"2026-05-01","Labor Day","SK",2026 +"2026-05-08","Day of Victory over Fascism","SK",2026 +"2026-07-05","St. Cyril and Methodius Day","SK",2026 +"2026-08-29","Slovak National Uprising Anniversary","SK",2026 +"2026-09-01","Constitution Day","SK",2026 +"2026-09-15","Day of Our Lady of the Seven Sorrows","SK",2026 +"2026-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2026 +"2026-11-01","All Saints' Day","SK",2026 +"2026-11-17","Struggle for Freedom and Democracy Day","SK",2026 +"2026-12-24","Christmas Eve","SK",2026 +"2026-12-25","Christmas Day","SK",2026 +"2026-12-26","Second Day of Christmas","SK",2026 +"2027-01-01","Day of the Establishment of the Slovak Republic","SK",2027 +"2027-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2027 +"2027-03-26","Good Friday","SK",2027 +"2027-03-29","Easter Monday","SK",2027 +"2027-05-01","Labor Day","SK",2027 +"2027-05-08","Day of Victory over Fascism","SK",2027 +"2027-07-05","St. Cyril and Methodius Day","SK",2027 +"2027-08-29","Slovak National Uprising Anniversary","SK",2027 +"2027-09-01","Constitution Day","SK",2027 +"2027-09-15","Day of Our Lady of the Seven Sorrows","SK",2027 +"2027-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2027 +"2027-11-01","All Saints' Day","SK",2027 +"2027-11-17","Struggle for Freedom and Democracy Day","SK",2027 +"2027-12-24","Christmas Eve","SK",2027 +"2027-12-25","Christmas Day","SK",2027 +"2027-12-26","Second Day of Christmas","SK",2027 +"2028-01-01","Day of the Establishment of the Slovak Republic","SK",2028 +"2028-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2028 +"2028-04-14","Good Friday","SK",2028 +"2028-04-17","Easter Monday","SK",2028 +"2028-05-01","Labor Day","SK",2028 +"2028-05-08","Day of Victory over Fascism","SK",2028 +"2028-07-05","St. Cyril and Methodius Day","SK",2028 +"2028-08-29","Slovak National Uprising Anniversary","SK",2028 +"2028-09-01","Constitution Day","SK",2028 +"2028-09-15","Day of Our Lady of the Seven Sorrows","SK",2028 +"2028-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2028 +"2028-11-01","All Saints' Day","SK",2028 +"2028-11-17","Struggle for Freedom and Democracy Day","SK",2028 +"2028-12-24","Christmas Eve","SK",2028 +"2028-12-25","Christmas Day","SK",2028 +"2028-12-26","Second Day of Christmas","SK",2028 +"2029-01-01","Day of the Establishment of the Slovak Republic","SK",2029 +"2029-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2029 +"2029-03-30","Good Friday","SK",2029 +"2029-04-02","Easter Monday","SK",2029 +"2029-05-01","Labor Day","SK",2029 +"2029-05-08","Day of Victory over Fascism","SK",2029 +"2029-07-05","St. Cyril and Methodius Day","SK",2029 +"2029-08-29","Slovak National Uprising Anniversary","SK",2029 +"2029-09-01","Constitution Day","SK",2029 +"2029-09-15","Day of Our Lady of the Seven Sorrows","SK",2029 +"2029-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2029 +"2029-11-01","All Saints' Day","SK",2029 +"2029-11-17","Struggle for Freedom and Democracy Day","SK",2029 +"2029-12-24","Christmas Eve","SK",2029 +"2029-12-25","Christmas Day","SK",2029 +"2029-12-26","Second Day of Christmas","SK",2029 +"2030-01-01","Day of the Establishment of the Slovak Republic","SK",2030 +"2030-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2030 +"2030-04-19","Good Friday","SK",2030 +"2030-04-22","Easter Monday","SK",2030 +"2030-05-01","Labor Day","SK",2030 +"2030-05-08","Day of Victory over Fascism","SK",2030 +"2030-07-05","St. Cyril and Methodius Day","SK",2030 +"2030-08-29","Slovak National Uprising Anniversary","SK",2030 +"2030-09-01","Constitution Day","SK",2030 +"2030-09-15","Day of Our Lady of the Seven Sorrows","SK",2030 +"2030-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2030 +"2030-11-01","All Saints' Day","SK",2030 +"2030-11-17","Struggle for Freedom and Democracy Day","SK",2030 +"2030-12-24","Christmas Eve","SK",2030 +"2030-12-25","Christmas Day","SK",2030 +"2030-12-26","Second Day of Christmas","SK",2030 +"2031-01-01","Day of the Establishment of the Slovak Republic","SK",2031 +"2031-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2031 +"2031-04-11","Good Friday","SK",2031 +"2031-04-14","Easter Monday","SK",2031 +"2031-05-01","Labor Day","SK",2031 +"2031-05-08","Day of Victory over Fascism","SK",2031 +"2031-07-05","St. Cyril and Methodius Day","SK",2031 +"2031-08-29","Slovak National Uprising Anniversary","SK",2031 +"2031-09-01","Constitution Day","SK",2031 +"2031-09-15","Day of Our Lady of the Seven Sorrows","SK",2031 +"2031-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2031 +"2031-11-01","All Saints' Day","SK",2031 +"2031-11-17","Struggle for Freedom and Democracy Day","SK",2031 +"2031-12-24","Christmas Eve","SK",2031 +"2031-12-25","Christmas Day","SK",2031 +"2031-12-26","Second Day of Christmas","SK",2031 +"2032-01-01","Day of the Establishment of the Slovak Republic","SK",2032 +"2032-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2032 +"2032-03-26","Good Friday","SK",2032 +"2032-03-29","Easter Monday","SK",2032 +"2032-05-01","Labor Day","SK",2032 +"2032-05-08","Day of Victory over Fascism","SK",2032 +"2032-07-05","St. Cyril and Methodius Day","SK",2032 +"2032-08-29","Slovak National Uprising Anniversary","SK",2032 +"2032-09-01","Constitution Day","SK",2032 +"2032-09-15","Day of Our Lady of the Seven Sorrows","SK",2032 +"2032-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2032 +"2032-11-01","All Saints' Day","SK",2032 +"2032-11-17","Struggle for Freedom and Democracy Day","SK",2032 +"2032-12-24","Christmas Eve","SK",2032 +"2032-12-25","Christmas Day","SK",2032 +"2032-12-26","Second Day of Christmas","SK",2032 +"2033-01-01","Day of the Establishment of the Slovak Republic","SK",2033 +"2033-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2033 +"2033-04-15","Good Friday","SK",2033 +"2033-04-18","Easter Monday","SK",2033 +"2033-05-01","Labor Day","SK",2033 +"2033-05-08","Day of Victory over Fascism","SK",2033 +"2033-07-05","St. Cyril and Methodius Day","SK",2033 +"2033-08-29","Slovak National Uprising Anniversary","SK",2033 +"2033-09-01","Constitution Day","SK",2033 +"2033-09-15","Day of Our Lady of the Seven Sorrows","SK",2033 +"2033-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2033 +"2033-11-01","All Saints' Day","SK",2033 +"2033-11-17","Struggle for Freedom and Democracy Day","SK",2033 +"2033-12-24","Christmas Eve","SK",2033 +"2033-12-25","Christmas Day","SK",2033 +"2033-12-26","Second Day of Christmas","SK",2033 +"2034-01-01","Day of the Establishment of the Slovak Republic","SK",2034 +"2034-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2034 +"2034-04-07","Good Friday","SK",2034 +"2034-04-10","Easter Monday","SK",2034 +"2034-05-01","Labor Day","SK",2034 +"2034-05-08","Day of Victory over Fascism","SK",2034 +"2034-07-05","St. Cyril and Methodius Day","SK",2034 +"2034-08-29","Slovak National Uprising Anniversary","SK",2034 +"2034-09-01","Constitution Day","SK",2034 +"2034-09-15","Day of Our Lady of the Seven Sorrows","SK",2034 +"2034-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2034 +"2034-11-01","All Saints' Day","SK",2034 +"2034-11-17","Struggle for Freedom and Democracy Day","SK",2034 +"2034-12-24","Christmas Eve","SK",2034 +"2034-12-25","Christmas Day","SK",2034 +"2034-12-26","Second Day of Christmas","SK",2034 +"2035-01-01","Day of the Establishment of the Slovak Republic","SK",2035 +"2035-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2035 +"2035-03-23","Good Friday","SK",2035 +"2035-03-26","Easter Monday","SK",2035 +"2035-05-01","Labor Day","SK",2035 +"2035-05-08","Day of Victory over Fascism","SK",2035 +"2035-07-05","St. Cyril and Methodius Day","SK",2035 +"2035-08-29","Slovak National Uprising Anniversary","SK",2035 +"2035-09-01","Constitution Day","SK",2035 +"2035-09-15","Day of Our Lady of the Seven Sorrows","SK",2035 +"2035-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2035 +"2035-11-01","All Saints' Day","SK",2035 +"2035-11-17","Struggle for Freedom and Democracy Day","SK",2035 +"2035-12-24","Christmas Eve","SK",2035 +"2035-12-25","Christmas Day","SK",2035 +"2035-12-26","Second Day of Christmas","SK",2035 +"2036-01-01","Day of the Establishment of the Slovak Republic","SK",2036 +"2036-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2036 +"2036-04-11","Good Friday","SK",2036 +"2036-04-14","Easter Monday","SK",2036 +"2036-05-01","Labor Day","SK",2036 +"2036-05-08","Day of Victory over Fascism","SK",2036 +"2036-07-05","St. Cyril and Methodius Day","SK",2036 +"2036-08-29","Slovak National Uprising Anniversary","SK",2036 +"2036-09-01","Constitution Day","SK",2036 +"2036-09-15","Day of Our Lady of the Seven Sorrows","SK",2036 +"2036-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2036 +"2036-11-01","All Saints' Day","SK",2036 +"2036-11-17","Struggle for Freedom and Democracy Day","SK",2036 +"2036-12-24","Christmas Eve","SK",2036 +"2036-12-25","Christmas Day","SK",2036 +"2036-12-26","Second Day of Christmas","SK",2036 +"2037-01-01","Day of the Establishment of the Slovak Republic","SK",2037 +"2037-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2037 +"2037-04-03","Good Friday","SK",2037 +"2037-04-06","Easter Monday","SK",2037 +"2037-05-01","Labor Day","SK",2037 +"2037-05-08","Day of Victory over Fascism","SK",2037 +"2037-07-05","St. Cyril and Methodius Day","SK",2037 +"2037-08-29","Slovak National Uprising Anniversary","SK",2037 +"2037-09-01","Constitution Day","SK",2037 +"2037-09-15","Day of Our Lady of the Seven Sorrows","SK",2037 +"2037-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2037 +"2037-11-01","All Saints' Day","SK",2037 +"2037-11-17","Struggle for Freedom and Democracy Day","SK",2037 +"2037-12-24","Christmas Eve","SK",2037 +"2037-12-25","Christmas Day","SK",2037 +"2037-12-26","Second Day of Christmas","SK",2037 +"2038-01-01","Day of the Establishment of the Slovak Republic","SK",2038 +"2038-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2038 +"2038-04-23","Good Friday","SK",2038 +"2038-04-26","Easter Monday","SK",2038 +"2038-05-01","Labor Day","SK",2038 +"2038-05-08","Day of Victory over Fascism","SK",2038 +"2038-07-05","St. Cyril and Methodius Day","SK",2038 +"2038-08-29","Slovak National Uprising Anniversary","SK",2038 +"2038-09-01","Constitution Day","SK",2038 +"2038-09-15","Day of Our Lady of the Seven Sorrows","SK",2038 +"2038-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2038 +"2038-11-01","All Saints' Day","SK",2038 +"2038-11-17","Struggle for Freedom and Democracy Day","SK",2038 +"2038-12-24","Christmas Eve","SK",2038 +"2038-12-25","Christmas Day","SK",2038 +"2038-12-26","Second Day of Christmas","SK",2038 +"2039-01-01","Day of the Establishment of the Slovak Republic","SK",2039 +"2039-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2039 +"2039-04-08","Good Friday","SK",2039 +"2039-04-11","Easter Monday","SK",2039 +"2039-05-01","Labor Day","SK",2039 +"2039-05-08","Day of Victory over Fascism","SK",2039 +"2039-07-05","St. Cyril and Methodius Day","SK",2039 +"2039-08-29","Slovak National Uprising Anniversary","SK",2039 +"2039-09-01","Constitution Day","SK",2039 +"2039-09-15","Day of Our Lady of the Seven Sorrows","SK",2039 +"2039-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2039 +"2039-11-01","All Saints' Day","SK",2039 +"2039-11-17","Struggle for Freedom and Democracy Day","SK",2039 +"2039-12-24","Christmas Eve","SK",2039 +"2039-12-25","Christmas Day","SK",2039 +"2039-12-26","Second Day of Christmas","SK",2039 +"2040-01-01","Day of the Establishment of the Slovak Republic","SK",2040 +"2040-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2040 +"2040-03-30","Good Friday","SK",2040 +"2040-04-02","Easter Monday","SK",2040 +"2040-05-01","Labor Day","SK",2040 +"2040-05-08","Day of Victory over Fascism","SK",2040 +"2040-07-05","St. Cyril and Methodius Day","SK",2040 +"2040-08-29","Slovak National Uprising Anniversary","SK",2040 +"2040-09-01","Constitution Day","SK",2040 +"2040-09-15","Day of Our Lady of the Seven Sorrows","SK",2040 +"2040-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2040 +"2040-11-01","All Saints' Day","SK",2040 +"2040-11-17","Struggle for Freedom and Democracy Day","SK",2040 +"2040-12-24","Christmas Eve","SK",2040 +"2040-12-25","Christmas Day","SK",2040 +"2040-12-26","Second Day of Christmas","SK",2040 +"2041-01-01","Day of the Establishment of the Slovak Republic","SK",2041 +"2041-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2041 +"2041-04-19","Good Friday","SK",2041 +"2041-04-22","Easter Monday","SK",2041 +"2041-05-01","Labor Day","SK",2041 +"2041-05-08","Day of Victory over Fascism","SK",2041 +"2041-07-05","St. Cyril and Methodius Day","SK",2041 +"2041-08-29","Slovak National Uprising Anniversary","SK",2041 +"2041-09-01","Constitution Day","SK",2041 +"2041-09-15","Day of Our Lady of the Seven Sorrows","SK",2041 +"2041-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2041 +"2041-11-01","All Saints' Day","SK",2041 +"2041-11-17","Struggle for Freedom and Democracy Day","SK",2041 +"2041-12-24","Christmas Eve","SK",2041 +"2041-12-25","Christmas Day","SK",2041 +"2041-12-26","Second Day of Christmas","SK",2041 +"2042-01-01","Day of the Establishment of the Slovak Republic","SK",2042 +"2042-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2042 +"2042-04-04","Good Friday","SK",2042 +"2042-04-07","Easter Monday","SK",2042 +"2042-05-01","Labor Day","SK",2042 +"2042-05-08","Day of Victory over Fascism","SK",2042 +"2042-07-05","St. Cyril and Methodius Day","SK",2042 +"2042-08-29","Slovak National Uprising Anniversary","SK",2042 +"2042-09-01","Constitution Day","SK",2042 +"2042-09-15","Day of Our Lady of the Seven Sorrows","SK",2042 +"2042-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2042 +"2042-11-01","All Saints' Day","SK",2042 +"2042-11-17","Struggle for Freedom and Democracy Day","SK",2042 +"2042-12-24","Christmas Eve","SK",2042 +"2042-12-25","Christmas Day","SK",2042 +"2042-12-26","Second Day of Christmas","SK",2042 +"2043-01-01","Day of the Establishment of the Slovak Republic","SK",2043 +"2043-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2043 +"2043-03-27","Good Friday","SK",2043 +"2043-03-30","Easter Monday","SK",2043 +"2043-05-01","Labor Day","SK",2043 +"2043-05-08","Day of Victory over Fascism","SK",2043 +"2043-07-05","St. Cyril and Methodius Day","SK",2043 +"2043-08-29","Slovak National Uprising Anniversary","SK",2043 +"2043-09-01","Constitution Day","SK",2043 +"2043-09-15","Day of Our Lady of the Seven Sorrows","SK",2043 +"2043-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2043 +"2043-11-01","All Saints' Day","SK",2043 +"2043-11-17","Struggle for Freedom and Democracy Day","SK",2043 +"2043-12-24","Christmas Eve","SK",2043 +"2043-12-25","Christmas Day","SK",2043 +"2043-12-26","Second Day of Christmas","SK",2043 +"2044-01-01","Day of the Establishment of the Slovak Republic","SK",2044 +"2044-01-06","Epiphany (Three Kings' Day and Orthodox Christmas)","SK",2044 +"2044-04-15","Good Friday","SK",2044 +"2044-04-18","Easter Monday","SK",2044 +"2044-05-01","Labor Day","SK",2044 +"2044-05-08","Day of Victory over Fascism","SK",2044 +"2044-07-05","St. Cyril and Methodius Day","SK",2044 +"2044-08-29","Slovak National Uprising Anniversary","SK",2044 +"2044-09-01","Constitution Day","SK",2044 +"2044-09-15","Day of Our Lady of the Seven Sorrows","SK",2044 +"2044-10-28","Day of the Establishment of the Independent Czech-Slovak State","SK",2044 +"2044-11-01","All Saints' Day","SK",2044 +"2044-11-17","Struggle for Freedom and Democracy Day","SK",2044 +"2044-12-24","Christmas Eve","SK",2044 +"2044-12-25","Christmas Day","SK",2044 +"2044-12-26","Second Day of Christmas","SK",2044 +"1995-01-01","New Year's Day","SM",1995 +"1995-01-06","Epiphany","SM",1995 +"1995-02-05","Feast of Saint Agatha","SM",1995 +"1995-03-25","Anniversary of the Arengo","SM",1995 +"1995-04-16","Easter Sunday","SM",1995 +"1995-04-17","Easter Monday","SM",1995 +"1995-05-01","Labour Day","SM",1995 +"1995-06-15","Corpus Cristi","SM",1995 +"1995-07-28","Liberation from Fascism Day","SM",1995 +"1995-08-15","Assumption Day","SM",1995 +"1995-09-03","Foundation Day","SM",1995 +"1995-11-01","All Saints' Day","SM",1995 +"1995-11-02","Commemoration of the Dead","SM",1995 +"1995-12-08","Immaculate Conception Day","SM",1995 +"1995-12-24","Christmas Eve","SM",1995 +"1995-12-25","Christmas Day","SM",1995 +"1995-12-26","Saint Stephen's Day","SM",1995 +"1995-12-31","New Year's Eve","SM",1995 +"1996-01-01","New Year's Day","SM",1996 +"1996-01-06","Epiphany","SM",1996 +"1996-02-05","Feast of Saint Agatha","SM",1996 +"1996-03-25","Anniversary of the Arengo","SM",1996 +"1996-04-07","Easter Sunday","SM",1996 +"1996-04-08","Easter Monday","SM",1996 +"1996-05-01","Labour Day","SM",1996 +"1996-06-06","Corpus Cristi","SM",1996 +"1996-07-28","Liberation from Fascism Day","SM",1996 +"1996-08-15","Assumption Day","SM",1996 +"1996-09-03","Foundation Day","SM",1996 +"1996-11-01","All Saints' Day","SM",1996 +"1996-11-02","Commemoration of the Dead","SM",1996 +"1996-12-08","Immaculate Conception Day","SM",1996 +"1996-12-24","Christmas Eve","SM",1996 +"1996-12-25","Christmas Day","SM",1996 +"1996-12-26","Saint Stephen's Day","SM",1996 +"1996-12-31","New Year's Eve","SM",1996 +"1997-01-01","New Year's Day","SM",1997 +"1997-01-06","Epiphany","SM",1997 +"1997-02-05","Feast of Saint Agatha","SM",1997 +"1997-03-25","Anniversary of the Arengo","SM",1997 +"1997-03-30","Easter Sunday","SM",1997 +"1997-03-31","Easter Monday","SM",1997 +"1997-05-01","Labour Day","SM",1997 +"1997-05-29","Corpus Cristi","SM",1997 +"1997-07-28","Liberation from Fascism Day","SM",1997 +"1997-08-15","Assumption Day","SM",1997 +"1997-09-03","Foundation Day","SM",1997 +"1997-11-01","All Saints' Day","SM",1997 +"1997-11-02","Commemoration of the Dead","SM",1997 +"1997-12-08","Immaculate Conception Day","SM",1997 +"1997-12-24","Christmas Eve","SM",1997 +"1997-12-25","Christmas Day","SM",1997 +"1997-12-26","Saint Stephen's Day","SM",1997 +"1997-12-31","New Year's Eve","SM",1997 +"1998-01-01","New Year's Day","SM",1998 +"1998-01-06","Epiphany","SM",1998 +"1998-02-05","Feast of Saint Agatha","SM",1998 +"1998-03-25","Anniversary of the Arengo","SM",1998 +"1998-04-12","Easter Sunday","SM",1998 +"1998-04-13","Easter Monday","SM",1998 +"1998-05-01","Labour Day","SM",1998 +"1998-06-11","Corpus Cristi","SM",1998 +"1998-07-28","Liberation from Fascism Day","SM",1998 +"1998-08-15","Assumption Day","SM",1998 +"1998-09-03","Foundation Day","SM",1998 +"1998-11-01","All Saints' Day","SM",1998 +"1998-11-02","Commemoration of the Dead","SM",1998 +"1998-12-08","Immaculate Conception Day","SM",1998 +"1998-12-24","Christmas Eve","SM",1998 +"1998-12-25","Christmas Day","SM",1998 +"1998-12-26","Saint Stephen's Day","SM",1998 +"1998-12-31","New Year's Eve","SM",1998 +"1999-01-01","New Year's Day","SM",1999 +"1999-01-06","Epiphany","SM",1999 +"1999-02-05","Feast of Saint Agatha","SM",1999 +"1999-03-25","Anniversary of the Arengo","SM",1999 +"1999-04-04","Easter Sunday","SM",1999 +"1999-04-05","Easter Monday","SM",1999 +"1999-05-01","Labour Day","SM",1999 +"1999-06-03","Corpus Cristi","SM",1999 +"1999-07-28","Liberation from Fascism Day","SM",1999 +"1999-08-15","Assumption Day","SM",1999 +"1999-09-03","Foundation Day","SM",1999 +"1999-11-01","All Saints' Day","SM",1999 +"1999-11-02","Commemoration of the Dead","SM",1999 +"1999-12-08","Immaculate Conception Day","SM",1999 +"1999-12-24","Christmas Eve","SM",1999 +"1999-12-25","Christmas Day","SM",1999 +"1999-12-26","Saint Stephen's Day","SM",1999 +"1999-12-31","New Year's Eve","SM",1999 +"2000-01-01","New Year's Day","SM",2000 +"2000-01-06","Epiphany","SM",2000 +"2000-02-05","Feast of Saint Agatha","SM",2000 +"2000-03-25","Anniversary of the Arengo","SM",2000 +"2000-04-23","Easter Sunday","SM",2000 +"2000-04-24","Easter Monday","SM",2000 +"2000-05-01","Labour Day","SM",2000 +"2000-06-22","Corpus Cristi","SM",2000 +"2000-07-28","Liberation from Fascism Day","SM",2000 +"2000-08-15","Assumption Day","SM",2000 +"2000-09-03","Foundation Day","SM",2000 +"2000-11-01","All Saints' Day","SM",2000 +"2000-11-02","Commemoration of the Dead","SM",2000 +"2000-12-08","Immaculate Conception Day","SM",2000 +"2000-12-24","Christmas Eve","SM",2000 +"2000-12-25","Christmas Day","SM",2000 +"2000-12-26","Saint Stephen's Day","SM",2000 +"2000-12-31","New Year's Eve","SM",2000 +"2001-01-01","New Year's Day","SM",2001 +"2001-01-06","Epiphany","SM",2001 +"2001-02-05","Feast of Saint Agatha","SM",2001 +"2001-03-25","Anniversary of the Arengo","SM",2001 +"2001-04-15","Easter Sunday","SM",2001 +"2001-04-16","Easter Monday","SM",2001 +"2001-05-01","Labour Day","SM",2001 +"2001-06-14","Corpus Cristi","SM",2001 +"2001-07-28","Liberation from Fascism Day","SM",2001 +"2001-08-15","Assumption Day","SM",2001 +"2001-09-03","Foundation Day","SM",2001 +"2001-11-01","All Saints' Day","SM",2001 +"2001-11-02","Commemoration of the Dead","SM",2001 +"2001-12-08","Immaculate Conception Day","SM",2001 +"2001-12-24","Christmas Eve","SM",2001 +"2001-12-25","Christmas Day","SM",2001 +"2001-12-26","Saint Stephen's Day","SM",2001 +"2001-12-31","New Year's Eve","SM",2001 +"2002-01-01","New Year's Day","SM",2002 +"2002-01-06","Epiphany","SM",2002 +"2002-02-05","Feast of Saint Agatha","SM",2002 +"2002-03-25","Anniversary of the Arengo","SM",2002 +"2002-03-31","Easter Sunday","SM",2002 +"2002-04-01","Easter Monday","SM",2002 +"2002-05-01","Labour Day","SM",2002 +"2002-05-30","Corpus Cristi","SM",2002 +"2002-07-28","Liberation from Fascism Day","SM",2002 +"2002-08-15","Assumption Day","SM",2002 +"2002-09-03","Foundation Day","SM",2002 +"2002-11-01","All Saints' Day","SM",2002 +"2002-11-02","Commemoration of the Dead","SM",2002 +"2002-12-08","Immaculate Conception Day","SM",2002 +"2002-12-24","Christmas Eve","SM",2002 +"2002-12-25","Christmas Day","SM",2002 +"2002-12-26","Saint Stephen's Day","SM",2002 +"2002-12-31","New Year's Eve","SM",2002 +"2003-01-01","New Year's Day","SM",2003 +"2003-01-06","Epiphany","SM",2003 +"2003-02-05","Feast of Saint Agatha","SM",2003 +"2003-03-25","Anniversary of the Arengo","SM",2003 +"2003-04-20","Easter Sunday","SM",2003 +"2003-04-21","Easter Monday","SM",2003 +"2003-05-01","Labour Day","SM",2003 +"2003-06-19","Corpus Cristi","SM",2003 +"2003-07-28","Liberation from Fascism Day","SM",2003 +"2003-08-15","Assumption Day","SM",2003 +"2003-09-03","Foundation Day","SM",2003 +"2003-11-01","All Saints' Day","SM",2003 +"2003-11-02","Commemoration of the Dead","SM",2003 +"2003-12-08","Immaculate Conception Day","SM",2003 +"2003-12-24","Christmas Eve","SM",2003 +"2003-12-25","Christmas Day","SM",2003 +"2003-12-26","Saint Stephen's Day","SM",2003 +"2003-12-31","New Year's Eve","SM",2003 +"2004-01-01","New Year's Day","SM",2004 +"2004-01-06","Epiphany","SM",2004 +"2004-02-05","Feast of Saint Agatha","SM",2004 +"2004-03-25","Anniversary of the Arengo","SM",2004 +"2004-04-11","Easter Sunday","SM",2004 +"2004-04-12","Easter Monday","SM",2004 +"2004-05-01","Labour Day","SM",2004 +"2004-06-10","Corpus Cristi","SM",2004 +"2004-07-28","Liberation from Fascism Day","SM",2004 +"2004-08-15","Assumption Day","SM",2004 +"2004-09-03","Foundation Day","SM",2004 +"2004-11-01","All Saints' Day","SM",2004 +"2004-11-02","Commemoration of the Dead","SM",2004 +"2004-12-08","Immaculate Conception Day","SM",2004 +"2004-12-24","Christmas Eve","SM",2004 +"2004-12-25","Christmas Day","SM",2004 +"2004-12-26","Saint Stephen's Day","SM",2004 +"2004-12-31","New Year's Eve","SM",2004 +"2005-01-01","New Year's Day","SM",2005 +"2005-01-06","Epiphany","SM",2005 +"2005-02-05","Feast of Saint Agatha","SM",2005 +"2005-03-25","Anniversary of the Arengo","SM",2005 +"2005-03-27","Easter Sunday","SM",2005 +"2005-03-28","Easter Monday","SM",2005 +"2005-05-01","Labour Day","SM",2005 +"2005-05-26","Corpus Cristi","SM",2005 +"2005-07-28","Liberation from Fascism Day","SM",2005 +"2005-08-15","Assumption Day","SM",2005 +"2005-09-03","Foundation Day","SM",2005 +"2005-11-01","All Saints' Day","SM",2005 +"2005-11-02","Commemoration of the Dead","SM",2005 +"2005-12-08","Immaculate Conception Day","SM",2005 +"2005-12-24","Christmas Eve","SM",2005 +"2005-12-25","Christmas Day","SM",2005 +"2005-12-26","Saint Stephen's Day","SM",2005 +"2005-12-31","New Year's Eve","SM",2005 +"2006-01-01","New Year's Day","SM",2006 +"2006-01-06","Epiphany","SM",2006 +"2006-02-05","Feast of Saint Agatha","SM",2006 +"2006-03-25","Anniversary of the Arengo","SM",2006 +"2006-04-16","Easter Sunday","SM",2006 +"2006-04-17","Easter Monday","SM",2006 +"2006-05-01","Labour Day","SM",2006 +"2006-06-15","Corpus Cristi","SM",2006 +"2006-07-28","Liberation from Fascism Day","SM",2006 +"2006-08-15","Assumption Day","SM",2006 +"2006-09-03","Foundation Day","SM",2006 +"2006-11-01","All Saints' Day","SM",2006 +"2006-11-02","Commemoration of the Dead","SM",2006 +"2006-12-08","Immaculate Conception Day","SM",2006 +"2006-12-24","Christmas Eve","SM",2006 +"2006-12-25","Christmas Day","SM",2006 +"2006-12-26","Saint Stephen's Day","SM",2006 +"2006-12-31","New Year's Eve","SM",2006 +"2007-01-01","New Year's Day","SM",2007 +"2007-01-06","Epiphany","SM",2007 +"2007-02-05","Feast of Saint Agatha","SM",2007 +"2007-03-25","Anniversary of the Arengo","SM",2007 +"2007-04-08","Easter Sunday","SM",2007 +"2007-04-09","Easter Monday","SM",2007 +"2007-05-01","Labour Day","SM",2007 +"2007-06-07","Corpus Cristi","SM",2007 +"2007-07-28","Liberation from Fascism Day","SM",2007 +"2007-08-15","Assumption Day","SM",2007 +"2007-09-03","Foundation Day","SM",2007 +"2007-11-01","All Saints' Day","SM",2007 +"2007-11-02","Commemoration of the Dead","SM",2007 +"2007-12-08","Immaculate Conception Day","SM",2007 +"2007-12-24","Christmas Eve","SM",2007 +"2007-12-25","Christmas Day","SM",2007 +"2007-12-26","Saint Stephen's Day","SM",2007 +"2007-12-31","New Year's Eve","SM",2007 +"2008-01-01","New Year's Day","SM",2008 +"2008-01-06","Epiphany","SM",2008 +"2008-02-05","Feast of Saint Agatha","SM",2008 +"2008-03-23","Easter Sunday","SM",2008 +"2008-03-24","Easter Monday","SM",2008 +"2008-03-25","Anniversary of the Arengo","SM",2008 +"2008-05-01","Labour Day","SM",2008 +"2008-05-22","Corpus Cristi","SM",2008 +"2008-07-28","Liberation from Fascism Day","SM",2008 +"2008-08-15","Assumption Day","SM",2008 +"2008-09-03","Foundation Day","SM",2008 +"2008-11-01","All Saints' Day","SM",2008 +"2008-11-02","Commemoration of the Dead","SM",2008 +"2008-12-08","Immaculate Conception Day","SM",2008 +"2008-12-24","Christmas Eve","SM",2008 +"2008-12-25","Christmas Day","SM",2008 +"2008-12-26","Saint Stephen's Day","SM",2008 +"2008-12-31","New Year's Eve","SM",2008 +"2009-01-01","New Year's Day","SM",2009 +"2009-01-06","Epiphany","SM",2009 +"2009-02-05","Feast of Saint Agatha","SM",2009 +"2009-03-25","Anniversary of the Arengo","SM",2009 +"2009-04-12","Easter Sunday","SM",2009 +"2009-04-13","Easter Monday","SM",2009 +"2009-05-01","Labour Day","SM",2009 +"2009-06-11","Corpus Cristi","SM",2009 +"2009-07-28","Liberation from Fascism Day","SM",2009 +"2009-08-15","Assumption Day","SM",2009 +"2009-09-03","Foundation Day","SM",2009 +"2009-11-01","All Saints' Day","SM",2009 +"2009-11-02","Commemoration of the Dead","SM",2009 +"2009-12-08","Immaculate Conception Day","SM",2009 +"2009-12-24","Christmas Eve","SM",2009 +"2009-12-25","Christmas Day","SM",2009 +"2009-12-26","Saint Stephen's Day","SM",2009 +"2009-12-31","New Year's Eve","SM",2009 +"2010-01-01","New Year's Day","SM",2010 +"2010-01-06","Epiphany","SM",2010 +"2010-02-05","Feast of Saint Agatha","SM",2010 +"2010-03-25","Anniversary of the Arengo","SM",2010 +"2010-04-04","Easter Sunday","SM",2010 +"2010-04-05","Easter Monday","SM",2010 +"2010-05-01","Labour Day","SM",2010 +"2010-06-03","Corpus Cristi","SM",2010 +"2010-07-28","Liberation from Fascism Day","SM",2010 +"2010-08-15","Assumption Day","SM",2010 +"2010-09-03","Foundation Day","SM",2010 +"2010-11-01","All Saints' Day","SM",2010 +"2010-11-02","Commemoration of the Dead","SM",2010 +"2010-12-08","Immaculate Conception Day","SM",2010 +"2010-12-24","Christmas Eve","SM",2010 +"2010-12-25","Christmas Day","SM",2010 +"2010-12-26","Saint Stephen's Day","SM",2010 +"2010-12-31","New Year's Eve","SM",2010 +"2011-01-01","New Year's Day","SM",2011 +"2011-01-06","Epiphany","SM",2011 +"2011-02-05","Feast of Saint Agatha","SM",2011 +"2011-03-25","Anniversary of the Arengo","SM",2011 +"2011-04-24","Easter Sunday","SM",2011 +"2011-04-25","Easter Monday","SM",2011 +"2011-05-01","Labour Day","SM",2011 +"2011-06-23","Corpus Cristi","SM",2011 +"2011-07-28","Liberation from Fascism Day","SM",2011 +"2011-08-15","Assumption Day","SM",2011 +"2011-09-03","Foundation Day","SM",2011 +"2011-11-01","All Saints' Day","SM",2011 +"2011-11-02","Commemoration of the Dead","SM",2011 +"2011-12-08","Immaculate Conception Day","SM",2011 +"2011-12-24","Christmas Eve","SM",2011 +"2011-12-25","Christmas Day","SM",2011 +"2011-12-26","Saint Stephen's Day","SM",2011 +"2011-12-31","New Year's Eve","SM",2011 +"2012-01-01","New Year's Day","SM",2012 +"2012-01-06","Epiphany","SM",2012 +"2012-02-05","Feast of Saint Agatha","SM",2012 +"2012-03-25","Anniversary of the Arengo","SM",2012 +"2012-04-08","Easter Sunday","SM",2012 +"2012-04-09","Easter Monday","SM",2012 +"2012-05-01","Labour Day","SM",2012 +"2012-06-07","Corpus Cristi","SM",2012 +"2012-07-28","Liberation from Fascism Day","SM",2012 +"2012-08-15","Assumption Day","SM",2012 +"2012-09-03","Foundation Day","SM",2012 +"2012-11-01","All Saints' Day","SM",2012 +"2012-11-02","Commemoration of the Dead","SM",2012 +"2012-12-08","Immaculate Conception Day","SM",2012 +"2012-12-24","Christmas Eve","SM",2012 +"2012-12-25","Christmas Day","SM",2012 +"2012-12-26","Saint Stephen's Day","SM",2012 +"2012-12-31","New Year's Eve","SM",2012 +"2013-01-01","New Year's Day","SM",2013 +"2013-01-06","Epiphany","SM",2013 +"2013-02-05","Feast of Saint Agatha","SM",2013 +"2013-03-25","Anniversary of the Arengo","SM",2013 +"2013-03-31","Easter Sunday","SM",2013 +"2013-04-01","Easter Monday","SM",2013 +"2013-05-01","Labour Day","SM",2013 +"2013-05-30","Corpus Cristi","SM",2013 +"2013-07-28","Liberation from Fascism Day","SM",2013 +"2013-08-15","Assumption Day","SM",2013 +"2013-09-03","Foundation Day","SM",2013 +"2013-11-01","All Saints' Day","SM",2013 +"2013-11-02","Commemoration of the Dead","SM",2013 +"2013-12-08","Immaculate Conception Day","SM",2013 +"2013-12-24","Christmas Eve","SM",2013 +"2013-12-25","Christmas Day","SM",2013 +"2013-12-26","Saint Stephen's Day","SM",2013 +"2013-12-31","New Year's Eve","SM",2013 +"2014-01-01","New Year's Day","SM",2014 +"2014-01-06","Epiphany","SM",2014 +"2014-02-05","Feast of Saint Agatha","SM",2014 +"2014-03-25","Anniversary of the Arengo","SM",2014 +"2014-04-20","Easter Sunday","SM",2014 +"2014-04-21","Easter Monday","SM",2014 +"2014-05-01","Labour Day","SM",2014 +"2014-06-19","Corpus Cristi","SM",2014 +"2014-07-28","Liberation from Fascism Day","SM",2014 +"2014-08-15","Assumption Day","SM",2014 +"2014-09-03","Foundation Day","SM",2014 +"2014-11-01","All Saints' Day","SM",2014 +"2014-11-02","Commemoration of the Dead","SM",2014 +"2014-12-08","Immaculate Conception Day","SM",2014 +"2014-12-24","Christmas Eve","SM",2014 +"2014-12-25","Christmas Day","SM",2014 +"2014-12-26","Saint Stephen's Day","SM",2014 +"2014-12-31","New Year's Eve","SM",2014 +"2015-01-01","New Year's Day","SM",2015 +"2015-01-06","Epiphany","SM",2015 +"2015-02-05","Feast of Saint Agatha","SM",2015 +"2015-03-25","Anniversary of the Arengo","SM",2015 +"2015-04-05","Easter Sunday","SM",2015 +"2015-04-06","Easter Monday","SM",2015 +"2015-05-01","Labour Day","SM",2015 +"2015-06-04","Corpus Cristi","SM",2015 +"2015-07-28","Liberation from Fascism Day","SM",2015 +"2015-08-15","Assumption Day","SM",2015 +"2015-09-03","Foundation Day","SM",2015 +"2015-11-01","All Saints' Day","SM",2015 +"2015-11-02","Commemoration of the Dead","SM",2015 +"2015-12-08","Immaculate Conception Day","SM",2015 +"2015-12-24","Christmas Eve","SM",2015 +"2015-12-25","Christmas Day","SM",2015 +"2015-12-26","Saint Stephen's Day","SM",2015 +"2015-12-31","New Year's Eve","SM",2015 +"2016-01-01","New Year's Day","SM",2016 +"2016-01-06","Epiphany","SM",2016 +"2016-02-05","Feast of Saint Agatha","SM",2016 +"2016-03-25","Anniversary of the Arengo","SM",2016 +"2016-03-27","Easter Sunday","SM",2016 +"2016-03-28","Easter Monday","SM",2016 +"2016-05-01","Labour Day","SM",2016 +"2016-05-26","Corpus Cristi","SM",2016 +"2016-07-28","Liberation from Fascism Day","SM",2016 +"2016-08-15","Assumption Day","SM",2016 +"2016-09-03","Foundation Day","SM",2016 +"2016-11-01","All Saints' Day","SM",2016 +"2016-11-02","Commemoration of the Dead","SM",2016 +"2016-12-08","Immaculate Conception Day","SM",2016 +"2016-12-24","Christmas Eve","SM",2016 +"2016-12-25","Christmas Day","SM",2016 +"2016-12-26","Saint Stephen's Day","SM",2016 +"2016-12-31","New Year's Eve","SM",2016 +"2017-01-01","New Year's Day","SM",2017 +"2017-01-06","Epiphany","SM",2017 +"2017-02-05","Feast of Saint Agatha","SM",2017 +"2017-03-25","Anniversary of the Arengo","SM",2017 +"2017-04-16","Easter Sunday","SM",2017 +"2017-04-17","Easter Monday","SM",2017 +"2017-05-01","Labour Day","SM",2017 +"2017-06-15","Corpus Cristi","SM",2017 +"2017-07-28","Liberation from Fascism Day","SM",2017 +"2017-08-15","Assumption Day","SM",2017 +"2017-09-03","Foundation Day","SM",2017 +"2017-11-01","All Saints' Day","SM",2017 +"2017-11-02","Commemoration of the Dead","SM",2017 +"2017-12-08","Immaculate Conception Day","SM",2017 +"2017-12-24","Christmas Eve","SM",2017 +"2017-12-25","Christmas Day","SM",2017 +"2017-12-26","Saint Stephen's Day","SM",2017 +"2017-12-31","New Year's Eve","SM",2017 +"2018-01-01","New Year's Day","SM",2018 +"2018-01-06","Epiphany","SM",2018 +"2018-02-05","Feast of Saint Agatha","SM",2018 +"2018-03-25","Anniversary of the Arengo","SM",2018 +"2018-04-01","Easter Sunday","SM",2018 +"2018-04-02","Easter Monday","SM",2018 +"2018-05-01","Labour Day","SM",2018 +"2018-05-31","Corpus Cristi","SM",2018 +"2018-07-28","Liberation from Fascism Day","SM",2018 +"2018-08-15","Assumption Day","SM",2018 +"2018-09-03","Foundation Day","SM",2018 +"2018-11-01","All Saints' Day","SM",2018 +"2018-11-02","Commemoration of the Dead","SM",2018 +"2018-12-08","Immaculate Conception Day","SM",2018 +"2018-12-24","Christmas Eve","SM",2018 +"2018-12-25","Christmas Day","SM",2018 +"2018-12-26","Saint Stephen's Day","SM",2018 +"2018-12-31","New Year's Eve","SM",2018 +"2019-01-01","New Year's Day","SM",2019 +"2019-01-06","Epiphany","SM",2019 +"2019-02-05","Feast of Saint Agatha","SM",2019 +"2019-03-25","Anniversary of the Arengo","SM",2019 +"2019-04-21","Easter Sunday","SM",2019 +"2019-04-22","Easter Monday","SM",2019 +"2019-05-01","Labour Day","SM",2019 +"2019-06-20","Corpus Cristi","SM",2019 +"2019-07-28","Liberation from Fascism Day","SM",2019 +"2019-08-15","Assumption Day","SM",2019 +"2019-09-03","Foundation Day","SM",2019 +"2019-11-01","All Saints' Day","SM",2019 +"2019-11-02","Commemoration of the Dead","SM",2019 +"2019-12-08","Immaculate Conception Day","SM",2019 +"2019-12-24","Christmas Eve","SM",2019 +"2019-12-25","Christmas Day","SM",2019 +"2019-12-26","Saint Stephen's Day","SM",2019 +"2019-12-31","New Year's Eve","SM",2019 +"2020-01-01","New Year's Day","SM",2020 +"2020-01-06","Epiphany","SM",2020 +"2020-02-05","Feast of Saint Agatha","SM",2020 +"2020-03-25","Anniversary of the Arengo","SM",2020 +"2020-04-12","Easter Sunday","SM",2020 +"2020-04-13","Easter Monday","SM",2020 +"2020-05-01","Labour Day","SM",2020 +"2020-06-11","Corpus Cristi","SM",2020 +"2020-07-28","Liberation from Fascism Day","SM",2020 +"2020-08-15","Assumption Day","SM",2020 +"2020-09-03","Foundation Day","SM",2020 +"2020-11-01","All Saints' Day","SM",2020 +"2020-11-02","Commemoration of the Dead","SM",2020 +"2020-12-08","Immaculate Conception Day","SM",2020 +"2020-12-24","Christmas Eve","SM",2020 +"2020-12-25","Christmas Day","SM",2020 +"2020-12-26","Saint Stephen's Day","SM",2020 +"2020-12-31","New Year's Eve","SM",2020 +"2021-01-01","New Year's Day","SM",2021 +"2021-01-06","Epiphany","SM",2021 +"2021-02-05","Feast of Saint Agatha","SM",2021 +"2021-03-25","Anniversary of the Arengo","SM",2021 +"2021-04-04","Easter Sunday","SM",2021 +"2021-04-05","Easter Monday","SM",2021 +"2021-05-01","Labour Day","SM",2021 +"2021-06-03","Corpus Cristi","SM",2021 +"2021-07-28","Liberation from Fascism Day","SM",2021 +"2021-08-15","Assumption Day","SM",2021 +"2021-09-03","Foundation Day","SM",2021 +"2021-11-01","All Saints' Day","SM",2021 +"2021-11-02","Commemoration of the Dead","SM",2021 +"2021-12-08","Immaculate Conception Day","SM",2021 +"2021-12-24","Christmas Eve","SM",2021 +"2021-12-25","Christmas Day","SM",2021 +"2021-12-26","Saint Stephen's Day","SM",2021 +"2021-12-31","New Year's Eve","SM",2021 +"2022-01-01","New Year's Day","SM",2022 +"2022-01-06","Epiphany","SM",2022 +"2022-02-05","Feast of Saint Agatha","SM",2022 +"2022-03-25","Anniversary of the Arengo","SM",2022 +"2022-04-17","Easter Sunday","SM",2022 +"2022-04-18","Easter Monday","SM",2022 +"2022-05-01","Labour Day","SM",2022 +"2022-06-16","Corpus Cristi","SM",2022 +"2022-07-28","Liberation from Fascism Day","SM",2022 +"2022-08-15","Assumption Day","SM",2022 +"2022-09-03","Foundation Day","SM",2022 +"2022-11-01","All Saints' Day","SM",2022 +"2022-11-02","Commemoration of the Dead","SM",2022 +"2022-12-08","Immaculate Conception Day","SM",2022 +"2022-12-24","Christmas Eve","SM",2022 +"2022-12-25","Christmas Day","SM",2022 +"2022-12-26","Saint Stephen's Day","SM",2022 +"2022-12-31","New Year's Eve","SM",2022 +"2023-01-01","New Year's Day","SM",2023 +"2023-01-06","Epiphany","SM",2023 +"2023-02-05","Feast of Saint Agatha","SM",2023 +"2023-03-25","Anniversary of the Arengo","SM",2023 +"2023-04-09","Easter Sunday","SM",2023 +"2023-04-10","Easter Monday","SM",2023 +"2023-05-01","Labour Day","SM",2023 +"2023-06-08","Corpus Cristi","SM",2023 +"2023-07-28","Liberation from Fascism Day","SM",2023 +"2023-08-15","Assumption Day","SM",2023 +"2023-09-03","Foundation Day","SM",2023 +"2023-11-01","All Saints' Day","SM",2023 +"2023-11-02","Commemoration of the Dead","SM",2023 +"2023-12-08","Immaculate Conception Day","SM",2023 +"2023-12-24","Christmas Eve","SM",2023 +"2023-12-25","Christmas Day","SM",2023 +"2023-12-26","Saint Stephen's Day","SM",2023 +"2023-12-31","New Year's Eve","SM",2023 +"2024-01-01","New Year's Day","SM",2024 +"2024-01-06","Epiphany","SM",2024 +"2024-02-05","Feast of Saint Agatha","SM",2024 +"2024-03-25","Anniversary of the Arengo","SM",2024 +"2024-03-31","Easter Sunday","SM",2024 +"2024-04-01","Easter Monday","SM",2024 +"2024-05-01","Labour Day","SM",2024 +"2024-05-30","Corpus Cristi","SM",2024 +"2024-07-28","Liberation from Fascism Day","SM",2024 +"2024-08-15","Assumption Day","SM",2024 +"2024-09-03","Foundation Day","SM",2024 +"2024-11-01","All Saints' Day","SM",2024 +"2024-11-02","Commemoration of the Dead","SM",2024 +"2024-12-08","Immaculate Conception Day","SM",2024 +"2024-12-24","Christmas Eve","SM",2024 +"2024-12-25","Christmas Day","SM",2024 +"2024-12-26","Saint Stephen's Day","SM",2024 +"2024-12-31","New Year's Eve","SM",2024 +"2025-01-01","New Year's Day","SM",2025 +"2025-01-06","Epiphany","SM",2025 +"2025-02-05","Feast of Saint Agatha","SM",2025 +"2025-03-25","Anniversary of the Arengo","SM",2025 +"2025-04-20","Easter Sunday","SM",2025 +"2025-04-21","Easter Monday","SM",2025 +"2025-05-01","Labour Day","SM",2025 +"2025-06-19","Corpus Cristi","SM",2025 +"2025-07-28","Liberation from Fascism Day","SM",2025 +"2025-08-15","Assumption Day","SM",2025 +"2025-09-03","Foundation Day","SM",2025 +"2025-11-01","All Saints' Day","SM",2025 +"2025-11-02","Commemoration of the Dead","SM",2025 +"2025-12-08","Immaculate Conception Day","SM",2025 +"2025-12-24","Christmas Eve","SM",2025 +"2025-12-25","Christmas Day","SM",2025 +"2025-12-26","Saint Stephen's Day","SM",2025 +"2025-12-31","New Year's Eve","SM",2025 +"2026-01-01","New Year's Day","SM",2026 +"2026-01-06","Epiphany","SM",2026 +"2026-02-05","Feast of Saint Agatha","SM",2026 +"2026-03-25","Anniversary of the Arengo","SM",2026 +"2026-04-05","Easter Sunday","SM",2026 +"2026-04-06","Easter Monday","SM",2026 +"2026-05-01","Labour Day","SM",2026 +"2026-06-04","Corpus Cristi","SM",2026 +"2026-07-28","Liberation from Fascism Day","SM",2026 +"2026-08-15","Assumption Day","SM",2026 +"2026-09-03","Foundation Day","SM",2026 +"2026-11-01","All Saints' Day","SM",2026 +"2026-11-02","Commemoration of the Dead","SM",2026 +"2026-12-08","Immaculate Conception Day","SM",2026 +"2026-12-24","Christmas Eve","SM",2026 +"2026-12-25","Christmas Day","SM",2026 +"2026-12-26","Saint Stephen's Day","SM",2026 +"2026-12-31","New Year's Eve","SM",2026 +"2027-01-01","New Year's Day","SM",2027 +"2027-01-06","Epiphany","SM",2027 +"2027-02-05","Feast of Saint Agatha","SM",2027 +"2027-03-25","Anniversary of the Arengo","SM",2027 +"2027-03-28","Easter Sunday","SM",2027 +"2027-03-29","Easter Monday","SM",2027 +"2027-05-01","Labour Day","SM",2027 +"2027-05-27","Corpus Cristi","SM",2027 +"2027-07-28","Liberation from Fascism Day","SM",2027 +"2027-08-15","Assumption Day","SM",2027 +"2027-09-03","Foundation Day","SM",2027 +"2027-11-01","All Saints' Day","SM",2027 +"2027-11-02","Commemoration of the Dead","SM",2027 +"2027-12-08","Immaculate Conception Day","SM",2027 +"2027-12-24","Christmas Eve","SM",2027 +"2027-12-25","Christmas Day","SM",2027 +"2027-12-26","Saint Stephen's Day","SM",2027 +"2027-12-31","New Year's Eve","SM",2027 +"2028-01-01","New Year's Day","SM",2028 +"2028-01-06","Epiphany","SM",2028 +"2028-02-05","Feast of Saint Agatha","SM",2028 +"2028-03-25","Anniversary of the Arengo","SM",2028 +"2028-04-16","Easter Sunday","SM",2028 +"2028-04-17","Easter Monday","SM",2028 +"2028-05-01","Labour Day","SM",2028 +"2028-06-15","Corpus Cristi","SM",2028 +"2028-07-28","Liberation from Fascism Day","SM",2028 +"2028-08-15","Assumption Day","SM",2028 +"2028-09-03","Foundation Day","SM",2028 +"2028-11-01","All Saints' Day","SM",2028 +"2028-11-02","Commemoration of the Dead","SM",2028 +"2028-12-08","Immaculate Conception Day","SM",2028 +"2028-12-24","Christmas Eve","SM",2028 +"2028-12-25","Christmas Day","SM",2028 +"2028-12-26","Saint Stephen's Day","SM",2028 +"2028-12-31","New Year's Eve","SM",2028 +"2029-01-01","New Year's Day","SM",2029 +"2029-01-06","Epiphany","SM",2029 +"2029-02-05","Feast of Saint Agatha","SM",2029 +"2029-03-25","Anniversary of the Arengo","SM",2029 +"2029-04-01","Easter Sunday","SM",2029 +"2029-04-02","Easter Monday","SM",2029 +"2029-05-01","Labour Day","SM",2029 +"2029-05-31","Corpus Cristi","SM",2029 +"2029-07-28","Liberation from Fascism Day","SM",2029 +"2029-08-15","Assumption Day","SM",2029 +"2029-09-03","Foundation Day","SM",2029 +"2029-11-01","All Saints' Day","SM",2029 +"2029-11-02","Commemoration of the Dead","SM",2029 +"2029-12-08","Immaculate Conception Day","SM",2029 +"2029-12-24","Christmas Eve","SM",2029 +"2029-12-25","Christmas Day","SM",2029 +"2029-12-26","Saint Stephen's Day","SM",2029 +"2029-12-31","New Year's Eve","SM",2029 +"2030-01-01","New Year's Day","SM",2030 +"2030-01-06","Epiphany","SM",2030 +"2030-02-05","Feast of Saint Agatha","SM",2030 +"2030-03-25","Anniversary of the Arengo","SM",2030 +"2030-04-21","Easter Sunday","SM",2030 +"2030-04-22","Easter Monday","SM",2030 +"2030-05-01","Labour Day","SM",2030 +"2030-06-20","Corpus Cristi","SM",2030 +"2030-07-28","Liberation from Fascism Day","SM",2030 +"2030-08-15","Assumption Day","SM",2030 +"2030-09-03","Foundation Day","SM",2030 +"2030-11-01","All Saints' Day","SM",2030 +"2030-11-02","Commemoration of the Dead","SM",2030 +"2030-12-08","Immaculate Conception Day","SM",2030 +"2030-12-24","Christmas Eve","SM",2030 +"2030-12-25","Christmas Day","SM",2030 +"2030-12-26","Saint Stephen's Day","SM",2030 +"2030-12-31","New Year's Eve","SM",2030 +"2031-01-01","New Year's Day","SM",2031 +"2031-01-06","Epiphany","SM",2031 +"2031-02-05","Feast of Saint Agatha","SM",2031 +"2031-03-25","Anniversary of the Arengo","SM",2031 +"2031-04-13","Easter Sunday","SM",2031 +"2031-04-14","Easter Monday","SM",2031 +"2031-05-01","Labour Day","SM",2031 +"2031-06-12","Corpus Cristi","SM",2031 +"2031-07-28","Liberation from Fascism Day","SM",2031 +"2031-08-15","Assumption Day","SM",2031 +"2031-09-03","Foundation Day","SM",2031 +"2031-11-01","All Saints' Day","SM",2031 +"2031-11-02","Commemoration of the Dead","SM",2031 +"2031-12-08","Immaculate Conception Day","SM",2031 +"2031-12-24","Christmas Eve","SM",2031 +"2031-12-25","Christmas Day","SM",2031 +"2031-12-26","Saint Stephen's Day","SM",2031 +"2031-12-31","New Year's Eve","SM",2031 +"2032-01-01","New Year's Day","SM",2032 +"2032-01-06","Epiphany","SM",2032 +"2032-02-05","Feast of Saint Agatha","SM",2032 +"2032-03-25","Anniversary of the Arengo","SM",2032 +"2032-03-28","Easter Sunday","SM",2032 +"2032-03-29","Easter Monday","SM",2032 +"2032-05-01","Labour Day","SM",2032 +"2032-05-27","Corpus Cristi","SM",2032 +"2032-07-28","Liberation from Fascism Day","SM",2032 +"2032-08-15","Assumption Day","SM",2032 +"2032-09-03","Foundation Day","SM",2032 +"2032-11-01","All Saints' Day","SM",2032 +"2032-11-02","Commemoration of the Dead","SM",2032 +"2032-12-08","Immaculate Conception Day","SM",2032 +"2032-12-24","Christmas Eve","SM",2032 +"2032-12-25","Christmas Day","SM",2032 +"2032-12-26","Saint Stephen's Day","SM",2032 +"2032-12-31","New Year's Eve","SM",2032 +"2033-01-01","New Year's Day","SM",2033 +"2033-01-06","Epiphany","SM",2033 +"2033-02-05","Feast of Saint Agatha","SM",2033 +"2033-03-25","Anniversary of the Arengo","SM",2033 +"2033-04-17","Easter Sunday","SM",2033 +"2033-04-18","Easter Monday","SM",2033 +"2033-05-01","Labour Day","SM",2033 +"2033-06-16","Corpus Cristi","SM",2033 +"2033-07-28","Liberation from Fascism Day","SM",2033 +"2033-08-15","Assumption Day","SM",2033 +"2033-09-03","Foundation Day","SM",2033 +"2033-11-01","All Saints' Day","SM",2033 +"2033-11-02","Commemoration of the Dead","SM",2033 +"2033-12-08","Immaculate Conception Day","SM",2033 +"2033-12-24","Christmas Eve","SM",2033 +"2033-12-25","Christmas Day","SM",2033 +"2033-12-26","Saint Stephen's Day","SM",2033 +"2033-12-31","New Year's Eve","SM",2033 +"2034-01-01","New Year's Day","SM",2034 +"2034-01-06","Epiphany","SM",2034 +"2034-02-05","Feast of Saint Agatha","SM",2034 +"2034-03-25","Anniversary of the Arengo","SM",2034 +"2034-04-09","Easter Sunday","SM",2034 +"2034-04-10","Easter Monday","SM",2034 +"2034-05-01","Labour Day","SM",2034 +"2034-06-08","Corpus Cristi","SM",2034 +"2034-07-28","Liberation from Fascism Day","SM",2034 +"2034-08-15","Assumption Day","SM",2034 +"2034-09-03","Foundation Day","SM",2034 +"2034-11-01","All Saints' Day","SM",2034 +"2034-11-02","Commemoration of the Dead","SM",2034 +"2034-12-08","Immaculate Conception Day","SM",2034 +"2034-12-24","Christmas Eve","SM",2034 +"2034-12-25","Christmas Day","SM",2034 +"2034-12-26","Saint Stephen's Day","SM",2034 +"2034-12-31","New Year's Eve","SM",2034 +"2035-01-01","New Year's Day","SM",2035 +"2035-01-06","Epiphany","SM",2035 +"2035-02-05","Feast of Saint Agatha","SM",2035 +"2035-03-25","Anniversary of the Arengo","SM",2035 +"2035-03-25","Easter Sunday","SM",2035 +"2035-03-26","Easter Monday","SM",2035 +"2035-05-01","Labour Day","SM",2035 +"2035-05-24","Corpus Cristi","SM",2035 +"2035-07-28","Liberation from Fascism Day","SM",2035 +"2035-08-15","Assumption Day","SM",2035 +"2035-09-03","Foundation Day","SM",2035 +"2035-11-01","All Saints' Day","SM",2035 +"2035-11-02","Commemoration of the Dead","SM",2035 +"2035-12-08","Immaculate Conception Day","SM",2035 +"2035-12-24","Christmas Eve","SM",2035 +"2035-12-25","Christmas Day","SM",2035 +"2035-12-26","Saint Stephen's Day","SM",2035 +"2035-12-31","New Year's Eve","SM",2035 +"2036-01-01","New Year's Day","SM",2036 +"2036-01-06","Epiphany","SM",2036 +"2036-02-05","Feast of Saint Agatha","SM",2036 +"2036-03-25","Anniversary of the Arengo","SM",2036 +"2036-04-13","Easter Sunday","SM",2036 +"2036-04-14","Easter Monday","SM",2036 +"2036-05-01","Labour Day","SM",2036 +"2036-06-12","Corpus Cristi","SM",2036 +"2036-07-28","Liberation from Fascism Day","SM",2036 +"2036-08-15","Assumption Day","SM",2036 +"2036-09-03","Foundation Day","SM",2036 +"2036-11-01","All Saints' Day","SM",2036 +"2036-11-02","Commemoration of the Dead","SM",2036 +"2036-12-08","Immaculate Conception Day","SM",2036 +"2036-12-24","Christmas Eve","SM",2036 +"2036-12-25","Christmas Day","SM",2036 +"2036-12-26","Saint Stephen's Day","SM",2036 +"2036-12-31","New Year's Eve","SM",2036 +"2037-01-01","New Year's Day","SM",2037 +"2037-01-06","Epiphany","SM",2037 +"2037-02-05","Feast of Saint Agatha","SM",2037 +"2037-03-25","Anniversary of the Arengo","SM",2037 +"2037-04-05","Easter Sunday","SM",2037 +"2037-04-06","Easter Monday","SM",2037 +"2037-05-01","Labour Day","SM",2037 +"2037-06-04","Corpus Cristi","SM",2037 +"2037-07-28","Liberation from Fascism Day","SM",2037 +"2037-08-15","Assumption Day","SM",2037 +"2037-09-03","Foundation Day","SM",2037 +"2037-11-01","All Saints' Day","SM",2037 +"2037-11-02","Commemoration of the Dead","SM",2037 +"2037-12-08","Immaculate Conception Day","SM",2037 +"2037-12-24","Christmas Eve","SM",2037 +"2037-12-25","Christmas Day","SM",2037 +"2037-12-26","Saint Stephen's Day","SM",2037 +"2037-12-31","New Year's Eve","SM",2037 +"2038-01-01","New Year's Day","SM",2038 +"2038-01-06","Epiphany","SM",2038 +"2038-02-05","Feast of Saint Agatha","SM",2038 +"2038-03-25","Anniversary of the Arengo","SM",2038 +"2038-04-25","Easter Sunday","SM",2038 +"2038-04-26","Easter Monday","SM",2038 +"2038-05-01","Labour Day","SM",2038 +"2038-06-24","Corpus Cristi","SM",2038 +"2038-07-28","Liberation from Fascism Day","SM",2038 +"2038-08-15","Assumption Day","SM",2038 +"2038-09-03","Foundation Day","SM",2038 +"2038-11-01","All Saints' Day","SM",2038 +"2038-11-02","Commemoration of the Dead","SM",2038 +"2038-12-08","Immaculate Conception Day","SM",2038 +"2038-12-24","Christmas Eve","SM",2038 +"2038-12-25","Christmas Day","SM",2038 +"2038-12-26","Saint Stephen's Day","SM",2038 +"2038-12-31","New Year's Eve","SM",2038 +"2039-01-01","New Year's Day","SM",2039 +"2039-01-06","Epiphany","SM",2039 +"2039-02-05","Feast of Saint Agatha","SM",2039 +"2039-03-25","Anniversary of the Arengo","SM",2039 +"2039-04-10","Easter Sunday","SM",2039 +"2039-04-11","Easter Monday","SM",2039 +"2039-05-01","Labour Day","SM",2039 +"2039-06-09","Corpus Cristi","SM",2039 +"2039-07-28","Liberation from Fascism Day","SM",2039 +"2039-08-15","Assumption Day","SM",2039 +"2039-09-03","Foundation Day","SM",2039 +"2039-11-01","All Saints' Day","SM",2039 +"2039-11-02","Commemoration of the Dead","SM",2039 +"2039-12-08","Immaculate Conception Day","SM",2039 +"2039-12-24","Christmas Eve","SM",2039 +"2039-12-25","Christmas Day","SM",2039 +"2039-12-26","Saint Stephen's Day","SM",2039 +"2039-12-31","New Year's Eve","SM",2039 +"2040-01-01","New Year's Day","SM",2040 +"2040-01-06","Epiphany","SM",2040 +"2040-02-05","Feast of Saint Agatha","SM",2040 +"2040-03-25","Anniversary of the Arengo","SM",2040 +"2040-04-01","Easter Sunday","SM",2040 +"2040-04-02","Easter Monday","SM",2040 +"2040-05-01","Labour Day","SM",2040 +"2040-05-31","Corpus Cristi","SM",2040 +"2040-07-28","Liberation from Fascism Day","SM",2040 +"2040-08-15","Assumption Day","SM",2040 +"2040-09-03","Foundation Day","SM",2040 +"2040-11-01","All Saints' Day","SM",2040 +"2040-11-02","Commemoration of the Dead","SM",2040 +"2040-12-08","Immaculate Conception Day","SM",2040 +"2040-12-24","Christmas Eve","SM",2040 +"2040-12-25","Christmas Day","SM",2040 +"2040-12-26","Saint Stephen's Day","SM",2040 +"2040-12-31","New Year's Eve","SM",2040 +"2041-01-01","New Year's Day","SM",2041 +"2041-01-06","Epiphany","SM",2041 +"2041-02-05","Feast of Saint Agatha","SM",2041 +"2041-03-25","Anniversary of the Arengo","SM",2041 +"2041-04-21","Easter Sunday","SM",2041 +"2041-04-22","Easter Monday","SM",2041 +"2041-05-01","Labour Day","SM",2041 +"2041-06-20","Corpus Cristi","SM",2041 +"2041-07-28","Liberation from Fascism Day","SM",2041 +"2041-08-15","Assumption Day","SM",2041 +"2041-09-03","Foundation Day","SM",2041 +"2041-11-01","All Saints' Day","SM",2041 +"2041-11-02","Commemoration of the Dead","SM",2041 +"2041-12-08","Immaculate Conception Day","SM",2041 +"2041-12-24","Christmas Eve","SM",2041 +"2041-12-25","Christmas Day","SM",2041 +"2041-12-26","Saint Stephen's Day","SM",2041 +"2041-12-31","New Year's Eve","SM",2041 +"2042-01-01","New Year's Day","SM",2042 +"2042-01-06","Epiphany","SM",2042 +"2042-02-05","Feast of Saint Agatha","SM",2042 +"2042-03-25","Anniversary of the Arengo","SM",2042 +"2042-04-06","Easter Sunday","SM",2042 +"2042-04-07","Easter Monday","SM",2042 +"2042-05-01","Labour Day","SM",2042 +"2042-06-05","Corpus Cristi","SM",2042 +"2042-07-28","Liberation from Fascism Day","SM",2042 +"2042-08-15","Assumption Day","SM",2042 +"2042-09-03","Foundation Day","SM",2042 +"2042-11-01","All Saints' Day","SM",2042 +"2042-11-02","Commemoration of the Dead","SM",2042 +"2042-12-08","Immaculate Conception Day","SM",2042 +"2042-12-24","Christmas Eve","SM",2042 +"2042-12-25","Christmas Day","SM",2042 +"2042-12-26","Saint Stephen's Day","SM",2042 +"2042-12-31","New Year's Eve","SM",2042 +"2043-01-01","New Year's Day","SM",2043 +"2043-01-06","Epiphany","SM",2043 +"2043-02-05","Feast of Saint Agatha","SM",2043 +"2043-03-25","Anniversary of the Arengo","SM",2043 +"2043-03-29","Easter Sunday","SM",2043 +"2043-03-30","Easter Monday","SM",2043 +"2043-05-01","Labour Day","SM",2043 +"2043-05-28","Corpus Cristi","SM",2043 +"2043-07-28","Liberation from Fascism Day","SM",2043 +"2043-08-15","Assumption Day","SM",2043 +"2043-09-03","Foundation Day","SM",2043 +"2043-11-01","All Saints' Day","SM",2043 +"2043-11-02","Commemoration of the Dead","SM",2043 +"2043-12-08","Immaculate Conception Day","SM",2043 +"2043-12-24","Christmas Eve","SM",2043 +"2043-12-25","Christmas Day","SM",2043 +"2043-12-26","Saint Stephen's Day","SM",2043 +"2043-12-31","New Year's Eve","SM",2043 +"2044-01-01","New Year's Day","SM",2044 +"2044-01-06","Epiphany","SM",2044 +"2044-02-05","Feast of Saint Agatha","SM",2044 +"2044-03-25","Anniversary of the Arengo","SM",2044 +"2044-04-17","Easter Sunday","SM",2044 +"2044-04-18","Easter Monday","SM",2044 +"2044-05-01","Labour Day","SM",2044 +"2044-06-16","Corpus Cristi","SM",2044 +"2044-07-28","Liberation from Fascism Day","SM",2044 +"2044-08-15","Assumption Day","SM",2044 +"2044-09-03","Foundation Day","SM",2044 +"2044-11-01","All Saints' Day","SM",2044 +"2044-11-02","Commemoration of the Dead","SM",2044 +"2044-12-08","Immaculate Conception Day","SM",2044 +"2044-12-24","Christmas Eve","SM",2044 +"2044-12-25","Christmas Day","SM",2044 +"2044-12-26","Saint Stephen's Day","SM",2044 +"2044-12-31","New Year's Eve","SM",2044 +"1995-01-01","New Year's Day","SZ",1995 +"1995-04-14","Good Friday","SZ",1995 +"1995-04-17","Easter Monday","SZ",1995 +"1995-04-19","King's Birthday","SZ",1995 +"1995-04-25","National Flag Day","SZ",1995 +"1995-05-01","Worker's Day","SZ",1995 +"1995-05-25","Ascension Day","SZ",1995 +"1995-07-22","Birthday of Late King Sobhuza","SZ",1995 +"1995-09-06","Independence Day","SZ",1995 +"1995-12-25","Christmas Day","SZ",1995 +"1995-12-26","Boxing Day","SZ",1995 +"1996-01-01","New Year's Day","SZ",1996 +"1996-04-05","Good Friday","SZ",1996 +"1996-04-08","Easter Monday","SZ",1996 +"1996-04-19","King's Birthday","SZ",1996 +"1996-04-25","National Flag Day","SZ",1996 +"1996-05-01","Worker's Day","SZ",1996 +"1996-05-16","Ascension Day","SZ",1996 +"1996-07-22","Birthday of Late King Sobhuza","SZ",1996 +"1996-09-06","Independence Day","SZ",1996 +"1996-12-25","Christmas Day","SZ",1996 +"1996-12-26","Boxing Day","SZ",1996 +"1997-01-01","New Year's Day","SZ",1997 +"1997-03-28","Good Friday","SZ",1997 +"1997-03-31","Easter Monday","SZ",1997 +"1997-04-19","King's Birthday","SZ",1997 +"1997-04-25","National Flag Day","SZ",1997 +"1997-05-01","Worker's Day","SZ",1997 +"1997-05-08","Ascension Day","SZ",1997 +"1997-07-22","Birthday of Late King Sobhuza","SZ",1997 +"1997-09-06","Independence Day","SZ",1997 +"1997-12-25","Christmas Day","SZ",1997 +"1997-12-26","Boxing Day","SZ",1997 +"1998-01-01","New Year's Day","SZ",1998 +"1998-04-10","Good Friday","SZ",1998 +"1998-04-13","Easter Monday","SZ",1998 +"1998-04-19","King's Birthday","SZ",1998 +"1998-04-25","National Flag Day","SZ",1998 +"1998-05-01","Worker's Day","SZ",1998 +"1998-05-21","Ascension Day","SZ",1998 +"1998-07-22","Birthday of Late King Sobhuza","SZ",1998 +"1998-09-06","Independence Day","SZ",1998 +"1998-12-25","Christmas Day","SZ",1998 +"1998-12-26","Boxing Day","SZ",1998 +"1999-01-01","New Year's Day","SZ",1999 +"1999-04-02","Good Friday","SZ",1999 +"1999-04-05","Easter Monday","SZ",1999 +"1999-04-19","King's Birthday","SZ",1999 +"1999-04-25","National Flag Day","SZ",1999 +"1999-05-01","Worker's Day","SZ",1999 +"1999-05-13","Ascension Day","SZ",1999 +"1999-07-22","Birthday of Late King Sobhuza","SZ",1999 +"1999-09-06","Independence Day","SZ",1999 +"1999-12-25","Christmas Day","SZ",1999 +"1999-12-26","Boxing Day","SZ",1999 +"1999-12-31","Y2K changeover","SZ",1999 +"2000-01-01","New Year's Day","SZ",2000 +"2000-01-03","Y2K changeover","SZ",2000 +"2000-04-19","King's Birthday","SZ",2000 +"2000-04-21","Good Friday","SZ",2000 +"2000-04-24","Easter Monday","SZ",2000 +"2000-04-25","National Flag Day","SZ",2000 +"2000-05-01","Worker's Day","SZ",2000 +"2000-06-01","Ascension Day","SZ",2000 +"2000-07-22","Birthday of Late King Sobhuza","SZ",2000 +"2000-09-06","Independence Day","SZ",2000 +"2000-12-25","Christmas Day","SZ",2000 +"2000-12-26","Boxing Day","SZ",2000 +"2001-01-01","New Year's Day","SZ",2001 +"2001-04-13","Good Friday","SZ",2001 +"2001-04-16","Easter Monday","SZ",2001 +"2001-04-19","King's Birthday","SZ",2001 +"2001-04-25","National Flag Day","SZ",2001 +"2001-05-01","Worker's Day","SZ",2001 +"2001-05-24","Ascension Day","SZ",2001 +"2001-07-22","Birthday of Late King Sobhuza","SZ",2001 +"2001-09-06","Independence Day","SZ",2001 +"2001-12-25","Christmas Day","SZ",2001 +"2001-12-26","Boxing Day","SZ",2001 +"2002-01-01","New Year's Day","SZ",2002 +"2002-03-29","Good Friday","SZ",2002 +"2002-04-01","Easter Monday","SZ",2002 +"2002-04-19","King's Birthday","SZ",2002 +"2002-04-25","National Flag Day","SZ",2002 +"2002-05-01","Worker's Day","SZ",2002 +"2002-05-09","Ascension Day","SZ",2002 +"2002-07-22","Birthday of Late King Sobhuza","SZ",2002 +"2002-09-06","Independence Day","SZ",2002 +"2002-12-25","Christmas Day","SZ",2002 +"2002-12-26","Boxing Day","SZ",2002 +"2003-01-01","New Year's Day","SZ",2003 +"2003-04-18","Good Friday","SZ",2003 +"2003-04-19","King's Birthday","SZ",2003 +"2003-04-21","Easter Monday","SZ",2003 +"2003-04-25","National Flag Day","SZ",2003 +"2003-05-01","Worker's Day","SZ",2003 +"2003-05-29","Ascension Day","SZ",2003 +"2003-07-22","Birthday of Late King Sobhuza","SZ",2003 +"2003-09-06","Independence Day","SZ",2003 +"2003-12-25","Christmas Day","SZ",2003 +"2003-12-26","Boxing Day","SZ",2003 +"2004-01-01","New Year's Day","SZ",2004 +"2004-04-09","Good Friday","SZ",2004 +"2004-04-12","Easter Monday","SZ",2004 +"2004-04-19","King's Birthday","SZ",2004 +"2004-04-25","National Flag Day","SZ",2004 +"2004-05-01","Worker's Day","SZ",2004 +"2004-05-20","Ascension Day","SZ",2004 +"2004-07-22","Birthday of Late King Sobhuza","SZ",2004 +"2004-09-06","Independence Day","SZ",2004 +"2004-12-25","Christmas Day","SZ",2004 +"2004-12-26","Boxing Day","SZ",2004 +"2005-01-01","New Year's Day","SZ",2005 +"2005-03-25","Good Friday","SZ",2005 +"2005-03-28","Easter Monday","SZ",2005 +"2005-04-19","King's Birthday","SZ",2005 +"2005-04-25","National Flag Day","SZ",2005 +"2005-05-01","Worker's Day","SZ",2005 +"2005-05-05","Ascension Day","SZ",2005 +"2005-07-22","Birthday of Late King Sobhuza","SZ",2005 +"2005-09-06","Independence Day","SZ",2005 +"2005-12-25","Christmas Day","SZ",2005 +"2005-12-26","Boxing Day","SZ",2005 +"2006-01-01","New Year's Day","SZ",2006 +"2006-04-14","Good Friday","SZ",2006 +"2006-04-17","Easter Monday","SZ",2006 +"2006-04-19","King's Birthday","SZ",2006 +"2006-04-25","National Flag Day","SZ",2006 +"2006-05-01","Worker's Day","SZ",2006 +"2006-05-25","Ascension Day","SZ",2006 +"2006-07-22","Birthday of Late King Sobhuza","SZ",2006 +"2006-09-06","Independence Day","SZ",2006 +"2006-12-25","Christmas Day","SZ",2006 +"2006-12-26","Boxing Day","SZ",2006 +"2007-01-01","New Year's Day","SZ",2007 +"2007-04-06","Good Friday","SZ",2007 +"2007-04-09","Easter Monday","SZ",2007 +"2007-04-19","King's Birthday","SZ",2007 +"2007-04-25","National Flag Day","SZ",2007 +"2007-05-01","Worker's Day","SZ",2007 +"2007-05-17","Ascension Day","SZ",2007 +"2007-07-22","Birthday of Late King Sobhuza","SZ",2007 +"2007-09-06","Independence Day","SZ",2007 +"2007-12-25","Christmas Day","SZ",2007 +"2007-12-26","Boxing Day","SZ",2007 +"2008-01-01","New Year's Day","SZ",2008 +"2008-03-21","Good Friday","SZ",2008 +"2008-03-24","Easter Monday","SZ",2008 +"2008-04-19","King's Birthday","SZ",2008 +"2008-04-25","National Flag Day","SZ",2008 +"2008-05-01","Ascension Day","SZ",2008 +"2008-05-01","Worker's Day","SZ",2008 +"2008-07-22","Birthday of Late King Sobhuza","SZ",2008 +"2008-09-06","Independence Day","SZ",2008 +"2008-12-25","Christmas Day","SZ",2008 +"2008-12-26","Boxing Day","SZ",2008 +"2009-01-01","New Year's Day","SZ",2009 +"2009-04-10","Good Friday","SZ",2009 +"2009-04-13","Easter Monday","SZ",2009 +"2009-04-19","King's Birthday","SZ",2009 +"2009-04-25","National Flag Day","SZ",2009 +"2009-05-01","Worker's Day","SZ",2009 +"2009-05-21","Ascension Day","SZ",2009 +"2009-07-22","Birthday of Late King Sobhuza","SZ",2009 +"2009-09-06","Independence Day","SZ",2009 +"2009-12-25","Christmas Day","SZ",2009 +"2009-12-26","Boxing Day","SZ",2009 +"2010-01-01","New Year's Day","SZ",2010 +"2010-04-02","Good Friday","SZ",2010 +"2010-04-05","Easter Monday","SZ",2010 +"2010-04-19","King's Birthday","SZ",2010 +"2010-04-25","National Flag Day","SZ",2010 +"2010-05-01","Worker's Day","SZ",2010 +"2010-05-13","Ascension Day","SZ",2010 +"2010-07-22","Birthday of Late King Sobhuza","SZ",2010 +"2010-09-06","Independence Day","SZ",2010 +"2010-12-25","Christmas Day","SZ",2010 +"2010-12-26","Boxing Day","SZ",2010 +"2011-01-01","New Year's Day","SZ",2011 +"2011-04-19","King's Birthday","SZ",2011 +"2011-04-22","Good Friday","SZ",2011 +"2011-04-25","Easter Monday","SZ",2011 +"2011-04-25","National Flag Day","SZ",2011 +"2011-05-01","Worker's Day","SZ",2011 +"2011-06-02","Ascension Day","SZ",2011 +"2011-07-22","Birthday of Late King Sobhuza","SZ",2011 +"2011-09-06","Independence Day","SZ",2011 +"2011-12-25","Christmas Day","SZ",2011 +"2011-12-26","Boxing Day","SZ",2011 +"2012-01-01","New Year's Day","SZ",2012 +"2012-04-06","Good Friday","SZ",2012 +"2012-04-09","Easter Monday","SZ",2012 +"2012-04-19","King's Birthday","SZ",2012 +"2012-04-25","National Flag Day","SZ",2012 +"2012-05-01","Worker's Day","SZ",2012 +"2012-05-17","Ascension Day","SZ",2012 +"2012-07-22","Birthday of Late King Sobhuza","SZ",2012 +"2012-09-06","Independence Day","SZ",2012 +"2012-12-25","Christmas Day","SZ",2012 +"2012-12-26","Boxing Day","SZ",2012 +"2013-01-01","New Year's Day","SZ",2013 +"2013-03-29","Good Friday","SZ",2013 +"2013-04-01","Easter Monday","SZ",2013 +"2013-04-19","King's Birthday","SZ",2013 +"2013-04-25","National Flag Day","SZ",2013 +"2013-05-01","Worker's Day","SZ",2013 +"2013-05-09","Ascension Day","SZ",2013 +"2013-07-22","Birthday of Late King Sobhuza","SZ",2013 +"2013-09-06","Independence Day","SZ",2013 +"2013-12-25","Christmas Day","SZ",2013 +"2013-12-26","Boxing Day","SZ",2013 +"2014-01-01","New Year's Day","SZ",2014 +"2014-04-18","Good Friday","SZ",2014 +"2014-04-19","King's Birthday","SZ",2014 +"2014-04-21","Easter Monday","SZ",2014 +"2014-04-25","National Flag Day","SZ",2014 +"2014-05-01","Worker's Day","SZ",2014 +"2014-05-29","Ascension Day","SZ",2014 +"2014-07-22","Birthday of Late King Sobhuza","SZ",2014 +"2014-09-06","Independence Day","SZ",2014 +"2014-12-25","Christmas Day","SZ",2014 +"2014-12-26","Boxing Day","SZ",2014 +"2015-01-01","New Year's Day","SZ",2015 +"2015-04-03","Good Friday","SZ",2015 +"2015-04-06","Easter Monday","SZ",2015 +"2015-04-19","King's Birthday","SZ",2015 +"2015-04-25","National Flag Day","SZ",2015 +"2015-05-01","Worker's Day","SZ",2015 +"2015-05-14","Ascension Day","SZ",2015 +"2015-07-22","Birthday of Late King Sobhuza","SZ",2015 +"2015-09-06","Independence Day","SZ",2015 +"2015-12-25","Christmas Day","SZ",2015 +"2015-12-26","Boxing Day","SZ",2015 +"2016-01-01","New Year's Day","SZ",2016 +"2016-03-25","Good Friday","SZ",2016 +"2016-03-28","Easter Monday","SZ",2016 +"2016-04-19","King's Birthday","SZ",2016 +"2016-04-25","National Flag Day","SZ",2016 +"2016-05-01","Worker's Day","SZ",2016 +"2016-05-05","Ascension Day","SZ",2016 +"2016-07-22","Birthday of Late King Sobhuza","SZ",2016 +"2016-09-06","Independence Day","SZ",2016 +"2016-12-25","Christmas Day","SZ",2016 +"2016-12-26","Boxing Day","SZ",2016 +"2017-01-01","New Year's Day","SZ",2017 +"2017-04-14","Good Friday","SZ",2017 +"2017-04-17","Easter Monday","SZ",2017 +"2017-04-19","King's Birthday","SZ",2017 +"2017-04-25","National Flag Day","SZ",2017 +"2017-05-01","Worker's Day","SZ",2017 +"2017-05-25","Ascension Day","SZ",2017 +"2017-07-22","Birthday of Late King Sobhuza","SZ",2017 +"2017-09-06","Independence Day","SZ",2017 +"2017-12-25","Christmas Day","SZ",2017 +"2017-12-26","Boxing Day","SZ",2017 +"2018-01-01","New Year's Day","SZ",2018 +"2018-03-30","Good Friday","SZ",2018 +"2018-04-02","Easter Monday","SZ",2018 +"2018-04-19","King's Birthday","SZ",2018 +"2018-04-25","National Flag Day","SZ",2018 +"2018-05-01","Worker's Day","SZ",2018 +"2018-05-10","Ascension Day","SZ",2018 +"2018-07-22","Birthday of Late King Sobhuza","SZ",2018 +"2018-09-06","Independence Day","SZ",2018 +"2018-12-25","Christmas Day","SZ",2018 +"2018-12-26","Boxing Day","SZ",2018 +"2019-01-01","New Year's Day","SZ",2019 +"2019-04-19","Good Friday","SZ",2019 +"2019-04-19","King's Birthday","SZ",2019 +"2019-04-22","Easter Monday","SZ",2019 +"2019-04-25","National Flag Day","SZ",2019 +"2019-05-01","Worker's Day","SZ",2019 +"2019-05-30","Ascension Day","SZ",2019 +"2019-07-22","Birthday of Late King Sobhuza","SZ",2019 +"2019-09-06","Independence Day","SZ",2019 +"2019-12-25","Christmas Day","SZ",2019 +"2019-12-26","Boxing Day","SZ",2019 +"2020-01-01","New Year's Day","SZ",2020 +"2020-04-10","Good Friday","SZ",2020 +"2020-04-13","Easter Monday","SZ",2020 +"2020-04-19","King's Birthday","SZ",2020 +"2020-04-25","National Flag Day","SZ",2020 +"2020-05-01","Worker's Day","SZ",2020 +"2020-05-21","Ascension Day","SZ",2020 +"2020-07-22","Birthday of Late King Sobhuza","SZ",2020 +"2020-09-06","Independence Day","SZ",2020 +"2020-12-25","Christmas Day","SZ",2020 +"2020-12-26","Boxing Day","SZ",2020 +"2021-01-01","New Year's Day","SZ",2021 +"2021-04-02","Good Friday","SZ",2021 +"2021-04-05","Easter Monday","SZ",2021 +"2021-04-19","King's Birthday","SZ",2021 +"2021-04-25","National Flag Day","SZ",2021 +"2021-04-26","National Flag Day (Observed)","SZ",2021 +"2021-05-01","Worker's Day","SZ",2021 +"2021-05-13","Ascension Day","SZ",2021 +"2021-07-22","Birthday of Late King Sobhuza","SZ",2021 +"2021-09-06","Independence Day","SZ",2021 +"2021-12-25","Christmas Day","SZ",2021 +"2021-12-26","Boxing Day","SZ",2021 +"2021-12-27","Boxing Day (Observed)","SZ",2021 +"2022-01-01","New Year's Day","SZ",2022 +"2022-04-15","Good Friday","SZ",2022 +"2022-04-18","Easter Monday","SZ",2022 +"2022-04-19","King's Birthday","SZ",2022 +"2022-04-25","National Flag Day","SZ",2022 +"2022-05-01","Worker's Day","SZ",2022 +"2022-05-02","Worker's Day (Observed)","SZ",2022 +"2022-05-26","Ascension Day","SZ",2022 +"2022-07-22","Birthday of Late King Sobhuza","SZ",2022 +"2022-09-06","Independence Day","SZ",2022 +"2022-12-25","Christmas Day","SZ",2022 +"2022-12-26","Boxing Day","SZ",2022 +"2022-12-27","Christmas Day (Observed)","SZ",2022 +"2023-01-01","New Year's Day","SZ",2023 +"2023-01-02","New Year's Day (Observed)","SZ",2023 +"2023-04-07","Good Friday","SZ",2023 +"2023-04-10","Easter Monday","SZ",2023 +"2023-04-19","King's Birthday","SZ",2023 +"2023-04-25","National Flag Day","SZ",2023 +"2023-05-01","Worker's Day","SZ",2023 +"2023-05-18","Ascension Day","SZ",2023 +"2023-07-22","Birthday of Late King Sobhuza","SZ",2023 +"2023-09-06","Independence Day","SZ",2023 +"2023-12-25","Christmas Day","SZ",2023 +"2023-12-26","Boxing Day","SZ",2023 +"2024-01-01","New Year's Day","SZ",2024 +"2024-03-29","Good Friday","SZ",2024 +"2024-04-01","Easter Monday","SZ",2024 +"2024-04-19","King's Birthday","SZ",2024 +"2024-04-25","National Flag Day","SZ",2024 +"2024-05-01","Worker's Day","SZ",2024 +"2024-05-09","Ascension Day","SZ",2024 +"2024-07-22","Birthday of Late King Sobhuza","SZ",2024 +"2024-09-06","Independence Day","SZ",2024 +"2024-12-25","Christmas Day","SZ",2024 +"2024-12-26","Boxing Day","SZ",2024 +"2025-01-01","New Year's Day","SZ",2025 +"2025-04-18","Good Friday","SZ",2025 +"2025-04-19","King's Birthday","SZ",2025 +"2025-04-21","Easter Monday","SZ",2025 +"2025-04-25","National Flag Day","SZ",2025 +"2025-05-01","Worker's Day","SZ",2025 +"2025-05-29","Ascension Day","SZ",2025 +"2025-07-22","Birthday of Late King Sobhuza","SZ",2025 +"2025-09-06","Independence Day","SZ",2025 +"2025-12-25","Christmas Day","SZ",2025 +"2025-12-26","Boxing Day","SZ",2025 +"2026-01-01","New Year's Day","SZ",2026 +"2026-04-03","Good Friday","SZ",2026 +"2026-04-06","Easter Monday","SZ",2026 +"2026-04-19","King's Birthday","SZ",2026 +"2026-04-20","King's Birthday (Observed)","SZ",2026 +"2026-04-25","National Flag Day","SZ",2026 +"2026-05-01","Worker's Day","SZ",2026 +"2026-05-14","Ascension Day","SZ",2026 +"2026-07-22","Birthday of Late King Sobhuza","SZ",2026 +"2026-09-06","Independence Day","SZ",2026 +"2026-09-07","Independence Day (Observed)","SZ",2026 +"2026-12-25","Christmas Day","SZ",2026 +"2026-12-26","Boxing Day","SZ",2026 +"2027-01-01","New Year's Day","SZ",2027 +"2027-03-26","Good Friday","SZ",2027 +"2027-03-29","Easter Monday","SZ",2027 +"2027-04-19","King's Birthday","SZ",2027 +"2027-04-25","National Flag Day","SZ",2027 +"2027-04-26","National Flag Day (Observed)","SZ",2027 +"2027-05-01","Worker's Day","SZ",2027 +"2027-05-06","Ascension Day","SZ",2027 +"2027-07-22","Birthday of Late King Sobhuza","SZ",2027 +"2027-09-06","Independence Day","SZ",2027 +"2027-12-25","Christmas Day","SZ",2027 +"2027-12-26","Boxing Day","SZ",2027 +"2027-12-27","Boxing Day (Observed)","SZ",2027 +"2028-01-01","New Year's Day","SZ",2028 +"2028-04-14","Good Friday","SZ",2028 +"2028-04-17","Easter Monday","SZ",2028 +"2028-04-19","King's Birthday","SZ",2028 +"2028-04-25","National Flag Day","SZ",2028 +"2028-05-01","Worker's Day","SZ",2028 +"2028-05-25","Ascension Day","SZ",2028 +"2028-07-22","Birthday of Late King Sobhuza","SZ",2028 +"2028-09-06","Independence Day","SZ",2028 +"2028-12-25","Christmas Day","SZ",2028 +"2028-12-26","Boxing Day","SZ",2028 +"2029-01-01","New Year's Day","SZ",2029 +"2029-03-30","Good Friday","SZ",2029 +"2029-04-02","Easter Monday","SZ",2029 +"2029-04-19","King's Birthday","SZ",2029 +"2029-04-25","National Flag Day","SZ",2029 +"2029-05-01","Worker's Day","SZ",2029 +"2029-05-10","Ascension Day","SZ",2029 +"2029-07-22","Birthday of Late King Sobhuza","SZ",2029 +"2029-07-23","Birthday of Late King Sobhuza (Observed)","SZ",2029 +"2029-09-06","Independence Day","SZ",2029 +"2029-12-25","Christmas Day","SZ",2029 +"2029-12-26","Boxing Day","SZ",2029 +"2030-01-01","New Year's Day","SZ",2030 +"2030-04-19","Good Friday","SZ",2030 +"2030-04-19","King's Birthday","SZ",2030 +"2030-04-22","Easter Monday","SZ",2030 +"2030-04-25","National Flag Day","SZ",2030 +"2030-05-01","Worker's Day","SZ",2030 +"2030-05-30","Ascension Day","SZ",2030 +"2030-07-22","Birthday of Late King Sobhuza","SZ",2030 +"2030-09-06","Independence Day","SZ",2030 +"2030-12-25","Christmas Day","SZ",2030 +"2030-12-26","Boxing Day","SZ",2030 +"2031-01-01","New Year's Day","SZ",2031 +"2031-04-11","Good Friday","SZ",2031 +"2031-04-14","Easter Monday","SZ",2031 +"2031-04-19","King's Birthday","SZ",2031 +"2031-04-25","National Flag Day","SZ",2031 +"2031-05-01","Worker's Day","SZ",2031 +"2031-05-22","Ascension Day","SZ",2031 +"2031-07-22","Birthday of Late King Sobhuza","SZ",2031 +"2031-09-06","Independence Day","SZ",2031 +"2031-12-25","Christmas Day","SZ",2031 +"2031-12-26","Boxing Day","SZ",2031 +"2032-01-01","New Year's Day","SZ",2032 +"2032-03-26","Good Friday","SZ",2032 +"2032-03-29","Easter Monday","SZ",2032 +"2032-04-19","King's Birthday","SZ",2032 +"2032-04-25","National Flag Day","SZ",2032 +"2032-04-26","National Flag Day (Observed)","SZ",2032 +"2032-05-01","Worker's Day","SZ",2032 +"2032-05-06","Ascension Day","SZ",2032 +"2032-07-22","Birthday of Late King Sobhuza","SZ",2032 +"2032-09-06","Independence Day","SZ",2032 +"2032-12-25","Christmas Day","SZ",2032 +"2032-12-26","Boxing Day","SZ",2032 +"2032-12-27","Boxing Day (Observed)","SZ",2032 +"2033-01-01","New Year's Day","SZ",2033 +"2033-04-15","Good Friday","SZ",2033 +"2033-04-18","Easter Monday","SZ",2033 +"2033-04-19","King's Birthday","SZ",2033 +"2033-04-25","National Flag Day","SZ",2033 +"2033-05-01","Worker's Day","SZ",2033 +"2033-05-02","Worker's Day (Observed)","SZ",2033 +"2033-05-26","Ascension Day","SZ",2033 +"2033-07-22","Birthday of Late King Sobhuza","SZ",2033 +"2033-09-06","Independence Day","SZ",2033 +"2033-12-25","Christmas Day","SZ",2033 +"2033-12-26","Boxing Day","SZ",2033 +"2033-12-27","Christmas Day (Observed)","SZ",2033 +"2034-01-01","New Year's Day","SZ",2034 +"2034-01-02","New Year's Day (Observed)","SZ",2034 +"2034-04-07","Good Friday","SZ",2034 +"2034-04-10","Easter Monday","SZ",2034 +"2034-04-19","King's Birthday","SZ",2034 +"2034-04-25","National Flag Day","SZ",2034 +"2034-05-01","Worker's Day","SZ",2034 +"2034-05-18","Ascension Day","SZ",2034 +"2034-07-22","Birthday of Late King Sobhuza","SZ",2034 +"2034-09-06","Independence Day","SZ",2034 +"2034-12-25","Christmas Day","SZ",2034 +"2034-12-26","Boxing Day","SZ",2034 +"2035-01-01","New Year's Day","SZ",2035 +"2035-03-23","Good Friday","SZ",2035 +"2035-03-26","Easter Monday","SZ",2035 +"2035-04-19","King's Birthday","SZ",2035 +"2035-04-25","National Flag Day","SZ",2035 +"2035-05-01","Worker's Day","SZ",2035 +"2035-05-03","Ascension Day","SZ",2035 +"2035-07-22","Birthday of Late King Sobhuza","SZ",2035 +"2035-07-23","Birthday of Late King Sobhuza (Observed)","SZ",2035 +"2035-09-06","Independence Day","SZ",2035 +"2035-12-25","Christmas Day","SZ",2035 +"2035-12-26","Boxing Day","SZ",2035 +"2036-01-01","New Year's Day","SZ",2036 +"2036-04-11","Good Friday","SZ",2036 +"2036-04-14","Easter Monday","SZ",2036 +"2036-04-19","King's Birthday","SZ",2036 +"2036-04-25","National Flag Day","SZ",2036 +"2036-05-01","Worker's Day","SZ",2036 +"2036-05-22","Ascension Day","SZ",2036 +"2036-07-22","Birthday of Late King Sobhuza","SZ",2036 +"2036-09-06","Independence Day","SZ",2036 +"2036-12-25","Christmas Day","SZ",2036 +"2036-12-26","Boxing Day","SZ",2036 +"2037-01-01","New Year's Day","SZ",2037 +"2037-04-03","Good Friday","SZ",2037 +"2037-04-06","Easter Monday","SZ",2037 +"2037-04-19","King's Birthday","SZ",2037 +"2037-04-20","King's Birthday (Observed)","SZ",2037 +"2037-04-25","National Flag Day","SZ",2037 +"2037-05-01","Worker's Day","SZ",2037 +"2037-05-14","Ascension Day","SZ",2037 +"2037-07-22","Birthday of Late King Sobhuza","SZ",2037 +"2037-09-06","Independence Day","SZ",2037 +"2037-09-07","Independence Day (Observed)","SZ",2037 +"2037-12-25","Christmas Day","SZ",2037 +"2037-12-26","Boxing Day","SZ",2037 +"2038-01-01","New Year's Day","SZ",2038 +"2038-04-19","King's Birthday","SZ",2038 +"2038-04-23","Good Friday","SZ",2038 +"2038-04-25","National Flag Day","SZ",2038 +"2038-04-26","Easter Monday","SZ",2038 +"2038-04-27","National Flag Day (Observed)","SZ",2038 +"2038-05-01","Worker's Day","SZ",2038 +"2038-06-03","Ascension Day","SZ",2038 +"2038-07-22","Birthday of Late King Sobhuza","SZ",2038 +"2038-09-06","Independence Day","SZ",2038 +"2038-12-25","Christmas Day","SZ",2038 +"2038-12-26","Boxing Day","SZ",2038 +"2038-12-27","Boxing Day (Observed)","SZ",2038 +"2039-01-01","New Year's Day","SZ",2039 +"2039-04-08","Good Friday","SZ",2039 +"2039-04-11","Easter Monday","SZ",2039 +"2039-04-19","King's Birthday","SZ",2039 +"2039-04-25","National Flag Day","SZ",2039 +"2039-05-01","Worker's Day","SZ",2039 +"2039-05-02","Worker's Day (Observed)","SZ",2039 +"2039-05-19","Ascension Day","SZ",2039 +"2039-07-22","Birthday of Late King Sobhuza","SZ",2039 +"2039-09-06","Independence Day","SZ",2039 +"2039-12-25","Christmas Day","SZ",2039 +"2039-12-26","Boxing Day","SZ",2039 +"2039-12-27","Christmas Day (Observed)","SZ",2039 +"2040-01-01","New Year's Day","SZ",2040 +"2040-01-02","New Year's Day (Observed)","SZ",2040 +"2040-03-30","Good Friday","SZ",2040 +"2040-04-02","Easter Monday","SZ",2040 +"2040-04-19","King's Birthday","SZ",2040 +"2040-04-25","National Flag Day","SZ",2040 +"2040-05-01","Worker's Day","SZ",2040 +"2040-05-10","Ascension Day","SZ",2040 +"2040-07-22","Birthday of Late King Sobhuza","SZ",2040 +"2040-07-23","Birthday of Late King Sobhuza (Observed)","SZ",2040 +"2040-09-06","Independence Day","SZ",2040 +"2040-12-25","Christmas Day","SZ",2040 +"2040-12-26","Boxing Day","SZ",2040 +"2041-01-01","New Year's Day","SZ",2041 +"2041-04-19","Good Friday","SZ",2041 +"2041-04-19","King's Birthday","SZ",2041 +"2041-04-22","Easter Monday","SZ",2041 +"2041-04-25","National Flag Day","SZ",2041 +"2041-05-01","Worker's Day","SZ",2041 +"2041-05-30","Ascension Day","SZ",2041 +"2041-07-22","Birthday of Late King Sobhuza","SZ",2041 +"2041-09-06","Independence Day","SZ",2041 +"2041-12-25","Christmas Day","SZ",2041 +"2041-12-26","Boxing Day","SZ",2041 +"2042-01-01","New Year's Day","SZ",2042 +"2042-04-04","Good Friday","SZ",2042 +"2042-04-07","Easter Monday","SZ",2042 +"2042-04-19","King's Birthday","SZ",2042 +"2042-04-25","National Flag Day","SZ",2042 +"2042-05-01","Worker's Day","SZ",2042 +"2042-05-15","Ascension Day","SZ",2042 +"2042-07-22","Birthday of Late King Sobhuza","SZ",2042 +"2042-09-06","Independence Day","SZ",2042 +"2042-12-25","Christmas Day","SZ",2042 +"2042-12-26","Boxing Day","SZ",2042 +"2043-01-01","New Year's Day","SZ",2043 +"2043-03-27","Good Friday","SZ",2043 +"2043-03-30","Easter Monday","SZ",2043 +"2043-04-19","King's Birthday","SZ",2043 +"2043-04-20","King's Birthday (Observed)","SZ",2043 +"2043-04-25","National Flag Day","SZ",2043 +"2043-05-01","Worker's Day","SZ",2043 +"2043-05-07","Ascension Day","SZ",2043 +"2043-07-22","Birthday of Late King Sobhuza","SZ",2043 +"2043-09-06","Independence Day","SZ",2043 +"2043-09-07","Independence Day (Observed)","SZ",2043 +"2043-12-25","Christmas Day","SZ",2043 +"2043-12-26","Boxing Day","SZ",2043 +"2044-01-01","New Year's Day","SZ",2044 +"2044-04-15","Good Friday","SZ",2044 +"2044-04-18","Easter Monday","SZ",2044 +"2044-04-19","King's Birthday","SZ",2044 +"2044-04-25","National Flag Day","SZ",2044 +"2044-05-01","Worker's Day","SZ",2044 +"2044-05-02","Worker's Day (Observed)","SZ",2044 +"2044-05-26","Ascension Day","SZ",2044 +"2044-07-22","Birthday of Late King Sobhuza","SZ",2044 +"2044-09-06","Independence Day","SZ",2044 +"2044-12-25","Christmas Day","SZ",2044 +"2044-12-26","Boxing Day","SZ",2044 +"2044-12-27","Christmas Day (Observed)","SZ",2044 +"1995-01-01","New Year's Day","TH",1995 +"1995-01-02","New Year's Day (in lieu)","TH",1995 +"1995-01-03","New Year's Eve (in lieu)","TH",1995 +"1995-02-14","Makha Bucha","TH",1995 +"1995-04-06","Chakri Memorial Day","TH",1995 +"1995-04-12","Songkran Festival","TH",1995 +"1995-04-13","Songkran Festival","TH",1995 +"1995-04-14","Songkran Festival","TH",1995 +"1995-05-01","National Labour Day","TH",1995 +"1995-05-05","Coronation Day","TH",1995 +"1995-05-13","Royal Ploughing Ceremony","TH",1995 +"1995-05-13","Visakha Bucha","TH",1995 +"1995-05-15","Royal Ploughing Ceremony (in lieu)","TH",1995 +"1995-05-15","Visakha Bucha (in lieu)","TH",1995 +"1995-07-11","Asarnha Bucha","TH",1995 +"1995-07-12","Buddhist Lent Day","TH",1995 +"1995-08-12","HM Queen Sirikit's Birthday","TH",1995 +"1995-08-12","National Mother's Day","TH",1995 +"1995-08-14","HM Queen Sirikit's Birthday (in lieu)","TH",1995 +"1995-08-14","National Mother's Day (in lieu)","TH",1995 +"1995-10-23","HM King Chulalongkorn Memorial Day","TH",1995 +"1995-12-05","HM King Bhumibol Adulyadej's Birthday","TH",1995 +"1995-12-05","National Day","TH",1995 +"1995-12-05","National Father's Day","TH",1995 +"1995-12-10","Constitution Day","TH",1995 +"1995-12-11","Constitution Day (in lieu)","TH",1995 +"1995-12-31","New Year's Eve","TH",1995 +"1996-01-01","New Year's Day","TH",1996 +"1996-01-02","New Year's Eve (in lieu)","TH",1996 +"1996-03-03","Makha Bucha","TH",1996 +"1996-03-04","Makha Bucha (in lieu)","TH",1996 +"1996-04-06","Chakri Memorial Day","TH",1996 +"1996-04-08","Chakri Memorial Day (in lieu)","TH",1996 +"1996-04-12","Songkran Festival","TH",1996 +"1996-04-13","Songkran Festival","TH",1996 +"1996-04-14","Songkran Festival","TH",1996 +"1996-04-15","Songkran Festival (in lieu)","TH",1996 +"1996-05-01","National Labour Day","TH",1996 +"1996-05-05","Coronation Day","TH",1996 +"1996-05-06","Coronation Day (in lieu)","TH",1996 +"1996-05-13","Royal Ploughing Ceremony","TH",1996 +"1996-05-31","Visakha Bucha","TH",1996 +"1996-06-10","HM King Bhumibol Adulyadej's Golden Jubilee","TH",1996 +"1996-07-29","Asarnha Bucha","TH",1996 +"1996-07-30","Buddhist Lent Day","TH",1996 +"1996-08-12","HM Queen Sirikit's Birthday","TH",1996 +"1996-08-12","National Mother's Day","TH",1996 +"1996-10-23","HM King Chulalongkorn Memorial Day","TH",1996 +"1996-12-05","HM King Bhumibol Adulyadej's Birthday","TH",1996 +"1996-12-05","National Day","TH",1996 +"1996-12-05","National Father's Day","TH",1996 +"1996-12-10","Constitution Day","TH",1996 +"1996-12-31","New Year's Eve","TH",1996 +"1997-01-01","New Year's Day","TH",1997 +"1997-02-21","Makha Bucha","TH",1997 +"1997-04-06","Chakri Memorial Day","TH",1997 +"1997-04-07","Chakri Memorial Day (in lieu)","TH",1997 +"1997-04-12","Songkran Festival","TH",1997 +"1997-04-13","Songkran Festival","TH",1997 +"1997-04-14","Songkran Festival","TH",1997 +"1997-04-15","Songkran Festival (in lieu)","TH",1997 +"1997-05-01","National Labour Day","TH",1997 +"1997-05-05","Coronation Day","TH",1997 +"1997-05-13","Royal Ploughing Ceremony","TH",1997 +"1997-05-20","Visakha Bucha","TH",1997 +"1997-07-19","Asarnha Bucha","TH",1997 +"1997-07-20","Buddhist Lent Day","TH",1997 +"1997-07-21","Asarnha Bucha (in lieu)","TH",1997 +"1997-08-12","HM Queen Sirikit's Birthday","TH",1997 +"1997-08-12","National Mother's Day","TH",1997 +"1997-10-23","HM King Chulalongkorn Memorial Day","TH",1997 +"1997-12-05","HM King Bhumibol Adulyadej's Birthday","TH",1997 +"1997-12-05","National Day","TH",1997 +"1997-12-05","National Father's Day","TH",1997 +"1997-12-10","Constitution Day","TH",1997 +"1997-12-31","New Year's Eve","TH",1997 +"1998-01-01","New Year's Day","TH",1998 +"1998-02-11","Makha Bucha","TH",1998 +"1998-04-06","Chakri Memorial Day","TH",1998 +"1998-04-13","Songkran Festival","TH",1998 +"1998-04-14","Songkran Festival","TH",1998 +"1998-04-15","Songkran Festival","TH",1998 +"1998-05-01","National Labour Day","TH",1998 +"1998-05-05","Coronation Day","TH",1998 +"1998-05-10","Visakha Bucha","TH",1998 +"1998-05-11","Special In Lieu Holiday","TH",1998 +"1998-05-13","Royal Ploughing Ceremony","TH",1998 +"1998-07-08","Asarnha Bucha","TH",1998 +"1998-07-09","Buddhist Lent Day","TH",1998 +"1998-08-12","HM Queen Sirikit's Birthday","TH",1998 +"1998-08-12","National Mother's Day","TH",1998 +"1998-10-23","HM King Chulalongkorn Memorial Day","TH",1998 +"1998-12-05","HM King Bhumibol Adulyadej's Birthday","TH",1998 +"1998-12-05","National Day","TH",1998 +"1998-12-05","National Father's Day","TH",1998 +"1998-12-07","Special In Lieu Holiday","TH",1998 +"1998-12-10","Constitution Day","TH",1998 +"1998-12-31","New Year's Eve","TH",1998 +"1999-01-01","New Year's Day","TH",1999 +"1999-03-01","Makha Bucha","TH",1999 +"1999-04-06","Chakri Memorial Day","TH",1999 +"1999-04-13","Songkran Festival","TH",1999 +"1999-04-14","Songkran Festival","TH",1999 +"1999-04-15","Songkran Festival","TH",1999 +"1999-05-01","National Labour Day","TH",1999 +"1999-05-03","Special In Lieu Holiday","TH",1999 +"1999-05-05","Coronation Day","TH",1999 +"1999-05-29","Visakha Bucha","TH",1999 +"1999-05-31","Special In Lieu Holiday","TH",1999 +"1999-07-27","Asarnha Bucha","TH",1999 +"1999-07-28","Buddhist Lent Day","TH",1999 +"1999-08-12","HM Queen Sirikit's Birthday","TH",1999 +"1999-08-12","National Mother's Day","TH",1999 +"1999-10-23","HM King Chulalongkorn Memorial Day","TH",1999 +"1999-10-25","Special In Lieu Holiday","TH",1999 +"1999-12-05","HM King Bhumibol Adulyadej's Birthday","TH",1999 +"1999-12-05","National Day","TH",1999 +"1999-12-05","National Father's Day","TH",1999 +"1999-12-06","Special In Lieu Holiday","TH",1999 +"1999-12-10","Constitution Day","TH",1999 +"1999-12-31","New Year's Eve","TH",1999 +"2000-01-01","New Year's Day","TH",2000 +"2000-01-03","Special In Lieu Holiday","TH",2000 +"2000-02-19","Makha Bucha","TH",2000 +"2000-02-21","Special In Lieu Holiday","TH",2000 +"2000-04-06","Chakri Memorial Day","TH",2000 +"2000-04-13","Songkran Festival","TH",2000 +"2000-04-14","Songkran Festival","TH",2000 +"2000-04-15","Songkran Festival","TH",2000 +"2000-05-01","National Labour Day","TH",2000 +"2000-05-05","Coronation Day","TH",2000 +"2000-05-15","Royal Ploughing Ceremony","TH",2000 +"2000-05-17","Visakha Bucha","TH",2000 +"2000-07-16","Asarnha Bucha","TH",2000 +"2000-07-17","Buddhist Lent Day","TH",2000 +"2000-08-12","HM Queen Sirikit's Birthday","TH",2000 +"2000-08-12","National Mother's Day","TH",2000 +"2000-08-14","Special In Lieu Holiday","TH",2000 +"2000-10-23","HM King Chulalongkorn Memorial Day","TH",2000 +"2000-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2000 +"2000-12-05","National Day","TH",2000 +"2000-12-05","National Father's Day","TH",2000 +"2000-12-10","Constitution Day","TH",2000 +"2000-12-11","Special In Lieu Holiday","TH",2000 +"2000-12-29","Thai Election Day","TH",2000 +"2000-12-31","New Year's Eve","TH",2000 +"2001-01-01","New Year's Day","TH",2001 +"2001-01-02","New Year's Eve (in lieu)","TH",2001 +"2001-02-08","Makha Bucha","TH",2001 +"2001-04-06","Chakri Memorial Day","TH",2001 +"2001-04-13","Songkran Festival","TH",2001 +"2001-04-14","Songkran Festival","TH",2001 +"2001-04-15","Songkran Festival","TH",2001 +"2001-04-16","Songkran Festival (in lieu)","TH",2001 +"2001-05-01","National Labour Day","TH",2001 +"2001-05-05","Coronation Day","TH",2001 +"2001-05-07","Coronation Day (in lieu)","TH",2001 +"2001-05-07","Visakha Bucha","TH",2001 +"2001-05-16","Royal Ploughing Ceremony","TH",2001 +"2001-07-05","Asarnha Bucha","TH",2001 +"2001-07-06","Buddhist Lent Day","TH",2001 +"2001-08-12","HM Queen Sirikit's Birthday","TH",2001 +"2001-08-12","National Mother's Day","TH",2001 +"2001-08-13","HM Queen Sirikit's Birthday (in lieu)","TH",2001 +"2001-08-13","National Mother's Day (in lieu)","TH",2001 +"2001-10-23","HM King Chulalongkorn Memorial Day","TH",2001 +"2001-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2001 +"2001-12-05","National Day","TH",2001 +"2001-12-05","National Father's Day","TH",2001 +"2001-12-10","Constitution Day","TH",2001 +"2001-12-31","New Year's Eve","TH",2001 +"2002-01-01","New Year's Day","TH",2002 +"2002-02-26","Makha Bucha","TH",2002 +"2002-04-06","Chakri Memorial Day","TH",2002 +"2002-04-08","Chakri Memorial Day (in lieu)","TH",2002 +"2002-04-13","Songkran Festival","TH",2002 +"2002-04-14","Songkran Festival","TH",2002 +"2002-04-15","Songkran Festival","TH",2002 +"2002-04-16","Songkran Festival (in lieu)","TH",2002 +"2002-05-01","National Labour Day","TH",2002 +"2002-05-05","Coronation Day","TH",2002 +"2002-05-06","Coronation Day (in lieu)","TH",2002 +"2002-05-09","Royal Ploughing Ceremony","TH",2002 +"2002-05-26","Visakha Bucha","TH",2002 +"2002-05-27","Visakha Bucha (in lieu)","TH",2002 +"2002-07-24","Asarnha Bucha","TH",2002 +"2002-07-25","Buddhist Lent Day","TH",2002 +"2002-08-12","HM Queen Sirikit's Birthday","TH",2002 +"2002-08-12","National Mother's Day","TH",2002 +"2002-10-23","HM King Chulalongkorn Memorial Day","TH",2002 +"2002-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2002 +"2002-12-05","National Day","TH",2002 +"2002-12-05","National Father's Day","TH",2002 +"2002-12-10","Constitution Day","TH",2002 +"2002-12-31","New Year's Eve","TH",2002 +"2003-01-01","New Year's Day","TH",2003 +"2003-02-16","Makha Bucha","TH",2003 +"2003-02-17","Makha Bucha (in lieu)","TH",2003 +"2003-04-06","Chakri Memorial Day","TH",2003 +"2003-04-07","Chakri Memorial Day (in lieu)","TH",2003 +"2003-04-13","Songkran Festival","TH",2003 +"2003-04-14","Songkran Festival","TH",2003 +"2003-04-15","Songkran Festival","TH",2003 +"2003-05-01","National Labour Day","TH",2003 +"2003-05-05","Coronation Day","TH",2003 +"2003-05-08","Royal Ploughing Ceremony","TH",2003 +"2003-05-15","Visakha Bucha","TH",2003 +"2003-07-13","Asarnha Bucha","TH",2003 +"2003-07-14","Buddhist Lent Day","TH",2003 +"2003-07-15","Asarnha Bucha (in lieu)","TH",2003 +"2003-08-12","HM Queen Sirikit's Birthday","TH",2003 +"2003-08-12","National Mother's Day","TH",2003 +"2003-10-23","HM King Chulalongkorn Memorial Day","TH",2003 +"2003-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2003 +"2003-12-05","National Day","TH",2003 +"2003-12-05","National Father's Day","TH",2003 +"2003-12-10","Constitution Day","TH",2003 +"2003-12-31","New Year's Eve","TH",2003 +"2004-01-01","New Year's Day","TH",2004 +"2004-03-05","Makha Bucha","TH",2004 +"2004-04-06","Chakri Memorial Day","TH",2004 +"2004-04-13","Songkran Festival","TH",2004 +"2004-04-14","Songkran Festival","TH",2004 +"2004-04-15","Songkran Festival","TH",2004 +"2004-05-01","National Labour Day","TH",2004 +"2004-05-03","National Labour Day (in lieu)","TH",2004 +"2004-05-05","Coronation Day","TH",2004 +"2004-05-07","Royal Ploughing Ceremony","TH",2004 +"2004-06-02","Visakha Bucha","TH",2004 +"2004-07-31","Asarnha Bucha","TH",2004 +"2004-08-01","Buddhist Lent Day","TH",2004 +"2004-08-02","Asarnha Bucha (in lieu)","TH",2004 +"2004-08-12","HM Queen Sirikit's Birthday","TH",2004 +"2004-08-12","National Mother's Day","TH",2004 +"2004-10-23","HM King Chulalongkorn Memorial Day","TH",2004 +"2004-10-25","HM King Chulalongkorn Memorial Day (in lieu)","TH",2004 +"2004-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2004 +"2004-12-05","National Day","TH",2004 +"2004-12-05","National Father's Day","TH",2004 +"2004-12-06","HM King Bhumibol Adulyadej's Birthday (in lieu)","TH",2004 +"2004-12-06","National Day (in lieu)","TH",2004 +"2004-12-06","National Father's Day (in lieu)","TH",2004 +"2004-12-10","Constitution Day","TH",2004 +"2004-12-31","New Year's Eve","TH",2004 +"2005-01-01","New Year's Day","TH",2005 +"2005-01-03","New Year's Day (in lieu)","TH",2005 +"2005-02-23","Makha Bucha","TH",2005 +"2005-04-06","Chakri Memorial Day","TH",2005 +"2005-04-13","Songkran Festival","TH",2005 +"2005-04-14","Songkran Festival","TH",2005 +"2005-04-15","Songkran Festival","TH",2005 +"2005-05-01","National Labour Day","TH",2005 +"2005-05-02","National Labour Day (in lieu)","TH",2005 +"2005-05-05","Coronation Day","TH",2005 +"2005-05-11","Royal Ploughing Ceremony","TH",2005 +"2005-05-22","Visakha Bucha","TH",2005 +"2005-05-23","Visakha Bucha (in lieu)","TH",2005 +"2005-07-20","Asarnha Bucha","TH",2005 +"2005-07-21","Buddhist Lent Day","TH",2005 +"2005-08-12","HM Queen Sirikit's Birthday","TH",2005 +"2005-08-12","National Mother's Day","TH",2005 +"2005-10-23","HM King Chulalongkorn Memorial Day","TH",2005 +"2005-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2005 +"2005-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2005 +"2005-12-05","National Day","TH",2005 +"2005-12-05","National Father's Day","TH",2005 +"2005-12-10","Constitution Day","TH",2005 +"2005-12-12","Constitution Day (in lieu)","TH",2005 +"2005-12-31","New Year's Eve","TH",2005 +"2006-01-01","New Year's Day","TH",2006 +"2006-01-02","New Year's Day (in lieu)","TH",2006 +"2006-01-03","New Year's Eve (in lieu)","TH",2006 +"2006-02-12","Makha Bucha","TH",2006 +"2006-02-13","Makha Bucha (in lieu)","TH",2006 +"2006-04-06","Chakri Memorial Day","TH",2006 +"2006-04-13","Songkran Festival","TH",2006 +"2006-04-14","Songkran Festival","TH",2006 +"2006-04-15","Songkran Festival","TH",2006 +"2006-04-17","Songkran Festival (in lieu)","TH",2006 +"2006-04-19","Thai Election Day","TH",2006 +"2006-05-01","National Labour Day","TH",2006 +"2006-05-05","Coronation Day","TH",2006 +"2006-05-11","Royal Ploughing Ceremony","TH",2006 +"2006-05-11","Visakha Bucha","TH",2006 +"2006-06-09","HM King Bhumibol Adulyadej's 60th Anniversary of Accession Event","TH",2006 +"2006-06-12","HM King Bhumibol Adulyadej's 60th Anniversary of Accession Event","TH",2006 +"2006-06-13","HM King Bhumibol Adulyadej's 60th Anniversary of Accession Event","TH",2006 +"2006-07-10","Asarnha Bucha","TH",2006 +"2006-07-11","Buddhist Lent Day","TH",2006 +"2006-08-12","HM Queen Sirikit's Birthday","TH",2006 +"2006-08-12","National Mother's Day","TH",2006 +"2006-08-14","HM Queen Sirikit's Birthday (in lieu)","TH",2006 +"2006-08-14","National Mother's Day (in lieu)","TH",2006 +"2006-09-20","Emergency Lockdown (Thai Military Coup d'etat)","TH",2006 +"2006-10-23","HM King Chulalongkorn Memorial Day","TH",2006 +"2006-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2006 +"2006-12-05","National Day","TH",2006 +"2006-12-05","National Father's Day","TH",2006 +"2006-12-10","Constitution Day","TH",2006 +"2006-12-11","Constitution Day (in lieu)","TH",2006 +"2006-12-31","New Year's Eve","TH",2006 +"2007-01-01","New Year's Day","TH",2007 +"2007-01-02","New Year's Eve (in lieu)","TH",2007 +"2007-03-03","Makha Bucha","TH",2007 +"2007-03-05","Makha Bucha (in lieu)","TH",2007 +"2007-04-06","Chakri Memorial Day","TH",2007 +"2007-04-13","Songkran Festival","TH",2007 +"2007-04-14","Songkran Festival","TH",2007 +"2007-04-15","Songkran Festival","TH",2007 +"2007-04-16","Songkran Festival (in lieu)","TH",2007 +"2007-05-01","National Labour Day","TH",2007 +"2007-05-05","Coronation Day","TH",2007 +"2007-05-07","Coronation Day (in lieu)","TH",2007 +"2007-05-10","Royal Ploughing Ceremony","TH",2007 +"2007-05-31","Visakha Bucha","TH",2007 +"2007-07-29","Asarnha Bucha","TH",2007 +"2007-07-30","Buddhist Lent Day","TH",2007 +"2007-07-31","Asarnha Bucha (in lieu)","TH",2007 +"2007-08-12","HM Queen Sirikit's Birthday","TH",2007 +"2007-08-12","National Mother's Day","TH",2007 +"2007-08-13","HM Queen Sirikit's Birthday (in lieu)","TH",2007 +"2007-08-13","National Mother's Day (in lieu)","TH",2007 +"2007-10-23","HM King Chulalongkorn Memorial Day","TH",2007 +"2007-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2007 +"2007-12-05","National Day","TH",2007 +"2007-12-05","National Father's Day","TH",2007 +"2007-12-10","Constitution Day","TH",2007 +"2007-12-24","Thai Election Day (in lieu)","TH",2007 +"2007-12-31","New Year's Eve","TH",2007 +"2008-01-01","New Year's Day","TH",2008 +"2008-02-21","Makha Bucha","TH",2008 +"2008-04-06","Chakri Memorial Day","TH",2008 +"2008-04-07","Chakri Memorial Day (in lieu)","TH",2008 +"2008-04-13","Songkran Festival","TH",2008 +"2008-04-14","Songkran Festival","TH",2008 +"2008-04-15","Songkran Festival","TH",2008 +"2008-05-01","National Labour Day","TH",2008 +"2008-05-05","Coronation Day","TH",2008 +"2008-05-09","Royal Ploughing Ceremony","TH",2008 +"2008-05-19","Visakha Bucha","TH",2008 +"2008-07-17","Asarnha Bucha","TH",2008 +"2008-07-18","Buddhist Lent Day","TH",2008 +"2008-08-12","HM Queen Sirikit's Birthday","TH",2008 +"2008-08-12","National Mother's Day","TH",2008 +"2008-10-23","HM King Chulalongkorn Memorial Day","TH",2008 +"2008-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2008 +"2008-12-05","National Day","TH",2008 +"2008-12-05","National Father's Day","TH",2008 +"2008-12-10","Constitution Day","TH",2008 +"2008-12-31","New Year's Eve","TH",2008 +"2009-01-01","New Year's Day","TH",2009 +"2009-01-02","Bridge Public Holiday","TH",2009 +"2009-02-09","Makha Bucha","TH",2009 +"2009-04-06","Chakri Memorial Day","TH",2009 +"2009-04-10","Emergency Lockdown (Thai Political Unrest)","TH",2009 +"2009-04-13","Songkran Festival","TH",2009 +"2009-04-14","Songkran Festival","TH",2009 +"2009-04-15","Songkran Festival","TH",2009 +"2009-04-16","Emergency Lockdown (Thai Political Unrest)","TH",2009 +"2009-04-17","Emergency Lockdown (Thai Political Unrest)","TH",2009 +"2009-05-01","National Labour Day","TH",2009 +"2009-05-05","Coronation Day","TH",2009 +"2009-05-08","Visakha Bucha","TH",2009 +"2009-05-11","Royal Ploughing Ceremony","TH",2009 +"2009-07-06","Bridge Public Holiday","TH",2009 +"2009-07-07","Asarnha Bucha","TH",2009 +"2009-07-08","Buddhist Lent Day","TH",2009 +"2009-08-12","HM Queen Sirikit's Birthday","TH",2009 +"2009-08-12","National Mother's Day","TH",2009 +"2009-10-23","HM King Chulalongkorn Memorial Day","TH",2009 +"2009-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2009 +"2009-12-05","National Day","TH",2009 +"2009-12-05","National Father's Day","TH",2009 +"2009-12-07","HM King Bhumibol Adulyadej's Birthday (in lieu)","TH",2009 +"2009-12-07","National Day (in lieu)","TH",2009 +"2009-12-07","National Father's Day (in lieu)","TH",2009 +"2009-12-10","Constitution Day","TH",2009 +"2009-12-31","New Year's Eve","TH",2009 +"2010-01-01","New Year's Day","TH",2010 +"2010-02-28","Makha Bucha","TH",2010 +"2010-03-01","Makha Bucha (in lieu)","TH",2010 +"2010-04-06","Chakri Memorial Day","TH",2010 +"2010-04-13","Songkran Festival","TH",2010 +"2010-04-14","Songkran Festival","TH",2010 +"2010-04-15","Songkran Festival","TH",2010 +"2010-05-01","National Labour Day","TH",2010 +"2010-05-03","National Labour Day (in lieu)","TH",2010 +"2010-05-05","Coronation Day","TH",2010 +"2010-05-10","Royal Ploughing Ceremony","TH",2010 +"2010-05-20","Bridge Public Holiday","TH",2010 +"2010-05-21","Bridge Public Holiday","TH",2010 +"2010-05-28","Visakha Bucha","TH",2010 +"2010-07-26","Asarnha Bucha","TH",2010 +"2010-07-27","Buddhist Lent Day","TH",2010 +"2010-08-12","HM Queen Sirikit's Birthday","TH",2010 +"2010-08-12","National Mother's Day","TH",2010 +"2010-08-13","Bridge Public Holiday","TH",2010 +"2010-10-23","HM King Chulalongkorn Memorial Day","TH",2010 +"2010-10-25","HM King Chulalongkorn Memorial Day (in lieu)","TH",2010 +"2010-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2010 +"2010-12-05","National Day","TH",2010 +"2010-12-05","National Father's Day","TH",2010 +"2010-12-06","HM King Bhumibol Adulyadej's Birthday (in lieu)","TH",2010 +"2010-12-06","National Day (in lieu)","TH",2010 +"2010-12-06","National Father's Day (in lieu)","TH",2010 +"2010-12-10","Constitution Day","TH",2010 +"2010-12-31","New Year's Eve","TH",2010 +"2011-01-01","New Year's Day","TH",2011 +"2011-01-03","New Year's Day (in lieu)","TH",2011 +"2011-02-18","Makha Bucha","TH",2011 +"2011-04-06","Chakri Memorial Day","TH",2011 +"2011-04-13","Songkran Festival","TH",2011 +"2011-04-14","Songkran Festival","TH",2011 +"2011-04-15","Songkran Festival","TH",2011 +"2011-05-01","National Labour Day","TH",2011 +"2011-05-02","National Labour Day (in lieu)","TH",2011 +"2011-05-05","Coronation Day","TH",2011 +"2011-05-13","Royal Ploughing Ceremony","TH",2011 +"2011-05-16","Bridge Public Holiday","TH",2011 +"2011-05-17","Visakha Bucha","TH",2011 +"2011-07-15","Asarnha Bucha","TH",2011 +"2011-07-16","Buddhist Lent Day","TH",2011 +"2011-07-18","Buddhist Lent Day (in lieu)","TH",2011 +"2011-08-12","HM Queen Sirikit's Birthday","TH",2011 +"2011-08-12","National Mother's Day","TH",2011 +"2011-10-23","HM King Chulalongkorn Memorial Day","TH",2011 +"2011-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2011 +"2011-10-27","Emergency Lockdown (2011 Thailand Floods)","TH",2011 +"2011-10-28","Emergency Lockdown (2011 Thailand Floods)","TH",2011 +"2011-10-29","Emergency Lockdown (2011 Thailand Floods)","TH",2011 +"2011-10-30","Emergency Lockdown (2011 Thailand Floods)","TH",2011 +"2011-10-31","Emergency Lockdown (2011 Thailand Floods)","TH",2011 +"2011-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2011 +"2011-12-05","National Day","TH",2011 +"2011-12-05","National Father's Day","TH",2011 +"2011-12-10","Constitution Day","TH",2011 +"2011-12-12","Constitution Day (in lieu)","TH",2011 +"2011-12-31","New Year's Eve","TH",2011 +"2012-01-01","New Year's Day","TH",2012 +"2012-01-02","New Year's Day (in lieu)","TH",2012 +"2012-01-03","New Year's Eve (in lieu)","TH",2012 +"2012-03-07","Makha Bucha","TH",2012 +"2012-04-06","Chakri Memorial Day","TH",2012 +"2012-04-09","Bridge Public Holiday","TH",2012 +"2012-04-13","Songkran Festival","TH",2012 +"2012-04-14","Songkran Festival","TH",2012 +"2012-04-15","Songkran Festival","TH",2012 +"2012-04-16","Songkran Festival (in lieu)","TH",2012 +"2012-05-01","National Labour Day","TH",2012 +"2012-05-05","Coronation Day","TH",2012 +"2012-05-07","Coronation Day (in lieu)","TH",2012 +"2012-05-09","Royal Ploughing Ceremony","TH",2012 +"2012-06-04","Visakha Bucha","TH",2012 +"2012-08-02","Asarnha Bucha","TH",2012 +"2012-08-03","Buddhist Lent Day","TH",2012 +"2012-08-12","HM Queen Sirikit's Birthday","TH",2012 +"2012-08-12","National Mother's Day","TH",2012 +"2012-08-13","HM Queen Sirikit's Birthday (in lieu)","TH",2012 +"2012-08-13","National Mother's Day (in lieu)","TH",2012 +"2012-10-23","HM King Chulalongkorn Memorial Day","TH",2012 +"2012-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2012 +"2012-12-05","National Day","TH",2012 +"2012-12-05","National Father's Day","TH",2012 +"2012-12-10","Constitution Day","TH",2012 +"2012-12-31","New Year's Eve","TH",2012 +"2013-01-01","New Year's Day","TH",2013 +"2013-02-25","Makha Bucha","TH",2013 +"2013-04-06","Chakri Memorial Day","TH",2013 +"2013-04-08","Chakri Memorial Day (in lieu)","TH",2013 +"2013-04-13","Songkran Festival","TH",2013 +"2013-04-14","Songkran Festival","TH",2013 +"2013-04-15","Songkran Festival","TH",2013 +"2013-04-16","Songkran Festival (in lieu)","TH",2013 +"2013-05-01","National Labour Day","TH",2013 +"2013-05-05","Coronation Day","TH",2013 +"2013-05-06","Coronation Day (in lieu)","TH",2013 +"2013-05-13","Royal Ploughing Ceremony","TH",2013 +"2013-05-24","Visakha Bucha","TH",2013 +"2013-07-22","Asarnha Bucha","TH",2013 +"2013-07-23","Buddhist Lent Day","TH",2013 +"2013-08-12","HM Queen Sirikit's Birthday","TH",2013 +"2013-08-12","National Mother's Day","TH",2013 +"2013-10-23","HM King Chulalongkorn Memorial Day","TH",2013 +"2013-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2013 +"2013-12-05","National Day","TH",2013 +"2013-12-05","National Father's Day","TH",2013 +"2013-12-10","Constitution Day","TH",2013 +"2013-12-30","Bridge Public Holiday","TH",2013 +"2013-12-31","New Year's Eve","TH",2013 +"2014-01-01","New Year's Day","TH",2014 +"2014-02-14","Makha Bucha","TH",2014 +"2014-04-06","Chakri Memorial Day","TH",2014 +"2014-04-07","Chakri Memorial Day (in lieu)","TH",2014 +"2014-04-13","Songkran Festival","TH",2014 +"2014-04-14","Songkran Festival","TH",2014 +"2014-04-15","Songkran Festival","TH",2014 +"2014-05-01","National Labour Day","TH",2014 +"2014-05-05","Coronation Day","TH",2014 +"2014-05-09","Royal Ploughing Ceremony","TH",2014 +"2014-05-13","Visakha Bucha","TH",2014 +"2014-07-11","Asarnha Bucha","TH",2014 +"2014-07-12","Buddhist Lent Day","TH",2014 +"2014-07-14","Buddhist Lent Day (in lieu)","TH",2014 +"2014-08-11","Bridge Public Holiday","TH",2014 +"2014-08-12","HM Queen Sirikit's Birthday","TH",2014 +"2014-08-12","National Mother's Day","TH",2014 +"2014-10-23","HM King Chulalongkorn Memorial Day","TH",2014 +"2014-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2014 +"2014-12-05","National Day","TH",2014 +"2014-12-05","National Father's Day","TH",2014 +"2014-12-10","Constitution Day","TH",2014 +"2014-12-31","New Year's Eve","TH",2014 +"2015-01-01","New Year's Day","TH",2015 +"2015-01-02","Bridge Public Holiday","TH",2015 +"2015-03-04","Makha Bucha","TH",2015 +"2015-04-06","Chakri Memorial Day","TH",2015 +"2015-04-13","Songkran Festival","TH",2015 +"2015-04-14","Songkran Festival","TH",2015 +"2015-04-15","Songkran Festival","TH",2015 +"2015-05-01","National Labour Day","TH",2015 +"2015-05-04","Bridge Public Holiday","TH",2015 +"2015-05-05","Coronation Day","TH",2015 +"2015-05-13","Royal Ploughing Ceremony","TH",2015 +"2015-06-01","Visakha Bucha","TH",2015 +"2015-07-30","Asarnha Bucha","TH",2015 +"2015-07-31","Buddhist Lent Day","TH",2015 +"2015-08-12","HM Queen Sirikit's Birthday","TH",2015 +"2015-08-12","National Mother's Day","TH",2015 +"2015-10-23","HM King Chulalongkorn Memorial Day","TH",2015 +"2015-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2015 +"2015-12-05","National Day","TH",2015 +"2015-12-05","National Father's Day","TH",2015 +"2015-12-07","HM King Bhumibol Adulyadej's Birthday (in lieu)","TH",2015 +"2015-12-07","National Day (in lieu)","TH",2015 +"2015-12-07","National Father's Day (in lieu)","TH",2015 +"2015-12-10","Constitution Day","TH",2015 +"2015-12-31","New Year's Eve","TH",2015 +"2016-01-01","New Year's Day","TH",2016 +"2016-02-22","Makha Bucha","TH",2016 +"2016-04-06","Chakri Memorial Day","TH",2016 +"2016-04-13","Songkran Festival","TH",2016 +"2016-04-14","Songkran Festival","TH",2016 +"2016-04-15","Songkran Festival","TH",2016 +"2016-05-01","National Labour Day","TH",2016 +"2016-05-02","National Labour Day (in lieu)","TH",2016 +"2016-05-05","Coronation Day","TH",2016 +"2016-05-06","Bridge Public Holiday","TH",2016 +"2016-05-09","Royal Ploughing Ceremony","TH",2016 +"2016-05-20","Visakha Bucha","TH",2016 +"2016-07-18","Bridge Public Holiday","TH",2016 +"2016-07-19","Asarnha Bucha","TH",2016 +"2016-07-20","Buddhist Lent Day","TH",2016 +"2016-08-12","HM Queen Sirikit's Birthday","TH",2016 +"2016-08-12","National Mother's Day","TH",2016 +"2016-10-14","Day of Mourning for HM King Bhumibol Adulyadej","TH",2016 +"2016-10-23","HM King Chulalongkorn Memorial Day","TH",2016 +"2016-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2016 +"2016-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2016 +"2016-12-05","National Day","TH",2016 +"2016-12-05","National Father's Day","TH",2016 +"2016-12-10","Constitution Day","TH",2016 +"2016-12-12","Constitution Day (in lieu)","TH",2016 +"2016-12-31","New Year's Eve","TH",2016 +"2017-01-01","New Year's Day","TH",2017 +"2017-01-02","New Year's Day (in lieu)","TH",2017 +"2017-01-03","New Year's Eve (in lieu)","TH",2017 +"2017-02-11","Makha Bucha","TH",2017 +"2017-02-13","Makha Bucha (in lieu)","TH",2017 +"2017-04-06","Chakri Memorial Day","TH",2017 +"2017-04-13","Songkran Festival","TH",2017 +"2017-04-14","Songkran Festival","TH",2017 +"2017-04-15","Songkran Festival","TH",2017 +"2017-04-17","Songkran Festival (in lieu)","TH",2017 +"2017-05-01","National Labour Day","TH",2017 +"2017-05-10","Visakha Bucha","TH",2017 +"2017-05-12","Royal Ploughing Ceremony","TH",2017 +"2017-07-08","Asarnha Bucha","TH",2017 +"2017-07-09","Buddhist Lent Day","TH",2017 +"2017-07-10","Asarnha Bucha (in lieu)","TH",2017 +"2017-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2017 +"2017-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2017 +"2017-08-12","National Mother's Day","TH",2017 +"2017-08-14","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2017 +"2017-08-14","National Mother's Day (in lieu)","TH",2017 +"2017-10-13","HM King Bhumibol Adulyadej Memorial Day","TH",2017 +"2017-10-23","HM King Chulalongkorn Memorial Day","TH",2017 +"2017-10-26","HM King Bhumibol Adulyadej's Royal Cremation Ceremony","TH",2017 +"2017-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2017 +"2017-12-05","National Day","TH",2017 +"2017-12-05","National Father's Day","TH",2017 +"2017-12-10","Constitution Day","TH",2017 +"2017-12-11","Constitution Day (in lieu)","TH",2017 +"2017-12-31","New Year's Eve","TH",2017 +"2018-01-01","New Year's Day","TH",2018 +"2018-01-02","New Year's Eve (in lieu)","TH",2018 +"2018-03-01","Makha Bucha","TH",2018 +"2018-04-06","Chakri Memorial Day","TH",2018 +"2018-04-13","Songkran Festival","TH",2018 +"2018-04-14","Songkran Festival","TH",2018 +"2018-04-15","Songkran Festival","TH",2018 +"2018-04-16","Songkran Festival (in lieu)","TH",2018 +"2018-05-01","National Labour Day","TH",2018 +"2018-05-14","Royal Ploughing Ceremony","TH",2018 +"2018-05-29","Visakha Bucha","TH",2018 +"2018-07-27","Asarnha Bucha","TH",2018 +"2018-07-28","Buddhist Lent Day","TH",2018 +"2018-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2018 +"2018-07-30","Buddhist Lent Day (in lieu)","TH",2018 +"2018-07-30","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2018 +"2018-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2018 +"2018-08-12","National Mother's Day","TH",2018 +"2018-08-13","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2018 +"2018-08-13","National Mother's Day (in lieu)","TH",2018 +"2018-10-13","HM King Bhumibol Adulyadej Memorial Day","TH",2018 +"2018-10-15","HM King Bhumibol Adulyadej Memorial Day (in lieu)","TH",2018 +"2018-10-23","HM King Chulalongkorn Memorial Day","TH",2018 +"2018-12-05","HM King Bhumibol Adulyadej's Birthday","TH",2018 +"2018-12-05","National Day","TH",2018 +"2018-12-05","National Father's Day","TH",2018 +"2018-12-10","Constitution Day","TH",2018 +"2018-12-31","New Year's Eve","TH",2018 +"2019-01-01","New Year's Day","TH",2019 +"2019-02-19","Makha Bucha","TH",2019 +"2019-04-06","Chakri Memorial Day","TH",2019 +"2019-04-08","Chakri Memorial Day (in lieu)","TH",2019 +"2019-04-13","Songkran Festival","TH",2019 +"2019-04-14","Songkran Festival","TH",2019 +"2019-04-15","Songkran Festival","TH",2019 +"2019-04-16","Songkran Festival (in lieu)","TH",2019 +"2019-05-01","National Labour Day","TH",2019 +"2019-05-06","HM King Maha Vajiralongkorn's Coronation Celebrations","TH",2019 +"2019-05-09","Royal Ploughing Ceremony","TH",2019 +"2019-05-18","Visakha Bucha","TH",2019 +"2019-05-20","Visakha Bucha (in lieu)","TH",2019 +"2019-06-03","HM Queen Suthida's Birthday","TH",2019 +"2019-07-16","Asarnha Bucha","TH",2019 +"2019-07-17","Buddhist Lent Day","TH",2019 +"2019-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2019 +"2019-07-29","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2019 +"2019-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2019 +"2019-08-12","National Mother's Day","TH",2019 +"2019-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2019 +"2019-10-14","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2019 +"2019-10-23","HM King Chulalongkorn Memorial Day","TH",2019 +"2019-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2019 +"2019-12-05","National Day","TH",2019 +"2019-12-05","National Father's Day","TH",2019 +"2019-12-10","Constitution Day","TH",2019 +"2019-12-31","New Year's Eve","TH",2019 +"2020-01-01","New Year's Day","TH",2020 +"2020-02-08","Makha Bucha","TH",2020 +"2020-02-10","Makha Bucha (in lieu)","TH",2020 +"2020-04-06","Chakri Memorial Day","TH",2020 +"2020-05-01","National Labour Day","TH",2020 +"2020-05-04","Coronation Day","TH",2020 +"2020-05-06","Visakha Bucha","TH",2020 +"2020-05-11","Royal Ploughing Ceremony","TH",2020 +"2020-06-03","HM Queen Suthida's Birthday","TH",2020 +"2020-07-05","Asarnha Bucha","TH",2020 +"2020-07-06","Buddhist Lent Day","TH",2020 +"2020-07-07","Asarnha Bucha (in lieu)","TH",2020 +"2020-07-27","Songkran Festival (in lieu)","TH",2020 +"2020-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2020 +"2020-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2020 +"2020-08-12","National Mother's Day","TH",2020 +"2020-09-04","Songkran Festival (in lieu)","TH",2020 +"2020-09-07","Songkran Festival (in lieu)","TH",2020 +"2020-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2020 +"2020-10-23","HM King Chulalongkorn Memorial Day","TH",2020 +"2020-11-19","Bridge Public Holiday","TH",2020 +"2020-11-20","Bridge Public Holiday","TH",2020 +"2020-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2020 +"2020-12-05","National Day","TH",2020 +"2020-12-05","National Father's Day","TH",2020 +"2020-12-07","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2020 +"2020-12-07","National Day (in lieu)","TH",2020 +"2020-12-07","National Father's Day (in lieu)","TH",2020 +"2020-12-10","Constitution Day","TH",2020 +"2020-12-11","Bridge Public Holiday","TH",2020 +"2020-12-31","New Year's Eve","TH",2020 +"2021-01-01","New Year's Day","TH",2021 +"2021-02-12","Bridge Public Holiday","TH",2021 +"2021-02-26","Makha Bucha","TH",2021 +"2021-04-06","Chakri Memorial Day","TH",2021 +"2021-04-12","Bridge Public Holiday","TH",2021 +"2021-04-13","Songkran Festival","TH",2021 +"2021-04-14","Songkran Festival","TH",2021 +"2021-04-15","Songkran Festival","TH",2021 +"2021-05-01","National Labour Day","TH",2021 +"2021-05-03","National Labour Day (in lieu)","TH",2021 +"2021-05-04","Coronation Day","TH",2021 +"2021-05-13","Royal Ploughing Ceremony","TH",2021 +"2021-05-26","Visakha Bucha","TH",2021 +"2021-06-03","HM Queen Suthida's Birthday","TH",2021 +"2021-07-24","Asarnha Bucha","TH",2021 +"2021-07-25","Buddhist Lent Day","TH",2021 +"2021-07-26","Asarnha Bucha (in lieu)","TH",2021 +"2021-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2021 +"2021-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2021 +"2021-08-12","National Mother's Day","TH",2021 +"2021-09-24","Bridge Public Holiday","TH",2021 +"2021-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2021 +"2021-10-23","HM King Chulalongkorn Memorial Day","TH",2021 +"2021-10-25","HM King Chulalongkorn Memorial Day (in lieu)","TH",2021 +"2021-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2021 +"2021-12-05","National Day","TH",2021 +"2021-12-05","National Father's Day","TH",2021 +"2021-12-06","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2021 +"2021-12-06","National Day (in lieu)","TH",2021 +"2021-12-06","National Father's Day (in lieu)","TH",2021 +"2021-12-10","Constitution Day","TH",2021 +"2021-12-31","New Year's Eve","TH",2021 +"2022-01-01","New Year's Day","TH",2022 +"2022-01-03","New Year's Day (in lieu)","TH",2022 +"2022-02-16","Makha Bucha","TH",2022 +"2022-04-06","Chakri Memorial Day","TH",2022 +"2022-04-13","Songkran Festival","TH",2022 +"2022-04-14","Songkran Festival","TH",2022 +"2022-04-15","Songkran Festival","TH",2022 +"2022-05-01","National Labour Day","TH",2022 +"2022-05-02","National Labour Day (in lieu)","TH",2022 +"2022-05-04","Coronation Day","TH",2022 +"2022-05-15","Visakha Bucha","TH",2022 +"2022-05-16","Visakha Bucha (in lieu)","TH",2022 +"2022-05-17","Royal Ploughing Ceremony","TH",2022 +"2022-06-03","HM Queen Suthida's Birthday","TH",2022 +"2022-07-13","Asarnha Bucha","TH",2022 +"2022-07-14","Buddhist Lent Day","TH",2022 +"2022-07-15","Bridge Public Holiday","TH",2022 +"2022-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2022 +"2022-07-29","Bridge Public Holiday","TH",2022 +"2022-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2022 +"2022-08-12","National Mother's Day","TH",2022 +"2022-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2022 +"2022-10-14","Bridge Public Holiday","TH",2022 +"2022-10-23","HM King Chulalongkorn Memorial Day","TH",2022 +"2022-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2022 +"2022-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2022 +"2022-12-05","National Day","TH",2022 +"2022-12-05","National Father's Day","TH",2022 +"2022-12-10","Constitution Day","TH",2022 +"2022-12-12","Constitution Day (in lieu)","TH",2022 +"2022-12-30","Bridge Public Holiday","TH",2022 +"2022-12-31","New Year's Eve","TH",2022 +"2023-01-01","New Year's Day","TH",2023 +"2023-01-02","New Year's Day (in lieu)","TH",2023 +"2023-01-03","New Year's Eve (in lieu)","TH",2023 +"2023-03-06","Makha Bucha","TH",2023 +"2023-04-06","Chakri Memorial Day","TH",2023 +"2023-04-13","Songkran Festival","TH",2023 +"2023-04-14","Songkran Festival","TH",2023 +"2023-04-15","Songkran Festival","TH",2023 +"2023-04-17","Songkran Festival (in lieu)","TH",2023 +"2023-05-01","National Labour Day","TH",2023 +"2023-05-04","Coronation Day","TH",2023 +"2023-05-05","Bridge Public Holiday","TH",2023 +"2023-05-11","Royal Ploughing Ceremony","TH",2023 +"2023-06-03","HM Queen Suthida's Birthday","TH",2023 +"2023-06-03","Visakha Bucha","TH",2023 +"2023-06-05","HM Queen Suthida's Birthday (in lieu)","TH",2023 +"2023-06-05","Visakha Bucha (in lieu)","TH",2023 +"2023-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2023 +"2023-08-01","Asarnha Bucha","TH",2023 +"2023-08-02","Buddhist Lent Day","TH",2023 +"2023-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2023 +"2023-08-12","National Mother's Day","TH",2023 +"2023-08-14","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2023 +"2023-08-14","National Mother's Day (in lieu)","TH",2023 +"2023-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2023 +"2023-10-23","HM King Chulalongkorn Memorial Day","TH",2023 +"2023-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2023 +"2023-12-05","National Day","TH",2023 +"2023-12-05","National Father's Day","TH",2023 +"2023-12-10","Constitution Day","TH",2023 +"2023-12-11","Constitution Day (in lieu)","TH",2023 +"2023-12-31","New Year's Eve","TH",2023 +"2024-01-01","New Year's Day","TH",2024 +"2024-01-02","New Year's Eve (in lieu)","TH",2024 +"2024-02-24","Makha Bucha","TH",2024 +"2024-02-26","Makha Bucha (in lieu)","TH",2024 +"2024-04-06","Chakri Memorial Day","TH",2024 +"2024-04-08","Chakri Memorial Day (in lieu)","TH",2024 +"2024-04-13","Songkran Festival","TH",2024 +"2024-04-14","Songkran Festival","TH",2024 +"2024-04-15","Songkran Festival","TH",2024 +"2024-04-16","Songkran Festival (in lieu)","TH",2024 +"2024-05-01","National Labour Day","TH",2024 +"2024-05-04","Coronation Day","TH",2024 +"2024-05-06","Coronation Day (in lieu)","TH",2024 +"2024-05-22","Visakha Bucha","TH",2024 +"2024-06-03","HM Queen Suthida's Birthday","TH",2024 +"2024-07-20","Asarnha Bucha","TH",2024 +"2024-07-21","Buddhist Lent Day","TH",2024 +"2024-07-22","Asarnha Bucha (in lieu)","TH",2024 +"2024-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2024 +"2024-07-29","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2024 +"2024-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2024 +"2024-08-12","National Mother's Day","TH",2024 +"2024-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2024 +"2024-10-14","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2024 +"2024-10-23","HM King Chulalongkorn Memorial Day","TH",2024 +"2024-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2024 +"2024-12-05","National Day","TH",2024 +"2024-12-05","National Father's Day","TH",2024 +"2024-12-10","Constitution Day","TH",2024 +"2024-12-31","New Year's Eve","TH",2024 +"2025-01-01","New Year's Day","TH",2025 +"2025-02-12","Makha Bucha","TH",2025 +"2025-04-06","Chakri Memorial Day","TH",2025 +"2025-04-07","Chakri Memorial Day (in lieu)","TH",2025 +"2025-04-13","Songkran Festival","TH",2025 +"2025-04-14","Songkran Festival","TH",2025 +"2025-04-15","Songkran Festival","TH",2025 +"2025-05-01","National Labour Day","TH",2025 +"2025-05-04","Coronation Day","TH",2025 +"2025-05-05","Coronation Day (in lieu)","TH",2025 +"2025-05-11","Visakha Bucha","TH",2025 +"2025-05-12","Visakha Bucha (in lieu)","TH",2025 +"2025-06-03","HM Queen Suthida's Birthday","TH",2025 +"2025-07-10","Asarnha Bucha","TH",2025 +"2025-07-11","Buddhist Lent Day","TH",2025 +"2025-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2025 +"2025-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2025 +"2025-08-12","National Mother's Day","TH",2025 +"2025-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2025 +"2025-10-23","HM King Chulalongkorn Memorial Day","TH",2025 +"2025-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2025 +"2025-12-05","National Day","TH",2025 +"2025-12-05","National Father's Day","TH",2025 +"2025-12-10","Constitution Day","TH",2025 +"2025-12-31","New Year's Eve","TH",2025 +"2026-01-01","New Year's Day","TH",2026 +"2026-03-03","Makha Bucha","TH",2026 +"2026-04-06","Chakri Memorial Day","TH",2026 +"2026-04-13","Songkran Festival","TH",2026 +"2026-04-14","Songkran Festival","TH",2026 +"2026-04-15","Songkran Festival","TH",2026 +"2026-05-01","National Labour Day","TH",2026 +"2026-05-04","Coronation Day","TH",2026 +"2026-05-31","Visakha Bucha","TH",2026 +"2026-06-01","Visakha Bucha (in lieu)","TH",2026 +"2026-06-03","HM Queen Suthida's Birthday","TH",2026 +"2026-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2026 +"2026-07-29","Asarnha Bucha","TH",2026 +"2026-07-30","Buddhist Lent Day","TH",2026 +"2026-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2026 +"2026-08-12","National Mother's Day","TH",2026 +"2026-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2026 +"2026-10-23","HM King Chulalongkorn Memorial Day","TH",2026 +"2026-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2026 +"2026-12-05","National Day","TH",2026 +"2026-12-05","National Father's Day","TH",2026 +"2026-12-07","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2026 +"2026-12-07","National Day (in lieu)","TH",2026 +"2026-12-07","National Father's Day (in lieu)","TH",2026 +"2026-12-10","Constitution Day","TH",2026 +"2026-12-31","New Year's Eve","TH",2026 +"2027-01-01","New Year's Day","TH",2027 +"2027-02-21","Makha Bucha","TH",2027 +"2027-02-22","Makha Bucha (in lieu)","TH",2027 +"2027-04-06","Chakri Memorial Day","TH",2027 +"2027-04-13","Songkran Festival","TH",2027 +"2027-04-14","Songkran Festival","TH",2027 +"2027-04-15","Songkran Festival","TH",2027 +"2027-05-01","National Labour Day","TH",2027 +"2027-05-03","National Labour Day (in lieu)","TH",2027 +"2027-05-04","Coronation Day","TH",2027 +"2027-05-20","Visakha Bucha","TH",2027 +"2027-06-03","HM Queen Suthida's Birthday","TH",2027 +"2027-07-18","Asarnha Bucha","TH",2027 +"2027-07-19","Buddhist Lent Day","TH",2027 +"2027-07-20","Asarnha Bucha (in lieu)","TH",2027 +"2027-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2027 +"2027-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2027 +"2027-08-12","National Mother's Day","TH",2027 +"2027-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2027 +"2027-10-23","HM King Chulalongkorn Memorial Day","TH",2027 +"2027-10-25","HM King Chulalongkorn Memorial Day (in lieu)","TH",2027 +"2027-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2027 +"2027-12-05","National Day","TH",2027 +"2027-12-05","National Father's Day","TH",2027 +"2027-12-06","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2027 +"2027-12-06","National Day (in lieu)","TH",2027 +"2027-12-06","National Father's Day (in lieu)","TH",2027 +"2027-12-10","Constitution Day","TH",2027 +"2027-12-31","New Year's Eve","TH",2027 +"2028-01-01","New Year's Day","TH",2028 +"2028-01-03","New Year's Day (in lieu)","TH",2028 +"2028-02-10","Makha Bucha","TH",2028 +"2028-04-06","Chakri Memorial Day","TH",2028 +"2028-04-13","Songkran Festival","TH",2028 +"2028-04-14","Songkran Festival","TH",2028 +"2028-04-15","Songkran Festival","TH",2028 +"2028-04-17","Songkran Festival (in lieu)","TH",2028 +"2028-05-01","National Labour Day","TH",2028 +"2028-05-04","Coronation Day","TH",2028 +"2028-05-08","Visakha Bucha","TH",2028 +"2028-06-03","HM Queen Suthida's Birthday","TH",2028 +"2028-06-05","HM Queen Suthida's Birthday (in lieu)","TH",2028 +"2028-07-06","Asarnha Bucha","TH",2028 +"2028-07-07","Buddhist Lent Day","TH",2028 +"2028-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2028 +"2028-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2028 +"2028-08-12","National Mother's Day","TH",2028 +"2028-08-14","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2028 +"2028-08-14","National Mother's Day (in lieu)","TH",2028 +"2028-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2028 +"2028-10-23","HM King Chulalongkorn Memorial Day","TH",2028 +"2028-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2028 +"2028-12-05","National Day","TH",2028 +"2028-12-05","National Father's Day","TH",2028 +"2028-12-10","Constitution Day","TH",2028 +"2028-12-11","Constitution Day (in lieu)","TH",2028 +"2028-12-31","New Year's Eve","TH",2028 +"2029-01-01","New Year's Day","TH",2029 +"2029-01-02","New Year's Eve (in lieu)","TH",2029 +"2029-02-27","Makha Bucha","TH",2029 +"2029-04-06","Chakri Memorial Day","TH",2029 +"2029-04-13","Songkran Festival","TH",2029 +"2029-04-14","Songkran Festival","TH",2029 +"2029-04-15","Songkran Festival","TH",2029 +"2029-04-16","Songkran Festival (in lieu)","TH",2029 +"2029-05-01","National Labour Day","TH",2029 +"2029-05-04","Coronation Day","TH",2029 +"2029-05-27","Visakha Bucha","TH",2029 +"2029-05-28","Visakha Bucha (in lieu)","TH",2029 +"2029-06-03","HM Queen Suthida's Birthday","TH",2029 +"2029-06-04","HM Queen Suthida's Birthday (in lieu)","TH",2029 +"2029-07-25","Asarnha Bucha","TH",2029 +"2029-07-26","Buddhist Lent Day","TH",2029 +"2029-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2029 +"2029-07-30","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2029 +"2029-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2029 +"2029-08-12","National Mother's Day","TH",2029 +"2029-08-13","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2029 +"2029-08-13","National Mother's Day (in lieu)","TH",2029 +"2029-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2029 +"2029-10-15","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2029 +"2029-10-23","HM King Chulalongkorn Memorial Day","TH",2029 +"2029-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2029 +"2029-12-05","National Day","TH",2029 +"2029-12-05","National Father's Day","TH",2029 +"2029-12-10","Constitution Day","TH",2029 +"2029-12-31","New Year's Eve","TH",2029 +"2030-01-01","New Year's Day","TH",2030 +"2030-02-17","Makha Bucha","TH",2030 +"2030-02-18","Makha Bucha (in lieu)","TH",2030 +"2030-04-06","Chakri Memorial Day","TH",2030 +"2030-04-08","Chakri Memorial Day (in lieu)","TH",2030 +"2030-04-13","Songkran Festival","TH",2030 +"2030-04-14","Songkran Festival","TH",2030 +"2030-04-15","Songkran Festival","TH",2030 +"2030-04-16","Songkran Festival (in lieu)","TH",2030 +"2030-05-01","National Labour Day","TH",2030 +"2030-05-04","Coronation Day","TH",2030 +"2030-05-06","Coronation Day (in lieu)","TH",2030 +"2030-05-16","Visakha Bucha","TH",2030 +"2030-06-03","HM Queen Suthida's Birthday","TH",2030 +"2030-07-14","Asarnha Bucha","TH",2030 +"2030-07-15","Buddhist Lent Day","TH",2030 +"2030-07-16","Asarnha Bucha (in lieu)","TH",2030 +"2030-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2030 +"2030-07-29","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2030 +"2030-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2030 +"2030-08-12","National Mother's Day","TH",2030 +"2030-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2030 +"2030-10-14","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2030 +"2030-10-23","HM King Chulalongkorn Memorial Day","TH",2030 +"2030-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2030 +"2030-12-05","National Day","TH",2030 +"2030-12-05","National Father's Day","TH",2030 +"2030-12-10","Constitution Day","TH",2030 +"2030-12-31","New Year's Eve","TH",2030 +"2031-01-01","New Year's Day","TH",2031 +"2031-03-07","Makha Bucha","TH",2031 +"2031-04-06","Chakri Memorial Day","TH",2031 +"2031-04-07","Chakri Memorial Day (in lieu)","TH",2031 +"2031-04-13","Songkran Festival","TH",2031 +"2031-04-14","Songkran Festival","TH",2031 +"2031-04-15","Songkran Festival","TH",2031 +"2031-05-01","National Labour Day","TH",2031 +"2031-05-04","Coronation Day","TH",2031 +"2031-05-05","Coronation Day (in lieu)","TH",2031 +"2031-06-03","HM Queen Suthida's Birthday","TH",2031 +"2031-06-04","Visakha Bucha","TH",2031 +"2031-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2031 +"2031-08-02","Asarnha Bucha","TH",2031 +"2031-08-03","Buddhist Lent Day","TH",2031 +"2031-08-04","Asarnha Bucha (in lieu)","TH",2031 +"2031-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2031 +"2031-08-12","National Mother's Day","TH",2031 +"2031-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2031 +"2031-10-23","HM King Chulalongkorn Memorial Day","TH",2031 +"2031-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2031 +"2031-12-05","National Day","TH",2031 +"2031-12-05","National Father's Day","TH",2031 +"2031-12-10","Constitution Day","TH",2031 +"2031-12-31","New Year's Eve","TH",2031 +"2032-01-01","New Year's Day","TH",2032 +"2032-02-25","Makha Bucha","TH",2032 +"2032-04-06","Chakri Memorial Day","TH",2032 +"2032-04-13","Songkran Festival","TH",2032 +"2032-04-14","Songkran Festival","TH",2032 +"2032-04-15","Songkran Festival","TH",2032 +"2032-05-01","National Labour Day","TH",2032 +"2032-05-03","National Labour Day (in lieu)","TH",2032 +"2032-05-04","Coronation Day","TH",2032 +"2032-05-23","Visakha Bucha","TH",2032 +"2032-05-24","Visakha Bucha (in lieu)","TH",2032 +"2032-06-03","HM Queen Suthida's Birthday","TH",2032 +"2032-07-22","Asarnha Bucha","TH",2032 +"2032-07-23","Buddhist Lent Day","TH",2032 +"2032-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2032 +"2032-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2032 +"2032-08-12","National Mother's Day","TH",2032 +"2032-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2032 +"2032-10-23","HM King Chulalongkorn Memorial Day","TH",2032 +"2032-10-25","HM King Chulalongkorn Memorial Day (in lieu)","TH",2032 +"2032-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2032 +"2032-12-05","National Day","TH",2032 +"2032-12-05","National Father's Day","TH",2032 +"2032-12-06","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2032 +"2032-12-06","National Day (in lieu)","TH",2032 +"2032-12-06","National Father's Day (in lieu)","TH",2032 +"2032-12-10","Constitution Day","TH",2032 +"2032-12-31","New Year's Eve","TH",2032 +"2033-01-01","New Year's Day","TH",2033 +"2033-01-03","New Year's Day (in lieu)","TH",2033 +"2033-02-14","Makha Bucha","TH",2033 +"2033-04-06","Chakri Memorial Day","TH",2033 +"2033-04-13","Songkran Festival","TH",2033 +"2033-04-14","Songkran Festival","TH",2033 +"2033-04-15","Songkran Festival","TH",2033 +"2033-05-01","National Labour Day","TH",2033 +"2033-05-02","National Labour Day (in lieu)","TH",2033 +"2033-05-04","Coronation Day","TH",2033 +"2033-05-13","Visakha Bucha","TH",2033 +"2033-06-03","HM Queen Suthida's Birthday","TH",2033 +"2033-07-11","Asarnha Bucha","TH",2033 +"2033-07-12","Buddhist Lent Day","TH",2033 +"2033-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2033 +"2033-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2033 +"2033-08-12","National Mother's Day","TH",2033 +"2033-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2033 +"2033-10-23","HM King Chulalongkorn Memorial Day","TH",2033 +"2033-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2033 +"2033-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2033 +"2033-12-05","National Day","TH",2033 +"2033-12-05","National Father's Day","TH",2033 +"2033-12-10","Constitution Day","TH",2033 +"2033-12-12","Constitution Day (in lieu)","TH",2033 +"2033-12-31","New Year's Eve","TH",2033 +"2034-01-01","New Year's Day","TH",2034 +"2034-01-02","New Year's Day (in lieu)","TH",2034 +"2034-01-03","New Year's Eve (in lieu)","TH",2034 +"2034-03-04","Makha Bucha","TH",2034 +"2034-03-06","Makha Bucha (in lieu)","TH",2034 +"2034-04-06","Chakri Memorial Day","TH",2034 +"2034-04-13","Songkran Festival","TH",2034 +"2034-04-14","Songkran Festival","TH",2034 +"2034-04-15","Songkran Festival","TH",2034 +"2034-04-17","Songkran Festival (in lieu)","TH",2034 +"2034-05-01","National Labour Day","TH",2034 +"2034-05-04","Coronation Day","TH",2034 +"2034-06-01","Visakha Bucha","TH",2034 +"2034-06-03","HM Queen Suthida's Birthday","TH",2034 +"2034-06-05","HM Queen Suthida's Birthday (in lieu)","TH",2034 +"2034-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2034 +"2034-07-30","Asarnha Bucha","TH",2034 +"2034-07-31","Buddhist Lent Day","TH",2034 +"2034-08-01","Asarnha Bucha (in lieu)","TH",2034 +"2034-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2034 +"2034-08-12","National Mother's Day","TH",2034 +"2034-08-14","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2034 +"2034-08-14","National Mother's Day (in lieu)","TH",2034 +"2034-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2034 +"2034-10-23","HM King Chulalongkorn Memorial Day","TH",2034 +"2034-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2034 +"2034-12-05","National Day","TH",2034 +"2034-12-05","National Father's Day","TH",2034 +"2034-12-10","Constitution Day","TH",2034 +"2034-12-11","Constitution Day (in lieu)","TH",2034 +"2034-12-31","New Year's Eve","TH",2034 +"2035-01-01","New Year's Day","TH",2035 +"2035-01-02","New Year's Eve (in lieu)","TH",2035 +"2035-02-22","Makha Bucha","TH",2035 +"2035-04-06","Chakri Memorial Day","TH",2035 +"2035-04-13","Songkran Festival","TH",2035 +"2035-04-14","Songkran Festival","TH",2035 +"2035-04-15","Songkran Festival","TH",2035 +"2035-04-16","Songkran Festival (in lieu)","TH",2035 +"2035-05-01","National Labour Day","TH",2035 +"2035-05-04","Coronation Day","TH",2035 +"2035-05-21","Visakha Bucha","TH",2035 +"2035-06-03","HM Queen Suthida's Birthday","TH",2035 +"2035-06-04","HM Queen Suthida's Birthday (in lieu)","TH",2035 +"2035-07-20","Asarnha Bucha","TH",2035 +"2035-07-21","Buddhist Lent Day","TH",2035 +"2035-07-23","Buddhist Lent Day (in lieu)","TH",2035 +"2035-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2035 +"2035-07-30","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2035 +"2035-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2035 +"2035-08-12","National Mother's Day","TH",2035 +"2035-08-13","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2035 +"2035-08-13","National Mother's Day (in lieu)","TH",2035 +"2035-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2035 +"2035-10-15","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2035 +"2035-10-23","HM King Chulalongkorn Memorial Day","TH",2035 +"2035-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2035 +"2035-12-05","National Day","TH",2035 +"2035-12-05","National Father's Day","TH",2035 +"2035-12-10","Constitution Day","TH",2035 +"2035-12-31","New Year's Eve","TH",2035 +"2036-01-01","New Year's Day","TH",2036 +"2036-02-12","Makha Bucha","TH",2036 +"2036-04-06","Chakri Memorial Day","TH",2036 +"2036-04-07","Chakri Memorial Day (in lieu)","TH",2036 +"2036-04-13","Songkran Festival","TH",2036 +"2036-04-14","Songkran Festival","TH",2036 +"2036-04-15","Songkran Festival","TH",2036 +"2036-05-01","National Labour Day","TH",2036 +"2036-05-04","Coronation Day","TH",2036 +"2036-05-05","Coronation Day (in lieu)","TH",2036 +"2036-05-10","Visakha Bucha","TH",2036 +"2036-05-12","Visakha Bucha (in lieu)","TH",2036 +"2036-06-03","HM Queen Suthida's Birthday","TH",2036 +"2036-07-08","Asarnha Bucha","TH",2036 +"2036-07-09","Buddhist Lent Day","TH",2036 +"2036-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2036 +"2036-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2036 +"2036-08-12","National Mother's Day","TH",2036 +"2036-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2036 +"2036-10-23","HM King Chulalongkorn Memorial Day","TH",2036 +"2036-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2036 +"2036-12-05","National Day","TH",2036 +"2036-12-05","National Father's Day","TH",2036 +"2036-12-10","Constitution Day","TH",2036 +"2036-12-31","New Year's Eve","TH",2036 +"2037-01-01","New Year's Day","TH",2037 +"2037-03-01","Makha Bucha","TH",2037 +"2037-03-02","Makha Bucha (in lieu)","TH",2037 +"2037-04-06","Chakri Memorial Day","TH",2037 +"2037-04-13","Songkran Festival","TH",2037 +"2037-04-14","Songkran Festival","TH",2037 +"2037-04-15","Songkran Festival","TH",2037 +"2037-05-01","National Labour Day","TH",2037 +"2037-05-04","Coronation Day","TH",2037 +"2037-05-29","Visakha Bucha","TH",2037 +"2037-06-03","HM Queen Suthida's Birthday","TH",2037 +"2037-07-27","Asarnha Bucha","TH",2037 +"2037-07-28","Buddhist Lent Day","TH",2037 +"2037-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2037 +"2037-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2037 +"2037-08-12","National Mother's Day","TH",2037 +"2037-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2037 +"2037-10-23","HM King Chulalongkorn Memorial Day","TH",2037 +"2037-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2037 +"2037-12-05","National Day","TH",2037 +"2037-12-05","National Father's Day","TH",2037 +"2037-12-07","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2037 +"2037-12-07","National Day (in lieu)","TH",2037 +"2037-12-07","National Father's Day (in lieu)","TH",2037 +"2037-12-10","Constitution Day","TH",2037 +"2037-12-31","New Year's Eve","TH",2037 +"2038-01-01","New Year's Day","TH",2038 +"2038-02-19","Makha Bucha","TH",2038 +"2038-04-06","Chakri Memorial Day","TH",2038 +"2038-04-13","Songkran Festival","TH",2038 +"2038-04-14","Songkran Festival","TH",2038 +"2038-04-15","Songkran Festival","TH",2038 +"2038-05-01","National Labour Day","TH",2038 +"2038-05-03","National Labour Day (in lieu)","TH",2038 +"2038-05-04","Coronation Day","TH",2038 +"2038-05-18","Visakha Bucha","TH",2038 +"2038-06-03","HM Queen Suthida's Birthday","TH",2038 +"2038-07-16","Asarnha Bucha","TH",2038 +"2038-07-17","Buddhist Lent Day","TH",2038 +"2038-07-19","Buddhist Lent Day (in lieu)","TH",2038 +"2038-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2038 +"2038-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2038 +"2038-08-12","National Mother's Day","TH",2038 +"2038-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2038 +"2038-10-23","HM King Chulalongkorn Memorial Day","TH",2038 +"2038-10-25","HM King Chulalongkorn Memorial Day (in lieu)","TH",2038 +"2038-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2038 +"2038-12-05","National Day","TH",2038 +"2038-12-05","National Father's Day","TH",2038 +"2038-12-06","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2038 +"2038-12-06","National Day (in lieu)","TH",2038 +"2038-12-06","National Father's Day (in lieu)","TH",2038 +"2038-12-10","Constitution Day","TH",2038 +"2038-12-31","New Year's Eve","TH",2038 +"2039-01-01","New Year's Day","TH",2039 +"2039-01-03","New Year's Day (in lieu)","TH",2039 +"2039-02-08","Makha Bucha","TH",2039 +"2039-04-06","Chakri Memorial Day","TH",2039 +"2039-04-13","Songkran Festival","TH",2039 +"2039-04-14","Songkran Festival","TH",2039 +"2039-04-15","Songkran Festival","TH",2039 +"2039-05-01","National Labour Day","TH",2039 +"2039-05-02","National Labour Day (in lieu)","TH",2039 +"2039-05-04","Coronation Day","TH",2039 +"2039-05-07","Visakha Bucha","TH",2039 +"2039-05-09","Visakha Bucha (in lieu)","TH",2039 +"2039-06-03","HM Queen Suthida's Birthday","TH",2039 +"2039-07-05","Asarnha Bucha","TH",2039 +"2039-07-06","Buddhist Lent Day","TH",2039 +"2039-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2039 +"2039-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2039 +"2039-08-12","National Mother's Day","TH",2039 +"2039-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2039 +"2039-10-23","HM King Chulalongkorn Memorial Day","TH",2039 +"2039-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2039 +"2039-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2039 +"2039-12-05","National Day","TH",2039 +"2039-12-05","National Father's Day","TH",2039 +"2039-12-10","Constitution Day","TH",2039 +"2039-12-12","Constitution Day (in lieu)","TH",2039 +"2039-12-31","New Year's Eve","TH",2039 +"2040-01-01","New Year's Day","TH",2040 +"2040-01-02","New Year's Day (in lieu)","TH",2040 +"2040-01-03","New Year's Eve (in lieu)","TH",2040 +"2040-02-26","Makha Bucha","TH",2040 +"2040-02-27","Makha Bucha (in lieu)","TH",2040 +"2040-04-06","Chakri Memorial Day","TH",2040 +"2040-04-13","Songkran Festival","TH",2040 +"2040-04-14","Songkran Festival","TH",2040 +"2040-04-15","Songkran Festival","TH",2040 +"2040-04-16","Songkran Festival (in lieu)","TH",2040 +"2040-05-01","National Labour Day","TH",2040 +"2040-05-04","Coronation Day","TH",2040 +"2040-05-25","Visakha Bucha","TH",2040 +"2040-06-03","HM Queen Suthida's Birthday","TH",2040 +"2040-06-04","HM Queen Suthida's Birthday (in lieu)","TH",2040 +"2040-07-23","Asarnha Bucha","TH",2040 +"2040-07-24","Buddhist Lent Day","TH",2040 +"2040-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2040 +"2040-07-30","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2040 +"2040-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2040 +"2040-08-12","National Mother's Day","TH",2040 +"2040-08-13","HM Queen Sirikit The Queen Mother's Birthday (in lieu)","TH",2040 +"2040-08-13","National Mother's Day (in lieu)","TH",2040 +"2040-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2040 +"2040-10-15","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2040 +"2040-10-23","HM King Chulalongkorn Memorial Day","TH",2040 +"2040-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2040 +"2040-12-05","National Day","TH",2040 +"2040-12-05","National Father's Day","TH",2040 +"2040-12-10","Constitution Day","TH",2040 +"2040-12-31","New Year's Eve","TH",2040 +"2041-01-01","New Year's Day","TH",2041 +"2041-02-15","Makha Bucha","TH",2041 +"2041-04-06","Chakri Memorial Day","TH",2041 +"2041-04-08","Chakri Memorial Day (in lieu)","TH",2041 +"2041-04-13","Songkran Festival","TH",2041 +"2041-04-14","Songkran Festival","TH",2041 +"2041-04-15","Songkran Festival","TH",2041 +"2041-04-16","Songkran Festival (in lieu)","TH",2041 +"2041-05-01","National Labour Day","TH",2041 +"2041-05-04","Coronation Day","TH",2041 +"2041-05-06","Coronation Day (in lieu)","TH",2041 +"2041-05-14","Visakha Bucha","TH",2041 +"2041-06-03","HM Queen Suthida's Birthday","TH",2041 +"2041-07-12","Asarnha Bucha","TH",2041 +"2041-07-13","Buddhist Lent Day","TH",2041 +"2041-07-15","Buddhist Lent Day (in lieu)","TH",2041 +"2041-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2041 +"2041-07-29","HM King Maha Vajiralongkorn's Birthday (in lieu)","TH",2041 +"2041-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2041 +"2041-08-12","National Mother's Day","TH",2041 +"2041-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2041 +"2041-10-14","HM King Bhumibol Adulyadej the Great Memorial Day (in lieu)","TH",2041 +"2041-10-23","HM King Chulalongkorn Memorial Day","TH",2041 +"2041-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2041 +"2041-12-05","National Day","TH",2041 +"2041-12-05","National Father's Day","TH",2041 +"2041-12-10","Constitution Day","TH",2041 +"2041-12-31","New Year's Eve","TH",2041 +"2042-01-01","New Year's Day","TH",2042 +"2042-03-05","Makha Bucha","TH",2042 +"2042-04-06","Chakri Memorial Day","TH",2042 +"2042-04-07","Chakri Memorial Day (in lieu)","TH",2042 +"2042-04-13","Songkran Festival","TH",2042 +"2042-04-14","Songkran Festival","TH",2042 +"2042-04-15","Songkran Festival","TH",2042 +"2042-05-01","National Labour Day","TH",2042 +"2042-05-04","Coronation Day","TH",2042 +"2042-05-05","Coronation Day (in lieu)","TH",2042 +"2042-06-02","Visakha Bucha","TH",2042 +"2042-06-03","HM Queen Suthida's Birthday","TH",2042 +"2042-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2042 +"2042-07-31","Asarnha Bucha","TH",2042 +"2042-08-01","Buddhist Lent Day","TH",2042 +"2042-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2042 +"2042-08-12","National Mother's Day","TH",2042 +"2042-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2042 +"2042-10-23","HM King Chulalongkorn Memorial Day","TH",2042 +"2042-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2042 +"2042-12-05","National Day","TH",2042 +"2042-12-05","National Father's Day","TH",2042 +"2042-12-10","Constitution Day","TH",2042 +"2042-12-31","New Year's Eve","TH",2042 +"2043-01-01","New Year's Day","TH",2043 +"2043-02-23","Makha Bucha","TH",2043 +"2043-04-06","Chakri Memorial Day","TH",2043 +"2043-04-13","Songkran Festival","TH",2043 +"2043-04-14","Songkran Festival","TH",2043 +"2043-04-15","Songkran Festival","TH",2043 +"2043-05-01","National Labour Day","TH",2043 +"2043-05-04","Coronation Day","TH",2043 +"2043-05-22","Visakha Bucha","TH",2043 +"2043-06-03","HM Queen Suthida's Birthday","TH",2043 +"2043-07-21","Asarnha Bucha","TH",2043 +"2043-07-22","Buddhist Lent Day","TH",2043 +"2043-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2043 +"2043-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2043 +"2043-08-12","National Mother's Day","TH",2043 +"2043-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2043 +"2043-10-23","HM King Chulalongkorn Memorial Day","TH",2043 +"2043-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2043 +"2043-12-05","National Day","TH",2043 +"2043-12-05","National Father's Day","TH",2043 +"2043-12-07","HM King Bhumibol Adulyadej the Great's Birthday (in lieu)","TH",2043 +"2043-12-07","National Day (in lieu)","TH",2043 +"2043-12-07","National Father's Day (in lieu)","TH",2043 +"2043-12-10","Constitution Day","TH",2043 +"2043-12-31","New Year's Eve","TH",2043 +"2044-01-01","New Year's Day","TH",2044 +"2044-02-13","Makha Bucha","TH",2044 +"2044-02-15","Makha Bucha (in lieu)","TH",2044 +"2044-04-06","Chakri Memorial Day","TH",2044 +"2044-04-13","Songkran Festival","TH",2044 +"2044-04-14","Songkran Festival","TH",2044 +"2044-04-15","Songkran Festival","TH",2044 +"2044-05-01","National Labour Day","TH",2044 +"2044-05-02","National Labour Day (in lieu)","TH",2044 +"2044-05-04","Coronation Day","TH",2044 +"2044-05-11","Visakha Bucha","TH",2044 +"2044-06-03","HM Queen Suthida's Birthday","TH",2044 +"2044-07-09","Asarnha Bucha","TH",2044 +"2044-07-10","Buddhist Lent Day","TH",2044 +"2044-07-11","Asarnha Bucha (in lieu)","TH",2044 +"2044-07-28","HM King Maha Vajiralongkorn's Birthday","TH",2044 +"2044-08-12","HM Queen Sirikit The Queen Mother's Birthday","TH",2044 +"2044-08-12","National Mother's Day","TH",2044 +"2044-10-13","HM King Bhumibol Adulyadej the Great Memorial Day","TH",2044 +"2044-10-23","HM King Chulalongkorn Memorial Day","TH",2044 +"2044-10-24","HM King Chulalongkorn Memorial Day (in lieu)","TH",2044 +"2044-12-05","HM King Bhumibol Adulyadej the Great's Birthday","TH",2044 +"2044-12-05","National Day","TH",2044 +"2044-12-05","National Father's Day","TH",2044 +"2044-12-10","Constitution Day","TH",2044 +"2044-12-12","Constitution Day (in lieu)","TH",2044 +"2044-12-31","New Year's Eve","TH",2044 +"1995-01-01","New Year's Day","TN",1995 +"1995-01-14","Revolution and Youth Day - January 14","TN",1995 +"1995-03-02","Eid al-Fitr* (*estimated)","TN",1995 +"1995-03-03","Eid al-Fitr Holiday* (*estimated)","TN",1995 +"1995-03-04","Eid al-Fitr Holiday* (*estimated)","TN",1995 +"1995-03-20","Independence Day","TN",1995 +"1995-04-09","Martyrs' Day","TN",1995 +"1995-05-01","Labour Day","TN",1995 +"1995-05-08","Arafat Day* (*estimated)","TN",1995 +"1995-05-09","Eid al-Adha* (*estimated)","TN",1995 +"1995-05-10","Eid al-Adha Holiday* (*estimated)","TN",1995 +"1995-05-11","Eid al-Adha Holiday* (*estimated)","TN",1995 +"1995-05-30","Islamic New Year* (*estimated)","TN",1995 +"1995-07-25","Republic Day","TN",1995 +"1995-08-08","Prophet Muhammad's Birthday* (*estimated)","TN",1995 +"1995-08-13","Women's Day","TN",1995 +"1995-10-15","Evacuation Day","TN",1995 +"1996-01-01","New Year's Day","TN",1996 +"1996-01-14","Revolution and Youth Day - January 14","TN",1996 +"1996-02-19","Eid al-Fitr* (*estimated)","TN",1996 +"1996-02-20","Eid al-Fitr Holiday* (*estimated)","TN",1996 +"1996-02-21","Eid al-Fitr Holiday* (*estimated)","TN",1996 +"1996-03-20","Independence Day","TN",1996 +"1996-04-09","Martyrs' Day","TN",1996 +"1996-04-26","Arafat Day* (*estimated)","TN",1996 +"1996-04-27","Eid al-Adha* (*estimated)","TN",1996 +"1996-04-28","Eid al-Adha Holiday* (*estimated)","TN",1996 +"1996-04-29","Eid al-Adha Holiday* (*estimated)","TN",1996 +"1996-05-01","Labour Day","TN",1996 +"1996-05-18","Islamic New Year* (*estimated)","TN",1996 +"1996-07-25","Republic Day","TN",1996 +"1996-07-27","Prophet Muhammad's Birthday* (*estimated)","TN",1996 +"1996-08-13","Women's Day","TN",1996 +"1996-10-15","Evacuation Day","TN",1996 +"1997-01-01","New Year's Day","TN",1997 +"1997-01-14","Revolution and Youth Day - January 14","TN",1997 +"1997-02-08","Eid al-Fitr* (*estimated)","TN",1997 +"1997-02-09","Eid al-Fitr Holiday* (*estimated)","TN",1997 +"1997-02-10","Eid al-Fitr Holiday* (*estimated)","TN",1997 +"1997-03-20","Independence Day","TN",1997 +"1997-04-09","Martyrs' Day","TN",1997 +"1997-04-16","Arafat Day* (*estimated)","TN",1997 +"1997-04-17","Eid al-Adha* (*estimated)","TN",1997 +"1997-04-18","Eid al-Adha Holiday* (*estimated)","TN",1997 +"1997-04-19","Eid al-Adha Holiday* (*estimated)","TN",1997 +"1997-05-01","Labour Day","TN",1997 +"1997-05-07","Islamic New Year* (*estimated)","TN",1997 +"1997-07-16","Prophet Muhammad's Birthday* (*estimated)","TN",1997 +"1997-07-25","Republic Day","TN",1997 +"1997-08-13","Women's Day","TN",1997 +"1997-10-15","Evacuation Day","TN",1997 +"1998-01-01","New Year's Day","TN",1998 +"1998-01-14","Revolution and Youth Day - January 14","TN",1998 +"1998-01-29","Eid al-Fitr* (*estimated)","TN",1998 +"1998-01-30","Eid al-Fitr Holiday* (*estimated)","TN",1998 +"1998-01-31","Eid al-Fitr Holiday* (*estimated)","TN",1998 +"1998-03-20","Independence Day","TN",1998 +"1998-04-06","Arafat Day* (*estimated)","TN",1998 +"1998-04-07","Eid al-Adha* (*estimated)","TN",1998 +"1998-04-08","Eid al-Adha Holiday* (*estimated)","TN",1998 +"1998-04-09","Eid al-Adha Holiday* (*estimated)","TN",1998 +"1998-04-09","Martyrs' Day","TN",1998 +"1998-04-27","Islamic New Year* (*estimated)","TN",1998 +"1998-05-01","Labour Day","TN",1998 +"1998-07-06","Prophet Muhammad's Birthday* (*estimated)","TN",1998 +"1998-07-25","Republic Day","TN",1998 +"1998-08-13","Women's Day","TN",1998 +"1998-10-15","Evacuation Day","TN",1998 +"1999-01-01","New Year's Day","TN",1999 +"1999-01-14","Revolution and Youth Day - January 14","TN",1999 +"1999-01-18","Eid al-Fitr* (*estimated)","TN",1999 +"1999-01-19","Eid al-Fitr Holiday* (*estimated)","TN",1999 +"1999-01-20","Eid al-Fitr Holiday* (*estimated)","TN",1999 +"1999-03-20","Independence Day","TN",1999 +"1999-03-26","Arafat Day* (*estimated)","TN",1999 +"1999-03-27","Eid al-Adha* (*estimated)","TN",1999 +"1999-03-28","Eid al-Adha Holiday* (*estimated)","TN",1999 +"1999-03-29","Eid al-Adha Holiday* (*estimated)","TN",1999 +"1999-04-09","Martyrs' Day","TN",1999 +"1999-04-17","Islamic New Year* (*estimated)","TN",1999 +"1999-05-01","Labour Day","TN",1999 +"1999-06-26","Prophet Muhammad's Birthday* (*estimated)","TN",1999 +"1999-07-25","Republic Day","TN",1999 +"1999-08-13","Women's Day","TN",1999 +"1999-10-15","Evacuation Day","TN",1999 +"2000-01-01","New Year's Day","TN",2000 +"2000-01-08","Eid al-Fitr* (*estimated)","TN",2000 +"2000-01-09","Eid al-Fitr Holiday* (*estimated)","TN",2000 +"2000-01-10","Eid al-Fitr Holiday* (*estimated)","TN",2000 +"2000-01-14","Revolution and Youth Day - January 14","TN",2000 +"2000-03-15","Arafat Day* (*estimated)","TN",2000 +"2000-03-16","Eid al-Adha* (*estimated)","TN",2000 +"2000-03-17","Eid al-Adha Holiday* (*estimated)","TN",2000 +"2000-03-18","Eid al-Adha Holiday* (*estimated)","TN",2000 +"2000-03-20","Independence Day","TN",2000 +"2000-04-06","Islamic New Year* (*estimated)","TN",2000 +"2000-04-09","Martyrs' Day","TN",2000 +"2000-05-01","Labour Day","TN",2000 +"2000-06-14","Prophet Muhammad's Birthday* (*estimated)","TN",2000 +"2000-07-25","Republic Day","TN",2000 +"2000-08-13","Women's Day","TN",2000 +"2000-10-15","Evacuation Day","TN",2000 +"2000-12-27","Eid al-Fitr* (*estimated)","TN",2000 +"2000-12-28","Eid al-Fitr Holiday* (*estimated)","TN",2000 +"2000-12-29","Eid al-Fitr Holiday* (*estimated)","TN",2000 +"2001-01-01","New Year's Day","TN",2001 +"2001-01-14","Revolution and Youth Day - January 14","TN",2001 +"2001-03-04","Arafat Day* (*estimated)","TN",2001 +"2001-03-05","Eid al-Adha* (*estimated)","TN",2001 +"2001-03-06","Eid al-Adha Holiday* (*estimated)","TN",2001 +"2001-03-07","Eid al-Adha Holiday* (*estimated)","TN",2001 +"2001-03-20","Independence Day","TN",2001 +"2001-03-26","Islamic New Year* (*estimated)","TN",2001 +"2001-04-09","Martyrs' Day","TN",2001 +"2001-05-01","Labour Day","TN",2001 +"2001-06-04","Prophet Muhammad's Birthday* (*estimated)","TN",2001 +"2001-07-25","Republic Day","TN",2001 +"2001-08-13","Women's Day","TN",2001 +"2001-10-15","Evacuation Day","TN",2001 +"2001-12-16","Eid al-Fitr* (*estimated)","TN",2001 +"2001-12-17","Eid al-Fitr Holiday* (*estimated)","TN",2001 +"2001-12-18","Eid al-Fitr Holiday* (*estimated)","TN",2001 +"2002-01-01","New Year's Day","TN",2002 +"2002-01-14","Revolution and Youth Day - January 14","TN",2002 +"2002-02-21","Arafat Day* (*estimated)","TN",2002 +"2002-02-22","Eid al-Adha* (*estimated)","TN",2002 +"2002-02-23","Eid al-Adha Holiday* (*estimated)","TN",2002 +"2002-02-24","Eid al-Adha Holiday* (*estimated)","TN",2002 +"2002-03-15","Islamic New Year* (*estimated)","TN",2002 +"2002-03-20","Independence Day","TN",2002 +"2002-04-09","Martyrs' Day","TN",2002 +"2002-05-01","Labour Day","TN",2002 +"2002-05-24","Prophet Muhammad's Birthday* (*estimated)","TN",2002 +"2002-07-25","Republic Day","TN",2002 +"2002-08-13","Women's Day","TN",2002 +"2002-10-15","Evacuation Day","TN",2002 +"2002-12-05","Eid al-Fitr* (*estimated)","TN",2002 +"2002-12-06","Eid al-Fitr Holiday* (*estimated)","TN",2002 +"2002-12-07","Eid al-Fitr Holiday* (*estimated)","TN",2002 +"2003-01-01","New Year's Day","TN",2003 +"2003-01-14","Revolution and Youth Day - January 14","TN",2003 +"2003-02-10","Arafat Day* (*estimated)","TN",2003 +"2003-02-11","Eid al-Adha* (*estimated)","TN",2003 +"2003-02-12","Eid al-Adha Holiday* (*estimated)","TN",2003 +"2003-02-13","Eid al-Adha Holiday* (*estimated)","TN",2003 +"2003-03-04","Islamic New Year* (*estimated)","TN",2003 +"2003-03-20","Independence Day","TN",2003 +"2003-04-09","Martyrs' Day","TN",2003 +"2003-05-01","Labour Day","TN",2003 +"2003-05-13","Prophet Muhammad's Birthday* (*estimated)","TN",2003 +"2003-07-25","Republic Day","TN",2003 +"2003-08-13","Women's Day","TN",2003 +"2003-10-15","Evacuation Day","TN",2003 +"2003-11-25","Eid al-Fitr* (*estimated)","TN",2003 +"2003-11-26","Eid al-Fitr Holiday* (*estimated)","TN",2003 +"2003-11-27","Eid al-Fitr Holiday* (*estimated)","TN",2003 +"2004-01-01","New Year's Day","TN",2004 +"2004-01-14","Revolution and Youth Day - January 14","TN",2004 +"2004-01-31","Arafat Day* (*estimated)","TN",2004 +"2004-02-01","Eid al-Adha* (*estimated)","TN",2004 +"2004-02-02","Eid al-Adha Holiday* (*estimated)","TN",2004 +"2004-02-03","Eid al-Adha Holiday* (*estimated)","TN",2004 +"2004-02-21","Islamic New Year* (*estimated)","TN",2004 +"2004-03-20","Independence Day","TN",2004 +"2004-04-09","Martyrs' Day","TN",2004 +"2004-05-01","Labour Day","TN",2004 +"2004-05-01","Prophet Muhammad's Birthday* (*estimated)","TN",2004 +"2004-07-25","Republic Day","TN",2004 +"2004-08-13","Women's Day","TN",2004 +"2004-10-15","Evacuation Day","TN",2004 +"2004-11-14","Eid al-Fitr* (*estimated)","TN",2004 +"2004-11-15","Eid al-Fitr Holiday* (*estimated)","TN",2004 +"2004-11-16","Eid al-Fitr Holiday* (*estimated)","TN",2004 +"2005-01-01","New Year's Day","TN",2005 +"2005-01-14","Revolution and Youth Day - January 14","TN",2005 +"2005-01-20","Arafat Day* (*estimated)","TN",2005 +"2005-01-21","Eid al-Adha* (*estimated)","TN",2005 +"2005-01-22","Eid al-Adha Holiday* (*estimated)","TN",2005 +"2005-01-23","Eid al-Adha Holiday* (*estimated)","TN",2005 +"2005-02-10","Islamic New Year* (*estimated)","TN",2005 +"2005-03-20","Independence Day","TN",2005 +"2005-04-09","Martyrs' Day","TN",2005 +"2005-04-21","Prophet Muhammad's Birthday* (*estimated)","TN",2005 +"2005-05-01","Labour Day","TN",2005 +"2005-07-25","Republic Day","TN",2005 +"2005-08-13","Women's Day","TN",2005 +"2005-10-15","Evacuation Day","TN",2005 +"2005-11-03","Eid al-Fitr* (*estimated)","TN",2005 +"2005-11-04","Eid al-Fitr Holiday* (*estimated)","TN",2005 +"2005-11-05","Eid al-Fitr Holiday* (*estimated)","TN",2005 +"2006-01-01","New Year's Day","TN",2006 +"2006-01-09","Arafat Day* (*estimated)","TN",2006 +"2006-01-10","Eid al-Adha* (*estimated)","TN",2006 +"2006-01-11","Eid al-Adha Holiday* (*estimated)","TN",2006 +"2006-01-12","Eid al-Adha Holiday* (*estimated)","TN",2006 +"2006-01-14","Revolution and Youth Day - January 14","TN",2006 +"2006-01-31","Islamic New Year* (*estimated)","TN",2006 +"2006-03-20","Independence Day","TN",2006 +"2006-04-09","Martyrs' Day","TN",2006 +"2006-04-10","Prophet Muhammad's Birthday* (*estimated)","TN",2006 +"2006-05-01","Labour Day","TN",2006 +"2006-07-25","Republic Day","TN",2006 +"2006-08-13","Women's Day","TN",2006 +"2006-10-15","Evacuation Day","TN",2006 +"2006-10-23","Eid al-Fitr* (*estimated)","TN",2006 +"2006-10-24","Eid al-Fitr Holiday* (*estimated)","TN",2006 +"2006-10-25","Eid al-Fitr Holiday* (*estimated)","TN",2006 +"2006-12-30","Arafat Day* (*estimated)","TN",2006 +"2006-12-31","Eid al-Adha* (*estimated)","TN",2006 +"2007-01-01","Eid al-Adha Holiday* (*estimated)","TN",2007 +"2007-01-01","New Year's Day","TN",2007 +"2007-01-02","Eid al-Adha Holiday* (*estimated)","TN",2007 +"2007-01-14","Revolution and Youth Day - January 14","TN",2007 +"2007-01-20","Islamic New Year* (*estimated)","TN",2007 +"2007-03-20","Independence Day","TN",2007 +"2007-03-31","Prophet Muhammad's Birthday* (*estimated)","TN",2007 +"2007-04-09","Martyrs' Day","TN",2007 +"2007-05-01","Labour Day","TN",2007 +"2007-07-25","Republic Day","TN",2007 +"2007-08-13","Women's Day","TN",2007 +"2007-10-13","Eid al-Fitr* (*estimated)","TN",2007 +"2007-10-14","Eid al-Fitr Holiday* (*estimated)","TN",2007 +"2007-10-15","Eid al-Fitr Holiday* (*estimated)","TN",2007 +"2007-10-15","Evacuation Day","TN",2007 +"2007-12-19","Arafat Day* (*estimated)","TN",2007 +"2007-12-20","Eid al-Adha* (*estimated)","TN",2007 +"2007-12-21","Eid al-Adha Holiday* (*estimated)","TN",2007 +"2007-12-22","Eid al-Adha Holiday* (*estimated)","TN",2007 +"2008-01-01","New Year's Day","TN",2008 +"2008-01-10","Islamic New Year* (*estimated)","TN",2008 +"2008-01-14","Revolution and Youth Day - January 14","TN",2008 +"2008-03-20","Independence Day","TN",2008 +"2008-03-20","Prophet Muhammad's Birthday* (*estimated)","TN",2008 +"2008-04-09","Martyrs' Day","TN",2008 +"2008-05-01","Labour Day","TN",2008 +"2008-07-25","Republic Day","TN",2008 +"2008-08-13","Women's Day","TN",2008 +"2008-10-01","Eid al-Fitr* (*estimated)","TN",2008 +"2008-10-02","Eid al-Fitr Holiday* (*estimated)","TN",2008 +"2008-10-03","Eid al-Fitr Holiday* (*estimated)","TN",2008 +"2008-10-15","Evacuation Day","TN",2008 +"2008-12-07","Arafat Day* (*estimated)","TN",2008 +"2008-12-08","Eid al-Adha* (*estimated)","TN",2008 +"2008-12-09","Eid al-Adha Holiday* (*estimated)","TN",2008 +"2008-12-10","Eid al-Adha Holiday* (*estimated)","TN",2008 +"2008-12-29","Islamic New Year* (*estimated)","TN",2008 +"2009-01-01","New Year's Day","TN",2009 +"2009-01-14","Revolution and Youth Day - January 14","TN",2009 +"2009-03-09","Prophet Muhammad's Birthday* (*estimated)","TN",2009 +"2009-03-20","Independence Day","TN",2009 +"2009-04-09","Martyrs' Day","TN",2009 +"2009-05-01","Labour Day","TN",2009 +"2009-07-25","Republic Day","TN",2009 +"2009-08-13","Women's Day","TN",2009 +"2009-09-20","Eid al-Fitr* (*estimated)","TN",2009 +"2009-09-21","Eid al-Fitr Holiday* (*estimated)","TN",2009 +"2009-09-22","Eid al-Fitr Holiday* (*estimated)","TN",2009 +"2009-10-15","Evacuation Day","TN",2009 +"2009-11-26","Arafat Day* (*estimated)","TN",2009 +"2009-11-27","Eid al-Adha* (*estimated)","TN",2009 +"2009-11-28","Eid al-Adha Holiday* (*estimated)","TN",2009 +"2009-11-29","Eid al-Adha Holiday* (*estimated)","TN",2009 +"2009-12-18","Islamic New Year* (*estimated)","TN",2009 +"2010-01-01","New Year's Day","TN",2010 +"2010-01-14","Revolution and Youth Day - January 14","TN",2010 +"2010-02-26","Prophet Muhammad's Birthday* (*estimated)","TN",2010 +"2010-03-20","Independence Day","TN",2010 +"2010-04-09","Martyrs' Day","TN",2010 +"2010-05-01","Labour Day","TN",2010 +"2010-07-25","Republic Day","TN",2010 +"2010-08-13","Women's Day","TN",2010 +"2010-09-10","Eid al-Fitr* (*estimated)","TN",2010 +"2010-09-11","Eid al-Fitr Holiday* (*estimated)","TN",2010 +"2010-09-12","Eid al-Fitr Holiday* (*estimated)","TN",2010 +"2010-10-15","Evacuation Day","TN",2010 +"2010-11-15","Arafat Day* (*estimated)","TN",2010 +"2010-11-16","Eid al-Adha* (*estimated)","TN",2010 +"2010-11-17","Eid al-Adha Holiday* (*estimated)","TN",2010 +"2010-11-18","Eid al-Adha Holiday* (*estimated)","TN",2010 +"2010-12-07","Islamic New Year* (*estimated)","TN",2010 +"2011-01-01","New Year's Day","TN",2011 +"2011-01-14","Revolution and Youth Day - January 14","TN",2011 +"2011-02-15","Prophet Muhammad's Birthday* (*estimated)","TN",2011 +"2011-03-20","Independence Day","TN",2011 +"2011-04-09","Martyrs' Day","TN",2011 +"2011-05-01","Labour Day","TN",2011 +"2011-07-25","Republic Day","TN",2011 +"2011-08-13","Women's Day","TN",2011 +"2011-08-30","Eid al-Fitr* (*estimated)","TN",2011 +"2011-08-31","Eid al-Fitr Holiday* (*estimated)","TN",2011 +"2011-09-01","Eid al-Fitr Holiday* (*estimated)","TN",2011 +"2011-10-15","Evacuation Day","TN",2011 +"2011-11-05","Arafat Day* (*estimated)","TN",2011 +"2011-11-06","Eid al-Adha* (*estimated)","TN",2011 +"2011-11-07","Eid al-Adha Holiday* (*estimated)","TN",2011 +"2011-11-08","Eid al-Adha Holiday* (*estimated)","TN",2011 +"2011-11-26","Islamic New Year* (*estimated)","TN",2011 +"2012-01-01","New Year's Day","TN",2012 +"2012-01-14","Revolution and Youth Day - January 14","TN",2012 +"2012-02-04","Prophet Muhammad's Birthday* (*estimated)","TN",2012 +"2012-03-20","Independence Day","TN",2012 +"2012-04-09","Martyrs' Day","TN",2012 +"2012-05-01","Labour Day","TN",2012 +"2012-07-25","Republic Day","TN",2012 +"2012-08-13","Women's Day","TN",2012 +"2012-08-19","Eid al-Fitr* (*estimated)","TN",2012 +"2012-08-20","Eid al-Fitr Holiday* (*estimated)","TN",2012 +"2012-08-21","Eid al-Fitr Holiday* (*estimated)","TN",2012 +"2012-10-15","Evacuation Day","TN",2012 +"2012-10-25","Arafat Day* (*estimated)","TN",2012 +"2012-10-26","Eid al-Adha* (*estimated)","TN",2012 +"2012-10-27","Eid al-Adha Holiday* (*estimated)","TN",2012 +"2012-10-28","Eid al-Adha Holiday* (*estimated)","TN",2012 +"2012-11-15","Islamic New Year* (*estimated)","TN",2012 +"2013-01-01","New Year's Day","TN",2013 +"2013-01-14","Revolution and Youth Day - January 14","TN",2013 +"2013-01-24","Prophet Muhammad's Birthday* (*estimated)","TN",2013 +"2013-03-20","Independence Day","TN",2013 +"2013-04-09","Martyrs' Day","TN",2013 +"2013-05-01","Labour Day","TN",2013 +"2013-07-25","Republic Day","TN",2013 +"2013-08-08","Eid al-Fitr* (*estimated)","TN",2013 +"2013-08-09","Eid al-Fitr Holiday* (*estimated)","TN",2013 +"2013-08-10","Eid al-Fitr Holiday* (*estimated)","TN",2013 +"2013-08-13","Women's Day","TN",2013 +"2013-10-14","Arafat Day* (*estimated)","TN",2013 +"2013-10-15","Eid al-Adha* (*estimated)","TN",2013 +"2013-10-15","Evacuation Day","TN",2013 +"2013-10-16","Eid al-Adha Holiday* (*estimated)","TN",2013 +"2013-10-17","Eid al-Adha Holiday* (*estimated)","TN",2013 +"2013-11-04","Islamic New Year* (*estimated)","TN",2013 +"2014-01-01","New Year's Day","TN",2014 +"2014-01-13","Prophet Muhammad's Birthday* (*estimated)","TN",2014 +"2014-01-14","Revolution and Youth Day - January 14","TN",2014 +"2014-03-20","Independence Day","TN",2014 +"2014-04-09","Martyrs' Day","TN",2014 +"2014-05-01","Labour Day","TN",2014 +"2014-07-25","Republic Day","TN",2014 +"2014-07-28","Eid al-Fitr* (*estimated)","TN",2014 +"2014-07-29","Eid al-Fitr Holiday* (*estimated)","TN",2014 +"2014-07-30","Eid al-Fitr Holiday* (*estimated)","TN",2014 +"2014-08-13","Women's Day","TN",2014 +"2014-10-03","Arafat Day* (*estimated)","TN",2014 +"2014-10-04","Eid al-Adha* (*estimated)","TN",2014 +"2014-10-05","Eid al-Adha Holiday* (*estimated)","TN",2014 +"2014-10-06","Eid al-Adha Holiday* (*estimated)","TN",2014 +"2014-10-15","Evacuation Day","TN",2014 +"2014-10-25","Islamic New Year* (*estimated)","TN",2014 +"2015-01-01","New Year's Day","TN",2015 +"2015-01-03","Prophet Muhammad's Birthday* (*estimated)","TN",2015 +"2015-01-14","Revolution and Youth Day - January 14","TN",2015 +"2015-03-20","Independence Day","TN",2015 +"2015-04-09","Martyrs' Day","TN",2015 +"2015-05-01","Labour Day","TN",2015 +"2015-07-17","Eid al-Fitr* (*estimated)","TN",2015 +"2015-07-18","Eid al-Fitr Holiday* (*estimated)","TN",2015 +"2015-07-19","Eid al-Fitr Holiday* (*estimated)","TN",2015 +"2015-07-25","Republic Day","TN",2015 +"2015-08-13","Women's Day","TN",2015 +"2015-09-22","Arafat Day* (*estimated)","TN",2015 +"2015-09-23","Eid al-Adha* (*estimated)","TN",2015 +"2015-09-24","Eid al-Adha Holiday* (*estimated)","TN",2015 +"2015-09-25","Eid al-Adha Holiday* (*estimated)","TN",2015 +"2015-10-14","Islamic New Year* (*estimated)","TN",2015 +"2015-10-15","Evacuation Day","TN",2015 +"2015-12-23","Prophet Muhammad's Birthday* (*estimated)","TN",2015 +"2016-01-01","New Year's Day","TN",2016 +"2016-01-14","Revolution and Youth Day - January 14","TN",2016 +"2016-03-20","Independence Day","TN",2016 +"2016-04-09","Martyrs' Day","TN",2016 +"2016-05-01","Labour Day","TN",2016 +"2016-07-06","Eid al-Fitr* (*estimated)","TN",2016 +"2016-07-07","Eid al-Fitr Holiday* (*estimated)","TN",2016 +"2016-07-08","Eid al-Fitr Holiday* (*estimated)","TN",2016 +"2016-07-25","Republic Day","TN",2016 +"2016-08-13","Women's Day","TN",2016 +"2016-09-10","Arafat Day* (*estimated)","TN",2016 +"2016-09-11","Eid al-Adha* (*estimated)","TN",2016 +"2016-09-12","Eid al-Adha Holiday* (*estimated)","TN",2016 +"2016-09-13","Eid al-Adha Holiday* (*estimated)","TN",2016 +"2016-10-02","Islamic New Year* (*estimated)","TN",2016 +"2016-10-15","Evacuation Day","TN",2016 +"2016-12-11","Prophet Muhammad's Birthday* (*estimated)","TN",2016 +"2017-01-01","New Year's Day","TN",2017 +"2017-01-14","Revolution and Youth Day - January 14","TN",2017 +"2017-03-20","Independence Day","TN",2017 +"2017-04-09","Martyrs' Day","TN",2017 +"2017-05-01","Labour Day","TN",2017 +"2017-06-25","Eid al-Fitr* (*estimated)","TN",2017 +"2017-06-26","Eid al-Fitr Holiday* (*estimated)","TN",2017 +"2017-06-27","Eid al-Fitr Holiday* (*estimated)","TN",2017 +"2017-07-25","Republic Day","TN",2017 +"2017-08-13","Women's Day","TN",2017 +"2017-08-31","Arafat Day* (*estimated)","TN",2017 +"2017-09-01","Eid al-Adha* (*estimated)","TN",2017 +"2017-09-02","Eid al-Adha Holiday* (*estimated)","TN",2017 +"2017-09-03","Eid al-Adha Holiday* (*estimated)","TN",2017 +"2017-09-21","Islamic New Year* (*estimated)","TN",2017 +"2017-10-15","Evacuation Day","TN",2017 +"2017-11-30","Prophet Muhammad's Birthday* (*estimated)","TN",2017 +"2018-01-01","New Year's Day","TN",2018 +"2018-01-14","Revolution and Youth Day - January 14","TN",2018 +"2018-03-20","Independence Day","TN",2018 +"2018-04-09","Martyrs' Day","TN",2018 +"2018-05-01","Labour Day","TN",2018 +"2018-06-15","Eid al-Fitr* (*estimated)","TN",2018 +"2018-06-16","Eid al-Fitr Holiday* (*estimated)","TN",2018 +"2018-06-17","Eid al-Fitr Holiday* (*estimated)","TN",2018 +"2018-07-25","Republic Day","TN",2018 +"2018-08-13","Women's Day","TN",2018 +"2018-08-20","Arafat Day* (*estimated)","TN",2018 +"2018-08-21","Eid al-Adha* (*estimated)","TN",2018 +"2018-08-22","Eid al-Adha Holiday* (*estimated)","TN",2018 +"2018-08-23","Eid al-Adha Holiday* (*estimated)","TN",2018 +"2018-09-11","Islamic New Year* (*estimated)","TN",2018 +"2018-10-15","Evacuation Day","TN",2018 +"2018-11-20","Prophet Muhammad's Birthday* (*estimated)","TN",2018 +"2019-01-01","New Year's Day","TN",2019 +"2019-01-14","Revolution and Youth Day - January 14","TN",2019 +"2019-03-20","Independence Day","TN",2019 +"2019-04-09","Martyrs' Day","TN",2019 +"2019-05-01","Labour Day","TN",2019 +"2019-06-04","Eid al-Fitr* (*estimated)","TN",2019 +"2019-06-05","Eid al-Fitr Holiday* (*estimated)","TN",2019 +"2019-06-06","Eid al-Fitr Holiday* (*estimated)","TN",2019 +"2019-07-25","Republic Day","TN",2019 +"2019-08-10","Arafat Day* (*estimated)","TN",2019 +"2019-08-11","Eid al-Adha* (*estimated)","TN",2019 +"2019-08-12","Eid al-Adha Holiday* (*estimated)","TN",2019 +"2019-08-13","Eid al-Adha Holiday* (*estimated)","TN",2019 +"2019-08-13","Women's Day","TN",2019 +"2019-08-31","Islamic New Year* (*estimated)","TN",2019 +"2019-10-15","Evacuation Day","TN",2019 +"2019-11-09","Prophet Muhammad's Birthday* (*estimated)","TN",2019 +"2020-01-01","New Year's Day","TN",2020 +"2020-01-14","Revolution and Youth Day - January 14","TN",2020 +"2020-03-20","Independence Day","TN",2020 +"2020-04-09","Martyrs' Day","TN",2020 +"2020-05-01","Labour Day","TN",2020 +"2020-05-24","Eid al-Fitr* (*estimated)","TN",2020 +"2020-05-25","Eid al-Fitr Holiday* (*estimated)","TN",2020 +"2020-05-26","Eid al-Fitr Holiday* (*estimated)","TN",2020 +"2020-07-25","Republic Day","TN",2020 +"2020-07-30","Arafat Day* (*estimated)","TN",2020 +"2020-07-31","Eid al-Adha* (*estimated)","TN",2020 +"2020-08-01","Eid al-Adha Holiday* (*estimated)","TN",2020 +"2020-08-02","Eid al-Adha Holiday* (*estimated)","TN",2020 +"2020-08-13","Women's Day","TN",2020 +"2020-08-20","Islamic New Year* (*estimated)","TN",2020 +"2020-10-15","Evacuation Day","TN",2020 +"2020-10-29","Prophet Muhammad's Birthday* (*estimated)","TN",2020 +"2021-01-01","New Year's Day","TN",2021 +"2021-01-14","Revolution and Youth Day - January 14","TN",2021 +"2021-03-20","Independence Day","TN",2021 +"2021-04-09","Martyrs' Day","TN",2021 +"2021-05-01","Labour Day","TN",2021 +"2021-05-13","Eid al-Fitr* (*estimated)","TN",2021 +"2021-05-14","Eid al-Fitr Holiday* (*estimated)","TN",2021 +"2021-05-15","Eid al-Fitr Holiday* (*estimated)","TN",2021 +"2021-07-19","Arafat Day* (*estimated)","TN",2021 +"2021-07-20","Eid al-Adha* (*estimated)","TN",2021 +"2021-07-21","Eid al-Adha Holiday* (*estimated)","TN",2021 +"2021-07-22","Eid al-Adha Holiday* (*estimated)","TN",2021 +"2021-07-25","Republic Day","TN",2021 +"2021-08-09","Islamic New Year* (*estimated)","TN",2021 +"2021-08-13","Women's Day","TN",2021 +"2021-10-15","Evacuation Day","TN",2021 +"2021-10-18","Prophet Muhammad's Birthday* (*estimated)","TN",2021 +"2022-01-01","New Year's Day","TN",2022 +"2022-01-14","Revolution and Youth Day - January 14","TN",2022 +"2022-03-20","Independence Day","TN",2022 +"2022-04-09","Martyrs' Day","TN",2022 +"2022-05-01","Labour Day","TN",2022 +"2022-05-02","Eid al-Fitr* (*estimated)","TN",2022 +"2022-05-03","Eid al-Fitr Holiday* (*estimated)","TN",2022 +"2022-05-04","Eid al-Fitr Holiday* (*estimated)","TN",2022 +"2022-07-08","Arafat Day* (*estimated)","TN",2022 +"2022-07-09","Eid al-Adha* (*estimated)","TN",2022 +"2022-07-10","Eid al-Adha Holiday* (*estimated)","TN",2022 +"2022-07-11","Eid al-Adha Holiday* (*estimated)","TN",2022 +"2022-07-25","Republic Day","TN",2022 +"2022-07-30","Islamic New Year* (*estimated)","TN",2022 +"2022-08-13","Women's Day","TN",2022 +"2022-10-08","Prophet Muhammad's Birthday* (*estimated)","TN",2022 +"2022-10-15","Evacuation Day","TN",2022 +"2023-01-01","New Year's Day","TN",2023 +"2023-01-14","Revolution and Youth Day - January 14","TN",2023 +"2023-03-20","Independence Day","TN",2023 +"2023-04-09","Martyrs' Day","TN",2023 +"2023-04-21","Eid al-Fitr* (*estimated)","TN",2023 +"2023-04-22","Eid al-Fitr Holiday* (*estimated)","TN",2023 +"2023-04-23","Eid al-Fitr Holiday* (*estimated)","TN",2023 +"2023-05-01","Labour Day","TN",2023 +"2023-06-27","Arafat Day* (*estimated)","TN",2023 +"2023-06-28","Eid al-Adha* (*estimated)","TN",2023 +"2023-06-29","Eid al-Adha Holiday* (*estimated)","TN",2023 +"2023-06-30","Eid al-Adha Holiday* (*estimated)","TN",2023 +"2023-07-19","Islamic New Year* (*estimated)","TN",2023 +"2023-07-25","Republic Day","TN",2023 +"2023-08-13","Women's Day","TN",2023 +"2023-09-27","Prophet Muhammad's Birthday* (*estimated)","TN",2023 +"2023-10-15","Evacuation Day","TN",2023 +"2024-01-01","New Year's Day","TN",2024 +"2024-01-14","Revolution and Youth Day - January 14","TN",2024 +"2024-03-20","Independence Day","TN",2024 +"2024-04-09","Martyrs' Day","TN",2024 +"2024-04-10","Eid al-Fitr* (*estimated)","TN",2024 +"2024-04-11","Eid al-Fitr Holiday* (*estimated)","TN",2024 +"2024-04-12","Eid al-Fitr Holiday* (*estimated)","TN",2024 +"2024-05-01","Labour Day","TN",2024 +"2024-06-15","Arafat Day* (*estimated)","TN",2024 +"2024-06-16","Eid al-Adha* (*estimated)","TN",2024 +"2024-06-17","Eid al-Adha Holiday* (*estimated)","TN",2024 +"2024-06-18","Eid al-Adha Holiday* (*estimated)","TN",2024 +"2024-07-07","Islamic New Year* (*estimated)","TN",2024 +"2024-07-25","Republic Day","TN",2024 +"2024-08-13","Women's Day","TN",2024 +"2024-09-15","Prophet Muhammad's Birthday* (*estimated)","TN",2024 +"2024-10-15","Evacuation Day","TN",2024 +"2025-01-01","New Year's Day","TN",2025 +"2025-01-14","Revolution and Youth Day - January 14","TN",2025 +"2025-03-20","Independence Day","TN",2025 +"2025-03-30","Eid al-Fitr* (*estimated)","TN",2025 +"2025-03-31","Eid al-Fitr Holiday* (*estimated)","TN",2025 +"2025-04-01","Eid al-Fitr Holiday* (*estimated)","TN",2025 +"2025-04-09","Martyrs' Day","TN",2025 +"2025-05-01","Labour Day","TN",2025 +"2025-06-05","Arafat Day* (*estimated)","TN",2025 +"2025-06-06","Eid al-Adha* (*estimated)","TN",2025 +"2025-06-07","Eid al-Adha Holiday* (*estimated)","TN",2025 +"2025-06-08","Eid al-Adha Holiday* (*estimated)","TN",2025 +"2025-06-26","Islamic New Year* (*estimated)","TN",2025 +"2025-07-25","Republic Day","TN",2025 +"2025-08-13","Women's Day","TN",2025 +"2025-09-04","Prophet Muhammad's Birthday* (*estimated)","TN",2025 +"2025-10-15","Evacuation Day","TN",2025 +"2026-01-01","New Year's Day","TN",2026 +"2026-01-14","Revolution and Youth Day - January 14","TN",2026 +"2026-03-20","Eid al-Fitr* (*estimated)","TN",2026 +"2026-03-20","Independence Day","TN",2026 +"2026-03-21","Eid al-Fitr Holiday* (*estimated)","TN",2026 +"2026-03-22","Eid al-Fitr Holiday* (*estimated)","TN",2026 +"2026-04-09","Martyrs' Day","TN",2026 +"2026-05-01","Labour Day","TN",2026 +"2026-05-26","Arafat Day* (*estimated)","TN",2026 +"2026-05-27","Eid al-Adha* (*estimated)","TN",2026 +"2026-05-28","Eid al-Adha Holiday* (*estimated)","TN",2026 +"2026-05-29","Eid al-Adha Holiday* (*estimated)","TN",2026 +"2026-06-16","Islamic New Year* (*estimated)","TN",2026 +"2026-07-25","Republic Day","TN",2026 +"2026-08-13","Women's Day","TN",2026 +"2026-08-25","Prophet Muhammad's Birthday* (*estimated)","TN",2026 +"2026-10-15","Evacuation Day","TN",2026 +"2027-01-01","New Year's Day","TN",2027 +"2027-01-14","Revolution and Youth Day - January 14","TN",2027 +"2027-03-09","Eid al-Fitr* (*estimated)","TN",2027 +"2027-03-10","Eid al-Fitr Holiday* (*estimated)","TN",2027 +"2027-03-11","Eid al-Fitr Holiday* (*estimated)","TN",2027 +"2027-03-20","Independence Day","TN",2027 +"2027-04-09","Martyrs' Day","TN",2027 +"2027-05-01","Labour Day","TN",2027 +"2027-05-15","Arafat Day* (*estimated)","TN",2027 +"2027-05-16","Eid al-Adha* (*estimated)","TN",2027 +"2027-05-17","Eid al-Adha Holiday* (*estimated)","TN",2027 +"2027-05-18","Eid al-Adha Holiday* (*estimated)","TN",2027 +"2027-06-06","Islamic New Year* (*estimated)","TN",2027 +"2027-07-25","Republic Day","TN",2027 +"2027-08-13","Women's Day","TN",2027 +"2027-08-14","Prophet Muhammad's Birthday* (*estimated)","TN",2027 +"2027-10-15","Evacuation Day","TN",2027 +"2028-01-01","New Year's Day","TN",2028 +"2028-01-14","Revolution and Youth Day - January 14","TN",2028 +"2028-02-26","Eid al-Fitr* (*estimated)","TN",2028 +"2028-02-27","Eid al-Fitr Holiday* (*estimated)","TN",2028 +"2028-02-28","Eid al-Fitr Holiday* (*estimated)","TN",2028 +"2028-03-20","Independence Day","TN",2028 +"2028-04-09","Martyrs' Day","TN",2028 +"2028-05-01","Labour Day","TN",2028 +"2028-05-04","Arafat Day* (*estimated)","TN",2028 +"2028-05-05","Eid al-Adha* (*estimated)","TN",2028 +"2028-05-06","Eid al-Adha Holiday* (*estimated)","TN",2028 +"2028-05-07","Eid al-Adha Holiday* (*estimated)","TN",2028 +"2028-05-25","Islamic New Year* (*estimated)","TN",2028 +"2028-07-25","Republic Day","TN",2028 +"2028-08-03","Prophet Muhammad's Birthday* (*estimated)","TN",2028 +"2028-08-13","Women's Day","TN",2028 +"2028-10-15","Evacuation Day","TN",2028 +"2029-01-01","New Year's Day","TN",2029 +"2029-01-14","Revolution and Youth Day - January 14","TN",2029 +"2029-02-14","Eid al-Fitr* (*estimated)","TN",2029 +"2029-02-15","Eid al-Fitr Holiday* (*estimated)","TN",2029 +"2029-02-16","Eid al-Fitr Holiday* (*estimated)","TN",2029 +"2029-03-20","Independence Day","TN",2029 +"2029-04-09","Martyrs' Day","TN",2029 +"2029-04-23","Arafat Day* (*estimated)","TN",2029 +"2029-04-24","Eid al-Adha* (*estimated)","TN",2029 +"2029-04-25","Eid al-Adha Holiday* (*estimated)","TN",2029 +"2029-04-26","Eid al-Adha Holiday* (*estimated)","TN",2029 +"2029-05-01","Labour Day","TN",2029 +"2029-05-14","Islamic New Year* (*estimated)","TN",2029 +"2029-07-24","Prophet Muhammad's Birthday* (*estimated)","TN",2029 +"2029-07-25","Republic Day","TN",2029 +"2029-08-13","Women's Day","TN",2029 +"2029-10-15","Evacuation Day","TN",2029 +"2030-01-01","New Year's Day","TN",2030 +"2030-01-14","Revolution and Youth Day - January 14","TN",2030 +"2030-02-04","Eid al-Fitr* (*estimated)","TN",2030 +"2030-02-05","Eid al-Fitr Holiday* (*estimated)","TN",2030 +"2030-02-06","Eid al-Fitr Holiday* (*estimated)","TN",2030 +"2030-03-20","Independence Day","TN",2030 +"2030-04-09","Martyrs' Day","TN",2030 +"2030-04-12","Arafat Day* (*estimated)","TN",2030 +"2030-04-13","Eid al-Adha* (*estimated)","TN",2030 +"2030-04-14","Eid al-Adha Holiday* (*estimated)","TN",2030 +"2030-04-15","Eid al-Adha Holiday* (*estimated)","TN",2030 +"2030-05-01","Labour Day","TN",2030 +"2030-05-03","Islamic New Year* (*estimated)","TN",2030 +"2030-07-13","Prophet Muhammad's Birthday* (*estimated)","TN",2030 +"2030-07-25","Republic Day","TN",2030 +"2030-08-13","Women's Day","TN",2030 +"2030-10-15","Evacuation Day","TN",2030 +"2031-01-01","New Year's Day","TN",2031 +"2031-01-14","Revolution and Youth Day - January 14","TN",2031 +"2031-01-24","Eid al-Fitr* (*estimated)","TN",2031 +"2031-01-25","Eid al-Fitr Holiday* (*estimated)","TN",2031 +"2031-01-26","Eid al-Fitr Holiday* (*estimated)","TN",2031 +"2031-03-20","Independence Day","TN",2031 +"2031-04-01","Arafat Day* (*estimated)","TN",2031 +"2031-04-02","Eid al-Adha* (*estimated)","TN",2031 +"2031-04-03","Eid al-Adha Holiday* (*estimated)","TN",2031 +"2031-04-04","Eid al-Adha Holiday* (*estimated)","TN",2031 +"2031-04-09","Martyrs' Day","TN",2031 +"2031-04-23","Islamic New Year* (*estimated)","TN",2031 +"2031-05-01","Labour Day","TN",2031 +"2031-07-02","Prophet Muhammad's Birthday* (*estimated)","TN",2031 +"2031-07-25","Republic Day","TN",2031 +"2031-08-13","Women's Day","TN",2031 +"2031-10-15","Evacuation Day","TN",2031 +"2032-01-01","New Year's Day","TN",2032 +"2032-01-14","Eid al-Fitr* (*estimated)","TN",2032 +"2032-01-14","Revolution and Youth Day - January 14","TN",2032 +"2032-01-15","Eid al-Fitr Holiday* (*estimated)","TN",2032 +"2032-01-16","Eid al-Fitr Holiday* (*estimated)","TN",2032 +"2032-03-20","Independence Day","TN",2032 +"2032-03-21","Arafat Day* (*estimated)","TN",2032 +"2032-03-22","Eid al-Adha* (*estimated)","TN",2032 +"2032-03-23","Eid al-Adha Holiday* (*estimated)","TN",2032 +"2032-03-24","Eid al-Adha Holiday* (*estimated)","TN",2032 +"2032-04-09","Martyrs' Day","TN",2032 +"2032-04-11","Islamic New Year* (*estimated)","TN",2032 +"2032-05-01","Labour Day","TN",2032 +"2032-06-20","Prophet Muhammad's Birthday* (*estimated)","TN",2032 +"2032-07-25","Republic Day","TN",2032 +"2032-08-13","Women's Day","TN",2032 +"2032-10-15","Evacuation Day","TN",2032 +"2033-01-01","New Year's Day","TN",2033 +"2033-01-02","Eid al-Fitr* (*estimated)","TN",2033 +"2033-01-03","Eid al-Fitr Holiday* (*estimated)","TN",2033 +"2033-01-04","Eid al-Fitr Holiday* (*estimated)","TN",2033 +"2033-01-14","Revolution and Youth Day - January 14","TN",2033 +"2033-03-10","Arafat Day* (*estimated)","TN",2033 +"2033-03-11","Eid al-Adha* (*estimated)","TN",2033 +"2033-03-12","Eid al-Adha Holiday* (*estimated)","TN",2033 +"2033-03-13","Eid al-Adha Holiday* (*estimated)","TN",2033 +"2033-03-20","Independence Day","TN",2033 +"2033-04-01","Islamic New Year* (*estimated)","TN",2033 +"2033-04-09","Martyrs' Day","TN",2033 +"2033-05-01","Labour Day","TN",2033 +"2033-06-09","Prophet Muhammad's Birthday* (*estimated)","TN",2033 +"2033-07-25","Republic Day","TN",2033 +"2033-08-13","Women's Day","TN",2033 +"2033-10-15","Evacuation Day","TN",2033 +"2033-12-23","Eid al-Fitr* (*estimated)","TN",2033 +"2033-12-24","Eid al-Fitr Holiday* (*estimated)","TN",2033 +"2033-12-25","Eid al-Fitr Holiday* (*estimated)","TN",2033 +"2034-01-01","New Year's Day","TN",2034 +"2034-01-14","Revolution and Youth Day - January 14","TN",2034 +"2034-02-28","Arafat Day* (*estimated)","TN",2034 +"2034-03-01","Eid al-Adha* (*estimated)","TN",2034 +"2034-03-02","Eid al-Adha Holiday* (*estimated)","TN",2034 +"2034-03-03","Eid al-Adha Holiday* (*estimated)","TN",2034 +"2034-03-20","Independence Day","TN",2034 +"2034-03-21","Islamic New Year* (*estimated)","TN",2034 +"2034-04-09","Martyrs' Day","TN",2034 +"2034-05-01","Labour Day","TN",2034 +"2034-05-30","Prophet Muhammad's Birthday* (*estimated)","TN",2034 +"2034-07-25","Republic Day","TN",2034 +"2034-08-13","Women's Day","TN",2034 +"2034-10-15","Evacuation Day","TN",2034 +"2034-12-12","Eid al-Fitr* (*estimated)","TN",2034 +"2034-12-13","Eid al-Fitr Holiday* (*estimated)","TN",2034 +"2034-12-14","Eid al-Fitr Holiday* (*estimated)","TN",2034 +"2035-01-01","New Year's Day","TN",2035 +"2035-01-14","Revolution and Youth Day - January 14","TN",2035 +"2035-02-17","Arafat Day* (*estimated)","TN",2035 +"2035-02-18","Eid al-Adha* (*estimated)","TN",2035 +"2035-02-19","Eid al-Adha Holiday* (*estimated)","TN",2035 +"2035-02-20","Eid al-Adha Holiday* (*estimated)","TN",2035 +"2035-03-11","Islamic New Year* (*estimated)","TN",2035 +"2035-03-20","Independence Day","TN",2035 +"2035-04-09","Martyrs' Day","TN",2035 +"2035-05-01","Labour Day","TN",2035 +"2035-05-20","Prophet Muhammad's Birthday* (*estimated)","TN",2035 +"2035-07-25","Republic Day","TN",2035 +"2035-08-13","Women's Day","TN",2035 +"2035-10-15","Evacuation Day","TN",2035 +"2035-12-01","Eid al-Fitr* (*estimated)","TN",2035 +"2035-12-02","Eid al-Fitr Holiday* (*estimated)","TN",2035 +"2035-12-03","Eid al-Fitr Holiday* (*estimated)","TN",2035 +"2036-01-01","New Year's Day","TN",2036 +"2036-01-14","Revolution and Youth Day - January 14","TN",2036 +"2036-02-06","Arafat Day* (*estimated)","TN",2036 +"2036-02-07","Eid al-Adha* (*estimated)","TN",2036 +"2036-02-08","Eid al-Adha Holiday* (*estimated)","TN",2036 +"2036-02-09","Eid al-Adha Holiday* (*estimated)","TN",2036 +"2036-02-28","Islamic New Year* (*estimated)","TN",2036 +"2036-03-20","Independence Day","TN",2036 +"2036-04-09","Martyrs' Day","TN",2036 +"2036-05-01","Labour Day","TN",2036 +"2036-05-08","Prophet Muhammad's Birthday* (*estimated)","TN",2036 +"2036-07-25","Republic Day","TN",2036 +"2036-08-13","Women's Day","TN",2036 +"2036-10-15","Evacuation Day","TN",2036 +"2036-11-19","Eid al-Fitr* (*estimated)","TN",2036 +"2036-11-20","Eid al-Fitr Holiday* (*estimated)","TN",2036 +"2036-11-21","Eid al-Fitr Holiday* (*estimated)","TN",2036 +"2037-01-01","New Year's Day","TN",2037 +"2037-01-14","Revolution and Youth Day - January 14","TN",2037 +"2037-01-25","Arafat Day* (*estimated)","TN",2037 +"2037-01-26","Eid al-Adha* (*estimated)","TN",2037 +"2037-01-27","Eid al-Adha Holiday* (*estimated)","TN",2037 +"2037-01-28","Eid al-Adha Holiday* (*estimated)","TN",2037 +"2037-02-16","Islamic New Year* (*estimated)","TN",2037 +"2037-03-20","Independence Day","TN",2037 +"2037-04-09","Martyrs' Day","TN",2037 +"2037-04-28","Prophet Muhammad's Birthday* (*estimated)","TN",2037 +"2037-05-01","Labour Day","TN",2037 +"2037-07-25","Republic Day","TN",2037 +"2037-08-13","Women's Day","TN",2037 +"2037-10-15","Evacuation Day","TN",2037 +"2037-11-08","Eid al-Fitr* (*estimated)","TN",2037 +"2037-11-09","Eid al-Fitr Holiday* (*estimated)","TN",2037 +"2037-11-10","Eid al-Fitr Holiday* (*estimated)","TN",2037 +"2038-01-01","New Year's Day","TN",2038 +"2038-01-14","Revolution and Youth Day - January 14","TN",2038 +"2038-01-15","Arafat Day* (*estimated)","TN",2038 +"2038-01-16","Eid al-Adha* (*estimated)","TN",2038 +"2038-01-17","Eid al-Adha Holiday* (*estimated)","TN",2038 +"2038-01-18","Eid al-Adha Holiday* (*estimated)","TN",2038 +"2038-02-05","Islamic New Year* (*estimated)","TN",2038 +"2038-03-20","Independence Day","TN",2038 +"2038-04-09","Martyrs' Day","TN",2038 +"2038-04-17","Prophet Muhammad's Birthday* (*estimated)","TN",2038 +"2038-05-01","Labour Day","TN",2038 +"2038-07-25","Republic Day","TN",2038 +"2038-08-13","Women's Day","TN",2038 +"2038-10-15","Evacuation Day","TN",2038 +"2038-10-29","Eid al-Fitr* (*estimated)","TN",2038 +"2038-10-30","Eid al-Fitr Holiday* (*estimated)","TN",2038 +"2038-10-31","Eid al-Fitr Holiday* (*estimated)","TN",2038 +"2039-01-01","New Year's Day","TN",2039 +"2039-01-04","Arafat Day* (*estimated)","TN",2039 +"2039-01-05","Eid al-Adha* (*estimated)","TN",2039 +"2039-01-06","Eid al-Adha Holiday* (*estimated)","TN",2039 +"2039-01-07","Eid al-Adha Holiday* (*estimated)","TN",2039 +"2039-01-14","Revolution and Youth Day - January 14","TN",2039 +"2039-01-26","Islamic New Year* (*estimated)","TN",2039 +"2039-03-20","Independence Day","TN",2039 +"2039-04-06","Prophet Muhammad's Birthday* (*estimated)","TN",2039 +"2039-04-09","Martyrs' Day","TN",2039 +"2039-05-01","Labour Day","TN",2039 +"2039-07-25","Republic Day","TN",2039 +"2039-08-13","Women's Day","TN",2039 +"2039-10-15","Evacuation Day","TN",2039 +"2039-10-19","Eid al-Fitr* (*estimated)","TN",2039 +"2039-10-20","Eid al-Fitr Holiday* (*estimated)","TN",2039 +"2039-10-21","Eid al-Fitr Holiday* (*estimated)","TN",2039 +"2039-12-25","Arafat Day* (*estimated)","TN",2039 +"2039-12-26","Eid al-Adha* (*estimated)","TN",2039 +"2039-12-27","Eid al-Adha Holiday* (*estimated)","TN",2039 +"2039-12-28","Eid al-Adha Holiday* (*estimated)","TN",2039 +"2040-01-01","New Year's Day","TN",2040 +"2040-01-14","Revolution and Youth Day - January 14","TN",2040 +"2040-01-15","Islamic New Year* (*estimated)","TN",2040 +"2040-03-20","Independence Day","TN",2040 +"2040-03-25","Prophet Muhammad's Birthday* (*estimated)","TN",2040 +"2040-04-09","Martyrs' Day","TN",2040 +"2040-05-01","Labour Day","TN",2040 +"2040-07-25","Republic Day","TN",2040 +"2040-08-13","Women's Day","TN",2040 +"2040-10-07","Eid al-Fitr* (*estimated)","TN",2040 +"2040-10-08","Eid al-Fitr Holiday* (*estimated)","TN",2040 +"2040-10-09","Eid al-Fitr Holiday* (*estimated)","TN",2040 +"2040-10-15","Evacuation Day","TN",2040 +"2040-12-13","Arafat Day* (*estimated)","TN",2040 +"2040-12-14","Eid al-Adha* (*estimated)","TN",2040 +"2040-12-15","Eid al-Adha Holiday* (*estimated)","TN",2040 +"2040-12-16","Eid al-Adha Holiday* (*estimated)","TN",2040 +"2041-01-01","New Year's Day","TN",2041 +"2041-01-04","Islamic New Year* (*estimated)","TN",2041 +"2041-01-14","Revolution and Youth Day - January 14","TN",2041 +"2041-03-15","Prophet Muhammad's Birthday* (*estimated)","TN",2041 +"2041-03-20","Independence Day","TN",2041 +"2041-04-09","Martyrs' Day","TN",2041 +"2041-05-01","Labour Day","TN",2041 +"2041-07-25","Republic Day","TN",2041 +"2041-08-13","Women's Day","TN",2041 +"2041-09-26","Eid al-Fitr* (*estimated)","TN",2041 +"2041-09-27","Eid al-Fitr Holiday* (*estimated)","TN",2041 +"2041-09-28","Eid al-Fitr Holiday* (*estimated)","TN",2041 +"2041-10-15","Evacuation Day","TN",2041 +"2041-12-03","Arafat Day* (*estimated)","TN",2041 +"2041-12-04","Eid al-Adha* (*estimated)","TN",2041 +"2041-12-05","Eid al-Adha Holiday* (*estimated)","TN",2041 +"2041-12-06","Eid al-Adha Holiday* (*estimated)","TN",2041 +"2041-12-24","Islamic New Year* (*estimated)","TN",2041 +"2042-01-01","New Year's Day","TN",2042 +"2042-01-14","Revolution and Youth Day - January 14","TN",2042 +"2042-03-04","Prophet Muhammad's Birthday* (*estimated)","TN",2042 +"2042-03-20","Independence Day","TN",2042 +"2042-04-09","Martyrs' Day","TN",2042 +"2042-05-01","Labour Day","TN",2042 +"2042-07-25","Republic Day","TN",2042 +"2042-08-13","Women's Day","TN",2042 +"2042-09-15","Eid al-Fitr* (*estimated)","TN",2042 +"2042-09-16","Eid al-Fitr Holiday* (*estimated)","TN",2042 +"2042-09-17","Eid al-Fitr Holiday* (*estimated)","TN",2042 +"2042-10-15","Evacuation Day","TN",2042 +"2042-11-22","Arafat Day* (*estimated)","TN",2042 +"2042-11-23","Eid al-Adha* (*estimated)","TN",2042 +"2042-11-24","Eid al-Adha Holiday* (*estimated)","TN",2042 +"2042-11-25","Eid al-Adha Holiday* (*estimated)","TN",2042 +"2042-12-14","Islamic New Year* (*estimated)","TN",2042 +"2043-01-01","New Year's Day","TN",2043 +"2043-01-14","Revolution and Youth Day - January 14","TN",2043 +"2043-02-22","Prophet Muhammad's Birthday* (*estimated)","TN",2043 +"2043-03-20","Independence Day","TN",2043 +"2043-04-09","Martyrs' Day","TN",2043 +"2043-05-01","Labour Day","TN",2043 +"2043-07-25","Republic Day","TN",2043 +"2043-08-13","Women's Day","TN",2043 +"2043-09-04","Eid al-Fitr* (*estimated)","TN",2043 +"2043-09-05","Eid al-Fitr Holiday* (*estimated)","TN",2043 +"2043-09-06","Eid al-Fitr Holiday* (*estimated)","TN",2043 +"2043-10-15","Evacuation Day","TN",2043 +"2043-11-11","Arafat Day* (*estimated)","TN",2043 +"2043-11-12","Eid al-Adha* (*estimated)","TN",2043 +"2043-11-13","Eid al-Adha Holiday* (*estimated)","TN",2043 +"2043-11-14","Eid al-Adha Holiday* (*estimated)","TN",2043 +"2043-12-03","Islamic New Year* (*estimated)","TN",2043 +"2044-01-01","New Year's Day","TN",2044 +"2044-01-14","Revolution and Youth Day - January 14","TN",2044 +"2044-02-11","Prophet Muhammad's Birthday* (*estimated)","TN",2044 +"2044-03-20","Independence Day","TN",2044 +"2044-04-09","Martyrs' Day","TN",2044 +"2044-05-01","Labour Day","TN",2044 +"2044-07-25","Republic Day","TN",2044 +"2044-08-13","Women's Day","TN",2044 +"2044-08-24","Eid al-Fitr* (*estimated)","TN",2044 +"2044-08-25","Eid al-Fitr Holiday* (*estimated)","TN",2044 +"2044-08-26","Eid al-Fitr Holiday* (*estimated)","TN",2044 +"2044-10-15","Evacuation Day","TN",2044 +"2044-10-30","Arafat Day* (*estimated)","TN",2044 +"2044-10-31","Eid al-Adha* (*estimated)","TN",2044 +"2044-11-01","Eid al-Adha Holiday* (*estimated)","TN",2044 +"2044-11-02","Eid al-Adha Holiday* (*estimated)","TN",2044 +"2044-11-21","Islamic New Year* (*estimated)","TN",2044 +"1995-01-01","New Year's Day","TR",1995 +"1995-03-02","Ramadan Feast* (*estimated)","TR",1995 +"1995-03-03","Ramadan Feast Holiday* (*estimated)","TR",1995 +"1995-03-04","Ramadan Feast Holiday* (*estimated)","TR",1995 +"1995-04-23","National Sovereignty and Children's Day","TR",1995 +"1995-05-01","Labour Day","TR",1995 +"1995-05-09","Sacrifice Feast* (*estimated)","TR",1995 +"1995-05-10","Sacrifice Feast Holiday* (*estimated)","TR",1995 +"1995-05-11","Sacrifice Feast Holiday* (*estimated)","TR",1995 +"1995-05-12","Sacrifice Feast Holiday* (*estimated)","TR",1995 +"1995-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",1995 +"1995-08-30","Victory Day","TR",1995 +"1995-10-29","Republic Day","TR",1995 +"1996-01-01","New Year's Day","TR",1996 +"1996-02-19","Ramadan Feast* (*estimated)","TR",1996 +"1996-02-20","Ramadan Feast Holiday* (*estimated)","TR",1996 +"1996-02-21","Ramadan Feast Holiday* (*estimated)","TR",1996 +"1996-04-23","National Sovereignty and Children's Day","TR",1996 +"1996-04-27","Sacrifice Feast* (*estimated)","TR",1996 +"1996-04-28","Sacrifice Feast Holiday* (*estimated)","TR",1996 +"1996-04-29","Sacrifice Feast Holiday* (*estimated)","TR",1996 +"1996-04-30","Sacrifice Feast Holiday* (*estimated)","TR",1996 +"1996-05-01","Labour Day","TR",1996 +"1996-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",1996 +"1996-08-30","Victory Day","TR",1996 +"1996-10-29","Republic Day","TR",1996 +"1997-01-01","New Year's Day","TR",1997 +"1997-02-08","Ramadan Feast* (*estimated)","TR",1997 +"1997-02-09","Ramadan Feast Holiday* (*estimated)","TR",1997 +"1997-02-10","Ramadan Feast Holiday* (*estimated)","TR",1997 +"1997-04-17","Sacrifice Feast* (*estimated)","TR",1997 +"1997-04-18","Sacrifice Feast Holiday* (*estimated)","TR",1997 +"1997-04-19","Sacrifice Feast Holiday* (*estimated)","TR",1997 +"1997-04-20","Sacrifice Feast Holiday* (*estimated)","TR",1997 +"1997-04-23","National Sovereignty and Children's Day","TR",1997 +"1997-05-01","Labour Day","TR",1997 +"1997-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",1997 +"1997-08-30","Victory Day","TR",1997 +"1997-10-29","Republic Day","TR",1997 +"1998-01-01","New Year's Day","TR",1998 +"1998-01-29","Ramadan Feast* (*estimated)","TR",1998 +"1998-01-30","Ramadan Feast Holiday* (*estimated)","TR",1998 +"1998-01-31","Ramadan Feast Holiday* (*estimated)","TR",1998 +"1998-04-07","Sacrifice Feast* (*estimated)","TR",1998 +"1998-04-08","Sacrifice Feast Holiday* (*estimated)","TR",1998 +"1998-04-09","Sacrifice Feast Holiday* (*estimated)","TR",1998 +"1998-04-10","Sacrifice Feast Holiday* (*estimated)","TR",1998 +"1998-04-23","National Sovereignty and Children's Day","TR",1998 +"1998-05-01","Labour Day","TR",1998 +"1998-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",1998 +"1998-08-30","Victory Day","TR",1998 +"1998-10-29","Republic Day","TR",1998 +"1999-01-01","New Year's Day","TR",1999 +"1999-01-18","Ramadan Feast* (*estimated)","TR",1999 +"1999-01-19","Ramadan Feast Holiday* (*estimated)","TR",1999 +"1999-01-20","Ramadan Feast Holiday* (*estimated)","TR",1999 +"1999-03-27","Sacrifice Feast* (*estimated)","TR",1999 +"1999-03-28","Sacrifice Feast Holiday* (*estimated)","TR",1999 +"1999-03-29","Sacrifice Feast Holiday* (*estimated)","TR",1999 +"1999-03-30","Sacrifice Feast Holiday* (*estimated)","TR",1999 +"1999-04-23","National Sovereignty and Children's Day","TR",1999 +"1999-05-01","Labour Day","TR",1999 +"1999-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",1999 +"1999-08-30","Victory Day","TR",1999 +"1999-10-29","Republic Day","TR",1999 +"2000-01-01","New Year's Day","TR",2000 +"2000-01-08","Ramadan Feast* (*estimated)","TR",2000 +"2000-01-09","Ramadan Feast Holiday* (*estimated)","TR",2000 +"2000-01-10","Ramadan Feast Holiday* (*estimated)","TR",2000 +"2000-03-16","Sacrifice Feast* (*estimated)","TR",2000 +"2000-03-17","Sacrifice Feast Holiday* (*estimated)","TR",2000 +"2000-03-18","Sacrifice Feast Holiday* (*estimated)","TR",2000 +"2000-03-19","Sacrifice Feast Holiday* (*estimated)","TR",2000 +"2000-04-23","National Sovereignty and Children's Day","TR",2000 +"2000-05-01","Labour Day","TR",2000 +"2000-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2000 +"2000-08-30","Victory Day","TR",2000 +"2000-10-29","Republic Day","TR",2000 +"2000-12-27","Ramadan Feast* (*estimated)","TR",2000 +"2000-12-28","Ramadan Feast Holiday* (*estimated)","TR",2000 +"2000-12-29","Ramadan Feast Holiday* (*estimated)","TR",2000 +"2001-01-01","New Year's Day","TR",2001 +"2001-03-05","Sacrifice Feast* (*estimated)","TR",2001 +"2001-03-06","Sacrifice Feast Holiday* (*estimated)","TR",2001 +"2001-03-07","Sacrifice Feast Holiday* (*estimated)","TR",2001 +"2001-03-08","Sacrifice Feast Holiday* (*estimated)","TR",2001 +"2001-04-23","National Sovereignty and Children's Day","TR",2001 +"2001-05-01","Labour Day","TR",2001 +"2001-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2001 +"2001-08-30","Victory Day","TR",2001 +"2001-10-29","Republic Day","TR",2001 +"2001-12-16","Ramadan Feast* (*estimated)","TR",2001 +"2001-12-17","Ramadan Feast Holiday* (*estimated)","TR",2001 +"2001-12-18","Ramadan Feast Holiday* (*estimated)","TR",2001 +"2002-01-01","New Year's Day","TR",2002 +"2002-02-22","Sacrifice Feast* (*estimated)","TR",2002 +"2002-02-23","Sacrifice Feast Holiday* (*estimated)","TR",2002 +"2002-02-24","Sacrifice Feast Holiday* (*estimated)","TR",2002 +"2002-02-25","Sacrifice Feast Holiday* (*estimated)","TR",2002 +"2002-04-23","National Sovereignty and Children's Day","TR",2002 +"2002-05-01","Labour Day","TR",2002 +"2002-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2002 +"2002-08-30","Victory Day","TR",2002 +"2002-10-29","Republic Day","TR",2002 +"2002-12-05","Ramadan Feast* (*estimated)","TR",2002 +"2002-12-06","Ramadan Feast Holiday* (*estimated)","TR",2002 +"2002-12-07","Ramadan Feast Holiday* (*estimated)","TR",2002 +"2003-01-01","New Year's Day","TR",2003 +"2003-02-11","Sacrifice Feast* (*estimated)","TR",2003 +"2003-02-12","Sacrifice Feast Holiday* (*estimated)","TR",2003 +"2003-02-13","Sacrifice Feast Holiday* (*estimated)","TR",2003 +"2003-02-14","Sacrifice Feast Holiday* (*estimated)","TR",2003 +"2003-04-23","National Sovereignty and Children's Day","TR",2003 +"2003-05-01","Labour Day","TR",2003 +"2003-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2003 +"2003-08-30","Victory Day","TR",2003 +"2003-10-29","Republic Day","TR",2003 +"2003-11-25","Ramadan Feast* (*estimated)","TR",2003 +"2003-11-26","Ramadan Feast Holiday* (*estimated)","TR",2003 +"2003-11-27","Ramadan Feast Holiday* (*estimated)","TR",2003 +"2004-01-01","New Year's Day","TR",2004 +"2004-02-01","Sacrifice Feast* (*estimated)","TR",2004 +"2004-02-02","Sacrifice Feast Holiday* (*estimated)","TR",2004 +"2004-02-03","Sacrifice Feast Holiday* (*estimated)","TR",2004 +"2004-02-04","Sacrifice Feast Holiday* (*estimated)","TR",2004 +"2004-04-23","National Sovereignty and Children's Day","TR",2004 +"2004-05-01","Labour Day","TR",2004 +"2004-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2004 +"2004-08-30","Victory Day","TR",2004 +"2004-10-29","Republic Day","TR",2004 +"2004-11-14","Ramadan Feast* (*estimated)","TR",2004 +"2004-11-15","Ramadan Feast Holiday* (*estimated)","TR",2004 +"2004-11-16","Ramadan Feast Holiday* (*estimated)","TR",2004 +"2005-01-01","New Year's Day","TR",2005 +"2005-01-21","Sacrifice Feast* (*estimated)","TR",2005 +"2005-01-22","Sacrifice Feast Holiday* (*estimated)","TR",2005 +"2005-01-23","Sacrifice Feast Holiday* (*estimated)","TR",2005 +"2005-01-24","Sacrifice Feast Holiday* (*estimated)","TR",2005 +"2005-04-23","National Sovereignty and Children's Day","TR",2005 +"2005-05-01","Labour Day","TR",2005 +"2005-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2005 +"2005-08-30","Victory Day","TR",2005 +"2005-10-29","Republic Day","TR",2005 +"2005-11-03","Ramadan Feast* (*estimated)","TR",2005 +"2005-11-04","Ramadan Feast Holiday* (*estimated)","TR",2005 +"2005-11-05","Ramadan Feast Holiday* (*estimated)","TR",2005 +"2006-01-01","New Year's Day","TR",2006 +"2006-01-10","Sacrifice Feast* (*estimated)","TR",2006 +"2006-01-11","Sacrifice Feast Holiday* (*estimated)","TR",2006 +"2006-01-12","Sacrifice Feast Holiday* (*estimated)","TR",2006 +"2006-01-13","Sacrifice Feast Holiday* (*estimated)","TR",2006 +"2006-04-23","National Sovereignty and Children's Day","TR",2006 +"2006-05-01","Labour Day","TR",2006 +"2006-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2006 +"2006-08-30","Victory Day","TR",2006 +"2006-10-23","Ramadan Feast* (*estimated)","TR",2006 +"2006-10-24","Ramadan Feast Holiday* (*estimated)","TR",2006 +"2006-10-25","Ramadan Feast Holiday* (*estimated)","TR",2006 +"2006-10-29","Republic Day","TR",2006 +"2006-12-31","Sacrifice Feast* (*estimated)","TR",2006 +"2007-01-01","New Year's Day","TR",2007 +"2007-01-01","Sacrifice Feast Holiday* (*estimated)","TR",2007 +"2007-01-02","Sacrifice Feast Holiday* (*estimated)","TR",2007 +"2007-01-03","Sacrifice Feast Holiday* (*estimated)","TR",2007 +"2007-04-23","National Sovereignty and Children's Day","TR",2007 +"2007-05-01","Labour Day","TR",2007 +"2007-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2007 +"2007-08-30","Victory Day","TR",2007 +"2007-10-13","Ramadan Feast* (*estimated)","TR",2007 +"2007-10-14","Ramadan Feast Holiday* (*estimated)","TR",2007 +"2007-10-15","Ramadan Feast Holiday* (*estimated)","TR",2007 +"2007-10-29","Republic Day","TR",2007 +"2007-12-20","Sacrifice Feast* (*estimated)","TR",2007 +"2007-12-21","Sacrifice Feast Holiday* (*estimated)","TR",2007 +"2007-12-22","Sacrifice Feast Holiday* (*estimated)","TR",2007 +"2007-12-23","Sacrifice Feast Holiday* (*estimated)","TR",2007 +"2008-01-01","New Year's Day","TR",2008 +"2008-04-23","National Sovereignty and Children's Day","TR",2008 +"2008-05-01","Labour Day","TR",2008 +"2008-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2008 +"2008-08-30","Victory Day","TR",2008 +"2008-10-01","Ramadan Feast* (*estimated)","TR",2008 +"2008-10-02","Ramadan Feast Holiday* (*estimated)","TR",2008 +"2008-10-03","Ramadan Feast Holiday* (*estimated)","TR",2008 +"2008-10-29","Republic Day","TR",2008 +"2008-12-08","Sacrifice Feast* (*estimated)","TR",2008 +"2008-12-09","Sacrifice Feast Holiday* (*estimated)","TR",2008 +"2008-12-10","Sacrifice Feast Holiday* (*estimated)","TR",2008 +"2008-12-11","Sacrifice Feast Holiday* (*estimated)","TR",2008 +"2009-01-01","New Year's Day","TR",2009 +"2009-04-23","National Sovereignty and Children's Day","TR",2009 +"2009-05-01","Labour Day","TR",2009 +"2009-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2009 +"2009-08-30","Victory Day","TR",2009 +"2009-09-20","Ramadan Feast* (*estimated)","TR",2009 +"2009-09-21","Ramadan Feast Holiday* (*estimated)","TR",2009 +"2009-09-22","Ramadan Feast Holiday* (*estimated)","TR",2009 +"2009-10-29","Republic Day","TR",2009 +"2009-11-27","Sacrifice Feast* (*estimated)","TR",2009 +"2009-11-28","Sacrifice Feast Holiday* (*estimated)","TR",2009 +"2009-11-29","Sacrifice Feast Holiday* (*estimated)","TR",2009 +"2009-11-30","Sacrifice Feast Holiday* (*estimated)","TR",2009 +"2010-01-01","New Year's Day","TR",2010 +"2010-04-23","National Sovereignty and Children's Day","TR",2010 +"2010-05-01","Labour Day","TR",2010 +"2010-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2010 +"2010-08-30","Victory Day","TR",2010 +"2010-09-10","Ramadan Feast* (*estimated)","TR",2010 +"2010-09-11","Ramadan Feast Holiday* (*estimated)","TR",2010 +"2010-09-12","Ramadan Feast Holiday* (*estimated)","TR",2010 +"2010-10-29","Republic Day","TR",2010 +"2010-11-16","Sacrifice Feast* (*estimated)","TR",2010 +"2010-11-17","Sacrifice Feast Holiday* (*estimated)","TR",2010 +"2010-11-18","Sacrifice Feast Holiday* (*estimated)","TR",2010 +"2010-11-19","Sacrifice Feast Holiday* (*estimated)","TR",2010 +"2011-01-01","New Year's Day","TR",2011 +"2011-04-23","National Sovereignty and Children's Day","TR",2011 +"2011-05-01","Labour Day","TR",2011 +"2011-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2011 +"2011-08-30","Ramadan Feast* (*estimated)","TR",2011 +"2011-08-30","Victory Day","TR",2011 +"2011-08-31","Ramadan Feast Holiday* (*estimated)","TR",2011 +"2011-09-01","Ramadan Feast Holiday* (*estimated)","TR",2011 +"2011-10-29","Republic Day","TR",2011 +"2011-11-06","Sacrifice Feast* (*estimated)","TR",2011 +"2011-11-07","Sacrifice Feast Holiday* (*estimated)","TR",2011 +"2011-11-08","Sacrifice Feast Holiday* (*estimated)","TR",2011 +"2011-11-09","Sacrifice Feast Holiday* (*estimated)","TR",2011 +"2012-01-01","New Year's Day","TR",2012 +"2012-04-23","National Sovereignty and Children's Day","TR",2012 +"2012-05-01","Labour Day","TR",2012 +"2012-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2012 +"2012-08-19","Ramadan Feast* (*estimated)","TR",2012 +"2012-08-20","Ramadan Feast Holiday* (*estimated)","TR",2012 +"2012-08-21","Ramadan Feast Holiday* (*estimated)","TR",2012 +"2012-08-30","Victory Day","TR",2012 +"2012-10-26","Sacrifice Feast* (*estimated)","TR",2012 +"2012-10-27","Sacrifice Feast Holiday* (*estimated)","TR",2012 +"2012-10-28","Sacrifice Feast Holiday* (*estimated)","TR",2012 +"2012-10-29","Republic Day","TR",2012 +"2012-10-29","Sacrifice Feast Holiday* (*estimated)","TR",2012 +"2013-01-01","New Year's Day","TR",2013 +"2013-04-23","National Sovereignty and Children's Day","TR",2013 +"2013-05-01","Labour Day","TR",2013 +"2013-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2013 +"2013-08-08","Ramadan Feast* (*estimated)","TR",2013 +"2013-08-09","Ramadan Feast Holiday* (*estimated)","TR",2013 +"2013-08-10","Ramadan Feast Holiday* (*estimated)","TR",2013 +"2013-08-30","Victory Day","TR",2013 +"2013-10-15","Sacrifice Feast* (*estimated)","TR",2013 +"2013-10-16","Sacrifice Feast Holiday* (*estimated)","TR",2013 +"2013-10-17","Sacrifice Feast Holiday* (*estimated)","TR",2013 +"2013-10-18","Sacrifice Feast Holiday* (*estimated)","TR",2013 +"2013-10-29","Republic Day","TR",2013 +"2014-01-01","New Year's Day","TR",2014 +"2014-04-23","National Sovereignty and Children's Day","TR",2014 +"2014-05-01","Labour Day","TR",2014 +"2014-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2014 +"2014-07-28","Ramadan Feast* (*estimated)","TR",2014 +"2014-07-29","Ramadan Feast Holiday* (*estimated)","TR",2014 +"2014-07-30","Ramadan Feast Holiday* (*estimated)","TR",2014 +"2014-08-30","Victory Day","TR",2014 +"2014-10-04","Sacrifice Feast* (*estimated)","TR",2014 +"2014-10-05","Sacrifice Feast Holiday* (*estimated)","TR",2014 +"2014-10-06","Sacrifice Feast Holiday* (*estimated)","TR",2014 +"2014-10-07","Sacrifice Feast Holiday* (*estimated)","TR",2014 +"2014-10-29","Republic Day","TR",2014 +"2015-01-01","New Year's Day","TR",2015 +"2015-04-23","National Sovereignty and Children's Day","TR",2015 +"2015-05-01","Labour Day","TR",2015 +"2015-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2015 +"2015-07-17","Ramadan Feast* (*estimated)","TR",2015 +"2015-07-18","Ramadan Feast Holiday* (*estimated)","TR",2015 +"2015-07-19","Ramadan Feast Holiday* (*estimated)","TR",2015 +"2015-08-30","Victory Day","TR",2015 +"2015-09-23","Sacrifice Feast* (*estimated)","TR",2015 +"2015-09-24","Sacrifice Feast Holiday* (*estimated)","TR",2015 +"2015-09-25","Sacrifice Feast Holiday* (*estimated)","TR",2015 +"2015-09-26","Sacrifice Feast Holiday* (*estimated)","TR",2015 +"2015-10-29","Republic Day","TR",2015 +"2016-01-01","New Year's Day","TR",2016 +"2016-04-23","National Sovereignty and Children's Day","TR",2016 +"2016-05-01","Labour Day","TR",2016 +"2016-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2016 +"2016-07-06","Ramadan Feast* (*estimated)","TR",2016 +"2016-07-07","Ramadan Feast Holiday* (*estimated)","TR",2016 +"2016-07-08","Ramadan Feast Holiday* (*estimated)","TR",2016 +"2016-08-30","Victory Day","TR",2016 +"2016-09-11","Sacrifice Feast* (*estimated)","TR",2016 +"2016-09-12","Sacrifice Feast Holiday* (*estimated)","TR",2016 +"2016-09-13","Sacrifice Feast Holiday* (*estimated)","TR",2016 +"2016-09-14","Sacrifice Feast Holiday* (*estimated)","TR",2016 +"2016-10-29","Republic Day","TR",2016 +"2017-01-01","New Year's Day","TR",2017 +"2017-04-23","National Sovereignty and Children's Day","TR",2017 +"2017-05-01","Labour Day","TR",2017 +"2017-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2017 +"2017-06-25","Ramadan Feast* (*estimated)","TR",2017 +"2017-06-26","Ramadan Feast Holiday* (*estimated)","TR",2017 +"2017-06-27","Ramadan Feast Holiday* (*estimated)","TR",2017 +"2017-07-15","Democracy and National Unity Day","TR",2017 +"2017-08-30","Victory Day","TR",2017 +"2017-09-01","Sacrifice Feast* (*estimated)","TR",2017 +"2017-09-02","Sacrifice Feast Holiday* (*estimated)","TR",2017 +"2017-09-03","Sacrifice Feast Holiday* (*estimated)","TR",2017 +"2017-09-04","Sacrifice Feast Holiday* (*estimated)","TR",2017 +"2017-10-29","Republic Day","TR",2017 +"2018-01-01","New Year's Day","TR",2018 +"2018-04-23","National Sovereignty and Children's Day","TR",2018 +"2018-05-01","Labour Day","TR",2018 +"2018-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2018 +"2018-06-15","Ramadan Feast* (*estimated)","TR",2018 +"2018-06-16","Ramadan Feast Holiday* (*estimated)","TR",2018 +"2018-06-17","Ramadan Feast Holiday* (*estimated)","TR",2018 +"2018-07-15","Democracy and National Unity Day","TR",2018 +"2018-08-21","Sacrifice Feast* (*estimated)","TR",2018 +"2018-08-22","Sacrifice Feast Holiday* (*estimated)","TR",2018 +"2018-08-23","Sacrifice Feast Holiday* (*estimated)","TR",2018 +"2018-08-24","Sacrifice Feast Holiday* (*estimated)","TR",2018 +"2018-08-30","Victory Day","TR",2018 +"2018-10-29","Republic Day","TR",2018 +"2019-01-01","New Year's Day","TR",2019 +"2019-04-23","National Sovereignty and Children's Day","TR",2019 +"2019-05-01","Labour Day","TR",2019 +"2019-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2019 +"2019-06-04","Ramadan Feast* (*estimated)","TR",2019 +"2019-06-05","Ramadan Feast Holiday* (*estimated)","TR",2019 +"2019-06-06","Ramadan Feast Holiday* (*estimated)","TR",2019 +"2019-07-15","Democracy and National Unity Day","TR",2019 +"2019-08-11","Sacrifice Feast* (*estimated)","TR",2019 +"2019-08-12","Sacrifice Feast Holiday* (*estimated)","TR",2019 +"2019-08-13","Sacrifice Feast Holiday* (*estimated)","TR",2019 +"2019-08-14","Sacrifice Feast Holiday* (*estimated)","TR",2019 +"2019-08-30","Victory Day","TR",2019 +"2019-10-29","Republic Day","TR",2019 +"2020-01-01","New Year's Day","TR",2020 +"2020-04-23","National Sovereignty and Children's Day","TR",2020 +"2020-05-01","Labour Day","TR",2020 +"2020-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2020 +"2020-05-24","Ramadan Feast* (*estimated)","TR",2020 +"2020-05-25","Ramadan Feast Holiday* (*estimated)","TR",2020 +"2020-05-26","Ramadan Feast Holiday* (*estimated)","TR",2020 +"2020-07-15","Democracy and National Unity Day","TR",2020 +"2020-07-31","Sacrifice Feast* (*estimated)","TR",2020 +"2020-08-01","Sacrifice Feast Holiday* (*estimated)","TR",2020 +"2020-08-02","Sacrifice Feast Holiday* (*estimated)","TR",2020 +"2020-08-03","Sacrifice Feast Holiday* (*estimated)","TR",2020 +"2020-08-30","Victory Day","TR",2020 +"2020-10-29","Republic Day","TR",2020 +"2021-01-01","New Year's Day","TR",2021 +"2021-04-23","National Sovereignty and Children's Day","TR",2021 +"2021-05-01","Labour Day","TR",2021 +"2021-05-13","Ramadan Feast* (*estimated)","TR",2021 +"2021-05-14","Ramadan Feast Holiday* (*estimated)","TR",2021 +"2021-05-15","Ramadan Feast Holiday* (*estimated)","TR",2021 +"2021-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2021 +"2021-07-15","Democracy and National Unity Day","TR",2021 +"2021-07-20","Sacrifice Feast* (*estimated)","TR",2021 +"2021-07-21","Sacrifice Feast Holiday* (*estimated)","TR",2021 +"2021-07-22","Sacrifice Feast Holiday* (*estimated)","TR",2021 +"2021-07-23","Sacrifice Feast Holiday* (*estimated)","TR",2021 +"2021-08-30","Victory Day","TR",2021 +"2021-10-29","Republic Day","TR",2021 +"2022-01-01","New Year's Day","TR",2022 +"2022-04-23","National Sovereignty and Children's Day","TR",2022 +"2022-05-01","Labour Day","TR",2022 +"2022-05-02","Ramadan Feast* (*estimated)","TR",2022 +"2022-05-03","Ramadan Feast Holiday* (*estimated)","TR",2022 +"2022-05-04","Ramadan Feast Holiday* (*estimated)","TR",2022 +"2022-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2022 +"2022-07-09","Sacrifice Feast* (*estimated)","TR",2022 +"2022-07-10","Sacrifice Feast Holiday* (*estimated)","TR",2022 +"2022-07-11","Sacrifice Feast Holiday* (*estimated)","TR",2022 +"2022-07-12","Sacrifice Feast Holiday* (*estimated)","TR",2022 +"2022-07-15","Democracy and National Unity Day","TR",2022 +"2022-08-30","Victory Day","TR",2022 +"2022-10-29","Republic Day","TR",2022 +"2023-01-01","New Year's Day","TR",2023 +"2023-04-21","Ramadan Feast* (*estimated)","TR",2023 +"2023-04-22","Ramadan Feast Holiday* (*estimated)","TR",2023 +"2023-04-23","National Sovereignty and Children's Day","TR",2023 +"2023-04-23","Ramadan Feast Holiday* (*estimated)","TR",2023 +"2023-05-01","Labour Day","TR",2023 +"2023-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2023 +"2023-06-28","Sacrifice Feast* (*estimated)","TR",2023 +"2023-06-29","Sacrifice Feast Holiday* (*estimated)","TR",2023 +"2023-06-30","Sacrifice Feast Holiday* (*estimated)","TR",2023 +"2023-07-01","Sacrifice Feast Holiday* (*estimated)","TR",2023 +"2023-07-15","Democracy and National Unity Day","TR",2023 +"2023-08-30","Victory Day","TR",2023 +"2023-10-29","Republic Day","TR",2023 +"2024-01-01","New Year's Day","TR",2024 +"2024-04-10","Ramadan Feast* (*estimated)","TR",2024 +"2024-04-11","Ramadan Feast Holiday* (*estimated)","TR",2024 +"2024-04-12","Ramadan Feast Holiday* (*estimated)","TR",2024 +"2024-04-23","National Sovereignty and Children's Day","TR",2024 +"2024-05-01","Labour Day","TR",2024 +"2024-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2024 +"2024-06-16","Sacrifice Feast* (*estimated)","TR",2024 +"2024-06-17","Sacrifice Feast Holiday* (*estimated)","TR",2024 +"2024-06-18","Sacrifice Feast Holiday* (*estimated)","TR",2024 +"2024-06-19","Sacrifice Feast Holiday* (*estimated)","TR",2024 +"2024-07-15","Democracy and National Unity Day","TR",2024 +"2024-08-30","Victory Day","TR",2024 +"2024-10-29","Republic Day","TR",2024 +"2025-01-01","New Year's Day","TR",2025 +"2025-03-30","Ramadan Feast* (*estimated)","TR",2025 +"2025-03-31","Ramadan Feast Holiday* (*estimated)","TR",2025 +"2025-04-01","Ramadan Feast Holiday* (*estimated)","TR",2025 +"2025-04-23","National Sovereignty and Children's Day","TR",2025 +"2025-05-01","Labour Day","TR",2025 +"2025-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2025 +"2025-06-06","Sacrifice Feast* (*estimated)","TR",2025 +"2025-06-07","Sacrifice Feast Holiday* (*estimated)","TR",2025 +"2025-06-08","Sacrifice Feast Holiday* (*estimated)","TR",2025 +"2025-06-09","Sacrifice Feast Holiday* (*estimated)","TR",2025 +"2025-07-15","Democracy and National Unity Day","TR",2025 +"2025-08-30","Victory Day","TR",2025 +"2025-10-29","Republic Day","TR",2025 +"2026-01-01","New Year's Day","TR",2026 +"2026-03-20","Ramadan Feast* (*estimated)","TR",2026 +"2026-03-21","Ramadan Feast Holiday* (*estimated)","TR",2026 +"2026-03-22","Ramadan Feast Holiday* (*estimated)","TR",2026 +"2026-04-23","National Sovereignty and Children's Day","TR",2026 +"2026-05-01","Labour Day","TR",2026 +"2026-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2026 +"2026-05-27","Sacrifice Feast* (*estimated)","TR",2026 +"2026-05-28","Sacrifice Feast Holiday* (*estimated)","TR",2026 +"2026-05-29","Sacrifice Feast Holiday* (*estimated)","TR",2026 +"2026-05-30","Sacrifice Feast Holiday* (*estimated)","TR",2026 +"2026-07-15","Democracy and National Unity Day","TR",2026 +"2026-08-30","Victory Day","TR",2026 +"2026-10-29","Republic Day","TR",2026 +"2027-01-01","New Year's Day","TR",2027 +"2027-03-09","Ramadan Feast* (*estimated)","TR",2027 +"2027-03-10","Ramadan Feast Holiday* (*estimated)","TR",2027 +"2027-03-11","Ramadan Feast Holiday* (*estimated)","TR",2027 +"2027-04-23","National Sovereignty and Children's Day","TR",2027 +"2027-05-01","Labour Day","TR",2027 +"2027-05-16","Sacrifice Feast* (*estimated)","TR",2027 +"2027-05-17","Sacrifice Feast Holiday* (*estimated)","TR",2027 +"2027-05-18","Sacrifice Feast Holiday* (*estimated)","TR",2027 +"2027-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2027 +"2027-05-19","Sacrifice Feast Holiday* (*estimated)","TR",2027 +"2027-07-15","Democracy and National Unity Day","TR",2027 +"2027-08-30","Victory Day","TR",2027 +"2027-10-29","Republic Day","TR",2027 +"2028-01-01","New Year's Day","TR",2028 +"2028-02-26","Ramadan Feast* (*estimated)","TR",2028 +"2028-02-27","Ramadan Feast Holiday* (*estimated)","TR",2028 +"2028-02-28","Ramadan Feast Holiday* (*estimated)","TR",2028 +"2028-04-23","National Sovereignty and Children's Day","TR",2028 +"2028-05-01","Labour Day","TR",2028 +"2028-05-05","Sacrifice Feast* (*estimated)","TR",2028 +"2028-05-06","Sacrifice Feast Holiday* (*estimated)","TR",2028 +"2028-05-07","Sacrifice Feast Holiday* (*estimated)","TR",2028 +"2028-05-08","Sacrifice Feast Holiday* (*estimated)","TR",2028 +"2028-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2028 +"2028-07-15","Democracy and National Unity Day","TR",2028 +"2028-08-30","Victory Day","TR",2028 +"2028-10-29","Republic Day","TR",2028 +"2029-01-01","New Year's Day","TR",2029 +"2029-02-14","Ramadan Feast* (*estimated)","TR",2029 +"2029-02-15","Ramadan Feast Holiday* (*estimated)","TR",2029 +"2029-02-16","Ramadan Feast Holiday* (*estimated)","TR",2029 +"2029-04-23","National Sovereignty and Children's Day","TR",2029 +"2029-04-24","Sacrifice Feast* (*estimated)","TR",2029 +"2029-04-25","Sacrifice Feast Holiday* (*estimated)","TR",2029 +"2029-04-26","Sacrifice Feast Holiday* (*estimated)","TR",2029 +"2029-04-27","Sacrifice Feast Holiday* (*estimated)","TR",2029 +"2029-05-01","Labour Day","TR",2029 +"2029-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2029 +"2029-07-15","Democracy and National Unity Day","TR",2029 +"2029-08-30","Victory Day","TR",2029 +"2029-10-29","Republic Day","TR",2029 +"2030-01-01","New Year's Day","TR",2030 +"2030-02-04","Ramadan Feast* (*estimated)","TR",2030 +"2030-02-05","Ramadan Feast Holiday* (*estimated)","TR",2030 +"2030-02-06","Ramadan Feast Holiday* (*estimated)","TR",2030 +"2030-04-13","Sacrifice Feast* (*estimated)","TR",2030 +"2030-04-14","Sacrifice Feast Holiday* (*estimated)","TR",2030 +"2030-04-15","Sacrifice Feast Holiday* (*estimated)","TR",2030 +"2030-04-16","Sacrifice Feast Holiday* (*estimated)","TR",2030 +"2030-04-23","National Sovereignty and Children's Day","TR",2030 +"2030-05-01","Labour Day","TR",2030 +"2030-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2030 +"2030-07-15","Democracy and National Unity Day","TR",2030 +"2030-08-30","Victory Day","TR",2030 +"2030-10-29","Republic Day","TR",2030 +"2031-01-01","New Year's Day","TR",2031 +"2031-01-24","Ramadan Feast* (*estimated)","TR",2031 +"2031-01-25","Ramadan Feast Holiday* (*estimated)","TR",2031 +"2031-01-26","Ramadan Feast Holiday* (*estimated)","TR",2031 +"2031-04-02","Sacrifice Feast* (*estimated)","TR",2031 +"2031-04-03","Sacrifice Feast Holiday* (*estimated)","TR",2031 +"2031-04-04","Sacrifice Feast Holiday* (*estimated)","TR",2031 +"2031-04-05","Sacrifice Feast Holiday* (*estimated)","TR",2031 +"2031-04-23","National Sovereignty and Children's Day","TR",2031 +"2031-05-01","Labour Day","TR",2031 +"2031-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2031 +"2031-07-15","Democracy and National Unity Day","TR",2031 +"2031-08-30","Victory Day","TR",2031 +"2031-10-29","Republic Day","TR",2031 +"2032-01-01","New Year's Day","TR",2032 +"2032-01-14","Ramadan Feast* (*estimated)","TR",2032 +"2032-01-15","Ramadan Feast Holiday* (*estimated)","TR",2032 +"2032-01-16","Ramadan Feast Holiday* (*estimated)","TR",2032 +"2032-03-22","Sacrifice Feast* (*estimated)","TR",2032 +"2032-03-23","Sacrifice Feast Holiday* (*estimated)","TR",2032 +"2032-03-24","Sacrifice Feast Holiday* (*estimated)","TR",2032 +"2032-03-25","Sacrifice Feast Holiday* (*estimated)","TR",2032 +"2032-04-23","National Sovereignty and Children's Day","TR",2032 +"2032-05-01","Labour Day","TR",2032 +"2032-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2032 +"2032-07-15","Democracy and National Unity Day","TR",2032 +"2032-08-30","Victory Day","TR",2032 +"2032-10-29","Republic Day","TR",2032 +"2033-01-01","New Year's Day","TR",2033 +"2033-01-02","Ramadan Feast* (*estimated)","TR",2033 +"2033-01-03","Ramadan Feast Holiday* (*estimated)","TR",2033 +"2033-01-04","Ramadan Feast Holiday* (*estimated)","TR",2033 +"2033-03-11","Sacrifice Feast* (*estimated)","TR",2033 +"2033-03-12","Sacrifice Feast Holiday* (*estimated)","TR",2033 +"2033-03-13","Sacrifice Feast Holiday* (*estimated)","TR",2033 +"2033-03-14","Sacrifice Feast Holiday* (*estimated)","TR",2033 +"2033-04-23","National Sovereignty and Children's Day","TR",2033 +"2033-05-01","Labour Day","TR",2033 +"2033-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2033 +"2033-07-15","Democracy and National Unity Day","TR",2033 +"2033-08-30","Victory Day","TR",2033 +"2033-10-29","Republic Day","TR",2033 +"2033-12-23","Ramadan Feast* (*estimated)","TR",2033 +"2033-12-24","Ramadan Feast Holiday* (*estimated)","TR",2033 +"2033-12-25","Ramadan Feast Holiday* (*estimated)","TR",2033 +"2034-01-01","New Year's Day","TR",2034 +"2034-03-01","Sacrifice Feast* (*estimated)","TR",2034 +"2034-03-02","Sacrifice Feast Holiday* (*estimated)","TR",2034 +"2034-03-03","Sacrifice Feast Holiday* (*estimated)","TR",2034 +"2034-03-04","Sacrifice Feast Holiday* (*estimated)","TR",2034 +"2034-04-23","National Sovereignty and Children's Day","TR",2034 +"2034-05-01","Labour Day","TR",2034 +"2034-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2034 +"2034-07-15","Democracy and National Unity Day","TR",2034 +"2034-08-30","Victory Day","TR",2034 +"2034-10-29","Republic Day","TR",2034 +"2034-12-12","Ramadan Feast* (*estimated)","TR",2034 +"2034-12-13","Ramadan Feast Holiday* (*estimated)","TR",2034 +"2034-12-14","Ramadan Feast Holiday* (*estimated)","TR",2034 +"2035-01-01","New Year's Day","TR",2035 +"2035-02-18","Sacrifice Feast* (*estimated)","TR",2035 +"2035-02-19","Sacrifice Feast Holiday* (*estimated)","TR",2035 +"2035-02-20","Sacrifice Feast Holiday* (*estimated)","TR",2035 +"2035-02-21","Sacrifice Feast Holiday* (*estimated)","TR",2035 +"2035-04-23","National Sovereignty and Children's Day","TR",2035 +"2035-05-01","Labour Day","TR",2035 +"2035-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2035 +"2035-07-15","Democracy and National Unity Day","TR",2035 +"2035-08-30","Victory Day","TR",2035 +"2035-10-29","Republic Day","TR",2035 +"2035-12-01","Ramadan Feast* (*estimated)","TR",2035 +"2035-12-02","Ramadan Feast Holiday* (*estimated)","TR",2035 +"2035-12-03","Ramadan Feast Holiday* (*estimated)","TR",2035 +"2036-01-01","New Year's Day","TR",2036 +"2036-02-07","Sacrifice Feast* (*estimated)","TR",2036 +"2036-02-08","Sacrifice Feast Holiday* (*estimated)","TR",2036 +"2036-02-09","Sacrifice Feast Holiday* (*estimated)","TR",2036 +"2036-02-10","Sacrifice Feast Holiday* (*estimated)","TR",2036 +"2036-04-23","National Sovereignty and Children's Day","TR",2036 +"2036-05-01","Labour Day","TR",2036 +"2036-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2036 +"2036-07-15","Democracy and National Unity Day","TR",2036 +"2036-08-30","Victory Day","TR",2036 +"2036-10-29","Republic Day","TR",2036 +"2036-11-19","Ramadan Feast* (*estimated)","TR",2036 +"2036-11-20","Ramadan Feast Holiday* (*estimated)","TR",2036 +"2036-11-21","Ramadan Feast Holiday* (*estimated)","TR",2036 +"2037-01-01","New Year's Day","TR",2037 +"2037-01-26","Sacrifice Feast* (*estimated)","TR",2037 +"2037-01-27","Sacrifice Feast Holiday* (*estimated)","TR",2037 +"2037-01-28","Sacrifice Feast Holiday* (*estimated)","TR",2037 +"2037-01-29","Sacrifice Feast Holiday* (*estimated)","TR",2037 +"2037-04-23","National Sovereignty and Children's Day","TR",2037 +"2037-05-01","Labour Day","TR",2037 +"2037-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2037 +"2037-07-15","Democracy and National Unity Day","TR",2037 +"2037-08-30","Victory Day","TR",2037 +"2037-10-29","Republic Day","TR",2037 +"2037-11-08","Ramadan Feast* (*estimated)","TR",2037 +"2037-11-09","Ramadan Feast Holiday* (*estimated)","TR",2037 +"2037-11-10","Ramadan Feast Holiday* (*estimated)","TR",2037 +"2038-01-01","New Year's Day","TR",2038 +"2038-01-16","Sacrifice Feast* (*estimated)","TR",2038 +"2038-01-17","Sacrifice Feast Holiday* (*estimated)","TR",2038 +"2038-01-18","Sacrifice Feast Holiday* (*estimated)","TR",2038 +"2038-01-19","Sacrifice Feast Holiday* (*estimated)","TR",2038 +"2038-04-23","National Sovereignty and Children's Day","TR",2038 +"2038-05-01","Labour Day","TR",2038 +"2038-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2038 +"2038-07-15","Democracy and National Unity Day","TR",2038 +"2038-08-30","Victory Day","TR",2038 +"2038-10-29","Ramadan Feast* (*estimated)","TR",2038 +"2038-10-29","Republic Day","TR",2038 +"2038-10-30","Ramadan Feast Holiday* (*estimated)","TR",2038 +"2038-10-31","Ramadan Feast Holiday* (*estimated)","TR",2038 +"2039-01-01","New Year's Day","TR",2039 +"2039-01-05","Sacrifice Feast* (*estimated)","TR",2039 +"2039-01-06","Sacrifice Feast Holiday* (*estimated)","TR",2039 +"2039-01-07","Sacrifice Feast Holiday* (*estimated)","TR",2039 +"2039-01-08","Sacrifice Feast Holiday* (*estimated)","TR",2039 +"2039-04-23","National Sovereignty and Children's Day","TR",2039 +"2039-05-01","Labour Day","TR",2039 +"2039-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2039 +"2039-07-15","Democracy and National Unity Day","TR",2039 +"2039-08-30","Victory Day","TR",2039 +"2039-10-19","Ramadan Feast* (*estimated)","TR",2039 +"2039-10-20","Ramadan Feast Holiday* (*estimated)","TR",2039 +"2039-10-21","Ramadan Feast Holiday* (*estimated)","TR",2039 +"2039-10-29","Republic Day","TR",2039 +"2039-12-26","Sacrifice Feast* (*estimated)","TR",2039 +"2039-12-27","Sacrifice Feast Holiday* (*estimated)","TR",2039 +"2039-12-28","Sacrifice Feast Holiday* (*estimated)","TR",2039 +"2039-12-29","Sacrifice Feast Holiday* (*estimated)","TR",2039 +"2040-01-01","New Year's Day","TR",2040 +"2040-04-23","National Sovereignty and Children's Day","TR",2040 +"2040-05-01","Labour Day","TR",2040 +"2040-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2040 +"2040-07-15","Democracy and National Unity Day","TR",2040 +"2040-08-30","Victory Day","TR",2040 +"2040-10-07","Ramadan Feast* (*estimated)","TR",2040 +"2040-10-08","Ramadan Feast Holiday* (*estimated)","TR",2040 +"2040-10-09","Ramadan Feast Holiday* (*estimated)","TR",2040 +"2040-10-29","Republic Day","TR",2040 +"2040-12-14","Sacrifice Feast* (*estimated)","TR",2040 +"2040-12-15","Sacrifice Feast Holiday* (*estimated)","TR",2040 +"2040-12-16","Sacrifice Feast Holiday* (*estimated)","TR",2040 +"2040-12-17","Sacrifice Feast Holiday* (*estimated)","TR",2040 +"2041-01-01","New Year's Day","TR",2041 +"2041-04-23","National Sovereignty and Children's Day","TR",2041 +"2041-05-01","Labour Day","TR",2041 +"2041-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2041 +"2041-07-15","Democracy and National Unity Day","TR",2041 +"2041-08-30","Victory Day","TR",2041 +"2041-09-26","Ramadan Feast* (*estimated)","TR",2041 +"2041-09-27","Ramadan Feast Holiday* (*estimated)","TR",2041 +"2041-09-28","Ramadan Feast Holiday* (*estimated)","TR",2041 +"2041-10-29","Republic Day","TR",2041 +"2041-12-04","Sacrifice Feast* (*estimated)","TR",2041 +"2041-12-05","Sacrifice Feast Holiday* (*estimated)","TR",2041 +"2041-12-06","Sacrifice Feast Holiday* (*estimated)","TR",2041 +"2041-12-07","Sacrifice Feast Holiday* (*estimated)","TR",2041 +"2042-01-01","New Year's Day","TR",2042 +"2042-04-23","National Sovereignty and Children's Day","TR",2042 +"2042-05-01","Labour Day","TR",2042 +"2042-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2042 +"2042-07-15","Democracy and National Unity Day","TR",2042 +"2042-08-30","Victory Day","TR",2042 +"2042-09-15","Ramadan Feast* (*estimated)","TR",2042 +"2042-09-16","Ramadan Feast Holiday* (*estimated)","TR",2042 +"2042-09-17","Ramadan Feast Holiday* (*estimated)","TR",2042 +"2042-10-29","Republic Day","TR",2042 +"2042-11-23","Sacrifice Feast* (*estimated)","TR",2042 +"2042-11-24","Sacrifice Feast Holiday* (*estimated)","TR",2042 +"2042-11-25","Sacrifice Feast Holiday* (*estimated)","TR",2042 +"2042-11-26","Sacrifice Feast Holiday* (*estimated)","TR",2042 +"2043-01-01","New Year's Day","TR",2043 +"2043-04-23","National Sovereignty and Children's Day","TR",2043 +"2043-05-01","Labour Day","TR",2043 +"2043-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2043 +"2043-07-15","Democracy and National Unity Day","TR",2043 +"2043-08-30","Victory Day","TR",2043 +"2043-09-04","Ramadan Feast* (*estimated)","TR",2043 +"2043-09-05","Ramadan Feast Holiday* (*estimated)","TR",2043 +"2043-09-06","Ramadan Feast Holiday* (*estimated)","TR",2043 +"2043-10-29","Republic Day","TR",2043 +"2043-11-12","Sacrifice Feast* (*estimated)","TR",2043 +"2043-11-13","Sacrifice Feast Holiday* (*estimated)","TR",2043 +"2043-11-14","Sacrifice Feast Holiday* (*estimated)","TR",2043 +"2043-11-15","Sacrifice Feast Holiday* (*estimated)","TR",2043 +"2044-01-01","New Year's Day","TR",2044 +"2044-04-23","National Sovereignty and Children's Day","TR",2044 +"2044-05-01","Labour Day","TR",2044 +"2044-05-19","Commemoration of Ataturk, Youth and Sports Day","TR",2044 +"2044-07-15","Democracy and National Unity Day","TR",2044 +"2044-08-24","Ramadan Feast* (*estimated)","TR",2044 +"2044-08-25","Ramadan Feast Holiday* (*estimated)","TR",2044 +"2044-08-26","Ramadan Feast Holiday* (*estimated)","TR",2044 +"2044-08-30","Victory Day","TR",2044 +"2044-10-29","Republic Day","TR",2044 +"2044-10-31","Sacrifice Feast* (*estimated)","TR",2044 +"2044-11-01","Sacrifice Feast Holiday* (*estimated)","TR",2044 +"2044-11-02","Sacrifice Feast Holiday* (*estimated)","TR",2044 +"2044-11-03","Sacrifice Feast Holiday* (*estimated)","TR",2044 +"1995-01-01","New Year's Day","TU",1995 +"1995-03-02","Ramadan Feast* (*estimated)","TU",1995 +"1995-03-03","Ramadan Feast Holiday* (*estimated)","TU",1995 +"1995-03-04","Ramadan Feast Holiday* (*estimated)","TU",1995 +"1995-04-23","National Sovereignty and Children's Day","TU",1995 +"1995-05-01","Labour Day","TU",1995 +"1995-05-09","Sacrifice Feast* (*estimated)","TU",1995 +"1995-05-10","Sacrifice Feast Holiday* (*estimated)","TU",1995 +"1995-05-11","Sacrifice Feast Holiday* (*estimated)","TU",1995 +"1995-05-12","Sacrifice Feast Holiday* (*estimated)","TU",1995 +"1995-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",1995 +"1995-08-30","Victory Day","TU",1995 +"1995-10-29","Republic Day","TU",1995 +"1996-01-01","New Year's Day","TU",1996 +"1996-02-19","Ramadan Feast* (*estimated)","TU",1996 +"1996-02-20","Ramadan Feast Holiday* (*estimated)","TU",1996 +"1996-02-21","Ramadan Feast Holiday* (*estimated)","TU",1996 +"1996-04-23","National Sovereignty and Children's Day","TU",1996 +"1996-04-27","Sacrifice Feast* (*estimated)","TU",1996 +"1996-04-28","Sacrifice Feast Holiday* (*estimated)","TU",1996 +"1996-04-29","Sacrifice Feast Holiday* (*estimated)","TU",1996 +"1996-04-30","Sacrifice Feast Holiday* (*estimated)","TU",1996 +"1996-05-01","Labour Day","TU",1996 +"1996-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",1996 +"1996-08-30","Victory Day","TU",1996 +"1996-10-29","Republic Day","TU",1996 +"1997-01-01","New Year's Day","TU",1997 +"1997-02-08","Ramadan Feast* (*estimated)","TU",1997 +"1997-02-09","Ramadan Feast Holiday* (*estimated)","TU",1997 +"1997-02-10","Ramadan Feast Holiday* (*estimated)","TU",1997 +"1997-04-17","Sacrifice Feast* (*estimated)","TU",1997 +"1997-04-18","Sacrifice Feast Holiday* (*estimated)","TU",1997 +"1997-04-19","Sacrifice Feast Holiday* (*estimated)","TU",1997 +"1997-04-20","Sacrifice Feast Holiday* (*estimated)","TU",1997 +"1997-04-23","National Sovereignty and Children's Day","TU",1997 +"1997-05-01","Labour Day","TU",1997 +"1997-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",1997 +"1997-08-30","Victory Day","TU",1997 +"1997-10-29","Republic Day","TU",1997 +"1998-01-01","New Year's Day","TU",1998 +"1998-01-29","Ramadan Feast* (*estimated)","TU",1998 +"1998-01-30","Ramadan Feast Holiday* (*estimated)","TU",1998 +"1998-01-31","Ramadan Feast Holiday* (*estimated)","TU",1998 +"1998-04-07","Sacrifice Feast* (*estimated)","TU",1998 +"1998-04-08","Sacrifice Feast Holiday* (*estimated)","TU",1998 +"1998-04-09","Sacrifice Feast Holiday* (*estimated)","TU",1998 +"1998-04-10","Sacrifice Feast Holiday* (*estimated)","TU",1998 +"1998-04-23","National Sovereignty and Children's Day","TU",1998 +"1998-05-01","Labour Day","TU",1998 +"1998-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",1998 +"1998-08-30","Victory Day","TU",1998 +"1998-10-29","Republic Day","TU",1998 +"1999-01-01","New Year's Day","TU",1999 +"1999-01-18","Ramadan Feast* (*estimated)","TU",1999 +"1999-01-19","Ramadan Feast Holiday* (*estimated)","TU",1999 +"1999-01-20","Ramadan Feast Holiday* (*estimated)","TU",1999 +"1999-03-27","Sacrifice Feast* (*estimated)","TU",1999 +"1999-03-28","Sacrifice Feast Holiday* (*estimated)","TU",1999 +"1999-03-29","Sacrifice Feast Holiday* (*estimated)","TU",1999 +"1999-03-30","Sacrifice Feast Holiday* (*estimated)","TU",1999 +"1999-04-23","National Sovereignty and Children's Day","TU",1999 +"1999-05-01","Labour Day","TU",1999 +"1999-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",1999 +"1999-08-30","Victory Day","TU",1999 +"1999-10-29","Republic Day","TU",1999 +"2000-01-01","New Year's Day","TU",2000 +"2000-01-08","Ramadan Feast* (*estimated)","TU",2000 +"2000-01-09","Ramadan Feast Holiday* (*estimated)","TU",2000 +"2000-01-10","Ramadan Feast Holiday* (*estimated)","TU",2000 +"2000-03-16","Sacrifice Feast* (*estimated)","TU",2000 +"2000-03-17","Sacrifice Feast Holiday* (*estimated)","TU",2000 +"2000-03-18","Sacrifice Feast Holiday* (*estimated)","TU",2000 +"2000-03-19","Sacrifice Feast Holiday* (*estimated)","TU",2000 +"2000-04-23","National Sovereignty and Children's Day","TU",2000 +"2000-05-01","Labour Day","TU",2000 +"2000-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2000 +"2000-08-30","Victory Day","TU",2000 +"2000-10-29","Republic Day","TU",2000 +"2000-12-27","Ramadan Feast* (*estimated)","TU",2000 +"2000-12-28","Ramadan Feast Holiday* (*estimated)","TU",2000 +"2000-12-29","Ramadan Feast Holiday* (*estimated)","TU",2000 +"2001-01-01","New Year's Day","TU",2001 +"2001-03-05","Sacrifice Feast* (*estimated)","TU",2001 +"2001-03-06","Sacrifice Feast Holiday* (*estimated)","TU",2001 +"2001-03-07","Sacrifice Feast Holiday* (*estimated)","TU",2001 +"2001-03-08","Sacrifice Feast Holiday* (*estimated)","TU",2001 +"2001-04-23","National Sovereignty and Children's Day","TU",2001 +"2001-05-01","Labour Day","TU",2001 +"2001-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2001 +"2001-08-30","Victory Day","TU",2001 +"2001-10-29","Republic Day","TU",2001 +"2001-12-16","Ramadan Feast* (*estimated)","TU",2001 +"2001-12-17","Ramadan Feast Holiday* (*estimated)","TU",2001 +"2001-12-18","Ramadan Feast Holiday* (*estimated)","TU",2001 +"2002-01-01","New Year's Day","TU",2002 +"2002-02-22","Sacrifice Feast* (*estimated)","TU",2002 +"2002-02-23","Sacrifice Feast Holiday* (*estimated)","TU",2002 +"2002-02-24","Sacrifice Feast Holiday* (*estimated)","TU",2002 +"2002-02-25","Sacrifice Feast Holiday* (*estimated)","TU",2002 +"2002-04-23","National Sovereignty and Children's Day","TU",2002 +"2002-05-01","Labour Day","TU",2002 +"2002-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2002 +"2002-08-30","Victory Day","TU",2002 +"2002-10-29","Republic Day","TU",2002 +"2002-12-05","Ramadan Feast* (*estimated)","TU",2002 +"2002-12-06","Ramadan Feast Holiday* (*estimated)","TU",2002 +"2002-12-07","Ramadan Feast Holiday* (*estimated)","TU",2002 +"2003-01-01","New Year's Day","TU",2003 +"2003-02-11","Sacrifice Feast* (*estimated)","TU",2003 +"2003-02-12","Sacrifice Feast Holiday* (*estimated)","TU",2003 +"2003-02-13","Sacrifice Feast Holiday* (*estimated)","TU",2003 +"2003-02-14","Sacrifice Feast Holiday* (*estimated)","TU",2003 +"2003-04-23","National Sovereignty and Children's Day","TU",2003 +"2003-05-01","Labour Day","TU",2003 +"2003-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2003 +"2003-08-30","Victory Day","TU",2003 +"2003-10-29","Republic Day","TU",2003 +"2003-11-25","Ramadan Feast* (*estimated)","TU",2003 +"2003-11-26","Ramadan Feast Holiday* (*estimated)","TU",2003 +"2003-11-27","Ramadan Feast Holiday* (*estimated)","TU",2003 +"2004-01-01","New Year's Day","TU",2004 +"2004-02-01","Sacrifice Feast* (*estimated)","TU",2004 +"2004-02-02","Sacrifice Feast Holiday* (*estimated)","TU",2004 +"2004-02-03","Sacrifice Feast Holiday* (*estimated)","TU",2004 +"2004-02-04","Sacrifice Feast Holiday* (*estimated)","TU",2004 +"2004-04-23","National Sovereignty and Children's Day","TU",2004 +"2004-05-01","Labour Day","TU",2004 +"2004-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2004 +"2004-08-30","Victory Day","TU",2004 +"2004-10-29","Republic Day","TU",2004 +"2004-11-14","Ramadan Feast* (*estimated)","TU",2004 +"2004-11-15","Ramadan Feast Holiday* (*estimated)","TU",2004 +"2004-11-16","Ramadan Feast Holiday* (*estimated)","TU",2004 +"2005-01-01","New Year's Day","TU",2005 +"2005-01-21","Sacrifice Feast* (*estimated)","TU",2005 +"2005-01-22","Sacrifice Feast Holiday* (*estimated)","TU",2005 +"2005-01-23","Sacrifice Feast Holiday* (*estimated)","TU",2005 +"2005-01-24","Sacrifice Feast Holiday* (*estimated)","TU",2005 +"2005-04-23","National Sovereignty and Children's Day","TU",2005 +"2005-05-01","Labour Day","TU",2005 +"2005-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2005 +"2005-08-30","Victory Day","TU",2005 +"2005-10-29","Republic Day","TU",2005 +"2005-11-03","Ramadan Feast* (*estimated)","TU",2005 +"2005-11-04","Ramadan Feast Holiday* (*estimated)","TU",2005 +"2005-11-05","Ramadan Feast Holiday* (*estimated)","TU",2005 +"2006-01-01","New Year's Day","TU",2006 +"2006-01-10","Sacrifice Feast* (*estimated)","TU",2006 +"2006-01-11","Sacrifice Feast Holiday* (*estimated)","TU",2006 +"2006-01-12","Sacrifice Feast Holiday* (*estimated)","TU",2006 +"2006-01-13","Sacrifice Feast Holiday* (*estimated)","TU",2006 +"2006-04-23","National Sovereignty and Children's Day","TU",2006 +"2006-05-01","Labour Day","TU",2006 +"2006-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2006 +"2006-08-30","Victory Day","TU",2006 +"2006-10-23","Ramadan Feast* (*estimated)","TU",2006 +"2006-10-24","Ramadan Feast Holiday* (*estimated)","TU",2006 +"2006-10-25","Ramadan Feast Holiday* (*estimated)","TU",2006 +"2006-10-29","Republic Day","TU",2006 +"2006-12-31","Sacrifice Feast* (*estimated)","TU",2006 +"2007-01-01","New Year's Day","TU",2007 +"2007-01-01","Sacrifice Feast Holiday* (*estimated)","TU",2007 +"2007-01-02","Sacrifice Feast Holiday* (*estimated)","TU",2007 +"2007-01-03","Sacrifice Feast Holiday* (*estimated)","TU",2007 +"2007-04-23","National Sovereignty and Children's Day","TU",2007 +"2007-05-01","Labour Day","TU",2007 +"2007-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2007 +"2007-08-30","Victory Day","TU",2007 +"2007-10-13","Ramadan Feast* (*estimated)","TU",2007 +"2007-10-14","Ramadan Feast Holiday* (*estimated)","TU",2007 +"2007-10-15","Ramadan Feast Holiday* (*estimated)","TU",2007 +"2007-10-29","Republic Day","TU",2007 +"2007-12-20","Sacrifice Feast* (*estimated)","TU",2007 +"2007-12-21","Sacrifice Feast Holiday* (*estimated)","TU",2007 +"2007-12-22","Sacrifice Feast Holiday* (*estimated)","TU",2007 +"2007-12-23","Sacrifice Feast Holiday* (*estimated)","TU",2007 +"2008-01-01","New Year's Day","TU",2008 +"2008-04-23","National Sovereignty and Children's Day","TU",2008 +"2008-05-01","Labour Day","TU",2008 +"2008-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2008 +"2008-08-30","Victory Day","TU",2008 +"2008-10-01","Ramadan Feast* (*estimated)","TU",2008 +"2008-10-02","Ramadan Feast Holiday* (*estimated)","TU",2008 +"2008-10-03","Ramadan Feast Holiday* (*estimated)","TU",2008 +"2008-10-29","Republic Day","TU",2008 +"2008-12-08","Sacrifice Feast* (*estimated)","TU",2008 +"2008-12-09","Sacrifice Feast Holiday* (*estimated)","TU",2008 +"2008-12-10","Sacrifice Feast Holiday* (*estimated)","TU",2008 +"2008-12-11","Sacrifice Feast Holiday* (*estimated)","TU",2008 +"2009-01-01","New Year's Day","TU",2009 +"2009-04-23","National Sovereignty and Children's Day","TU",2009 +"2009-05-01","Labour Day","TU",2009 +"2009-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2009 +"2009-08-30","Victory Day","TU",2009 +"2009-09-20","Ramadan Feast* (*estimated)","TU",2009 +"2009-09-21","Ramadan Feast Holiday* (*estimated)","TU",2009 +"2009-09-22","Ramadan Feast Holiday* (*estimated)","TU",2009 +"2009-10-29","Republic Day","TU",2009 +"2009-11-27","Sacrifice Feast* (*estimated)","TU",2009 +"2009-11-28","Sacrifice Feast Holiday* (*estimated)","TU",2009 +"2009-11-29","Sacrifice Feast Holiday* (*estimated)","TU",2009 +"2009-11-30","Sacrifice Feast Holiday* (*estimated)","TU",2009 +"2010-01-01","New Year's Day","TU",2010 +"2010-04-23","National Sovereignty and Children's Day","TU",2010 +"2010-05-01","Labour Day","TU",2010 +"2010-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2010 +"2010-08-30","Victory Day","TU",2010 +"2010-09-10","Ramadan Feast* (*estimated)","TU",2010 +"2010-09-11","Ramadan Feast Holiday* (*estimated)","TU",2010 +"2010-09-12","Ramadan Feast Holiday* (*estimated)","TU",2010 +"2010-10-29","Republic Day","TU",2010 +"2010-11-16","Sacrifice Feast* (*estimated)","TU",2010 +"2010-11-17","Sacrifice Feast Holiday* (*estimated)","TU",2010 +"2010-11-18","Sacrifice Feast Holiday* (*estimated)","TU",2010 +"2010-11-19","Sacrifice Feast Holiday* (*estimated)","TU",2010 +"2011-01-01","New Year's Day","TU",2011 +"2011-04-23","National Sovereignty and Children's Day","TU",2011 +"2011-05-01","Labour Day","TU",2011 +"2011-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2011 +"2011-08-30","Ramadan Feast* (*estimated)","TU",2011 +"2011-08-30","Victory Day","TU",2011 +"2011-08-31","Ramadan Feast Holiday* (*estimated)","TU",2011 +"2011-09-01","Ramadan Feast Holiday* (*estimated)","TU",2011 +"2011-10-29","Republic Day","TU",2011 +"2011-11-06","Sacrifice Feast* (*estimated)","TU",2011 +"2011-11-07","Sacrifice Feast Holiday* (*estimated)","TU",2011 +"2011-11-08","Sacrifice Feast Holiday* (*estimated)","TU",2011 +"2011-11-09","Sacrifice Feast Holiday* (*estimated)","TU",2011 +"2012-01-01","New Year's Day","TU",2012 +"2012-04-23","National Sovereignty and Children's Day","TU",2012 +"2012-05-01","Labour Day","TU",2012 +"2012-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2012 +"2012-08-19","Ramadan Feast* (*estimated)","TU",2012 +"2012-08-20","Ramadan Feast Holiday* (*estimated)","TU",2012 +"2012-08-21","Ramadan Feast Holiday* (*estimated)","TU",2012 +"2012-08-30","Victory Day","TU",2012 +"2012-10-26","Sacrifice Feast* (*estimated)","TU",2012 +"2012-10-27","Sacrifice Feast Holiday* (*estimated)","TU",2012 +"2012-10-28","Sacrifice Feast Holiday* (*estimated)","TU",2012 +"2012-10-29","Republic Day","TU",2012 +"2012-10-29","Sacrifice Feast Holiday* (*estimated)","TU",2012 +"2013-01-01","New Year's Day","TU",2013 +"2013-04-23","National Sovereignty and Children's Day","TU",2013 +"2013-05-01","Labour Day","TU",2013 +"2013-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2013 +"2013-08-08","Ramadan Feast* (*estimated)","TU",2013 +"2013-08-09","Ramadan Feast Holiday* (*estimated)","TU",2013 +"2013-08-10","Ramadan Feast Holiday* (*estimated)","TU",2013 +"2013-08-30","Victory Day","TU",2013 +"2013-10-15","Sacrifice Feast* (*estimated)","TU",2013 +"2013-10-16","Sacrifice Feast Holiday* (*estimated)","TU",2013 +"2013-10-17","Sacrifice Feast Holiday* (*estimated)","TU",2013 +"2013-10-18","Sacrifice Feast Holiday* (*estimated)","TU",2013 +"2013-10-29","Republic Day","TU",2013 +"2014-01-01","New Year's Day","TU",2014 +"2014-04-23","National Sovereignty and Children's Day","TU",2014 +"2014-05-01","Labour Day","TU",2014 +"2014-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2014 +"2014-07-28","Ramadan Feast* (*estimated)","TU",2014 +"2014-07-29","Ramadan Feast Holiday* (*estimated)","TU",2014 +"2014-07-30","Ramadan Feast Holiday* (*estimated)","TU",2014 +"2014-08-30","Victory Day","TU",2014 +"2014-10-04","Sacrifice Feast* (*estimated)","TU",2014 +"2014-10-05","Sacrifice Feast Holiday* (*estimated)","TU",2014 +"2014-10-06","Sacrifice Feast Holiday* (*estimated)","TU",2014 +"2014-10-07","Sacrifice Feast Holiday* (*estimated)","TU",2014 +"2014-10-29","Republic Day","TU",2014 +"2015-01-01","New Year's Day","TU",2015 +"2015-04-23","National Sovereignty and Children's Day","TU",2015 +"2015-05-01","Labour Day","TU",2015 +"2015-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2015 +"2015-07-17","Ramadan Feast* (*estimated)","TU",2015 +"2015-07-18","Ramadan Feast Holiday* (*estimated)","TU",2015 +"2015-07-19","Ramadan Feast Holiday* (*estimated)","TU",2015 +"2015-08-30","Victory Day","TU",2015 +"2015-09-23","Sacrifice Feast* (*estimated)","TU",2015 +"2015-09-24","Sacrifice Feast Holiday* (*estimated)","TU",2015 +"2015-09-25","Sacrifice Feast Holiday* (*estimated)","TU",2015 +"2015-09-26","Sacrifice Feast Holiday* (*estimated)","TU",2015 +"2015-10-29","Republic Day","TU",2015 +"2016-01-01","New Year's Day","TU",2016 +"2016-04-23","National Sovereignty and Children's Day","TU",2016 +"2016-05-01","Labour Day","TU",2016 +"2016-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2016 +"2016-07-06","Ramadan Feast* (*estimated)","TU",2016 +"2016-07-07","Ramadan Feast Holiday* (*estimated)","TU",2016 +"2016-07-08","Ramadan Feast Holiday* (*estimated)","TU",2016 +"2016-08-30","Victory Day","TU",2016 +"2016-09-11","Sacrifice Feast* (*estimated)","TU",2016 +"2016-09-12","Sacrifice Feast Holiday* (*estimated)","TU",2016 +"2016-09-13","Sacrifice Feast Holiday* (*estimated)","TU",2016 +"2016-09-14","Sacrifice Feast Holiday* (*estimated)","TU",2016 +"2016-10-29","Republic Day","TU",2016 +"2017-01-01","New Year's Day","TU",2017 +"2017-04-23","National Sovereignty and Children's Day","TU",2017 +"2017-05-01","Labour Day","TU",2017 +"2017-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2017 +"2017-06-25","Ramadan Feast* (*estimated)","TU",2017 +"2017-06-26","Ramadan Feast Holiday* (*estimated)","TU",2017 +"2017-06-27","Ramadan Feast Holiday* (*estimated)","TU",2017 +"2017-07-15","Democracy and National Unity Day","TU",2017 +"2017-08-30","Victory Day","TU",2017 +"2017-09-01","Sacrifice Feast* (*estimated)","TU",2017 +"2017-09-02","Sacrifice Feast Holiday* (*estimated)","TU",2017 +"2017-09-03","Sacrifice Feast Holiday* (*estimated)","TU",2017 +"2017-09-04","Sacrifice Feast Holiday* (*estimated)","TU",2017 +"2017-10-29","Republic Day","TU",2017 +"2018-01-01","New Year's Day","TU",2018 +"2018-04-23","National Sovereignty and Children's Day","TU",2018 +"2018-05-01","Labour Day","TU",2018 +"2018-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2018 +"2018-06-15","Ramadan Feast* (*estimated)","TU",2018 +"2018-06-16","Ramadan Feast Holiday* (*estimated)","TU",2018 +"2018-06-17","Ramadan Feast Holiday* (*estimated)","TU",2018 +"2018-07-15","Democracy and National Unity Day","TU",2018 +"2018-08-21","Sacrifice Feast* (*estimated)","TU",2018 +"2018-08-22","Sacrifice Feast Holiday* (*estimated)","TU",2018 +"2018-08-23","Sacrifice Feast Holiday* (*estimated)","TU",2018 +"2018-08-24","Sacrifice Feast Holiday* (*estimated)","TU",2018 +"2018-08-30","Victory Day","TU",2018 +"2018-10-29","Republic Day","TU",2018 +"2019-01-01","New Year's Day","TU",2019 +"2019-04-23","National Sovereignty and Children's Day","TU",2019 +"2019-05-01","Labour Day","TU",2019 +"2019-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2019 +"2019-06-04","Ramadan Feast* (*estimated)","TU",2019 +"2019-06-05","Ramadan Feast Holiday* (*estimated)","TU",2019 +"2019-06-06","Ramadan Feast Holiday* (*estimated)","TU",2019 +"2019-07-15","Democracy and National Unity Day","TU",2019 +"2019-08-11","Sacrifice Feast* (*estimated)","TU",2019 +"2019-08-12","Sacrifice Feast Holiday* (*estimated)","TU",2019 +"2019-08-13","Sacrifice Feast Holiday* (*estimated)","TU",2019 +"2019-08-14","Sacrifice Feast Holiday* (*estimated)","TU",2019 +"2019-08-30","Victory Day","TU",2019 +"2019-10-29","Republic Day","TU",2019 +"2020-01-01","New Year's Day","TU",2020 +"2020-04-23","National Sovereignty and Children's Day","TU",2020 +"2020-05-01","Labour Day","TU",2020 +"2020-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2020 +"2020-05-24","Ramadan Feast* (*estimated)","TU",2020 +"2020-05-25","Ramadan Feast Holiday* (*estimated)","TU",2020 +"2020-05-26","Ramadan Feast Holiday* (*estimated)","TU",2020 +"2020-07-15","Democracy and National Unity Day","TU",2020 +"2020-07-31","Sacrifice Feast* (*estimated)","TU",2020 +"2020-08-01","Sacrifice Feast Holiday* (*estimated)","TU",2020 +"2020-08-02","Sacrifice Feast Holiday* (*estimated)","TU",2020 +"2020-08-03","Sacrifice Feast Holiday* (*estimated)","TU",2020 +"2020-08-30","Victory Day","TU",2020 +"2020-10-29","Republic Day","TU",2020 +"2021-01-01","New Year's Day","TU",2021 +"2021-04-23","National Sovereignty and Children's Day","TU",2021 +"2021-05-01","Labour Day","TU",2021 +"2021-05-13","Ramadan Feast* (*estimated)","TU",2021 +"2021-05-14","Ramadan Feast Holiday* (*estimated)","TU",2021 +"2021-05-15","Ramadan Feast Holiday* (*estimated)","TU",2021 +"2021-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2021 +"2021-07-15","Democracy and National Unity Day","TU",2021 +"2021-07-20","Sacrifice Feast* (*estimated)","TU",2021 +"2021-07-21","Sacrifice Feast Holiday* (*estimated)","TU",2021 +"2021-07-22","Sacrifice Feast Holiday* (*estimated)","TU",2021 +"2021-07-23","Sacrifice Feast Holiday* (*estimated)","TU",2021 +"2021-08-30","Victory Day","TU",2021 +"2021-10-29","Republic Day","TU",2021 +"2022-01-01","New Year's Day","TU",2022 +"2022-04-23","National Sovereignty and Children's Day","TU",2022 +"2022-05-01","Labour Day","TU",2022 +"2022-05-02","Ramadan Feast* (*estimated)","TU",2022 +"2022-05-03","Ramadan Feast Holiday* (*estimated)","TU",2022 +"2022-05-04","Ramadan Feast Holiday* (*estimated)","TU",2022 +"2022-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2022 +"2022-07-09","Sacrifice Feast* (*estimated)","TU",2022 +"2022-07-10","Sacrifice Feast Holiday* (*estimated)","TU",2022 +"2022-07-11","Sacrifice Feast Holiday* (*estimated)","TU",2022 +"2022-07-12","Sacrifice Feast Holiday* (*estimated)","TU",2022 +"2022-07-15","Democracy and National Unity Day","TU",2022 +"2022-08-30","Victory Day","TU",2022 +"2022-10-29","Republic Day","TU",2022 +"2023-01-01","New Year's Day","TU",2023 +"2023-04-21","Ramadan Feast* (*estimated)","TU",2023 +"2023-04-22","Ramadan Feast Holiday* (*estimated)","TU",2023 +"2023-04-23","National Sovereignty and Children's Day","TU",2023 +"2023-04-23","Ramadan Feast Holiday* (*estimated)","TU",2023 +"2023-05-01","Labour Day","TU",2023 +"2023-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2023 +"2023-06-28","Sacrifice Feast* (*estimated)","TU",2023 +"2023-06-29","Sacrifice Feast Holiday* (*estimated)","TU",2023 +"2023-06-30","Sacrifice Feast Holiday* (*estimated)","TU",2023 +"2023-07-01","Sacrifice Feast Holiday* (*estimated)","TU",2023 +"2023-07-15","Democracy and National Unity Day","TU",2023 +"2023-08-30","Victory Day","TU",2023 +"2023-10-29","Republic Day","TU",2023 +"2024-01-01","New Year's Day","TU",2024 +"2024-04-10","Ramadan Feast* (*estimated)","TU",2024 +"2024-04-11","Ramadan Feast Holiday* (*estimated)","TU",2024 +"2024-04-12","Ramadan Feast Holiday* (*estimated)","TU",2024 +"2024-04-23","National Sovereignty and Children's Day","TU",2024 +"2024-05-01","Labour Day","TU",2024 +"2024-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2024 +"2024-06-16","Sacrifice Feast* (*estimated)","TU",2024 +"2024-06-17","Sacrifice Feast Holiday* (*estimated)","TU",2024 +"2024-06-18","Sacrifice Feast Holiday* (*estimated)","TU",2024 +"2024-06-19","Sacrifice Feast Holiday* (*estimated)","TU",2024 +"2024-07-15","Democracy and National Unity Day","TU",2024 +"2024-08-30","Victory Day","TU",2024 +"2024-10-29","Republic Day","TU",2024 +"2025-01-01","New Year's Day","TU",2025 +"2025-03-30","Ramadan Feast* (*estimated)","TU",2025 +"2025-03-31","Ramadan Feast Holiday* (*estimated)","TU",2025 +"2025-04-01","Ramadan Feast Holiday* (*estimated)","TU",2025 +"2025-04-23","National Sovereignty and Children's Day","TU",2025 +"2025-05-01","Labour Day","TU",2025 +"2025-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2025 +"2025-06-06","Sacrifice Feast* (*estimated)","TU",2025 +"2025-06-07","Sacrifice Feast Holiday* (*estimated)","TU",2025 +"2025-06-08","Sacrifice Feast Holiday* (*estimated)","TU",2025 +"2025-06-09","Sacrifice Feast Holiday* (*estimated)","TU",2025 +"2025-07-15","Democracy and National Unity Day","TU",2025 +"2025-08-30","Victory Day","TU",2025 +"2025-10-29","Republic Day","TU",2025 +"2026-01-01","New Year's Day","TU",2026 +"2026-03-20","Ramadan Feast* (*estimated)","TU",2026 +"2026-03-21","Ramadan Feast Holiday* (*estimated)","TU",2026 +"2026-03-22","Ramadan Feast Holiday* (*estimated)","TU",2026 +"2026-04-23","National Sovereignty and Children's Day","TU",2026 +"2026-05-01","Labour Day","TU",2026 +"2026-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2026 +"2026-05-27","Sacrifice Feast* (*estimated)","TU",2026 +"2026-05-28","Sacrifice Feast Holiday* (*estimated)","TU",2026 +"2026-05-29","Sacrifice Feast Holiday* (*estimated)","TU",2026 +"2026-05-30","Sacrifice Feast Holiday* (*estimated)","TU",2026 +"2026-07-15","Democracy and National Unity Day","TU",2026 +"2026-08-30","Victory Day","TU",2026 +"2026-10-29","Republic Day","TU",2026 +"2027-01-01","New Year's Day","TU",2027 +"2027-03-09","Ramadan Feast* (*estimated)","TU",2027 +"2027-03-10","Ramadan Feast Holiday* (*estimated)","TU",2027 +"2027-03-11","Ramadan Feast Holiday* (*estimated)","TU",2027 +"2027-04-23","National Sovereignty and Children's Day","TU",2027 +"2027-05-01","Labour Day","TU",2027 +"2027-05-16","Sacrifice Feast* (*estimated)","TU",2027 +"2027-05-17","Sacrifice Feast Holiday* (*estimated)","TU",2027 +"2027-05-18","Sacrifice Feast Holiday* (*estimated)","TU",2027 +"2027-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2027 +"2027-05-19","Sacrifice Feast Holiday* (*estimated)","TU",2027 +"2027-07-15","Democracy and National Unity Day","TU",2027 +"2027-08-30","Victory Day","TU",2027 +"2027-10-29","Republic Day","TU",2027 +"2028-01-01","New Year's Day","TU",2028 +"2028-02-26","Ramadan Feast* (*estimated)","TU",2028 +"2028-02-27","Ramadan Feast Holiday* (*estimated)","TU",2028 +"2028-02-28","Ramadan Feast Holiday* (*estimated)","TU",2028 +"2028-04-23","National Sovereignty and Children's Day","TU",2028 +"2028-05-01","Labour Day","TU",2028 +"2028-05-05","Sacrifice Feast* (*estimated)","TU",2028 +"2028-05-06","Sacrifice Feast Holiday* (*estimated)","TU",2028 +"2028-05-07","Sacrifice Feast Holiday* (*estimated)","TU",2028 +"2028-05-08","Sacrifice Feast Holiday* (*estimated)","TU",2028 +"2028-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2028 +"2028-07-15","Democracy and National Unity Day","TU",2028 +"2028-08-30","Victory Day","TU",2028 +"2028-10-29","Republic Day","TU",2028 +"2029-01-01","New Year's Day","TU",2029 +"2029-02-14","Ramadan Feast* (*estimated)","TU",2029 +"2029-02-15","Ramadan Feast Holiday* (*estimated)","TU",2029 +"2029-02-16","Ramadan Feast Holiday* (*estimated)","TU",2029 +"2029-04-23","National Sovereignty and Children's Day","TU",2029 +"2029-04-24","Sacrifice Feast* (*estimated)","TU",2029 +"2029-04-25","Sacrifice Feast Holiday* (*estimated)","TU",2029 +"2029-04-26","Sacrifice Feast Holiday* (*estimated)","TU",2029 +"2029-04-27","Sacrifice Feast Holiday* (*estimated)","TU",2029 +"2029-05-01","Labour Day","TU",2029 +"2029-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2029 +"2029-07-15","Democracy and National Unity Day","TU",2029 +"2029-08-30","Victory Day","TU",2029 +"2029-10-29","Republic Day","TU",2029 +"2030-01-01","New Year's Day","TU",2030 +"2030-02-04","Ramadan Feast* (*estimated)","TU",2030 +"2030-02-05","Ramadan Feast Holiday* (*estimated)","TU",2030 +"2030-02-06","Ramadan Feast Holiday* (*estimated)","TU",2030 +"2030-04-13","Sacrifice Feast* (*estimated)","TU",2030 +"2030-04-14","Sacrifice Feast Holiday* (*estimated)","TU",2030 +"2030-04-15","Sacrifice Feast Holiday* (*estimated)","TU",2030 +"2030-04-16","Sacrifice Feast Holiday* (*estimated)","TU",2030 +"2030-04-23","National Sovereignty and Children's Day","TU",2030 +"2030-05-01","Labour Day","TU",2030 +"2030-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2030 +"2030-07-15","Democracy and National Unity Day","TU",2030 +"2030-08-30","Victory Day","TU",2030 +"2030-10-29","Republic Day","TU",2030 +"2031-01-01","New Year's Day","TU",2031 +"2031-01-24","Ramadan Feast* (*estimated)","TU",2031 +"2031-01-25","Ramadan Feast Holiday* (*estimated)","TU",2031 +"2031-01-26","Ramadan Feast Holiday* (*estimated)","TU",2031 +"2031-04-02","Sacrifice Feast* (*estimated)","TU",2031 +"2031-04-03","Sacrifice Feast Holiday* (*estimated)","TU",2031 +"2031-04-04","Sacrifice Feast Holiday* (*estimated)","TU",2031 +"2031-04-05","Sacrifice Feast Holiday* (*estimated)","TU",2031 +"2031-04-23","National Sovereignty and Children's Day","TU",2031 +"2031-05-01","Labour Day","TU",2031 +"2031-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2031 +"2031-07-15","Democracy and National Unity Day","TU",2031 +"2031-08-30","Victory Day","TU",2031 +"2031-10-29","Republic Day","TU",2031 +"2032-01-01","New Year's Day","TU",2032 +"2032-01-14","Ramadan Feast* (*estimated)","TU",2032 +"2032-01-15","Ramadan Feast Holiday* (*estimated)","TU",2032 +"2032-01-16","Ramadan Feast Holiday* (*estimated)","TU",2032 +"2032-03-22","Sacrifice Feast* (*estimated)","TU",2032 +"2032-03-23","Sacrifice Feast Holiday* (*estimated)","TU",2032 +"2032-03-24","Sacrifice Feast Holiday* (*estimated)","TU",2032 +"2032-03-25","Sacrifice Feast Holiday* (*estimated)","TU",2032 +"2032-04-23","National Sovereignty and Children's Day","TU",2032 +"2032-05-01","Labour Day","TU",2032 +"2032-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2032 +"2032-07-15","Democracy and National Unity Day","TU",2032 +"2032-08-30","Victory Day","TU",2032 +"2032-10-29","Republic Day","TU",2032 +"2033-01-01","New Year's Day","TU",2033 +"2033-01-02","Ramadan Feast* (*estimated)","TU",2033 +"2033-01-03","Ramadan Feast Holiday* (*estimated)","TU",2033 +"2033-01-04","Ramadan Feast Holiday* (*estimated)","TU",2033 +"2033-03-11","Sacrifice Feast* (*estimated)","TU",2033 +"2033-03-12","Sacrifice Feast Holiday* (*estimated)","TU",2033 +"2033-03-13","Sacrifice Feast Holiday* (*estimated)","TU",2033 +"2033-03-14","Sacrifice Feast Holiday* (*estimated)","TU",2033 +"2033-04-23","National Sovereignty and Children's Day","TU",2033 +"2033-05-01","Labour Day","TU",2033 +"2033-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2033 +"2033-07-15","Democracy and National Unity Day","TU",2033 +"2033-08-30","Victory Day","TU",2033 +"2033-10-29","Republic Day","TU",2033 +"2033-12-23","Ramadan Feast* (*estimated)","TU",2033 +"2033-12-24","Ramadan Feast Holiday* (*estimated)","TU",2033 +"2033-12-25","Ramadan Feast Holiday* (*estimated)","TU",2033 +"2034-01-01","New Year's Day","TU",2034 +"2034-03-01","Sacrifice Feast* (*estimated)","TU",2034 +"2034-03-02","Sacrifice Feast Holiday* (*estimated)","TU",2034 +"2034-03-03","Sacrifice Feast Holiday* (*estimated)","TU",2034 +"2034-03-04","Sacrifice Feast Holiday* (*estimated)","TU",2034 +"2034-04-23","National Sovereignty and Children's Day","TU",2034 +"2034-05-01","Labour Day","TU",2034 +"2034-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2034 +"2034-07-15","Democracy and National Unity Day","TU",2034 +"2034-08-30","Victory Day","TU",2034 +"2034-10-29","Republic Day","TU",2034 +"2034-12-12","Ramadan Feast* (*estimated)","TU",2034 +"2034-12-13","Ramadan Feast Holiday* (*estimated)","TU",2034 +"2034-12-14","Ramadan Feast Holiday* (*estimated)","TU",2034 +"2035-01-01","New Year's Day","TU",2035 +"2035-02-18","Sacrifice Feast* (*estimated)","TU",2035 +"2035-02-19","Sacrifice Feast Holiday* (*estimated)","TU",2035 +"2035-02-20","Sacrifice Feast Holiday* (*estimated)","TU",2035 +"2035-02-21","Sacrifice Feast Holiday* (*estimated)","TU",2035 +"2035-04-23","National Sovereignty and Children's Day","TU",2035 +"2035-05-01","Labour Day","TU",2035 +"2035-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2035 +"2035-07-15","Democracy and National Unity Day","TU",2035 +"2035-08-30","Victory Day","TU",2035 +"2035-10-29","Republic Day","TU",2035 +"2035-12-01","Ramadan Feast* (*estimated)","TU",2035 +"2035-12-02","Ramadan Feast Holiday* (*estimated)","TU",2035 +"2035-12-03","Ramadan Feast Holiday* (*estimated)","TU",2035 +"2036-01-01","New Year's Day","TU",2036 +"2036-02-07","Sacrifice Feast* (*estimated)","TU",2036 +"2036-02-08","Sacrifice Feast Holiday* (*estimated)","TU",2036 +"2036-02-09","Sacrifice Feast Holiday* (*estimated)","TU",2036 +"2036-02-10","Sacrifice Feast Holiday* (*estimated)","TU",2036 +"2036-04-23","National Sovereignty and Children's Day","TU",2036 +"2036-05-01","Labour Day","TU",2036 +"2036-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2036 +"2036-07-15","Democracy and National Unity Day","TU",2036 +"2036-08-30","Victory Day","TU",2036 +"2036-10-29","Republic Day","TU",2036 +"2036-11-19","Ramadan Feast* (*estimated)","TU",2036 +"2036-11-20","Ramadan Feast Holiday* (*estimated)","TU",2036 +"2036-11-21","Ramadan Feast Holiday* (*estimated)","TU",2036 +"2037-01-01","New Year's Day","TU",2037 +"2037-01-26","Sacrifice Feast* (*estimated)","TU",2037 +"2037-01-27","Sacrifice Feast Holiday* (*estimated)","TU",2037 +"2037-01-28","Sacrifice Feast Holiday* (*estimated)","TU",2037 +"2037-01-29","Sacrifice Feast Holiday* (*estimated)","TU",2037 +"2037-04-23","National Sovereignty and Children's Day","TU",2037 +"2037-05-01","Labour Day","TU",2037 +"2037-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2037 +"2037-07-15","Democracy and National Unity Day","TU",2037 +"2037-08-30","Victory Day","TU",2037 +"2037-10-29","Republic Day","TU",2037 +"2037-11-08","Ramadan Feast* (*estimated)","TU",2037 +"2037-11-09","Ramadan Feast Holiday* (*estimated)","TU",2037 +"2037-11-10","Ramadan Feast Holiday* (*estimated)","TU",2037 +"2038-01-01","New Year's Day","TU",2038 +"2038-01-16","Sacrifice Feast* (*estimated)","TU",2038 +"2038-01-17","Sacrifice Feast Holiday* (*estimated)","TU",2038 +"2038-01-18","Sacrifice Feast Holiday* (*estimated)","TU",2038 +"2038-01-19","Sacrifice Feast Holiday* (*estimated)","TU",2038 +"2038-04-23","National Sovereignty and Children's Day","TU",2038 +"2038-05-01","Labour Day","TU",2038 +"2038-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2038 +"2038-07-15","Democracy and National Unity Day","TU",2038 +"2038-08-30","Victory Day","TU",2038 +"2038-10-29","Ramadan Feast* (*estimated)","TU",2038 +"2038-10-29","Republic Day","TU",2038 +"2038-10-30","Ramadan Feast Holiday* (*estimated)","TU",2038 +"2038-10-31","Ramadan Feast Holiday* (*estimated)","TU",2038 +"2039-01-01","New Year's Day","TU",2039 +"2039-01-05","Sacrifice Feast* (*estimated)","TU",2039 +"2039-01-06","Sacrifice Feast Holiday* (*estimated)","TU",2039 +"2039-01-07","Sacrifice Feast Holiday* (*estimated)","TU",2039 +"2039-01-08","Sacrifice Feast Holiday* (*estimated)","TU",2039 +"2039-04-23","National Sovereignty and Children's Day","TU",2039 +"2039-05-01","Labour Day","TU",2039 +"2039-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2039 +"2039-07-15","Democracy and National Unity Day","TU",2039 +"2039-08-30","Victory Day","TU",2039 +"2039-10-19","Ramadan Feast* (*estimated)","TU",2039 +"2039-10-20","Ramadan Feast Holiday* (*estimated)","TU",2039 +"2039-10-21","Ramadan Feast Holiday* (*estimated)","TU",2039 +"2039-10-29","Republic Day","TU",2039 +"2039-12-26","Sacrifice Feast* (*estimated)","TU",2039 +"2039-12-27","Sacrifice Feast Holiday* (*estimated)","TU",2039 +"2039-12-28","Sacrifice Feast Holiday* (*estimated)","TU",2039 +"2039-12-29","Sacrifice Feast Holiday* (*estimated)","TU",2039 +"2040-01-01","New Year's Day","TU",2040 +"2040-04-23","National Sovereignty and Children's Day","TU",2040 +"2040-05-01","Labour Day","TU",2040 +"2040-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2040 +"2040-07-15","Democracy and National Unity Day","TU",2040 +"2040-08-30","Victory Day","TU",2040 +"2040-10-07","Ramadan Feast* (*estimated)","TU",2040 +"2040-10-08","Ramadan Feast Holiday* (*estimated)","TU",2040 +"2040-10-09","Ramadan Feast Holiday* (*estimated)","TU",2040 +"2040-10-29","Republic Day","TU",2040 +"2040-12-14","Sacrifice Feast* (*estimated)","TU",2040 +"2040-12-15","Sacrifice Feast Holiday* (*estimated)","TU",2040 +"2040-12-16","Sacrifice Feast Holiday* (*estimated)","TU",2040 +"2040-12-17","Sacrifice Feast Holiday* (*estimated)","TU",2040 +"2041-01-01","New Year's Day","TU",2041 +"2041-04-23","National Sovereignty and Children's Day","TU",2041 +"2041-05-01","Labour Day","TU",2041 +"2041-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2041 +"2041-07-15","Democracy and National Unity Day","TU",2041 +"2041-08-30","Victory Day","TU",2041 +"2041-09-26","Ramadan Feast* (*estimated)","TU",2041 +"2041-09-27","Ramadan Feast Holiday* (*estimated)","TU",2041 +"2041-09-28","Ramadan Feast Holiday* (*estimated)","TU",2041 +"2041-10-29","Republic Day","TU",2041 +"2041-12-04","Sacrifice Feast* (*estimated)","TU",2041 +"2041-12-05","Sacrifice Feast Holiday* (*estimated)","TU",2041 +"2041-12-06","Sacrifice Feast Holiday* (*estimated)","TU",2041 +"2041-12-07","Sacrifice Feast Holiday* (*estimated)","TU",2041 +"2042-01-01","New Year's Day","TU",2042 +"2042-04-23","National Sovereignty and Children's Day","TU",2042 +"2042-05-01","Labour Day","TU",2042 +"2042-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2042 +"2042-07-15","Democracy and National Unity Day","TU",2042 +"2042-08-30","Victory Day","TU",2042 +"2042-09-15","Ramadan Feast* (*estimated)","TU",2042 +"2042-09-16","Ramadan Feast Holiday* (*estimated)","TU",2042 +"2042-09-17","Ramadan Feast Holiday* (*estimated)","TU",2042 +"2042-10-29","Republic Day","TU",2042 +"2042-11-23","Sacrifice Feast* (*estimated)","TU",2042 +"2042-11-24","Sacrifice Feast Holiday* (*estimated)","TU",2042 +"2042-11-25","Sacrifice Feast Holiday* (*estimated)","TU",2042 +"2042-11-26","Sacrifice Feast Holiday* (*estimated)","TU",2042 +"2043-01-01","New Year's Day","TU",2043 +"2043-04-23","National Sovereignty and Children's Day","TU",2043 +"2043-05-01","Labour Day","TU",2043 +"2043-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2043 +"2043-07-15","Democracy and National Unity Day","TU",2043 +"2043-08-30","Victory Day","TU",2043 +"2043-09-04","Ramadan Feast* (*estimated)","TU",2043 +"2043-09-05","Ramadan Feast Holiday* (*estimated)","TU",2043 +"2043-09-06","Ramadan Feast Holiday* (*estimated)","TU",2043 +"2043-10-29","Republic Day","TU",2043 +"2043-11-12","Sacrifice Feast* (*estimated)","TU",2043 +"2043-11-13","Sacrifice Feast Holiday* (*estimated)","TU",2043 +"2043-11-14","Sacrifice Feast Holiday* (*estimated)","TU",2043 +"2043-11-15","Sacrifice Feast Holiday* (*estimated)","TU",2043 +"2044-01-01","New Year's Day","TU",2044 +"2044-04-23","National Sovereignty and Children's Day","TU",2044 +"2044-05-01","Labour Day","TU",2044 +"2044-05-19","Commemoration of Ataturk, Youth and Sports Day","TU",2044 +"2044-07-15","Democracy and National Unity Day","TU",2044 +"2044-08-24","Ramadan Feast* (*estimated)","TU",2044 +"2044-08-25","Ramadan Feast Holiday* (*estimated)","TU",2044 +"2044-08-26","Ramadan Feast Holiday* (*estimated)","TU",2044 +"2044-08-30","Victory Day","TU",2044 +"2044-10-29","Republic Day","TU",2044 +"2044-10-31","Sacrifice Feast* (*estimated)","TU",2044 +"2044-11-01","Sacrifice Feast Holiday* (*estimated)","TU",2044 +"2044-11-02","Sacrifice Feast Holiday* (*estimated)","TU",2044 +"2044-11-03","Sacrifice Feast Holiday* (*estimated)","TU",2044 +"1995-01-01","Founding of the Republic of China (New Year's Day)","TW",1995 +"1995-01-30","Chinese New Year's Eve","TW",1995 +"1995-01-31","Spring Festival","TW",1995 +"1995-02-01","Spring Festival","TW",1995 +"1995-02-02","Spring Festival","TW",1995 +"1995-02-28","Peace Memorial Day","TW",1995 +"1995-04-04","Children's Day","TW",1995 +"1995-06-02","Dragon Boat Festival","TW",1995 +"1995-09-09","Mid-Autumn Festival","TW",1995 +"1995-10-10","National Day","TW",1995 +"1995-10-11","National Day","TW",1995 +"1996-01-01","Founding of the Republic of China (New Year's Day)","TW",1996 +"1996-02-18","Chinese New Year's Eve","TW",1996 +"1996-02-19","Spring Festival","TW",1996 +"1996-02-20","Spring Festival","TW",1996 +"1996-02-21","Spring Festival","TW",1996 +"1996-02-28","Peace Memorial Day","TW",1996 +"1996-04-04","Children's Day","TW",1996 +"1996-06-20","Dragon Boat Festival","TW",1996 +"1996-09-27","Mid-Autumn Festival","TW",1996 +"1996-10-10","National Day","TW",1996 +"1996-10-11","National Day","TW",1996 +"1997-01-01","Founding of the Republic of China (New Year's Day)","TW",1997 +"1997-02-06","Chinese New Year's Eve","TW",1997 +"1997-02-07","Spring Festival","TW",1997 +"1997-02-08","Spring Festival","TW",1997 +"1997-02-09","Spring Festival","TW",1997 +"1997-02-28","Peace Memorial Day","TW",1997 +"1997-04-04","Children's Day","TW",1997 +"1997-06-09","Dragon Boat Festival","TW",1997 +"1997-09-16","Mid-Autumn Festival","TW",1997 +"1997-10-10","National Day","TW",1997 +"1997-10-11","National Day","TW",1997 +"1998-01-01","Founding of the Republic of China (New Year's Day)","TW",1998 +"1998-01-27","Chinese New Year's Eve","TW",1998 +"1998-01-28","Spring Festival","TW",1998 +"1998-01-29","Spring Festival","TW",1998 +"1998-01-30","Spring Festival","TW",1998 +"1998-02-28","Peace Memorial Day","TW",1998 +"1998-04-04","Children's Day","TW",1998 +"1998-05-30","Dragon Boat Festival","TW",1998 +"1998-10-05","Mid-Autumn Festival","TW",1998 +"1998-10-10","National Day","TW",1998 +"1998-10-11","National Day","TW",1998 +"1999-01-01","Founding of the Republic of China (New Year's Day)","TW",1999 +"1999-02-15","Chinese New Year's Eve","TW",1999 +"1999-02-16","Spring Festival","TW",1999 +"1999-02-17","Spring Festival","TW",1999 +"1999-02-18","Spring Festival","TW",1999 +"1999-02-28","Peace Memorial Day","TW",1999 +"1999-04-04","Children's Day","TW",1999 +"1999-06-18","Dragon Boat Festival","TW",1999 +"1999-09-24","Mid-Autumn Festival","TW",1999 +"1999-10-10","National Day","TW",1999 +"1999-10-11","National Day","TW",1999 +"2000-01-01","Founding of the Republic of China (New Year's Day)","TW",2000 +"2000-02-04","Chinese New Year's Eve","TW",2000 +"2000-02-05","Spring Festival","TW",2000 +"2000-02-06","Spring Festival","TW",2000 +"2000-02-07","Spring Festival","TW",2000 +"2000-02-28","Peace Memorial Day","TW",2000 +"2000-04-04","Children's Day","TW",2000 +"2000-06-06","Dragon Boat Festival","TW",2000 +"2000-09-12","Mid-Autumn Festival","TW",2000 +"2000-10-10","National Day","TW",2000 +"2000-10-11","National Day","TW",2000 +"2001-01-01","Founding of the Republic of China (New Year's Day)","TW",2001 +"2001-01-23","Chinese New Year's Eve","TW",2001 +"2001-01-24","Spring Festival","TW",2001 +"2001-01-25","Spring Festival","TW",2001 +"2001-01-26","Spring Festival","TW",2001 +"2001-02-28","Peace Memorial Day","TW",2001 +"2001-04-04","Children's Day","TW",2001 +"2001-06-25","Dragon Boat Festival","TW",2001 +"2001-10-01","Mid-Autumn Festival","TW",2001 +"2001-10-10","National Day","TW",2001 +"2001-10-11","National Day","TW",2001 +"2002-01-01","Founding of the Republic of China (New Year's Day)","TW",2002 +"2002-02-11","Chinese New Year's Eve","TW",2002 +"2002-02-12","Spring Festival","TW",2002 +"2002-02-13","Spring Festival","TW",2002 +"2002-02-14","Spring Festival","TW",2002 +"2002-02-28","Peace Memorial Day","TW",2002 +"2002-04-04","Children's Day","TW",2002 +"2002-06-15","Dragon Boat Festival","TW",2002 +"2002-09-21","Mid-Autumn Festival","TW",2002 +"2002-10-10","National Day","TW",2002 +"2002-10-11","National Day","TW",2002 +"2003-01-01","Founding of the Republic of China (New Year's Day)","TW",2003 +"2003-01-31","Chinese New Year's Eve","TW",2003 +"2003-02-01","Spring Festival","TW",2003 +"2003-02-02","Spring Festival","TW",2003 +"2003-02-03","Spring Festival","TW",2003 +"2003-02-28","Peace Memorial Day","TW",2003 +"2003-04-04","Children's Day","TW",2003 +"2003-06-04","Dragon Boat Festival","TW",2003 +"2003-09-11","Mid-Autumn Festival","TW",2003 +"2003-10-10","National Day","TW",2003 +"2003-10-11","National Day","TW",2003 +"2004-01-01","Founding of the Republic of China (New Year's Day)","TW",2004 +"2004-01-21","Chinese New Year's Eve","TW",2004 +"2004-01-22","Spring Festival","TW",2004 +"2004-01-23","Spring Festival","TW",2004 +"2004-01-24","Spring Festival","TW",2004 +"2004-02-28","Peace Memorial Day","TW",2004 +"2004-04-04","Children's Day","TW",2004 +"2004-06-22","Dragon Boat Festival","TW",2004 +"2004-09-28","Mid-Autumn Festival","TW",2004 +"2004-10-10","National Day","TW",2004 +"2004-10-11","National Day","TW",2004 +"2005-01-01","Founding of the Republic of China (New Year's Day)","TW",2005 +"2005-02-08","Chinese New Year's Eve","TW",2005 +"2005-02-09","Spring Festival","TW",2005 +"2005-02-10","Spring Festival","TW",2005 +"2005-02-11","Spring Festival","TW",2005 +"2005-02-28","Peace Memorial Day","TW",2005 +"2005-04-04","Children's Day","TW",2005 +"2005-06-11","Dragon Boat Festival","TW",2005 +"2005-09-18","Mid-Autumn Festival","TW",2005 +"2005-10-10","National Day","TW",2005 +"2005-10-11","National Day","TW",2005 +"2006-01-01","Founding of the Republic of China (New Year's Day)","TW",2006 +"2006-01-28","Chinese New Year's Eve","TW",2006 +"2006-01-29","Spring Festival","TW",2006 +"2006-01-30","Spring Festival","TW",2006 +"2006-01-31","Spring Festival","TW",2006 +"2006-02-28","Peace Memorial Day","TW",2006 +"2006-04-04","Children's Day","TW",2006 +"2006-05-31","Dragon Boat Festival","TW",2006 +"2006-10-06","Mid-Autumn Festival","TW",2006 +"2006-10-10","National Day","TW",2006 +"2006-10-11","National Day","TW",2006 +"2007-01-01","Founding of the Republic of China (New Year's Day)","TW",2007 +"2007-02-17","Chinese New Year's Eve","TW",2007 +"2007-02-18","Spring Festival","TW",2007 +"2007-02-19","Spring Festival","TW",2007 +"2007-02-20","Spring Festival","TW",2007 +"2007-02-28","Peace Memorial Day","TW",2007 +"2007-04-04","Children's Day","TW",2007 +"2007-06-19","Dragon Boat Festival","TW",2007 +"2007-09-25","Mid-Autumn Festival","TW",2007 +"2007-10-10","National Day","TW",2007 +"2007-10-11","National Day","TW",2007 +"2008-01-01","Founding of the Republic of China (New Year's Day)","TW",2008 +"2008-02-06","Chinese New Year's Eve","TW",2008 +"2008-02-07","Spring Festival","TW",2008 +"2008-02-08","Spring Festival","TW",2008 +"2008-02-09","Spring Festival","TW",2008 +"2008-02-28","Peace Memorial Day","TW",2008 +"2008-04-04","Children's Day","TW",2008 +"2008-06-08","Dragon Boat Festival","TW",2008 +"2008-09-14","Mid-Autumn Festival","TW",2008 +"2008-10-10","National Day","TW",2008 +"2008-10-11","National Day","TW",2008 +"2009-01-01","Founding of the Republic of China (New Year's Day)","TW",2009 +"2009-01-25","Chinese New Year's Eve","TW",2009 +"2009-01-26","Spring Festival","TW",2009 +"2009-01-27","Spring Festival","TW",2009 +"2009-01-28","Spring Festival","TW",2009 +"2009-02-28","Peace Memorial Day","TW",2009 +"2009-04-04","Children's Day","TW",2009 +"2009-05-28","Dragon Boat Festival","TW",2009 +"2009-10-03","Mid-Autumn Festival","TW",2009 +"2009-10-10","National Day","TW",2009 +"2009-10-11","National Day","TW",2009 +"2010-01-01","Founding of the Republic of China (New Year's Day)","TW",2010 +"2010-02-13","Chinese New Year's Eve","TW",2010 +"2010-02-14","Spring Festival","TW",2010 +"2010-02-15","Spring Festival","TW",2010 +"2010-02-16","Spring Festival","TW",2010 +"2010-02-28","Peace Memorial Day","TW",2010 +"2010-04-04","Children's Day","TW",2010 +"2010-06-16","Dragon Boat Festival","TW",2010 +"2010-09-22","Mid-Autumn Festival","TW",2010 +"2010-10-10","National Day","TW",2010 +"2010-10-11","National Day","TW",2010 +"2011-01-01","Founding of the Republic of China (New Year's Day)","TW",2011 +"2011-02-02","Chinese New Year's Eve","TW",2011 +"2011-02-03","Spring Festival","TW",2011 +"2011-02-04","Spring Festival","TW",2011 +"2011-02-05","Spring Festival","TW",2011 +"2011-02-28","Peace Memorial Day","TW",2011 +"2011-04-04","Children's Day","TW",2011 +"2011-06-06","Dragon Boat Festival","TW",2011 +"2011-09-12","Mid-Autumn Festival","TW",2011 +"2011-10-10","National Day","TW",2011 +"2011-10-11","National Day","TW",2011 +"2012-01-01","Founding of the Republic of China (New Year's Day)","TW",2012 +"2012-01-22","Chinese New Year's Eve","TW",2012 +"2012-01-23","Spring Festival","TW",2012 +"2012-01-24","Spring Festival","TW",2012 +"2012-01-25","Spring Festival","TW",2012 +"2012-02-28","Peace Memorial Day","TW",2012 +"2012-04-04","Children's Day","TW",2012 +"2012-06-23","Dragon Boat Festival","TW",2012 +"2012-09-30","Mid-Autumn Festival","TW",2012 +"2012-10-10","National Day","TW",2012 +"2012-10-11","National Day","TW",2012 +"2013-01-01","Founding of the Republic of China (New Year's Day)","TW",2013 +"2013-02-09","Chinese New Year's Eve","TW",2013 +"2013-02-10","Spring Festival","TW",2013 +"2013-02-11","Spring Festival","TW",2013 +"2013-02-12","Spring Festival","TW",2013 +"2013-02-28","Peace Memorial Day","TW",2013 +"2013-04-04","Children's Day","TW",2013 +"2013-06-12","Dragon Boat Festival","TW",2013 +"2013-09-19","Mid-Autumn Festival","TW",2013 +"2013-10-10","National Day","TW",2013 +"2013-10-11","National Day","TW",2013 +"2014-01-01","Founding of the Republic of China (New Year's Day)","TW",2014 +"2014-01-30","Chinese New Year's Eve","TW",2014 +"2014-01-31","Spring Festival","TW",2014 +"2014-02-01","Spring Festival","TW",2014 +"2014-02-02","Spring Festival","TW",2014 +"2014-02-28","Peace Memorial Day","TW",2014 +"2014-04-04","Children's Day","TW",2014 +"2014-06-02","Dragon Boat Festival","TW",2014 +"2014-09-08","Mid-Autumn Festival","TW",2014 +"2014-10-10","National Day","TW",2014 +"2014-10-11","National Day","TW",2014 +"2015-01-01","Founding of the Republic of China (New Year's Day)","TW",2015 +"2015-02-18","Chinese New Year's Eve","TW",2015 +"2015-02-19","Spring Festival","TW",2015 +"2015-02-20","Spring Festival","TW",2015 +"2015-02-21","Spring Festival","TW",2015 +"2015-02-28","Peace Memorial Day","TW",2015 +"2015-04-04","Children's Day","TW",2015 +"2015-06-20","Dragon Boat Festival","TW",2015 +"2015-09-27","Mid-Autumn Festival","TW",2015 +"2015-10-10","National Day","TW",2015 +"2015-10-11","National Day","TW",2015 +"2016-01-01","Founding of the Republic of China (New Year's Day)","TW",2016 +"2016-02-07","Chinese New Year's Eve","TW",2016 +"2016-02-08","Spring Festival","TW",2016 +"2016-02-09","Spring Festival","TW",2016 +"2016-02-10","Spring Festival","TW",2016 +"2016-02-28","Peace Memorial Day","TW",2016 +"2016-04-04","Children's Day","TW",2016 +"2016-06-09","Dragon Boat Festival","TW",2016 +"2016-09-15","Mid-Autumn Festival","TW",2016 +"2016-10-10","National Day","TW",2016 +"2016-10-11","National Day","TW",2016 +"2017-01-01","Founding of the Republic of China (New Year's Day)","TW",2017 +"2017-01-27","Chinese New Year's Eve","TW",2017 +"2017-01-28","Spring Festival","TW",2017 +"2017-01-29","Spring Festival","TW",2017 +"2017-01-30","Spring Festival","TW",2017 +"2017-02-28","Peace Memorial Day","TW",2017 +"2017-04-04","Children's Day","TW",2017 +"2017-05-30","Dragon Boat Festival","TW",2017 +"2017-10-04","Mid-Autumn Festival","TW",2017 +"2017-10-10","National Day","TW",2017 +"2017-10-11","National Day","TW",2017 +"2018-01-01","Founding of the Republic of China (New Year's Day)","TW",2018 +"2018-02-15","Chinese New Year's Eve","TW",2018 +"2018-02-16","Spring Festival","TW",2018 +"2018-02-17","Spring Festival","TW",2018 +"2018-02-18","Spring Festival","TW",2018 +"2018-02-28","Peace Memorial Day","TW",2018 +"2018-04-04","Children's Day","TW",2018 +"2018-06-18","Dragon Boat Festival","TW",2018 +"2018-09-24","Mid-Autumn Festival","TW",2018 +"2018-10-10","National Day","TW",2018 +"2018-10-11","National Day","TW",2018 +"2019-01-01","Founding of the Republic of China (New Year's Day)","TW",2019 +"2019-02-04","Chinese New Year's Eve","TW",2019 +"2019-02-05","Spring Festival","TW",2019 +"2019-02-06","Spring Festival","TW",2019 +"2019-02-07","Spring Festival","TW",2019 +"2019-02-28","Peace Memorial Day","TW",2019 +"2019-04-04","Children's Day","TW",2019 +"2019-06-07","Dragon Boat Festival","TW",2019 +"2019-09-13","Mid-Autumn Festival","TW",2019 +"2019-10-10","National Day","TW",2019 +"2019-10-11","National Day","TW",2019 +"2020-01-01","Founding of the Republic of China (New Year's Day)","TW",2020 +"2020-01-24","Chinese New Year's Eve","TW",2020 +"2020-01-25","Spring Festival","TW",2020 +"2020-01-26","Spring Festival","TW",2020 +"2020-01-27","Spring Festival","TW",2020 +"2020-02-28","Peace Memorial Day","TW",2020 +"2020-04-04","Children's Day","TW",2020 +"2020-06-25","Dragon Boat Festival","TW",2020 +"2020-10-01","Mid-Autumn Festival","TW",2020 +"2020-10-10","National Day","TW",2020 +"2020-10-11","National Day","TW",2020 +"2021-01-01","Founding of the Republic of China (New Year's Day)","TW",2021 +"2021-02-11","Chinese New Year's Eve","TW",2021 +"2021-02-12","Spring Festival","TW",2021 +"2021-02-13","Spring Festival","TW",2021 +"2021-02-14","Spring Festival","TW",2021 +"2021-02-15","Spring Festival","TW",2021 +"2021-02-16","Spring Festival","TW",2021 +"2021-02-28","Peace Memorial Day","TW",2021 +"2021-04-04","Children's Day","TW",2021 +"2021-06-14","Dragon Boat Festival","TW",2021 +"2021-09-21","Mid-Autumn Festival","TW",2021 +"2021-10-10","National Day","TW",2021 +"2021-10-11","National Day","TW",2021 +"2022-01-01","Founding of the Republic of China (New Year's Day)","TW",2022 +"2022-01-31","Chinese New Year's Eve","TW",2022 +"2022-02-01","Spring Festival","TW",2022 +"2022-02-02","Spring Festival","TW",2022 +"2022-02-03","Spring Festival","TW",2022 +"2022-02-28","Peace Memorial Day","TW",2022 +"2022-04-04","Children's Day","TW",2022 +"2022-06-03","Dragon Boat Festival","TW",2022 +"2022-09-10","Mid-Autumn Festival","TW",2022 +"2022-10-10","National Day","TW",2022 +"2022-10-11","National Day","TW",2022 +"2023-01-01","Founding of the Republic of China (New Year's Day)","TW",2023 +"2023-01-21","Chinese New Year's Eve","TW",2023 +"2023-01-22","Spring Festival","TW",2023 +"2023-01-23","Spring Festival","TW",2023 +"2023-01-24","Spring Festival","TW",2023 +"2023-02-28","Peace Memorial Day","TW",2023 +"2023-04-04","Children's Day","TW",2023 +"2023-06-22","Dragon Boat Festival","TW",2023 +"2023-09-29","Mid-Autumn Festival","TW",2023 +"2023-10-10","National Day","TW",2023 +"2023-10-11","National Day","TW",2023 +"2024-01-01","Founding of the Republic of China (New Year's Day)","TW",2024 +"2024-02-09","Chinese New Year's Eve","TW",2024 +"2024-02-10","Spring Festival","TW",2024 +"2024-02-11","Spring Festival","TW",2024 +"2024-02-12","Spring Festival","TW",2024 +"2024-02-28","Peace Memorial Day","TW",2024 +"2024-04-04","Children's Day","TW",2024 +"2024-06-10","Dragon Boat Festival","TW",2024 +"2024-09-17","Mid-Autumn Festival","TW",2024 +"2024-10-10","National Day","TW",2024 +"2024-10-11","National Day","TW",2024 +"2025-01-01","Founding of the Republic of China (New Year's Day)","TW",2025 +"2025-01-28","Chinese New Year's Eve","TW",2025 +"2025-01-29","Spring Festival","TW",2025 +"2025-01-30","Spring Festival","TW",2025 +"2025-01-31","Spring Festival","TW",2025 +"2025-02-28","Peace Memorial Day","TW",2025 +"2025-04-04","Children's Day","TW",2025 +"2025-05-31","Dragon Boat Festival","TW",2025 +"2025-10-06","Mid-Autumn Festival","TW",2025 +"2025-10-10","National Day","TW",2025 +"2025-10-11","National Day","TW",2025 +"2026-01-01","Founding of the Republic of China (New Year's Day)","TW",2026 +"2026-02-16","Chinese New Year's Eve","TW",2026 +"2026-02-17","Spring Festival","TW",2026 +"2026-02-18","Spring Festival","TW",2026 +"2026-02-19","Spring Festival","TW",2026 +"2026-02-28","Peace Memorial Day","TW",2026 +"2026-04-04","Children's Day","TW",2026 +"2026-06-19","Dragon Boat Festival","TW",2026 +"2026-09-25","Mid-Autumn Festival","TW",2026 +"2026-10-10","National Day","TW",2026 +"2026-10-11","National Day","TW",2026 +"2027-01-01","Founding of the Republic of China (New Year's Day)","TW",2027 +"2027-02-05","Chinese New Year's Eve","TW",2027 +"2027-02-06","Spring Festival","TW",2027 +"2027-02-07","Spring Festival","TW",2027 +"2027-02-08","Spring Festival","TW",2027 +"2027-02-28","Peace Memorial Day","TW",2027 +"2027-04-04","Children's Day","TW",2027 +"2027-06-09","Dragon Boat Festival","TW",2027 +"2027-09-15","Mid-Autumn Festival","TW",2027 +"2027-10-10","National Day","TW",2027 +"2027-10-11","National Day","TW",2027 +"2028-01-01","Founding of the Republic of China (New Year's Day)","TW",2028 +"2028-01-25","Chinese New Year's Eve","TW",2028 +"2028-01-26","Spring Festival","TW",2028 +"2028-01-27","Spring Festival","TW",2028 +"2028-01-28","Spring Festival","TW",2028 +"2028-02-28","Peace Memorial Day","TW",2028 +"2028-04-04","Children's Day","TW",2028 +"2028-05-28","Dragon Boat Festival","TW",2028 +"2028-10-03","Mid-Autumn Festival","TW",2028 +"2028-10-10","National Day","TW",2028 +"2028-10-11","National Day","TW",2028 +"2029-01-01","Founding of the Republic of China (New Year's Day)","TW",2029 +"2029-02-12","Chinese New Year's Eve","TW",2029 +"2029-02-13","Spring Festival","TW",2029 +"2029-02-14","Spring Festival","TW",2029 +"2029-02-15","Spring Festival","TW",2029 +"2029-02-28","Peace Memorial Day","TW",2029 +"2029-04-04","Children's Day","TW",2029 +"2029-06-16","Dragon Boat Festival","TW",2029 +"2029-09-22","Mid-Autumn Festival","TW",2029 +"2029-10-10","National Day","TW",2029 +"2029-10-11","National Day","TW",2029 +"2030-01-01","Founding of the Republic of China (New Year's Day)","TW",2030 +"2030-02-02","Chinese New Year's Eve","TW",2030 +"2030-02-03","Spring Festival","TW",2030 +"2030-02-04","Spring Festival","TW",2030 +"2030-02-05","Spring Festival","TW",2030 +"2030-02-28","Peace Memorial Day","TW",2030 +"2030-04-04","Children's Day","TW",2030 +"2030-06-05","Dragon Boat Festival","TW",2030 +"2030-09-12","Mid-Autumn Festival","TW",2030 +"2030-10-10","National Day","TW",2030 +"2030-10-11","National Day","TW",2030 +"2031-01-01","Founding of the Republic of China (New Year's Day)","TW",2031 +"2031-01-22","Chinese New Year's Eve","TW",2031 +"2031-01-23","Spring Festival","TW",2031 +"2031-01-24","Spring Festival","TW",2031 +"2031-01-25","Spring Festival","TW",2031 +"2031-02-28","Peace Memorial Day","TW",2031 +"2031-04-04","Children's Day","TW",2031 +"2031-06-24","Dragon Boat Festival","TW",2031 +"2031-10-01","Mid-Autumn Festival","TW",2031 +"2031-10-10","National Day","TW",2031 +"2031-10-11","National Day","TW",2031 +"2032-01-01","Founding of the Republic of China (New Year's Day)","TW",2032 +"2032-02-10","Chinese New Year's Eve","TW",2032 +"2032-02-11","Spring Festival","TW",2032 +"2032-02-12","Spring Festival","TW",2032 +"2032-02-13","Spring Festival","TW",2032 +"2032-02-28","Peace Memorial Day","TW",2032 +"2032-04-04","Children's Day","TW",2032 +"2032-06-12","Dragon Boat Festival","TW",2032 +"2032-09-19","Mid-Autumn Festival","TW",2032 +"2032-10-10","National Day","TW",2032 +"2032-10-11","National Day","TW",2032 +"2033-01-01","Founding of the Republic of China (New Year's Day)","TW",2033 +"2033-01-30","Chinese New Year's Eve","TW",2033 +"2033-01-31","Spring Festival","TW",2033 +"2033-02-01","Spring Festival","TW",2033 +"2033-02-02","Spring Festival","TW",2033 +"2033-02-28","Peace Memorial Day","TW",2033 +"2033-04-04","Children's Day","TW",2033 +"2033-06-01","Dragon Boat Festival","TW",2033 +"2033-09-08","Mid-Autumn Festival","TW",2033 +"2033-10-10","National Day","TW",2033 +"2033-10-11","National Day","TW",2033 +"2034-01-01","Founding of the Republic of China (New Year's Day)","TW",2034 +"2034-02-18","Chinese New Year's Eve","TW",2034 +"2034-02-19","Spring Festival","TW",2034 +"2034-02-20","Spring Festival","TW",2034 +"2034-02-21","Spring Festival","TW",2034 +"2034-02-28","Peace Memorial Day","TW",2034 +"2034-04-04","Children's Day","TW",2034 +"2034-06-20","Dragon Boat Festival","TW",2034 +"2034-09-27","Mid-Autumn Festival","TW",2034 +"2034-10-10","National Day","TW",2034 +"2034-10-11","National Day","TW",2034 +"2035-01-01","Founding of the Republic of China (New Year's Day)","TW",2035 +"2035-02-07","Chinese New Year's Eve","TW",2035 +"2035-02-08","Spring Festival","TW",2035 +"2035-02-09","Spring Festival","TW",2035 +"2035-02-10","Spring Festival","TW",2035 +"2035-02-28","Peace Memorial Day","TW",2035 +"2035-04-04","Children's Day","TW",2035 +"2035-06-10","Dragon Boat Festival","TW",2035 +"2035-09-16","Mid-Autumn Festival","TW",2035 +"2035-10-10","National Day","TW",2035 +"2035-10-11","National Day","TW",2035 +"2036-01-01","Founding of the Republic of China (New Year's Day)","TW",2036 +"2036-01-27","Chinese New Year's Eve","TW",2036 +"2036-01-28","Spring Festival","TW",2036 +"2036-01-29","Spring Festival","TW",2036 +"2036-01-30","Spring Festival","TW",2036 +"2036-02-28","Peace Memorial Day","TW",2036 +"2036-04-04","Children's Day","TW",2036 +"2036-05-30","Dragon Boat Festival","TW",2036 +"2036-10-04","Mid-Autumn Festival","TW",2036 +"2036-10-10","National Day","TW",2036 +"2036-10-11","National Day","TW",2036 +"2037-01-01","Founding of the Republic of China (New Year's Day)","TW",2037 +"2037-02-14","Chinese New Year's Eve","TW",2037 +"2037-02-15","Spring Festival","TW",2037 +"2037-02-16","Spring Festival","TW",2037 +"2037-02-17","Spring Festival","TW",2037 +"2037-02-28","Peace Memorial Day","TW",2037 +"2037-04-04","Children's Day","TW",2037 +"2037-06-18","Dragon Boat Festival","TW",2037 +"2037-09-24","Mid-Autumn Festival","TW",2037 +"2037-10-10","National Day","TW",2037 +"2037-10-11","National Day","TW",2037 +"2038-01-01","Founding of the Republic of China (New Year's Day)","TW",2038 +"2038-02-03","Chinese New Year's Eve","TW",2038 +"2038-02-04","Spring Festival","TW",2038 +"2038-02-05","Spring Festival","TW",2038 +"2038-02-06","Spring Festival","TW",2038 +"2038-02-28","Peace Memorial Day","TW",2038 +"2038-04-04","Children's Day","TW",2038 +"2038-06-07","Dragon Boat Festival","TW",2038 +"2038-09-13","Mid-Autumn Festival","TW",2038 +"2038-10-10","National Day","TW",2038 +"2038-10-11","National Day","TW",2038 +"2039-01-01","Founding of the Republic of China (New Year's Day)","TW",2039 +"2039-01-23","Chinese New Year's Eve","TW",2039 +"2039-01-24","Spring Festival","TW",2039 +"2039-01-25","Spring Festival","TW",2039 +"2039-01-26","Spring Festival","TW",2039 +"2039-02-28","Peace Memorial Day","TW",2039 +"2039-04-04","Children's Day","TW",2039 +"2039-05-27","Dragon Boat Festival","TW",2039 +"2039-10-02","Mid-Autumn Festival","TW",2039 +"2039-10-10","National Day","TW",2039 +"2039-10-11","National Day","TW",2039 +"2040-01-01","Founding of the Republic of China (New Year's Day)","TW",2040 +"2040-02-11","Chinese New Year's Eve","TW",2040 +"2040-02-12","Spring Festival","TW",2040 +"2040-02-13","Spring Festival","TW",2040 +"2040-02-14","Spring Festival","TW",2040 +"2040-02-28","Peace Memorial Day","TW",2040 +"2040-04-04","Children's Day","TW",2040 +"2040-06-14","Dragon Boat Festival","TW",2040 +"2040-09-20","Mid-Autumn Festival","TW",2040 +"2040-10-10","National Day","TW",2040 +"2040-10-11","National Day","TW",2040 +"2041-01-01","Founding of the Republic of China (New Year's Day)","TW",2041 +"2041-01-31","Chinese New Year's Eve","TW",2041 +"2041-02-01","Spring Festival","TW",2041 +"2041-02-02","Spring Festival","TW",2041 +"2041-02-03","Spring Festival","TW",2041 +"2041-02-28","Peace Memorial Day","TW",2041 +"2041-04-04","Children's Day","TW",2041 +"2041-06-03","Dragon Boat Festival","TW",2041 +"2041-09-10","Mid-Autumn Festival","TW",2041 +"2041-10-10","National Day","TW",2041 +"2041-10-11","National Day","TW",2041 +"2042-01-01","Founding of the Republic of China (New Year's Day)","TW",2042 +"2042-01-21","Chinese New Year's Eve","TW",2042 +"2042-01-22","Spring Festival","TW",2042 +"2042-01-23","Spring Festival","TW",2042 +"2042-01-24","Spring Festival","TW",2042 +"2042-02-28","Peace Memorial Day","TW",2042 +"2042-04-04","Children's Day","TW",2042 +"2042-06-22","Dragon Boat Festival","TW",2042 +"2042-09-28","Mid-Autumn Festival","TW",2042 +"2042-10-10","National Day","TW",2042 +"2042-10-11","National Day","TW",2042 +"2043-01-01","Founding of the Republic of China (New Year's Day)","TW",2043 +"2043-02-09","Chinese New Year's Eve","TW",2043 +"2043-02-10","Spring Festival","TW",2043 +"2043-02-11","Spring Festival","TW",2043 +"2043-02-12","Spring Festival","TW",2043 +"2043-02-28","Peace Memorial Day","TW",2043 +"2043-04-04","Children's Day","TW",2043 +"2043-06-11","Dragon Boat Festival","TW",2043 +"2043-09-17","Mid-Autumn Festival","TW",2043 +"2043-10-10","National Day","TW",2043 +"2043-10-11","National Day","TW",2043 +"2044-01-01","Founding of the Republic of China (New Year's Day)","TW",2044 +"2044-01-29","Chinese New Year's Eve","TW",2044 +"2044-01-30","Spring Festival","TW",2044 +"2044-01-31","Spring Festival","TW",2044 +"2044-02-01","Spring Festival","TW",2044 +"2044-02-28","Peace Memorial Day","TW",2044 +"2044-04-04","Children's Day","TW",2044 +"2044-05-31","Dragon Boat Festival","TW",2044 +"2044-10-05","Mid-Autumn Festival","TW",2044 +"2044-10-10","National Day","TW",2044 +"2044-10-11","National Day","TW",2044 +"1995-01-01","New Year's Day","UA",1995 +"1995-01-07","Christmas (Julian calendar)","UA",1995 +"1995-03-08","International Women's Day","UA",1995 +"1995-04-23","Easter Sunday (Pascha)","UA",1995 +"1995-04-24","Easter Sunday (Pascha) (Observed)","UA",1995 +"1995-05-01","International Workers' Solidarity Day","UA",1995 +"1995-05-02","International Workers' Solidarity Day","UA",1995 +"1995-05-09","Victory Day","UA",1995 +"1995-06-11","Holy Trinity Day","UA",1995 +"1995-06-12","Holy Trinity Day (Observed)","UA",1995 +"1995-08-24","Independence Day","UA",1995 +"1995-11-07","Anniversary of the Great October Socialist Revolution","UA",1995 +"1995-11-08","Anniversary of the Great October Socialist Revolution","UA",1995 +"1996-01-01","New Year's Day","UA",1996 +"1996-01-07","Christmas (Julian calendar)","UA",1996 +"1996-01-08","Christmas (Julian calendar) (Observed)","UA",1996 +"1996-03-08","International Women's Day","UA",1996 +"1996-04-14","Easter Sunday (Pascha)","UA",1996 +"1996-04-15","Easter Sunday (Pascha) (Observed)","UA",1996 +"1996-05-01","International Workers' Solidarity Day","UA",1996 +"1996-05-02","International Workers' Solidarity Day","UA",1996 +"1996-05-09","Victory Day","UA",1996 +"1996-06-02","Holy Trinity Day","UA",1996 +"1996-06-03","Holy Trinity Day (Observed)","UA",1996 +"1996-08-24","Independence Day","UA",1996 +"1996-08-26","Independence Day (Observed)","UA",1996 +"1996-11-07","Anniversary of the Great October Socialist Revolution","UA",1996 +"1996-11-08","Anniversary of the Great October Socialist Revolution","UA",1996 +"1997-01-01","New Year's Day","UA",1997 +"1997-01-07","Christmas (Julian calendar)","UA",1997 +"1997-03-08","International Women's Day","UA",1997 +"1997-03-10","International Women's Day (Observed)","UA",1997 +"1997-04-27","Easter Sunday (Pascha)","UA",1997 +"1997-04-28","Easter Sunday (Pascha) (Observed)","UA",1997 +"1997-05-01","International Workers' Solidarity Day","UA",1997 +"1997-05-02","International Workers' Solidarity Day","UA",1997 +"1997-05-09","Victory Day","UA",1997 +"1997-06-15","Holy Trinity Day","UA",1997 +"1997-06-16","Holy Trinity Day (Observed)","UA",1997 +"1997-06-28","Day of the Constitution of Ukraine","UA",1997 +"1997-06-30","Day of the Constitution of Ukraine (Observed)","UA",1997 +"1997-08-24","Independence Day","UA",1997 +"1997-08-25","Independence Day (Observed)","UA",1997 +"1997-11-07","Anniversary of the Great October Socialist Revolution","UA",1997 +"1997-11-08","Anniversary of the Great October Socialist Revolution","UA",1997 +"1997-11-10","Anniversary of the Great October Socialist Revolution (Observed)","UA",1997 +"1998-01-01","New Year's Day","UA",1998 +"1998-01-07","Christmas (Julian calendar)","UA",1998 +"1998-03-08","International Women's Day","UA",1998 +"1998-04-19","Easter Sunday (Pascha)","UA",1998 +"1998-05-01","International Workers' Solidarity Day","UA",1998 +"1998-05-02","International Workers' Solidarity Day","UA",1998 +"1998-05-09","Victory Day","UA",1998 +"1998-06-07","Holy Trinity Day","UA",1998 +"1998-06-28","Day of the Constitution of Ukraine","UA",1998 +"1998-08-24","Independence Day","UA",1998 +"1998-11-07","Anniversary of the Great October Socialist Revolution","UA",1998 +"1998-11-08","Anniversary of the Great October Socialist Revolution","UA",1998 +"1999-01-01","New Year's Day","UA",1999 +"1999-01-07","Christmas (Julian calendar)","UA",1999 +"1999-03-08","International Women's Day","UA",1999 +"1999-04-11","Easter Sunday (Pascha)","UA",1999 +"1999-05-01","International Workers' Solidarity Day","UA",1999 +"1999-05-02","International Workers' Solidarity Day","UA",1999 +"1999-05-03","International Workers' Solidarity Day (Observed)","UA",1999 +"1999-05-04","International Workers' Solidarity Day (Observed)","UA",1999 +"1999-05-09","Victory Day","UA",1999 +"1999-05-10","Victory Day (Observed)","UA",1999 +"1999-05-30","Holy Trinity Day","UA",1999 +"1999-05-31","Holy Trinity Day (Observed)","UA",1999 +"1999-06-28","Day of the Constitution of Ukraine","UA",1999 +"1999-08-24","Independence Day","UA",1999 +"1999-11-07","Anniversary of the Great October Socialist Revolution","UA",1999 +"1999-11-08","Anniversary of the Great October Socialist Revolution","UA",1999 +"1999-11-09","Anniversary of the Great October Socialist Revolution (Observed)","UA",1999 +"2000-01-01","New Year's Day","UA",2000 +"2000-01-03","New Year's Day (Observed)","UA",2000 +"2000-01-07","Christmas (Julian calendar)","UA",2000 +"2000-03-08","International Women's Day","UA",2000 +"2000-04-30","Easter Sunday (Pascha)","UA",2000 +"2000-05-01","International Workers' Solidarity Day","UA",2000 +"2000-05-02","International Workers' Solidarity Day","UA",2000 +"2000-05-03","Easter Sunday (Pascha) (Observed)","UA",2000 +"2000-05-09","Victory Day","UA",2000 +"2000-06-18","Holy Trinity Day","UA",2000 +"2000-06-19","Holy Trinity Day (Observed)","UA",2000 +"2000-06-28","Day of the Constitution of Ukraine","UA",2000 +"2000-08-24","Independence Day","UA",2000 +"2001-01-01","New Year's Day","UA",2001 +"2001-01-07","Christmas (Julian calendar)","UA",2001 +"2001-01-08","Christmas (Julian calendar) (Observed)","UA",2001 +"2001-03-08","International Women's Day","UA",2001 +"2001-04-15","Easter Sunday (Pascha)","UA",2001 +"2001-04-16","Easter Sunday (Pascha) (Observed)","UA",2001 +"2001-05-01","International Workers' Solidarity Day","UA",2001 +"2001-05-02","International Workers' Solidarity Day","UA",2001 +"2001-05-09","Victory Day","UA",2001 +"2001-06-03","Holy Trinity Day","UA",2001 +"2001-06-04","Holy Trinity Day (Observed)","UA",2001 +"2001-06-28","Day of the Constitution of Ukraine","UA",2001 +"2001-08-24","Independence Day","UA",2001 +"2002-01-01","New Year's Day","UA",2002 +"2002-01-07","Christmas (Julian calendar)","UA",2002 +"2002-03-08","International Women's Day","UA",2002 +"2002-05-01","International Workers' Solidarity Day","UA",2002 +"2002-05-02","International Workers' Solidarity Day","UA",2002 +"2002-05-05","Easter Sunday (Pascha)","UA",2002 +"2002-05-06","Easter Sunday (Pascha) (Observed)","UA",2002 +"2002-05-09","Victory Day","UA",2002 +"2002-06-23","Holy Trinity Day","UA",2002 +"2002-06-24","Holy Trinity Day (Observed)","UA",2002 +"2002-06-28","Day of the Constitution of Ukraine","UA",2002 +"2002-08-24","Independence Day","UA",2002 +"2002-08-26","Independence Day (Observed)","UA",2002 +"2003-01-01","New Year's Day","UA",2003 +"2003-01-07","Christmas (Julian calendar)","UA",2003 +"2003-03-08","International Women's Day","UA",2003 +"2003-03-10","International Women's Day (Observed)","UA",2003 +"2003-04-27","Easter Sunday (Pascha)","UA",2003 +"2003-04-28","Easter Sunday (Pascha) (Observed)","UA",2003 +"2003-05-01","International Workers' Solidarity Day","UA",2003 +"2003-05-02","International Workers' Solidarity Day","UA",2003 +"2003-05-09","Victory Day","UA",2003 +"2003-06-15","Holy Trinity Day","UA",2003 +"2003-06-16","Holy Trinity Day (Observed)","UA",2003 +"2003-06-28","Day of the Constitution of Ukraine","UA",2003 +"2003-06-30","Day of the Constitution of Ukraine (Observed)","UA",2003 +"2003-08-24","Independence Day","UA",2003 +"2003-08-25","Independence Day (Observed)","UA",2003 +"2004-01-01","New Year's Day","UA",2004 +"2004-01-07","Christmas (Julian calendar)","UA",2004 +"2004-03-08","International Women's Day","UA",2004 +"2004-04-11","Easter Sunday (Pascha)","UA",2004 +"2004-04-12","Easter Sunday (Pascha) (Observed)","UA",2004 +"2004-05-01","International Workers' Solidarity Day","UA",2004 +"2004-05-02","International Workers' Solidarity Day","UA",2004 +"2004-05-03","International Workers' Solidarity Day (Observed)","UA",2004 +"2004-05-04","International Workers' Solidarity Day (Observed)","UA",2004 +"2004-05-09","Victory Day","UA",2004 +"2004-05-10","Victory Day (Observed)","UA",2004 +"2004-05-30","Holy Trinity Day","UA",2004 +"2004-05-31","Holy Trinity Day (Observed)","UA",2004 +"2004-06-28","Day of the Constitution of Ukraine","UA",2004 +"2004-08-24","Independence Day","UA",2004 +"2005-01-01","New Year's Day","UA",2005 +"2005-01-03","New Year's Day (Observed)","UA",2005 +"2005-01-07","Christmas (Julian calendar)","UA",2005 +"2005-03-08","International Women's Day","UA",2005 +"2005-05-01","Easter Sunday (Pascha)","UA",2005 +"2005-05-01","International Workers' Solidarity Day","UA",2005 +"2005-05-02","International Workers' Solidarity Day","UA",2005 +"2005-05-03","Easter Sunday (Pascha)","UA",2005 +"2005-05-03","International Workers' Solidarity Day (Observed)","UA",2005 +"2005-05-09","Victory Day","UA",2005 +"2005-06-19","Holy Trinity Day","UA",2005 +"2005-06-20","Holy Trinity Day (Observed)","UA",2005 +"2005-06-28","Day of the Constitution of Ukraine","UA",2005 +"2005-08-24","Independence Day","UA",2005 +"2006-01-01","New Year's Day","UA",2006 +"2006-01-02","New Year's Day (Observed)","UA",2006 +"2006-01-07","Christmas (Julian calendar)","UA",2006 +"2006-01-09","Christmas (Julian calendar) (Observed)","UA",2006 +"2006-03-08","International Women's Day","UA",2006 +"2006-04-23","Easter Sunday (Pascha)","UA",2006 +"2006-04-24","Easter Sunday (Pascha) (Observed)","UA",2006 +"2006-05-01","International Workers' Solidarity Day","UA",2006 +"2006-05-02","International Workers' Solidarity Day","UA",2006 +"2006-05-09","Victory Day","UA",2006 +"2006-06-11","Holy Trinity Day","UA",2006 +"2006-06-12","Holy Trinity Day (Observed)","UA",2006 +"2006-06-28","Day of the Constitution of Ukraine","UA",2006 +"2006-08-24","Independence Day","UA",2006 +"2007-01-01","New Year's Day","UA",2007 +"2007-01-07","Christmas (Julian calendar)","UA",2007 +"2007-01-08","Christmas (Julian calendar) (Observed)","UA",2007 +"2007-03-08","International Women's Day","UA",2007 +"2007-04-08","Easter Sunday (Pascha)","UA",2007 +"2007-04-09","Easter Sunday (Pascha) (Observed)","UA",2007 +"2007-05-01","International Workers' Solidarity Day","UA",2007 +"2007-05-02","International Workers' Solidarity Day","UA",2007 +"2007-05-09","Victory Day","UA",2007 +"2007-05-27","Holy Trinity Day","UA",2007 +"2007-05-28","Holy Trinity Day (Observed)","UA",2007 +"2007-06-28","Day of the Constitution of Ukraine","UA",2007 +"2007-08-24","Independence Day","UA",2007 +"2008-01-01","New Year's Day","UA",2008 +"2008-01-07","Christmas (Julian calendar)","UA",2008 +"2008-03-08","International Women's Day","UA",2008 +"2008-03-10","International Women's Day (Observed)","UA",2008 +"2008-04-27","Easter Sunday (Pascha)","UA",2008 +"2008-04-28","Easter Sunday (Pascha) (Observed)","UA",2008 +"2008-05-01","International Workers' Solidarity Day","UA",2008 +"2008-05-02","International Workers' Solidarity Day","UA",2008 +"2008-05-09","Victory Day","UA",2008 +"2008-06-15","Holy Trinity Day","UA",2008 +"2008-06-16","Holy Trinity Day (Observed)","UA",2008 +"2008-06-28","Day of the Constitution of Ukraine","UA",2008 +"2008-06-30","Day of the Constitution of Ukraine (Observed)","UA",2008 +"2008-08-24","Independence Day","UA",2008 +"2008-08-25","Independence Day (Observed)","UA",2008 +"2009-01-01","New Year's Day","UA",2009 +"2009-01-07","Christmas (Julian calendar)","UA",2009 +"2009-03-08","International Women's Day","UA",2009 +"2009-03-09","International Women's Day (Observed)","UA",2009 +"2009-04-19","Easter Sunday (Pascha)","UA",2009 +"2009-04-20","Easter Sunday (Pascha) (Observed)","UA",2009 +"2009-05-01","International Workers' Solidarity Day","UA",2009 +"2009-05-02","International Workers' Solidarity Day","UA",2009 +"2009-05-04","International Workers' Solidarity Day (Observed)","UA",2009 +"2009-05-09","Victory Day","UA",2009 +"2009-05-11","Victory Day (Observed)","UA",2009 +"2009-06-07","Holy Trinity Day","UA",2009 +"2009-06-08","Holy Trinity Day (Observed)","UA",2009 +"2009-06-28","Day of the Constitution of Ukraine","UA",2009 +"2009-06-29","Day of the Constitution of Ukraine (Observed)","UA",2009 +"2009-08-24","Independence Day","UA",2009 +"2010-01-01","New Year's Day","UA",2010 +"2010-01-07","Christmas (Julian calendar)","UA",2010 +"2010-03-08","International Women's Day","UA",2010 +"2010-04-04","Easter Sunday (Pascha)","UA",2010 +"2010-04-05","Easter Sunday (Pascha) (Observed)","UA",2010 +"2010-05-01","International Workers' Solidarity Day","UA",2010 +"2010-05-02","International Workers' Solidarity Day","UA",2010 +"2010-05-03","International Workers' Solidarity Day (Observed)","UA",2010 +"2010-05-04","International Workers' Solidarity Day (Observed)","UA",2010 +"2010-05-09","Victory Day","UA",2010 +"2010-05-10","Victory Day (Observed)","UA",2010 +"2010-05-23","Holy Trinity Day","UA",2010 +"2010-05-24","Holy Trinity Day (Observed)","UA",2010 +"2010-06-28","Day of the Constitution of Ukraine","UA",2010 +"2010-08-24","Independence Day","UA",2010 +"2011-01-01","New Year's Day","UA",2011 +"2011-01-03","New Year's Day (Observed)","UA",2011 +"2011-01-07","Christmas (Julian calendar)","UA",2011 +"2011-03-08","International Women's Day","UA",2011 +"2011-04-24","Easter Sunday (Pascha)","UA",2011 +"2011-04-25","Easter Sunday (Pascha) (Observed)","UA",2011 +"2011-05-01","International Workers' Solidarity Day","UA",2011 +"2011-05-02","International Workers' Solidarity Day","UA",2011 +"2011-05-03","International Workers' Solidarity Day (Observed)","UA",2011 +"2011-05-09","Victory Day","UA",2011 +"2011-06-12","Holy Trinity Day","UA",2011 +"2011-06-13","Holy Trinity Day (Observed)","UA",2011 +"2011-06-28","Day of the Constitution of Ukraine","UA",2011 +"2011-08-24","Independence Day","UA",2011 +"2012-01-01","New Year's Day","UA",2012 +"2012-01-02","New Year's Day (Observed)","UA",2012 +"2012-01-07","Christmas (Julian calendar)","UA",2012 +"2012-01-09","Christmas (Julian calendar) (Observed)","UA",2012 +"2012-03-08","International Women's Day","UA",2012 +"2012-04-15","Easter Sunday (Pascha)","UA",2012 +"2012-04-16","Easter Sunday (Pascha) (Observed)","UA",2012 +"2012-05-01","International Workers' Solidarity Day","UA",2012 +"2012-05-02","International Workers' Solidarity Day","UA",2012 +"2012-05-09","Victory Day","UA",2012 +"2012-06-03","Holy Trinity Day","UA",2012 +"2012-06-04","Holy Trinity Day (Observed)","UA",2012 +"2012-06-28","Day of the Constitution of Ukraine","UA",2012 +"2012-08-24","Independence Day","UA",2012 +"2013-01-01","New Year's Day","UA",2013 +"2013-01-07","Christmas (Julian calendar)","UA",2013 +"2013-03-08","International Women's Day","UA",2013 +"2013-05-01","International Workers' Solidarity Day","UA",2013 +"2013-05-02","International Workers' Solidarity Day","UA",2013 +"2013-05-05","Easter Sunday (Pascha)","UA",2013 +"2013-05-06","Easter Sunday (Pascha) (Observed)","UA",2013 +"2013-05-09","Victory Day","UA",2013 +"2013-06-23","Holy Trinity Day","UA",2013 +"2013-06-24","Holy Trinity Day (Observed)","UA",2013 +"2013-06-28","Day of the Constitution of Ukraine","UA",2013 +"2013-08-24","Independence Day","UA",2013 +"2013-08-26","Independence Day (Observed)","UA",2013 +"2014-01-01","New Year's Day","UA",2014 +"2014-01-07","Christmas (Julian calendar)","UA",2014 +"2014-03-08","International Women's Day","UA",2014 +"2014-03-10","International Women's Day (Observed)","UA",2014 +"2014-04-20","Easter Sunday (Pascha)","UA",2014 +"2014-04-21","Easter Sunday (Pascha) (Observed)","UA",2014 +"2014-05-01","International Workers' Solidarity Day","UA",2014 +"2014-05-02","International Workers' Solidarity Day","UA",2014 +"2014-05-09","Victory Day","UA",2014 +"2014-06-08","Holy Trinity Day","UA",2014 +"2014-06-09","Holy Trinity Day (Observed)","UA",2014 +"2014-06-28","Day of the Constitution of Ukraine","UA",2014 +"2014-06-30","Day of the Constitution of Ukraine (Observed)","UA",2014 +"2014-08-24","Independence Day","UA",2014 +"2014-08-25","Independence Day (Observed)","UA",2014 +"2015-01-01","New Year's Day","UA",2015 +"2015-01-07","Christmas (Julian calendar)","UA",2015 +"2015-03-08","International Women's Day","UA",2015 +"2015-03-09","International Women's Day (Observed)","UA",2015 +"2015-04-12","Easter Sunday (Pascha)","UA",2015 +"2015-04-13","Easter Sunday (Pascha) (Observed)","UA",2015 +"2015-05-01","International Workers' Solidarity Day","UA",2015 +"2015-05-02","International Workers' Solidarity Day","UA",2015 +"2015-05-04","International Workers' Solidarity Day (Observed)","UA",2015 +"2015-05-09","Victory Day","UA",2015 +"2015-05-11","Victory Day (Observed)","UA",2015 +"2015-05-31","Holy Trinity Day","UA",2015 +"2015-06-01","Holy Trinity Day (Observed)","UA",2015 +"2015-06-28","Day of the Constitution of Ukraine","UA",2015 +"2015-06-29","Day of the Constitution of Ukraine (Observed)","UA",2015 +"2015-08-24","Independence Day","UA",2015 +"2015-10-14","Defender of Ukraine Day","UA",2015 +"2016-01-01","New Year's Day","UA",2016 +"2016-01-07","Christmas (Julian calendar)","UA",2016 +"2016-03-08","International Women's Day","UA",2016 +"2016-05-01","Easter Sunday (Pascha)","UA",2016 +"2016-05-01","International Workers' Solidarity Day","UA",2016 +"2016-05-02","International Workers' Solidarity Day","UA",2016 +"2016-05-03","Easter Sunday (Pascha)","UA",2016 +"2016-05-03","International Workers' Solidarity Day (Observed)","UA",2016 +"2016-05-09","Day of Victory over Nazism in World War II (Victory Day)","UA",2016 +"2016-06-19","Holy Trinity Day","UA",2016 +"2016-06-20","Holy Trinity Day (Observed)","UA",2016 +"2016-06-28","Day of the Constitution of Ukraine","UA",2016 +"2016-08-24","Independence Day","UA",2016 +"2016-10-14","Defender of Ukraine Day","UA",2016 +"2017-01-01","New Year's Day","UA",2017 +"2017-01-02","New Year's Day (Observed)","UA",2017 +"2017-01-07","Christmas (Julian calendar)","UA",2017 +"2017-01-09","Christmas (Julian calendar) (Observed)","UA",2017 +"2017-03-08","International Women's Day","UA",2017 +"2017-04-16","Easter Sunday (Pascha)","UA",2017 +"2017-04-17","Easter Sunday (Pascha) (Observed)","UA",2017 +"2017-05-01","International Workers' Solidarity Day","UA",2017 +"2017-05-02","International Workers' Solidarity Day","UA",2017 +"2017-05-09","Day of Victory over Nazism in World War II (Victory Day)","UA",2017 +"2017-06-04","Holy Trinity Day","UA",2017 +"2017-06-05","Holy Trinity Day (Observed)","UA",2017 +"2017-06-28","Day of the Constitution of Ukraine","UA",2017 +"2017-08-24","Independence Day","UA",2017 +"2017-10-14","Defender of Ukraine Day","UA",2017 +"2017-10-16","Defender of Ukraine Day (Observed)","UA",2017 +"2017-12-25","Christmas (Gregorian calendar)","UA",2017 +"2018-01-01","New Year's Day","UA",2018 +"2018-01-07","Christmas (Julian calendar)","UA",2018 +"2018-01-08","Christmas (Julian calendar) (Observed)","UA",2018 +"2018-03-08","International Women's Day","UA",2018 +"2018-04-08","Easter Sunday (Pascha)","UA",2018 +"2018-04-09","Easter Sunday (Pascha) (Observed)","UA",2018 +"2018-05-01","Labor Day","UA",2018 +"2018-05-09","Day of Victory over Nazism in World War II (Victory Day)","UA",2018 +"2018-05-27","Holy Trinity Day","UA",2018 +"2018-05-28","Holy Trinity Day (Observed)","UA",2018 +"2018-06-28","Day of the Constitution of Ukraine","UA",2018 +"2018-08-24","Independence Day","UA",2018 +"2018-10-14","Defender of Ukraine Day","UA",2018 +"2018-10-15","Defender of Ukraine Day (Observed)","UA",2018 +"2018-12-25","Christmas (Gregorian calendar)","UA",2018 +"2019-01-01","New Year's Day","UA",2019 +"2019-01-07","Christmas (Julian calendar)","UA",2019 +"2019-03-08","International Women's Day","UA",2019 +"2019-04-28","Easter Sunday (Pascha)","UA",2019 +"2019-04-29","Easter Sunday (Pascha) (Observed)","UA",2019 +"2019-05-01","Labor Day","UA",2019 +"2019-05-09","Day of Victory over Nazism in World War II (Victory Day)","UA",2019 +"2019-06-16","Holy Trinity Day","UA",2019 +"2019-06-17","Holy Trinity Day (Observed)","UA",2019 +"2019-06-28","Day of the Constitution of Ukraine","UA",2019 +"2019-08-24","Independence Day","UA",2019 +"2019-08-26","Independence Day (Observed)","UA",2019 +"2019-10-14","Defender of Ukraine Day","UA",2019 +"2019-12-25","Christmas (Gregorian calendar)","UA",2019 +"2020-01-01","New Year's Day","UA",2020 +"2020-01-07","Christmas (Julian calendar)","UA",2020 +"2020-03-08","International Women's Day","UA",2020 +"2020-03-09","International Women's Day (Observed)","UA",2020 +"2020-04-19","Easter Sunday (Pascha)","UA",2020 +"2020-04-20","Easter Sunday (Pascha) (Observed)","UA",2020 +"2020-05-01","Labor Day","UA",2020 +"2020-05-09","Day of Victory over Nazism in World War II (Victory Day)","UA",2020 +"2020-05-11","Day of Victory over Nazism in World War II (Victory Day) (Observed)","UA",2020 +"2020-06-07","Holy Trinity Day","UA",2020 +"2020-06-08","Holy Trinity Day (Observed)","UA",2020 +"2020-06-28","Day of the Constitution of Ukraine","UA",2020 +"2020-06-29","Day of the Constitution of Ukraine (Observed)","UA",2020 +"2020-08-24","Independence Day","UA",2020 +"2020-10-14","Defender of Ukraine Day","UA",2020 +"2020-12-25","Christmas (Gregorian calendar)","UA",2020 +"2021-01-01","New Year's Day","UA",2021 +"2021-01-07","Christmas (Julian calendar)","UA",2021 +"2021-03-08","International Women's Day","UA",2021 +"2021-05-01","Labor Day","UA",2021 +"2021-05-02","Easter Sunday (Pascha)","UA",2021 +"2021-05-03","Labor Day (Observed)","UA",2021 +"2021-05-04","Easter Sunday (Pascha) (Observed)","UA",2021 +"2021-05-09","Day of Victory over Nazism in World War II (Victory Day)","UA",2021 +"2021-05-10","Day of Victory over Nazism in World War II (Victory Day) (Observed)","UA",2021 +"2021-06-20","Holy Trinity Day","UA",2021 +"2021-06-21","Holy Trinity Day (Observed)","UA",2021 +"2021-06-28","Day of the Constitution of Ukraine","UA",2021 +"2021-08-24","Independence Day","UA",2021 +"2021-10-14","Day of defenders of Ukraine","UA",2021 +"2021-12-25","Christmas (Gregorian calendar)","UA",2021 +"2021-12-27","Christmas (Gregorian calendar) (Observed)","UA",2021 +"2022-01-01","New Year's Day","UA",2022 +"2022-01-03","New Year's Day (Observed)","UA",2022 +"2022-01-07","Christmas (Julian calendar)","UA",2022 +"2022-03-08","International Women's Day","UA",2022 +"1995-01-01","New Year's Day","UK",1995 +"1995-01-02","New Year Holiday [Scotland]","UK",1995 +"1995-01-02","New Year's Day (Observed)","UK",1995 +"1995-01-03","New Year Holiday [Scotland] (Observed)","UK",1995 +"1995-03-17","St. Patrick's Day [Northern Ireland]","UK",1995 +"1995-04-14","Good Friday","UK",1995 +"1995-04-17","Easter Monday [England/Wales/Northern Ireland]","UK",1995 +"1995-05-08","May Day","UK",1995 +"1995-05-29","Spring Bank Holiday","UK",1995 +"1995-07-12","Battle of the Boyne [Northern Ireland]","UK",1995 +"1995-08-07","Summer Bank Holiday [Scotland]","UK",1995 +"1995-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",1995 +"1995-11-30","St. Andrew's Day [Scotland]","UK",1995 +"1995-12-25","Christmas Day","UK",1995 +"1995-12-26","Boxing Day","UK",1995 +"1996-01-01","New Year's Day","UK",1996 +"1996-01-02","New Year Holiday [Scotland]","UK",1996 +"1996-03-17","St. Patrick's Day [Northern Ireland]","UK",1996 +"1996-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",1996 +"1996-04-05","Good Friday","UK",1996 +"1996-04-08","Easter Monday [England/Wales/Northern Ireland]","UK",1996 +"1996-05-06","May Day","UK",1996 +"1996-05-27","Spring Bank Holiday","UK",1996 +"1996-07-12","Battle of the Boyne [Northern Ireland]","UK",1996 +"1996-08-05","Summer Bank Holiday [Scotland]","UK",1996 +"1996-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",1996 +"1996-11-30","St. Andrew's Day [Scotland]","UK",1996 +"1996-12-25","Christmas Day","UK",1996 +"1996-12-26","Boxing Day","UK",1996 +"1997-01-01","New Year's Day","UK",1997 +"1997-01-02","New Year Holiday [Scotland]","UK",1997 +"1997-03-17","St. Patrick's Day [Northern Ireland]","UK",1997 +"1997-03-28","Good Friday","UK",1997 +"1997-03-31","Easter Monday [England/Wales/Northern Ireland]","UK",1997 +"1997-05-05","May Day","UK",1997 +"1997-05-26","Spring Bank Holiday","UK",1997 +"1997-07-12","Battle of the Boyne [Northern Ireland]","UK",1997 +"1997-08-04","Summer Bank Holiday [Scotland]","UK",1997 +"1997-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",1997 +"1997-11-30","St. Andrew's Day [Scotland]","UK",1997 +"1997-12-25","Christmas Day","UK",1997 +"1997-12-26","Boxing Day","UK",1997 +"1998-01-01","New Year's Day","UK",1998 +"1998-01-02","New Year Holiday [Scotland]","UK",1998 +"1998-03-17","St. Patrick's Day [Northern Ireland]","UK",1998 +"1998-04-10","Good Friday","UK",1998 +"1998-04-13","Easter Monday [England/Wales/Northern Ireland]","UK",1998 +"1998-05-04","May Day","UK",1998 +"1998-05-25","Spring Bank Holiday","UK",1998 +"1998-07-12","Battle of the Boyne [Northern Ireland]","UK",1998 +"1998-08-03","Summer Bank Holiday [Scotland]","UK",1998 +"1998-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",1998 +"1998-11-30","St. Andrew's Day [Scotland]","UK",1998 +"1998-12-25","Christmas Day","UK",1998 +"1998-12-26","Boxing Day","UK",1998 +"1998-12-28","Boxing Day (Observed)","UK",1998 +"1999-01-01","New Year's Day","UK",1999 +"1999-01-02","New Year Holiday [Scotland]","UK",1999 +"1999-01-04","New Year Holiday [Scotland] (Observed)","UK",1999 +"1999-03-17","St. Patrick's Day [Northern Ireland]","UK",1999 +"1999-04-02","Good Friday","UK",1999 +"1999-04-05","Easter Monday [England/Wales/Northern Ireland]","UK",1999 +"1999-05-03","May Day","UK",1999 +"1999-05-31","Spring Bank Holiday","UK",1999 +"1999-07-12","Battle of the Boyne [Northern Ireland]","UK",1999 +"1999-08-02","Summer Bank Holiday [Scotland]","UK",1999 +"1999-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",1999 +"1999-11-30","St. Andrew's Day [Scotland]","UK",1999 +"1999-12-25","Christmas Day","UK",1999 +"1999-12-26","Boxing Day","UK",1999 +"1999-12-27","Christmas Day (Observed)","UK",1999 +"1999-12-28","Boxing Day (Observed)","UK",1999 +"1999-12-31","Millennium Celebrations","UK",1999 +"2000-01-01","New Year's Day","UK",2000 +"2000-01-02","New Year Holiday [Scotland]","UK",2000 +"2000-01-03","New Year's Day (Observed)","UK",2000 +"2000-01-04","New Year Holiday [Scotland] (Observed)","UK",2000 +"2000-03-17","St. Patrick's Day [Northern Ireland]","UK",2000 +"2000-04-21","Good Friday","UK",2000 +"2000-04-24","Easter Monday [England/Wales/Northern Ireland]","UK",2000 +"2000-05-01","May Day","UK",2000 +"2000-05-29","Spring Bank Holiday","UK",2000 +"2000-07-12","Battle of the Boyne [Northern Ireland]","UK",2000 +"2000-08-07","Summer Bank Holiday [Scotland]","UK",2000 +"2000-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2000 +"2000-11-30","St. Andrew's Day [Scotland]","UK",2000 +"2000-12-25","Christmas Day","UK",2000 +"2000-12-26","Boxing Day","UK",2000 +"2001-01-01","New Year's Day","UK",2001 +"2001-01-02","New Year Holiday [Scotland]","UK",2001 +"2001-03-17","St. Patrick's Day [Northern Ireland]","UK",2001 +"2001-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2001 +"2001-04-13","Good Friday","UK",2001 +"2001-04-16","Easter Monday [England/Wales/Northern Ireland]","UK",2001 +"2001-05-07","May Day","UK",2001 +"2001-05-28","Spring Bank Holiday","UK",2001 +"2001-07-12","Battle of the Boyne [Northern Ireland]","UK",2001 +"2001-08-06","Summer Bank Holiday [Scotland]","UK",2001 +"2001-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2001 +"2001-11-30","St. Andrew's Day [Scotland]","UK",2001 +"2001-12-25","Christmas Day","UK",2001 +"2001-12-26","Boxing Day","UK",2001 +"2002-01-01","New Year's Day","UK",2002 +"2002-01-02","New Year Holiday [Scotland]","UK",2002 +"2002-03-17","St. Patrick's Day [Northern Ireland]","UK",2002 +"2002-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",2002 +"2002-03-29","Good Friday","UK",2002 +"2002-04-01","Easter Monday [England/Wales/Northern Ireland]","UK",2002 +"2002-05-06","May Day","UK",2002 +"2002-05-27","Spring Bank Holiday","UK",2002 +"2002-06-03","Golden Jubilee of Elizabeth II","UK",2002 +"2002-07-12","Battle of the Boyne [Northern Ireland]","UK",2002 +"2002-08-05","Summer Bank Holiday [Scotland]","UK",2002 +"2002-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2002 +"2002-11-30","St. Andrew's Day [Scotland]","UK",2002 +"2002-12-25","Christmas Day","UK",2002 +"2002-12-26","Boxing Day","UK",2002 +"2003-01-01","New Year's Day","UK",2003 +"2003-01-02","New Year Holiday [Scotland]","UK",2003 +"2003-03-17","St. Patrick's Day [Northern Ireland]","UK",2003 +"2003-04-18","Good Friday","UK",2003 +"2003-04-21","Easter Monday [England/Wales/Northern Ireland]","UK",2003 +"2003-05-05","May Day","UK",2003 +"2003-05-26","Spring Bank Holiday","UK",2003 +"2003-07-12","Battle of the Boyne [Northern Ireland]","UK",2003 +"2003-08-04","Summer Bank Holiday [Scotland]","UK",2003 +"2003-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2003 +"2003-11-30","St. Andrew's Day [Scotland]","UK",2003 +"2003-12-25","Christmas Day","UK",2003 +"2003-12-26","Boxing Day","UK",2003 +"2004-01-01","New Year's Day","UK",2004 +"2004-01-02","New Year Holiday [Scotland]","UK",2004 +"2004-03-17","St. Patrick's Day [Northern Ireland]","UK",2004 +"2004-04-09","Good Friday","UK",2004 +"2004-04-12","Easter Monday [England/Wales/Northern Ireland]","UK",2004 +"2004-05-03","May Day","UK",2004 +"2004-05-31","Spring Bank Holiday","UK",2004 +"2004-07-12","Battle of the Boyne [Northern Ireland]","UK",2004 +"2004-08-02","Summer Bank Holiday [Scotland]","UK",2004 +"2004-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2004 +"2004-11-30","St. Andrew's Day [Scotland]","UK",2004 +"2004-12-25","Christmas Day","UK",2004 +"2004-12-26","Boxing Day","UK",2004 +"2004-12-27","Christmas Day (Observed)","UK",2004 +"2004-12-28","Boxing Day (Observed)","UK",2004 +"2005-01-01","New Year's Day","UK",2005 +"2005-01-02","New Year Holiday [Scotland]","UK",2005 +"2005-01-03","New Year's Day (Observed)","UK",2005 +"2005-01-04","New Year Holiday [Scotland] (Observed)","UK",2005 +"2005-03-17","St. Patrick's Day [Northern Ireland]","UK",2005 +"2005-03-25","Good Friday","UK",2005 +"2005-03-28","Easter Monday [England/Wales/Northern Ireland]","UK",2005 +"2005-05-02","May Day","UK",2005 +"2005-05-30","Spring Bank Holiday","UK",2005 +"2005-07-12","Battle of the Boyne [Northern Ireland]","UK",2005 +"2005-08-01","Summer Bank Holiday [Scotland]","UK",2005 +"2005-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2005 +"2005-11-30","St. Andrew's Day [Scotland]","UK",2005 +"2005-12-25","Christmas Day","UK",2005 +"2005-12-26","Boxing Day","UK",2005 +"2005-12-27","Christmas Day (Observed)","UK",2005 +"2006-01-01","New Year's Day","UK",2006 +"2006-01-02","New Year Holiday [Scotland]","UK",2006 +"2006-01-02","New Year's Day (Observed)","UK",2006 +"2006-01-03","New Year Holiday [Scotland] (Observed)","UK",2006 +"2006-03-17","St. Patrick's Day [Northern Ireland]","UK",2006 +"2006-04-14","Good Friday","UK",2006 +"2006-04-17","Easter Monday [England/Wales/Northern Ireland]","UK",2006 +"2006-05-01","May Day","UK",2006 +"2006-05-29","Spring Bank Holiday","UK",2006 +"2006-07-12","Battle of the Boyne [Northern Ireland]","UK",2006 +"2006-08-07","Summer Bank Holiday [Scotland]","UK",2006 +"2006-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2006 +"2006-11-30","St. Andrew's Day [Scotland]","UK",2006 +"2006-12-25","Christmas Day","UK",2006 +"2006-12-26","Boxing Day","UK",2006 +"2007-01-01","New Year's Day","UK",2007 +"2007-01-02","New Year Holiday [Scotland]","UK",2007 +"2007-03-17","St. Patrick's Day [Northern Ireland]","UK",2007 +"2007-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2007 +"2007-04-06","Good Friday","UK",2007 +"2007-04-09","Easter Monday [England/Wales/Northern Ireland]","UK",2007 +"2007-05-07","May Day","UK",2007 +"2007-05-28","Spring Bank Holiday","UK",2007 +"2007-07-12","Battle of the Boyne [Northern Ireland]","UK",2007 +"2007-08-06","Summer Bank Holiday [Scotland]","UK",2007 +"2007-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2007 +"2007-11-30","St. Andrew's Day [Scotland]","UK",2007 +"2007-12-25","Christmas Day","UK",2007 +"2007-12-26","Boxing Day","UK",2007 +"2008-01-01","New Year's Day","UK",2008 +"2008-01-02","New Year Holiday [Scotland]","UK",2008 +"2008-03-17","St. Patrick's Day [Northern Ireland]","UK",2008 +"2008-03-21","Good Friday","UK",2008 +"2008-03-24","Easter Monday [England/Wales/Northern Ireland]","UK",2008 +"2008-05-05","May Day","UK",2008 +"2008-05-26","Spring Bank Holiday","UK",2008 +"2008-07-12","Battle of the Boyne [Northern Ireland]","UK",2008 +"2008-08-04","Summer Bank Holiday [Scotland]","UK",2008 +"2008-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2008 +"2008-11-30","St. Andrew's Day [Scotland]","UK",2008 +"2008-12-25","Christmas Day","UK",2008 +"2008-12-26","Boxing Day","UK",2008 +"2009-01-01","New Year's Day","UK",2009 +"2009-01-02","New Year Holiday [Scotland]","UK",2009 +"2009-03-17","St. Patrick's Day [Northern Ireland]","UK",2009 +"2009-04-10","Good Friday","UK",2009 +"2009-04-13","Easter Monday [England/Wales/Northern Ireland]","UK",2009 +"2009-05-04","May Day","UK",2009 +"2009-05-25","Spring Bank Holiday","UK",2009 +"2009-07-12","Battle of the Boyne [Northern Ireland]","UK",2009 +"2009-08-03","Summer Bank Holiday [Scotland]","UK",2009 +"2009-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2009 +"2009-11-30","St. Andrew's Day [Scotland]","UK",2009 +"2009-12-25","Christmas Day","UK",2009 +"2009-12-26","Boxing Day","UK",2009 +"2009-12-28","Boxing Day (Observed)","UK",2009 +"2010-01-01","New Year's Day","UK",2010 +"2010-01-02","New Year Holiday [Scotland]","UK",2010 +"2010-01-04","New Year Holiday [Scotland] (Observed)","UK",2010 +"2010-03-17","St. Patrick's Day [Northern Ireland]","UK",2010 +"2010-04-02","Good Friday","UK",2010 +"2010-04-05","Easter Monday [England/Wales/Northern Ireland]","UK",2010 +"2010-05-03","May Day","UK",2010 +"2010-05-31","Spring Bank Holiday","UK",2010 +"2010-07-12","Battle of the Boyne [Northern Ireland]","UK",2010 +"2010-08-02","Summer Bank Holiday [Scotland]","UK",2010 +"2010-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2010 +"2010-11-30","St. Andrew's Day [Scotland]","UK",2010 +"2010-12-25","Christmas Day","UK",2010 +"2010-12-26","Boxing Day","UK",2010 +"2010-12-27","Christmas Day (Observed)","UK",2010 +"2010-12-28","Boxing Day (Observed)","UK",2010 +"2011-01-01","New Year's Day","UK",2011 +"2011-01-02","New Year Holiday [Scotland]","UK",2011 +"2011-01-03","New Year's Day (Observed)","UK",2011 +"2011-01-04","New Year Holiday [Scotland] (Observed)","UK",2011 +"2011-03-17","St. Patrick's Day [Northern Ireland]","UK",2011 +"2011-04-22","Good Friday","UK",2011 +"2011-04-25","Easter Monday [England/Wales/Northern Ireland]","UK",2011 +"2011-04-29","Wedding of William and Catherine","UK",2011 +"2011-05-02","May Day","UK",2011 +"2011-05-30","Spring Bank Holiday","UK",2011 +"2011-07-12","Battle of the Boyne [Northern Ireland]","UK",2011 +"2011-08-01","Summer Bank Holiday [Scotland]","UK",2011 +"2011-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2011 +"2011-11-30","St. Andrew's Day [Scotland]","UK",2011 +"2011-12-25","Christmas Day","UK",2011 +"2011-12-26","Boxing Day","UK",2011 +"2011-12-27","Christmas Day (Observed)","UK",2011 +"2012-01-01","New Year's Day","UK",2012 +"2012-01-02","New Year Holiday [Scotland]","UK",2012 +"2012-01-02","New Year's Day (Observed)","UK",2012 +"2012-01-03","New Year Holiday [Scotland] (Observed)","UK",2012 +"2012-03-17","St. Patrick's Day [Northern Ireland]","UK",2012 +"2012-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2012 +"2012-04-06","Good Friday","UK",2012 +"2012-04-09","Easter Monday [England/Wales/Northern Ireland]","UK",2012 +"2012-05-07","May Day","UK",2012 +"2012-06-04","Spring Bank Holiday","UK",2012 +"2012-06-05","Diamond Jubilee of Elizabeth II","UK",2012 +"2012-07-12","Battle of the Boyne [Northern Ireland]","UK",2012 +"2012-08-06","Summer Bank Holiday [Scotland]","UK",2012 +"2012-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2012 +"2012-11-30","St. Andrew's Day [Scotland]","UK",2012 +"2012-12-25","Christmas Day","UK",2012 +"2012-12-26","Boxing Day","UK",2012 +"2013-01-01","New Year's Day","UK",2013 +"2013-01-02","New Year Holiday [Scotland]","UK",2013 +"2013-03-17","St. Patrick's Day [Northern Ireland]","UK",2013 +"2013-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",2013 +"2013-03-29","Good Friday","UK",2013 +"2013-04-01","Easter Monday [England/Wales/Northern Ireland]","UK",2013 +"2013-05-06","May Day","UK",2013 +"2013-05-27","Spring Bank Holiday","UK",2013 +"2013-07-12","Battle of the Boyne [Northern Ireland]","UK",2013 +"2013-08-05","Summer Bank Holiday [Scotland]","UK",2013 +"2013-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2013 +"2013-11-30","St. Andrew's Day [Scotland]","UK",2013 +"2013-12-25","Christmas Day","UK",2013 +"2013-12-26","Boxing Day","UK",2013 +"2014-01-01","New Year's Day","UK",2014 +"2014-01-02","New Year Holiday [Scotland]","UK",2014 +"2014-03-17","St. Patrick's Day [Northern Ireland]","UK",2014 +"2014-04-18","Good Friday","UK",2014 +"2014-04-21","Easter Monday [England/Wales/Northern Ireland]","UK",2014 +"2014-05-05","May Day","UK",2014 +"2014-05-26","Spring Bank Holiday","UK",2014 +"2014-07-12","Battle of the Boyne [Northern Ireland]","UK",2014 +"2014-08-04","Summer Bank Holiday [Scotland]","UK",2014 +"2014-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2014 +"2014-11-30","St. Andrew's Day [Scotland]","UK",2014 +"2014-12-25","Christmas Day","UK",2014 +"2014-12-26","Boxing Day","UK",2014 +"2015-01-01","New Year's Day","UK",2015 +"2015-01-02","New Year Holiday [Scotland]","UK",2015 +"2015-03-17","St. Patrick's Day [Northern Ireland]","UK",2015 +"2015-04-03","Good Friday","UK",2015 +"2015-04-06","Easter Monday [England/Wales/Northern Ireland]","UK",2015 +"2015-05-04","May Day","UK",2015 +"2015-05-25","Spring Bank Holiday","UK",2015 +"2015-07-12","Battle of the Boyne [Northern Ireland]","UK",2015 +"2015-08-03","Summer Bank Holiday [Scotland]","UK",2015 +"2015-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2015 +"2015-11-30","St. Andrew's Day [Scotland]","UK",2015 +"2015-12-25","Christmas Day","UK",2015 +"2015-12-26","Boxing Day","UK",2015 +"2015-12-28","Boxing Day (Observed)","UK",2015 +"2016-01-01","New Year's Day","UK",2016 +"2016-01-02","New Year Holiday [Scotland]","UK",2016 +"2016-01-04","New Year Holiday [Scotland] (Observed)","UK",2016 +"2016-03-17","St. Patrick's Day [Northern Ireland]","UK",2016 +"2016-03-25","Good Friday","UK",2016 +"2016-03-28","Easter Monday [England/Wales/Northern Ireland]","UK",2016 +"2016-05-02","May Day","UK",2016 +"2016-05-30","Spring Bank Holiday","UK",2016 +"2016-07-12","Battle of the Boyne [Northern Ireland]","UK",2016 +"2016-08-01","Summer Bank Holiday [Scotland]","UK",2016 +"2016-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2016 +"2016-11-30","St. Andrew's Day [Scotland]","UK",2016 +"2016-12-25","Christmas Day","UK",2016 +"2016-12-26","Boxing Day","UK",2016 +"2016-12-27","Christmas Day (Observed)","UK",2016 +"2017-01-01","New Year's Day","UK",2017 +"2017-01-02","New Year Holiday [Scotland]","UK",2017 +"2017-01-02","New Year's Day (Observed)","UK",2017 +"2017-01-03","New Year Holiday [Scotland] (Observed)","UK",2017 +"2017-03-17","St. Patrick's Day [Northern Ireland]","UK",2017 +"2017-04-14","Good Friday","UK",2017 +"2017-04-17","Easter Monday [England/Wales/Northern Ireland]","UK",2017 +"2017-05-01","May Day","UK",2017 +"2017-05-29","Spring Bank Holiday","UK",2017 +"2017-07-12","Battle of the Boyne [Northern Ireland]","UK",2017 +"2017-08-07","Summer Bank Holiday [Scotland]","UK",2017 +"2017-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2017 +"2017-11-30","St. Andrew's Day [Scotland]","UK",2017 +"2017-12-25","Christmas Day","UK",2017 +"2017-12-26","Boxing Day","UK",2017 +"2018-01-01","New Year's Day","UK",2018 +"2018-01-02","New Year Holiday [Scotland]","UK",2018 +"2018-03-17","St. Patrick's Day [Northern Ireland]","UK",2018 +"2018-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2018 +"2018-03-30","Good Friday","UK",2018 +"2018-04-02","Easter Monday [England/Wales/Northern Ireland]","UK",2018 +"2018-05-07","May Day","UK",2018 +"2018-05-28","Spring Bank Holiday","UK",2018 +"2018-07-12","Battle of the Boyne [Northern Ireland]","UK",2018 +"2018-08-06","Summer Bank Holiday [Scotland]","UK",2018 +"2018-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2018 +"2018-11-30","St. Andrew's Day [Scotland]","UK",2018 +"2018-12-25","Christmas Day","UK",2018 +"2018-12-26","Boxing Day","UK",2018 +"2019-01-01","New Year's Day","UK",2019 +"2019-01-02","New Year Holiday [Scotland]","UK",2019 +"2019-03-17","St. Patrick's Day [Northern Ireland]","UK",2019 +"2019-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",2019 +"2019-04-19","Good Friday","UK",2019 +"2019-04-22","Easter Monday [England/Wales/Northern Ireland]","UK",2019 +"2019-05-06","May Day","UK",2019 +"2019-05-27","Spring Bank Holiday","UK",2019 +"2019-07-12","Battle of the Boyne [Northern Ireland]","UK",2019 +"2019-08-05","Summer Bank Holiday [Scotland]","UK",2019 +"2019-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2019 +"2019-11-30","St. Andrew's Day [Scotland]","UK",2019 +"2019-12-25","Christmas Day","UK",2019 +"2019-12-26","Boxing Day","UK",2019 +"2020-01-01","New Year's Day","UK",2020 +"2020-01-02","New Year Holiday [Scotland]","UK",2020 +"2020-03-17","St. Patrick's Day [Northern Ireland]","UK",2020 +"2020-04-10","Good Friday","UK",2020 +"2020-04-13","Easter Monday [England/Wales/Northern Ireland]","UK",2020 +"2020-05-08","May Day","UK",2020 +"2020-05-25","Spring Bank Holiday","UK",2020 +"2020-07-12","Battle of the Boyne [Northern Ireland]","UK",2020 +"2020-08-03","Summer Bank Holiday [Scotland]","UK",2020 +"2020-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2020 +"2020-11-30","St. Andrew's Day [Scotland]","UK",2020 +"2020-12-25","Christmas Day","UK",2020 +"2020-12-26","Boxing Day","UK",2020 +"2020-12-28","Boxing Day (Observed)","UK",2020 +"2021-01-01","New Year's Day","UK",2021 +"2021-01-02","New Year Holiday [Scotland]","UK",2021 +"2021-01-04","New Year Holiday [Scotland] (Observed)","UK",2021 +"2021-03-17","St. Patrick's Day [Northern Ireland]","UK",2021 +"2021-04-02","Good Friday","UK",2021 +"2021-04-05","Easter Monday [England/Wales/Northern Ireland]","UK",2021 +"2021-05-03","May Day","UK",2021 +"2021-05-31","Spring Bank Holiday","UK",2021 +"2021-07-12","Battle of the Boyne [Northern Ireland]","UK",2021 +"2021-08-02","Summer Bank Holiday [Scotland]","UK",2021 +"2021-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2021 +"2021-11-30","St. Andrew's Day [Scotland]","UK",2021 +"2021-12-25","Christmas Day","UK",2021 +"2021-12-26","Boxing Day","UK",2021 +"2021-12-27","Christmas Day (Observed)","UK",2021 +"2021-12-28","Boxing Day (Observed)","UK",2021 +"2022-01-01","New Year's Day","UK",2022 +"2022-01-02","New Year Holiday [Scotland]","UK",2022 +"2022-01-03","New Year's Day (Observed)","UK",2022 +"2022-01-04","New Year Holiday [Scotland] (Observed)","UK",2022 +"2022-03-17","St. Patrick's Day [Northern Ireland]","UK",2022 +"2022-04-15","Good Friday","UK",2022 +"2022-04-18","Easter Monday [England/Wales/Northern Ireland]","UK",2022 +"2022-05-02","May Day","UK",2022 +"2022-06-02","Spring Bank Holiday","UK",2022 +"2022-06-03","Platinum Jubilee of Elizabeth II","UK",2022 +"2022-07-12","Battle of the Boyne [Northern Ireland]","UK",2022 +"2022-08-01","Summer Bank Holiday [Scotland]","UK",2022 +"2022-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2022 +"2022-09-19","State Funeral of Queen Elizabeth II","UK",2022 +"2022-11-30","St. Andrew's Day [Scotland]","UK",2022 +"2022-12-25","Christmas Day","UK",2022 +"2022-12-26","Boxing Day","UK",2022 +"2022-12-27","Christmas Day (Observed)","UK",2022 +"2023-01-01","New Year's Day","UK",2023 +"2023-01-02","New Year Holiday [Scotland]","UK",2023 +"2023-01-02","New Year's Day (Observed)","UK",2023 +"2023-01-03","New Year Holiday [Scotland] (Observed)","UK",2023 +"2023-03-17","St. Patrick's Day [Northern Ireland]","UK",2023 +"2023-04-07","Good Friday","UK",2023 +"2023-04-10","Easter Monday [England/Wales/Northern Ireland]","UK",2023 +"2023-05-01","May Day","UK",2023 +"2023-05-08","Coronation of Charles III","UK",2023 +"2023-05-29","Spring Bank Holiday","UK",2023 +"2023-07-12","Battle of the Boyne [Northern Ireland]","UK",2023 +"2023-08-07","Summer Bank Holiday [Scotland]","UK",2023 +"2023-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2023 +"2023-11-30","St. Andrew's Day [Scotland]","UK",2023 +"2023-12-25","Christmas Day","UK",2023 +"2023-12-26","Boxing Day","UK",2023 +"2024-01-01","New Year's Day","UK",2024 +"2024-01-02","New Year Holiday [Scotland]","UK",2024 +"2024-03-17","St. Patrick's Day [Northern Ireland]","UK",2024 +"2024-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",2024 +"2024-03-29","Good Friday","UK",2024 +"2024-04-01","Easter Monday [England/Wales/Northern Ireland]","UK",2024 +"2024-05-06","May Day","UK",2024 +"2024-05-27","Spring Bank Holiday","UK",2024 +"2024-07-12","Battle of the Boyne [Northern Ireland]","UK",2024 +"2024-08-05","Summer Bank Holiday [Scotland]","UK",2024 +"2024-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2024 +"2024-11-30","St. Andrew's Day [Scotland]","UK",2024 +"2024-12-25","Christmas Day","UK",2024 +"2024-12-26","Boxing Day","UK",2024 +"2025-01-01","New Year's Day","UK",2025 +"2025-01-02","New Year Holiday [Scotland]","UK",2025 +"2025-03-17","St. Patrick's Day [Northern Ireland]","UK",2025 +"2025-04-18","Good Friday","UK",2025 +"2025-04-21","Easter Monday [England/Wales/Northern Ireland]","UK",2025 +"2025-05-05","May Day","UK",2025 +"2025-05-26","Spring Bank Holiday","UK",2025 +"2025-07-12","Battle of the Boyne [Northern Ireland]","UK",2025 +"2025-08-04","Summer Bank Holiday [Scotland]","UK",2025 +"2025-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2025 +"2025-11-30","St. Andrew's Day [Scotland]","UK",2025 +"2025-12-25","Christmas Day","UK",2025 +"2025-12-26","Boxing Day","UK",2025 +"2026-01-01","New Year's Day","UK",2026 +"2026-01-02","New Year Holiday [Scotland]","UK",2026 +"2026-03-17","St. Patrick's Day [Northern Ireland]","UK",2026 +"2026-04-03","Good Friday","UK",2026 +"2026-04-06","Easter Monday [England/Wales/Northern Ireland]","UK",2026 +"2026-05-04","May Day","UK",2026 +"2026-05-25","Spring Bank Holiday","UK",2026 +"2026-07-12","Battle of the Boyne [Northern Ireland]","UK",2026 +"2026-08-03","Summer Bank Holiday [Scotland]","UK",2026 +"2026-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2026 +"2026-11-30","St. Andrew's Day [Scotland]","UK",2026 +"2026-12-25","Christmas Day","UK",2026 +"2026-12-26","Boxing Day","UK",2026 +"2026-12-28","Boxing Day (Observed)","UK",2026 +"2027-01-01","New Year's Day","UK",2027 +"2027-01-02","New Year Holiday [Scotland]","UK",2027 +"2027-01-04","New Year Holiday [Scotland] (Observed)","UK",2027 +"2027-03-17","St. Patrick's Day [Northern Ireland]","UK",2027 +"2027-03-26","Good Friday","UK",2027 +"2027-03-29","Easter Monday [England/Wales/Northern Ireland]","UK",2027 +"2027-05-03","May Day","UK",2027 +"2027-05-31","Spring Bank Holiday","UK",2027 +"2027-07-12","Battle of the Boyne [Northern Ireland]","UK",2027 +"2027-08-02","Summer Bank Holiday [Scotland]","UK",2027 +"2027-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2027 +"2027-11-30","St. Andrew's Day [Scotland]","UK",2027 +"2027-12-25","Christmas Day","UK",2027 +"2027-12-26","Boxing Day","UK",2027 +"2027-12-27","Christmas Day (Observed)","UK",2027 +"2027-12-28","Boxing Day (Observed)","UK",2027 +"2028-01-01","New Year's Day","UK",2028 +"2028-01-02","New Year Holiday [Scotland]","UK",2028 +"2028-01-03","New Year's Day (Observed)","UK",2028 +"2028-01-04","New Year Holiday [Scotland] (Observed)","UK",2028 +"2028-03-17","St. Patrick's Day [Northern Ireland]","UK",2028 +"2028-04-14","Good Friday","UK",2028 +"2028-04-17","Easter Monday [England/Wales/Northern Ireland]","UK",2028 +"2028-05-01","May Day","UK",2028 +"2028-05-29","Spring Bank Holiday","UK",2028 +"2028-07-12","Battle of the Boyne [Northern Ireland]","UK",2028 +"2028-08-07","Summer Bank Holiday [Scotland]","UK",2028 +"2028-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2028 +"2028-11-30","St. Andrew's Day [Scotland]","UK",2028 +"2028-12-25","Christmas Day","UK",2028 +"2028-12-26","Boxing Day","UK",2028 +"2029-01-01","New Year's Day","UK",2029 +"2029-01-02","New Year Holiday [Scotland]","UK",2029 +"2029-03-17","St. Patrick's Day [Northern Ireland]","UK",2029 +"2029-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2029 +"2029-03-30","Good Friday","UK",2029 +"2029-04-02","Easter Monday [England/Wales/Northern Ireland]","UK",2029 +"2029-05-07","May Day","UK",2029 +"2029-05-28","Spring Bank Holiday","UK",2029 +"2029-07-12","Battle of the Boyne [Northern Ireland]","UK",2029 +"2029-08-06","Summer Bank Holiday [Scotland]","UK",2029 +"2029-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2029 +"2029-11-30","St. Andrew's Day [Scotland]","UK",2029 +"2029-12-25","Christmas Day","UK",2029 +"2029-12-26","Boxing Day","UK",2029 +"2030-01-01","New Year's Day","UK",2030 +"2030-01-02","New Year Holiday [Scotland]","UK",2030 +"2030-03-17","St. Patrick's Day [Northern Ireland]","UK",2030 +"2030-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",2030 +"2030-04-19","Good Friday","UK",2030 +"2030-04-22","Easter Monday [England/Wales/Northern Ireland]","UK",2030 +"2030-05-06","May Day","UK",2030 +"2030-05-27","Spring Bank Holiday","UK",2030 +"2030-07-12","Battle of the Boyne [Northern Ireland]","UK",2030 +"2030-08-05","Summer Bank Holiday [Scotland]","UK",2030 +"2030-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2030 +"2030-11-30","St. Andrew's Day [Scotland]","UK",2030 +"2030-12-25","Christmas Day","UK",2030 +"2030-12-26","Boxing Day","UK",2030 +"2031-01-01","New Year's Day","UK",2031 +"2031-01-02","New Year Holiday [Scotland]","UK",2031 +"2031-03-17","St. Patrick's Day [Northern Ireland]","UK",2031 +"2031-04-11","Good Friday","UK",2031 +"2031-04-14","Easter Monday [England/Wales/Northern Ireland]","UK",2031 +"2031-05-05","May Day","UK",2031 +"2031-05-26","Spring Bank Holiday","UK",2031 +"2031-07-12","Battle of the Boyne [Northern Ireland]","UK",2031 +"2031-08-04","Summer Bank Holiday [Scotland]","UK",2031 +"2031-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2031 +"2031-11-30","St. Andrew's Day [Scotland]","UK",2031 +"2031-12-25","Christmas Day","UK",2031 +"2031-12-26","Boxing Day","UK",2031 +"2032-01-01","New Year's Day","UK",2032 +"2032-01-02","New Year Holiday [Scotland]","UK",2032 +"2032-03-17","St. Patrick's Day [Northern Ireland]","UK",2032 +"2032-03-26","Good Friday","UK",2032 +"2032-03-29","Easter Monday [England/Wales/Northern Ireland]","UK",2032 +"2032-05-03","May Day","UK",2032 +"2032-05-31","Spring Bank Holiday","UK",2032 +"2032-07-12","Battle of the Boyne [Northern Ireland]","UK",2032 +"2032-08-02","Summer Bank Holiday [Scotland]","UK",2032 +"2032-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2032 +"2032-11-30","St. Andrew's Day [Scotland]","UK",2032 +"2032-12-25","Christmas Day","UK",2032 +"2032-12-26","Boxing Day","UK",2032 +"2032-12-27","Christmas Day (Observed)","UK",2032 +"2032-12-28","Boxing Day (Observed)","UK",2032 +"2033-01-01","New Year's Day","UK",2033 +"2033-01-02","New Year Holiday [Scotland]","UK",2033 +"2033-01-03","New Year's Day (Observed)","UK",2033 +"2033-01-04","New Year Holiday [Scotland] (Observed)","UK",2033 +"2033-03-17","St. Patrick's Day [Northern Ireland]","UK",2033 +"2033-04-15","Good Friday","UK",2033 +"2033-04-18","Easter Monday [England/Wales/Northern Ireland]","UK",2033 +"2033-05-02","May Day","UK",2033 +"2033-05-30","Spring Bank Holiday","UK",2033 +"2033-07-12","Battle of the Boyne [Northern Ireland]","UK",2033 +"2033-08-01","Summer Bank Holiday [Scotland]","UK",2033 +"2033-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2033 +"2033-11-30","St. Andrew's Day [Scotland]","UK",2033 +"2033-12-25","Christmas Day","UK",2033 +"2033-12-26","Boxing Day","UK",2033 +"2033-12-27","Christmas Day (Observed)","UK",2033 +"2034-01-01","New Year's Day","UK",2034 +"2034-01-02","New Year Holiday [Scotland]","UK",2034 +"2034-01-02","New Year's Day (Observed)","UK",2034 +"2034-01-03","New Year Holiday [Scotland] (Observed)","UK",2034 +"2034-03-17","St. Patrick's Day [Northern Ireland]","UK",2034 +"2034-04-07","Good Friday","UK",2034 +"2034-04-10","Easter Monday [England/Wales/Northern Ireland]","UK",2034 +"2034-05-01","May Day","UK",2034 +"2034-05-29","Spring Bank Holiday","UK",2034 +"2034-07-12","Battle of the Boyne [Northern Ireland]","UK",2034 +"2034-08-07","Summer Bank Holiday [Scotland]","UK",2034 +"2034-08-28","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2034 +"2034-11-30","St. Andrew's Day [Scotland]","UK",2034 +"2034-12-25","Christmas Day","UK",2034 +"2034-12-26","Boxing Day","UK",2034 +"2035-01-01","New Year's Day","UK",2035 +"2035-01-02","New Year Holiday [Scotland]","UK",2035 +"2035-03-17","St. Patrick's Day [Northern Ireland]","UK",2035 +"2035-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2035 +"2035-03-23","Good Friday","UK",2035 +"2035-03-26","Easter Monday [England/Wales/Northern Ireland]","UK",2035 +"2035-05-07","May Day","UK",2035 +"2035-05-28","Spring Bank Holiday","UK",2035 +"2035-07-12","Battle of the Boyne [Northern Ireland]","UK",2035 +"2035-08-06","Summer Bank Holiday [Scotland]","UK",2035 +"2035-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2035 +"2035-11-30","St. Andrew's Day [Scotland]","UK",2035 +"2035-12-25","Christmas Day","UK",2035 +"2035-12-26","Boxing Day","UK",2035 +"2036-01-01","New Year's Day","UK",2036 +"2036-01-02","New Year Holiday [Scotland]","UK",2036 +"2036-03-17","St. Patrick's Day [Northern Ireland]","UK",2036 +"2036-04-11","Good Friday","UK",2036 +"2036-04-14","Easter Monday [England/Wales/Northern Ireland]","UK",2036 +"2036-05-05","May Day","UK",2036 +"2036-05-26","Spring Bank Holiday","UK",2036 +"2036-07-12","Battle of the Boyne [Northern Ireland]","UK",2036 +"2036-08-04","Summer Bank Holiday [Scotland]","UK",2036 +"2036-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2036 +"2036-11-30","St. Andrew's Day [Scotland]","UK",2036 +"2036-12-25","Christmas Day","UK",2036 +"2036-12-26","Boxing Day","UK",2036 +"2037-01-01","New Year's Day","UK",2037 +"2037-01-02","New Year Holiday [Scotland]","UK",2037 +"2037-03-17","St. Patrick's Day [Northern Ireland]","UK",2037 +"2037-04-03","Good Friday","UK",2037 +"2037-04-06","Easter Monday [England/Wales/Northern Ireland]","UK",2037 +"2037-05-04","May Day","UK",2037 +"2037-05-25","Spring Bank Holiday","UK",2037 +"2037-07-12","Battle of the Boyne [Northern Ireland]","UK",2037 +"2037-08-03","Summer Bank Holiday [Scotland]","UK",2037 +"2037-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2037 +"2037-11-30","St. Andrew's Day [Scotland]","UK",2037 +"2037-12-25","Christmas Day","UK",2037 +"2037-12-26","Boxing Day","UK",2037 +"2037-12-28","Boxing Day (Observed)","UK",2037 +"2038-01-01","New Year's Day","UK",2038 +"2038-01-02","New Year Holiday [Scotland]","UK",2038 +"2038-01-04","New Year Holiday [Scotland] (Observed)","UK",2038 +"2038-03-17","St. Patrick's Day [Northern Ireland]","UK",2038 +"2038-04-23","Good Friday","UK",2038 +"2038-04-26","Easter Monday [England/Wales/Northern Ireland]","UK",2038 +"2038-05-03","May Day","UK",2038 +"2038-05-31","Spring Bank Holiday","UK",2038 +"2038-07-12","Battle of the Boyne [Northern Ireland]","UK",2038 +"2038-08-02","Summer Bank Holiday [Scotland]","UK",2038 +"2038-08-30","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2038 +"2038-11-30","St. Andrew's Day [Scotland]","UK",2038 +"2038-12-25","Christmas Day","UK",2038 +"2038-12-26","Boxing Day","UK",2038 +"2038-12-27","Christmas Day (Observed)","UK",2038 +"2038-12-28","Boxing Day (Observed)","UK",2038 +"2039-01-01","New Year's Day","UK",2039 +"2039-01-02","New Year Holiday [Scotland]","UK",2039 +"2039-01-03","New Year's Day (Observed)","UK",2039 +"2039-01-04","New Year Holiday [Scotland] (Observed)","UK",2039 +"2039-03-17","St. Patrick's Day [Northern Ireland]","UK",2039 +"2039-04-08","Good Friday","UK",2039 +"2039-04-11","Easter Monday [England/Wales/Northern Ireland]","UK",2039 +"2039-05-02","May Day","UK",2039 +"2039-05-30","Spring Bank Holiday","UK",2039 +"2039-07-12","Battle of the Boyne [Northern Ireland]","UK",2039 +"2039-08-01","Summer Bank Holiday [Scotland]","UK",2039 +"2039-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2039 +"2039-11-30","St. Andrew's Day [Scotland]","UK",2039 +"2039-12-25","Christmas Day","UK",2039 +"2039-12-26","Boxing Day","UK",2039 +"2039-12-27","Christmas Day (Observed)","UK",2039 +"2040-01-01","New Year's Day","UK",2040 +"2040-01-02","New Year Holiday [Scotland]","UK",2040 +"2040-01-02","New Year's Day (Observed)","UK",2040 +"2040-01-03","New Year Holiday [Scotland] (Observed)","UK",2040 +"2040-03-17","St. Patrick's Day [Northern Ireland]","UK",2040 +"2040-03-19","St. Patrick's Day [Northern Ireland] (Observed)","UK",2040 +"2040-03-30","Good Friday","UK",2040 +"2040-04-02","Easter Monday [England/Wales/Northern Ireland]","UK",2040 +"2040-05-07","May Day","UK",2040 +"2040-05-28","Spring Bank Holiday","UK",2040 +"2040-07-12","Battle of the Boyne [Northern Ireland]","UK",2040 +"2040-08-06","Summer Bank Holiday [Scotland]","UK",2040 +"2040-08-27","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2040 +"2040-11-30","St. Andrew's Day [Scotland]","UK",2040 +"2040-12-25","Christmas Day","UK",2040 +"2040-12-26","Boxing Day","UK",2040 +"2041-01-01","New Year's Day","UK",2041 +"2041-01-02","New Year Holiday [Scotland]","UK",2041 +"2041-03-17","St. Patrick's Day [Northern Ireland]","UK",2041 +"2041-03-18","St. Patrick's Day [Northern Ireland] (Observed)","UK",2041 +"2041-04-19","Good Friday","UK",2041 +"2041-04-22","Easter Monday [England/Wales/Northern Ireland]","UK",2041 +"2041-05-06","May Day","UK",2041 +"2041-05-27","Spring Bank Holiday","UK",2041 +"2041-07-12","Battle of the Boyne [Northern Ireland]","UK",2041 +"2041-08-05","Summer Bank Holiday [Scotland]","UK",2041 +"2041-08-26","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2041 +"2041-11-30","St. Andrew's Day [Scotland]","UK",2041 +"2041-12-25","Christmas Day","UK",2041 +"2041-12-26","Boxing Day","UK",2041 +"2042-01-01","New Year's Day","UK",2042 +"2042-01-02","New Year Holiday [Scotland]","UK",2042 +"2042-03-17","St. Patrick's Day [Northern Ireland]","UK",2042 +"2042-04-04","Good Friday","UK",2042 +"2042-04-07","Easter Monday [England/Wales/Northern Ireland]","UK",2042 +"2042-05-05","May Day","UK",2042 +"2042-05-26","Spring Bank Holiday","UK",2042 +"2042-07-12","Battle of the Boyne [Northern Ireland]","UK",2042 +"2042-08-04","Summer Bank Holiday [Scotland]","UK",2042 +"2042-08-25","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2042 +"2042-11-30","St. Andrew's Day [Scotland]","UK",2042 +"2042-12-25","Christmas Day","UK",2042 +"2042-12-26","Boxing Day","UK",2042 +"2043-01-01","New Year's Day","UK",2043 +"2043-01-02","New Year Holiday [Scotland]","UK",2043 +"2043-03-17","St. Patrick's Day [Northern Ireland]","UK",2043 +"2043-03-27","Good Friday","UK",2043 +"2043-03-30","Easter Monday [England/Wales/Northern Ireland]","UK",2043 +"2043-05-04","May Day","UK",2043 +"2043-05-25","Spring Bank Holiday","UK",2043 +"2043-07-12","Battle of the Boyne [Northern Ireland]","UK",2043 +"2043-08-03","Summer Bank Holiday [Scotland]","UK",2043 +"2043-08-31","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2043 +"2043-11-30","St. Andrew's Day [Scotland]","UK",2043 +"2043-12-25","Christmas Day","UK",2043 +"2043-12-26","Boxing Day","UK",2043 +"2043-12-28","Boxing Day (Observed)","UK",2043 +"2044-01-01","New Year's Day","UK",2044 +"2044-01-02","New Year Holiday [Scotland]","UK",2044 +"2044-01-04","New Year Holiday [Scotland] (Observed)","UK",2044 +"2044-03-17","St. Patrick's Day [Northern Ireland]","UK",2044 +"2044-04-15","Good Friday","UK",2044 +"2044-04-18","Easter Monday [England/Wales/Northern Ireland]","UK",2044 +"2044-05-02","May Day","UK",2044 +"2044-05-30","Spring Bank Holiday","UK",2044 +"2044-07-12","Battle of the Boyne [Northern Ireland]","UK",2044 +"2044-08-01","Summer Bank Holiday [Scotland]","UK",2044 +"2044-08-29","Late Summer Bank Holiday [England/Wales/Northern Ireland]","UK",2044 +"2044-11-30","St. Andrew's Day [Scotland]","UK",2044 +"2044-12-25","Christmas Day","UK",2044 +"2044-12-26","Boxing Day","UK",2044 +"2044-12-27","Christmas Day (Observed)","UK",2044 +"1995-01-01","New Year's Day","UM",1995 +"1995-01-02","New Year's Day (Observed)","UM",1995 +"1995-01-16","Martin Luther King Jr. Day","UM",1995 +"1995-02-20","Washington's Birthday","UM",1995 +"1995-05-29","Memorial Day","UM",1995 +"1995-07-04","Independence Day","UM",1995 +"1995-09-04","Labor Day","UM",1995 +"1995-10-09","Columbus Day","UM",1995 +"1995-11-10","Veterans Day (Observed)","UM",1995 +"1995-11-11","Veterans Day","UM",1995 +"1995-11-23","Thanksgiving","UM",1995 +"1995-12-25","Christmas Day","UM",1995 +"1996-01-01","New Year's Day","UM",1996 +"1996-01-15","Martin Luther King Jr. Day","UM",1996 +"1996-02-19","Washington's Birthday","UM",1996 +"1996-05-27","Memorial Day","UM",1996 +"1996-07-04","Independence Day","UM",1996 +"1996-09-02","Labor Day","UM",1996 +"1996-10-14","Columbus Day","UM",1996 +"1996-11-11","Veterans Day","UM",1996 +"1996-11-28","Thanksgiving","UM",1996 +"1996-12-25","Christmas Day","UM",1996 +"1997-01-01","New Year's Day","UM",1997 +"1997-01-20","Martin Luther King Jr. Day","UM",1997 +"1997-02-17","Washington's Birthday","UM",1997 +"1997-05-26","Memorial Day","UM",1997 +"1997-07-04","Independence Day","UM",1997 +"1997-09-01","Labor Day","UM",1997 +"1997-10-13","Columbus Day","UM",1997 +"1997-11-11","Veterans Day","UM",1997 +"1997-11-27","Thanksgiving","UM",1997 +"1997-12-25","Christmas Day","UM",1997 +"1998-01-01","New Year's Day","UM",1998 +"1998-01-19","Martin Luther King Jr. Day","UM",1998 +"1998-02-16","Washington's Birthday","UM",1998 +"1998-05-25","Memorial Day","UM",1998 +"1998-07-03","Independence Day (Observed)","UM",1998 +"1998-07-04","Independence Day","UM",1998 +"1998-09-07","Labor Day","UM",1998 +"1998-10-12","Columbus Day","UM",1998 +"1998-11-11","Veterans Day","UM",1998 +"1998-11-26","Thanksgiving","UM",1998 +"1998-12-25","Christmas Day","UM",1998 +"1999-01-01","New Year's Day","UM",1999 +"1999-01-18","Martin Luther King Jr. Day","UM",1999 +"1999-02-15","Washington's Birthday","UM",1999 +"1999-05-31","Memorial Day","UM",1999 +"1999-07-04","Independence Day","UM",1999 +"1999-07-05","Independence Day (Observed)","UM",1999 +"1999-09-06","Labor Day","UM",1999 +"1999-10-11","Columbus Day","UM",1999 +"1999-11-11","Veterans Day","UM",1999 +"1999-11-25","Thanksgiving","UM",1999 +"1999-12-24","Christmas Day (Observed)","UM",1999 +"1999-12-25","Christmas Day","UM",1999 +"1999-12-31","New Year's Day (Observed)","UM",1999 +"2000-01-01","New Year's Day","UM",2000 +"2000-01-17","Martin Luther King Jr. Day","UM",2000 +"2000-02-21","Washington's Birthday","UM",2000 +"2000-05-29","Memorial Day","UM",2000 +"2000-07-04","Independence Day","UM",2000 +"2000-09-04","Labor Day","UM",2000 +"2000-10-09","Columbus Day","UM",2000 +"2000-11-10","Veterans Day (Observed)","UM",2000 +"2000-11-11","Veterans Day","UM",2000 +"2000-11-23","Thanksgiving","UM",2000 +"2000-12-25","Christmas Day","UM",2000 +"2001-01-01","New Year's Day","UM",2001 +"2001-01-15","Martin Luther King Jr. Day","UM",2001 +"2001-02-19","Washington's Birthday","UM",2001 +"2001-05-28","Memorial Day","UM",2001 +"2001-07-04","Independence Day","UM",2001 +"2001-09-03","Labor Day","UM",2001 +"2001-10-08","Columbus Day","UM",2001 +"2001-11-11","Veterans Day","UM",2001 +"2001-11-12","Veterans Day (Observed)","UM",2001 +"2001-11-22","Thanksgiving","UM",2001 +"2001-12-25","Christmas Day","UM",2001 +"2002-01-01","New Year's Day","UM",2002 +"2002-01-21","Martin Luther King Jr. Day","UM",2002 +"2002-02-18","Washington's Birthday","UM",2002 +"2002-05-27","Memorial Day","UM",2002 +"2002-07-04","Independence Day","UM",2002 +"2002-09-02","Labor Day","UM",2002 +"2002-10-14","Columbus Day","UM",2002 +"2002-11-11","Veterans Day","UM",2002 +"2002-11-28","Thanksgiving","UM",2002 +"2002-12-25","Christmas Day","UM",2002 +"2003-01-01","New Year's Day","UM",2003 +"2003-01-20","Martin Luther King Jr. Day","UM",2003 +"2003-02-17","Washington's Birthday","UM",2003 +"2003-05-26","Memorial Day","UM",2003 +"2003-07-04","Independence Day","UM",2003 +"2003-09-01","Labor Day","UM",2003 +"2003-10-13","Columbus Day","UM",2003 +"2003-11-11","Veterans Day","UM",2003 +"2003-11-27","Thanksgiving","UM",2003 +"2003-12-25","Christmas Day","UM",2003 +"2004-01-01","New Year's Day","UM",2004 +"2004-01-19","Martin Luther King Jr. Day","UM",2004 +"2004-02-16","Washington's Birthday","UM",2004 +"2004-05-31","Memorial Day","UM",2004 +"2004-07-04","Independence Day","UM",2004 +"2004-07-05","Independence Day (Observed)","UM",2004 +"2004-09-06","Labor Day","UM",2004 +"2004-10-11","Columbus Day","UM",2004 +"2004-11-11","Veterans Day","UM",2004 +"2004-11-25","Thanksgiving","UM",2004 +"2004-12-24","Christmas Day (Observed)","UM",2004 +"2004-12-25","Christmas Day","UM",2004 +"2004-12-31","New Year's Day (Observed)","UM",2004 +"2005-01-01","New Year's Day","UM",2005 +"2005-01-17","Martin Luther King Jr. Day","UM",2005 +"2005-02-21","Washington's Birthday","UM",2005 +"2005-05-30","Memorial Day","UM",2005 +"2005-07-04","Independence Day","UM",2005 +"2005-09-05","Labor Day","UM",2005 +"2005-10-10","Columbus Day","UM",2005 +"2005-11-11","Veterans Day","UM",2005 +"2005-11-24","Thanksgiving","UM",2005 +"2005-12-25","Christmas Day","UM",2005 +"2005-12-26","Christmas Day (Observed)","UM",2005 +"2006-01-01","New Year's Day","UM",2006 +"2006-01-02","New Year's Day (Observed)","UM",2006 +"2006-01-16","Martin Luther King Jr. Day","UM",2006 +"2006-02-20","Washington's Birthday","UM",2006 +"2006-05-29","Memorial Day","UM",2006 +"2006-07-04","Independence Day","UM",2006 +"2006-09-04","Labor Day","UM",2006 +"2006-10-09","Columbus Day","UM",2006 +"2006-11-10","Veterans Day (Observed)","UM",2006 +"2006-11-11","Veterans Day","UM",2006 +"2006-11-23","Thanksgiving","UM",2006 +"2006-12-25","Christmas Day","UM",2006 +"2007-01-01","New Year's Day","UM",2007 +"2007-01-15","Martin Luther King Jr. Day","UM",2007 +"2007-02-19","Washington's Birthday","UM",2007 +"2007-05-28","Memorial Day","UM",2007 +"2007-07-04","Independence Day","UM",2007 +"2007-09-03","Labor Day","UM",2007 +"2007-10-08","Columbus Day","UM",2007 +"2007-11-11","Veterans Day","UM",2007 +"2007-11-12","Veterans Day (Observed)","UM",2007 +"2007-11-22","Thanksgiving","UM",2007 +"2007-12-25","Christmas Day","UM",2007 +"2008-01-01","New Year's Day","UM",2008 +"2008-01-21","Martin Luther King Jr. Day","UM",2008 +"2008-02-18","Washington's Birthday","UM",2008 +"2008-05-26","Memorial Day","UM",2008 +"2008-07-04","Independence Day","UM",2008 +"2008-09-01","Labor Day","UM",2008 +"2008-10-13","Columbus Day","UM",2008 +"2008-11-11","Veterans Day","UM",2008 +"2008-11-27","Thanksgiving","UM",2008 +"2008-12-25","Christmas Day","UM",2008 +"2009-01-01","New Year's Day","UM",2009 +"2009-01-19","Martin Luther King Jr. Day","UM",2009 +"2009-02-16","Washington's Birthday","UM",2009 +"2009-05-25","Memorial Day","UM",2009 +"2009-07-03","Independence Day (Observed)","UM",2009 +"2009-07-04","Independence Day","UM",2009 +"2009-09-07","Labor Day","UM",2009 +"2009-10-12","Columbus Day","UM",2009 +"2009-11-11","Veterans Day","UM",2009 +"2009-11-26","Thanksgiving","UM",2009 +"2009-12-25","Christmas Day","UM",2009 +"2010-01-01","New Year's Day","UM",2010 +"2010-01-18","Martin Luther King Jr. Day","UM",2010 +"2010-02-15","Washington's Birthday","UM",2010 +"2010-05-31","Memorial Day","UM",2010 +"2010-07-04","Independence Day","UM",2010 +"2010-07-05","Independence Day (Observed)","UM",2010 +"2010-09-06","Labor Day","UM",2010 +"2010-10-11","Columbus Day","UM",2010 +"2010-11-11","Veterans Day","UM",2010 +"2010-11-25","Thanksgiving","UM",2010 +"2010-12-24","Christmas Day (Observed)","UM",2010 +"2010-12-25","Christmas Day","UM",2010 +"2010-12-31","New Year's Day (Observed)","UM",2010 +"2011-01-01","New Year's Day","UM",2011 +"2011-01-17","Martin Luther King Jr. Day","UM",2011 +"2011-02-21","Washington's Birthday","UM",2011 +"2011-05-30","Memorial Day","UM",2011 +"2011-07-04","Independence Day","UM",2011 +"2011-09-05","Labor Day","UM",2011 +"2011-10-10","Columbus Day","UM",2011 +"2011-11-11","Veterans Day","UM",2011 +"2011-11-24","Thanksgiving","UM",2011 +"2011-12-25","Christmas Day","UM",2011 +"2011-12-26","Christmas Day (Observed)","UM",2011 +"2012-01-01","New Year's Day","UM",2012 +"2012-01-02","New Year's Day (Observed)","UM",2012 +"2012-01-16","Martin Luther King Jr. Day","UM",2012 +"2012-02-20","Washington's Birthday","UM",2012 +"2012-05-28","Memorial Day","UM",2012 +"2012-07-04","Independence Day","UM",2012 +"2012-09-03","Labor Day","UM",2012 +"2012-10-08","Columbus Day","UM",2012 +"2012-11-11","Veterans Day","UM",2012 +"2012-11-12","Veterans Day (Observed)","UM",2012 +"2012-11-22","Thanksgiving","UM",2012 +"2012-12-25","Christmas Day","UM",2012 +"2013-01-01","New Year's Day","UM",2013 +"2013-01-21","Martin Luther King Jr. Day","UM",2013 +"2013-02-18","Washington's Birthday","UM",2013 +"2013-05-27","Memorial Day","UM",2013 +"2013-07-04","Independence Day","UM",2013 +"2013-09-02","Labor Day","UM",2013 +"2013-10-14","Columbus Day","UM",2013 +"2013-11-11","Veterans Day","UM",2013 +"2013-11-28","Thanksgiving","UM",2013 +"2013-12-25","Christmas Day","UM",2013 +"2014-01-01","New Year's Day","UM",2014 +"2014-01-20","Martin Luther King Jr. Day","UM",2014 +"2014-02-17","Washington's Birthday","UM",2014 +"2014-05-26","Memorial Day","UM",2014 +"2014-07-04","Independence Day","UM",2014 +"2014-09-01","Labor Day","UM",2014 +"2014-10-13","Columbus Day","UM",2014 +"2014-11-11","Veterans Day","UM",2014 +"2014-11-27","Thanksgiving","UM",2014 +"2014-12-25","Christmas Day","UM",2014 +"2015-01-01","New Year's Day","UM",2015 +"2015-01-19","Martin Luther King Jr. Day","UM",2015 +"2015-02-16","Washington's Birthday","UM",2015 +"2015-05-25","Memorial Day","UM",2015 +"2015-07-03","Independence Day (Observed)","UM",2015 +"2015-07-04","Independence Day","UM",2015 +"2015-09-07","Labor Day","UM",2015 +"2015-10-12","Columbus Day","UM",2015 +"2015-11-11","Veterans Day","UM",2015 +"2015-11-26","Thanksgiving","UM",2015 +"2015-12-25","Christmas Day","UM",2015 +"2016-01-01","New Year's Day","UM",2016 +"2016-01-18","Martin Luther King Jr. Day","UM",2016 +"2016-02-15","Washington's Birthday","UM",2016 +"2016-05-30","Memorial Day","UM",2016 +"2016-07-04","Independence Day","UM",2016 +"2016-09-05","Labor Day","UM",2016 +"2016-10-10","Columbus Day","UM",2016 +"2016-11-11","Veterans Day","UM",2016 +"2016-11-24","Thanksgiving","UM",2016 +"2016-12-25","Christmas Day","UM",2016 +"2016-12-26","Christmas Day (Observed)","UM",2016 +"2017-01-01","New Year's Day","UM",2017 +"2017-01-02","New Year's Day (Observed)","UM",2017 +"2017-01-16","Martin Luther King Jr. Day","UM",2017 +"2017-02-20","Washington's Birthday","UM",2017 +"2017-05-29","Memorial Day","UM",2017 +"2017-07-04","Independence Day","UM",2017 +"2017-09-04","Labor Day","UM",2017 +"2017-10-09","Columbus Day","UM",2017 +"2017-11-10","Veterans Day (Observed)","UM",2017 +"2017-11-11","Veterans Day","UM",2017 +"2017-11-23","Thanksgiving","UM",2017 +"2017-12-25","Christmas Day","UM",2017 +"2018-01-01","New Year's Day","UM",2018 +"2018-01-15","Martin Luther King Jr. Day","UM",2018 +"2018-02-19","Washington's Birthday","UM",2018 +"2018-05-28","Memorial Day","UM",2018 +"2018-07-04","Independence Day","UM",2018 +"2018-09-03","Labor Day","UM",2018 +"2018-10-08","Columbus Day","UM",2018 +"2018-11-11","Veterans Day","UM",2018 +"2018-11-12","Veterans Day (Observed)","UM",2018 +"2018-11-22","Thanksgiving","UM",2018 +"2018-12-25","Christmas Day","UM",2018 +"2019-01-01","New Year's Day","UM",2019 +"2019-01-21","Martin Luther King Jr. Day","UM",2019 +"2019-02-18","Washington's Birthday","UM",2019 +"2019-05-27","Memorial Day","UM",2019 +"2019-07-04","Independence Day","UM",2019 +"2019-09-02","Labor Day","UM",2019 +"2019-10-14","Columbus Day","UM",2019 +"2019-11-11","Veterans Day","UM",2019 +"2019-11-28","Thanksgiving","UM",2019 +"2019-12-25","Christmas Day","UM",2019 +"2020-01-01","New Year's Day","UM",2020 +"2020-01-20","Martin Luther King Jr. Day","UM",2020 +"2020-02-17","Washington's Birthday","UM",2020 +"2020-05-25","Memorial Day","UM",2020 +"2020-07-03","Independence Day (Observed)","UM",2020 +"2020-07-04","Independence Day","UM",2020 +"2020-09-07","Labor Day","UM",2020 +"2020-10-12","Columbus Day","UM",2020 +"2020-11-11","Veterans Day","UM",2020 +"2020-11-26","Thanksgiving","UM",2020 +"2020-12-25","Christmas Day","UM",2020 +"2021-01-01","New Year's Day","UM",2021 +"2021-01-18","Martin Luther King Jr. Day","UM",2021 +"2021-02-15","Washington's Birthday","UM",2021 +"2021-05-31","Memorial Day","UM",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","UM",2021 +"2021-06-19","Juneteenth National Independence Day","UM",2021 +"2021-07-04","Independence Day","UM",2021 +"2021-07-05","Independence Day (Observed)","UM",2021 +"2021-09-06","Labor Day","UM",2021 +"2021-10-11","Columbus Day","UM",2021 +"2021-11-11","Veterans Day","UM",2021 +"2021-11-25","Thanksgiving","UM",2021 +"2021-12-24","Christmas Day (Observed)","UM",2021 +"2021-12-25","Christmas Day","UM",2021 +"2021-12-31","New Year's Day (Observed)","UM",2021 +"2022-01-01","New Year's Day","UM",2022 +"2022-01-17","Martin Luther King Jr. Day","UM",2022 +"2022-02-21","Washington's Birthday","UM",2022 +"2022-05-30","Memorial Day","UM",2022 +"2022-06-19","Juneteenth National Independence Day","UM",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","UM",2022 +"2022-07-04","Independence Day","UM",2022 +"2022-09-05","Labor Day","UM",2022 +"2022-10-10","Columbus Day","UM",2022 +"2022-11-11","Veterans Day","UM",2022 +"2022-11-24","Thanksgiving","UM",2022 +"2022-12-25","Christmas Day","UM",2022 +"2022-12-26","Christmas Day (Observed)","UM",2022 +"2023-01-01","New Year's Day","UM",2023 +"2023-01-02","New Year's Day (Observed)","UM",2023 +"2023-01-16","Martin Luther King Jr. Day","UM",2023 +"2023-02-20","Washington's Birthday","UM",2023 +"2023-05-29","Memorial Day","UM",2023 +"2023-06-19","Juneteenth National Independence Day","UM",2023 +"2023-07-04","Independence Day","UM",2023 +"2023-09-04","Labor Day","UM",2023 +"2023-10-09","Columbus Day","UM",2023 +"2023-11-10","Veterans Day (Observed)","UM",2023 +"2023-11-11","Veterans Day","UM",2023 +"2023-11-23","Thanksgiving","UM",2023 +"2023-12-25","Christmas Day","UM",2023 +"2024-01-01","New Year's Day","UM",2024 +"2024-01-15","Martin Luther King Jr. Day","UM",2024 +"2024-02-19","Washington's Birthday","UM",2024 +"2024-05-27","Memorial Day","UM",2024 +"2024-06-19","Juneteenth National Independence Day","UM",2024 +"2024-07-04","Independence Day","UM",2024 +"2024-09-02","Labor Day","UM",2024 +"2024-10-14","Columbus Day","UM",2024 +"2024-11-11","Veterans Day","UM",2024 +"2024-11-28","Thanksgiving","UM",2024 +"2024-12-25","Christmas Day","UM",2024 +"2025-01-01","New Year's Day","UM",2025 +"2025-01-20","Martin Luther King Jr. Day","UM",2025 +"2025-02-17","Washington's Birthday","UM",2025 +"2025-05-26","Memorial Day","UM",2025 +"2025-06-19","Juneteenth National Independence Day","UM",2025 +"2025-07-04","Independence Day","UM",2025 +"2025-09-01","Labor Day","UM",2025 +"2025-10-13","Columbus Day","UM",2025 +"2025-11-11","Veterans Day","UM",2025 +"2025-11-27","Thanksgiving","UM",2025 +"2025-12-25","Christmas Day","UM",2025 +"2026-01-01","New Year's Day","UM",2026 +"2026-01-19","Martin Luther King Jr. Day","UM",2026 +"2026-02-16","Washington's Birthday","UM",2026 +"2026-05-25","Memorial Day","UM",2026 +"2026-06-19","Juneteenth National Independence Day","UM",2026 +"2026-07-03","Independence Day (Observed)","UM",2026 +"2026-07-04","Independence Day","UM",2026 +"2026-09-07","Labor Day","UM",2026 +"2026-10-12","Columbus Day","UM",2026 +"2026-11-11","Veterans Day","UM",2026 +"2026-11-26","Thanksgiving","UM",2026 +"2026-12-25","Christmas Day","UM",2026 +"2027-01-01","New Year's Day","UM",2027 +"2027-01-18","Martin Luther King Jr. Day","UM",2027 +"2027-02-15","Washington's Birthday","UM",2027 +"2027-05-31","Memorial Day","UM",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","UM",2027 +"2027-06-19","Juneteenth National Independence Day","UM",2027 +"2027-07-04","Independence Day","UM",2027 +"2027-07-05","Independence Day (Observed)","UM",2027 +"2027-09-06","Labor Day","UM",2027 +"2027-10-11","Columbus Day","UM",2027 +"2027-11-11","Veterans Day","UM",2027 +"2027-11-25","Thanksgiving","UM",2027 +"2027-12-24","Christmas Day (Observed)","UM",2027 +"2027-12-25","Christmas Day","UM",2027 +"2027-12-31","New Year's Day (Observed)","UM",2027 +"2028-01-01","New Year's Day","UM",2028 +"2028-01-17","Martin Luther King Jr. Day","UM",2028 +"2028-02-21","Washington's Birthday","UM",2028 +"2028-05-29","Memorial Day","UM",2028 +"2028-06-19","Juneteenth National Independence Day","UM",2028 +"2028-07-04","Independence Day","UM",2028 +"2028-09-04","Labor Day","UM",2028 +"2028-10-09","Columbus Day","UM",2028 +"2028-11-10","Veterans Day (Observed)","UM",2028 +"2028-11-11","Veterans Day","UM",2028 +"2028-11-23","Thanksgiving","UM",2028 +"2028-12-25","Christmas Day","UM",2028 +"2029-01-01","New Year's Day","UM",2029 +"2029-01-15","Martin Luther King Jr. Day","UM",2029 +"2029-02-19","Washington's Birthday","UM",2029 +"2029-05-28","Memorial Day","UM",2029 +"2029-06-19","Juneteenth National Independence Day","UM",2029 +"2029-07-04","Independence Day","UM",2029 +"2029-09-03","Labor Day","UM",2029 +"2029-10-08","Columbus Day","UM",2029 +"2029-11-11","Veterans Day","UM",2029 +"2029-11-12","Veterans Day (Observed)","UM",2029 +"2029-11-22","Thanksgiving","UM",2029 +"2029-12-25","Christmas Day","UM",2029 +"2030-01-01","New Year's Day","UM",2030 +"2030-01-21","Martin Luther King Jr. Day","UM",2030 +"2030-02-18","Washington's Birthday","UM",2030 +"2030-05-27","Memorial Day","UM",2030 +"2030-06-19","Juneteenth National Independence Day","UM",2030 +"2030-07-04","Independence Day","UM",2030 +"2030-09-02","Labor Day","UM",2030 +"2030-10-14","Columbus Day","UM",2030 +"2030-11-11","Veterans Day","UM",2030 +"2030-11-28","Thanksgiving","UM",2030 +"2030-12-25","Christmas Day","UM",2030 +"2031-01-01","New Year's Day","UM",2031 +"2031-01-20","Martin Luther King Jr. Day","UM",2031 +"2031-02-17","Washington's Birthday","UM",2031 +"2031-05-26","Memorial Day","UM",2031 +"2031-06-19","Juneteenth National Independence Day","UM",2031 +"2031-07-04","Independence Day","UM",2031 +"2031-09-01","Labor Day","UM",2031 +"2031-10-13","Columbus Day","UM",2031 +"2031-11-11","Veterans Day","UM",2031 +"2031-11-27","Thanksgiving","UM",2031 +"2031-12-25","Christmas Day","UM",2031 +"2032-01-01","New Year's Day","UM",2032 +"2032-01-19","Martin Luther King Jr. Day","UM",2032 +"2032-02-16","Washington's Birthday","UM",2032 +"2032-05-31","Memorial Day","UM",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","UM",2032 +"2032-06-19","Juneteenth National Independence Day","UM",2032 +"2032-07-04","Independence Day","UM",2032 +"2032-07-05","Independence Day (Observed)","UM",2032 +"2032-09-06","Labor Day","UM",2032 +"2032-10-11","Columbus Day","UM",2032 +"2032-11-11","Veterans Day","UM",2032 +"2032-11-25","Thanksgiving","UM",2032 +"2032-12-24","Christmas Day (Observed)","UM",2032 +"2032-12-25","Christmas Day","UM",2032 +"2032-12-31","New Year's Day (Observed)","UM",2032 +"2033-01-01","New Year's Day","UM",2033 +"2033-01-17","Martin Luther King Jr. Day","UM",2033 +"2033-02-21","Washington's Birthday","UM",2033 +"2033-05-30","Memorial Day","UM",2033 +"2033-06-19","Juneteenth National Independence Day","UM",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","UM",2033 +"2033-07-04","Independence Day","UM",2033 +"2033-09-05","Labor Day","UM",2033 +"2033-10-10","Columbus Day","UM",2033 +"2033-11-11","Veterans Day","UM",2033 +"2033-11-24","Thanksgiving","UM",2033 +"2033-12-25","Christmas Day","UM",2033 +"2033-12-26","Christmas Day (Observed)","UM",2033 +"2034-01-01","New Year's Day","UM",2034 +"2034-01-02","New Year's Day (Observed)","UM",2034 +"2034-01-16","Martin Luther King Jr. Day","UM",2034 +"2034-02-20","Washington's Birthday","UM",2034 +"2034-05-29","Memorial Day","UM",2034 +"2034-06-19","Juneteenth National Independence Day","UM",2034 +"2034-07-04","Independence Day","UM",2034 +"2034-09-04","Labor Day","UM",2034 +"2034-10-09","Columbus Day","UM",2034 +"2034-11-10","Veterans Day (Observed)","UM",2034 +"2034-11-11","Veterans Day","UM",2034 +"2034-11-23","Thanksgiving","UM",2034 +"2034-12-25","Christmas Day","UM",2034 +"2035-01-01","New Year's Day","UM",2035 +"2035-01-15","Martin Luther King Jr. Day","UM",2035 +"2035-02-19","Washington's Birthday","UM",2035 +"2035-05-28","Memorial Day","UM",2035 +"2035-06-19","Juneteenth National Independence Day","UM",2035 +"2035-07-04","Independence Day","UM",2035 +"2035-09-03","Labor Day","UM",2035 +"2035-10-08","Columbus Day","UM",2035 +"2035-11-11","Veterans Day","UM",2035 +"2035-11-12","Veterans Day (Observed)","UM",2035 +"2035-11-22","Thanksgiving","UM",2035 +"2035-12-25","Christmas Day","UM",2035 +"2036-01-01","New Year's Day","UM",2036 +"2036-01-21","Martin Luther King Jr. Day","UM",2036 +"2036-02-18","Washington's Birthday","UM",2036 +"2036-05-26","Memorial Day","UM",2036 +"2036-06-19","Juneteenth National Independence Day","UM",2036 +"2036-07-04","Independence Day","UM",2036 +"2036-09-01","Labor Day","UM",2036 +"2036-10-13","Columbus Day","UM",2036 +"2036-11-11","Veterans Day","UM",2036 +"2036-11-27","Thanksgiving","UM",2036 +"2036-12-25","Christmas Day","UM",2036 +"2037-01-01","New Year's Day","UM",2037 +"2037-01-19","Martin Luther King Jr. Day","UM",2037 +"2037-02-16","Washington's Birthday","UM",2037 +"2037-05-25","Memorial Day","UM",2037 +"2037-06-19","Juneteenth National Independence Day","UM",2037 +"2037-07-03","Independence Day (Observed)","UM",2037 +"2037-07-04","Independence Day","UM",2037 +"2037-09-07","Labor Day","UM",2037 +"2037-10-12","Columbus Day","UM",2037 +"2037-11-11","Veterans Day","UM",2037 +"2037-11-26","Thanksgiving","UM",2037 +"2037-12-25","Christmas Day","UM",2037 +"2038-01-01","New Year's Day","UM",2038 +"2038-01-18","Martin Luther King Jr. Day","UM",2038 +"2038-02-15","Washington's Birthday","UM",2038 +"2038-05-31","Memorial Day","UM",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","UM",2038 +"2038-06-19","Juneteenth National Independence Day","UM",2038 +"2038-07-04","Independence Day","UM",2038 +"2038-07-05","Independence Day (Observed)","UM",2038 +"2038-09-06","Labor Day","UM",2038 +"2038-10-11","Columbus Day","UM",2038 +"2038-11-11","Veterans Day","UM",2038 +"2038-11-25","Thanksgiving","UM",2038 +"2038-12-24","Christmas Day (Observed)","UM",2038 +"2038-12-25","Christmas Day","UM",2038 +"2038-12-31","New Year's Day (Observed)","UM",2038 +"2039-01-01","New Year's Day","UM",2039 +"2039-01-17","Martin Luther King Jr. Day","UM",2039 +"2039-02-21","Washington's Birthday","UM",2039 +"2039-05-30","Memorial Day","UM",2039 +"2039-06-19","Juneteenth National Independence Day","UM",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","UM",2039 +"2039-07-04","Independence Day","UM",2039 +"2039-09-05","Labor Day","UM",2039 +"2039-10-10","Columbus Day","UM",2039 +"2039-11-11","Veterans Day","UM",2039 +"2039-11-24","Thanksgiving","UM",2039 +"2039-12-25","Christmas Day","UM",2039 +"2039-12-26","Christmas Day (Observed)","UM",2039 +"2040-01-01","New Year's Day","UM",2040 +"2040-01-02","New Year's Day (Observed)","UM",2040 +"2040-01-16","Martin Luther King Jr. Day","UM",2040 +"2040-02-20","Washington's Birthday","UM",2040 +"2040-05-28","Memorial Day","UM",2040 +"2040-06-19","Juneteenth National Independence Day","UM",2040 +"2040-07-04","Independence Day","UM",2040 +"2040-09-03","Labor Day","UM",2040 +"2040-10-08","Columbus Day","UM",2040 +"2040-11-11","Veterans Day","UM",2040 +"2040-11-12","Veterans Day (Observed)","UM",2040 +"2040-11-22","Thanksgiving","UM",2040 +"2040-12-25","Christmas Day","UM",2040 +"2041-01-01","New Year's Day","UM",2041 +"2041-01-21","Martin Luther King Jr. Day","UM",2041 +"2041-02-18","Washington's Birthday","UM",2041 +"2041-05-27","Memorial Day","UM",2041 +"2041-06-19","Juneteenth National Independence Day","UM",2041 +"2041-07-04","Independence Day","UM",2041 +"2041-09-02","Labor Day","UM",2041 +"2041-10-14","Columbus Day","UM",2041 +"2041-11-11","Veterans Day","UM",2041 +"2041-11-28","Thanksgiving","UM",2041 +"2041-12-25","Christmas Day","UM",2041 +"2042-01-01","New Year's Day","UM",2042 +"2042-01-20","Martin Luther King Jr. Day","UM",2042 +"2042-02-17","Washington's Birthday","UM",2042 +"2042-05-26","Memorial Day","UM",2042 +"2042-06-19","Juneteenth National Independence Day","UM",2042 +"2042-07-04","Independence Day","UM",2042 +"2042-09-01","Labor Day","UM",2042 +"2042-10-13","Columbus Day","UM",2042 +"2042-11-11","Veterans Day","UM",2042 +"2042-11-27","Thanksgiving","UM",2042 +"2042-12-25","Christmas Day","UM",2042 +"2043-01-01","New Year's Day","UM",2043 +"2043-01-19","Martin Luther King Jr. Day","UM",2043 +"2043-02-16","Washington's Birthday","UM",2043 +"2043-05-25","Memorial Day","UM",2043 +"2043-06-19","Juneteenth National Independence Day","UM",2043 +"2043-07-03","Independence Day (Observed)","UM",2043 +"2043-07-04","Independence Day","UM",2043 +"2043-09-07","Labor Day","UM",2043 +"2043-10-12","Columbus Day","UM",2043 +"2043-11-11","Veterans Day","UM",2043 +"2043-11-26","Thanksgiving","UM",2043 +"2043-12-25","Christmas Day","UM",2043 +"2044-01-01","New Year's Day","UM",2044 +"2044-01-18","Martin Luther King Jr. Day","UM",2044 +"2044-02-15","Washington's Birthday","UM",2044 +"2044-05-30","Memorial Day","UM",2044 +"2044-06-19","Juneteenth National Independence Day","UM",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","UM",2044 +"2044-07-04","Independence Day","UM",2044 +"2044-09-05","Labor Day","UM",2044 +"2044-10-10","Columbus Day","UM",2044 +"2044-11-11","Veterans Day","UM",2044 +"2044-11-24","Thanksgiving","UM",2044 +"2044-12-25","Christmas Day","UM",2044 +"2044-12-26","Christmas Day (Observed)","UM",2044 +"1995-01-01","New Year's Day","US",1995 +"1995-01-02","New Year's Day (Observed)","US",1995 +"1995-01-16","Martin Luther King Jr. Day","US",1995 +"1995-02-20","Washington's Birthday","US",1995 +"1995-05-29","Memorial Day","US",1995 +"1995-07-04","Independence Day","US",1995 +"1995-09-04","Labor Day","US",1995 +"1995-10-09","Columbus Day","US",1995 +"1995-11-10","Veterans Day (Observed)","US",1995 +"1995-11-11","Veterans Day","US",1995 +"1995-11-23","Thanksgiving","US",1995 +"1995-12-25","Christmas Day","US",1995 +"1996-01-01","New Year's Day","US",1996 +"1996-01-15","Martin Luther King Jr. Day","US",1996 +"1996-02-19","Washington's Birthday","US",1996 +"1996-05-27","Memorial Day","US",1996 +"1996-07-04","Independence Day","US",1996 +"1996-09-02","Labor Day","US",1996 +"1996-10-14","Columbus Day","US",1996 +"1996-11-11","Veterans Day","US",1996 +"1996-11-28","Thanksgiving","US",1996 +"1996-12-25","Christmas Day","US",1996 +"1997-01-01","New Year's Day","US",1997 +"1997-01-20","Martin Luther King Jr. Day","US",1997 +"1997-02-17","Washington's Birthday","US",1997 +"1997-05-26","Memorial Day","US",1997 +"1997-07-04","Independence Day","US",1997 +"1997-09-01","Labor Day","US",1997 +"1997-10-13","Columbus Day","US",1997 +"1997-11-11","Veterans Day","US",1997 +"1997-11-27","Thanksgiving","US",1997 +"1997-12-25","Christmas Day","US",1997 +"1998-01-01","New Year's Day","US",1998 +"1998-01-19","Martin Luther King Jr. Day","US",1998 +"1998-02-16","Washington's Birthday","US",1998 +"1998-05-25","Memorial Day","US",1998 +"1998-07-03","Independence Day (Observed)","US",1998 +"1998-07-04","Independence Day","US",1998 +"1998-09-07","Labor Day","US",1998 +"1998-10-12","Columbus Day","US",1998 +"1998-11-11","Veterans Day","US",1998 +"1998-11-26","Thanksgiving","US",1998 +"1998-12-25","Christmas Day","US",1998 +"1999-01-01","New Year's Day","US",1999 +"1999-01-18","Martin Luther King Jr. Day","US",1999 +"1999-02-15","Washington's Birthday","US",1999 +"1999-05-31","Memorial Day","US",1999 +"1999-07-04","Independence Day","US",1999 +"1999-07-05","Independence Day (Observed)","US",1999 +"1999-09-06","Labor Day","US",1999 +"1999-10-11","Columbus Day","US",1999 +"1999-11-11","Veterans Day","US",1999 +"1999-11-25","Thanksgiving","US",1999 +"1999-12-24","Christmas Day (Observed)","US",1999 +"1999-12-25","Christmas Day","US",1999 +"1999-12-31","New Year's Day (Observed)","US",1999 +"2000-01-01","New Year's Day","US",2000 +"2000-01-17","Martin Luther King Jr. Day","US",2000 +"2000-02-21","Washington's Birthday","US",2000 +"2000-05-29","Memorial Day","US",2000 +"2000-07-04","Independence Day","US",2000 +"2000-09-04","Labor Day","US",2000 +"2000-10-09","Columbus Day","US",2000 +"2000-11-10","Veterans Day (Observed)","US",2000 +"2000-11-11","Veterans Day","US",2000 +"2000-11-23","Thanksgiving","US",2000 +"2000-12-25","Christmas Day","US",2000 +"2001-01-01","New Year's Day","US",2001 +"2001-01-15","Martin Luther King Jr. Day","US",2001 +"2001-02-19","Washington's Birthday","US",2001 +"2001-05-28","Memorial Day","US",2001 +"2001-07-04","Independence Day","US",2001 +"2001-09-03","Labor Day","US",2001 +"2001-10-08","Columbus Day","US",2001 +"2001-11-11","Veterans Day","US",2001 +"2001-11-12","Veterans Day (Observed)","US",2001 +"2001-11-22","Thanksgiving","US",2001 +"2001-12-25","Christmas Day","US",2001 +"2002-01-01","New Year's Day","US",2002 +"2002-01-21","Martin Luther King Jr. Day","US",2002 +"2002-02-18","Washington's Birthday","US",2002 +"2002-05-27","Memorial Day","US",2002 +"2002-07-04","Independence Day","US",2002 +"2002-09-02","Labor Day","US",2002 +"2002-10-14","Columbus Day","US",2002 +"2002-11-11","Veterans Day","US",2002 +"2002-11-28","Thanksgiving","US",2002 +"2002-12-25","Christmas Day","US",2002 +"2003-01-01","New Year's Day","US",2003 +"2003-01-20","Martin Luther King Jr. Day","US",2003 +"2003-02-17","Washington's Birthday","US",2003 +"2003-05-26","Memorial Day","US",2003 +"2003-07-04","Independence Day","US",2003 +"2003-09-01","Labor Day","US",2003 +"2003-10-13","Columbus Day","US",2003 +"2003-11-11","Veterans Day","US",2003 +"2003-11-27","Thanksgiving","US",2003 +"2003-12-25","Christmas Day","US",2003 +"2004-01-01","New Year's Day","US",2004 +"2004-01-19","Martin Luther King Jr. Day","US",2004 +"2004-02-16","Washington's Birthday","US",2004 +"2004-05-31","Memorial Day","US",2004 +"2004-07-04","Independence Day","US",2004 +"2004-07-05","Independence Day (Observed)","US",2004 +"2004-09-06","Labor Day","US",2004 +"2004-10-11","Columbus Day","US",2004 +"2004-11-11","Veterans Day","US",2004 +"2004-11-25","Thanksgiving","US",2004 +"2004-12-24","Christmas Day (Observed)","US",2004 +"2004-12-25","Christmas Day","US",2004 +"2004-12-31","New Year's Day (Observed)","US",2004 +"2005-01-01","New Year's Day","US",2005 +"2005-01-17","Martin Luther King Jr. Day","US",2005 +"2005-02-21","Washington's Birthday","US",2005 +"2005-05-30","Memorial Day","US",2005 +"2005-07-04","Independence Day","US",2005 +"2005-09-05","Labor Day","US",2005 +"2005-10-10","Columbus Day","US",2005 +"2005-11-11","Veterans Day","US",2005 +"2005-11-24","Thanksgiving","US",2005 +"2005-12-25","Christmas Day","US",2005 +"2005-12-26","Christmas Day (Observed)","US",2005 +"2006-01-01","New Year's Day","US",2006 +"2006-01-02","New Year's Day (Observed)","US",2006 +"2006-01-16","Martin Luther King Jr. Day","US",2006 +"2006-02-20","Washington's Birthday","US",2006 +"2006-05-29","Memorial Day","US",2006 +"2006-07-04","Independence Day","US",2006 +"2006-09-04","Labor Day","US",2006 +"2006-10-09","Columbus Day","US",2006 +"2006-11-10","Veterans Day (Observed)","US",2006 +"2006-11-11","Veterans Day","US",2006 +"2006-11-23","Thanksgiving","US",2006 +"2006-12-25","Christmas Day","US",2006 +"2007-01-01","New Year's Day","US",2007 +"2007-01-15","Martin Luther King Jr. Day","US",2007 +"2007-02-19","Washington's Birthday","US",2007 +"2007-05-28","Memorial Day","US",2007 +"2007-07-04","Independence Day","US",2007 +"2007-09-03","Labor Day","US",2007 +"2007-10-08","Columbus Day","US",2007 +"2007-11-11","Veterans Day","US",2007 +"2007-11-12","Veterans Day (Observed)","US",2007 +"2007-11-22","Thanksgiving","US",2007 +"2007-12-25","Christmas Day","US",2007 +"2008-01-01","New Year's Day","US",2008 +"2008-01-21","Martin Luther King Jr. Day","US",2008 +"2008-02-18","Washington's Birthday","US",2008 +"2008-05-26","Memorial Day","US",2008 +"2008-07-04","Independence Day","US",2008 +"2008-09-01","Labor Day","US",2008 +"2008-10-13","Columbus Day","US",2008 +"2008-11-11","Veterans Day","US",2008 +"2008-11-27","Thanksgiving","US",2008 +"2008-12-25","Christmas Day","US",2008 +"2009-01-01","New Year's Day","US",2009 +"2009-01-19","Martin Luther King Jr. Day","US",2009 +"2009-02-16","Washington's Birthday","US",2009 +"2009-05-25","Memorial Day","US",2009 +"2009-07-03","Independence Day (Observed)","US",2009 +"2009-07-04","Independence Day","US",2009 +"2009-09-07","Labor Day","US",2009 +"2009-10-12","Columbus Day","US",2009 +"2009-11-11","Veterans Day","US",2009 +"2009-11-26","Thanksgiving","US",2009 +"2009-12-25","Christmas Day","US",2009 +"2010-01-01","New Year's Day","US",2010 +"2010-01-18","Martin Luther King Jr. Day","US",2010 +"2010-02-15","Washington's Birthday","US",2010 +"2010-05-31","Memorial Day","US",2010 +"2010-07-04","Independence Day","US",2010 +"2010-07-05","Independence Day (Observed)","US",2010 +"2010-09-06","Labor Day","US",2010 +"2010-10-11","Columbus Day","US",2010 +"2010-11-11","Veterans Day","US",2010 +"2010-11-25","Thanksgiving","US",2010 +"2010-12-24","Christmas Day (Observed)","US",2010 +"2010-12-25","Christmas Day","US",2010 +"2010-12-31","New Year's Day (Observed)","US",2010 +"2011-01-01","New Year's Day","US",2011 +"2011-01-17","Martin Luther King Jr. Day","US",2011 +"2011-02-21","Washington's Birthday","US",2011 +"2011-05-30","Memorial Day","US",2011 +"2011-07-04","Independence Day","US",2011 +"2011-09-05","Labor Day","US",2011 +"2011-10-10","Columbus Day","US",2011 +"2011-11-11","Veterans Day","US",2011 +"2011-11-24","Thanksgiving","US",2011 +"2011-12-25","Christmas Day","US",2011 +"2011-12-26","Christmas Day (Observed)","US",2011 +"2012-01-01","New Year's Day","US",2012 +"2012-01-02","New Year's Day (Observed)","US",2012 +"2012-01-16","Martin Luther King Jr. Day","US",2012 +"2012-02-20","Washington's Birthday","US",2012 +"2012-05-28","Memorial Day","US",2012 +"2012-07-04","Independence Day","US",2012 +"2012-09-03","Labor Day","US",2012 +"2012-10-08","Columbus Day","US",2012 +"2012-11-11","Veterans Day","US",2012 +"2012-11-12","Veterans Day (Observed)","US",2012 +"2012-11-22","Thanksgiving","US",2012 +"2012-12-25","Christmas Day","US",2012 +"2013-01-01","New Year's Day","US",2013 +"2013-01-21","Martin Luther King Jr. Day","US",2013 +"2013-02-18","Washington's Birthday","US",2013 +"2013-05-27","Memorial Day","US",2013 +"2013-07-04","Independence Day","US",2013 +"2013-09-02","Labor Day","US",2013 +"2013-10-14","Columbus Day","US",2013 +"2013-11-11","Veterans Day","US",2013 +"2013-11-28","Thanksgiving","US",2013 +"2013-12-25","Christmas Day","US",2013 +"2014-01-01","New Year's Day","US",2014 +"2014-01-20","Martin Luther King Jr. Day","US",2014 +"2014-02-17","Washington's Birthday","US",2014 +"2014-05-26","Memorial Day","US",2014 +"2014-07-04","Independence Day","US",2014 +"2014-09-01","Labor Day","US",2014 +"2014-10-13","Columbus Day","US",2014 +"2014-11-11","Veterans Day","US",2014 +"2014-11-27","Thanksgiving","US",2014 +"2014-12-25","Christmas Day","US",2014 +"2015-01-01","New Year's Day","US",2015 +"2015-01-19","Martin Luther King Jr. Day","US",2015 +"2015-02-16","Washington's Birthday","US",2015 +"2015-05-25","Memorial Day","US",2015 +"2015-07-03","Independence Day (Observed)","US",2015 +"2015-07-04","Independence Day","US",2015 +"2015-09-07","Labor Day","US",2015 +"2015-10-12","Columbus Day","US",2015 +"2015-11-11","Veterans Day","US",2015 +"2015-11-26","Thanksgiving","US",2015 +"2015-12-25","Christmas Day","US",2015 +"2016-01-01","New Year's Day","US",2016 +"2016-01-18","Martin Luther King Jr. Day","US",2016 +"2016-02-15","Washington's Birthday","US",2016 +"2016-05-30","Memorial Day","US",2016 +"2016-07-04","Independence Day","US",2016 +"2016-09-05","Labor Day","US",2016 +"2016-10-10","Columbus Day","US",2016 +"2016-11-11","Veterans Day","US",2016 +"2016-11-24","Thanksgiving","US",2016 +"2016-12-25","Christmas Day","US",2016 +"2016-12-26","Christmas Day (Observed)","US",2016 +"2017-01-01","New Year's Day","US",2017 +"2017-01-02","New Year's Day (Observed)","US",2017 +"2017-01-16","Martin Luther King Jr. Day","US",2017 +"2017-02-20","Washington's Birthday","US",2017 +"2017-05-29","Memorial Day","US",2017 +"2017-07-04","Independence Day","US",2017 +"2017-09-04","Labor Day","US",2017 +"2017-10-09","Columbus Day","US",2017 +"2017-11-10","Veterans Day (Observed)","US",2017 +"2017-11-11","Veterans Day","US",2017 +"2017-11-23","Thanksgiving","US",2017 +"2017-12-25","Christmas Day","US",2017 +"2018-01-01","New Year's Day","US",2018 +"2018-01-15","Martin Luther King Jr. Day","US",2018 +"2018-02-19","Washington's Birthday","US",2018 +"2018-05-28","Memorial Day","US",2018 +"2018-07-04","Independence Day","US",2018 +"2018-09-03","Labor Day","US",2018 +"2018-10-08","Columbus Day","US",2018 +"2018-11-11","Veterans Day","US",2018 +"2018-11-12","Veterans Day (Observed)","US",2018 +"2018-11-22","Thanksgiving","US",2018 +"2018-12-25","Christmas Day","US",2018 +"2019-01-01","New Year's Day","US",2019 +"2019-01-21","Martin Luther King Jr. Day","US",2019 +"2019-02-18","Washington's Birthday","US",2019 +"2019-05-27","Memorial Day","US",2019 +"2019-07-04","Independence Day","US",2019 +"2019-09-02","Labor Day","US",2019 +"2019-10-14","Columbus Day","US",2019 +"2019-11-11","Veterans Day","US",2019 +"2019-11-28","Thanksgiving","US",2019 +"2019-12-25","Christmas Day","US",2019 +"2020-01-01","New Year's Day","US",2020 +"2020-01-20","Martin Luther King Jr. Day","US",2020 +"2020-02-17","Washington's Birthday","US",2020 +"2020-05-25","Memorial Day","US",2020 +"2020-07-03","Independence Day (Observed)","US",2020 +"2020-07-04","Independence Day","US",2020 +"2020-09-07","Labor Day","US",2020 +"2020-10-12","Columbus Day","US",2020 +"2020-11-11","Veterans Day","US",2020 +"2020-11-26","Thanksgiving","US",2020 +"2020-12-25","Christmas Day","US",2020 +"2021-01-01","New Year's Day","US",2021 +"2021-01-18","Martin Luther King Jr. Day","US",2021 +"2021-02-15","Washington's Birthday","US",2021 +"2021-05-31","Memorial Day","US",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","US",2021 +"2021-06-19","Juneteenth National Independence Day","US",2021 +"2021-07-04","Independence Day","US",2021 +"2021-07-05","Independence Day (Observed)","US",2021 +"2021-09-06","Labor Day","US",2021 +"2021-10-11","Columbus Day","US",2021 +"2021-11-11","Veterans Day","US",2021 +"2021-11-25","Thanksgiving","US",2021 +"2021-12-24","Christmas Day (Observed)","US",2021 +"2021-12-25","Christmas Day","US",2021 +"2021-12-31","New Year's Day (Observed)","US",2021 +"2022-01-01","New Year's Day","US",2022 +"2022-01-17","Martin Luther King Jr. Day","US",2022 +"2022-02-21","Washington's Birthday","US",2022 +"2022-05-30","Memorial Day","US",2022 +"2022-06-19","Juneteenth National Independence Day","US",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","US",2022 +"2022-07-04","Independence Day","US",2022 +"2022-09-05","Labor Day","US",2022 +"2022-10-10","Columbus Day","US",2022 +"2022-11-11","Veterans Day","US",2022 +"2022-11-24","Thanksgiving","US",2022 +"2022-12-25","Christmas Day","US",2022 +"2022-12-26","Christmas Day (Observed)","US",2022 +"2023-01-01","New Year's Day","US",2023 +"2023-01-02","New Year's Day (Observed)","US",2023 +"2023-01-16","Martin Luther King Jr. Day","US",2023 +"2023-02-20","Washington's Birthday","US",2023 +"2023-05-29","Memorial Day","US",2023 +"2023-06-19","Juneteenth National Independence Day","US",2023 +"2023-07-04","Independence Day","US",2023 +"2023-09-04","Labor Day","US",2023 +"2023-10-09","Columbus Day","US",2023 +"2023-11-10","Veterans Day (Observed)","US",2023 +"2023-11-11","Veterans Day","US",2023 +"2023-11-23","Thanksgiving","US",2023 +"2023-12-25","Christmas Day","US",2023 +"2024-01-01","New Year's Day","US",2024 +"2024-01-15","Martin Luther King Jr. Day","US",2024 +"2024-02-19","Washington's Birthday","US",2024 +"2024-05-27","Memorial Day","US",2024 +"2024-06-19","Juneteenth National Independence Day","US",2024 +"2024-07-04","Independence Day","US",2024 +"2024-09-02","Labor Day","US",2024 +"2024-10-14","Columbus Day","US",2024 +"2024-11-11","Veterans Day","US",2024 +"2024-11-28","Thanksgiving","US",2024 +"2024-12-25","Christmas Day","US",2024 +"2025-01-01","New Year's Day","US",2025 +"2025-01-20","Martin Luther King Jr. Day","US",2025 +"2025-02-17","Washington's Birthday","US",2025 +"2025-05-26","Memorial Day","US",2025 +"2025-06-19","Juneteenth National Independence Day","US",2025 +"2025-07-04","Independence Day","US",2025 +"2025-09-01","Labor Day","US",2025 +"2025-10-13","Columbus Day","US",2025 +"2025-11-11","Veterans Day","US",2025 +"2025-11-27","Thanksgiving","US",2025 +"2025-12-25","Christmas Day","US",2025 +"2026-01-01","New Year's Day","US",2026 +"2026-01-19","Martin Luther King Jr. Day","US",2026 +"2026-02-16","Washington's Birthday","US",2026 +"2026-05-25","Memorial Day","US",2026 +"2026-06-19","Juneteenth National Independence Day","US",2026 +"2026-07-03","Independence Day (Observed)","US",2026 +"2026-07-04","Independence Day","US",2026 +"2026-09-07","Labor Day","US",2026 +"2026-10-12","Columbus Day","US",2026 +"2026-11-11","Veterans Day","US",2026 +"2026-11-26","Thanksgiving","US",2026 +"2026-12-25","Christmas Day","US",2026 +"2027-01-01","New Year's Day","US",2027 +"2027-01-18","Martin Luther King Jr. Day","US",2027 +"2027-02-15","Washington's Birthday","US",2027 +"2027-05-31","Memorial Day","US",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","US",2027 +"2027-06-19","Juneteenth National Independence Day","US",2027 +"2027-07-04","Independence Day","US",2027 +"2027-07-05","Independence Day (Observed)","US",2027 +"2027-09-06","Labor Day","US",2027 +"2027-10-11","Columbus Day","US",2027 +"2027-11-11","Veterans Day","US",2027 +"2027-11-25","Thanksgiving","US",2027 +"2027-12-24","Christmas Day (Observed)","US",2027 +"2027-12-25","Christmas Day","US",2027 +"2027-12-31","New Year's Day (Observed)","US",2027 +"2028-01-01","New Year's Day","US",2028 +"2028-01-17","Martin Luther King Jr. Day","US",2028 +"2028-02-21","Washington's Birthday","US",2028 +"2028-05-29","Memorial Day","US",2028 +"2028-06-19","Juneteenth National Independence Day","US",2028 +"2028-07-04","Independence Day","US",2028 +"2028-09-04","Labor Day","US",2028 +"2028-10-09","Columbus Day","US",2028 +"2028-11-10","Veterans Day (Observed)","US",2028 +"2028-11-11","Veterans Day","US",2028 +"2028-11-23","Thanksgiving","US",2028 +"2028-12-25","Christmas Day","US",2028 +"2029-01-01","New Year's Day","US",2029 +"2029-01-15","Martin Luther King Jr. Day","US",2029 +"2029-02-19","Washington's Birthday","US",2029 +"2029-05-28","Memorial Day","US",2029 +"2029-06-19","Juneteenth National Independence Day","US",2029 +"2029-07-04","Independence Day","US",2029 +"2029-09-03","Labor Day","US",2029 +"2029-10-08","Columbus Day","US",2029 +"2029-11-11","Veterans Day","US",2029 +"2029-11-12","Veterans Day (Observed)","US",2029 +"2029-11-22","Thanksgiving","US",2029 +"2029-12-25","Christmas Day","US",2029 +"2030-01-01","New Year's Day","US",2030 +"2030-01-21","Martin Luther King Jr. Day","US",2030 +"2030-02-18","Washington's Birthday","US",2030 +"2030-05-27","Memorial Day","US",2030 +"2030-06-19","Juneteenth National Independence Day","US",2030 +"2030-07-04","Independence Day","US",2030 +"2030-09-02","Labor Day","US",2030 +"2030-10-14","Columbus Day","US",2030 +"2030-11-11","Veterans Day","US",2030 +"2030-11-28","Thanksgiving","US",2030 +"2030-12-25","Christmas Day","US",2030 +"2031-01-01","New Year's Day","US",2031 +"2031-01-20","Martin Luther King Jr. Day","US",2031 +"2031-02-17","Washington's Birthday","US",2031 +"2031-05-26","Memorial Day","US",2031 +"2031-06-19","Juneteenth National Independence Day","US",2031 +"2031-07-04","Independence Day","US",2031 +"2031-09-01","Labor Day","US",2031 +"2031-10-13","Columbus Day","US",2031 +"2031-11-11","Veterans Day","US",2031 +"2031-11-27","Thanksgiving","US",2031 +"2031-12-25","Christmas Day","US",2031 +"2032-01-01","New Year's Day","US",2032 +"2032-01-19","Martin Luther King Jr. Day","US",2032 +"2032-02-16","Washington's Birthday","US",2032 +"2032-05-31","Memorial Day","US",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","US",2032 +"2032-06-19","Juneteenth National Independence Day","US",2032 +"2032-07-04","Independence Day","US",2032 +"2032-07-05","Independence Day (Observed)","US",2032 +"2032-09-06","Labor Day","US",2032 +"2032-10-11","Columbus Day","US",2032 +"2032-11-11","Veterans Day","US",2032 +"2032-11-25","Thanksgiving","US",2032 +"2032-12-24","Christmas Day (Observed)","US",2032 +"2032-12-25","Christmas Day","US",2032 +"2032-12-31","New Year's Day (Observed)","US",2032 +"2033-01-01","New Year's Day","US",2033 +"2033-01-17","Martin Luther King Jr. Day","US",2033 +"2033-02-21","Washington's Birthday","US",2033 +"2033-05-30","Memorial Day","US",2033 +"2033-06-19","Juneteenth National Independence Day","US",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","US",2033 +"2033-07-04","Independence Day","US",2033 +"2033-09-05","Labor Day","US",2033 +"2033-10-10","Columbus Day","US",2033 +"2033-11-11","Veterans Day","US",2033 +"2033-11-24","Thanksgiving","US",2033 +"2033-12-25","Christmas Day","US",2033 +"2033-12-26","Christmas Day (Observed)","US",2033 +"2034-01-01","New Year's Day","US",2034 +"2034-01-02","New Year's Day (Observed)","US",2034 +"2034-01-16","Martin Luther King Jr. Day","US",2034 +"2034-02-20","Washington's Birthday","US",2034 +"2034-05-29","Memorial Day","US",2034 +"2034-06-19","Juneteenth National Independence Day","US",2034 +"2034-07-04","Independence Day","US",2034 +"2034-09-04","Labor Day","US",2034 +"2034-10-09","Columbus Day","US",2034 +"2034-11-10","Veterans Day (Observed)","US",2034 +"2034-11-11","Veterans Day","US",2034 +"2034-11-23","Thanksgiving","US",2034 +"2034-12-25","Christmas Day","US",2034 +"2035-01-01","New Year's Day","US",2035 +"2035-01-15","Martin Luther King Jr. Day","US",2035 +"2035-02-19","Washington's Birthday","US",2035 +"2035-05-28","Memorial Day","US",2035 +"2035-06-19","Juneteenth National Independence Day","US",2035 +"2035-07-04","Independence Day","US",2035 +"2035-09-03","Labor Day","US",2035 +"2035-10-08","Columbus Day","US",2035 +"2035-11-11","Veterans Day","US",2035 +"2035-11-12","Veterans Day (Observed)","US",2035 +"2035-11-22","Thanksgiving","US",2035 +"2035-12-25","Christmas Day","US",2035 +"2036-01-01","New Year's Day","US",2036 +"2036-01-21","Martin Luther King Jr. Day","US",2036 +"2036-02-18","Washington's Birthday","US",2036 +"2036-05-26","Memorial Day","US",2036 +"2036-06-19","Juneteenth National Independence Day","US",2036 +"2036-07-04","Independence Day","US",2036 +"2036-09-01","Labor Day","US",2036 +"2036-10-13","Columbus Day","US",2036 +"2036-11-11","Veterans Day","US",2036 +"2036-11-27","Thanksgiving","US",2036 +"2036-12-25","Christmas Day","US",2036 +"2037-01-01","New Year's Day","US",2037 +"2037-01-19","Martin Luther King Jr. Day","US",2037 +"2037-02-16","Washington's Birthday","US",2037 +"2037-05-25","Memorial Day","US",2037 +"2037-06-19","Juneteenth National Independence Day","US",2037 +"2037-07-03","Independence Day (Observed)","US",2037 +"2037-07-04","Independence Day","US",2037 +"2037-09-07","Labor Day","US",2037 +"2037-10-12","Columbus Day","US",2037 +"2037-11-11","Veterans Day","US",2037 +"2037-11-26","Thanksgiving","US",2037 +"2037-12-25","Christmas Day","US",2037 +"2038-01-01","New Year's Day","US",2038 +"2038-01-18","Martin Luther King Jr. Day","US",2038 +"2038-02-15","Washington's Birthday","US",2038 +"2038-05-31","Memorial Day","US",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","US",2038 +"2038-06-19","Juneteenth National Independence Day","US",2038 +"2038-07-04","Independence Day","US",2038 +"2038-07-05","Independence Day (Observed)","US",2038 +"2038-09-06","Labor Day","US",2038 +"2038-10-11","Columbus Day","US",2038 +"2038-11-11","Veterans Day","US",2038 +"2038-11-25","Thanksgiving","US",2038 +"2038-12-24","Christmas Day (Observed)","US",2038 +"2038-12-25","Christmas Day","US",2038 +"2038-12-31","New Year's Day (Observed)","US",2038 +"2039-01-01","New Year's Day","US",2039 +"2039-01-17","Martin Luther King Jr. Day","US",2039 +"2039-02-21","Washington's Birthday","US",2039 +"2039-05-30","Memorial Day","US",2039 +"2039-06-19","Juneteenth National Independence Day","US",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","US",2039 +"2039-07-04","Independence Day","US",2039 +"2039-09-05","Labor Day","US",2039 +"2039-10-10","Columbus Day","US",2039 +"2039-11-11","Veterans Day","US",2039 +"2039-11-24","Thanksgiving","US",2039 +"2039-12-25","Christmas Day","US",2039 +"2039-12-26","Christmas Day (Observed)","US",2039 +"2040-01-01","New Year's Day","US",2040 +"2040-01-02","New Year's Day (Observed)","US",2040 +"2040-01-16","Martin Luther King Jr. Day","US",2040 +"2040-02-20","Washington's Birthday","US",2040 +"2040-05-28","Memorial Day","US",2040 +"2040-06-19","Juneteenth National Independence Day","US",2040 +"2040-07-04","Independence Day","US",2040 +"2040-09-03","Labor Day","US",2040 +"2040-10-08","Columbus Day","US",2040 +"2040-11-11","Veterans Day","US",2040 +"2040-11-12","Veterans Day (Observed)","US",2040 +"2040-11-22","Thanksgiving","US",2040 +"2040-12-25","Christmas Day","US",2040 +"2041-01-01","New Year's Day","US",2041 +"2041-01-21","Martin Luther King Jr. Day","US",2041 +"2041-02-18","Washington's Birthday","US",2041 +"2041-05-27","Memorial Day","US",2041 +"2041-06-19","Juneteenth National Independence Day","US",2041 +"2041-07-04","Independence Day","US",2041 +"2041-09-02","Labor Day","US",2041 +"2041-10-14","Columbus Day","US",2041 +"2041-11-11","Veterans Day","US",2041 +"2041-11-28","Thanksgiving","US",2041 +"2041-12-25","Christmas Day","US",2041 +"2042-01-01","New Year's Day","US",2042 +"2042-01-20","Martin Luther King Jr. Day","US",2042 +"2042-02-17","Washington's Birthday","US",2042 +"2042-05-26","Memorial Day","US",2042 +"2042-06-19","Juneteenth National Independence Day","US",2042 +"2042-07-04","Independence Day","US",2042 +"2042-09-01","Labor Day","US",2042 +"2042-10-13","Columbus Day","US",2042 +"2042-11-11","Veterans Day","US",2042 +"2042-11-27","Thanksgiving","US",2042 +"2042-12-25","Christmas Day","US",2042 +"2043-01-01","New Year's Day","US",2043 +"2043-01-19","Martin Luther King Jr. Day","US",2043 +"2043-02-16","Washington's Birthday","US",2043 +"2043-05-25","Memorial Day","US",2043 +"2043-06-19","Juneteenth National Independence Day","US",2043 +"2043-07-03","Independence Day (Observed)","US",2043 +"2043-07-04","Independence Day","US",2043 +"2043-09-07","Labor Day","US",2043 +"2043-10-12","Columbus Day","US",2043 +"2043-11-11","Veterans Day","US",2043 +"2043-11-26","Thanksgiving","US",2043 +"2043-12-25","Christmas Day","US",2043 +"2044-01-01","New Year's Day","US",2044 +"2044-01-18","Martin Luther King Jr. Day","US",2044 +"2044-02-15","Washington's Birthday","US",2044 +"2044-05-30","Memorial Day","US",2044 +"2044-06-19","Juneteenth National Independence Day","US",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","US",2044 +"2044-07-04","Independence Day","US",2044 +"2044-09-05","Labor Day","US",2044 +"2044-10-10","Columbus Day","US",2044 +"2044-11-11","Veterans Day","US",2044 +"2044-11-24","Thanksgiving","US",2044 +"2044-12-25","Christmas Day","US",2044 +"2044-12-26","Christmas Day (Observed)","US",2044 +"1995-01-01","New Year's Day","UY",1995 +"1995-01-06","Children's Day","UY",1995 +"1995-02-27","Carnival Day","UY",1995 +"1995-02-28","Carnival Day","UY",1995 +"1995-04-13","Maundy Thursday","UY",1995 +"1995-04-14","Good Friday","UY",1995 +"1995-04-16","Easter Day","UY",1995 +"1995-04-17","Landing of the 33 Patriots","UY",1995 +"1995-05-01","International Workers' Day","UY",1995 +"1995-05-22","Battle of Las Piedras","UY",1995 +"1995-06-19","Birthday of Jose Gervasio Artigas","UY",1995 +"1995-07-18","Constitution Day","UY",1995 +"1995-08-25","Independence Day","UY",1995 +"1995-10-16","Respect for Cultural Diversity Day","UY",1995 +"1995-11-02","All Souls' Day","UY",1995 +"1995-12-25","Day of the Family","UY",1995 +"1996-01-01","New Year's Day","UY",1996 +"1996-01-06","Children's Day","UY",1996 +"1996-02-19","Carnival Day","UY",1996 +"1996-02-20","Carnival Day","UY",1996 +"1996-04-04","Maundy Thursday","UY",1996 +"1996-04-05","Good Friday","UY",1996 +"1996-04-07","Easter Day","UY",1996 +"1996-04-22","Landing of the 33 Patriots","UY",1996 +"1996-05-01","International Workers' Day","UY",1996 +"1996-05-18","Battle of Las Piedras","UY",1996 +"1996-06-19","Birthday of Jose Gervasio Artigas","UY",1996 +"1996-07-18","Constitution Day","UY",1996 +"1996-08-25","Independence Day","UY",1996 +"1996-10-12","Respect for Cultural Diversity Day","UY",1996 +"1996-11-02","All Souls' Day","UY",1996 +"1996-12-25","Day of the Family","UY",1996 +"1997-01-01","New Year's Day","UY",1997 +"1997-01-06","Children's Day","UY",1997 +"1997-02-10","Carnival Day","UY",1997 +"1997-02-11","Carnival Day","UY",1997 +"1997-03-27","Maundy Thursday","UY",1997 +"1997-03-28","Good Friday","UY",1997 +"1997-03-30","Easter Day","UY",1997 +"1997-04-19","Landing of the 33 Patriots","UY",1997 +"1997-05-01","International Workers' Day","UY",1997 +"1997-05-18","Battle of Las Piedras","UY",1997 +"1997-06-19","Birthday of Jose Gervasio Artigas","UY",1997 +"1997-07-18","Constitution Day","UY",1997 +"1997-08-25","Independence Day","UY",1997 +"1997-10-12","Respect for Cultural Diversity Day","UY",1997 +"1997-11-02","All Souls' Day","UY",1997 +"1997-12-25","Day of the Family","UY",1997 +"1998-01-01","New Year's Day","UY",1998 +"1998-01-06","Children's Day","UY",1998 +"1998-02-23","Carnival Day","UY",1998 +"1998-02-24","Carnival Day","UY",1998 +"1998-04-09","Maundy Thursday","UY",1998 +"1998-04-10","Good Friday","UY",1998 +"1998-04-12","Easter Day","UY",1998 +"1998-04-19","Landing of the 33 Patriots","UY",1998 +"1998-05-01","International Workers' Day","UY",1998 +"1998-05-18","Battle of Las Piedras","UY",1998 +"1998-06-19","Birthday of Jose Gervasio Artigas","UY",1998 +"1998-07-18","Constitution Day","UY",1998 +"1998-08-25","Independence Day","UY",1998 +"1998-10-12","Respect for Cultural Diversity Day","UY",1998 +"1998-11-02","All Souls' Day","UY",1998 +"1998-12-25","Day of the Family","UY",1998 +"1999-01-01","New Year's Day","UY",1999 +"1999-01-06","Children's Day","UY",1999 +"1999-02-15","Carnival Day","UY",1999 +"1999-02-16","Carnival Day","UY",1999 +"1999-04-01","Maundy Thursday","UY",1999 +"1999-04-02","Good Friday","UY",1999 +"1999-04-04","Easter Day","UY",1999 +"1999-04-19","Landing of the 33 Patriots","UY",1999 +"1999-05-01","International Workers' Day","UY",1999 +"1999-05-17","Battle of Las Piedras","UY",1999 +"1999-06-19","Birthday of Jose Gervasio Artigas","UY",1999 +"1999-07-18","Constitution Day","UY",1999 +"1999-08-25","Independence Day","UY",1999 +"1999-10-11","Respect for Cultural Diversity Day","UY",1999 +"1999-11-02","All Souls' Day","UY",1999 +"1999-12-25","Day of the Family","UY",1999 +"2000-01-01","New Year's Day","UY",2000 +"2000-01-06","Children's Day","UY",2000 +"2000-03-06","Carnival Day","UY",2000 +"2000-03-07","Carnival Day","UY",2000 +"2000-04-17","Landing of the 33 Patriots","UY",2000 +"2000-04-20","Maundy Thursday","UY",2000 +"2000-04-21","Good Friday","UY",2000 +"2000-04-23","Easter Day","UY",2000 +"2000-05-01","International Workers' Day","UY",2000 +"2000-05-22","Battle of Las Piedras","UY",2000 +"2000-06-19","Birthday of Jose Gervasio Artigas","UY",2000 +"2000-07-18","Constitution Day","UY",2000 +"2000-08-25","Independence Day","UY",2000 +"2000-10-16","Respect for Cultural Diversity Day","UY",2000 +"2000-11-02","All Souls' Day","UY",2000 +"2000-12-25","Day of the Family","UY",2000 +"2001-01-01","New Year's Day","UY",2001 +"2001-01-06","Children's Day","UY",2001 +"2001-02-26","Carnival Day","UY",2001 +"2001-02-27","Carnival Day","UY",2001 +"2001-04-12","Maundy Thursday","UY",2001 +"2001-04-13","Good Friday","UY",2001 +"2001-04-15","Easter Day","UY",2001 +"2001-04-23","Landing of the 33 Patriots","UY",2001 +"2001-05-01","International Workers' Day","UY",2001 +"2001-05-21","Battle of Las Piedras","UY",2001 +"2001-06-19","Birthday of Jose Gervasio Artigas","UY",2001 +"2001-07-18","Constitution Day","UY",2001 +"2001-08-25","Independence Day","UY",2001 +"2001-10-15","Respect for Cultural Diversity Day","UY",2001 +"2001-11-02","All Souls' Day","UY",2001 +"2001-12-25","Day of the Family","UY",2001 +"2002-01-01","New Year's Day","UY",2002 +"2002-01-06","Children's Day","UY",2002 +"2002-02-11","Carnival Day","UY",2002 +"2002-02-12","Carnival Day","UY",2002 +"2002-03-28","Maundy Thursday","UY",2002 +"2002-03-29","Good Friday","UY",2002 +"2002-03-31","Easter Day","UY",2002 +"2002-04-22","Landing of the 33 Patriots","UY",2002 +"2002-05-01","International Workers' Day","UY",2002 +"2002-05-18","Battle of Las Piedras","UY",2002 +"2002-06-19","Birthday of Jose Gervasio Artigas","UY",2002 +"2002-07-18","Constitution Day","UY",2002 +"2002-08-25","Independence Day","UY",2002 +"2002-10-12","Respect for Cultural Diversity Day","UY",2002 +"2002-11-02","All Souls' Day","UY",2002 +"2002-12-25","Day of the Family","UY",2002 +"2003-01-01","New Year's Day","UY",2003 +"2003-01-06","Children's Day","UY",2003 +"2003-03-03","Carnival Day","UY",2003 +"2003-03-04","Carnival Day","UY",2003 +"2003-04-17","Maundy Thursday","UY",2003 +"2003-04-18","Good Friday","UY",2003 +"2003-04-19","Landing of the 33 Patriots","UY",2003 +"2003-04-20","Easter Day","UY",2003 +"2003-05-01","International Workers' Day","UY",2003 +"2003-05-18","Battle of Las Piedras","UY",2003 +"2003-06-19","Birthday of Jose Gervasio Artigas","UY",2003 +"2003-07-18","Constitution Day","UY",2003 +"2003-08-25","Independence Day","UY",2003 +"2003-10-12","Respect for Cultural Diversity Day","UY",2003 +"2003-11-02","All Souls' Day","UY",2003 +"2003-12-25","Day of the Family","UY",2003 +"2004-01-01","New Year's Day","UY",2004 +"2004-01-06","Children's Day","UY",2004 +"2004-02-23","Carnival Day","UY",2004 +"2004-02-24","Carnival Day","UY",2004 +"2004-04-08","Maundy Thursday","UY",2004 +"2004-04-09","Good Friday","UY",2004 +"2004-04-11","Easter Day","UY",2004 +"2004-04-19","Landing of the 33 Patriots","UY",2004 +"2004-05-01","International Workers' Day","UY",2004 +"2004-05-17","Battle of Las Piedras","UY",2004 +"2004-06-19","Birthday of Jose Gervasio Artigas","UY",2004 +"2004-07-18","Constitution Day","UY",2004 +"2004-08-25","Independence Day","UY",2004 +"2004-10-11","Respect for Cultural Diversity Day","UY",2004 +"2004-11-02","All Souls' Day","UY",2004 +"2004-12-25","Day of the Family","UY",2004 +"2005-01-01","New Year's Day","UY",2005 +"2005-01-06","Children's Day","UY",2005 +"2005-02-07","Carnival Day","UY",2005 +"2005-02-08","Carnival Day","UY",2005 +"2005-03-24","Maundy Thursday","UY",2005 +"2005-03-25","Good Friday","UY",2005 +"2005-03-27","Easter Day","UY",2005 +"2005-04-18","Landing of the 33 Patriots","UY",2005 +"2005-05-01","International Workers' Day","UY",2005 +"2005-05-16","Battle of Las Piedras","UY",2005 +"2005-06-19","Birthday of Jose Gervasio Artigas","UY",2005 +"2005-07-18","Constitution Day","UY",2005 +"2005-08-25","Independence Day","UY",2005 +"2005-10-10","Respect for Cultural Diversity Day","UY",2005 +"2005-11-02","All Souls' Day","UY",2005 +"2005-12-25","Day of the Family","UY",2005 +"2006-01-01","New Year's Day","UY",2006 +"2006-01-06","Children's Day","UY",2006 +"2006-02-27","Carnival Day","UY",2006 +"2006-02-28","Carnival Day","UY",2006 +"2006-04-13","Maundy Thursday","UY",2006 +"2006-04-14","Good Friday","UY",2006 +"2006-04-16","Easter Day","UY",2006 +"2006-04-17","Landing of the 33 Patriots","UY",2006 +"2006-05-01","International Workers' Day","UY",2006 +"2006-05-22","Battle of Las Piedras","UY",2006 +"2006-06-19","Birthday of Jose Gervasio Artigas","UY",2006 +"2006-07-18","Constitution Day","UY",2006 +"2006-08-25","Independence Day","UY",2006 +"2006-10-16","Respect for Cultural Diversity Day","UY",2006 +"2006-11-02","All Souls' Day","UY",2006 +"2006-12-25","Day of the Family","UY",2006 +"2007-01-01","New Year's Day","UY",2007 +"2007-01-06","Children's Day","UY",2007 +"2007-02-19","Carnival Day","UY",2007 +"2007-02-20","Carnival Day","UY",2007 +"2007-04-05","Maundy Thursday","UY",2007 +"2007-04-06","Good Friday","UY",2007 +"2007-04-08","Easter Day","UY",2007 +"2007-04-23","Landing of the 33 Patriots","UY",2007 +"2007-05-01","International Workers' Day","UY",2007 +"2007-05-21","Battle of Las Piedras","UY",2007 +"2007-06-19","Birthday of Jose Gervasio Artigas","UY",2007 +"2007-07-18","Constitution Day","UY",2007 +"2007-08-25","Independence Day","UY",2007 +"2007-10-15","Respect for Cultural Diversity Day","UY",2007 +"2007-11-02","All Souls' Day","UY",2007 +"2007-12-25","Day of the Family","UY",2007 +"2008-01-01","New Year's Day","UY",2008 +"2008-01-06","Children's Day","UY",2008 +"2008-02-04","Carnival Day","UY",2008 +"2008-02-05","Carnival Day","UY",2008 +"2008-03-20","Maundy Thursday","UY",2008 +"2008-03-21","Good Friday","UY",2008 +"2008-03-23","Easter Day","UY",2008 +"2008-04-19","Landing of the 33 Patriots","UY",2008 +"2008-05-01","International Workers' Day","UY",2008 +"2008-05-18","Battle of Las Piedras","UY",2008 +"2008-06-19","Birthday of Jose Gervasio Artigas","UY",2008 +"2008-07-18","Constitution Day","UY",2008 +"2008-08-25","Independence Day","UY",2008 +"2008-10-12","Respect for Cultural Diversity Day","UY",2008 +"2008-11-02","All Souls' Day","UY",2008 +"2008-12-25","Day of the Family","UY",2008 +"2009-01-01","New Year's Day","UY",2009 +"2009-01-06","Children's Day","UY",2009 +"2009-02-23","Carnival Day","UY",2009 +"2009-02-24","Carnival Day","UY",2009 +"2009-04-09","Maundy Thursday","UY",2009 +"2009-04-10","Good Friday","UY",2009 +"2009-04-12","Easter Day","UY",2009 +"2009-04-19","Landing of the 33 Patriots","UY",2009 +"2009-05-01","International Workers' Day","UY",2009 +"2009-05-18","Battle of Las Piedras","UY",2009 +"2009-06-19","Birthday of Jose Gervasio Artigas","UY",2009 +"2009-07-18","Constitution Day","UY",2009 +"2009-08-25","Independence Day","UY",2009 +"2009-10-12","Respect for Cultural Diversity Day","UY",2009 +"2009-11-02","All Souls' Day","UY",2009 +"2009-12-25","Day of the Family","UY",2009 +"2010-01-01","New Year's Day","UY",2010 +"2010-01-06","Children's Day","UY",2010 +"2010-02-15","Carnival Day","UY",2010 +"2010-02-16","Carnival Day","UY",2010 +"2010-04-01","Maundy Thursday","UY",2010 +"2010-04-02","Good Friday","UY",2010 +"2010-04-04","Easter Day","UY",2010 +"2010-04-19","Landing of the 33 Patriots","UY",2010 +"2010-05-01","International Workers' Day","UY",2010 +"2010-05-17","Battle of Las Piedras","UY",2010 +"2010-06-19","Birthday of Jose Gervasio Artigas","UY",2010 +"2010-07-18","Constitution Day","UY",2010 +"2010-08-25","Independence Day","UY",2010 +"2010-10-11","Respect for Cultural Diversity Day","UY",2010 +"2010-11-02","All Souls' Day","UY",2010 +"2010-12-25","Day of the Family","UY",2010 +"2011-01-01","New Year's Day","UY",2011 +"2011-01-06","Children's Day","UY",2011 +"2011-03-07","Carnival Day","UY",2011 +"2011-03-08","Carnival Day","UY",2011 +"2011-04-18","Landing of the 33 Patriots","UY",2011 +"2011-04-21","Maundy Thursday","UY",2011 +"2011-04-22","Good Friday","UY",2011 +"2011-04-24","Easter Day","UY",2011 +"2011-05-01","International Workers' Day","UY",2011 +"2011-05-16","Battle of Las Piedras","UY",2011 +"2011-06-19","Birthday of Jose Gervasio Artigas","UY",2011 +"2011-07-18","Constitution Day","UY",2011 +"2011-08-25","Independence Day","UY",2011 +"2011-10-10","Respect for Cultural Diversity Day","UY",2011 +"2011-11-02","All Souls' Day","UY",2011 +"2011-12-25","Day of the Family","UY",2011 +"2012-01-01","New Year's Day","UY",2012 +"2012-01-06","Children's Day","UY",2012 +"2012-02-20","Carnival Day","UY",2012 +"2012-02-21","Carnival Day","UY",2012 +"2012-04-05","Maundy Thursday","UY",2012 +"2012-04-06","Good Friday","UY",2012 +"2012-04-08","Easter Day","UY",2012 +"2012-04-23","Landing of the 33 Patriots","UY",2012 +"2012-05-01","International Workers' Day","UY",2012 +"2012-05-21","Battle of Las Piedras","UY",2012 +"2012-06-19","Birthday of Jose Gervasio Artigas","UY",2012 +"2012-07-18","Constitution Day","UY",2012 +"2012-08-25","Independence Day","UY",2012 +"2012-10-15","Respect for Cultural Diversity Day","UY",2012 +"2012-11-02","All Souls' Day","UY",2012 +"2012-12-25","Day of the Family","UY",2012 +"2013-01-01","New Year's Day","UY",2013 +"2013-01-06","Children's Day","UY",2013 +"2013-02-11","Carnival Day","UY",2013 +"2013-02-12","Carnival Day","UY",2013 +"2013-03-28","Maundy Thursday","UY",2013 +"2013-03-29","Good Friday","UY",2013 +"2013-03-31","Easter Day","UY",2013 +"2013-04-22","Landing of the 33 Patriots","UY",2013 +"2013-05-01","International Workers' Day","UY",2013 +"2013-05-18","Battle of Las Piedras","UY",2013 +"2013-06-19","Birthday of Jose Gervasio Artigas","UY",2013 +"2013-07-18","Constitution Day","UY",2013 +"2013-08-25","Independence Day","UY",2013 +"2013-10-12","Respect for Cultural Diversity Day","UY",2013 +"2013-11-02","All Souls' Day","UY",2013 +"2013-12-25","Day of the Family","UY",2013 +"2014-01-01","New Year's Day","UY",2014 +"2014-01-06","Children's Day","UY",2014 +"2014-03-03","Carnival Day","UY",2014 +"2014-03-04","Carnival Day","UY",2014 +"2014-04-17","Maundy Thursday","UY",2014 +"2014-04-18","Good Friday","UY",2014 +"2014-04-19","Landing of the 33 Patriots","UY",2014 +"2014-04-20","Easter Day","UY",2014 +"2014-05-01","International Workers' Day","UY",2014 +"2014-05-18","Battle of Las Piedras","UY",2014 +"2014-06-19","Birthday of Jose Gervasio Artigas","UY",2014 +"2014-07-18","Constitution Day","UY",2014 +"2014-08-25","Independence Day","UY",2014 +"2014-10-12","Respect for Cultural Diversity Day","UY",2014 +"2014-11-02","All Souls' Day","UY",2014 +"2014-12-25","Day of the Family","UY",2014 +"2015-01-01","New Year's Day","UY",2015 +"2015-01-06","Children's Day","UY",2015 +"2015-02-16","Carnival Day","UY",2015 +"2015-02-17","Carnival Day","UY",2015 +"2015-04-02","Maundy Thursday","UY",2015 +"2015-04-03","Good Friday","UY",2015 +"2015-04-05","Easter Day","UY",2015 +"2015-04-19","Landing of the 33 Patriots","UY",2015 +"2015-05-01","International Workers' Day","UY",2015 +"2015-05-18","Battle of Las Piedras","UY",2015 +"2015-06-19","Birthday of Jose Gervasio Artigas","UY",2015 +"2015-07-18","Constitution Day","UY",2015 +"2015-08-25","Independence Day","UY",2015 +"2015-10-12","Respect for Cultural Diversity Day","UY",2015 +"2015-11-02","All Souls' Day","UY",2015 +"2015-12-25","Day of the Family","UY",2015 +"2016-01-01","New Year's Day","UY",2016 +"2016-01-06","Children's Day","UY",2016 +"2016-02-08","Carnival Day","UY",2016 +"2016-02-09","Carnival Day","UY",2016 +"2016-03-24","Maundy Thursday","UY",2016 +"2016-03-25","Good Friday","UY",2016 +"2016-03-27","Easter Day","UY",2016 +"2016-04-18","Landing of the 33 Patriots","UY",2016 +"2016-05-01","International Workers' Day","UY",2016 +"2016-05-16","Battle of Las Piedras","UY",2016 +"2016-06-19","Birthday of Jose Gervasio Artigas","UY",2016 +"2016-07-18","Constitution Day","UY",2016 +"2016-08-25","Independence Day","UY",2016 +"2016-10-10","Respect for Cultural Diversity Day","UY",2016 +"2016-11-02","All Souls' Day","UY",2016 +"2016-12-25","Day of the Family","UY",2016 +"2017-01-01","New Year's Day","UY",2017 +"2017-01-06","Children's Day","UY",2017 +"2017-02-27","Carnival Day","UY",2017 +"2017-02-28","Carnival Day","UY",2017 +"2017-04-13","Maundy Thursday","UY",2017 +"2017-04-14","Good Friday","UY",2017 +"2017-04-16","Easter Day","UY",2017 +"2017-04-17","Landing of the 33 Patriots","UY",2017 +"2017-05-01","International Workers' Day","UY",2017 +"2017-05-22","Battle of Las Piedras","UY",2017 +"2017-06-19","Birthday of Jose Gervasio Artigas","UY",2017 +"2017-07-18","Constitution Day","UY",2017 +"2017-08-25","Independence Day","UY",2017 +"2017-10-16","Respect for Cultural Diversity Day","UY",2017 +"2017-11-02","All Souls' Day","UY",2017 +"2017-12-25","Day of the Family","UY",2017 +"2018-01-01","New Year's Day","UY",2018 +"2018-01-06","Children's Day","UY",2018 +"2018-02-12","Carnival Day","UY",2018 +"2018-02-13","Carnival Day","UY",2018 +"2018-03-29","Maundy Thursday","UY",2018 +"2018-03-30","Good Friday","UY",2018 +"2018-04-01","Easter Day","UY",2018 +"2018-04-23","Landing of the 33 Patriots","UY",2018 +"2018-05-01","International Workers' Day","UY",2018 +"2018-05-21","Battle of Las Piedras","UY",2018 +"2018-06-19","Birthday of Jose Gervasio Artigas","UY",2018 +"2018-07-18","Constitution Day","UY",2018 +"2018-08-25","Independence Day","UY",2018 +"2018-10-15","Respect for Cultural Diversity Day","UY",2018 +"2018-11-02","All Souls' Day","UY",2018 +"2018-12-25","Day of the Family","UY",2018 +"2019-01-01","New Year's Day","UY",2019 +"2019-01-06","Children's Day","UY",2019 +"2019-03-04","Carnival Day","UY",2019 +"2019-03-05","Carnival Day","UY",2019 +"2019-04-18","Maundy Thursday","UY",2019 +"2019-04-19","Good Friday","UY",2019 +"2019-04-21","Easter Day","UY",2019 +"2019-04-22","Landing of the 33 Patriots","UY",2019 +"2019-05-01","International Workers' Day","UY",2019 +"2019-05-18","Battle of Las Piedras","UY",2019 +"2019-06-19","Birthday of Jose Gervasio Artigas","UY",2019 +"2019-07-18","Constitution Day","UY",2019 +"2019-08-25","Independence Day","UY",2019 +"2019-10-12","Respect for Cultural Diversity Day","UY",2019 +"2019-11-02","All Souls' Day","UY",2019 +"2019-12-25","Day of the Family","UY",2019 +"2020-01-01","New Year's Day","UY",2020 +"2020-01-06","Children's Day","UY",2020 +"2020-02-24","Carnival Day","UY",2020 +"2020-02-25","Carnival Day","UY",2020 +"2020-04-09","Maundy Thursday","UY",2020 +"2020-04-10","Good Friday","UY",2020 +"2020-04-12","Easter Day","UY",2020 +"2020-04-19","Landing of the 33 Patriots","UY",2020 +"2020-05-01","International Workers' Day","UY",2020 +"2020-05-18","Battle of Las Piedras","UY",2020 +"2020-06-19","Birthday of Jose Gervasio Artigas","UY",2020 +"2020-07-18","Constitution Day","UY",2020 +"2020-08-25","Independence Day","UY",2020 +"2020-10-12","Respect for Cultural Diversity Day","UY",2020 +"2020-11-02","All Souls' Day","UY",2020 +"2020-12-25","Day of the Family","UY",2020 +"2021-01-01","New Year's Day","UY",2021 +"2021-01-06","Children's Day","UY",2021 +"2021-02-15","Carnival Day","UY",2021 +"2021-02-16","Carnival Day","UY",2021 +"2021-04-01","Maundy Thursday","UY",2021 +"2021-04-02","Good Friday","UY",2021 +"2021-04-04","Easter Day","UY",2021 +"2021-04-19","Landing of the 33 Patriots","UY",2021 +"2021-05-01","International Workers' Day","UY",2021 +"2021-05-17","Battle of Las Piedras","UY",2021 +"2021-06-19","Birthday of Jose Gervasio Artigas","UY",2021 +"2021-07-18","Constitution Day","UY",2021 +"2021-08-25","Independence Day","UY",2021 +"2021-10-11","Respect for Cultural Diversity Day","UY",2021 +"2021-11-02","All Souls' Day","UY",2021 +"2021-12-25","Day of the Family","UY",2021 +"2022-01-01","New Year's Day","UY",2022 +"2022-01-06","Children's Day","UY",2022 +"2022-02-28","Carnival Day","UY",2022 +"2022-03-01","Carnival Day","UY",2022 +"2022-04-14","Maundy Thursday","UY",2022 +"2022-04-15","Good Friday","UY",2022 +"2022-04-17","Easter Day","UY",2022 +"2022-04-18","Landing of the 33 Patriots","UY",2022 +"2022-05-01","International Workers' Day","UY",2022 +"2022-05-16","Battle of Las Piedras","UY",2022 +"2022-06-19","Birthday of Jose Gervasio Artigas","UY",2022 +"2022-07-18","Constitution Day","UY",2022 +"2022-08-25","Independence Day","UY",2022 +"2022-10-10","Respect for Cultural Diversity Day","UY",2022 +"2022-11-02","All Souls' Day","UY",2022 +"2022-12-25","Day of the Family","UY",2022 +"2023-01-01","New Year's Day","UY",2023 +"2023-01-06","Children's Day","UY",2023 +"2023-02-20","Carnival Day","UY",2023 +"2023-02-21","Carnival Day","UY",2023 +"2023-04-06","Maundy Thursday","UY",2023 +"2023-04-07","Good Friday","UY",2023 +"2023-04-09","Easter Day","UY",2023 +"2023-04-17","Landing of the 33 Patriots","UY",2023 +"2023-05-01","International Workers' Day","UY",2023 +"2023-05-22","Battle of Las Piedras","UY",2023 +"2023-06-19","Birthday of Jose Gervasio Artigas","UY",2023 +"2023-07-18","Constitution Day","UY",2023 +"2023-08-25","Independence Day","UY",2023 +"2023-10-16","Respect for Cultural Diversity Day","UY",2023 +"2023-11-02","All Souls' Day","UY",2023 +"2023-12-25","Day of the Family","UY",2023 +"2024-01-01","New Year's Day","UY",2024 +"2024-01-06","Children's Day","UY",2024 +"2024-02-12","Carnival Day","UY",2024 +"2024-02-13","Carnival Day","UY",2024 +"2024-03-28","Maundy Thursday","UY",2024 +"2024-03-29","Good Friday","UY",2024 +"2024-03-31","Easter Day","UY",2024 +"2024-04-22","Landing of the 33 Patriots","UY",2024 +"2024-05-01","International Workers' Day","UY",2024 +"2024-05-18","Battle of Las Piedras","UY",2024 +"2024-06-19","Birthday of Jose Gervasio Artigas","UY",2024 +"2024-07-18","Constitution Day","UY",2024 +"2024-08-25","Independence Day","UY",2024 +"2024-10-12","Respect for Cultural Diversity Day","UY",2024 +"2024-11-02","All Souls' Day","UY",2024 +"2024-12-25","Day of the Family","UY",2024 +"2025-01-01","New Year's Day","UY",2025 +"2025-01-06","Children's Day","UY",2025 +"2025-03-03","Carnival Day","UY",2025 +"2025-03-04","Carnival Day","UY",2025 +"2025-04-17","Maundy Thursday","UY",2025 +"2025-04-18","Good Friday","UY",2025 +"2025-04-19","Landing of the 33 Patriots","UY",2025 +"2025-04-20","Easter Day","UY",2025 +"2025-05-01","International Workers' Day","UY",2025 +"2025-05-18","Battle of Las Piedras","UY",2025 +"2025-06-19","Birthday of Jose Gervasio Artigas","UY",2025 +"2025-07-18","Constitution Day","UY",2025 +"2025-08-25","Independence Day","UY",2025 +"2025-10-12","Respect for Cultural Diversity Day","UY",2025 +"2025-11-02","All Souls' Day","UY",2025 +"2025-12-25","Day of the Family","UY",2025 +"2026-01-01","New Year's Day","UY",2026 +"2026-01-06","Children's Day","UY",2026 +"2026-02-16","Carnival Day","UY",2026 +"2026-02-17","Carnival Day","UY",2026 +"2026-04-02","Maundy Thursday","UY",2026 +"2026-04-03","Good Friday","UY",2026 +"2026-04-05","Easter Day","UY",2026 +"2026-04-19","Landing of the 33 Patriots","UY",2026 +"2026-05-01","International Workers' Day","UY",2026 +"2026-05-18","Battle of Las Piedras","UY",2026 +"2026-06-19","Birthday of Jose Gervasio Artigas","UY",2026 +"2026-07-18","Constitution Day","UY",2026 +"2026-08-25","Independence Day","UY",2026 +"2026-10-12","Respect for Cultural Diversity Day","UY",2026 +"2026-11-02","All Souls' Day","UY",2026 +"2026-12-25","Day of the Family","UY",2026 +"2027-01-01","New Year's Day","UY",2027 +"2027-01-06","Children's Day","UY",2027 +"2027-02-08","Carnival Day","UY",2027 +"2027-02-09","Carnival Day","UY",2027 +"2027-03-25","Maundy Thursday","UY",2027 +"2027-03-26","Good Friday","UY",2027 +"2027-03-28","Easter Day","UY",2027 +"2027-04-19","Landing of the 33 Patriots","UY",2027 +"2027-05-01","International Workers' Day","UY",2027 +"2027-05-17","Battle of Las Piedras","UY",2027 +"2027-06-19","Birthday of Jose Gervasio Artigas","UY",2027 +"2027-07-18","Constitution Day","UY",2027 +"2027-08-25","Independence Day","UY",2027 +"2027-10-11","Respect for Cultural Diversity Day","UY",2027 +"2027-11-02","All Souls' Day","UY",2027 +"2027-12-25","Day of the Family","UY",2027 +"2028-01-01","New Year's Day","UY",2028 +"2028-01-06","Children's Day","UY",2028 +"2028-02-28","Carnival Day","UY",2028 +"2028-02-29","Carnival Day","UY",2028 +"2028-04-13","Maundy Thursday","UY",2028 +"2028-04-14","Good Friday","UY",2028 +"2028-04-16","Easter Day","UY",2028 +"2028-04-17","Landing of the 33 Patriots","UY",2028 +"2028-05-01","International Workers' Day","UY",2028 +"2028-05-22","Battle of Las Piedras","UY",2028 +"2028-06-19","Birthday of Jose Gervasio Artigas","UY",2028 +"2028-07-18","Constitution Day","UY",2028 +"2028-08-25","Independence Day","UY",2028 +"2028-10-16","Respect for Cultural Diversity Day","UY",2028 +"2028-11-02","All Souls' Day","UY",2028 +"2028-12-25","Day of the Family","UY",2028 +"2029-01-01","New Year's Day","UY",2029 +"2029-01-06","Children's Day","UY",2029 +"2029-02-12","Carnival Day","UY",2029 +"2029-02-13","Carnival Day","UY",2029 +"2029-03-29","Maundy Thursday","UY",2029 +"2029-03-30","Good Friday","UY",2029 +"2029-04-01","Easter Day","UY",2029 +"2029-04-23","Landing of the 33 Patriots","UY",2029 +"2029-05-01","International Workers' Day","UY",2029 +"2029-05-21","Battle of Las Piedras","UY",2029 +"2029-06-19","Birthday of Jose Gervasio Artigas","UY",2029 +"2029-07-18","Constitution Day","UY",2029 +"2029-08-25","Independence Day","UY",2029 +"2029-10-15","Respect for Cultural Diversity Day","UY",2029 +"2029-11-02","All Souls' Day","UY",2029 +"2029-12-25","Day of the Family","UY",2029 +"2030-01-01","New Year's Day","UY",2030 +"2030-01-06","Children's Day","UY",2030 +"2030-03-04","Carnival Day","UY",2030 +"2030-03-05","Carnival Day","UY",2030 +"2030-04-18","Maundy Thursday","UY",2030 +"2030-04-19","Good Friday","UY",2030 +"2030-04-21","Easter Day","UY",2030 +"2030-04-22","Landing of the 33 Patriots","UY",2030 +"2030-05-01","International Workers' Day","UY",2030 +"2030-05-18","Battle of Las Piedras","UY",2030 +"2030-06-19","Birthday of Jose Gervasio Artigas","UY",2030 +"2030-07-18","Constitution Day","UY",2030 +"2030-08-25","Independence Day","UY",2030 +"2030-10-12","Respect for Cultural Diversity Day","UY",2030 +"2030-11-02","All Souls' Day","UY",2030 +"2030-12-25","Day of the Family","UY",2030 +"2031-01-01","New Year's Day","UY",2031 +"2031-01-06","Children's Day","UY",2031 +"2031-02-24","Carnival Day","UY",2031 +"2031-02-25","Carnival Day","UY",2031 +"2031-04-10","Maundy Thursday","UY",2031 +"2031-04-11","Good Friday","UY",2031 +"2031-04-13","Easter Day","UY",2031 +"2031-04-19","Landing of the 33 Patriots","UY",2031 +"2031-05-01","International Workers' Day","UY",2031 +"2031-05-18","Battle of Las Piedras","UY",2031 +"2031-06-19","Birthday of Jose Gervasio Artigas","UY",2031 +"2031-07-18","Constitution Day","UY",2031 +"2031-08-25","Independence Day","UY",2031 +"2031-10-12","Respect for Cultural Diversity Day","UY",2031 +"2031-11-02","All Souls' Day","UY",2031 +"2031-12-25","Day of the Family","UY",2031 +"2032-01-01","New Year's Day","UY",2032 +"2032-01-06","Children's Day","UY",2032 +"2032-02-09","Carnival Day","UY",2032 +"2032-02-10","Carnival Day","UY",2032 +"2032-03-25","Maundy Thursday","UY",2032 +"2032-03-26","Good Friday","UY",2032 +"2032-03-28","Easter Day","UY",2032 +"2032-04-19","Landing of the 33 Patriots","UY",2032 +"2032-05-01","International Workers' Day","UY",2032 +"2032-05-17","Battle of Las Piedras","UY",2032 +"2032-06-19","Birthday of Jose Gervasio Artigas","UY",2032 +"2032-07-18","Constitution Day","UY",2032 +"2032-08-25","Independence Day","UY",2032 +"2032-10-11","Respect for Cultural Diversity Day","UY",2032 +"2032-11-02","All Souls' Day","UY",2032 +"2032-12-25","Day of the Family","UY",2032 +"2033-01-01","New Year's Day","UY",2033 +"2033-01-06","Children's Day","UY",2033 +"2033-02-28","Carnival Day","UY",2033 +"2033-03-01","Carnival Day","UY",2033 +"2033-04-14","Maundy Thursday","UY",2033 +"2033-04-15","Good Friday","UY",2033 +"2033-04-17","Easter Day","UY",2033 +"2033-04-18","Landing of the 33 Patriots","UY",2033 +"2033-05-01","International Workers' Day","UY",2033 +"2033-05-16","Battle of Las Piedras","UY",2033 +"2033-06-19","Birthday of Jose Gervasio Artigas","UY",2033 +"2033-07-18","Constitution Day","UY",2033 +"2033-08-25","Independence Day","UY",2033 +"2033-10-10","Respect for Cultural Diversity Day","UY",2033 +"2033-11-02","All Souls' Day","UY",2033 +"2033-12-25","Day of the Family","UY",2033 +"2034-01-01","New Year's Day","UY",2034 +"2034-01-06","Children's Day","UY",2034 +"2034-02-20","Carnival Day","UY",2034 +"2034-02-21","Carnival Day","UY",2034 +"2034-04-06","Maundy Thursday","UY",2034 +"2034-04-07","Good Friday","UY",2034 +"2034-04-09","Easter Day","UY",2034 +"2034-04-17","Landing of the 33 Patriots","UY",2034 +"2034-05-01","International Workers' Day","UY",2034 +"2034-05-22","Battle of Las Piedras","UY",2034 +"2034-06-19","Birthday of Jose Gervasio Artigas","UY",2034 +"2034-07-18","Constitution Day","UY",2034 +"2034-08-25","Independence Day","UY",2034 +"2034-10-16","Respect for Cultural Diversity Day","UY",2034 +"2034-11-02","All Souls' Day","UY",2034 +"2034-12-25","Day of the Family","UY",2034 +"2035-01-01","New Year's Day","UY",2035 +"2035-01-06","Children's Day","UY",2035 +"2035-02-05","Carnival Day","UY",2035 +"2035-02-06","Carnival Day","UY",2035 +"2035-03-22","Maundy Thursday","UY",2035 +"2035-03-23","Good Friday","UY",2035 +"2035-03-25","Easter Day","UY",2035 +"2035-04-23","Landing of the 33 Patriots","UY",2035 +"2035-05-01","International Workers' Day","UY",2035 +"2035-05-21","Battle of Las Piedras","UY",2035 +"2035-06-19","Birthday of Jose Gervasio Artigas","UY",2035 +"2035-07-18","Constitution Day","UY",2035 +"2035-08-25","Independence Day","UY",2035 +"2035-10-15","Respect for Cultural Diversity Day","UY",2035 +"2035-11-02","All Souls' Day","UY",2035 +"2035-12-25","Day of the Family","UY",2035 +"2036-01-01","New Year's Day","UY",2036 +"2036-01-06","Children's Day","UY",2036 +"2036-02-25","Carnival Day","UY",2036 +"2036-02-26","Carnival Day","UY",2036 +"2036-04-10","Maundy Thursday","UY",2036 +"2036-04-11","Good Friday","UY",2036 +"2036-04-13","Easter Day","UY",2036 +"2036-04-19","Landing of the 33 Patriots","UY",2036 +"2036-05-01","International Workers' Day","UY",2036 +"2036-05-18","Battle of Las Piedras","UY",2036 +"2036-06-19","Birthday of Jose Gervasio Artigas","UY",2036 +"2036-07-18","Constitution Day","UY",2036 +"2036-08-25","Independence Day","UY",2036 +"2036-10-12","Respect for Cultural Diversity Day","UY",2036 +"2036-11-02","All Souls' Day","UY",2036 +"2036-12-25","Day of the Family","UY",2036 +"2037-01-01","New Year's Day","UY",2037 +"2037-01-06","Children's Day","UY",2037 +"2037-02-16","Carnival Day","UY",2037 +"2037-02-17","Carnival Day","UY",2037 +"2037-04-02","Maundy Thursday","UY",2037 +"2037-04-03","Good Friday","UY",2037 +"2037-04-05","Easter Day","UY",2037 +"2037-04-19","Landing of the 33 Patriots","UY",2037 +"2037-05-01","International Workers' Day","UY",2037 +"2037-05-18","Battle of Las Piedras","UY",2037 +"2037-06-19","Birthday of Jose Gervasio Artigas","UY",2037 +"2037-07-18","Constitution Day","UY",2037 +"2037-08-25","Independence Day","UY",2037 +"2037-10-12","Respect for Cultural Diversity Day","UY",2037 +"2037-11-02","All Souls' Day","UY",2037 +"2037-12-25","Day of the Family","UY",2037 +"2038-01-01","New Year's Day","UY",2038 +"2038-01-06","Children's Day","UY",2038 +"2038-03-08","Carnival Day","UY",2038 +"2038-03-09","Carnival Day","UY",2038 +"2038-04-19","Landing of the 33 Patriots","UY",2038 +"2038-04-22","Maundy Thursday","UY",2038 +"2038-04-23","Good Friday","UY",2038 +"2038-04-25","Easter Day","UY",2038 +"2038-05-01","International Workers' Day","UY",2038 +"2038-05-17","Battle of Las Piedras","UY",2038 +"2038-06-19","Birthday of Jose Gervasio Artigas","UY",2038 +"2038-07-18","Constitution Day","UY",2038 +"2038-08-25","Independence Day","UY",2038 +"2038-10-11","Respect for Cultural Diversity Day","UY",2038 +"2038-11-02","All Souls' Day","UY",2038 +"2038-12-25","Day of the Family","UY",2038 +"2039-01-01","New Year's Day","UY",2039 +"2039-01-06","Children's Day","UY",2039 +"2039-02-21","Carnival Day","UY",2039 +"2039-02-22","Carnival Day","UY",2039 +"2039-04-07","Maundy Thursday","UY",2039 +"2039-04-08","Good Friday","UY",2039 +"2039-04-10","Easter Day","UY",2039 +"2039-04-18","Landing of the 33 Patriots","UY",2039 +"2039-05-01","International Workers' Day","UY",2039 +"2039-05-16","Battle of Las Piedras","UY",2039 +"2039-06-19","Birthday of Jose Gervasio Artigas","UY",2039 +"2039-07-18","Constitution Day","UY",2039 +"2039-08-25","Independence Day","UY",2039 +"2039-10-10","Respect for Cultural Diversity Day","UY",2039 +"2039-11-02","All Souls' Day","UY",2039 +"2039-12-25","Day of the Family","UY",2039 +"2040-01-01","New Year's Day","UY",2040 +"2040-01-06","Children's Day","UY",2040 +"2040-02-13","Carnival Day","UY",2040 +"2040-02-14","Carnival Day","UY",2040 +"2040-03-29","Maundy Thursday","UY",2040 +"2040-03-30","Good Friday","UY",2040 +"2040-04-01","Easter Day","UY",2040 +"2040-04-23","Landing of the 33 Patriots","UY",2040 +"2040-05-01","International Workers' Day","UY",2040 +"2040-05-21","Battle of Las Piedras","UY",2040 +"2040-06-19","Birthday of Jose Gervasio Artigas","UY",2040 +"2040-07-18","Constitution Day","UY",2040 +"2040-08-25","Independence Day","UY",2040 +"2040-10-15","Respect for Cultural Diversity Day","UY",2040 +"2040-11-02","All Souls' Day","UY",2040 +"2040-12-25","Day of the Family","UY",2040 +"2041-01-01","New Year's Day","UY",2041 +"2041-01-06","Children's Day","UY",2041 +"2041-03-04","Carnival Day","UY",2041 +"2041-03-05","Carnival Day","UY",2041 +"2041-04-18","Maundy Thursday","UY",2041 +"2041-04-19","Good Friday","UY",2041 +"2041-04-21","Easter Day","UY",2041 +"2041-04-22","Landing of the 33 Patriots","UY",2041 +"2041-05-01","International Workers' Day","UY",2041 +"2041-05-18","Battle of Las Piedras","UY",2041 +"2041-06-19","Birthday of Jose Gervasio Artigas","UY",2041 +"2041-07-18","Constitution Day","UY",2041 +"2041-08-25","Independence Day","UY",2041 +"2041-10-12","Respect for Cultural Diversity Day","UY",2041 +"2041-11-02","All Souls' Day","UY",2041 +"2041-12-25","Day of the Family","UY",2041 +"2042-01-01","New Year's Day","UY",2042 +"2042-01-06","Children's Day","UY",2042 +"2042-02-17","Carnival Day","UY",2042 +"2042-02-18","Carnival Day","UY",2042 +"2042-04-03","Maundy Thursday","UY",2042 +"2042-04-04","Good Friday","UY",2042 +"2042-04-06","Easter Day","UY",2042 +"2042-04-19","Landing of the 33 Patriots","UY",2042 +"2042-05-01","International Workers' Day","UY",2042 +"2042-05-18","Battle of Las Piedras","UY",2042 +"2042-06-19","Birthday of Jose Gervasio Artigas","UY",2042 +"2042-07-18","Constitution Day","UY",2042 +"2042-08-25","Independence Day","UY",2042 +"2042-10-12","Respect for Cultural Diversity Day","UY",2042 +"2042-11-02","All Souls' Day","UY",2042 +"2042-12-25","Day of the Family","UY",2042 +"2043-01-01","New Year's Day","UY",2043 +"2043-01-06","Children's Day","UY",2043 +"2043-02-09","Carnival Day","UY",2043 +"2043-02-10","Carnival Day","UY",2043 +"2043-03-26","Maundy Thursday","UY",2043 +"2043-03-27","Good Friday","UY",2043 +"2043-03-29","Easter Day","UY",2043 +"2043-04-19","Landing of the 33 Patriots","UY",2043 +"2043-05-01","International Workers' Day","UY",2043 +"2043-05-18","Battle of Las Piedras","UY",2043 +"2043-06-19","Birthday of Jose Gervasio Artigas","UY",2043 +"2043-07-18","Constitution Day","UY",2043 +"2043-08-25","Independence Day","UY",2043 +"2043-10-12","Respect for Cultural Diversity Day","UY",2043 +"2043-11-02","All Souls' Day","UY",2043 +"2043-12-25","Day of the Family","UY",2043 +"2044-01-01","New Year's Day","UY",2044 +"2044-01-06","Children's Day","UY",2044 +"2044-02-29","Carnival Day","UY",2044 +"2044-03-01","Carnival Day","UY",2044 +"2044-04-14","Maundy Thursday","UY",2044 +"2044-04-15","Good Friday","UY",2044 +"2044-04-17","Easter Day","UY",2044 +"2044-04-18","Landing of the 33 Patriots","UY",2044 +"2044-05-01","International Workers' Day","UY",2044 +"2044-05-16","Battle of Las Piedras","UY",2044 +"2044-06-19","Birthday of Jose Gervasio Artigas","UY",2044 +"2044-07-18","Constitution Day","UY",2044 +"2044-08-25","Independence Day","UY",2044 +"2044-10-10","Respect for Cultural Diversity Day","UY",2044 +"2044-11-02","All Souls' Day","UY",2044 +"2044-12-25","Day of the Family","UY",2044 +"1995-01-01","New Year","UZ",1995 +"1995-03-02","Ramadan Khait* (*estimated)","UZ",1995 +"1995-03-08","Women's Day","UZ",1995 +"1995-03-21","Nauryz","UZ",1995 +"1995-05-09","Kurban Khait* (*estimated)","UZ",1995 +"1995-05-09","Memorial Day","UZ",1995 +"1995-09-01","Independence Day","UZ",1995 +"1995-10-01","Teacher's Day","UZ",1995 +"1995-12-08","Constitution Day","UZ",1995 +"1996-01-01","New Year","UZ",1996 +"1996-02-19","Ramadan Khait* (*estimated)","UZ",1996 +"1996-03-08","Women's Day","UZ",1996 +"1996-03-21","Nauryz","UZ",1996 +"1996-04-27","Kurban Khait* (*estimated)","UZ",1996 +"1996-05-09","Memorial Day","UZ",1996 +"1996-09-01","Independence Day","UZ",1996 +"1996-10-01","Teacher's Day","UZ",1996 +"1996-12-08","Constitution Day","UZ",1996 +"1997-01-01","New Year","UZ",1997 +"1997-02-08","Ramadan Khait* (*estimated)","UZ",1997 +"1997-03-08","Women's Day","UZ",1997 +"1997-03-21","Nauryz","UZ",1997 +"1997-04-17","Kurban Khait* (*estimated)","UZ",1997 +"1997-05-09","Memorial Day","UZ",1997 +"1997-09-01","Independence Day","UZ",1997 +"1997-10-01","Teacher's Day","UZ",1997 +"1997-12-08","Constitution Day","UZ",1997 +"1998-01-01","New Year","UZ",1998 +"1998-01-29","Ramadan Khait* (*estimated)","UZ",1998 +"1998-03-08","Women's Day","UZ",1998 +"1998-03-21","Nauryz","UZ",1998 +"1998-04-07","Kurban Khait* (*estimated)","UZ",1998 +"1998-05-09","Memorial Day","UZ",1998 +"1998-09-01","Independence Day","UZ",1998 +"1998-10-01","Teacher's Day","UZ",1998 +"1998-12-08","Constitution Day","UZ",1998 +"1999-01-01","New Year","UZ",1999 +"1999-01-18","Ramadan Khait* (*estimated)","UZ",1999 +"1999-03-08","Women's Day","UZ",1999 +"1999-03-21","Nauryz","UZ",1999 +"1999-03-27","Kurban Khait* (*estimated)","UZ",1999 +"1999-05-09","Memorial Day","UZ",1999 +"1999-09-01","Independence Day","UZ",1999 +"1999-10-01","Teacher's Day","UZ",1999 +"1999-12-08","Constitution Day","UZ",1999 +"2000-01-01","New Year","UZ",2000 +"2000-01-08","Ramadan Khait* (*estimated)","UZ",2000 +"2000-03-08","Women's Day","UZ",2000 +"2000-03-16","Kurban Khait* (*estimated)","UZ",2000 +"2000-03-21","Nauryz","UZ",2000 +"2000-05-09","Memorial Day","UZ",2000 +"2000-09-01","Independence Day","UZ",2000 +"2000-10-01","Teacher's Day","UZ",2000 +"2000-12-08","Constitution Day","UZ",2000 +"2000-12-27","Ramadan Khait* (*estimated)","UZ",2000 +"2001-01-01","New Year","UZ",2001 +"2001-03-05","Kurban Khait* (*estimated)","UZ",2001 +"2001-03-08","Women's Day","UZ",2001 +"2001-03-21","Nauryz","UZ",2001 +"2001-05-09","Memorial Day","UZ",2001 +"2001-09-01","Independence Day","UZ",2001 +"2001-10-01","Teacher's Day","UZ",2001 +"2001-12-08","Constitution Day","UZ",2001 +"2001-12-16","Ramadan Khait* (*estimated)","UZ",2001 +"2002-01-01","New Year","UZ",2002 +"2002-02-22","Kurban Khait* (*estimated)","UZ",2002 +"2002-03-08","Women's Day","UZ",2002 +"2002-03-21","Nauryz","UZ",2002 +"2002-05-09","Memorial Day","UZ",2002 +"2002-09-01","Independence Day","UZ",2002 +"2002-10-01","Teacher's Day","UZ",2002 +"2002-12-05","Ramadan Khait* (*estimated)","UZ",2002 +"2002-12-08","Constitution Day","UZ",2002 +"2003-01-01","New Year","UZ",2003 +"2003-02-11","Kurban Khait* (*estimated)","UZ",2003 +"2003-03-08","Women's Day","UZ",2003 +"2003-03-21","Nauryz","UZ",2003 +"2003-05-09","Memorial Day","UZ",2003 +"2003-09-01","Independence Day","UZ",2003 +"2003-10-01","Teacher's Day","UZ",2003 +"2003-11-25","Ramadan Khait* (*estimated)","UZ",2003 +"2003-12-08","Constitution Day","UZ",2003 +"2004-01-01","New Year","UZ",2004 +"2004-02-01","Kurban Khait* (*estimated)","UZ",2004 +"2004-03-08","Women's Day","UZ",2004 +"2004-03-21","Nauryz","UZ",2004 +"2004-05-09","Memorial Day","UZ",2004 +"2004-09-01","Independence Day","UZ",2004 +"2004-10-01","Teacher's Day","UZ",2004 +"2004-11-14","Ramadan Khait* (*estimated)","UZ",2004 +"2004-12-08","Constitution Day","UZ",2004 +"2005-01-01","New Year","UZ",2005 +"2005-01-21","Kurban Khait* (*estimated)","UZ",2005 +"2005-03-08","Women's Day","UZ",2005 +"2005-03-21","Nauryz","UZ",2005 +"2005-05-09","Memorial Day","UZ",2005 +"2005-09-01","Independence Day","UZ",2005 +"2005-10-01","Teacher's Day","UZ",2005 +"2005-11-03","Ramadan Khait* (*estimated)","UZ",2005 +"2005-12-08","Constitution Day","UZ",2005 +"2006-01-01","New Year","UZ",2006 +"2006-01-10","Kurban Khait* (*estimated)","UZ",2006 +"2006-03-08","Women's Day","UZ",2006 +"2006-03-21","Nauryz","UZ",2006 +"2006-05-09","Memorial Day","UZ",2006 +"2006-09-01","Independence Day","UZ",2006 +"2006-10-01","Teacher's Day","UZ",2006 +"2006-10-23","Ramadan Khait* (*estimated)","UZ",2006 +"2006-12-08","Constitution Day","UZ",2006 +"2006-12-31","Kurban Khait* (*estimated)","UZ",2006 +"2007-01-01","New Year","UZ",2007 +"2007-03-08","Women's Day","UZ",2007 +"2007-03-21","Nauryz","UZ",2007 +"2007-05-09","Memorial Day","UZ",2007 +"2007-09-01","Independence Day","UZ",2007 +"2007-10-01","Teacher's Day","UZ",2007 +"2007-10-13","Ramadan Khait* (*estimated)","UZ",2007 +"2007-12-08","Constitution Day","UZ",2007 +"2007-12-20","Kurban Khait* (*estimated)","UZ",2007 +"2008-01-01","New Year","UZ",2008 +"2008-03-08","Women's Day","UZ",2008 +"2008-03-21","Nauryz","UZ",2008 +"2008-05-09","Memorial Day","UZ",2008 +"2008-09-01","Independence Day","UZ",2008 +"2008-10-01","Ramadan Khait* (*estimated)","UZ",2008 +"2008-10-01","Teacher's Day","UZ",2008 +"2008-12-08","Constitution Day","UZ",2008 +"2008-12-08","Kurban Khait* (*estimated)","UZ",2008 +"2009-01-01","New Year","UZ",2009 +"2009-03-08","Women's Day","UZ",2009 +"2009-03-21","Nauryz","UZ",2009 +"2009-05-09","Memorial Day","UZ",2009 +"2009-09-01","Independence Day","UZ",2009 +"2009-09-20","Ramadan Khait* (*estimated)","UZ",2009 +"2009-10-01","Teacher's Day","UZ",2009 +"2009-11-27","Kurban Khait* (*estimated)","UZ",2009 +"2009-12-08","Constitution Day","UZ",2009 +"2010-01-01","New Year","UZ",2010 +"2010-03-08","Women's Day","UZ",2010 +"2010-03-21","Nauryz","UZ",2010 +"2010-05-09","Memorial Day","UZ",2010 +"2010-09-01","Independence Day","UZ",2010 +"2010-09-10","Ramadan Khait* (*estimated)","UZ",2010 +"2010-10-01","Teacher's Day","UZ",2010 +"2010-11-16","Kurban Khait* (*estimated)","UZ",2010 +"2010-12-08","Constitution Day","UZ",2010 +"2011-01-01","New Year","UZ",2011 +"2011-03-08","Women's Day","UZ",2011 +"2011-03-21","Nauryz","UZ",2011 +"2011-05-09","Memorial Day","UZ",2011 +"2011-08-30","Ramadan Khait* (*estimated)","UZ",2011 +"2011-09-01","Independence Day","UZ",2011 +"2011-10-01","Teacher's Day","UZ",2011 +"2011-11-06","Kurban Khait* (*estimated)","UZ",2011 +"2011-12-08","Constitution Day","UZ",2011 +"2012-01-01","New Year","UZ",2012 +"2012-03-08","Women's Day","UZ",2012 +"2012-03-21","Nauryz","UZ",2012 +"2012-05-09","Memorial Day","UZ",2012 +"2012-08-19","Ramadan Khait* (*estimated)","UZ",2012 +"2012-09-01","Independence Day","UZ",2012 +"2012-10-01","Teacher's Day","UZ",2012 +"2012-10-26","Kurban Khait* (*estimated)","UZ",2012 +"2012-12-08","Constitution Day","UZ",2012 +"2013-01-01","New Year","UZ",2013 +"2013-03-08","Women's Day","UZ",2013 +"2013-03-21","Nauryz","UZ",2013 +"2013-05-09","Memorial Day","UZ",2013 +"2013-08-08","Ramadan Khait* (*estimated)","UZ",2013 +"2013-09-01","Independence Day","UZ",2013 +"2013-10-01","Teacher's Day","UZ",2013 +"2013-10-15","Kurban Khait* (*estimated)","UZ",2013 +"2013-12-08","Constitution Day","UZ",2013 +"2014-01-01","New Year","UZ",2014 +"2014-03-08","Women's Day","UZ",2014 +"2014-03-21","Nauryz","UZ",2014 +"2014-05-09","Memorial Day","UZ",2014 +"2014-07-28","Ramadan Khait* (*estimated)","UZ",2014 +"2014-09-01","Independence Day","UZ",2014 +"2014-10-01","Teacher's Day","UZ",2014 +"2014-10-04","Kurban Khait* (*estimated)","UZ",2014 +"2014-12-08","Constitution Day","UZ",2014 +"2015-01-01","New Year","UZ",2015 +"2015-03-08","Women's Day","UZ",2015 +"2015-03-21","Nauryz","UZ",2015 +"2015-05-09","Memorial Day","UZ",2015 +"2015-07-17","Ramadan Khait* (*estimated)","UZ",2015 +"2015-09-01","Independence Day","UZ",2015 +"2015-09-23","Kurban Khait* (*estimated)","UZ",2015 +"2015-10-01","Teacher's Day","UZ",2015 +"2015-12-08","Constitution Day","UZ",2015 +"2016-01-01","New Year","UZ",2016 +"2016-03-08","Women's Day","UZ",2016 +"2016-03-21","Nauryz","UZ",2016 +"2016-05-09","Memorial Day","UZ",2016 +"2016-07-06","Ramadan Khait* (*estimated)","UZ",2016 +"2016-09-01","Independence Day","UZ",2016 +"2016-09-11","Kurban Khait* (*estimated)","UZ",2016 +"2016-10-01","Teacher's Day","UZ",2016 +"2016-12-08","Constitution Day","UZ",2016 +"2017-01-01","New Year","UZ",2017 +"2017-03-08","Women's Day","UZ",2017 +"2017-03-21","Nauryz","UZ",2017 +"2017-05-09","Memorial Day","UZ",2017 +"2017-06-25","Ramadan Khait* (*estimated)","UZ",2017 +"2017-09-01","Independence Day","UZ",2017 +"2017-09-01","Kurban Khait* (*estimated)","UZ",2017 +"2017-10-01","Teacher's Day","UZ",2017 +"2017-12-08","Constitution Day","UZ",2017 +"2018-01-01","New Year","UZ",2018 +"2018-03-08","Women's Day","UZ",2018 +"2018-03-21","Nauryz","UZ",2018 +"2018-05-09","Memorial Day","UZ",2018 +"2018-06-15","Ramadan Khait* (*estimated)","UZ",2018 +"2018-08-21","Kurban Khait* (*estimated)","UZ",2018 +"2018-09-01","Independence Day","UZ",2018 +"2018-10-01","Teacher's Day","UZ",2018 +"2018-12-08","Constitution Day","UZ",2018 +"2019-01-01","New Year","UZ",2019 +"2019-03-08","Women's Day","UZ",2019 +"2019-03-21","Nauryz","UZ",2019 +"2019-05-09","Memorial Day","UZ",2019 +"2019-06-04","Ramadan Khait* (*estimated)","UZ",2019 +"2019-08-11","Kurban Khait* (*estimated)","UZ",2019 +"2019-09-01","Independence Day","UZ",2019 +"2019-10-01","Teacher's Day","UZ",2019 +"2019-12-08","Constitution Day","UZ",2019 +"2020-01-01","New Year","UZ",2020 +"2020-03-08","Women's Day","UZ",2020 +"2020-03-21","Nauryz","UZ",2020 +"2020-05-09","Memorial Day","UZ",2020 +"2020-05-24","Ramadan Khait* (*estimated)","UZ",2020 +"2020-07-31","Kurban Khait* (*estimated)","UZ",2020 +"2020-09-01","Independence Day","UZ",2020 +"2020-10-01","Teacher's Day","UZ",2020 +"2020-12-08","Constitution Day","UZ",2020 +"2021-01-01","New Year","UZ",2021 +"2021-03-08","Women's Day","UZ",2021 +"2021-03-21","Nauryz","UZ",2021 +"2021-05-09","Memorial Day","UZ",2021 +"2021-05-13","Ramadan Khait* (*estimated)","UZ",2021 +"2021-07-20","Kurban Khait* (*estimated)","UZ",2021 +"2021-09-01","Independence Day","UZ",2021 +"2021-10-01","Teacher's Day","UZ",2021 +"2021-12-08","Constitution Day","UZ",2021 +"2022-01-01","New Year","UZ",2022 +"2022-03-08","Women's Day","UZ",2022 +"2022-03-21","Nauryz","UZ",2022 +"2022-05-02","Ramadan Khait* (*estimated)","UZ",2022 +"2022-05-09","Memorial Day","UZ",2022 +"2022-07-09","Kurban Khait* (*estimated)","UZ",2022 +"2022-09-01","Independence Day","UZ",2022 +"2022-10-01","Teacher's Day","UZ",2022 +"2022-12-08","Constitution Day","UZ",2022 +"2023-01-01","New Year","UZ",2023 +"2023-03-08","Women's Day","UZ",2023 +"2023-03-21","Nauryz","UZ",2023 +"2023-04-21","Ramadan Khait* (*estimated)","UZ",2023 +"2023-05-09","Memorial Day","UZ",2023 +"2023-06-28","Kurban Khait* (*estimated)","UZ",2023 +"2023-09-01","Independence Day","UZ",2023 +"2023-10-01","Teacher's Day","UZ",2023 +"2023-12-08","Constitution Day","UZ",2023 +"2024-01-01","New Year","UZ",2024 +"2024-03-08","Women's Day","UZ",2024 +"2024-03-21","Nauryz","UZ",2024 +"2024-04-10","Ramadan Khait* (*estimated)","UZ",2024 +"2024-05-09","Memorial Day","UZ",2024 +"2024-06-16","Kurban Khait* (*estimated)","UZ",2024 +"2024-09-01","Independence Day","UZ",2024 +"2024-10-01","Teacher's Day","UZ",2024 +"2024-12-08","Constitution Day","UZ",2024 +"2025-01-01","New Year","UZ",2025 +"2025-03-08","Women's Day","UZ",2025 +"2025-03-21","Nauryz","UZ",2025 +"2025-03-30","Ramadan Khait* (*estimated)","UZ",2025 +"2025-05-09","Memorial Day","UZ",2025 +"2025-06-06","Kurban Khait* (*estimated)","UZ",2025 +"2025-09-01","Independence Day","UZ",2025 +"2025-10-01","Teacher's Day","UZ",2025 +"2025-12-08","Constitution Day","UZ",2025 +"2026-01-01","New Year","UZ",2026 +"2026-03-08","Women's Day","UZ",2026 +"2026-03-20","Ramadan Khait* (*estimated)","UZ",2026 +"2026-03-21","Nauryz","UZ",2026 +"2026-05-09","Memorial Day","UZ",2026 +"2026-05-27","Kurban Khait* (*estimated)","UZ",2026 +"2026-09-01","Independence Day","UZ",2026 +"2026-10-01","Teacher's Day","UZ",2026 +"2026-12-08","Constitution Day","UZ",2026 +"2027-01-01","New Year","UZ",2027 +"2027-03-08","Women's Day","UZ",2027 +"2027-03-09","Ramadan Khait* (*estimated)","UZ",2027 +"2027-03-21","Nauryz","UZ",2027 +"2027-05-09","Memorial Day","UZ",2027 +"2027-05-16","Kurban Khait* (*estimated)","UZ",2027 +"2027-09-01","Independence Day","UZ",2027 +"2027-10-01","Teacher's Day","UZ",2027 +"2027-12-08","Constitution Day","UZ",2027 +"2028-01-01","New Year","UZ",2028 +"2028-02-26","Ramadan Khait* (*estimated)","UZ",2028 +"2028-03-08","Women's Day","UZ",2028 +"2028-03-21","Nauryz","UZ",2028 +"2028-05-05","Kurban Khait* (*estimated)","UZ",2028 +"2028-05-09","Memorial Day","UZ",2028 +"2028-09-01","Independence Day","UZ",2028 +"2028-10-01","Teacher's Day","UZ",2028 +"2028-12-08","Constitution Day","UZ",2028 +"2029-01-01","New Year","UZ",2029 +"2029-02-14","Ramadan Khait* (*estimated)","UZ",2029 +"2029-03-08","Women's Day","UZ",2029 +"2029-03-21","Nauryz","UZ",2029 +"2029-04-24","Kurban Khait* (*estimated)","UZ",2029 +"2029-05-09","Memorial Day","UZ",2029 +"2029-09-01","Independence Day","UZ",2029 +"2029-10-01","Teacher's Day","UZ",2029 +"2029-12-08","Constitution Day","UZ",2029 +"2030-01-01","New Year","UZ",2030 +"2030-02-04","Ramadan Khait* (*estimated)","UZ",2030 +"2030-03-08","Women's Day","UZ",2030 +"2030-03-21","Nauryz","UZ",2030 +"2030-04-13","Kurban Khait* (*estimated)","UZ",2030 +"2030-05-09","Memorial Day","UZ",2030 +"2030-09-01","Independence Day","UZ",2030 +"2030-10-01","Teacher's Day","UZ",2030 +"2030-12-08","Constitution Day","UZ",2030 +"2031-01-01","New Year","UZ",2031 +"2031-01-24","Ramadan Khait* (*estimated)","UZ",2031 +"2031-03-08","Women's Day","UZ",2031 +"2031-03-21","Nauryz","UZ",2031 +"2031-04-02","Kurban Khait* (*estimated)","UZ",2031 +"2031-05-09","Memorial Day","UZ",2031 +"2031-09-01","Independence Day","UZ",2031 +"2031-10-01","Teacher's Day","UZ",2031 +"2031-12-08","Constitution Day","UZ",2031 +"2032-01-01","New Year","UZ",2032 +"2032-01-14","Ramadan Khait* (*estimated)","UZ",2032 +"2032-03-08","Women's Day","UZ",2032 +"2032-03-21","Nauryz","UZ",2032 +"2032-03-22","Kurban Khait* (*estimated)","UZ",2032 +"2032-05-09","Memorial Day","UZ",2032 +"2032-09-01","Independence Day","UZ",2032 +"2032-10-01","Teacher's Day","UZ",2032 +"2032-12-08","Constitution Day","UZ",2032 +"2033-01-01","New Year","UZ",2033 +"2033-01-02","Ramadan Khait* (*estimated)","UZ",2033 +"2033-03-08","Women's Day","UZ",2033 +"2033-03-11","Kurban Khait* (*estimated)","UZ",2033 +"2033-03-21","Nauryz","UZ",2033 +"2033-05-09","Memorial Day","UZ",2033 +"2033-09-01","Independence Day","UZ",2033 +"2033-10-01","Teacher's Day","UZ",2033 +"2033-12-08","Constitution Day","UZ",2033 +"2033-12-23","Ramadan Khait* (*estimated)","UZ",2033 +"2034-01-01","New Year","UZ",2034 +"2034-03-01","Kurban Khait* (*estimated)","UZ",2034 +"2034-03-08","Women's Day","UZ",2034 +"2034-03-21","Nauryz","UZ",2034 +"2034-05-09","Memorial Day","UZ",2034 +"2034-09-01","Independence Day","UZ",2034 +"2034-10-01","Teacher's Day","UZ",2034 +"2034-12-08","Constitution Day","UZ",2034 +"2034-12-12","Ramadan Khait* (*estimated)","UZ",2034 +"2035-01-01","New Year","UZ",2035 +"2035-02-18","Kurban Khait* (*estimated)","UZ",2035 +"2035-03-08","Women's Day","UZ",2035 +"2035-03-21","Nauryz","UZ",2035 +"2035-05-09","Memorial Day","UZ",2035 +"2035-09-01","Independence Day","UZ",2035 +"2035-10-01","Teacher's Day","UZ",2035 +"2035-12-01","Ramadan Khait* (*estimated)","UZ",2035 +"2035-12-08","Constitution Day","UZ",2035 +"2036-01-01","New Year","UZ",2036 +"2036-02-07","Kurban Khait* (*estimated)","UZ",2036 +"2036-03-08","Women's Day","UZ",2036 +"2036-03-21","Nauryz","UZ",2036 +"2036-05-09","Memorial Day","UZ",2036 +"2036-09-01","Independence Day","UZ",2036 +"2036-10-01","Teacher's Day","UZ",2036 +"2036-11-19","Ramadan Khait* (*estimated)","UZ",2036 +"2036-12-08","Constitution Day","UZ",2036 +"2037-01-01","New Year","UZ",2037 +"2037-01-26","Kurban Khait* (*estimated)","UZ",2037 +"2037-03-08","Women's Day","UZ",2037 +"2037-03-21","Nauryz","UZ",2037 +"2037-05-09","Memorial Day","UZ",2037 +"2037-09-01","Independence Day","UZ",2037 +"2037-10-01","Teacher's Day","UZ",2037 +"2037-11-08","Ramadan Khait* (*estimated)","UZ",2037 +"2037-12-08","Constitution Day","UZ",2037 +"2038-01-01","New Year","UZ",2038 +"2038-01-16","Kurban Khait* (*estimated)","UZ",2038 +"2038-03-08","Women's Day","UZ",2038 +"2038-03-21","Nauryz","UZ",2038 +"2038-05-09","Memorial Day","UZ",2038 +"2038-09-01","Independence Day","UZ",2038 +"2038-10-01","Teacher's Day","UZ",2038 +"2038-10-29","Ramadan Khait* (*estimated)","UZ",2038 +"2038-12-08","Constitution Day","UZ",2038 +"2039-01-01","New Year","UZ",2039 +"2039-01-05","Kurban Khait* (*estimated)","UZ",2039 +"2039-03-08","Women's Day","UZ",2039 +"2039-03-21","Nauryz","UZ",2039 +"2039-05-09","Memorial Day","UZ",2039 +"2039-09-01","Independence Day","UZ",2039 +"2039-10-01","Teacher's Day","UZ",2039 +"2039-10-19","Ramadan Khait* (*estimated)","UZ",2039 +"2039-12-08","Constitution Day","UZ",2039 +"2039-12-26","Kurban Khait* (*estimated)","UZ",2039 +"2040-01-01","New Year","UZ",2040 +"2040-03-08","Women's Day","UZ",2040 +"2040-03-21","Nauryz","UZ",2040 +"2040-05-09","Memorial Day","UZ",2040 +"2040-09-01","Independence Day","UZ",2040 +"2040-10-01","Teacher's Day","UZ",2040 +"2040-10-07","Ramadan Khait* (*estimated)","UZ",2040 +"2040-12-08","Constitution Day","UZ",2040 +"2040-12-14","Kurban Khait* (*estimated)","UZ",2040 +"2041-01-01","New Year","UZ",2041 +"2041-03-08","Women's Day","UZ",2041 +"2041-03-21","Nauryz","UZ",2041 +"2041-05-09","Memorial Day","UZ",2041 +"2041-09-01","Independence Day","UZ",2041 +"2041-09-26","Ramadan Khait* (*estimated)","UZ",2041 +"2041-10-01","Teacher's Day","UZ",2041 +"2041-12-04","Kurban Khait* (*estimated)","UZ",2041 +"2041-12-08","Constitution Day","UZ",2041 +"2042-01-01","New Year","UZ",2042 +"2042-03-08","Women's Day","UZ",2042 +"2042-03-21","Nauryz","UZ",2042 +"2042-05-09","Memorial Day","UZ",2042 +"2042-09-01","Independence Day","UZ",2042 +"2042-09-15","Ramadan Khait* (*estimated)","UZ",2042 +"2042-10-01","Teacher's Day","UZ",2042 +"2042-11-23","Kurban Khait* (*estimated)","UZ",2042 +"2042-12-08","Constitution Day","UZ",2042 +"2043-01-01","New Year","UZ",2043 +"2043-03-08","Women's Day","UZ",2043 +"2043-03-21","Nauryz","UZ",2043 +"2043-05-09","Memorial Day","UZ",2043 +"2043-09-01","Independence Day","UZ",2043 +"2043-09-04","Ramadan Khait* (*estimated)","UZ",2043 +"2043-10-01","Teacher's Day","UZ",2043 +"2043-11-12","Kurban Khait* (*estimated)","UZ",2043 +"2043-12-08","Constitution Day","UZ",2043 +"2044-01-01","New Year","UZ",2044 +"2044-03-08","Women's Day","UZ",2044 +"2044-03-21","Nauryz","UZ",2044 +"2044-05-09","Memorial Day","UZ",2044 +"2044-08-24","Ramadan Khait* (*estimated)","UZ",2044 +"2044-09-01","Independence Day","UZ",2044 +"2044-10-01","Teacher's Day","UZ",2044 +"2044-10-31","Kurban Khait* (*estimated)","UZ",2044 +"2044-12-08","Constitution Day","UZ",2044 +"1995-01-01","Solemnity of Mary Day","VA",1995 +"1995-01-06","Epiphany","VA",1995 +"1995-02-11","Lateran Treaty Day","VA",1995 +"1995-03-13","Anniversary of the election of Pope Francis","VA",1995 +"1995-03-19","Saint Joseph's Day","VA",1995 +"1995-04-16","Easter Sunday","VA",1995 +"1995-04-17","Easter Monday","VA",1995 +"1995-04-23","Saint George's Day","VA",1995 +"1995-05-01","Saint Joseph the Worker's Day","VA",1995 +"1995-06-29","Saint Peter and Saint Paul's Day","VA",1995 +"1995-08-15","Assumption Day","VA",1995 +"1995-09-08","Nativity of Mary Day","VA",1995 +"1995-11-01","All Saints' Day","VA",1995 +"1995-12-08","Immaculate Conception Day","VA",1995 +"1995-12-25","Christmas Day","VA",1995 +"1995-12-26","Saint Stephen's Day","VA",1995 +"1996-01-01","Solemnity of Mary Day","VA",1996 +"1996-01-06","Epiphany","VA",1996 +"1996-02-11","Lateran Treaty Day","VA",1996 +"1996-03-13","Anniversary of the election of Pope Francis","VA",1996 +"1996-03-19","Saint Joseph's Day","VA",1996 +"1996-04-07","Easter Sunday","VA",1996 +"1996-04-08","Easter Monday","VA",1996 +"1996-04-23","Saint George's Day","VA",1996 +"1996-05-01","Saint Joseph the Worker's Day","VA",1996 +"1996-06-29","Saint Peter and Saint Paul's Day","VA",1996 +"1996-08-15","Assumption Day","VA",1996 +"1996-09-08","Nativity of Mary Day","VA",1996 +"1996-11-01","All Saints' Day","VA",1996 +"1996-12-08","Immaculate Conception Day","VA",1996 +"1996-12-25","Christmas Day","VA",1996 +"1996-12-26","Saint Stephen's Day","VA",1996 +"1997-01-01","Solemnity of Mary Day","VA",1997 +"1997-01-06","Epiphany","VA",1997 +"1997-02-11","Lateran Treaty Day","VA",1997 +"1997-03-13","Anniversary of the election of Pope Francis","VA",1997 +"1997-03-19","Saint Joseph's Day","VA",1997 +"1997-03-30","Easter Sunday","VA",1997 +"1997-03-31","Easter Monday","VA",1997 +"1997-04-23","Saint George's Day","VA",1997 +"1997-05-01","Saint Joseph the Worker's Day","VA",1997 +"1997-06-29","Saint Peter and Saint Paul's Day","VA",1997 +"1997-08-15","Assumption Day","VA",1997 +"1997-09-08","Nativity of Mary Day","VA",1997 +"1997-11-01","All Saints' Day","VA",1997 +"1997-12-08","Immaculate Conception Day","VA",1997 +"1997-12-25","Christmas Day","VA",1997 +"1997-12-26","Saint Stephen's Day","VA",1997 +"1998-01-01","Solemnity of Mary Day","VA",1998 +"1998-01-06","Epiphany","VA",1998 +"1998-02-11","Lateran Treaty Day","VA",1998 +"1998-03-13","Anniversary of the election of Pope Francis","VA",1998 +"1998-03-19","Saint Joseph's Day","VA",1998 +"1998-04-12","Easter Sunday","VA",1998 +"1998-04-13","Easter Monday","VA",1998 +"1998-04-23","Saint George's Day","VA",1998 +"1998-05-01","Saint Joseph the Worker's Day","VA",1998 +"1998-06-29","Saint Peter and Saint Paul's Day","VA",1998 +"1998-08-15","Assumption Day","VA",1998 +"1998-09-08","Nativity of Mary Day","VA",1998 +"1998-11-01","All Saints' Day","VA",1998 +"1998-12-08","Immaculate Conception Day","VA",1998 +"1998-12-25","Christmas Day","VA",1998 +"1998-12-26","Saint Stephen's Day","VA",1998 +"1999-01-01","Solemnity of Mary Day","VA",1999 +"1999-01-06","Epiphany","VA",1999 +"1999-02-11","Lateran Treaty Day","VA",1999 +"1999-03-13","Anniversary of the election of Pope Francis","VA",1999 +"1999-03-19","Saint Joseph's Day","VA",1999 +"1999-04-04","Easter Sunday","VA",1999 +"1999-04-05","Easter Monday","VA",1999 +"1999-04-23","Saint George's Day","VA",1999 +"1999-05-01","Saint Joseph the Worker's Day","VA",1999 +"1999-06-29","Saint Peter and Saint Paul's Day","VA",1999 +"1999-08-15","Assumption Day","VA",1999 +"1999-09-08","Nativity of Mary Day","VA",1999 +"1999-11-01","All Saints' Day","VA",1999 +"1999-12-08","Immaculate Conception Day","VA",1999 +"1999-12-25","Christmas Day","VA",1999 +"1999-12-26","Saint Stephen's Day","VA",1999 +"2000-01-01","Solemnity of Mary Day","VA",2000 +"2000-01-06","Epiphany","VA",2000 +"2000-02-11","Lateran Treaty Day","VA",2000 +"2000-03-13","Anniversary of the election of Pope Francis","VA",2000 +"2000-03-19","Saint Joseph's Day","VA",2000 +"2000-04-23","Easter Sunday","VA",2000 +"2000-04-23","Saint George's Day","VA",2000 +"2000-04-24","Easter Monday","VA",2000 +"2000-05-01","Saint Joseph the Worker's Day","VA",2000 +"2000-06-29","Saint Peter and Saint Paul's Day","VA",2000 +"2000-08-15","Assumption Day","VA",2000 +"2000-09-08","Nativity of Mary Day","VA",2000 +"2000-11-01","All Saints' Day","VA",2000 +"2000-12-08","Immaculate Conception Day","VA",2000 +"2000-12-25","Christmas Day","VA",2000 +"2000-12-26","Saint Stephen's Day","VA",2000 +"2001-01-01","Solemnity of Mary Day","VA",2001 +"2001-01-06","Epiphany","VA",2001 +"2001-02-11","Lateran Treaty Day","VA",2001 +"2001-03-13","Anniversary of the election of Pope Francis","VA",2001 +"2001-03-19","Saint Joseph's Day","VA",2001 +"2001-04-15","Easter Sunday","VA",2001 +"2001-04-16","Easter Monday","VA",2001 +"2001-04-23","Saint George's Day","VA",2001 +"2001-05-01","Saint Joseph the Worker's Day","VA",2001 +"2001-06-29","Saint Peter and Saint Paul's Day","VA",2001 +"2001-08-15","Assumption Day","VA",2001 +"2001-09-08","Nativity of Mary Day","VA",2001 +"2001-11-01","All Saints' Day","VA",2001 +"2001-12-08","Immaculate Conception Day","VA",2001 +"2001-12-25","Christmas Day","VA",2001 +"2001-12-26","Saint Stephen's Day","VA",2001 +"2002-01-01","Solemnity of Mary Day","VA",2002 +"2002-01-06","Epiphany","VA",2002 +"2002-02-11","Lateran Treaty Day","VA",2002 +"2002-03-13","Anniversary of the election of Pope Francis","VA",2002 +"2002-03-19","Saint Joseph's Day","VA",2002 +"2002-03-31","Easter Sunday","VA",2002 +"2002-04-01","Easter Monday","VA",2002 +"2002-04-23","Saint George's Day","VA",2002 +"2002-05-01","Saint Joseph the Worker's Day","VA",2002 +"2002-06-29","Saint Peter and Saint Paul's Day","VA",2002 +"2002-08-15","Assumption Day","VA",2002 +"2002-09-08","Nativity of Mary Day","VA",2002 +"2002-11-01","All Saints' Day","VA",2002 +"2002-12-08","Immaculate Conception Day","VA",2002 +"2002-12-25","Christmas Day","VA",2002 +"2002-12-26","Saint Stephen's Day","VA",2002 +"2003-01-01","Solemnity of Mary Day","VA",2003 +"2003-01-06","Epiphany","VA",2003 +"2003-02-11","Lateran Treaty Day","VA",2003 +"2003-03-13","Anniversary of the election of Pope Francis","VA",2003 +"2003-03-19","Saint Joseph's Day","VA",2003 +"2003-04-20","Easter Sunday","VA",2003 +"2003-04-21","Easter Monday","VA",2003 +"2003-04-23","Saint George's Day","VA",2003 +"2003-05-01","Saint Joseph the Worker's Day","VA",2003 +"2003-06-29","Saint Peter and Saint Paul's Day","VA",2003 +"2003-08-15","Assumption Day","VA",2003 +"2003-09-08","Nativity of Mary Day","VA",2003 +"2003-11-01","All Saints' Day","VA",2003 +"2003-12-08","Immaculate Conception Day","VA",2003 +"2003-12-25","Christmas Day","VA",2003 +"2003-12-26","Saint Stephen's Day","VA",2003 +"2004-01-01","Solemnity of Mary Day","VA",2004 +"2004-01-06","Epiphany","VA",2004 +"2004-02-11","Lateran Treaty Day","VA",2004 +"2004-03-13","Anniversary of the election of Pope Francis","VA",2004 +"2004-03-19","Saint Joseph's Day","VA",2004 +"2004-04-11","Easter Sunday","VA",2004 +"2004-04-12","Easter Monday","VA",2004 +"2004-04-23","Saint George's Day","VA",2004 +"2004-05-01","Saint Joseph the Worker's Day","VA",2004 +"2004-06-29","Saint Peter and Saint Paul's Day","VA",2004 +"2004-08-15","Assumption Day","VA",2004 +"2004-09-08","Nativity of Mary Day","VA",2004 +"2004-11-01","All Saints' Day","VA",2004 +"2004-12-08","Immaculate Conception Day","VA",2004 +"2004-12-25","Christmas Day","VA",2004 +"2004-12-26","Saint Stephen's Day","VA",2004 +"2005-01-01","Solemnity of Mary Day","VA",2005 +"2005-01-06","Epiphany","VA",2005 +"2005-02-11","Lateran Treaty Day","VA",2005 +"2005-03-13","Anniversary of the election of Pope Francis","VA",2005 +"2005-03-19","Saint Joseph's Day","VA",2005 +"2005-03-27","Easter Sunday","VA",2005 +"2005-03-28","Easter Monday","VA",2005 +"2005-04-23","Saint George's Day","VA",2005 +"2005-05-01","Saint Joseph the Worker's Day","VA",2005 +"2005-06-29","Saint Peter and Saint Paul's Day","VA",2005 +"2005-08-15","Assumption Day","VA",2005 +"2005-09-08","Nativity of Mary Day","VA",2005 +"2005-11-01","All Saints' Day","VA",2005 +"2005-12-08","Immaculate Conception Day","VA",2005 +"2005-12-25","Christmas Day","VA",2005 +"2005-12-26","Saint Stephen's Day","VA",2005 +"2006-01-01","Solemnity of Mary Day","VA",2006 +"2006-01-06","Epiphany","VA",2006 +"2006-02-11","Lateran Treaty Day","VA",2006 +"2006-03-13","Anniversary of the election of Pope Francis","VA",2006 +"2006-03-19","Saint Joseph's Day","VA",2006 +"2006-04-16","Easter Sunday","VA",2006 +"2006-04-17","Easter Monday","VA",2006 +"2006-04-23","Saint George's Day","VA",2006 +"2006-05-01","Saint Joseph the Worker's Day","VA",2006 +"2006-06-29","Saint Peter and Saint Paul's Day","VA",2006 +"2006-08-15","Assumption Day","VA",2006 +"2006-09-08","Nativity of Mary Day","VA",2006 +"2006-11-01","All Saints' Day","VA",2006 +"2006-12-08","Immaculate Conception Day","VA",2006 +"2006-12-25","Christmas Day","VA",2006 +"2006-12-26","Saint Stephen's Day","VA",2006 +"2007-01-01","Solemnity of Mary Day","VA",2007 +"2007-01-06","Epiphany","VA",2007 +"2007-02-11","Lateran Treaty Day","VA",2007 +"2007-03-13","Anniversary of the election of Pope Francis","VA",2007 +"2007-03-19","Saint Joseph's Day","VA",2007 +"2007-04-08","Easter Sunday","VA",2007 +"2007-04-09","Easter Monday","VA",2007 +"2007-04-23","Saint George's Day","VA",2007 +"2007-05-01","Saint Joseph the Worker's Day","VA",2007 +"2007-06-29","Saint Peter and Saint Paul's Day","VA",2007 +"2007-08-15","Assumption Day","VA",2007 +"2007-09-08","Nativity of Mary Day","VA",2007 +"2007-11-01","All Saints' Day","VA",2007 +"2007-12-08","Immaculate Conception Day","VA",2007 +"2007-12-25","Christmas Day","VA",2007 +"2007-12-26","Saint Stephen's Day","VA",2007 +"2008-01-01","Solemnity of Mary Day","VA",2008 +"2008-01-06","Epiphany","VA",2008 +"2008-02-11","Lateran Treaty Day","VA",2008 +"2008-03-13","Anniversary of the election of Pope Francis","VA",2008 +"2008-03-19","Saint Joseph's Day","VA",2008 +"2008-03-23","Easter Sunday","VA",2008 +"2008-03-24","Easter Monday","VA",2008 +"2008-04-23","Saint George's Day","VA",2008 +"2008-05-01","Saint Joseph the Worker's Day","VA",2008 +"2008-06-29","Saint Peter and Saint Paul's Day","VA",2008 +"2008-08-15","Assumption Day","VA",2008 +"2008-09-08","Nativity of Mary Day","VA",2008 +"2008-11-01","All Saints' Day","VA",2008 +"2008-12-08","Immaculate Conception Day","VA",2008 +"2008-12-25","Christmas Day","VA",2008 +"2008-12-26","Saint Stephen's Day","VA",2008 +"2009-01-01","Solemnity of Mary Day","VA",2009 +"2009-01-06","Epiphany","VA",2009 +"2009-02-11","Lateran Treaty Day","VA",2009 +"2009-03-13","Anniversary of the election of Pope Francis","VA",2009 +"2009-03-19","Saint Joseph's Day","VA",2009 +"2009-04-12","Easter Sunday","VA",2009 +"2009-04-13","Easter Monday","VA",2009 +"2009-04-23","Saint George's Day","VA",2009 +"2009-05-01","Saint Joseph the Worker's Day","VA",2009 +"2009-06-29","Saint Peter and Saint Paul's Day","VA",2009 +"2009-08-15","Assumption Day","VA",2009 +"2009-09-08","Nativity of Mary Day","VA",2009 +"2009-11-01","All Saints' Day","VA",2009 +"2009-12-08","Immaculate Conception Day","VA",2009 +"2009-12-25","Christmas Day","VA",2009 +"2009-12-26","Saint Stephen's Day","VA",2009 +"2010-01-01","Solemnity of Mary Day","VA",2010 +"2010-01-06","Epiphany","VA",2010 +"2010-02-11","Lateran Treaty Day","VA",2010 +"2010-03-13","Anniversary of the election of Pope Francis","VA",2010 +"2010-03-19","Saint Joseph's Day","VA",2010 +"2010-04-04","Easter Sunday","VA",2010 +"2010-04-05","Easter Monday","VA",2010 +"2010-04-23","Saint George's Day","VA",2010 +"2010-05-01","Saint Joseph the Worker's Day","VA",2010 +"2010-06-29","Saint Peter and Saint Paul's Day","VA",2010 +"2010-08-15","Assumption Day","VA",2010 +"2010-09-08","Nativity of Mary Day","VA",2010 +"2010-11-01","All Saints' Day","VA",2010 +"2010-12-08","Immaculate Conception Day","VA",2010 +"2010-12-25","Christmas Day","VA",2010 +"2010-12-26","Saint Stephen's Day","VA",2010 +"2011-01-01","Solemnity of Mary Day","VA",2011 +"2011-01-06","Epiphany","VA",2011 +"2011-02-11","Lateran Treaty Day","VA",2011 +"2011-03-13","Anniversary of the election of Pope Francis","VA",2011 +"2011-03-19","Saint Joseph's Day","VA",2011 +"2011-04-23","Saint George's Day","VA",2011 +"2011-04-24","Easter Sunday","VA",2011 +"2011-04-25","Easter Monday","VA",2011 +"2011-05-01","Saint Joseph the Worker's Day","VA",2011 +"2011-06-29","Saint Peter and Saint Paul's Day","VA",2011 +"2011-08-15","Assumption Day","VA",2011 +"2011-09-08","Nativity of Mary Day","VA",2011 +"2011-11-01","All Saints' Day","VA",2011 +"2011-12-08","Immaculate Conception Day","VA",2011 +"2011-12-25","Christmas Day","VA",2011 +"2011-12-26","Saint Stephen's Day","VA",2011 +"2012-01-01","Solemnity of Mary Day","VA",2012 +"2012-01-06","Epiphany","VA",2012 +"2012-02-11","Lateran Treaty Day","VA",2012 +"2012-03-13","Anniversary of the election of Pope Francis","VA",2012 +"2012-03-19","Saint Joseph's Day","VA",2012 +"2012-04-08","Easter Sunday","VA",2012 +"2012-04-09","Easter Monday","VA",2012 +"2012-04-23","Saint George's Day","VA",2012 +"2012-05-01","Saint Joseph the Worker's Day","VA",2012 +"2012-06-29","Saint Peter and Saint Paul's Day","VA",2012 +"2012-08-15","Assumption Day","VA",2012 +"2012-09-08","Nativity of Mary Day","VA",2012 +"2012-11-01","All Saints' Day","VA",2012 +"2012-12-08","Immaculate Conception Day","VA",2012 +"2012-12-25","Christmas Day","VA",2012 +"2012-12-26","Saint Stephen's Day","VA",2012 +"2013-01-01","Solemnity of Mary Day","VA",2013 +"2013-01-06","Epiphany","VA",2013 +"2013-02-11","Lateran Treaty Day","VA",2013 +"2013-03-13","Anniversary of the election of Pope Francis","VA",2013 +"2013-03-19","Saint Joseph's Day","VA",2013 +"2013-03-31","Easter Sunday","VA",2013 +"2013-04-01","Easter Monday","VA",2013 +"2013-04-23","Saint George's Day","VA",2013 +"2013-05-01","Saint Joseph the Worker's Day","VA",2013 +"2013-06-29","Saint Peter and Saint Paul's Day","VA",2013 +"2013-08-15","Assumption Day","VA",2013 +"2013-09-08","Nativity of Mary Day","VA",2013 +"2013-11-01","All Saints' Day","VA",2013 +"2013-12-08","Immaculate Conception Day","VA",2013 +"2013-12-25","Christmas Day","VA",2013 +"2013-12-26","Saint Stephen's Day","VA",2013 +"2014-01-01","Solemnity of Mary Day","VA",2014 +"2014-01-06","Epiphany","VA",2014 +"2014-02-11","Lateran Treaty Day","VA",2014 +"2014-03-13","Anniversary of the election of Pope Francis","VA",2014 +"2014-03-19","Saint Joseph's Day","VA",2014 +"2014-04-20","Easter Sunday","VA",2014 +"2014-04-21","Easter Monday","VA",2014 +"2014-04-23","Saint George's Day","VA",2014 +"2014-05-01","Saint Joseph the Worker's Day","VA",2014 +"2014-06-29","Saint Peter and Saint Paul's Day","VA",2014 +"2014-08-15","Assumption Day","VA",2014 +"2014-09-08","Nativity of Mary Day","VA",2014 +"2014-11-01","All Saints' Day","VA",2014 +"2014-12-08","Immaculate Conception Day","VA",2014 +"2014-12-25","Christmas Day","VA",2014 +"2014-12-26","Saint Stephen's Day","VA",2014 +"2015-01-01","Solemnity of Mary Day","VA",2015 +"2015-01-06","Epiphany","VA",2015 +"2015-02-11","Lateran Treaty Day","VA",2015 +"2015-03-13","Anniversary of the election of Pope Francis","VA",2015 +"2015-03-19","Saint Joseph's Day","VA",2015 +"2015-04-05","Easter Sunday","VA",2015 +"2015-04-06","Easter Monday","VA",2015 +"2015-04-23","Saint George's Day","VA",2015 +"2015-05-01","Saint Joseph the Worker's Day","VA",2015 +"2015-06-29","Saint Peter and Saint Paul's Day","VA",2015 +"2015-08-15","Assumption Day","VA",2015 +"2015-09-08","Nativity of Mary Day","VA",2015 +"2015-11-01","All Saints' Day","VA",2015 +"2015-12-08","Immaculate Conception Day","VA",2015 +"2015-12-25","Christmas Day","VA",2015 +"2015-12-26","Saint Stephen's Day","VA",2015 +"2016-01-01","Solemnity of Mary Day","VA",2016 +"2016-01-06","Epiphany","VA",2016 +"2016-02-11","Lateran Treaty Day","VA",2016 +"2016-03-13","Anniversary of the election of Pope Francis","VA",2016 +"2016-03-19","Saint Joseph's Day","VA",2016 +"2016-03-27","Easter Sunday","VA",2016 +"2016-03-28","Easter Monday","VA",2016 +"2016-04-23","Saint George's Day","VA",2016 +"2016-05-01","Saint Joseph the Worker's Day","VA",2016 +"2016-06-29","Saint Peter and Saint Paul's Day","VA",2016 +"2016-08-15","Assumption Day","VA",2016 +"2016-09-08","Nativity of Mary Day","VA",2016 +"2016-11-01","All Saints' Day","VA",2016 +"2016-12-08","Immaculate Conception Day","VA",2016 +"2016-12-25","Christmas Day","VA",2016 +"2016-12-26","Saint Stephen's Day","VA",2016 +"2017-01-01","Solemnity of Mary Day","VA",2017 +"2017-01-06","Epiphany","VA",2017 +"2017-02-11","Lateran Treaty Day","VA",2017 +"2017-03-13","Anniversary of the election of Pope Francis","VA",2017 +"2017-03-19","Saint Joseph's Day","VA",2017 +"2017-04-16","Easter Sunday","VA",2017 +"2017-04-17","Easter Monday","VA",2017 +"2017-04-23","Saint George's Day","VA",2017 +"2017-05-01","Saint Joseph the Worker's Day","VA",2017 +"2017-06-29","Saint Peter and Saint Paul's Day","VA",2017 +"2017-08-15","Assumption Day","VA",2017 +"2017-09-08","Nativity of Mary Day","VA",2017 +"2017-11-01","All Saints' Day","VA",2017 +"2017-12-08","Immaculate Conception Day","VA",2017 +"2017-12-25","Christmas Day","VA",2017 +"2017-12-26","Saint Stephen's Day","VA",2017 +"2018-01-01","Solemnity of Mary Day","VA",2018 +"2018-01-06","Epiphany","VA",2018 +"2018-02-11","Lateran Treaty Day","VA",2018 +"2018-03-13","Anniversary of the election of Pope Francis","VA",2018 +"2018-03-19","Saint Joseph's Day","VA",2018 +"2018-04-01","Easter Sunday","VA",2018 +"2018-04-02","Easter Monday","VA",2018 +"2018-04-23","Saint George's Day","VA",2018 +"2018-05-01","Saint Joseph the Worker's Day","VA",2018 +"2018-06-29","Saint Peter and Saint Paul's Day","VA",2018 +"2018-08-15","Assumption Day","VA",2018 +"2018-09-08","Nativity of Mary Day","VA",2018 +"2018-11-01","All Saints' Day","VA",2018 +"2018-12-08","Immaculate Conception Day","VA",2018 +"2018-12-25","Christmas Day","VA",2018 +"2018-12-26","Saint Stephen's Day","VA",2018 +"2019-01-01","Solemnity of Mary Day","VA",2019 +"2019-01-06","Epiphany","VA",2019 +"2019-02-11","Lateran Treaty Day","VA",2019 +"2019-03-13","Anniversary of the election of Pope Francis","VA",2019 +"2019-03-19","Saint Joseph's Day","VA",2019 +"2019-04-21","Easter Sunday","VA",2019 +"2019-04-22","Easter Monday","VA",2019 +"2019-04-23","Saint George's Day","VA",2019 +"2019-05-01","Saint Joseph the Worker's Day","VA",2019 +"2019-06-29","Saint Peter and Saint Paul's Day","VA",2019 +"2019-08-15","Assumption Day","VA",2019 +"2019-09-08","Nativity of Mary Day","VA",2019 +"2019-11-01","All Saints' Day","VA",2019 +"2019-12-08","Immaculate Conception Day","VA",2019 +"2019-12-25","Christmas Day","VA",2019 +"2019-12-26","Saint Stephen's Day","VA",2019 +"2020-01-01","Solemnity of Mary Day","VA",2020 +"2020-01-06","Epiphany","VA",2020 +"2020-02-11","Lateran Treaty Day","VA",2020 +"2020-03-13","Anniversary of the election of Pope Francis","VA",2020 +"2020-03-19","Saint Joseph's Day","VA",2020 +"2020-04-12","Easter Sunday","VA",2020 +"2020-04-13","Easter Monday","VA",2020 +"2020-04-23","Saint George's Day","VA",2020 +"2020-05-01","Saint Joseph the Worker's Day","VA",2020 +"2020-06-29","Saint Peter and Saint Paul's Day","VA",2020 +"2020-08-15","Assumption Day","VA",2020 +"2020-09-08","Nativity of Mary Day","VA",2020 +"2020-11-01","All Saints' Day","VA",2020 +"2020-12-08","Immaculate Conception Day","VA",2020 +"2020-12-25","Christmas Day","VA",2020 +"2020-12-26","Saint Stephen's Day","VA",2020 +"2021-01-01","Solemnity of Mary Day","VA",2021 +"2021-01-06","Epiphany","VA",2021 +"2021-02-11","Lateran Treaty Day","VA",2021 +"2021-03-13","Anniversary of the election of Pope Francis","VA",2021 +"2021-03-19","Saint Joseph's Day","VA",2021 +"2021-04-04","Easter Sunday","VA",2021 +"2021-04-05","Easter Monday","VA",2021 +"2021-04-23","Saint George's Day","VA",2021 +"2021-05-01","Saint Joseph the Worker's Day","VA",2021 +"2021-06-29","Saint Peter and Saint Paul's Day","VA",2021 +"2021-08-15","Assumption Day","VA",2021 +"2021-09-08","Nativity of Mary Day","VA",2021 +"2021-11-01","All Saints' Day","VA",2021 +"2021-12-08","Immaculate Conception Day","VA",2021 +"2021-12-25","Christmas Day","VA",2021 +"2021-12-26","Saint Stephen's Day","VA",2021 +"2022-01-01","Solemnity of Mary Day","VA",2022 +"2022-01-06","Epiphany","VA",2022 +"2022-02-11","Lateran Treaty Day","VA",2022 +"2022-03-13","Anniversary of the election of Pope Francis","VA",2022 +"2022-03-19","Saint Joseph's Day","VA",2022 +"2022-04-17","Easter Sunday","VA",2022 +"2022-04-18","Easter Monday","VA",2022 +"2022-04-23","Saint George's Day","VA",2022 +"2022-05-01","Saint Joseph the Worker's Day","VA",2022 +"2022-06-29","Saint Peter and Saint Paul's Day","VA",2022 +"2022-08-15","Assumption Day","VA",2022 +"2022-09-08","Nativity of Mary Day","VA",2022 +"2022-11-01","All Saints' Day","VA",2022 +"2022-12-08","Immaculate Conception Day","VA",2022 +"2022-12-25","Christmas Day","VA",2022 +"2022-12-26","Saint Stephen's Day","VA",2022 +"2023-01-01","Solemnity of Mary Day","VA",2023 +"2023-01-06","Epiphany","VA",2023 +"2023-02-11","Lateran Treaty Day","VA",2023 +"2023-03-13","Anniversary of the election of Pope Francis","VA",2023 +"2023-03-19","Saint Joseph's Day","VA",2023 +"2023-04-09","Easter Sunday","VA",2023 +"2023-04-10","Easter Monday","VA",2023 +"2023-04-23","Saint George's Day","VA",2023 +"2023-05-01","Saint Joseph the Worker's Day","VA",2023 +"2023-06-29","Saint Peter and Saint Paul's Day","VA",2023 +"2023-08-15","Assumption Day","VA",2023 +"2023-09-08","Nativity of Mary Day","VA",2023 +"2023-11-01","All Saints' Day","VA",2023 +"2023-12-08","Immaculate Conception Day","VA",2023 +"2023-12-25","Christmas Day","VA",2023 +"2023-12-26","Saint Stephen's Day","VA",2023 +"2024-01-01","Solemnity of Mary Day","VA",2024 +"2024-01-06","Epiphany","VA",2024 +"2024-02-11","Lateran Treaty Day","VA",2024 +"2024-03-13","Anniversary of the election of Pope Francis","VA",2024 +"2024-03-19","Saint Joseph's Day","VA",2024 +"2024-03-31","Easter Sunday","VA",2024 +"2024-04-01","Easter Monday","VA",2024 +"2024-04-23","Saint George's Day","VA",2024 +"2024-05-01","Saint Joseph the Worker's Day","VA",2024 +"2024-06-29","Saint Peter and Saint Paul's Day","VA",2024 +"2024-08-15","Assumption Day","VA",2024 +"2024-09-08","Nativity of Mary Day","VA",2024 +"2024-11-01","All Saints' Day","VA",2024 +"2024-12-08","Immaculate Conception Day","VA",2024 +"2024-12-25","Christmas Day","VA",2024 +"2024-12-26","Saint Stephen's Day","VA",2024 +"2025-01-01","Solemnity of Mary Day","VA",2025 +"2025-01-06","Epiphany","VA",2025 +"2025-02-11","Lateran Treaty Day","VA",2025 +"2025-03-13","Anniversary of the election of Pope Francis","VA",2025 +"2025-03-19","Saint Joseph's Day","VA",2025 +"2025-04-20","Easter Sunday","VA",2025 +"2025-04-21","Easter Monday","VA",2025 +"2025-04-23","Saint George's Day","VA",2025 +"2025-05-01","Saint Joseph the Worker's Day","VA",2025 +"2025-06-29","Saint Peter and Saint Paul's Day","VA",2025 +"2025-08-15","Assumption Day","VA",2025 +"2025-09-08","Nativity of Mary Day","VA",2025 +"2025-11-01","All Saints' Day","VA",2025 +"2025-12-08","Immaculate Conception Day","VA",2025 +"2025-12-25","Christmas Day","VA",2025 +"2025-12-26","Saint Stephen's Day","VA",2025 +"2026-01-01","Solemnity of Mary Day","VA",2026 +"2026-01-06","Epiphany","VA",2026 +"2026-02-11","Lateran Treaty Day","VA",2026 +"2026-03-13","Anniversary of the election of Pope Francis","VA",2026 +"2026-03-19","Saint Joseph's Day","VA",2026 +"2026-04-05","Easter Sunday","VA",2026 +"2026-04-06","Easter Monday","VA",2026 +"2026-04-23","Saint George's Day","VA",2026 +"2026-05-01","Saint Joseph the Worker's Day","VA",2026 +"2026-06-29","Saint Peter and Saint Paul's Day","VA",2026 +"2026-08-15","Assumption Day","VA",2026 +"2026-09-08","Nativity of Mary Day","VA",2026 +"2026-11-01","All Saints' Day","VA",2026 +"2026-12-08","Immaculate Conception Day","VA",2026 +"2026-12-25","Christmas Day","VA",2026 +"2026-12-26","Saint Stephen's Day","VA",2026 +"2027-01-01","Solemnity of Mary Day","VA",2027 +"2027-01-06","Epiphany","VA",2027 +"2027-02-11","Lateran Treaty Day","VA",2027 +"2027-03-13","Anniversary of the election of Pope Francis","VA",2027 +"2027-03-19","Saint Joseph's Day","VA",2027 +"2027-03-28","Easter Sunday","VA",2027 +"2027-03-29","Easter Monday","VA",2027 +"2027-04-23","Saint George's Day","VA",2027 +"2027-05-01","Saint Joseph the Worker's Day","VA",2027 +"2027-06-29","Saint Peter and Saint Paul's Day","VA",2027 +"2027-08-15","Assumption Day","VA",2027 +"2027-09-08","Nativity of Mary Day","VA",2027 +"2027-11-01","All Saints' Day","VA",2027 +"2027-12-08","Immaculate Conception Day","VA",2027 +"2027-12-25","Christmas Day","VA",2027 +"2027-12-26","Saint Stephen's Day","VA",2027 +"2028-01-01","Solemnity of Mary Day","VA",2028 +"2028-01-06","Epiphany","VA",2028 +"2028-02-11","Lateran Treaty Day","VA",2028 +"2028-03-13","Anniversary of the election of Pope Francis","VA",2028 +"2028-03-19","Saint Joseph's Day","VA",2028 +"2028-04-16","Easter Sunday","VA",2028 +"2028-04-17","Easter Monday","VA",2028 +"2028-04-23","Saint George's Day","VA",2028 +"2028-05-01","Saint Joseph the Worker's Day","VA",2028 +"2028-06-29","Saint Peter and Saint Paul's Day","VA",2028 +"2028-08-15","Assumption Day","VA",2028 +"2028-09-08","Nativity of Mary Day","VA",2028 +"2028-11-01","All Saints' Day","VA",2028 +"2028-12-08","Immaculate Conception Day","VA",2028 +"2028-12-25","Christmas Day","VA",2028 +"2028-12-26","Saint Stephen's Day","VA",2028 +"2029-01-01","Solemnity of Mary Day","VA",2029 +"2029-01-06","Epiphany","VA",2029 +"2029-02-11","Lateran Treaty Day","VA",2029 +"2029-03-13","Anniversary of the election of Pope Francis","VA",2029 +"2029-03-19","Saint Joseph's Day","VA",2029 +"2029-04-01","Easter Sunday","VA",2029 +"2029-04-02","Easter Monday","VA",2029 +"2029-04-23","Saint George's Day","VA",2029 +"2029-05-01","Saint Joseph the Worker's Day","VA",2029 +"2029-06-29","Saint Peter and Saint Paul's Day","VA",2029 +"2029-08-15","Assumption Day","VA",2029 +"2029-09-08","Nativity of Mary Day","VA",2029 +"2029-11-01","All Saints' Day","VA",2029 +"2029-12-08","Immaculate Conception Day","VA",2029 +"2029-12-25","Christmas Day","VA",2029 +"2029-12-26","Saint Stephen's Day","VA",2029 +"2030-01-01","Solemnity of Mary Day","VA",2030 +"2030-01-06","Epiphany","VA",2030 +"2030-02-11","Lateran Treaty Day","VA",2030 +"2030-03-13","Anniversary of the election of Pope Francis","VA",2030 +"2030-03-19","Saint Joseph's Day","VA",2030 +"2030-04-21","Easter Sunday","VA",2030 +"2030-04-22","Easter Monday","VA",2030 +"2030-04-23","Saint George's Day","VA",2030 +"2030-05-01","Saint Joseph the Worker's Day","VA",2030 +"2030-06-29","Saint Peter and Saint Paul's Day","VA",2030 +"2030-08-15","Assumption Day","VA",2030 +"2030-09-08","Nativity of Mary Day","VA",2030 +"2030-11-01","All Saints' Day","VA",2030 +"2030-12-08","Immaculate Conception Day","VA",2030 +"2030-12-25","Christmas Day","VA",2030 +"2030-12-26","Saint Stephen's Day","VA",2030 +"2031-01-01","Solemnity of Mary Day","VA",2031 +"2031-01-06","Epiphany","VA",2031 +"2031-02-11","Lateran Treaty Day","VA",2031 +"2031-03-13","Anniversary of the election of Pope Francis","VA",2031 +"2031-03-19","Saint Joseph's Day","VA",2031 +"2031-04-13","Easter Sunday","VA",2031 +"2031-04-14","Easter Monday","VA",2031 +"2031-04-23","Saint George's Day","VA",2031 +"2031-05-01","Saint Joseph the Worker's Day","VA",2031 +"2031-06-29","Saint Peter and Saint Paul's Day","VA",2031 +"2031-08-15","Assumption Day","VA",2031 +"2031-09-08","Nativity of Mary Day","VA",2031 +"2031-11-01","All Saints' Day","VA",2031 +"2031-12-08","Immaculate Conception Day","VA",2031 +"2031-12-25","Christmas Day","VA",2031 +"2031-12-26","Saint Stephen's Day","VA",2031 +"2032-01-01","Solemnity of Mary Day","VA",2032 +"2032-01-06","Epiphany","VA",2032 +"2032-02-11","Lateran Treaty Day","VA",2032 +"2032-03-13","Anniversary of the election of Pope Francis","VA",2032 +"2032-03-19","Saint Joseph's Day","VA",2032 +"2032-03-28","Easter Sunday","VA",2032 +"2032-03-29","Easter Monday","VA",2032 +"2032-04-23","Saint George's Day","VA",2032 +"2032-05-01","Saint Joseph the Worker's Day","VA",2032 +"2032-06-29","Saint Peter and Saint Paul's Day","VA",2032 +"2032-08-15","Assumption Day","VA",2032 +"2032-09-08","Nativity of Mary Day","VA",2032 +"2032-11-01","All Saints' Day","VA",2032 +"2032-12-08","Immaculate Conception Day","VA",2032 +"2032-12-25","Christmas Day","VA",2032 +"2032-12-26","Saint Stephen's Day","VA",2032 +"2033-01-01","Solemnity of Mary Day","VA",2033 +"2033-01-06","Epiphany","VA",2033 +"2033-02-11","Lateran Treaty Day","VA",2033 +"2033-03-13","Anniversary of the election of Pope Francis","VA",2033 +"2033-03-19","Saint Joseph's Day","VA",2033 +"2033-04-17","Easter Sunday","VA",2033 +"2033-04-18","Easter Monday","VA",2033 +"2033-04-23","Saint George's Day","VA",2033 +"2033-05-01","Saint Joseph the Worker's Day","VA",2033 +"2033-06-29","Saint Peter and Saint Paul's Day","VA",2033 +"2033-08-15","Assumption Day","VA",2033 +"2033-09-08","Nativity of Mary Day","VA",2033 +"2033-11-01","All Saints' Day","VA",2033 +"2033-12-08","Immaculate Conception Day","VA",2033 +"2033-12-25","Christmas Day","VA",2033 +"2033-12-26","Saint Stephen's Day","VA",2033 +"2034-01-01","Solemnity of Mary Day","VA",2034 +"2034-01-06","Epiphany","VA",2034 +"2034-02-11","Lateran Treaty Day","VA",2034 +"2034-03-13","Anniversary of the election of Pope Francis","VA",2034 +"2034-03-19","Saint Joseph's Day","VA",2034 +"2034-04-09","Easter Sunday","VA",2034 +"2034-04-10","Easter Monday","VA",2034 +"2034-04-23","Saint George's Day","VA",2034 +"2034-05-01","Saint Joseph the Worker's Day","VA",2034 +"2034-06-29","Saint Peter and Saint Paul's Day","VA",2034 +"2034-08-15","Assumption Day","VA",2034 +"2034-09-08","Nativity of Mary Day","VA",2034 +"2034-11-01","All Saints' Day","VA",2034 +"2034-12-08","Immaculate Conception Day","VA",2034 +"2034-12-25","Christmas Day","VA",2034 +"2034-12-26","Saint Stephen's Day","VA",2034 +"2035-01-01","Solemnity of Mary Day","VA",2035 +"2035-01-06","Epiphany","VA",2035 +"2035-02-11","Lateran Treaty Day","VA",2035 +"2035-03-13","Anniversary of the election of Pope Francis","VA",2035 +"2035-03-19","Saint Joseph's Day","VA",2035 +"2035-03-25","Easter Sunday","VA",2035 +"2035-03-26","Easter Monday","VA",2035 +"2035-04-23","Saint George's Day","VA",2035 +"2035-05-01","Saint Joseph the Worker's Day","VA",2035 +"2035-06-29","Saint Peter and Saint Paul's Day","VA",2035 +"2035-08-15","Assumption Day","VA",2035 +"2035-09-08","Nativity of Mary Day","VA",2035 +"2035-11-01","All Saints' Day","VA",2035 +"2035-12-08","Immaculate Conception Day","VA",2035 +"2035-12-25","Christmas Day","VA",2035 +"2035-12-26","Saint Stephen's Day","VA",2035 +"2036-01-01","Solemnity of Mary Day","VA",2036 +"2036-01-06","Epiphany","VA",2036 +"2036-02-11","Lateran Treaty Day","VA",2036 +"2036-03-13","Anniversary of the election of Pope Francis","VA",2036 +"2036-03-19","Saint Joseph's Day","VA",2036 +"2036-04-13","Easter Sunday","VA",2036 +"2036-04-14","Easter Monday","VA",2036 +"2036-04-23","Saint George's Day","VA",2036 +"2036-05-01","Saint Joseph the Worker's Day","VA",2036 +"2036-06-29","Saint Peter and Saint Paul's Day","VA",2036 +"2036-08-15","Assumption Day","VA",2036 +"2036-09-08","Nativity of Mary Day","VA",2036 +"2036-11-01","All Saints' Day","VA",2036 +"2036-12-08","Immaculate Conception Day","VA",2036 +"2036-12-25","Christmas Day","VA",2036 +"2036-12-26","Saint Stephen's Day","VA",2036 +"2037-01-01","Solemnity of Mary Day","VA",2037 +"2037-01-06","Epiphany","VA",2037 +"2037-02-11","Lateran Treaty Day","VA",2037 +"2037-03-13","Anniversary of the election of Pope Francis","VA",2037 +"2037-03-19","Saint Joseph's Day","VA",2037 +"2037-04-05","Easter Sunday","VA",2037 +"2037-04-06","Easter Monday","VA",2037 +"2037-04-23","Saint George's Day","VA",2037 +"2037-05-01","Saint Joseph the Worker's Day","VA",2037 +"2037-06-29","Saint Peter and Saint Paul's Day","VA",2037 +"2037-08-15","Assumption Day","VA",2037 +"2037-09-08","Nativity of Mary Day","VA",2037 +"2037-11-01","All Saints' Day","VA",2037 +"2037-12-08","Immaculate Conception Day","VA",2037 +"2037-12-25","Christmas Day","VA",2037 +"2037-12-26","Saint Stephen's Day","VA",2037 +"2038-01-01","Solemnity of Mary Day","VA",2038 +"2038-01-06","Epiphany","VA",2038 +"2038-02-11","Lateran Treaty Day","VA",2038 +"2038-03-13","Anniversary of the election of Pope Francis","VA",2038 +"2038-03-19","Saint Joseph's Day","VA",2038 +"2038-04-23","Saint George's Day","VA",2038 +"2038-04-25","Easter Sunday","VA",2038 +"2038-04-26","Easter Monday","VA",2038 +"2038-05-01","Saint Joseph the Worker's Day","VA",2038 +"2038-06-29","Saint Peter and Saint Paul's Day","VA",2038 +"2038-08-15","Assumption Day","VA",2038 +"2038-09-08","Nativity of Mary Day","VA",2038 +"2038-11-01","All Saints' Day","VA",2038 +"2038-12-08","Immaculate Conception Day","VA",2038 +"2038-12-25","Christmas Day","VA",2038 +"2038-12-26","Saint Stephen's Day","VA",2038 +"2039-01-01","Solemnity of Mary Day","VA",2039 +"2039-01-06","Epiphany","VA",2039 +"2039-02-11","Lateran Treaty Day","VA",2039 +"2039-03-13","Anniversary of the election of Pope Francis","VA",2039 +"2039-03-19","Saint Joseph's Day","VA",2039 +"2039-04-10","Easter Sunday","VA",2039 +"2039-04-11","Easter Monday","VA",2039 +"2039-04-23","Saint George's Day","VA",2039 +"2039-05-01","Saint Joseph the Worker's Day","VA",2039 +"2039-06-29","Saint Peter and Saint Paul's Day","VA",2039 +"2039-08-15","Assumption Day","VA",2039 +"2039-09-08","Nativity of Mary Day","VA",2039 +"2039-11-01","All Saints' Day","VA",2039 +"2039-12-08","Immaculate Conception Day","VA",2039 +"2039-12-25","Christmas Day","VA",2039 +"2039-12-26","Saint Stephen's Day","VA",2039 +"2040-01-01","Solemnity of Mary Day","VA",2040 +"2040-01-06","Epiphany","VA",2040 +"2040-02-11","Lateran Treaty Day","VA",2040 +"2040-03-13","Anniversary of the election of Pope Francis","VA",2040 +"2040-03-19","Saint Joseph's Day","VA",2040 +"2040-04-01","Easter Sunday","VA",2040 +"2040-04-02","Easter Monday","VA",2040 +"2040-04-23","Saint George's Day","VA",2040 +"2040-05-01","Saint Joseph the Worker's Day","VA",2040 +"2040-06-29","Saint Peter and Saint Paul's Day","VA",2040 +"2040-08-15","Assumption Day","VA",2040 +"2040-09-08","Nativity of Mary Day","VA",2040 +"2040-11-01","All Saints' Day","VA",2040 +"2040-12-08","Immaculate Conception Day","VA",2040 +"2040-12-25","Christmas Day","VA",2040 +"2040-12-26","Saint Stephen's Day","VA",2040 +"2041-01-01","Solemnity of Mary Day","VA",2041 +"2041-01-06","Epiphany","VA",2041 +"2041-02-11","Lateran Treaty Day","VA",2041 +"2041-03-13","Anniversary of the election of Pope Francis","VA",2041 +"2041-03-19","Saint Joseph's Day","VA",2041 +"2041-04-21","Easter Sunday","VA",2041 +"2041-04-22","Easter Monday","VA",2041 +"2041-04-23","Saint George's Day","VA",2041 +"2041-05-01","Saint Joseph the Worker's Day","VA",2041 +"2041-06-29","Saint Peter and Saint Paul's Day","VA",2041 +"2041-08-15","Assumption Day","VA",2041 +"2041-09-08","Nativity of Mary Day","VA",2041 +"2041-11-01","All Saints' Day","VA",2041 +"2041-12-08","Immaculate Conception Day","VA",2041 +"2041-12-25","Christmas Day","VA",2041 +"2041-12-26","Saint Stephen's Day","VA",2041 +"2042-01-01","Solemnity of Mary Day","VA",2042 +"2042-01-06","Epiphany","VA",2042 +"2042-02-11","Lateran Treaty Day","VA",2042 +"2042-03-13","Anniversary of the election of Pope Francis","VA",2042 +"2042-03-19","Saint Joseph's Day","VA",2042 +"2042-04-06","Easter Sunday","VA",2042 +"2042-04-07","Easter Monday","VA",2042 +"2042-04-23","Saint George's Day","VA",2042 +"2042-05-01","Saint Joseph the Worker's Day","VA",2042 +"2042-06-29","Saint Peter and Saint Paul's Day","VA",2042 +"2042-08-15","Assumption Day","VA",2042 +"2042-09-08","Nativity of Mary Day","VA",2042 +"2042-11-01","All Saints' Day","VA",2042 +"2042-12-08","Immaculate Conception Day","VA",2042 +"2042-12-25","Christmas Day","VA",2042 +"2042-12-26","Saint Stephen's Day","VA",2042 +"2043-01-01","Solemnity of Mary Day","VA",2043 +"2043-01-06","Epiphany","VA",2043 +"2043-02-11","Lateran Treaty Day","VA",2043 +"2043-03-13","Anniversary of the election of Pope Francis","VA",2043 +"2043-03-19","Saint Joseph's Day","VA",2043 +"2043-03-29","Easter Sunday","VA",2043 +"2043-03-30","Easter Monday","VA",2043 +"2043-04-23","Saint George's Day","VA",2043 +"2043-05-01","Saint Joseph the Worker's Day","VA",2043 +"2043-06-29","Saint Peter and Saint Paul's Day","VA",2043 +"2043-08-15","Assumption Day","VA",2043 +"2043-09-08","Nativity of Mary Day","VA",2043 +"2043-11-01","All Saints' Day","VA",2043 +"2043-12-08","Immaculate Conception Day","VA",2043 +"2043-12-25","Christmas Day","VA",2043 +"2043-12-26","Saint Stephen's Day","VA",2043 +"2044-01-01","Solemnity of Mary Day","VA",2044 +"2044-01-06","Epiphany","VA",2044 +"2044-02-11","Lateran Treaty Day","VA",2044 +"2044-03-13","Anniversary of the election of Pope Francis","VA",2044 +"2044-03-19","Saint Joseph's Day","VA",2044 +"2044-04-17","Easter Sunday","VA",2044 +"2044-04-18","Easter Monday","VA",2044 +"2044-04-23","Saint George's Day","VA",2044 +"2044-05-01","Saint Joseph the Worker's Day","VA",2044 +"2044-06-29","Saint Peter and Saint Paul's Day","VA",2044 +"2044-08-15","Assumption Day","VA",2044 +"2044-09-08","Nativity of Mary Day","VA",2044 +"2044-11-01","All Saints' Day","VA",2044 +"2044-12-08","Immaculate Conception Day","VA",2044 +"2044-12-25","Christmas Day","VA",2044 +"2044-12-26","Saint Stephen's Day","VA",2044 +"1995-01-01","New Year's Day","VE",1995 +"1995-02-27","Monday of Carnival","VE",1995 +"1995-02-28","Tuesday of Carnival","VE",1995 +"1995-04-13","Maundy Thursday","VE",1995 +"1995-04-14","Good Friday","VE",1995 +"1995-04-19","Declaration of Independence","VE",1995 +"1995-05-01","International Worker's Day","VE",1995 +"1995-06-24","Battle of Carabobo","VE",1995 +"1995-07-05","Independence Day","VE",1995 +"1995-07-24","Birthday of Simon Bolivar","VE",1995 +"1995-10-12","Columbus Day","VE",1995 +"1995-12-24","Christmas Eve","VE",1995 +"1995-12-25","Christmas Day","VE",1995 +"1995-12-31","New Year's Eve","VE",1995 +"1996-01-01","New Year's Day","VE",1996 +"1996-02-19","Monday of Carnival","VE",1996 +"1996-02-20","Tuesday of Carnival","VE",1996 +"1996-04-04","Maundy Thursday","VE",1996 +"1996-04-05","Good Friday","VE",1996 +"1996-04-19","Declaration of Independence","VE",1996 +"1996-05-01","International Worker's Day","VE",1996 +"1996-06-24","Battle of Carabobo","VE",1996 +"1996-07-05","Independence Day","VE",1996 +"1996-07-24","Birthday of Simon Bolivar","VE",1996 +"1996-10-12","Columbus Day","VE",1996 +"1996-12-24","Christmas Eve","VE",1996 +"1996-12-25","Christmas Day","VE",1996 +"1996-12-31","New Year's Eve","VE",1996 +"1997-01-01","New Year's Day","VE",1997 +"1997-02-10","Monday of Carnival","VE",1997 +"1997-02-11","Tuesday of Carnival","VE",1997 +"1997-03-27","Maundy Thursday","VE",1997 +"1997-03-28","Good Friday","VE",1997 +"1997-04-19","Declaration of Independence","VE",1997 +"1997-05-01","International Worker's Day","VE",1997 +"1997-06-24","Battle of Carabobo","VE",1997 +"1997-07-05","Independence Day","VE",1997 +"1997-07-24","Birthday of Simon Bolivar","VE",1997 +"1997-10-12","Columbus Day","VE",1997 +"1997-12-24","Christmas Eve","VE",1997 +"1997-12-25","Christmas Day","VE",1997 +"1997-12-31","New Year's Eve","VE",1997 +"1998-01-01","New Year's Day","VE",1998 +"1998-02-23","Monday of Carnival","VE",1998 +"1998-02-24","Tuesday of Carnival","VE",1998 +"1998-04-09","Maundy Thursday","VE",1998 +"1998-04-10","Good Friday","VE",1998 +"1998-04-19","Declaration of Independence","VE",1998 +"1998-05-01","International Worker's Day","VE",1998 +"1998-06-24","Battle of Carabobo","VE",1998 +"1998-07-05","Independence Day","VE",1998 +"1998-07-24","Birthday of Simon Bolivar","VE",1998 +"1998-10-12","Columbus Day","VE",1998 +"1998-12-24","Christmas Eve","VE",1998 +"1998-12-25","Christmas Day","VE",1998 +"1998-12-31","New Year's Eve","VE",1998 +"1999-01-01","New Year's Day","VE",1999 +"1999-02-15","Monday of Carnival","VE",1999 +"1999-02-16","Tuesday of Carnival","VE",1999 +"1999-04-01","Maundy Thursday","VE",1999 +"1999-04-02","Good Friday","VE",1999 +"1999-04-19","Declaration of Independence","VE",1999 +"1999-05-01","International Worker's Day","VE",1999 +"1999-06-24","Battle of Carabobo","VE",1999 +"1999-07-05","Independence Day","VE",1999 +"1999-07-24","Birthday of Simon Bolivar","VE",1999 +"1999-10-12","Columbus Day","VE",1999 +"1999-12-24","Christmas Eve","VE",1999 +"1999-12-25","Christmas Day","VE",1999 +"1999-12-31","New Year's Eve","VE",1999 +"2000-01-01","New Year's Day","VE",2000 +"2000-03-06","Monday of Carnival","VE",2000 +"2000-03-07","Tuesday of Carnival","VE",2000 +"2000-04-19","Declaration of Independence","VE",2000 +"2000-04-20","Maundy Thursday","VE",2000 +"2000-04-21","Good Friday","VE",2000 +"2000-05-01","International Worker's Day","VE",2000 +"2000-06-24","Battle of Carabobo","VE",2000 +"2000-07-05","Independence Day","VE",2000 +"2000-07-24","Birthday of Simon Bolivar","VE",2000 +"2000-10-12","Columbus Day","VE",2000 +"2000-12-24","Christmas Eve","VE",2000 +"2000-12-25","Christmas Day","VE",2000 +"2000-12-31","New Year's Eve","VE",2000 +"2001-01-01","New Year's Day","VE",2001 +"2001-02-26","Monday of Carnival","VE",2001 +"2001-02-27","Tuesday of Carnival","VE",2001 +"2001-04-12","Maundy Thursday","VE",2001 +"2001-04-13","Good Friday","VE",2001 +"2001-04-19","Declaration of Independence","VE",2001 +"2001-05-01","International Worker's Day","VE",2001 +"2001-06-24","Battle of Carabobo","VE",2001 +"2001-07-05","Independence Day","VE",2001 +"2001-07-24","Birthday of Simon Bolivar","VE",2001 +"2001-10-12","Columbus Day","VE",2001 +"2001-12-24","Christmas Eve","VE",2001 +"2001-12-25","Christmas Day","VE",2001 +"2001-12-31","New Year's Eve","VE",2001 +"2002-01-01","New Year's Day","VE",2002 +"2002-02-11","Monday of Carnival","VE",2002 +"2002-02-12","Tuesday of Carnival","VE",2002 +"2002-03-28","Maundy Thursday","VE",2002 +"2002-03-29","Good Friday","VE",2002 +"2002-04-19","Declaration of Independence","VE",2002 +"2002-05-01","International Worker's Day","VE",2002 +"2002-06-24","Battle of Carabobo","VE",2002 +"2002-07-05","Independence Day","VE",2002 +"2002-07-24","Birthday of Simon Bolivar","VE",2002 +"2002-10-12","Day of Indigenous Resistance","VE",2002 +"2002-12-24","Christmas Eve","VE",2002 +"2002-12-25","Christmas Day","VE",2002 +"2002-12-31","New Year's Eve","VE",2002 +"2003-01-01","New Year's Day","VE",2003 +"2003-03-03","Monday of Carnival","VE",2003 +"2003-03-04","Tuesday of Carnival","VE",2003 +"2003-04-17","Maundy Thursday","VE",2003 +"2003-04-18","Good Friday","VE",2003 +"2003-04-19","Declaration of Independence","VE",2003 +"2003-05-01","International Worker's Day","VE",2003 +"2003-06-24","Battle of Carabobo","VE",2003 +"2003-07-05","Independence Day","VE",2003 +"2003-07-24","Birthday of Simon Bolivar","VE",2003 +"2003-10-12","Day of Indigenous Resistance","VE",2003 +"2003-12-24","Christmas Eve","VE",2003 +"2003-12-25","Christmas Day","VE",2003 +"2003-12-31","New Year's Eve","VE",2003 +"2004-01-01","New Year's Day","VE",2004 +"2004-02-23","Monday of Carnival","VE",2004 +"2004-02-24","Tuesday of Carnival","VE",2004 +"2004-04-08","Maundy Thursday","VE",2004 +"2004-04-09","Good Friday","VE",2004 +"2004-04-19","Declaration of Independence","VE",2004 +"2004-05-01","International Worker's Day","VE",2004 +"2004-06-24","Battle of Carabobo","VE",2004 +"2004-07-05","Independence Day","VE",2004 +"2004-07-24","Birthday of Simon Bolivar","VE",2004 +"2004-10-12","Day of Indigenous Resistance","VE",2004 +"2004-12-24","Christmas Eve","VE",2004 +"2004-12-25","Christmas Day","VE",2004 +"2004-12-31","New Year's Eve","VE",2004 +"2005-01-01","New Year's Day","VE",2005 +"2005-02-07","Monday of Carnival","VE",2005 +"2005-02-08","Tuesday of Carnival","VE",2005 +"2005-03-24","Maundy Thursday","VE",2005 +"2005-03-25","Good Friday","VE",2005 +"2005-04-19","Declaration of Independence","VE",2005 +"2005-05-01","International Worker's Day","VE",2005 +"2005-06-24","Battle of Carabobo","VE",2005 +"2005-07-05","Independence Day","VE",2005 +"2005-07-24","Birthday of Simon Bolivar","VE",2005 +"2005-10-12","Day of Indigenous Resistance","VE",2005 +"2005-12-24","Christmas Eve","VE",2005 +"2005-12-25","Christmas Day","VE",2005 +"2005-12-31","New Year's Eve","VE",2005 +"2006-01-01","New Year's Day","VE",2006 +"2006-02-27","Monday of Carnival","VE",2006 +"2006-02-28","Tuesday of Carnival","VE",2006 +"2006-04-13","Maundy Thursday","VE",2006 +"2006-04-14","Good Friday","VE",2006 +"2006-04-19","Declaration of Independence","VE",2006 +"2006-05-01","International Worker's Day","VE",2006 +"2006-06-24","Battle of Carabobo","VE",2006 +"2006-07-05","Independence Day","VE",2006 +"2006-07-24","Birthday of Simon Bolivar","VE",2006 +"2006-10-12","Day of Indigenous Resistance","VE",2006 +"2006-12-24","Christmas Eve","VE",2006 +"2006-12-25","Christmas Day","VE",2006 +"2006-12-31","New Year's Eve","VE",2006 +"2007-01-01","New Year's Day","VE",2007 +"2007-02-19","Monday of Carnival","VE",2007 +"2007-02-20","Tuesday of Carnival","VE",2007 +"2007-04-05","Maundy Thursday","VE",2007 +"2007-04-06","Good Friday","VE",2007 +"2007-04-19","Declaration of Independence","VE",2007 +"2007-05-01","International Worker's Day","VE",2007 +"2007-06-24","Battle of Carabobo","VE",2007 +"2007-07-05","Independence Day","VE",2007 +"2007-07-24","Birthday of Simon Bolivar","VE",2007 +"2007-10-12","Day of Indigenous Resistance","VE",2007 +"2007-12-24","Christmas Eve","VE",2007 +"2007-12-25","Christmas Day","VE",2007 +"2007-12-31","New Year's Eve","VE",2007 +"2008-01-01","New Year's Day","VE",2008 +"2008-02-04","Monday of Carnival","VE",2008 +"2008-02-05","Tuesday of Carnival","VE",2008 +"2008-03-20","Maundy Thursday","VE",2008 +"2008-03-21","Good Friday","VE",2008 +"2008-04-19","Declaration of Independence","VE",2008 +"2008-05-01","International Worker's Day","VE",2008 +"2008-06-24","Battle of Carabobo","VE",2008 +"2008-07-05","Independence Day","VE",2008 +"2008-07-24","Birthday of Simon Bolivar","VE",2008 +"2008-10-12","Day of Indigenous Resistance","VE",2008 +"2008-12-24","Christmas Eve","VE",2008 +"2008-12-25","Christmas Day","VE",2008 +"2008-12-31","New Year's Eve","VE",2008 +"2009-01-01","New Year's Day","VE",2009 +"2009-02-23","Monday of Carnival","VE",2009 +"2009-02-24","Tuesday of Carnival","VE",2009 +"2009-04-09","Maundy Thursday","VE",2009 +"2009-04-10","Good Friday","VE",2009 +"2009-04-19","Declaration of Independence","VE",2009 +"2009-05-01","International Worker's Day","VE",2009 +"2009-06-24","Battle of Carabobo","VE",2009 +"2009-07-05","Independence Day","VE",2009 +"2009-07-24","Birthday of Simon Bolivar","VE",2009 +"2009-10-12","Day of Indigenous Resistance","VE",2009 +"2009-12-24","Christmas Eve","VE",2009 +"2009-12-25","Christmas Day","VE",2009 +"2009-12-31","New Year's Eve","VE",2009 +"2010-01-01","New Year's Day","VE",2010 +"2010-02-15","Monday of Carnival","VE",2010 +"2010-02-16","Tuesday of Carnival","VE",2010 +"2010-04-01","Maundy Thursday","VE",2010 +"2010-04-02","Good Friday","VE",2010 +"2010-04-19","Declaration of Independence","VE",2010 +"2010-05-01","International Worker's Day","VE",2010 +"2010-06-24","Battle of Carabobo","VE",2010 +"2010-07-05","Independence Day","VE",2010 +"2010-07-24","Birthday of Simon Bolivar","VE",2010 +"2010-10-12","Day of Indigenous Resistance","VE",2010 +"2010-12-24","Christmas Eve","VE",2010 +"2010-12-25","Christmas Day","VE",2010 +"2010-12-31","New Year's Eve","VE",2010 +"2011-01-01","New Year's Day","VE",2011 +"2011-03-07","Monday of Carnival","VE",2011 +"2011-03-08","Tuesday of Carnival","VE",2011 +"2011-04-19","Declaration of Independence","VE",2011 +"2011-04-21","Maundy Thursday","VE",2011 +"2011-04-22","Good Friday","VE",2011 +"2011-05-01","International Worker's Day","VE",2011 +"2011-06-24","Battle of Carabobo","VE",2011 +"2011-07-05","Independence Day","VE",2011 +"2011-07-24","Birthday of Simon Bolivar","VE",2011 +"2011-10-12","Day of Indigenous Resistance","VE",2011 +"2011-12-24","Christmas Eve","VE",2011 +"2011-12-25","Christmas Day","VE",2011 +"2011-12-31","New Year's Eve","VE",2011 +"2012-01-01","New Year's Day","VE",2012 +"2012-02-20","Monday of Carnival","VE",2012 +"2012-02-21","Tuesday of Carnival","VE",2012 +"2012-04-05","Maundy Thursday","VE",2012 +"2012-04-06","Good Friday","VE",2012 +"2012-04-19","Declaration of Independence","VE",2012 +"2012-05-01","International Worker's Day","VE",2012 +"2012-06-24","Battle of Carabobo","VE",2012 +"2012-07-05","Independence Day","VE",2012 +"2012-07-24","Birthday of Simon Bolivar","VE",2012 +"2012-10-12","Day of Indigenous Resistance","VE",2012 +"2012-12-24","Christmas Eve","VE",2012 +"2012-12-25","Christmas Day","VE",2012 +"2012-12-31","New Year's Eve","VE",2012 +"2013-01-01","New Year's Day","VE",2013 +"2013-02-11","Monday of Carnival","VE",2013 +"2013-02-12","Tuesday of Carnival","VE",2013 +"2013-03-28","Maundy Thursday","VE",2013 +"2013-03-29","Good Friday","VE",2013 +"2013-04-19","Declaration of Independence","VE",2013 +"2013-05-01","International Worker's Day","VE",2013 +"2013-06-24","Battle of Carabobo","VE",2013 +"2013-07-05","Independence Day","VE",2013 +"2013-07-24","Birthday of Simon Bolivar","VE",2013 +"2013-10-12","Day of Indigenous Resistance","VE",2013 +"2013-12-24","Christmas Eve","VE",2013 +"2013-12-25","Christmas Day","VE",2013 +"2013-12-31","New Year's Eve","VE",2013 +"2014-01-01","New Year's Day","VE",2014 +"2014-03-03","Monday of Carnival","VE",2014 +"2014-03-04","Tuesday of Carnival","VE",2014 +"2014-04-17","Maundy Thursday","VE",2014 +"2014-04-18","Good Friday","VE",2014 +"2014-04-19","Declaration of Independence","VE",2014 +"2014-05-01","International Worker's Day","VE",2014 +"2014-06-24","Battle of Carabobo","VE",2014 +"2014-07-05","Independence Day","VE",2014 +"2014-07-24","Birthday of Simon Bolivar","VE",2014 +"2014-10-12","Day of Indigenous Resistance","VE",2014 +"2014-12-24","Christmas Eve","VE",2014 +"2014-12-25","Christmas Day","VE",2014 +"2014-12-31","New Year's Eve","VE",2014 +"2015-01-01","New Year's Day","VE",2015 +"2015-02-16","Monday of Carnival","VE",2015 +"2015-02-17","Tuesday of Carnival","VE",2015 +"2015-04-02","Maundy Thursday","VE",2015 +"2015-04-03","Good Friday","VE",2015 +"2015-04-19","Declaration of Independence","VE",2015 +"2015-05-01","International Worker's Day","VE",2015 +"2015-06-24","Battle of Carabobo","VE",2015 +"2015-07-05","Independence Day","VE",2015 +"2015-07-24","Birthday of Simon Bolivar","VE",2015 +"2015-10-12","Day of Indigenous Resistance","VE",2015 +"2015-12-24","Christmas Eve","VE",2015 +"2015-12-25","Christmas Day","VE",2015 +"2015-12-31","New Year's Eve","VE",2015 +"2016-01-01","New Year's Day","VE",2016 +"2016-02-08","Monday of Carnival","VE",2016 +"2016-02-09","Tuesday of Carnival","VE",2016 +"2016-03-24","Maundy Thursday","VE",2016 +"2016-03-25","Good Friday","VE",2016 +"2016-04-19","Declaration of Independence","VE",2016 +"2016-05-01","International Worker's Day","VE",2016 +"2016-06-24","Battle of Carabobo","VE",2016 +"2016-07-05","Independence Day","VE",2016 +"2016-07-24","Birthday of Simon Bolivar","VE",2016 +"2016-10-12","Day of Indigenous Resistance","VE",2016 +"2016-12-24","Christmas Eve","VE",2016 +"2016-12-25","Christmas Day","VE",2016 +"2016-12-31","New Year's Eve","VE",2016 +"2017-01-01","New Year's Day","VE",2017 +"2017-02-27","Monday of Carnival","VE",2017 +"2017-02-28","Tuesday of Carnival","VE",2017 +"2017-04-13","Maundy Thursday","VE",2017 +"2017-04-14","Good Friday","VE",2017 +"2017-04-19","Declaration of Independence","VE",2017 +"2017-05-01","International Worker's Day","VE",2017 +"2017-06-24","Battle of Carabobo","VE",2017 +"2017-07-05","Independence Day","VE",2017 +"2017-07-24","Birthday of Simon Bolivar","VE",2017 +"2017-10-12","Day of Indigenous Resistance","VE",2017 +"2017-12-24","Christmas Eve","VE",2017 +"2017-12-25","Christmas Day","VE",2017 +"2017-12-31","New Year's Eve","VE",2017 +"2018-01-01","New Year's Day","VE",2018 +"2018-02-12","Monday of Carnival","VE",2018 +"2018-02-13","Tuesday of Carnival","VE",2018 +"2018-03-29","Maundy Thursday","VE",2018 +"2018-03-30","Good Friday","VE",2018 +"2018-04-19","Declaration of Independence","VE",2018 +"2018-05-01","International Worker's Day","VE",2018 +"2018-06-24","Battle of Carabobo","VE",2018 +"2018-07-05","Independence Day","VE",2018 +"2018-07-24","Birthday of Simon Bolivar","VE",2018 +"2018-10-12","Day of Indigenous Resistance","VE",2018 +"2018-12-24","Christmas Eve","VE",2018 +"2018-12-25","Christmas Day","VE",2018 +"2018-12-31","New Year's Eve","VE",2018 +"2019-01-01","New Year's Day","VE",2019 +"2019-03-04","Monday of Carnival","VE",2019 +"2019-03-05","Tuesday of Carnival","VE",2019 +"2019-04-18","Maundy Thursday","VE",2019 +"2019-04-19","Declaration of Independence","VE",2019 +"2019-04-19","Good Friday","VE",2019 +"2019-05-01","International Worker's Day","VE",2019 +"2019-06-24","Battle of Carabobo","VE",2019 +"2019-07-05","Independence Day","VE",2019 +"2019-07-24","Birthday of Simon Bolivar","VE",2019 +"2019-10-12","Day of Indigenous Resistance","VE",2019 +"2019-12-24","Christmas Eve","VE",2019 +"2019-12-25","Christmas Day","VE",2019 +"2019-12-31","New Year's Eve","VE",2019 +"2020-01-01","New Year's Day","VE",2020 +"2020-02-24","Monday of Carnival","VE",2020 +"2020-02-25","Tuesday of Carnival","VE",2020 +"2020-04-09","Maundy Thursday","VE",2020 +"2020-04-10","Good Friday","VE",2020 +"2020-04-19","Declaration of Independence","VE",2020 +"2020-05-01","International Worker's Day","VE",2020 +"2020-06-24","Battle of Carabobo","VE",2020 +"2020-07-05","Independence Day","VE",2020 +"2020-07-24","Birthday of Simon Bolivar","VE",2020 +"2020-10-12","Day of Indigenous Resistance","VE",2020 +"2020-12-24","Christmas Eve","VE",2020 +"2020-12-25","Christmas Day","VE",2020 +"2020-12-31","New Year's Eve","VE",2020 +"2021-01-01","New Year's Day","VE",2021 +"2021-02-15","Monday of Carnival","VE",2021 +"2021-02-16","Tuesday of Carnival","VE",2021 +"2021-04-01","Maundy Thursday","VE",2021 +"2021-04-02","Good Friday","VE",2021 +"2021-04-19","Declaration of Independence","VE",2021 +"2021-05-01","International Worker's Day","VE",2021 +"2021-06-24","Battle of Carabobo","VE",2021 +"2021-07-05","Independence Day","VE",2021 +"2021-07-24","Birthday of Simon Bolivar","VE",2021 +"2021-10-12","Day of Indigenous Resistance","VE",2021 +"2021-12-24","Christmas Eve","VE",2021 +"2021-12-25","Christmas Day","VE",2021 +"2021-12-31","New Year's Eve","VE",2021 +"2022-01-01","New Year's Day","VE",2022 +"2022-02-28","Monday of Carnival","VE",2022 +"2022-03-01","Tuesday of Carnival","VE",2022 +"2022-04-14","Maundy Thursday","VE",2022 +"2022-04-15","Good Friday","VE",2022 +"2022-04-19","Declaration of Independence","VE",2022 +"2022-05-01","International Worker's Day","VE",2022 +"2022-06-24","Battle of Carabobo","VE",2022 +"2022-07-05","Independence Day","VE",2022 +"2022-07-24","Birthday of Simon Bolivar","VE",2022 +"2022-10-12","Day of Indigenous Resistance","VE",2022 +"2022-12-24","Christmas Eve","VE",2022 +"2022-12-25","Christmas Day","VE",2022 +"2022-12-31","New Year's Eve","VE",2022 +"2023-01-01","New Year's Day","VE",2023 +"2023-02-20","Monday of Carnival","VE",2023 +"2023-02-21","Tuesday of Carnival","VE",2023 +"2023-04-06","Maundy Thursday","VE",2023 +"2023-04-07","Good Friday","VE",2023 +"2023-04-19","Declaration of Independence","VE",2023 +"2023-05-01","International Worker's Day","VE",2023 +"2023-06-24","Battle of Carabobo","VE",2023 +"2023-07-05","Independence Day","VE",2023 +"2023-07-24","Birthday of Simon Bolivar","VE",2023 +"2023-10-12","Day of Indigenous Resistance","VE",2023 +"2023-12-24","Christmas Eve","VE",2023 +"2023-12-25","Christmas Day","VE",2023 +"2023-12-31","New Year's Eve","VE",2023 +"2024-01-01","New Year's Day","VE",2024 +"2024-02-12","Monday of Carnival","VE",2024 +"2024-02-13","Tuesday of Carnival","VE",2024 +"2024-03-28","Maundy Thursday","VE",2024 +"2024-03-29","Good Friday","VE",2024 +"2024-04-19","Declaration of Independence","VE",2024 +"2024-05-01","International Worker's Day","VE",2024 +"2024-06-24","Battle of Carabobo","VE",2024 +"2024-07-05","Independence Day","VE",2024 +"2024-07-24","Birthday of Simon Bolivar","VE",2024 +"2024-10-12","Day of Indigenous Resistance","VE",2024 +"2024-12-24","Christmas Eve","VE",2024 +"2024-12-25","Christmas Day","VE",2024 +"2024-12-31","New Year's Eve","VE",2024 +"2025-01-01","New Year's Day","VE",2025 +"2025-03-03","Monday of Carnival","VE",2025 +"2025-03-04","Tuesday of Carnival","VE",2025 +"2025-04-17","Maundy Thursday","VE",2025 +"2025-04-18","Good Friday","VE",2025 +"2025-04-19","Declaration of Independence","VE",2025 +"2025-05-01","International Worker's Day","VE",2025 +"2025-06-24","Battle of Carabobo","VE",2025 +"2025-07-05","Independence Day","VE",2025 +"2025-07-24","Birthday of Simon Bolivar","VE",2025 +"2025-10-12","Day of Indigenous Resistance","VE",2025 +"2025-12-24","Christmas Eve","VE",2025 +"2025-12-25","Christmas Day","VE",2025 +"2025-12-31","New Year's Eve","VE",2025 +"2026-01-01","New Year's Day","VE",2026 +"2026-02-16","Monday of Carnival","VE",2026 +"2026-02-17","Tuesday of Carnival","VE",2026 +"2026-04-02","Maundy Thursday","VE",2026 +"2026-04-03","Good Friday","VE",2026 +"2026-04-19","Declaration of Independence","VE",2026 +"2026-05-01","International Worker's Day","VE",2026 +"2026-06-24","Battle of Carabobo","VE",2026 +"2026-07-05","Independence Day","VE",2026 +"2026-07-24","Birthday of Simon Bolivar","VE",2026 +"2026-10-12","Day of Indigenous Resistance","VE",2026 +"2026-12-24","Christmas Eve","VE",2026 +"2026-12-25","Christmas Day","VE",2026 +"2026-12-31","New Year's Eve","VE",2026 +"2027-01-01","New Year's Day","VE",2027 +"2027-02-08","Monday of Carnival","VE",2027 +"2027-02-09","Tuesday of Carnival","VE",2027 +"2027-03-25","Maundy Thursday","VE",2027 +"2027-03-26","Good Friday","VE",2027 +"2027-04-19","Declaration of Independence","VE",2027 +"2027-05-01","International Worker's Day","VE",2027 +"2027-06-24","Battle of Carabobo","VE",2027 +"2027-07-05","Independence Day","VE",2027 +"2027-07-24","Birthday of Simon Bolivar","VE",2027 +"2027-10-12","Day of Indigenous Resistance","VE",2027 +"2027-12-24","Christmas Eve","VE",2027 +"2027-12-25","Christmas Day","VE",2027 +"2027-12-31","New Year's Eve","VE",2027 +"2028-01-01","New Year's Day","VE",2028 +"2028-02-28","Monday of Carnival","VE",2028 +"2028-02-29","Tuesday of Carnival","VE",2028 +"2028-04-13","Maundy Thursday","VE",2028 +"2028-04-14","Good Friday","VE",2028 +"2028-04-19","Declaration of Independence","VE",2028 +"2028-05-01","International Worker's Day","VE",2028 +"2028-06-24","Battle of Carabobo","VE",2028 +"2028-07-05","Independence Day","VE",2028 +"2028-07-24","Birthday of Simon Bolivar","VE",2028 +"2028-10-12","Day of Indigenous Resistance","VE",2028 +"2028-12-24","Christmas Eve","VE",2028 +"2028-12-25","Christmas Day","VE",2028 +"2028-12-31","New Year's Eve","VE",2028 +"2029-01-01","New Year's Day","VE",2029 +"2029-02-12","Monday of Carnival","VE",2029 +"2029-02-13","Tuesday of Carnival","VE",2029 +"2029-03-29","Maundy Thursday","VE",2029 +"2029-03-30","Good Friday","VE",2029 +"2029-04-19","Declaration of Independence","VE",2029 +"2029-05-01","International Worker's Day","VE",2029 +"2029-06-24","Battle of Carabobo","VE",2029 +"2029-07-05","Independence Day","VE",2029 +"2029-07-24","Birthday of Simon Bolivar","VE",2029 +"2029-10-12","Day of Indigenous Resistance","VE",2029 +"2029-12-24","Christmas Eve","VE",2029 +"2029-12-25","Christmas Day","VE",2029 +"2029-12-31","New Year's Eve","VE",2029 +"2030-01-01","New Year's Day","VE",2030 +"2030-03-04","Monday of Carnival","VE",2030 +"2030-03-05","Tuesday of Carnival","VE",2030 +"2030-04-18","Maundy Thursday","VE",2030 +"2030-04-19","Declaration of Independence","VE",2030 +"2030-04-19","Good Friday","VE",2030 +"2030-05-01","International Worker's Day","VE",2030 +"2030-06-24","Battle of Carabobo","VE",2030 +"2030-07-05","Independence Day","VE",2030 +"2030-07-24","Birthday of Simon Bolivar","VE",2030 +"2030-10-12","Day of Indigenous Resistance","VE",2030 +"2030-12-24","Christmas Eve","VE",2030 +"2030-12-25","Christmas Day","VE",2030 +"2030-12-31","New Year's Eve","VE",2030 +"2031-01-01","New Year's Day","VE",2031 +"2031-02-24","Monday of Carnival","VE",2031 +"2031-02-25","Tuesday of Carnival","VE",2031 +"2031-04-10","Maundy Thursday","VE",2031 +"2031-04-11","Good Friday","VE",2031 +"2031-04-19","Declaration of Independence","VE",2031 +"2031-05-01","International Worker's Day","VE",2031 +"2031-06-24","Battle of Carabobo","VE",2031 +"2031-07-05","Independence Day","VE",2031 +"2031-07-24","Birthday of Simon Bolivar","VE",2031 +"2031-10-12","Day of Indigenous Resistance","VE",2031 +"2031-12-24","Christmas Eve","VE",2031 +"2031-12-25","Christmas Day","VE",2031 +"2031-12-31","New Year's Eve","VE",2031 +"2032-01-01","New Year's Day","VE",2032 +"2032-02-09","Monday of Carnival","VE",2032 +"2032-02-10","Tuesday of Carnival","VE",2032 +"2032-03-25","Maundy Thursday","VE",2032 +"2032-03-26","Good Friday","VE",2032 +"2032-04-19","Declaration of Independence","VE",2032 +"2032-05-01","International Worker's Day","VE",2032 +"2032-06-24","Battle of Carabobo","VE",2032 +"2032-07-05","Independence Day","VE",2032 +"2032-07-24","Birthday of Simon Bolivar","VE",2032 +"2032-10-12","Day of Indigenous Resistance","VE",2032 +"2032-12-24","Christmas Eve","VE",2032 +"2032-12-25","Christmas Day","VE",2032 +"2032-12-31","New Year's Eve","VE",2032 +"2033-01-01","New Year's Day","VE",2033 +"2033-02-28","Monday of Carnival","VE",2033 +"2033-03-01","Tuesday of Carnival","VE",2033 +"2033-04-14","Maundy Thursday","VE",2033 +"2033-04-15","Good Friday","VE",2033 +"2033-04-19","Declaration of Independence","VE",2033 +"2033-05-01","International Worker's Day","VE",2033 +"2033-06-24","Battle of Carabobo","VE",2033 +"2033-07-05","Independence Day","VE",2033 +"2033-07-24","Birthday of Simon Bolivar","VE",2033 +"2033-10-12","Day of Indigenous Resistance","VE",2033 +"2033-12-24","Christmas Eve","VE",2033 +"2033-12-25","Christmas Day","VE",2033 +"2033-12-31","New Year's Eve","VE",2033 +"2034-01-01","New Year's Day","VE",2034 +"2034-02-20","Monday of Carnival","VE",2034 +"2034-02-21","Tuesday of Carnival","VE",2034 +"2034-04-06","Maundy Thursday","VE",2034 +"2034-04-07","Good Friday","VE",2034 +"2034-04-19","Declaration of Independence","VE",2034 +"2034-05-01","International Worker's Day","VE",2034 +"2034-06-24","Battle of Carabobo","VE",2034 +"2034-07-05","Independence Day","VE",2034 +"2034-07-24","Birthday of Simon Bolivar","VE",2034 +"2034-10-12","Day of Indigenous Resistance","VE",2034 +"2034-12-24","Christmas Eve","VE",2034 +"2034-12-25","Christmas Day","VE",2034 +"2034-12-31","New Year's Eve","VE",2034 +"2035-01-01","New Year's Day","VE",2035 +"2035-02-05","Monday of Carnival","VE",2035 +"2035-02-06","Tuesday of Carnival","VE",2035 +"2035-03-22","Maundy Thursday","VE",2035 +"2035-03-23","Good Friday","VE",2035 +"2035-04-19","Declaration of Independence","VE",2035 +"2035-05-01","International Worker's Day","VE",2035 +"2035-06-24","Battle of Carabobo","VE",2035 +"2035-07-05","Independence Day","VE",2035 +"2035-07-24","Birthday of Simon Bolivar","VE",2035 +"2035-10-12","Day of Indigenous Resistance","VE",2035 +"2035-12-24","Christmas Eve","VE",2035 +"2035-12-25","Christmas Day","VE",2035 +"2035-12-31","New Year's Eve","VE",2035 +"2036-01-01","New Year's Day","VE",2036 +"2036-02-25","Monday of Carnival","VE",2036 +"2036-02-26","Tuesday of Carnival","VE",2036 +"2036-04-10","Maundy Thursday","VE",2036 +"2036-04-11","Good Friday","VE",2036 +"2036-04-19","Declaration of Independence","VE",2036 +"2036-05-01","International Worker's Day","VE",2036 +"2036-06-24","Battle of Carabobo","VE",2036 +"2036-07-05","Independence Day","VE",2036 +"2036-07-24","Birthday of Simon Bolivar","VE",2036 +"2036-10-12","Day of Indigenous Resistance","VE",2036 +"2036-12-24","Christmas Eve","VE",2036 +"2036-12-25","Christmas Day","VE",2036 +"2036-12-31","New Year's Eve","VE",2036 +"2037-01-01","New Year's Day","VE",2037 +"2037-02-16","Monday of Carnival","VE",2037 +"2037-02-17","Tuesday of Carnival","VE",2037 +"2037-04-02","Maundy Thursday","VE",2037 +"2037-04-03","Good Friday","VE",2037 +"2037-04-19","Declaration of Independence","VE",2037 +"2037-05-01","International Worker's Day","VE",2037 +"2037-06-24","Battle of Carabobo","VE",2037 +"2037-07-05","Independence Day","VE",2037 +"2037-07-24","Birthday of Simon Bolivar","VE",2037 +"2037-10-12","Day of Indigenous Resistance","VE",2037 +"2037-12-24","Christmas Eve","VE",2037 +"2037-12-25","Christmas Day","VE",2037 +"2037-12-31","New Year's Eve","VE",2037 +"2038-01-01","New Year's Day","VE",2038 +"2038-03-08","Monday of Carnival","VE",2038 +"2038-03-09","Tuesday of Carnival","VE",2038 +"2038-04-19","Declaration of Independence","VE",2038 +"2038-04-22","Maundy Thursday","VE",2038 +"2038-04-23","Good Friday","VE",2038 +"2038-05-01","International Worker's Day","VE",2038 +"2038-06-24","Battle of Carabobo","VE",2038 +"2038-07-05","Independence Day","VE",2038 +"2038-07-24","Birthday of Simon Bolivar","VE",2038 +"2038-10-12","Day of Indigenous Resistance","VE",2038 +"2038-12-24","Christmas Eve","VE",2038 +"2038-12-25","Christmas Day","VE",2038 +"2038-12-31","New Year's Eve","VE",2038 +"2039-01-01","New Year's Day","VE",2039 +"2039-02-21","Monday of Carnival","VE",2039 +"2039-02-22","Tuesday of Carnival","VE",2039 +"2039-04-07","Maundy Thursday","VE",2039 +"2039-04-08","Good Friday","VE",2039 +"2039-04-19","Declaration of Independence","VE",2039 +"2039-05-01","International Worker's Day","VE",2039 +"2039-06-24","Battle of Carabobo","VE",2039 +"2039-07-05","Independence Day","VE",2039 +"2039-07-24","Birthday of Simon Bolivar","VE",2039 +"2039-10-12","Day of Indigenous Resistance","VE",2039 +"2039-12-24","Christmas Eve","VE",2039 +"2039-12-25","Christmas Day","VE",2039 +"2039-12-31","New Year's Eve","VE",2039 +"2040-01-01","New Year's Day","VE",2040 +"2040-02-13","Monday of Carnival","VE",2040 +"2040-02-14","Tuesday of Carnival","VE",2040 +"2040-03-29","Maundy Thursday","VE",2040 +"2040-03-30","Good Friday","VE",2040 +"2040-04-19","Declaration of Independence","VE",2040 +"2040-05-01","International Worker's Day","VE",2040 +"2040-06-24","Battle of Carabobo","VE",2040 +"2040-07-05","Independence Day","VE",2040 +"2040-07-24","Birthday of Simon Bolivar","VE",2040 +"2040-10-12","Day of Indigenous Resistance","VE",2040 +"2040-12-24","Christmas Eve","VE",2040 +"2040-12-25","Christmas Day","VE",2040 +"2040-12-31","New Year's Eve","VE",2040 +"2041-01-01","New Year's Day","VE",2041 +"2041-03-04","Monday of Carnival","VE",2041 +"2041-03-05","Tuesday of Carnival","VE",2041 +"2041-04-18","Maundy Thursday","VE",2041 +"2041-04-19","Declaration of Independence","VE",2041 +"2041-04-19","Good Friday","VE",2041 +"2041-05-01","International Worker's Day","VE",2041 +"2041-06-24","Battle of Carabobo","VE",2041 +"2041-07-05","Independence Day","VE",2041 +"2041-07-24","Birthday of Simon Bolivar","VE",2041 +"2041-10-12","Day of Indigenous Resistance","VE",2041 +"2041-12-24","Christmas Eve","VE",2041 +"2041-12-25","Christmas Day","VE",2041 +"2041-12-31","New Year's Eve","VE",2041 +"2042-01-01","New Year's Day","VE",2042 +"2042-02-17","Monday of Carnival","VE",2042 +"2042-02-18","Tuesday of Carnival","VE",2042 +"2042-04-03","Maundy Thursday","VE",2042 +"2042-04-04","Good Friday","VE",2042 +"2042-04-19","Declaration of Independence","VE",2042 +"2042-05-01","International Worker's Day","VE",2042 +"2042-06-24","Battle of Carabobo","VE",2042 +"2042-07-05","Independence Day","VE",2042 +"2042-07-24","Birthday of Simon Bolivar","VE",2042 +"2042-10-12","Day of Indigenous Resistance","VE",2042 +"2042-12-24","Christmas Eve","VE",2042 +"2042-12-25","Christmas Day","VE",2042 +"2042-12-31","New Year's Eve","VE",2042 +"2043-01-01","New Year's Day","VE",2043 +"2043-02-09","Monday of Carnival","VE",2043 +"2043-02-10","Tuesday of Carnival","VE",2043 +"2043-03-26","Maundy Thursday","VE",2043 +"2043-03-27","Good Friday","VE",2043 +"2043-04-19","Declaration of Independence","VE",2043 +"2043-05-01","International Worker's Day","VE",2043 +"2043-06-24","Battle of Carabobo","VE",2043 +"2043-07-05","Independence Day","VE",2043 +"2043-07-24","Birthday of Simon Bolivar","VE",2043 +"2043-10-12","Day of Indigenous Resistance","VE",2043 +"2043-12-24","Christmas Eve","VE",2043 +"2043-12-25","Christmas Day","VE",2043 +"2043-12-31","New Year's Eve","VE",2043 +"2044-01-01","New Year's Day","VE",2044 +"2044-02-29","Monday of Carnival","VE",2044 +"2044-03-01","Tuesday of Carnival","VE",2044 +"2044-04-14","Maundy Thursday","VE",2044 +"2044-04-15","Good Friday","VE",2044 +"2044-04-19","Declaration of Independence","VE",2044 +"2044-05-01","International Worker's Day","VE",2044 +"2044-06-24","Battle of Carabobo","VE",2044 +"2044-07-05","Independence Day","VE",2044 +"2044-07-24","Birthday of Simon Bolivar","VE",2044 +"2044-10-12","Day of Indigenous Resistance","VE",2044 +"2044-12-24","Christmas Eve","VE",2044 +"2044-12-25","Christmas Day","VE",2044 +"2044-12-31","New Year's Eve","VE",2044 +"1995-01-01","New Year's Day","VI",1995 +"1995-01-02","New Year's Day (Observed)","VI",1995 +"1995-01-06","Three King's Day","VI",1995 +"1995-01-16","Martin Luther King Jr. Day","VI",1995 +"1995-02-20","Presidents' Day","VI",1995 +"1995-03-31","Transfer Day","VI",1995 +"1995-04-13","Holy Thursday","VI",1995 +"1995-04-14","Good Friday","VI",1995 +"1995-04-17","Easter Monday","VI",1995 +"1995-05-29","Memorial Day","VI",1995 +"1995-07-03","Emancipation Day","VI",1995 +"1995-07-04","Independence Day","VI",1995 +"1995-09-04","Labor Day","VI",1995 +"1995-10-09","Columbus Day and Puerto Rico Friendship Day","VI",1995 +"1995-11-01","Liberty Day","VI",1995 +"1995-11-10","Veterans Day (Observed)","VI",1995 +"1995-11-11","Veterans Day","VI",1995 +"1995-11-23","Thanksgiving","VI",1995 +"1995-12-25","Christmas Day","VI",1995 +"1995-12-26","Christmas Second Day","VI",1995 +"1996-01-01","New Year's Day","VI",1996 +"1996-01-06","Three King's Day","VI",1996 +"1996-01-15","Martin Luther King Jr. Day","VI",1996 +"1996-02-19","Presidents' Day","VI",1996 +"1996-03-31","Transfer Day","VI",1996 +"1996-04-04","Holy Thursday","VI",1996 +"1996-04-05","Good Friday","VI",1996 +"1996-04-08","Easter Monday","VI",1996 +"1996-05-27","Memorial Day","VI",1996 +"1996-07-03","Emancipation Day","VI",1996 +"1996-07-04","Independence Day","VI",1996 +"1996-09-02","Labor Day","VI",1996 +"1996-10-14","Columbus Day and Puerto Rico Friendship Day","VI",1996 +"1996-11-01","Liberty Day","VI",1996 +"1996-11-11","Veterans Day","VI",1996 +"1996-11-28","Thanksgiving","VI",1996 +"1996-12-25","Christmas Day","VI",1996 +"1996-12-26","Christmas Second Day","VI",1996 +"1997-01-01","New Year's Day","VI",1997 +"1997-01-06","Three King's Day","VI",1997 +"1997-01-20","Martin Luther King Jr. Day","VI",1997 +"1997-02-17","Presidents' Day","VI",1997 +"1997-03-27","Holy Thursday","VI",1997 +"1997-03-28","Good Friday","VI",1997 +"1997-03-31","Easter Monday","VI",1997 +"1997-03-31","Transfer Day","VI",1997 +"1997-05-26","Memorial Day","VI",1997 +"1997-07-03","Emancipation Day","VI",1997 +"1997-07-04","Independence Day","VI",1997 +"1997-09-01","Labor Day","VI",1997 +"1997-10-13","Columbus Day and Puerto Rico Friendship Day","VI",1997 +"1997-11-01","Liberty Day","VI",1997 +"1997-11-11","Veterans Day","VI",1997 +"1997-11-27","Thanksgiving","VI",1997 +"1997-12-25","Christmas Day","VI",1997 +"1997-12-26","Christmas Second Day","VI",1997 +"1998-01-01","New Year's Day","VI",1998 +"1998-01-06","Three King's Day","VI",1998 +"1998-01-19","Martin Luther King Jr. Day","VI",1998 +"1998-02-16","Presidents' Day","VI",1998 +"1998-03-31","Transfer Day","VI",1998 +"1998-04-09","Holy Thursday","VI",1998 +"1998-04-10","Good Friday","VI",1998 +"1998-04-13","Easter Monday","VI",1998 +"1998-05-25","Memorial Day","VI",1998 +"1998-07-03","Emancipation Day","VI",1998 +"1998-07-03","Independence Day (Observed)","VI",1998 +"1998-07-04","Independence Day","VI",1998 +"1998-09-07","Labor Day","VI",1998 +"1998-10-12","Columbus Day and Puerto Rico Friendship Day","VI",1998 +"1998-11-01","Liberty Day","VI",1998 +"1998-11-11","Veterans Day","VI",1998 +"1998-11-26","Thanksgiving","VI",1998 +"1998-12-25","Christmas Day","VI",1998 +"1998-12-26","Christmas Second Day","VI",1998 +"1999-01-01","New Year's Day","VI",1999 +"1999-01-06","Three King's Day","VI",1999 +"1999-01-18","Martin Luther King Jr. Day","VI",1999 +"1999-02-15","Presidents' Day","VI",1999 +"1999-03-31","Transfer Day","VI",1999 +"1999-04-01","Holy Thursday","VI",1999 +"1999-04-02","Good Friday","VI",1999 +"1999-04-05","Easter Monday","VI",1999 +"1999-05-31","Memorial Day","VI",1999 +"1999-07-03","Emancipation Day","VI",1999 +"1999-07-04","Independence Day","VI",1999 +"1999-07-05","Independence Day (Observed)","VI",1999 +"1999-09-06","Labor Day","VI",1999 +"1999-10-11","Columbus Day and Puerto Rico Friendship Day","VI",1999 +"1999-11-01","Liberty Day","VI",1999 +"1999-11-11","Veterans Day","VI",1999 +"1999-11-25","Thanksgiving","VI",1999 +"1999-12-24","Christmas Day (Observed)","VI",1999 +"1999-12-25","Christmas Day","VI",1999 +"1999-12-26","Christmas Second Day","VI",1999 +"1999-12-31","New Year's Day (Observed)","VI",1999 +"2000-01-01","New Year's Day","VI",2000 +"2000-01-06","Three King's Day","VI",2000 +"2000-01-17","Martin Luther King Jr. Day","VI",2000 +"2000-02-21","Presidents' Day","VI",2000 +"2000-03-31","Transfer Day","VI",2000 +"2000-04-20","Holy Thursday","VI",2000 +"2000-04-21","Good Friday","VI",2000 +"2000-04-24","Easter Monday","VI",2000 +"2000-05-29","Memorial Day","VI",2000 +"2000-07-03","Emancipation Day","VI",2000 +"2000-07-04","Independence Day","VI",2000 +"2000-09-04","Labor Day","VI",2000 +"2000-10-09","Columbus Day and Puerto Rico Friendship Day","VI",2000 +"2000-11-01","Liberty Day","VI",2000 +"2000-11-10","Veterans Day (Observed)","VI",2000 +"2000-11-11","Veterans Day","VI",2000 +"2000-11-23","Thanksgiving","VI",2000 +"2000-12-25","Christmas Day","VI",2000 +"2000-12-26","Christmas Second Day","VI",2000 +"2001-01-01","New Year's Day","VI",2001 +"2001-01-06","Three King's Day","VI",2001 +"2001-01-15","Martin Luther King Jr. Day","VI",2001 +"2001-02-19","Presidents' Day","VI",2001 +"2001-03-31","Transfer Day","VI",2001 +"2001-04-12","Holy Thursday","VI",2001 +"2001-04-13","Good Friday","VI",2001 +"2001-04-16","Easter Monday","VI",2001 +"2001-05-28","Memorial Day","VI",2001 +"2001-07-03","Emancipation Day","VI",2001 +"2001-07-04","Independence Day","VI",2001 +"2001-09-03","Labor Day","VI",2001 +"2001-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2001 +"2001-11-01","Liberty Day","VI",2001 +"2001-11-11","Veterans Day","VI",2001 +"2001-11-12","Veterans Day (Observed)","VI",2001 +"2001-11-22","Thanksgiving","VI",2001 +"2001-12-25","Christmas Day","VI",2001 +"2001-12-26","Christmas Second Day","VI",2001 +"2002-01-01","New Year's Day","VI",2002 +"2002-01-06","Three King's Day","VI",2002 +"2002-01-21","Martin Luther King Jr. Day","VI",2002 +"2002-02-18","Presidents' Day","VI",2002 +"2002-03-28","Holy Thursday","VI",2002 +"2002-03-29","Good Friday","VI",2002 +"2002-03-31","Transfer Day","VI",2002 +"2002-04-01","Easter Monday","VI",2002 +"2002-05-27","Memorial Day","VI",2002 +"2002-07-03","Emancipation Day","VI",2002 +"2002-07-04","Independence Day","VI",2002 +"2002-09-02","Labor Day","VI",2002 +"2002-10-14","Columbus Day and Puerto Rico Friendship Day","VI",2002 +"2002-11-01","Liberty Day","VI",2002 +"2002-11-11","Veterans Day","VI",2002 +"2002-11-28","Thanksgiving","VI",2002 +"2002-12-25","Christmas Day","VI",2002 +"2002-12-26","Christmas Second Day","VI",2002 +"2003-01-01","New Year's Day","VI",2003 +"2003-01-06","Three King's Day","VI",2003 +"2003-01-20","Martin Luther King Jr. Day","VI",2003 +"2003-02-17","Presidents' Day","VI",2003 +"2003-03-31","Transfer Day","VI",2003 +"2003-04-17","Holy Thursday","VI",2003 +"2003-04-18","Good Friday","VI",2003 +"2003-04-21","Easter Monday","VI",2003 +"2003-05-26","Memorial Day","VI",2003 +"2003-07-03","Emancipation Day","VI",2003 +"2003-07-04","Independence Day","VI",2003 +"2003-09-01","Labor Day","VI",2003 +"2003-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2003 +"2003-11-01","Liberty Day","VI",2003 +"2003-11-11","Veterans Day","VI",2003 +"2003-11-27","Thanksgiving","VI",2003 +"2003-12-25","Christmas Day","VI",2003 +"2003-12-26","Christmas Second Day","VI",2003 +"2004-01-01","New Year's Day","VI",2004 +"2004-01-06","Three King's Day","VI",2004 +"2004-01-19","Martin Luther King Jr. Day","VI",2004 +"2004-02-16","Presidents' Day","VI",2004 +"2004-03-31","Transfer Day","VI",2004 +"2004-04-08","Holy Thursday","VI",2004 +"2004-04-09","Good Friday","VI",2004 +"2004-04-12","Easter Monday","VI",2004 +"2004-05-31","Memorial Day","VI",2004 +"2004-07-03","Emancipation Day","VI",2004 +"2004-07-04","Independence Day","VI",2004 +"2004-07-05","Independence Day (Observed)","VI",2004 +"2004-09-06","Labor Day","VI",2004 +"2004-10-11","Columbus Day and Puerto Rico Friendship Day","VI",2004 +"2004-11-01","Liberty Day","VI",2004 +"2004-11-11","Veterans Day","VI",2004 +"2004-11-25","Thanksgiving","VI",2004 +"2004-12-24","Christmas Day (Observed)","VI",2004 +"2004-12-25","Christmas Day","VI",2004 +"2004-12-26","Christmas Second Day","VI",2004 +"2004-12-31","New Year's Day (Observed)","VI",2004 +"2005-01-01","New Year's Day","VI",2005 +"2005-01-06","Three King's Day","VI",2005 +"2005-01-17","Martin Luther King Jr. Day","VI",2005 +"2005-02-21","Presidents' Day","VI",2005 +"2005-03-24","Holy Thursday","VI",2005 +"2005-03-25","Good Friday","VI",2005 +"2005-03-28","Easter Monday","VI",2005 +"2005-03-31","Transfer Day","VI",2005 +"2005-05-30","Memorial Day","VI",2005 +"2005-07-03","Emancipation Day","VI",2005 +"2005-07-04","Independence Day","VI",2005 +"2005-09-05","Labor Day","VI",2005 +"2005-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2005 +"2005-11-01","Liberty Day","VI",2005 +"2005-11-11","Veterans Day","VI",2005 +"2005-11-24","Thanksgiving","VI",2005 +"2005-12-25","Christmas Day","VI",2005 +"2005-12-26","Christmas Day (Observed)","VI",2005 +"2005-12-26","Christmas Second Day","VI",2005 +"2006-01-01","New Year's Day","VI",2006 +"2006-01-02","New Year's Day (Observed)","VI",2006 +"2006-01-06","Three King's Day","VI",2006 +"2006-01-16","Martin Luther King Jr. Day","VI",2006 +"2006-02-20","Presidents' Day","VI",2006 +"2006-03-31","Transfer Day","VI",2006 +"2006-04-13","Holy Thursday","VI",2006 +"2006-04-14","Good Friday","VI",2006 +"2006-04-17","Easter Monday","VI",2006 +"2006-05-29","Memorial Day","VI",2006 +"2006-07-03","Emancipation Day","VI",2006 +"2006-07-04","Independence Day","VI",2006 +"2006-09-04","Labor Day","VI",2006 +"2006-10-09","Columbus Day and Puerto Rico Friendship Day","VI",2006 +"2006-11-01","Liberty Day","VI",2006 +"2006-11-10","Veterans Day (Observed)","VI",2006 +"2006-11-11","Veterans Day","VI",2006 +"2006-11-23","Thanksgiving","VI",2006 +"2006-12-25","Christmas Day","VI",2006 +"2006-12-26","Christmas Second Day","VI",2006 +"2007-01-01","New Year's Day","VI",2007 +"2007-01-06","Three King's Day","VI",2007 +"2007-01-15","Martin Luther King Jr. Day","VI",2007 +"2007-02-19","Presidents' Day","VI",2007 +"2007-03-31","Transfer Day","VI",2007 +"2007-04-05","Holy Thursday","VI",2007 +"2007-04-06","Good Friday","VI",2007 +"2007-04-09","Easter Monday","VI",2007 +"2007-05-28","Memorial Day","VI",2007 +"2007-07-03","Emancipation Day","VI",2007 +"2007-07-04","Independence Day","VI",2007 +"2007-09-03","Labor Day","VI",2007 +"2007-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2007 +"2007-11-01","Liberty Day","VI",2007 +"2007-11-11","Veterans Day","VI",2007 +"2007-11-12","Veterans Day (Observed)","VI",2007 +"2007-11-22","Thanksgiving","VI",2007 +"2007-12-25","Christmas Day","VI",2007 +"2007-12-26","Christmas Second Day","VI",2007 +"2008-01-01","New Year's Day","VI",2008 +"2008-01-06","Three King's Day","VI",2008 +"2008-01-21","Martin Luther King Jr. Day","VI",2008 +"2008-02-18","Presidents' Day","VI",2008 +"2008-03-20","Holy Thursday","VI",2008 +"2008-03-21","Good Friday","VI",2008 +"2008-03-24","Easter Monday","VI",2008 +"2008-03-31","Transfer Day","VI",2008 +"2008-05-26","Memorial Day","VI",2008 +"2008-07-03","Emancipation Day","VI",2008 +"2008-07-04","Independence Day","VI",2008 +"2008-09-01","Labor Day","VI",2008 +"2008-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2008 +"2008-11-01","Liberty Day","VI",2008 +"2008-11-11","Veterans Day","VI",2008 +"2008-11-27","Thanksgiving","VI",2008 +"2008-12-25","Christmas Day","VI",2008 +"2008-12-26","Christmas Second Day","VI",2008 +"2009-01-01","New Year's Day","VI",2009 +"2009-01-06","Three King's Day","VI",2009 +"2009-01-19","Martin Luther King Jr. Day","VI",2009 +"2009-02-16","Presidents' Day","VI",2009 +"2009-03-31","Transfer Day","VI",2009 +"2009-04-09","Holy Thursday","VI",2009 +"2009-04-10","Good Friday","VI",2009 +"2009-04-13","Easter Monday","VI",2009 +"2009-05-25","Memorial Day","VI",2009 +"2009-07-03","Emancipation Day","VI",2009 +"2009-07-03","Independence Day (Observed)","VI",2009 +"2009-07-04","Independence Day","VI",2009 +"2009-09-07","Labor Day","VI",2009 +"2009-10-12","Columbus Day and Puerto Rico Friendship Day","VI",2009 +"2009-11-01","Liberty Day","VI",2009 +"2009-11-11","Veterans Day","VI",2009 +"2009-11-26","Thanksgiving","VI",2009 +"2009-12-25","Christmas Day","VI",2009 +"2009-12-26","Christmas Second Day","VI",2009 +"2010-01-01","New Year's Day","VI",2010 +"2010-01-06","Three King's Day","VI",2010 +"2010-01-18","Martin Luther King Jr. Day","VI",2010 +"2010-02-15","Presidents' Day","VI",2010 +"2010-03-31","Transfer Day","VI",2010 +"2010-04-01","Holy Thursday","VI",2010 +"2010-04-02","Good Friday","VI",2010 +"2010-04-05","Easter Monday","VI",2010 +"2010-05-31","Memorial Day","VI",2010 +"2010-07-03","Emancipation Day","VI",2010 +"2010-07-04","Independence Day","VI",2010 +"2010-07-05","Independence Day (Observed)","VI",2010 +"2010-09-06","Labor Day","VI",2010 +"2010-10-11","Columbus Day and Puerto Rico Friendship Day","VI",2010 +"2010-11-01","Liberty Day","VI",2010 +"2010-11-11","Veterans Day","VI",2010 +"2010-11-25","Thanksgiving","VI",2010 +"2010-12-24","Christmas Day (Observed)","VI",2010 +"2010-12-25","Christmas Day","VI",2010 +"2010-12-26","Christmas Second Day","VI",2010 +"2010-12-31","New Year's Day (Observed)","VI",2010 +"2011-01-01","New Year's Day","VI",2011 +"2011-01-06","Three King's Day","VI",2011 +"2011-01-17","Martin Luther King Jr. Day","VI",2011 +"2011-02-21","Presidents' Day","VI",2011 +"2011-03-31","Transfer Day","VI",2011 +"2011-04-21","Holy Thursday","VI",2011 +"2011-04-22","Good Friday","VI",2011 +"2011-04-25","Easter Monday","VI",2011 +"2011-05-30","Memorial Day","VI",2011 +"2011-07-03","Emancipation Day","VI",2011 +"2011-07-04","Independence Day","VI",2011 +"2011-09-05","Labor Day","VI",2011 +"2011-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2011 +"2011-11-01","Liberty Day","VI",2011 +"2011-11-11","Veterans Day","VI",2011 +"2011-11-24","Thanksgiving","VI",2011 +"2011-12-25","Christmas Day","VI",2011 +"2011-12-26","Christmas Day (Observed)","VI",2011 +"2011-12-26","Christmas Second Day","VI",2011 +"2012-01-01","New Year's Day","VI",2012 +"2012-01-02","New Year's Day (Observed)","VI",2012 +"2012-01-06","Three King's Day","VI",2012 +"2012-01-16","Martin Luther King Jr. Day","VI",2012 +"2012-02-20","Presidents' Day","VI",2012 +"2012-03-31","Transfer Day","VI",2012 +"2012-04-05","Holy Thursday","VI",2012 +"2012-04-06","Good Friday","VI",2012 +"2012-04-09","Easter Monday","VI",2012 +"2012-05-28","Memorial Day","VI",2012 +"2012-07-03","Emancipation Day","VI",2012 +"2012-07-04","Independence Day","VI",2012 +"2012-09-03","Labor Day","VI",2012 +"2012-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2012 +"2012-11-01","Liberty Day","VI",2012 +"2012-11-11","Veterans Day","VI",2012 +"2012-11-12","Veterans Day (Observed)","VI",2012 +"2012-11-22","Thanksgiving","VI",2012 +"2012-12-25","Christmas Day","VI",2012 +"2012-12-26","Christmas Second Day","VI",2012 +"2013-01-01","New Year's Day","VI",2013 +"2013-01-06","Three King's Day","VI",2013 +"2013-01-21","Martin Luther King Jr. Day","VI",2013 +"2013-02-18","Presidents' Day","VI",2013 +"2013-03-28","Holy Thursday","VI",2013 +"2013-03-29","Good Friday","VI",2013 +"2013-03-31","Transfer Day","VI",2013 +"2013-04-01","Easter Monday","VI",2013 +"2013-05-27","Memorial Day","VI",2013 +"2013-07-03","Emancipation Day","VI",2013 +"2013-07-04","Independence Day","VI",2013 +"2013-09-02","Labor Day","VI",2013 +"2013-10-14","Columbus Day and Puerto Rico Friendship Day","VI",2013 +"2013-11-01","Liberty Day","VI",2013 +"2013-11-11","Veterans Day","VI",2013 +"2013-11-28","Thanksgiving","VI",2013 +"2013-12-25","Christmas Day","VI",2013 +"2013-12-26","Christmas Second Day","VI",2013 +"2014-01-01","New Year's Day","VI",2014 +"2014-01-06","Three King's Day","VI",2014 +"2014-01-20","Martin Luther King Jr. Day","VI",2014 +"2014-02-17","Presidents' Day","VI",2014 +"2014-03-31","Transfer Day","VI",2014 +"2014-04-17","Holy Thursday","VI",2014 +"2014-04-18","Good Friday","VI",2014 +"2014-04-21","Easter Monday","VI",2014 +"2014-05-26","Memorial Day","VI",2014 +"2014-07-03","Emancipation Day","VI",2014 +"2014-07-04","Independence Day","VI",2014 +"2014-09-01","Labor Day","VI",2014 +"2014-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2014 +"2014-11-01","Liberty Day","VI",2014 +"2014-11-11","Veterans Day","VI",2014 +"2014-11-27","Thanksgiving","VI",2014 +"2014-12-25","Christmas Day","VI",2014 +"2014-12-26","Christmas Second Day","VI",2014 +"2015-01-01","New Year's Day","VI",2015 +"2015-01-06","Three King's Day","VI",2015 +"2015-01-19","Martin Luther King Jr. Day","VI",2015 +"2015-02-16","Presidents' Day","VI",2015 +"2015-03-31","Transfer Day","VI",2015 +"2015-04-02","Holy Thursday","VI",2015 +"2015-04-03","Good Friday","VI",2015 +"2015-04-06","Easter Monday","VI",2015 +"2015-05-25","Memorial Day","VI",2015 +"2015-07-03","Emancipation Day","VI",2015 +"2015-07-03","Independence Day (Observed)","VI",2015 +"2015-07-04","Independence Day","VI",2015 +"2015-09-07","Labor Day","VI",2015 +"2015-10-12","Columbus Day and Puerto Rico Friendship Day","VI",2015 +"2015-11-01","Liberty Day","VI",2015 +"2015-11-11","Veterans Day","VI",2015 +"2015-11-26","Thanksgiving","VI",2015 +"2015-12-25","Christmas Day","VI",2015 +"2015-12-26","Christmas Second Day","VI",2015 +"2016-01-01","New Year's Day","VI",2016 +"2016-01-06","Three King's Day","VI",2016 +"2016-01-18","Martin Luther King Jr. Day","VI",2016 +"2016-02-15","Presidents' Day","VI",2016 +"2016-03-24","Holy Thursday","VI",2016 +"2016-03-25","Good Friday","VI",2016 +"2016-03-28","Easter Monday","VI",2016 +"2016-03-31","Transfer Day","VI",2016 +"2016-05-30","Memorial Day","VI",2016 +"2016-07-03","Emancipation Day","VI",2016 +"2016-07-04","Independence Day","VI",2016 +"2016-09-05","Labor Day","VI",2016 +"2016-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2016 +"2016-11-01","Liberty Day","VI",2016 +"2016-11-11","Veterans Day","VI",2016 +"2016-11-24","Thanksgiving","VI",2016 +"2016-12-25","Christmas Day","VI",2016 +"2016-12-26","Christmas Day (Observed)","VI",2016 +"2016-12-26","Christmas Second Day","VI",2016 +"2017-01-01","New Year's Day","VI",2017 +"2017-01-02","New Year's Day (Observed)","VI",2017 +"2017-01-06","Three King's Day","VI",2017 +"2017-01-16","Martin Luther King Jr. Day","VI",2017 +"2017-02-20","Presidents' Day","VI",2017 +"2017-03-31","Transfer Day","VI",2017 +"2017-04-13","Holy Thursday","VI",2017 +"2017-04-14","Good Friday","VI",2017 +"2017-04-17","Easter Monday","VI",2017 +"2017-05-29","Memorial Day","VI",2017 +"2017-07-03","Emancipation Day","VI",2017 +"2017-07-04","Independence Day","VI",2017 +"2017-09-04","Labor Day","VI",2017 +"2017-10-09","Columbus Day and Puerto Rico Friendship Day","VI",2017 +"2017-11-01","Liberty Day","VI",2017 +"2017-11-10","Veterans Day (Observed)","VI",2017 +"2017-11-11","Veterans Day","VI",2017 +"2017-11-23","Thanksgiving","VI",2017 +"2017-12-25","Christmas Day","VI",2017 +"2017-12-26","Christmas Second Day","VI",2017 +"2018-01-01","New Year's Day","VI",2018 +"2018-01-06","Three King's Day","VI",2018 +"2018-01-15","Martin Luther King Jr. Day","VI",2018 +"2018-02-19","Presidents' Day","VI",2018 +"2018-03-29","Holy Thursday","VI",2018 +"2018-03-30","Good Friday","VI",2018 +"2018-03-31","Transfer Day","VI",2018 +"2018-04-02","Easter Monday","VI",2018 +"2018-05-28","Memorial Day","VI",2018 +"2018-07-03","Emancipation Day","VI",2018 +"2018-07-04","Independence Day","VI",2018 +"2018-09-03","Labor Day","VI",2018 +"2018-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2018 +"2018-11-01","Liberty Day","VI",2018 +"2018-11-11","Veterans Day","VI",2018 +"2018-11-12","Veterans Day (Observed)","VI",2018 +"2018-11-22","Thanksgiving","VI",2018 +"2018-12-25","Christmas Day","VI",2018 +"2018-12-26","Christmas Second Day","VI",2018 +"2019-01-01","New Year's Day","VI",2019 +"2019-01-06","Three King's Day","VI",2019 +"2019-01-21","Martin Luther King Jr. Day","VI",2019 +"2019-02-18","Presidents' Day","VI",2019 +"2019-03-31","Transfer Day","VI",2019 +"2019-04-18","Holy Thursday","VI",2019 +"2019-04-19","Good Friday","VI",2019 +"2019-04-22","Easter Monday","VI",2019 +"2019-05-27","Memorial Day","VI",2019 +"2019-07-03","Emancipation Day","VI",2019 +"2019-07-04","Independence Day","VI",2019 +"2019-09-02","Labor Day","VI",2019 +"2019-10-14","Columbus Day and Puerto Rico Friendship Day","VI",2019 +"2019-11-01","Liberty Day","VI",2019 +"2019-11-11","Veterans Day","VI",2019 +"2019-11-28","Thanksgiving","VI",2019 +"2019-12-25","Christmas Day","VI",2019 +"2019-12-26","Christmas Second Day","VI",2019 +"2020-01-01","New Year's Day","VI",2020 +"2020-01-06","Three King's Day","VI",2020 +"2020-01-20","Martin Luther King Jr. Day","VI",2020 +"2020-02-17","Presidents' Day","VI",2020 +"2020-03-31","Transfer Day","VI",2020 +"2020-04-09","Holy Thursday","VI",2020 +"2020-04-10","Good Friday","VI",2020 +"2020-04-13","Easter Monday","VI",2020 +"2020-05-25","Memorial Day","VI",2020 +"2020-07-03","Emancipation Day","VI",2020 +"2020-07-03","Independence Day (Observed)","VI",2020 +"2020-07-04","Independence Day","VI",2020 +"2020-09-07","Labor Day","VI",2020 +"2020-10-12","Columbus Day and Puerto Rico Friendship Day","VI",2020 +"2020-11-01","Liberty Day","VI",2020 +"2020-11-11","Veterans Day","VI",2020 +"2020-11-26","Thanksgiving","VI",2020 +"2020-12-25","Christmas Day","VI",2020 +"2020-12-26","Christmas Second Day","VI",2020 +"2021-01-01","New Year's Day","VI",2021 +"2021-01-06","Three King's Day","VI",2021 +"2021-01-18","Martin Luther King Jr. Day","VI",2021 +"2021-02-15","Presidents' Day","VI",2021 +"2021-03-31","Transfer Day","VI",2021 +"2021-04-01","Holy Thursday","VI",2021 +"2021-04-02","Good Friday","VI",2021 +"2021-04-05","Easter Monday","VI",2021 +"2021-05-31","Memorial Day","VI",2021 +"2021-06-18","Juneteenth National Independence Day (Observed)","VI",2021 +"2021-06-19","Juneteenth National Independence Day","VI",2021 +"2021-07-03","Emancipation Day","VI",2021 +"2021-07-04","Independence Day","VI",2021 +"2021-07-05","Independence Day (Observed)","VI",2021 +"2021-09-06","Labor Day","VI",2021 +"2021-10-11","Columbus Day and Puerto Rico Friendship Day","VI",2021 +"2021-11-01","Liberty Day","VI",2021 +"2021-11-11","Veterans Day","VI",2021 +"2021-11-25","Thanksgiving","VI",2021 +"2021-12-24","Christmas Day (Observed)","VI",2021 +"2021-12-25","Christmas Day","VI",2021 +"2021-12-26","Christmas Second Day","VI",2021 +"2021-12-31","New Year's Day (Observed)","VI",2021 +"2022-01-01","New Year's Day","VI",2022 +"2022-01-06","Three King's Day","VI",2022 +"2022-01-17","Martin Luther King Jr. Day","VI",2022 +"2022-02-21","Presidents' Day","VI",2022 +"2022-03-31","Transfer Day","VI",2022 +"2022-04-14","Holy Thursday","VI",2022 +"2022-04-15","Good Friday","VI",2022 +"2022-04-18","Easter Monday","VI",2022 +"2022-05-30","Memorial Day","VI",2022 +"2022-06-19","Juneteenth National Independence Day","VI",2022 +"2022-06-20","Juneteenth National Independence Day (Observed)","VI",2022 +"2022-07-03","Emancipation Day","VI",2022 +"2022-07-04","Independence Day","VI",2022 +"2022-09-05","Labor Day","VI",2022 +"2022-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2022 +"2022-11-01","Liberty Day","VI",2022 +"2022-11-11","Veterans Day","VI",2022 +"2022-11-24","Thanksgiving","VI",2022 +"2022-12-25","Christmas Day","VI",2022 +"2022-12-26","Christmas Day (Observed)","VI",2022 +"2022-12-26","Christmas Second Day","VI",2022 +"2023-01-01","New Year's Day","VI",2023 +"2023-01-02","New Year's Day (Observed)","VI",2023 +"2023-01-06","Three King's Day","VI",2023 +"2023-01-16","Martin Luther King Jr. Day","VI",2023 +"2023-02-20","Presidents' Day","VI",2023 +"2023-03-31","Transfer Day","VI",2023 +"2023-04-06","Holy Thursday","VI",2023 +"2023-04-07","Good Friday","VI",2023 +"2023-04-10","Easter Monday","VI",2023 +"2023-05-29","Memorial Day","VI",2023 +"2023-06-19","Juneteenth National Independence Day","VI",2023 +"2023-07-03","Emancipation Day","VI",2023 +"2023-07-04","Independence Day","VI",2023 +"2023-09-04","Labor Day","VI",2023 +"2023-10-09","Columbus Day and Puerto Rico Friendship Day","VI",2023 +"2023-11-01","Liberty Day","VI",2023 +"2023-11-10","Veterans Day (Observed)","VI",2023 +"2023-11-11","Veterans Day","VI",2023 +"2023-11-23","Thanksgiving","VI",2023 +"2023-12-25","Christmas Day","VI",2023 +"2023-12-26","Christmas Second Day","VI",2023 +"2024-01-01","New Year's Day","VI",2024 +"2024-01-06","Three King's Day","VI",2024 +"2024-01-15","Martin Luther King Jr. Day","VI",2024 +"2024-02-19","Presidents' Day","VI",2024 +"2024-03-28","Holy Thursday","VI",2024 +"2024-03-29","Good Friday","VI",2024 +"2024-03-31","Transfer Day","VI",2024 +"2024-04-01","Easter Monday","VI",2024 +"2024-05-27","Memorial Day","VI",2024 +"2024-06-19","Juneteenth National Independence Day","VI",2024 +"2024-07-03","Emancipation Day","VI",2024 +"2024-07-04","Independence Day","VI",2024 +"2024-09-02","Labor Day","VI",2024 +"2024-10-14","Columbus Day and Puerto Rico Friendship Day","VI",2024 +"2024-11-01","Liberty Day","VI",2024 +"2024-11-11","Veterans Day","VI",2024 +"2024-11-28","Thanksgiving","VI",2024 +"2024-12-25","Christmas Day","VI",2024 +"2024-12-26","Christmas Second Day","VI",2024 +"2025-01-01","New Year's Day","VI",2025 +"2025-01-06","Three King's Day","VI",2025 +"2025-01-20","Martin Luther King Jr. Day","VI",2025 +"2025-02-17","Presidents' Day","VI",2025 +"2025-03-31","Transfer Day","VI",2025 +"2025-04-17","Holy Thursday","VI",2025 +"2025-04-18","Good Friday","VI",2025 +"2025-04-21","Easter Monday","VI",2025 +"2025-05-26","Memorial Day","VI",2025 +"2025-06-19","Juneteenth National Independence Day","VI",2025 +"2025-07-03","Emancipation Day","VI",2025 +"2025-07-04","Independence Day","VI",2025 +"2025-09-01","Labor Day","VI",2025 +"2025-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2025 +"2025-11-01","Liberty Day","VI",2025 +"2025-11-11","Veterans Day","VI",2025 +"2025-11-27","Thanksgiving","VI",2025 +"2025-12-25","Christmas Day","VI",2025 +"2025-12-26","Christmas Second Day","VI",2025 +"2026-01-01","New Year's Day","VI",2026 +"2026-01-06","Three King's Day","VI",2026 +"2026-01-19","Martin Luther King Jr. Day","VI",2026 +"2026-02-16","Presidents' Day","VI",2026 +"2026-03-31","Transfer Day","VI",2026 +"2026-04-02","Holy Thursday","VI",2026 +"2026-04-03","Good Friday","VI",2026 +"2026-04-06","Easter Monday","VI",2026 +"2026-05-25","Memorial Day","VI",2026 +"2026-06-19","Juneteenth National Independence Day","VI",2026 +"2026-07-03","Emancipation Day","VI",2026 +"2026-07-03","Independence Day (Observed)","VI",2026 +"2026-07-04","Independence Day","VI",2026 +"2026-09-07","Labor Day","VI",2026 +"2026-10-12","Columbus Day and Puerto Rico Friendship Day","VI",2026 +"2026-11-01","Liberty Day","VI",2026 +"2026-11-11","Veterans Day","VI",2026 +"2026-11-26","Thanksgiving","VI",2026 +"2026-12-25","Christmas Day","VI",2026 +"2026-12-26","Christmas Second Day","VI",2026 +"2027-01-01","New Year's Day","VI",2027 +"2027-01-06","Three King's Day","VI",2027 +"2027-01-18","Martin Luther King Jr. Day","VI",2027 +"2027-02-15","Presidents' Day","VI",2027 +"2027-03-25","Holy Thursday","VI",2027 +"2027-03-26","Good Friday","VI",2027 +"2027-03-29","Easter Monday","VI",2027 +"2027-03-31","Transfer Day","VI",2027 +"2027-05-31","Memorial Day","VI",2027 +"2027-06-18","Juneteenth National Independence Day (Observed)","VI",2027 +"2027-06-19","Juneteenth National Independence Day","VI",2027 +"2027-07-03","Emancipation Day","VI",2027 +"2027-07-04","Independence Day","VI",2027 +"2027-07-05","Independence Day (Observed)","VI",2027 +"2027-09-06","Labor Day","VI",2027 +"2027-10-11","Columbus Day and Puerto Rico Friendship Day","VI",2027 +"2027-11-01","Liberty Day","VI",2027 +"2027-11-11","Veterans Day","VI",2027 +"2027-11-25","Thanksgiving","VI",2027 +"2027-12-24","Christmas Day (Observed)","VI",2027 +"2027-12-25","Christmas Day","VI",2027 +"2027-12-26","Christmas Second Day","VI",2027 +"2027-12-31","New Year's Day (Observed)","VI",2027 +"2028-01-01","New Year's Day","VI",2028 +"2028-01-06","Three King's Day","VI",2028 +"2028-01-17","Martin Luther King Jr. Day","VI",2028 +"2028-02-21","Presidents' Day","VI",2028 +"2028-03-31","Transfer Day","VI",2028 +"2028-04-13","Holy Thursday","VI",2028 +"2028-04-14","Good Friday","VI",2028 +"2028-04-17","Easter Monday","VI",2028 +"2028-05-29","Memorial Day","VI",2028 +"2028-06-19","Juneteenth National Independence Day","VI",2028 +"2028-07-03","Emancipation Day","VI",2028 +"2028-07-04","Independence Day","VI",2028 +"2028-09-04","Labor Day","VI",2028 +"2028-10-09","Columbus Day and Puerto Rico Friendship Day","VI",2028 +"2028-11-01","Liberty Day","VI",2028 +"2028-11-10","Veterans Day (Observed)","VI",2028 +"2028-11-11","Veterans Day","VI",2028 +"2028-11-23","Thanksgiving","VI",2028 +"2028-12-25","Christmas Day","VI",2028 +"2028-12-26","Christmas Second Day","VI",2028 +"2029-01-01","New Year's Day","VI",2029 +"2029-01-06","Three King's Day","VI",2029 +"2029-01-15","Martin Luther King Jr. Day","VI",2029 +"2029-02-19","Presidents' Day","VI",2029 +"2029-03-29","Holy Thursday","VI",2029 +"2029-03-30","Good Friday","VI",2029 +"2029-03-31","Transfer Day","VI",2029 +"2029-04-02","Easter Monday","VI",2029 +"2029-05-28","Memorial Day","VI",2029 +"2029-06-19","Juneteenth National Independence Day","VI",2029 +"2029-07-03","Emancipation Day","VI",2029 +"2029-07-04","Independence Day","VI",2029 +"2029-09-03","Labor Day","VI",2029 +"2029-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2029 +"2029-11-01","Liberty Day","VI",2029 +"2029-11-11","Veterans Day","VI",2029 +"2029-11-12","Veterans Day (Observed)","VI",2029 +"2029-11-22","Thanksgiving","VI",2029 +"2029-12-25","Christmas Day","VI",2029 +"2029-12-26","Christmas Second Day","VI",2029 +"2030-01-01","New Year's Day","VI",2030 +"2030-01-06","Three King's Day","VI",2030 +"2030-01-21","Martin Luther King Jr. Day","VI",2030 +"2030-02-18","Presidents' Day","VI",2030 +"2030-03-31","Transfer Day","VI",2030 +"2030-04-18","Holy Thursday","VI",2030 +"2030-04-19","Good Friday","VI",2030 +"2030-04-22","Easter Monday","VI",2030 +"2030-05-27","Memorial Day","VI",2030 +"2030-06-19","Juneteenth National Independence Day","VI",2030 +"2030-07-03","Emancipation Day","VI",2030 +"2030-07-04","Independence Day","VI",2030 +"2030-09-02","Labor Day","VI",2030 +"2030-10-14","Columbus Day and Puerto Rico Friendship Day","VI",2030 +"2030-11-01","Liberty Day","VI",2030 +"2030-11-11","Veterans Day","VI",2030 +"2030-11-28","Thanksgiving","VI",2030 +"2030-12-25","Christmas Day","VI",2030 +"2030-12-26","Christmas Second Day","VI",2030 +"2031-01-01","New Year's Day","VI",2031 +"2031-01-06","Three King's Day","VI",2031 +"2031-01-20","Martin Luther King Jr. Day","VI",2031 +"2031-02-17","Presidents' Day","VI",2031 +"2031-03-31","Transfer Day","VI",2031 +"2031-04-10","Holy Thursday","VI",2031 +"2031-04-11","Good Friday","VI",2031 +"2031-04-14","Easter Monday","VI",2031 +"2031-05-26","Memorial Day","VI",2031 +"2031-06-19","Juneteenth National Independence Day","VI",2031 +"2031-07-03","Emancipation Day","VI",2031 +"2031-07-04","Independence Day","VI",2031 +"2031-09-01","Labor Day","VI",2031 +"2031-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2031 +"2031-11-01","Liberty Day","VI",2031 +"2031-11-11","Veterans Day","VI",2031 +"2031-11-27","Thanksgiving","VI",2031 +"2031-12-25","Christmas Day","VI",2031 +"2031-12-26","Christmas Second Day","VI",2031 +"2032-01-01","New Year's Day","VI",2032 +"2032-01-06","Three King's Day","VI",2032 +"2032-01-19","Martin Luther King Jr. Day","VI",2032 +"2032-02-16","Presidents' Day","VI",2032 +"2032-03-25","Holy Thursday","VI",2032 +"2032-03-26","Good Friday","VI",2032 +"2032-03-29","Easter Monday","VI",2032 +"2032-03-31","Transfer Day","VI",2032 +"2032-05-31","Memorial Day","VI",2032 +"2032-06-18","Juneteenth National Independence Day (Observed)","VI",2032 +"2032-06-19","Juneteenth National Independence Day","VI",2032 +"2032-07-03","Emancipation Day","VI",2032 +"2032-07-04","Independence Day","VI",2032 +"2032-07-05","Independence Day (Observed)","VI",2032 +"2032-09-06","Labor Day","VI",2032 +"2032-10-11","Columbus Day and Puerto Rico Friendship Day","VI",2032 +"2032-11-01","Liberty Day","VI",2032 +"2032-11-11","Veterans Day","VI",2032 +"2032-11-25","Thanksgiving","VI",2032 +"2032-12-24","Christmas Day (Observed)","VI",2032 +"2032-12-25","Christmas Day","VI",2032 +"2032-12-26","Christmas Second Day","VI",2032 +"2032-12-31","New Year's Day (Observed)","VI",2032 +"2033-01-01","New Year's Day","VI",2033 +"2033-01-06","Three King's Day","VI",2033 +"2033-01-17","Martin Luther King Jr. Day","VI",2033 +"2033-02-21","Presidents' Day","VI",2033 +"2033-03-31","Transfer Day","VI",2033 +"2033-04-14","Holy Thursday","VI",2033 +"2033-04-15","Good Friday","VI",2033 +"2033-04-18","Easter Monday","VI",2033 +"2033-05-30","Memorial Day","VI",2033 +"2033-06-19","Juneteenth National Independence Day","VI",2033 +"2033-06-20","Juneteenth National Independence Day (Observed)","VI",2033 +"2033-07-03","Emancipation Day","VI",2033 +"2033-07-04","Independence Day","VI",2033 +"2033-09-05","Labor Day","VI",2033 +"2033-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2033 +"2033-11-01","Liberty Day","VI",2033 +"2033-11-11","Veterans Day","VI",2033 +"2033-11-24","Thanksgiving","VI",2033 +"2033-12-25","Christmas Day","VI",2033 +"2033-12-26","Christmas Day (Observed)","VI",2033 +"2033-12-26","Christmas Second Day","VI",2033 +"2034-01-01","New Year's Day","VI",2034 +"2034-01-02","New Year's Day (Observed)","VI",2034 +"2034-01-06","Three King's Day","VI",2034 +"2034-01-16","Martin Luther King Jr. Day","VI",2034 +"2034-02-20","Presidents' Day","VI",2034 +"2034-03-31","Transfer Day","VI",2034 +"2034-04-06","Holy Thursday","VI",2034 +"2034-04-07","Good Friday","VI",2034 +"2034-04-10","Easter Monday","VI",2034 +"2034-05-29","Memorial Day","VI",2034 +"2034-06-19","Juneteenth National Independence Day","VI",2034 +"2034-07-03","Emancipation Day","VI",2034 +"2034-07-04","Independence Day","VI",2034 +"2034-09-04","Labor Day","VI",2034 +"2034-10-09","Columbus Day and Puerto Rico Friendship Day","VI",2034 +"2034-11-01","Liberty Day","VI",2034 +"2034-11-10","Veterans Day (Observed)","VI",2034 +"2034-11-11","Veterans Day","VI",2034 +"2034-11-23","Thanksgiving","VI",2034 +"2034-12-25","Christmas Day","VI",2034 +"2034-12-26","Christmas Second Day","VI",2034 +"2035-01-01","New Year's Day","VI",2035 +"2035-01-06","Three King's Day","VI",2035 +"2035-01-15","Martin Luther King Jr. Day","VI",2035 +"2035-02-19","Presidents' Day","VI",2035 +"2035-03-22","Holy Thursday","VI",2035 +"2035-03-23","Good Friday","VI",2035 +"2035-03-26","Easter Monday","VI",2035 +"2035-03-31","Transfer Day","VI",2035 +"2035-05-28","Memorial Day","VI",2035 +"2035-06-19","Juneteenth National Independence Day","VI",2035 +"2035-07-03","Emancipation Day","VI",2035 +"2035-07-04","Independence Day","VI",2035 +"2035-09-03","Labor Day","VI",2035 +"2035-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2035 +"2035-11-01","Liberty Day","VI",2035 +"2035-11-11","Veterans Day","VI",2035 +"2035-11-12","Veterans Day (Observed)","VI",2035 +"2035-11-22","Thanksgiving","VI",2035 +"2035-12-25","Christmas Day","VI",2035 +"2035-12-26","Christmas Second Day","VI",2035 +"2036-01-01","New Year's Day","VI",2036 +"2036-01-06","Three King's Day","VI",2036 +"2036-01-21","Martin Luther King Jr. Day","VI",2036 +"2036-02-18","Presidents' Day","VI",2036 +"2036-03-31","Transfer Day","VI",2036 +"2036-04-10","Holy Thursday","VI",2036 +"2036-04-11","Good Friday","VI",2036 +"2036-04-14","Easter Monday","VI",2036 +"2036-05-26","Memorial Day","VI",2036 +"2036-06-19","Juneteenth National Independence Day","VI",2036 +"2036-07-03","Emancipation Day","VI",2036 +"2036-07-04","Independence Day","VI",2036 +"2036-09-01","Labor Day","VI",2036 +"2036-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2036 +"2036-11-01","Liberty Day","VI",2036 +"2036-11-11","Veterans Day","VI",2036 +"2036-11-27","Thanksgiving","VI",2036 +"2036-12-25","Christmas Day","VI",2036 +"2036-12-26","Christmas Second Day","VI",2036 +"2037-01-01","New Year's Day","VI",2037 +"2037-01-06","Three King's Day","VI",2037 +"2037-01-19","Martin Luther King Jr. Day","VI",2037 +"2037-02-16","Presidents' Day","VI",2037 +"2037-03-31","Transfer Day","VI",2037 +"2037-04-02","Holy Thursday","VI",2037 +"2037-04-03","Good Friday","VI",2037 +"2037-04-06","Easter Monday","VI",2037 +"2037-05-25","Memorial Day","VI",2037 +"2037-06-19","Juneteenth National Independence Day","VI",2037 +"2037-07-03","Emancipation Day","VI",2037 +"2037-07-03","Independence Day (Observed)","VI",2037 +"2037-07-04","Independence Day","VI",2037 +"2037-09-07","Labor Day","VI",2037 +"2037-10-12","Columbus Day and Puerto Rico Friendship Day","VI",2037 +"2037-11-01","Liberty Day","VI",2037 +"2037-11-11","Veterans Day","VI",2037 +"2037-11-26","Thanksgiving","VI",2037 +"2037-12-25","Christmas Day","VI",2037 +"2037-12-26","Christmas Second Day","VI",2037 +"2038-01-01","New Year's Day","VI",2038 +"2038-01-06","Three King's Day","VI",2038 +"2038-01-18","Martin Luther King Jr. Day","VI",2038 +"2038-02-15","Presidents' Day","VI",2038 +"2038-03-31","Transfer Day","VI",2038 +"2038-04-22","Holy Thursday","VI",2038 +"2038-04-23","Good Friday","VI",2038 +"2038-04-26","Easter Monday","VI",2038 +"2038-05-31","Memorial Day","VI",2038 +"2038-06-18","Juneteenth National Independence Day (Observed)","VI",2038 +"2038-06-19","Juneteenth National Independence Day","VI",2038 +"2038-07-03","Emancipation Day","VI",2038 +"2038-07-04","Independence Day","VI",2038 +"2038-07-05","Independence Day (Observed)","VI",2038 +"2038-09-06","Labor Day","VI",2038 +"2038-10-11","Columbus Day and Puerto Rico Friendship Day","VI",2038 +"2038-11-01","Liberty Day","VI",2038 +"2038-11-11","Veterans Day","VI",2038 +"2038-11-25","Thanksgiving","VI",2038 +"2038-12-24","Christmas Day (Observed)","VI",2038 +"2038-12-25","Christmas Day","VI",2038 +"2038-12-26","Christmas Second Day","VI",2038 +"2038-12-31","New Year's Day (Observed)","VI",2038 +"2039-01-01","New Year's Day","VI",2039 +"2039-01-06","Three King's Day","VI",2039 +"2039-01-17","Martin Luther King Jr. Day","VI",2039 +"2039-02-21","Presidents' Day","VI",2039 +"2039-03-31","Transfer Day","VI",2039 +"2039-04-07","Holy Thursday","VI",2039 +"2039-04-08","Good Friday","VI",2039 +"2039-04-11","Easter Monday","VI",2039 +"2039-05-30","Memorial Day","VI",2039 +"2039-06-19","Juneteenth National Independence Day","VI",2039 +"2039-06-20","Juneteenth National Independence Day (Observed)","VI",2039 +"2039-07-03","Emancipation Day","VI",2039 +"2039-07-04","Independence Day","VI",2039 +"2039-09-05","Labor Day","VI",2039 +"2039-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2039 +"2039-11-01","Liberty Day","VI",2039 +"2039-11-11","Veterans Day","VI",2039 +"2039-11-24","Thanksgiving","VI",2039 +"2039-12-25","Christmas Day","VI",2039 +"2039-12-26","Christmas Day (Observed)","VI",2039 +"2039-12-26","Christmas Second Day","VI",2039 +"2040-01-01","New Year's Day","VI",2040 +"2040-01-02","New Year's Day (Observed)","VI",2040 +"2040-01-06","Three King's Day","VI",2040 +"2040-01-16","Martin Luther King Jr. Day","VI",2040 +"2040-02-20","Presidents' Day","VI",2040 +"2040-03-29","Holy Thursday","VI",2040 +"2040-03-30","Good Friday","VI",2040 +"2040-03-31","Transfer Day","VI",2040 +"2040-04-02","Easter Monday","VI",2040 +"2040-05-28","Memorial Day","VI",2040 +"2040-06-19","Juneteenth National Independence Day","VI",2040 +"2040-07-03","Emancipation Day","VI",2040 +"2040-07-04","Independence Day","VI",2040 +"2040-09-03","Labor Day","VI",2040 +"2040-10-08","Columbus Day and Puerto Rico Friendship Day","VI",2040 +"2040-11-01","Liberty Day","VI",2040 +"2040-11-11","Veterans Day","VI",2040 +"2040-11-12","Veterans Day (Observed)","VI",2040 +"2040-11-22","Thanksgiving","VI",2040 +"2040-12-25","Christmas Day","VI",2040 +"2040-12-26","Christmas Second Day","VI",2040 +"2041-01-01","New Year's Day","VI",2041 +"2041-01-06","Three King's Day","VI",2041 +"2041-01-21","Martin Luther King Jr. Day","VI",2041 +"2041-02-18","Presidents' Day","VI",2041 +"2041-03-31","Transfer Day","VI",2041 +"2041-04-18","Holy Thursday","VI",2041 +"2041-04-19","Good Friday","VI",2041 +"2041-04-22","Easter Monday","VI",2041 +"2041-05-27","Memorial Day","VI",2041 +"2041-06-19","Juneteenth National Independence Day","VI",2041 +"2041-07-03","Emancipation Day","VI",2041 +"2041-07-04","Independence Day","VI",2041 +"2041-09-02","Labor Day","VI",2041 +"2041-10-14","Columbus Day and Puerto Rico Friendship Day","VI",2041 +"2041-11-01","Liberty Day","VI",2041 +"2041-11-11","Veterans Day","VI",2041 +"2041-11-28","Thanksgiving","VI",2041 +"2041-12-25","Christmas Day","VI",2041 +"2041-12-26","Christmas Second Day","VI",2041 +"2042-01-01","New Year's Day","VI",2042 +"2042-01-06","Three King's Day","VI",2042 +"2042-01-20","Martin Luther King Jr. Day","VI",2042 +"2042-02-17","Presidents' Day","VI",2042 +"2042-03-31","Transfer Day","VI",2042 +"2042-04-03","Holy Thursday","VI",2042 +"2042-04-04","Good Friday","VI",2042 +"2042-04-07","Easter Monday","VI",2042 +"2042-05-26","Memorial Day","VI",2042 +"2042-06-19","Juneteenth National Independence Day","VI",2042 +"2042-07-03","Emancipation Day","VI",2042 +"2042-07-04","Independence Day","VI",2042 +"2042-09-01","Labor Day","VI",2042 +"2042-10-13","Columbus Day and Puerto Rico Friendship Day","VI",2042 +"2042-11-01","Liberty Day","VI",2042 +"2042-11-11","Veterans Day","VI",2042 +"2042-11-27","Thanksgiving","VI",2042 +"2042-12-25","Christmas Day","VI",2042 +"2042-12-26","Christmas Second Day","VI",2042 +"2043-01-01","New Year's Day","VI",2043 +"2043-01-06","Three King's Day","VI",2043 +"2043-01-19","Martin Luther King Jr. Day","VI",2043 +"2043-02-16","Presidents' Day","VI",2043 +"2043-03-26","Holy Thursday","VI",2043 +"2043-03-27","Good Friday","VI",2043 +"2043-03-30","Easter Monday","VI",2043 +"2043-03-31","Transfer Day","VI",2043 +"2043-05-25","Memorial Day","VI",2043 +"2043-06-19","Juneteenth National Independence Day","VI",2043 +"2043-07-03","Emancipation Day","VI",2043 +"2043-07-03","Independence Day (Observed)","VI",2043 +"2043-07-04","Independence Day","VI",2043 +"2043-09-07","Labor Day","VI",2043 +"2043-10-12","Columbus Day and Puerto Rico Friendship Day","VI",2043 +"2043-11-01","Liberty Day","VI",2043 +"2043-11-11","Veterans Day","VI",2043 +"2043-11-26","Thanksgiving","VI",2043 +"2043-12-25","Christmas Day","VI",2043 +"2043-12-26","Christmas Second Day","VI",2043 +"2044-01-01","New Year's Day","VI",2044 +"2044-01-06","Three King's Day","VI",2044 +"2044-01-18","Martin Luther King Jr. Day","VI",2044 +"2044-02-15","Presidents' Day","VI",2044 +"2044-03-31","Transfer Day","VI",2044 +"2044-04-14","Holy Thursday","VI",2044 +"2044-04-15","Good Friday","VI",2044 +"2044-04-18","Easter Monday","VI",2044 +"2044-05-30","Memorial Day","VI",2044 +"2044-06-19","Juneteenth National Independence Day","VI",2044 +"2044-06-20","Juneteenth National Independence Day (Observed)","VI",2044 +"2044-07-03","Emancipation Day","VI",2044 +"2044-07-04","Independence Day","VI",2044 +"2044-09-05","Labor Day","VI",2044 +"2044-10-10","Columbus Day and Puerto Rico Friendship Day","VI",2044 +"2044-11-01","Liberty Day","VI",2044 +"2044-11-11","Veterans Day","VI",2044 +"2044-11-24","Thanksgiving","VI",2044 +"2044-12-25","Christmas Day","VI",2044 +"2044-12-26","Christmas Day (Observed)","VI",2044 +"2044-12-26","Christmas Second Day","VI",2044 +"1995-01-01","International New Year's Day","VN",1995 +"1995-01-02","International New Year's Day (Observed)","VN",1995 +"1995-01-30","Vietnamese New Year's Eve","VN",1995 +"1995-01-31","Vietnamese New Year","VN",1995 +"1995-02-01","The second day of Tet Holiday","VN",1995 +"1995-02-02","The third day of Tet Holiday","VN",1995 +"1995-02-03","The forth day of Tet Holiday","VN",1995 +"1995-02-04","The fifth day of Tet Holiday","VN",1995 +"1995-04-30","Liberation Day/Reunification Day","VN",1995 +"1995-05-01","International Labor Day","VN",1995 +"1995-05-02","Liberation Day/Reunification Day (Observed)","VN",1995 +"1995-09-02","Independence Day","VN",1995 +"1995-09-04","Independence Day (Observed)","VN",1995 +"1996-01-01","International New Year's Day","VN",1996 +"1996-02-18","Vietnamese New Year's Eve","VN",1996 +"1996-02-19","Vietnamese New Year","VN",1996 +"1996-02-20","The second day of Tet Holiday","VN",1996 +"1996-02-21","The third day of Tet Holiday","VN",1996 +"1996-02-22","The forth day of Tet Holiday","VN",1996 +"1996-02-23","The fifth day of Tet Holiday","VN",1996 +"1996-04-30","Liberation Day/Reunification Day","VN",1996 +"1996-05-01","International Labor Day","VN",1996 +"1996-09-02","Independence Day","VN",1996 +"1997-01-01","International New Year's Day","VN",1997 +"1997-02-06","Vietnamese New Year's Eve","VN",1997 +"1997-02-07","Vietnamese New Year","VN",1997 +"1997-02-08","The second day of Tet Holiday","VN",1997 +"1997-02-09","The third day of Tet Holiday","VN",1997 +"1997-02-10","The forth day of Tet Holiday","VN",1997 +"1997-02-11","The fifth day of Tet Holiday","VN",1997 +"1997-04-30","Liberation Day/Reunification Day","VN",1997 +"1997-05-01","International Labor Day","VN",1997 +"1997-09-02","Independence Day","VN",1997 +"1998-01-01","International New Year's Day","VN",1998 +"1998-01-27","Vietnamese New Year's Eve","VN",1998 +"1998-01-28","Vietnamese New Year","VN",1998 +"1998-01-29","The second day of Tet Holiday","VN",1998 +"1998-01-30","The third day of Tet Holiday","VN",1998 +"1998-01-31","The forth day of Tet Holiday","VN",1998 +"1998-02-01","The fifth day of Tet Holiday","VN",1998 +"1998-04-30","Liberation Day/Reunification Day","VN",1998 +"1998-05-01","International Labor Day","VN",1998 +"1998-09-02","Independence Day","VN",1998 +"1999-01-01","International New Year's Day","VN",1999 +"1999-02-15","Vietnamese New Year's Eve","VN",1999 +"1999-02-16","Vietnamese New Year","VN",1999 +"1999-02-17","The second day of Tet Holiday","VN",1999 +"1999-02-18","The third day of Tet Holiday","VN",1999 +"1999-02-19","The forth day of Tet Holiday","VN",1999 +"1999-02-20","The fifth day of Tet Holiday","VN",1999 +"1999-04-30","Liberation Day/Reunification Day","VN",1999 +"1999-05-01","International Labor Day","VN",1999 +"1999-05-03","International Labor Day (Observed)","VN",1999 +"1999-09-02","Independence Day","VN",1999 +"2000-01-01","International New Year's Day","VN",2000 +"2000-01-03","International New Year's Day (Observed)","VN",2000 +"2000-02-04","Vietnamese New Year's Eve","VN",2000 +"2000-02-05","Vietnamese New Year","VN",2000 +"2000-02-06","The second day of Tet Holiday","VN",2000 +"2000-02-07","The third day of Tet Holiday","VN",2000 +"2000-02-08","The forth day of Tet Holiday","VN",2000 +"2000-02-09","The fifth day of Tet Holiday","VN",2000 +"2000-04-30","Liberation Day/Reunification Day","VN",2000 +"2000-05-01","International Labor Day","VN",2000 +"2000-05-02","Liberation Day/Reunification Day (Observed)","VN",2000 +"2000-09-02","Independence Day","VN",2000 +"2000-09-04","Independence Day (Observed)","VN",2000 +"2001-01-01","International New Year's Day","VN",2001 +"2001-01-23","Vietnamese New Year's Eve","VN",2001 +"2001-01-24","Vietnamese New Year","VN",2001 +"2001-01-25","The second day of Tet Holiday","VN",2001 +"2001-01-26","The third day of Tet Holiday","VN",2001 +"2001-01-27","The forth day of Tet Holiday","VN",2001 +"2001-01-28","The fifth day of Tet Holiday","VN",2001 +"2001-04-30","Liberation Day/Reunification Day","VN",2001 +"2001-05-01","International Labor Day","VN",2001 +"2001-09-02","Independence Day","VN",2001 +"2001-09-03","Independence Day (Observed)","VN",2001 +"2002-01-01","International New Year's Day","VN",2002 +"2002-02-11","Vietnamese New Year's Eve","VN",2002 +"2002-02-12","Vietnamese New Year","VN",2002 +"2002-02-13","The second day of Tet Holiday","VN",2002 +"2002-02-14","The third day of Tet Holiday","VN",2002 +"2002-02-15","The forth day of Tet Holiday","VN",2002 +"2002-02-16","The fifth day of Tet Holiday","VN",2002 +"2002-04-30","Liberation Day/Reunification Day","VN",2002 +"2002-05-01","International Labor Day","VN",2002 +"2002-09-02","Independence Day","VN",2002 +"2003-01-01","International New Year's Day","VN",2003 +"2003-01-31","Vietnamese New Year's Eve","VN",2003 +"2003-02-01","Vietnamese New Year","VN",2003 +"2003-02-02","The second day of Tet Holiday","VN",2003 +"2003-02-03","The third day of Tet Holiday","VN",2003 +"2003-02-04","The forth day of Tet Holiday","VN",2003 +"2003-02-05","The fifth day of Tet Holiday","VN",2003 +"2003-04-30","Liberation Day/Reunification Day","VN",2003 +"2003-05-01","International Labor Day","VN",2003 +"2003-09-02","Independence Day","VN",2003 +"2004-01-01","International New Year's Day","VN",2004 +"2004-01-21","Vietnamese New Year's Eve","VN",2004 +"2004-01-22","Vietnamese New Year","VN",2004 +"2004-01-23","The second day of Tet Holiday","VN",2004 +"2004-01-24","The third day of Tet Holiday","VN",2004 +"2004-01-25","The forth day of Tet Holiday","VN",2004 +"2004-01-26","The fifth day of Tet Holiday","VN",2004 +"2004-04-30","Liberation Day/Reunification Day","VN",2004 +"2004-05-01","International Labor Day","VN",2004 +"2004-05-03","International Labor Day (Observed)","VN",2004 +"2004-09-02","Independence Day","VN",2004 +"2005-01-01","International New Year's Day","VN",2005 +"2005-01-03","International New Year's Day (Observed)","VN",2005 +"2005-02-08","Vietnamese New Year's Eve","VN",2005 +"2005-02-09","Vietnamese New Year","VN",2005 +"2005-02-10","The second day of Tet Holiday","VN",2005 +"2005-02-11","The third day of Tet Holiday","VN",2005 +"2005-02-12","The forth day of Tet Holiday","VN",2005 +"2005-02-13","The fifth day of Tet Holiday","VN",2005 +"2005-04-30","Liberation Day/Reunification Day","VN",2005 +"2005-05-01","International Labor Day","VN",2005 +"2005-05-02","Liberation Day/Reunification Day (Observed)","VN",2005 +"2005-05-03","International Labor Day (Observed)","VN",2005 +"2005-09-02","Independence Day","VN",2005 +"2006-01-01","International New Year's Day","VN",2006 +"2006-01-02","International New Year's Day (Observed)","VN",2006 +"2006-01-28","Vietnamese New Year's Eve","VN",2006 +"2006-01-29","Vietnamese New Year","VN",2006 +"2006-01-30","The second day of Tet Holiday","VN",2006 +"2006-01-31","The third day of Tet Holiday","VN",2006 +"2006-02-01","The forth day of Tet Holiday","VN",2006 +"2006-02-02","The fifth day of Tet Holiday","VN",2006 +"2006-04-30","Liberation Day/Reunification Day","VN",2006 +"2006-05-01","International Labor Day","VN",2006 +"2006-05-02","Liberation Day/Reunification Day (Observed)","VN",2006 +"2006-09-02","Independence Day","VN",2006 +"2006-09-04","Independence Day (Observed)","VN",2006 +"2007-01-01","International New Year's Day","VN",2007 +"2007-02-17","Vietnamese New Year's Eve","VN",2007 +"2007-02-18","Vietnamese New Year","VN",2007 +"2007-02-19","The second day of Tet Holiday","VN",2007 +"2007-02-20","The third day of Tet Holiday","VN",2007 +"2007-02-21","The forth day of Tet Holiday","VN",2007 +"2007-02-22","The fifth day of Tet Holiday","VN",2007 +"2007-04-26","Hung Kings Commemoration Day","VN",2007 +"2007-04-30","Liberation Day/Reunification Day","VN",2007 +"2007-05-01","International Labor Day","VN",2007 +"2007-09-02","Independence Day","VN",2007 +"2007-09-03","Independence Day (Observed)","VN",2007 +"2008-01-01","International New Year's Day","VN",2008 +"2008-02-06","Vietnamese New Year's Eve","VN",2008 +"2008-02-07","Vietnamese New Year","VN",2008 +"2008-02-08","The second day of Tet Holiday","VN",2008 +"2008-02-09","The third day of Tet Holiday","VN",2008 +"2008-02-10","The forth day of Tet Holiday","VN",2008 +"2008-02-11","The fifth day of Tet Holiday","VN",2008 +"2008-04-15","Hung Kings Commemoration Day","VN",2008 +"2008-04-30","Liberation Day/Reunification Day","VN",2008 +"2008-05-01","International Labor Day","VN",2008 +"2008-09-02","Independence Day","VN",2008 +"2009-01-01","International New Year's Day","VN",2009 +"2009-01-25","Vietnamese New Year's Eve","VN",2009 +"2009-01-26","Vietnamese New Year","VN",2009 +"2009-01-27","The second day of Tet Holiday","VN",2009 +"2009-01-28","The third day of Tet Holiday","VN",2009 +"2009-01-29","The forth day of Tet Holiday","VN",2009 +"2009-01-30","The fifth day of Tet Holiday","VN",2009 +"2009-04-05","Hung Kings Commemoration Day","VN",2009 +"2009-04-06","Hung Kings Commemoration Day (Observed)","VN",2009 +"2009-04-30","Liberation Day/Reunification Day","VN",2009 +"2009-05-01","International Labor Day","VN",2009 +"2009-09-02","Independence Day","VN",2009 +"2010-01-01","International New Year's Day","VN",2010 +"2010-02-13","Vietnamese New Year's Eve","VN",2010 +"2010-02-14","Vietnamese New Year","VN",2010 +"2010-02-15","The second day of Tet Holiday","VN",2010 +"2010-02-16","The third day of Tet Holiday","VN",2010 +"2010-02-17","The forth day of Tet Holiday","VN",2010 +"2010-02-18","The fifth day of Tet Holiday","VN",2010 +"2010-04-23","Hung Kings Commemoration Day","VN",2010 +"2010-04-30","Liberation Day/Reunification Day","VN",2010 +"2010-05-01","International Labor Day","VN",2010 +"2010-05-03","International Labor Day (Observed)","VN",2010 +"2010-09-02","Independence Day","VN",2010 +"2011-01-01","International New Year's Day","VN",2011 +"2011-01-03","International New Year's Day (Observed)","VN",2011 +"2011-02-02","Vietnamese New Year's Eve","VN",2011 +"2011-02-03","Vietnamese New Year","VN",2011 +"2011-02-04","The second day of Tet Holiday","VN",2011 +"2011-02-05","The third day of Tet Holiday","VN",2011 +"2011-02-06","The forth day of Tet Holiday","VN",2011 +"2011-02-07","The fifth day of Tet Holiday","VN",2011 +"2011-04-12","Hung Kings Commemoration Day","VN",2011 +"2011-04-30","Liberation Day/Reunification Day","VN",2011 +"2011-05-01","International Labor Day","VN",2011 +"2011-05-02","Liberation Day/Reunification Day (Observed)","VN",2011 +"2011-05-03","International Labor Day (Observed)","VN",2011 +"2011-09-02","Independence Day","VN",2011 +"2012-01-01","International New Year's Day","VN",2012 +"2012-01-02","International New Year's Day (Observed)","VN",2012 +"2012-01-22","Vietnamese New Year's Eve","VN",2012 +"2012-01-23","Vietnamese New Year","VN",2012 +"2012-01-24","The second day of Tet Holiday","VN",2012 +"2012-01-25","The third day of Tet Holiday","VN",2012 +"2012-01-26","The forth day of Tet Holiday","VN",2012 +"2012-01-27","The fifth day of Tet Holiday","VN",2012 +"2012-03-31","Hung Kings Commemoration Day","VN",2012 +"2012-04-02","Hung Kings Commemoration Day (Observed)","VN",2012 +"2012-04-30","Liberation Day/Reunification Day","VN",2012 +"2012-05-01","International Labor Day","VN",2012 +"2012-09-02","Independence Day","VN",2012 +"2012-09-03","Independence Day (Observed)","VN",2012 +"2013-01-01","International New Year's Day","VN",2013 +"2013-02-09","Vietnamese New Year's Eve","VN",2013 +"2013-02-10","Vietnamese New Year","VN",2013 +"2013-02-11","The second day of Tet Holiday","VN",2013 +"2013-02-12","The third day of Tet Holiday","VN",2013 +"2013-02-13","The forth day of Tet Holiday","VN",2013 +"2013-02-14","The fifth day of Tet Holiday","VN",2013 +"2013-04-19","Hung Kings Commemoration Day","VN",2013 +"2013-04-30","Liberation Day/Reunification Day","VN",2013 +"2013-05-01","International Labor Day","VN",2013 +"2013-09-02","Independence Day","VN",2013 +"2014-01-01","International New Year's Day","VN",2014 +"2014-01-30","Vietnamese New Year's Eve","VN",2014 +"2014-01-31","Vietnamese New Year","VN",2014 +"2014-02-01","The second day of Tet Holiday","VN",2014 +"2014-02-02","The third day of Tet Holiday","VN",2014 +"2014-02-03","The forth day of Tet Holiday","VN",2014 +"2014-02-04","The fifth day of Tet Holiday","VN",2014 +"2014-04-09","Hung Kings Commemoration Day","VN",2014 +"2014-04-30","Liberation Day/Reunification Day","VN",2014 +"2014-05-01","International Labor Day","VN",2014 +"2014-09-02","Independence Day","VN",2014 +"2015-01-01","International New Year's Day","VN",2015 +"2015-02-18","Vietnamese New Year's Eve","VN",2015 +"2015-02-19","Vietnamese New Year","VN",2015 +"2015-02-20","The second day of Tet Holiday","VN",2015 +"2015-02-21","The third day of Tet Holiday","VN",2015 +"2015-02-22","The forth day of Tet Holiday","VN",2015 +"2015-02-23","The fifth day of Tet Holiday","VN",2015 +"2015-04-28","Hung Kings Commemoration Day","VN",2015 +"2015-04-30","Liberation Day/Reunification Day","VN",2015 +"2015-05-01","International Labor Day","VN",2015 +"2015-09-02","Independence Day","VN",2015 +"2016-01-01","International New Year's Day","VN",2016 +"2016-02-07","Vietnamese New Year's Eve","VN",2016 +"2016-02-08","Vietnamese New Year","VN",2016 +"2016-02-09","The second day of Tet Holiday","VN",2016 +"2016-02-10","The third day of Tet Holiday","VN",2016 +"2016-02-11","The forth day of Tet Holiday","VN",2016 +"2016-02-12","The fifth day of Tet Holiday","VN",2016 +"2016-04-16","Hung Kings Commemoration Day","VN",2016 +"2016-04-18","Hung Kings Commemoration Day (Observed)","VN",2016 +"2016-04-30","Liberation Day/Reunification Day","VN",2016 +"2016-05-01","International Labor Day","VN",2016 +"2016-05-02","Liberation Day/Reunification Day (Observed)","VN",2016 +"2016-05-03","International Labor Day (Observed)","VN",2016 +"2016-09-02","Independence Day","VN",2016 +"2017-01-01","International New Year's Day","VN",2017 +"2017-01-02","International New Year's Day (Observed)","VN",2017 +"2017-01-27","Vietnamese New Year's Eve","VN",2017 +"2017-01-28","Vietnamese New Year","VN",2017 +"2017-01-29","The second day of Tet Holiday","VN",2017 +"2017-01-30","The third day of Tet Holiday","VN",2017 +"2017-01-31","The forth day of Tet Holiday","VN",2017 +"2017-02-01","The fifth day of Tet Holiday","VN",2017 +"2017-04-06","Hung Kings Commemoration Day","VN",2017 +"2017-04-30","Liberation Day/Reunification Day","VN",2017 +"2017-05-01","International Labor Day","VN",2017 +"2017-05-02","Liberation Day/Reunification Day (Observed)","VN",2017 +"2017-09-02","Independence Day","VN",2017 +"2017-09-04","Independence Day (Observed)","VN",2017 +"2018-01-01","International New Year's Day","VN",2018 +"2018-02-15","Vietnamese New Year's Eve","VN",2018 +"2018-02-16","Vietnamese New Year","VN",2018 +"2018-02-17","The second day of Tet Holiday","VN",2018 +"2018-02-18","The third day of Tet Holiday","VN",2018 +"2018-02-19","The forth day of Tet Holiday","VN",2018 +"2018-02-20","The fifth day of Tet Holiday","VN",2018 +"2018-04-25","Hung Kings Commemoration Day","VN",2018 +"2018-04-30","Liberation Day/Reunification Day","VN",2018 +"2018-05-01","International Labor Day","VN",2018 +"2018-09-02","Independence Day","VN",2018 +"2018-09-03","Independence Day (Observed)","VN",2018 +"2019-01-01","International New Year's Day","VN",2019 +"2019-02-04","Vietnamese New Year's Eve","VN",2019 +"2019-02-05","Vietnamese New Year","VN",2019 +"2019-02-06","The second day of Tet Holiday","VN",2019 +"2019-02-07","The third day of Tet Holiday","VN",2019 +"2019-02-08","The forth day of Tet Holiday","VN",2019 +"2019-02-09","The fifth day of Tet Holiday","VN",2019 +"2019-04-14","Hung Kings Commemoration Day","VN",2019 +"2019-04-15","Hung Kings Commemoration Day (Observed)","VN",2019 +"2019-04-30","Liberation Day/Reunification Day","VN",2019 +"2019-05-01","International Labor Day","VN",2019 +"2019-09-02","Independence Day","VN",2019 +"2020-01-01","International New Year's Day","VN",2020 +"2020-01-24","Vietnamese New Year's Eve","VN",2020 +"2020-01-25","Vietnamese New Year","VN",2020 +"2020-01-26","The second day of Tet Holiday","VN",2020 +"2020-01-27","The third day of Tet Holiday","VN",2020 +"2020-01-28","The forth day of Tet Holiday","VN",2020 +"2020-01-29","The fifth day of Tet Holiday","VN",2020 +"2020-04-02","Hung Kings Commemoration Day","VN",2020 +"2020-04-30","Liberation Day/Reunification Day","VN",2020 +"2020-05-01","International Labor Day","VN",2020 +"2020-09-02","Independence Day","VN",2020 +"2021-01-01","International New Year's Day","VN",2021 +"2021-02-11","Vietnamese New Year's Eve","VN",2021 +"2021-02-12","Vietnamese New Year","VN",2021 +"2021-02-13","The second day of Tet Holiday","VN",2021 +"2021-02-14","The third day of Tet Holiday","VN",2021 +"2021-02-15","The forth day of Tet Holiday","VN",2021 +"2021-02-16","The fifth day of Tet Holiday","VN",2021 +"2021-04-21","Hung Kings Commemoration Day","VN",2021 +"2021-04-30","Liberation Day/Reunification Day","VN",2021 +"2021-05-01","International Labor Day","VN",2021 +"2021-05-03","International Labor Day (Observed)","VN",2021 +"2021-09-02","Independence Day","VN",2021 +"2022-01-01","International New Year's Day","VN",2022 +"2022-01-03","International New Year's Day (Observed)","VN",2022 +"2022-01-31","Vietnamese New Year's Eve","VN",2022 +"2022-02-01","Vietnamese New Year","VN",2022 +"2022-02-02","The second day of Tet Holiday","VN",2022 +"2022-02-03","The third day of Tet Holiday","VN",2022 +"2022-02-04","The forth day of Tet Holiday","VN",2022 +"2022-02-05","The fifth day of Tet Holiday","VN",2022 +"2022-04-10","Hung Kings Commemoration Day","VN",2022 +"2022-04-11","Hung Kings Commemoration Day (Observed)","VN",2022 +"2022-04-30","Liberation Day/Reunification Day","VN",2022 +"2022-05-01","International Labor Day","VN",2022 +"2022-05-02","Liberation Day/Reunification Day (Observed)","VN",2022 +"2022-05-03","International Labor Day (Observed)","VN",2022 +"2022-09-02","Independence Day","VN",2022 +"2023-01-01","International New Year's Day","VN",2023 +"2023-01-02","International New Year's Day (Observed)","VN",2023 +"2023-01-21","Vietnamese New Year's Eve","VN",2023 +"2023-01-22","Vietnamese New Year","VN",2023 +"2023-01-23","The second day of Tet Holiday","VN",2023 +"2023-01-24","The third day of Tet Holiday","VN",2023 +"2023-01-25","The forth day of Tet Holiday","VN",2023 +"2023-01-26","The fifth day of Tet Holiday","VN",2023 +"2023-04-29","Hung Kings Commemoration Day","VN",2023 +"2023-04-30","Liberation Day/Reunification Day","VN",2023 +"2023-05-01","International Labor Day","VN",2023 +"2023-05-02","Hung Kings Commemoration Day (Observed)","VN",2023 +"2023-05-03","Liberation Day/Reunification Day (Observed)","VN",2023 +"2023-09-02","Independence Day","VN",2023 +"2023-09-04","Independence Day (Observed)","VN",2023 +"2024-01-01","International New Year's Day","VN",2024 +"2024-02-09","Vietnamese New Year's Eve","VN",2024 +"2024-02-10","Vietnamese New Year","VN",2024 +"2024-02-11","The second day of Tet Holiday","VN",2024 +"2024-02-12","The third day of Tet Holiday","VN",2024 +"2024-02-13","The forth day of Tet Holiday","VN",2024 +"2024-02-14","The fifth day of Tet Holiday","VN",2024 +"2024-04-18","Hung Kings Commemoration Day","VN",2024 +"2024-04-30","Liberation Day/Reunification Day","VN",2024 +"2024-05-01","International Labor Day","VN",2024 +"2024-09-02","Independence Day","VN",2024 +"2025-01-01","International New Year's Day","VN",2025 +"2025-01-28","Vietnamese New Year's Eve","VN",2025 +"2025-01-29","Vietnamese New Year","VN",2025 +"2025-01-30","The second day of Tet Holiday","VN",2025 +"2025-01-31","The third day of Tet Holiday","VN",2025 +"2025-02-01","The forth day of Tet Holiday","VN",2025 +"2025-02-02","The fifth day of Tet Holiday","VN",2025 +"2025-04-07","Hung Kings Commemoration Day","VN",2025 +"2025-04-30","Liberation Day/Reunification Day","VN",2025 +"2025-05-01","International Labor Day","VN",2025 +"2025-09-02","Independence Day","VN",2025 +"2026-01-01","International New Year's Day","VN",2026 +"2026-02-16","Vietnamese New Year's Eve","VN",2026 +"2026-02-17","Vietnamese New Year","VN",2026 +"2026-02-18","The second day of Tet Holiday","VN",2026 +"2026-02-19","The third day of Tet Holiday","VN",2026 +"2026-02-20","The forth day of Tet Holiday","VN",2026 +"2026-02-21","The fifth day of Tet Holiday","VN",2026 +"2026-04-26","Hung Kings Commemoration Day","VN",2026 +"2026-04-27","Hung Kings Commemoration Day (Observed)","VN",2026 +"2026-04-30","Liberation Day/Reunification Day","VN",2026 +"2026-05-01","International Labor Day","VN",2026 +"2026-09-02","Independence Day","VN",2026 +"2027-01-01","International New Year's Day","VN",2027 +"2027-02-05","Vietnamese New Year's Eve","VN",2027 +"2027-02-06","Vietnamese New Year","VN",2027 +"2027-02-07","The second day of Tet Holiday","VN",2027 +"2027-02-08","The third day of Tet Holiday","VN",2027 +"2027-02-09","The forth day of Tet Holiday","VN",2027 +"2027-02-10","The fifth day of Tet Holiday","VN",2027 +"2027-04-16","Hung Kings Commemoration Day","VN",2027 +"2027-04-30","Liberation Day/Reunification Day","VN",2027 +"2027-05-01","International Labor Day","VN",2027 +"2027-05-03","International Labor Day (Observed)","VN",2027 +"2027-09-02","Independence Day","VN",2027 +"2028-01-01","International New Year's Day","VN",2028 +"2028-01-03","International New Year's Day (Observed)","VN",2028 +"2028-01-25","Vietnamese New Year's Eve","VN",2028 +"2028-01-26","Vietnamese New Year","VN",2028 +"2028-01-27","The second day of Tet Holiday","VN",2028 +"2028-01-28","The third day of Tet Holiday","VN",2028 +"2028-01-29","The forth day of Tet Holiday","VN",2028 +"2028-01-30","The fifth day of Tet Holiday","VN",2028 +"2028-04-04","Hung Kings Commemoration Day","VN",2028 +"2028-04-30","Liberation Day/Reunification Day","VN",2028 +"2028-05-01","International Labor Day","VN",2028 +"2028-05-02","Liberation Day/Reunification Day (Observed)","VN",2028 +"2028-09-02","Independence Day","VN",2028 +"2028-09-04","Independence Day (Observed)","VN",2028 +"2029-01-01","International New Year's Day","VN",2029 +"2029-02-12","Vietnamese New Year's Eve","VN",2029 +"2029-02-13","Vietnamese New Year","VN",2029 +"2029-02-14","The second day of Tet Holiday","VN",2029 +"2029-02-15","The third day of Tet Holiday","VN",2029 +"2029-02-16","The forth day of Tet Holiday","VN",2029 +"2029-02-17","The fifth day of Tet Holiday","VN",2029 +"2029-04-23","Hung Kings Commemoration Day","VN",2029 +"2029-04-30","Liberation Day/Reunification Day","VN",2029 +"2029-05-01","International Labor Day","VN",2029 +"2029-09-02","Independence Day","VN",2029 +"2029-09-03","Independence Day (Observed)","VN",2029 +"2030-01-01","International New Year's Day","VN",2030 +"2030-02-02","Vietnamese New Year's Eve","VN",2030 +"2030-02-03","Vietnamese New Year","VN",2030 +"2030-02-04","The second day of Tet Holiday","VN",2030 +"2030-02-05","The third day of Tet Holiday","VN",2030 +"2030-02-06","The forth day of Tet Holiday","VN",2030 +"2030-02-07","The fifth day of Tet Holiday","VN",2030 +"2030-04-12","Hung Kings Commemoration Day","VN",2030 +"2030-04-30","Liberation Day/Reunification Day","VN",2030 +"2030-05-01","International Labor Day","VN",2030 +"2030-09-02","Independence Day","VN",2030 +"2031-01-01","International New Year's Day","VN",2031 +"2031-01-22","Vietnamese New Year's Eve","VN",2031 +"2031-01-23","Vietnamese New Year","VN",2031 +"2031-01-24","The second day of Tet Holiday","VN",2031 +"2031-01-25","The third day of Tet Holiday","VN",2031 +"2031-01-26","The forth day of Tet Holiday","VN",2031 +"2031-01-27","The fifth day of Tet Holiday","VN",2031 +"2031-04-01","Hung Kings Commemoration Day","VN",2031 +"2031-04-30","Liberation Day/Reunification Day","VN",2031 +"2031-05-01","International Labor Day","VN",2031 +"2031-09-02","Independence Day","VN",2031 +"2032-01-01","International New Year's Day","VN",2032 +"2032-02-10","Vietnamese New Year's Eve","VN",2032 +"2032-02-11","Vietnamese New Year","VN",2032 +"2032-02-12","The second day of Tet Holiday","VN",2032 +"2032-02-13","The third day of Tet Holiday","VN",2032 +"2032-02-14","The forth day of Tet Holiday","VN",2032 +"2032-02-15","The fifth day of Tet Holiday","VN",2032 +"2032-04-19","Hung Kings Commemoration Day","VN",2032 +"2032-04-30","Liberation Day/Reunification Day","VN",2032 +"2032-05-01","International Labor Day","VN",2032 +"2032-05-03","International Labor Day (Observed)","VN",2032 +"2032-09-02","Independence Day","VN",2032 +"2033-01-01","International New Year's Day","VN",2033 +"2033-01-03","International New Year's Day (Observed)","VN",2033 +"2033-01-30","Vietnamese New Year's Eve","VN",2033 +"2033-01-31","Vietnamese New Year","VN",2033 +"2033-02-01","The second day of Tet Holiday","VN",2033 +"2033-02-02","The third day of Tet Holiday","VN",2033 +"2033-02-03","The forth day of Tet Holiday","VN",2033 +"2033-02-04","The fifth day of Tet Holiday","VN",2033 +"2033-04-09","Hung Kings Commemoration Day","VN",2033 +"2033-04-11","Hung Kings Commemoration Day (Observed)","VN",2033 +"2033-04-30","Liberation Day/Reunification Day","VN",2033 +"2033-05-01","International Labor Day","VN",2033 +"2033-05-02","Liberation Day/Reunification Day (Observed)","VN",2033 +"2033-05-03","International Labor Day (Observed)","VN",2033 +"2033-09-02","Independence Day","VN",2033 +"2034-01-01","International New Year's Day","VN",2034 +"2034-01-02","International New Year's Day (Observed)","VN",2034 +"2034-02-18","Vietnamese New Year's Eve","VN",2034 +"2034-02-19","Vietnamese New Year","VN",2034 +"2034-02-20","The second day of Tet Holiday","VN",2034 +"2034-02-21","The third day of Tet Holiday","VN",2034 +"2034-02-22","The forth day of Tet Holiday","VN",2034 +"2034-02-23","The fifth day of Tet Holiday","VN",2034 +"2034-04-28","Hung Kings Commemoration Day","VN",2034 +"2034-04-30","Liberation Day/Reunification Day","VN",2034 +"2034-05-01","International Labor Day","VN",2034 +"2034-05-02","Liberation Day/Reunification Day (Observed)","VN",2034 +"2034-09-02","Independence Day","VN",2034 +"2034-09-04","Independence Day (Observed)","VN",2034 +"2035-01-01","International New Year's Day","VN",2035 +"2035-02-07","Vietnamese New Year's Eve","VN",2035 +"2035-02-08","Vietnamese New Year","VN",2035 +"2035-02-09","The second day of Tet Holiday","VN",2035 +"2035-02-10","The third day of Tet Holiday","VN",2035 +"2035-02-11","The forth day of Tet Holiday","VN",2035 +"2035-02-12","The fifth day of Tet Holiday","VN",2035 +"2035-04-17","Hung Kings Commemoration Day","VN",2035 +"2035-04-30","Liberation Day/Reunification Day","VN",2035 +"2035-05-01","International Labor Day","VN",2035 +"2035-09-02","Independence Day","VN",2035 +"2035-09-03","Independence Day (Observed)","VN",2035 +"2036-01-01","International New Year's Day","VN",2036 +"2036-01-27","Vietnamese New Year's Eve","VN",2036 +"2036-01-28","Vietnamese New Year","VN",2036 +"2036-01-29","The second day of Tet Holiday","VN",2036 +"2036-01-30","The third day of Tet Holiday","VN",2036 +"2036-01-31","The forth day of Tet Holiday","VN",2036 +"2036-02-01","The fifth day of Tet Holiday","VN",2036 +"2036-04-06","Hung Kings Commemoration Day","VN",2036 +"2036-04-07","Hung Kings Commemoration Day (Observed)","VN",2036 +"2036-04-30","Liberation Day/Reunification Day","VN",2036 +"2036-05-01","International Labor Day","VN",2036 +"2036-09-02","Independence Day","VN",2036 +"2037-01-01","International New Year's Day","VN",2037 +"2037-02-14","Vietnamese New Year's Eve","VN",2037 +"2037-02-15","Vietnamese New Year","VN",2037 +"2037-02-16","The second day of Tet Holiday","VN",2037 +"2037-02-17","The third day of Tet Holiday","VN",2037 +"2037-02-18","The forth day of Tet Holiday","VN",2037 +"2037-02-19","The fifth day of Tet Holiday","VN",2037 +"2037-04-25","Hung Kings Commemoration Day","VN",2037 +"2037-04-27","Hung Kings Commemoration Day (Observed)","VN",2037 +"2037-04-30","Liberation Day/Reunification Day","VN",2037 +"2037-05-01","International Labor Day","VN",2037 +"2037-09-02","Independence Day","VN",2037 +"2038-01-01","International New Year's Day","VN",2038 +"2038-02-03","Vietnamese New Year's Eve","VN",2038 +"2038-02-04","Vietnamese New Year","VN",2038 +"2038-02-05","The second day of Tet Holiday","VN",2038 +"2038-02-06","The third day of Tet Holiday","VN",2038 +"2038-02-07","The forth day of Tet Holiday","VN",2038 +"2038-02-08","The fifth day of Tet Holiday","VN",2038 +"2038-04-14","Hung Kings Commemoration Day","VN",2038 +"2038-04-30","Liberation Day/Reunification Day","VN",2038 +"2038-05-01","International Labor Day","VN",2038 +"2038-05-03","International Labor Day (Observed)","VN",2038 +"2038-09-02","Independence Day","VN",2038 +"2039-01-01","International New Year's Day","VN",2039 +"2039-01-03","International New Year's Day (Observed)","VN",2039 +"2039-01-23","Vietnamese New Year's Eve","VN",2039 +"2039-01-24","Vietnamese New Year","VN",2039 +"2039-01-25","The second day of Tet Holiday","VN",2039 +"2039-01-26","The third day of Tet Holiday","VN",2039 +"2039-01-27","The forth day of Tet Holiday","VN",2039 +"2039-01-28","The fifth day of Tet Holiday","VN",2039 +"2039-04-03","Hung Kings Commemoration Day","VN",2039 +"2039-04-04","Hung Kings Commemoration Day (Observed)","VN",2039 +"2039-04-30","Liberation Day/Reunification Day","VN",2039 +"2039-05-01","International Labor Day","VN",2039 +"2039-05-02","Liberation Day/Reunification Day (Observed)","VN",2039 +"2039-05-03","International Labor Day (Observed)","VN",2039 +"2039-09-02","Independence Day","VN",2039 +"2040-01-01","International New Year's Day","VN",2040 +"2040-01-02","International New Year's Day (Observed)","VN",2040 +"2040-02-11","Vietnamese New Year's Eve","VN",2040 +"2040-02-12","Vietnamese New Year","VN",2040 +"2040-02-13","The second day of Tet Holiday","VN",2040 +"2040-02-14","The third day of Tet Holiday","VN",2040 +"2040-02-15","The forth day of Tet Holiday","VN",2040 +"2040-02-16","The fifth day of Tet Holiday","VN",2040 +"2040-04-20","Hung Kings Commemoration Day","VN",2040 +"2040-04-30","Liberation Day/Reunification Day","VN",2040 +"2040-05-01","International Labor Day","VN",2040 +"2040-09-02","Independence Day","VN",2040 +"2040-09-03","Independence Day (Observed)","VN",2040 +"2041-01-01","International New Year's Day","VN",2041 +"2041-01-31","Vietnamese New Year's Eve","VN",2041 +"2041-02-01","Vietnamese New Year","VN",2041 +"2041-02-02","The second day of Tet Holiday","VN",2041 +"2041-02-03","The third day of Tet Holiday","VN",2041 +"2041-02-04","The forth day of Tet Holiday","VN",2041 +"2041-02-05","The fifth day of Tet Holiday","VN",2041 +"2041-04-10","Hung Kings Commemoration Day","VN",2041 +"2041-04-30","Liberation Day/Reunification Day","VN",2041 +"2041-05-01","International Labor Day","VN",2041 +"2041-09-02","Independence Day","VN",2041 +"2042-01-01","International New Year's Day","VN",2042 +"2042-01-21","Vietnamese New Year's Eve","VN",2042 +"2042-01-22","Vietnamese New Year","VN",2042 +"2042-01-23","The second day of Tet Holiday","VN",2042 +"2042-01-24","The third day of Tet Holiday","VN",2042 +"2042-01-25","The forth day of Tet Holiday","VN",2042 +"2042-01-26","The fifth day of Tet Holiday","VN",2042 +"2042-04-29","Hung Kings Commemoration Day","VN",2042 +"2042-04-30","Liberation Day/Reunification Day","VN",2042 +"2042-05-01","International Labor Day","VN",2042 +"2042-09-02","Independence Day","VN",2042 +"2043-01-01","International New Year's Day","VN",2043 +"2043-02-09","Vietnamese New Year's Eve","VN",2043 +"2043-02-10","Vietnamese New Year","VN",2043 +"2043-02-11","The second day of Tet Holiday","VN",2043 +"2043-02-12","The third day of Tet Holiday","VN",2043 +"2043-02-13","The forth day of Tet Holiday","VN",2043 +"2043-02-14","The fifth day of Tet Holiday","VN",2043 +"2043-04-19","Hung Kings Commemoration Day","VN",2043 +"2043-04-20","Hung Kings Commemoration Day (Observed)","VN",2043 +"2043-04-30","Liberation Day/Reunification Day","VN",2043 +"2043-05-01","International Labor Day","VN",2043 +"2043-09-02","Independence Day","VN",2043 +"2044-01-01","International New Year's Day","VN",2044 +"2044-01-29","Vietnamese New Year's Eve","VN",2044 +"2044-01-30","Vietnamese New Year","VN",2044 +"2044-01-31","The second day of Tet Holiday","VN",2044 +"2044-02-01","The third day of Tet Holiday","VN",2044 +"2044-02-02","The forth day of Tet Holiday","VN",2044 +"2044-02-03","The fifth day of Tet Holiday","VN",2044 +"2044-04-07","Hung Kings Commemoration Day","VN",2044 +"2044-04-30","Liberation Day/Reunification Day","VN",2044 +"2044-05-01","International Labor Day","VN",2044 +"2044-05-02","Liberation Day/Reunification Day (Observed)","VN",2044 +"2044-05-03","International Labor Day (Observed)","VN",2044 +"2044-09-02","Independence Day","VN",2044 +"1995-01-01","New Year's Day","ZA",1995 +"1995-01-02","New Year's Day (Observed)","ZA",1995 +"1995-03-21","Human Rights Day","ZA",1995 +"1995-04-14","Good Friday","ZA",1995 +"1995-04-17","Family Day","ZA",1995 +"1995-04-27","Freedom Day","ZA",1995 +"1995-05-01","Workers' Day","ZA",1995 +"1995-06-16","Youth Day","ZA",1995 +"1995-08-09","National Women's Day","ZA",1995 +"1995-09-24","Heritage Day","ZA",1995 +"1995-09-25","Heritage Day (Observed)","ZA",1995 +"1995-12-16","Day of Reconciliation","ZA",1995 +"1995-12-25","Christmas Day","ZA",1995 +"1995-12-26","Day of Goodwill","ZA",1995 +"1996-01-01","New Year's Day","ZA",1996 +"1996-03-21","Human Rights Day","ZA",1996 +"1996-04-05","Good Friday","ZA",1996 +"1996-04-08","Family Day","ZA",1996 +"1996-04-27","Freedom Day","ZA",1996 +"1996-05-01","Workers' Day","ZA",1996 +"1996-06-16","Youth Day","ZA",1996 +"1996-06-17","Youth Day (Observed)","ZA",1996 +"1996-08-09","National Women's Day","ZA",1996 +"1996-09-24","Heritage Day","ZA",1996 +"1996-12-16","Day of Reconciliation","ZA",1996 +"1996-12-25","Christmas Day","ZA",1996 +"1996-12-26","Day of Goodwill","ZA",1996 +"1997-01-01","New Year's Day","ZA",1997 +"1997-03-21","Human Rights Day","ZA",1997 +"1997-03-28","Good Friday","ZA",1997 +"1997-03-31","Family Day","ZA",1997 +"1997-04-27","Freedom Day","ZA",1997 +"1997-04-28","Freedom Day (Observed)","ZA",1997 +"1997-05-01","Workers' Day","ZA",1997 +"1997-06-16","Youth Day","ZA",1997 +"1997-08-09","National Women's Day","ZA",1997 +"1997-09-24","Heritage Day","ZA",1997 +"1997-12-16","Day of Reconciliation","ZA",1997 +"1997-12-25","Christmas Day","ZA",1997 +"1997-12-26","Day of Goodwill","ZA",1997 +"1998-01-01","New Year's Day","ZA",1998 +"1998-03-21","Human Rights Day","ZA",1998 +"1998-04-10","Good Friday","ZA",1998 +"1998-04-13","Family Day","ZA",1998 +"1998-04-27","Freedom Day","ZA",1998 +"1998-05-01","Workers' Day","ZA",1998 +"1998-06-16","Youth Day","ZA",1998 +"1998-08-09","National Women's Day","ZA",1998 +"1998-08-10","National Women's Day (Observed)","ZA",1998 +"1998-09-24","Heritage Day","ZA",1998 +"1998-12-16","Day of Reconciliation","ZA",1998 +"1998-12-25","Christmas Day","ZA",1998 +"1998-12-26","Day of Goodwill","ZA",1998 +"1999-01-01","New Year's Day","ZA",1999 +"1999-03-21","Human Rights Day","ZA",1999 +"1999-03-22","Human Rights Day (Observed)","ZA",1999 +"1999-04-02","Good Friday","ZA",1999 +"1999-04-05","Family Day","ZA",1999 +"1999-04-27","Freedom Day","ZA",1999 +"1999-05-01","Workers' Day","ZA",1999 +"1999-06-02","National and provincial government elections","ZA",1999 +"1999-06-16","Youth Day","ZA",1999 +"1999-08-09","National Women's Day","ZA",1999 +"1999-09-24","Heritage Day","ZA",1999 +"1999-12-16","Day of Reconciliation","ZA",1999 +"1999-12-25","Christmas Day","ZA",1999 +"1999-12-26","Day of Goodwill","ZA",1999 +"1999-12-27","Day of Goodwill (Observed)","ZA",1999 +"1999-12-31","Y2K changeover","ZA",1999 +"2000-01-01","New Year's Day","ZA",2000 +"2000-01-02","Y2K changeover","ZA",2000 +"2000-01-03","Y2K changeover (Observed)","ZA",2000 +"2000-03-21","Human Rights Day","ZA",2000 +"2000-04-21","Good Friday","ZA",2000 +"2000-04-24","Family Day","ZA",2000 +"2000-04-27","Freedom Day","ZA",2000 +"2000-05-01","Workers' Day","ZA",2000 +"2000-06-16","Youth Day","ZA",2000 +"2000-08-09","National Women's Day","ZA",2000 +"2000-09-24","Heritage Day","ZA",2000 +"2000-09-25","Heritage Day (Observed)","ZA",2000 +"2000-12-16","Day of Reconciliation","ZA",2000 +"2000-12-25","Christmas Day","ZA",2000 +"2000-12-26","Day of Goodwill","ZA",2000 +"2001-01-01","New Year's Day","ZA",2001 +"2001-03-21","Human Rights Day","ZA",2001 +"2001-04-13","Good Friday","ZA",2001 +"2001-04-16","Family Day","ZA",2001 +"2001-04-27","Freedom Day","ZA",2001 +"2001-05-01","Workers' Day","ZA",2001 +"2001-06-16","Youth Day","ZA",2001 +"2001-08-09","National Women's Day","ZA",2001 +"2001-09-24","Heritage Day","ZA",2001 +"2001-12-16","Day of Reconciliation","ZA",2001 +"2001-12-17","Day of Reconciliation (Observed)","ZA",2001 +"2001-12-25","Christmas Day","ZA",2001 +"2001-12-26","Day of Goodwill","ZA",2001 +"2002-01-01","New Year's Day","ZA",2002 +"2002-03-21","Human Rights Day","ZA",2002 +"2002-03-29","Good Friday","ZA",2002 +"2002-04-01","Family Day","ZA",2002 +"2002-04-27","Freedom Day","ZA",2002 +"2002-05-01","Workers' Day","ZA",2002 +"2002-06-16","Youth Day","ZA",2002 +"2002-06-17","Youth Day (Observed)","ZA",2002 +"2002-08-09","National Women's Day","ZA",2002 +"2002-09-24","Heritage Day","ZA",2002 +"2002-12-16","Day of Reconciliation","ZA",2002 +"2002-12-25","Christmas Day","ZA",2002 +"2002-12-26","Day of Goodwill","ZA",2002 +"2003-01-01","New Year's Day","ZA",2003 +"2003-03-21","Human Rights Day","ZA",2003 +"2003-04-18","Good Friday","ZA",2003 +"2003-04-21","Family Day","ZA",2003 +"2003-04-27","Freedom Day","ZA",2003 +"2003-04-28","Freedom Day (Observed)","ZA",2003 +"2003-05-01","Workers' Day","ZA",2003 +"2003-06-16","Youth Day","ZA",2003 +"2003-08-09","National Women's Day","ZA",2003 +"2003-09-24","Heritage Day","ZA",2003 +"2003-12-16","Day of Reconciliation","ZA",2003 +"2003-12-25","Christmas Day","ZA",2003 +"2003-12-26","Day of Goodwill","ZA",2003 +"2004-01-01","New Year's Day","ZA",2004 +"2004-03-21","Human Rights Day","ZA",2004 +"2004-03-22","Human Rights Day (Observed)","ZA",2004 +"2004-04-09","Good Friday","ZA",2004 +"2004-04-12","Family Day","ZA",2004 +"2004-04-14","National and provincial government elections","ZA",2004 +"2004-04-27","Freedom Day","ZA",2004 +"2004-05-01","Workers' Day","ZA",2004 +"2004-06-16","Youth Day","ZA",2004 +"2004-08-09","National Women's Day","ZA",2004 +"2004-09-24","Heritage Day","ZA",2004 +"2004-12-16","Day of Reconciliation","ZA",2004 +"2004-12-25","Christmas Day","ZA",2004 +"2004-12-26","Day of Goodwill","ZA",2004 +"2004-12-27","Day of Goodwill (Observed)","ZA",2004 +"2005-01-01","New Year's Day","ZA",2005 +"2005-03-21","Human Rights Day","ZA",2005 +"2005-03-25","Good Friday","ZA",2005 +"2005-03-28","Family Day","ZA",2005 +"2005-04-27","Freedom Day","ZA",2005 +"2005-05-01","Workers' Day","ZA",2005 +"2005-05-02","Workers' Day (Observed)","ZA",2005 +"2005-06-16","Youth Day","ZA",2005 +"2005-08-09","National Women's Day","ZA",2005 +"2005-09-24","Heritage Day","ZA",2005 +"2005-12-16","Day of Reconciliation","ZA",2005 +"2005-12-25","Christmas Day","ZA",2005 +"2005-12-26","Day of Goodwill","ZA",2005 +"2006-01-01","New Year's Day","ZA",2006 +"2006-01-02","New Year's Day (Observed)","ZA",2006 +"2006-03-01","Local government elections","ZA",2006 +"2006-03-21","Human Rights Day","ZA",2006 +"2006-04-14","Good Friday","ZA",2006 +"2006-04-17","Family Day","ZA",2006 +"2006-04-27","Freedom Day","ZA",2006 +"2006-05-01","Workers' Day","ZA",2006 +"2006-06-16","Youth Day","ZA",2006 +"2006-08-09","National Women's Day","ZA",2006 +"2006-09-24","Heritage Day","ZA",2006 +"2006-09-25","Heritage Day (Observed)","ZA",2006 +"2006-12-16","Day of Reconciliation","ZA",2006 +"2006-12-25","Christmas Day","ZA",2006 +"2006-12-26","Day of Goodwill","ZA",2006 +"2007-01-01","New Year's Day","ZA",2007 +"2007-03-21","Human Rights Day","ZA",2007 +"2007-04-06","Good Friday","ZA",2007 +"2007-04-09","Family Day","ZA",2007 +"2007-04-27","Freedom Day","ZA",2007 +"2007-05-01","Workers' Day","ZA",2007 +"2007-06-16","Youth Day","ZA",2007 +"2007-08-09","National Women's Day","ZA",2007 +"2007-09-24","Heritage Day","ZA",2007 +"2007-12-16","Day of Reconciliation","ZA",2007 +"2007-12-17","Day of Reconciliation (Observed)","ZA",2007 +"2007-12-25","Christmas Day","ZA",2007 +"2007-12-26","Day of Goodwill","ZA",2007 +"2008-01-01","New Year's Day","ZA",2008 +"2008-03-21","Good Friday","ZA",2008 +"2008-03-21","Human Rights Day","ZA",2008 +"2008-03-24","Family Day","ZA",2008 +"2008-04-27","Freedom Day","ZA",2008 +"2008-04-28","Freedom Day (Observed)","ZA",2008 +"2008-05-01","Workers' Day","ZA",2008 +"2008-05-02","Public holiday by presidential decree","ZA",2008 +"2008-06-16","Youth Day","ZA",2008 +"2008-08-09","National Women's Day","ZA",2008 +"2008-09-24","Heritage Day","ZA",2008 +"2008-12-16","Day of Reconciliation","ZA",2008 +"2008-12-25","Christmas Day","ZA",2008 +"2008-12-26","Day of Goodwill","ZA",2008 +"2009-01-01","New Year's Day","ZA",2009 +"2009-03-21","Human Rights Day","ZA",2009 +"2009-04-10","Good Friday","ZA",2009 +"2009-04-13","Family Day","ZA",2009 +"2009-04-22","National and provincial government elections","ZA",2009 +"2009-04-27","Freedom Day","ZA",2009 +"2009-05-01","Workers' Day","ZA",2009 +"2009-06-16","Youth Day","ZA",2009 +"2009-08-09","National Women's Day","ZA",2009 +"2009-08-10","National Women's Day (Observed)","ZA",2009 +"2009-09-24","Heritage Day","ZA",2009 +"2009-12-16","Day of Reconciliation","ZA",2009 +"2009-12-25","Christmas Day","ZA",2009 +"2009-12-26","Day of Goodwill","ZA",2009 +"2010-01-01","New Year's Day","ZA",2010 +"2010-03-21","Human Rights Day","ZA",2010 +"2010-03-22","Human Rights Day (Observed)","ZA",2010 +"2010-04-02","Good Friday","ZA",2010 +"2010-04-05","Family Day","ZA",2010 +"2010-04-27","Freedom Day","ZA",2010 +"2010-05-01","Workers' Day","ZA",2010 +"2010-06-16","Youth Day","ZA",2010 +"2010-08-09","National Women's Day","ZA",2010 +"2010-09-24","Heritage Day","ZA",2010 +"2010-12-16","Day of Reconciliation","ZA",2010 +"2010-12-25","Christmas Day","ZA",2010 +"2010-12-26","Day of Goodwill","ZA",2010 +"2010-12-27","Day of Goodwill (Observed)","ZA",2010 +"2011-01-01","New Year's Day","ZA",2011 +"2011-03-21","Human Rights Day","ZA",2011 +"2011-04-22","Good Friday","ZA",2011 +"2011-04-25","Family Day","ZA",2011 +"2011-04-27","Freedom Day","ZA",2011 +"2011-05-01","Workers' Day","ZA",2011 +"2011-05-02","Workers' Day (Observed)","ZA",2011 +"2011-05-18","Local government elections","ZA",2011 +"2011-06-16","Youth Day","ZA",2011 +"2011-08-09","National Women's Day","ZA",2011 +"2011-09-24","Heritage Day","ZA",2011 +"2011-12-16","Day of Reconciliation","ZA",2011 +"2011-12-25","Christmas Day","ZA",2011 +"2011-12-26","Day of Goodwill","ZA",2011 +"2011-12-27","Public holiday by presidential decree","ZA",2011 +"2012-01-01","New Year's Day","ZA",2012 +"2012-01-02","New Year's Day (Observed)","ZA",2012 +"2012-03-21","Human Rights Day","ZA",2012 +"2012-04-06","Good Friday","ZA",2012 +"2012-04-09","Family Day","ZA",2012 +"2012-04-27","Freedom Day","ZA",2012 +"2012-05-01","Workers' Day","ZA",2012 +"2012-06-16","Youth Day","ZA",2012 +"2012-08-09","National Women's Day","ZA",2012 +"2012-09-24","Heritage Day","ZA",2012 +"2012-12-16","Day of Reconciliation","ZA",2012 +"2012-12-17","Day of Reconciliation (Observed)","ZA",2012 +"2012-12-25","Christmas Day","ZA",2012 +"2012-12-26","Day of Goodwill","ZA",2012 +"2013-01-01","New Year's Day","ZA",2013 +"2013-03-21","Human Rights Day","ZA",2013 +"2013-03-29","Good Friday","ZA",2013 +"2013-04-01","Family Day","ZA",2013 +"2013-04-27","Freedom Day","ZA",2013 +"2013-05-01","Workers' Day","ZA",2013 +"2013-06-16","Youth Day","ZA",2013 +"2013-06-17","Youth Day (Observed)","ZA",2013 +"2013-08-09","National Women's Day","ZA",2013 +"2013-09-24","Heritage Day","ZA",2013 +"2013-12-16","Day of Reconciliation","ZA",2013 +"2013-12-25","Christmas Day","ZA",2013 +"2013-12-26","Day of Goodwill","ZA",2013 +"2014-01-01","New Year's Day","ZA",2014 +"2014-03-21","Human Rights Day","ZA",2014 +"2014-04-18","Good Friday","ZA",2014 +"2014-04-21","Family Day","ZA",2014 +"2014-04-27","Freedom Day","ZA",2014 +"2014-04-28","Freedom Day (Observed)","ZA",2014 +"2014-05-01","Workers' Day","ZA",2014 +"2014-05-07","National and provincial government elections","ZA",2014 +"2014-06-16","Youth Day","ZA",2014 +"2014-08-09","National Women's Day","ZA",2014 +"2014-09-24","Heritage Day","ZA",2014 +"2014-12-16","Day of Reconciliation","ZA",2014 +"2014-12-25","Christmas Day","ZA",2014 +"2014-12-26","Day of Goodwill","ZA",2014 +"2015-01-01","New Year's Day","ZA",2015 +"2015-03-21","Human Rights Day","ZA",2015 +"2015-04-03","Good Friday","ZA",2015 +"2015-04-06","Family Day","ZA",2015 +"2015-04-27","Freedom Day","ZA",2015 +"2015-05-01","Workers' Day","ZA",2015 +"2015-06-16","Youth Day","ZA",2015 +"2015-08-09","National Women's Day","ZA",2015 +"2015-08-10","National Women's Day (Observed)","ZA",2015 +"2015-09-24","Heritage Day","ZA",2015 +"2015-12-16","Day of Reconciliation","ZA",2015 +"2015-12-25","Christmas Day","ZA",2015 +"2015-12-26","Day of Goodwill","ZA",2015 +"2016-01-01","New Year's Day","ZA",2016 +"2016-03-21","Human Rights Day","ZA",2016 +"2016-03-25","Good Friday","ZA",2016 +"2016-03-28","Family Day","ZA",2016 +"2016-04-27","Freedom Day","ZA",2016 +"2016-05-01","Workers' Day","ZA",2016 +"2016-05-02","Workers' Day (Observed)","ZA",2016 +"2016-06-16","Youth Day","ZA",2016 +"2016-08-03","Local government elections","ZA",2016 +"2016-08-09","National Women's Day","ZA",2016 +"2016-09-24","Heritage Day","ZA",2016 +"2016-12-16","Day of Reconciliation","ZA",2016 +"2016-12-25","Christmas Day","ZA",2016 +"2016-12-26","Day of Goodwill","ZA",2016 +"2016-12-27","Public holiday by presidential decree","ZA",2016 +"2017-01-01","New Year's Day","ZA",2017 +"2017-01-02","New Year's Day (Observed)","ZA",2017 +"2017-03-21","Human Rights Day","ZA",2017 +"2017-04-14","Good Friday","ZA",2017 +"2017-04-17","Family Day","ZA",2017 +"2017-04-27","Freedom Day","ZA",2017 +"2017-05-01","Workers' Day","ZA",2017 +"2017-06-16","Youth Day","ZA",2017 +"2017-08-09","National Women's Day","ZA",2017 +"2017-09-24","Heritage Day","ZA",2017 +"2017-09-25","Heritage Day (Observed)","ZA",2017 +"2017-12-16","Day of Reconciliation","ZA",2017 +"2017-12-25","Christmas Day","ZA",2017 +"2017-12-26","Day of Goodwill","ZA",2017 +"2018-01-01","New Year's Day","ZA",2018 +"2018-03-21","Human Rights Day","ZA",2018 +"2018-03-30","Good Friday","ZA",2018 +"2018-04-02","Family Day","ZA",2018 +"2018-04-27","Freedom Day","ZA",2018 +"2018-05-01","Workers' Day","ZA",2018 +"2018-06-16","Youth Day","ZA",2018 +"2018-08-09","National Women's Day","ZA",2018 +"2018-09-24","Heritage Day","ZA",2018 +"2018-12-16","Day of Reconciliation","ZA",2018 +"2018-12-17","Day of Reconciliation (Observed)","ZA",2018 +"2018-12-25","Christmas Day","ZA",2018 +"2018-12-26","Day of Goodwill","ZA",2018 +"2019-01-01","New Year's Day","ZA",2019 +"2019-03-21","Human Rights Day","ZA",2019 +"2019-04-19","Good Friday","ZA",2019 +"2019-04-22","Family Day","ZA",2019 +"2019-04-27","Freedom Day","ZA",2019 +"2019-05-01","Workers' Day","ZA",2019 +"2019-05-08","National and provincial government elections","ZA",2019 +"2019-06-16","Youth Day","ZA",2019 +"2019-06-17","Youth Day (Observed)","ZA",2019 +"2019-08-09","National Women's Day","ZA",2019 +"2019-09-24","Heritage Day","ZA",2019 +"2019-12-16","Day of Reconciliation","ZA",2019 +"2019-12-25","Christmas Day","ZA",2019 +"2019-12-26","Day of Goodwill","ZA",2019 +"2020-01-01","New Year's Day","ZA",2020 +"2020-03-21","Human Rights Day","ZA",2020 +"2020-04-10","Good Friday","ZA",2020 +"2020-04-13","Family Day","ZA",2020 +"2020-04-27","Freedom Day","ZA",2020 +"2020-05-01","Workers' Day","ZA",2020 +"2020-06-16","Youth Day","ZA",2020 +"2020-08-09","National Women's Day","ZA",2020 +"2020-08-10","National Women's Day (Observed)","ZA",2020 +"2020-09-24","Heritage Day","ZA",2020 +"2020-12-16","Day of Reconciliation","ZA",2020 +"2020-12-25","Christmas Day","ZA",2020 +"2020-12-26","Day of Goodwill","ZA",2020 +"2021-01-01","New Year's Day","ZA",2021 +"2021-03-21","Human Rights Day","ZA",2021 +"2021-03-22","Human Rights Day (Observed)","ZA",2021 +"2021-04-02","Good Friday","ZA",2021 +"2021-04-05","Family Day","ZA",2021 +"2021-04-27","Freedom Day","ZA",2021 +"2021-05-01","Workers' Day","ZA",2021 +"2021-06-16","Youth Day","ZA",2021 +"2021-08-09","National Women's Day","ZA",2021 +"2021-09-24","Heritage Day","ZA",2021 +"2021-11-01","Municipal elections","ZA",2021 +"2021-12-16","Day of Reconciliation","ZA",2021 +"2021-12-25","Christmas Day","ZA",2021 +"2021-12-26","Day of Goodwill","ZA",2021 +"2021-12-27","Day of Goodwill (Observed)","ZA",2021 +"2022-01-01","New Year's Day","ZA",2022 +"2022-03-21","Human Rights Day","ZA",2022 +"2022-04-15","Good Friday","ZA",2022 +"2022-04-18","Family Day","ZA",2022 +"2022-04-27","Freedom Day","ZA",2022 +"2022-05-01","Workers' Day","ZA",2022 +"2022-05-02","Workers' Day (Observed)","ZA",2022 +"2022-06-16","Youth Day","ZA",2022 +"2022-08-09","National Women's Day","ZA",2022 +"2022-09-24","Heritage Day","ZA",2022 +"2022-12-16","Day of Reconciliation","ZA",2022 +"2022-12-25","Christmas Day","ZA",2022 +"2022-12-26","Day of Goodwill","ZA",2022 +"2022-12-27","Public holiday by presidential decree","ZA",2022 +"2023-01-01","New Year's Day","ZA",2023 +"2023-01-02","New Year's Day (Observed)","ZA",2023 +"2023-03-21","Human Rights Day","ZA",2023 +"2023-04-07","Good Friday","ZA",2023 +"2023-04-10","Family Day","ZA",2023 +"2023-04-27","Freedom Day","ZA",2023 +"2023-05-01","Workers' Day","ZA",2023 +"2023-06-16","Youth Day","ZA",2023 +"2023-08-09","National Women's Day","ZA",2023 +"2023-09-24","Heritage Day","ZA",2023 +"2023-09-25","Heritage Day (Observed)","ZA",2023 +"2023-12-16","Day of Reconciliation","ZA",2023 +"2023-12-25","Christmas Day","ZA",2023 +"2023-12-26","Day of Goodwill","ZA",2023 +"2024-01-01","New Year's Day","ZA",2024 +"2024-03-21","Human Rights Day","ZA",2024 +"2024-03-29","Good Friday","ZA",2024 +"2024-04-01","Family Day","ZA",2024 +"2024-04-27","Freedom Day","ZA",2024 +"2024-05-01","Workers' Day","ZA",2024 +"2024-06-16","Youth Day","ZA",2024 +"2024-06-17","Youth Day (Observed)","ZA",2024 +"2024-08-09","National Women's Day","ZA",2024 +"2024-09-24","Heritage Day","ZA",2024 +"2024-12-16","Day of Reconciliation","ZA",2024 +"2024-12-25","Christmas Day","ZA",2024 +"2024-12-26","Day of Goodwill","ZA",2024 +"2025-01-01","New Year's Day","ZA",2025 +"2025-03-21","Human Rights Day","ZA",2025 +"2025-04-18","Good Friday","ZA",2025 +"2025-04-21","Family Day","ZA",2025 +"2025-04-27","Freedom Day","ZA",2025 +"2025-04-28","Freedom Day (Observed)","ZA",2025 +"2025-05-01","Workers' Day","ZA",2025 +"2025-06-16","Youth Day","ZA",2025 +"2025-08-09","National Women's Day","ZA",2025 +"2025-09-24","Heritage Day","ZA",2025 +"2025-12-16","Day of Reconciliation","ZA",2025 +"2025-12-25","Christmas Day","ZA",2025 +"2025-12-26","Day of Goodwill","ZA",2025 +"2026-01-01","New Year's Day","ZA",2026 +"2026-03-21","Human Rights Day","ZA",2026 +"2026-04-03","Good Friday","ZA",2026 +"2026-04-06","Family Day","ZA",2026 +"2026-04-27","Freedom Day","ZA",2026 +"2026-05-01","Workers' Day","ZA",2026 +"2026-06-16","Youth Day","ZA",2026 +"2026-08-09","National Women's Day","ZA",2026 +"2026-08-10","National Women's Day (Observed)","ZA",2026 +"2026-09-24","Heritage Day","ZA",2026 +"2026-12-16","Day of Reconciliation","ZA",2026 +"2026-12-25","Christmas Day","ZA",2026 +"2026-12-26","Day of Goodwill","ZA",2026 +"2027-01-01","New Year's Day","ZA",2027 +"2027-03-21","Human Rights Day","ZA",2027 +"2027-03-22","Human Rights Day (Observed)","ZA",2027 +"2027-03-26","Good Friday","ZA",2027 +"2027-03-29","Family Day","ZA",2027 +"2027-04-27","Freedom Day","ZA",2027 +"2027-05-01","Workers' Day","ZA",2027 +"2027-06-16","Youth Day","ZA",2027 +"2027-08-09","National Women's Day","ZA",2027 +"2027-09-24","Heritage Day","ZA",2027 +"2027-12-16","Day of Reconciliation","ZA",2027 +"2027-12-25","Christmas Day","ZA",2027 +"2027-12-26","Day of Goodwill","ZA",2027 +"2027-12-27","Day of Goodwill (Observed)","ZA",2027 +"2028-01-01","New Year's Day","ZA",2028 +"2028-03-21","Human Rights Day","ZA",2028 +"2028-04-14","Good Friday","ZA",2028 +"2028-04-17","Family Day","ZA",2028 +"2028-04-27","Freedom Day","ZA",2028 +"2028-05-01","Workers' Day","ZA",2028 +"2028-06-16","Youth Day","ZA",2028 +"2028-08-09","National Women's Day","ZA",2028 +"2028-09-24","Heritage Day","ZA",2028 +"2028-09-25","Heritage Day (Observed)","ZA",2028 +"2028-12-16","Day of Reconciliation","ZA",2028 +"2028-12-25","Christmas Day","ZA",2028 +"2028-12-26","Day of Goodwill","ZA",2028 +"2029-01-01","New Year's Day","ZA",2029 +"2029-03-21","Human Rights Day","ZA",2029 +"2029-03-30","Good Friday","ZA",2029 +"2029-04-02","Family Day","ZA",2029 +"2029-04-27","Freedom Day","ZA",2029 +"2029-05-01","Workers' Day","ZA",2029 +"2029-06-16","Youth Day","ZA",2029 +"2029-08-09","National Women's Day","ZA",2029 +"2029-09-24","Heritage Day","ZA",2029 +"2029-12-16","Day of Reconciliation","ZA",2029 +"2029-12-17","Day of Reconciliation (Observed)","ZA",2029 +"2029-12-25","Christmas Day","ZA",2029 +"2029-12-26","Day of Goodwill","ZA",2029 +"2030-01-01","New Year's Day","ZA",2030 +"2030-03-21","Human Rights Day","ZA",2030 +"2030-04-19","Good Friday","ZA",2030 +"2030-04-22","Family Day","ZA",2030 +"2030-04-27","Freedom Day","ZA",2030 +"2030-05-01","Workers' Day","ZA",2030 +"2030-06-16","Youth Day","ZA",2030 +"2030-06-17","Youth Day (Observed)","ZA",2030 +"2030-08-09","National Women's Day","ZA",2030 +"2030-09-24","Heritage Day","ZA",2030 +"2030-12-16","Day of Reconciliation","ZA",2030 +"2030-12-25","Christmas Day","ZA",2030 +"2030-12-26","Day of Goodwill","ZA",2030 +"2031-01-01","New Year's Day","ZA",2031 +"2031-03-21","Human Rights Day","ZA",2031 +"2031-04-11","Good Friday","ZA",2031 +"2031-04-14","Family Day","ZA",2031 +"2031-04-27","Freedom Day","ZA",2031 +"2031-04-28","Freedom Day (Observed)","ZA",2031 +"2031-05-01","Workers' Day","ZA",2031 +"2031-06-16","Youth Day","ZA",2031 +"2031-08-09","National Women's Day","ZA",2031 +"2031-09-24","Heritage Day","ZA",2031 +"2031-12-16","Day of Reconciliation","ZA",2031 +"2031-12-25","Christmas Day","ZA",2031 +"2031-12-26","Day of Goodwill","ZA",2031 +"2032-01-01","New Year's Day","ZA",2032 +"2032-03-21","Human Rights Day","ZA",2032 +"2032-03-22","Human Rights Day (Observed)","ZA",2032 +"2032-03-26","Good Friday","ZA",2032 +"2032-03-29","Family Day","ZA",2032 +"2032-04-27","Freedom Day","ZA",2032 +"2032-05-01","Workers' Day","ZA",2032 +"2032-06-16","Youth Day","ZA",2032 +"2032-08-09","National Women's Day","ZA",2032 +"2032-09-24","Heritage Day","ZA",2032 +"2032-12-16","Day of Reconciliation","ZA",2032 +"2032-12-25","Christmas Day","ZA",2032 +"2032-12-26","Day of Goodwill","ZA",2032 +"2032-12-27","Day of Goodwill (Observed)","ZA",2032 +"2033-01-01","New Year's Day","ZA",2033 +"2033-03-21","Human Rights Day","ZA",2033 +"2033-04-15","Good Friday","ZA",2033 +"2033-04-18","Family Day","ZA",2033 +"2033-04-27","Freedom Day","ZA",2033 +"2033-05-01","Workers' Day","ZA",2033 +"2033-05-02","Workers' Day (Observed)","ZA",2033 +"2033-06-16","Youth Day","ZA",2033 +"2033-08-09","National Women's Day","ZA",2033 +"2033-09-24","Heritage Day","ZA",2033 +"2033-12-16","Day of Reconciliation","ZA",2033 +"2033-12-25","Christmas Day","ZA",2033 +"2033-12-26","Day of Goodwill","ZA",2033 +"2034-01-01","New Year's Day","ZA",2034 +"2034-01-02","New Year's Day (Observed)","ZA",2034 +"2034-03-21","Human Rights Day","ZA",2034 +"2034-04-07","Good Friday","ZA",2034 +"2034-04-10","Family Day","ZA",2034 +"2034-04-27","Freedom Day","ZA",2034 +"2034-05-01","Workers' Day","ZA",2034 +"2034-06-16","Youth Day","ZA",2034 +"2034-08-09","National Women's Day","ZA",2034 +"2034-09-24","Heritage Day","ZA",2034 +"2034-09-25","Heritage Day (Observed)","ZA",2034 +"2034-12-16","Day of Reconciliation","ZA",2034 +"2034-12-25","Christmas Day","ZA",2034 +"2034-12-26","Day of Goodwill","ZA",2034 +"2035-01-01","New Year's Day","ZA",2035 +"2035-03-21","Human Rights Day","ZA",2035 +"2035-03-23","Good Friday","ZA",2035 +"2035-03-26","Family Day","ZA",2035 +"2035-04-27","Freedom Day","ZA",2035 +"2035-05-01","Workers' Day","ZA",2035 +"2035-06-16","Youth Day","ZA",2035 +"2035-08-09","National Women's Day","ZA",2035 +"2035-09-24","Heritage Day","ZA",2035 +"2035-12-16","Day of Reconciliation","ZA",2035 +"2035-12-17","Day of Reconciliation (Observed)","ZA",2035 +"2035-12-25","Christmas Day","ZA",2035 +"2035-12-26","Day of Goodwill","ZA",2035 +"2036-01-01","New Year's Day","ZA",2036 +"2036-03-21","Human Rights Day","ZA",2036 +"2036-04-11","Good Friday","ZA",2036 +"2036-04-14","Family Day","ZA",2036 +"2036-04-27","Freedom Day","ZA",2036 +"2036-04-28","Freedom Day (Observed)","ZA",2036 +"2036-05-01","Workers' Day","ZA",2036 +"2036-06-16","Youth Day","ZA",2036 +"2036-08-09","National Women's Day","ZA",2036 +"2036-09-24","Heritage Day","ZA",2036 +"2036-12-16","Day of Reconciliation","ZA",2036 +"2036-12-25","Christmas Day","ZA",2036 +"2036-12-26","Day of Goodwill","ZA",2036 +"2037-01-01","New Year's Day","ZA",2037 +"2037-03-21","Human Rights Day","ZA",2037 +"2037-04-03","Good Friday","ZA",2037 +"2037-04-06","Family Day","ZA",2037 +"2037-04-27","Freedom Day","ZA",2037 +"2037-05-01","Workers' Day","ZA",2037 +"2037-06-16","Youth Day","ZA",2037 +"2037-08-09","National Women's Day","ZA",2037 +"2037-08-10","National Women's Day (Observed)","ZA",2037 +"2037-09-24","Heritage Day","ZA",2037 +"2037-12-16","Day of Reconciliation","ZA",2037 +"2037-12-25","Christmas Day","ZA",2037 +"2037-12-26","Day of Goodwill","ZA",2037 +"2038-01-01","New Year's Day","ZA",2038 +"2038-03-21","Human Rights Day","ZA",2038 +"2038-03-22","Human Rights Day (Observed)","ZA",2038 +"2038-04-23","Good Friday","ZA",2038 +"2038-04-26","Family Day","ZA",2038 +"2038-04-27","Freedom Day","ZA",2038 +"2038-05-01","Workers' Day","ZA",2038 +"2038-06-16","Youth Day","ZA",2038 +"2038-08-09","National Women's Day","ZA",2038 +"2038-09-24","Heritage Day","ZA",2038 +"2038-12-16","Day of Reconciliation","ZA",2038 +"2038-12-25","Christmas Day","ZA",2038 +"2038-12-26","Day of Goodwill","ZA",2038 +"2038-12-27","Day of Goodwill (Observed)","ZA",2038 +"2039-01-01","New Year's Day","ZA",2039 +"2039-03-21","Human Rights Day","ZA",2039 +"2039-04-08","Good Friday","ZA",2039 +"2039-04-11","Family Day","ZA",2039 +"2039-04-27","Freedom Day","ZA",2039 +"2039-05-01","Workers' Day","ZA",2039 +"2039-05-02","Workers' Day (Observed)","ZA",2039 +"2039-06-16","Youth Day","ZA",2039 +"2039-08-09","National Women's Day","ZA",2039 +"2039-09-24","Heritage Day","ZA",2039 +"2039-12-16","Day of Reconciliation","ZA",2039 +"2039-12-25","Christmas Day","ZA",2039 +"2039-12-26","Day of Goodwill","ZA",2039 +"2040-01-01","New Year's Day","ZA",2040 +"2040-01-02","New Year's Day (Observed)","ZA",2040 +"2040-03-21","Human Rights Day","ZA",2040 +"2040-03-30","Good Friday","ZA",2040 +"2040-04-02","Family Day","ZA",2040 +"2040-04-27","Freedom Day","ZA",2040 +"2040-05-01","Workers' Day","ZA",2040 +"2040-06-16","Youth Day","ZA",2040 +"2040-08-09","National Women's Day","ZA",2040 +"2040-09-24","Heritage Day","ZA",2040 +"2040-12-16","Day of Reconciliation","ZA",2040 +"2040-12-17","Day of Reconciliation (Observed)","ZA",2040 +"2040-12-25","Christmas Day","ZA",2040 +"2040-12-26","Day of Goodwill","ZA",2040 +"2041-01-01","New Year's Day","ZA",2041 +"2041-03-21","Human Rights Day","ZA",2041 +"2041-04-19","Good Friday","ZA",2041 +"2041-04-22","Family Day","ZA",2041 +"2041-04-27","Freedom Day","ZA",2041 +"2041-05-01","Workers' Day","ZA",2041 +"2041-06-16","Youth Day","ZA",2041 +"2041-06-17","Youth Day (Observed)","ZA",2041 +"2041-08-09","National Women's Day","ZA",2041 +"2041-09-24","Heritage Day","ZA",2041 +"2041-12-16","Day of Reconciliation","ZA",2041 +"2041-12-25","Christmas Day","ZA",2041 +"2041-12-26","Day of Goodwill","ZA",2041 +"2042-01-01","New Year's Day","ZA",2042 +"2042-03-21","Human Rights Day","ZA",2042 +"2042-04-04","Good Friday","ZA",2042 +"2042-04-07","Family Day","ZA",2042 +"2042-04-27","Freedom Day","ZA",2042 +"2042-04-28","Freedom Day (Observed)","ZA",2042 +"2042-05-01","Workers' Day","ZA",2042 +"2042-06-16","Youth Day","ZA",2042 +"2042-08-09","National Women's Day","ZA",2042 +"2042-09-24","Heritage Day","ZA",2042 +"2042-12-16","Day of Reconciliation","ZA",2042 +"2042-12-25","Christmas Day","ZA",2042 +"2042-12-26","Day of Goodwill","ZA",2042 +"2043-01-01","New Year's Day","ZA",2043 +"2043-03-21","Human Rights Day","ZA",2043 +"2043-03-27","Good Friday","ZA",2043 +"2043-03-30","Family Day","ZA",2043 +"2043-04-27","Freedom Day","ZA",2043 +"2043-05-01","Workers' Day","ZA",2043 +"2043-06-16","Youth Day","ZA",2043 +"2043-08-09","National Women's Day","ZA",2043 +"2043-08-10","National Women's Day (Observed)","ZA",2043 +"2043-09-24","Heritage Day","ZA",2043 +"2043-12-16","Day of Reconciliation","ZA",2043 +"2043-12-25","Christmas Day","ZA",2043 +"2043-12-26","Day of Goodwill","ZA",2043 +"2044-01-01","New Year's Day","ZA",2044 +"2044-03-21","Human Rights Day","ZA",2044 +"2044-04-15","Good Friday","ZA",2044 +"2044-04-18","Family Day","ZA",2044 +"2044-04-27","Freedom Day","ZA",2044 +"2044-05-01","Workers' Day","ZA",2044 +"2044-05-02","Workers' Day (Observed)","ZA",2044 +"2044-06-16","Youth Day","ZA",2044 +"2044-08-09","National Women's Day","ZA",2044 +"2044-09-24","Heritage Day","ZA",2044 +"2044-12-16","Day of Reconciliation","ZA",2044 +"2044-12-25","Christmas Day","ZA",2044 +"2044-12-26","Day of Goodwill","ZA",2044 +"1995-01-01","New Year's Day","ZM",1995 +"1995-01-02","New Year's Day (Observed)","ZM",1995 +"1995-03-08","International Women's Day","ZM",1995 +"1995-03-12","Youth Day","ZM",1995 +"1995-03-13","Youth Day (Observed)","ZM",1995 +"1995-04-14","Good Friday","ZM",1995 +"1995-04-15","Holy Saturday","ZM",1995 +"1995-04-17","Easter Monday","ZM",1995 +"1995-05-01","Labour Day","ZM",1995 +"1995-05-25","Africa Freedom Day","ZM",1995 +"1995-07-03","Heroes' Day","ZM",1995 +"1995-07-04","Unity Day","ZM",1995 +"1995-08-07","Farmers' Day","ZM",1995 +"1995-10-24","Independence Day","ZM",1995 +"1995-12-25","Christmas Day","ZM",1995 +"1996-01-01","New Year's Day","ZM",1996 +"1996-03-08","International Women's Day","ZM",1996 +"1996-03-12","Youth Day","ZM",1996 +"1996-04-05","Good Friday","ZM",1996 +"1996-04-06","Holy Saturday","ZM",1996 +"1996-04-08","Easter Monday","ZM",1996 +"1996-05-01","Labour Day","ZM",1996 +"1996-05-25","Africa Freedom Day","ZM",1996 +"1996-07-01","Heroes' Day","ZM",1996 +"1996-07-02","Unity Day","ZM",1996 +"1996-08-05","Farmers' Day","ZM",1996 +"1996-10-24","Independence Day","ZM",1996 +"1996-12-25","Christmas Day","ZM",1996 +"1997-01-01","New Year's Day","ZM",1997 +"1997-03-08","International Women's Day","ZM",1997 +"1997-03-12","Youth Day","ZM",1997 +"1997-03-28","Good Friday","ZM",1997 +"1997-03-29","Holy Saturday","ZM",1997 +"1997-03-31","Easter Monday","ZM",1997 +"1997-05-01","Labour Day","ZM",1997 +"1997-05-25","Africa Freedom Day","ZM",1997 +"1997-05-26","Africa Freedom Day (Observed)","ZM",1997 +"1997-07-07","Heroes' Day","ZM",1997 +"1997-07-08","Unity Day","ZM",1997 +"1997-08-04","Farmers' Day","ZM",1997 +"1997-10-24","Independence Day","ZM",1997 +"1997-12-25","Christmas Day","ZM",1997 +"1998-01-01","New Year's Day","ZM",1998 +"1998-03-08","International Women's Day","ZM",1998 +"1998-03-09","International Women's Day (Observed)","ZM",1998 +"1998-03-12","Youth Day","ZM",1998 +"1998-04-10","Good Friday","ZM",1998 +"1998-04-11","Holy Saturday","ZM",1998 +"1998-04-13","Easter Monday","ZM",1998 +"1998-05-01","Labour Day","ZM",1998 +"1998-05-25","Africa Freedom Day","ZM",1998 +"1998-07-06","Heroes' Day","ZM",1998 +"1998-07-07","Unity Day","ZM",1998 +"1998-08-03","Farmers' Day","ZM",1998 +"1998-10-24","Independence Day","ZM",1998 +"1998-12-25","Christmas Day","ZM",1998 +"1999-01-01","New Year's Day","ZM",1999 +"1999-03-08","International Women's Day","ZM",1999 +"1999-03-12","Youth Day","ZM",1999 +"1999-04-02","Good Friday","ZM",1999 +"1999-04-03","Holy Saturday","ZM",1999 +"1999-04-05","Easter Monday","ZM",1999 +"1999-05-01","Labour Day","ZM",1999 +"1999-05-25","Africa Freedom Day","ZM",1999 +"1999-07-05","Heroes' Day","ZM",1999 +"1999-07-06","Unity Day","ZM",1999 +"1999-08-02","Farmers' Day","ZM",1999 +"1999-10-24","Independence Day","ZM",1999 +"1999-10-25","Independence Day (Observed)","ZM",1999 +"1999-12-25","Christmas Day","ZM",1999 +"2000-01-01","New Year's Day","ZM",2000 +"2000-03-08","International Women's Day","ZM",2000 +"2000-03-12","Youth Day","ZM",2000 +"2000-03-13","Youth Day (Observed)","ZM",2000 +"2000-04-21","Good Friday","ZM",2000 +"2000-04-22","Holy Saturday","ZM",2000 +"2000-04-24","Easter Monday","ZM",2000 +"2000-05-01","Labour Day","ZM",2000 +"2000-05-25","Africa Freedom Day","ZM",2000 +"2000-07-03","Heroes' Day","ZM",2000 +"2000-07-04","Unity Day","ZM",2000 +"2000-08-07","Farmers' Day","ZM",2000 +"2000-10-24","Independence Day","ZM",2000 +"2000-12-25","Christmas Day","ZM",2000 +"2001-01-01","New Year's Day","ZM",2001 +"2001-03-08","International Women's Day","ZM",2001 +"2001-03-12","Youth Day","ZM",2001 +"2001-04-13","Good Friday","ZM",2001 +"2001-04-14","Holy Saturday","ZM",2001 +"2001-04-16","Easter Monday","ZM",2001 +"2001-05-01","Labour Day","ZM",2001 +"2001-05-25","Africa Freedom Day","ZM",2001 +"2001-07-02","Heroes' Day","ZM",2001 +"2001-07-03","Unity Day","ZM",2001 +"2001-08-06","Farmers' Day","ZM",2001 +"2001-10-24","Independence Day","ZM",2001 +"2001-12-25","Christmas Day","ZM",2001 +"2002-01-01","New Year's Day","ZM",2002 +"2002-03-08","International Women's Day","ZM",2002 +"2002-03-12","Youth Day","ZM",2002 +"2002-03-29","Good Friday","ZM",2002 +"2002-03-30","Holy Saturday","ZM",2002 +"2002-04-01","Easter Monday","ZM",2002 +"2002-05-01","Labour Day","ZM",2002 +"2002-05-25","Africa Freedom Day","ZM",2002 +"2002-07-01","Heroes' Day","ZM",2002 +"2002-07-02","Unity Day","ZM",2002 +"2002-08-05","Farmers' Day","ZM",2002 +"2002-10-24","Independence Day","ZM",2002 +"2002-12-25","Christmas Day","ZM",2002 +"2003-01-01","New Year's Day","ZM",2003 +"2003-03-08","International Women's Day","ZM",2003 +"2003-03-12","Youth Day","ZM",2003 +"2003-04-18","Good Friday","ZM",2003 +"2003-04-19","Holy Saturday","ZM",2003 +"2003-04-21","Easter Monday","ZM",2003 +"2003-05-01","Labour Day","ZM",2003 +"2003-05-25","Africa Freedom Day","ZM",2003 +"2003-05-26","Africa Freedom Day (Observed)","ZM",2003 +"2003-07-07","Heroes' Day","ZM",2003 +"2003-07-08","Unity Day","ZM",2003 +"2003-08-04","Farmers' Day","ZM",2003 +"2003-10-24","Independence Day","ZM",2003 +"2003-12-25","Christmas Day","ZM",2003 +"2004-01-01","New Year's Day","ZM",2004 +"2004-03-08","International Women's Day","ZM",2004 +"2004-03-12","Youth Day","ZM",2004 +"2004-04-09","Good Friday","ZM",2004 +"2004-04-10","Holy Saturday","ZM",2004 +"2004-04-12","Easter Monday","ZM",2004 +"2004-05-01","Labour Day","ZM",2004 +"2004-05-25","Africa Freedom Day","ZM",2004 +"2004-07-05","Heroes' Day","ZM",2004 +"2004-07-06","Unity Day","ZM",2004 +"2004-08-02","Farmers' Day","ZM",2004 +"2004-10-24","Independence Day","ZM",2004 +"2004-10-25","Independence Day (Observed)","ZM",2004 +"2004-12-25","Christmas Day","ZM",2004 +"2005-01-01","New Year's Day","ZM",2005 +"2005-03-08","International Women's Day","ZM",2005 +"2005-03-12","Youth Day","ZM",2005 +"2005-03-25","Good Friday","ZM",2005 +"2005-03-26","Holy Saturday","ZM",2005 +"2005-03-28","Easter Monday","ZM",2005 +"2005-05-01","Labour Day","ZM",2005 +"2005-05-02","Labour Day (Observed)","ZM",2005 +"2005-05-25","Africa Freedom Day","ZM",2005 +"2005-07-04","Heroes' Day","ZM",2005 +"2005-07-05","Unity Day","ZM",2005 +"2005-08-01","Farmers' Day","ZM",2005 +"2005-10-24","Independence Day","ZM",2005 +"2005-12-25","Christmas Day","ZM",2005 +"2005-12-26","Christmas Day (Observed)","ZM",2005 +"2006-01-01","New Year's Day","ZM",2006 +"2006-01-02","New Year's Day (Observed)","ZM",2006 +"2006-03-08","International Women's Day","ZM",2006 +"2006-03-12","Youth Day","ZM",2006 +"2006-03-13","Youth Day (Observed)","ZM",2006 +"2006-04-14","Good Friday","ZM",2006 +"2006-04-15","Holy Saturday","ZM",2006 +"2006-04-17","Easter Monday","ZM",2006 +"2006-05-01","Labour Day","ZM",2006 +"2006-05-25","Africa Freedom Day","ZM",2006 +"2006-07-03","Heroes' Day","ZM",2006 +"2006-07-04","Unity Day","ZM",2006 +"2006-08-07","Farmers' Day","ZM",2006 +"2006-10-24","Independence Day","ZM",2006 +"2006-12-25","Christmas Day","ZM",2006 +"2007-01-01","New Year's Day","ZM",2007 +"2007-03-08","International Women's Day","ZM",2007 +"2007-03-12","Youth Day","ZM",2007 +"2007-04-06","Good Friday","ZM",2007 +"2007-04-07","Holy Saturday","ZM",2007 +"2007-04-09","Easter Monday","ZM",2007 +"2007-05-01","Labour Day","ZM",2007 +"2007-05-25","Africa Freedom Day","ZM",2007 +"2007-07-02","Heroes' Day","ZM",2007 +"2007-07-03","Unity Day","ZM",2007 +"2007-08-06","Farmers' Day","ZM",2007 +"2007-10-24","Independence Day","ZM",2007 +"2007-12-25","Christmas Day","ZM",2007 +"2008-01-01","New Year's Day","ZM",2008 +"2008-03-08","International Women's Day","ZM",2008 +"2008-03-12","Youth Day","ZM",2008 +"2008-03-21","Good Friday","ZM",2008 +"2008-03-22","Holy Saturday","ZM",2008 +"2008-03-24","Easter Monday","ZM",2008 +"2008-05-01","Labour Day","ZM",2008 +"2008-05-25","Africa Freedom Day","ZM",2008 +"2008-05-26","Africa Freedom Day (Observed)","ZM",2008 +"2008-07-07","Heroes' Day","ZM",2008 +"2008-07-08","Unity Day","ZM",2008 +"2008-08-04","Farmers' Day","ZM",2008 +"2008-10-24","Independence Day","ZM",2008 +"2008-12-25","Christmas Day","ZM",2008 +"2009-01-01","New Year's Day","ZM",2009 +"2009-03-08","International Women's Day","ZM",2009 +"2009-03-09","International Women's Day (Observed)","ZM",2009 +"2009-03-12","Youth Day","ZM",2009 +"2009-04-10","Good Friday","ZM",2009 +"2009-04-11","Holy Saturday","ZM",2009 +"2009-04-13","Easter Monday","ZM",2009 +"2009-05-01","Labour Day","ZM",2009 +"2009-05-25","Africa Freedom Day","ZM",2009 +"2009-07-06","Heroes' Day","ZM",2009 +"2009-07-07","Unity Day","ZM",2009 +"2009-08-03","Farmers' Day","ZM",2009 +"2009-10-24","Independence Day","ZM",2009 +"2009-12-25","Christmas Day","ZM",2009 +"2010-01-01","New Year's Day","ZM",2010 +"2010-03-08","International Women's Day","ZM",2010 +"2010-03-12","Youth Day","ZM",2010 +"2010-04-02","Good Friday","ZM",2010 +"2010-04-03","Holy Saturday","ZM",2010 +"2010-04-05","Easter Monday","ZM",2010 +"2010-05-01","Labour Day","ZM",2010 +"2010-05-25","Africa Freedom Day","ZM",2010 +"2010-07-05","Heroes' Day","ZM",2010 +"2010-07-06","Unity Day","ZM",2010 +"2010-08-02","Farmers' Day","ZM",2010 +"2010-10-24","Independence Day","ZM",2010 +"2010-10-25","Independence Day (Observed)","ZM",2010 +"2010-12-25","Christmas Day","ZM",2010 +"2011-01-01","New Year's Day","ZM",2011 +"2011-03-08","International Women's Day","ZM",2011 +"2011-03-12","Youth Day","ZM",2011 +"2011-04-22","Good Friday","ZM",2011 +"2011-04-23","Holy Saturday","ZM",2011 +"2011-04-25","Easter Monday","ZM",2011 +"2011-05-01","Labour Day","ZM",2011 +"2011-05-02","Labour Day (Observed)","ZM",2011 +"2011-05-25","Africa Freedom Day","ZM",2011 +"2011-07-04","Heroes' Day","ZM",2011 +"2011-07-05","Unity Day","ZM",2011 +"2011-08-01","Farmers' Day","ZM",2011 +"2011-10-24","Independence Day","ZM",2011 +"2011-12-25","Christmas Day","ZM",2011 +"2011-12-26","Christmas Day (Observed)","ZM",2011 +"2012-01-01","New Year's Day","ZM",2012 +"2012-01-02","New Year's Day (Observed)","ZM",2012 +"2012-03-08","International Women's Day","ZM",2012 +"2012-03-12","Youth Day","ZM",2012 +"2012-04-06","Good Friday","ZM",2012 +"2012-04-07","Holy Saturday","ZM",2012 +"2012-04-09","Easter Monday","ZM",2012 +"2012-05-01","Labour Day","ZM",2012 +"2012-05-25","Africa Freedom Day","ZM",2012 +"2012-07-02","Heroes' Day","ZM",2012 +"2012-07-03","Unity Day","ZM",2012 +"2012-08-06","Farmers' Day","ZM",2012 +"2012-10-24","Independence Day","ZM",2012 +"2012-12-25","Christmas Day","ZM",2012 +"2013-01-01","New Year's Day","ZM",2013 +"2013-03-08","International Women's Day","ZM",2013 +"2013-03-12","Youth Day","ZM",2013 +"2013-03-29","Good Friday","ZM",2013 +"2013-03-30","Holy Saturday","ZM",2013 +"2013-04-01","Easter Monday","ZM",2013 +"2013-05-01","Labour Day","ZM",2013 +"2013-05-25","Africa Freedom Day","ZM",2013 +"2013-07-01","Heroes' Day","ZM",2013 +"2013-07-02","Unity Day","ZM",2013 +"2013-08-05","Farmers' Day","ZM",2013 +"2013-10-24","Independence Day","ZM",2013 +"2013-12-25","Christmas Day","ZM",2013 +"2014-01-01","New Year's Day","ZM",2014 +"2014-03-08","International Women's Day","ZM",2014 +"2014-03-12","Youth Day","ZM",2014 +"2014-04-18","Good Friday","ZM",2014 +"2014-04-19","Holy Saturday","ZM",2014 +"2014-04-21","Easter Monday","ZM",2014 +"2014-05-01","Labour Day","ZM",2014 +"2014-05-25","Africa Freedom Day","ZM",2014 +"2014-05-26","Africa Freedom Day (Observed)","ZM",2014 +"2014-07-07","Heroes' Day","ZM",2014 +"2014-07-08","Unity Day","ZM",2014 +"2014-08-04","Farmers' Day","ZM",2014 +"2014-10-24","Independence Day","ZM",2014 +"2014-12-25","Christmas Day","ZM",2014 +"2015-01-01","New Year's Day","ZM",2015 +"2015-03-08","International Women's Day","ZM",2015 +"2015-03-09","International Women's Day (Observed)","ZM",2015 +"2015-03-12","Youth Day","ZM",2015 +"2015-04-03","Good Friday","ZM",2015 +"2015-04-04","Holy Saturday","ZM",2015 +"2015-04-06","Easter Monday","ZM",2015 +"2015-05-01","Labour Day","ZM",2015 +"2015-05-25","Africa Freedom Day","ZM",2015 +"2015-07-06","Heroes' Day","ZM",2015 +"2015-07-07","Unity Day","ZM",2015 +"2015-08-03","Farmers' Day","ZM",2015 +"2015-10-18","National Prayer Day","ZM",2015 +"2015-10-19","National Prayer Day (Observed)","ZM",2015 +"2015-10-24","Independence Day","ZM",2015 +"2015-12-25","Christmas Day","ZM",2015 +"2016-01-01","New Year's Day","ZM",2016 +"2016-03-08","International Women's Day","ZM",2016 +"2016-03-12","Youth Day","ZM",2016 +"2016-03-25","Good Friday","ZM",2016 +"2016-03-26","Holy Saturday","ZM",2016 +"2016-03-28","Easter Monday","ZM",2016 +"2016-05-01","Labour Day","ZM",2016 +"2016-05-02","Labour Day (Observed)","ZM",2016 +"2016-05-25","Africa Freedom Day","ZM",2016 +"2016-07-04","Heroes' Day","ZM",2016 +"2016-07-05","Unity Day","ZM",2016 +"2016-08-01","Farmers' Day","ZM",2016 +"2016-08-11","General elections and referendum","ZM",2016 +"2016-09-13","Inauguration ceremony of President-elect and Vice President-elect","ZM",2016 +"2016-10-18","National Prayer Day","ZM",2016 +"2016-10-24","Independence Day","ZM",2016 +"2016-12-25","Christmas Day","ZM",2016 +"2016-12-26","Christmas Day (Observed)","ZM",2016 +"2017-01-01","New Year's Day","ZM",2017 +"2017-01-02","New Year's Day (Observed)","ZM",2017 +"2017-03-08","International Women's Day","ZM",2017 +"2017-03-12","Youth Day","ZM",2017 +"2017-03-13","Youth Day (Observed)","ZM",2017 +"2017-04-14","Good Friday","ZM",2017 +"2017-04-15","Holy Saturday","ZM",2017 +"2017-04-17","Easter Monday","ZM",2017 +"2017-05-01","Labour Day","ZM",2017 +"2017-05-25","Africa Freedom Day","ZM",2017 +"2017-07-03","Heroes' Day","ZM",2017 +"2017-07-04","Unity Day","ZM",2017 +"2017-08-07","Farmers' Day","ZM",2017 +"2017-10-18","National Prayer Day","ZM",2017 +"2017-10-24","Independence Day","ZM",2017 +"2017-12-25","Christmas Day","ZM",2017 +"2018-01-01","New Year's Day","ZM",2018 +"2018-03-08","International Women's Day","ZM",2018 +"2018-03-09","Public holiday","ZM",2018 +"2018-03-12","Youth Day","ZM",2018 +"2018-03-30","Good Friday","ZM",2018 +"2018-03-31","Holy Saturday","ZM",2018 +"2018-04-02","Easter Monday","ZM",2018 +"2018-05-01","Labour Day","ZM",2018 +"2018-05-25","Africa Freedom Day","ZM",2018 +"2018-07-02","Heroes' Day","ZM",2018 +"2018-07-03","Unity Day","ZM",2018 +"2018-07-26","Lusaka mayoral and other local government elections","ZM",2018 +"2018-08-06","Farmers' Day","ZM",2018 +"2018-10-18","National Prayer Day","ZM",2018 +"2018-10-24","Independence Day","ZM",2018 +"2018-12-25","Christmas Day","ZM",2018 +"2019-01-01","New Year's Day","ZM",2019 +"2019-03-08","International Women's Day","ZM",2019 +"2019-03-12","Youth Day","ZM",2019 +"2019-04-19","Good Friday","ZM",2019 +"2019-04-20","Holy Saturday","ZM",2019 +"2019-04-22","Easter Monday","ZM",2019 +"2019-05-01","Labour Day","ZM",2019 +"2019-05-25","Africa Freedom Day","ZM",2019 +"2019-07-01","Heroes' Day","ZM",2019 +"2019-07-02","Unity Day","ZM",2019 +"2019-08-05","Farmers' Day","ZM",2019 +"2019-10-18","National Prayer Day","ZM",2019 +"2019-10-24","Independence Day","ZM",2019 +"2019-12-25","Christmas Day","ZM",2019 +"2020-01-01","New Year's Day","ZM",2020 +"2020-03-08","International Women's Day","ZM",2020 +"2020-03-09","International Women's Day (Observed)","ZM",2020 +"2020-03-12","Youth Day","ZM",2020 +"2020-04-10","Good Friday","ZM",2020 +"2020-04-11","Holy Saturday","ZM",2020 +"2020-04-13","Easter Monday","ZM",2020 +"2020-05-01","Labour Day","ZM",2020 +"2020-05-25","Africa Freedom Day","ZM",2020 +"2020-07-06","Heroes' Day","ZM",2020 +"2020-07-07","Unity Day","ZM",2020 +"2020-08-03","Farmers' Day","ZM",2020 +"2020-10-18","National Prayer Day","ZM",2020 +"2020-10-19","National Prayer Day (Observed)","ZM",2020 +"2020-10-24","Independence Day","ZM",2020 +"2020-12-25","Christmas Day","ZM",2020 +"2021-01-01","New Year's Day","ZM",2021 +"2021-03-08","International Women's Day","ZM",2021 +"2021-03-12","Youth Day","ZM",2021 +"2021-04-02","Good Friday","ZM",2021 +"2021-04-03","Holy Saturday","ZM",2021 +"2021-04-05","Easter Monday","ZM",2021 +"2021-05-01","Labour Day","ZM",2021 +"2021-05-25","Africa Freedom Day","ZM",2021 +"2021-07-02","Memorial service for Kenneth Kaunda","ZM",2021 +"2021-07-05","Heroes' Day","ZM",2021 +"2021-07-06","Unity Day","ZM",2021 +"2021-07-07","Funeral of Kenneth Kaunda","ZM",2021 +"2021-08-02","Farmers' Day","ZM",2021 +"2021-08-12","General elections","ZM",2021 +"2021-08-13","Counting in general elections","ZM",2021 +"2021-08-24","Presidential inauguration","ZM",2021 +"2021-10-18","National Prayer Day","ZM",2021 +"2021-10-24","Independence Day","ZM",2021 +"2021-10-25","Independence Day (Observed)","ZM",2021 +"2021-12-25","Christmas Day","ZM",2021 +"2022-01-01","New Year's Day","ZM",2022 +"2022-03-08","International Women's Day","ZM",2022 +"2022-03-12","Youth Day","ZM",2022 +"2022-03-18","Funeral of Rupiah Banda","ZM",2022 +"2022-04-15","Good Friday","ZM",2022 +"2022-04-16","Holy Saturday","ZM",2022 +"2022-04-18","Easter Monday","ZM",2022 +"2022-04-28","Kenneth Kaunda Day","ZM",2022 +"2022-05-01","Labour Day","ZM",2022 +"2022-05-02","Labour Day (Observed)","ZM",2022 +"2022-05-25","Africa Freedom Day","ZM",2022 +"2022-07-04","Heroes' Day","ZM",2022 +"2022-07-05","Unity Day","ZM",2022 +"2022-08-01","Farmers' Day","ZM",2022 +"2022-10-18","National Prayer Day","ZM",2022 +"2022-10-24","Independence Day","ZM",2022 +"2022-12-25","Christmas Day","ZM",2022 +"2022-12-26","Christmas Day (Observed)","ZM",2022 +"2023-01-01","New Year's Day","ZM",2023 +"2023-01-02","New Year's Day (Observed)","ZM",2023 +"2023-03-08","International Women's Day","ZM",2023 +"2023-03-12","Youth Day","ZM",2023 +"2023-03-13","Youth Day (Observed)","ZM",2023 +"2023-04-07","Good Friday","ZM",2023 +"2023-04-08","Holy Saturday","ZM",2023 +"2023-04-10","Easter Monday","ZM",2023 +"2023-04-28","Kenneth Kaunda Day","ZM",2023 +"2023-05-01","Labour Day","ZM",2023 +"2023-05-25","Africa Freedom Day","ZM",2023 +"2023-07-03","Heroes' Day","ZM",2023 +"2023-07-04","Unity Day","ZM",2023 +"2023-08-07","Farmers' Day","ZM",2023 +"2023-10-18","National Prayer Day","ZM",2023 +"2023-10-24","Independence Day","ZM",2023 +"2023-12-25","Christmas Day","ZM",2023 +"2024-01-01","New Year's Day","ZM",2024 +"2024-03-08","International Women's Day","ZM",2024 +"2024-03-12","Youth Day","ZM",2024 +"2024-03-29","Good Friday","ZM",2024 +"2024-03-30","Holy Saturday","ZM",2024 +"2024-04-01","Easter Monday","ZM",2024 +"2024-04-28","Kenneth Kaunda Day","ZM",2024 +"2024-04-29","Kenneth Kaunda Day (Observed)","ZM",2024 +"2024-05-01","Labour Day","ZM",2024 +"2024-05-25","Africa Freedom Day","ZM",2024 +"2024-07-01","Heroes' Day","ZM",2024 +"2024-07-02","Unity Day","ZM",2024 +"2024-08-05","Farmers' Day","ZM",2024 +"2024-10-18","National Prayer Day","ZM",2024 +"2024-10-24","Independence Day","ZM",2024 +"2024-12-25","Christmas Day","ZM",2024 +"2025-01-01","New Year's Day","ZM",2025 +"2025-03-08","International Women's Day","ZM",2025 +"2025-03-12","Youth Day","ZM",2025 +"2025-04-18","Good Friday","ZM",2025 +"2025-04-19","Holy Saturday","ZM",2025 +"2025-04-21","Easter Monday","ZM",2025 +"2025-04-28","Kenneth Kaunda Day","ZM",2025 +"2025-05-01","Labour Day","ZM",2025 +"2025-05-25","Africa Freedom Day","ZM",2025 +"2025-05-26","Africa Freedom Day (Observed)","ZM",2025 +"2025-07-07","Heroes' Day","ZM",2025 +"2025-07-08","Unity Day","ZM",2025 +"2025-08-04","Farmers' Day","ZM",2025 +"2025-10-18","National Prayer Day","ZM",2025 +"2025-10-24","Independence Day","ZM",2025 +"2025-12-25","Christmas Day","ZM",2025 +"2026-01-01","New Year's Day","ZM",2026 +"2026-03-08","International Women's Day","ZM",2026 +"2026-03-09","International Women's Day (Observed)","ZM",2026 +"2026-03-12","Youth Day","ZM",2026 +"2026-04-03","Good Friday","ZM",2026 +"2026-04-04","Holy Saturday","ZM",2026 +"2026-04-06","Easter Monday","ZM",2026 +"2026-04-28","Kenneth Kaunda Day","ZM",2026 +"2026-05-01","Labour Day","ZM",2026 +"2026-05-25","Africa Freedom Day","ZM",2026 +"2026-07-06","Heroes' Day","ZM",2026 +"2026-07-07","Unity Day","ZM",2026 +"2026-08-03","Farmers' Day","ZM",2026 +"2026-10-18","National Prayer Day","ZM",2026 +"2026-10-19","National Prayer Day (Observed)","ZM",2026 +"2026-10-24","Independence Day","ZM",2026 +"2026-12-25","Christmas Day","ZM",2026 +"2027-01-01","New Year's Day","ZM",2027 +"2027-03-08","International Women's Day","ZM",2027 +"2027-03-12","Youth Day","ZM",2027 +"2027-03-26","Good Friday","ZM",2027 +"2027-03-27","Holy Saturday","ZM",2027 +"2027-03-29","Easter Monday","ZM",2027 +"2027-04-28","Kenneth Kaunda Day","ZM",2027 +"2027-05-01","Labour Day","ZM",2027 +"2027-05-25","Africa Freedom Day","ZM",2027 +"2027-07-05","Heroes' Day","ZM",2027 +"2027-07-06","Unity Day","ZM",2027 +"2027-08-02","Farmers' Day","ZM",2027 +"2027-10-18","National Prayer Day","ZM",2027 +"2027-10-24","Independence Day","ZM",2027 +"2027-10-25","Independence Day (Observed)","ZM",2027 +"2027-12-25","Christmas Day","ZM",2027 +"2028-01-01","New Year's Day","ZM",2028 +"2028-03-08","International Women's Day","ZM",2028 +"2028-03-12","Youth Day","ZM",2028 +"2028-03-13","Youth Day (Observed)","ZM",2028 +"2028-04-14","Good Friday","ZM",2028 +"2028-04-15","Holy Saturday","ZM",2028 +"2028-04-17","Easter Monday","ZM",2028 +"2028-04-28","Kenneth Kaunda Day","ZM",2028 +"2028-05-01","Labour Day","ZM",2028 +"2028-05-25","Africa Freedom Day","ZM",2028 +"2028-07-03","Heroes' Day","ZM",2028 +"2028-07-04","Unity Day","ZM",2028 +"2028-08-07","Farmers' Day","ZM",2028 +"2028-10-18","National Prayer Day","ZM",2028 +"2028-10-24","Independence Day","ZM",2028 +"2028-12-25","Christmas Day","ZM",2028 +"2029-01-01","New Year's Day","ZM",2029 +"2029-03-08","International Women's Day","ZM",2029 +"2029-03-12","Youth Day","ZM",2029 +"2029-03-30","Good Friday","ZM",2029 +"2029-03-31","Holy Saturday","ZM",2029 +"2029-04-02","Easter Monday","ZM",2029 +"2029-04-28","Kenneth Kaunda Day","ZM",2029 +"2029-05-01","Labour Day","ZM",2029 +"2029-05-25","Africa Freedom Day","ZM",2029 +"2029-07-02","Heroes' Day","ZM",2029 +"2029-07-03","Unity Day","ZM",2029 +"2029-08-06","Farmers' Day","ZM",2029 +"2029-10-18","National Prayer Day","ZM",2029 +"2029-10-24","Independence Day","ZM",2029 +"2029-12-25","Christmas Day","ZM",2029 +"2030-01-01","New Year's Day","ZM",2030 +"2030-03-08","International Women's Day","ZM",2030 +"2030-03-12","Youth Day","ZM",2030 +"2030-04-19","Good Friday","ZM",2030 +"2030-04-20","Holy Saturday","ZM",2030 +"2030-04-22","Easter Monday","ZM",2030 +"2030-04-28","Kenneth Kaunda Day","ZM",2030 +"2030-04-29","Kenneth Kaunda Day (Observed)","ZM",2030 +"2030-05-01","Labour Day","ZM",2030 +"2030-05-25","Africa Freedom Day","ZM",2030 +"2030-07-01","Heroes' Day","ZM",2030 +"2030-07-02","Unity Day","ZM",2030 +"2030-08-05","Farmers' Day","ZM",2030 +"2030-10-18","National Prayer Day","ZM",2030 +"2030-10-24","Independence Day","ZM",2030 +"2030-12-25","Christmas Day","ZM",2030 +"2031-01-01","New Year's Day","ZM",2031 +"2031-03-08","International Women's Day","ZM",2031 +"2031-03-12","Youth Day","ZM",2031 +"2031-04-11","Good Friday","ZM",2031 +"2031-04-12","Holy Saturday","ZM",2031 +"2031-04-14","Easter Monday","ZM",2031 +"2031-04-28","Kenneth Kaunda Day","ZM",2031 +"2031-05-01","Labour Day","ZM",2031 +"2031-05-25","Africa Freedom Day","ZM",2031 +"2031-05-26","Africa Freedom Day (Observed)","ZM",2031 +"2031-07-07","Heroes' Day","ZM",2031 +"2031-07-08","Unity Day","ZM",2031 +"2031-08-04","Farmers' Day","ZM",2031 +"2031-10-18","National Prayer Day","ZM",2031 +"2031-10-24","Independence Day","ZM",2031 +"2031-12-25","Christmas Day","ZM",2031 +"2032-01-01","New Year's Day","ZM",2032 +"2032-03-08","International Women's Day","ZM",2032 +"2032-03-12","Youth Day","ZM",2032 +"2032-03-26","Good Friday","ZM",2032 +"2032-03-27","Holy Saturday","ZM",2032 +"2032-03-29","Easter Monday","ZM",2032 +"2032-04-28","Kenneth Kaunda Day","ZM",2032 +"2032-05-01","Labour Day","ZM",2032 +"2032-05-25","Africa Freedom Day","ZM",2032 +"2032-07-05","Heroes' Day","ZM",2032 +"2032-07-06","Unity Day","ZM",2032 +"2032-08-02","Farmers' Day","ZM",2032 +"2032-10-18","National Prayer Day","ZM",2032 +"2032-10-24","Independence Day","ZM",2032 +"2032-10-25","Independence Day (Observed)","ZM",2032 +"2032-12-25","Christmas Day","ZM",2032 +"2033-01-01","New Year's Day","ZM",2033 +"2033-03-08","International Women's Day","ZM",2033 +"2033-03-12","Youth Day","ZM",2033 +"2033-04-15","Good Friday","ZM",2033 +"2033-04-16","Holy Saturday","ZM",2033 +"2033-04-18","Easter Monday","ZM",2033 +"2033-04-28","Kenneth Kaunda Day","ZM",2033 +"2033-05-01","Labour Day","ZM",2033 +"2033-05-02","Labour Day (Observed)","ZM",2033 +"2033-05-25","Africa Freedom Day","ZM",2033 +"2033-07-04","Heroes' Day","ZM",2033 +"2033-07-05","Unity Day","ZM",2033 +"2033-08-01","Farmers' Day","ZM",2033 +"2033-10-18","National Prayer Day","ZM",2033 +"2033-10-24","Independence Day","ZM",2033 +"2033-12-25","Christmas Day","ZM",2033 +"2033-12-26","Christmas Day (Observed)","ZM",2033 +"2034-01-01","New Year's Day","ZM",2034 +"2034-01-02","New Year's Day (Observed)","ZM",2034 +"2034-03-08","International Women's Day","ZM",2034 +"2034-03-12","Youth Day","ZM",2034 +"2034-03-13","Youth Day (Observed)","ZM",2034 +"2034-04-07","Good Friday","ZM",2034 +"2034-04-08","Holy Saturday","ZM",2034 +"2034-04-10","Easter Monday","ZM",2034 +"2034-04-28","Kenneth Kaunda Day","ZM",2034 +"2034-05-01","Labour Day","ZM",2034 +"2034-05-25","Africa Freedom Day","ZM",2034 +"2034-07-03","Heroes' Day","ZM",2034 +"2034-07-04","Unity Day","ZM",2034 +"2034-08-07","Farmers' Day","ZM",2034 +"2034-10-18","National Prayer Day","ZM",2034 +"2034-10-24","Independence Day","ZM",2034 +"2034-12-25","Christmas Day","ZM",2034 +"2035-01-01","New Year's Day","ZM",2035 +"2035-03-08","International Women's Day","ZM",2035 +"2035-03-12","Youth Day","ZM",2035 +"2035-03-23","Good Friday","ZM",2035 +"2035-03-24","Holy Saturday","ZM",2035 +"2035-03-26","Easter Monday","ZM",2035 +"2035-04-28","Kenneth Kaunda Day","ZM",2035 +"2035-05-01","Labour Day","ZM",2035 +"2035-05-25","Africa Freedom Day","ZM",2035 +"2035-07-02","Heroes' Day","ZM",2035 +"2035-07-03","Unity Day","ZM",2035 +"2035-08-06","Farmers' Day","ZM",2035 +"2035-10-18","National Prayer Day","ZM",2035 +"2035-10-24","Independence Day","ZM",2035 +"2035-12-25","Christmas Day","ZM",2035 +"2036-01-01","New Year's Day","ZM",2036 +"2036-03-08","International Women's Day","ZM",2036 +"2036-03-12","Youth Day","ZM",2036 +"2036-04-11","Good Friday","ZM",2036 +"2036-04-12","Holy Saturday","ZM",2036 +"2036-04-14","Easter Monday","ZM",2036 +"2036-04-28","Kenneth Kaunda Day","ZM",2036 +"2036-05-01","Labour Day","ZM",2036 +"2036-05-25","Africa Freedom Day","ZM",2036 +"2036-05-26","Africa Freedom Day (Observed)","ZM",2036 +"2036-07-07","Heroes' Day","ZM",2036 +"2036-07-08","Unity Day","ZM",2036 +"2036-08-04","Farmers' Day","ZM",2036 +"2036-10-18","National Prayer Day","ZM",2036 +"2036-10-24","Independence Day","ZM",2036 +"2036-12-25","Christmas Day","ZM",2036 +"2037-01-01","New Year's Day","ZM",2037 +"2037-03-08","International Women's Day","ZM",2037 +"2037-03-09","International Women's Day (Observed)","ZM",2037 +"2037-03-12","Youth Day","ZM",2037 +"2037-04-03","Good Friday","ZM",2037 +"2037-04-04","Holy Saturday","ZM",2037 +"2037-04-06","Easter Monday","ZM",2037 +"2037-04-28","Kenneth Kaunda Day","ZM",2037 +"2037-05-01","Labour Day","ZM",2037 +"2037-05-25","Africa Freedom Day","ZM",2037 +"2037-07-06","Heroes' Day","ZM",2037 +"2037-07-07","Unity Day","ZM",2037 +"2037-08-03","Farmers' Day","ZM",2037 +"2037-10-18","National Prayer Day","ZM",2037 +"2037-10-19","National Prayer Day (Observed)","ZM",2037 +"2037-10-24","Independence Day","ZM",2037 +"2037-12-25","Christmas Day","ZM",2037 +"2038-01-01","New Year's Day","ZM",2038 +"2038-03-08","International Women's Day","ZM",2038 +"2038-03-12","Youth Day","ZM",2038 +"2038-04-23","Good Friday","ZM",2038 +"2038-04-24","Holy Saturday","ZM",2038 +"2038-04-26","Easter Monday","ZM",2038 +"2038-04-28","Kenneth Kaunda Day","ZM",2038 +"2038-05-01","Labour Day","ZM",2038 +"2038-05-25","Africa Freedom Day","ZM",2038 +"2038-07-05","Heroes' Day","ZM",2038 +"2038-07-06","Unity Day","ZM",2038 +"2038-08-02","Farmers' Day","ZM",2038 +"2038-10-18","National Prayer Day","ZM",2038 +"2038-10-24","Independence Day","ZM",2038 +"2038-10-25","Independence Day (Observed)","ZM",2038 +"2038-12-25","Christmas Day","ZM",2038 +"2039-01-01","New Year's Day","ZM",2039 +"2039-03-08","International Women's Day","ZM",2039 +"2039-03-12","Youth Day","ZM",2039 +"2039-04-08","Good Friday","ZM",2039 +"2039-04-09","Holy Saturday","ZM",2039 +"2039-04-11","Easter Monday","ZM",2039 +"2039-04-28","Kenneth Kaunda Day","ZM",2039 +"2039-05-01","Labour Day","ZM",2039 +"2039-05-02","Labour Day (Observed)","ZM",2039 +"2039-05-25","Africa Freedom Day","ZM",2039 +"2039-07-04","Heroes' Day","ZM",2039 +"2039-07-05","Unity Day","ZM",2039 +"2039-08-01","Farmers' Day","ZM",2039 +"2039-10-18","National Prayer Day","ZM",2039 +"2039-10-24","Independence Day","ZM",2039 +"2039-12-25","Christmas Day","ZM",2039 +"2039-12-26","Christmas Day (Observed)","ZM",2039 +"2040-01-01","New Year's Day","ZM",2040 +"2040-01-02","New Year's Day (Observed)","ZM",2040 +"2040-03-08","International Women's Day","ZM",2040 +"2040-03-12","Youth Day","ZM",2040 +"2040-03-30","Good Friday","ZM",2040 +"2040-03-31","Holy Saturday","ZM",2040 +"2040-04-02","Easter Monday","ZM",2040 +"2040-04-28","Kenneth Kaunda Day","ZM",2040 +"2040-05-01","Labour Day","ZM",2040 +"2040-05-25","Africa Freedom Day","ZM",2040 +"2040-07-02","Heroes' Day","ZM",2040 +"2040-07-03","Unity Day","ZM",2040 +"2040-08-06","Farmers' Day","ZM",2040 +"2040-10-18","National Prayer Day","ZM",2040 +"2040-10-24","Independence Day","ZM",2040 +"2040-12-25","Christmas Day","ZM",2040 +"2041-01-01","New Year's Day","ZM",2041 +"2041-03-08","International Women's Day","ZM",2041 +"2041-03-12","Youth Day","ZM",2041 +"2041-04-19","Good Friday","ZM",2041 +"2041-04-20","Holy Saturday","ZM",2041 +"2041-04-22","Easter Monday","ZM",2041 +"2041-04-28","Kenneth Kaunda Day","ZM",2041 +"2041-04-29","Kenneth Kaunda Day (Observed)","ZM",2041 +"2041-05-01","Labour Day","ZM",2041 +"2041-05-25","Africa Freedom Day","ZM",2041 +"2041-07-01","Heroes' Day","ZM",2041 +"2041-07-02","Unity Day","ZM",2041 +"2041-08-05","Farmers' Day","ZM",2041 +"2041-10-18","National Prayer Day","ZM",2041 +"2041-10-24","Independence Day","ZM",2041 +"2041-12-25","Christmas Day","ZM",2041 +"2042-01-01","New Year's Day","ZM",2042 +"2042-03-08","International Women's Day","ZM",2042 +"2042-03-12","Youth Day","ZM",2042 +"2042-04-04","Good Friday","ZM",2042 +"2042-04-05","Holy Saturday","ZM",2042 +"2042-04-07","Easter Monday","ZM",2042 +"2042-04-28","Kenneth Kaunda Day","ZM",2042 +"2042-05-01","Labour Day","ZM",2042 +"2042-05-25","Africa Freedom Day","ZM",2042 +"2042-05-26","Africa Freedom Day (Observed)","ZM",2042 +"2042-07-07","Heroes' Day","ZM",2042 +"2042-07-08","Unity Day","ZM",2042 +"2042-08-04","Farmers' Day","ZM",2042 +"2042-10-18","National Prayer Day","ZM",2042 +"2042-10-24","Independence Day","ZM",2042 +"2042-12-25","Christmas Day","ZM",2042 +"2043-01-01","New Year's Day","ZM",2043 +"2043-03-08","International Women's Day","ZM",2043 +"2043-03-09","International Women's Day (Observed)","ZM",2043 +"2043-03-12","Youth Day","ZM",2043 +"2043-03-27","Good Friday","ZM",2043 +"2043-03-28","Holy Saturday","ZM",2043 +"2043-03-30","Easter Monday","ZM",2043 +"2043-04-28","Kenneth Kaunda Day","ZM",2043 +"2043-05-01","Labour Day","ZM",2043 +"2043-05-25","Africa Freedom Day","ZM",2043 +"2043-07-06","Heroes' Day","ZM",2043 +"2043-07-07","Unity Day","ZM",2043 +"2043-08-03","Farmers' Day","ZM",2043 +"2043-10-18","National Prayer Day","ZM",2043 +"2043-10-19","National Prayer Day (Observed)","ZM",2043 +"2043-10-24","Independence Day","ZM",2043 +"2043-12-25","Christmas Day","ZM",2043 +"2044-01-01","New Year's Day","ZM",2044 +"2044-03-08","International Women's Day","ZM",2044 +"2044-03-12","Youth Day","ZM",2044 +"2044-04-15","Good Friday","ZM",2044 +"2044-04-16","Holy Saturday","ZM",2044 +"2044-04-18","Easter Monday","ZM",2044 +"2044-04-28","Kenneth Kaunda Day","ZM",2044 +"2044-05-01","Labour Day","ZM",2044 +"2044-05-02","Labour Day (Observed)","ZM",2044 +"2044-05-25","Africa Freedom Day","ZM",2044 +"2044-07-04","Heroes' Day","ZM",2044 +"2044-07-05","Unity Day","ZM",2044 +"2044-08-01","Farmers' Day","ZM",2044 +"2044-10-18","National Prayer Day","ZM",2044 +"2044-10-24","Independence Day","ZM",2044 +"2044-12-25","Christmas Day","ZM",2044 +"2044-12-26","Christmas Day (Observed)","ZM",2044 +"1995-01-01","New Year's Day","ZW",1995 +"1995-01-02","New Year's Day (Observed)","ZW",1995 +"1995-04-14","Good Friday","ZW",1995 +"1995-04-15","Easter Saturday","ZW",1995 +"1995-04-17","Easter Monday","ZW",1995 +"1995-04-18","Independence Day","ZW",1995 +"1995-05-01","Workers' Day","ZW",1995 +"1995-05-25","Africa Day","ZW",1995 +"1995-08-14","Zimbabwe Heroes' Day","ZW",1995 +"1995-08-15","Defense Forces Day","ZW",1995 +"1995-12-22","Unity Day","ZW",1995 +"1995-12-25","Christmas Day","ZW",1995 +"1995-12-26","Boxing Day","ZW",1995 +"1996-01-01","New Year's Day","ZW",1996 +"1996-04-05","Good Friday","ZW",1996 +"1996-04-06","Easter Saturday","ZW",1996 +"1996-04-08","Easter Monday","ZW",1996 +"1996-04-18","Independence Day","ZW",1996 +"1996-05-01","Workers' Day","ZW",1996 +"1996-05-25","Africa Day","ZW",1996 +"1996-08-12","Zimbabwe Heroes' Day","ZW",1996 +"1996-08-13","Defense Forces Day","ZW",1996 +"1996-12-22","Unity Day","ZW",1996 +"1996-12-23","Unity Day (Observed)","ZW",1996 +"1996-12-25","Christmas Day","ZW",1996 +"1996-12-26","Boxing Day","ZW",1996 +"1997-01-01","New Year's Day","ZW",1997 +"1997-03-28","Good Friday","ZW",1997 +"1997-03-29","Easter Saturday","ZW",1997 +"1997-03-31","Easter Monday","ZW",1997 +"1997-04-18","Independence Day","ZW",1997 +"1997-05-01","Workers' Day","ZW",1997 +"1997-05-25","Africa Day","ZW",1997 +"1997-05-26","Africa Day (Observed)","ZW",1997 +"1997-08-11","Zimbabwe Heroes' Day","ZW",1997 +"1997-08-12","Defense Forces Day","ZW",1997 +"1997-12-22","Unity Day","ZW",1997 +"1997-12-25","Christmas Day","ZW",1997 +"1997-12-26","Boxing Day","ZW",1997 +"1998-01-01","New Year's Day","ZW",1998 +"1998-04-10","Good Friday","ZW",1998 +"1998-04-11","Easter Saturday","ZW",1998 +"1998-04-13","Easter Monday","ZW",1998 +"1998-04-18","Independence Day","ZW",1998 +"1998-05-01","Workers' Day","ZW",1998 +"1998-05-25","Africa Day","ZW",1998 +"1998-08-10","Zimbabwe Heroes' Day","ZW",1998 +"1998-08-11","Defense Forces Day","ZW",1998 +"1998-12-22","Unity Day","ZW",1998 +"1998-12-25","Christmas Day","ZW",1998 +"1998-12-26","Boxing Day","ZW",1998 +"1999-01-01","New Year's Day","ZW",1999 +"1999-04-02","Good Friday","ZW",1999 +"1999-04-03","Easter Saturday","ZW",1999 +"1999-04-05","Easter Monday","ZW",1999 +"1999-04-18","Independence Day","ZW",1999 +"1999-04-19","Independence Day (Observed)","ZW",1999 +"1999-05-01","Workers' Day","ZW",1999 +"1999-05-25","Africa Day","ZW",1999 +"1999-08-09","Zimbabwe Heroes' Day","ZW",1999 +"1999-08-10","Defense Forces Day","ZW",1999 +"1999-12-22","Unity Day","ZW",1999 +"1999-12-25","Christmas Day","ZW",1999 +"1999-12-26","Boxing Day","ZW",1999 +"1999-12-27","Boxing Day (Observed)","ZW",1999 +"2000-01-01","New Year's Day","ZW",2000 +"2000-04-18","Independence Day","ZW",2000 +"2000-04-21","Good Friday","ZW",2000 +"2000-04-22","Easter Saturday","ZW",2000 +"2000-04-24","Easter Monday","ZW",2000 +"2000-05-01","Workers' Day","ZW",2000 +"2000-05-25","Africa Day","ZW",2000 +"2000-08-14","Zimbabwe Heroes' Day","ZW",2000 +"2000-08-15","Defense Forces Day","ZW",2000 +"2000-12-22","Unity Day","ZW",2000 +"2000-12-25","Christmas Day","ZW",2000 +"2000-12-26","Boxing Day","ZW",2000 +"2001-01-01","New Year's Day","ZW",2001 +"2001-04-13","Good Friday","ZW",2001 +"2001-04-14","Easter Saturday","ZW",2001 +"2001-04-16","Easter Monday","ZW",2001 +"2001-04-18","Independence Day","ZW",2001 +"2001-05-01","Workers' Day","ZW",2001 +"2001-05-25","Africa Day","ZW",2001 +"2001-08-13","Zimbabwe Heroes' Day","ZW",2001 +"2001-08-14","Defense Forces Day","ZW",2001 +"2001-12-22","Unity Day","ZW",2001 +"2001-12-25","Christmas Day","ZW",2001 +"2001-12-26","Boxing Day","ZW",2001 +"2002-01-01","New Year's Day","ZW",2002 +"2002-03-29","Good Friday","ZW",2002 +"2002-03-30","Easter Saturday","ZW",2002 +"2002-04-01","Easter Monday","ZW",2002 +"2002-04-18","Independence Day","ZW",2002 +"2002-05-01","Workers' Day","ZW",2002 +"2002-05-25","Africa Day","ZW",2002 +"2002-08-12","Zimbabwe Heroes' Day","ZW",2002 +"2002-08-13","Defense Forces Day","ZW",2002 +"2002-12-22","Unity Day","ZW",2002 +"2002-12-23","Unity Day (Observed)","ZW",2002 +"2002-12-25","Christmas Day","ZW",2002 +"2002-12-26","Boxing Day","ZW",2002 +"2003-01-01","New Year's Day","ZW",2003 +"2003-04-18","Good Friday","ZW",2003 +"2003-04-18","Independence Day","ZW",2003 +"2003-04-19","Easter Saturday","ZW",2003 +"2003-04-21","Easter Monday","ZW",2003 +"2003-05-01","Workers' Day","ZW",2003 +"2003-05-25","Africa Day","ZW",2003 +"2003-05-26","Africa Day (Observed)","ZW",2003 +"2003-08-11","Zimbabwe Heroes' Day","ZW",2003 +"2003-08-12","Defense Forces Day","ZW",2003 +"2003-12-22","Unity Day","ZW",2003 +"2003-12-25","Christmas Day","ZW",2003 +"2003-12-26","Boxing Day","ZW",2003 +"2004-01-01","New Year's Day","ZW",2004 +"2004-04-09","Good Friday","ZW",2004 +"2004-04-10","Easter Saturday","ZW",2004 +"2004-04-12","Easter Monday","ZW",2004 +"2004-04-18","Independence Day","ZW",2004 +"2004-04-19","Independence Day (Observed)","ZW",2004 +"2004-05-01","Workers' Day","ZW",2004 +"2004-05-25","Africa Day","ZW",2004 +"2004-08-09","Zimbabwe Heroes' Day","ZW",2004 +"2004-08-10","Defense Forces Day","ZW",2004 +"2004-12-22","Unity Day","ZW",2004 +"2004-12-25","Christmas Day","ZW",2004 +"2004-12-26","Boxing Day","ZW",2004 +"2004-12-27","Boxing Day (Observed)","ZW",2004 +"2005-01-01","New Year's Day","ZW",2005 +"2005-03-25","Good Friday","ZW",2005 +"2005-03-26","Easter Saturday","ZW",2005 +"2005-03-28","Easter Monday","ZW",2005 +"2005-04-18","Independence Day","ZW",2005 +"2005-05-01","Workers' Day","ZW",2005 +"2005-05-02","Workers' Day (Observed)","ZW",2005 +"2005-05-25","Africa Day","ZW",2005 +"2005-08-08","Zimbabwe Heroes' Day","ZW",2005 +"2005-08-09","Defense Forces Day","ZW",2005 +"2005-12-22","Unity Day","ZW",2005 +"2005-12-25","Christmas Day","ZW",2005 +"2005-12-26","Boxing Day","ZW",2005 +"2005-12-27","Christmas Day (Observed)","ZW",2005 +"2006-01-01","New Year's Day","ZW",2006 +"2006-01-02","New Year's Day (Observed)","ZW",2006 +"2006-04-14","Good Friday","ZW",2006 +"2006-04-15","Easter Saturday","ZW",2006 +"2006-04-17","Easter Monday","ZW",2006 +"2006-04-18","Independence Day","ZW",2006 +"2006-05-01","Workers' Day","ZW",2006 +"2006-05-25","Africa Day","ZW",2006 +"2006-08-14","Zimbabwe Heroes' Day","ZW",2006 +"2006-08-15","Defense Forces Day","ZW",2006 +"2006-12-22","Unity Day","ZW",2006 +"2006-12-25","Christmas Day","ZW",2006 +"2006-12-26","Boxing Day","ZW",2006 +"2007-01-01","New Year's Day","ZW",2007 +"2007-04-06","Good Friday","ZW",2007 +"2007-04-07","Easter Saturday","ZW",2007 +"2007-04-09","Easter Monday","ZW",2007 +"2007-04-18","Independence Day","ZW",2007 +"2007-05-01","Workers' Day","ZW",2007 +"2007-05-25","Africa Day","ZW",2007 +"2007-08-13","Zimbabwe Heroes' Day","ZW",2007 +"2007-08-14","Defense Forces Day","ZW",2007 +"2007-12-22","Unity Day","ZW",2007 +"2007-12-25","Christmas Day","ZW",2007 +"2007-12-26","Boxing Day","ZW",2007 +"2008-01-01","New Year's Day","ZW",2008 +"2008-03-21","Good Friday","ZW",2008 +"2008-03-22","Easter Saturday","ZW",2008 +"2008-03-24","Easter Monday","ZW",2008 +"2008-04-18","Independence Day","ZW",2008 +"2008-05-01","Workers' Day","ZW",2008 +"2008-05-25","Africa Day","ZW",2008 +"2008-05-26","Africa Day (Observed)","ZW",2008 +"2008-08-11","Zimbabwe Heroes' Day","ZW",2008 +"2008-08-12","Defense Forces Day","ZW",2008 +"2008-12-22","Unity Day","ZW",2008 +"2008-12-25","Christmas Day","ZW",2008 +"2008-12-26","Boxing Day","ZW",2008 +"2009-01-01","New Year's Day","ZW",2009 +"2009-04-10","Good Friday","ZW",2009 +"2009-04-11","Easter Saturday","ZW",2009 +"2009-04-13","Easter Monday","ZW",2009 +"2009-04-18","Independence Day","ZW",2009 +"2009-05-01","Workers' Day","ZW",2009 +"2009-05-25","Africa Day","ZW",2009 +"2009-08-10","Zimbabwe Heroes' Day","ZW",2009 +"2009-08-11","Defense Forces Day","ZW",2009 +"2009-12-22","Unity Day","ZW",2009 +"2009-12-25","Christmas Day","ZW",2009 +"2009-12-26","Boxing Day","ZW",2009 +"2010-01-01","New Year's Day","ZW",2010 +"2010-04-02","Good Friday","ZW",2010 +"2010-04-03","Easter Saturday","ZW",2010 +"2010-04-05","Easter Monday","ZW",2010 +"2010-04-18","Independence Day","ZW",2010 +"2010-04-19","Independence Day (Observed)","ZW",2010 +"2010-05-01","Workers' Day","ZW",2010 +"2010-05-25","Africa Day","ZW",2010 +"2010-08-09","Zimbabwe Heroes' Day","ZW",2010 +"2010-08-10","Defense Forces Day","ZW",2010 +"2010-12-22","Unity Day","ZW",2010 +"2010-12-25","Christmas Day","ZW",2010 +"2010-12-26","Boxing Day","ZW",2010 +"2010-12-27","Boxing Day (Observed)","ZW",2010 +"2011-01-01","New Year's Day","ZW",2011 +"2011-04-18","Independence Day","ZW",2011 +"2011-04-22","Good Friday","ZW",2011 +"2011-04-23","Easter Saturday","ZW",2011 +"2011-04-25","Easter Monday","ZW",2011 +"2011-05-01","Workers' Day","ZW",2011 +"2011-05-02","Workers' Day (Observed)","ZW",2011 +"2011-05-25","Africa Day","ZW",2011 +"2011-08-08","Zimbabwe Heroes' Day","ZW",2011 +"2011-08-09","Defense Forces Day","ZW",2011 +"2011-12-22","Unity Day","ZW",2011 +"2011-12-25","Christmas Day","ZW",2011 +"2011-12-26","Boxing Day","ZW",2011 +"2011-12-27","Christmas Day (Observed)","ZW",2011 +"2012-01-01","New Year's Day","ZW",2012 +"2012-01-02","New Year's Day (Observed)","ZW",2012 +"2012-04-06","Good Friday","ZW",2012 +"2012-04-07","Easter Saturday","ZW",2012 +"2012-04-09","Easter Monday","ZW",2012 +"2012-04-18","Independence Day","ZW",2012 +"2012-05-01","Workers' Day","ZW",2012 +"2012-05-25","Africa Day","ZW",2012 +"2012-08-13","Zimbabwe Heroes' Day","ZW",2012 +"2012-08-14","Defense Forces Day","ZW",2012 +"2012-12-22","Unity Day","ZW",2012 +"2012-12-25","Christmas Day","ZW",2012 +"2012-12-26","Boxing Day","ZW",2012 +"2013-01-01","New Year's Day","ZW",2013 +"2013-03-29","Good Friday","ZW",2013 +"2013-03-30","Easter Saturday","ZW",2013 +"2013-04-01","Easter Monday","ZW",2013 +"2013-04-18","Independence Day","ZW",2013 +"2013-05-01","Workers' Day","ZW",2013 +"2013-05-25","Africa Day","ZW",2013 +"2013-08-12","Zimbabwe Heroes' Day","ZW",2013 +"2013-08-13","Defense Forces Day","ZW",2013 +"2013-12-22","Unity Day","ZW",2013 +"2013-12-23","Unity Day (Observed)","ZW",2013 +"2013-12-25","Christmas Day","ZW",2013 +"2013-12-26","Boxing Day","ZW",2013 +"2014-01-01","New Year's Day","ZW",2014 +"2014-04-18","Good Friday","ZW",2014 +"2014-04-18","Independence Day","ZW",2014 +"2014-04-19","Easter Saturday","ZW",2014 +"2014-04-21","Easter Monday","ZW",2014 +"2014-05-01","Workers' Day","ZW",2014 +"2014-05-25","Africa Day","ZW",2014 +"2014-05-26","Africa Day (Observed)","ZW",2014 +"2014-08-11","Zimbabwe Heroes' Day","ZW",2014 +"2014-08-12","Defense Forces Day","ZW",2014 +"2014-12-22","Unity Day","ZW",2014 +"2014-12-25","Christmas Day","ZW",2014 +"2014-12-26","Boxing Day","ZW",2014 +"2015-01-01","New Year's Day","ZW",2015 +"2015-04-03","Good Friday","ZW",2015 +"2015-04-04","Easter Saturday","ZW",2015 +"2015-04-06","Easter Monday","ZW",2015 +"2015-04-18","Independence Day","ZW",2015 +"2015-05-01","Workers' Day","ZW",2015 +"2015-05-25","Africa Day","ZW",2015 +"2015-08-10","Zimbabwe Heroes' Day","ZW",2015 +"2015-08-11","Defense Forces Day","ZW",2015 +"2015-12-22","Unity Day","ZW",2015 +"2015-12-25","Christmas Day","ZW",2015 +"2015-12-26","Boxing Day","ZW",2015 +"2016-01-01","New Year's Day","ZW",2016 +"2016-03-25","Good Friday","ZW",2016 +"2016-03-26","Easter Saturday","ZW",2016 +"2016-03-28","Easter Monday","ZW",2016 +"2016-04-18","Independence Day","ZW",2016 +"2016-05-01","Workers' Day","ZW",2016 +"2016-05-02","Workers' Day (Observed)","ZW",2016 +"2016-05-25","Africa Day","ZW",2016 +"2016-08-08","Zimbabwe Heroes' Day","ZW",2016 +"2016-08-09","Defense Forces Day","ZW",2016 +"2016-12-22","Unity Day","ZW",2016 +"2016-12-25","Christmas Day","ZW",2016 +"2016-12-26","Boxing Day","ZW",2016 +"2016-12-27","Christmas Day (Observed)","ZW",2016 +"2017-01-01","New Year's Day","ZW",2017 +"2017-01-02","New Year's Day (Observed)","ZW",2017 +"2017-04-14","Good Friday","ZW",2017 +"2017-04-15","Easter Saturday","ZW",2017 +"2017-04-17","Easter Monday","ZW",2017 +"2017-04-18","Independence Day","ZW",2017 +"2017-05-01","Workers' Day","ZW",2017 +"2017-05-25","Africa Day","ZW",2017 +"2017-08-14","Zimbabwe Heroes' Day","ZW",2017 +"2017-08-15","Defense Forces Day","ZW",2017 +"2017-12-22","Unity Day","ZW",2017 +"2017-12-25","Christmas Day","ZW",2017 +"2017-12-26","Boxing Day","ZW",2017 +"2018-01-01","New Year's Day","ZW",2018 +"2018-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2018 +"2018-03-30","Good Friday","ZW",2018 +"2018-03-31","Easter Saturday","ZW",2018 +"2018-04-02","Easter Monday","ZW",2018 +"2018-04-18","Independence Day","ZW",2018 +"2018-05-01","Workers' Day","ZW",2018 +"2018-05-25","Africa Day","ZW",2018 +"2018-08-13","Zimbabwe Heroes' Day","ZW",2018 +"2018-08-14","Defense Forces Day","ZW",2018 +"2018-12-22","Unity Day","ZW",2018 +"2018-12-25","Christmas Day","ZW",2018 +"2018-12-26","Boxing Day","ZW",2018 +"2019-01-01","New Year's Day","ZW",2019 +"2019-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2019 +"2019-04-18","Independence Day","ZW",2019 +"2019-04-19","Good Friday","ZW",2019 +"2019-04-20","Easter Saturday","ZW",2019 +"2019-04-22","Easter Monday","ZW",2019 +"2019-05-01","Workers' Day","ZW",2019 +"2019-05-25","Africa Day","ZW",2019 +"2019-08-12","Zimbabwe Heroes' Day","ZW",2019 +"2019-08-13","Defense Forces Day","ZW",2019 +"2019-12-22","Unity Day","ZW",2019 +"2019-12-23","Unity Day (Observed)","ZW",2019 +"2019-12-25","Christmas Day","ZW",2019 +"2019-12-26","Boxing Day","ZW",2019 +"2020-01-01","New Year's Day","ZW",2020 +"2020-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2020 +"2020-04-10","Good Friday","ZW",2020 +"2020-04-11","Easter Saturday","ZW",2020 +"2020-04-13","Easter Monday","ZW",2020 +"2020-04-18","Independence Day","ZW",2020 +"2020-05-01","Workers' Day","ZW",2020 +"2020-05-25","Africa Day","ZW",2020 +"2020-08-10","Zimbabwe Heroes' Day","ZW",2020 +"2020-08-11","Defense Forces Day","ZW",2020 +"2020-12-22","Unity Day","ZW",2020 +"2020-12-25","Christmas Day","ZW",2020 +"2020-12-26","Boxing Day","ZW",2020 +"2021-01-01","New Year's Day","ZW",2021 +"2021-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2021 +"2021-02-22","Robert Gabriel Mugabe National Youth Day (Observed)","ZW",2021 +"2021-04-02","Good Friday","ZW",2021 +"2021-04-03","Easter Saturday","ZW",2021 +"2021-04-05","Easter Monday","ZW",2021 +"2021-04-18","Independence Day","ZW",2021 +"2021-04-19","Independence Day (Observed)","ZW",2021 +"2021-05-01","Workers' Day","ZW",2021 +"2021-05-25","Africa Day","ZW",2021 +"2021-08-09","Zimbabwe Heroes' Day","ZW",2021 +"2021-08-10","Defense Forces Day","ZW",2021 +"2021-12-22","Unity Day","ZW",2021 +"2021-12-25","Christmas Day","ZW",2021 +"2021-12-26","Boxing Day","ZW",2021 +"2021-12-27","Boxing Day (Observed)","ZW",2021 +"2022-01-01","New Year's Day","ZW",2022 +"2022-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2022 +"2022-04-15","Good Friday","ZW",2022 +"2022-04-16","Easter Saturday","ZW",2022 +"2022-04-18","Easter Monday","ZW",2022 +"2022-04-18","Independence Day","ZW",2022 +"2022-05-01","Workers' Day","ZW",2022 +"2022-05-02","Workers' Day (Observed)","ZW",2022 +"2022-05-25","Africa Day","ZW",2022 +"2022-08-08","Zimbabwe Heroes' Day","ZW",2022 +"2022-08-09","Defense Forces Day","ZW",2022 +"2022-12-22","Unity Day","ZW",2022 +"2022-12-25","Christmas Day","ZW",2022 +"2022-12-26","Boxing Day","ZW",2022 +"2022-12-27","Christmas Day (Observed)","ZW",2022 +"2023-01-01","New Year's Day","ZW",2023 +"2023-01-02","New Year's Day (Observed)","ZW",2023 +"2023-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2023 +"2023-04-07","Good Friday","ZW",2023 +"2023-04-08","Easter Saturday","ZW",2023 +"2023-04-10","Easter Monday","ZW",2023 +"2023-04-18","Independence Day","ZW",2023 +"2023-05-01","Workers' Day","ZW",2023 +"2023-05-25","Africa Day","ZW",2023 +"2023-08-14","Zimbabwe Heroes' Day","ZW",2023 +"2023-08-15","Defense Forces Day","ZW",2023 +"2023-12-22","Unity Day","ZW",2023 +"2023-12-25","Christmas Day","ZW",2023 +"2023-12-26","Boxing Day","ZW",2023 +"2024-01-01","New Year's Day","ZW",2024 +"2024-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2024 +"2024-03-29","Good Friday","ZW",2024 +"2024-03-30","Easter Saturday","ZW",2024 +"2024-04-01","Easter Monday","ZW",2024 +"2024-04-18","Independence Day","ZW",2024 +"2024-05-01","Workers' Day","ZW",2024 +"2024-05-25","Africa Day","ZW",2024 +"2024-08-12","Zimbabwe Heroes' Day","ZW",2024 +"2024-08-13","Defense Forces Day","ZW",2024 +"2024-12-22","Unity Day","ZW",2024 +"2024-12-23","Unity Day (Observed)","ZW",2024 +"2024-12-25","Christmas Day","ZW",2024 +"2024-12-26","Boxing Day","ZW",2024 +"2025-01-01","New Year's Day","ZW",2025 +"2025-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2025 +"2025-04-18","Good Friday","ZW",2025 +"2025-04-18","Independence Day","ZW",2025 +"2025-04-19","Easter Saturday","ZW",2025 +"2025-04-21","Easter Monday","ZW",2025 +"2025-05-01","Workers' Day","ZW",2025 +"2025-05-25","Africa Day","ZW",2025 +"2025-05-26","Africa Day (Observed)","ZW",2025 +"2025-08-11","Zimbabwe Heroes' Day","ZW",2025 +"2025-08-12","Defense Forces Day","ZW",2025 +"2025-12-22","Unity Day","ZW",2025 +"2025-12-25","Christmas Day","ZW",2025 +"2025-12-26","Boxing Day","ZW",2025 +"2026-01-01","New Year's Day","ZW",2026 +"2026-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2026 +"2026-04-03","Good Friday","ZW",2026 +"2026-04-04","Easter Saturday","ZW",2026 +"2026-04-06","Easter Monday","ZW",2026 +"2026-04-18","Independence Day","ZW",2026 +"2026-05-01","Workers' Day","ZW",2026 +"2026-05-25","Africa Day","ZW",2026 +"2026-08-10","Zimbabwe Heroes' Day","ZW",2026 +"2026-08-11","Defense Forces Day","ZW",2026 +"2026-12-22","Unity Day","ZW",2026 +"2026-12-25","Christmas Day","ZW",2026 +"2026-12-26","Boxing Day","ZW",2026 +"2027-01-01","New Year's Day","ZW",2027 +"2027-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2027 +"2027-02-22","Robert Gabriel Mugabe National Youth Day (Observed)","ZW",2027 +"2027-03-26","Good Friday","ZW",2027 +"2027-03-27","Easter Saturday","ZW",2027 +"2027-03-29","Easter Monday","ZW",2027 +"2027-04-18","Independence Day","ZW",2027 +"2027-04-19","Independence Day (Observed)","ZW",2027 +"2027-05-01","Workers' Day","ZW",2027 +"2027-05-25","Africa Day","ZW",2027 +"2027-08-09","Zimbabwe Heroes' Day","ZW",2027 +"2027-08-10","Defense Forces Day","ZW",2027 +"2027-12-22","Unity Day","ZW",2027 +"2027-12-25","Christmas Day","ZW",2027 +"2027-12-26","Boxing Day","ZW",2027 +"2027-12-27","Boxing Day (Observed)","ZW",2027 +"2028-01-01","New Year's Day","ZW",2028 +"2028-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2028 +"2028-04-14","Good Friday","ZW",2028 +"2028-04-15","Easter Saturday","ZW",2028 +"2028-04-17","Easter Monday","ZW",2028 +"2028-04-18","Independence Day","ZW",2028 +"2028-05-01","Workers' Day","ZW",2028 +"2028-05-25","Africa Day","ZW",2028 +"2028-08-14","Zimbabwe Heroes' Day","ZW",2028 +"2028-08-15","Defense Forces Day","ZW",2028 +"2028-12-22","Unity Day","ZW",2028 +"2028-12-25","Christmas Day","ZW",2028 +"2028-12-26","Boxing Day","ZW",2028 +"2029-01-01","New Year's Day","ZW",2029 +"2029-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2029 +"2029-03-30","Good Friday","ZW",2029 +"2029-03-31","Easter Saturday","ZW",2029 +"2029-04-02","Easter Monday","ZW",2029 +"2029-04-18","Independence Day","ZW",2029 +"2029-05-01","Workers' Day","ZW",2029 +"2029-05-25","Africa Day","ZW",2029 +"2029-08-13","Zimbabwe Heroes' Day","ZW",2029 +"2029-08-14","Defense Forces Day","ZW",2029 +"2029-12-22","Unity Day","ZW",2029 +"2029-12-25","Christmas Day","ZW",2029 +"2029-12-26","Boxing Day","ZW",2029 +"2030-01-01","New Year's Day","ZW",2030 +"2030-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2030 +"2030-04-18","Independence Day","ZW",2030 +"2030-04-19","Good Friday","ZW",2030 +"2030-04-20","Easter Saturday","ZW",2030 +"2030-04-22","Easter Monday","ZW",2030 +"2030-05-01","Workers' Day","ZW",2030 +"2030-05-25","Africa Day","ZW",2030 +"2030-08-12","Zimbabwe Heroes' Day","ZW",2030 +"2030-08-13","Defense Forces Day","ZW",2030 +"2030-12-22","Unity Day","ZW",2030 +"2030-12-23","Unity Day (Observed)","ZW",2030 +"2030-12-25","Christmas Day","ZW",2030 +"2030-12-26","Boxing Day","ZW",2030 +"2031-01-01","New Year's Day","ZW",2031 +"2031-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2031 +"2031-04-11","Good Friday","ZW",2031 +"2031-04-12","Easter Saturday","ZW",2031 +"2031-04-14","Easter Monday","ZW",2031 +"2031-04-18","Independence Day","ZW",2031 +"2031-05-01","Workers' Day","ZW",2031 +"2031-05-25","Africa Day","ZW",2031 +"2031-05-26","Africa Day (Observed)","ZW",2031 +"2031-08-11","Zimbabwe Heroes' Day","ZW",2031 +"2031-08-12","Defense Forces Day","ZW",2031 +"2031-12-22","Unity Day","ZW",2031 +"2031-12-25","Christmas Day","ZW",2031 +"2031-12-26","Boxing Day","ZW",2031 +"2032-01-01","New Year's Day","ZW",2032 +"2032-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2032 +"2032-03-26","Good Friday","ZW",2032 +"2032-03-27","Easter Saturday","ZW",2032 +"2032-03-29","Easter Monday","ZW",2032 +"2032-04-18","Independence Day","ZW",2032 +"2032-04-19","Independence Day (Observed)","ZW",2032 +"2032-05-01","Workers' Day","ZW",2032 +"2032-05-25","Africa Day","ZW",2032 +"2032-08-09","Zimbabwe Heroes' Day","ZW",2032 +"2032-08-10","Defense Forces Day","ZW",2032 +"2032-12-22","Unity Day","ZW",2032 +"2032-12-25","Christmas Day","ZW",2032 +"2032-12-26","Boxing Day","ZW",2032 +"2032-12-27","Boxing Day (Observed)","ZW",2032 +"2033-01-01","New Year's Day","ZW",2033 +"2033-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2033 +"2033-04-15","Good Friday","ZW",2033 +"2033-04-16","Easter Saturday","ZW",2033 +"2033-04-18","Easter Monday","ZW",2033 +"2033-04-18","Independence Day","ZW",2033 +"2033-05-01","Workers' Day","ZW",2033 +"2033-05-02","Workers' Day (Observed)","ZW",2033 +"2033-05-25","Africa Day","ZW",2033 +"2033-08-08","Zimbabwe Heroes' Day","ZW",2033 +"2033-08-09","Defense Forces Day","ZW",2033 +"2033-12-22","Unity Day","ZW",2033 +"2033-12-25","Christmas Day","ZW",2033 +"2033-12-26","Boxing Day","ZW",2033 +"2033-12-27","Christmas Day (Observed)","ZW",2033 +"2034-01-01","New Year's Day","ZW",2034 +"2034-01-02","New Year's Day (Observed)","ZW",2034 +"2034-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2034 +"2034-04-07","Good Friday","ZW",2034 +"2034-04-08","Easter Saturday","ZW",2034 +"2034-04-10","Easter Monday","ZW",2034 +"2034-04-18","Independence Day","ZW",2034 +"2034-05-01","Workers' Day","ZW",2034 +"2034-05-25","Africa Day","ZW",2034 +"2034-08-14","Zimbabwe Heroes' Day","ZW",2034 +"2034-08-15","Defense Forces Day","ZW",2034 +"2034-12-22","Unity Day","ZW",2034 +"2034-12-25","Christmas Day","ZW",2034 +"2034-12-26","Boxing Day","ZW",2034 +"2035-01-01","New Year's Day","ZW",2035 +"2035-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2035 +"2035-03-23","Good Friday","ZW",2035 +"2035-03-24","Easter Saturday","ZW",2035 +"2035-03-26","Easter Monday","ZW",2035 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Mugabe National Youth Day","ZW",2037 +"2037-04-03","Good Friday","ZW",2037 +"2037-04-04","Easter Saturday","ZW",2037 +"2037-04-06","Easter Monday","ZW",2037 +"2037-04-18","Independence Day","ZW",2037 +"2037-05-01","Workers' Day","ZW",2037 +"2037-05-25","Africa Day","ZW",2037 +"2037-08-10","Zimbabwe Heroes' Day","ZW",2037 +"2037-08-11","Defense Forces Day","ZW",2037 +"2037-12-22","Unity Day","ZW",2037 +"2037-12-25","Christmas Day","ZW",2037 +"2037-12-26","Boxing Day","ZW",2037 +"2038-01-01","New Year's Day","ZW",2038 +"2038-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2038 +"2038-02-22","Robert Gabriel Mugabe National Youth Day (Observed)","ZW",2038 +"2038-04-18","Independence Day","ZW",2038 +"2038-04-19","Independence Day (Observed)","ZW",2038 +"2038-04-23","Good Friday","ZW",2038 +"2038-04-24","Easter Saturday","ZW",2038 +"2038-04-26","Easter Monday","ZW",2038 +"2038-05-01","Workers' Day","ZW",2038 +"2038-05-25","Africa Day","ZW",2038 +"2038-08-09","Zimbabwe Heroes' Day","ZW",2038 +"2038-08-10","Defense Forces Day","ZW",2038 +"2038-12-22","Unity Day","ZW",2038 +"2038-12-25","Christmas Day","ZW",2038 +"2038-12-26","Boxing Day","ZW",2038 +"2038-12-27","Boxing Day (Observed)","ZW",2038 +"2039-01-01","New Year's Day","ZW",2039 +"2039-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2039 +"2039-04-08","Good Friday","ZW",2039 +"2039-04-09","Easter Saturday","ZW",2039 +"2039-04-11","Easter Monday","ZW",2039 +"2039-04-18","Independence Day","ZW",2039 +"2039-05-01","Workers' Day","ZW",2039 +"2039-05-02","Workers' Day (Observed)","ZW",2039 +"2039-05-25","Africa Day","ZW",2039 +"2039-08-08","Zimbabwe Heroes' Day","ZW",2039 +"2039-08-09","Defense Forces Day","ZW",2039 +"2039-12-22","Unity Day","ZW",2039 +"2039-12-25","Christmas Day","ZW",2039 +"2039-12-26","Boxing Day","ZW",2039 +"2039-12-27","Christmas Day (Observed)","ZW",2039 +"2040-01-01","New Year's Day","ZW",2040 +"2040-01-02","New Year's Day (Observed)","ZW",2040 +"2040-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2040 +"2040-03-30","Good Friday","ZW",2040 +"2040-03-31","Easter Saturday","ZW",2040 +"2040-04-02","Easter Monday","ZW",2040 +"2040-04-18","Independence Day","ZW",2040 +"2040-05-01","Workers' Day","ZW",2040 +"2040-05-25","Africa Day","ZW",2040 +"2040-08-13","Zimbabwe Heroes' Day","ZW",2040 +"2040-08-14","Defense Forces Day","ZW",2040 +"2040-12-22","Unity Day","ZW",2040 +"2040-12-25","Christmas Day","ZW",2040 +"2040-12-26","Boxing Day","ZW",2040 +"2041-01-01","New Year's Day","ZW",2041 +"2041-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2041 +"2041-04-18","Independence Day","ZW",2041 +"2041-04-19","Good Friday","ZW",2041 +"2041-04-20","Easter Saturday","ZW",2041 +"2041-04-22","Easter Monday","ZW",2041 +"2041-05-01","Workers' Day","ZW",2041 +"2041-05-25","Africa Day","ZW",2041 +"2041-08-12","Zimbabwe Heroes' Day","ZW",2041 +"2041-08-13","Defense Forces Day","ZW",2041 +"2041-12-22","Unity Day","ZW",2041 +"2041-12-23","Unity Day (Observed)","ZW",2041 +"2041-12-25","Christmas Day","ZW",2041 +"2041-12-26","Boxing Day","ZW",2041 +"2042-01-01","New Year's Day","ZW",2042 +"2042-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2042 +"2042-04-04","Good Friday","ZW",2042 +"2042-04-05","Easter Saturday","ZW",2042 +"2042-04-07","Easter Monday","ZW",2042 +"2042-04-18","Independence Day","ZW",2042 +"2042-05-01","Workers' Day","ZW",2042 +"2042-05-25","Africa Day","ZW",2042 +"2042-05-26","Africa Day (Observed)","ZW",2042 +"2042-08-11","Zimbabwe Heroes' Day","ZW",2042 +"2042-08-12","Defense Forces Day","ZW",2042 +"2042-12-22","Unity Day","ZW",2042 +"2042-12-25","Christmas Day","ZW",2042 +"2042-12-26","Boxing Day","ZW",2042 +"2043-01-01","New Year's Day","ZW",2043 +"2043-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2043 +"2043-03-27","Good Friday","ZW",2043 +"2043-03-28","Easter Saturday","ZW",2043 +"2043-03-30","Easter Monday","ZW",2043 +"2043-04-18","Independence Day","ZW",2043 +"2043-05-01","Workers' Day","ZW",2043 +"2043-05-25","Africa Day","ZW",2043 +"2043-08-10","Zimbabwe Heroes' Day","ZW",2043 +"2043-08-11","Defense Forces Day","ZW",2043 +"2043-12-22","Unity Day","ZW",2043 +"2043-12-25","Christmas Day","ZW",2043 +"2043-12-26","Boxing Day","ZW",2043 +"2044-01-01","New Year's Day","ZW",2044 +"2044-02-21","Robert Gabriel Mugabe National Youth Day","ZW",2044 +"2044-02-22","Robert Gabriel Mugabe National Youth Day (Observed)","ZW",2044 +"2044-04-15","Good Friday","ZW",2044 +"2044-04-16","Easter Saturday","ZW",2044 +"2044-04-18","Easter Monday","ZW",2044 +"2044-04-18","Independence Day","ZW",2044 +"2044-05-01","Workers' Day","ZW",2044 +"2044-05-02","Workers' Day (Observed)","ZW",2044 +"2044-05-25","Africa Day","ZW",2044 +"2044-08-08","Zimbabwe Heroes' Day","ZW",2044 +"2044-08-09","Defense Forces Day","ZW",2044 +"2044-12-22","Unity Day","ZW",2044 +"2044-12-25","Christmas Day","ZW",2044 +"2044-12-26","Boxing Day","ZW",2044 +"2044-12-27","Christmas Day (Observed)","ZW",2044 diff --git a/python/src/robyn/tutorials/resources/dt_simulated_weekly.csv b/python/src/robyn/tutorials/resources/dt_simulated_weekly.csv new file mode 100644 index 000000000..494d4d3fd --- /dev/null +++ b/python/src/robyn/tutorials/resources/dt_simulated_weekly.csv @@ -0,0 +1,209 @@ +"DATE","revenue","tv_S","ooh_S","print_S","facebook_I","search_clicks_P","search_S","competitor_sales_B","facebook_S","events","newsletter" +2015-11-23,2754371.66666667,22358.3466666667,0,12728.4888888889,24301284.2375304,0,0,8125009,7607.1329148046,"na",19401.6538461538 +2015-11-30,2584276.66666667,28613.4533333333,0,0,5527033.1817753,9837.2384857852,4133.33333333333,7901549,1141.95245035415,"na",14791 +2015-12-07,2547386.66666667,0,132278.4,453.866666666667,16651591.2234904,12044.1196528263,3786.66666666667,8300197,4256.37537782657,"na",14544 +2015-12-14,2875220,83450.3066666667,0,17680,10549765.6762647,12268.0703194346,4253.33333333333,8122883,2800.49067685105,"na",2800 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This notebook demonstrates how to use Robyn to build and analyze marketing mix models.\n", + "\n", + "This notebook demonstrates the basic workflow of using Robyn for Marketing Mix Modeling. For your own analysis:\n", + "\n", + "1. Replace the sample data with your marketing data\n", + "2. Adjust the model parameters based on your business context\n", + "3. Validate results against your business knowledge \n", + "4. Use the optimization insights to guide marketing budget allocation\n", + "\n", + "For more information, visit the [Robyn documentation](https://github.com/facebookexperimental/Robyn)." + ] + }, + { + "cell_type": "markdown", + "id": "4041ca28", + "metadata": {}, + "source": [ + "\n", + "## Installation\n", + "\n", + "[Running via pip] Install Robyn using pip.\n", + "\n", + "After installation, you might need to restart your Jupyter kernel to use the newly installed package. You can do this by:\n", + "- Going to the Kernel menu\n", + "- Selecting \"Restart Kernel\"\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "69359cd2", + "metadata": {}, + "outputs": [], + "source": [ + "%pip install robynpy==0.1.2" + ] + }, + { + "cell_type": "markdown", + "id": "6ef326a9", + "metadata": {}, + "source": [ + "\n", + "[Running locally] If building locally, make sure we are importing the Robyn modules from the local src directory:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "bd0feec2", + "metadata": {}, + "outputs": [], + "source": [ + "# import sys\n", + "# import os\n", + "\n", + "# notebook_path = os.path.abspath(\"\")\n", + "# robyn_path = os.path.abspath(os.path.join(notebook_path, \"../../\"))\n", + "# if robyn_path not in sys.path:\n", + "# sys.path.append(robyn_path)" + ] + }, + { + "cell_type": "markdown", + "id": "6fd474b7", + "metadata": {}, + "source": [ + "\n", + "## Import Required Libraries\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eb8146e8", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:25:35,107 - robyn - INFO - Logging is set up to console only.\n", + "/Users/yijuilee/robynpy_release_reviews/Robyn/.pyvenv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "from robyn.robyn import Robyn\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.data.entities.enums import AdstockType, DependentVarType" + ] + }, + { + "cell_type": "markdown", + "id": "08d71fdd", + "metadata": {}, + "source": [ + "## Loading Simulated Data with `robynpy` if you are running on Google Colab.\n", + "\n", + "[Running via pip] After installing the `robynpy` package using pip, you can load the simulated data by following these steps:\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "07c9de70", + "metadata": {}, + "outputs": [], + "source": [ + "# # Step 1: Import Necessary Libraries\n", + "# import importlib\n", + "# import robyn\n", + "# import os\n", + "# import pandas as pd\n", + "\n", + "# # Step 2: Load the `robyn` Package\n", + "# pkg = importlib.import_module('robyn')\n", + "\n", + "# # Step 3: Define the Path to Tutorials\n", + "# tutorials_path = pkg.__path__[0] + '/tutorials'\n", + "\n", + "# # Step 4: Load and Display Simulated Weekly Data\n", + "# dt_simulated_weekly = pd.read_csv(tutorials_path + \"/resources/dt_simulated_weekly.csv\")\n", + "# print(\"Simulated Data...\")\n", + "# print(dt_simulated_weekly.head())\n", + "\n", + "# # Step 5: Load and Display Prophet Holidays Data\n", + "# dt_prophet_holidays = pd.read_csv(tutorials_path + \"/resources/dt_prophet_holidays.csv\")\n", + "# print(\"Holidays Data...\")\n", + "# print(dt_prophet_holidays.head())" + ] + }, + { + "cell_type": "markdown", + "id": "442024b2", + "metadata": {}, + "source": [ + "## Loading Simulated Data from Local Build\n", + "\n", + "[Running locally] For this demonstration, we'll use simulated data from our local build." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "6f14728b", + "metadata": {}, + "outputs": [], + "source": [ + "# Load simulated weekly data\n", + "dt_simulated_weekly = pd.read_csv(\"resources/dt_simulated_weekly.csv\")\n", + "\n", + "# Load holidays data (used for seasonality modeling)\n", + "dt_prophet_holidays = pd.read_csv(\"resources/dt_prophet_holidays.csv\")" + ] + }, + { + "cell_type": "markdown", + "id": "eefbc5da", + "metadata": {}, + "source": [ + "## Configure MMM Data\n", + "\n", + "Define the model specification including dependent variables, independent variables, and analysis window. Here's what each parameter means:\n", + "\n", + "### Key Components:\n", + "- `dep_var`: Your target metric (e.g., \"revenue\", \"conversions\")\n", + "- `dep_var_type`: Type of dependent variable (\"revenue\" for ROI or \"conversion\" for CPA)\n", + "- `date_var`: Column name containing dates\n", + "- `window_start/end`: Analysis time period\n", + "\n", + "### Variable Types:\n", + "- `paid_media_spends`: Columns containing media spend data (e.g., TV, Facebook, Search)\n", + "- `paid_media_vars`: Media exposure metrics (impressions, clicks) in same order as spends\n", + "- `context_vars`: External factors (e.g., competitor activities, events, seasonality)\n", + "- `organic_vars`: Marketing activities without direct spend (e.g., email, social posts)\n", + "\n", + "Example configuration:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6c898a44", + "metadata": {}, + "outputs": [], + "source": [ + "mmm_data_spec = MMMData.MMMDataSpec(\n", + " dep_var=\"revenue\", # Target variable\n", + " dep_var_type=\"revenue\", # Type: \"revenue\" or \"conversion\"\n", + " date_var=\"DATE\", # Date column name\n", + " context_vars=[\"competitor_sales_B\", \"events\"], # External factors\n", + " paid_media_spends=[\n", + " \"tv_S\",\n", + " \"ooh_S\",\n", + " \"print_S\",\n", + " \"facebook_S\",\n", + " \"search_S\",\n", + " ], # Media spend columns\n", + " paid_media_vars=[\n", + " \"tv_S\",\n", + " \"ooh_S\",\n", + " \"print_S\",\n", + " \"facebook_I\",\n", + " \"search_clicks_P\",\n", + " ], # Media metrics\n", + " organic_vars=[\"newsletter\"], # Non-paid marketing activities\n", + " window_start=\"2016-01-01\", # Analysis start date\n", + " window_end=\"2018-12-31\", # Analysis end date\n", + ")\n", + "\n", + "mmm_data = MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec)" + ] + }, + { + "cell_type": "markdown", + "id": "12adcbb3", + "metadata": {}, + "source": [ + "## Configure Holiday Data\n", + "\n", + "Holiday data helps capture seasonality and special events in your model. The HolidaysData configuration includes:\n", + "\n", + "### Components:\n", + "- `dt_holidays`: DataFrame containing holiday/events data\n", + "- `prophet_vars`: Time components to model:\n", + " - \"trend\": Long-term trend\n", + " - \"season\": Seasonal patterns\n", + " - \"holiday\": Holiday/event effects\n", + "- `prophet_country`: Country code for built-in holidays (e.g., \"DE\" for Germany)\n", + "- `prophet_signs`: Effect direction for each prophet_var:\n", + " - \"default\": Let the model determine direction\n", + " - \"positive\": Force positive effect\n", + " - \"negative\": Force negative effect\n", + "\n", + "Note: You can add custom events (school breaks, promotional periods, etc.) to the holidays data." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "060564d8", + "metadata": {}, + "outputs": [], + "source": [ + "holidays_data = HolidaysData(\n", + " dt_holidays=dt_prophet_holidays,\n", + " prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + " prophet_country=\"DE\",\n", + " prophet_signs=[\"default\", \"default\", \"default\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "dc127bdd", + "metadata": {}, + "source": [ + "## Configure Hyperparameters\n", + "\n", + "Hyperparameters control how media effects are modeled. Each channel requires three key parameters:\n", + "\n", + "### Media Channel Parameters:\n", + "- `alphas`: Controls saturation curve shape [0.5, 3]\n", + " - Lower values (0.5-1): More diminishing returns\n", + " - Higher values (2-3): More S-shaped response\n", + " \n", + "- `gammas`: Controls saturation curve inflection point [0.3, 1]\n", + " - Lower values: Earlier diminishing returns\n", + " - Higher values: Later diminishing returns\n", + "\n", + "- `thetas`: Controls adstock decay rate [0, 0.8]\n", + " - Lower values (0-0.2): Fast decay (e.g., Search, Social)\n", + " - Medium values (0.1-0.4): Medium decay (e.g., Print, OOH)\n", + " - Higher values (0.3-0.8): Slow decay (e.g., TV)\n", + "\n", + "### Global Parameters:\n", + "- `adstock`: Type of carryover effect modeling\n", + " - \"geometric\": Fixed decay rate\n", + " - \"weibull_cdf\": Flexible decay with cumulative distribution\n", + " - \"weibull_pdf\": Flexible decay with potential peak delay\n", + "\n", + "- `lambda_`: Ridge regression regularization [0, 1]\n", + "- `train_size`: Proportion of data for training [0.5, 0.8]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "32f6e411", + "metadata": {}, + "outputs": [], + "source": [ + "hyperparameters = Hyperparameters(\n", + " hyperparameters={\n", + " \"facebook_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"print_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"tv_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.3, 0.8],\n", + " ),\n", + " \"search_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"ooh_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"newsletter\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " },\n", + " adstock=AdstockType.GEOMETRIC,\n", + " lambda_=[0, 1],\n", + " train_size=[0.5, 0.8],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "13abb5f1", + "metadata": {}, + "source": [ + "## Initialize Robyn\n", + "\n", + "After configuring our data specifications and parameters, we initialize the Robyn model:\n", + "1. Create a Robyn instance with an output directory\n", + "2. Initialize with our configured inputs:\n", + " - MMM data with variables and time window\n", + " - Holiday data for seasonality\n", + " - Hyperparameters for media transformations\n", + "\n", + "This step prepares our configured data for the modeling process:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "2850c314", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO: Initialized Robyn in output\n", + "2025-02-04 23:25:38,258 - robyn.robyn - INFO - Initialized Robyn in output\n", + "INFO: Validating input data\n", + "2025-02-04 23:25:38,259 - robyn.robyn - INFO - Validating input data\n", + "2025-02-04 23:25:38,260 - robyn.data.validation.mmmdata_validation - INFO - Starting complete MMMData validation\n", + "2025-02-04 23:25:38,261 - robyn.data.validation.mmmdata_validation - INFO - Missing and infinite value check passed successfully\n", + "2025-02-04 23:25:38,263 - robyn.data.validation.mmmdata_validation - INFO - No-variance check passed successfully\n", + "2025-02-04 23:25:38,263 - robyn.data.validation.mmmdata_validation - INFO - Variable names validation passed successfully\n", + "2025-02-04 23:25:38,264 - robyn.data.validation.mmmdata_validation - INFO - Date variable validation passed successfully\n", + "2025-02-04 23:25:38,265 - robyn.data.validation.mmmdata_validation - INFO - Dependent variable validation passed successfully\n", + "2025-02-04 23:25:38,265 - robyn.data.validation.mmmdata_validation - INFO - All validations passed successfully\n", + "2025-02-04 23:25:38,265 - robyn.data.validation.holidays_data_validation - INFO - Starting complete validation process\n", + "2025-02-04 23:25:38,272 - robyn.data.validation.holidays_data_validation - INFO - Holidays validation completed. Status: True\n", + "2025-02-04 23:25:38,274 - robyn.data.validation.holidays_data_validation - INFO - Prophet validation completed. Status: True\n", + "2025-02-04 23:25:38,275 - robyn.data.validation.holidays_data_validation - INFO - Validation complete. Overall status: True\n", + "2025-02-04 23:25:38,275 - robyn.data.validation.hyperparameter_validation - INFO - Starting validation process\n", + "2025-02-04 23:25:38,276 - robyn.data.validation.hyperparameter_validation - INFO - Starting hyperparameters validation\n", + "2025-02-04 23:25:38,276 - robyn.data.validation.hyperparameter_validation - INFO - Hyperparameter validation completed. Status: True\n", + "2025-02-04 23:25:38,276 - robyn.data.validation.hyperparameter_validation - INFO - Validation completed with status: True\n", + "INFO: Data initialization complete\n", + "2025-02-04 23:25:38,277 - robyn.robyn - INFO - Data initialization complete\n" + ] + } + ], + "source": [ + "robyn = Robyn(working_dir=\"output\")\n", + "robyn.initialize(\n", + " mmm_data=mmm_data,\n", + " holidays_data=holidays_data,\n", + " hyperparameters=hyperparameters,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "9c8bb82e", + "metadata": {}, + "source": [ + "## Run Feature Engineering\n", + "\n", + "Run preprocessing transformations on our input data to generate model-ready features:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "72917fc5", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO: Performing feature engineering\n", + "2025-02-04 23:25:38,291 - robyn.robyn - INFO - Performing feature engineering\n", + "2025-02-04 23:25:38,292 - robyn.modeling.feature_engineering - INFO - Starting feature engineering process\n", + "2025-02-04 23:25:38,294 - robyn.modeling.feature_engineering - INFO - Starting Prophet decomposition\n", + "2025-02-04 23:25:38,295 - robyn.modeling.feature_engineering - INFO - Starting Prophet decomposition\n", + "/Users/yijuilee/robynpy_release_reviews/Robyn/.pyvenv/lib/python3.12/site-packages/prophet/forecaster.py:187: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " self.holidays['ds'] = pd.to_datetime(self.holidays['ds'])\n", + "2025-02-04 23:25:38,940 - cmdstanpy - DEBUG - input tempfile: /var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpnooqg2eb/445l1rdj.json\n", + "2025-02-04 23:25:38,953 - cmdstanpy - DEBUG - input tempfile: /var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpnooqg2eb/2gkdsjx4.json\n", + "2025-02-04 23:25:38,956 - cmdstanpy - DEBUG - idx 0\n", + "2025-02-04 23:25:38,956 - cmdstanpy - DEBUG - running CmdStan, num_threads: None\n", + "2025-02-04 23:25:38,956 - cmdstanpy - DEBUG - CmdStan args: ['/Users/yijuilee/robynpy_release_reviews/Robyn/.pyvenv/lib/python3.12/site-packages/prophet/stan_model/prophet_model.bin', 'random', 'seed=23885', 'data', 'file=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpnooqg2eb/445l1rdj.json', 'init=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpnooqg2eb/2gkdsjx4.json', 'output', 'file=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpnooqg2eb/prophet_model5gvf7x2b/prophet_model-20250204232538.csv', 'method=optimize', 'algorithm=lbfgs', 'iter=10000']\n", + "23:25:38 - cmdstanpy - INFO - Chain [1] start processing\n", + "2025-02-04 23:25:38,957 - cmdstanpy - INFO - Chain [1] start processing\n", + "23:25:39 - cmdstanpy - INFO - Chain [1] done processing\n", + "2025-02-04 23:25:39,083 - cmdstanpy - INFO - Chain [1] done processing\n", + "2025-02-04 23:25:39,168 - robyn.modeling.feature_engineering - INFO - Prophet decomposition complete\n", + "2025-02-04 23:25:39,169 - robyn.modeling.feature_engineering - INFO - Starting model runs for paid media variables with different exposure metrics\n", + "2025-02-04 23:25:39,170 - robyn.modeling.feature_engineering - INFO - Fitting spend-exposure model for facebook_I\n", + "2025-02-04 23:25:39,183 - robyn.modeling.feature_engineering - INFO - Fitting spend-exposure model for search_clicks_P\n", + "2025-02-04 23:25:39,191 - robyn.modeling.feature_engineering - INFO - Completed model runs for 2 channels\n", + "2025-02-04 23:25:39,192 - robyn.modeling.feature_engineering - INFO - Feature engineering complete\n", + "2025-02-04 23:25:39,193 - robyn.modeling.feature_engineering - INFO - Filled 0 missing values\n", + "2025-02-04 23:25:39,194 - robyn.visualization.feature_visualization - INFO - Initializing FeaturePlotter\n", + "2025-02-04 23:25:39,194 - robyn.visualization.feature_visualization - INFO - Generating all plots\n", + "2025-02-04 23:25:39,194 - robyn.visualization.feature_visualization - INFO - Generating spend-exposure plot for channel: facebook_I\n", + "2025-02-04 23:25:39,195 - robyn.visualization.feature_visualization - INFO - Found result for channel facebook_I\n", + "2025-02-04 23:25:39,323 - robyn.visualization.feature_visualization - INFO - Successfully generated spend-exposure plot for channel facebook_I\n", + "2025-02-04 23:25:39,324 - robyn.visualization.feature_visualization - INFO - Generating spend-exposure plot for channel: search_clicks_P\n", + "2025-02-04 23:25:39,324 - robyn.visualization.feature_visualization - INFO - Found result for channel search_clicks_P\n", + "2025-02-04 23:25:39,481 - robyn.visualization.feature_visualization - INFO - Successfully generated spend-exposure plot for channel search_clicks_P\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "# Run feature engineering\n", + "robyn.feature_engineering();" + ] + }, + { + "cell_type": "markdown", + "id": "d836832f", + "metadata": {}, + "source": [ + "## Model Training\n", + "\n", + "Configure and execute model training using multiple trials and iterations to find optimal solutions. Key settings include:\n", + "- Number of trials and iterations for optimization\n", + "- Time-series validation for robustness\n", + "- Parallel processing configuration\n", + "- Model type and regularization settings" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "08cc2ddb", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO: Training models\n", + "2025-02-04 23:25:39,627 - robyn.robyn - INFO - Training models\n", + "2025-02-04 23:25:39,629 - robyn.modeling.base_model_executor - INFO - Initializing BaseModelExecutor\n", + "2025-02-04 23:25:39,629 - robyn.modeling.model_executor - INFO - Starting model execution with model_name=Models.RIDGE\n", + "2025-02-04 23:25:39,630 - robyn.modeling.base_model_executor - INFO - Input validation successful\n", + "2025-02-04 23:25:39,631 - robyn.modeling.base_model_executor - INFO - Preparing hyperparameters\n", + "2025-02-04 23:25:39,631 - robyn.modeling.base_model_executor - INFO - Completed hyperparameter preparation with 20 parameters to optimize\n", + "2025-02-04 23:25:39,632 - robyn.modeling.model_executor - INFO - Initializing Ridge model builder\n", + "2025-02-04 23:25:39,632 - robyn.modeling.model_executor - INFO - Building models with configured parameters\n", + "2025-02-04 23:25:39,632 - robyn.modeling.ridge.ridge_data_builder - INFO - Collecting hyperparameters for optimization...\n", + "Running trial 1 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:27:20,807 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.69 mins\n", + "Running trial 2 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:29:03,024 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.70 mins\n", + "Running trial 3 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:30:44,501 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.69 mins\n", + "Running trial 4 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:32:25,696 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.67 mins\n", + "Running trial 5 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:34:06,861 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.67 mins\n", + "2025-02-04 23:34:07,210 - robyn.visualization.model_convergence_visualizer - INFO - Initialized ModelConvergenceVisualizer\n", + "2025-02-04 23:34:07,211 - robyn.modeling.convergence.convergence - INFO - Starting convergence calculation\n", + "2025-02-04 23:34:07,215 - robyn.modeling.convergence.convergence - WARNING - 'mape' column not found or all zeros. Assuming model is not calibrated.\n", + "2025-02-04 23:34:07,232 - robyn.modeling.convergence.convergence - INFO - Convergence status for DECOMP.RSSD: converged\n", + "2025-02-04 23:34:07,232 - robyn.modeling.convergence.convergence - INFO - DECOMP.RSSD converged: sd@qt.20 0.024 <= 0.040 & |med@qt.20| 0.03 <= 0.08\n", + "2025-02-04 23:34:07,233 - robyn.modeling.convergence.convergence - WARNING - Convergence status for NRMSE: NOT converged\n", + "2025-02-04 23:34:07,233 - robyn.modeling.convergence.convergence - INFO - NRMSE NOT converged: sd@qt.20 0.015 <= 0.026 & |med@qt.20| 0.05 > 0.00\n", + "2025-02-04 23:34:07,261 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2025-02-04 23:34:07,272 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2025-02-04 23:34:07,278 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2025-02-04 23:34:07,831 - robyn.visualization.model_convergence_visualizer - INFO - Successfully created moo distribution plot\n", + "2025-02-04 23:34:08,088 - robyn.visualization.model_convergence_visualizer - INFO - Successfully created moo cloud plot\n", + "2025-02-04 23:34:08,276 - robyn.modeling.convergence.convergence - INFO - Convergence calculation completed successfully\n", + "2025-02-04 23:34:08,315 - robyn.modeling.model_executor - INFO - Model building completed successfully\n", + "2025-02-04 23:34:08,316 - robyn.modeling.model_executor - INFO - Model execution completed successfully\n", + "2025-02-04 23:34:08,316 - robyn.visualization.model_convergence_visualizer - INFO - Initialized ModelConvergenceVisualizer\n", + "2025-02-04 23:34:08,316 - robyn.visualization.model_convergence_visualizer - WARNING - this method is not yet implemented\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.modeling.entities.enums import Models, NevergradAlgorithm\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "\n", + "trials_config = TrialsConfig(iterations=2000, trials=5)\n", + "\n", + "robyn.train_models(\n", + " trials_config=trials_config,\n", + " ts_validation=True,\n", + " add_penalty_factor=False,\n", + " rssd_zero_penalty=True,\n", + " cores=8,\n", + " nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE,\n", + " model_name=Models.RIDGE,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "69d510f2", + "metadata": {}, + "source": [ + "## Evaluate Models\n", + "\n", + "After training, we cluster similar models to identify stable solutions. This helps find consistent patterns in:\n", + "- Model performance metrics\n", + "- Channel contribution patterns\n", + "- Hyperparameter choices\n", + "\n", + "The clustering process helps select reliable models from our training results." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c6d397f9", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO: Evaluating models\n", + "2025-02-04 23:34:08,900 - robyn.robyn - INFO - Evaluating models\n", + "2025-02-04 23:34:08 [INFO] Starting Pareto optimization\n", + "2025-02-04 23:34:08,902 - robyn.modeling.pareto.data_aggregator - INFO - Starting model data aggregation\n", + "2025-02-04 23:34:08 [INFO] Computing Pareto fronts\n", + "2025-02-04 23:34:09 [INFO] Pareto front computation completed\n", + "2025-02-04 23:34:09 [INFO] Preparing Pareto data\n", + "2025-02-04 23:34:09 [INFO] Number of Pareto-optimal solutions found: 8214\n", + "2025-02-04 23:34:09 [INFO] Selected 4 Pareto-fronts containing 139 candidates\n", + "2025-02-04 23:34:09 [INFO] Selected Pareto fronts: 5\n", + "2025-02-04 23:34:09 [INFO] Filtering data for selected Pareto fronts...\n", + "2025-02-04 23:34:09 [INFO] Pareto data preparation completed\n", + "2025-02-04 23:34:09,593 - robyn.modeling.pareto.response_curve - INFO - Calculating response curves for 695 models' media variables...\n", + "Processing rows: 100%|██████████| 695/695 [00:06<00:00, 101.82it/s]\n", + "2025-02-04 23:34:17,765 - robyn.modeling.pareto.response_curve - INFO - Successfully processed 695 response curves\n", + "2025-02-04 23:34:17,765 - robyn.modeling.pareto.response_curve - INFO - Computing final metrics...\n", + "2025-02-04 23:34:17,766 - robyn.modeling.pareto.response_curve - INFO - Calculating ROI and CPA metrics...\n", + "2025-02-04 23:34:17,821 - robyn.modeling.pareto.response_curve - INFO - Final Pareto Data updated with response curves:\n", + "Decomp Spend Distribution:\n", + "\n", + "2025-02-04 23:34:17,822 - robyn.modeling.pareto.response_curve - INFO - DataFrame columns: Index(['rn', 'coef', 'xDecompAgg', 'total_spend', 'mean_spend', 'spend_share',\n", + " 'effect_share', 'sol_id', 'rsq_train', 'rsq_val', 'rsq_test', 'nrmse',\n", + " 'decomp_rssd', 'mape', 'lambda', 'lambda_hp', 'lambda_max',\n", + " 'lambda_min_ratio', 'trial', 'iterNG', 'iterPar', 'Elapsed', 'pos',\n", + " 'robynPareto', 'mean_response', 'mean_spend_adstocked',\n", + " 'mean_carryover', 'roi_mean', 'roi_total', 'cpa_mean', 'cpa_total'],\n", + " dtype='object')\n", + "2025-02-04 23:34:17,822 - robyn.modeling.pareto.response_curve - INFO - DataFrame Shape: (695, 31)\n", + "2025-02-04 23:34:17,822 - robyn.modeling.pareto.response_curve - INFO - X Spend Aggregated with response curves:\n", + "\n", + "2025-02-04 23:34:17,822 - robyn.modeling.pareto.response_curve - INFO - DataFrame columns: Index(['rn', 'coef', 'xDecompAgg', 'xDecompPerc', 'xDecompMeanNon0',\n", + " 'xDecompMeanNon0Perc', 'xDecompAggRF', 'xDecompPercRF',\n", + " 'xDecompMeanNon0RF', 'xDecompMeanNon0PercRF', 'pos', 'train_size',\n", + " 'rsq_train', 'rsq_val', 'rsq_test', 'nrmse_train', 'nrmse_val',\n", + " 'nrmse_test', 'nrmse', 'decomp.rssd', 'mape', 'lambda', 'lambda_hp',\n", + " 'lambda_max', 'lambda_min_ratio', 'sol_id', 'trial', 'iterNG',\n", + " 'iterPar', 'Elapsed', 'iterations', 'robynPareto', 'total_spend',\n", + " 'mean_spend', 'mean_spend_adstocked', 'mean_carryover', 'mean_response',\n", + " 'spend_share', 'effect_share', 'roi_mean', 'roi_total', 'cpa_total'],\n", + " dtype='object')\n", + "2025-02-04 23:34:17,823 - robyn.modeling.pareto.response_curve - INFO - DataFrame Shape: (120000, 42)\n", + "2025-02-04 23:34:17,823 - robyn.modeling.pareto.response_curve - INFO - Response curves calculated successfully\n", + "2025-02-04 23:34:17,826 - robyn.modeling.pareto.plot_data_generator - INFO - Starting plot data generation...\n", + "2025-02-04 23:34:17,826 - robyn.modeling.pareto.plot_data_generator - INFO - Processing Pareto front 1\n", + "2025-02-04 23:34:17,830 - robyn.modeling.pareto.plot_data_generator - INFO - Pareto-Front: 1 [32 models]\n", + "Processing Solutions: 0%| | 0/32 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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1GqBs6jQAdZboEeLZz352OvLII/Ma7bH++vrrr59e97rXpT//+c8T1/n5z3+edtppp7x++8Ybb5wOOuigdPPNN+fLYlRxLPf0u9/9buL63/rWt/J5X/va1ybOu+yyy/J5Mdp4fHw8HXHEEfm+11133fz1Yx/7WO2mUNGBuMcee6QnPvGJ+RTr0VedjDEy+jnPeU7+/uCDD863d9RRR6Wjjz46nxf3Gz+HuO/Pfvaz6bnPfW6+7+c973npC1/4wgL3tfPOO6cDDjggvelNb0obbrhhes1rXrOYnm2gRMsvv3z+3MeMiYc97GEzLh8VS9VtueWWab311ksve9nL0o9//OPa261+L/7Y33HHHfPvvfSlL00/+MEPJq7z1Kc+NX/dfffd0yGHHDJxXiw5FctHxfWrYAUAAAAASrPEI+7oJPvTn/6UPvShD6X3v//96ZJLLskhRYglT3bdddd073vfO33iE59Ib3/729NPf/rTtMsuu+TNZWPj2Xvd617pwgsvnLi9n/zkJxPBRyWWWnngAx+YQ5DPfe5z6ctf/nIOIWJt+NinItaA//SnPz1t+6666qq0/fbb52VeImj5wAc+kMOL+L04b6WVVpoIK97whjfk72NZl+hgDLGmfbXMS3QQRmCzzTbbpM985jPp+c9/ft4745hjjlngPmN5l1jbPtoUa9gDc1fUlXe+851pxRVXrA0iYkmnWK4ugtDf/va3uTZMrnNTxZ4W1UyKX//613m2RezNE7XvggsuyJdtttlmOXh9/OMfn0/x/aabbpprT9zPXnvtla8X38eJhVfNcgGgXGo1QNnUaQA6XULqvve9b/rUpz41cUC6+uqr84yFW265Jc+MePSjH52OPfbYicsjhNhqq63SN77xjTyqOGZlxEjkqqM/vl9nnXVy+FH50Y9+lDvlYsphBCAx+yFGFof4/RgBPVPnYQQScfmJJ544sXxLBCdbbLFF7hiMsCU6/sIjH/nItPbaa+fvH/rQh+avMYuiCkK++tWvpv333z+Pdg7PfOYz81qO8fhe9apXpQc84AH5/Fji5dBDD83hDDC3Nf0xHjXkjjvuyF8jDI0gI4Ldyy+/PNenqE11YvmoCFLvd7/75fAiAt0ITZ/xjGfky+O24lSJgDZqVcx8i03D3/Oe9+SZbeElL3lJ/tn07dmL5b8AKJtaDVA2dRqAOku8lyqWNZncgVd1/EeH3W9+85scPMTBKjbIjlMsZ/LYxz52gRHEv/jFL/LyKhESXHfddWnPPfdMf/vb3/Lp9ttvz0tHxfXCU57ylPy7ERhEAPHHP/4xd9S9+MUvnrZ9MaMjQo6YBVK1IYKMJz/5yQvM/GgStxOPI5aYqm4nTvHznXfemR9D5TGPeYzwAsiiNh122GF5JljUygg6t9tuu3zZpZdeOuPvVYFrLDsVQUTUlFe84hWNvxezxOK6EbT+7//+b/rKV76S62XMGIvv4zxmz8wVgPKp1QBlU6cB6HQGRsxumKwa2Xvttdfmg1Qs+RSnqZZbbrn8NYKJWHrql7/8ZV6KKmZsbL755uk+97lPnoURX2OWQ8x2CDFTI5ZnihkcH/3oR9Phhx+e1lhjjbyES7Ue/NRlWKLDbrpOu1iWaraq5Vxi9sh0rr/++onvo30AIYLSCGY32mijif0oIvwMM80cC6uvvnqugbERd6UKi2eaQRH7/XznO9/JIXDUtwiRQwQfEQjHTIyLL744bb311ov1MQIAAABAkQFG3ejhCB5iaZPpOv2r4CM69GLGQiwdFTMwYrZELMEUm21fdNFFucMuOv6q0cjRcRdLT8Up9rA4//zz834U++yzz8SsjsmigzA2GJ9uM+2RkZGFWiornHTSSdMGFLHMC8BUH/nIR9Jll12WnvOc56Qjjjgi/fvf/84BbIjaNJMIciPAiD11Xv3qV6fVVlttYimoWIpvOh//+MdzrXrta1+7QNDx97//PYfKk89jduJ4BEDZ1GqAsqnTANTprKcqOvljP4mYVRHLTFWnmC0Re2REOFGJWRjxcyzDFEtEhfga58X+F9GRV4llWGLGRnjQgx6Ul2KJMCPWlY/lpqaKQCSWmYp9Lqo2xB4ase782WefPeMa9lM7+WLJqRB7e0x+PDfffHP65Cc/OTFDA2CyN77xjTnMPffcc3Nd22STTdKVV16Z61dcFmKZvDg/TlFTQiz7FOFu1LYIgaMGnXnmmfmP/whsp4rbOO+889LrXve6iZkdT3jCE/LXPfbYI7373e9e4Dxmp5otA0C51GqAsqnTANTpdKhtbHj9f//3f+ktb3lLninx/e9/Py8BVW3UXYl9MqLz7cYbb8yBQ4jloGLJk1h6ZXKAEbMxvvzlL+dZFxFwfPvb304nnHBC/r3ploTaa6+98sbi0YF3zjnn5EAkOv/OOOOMtNZaa+XrVJ190a5qyZVqxkUsxxKb4q655pppm222Se9617vy3huxJ0a048ADD8wdjjE6GmCqLbbYIh177LF5VlmEpbEfz3Of+9xcP6o9g2IPoFiGLk79fn9iltopp5ySQ9rYwDv+6I/bOP7449OTnvSkaWdfPPjBD04777zzxHnPe97zcs2NGhe3EeFG7KnB7NlwEKB8ajVA2dRpAOr0BkvwSBEbWEdwEBvUVr75zW+mgw8+OI82XnXVVXMocPTRR6dLLrkkjxyO4CIChGpGQxgdHU1Pe9rTcufb9773vXxedOLFba+88soL7F8RnXif/vSnc3AR4UZ0zEU7IiSJzXEj1Nhll13SySefPDGbIza8jaVbYp+NeDoe97jH5Q1uY0mXSjyGU089NbcxlqKKUGLvvfdOl19+eXrZy16WDjnkkHzf0RF52mmn5fuOEdQRruy7777p/ve/f76dqvPwC1/4Qu1zF7cVoc6mFx6bRvqji+01ARbO7bseluavtmbXzaBQcSyabpYeAOVQqwHKpk4D0FmAQXsCDCiDAIM6cQiNJcAAKJdaDVA2dRqAOnZrBYCWrNcLUD61GqBs6jQAdQQYAAAAAABAcQQYANCStXoByqdWA5RNnQagjgADAFqyjRRA+dRqgLKp0wDUEWAAQEvj4+NdNwGABmo1QNnUaQDqCDAAAAAAAIDiCDAAoKWRkZGumwBAA7UaoGzqNAB1BBgA0FK/3++6CQA0UKsByqZOA1BHgAEALdlwEKB8ajVA2dRpAOoIMACgpV6v13UTAGigVgOUTZ0GoI4AAwBaGh4e7roJADRQqwHKpk4DUEeAAQAtjY2Ndd0EABqo1QBlU6cBqCPAAAAAAAAAiiPAAICWTHcHKJ9aDVA2dRqAOgIMAGhpMBh03QQAGqjVAGVTpwGoI8AAgJbGx8e7bgIADdRqgLKp0wDUEWAAAAAAAADFEWAAQEsjIyNdNwGABmo1QNnUaQDqCDAAoKV+v991EwBooFYDlE2dBqCOAAMAWrLhIED51GqAsqnTANQRYABAS71er+smANBArQYomzoNQB0BBgC0NDw83HUTAGigVgOUTZ0GoI4AAwBaGhsb67oJADRQqwHKpk4DUEeAAQAAAAAAFEeAAQAtme4OUD61GqBs6jQAdQQYAAAAAABAcQQYANBSv9/vugkANFCrAcqmTgNQR4ABAAAAAAAUR4ABAC2NjIx03QQAGqjVAGVTpwGoI8AAgJZMdwcon1oNUDZ1GoA6Yu7C3b7joWlkSM4EXektP7/rJlCwwWDQdRMAaKBWA5RNnQagjgCjcPMfuYbplACF6vV6XTcBgAZqNUDZ1GkA6hjaDwAtDQ8Pd90EABqo1QBlU6cBqCPAAICWxsbGum4CAA3UaoCyqdMA1BFgAAAAAAAAxRFgAEBLQ0MOowClU6sByqZOA1DHUQIAWrLhIED51GqAsqnTANQRYABAS/1+v+smANBArQYomzoNQB0BBgAAAAAAUBwBBgC0NDIy0nUTAGigVgOUTZ0GoI4AAwBaMt0doHxqNUDZ1GkA6ggwAKClwWDQdRMAaKBWA5RNnQagjgADAFrq9XpdNwGABmo1QNnUaQDqCDAAoKXh4eGumwBAA7UaoGzqNAB1BBgA0NLY2FjXTQCggVoNUDZ1GoA6AgwAAAAAAKA4AgwAaGloyGEUoHRqNUDZ1GkA6jhKAEBLNhwEKJ9aDVA2dRqAOgIMAGip3+933QQAGqjVAGVTpwGoI8AAAAAAAACKI8AAgP+vvbuAkqy62gZ8eroHd4ITPDgE9+DuNh8QAgT9cA8WgkMG1+CQwYME9+ASggV+IAyE4BrcbVr+tc+3bq/unuHWzAWm7jDPs1avnq66XX2qpntX1XnvObuitra2Zg8BgAbUaoB6U6cBKCPAAICKLHcHqD+1GqDe1GkAyggwAKCirq6uZg8BgAbUaoB6U6cBKCPAAICKWlpamj0EABpQqwHqTZ0GoIwAAwAqam1tbfYQAGhArQaoN3UagDICDACoqL29vdlDAKABtRqg3tRpAMoIMAAAAAAAgNoRYABARf36eRoFqDu1GqDe1GkAyniWAICKNBwEqD+1GqDe1GkAyggwAKCijo6OZg8BgAbUaoB6U6cBKCPAAAAAAAAAakeAAQAVtbW1NXsIADSgVgPUmzoNQBkBBgBU1NnZ2ewhANCAWg1Qb+o0AGUEGABQkTdbAPWnVgPUmzoNQBkBBgAAAAAAUDsCDACoqH///s0eAgANqNUA9aZOA1BGgAEAFQ0ZMqTZQwCgAbUaoN7UaQDKCDAAAAAAAIDaEWAAQEX9+nkaBag7tRqg3tRpAMp4lgCAilpaWpo9BAAaUKsB6k2dBqCMAAMAKuro6Gj2EABoQK0GqDd1GoAyAgwAAAAAAKB2BBgAUFFra2uzhwBAA2o1QL2p0wCUEWAAQEVdXV3NHgIADajVAPWmTgNQRoABABV1dnY2ewgANKBWA9SbOg1AGQEGAAAAAABQOwIMAKiof//+zR4CAA2o1QD1pk4DUEaAAQAVDRkypNlDAKABtRqg3tRpAMoIMAAAAAAAgNoRYABARf36eRoFqDu1GqDe1GkAyniWAICKWlpamj0EABpQqwHqTZ0GoIwAAwAq6ujoaPYQAGhArQaoN3UagDICDAAAAAAAoHYEGABQUWtra7OHAEADajVAvanTAJQRYABARV1dXc0eAgANqNUA9aZOA1BGgAEAFXV2djZ7CAA0oFYD1Js6DUAZAQYAAAAAAFA7AgwAqKh///7NHgIADajVAPWmTgNQRoABABW1t7c3ewgANKBWA9SbOg1AGQEGAFSk4SBA/anVAPWmTgNQRoABABX16+dpFKDu1GqAelOnASjjWQIAKvJmC6D+1GqAelOnASjjWQIAKrJfL0D9qdUA9aZOA1BGgAEAAAAAANSOAAMAKmptbW32EABoQK0GqDd1GoAyAgwAqKirq6vZQwCgAbUaoN7UaQDKCDAAoKLOzs5mDwGABtRqgHpTpwEoI8AAAAAAAABqR4ABABW1tbU1ewgANKBWA9SbOg1AGQEGAFTU0dHR7CEA0IBaDVBv6jQAZQQYAFCRhoMA9adWA9SbOg1AGQEGAFTU0tLS7CEA0IBaDVBv6jQAZQQYAFBRa2trs4cAQANqNUC9qdMAlBFgAEBF7e3tzR4CAA2o1QD1pk4DUKat9Fqa7vPXXkht/eRMP2UtY4+Xxp1immYPAwAAAACgVgQYNTfeJQento4hzR4GP6LPfzuw2UMAKrLcHaD+1GqAelOnASjj1H4AqKirq6vZQwCgAbUaoN7UaQDKCDAAoKLOzs5mDwGABtRqgHpTpwEoI8AAAAAAAABqR4ABABW1tWklBVB3ajVAvanTAJQRYABARR0dHc0eAgANqNUA9aZOA1BGgAEAFWk4CFB/ajVAvanTAJQRYABARS0tLc0eAgANqNUA9aZOA1BGgAEAFbW2tjZ7CAA0oFYD1Js6DUAZAQYAVNTe3t7sIQDQgFoNUG/qNABlBBgAAAAAAEDtCDAAoCLL3QHqT60GqDd1GoAyAgwAAAAAAKB2BBgAUFFHR0ezhwBAA2o1QL2p0wCUEWAAAAAAAAC1I8AAgIra2tqaPQQAGlCrAepNnQagjAADACqy3B2g/tRqgHpTpwEoI8AAgIq6urqaPQQAGlCrAepNnQagjAADACpqaWlp9hAAaECtBqg3dRqAMgIMAKiotbW12UMAoAG1GqDe1GkAyggwAKCi9vb2Zg8BgAbUaoB6U6cBKCPAAAAAAAAAakeAAQAV9evnaRSg7tRqgHpTpwEo41kCACrScBCg/tRqgHpTpwEoI8AAgIo6OjqaPQQAGlCrAepNnQagjAADAAAAAACoHQEGAFTU1tbW7CEA0IBaDVBv6jQAZQQYAFCR5e4A9adWA9SbOg1AGQEGAFTU1dXV7CEA0IBaDVBv6jQAZQQYMIobMmRIOuOMM9Iqq6yS5p133rTiiiumE044IX399dfD9f1fffVVWmmlldJss82Wrr766u7LBw8enDbccMM033zzpQEDBuSvexo0aFCaffbZ03PPPfeD3ycYVbS0tDR7CAA0oFYD1Js6DcAPFmC88847adNNN03zzDNPWnzxxfPE58hw6qmn5snVkWWzzTbLHz+Eu+66K22xxRZpoYUWyo9bTBQfeeSR6YMPPvhBbh9OOumk/PHKK6+kscceO73++uvprLPOSkccccRwff8pp5ySXnvttaEu32uvvdLTTz+dz4Z56qmn0t5779193RdffJF/xuqrr55DDBhdtba2NnsIADSgVgPUmzoNwA8WYFxwwQXpySefTEcffXQ67bTT8mQp3+2aa65JO+64Y5pxxhnTsccem84555wcZtx2221po402Sp988kmzh8hPwHXXXZc/n3jiienhhx/OYUa4/fbbG35vBBPxd93Xp59+ml588cW01FJLpSeeeCLNMsss6T//+U++PPz5z3/Ov7+77LLLD35/YFTS3t7e7CEA0IBaDVBv6jQAZdpG5OCPP/44TT755Pmsaxr705/+lNZYY410yCGHdF+22GKL5dUY66yzTrryyivTNtts09QxMur79ttvey27LfYPnWSSSRpuPfX73/8+dXZ2pv79++evC/36/V+2GdtQxd998TPizJgPP/wwBxjrrrtuDucAAAAAAJq6AmP55ZfP++O/9dZbeTun2NYp9r7feeed86T8XHPNlX71q1/lbWt67r0fE59xRvgKK6yQ9+dfc80188qEnu644460/vrr5y2WllxyyXwbX3755VBjiONin/84Lvbkf+ihh3pd/+6776b9998/LbPMMvlnxf79d955Z69jvvnmmxwsrLrqqvl2Vl555XT22WfnSdzvcv/996e55547T/aOSHOp999/f5jHx5Y7Mc64Tfi+Ntlkk/x59913T4suumjaY4890s9+9rN0+OGHl35f/N7/+9//zn8nEUz2NN544+Xfz8ceeyxvFxdbTMXfy7jjjpu/L/6O4m8fRndF2AdAfanVAPWmTgNQZrifJWLLqAgGJptssnT55ZfnSc/ohxF9MAYOHJi3R4rVBhdddFG68MILu78v9s2Ps7UjcIg982NLmv322y/deOON+fobbrgh7bTTTmmmmWbKwUJMil5//fV566W+k/8RIGy++eY5PImJ1G233Tbv0V+EBTGmmHCNCdw4Zppppsm3HbcX4va23377dO655+bxnHnmmTnIiIDl4IMPHub9fvTRR/OY1lprrRysjEhzqWWXXTbddNNNeQxxf//73/92X/fb3/42Bz/wfcXvZwR/IVZLFEtwY6XEd4ntoeL3P4KOffbZZ5jHxJZU0RB8hhlmyAFkNAaPPjiXXnpp2njjjdPUU0+dj+u5cgNGNxoOAtSfWg1Qb+o0AD/IFlJzzjln3pJmjDHGSPPNN1964IEH0hxzzJFOPvnkfLZ2WGKJJdKDDz6Y9+Hfbrvt8tnd0e/hgAMOyL0fQpzN/eabb+ZjIvA47rjj8sqN+FyICdOY4L/33ntzCFA49NBDc+BQ3E5MqkZwEk2IIySJCdv4eRFchAhc4naOOeaYvPIjVlL8/e9/zxOx8bNDTPyONdZY+X5EOPKLX/yiV3+A//3f/82rPqLx9og+qcYZ8LGyI3oRxOqRMN100+Vxb7nllmmKKaYYoduDYYmQMP7uYgVGNJ+/9dZbc9gXTbhjZdS0007b6/j4nYzrY3VUfJ5gggmGebvxuxqhYk9xfJwdE0Fg9MOJMPLll1/OW0lFkBm1AUYnHR0dzhgDqDm1GqDe1GkAylR+hoiVFBdffHEac8wxc3Pf2KrpjDPOyCFCsV/+448/nj/HNk09xeqImNx/6aWX8hndsT1VnDFefCy88MI5FIlJ2ULs0d/zduLnLr300nmFRHjkkUfS/PPP3x1eFNZee+303nvv5Z8Vx7S1tXWHID2PKW6jEFtlxQqPWLVx0EEHVXoyHX/88XO4EuFF3EYEIdEEOcKWGEM0R4bv45lnnsmBRfy9RNgWn2MlUgRxsTLinnvuGep7Lrnkkvy7FwHfiPSzib+h2P4tQpJYubHvvvvmraSOP/74/DcWXwMAAAAAND3AiLO4Y9XEIossklczRCAxePDgHCwUiu1sJp100mHeRnF9rKyIM8V7fnz++ee5p0Vh4oknHipEiNuNQCB88skneXurvmKiNcRxcUzcTjQi7qn4vs8++6z7sjfeeCP3AIhJ4Ng+6/uIM+Bju60IM6JvRwQ4sZqjUY8CaOSVV17JnyNo67lCqPhbiS3e+ooVQSFWOEU/m/iIVVEherNEQDEssUppnHHGyY3n4+8pfvYCCyyQVzdFYBJf9/wbgtFBhOIA1JtaDVBv6jQAZSo/S0Qj30GDBuXwIVZGxGqDEGd/F4qtaWJVxpRTTtlr//0IL4rrYw/+CEL6mnDCCbv/HROjfSdpo+9FbGtVHBtngfdVXBbBRRzz0Ucf5eWJPUOMIiiJYwqzzjpr7tkR/THOP//8HNJEE+PhFVtZRV+Nyy67LG+v03NiOR6vWDlyxRVXDPftwbBMP/30+fMXX3yRe1NEUPaPf/wjb98WhtUoPn7P+25fFn9L8XcRfyM9/w56rvSI3+lddtklHxMBY3j77bfziqvib8jepYxuIszvG4oDUC9qNUC9qdMA/CgrMGJ7qFlmmSVtsMEG3eFFNKmOidN48gkLLrhg/nzXXXf1+t5YuRE9JaJxd6yiiNUOEQ4UHzG5GtvSPPvss93fE2eSx8RsISZsY3ucRRddNH8d207FtjjFmeSFaOAdKyxiojdCktiiKrbc6XtMz/GGiSaaKJ8FEA24I3w58MAD8/cOrzgjPUKaCy64YJjXx9nqEZLA9xF/L8stt1z+92GHHZZ/h6PfTIR90SQ+esXElmWx3VqxsiJWAt133329PoqAMXpaxPXDaugdwUb0lAmxVVX8jkcdiJ8Zf3fx+1z0w4HRRfF8B0B9qdUA9aZOA/CjrMCYd9550+mnn55XYkTj3ldffTWvWIizsYtta2afffbc6+HYY49NX3/9dW76HZOld999d96WKRL2PfbYI/eHiH/HRGxsTRO3G2FIbCXVswdGNAPfc8898yRp/Ny4zR133DFfH02xI4iICdadd945BxDXXnttDj2OOuqovPIhJnEj8IgwIm4/xhd9L6IR+HrrrZcDmb7GHnvsvJIimpKfd955uc/A8IhwJr4nHpPopxF9NmKS+IMPPkjXXXdd3koqJpbh+4rAIVZDxe97hIER2MXfXfythFgtEb/vsf1TFQ8//HB64IEHcrgx7rjjdl9+zDHH5L/d6IETQYot0RgdWXUEUH9qNUC9qdMAlGnpilO1h1NMYMaEf6yoiKBi4MCBeT/92N5pqqmmytssxRNPTNpHA+7YIiqOi7AiJu1j+6aZZ5457bDDDr0act98883p3HPPTS+88EKeZI199Xffffe8N3+InhFXXnll3mrqhBNOyNtC/fKXv8z79fcMOV5//fW8ciN+dvSuiIAiGnGvsMIK3cdEuBITvjfddFPe2ir6UwwYMCAHIEXfgOJM9Ysuuqj7+3bddde84iNCkhlmmGF4H7J0yy235LHHapKYSI7HZKGFFsrBS4zvu8Rqj+hRsMzfz0ptHUOG++cx6vn8twPTeDP83+86AAAAAAAVAgxGHgHG6EOAAaOuCMtjhSAA9aVWA9SbOg3Aj7KF1OgqGh03ynxiFYoGVAAAAAAAUJ0AYwRFj43YRqvMNNNMM1TjcgB+eoqtBwGoL7UaoN7UaQDKCDBG0KGHHpq++OKL0mPGGGOMkTYeAJpHw0GA+lOrAepNnQagjABjBM0000zNHgIANdpW0BljAPWmVgPUmzoNQBnPEAAAAAAAQO0IMACgotbW1mYPAYAG1GqAelOnASgjwACAirq6upo9BAAaUKsB6k2dBqCMAAMAKurs7Gz2EABoQK0GqDd1GoAyAgwAAAAAAKB2BBgAUFH//v2bPQQAGlCrAepNnQagjAADACoaMmRIs4cAQANqNUC9qdMAlBFgAAAAAAAAtSPAAICK+vXzNApQd2o1QL2p0wCU8SwBABW1tLQ0ewgANKBWA9SbOg1AGQEGAFTU0dHR7CEA0IBaDVBv6jQAZQQYAAAAAABA7QgwAKCi1tbWZg8BgAbUaoB6U6cBKCPAAICKurq6mj0EABpQqwHqTZ0GoIwAAwAq6uzsbPYQAGhArQaoN3UagDICDAAAAAAAoHYEGABQUf/+/Zs9BAAaUKsB6k2dBqCMAAMAKhoyZEizhwBAA2o1QL2p0wCUEWAAAAAAAAC1I8AAgIr69fM0ClB3ajVAvanTAJTxLAEAFXmzBVB/ajVAvanTAJTxLAEAFbW3tzd7CAA0oFYD1Js6DUAZAQYAAAAAAFA7AgwAqKi1tbXZQwCgAbUaoN7UaQDKCDAAoKKurq5mDwGABtRqgHpTpwEoI8AAgIo6OzubPQQAGlCrAepNnQagTFvptTTd55semtr6yZl+ylrGHq/ZQwAAAAAAqB0BRs2NN90vUlub/yaAOlKfAepPrQaoN3UagDJO7QeAijo6Opo9BAAaUKsB6k2dBqCMAAMAKtJwEKD+1GqAelOnASgjwACAilpaWpo9BAAaUKsB6k2dBqCMAAMAKmptbW32EABoQK0GqDd1GoAyAgwAqKi9vb3ZQwCgAbUaoN7UaQDKCDAAAAAAAIDaEWAAQEWWuwPUn1oNUG/qNABlBBgAUFFXV1ezhwBAA2o1QL2p0wCUEWAAQEWdnZ3NHgIADajVAPWmTgNQRoABAAAAAADUjgADACpqa2tr9hAAaECtBqg3dRqAMgIMAKioo6Oj2UMAoAG1GqDe1GkAyggwAKAiDQcB6k+tBqg3dRqAMgIMAKiopaWl2UMAoAG1GqDe1GkAyggwAKCi1tbWZg8BgAbUaoB6U6cBKCPAAICK2tvbmz0EABpQqwHqTZ0GoIwAAwAAAAAAqB0BBgBUZLk7QP2p1QD1pk4DUEaAAQAVdXV1NXsIADSgVgPUmzoNQBkBBgBU1NnZ2ewhANCAWg1Qb+o0AGUEGAAAAAAAQO0IMACgora2tmYPAYAG1GqAelOnASgjwACAijo6Opo9BAAaUKsB6k2dBqCMAAMAKtJwEKD+1GqAelOnASgjwACAilpaWpo9BAAaUKsB6k2dBqCMAAMAKmptbW32EABoQK0GqDd1GoAyAgwAqKi9vb3ZQwCgAbUaoN7UaQDKCDAAAAAAAIDaEWAAQEWWuwPUn1oNUG/qNABlBBgAAAAAAEDtCDAAoKKOjo5mDwGABtRqgHpTpwEoI8AAAAAAAABqR4ABABW1tbU1ewgANKBWA9SbOg1AGQEGAFRkuTtA/anVAPWmTgNQRoABABV1dXU1ewgANKBWA9SbOg1AGQEGAFTU0tLS7CEA0IBaDVBv6jQAZQQYAFBRa2trs4cAQANqNUC9qdMAlBFgAEBF7e3tzR4CAA2o1QD1pk4DUKat9FqavgekJ3KA+ooabck7QL2p1QD1pk4DjDor5lqaUK8FGDXV0dGRPz/44IPNHgoAAAAAAKOxZZZZJrW1jfw4oaWrONWfWuns7Ezffvtt05ItAAAAAAAIzZqnFmAAAAAAAAC1o4k3AAAAAABQOwKMJnjggQfSBhtskH75y1+m5ZdfPp133nndTbuHDBmSDjrooLTwwgunVVZZJd177729vvfrr7/O+409/vjjTRo9wE9vy77LLrssrbXWWmn++edPK6ywQjrqqKPS559/3n3MJptskmabbbahPp5++unuY0466aS0+OKLp+WWWy5dffXVvX5G1Pj1118/XX/99SP1vgH8VHzzzTdprrnmGqoOR90uRE3ebLPN8mVLLbVUOuGEE/KWrD2p1QA/vIcffniYr5WLj9NOOy0f5zU1QHO88847aaGFFsr1uqdXX301bb/99vm6RRddNB188MG95kLCF198kQ499NC05JJL5tfZ2267bXrppZd6HRPz1GussUa+nX322Sd9+eWXva6/8MIL05Zbbll5/Jp4j2RPPvlk/sVYbbXV0m677Zb/g4899tjctHu77bZLV1xxRfrb3/6W/vjHP+Yn8T322CPdcccdaZJJJsnff8EFF6Q555wzLbjggs2+KwA/Ceeee25+o7T11lvnN0svv/xyOuWUU9ILL7yQzj///HzM888/n59sV1111V7fO/PMM+fP99xzTz72iCOOSJ988kn6wx/+kOaZZ570i1/8Il9/00035aAkQhIARty///3v1N7enl83TzfddN2X9+v3f+djvf7667lOzzfffLmmv/jii+nEE09MH3/8cTrssMPyMWo1wI8jAubLL798qMujHse8RkxqRfjgNTXAyPf222/n+Y7PPvus1+Wffvpp2mKLLdLPfvazNHDgwPThhx/m19pvvPFGPtm+sNdee6X/9//+X/rd736XxhtvvBxKb7755rkmTzjhhPmEod133z2fcL/SSivlE0LPOOOM/H0hApEzzzwznXPOOZXvgwBjJDv11FPTHHPMkX8hwtJLL53fjMV/ZPzn//3vf0+rr756WnHFFfNZwJdcckl66qmn0rLLLps++uij/GR+8cUXN/tuAPwkxBugeBLdaKONup9cl1hiiTTxxBPnAPmZZ55JE0wwQT7jIJ6MY2JsWKJ2x/etvfba+esrr7wyPfLII/nNVjyZxyRanMnQjGZXAD8Fzz33XGpra8uTXmOMMcZQ10ctH3fccdPpp5+er4+aPdZYY6XDDz88nzw09dRTq9UAP5KY0Or7OvnOO+9MDz30UDr55JPTjDPOmM/y9ZoaYOTOd1x77bXp6KOPHub1sRNFnOwTq92KE+enmGKKfIJ9nHAfJ88/8cQT6e67705nn312rt8hVlnEnPWll16adthhh7wa4913381zKjGXEieF3nDDDd1zLPE6PVZ3RNhdlS2kRqJ4wo2lOpFG9RRbRcUTefxyxBPxmGOOmS+Pf8cbtVidEeINWWw5VZx9AMD3E2cCrLPOOmnNNdfsdflMM83UfUbv4MGD879nn33277ydnrU79O/fv7t2x5N6TJxFYA1ANVGLozYPK7wotmiNN1U9r4+wI964xXVBrQYYOWLr61hFESdiFqstvKYGGLmef/75HPquu+666Zhjjhnq+niNHCFFEV6E2IY1Tgq67777uo8ZZ5xx8uWFOD5aH/RtexAnDxW1O16Dh//+97/55PxYofF9CDBGopgIix4XM8wwQ6/Lp59++vw5Eqo4EyGWTcZ/cGwdFXuGzT333Pl7IxHbddddmzR6gJ+eWF1x4IEHDrUtX9TfMMsss+Q3W/GEHU/4cdZALGPvu+dj1O44OyzqeCytjK1OFlhggbxEM1bYxVJLAKqLWtza2pq22mqrXHMXWWSR3DcuguiYKHvzzTfzGb49xZurOCs4anNQqwFGjtjrPOY0DjjggO7LvKYGGLmmmmqq3KZg//337w4XeootV/u+fo7X29NOO2336+c4Jr6Oy3uKLV2LY2KeO1Ze/PWvf83bUN16663dcyyxE1Fs+1fMfVclwBiJir3G4o1UT5FshXgD9pvf/CafXRZnKsQvWCx7j+U7sXfk//zP/6SJJpoo7bfffnnVRrxp++qrr5pyXwB+quLNUiyPjMaBs846a962JMLkCDv+9Kc/5bPJYgn8pptumt+YhTizLFbXxUqO2A4wehxF+BxLJWOSLZZKRm+jOC62poondQCGT7FvetTeWK4etTW2hbrxxhvzEvfYJ31Yr7GL19lFI0K1GmDk7DwRAUZsjd1zwspraoCRa6KJJkpTTjll6Tx1MSf9Xa+f45jveo0duwmFCEeih0bU9tgGMHYT2nnnnXP4ccstt6Qdd9wxb0O1/vrrpwEDBuTtAkeUHhgjUbF85rtEE8L4T49mKHEmWSydjCWUsQf7/fffn26//fYcZETn+NhOKjrAR6PZfffdd6TdB4CfstjKLybF4gyDeHMU4s3RNttsk5dIFvs9xplgq622Wn5zFmeCRa2OJrGxmiPOTIiPeCMWPYuuuuqqvGQynqTj7IM4e+yQQw7J9RuA4QswohFgrKgotlKNmhwNB6MGxxatZYq90tVqgB/fbbfdlt577738+rknr6kB6vcau9Hr5+E5JsSJ+NH3KE60H3vssfNlcQL+Zpttlue7I5A+/vjj89z4TjvtlHe9mHTSSdPwsgJjJBp//PHz5yKhKhSpVs9EK4KM4hchGn5Ht/hIzuLFQKzEmHnmmdPGG2+cvwbg+7v55pvTlltumZdZDho0KC+BLPbpLd5oFX7+85/nOhxnkvUUe68XSyujYWGcPRar6qJWRzPCmHjbYostclPDYj9fAMrFm57YbqRvH7h4oxTeeOONYb7GLl5nF6/BC2o1wI8namnU0b69LrymBqiX8cYbr+Hr5+86Ji7r+xo7FOHFY489lp588skcXMfqizhJNFbYxY5CMedS9NgYXgKMkSj2B4sn4Vgm2dNrr72WP8cTd1/xHxpLbmL5ZPjggw9ykBEmnHDC9P7774+UsQP8lJ133nlpzz33zPvuxpldk08+eb68vb09XXP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y18nl8NyTvE5fh64DTU1NsmDBAhk3bpyj5xU6jdvt5ngpQ+Z6kb3ezM2v920Vh4tIpidSWzJTk2VYQOPsHOmZFYPGRgm0+l1ZVX1AbyZTZNpecVCaOlgCz4xTMiPApgwtsBczoilYvN71IXO9yF4fMtfJ3Y3c8/PzJdIYoQQAQIIwRaTNe2tkyeb9snB9uezYf7DN7QYXZcu04YUycXC+nYLFtKvwMU3Ie/fIsJdJQwqarzcry+2q/LI/05dFJtOzytefyZSaTP8qc/nzh1tkYEGmTBlaKFOHFsjgXtkJN70QAADEP0YoKe0U7/ShcwgvMteL7BOf+TVuChO+kUimf09bzMijacMKZeqwQunTMyPq+4n2C4CLNlbI4o3ldkRZW4py02TykEI7cumI/j0kuZ0CIK93fchcL7LXh8x18nQj92iMUKKgpBAnI33IXC+yT0wej1fW7Kqyo5AWbSxvcxUyU3IY1b+HTB1WIFOHFtom2nA20+dqsS0uVdiRSm3JzUixI58mDy2QscU9JS3l8PsfXu/6kLleZK8PmevkoaAUORSUQsP8W33IXC+yTxxmytTq7ZV2FJIpOFTWNrbaxgxcMU2ep48okilDCiSvm02eETv7ahpkyaYKWbyhQlZtr7T5t5Se6pJxJXm2YDhhcL5kpCTxeleGc7xeZK8PmevkdngPJQpKCnEy0ofM9SL7+Nbo9shnpYeKSEs3VbS5TL2Z/mRGqpipbGbkSnaai8wTTE19kyzbvM8WEpdv3Sf1LVaR8z0PjuyfK1OHFdkV4wpyKCZqwDleL7LXh8x1clNQihwKSqExkdPcUxcy14vs409Dk1tWbD3UVHvp5n1ysMHdahuz3Pz4QXm2iGQaa5tl7X3IPPGfHytLK21xqb0iozGiT46dFmcae/fPD37FOMQHXu96kb0+ZK6Ttxu5U1DqBAWl0FDd1ofM9SL7+FDX4JZlW/bZkUjma1sjUMz0pgmD8mX68EIZX5IvGWlt50rmephpcGt2Hviy71K5lFW17qVl+FaMM029h7BiXELh9a4X2etD5jq5GaEUORSUQsPJSB8y14vsnT2NyYwwWbShwo5IMtPbWspKS5aJQwpk+rBCGVsS2IC5PWSuk3k7t3F3lSzdst/2XSqtqG1zu8KcNLva38yRRTKsdw7FpTjH610vsteHzHVyU1CKHApKoeFkpA+Z60X2zmKmr5lRSB+vL7PTltpqtGxW8TJTlcx0tjEDe0pKcnAre5C5Xv7Z7/pyxbhFGytk/a4qaevNXu8e6TJzRJG9FBdmUVyKQ7ze9SJ7fchcJzcFpcihoBQa5t/qQ+Z6kX3smaLRytL98p8v9tpVuxqaWo9EystKtdORTBHpqAE9bYPlUJG5Xu1lb1aMM6PhTIHps21tFzLNtLgZI4pkxvAiei7FEV7vepG9PmSuk5ceSpFDQSk0VLf1IXO9yD42zK/WzWU18t4Xe+WDdWVSWdvY5tQjU0Ay049G9s0VVzeKSP7IXK+uZF9d12hHLX20rswWl9p6F2j6LJlRS6bAVJSbHrkdRrfxeteL7PUhc53cjFCKHApKoeFkpA+Z60X20VVRXS/vry2zhaS2etjkpKfY3jXHjOwlI/pGpn8NmesVbPb7axrk4w3ltri0ZmdVm9uYYqcpLplm8HnZaWHcW4QDr3e9yF4fMtfJTUEpcigohcbj8YjLFVxPDsQ3MteL7KOzQtuijeXy3pq98llpZateNSmuJJk4OF++ckQvu0pbsD2RgkXmenUn+7KqeltYMpeNe2ta3W5qn6MH9LTFpanDCiQnIzUMe4zu4vWuF9nrQ+Y6ebqROwWlTlBQCg0nI33IXC+yjwyP6Yu0rdIWkRZvKJf6NvoimZEdpog0Y3hhVD98k7le4cp+5/6DtrD04boy2VZxsNXtpsfX2OI8O9pu8pACyUzjPVis8HrXi+z1IXOdPBSUIoeCUmgYLqkPmetF9uG1xfRFWrNXPlhbZhsdt7Vq1ldG9bKXvnmxaWxM5npFIvvS8hr5cF25fLB2r+w5UN/q9tRkl0wYnCezRvSyX9NSeO5FE693vcheHzLXye3wKW8pEf8JAADEMVM4Mh+mzSptW8tb90XKTk+2K2OZ0UhmVBIrsCCRFBdmy/mF2XLetGLZuKfajlr6aF25VHxZUG10e2TRhgp7yUh1yeShhTJzRKEdwRTp6Z0AACC2GKGkEEtO6kPmepF9aOoa3bJkY4UtIq3ctr/VSlhmyo/ph2RGIk0ckm9HaTgFmesVrew9Xq9t4m2mxX28vkwOHGxqtU12eopMG1ZgV4ozvZfCtYohAvF614vs9SFznbzdyN3xU9527dolp59+ujz66KMybdq0Dgs/Tz31lLz00kuyZ88eGTRokFx99dVy6qmnBmy3cuVKuffee+Wzzz6T7OxsmTNnjlx33XWSltb2qiIUlELDcEl9yFwvsg+uL9Kq7ZV2hTbTZLuusXVfpOF9cmwRyXxI7pHpzKbEZK5XLLJ3m9fNtko7cmnRhnKpbXC32qZnVqpMH1Zoey6N6JsrLj4QhQ2vd73IXh8y18mdqFPedu7cKd/5znekqqrtZWb9Pfzww/Kb3/xGrr32Wpk0aZLMnz9ffvCDH9gDc9JJJ9ltSktLZe7cuTJ+/Hh58MEHZcOGDfLAAw/I/v375Ze//GWouwkAQKc9Yv5j+iKtKWuexuOvV266HPNlX6T++bHpiwQ4lW3QXZJnL985bqh8unW/LS4t2VQh9V8WZStrG2Xeyl32UpiTZguys0YUyeBe2fy1HQCAOJYSSpfx1157Te65554u3+fll1+2I5nMaCNjxowZsmrVKvnjH//YXFD67W9/a0clPfbYY3ZE0uzZsyUjI0Nuv/12ueaaa6R///7B7ioAAG1qcnvk4/Xl8s9Pd8qG3dWtbs9KS5bpwwvlK0f0llH9GFEBdIWZ+jlpSIG91De65ZPN+2xxafmWfdLoPjQgvry6Qf6+bIe99O2ZYUctzRxRJAMLsmK9+wAAINIFpTVr1shtt90mF154ocycOVOuuuqqTu/T0NAgOTk5Adfl5eXJjh07mr9///33bRHJf3rbySefLL/4xS/sbeedd16wu4p2sNykPmSuF9kHqjrYKG+v2m1HSrRcpc2MtBhXkmdHIk0akh+3q1WRuV5Oyj49NdmORDKX2vomO2LJFJdWllbaaXLGrso6eWXxNnspKcxq3t4UmhB/mSO6yF4fMtfJ5fDcgy4o9evXz05Z69u3ryxcuLBL97nkkkvkySeflK9+9asyceJEeeedd+S9996TH/7wh/b2uro62b59uwwZMiTgfgUFBbYQtWnTpmB3E52MMmP+rS5krhfZH7K9olb+uWKnndrW0BTYG8l8kP3qUX3sylQ9s9ru2RdPyFwvp2aflZ4ixx7R214OHGy0vZZMQ+/V2w+Ir5GnWUFxa/lWef7jrTKsd44dtTR9RKEU5qTHeO+dzamZI/LIXh8y18nj8NyDLiiZkUXBuuyyy2T58uVy5ZVXNl93zjnnyBVXXGH/7evD1HIUk2GmwVVXt56OAABAR8yaE6afyz9W7JQVW/cH3GYmsJlpOaeM6ydHDehBHxcgSkwz+68d3ddeKqob5OMNZfLR2jJZ5zf1dMOeanv5wweb5Yj+PWxxyawYlwgFXwAAEknITbm7ykx3u+iii2Tv3r12+trQoUNl2bJl8n//93+SlZUlP/vZz2zVrSOdvdE3nc99w8H8H8v/e99j+Ba1i9W25uL73txm7ue7r6k8+v4vkdq25TFzynEJ17bROIadbevE4xLOzKP9nG25bTw8D510jjC3B3uOcOJxCWZbMwLpvTV75V+f7pLt+w6Kv4xUl8w+opecNKav9M3LTMhzhP/PjUU2nCNid44wt0XjfUS4/q/52aly0tF97GXPgTpZtPFQz6UtZbXN9/9ixwF7eeY/G2X0wJ4yY3ihTB6SL7mZabyP+FK8nb85R0T2XO+Ezxrxcgzj7RzRVuZOOS6cI7wR29Zc193PgXFdUJo3b5588cUX8vTTT9ueS8bUqVPtaCSzepvpjTRgwAB7fU1NTav7m9FJubm5Hf4M84TwDQNrORyso+FhsdrW/3vfEyCa2/qelKHuf7xtG+vj3d39D8e24cxc6zGM5rbhPIbmOl/2iX68zWiHN1futD2SquqaWq3UdvK4fvLVI3vb6TftPVYiPL/by7y7j9vVbRPhGDp92/aOiznXx+vx7pefLWdOMpeBsn1frXy0rlw+XFsmO/YfKgqbtkum/5K5PLUgScYNyrMjlyYNLpCMNFfcnJPDsa2/tn6/O/E5689pxzBet+3oXO/k52wibhvN492VzIPdf6dty3M2kK/g1Z3HjeuCkq/xtumd5G/KlCn26/r162XkyJHSp08f2bJlS8A25eXltsg0bNiwSO+mKv5/1YIOZK6XhuzNKm3/XLFDPlpf3tzs18es0Hba+P52eptpuq2BhsyR2NkPyM+Sb07NknOmDLS9lUxhyYxc2ltVb29v8nhl6aZ99pKe4pKJQ/JtcWlciWmm7+zmpeGWKJkjeGSvD5nr5HV47hEvKJkpbsaSJUvkmGOOab7+k08+sV8HDhxov86aNUveffddufXWW5tXejOjm0x1bfr06ZHeTQBAHPF4vLJ4Y4X8Y8UOWbPzUB8+H1M4MitFnTK2nwzr07o3H4D4YP4iO6go216+NaNE1u+utoWlj9eVyb7aRrtNfZPHjmYyl8y0ZJkytMAWl44e2FNSknUVlwAAiPuCkpmiZkYdlZSU2FXajj/+eBk3bpz8+Mc/luuvv94WmD799FPbQ8ncNnbsWHs/06D7jTfesF/nzp0rmzdvlvvvv99Oievfv3+4d1O1jqY+ITGRuV6Jlr1Zfvzfq/fIvz7d2TxawSc3I8U2+j3x6L5SkKO3eW+iZY6uS+TsTXFpRN9ce7l41mD5fMcBu1Lcwg3lzVNcDza45T9f7LUXcz6YNqzQFpeP7N9DXAk6QjGRM0fHyF4fMtfJ5fDck7zdGEO1cOFCueSSS+TZZ5+VadOmBVx31113yZw5c5qLTA888IAdcVRZWSnFxcVy1lln2dXffKORfKOY7r33Xvn8888lPz9fzjzzTLnhhhskNTW1zZ/f1NQkCxYssAWraM4TjHemARnHSxcy1ytRst9VWSf/WrFT3v18t9Q1BjYaHFiQKaeM6y/HjCyS9NT4/792V6JkjuBpzL7J7ZHPtlXakUtm1KIpKrWUn5Uq00cU2ZFLw/vktOqjEc80Zo5DyF4fMtfJ3Y3cTU3F0QWlWKOgFBpORvqQuV7xnL359bR6+wH554qdsnRThbT8ZTV+UJ4tJI0t7plQHxA1Z47u0Z69WeFxxdZDK8WZ/krm+5ZMg35TWJo5skhKCrPi/tyhPXPNyF4fMtfJTUEpcigohYaTkT5krlc8Zt/o9tgmvKaQtLkscPVP03D32CN62f5IAwqyYraPThaPmSM8yP6wuga3LN1cYYtLy7fsb9Ww3+ifn3mouDSiyP47HpG5XmSvD5nr5KagFDkUlEJjIo/3v8ghOGSuVzxlX1nbIG99tlve/GyXVH7ZcNenIDtNThrbV44/qo/kZrY9DRrxlznCi+zbVl3XJEs2lsuH68rls237pY3akgwuypYZIw71XOrdI0PiBZnrRfb6kLlO3m7kTkGpExSUQkN1Wx8y1ysest9SVmNHI32wdq80ugN/JQ3rnSOnju9nm+uyYlPiZI7IIPuuFa4XbqiwDb1NY++2jOiTIzNGFsn0YUWOb/BP5nqRvT5krpObEUqRQ0EpNJyM9CFzvZyavcfrlWWb98k/VuyUVdsqA24zf4QxBaRTx/WXEX0Tq4Gu5swReWQfnPLqevl4fbmdYrthT3Wr282Z56gBPeyopanDCqWHA0dHkrleZK8PmevkpqAUORSUQuPxeBy//CDCi8z1clr2Ho/XfoB7ZUmpbKs4GHBbVlqynDC6j3x9TF/pFUdTTpzGaZkjesi+eytJmlFL5rK1vLbV7cmuJBlT3NP2W5o8tECy0lLECchcL7LXh8x18nQjdwpKnaCgFBpORvqQuV5Oyd40xDUf1F5Zsk127AssJPXtmSGnjOsns4/oLRlpnMsTJXNEH9mHR2l5rXy0vsyOXDKFppZSk5Nk/KB8W1yaODhf0lNjd94ic73IXh8y18nj8IKSM/68gqiK4xoiQkTmesU6e1NIMr2RXlm8rdUHs1H9cuUbEwfIhMH54mJaW8Jkjtgh+/AoLsyS4sISOXdqsWzeW2NXijOX8uoGe7vp9bZ4Y4W9pKe6ZPKQAltcGluSJ6lR7vVG5nqRvT5krpPX4blTUAIAhF2T2yPvr9krry7dLrtbFJKO7N9DzplaLKMH9KA/EgDHMuenIb1z7OWCmYNk3a4qO2rJTNutPHhoJcr6Ro98sLbMXrLTk2XK0EJbXBo9sKedJgcAQCJjyptCLDmpD5nrFe3sTSHpP2v2ymtLtsmeA/UBt5nmtudMKbYftBA5vN71Ivvojbxcvb3STuM1K8bV1De12qZHZopMH15kG3qb0ZiRGoVJ5nqRvT5krpO3G7nTQ6kTFJRCwwoB+pC5XtHK3hSS3v18j7y2dLuUVQUWko4e2FPOmTJQjhxAISkaeL3rRfbRZ859n5bulw/XlcuSjeVS1+hptU1BdprMGGFGLvWSob2zw/qBkMz1Int9yFwnN6u8RQ4FpdBwMtKHzPWKdPaNbo/8e/UeeX3ptub+Ij5ji/PknKkDZVS/HhH7+WiN17teZB9bDU1u+WTzPttvadnm/fb82FKfnhl2StzMEYVSXJjd7Z9J5nqRvT5krpObglLkUFAKDScjfchcr0hl39BkCkm75fVPtktFi0LSuJI8O7VtZL/csP9cdI7Xu15k7xy1DU2ydNM+23PJjGAy0+RaGliQaYtLZlpcv7zMkH4OmetF9vqQuU5uCkqRQ0EpNMy/1YfM9Qp39qaQ9M7q3fLXpduloiawkDRhUL4dkTS8D4WkWOL1rhfZO1N1XaMs2lBhRy6t2l4pbb3zHtor2xaWzKUoN73Lj03mepG9PmSuk5ceSpFDQSk0VLf1IXO9wpW9LSStOjQiaV+LQtKkwfkyZ0qxDOuT0+2fg+7j9a4X2Tvf/poG+XhDuW3ovWZnVZvbmCbeprA0fXih5GWldfh4ZK4X2etD5jq5GaEUORSUQsPJSB8y16u72ZueIG+t2i1/W7pd9tUeWibbZ/KQAtts2yypDefg9a4X2ccXs4CBKSyZkUub9ta0ut38QdosamCKS1OHFkhORmqrbchcL7LXh8x1clNQihwKSqHxeDzicrlivRuIIjLXK9TsbSHps93y10+2y/4WhaQpQwtkjikk9aKQ5ES83vUi+/i1Y99B+Wh9me25tH3fwVa3J7uSbH8603Np0pACyUw79L6XzPUie33IXCdPN3KnoNQJCkqhYf6tPmSuV7DZ1zd+OSKpnUKSabY9uFf3VyZC5PB614vsEyPD0vJaO2rJXPYcqG+1TWqySyYOzrfFpfGDekp6akpM9hWxxetdHzLXyUsPpcihoBQahkvqQ+Z6dTV7W0gyI5KWbZfKFoWkqcMOFZIGFVFIige83vUi+8Ri3qJv3FNtC0sfrStvtRCCkZHqkilDC21xaUxxT0lJZvSCFrze9SFzndxMeYscCkqh4WSkD5nr1Vn2dbaQtEv+9skOqTwYWEiaNqzQTm2jkBRfeL3rRfaJy+P12ibeH67dKx+vL5equqZW2+Skp8jUYYUyc2SRHNW/h7hcjGRIZLze9SFzndwUlCKHglJoGC6pD5nr1V72ppA0f+Uu+duy7XLg4OEPJmbLacMLZc7kgVJCISku8XrXi+x1cHu88tm2StvQe9GGcqltcLfaJi8r1a4SZxp6j+ibKy6eFwmH17s+ZK6TlylvkUNBKTQ0dNOHzPVqmX1dg1ve/GyX/L2dQpJZta24kEJSPOP1rhfZ61Pf2CQrtx2wzbyXbqqQ+iZPq22KctNsYclMixtclM0H0gTB610fMtfJQ1PuyKGgFBqGS+pD5nr5sjeFpHkrd8rfl+0ImCphPlZMH2FGJBVLcWFWTPcV4cHrXS+y1525GXm6bPM+23Np+ZZ90uhu/Ra/X16GLSyZy4ACzvnxjNe7PmSuk5spb5FDQSk0nIz0IXO9qg82yNur97RZSDJ/sTY9kgbyoSKh8HrXi+z1aS/z2vomWbyxwhaXVpbuF08b7/ZLCrNsYcn8LujTMyM6O4yw4fWuD5nr5KagFDkUlACgbQfNiKRPD41Iqq4PLCSZhq2mRxJ/nQaAxHfgYKPttWSKS59vPyBtvfEf1ifnUHFpeKEU5KTHYC8BAOFGQakTFJRCQ3VbHzLXo7ahSeZ9ukveaFlIShKZNaJIzp4yUAbkU0hKZLze9SJ7fYLNvKK6QT7eUCYfrS2TdburW91u/uhwRP8e9g8PZqXPHpmpYd5jhAuvd33IXCc3I5Qih4JSaDgZ6UPmOgpJ/1qxU95YvlNqWhaSRvayI5L652fGdB8RHbze9SJ7fbqT+Z4DdXalODNyaUtZbavbXUkiY4rz7JS4KUMLJDs9JQx7jHDh9a4PmevkpqAUORSUQsMKAfqQeeIyfTL++elO+UcbhaRjRvaSsyb1lwEFrNqmCa93vchen3Blvr2i1haWzGXn/rpWt6e4kmT8oHw7LW7ikHzJSOV9d6zxeteHzHXysMpb5FBQCo2JnCVjdSHzxGOKR2ZE0j9W7JCaenfAX5SPGdVLzp48UPrlZZK9QmSuF9nrE+7MzeOZ0Uq+4lJZVX2rbdJTXLaoZIpLpsiUmswH3Fjg9a4Pmevk7Ubuji8o7dq1S04//XR59NFHZdq0aW1u88orr8itt97a7mPcfffdcvbZZ9t/v/XWW/LYY4/Jpk2bpKioSM4880y56qqrJC0trc37UlAKDcMl9SHzxCok/dMUkpbvkNqGwELSV74sJPXNOzy1jez1IXO9yF6fSGZuPiKs311tC0tmatz+2sZW22SlJdvpcKa4NHpgT0mhuBQ1vN71IXOd3A6f8hbyZOidO3fKd77zHamqqupwu+OOO06ef/75Vtf/7Gc/k+rqapk9e7b9/oMPPpDrrrtOTj31VLnppptk3bp1cv/998u+ffvkv//7v0PdTQBICNV1ppC0wxaTWhaSjj2it5xlCkks+wwACBPzF/ERfXPt5eJZg+XzHQdscWnh+vLmRR/M76MFX+y1l9yMFJk2vNAWl0xjbxcjKQAg4aWEMofvtddek3vuuadL2xcUFNiLv2effVY2bNggzz33XPNtZiRT//795Ve/+pWtwM2aNUvKy8vl6aeflltuuUVSU1llIlyYe6sPmcf3iCQzGukfK3bKwTYKSWZEUp8OCklkrw+Z60X2+kQrc5cryY5AMpe5xw6Rldsq7UpxizdWyMHGQ7+bquqa5K3PdttLfnaaTP+yuDS8Tw7TdCKA17s+ZK6Ty+G5B11QWrNmjdx2221y4YUXysyZM+2UtGCUlZXJgw8+KBdccIGdquZTX18vmZmZAcO58vLypLGxUWpqauy/ER7Mv9WHzON51bbAHknJriQ59gjTbLvjQpIP2etD5nqRvT6xyNxMa5swKN9eGpo8snzLPjty6ZPN++z3xr6aBjui1lx690i3K8WZ4lJJYRbP0TDh9a4PmevkdXjuQReU+vXrJ/Pnz5e+ffvKwoULg/6BDz30kK2yff/73w+4/qKLLpIrr7xSnnzySTn33HNl48aN8vvf/95OiaOYFF5x3IcdISLz+FHX4JZ5K3fK3z7Z0TylwFdImm0KSZMHSu8eXZ/aRvb6kLleZK9PrDNPS3HJ1GGF9mJ+fy3dXGGLS8u37Be359C+7TlQL68v3W4vA/IzbWHJFJj65x/u94f4yx7RR+Y6eR2ee9AFpe4Ud8wUNjNdbu7cudKjR4+A26ZPn257Mt177732Yhx11FFy3333hfzzACBe1De6Zf5nu+Svn2yXAwebWk1tmzMluEISAADRlJGWLLNG9rIX0/dv8cZyW1z6bFul+D4Pbd93UF5cVGovg3tlHyouDS+UXvx+A4C4FHJT7lC8+OKLtgfTpZde2uo2M43O9FH67ne/KzNmzJDt27fLI488IldccYU888wzdjpcR53PDTPyyTy+j//3vmFivgpfrLY1F9/35jZzP999zXQ/3/8lUtv6bve/rxOOS7i2jcYx7GxbJx6XcGYe7edsy23j4XkYzLZmdsBbn+2Svy3bEbCCjrnbMSOL5KxJAwKabYdyDM02wZ4jYn1cOEd0b1uzL7E63pwjdLyPcNpx0XyOcGI2malJcuyoIjuytrK2URZuKJeP1pfLmp2HF/PZvLfGXv784RYZ0SdHZowolOnDi6Rn5qGPJ5wjQjvXc45I3HNEW5k75bjwPsIb0W3N11AfN9KSvL6fHAIz5e2SSy6xTbanTZvW6fZnn3229O7dW5544omA63fv3m2ntl199dXygx/8oPn69evXy2mnnWZXefv2t7/d6vGamppkwYIFthcTSyh2HUtO6kPmztPo9si/V++R15Zsk4qahubrza8EMxXgnKkDZUB+Vrd/DtnrQ+Z6kb0+8ZZ5WVW9XSXOjFzasKe61e3mc9FRA3rakUtThxZIbiaL8iRK9ug+MtfJ3Y3c8/PzJWFGKJmi0erVq9scnbRjxw5bUZs4cWLA9cOHD7dT7NatWxet3QSAiGpye+Q/X+yVV5aUSlnV4UKSMXVYgZw7tViKC7Njtn8AAERKUW66nDahv73sqqyTj9aV2cvW8lp7u/kz96ptlfby1IKNMra4p/0jy+ShBZKVFtWJFQCALojamXnFihX2a8uikTFo0CBbdVu6dKkdqeRjGnPv379fiouLo7WbKviGxUEPMo8905z0vTV75ZXFpbZBqb/JQwrkm1OLbT+JcCN7fchcL7LXJ54zN9O5z5480F5Ky2vtqCVTXDKFJt/vzWVb9ttLanKSXVVu5sgi+zU9lVEa8Zw9QkPmOiU5PPewF5Sqq6vtVLWSkhIpKChovn7t2rWSlpZmr2/JbGdGLpkV3oyZM2faUUumh9KAAQPkvPPOC/duqub0JyXCj8xjx+Px2jfJLy0qbX6T7DNhUJ58c2qJDOuTE7GfT/b6kLleZK9PomReXJgl5xeWyHnTimXT3hr7e9NcKqoPjeRtdHtl0cYKe0lPddk/xJhpceNK8iQl2SUaJUr26Doy1ylJW0Fp1apVtq/SXXfdJXPmzGm+vqysrNXKbv5uvvlm6dOnjzz33HPy1FNP2V5Ls2bNsj2VOrofgmeadDH/Vhcyjz6P12v7RJhCklnVxt+Y4p5y7tQSGdkvN/L7QfbqkLleZK9PomVuPjgN7Z1jLxfOHCTrdlXJB2vL7O/TyoOHFq6ob/TY68wlOz1Zpg4rtMUl03sp2SyNqkSiZY/OkblOHofn3q2m3LFGU+7Q0NBNHzKPHnNKXbyxwhaSfD0hfI4a0EPOnVYiR/aPXpGc7PUhc73IXh8tmZvpb6u3V9pRS4s2lEtN/eEVxXx6ZqbKtOGHikvmDzYuh/9Vv7u0ZI/DyFwnt8ObclNQUshE7vShcwgvMo/OMf5k8z55cVGpXQbZ36h+uXLetBIZPbBnTPaL7HUhc73IXh+NmZvFLVZs3W/7LS3eVGFHLLVUkJMmM4YXyayRRTKkV3ZCHiON2WtH5jp5u5E7BaVOUFAKfdicy6VzvrlWZB455hRq3ti+uLC01RLIw/vk2BFJZpWaWL0BIHt9yFwvstdHe+b1jW5ZtmWfHbm0bPM+22uprebfZqU4M3LJ9GpKFNqz14jMdfJ0I3cKSp2goBQahkvqQ+bhZ06dn22rtIWktbuqAm4zfw09d1qxXYkm1n9JInt9yFwvsteHzA+rbWiSpZv2yYdr98qnpZV2mlxLxQVZdqW4GcMLpW9epsQzsteHzHVyM+UtcigohYaTkT5kHl6fb6+UFxaWyuc7DgRcX1KYZQtJZvWZWBeSfMheHzLXi+z1IfO2VR1stCvCmZFLq7dVSlsfdob2zrajlqYPL5Ki3HSJN2SvD5nr5KagFDkUlABE09qdVfLCwq12ZJK/gQWZ8s2pxXalmURvAgoAQDzZV9NgV4kzxaWWI4r9ex0eKi4VSs+stKjvIwBEAgWlTlBQCg3VbX3IvHvW766yU9tMryR//fIybCHJNP50OXSpYrLXh8z1Int9yDw4ew/UycdfFpc2tVhAwzB/Ezp6YE9bXJoytFByMlLEqcheHzLXyc0IpcihoBQaTkb6kHloNu2tlpcWlsrSzfsCru/dI90WkmaN7CXJDi0k+ZC9PmSuF9nrQ+ah27HvoHy0vkw+XFsm2/cdbHW7+f0+viTPNvQ2U9kz0px1nMleHzLXyU1BKXIoKIWGk5E+ZB6crWU18tKiUtt/wZ/psXDOlIHylVG9JCU5PlbZIHt9yFwvsteHzLvPfBTaWl5rRy19tK5M9hyob7VNWopLJg7OtyOXxg/Kk7SU2B9zsteHzHVyU1CKHApKoTGRO6VhMKKDzLtme0WtvLio1A6H91eQkyZzJg+U447sHTeFJB+y14fM9SJ7fcg8/Mdzw55qO2rpo/Xltv9SS5mpyTJ5aIFdLW7MwJ4xe19A9vqQuU7ebuROQakTFJRCQ3VbHzLv2M79B+XlRaXywdqygJVg8rNS5czJA+X4o/rYv07GI7LXh8z1Int9yDxyPF6vrNlxwI5cMn9oqqprarVNTnqKTBteaEcuHdm/R1T7KZK9PmSuk5sRSpFDQSk0nIz0IfO27a6sk1cWl8p7a/aKx+9M2DMzVb4xaYCceLQpJMX3cSN7fchcL7LXh8yjw+3x2hVeP1y7106HP9jgbrVNXlaqTB9eZItLI/rmRHwkCdnrQ+Y6uSkoRQ4FpdB4PB5xueJztAVCQ+atV3l5dcl2WfDFHvsm0Sc3I0XOmDhAvj6mr2SkJsY5hez1IXO9yF4fMo++RrdHVmzZb0cuLd1UIfVNnlbbmJ6LprBkLoOKsiJSXCJ7fchcJ083cqeg1AkKSqHhZKQPmR9SUV0vry7ZJu+sDiwkZaenyOkT+svJY/tJpsNWcekusteHzPUie33IPLbqGt3yyeZ9tpn3ss37pMl/uPOX+udlyowRhbbn0oD8rLD9bLLXh8x18lBQihwKSqFhuKQ+2jPfX9Mgry3dLm+v2iWN7sOnPFM8Om18fzl1XD/JSk+RRKQ9e43IXC+y14fMnaOmvkkWb6ywxaWVpfsDptL7mNFKZtTSjBFF0rtHRrd+HtnrQ+Y6uZnyFjkUlELDyUgfrZkfONgory/dLvM/2yUNfkPSM1Jdcsq4/nLa+H6Sk5EqiUxr9pqRuV5krw+ZO/f9x8IN5Xa1uC92HAhY8MNneJ8cW1wyfZfMarLBInt9yFwnNwWlyKGgFBqWnNRHW+ZVBxvl78t2yL9W7pT6xsOFpPQUl3x9bF85Y8IA6ZGZ2IUkrdmDzDUje33IPD6m25tV4kzPpfW7q1vdbtI7on8PmTWySKYOK+zy+xOy14fMdfJ2I3cKSp2goBQaqtv6aMm8uq5J/rFih/xz+U452Hh4BZbUZJddsc2s3JaXFfxfAeOZluxxGJnrRfb6kHn8rS778foyW1zaUlbb6nZXksiY4jw7cmnK0IIOp+OTvT5krpObEUqRQ0EpNJyM9En0zGsbmmwR6Y3lO6TWbynfFFeSfM0UkiYODGk4eSJI9OzRGpnrRfb6kHn82l5RawtL5rJzf12r2817mAmD822/pYmD81utPkv2+pC5Tm4KSpFDQSk0nIz0SdTM6xrc8q9Pd9rpbdX1Tc3XJ7uS5KtH9ZazJg20S/dqlqjZo31krhfZ60Pm8c98FNtcVmMLS6ahd1lVQ6ttzJT9SUMK7MilcYPy7MhrsteHzHVyU1CKHApKoWH+rT6Jlnl9o1veXLlL/vrJdqmqawoYKj77yN5y9uSB3V49JVEkWvboHJnrRfb6kHni5bluV7UtLpmpcftrG1ttk5WWbHstzRheKEcX59k/okEHXu86eemhFDkUlEJDdVufRMncrNT21qpdduW2Sr83WeYc+5VRvWTOlGLp25NCUiJmj64jc73IXh8yT1wej1c+33HAFpcWri8PGInt0yMzRaYNK7Qjl0b17yEuig0Jjde7Tm5GKEUOBaXQcDLSJ94zb3R75J1Vu+W1pdtlX83hoeDmbZPpLfDNqcXSPz8zpvvoVPGePYJH5nqRvT5krkOT2yMrSyttcWnJxoqAhUd8CrLTZPrwQpk5skiG9c5hJEsC4vWuk5uCUuRQUAqNx+MRl8sV691AFMVr5uYN1Luf75FXl2yT8urAngLmTdM5U4qluDArZvsXD+I1e4SOzPUie33IXJ+GJrcs37JfPli7Vz7ZvN/+0a2l3j3S7aglczHvkyguJQZe7zp5upE7BaVOUFAKDScjfeItc7fHK+99sUdeWbJN9hyoD7jNLKNrRiQNKsqO2f7Fk3jLHt1H5nqRvT5krjv7+iavLN1UYZt5L9+6375/amlgQaYdzT1jeBGjueMcr3edPBSUIoeCUmgYLqlPvGRu+gV8sK5MXl5UKrsqA5fQnTAoX86dVixDe+fEbP/iUbxkj/Ahc73IXh8y16tl9tV1TbJ4Y7mdFvfZtkpp6xPekF7ZdtSSKTBpXwU3HvF618nNlLfIoaAUGk5G+jg9c4/XKx+vL5eXFpXKjn0HA24bV5JnRySN6Jsbs/2LZ07PHuFH5nqRvT5krldH2e+vbbCNvE1xac3Oqja3Gdk31xaXTAuBvOy0CO8twoHXu05uCkqRQ0EpNCw5qY9TMzeFpMUbKmwhqbSiNuC20QN7yrlTi+WI/j1itn+JwKnZI3LIXC+y14fM9epq9mVV9fLx+jJbXNq4p6bV7eYhRg/oaYtLU4cVSE5GaoT2GN3F610nbzdyp6DUCQpKoaG6rY/TMjennaWb98lLC0tlc1ngm5tR/XLlvGkltqCExMsekUfmepG9PmSuVyjZ79p/UD5aX24bem+rCBwRbiS7kmRscZ5dKW7ykALJTOO55SS83nVyJ/IIpV27dsnpp58ujz76qEybNq3NbV555RW59dZb232Mu+++W84++2z77w0bNsivfvUrWbRokaSkpMiUKVPklltukeLi4jbvS0EpNJyM9HFK5uZ0Y5pGvrhwa6u/ko3okyPnTS+Rowf25K8vCZg9oofM9SJ7fchcr+5mX1peIx+uOzQtbneLvpVGarJLJgzOsyOXJg7Ol7QUnmexxutdJ3eiFpR27twp3/nOd2wR6Nlnn223oFRRUSFbt25tdf3PfvYzqa6utgWngoIC+3hnnXWWDBkyRK655ho5ePCgPPjgg7ar+d/+9jfJyMho9RgUlELDyUifWGduTjOmQeQLC0tl3a7AufxDe2fLudNKZHxJHoWkBMwe0UfmepG9PmSuV7iyN+/RzB/5TGHpo/VlUlHd0GqbjFSXHbFkmnmb3pYpyaw0Fgu83nVyO7yglBLsHUyB57XXXpN77rmnS9ubYpG5+DMFKFOIeu6555pve/jhhyUnJ0eefvppycw8tKTlwIED5bvf/a589tlnMnny5GB3Fe1guUl9Ypn56u2HCklf7DgQcP2goixbSJo0OJ9CUgTxeteHzPUie33IXK9wZW/egw3rk2MvF80aJGt3VtnikmnqXXmw0W5T1+iR99eW2Ut2eopMG3aouGR6L7lcvIeLFl7vOrkcnnvQBaU1a9bIbbfdJhdeeKHMnDlTrrrqqqDuX1ZWZkceXXDBBXZkka8y/uabb8rll1/eXEwyxowZI++//36wu4guFAWpbusSi8zX7DxgC0mrtlUGXD+wIFPOnVoiU4YViItCUsTxeteHzPUie33IXK9IZG/el5nFUMzl0q8MsX8UNMWlRRvKpabebbepqW+Sd1bvsZeeWakyfVih7blkVuPlfV1k8XrXyePw3IMuKPXr10/mz58vffv2lYULFwb9Ax966CFbZfv+97/ffN22bdukqqpK+vfvL7/4xS/kjTfesFPejjnmGFu8Mj8LQHwwU9rMqm0rtu4PuL5/fqZ8c2qxXZ6WNxwAAADOZRp0jynOs5fLZw+VT7fut8WlJZsqpL7RY7eprG2UeSt32UthTpodtTRrRJEM7pXN6HNAiaALSnl5eSH/sPLycjtdbu7cudKjx+GlwPft22e//vrXv5axY8fK/fffb7c1Xy+55BJ7n6ysrJB/LgJxgtcnGplv2lNtRyQt23Lo9ezTt2eGnDO12L7BYFh09PF614fM9SJ7fchcr2hmbxp0TxpSYC/1jW77Xu/DtWX2a6P7UDve8uoG+fuyHfZi3vuZUUumoffAAj7DhQuvd52SHJ570AWl7njxxRftkK1LL7004PqGhkPN34qKiuSRRx5pnic4aNAgOf/8821TbvO1o0ZVhrmfeXwf/+99Qfh6kMdqW3PxfW9uM/fz3dcMZfP9XyK1bctj5pTjEq5to3EMO9vWicclnJm3PC6b9lTJy4u3yZJNgYWkXrnpcvbkAXLMyCL7Vy5TTArH8Y6H56GTzhH+j93Vc4QTj0u4ttVwjjAXc12sjne0f69xjjh8XMxt0Xgf4cTjovUcYcRbNpwjInuuj/QxTHGJTBtWKFOHFkhNfaMs3bRPFm6okE9LK8XtOXTfXZV18sribfZSXJAlM0YUyvRhBdKnZ4ajjmG8nSPM7S0zd8px4Rzhjdi25jr//Qv2cROqoDRv3jyZNWtWqybdphm3ceyxx9oD4DN+/HjJzc2V1atXd/i45gnhm1fYcn5hR/MNY7Wt//e+J0A0t+2sU3w8HMN4Ot7d3f9wbBvOzH3/120VtXZq28frywNuN0Oez548UI47snerVUDi+RhGc9twPw9951WOt55zRHu/E6OxD4lyDJ28bXvHpa1zPcc7sc8RnWXekhO2ddoxjOdt2zvXR+s5m5uZLscd1ddeqg42yqKNFXZa3OptleIreZZW1Erpwlo7in1Y7xw7amn6iEIpzEkP6v/q5G2jdbxNwaArmQe7/07blnNEa2bfu/O4CVFQ2r17ty0MtRydZBQXF9uD5Bup1PIXZUZGRpT2EkBnduw7KC8vLrVDnQ//fVQkPztNzpo0QI4f3ccOjQYAAIAOuZmpcsLoPvayr6bB/sHRFJdMb02fDXuq7eUPH2y2jb9NccmsGNczKy2m+w4gDgpKK1assF8nTpzY6rbs7GyZMmWKXenthz/8oaSlHTqpfPTRR1JbWyuTJ0+O1m6q4D8KDDqEI/NDw5dL5b01e8VvpL1d4ePMSQPka6P7SFpK9Krh6Bpe7/qQuV5krw+Z6+Xk7M0fGU8Z189e9hyoay4ubd5b07zNFzsO2Msz/9koRw/Mk5kjCmXKsELJTo/qBJq44uTMoTf3sL9iq6urZf369VJSUhIwtW3t2rW2UGSub4spJF188cVy5ZVXyuWXX26bcpsm3ePGjZPjjz8+3LupmplTGc1hcIjvzPceqJNXlmyTBZ/vkS+nxlu5GSnyjYkD5Otj+kp6Ks8np+L1rg+Z60X2+pC5XvGSfe8eGfb9ormYUe4frSuTD9aV2X8b5r3lp6X77eV3726UcYNMcalIJg0ukIw05///oileMoeu3MNeUFq1apVdme2uu+6SOXPmNF9fVlYWsLJbSxMmTJBnn31WHnjgAbnhhhvsNLevfe1r8l//9V+OPoBAoiqvrpdXl2yTf6/e09xk0TB/OTpjQn85eWw/ftEDAACgS/rnZ9qVf+dMGShby2vtqCVTYNpzoN7e3uTx2ibf5pKW4pKJg/NtcWn8oHz7PQDnSfL6LxMRZ5qammTBggV2FBNFp67rrEEzdGdu5r2/vnSbvPXZbvuL3ScrLVlOm9DfDl/OSmM4crzg9a4PmetF9vqQuV6Jkr35KLp+d7UtLn28rkz21Ta22iYzLVmmDCmQmSOL5OiBPVst+qJFomSO6OWen58vkUZBSSETecsu90hsXcm8stYUkrbL/M92S6P78FKTmanJcsr4fnLquP6Sk0EhKd7weteHzPUie33IXK9EzN7j8coXOw/Y4tLC9eVSVdfUahvTcmHasEKZMaJIjuzfQ1yuxDoG2jJHZHOnoNQJCkqhobqtT0eZHzjYKH9btl3e/HSX1DcdLiSlp7jstLbTJ/S3K3cgPvF614fM9SJ7fchcr0TPvsntkVXbKm1xadHGCjnY4G61TX5WqkwfUWSnxQ3vk5PwxZZEzxxtY4RSBFFQCg0nI33ayry6rkneWL5D/rlih9Q1Hi4kpSa7bKPtb0zszzKuCYDXuz5krhfZ60PmemnKvqHJIyu27rPFJdNfyXzfUq/cdFtYMtPiSgqzErK4pClzHEZBKYIoKIXeKd7pyw8icpnX1jfJP1bstMUk/7/2pCYnyQmj+8qZkwbY5V6RGHi960PmepG9PmSul9bs6xrc8snmQ8Wl5Vv2BfT79G/+bYtLI4rsvxOF1sy183QjdwpKnaCgFBpORjozr2/yyr8+3Sl/X7ZDauoPz0lPdplCUh9bSCrMSY/pfiL8eL3rQ+Z6kb0+ZK4X2Yt9P7t4Y4VdKW5l6X5po7Ykg4uyZcaIQz2XevfIkHhG5jp5KChFDgWl0DBcUpe6Rrf8a8UOeWP5zoDmhqaQNPuI3nL25AHSK85/waJ9vN71IXO9yF4fMteL7Fv3BF24oVw+XFsmX+w4IG19wB3RJ0dmjCyS6cOKpCAn/kbjk7lObqa8RQ4FpdBwMtKhocltV2z769LtUnnw8BKsZkr5saN6yZwpxdKnJ4WkRMfrXR8y14vs9SFzvci+feXV9fLx+nI7LW7D7upWt5vuSkcN6GFHLU0dVig94mTxGTLXyU1BKXIoKIWGJScTW6PbI2+v2i2vL9km+2r9CkkiMmtkkS0kJdJ8cnSM17s+ZK4X2etD5nqRfdfsrqyzU+JMcWlreW2r282I/THFPW2/pclDCiQrPUWcisx18nYjdwpKnaCgFBqq24m7vOq7n++RV5Zsk4rqhoDbpg0rkPOmlciAgqyY7R9ig9e7PmSuF9nrQ+Z6kX3wtlXU2uLSB2vLZFdlXavbzQI14wfl2+LSxMH5kp7qrONL5jq5GaEUORSUQsPJKPEKSe+t2SuvLN4me6vqA26bOrRAvjm1WAbkZ5C5Urze9SFzvcheHzLXi+xDZz7+bi6rsf2WPlpfJmVVgX+INdJTXTJpcIHMHFkk40ryJDU59s2wyVwnt8MLSs4d0wegQx6PV95fu1deXrzNDuf1N2lwvnxzWrEM6ZXTfCICAAAAtDPTh8x7ZHO5YOYgWberyo5c+mh9uVR+2S6ivtFjp8mZS3Z6skwZWmhHLo0e2NNOkwNwCCOUFGL+bfwXksxfU15etE127D8YcJv5C8q504pleJ/cgOvJXC+y14fM9SJ7fchcL7KPzHvs1TsO2JFLZsW4mvrDqyP79MhMkenDi2xD71H9csUVxQzIXCcvPZQih4JSaBguGZ88Xq8s2lAuLy0qlW0VgYUk00zQTG0b1a9Hm/clc73IXh8y14vs9SFzvcg+8i0lVpZW2hFKizeWS12jp9U2BdlpMmPEoZFLQ3vnRLzYQ+Y6uZnyBqA7TM136aZ98uKirbKlLHB1iiP797Ajko4a0DNm+wcAAAAkkpRkl0wYnG8vDU1DZfmW/baZ9yeb99kVlY2KmgZ5Y/lOe+nTM8MWlmaOKJTiwuxY7z4QNYxQUsjj8YjLFfvGcuiYeWmaX14vLtwqG/fWBNw2om+unDetWI4e2LNLfw0hc73IXh8y14vs9SFzvcg+Ng42uGXppgo7cmnF1v3i9rT+KD2wINMWl8y0uH55mWH72WSuk6cbuTPlrRMUlELDycjZzEvy09JKW0hav7s64LZhvXNsIWlsSV5Qw2rJXC+y14fM9SJ7fchcL7KPveq6Rlm0scI29P5sW6W09al6aK9sW1gyl6Lc9G79PDLXyUNBKXIoKIWG+bfOtWpbpbywcKus2VkVcP3gXtly7tRimTg4P6T52WSuF9nrQ+Z6kb0+ZK4X2TvL/toGWbi+3I5cavk+3sc08TaFpenDCyUvKy3on0HmOrkd3kOJgpJCnIyc54sdB+yIpFXbDwRcX1KYZZttTxla0K1Gf2SuF9nrQ+Z6kb0+ZK4X2TtXWVW9HbVkLi3bVhjmLb1pW2GKS1OHFkhORmqXHpfMdXJTUIocCkqhYclJ51i3q8qOSDKrSPgbkJ9pC0nThheGZTlSMteL7PUhc73IXh8y14vs48PO/QdtYcmMXGq5SrOR7EqScSV5tufSpCEFkpnW/mdaMtfJ243cKSh1goJSaKhux96G3dXy0qKtsmzL/oDr+/bMsIUk80vF5QrfLwwy14vs9SFzvcheHzLXi+zjT2l5jXy4rlw+WLtX9hyob3V7arLLtrcwnwMmDM6TtJTAfMlcJzcjlCKHglJoOBnFzua9NfLSolJZsqki4PrePdLlnCnFcsyoXvYvFeFG5nqRvT5krhfZ60PmepF9/DIfvzfuqbajlj5aVy4VNQ2ttslIdcnkoYUyc0ShjC3Ok5RkF5kr5aagFDkUlELDySj6Sstr5cVFW2XRhsBCUlFumsyZXCzHHtHL/qKIFDLXi+z1IXO9yF4fMteL7BODx+u1TbzNtLiP15fJgYNNrbbJSU+RqcMKZfqwfDm6OD+ssxjgfG4KSpFDQQlOt31frby8aJv9JeH/QivITpOzJg+Urx7V2w5vBQAAAKCX2+O1Kz6bkUuLNpRLbYO71TY9s1JlxvBC29B7RN/csPRaReLKp6DUMQpKoeEvGpG3a/9BeXnxNnl/7V7xf4XlZaXKmZMGygmj+0haSvQKSWSuF9nrQ+Z6kb0+ZK4X2Se2RrdHPt263xaXTKuM+kZPq23MTIcZw4tsz6XBvbJp2J2g3IxQihwKSqHhF1Dk7DlQJ68s3ib/+WKPePxeWT0yU+QbEwfIiUf3lfTU6B97MteL7PUhc73IXh8y14vs9ahvdMsnm/fZZt4rtu6XRnfrj+/98jJsYclcBhRkxWQ/ERkUlCKIglJoPB6PuFxMswqnsqp6eW3JNvn353vscFX/Oc9nTOwvJ43pJxkdLAMaaWSuF9nrQ+Z6kb0+ZK4X2evMvK7RY0csmZFLK0srAz53+JQUZtnCkpkW16dnRkz2Fc54rVNQ6gQFpdCYyBkSGR4V1Q3y2tJt8s6q3dLkd0LPTk+W08b3l5PH9ZOstBSJNTLXi+z1IXO9yF4fMteL7PVpmfmBg42215Lp1bp6+4GAfq0+w/rkHCouDS+Ugpz0qO4vYv9ap6DUCQpKoWGIbPftr22Q15dul7c+223nOPtkpibLqeP7yanj+0t2euwLST5krhfZ60PmepG9PmSuF9nr01Hm5o/cCzeU25FL63ZVtbrdlCOO6N9DZo4skmnDCqVHZmoU9hjhwJS3CKKgFBp+AYXO/CXgb59sl3krd0lD0+FCUnqqS04Z209On9BfcjKcd4Imc73IXh8y14vs9SFzvchen65mbnq6mlFLH60rl81lNa1udyWJjCnOs1PipgwtcNQfwaGsoLRr1y45/fTT5dFHH5Vp06a1uc0rr7wit956a7uPcffdd8vZZ5/d6vo777xTfv/738uaNWvavS8FpdAwRDZ41XWN8vdlO+Rfn+60c5d9zEptJ43pK2dMHODoSj+Z60X2+pC5XmSvD5nrRfb6hJL59n21trD04doy2bH/YKvbU1xJMn5Qvp0WN3FIvmTEYPEgxPeUt5DLkTt37pTvfOc7UlXVekidv+OOO06ef/75Vtf/7Gc/k+rqapk9e3ar2xYvXizPPvtsqLuGTvALqOtq6pvkH8t3yD9W7JSDDe7m61OTk+RrR/eVMycOkLzsNHE6MteL7PUhc73IXh8y14vs9Qkl8wH5WfLNqVlyzpSBsrW81haWzLS4vVX19nbTA9Y0+TaX9BSXLSqZ4tK4knz7h3PEntfhr/WUULqMv/baa3LPPfd0afuCggJ78WeKRRs2bJDnnnuu1W01NTV2RFOfPn3sCCiEXxzPcowaUzz654od8sbyHVJT7w6o4h8/uo+cNWlAXDW2I3O9yF4fMteL7PUhc73IXp/uZG4KEoOKsu3lWzNKZP3ualtY+nhdmeyrbbTb1Dd57Ggmc8lMS7bT4WaNKJLRA3tKSjLFpVjxOvy1HnRByUxBu+222+TCCy+UmTNnylVXXRXU/cvKyuTBBx+UCy64wE5Va+nee++VoqIimTFjhjz22GPB7h7QLXWNbpn36U47va2qrqn5+mRXkhx3ZG85e/JAKcqNn0ISAAAAAPgXl0b0zbWXi2cNls93HLA9l0xTb9/nH/PH9f98sddecjNSZNrwQjty6Yh+PcRlmjABoRaU+vXrJ/Pnz5e+ffvKwoULg727PPTQQ+JyueT73/9+q9s++OADef311+XVV1+Vv//970E/NrqGflOt1Te67Yptr3+yTQ4cPFxIMufLY4/oLXOmDJTePTIkXpG5XmSvD5nrRfb6kLleZK9PJDI3xSEzAslcLjt2iHy2rdKOXFq8saK53YcpMpnPSeaSn50m078sLg3vk+PoqViJItnhr/WgC0p5eXkh/7Dy8nI7XW7u3LnSo0ePgNtML6af/vSncsMNN8iQIUNC/hnoHKtCHGZWantn1W55bek22f/lcE/DnBuPGdnLFpL65WVKvCNzvcheHzLXi+z1IXO9yF6fSGduprWZBt3mYj4jrdi6zxaXlm7a17y69b6aBvnnip320is33RaWZo4skpLCLIpLSl/rUV0j8MUXX7Q9mC699NI2V3Uzo54uu+yykA6yYUY+mcf38f/e9wT3zUGM1bbm4vve3Gbu57uveaL4/i+R2ta3r/73dcJxCde2XT0uTW6P/Gdtuby6eJtU1DQ03988uqm6nzO1WPrnZTQfq2COtxOPSzgzj/ZztuW28fA8dNI5wlyCPUc48biEa9tYPGejfY5o63diNI8354jYnSOMaLyPcOJx0XqO8P/97pRjyDkitud6J3zWiJdjGG/niGh+5k1OEpk8pEAmDsqzLUGWbdlveyst37pf3J5D25vG3q9/st1eBuRnyvThBTJjeKH0z8/q1j5wjpCAbc1+dudxIy3J6/8uJEhmytsll1xim2xPmzat0+3PPvts6d27tzzxxBMB1//73/+WG2+8UV5++eXm0UmPPvqo7aG0atUqe1DMpaWmpiZZsGCB7cXk5Kqd05gnWFvHUwNbSPpir7yypFTKqg4Xkoypwwrk3KnFUlyYLYlGc+bakb0+ZK4X2etD5nqRvT5OyLy6rkmWbCyXD9eVy2fb9suXtaUAg3tl25FLprjUK45bhiRC7vn5+ZIwI5R2794tq1evbnN00rx586S+vl5OP/30VreNHj3aFqLuvvvuKO1p4vNVMTUxlfT31+yVlxeXyp4Dh5bJ9DHV929OLbYnv0SlMXMcQvb6kLleZK8PmetF9vo4IfOcjBQ57qg+9lJZ2yALN1TYht6msbfP5r019vLnD7fYxt+muGRmgJj+S4jP3B1RUFqxYoX9OnHixFa3XXfddXLRRRcFXPfCCy/Yy0svvRSVypq2KqeWEV0ej9fO/TWFpJ376wJumzAoT745tUSG9cmRRKcpcwQie33IXC+y14fM9SJ7fZyWec+sNPn6mL72Ul5dLx+vL5cP15bJhj3Vzdus21VlL8++v0mOGtDTFpemDi2Q3MzUmO57PPE4LPeIF5Sqq6tl/fr1UlJSIgUFBc3Xr127VtLS0uz1LQ0cONBe/L377rv265gxY8K9i1DA4/XKog3l8tKiUtlWcTDgtjHFPeXcqSUysl9uzPYPAAAAABJBYU66nDa+v73sqqyzo5bMZWt5rb3dNNlZta3SXp5asFHGFveUGSOKZPLQAslKi2pbZ4RZ2NMzPY9MX6W77rpL5syZ03x9WVlZq5XdEBuxnnsbSaYlmFnm0hSSfCcwn6MG9JBzp5XIkf31PQ8TOXN0jOz1IXO9yF4fMteL7PWJl8z79syQsycPtJfS8lr5aH2ZHblkCk2+ViSmybe5pCYnyYRB+XalOPM1PdW5I3FixeXw3LvVlDvWaModvw3dws08jT/ZvE9eXFRq5+z6G9UvV86bViKjB/YUrRIxc3QN2etD5nqRvT5krhfZ6xPPmZvPauYzmmlFYi7l1YGLIxnpqS7b29ZMixtXkicpyfH5f9XWlJuCkkJm6cFEOV7m6fvp1v3ywqJS2bD78HxdY3ifHDsiyQypdHozs0hLpMwRHLLXh8z1Int9yFwvstcnUTI3rUlMXyU7LW59uVTWNrbaJjs9WaYOK7TFJdN7Kdml97Ocuxu5U1DqBAUlvScj87Rdtf2AvLhwq6zZWRVw25Be2XLutGI7bFJ7ISmRMkdoyF4fMteL7PUhc73IXp9EzNxMf1u9vdIWl8yKcTX1Ta226ZmZKtOGHyoumR64LmWf79wUlCKHgpJOZlnKFz7eGrA8pVFSmGULSWaoJIUkAAAAAIgPTW6PfFq6Xz5cVy5LNpZLXaOn1TYFOWkyY3iRLS4N7Z3NZ75OUFDqBAUlXdXttTur5MVFW2VlaWXA9QMLMuWbU4vtsEhtFetEzxzdR/b6kLleZK8PmetF9vpoyryhyS3LNpviUpntk9vobl1c6tMzwxaWZo4olOLCbElUbkYoRQ4FJR0now27TSGpVJZv2R9wfb+8DFtIMlVql+J5tYmYOcKH7PUhc73IXh8y14vs9dGa+cEGtyzZVGFXijMjmMw0uZaKC7LsSnEzhhdK37xMSSRuCkqRQ0EpsVcIMCsBmB5JSzfvC7i+d490W0iaNbKX6gZtiZg5wo/s9SFzvcheHzLXi+z1IXOR6rpGWbShwo5cWrW9UtqqZJipcGbk0vThRVKUmy7xzsMqb5FDQSk0JnInzzctLTeFpFJZtLEi4HpzQjhnykD5yqheLCOZYJkjcsheHzLXi+z1IXO9yF4fMg+0v6ZBPt5Qbht6t1ykyWdUv9wvi0uF0jMrTbTlnk9BqWMUlBJruOT2fbXy0qJS+XhduXhbNF+bM3mgHHdkbwpJCZY5Io/s9SFzvcheHzLXi+z1IfP2lVXV28KSGbm0aW9Nq9tNPebogT1tcWnK0ELJyUiReOFmylvkUFBKjJPRzv0H5eXF2+SDtXsDhi3mZ6XKmZMHyvFH9ZG0FApJiZQ5oofs9SFzvcheHzLXi+z1IfOu2bHvoHy0vsz2XNq+72Cr203LlPEleTJjRJFdHTwjzdnH1E1BKXIoKMX3cMndlXXy6pJt8p8v9oh/b7WemanyjUkD5MSjTSGJXBMpc0Qf2etD5nqRvT5krhfZ60PmwR+v0vJaO2rJXPYcqG+1jRm0MHFwvh25NH5QniM/e3qZ8hY5FJTis6GbGZL4yuJtsuCLPQFd+nMzUuSMiQPk62P6SkYqeSZS5ogdsteHzPUie33IXC+y14fMQ2dKHhv3VNvC0kfryqWipqHVNpmpyTJ5aIFdLW7MwJ6OabXioSl35FBQiq/hkhXV9fLa0u3y9qrdAYWk7PQUOX1Cfzl5bD/JdPiQw3jFEFm9yF4fMteL7PUhc73IXh8yDw+P12ubeH+4dq98vL5cquqaWm3TMytVfnzaETK8T67EmtvhU97ipxsV4roD/+ufbJe3Ptslje7DhSRTPDptfH85dVw/yUrnqQgAAAAAiBxXUpIc2b+HvVx27FD5bFulbei9aEO51Da47TaVtY3y3hd7HVFQcjo+xSsUraGSBw42yl8/2S5vrtwlDU2e5uszUl1yyrj+ctr4fpKTkRqVfdGO4bF6kb0+ZK4X2etD5nqRvT5kHn6mQfe4kjx7+c5xQ2XF1v22uFR1sElOGttPnMDl8NwpKClk5mFGcrhk1cFG+fvyHfKvT3dKfePhQlJ6iku+PravnDFhgPTIpJCUSJnDucheHzLXi+z1IXO9yF4fMo+s1GSXXfXNXJzE4/DcKSghbGrqm+SN5Tvkn8t3ysHGQ8MFfS9Os2KbWbktLystpvsIAAAAAAC6j4ISuq22oUn+uWKnvLFsR/O8UyPFlSRfM4WkiQOlIIdCEgAAAAAAiYKCkkLhmodZ1+CWeSt3yt8+2SHV9U0Bc1G/elRvOWvSQCnKTQ/Lz0Jiz71F5JC9PmSuF9nrQ+Z6kb0+ZK6Ty+G5U1BSqLvzMOsb3bbRtmm47b/MoitJZPaRveXsyQOld4+MMO0tNMy9ReSQvT5krhfZ60PmepG9PmSuk8fhuVNQQpeZldreWrVLXl+63S6l6JOUJPKVUb1kzpRi6duTQhIAAAAAAImOgpJCSaYCFIRGt0f+vXq3vLpku+yraTj8OCIyY0SRfHNqsfTPz4zAniJWmSNxkL0+ZK4X2etD5nqRvT5krlOSw3OnoIR2Nbk9suCLvfLqklIpqzpcSDKmDy+Uc6YUS3FhVsz2DwAAAAAAxAYFJYW8Xm+Ht7s9XnlvzV55ZXGp7DlQH3DblKEFdkTSoKLsCO8lopk5EhfZ60PmepG9PmSuF9nrQ+Y6eR2eOwUlNPN4vPLBujJ5eVGp7KqsC7htwqB8OXdasQztnROz/QMAAAAAAM5AQUmhlksPerxe+Xh9uby0qFR27DsYcNu4kjw7ImlE39wo7yU0LTeJyCF7fchcL7LXh8z1Int9yFwnl8Nzp6CkeOlBU0hasrFCXlxYKqUVtQHbjB7YU86dWixH9O8Rs/2EnuUmETlkrw+Z60X2+pC5XmSvD5nr5HF47hSUlM7DXLrpUCFpc1lNwG2j+uXKedNKbEEJAAAAAACgLRSUlBWSVmzdLy8s3Cob9wQWkkb0yZHzppfI0QN7On5pQgAAAAAAEMcFpV27dsnpp58ujz76qEybNq3NbV555RW59dZb232Mu+++W84++2z773/+85/yu9/9TjZu3Cg9evSQmTNnyk033SRFRUXd2U31TCHps22V8sLCUlm3qyrgtqG9s+XcaSUyviSPQlICc/rcW0QO2etD5nqRvT5krhfZ60PmOrkcnnvIBaWdO3fKd77zHamqCixQtHTcccfJ888/3+r6n/3sZ1JdXS2zZ8+237/xxhvywx/+UM4//3z5wQ9+IGVlZfK///u/cumll9qiVHp6eqi7qtrq7ZV2atvnOw4EXD+oKMsWkiYNzqeQpIDT594icsheHzLXi+z1IXO9yF4fMtfJ4/DcU0L5D7322mtyzz33dGn7goICe/H37LPPyoYNG+S5555rvu3xxx+3xaVf/vKXzdsNGTJEzjvvPPn3v/8tJ598crC7qtqanQdsIcmMTPI3sCBTzpk8UKaNKBIXhSQAAAAAABCNgtKaNWvktttukwsvvNBOSbvqqquCur8ZefTggw/KBRdcIOPGjWsuUs2aNUsmT54csO3QoUPt161btwa7m2qt311lC0mmV5K//vmZ8s2pxTJ9eKGZA0cxSRlGoelF9vqQuV5krw+Z60X2+pC5TkkOzz3oglK/fv1k/vz50rdvX1m4cGHQP/Chhx6y8wC///3vN19nvr/llltabfvWW2/ZryNGjAj652izaW+1LSR9snlfwPV9e2bIOVOLZZYZkeQ69GT0eL0x2ksAAAAAAJAIgi4o5eXlhfzDysvL7XS5uXPn2qbbHTGjksy0uiOPPLK5zxJa21JWIy8tKpXFGysCru+Vmy7nTBkoXzmityR/WUjyb9INXchcL7LXh8z1Int9yFwvsteHzHXyOjz3bq3yFqwXX3zRTm8zjbY7YvormYbfKSkpzSOaOuJ2u+1Xs515fB//731DxXyBxGpbc/F9b24z9/Pd1zTb8v1fOtt2Z2W9vLhwqyzcEFhIKsxJk7MnD5RjRxUdKiR5zf0PP65vX/1/jhOOS7i2DeYYRmpbJx6XcGYejWPY0bbx8Dx0wjnCt625BPO4Tj0u4dpWwzmird+J0TzenCNid44wIn28nXpctJ4j/H+/O+UYco6I7bk+Fs9ZzhHROd7x9Jm3O9tyjpCAbc1+dudxIy3J6/8uJEhmytsll1xim2xPmzat0+3PPvts6d27tzzxxBMdPub1118vWVlZ8uSTT8qwYcPa3bapqUkWLFhgezE5ufN5OO3Yd1BeXlwqH64tE//g8rPT5KxJA+T40X0kNbnjApyJ3PfEgw5krhfZ60PmepG9PmSuF9nrQ+Y6ebuRe35+viTMCKXdu3fL6tWrOxyd9Pe//932UjKru/3ud7+TPn36RGv3HG93ZZ0tJL23Zq/pqd2sZ1aqnDlpgHxtdB9JS+laUc1ULLUU4HAImetF9vqQuV5krw+Z60X2+pC5Th6H5x61gtKKFSvs14kTJ7Z5uxlpdPPNN8ukSZPk//7v/yQnJydau+Zoew/UyatLtsmCL/aK23O4kpSbkSLfmDhAvj6mr6SnOvcJBgAAAAAAEk/YC0rV1dWyfv16KSkpkYKCgubr165dK2lpafb6lurr6+WnP/2pZGdnyzXXXGPv78+sKGcumpRX18trS7bJO6v3BBSSstNT5IwJ/eXksf0kI41CEgAAAAAASICC0qpVq2xfpbvuukvmzJnTfH1ZWVm7K7t98sknsnfvXvvvyy+/vNXt1113ne2rpMG+mgZ5fek2eeuz3dLkV0jKSkuW08b3l1PG95OstO7FZhp1QRcy14vs9SFzvcheHzLXi+z1IXOdXA7PvVtNuWMtkZpyV9Y2yF8/2S5vrtwtje7DXdkzU5NtEenUcf0lJyM89T/TKT7ejxeCQ+Z6kb0+ZK4X2etD5nqRvT5krpO7G7knVFNutK3J7ZEXF5bKvz7dKfVNhwtJ6SkuO63t9An9JTczNab7CAAAAAAA4I+CUoy9tnS7vP7J9ubvU5NdttH2Nyb2l55ZaRH5mSw3qQ+Z60X2+pC5XmSvD5nrRfb6kLlOSQ7PnYJSjJnV2ozU5CQ5YXRfOXPSAMnPjkwhCQAAAAAAIBwoKMXYSWP7yah+PSQ/OzViI5JaiuO2WQgRmetF9vqQuV5krw+Z60X2+pC5Tl6H505ByQEG98qO9S4AAAAAAAB0mbPXoIPKpQcRfmSuF9nrQ+Z6kb0+ZK4X2etD5jq5HJ67s/cOEeHxHF5NDjqQuV5krw+Z60X2+pC5XmSvD5nr5HF47hSUAAAAAAAAEBQKSgAAAAAAAAgKBSWFnD4PE+FH5nqRvT5krhfZ60PmepG9PmSuk8vhuTt776ByHibCj8z1Int9yFwvsteHzPUie33IXCePw3NPkTjm9XrtV7fbHetdiSscL33IXC+y14fM9SJ7fchcL7LXh8x1cncj96amJklOTpakpCSJlJREOLifffZZrHcFAAAAAADAMWbPni0pKZEr+yR5fcN84nT4V0NDQ8SrbgAAAAAAAPEkOcK1krguKAEAAAAAACD6aMoNAAAAAACAoFBQAgAAAAAAQFAoKDmgD9Rf/vIXOeOMM2TChAlywgknyJ133inV1dXN22zZskWuueYamTx5skybNk1uu+22gNtbuvvuu+Xiiy9u87ZXXnnF/qwxY8bI8ccfL4888kiXOsfX1NTIL37xC5k1a5bdzyuvvFI2btzY7vbvvPOOjBo1qtPH1ShRMn/44Ydtxu1dFi1aFPSxSXTRyr672fB6D59EyZzXu7PP9bW1tXLPPffYc7z5Weeff7589NFHXdpPXu/hkyiZ83p3dvZVVVX2vjNnzpTx48fLBRdcIB988EGXV3x68MEHbZPecePGyYUXXigrVqxod/vVq1fL6NGjZdu2bV16fC0SJW/zGaGj1/qrr74a9LFJdOHKfsuWLXLjjTfKMcccI5MmTbK5tnUO//3vfy8nnniijB07Vs4++2xZsGCB8363mx5KiJ0nnnjCe+SRR3p//etfez/44APvH//4R+/UqVO9l112mdfj8XgrKyu9s2fP9p5zzjne+fPne59//nnv5MmTvZdffnmbj/fkk096R44c6f32t7/d6jbz2KNGjfLec8893g8//ND72GOPeUePHu297777Ot3Pq6++2jt9+nT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", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:34:48,341 - robyn.visualization.cluster_visualizer - WARNING - create_correlations_heatmap method is not implemented.\n" + ] + }, + { + "data": { + "image/png": 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", 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WoaawaCE6laW4F5QGslZhJfni3N6V1AqVchpfqdRrSadWaXwefSHX6UX60ZdB9SbSuDjtUe8gefPNN/1Pe1ScKiw+FfYUKYWWUeHpTiqUqfiiL7TqiTNkyJAWpxclp84VXv2us+Ups88+e6tT7lSY0U9btD5VTGqP1qmKe/rRMlCvEn2Z1ylg6j3SnmS8KJ3ClJzipCKbepGoQKSeMSrAKbN6unSFikwqWqlHjbY59dRRZp3al5yW1V7PMRXcVHRSIaaUaQsLfG1RUUpFEZ26qV4z+l0/Kjyp95V64RTvS21pa7tS8eXf//53flvQc6qQo9fU9l7YC0gKt9NCOt1UVHBLik8qbrW13xdOmxS3VHxTj7P2qOiSZGyr94+KWqX25FPxVduQ8qlgpsepGKTtW8WmZP46otPltIxUQFWRsr33GxXLVGBSsVQ9o/S6Ktqq8KQehSrmbbLJJv6iBirctqen3v8AAEiL4hMAIPNUOBgxYkSrXh8qPqnHkb5860uaehC0R1cgUzFDA09rnKa2JF9ii3t1tFcE0JhE+tEXSfWAUS8dzat6UKiQowJVW5JeKSqSdMdV60qloovGEFJvERVh1GNLVy9LqJeKvpzq1CONv9RRzyB9kVVhYsEFF8z3XlPvGA2qrEJE8emEop4gGhBap55pXWl5q3CjApHmQ1+2i6mYp6umaT1rnjqidSyFp3Hq8SpeaFBonUomGjOpsOjWVbpymIpPSY+npPhROBB2W0VHzVMybfHg1G1N2xEVOjRmmgoXOpVPPctU3NM+ofWw/fbbp86l0xS1XepUMK0b9cLS6bFaXyqYtHUKZHu95drK0dm0Kk4lA5prm0jWW2dF0MIrBCZUJOuogFdMGdVzTD8JFb7VIyo5jVTPp31IRbu2eqUl865CZXtUqNZy2GOPPfzf2raVOzmVNelF1llRqTvf/wAAKCfGfAIAZJ6+qOnLXuFPciqUvhCq+KHi1Ouvv97uc6jXjOgKZO1JTm8pvtKcvhQXXzJez6cv/UkxSac7aWBkXQZeOpqX5PLs77zzTpv3q0eSvuSXctphWup9ot5D6hGiK+sV97xSjy19Ye+oh5HoVC9Rj5/iXk8q9KhgVPyjnjQqaOkLtS4RL/rCrQJMcppTR0XB4lP1iiVf9lUEK+4BVjh4u04p6w5JsSQ5TVSv0966V08n9XpSfvX6SaZVsa6Yip96Dm1XSQ+ttnowaXmfeuqpfn3pOVUMU8+25DS1jrbBjujqe5oHbcsak0qF1OT11RNJins+JWMkFUqKNDpVsrCnk4qQScGouOil7UGFLhVf9Bj1QCp+LdGA6BovSUUhzZ/WgYpvxT755JNWV+Zriwbf1zhMhWOgJTS2lCQDrP/8889+u9eyLqbMOq1Wp1m217tOy0k9JlUETYpyGuNKP8UFus56rnXn+x8AAOVE8QkAEDQVUTQwcjJQc3ExRePC6Kpg6nGjgbw1sHF7ksGu1YOpkHoWFPeGUk8D3V78esnpgYWnoqmopS+3CX251lg/6qXy6KOPtioo6BSf5557LtUV3tJQTxadlqVMugpc4ZdeFY7Um0s9ozQ4cnGvEf2t5f3000/7XhQ6bSihgZQ7K+4kA0JrXJzkC72+PGt8I131rXg5qwCXFBoLB5PuaOBsFV8Kr0ym0590OlrimGOOmegxclT0SAZP1yDRop54KoKoZ4mKJgktX12ZTUWQpHeXlp0KUSq66ZS54uKjxvxSD65kG0h6ahVuR9r2NNaTxtkqpFO+2toGC9dzKUU8FVkKaRwu7UdJpkKaL/WSSgpF+lfFRhVyddpjW8XLwuKqrnanoqHWsfZpzYPGDVPx6Nprr23xWA3or95Q6kGnnkLKpgHtVdQsnFbPr3kohZ5DPb20Txb2sNNzaj/XKXebb755fv/V+FQaD0sD2yeSzBq/Sad9tlc4UuFJ9yVXLRQV21TgTk5zTN5X2hoTr1zvfwAAlBOn3QEAgqdeR+oBokGl1SNBxRN9OdQX31dffdX31tAYKvoSmfRSaYtOk1PvGn2ZV+8EnVKj3hQ6DW3hhRf2BYGExlLSl2AVcdZbbz1/ipO+KGtsIp26Nnjw4Py0ek7Ng3qS6DVUrFBPIF3FS6c3af41HpF6j6jwpd4QSQ+qctEXVZ0ypi/Q+jKcnLKjL8VaTjoNTsUVFZmS5aLTyVQo0ZXOdJsKAMkl4XXaoYoH6omhL+ft0aDLKq6oN4kKQCoeqAeLvhSreHH77bf7U57Uc0SvoyKcike77bZbh2PfiIoVyqQfFTE0jypC6W/1JNHpkOpxpS/i2k70WslpTu1Rb6XCAa9VYNBy0HOq55NOZerXr5+/T2ME6bRGja2lIp560mg8H72mlrMG2dYA6KLlpqKaTrvS+FfKph482t5UQNA2VNhbKxlTKRmkWj3U9txzT7+tavwpFTFVzFLxUwUtbe+FhUGtPxU2NK0KfsWDXxcvRxVxNP6Q9h89l3owqeCqnklaL8U9AVW80SmnWl5LLbWU78WkLOqNlYy/VUjPq6KUrmypXlB6bu0DBxxwQH4aDfSt51AvPBVDl1xyyXwvueQU0mT70zJXcUzLVM+l5ae/NZ8dnf5WSK+n9aZtQ8UsFa80Ppq2HRVGkzGrRPuv1oHWkeZHvZy0D6g3owrL7Y1ppsKUeiHplNvCsai0zHUa7N577+1PWdU2qmJ44el/5X7/AwCgnOj5BAAwQVc2U88bfXlMeqWoF5F6BuiLoE4lau+qYQn1MtEpfioaqACgL/r6sqZ/iwsq+iKsXif6cqjigr6s6wu6ilE333xzi6uN6XQ8DQysnhr6Ei36YqmxeTTfepwGHNa/6hmjXkEaS6mcNH+aL1Hxp3BsGY1HpN4SOvVPhQQV2dQzRTlVaNF9+jJeOI5P0gOksOjWFvW+0Kk/+kKf9JRSoUDFEw2QrS/JKkypIKZCnk7Z0sDlGnS8MyqcqYClIoIKDiouqZinYou2BxWKVJxQ0UMFgs4KT6LxnDRmVPKjL/CaP502p+KHihDFva/U80nbhQpnSY8rFSl0qlhhb7b+/fv7da3Cg4os2m5ULNlvv/38/BYuX82vipUqPGk6FWy0TWnb1ONV9NA2qGKD1oFet3AQcJ0ipuKOlnOy3NujbFr3KmCoR5qeS72gVLDUY1XwKe6tpfGPlE80Tz/99JM/hU2ndmofLKbbVRDTOlJxV/uNllthQUYFSL327rvv7otO2jdV4FHxVrersJXQutTrav/XfqTnVW+l4mXeEQ2ornnQ+4S2Z61nFXL0XMWnq2larbt1113XL3OtExU6tYy0r7T3mlqu2r8KC4OiZaF9So/TPKgnlHpAtrXsyvX+BwBAOVXk2jqRHgAAwDCd3pf0msHEUTFIvcBUGOqMegtpfCIVbHR1OQAAEAdaXQAAIDoUngAAACYdWl4AAAAAAAAoG4pPAAAAAAAAKBvGfAIAAAAAAEDZ0PMJAAAAAAAAZUPxCQAAAAAAAGVD8QkAEJynnnrK7bPPPm6FFVZwffv2dSuvvLLbb7/9/O0hueiii1yfPn3ck08+2eKy9QMGDHBZ8/777/t5Pfroozuc/1I1NTW5m266yY0dO7ak6YuXy8S8dmfq6urcNddc0+I25dbraTmE4IsvvnC77LKLW3rppV3//v3dZZddNlHP98orr/j8p59+uiu3zz//3D3yyCNlfx0AADDpVE/C1wIAYKKdeuqpvmgxxxxzuLXWWstNN9107ocffnDDhw93Tz/9tNt66639NKHaeeedXX19vQvBwIED3YEHHujmm2++1I894ogjfIFh8ODBmVsuO+64oy+A7L777vnb1l57bb/NzTjjjC4ERx11lHvzzTfdOuus4+aff/5MFjTb8sEHH7gtt9zSbbfddm799dfv6dkBAADdhOITACAY6n2hwtO6667rzjvvPFdd/ffH2OjRo32BYtiwYW611VbzxYIQ7brrri4Uyy23nP/pilGjRmV2ubQ1b9qeQtqm3n33XTfrrLO6iy++uKdnJZXff//dNTQ09PRsAACAbsZpdwCAYDz77LP+3x122KFF4Ummmmoq35tGnnjiiR6ZPyArVMCZdtppe3o2AAAAPIpPAIBgJD0iPvroozbv16lFF1xwQateMr/88ov7v//7P38az1JLLeV/NtxwQz8OTmNjY6txbe677z7fg0rTL7HEEm699dbzt4nGldp88839c6gH1s0339zitZKxiD788EN32mmnueWXX94ts8wyfp5ef/311GMb3X333f75XnrpJXf11Ve7QYMG+XGu1Avn0ksv9WMnFVKeyy+/3M/bkksu6TbYYAN35513uksuucQ/z9dff13SqU8aQ0un1S277LLumGOOcb/99lur6doad+nLL790hxxyiFtjjTX8fCrPySef7H766af8NHrMiBEj/O96/p122qnFuEpvvfWWn28t+2233dblcrl2x8IaP368O+OMM/z4X/369fPPpfVYKFmG1113XavHa3rd98cff/hlo9+/+eYb35OucIyr9sZ8evjhh/086rU1vpJ+f+ihh1q9TvJc//3vf/1ralplP/TQQ0taJ6LTDrXNatlo2arXmdbT22+/3WqdJOtRv2vZdUbrUPOlZazn1fb66quvdviYwmVXKFmO+++/f4vbb7zxRr/vJONQbb/99i3GdtK8q/ei3HDDDf45CtelenPpOTV/2rY32WQTd+utt/rto61lrWWlPPppa90X5tDpiVrv2naTxxx88MH+vUP5TjjhBP+62if23XffNtdZqfMnzzzzjNtzzz39+8Piiy/u/9Vji7cvzZvW3/fff++L63puvfeoAF+8nQMAkGWcdgcACMZKK63kv8CqkKQBlTfaaCP/Ja+qqsrf37t371bjxKiIoHGgvvvuO/8lTkUbfaFU76jzzz/fn+aj8XEKXXvttb6IogKVvhTec8897p///Kf/Mq/XVzFKX07vv/9+969//cvNMsssrU7JUsFm5MiRbuONN3Z//vmne/TRR/0A0PpCrAHS0zrnnHP8OER6bRV2VOBQoU3Fl8MOOyw/nYoZyqYv4Ppy/9VXX7njjjvOzTXXXCW9jr786outCh0qYE099dS+4Pbcc891+lgtVxUtfv31V//YmWee2Rfh9AVcX5S1vGpqavw4UVqm+rK/1157+TGJCqmgosKT1vfkk0/uKioq2n3Ns846yxcltS0ky3m33XbzxbbVV1/dpaGsmrfrr7/eDzq+9957u0UXXbTd6bUdamDymWaayb9+0jvv8MMPd++99577xz/+0ao4oeKKipEa00hFNhVf3nnnHV/Eqq2tbfe1ND/KpQLmwgsv7B//888/+6KR1o22BW2DyThcOt1O41OpGKZegR1RsVKnsc4wwwx+vfXq1cs9+OCDfl1eccUVfj1MLD3Pv//9b19o0TxpnWldaXtVtk033dTP+2abbea3DRVYVlllFT/OlmhMN+XS9qMC7PTTT+9zq7CpZV08zpvu036g59Ny0vN1ZMyYMX6Z6lRFvV9oOT/22GN+W9Z2pf1Bz/Xxxx/7wtGPP/7o7rrrrvy2mWb+dOqw/p577rn9dqPHqICo/ezll1/2y0X7TkKvr315sskm88tJebS97LHHHn5ZLbTQQhO9fgAAKLscAAABOemkk3ILL7xw/qd///65vfbaK3fttdfmvvvuu1bTX3755X66YcOGtbj922+/zfXt2ze30kor5W97+eWX/bSLLrpo7u23387fftttt+Vf75lnnsnf/sorr/jbDjnkkPxtQ4YMyc/Xl19+mb/9zTffzC222GK5tdZaK9fU1NRi2ieeeCI/3RprrJFbZpll8n/fddddfhrd9sUXX+RvHzlyZG7xxRfPrbjiivnbHn30UT/t/vvvn6uvr8/fftNNN+XnX4/ryA477ODzv/jii/nbRo0aldtggw3844866qhWWZP5v/HGG/3fd955Z4vnPOWUU1otux133NHf9vvvv+dv03PrtgMPPLDVfBUvl+S1l1122RaZ3n333dxSSy2VW3311XONjY0tlqG2kWJtzUfxaxXO23vvvef/fvXVV/3fm266qV8+hctqo4028veNGDEif3uy/K+88sr8bc3Nzbndd9/d3z58+PBcRy6++GI/3dFHH51raGjI3/7OO+/kllxyydyAAQNyo0ePbvF6gwcPznXms88+89vleuutl/vxxx/zt2tb69evn89SuG+cdtppHS470frQ7fvtt1/+toEDB+bWXnvtFvOu/VX74Oabb56/ra3XGTt2bG755ZfPrbDCCi3Wtfajgw46yE//7LPPtsiun6eeeqrT/IU5DjjgAL9ORPOpbUi3b7PNNrm6urpW03/yySep50/Po/eGQYMG5f78888239v0flP8WlqWhfv0pZde6m8/55xzSsoIAEBP47Q7AEBQ1JNAPTXUK0I9BtRjQb0OzjzzTH/1O/WuaG5uzk+vXkannHKK7zFQaLbZZvO9gdRbp5h6pui0poROERJd1a2wN03Sm0I9eNq6Ypp6NhROq9Ol1BvqjTfeSJ1bvSnmmWee/N9zzjmnW2CBBXwvCPUcEfWCEPXk0rJJqEdHKVek01UDdaqVlq1OY0uoF8cBBxzQ6eOT5a4ePoWnA6pn1vPPP19yTyRlLZV6EmlZJBZbbDF/Bb1vv/3Wvfbaa65cdCqfqEeclk9Cvydjj6lnTCH1zEtOKxP1mtGybm8bKqR1q54v6sVWON6ZehKpV4xODXv88cdT51AvG52qqVO+1IMroW1N29EWW2zRLQOA69Qz7Wva/hPqZaSeX7fcckuHj9VVLPVY9fQpXNeVlZUdLmtdeCANrZukJ5OWsXrfJae+FfZKS/b75NS7NPOn/UK9nk4//XTfq6+Qen61N+C9rrxYuE8n2TrbbgAAyApOuwMABEdFDP3odBQVGDQekr4A6lQ5nd6jIkhyypOKEfrRtP/73//8NDplT6e56PfiMZOksMgj+tIvhV8sRacniU7JKZZ8kSykUwR16plO31OBK41555231W3J6VR6fc2LTt/SINOFRa/kS7DG2dFpex3RfElh4S2hx3dGp2wNHTrUj4Ol04JU+Ft11VX9F+XCwkZnipdzR5LCYPFyvv32232erl6NrzN6bi3XttZjcluyPBOzzz57q1PrCtdhe1RgVdFGWaeccso2X0+n/xW/Xqk5RGNWFdPpcd1lm2228ftmMpZXsl0kBZ6OaLtOipoaF6qYTrstzq7CVnI6bqmK9/ukONTefp8U5dLMn95LtAxE++Onn37qT43V6Xx6H5PC4nl7+3+yHXS03QAAkCUUnwAAwZpiiin8F1j9qJeGBtbWwMAaU0Xjr+iLnnoFaTwbFSPGjRvnH6cxmjTY83TTTddiIOziYlOxjsbkKabXKKYxeJJiQlptvXbSSyMZ0Fjj07TXw6lwDJn2JANHa7kWm2aaaUrKrHWggdA1fs0DDzzgf9RjQwNNH3/88SUtQ/VaKZXGKSqWzP/YsWNLfp60tA5VhGgrjwpK2oaS7S3NOmyLCqfJ83a0bjX+V1rJOm+rqNWdNA6Wiju33XabH+tKhWAVarS9nnTSSS162hXTuG3S1kDuCY3d1tVtaGL3+7Tzp96F6qmpYpVoO1pkkUV8LzaNTdfWtlA8D6VsNwAAZAnFJwBAEPRlXwUMfVnVaXfF9GVsq6228qcR6RQvXR1K02pAap3Wo145GkhbA3Enl6DX4ORtFZ+6Q1uFgORLqope5aACQnuFrVIKXhpwu3A+C5VayNGpjLr6nHqUqUeIBl3WKWoq/ql4UjwI98Rqa141GHRhwayjL+rFBaJSqcClx6p4kyy3hAqeWv/dtZ6TYppOi+yogJRs12kkvXtU4CqeX2VQ0UM9vDpS3FOnrW1f62DLLbf0Pzqt7MUXX/QDgutUQQ0wr56LhacvtjWPumJdR0WqnpJm/nSanK5yp+KYTr9TrzX1alLvKPUWLLxyJAAAljDmEwAgCCqsqNCgL60a56gj+rKcnOalq3apd8yFF17oT8FKvqDrC7LGBSpX7wGd1lcsGetJp4WVg3pOqOiWFF8KqadJZ3R6oooE//3vf1vdl5xa1BH1dtKYXCp06cu0xsZRDzSdhie6gtikWM5vvvlmi9MHk7FyigtoWu+FYxCloZ4q7WXSbXruBRdc0HXXtq9Tv3S6aFtjlKknjXTl9XTlPFFvpGKnnXaaX4ftLaOkN05xAU+nkRVSjzz1ckrGJNP+qKtADhkyxBeU9XhdEU7aurKhCsbtbYO//fabHz/pvvvucz0lzfypuKT3noMPPthfVU/jtiWnB+oUPKE3EwDAIopPAIBgqOeSxjjRF7e2Ciwqfqg4tc466+RPI9IpLeqJkvQOEfXK0RfCpIdGdwyoXOzqq69uMY8q6OgUNBWIksJFd9MXeX1xPfvss1uMZaUvvm0VaYqpYKcBsHW5d11mPqFi0sUXX9zp4z/77DN36623+p9CyaDIGvMokRSEJnbZ33jjjS0KMhoDTL3fdPn5pMg3//zz+3/VC6twuahHnIoDxTRvGoS7s2UtOqWz8PX1u5a/bLLJJq67bLbZZn57Va+ywnnTqVs6zVS9r9Zcc83Uz7vRRhv5Yu1ll13mi0SFBSQNBq6ebPppS3KK5zPPPJO/Tfuatv3inls33HCDO//881st76QAnGwbyWDqhdtFsj9fddVVrcYtO+ecc/xzFxe8JqU085eMF1VcQNeYUJpOOtv2AAAIEafdAQCCse+++7qPPvrIF0Z0RTQNaK1TVvRlTT17VOBRoUG9bxLqYaHBmHXVrrXXXttPq9Py9CVRp/moWKAvxKWMiZSGnlMFA30xVfFG85ycalMuG264oS80qcj1ySef+J5eGlT92Wef9adUqbjQ2SDMJ554oh9o+tBDD/XLS+M4qbjQ2alXop4cw4YNc+eee64bMWKE7xGiU6xUDNKpSXvvvXerMbGOPfZYt9JKK7W4ClwaKlaoyKNBnJPX0nLWmDqFPbpU9FPPM10ZTuN9ffjhh77Ipp49xb3CtC2ol9GRRx7pt7HiKyWKnmO33XZz1157rb+63hprrOFv17LSqZx77bWXn6a76Pm03Wrdat6XX355n1c9aVRwVGGnK+M2qeeNeqepF5KWo3Lo+XQKmApJOm21PTqFTgU8FcS0DLWNqQCs0ysLr+SmHlIqGKsnlYpd2ie0jtRjS0VRvW5SIEy2CxW+9Bzah1RI1GO1PvS3tkutIz1ePbY0aLmuBtdTVPgrdf60fHVFTp06rGKtLg6gfVTbTTKmV1sFUQAAQkfPJwBAMFRo0Jdk9cJRDx19cVVvgTvuuMN/UdZlzXVqT+HYMYcddpg76KCDfPFEX5T1ZX2OOebwvTNUzJLhw4d3+7wed9xxvieKBiFWjxt96dS4RyqClItOWdLpTcqlAY51uptOmVJPHBUrShmIWb1cNJ8q5ujLsy4Rr+KNBhHvjMZYUi+c7bbbzhdvrr/+el/40pXNVJQq7PGleVTh54UXXsifltcVKnzoyocaV0qFDxWyNP/FV1HTl30VBjRfmked6qX50zwU07hUKniokNXR6VxHH32079mi7UlFIRVM1BtI60CFiO6kHjMaU0hFHPUKUu8yFc+S7UoFj6464IADfPFqttlmyxcv1WtMy6mjU0S1PnUFO53eqOy6kqPGPNJ8Fhc5d9ppJ/8aOn1QhS2tc/ViPOaYY/w6TGhZqvCpbVnTJKcDanw2zY+2Y+1P+l1F3f3339+/XluD5E9Kpc6fimsqWGo6rT+9J6kQruWjZajTgvV4Tr0DAFhTkePTDQCAbqPCg4pjQ4cOnaiCQFfoSlnqPdFWD5gdd9zRj0mj3j9tjasDAAAAlAs9nwAAMOLKK6/0V8/SKW+FVHDSINgDBw6k8AQAAIBJjjGfAAAwQuNa6fS2ffbZx4+JpVN8vv76a3+qoU77Oeqoo3p6FgEAABAhik8AABih8aRUfNL4RhpPRgNSa/wrjd+ksWc0uDEAAAAwqTHmEwA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", 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", 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", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO: Model evaluation complete\n", + "2025-02-04 23:34:48,802 - robyn.robyn - INFO - Model evaluation complete\n" + ] + } + ], + "source": [ + "from robyn.modeling.clustering.clustering_config import ClusterBy, ClusteringConfig\n", + "\n", + "configs = ClusteringConfig(\n", + " dep_var_type=DependentVarType(mmm_data.mmmdata_spec.dep_var_type),\n", + " cluster_by=ClusterBy.HYPERPARAMETERS,\n", + " max_clusters=10,\n", + " min_clusters=3,\n", + " weights=[1.0, 1.0, 1.0],\n", + ")\n", + "\n", + "robyn.evaluate_models(cluster_config=configs)" + ] + }, + { + "cell_type": "markdown", + "id": "7cebb194", + "metadata": {}, + "source": [ + "## Generate One-Pager Report\n", + "\n", + "The one-pager visualizes key model results and diagnostics through 8 plots:\n", + "- Channel performance: Spend vs Effect comparisons and ROI metrics\n", + "- Model fit: Decomposition, actual vs predicted, and residual analysis \n", + "- Response patterns: Carryover effects, adstock rates, and channel response curves\n", + "- Model stability: Bootstrapped performance metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a0f68f80", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[
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,\n", + "
]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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I4/3kJz8p12pnZ8wr7/+Wt7yl7YD6djLj1BprrFEGjCceDwCDkSgKMAGSRetksttuu63bi0Obqq91EkaquC2//PIDPnfjjTeuNt100/LvoaaKZWLafPPNh0wUzcn9n//855LklWmhe0lGuSZZNEloCaQOpE5WSvCnf3ISzZbR0klUS8JhgrYDyUjzukJhgmd33HFHB5eytyUwniqSb3vb29oGSWOwisYJgtbTqqX6MWPv91IpPNXh55133tn6Wakg89rXvrYk++YiSC6ODJVImQsjSQZN8nB/qaqQavVp0xnA0C5RdMUVVxzVsh588MGl8sRee+1VzQ6ppJPfkgT3czEgCaDDkSB7/XoAAAAYyrrrrlviXOH6zOyTQemZaSYxjDe96U2zPPbQQw+VypZDxbxe97rXleS9xGnquAajN9ZBxCORJOxURU4cORVCUyFzqOdHkiPXW2+9Zzz+f//3f6Xd/uUvf6luuOGGcYvjPfzww9UhhxxSErcHi42Pxbvf/e4SV//Pf/5T4r91HHc4Ma9UH04hAQAYjERRgAmgnhY2J8v95eL+WWedVaaXXXvttau11lqreuMb31hGjuWEp51Mz5mpF5Los9pqq5W/Ofn4/ve/33b6hhe96EVlBFumbEiiQT4nozbzmkxrM5CcdCVRYLPNNitTOKTaYqY/SEXNdvI5ee+s5ze/+c0SEMj6JBiT1/36178e8/rUrrzyyjI6MSPtsmybbLJJ9bGPfWzYI/RqF110URmFmJGf22yzzZDPzzSxSU5oHRWZaVGy7v0DILVzzjmnPN5/upV6eyVxJOubk+J8L5liJdstjydJZKAE1zyewEpObmup7pjl2X777csJdt5zq622KqMyc2LaTpIec+KeRNhs/3zPqaCa6UiGmhK3v/vvv79U0c22WH/99ct3U3+f/ZNY6mquWY/s70lES7JuphLJ61796leXamYDLXeq8qUi4itf+cqSZJJ2k1HLY5HvI4GMBA0ThGinXo8tt9xy0PdKgk32kwS4snwJCCQRJpUEs88N9JpTTz21PC9TWrV+H2lT/at31vteko0y0jR/sz3qNpGgx1BTm7RK9eO6Xxqsb8g0xxdffHF12WWXVUsvvfQzlif9Rvbr7FfZp7Nds09k3QeqQDrSvrDu2374wx/2TSOVz0qbyD6fwGTec6B9PslP2dfyOakiPFhlxrpP22677cr3mO2b7Zz1u/baa6vRyH6dpM20uyzz1ltvXfqW1gqDaX9JAqvXs50Ej7K9ktibygiDSb+RSnyRPnko6fuzjOnzE3xrJ9WVs39mu9T7+EC/Ednvv/Wtb5WqtHU7z2sS+EvF5v5tPX1C1j19c7ZFEizz7/RraR/53WiXKJm+Nq/LY/l9Sf+TdlT3E6maO9B+mG3U+ruXz8l014O1h5FIG88UWgsssEBpowO1waGqJeZ3IvtEu+8xvwnpW+u+p25/GRQxVAXL/n3zQEmCmTYtj9fTgGU75//1/pWpwfP/vM9Qv5MjXd6xfL/drq6Qfjr7ddbxggsuqN7+9rcP+vw6ET+DjrLPtJNk0Wjti/I5+T3Oa9Jfj1T69/SJr3/960sfNTvk+0tl7r333rtUCklV9+HI4Kv8Nl599dV93x0AAECT1OetiQlHzp1f9apX9T2eWEger+MedZw5Mcd2MeTRxBjrOFtek9hXzu0yY0zea7gSD0t8JMvULq4bGXBex7EzELCWQfi77LJLOV9PfCVxoMRxulHRs742M9D1mdFs35GsX//9oVXiGrvuumuJaeZzE+MYKNZY7y+5Pfroo22TAuvH+0tsNfGSnXbaqcTqs8y5dpABnGecccaAMdSRuOKKK8r1pLx//+qadbxrqJhXihecf/75Jd6Y/Wqs16vaGez7iMSk8nhiWa0xslr2k/w/311rjDqxsm5dXxtIHTcZ7SDikci1lPQHifN+5zvfmaVCaDt1HLv/jGa1OeaYo1puueXKv1vbxFjjeKlQmuIXuQ6V60CzwzXXXFPicelXEiNt3f8Hk+tNGVieNpBZhgBgIMP7ZQGga5Jwdsstt7QdLZkqUbvttls50cmJTxIBMmIyJzsZJZfkziRJLbroon2vyUlWTmKSBJEErSQHJRkgQYjccuG9npah/4l6kiJjpZVWKidDeX5OLnMy23/0XE7GkwSVJI1UTcxJ6oMPPlj95je/Kbc8fuSRR5YTl/4OOuigciK78MILlwqdf/3rX8trkmiTZKC6auNo1yeVuDJta2TbZH2S3JOkiySX5rF2CTjtZLtETtLbrUt/mSa4/1TBY5FgU5Kmsp/k5DbJjzlxT5Jktk32gQQR+sv9kQqn9bQ1CegkWa6ewjVT/OY7yP6XBLQkJ2V62uxntST1JACV1y6++OJl+2eEbxJxc8v+ke9sOJJ8l4BF9pPsM3ViWb6b+vvMPpX17a9exgQTkvSS0aIJpCRRKPtNAnOtJ9RJek7yVhKMkgiTbZdg2Yc+9KG2I1CHK+3wNa95TUlaueSSS9oGHJKcleSWJAomkNZOliXBwiQuZ7kzhXf28SS25Jb3rqePbg2OJJE72yv3JxCSgEL+X38faQ/tKtAlGTSBo3vuuad87/m8bNOvf/3r1S9/+cuS9DOc6Y3SXjOdcZI8k4id4GGCX+0q7Q7WDtK/ZLRslifVD7PuqZSYviH7wTHHHDPL9zmavrC1De+///59CUQZSZzAdBKWE5TpX3UugdyM6M0+n/fL8iXRNJ+foFs7SbhN4nQCy/X+me84bSqBvbSRtNnhSqAnydxZv7rqdL6vJHRn+TJqOFN1ZxslgTT/zzZol5ycvjjtJn1Y/ynk222ryPsmkXsoqQDQOtV1f0lqTlvMsma7pDJAvY/nu29NYsw6Z6rt7I+R/Tv7Wp6X7Z9b1iWBsNZ2EUkSTXvPvpNksnxnCT5mhHre7ytf+Urb4HGSUhP0TXtNm3jggQfK/pQ2lN+lejqrWt4riZHZntmP0hcn4S59am7pXz/wgQ9UY5Hku7x/9pf+08pHgulpK0l6T9A/yclJVu3/3IGmcE+/me2e/iS/aVmHtL+sd/2+aUvjHQjNPpALGrkokQss2a/zGUMlKY5leUf6/Q5VXSH7Vdpf9qssT6Y5z4WaJK/nM8ZDLpSk72+9QDgcA12YinpAR2uieGvQPL8b2VbpF7MfJdE6/XMGyAzUfydonmXNAJz8f3Z4wxveUB166KEDLsdgkkCf/SO/x+0ugAEAADRJzlkT360LAiQRLDGmnGvmXDqDBHPLeWhicIl1jyXGmLjDHnvsURLZEmfLuXYSBTNDVmLBw01AyjImLpjB2IlLpVpgfzmHziDmDOirp4FOvOjoo48u/058ODGCrF+em1vigxl03CmJb9eJlf2vz4xm+47X+iVxM0lkSQrMuXHievl+EgsaKHluNDIwOzHenEcn9lLHnBPHSyw2t1y7qWddG606mThJs/0llpp4RD7rsMMOK7GYxLLbxZcHSmocy/Wqsci2SjtNDDTy3SRunVjYYDp1fW04Ma/sW7nekdhwrv3kOlyugYwknj2UfL+5/jjSa2cjjXmNJY6X2HISgPO8xLwHShYeq1xvTbGDkU5tn+87fdQf//jH6ve//32JEwNAOyqKAjRYXbUuJ/sJGmS60f4nDDk5TnAoJ9IJPCQpIic3SXbLyfuBBx7Y9/wEKY444ojyN0lQGX2Z5Mj8zYjFBG8yUrjdFMFJtEuQKZ+Rk6EkqyQBM8uW12ZZaznxTCJVTmIzwjInofmcVA9MRbcknCVBqq4U1iqBqLx/TmZz4pl/J/kmSUz5rCRCjWV9svxJBE1yYF5Tf0aWMdU+E5jKsg9VWa9WTzfTiVGV7SRIl6S8JIXmRDrbKhW8MvIykgTRbqRznSia59YSWEgyU06S8175vur3TPAgCYfZRq2V1rKdkzCXfSEnytn+CVIkATIn1Nkvc1I6HNlXE+xINcd8ZtYpt7xvgop1IK1dMDLLmeXO+ibxLp+bEZfZB9IO8r23brMkBiZJNNupXu58ZhKeh7u8o5l+Pvtiliej8Aeq7pbgRhLKEmDMaOHsz/m+sl75m/XMsqZaaqsk5uQ7SgJf/ZokeCYAlIBl3Y7bJe1kWfN9ZTuk/0j7TJJokt0S9EuS43AkIJq2m+2eAGoCoem3kpCcfSRtbTgVSrPvpf9IsCXJ2/le05azzfLdfu1rXxtTX9gq75Wkoez72d9++tOf9j03y9E64jiJZPms7PNJDK33nfxNQuZVV131jPdPAme2X5Km8v5ZvmyHvCaB23zf6cdGIts2SeEnnXRSaW9Z19yS/Jd1bd03kkwV2SfaVX3IMkXdZwynv8vvUQKUY5UAafbN7M9pw9kmdWXm/D60tvU6aTmJnklayz6bbZ9gfX4XcuEiyW3ZHv3lNymflT4/z89nZd9IEly+y2zHdpJAmqBzXpPPzDas21KCo637ctp2KhvmNywVIBKYz+fkNWkH2XezTu2WbyTqZN12ia2RKhL1aPmsY10tM39POeWUkvTX7jchsr1zISi/f3lN9v+sd/aR9D8JSGcbZz3HW4LkaYv1hYz0xfl/PU347FjekXy/g6kDzHlNEoHzvediWtp6Ll7k9yv74HhIcvRIkkTrARfZP7NvtlNXv06gv3+iaNYt30G2VY6Tso2yH9dTgbWTRNsk76cfbZecP17yWzuaJNGop+yqq3cAAAA0Wc5966IHkQGROWfOoMj8TWJTZKBo/p/Y3FhijIlj5HwpcaY65pRz3MTmEidsV41yIHW8KZ/d7nWJQbbGqHM+mUS2xCkTF8y5Zx233WeffcpzkmSZGH4nZDtkRqpI3LF14PRotu94rV/ijanwGvm+c60m8cbEN3POm8Hv4yVxs8Qb68S6xGnr6ykZIBpZ/tHOmtQ/5pXt3E7iDNluiQclaTkxz8R065lGEhcfyFiuV41V4iqtsexcT2mNgY338o7k+tpQ6gI2iYcnxpV+IO+Zaw4pEpH4+Ej6g8Fkvx1Jkmgd86rjcv3lGlC9T7TGvEYbx8t6prprkjeToD07ZZ8ZaZJoTcwLgOGQKArQZUm8y7TFrbcEd5JIlpPdnIwl6SMJcq0j2ZLskYSmXIRP8KZODKlHKSbgkESeBBtSaa1Ockq1zYws6590ms9KhagkO7VLJsp7pbJeXXEuiWBJqMjrkjjYOmI0J6s5Ecs6pCJXks1qr3jFK0pCW6Q6ZRID+8tovIyaTeJPJMEm2ylS0apevtGsT13dMkGMJCTWUiUryT15nzw/ga/hqKc6zojDbsl6ZrRy/T1lP9loo41KsDAJNPVo1dYEkJwQZ5nzfUSSTZOIle2QAENroCL72Oc+97ny3ScolIBE/xPrnLzW31ckSJOEpWzj4Ywyz3Im0JgT4JyQtyZR5t91xcds7yxruwTFfLet7SCjWjO6M1qDYwnW5bOyzRJQq/fPjOxO4G84lRIHk6BLtlkq0+VzWtXTfw827XwCbnltqkQmcNM6nW4S2+qkuASU0gYi7S3rmHaZ7dc6PU/WK9svfxMMqpP9+kuicEbv1xKUS/uJkQQXs93TH7RWLMz3mwBStm+q9aYCYPaloabGbv0uMgK2Dj6mP6yT3UbTF7ZKO0iwvXU7pzJr/T4ZgVvLNk//kO8427SuappR7Un2rKdwblW3kWzP1oTyfB+phpy2kv10pEG1VL9tHbWd9853GAkAppJlpC0nyT/7SGvCdOQ5SZJLnzHYPjm7+rusdxKIW9tg/R1ne9TByEgQMiPkE4BP5eJW6bdzMSRapylrlWqkrX1+Eszq6sQD7d9pb+kj6v4on5+gffqpXAxonbY+yfHZN/Lbk9+r1koRSexLBYCop4MbrVQGHmxwQtpB9tPWfSMB4roSb/rqLE+Cof2nV89FjARC0xbSllIdoJb+KO0ubSnJ9ENNbd8JY13ekXy/g6mTKtOO8n7ZV7NPZZ9I28sFowTORzI933hJ+8+xQNYnicL95SJOHThu/a2u1ymJ1Lkgmd/9urJoEjSzT+VCTP9+PL+v6WdSMbtO+m6iutp31j99IwAAwOyUOFM9pXe721gHlY53jDGDBSMx/Nb4Q2JzddLkcKWaYSrcJeGt/4DDJE0mLpXz8focMjOH5Pw0y9waF8xzcn6auGNiWHnteOl/bSa3DCzN+ua7Syw6MdP+s2aNZvuO1/ol5pBz/cShch0lMeHIjF9ZzuHMDDVcGQyd98933xrvzTKn0mgdQ60Hoo5GrvEkxpPPqSvL9pdB06mi2loxN69LLCLx8MTCcl0pSZX9jfV6Vad16vraYBLPT6GNyHecBPVUyU0cKZ+f+HASlEfaJ4yXxJ4iMbh233n6sfQ7A8W8RhrHy/WxXOtJYZ/W6w9NjXnVMWQAaEeiKECXZcqYJPK13nJfTvBSsSnJUvUI1FZ1YCUBi9aksFqCAvXUAjlhqxNIMqVFRtAlGac1CaeuApUTnv5JOJFlSSWr/upphfMZddJJ/XmpltdOTtqTdJgTtXqkaKt20763Tl1dn6SNdH1SgS/PyQlya8JQqzooVa/DUOqRfYNNcTG7tass1xpgS0XGdtVEk1xVJzNlfXPCnKSSdsGYnDjXiUet26Y+KU7CW/9KdTlpTgW/4Uxxkf0hQYbc2gWyWkdQ1if4rRJUbbd/JugWrSf29dTVCbq1m7p5sAp2w5FtX1d8619VNCNTsy1TYXMgddvO9m43zUkCFrnl+6rbT56X7yVJje2+vwSWklA90PZLYGfNNdcc1vYbjkwRlGShBLW23XbbWYIn6ScSvMl2TnJyOwk6tqualxG9CYyl0l8CsaPtC1sl6bPdCN12655ku/6VeGtpS+3uz/RRkUS1JNC2JjpnXRKE+uQnP1mSTYcrn5WAdX+pnppk1ewbraOG6+oNdZWGWvqGTMGTbT1QhdtW9Xaqp+0Zq3bTE+X7qhNRW4PiqV6QoF279pn+t95+A1VcaPe7MtT+nWBsHWhv3fb1iPXW19UJ9HVydX+5P++V6ttjmYq7Tj6v96t2cmEi2yuB8iTzZb9o7evyHgmgZ7BHEgFrdTJl2lm76a/qaaUiFSq6bazLO5LvdzBpX1mGBKCzf+bYJG0lSeC5gJHlSAWDJOd2WpLZ81scSZxNonIuouQ3IQn2qZxQt7c68T2SeJ11SdWTJM+mT862yfFUBpPkNyz7TpKPazluTUWFtMVMCd9k+Y7zW52+criVYwEAAEYrcbxUeRvoNrsKEIwmxpjkosQOcy5bD8ptNZrpkOu4VP8YdeKk+eycP9dJljn/zPlaBnsnrt+/SmTOa5OklsHh46X/tZncMjAy585Z3yR8nn/++c+Y1WI023e81q+Ob7eLRWZ/Gs8pwTMgPQMt200Jn9hAHcsfS5XXOt6V2O5gMdIkHafCbeItmY2mNWk0spwpUJBrEq3Ger2q0zp1fW0wuYaW2GGK2iSmle8/A7KzfyUunbh/npN23FpooVOSxF5f/0rsKjMMpfBArhWm4mzabbuY12jieOkXk/CdhPHsd01WF7LoX8AEAFr9v19GALoiAYU6KSEn1hlFm+TQJDXmxCbTlrRWJqvVVdNSKSujXNupp1yvp0qoEwYyUi4n+Lkl6JCToJw8JmmidXRiqxe/+MVt769PxjO6MEkCCYrUSTCDTZ+RaSQyKjGjaPtrl/DXGmypkzJHuj71qNb6JLedOokuIweT9Ng/iaS/BLFyYt3NkaapFtZORhRnVGlO1jM1Sz2CtN208/X+lPUeaH+qv9fWqTdyEp4Kf0k4yS3BnFQzzcjWJJKMdPRyTsqzLAnqZFlyUp7k3tYRyf2r4MVA08/WgcvW19T7XD26sl3S6VglsToBxCRL1sGDu+++uyTTpk0PlpRXfxepPtpuKvO45557yt/+06BkfdPuM7o32y//zvbLSNl65Oxott9oEqHTPrMf1FVrs/5JEM161YnlSVZLpc3+23yg/iZ9YYIdCaZm/RKcGU1fOFR/M9S+M9DI9nZJ9mussUZJVkvScJKucsv6JriWNrLuuuvOUo13OFINd6C+Ovt1tk3ruib4lYSuBA6TJFYH3xNYHe608619zXj1dwPtdwkIJ0m0f6W/JDsm2JfvOpVx0z9kPZM0XAc4B5pWvd33PNT+PdC+Uf8e1ftGPjv7dyQQnerb7eRCQJJss8wD9duDyTFBvU2Gk9ibAHAqqeaWYH1dWTPVfVMd9vLLLy9B0yT6t+7fg03zlN/1VJVs99vdaWNd3uF+v0OpEzHbyW9ggvppf0kmrqvYdrrqeI4pE8BPkmfrtGTpQ7N8OUZo3ady/JDbQN7znveU3/wkpGffSn+UhPdUSMk0XON5wW52yLFd+pkcu6ay8mCJ1wAAAGOVioDtki5nt9HEGBNTGiz2lXPmxKXazdozkAyezXTbGYCduE49mL3/tPOReEmm2s5sXzmPzS2flzha4v0ZDN5u4P9Y1BUGI+e4ieElWTPni4nZJX7XLnY3mu07HuuXWT7qOP1A39N4xLf7x2TzmVnPrEtirVn/7Ad1guhAMbnhqGdGajcQuN05fQZF51a/NjGufG+JxSfOd/LJJ5ck7GzTxO3Ger2qk8ZjeYd7fW0wSZjMTFADScw714HSrhMjalfMZHZLoZjEovL91zPS1d74xjeWviZtrTXmNdI4Xq4XJm6WuG6u2+Zvk9Xr2oTKuAA0l0RRgAbJCXcCDzkBzEi9nGTlYnxGwPUfqVsnxaQS0lDVkOrpgiPTpSTRKidImTYkyS1JaMstF80zXXimYO9voIS/1hGe+ZzWSnODjf7M6MNoN93yUMGQ1qDDSNan3mZZxv7TsfeXBJEs21DJOKlIl5Px/tVMB5Jk4CRsDJSkOBrtRizXSWtJ5M3U10nmSKApCYQJ5KTCY4IltXrbJDlrqG3TOuI0o1czmjKVyrK/JjCTIF9u2Z/f/va3l4DCcAJ4CcrlZLv/KNiMtM4o1W9+85sDvrZdMvVA+0y9/AMl2g0nIDWUbOu0mWzvOjEvCbtZjqGm+K6XL0lw/UeVD9a2ExhK0nSSz1vXNwHIJK5mpHmCse2Md4C1nSQOpV/LLcGbtMsENtNWE2xpNViCcd2v1NtptH3haPqb+rPq/mu4+06mtk87yT6cAGr29dwyZU/271REHslI/+H0ra2VYxMczD6ZNpoqkwlIJ/CfCp1J7m5XEaCdBK4jVVGzLYaTrJigcQZDtOunhmq3rZIgmSDdN77xjVkqFGRbJNk47WywixSj2ceHu2+0/o7VlW5Huh8OR+vrBuq/BpLnZ/BEbu9///vLLcH98847ry9RtF6Pwfav+rF2v92dNtblHUnbH4s6gTx9dLckWJ7jyyQJ53clFRWSxJ8k8iTSxkiSl+vk3LoiZxK387uf44qBql00TdpEEkXradQAAAB6zWhijPXfweIOIy0MUMeekkyWRL7MUJbYUga0Jo7VPyaWqawzsDEV/VKpMLH33M4555xS/W/fffctgyJnh6x3EleTaJlZkjLIOjGFVPrsnyw62hjuWNev9b0GilGO59TziScfccQRpWJj6xTeiS2kYEficfUg/dGqz81HWq223r+SjJxbliXXg5JomRhiEkVbY0KjvV7VSeOxvJ2MeSXe3K3qldk+ma0r1YpzTSTJkam0mkqjSWKtY54DFSsYThwvcf3E0XOdtl2RiKap++5cG8i1yJHE3wGYPCSKAjRQknqOPPLIUvUyiTwZwZrKe+0O+HOy8+53v3tE758T5NwSVEgCYar8JVCTk5+c+OQEa6eddprlNe2mq+6fNJhARmvAJI8NlDg1VMLV7Fif+rMyLUX/KZjH8tl1Va0klw5VGTDJrPm+kpCRQFO7qbL7G8u0LakUmAqGOVlOolhdTTTJIe32p+23375UAxuJjBb9whe+UJYz03AkCTDbJKOLM4VHtkkS4QaT4E2SfpOomhPuTPuRRJSMis5+lZPawRJFR6IOlCVJsZ3+VQxHI8GYJOUkAefSSy8tgcWMLs+JeSqKDqb+LrLvDpVUWsu2T+XSBC2SlJfKmqnKme1XJ/8MNxlwLPbbb78S4ExS0mtf+9oBn5d9Md9xkuDrSgXD3efrviP7xVj7wtHsOxmlPFDAcKB+MiONd9hhh3JLMnvaSKpHZzrsBNIykjkJewNVUu1voH036mXr3/emL0jgLn1BEkXrviBB1NbpdwaT4G/27QSF05cNtS8n6JjpnhKkO+SQQ9pOGz9c6UPSb6cfT2AuyaHZv7O/p4/JvjeSahbjqfXiSb7b4fTro9Ea2MvvXf+gf7ZP+uIMRDj++OMHfJ+0nYMOOqhUjMz7JME/y1z/Rg42/VR9MWK4v90DBZ7H8rtWmx3LO1pp+0NdzOhEQv5gUr04t/7+/Oc/l7/9p2vL726WuV1l9dbvNc/JQIjIQJPBguZ1RZP0/d2optNu3xhosA0AAMBEN5oY41Bx0xgo/jWYxKUSL84A5iSKJj6VWPrmm2/eNik1yZq5JQ6XogKJo+X1iWEkppE4xnhOr97u/DWxqFSDTQLal770pWfMEjKa7Tse61dXZK2/p3bXX4b6jtrFa9q9Js/bY489yvl+limxzVSSTOypnk0kce+xJorW5+YDDa5ORdp8D4l5J9Y4kMQkkiia62l1zLk1JjSe16sGinmNpn20ml3LOxpZx8SBB0o2rLdBN2NeiQsnMbSehr5dzCvXA0cbx6tjXqecckq5tZM4eR3zaq1Q3A110nW2S7djkQA018jmuQSgYzLirR45+vWvf70kn7RKFc1IFaeBpLJZTobqk8Zc9E91yfoEKSeZCTgkMTAn2pmOoXU64latU3+3qhNzkoyWIEXes05MG6iyWk4g68fq9RiNka5P/VkJXOS17aQqXUYzZ1TzcCRRKidcSYSqq3INJslg9SjGOpmonq5ioGWqpxoZjSSE5qQw2yOVVJOs2H9Kn9ZKgYPtT6kMmKnT66qUeb88P4mBdXAsFcpSQTSfU1dybbc/9XfBBReUJNEkfmW0bxLZMn1MnQw43O9jOFIFNur9pt16jocEOiOJoln+bKckaw5VhXE4bTuVSrPv14GnfEaCXxnJnQqdCYhtsMEGfW0xya/ZvrNbkhTTvjK1/FDq6c+zzMP9DrIe/ad/H01fONZ9Z6CExHbLkM+89tpr+0ZWJ4iaCrlHH310SRRNclam+6kTN4cjVQoGmiKoXrb+AbDXvOY1JWk++2GC0Jk+ZyTTzkf23fw2xZlnnjnk87N+2ffTtw03CbadvEe9fRKQS2WFJGKnMnKdnF9P5dUNuYhS9+cD7Yf5vjKIIe10ONM7tZPf2DrA164957G0nSQED7WvL7744n2/P3XAeai+Ma6//vryN9t+MLPzd602nss7WrmIkwskSX4faF3r5RtoOrjZKcdbGWSRBOJ2y5fHf/7zn5d/v+QlL+nbt1IZdPXVV+/7fR9ondInZHBTjiHymna31mnS6vvGo3L3WGRb1Bc967YAAADQa0YTY6zPtZPs1C4RLsmdo5maOzH0xE9SbCGJTEkUbReXysDSxPHq2GDO2TLIObNQ5fy1jksNJ948VklorQfeZ0Bu/3jlaLbveKxfEtzqJM2BYiLtlql1oHi7GEG7mZqy/EkSzWtzjSoz1GS2mvrzxysmV5+bDxS/zvImplbHM0cScx7v61WDxbzyPrm+NBadvL42mM997nMlnvve9753wOfUcehuxLwSWzz33HPLtaR2EotP20u8NIVORhvHyzYYKOb13Oc+ty8+Vt/XbXUbSqy63eBvAAiJogAN9qEPfajvxDYVRVtPXl75yleWv5muJSNN+8voy1QYTMWwjNSNH//4xyVxMJXX+gd6kmyTxLI64NNfEv/ajYasqzy2jnBNsmBkquV26sS5nKSNpaLUSNcnI10zzXMCMgMldSZ5K1U199lnn2EtQxIkMpV2/drBAmVZ73oEYiri9R8FnJPX/tUsk4xZJ3GMRj3ldBLDzj777HICnRPjOjG0lgBPtllGP7YLJGU5kviZioB1gth1111Xqkbutttubatw1oGtdvtTf3US3fLLL992NGeSH2ujTbKqvepVryp/k3jWbnT8hRdeWI2HbNOM6M2o8Oxvw5l2vrVtZ4rgdts1SYIZvZ19P8G61u2XqVXq5NpW+fx6aqCxbr/B1FVEU9kwyZEDyTKk/dZVKtsFZNolYyZImm2SQE32ldH2hWPdd5LY3H+/zv/b9SupDp3AcrsRxwn81QmUw2kntey3Wd/+0lekknISQpNo3SqJ3FtssUX5nLSntN9swySDjUSCgwkypa9IMG4gSZ5PkDuS1DmWqXmyf9d9fGvSWS3B9TqhLX1VN6S6dCRo3k6m50rFg+yHg1XlGCoQXQcg2yXPpy3loksStk844YRB36seNJDkwDr5tF6HtN92FRwS+M+gg+FUKK5/11JZur+8d6pPt1MHMIczBdZ4Lu9oZX9M35rvtO7TWuW7qAeIjLS6yHjI9sxvf6qb5Leov/SJ+U3JhcD6mCkXUuopuS666KK273vWWWf1JaBnv0x1kRzztbul6ketvq9dO+6kuv3kQlfdpgAAAJqsdRar/ufMA51LjybGmHhSzukTS67PqfvHt+uKdSOtGJnz4sRtcp6cuGHi1vW5aC2zU6X4Qx1TapWqhvVMGSOJo41FrskkVp1z/0MPPXTM23e81q+OUbabgSsxijru06p1Zpp28Zp2SZh1zDmJcO0SElMJNbMnjTUmVycoJ47SbvBzHXNOPLLdftmqXvfWmPN4Xq+qt2O7bXjVVVf1FdkYS8yrU9fXBpPZ3vKdZpu3m1o+sfsUt0nflJhzpyUe9YlPfKL65Cc/2bZPOu200/qS0RMrH20cL0niA8W8cs2hft/6vm6rY179r/8BQCuJogANliSiTKdcn3jWJzeRE8D111+/nAQl6bB1+uacDCSpLyelGX1YTzOe4EVOipJUk2BE69SvOdk7/fTTZzkRbZX3TEJmnYyRYMWpp55akl+SgJRkwVqmf04A5Ze//GU5UWv9nFQaPPDAA8u/M9V4nQg7GiNdn5yM11Uu8/zWCn456c0UMnWS4C677DKihN4kXCUJM9OfJAmrNak3J5757urk00yD0XrynFGMObHN84499ti+RL5s62yr0YzSblVXDz3xxBNn+X+rVFvLfpLPTsJHXYUtsh9lHbMcSXzMOsaaa65ZEiyyDx5wwAGzBEGSsHfSSSf1JUwOpT5xTXCpNcEw32n2s9Z9f6xTwyepOSfv2afzndTLnXXPNsrI0vGQAGj20QQfvvjFL5ZgXx3EG0z2j2yPtOk999xzlsp7+Q6yD2d/TbAmScCt2y+j/VuDevnsBAxbg49j3X6DyQj4TAme/T9tKMHP/glcaa9Zh1Snzfew1VZbtX2vvffee5aAW/qOTBsUmap9LH3haKXKc4LYaR+ZBqpOns82TbC43Sj++jPTL9QJw7UE2urgZbt+dzD5vIzor11zzTXVRz/60fLvJCS2q1xbV2k4+eSTy3KMpJpoLd9vneh++OGHl4B5HRCuJUiYfuIf//hHGb3cP5A+UglE1xdEknDbmuycShT5/amD0bNz/x5Mqvimzec3Mf1463LktzDbKpI0PJZqiul36++7v3znaTd1Il9+s/tXu0iwPb91SWBOMLm1LaUtJjCfygdpN60VIdIWM8Va+uTsA0P1ZXlOpD3WSYWR984yDhQ0r6fLSsLzUMZzeUcr/UE9tVW+4+yPrZU4slw5Hkl/Pdb+Z7Tqiyn5HWgN7Ge/POSQQ8q/sx/UFTHq47hIcPycc87p67eyX6cfzqCXfFcf+MAHqomoTixfbbXVBpw+DQAAoElap5fuf85cJ0H1v380McbECuoKgpl2vTX2lHOpscR46jhUHTNOHLE1AbY+h835aWZLSfyiNfkw1QHr6oGtcbSc+yf+kVs9UH68POc5z+mLgyWOl6TQsWzf0axfOzlvzz6RhMEkstXvk/hoZuJpN5NLnl9Pj33MMcf0xWzz2i9/+cttB4vWMedUKfzqV7/ad3+uDSXRLp9VG6hC43DkGlEKfAwU80oCc524l7hSYvhJZm6V+GSuUWS5UvF0u+22my3Xq+qqkRm4nMTQWuLFmWltICOJeXXq+tpgMjg414zyvSZulMTnWq7fpJ/IfpAYcDcG4SbmnOsCWb70VfXA/OzPZ5xxRknazDbPta6JFMcbq7r91LFZAGjn/9WZB6CREkBJglECEUmQyQlKPYVqKljmpDEnZkk8TMXMBFdSETJBkSSNJMGurtCYoFGSQ3JhPyf/qYpXn+wloJGTqFw0b036rKWCX0ZrJkiRpMgkZCQ5IxfYUy2qPpGvn3vUUUdV+++/f0kUy+fkviQP1kkKCYoMt2rnQEazPqmIecstt5TElQQykvCQE8RMl11Py5ApVForpA4l2znvlxPmBMxyop4T+JwgJ/CTIFUdKMmU03XCUOtJbU7qU6kztwQZUs0riS5JyshJdxINxzIFepK5crKcYF+dNNLfwQcfXAIVqfSW5UwgKCfTWY4EI/LaBJ6yverE2wSVMjI60wUlQbHeN7P9s+zZL+pk58EkeSrVCbN/JBkvn539Nu+T5c77ZN9OQKLdNDgjke8kbSfJdJkaO1Xpsn8mmJQAU6ofjleyaLZ9tk3WIe871LTzkTaVgGnadipEJtk0bTttOkHGJMktvfTSZSrhWvbX7OsJSGV/yb6X0c3ZXgkQpkJcvpskko51+w0m1dmShJi2nWm20w7SPySomnVPn1EnFaaSZdazrmbYKkmd6S+SCJap2ZOQWSdMJwG1f2W+kfaFo5X3SRJgAsTpl1PVM0mM2U+zndvtO0lizb6Wtp22kO2RYGUqbtb94dvf/va2lVUHkm2SPiWBuOy7Wdf0a/W+MNCUQAmepeps2nna72gDXgnI5vX5TUqQOFU0s07py/LedaA27TjfcfbXsU4/lUrP+T1J4nj6+nxe9uXcst9lO6fvmp3792Cyz+W7zXecNpBlTRJj6/ecKsv5XRyLVMZM4L71Qk2rbKf016kgmd+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eeCM++eQTJCUlISoqSlX/lHWQHbbNmjVTFUilcunp06exYMECVRl18uTJKsiprwQqFUmlaqr8nKLkd5BKp1JBVIKmcgKztKxv0KBBifOHhErld2vZsqVR/n+IqHpkZ2s7VEVEZdt/KQ1ybLZdqPnbHZemQ10XvDMmRFXtW3M0sfoqirrYIjZVp+m/YzjnEpleeEIW7p9/AaPaeeKhGwtXsHthaCCc7Gvh9WWVC7LrnYvOQGZ2LloEaSQoeq39/N9HDG8/f/hKGloFl7/+zg42qqroT7tiOd9SvktxmUjPykWMxk/YIPPKycnFN9uicXtnb3g4mybM3aepOxY/3EhVFy3PxJ61sfFEkprTjenApVRciMlE42vhT0MEedrD2b4WzkRpPyiam1u5rgGUx+7aV6JCfv/9d7Xz/7nnnsu/rU6dOqpNmVSxkIMKzZs3N+s6EhERERERERFZo6VLlyItLQ3Tp09XFz0Jh0q4VEKTUm20IAlySkDyjTfewLvvvquqfUqHmGnTpqn7ZT+OtKqX8Gl8fLwKeUq1UnH77bcjJiYGEyZMUMFOafn+wgsvqPu+++47Fb7Ut7cXwcHBKpQpP+utt95SIVSpJDpmzBj1HOKVV15R9/fp0wceHh7qZ8vPLM8XX3yhAqTS4l6CrFL59L777kNiYqJqNS/BVD1ZrkOHDoX2XclrJK3uiYiIqHrsu5iqqhMZUnHTnKYM8Mfqo4m457tzODitJfw97KuloqgEtVIzc+DqqO3Xg4hMF0qa8P152NoA8+6uV6zqmZeLHV4ZHoTnllzGUwMDKl0R9Fh4Xht2LbSeF80CndAmxBmL98ZhTAfvcpePSc5GeGI2WgcbdtLBo339cdOnp7HrXAq6N3QzwhqTpZOTOgp+JSrJ+uNJOB+TiQdN0Ha+MsZ19MJjC23ww44YvD4yuMrPJ2F6qWb91K+X0DbUGWM7lj8f68nnVWN/J9Wynqwbg6JWQqp/SnUHIV/lgMHmzZtVmzAhBxdkJ79Uo7j11lsNmgSuXLmiKj5IVVE9eQ45ECA73onIMrD0NpG2cEwSaQvHJJG2cExSTSfVQIWEQIsGQfXat29f5nP07t1bXUoybNgwdSmpRd7jjz+uLkUVbElflJeXl6puWhIJh0oF0PK88847ha7rw6t6DzzwgLoUNXbsWHUhIsuj32dNRJYbFNVy23k9G5ta+GFCfbSdfhQTfziP5Y81NvjvDYMrirrmhUNjUnSaDYpyziUyrU//iVIh9VWPN4afe8kB9Uf6+GH2hki8+McV/DG5UZmVSaXKXOf6rrC3LTx/HQ9Ph7uTDYK9DA/Bm6Kq6Hurw1X7eakCWpYjYWnqaysDg6LDWnmotsjyumk1KMr51kxB0XS2nqfSfb01Gi2DnNC9oSu0SLYfb+vkje93xODVEUFq+7WyEtN0ePDHC/h1b5z6nPnw1lA4GVDVtKAhLT3gUs78rQU8hlA12v8fJoNISzCpoCA7+2fNmoXo6OhCO/KlfZmkx0s6GFASqSQhlSCk/dcdd9yh2o9JW3udTqeCo9J6jIiIiIiIiIiIiIioInhQh8iyK+Xtv5SKjnW0HxQVgZ72+P7e+lh5OBFzNkYZ/DtK+MTQiqIiVsNtbznnEpmOtFKfuuQynujvj6GtPUtdTtoRv3VzMJYeiMe208nF7peg5fQVV9HolcPo+d4J+D59AKM/P425m6Jw9lqlt2NX01U1Ui2NcQmKyvwpQdnyHLmaDjsboGmAYZkDCU893s9PVSwNi8+EFmnp/6Im0AdEWVGUShOVlKXmWakmquXxKe3npU38PyeTKv0c++VErhnHsOpIAn59qCE+u7NuhUOi4v1bQvHGqKpXNiVtY0VRKyEVHOzt7VVr+LZt26JLly7466+/0KNHD3X/smXLMHDgQLi5GXaGjbSdlzZn3377LdavX48vv/xSXaQahLSjv+2228p8vARK5SJnzuTkXP9wLnhdPxlLgLXofaZcVi7663KfPE7/WKmoIb9HdS6r1dfFWMua4jUsb1ktvi7GXLa81yU7O1stV12vt1ZfF84RlrFsTZwj5CLrZ6rX29TvWc4RnCMsbY6Q2+S6VuYIUy/LOYJzhNZew4K0MEdobTvC1MtyjrDuOeLIkSN4//33cenSJTRt2lS1ig8NDS20/klJSaq7jOxv0pNKpxMnTlQnFEsbe/mb8/nnn8fNN9+s7l+1ahUOHTqEqVOn5j+GiKgg/X5jIrI8pyIzkJKRgw4WUFFUb3gbTzzZ31+1ee7b1A1tQ8ted2kjLwyrKKr9oCjnXCLTkL+jJi+4iIZ+jnhnTEi5y4/v4oMP10aouWnb1Gbq7zh5DglCTv39CsLis1TgdGwHL2w8kYQ1RxPxxMKLyM6BqqyZmK5TVTa1RIKrrYOd1O8wur1XuaHapgFOcJC0qIEm9KyNV/4MU22V39RgkInzrblaz7OiKJVs/s5YyK66/3X3hZb1bOSqQvPfbY9B/+YVm9flc0NOInhq8WW0DnbG3080Vu3jrZ1+3yVVDoOiVmrcuHGYPn06Xn/9daSkpGDbtm34+uuvK/QcQUFBaoe/XOSgwfbt27FgwQJMmzYNAQEB6NOnT6mPlQMP+hCM/mvB+8p6nDmWLXhdf2DHnMtWdP0tbVm+3sZd1pDfVf+HCV/Dyi3L96xpl7X211t+dkk7C8w5R1T3slVZf0tY1trfs1pb1tivoQRp5L6a+nrzPVv9y3KOqNiyMibL2qnO19u0y/I1rP5lzfWezcjIwEsvvaRCn/369cP8+fPx6quv4vvvvy+07Llz59CkSRN1MnJRH3/8Md58800EBwfj3nvvVUHRrKwsddLxvHnzSng1iIiIyNJJNVHRwUIqiuq9MzZEVWm6Y945/PtSizJbaiZdC54YUlHU91rr+dgUhlSIaroVhxKw9XQyVj7euNy26/oKme+NC8WgWadUxbt6vo6YsugStpxOxsi2nlj7ZBM0CcgL+/Rs5IaXhweptsL60KjMacPKqFpqzqqiH6yNQHpWTpnV7I5cTVOhporwdLbFhB6++GJzFF4eFqgqs1LNpQ+IsqJozSMRwZzc8oOE87ZGq7B9bTdtx+Jkv53MbVJJ+tPxddVcZ6hnFl/Gx+sj8VhfP3xwSyjnRTII3yVWavDgweoA28aNG7Fy5Ur4+fmhe/fuBj/+vffew44dO/Kv16lTR7WjX7x4MQIDA7Fp06ZqWnMiMraiBwWJyLw4Jom0hWOSSFs4JolMY+/evaprjOw/kg41EyZMwJUrV1QwtKBTp06hefPmJT6HPK5gdW7x66+/quf09NTeAUsi0g47O20fqCOi0u27mIp6vg7w1fgB96IkrLTg/gY4H52BZxZfMqiVrSEVRT2cbGFTS9sVRTnnElU/XU4uXvzjCvo0dcPQClT5HNjCA4NbeuC++RfQ+e1jiEnJxuonm+CvRxvnh0QL8nC2xc3tvVRL4SOvt8IdXXygxaBoUnoOVh8pvf28/A0pFUVbBVe86t1j/fwRlZSNRf/GQWs435qroiiDojXNuZgMHLycioRr22wl2XYmBcfD0/FAr9qwBPd090WmLhfzd8QY/JgrcZmYszES00cFY874ujUqJFqrVs35XasDXz0r5eLigmHDhmHNmjVYsWKFqupQkVLnEhKVChBFOTg4qHZjvr7aLs9MRNex9DaRtnBMEmkLxySRtnBMEpnGhQsXUK9evfzrEvQMCQnB+fPnCy13+vRpdduQIUNw44034p133kFmZqa676mnnsKMGTMwadIk1X1GOtosWbIE99xzj8l/HyKyLNKWk4gsNyja0cKqieq1DHbGx7fVUS2LpRqfMSqKSkVAqVJ1OT4LWsU5l6j6/bwrFofD0lXL+YqeACsV4Or6OGDO7XXw37SWKjhqyVoEOasAqLSfL01kUjZiUnRoVcGKoqJZoJMK487eEKm5fUicb80UFC0jLEjWR8b9xZhM6HKB3edSsOd8SonLSTXRhrUd0K+ZOyxBiLcDbuvkjY/WRSBbfjkDfPZPlKpg/UR/f9Q0Wpv/LQ2DolbE1dVVVX8IDw9X18eOHasqih44cEB9XxGys19azT/55JPYs2ePet7du3dj6tSpase/VBclIiIiIiIiIiLLk5aWpk4ELkiup6enF7rN2dkZXbt2xW+//YZFixapfURffvmluk8616xdu1bte5IgqZxwfNddd6kuNLIf6uGHH0ZMjOGVEIio5uBBHSLLHbsqKFrXMoOi4qEba6NBbQesPpJglIqioncTN6wtI3hqbpxziapXRlYOXl0WhjHtvdC9oVuFH98mxFkFRB/t5w87W+vosnJrR2/8dTBetZ8vyZGwNPW1oq3n9SQUtfdiKnacLTkgZi6cb83Tel5/ggfVDFtPJyM1MweN/Bzh6miDQbNOYde5wnNBfGo2fv03Fvf3qq1O6rEUzw0OxPmYTPy2r/yKySkZOny5JUr9jlJtuubhfFsVDIpakTvuuAMnT57EqFGj1BkrnTt3Vi3n27dvX6hKhCF69+6NH3/8UVWJkLCo7PCX8KicBbVw4ULUrm0ZJZqJiIiIiIiIiAjFQqEZGRmFbpOQqHSoKUj2CT377LNwd3dHcHAwHnroIWzYsKHY80VHR2Pr1q0YOXIk3nzzTRUmlSCpPlRKRFRQRSttEZE2XIjJRFyqDh0sOCgq80+rIGccCy98ckxB+sCJoUHREW08set8CqKStFlVlHMuUfWauykKl2Iz8faYEHOviubaz686XHIoX6qvOtjVUkGvyhjS0gNN/B1VVVEt4XxrWsnprChaE/2wI0ZV0fR0tkXX+q6qgvHgWSex40xy/jK/7IlTbdwn9LSsLsmyjT2ohTveXxNRbvB8/s5YxKfqamQ10Tycb6uCQVEr0rdvX+zatUtV/pSWYUJaz//yyy+Ver6OHTti7ty5qrLo4cOHsW3bNrz77rsIDQ018poTUXXiHyZE2sIxSaQtHJNE2sIxSWQa9evXx8WLF/OvywnHly9fRt26dQst9/XXX+PSpUv51+WEYkfH4gfzPvvsM1VBNCEhQY1jOXG5SZMmOHv2bDX/JkRkifT7ronIskg1UWHJFUVF80AnHC8jKKoPnBjSel4MbeUJOZb/9xFtVhXlnEtUfRLTdJixKhz39aqt5hbK0zLYGV3qu2D8vHN4ZvGlYkF6qSjaItCp0hVUpULg4/38VdW9y3GZ0ArOt+apKKpvQU/WTyqJ/ro3DiFe9iomaGdTC38/0QRtQ10wZPYpbL8WFv16S5Q6kSfYywGWRqqKyjb3huNJpS6Tk5OLWesjMKaDFxrUrlzg3tLxGELVMChKRGTl2OqASFs4Jom0hWOSSFs4JolMQ04Ojo2NxcqVK5GVlYXvv/8eISEhaNCgQaHlTpw4gY8++ki1qr9y5Qq++uor1cmmoPPnz6tAaP/+/eHt7a0qlYaFheHIkSM82ZiISpSdnW3uVSCiSth/KRWBHnYI8rSHJWsR5KTaeqZl5pRZUdTVwbBDqIGe9uhczwUrS6mcZ26cc4mqzwdrI1RY7fWbgsy9KpqzbkpTvDg0EF9vjUbDlw/jtb/CkJCWF+w7HJaGVpVsO693bw9fuDjY4ItNUdAKzrempQ+I6gOjZP2WHohX1YpDCgRA5cSeVY83Roc6LhjyySlVaXj/pTQ8eINldkge2MId7es44701EaUus+pIIk5GZOCpAQGoqXJzGRCvCgZFaxipBNGhQ4cyL4sXLzb3ahIRERERERERUTW2npcAqOwDGjJkiOpOM2PGDHXf+PHj8ffff6vvX3zxRXWwq0+fPrjlllswcOBAdX9BH3/8MaZMmaK+t7Ozw9SpUzF27FisXr0aDz74oBl+OyIiIjJUZnYOOr51FOuOlV8NU6obWXo1USFV/+T8tJMR6aVWFHV1tFEV6wwlVaukomi2jie+EdUUEYlZ+GhdBJ7o548Qb8urWlfdPJxt8drIYJyd0QaTevvhvTXhaPjyIby/OhxHwtLROtipys8/sWdtfLklGulZDAzV7KAo//9rivk7YtCrkWuxk3ncnGyx8vHG6sSdJxddQrCXvar4bqmVMqcODsSao4n471JeNf+iPloboao292zkavL1I+tgZ+4VINO67bbbMHjw4DKX8fX1Ndn6EBERERERERGR6TVv3hzfffddsdt/+eWXQvuI5syZU+bzfPLJJ4WuS6BULkREpbGxYf0KIq3YeTZFVV36dGMkBrbwKDco+oCFVmcqSN8e+lh4OtrVcSmxoqibY8XmqeGtPfHG8qvYcTYZNzZxh5ZwziWqHtNXXIW9bS28MDTQ3KuiabXd7PD+LaGYMsAfb628ipeWXkF2DqpcUVQ81tdPVQ9cuCcWE3qa//OJ861psfV8zRIWn4m1xxLxxV11cXxv8ftdHW2x4vEmeGD+efRr5g47W8ttTX5rJ2+8uPQK3l8TgZ/uL9z5R8KjG04k4ZcHGtTo9us1+Xc3BgZFaxhPT091IaKagx+URNrCMUmkLRyTRNrCMUlERGT9+HlPpB3rjieprysPJyImORu+biUfNryakIXwxGzV1tPS+bjawd/dDsfDS68oKm1MK0IqWPm526nXUWtBUc65RMZ3JioDX26Owls3h8DblXELQ0jV1bl31cOzgwPx2944DG5Z9skJhmgS4IThrT1UWFRa0Zt7vjP3z69JpIJ3elYu7GzYer6m+GlXLBzsauG2zj54s4SgqHBxsMGCBxrC0knI9emBAXh68SXMGB2Mer6O+ffNWh+JUG97jOvobdZ1JMvG0xqIiKxcrvTRISLN4Jgk0haOSSJt4ZgkIiKyfjodD+YSacXao4no29QNObm5+HVvXJnVRIU1tJ4XLYKccOxqyUHRylQUlTb1w1p5YMWhBGgN51wi45v25xX4e9jj8f7+5l4Vi9PIzxHPDw2Ek71xYiqP9/NXlbF3ny+5RbMpcb41nZTMvCqigZ72rChaQ/YX/7AjBqPbe8HTuWIn81iq+3v5qt9VgqF64QlZWLAnVs17UtG6JuMxhKphUJSIiIiIiIiIiIiIiIioBklI02H3+RTc2dUHQ1p64KddMaUuu/9iKrxdbFHP1wHWQNrPH48opaJohg7ujhUPIYxo44lDV9JwMTbTCGtIRFp1NCwNv+yJw+s3BanqdWReg1p6qPb2f/0Xb+5VIROS6t8i0MM+/3uyXnsvpOLo1XTc290XNYWroy0e6eOHr7dGIy4lW932+aYoFRB98Iba5l49snDceiEisnJsdUCkLRyTRNrCMUmkLRyTRERE1s/OzjJatD664CI2ncxry01kjf45kYScXGBgCw/8r5svtp9JwdmojFIriko1UWvZXm8R6IQT4enQyQtQRHJ6DtycKn74VNoo29oAqw5rq6qopcy5RJbijwPxcHeyUa3OyfxsbWphaCsPLNdARWfOt2aoKCpBUVYUtXpSTTTQw05ts9YkUjk0W5eLuZuikJaZo75O7OELb1fONbVqMepYFXz1iIisHEtvE2kLxySRtnBMEmkLxyQREZH1y8nJsYhtknnborHhOIOiZL3WHUtEw9oOaFDbETe391Lt1kurKrrvUl5Q1FpIRdGM7FxciCle/TOpkhVFvVzs0KuRm+baz1vCnEtkSVYfScSA5h5wsGPMQiukovPBy2m4ZOaKzpxvTUcfDmXreeuXmZ2DX/bEqpOa7GpYu3V/D3tM7OmLTzZE4ptt0YhJycaTA/zNvVoawWMIVcEtGCIiIiIiIiIiIiIiMglLOIguB5wzs3MRn8ZWlmS91h1Pyq/MJO2Tx3X0xk+7YoudvBWTnK0ClR3qWE9QtEWQs/p6LDzdaBVF9WGl9ceTkJ6lnXnOEuZcIkuRkKbD9rPJqoIlaceQaxWdV5q5ojPnW3O0nrdDli4XGRr63CXjkhNwYlJ0NbaK89MDAxCVnI2nF1/GyLaeaOzvZO5V0gQWm6gaBkWJiIiIiIiIiIiIiMgkLKF1tQTjRFxq3lcia3M5LhPHw9MLtfD8XzcfnIrMwJ7zqYWW3X8p77o1VRQN9bJX4Vh5DYxVUVQMb+2J1MwcbDqpnWrEljDnElmK9ccSocvJCyaSdkgbZi1UdOZ8a4aKoh72ha6T9Zm/M1Ztg7YOyTvJp6ZpEuCEsR28VCBaQqOkx/m2KhgUJSKycjY2nOqJtIRjkkhbOCaJtIVjkoiIyPrZ2dlB66KvBUXjU1lRlKyTVL2UPEu/Zu75t8n3QZ72+HFn4fbz+y+mqrb0TfwdYS1sbGqp9vMlBUUlbCK/b2W0CnZCXR8Hs4eVLG3OJbIUq48molmAI+rXtp750FpooaIz51vTSc7I20aX7ZaC18m6yN9ksk1VU6uJ6s0cHYLpo4LRu4mbuVdFM2wYzK8SHoEhIrJybHVApC0ck0TawjFJpC0ck0RERNYvKysLWsegKFm7dccSVSv52m7XQy22NrVwZ1cfLPw3TlUt0tt3KRXt67iocKU1kaDosatpxW5PStfB3cm20tXkJKwkoQattMS0hDmXyBLImP77SCKGtvI096pQCWTulYrO/5wwX0Vnzremo68g6s+Kolbtl92xau4d38UbNZlUFX1lRBCrFheQk8sxXxUMihIREREREREREREREV0Tk3ItKJrGoChZHzngLkHRQS2uVxPVu7ubjwpKrzmamH/bvoupVtV2Xq9FNVQUFcNbe+BsdCZORmRUcQ2JSEtkvrgYm4khrdh2XotaBjmhnq8DlmuoojNVH/msdnGwgadz3okdDIpapx92xKgQuJ97XiCYiIyDQVEiIiIiIiIiIiIiIjIJGxsbC6oomveVyJocvZqO8MRsDGxRPOzUNtQZrYOd8NOuvPbziWk6FXjsUMcZ1kYqisak6BCVdL0CXGZ2DjKzcytdUVT0b+4BJ/tammk/bwlzLpElWH0kEY52tdCnafGQPZmfqujc2rwVnTnfmk5yuk6d1KE/sUOuk3U5cCkVey+m1vi281QyVletGn5aERFZOX5QEmkLxySRtnBMEmkLxyQREZH1s4TP+/ygKCuKkhWSaqISdurVyK3E8fm/br5YeiBehUT/u5yqbrfKiqJBTuprwaqi+opkVakoKhXO+jVzx8rD2giKWsKcS2QJpO187yZuaoyTNknlwfMxmTh2tXi1aFPgfGs6+urf+UFRVhS1Oh+ujUBdHwfc1NbL3KtCZHW4JUNEZOXMdeYcEZWMY5JIWzgmibSFY5KIiMj66XTaD19KlUGRlJ6DbB23T8j00jKr77237lgSbmjsBudSwk53dvVBRnYuft8fh/2X0lSotEWQ9VUUbeznCJtaKBQoSrpWkawqFUXF8Nae2HwqOf/5zMkS5lwiS5iTN51KwtBWnuZeFSqDhPSdzVjRmfOt6SRn6ODmZAs3R33reb721uRSbCYW7onFUwP8YW/LADYVx2MIVcOgKBERERERERERERERUZGKoiJRA0EvqnlGzz2Dfh+dRE6OcQ+CZuly8c/JpBLbzuvV8XFA36bu+GlXLPZdTFXt6K3xIL2jvQ0a+TkavaKoPigqr/Xao4lVXk8iMr/Np5KQnpWLoa1KnzvJ/OQEiAHNPbBCIxWdqforijrZ11InfbCiqLbJ9tAziy8ZHO6bvSESro62uP+G2tW+bkQ1EYOiRERWjq0OiLSFY5JIWzgmibSFY5KIiMj62dpWrVKfqYKi/u526vv4VAZFybTORmVgzdFEbD2djC82Rxn1uXedS1FhioHN3ctc7n/dfLDhRBLWHktEhzrW13Zer3mgE46FG7+iaEM/R/XcWmg/bwlzLpEltJ0P9bZHiyAnc68KGdB+Xj4/41Ovn/RjKpY430pw7+lfL+FcdAYsLyhqq/YjSmCUQVFte21ZGD5aF4nf98eXu2xCmg5fbonC5D5+Vd4eI+vFYwhVw6AoEZGVY+ltIm3hmCTSFo5JIm3hmCQiIrJ+lvB5H5OSjcb+jur7ODMEDahm+3FnjAo93N3dBy/8cQVX4jKN9tzrjiXC28UWHeqWHf4c19FbtZwPi89Cx3KWtWQtAp2qpaKoPqy08nCi2ec8c/98ImsJikrbeQZTtG94G0/ocqBOuDA1S5xvo5Ky8fH6SIurgK1az1/7rJYW9MnsAKBZx66mYcfZFAR52uPpxZeRmll2qPfrLVGqgvPj/fxMto5ENQ2DokREREREREREREREZBI5OTkWUVG0sV9eUJQVRcnUIZP5O2NwaydvzL69DlwdbPD4wktGDYr2b+4OW+nTWgZPZ1uMauulvrfmoKhU/bwQm5kfWtBXFJXQSVWNbu+FqwlZmLkqHOZkCXMukZZdiMlQgXK2nbcMdX0c0CbEGcsPmb6isyXOtxFJ2fnbvpYkOT2v9bxgRVFt+3ZbDHxcbbFuShOEJ2bh3b9L3y7KzM7BrPWRqrJ9sJeDSdeTLIslBvO1hEFRIiIiIiIiIiIiIiKiawedVFDUP6+9bHwag6JkOtvPpOBsdCbu6e4LLxc7zL6jLv44EI8/9sdV+bkT03TYeS4FA5sbFnZ6rJ8f2oU6q8CNtZI20nKc+WREXlVRfdDE3QgVRW9o7IbXbgrCy3+G4ZP1EVV+vpycXKRkcD4iMrXVRxJhawMMaO5u7lWhClR0XnU4EbocBonKE5GYlV9N3/Iqiuad1CFfk/j5qElZurwToP7XzRctg53x7KAAvLs6HOeiM0pcftG/cbgSn4VnBgWYfF2JahI7c68AERFVLxsbnhNApCUck0TawjFJpC0ck0RERNbP3t4eWpaSkYPM7Fw0rJ1XxYYVRcmUftgRg3q+DujdxE1dv6WjF25q44nHFl7CgOYe8HCufKXLzaeSVDvegS0MCzvd2MQdB6a1hDWTiqLi2NV0tK/joiqK2tkADnbGaS8tQVGZU6b8ehmujrZ44Iba5T5GQqt7L6TifEwGzsdkqosEKqTyqYSeDr/WKn+9rWHOJTIWGR9SLNnY7eGl7Xz3Bq4qvE+WExR95+9w7Dmfgu4N8z5PTcES51t9UNTiKopmXK8o6u5koyqMkvasOJSAyKRs3NfTV11/cWig2taVFvR/TG5U7GS9D9ZGYFhrD7QKtt6TlMg4bGrxGEJV8NUjIrJyltjqgMiacUwSaQvHJJG2cEwSEVFVpaSkYP/+/fjnn3/U9YQE07edpLJlZeUdkNYq/YHyAA97eDjZsKIomUxaZg5+3RuHu7v5wOZaa3gJPH12Z10kpOnw0tIrVXr+dceSVAi1kZ+jkdbY8knwK9DDTrWV1gdP3J1sjRY0k+d5b1wIHunjh4d+uoCfd8WUumxMcjYm/3wBzV87gju/OafCEv9eSFVBmJFtPfHBuFA42dtUuLqs1udcImOQdsX1XjyERq8cxpRFl7DheKKqZFdV8hzrjydiaCtPo6wnmYYEe71dbFVIzZQscb4NT8zb7o1J0VleUNTpekVRqTBK2vPttmh0quuCdnVc1HX5P/vgllAsPRCPNUcTCy279lgSDl5Ow3ODA820tmRJcnJ5DKEqeOoLEREREREREREREVm06OhozJgxA2vXroVOp1PhnKNHj2LBggX4/fffMXPmTHTu3Nncq0kWQN9609fVToXI4lMtq8ISWa5lB+NVIPTu7nlVl/Tq+jhgxs3BeGrxZdzV1Qc9GlWuOtq644kY2Nzd6NX2LJ1U5zx2LSgqFUX1FcqMRV7vOXfUQWpmDu79/jyc7W0wtqN3oSqI87ZGqyBwti4Xs26rg3t7+MKzhOqxG08kYfmhBLw4LMio60hk6WRsSLvi8V288du+OHyyIVKNoeGtPTCqnReGtvKoVEXQnWeTkZiegyGtPKplval62NnWwrDWniooOv3mEHOvjqZZbkXR65/X8tXS1r8muJqQhZWHEzDnjrqFbr+9sze+2ByFJxZexMFXW8JBSrkD+GBNODrWdUHfpqarAkxUU7GiKBERERERERERERFZrNjYWNx+++1YtWoV2rZti5YtW6rWdcLZ2RlhYWF48MEHceLECXOvKslBCRttH5bQH2iu7SZBUVu2nieTmb8zVlVBaxpQvK34Y/38VUUmqUpZmSp5crD+SFg6BrZg2KmoFkHOxSqKGptUiJ13Tz3c0tEbd8w7h5XXqtztOJOMrjOPY9LPF3FzOy+cnN4aT/T3LzEkKqSy6I6zKYhKyrKaOZfIGKQ6XYPaDvj5/ga49E4b7H25BaYM8Fdje/y8c6ra6NmojEq1nZftAZl/yfLaz++/lIYrcZkm+5mWON9aYlBU/s4r2Hpevsp10hZpMW9vW0sF+IueQDP79jo4FZmBORuj1G0HLqWqiqLPDQ7gCU1kEL5PqsbyPq2IiKhC+EFJpC0ck0TawjFJpC0ck0REVBmzZ8/G1atXMXfuXFVBtF+/fvn3TZgwAd9++y2ys7PV/WR+Wv+81x8o95WgqLMtW8+TyYIafx9JUJUkS2JrUwtf311PVb6UiksVtf5YXnvP/s3cq7yu1lhR9GREuqrsWTB4Ymzyf/jjfQ1UhcNxX57BLV+eQc/38k5g2PF8M3x7b30EeNiX+RzD2+S1v155uHC7Vkuec4mqKicnF3/+l4Ax7b3U+10uUpXu9ZHB2PdKS5x/uzVcHGzwxvKwCj/36iOJGNzSQ4W9ybJIFVn5b5OKhqZiifNtRH7recsJiqZl5ULOCZSW84Kt57UZ5pW28+M6eJdYzbltqAse6eOn5mU5menDtRGo5+ugTqghourHoCgRkZXTV9AgIm3gmCTSFo5JIm3hmCQiosrYsGEDBg0aVCggWlC3bt0wePBgHDhwwOTrRsXpdNo+kBuTooOzfS0VKmFFUTKVBbtjVZDwts6lHyBvX8cFzwwMwBvLr+JURF4FTENJu/L2dZzhX04QsSZqEeiEjOxcnI/JVK3nq6OiqJ5U1lr0YEP0bequWmV/cVdd7H6xObo3NKzNqgRJu9Z3xfKD8VYz5xJV1a5zKSpoNLq9V4n31/N1xLQRQfhxVyyOhKUZ/LyRiVnYezEVQ1qyErMl8nG1Q4+Grqr9vKlY4nwbnpiltntleze7EhXLzSE5Pe91ZkVR7dp6OllVDL3/htqlLvPmqGA42tngvh/OY+GeWDw1wB92tpYXtibz4DGEqmFQlIiIiIiIiIiIiIgsVlxcHOrUqVPmMgEBAapFPZEhFUWlzayQiqJxqZZTYYks1/ydMaqtuARbyvLayGAEedrj8YWXDD5A+u/5FPy6Nw739yr9YH1Nrygqjl1Nq9aKonqO9jZY8VhjhL3bFg/39lMB4Yq4qY0nVh9NRGY2QzFE4o8D8fBzt0PPRqUHrh+4oTbq+Thg2p+GVxVdczSvcq9UFCXLdHM7L/x9JBEnwit2ckVNq2jeIshZfR9rIVVF9aFQt2sndshXfXiUtOHbbTFoUNsBfZqUPi97u9rh7dHBaozK/+F93E4lMhkGRYmIrJwltjogsmYck0TawjFJpC0ck0REVBmBgYE4evRomcscPHhQLUfmZ2tbfdX6jBUUlbbzQlolsvU8VbeDl1Nx4FIa7ulectv5gqTS7ezb66ig4NID8Qa1ZJZQaetgZ0zq7WekNbYuod72cHW0wfHw9GqvKKonbawlMFoZEihOSs/B5lPJVjHnElWFBOYlKCqBwLJC1w52NnhjZLBads/5FIOeW+ZZqcQc6MlKzJbq0X7+qOvjgIk/nIcup/qrz1nafCuvSVRyNloFO+VvA1sCfZt5VhTVpsQ0nTpB6b6etdX2TlkkHConwLw2Isgk219kPXgMoWoYFCUisnIsvU2kLRyTRNrCMUmkLRyTRHk2b96M8ePHo3///pgwYQL+++8/dfuSJUswevRodfsjjzyCCxcu5D/mxRdfRJ8+fVTrbbnce++9xZ73r7/+Uo8v6LfffsOoUaNU2+7nnnsuv+LilClT1PN06NBBXVq3bq0u4oEHHsi/veh9epmZmbjllluwa9eu/NuysrIwbdo0dO/eHT169MDMmTORk5N3QCcqKgqPPvoounTpgiFDhmD16tWlvj4///yz+l1l2cmTJyMmJkbdPmfOHLRq1UqtU/v27dG1a1dMnToVqamplfp/IMsh75kdO3Zg4cKFJd7/3XffYe/evRg4cKDJ140s7/M+pkhFUbaep+o2f2eses8Na+1p0PIj23mpg+pTfr2MlGthidJIq+Wd51Iw5446bOdZxoHm5gFOOBaebpKKolXVNtQZdbztsexgglXMuURVcSQsHacjMzCmlLbzBd3VzQctgpzw8tIr5S57MTYTyw8lYGgrw+Zl0iY5ueK7e+urz8FZ6yOr/edZ2nwr27y6HKDVtYqilhMUzSkWFM3IzkWWzrJef2u16N9YpGXlYELP8k+AkoD/sscaY8rAAJOsGxHl0fZfO0RERERERERERDVIWFgY3njjDRXaXLduHe644w71/YEDB/DNN99g9uzZ6nYJQ7799tv5jzt16hS++uorbNy4UV1++OGHQs8bHh6ugpQFnTx5Et9//7163IoVK+Di4oLPPvtM3Tdr1iz1PPv378fu3bvRokULFUYV8+bNU7eXdJ+IiIhQYdJDhw4V+nkLFixQv9+GDRvUz9u6dSv+/PNPdd/zzz8PR0dHbNq0Sf3sV199FUeOHCn2+hw7dgxz587FL7/8gm3btsHV1RUffPBB/v0jR45U6yWvl/wcCaB+/vnnVfxfIa2bNGkSGjdurMaOvAdWrVqlbn/hhRfU9ffeew9169ZVy5H56QPiltB63tvFlhVFqVpl63Lx864Y3NnVB/YVCHJ+cnsd1S727VXhpS6TkKbD879fxu2dvdGnqbuR1tg6SXjMlBVFqxpsvamtF5YdjDcolKT1OZeoKqRCqLuTDQY0dzcokPTWqGCsPZaEjSeSypw7h885pU4WeWqAv5HXmEytV2M3TOnvj1f+vFLtLegtbb6NSMoLhuorisZYWut5R9tCX8s7eYZM13Z+SEsPhHo7mHtVyIpZWjBfaxgUJSIiIiIiIiIi0ggJdN58883o2LEjbGxsMHToUHW7k5OTqv4pYbeMjAykpKTA0zOvwo1UzJRwZoMGDUrdgTpjxgzcdNNNhW6/fPmyOpil0+nyW+U5ODiUWI3Rzc0Nd911V7n3JSUlYcyYMbjxxhsRHBxcaFmpgCo/S38ATX4/CYfK+m/fvl2FRSWsKsHT4cOH54dIiz6H/D7lrbOQ9ZLKo8ePHy/xfrIe8n8t4WEJVl+5cgVnzpxR75OlS5eq94yMKbnfw8PD3KtKFiA6JRu+rvrW87ZIychhhSKqNuuOJSI8MRv3dPep0OMa+jnixaGBeH9NRKnBlzeXh6kW5R/cEmqktbVezQOdcOxqXlBU6xVFhVSUPRedqdaZqCb7Y38chrf2hKO9YeN2TAcvdK7noqqKlhQykc/7W788gyvxWVj5eGP4e7DtvDV4a3QI6nhXvQX9ppNJmPj9easJKMkJJ/rPQOnibDEVRdOLt54Xss1D5nU0LE1V8L2/V21zrwoRlSFvbwcREVktOfBGRNrBMUmkLRyTRNrCMUkEFRCVi97hw4dVMLROnToqRClVOKWdulTS1FfKlFCcs7Mznn76aZw+fVpVVnz22WdRv379/Jb1vr6+uOGGG1SVUL1u3brBz88P48aNU4HL0NBQVV20oPj4eHz55ZdYtGhRsXUt6T4JtEq1UG9vbxXMK+jWW2/Ffffdp1rGS1hUQrASCE1OTlYH2+SxerI+Fy9eLPYz5XcICAhQLcRlGQnOltZuPC4uTlVfHTx4sEGvPVl+WPS1117DK6+8gnPnziExMVGNmYYNG5YaJibzsLe3t5zW8y52+dXF9LcRGdP8nTFoGeSEjnVdKvzYqUMC1eMfX3gRq59soipN6h27mobZGyLxxshgVnQyQItAJ8Sl6mBTC5qvKCr6N3dXLZWlNXbL4LyWwZY65xJV1vnoDOy/lIbnhwQa/BiZJ98eHYLBn5zCikMJqjqvnvw98siCi/jnZLKaU1tca8dN1tOC/sYPTqgW9M8Mqniba3l/PLP4MvZeTMUjff3Qpb6rxc+3+qBokKc9fFxsEZOis6iKoq7XAqL6z+1kVhQ1u2+3x6i/mUa1yzupmai62NTiMYSq4KtHRGTlLK3VAZG145gk0haOSSJt4ZgkKuzSpUuqpftDDz2kgqGia9euqj27viV9VlYW0tLS0KpVKzzzzDOqCme7du3UfdnZ2aq6ogQpJURalARQmzdvrgKda9asQdOmTfHuu+8WWkYe26NHDxU+Laqk++TgmIRES5KZmanagO/cuRPr169XAdeff/5ZBfwkPPrhhx8iPT1dVQD9+++/1fIlrbP8ritXrlRt71u2bKna1OstX74cnTt3RqdOndS6ye/fr1+/Cr7yZMkkQCzvSQlcN2nSBFevXlUVeEk7ZN7SKgkBFGw9L21nRXyqZVRYIssiAWRpm3xvD99CIU9DOTvYYPYddVUb5SX74gu9j59YdAn1fB0rFYapiaSampBCc5ZQUdTJ3gYDW7hj2cEEi55ziapi6YF4ONjVwrDWFQskydjp29QNL/8ZhpwC1SXfXR2BeVuj8fXd9dCvWfmt7KlmtaBfczRRhUQd7Wrh512xVjHfSkVz+cxzdbSFr5ud5VQUzdCpse9gV7iiqD5ASuaRmZ2jTmD6Xzef/P8bouqSk8vxXhUcoURERERERERERBpz5MgRFRAdNWpUoZbvUhlRwpgTJ05Ubd4lbCnh0Y8//li1npdW7g888ABiY2NVVcW33noLTzzxRIktt+fNm6cqlcrjJIj65JNPYsOGDarCp54ET2+55ZYS17Gs+0oiodebbroJnp6eqnrppEmT8Ntvv6n73n//fRXok1bx7733nmpfLwHSoubMmYN69eqhUaNG6v4XXngBq1evVq+FkOf/999/sXfvXvz333/qecaPH6/a25N127NnD6ZMmQKdLq+SjASOBwwYoCrX9uzZE59++qm5V5EsgLSZz8jOLdR6XsSnskIRGd/Pu2LU++2urhVrO1/QiDaeqmrTU4sv5bdi/WN/PNYdS8Ks20INbsdc0zX2d4TttZfKEiqKipFtvbD9TLKqgkzXzd8Rgw3HE829GmQCErQf2NwdHtdO6jCUBPNnjA7BwctpWPRvnLpt0Z5YvPjHFbw6IkiF98k6VaUF/YyV4eha3wWTevth4b+xVWphr6WKogEeeVVQ5SQpS/k8kUBowZM63PIrijI4Zk4bTyQhKikbEziHEmke/0K0QrLDvH///lV+noiICLz88su48cYb0bp1a9XaS1qbldT2i4iIiIiIiIiIjEMqbkq4U4KUDz74oLpN2rm/+eabhSrwSiBOwpLSjn7t2rX598ntcpHA59GjR9XjpFW7tKOX/T3yfXh4OCIjIwtVPbGzs1MHTqUiowgLC1PLSciupGqnpd1XGlm+6M+Ti76NvQT5du3ahW+//Vb9bKl2ashzFFzngiQ0e//99yMqKgqnTp0yeD3J8uzYsQMTJkxQoWEJHAtpQS/vl27duiEkJASfffaZCjeT+dnYaPewRExK3gHyYhVF0xgUJePKyMrBO3+H447O3gipYmv4WbfVUVXA3lp5FamZOXj6t8sY3tqjUEtlKptUvmrk56i+t4SKovqQsOSUVh1OsNg5tzrM/Dsc322PMfdqUDWLSsrC1tPJGNOh5E4G5enZyA03tfHEq8vCsOlkEu79/ryqgvf6yCCjrytprwX9znMpqgW9obacSsKW08l4eXgQ7urmg4jEbBWKs/T5Ni8omrfNKydJRVtUUPT63//5FUWvnTBD5rH8YALq+TqgbaizuVeFaoDKdGOg6yzr04pMRlp73XPPPYiOjsbs2bPVTlapTCE7WqUKg1SlICLLwA9KIm3hmCTSFo5JIm3hmCSCOkH3pZdeUifv3nzzzfm3S7v1f/75B/v371dByS+++EK11ZYAnFz/6KOPVAVR2aczd+5cVXGzQ4cOqk39unXr1OWDDz5AQECA+j4wMBDdu3fHkiVLcOHCBdXS/fPPP1ft2p2dnfOrmsrPlSqmRR06dKjU+0ojJyN/8sknqvqnhDe//vprDBkyRN03ffp0zJ8/XwVgN2/erNZ79OjRJT6HtKs/e/asWmf5vXv37g0XF5diy2ZnZ+OXX35R1VQbNmxo8HqS5ZHquFIVd/HixaparVTaPXz4sDrx/fvvv8fSpUvVe2DBggXmXlXS+EF0/QHy/KDotYqicawoSkb27fYYXI7PwrQRVQ8lNajtiJeGBeHDtRF4+KcLuJqQpcKjVDEtrrWft5SKokGe9uhcz6Xc9vNannOrg7z/LSXsRJX313957/tRbSvWdr6gt24OxunIDAz8+CS6NXDFvLvrcZ9EDVCZFvRSTbRNiLMKF8u8K1WoF+yOtfj5VgKvAe7XK4paytwpgdBCFUXZet7scnNzsexQghojnEfJNPg+qwrL+rQik9m2bRvOnz+vWn3JQQU56NClSxd15n1iYiKWL19u7lUkogpsnBGRdnBMEmkLxySRtnBMEkEF2tLS0lRwsl+/fvkXqbj52muvYebMmRgxYoQKlMr3shNe7pf29NI6XoKXEpJ7++23y/1Z48aNU2HUxx9/HCNHjkRKSgqmTZuWf79UY/Tz8yvxsVeuXCn1vtK88cYb8Pf3x6BBg1RLeKlGKlUghfy+69evR6dOnVSgVTrmBAcHq/teffVVdRF33nknbr/9dkycOFEFRCV0+s477+T/jGXLlql9WXLp2rWrCsVKANbd3b1C60qWRUKhw4cPV12RxMaNG9XYGDZsmLougWYJGbOyrDZIiFur9AfIfa8FRT2cbCHHOuNTtbvOZJnVRN9edRXju/igRZBxqi49NzgA9Xwd8dOuWDw9MABNAvJCj2S45teCopZSUVRIIOPvIwnI0uVa5JxrbGmZOUhI06nWt2T9bed7NXKD/7W22ZXRro4LJvb0RbNAJ/wxuREc7S1n7JNxWtDfMe+sqsRdln/Pp2D10US8NCwQNja11N8Yd3bxwZJ9cUjPyrHo+TY8MQuBngVaz1+rrG9preed7W3U9npyBk/sMpcjYem4EJOJkVUI7xNVRG4ug+FVkbe3g6pEKhxINQTZCS/VC/r06YMXX3wRnp6e6jbZWf3vv/+qs9ql1dELL7yQvyM9ISEB77//vnoOqdIpFQ4GDBigqkZI9QZptyU7vqdMmYJvvvlGBTZ/++03tayEOOVxstHRuXNnVW2iXr16+ev11Vdf4aefflIHEtq1a6d2uNevX9+g30l/xotUqihYvULW76+//oKPj4/RX0ciIiIiIiIioppOWs7LpTSy36kk//vf/9SlLBLClCCqnhzkktb2+vb2Rd19993w9i65nWNpjylow4YNha57eXmpEGhJpALqwoULS7zvzTffLLTOEmyVS1Gl3U7WTyrpFgwDS1Va0atXr/zbpFqtnR13h1PZYlJ0hSqKSiBAwqLxrChKRvTNtmiEGamaqJ6TvQ2+uacePlgTgZeHBRrteWsSfWi3YDtbrRvZzguvL7+q2iL3b+6Bmk6qiYpoCwk7UeUkpeuw7lgiZo4JqfJzSRVRiVnb2rAyWU1rQf/bww3R490TePDHC/jpvvqlVkF8e1U4mvg74tZO1/8uvrOrD95ccRUrDiVgXMeS/162mNbz7pbYel5X6LNattddHWxYUdSMlh9KgKujDfo05Qm6RJaAp8ZUkQQ2H3vsMVWBYeXKlfj000+xZ88eFeKMiIhQVQ4kvCnhTmkJlpycrKoepKamqsdLaPTo0aPqcdLeXQKmssN+0aJF+T9Dp9OpQKjcNmPGDLVT87777sPp06dVRYRff/1V3fbAAw+oZfVVHfbt25cfFpV2XhI+NZS0GZMz8KdOnaoqUUjFhxUrViAuLg4NGjRQIVgisgws8U6kLRyTRNrCMUmkLRyTRERUGXXq1MF///2nvo+Ojlb7RRs3bozAwMD8IKnsX5XlyPxsbbUbwpID5E72tVSAQE/az8enMShKxiHVxyR0ItVE9RUsjUUOzi97rDHcLKR1utYMauGO2zt7o56vAyxFhzrOCPayx/Iy2s9rec6ttqCohYSdqHL+PpKIjOxcjGnvVeXnkoAZQ6I1U9tQF3x7Tz3VQn7W+sgSlzkSlqaq174wNLDQ+0Sq0Haq61Ks/bwlzbc5ObmISs5GwLWqvHKSlGzvZpdRoVpTFUWdCsecpMIog6Lms/xgPAa18FAnLhGZAo8hVA1Poa4iCYPKjkZphSXVPuUigVAJbP7yyy9qZ+Qrr7ySv/ysWbPQvXt3/P333xg7dqw6q11aujdr1kzdHxoaqoKdJ0+eLPRzJBiqrwa6ZcsWnDhxQj2HhDbFW2+9he+//15VKBX29vaqQoObm5u6fscdd+Djjz82+PeSdkw///wz5s+fr36O/C4LFixQZ91L0FUCrfIzSiO/v1ykMqmEWPUKXtcPXn1rQXMtKxf9dblPHqd/rGzQ6cO31bWsVl8XYy1ritewvGW1+LoYc9nyXhepOizLVdfrrdXXhXOEZSxbE+cIueh3GGhhjqju19sS3oecI7S7rCleQ7lNrmtljjD1spwjOEdo7TUsSAtzhNa2I0y9LOeImjdHHDlyRJ38fOnSJbWvSrrXFK0oKq3epQ38tm3b1ONHjRqlTjSWfUby+KeeekqdaPzwww+rk5rFwYMH8e2336r9YkTVYfDgwepEfKmCGx4ert7ncmK/vmPS7NmzcfHiRbz++uvmXlUqME9qUUxydn41UT1vCYqyoigZyTdbo1WYzZjVRMk4gr0csPDBhrAksv0m7eeXHUrAh7eG5m+PWsqcWx1tlEVKRo5qQ+9cIPRP1uOP/XFoX8cZ9Ws7mntVyMLd3sUHey+m4rkll9Eu1LlYZeaZq8JRx9se/+tWvNOqVBV9cekVxKdmw8vFzuLmW2kzr8tBfut5Xzc7yOrHpWbDz730DIgWSCA06Np668lJMsnp3F43Bzk5Y8fZFHz1v+udj4lI2xgUraIWLVrgpptuwqRJk1Q7eQl+9u3bF4MGDVKVQk+dOoUOHToUekxGRoZqSS+k4qi04frjjz9w/vx5VSX08uXLaNiw8B+jBVvGS4hUKnrqQ6IiICAAzz//fP51X1/f/JCovmV8enp6hX43JycnPPTQQ+oiO/h3796tqp1KgNTZ2RnPPfdcqY+VAw/6EEzRs2fKOpvGXMsWvF70D2lzLFvR9be0Zfl6G3dZQ35XOXhn6LIVeV5jrL8lLMv3rGmXtfbXW362fkyaYh2s8TXU2rLW/p7V2rLGfg0lHCP31dTXm+/Z6l+Wc0TFlpUxWdLnpKHPy9fbuMvyNaz+ZbX0npX9VXJisLS979evnzp5+LXXXsOff/5ZaPl33nlHjVNp7S37mu699161X+vWW2/Fl19+qa5LaG/o0KEYP348XF1d1cnL8lxE1WXy5Mmqo9LixYvVAdrhw4er0KjYv38/jh8/jgkTJuC2224z96rStc/7suZOcx/oLBoU9XJmRVEyYjXRv8NVuESqkREZgwRFv9oSjRMRGYWq1Cak5bXnXnc0AQNbelp0e+SKVhTVh6BCHSynOiwZJjM7R7X7fmZQgLlXhazEzDEhOHApFbd9dRb/vtQiP4B8JioDv+yJxSe314GDXfH9VFKB+tkll/H7/njc16u25rdxiwpPzKu8rG89r9/+lW1h7QdFpfV84aA4K4qaz6rDCcjJBYa3YUdiMh1LCuZrEYOiRvDhhx/i0UcfVTvIt2/frgKUnTp1UhU3pXpoSTvC3d3d1caCVFeQMKmETWUHZqtWrTBt2rRiyzsW+LCTCg3lqepGiOxUzcrKUkFWIdUjpAW9XOSAgbRqKisoSkRERERERERElmPv3r3qRGMJeQoJ1S1cuFCd1CwtvPWkIqPskJVuNBLMk4Cpl5dXoX1Wcr++uqlUc6xXr16hk6CJjE32hb7xxhtqf6W8/2Tfq56EmCU0Wrt23gFcorLIwXFf1yJBURc7VS2KqKq+3hKNcFYTJSMboFq91sKy/+KRkeWBVUcSVWhj+5lkZOcAIV72+GJLDB7p44ePbg2FoxW3hS0YFJX5PNSbQVFrs+F4EhLTczDaCG3niYS0lP/lgYboMvMYxnxxBtumNoeLgw3e/Tscfu52uP9aCLSoEG8H9G3qrtrP64OiliTiWgVmfet5X9e8bElMis4yWs87Fm09b4ukDO2vuzVafjABXeq7FKvySkTaZb1/DZjIf//9h7fffltVAJUd6F999ZW6vnPnTlVhVCqHBgUFqR3icpFKoHK/VAU9duyYCpd+8sknePbZZ1Wrrrp166o2SGUloGXnvLSYv3DhQv5tsbGx6NatGw4cOGCU30sOAki7puTk5GL3yUEDqVhKRJahpHYzRGQ+HJNE2sIxSaQtHJNE5iP7mWTfVcHgXUhICM6ePVtoOTkxWkKiciLxwIED1TJSgVTICdESLh07dqxqQS/daubOnYvHHnvM5L8P1UzSYalgSFSEhoYyJKoxhhRCMBepQMeKolRd1URn/h2u2tc2DWA1UTIeCTQNaO6B5/+4gvZvHcNbK6/C09kWs++oi3MzWuPizNaYe2ddzNsWjRveP4Hz0Rmw5qCo/7XqeBIUJeuz7GACGtZ2QJsQZ3OvClkRabv+x6RGOBGejod+vIDLcZn4fkcMnh4YAGeH0uM0d3X1wYYTSfkhdS1v45YeFC1eUVTrpMW8BEMLcneyQXI6K4qaWpYuF38fSVDVzYlMqVYtRh2rwnI+rTS883HBggVqJ7m0LpIqCitXrlRVEqTl0erVq1UI9JFHHlHLv/vuuzhx4gSaNm2qKnbKBsOqVavg4+OD+Ph4fPHFF6oaQ2ZmZqk/s0ePHmjdurVqNf/SSy+pNvDvvfeeeg6pSLply5Yq/14TJ07EihUr1Nn2Ui21efPmqv38tm3b8Ndff6lWYkRkGfSVXIhIGzgmibSFY5JIWzgmicwnLS1NBTsLkutye0nef/991RVn0qRJ6iToZ555Bs2aNcOyZcvyl/n999/Rq1cvFUKV5WQf1vTp01ldlKqFnLD/559/4sqVK2rfakkn4stnzJw5c8yyfnSdTqfT7IF0OThesHWz8HKxRXwqg6JUNdIaPDIpC68MZzVRMr5XRwSp4NyA5u64sbFboaqh2dnZmNTHT1X7uvWrs+g44xjmT6yPm9paX0VGCWu1DXXGumNJiErSftiJKu6/y6no3tCN+w3I6NrVccG399bH+HnnsPdiqqpYObmPX5mPGdvBC4/8chEL98TiqYEBmt7GLan1vPyOrtcCl94udpBhFWMJQdFSKoqyA4DpbT2drKo8W+M2BWkbW89XjWV8UmlYo0aN1M5Fqb4pgVEbGxvVbv7rr79W1UF/+ukn1Zp+/PjxqhJDx44dMX/+fBXqFO+88456/M8//6wqkPbt21dVJt2wYUOpP1N+xueff46ZM2eqQKdsDMvPnDdvngqsGkNgYKBqP//ZZ5+pCqgSXnV0dES7du3wzTffoEuXLkb5OUREREREREREZH4SCpUToAtKT0+Hq6tricvLfiLZl/XQQw+p/WISFC1Inkv2i8l+sDvvvFPtx5IAnwRMZX8TkTHt3r0bDzzwgDoxv6wDBgwVaIOWD+qU2Hre2RZxDIpSFaRl5uAdVU3UF01YTZSqQdcGrupS1pzbqZ4r9r7UAhN+OI+Rn53B80MC8NbNIbCztZ7PxvDELHRv4KqCK5ZQFY8q7kREBga39DD3apCVuqOLD/ZeSMUHayPw2k1BcHcqXLWyKG9XOwxv7anaz0tQVMvbuCVVFNW3nRfyWSDbvNGWEhQt8n8jwdHLcawoamrLD8Yj2MseHeqwyjOZmuXMt1rEoKgRSHstfYutolq2bKmClaUZOXKkuhT14osvqq/STl4qkBYVEBCAWbNmlficjz/+uLoUJC2/5FIRQUFBeOuttyr0GCIiIiIiIiIisjxS5VO65OhJNZTLly+jQYMGhZaT9vJyQrSc7CykcmPRVt/ixx9/xJgxY1Q3nnPnzqnuOi4uLsVa2RMZw+zZs1XFtClTpqBPnz7qfcdQqHZp9f9GDu6X2HpeVRTV/kFz0q6vtkRdqyYaaO5VoRo+50qoaenkRvhgTQReXHoFO8+lYNXjTcpsrWxpFUWDPO3VPG4JYSeqmNiUbPX/2oyBe6pGM8eEoH0dZ4xub1iFxDu7+uC2r87iZEQ6GvraWVhQtPD6WsLcmZmdo9qdF68oaqMCpGRayw4mYERrT83+fUfWjO+5qrCcTysiIqoUbpwRaQvHJJG2cEwSaQvHJJH5SBec2NhYFRYdNGiQqgQaEhKiuukUPSn6iy++QIcOHZCamoqvvvoK//vf/wotk5CQoJ5n0aJF6npoaCgOHz6sKorK90TGJu+v4cOHqyAzaZ903tKi1MwcpGfllhAUtUNaVi4ysnIKtXMmMoSEGaSa6N3dfNHYn+EmMv+cK39zPTckEB3qumDQrFNYeywRo9pZfsvYbF0uIpOyGRS1YifC09XXZoGcS6n6SGXNu7r5Grz8TW084e5kg192x+LVm4JgKSISsxHgXrhTrVTVl5OmtEwfBi2p9XxyBjsAmJKEo09FZuDDW7iPh0yPxxCqhkHRGmb//v247777ylxmyJAheOedd0y2TkRU/dUQ+GFJpB0ck0TawjFJpC0ck0TmbT3/0Ucf4d1338UHH3yAJk2aYMaMGeq+ESNGqADeqFGjMHnyZBUEHTp0qGo/L23lb7vttkLPJUFS2f9kb5934OmFF15Q3W+kjf3HH39slt+PrJu8F/38/My9GmQgqf6qnx+0RB8q8i0aFHXOC1klpOngz6AoVdDRsDSEJ2bj/htqm3tVqIYqbc4d0NxdtYvdfibZKoKiUrVXuj4zKGq9jl8LijZlRVHSEKnIPLaDN37eHYsXh9SGg4MDLEF4YhZ6NnIrdJslzJ36oKirY/HW86woalrLDybAyb4WBrTwMPeqUA2Um8vxXhUMitYwUvVh6dKlZS4jO+2JiIiIiIiIiKhmad68Ob777rtit69YsSL/eznw9eqrr6pLaZ5//vlC16UV+NatW428tkTX3XDDDeo99uyzz2q2WiVpX0xKXhWiohVFvV3y3lPxEhT10F7AlbTt0JU09bVNiLO5V4WoEDlBr2dDV2w/kwJraTsvAj3ygqKRidoOO1HFnYhIR10fB7g48KQN0hZpP//Djhjsu5iG7o0dLKf1vHvhbV45WepUZF4gW6uS03UlVxR1ss2/j0xj+aEE9G/mzjmZyAIxKFoDz66vV6+euVeDiEyIFZmItIVjkkhbOCaJtIVjkoiIKmPq1Kmquu2UKVMwYcIENGjQoNRqPm5uhSvnkOlpNcyrr6BUvPX8taBoKg8+U+WConW87eF5rTItkZbm3B4N3fDyn1eQmZ0DBzvLDnpI5V6hKoq62uHoVW2HnajiTkRkoFmAo7lXg6gYCcv5u9vh2x1x6N7YE1qXk5OLqORsBBQ5AUq2gXectdTW8zZIy8qFLicXtjbct1jd4lOzseVUEmbfUdfcq0I1FI8hVA2DokRERERERERERERksSQkmpqairVr12LdunVlHkw4evSoSdeNisuV3sAalN963rVwqMrLxS6/oihRRR0OS2M1UdLsnNuzkSvSs3Lx3+U0dKnvavEVRSUzIMEnCTtFJWk77ESVqyg6oJm7uVeDqBg721p4fkggnvntMu7o4oP+zbXdijsmJRu6HJkv7Syw9by+omjx1vMiJSMHHjw5p9A2wJOLLmF4a08MbW28EPPqI4nIzgFGtNF+MJqIirPs08OIiMhid74T1VQck0TawjFJpC0ck0REVBnBwcFo3LgxunTpgs6dO5d66dSpU6We/9y5c+jQoQN+//33UpeJi4vDM888o9aha9eueOONN5CWltdyWrzwwgto1qwZJk2aVOLjV6xYoe6/++67Ye1ycvIqAWlNTHI2nOxrFWuf6HXtYLNUziGqTEVRBkVJq3NuhzoucLSrhe1nkmHpJCjq52anAlv6sBP/vrQe2bpcnI7MQLNAJ3OvClGJpgzwR58mrpjw/XnNbzPqKzAHFqkoKidLxaXqVFVOy6soalsoSEp5Vh1OxJyNUZizMdLobefbhTqjrk/JXTyIqhu38aqGFUWJiIiIiIiIiIiIyGL9+OOP1fbcWVlZePbZZ1XF0rI88cQTKhj6/fffIzExES+//LJ6zLvvvpu/jL29PbZt24bk5GS4ubkVevzKlSvZPs3MJFTk62pX7P9BDkRLB0u2nqeKkqDIpbgsBkVJsxztbdC5ngu2n0nBkwNg8UFRaTsv/NztkKXLRVI6K8tZi/MxGer/tFkAg6KkTTY2tfDN3XXQ8e2TeOyXS/jp/gbQqojELPW1pNbzkr2SsKh8r+mgqFPJFUX19xNU4PeFP67A3rYWNp5IQnpWDpzsbYzyvCsPJ2Bybz+jrCcRmR4rihIRWTkeZCDSFo5JIm3hmCTSFo5JIiIyBgliRkdHIzu76tV85syZUyzUWdT+/fuxe/duFQpt1aoVevTogTfffBN//vknIiIi8pdr3bo1nJycsGHDhmLru2XLlkpXPLU0dnZ2mg2KlnRQXA78ezrnVVgiqojDYenqK4OipOU5t2cjN2w/ax0VRfXV8fRzudZbKJPhTkRkqK+sKEpa1tDfBZ+Nr4ufd8di0Z5YaD8oWvjzQU6Y0lfZ16rkdB1k16GzfeH9h+7XgqNJ6dxe11uwO1ZVtv/8zrpIy8rFppNJRnnenWdTEJuiw01t2XaezKdWLUYdq4KvHhGRlWPpbSJt4Zgk0haOSSJt4ZgkIqLKklDo3LlzMWDAANX+/cYbb0SbNm0wZMgQfPHFF5UKje7ZsweLFi3CO++8U+Zy//77L/z8/NCoUaP826T9vJwAsXfv3kIVRWX9/v7770KPX7dunWo7X6dOHdQEOp02D+DGpJQcFBVeLraIT9PmepN2ycF5OxugOYNNpOE5V4Kil+OycCk2E5YsvEBFUQZFrc/x8HS4ONgg1KtwBUQirc23d3Xzwa2dvDF5wUVcidPmvBqRmK0qcLpea9euZwlzp1QMlXUvqQOA/n4CMrJyMO2vMIxp74X7e/ki1NtetaE3Vtt5qdzdpb6rUZ6PqDJ4DKFqGBQlIiIiIiIiIiIiIouVmZmJiRMnYvbs2YiJiUHz5s3Ru3dvtGvXTlX0/OSTT9T9FQkoSvv4qVOn4pVXXkFQUFCZy8rPKLqMg4MDvLy8cPXq1UK3Dxs2DFu3blVVRAu2nR8xYgRqCq0e1NG3ni+Jl7OtaiNOVNGgaNMAJzhIWpRIo3Nuj4Z5QY/tZyy7qujVRAZFrdmJ8HQ0DXBUVb6JtDzfSoDxi7vqqhbfE384j5wc7W33hidmFWs7L3yvzZ1y8pRWJWfo4FYk4FqwFT2DonnmbopSJ4DMGB2s3pPDWnli1ZEEozy3tJ0f1soDtpyPyay0N7daEm32eCEiIiIiIiIiIiIiMsB3332nqn+OHDkSL774Inx8fPLvk0DmjBkzsHTpUvz444+YMGGCQc/5+uuvo0OHDuo5y5OWlqaCoUU5OjoiIyOvVapez5494ezsjI0bN6rnTkhIwI4dOzB9+nQcP37coHWT6qhZWVmqnbCEX/UHpW1tbfMrp8r3Qh+OLWtZG5u8qjymWDYnJyf/ulRYld+jpGXleeQ5ZfnKLCvrILfJsnIp+LoUXLbg+kcnZ6kQiv7nFFzW09kG8am6/Oc15+st6yMXuV2uV9drWHBZQ1/Dkl6X6lrWEl7vg5dT0CrIUS1THe9ZS3kNK/N6a3GOsNT3rP6+0l4XH2egUW0HbD+bgrHt3S1yjtC3nvd3s1Hr5e2cF84OT8go9/PSUuZka37PGrLs8fA0NAtwUt9zjrCM96yW5ghTvd7619bdIRfz/heKEZ+dw+wNEXi0j6+m5oirCZnwd89b74Lr73Vt7owwYO401xwhreVdHWqp9Su4rKNN3vKJqVnqvpzcvN9XvhZd1trniOSMXMxYFY4JPXzQuLadWmZwCzd8vTUaJ8NT0CTApdJzhARx5USox/r4qmXMNUfI/6tcl38FPxe0PkdwO6Lqr2He/7oE81GpbTwt/q1Rq0iFZFNgUJSIyMqZ48OFiErHMUmkLRyTRNrCMUlERJXx119/oWnTpnj33XfVTviC3Nzc8NZbb+HIkSP4448/DAqKSqhU2skvW7bMoJ/v5OSkqpoWJSFRFxeXQrfp28+vXr1aBUXXrFmD9u3bIyAgAIaSgwnyPPrviz5/QQVfDy0sKwdG9AdWnlx0CXd380HnAm0Li/7/6Q8wlfe8RZctb51KWjYmRQc/N/sSl/VxtVet57XyGlb2danKsoa8hqZeVsuvtxwAPHI1A8Nae+XfZuz3rDGW1eIcYYr3tzW/3kVfQzlpoeDfWSW9Lj0auWHH2WSLnSNiU7KRmZ2LUB8ntbw8wt3JBvFpudX+ecn3rGmWPRmZgX7NPPh6G2FZbkeUvP7GWFYfVJJlh7f1weP9kvHi0jAMbumJlsHO5T6vqd6zUUk6BHo45D+m4LJeLraIM8HcWdllUzJz4e5kW2h5WdbTNm+Z1Ky857Kplfd4+Vp0WWufIz5eFaYqr745KiT/tsGtvCAF7tceS0HTQNdKzxEHLqeqgF73Rh75jzHHHCH/rzLW5F/R9dXyHFHSsvxcq9iyef/rectWZp7S4uttDux3QURk5bTazouopuKYJNIWjkkibeGYJCKiyrh06RJ69OhRbEd9wZ3w3bt3x8WLFw16viVLlqgW9n379lVVReUiXnvtNTzwwAPFlg8MDERkZGSh2yQ4Gh8fD39//2LLDx8+HJs3b0ZKSgpWrVqlrtck+moaW08nY+bf4dBU6/lrLTeLkoPmUlGUyFBX4rPUe6ZNSF4whMjcc25ZejZyw/6LqUjNtMyWvVJNVAReaz2vbz8fxdbzViEhTYeIxGw0C3Qy96oQVWi+fWdsKOr7OuJ/355DZnaOplrPF5wvC/J1tUNMsuW1npc26C4OUvGyZm+vhydk4cO1EXiinz9CvK93vPBwtsUNjd2w6khilZ5/z/kU9Tq34HxMZpZ7rWowVQ6DokRERERERERERERksaSVe3R0dJnLSPCzpPbwJfnggw+wcuVKVVlUfxFPPPGEamNfVJcuXRAeHo4LFy7k37Z79271tVOnTsWWl9CqVBrVVy4dMmQIaiKpJrrsYIKqBGduEo5Kz8pVwaKSeDnbqoqiRIaStpyCQVGyBD0bukIyTP+eT4GlBmNEUIHgk5+bnToBgCzfifB09bVZgKO5V4WoQiRQ99N99XE4LB03fXoa8anamJMiErMQ4F7yNq9sC0drYNu8NMnpOXBzKjni5OaY1xq9Jpu+4ioc7GrhhaGBxe4b1toTG44nIj2r8q/RnvOp6FjXBXa27AhFZMkYFCUisnJs30mkLRyTRNrCMUmkLRyTRERUGRLGXLduHY4fP17i/UePHsXatWvRsWNHg55P2sDXq1ev0EX4+vqq+3Q6HaKiopCenhdcaNeunXrup556CgcPHsTOnTvx6quvYvTo0SW2lJc2ZIMGDcJHH32kQqY+Pj6oSfRt1sZ39UFObi4W/Rtn7lXKDxOVGhR1sdPMwX2ynKCoBBbq+RgWUCeqLoa0tmwd4qzer9vPplh0RdGCQVEVdmJQ1CqciMjb3moawAp2ZHnzbad6rlj9ZBPsuZCKXu+dwLnoDJhTTk6uqrYc4FFaRVFbi6woKmp6UPR0ZDq+2hKFF4cGwtvVrsSgaFpWLjafSq70z9hzIQVd6rlUcU2Jqo7HEKqGQVEiIiIiIiIiIiIisliTJk1S4c27774bn376KXbs2IHDhw9j/fr1eO+993DXXXchJycHkydPNsrPu3r1Km644QZVdVR/kEJ+bmhoKO69915MmTIFvXv3xuuvv17qc0i7+eTkZIwYMQI1TW5urvoqB6iHtvLE/B0x5l6l/DCRHBwvraJoHFvPUwWDoq2DnWFjw4OYpI05tyzSsrd7Q1dsP1P58Ii5g6IeTjaqep8eg6LW43h4OkK87OHuVH7omUiL822/Zu7Y+XxzZGTnots7x7HDjHNtTEo2dDmyHV5GRVENz50SBJVAaEncnGyRnF5zt9df+TNM/X31eD//Eu9vHeyk5tJVhxMq9fzyvjgXnYku9V2ruKZEZG4lfwIQEZFV/WHCsyqItINjkkhbOCaJtIVjkoiIKqNt27aYNWsWXnrpJRXYLPhZIp8t7u7uKjAqy1XWiRMn8r+XQGjB6/pqo7Nnzy718e+8806h6z169Cj2HEWXsVYS2tVXXLqnuw9u//ocTkakm7VSWEy5FUVt1cF9adXoZM/6G2RYUJQH0klrc25ZejZ0w2f/RFrk32QSFC1YTVQ/n+8+n2q2dSLjVhRtxmqiZOHzbbNAJ+x8oTnGzD2Dfh+dxPcT6uOOLqbvKhCemLfNG1hKRVGZO3edS7HMoGgNrii690KK6tIw7+56cC5w0kRB8tk+vLWnCop+fFudCv+Mf8/nvS+61GdFUbKME6GodAyKEhEREREREREREZFFGzhwILp3765a0EsAU6p1urq6onnz5uo+Nzc3c68ilWBkWy94Otvix50xmH5ziHZbzzvnHfSPT9Uh0JNBUSpbli4Xx8LTcV+v2uZeFSKD9WzkijdX6HAqMsPiWnxfTcxCYAlBUS1XxSPDnQhPx41N3M29GkRVJvPSuilN8MCPFzB+3jmcjszAy8MDTRrOj0jMUl9Lbz1vh5gUnYW2nrdV99dEs9ZHorG/I+7t4VvmcsNae+DrrdE4F52BBrUdK/Qz9lxIhbeLLRr5VexxRKQ9DIoSEVk5Szv7l8jacUwSaQvHJJG2cEwSEVFVSBh09OjR5l4NKoed3fXDElLx5rZO3vhxVyzeGBlstjbdEiZytKtVqG1x0YqiIj5NgqIlH1gn0jsdmY7M7Fy0CXE296oQFZpzy9KtgSvkz7EdZ1MsLigaXkpF0VjVYjkXtmb6bKGqk/8/CS8/cAOD92Qd862jvQ3mT6yv5tlpf4XhVGQ65t1TH/a2tUwcFC299bzMnTk5uWbbLq9sRVF3Jxskpde8iqKZ2TlYdjABUwb4w66c99GA5h6ws4GqKvpI35Jb1Jdmz/kUdK7nwn23pAm1avHkzargq0dEZOVYeptIWzgmibSFY5JIWzgmiYioKpYuXYr7778fvXr1Um3m+/TpgyeeeAKbNm0y96pRATpd4Uo/9/TwxYWYTGw5nWy2dYpJyVYHxks78OnlkncwPT6V1enIsLbzgkFR0uKcWxqZ51oGOWH7GfPNxVVqPV+kOp7M6Tm5QFxqzawuZy0uxmYiIzuXrefJquZb2d6cNiIIC+5vgF/2xOH2r86qsJ8pRCRmq6ClaylVOX2vzZ1ycpQWJafr4ObEiqIFrT+ehIQ0HcZ19C53WQ9nW9zQ2A2rDidWeH+tBEW71HetwpoSGQ+PIVQNg6JEREREREREREREZLEyMzMxceJEvPjii9i2bRuys7NRt25ddfBgzZo1mDRpkrqPtHlQp1cjVzSo7YD5O2PMtk5SUVQOjJdG2izqW88TGRIUDfSwU0E1Iks6kN6zoZvlBkVLqCgq2H7e8tvOi2aBDIqS9QWXxnf1we+TGmLF4QSM++Is0rOqPywanphVatt5rc+dUmE4LSu31IqicrtUHK1pluyLQxN/R7QONmyeHNbaExtOJFXo/XYlPgvhidkMipKGMChaFQyKEhEREREREREREZHF+vzzz7Fjxw4MHDgQa9euxa5du7B8+XJs3rwZ69evV7dLtdGffvrJ3KtK16ooFb1+T3dfLN4bh9RM8xzclYPhtV1LD/V5OV9vPU9kSFCU1URJKyrSIrZnI1ccuZpuUdWT5XMjMT2nWFDUz91es2EnMtyJiHQ42ddCXR8Hc68KUbkq05L7prZeWPZoY6w7noibPz9T7dvC0nq+tLbzwvfa9rAW586UayFQBkWvy9blYumBeFVN1ND3nwRF5X225ZThJ4ZINVHRpZ5LpdeVyLgqPt/SdQyKEhFZucr8YUJE1YdjkkhbOCaJtIVjkoiIKmPZsmVo2bIlPvnkE9SpU6fQfSEhIfj444/RpEkTLFy40GzrSNfZ2hZvF3l3d18kpefgzwPxZm09XxpXRxvY2rCiKBmGQVHS+pxbmp6N3CAF8XadywuEWEo1URHIiqJW6UREBpr4O8HWhvsKyLrm24IGt/TAiscaY+vpZNz06WmkVGP7dGk9H3AtSF8S/dwZo8G5U99WXlrMl6Qmtp7ffCoJMSk6jOvgZfBjpPJoiJc9Vh5OMPgxe86nqhMyQrwZ2idt4DGEqmFQlIjIylW01QERVS+OSSJt4Zgk0haOSSIiqozo6Gh0794dNjYl7+62s7NDjx49cPnyZZOvGxWXnV38wHMjP0fVgt5c7efLaz0vB6KkqigrilJ5ktN1OBudidbBDIqSdufc0kjrWl9XW2w/YzlB0fBrQdGiFUW9XWwhGQIGRS377//j4eloFuBokvUhMuV8W1T/5h74+4nGqnLj0NmnkVhN25wRSVnFgvUF6beHtTh36quFsqLodUv2xaOerwM6VaDSp/xdI1VFV1UkKHohBV3qs5ooaUdubs0a68bGoCgRERERERERERERWSypFnr48OEylzl9+jTq169vsnWiipP282uOJuZXhzN56/kygqLCy8UOcSnaO2hO2iJtuwUripIlkvCIVBXdftbwdrTmdrWUoKhUoPRxsdVk2InyAr5Nph3Br//Gltt6vlmAk8nWi6hMO78HXgmttqe/sYk71k5poiqTD/7kFOJTs6tl7AW4l77Na29bCx5ONqravmaDok6lVBR1slXt6XNyasZJ6PJ7/nEgHmPbe1W4uuKwVh6qYvO56AyDQv3/XkhFl3quVVhbItISBkWJiKwcS28TaQvHJJG2cEwSaQvHJBERVcZzzz2H/fv346233kJSUlKx+7/++mvs3LkTTz31lFnWjwxry3lbZ291cHrB7rJDI9UhxpCgKCuKkgEk3CGbtC1ZUZQstBWyBEWl9bzOQoI2EhR1tKulKogWJfM6g6LaI6GjyQsu4kxUBmasCi+1smhSug5h8VloFsigKGlEVhrg7GX01vMFdW/ohvVPNcGpyHQ0fPkwHllwUc3JxujAI8HCqORsBHiUXlFUy3OnVG0vr6KoSM2sGZUGd5xNUZ+B4zp6V/ixA1t4wM4GBlUVPR2ZgfhUHSuKkqbwGELVlL3ng4iIiIiIiIiIiIhIw5YsWaKqhf7888/4448/0KxZMwQEBCA9PR1HjhxBVFQUXFxcMGvWLHUpeHDh999/N+u6U+GKnTe381Lt558ZFGCynysHk9OyclW75bLXz1YdJCUqy+EraWjs5wgXB9ZpIcvUs6ErktJzcCQsDW1DtR8KkZCMtFEuKTCg1bBTTbfo3zgsPRCPR/r44fNNUdhyKhm9m7oXW+5kRF6FZlYUJc24cXLepZp1queKvS+1wJdbovHjzhjM3RSFZgGOuLeHL/7XzRd1fBwq9bxSJVSXAwR4lB0R8tXo3GlI6/mCy1m7JfviEOhhhx4NK17p08PZFjc0dsOqw4l4pK9/mcvuuZCqvnZmRVEiq8GgKBGRlZOzzHhWBZF2cEwSaQvHJJG2cEwSEVFl/PXXX/nfp6SkYN++fcWWkduPHTtW6DZ+5piHTqeDjU3JB3jv6eGLmz49jf8upaJdHReTVRMV5beeZ0VRMqyiKNvOk6XMuSXpXN9VVRnbfibFcoKipVTHk3k9KimvNT1pQ2RiFh775SJu7eSNT8fXwYYTSZizMbLEoKi0RRasKEqakRQFfDYEGPcx0KRPlefbstSv7YiZY0Lw1s3B2HgiCT/siMH0FVfx8p9hGNjcHT9MbIAgz7IrgxYVnpi3zVvanFlw7oxJ0d42b3KGvqJoKa3nr92uX87a95/+fiAeYzp4w8amcn/TDmvtiTeWX0V6Vg6c7Et/3+45n4KGtR1UgJhIK4xRZbkm42gmIiIiIiIiIiIiIot1/Phxc68CGcnglh7wd7dTVUU/NFFQVF8xyZDW85diM02yTmS5DoWlqSp5RJZKquG2r+OC7WeTMckC3svhiVmlhqX83O1x8HJeJTTShscWXlIn6nx6Rx319bG+fnjy10u4HJeJUO/CVRJPhKeranmezlVv501kFKveAC7vB5w9TfYjbW1qqTbhcvn8zrr4bW8cpvx6CZ//E4npN4dU6LkiEvOC8+W1nvd1tcP5GO1t8+orhbqWUlHU3anmVBTdeyEVF2IyMa6DV6WfY2RbTzz/+xUs3huHu7v7lhkU7VKf1USJrAl7XxARWTlWxyDSFo5JIm3hmCTSFo5JIiIi62dnV3og0962Fu7s6oOfd8ciMzvHpEFROSheFm8XO1YUpXIDGFFJ2awoShYz55bmxsZuWLIvHs8vuawCfFqvKFpaUJSt57VFAm4SSJKQqP+1oJpUEpdw8heboootfyIindVESVvqdgZunwuEtjfafFsR7k62mNirtqoiuWR/fIUffz0oamdARVHtzZ0SAHW2r6XCs2VVFE1Kt/7tdfn/93W1RZ8SqjEbqkWQM25q44kZK69Cl1NydcZsXS72XUxlUJQ0p1YtRh2rgq8eEZGVY+ltIm3hmCTSFo5JIm3hmCQq3YIFC/Dmm28WqqA4ceJE9OvXD/fccw+OHj1a7DEffvghvv7661JbdY8ePbrQbd9++y1GjRqFQYMG4ZlnnkFkZGT+fd27d0eHDh3yLzNmzFC3jxgxotDtrVu3xpAhQ9R9WVlZmDZtmnpsjx49MHPmTOTk5AW/Cj5GLi1btsR9992X37LvvffeU4/r1q2b+ln6xxV1+PBhjBs3Tj3HmDFjcPDgQXX7rl270Lx580I/4+6778a5c+cq/NqTZZD3zaZNm/KvZ2ZmqjEwfvx4PPvsszh58qRZ148K/1+V5cEbaquw3acbi4dGqoP+QLhBredTrf/AM1Wt7bxoHcygKFnOnFuSV28KUpVxv9gchQYvHcKd886qimJaxKCoZZD/h0d+uYgx7b1wW2fvQsG3CT188dXWaGRkFd7ePx6ejmYBDIqShnSfALQfC0SfM9p8Wxm3dPTCsavpOBqWt91hqIjEbFWN07WU1u1anzuT03Vwcyp93d0ca0ZFUdl3umRfHG5u7wU726qdcD9tRBBORGSoIH9Jjl5NQ1pWLrrUM02nByJD8RhC1TAoSkREREREREREpFFysGn+/Pn49NNP829LSUlRQc5bb70VGzZswNixY/Hyyy/n35+RkYGPP/4YixcvLvE5w8PDMWfOnEK3rV69Wl2+/PJLrFixAoGBgXjrrbfUfREREcjOzsb+/fvzL/qfJ8vqb9u8ebN63AsvvJAfbg0LC1PrKMtt3boVf/75p7qv4HMtX74cPj4+ePrpp/MDq3v27MHKlSuxatUq7Ny5E0uXLi32eyQnJ2PSpEkqALpv3z7ccccdmDJlSv79wcHB+T9Dnq9jx454/vnnq/T/QdoUHR2NkSNHqvdDTEyMuk3ev/Pmzct/j0lg9MyZM+ZeVTLgoE7LYGdM7uOH15eHITwhr/JRdZID4Y52tUptY1mw9bxUFOVBKesnwYuigSVDg6JO9rXQ2N+xWtaLqDIqM2d5udjh/VtCcfndtvjw1jrYeS4FXWcex43vn8Dv++JKrTxmalLpLCo5u8ygaGJ6jskqVFPpnlh4Ub1vpHV20U4ij/b1VyeI/FogqJSTk4uTUlGUQVHSkshTwHd3AAsfLvFuU20jDmrhodqs/7av5HBfacITsxBYTtt5fZX92JRsNQ61RAKg+jBoSfQhUmsPih4OS8epyAyM63A9dF9ZXRu4YkhLD0xfebXE/+8951MhBVw71mVQlLRGW/OTpWFQlIiIiIiIiIiISKOkiuh///2Hm2++Of+2LVu2oH79+hg+fLg60CpVQAtW63zyySeRlJSEvn37lnjwSip03nTTTYVuT0xMVJVJg4KC4ODgoKpzSrVOffXSZs2albuu77//vqoCKlVOxYULF1TQVb9eNjY2cHQsHp559dVXcdddd6lqpEICrlOnTlXhUblIeLVXr17FHicB1IYNG6rKqPI6SHB29uzZJVYflTaAQ4cOVb8LWZ/PPvsMZ8+exZ133qneY/J+/uOPP1RY+J9//sFPP/2k3heyHJlf0YBISd4cFQwH21p48Y8rJgmK+rrZlbteUlE0MzsX6Vk8KGXN/j6cgFZvHEXDVw7jgzXhSEzTVSgo2jLIudSWqERanXNLI9Uen+jvj1PTW+P3SQ3VbeO+PIvnf6/+udnQNsqSyyorKCpiUlgN2pz+PBCPX/bE4ZPb6iCwhP8raS8/uKUH5my83s3gcnyWqmLH1vOkKXMGAs5ewC2fGH2+rQhHexuMbOuF3/bFV3jOLK/tvH7u1OUACRXYBjKF5Axdfnv5krg6XKsoauWt56WaqIeTDQY0r3zb+aJVxI+EpWPpgeLvpz0XUtAiyKnMSq5E5sG/t6qCQVEiIitnqj9MiMgwHJNE2sIxSaQtHJNExT3++OOqfbYEJvVOnTqlAnAvvfQSBg8ejMmTJ6twpwQx9ZUUJXzp4lK86sOSJUvg6+uLG264odDtErKUNvJ627dvR6NGjdT3Eq6U4J0EUiWw+eKLL6pqngVJpUapGqqvCqp/zhMnTqBLly6q9byEOiXcWpBUGZWA3/33359fLVUCpufPn1ct7Hv37o3ffvsN/v7+xX6XY8eOITQ0FE888YRqUf+///1PhQT1r0NB0oZcgoPyfGR9pOW8BKOnTZsGNzc3dT0rK0tV25Uqt507d8awYcOwa9cuc68qAbC1Lf9Ao4+rHWaMDsH3O2Kw61z57Y4lBP/dtmgcvJxa4fWJSc4ut+28vsKeiEvVXitOMg4JhT700wX0aeqGoa088NLSMNR98RBe+uOKCleU53BYGtqEsO08Wd6cW+5z2NTCmA7e2PJcM7w8LBCf/xOpibbEUh1PBJYSfNLP7VpY15pKqhJO+vkCRrb1xF3drv89U9Tj/fxU5brd1z7zT4Snq6/NAlihmTTkgSXA2I+AwBbVNt9WpP28nKAilXcr0no+wN2AiqIanTvLqygqbdilsru1VxSVoKgEhSUwbAw9G7mhfzN3VVW0aFVcmZe71HM1ys8hMiYeQ6gaBkWJiKwc22ERaQvHJJG2cEwSaQvHJFFxtWvXLnabhDalTbwE3yScKaFPqcAp7eFLe4y4cuUKFi5cWCjMWRJpIf/dd9/hsccey6/G2b59e3z//fdYtmyZau2tb0uvJ/fdcssthQKtEs6UduDSOn79+vUqTPrzzz8Xepy0mZ84caIKugqphCrWrl2LRYsWqfb18jtKyLOk10HWRyqKSpVVqWT66KOPqoCgkLb3EhCUi6y/PJeEV8n6REVFFap6K+9hOXBw44035t8mAemiAWcyD/1cVZ4HbqiNDnWc8fjCi+W2vnxj+VXcN/8COs04hjeXhyFLZ/g2RXRKtmqxWR5pPS/iU627SlFN9vzvlxGbqsP399bHN/fUx7kZrdX7UKrc1XvxkAo7nYnKKPGx8h6VakwMipKlzrmGenKAv2r2KWFRc7uakLfNV15F0aik8oPeZHzZulzcP/8C0rNz8cVdxVvOFzSstSca1nbIryp6IiId9ra1UN+XQVHSkHqdgdwcYPk0IC2x2ufbsgxt5QlXRxsVGjRURFJWiVV9S6/GbFlBUSEVR6XyqLWSYLC0nh/X0cuozytVRQ9cSsPygwn5t6Vn5aiT8LrUZ9t50p5cmYup0hgUJSIiIiIiIiIisiD29vZo27atCsHJ91JJMy4uTlXhLI203ZZwp1Tf9PDwKHW5pUuX4o033lDt6du1a6duk2qf06dPz28FL88hbd8LBkJXrlypgqIFSeVRaXHv6empKn9OmjRJVQfVi4yMxJ49e3DzzTcX+t3EQw89BC8vL/W4O+64Axs3bizxdejYsSP69++vgqYPPPCACrFKhVIhVVf//fdfdTl8+DA++eQTPPnkkzh48KCBrzRZCj8/P/V+0r/XpVKtvO/atGmTv4xUt5XqomQ5pILdnDvqqko2Ulm0NJ9ujFRB0emjgvHisCC8ueIqus08pqosGSLa4Iqi14KiGmvDScbxz4kkfLE5Gu+OCUH92nnBpBBvB3xwSyguzmyDV0cE4Y/98Wj26mE8MP88LsZmFnr82egMpGbmMChKVs/P3R739ZQAdRTSMnPMHhSV7KF/KRXyWFHUfCQ8LxWalx2Mx/wJ9RHslXdSWFmf+Y/09ceif+NUBWepKNrE31FVCCTShKx0YNV04Ow2YMe3QLJ5w/LODjYY0dqzQu3nwxOyEOBe/javr6utJufO8lrPCwmSWnNFUQkGuzjYYEgrT6M+b5+m7rixsZv6O0p/Ev9/l9OQnQN0qc+KokTWhkFRKkYOLCxevNjcq0FERsLS20TawjFJpC0ck0TawjFJZJi6desWqowoO/L1l9JIiO7o0aN48803MXDgQDz77LOIiIhQ34eHh6tlvvnmG3z55ZeYPXs2evbsmf/YH374AYcOHSoUDNVXABX79u1TVUybNGlS6GfK8+qre+ork8pFT6qAdu3aVQX69CSIKkFWfWVRodPpSvzd6tevX2g5WUZCgiUtK+3oBwwYgIYNG6oKp2RdJBD6999/q6Dz22+/rfZvyntbPldSUlLUe1veb7169TL3qtK18WioXo3dcFdXH7zwxxXEl9Dy/ZfdsXhi0SU8PdAfLw8PxJujgrHrhebI1OWq6qIzVl5VFc2M0nqeFUWtVkqGDvfPP68OkE/u41fsfm9XO7w0PAjn326DD8aF4q+DCWgy7TCmLLqU35JeH0xuHexk8vUnMtaca6inBwWoluJlhfhNFRT1d7crNUzo4WSjqlJqLexk7WRb/OnFl9X744cJ9TGynWGV7+7r6av+v77eEq0qijYL4HxKGpKeCGz+DHDzB2ZcAfwam2S+LYtUldx3MRVnS6l2XjS8HZWcjQAPA1rPX6u0H5OirW3e5PQcuDnZ1PCgaDyGt/ZQYVFjmzYiCP9eSMXqI3nVcvecT1FzclueBEUaxGMIVcOgKBXz3nvv4a+//jL3ahARERERERERUQmkxfqFCxdUVU8JUc6fP18FNRs3Ln6wSk8qKW7atAnr1q1Tlw8++AABAQHqe7lPWtn/+uuvKijaqlWrQo+9dOkS3n33XcTHxyM2NlZV5ixYBVQqdEpr96Kk4qksK2FOaQ3+9ddfY8iQIYUep69aWnBn76hRo1RL+oSEBFy5cgULFy7E4MGDiz2/PNe5c+fUusvr8NVXX8Hf379QC/KCdu3ahVOnThX7mWT5nnnmGVWBVqrY/vTTT+r7yZMnq/vkvf7++++jTp06qqotWd5BnffGhahKjVI1tKDVRxJwz3fncHc3H7w/LjT/eTvVc8Xel1rgucEBePWvMHR/5zgOl1FdVAJE+spJZWFFUes17c8whCVk4Zt76sHGplaZ1bumDAzA2bdaqwqjEoJq+PJhvLz0CracSoaPq22pLbCJrOlAeiM/R4zr6I0P10ZAl1N2GL+6g6JljTn53eVEAAZFTUs+rz/ZEInPxtfFXd18DX6chPL/180HczdH4cjVdDQLZFCUNMTdH5gZDrS8/vesuYNLw1t7wsm+lkHt56WNvC4HCPAo/+QoR3sbuDvZWGhFUettPX8hJgN7L6aqz9/qMLCFO7o3cM2vKipB0Xahzur9QETWhaOaiimr+gQRWR6OaSJt4Zgk0haOSSJt4ZgkMowEPGfNmoUff/wRgwYNUm22JchZlQNTv/zyi6pSeu+996ogqv4inn76aRWyk2Dm0KFD0aBBA9XCXS8sLEy1/i5KWthLcFPWccyYMapK6YQJE8p93PPPP6/CniNGjMC4ceNUKFXCo+KLL75QLeZFUFAQ5s2bpwKinTt3Vu3pP/vss/zXQZ6/Q4cO+ZdXX30Vr7zyCrp161bp14m0W2V3yZIl6v/35ZdfVifBh4SE5AeWpYLub7/9pt6PZH4S7K4IaVc7bXgQ5myMxJGwvMDnzrPJGPvFWQxt5Yl599QvFu6TA5ozRodg5wvNkZaVg85vH8O209crMVem9bxU7pGqOiVVNiXLJe+lWRsiMX1UMJoYWL3OzckWLw8PwtkZrfFEf398vC4CH6+PVG3nWd2GzCI5GkiKMsqcaygJ45+JysDSA4a3PTa28MRsBJZTHY9BUdOS+VCCojPHhJRYobk8j/XzR1h8lro0C3CslnUkqrK5I4C175psvi1re2RYK08s2V/+PByRmDcPljdnFqwqqrW5UyqFSsXQskjFUak8ao3+PpIIWxtgWGvjtp3Xk21YqSq642wKNhxPwp4LqWw7T5rFYwhVU/7eDzI5qbIgVT3Xrl2r2nNJFYfnnntOnQkvO9alskOfPn3yl5cz5c+fP6926EvrL6nUIDtDZee+tPx64okncMMNN6hlf//9d8ydO1edUS9fr169iqZNm6odqJ06dcILL7yAP/74Qy0rO+RPnDihnnv69Ok4cOCAat/VsWNHTJ06tdTqDEREREREREREZFwPPvhgoetSFfO7774r8zESjCyN7AeSNt1633//fanLuri4YObMmaXe//rrr5d4u+zLkmqOpZEKoyWRtvYS+JNLUUUrQsrvIQHBoiQMevz48VJ/NlkfHx8f3HXXXcVu79+/v7qQZZsywB/fbIvGk4suYfbtdTDi09PoWNcFix5qqMKbpZGDm3tfboHBs05h3Jdn8O9LLRDq7ZB/v1QqTcvKNSgoKgdPpaooW89bj4ysHNw3/wK61HPBUwMDKvx4H1c7FYZ6sr8/PloXoaowEZnFspeBS/uAqXtM9iNlfu3b1A3vrQ7H2A5eZglJS0XRlkFlB7wZFDWdb7dFq5bzzw8JwAtDAyv1HBK479PUDZtOJrP1PGnLma3Ab08Cj6wCGvcGAlpAC27p5I27vjmHi7GZqOtzfRu3qPDELPXVkNbz+rkzxgKDou5WXFF07bFEdGvgCk/n8jshVNaw1h7oVNcFLy69guPh6XhuUMW3j4lI+1hRVIPJZ9nxLy29JBAqLb+kddf48eNVgLRLly5Yvnx5/vIZGRlYs2YNxo4dmx8a3bZtm9oJL4HPYcOGqR3o//zzT/5jJBwqLbuk5ZIs4+zsrAKi8rMlMCqPkSoLUo1CXzVCKlXITvfFixfDxsYGjz32mBleHSKqDJ7FTqQtHJNE2sIxSaQtHJNERFQVp0+fVvs877//ftxyyy3qNtkvKqFoOQGetMHOruL1K6RC6Kzb6mD98ST0ePc4QrwcsOzRRqrKZ3mc7G3w28MN4WBbC2PmnkFa5vX3gv4AuFRNMoSXsy1bz1uR6Suu4nRkBr69tz5sy2g5X55AT3u8Ny4UY6upFShRuVqNAFx8gMy8qstVnXMN9dzgQOw+n4otp0qu2Gzu1vOCQVHTWLw3Dg/+eAGTetdWAfqqvq88nGzQMtjZaOtHVGVOHkDdLoCDCzDoeaBtXscLU823pbmpjScc7Grh93Laz0fkB0XtLLiiqAGt551skGSFFUV1ObmqyufA5h7V+nP0VUX3nE+FFGxkRVHSqlq1GHWsClYU1ZidO3eqyp3yVaou6IOa+/btw/z581Ug9M0330RaWpoKeG7YsEGVMZdw54ULF1SIVHZ8tmiRdxbLxIkTVfWEb775Bn379lW3SZVSaf1VcJlHH30UUVFRqv2Sk5MT7O3t81t/Xbx4UbUGk3ZNcvvbb7+Ns2fPqp2rEhotiayTXOT+gjthC17XHwDUlwU217Jy0V+X++Rx+sfa2trml4mvrmW1+roYa1lTvIblLavF18WYy5b3umRnZ6vlquv11urrwjnCMpatiXOEXGT9TPV6m/o9yzmCc4SlzRFym1zXyhxh6mU5R3CO0NprWJAW5gitbUeYelnOETV7jjh27JhqZ3/58mW0bNkS77zzjmrvXZCc1Cz7qbZs2aKeW/ZPSRcaqQgqt8kJyfI3qbSSl/bxYtWqVTh06JBajsiYvvrqK9VpqeB4ELt27VIVc+Vke7lf9m+Secn/UWUOpA9v44nR7b1w8HIqVj/ZBF4uhj+Hv4c9lj7SGDe8dxwP/XQB8yfWV+8R/QFwQyqKClYUtR77L6bindXheO2mYLRiGImsIcB09TCQEgM4hBplzjW08lirYCe8tyYCvZu6V+o59l1MVVXLXB1s4Opoc/2roy18XGzhXUqQX7ZZpUKeIUHRU5HplVo3MszW08mqouEdXXzw2fi6+dtglTWijSdiPmoPuzIqhhOZXEhbYPwXed+nxgGxF4DQ9iabb0vj4WyLwS088Nu+OEwpozq6tJ7Xz62GkLnzUlwmtELmfINaz+srilrZn3zyWRmXqsOgltUbFBWj2nmiXagzTkdloEU5VbuJzEW/75Iqh0FRjTly5Ih6U/fr16/Q7dJSXqqHSssw2QG/fv163HTTTarF/MCBA+Hm5qZ2wIs777yz0GMlGOrhUfhDo1GjRvnfu7u75y9XkqeeekqFQxcsWICuXbvixhtvVD9bDiaURg4O6EMw+q8F7yvrceZYtuD1on/AmGPZiq6/pS3L19u4yxryu+rHK1/Dyi3L96xpl7X211t+dkmfoeacI6p72aqsvyUsa+3vWa0ta+zXUMIxcl9Nfb35nq3+ZTlHVGxZGZPl/a1p6HW+3lVflq9h9S+r1fes7IOS7jNPPPEExowZowJ4U6ZMwe+//15ouffee08tK/up5OvkyZPx7bffqu42H3/8sdqHFRwcjHvvvVcFRWXfk9w/b968Yj+TqCpWr16Njz76SHVJkvft5s2bVThU3HHHHTh58iQ2btyo9m/K+5Es96DO4ocaqoo6UmG0oqRVvVSOHD/vHNrXccEzgwIQk1LBoKizLeJStVVdiSru8JU0jPvyjAqIVrY9MpGmJFwB7v0J8C4cEq3uA+mynSnVHyd8fx5HwtIqHLpOydBh0KyTiE0pOYBvb1sLa55sgr7NiodQ5TGZ2bmsKGpmqZk56v+/S30XfD+hPmyqUJ25IIZESXOSY4CstLx5dtd84K8XgI9SZSI0e3BJ2s/LOAyLz0SwV8nt5yVYH2hg23n93Ln/Uiq0Ii1LToCViqGl738REiSVQCncYFXWHk2Eu5ONaj1f3eSz/eu76+Hg5bQqVdwnql4MilYFg6IaIwfFJPRZdMe7kGoMLi4uGDp0KJYtW4YbbrhBhUNlZ33BjY+ff/4Zrq6FPySKHmiT5yqqtI2Xu+66S/3MTZs2YceOHZg9ezbmzp2rKpfWrl27Sr8vERERERERERFpy969e9VJx4MHD1b7kCQA+sMPP6i23o0bNy60L+mRRx5R+6HkIicWb9u2Td2nr9qor94tfv31V/Wcnp6eZvrNyFp99913quKtvE/lPSvvYb169eqp/aejRo3CH3/8waCoBlSl0pgER6oSHpFqZwcupWLqkstoHeykKvMIX4MritoxKGrhpDXrPd+fRyM/R/w5uZEKohFZvC1zgXpdgKaFi9CIqlZ3LM/4Lt54eekVfLAmAt9NqF+hx36zLQYJaTocf6MVvF1skZKZg5SMHBU+lO+fWXwJ01dcLTEoKqEnUV7wye9aUFS2Sav7taiJ5P/+SnwmVj7emPMpWbdNc4Ad84C3LgMdbwOa9JE/dgsFRc01x4xq6wk7G+CP/fF4tJ9/qa3nDW07r9821lLIPjk9b5u9/Iqi14KiVmbd8ST0bepusnlWWs6z7TxpG7c5qqLip91StWratCmSk5NVhQXZiam/fP3116o6gxg3bpza6a4Panbv3l3d3qRJE/VVWsgXfKyETksKnpam4EZMTEyMqv4g6yNt799//31VxVR+xu7du43++xOR8XHnB5G2cEwSaQvHJJG2cEwSacOFCxfUPiU9CXrWqVMHZ8+eLbTcW2+9hebNm+dfl5OMZd+WvkPNjBkzVHXRadOmISUlBUuWLME999xjwt+EaooTJ05gwIABJZ4cr38P9+7dGxcvXjT5ulFxZVViNoUZo0MwpJUH7ph3DjvPpsDBrla5B50LVhRl63nLlJOTi1f/CsO4L89ieGtPbJ/aDPVrO5p7tYiM4+mtwIXdwI5vTT7nOtjZYMoAf/y8OxZXKtCmOEuXiw/XRmB8Fx80C3SCv4c9GtR2ROsQZ3Rt4Ip+zdzx0rAgbDiRhH/PpxR7/NWEvKCoIRVF07NyVfiUjGvb6WR8siESb90cgqYBbE9MVq77BGDiwrzvPYPy2s4XKdRlrm1cb1c7DGie136+qIysHLy14ip+3RuH5oGGj1OZO6XyvlbaO+vDnwa3nrci8vm17UwyBrao/rbzRJaCxxCqhkFRjZG27i1atFA703fu3Kl2zM+cOVMFPfXt4jt37oygoCBV2VPadumrhUpQVFrWv/baa9iwYQMuXbqkAqZffvmlOqPeUFK1NDIyUj1eKjz8888/eOWVV3Ds2DF128KFC1VViNatW1fb60BExqOVjXgiysMxSaQtHJNE2sIxSaQNaWlpcHIqfBDJ2dlZ3V4aOblYgqQTJ05U1+XE5rVr16p230OGDFEt56VrjYRJ5WTkhx9+WJ2gTGQMclBWwshlSUhIMHtAkfJkZ5u3OpG0UFxwfwP4u9upgIscCDf0QJOXiy3i06zr4HNNkJimw+i5Z/DWyqt4e3QwFj3YAK6OnA/IyjTuA/hcP9HHlHPuQzf6wdm+lppTDfXrv7G4GJuJ5wYHlLrMmA5eaOLviHdXh1cpKCq0VBnPGqRl5uC++efRrb6rCgoTWT3f+kCjG/K+z0oHlk8DLu3TzDautJ/ffCpZVQ7VW30kAa3fPIo3lofh8X7++OS2OgY/n6+rLXQ5UFWftUAf/pQgqCEVRa1p7+Lmk0nIzM7FoBbFq2sT1VS5uTwBqCoYFNUY2VkpO84lhDllyhTVEmnPnj349NNP0aNHj/zlxowZo3Z+yo71gj7++GPVwuvVV1/F8OHDVdVRqd4gyxtq9OjRase/tAuTHfYSNpUw6oQJEzBixAhs375dtWuqSPiUiIiIiIiIiIgsg4REMzIyCt0m+4qkvXxRcjDs5ZdfxurVq/H999/D29u72DLR0dHYunUrRo4cqTrXyEnNEiSVr0TG0KZNG3XifGJiYon3y3tQujXxxHcq2EL+z0caw8PJBr6uhrfhZEVRy3MyIh3d3jmOTSeTsOzRxnhxWBAr0JB1kZPtPuwJNOwFNBtgllXwcLbFpN5++HJzFOJTsw06QfC9NREY2soDbUNdygz2PzsoAEv2x6uxXDQo6ulsC2eHsg91MyhaPV5bFoYLMZn49t566v+JyOrt/w04+Gfe97YOwJ6fgagz0IrR7b0gmzdLD8TjUmwmbvnyDIbOPo063g74b1pLvDcuFG5Ohp8ko587Y1J0llVR1MlWfSzmWNGJ6GuPJSLEy75CFWGJiMpi+B4QMhkfHx9VRbQsjzzyiLoUJdUdXnrpJXUpiQRLi4ZLu3XrptozFdyxunnz5vzrAQEBKhhKRERERERERETWr379+li5cmX+dZ1Op1p2N2jQoNBymZmZePTRRxEfH49FixbB19e3xOf77LPPVAVRqego4Rw/Pz/VGWfbtm3V/rtQzfDQQw/hvvvuU1VrH3/8cRUMFVeuXMGhQ4fUyfUSItVXvCXz0nfIMjc52Pr3E00qFB6S1p4SgpKQE8OG2rfrXAqGfHJKVRzc/WIL1d6ayOrosoDAFkBONhBxEghoapY598kB/vh8UxSeXnwZ395bv8xl1xxNxMHLaZhlQHW7e3r4qlDiB2si8NXd9QoFRcurJioYFK2eufXDtRGYMToELYKczb06RKax71fAzhFoe3Ney/k3zmpqG1fmur5N3THz73A889tleDjZqgr6d3TxrtQ2q/5EKpk7G/k5QjNB0XLCrvogabbOeoKi644nqbbz/NuD6DqOh6rRxh4ZIiKqNvygJNIWjkkibeGYJNIWjkkibejYsSNiY2NVWFTCoHPnzlWdZRo1alRouenTp6vw3fz580sNiZ4/f161pO/fv7+qNiqVSsPCwnDkyBGEhoaa6DciayedmKRa7YULF/Dkk0+q4LIE+QYOHIinnnoKly9fxvPPP4/evXube1VJY5/3PRq5YWQ7rwpVFM3OAVIz2epO63Q5uXj4pwto7OeInS80Z0iUrJedA3DXN8DxtcA3t5htzg32csDs2+vgu+0xqqJdWd5bHYEu9V3Qt6lbuc/rZG+DKQMC8MPOmPx28yI8MQuBHuXXQ/JlUNSoMrJycN8P59Gxrouq9kpUY9z/K3Dvj5rexv1fNx9cjsvEQzfUxvE3WmF8V59Kr5PWQvbJ6TrDKopeu19nJZvqEYlZ6sQKtp0nImNiRVEiIivHCgdE2sIxSaQtHJNE2sIxSaSd1vMfffQR3n33XXzwwQdo0aIFZs2ape4bMWKEqg7ar18//Pbbb7Czs0PPnj3zH9upUyfMmzcv/7pUcpwyZYr6XpadOnWq6nYTHByMOXPmmOG3I2t16623qiDon3/+qYLISUlJcHFxQbNmzTBq1CjUq1dP3ebuzoNs5iZVirVSVbSivFzyqhhJ+3lXR8Pbd5Lpzd8Rg/8up2H71GaqPTWR1crKANLigD6PA70eNuucO6GnL/78Lx4P/ngBPRq6IsCjeMXPf8+nYMOJJCx+qKHBf/tN6uOHt1ddxax1EXh3XN6JRhIaDTagoqiLg426RCVpI+xk6d5ccRWnIjOw7+UWsLPl3+5Ug/31EhB+FHhoqWa2ce/t4YsxHbyNst2jD9nHaCUoamjr+Wvb59k51lFRdN2xRPVVKooSUeFjCFR5DIoSERERERERERFRIc2bN8d3332nqoAWtGLFivzvjx07Vu7zfPLJJ4Wu33LLLepCZCxSpTYrKwtubm4ICAhQbehLIu/dmTNnYuvWrSZfR7IeUlFUxKfpEFJ4eiQNScnQ4eU/w3BbJ29VNZbIql3aB3zUE3jpEBDSxqyrIsHPr/5XD23ePIoH5l/AX482KhYGfW9NhGpjPKaD4dWcJfQ0qbcfvtgchZeGB6nrEhTtVNfF4Mp4WqmKZ8n2XkjBu6vD8dpNwWgdwpbzVMN8NhTofCfQ7Z686/W6AF7a6pAh862xTo6Ras6ujjaamTtTMnNgb1sLDnZlB0XdnfQVRa0jRLbuWBLahjqXeOIFEVFlWeZpu0REZDBWZCLSFo5JIm3hmCTSFo5JIiIy1L59+zB+/Hi0b98eXbp0wYABA/DHH38UWy4sLEyFR5999lnExMSYZV2pMKkubKn0FUXjUvPaX5I2fbAmAjEp2XhnbIi5V4Wo+gU0Ax7+C7CxBZa/CiRHm3XO9fewx7y762H5oQTM21p4XU5HpmPJvjjVstzWpmJ/+00ZGID07FzM3RSlrktQNMiAiqLCT4KiKaWHndIyc3A0LK1C61PTHAlLw93fnUebEGe8MDTQ3KtDZHoBzQE3v+vX240Bej9iNdu4pYXsZXtKK63ny6smWriiKKyiYuLaY4kY2JwdMYiKqlWLUceq4KtHRGTlWHqbSFs4Jom0hWOSSFs4JomIyBD//fcf7rnnHuzfvx+2trbw8vLClStX8NJLL+GHH37IX+7XX3/FiBEjsHnzZri6uuKVV14x63pTnpwcyz1y6+WSFwCIT9XGQXMqLiw+U1UsfKKfPxrUdjT36hBVP1cfoM1IQJcF7PwWSIow+5w7sp0XHrihNp5afBlnojLyb/9oXaQKHkl75IqSUOi93X0xa32EaoWclJ5jcFC0vIqi7/wdji4zjyPTGpJFRiav26MLLqLtm0eRpcvFT/c1UFX9iGqcW2YBrYZdv56ZCpzflffVCrZxS+Lrqp1qzNJ63rCgqPVUFD0eno4r8VkYxLbzRCWw/DFuTgyKEhEREREREREREZHF+Prrr5GdnY1HH31UhUV37NiB3377DaGhofjss8+QmZmJ6dOn47XXXkNaWhoGDx6sWs/fdddd5l51svCD6Pmt51lRVLOm/RUGZ/taeHk4K95RDXHlILD1KyCkLfDWZSColSbm3I9uDUWAux3u/vYcsnW5iEzMwnfbo/FEf384O1Tu8PSzgwMQmZSN91aHq+uBHsYJiv66Nw6pmTn47zKriupJaPbjdRFo/Mph/Lw7Fu+PC8WR11qiVTBbzlMNpMsG4i4B2ZnXb4s4AXzQHQg7bBXbuJqvKJqhg5tT3nZ4WVyvBUWzrSAouvZYEhzsauHGJm7mXhUizWGxiaphUJSIiIiIiIiIiIiILMbBgwdVy/nHH38c9vZ5IZHWrVuriqGJiYmYNm0afv75Z/j6+uLTTz/F7NmzERAQYO7Vpmtq1bLcSmRO9rXUAdv4NO0GRSUMNfLT04hKykJN89+lVHy3PQav3RScX/2VyOqd3gz8+bzm5lx3J1vMn9gAu86lqGDnnI2Rqt385D4FWjdXUNMAJ4zr4IVZGyLVdWNUFJWW81K1Tew+l4KaToIXy/6LR+s3juLZ3y7jzq4+ODW9FZ4eFAAHO8YKqIaKvwxMqwuc2nT9tsAWwAv780L6VrCNWxJfV1uLqygq85Rsq+usILO77lgiejZ0hatj+QFZoprHuuZbU+MWHRGRlbOx4VRPpCUck0TawjFJpC0ck0REZIj4+Hi0a9eu2O0dO3ZUX//66y906dIFf/75JwYOHGiGNaSy2NlZboBPAgBSVVTLFUXXHk3E8kMJWHYwATUt3PTsksto4u+ISVUIohFZnD6PAe/F5n3/6RBg/UeamXN7NXbD80MC8dqyMMzeEImHbqgNH9eqrY88X2Z2rtGCor/ti4O7kw3ahDhj93kGRScvuIhRn59BPV8H/DetJT6/sy783A17nYmslrs/8MgqoE7e3xqKvRMQ2j7vqxVs41amGrPpg6KGBSYlUGrpFUWzdLn452QS284TlcLGyoL5psYjMEREVs7aWh0QWTqOSSJt4Zgk0haOSSIiMoS0lnd3dy92u/62wMBA1Z5eKoqS9mRlWXalS28XW01XFNUHnaQKUU2y6nAi1h1LwntjQ2FvywOHVMPoD5Y36QP4N9XUnPv6yCC0DnFWrd2nDKx6de/O9V3Rv5k7HO1qwcvFtkJhp5wSgkNL9sfjpjae6N3ETVU/rcmWH4zHl5uj8dn4OljzZBP1/0ZEUqbSBWg5FHAr8rfFP7OBfxdqZr6tltbzmgmK6gyqKCokUKqz8KCofB4lpedgUEsGRYlKkpPLYwhVwaAoEREREREREREREVmNoUOHwsnpenUfImOSlubxqcY7aJ6WmYPP/4k02gFtfdBp3fGkEkNR1ihbl1dNtE9TN4xq52nu1SEyrdVvA0ueyvt+yEtAm5ugJdIGeMVjjbH6ySao6+NglOecfUcdfHRrqMFtniXsJG2IE4qE/E9FpOPg5TTc0tEbXeu74kREhlHnd0siv/fDP1/E8NYemNzHz+paaBNVSeQp4J85QGZa4dvP7QDCDsFa+brmheylaru5Jacb1nr+ekVRWDQ54UtOTutY18Xcq0JEVohBUSIiIiIiIiIiIiKyGq6uruZeBSqDjY1lH5ZQreeNWFH0i81RePSXS9h+JtkobSr3XUxVYcmopGwculIk0GCl5m2NxrGr6fjwFsODY0RWw8kTcPHJ+z45Brh6VHNzbrCXA/o3N15VtFbBznikr7/By/u557WDLtpCWaqJujjYYGhrT3RrkLftsOd8KmqiZ367jOR0Hb78Xz3Oo0RFXfkP+HMqULSC3cRfgFEzNDXfGlOTACcVuNytgXkxr6Ko4a3nLb2i6Npjiejf3B22NpyPiUrCbZWqsa5PKyIiKoYflETawjFJpC0ck0TawjFJRERk/Sz9815aHcen6oxWCXPW+kj1vTFCnQcvpyIjOxdPDQiAs30tVVXU2p2LzsBry8Jwd3cfdKrHkDjVQH0eBYZNy/v+n0+AzwZb1ZxrDFJRtMSg6L44DGvtocKiTfwd4elsi93na177+TVHE/Htthh8eGsdhHobp+orkVXpcAvwcRrgWPZ2hrXNtwOau6NBbQd8ujFvW7WqMrJysP5YYqUem5xRkYqitsi24KCoVL+WDgGDWrDtPBFVj7wtYyIislrSEsDa/jghsmQck0TawjFJpC0ck0REZKjdu3fj008/rdB98hnz6KOPmmDtqCw6nc6iKy5JUPRUZIZRnuu3fXG4GJsJH1dbowRFpeKTnQ3QvaErbmzijrVHE/HMoABYq22nkzF67hl4ONngnTEh5l4dIvNIiQUcXAF7R6DnA0D7cVY151ZXUPRCTAb+vZCaP0fa2NRC1/ouKpxTkySl6/DgjxdUIOz+Xr7mXh2qCS7sAT7sCTy2FmjaFxZt/2/Ar48Bb10GbO2sbr6VapaP9PHDy3+G4YNbQhHgYV+l5/thRwwe/vkizrzVGg39HCseFHUysKKokw3ijVf83+T+OZEEXQ4YFCUq5xgCVR6DokRERERERERERERkUSQMKpeK3MegKBmt9Xxq4ap0lT249eHaCBXOCfSwx0EjBEUl4NQu1AVO9jYY2NxdVdqU6k2O9tYTWtD7aWcM7v/xAro3cMXvkxrB91oQjKjG+agn0OomYOwHgE/dvAsV4uNaPCi6ZF88HO1qYUQbz/zbutZ3xbxt0WY5gTEtMwdDZ5/CJ7fXQfs6Lib7uc//fgUxKdnYdHdTnrRJppGVDuRkA0dXWU5QdPPnwLntwL0/Fb7dvxnQ53FAl6WCotbovl618epfYfh6SzReGRFUpefadCpZfd14IqkSQVFpPW/Y9qy7oy1iVEVRy5zT1h1LVJVcK/oaEREZyjo/sYiIKB//uCfSFo5JIm3hmCTSFo5JIiIyxMyZM829ClQFtraGVQPSKi8XO8SnVb1M0ZZTyaqa3crHG+Pg5TT8dTC+yuEkCYr2b+auvh/U0gNTf7+CHWdT0PfabdYgJycX0/4Kw9urwjGxpy++uKsuHKSMKlFNdcscwCMw7/ukSGDTHKDng/mBUUufc43B3raWqgZdKCi6Pw6DW3rAvUCFum4NXDFjVbiq9FzP17QBnS2nk7H5VDL+PBBvsqCoVK2buykKn95RB/VrM5BEJtL4RuDDJMDRDRbDxRvwLKFyeUibvMs11jjfStD+rm6++GJzFJ4fGqjm08qQbdxNJ5Pyg6L331C7+lrPO9lcaz1vWfsY5TVacSgBi/fF4eZ2XuZeHSJN4zGEqmFQlIjIyrF9J5G2cEwSaQvHJJG2cEwSEZEhxowZY+5VoBrcJi6voqiuytstH66LQMsgJwxt5QF5SZLSc3AhJrPSYZ2ENB2Oh6fjhaF5gbG2Ic6q3fLaY4lWExRNzczBPd+dw+/74/Hu2BA8NziA245ELQYVrtS383ug5fD8oKilz7nGIvNh1LWg6JW4TGw/k4IfJtQvtEzXBq7q6+7zqSYPiq4/lqi+7jyXYpKfl5Khw/3zz+PGxm6Y3MfPJD+TSMnOBBzyxprF6Dw+71KUzK8XdueFSL1DrXa+fayvH+ZtjcbSA/G4tZN3pZ7jXHQmrsRnqW3fjSeTKrQdnZmdg8zsXLg5Gth63tH2WlDUMshr8feRRNUJYM/5VDUvTx1y7QQQIqJqwNMsiYiIiIiIiIiIiIjIJHJycmDJpCqdHHuWykaVdSI8HX/9l4BnBuUFHduGOqvbD1Wh/fye8yn5FfGEjU0t1dZe2ldag7D4TPR+/wRWHU5UreblADpDolTj6bKBrV8C0Wfzrks49K1LQMMeVjPnGkttV7v8iqJ/HIiHFCIe2fZ623kR4GGPer4Oqjqzqa0/ngSbWnmVoaVycnV75c8whCVk4Zt76qnPCyKTmX838LgNMHcELEZKLJBRyrwwZyCwb5FVz7ft6rio8OKnGyMr/RybTyVBNtteGR6EsPgsnIrMMPixKde2uQ2uKOpoA12OZQRE1xxNRM93T2D4nNOqWuvaKU2w6dmmaMS280RlstZgvqkwKEpERERERERERERERGQAb5e8akbS+nzn2WRk6yp+kOrj9REI8LDDXV191PUQL3sVQD1YhaDo7nMp8HS2RVP/6weWB7XwUO3t41Kut1u2RFFJWbjx/ROISMrC1ueaYXR7tuMkUjKSgEWPAJcPmHtNLKKiqD4oumRfHAY094C3a/HGm13ru6r51JRiU7Kx71Iqbu/sjbhUXYUCVJWx40wyPtkQiRk3h6BJgFO1/iyiYno9DPR/BnDyBHRZsAhfjwV+eaj47ZJ8fG4P0KuE+6zM4/39sflUMg5eTq3U4+WxbUKcVUBfgvobjue1oTeE/uQsNydDK4rqW89r15GwNPT+4CSGfHIKsqZ/P9FYbeMObOHBE6GIqNoxKEpEZOVsbDjVE2kJxySRtnBMEmkLxyQREZH1s7e3hyXrUt8Vt3T0wuf/RKLHuydQ+5n/MO6LM/hiUxTORmUYFHr8YUcMHuvrD0f7vG0fVVU0xLlKFUV3nU9Bl/ouhSrDDWzhrqqf/nPS8IPxWpOelYPRc8+okMCWZ5uhQ10Xc68SkXa4eAOzs4G2o6/f9s2twPJpVjPnGoufe15QNDIxSwWWxnUsOXAuVZn3Xkyt1EkAlfXPCWnDDLw4LEjlznacTa62nyW/16QFF9GprgueHOBfbT+HqFTN+gNjPwAmLgBsLWR+GjkD6PdUyfcFNgec3K1+vpWTdOTEpk83RlXq8TLv9m7spsKesi298URFgqK6ClYUtYUuJ1cFMLXqwR8vIDwxCysea4wdzzfDkFaeDIgSVYBNLR5DqAq+ekREVs5aWx0QWSqOSSJt4Zgk0haOSSIiIuuXlWUh1aNK4eNqh8UPN0LMR+2xfWozPD3QHxGJWXhs4UU0euUwur9zHOejSw+Mzt0UBTkMPLmPX6HbpcpSZSuKSus9aVfcrX5e23m9er6OaOzviLXHLDMoKr/XfT+cx76Lqfjr0caoX5ttOImKkWBJwRPuGt0IhLSzmjnX2BVFlx6IV9dLq0zctb4LUjNzVLU3U7adlzbD8jnQMsgJO6uxouln/0SqkxLm3lkXtmw5T+bw7y9A7AUgIxlIS4RFaNQLqNe55Pv+WwqsfMPq51tpiz6ptx9+2hWjqiBXxJW4TJyJykDvpnmB2n7N3LHxpATkcytWUbQCreflqbXamVo6Euw4m4KPbgnF8DYMiBJVRk4ujyFUBYOiREREREREREREREREFWBnWws9Grnh1ZuCsXVqcxUcXfJwQ0QmZaHT28ew+khCscekZebg03+iMLFnbfi6FW55LBVFT0akqwqaFXUpLgsRidno2qBwUFTffn7dMQsJYhTx+rKr+GVPHH6c2EBV+SOiIi7/B3w+DIgPu35b3yeADreYc600HRRdsj8efZq6w8+95Mp/Heu6wNYGKnxvKuuPJ2JA87wAVfcGrth5tnp+9tWELEz7KwwP31gbnYucWEBkEhkpwPd3Ame2Aa+EAlvnGv7YszuA9CTzpP+2fQ1cOVTyfRJ6vbQPNcGDN9aGFFv+bntMhR635XReleQbG7upr/2buSMqKRtHwtIrGBQ1sPX8tRb1ORpNin68LhJN/B0xoo2nuVeFiGooBkWJiIiIiIiIiIiIiMgkbApWvrMins62GNvRG/++1AJd67ti2JzTeGvFVeRI7/drpAqTBJWeGli83a9UktPlAMeuGnbQvCB9oEl+blEDm7vjVGQGLsSUXuVUi37cGYM3V1zFzDEhuKWTt7lXh0i77F0AO4fr11NigcsHrH7OrUxQNC5Vhw3HEzGuQ8nVRIWroy1aBztj93nTBEUvx2XiREQGBrbwUNe7N3RTFT+T0/NaLRvTs79dhqOdDWaMDjH6cxMZxNEV+DAZaD8WuOcnoP04wx6XHA181BN41gM4tgYm98czwJktJd/X70ng4T9rxHwb4GGP2zp5q8rE0tq9Im3nmwY4ItAzL6Dfs5EbHOxqGdx+Xj8fVqSiqJDtaq2RrgO/7YvDlAH+sGFVZ6JKYyXeqrHuTysiIuIHJZHGcEwSaQvHJJG2cEwSERFZP2v/vJfW9Msfa4xpw4NU5bbRc88gPjVbBUY/WheJm9t5obG/U7HHtQ5xVl8lIFRRu8+loK6PQ/4B+IKkvacch15nQe3nN59Mwv3zL+C+Xr54fkiAuVeHSLtC2wEPLgHcal+/bfd84MOe+VX3rH3OrUhQVEg1vDFlBEWFVDA2VUVRaTuvn6v1FUUlf/XvhVSj/hwJZC3YHYv3xoaozykis4ZF7Z2ANjcBfo0Ne4yzF/Dif0CP+wEPM2wXfJAI3Di53MVqwnz7WD9/nIvOxKrDxSvnl2bzqST0bpI3xwlnBxs11xkcFNVXFL1WKdTQoKgWK4rO2RipTi67t4evuVeFiGowBkWJiKxcrgY3hIlqMo5JIm3hmCTSFo5JIiIi66fTGb9KmtbY2tTCG6OCsezRRqrdZpeZx/Hh2ggcD0/Hs4NKDji4O9miQW0HHKxEUFQCTaW1Zvd2tUPnei5Yd9wy2s+fjkzHmC/O4IbGbph7Z90aEbogqrSs9LxLQR1vB57ZXqPm3IoERXs2dEWwV4EKrCWQ6sxHrqYjqRqqepbUdr59Hef89WsR5AR3JxvsNGJQNTM7B4/+chE9G7kynETmdfIf4NvbgawM4MpBYIuBredt7YCQtsBd84DQ9jCL0rZHos8Bz9cGTm+pEfOtbG92qe+CORujDFpeKulLi/k+TfLazutJOP6fk0mFKu+XJjlDp15+Z3vDtgn1LepNUVE0KikLT/16CTvOJJe7bGKaDvO2RuPh3n6qejURVR6PIVQNg6JERERERERERERERERGdlNbL9WK3sXBBlN/v6IOrktQpzRtQ5wrXFE0W5eLvRdT0bW+S6nLSEtjqVpnyMF4c4pNycaIT0/Dz80OSx5uCAc7HsIiKtPGWcDLRdqIewblBakYsi5EH8Qc19G73GVlrpb8wV4jV/UsKeQgc/OA5nlt5/UnGkhQdefZ8kNHhpq1PhInI9JV+J6tjsmssjOA1HjAzgE4twNY9gqQY0C4ctPxTPIAAQAASURBVOcPwKbP8r4/uRHYtxgmE3sRmD0AuHqk5Pulwmn/pwGvUNQUj/X1x5qjiTgRXuREhRJsPZ03l/Vuer2iqD4oGpeqw3+X0wyqKCpVQg09eUjC9tVdUVTm74V7YtHy9aNqjh335VkVGi3Lt9uikZqZg8f6+lXbehERGYJ/ZRMRWTmedU+kLRyTRNrCMUmkLRyTRERE1s/WtmZV0Gnk54gdzzfHi0MD8cntdcrc3mkT4oyDlysWTDoSlqYOOpdWUVQfFI1Kyq5UtVJTennpFbWeKx5voiqhElE52owC7vy68G1picDyaUD4sRo555amsZ8j3h0bgvt61S53WanqKaGk3eert/38iYgMhMVnYUDzwgEqacksFUWNUS3rUmwm3lh+FY/380fb0NJPKCAyiZZDgMdW5wXZez4AvBsN2BgwR4UfAS7vz/t+70Jg57cwnVzAzQ+wcyz5bgcXYMhLQO0GNWa+vb2zN/zc7fDpxshyl918Mgn1fB1Q18eh2DznZF/LoPbzeUFRw1/b6q4oGhafidFzz2D8vHMq8Lr/lRaqcvP98y+UOm/rcnLxyYZI3NHFByHeZVe1JqLy8RhC1TAoSkRk5Vh6m0hbOCaJtIVjkkhbOCaJiIisX038vJeKom+PCSkzzCkkxBOemK3adBpKgky2NkDHuqUHgKTVsrTrXHdMu+3nwxOy8N32GDw7KECFa4nIAEEtgfZjC99mYwPs+gGIvVBj59ySSCXNqUMC4elcfthIqnp2rueCXUZs/16S9ccSIYWTb2xcuCVz94auiEjMxoWYzCr/jKcWX1K/8xsjg6v8XERVJi3n9XOSBEQNDfqMfi+v7bwY9zEweSVMxqcecN9CwK9x6ctcOQhc2l9j5ltHexs80scP32yLRmRi2VU0N59KRu8ibef1z9GrkZthQdF0nQrvG0q/rLErisr/7zdbo1UV0d3nUvD7pIb49aGGaF/HBd/dWx/LDibgs3+iSnzs0gPxOB+TiacGBhh1nYiIKoNBUSIiIiIiIiIiIiIiMomcnGoq72MFpKKoqEj7eQkytQ52hmsZlZbkYHzvJu5Yd6z8g/HmIlWWHOxq4RG24yQynLRgPrGh8G2ObsD0i0DLoeoq59zKkWB/dVcUlbbz3Ru6wc2p8PwttwmpKlqeRxZcRIOXDuHmz09j2p9X8NveONVmXqrXrT6SgCX74vHhLaHwMCAgS1TtvroZ+O6OvO8lxDdnEPDvL2U/RpYrGPiTCp4SME0qOZBndFnpQHpS4XUo6s8XgJWv16j5VqoUSwBf2q6XJjFNh/2XUtU2aEmkGuemU0nI1uUa1HreULI9KW8RY1YUlerMgz85hQd+vIAx7b1w9PVWGNPBO//+ke28VEv5Z3+7XGJ3gI/WRaBPU7cyT+wiomt0WUDY4byTC0pRU4L51YVBUSIiIiL6P3t3AR7F1YUB+CMGIRBIcHd3d3cv2hZvgaKlWClaWqy4FEpb7EeKVChSXItTpBQo7m7BISHK/5yZbnQ3Wd/Zzffy7EN25u7MzWTn7uzMmXNARERERERERI4vjSxlOE0pP3/0RmCCmUpF3UIpse/yKwSHai+I4UVQOOb9+Qi9q6dD6uQsOU9ktD2zgD0zHd0Ll1Q+pw/uPAtVSgwbEhFhfpCCBHLuufQKdWOVnRdpU3ggb/qkOHwt/kDR+y9CsWD/YxTKlAxvQ99hwYEAtJ1/DQW+PAvfz/5RfpZArA/KRQUzETlU7UFAlZ7qzxLJl7EQkDyB9+fNY8BQP+DBhahp57YBIzMBAddgcyd+Bob4qoFLhrRfAHRagsQkTQoPJavo3D8f4dkb/ZnwD119DRkm9WUUFTI+vXobgb9vxX/c+zpYMoq6m1SS2sMtidUyisqxc5O5V3DhwVts7Z8X/+uaE34+cY9Xp7bJivwZkikl6QNDImLc1HXo6hsMYjZRIuPc+QeYWAy4d9rRPXFZDBQlInJxblJqhog0g/skkbZwnyTSFu6TRMb59ttvUb16ddSqVUt5NGjQQJl+4cIFfPTRR8q0zp0749y5c3Fee+zYMVSqVCnGtE2bNqF169aoW7cuvvzyS7x+/Tpy3oEDB9C4cWOUKlUKHTp0wM2bahlT0apVK5QsWVKZJ4++fftGzqtYsWLkdHlMmDBBmR4aGorRo0cr86Uf33zzTWTmlQcPHqBXr14oX7688vt99913BjMHzJkzB1WrVkXp0qXRu3dvPH6sZpT5/fffUahQIWWd0jeZL8sMCAiwcKsTkbV4eno6ugua5eGeBIUzeRudUVRKcZ69F6QENCWkXiFfBIW+w6EEAo8c4fu9j/E27B0G8AI6adl/pdw15ZN1QLff4k7/6WPgl37KjxxzzaMLwJdgfH3+OPUcaQafwsTN983KanXyViCeB4ajTiFfvfMr5vLBkWtRx+T6LD4YAE/3JFjZLRe2fZYPD6aWwIOpxbFjQD6MbZ4ZH5bzx4JOOZSgKSJNKFQfKFA76nnbbyOzHxvkmxGo+wXgly1qWt5qwAc/AintcNyQrwbw0WrAw8twm9RZlIDXxDbeSuBjSNg7zDVQbl3Kzmfw9UC+9En1zi+X0wc+Sd0SLD+vZBRNZtr5Qne3JFbLKDp2030lSHRj37xoUCSVwXbJPN2wunsuXA8IxuBfb0dOn7nzoRL837SY4dcSUTSpsgB9tgCZihhs4paE1xAswa1HROTiElOpAyJnwH2SSFu4TxJpC/dJIuNcvnwZY8eOxZ49e5THtm3b8ObNGwwePBht27bF7t27lSDOkSNHxnidtJk4cWKMi9mnTp3C9OnTleDNLVu2wMfHR1m2uH//PgYOHKgs58SJEyhbtixGjRqlzAsPD8eVK1ewd+9enDx5UnnoAjsfPnyIsLCwyOny0PVl5cqVuHfvntJHCVCVQNT169cr80aMGIGsWbMq06TdunXr8Mcff8T5/Tds2KD0de3atfjrr7/g7++PKVOmRM6Xfso6//nnHxw+fBipUqWKDFQlIseT8YHiLz9/2shA0eM3A5VMTcZkFJXlpkvpgZ3nX0JLgkIiMGvXQ3StlAaZUiWuAAtyIifXAGNyA8/vQlMkANBTTwBOnqpALvXGII655sni54XMqT2VTHCx/e9gAFr+cBXZ/b0wcv09DPjljsnZRXdeeKUESJXPmdxgoOjJ20F4ayALtGQklQyiH5Tzj5GJOYOvJ+oW8sXgehnwY8ccyJNOf4AWkd2FhwFHf4o5joYEAY+vxv86/+xAg+FAUp+Y5ecrd4s5zVbS5ATKvJ9w9rvlXREWFH9wt6vJmMoTPaqmVY7j5Oal2KSsvJSdNxSsLoHu1fKmwG5jAkVNyCgqrJVR9Oj1N5i09QG+bJIJJbIlXDa+cGZvzGyXDT/sC8Dak89w80kwfvv7GQbUTg83NwbtExllwzBg63h1rDfAWhmDEysGihIRERERERERETkRCdDMly9fjGn79+9Hzpw5leyfciGmefPmMbJ1ilmzZqFmzZoxXrdv3z4lk6hk35QMKJ988okSqPny5Uts3bpVmVelShUl469k7tQFfF6/fl0J0JQgzNgks2mBAgX09l0ykkqQqa5fstykSZMqz728vJTsn/K/BIzWqVNHCfaMTX633377DenSpUNQUJCSATV16tR61yfLrlevntInItIGczKvJSbFs3jj7L23ShBQQo7eeIMUSd2UssMJkYvTdQqmxOZ/X2jqb7D08BM8fhWGz+szmyhplJQbzlAA6P4bkCIdNEUyhx5fFXd6pY+Bch2UH7W0vzubCjl9lCAhHdmWU7Y9wMfLbqJ71bT4e2QhfN8+O+bseYSOi68jJMz4Gx93XXiplGP28tB/qb5ibh+Ehr9TMo/qs+3sS9x8EoJe1TX2niQy5PVjYFkn4PbJqGl7vwUml5ady/DrLu4CHl6MOz0iHFj7OXB6A2zq6sGE1yEBr48u4V3QcyQ2nzfIiJdB4fhhX8ysolJ6/diNQNQwUHY+evn5A1dexzt+qqXnTc0oKjejw+KbmbosuYHS2ZNjWMOMRr/uk2pp0apUanRbdhMj1t2DbzJ3dK2cxrLOECUmtQcBeaoBO6fF04jHt5ZgoCgREREREREREZGTkBLqL168UII+GzZsiG7duuHff/9VsoxmzpxZycpZv359JahTAi4lEFMcOnQId+7cUTKORicBmsmSRQUYSXuZJlk/ZZl+fn74+OOPUaFCBXz66aeRAZkSeClt27Vrp5SQ79evn5JJVDdPAk0loFOCTIcPHx5Zzl7Wf/HiRZQrV055Xe7cuZXgVlnWDz/8gLRp00aWqD948CDy588fZxtIIGzy5Mnx008/KWXqJStq9+7d9W6vwMBAbNy4USllT0TaoBuXyHDmT7m4fu1xcIJtJdNd2RzJlfKaxvi4clr8czsIv/2tjUCGsPB3mLL9AdqW8UPe9AkHuxI5xK0TwMRigF/2+EsPO4Kh4KrA58DNY8qPHHPNVz6XD47dfKME7kvG0CG/3cEXv99VMstJgKiMvb1qpMMvPXJjzcnnaPbdVb1Z9WKTLKESGFWnoP6y86J41uRI5pkER/RkNBU/7n+MUtm8Uc5ARlIizUmVCZjxBihYL2pamQ+A3pvif93qXsDBBXGnu7kDAVeBl/dhU8d+AraOi79N7krA4ENwk98xkZHMyp0rpcH0HQ9jZECWY1QJdq+eP2WCgaK6oNL4M4q6mZxRNNzCGyVGb7iHawHBWNo1Jzzcjc8GKucrFnTKoWSNXnn0KXpWTwcfEzOiEiVqWUsC3qmAizsNNjGUqZiMw28HREQujh+URNrCfZJIW7hPEmkL90mihD1//hylS5dG586dlbLsEowpJedlupSgb9SokVLSvWrVqhg6dKhSblSCNmfOnBmnFL2QQE7JHHr+/HkEBwdj4cKFcHd3R0hIiPI6ydzZv39/JfNo9uzZ8fnnnyuvk2DSYsWKKQGrO3fuVDKLDhkyRJnn4eGhZChdsmSJ0scnT55g/PjxyjxZbrNmzXDkyBHs2rULV69exYoVK2L0STKODhs2TMlw2rJlS4PbQoJOJeNotWrVlD7qnDhxQik/L48yZcooGVKbNm1qtb8BEVmGQUvxK57VW/n/jBHl5yWjqDFl53XqFfZF8xKpMPjX28pFeUf79cQzXA8IwRcNjM/SRGR3GQsDPdaqgaIruqmBo1rR6X9A2Q/jTj+zAZhaXslyxzHXfDK+vnobgX/vBqHr0huYuesR5n6QDV83zxzju2ubMn7Y8mleHL72GnVmXkLA67B4l3v42hu8DX2nZHk2REoyl83hgyPX4gaK3n4ago2nXyjBR/wOTU5Fygh7Jo167p8DyFNVTgYZfs2wk0CDEfrn9fgdqNoTNvXB90oQqDHcEun+OKxBRjx6FYbFBwMip+279Ap+yd1RJIGs96WyJUcqb3fsiaf8vATgm1p6XgL5jUjOb5AE88/Y+RDjmmdWysmbyt/HAyu75VKC+fvVZOZnIqNJgPfumUCJlkDfrfE0TJzjrbXw2wERkYtjaRkibeE+SaQt3CeJtIX7JFHC8ubNi7lz5ypBmhJI2aJFCyUL58mTJ1G8eHElaFKmd+zYEc+ePcONGzcwffp0tGnTRinnHpsEU0q5eclEKtlB8+TJA29vb6RIkUJZjq4svZRwl4yiR48eVbKDSoDq7NmzlSymPj4+SpCobp5kOR03bpxSml4eEsS5e/duZX2SXVSCNiWwVPojpeYlGDV6BlDJhiql7SVoVbKiGiJ9kmyogwYNUgJG5fcVEhx6/Phx5XH69GklYFYCa+/ft3G2GSIyigSwk2EZfD2RLqUHTicQKHrveQjuPAtF+ZzGB4qKGW2z4eGrMEze+gCOPu6btO0BGhT2RanszIhHGubtC5R4D/DxV8sfv3TsvhNJvjuFGsg8XKQxMOwfJQMqx1zzlcmeXIlfazz3ClYfe4ZV3XKhb630etvWLuiLvYML4MaTEFSdcgE3nxjOCr3r/EukTeGB4lniDz6qmMtHb0bRhQcCkNzLDe3L+5vxWxE5yJmNwP8+jJkJWWqDS2nhm8cNvy5pCnX8NST4DXDjL9iUu2fCbcYVRMTWCUiM8mVIhvfL+mHytodKFlGx7/JrVMuXAm4JZL2XTJ3V86XA7vgCRc3IKOrurpaslxuvpm57gA2nnuPCg7eR/YvPm+BwdF1yQxmDB9fLAHNVy5cSR4cXQhY/jWUjJ9KyoBfAxtHAvTPqcwPXCt69c/xNj86MgaIuqkCBAvj9998tXs6GDRuUiwRyQaBUqVJo3bo1Vq9ebZU+EhERERERERGRaaTM+po1a2JMkyydknlTV95dF4Cje/z5559YsGCBEvQpAaRCfpbgSslEKmXl165di/Xr1yvZSqXsu2QPlUf0ZUoWUclaJMtct26dkqkzeh8kY5UEly5duhRnzpyJMU8X8PngwQNl+TqSfVQe4sWLF0r/ZDlSVl6CTPX5/vvvlQyp0Zcvy5CA1dikP3JuS9YvwbRERM5AgocSyih69L8SnaZkFBV50iXFkHoZMHnbA1wPSLi8va1s+fclTt8JwvBGzCZKGiYXp9cPB+6cUsscDzoAFG0CTXj1EBiYTA2+ii1FWiBrCbXPZDZfbzUb3ougcGzqlxfvl4s/MFOC3g8OLaAEIpX75gLm/fkIIWFxAxl2XXillFtOKICqUm4f3HoaotwYoBMW/g4LDwagQwV/pEzGvy85kYhQICwkZvZQyXi8by5wx8D3tPPbgSUdgPCo749xbJsIzGusLtsWfvsM+HNOwu3qDMG7fLWQWI1olEkZr3468kQZ9yTDcvV88Zed15Hx8NDV1zFK14vwiHfYce4lngeFI4WJ410Ofy/4JnPHy7fhGLvpPlrMu4pCY87Cu9/fyD/6X/RdeQsHr7zWe8P6sN/vKuPukq45lcykRGRHyVMD018BJVoB4woBe40Yf8lkDBQlgySbw5gxY5ST6XKxQC5CvPfee0qpMMlcQUTOgaVHiLSF+ySRtnCfJNIW7pNECZOARzkvI0GekiHq559/VgIv69evj5s3byqZO6V0+7Jly5RMo5KBdO/evUp5eHlIAKaQn+XG4MuXLysZP6U8/KtXr/Dtt9+iSZMmSuBlgwYNsH//fqWUuwRjSgbRSpUqIWXKlEr2zgkTJiiBn2/evMGUKVOU9pLl8/bt25g8ebIShPr06VPldZL5VEjGU3ku63r8+LESwCqvEwMHDlQylH733XdIntxwdjnpt9zIfOXKFQQFBSnrbtiwod7so3LhZ9OmTUofCxcubLO/CxEZz11S/FC8imXxTjCj6F/X3yBzak+zshQNb5hRyWY35Lc7sBXJmLfx9HO9QVJi0tYHSqYmySJFpFmBz4CTvwLPbkVNex0APL4Ch0uaEui0FMhWKu48CZj6YxRw6wTHXAut7J4bf48shHqFfY1qnzd9Mhz6oiAaF02FfqtvK4FJK/56goj/aiC/DArHsZtvUDeesvM6FXP7RI73OhvPvMC956HoWY2ljMnJSBnhHjFveFSMvQFU6aH/NaFvgbcv48/oWfNTYOhxJYOyTbh7GZdRtHJ3uOWpjMSqaBZvvFcyNb7Z+kC5mSko9J3Rx3gSKBoc9g5Hrqlj3bl7QfhizR1kH34G9WdfRq40Xqhh4vGif3IP5E6bFFXypMDL2SVxd3Ix7BmUH999mF3JZr/h9HNUnXoRuUf+ixFr7+Lf/467d194ibl/PsY3LbMgf4ZkZmwJIrKYXB+QGwmq9gSylzPQhNcQLKHerk+kx8qVK5UMolKaTCd37tx4+PChcrGhX79+Du0fERlHLorxw5JIO7hPEmkL90kibeE+SZSwQoUK4fPPP1du5A0ICEC+fPkwbdo0ZMiQAbNmzVIeMk/O4UiwZkL7VLly5ZRS8JLJUwJMa9eujc8++0yZJ4GVU6dOVW4kvnv3rpJtdNKkSco8KeX+6NEj5dyRBGvWqFEDY8eOVeZJKXgpPS8BoLJfN27cOHKZX3/9tdK/evXqKcGokgm1a9euuHTpEg4ePKgEmpYtWzayf82aNVOW++WXXyrP5WcJVpWg0h49eijrrlWrFkaOHBn5Gik5L5VxdLJly6ZkIM2ZM6dV/xZEZB59mXsobkbR2bsfKaUvfZLqD/KSwKEKJpad15GsTFNaZ0WHRdeVgM46hYwLgDLW41ehaD7vKgJDIpDGxx3vl/VHxwr+StCTfC5JBqf9V15jXe88PPYjbZNyx19diVn28sfmQMoMwCdrHdkzIKkPUKGz/nkS1HRiNZClON5lKWnvnrlc4L6pMvh6KpnoJHvzqPV30XHxDUzZ/hATWmSGxIuGR8CocTdzai9k8/PE4Wtv0LKUnzLth72PUT5nciV7KZFTCQkCPJPFzCiakOLN1Ud8fG2cmbzlVOPaPbqMd09vAgXrIrEa2Sijkk150K+34ZPUDaWyJTf6uNffxx3jN99XbmI6cStQef5hOX90rpgG5XImt+h4UV4r46k8ahZQg/Rnv59NORZdefQpftj3WAlwLZ7VG09eh6FG/hT4tFZ6s9dHRBY48TNwaAHQbwdQa4Cje+OykrzjWRlNkowLkl1BskBIhgY5MS8nwKUUmJCSYfPmzVOyPkhZLcn0IPOTJUsWWXr+k08+Ucp8SdaH1KlTKyf8e/bsaXQfJEBU3h6LFy9GqlSpIqe/fPlSyTKRK1euOK+ReceOHUPBggXjzfxARPYjpQGlbB8RaQP3SSJt4T5JpC3cJ4m0x89PvShNRI6nO/cqAd6+vtYN7LMnyYLs6WlEZqZE7PiNN8qF9r+GFUR5PaXl/7z4CrVnXsIP7bPjk+rmZZWTc//Vpl5UynmeHFUYnu7WC9gcue4uvt39CJs/zYuNp19gxdGnuPs8FLnTeqFDhTRKoOiDl6E482XhBEsvEzlURHjc8u13TwO+mYCUDs7o+PwucGU/ULwF4GU4mJFjruMdvvoaw9fdxd5Lr+GbzA1+Ph64PqGoUYFP7eZfw4MXodj3eQFcexyMvKP/xaJOOfBRlbR26TuR1UyrBGQuCrRfEHP6wQXAX0uAQQfjvibwuVqGOCGnNwAnVgEfrYLVBb8GvHwSDnDdMBLvjq1AknE3kJg1nH0Z2869RP3Cvtj2WT6jXyc3L/164hmaFEuFzhX9lf+9PMw/Pzh41ho8exUIv5TJMX1A63jbBodGKH2WoNGTtwOx5dN8yJ0uqdnrJtsz5e9LTubcNuDMeuD9ecDrJ8DV/UCx5mqG0Wh/+1QpkmHmwLaO7q3T4tUXDZLsDR9//LGS/UCyNvz+++/Inz8/unXrhtOnT2PHjh3o3bs3atasqcyTTAybN29WsjVEJ6XEpFS8zPvwww8xY8YMHD582Oh+dO/eHefOnUP16tWVoNP58+cr65fyYvqCRImIiIiIiIiIiIiIyDKFM3tD4ifP6Ck//zwwDJ3/d10pwdm9qvmBQhKgNOeD7Dh3/y2+3/sY1vLsTRjm7HmEPjXSoVq+lJjcOitufVMMuwflV7I4zd71ELsvvsIXDTIySJS0b3plYPPXMadlKe74IFFx8yiw5EMgJNDRPaEEVMqTQil5vLV/XhTO5I2uldIYnR2vYi4fHL/5BqHh77DgQAB8k7nj/XL+Nu8zkdU1Gg1U/Cju9LR5gLw1Y2ZuFuGhwPD0wIH5CS87iZsa2B8WAquKiACG+KrBrAmpMxhhg48gsRvZWM3wamzZeZ2FnXLg0bTiWNs7j5JB2ZIgUVMl9XRD8xKpsbpHblwcW5RBokSOVLiBGiQqbp8AFrQEnlx3dK9cDkvPa9CBAwdw9uxZ/PHHH0qAqJBgUMkOumjRIty7d08pz9WnTx9lngRtyt2/ffv2xZUrV5A3b15levv27ZVAUSFtJTPov//+q5TnMkbDhg2RMWNGpcy8lP7au3evMl3KdE2cOBFlypSJN9hVHpIJRjLC6ER/rvsSpEtq66i28tA9l3nyOt1r3d3dld/Dlm21ul2s1dYe2zChtlrcLtZsa8x2kfm22t5a3S4cI5yjbWIcI6Inc9fKGGHLts7wPuQYod229tqGMl0rY4S923KM4BihtW0o86P/rvG1TYzHEfZuyzGCY4Sci5KS7Tdu3FCq3UjZ+ezZs8NQdZxWrVop55GyZs2qTNu/f79SEj4sLAxffPEFWrRooUzfsmWLsuyhQ4fqXRaRVkhVJXnfy3s5ODhYyeQp7+U8efLobS+VocaPH499+/Yp+5RUgZL3ube3mult2LBhWLt2LWrVqoUffvghzus3bdqkJAMoX748li9fDlfl4cHLEglJ7uWGvOmT4rSeQNF+q27jRVC4UtbY0kBLKV38SbW0+HLDPXxYzg/pUlqedXDun4+VgKZB9TJETpN+1iqQUnnM/SC7kq2pUu64mVKJNKdKDyCtes0thr9/BY6vdGz5+WItgGkvgaQGgnF+GwC8fgyPLj/Zu2ekhxwXNCiSSnmYomJuHwSFvsOJm2+w+GCAkmlPPiOInE6RxvqnF6itPmKT76VdVgDZDccjRCrWVH1YnfRhJZCjbMJNffzhwUK+yk1Cyz7KiYZFTKt+4O3lpjyIKJF7dkcZT+GVHMhTDZhwD/BVA9CjSyI3CJDZeEZGgy5duqRk7dQFieq+QJQtW1YJIpVAUTnJGJ2cPNS9VhcoKgGd0Uk5IjmhaYqSJUsqD7locOHCBSVYVDKV9ujRQ8lsmiZNGr2vkwsP8tD9HHueIY5qG/257sKII9ua2n9na8vtbd22Cf2ucnFPHsa0TazbkO9ZbbV19e0tn6m6fdIefXDFbai1tq7+ntVaW2tvQ9knZV5i3d58z9q+LccI09rKPsntrZ223Ia2b6vl96ycQxoxYgSGDx+O+vXrK5VmBgwYoFS3ie3q1asYOHAg7t69G2O6BJmOHTsWmTNnRpcuXZRAUSl/KjczL1y4UO96ibREbsyXzyZ5//v4+GD27Nno2rUrtm/fHhn8GV3//v0RFBSEJUuWKGXiJVA6MDAQkydPjmwj5X/lpvzXr18jRYqYwT1SGSr2PuuKJGCdwaIJK57FO05G0Z+PPVXKuC//KCdypLFOtqPxLbLg5+PPMHLdPczvlMOiZb16G45Zux7ik2rpkMFXf9CpBAFUzmNalikih6ncXf/0ZL6ATxogNBjwdFDmMTm/mCyl4fm5KiklkznmOrdS2ZLD0z0Jhq29i0evwtCzugay2RKZSjIfn/wNKNQA8I26kUQhNy4+vACkSAukTB813cMLKG1CWWHJQPr0JpBOT3C/udzcgbIfGNc24DrebRqDJM0nAH7ZkJh1qqg/foSIKEFz6wGFGwKtZwJe3upDj+hJmch0DLPVIENvapkuX+b0zddlf4j+ZU/fiX5jd5gHDx4oWUzlfyEBLZI5Qkrey4nON2/e4NixY0b/TkRERERERERE5DxOnDih3HTctGlTeHl5KeeEbt++rVSziR0kKkGgH30Ut4ygBMTpzkfpzlP98ssvSuBpqlSmZVMisrcXL14gS5YsSobQ4sWLK1lEpWrTo0ePcPny5TjtT548iaNHjypBoUWKFFGqOkmg9Pr16/Hw4cPIdkWLFkWyZMmwe/fuGK+XwFHJXBpfFSdXwYs6ximWxRun7wRGbq+7z0LQe+UttCvjhw4VrFd2OG0KD4xtlhkLDwYoGess8cPex3j1NgKf148VBELkjK4eBK4dNlwWs8NCxwWJiuOrgNW9Dc8v8z5QuRvHXCcnwfUls3lj76XXqJo3BYpk1h8wQaRpT28By7sAjy/rz9r5TQk1kDS6y3uBU+uMX8cfI4HZteKWsLfE6yfA0Z+AN0+NaPwOeHwFePvKeusnIkpsOiwCqnwS9fzPOcDmr/U05PGtJRgoqkEFChTAq1evlOygOvJFTk7QS7ZQmf/333/HeM3x48eV/w2VPTKVXAD49ddfsWHDhjjz5CKBSJs2rVXWRURERERERERE2nLz5k3kyBGVWU4CPbNly4Zr167FaJchQwZs27YNLVu2jLMMyTI6YcIE9OrVC6NHj1ZuPF6zZg06d+5sl9+ByBISzDx9+vTIqk9Pnz5VbqDPmDFjZEWn2Odn06VLF+P8rFSBkgyhcl43egB1nTp1sHXr1hiv37lzp3LeV/YzV5cYsqZaK1D0yZtwPHgZhoiId+i69IYSMPR9h+xW34a9a6RDkUzJ0GflLYRHmHfRLTAkAtN2PMRHldMgq5+XVftH5BC7pgJbxxmeHxaiBjGFh9mzV9HWH6xm6TMk6CVw/QiSvFMTzZDzqpjLR/m/ZzVelyUnlbEgMCMQyFlBf9bOQQeBMrEyd/79M7BrmvHrkMCiHnGrX1jk0SVgWSfg5f2E26bNjYgB+4BMha3bByKixCR3ZSBjoajnoYEGAvB5TsESrDWgQVWrVkWhQoUwePBg5SS6lHeXcu8SODpmzBjlDvTPPvsM8+bNQ6NGjXDjxg2MGzcOtWrVslqgqL+/P7p3766UU5KT+A0bNlRKIUnWCFlvhQoVULZsWausi4hsiyffibSF+ySRtnCfJNIW7pNE2iHlsyXrYXRSalumRxe7dHZ0FStWxI4dOyKfz5kzBx06dMDevXvxww8/KEF1EydOVM59EWmZnKOVbLhyc/3333+P5MmTx2kj52wzZcoUY5q0T506Ne7fj3lxWc7pfvrppzHKz0vZ+SZNmuDChQtwdfoqYVFcxbOq7zPJKnrhwVvsPP8K2z/LB38f61/W8XBPgu875EC1qRcxf3+AEjhqqoUHAvDkTRi+aJDR6v0jcojua4DAZ4bn3z8LLGgJ9N8D5K8Ju6vYVX0YcmUf8GMzuI+/A3hlsWfPyMpalvLD0RuBaFPGz9FdITKfgfLBipzl4057fx4QGmz88q1Zcl4ndyVgZhDgrlbKMOoYVzKa8twWEZHpnt8Djq9Uj29T/HdzTL0v9DblNQTLMFBUg+QgYvHixUqZon79+iEkJEQpSSR3rJcsWVJpM2PGDOWkpARtSlCnlAHr37+/VfsxYMAA5MyZUzkJumLFCrx9+xaZM2dWTmT27NnTqusiItuRjMT8sCTSDu6TRNrCfZJIW7hPEmmHBIkGB8e8MCdBoj4+akYjUwUEBODAgQNYvnw5ateujbVr12Ljxo348ccfMWLECCv1msg2unTpgvfff185R9q3b1+sXLlSKS8fe/+QwNDYkiZNGmdfqly5shJ4vWfPHjRr1kwpc3/48GElGYAxgaJhYWEIDQ2Fh4cHwsPDIz8/5byyzIsejCnzRXxt3dzclGn2aBsREaGc75afJbuq/B762spyZJnSXpjaVvog06StPKJvl+htE9qGprS19vbO6psEPkndsPrYU6w69gz9aqZB3UIplbbSJ2krr7XWNqyUyxsfVfLD8LV30LJkaqT5Lx7amG0Y+DYUU7Y9wIfl/JArrVfkepxpe8f3nrXF9nbF96w1t7c529Am29snDcL/axtnG2YujncjziIiXT7AEWNyRDjcPDwNv2dzVoLH8FN465ESHqGhVt+G0dva6z2bWMeIWgVS4sCQvHj3Lhzh4er71pW2oVOPEa7yno2IgPu+2UCuSgjPUdH6Y8TJX/Hu7GaEt1+kd7tEnN8BXD+Mdw1Gxtounnj333GPUdv75Bql/HtEnSFW3N6eSIIkCP/v94l3uVPKAMWaIazRV3YdI1z9PWvO+zviv2za8r9sR25vbX2uWXocIX9XeS7/dN+NuL2d/z0b8eAi3Ld8DZRqg/BkqaPaRoQiTH5XL2/lby71LyIiwhM8J+IsxxFJHHAthIGiGiXBnxIoakjjxo2VhyEXL16MM2337t0m9+O9995THkRERERERERElHjIzcOS4VBHToDeunULuXLlMmt53333nXLjsQTEyUlQySaaL18+HDx40Iq9JrINXan5CRMm4NSpU0r1p2+++SZOcLUEQMYmQaKxM5Dqys9v27ZNCRTdvn27kiAgQ4YMRvVHF2Sp+zn2sqOTixLRX+fotnJhJHr/42ura2/McmO3TahPtmpr7W1YNLM3lhx+ikKZkmFKa7XkvPTH3O2SUNupbbLjjzNnMfi3O1jRLZfR22XFsRe49yIUIxtnVvrorNtbX1tbbm9XfM86xfaOiIDHm8dAqkyGt6GUPD75q5JVNN7+Zy4MZan/ZZCz6zac1xxI5gt8/LP+beiZBkiZRgkSjb5sa71nY7e113tWa+9vjhH2bcvtbaNt+PIBsF7N2uY2953B/pu/vd8hiQTLRJsWva3748vAhW1AkzHqa1/dAxa/D7RfCGQuavw2fHwJuP033K11nHx2M3Dkf8DHv8Tou6HlhtX8DB4ZC8ZYD9+z9m2r295uSdRp8r8tPgNdeXvb6z1ryXGE/F3lO4f8i91fbm8nfs8WrAVMe6m21QVPhgQCQ1LBs8MioEJn5W8uc6J/53T27e0IMXtOREQuhxmZiLSF+ySRtnCfJNIW7pNE2lG6dGk8ffoU69atU4LfpLJN9uzZkSdPHpOXdePGDVy7dk3JJOrn56cEzt27dw9nz55F1qxZbdJ/IkvJ+3/Tpk2RmR90FwIkaPTRo0dx2mfMmDHOdNl3nj9/jvTp08dpL0kA9u3bhzdv3mDLli3xJgVwNY6+KOJMimfxhocb8NPHueDtZfvLOWlSeGBam6xYefQpdpxTL9IlJDT8Hb7Z+gBtS/uhYMZkNu8jkcV+6QvMra8EjBqU1AdIlVkG/viXFR4GzKoJ7J4Bu6vRH6jcI/42G7+E+3XelENECfDNCHxxAhh63DbLL/sh0GmJ4fk1+gKDD0U9jwgH0hcAkvubtp6GI4Eea2A10g95GHmuyq3SR0CeKtZbPxFRYiPjbfQx1yu5+vmRp1qsZryGYAkGiiZCvXr1QqlSpeJ9XL9+3dHdJCIiIiIiIiIiB5HsiDNmzFBKxVeoUAGHDh3CrFmzlHlNmjTBhg0bjF7WzJkzMWDAgMi76ocOHYpWrVop2RR79EggwIHIQQICAjBo0CClJLyOlBo7d+6c3oDpcuXK4cGDB7h582bktKNHjyr/lylTJk77ihUrKplGJRj7+PHjaNCgARILKbVGxhnZOCN2DMiP0tljZqW1pc4V/VEjfwr0WXULb0PjCaT7z6qjT3HjSYjSVyLNk+DQqj2B97+LPwi0eAu1TULcPYCCdYEc5WB3RRqp646PZMN7dNlePSIiZ5atNJA97jGrVQS/UTMvGyttbqDzUiB1ZtPXJet5+wpWUawZ0ON341f98BJwcZd11k1ElNj8MQpY3Tvu9HIdgLTmVTci/Vh6PhH6+uuv8fbt23jbZM5sxoEXEWn25DvvqiDSDu6TRNrCfZJIW7hPEmlLwYIFsWZN3IwskmVRn4sXL+qdPnv27BjP27RpozyItCx//vyoXr06xo8frzxSpUqFH3/8ES9fvkTXrl0RHh6uZB1NmTKlElhdokQJJRPvwIED8dVXXyEwMBBffvkl3nvvPb0l5SVoul69ekpAtgSZ+vubmDHJiUVERDCrqJFypEmqPOxJjsW+b58dJcadxzdbHuDr5oavFYRHvMPELffRvEQqFM9qv2BWIrOt6gGEBAEfrVSf/1cyPobg18Dzu0D6/MZlkWs4KmpZ8kgoC6m1nN4AZCwEpM9nuM0XxxEeGsqsQUQUv8P/A46vBPJWB2p8CiRPbd3lTy0HFGoItDaQfTn0LTC+ENDsG6DsB8CTG4BPGiBZStPXtbQj8OYJ0Herxd1GeCjg5mF0RlEcWw4cXQaMv235uomIjBUarN685Obk37HT5NKfSVqC8C9sB2r0i5zEm08tw+8GiZCcmMyRI0e8D09PT0d3k4iIiIiIiIiIiMhhJIizUqVKSvBn27ZtlTLyK1asUG6yv3//PqpWrYrNmzdHBtfNnTsXWbNmRZcuXZQsuhJoKkGjhki5+devXytZeom0pFAmbwytnwGTtj3AxQf6k068DArHqPX3cPFhMEY2ymT3PhKZpWhTNUOcZBZd0BrYOTVum4u7gXEFgWe3jF+uXKz+34fAlq9hN8s6AWeMz/BORGSQBBhJkPzeOcDL+9ZffvNJakY4QzyTAeW7RAW+L2kP/NLXvHVV7g7UHgyrWPkJMDNmueP4RNQcAAw/ZZ11ExElJOA68H1TYGAy4PR6OL3K3YA6g+JOv3MSWD/MetmiCUneMdSWrEjuqD927JiScUJKJxGR4zErE5G2cJ8k0hbuk0Tawn2SSHv8/Pwc3QUiinXuVTKQ+vr6wlnx8945BIVEoOjXZ5EzTVLsHJgv8m/24EUoZu9+hO/3PkZgSAQG1kmPya2zOrq7RKbb9g2QsSBQomXM6XIR+uZRIH9t47PIid0zAb/sQKnWsIugl2pwl1c81+I2fol3N48iiTUy6xER2cudU+r4lqmIY/txZT/w9iVQ1LibuniMqx2DZ63Bs1eB8EuZHNMH2OlzmeyGf9//XDsM/NIHKNoMqNAZSJcXTu3hRfVY2ss7bnbnJO5K1n7d3z51yuSYkZj/9hZi6XkiIhfHLyZE2sJ9kkhbuE8SaQv3SSIiItcXHh4ODw9emtA6by83fPdhdjSacwUr/nqKCrl8MG3HQyw9/AReHknQs1o6DKiTHln8vBzdVSLj3DgKhAQC+WuqzxsM199OSh0XqGP68msPjPpZMpbaugS9txE3DOQohwiftHDyQqREZGuvHgMp0poWHG+swGfAmT+AIk2AFGkMt3t2B3h2G8hdCchawrJ1Kpn1kgDFm1u2nLzGZxMV4Y+uwmPbOKDpWMA/h2XrJiJKiIyXw07CJUhWa8no32UFUK59zHnucathMx+mZVh6noiIiIiIiIiIiIiI7IIXdZxHw6Kp0K6MH3quuIUCY85i/ann+KpZZtz6phimtsnKIFFyLgd+AP4YETeAaXVv4MkN9XlYCLCqJ3D/rPnrWfs58HMf2DyoS0rdJ9TPYs0QUbW3bftCRM5NAttHZQH2zQMWtgG2T7Lu8h9dBpZ3AV7ci7/dwR+BxW2Be/8CW8ergf3mOrocOPkrLHZ2i5rd1Ejv8A4IuMryyERke3LM+upR1PNzW4ENsY5znYm7FzBgr+GbtX7pB2wYGW0CzylYgrftEhERERERERERERGRXTB7uHOZ9X42BIdFoHHRVOhcKQ2SeTL/CDmpDouAN0/iXpS+egAo3gJIkxN4eR+4fhio1M389WQsBIQEwaZCg4BXD4GI8PjbBb9GklsngZzlAM9ktu0TETmndxFAt9+AzEWB4FdAunzWXX7O8sCMQMAjgZtLqvcDqvRUx2AJWq03zPx1frRKbwY6k60ZABRrbnSG0yRpcgGDDli+XiKihFzaA8xrCIy5rJacl4zMt06oZdqtMf7Zm3xG5K1ueH7aPEDSFMA13QSeU7AEA0WJiFwcT74TaQv3SSJt4T5JpC3cJ4mIiFyfuzuLIDuTTKk8sa5PXkd3g8hy8l1DSitHl9QHGH4qqky8lAoecdqy9VT6OOpnyaBsi+84/tmB/rsTbnf3NDxmVwdGnFGDwIiIYnP3iCrRXt+C4Mz4eHkn3MY3g/q/X1ugdFvL1qcLkrJ0DB72jxpIa+oxrq3GfiIinRzlgK4r1QBKUbk7UKUHnNaNo8DV/UDtQfrHz9oD1f+PrVH+4zUEy/DWTyIiF8dyXkTawn2SSFu4TxJpC/dJIiIi1xcWFuboLhBRYrP/B2B+SzV4JzYJEg1+DRxZAoS+td4698wCFrXVv05LGbvMrCUR+vkJ62cIJCLXIaXVDy9WxxUpmS6l363p0CJgde+E20mp+V8+VYOFrOGHZsD6LywPcJUbCkw5xv2mpHOXfyYi5+DjD5T9MCqoUve/jKGvY2XQdwa3jgP75xkOspcs+g8uABHquYR3JgTxU1wMFCUiIiIiIiIiIiIiIiIi1ySZ6jIUNHzx+dKfwOpewEBvYOc066zTP6daht4WgaJ//6L2VYK64uOVHMhcDPBMav0+EJFruLQb2DBcHR+PLgcmlwYirBiAI8t1MyKbvEcy4NpBYFoFNXDVUkWbAnniKWOcECnfvLANcNXEUvJ1BqvrJiKylSc3gHVfAK8DYk4PegHMrgn8tRROp3of4Kurhue/uAeMLwS8eWrPXrkslp4nInJxTL1NpC3cJ4m0hfskkbZwnyQiInJ9LD1PRHZXoqX6MKRoE2DMFTVgKktxK63zPfWhy4JkTKCUsbKWAlpMBrwSznTnvnMykL0MUKSR9dZPRK5DyvnW+FT9WcZJKWdsTZU+Vh8JkezOQ48B2yYAGQpZvt6qPS17fViwmm06PMy0Y9zynSxbLxFRQh5fAU6sAhqOijndOxUw+DCQuShcTuqsQP/dwMZHwJsQXkOwEDOKEhEREREREREREREREZHreX4XuHsm/syecrHZLytQobNSrt2qTq9XM/QFvbTeMjPkB2r2VwOrEpDkyl7g4QXrrZuIXI/7f7nFUmVSA0WNGFuMJpmPjc2sLAH1DUcDuStZvl5Z58Xd6vhvjqQpgL5bgfw1TXvdo8vA+R3mrZOIEjcZO0LfJtyuYF1g7E0gWcq487KWUMdSE4LcNeGHZsCuGYbny7F6/lqAG3NhWgMDRYmIXNw7W5S2ISKzcZ8k0hbuk0Tawn2SiIjI9YWHhzu6C0SUmBxZAsysqmb1dIRMRYA81aICsazh3r/A5b1GNQ3rtVnNGEhEpM+PLYC/lkWVW98yDrj9t/WWP64gsGWscW2XdgL6Wyn7sgQV/dIHOLzIvNfL+SkTz1Epx7jHVgDLu5i3TiJKvJ7dBlZ8DATEU35dN06HBKljnCH75gFTygAREXAaOcoD6fLE30aOfR9fVn7kNQTLMNyWiIiIiIiIiIiIiIiIiFxP7UFA0abWDdQ0Rbq8QLu56s9hIYCHl+XLPLQAuLgLGPmv5csiosTNLxuQ3E/9WTK1HVoIpM0DZCttneXL+Jc2r3FtpUS9ri/W0H8PkDKDea+9uh/4tjYw+oI6jhtLAvNrfWbeOoko8ZIbmgrUBZKlir+dHP8taAV8eVEdv/WRzNAhgUBEGOBmheNOe2g0OuE2j68Arx4BybLYo0cujYGiREQuLkl8d5QQkd1xnyTSFu6TRNrCfZKIiMj1eXjwsgQR2ZGXt1qG09Hunga+bwL02mh5f5pNBBq8Maqpx/65wNHlwDArZggkItehC2QXck5m3E3rLr9ES+PbSllheVhLqkzmv1aCZdvOBXwzmnaM65lAkBcRkT5pcgKd/gfsngk8uQ60/VZ/u0xFgZbTgNRZDS9LAkXl4SyC36gZVSWjqLun4XaVuwFH1wCvApEkCYunW4Jbj4jIxTH1NpG2cJ8k0hbuk0Tawn2SiIjI9bH0PBHZzbVDwLLOQNBLR/cESJ8fKNUm/gv7xkrqA6RMb1TT8MwlgLLtLV8nEbmet6+Alw9MLrFutJcPgSNLgaAXcIinN4HvGgIPzpv+2tRZgGq9gKQpTDvGfXoLWNoJCLhu+jqJKPGSMUPGSi8fddwxNC77ZQWq94m/9LwIfQtsGQdcPQjNu3kUGF8IeHLD6JfwGoJlGChKRERERERERERERER2wYs6RGQ3csH9xT0gWUpH9wTwTAa0ngmkSKNmTrJkLNw2US0PbYR3eaoBdYeYvy4icl2n1wMjMqklinU2fw3MNyELaEKZlH/q6rhA0WS+6tgbHmr6ax9eAs5uMf0YV4K3nt4Agl+Zvk4iSryWdQR+6QtU/QRoPlF/IKgEv++cZtyYKpk5L2wH7p2B5mUrAwzYC/jnSLjtjSPA87sy4tqjZy6LNV6IiIiIiIiIiIiIiMgukiSU/YSIyFqKNFIfWhL4HJhcGmgwAqjc3bxlSHlOIwNNk4QFA7ePARkLA8lTm7c+InJNBeoAvTaqWYp1shQHvK1UPr1QPWBmEODuBYdI7gd8ss681/6zBtg9HZgcYNoxrl82YOB+89ZJRInXBz9GBYdGhKs3BGUsBOStHtXmzj/AtglqtuOEuLkD/fcA7k4QEujtG/P3jE+qLECYlKfnOQVLOMG7goiILMGT70Tawn2SSFu4TxJpC/dJIiIi1+fu7u7oLhBRYhASBLx9AfhmhKZIsGbTcUC6vOYv44PvjW7qHvQUmFEF6L1Ze0GzRORYqTIBqZrEnFbCStlEdSSjpyNJNtHAZ0DK9Ka9rvYgk4P5YxzjRkQAbizuS0RGylw06uckbsBfS4HCjWIGUBZvAUx6pGYLNYYuSPTgAiDgGtDiG2jSyd/UzNYVOifcVoLxXwXyGoKF+OlEROTiWM6LSFu4TxJpC/dJIm3hPklEROT6wsLCHN0FIkoMLu5USyo/vQXNKdcByFnBLqsK80kPDD8N5Kthl/URkRM5/D/g0p6Y00LfArf/jlmO3lx7ZgNrBsGhVvcCvo8VDGsMz6RAynTmHeNOKg1sGGb6Ookocbr3L7BlLBD8Rn0uQZCSDbTR6Kg2kmVUAtCNDRKNLjQICH5tdDZ6u5PPobObTHrJu3cRNutOYsBAUSIiIiIiIiIiIiIiIiJyHbkqA91+UzMPaY1cqD/wI3DjL/NePzSNmh3KGFJ6NEsxwCu5eesiItd1aAFwflvMaY8uA5PLAHdOWb58Nw/zgpqsqXo/oNUM01/357fAjinmrbPOYKBYc/NeS0SJz6NL6nGhR9KYwepyvHh2ixrAL2P1yMzAy4emL79mf6DdHDUAVYJNteb974CPf3Z0LxIVlp4nInJxTL1NpC3cJ4m0hfskkbZwnyQiInJ9bizDSUT2kCINUKo1NEm+9+yeAVTuYXpmUQkaaDwGyFHe+DF373dA0hRAxS7m9ZeIXNPgQ3EzzKXPD3x+FMhUxPLl1+gLh8tWyrzXvXliclbVyGNcyRpNRGSskq3UR2xPbwI/NgM6/6SOZTX6ASnTm7+ei7uAdV8An+4EkqeGM+M1BMswUJSIiIiIiIiIiIiIiOyCF3WIyOZePVIzwdUeCKTOAk0aeRZwN+MyrYyhkhnK6OZJgLv/AMn9TF8XEbm+2MdlksUuRznrLDvoBZDMN+467EmCPQ8tAgo1ADLkN/51Tb42/xhXsrIGXAMKNzB5GUREkdLkBIafBjIWUsfRhqMsW55/TvUmgCQaunEzNBiYUARo+y1QpLGje5NoaOgdQEREtvAu9t2ARORQ3CeJtIX7JJG2cJ8kIiJyfeHh4Y7uAhG5uifXgb9XS9gONMucIFER/Bo4v10NwDJ2zG2/AHjPzBLKROSarh8BJpcFnt+NO2//D8Dfv1i+jpFZgN0z4VBuHsCGYcDtv+13jHtiNbCcGZyJyEjjiwCHFuqfl6kw8PwOsGOyyVmO40iXB+i8FPD2VcvZa0F4CFCyNZA6q0kv4zUEyzBQlIiIiIiIiIiIiIiIiIhcg5RzH3cbSJ0ZmvXsNvB1PuDqAdNe9/gK8F0DNWMdEZG5vHyAbKX1Zxu+she4ddyy5UsQT6elQNGmcCgPL2DaK6DsB6a9bmwBYMtY89YpWZ9HnzfvtUSUuEREAGXbAxmLGG7z70Zg/TB1XLXWMaiMcXLjkaMlSwm8NxnIUtzRPUlUWHqeiMjFsZwXkbZwnyTSFu6TRNrCfZKIiMj1eXjwsgQR2VhEOODmDk3zzaQGUCX3N+11UjJ07E0gZQbjx9yTvwGrewET7wPunub1l4hcS5ZiQPv5+ud9tMry5cv5nVKtoQluZuROqz8cyFDQvGNc71Smr4+IEicZnxqOjL9NlZ5q1s2kPtZZZ6osQLkO6jGlqcLDzM+Kr8/LB0DgM3W8NeG6QJIkzIlpCW49IiIXx9TbRNrCfZJIW7hPEmkL90kiIiLXx9LzRGRTYSHAUH/guJSe1zC5yN56plpS1KTXeQL+2QHPpMaPuRkLAXWGqBf3iYhEwHXgdYDtlv/0FnBkieWlkq1BSjrPrW/aayp2BXJVNO8YV7L1Le2kZoAmIoqPjBO3TyYcTJoyvfXWKctrPhFInUUdo8ND429/4yhweDEwtTywYTis6uhyYFpFk4JEBa8hWIaBokREREREREREREREZBe8qENENiUXu5uOU0sqa13gc+DMRtNKiUqp+tW91aypxo65kjGq/jDAy9v8vhKRa1nZDfilr/55p9cDo7KqgffmktL1P32UcACSPaTOCmQtafxYK32WsfnVI/OOcSXT3dObQPAbMzpLRInK/u+BRW0ds265gWhGVWDjl/G3k8+Ew4uA6v2AYs2t24cKXYFPd5nxQp5TsARrvBARERERERERETmZb7/9Fr/99hvc3dWyql5eXti2bRvWrVuH5cuX4/nz58ifPz+GDh2KXLlyxbh49cUXX6B69epo2rSpMi00NBSzZs3Czp07ERERgWrVqmHIkCFInjx55OtCQkLQvn17fP7556hQoUKc/sh06cukSZOU502aNMG9e/ci58s6smTJovTx1atXGDt2LPbv36+8plGjRko/5XfQuX37Nlq2bInjx48b3Abz58/HihUr8PbtW+V3kd9LljFnzhz88MMPys/y+8r/NWvWxFdffRXjdyIix0hiYrYQIiKTSFnOmv3hFK4fAn5sBnx1FUib27jXvH4M3P4bcFOPAY0acyMigBtHAP8cavYoIqK2cw0H2qTJDVTqpgZMekR9RzNJyVbAzLfmv96aCjdUH8aSTKsyNvf8Ayimfmc26RhXxtmB+8zoKBG5BAkafxdh3LFa46/U0vKOym5fawCQvUz87ZqNB0KDAC8bnE9LmU59mIznFCzBjKJERC6OJ9+JtIX7JJG2cJ8k0hbuk0TGu3z5shJsuWfPHuUhAZinT5/Gjz/+iClTpmD79u2oWLGiEoCpIwGao0aNwr59MS9aSWDp9evXsWbNGmzYsAFPnz5Vpuk8fPgQ3bt3x5kzZ/T2RQJMN27cGGPapk2bcPLkSeUh68uYMSOGDRumzJP+BQcHY9euXfjjjz+U5S5evDjytf/88w86d+6s9NcQed2yZcuwYMEC7N69G3fv3sXUqVMj5zdr1kxZtyxL5j9+/Bjz5s0zaRsTkW3oAtyJiGzi0h41kNIZ5KsJjL0JpIm6qSdBJVoCn/9l2pgr37Nm1wROrTWvn0TkejIVVrMN65OlGNDkazXw3hKeSU0uJ2yzoK2A68ZnCJUSzxPuAQVqW3aMK0H6RJT47JkF9PcwLotxspRAhvxwmAqd1c8CyS766nHUdLlRYEFr4MJOdRyXIFEJoj++Ggh9a73175oOnNtm8st4DcEyDBQlInJxLOdFpC3cJ4m0hfskkbZwnyQy3pUrV5AvX74Y0yQYskOHDsiTJ49ykapNmzZKZs4XL14o8yX4MkOGDChWrFiM13Xp0gUzZsxAihQpEBgYqGToTJUqlTJPgjUls6dkGc2cOXOcfkhQqQRotmrVymBfZb4ErdaqVStyX+/Tpw98fHzg7++vZAOVgE5x4MABDBo0SAlMjY8Ep8rvKllTZTmyPAly1TeOyO9Vo0YNXLhwId5lEpF9hIWFOboLROTKNo5WL9A7A7no7p/dpoFUypgryx9xBqjY1WbrISInIsFAm8YAz+/qny/fqSTg3tD86F4/Ac5ujhs4tHU8sGEkNGNSCeDIEuPaShbAVJlMzp4X4xh3cllg3ecmdpJcyt3TwNgCwAOeh0h0UmYAqvVJ+Pgu+A2wrDNwV/9N2Xa1soeaSVl3Ti0sGHgXDrhFK1L+8CKw5EPg8RXrrffsJuDuKZNf9k4ytpLZWHqeiIiIiIiIiIjIiQQEBCjBn1IuXrJxSkn3gQMHok6dOjHaHTp0CGnTpo0M+pTsm/K8d+/eMdpJUKk8pGT7ypUrkTdvXiUjp0iWLJmSHdTPzw+rVq2K05evv/5aCep88OCBktUztqtXryqv37FjR+S08ePHx2izd+9eFC5cWPm5SJEi2Lp1Kx49ij/bS0REBLy9vWP8Ds+fP48Mio3u2bNnSmBp/fr1410mERERuYDP9gBvDWcl15yTv6lBVh2jsqvHa80g4N4Z4NOoYyujZChgVveIyAU9vwMcWgiU+VD/fCULcS2gwUigXlSFCr0u7QYWtwO+eQh4JgP++R3w8gE8o76rOZz8Pn22AWlzGx/g9+e3QMupQHI/89ZZZzDgl82815JreP1Y3ddkv6DEpVx79SFBl/EFi755Ajy6DERo4EbKmv2B4Fdqf0OCgKQpgE/WxWyToxww5an546I+/Xdbb1lkNGYUJSJycUy9TaQt3CeJtIX7JJG2cJ8kMo4ERJYuXVrJECol2Js3b47BgwfHCJL8999/MWnSJCWAVEeCROPzySefKAGd6dOnV14rPD09lSBRfTZv3ow3b96gbdu2Bpe5ZMkSJbOpZA41lG302rVr+Oijj5Tnsi4vL68EtgBQs2ZNrFixAjdu3MDr16+VIFghJe3Fxo0bUbZsWZQpUwaVKlVSglh1GU2JyLHc3HhZgohsyN0T8NF/3KFJEkQQGmR8ieJCDYByHU0fc4+tBHZMNrOTRORSspUCJtwFMhY03GbQQaDKJ/GPXZf2AMWaAV9dU8u1i6PLgOMr1UDJhqOgGbkrAb4ZjGv79qUakI8k5h/jlv0QyFPVxE6SS5GMvFK+mwHDiYtkV5aMm9u+AWZVj7+tZJUfclgdkx1N+pC3OnDvX2BiUeDF/bhtPLysGyRqAV5DsAzPyBARERERERERETkRyfg5d+5cpYS8BHK2aNFCCQI9depUZPn2zz77DP3794+TZTQ+SZMmVcq09+jRAwcPHkwwq6mUqx83bpzBNiEhIUowqQSK6ivLN3LkSGzbtk0JJjUUjGqIlLqXkvUSLCs/S2l5kTJlSuV/mXf8+HGcOHFC2S4tW7bEhx9+iMDAQJPWQ0TWx4s6RGQzksluQWvjgy61oHRb4KNVEmFkXPvCDYCKXUwfc59cUy/+ExEZI3NRIHlqw/NlPPm2NnDtIJA2V9R0yUDXXr2JT1NuHgfWDzeurQR4fv5X/L9/Qse4kiXw7BYTO0kuRW7qGPaPGnhMicfNo8DX+QAvb6Bkm6hS7vpIILHWPDgPFGkC+GbUP3/HFGDjl9ZZ142/gK/yAAHXrbM8MhoDRYmIXNy7+A5AiMjuuE8SaQv3SSJt4T5JZBwJfFyzZk2coEwJ9JRMml999RXGjh2rBJAaY/Lkyfj9999jLEsCRuMjgaQSLCol6iVz5/z585V160rWi7///lsJYM2XL1+cvvbu3RuXLl3Czz//jOzZs8NUUpq+Xbt22LdvH7Zv34506dIpy0mePHmctrJdunXrhsePH+Py5csmr4uIrCs8PNzRXSAiV+XmDiRLaXzQpVaEhejP3KTPzWNqpipTx1zJ7NdluZkdJCKX8tsA4KeP429zZiOwdXz8gaTDTwG5q+jPOqc1T28Cp34Hgt/Y5xj35K/A8s42Wxc5gfAQYEIR4N+Nju4J2VPWUkCfLUD1fkCtz+IvPb+oLbD4fWjuBqa238bfb2tJ7q8G0/qkMfmlvIZgGSf7pkQ6cvK+QIECJu0oa9euxZMnT0xaz/79+9GpUyelnFmJEiWUk/1y4j80VIPR7UREREREREREiYCUZpeMov/884+SmVOCLeVcjQRETps2DTNnzkSVKnou2BlQuHBhrFy5Ugm+lPL1cu6nUaNG8b5GglBl/ZK1Ux5Stl6yeP7xxx+RbU6fPo2SJUvGea1kIX358iWWLVuGNGlMPyEsJEBUMqZK2Xnp9+zZs5XAUX1kG61atQq+vr7InTu3WesjIiIiJ1C8BdBpCZzOwtbAim7GtV3ZA9g909Y9IiJnF1+muhzlgJwV4399wBXg6gHD8yWIKEtxwDMZnEKp1sCXF4GkPgm33TYRGF/YsvVJkNiXvEkxUTuyBEiXFygc/7kVcjFyw1LhhoC7B/Dgghp0b0iVnkCFrnAq9YYCTcdaZ1np8wHvTQa8fa2zPDKah/FNSUsaN26MatWqGd3+2LFjGDZsGHbt2mX0ayQzhGR3GDhwoJKJwsPDQ8kE8c033+D69evK/0SkfSznRaQt3CeJtIX7JJG2cJ8kMk6hQoXw+eefY/z48UpWT8nYKQGiixYtUrJ1SgBldBIkmTGjgbJRgHJj8MOHD/HRRx8pz+vXr4/u3btb3M979+4pmT6je/XqFX777TflPFPlypUjp5cpUwYLFy6Md3lffqmWt5JsqVJu/uzZs6hTpw7c3d3Rtm1bJWuojgSsSll73diSP39+zJs3L7I0PRE5juz/RERWFxEOPL0FpMlpnyxI1iTZPt09jWvbexPg5mH6mCvlPec1Aob8pV6YJyLXtaqnWu76o1X655frkPAyag1QH/qEBgOL2gCNvlSDTl1NvpqAT1rLjnEZ+EQSMFisBZDC9PcSObE/RgHFmgE5KwB/LQH+/gUo2kT/sWkRJw0iDnqpZo629EaBh5fUagDp8pj80iRJmBPTEkneMSdrovDXX3+hc+fOSqBo1qxZjXqNXFSQbBTff/99nIsLckJelimZGKKTbBASlFqwYEG9pb6IyP4iIiLg5myldohcGPdJIm3hPkmkLdwnibTHz8/P0V0goljnXsuVKxfnvKwzkSy/DBYlIqu7fxaYUBTovwfIX9PRvdHemPvygZrdrOJHgG8GR3eLiGzlxM/Ar58Cbb4Fyn6gP6j+1gkgU2EgaQrz1vH8rpoF+b0palZRZzGnLpC7CtDka9sf4z67A2wYBjQaw+B8Bxg8aw2evQqEX8rkmD6gteM6sncukKEgULCu4/rggjTz99UXRD+lDNBgJFD2QyDwOeDpDXgmjdv2xX3g6n6gSBPjMh1rhYxto7MBvTaqAbCWWNQWCHwGfLrT5L99qhTemDmwjWXrT8R49UUDpIT8ihUrlPJYxYoVU7I4RM/8OWfOHHTs2FHJ7Ckl4KU8V+zS8/KzZGPo2rUrihcvjqpVqyolyKIHiQrJsiCvNYZkW7hw4YKSUSK69957Dxs3bmQgKBERERERERERERGZhLkriMgm/HOo2TZzlIVT+vNb4GICVQFl/Py5L3D9iOljrm9GoP4wBokSubrQt0Ch+vqDRMXzO8C0CsDVg/EvRzI0j8gMXNkXd17qLEDfrc4VJCqKtwRyVUq43e2/gbtnLDvGlSx5sg2DX5u8HHIRQS+Aw4uBG8Z/ZpOTk4DQkf+qQaIieWr9QaJC3heL31fHbGci43+Xn4BspS1fVutZQLt5Zr6Y5xQswUBRjZDyYC1atMD69etRo0YN9OvXTynzriN3iqdNm1aZ36lTJ73LmDx5Mlq2bIlNmzYpgaUSYCqvK1WqlPKz+PXXX5Wy9cbo0qULnjx5gtq1ays/S+Dp0aNH4enpiTx58vCubyIiIiIiIiIiF3fq1CnlpuGSJUuiffv2uHXrlsG2z58/V84j3blzJ3La/v37Ub16daXMvJzX0tmyZQumTJli8/4TkfZIggIiIquTzHhFGpufIc/Rjq8CbhyNv01YCHD9MPD6sXljrpSff3jRgk4SkeZV7KIG8bx6rAaWP78Xc75vJuCLvxMOmEyRDqjSA0iVOe68R5fVwHVnU6MvULhhwu02jAC2mJ51NMZ4myoTMHAfkK2UycshF/G/D4A0OYGGoxzdE7KXiIi40/bMAhbqyXxZoiUw+QmQIg2cioxz5TqoY5yl5CamDPnN7Yjl60/EGOmnEa1atUKHDh2Un4cMGaIEZP70009KBtHopeBTpkyp/Bw9iFRHTtpLsKno1asXFi1apLSTUkSpUqVSpvv7+yNZsmRG9UnWLdlH//e//2Hv3r04ckS92yF9+vQYM2YM6tY1nCI7PDxceUjJQCkdqBP9ue5gSXd3jaPaykP3XObJ63SvdXd3V34PW7bV6naxVlt7bMOE2mpxu1izrTHbRebbantrdbtwjHCOtolxjIh+V6lWxghbtnWG9yHHCO22tdc2lOlaGSPs3ZZjBMcIrW1DmR/9d42vbWI8jrB3W44RHCOCgoLQt29fDBs2DPXr18f8+fMxYMAAvdVqrl69qlTDuXv3bozpM2fOxNixY5E5c2blRmQ5dxUaGorFixdj4cKFcZZDRK5PxiIiIqvbPRPIWsp5y84PPqRefI+PZKUaFvf6oNFj7vKuQOFGQOsZZnaSiDQvJAjw8gY8vIAL24GSrYDU0YI9ZboxwYuyDH0l2l8/AcYVADouASqoFU2dKsPjzWNA/lpqxk9DOi8H3kV9b7boGFe+b7sxd1ui1GAUkIR/+0Tlf+8DSVMCHRdHTfPLDmQsrL+9jz+ckoyj9/4FKn1k/GsiwoH7Z4G0eYCkPsDGL4G7p4BmE4DMRU3ugu4cJpmHgaIaUaFChRjPJQvowYNRKd/TpEkTGSRqiGT5jE7ay4l3S+TNmxcTJkyIPOEvWSAkgPWzzz5TLgpIyXtDB0K6g6HYB0XxnQh0VNvoz2MPKo5oa2r/na0tt7d12yb0u8rFPXkY0zaxbkO+Z7XV1tW3t1yI1+2T9uiDK25DrbV19fes1tpaexvKPinzEuv25nvW9m05RpjWVvZJbm/ttOU2tH1brb9n//nnH6ROnRpNmzZVnvfu3RtLly7FlStXlHNGOnLOSIJABw8erASVRieVaXQBqLp1/fLLL0rgqe7GZiJKXMLCwiLHBr3CQ4HbJ4G0uYEUae3ZNSJyZsdXAhFhzhsoKsdsuhvMrXjxO8aY22cLkNxJgxKIKGEyhgxLB7SYBNToB4y+GDdI8dQ64Ml1oPbAhJf34Lx6XBa9xHyylEC/HUBmJys7r8uq/F0D4Kur6nGmISnTWecYd2p5IFdloM0ss5ZHTi5PFeD3wcCxn4D3v3N0b8geSr8fNwhdgvXlEduyLkDBekD5jnA657cDfy0xLVA04BrwTQn1WFQyO8uNS+nzAemizi2a4t27qBvzyXQMYdeI2GXcddk4dYzJAurl5RVnWvSsZaYIDAzE+PHjcf78+RiBqF27dlVO5kt/Dxw4YNayiYiIiIiIiIhI+27evIncuaMuoEmgZ7Zs2XDt2rUY7TJkyIBt27ahZcuWcZYhWUblJmSpfjN69Gi8efMGa9asQefOTpZ9hojsZ/skYFoF4NxWR/eEiJzJ0GNAnSFwWlImenQ24NwWw21unQBGZAIeXDBvHVIC19vX7C4SkcZJ4MyH84EC/1UFlViDoJfAtUNRbe6dAS7tMW55az8H/hgZc5pkJC1Qx+xgSofKXQUYcxnwz5Hw731um+Xrk8+kUnpKTlPicGwlEBoEZCri6J6Qvcj+LiXlY3t+D7h2OOY0d091PHVG9b4AvrxkXFsJlr64Ww0IHbAXyFtdnZ67ElC+E+BpXDVssi4GimrEmTNnYjw/efIkihSx3oeGqal3JTD1jz/+wOrVq+PM8/HxUS4MSJZTIiIiIiIiIiJyTVJ6PvbNy97e3sr06FKkSKGcL9KnYsWK2LFjB/bs2YMGDRooJec7dOiAvXv3olWrVujZsyeePHli09+DiLRFX5WNGOU5//kNqNAFKNnant0iImdmg0ycdicZlCt1A/xzxtMmHVCtt/q/OWOuBOCvGWRhR4lIsySTXbn2QMaCUdM2fQksbqeW/RWNRgO9Nhi3vPfnAR0WxxxrfxugZuZ0RlLuWIKV4is7L26fAF7et/wYt3Q7IE9Vk5dDLmL9F4BvRqB6H0f3hOzh4SX1OEu+z8a2/RtgWazMoR0WqmOEM3L3MO6YOywEuHUcePVQbS9Bol7JrdIFlp63DEvPa4SU7ZIMDUWLFlUydl68eDGy5Ls1JE+u7nAXLlyAn5+fwZP30Q9khgwZglGjRinPW7duDX9/f9y6dUs5oZ8pUyY0bNjQav0jItvhByWRtnCfJNIW7pNE2sJ9kkhbJEj07du3MaZJkGhC55UMCQgIUCrULF++HLVr18batWuxceNG/PjjjxgxYoSVek1ETv15LxfYh59SgxkSuohPRKSzYbiaJa/3JjgtGRubfB1/G//sQKMvzR9zXz0C7p02s4NEpHmSbfjuKaBU26iS8/WHAXU/N++4Ssac6N6+BK7sUzOKOqs9swCPZEC1Xobb9N9tnWPcx1eAR5eAIo3NWh45uXG3gMBnQMB1IG0uR/eGbO3kL+r4Mulx3HkyDjceE/U86IU6JidNAackNw3MqQtU/AgoHysANjrJmCpZRElzmFFUIz744AMsWbIEzZs3x/Hjx7Fo0SIULBjtbh8L5c+fHzVq1MCAAQPw888/G/Watm3bKifqJTi0R48eSmConLTPkSOHckI/dkYJItKmd7q7qYlIE7hPEmkL90kibeE+SaQtOXPmxI0bNyKfh4eHK+eJcuUy7yLHd999p2QQffHihXIRLV26dMiXL1+cUvZE5NpkLDE8M1T9/9pBYFVPu/WJiDTK2O8HeaoBxZrD6b15ChxfDYSH6Z8vpUtNzOQXY8yt0Bn4dKeFnSQizTq3BVjVI2amN8lomDqLehNO6FtgeEbg5Brjlnf3NLCyBxASqD73TgUM+xso1gxO68l14OlN+xzjnvwNWBpPEBUZdxzQLwmw/3s4HdkP/5wNzPqv1Da5tgYjgRFn9GfalDFYMsfryPt5VFbjj3O1Rn7HLCVi/k76SKC0jfAagmWYUVQj8ubNi6FDh+qd9+mnnyqP6KQ0lzx0JANpbLt3R93t4uXlhfnz55vcr5o1ayoPIiIiIiIiIiJKXEqXLq2UhV+3bh0aN26snFvKnj078uTJY/KyJOBUAkLHjBmDsLAwBAcH4969ezh79iyyZs1qk/4TkROaXAYo8wGQuRjw4BwQEgR4eTu6V0TkKCdWA0eWAD3XA57xJC8p2gQu4f5ZYMmHQOai6kNftqo/RgIz3li2Hrm4zmoORK6n9kCgcve4+3fwa/UYq9ZAoManQIYCxi1PXnf7JBD4XC0XHPQS8PaFU2szO/75Z7cAyzoBfbcB2ctYtq7qfYFqvS1bRmInn1clWwNpnCwjp3yHmf8eULY98PEvju4N2YOMu6kyGZ5/4Ec1+327uUCpNkCmos59LNZ6RsJtJpcGynUEmo6zR4/IBMwoSkTk4li+k0hbuE8SaQv3SSJt4T5JpC1STUaqzUhlmQoVKuDQoUOYNWuWMq9JkybYsGGD0cuaOXOmUulGeHh4KDdMy03Q27ZtUyrZEFHiIWOAwQvBEryQr6aaqWrgfgaJEiV2yf2BjAWBzV8Dfy3T3+Z1AHB+h5opz9nlrAB881B/kKio0AX4/Jj5Y+6L+8DnqYHz2y3sKBFpVrKUcadJeeNKHwO5KgENRxoeY2LLXRn44jiQOrOakXRMTmDvXDi9iAj1oU/2skC9YUC20pYf48rfQrKwkvnc3IDuvwGFG8KpRISpf38Jys5dydG9IVt7dgeYWx94cMFwGzcPIMl/4Xnp8gLFmsKpSTD03TOG58t3+9azgVJtbbL6JLptSWZhRtFEaOzYsVi7dm2CpcAqV65stz4REWyaepsX3Im0g/skkbZwnyTSFu6TRNpTtGhRrFkTtzThpk2b9LbXV/VGzJ4dM3NLmzZtlAcRJT4RERFwd3ePO0OOAarEChwPCwE8vOzWNyLSmMIN1MeKbkBgBv1tLu0BFrdTAyzjyzrqDGS8S5keCA9Vn7t7xpyf3E99mDvm+qQB6g8H0pmeHT5Bj68Cc+oAA/YC/jmsv3wiStiyzkDB+kB5PeXO630BPLkB3DwO5Chr2nIl4EcCRdt9Z1YApabcPQ1MqwAMOhj3d5HfM2U6oO4Q6xzjPr8HrPscaDhavemBTCc3OPw+GCjXwbmyh0uQqAS4PrwIbJ8E1B7E7zSuTLIve3rHHxheuVvUOLNzClCiFZA+H5zWyV+B5V2AaS/136Ag3+2LN7dhB1h63hIMFNUAQyfQbaVfv37o0qVLvG3Sp09vt/4QERERERERERERUSIPFD3xs5p1J2tJ9blkZUmdFei42O59JCIN2DlVLTebNjfQYZHhdtLmy0tqgKUrCA1WS3VW+QSo9VnMecdWAG9fmlTKOMaYK0EqEixmC68eAkEvgKR6ggWIyD7cveIPRtv/vRqgNNeEAJuJxYHS76uZSMt+CKcnJcybTwJSZow5/dUjYE5d9fMmRznrHOO6ewDP7wIhbyzsdCJ29xRwYhXw4q5zBYqGhwHhIcCjS8Cuaepnuoe/o3tFtiKB4D3XJ9wu+A1w+wSw/Ru19LwzB4pKlt/Bhw3fpHVoIZA2L5C/ps2STZD5GCiaCPn7+ysPIiIiIiIiIiIiIiKHkws9G0cBZdtHBYpW68NynUSJ1cuHwK7pQLp8aqCoLoDy8CKgXEfA2zdmWVpnvtAem2dSNRA0TzX9ATOybUwIFI3j9kngXQSQvQysSkpUT31m3WUSuRIZwyRLsIxZttJhYfzzK3cH8tc2bZlyPCal6vd+B+SqaP2xw94k813sIHxdFvssxYE0/33mWIPcwDDgT+stLzGSYLSpchNCCjiVm0eBGVWAkWeByQGO7g3ZWsB1wC+bGhwen98+A278BUx5pn7/dWYyvsV3k9aRJUC+mjYLFCXLMFCUiMjFudnySycRmYz7JJG2cJ8k0hbuk0RERK7P0zNWKWVdabrRF4DQt1HTSrxn134RkYb4ZgC+vg54JI2a9voxsG4okCpz1PggF9kXtQWq9wXy14LLqNFP//T3plg+5kpQvpuHcZmvjHX1AJDcX82SFRasBqMRUUwjMgKVugGtptlm+SFBwLvw+APqJKje1MD6ar3U7IhS1l7KZzt7oKguYD7wKVCgTtQ0v6xAl5+sf4wrIsIBNz3Z9Mk40W8OcRbp8qrvJ6mOQK5NjkUnlwLqfK5mXo5P3aFqyXT57isPZ3dgPuCTBijVOu68QQfUsc9G3JLwGoIluPWIiFyclDogIu3gPkmkLdwnibSF+yQREZHrCw0N1T9DLqAn9Yl6HvwaOLYSeHHfbn0jIg14+UAtYe7lHTPzngTxjL0ZM4hcxgkJMHf2rEz6BFwD5jZQyxZbc8xtvxDovAxWtWUssP4L4MZR4Pph6y6byFVIJuCsJWy3/DMbgMEpgcDn1l3u01vAlX3AV1eBqj3hEvbPA9Z9of4snx8ruqtZ/mxxjDu1ArBmoMXLTrQkEG1IKmBFNzgVybRYroMakCzvgTv/OLpHZCsyhnyyHij7YcJtM+QHjvwPWOUiY+n5rcCNI3Gn6wJEbRggHyHZ8clszChKRERERERERERERESOM68RkK8WUE+yrPxHgr+WdgA+WQcUb+HI3hGRPf0xErh+BBj5b9xsSynSqBfk7/0LZCmmlhDuvREuSTI0RYQBrwOA1FnUabNqAoUaAA2Gm7/cVJlgdb02Am+e2GbZRK5Axq3mE227jtyVga4rgeSprbvcE6uAbROAaS8BdwMZM52NZGf2+u/mJBm77p8FQgJts646QwDfjLZZdmIgN4zI+87Zsgc+ugzcPAYUrAtkKQ54eju6R2TL92i+Gsa3l5uc5PjOFfT4Xf/0+e8BaXMDbWbbu0dkJAaKEhERERERERERERGRXbhFzxCok68mkKlIzGkp0gJTnlk/4IGItK3peODxFcMlOQ/8CKwZAIy7pZZQ907lmiV95ffqvyvmNMmmmqGQZWOuZP3cOwfo+D/A3QqXiSWo3zMZg0SJ4iMZJZ/eVAMUk/kCvhmsvw6/bMZltDNV5R7A3rnAzqlA3c/hEpL7xTzeHHzIKmWg9R7jlm5r8XITtcrd1YezubgT+LU/MDsEaL/A0b0hWzq+GpDsluXaG9e++Tfq8asrK/2+ehxrQ0msMGYnZk4Wek9ERKbiByWRtnCfJNIW7pNE2sJ9koiIKJF+3tf7AijaJO50BokSJb6sexJwmLea4TZSyrXPVrWsq2QdXuTiQTiPrwK7pqs/1xoAFG5g2ZgrWfOe3lAzWlnq2R1gREbg0p9RGdRGZLZKCWcil5K/lpoN+JsSwLGfbLOOv38Frh60TVClBIjmrACX8eYpsKAV8HMfNZuolc5F6T3GlXHxzB9WWX6iJJ9VcmwQEgREOFGp6aq9gGkv1J+f3wOCXjq6R2Qrl3YB57YY316y4Xu5SIbZO6eAkVmAB+djTi/fESjWzFG9IiO4eKgyERG9e/eOF9yJNIT7JJG2cJ8k0hbuk0RERK4vPDw8Zsali7uBNDnV8nT6gh4koKLnerv2kYgc4PUTYE5t4MMFQM7y8V9gz19T/bnuF65TCtmQG0eAPTOBCl2AgGtA+nwxs+GZOubKtsu/3zp980oO1B4MZC+jPpcgX8n8liKddZZP5CqKt1D/z1oSyGhaVmCj7ZisBtnnqWLd5co5mpr94VLkcyToBXBqLZAiPdAkVlZ7M8UZb8XpdcDW8VFBg2SaKWXVsvMSiDbhnvNkr5b9Rj4jJcj1yxxA22+Bar0d3SuyBckYK3/nxCh1VqDSx0DSFDG/28t7P1dFm19DIPMxUJSIiIiIiIiIiIiIiBxjdU+gSGOgzey48+Sik08aICLcNUtLE1GU0EAgU1EgTS7j2v/cF3jzBPh4NVxamQ+BEq2A8BBgWgXg41+sU8pYLrBbepOejz/QaHTMMbvpWIu7RrEcXgys6AbMibBa5kOyoyc3gICrQN4atg2cGXoMiAiz3fJdidxg0H8XEBosg6Ft1yXBgZJdkszz3lQ1UDTwmRrg6ywOLgAenANazwR6b7JdgDg5lu5YKrF+NqdIAzQdF3Parqnq8WC3Xx3VKzICS88TEbk4ZmQi0hbuk0Tawn2SSFu4TxIREbk+d/dYAZ/DTgINRupvXKQR0HExg0SJtERKv/4xCrh72rrL9csGdF0BpDQyG2WBOomjrKVkp5MSpaFvgc7LgIJ1LRtzJahhWHpg//eW9UtKKe+ZFTeL1uMrwI2jli2bYkrur5Yt5/dl5/TP78CP/2UUffUIWNUTeHDB+uuR94erZ1i2Ns+kgGcyqy0uzngrJGDKmQIctUY+54s2UUtZR89aqHVyk1t4qPpzofrqMQ65nr+WAl/l/S/oPJGSbPc3j0U977UJ+HC+zVfLawiWYaAoEZGLY+ptIm3hPkmkLdwnibSF+yQREVEi/LyXi74p0xt+QdBL4OVDm/eLiIx077Sa4VBX/vzRZcuXeWodcH67aa8p2Qoo1wGJxupewN65JpWd1zvmyoX1xl8BuStb1p87J4GLu+IGL26fBPzcx7JlU0wl3gP6bnV0L8hctQYAo84C7h7qMc+Nv4CXD6y7jtsngVk1gGd3rLtcsvyc1ov7wKJ2wP2zjuiScwt+DRxZAjy9BRxfBTy9CadRrRfQbq76s/RdynGT65FM+FJ6XYLOE6ttE4DVvWPe4GTisSrZHwNFiYiIiIiIiIiIiIjILiIkG6HOyh5qRrr4zKwKbP7K5v0iIiOyY4msJYHPj6rZsSTgaVwB4PJey5Z98lfLM1y6ulbTgV4bLRtzdar3Uf+Olmj0JfDJ+rjTm4wF+myxbNkUk2TvHVcIeHjJ0T0hc0jQjH8O9Wev5MDwf4D8Na27DinNnSozkMzXussly8dbj6TA3VOAbyb1uXxeBr+xe9+c0rPbwE8fAQ8vAEvaA1cPwmlINlFd4PC+74Azej4vyfnlKAs0GIFELfpxn1QckKzZdsBkE5bxsPD1REREREREREREREREpkuRDvBOHX+b9+cBKTPYq0dEZChIdP57QO4qQP1hgF9WdXr2csBHq4E81aLKKseXIdgQKTkfFmLdPruatLmtt6z759S/lbnBanf+ATIXVwPgYkud2eLuUSy/9lcDpSTIkJyLZEJc3RNo8y2QPl/U9MDngHequBl5zZW1BPDRKussi6zLxx8YdEj9X/7uc+oAbeeqGSdfPVaDfFOkcXQvtSljIWDmW8DNHZj+CvDygdP4rqH6/eWjlcCgA47uDdmCHLee3QzkqwkkT+D7rCtLnSXmsSqziToFZhQlInJxbvpO1hCRw3CfJNIW7pNE2sJ9koiIyPV5enpGPWk+EajYNf4X5KkaM7iCiOxPgjQkSDRrqVjT3YDS7dT/7/0LfJkDuLDTvHV4eFmlqxTPmKtz4Afg137mLfB1ADC1PHBwvoH5T4AV3dUsmGQdDUYCn6yLCtAm5xH8StJ9xrwp5so+4At/4PEV661HypszS6U2x1uhCwSVYLLRF4AyH6jPd88AJhYDQoPt10lnIyW93T2ApCmsF1htD3U/B6p84uhekC3JWL6wNfDiHhK1t6+AlZ8AN48BlT4G6gy2y2rdJMiezMatR0SUGEsdEJHDcJ8k0hbuk0Tawn2SiIjI9YWGhqo/SBCRBBQlRLLebRkLPE/kF+GIHEGyn13cpf4smUQLNzDcNkNBoOV0IG9109axYzLwbW3L+kkJj7nRNf4KGGRmCV+fNMCAfVGBTrFJ1kvJOPrmqXnLp7gK1FH3L25T55OpCNBnM5AyXdS0LCWBDouBFGmtt57lXYFlna23PLLeeBtburxR2QfLdwT6beeNEoac3gAsaquWcF8zCDi0EE6jcMOorN3bvgF+7uvoHpG1FawLfHUVyFQYiZoc9909BVw7BDy4YLfVRrzjNQRLMFCUiIiIiIiIiIiIiIjsSwIa1hqRcSQ8FPjzW+DJNXv0ioii2zUNWNoRCAlMuK1k/KreRw14kQBTY2UpARRubFE3yURSAlnKXpvq8l4gIhzIVdFwmVUvb+CL4+aXtae4zm8DxhUETq11dE/IVAHX5I7YmNO8fdVs6tYsz9viG6DBCOstj+wXSJy5qHNlyrSrd0ASd3X7hAWr3wmcKchVFzQnQeG+GR3dI7KmgOtqAHOanI7uiTaqDnz+F3DvNLC4naN7Q0ZioCgREREREREREREREdmFm5SoFr02Ao2+TPgFqTIDkx6rJeiJyL4ajwEG7lezBRnrwHxgVFYgLMT4rFt1h5jdRTJyzI1OSl4v7QQ8u2P8gp7eBObUBY6vNK59eJjxy6b4/dQVKNQAKNbM0T0hU4S+VQN8D/4Yd54EkO2YYr11ZSsNZC9jveWR9cbbhJzbBvz0sS264/yKtwA+Xq3+/P53QLXecBo/fQScXqf+XKUH0Gi0o3tE1hL4DJhUAtg719E90RapKvDxL3ZbXRIG2FuEgaJERC6OH5RE2sJ9kkhbuE8SaQv3SSIiokT0ee+XFUib25gXMNMSkb1JUODtk4C7p1om19RSnO0XqpmWEiKBipf+ZFCh3b9jJVH/xsGvjQt2k7+lfw5g8CGgfKeEX7N+GDC1nFn9JT1GnVeDL1Kmd3RPyNQsa322AsWax5338Dywayrw5qnl65Fl7JwKvLhv+bLI/ue0JFPmq4dASJAtuuTcJJt59Iy8zpRRdNxNoOZn6s+h8jd+7OgekbV4pwa6rgLKfujonmjHrhnA+EJAxoKO7gkZiYGiREQu7p0xJ+SIyG64TxJpC/dJIm3hPklEROT6wsPDTX+RlJ6fVtEW3SEiQ/vcj83NC8qQAPCyHwCeSRNuK6W05zVUy5mT/cbcdHmAgfsSvqAvQTrTK0VlzcpRzrjA/aLNgLpDzewxxeHjD5z8Bfh3k6N7QqaQQPsCtYHUWfTvI988Uv+2lpKg763jgDdPLF8W2f8Yt3hzoPcmwMvbFl1ybgtaAf97X/355z7AtEpwGklTRP1N984BxuZzdI8oIa+fqDcvxUeOV+U4qGgTIEVae/VM+7IUV4//7Xhen9cQLMNAUSIiIiIiIiIiIiIi0q5MRYFiLex68YkoUWsxGfh0pxroZI47/wA7pyXcrnpfYORZ44JKyfqiZ2rTxys5UOZDIF9N05abpwozbVmLZKFb2gnYMg64ss/RvSFT7JsHnNmof567hxpsZI3jmmylgKkvgExFLF8WOW4sDrjm6F5oj9xwUONT9edyHZ2nfLtk6178PnDzuPq8xHtAlxWO7hUZuiFGPmMfXwG2fwMs76JmgDVE5q8ZZM8eOgepJjDwAKuAOBEGihIRuTiW7yTSFu6TRNrCfZJIW7hPEhERuT53d3fTXyQZuRoM58UnInsFpkkQU4YC5i9DAkX3zVXLlsfHzU3Nbkn2H3MnlwHWfa5/3pGlarZXUW8okKWYaSsNC1FfL5kOyTKhQep27LkBeG+yo3tDpvh3I3DjSALZ0itYZ11yfMRjJOc8xhV7ZgETi6tjJ8U8/s9bXf05d2WgeAs4BQk0fPM0Kit7urxqBkrSnrcvgQfngZcPgWYTgM/2xH/zktw4k6O8PXvoPOz8GcRrCJZhoCgRkYtj6m0ibeE+SaQt3CeJtIX7JBERkesz+/P+9kng0WVrd8d5jS0A7Jzq6F6Qq7m8FxidDbh72rLlSOavr68DnskMt3l4Cfi+CYMJHTXm1hkClGip7wXAuc3A5QTKryZkYRvgwg7LlkGAf3Zg4D4gawlH94RM1Wcz0HSc4flZSgAlWyec2TchG0YCq3pZtgxy7DFu6bZAr42Am5mBpq7qr2VRmVaf3gKOr3KO6gIp0gCf7gByV1KfP7sN7P8BCH7j6J5R9GBeyfzqmxEYekzNhC4BolI+XQK2V/YA7pyK+7rK3YGyHziix0RWxUBRIiIiIiIiIiIiIiKyiwhzAyL+9wGw7ztrd8d5+edwjovl5FyylQZazQAym5hB0lBZ5Yhww21C3gDhYUByf8vWReaNuVIaPk/VqOeS+UxKr8rfrctPQOtZ5q/UwwuY+ACo1M38ZVBMW8cD//vQ0b0gY+n2u/gynuWrAdT7Qs2sbAnJypyxoGXLIMce4/plA/LXZKBo7JLgUub7+mH1+bVDwJL26rGD1sU+Pn90Cfi1H/D6saN6RLGt6gH82EL9W8UepyUb/oNzwLNbUdMu7gLWfh5/WXqyKyabsIyHha8nIiIiIiIiIiIiIiKyLcm0lCqTo3uhHf22O7oH5GrkgmuylED1PtZZ3t7vgD0zgTGX9QdLZSsF9NtmnXWR6SRL2/2zQLFm6vM/RgHHV6p/r/gywRorZTrLl0FqRr1f+gLvfw+4ezm6N2SsdZ+rmZklq2B8HlxQg8fyVjN/XZU+Nv+1pB1XDwKnfgdaTXd0T7TBKzkwK1pQnmTAnv4K8PKBU2Rn/64+MOq8GsidvzYwO9TupbkpHjU+BV4H6P+bePsCA/ZHBfEHvVSz3987o94IQ+QCmFGUiMjFuVl6NyIRWRX3SSJt4T5JpC3cJ4mIiFyfp6eneS9Mnw9ImsLa3XFOz++qpWZvHnN0T8hVSObP2TWBU2utt8ycFYCanwERYfrnP7zIrLiOHHPP/AEsfj/qbyCl6CWTqDWCRMXfvwDLP7LOshKz7GXU8uXlOwL1hjq6N2SsQg2Ach0SbrdjMvD7IPPXIxks759TM+CR8x7jipcPgCv7WJ48OgnK0wXmSVlw+R7gDMGW6fKqWblTplefS5+dod+uTo53Di9Wx80c5YAijQy31Z2f/nMOMLkUULIN0GcL/44a4paE1xAswa1HROTizC51QEQ2wX2SSFu4TxJpC/dJIiLSiufPn+PLL79E9erVUbp0aXz44Yc4fvy4wfZ37txBz549lbZVq1bFrFmzEB4eVXK5U6dOKFCgAMaPH6/39fPnz1fmDxs2DK4uLMxA0FhCHl8FlnVWL6QndlIeevtEYE4dR/eEXKnEa/oCQOps1ltmjrJAzU8Bdz2BM09vAeMKqsGK5JgxV7IQ9t8NfN8ECHymZgCVUtjWZChImIyXqQhQawAQ/Bp4eMnRvSFjFaoPVOyacLsWk4AB+8xfz4u7wIQiallkct5jXFGqNTD0GJDUCTJm2sONo8D8lurnk3j5UL254e4ZaJ5fVjU7u2RpF5K5cm4D9Xcix7n3L7CiG3Bpt/GvKd4cqDlAzTLKIFFNieDNZhZhoCgRERERERERERERUTSDBg3CyZMnMWPGDKxZswaFChVCt27dcO3atThtQ0NDlXli9erV+Oqrr7Bq1Sp89913cbIMbd++He/0XNTYvHkzkiSSi0/6fn+juLkDjy4Db55Yu0vOR4K5vrwEfPano3tCrkKCGdrPV4M7rUnKKktmydgky1bf7dYPTCTjx1z5myf3A0KD1EBhayvdDuiy3PrLTWzunAJu/AWcWA2MK6BmQiNte3JDDYIPC0m4rW8GwMvb/HWlSAcM3A/krmz+Msjxx7jR6QIjEzu50SAsGPBIqj5381C/A4Q5QfbcgGvA2c1Rz9291EBD+S5DjpOlGPDNIyBvdeNf459DvemJNIiBopZgoCgREREREREREZGTun79upLx8N69e8rzQ4cOKZkPa9eujYEDB+LRo0eRbTdt2oTWrVujbt26SqbE169fR17QWrBgAZo0aaK87vPPP8eTJ3EDsX799VdlfnStWrVCyZIlUapUKeXRt2/fyHkVK1aMnC6PCRMmKNNfvXqlrEPmV6lSRcmwGBKiXkiN3l4ehQsXxscffxzvNjh8+DAKFiwY+fyvv/5SnkdfjmRzlG1FZIybN2/i4MGDSsBn2bJlkStXLowePRrp06fHH3/EzX63bds2ZR+cMmUK8ufPr+xjEmi6dOnSyPe2qFChAh4/foy///47xuvlvXnjxg0UKVIEiYGbrpSfqdLkBIYcVrOrEZA+H5CttKN7Qa7g6HLg5G+2WfaZ9cBvn8UNbpPy5oXqAd6pbLNeMm7MzVAA+GwPkDqLbVYu5bBtEYSamOyeDqwdAhRuDAzY6+jekDH+3QQsbmd8+9+HADunxZwmAYeSST0hMpbmqaoGfZPzHuPq7P8e+DKHcUHGrk6Cn/tsBrySq89TpAE+3amWDNe6MxuARdHGAAkS7fYrkL2MI3tFQrKne3g5uhdkBYnlJltbYaAoEZGL4wclkbZwnyTSFu6TRNrCfZLI9NJ248aNiwxEu3v3LkaMGIEePXooWQuLFy+OIUOGKIGgp06dwvTp05Vgty1btsDHxwdjx45VXrd161bs2rULy5YtU16XOnVqzJkzJ8a6dEFw0UlZ7StXrmDv3r1K5kV56DIoPnz4UOmfbro8Ro4cqcyT5QQHByvrlKC7M2fOYPHixcq86O03btwIf39/JeDOEAl2leXGzt6SOXPmyOUcO3ZMKQf+xRdfWGW7k+vz8/NTSsEXK1YsxmeUPF6+fBmnvZSklyDPVKmiAp4kEFren+fPn4+cli5dOiXwVPa52NlEa9asieTJ/7sQ6uIsvogeEmStrjivP0YB8xoBW8YBb185ujfkzOTz8581wPXDtll+9b7A2Juy48ecvmEEcO2QbdZJ1h1zzRURDgz1Aw6rx3hkprZz1QCj1JnVLGiO+nuS8aTk9NfXjQ9GkoyikjVR9plg9UY+HF8FjM0PvHoEhIcCz9WbAuM4txXY/4P1+k6OHW8L1gfaL7RWd5xbaLD+DMrOkFW5ai/gqysxp8lNE/wO41hLO6pjK7kIXkOwBI8miYhcnFVKHRCR1XCfJNIW7pNE2sJ9ksg0EthZokSJGJk1JbBNsn56eHigS5cuuHPnjhLMuW/fPiXLoWT/lPLXn3zyCQ4cOKAEvTVs2BD/+9//kCZNGgQFBSEwMDBGwJvsmxKMKdlIY2dBlEDO6G11Lly4gAIFCujttyyvT58+SrCqvL5p06b4559/4rSTrKcdOnRA0aJFDW6DiRMnon79+vFuJ9kW8jtKn4iM4evrixo1asDLyytG1lDJNFqtWrU47R88eICMGTPGmCbZR8X9+/djTG/UqFGc8vMSvC0ZfRMLCSI3mwSXTSiiBrclZpJd1TM5sG+uGkRCZC65UeuTdUDLWNnsrCVpirjBUpJl8twW4OlN26yTrDfmWkJK7HZaChRq4Jj1uwrJROebEXj5ENgxGXj5wNE9ImPGVfmbGavpOKBGP2BiMWCrWoEBhRsCvTcD3qmBJe2B/72v/7UScH/yV+v0mxw/3qbLA5Rux4yHQrKRT68Yc9qYXMDWcdA8yfQbewwYlQ3Y+62jeqRtJ9cYDoa3Fvnu6O6lBuWTS3j3zgmCxjXMw9EdICIiIiIiIiIiItNcvnwZO3fuVDJxrlqlZkWIiIhAsmTJ4mRAlGDR2PMk24lMk0yhUqbd29tbKS0/Y8YMJcBNStHrrFy5EmnTpkWtWrWUADcdCbyU5bRr1w63b99GmTJllIylGTJkUOZJEGrz5s2VMvbVq1dXgk1TpEihlJqPTjKSSon56CSI9dq1a/j+++8NbgN53a1bt/DNN98oga6GSMbVtWvXKn0gMoeUih8+fLgSlCyZP2N7+/atElwaXdKk6kUoyZ4bXYMGDZR9QLLdSqbbS5cuKcGkEpgqwd/GXoQODQ1VgqAls68Encq+7u7uHnmBWn4WMl/E11b2Y5lmj7Yy7ujmS9C6/B762spyZJnSPkbb4i3hlrU0koSHI/y/YFF9bWUdMk2WK4/o2yV624S2oSlt7bW9pT8R5bogSfmuynNlu4SGGr8NTdne/7W11zbU7PaOiFCmR25vM7ZhQm0d9p6V5//9bvKzTbbhn98iyb+bENF7s9oW7sDgo2rbiAi929vS96xmt7cD3rOG2tpljCjWMt73litub2u/Z902joR7zgoIS5cP7jumICJfLbilzOBS29Cc7a3ZMeL1Q7z7X3uEt54N96zFTdvejcYgPE1u5TPdI7kfwvPXUdvWGgR3T2+E6et/g9Emj9/2+lxLjMcRum1r0fa+fRJu5zbDvfGXifpzLaJsR6BQI7i/exfZ1q3RV3DLVFj/vhBre0f8F0Qm/8t2tOcYgcP/w7unNxHR8L/9U5bzwY9A+gLK76PF7e2wMSLoBTwWtwM6LUFYqQ+M3i7yd5Xn8k/mGbUN2y9Ul/tfHxPb9naVMUL9q6s3oCd0TsRZjiOSOKDCGgNFiYhcHMt3EmkL90kibeE+SaQt3CeJjCMnJ6XkvJRSjx78WaFCBSWw8siRI0p5awkglQA2CZSsUqWKUpZeshnmzp0bCxcuVE5Q6srWCwnqbNasGWbOnKm0lTYSALp06VIliDR2Rk45sSkZTKUfklVUsntKqfvly5crJzsle+nAgQOVtsOGDVOC4yZNmhRjGVOnTlUCQuX/6CQA9qOPPoqR0TG6Fy9eKOuTgFZ9Y4cEwMo2EJIhVU7Mfvfdd2Ztb0rcJCBb3tcS1Dltmv6Me7IfRt+XogeIxi4nL5l7y5Urp2QolWVK2fl69eoZfK/rI/uXXHzQ/Rydbrq+EphaaCvjjgTR6qbF11bXPsZyc5ZTH3rKpUVvm1CfbNXWXtvQPeAq4J9ducRj8jY0s629tqEmt7eVtmF8bR22DU+sANZ/AUy4Cw8PT9tsw/T5gNyV4Cb9SpIEnknexciWlqi2twPes9HH3NhtbT5G3D8LXD8Mj8rdE27rItvb6u/ZJ9eAtLngUao1MOWJhFm73DbU1PY2sk8G24YEIknKdHBLlUFWYNpyy7wf49gmsm3uSmpbuUEmIkwW6BTbMDEeRyjB3f8FBUXvj0nb8MlV4MhioPZAeCZLGX/b2L9r0Evg9t9A/ppOuw0j2+arGrdtxS5q2xgt9b+/3ZKo0+T/6Mu2yxgRGAC8ug/36N/XSrfR9vZ21BjhmRYYfAi4tMek7SJ/V+XGaKiBgQluQ8lY6p0KSOqTaLe3q4yz6l9dbWvOOREtbm9HYOl5IiIXx/KdRNrCfZJIW7hPEmkL90ki4yxatEgJMItedl7kyJFDyegpgZ4S9CkBpbly5VKyeErQpJSblwBQyQCaJ08eJYuozIseSCABb1IW/t9//1WCMSWLoi4QNDZZx+zZs5E5c2aljLwE0x09ehSvX79Gt27dlGBWKS0vj/79+2P37t2Rr5W76SXDqATLLVmyBH5+fpHzHj16hGPHjqFFixYGt4EsW8rSZ88ugVJxSZ+OHz+uPOR3kX5+9tlnOH36tMnbmxKvn376CZ9++qmSTfeHH36IzBIam5Sdl/dtdLrnkmE3tsaNGyvvffnck7Lz8jwxsfjz/uYxYKeNymQ7g+DXwLgCwMnfgGmVgGMrHN0jcmbZSgP1hwPuscMurKhIY6DJ12o5ZjGjCrDuC9utj7TzHevqAeD3wUCEmnGJzND9N6Bab0f3gowlgfHyN0uVybrLlcxjc+tHlaYX4WHA1/mAU+usuy5y7Hhbqg3w9XUgVpCoUc5sAL6tBTy9Baf3z+/AvX9jTrt1AriyH5pX7wugfVSFFsW5bcDlvY7qkbYFXAe2TwTevrLdOn4fBMxraLvlEzkZZhQlIiIiIiIiIiJyInv27EFAQAA2btwYOa1jx45KoGahQoXw888/K9PevHmjZAPNly8fnj9/rmQcbdNGzWQhJdslkFQCLaVsu2Q/7NWrlzJPMiPK3e2SiVMCKyVQVEhZpaCgICXodMOGDUpQqJSkr1q1auTrdHf1y3olmFUyjurm6TImys99+/ZV+iR9lQyL0e3fvx/ly5fXG5yqs337dvz555/49ttvI0s2Sb8kmC826VOdOnWUTKqSbbV48eIW/gUoMVi5cqUSkNypUyclqDm+rNeSIXTdunVKkLQu+FreaxJAXbBgwTjtJYPo2LFjlfe/BGRXrlwZiYnssxZl0Lh9Eji0AKjZP0ZWQqs7uQbIWR7wywZNcfcCPvsTyFAQuHMS8LVyMAolLllLqA9be3YHeHIdyFsNqD0ISJ3V9usk64y5lqj0MVDlk6ggYTKfBKBJkHXtwYBkFyVtenYb8EkDeMXMKG8xyVpW/D0gY7TjyvAQoGRrwD+HdddFjh1v3f57fViI6ce5ZdsDOSv8l3Xeya3upR7rZy4aNW33DODFPeCzPXA6u6YCKdIB+Wo4uifasqonkLkYMPWFbY8VGn0JvH1pu+WT3THZhGWYUZSIiIiIiIiIiMiJSHDZrl27lJLY8tBlPixatKiSNVSCQCWgc+7cuUqwZvr06XH58mUlq+eTJ0/w6tUrJcCySZMmSjkked3vv/+O69evK6Xq58yZowRWZsqUSQkU1WXmlCBMXaZO+f/Zs2eYMGECHjx4oASlTpkyBQ0aNFCyLkrJ+smTJyvBoE+fPlUyeuoyhErw3cuXL7Fs2bI4QaJC1hk7W6q+Nrp+SdCqkJ915eZj++uvv5RtkNByiYTsCxMnTlQCOnv27KkEZj9+/Fh5yP4jwc7ys67cfN26dZEuXToMGDAAFy5cUPbLGTNm4OOPP9ZbUl6y7Erg9tSpU1G/fv04ZckoAZW7AaMv2DZIVC48/e994I+R0Bz5veUis28GoNV0oEBtR/eInNnFXcDjK7ZfjwR3LO2o7ltlP1QDRsn1Saba+AI/nt9VMyM/uKC+N46vAoLfwKWd3w6cUG/qStDLB8DglOprZDtmLQn4+Nu6h2SJeY1slzG5Rl+gQJ2o5xKM2mISkK2UbdZHjvPXMmBUFiA81Lj298/+l232nZrVVrI4P70JpzbhrhoYH12774BeUTfLatacusDPfWJO670Z6LrSUT3SLi8fIGkK299QkqkwkKuibddB5ER4BoqIyMXFl/GCiOyP+ySRtnCfJNIW7pNElpHsoJKps1+/fko2UMnK+dVXX0VmPGzatKmSeVQyg9auXVspxa6b17t3bwwcOFAJFK1SpQoGDRqU4Po6d+6slNdu3bq1Ephao0YNJUuikNdLQKgEjsqd/lJaW9YnQXa//fabEhgXPYtimTJlsHDhQuXne/fu6c3CKIGqEgyqaxcfWUapUlEXTSVYdtSoUUpwHlFCpCy8ZNzdsWOH8oiuZcuWykPe/xLsLO8pCY6W9+XXX3+Ndu3aKdlw27dvjz59Yl0gjKZRo0Y4ePCgErCd2FgcGKvLtBQaDHgmhU3IMcnQE9rMenjzGHBln5qV8c0TICTQNTJHkWMs7QRU7g40VT+/babeUKDhKODCTjV4MH9N266PIjn8ZoT576mZECt2jTtPgkJTplfLdEuJ4aUdgH471QB4CZCS94qr+d+HasbJMu8n3NbTG2j8FZA+v/r8/Xk27x5ZqP1CIJmv7ZYf9AJY2R2oOQBIk1PNkJexkO3WR44ZbyUraKOvjB8Hrx4E/v5ZPTb08gZ+7gtc3QeM+FfNRuuM5PeO/bsnTw2nULkH4B2rr7a8wc2ZtZ6h/r+yh/q9q/EY66/j1gng/DY18NhW3x3J7pIkcdKxTSOSvGNOVofau3evklHh6tWrSJ48uXJCffjw4crJRJk2adIk5QS4lCmSk47Dhg1T7k4XUpZI7jqXZUhmBl9fXyXbg5RC8vb2VtosWrQIq1atUjI7yAlxOXEvJyh1F9+kRNe8efOUjAqyDjkxKRcFkiVLpswvUKCAkhlCSpn9/fffyjo++OAD5YKDPpIN4tixY8rJfPl9iEgbpQ6kzB4RaQP3SSJt4T5JpC3cJ4m0x8/Pz9FdIKJY514luFvO0zqrsLAwyy+kH1wAbBytZhvSBY5ay5k/gIcX1IuJWjwu2f8DsGMSMPYGsPh94HUA0H8XnMq/m4DCDa3/tyPTBT5TMznaK0vhjy0ANw+gxxr7rI+sM+Za4rcBQL6aQIn3Em4rGfD8sqvB+gtaA8GvgG6/Ad7O+5kXQ3gYMMAL+OBHoEoP01//6rH6f0r1OjElQhERwMJWQJWewM2jwIEfgIn3Hd0rstV4GxIEeCQ17ng0+g1U988BIW+AHOXglJ7eAn7rD7SYAmT4L1BenN8BHF8JdPpfgosYPGsNnr0KhF/K5Jg+oDUc7sB84N4ZoN0cR/dEOySruGQT9U4F7JwKpEin/6YSS/++kqF3y9fAmCu2z1xKNqf726dK4Y2ZA9s4ujtOS4NnORIPCe6UgEsJ3ty8ebNSDkxO9EmZrocPHyp3nefIkUPJsiAZE16/fo33339fyQghJGj03LlzyuvkLncJMF23bp1Sfkzs3r0bP/74o3In+/bt2zFkyBB8//33keW45G54yRZRs2ZNpbyYtJN+xM4YIWXC5C75TZs2KVknpPyY9JOIiIiIiIiIiIiIyBRWyV2Ru4qaZc3YkpymkIu41w4CT64Dq3urgZhaUq2XGiQqGo4GWs+CU5GMqD80VS/akuMl97NfkOi+eUDqLECnJfZZHykcni+ozay4QaISMLmqp1pyPjr/HFFBHJJxUwIqXSVIVLh7AFNfAGXbG196/uKuqM+6+S2A9TYqa06We3gJ2DkNCH5tu3VIwOAn64AijYBqfdRy1uS64+2v/dSszIaWK4GTcvOUzI+eKVHKbEuQqEyXMvTOJiz4v2yqsYJuJfj1+R3D20MrZNyWGx+ik882BinGtGE4MKeu+nPdz40OEjVZhc4MEnVJGh8HNI6l5x1IgkFDQkKQOXNmZMmSRXlIQKiU/5IsoBkzZlRKYunMmjULFStWxNatW9GqVSulDJjcPS5ZP0XWrFnx008/4dKlS8rzW7duwcvLS1murEMeklVU/hfz589HvXr1Iksg5cqVSzmAkRJlV65cQd68eZXp7733Hlq0aKH83KtXLyVLqWQXlXUbIr+DPCQTjGSE0Yn+XJfVVHfQ5Ki28tA9l3nyOt1r3d3dld/Dlm21ul2s1dYe2zChtlrcLtZsm9B2kecy31bbW6vbhWOEc7RNjGNE9GlaGCNsvb2d4X3IMUK7be2xDWWalsYIe7flGMExQmvbUET/XeNrmxiPI+zdlmMExwjdvFOnTmHMmDG4ceMGChcurFTAkTL3+jx//lw5byUlueVcldi/f79SAUcyrHzxxReR55m2bNmCM2fOYOjQoXqXRUSuSTfeWEQugMvDFhqMUDN2BVxVA0ZfPQRSpIUmZS4Kp5O9LPBtOC/WasGNv9TgzXZzgWQpbb8+yYomD3usi6w75loiLAR4dhtIlydqmgT6XNmnluc1pHQ7uKTbfwPrhqqZoCWTWkLBRks7AjPeqCWYW89M+DXkOA/OAVvHAtX72icb9O7pQIORtl8XOW68LdcReP1YPWaSgE8ptRx9HZf3qGNKpW5xj6vke73cmKOUsf8STiV9PqD3prjT5aYDY7JTO5oE9zYZC9QeGDXNnCzSrq7RGOBNQNQNJI8uAmlyA15q5WSr0AUVO/pYiGyAf1NLMFDUgQoVKoSmTZsqwZdSTl4CPyW7pwRvSqZQKQdfqlSpGK8JDg5WStILyTgqWUPXrl2rnKiX4M47d+4gd+7cyvzmzZtjzZo1aNCggRL0WblyZeVnXaCoBJRKqfnoypcvHzlPFyiaJ0+0L29S0SBlSoSGxn+ntlx4kIfu59jz4nudI9pGfx77IM4RbU3tv7O15fa2btuEflcpc6Brw21oXlu+Z+3b1tW3t1xw13fCwFFjhDNuQ621dfX3rNbaWnsb6gJFE+v25nvW9m05RpjWVrdPmrtcbm/rtuU2tH1bZ3jPyrkoualYKtvUr19fufF4wIABSnWa2OSc1cCBA3H37t0Y02fOnImxY8cq56S6dOmiBIrKuaXFixdj4cKFBtdPRK4pvnHHJI8uA+e2ADX7W2d5UtL3wnagzIcSLa9epB5xGpozv6WaUbXuEOD+WeCf39VAEWPKkmoBMyppR9BLNSDaK7l91le5m33WQ7YZc811dDmwqgcwIxDwTKZOS5MTGHk24XFr/w9qduf3JsMlXNkP/NwbyFrKuIzYJVqpWdA8/wuakYAv0i4JYCv+wj6fcW9fATsmq+8lyb5Lrjne5q8V9fPG0epn9kero95jzSeqwfj6xlJpU7C+ejzrbJTfycPwZ4QE/2n5WHL0hbhB/dJnyZSq+xwk9QYS3U0kD84D3xQHBu4H8lS13jqe3QImlVYDj3NVtN5yyeEcfiOUk3OSMweua/r06Ur2hO7du+PZs2f4/PPP0a1bNyVjg2QPlVLy0R9SYl43v2fPnhg/frwSBNa4cWOlzHzp0qUjl+3v74/169dj5cqVSoCoZH/o0KGDUqo+eoaI6HSZImSZOpKVNDZ9ryUibeL+SqQt3CeJtIX7JJG2cJ8k0p4jR44gderUys3Oco6od+/euH37tnLDcuwgUQkC/eijj+Isw9PTM3If1108++WXX5TA01SpUtnpNyEirZDswlZx9xSwSTLRPLXO8k6tBX7pq2bpik4y3GhJ9jJRF1UfXgT2fWfbMrfW9vevQL8kwJ/fOronVKgeMOgA4ObgQEJyjjHXXIUbAZ/uinqfHV4MPLtjXHC7BFOGBsFlyO+SKjPQ5ScguV/C7SWrmoz3umCIS3+qgbekXfYKXPHPDow4AxSqb5/1kePH2xzlgTzV1PfYX8uAM3+o0z3ixnFEqvUZUKQxnM7uGcCIjHGn3/kHGJBM/V/LUmcBvGOd5zg4HxjkE5XhMrG7dlj9HidBwSJDAeCzP4GsJa27HslkL/tB2piJ8cj5vXsXs0IZmYaBog4kgZsTJ05UMoB27dpVycggz+UEvGQYlRPsmTJlQo4cOZSHnDiX+ZLt8/z589i3bx9mz56NIUOGKNlDpeSXlJvXXVjbsGGDUsK+TJky6N+/v3ICvm3btti8ebMyX0rWSwn56I4fP643iygRERERERERESU+169fj6xeIyTQM1u2bLh27VqMdhkyZFBucG7ZsmWcZUiW0QkTJihVdUaPHo03b94oVXA6d+5sl9+BiFxU8RbApMeAj791llf1EzUDUIo0UdM2jACmaSyDW8NRQIn/xtqSrYBvHgDevnAaugvnyXijgMPpLs4T2VLqzGpWPCmdLlls/xgJnF5n3Gtrfgq0daGgcgnq67cDePVI3RYJObYS2Doh6vm5zerNAaRNC1qpWT7tJXNR4wKOyXUy1tboF3WzlGTVN4bcULWsC/DwEpyGBLe20TP2+2UHWk4DUmWCZgU+B1b1VLP+R5evFtBpKQNFdR5dUm/Sk2MDXcBzvhpxM7Fayjcj0OhLIGU66y6XyMmx9LwDpUiRQsn2KVkV2rVrp5TykiDOnDlzKtkZ5OS6BIH26dNHaT958mRcvHgR+fPnV8pzSdZPyUYqmUOfP3+OH374AY8fP0ZIiPrlXpYnr/Hx8UHZsmXx4MEDHDt2TPlZSBbTzz77DPPmzUOjRo2U8vXjxo1DrVq1GChK5EKYeptIW7hPEmkL90kibeE+SaQ9gYGBSJYsZnk0b29vBAUFxTnPZYhUzdmxY0fk8zlz5ihVb/bu3aucz5IbpuXm6DRpogVnEZHLslpZTt2FRamSZWnZ9dt/A9lKqxcTY2fCy1gImhESCDy9pWaY0/3+zhgoNZcXyTVheiU1O1mbWY7uCbly6XlxYD6QNjdQsK4akO/lY/xrQ4KAd+HWDx5xhNBgwN0DGJkZeH8eULVnwiVzH56Pev7eFJt3kSyQvRyQzgnLfJPzjbdlPgCylDCurVdy4OEF4OkNIEN+OIUsxdVHbHJzmC5YVqvkWF2+V7x9FXO6bHtn2f72ULGL+oju7GbgwQWgziDrrefsFvW7XJqc1lsmaQKvIViGGUUdSIIx5cS4ZBB977338OGHHyoHEAsWLFCyg/70009KhgWZ3rFjRyWgdNmyZUpgqGRpmDRpEnbv3q2UnZeAT5kmmUn//fdfZfmSPfTTTz+NDAQdMGAAqlatilGjRinzpRz9jBkzlGDTZs2aYcyYMWjSpAlmzeJJASIiIiIiIiIiUoNC3759G2OaBInKjcnmCAgIwIEDB5RzUWPHjsWPP/6oBJLK/0SUOOgqYlnFmY3AyExA8Bvzl3H1IDC5DHD1QNx5easB5TtBM+TC8/hCwKPL6nPJSCd9P78dTkMy6b1+ov5PjlV/BFCqraN7Qc405prr6FJg1zQg6IWaVViCJY0hNwIMSwccWgSX8EMTYHkXoNdG48pB1x+mlqkn59BguJrpmxItu423OcrFX3I+Os9kwJAj6o06zuL8DuDmMf3zzm0FAmJWN9FcFu2hx4BcFWNOfx0AHF+lfg4mdvLZHhEed/qdf4Dz26y7nv99APz9s/WWSeQimFHUwSR7pzz0KVy4MBYtMvzlR06oyyO24cOHR/7co0cP5WGIBJnKwxDJYBqbBKcSkXN9MeFdFUTawX2SSFu4TxJpC/dJIu2RsvNr166NfB4eHo5bt24hV65cZi3vu+++Q8+ePfHixQtlf5dsovny5cPBgwet2Gsi0rKIiAjrZVzKVASo3g8IDzV/GbkrA323Abmr6J8v2W2k1KWUeHW0zMWBAXvVzHwiqQ+QrYxzlZ5d1lm9CJw6CzD+jqN7k7iVau3oHpCzjbnmGrAPGFsAWDcU+NCEm4MkW3TnZfozyzmj2oPVoK38+q8LJ+jcNmDL18DA/YCbBjLFUsxy0y/uAenzGx8ITS5HE+OtPnKeTW7SObMeqPQxNG/jKCBzMTUgNrZFbYHGX1s366Q9BFwFlrQHhp9ync80c905CXxbCxh8WP0up9NghPqwFjmGGHcLeBdhvWWSZmjiRignxoyiREREREREREREpFeFChXw5MkTrFu3DiEhIfj++++VSjhSKcdUN27cwLVr11C7dm34+fkhODgY9+7dw9mzZ5E1a1ab9J+IXFzaXECj0UDy1OYFdZz4Wb14LlmWDN2s8nMfNQOQFnj7Anmrq4FGQgKF2s/XfyFdq5qOAzovBzosdnRPEreXD4C/f7EsGy+RsWSskiD3Jl+b/lrJ0JguL1xCkUZqkKjcgHByTcLtZ1QB/lCrRCqS+QIZClp2cwTZxsWdwIQiQNBzR/eESL8re4FfPwWe3YbmDToAtJmtf97oi0D1PtCsi7uAYemB53djTpcbu6a/VgNgE7uUGdSs9mkNnFOyZgCgZDF3phvqiOyEgaJERC6OGZmItIX7JJG2cJ8k0hbuk0TakyxZMqUs/PLly5Wg0UOHDmHWrFnKvCZNmmDDhg1GL2vmzJkYMGCA8rOHhweGDh2KVq1aYdu2bfFWxCEi1yL7v1W9fAgcXGD8RUVdu7Ob1BLAL+7H337ocaDZeGjCqXXAkSVxf//n9+A0JKi1fEfnKoHqim78BSx+HwhhoKirs/qYay7JIuyb0fTXPbkB7JgChIfBqYW+BY6tVMdsufng6LKEX1PxYyBfzajnuSsBHRdH3SxA2lGwnpo51yeNo3tCDqSZ8Vaf4u8BY28Cftmgee6eatZ8Q6XdtTwG+ucEag0AvGPdxCaZhuV34nlPwC8rUH9Y3L+jlKP/Oh9waKF11rN9ErBpjHWWRZqTJAlDHS2h4U8rIiKyBpbvJNIW7pNE2sJ9kkhbuE8SaVPRokWxZk3crEebNm3S2/7ixYt6p8+eHTMrSJs2bZQHESUu4eHh1r2Q/uCcmvUzbw0gQ/742/72mfq/ZCkq3Q7IXxtIlSn+16RIC824/Cfw9CZQsWvUtMXtgNRZga4r4BT2zAaylwHunAJKtwVSpnd0jxKnYs2BKU/jBjKQy7H6mGtvT64DW8epY3aanHBaksVvaQeg/x6g8zLjgoUqd4sbRPM6QN1vPZParKtkZta6vNUc3QtyME2Pt1KGW45pw0KAt6+AFBoNag4NBv73PlB3KJC7ctz5u2YAHkmBGn2hSeny6C+fHhIILO8K1PwMyFMFidqRpWp2bf/scbOPV+4OZClunfUon7M8x+yqWHreMgyzJSIiIiIiIiIiIiIi57yok6caMDlAf5CoZKCTLJxSZl5kKARkLBKVrSihIFFx9zQwpx7w6jEcrs0s4JO1Mae1ngk0HA2nyai3cRRwfjvw+0Dg8RVH9yjxkovnUoqTN2m5PKe/kJ63OjD1hXMHiYr0+YDpr9TAJ2P2OwkKvbhbDQzVeXgRGJERuHXcpl0lM/z5LXBmo6N7QQ7mFOPtnDrAGrXKhyaFvY0/g/SLu8DLBKoBONLTW8C1w3Gnu3kAQc+B8BAkam+eAiu7q5nt9an3BZCzgnXWJctq8pV1lkUa5ATjrYZp9JYGIiIiIiIiIiIiIiJyNVbPHi6lHCWTl1yc1y07PFQNBH0TACxqC3RaApTrAFTrZfryk6YAkqUEgl8DKdNBc7KVhtOQEpMSKBURATT5mkGKjrRhBJAyA1Drvyy75LKcvmKDZBhzFfJ5Is7vUIPmBx1QP6v0CXymBnT1+B0o0VKd5p8D6LkByFDQfn0m45zbCuQoDxRr6uiekAM5xXgrNxelzgLNkmP63vEEXbeaDk07sRrYMUnN2h6dhxfQb7ujeqUdPv7AtBeAobLhcmPerWNAkcaWrSfohXrDhayPXJQTjLcaxoyiREQuzim+mBAlItwnibSF+ySRtnCfJCIicn3u7jYI+pGsNF/lBl4+BPbOBSYWV4MRfTMCYy6rQaLmSptbDdRJmwsOJRc7xxYATq+POf3GUbUMpzOR8qc87nP8++ldhKN7Qc465trbxi/Vkr3O7PgqYOUn6s/JU6uldcOCDbeXjL9fXQUK1I2altQHKNZMuyWjE7M+m5m5jpxjvC1UH8j0X3Z9LZJsonKM4qyqfAIMMZAtU25qk+8niZ1XcvXmMX0u7gK+b6JmHrXE0Z+AkZmAsESewdWF8RqCZRgoSkTk4pyi1AFRIsJ9kkhbuE8SaQv3SSIiItcXFhZPOUlzpckNFG2mZhLNVQmo1geI+G891ihXLMt9fg8OJRc6i7cA/LLFnH77b+DP2erFZ627dgiYVUPNFrSsC7BvnqN7lHi9NxmoPdDRvSBnHXPtLX1+IHNxODX5TNKVHM5RDmi/ICrDqKFMqnKjgmS0ju7gAuDOP7btKxG59nj74AIwqybw8gE05+RvwGdewNtX+ufvmAJ8lReaJTcCpM+nf97X+YDNY5CoLe2o3tRnSNEmwPg76s0SlijxHtD9dzWTK7mkd7zhzSIMFCUiIiIiIiIiIiIiIuclJeHbfgv4ZQWylwFqfmrdC4O/9AO+t7AEoqW8vIH3psQtNV+tFzDupnNk6PRIqga6SlY8yfYq5UXJ/iTwOfiNo3tBZLzyHYE6g+DUyncCOi1Rf5bAfgnQCn5tuP3dM8Cv/dXyudGtHwZc2WfbvpJpzu8AxuRSs5oTOQM5BpOMjpZmbTSUEXRcQeDSn+a9XgLp3//ecCB9vhpA3aHQrGMrgD+/1T+v6TigWHMkaqmzAinSGZ4vN0ekzmL59xpZhgSdEpFeHvonExGRq2DqbSJt4T5JpC3cJ4m0hfskERGR63OKspyxVe8LVOji2D5IFs43AUCGgs4RFKqPBPF2+SkqoyU5xs3jwIzKwPDTQJZiju4N2ZhTjrmxSaneRxeB5P6AbwY4pZBAwNNbHb9D3wIjMgGdl6kBpPq8fgxc2gMkiZXzaXKA834GuKrUmYFS7YAUaR3dE3IwpxlvJetl3622Wba7hxoMf+80kL+m6a9Pl0d9GJKzgvrQqvvngOd39M8r+6G9e6M9LSYl3GbbN+rNZNX7mLeOoJfArqlA5R6Af3bzlkGax2sIlmFGUSIiIiIiIiIiIiIiIkOyFAdyV3ZsH06sBiaVjDv9yQ1gchng9kloXuCzqOx4ocHMvuYoEoDReXn8gRhEWiLlRSeVUsdBZzWuELBpTFSG6J5/APnrGG5foDYw8kzc0vMMjNCeTEXUmx/cnCRIkEjnzing9HrD838fAkwuq2YiN8WXF4Ga/c3r07VDwOW9hudLFtRzW4GQIGhS8wlA56X65934S/39EquAa8Yd+79+pN4cZ66nN4CD8+PP2k2UyDFQlIjIxb2TO7eISDO4TxJpC/dJIm3hPklEROT6wsPD4XTkGGXPbODaYcf1ocwHwIB9cYOEkvkC2cuqmeq0bsMIYPZ/2aW2fA1Mr+joHiVOKdOrpby9kju6J2QHTjnm6stQN3C/4zM7W6LVdKBkq6jnxZqqmShN9ftgYOsEq3aNLHTrBPD0lqN7QRrgdOPtwR+BbRPV41wdCQqVrMfCLxvQfCLg7mnc8uR10yqpgZ5Sgt4ce2YBW8cZnn/3NDCvkeGsnVq2/Rt1eydW8j1gYbTPQUNazwQafWnZDX4THwAZC5m/DNI8XkOwDEvPExERERERERERERERGSLBmQd+ULPa5a7kmD6kTKc+YvPxBz78EU6hWh+g9Pvqz+U6AvlrO7pHiZNk4pKgjwLxZDMk0poc5eDUSrWJ+fz0BvX/4s31t9/0FXBpNzBwX8zpyf0A79Q26iSZZXlXIF8NoN1cR/eEyDTNvwG8fKJuQooIB6ZVBIo0AZqOBWp9FjXdmIy5kjU+XV7g3Bbgh6bA1OemZ9rtuiL+bKFSdn7cbcA3IzRJglizlARafBN3XqelgFsiDs9qOQ1488S4tlJ5QN47cqOIqSSAkNm3ieKViEciIqLEIQkPhog0hfskkbZwnyTSFu6TRERErs/Dw0kvS4w659iLjn/OAdLmBoo2iTvvxX31YqpkitSyLMWifs5UWH2Q/e2dq2YTZaBoouC0Y66+Esn7v1eD8cwJHHGklw+Ai7uAYs2jSskfXaYGbBsKFM1dBfDNEHd6w1G27SuZrs8WR/eANMLpxlvvVOr/N48BmYoCXt5A9X5A1pJRbW7/DcxrDAw+pB6HxkfGrC7LgQfngTS51ayipgaKyrjoHU8GU+mjV1ZoVvH3gFSZ49/eiZVfVvWRkIcXgQlFgM/+BPJUNW0d8p4bmw9oMBKo3N3srpL2JUnC4umW4NYjInJxTL1NpC3cJ4m0hfskkbZwnyQiInJ9TleWU8fRN7Sc26xeyNdHyrnvmAzNO7IEuHFU/fnVI2Dvd8DrAEf3KvHp9QfQeZmje0F24rRjbmxvXwI3jgCvH8Pp3D4JLO2o/g463X4FPlpl+DWF6gHVeuvPshb4zDb9JNsGP5HLc8rxVo7HppYH9s9Tn1f6CMhWKmp+hoJA+U6Au1f8ywkJBM5uUUvXS8nvqp8AnknNy9Cry7isj4yBq3oB149Ak6r2BIo10z/v71+BNQORKF3eC6z9XA3kTIh/TqDdd0DaPKavJzwEqNYXyOWgChBkN7yGYBkGihIRERERERERERERkV047UWda4eAMbmAlw8dl7GsyVf653VcopZ117ptE4Dz29SfJdjr94HAk+uO7lXiI0HPnskc3QuyE6cdc2PLWw0Y/g+QKhOcTpFGwPRXgG8m428+kODSgGtxp/8xEpjOABjNuH8W+OVT4M1TR/eENMApx1vJRj/spBrgqI9kIG85NeFg6Iu7ge8bA09v/vd8l5qN1FQSUC/BpvFlHL11XLs3GskNURJ8a+h3kyoAiZFsk8t/GpcRXAKM5f1ozue9vF/rDgEyFTGrm+RMnHC81RAGihIRERERERERERERkV0kcXRmTnP5ZQNKtdXmRanclYB0ZmTdsbcxl6PKJmcsDMwKBnKUc3SvEpdnd4DZtYB7/zq6J2QnTjvmGhLhhBn7RNIUgFu0y/Jn/gCmV5bIMv3tV3YHdkyJO71CZ6DNt7brJ5lGbh65vIfB9+Tc462UmpcxKr5xV7LC3zxuuE3RJsCo80C6vOrztUOAgwtM70uP34FSrQ3Pl3H0i+NAsabQpFnV1Myh+lTuBny8GolS6bbAkL+Mby83SxjajoZERAB7ZgPP75ncPXJGTjreagQDRYmIXJzTfjEhclHcJ4m0hfskkbb8n737gHKiasM4/tB7byJdlKbSERGVpggiXQVFVFAExAIWwIpdrCCIiogVuyLSQSw0QYqoiJTPRlFUpPf+nfeOWbZvtmaS/H+cnN1kJpObkHuTnXnmvfRJAAAiX44cORS2QdFOT0qFT8r6x/5jpfTAqdLmn5KeznHBywoLge979pPvflnPqnQVKpN8IAQRJWzH3MS8fZ30cieFnTlPSZPviXtb/uJS2TOSrpzX5xOp7X0Jby9XW6rZOnPaidSr3lK650evih2iXkSNt7Flyy59NlxaOyeZdbJJJ9U4cf2mOd704alhgdRwPRkgYMi3Uv3LQ90Kf7Fqs4f2xz1ZIiXfT5QmD03d4/z7izT5LmnL/1LdRIQfjiGkD0FRAIhwYTnVARDB6JOAv9AnAX+hTwIAEPmOHDmisLV9o7Rhefq3YwdLze4t0qhW3rT2yclbSKrb1ZseNDE2lePXaajalJW2bZBGNotbyfL1HuETcI0UJat41axKVA51S5BFwnrMjc/GwbN7KfwkEoyv2lS68mUpZ+7E71K8olS0XMLbbTr6BWOloxH0/xrO2IeBSB1vY7Pxa8gKqXUSwT2r/Dj6AunwgRO3FSyRumCgWb9UujWXtHlV8uuNvlD66Fb5kk15XqhU0q/TwDzSoX2KGvu2Sy+1kxam8vt+67ul+1MZ+Cx9mvTEv1LVc1N3P4Sl48ePhboJYY2gKAAAAAAAAAAAQEpmPuJVtEuP166QXu3m/V6guFSwpJQ9hQpUFurr9IS3bmIuHiYNXip/Oy4VqyjlLnDipsJlpbyFQ9mo6LPn3+gKKCCynH6xVLeLws4Fd0jtH0k4Re7OzdLBvQnXt2Uf3pL4iQmbvpPe7y8d2JV57UXw7ASIiXeEuhVA5sudzwtG79+ZcFm+olKZGlKuvHGnDn+hrRcUDJZ9373iZaloheTXa3y1VOti+c7ebdKkwdKWXxJfXr6u1PkZr0JrtMhfTLp7pXTOdal/v6UmaGzvTatGa9WdU/q7CgBBUQCIdJTeBvyFPgn4C30S8Bf6JAAAkS97aqsL+Umbe6UbZ6TuPnbgcvqD0sZvvetWDe/8G73f7UBm7/e96kNrkpnO0w44b/lZYa14Jemat7yKlgFdnpYadg9lq6LPxwOl55m2OpqE9Zgbn03TvnKK9O9vCisWrIpfedLCU/ecLP2UyGfK4f1epehdfyVcVrujNOqod6IBQq/pDVKtNqFuBXwiosbbxLzXX3qpfcLba14oXf583NssNJojt3RwT/DbL3ySdM71Ur4UTiI6q6dU6yL5cqz/fpK0b1vSFS+b3RQ3UBvJrMKsffaVOlXKUzB197X72Xtt2XvBrW9VaO0zNfbMBYhoHENInwj/tAIAAAAAAAAAAH4R1gd1ilWQipRN/UFSCwL9/o13vWbrhKGSFR9LY1p7U9EnZtaj0htXJf0YFkIdXl/avlG+dWC3tG9Hwtdm19+halF0anWn1HF4qFuBLBTWY24C2aTxl0mrpilsHD4o3VlU+ubNhFXW+k5OfIrcPAWku3+QzmiXcJmdYBBR/6dh7qyrpBoXhLoV8InIGm8T0ahHwunn7TuoVQ+N76SaUt9Pve/OwfpjpbQqiBOy7ASqXxfJd+xkqGHrpEqNkv4ubM8v/vfhSDXtfum55glPlAiG9aWi5b3Pw2DkLeSdjFfqtNQ/FhCFCIoCQIQ7npYvYAAyDX0S8Bf6JOAv9EkAACLf0aNHFbYC0wGv/iy4dW0KSps6cdB86bz+Sa9rUykP+1kqVCrx5Zc8Il31WtL3z1dMqnSWv6eyXDBWGlY57m1T75NGnBeqFkWn8nUSD6YhYoX1mBtfjpzSQ+ul8wcorPR6TzqtWdzbrPLgme29CnqpseNPbzrnTd9naBORBrv/8UJfh/aHuiXwiYgabxNz6nnS6fGmfJ/zlPThTYmvf/SI9104WEsnSB/enPJ681+Q3u6tsLNjk/TixV71y2hwZgfp7N5pP7mh+4ve52SwMxfYiVC58qTtsRB2OIaQPj7eawAAAAAAAAAAAOATFuz5a7W0O4gqmJOHelV0bKrkHLlSroJT8pSklxc92avMlFwFoytekoqWk2/V6Sxd+07c286+Vur+UqhaFDnsQOnMR6R1X3pTcq/9IvH1rILrnKelrb9ndQuBjFO4THhV1LTQSoNuUol4QXnz3URp1fSEt/88T7qvorR9U8JlOXNLufJnTlsRd1y1z/svRiS9zi8LvNBXaqbWBsKdhRw/uNk7Icpc/aYXhk/Myx2lCb2C33b7R6XBS1Ne78Kh0s2fy3fsRLIHT5P2bE18uU3B/sgmqfJZigp2YtLZ16T9/seOSlt+Tnk9m1Fh8evSoX1pfywgyhAUBYAIF/FTHQBhhj4J+At9EvAX+iQAAJEvZ86cCms3f+ZNNZuSJtdJbe5LOSQasOk76emzpT3/Jlz2yZ3S70uSv78FilJTtSmrlaqasApV2dOl6i1D1aLIYQfSf57vTf06/QFp0p2JT/O5c7M040Fp2/pQtBIhEvZjbnz/mys939qrVBcO/lojLZng9dP4Fr0qrfgo4e2Fy0qNr5HyF024rGBJqc/HXnVgZI7vP5HGX+YFdr96zpsuOjG1O0oP/e79nwCRON4mZv9Oac1saecf3nX7npvU9PIW6LRLaqpG5y+W8npWgd9OovKbImWlOl2Sni7dXis7qSvYvw3C1f5d0mtXSFt+Sd92vv3QC96m9PeNfS/4YIB0/L/wMqJCNj/PpBEGePUAIMJRehvwF/ok4C/0ScBf6JMAAES+iJiW8/DBpG//7EnpyCGpTHWp/mXBb9OCQUXLewfg42zzgLRqmlctJzmPni4tGi9fB2/Wxqv+tOsv6avR/g64+v1AvB2Et2DFjdOlVrdJnZ+SBs1PvOKiVZ59epdU9bxQtBYhEhFjbmy58kr5ikgHdiks2Lj37g1SYoGGflOkq15NeHvp06RLHpbyFEz6s8Y+G5A5sueU8hSSzu4lDfufV/U70fVyeNMdc8IrInW8TUyVJtJ9a7xw6KvdpFmPJT9V/SlNgt/2pMFegD4ldmLMu/2S/j4eKiefIXV6wvucSoxVYX3nBi+EHsnshCSryJwrX/q2YyeT3TxHyp1E8DbATuB79M+kPzMRkTiGkD4ERQEAAAAAAAAAQJYI+4M6P82SBuWVDu71rr/cWXrjvwqjh/dL0+6TNn6btumUr//Iq7wZmx1svvcnqV7X5O9/w6dSg+7yrbnPe1X14gdFJ91Bhcu0eq+fNP5Sr3qoBZZModJS7vxe4Pjo4YT3sUBTdg4NRpOwH3Pjq9xYuu5DqUBxhYVmA6QntiYeJkwqYLhtg/THD0lv856y0lejMq6N8ATCt2e2l3q+JuXM7VX+s0rf+7YnXH/KvcGF2hA1Im68TYyNW3axKuWlq3vTqSdl3w5p7hhpx5/BnwBzaH8Q6+2QNiyVDv33Xdwv7HutBSSTYt+//lol7U1iavpIUe5MaeiK9Fd9te+01Vt5Y7G9ton6r8/ZCSSIMlEw3mYi/hoEAAAAAAAAAABZIlu4V96qeq7U5l4vjGcaXy01uML7PW9hafByqcrZadu2TU1s0yfagfLUqtY86ak//eCWz6Ue8SqelqsjjTggVagXqlaFHwuhBKaw7jhcuvqthGEzCzQNqyIteSvu7Z89Ib15dda1Fb4Q9mNuYqxq8+5/FDZyJ1FVbcXH0sjmCW9f8JL0csekt3fFOOmMSzKuffCC9aNbSTMeSvhes4rdXzyb8D57tnhBOCCSx9vEWCX4+yt5FXXrX570ekcOShMHSZtXBbfdK17ywvUpqdZCGrLcfycMfP2K9FyL5Ne5baFUp7Mi1rqvvFkQMrIvTBsmPXNO4pW07bEerysdPZJxj4cwESXjbSbJmVkbBgD4Q9T8YQKECfok4C/0ScBf6JMAAES+HDn+q3wYrvIU8KYEDoh9sNcqBdm0k2ll1Zmeay5d+67U8L/qoEvf9g6Q2jSfNsV4UlbN8AKCja6Ub8WvZMl3v+RDS1bJ7s8fpSfqe8GCSo28ENPKyd708sUrJn7f/MWkzs9INS+Ke3vR8olXGUVEC/sxNzHjupyYut0qs1nlZZty1qrW2ZS+p5yTdP/Iah/eIpU6TWp+c8JlFnIqU92bjjj2+NhioNTov0rViUmpwjRSz8bbhj2kig3i3m6V7K6eIFWon/A+V4zNsuYhPETkeJsYG7uu/1iqel7KFSGf3Zf899fYJ8Ict7EwjF/DJtdJp7dT1LL/w49vlcrXk3q+nnHbPec676Qy+6yPL08hqeEVwb3HEFE4hpA+VBQFgAgXFVMdAGGEPgn4C30S8Bf6JAAAke/IESq+JKlYeemuH+JWZypdzQsMpXQA9Mcp0rK35UtW5WfE+dKaOQmXvdpN+jpepdFoZ9NO311W+mWhVLis1HWkVOy/0FvtjlLL270wRXKa9Eo45WejHl41XESViBxz7X188QPe73efJH3zpvf7phXS1Hv8VW00Vz4vbJhUVTwLG8YP0Vu4qmytpLe59guvahsyxrb13s/zb5QqN064vOaFUsESCT/XqGCHaBhvk3Jmeyl/0eTXsSBXsAG+3X9Lt+aSVk1Ped1df0t3nSStni1fKVI25Sr59n140mBFJPv/thObOj6Rsdu1yrWBE/PiV6e1k6MuHJKxj4ewcDylv4WQLIKiAAAAAAAAQARYtWqVevfurZYtW6pv37765ZdfYpZ9/fXXuuKKK9yyQYMG6Z9/Eh5AX7p0qZo0aRJz/fXXX1e9evViLnXq1FH16tX17bff6qWXXkpymfnqq6900UUXqW7duurXr5+2bdsWs9133nlHLVq0cPfr2bOnfv3115hlP/74o7p27eqWde7cWT/88EOiz3XLli0aMGCAGjVq5B5n1qxZMcvsOdauXdttwx6/VatW+vDDDzPgFQaALFDuzLihIasi2e6/QFRyur0g9Z8mX7KpR+0gb+4CCZcVOVnKVyQUrfIvq5jU9AapXG0vnGThpcJlvGXl63pVY616YkosmPtiuxNT1f+1JvFpO4FwU+VsqVJDL5TSZ5J0+sXe7TUulO763lvmF52ekM7tm/gyqyRqVVAP7Yt7+/wXpeXvJ73NL56RvnouY9sZrSxo9sCpXjA/ORZeG9nsRDh03RfSoHzetMcAkvblc95JQSmx74hXvCydXDvlde174/kDpOKV5SvffigtfiPlqqPxK75HEvt+GvjOmtHse+1jZ0oblnvXD+6R9mzJnMcCIhxBUQAAAAAAACDM7dmzR3fccYcLTc6ePVudOnXSwIEDtX//fv3xxx+6++671adPH7fMQpS2buwqvnv37tVjjz0W57Zrr71WK1asiLl0795dbdq0Uf369V34M6llFuK07T/00EP65ptvVLJkSQ0bNsxtc9myZRozZoxeffVVLV++XGeddZbuvffemOdg27XwqAVObZv2HBIzZMgQ5cmTR3PnztXIkSN1//33u6BswLhx41y7vvvuOz3//PN65JFH9PPPP2fi/wCAYGWPXzkNcVmQ76X20veTvOubvvMqTIazPAWka96STjlxMkKMriOkepeGolX+ZdUEOzwm5S2Uvu1YkCJnXmn/TmnfDumRmifeV4gaET/mnnmJVOK/sJBV7rSQyvql0ufPhrplXqjQ+l5SM2fs/FO6t5z0v3jVQX9ZIG38LwiTGJvy2S5Iv9OaS9d/JFVJ5PMptsInSSWresEkU6aGdOlzXtVnIFrG27SwE4JKV095PfvOc871XnX9YE6oaXufVKaafMXG8tUzk1/n7Guk6q0UkV67InM/e6u19E4OqVDfu753q/Qv+3iiFVPPpw+fVgAQ4figBPyFPgn4C30S8Bf6JJB2VnmzQIEC6tatm3LmzKm2bduqYMGCrkrookWLdOaZZ7pKm7bsmmuu0aZNm+IEJy1s2bx58yS3b6HLqVOnuvBnSss+++wzNWjQQI0bN3Zhzttvv11ffPGFC4I2bNjQhVWrVKmiAwcOaPfu3Spa1JuyztY55ZRTXMjVxoPLLrtMo0aN0jGrthTLvn37XIVUC4vmz59fNWvW1MUXX6xPP/000bbb8sqVK2vdunVpfn0BZBw+74M4+G1BwZx5vOsTekmzH0/5fms/l4bXlw7tl+9Ym/ZtTzwsZcFYm0IUnh+nSQvHJR0sSw2rRtvnY6lAcSl3fmngXKl6y4xoJcJIVI65FhRd/Jp0+GBo2/HPOmlwMenXJKpVWtW1vlOkio3i3n7t21KnJ5P/nCCQln42zlq4uHbHlF9PCyZd9eqJqbaLV/SqPQc7rTaiQlSOtympf5l0ScJ9CAn8+5t3MkugCnpKrKrkvydmJvGFbmOkXu8mv85fq09UxIw0patJRctl3vZtnK7dwasmvn+7VKyCVNFHFcSBMMK3SACIcLGrwQAIPfok4C/0ScBf6JNA2h09elR58+ZNUNHEAqEWtIy9zA5g2cWWGQtd2u8WzEzKE088oZtuuklFihRJcZlNJW+Bz4BixYq50Or69evddQu0fvnlly5M+sknn+iWW25xt69evVrly5d31y1ketVVV7mgafzKLPZ8bLyI/Zxy5MihDRsSr7hnVUz/+usv93gA/DFeIQU9xkunt/V+v+FT6aK7U75P/uJS5cbS0cPyHZuyd3BxLywa36dDpVGEF+NUEvxhkncQPCOn6vxtkXTq+V4IGVElKsfcpn28Kehz/Re4D5UiZaXe70tlT098eY5cXkXUQqVSt92lb0tvX58hTYxqL7SV5r0Q/Pp28tr3n0gbv5V+mhm5YS+kWVSOtymx/Xxbf5f2bkt+PavEOf5SKVuQ8aXXuksLXlLYmfWYNPE2RaR2D0oNumX+41ilbjshZPc/UvZcmf948CWOIaQPQVEAAAAAAAAgzNl08v/884+mTZumI0eOuKqdv//+uw4dOuRClxaWXLx4sVs2YcIEV83Tlu3atUsjRozQPffck+S2bRp4C5J27do1qGU23X380Gq+fPnc7QFNmzbV999/76qb9u/fP6YtU6ZMcRVF58+frxYtWmjAgAE6fDhu6MlCp40aNdIzzzzjnseaNWs0c+ZMt40Am8LeqpfWqVNHPXr0cNsqUaJEml9fAMhyf62R/l7rVS2zijkpqVBP6v6ilK+wfMem9L3uIynff5XYYrNpRi8fE4pW+VPHx71wcEayirRv9pTm8jojSlgA00402rbBC5SESv5iUv3LvZ9JWf6+tHr2iesWfBh2irTsveS3fTxuxX2k0tEjUqWzpJInTm4LypR7pRUfS5PvlhaNz6zWAZHj2BHpwdOkbz9Ifr2mN0iP/RX8iTI3zpAuGCJfebmT9NkTya/T+SnvBIJIY5VSt3snImc6q+xc+WypUJmseTwgAhEUBYAIx1QHgL/QJwF/oU8C/kKfBFLHKnlaANIuw4YNc9fff/99tWvXzk1FbwFRC1VWqlRJ9913nwuEdujQwQUvbep3W2Zhy0svvdRV8kyKTenevn175c6dO6hlFgq1AGdsFhK1SqIBtr5dbrzxRhcQtWnhc+XKpfr166tly5Zu2fXXX6+tW7e6CqXxPfXUU9q8ebOaNWumJ598Up07d3bPJ+Cll15y4VgLo9qU9j///LOGDx+eptcZQMbKmZNpWoPyShev4tBHt0rbvIrMKVY6275R2r9LvlP0ZKle18Sn9j35DKla81C0yp/hYAuJZfRUxtd/JDXtKy19K2O3i7AQtWPuwb3SY2dI818MXRt+XeSFCpOzcKz0Q6xwuE273KiHVOrUpO9jy20adKSdjbM2HXatNsHfxz7DblsodXhUunOJ1DGFQBiiTtSOtykF92+eI9VNeNJpHNlzSAVLBr9dGyMLlvDfiVE2/XpyCp/kXSLNJ3dKb/fOusfLWzhjq+8j7GQLtvowEsWrJ2nlypVq27atzjjjDLdDPTNZhYXq1avrm2++ydTHGTp0qHr27Jmubfz999+umsR5553nXptzzz1XgwcPTnIaLwD+ROltwF/ok4C/0CcBf6FPAqkzZMgQN4W7XWyflgUx33zzTc2aNUu33XabC0eeeuqp2rt3rwuGWoh0+vTp6tatmzZu3KjTTjtNX331lcaNG6cLLrjATfVu7Pfvvvsu5nHmzZun1q1bJ9qGxJbZY1k104Bt27Zpz549qlixoptq3vZbxZ5G3qboK1y4sCpXrqzdu3fHGRMC08zHt2PHDj3//PNuH9urr76qP//8UzVq1Ei0jeXKlXNVShcuXJiq1xdA5rB+jSD0+US6+AFv2vDDB1Ne/8hB6b6K0soMrkaZEdZ+ETcIFduOP6WvRoe26p8f7N4iDa+TORXqrJphm3ukOxZn/Lbhe1E75uYpIPWZJDW/OXRt+O4jaeZDya9z8+dStzHxAowPS5UaJn8/+1zg7+e0+Xud9OVz0uG4J7YFXcnO2JTHeQtleNMQ3qJ2vE3Jac2kQqWSX2faMGnO08Fvc9m7Xj/2kwuHSHU6J7/O6s+8UGWksZMXLhsd6lYgqvAdKD0IikoaO3asq1hgO8pvuOGGUDfHF2yqrquvvlr//vuvRo0a5Q4wWNUJq9RwxRVXuB38AAAAAAAA8AebUt6mW7cToq1i6Ouvv65ChQq5KemtKqft87KTf62ypwUsrXJn6dKlNXfuXM2ZM8ddbEp6Y7/XrVvX/W77hrZs2aLTTz89wWMmtcyCpkuXLnXBzIMHD7p9Slb11IKs1h7bz2TLbf+TLbOAZ4UKFXTRRRfpt99+c8stPPryyy+7NtpJ1/E9/PDDLhRrB+MsrGrPw8KgibH9WNOmTYt5TgBCi4PoQSpTXarUSLp3lVQmhepEJnc+acAsqcaF8p1l70hfjEh82c4/pEl3SjuyaLpKv7IqWv1npFxxC0ilqB5zq7eU8hQMXaCyyzPSnUuTXyd+RbSDe6SN3yYfYrTg/aC80t6tGdPOaPPLfOmLZ+zFT9v9P3tSurectHNzRrcMYS6qx9vk/P6NNP3BpJfbGL1ny4kgdjA2r5I2LJPvpl9PqbL/zj+l9Sl8LoSjQqW9v12ALEKxifQhKGrj8c6dqlmzpqtqUKxYsVA3xxdsR75VfrCpu+rVq+cqLzRq1Ehjxoxx04FNnTo11E0EAAAAAADAfyyE+cADD+jBBx90gUubct2mZ8+ePbvb5zVgwADddNNNbpp42xdm6wbDKnUWKVIk0Wnnk1pWpkwZFwB99NFH1aRJEzdrzUMPedWUqlat6tp17733utlrLBhqJylny5ZNZcuW1SuvvOICog0bNnSVUm1flC0zto/KppMPBEU///xzNWjQQE8//bRGjx6tk08+OaYNffr0cevbxWYSstfAZs4BEHqBPo0gTL1f+vREFeYU1Wztz+kse7wi3fJ54ssqNpRG7PemoI9m1i8s1GbVP4EMFPVj7rcfSCPOtQRX2u5voc0FL3tTwpv/zfUuwcqZ8Dt0HEvflsbEmv58w3LpiQbStmRmd6xQX+r5hpQ7f/DtwAnnXCfdt1bKlSdt9292k3TlK/78vEVIRf14m5R/1knL35WOHk58ub1u3V6Qzrk++G22f0S65i35hn3GPFJL+vb95Nc7+xpp4FeKKCs+kiYNDnUrEHUYb9Mjp6Jcy5Yt9ccff7jfJ02a5Ka/euedd1wVAqs2YNNetWrVyu1Izpcvn1tv/fr1Gj58uJYsWaKcOXOqadOmbnmJEiXc8o8//tjt1LbtWsCye/fubhp42zEfsGLFCj3yyCNuZ3i1atXclO5nn312zHJri02bZWHNkiVL6tJLL1Xfvn2VI0cOt9wqez7zzDNatGiRmz7MdorfeeedSU6xZTvmbZvjx493lRtSEmirTT/WsWPHmNvt9Zg8ebKKFy+exlccQFaLPfYACD36JOAv9EnAX+iTQPqcf/757pIYq7aZVMXNAAtaLl4cd1pa24+U1JTtyS0777zz3CUxVnHULomxfVy2by0xtj8twAKn7733XqLrffHFF4neDsAfbJ86gmTVlTadGPuCOlCbI5dU+8Q+fd/I7h3bSIBQhfTdRGnpBOnad9MeXAKSEPVjbvFKUsVG0uH93nT0qbXpe+mDG6Umvb3rnz9zYiplqx5nVSUt5J2YlztJDa+U6l+e9PYLlJBKVj1xvWIDafAyr91JKVZBanx16p8LvGnnS53qVeFOKwvoWtgUiCfqx9uknNXTuyRm/07pp5leRfUcYf763bZQKlFFUfn3yrb1oW4Fokx2/oZMl6g/AvPRRx/FVBZYsGCBq2Dw008/uSm4bJqru+66ywUs33/fS/9bNc0ePXq4qbHeeOMNvfbaa27aroEDB7rltp5V4bQKDTalld0+btw4V9kgNgts9u/fX59++qlq1arlQqBWXcHY1GD33XefunXr5kKZt956q1vfwqlmz549bvp3W//FF190O8Xz5s2rq666Kib0Gpu1xx7H2hpMSNRYtYczzjjDBVitCoVVo7Dns337dlWpUsVViwAQHpjqAPAX+iTgL/RJwF/okwAARL7Dh5OoJoSErLrS7YuCX3/Zu9L3k+Q74y/zquYlZVwXafEbiloW7s1fnJAoMkXUj7mVG0uXjkxbSNQ06SWNOnIiwHTdh9J1H3i/z3hImj4s8fvZlKj5ikm5Uqj6WauN1G3Miet5Cnph0eTGg4N7peXvM/V5atnr9nRj6TPveDuQ0aJ+vE2LVTOkt672woapYd957y3vjbV+YCe+n3KOVKRs8uut/VwaWlra5eWCIsJ5/aXeKVRSBTLYseMcQ0iPMI/lp59VxsyVK5cLWpYqVcpNeWVTrFevXt0tL1++vCZMmKB169a569OnT3cVPJ999tmYsKRVBrUQpYVHX3jhBRcAbdeunVtWoUIFF+y0oKUFPgNuvvlmXXzxxe53m+rr66+/dpVMA8FSC31aINVUrlxZO3bscNNy3XLLLZoyZYoLbE6cODGmsqdVF7VKDG+//bYLdwbYNF9WhcHCpxZIDZZNGWbbevPNNzVz5ky9++67rn12JowFWC1Aa69bUo4ePeouVg0m9oG+2NcD5deP//cBHqp17RK4bsvsfoH7WgVXex6Zua5fX5eMWjcrXsOU1vXj65KR66b0uth1W55Zr7dfXxfGiPBYNxrHiNi3+WGMyOzXOxzeh4wR/l03K15Du81PY0RWr8sYwRjht9fQxH6uya0bjd8jsnpdxgjGiNjtt1lv7r77bq1evdpN4277w84880wlxqaOt31RdqCsS5cuGjJkiNvepk2b3D4xO+m6c+fObvr5wMw5NlOO7YMDAMSS2kopfRKvyBxyFoLMnUxIq2h5KV9hRa0z23sXAJnj6BGvam+5OlKFesHf75s3pRoXxg3+xA5wXjpKylck6fG752spP4ZNab/rr//GyXzSuq+k3xZJF92V9H0O7pZe6y71nSKdeUnwzyfaWVi439TorPgHhNqollL1C6SL7o57e8PuUtVzUw5YxlemhtS0rzeG+qES6Z5/pQVjpcbXSMXKJ71e8cpS81ulXHkVEQ7tO1FpGUDY8MGo6S9XXnmlm57KpqC3HeA///yz24l9yimnuOUWGLXgZuyKmjbdu11sqvq//vrLhUife+65mOW2U/3gwYNuO3ny5ImZRivAwpcW4vzf//7ntvHvv//GWW7OOusst3P9119/jWlD7OnfLehq1UIDgVbz3XffaenSpW69smVT+eH63zZvuOEGd7Fg6pIlS1x1VQuQ5suXz+3AT4odeLBL4Pf4y5K7XyjWjX09cGAklOumtv3hti6vd8auG8xztQNywa6bmu1mRPvDYV3es1m7bqS/3vbYgT6ZFW2IxNfQb+tG+nvWb+tm9Gto39VtWbS+3rxnM39dxojUrWt9MrHPyWC3y+udsevyGmb+uuH0nh00aJCbkcdm2LEZcAYMGKA5c+a4k41js9s+/PBDN4uPLbP9SrYvqWfPnu6nzWJjJyZbULR79+469dRT3X40C5ACiA7JfdYjQl0xNvnll41SVE87X7GhVLxiqFuCCMWYa1+Is0ufPeEFeIINiu7ZKn0wwKvsnNSUyYVKnZg6OX5g9PAB72K3Jxf63/KL9HB16ZYvpGotpM0/Sj98knxQtGBp6amdXvVRJAwF/zzPey0Te92rNg1FqxAlGG+TcWYHqUzNuLcd2C3lLZR8sDIpNpanJvif2awi6lfPSae3Tf75lKoqtblHEePbD6T3+kpPbOUzCVkq/r5OpA6fVrHYASmbAt4qIlh40yp+jh07VvXr149Zx25P7v4mMF194GI7z2fPnu2qiya1E96qOdjO80DVhqS2bY+f3Dqx25c/f35XCdQCn/acUsN26FsF0YBixYq5Kehtqnv7OXfu3FRtD0Do8EEJ+At9EvAX+iTgL/RJwJ9++eUXVwX0uuuuczPMdO3a1Z1EvWhRwumQp06d6gKgJ598skqWLOn2tX366adume23sn4eqHJqB9LWrl3rZtJp3LhxCJ4ZgFDg8z4TffuhNOI8+crRw9LebXYAI+l1Du2PrCk4U/PafHCTtOTNULcEEYwx16W3pMHLpNZDg79PwRLSI5ukepcnv97mn6R7TpZ+/Tru7atnSYOLSbtTGNssJN5/mnRybe96s5ukO5ek/HysCjOhtBPmjvH+L9Z8Jo1uJf25Mu7ype9IL7aTDh8MVQsRBRhvk9FioFTrohPXLe/yXAvpk6QLkyXLvjv+ttgLm/rBSTWl4f9IFU7kihJlY5B9XuzbrohQraV01euERIEwwzfIWGzqrHnz5rkqBnfccYc6dOjgptKyHeGBcKZVObBKo7t3n/jQWbVqlauGYBU/rXrnxo0bValSpZiLLR85cmScx/rxxx9jfrcp6+36aaed5nag22X58uVx1l+2bJnbEW/tqV69umvD1q1bY5ZbxVLbhrUvoFq1aqpXr56b2t520ltFh2BZJdXnn39ee/bsSbCscOHCKlGiRNDbAhBaSYXLAYQGfRLwF/ok4C/0ScCfbIYb28cV+8TnKlWquNsTWzcwM0/89a666iq3z8tOQm7Xrp1bb8SIERo4cGAWPRMAfmBFE5BJCpbywkbJhTKz2p8/SkNKSJtWJL3OJ3dIY1orqlhQIEcuadg6qdktoW4NIhhjbqxpx83vKYQwzZFD3sWqgcaeaj6p6Y/bPSyVOi3u7ZXOknq/71X/TI5NP3z6xV4wNTXe7eudHAAvMDZ/jBfOrdXGCwWX+y94+9oV0jdvSvmLSqVOTfn/E0gHxttkWOXltZ/H/Y5q09DX6ZK27W1bLz3TRNr0ncKKVR59tqn0+zeKCHayQ8MrQt0KRCGOIaQPQdFYLKBplQ1mzJjhwp4rV650O6q3bNniwpymffv2rmKCTbu+Zs0aF84cNmyYC2Xa9O59+vTRW2+9pQkTJriA6WeffeaCmlbVM/ZUXM8884wLblogc+jQoW77PXr0cMusOoPd3yp6rl+/XlOmTHGhzW7duqlQoUKuDUWLFnVt++GHH1w7LNi6b98+t058559/vi655BLXjp07dwb1WvTq1ctVdbBpwaydmzZtcq/HSy+95Cqk9uvXL8NedwAAAAAAAPiX7XPKly9fnNtsX9f+/fsTrGu32bIAu9+BAwfc72XKlNF7773nKpHedttt+uabb9x+Njs5+sorr3T7tb7//vsseEYAEKGqNZe6jfFXlbkSlaXrPkoYoort3H7SZaMVNRa8LA2v601LbRWYrDIggMy37ivp6cZeFbrkLH1bGlYluEp1Nt62uu3ENPQBRcpK9S8Pbjy2x1v7hff7hN7SR7emfJ+De6Qj3nfsqJc7nzRkhdTsZm+6+YoNTkxDn6+olLewF8a99LlQtxSIXlZFc/QF0o6N3nXrq3W7SKc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muw3Tbt/fRPF4tF80AAB+m7dynu6cdrs+rfxUPct66nvDf6DNe29ev3728tn61VsX6optfqe+5c2/R3ziy8f19KwnXXBz815b6PhRJ7hw4W0f36KepT211+B9VGXdOJNVevyLf+uDxe/rkKGHqqKkU/1yC2pWWWizvgNnk86cTTp41qaCM/V8EQYtG8KYTTpx1l02BDnDcKd13ay7Xd36oGtn4xCn69YZK4n8P5sAAAA+OPLII13n0JAFPa3b54QJExqdoGFdQFsKcJqmwU3rGmHdQ20Y+qZs+Pnf//737jNc61Zq84gW6w5i3T0An1C38FFk6tY+YykvD6bevYNh6q3LqIVGV6wI5i0wWndCCApbZOoWaCVqFj6ibuGjpAd1G+29wzp1e7jtttu02Wab1S+zL5JtsjPPp06d6q5vsMEGrQ6J2tntd9xxhwuXon2kbUiNK39bP19y+mmK9eqV031Cx0omUnrmL1P04Suz65dtf+goTThoBGEPAECHd+X8/QfXaZu+E3T6JmdqysJ3dfOHv9c5Y89XWimtSKzQPZ/epdp0rV6d97LrJhkGO12oM1Wtr1bM0azlX2q9ToOUSCX05oJJenvBW+7+bb3595d1J8BkuPvT5rsu5UJMMRfUDEOcDddbtywIedYFQTO3C8Of8VJe0wEAADxiYdDMQKgNIW+fhf7yl790IdLQlClTGg0hn+mFF17QT3/6Uz366KMaMmRI/WeqH3/8sfbaa69VtrfPZG1EJguJPvPMM7rzzjs75HfD2mMgNviIuoWPIlu38bhkIyeGoyda9yoLjYbdRm2/LQRgE58DFZzI1i3QAmoWPqJu4aO0B3VLUDRP2Rns3/rWtxote/rpp91Z6ueff76mTZumrl27umGUrEuoDRO/zz776Mc//rFKbRiFjLTzWWed5W57+eWXExJtZ8nHHlPqgw/c9djIkSr+zrdzvUvoQLXVCT1289uaMWW+m7fPDvb44WYau8vQXO8aACCi/0xYJ00X1nQdNusCm/UdOYPLRstTLS9fVrvMhUH/tfwB/WvmA/U/59J3f7XKz34wY31zPl82Ux0lrngQwKzvvlle34WzYVlmYNPCmnVdOhuFOZsuC4ZfpxMnAAAAVsc+Mz388MN1ww03aMCAARo6dKj+/ve/a/Lkye4yNH/+fPeZaufOnbXVVlu5E/fPOecc99mrdSW1k/gXL16sY489ttmfY11M//SnP6lfv37aaKONsvgbojX4nwE+om7hI2/q1r47tUYvNlkAwIKj1mnUhqq367aMjqMFw5u6BepQs/ARdQsfxTyoW4KiBeLtt9/Weeed585g32WXXdwHltXV1Ro7dqyOO+44ffTRR/rd736nOXPmuMuQDYFUW1urjTfeWH/4wx+09957uw9L18TOvK+xf4zQshUrVHLt9QoPEzWn/ljVdiYi8lLVslo986cPNf/z4DkuKo5pl2NGa+jYbu5LA6wb65QMALk89iTTySC8mQpCmTV1Q6cH1+uGUq9fXhNcNrsuuF6dCrZJK9pnnhXHStS1uKsLZC6trVRZvFzxWEwLaxZqqx5bqUtJtyDE6YZSDwKdwWXGfDiceizoxlkUK2q/f6SSdZN1dFJSCa1on/sFcoT3PABywcJvQKGxz067d++uSy65RAsWLNAmm2ziun5uuumm9dvsuOOOOvXUU3XaaaepS5cubv3VV1+tH/3oR+5z13Hjxumee+5Rnz59mv0ZNtz8dddd12KQFLlVZGEfwDPULXzkZd3a51ZlZcFk75XD4KiFRpcuDTqOGltvnUmRd7ysWxQ0ahY+om7hoyIP6jaW9qHvKdbJs88+67qC2pntf/zjH1VWVuaGPlq+fLn7wDNkQx2deeaZrsOofYA5evRod2kfctptDj74YNel9Prrr1/tF5eTJk1yQyfZGfVoWc31Nyjx59vd9aLddlPZ71t+XOG3ygUr9MDVb2jR3OVuvqyiWIecsbUGj+6d613LGxa2zRwmDgDWJOzU6aaEXa5smM+cEi0sT1ZpRe0K1aZr3O1tuPaosg6aFuS0MOvK5Er1KeujPuV9tTK5QrOXz9b4vtvq/UXvaWyvsRrUaZDun/EPHbHhUepb3tcFOMuLbCp3nT3Pm/QLDekyxA1db6HOGz64Tpv23FSHrv9t/enjW/XBovfVuaSLltZU6sBhB2vPQasOswlg7fGeB0AuEBQFoiP87HX8+PFuRCl0HGueYJ1hAZ9Qt/BRXtZtKiVVVdkLd3CZTAZD1Ofb71nA8rJukdeoWfiIukWz7OSc9ddXVNV6ULd0FM1zdta6DRlvw8r/9re/rR9Wvri4uFFI1IwcOdJdzp07t/5M9zPOOKN+uXUkveiii7T99tu74Zew9lKzZilx193BTEmJSs76ea53CR1kwaylevCaN7RsUZWb79y9TN8+axv1HcKH+QDQ5mHY07UulGlhRwtqrnQhzpXBfCK8DNZnXs/cNgx5WmgyaopjxXVDqpe7cGYwpHp5XUgzmA8Dmw3Xg+6cjZeH91HuOpT+Z/Yzem/hZC2uWeICstv22077DN5H3Uq764I3z9OcFbO1fb/t9b0R33f7YUHR8X23cUHRVfYxXqy9B++rPuXBe8V9B++nR794xAVFTdeSrjpn8/M0vXK6bvrw9xrdfbSGdhmW5UcSAAAAAAAAyBHrImrNdMKGOrW1QadRC45aiNRCozYBAAAAWca70Dx277336te//rV+8IMf6IILLmg0hKctGzx4sK644or6Ze+9955LNq+fkb7ObItr4dCJEyfqN7/5jetOOmLEiCz+Nvml9pprg6S7/RH+4PuKDx2S611CB5g1baEevn6SqlcEw4z07N/ZhUS796XbLoDCkUglgqBmZohzlYBn0NHTXdYHPoP5zBBolMKd1k3TporiTqqoC2laMLO8uO7Slq0S4Fw18OlCnfFguYUw20tNska3fvxHF9isrFmilFL165788nG9PO8ljeg2wj2m1ckqvTD3eb0494X6bS588zwdO/J4bdd/+0b3O6BigFYkGoZvD+63YYCCrfqMU5eSrtqi95basf/O+sNHN+uSrS51vysAAAAA+CLOUMHwEHULHxVE3VpXqV69gsm+G1yyJBim3kKjts6DIUpRgHWLvELNwkfULXwU96BuCYrmqRkzZrhA55577qmTTjpJCxYsqF9XXl6uvffe260fO3asdtxxRxcS/d3vfqcf/ehH6tKlS4v3a91JDzzwQDdE/QMPPOCGpEfbJCe9qeR/ng1mevdWyYn/l+tdQgf49J15+vcf3laiNgjm9N+guw47c7w6deNvBkD0pdKpjC6czYU7q1YNeWasz7yddbCMAhtCvSIjxFleVFE3pHpFfWizoi7oGYY+K4oq6kKdFausK4oVRXYIaAuJXv7ur/Xlsi+U1KrhWgt3Lq5ZpLcWvKmYYrphuxtdd9HQD5//vi7b+opmO4pu339HTZzzrMb12Vol8RI9+eUT2rrPNs3ux1HDv6dfvnWB7p5+l04YfWI7/5YAAAAA0HEymy4AvqBu4aOCq1sb+bFv32CqrpYWL5ZWrLDhlOzBCIKjHgQMCl3B1S28R83CR9QtfBTzoG4Jiuapp59+WrW1tfrPf/7jpkyHHnqorrzySlegd999twuM9u3bV8cee6xOPHH1X+L37t1bl112mU455RTXjfTiiy/u4N8kv6STSdX89nf186Wnn6bYaoK58NN7L3yp/9z5ntKpoMPasE366KBTx6m0gkMugI5nwcyViRVa4UKcdrnCBTdXJOsu3fwKF+LMXBd27bT56lS1osCCiGFIs6K4ou56hQtsVjS5Xl5cN2/L3bbh8uAyHiucD1itk2hLIdFMaaVdUPSvn9yp0zb5aYvbnTfpHB049CBt338H7T14H9WkanTZO5e4etmu3/bab8j+zd7OQrYnjjlFl797qTbpuanbFgAAAAB8kEwmvegEAmSibuGjgq5ba8bTv38QEk0kpKoqadmyIEBq3UYNHUcjqaDrFl6iZuEj6hY+SnpQt7F02t59Au2jsrJSkyZN0pgxY9SpE8NrN5V45FHVXHChux7baIzK/36fYvyDlzfscPrG45/qpQem1i8bM2E97XPC5ioqjvaLge+i2tUPaCsL4FlQMwh6rhrmzAyA1oc+XRg0uI0tq03ntoOnddpsGtZs6XrjcGfQ5dPWu+6dRRXtOhR7oRx7bJj5i9660HUMba2epT116bjL1a20W4fuG4D8PO4AyH89e/bM9S4AaPLZ6/jx49WtG+/fO5I1YSixcA7gEeoWPqJuW5BMBsFRG6J+5cpg3th3ijxeOUfdwjfULHxE3aJZNTXS+usrqmo9qNtof/sO5JF0dbVqb7ypfr707LMIieYR6x763H0f6u3/zKxfttWe62uXozZWLB799tIA1l0ynXRhzeV1Ic8VieXucnlieUP4s1HAM7i04drDoGcincjJvltXSRfeLO60aqBzlZBnRQuBTxuavUIlsRIv2urnq6dmPaUlNYvbdJslNUv01KwndfiGR3TYfgEAAACAT4qL+eoE/qFu4SPqtgX2/WHnzsFkrMOoBSMsOGpD1dt161ZlXUmRddQtfEPNwkfULXxU7EHdRn8PgTyR+Nu9Ss+d667Hd9pJRdtsk+tdQjtJJlJ66s+T9fFrc+qX7fid0dpm/+GEpQCPpNIpVSer6oKeDSHPIPQZLGs8n7l+uaqSVTkLeVpos1NRJxf0bLgedufspE7ueqf65Z1su4zlFvgspKHZ89l7Cye7IeXbIqWUux1BUQAAAABoGC7Ohy94gEzULXxE3baShULLy4Opd++gw+jSpTb0SBAiLS0NtkFWULfwDTULH1G38FHSg7qN9t4BeSK9eLFq//TnYCYeV+nPzsj1LqGd1KxM6JGb3tIXHyxw89Y9dK/jNtOmOw3J9a4BBSedTruh2xuHOJsPfDYEPzPnV7Q5YNceIU8X2nQhziC0mRn6dEHOjEBno9Bn3ToLeRJ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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "robyn.generate_one_pager()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "9ed54130", + "metadata": {}, + "outputs": [], + "source": [ + "# robyn.generate_one_pager(solution_id=\"1_1994_1\")" + ] + }, + { + "cell_type": "markdown", + "id": "e87e98ff", + "metadata": {}, + "source": [ + "## Budget Allocation Optimization\n", + "\n", + "Robyn provides different scenarios for budget allocation optimization. Let's explore the \"max_response\" scenario:\n", + "\n", + "### Scenario: Maximum Response\n", + "This scenario answers the question: \"What's the maximum return given certain spend constraints?\"\n", + "\n", + "Key parameters:\n", + "- `total_budget`: When set to None, uses the total spend in the selected date range\n", + "- `channel_constr_low`: Minimum spend multiplier (e.g., 0.7 means channel spend can't go below 70% of current)\n", + "- `channel_constr_up`: Maximum spend multiplier per channel (e.g., 1.5 means channel spend can't exceed 150% of current)\n", + "- `channel_constr_multiplier`: Extends bounds for wider optimization insights\n", + "- `date_range`: Period for optimization (\"all\", \"last_X\", or specific date range)\n", + "\n", + "Note: Other scenarios include:\n", + "- \"target_efficiency\": Optimize spend to hit specific ROAS or CPA targets\n", + "- \"min_spend\": Find minimum spend required to hit response targets\n", + "- \"max_response_expected\": Maximize expected response within confidence intervals\n", + "\n", + "For this example, we'll demonstrate the \"max_response\" scenario:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "2859a6cb", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO: Optimizing budget allocation\n", + "2025-02-04 23:34:51,186 - robyn.robyn - INFO - Optimizing budget allocation\n", + "INFO: Selected model for budget optimization: 4_1242_1\n", + "2025-02-04 23:34:51,187 - robyn.robyn - INFO - Selected model for budget optimization: 4_1242_1\n", + "2025-02-04 23:34:51,415 - robyn.visualization.allocator_visualizer - INFO - Initializing AllocatorPlotter\n", + "2025-02-04 23:34:51,416 - robyn.visualization.allocator_visualizer - INFO - Creating all plots for model 4_1242_1\n", + "2025-02-04 23:34:51,416 - robyn.visualization.allocator_visualizer - INFO - Creating budget comparison plot\n", + "2025-02-04 23:34:51,443 - robyn.visualization.allocator_visualizer - INFO - Creating allocation matrix plot\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:34:51,754 - robyn.visualization.base_visualizer - INFO - Saving multiple plots to: /Users/yijuilee/robynpy_release_reviews/Robyn/python/src/robyn/tutorials/output\n", + "2025-02-04 23:34:51,904 - robyn.visualization.base_visualizer - INFO - Plot budget_opt saved successfully\n", + "2025-02-04 23:34:52,102 - robyn.visualization.base_visualizer - INFO - Plot allocation saved successfully\n", + "INFO: Budget optimization complete\n", + "2025-02-04 23:34:52,102 - robyn.robyn - INFO - Budget optimization complete\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.allocator.entities.allocation_params import AllocatorParams\n", + "from robyn.allocator.constants import (\n", + " SCENARIO_MAX_RESPONSE,\n", + " CONSTRAINT_MODE_EQ,\n", + ")\n", + "\n", + "allocator_params = AllocatorParams(\n", + " scenario=SCENARIO_MAX_RESPONSE,\n", + " total_budget=None, # Uses total spend in date_range when None\n", + " date_range=\"all\",\n", + " channel_constr_low=[0.7], # Minimum spend multiplier\n", + " channel_constr_up=[1.2, 1.5, 1.5, 1.5, 1.5], # Maximum spend multiplier\n", + " channel_constr_multiplier=3.0,\n", + " optim_algo=\"SLSQP_AUGLAG\",\n", + " maxeval=100000,\n", + " constr_mode=CONSTRAINT_MODE_EQ,\n", + " plots=True,\n", + ")\n", + "\n", + "allocation_result = robyn.optimize_budget(\n", + " allocator_params=allocator_params,\n", + " select_model=None,\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".pyvenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/python/src/robyn/tutorials/tutorial1_src.ipynb b/python/src/robyn/tutorials/tutorial1_src.ipynb new file mode 100644 index 000000000..bef5cb32b --- /dev/null +++ b/python/src/robyn/tutorials/tutorial1_src.ipynb @@ -0,0 +1,1393 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Robyn: Marketing Mix Modeling in Python (Source Implementation)\n", + "\n", + "Welcome to Robyn, a powerful Marketing Mix Modeling (MMM) tool developed by Meta. This notebook demonstrates how to use Robyn to build and analyze marketing mix models.\n", + "\n", + "This notebook demonstrates the basic (source implementation) workflow of using Robyn for Marketing Mix Modeling. For your own analysis:\n", + "\n", + "1. Replace the sample data with your marketing data\n", + "2. Adjust the model parameters based on your business context\n", + "3. Validate results against your business knowledge \n", + "4. Use the optimization insights to guide marketing budget allocation\n", + "\n", + "For more information, visit the [Robyn documentation](https://github.com/facebookexperimental/Robyn).\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## Installation\n", + "\n", + "[Running via pip] Install Robyn using pip.\n", + "\n", + "After installation, you might need to restart your Jupyter kernel to use the newly installed package. You can do this by:\n", + "- Going to the Kernel menu\n", + "- Selecting \"Restart Kernel\"\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%pip install robynpy==0.1.2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "[Running locally] If building locally, make sure we are importing the Robyn modules from the local src directory:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# # Local Import\n", + "# import os\n", + "# import sys\n", + "\n", + "# notebook_path = os.path.abspath(\"\")\n", + "# robyn_path = os.path.abspath(os.path.join(notebook_path, \"../../\"))\n", + "# if robyn_path not in sys.path:\n", + "# sys.path.append(robyn_path)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Import Required Libraries\n", + "\n", + "We'll import the core components directly from Robyn's source:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:25:15,849 - robyn - INFO - Logging is set up to console only.\n", + "/Users/yijuilee/robynpy_release_reviews/Robyn/.pyvenv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "from robyn.modeling.model_executor import ModelExecutor\n", + "from robyn.modeling.entities.enums import NevergradAlgorithm, Models\n", + "from robyn.modeling.feature_engineering import FeatureEngineering" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading Simulated Data with `robynpy` if you are running on Google Colab.\n", + "\n", + "[Running via pip] After installing the `robynpy` package using pip, you can load the simulated data by following these steps:\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# # Step 1: Import Necessary Libraries\n", + "# import importlib\n", + "# import robyn\n", + "# import os\n", + "# import pandas as pd\n", + "\n", + "# # Step 2: Load the `robyn` Package\n", + "# pkg = importlib.import_module(\"robyn\")\n", + "\n", + "# # Step 3: Define the Path to Tutorials\n", + "# tutorials_path = pkg.__path__[0] + \"/tutorials\"\n", + "\n", + "# # Step 4: Load and Display Simulated Weekly Data\n", + "# dt_simulated_weekly = pd.read_csv(tutorials_path + \"/resources/dt_simulated_weekly.csv\")\n", + "# print(\"Simulated Data...\")\n", + "# print(dt_simulated_weekly.head())\n", + "\n", + "# # Step 5: Load and Display Prophet Holidays Data\n", + "# dt_prophet_holidays = pd.read_csv(tutorials_path + \"/resources/dt_prophet_holidays.csv\")\n", + "# print(\"Holidays Data...\")\n", + "# print(dt_prophet_holidays.head())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading Simulated Data from Local Build\n", + "\n", + "[Running locally] For this demonstration, we'll use simulated data from our local build." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the simulated data and holidays data\n", + "dt_simulated_weekly = pd.read_csv(\"resources/dt_simulated_weekly.csv\")\n", + "\n", + "dt_prophet_holidays = pd.read_csv(\"resources/dt_prophet_holidays.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Configure MMM Data\n", + "\n", + "Define the model specification including dependent variables, independent variables, and analysis window. Here's what each parameter means:\n", + "\n", + "### Key Components:\n", + "- `dep_var`: Your target metric (e.g., \"revenue\", \"conversions\")\n", + "- `dep_var_type`: Type of dependent variable (\"revenue\" for ROI or \"conversion\" for CPA)\n", + "- `date_var`: Column name containing dates\n", + "- `window_start/end`: Analysis time period\n", + "\n", + "### Variable Types:\n", + "- `paid_media_spends`: Columns containing media spend data (e.g., TV, Facebook, Search)\n", + "- `paid_media_vars`: Media exposure metrics (impressions, clicks) in same order as spends\n", + "- `context_vars`: External factors (e.g., competitor activities, events, seasonality)\n", + "- `organic_vars`: Marketing activities without direct spend (e.g., email, social posts)\n", + "\n", + "Example configuration:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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DATErevenuetv_Sooh_Sprint_Sfacebook_Isearch_clicks_Psearch_Scompetitor_sales_Bfacebook_Seventsnewsletter
02015-11-232.754372e+0622358.3466670.012728.4888892.430128e+070.0000000.00000081250097607.132915na19401.653846
12015-11-302.584277e+0628613.4533330.00.0000005.527033e+069837.2384864133.33333379015491141.952450na14791.000000
22015-12-072.547387e+060.000000132278.4453.8666671.665159e+0712044.1196533786.66666783001974256.375378na14544.000000
32015-12-142.875220e+0683450.3066670.017680.0000001.054977e+0712268.0703194253.33333381228832800.490677na2800.000000
42015-12-212.215953e+060.000000277336.00.0000002.934090e+069467.2480233613.3333337105985689.582605na15478.000000
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" + ], + "text/plain": [ + " DATE revenue tv_S ooh_S print_S \\\n", + "0 2015-11-23 2.754372e+06 22358.346667 0.0 12728.488889 \n", + "1 2015-11-30 2.584277e+06 28613.453333 0.0 0.000000 \n", + "2 2015-12-07 2.547387e+06 0.000000 132278.4 453.866667 \n", + "3 2015-12-14 2.875220e+06 83450.306667 0.0 17680.000000 \n", + "4 2015-12-21 2.215953e+06 0.000000 277336.0 0.000000 \n", + "\n", + " facebook_I search_clicks_P search_S competitor_sales_B \\\n", + "0 2.430128e+07 0.000000 0.000000 8125009 \n", + "1 5.527033e+06 9837.238486 4133.333333 7901549 \n", + "2 1.665159e+07 12044.119653 3786.666667 8300197 \n", + "3 1.054977e+07 12268.070319 4253.333333 8122883 \n", + "4 2.934090e+06 9467.248023 3613.333333 7105985 \n", + "\n", + " facebook_S events newsletter \n", + "0 7607.132915 na 19401.653846 \n", + "1 1141.952450 na 14791.000000 \n", + "2 4256.375378 na 14544.000000 \n", + "3 2800.490677 na 2800.000000 \n", + "4 689.582605 na 15478.000000 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def setup_mmm_data(dt_simulated_weekly) -> MMMData:\n", + "\n", + " mmm_data_spec = MMMData.MMMDataSpec(\n", + " dep_var=\"revenue\",\n", + " dep_var_type=\"revenue\",\n", + " date_var=\"DATE\",\n", + " context_vars=[\"competitor_sales_B\", \"events\"],\n", + " factor_vars=[\"events\"],\n", + " paid_media_spends=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_S\", \"search_S\"],\n", + " paid_media_vars=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_I\", \"search_clicks_P\"],\n", + " organic_vars=[\"newsletter\"],\n", + " window_start=\"2016-01-01\",\n", + " window_end=\"2018-12-31\",\n", + " )\n", + "\n", + " return MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec)\n", + "\n", + "\n", + "mmm_data = setup_mmm_data(dt_simulated_weekly)\n", + "mmm_data.data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Configure Hyperparameters\n", + "\n", + "Hyperparameters control how media effects are modeled. Each channel requires three key parameters:\n", + "\n", + "### Media Channel Parameters:\n", + "- `alphas`: Controls saturation curve shape [0.5, 3]\n", + " - Lower values (0.5-1): More diminishing returns\n", + " - Higher values (2-3): More S-shaped response\n", + " \n", + "- `gammas`: Controls saturation curve inflection point [0.3, 1]\n", + " - Lower values: Earlier diminishing returns\n", + " - Higher values: Later diminishing returns\n", + "\n", + "- `thetas`: Controls adstock decay rate [0, 0.8]\n", + " - Lower values (0-0.2): Fast decay (e.g., Search, Social)\n", + " - Medium values (0.1-0.4): Medium decay (e.g., Print, OOH)\n", + " - Higher values (0.3-0.8): Slow decay (e.g., TV)\n", + "\n", + "### Global Parameters:\n", + "- `adstock`: Type of carryover effect modeling\n", + " - \"geometric\": Fixed decay rate\n", + " - \"weibull_cdf\": Flexible decay with cumulative distribution\n", + " - \"weibull_pdf\": Flexible decay with potential peak delay\n", + "\n", + "- `lambda_`: Ridge regression regularization [0, 1]\n", + "- `train_size`: Proportion of data for training [0.5, 0.8]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hyperparameters setup complete.\n" + ] + } + ], + "source": [ + "hyperparameters = Hyperparameters(\n", + " {\n", + " \"facebook_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"print_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"tv_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.3, 0.8],\n", + " ),\n", + " \"search_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"ooh_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"newsletter\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " },\n", + " adstock=AdstockType.GEOMETRIC,\n", + " lambda_=[0, 1],\n", + " train_size=[0.5, 0.8],\n", + ")\n", + "\n", + "print(\"Hyperparameters setup complete.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Configure Holiday Data\n", + "\n", + "Holiday data helps capture seasonality and special events in your model. The HolidaysData configuration includes:\n", + "\n", + "### Components:\n", + "- `dt_holidays`: DataFrame containing holiday/events data\n", + "- `prophet_vars`: Time components to model:\n", + " - \"trend\": Long-term trend\n", + " - \"season\": Seasonal patterns\n", + " - \"holiday\": Holiday/event effects\n", + "- `prophet_country`: Country code for built-in holidays (e.g., \"DE\" for Germany)\n", + "- `prophet_signs`: Effect direction for each prophet_var:\n", + " - \"default\": Let the model determine direction\n", + " - \"positive\": Force positive effect\n", + " - \"negative\": Force negative effect\n", + "\n", + "Note: You can add custom events (school breaks, promotional periods, etc.) to the holidays data." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Create HolidaysData object\n", + "holidays_data = HolidaysData(\n", + " dt_holidays=dt_prophet_holidays,\n", + " prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + " prophet_country=\"DE\",\n", + " prophet_signs=[\"default\", \"default\", \"default\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Engineering Process\n", + "\n", + "The feature engineering step prepares raw marketing data for modeling through four main steps:\n", + "\n", + "### 1. Data Preprocessing\n", + "- Standardizes dates and variables\n", + "- Applies analysis time window\n", + "- Handles missing values and data types\n", + "\n", + "### 2. Time Series Decomposition\n", + "Uses Prophet to decompose data into:\n", + "- Trend and seasonality components\n", + "- Holiday and event effects\n", + "- Monthly/weekly patterns\n", + "\n", + "### 3. Media Variable Processing\n", + "For channels with different spend vs. exposure metrics:\n", + "- Fits and compares linear and non-linear models\n", + "- Selects best model based on fit metrics\n", + "- Generates spend-exposure relationship plots\n", + "\n", + "### 4. Marketing Effect Transformations\n", + "Applies marketing-specific adjustments:\n", + "- Adstock transformation for carryover effects\n", + "- Saturation curves for diminishing returns\n", + "- Media cost factor normalization\n", + "\n", + "The output is a FeaturizedMMMData object containing the transformed features ready for modeling." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:25:18,111 - robyn.modeling.feature_engineering - INFO - Starting feature engineering process\n", + "2025-02-04 23:25:18,114 - robyn.modeling.feature_engineering - INFO - Starting Prophet decomposition\n", + "2025-02-04 23:25:18,114 - robyn.modeling.feature_engineering - INFO - Starting Prophet decomposition\n", + "/Users/yijuilee/robynpy_release_reviews/Robyn/.pyvenv/lib/python3.12/site-packages/prophet/forecaster.py:187: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " self.holidays['ds'] = pd.to_datetime(self.holidays['ds'])\n", + "2025-02-04 23:25:18,837 - cmdstanpy - DEBUG - input tempfile: /var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpp_er_mkt/f1w2fj37.json\n", + "2025-02-04 23:25:18,846 - cmdstanpy - DEBUG - input tempfile: /var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpp_er_mkt/fp_3pbgl.json\n", + "2025-02-04 23:25:18,848 - cmdstanpy - DEBUG - idx 0\n", + "2025-02-04 23:25:18,849 - cmdstanpy - DEBUG - running CmdStan, num_threads: None\n", + "2025-02-04 23:25:18,849 - cmdstanpy - DEBUG - CmdStan args: ['/Users/yijuilee/robynpy_release_reviews/Robyn/.pyvenv/lib/python3.12/site-packages/prophet/stan_model/prophet_model.bin', 'random', 'seed=45931', 'data', 'file=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpp_er_mkt/f1w2fj37.json', 'init=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpp_er_mkt/fp_3pbgl.json', 'output', 'file=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpp_er_mkt/prophet_modelwesc_mpq/prophet_model-20250204232518.csv', 'method=optimize', 'algorithm=lbfgs', 'iter=10000']\n", + "23:25:18 - cmdstanpy - INFO - Chain [1] start processing\n", + "2025-02-04 23:25:18,849 - cmdstanpy - INFO - Chain [1] start processing\n", + "23:25:18 - cmdstanpy - INFO - Chain [1] done processing\n", + "2025-02-04 23:25:18,906 - cmdstanpy - INFO - Chain [1] done processing\n", + "2025-02-04 23:25:18,974 - robyn.modeling.feature_engineering - INFO - Prophet decomposition complete\n", + "2025-02-04 23:25:18,976 - robyn.modeling.feature_engineering - INFO - Starting model runs for paid media variables with different exposure metrics\n", + "2025-02-04 23:25:18,976 - robyn.modeling.feature_engineering - INFO - Fitting spend-exposure model for facebook_I\n", + "2025-02-04 23:25:18,991 - robyn.modeling.feature_engineering - INFO - Fitting spend-exposure model for search_clicks_P\n", + "2025-02-04 23:25:18,999 - robyn.modeling.feature_engineering - INFO - Completed model runs for 2 channels\n", + "2025-02-04 23:25:19,000 - robyn.modeling.feature_engineering - INFO - Feature engineering complete\n", + "/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/robyn/modeling/feature_engineering.py:109: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " dt_mod = dt_mod.fillna(method=\"ffill\").fillna(method=\"bfill\")\n", + "2025-02-04 23:25:19,003 - robyn.modeling.feature_engineering - INFO - Filled 0 missing values\n" + ] + } + ], + "source": [ + "# Setup FeaturizedMMMData\n", + "feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data)\n", + "\n", + "featurized_mmm_data = feature_engineering.perform_feature_engineering()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualize Feature Relationships\n", + "\n", + "Plot the spend-exposure relationships for each channel to understand how media spend translates to exposure metrics. These plots show:\n", + "- How media spend relates to exposure (impressions, clicks, etc.)\n", + "- Model fit quality (R² value)\n", + "- Whether the relationship follows linear or Michaelis-Menten patterns" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:25:19,027 - robyn.visualization.feature_visualization - INFO - Initializing FeaturePlotter\n", + "2025-02-04 23:25:19,027 - robyn.visualization.feature_visualization - INFO - Generating spend-exposure plot for channel: facebook_I\n", + "2025-02-04 23:25:19,027 - robyn.visualization.feature_visualization - INFO - Found result for channel facebook_I\n", + "2025-02-04 23:25:19,194 - robyn.visualization.feature_visualization - INFO - Successfully generated spend-exposure plot for channel facebook_I\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:25:19,339 - robyn.visualization.feature_visualization - INFO - Generating spend-exposure plot for channel: search_clicks_P\n", + "2025-02-04 23:25:19,346 - robyn.visualization.feature_visualization - INFO - Found result for channel search_clicks_P\n", + "2025-02-04 23:25:19,497 - robyn.visualization.feature_visualization - INFO - Successfully generated spend-exposure plot for channel search_clicks_P\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.visualization.feature_visualization import FeaturePlotter\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "# Create plotter instance\n", + "feature_plotter = FeaturePlotter(mmm_data, hyperparameters, featurized_mmm_data)\n", + "results_list = featurized_mmm_data.modNLS[\"results\"]\n", + "\n", + "# Plot each channel\n", + "for result in results_list:\n", + " channel = result[\"channel\"]\n", + " try:\n", + " # Get the figure dictionary\n", + " fig_dict = feature_plotter.plot_spend_exposure(channel)\n", + " \n", + " if \"spend-exposure\" in fig_dict:\n", + " fig = fig_dict[\"spend-exposure\"]\n", + " # Need to get the axis from the figure\n", + " ax = fig.get_axes()[0]\n", + " # Draw the figure to make sure it's rendered\n", + " fig.canvas.draw()\n", + " # Display using display instead of show\n", + " from IPython.display import display\n", + " display(fig)\n", + " \n", + " except ValueError as e:\n", + " print(f\"Skipping {channel}: {str(e)}\")\n", + " except Exception as e:\n", + " print(f\"Error plotting {channel}: {str(e)}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model Training\n", + "\n", + "### Training Configuration:\n", + "- `trials`: Number of parallel optimization trials (e.g., 5)\n", + "- `iterations`: Optimization iterations per trial (e.g., 2000)\n", + "- `ts_validation`: Whether to use time-series validation\n", + "- `cores`: Number of CPU cores to use for parallel processing\n", + "- `nevergrad_algo`: Optimization algorithm (TWO_POINTS_DE recommended)\n", + "- `model_name`: Model type (RIDGE regression recommended)\n", + "\n", + "Parameters:\n", + "- `add_penalty_factor`: Additional regularization for stability\n", + "- `rssd_zero_penalty`: Penalize unrealistic zero contributions\n", + "- `intercept`: Include intercept term\n", + "- `intercept_sign`: Control intercept direction\n", + "\n", + "Note: More iterations and trials generally lead to better results but increase computation time." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:25:19,580 - robyn.modeling.base_model_executor - INFO - Initializing BaseModelExecutor\n", + "2025-02-04 23:25:19,581 - robyn.modeling.model_executor - INFO - Starting model execution with model_name=Models.RIDGE\n", + "2025-02-04 23:25:19,582 - robyn.modeling.base_model_executor - INFO - Input validation successful\n", + "2025-02-04 23:25:19,582 - robyn.modeling.base_model_executor - INFO - Preparing hyperparameters\n", + "2025-02-04 23:25:19,582 - robyn.modeling.base_model_executor - INFO - Completed hyperparameter preparation with 20 parameters to optimize\n", + "2025-02-04 23:25:19,583 - robyn.modeling.model_executor - INFO - Initializing Ridge model builder\n", + "2025-02-04 23:25:19,583 - robyn.modeling.model_executor - INFO - Building models with configured parameters\n", + "2025-02-04 23:25:19,584 - robyn.modeling.ridge.ridge_data_builder - INFO - Collecting hyperparameters for optimization...\n", + "Running trial 1 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:27:00,752 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.69 mins\n", + "Running trial 2 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:28:41,582 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.67 mins\n", + "Running trial 3 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:30:22,923 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.67 mins\n", + "Running trial 4 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:32:03,794 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.66 mins\n", + "Running trial 5 of total 5 trials: 100%|███████████████████████████████████\n", + "2025-02-04 23:33:44,826 - robyn.modeling.ridge.ridge_evaluate_model - INFO - Finished in 1.67 mins\n", + "2025-02-04 23:33:45,176 - robyn.visualization.model_convergence_visualizer - INFO - Initialized ModelConvergenceVisualizer\n", + "2025-02-04 23:33:45,176 - robyn.modeling.convergence.convergence - INFO - Starting convergence calculation\n", + "2025-02-04 23:33:45,179 - robyn.modeling.convergence.convergence - WARNING - 'mape' column not found or all zeros. Assuming model is not calibrated.\n", + "2025-02-04 23:33:45,200 - robyn.modeling.convergence.convergence - INFO - Convergence status for DECOMP.RSSD: converged\n", + "2025-02-04 23:33:45,200 - robyn.modeling.convergence.convergence - INFO - DECOMP.RSSD converged: sd@qt.20 0.024 <= 0.040 & |med@qt.20| 0.03 <= 0.08\n", + "2025-02-04 23:33:45,201 - robyn.modeling.convergence.convergence - WARNING - Convergence status for NRMSE: NOT converged\n", + "2025-02-04 23:33:45,201 - robyn.modeling.convergence.convergence - INFO - NRMSE NOT converged: sd@qt.20 0.015 <= 0.026 & |med@qt.20| 0.05 > 0.00\n", + "2025-02-04 23:33:45,231 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2025-02-04 23:33:45,241 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2025-02-04 23:33:45,247 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2025-02-04 23:33:46,055 - robyn.visualization.model_convergence_visualizer - INFO - Successfully created moo distribution plot\n", + "2025-02-04 23:33:46,409 - robyn.visualization.model_convergence_visualizer - INFO - Successfully created moo cloud plot\n", + "2025-02-04 23:33:46,598 - robyn.modeling.convergence.convergence - INFO - Convergence calculation completed successfully\n", + "2025-02-04 23:33:46,634 - robyn.modeling.model_executor - INFO - Model building completed successfully\n", + "2025-02-04 23:33:46,634 - robyn.modeling.model_executor - INFO - Model execution completed successfully\n" + ] + } + ], + "source": [ + "plt.ioff()\n", + "model_executor = ModelExecutor(\n", + " mmmdata=mmm_data,\n", + " holidays_data=holidays_data,\n", + " hyperparameters=hyperparameters,\n", + " calibration_input=None,\n", + " featurized_mmm_data=featurized_mmm_data,\n", + ")\n", + "\n", + "trials_config = TrialsConfig(iterations=2000, trials=5)\n", + "\n", + "output_models = model_executor.model_run(\n", + " trials_config=trials_config,\n", + " ts_validation=True,\n", + " add_penalty_factor=False,\n", + " rssd_zero_penalty=True,\n", + " cores=8,\n", + " nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE,\n", + " intercept=True,\n", + " intercept_sign=\"non_negative\",\n", + " model_name=Models.RIDGE,\n", + ")\n", + "plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model Convergence Analysis\n", + "\n", + "After training the models, we can examine two key visualization plots that help assess model convergence and optimization quality:\n", + "\n", + "### MOO Cloud Plot\n", + "This plot shows the distribution of model solutions in the objective space:\n", + "- X-axis: Model fit error (NRMSE) - lower is better\n", + "- Y-axis: Decomposition error - lower is better\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image, display\n", + "import base64\n", + "\n", + "# Display the MOO Cloud Plot\n", + "if \"moo_cloud_plot\" in output_models.convergence:\n", + " moo_cloud_plot = output_models.convergence[\"moo_cloud_plot\"]\n", + " display(Image(data=base64.b64decode(moo_cloud_plot)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### MOO Distribution Plot \n", + "This plot shows the distribution of objective values across all trials:\n", + "- Shows the spread of NRMSE and decomposition errors\n", + "- Helps identify if optimization has converged to stable solutions\n", + "- Wide distributions may indicate need for more iterations\n", + "- Narrow distributions suggest consistent model performance" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Display the MOO Distribution Plot\n", + "if \"moo_distrb_plot\" in output_models.convergence:\n", + " moo_distrb_plot = output_models.convergence[\"moo_distrb_plot\"]\n", + " display(Image(data=base64.b64decode(moo_distrb_plot)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model Selection and Clustering\n", + "\n", + "### 1. Pareto Optimization\n", + "Pareto optimization helps select the best models by balancing multiple objectives:\n", + "- Model accuracy (NRMSE)\n", + "- Decomposition accuracy\n", + "- Model robustness\n", + "\n", + "Parameters:\n", + "- `pareto_fronts`: Number of Pareto fronts to consider (\"auto\" recommended)\n", + "- `min_candidates`: Minimum number of models to retain (e.g., 100)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2025-02-04 23:33:46 [INFO] Starting Pareto optimization\n", + "2025-02-04 23:33:46,748 - robyn.modeling.pareto.data_aggregator - INFO - Starting model data aggregation\n", + "2025-02-04 23:33:46 [INFO] Computing Pareto fronts\n", + "2025-02-04 23:33:47 [INFO] Pareto front computation completed\n", + "2025-02-04 23:33:47 [INFO] Preparing Pareto data\n", + "2025-02-04 23:33:47 [INFO] Number of Pareto-optimal solutions found: 8214\n", + "2025-02-04 23:33:47 [INFO] Selected 4 Pareto-fronts containing 139 candidates\n", + "2025-02-04 23:33:47 [INFO] Selected Pareto fronts: 5\n", + "2025-02-04 23:33:47 [INFO] Filtering data for selected Pareto fronts...\n", + "2025-02-04 23:33:47 [INFO] Pareto data preparation completed\n", + "2025-02-04 23:33:47,302 - robyn.modeling.pareto.response_curve - INFO - Calculating response curves for 695 models' media variables...\n", + "Processing rows: 100%|██████████| 695/695 [00:05<00:00, 118.43it/s]\n", + "2025-02-04 23:33:53,925 - robyn.modeling.pareto.response_curve - INFO - Successfully processed 695 response curves\n", + "2025-02-04 23:33:53,925 - robyn.modeling.pareto.response_curve - INFO - Computing final metrics...\n", + "2025-02-04 23:33:53,926 - robyn.modeling.pareto.response_curve - INFO - Calculating ROI and CPA metrics...\n", + "2025-02-04 23:33:53,953 - robyn.modeling.pareto.response_curve - INFO - Final Pareto Data updated with response curves:\n", + "Decomp Spend Distribution:\n", + "\n", + "2025-02-04 23:33:53,953 - robyn.modeling.pareto.response_curve - INFO - DataFrame columns: Index(['rn', 'coef', 'xDecompAgg', 'total_spend', 'mean_spend', 'spend_share',\n", + " 'effect_share', 'sol_id', 'rsq_train', 'rsq_val', 'rsq_test', 'nrmse',\n", + " 'decomp_rssd', 'mape', 'lambda', 'lambda_hp', 'lambda_max',\n", + " 'lambda_min_ratio', 'trial', 'iterNG', 'iterPar', 'Elapsed', 'pos',\n", + " 'robynPareto', 'mean_response', 'mean_spend_adstocked',\n", + " 'mean_carryover', 'roi_mean', 'roi_total', 'cpa_mean', 'cpa_total'],\n", + " dtype='object')\n", + "2025-02-04 23:33:53,953 - robyn.modeling.pareto.response_curve - INFO - DataFrame Shape: (695, 31)\n", + "2025-02-04 23:33:53,954 - robyn.modeling.pareto.response_curve - INFO - X Spend Aggregated with response curves:\n", + "\n", + "2025-02-04 23:33:53,954 - robyn.modeling.pareto.response_curve - INFO - DataFrame columns: Index(['rn', 'coef', 'xDecompAgg', 'xDecompPerc', 'xDecompMeanNon0',\n", + " 'xDecompMeanNon0Perc', 'xDecompAggRF', 'xDecompPercRF',\n", + " 'xDecompMeanNon0RF', 'xDecompMeanNon0PercRF', 'pos', 'train_size',\n", + " 'rsq_train', 'rsq_val', 'rsq_test', 'nrmse_train', 'nrmse_val',\n", + " 'nrmse_test', 'nrmse', 'decomp.rssd', 'mape', 'lambda', 'lambda_hp',\n", + " 'lambda_max', 'lambda_min_ratio', 'sol_id', 'trial', 'iterNG',\n", + " 'iterPar', 'Elapsed', 'iterations', 'robynPareto', 'total_spend',\n", + " 'mean_spend', 'mean_spend_adstocked', 'mean_carryover', 'mean_response',\n", + " 'spend_share', 'effect_share', 'roi_mean', 'roi_total', 'cpa_total'],\n", + " dtype='object')\n", + "2025-02-04 23:33:53,954 - robyn.modeling.pareto.response_curve - INFO - DataFrame Shape: (120000, 42)\n", + "2025-02-04 23:33:53,954 - robyn.modeling.pareto.response_curve - INFO - Response curves calculated successfully\n", + "2025-02-04 23:33:53,957 - robyn.modeling.pareto.plot_data_generator - INFO - Starting plot data generation...\n", + "2025-02-04 23:33:53,958 - robyn.modeling.pareto.plot_data_generator - INFO - Processing Pareto front 1\n", + "2025-02-04 23:33:53,962 - robyn.modeling.pareto.plot_data_generator - INFO - Pareto-Front: 1 [32 models]\n", + "Processing Solutions: 0%| | 0/32 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.visualization.allocator_visualizer import AllocatorPlotter\n", + "\n", + "plotter = AllocatorPlotter(\n", + " allocation_result=max_response_result, budget_allocator=max_response_allocator\n", + ")\n", + "\n", + "plots = plotter.plot_all(display_plots=True, export_location=None)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".pyvenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/src/robyn/visualization/allocator_visualizer.py b/python/src/robyn/visualization/allocator_visualizer.py new file mode 100644 index 000000000..31f4929d9 --- /dev/null +++ b/python/src/robyn/visualization/allocator_visualizer.py @@ -0,0 +1,648 @@ +# robyn/allocator_v2/visualization/allocator_plotter.py + +import matplotlib.pyplot as plt +import seaborn as sns +import pandas as pd +import numpy as np +from typing import Dict, Union +from pathlib import Path +import logging + +from robyn.allocator.entities.allocation_result import ( + AllocationResult, +) +from robyn.allocator.optimizer import BudgetAllocator +from robyn.visualization.base_visualizer import BaseVisualizer + +logger = logging.getLogger(__name__) + + +class AllocatorPlotter(BaseVisualizer): + """Generates plots for Robyn allocator results.""" + + def __init__( + self, + allocation_result: AllocationResult, + budget_allocator: BudgetAllocator, + ): + """ + Initialize AllocatorPlotter with all necessary data. + + Args: + allocation_result: Results from budget allocation + budget_allocator: Budget allocator instance with model parameters + """ + super().__init__() + logger.info("Initializing AllocatorPlotter") + + # Store provided data + self.allocation_result = allocation_result + self.budget_allocator = budget_allocator + + # Store commonly used data + self.dt_optimOut = allocation_result.dt_optimOut + self.mainPoints = allocation_result.mainPoints + + # Infer plotting configurations + self.metric = ( + "ROAS" + if budget_allocator.mmm_data.mmmdata_spec.dep_var_type == "revenue" + else "CPA" + ) + self.interval_type = budget_allocator.mmm_data.mmmdata_spec.interval_type + self.model_id = budget_allocator.select_model + self.scenario = allocation_result.scenario + + # Pre-calculate scenario metrics + self.scenarios = { + "Initial": { + "spend": self.dt_optimOut.init_spend_unit.sum(), + "response": self.dt_optimOut.init_response_unit.sum(), + }, + "Bounded": { + "spend": self.dt_optimOut.optm_spend_unit.sum(), + "response": self.dt_optimOut.optm_response_unit.sum(), + }, + "Bounded x3": { + "spend": self.dt_optimOut.optm_spend_unit_unbound.sum(), + "response": self.dt_optimOut.optm_response_unit_unbound.sum(), + }, + } + + # Calculate percentage changes and metrics for each scenario + for scenario in self.scenarios: + if scenario != "Initial": + self.scenarios[scenario].update( + { + "spend_pct_change": ( + self.scenarios[scenario]["spend"] + / self.scenarios["Initial"]["spend"] + - 1 + ) + * 100, + "response_pct_change": ( + self.scenarios[scenario]["response"] + / self.scenarios["Initial"]["response"] + - 1 + ) + * 100, + } + ) + if self.metric == "ROAS": + self.scenarios[scenario]["metric_value"] = ( + self.scenarios[scenario]["response"] + / self.scenarios[scenario]["spend"] + ) + else: # CPA + self.scenarios[scenario]["metric_value"] = ( + self.scenarios[scenario]["spend"] + / self.scenarios[scenario]["response"] + ) + + logger.debug("AllocatorPlotter initialized with data") + + def _plot_allocation_matrix(self) -> plt.Figure: + """Plot allocation matrix matching R format.""" + if self.dt_optimOut is None: + raise ValueError("dt_optimOut must be provided") + + logger.info("Creating allocation matrix plot") + try: + # Adjust the figsize to make the plots smaller + fig, axes = plt.subplots(1, 3, figsize=(10, 6)) # Reduced from (15, 10) + + scenarios = ["Initial", "Bounded", "Bounded x3"] + metrics = [ + "abs.mean\nspend", + "mean\nspend%", + "mean\nresponse%", + f"mean\n{self.metric}", + f"m{self.metric}", + ] + + # Define color schemes for each scenario + color_schemes = { + "Initial": sns.light_palette("#C0C0C0", as_cmap=True), + "Bounded": sns.light_palette("#6495ED", as_cmap=True), + "Bounded x3": sns.light_palette("#efb400", as_cmap=True), + } + + for i, scenario in enumerate(scenarios): + data = self._get_allocation_data(scenario) + + # Format data for heatmap + plot_data = data.copy() + plot_data["abs.mean\nspend"] = plot_data["abs.mean\nspend"].apply( + lambda x: f"{x/1000:.0f}K" + ) + for col in metrics[1:]: + plot_data[col] = plot_data[col].apply( + lambda x: (f"{x*100:.1f}%" if col.endswith("%") else f"{x:.2f}") + ) + + # Normalize each column independently + norm_data = data.copy() + for col in metrics: + col_values = norm_data[col].values + if col_values.any(): + min_val = col_values.min() + max_val = col_values.max() + if max_val > min_val: + norm_data[col] = (col_values - min_val) / ( + max_val - min_val + ) + else: + norm_data[col] = 0 + + # Create heatmap + sns.heatmap( + norm_data[metrics], + ax=axes[i], + cmap=color_schemes[scenario], + annot=plot_data[metrics].values, + fmt="", + cbar=False, + annot_kws={"fontsize": 8}, # Set the font size for annotations + ) + + axes[i].set_title(scenario, fontsize=8) + axes[i].set_ylabel("Paid Media" if i == 0 else "", fontsize=8) + + # Set the font size for xticks and yticks + axes[i].tick_params(axis="x", labelsize=8) # Adjust xtick label size + axes[i].tick_params(axis="y", labelsize=8) # Adjust ytick label size + + plt.suptitle( + f"Budget Allocation per Paid Media Variable per {self.interval_type}", + ) + plt.tight_layout(pad=2.0) + + return fig + + except Exception as e: + logger.error("Failed to create allocation matrix plot: %s", str(e)) + raise + + def _plot_response_curves(self) -> plt.Figure: + """Plot response curves with optimization points.""" + if any( + attr is None + for attr in [self.dt_optimOut, self.mainPoints, self.budget_allocator] + ): + raise ValueError("All data attributes must be provided") + + logger.info("Creating response curves plot") + try: + n_channels = len(self.dt_optimOut.channels) + n_rows = (n_channels + 2) // 3 # 3 columns + fig, axes = plt.subplots(n_rows, 3, figsize=(15, 5 * n_rows), squeeze=False) + axes = axes.flatten() + + scenarios = ["Initial", "Bounded", "Bounded x3"] + scenario_colors = ["gray", "#4682B4", "#DAA520"] + + # Plot for each channel + for i, channel in enumerate(self.dt_optimOut.channels): + ax = axes[i] + + # Get channel parameters + carryover = ( + self.budget_allocator.allocator_data_preparer.hill_params.carryover[ + i + ] + ) + + # Generate response curve + max_spend = np.max(self.mainPoints.spend_points[:, i]) * 1.5 + spend_range = np.linspace(0, max_spend, 100) + response = self._calculate_response_curve_hill(spend_range, i) + + # Plot grey area for historical carryover + carryover_mask = spend_range <= carryover + if any(carryover_mask): + ax.fill_between( + spend_range[carryover_mask], + response[carryover_mask], + color="grey", + alpha=0.4, + label="Historical Carryover", + ) + + # Plot main curve + ax.plot( + spend_range, response, label=channel, color="#1f77b4", alpha=0.7 + ) + + # Add constraint lines + lower_bound = self.dt_optimOut.init_spend_unit[i] * 0.7 + upper_bound = self.dt_optimOut.init_spend_unit[i] * 1.2 + + # Add constraint lines for bounded scenario + ax.axvline(x=lower_bound, color="gray", linestyle="--", alpha=0.3) + ax.axvline(x=upper_bound, color="gray", linestyle="--", alpha=0.3) + + # Add extended constraint lines for unbounded scenario + lower_bound_ext = ( + self.dt_optimOut.init_spend_unit[i] * 0.1 + ) # Using 0.1 as in R + upper_bound_ext = ( + self.dt_optimOut.init_spend_unit[i] * 1.6 + ) # Using 1.6 as in R + ax.axvline(x=lower_bound_ext, color="gray", linestyle=":", alpha=0.2) + ax.axvline(x=upper_bound_ext, color="gray", linestyle=":", alpha=0.2) + + # Plot points for each scenario + for scenario_idx in range(len(scenarios)): + ax.scatter( + self.mainPoints.spend_points[scenario_idx, i], + self.mainPoints.response_points[scenario_idx, i], + color=scenario_colors[scenario_idx], + marker="o", + s=100, + label=scenarios[scenario_idx], + zorder=5, + ) + + # Add spend amount annotation + ax.annotate( + f"{self.mainPoints.spend_points[scenario_idx, i]:,.0f}", + ( + self.mainPoints.spend_points[scenario_idx, i], + self.mainPoints.response_points[scenario_idx, i], + ), + xytext=(10, 5), + textcoords="offset points", + fontsize=8, + ) + + # Customize subplot + ax.set_title(channel, fontsize=10) + ax.set_xlabel("Spend") + ax.set_ylabel("Response") + + # Format axis labels + ax.yaxis.set_major_formatter( + plt.FuncFormatter(lambda x, p: format(int(x), ",")) + ) + ax.xaxis.set_major_formatter( + plt.FuncFormatter(lambda x, p: format(int(x), ",")) + ) + + # Add legend to first plot only + if i == 0: + ax.legend(bbox_to_anchor=(1.05, 1), loc="upper left") + + # Remove empty subplots + for j in range(i + 1, len(axes)): + fig.delaxes(axes[j]) + + # Main title + plt.suptitle( + f"Simulated Response Curve per {self.interval_type}\n" + f"Spend per {self.interval_type} (grey area: mean historical carryover)", + y=1.02, + ) + + plt.tight_layout() + return fig + + except Exception as e: + logger.error("Failed to create response curves plot: %s", str(e)) + raise + + def _calculate_response_curve_hill( + self, spend_range: np.ndarray, channel_idx: int + ) -> np.ndarray: + """Calculate response values using Hill transformation.""" + try: + # Get parameters from budget allocator + alpha = self.budget_allocator.allocator_data_preparer.hill_params.alphas[ + channel_idx + ] + coef = self.budget_allocator.allocator_data_preparer.hill_params.coefs[ + channel_idx + ] + carryover = ( + self.budget_allocator.allocator_data_preparer.hill_params.carryover[ + channel_idx + ] + ) + gamma = self.budget_allocator.allocator_data_preparer.hill_params.gammas[ + channel_idx + ] + + # Get range values + channel = self.budget_allocator.allocator_data_preparer.media_spend_sorted[ + channel_idx + ] + x_range = self.budget_allocator.allocator_data_preparer.adstocked_ranges[ + channel + ] + inflexion = self.budget_allocator.allocator_data_preparer.inflexions[ + channel + ] + + # Step 1: Adstock transformation + x_adstocked = spend_range + carryover + + # Step 2: Hill transformation + x_hill = np.power(x_adstocked, alpha) + gamma_hill = np.power(inflexion, alpha) + + # Step 3: Response calculation with saturation + response = coef * (x_hill / (x_hill + gamma_hill)) + + return response + + except Exception as e: + logger.error( + "Failed to calculate response curve for channel %d: %s", + channel_idx, + str(e), + ) + raise + + def _get_allocation_data(self, scenario: str) -> pd.DataFrame: + """Prepare data for allocation matrix plot.""" + try: + if scenario == "Initial": + data = { + "abs.mean\nspend": self.dt_optimOut.init_spend_unit, + "mean\nspend%": self.dt_optimOut.init_spend_unit + / self.dt_optimOut.init_spend_unit.sum(), + "mean\nresponse%": self.dt_optimOut.init_response_unit + / self.dt_optimOut.init_response_unit.sum(), + f"mean\n{self.dt_optimOut.metric}": self.dt_optimOut.init_response_unit + / np.where( + self.dt_optimOut.init_spend_unit > 0, + self.dt_optimOut.init_spend_unit, + np.inf, + ), + f"m{self.dt_optimOut.metric}": self.dt_optimOut.init_response_marg_unit, # Use pre-calculated marginal response + } + elif scenario == "Bounded": + data = { + "abs.mean\nspend": self.dt_optimOut.optm_spend_unit, + "mean\nspend%": self.dt_optimOut.optm_spend_unit + / self.dt_optimOut.optm_spend_unit.sum(), + "mean\nresponse%": self.dt_optimOut.optm_response_unit + / self.dt_optimOut.optm_response_unit.sum(), + f"mean\n{self.dt_optimOut.metric}": self.dt_optimOut.optm_response_unit + / np.where( + self.dt_optimOut.optm_spend_unit > 0, + self.dt_optimOut.optm_spend_unit, + np.inf, + ), + f"m{self.dt_optimOut.metric}": self.dt_optimOut.optm_response_marg_unit, # Use pre-calculated marginal response + } + else: # "Bounded x3" + data = { + "abs.mean\nspend": self.dt_optimOut.optm_spend_unit_unbound, + "mean\nspend%": self.dt_optimOut.optm_spend_unit_unbound + / self.dt_optimOut.optm_spend_unit_unbound.sum(), + "mean\nresponse%": self.dt_optimOut.optm_response_unit_unbound + / self.dt_optimOut.optm_response_unit_unbound.sum(), + f"mean\n{self.dt_optimOut.metric}": self.dt_optimOut.optm_response_unit_unbound + / np.where( + self.dt_optimOut.optm_spend_unit_unbound > 0, + self.dt_optimOut.optm_spend_unit_unbound, + np.inf, + ), + f"m{self.dt_optimOut.metric}": self.dt_optimOut.optm_response_marg_unit_unbound, # Use pre-calculated marginal response + } + + return pd.DataFrame(data, index=self.dt_optimOut.channels) + + except Exception as e: + logger.error( + "Failed to get allocation data for scenario %s: %s", scenario, str(e) + ) + raise + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> Dict[str, plt.Figure]: + """ + Create all allocator plots. + """ + logger.info(f"Creating all plots for model {self.model_id}") + + try: + plots = { + "budget_opt": self._plot_budget_comparison(), + "allocation": self._plot_allocation_matrix(), + # "response": self._plot_response_curves(), + } + + if display_plots: + self.display_plots(plots) + + if export_location is not None: + self.export_plots_fig(export_location, plots) + + return plots + + except Exception as e: + logger.error("Failed to generate all plots: %s", str(e)) + raise + + def _plot_budget_comparison(self) -> plt.Figure: + """Plot budget comparison with raw values and summary stats, matching R version.""" + logger.info("Creating budget comparison plot") + try: + # Create figure with grid + fig, ax = plt.subplots(figsize=(12, 8)) + ax.grid(True, axis="y", linestyle="--", alpha=0.7, zorder=0) + + # Get number of periods + n_periods = int( + self.dt_optimOut.periods.split()[0] + ) # e.g., "156 weeks" -> 156 + + # Calculate scenarios with total values (not unit values) + self.scenarios = { + "Initial": { + "spend": np.sum(self.dt_optimOut.init_spend_unit) * n_periods, + "response": np.sum(self.dt_optimOut.init_response_unit) * n_periods, + }, + "Bounded": { + "spend": np.sum(self.dt_optimOut.optm_spend_unit) * n_periods, + "response": np.sum(self.dt_optimOut.optm_response_unit) * n_periods, + }, + "Bounded x3": { + "spend": np.sum(self.dt_optimOut.optm_spend_unit_unbound) + * n_periods, + "response": np.sum(self.dt_optimOut.optm_response_unit_unbound) + * n_periods, + }, + } + + # Print debugging information + logger.debug("Budget comparison values:") + for scenario, values in self.scenarios.items(): + logger.debug( + f"{scenario}: Spend = {values['spend']:,.2f}, Response = {values['response']:,.2f}" + ) + + # Calculate percentage changes and metrics + for scenario in self.scenarios: + if scenario != "Initial": + self.scenarios[scenario].update( + { + "spend_pct_change": ( + self.scenarios[scenario]["spend"] + / self.scenarios["Initial"]["spend"] + - 1 + ) + * 100, + "response_pct_change": ( + self.scenarios[scenario]["response"] + / self.scenarios["Initial"]["response"] + - 1 + ) + * 100, + } + ) + if self.metric == "ROAS": + self.scenarios[scenario]["metric_value"] = ( + self.scenarios[scenario]["response"] + / self.scenarios[scenario]["spend"] + ) + else: # CPA + self.scenarios[scenario]["metric_value"] = ( + self.scenarios[scenario]["spend"] + / self.scenarios[scenario]["response"] + ) + + # Define colors for each scenario + scenario_colors = { + "Initial": "#C0C0C0", # Silver + "Bounded": "#4682B4", # Steel Blue + "Bounded x3": "#DAA520", # Golden Rod + } + + # Define spacing parameters + group_width = 1.2 + group_spacing = 2.0 + bar_spacing = 0.4 + bar_width = 0.3 + + x_base = np.arange( + 0, + len(self.scenarios) * (group_spacing + group_width), + group_spacing + group_width, + ) + + # Plot bars for each scenario + for i, (scenario, data) in enumerate(self.scenarios.items()): + x_group = x_base[i] + x_spend = x_group + (group_width - bar_spacing) / 2 + x_response = x_group + (group_width + bar_spacing) / 2 + + spend_bar = ax.bar( + x_spend, + data["spend"], + bar_width, + label=scenario, + color=scenario_colors[scenario], + zorder=3, + ) + response_bar = ax.bar( + x_response, + data["response"], + bar_width, + color=scenario_colors[scenario], + zorder=3, + ) + + # Add value labels + for bar in [spend_bar, response_bar]: + height = bar[0].get_height() + ax.text( + bar[0].get_x() + bar[0].get_width() / 2.0, + height, + f"{height:,.0f}", + ha="center", + va="bottom", + fontsize=8, + zorder=4, + ) + + # Add "total spend" and "total response" labels + for x_pos, label in [ + (x_spend, "total spend"), + (x_response, "total response"), + ]: + ax.text( + x_pos - 0.25, + ax.get_ylim()[0] * 0.02, + label, + ha="center", + va="top", + rotation=45, + fontsize=8, + zorder=4, + ) + + # Add metrics text + if scenario == "Initial": + metrics_text = ( + f"Spend\nResp\n{self.metric}: " + f"{data['response']/data['spend']:.2f}" + ) + else: + metrics_text = ( + f"Spend: {data['spend_pct_change']:+.1f}%\n" + f"Resp: {data['response_pct_change']:+.1f}%\n" + f"{self.metric}: {data['metric_value']:.2f}" + ) + + ax.text( + x_group + group_width / 2, + ax.get_ylim()[1], + metrics_text, + ha="center", + va="bottom", + fontsize=8, + fontweight="bold", + zorder=4, + ) + + # Customize plot + ax.set_title( + f"Total Budget Optimization Result (scaled up to {self.dt_optimOut.periods})", + pad=20, + fontsize=10, + loc="left", + ) + + # Remove axis ticks and labels + ax.set_xticks([]) + ax.set_ylabel("") + ax.yaxis.set_major_formatter( + plt.FuncFormatter(lambda x, p: format(int(x), ",")) + ) + ax.tick_params(axis="y", labelsize=8) + ax.set_xticklabels(ax.get_xticks(), rotation=45, ha="right", fontsize=8) + + # Customize legend + ax.legend( + title=None, + loc="upper right", + bbox_to_anchor=(1, 1.1), + ncol=3, + frameon=False, + fontsize=8, + ) + + # Remove spines + ax.spines["top"].set_visible(False) + ax.spines["right"].set_visible(False) + ax.spines["bottom"].set_visible(False) + + plt.tight_layout(pad=2.0) + return fig + + except Exception as e: + logger.error("Failed to create budget comparison plot: %s", str(e)) + raise diff --git a/python/src/robyn/visualization/base_visualizer.py b/python/src/robyn/visualization/base_visualizer.py new file mode 100644 index 000000000..bbfb5f172 --- /dev/null +++ b/python/src/robyn/visualization/base_visualizer.py @@ -0,0 +1,389 @@ +# pyre-strict + +import logging + +from abc import ABC, abstractmethod +from typing import Dict, Optional, Tuple, Union, List +from pathlib import Path +from IPython.display import Image, display + +import matplotlib.pyplot as plt +import numpy as np +import base64 +import io + +logger = logging.getLogger(__name__) + + +class BaseVisualizer(ABC): + """ + Base class for all Robyn visualization components. + Provides common plotting functionality and styling. + """ + + def __init__(self, style: str = "bmh"): + """ + Initialize BaseVisualizer with common plot settings. + + Args: + style: matplotlib style to use (default: "bmh") + """ + logger.debug("Initializing BaseVisualizer with style: %s", style) + + # Store style settings + self.style = style + self.default_figsize = (12, 8) + + # Enhanced color schemes + self.colors = { + "primary": "#4688C7", # Steel blue + "secondary": "#FF9F1C", # Orange + "positive": "#2ECC71", # Green + "negative": "#E74C3C", # Red + "neutral": "#95A5A6", # Gray + "current": "lightgray", # For current values + "optimal": "#4688C7", # For optimal values + "grid": "#E0E0E0", # For grid lines + } + logger.debug("Color scheme initialized: %s", self.colors) + + # Plot settings + self.font_sizes = { + "title": 14, + "subtitle": 12, + "label": 12, + "tick": 10, + "annotation": 9, + "legend": 10, + } + logger.debug("Font sizes configured: %s", self.font_sizes) + + # Default alpha values + self.alpha = {"primary": 0.7, "secondary": 0.5, "grid": 0.3, "annotation": 0.7} + + # Default spacing + self.spacing = {"tight_layout_pad": 1.05, "subplot_adjust_hspace": 0.4} + + # Initialize plot tracking + self.current_figure: Optional[plt.Figure] = None + self.current_axes: Optional[Union[plt.Axes, np.ndarray]] = None + + # Apply default style + self._setup_plot_style() + logger.debug("BaseVisualizer initialization completed") + + def _setup_plot_style(self) -> None: + """Configure default plotting style.""" + logger.debug("Setting up plot style with style: %s", self.style) + try: + plt.style.use(self.style) + + plt.rcParams.update( + { + "figure.figsize": self.default_figsize, + "axes.grid": True, + "axes.spines.top": False, + "axes.spines.right": False, + "font.size": self.font_sizes["label"], + "grid.alpha": self.alpha["grid"], + "grid.color": self.colors["grid"], + } + ) + logger.debug("Plot style parameters updated successfully") + except Exception as e: + logger.error("Failed to setup plot style: %s", str(e)) + raise + + def create_figure( + self, nrows: int = 1, ncols: int = 1, figsize: Optional[Tuple[int, int]] = None + ) -> Tuple[plt.Figure, Union[plt.Axes, np.ndarray]]: + """ + Create and track a new figure. + + Args: + nrows: Number of subplot rows + ncols: Number of subplot columns + figsize: Optional custom figure size + + Returns: + Tuple of (figure, axes) + """ + logger.info("Creating new figure with dimensions %dx%d", nrows, ncols) + figsize = figsize or self.default_figsize + logger.debug("Using figure size: %s", figsize) + + try: + self.current_figure, axes = plt.subplots( + nrows=nrows, ncols=ncols, figsize=figsize + ) + if nrows == ncols == 1: + self.current_axes = axes + else: + self.current_axes = np.array(axes) + logger.debug("Figure created successfully") + return self.current_figure, axes + except Exception as e: + logger.error("Failed to create figure: %s", str(e)) + raise + + def setup_axis( + self, + ax: plt.Axes, + title: Optional[str] = None, + xlabel: Optional[str] = None, + ylabel: Optional[str] = None, + xticks: Optional[List] = None, + yticks: Optional[List] = None, + xticklabels: Optional[List] = None, + yticklabels: Optional[List] = None, + rotation: int = 0, + ) -> None: + """ + Apply common axis setup and styling. + + Args: + ax: Matplotlib axes to style + title: Optional axis title + xlabel: Optional x-axis label + ylabel: Optional y-axis label + xticks: Optional list of x-axis tick positions + yticks: Optional list of y-axis tick positions + xticklabels: Optional list of x-axis tick labels + yticklabels: Optional list of y-axis tick labels + rotation: Rotation angle for tick labels + """ + logger.debug( + "Setting up axis with title: %s, xlabel: %s, ylabel: %s", + title, + xlabel, + ylabel, + ) + + try: + if title: + ax.set_title(title, fontsize=self.font_sizes["title"]) + if xlabel: + ax.set_xlabel(xlabel, fontsize=self.font_sizes["label"]) + if ylabel: + ax.set_ylabel(ylabel, fontsize=self.font_sizes["label"]) + + if xticks is not None: + logger.debug("Setting x-ticks: %s", xticks) + ax.set_xticks(xticks) + if yticks is not None: + logger.debug("Setting y-ticks: %s", yticks) + ax.set_yticks(yticks) + + if xticklabels is not None: + logger.debug("Setting x-tick labels with rotation: %d", rotation) + ax.set_xticklabels( + xticklabels, rotation=rotation, fontsize=self.font_sizes["tick"] + ) + if yticklabels is not None: + logger.debug("Setting y-tick labels") + ax.set_yticklabels(yticklabels, fontsize=self.font_sizes["tick"]) + + ax.tick_params(labelsize=self.font_sizes["tick"]) + ax.grid(True, alpha=self.alpha["grid"], color=self.colors["grid"]) + logger.debug("Axis setup completed successfully") + except Exception as e: + logger.error("Failed to setup axis: %s", str(e)) + raise + + def add_percentage_annotation( + self, + ax: plt.Axes, + x: float, + y: float, + percentage: float, + va: str = "bottom", + ha: str = "center", + ) -> None: + """ + Add a percentage change annotation to the plot. + + Args: + ax: Matplotlib axes to annotate + x: X-coordinate for annotation + y: Y-coordinate for annotation + percentage: Percentage value to display + va: Vertical alignment + ha: Horizontal alignment + """ + logger.debug( + "Adding percentage annotation at (x=%f, y=%f) with value: %f%%", + x, + y, + percentage, + ) + try: + color = ( + self.colors["positive"] if percentage >= 0 else self.colors["negative"] + ) + ax.text( + x, + y, + f"{percentage:.1f}%", + color=color, + va=va, + ha=ha, + fontsize=self.font_sizes["annotation"], + alpha=self.alpha["annotation"], + ) + logger.debug("Percentage annotation added successfully") + except Exception as e: + logger.error("Failed to add percentage annotation: %s", str(e)) + raise + + def add_legend( + self, ax: plt.Axes, loc: str = "best", title: Optional[str] = None + ) -> None: + """ + Add a formatted legend to the plot. + + Args: + ax: Matplotlib axes to add legend to + loc: Legend location + title: Optional legend title + """ + logger.debug("Adding legend with location: %s and title: %s", loc, title) + try: + legend = ax.legend( + fontsize=self.font_sizes["legend"], + loc=loc, + framealpha=self.alpha["annotation"], + ) + if title: + legend.set_title(title, prop={"size": self.font_sizes["legend"]}) + logger.debug("Legend added successfully") + except Exception as e: + logger.error("Failed to add legend: %s", str(e)) + raise + + def finalize_figure( + self, tight_layout: bool = True, adjust_spacing: bool = False + ) -> None: + """ + Apply final formatting to the current figure. + + Args: + tight_layout: Whether to apply tight_layout + adjust_spacing: Whether to adjust subplot spacing + """ + logger.info( + "Finalizing figure with tight_layout=%s, adjust_spacing=%s", + tight_layout, + adjust_spacing, + ) + + if self.current_figure is None: + logger.warning("No current figure to finalize") + return + + try: + if tight_layout: + self.current_figure.tight_layout(pad=self.spacing["tight_layout_pad"]) + if adjust_spacing: + self.current_figure.subplots_adjust( + hspace=self.spacing["subplot_adjust_hspace"] + ) + logger.debug("Figure finalization completed successfully") + except Exception as e: + logger.error("Failed to finalize figure: %s", str(e)) + raise + + def cleanup(self) -> None: + """Close the current plot and clear matplotlib memory.""" + logger.debug("Performing cleanup") + if self.current_figure is not None: + plt.close(self.current_figure) + self.current_figure = None + self.current_axes = None + logger.debug("Cleanup completed successfully") + else: + logger.debug("No figure to clean up") + + @staticmethod + def export_plots_base64( + export_location: Union[str, Path], plots: Dict[str, str], dpi: int = 300 + ) -> None: + logger.info("Exporting base64 plots to: %s", export_location) + export_path = Path(export_location) + export_path.mkdir(parents=True, exist_ok=True) + + for plot_name, base64_str in plots.items(): + filename = export_path / f"{plot_name}.png" + logger.debug("Saving base64 plot: %s to %s", plot_name, filename) + try: + image_data = base64.b64decode(base64_str) + with open(filename, "wb") as f: + f.write(image_data) + logger.info("Base64 plot %s saved successfully", plot_name) + except Exception as e: + logger.error("Failed to save base64 plot %s: %s", plot_name, str(e)) + raise + pass + + @staticmethod + def export_plots_fig( + export_location: Union[str, Path], plots: Dict[str, plt.Figure], dpi: int = 300 + ) -> None: + """ + Save multiple plots to the specified location. + + Args: + export_location: Directory to save the plots + plots: Dictionary of plot names and their corresponding figures + dpi: Resolution for saved plots + """ + logger.info("Saving multiple plots to: %s", export_location) + export_path = Path(export_location) + export_path.mkdir(parents=True, exist_ok=True) + + for plot_name, fig in plots.items(): + filename = export_path / f"{plot_name}.png" + logger.debug("Saving plot: %s to %s", plot_name, filename) + try: + fig.savefig( + filename, + dpi=dpi, + bbox_inches="tight", + facecolor="white", + edgecolor="none", + ) + logger.info("Plot %s saved successfully", plot_name) + except Exception as e: + logger.error("Failed to save plot %s: %s", plot_name, str(e)) + raise + + @abstractmethod + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> None: + pass + + @staticmethod + def display_plots(plot_collect: Dict[str, plt.Figure]) -> None: + """Display the plot.""" + for plot_name, fig in plot_collect.items(): + display(fig) + + @staticmethod + def _display_base64_image(base64_image: str): + """Helper method to display a base64-encoded image.""" + display(Image(data=base64.b64decode(base64_image))) + + def convert_plot_to_base64(self, fig: plt.Figure) -> str: + logger.debug("Converting plot to base64") + try: + buffer = io.BytesIO() + fig.savefig(buffer, format="png") + buffer.seek(0) + image_png = buffer.getvalue() + buffer.close() + graphic = base64.b64encode(image_png) + logger.debug("Successfully converted plot to base64") + return graphic.decode("utf-8") + except Exception as e: + logger.error("Failed to convert plot to base64: %s", str(e), exc_info=True) + raise diff --git a/python/src/robyn/visualization/cluster_visualizer.py b/python/src/robyn/visualization/cluster_visualizer.py new file mode 100644 index 000000000..66da3dc04 --- /dev/null +++ b/python/src/robyn/visualization/cluster_visualizer.py @@ -0,0 +1,655 @@ +# pyre-strict +import logging +from pathlib import Path +from typing import Dict, Optional, Union + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import seaborn as sns +from matplotlib.figure import Figure +from matplotlib.ticker import FixedLocator +from scipy import stats + +from robyn.data.entities.enums import DependentVarType +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.clustering.clustering_config import ClusteringConfig +from robyn.modeling.entities.ci_collection_data import ConfidenceIntervalCollectionData +from robyn.modeling.entities.clustering_results import ClusteredResult +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.visualization.base_visualizer import BaseVisualizer + +logger = logging.getLogger(__name__) + + +class ClusterVisualizer(BaseVisualizer): + + def __init__( + self, + pareto_result: Optional[ParetoResult], + clustered_result: Optional[ClusteredResult], + mmm_data: Optional[MMMData], + ): + super().__init__() + if clustered_result is not None: + self.clustered_result = clustered_result + if pareto_result is not None: + self.pareto_result = pareto_result + if mmm_data is not None: + self.mmm_data = mmm_data + + def create_wss_plot(self, nclusters: pd.DataFrame, k: Optional[int]) -> Figure: + """ + Creates a WSS plot for the given DataFrame. + + Args: + nclusters (pd.DataFrame): The DataFrame containing the data to cluster. + k (int): The maximum number of clusters to consider. + seed (int): Random seed for reproducibility. + + Returns: + plt.Figure: The WSS plot figure. + """ + plt.figure(figsize=(10, 6)) + sns.lineplot(data=nclusters, x="n", y="wss", marker="o") + plt.title("Total Number of Clusters") + plt.suptitle("HINT: Where does the curve level?") + plt.xlabel("Number of Clusters") + plt.ylabel("Within Groups Sum of Squares") + plt.grid(True) + plt.gcf().set_facecolor("white") + + # If k is determined, add a horizontal line and update the subtitle + if k is not None: + yintercept = nclusters.loc[nclusters["n"] == k, "wss"].values[0] + plt.axhline(y=yintercept, color="red", linestyle="--") + plt.suptitle(f"Number of clusters selected: {k}") + + fig = plt.gcf() + plt.close(fig) + return fig # Return the current figure + + def plot_confidence_intervals( + self, + ci_results: ConfidenceIntervalCollectionData, + config: ClusteringConfig, + ) -> Figure: + """ + Creates a plot of the bootstrapped confidence intervals for model performance metrics. + + Args: + sim_collect (pd.DataFrame): The DataFrame containing the bootstrapped data, + confidence_interval_df (pd.DataFrame): The data containing confidence intervals for plotting. + config (ClusteringConfig): Configuration for the clustering process. + + Returns: + Figure: The matplotlib figure object containing the plot. + """ + sim_collect = ci_results.sim_collect + confidence_interval_df = ci_results.confidence_interval_df + + # Determine metric type + temp = "CPA" if config.dep_var_type == DependentVarType.CONVERSION else "ROAS" + + # Drop NA values + confidence_interval_df = confidence_interval_df.dropna() + + # Setup the figure + unique_clusters = sorted(sim_collect["cluster_title"].unique()) + n_clusters = len(unique_clusters) + n_cols = min(2, n_clusters) + n_rows = int(np.ceil(n_clusters / n_cols)) + + fig, axes = plt.subplots(n_rows, n_cols, figsize=(12, 12)) + if n_clusters == 1: + axes = np.array([axes]) + axes = axes.flatten() + + # Calculate figure-level x_range for consistent scaling + x_min, x_max = sim_collect["x_sim"].min(), sim_collect["x_sim"].max() + + # Main plotting loop + for idx, (cluster, ax) in enumerate(zip(unique_clusters, axes)): + # Filter data for current cluster + cluster_data = sim_collect[sim_collect["cluster_title"] == cluster].copy() + cluster_ci = confidence_interval_df[ + confidence_interval_df["cluster_title"] == cluster + ] + + # Get unique rn values preserving original order + unique_rns = pd.Categorical(cluster_data["rn"]).categories + + # Create data matrix for efficient plotting + data_matrix = [] + y_positions = [] + + for i, rn_val in enumerate(unique_rns): + rn_data = cluster_data[cluster_data["rn"] == rn_val]["x_sim"].values + if len(rn_data) > 0: + # Calculate KDE with minimum density threshold (rel_min_height) + kde = stats.gaussian_kde(rn_data, bw_method=0.5) + x_range = np.linspace(x_min, x_max, 200) + density = kde(x_range) + + # Apply minimum density threshold (equivalent to rel_min_height = 0.01) + density[density < np.max(density) * 0.01] = 0 + + # Scale density for better visualization + density = density * 3 # Matches scale=3 in R code + + data_matrix.append(density) + y_positions.append(i) + + # Convert to numpy array for faster operations + data_matrix = np.array(data_matrix) + + # Plot ridges + for i, density in enumerate(data_matrix): + y_base = y_positions[i] + x_range = np.linspace(x_min, x_max, len(density)) + + # Fill area + ax.fill_between( + x_range, + y_base, + y_base + density, + alpha=0.5, + color="#4682B4", # Steel blue color + ) + + # Add outline + ax.plot(x_range, y_base + density, color="#4682B4", linewidth=0.5) + + # Add CI text for each unique rn value + for i, rn_val in enumerate(unique_rns): + cluster_ci_rn = cluster_ci[cluster_ci["rn"] == rn_val] + if not cluster_ci_rn.empty: + # Match R's position_nudge behavior + y_pos = y_positions[i] + 0.1 + x_pos = cluster_ci_rn["boot_mean"].iloc[0] - 0.02 + ax.text( + x_pos, + y_pos, + cluster_ci_rn["boot_ci"].iloc[0], + color="#4D4D4D", + size=9, + ) + + # Add vertical line at x=1 + ax.axvline(x=1, linestyle="--", linewidth=0.5, color="#BFBFBF") + + # Set axis properties + ax.set_xlim(x_min, x_max) + ax.set_ylim(-0.5, len(unique_rns)) + ax.yaxis.set_major_locator(FixedLocator(y_positions)) + ax.set_yticklabels(unique_rns) + + # Add horizontal line for ROAS + if temp == "ROAS": + ax.axhline( + y=1, alpha=0.5, color="#808080", linestyle="--" + ) # Equivalent to grey50 + + # Style the plot to match theme_lares + ax.set_title(f"Cluster {cluster}") + ax.set_xlabel(temp) + ax.set_ylabel("Density") + ax.spines["top"].set_visible(False) + ax.spines["right"].set_visible(False) + # Add visible bottom axis line + ax.spines["bottom"].set_visible(True) + ax.spines["bottom"].set_linewidth(0.5) + ax.set_facecolor("white") + + # Hide empty subplots + for ax in axes[n_clusters:]: + ax.set_visible(False) + + # Set overall title and subtitle + fig.suptitle( + f"In-Cluster {temp} & Bootstrapped 95% CI\n" + "Sampling distribution of cluster mean", + y=0.95, + ) + + # Add caption + fig.text( + 0.5, + 0.02, + f"Based on {ci_results.boot_n:,} bootstrap results with {ci_results.sim_n:,} simulations", + ha="center", + ) + + plt.tight_layout(rect=(0, 0.05, 1, 0.92)) + + figs = plt.gcf() + plt.close(figs) + return figs + + def plot_top_solutions_errors( + self, + df: pd.DataFrame, + top_sols: pd.DataFrame, + limit: int = 1, + balance: list[float] = [1, 1, 1], + ) -> Figure: + """ + Plot the top solutions errors. + Parameters: + df (pd.DataFrame): The DataFrame containing the data. + top_sols (pd.DataFrame): The DataFrame containing the top solutions. + limit (int): The number of top solutions to plot. Default is 1. + balance (Dict[str, float]): The weights for the NRMSE, DECOMP.RSSD, and MAPE metrics. Default is {"nrmse": 1.0, "decomp_rssd": 1.0, "mape": 1.0}. + Returns: + Figure: The matplotlib figure object containing the plot. + """ + # Normalize the balance weights + balance = [b / sum(balance) for b in balance] + + # Merge the DataFrames + merged_df = pd.merge(df, top_sols.iloc[:, :3], on="sol_id", how="left") + merged_df["alpha"] = np.where(merged_df["cluster"].isna(), 0.6, 1) + merged_df["label"] = merged_df.apply( + lambda row: ( + f"[{row['cluster']}:{row['rank']}]" + if not pd.isna(row["cluster"]) + else None + ), + axis=1, + ) + + # Create a new column 'highlight' to track whether each row should be highlighted or not + merged_df["highlight"] = merged_df["label"].notna() + + # Plot the data + plt.figure(figsize=(10, 8)) + palette = sns.color_palette( + "husl", + n_colors=len(merged_df.loc[merged_df["highlight"], "label"].unique()), + as_cmap=False, + ) + + sns.scatterplot( + data=merged_df[~merged_df["highlight"]], + x="nrmse", + y="decomp.rssd", + color="gray", + ) + sns.scatterplot( + data=merged_df[merged_df["highlight"]], + x="nrmse", + y="decomp.rssd", + hue="label", + palette=palette, + ) + + for i, row in merged_df.iterrows(): + if row["highlight"]: + plt.scatter( + row["nrmse"], + row["decomp.rssd"], + alpha=row["alpha"], + color=palette[ + list( + merged_df.loc[merged_df["highlight"], "label"].unique() + ).index(row["label"]) + ], + ) + plt.annotate( + row["label"], + (row["nrmse"], row["decomp.rssd"]), + xytext=(0, 10), + textcoords="offset points", + ha="center", + ) + + plt.title( + f"Selecting Top {limit} Performing Models by Cluster\nBased on minimum (weighted) distance to origin" + ) + plt.xlabel("NRMSE") + plt.ylabel("DECOMP.RSSD") + plt.legend(title="Cluster") + plt.figtext( + 0.5, + 0.01, + f"Weights: NRMSE {round(100 * balance[0])}%, DECOMP.RSSD {round(100 * balance[1])}%, MAPE {round(100 * balance[2])}%", + ha="center", + fontsize=10, + ) + figs = plt.gcf() + plt.close(figs) + return figs # Return the current figure + + def plot_topsols_rois( + self, df: pd.DataFrame, top_sols: pd.DataFrame, all_media: list[str] + ) -> Figure: + """ + Plot the top performing models by media. + Args: + df (pd.DataFrame): The input DataFrame. + top_sols (pd.DataFrame): The top solutions DataFrame. + all_media (list[str]): A list of media names. + limit (int, optional): The number of top performing models to select. Defaults to 1. + Returns: + plt.Figure: The matplotlib figure object containing the plot. + """ + # Select real columns from df + real_rois = df.drop(columns=["mape", "nrmse", "decomp.rssd"]).copy() + real_rois.columns = ["real_" + col for col in real_rois.columns] + + # Merge DataFrames + merged_df = pd.merge( + top_sols, + real_rois, + left_on="sol_id", # Changed from sol_id to match R code + right_on="real_sol_id", + how="left", + ) + + # Create label column + merged_df["label"] = merged_df.apply( + lambda row: f'[{row["cluster"]}.{row["rank"]}]\n{row["sol_id"]}', axis=1 + ) + + # Melt the DataFrame - only select columns containing media names + media_cols = [ + col for col in merged_df.columns if any(media in col for media in all_media) + ] + melted_df = pd.melt( + merged_df, + id_vars=["label"], + value_vars=media_cols, + var_name="media", + value_name="perf", + ) + + # Filter and clean media names + melted_df = melted_df[melted_df["media"].str.contains("real_")].copy() + melted_df["media"] = melted_df["media"].str.replace("real_", "") + media_order = ( + melted_df.groupby("media")["perf"].mean().sort_values(ascending=False).index + ) + + # Create the plot + labels = melted_df["label"].unique() + n_labels = len(labels) + fig, axes = plt.subplots(n_labels, 1, figsize=(10, n_labels * 2), squeeze=False) + + # Plot each subplot + for idx, (label, ax) in enumerate(zip(labels, axes.flatten())): + data = melted_df[melted_df["label"] == label] + + sns.barplot( + data=data, + x="perf", + y="media", + order=media_order, # Use global media ordering + ax=ax, + ) + + ax.set_title(label, loc="right", y=0.5) + ax.set_xlabel("Mean metric per media" if idx == n_labels - 1 else "") + ax.set_ylabel("") + + # Adjust layout + plt.suptitle("Top Performing Models", y=1.02) + plt.tight_layout() + + figs = plt.gcf() + plt.close(figs) + return figs # Return the current figure + + def create_correlations_heatmap(self, correlations: pd.DataFrame) -> Figure: + """ + Creates a heatmap for the correlations. + + Args: + correlations (pd.DataFrame): The DataFrame containing correlation values. + + Returns: + plt.Figure: The heatmap figure. + """ + raise NotImplementedError + + def plot_dimensionality_reduction(self) -> None: + """ + Plot the results of dimensionality reduction (PCA or t-SNE). + """ + raise NotImplementedError + + def generate_bootstrap_confidence( + self, solution_id: str, ax: Optional[plt.Axes] = None + ) -> Optional[plt.Figure]: + """Generate error bar plot showing bootstrapped ROI/CPA confidence intervals.""" + logger.debug("Starting generation of bootstrap confidence plot") + if not hasattr(self, "pareto_result"): + raise ValueError("Pareto result not initialized") + + if solution_id not in self.pareto_result.plot_data_collect: + raise ValueError(f"Invalid solution ID: {solution_id}") + + x_decomp_agg = self.pareto_result.x_decomp_agg[ + self.pareto_result.x_decomp_agg["sol_id"] == solution_id + ] + + if "ci_low" not in x_decomp_agg.columns: + if ax is None: + fig, ax = plt.subplots(figsize=(10, 6)) + ax.text(0.5, 0.5, "No bootstrap results", ha="center", va="center") + return fig + else: + ax.text(0.5, 0.5, "No bootstrap results", ha="center", va="center") + return None + + bootstrap_data = x_decomp_agg[ + (~x_decomp_agg["ci_low"].isna()) + & (~x_decomp_agg["ci_up"].isna()) + & (~x_decomp_agg["boot_mean"].isna()) + & (x_decomp_agg["sol_id"] == solution_id) + ][["rn", "sol_id", "boot_mean", "ci_low", "ci_up"]] + + if bootstrap_data.empty: + if ax is None: + fig, ax = plt.subplots(figsize=(16, 10)) + ax.text( + 0.5, + 0.5, + "No valid bootstrap results after filtering", + ha="center", + va="center", + ) + return fig + else: + ax.text( + 0.5, + 0.5, + "No valid bootstrap results after filtering", + ha="center", + va="center", + ) + return None + + # Sort data alphabetically by rn + bootstrap_data = bootstrap_data.sort_values("rn", ascending=True) + + if ax is None: + fig, ax = plt.subplots(figsize=(12, min(8, 3 + len(bootstrap_data) * 0.3))) + else: + fig = None + + ax.set_facecolor("white") + + metric_type = ( + "ROAS" + if ( + self.mmm_data + and hasattr(self.mmm_data.mmmdata_spec, "dep_var_type") + and self.mmm_data.mmmdata_spec.dep_var_type == DependentVarType.REVENUE + ) + else "CPA" + ) + + y_pos = range(len(bootstrap_data)) + + ax.errorbar( + x=bootstrap_data["boot_mean"], + y=y_pos, + xerr=[ + (bootstrap_data["boot_mean"] - bootstrap_data["ci_low"]), + (bootstrap_data["ci_up"] - bootstrap_data["boot_mean"]), + ], + fmt="o", + color="black", + capsize=3, + markersize=3, + elinewidth=1, + zorder=3, + ) + + for i, row in enumerate(bootstrap_data.itertuples()): + ax.text( + row.boot_mean, + i, + f"{float(f'{row.boot_mean:.2g}')}", + va="bottom", + ha="center", + fontsize=10, + color="black", + ) + + ax.text( + row.ci_low, + i, + f"{float(f'{row.ci_low:.2g}')}", + va="center", + ha="right", + fontsize=9, + color="black", + ) + + ax.text( + row.ci_up, + i, + f"{float(f'{row.ci_up:.2g}')}", + va="center", + ha="left", + fontsize=9, + color="black", + ) + + ax.set_yticks(y_pos) + ax.set_yticklabels(bootstrap_data["rn"], fontsize=9) + + ax.spines["right"].set_visible(False) + ax.spines["top"].set_visible(False) + + if metric_type == "ROAS": + ax.axvline(x=1, color="gray", linestyle="--", alpha=0.5, zorder=2) + + cluster_txt = "" + if self.clustered_result is not None: + temp2 = self.clustered_result.cluster_data + + if "n" not in temp2.columns: + temp2 = ( + temp2.groupby("cluster") + .apply(lambda x: x.assign(n=len(x))) + .reset_index(drop=True) + ) + temp2 = temp2[temp2["sol_id"] == solution_id] + if not temp2.empty: + cluster_txt = f" {temp2['cluster'].iloc[0]} ({temp2['n'].iloc[0]} IDs)" + + title = f"In-cluster{cluster_txt} bootstrapped {metric_type} [95% CI & mean]" + + ax.set_title(title, pad=20, fontsize=11) + + x_min = bootstrap_data["ci_low"].min() + x_max = bootstrap_data["ci_up"].max() + margin = (x_max - x_min) * 0.05 + ax.set_xlim(x_min - margin, x_max + margin) + + ax.grid(True, axis="x", color="lightgray", linestyle="-", alpha=0.3, zorder=1) + ax.set_axisbelow(True) + + logger.debug("Successfully generated bootstrap confidence plot") + if fig: + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + return fig + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> None: + """ + Generate and optionally display or export all plots. + + Args: + display_plots (bool): Whether to display the plots. Default is True. + export_location (Union[str, Path]): The location to export the plots. Default is None. + """ + plots: Dict[str, plt.Figure] = {} + + # Generate plots + if ( + hasattr(self, "pareto_result") + and hasattr(self, "clustered_result") + and hasattr(self, "mmm_data") + ): + try: + wss_plot = self.clustered_result.wss + plots["wss_plot"] = wss_plot + except Exception as e: + logger.error(f"Failed to create WSS plot: {e}") + + try: + ci_plot = ( + self.clustered_result.cluster_ci.clusters_confidence_interval_plot + ) + plots["ci_plot"] = ci_plot + except Exception as e: + logger.error(f"Failed to create confidence intervals plot: {e}") + + try: + plots["top_solutions_errors_plot"] = ( + self.clustered_result.plots.top_solutions_errors_plot + ) + except Exception as e: + logger.error(f"Failed to create top solutions errors plot: {e}") + + try: + plots["topsols_rois_plot"] = ( + self.clustered_result.plots.top_solutions_rois_plot + ) + except Exception as e: + logger.error(f"Failed to create top solutions ROIs plot: {e}") + + try: + correlations_heatmap = self.clustered_result.correlations + if correlations_heatmap is None: + logger.warning( + "create_correlations_heatmap method is not implemented." + ) + else: + plots["correlations_heatmap"] = correlations_heatmap + except Exception as e: + logger.error(f"Failed to create correlations heatmap: {e}") + + try: + solution_ids = self.pareto_result.plot_data_collect.keys() + for solution_id in solution_ids: + bootstrap_confidence_plot = self.generate_bootstrap_confidence( + solution_id + ) + if bootstrap_confidence_plot: + plots[f"bootstrap_confidence_plot_{solution_id}"] = ( + bootstrap_confidence_plot + ) + + break # This will generate too many plots. Only generate plots for the first solution. we can export all plots to a folder if too many to display + except Exception as e: + logger.error(f"Failed to create bootstrap confidence plot: {e}") + + if display_plots: + super().display_plots(plots) diff --git a/python/src/robyn/visualization/feature_visualization.py b/python/src/robyn/visualization/feature_visualization.py new file mode 100644 index 000000000..711d9fda2 --- /dev/null +++ b/python/src/robyn/visualization/feature_visualization.py @@ -0,0 +1,222 @@ +# pyre-strict +import logging +from pathlib import Path +from typing import Dict, Optional, Union + +import seaborn as sns +import matplotlib.pyplot as plt + +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.hyperparameters import Hyperparameters +from robyn.modeling.feature_engineering import FeaturizedMMMData +from robyn.visualization.base_visualizer import BaseVisualizer + + +logger = logging.getLogger(__name__) + + +class FeaturePlotter(BaseVisualizer): + """ + A class for creating various plots related to feature engineering in the Robyn framework. + """ + + def __init__( + self, + mmm_data: MMMData, + hyperparameters: Hyperparameters, + featurized_mmmdata: Optional[FeaturizedMMMData] = None, + ): + """ + Initialize the FeaturePlotter class. + + Args: + mmm_data (MMMData): The input data and specifications for the MMM. + hyperparameters (Hyperparameters): The hyperparameters for the model. + """ + super().__init__() + self.mmm_data = mmm_data + self.hyperparameters = hyperparameters + self.featurized_mmmdata = featurized_mmmdata + logger.info("Initializing FeaturePlotter") + logger.debug("MMM Data: %s", mmm_data) + logger.debug("Hyperparameters: %s", hyperparameters) + + def plot_spend_exposure( + self, channel: str, display: bool = True + ) -> Dict[str, plt.Figure]: + """ + Generates a spend-exposure plot for a specified channel. + + Parameters: + ----------- + channel : str + The name of the channel for which the spend-exposure plot is to be generated. + + Returns: + -------- + plt.Figure + The matplotlib Figure object containing the spend-exposure plot. + + Raises: + ------- + ValueError + If no spend-exposure data or plot data is available for the specified channel. + Exception + If any other error occurs during the plot generation process. + + Notes: + ------ + The function retrieves the model results and plot data for the specified channel from the featurized_mmmdata attribute. + It creates a scatter plot of the actual data and a fitted line plot. The plot includes model information such as + model type, R-squared value, and model-specific parameters (e.g., Vmax and Km for Michaelis-Menten model or coefficient for linear model). + """ + logger.info("Generating spend-exposure plot for channel: %s", channel) + + try: + # Find the result for the current channel + res = next( + ( + item + for item in self.featurized_mmmdata.modNLS["results"] + if item["channel"] == channel + ), + None, + ) + logger.info("Found result for channel %s", channel) + if res is None: + logger.error("Channel %s not found in featurized data results", channel) + raise ValueError( + f"No spend-exposure data available for channel: {channel}" + ) + plot_data = self.featurized_mmmdata.modNLS["plots"].get(channel) + if plot_data is None: + logger.error("Plot data for channel %s not found", channel) + raise ValueError(f"No plot data available for channel: {channel}") + fig, ax = plt.subplots(figsize=(10, 6)) + # Plot scatter of actual data + sns.scatterplot( + x="spend", + y="exposure", + data=plot_data, + ax=ax, + alpha=0.6, + label="Actual", + ) + logger.debug("Created scatter plot for actual data") + # Plot fitted line + sns.lineplot( + x="spend", y="yhat", data=plot_data, ax=ax, color="red", label="Fitted" + ) + logger.debug("Added fitted line to plot") + ax.set_xlabel(f"Spend [{channel}]") + ax.set_ylabel(f"Exposure [{channel}]") + ax.set_title(f"Spend vs Exposure for {channel}") + # Add model information to the plot + model_type = res["model_type"] + rsq = res["rsq"] + logger.debug("Model type: %s, R-squared: %f", model_type, rsq) + if model_type == "nls": + Vmax, Km = res["Vmax"], res["Km"] + ax.text( + 0.05, + 0.95, + f"Model: Michaelis-Menten\nR² = {rsq:.4f}\nVmax = {Vmax:.2f}\nKm = {Km:.2f}", + transform=ax.transAxes, + verticalalignment="top", + bbox=dict(boxstyle="round", facecolor="white", alpha=0.7), + ) + logger.debug("Added NLS model parameters: Vmax=%f, Km=%f", Vmax, Km) + else: + coef = res["coef_lm"] + ax.text( + 0.05, + 0.95, + f"Model: Linear\nR² = {rsq:.4f}\nCoefficient = {coef:.4f}", + transform=ax.transAxes, + verticalalignment="top", + bbox=dict(boxstyle="round", facecolor="white", alpha=0.7), + ) + logger.debug("Added linear model parameters: coefficient=%f", coef) + plt.legend() + plt.tight_layout() + plt.close() + logger.info( + "Successfully generated spend-exposure plot for channel %s", channel + ) + return {"spend-exposure": fig} + except Exception as e: + logger.error( + "Failed to generate spend-exposure plot for channel %s: %s", + channel, + str(e), + exc_info=True, + ) + raise + + def plot_feature_importance( + self, feature_importance: Dict[str, float], display: bool = True + ) -> Dict[str, plt.Figure]: + """ + Plot the importance of different features in the model. + + Args: + feature_importance (Dict[str, float]): Dictionary of feature importances. + + Returns: + plt.Figure: A matplotlib Figure object containing the feature importance plot. + """ + logger.info("Generating feature importance plot") + logger.debug("Feature importance data: %s", feature_importance) + try: + # Implementation placeholder + logger.warning("plot_feature_importance method not implemented yet") + + except Exception as e: + logger.error("Failed to generate feature importance plot: %s", str(e)) + raise + + def plot_response_curves(self, display: bool = True) -> Dict[str, plt.Figure]: + """ + Plot response curves for different channels. + + Args: + self.featurized_mmmdata (FeaturizedMMMData): The featurized data after feature engineering. + + Returns: + Dict[str, plt.Figure]: Dictionary mapping channel names to their respective response curve plots. + """ + logger.info("Generating response curves") + logger.debug("Processing featurized data: %s", self.featurized_mmmdata) + try: + dt_mod = self.featurized_mmmdata.dt_mod + logger.debug("Modified data: %s", dt_mod) + # Rest of the method implementation + logger.warning("plot_response_curves method not fully implemented yet") + + except Exception as e: + logger.error("Failed to generate response curves: %s", str(e)) + raise + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> Dict[str, plt.Figure]: + """ + Override the abstract method plot_all from BaseVisualizer. + """ + logger.info("Generating all plots") + plot_collect: Dict[str, plt.Figure] = {} + try: + for item in self.featurized_mmmdata.modNLS["results"]: + channel = item["channel"] + # plot_collect.update(self.plot_adstock(channel, display)) + # plot_collect.update(self.plot_saturation(channel, display)) + plot_collect[channel] = self.plot_spend_exposure( + channel, display_plots + )["spend-exposure"] + + # plot_collect.update(self.plot_feature_importance({}, display)) + + super().display_plots(plot_collect) + except Exception as e: + logger.error("Failed to generate all plots: %s", str(e)) + raise diff --git a/python/src/robyn/visualization/model_convergence_visualizer.py b/python/src/robyn/visualization/model_convergence_visualizer.py new file mode 100644 index 000000000..8165a3105 --- /dev/null +++ b/python/src/robyn/visualization/model_convergence_visualizer.py @@ -0,0 +1,330 @@ +from pathlib import Path +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib +from IPython.display import Image, display + +matplotlib.use("Agg") +import seaborn as sns +from typing import List, Optional, Union +import io +import base64 +import logging +from robyn.modeling.entities.modeloutputs import Trial + +# Initialize logger for this module +logger = logging.getLogger(__name__) + + +class ModelConvergenceVisualizer: + def __init__( + self, + n_cuts: Optional[int] = None, + nrmse_win: Optional[List[float]] = None, + ts_validation_plot: Optional[List[Trial]] = None, + moo_cloud_plot: Optional[pd.DataFrame] = None, + moo_distrb_plot: Optional[pd.DataFrame] = None, + ): + self.n_cuts = n_cuts + self.nrmse_win = nrmse_win + self.ts_validation_plot = ts_validation_plot + self.moo_cloud_plot = moo_cloud_plot + self.moo_distrb_plot = moo_distrb_plot + logger.info("Initialized ModelConvergenceVisualizer") + + def create_moo_distrb_plot( + self, dt_objfunc_cvg: pd.DataFrame, conv_msg: List[str] + ) -> str: + logger.debug( + "Starting moo distribution plot creation with data shape: %s", + dt_objfunc_cvg.shape, + ) + try: + # Convert 'cuts' to categorical with a specific order + dt_objfunc_cvg["id"] = dt_objfunc_cvg["cuts"].astype(int) + dt_objfunc_cvg["cuts"] = pd.Categorical( + dt_objfunc_cvg["cuts"], + categories=sorted(dt_objfunc_cvg["cuts"].unique(), reverse=True), + ) + # Clip values based on quantiles + logger.debug( + "Processing error types: %s", dt_objfunc_cvg["error_type"].unique() + ) + for error_type in dt_objfunc_cvg["error_type"].unique(): + mask = dt_objfunc_cvg["error_type"] == error_type + original_values = dt_objfunc_cvg.loc[mask, "value"] + quantiles = np.quantile(original_values, self.nrmse_win) + dt_objfunc_cvg.loc[mask, "value"] = np.clip(original_values, *quantiles) + logger.debug( + "Clipped values for error_type %s: min=%f, max=%f", + error_type, + quantiles[0], + quantiles[1], + ) + # Set the style and color palette + sns.set_style("whitegrid") + sns.set_palette("Set2") + # Create the violin plot with a larger figure size + fig, ax = plt.subplots(figsize=(14, 10)) + sns.violinplot( + data=dt_objfunc_cvg, + x="value", + y="cuts", + hue="error_type", + split=True, + inner="quartile", + ax=ax, + ) + ax.set_xlabel("Objective functions", fontsize=12, ha="left", x=0) + ax.set_ylabel("Iterations [#]", fontsize=12) + ax.set_title( + "Objective convergence by iterations quantiles", + fontsize=14, + fontweight="bold", + ) + ax.grid(True, linestyle="--", linewidth=0.5) + # Adjust layout to make room for figtext on the bottom right + plt.subplots_adjust(right=0.75, bottom=0.15) + # Add text annotations on the bottom right + plt.figtext( + 0.98, + 0, + "\n".join(conv_msg), + ha="right", + va="bottom", + fontsize=8, + wrap=True, + ) + plt.tight_layout() + logger.info("Successfully created moo distribution plot") + return self._convert_plot_to_base64(fig) + except Exception as e: + logger.error( + "Failed to create moo distribution plot: %s", str(e), exc_info=True + ) + raise + + def create_moo_cloud_plot( + self, df: pd.DataFrame, conv_msg: List[str], calibrated: bool + ) -> str: + logger.debug( + "Starting moo cloud plot creation with data shape: %s, calibrated=%s", + df.shape, + calibrated, + ) + + try: + # Clip NRMSE values based on quantiles + original_nrmse = df["nrmse"] + quantiles = np.quantile(original_nrmse, self.nrmse_win) + df["nrmse"] = np.clip(original_nrmse, *quantiles) + logger.debug( + "Clipped NRMSE values: min=%f, max=%f", quantiles[0], quantiles[1] + ) + # Set the style and color palette + sns.set_style("whitegrid") + sns.set_palette("Set2") + # Create the scatter plot + fig, ax = plt.subplots(figsize=(12, 10)) + scatter = ax.scatter( + df["nrmse"], + df["decomp.rssd"], + c=df["ElapsedAccum"], + cmap="viridis", + alpha=0.7, + ) + if calibrated and "mape" in df.columns: + logger.debug("Adding calibrated MAPE visualization") + sizes = (df["mape"] - df["mape"].min()) / ( + df["mape"].max() - df["mape"].min() + ) + sizes = sizes * 100 + 10 + ax.scatter( + df["nrmse"], + df["decomp.rssd"], + s=sizes, + alpha=0.5, + edgecolor="w", + linewidth=0.5, + ) + plt.colorbar(scatter, label="Time [s]") + ax.set_xlabel("NRMSE", fontsize=12, ha="left", x=0) + ax.set_ylabel("DECOMP.RSSD", fontsize=12) + ax.set_title( + "Multi-objective evolutionary performance", + fontsize=14, + fontweight="bold", + ) + # Add text annotations on the bottom right + plt.figtext( + 0.98, + 0, + "\n".join(conv_msg), + ha="right", + va="bottom", + fontsize=8, + wrap=True, + ) + plt.tight_layout() + + logger.info("Successfully created moo cloud plot") + return self._convert_plot_to_base64(fig) + + except Exception as e: + logger.error("Failed to create moo cloud plot: %s", str(e), exc_info=True) + raise + + def create_ts_validation_plot(self, trials: List[Trial]) -> str: + logger.debug( + "Starting time-series validation plot creation with %d trials", len(trials) + ) + try: + # Concatenate trial data + result_hyp_param = pd.concat( + [trial.result_hyp_param for trial in trials], ignore_index=True + ) + result_hyp_param["trial"] = ( + result_hyp_param.groupby("sol_id").cumcount() + 1 + ) + result_hyp_param["iteration"] = result_hyp_param.index + 1 + logger.debug("Processing metrics for validation plot") + result_hyp_param_long = result_hyp_param.melt( + id_vars=["sol_id", "trial", "train_size", "iteration"], + value_vars=[ + "rsq_train", + "rsq_val", + "rsq_test", + "nrmse_train", + "nrmse_val", + "nrmse_test", + ], + var_name="metric", + value_name="value", + ) + # Extract dataset and metric type + result_hyp_param_long["dataset"] = ( + result_hyp_param_long["metric"].str.split("_").str[-1] + ) + result_hyp_param_long["metric_type"] = ( + result_hyp_param_long["metric"].str.split("_").str[0] + ) + # Winsorize the data + logger.debug("Winsorizing metric values") + result_hyp_param_long["value"] = result_hyp_param_long.groupby( + "metric_type" + )["value"].transform( + lambda x: np.clip( + x, + np.percentile(x, self.nrmse_win[0] * 100), + np.percentile(x, self.nrmse_win[1] * 100), + ) + ) + # Set the style and color palette + sns.set_style("whitegrid") + sns.set_palette("Set2") + # Determine the number of trials + num_trials = result_hyp_param["trial"].nunique() + # Create subplots + fig, axes = plt.subplots( + num_trials + 1, + 1, + figsize=(12, 5 * (num_trials + 1)), + gridspec_kw={"height_ratios": [3] * num_trials + [1]}, + ) + # NRMSE plots for each trial + for i, (trial, ax) in enumerate( + zip(result_hyp_param["trial"].unique(), axes[:-1]) + ): + nrmse_data = result_hyp_param_long[ + (result_hyp_param_long["metric_type"] == "nrmse") + & (result_hyp_param_long["trial"] == trial) + ] + sns.scatterplot( + data=nrmse_data, + x="iteration", + y="value", + hue="dataset", + style="dataset", + markers=["o", "s", "D"], # Different markers for train, val, test + ax=ax, + alpha=0.6, + ) + sns.lineplot( + data=nrmse_data, + x="iteration", + y="value", + hue="dataset", + ax=ax, + legend=False, + linewidth=1, + ) + ax.set_ylabel(f"NRMSE [Trial {trial}]", fontsize=12, fontweight="bold") + ax.set_xlabel("Iteration", fontsize=12, fontweight="bold") + ax.legend(title="Dataset", loc="upper right") + # Train Size plot + sns.scatterplot( + data=result_hyp_param, + x="iteration", + y="train_size", + hue="trial", + ax=axes[-1], + legend=False, + ) + axes[-1].set_ylabel("Train Size", fontsize=12, fontweight="bold") + axes[-1].set_xlabel("Iteration", fontsize=12, fontweight="bold") + axes[-1].set_ylim(0, 1) + axes[-1].yaxis.set_major_formatter( + plt.FuncFormatter(lambda y, _: "{:.0%}".format(y)) + ) + # Set the overall title + plt.suptitle( + "Time-series validation & Convergence", fontsize=14, fontweight="bold" + ) + plt.tight_layout() + logger.info("Successfully created time-series validation plot") + return self._convert_plot_to_base64(fig) + except Exception as e: + logger.error( + "Failed to create time-series validation plot: %s", + str(e), + exc_info=True, + ) + raise + + def _convert_plot_to_base64(self, fig: plt.Figure) -> str: + logger.debug("Converting plot to base64") + try: + buffer = io.BytesIO() + fig.savefig(buffer, format="png") + buffer.seek(0) + image_png = buffer.getvalue() + buffer.close() + graphic = base64.b64encode(image_png) + logger.debug("Successfully converted plot to base64") + return graphic.decode("utf-8") + except Exception as e: + logger.error("Failed to convert plot to base64: %s", str(e), exc_info=True) + raise + + def display_moo_distrb_plot(self): + """Display the MOO Distribution Plot.""" + self._display_base64_image(self.moo_distrb_plot) + + def display_moo_cloud_plot(self): + """Display the MOO Cloud Plot.""" + self._display_base64_image(self.moo_cloud_plot) + + def display_ts_validation_plot(self): + """Display the Time-Series Validation Plot.""" + self._display_base64_image(self.ts_validation_plot) + + def _display_base64_image(self, base64_image: str): + """Helper method to display a base64-encoded image.""" + display(Image(data=base64.b64decode(base64_image))) + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> None: + + logger.warning("this method is not yet implemented") diff --git a/python/src/robyn/visualization/pareto_visualizer.py b/python/src/robyn/visualization/pareto_visualizer.py new file mode 100644 index 000000000..f9923e356 --- /dev/null +++ b/python/src/robyn/visualization/pareto_visualizer.py @@ -0,0 +1,1005 @@ +from pathlib import Path +import re +from typing import Dict, List, Optional, Union +from matplotlib import ticker +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +from robyn.modeling.entities.modeloutputs import ModelOutputs +import seaborn as sns +import logging +from robyn.data.entities.enums import ProphetVariableType +from robyn.data.entities.holidays_data import HolidaysData +from robyn.modeling.entities.featurized_mmm_data import FeaturizedMMMData +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.data.entities.hyperparameters import AdstockType, Hyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.visualization.base_visualizer import BaseVisualizer +from robyn.data.entities.enums import DependentVarType +import math +import matplotlib.dates as mdates + +logger = logging.getLogger(__name__) + + +class ParetoVisualizer(BaseVisualizer): + def __init__( + self, + pareto_result: ParetoResult, + mmm_data: MMMData, + holiday_data: Optional[HolidaysData] = None, + hyperparameter: Optional[Hyperparameters] = None, + featurized_mmm_data: Optional[FeaturizedMMMData] = None, + unfiltered_pareto_result: Optional[ParetoResult] = None, + model_outputs: Optional[ModelOutputs] = None, + ): + super().__init__() + self.pareto_result = pareto_result + self.mmm_data = mmm_data + self.holiday_data = holiday_data + self.hyperparameter = hyperparameter + self.featurized_mmm_data = featurized_mmm_data + self.unfiltered_pareto_result = unfiltered_pareto_result + self.model_outputs = model_outputs + + def _baseline_vars( + self, baseline_level, prophet_vars: List[ProphetVariableType] = [] + ) -> list: + """ + Returns a list of baseline variables based on the provided level. + Args: + InputCollect (dict): A dictionary containing various input data. + baseline_level (int): The level of baseline variables to include. + Returns: + list: A list of baseline variable names. + """ + # Check if baseline_level is valid + if baseline_level < 0 or baseline_level > 5: + raise ValueError("baseline_level must be an integer between 0 and 5") + baseline_variables = [] + # Level 1: Include intercept variables + if baseline_level >= 1: + baseline_variables.extend(["(Intercept)", "intercept"]) + # Level 2: Include trend variables + if baseline_level >= 2: + baseline_variables.append("trend") + # Level 3: Include prophet variables + if baseline_level >= 3: + baseline_variables.extend(list(set(baseline_variables + prophet_vars))) + # Level 4: Include context variables + if baseline_level >= 4: + baseline_variables.extend(self.mmm_data.mmmdata_spec.context_vars) + # Level 5: Include organic variables + if baseline_level >= 5: + baseline_variables.extend(self.mmm_data.mmmdata_spec.organic_vars) + return list(set(baseline_variables)) + + def format_number(self, x: float, pos=None) -> str: + """Format large numbers with K/M/B abbreviations. + + Args: + x: Number to format + pos: Position (required by matplotlib FuncFormatter but not used) + + Returns: + Formatted string + """ + if abs(x) >= 1e9: + return f"{x/1e9:.1f}B" + elif abs(x) >= 1e6: + return f"{x/1e6:.1f}M" + elif abs(x) >= 1e3: + return f"{x/1e3:.1f}K" + else: + return f"{x:.1f}" + + def generate_waterfall( + self, solution_id: str, ax: Optional[plt.Axes] = None, baseline_level: int = 0 + ) -> Optional[plt.Figure]: + """Generate waterfall chart for specific solution.""" + + logger.debug("Starting generation of waterfall plot") + if solution_id not in self.pareto_result.plot_data_collect: + raise ValueError(f"Invalid solution ID: {solution_id}") + + # Get data for specific solution + plot_data = self.pareto_result.plot_data_collect[solution_id] + waterfall_data = plot_data["plot2data"]["plotWaterfallLoop"].copy() + + # Get baseline variables + prophet_vars = self.holiday_data.prophet_vars if self.holiday_data else [] + baseline_vars = self._baseline_vars(baseline_level, prophet_vars) + + # Transform baseline variables + waterfall_data["rn"] = np.where( + waterfall_data["rn"].isin(baseline_vars), + f"Baseline_L{baseline_level}", + waterfall_data["rn"], + ) + + # Group and summarize + waterfall_data = ( + waterfall_data.groupby("rn", as_index=False) + .agg({"xDecompAgg": "sum", "xDecompPerc": "sum"}) + .reset_index() + ) + + # Sort by percentage contribution + waterfall_data = waterfall_data.sort_values("xDecompPerc", ascending=True) + + # Calculate waterfall positions + waterfall_data["end"] = 1 - waterfall_data["xDecompPerc"].cumsum() + waterfall_data["start"] = waterfall_data["end"].shift(1) + waterfall_data["start"] = waterfall_data["start"].fillna(1) + waterfall_data["sign"] = np.where( + waterfall_data["xDecompPerc"] >= 0, "Positive", "Negative" + ) + + # Create figure if no axes provided + if ax is None: + fig, ax = plt.subplots(figsize=(12, 8)) + else: + fig = None + + # Define colors + colors = {"Positive": "#59B3D2", "Negative": "#E5586E"} + + # Create categorical y-axis positions + y_pos = np.arange(len(waterfall_data)) + + # Create horizontal bars + bars = ax.barh( + y=y_pos, + width=waterfall_data["start"] - waterfall_data["end"], + left=waterfall_data["end"], + color=[colors[sign] for sign in waterfall_data["sign"]], + height=0.6, + ) + + # Add text labels + for idx, row in enumerate(waterfall_data.itertuples()): + # Format label text + if abs(row.xDecompAgg) >= 1e9: + formatted_num = f"{row.xDecompAgg/1e9:.1f}B" + elif abs(row.xDecompAgg) >= 1e6: + formatted_num = f"{row.xDecompAgg/1e6:.1f}M" + elif abs(row.xDecompAgg) >= 1e3: + formatted_num = f"{row.xDecompAgg/1e3:.1f}K" + else: + formatted_num = f"{row.xDecompAgg:.1f}" + + # Calculate x-position as the middle of the bar + x_pos = (row.start + row.end) / 2 + + # Use y_pos[idx] to ensure alignment with bars + ax.text( + x_pos, + y_pos[idx], # Use the same y-position as the corresponding bar + f"{formatted_num}\n{row.xDecompPerc*100:.1f}%", + ha="center", # Center align horizontally + va="center", # Center align vertically + fontsize=9, + linespacing=0.9, + ) + + # Set y-ticks and labels + ax.set_yticks(y_pos) + ax.set_yticklabels(waterfall_data["rn"]) + + # Format x-axis as percentage + ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: "{:.0%}".format(x))) + ax.set_xticks(np.arange(0, 1.1, 0.2)) + + # Set plot limits + ax.set_xlim(0, 1) + ax.set_ylim(-0.5, len(waterfall_data) - 0.5) + + # Add legend at top + from matplotlib.patches import Patch + + legend_elements = [ + Patch(facecolor=colors["Positive"], label="Positive"), + Patch(facecolor=colors["Negative"], label="Negative"), + ] + + # Create legend with white background + legend = ax.legend( + handles=legend_elements, + title="Sign", + loc="upper left", + bbox_to_anchor=(0, 1.15), + ncol=2, + frameon=True, + framealpha=1.0, + ) + + # Set title + ax.set_title("Response Decomposition Waterfall", pad=30, x=0.5, y=1.05) + + # Label axes + ax.set_xlabel("Contribution") + ax.set_ylabel(None) + + # Customize grid + ax.grid(True, axis="x", alpha=0.2) + ax.set_axisbelow(True) + + logger.debug("Successfully generated waterfall plot") + # Adjust layout + if fig: + plt.subplots_adjust(right=0.85, top=0.85) + fig = plt.gcf() + plt.close(fig) + return fig + + return None + + def generate_fitted_vs_actual( + self, solution_id: str, ax: Optional[plt.Axes] = None + ) -> Optional[plt.Figure]: + """Generate time series plot comparing fitted vs actual values. + + Args: + ax: Optional matplotlib axes to plot on. If None, creates new figure + + Returns: + Optional[plt.Figure]: Generated matplotlib Figure object + """ + + logger.debug("Starting generation of fitted vs actual plot") + + if solution_id not in self.pareto_result.plot_data_collect: + raise ValueError(f"Invalid solution ID: {solution_id}") + + # Get data for specific solution + plot_data = self.pareto_result.plot_data_collect[solution_id] + ts_data = plot_data["plot5data"]["xDecompVecPlotMelted"].copy() + + # Ensure ds column is datetime and remove any NaT values + ts_data["ds"] = pd.to_datetime(ts_data["ds"]) + ts_data = ts_data.dropna(subset=["ds"]) # Remove rows with NaT dates + + if ts_data.empty: + logger.warning(f"No valid date data found for solution {solution_id}") + return None + + ts_data["linetype"] = np.where( + ts_data["variable"] == "predicted", "solid", "dotted" + ) + ts_data["variable"] = ts_data["variable"].str.title() + + # Get train_size from x_decomp_agg + train_size_series = self.pareto_result.x_decomp_agg[ + self.pareto_result.x_decomp_agg["sol_id"] == solution_id + ]["train_size"] + + if not train_size_series.empty: + train_size = float(train_size_series.iloc[0]) + else: + train_size = 0 + + if ax is None: + fig, ax = plt.subplots(figsize=(20, 10)) + else: + fig = None + + colors = { + "Actual": "#FF6B00", # Darker orange + "Predicted": "#0066CC", # Darker blue + } + + # Plot lines with different styles for predicted vs actual + for var in ts_data["variable"].unique(): + var_data = ts_data[ts_data["variable"] == var] + linestyle = "solid" if var_data["linetype"].iloc[0] == "solid" else "dotted" + ax.plot( + var_data["ds"], + var_data["value"], + label=var, + linestyle=linestyle, + linewidth=1, + color=colors[var], + ) + + # Format y-axis with abbreviations + ax.yaxis.set_major_formatter(ticker.FuncFormatter(self.format_number)) + + # Set y-axis limits with some padding + y_min, y_max = ax.get_ylim() + ax.set_ylim(y_min, y_max * 1.2) # Add 20% padding at the top + + # Add training/validation/test splits if train_size exists and is valid + if train_size > 0: + try: + # Get unique sorted dates, excluding NaT + unique_dates = sorted(ts_data["ds"].dropna().unique()) + total_days = len(unique_dates) + + if total_days > 0: + # Calculate split points + train_cut = int(total_days * train_size) + val_cut = train_cut + int(total_days * (1 - train_size) / 2) + + # Get dates for splits + splits = [ + (train_cut, "Train", train_size), + (val_cut, "Validation", (1 - train_size) / 2), + (total_days - 1, "Test", (1 - train_size) / 2), + ] + + # Get y-axis limits for text placement + y_min, y_max = ax.get_ylim() + + # Add vertical lines and labels + for idx, label, size in splits: + if 0 <= idx < len(unique_dates): # Ensure index is valid + date = unique_dates[idx] + if pd.notna(date): # Check if date is valid + # Add vertical line - extend beyond the top of the plot + ax.axvline( + date, color="#39638b", alpha=0.8, ymin=0, ymax=1.1 + ) + + # Add rotated text label + ax.text( + date, + y_max, + f"{label}: {size*100:.1f}%", + rotation=270, + color="#39638b", + alpha=0.5, + size=9, + ha="left", + va="top", + ) + except Exception as e: + logger.warning(f"Error adding split lines: {str(e)}") + # Continue with the rest of the plot even if split lines fail + + # Set title and labels + ax.set_title("Actual vs. Predicted Response", pad=20) + ax.set_xlabel("Date") + ax.set_ylabel("Response") + + # Configure legend + ax.legend( + bbox_to_anchor=(0.01, 1.02), # Position at top-left + loc="lower left", + ncol=2, # Two columns side by side + borderaxespad=0, + frameon=False, + fontsize=7, + handlelength=2, # Length of the legend lines + handletextpad=0.5, # Space between line and text + columnspacing=1.0, # Space between columns + ) + + # Grid styling + ax.grid(True, alpha=0.2) + ax.set_axisbelow(True) + ax.set_facecolor("white") + + # Format dates on x-axis using datetime locator and formatter + years = mdates.YearLocator() + years_fmt = mdates.DateFormatter("%Y") + ax.xaxis.set_major_locator(years) + ax.xaxis.set_major_formatter(years_fmt) + + logger.debug("Successfully generated fitted vs actual plot") + if fig: + plt.tight_layout() + plt.subplots_adjust(top=0.85) + fig = plt.gcf() + plt.close(fig) + return fig + return None + + def generate_diagnostic_plot( + self, solution_id: str, ax: Optional[plt.Axes] = None + ) -> Optional[plt.Figure]: + """Generate diagnostic scatter plot of fitted vs residual values. + + Args: + ax: Optional matplotlib axes to plot on. If None, creates new figure + + Returns: + Optional[plt.Figure]: Generated matplotlib Figure object + """ + + logger.debug("Starting generation of diagnostic plot") + + if solution_id not in self.pareto_result.plot_data_collect: + raise ValueError(f"Invalid solution ID: {solution_id}") + + # Get data for specific solution + plot_data = self.pareto_result.plot_data_collect[solution_id] + diag_data = plot_data["plot6data"]["xDecompVecPlot"].copy() + + # Calculate residuals + diag_data["residuals"] = diag_data["actual"] - diag_data["predicted"] + + # Create figure if no axes provided + if ax is None: + fig, ax = plt.subplots(figsize=(16, 10)) + else: + fig = None + + # Create scatter plot + ax.scatter( + diag_data["predicted"], diag_data["residuals"], alpha=0.5, color="steelblue" + ) + + # Add horizontal line at y=0 + ax.axhline(y=0, color="black", linestyle="-", linewidth=0.8) + + # Add smoothed line with confidence interval + from scipy.stats import gaussian_kde + + x_smooth = np.linspace( + diag_data["predicted"].min(), diag_data["predicted"].max(), 100 + ) + + # Fit LOWESS + from statsmodels.nonparametric.smoothers_lowess import lowess + + smoothed = lowess(diag_data["residuals"], diag_data["predicted"], frac=0.2) + + # Plot smoothed line + ax.plot(smoothed[:, 0], smoothed[:, 1], color="red", linewidth=2, alpha=0.8) + + # Calculate confidence intervals (using standard error bands) + residual_std = np.std(diag_data["residuals"]) + ax.fill_between( + smoothed[:, 0], + smoothed[:, 1] - 2 * residual_std, + smoothed[:, 1] + 2 * residual_std, + color="red", + alpha=0.1, + ) + + # Format axes with abbreviations + ax.xaxis.set_major_formatter(ticker.FuncFormatter(self.format_number)) + ax.yaxis.set_major_formatter(ticker.FuncFormatter(self.format_number)) + + # Set labels and title + ax.set_xlabel("Fitted") + ax.set_ylabel("Residual") + ax.set_title("Fitted vs. Residual") + + # Customize grid + ax.grid(True, alpha=0.2) + ax.set_axisbelow(True) + + # Use white background + ax.set_facecolor("white") + + logger.debug("Successfully generated of diagnostic plot") + + if fig: + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + return fig + return None + + def generate_immediate_vs_carryover( + self, solution_id: str, ax: Optional[plt.Axes] = None + ) -> Optional[plt.Figure]: + """Generate stacked bar chart comparing immediate vs carryover effects. + + Args: + ax: Optional matplotlib axes to plot on. If None, creates new figure + + Returns: + plt.Figure if ax is None, else None + """ + + logger.debug("Starting generation of immediate vs carryover plot") + + if solution_id not in self.pareto_result.plot_data_collect: + raise ValueError(f"Invalid solution ID: {solution_id}") + + plot_data = self.pareto_result.plot_data_collect[solution_id] + df_imme_caov = plot_data["plot7data"].copy() + + # Ensure percentage is numeric + df_imme_caov["percentage"] = pd.to_numeric( + df_imme_caov["percentage"], errors="coerce" + ) + + # Sort channels alphabetically + df_imme_caov = df_imme_caov.sort_values("rn", ascending=True) + + # Set up type factor levels matching R plot order + df_imme_caov["type"] = pd.Categorical( + df_imme_caov["type"], categories=["Immediate", "Carryover"], ordered=True + ) + + if ax is None: + fig, ax = plt.subplots(figsize=(16, 10)) + else: + fig = None + + colors = {"Immediate": "#59B3D2", "Carryover": "coral"} + + bottom = np.zeros(len(df_imme_caov["rn"].unique())) + y_pos = range(len(df_imme_caov["rn"].unique())) + channels = df_imme_caov["rn"].unique() + types = ["Immediate", "Carryover"] # Order changed to Immediate first + + # Normalize percentages to sum to 100% for each channel + for channel in channels: + mask = df_imme_caov["rn"] == channel + total = df_imme_caov.loc[mask, "percentage"].sum() + if total > 0: # Avoid division by zero + df_imme_caov.loc[mask, "percentage"] = ( + df_imme_caov.loc[mask, "percentage"] / total + ) + + for type_name in types: + type_data = df_imme_caov[df_imme_caov["type"] == type_name] + percentages = type_data["percentage"].values + + bars = ax.barh( + y_pos, + percentages, + left=bottom, + height=0.5, + label=type_name, + color=colors[type_name], + ) + + for i, (rect, percentage) in enumerate(zip(bars, percentages)): + width = rect.get_width() + x_pos = bottom[i] + width / 2 + try: + percentage_text = f"{round(float(percentage) * 100)}%" + except (ValueError, TypeError): + percentage_text = "0%" + ax.text(x_pos, i, percentage_text, ha="center", va="center") + + bottom += percentages + + ax.set_yticks(y_pos) + ax.set_yticklabels(channels) + + ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f"{x*100:.0f}%")) + ax.set_xlim(0, 1) + + # Reduced legend size + ax.legend( + title=None, + bbox_to_anchor=(0, 1.02, 0.15, 0.1), # Reduced width from 0.3 to 0.2 + loc="lower left", + ncol=2, + mode="expand", + borderaxespad=0, + frameon=False, + fontsize=7, # Reduced from 8 to 7 + ) + + ax.set_xlabel("% Response") + ax.set_ylabel(None) + ax.set_title("Immediate vs. Carryover Response Percentage", pad=50, y=1.2) + + ax.grid(True, axis="x", alpha=0.2) + ax.grid(False, axis="y") + ax.set_axisbelow(True) + ax.set_facecolor("white") + + if fig: + plt.tight_layout() + plt.subplots_adjust(top=0.85) + fig = plt.gcf() + plt.close(fig) + return fig + return None + + def generate_adstock_rate( + self, solution_id: str, ax: Optional[plt.Axes] = None + ) -> Optional[plt.Figure]: + """Generate adstock rate visualization based on adstock type. + + Args: + solution_id: ID of solution to visualize + ax: Optional matplotlib axes to plot on. If None, creates new figure + + Returns: + Optional[plt.Figure]: Generated figure if ax is None, otherwise None + """ + + logger.debug("Starting generation of adstock plot") + + plot_data = self.pareto_result.plot_data_collect[solution_id] + adstock_data = plot_data["plot3data"] + + if ax is None: + fig, ax = plt.subplots(figsize=(16, 10)) + else: + fig = None + + # Handle different adstock types + if self.hyperparameter.adstock == AdstockType.GEOMETRIC: + dt_geometric = adstock_data["dt_geometric"].copy() + + # Sort data alphabetically by channel + dt_geometric = dt_geometric.sort_values("channels", ascending=True) + + bars = ax.barh( + y=range(len(dt_geometric)), + width=dt_geometric["thetas"], + height=0.5, + color="coral", + ) + + for i, theta in enumerate(dt_geometric["thetas"]): + ax.text( + theta + 0.01, i, f"{theta*100:.1f}%", va="center", fontweight="bold" + ) + + ax.set_yticks(range(len(dt_geometric))) + ax.set_yticklabels(dt_geometric["channels"]) + + # Format x-axis with 25% increments + ax.xaxis.set_major_formatter( + plt.FuncFormatter(lambda x, p: f"{x*100:.0f}%") + ) + ax.set_xlim(0, 1) + ax.set_xticks(np.arange(0, 1.25, 0.25)) # Changed to 0.25 increments + + # Set title and labels + interval_type = ( + self.mmm_data.mmmdata_spec.interval_type if self.mmm_data else "day" + ) + ax.set_title( + f"Geometric Adstock: Fixed Rate Over Time (Solution {solution_id})" + ) + ax.set_xlabel(f"Thetas [by {interval_type}]") + ax.set_ylabel(None) + + elif self.hyperparameter.adstock in [ + AdstockType.WEIBULL_CDF, + AdstockType.WEIBULL_PDF, + ]: + # [Weibull code remains the same] + weibull_data = adstock_data["weibullCollect"] + wb_type = adstock_data["wb_type"] + + channels = sorted( + weibull_data["channel"].unique() + ) # Sort channels alphabetically + rows = (len(channels) + 2) // 3 + + if ax is None: + fig, axes = plt.subplots(rows, 3, figsize=(15, 4 * rows), squeeze=False) + axes = axes.flatten() + else: + gs = ax.get_gridspec() + subfigs = ax.figure.subfigures(rows, 3) + axes = [subfig.subplots() for subfig in subfigs] + axes = [ax for sublist in axes for ax in sublist] + + for idx, channel in enumerate(channels): + ax_sub = axes[idx] + channel_data = weibull_data[weibull_data["channel"] == channel] + + ax_sub.plot( + channel_data["x"], + channel_data["decay_accumulated"], + color="steelblue", + ) + + ax_sub.axhline(y=0.5, color="gray", linestyle="--", alpha=0.5) + ax_sub.text( + max(channel_data["x"]), + 0.5, + "Halflife", + color="gray", + va="bottom", + ha="right", + ) + + ax_sub.set_title(channel) + ax_sub.grid(True, alpha=0.2) + ax_sub.set_ylim(0, 1) + + # Customize grid + if self.hyperparameter.adstock == AdstockType.GEOMETRIC: + ax.grid(True, axis="x", alpha=0.2) + ax.grid(False, axis="y") + ax.set_axisbelow(True) + + ax.set_facecolor("white") + + logger.debug("Successfully generated adstock plot") + + if fig: + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + return fig + return None + + def create_prophet_decomposition_plot(self): + """Create Prophet Decomposition Plot.""" + prophet_vars = ( + [ProphetVariableType(var) for var in self.holiday_data.prophet_vars] + if self.holiday_data and self.holiday_data.prophet_vars + else [] + ) + factor_vars = self.mmm_data.mmmdata_spec.factor_vars if self.mmm_data else [] + if not (prophet_vars or factor_vars): + return None + df = self.featurized_mmm_data.dt_mod.copy() + prophet_vars_str = [variable.value for variable in prophet_vars] + prophet_vars_str.sort(reverse=True) + value_variables = ( + [ + ( + "dep_var" + if hasattr(df, "dep_var") + else self.mmm_data.mmmdata_spec.dep_var + ) + ] + + factor_vars + + prophet_vars_str + ) + df_long = df.melt( + id_vars=["ds"], + value_vars=value_variables, + var_name="variable", + value_name="value", + ) + df_long["ds"] = pd.to_datetime(df_long["ds"]) + plt.figure(figsize=(12, 3 * len(df_long["variable"].unique()))) + prophet_decomp_plot = plt.figure( + figsize=(12, 3 * len(df_long["variable"].unique())) + ) + gs = prophet_decomp_plot.add_gridspec(len(df_long["variable"].unique()), 1) + for i, var in enumerate(df_long["variable"].unique()): + ax = prophet_decomp_plot.add_subplot(gs[i, 0]) + var_data = df_long[df_long["variable"] == var] + ax.plot(var_data["ds"], var_data["value"], color="steelblue") + ax.set_title(var) + ax.set_xlabel(None) + ax.set_ylabel(None) + plt.suptitle("Prophet decomposition") + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + return fig + + def create_hyperparameter_sampling_distribution(self): + """Create Hyperparameter Sampling Distribution Plot.""" + unfiltered_pareto_results = self.unfiltered_pareto_result + if unfiltered_pareto_results is None: + return None + result_hyp_param = unfiltered_pareto_results.result_hyp_param + hp_names = list(self.hyperparameter.hyperparameters.keys()) + hp_names = [name.replace("lambda", "lambda_hp") for name in hp_names] + matching_columns = [ + col + for col in result_hyp_param.columns + if any(re.search(pattern, col, re.IGNORECASE) for pattern in hp_names) + ] + matching_columns.sort() + hyp_df = result_hyp_param[matching_columns] + melted_df = hyp_df.melt(var_name="variable", value_name="value") + melted_df["variable"] = melted_df["variable"].replace("lambda_hp", "lambda") + + def parse_variable(variable): + parts = variable.split("_") + return {"type": parts[-1], "channel": "_".join(parts[:-1])} + + parsed_vars = melted_df["variable"].apply(parse_variable).apply(pd.Series) + melted_df[["type", "channel"]] = parsed_vars + melted_df["type"] = pd.Categorical( + melted_df["type"], categories=melted_df["type"].unique() + ) + melted_df["channel"] = pd.Categorical( + melted_df["channel"], categories=melted_df["channel"].unique()[::-1] + ) + plt.figure(figsize=(12, 7)) + g = sns.FacetGrid(melted_df, col="type", sharex=False, height=6, aspect=1) + + def violin_plot(x, y, **kwargs): + sns.violinplot(x=x, y=y, **kwargs, alpha=0.8, linewidth=0) + + g.map_dataframe( + violin_plot, x="value", y="channel", hue="channel", palette="Set2" + ) + g.set_titles("{col_name}") + g.set_xlabels("Hyperparameter space") + g.set_ylabels("") + g.figure.suptitle("Hyperparameters Optimization Distributions", y=1.05) + subtitle_text = ( + f"Sample distribution, iterations = " + f"{self.model_outputs.iterations} x {len(self.model_outputs.trials)} trial" + ) + g.figure.text(0.5, 0.98, subtitle_text, ha="center", fontsize=10) + plt.subplots_adjust(top=0.9) + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + return fig + + def create_pareto_front_plot(self, is_calibrated): + """Create Pareto Front Plot.""" + unfiltered_pareto_results = self.unfiltered_pareto_result + result_hyp_param = unfiltered_pareto_results.result_hyp_param + pareto_fronts = self.pareto_result.pareto_fronts + if is_calibrated: + result_hyp_param["iterations"] = np.where( + result_hyp_param["robynPareto"].isna(), + np.nan, + result_hyp_param["iterations"], + ) + result_hyp_param = result_hyp_param.sort_values( + by="robynPareto", na_position="first" + ) + pareto_fronts_vec = list(range(1, pareto_fronts + 1)) + plt.figure(figsize=(12, 8)) + scatter = plt.scatter( + result_hyp_param["nrmse"], + result_hyp_param["decomp.rssd"], + c=result_hyp_param["iterations"], + cmap="Blues", + alpha=0.7, + ) + plt.colorbar(scatter, label="Iterations") + if is_calibrated: + scatter = plt.scatter( + result_hyp_param["nrmse"], + result_hyp_param["decomp.rssd"], + c=result_hyp_param["iterations"], + cmap="Blues", + s=result_hyp_param["mape"] * 100, + alpha=1 - result_hyp_param["mape"], + ) + for pfs in range(1, max(pareto_fronts_vec) + 1): + temp = result_hyp_param[result_hyp_param["robynPareto"] == pfs] + if len(temp) > 1: + temp = temp.sort_values("nrmse") + plt.plot(temp["nrmse"], temp["decomp.rssd"], color="coral", linewidth=2) + plt.title( + "Multi-objective Evolutionary Performance" + + (" with Calibration" if is_calibrated else "") + ) + plt.xlabel("NRMSE") + plt.ylabel("DECOMP.RSSD") + plt.suptitle( + f"2D Pareto fronts with {self.model_outputs.nevergrad_algo or 'Unknown'}, " + f"for {len(self.model_outputs.trials)} trial{'' if pareto_fronts == 1 else 's'} " + f"with {self.model_outputs.iterations or 1} iterations each" + ) + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + return fig + + def create_ridgeline_model_convergence(self): + """Create Ridgeline Model Convergence Plots.""" + all_plots = {} + x_decomp_agg = self.unfiltered_pareto_result.x_decomp_agg + paid_media_spends = self.mmm_data.mmmdata_spec.paid_media_spends + dt_ridges = x_decomp_agg[x_decomp_agg["rn"].isin(paid_media_spends)].copy() + dt_ridges["iteration"] = ( + dt_ridges["iterNG"] - 1 + ) * self.model_outputs.cores + dt_ridges["iterPar"] + dt_ridges = dt_ridges[["rn", "roi_total", "iteration", "trial"]] + dt_ridges = dt_ridges.sort_values(["iteration", "rn"]) + iterations = self.model_outputs.iterations or 100 + qt_len = ( + 1 + if iterations <= 100 + else (20 if iterations > 2000 else int(np.ceil(iterations / 100))) + ) + set_qt = np.floor(np.linspace(1, iterations, qt_len + 1)).astype(int) + set_bin = set_qt[1:] + dt_ridges["iter_bin"] = pd.cut( + dt_ridges["iteration"], bins=set_qt, labels=set_bin + ) + dt_ridges = dt_ridges.dropna(subset=["iter_bin"]) + dt_ridges["iter_bin"] = pd.Categorical( + dt_ridges["iter_bin"], + categories=sorted(set_bin, reverse=True), + ordered=True, + ) + dt_ridges["trial"] = dt_ridges["trial"].astype("category") + plot_vars = dt_ridges["rn"].unique() + plot_n = int(np.ceil(len(plot_vars) / 6)) + metric = ( + "ROAS" + if self.mmm_data.mmmdata_spec.dep_var_type == DependentVarType.REVENUE + else "CPA" + ) + for pl in range(1, plot_n + 1): + start_idx = (pl - 1) * 6 + loop_vars = plot_vars[start_idx : start_idx + 6] + dt_ridges_loop = dt_ridges[dt_ridges["rn"].isin(loop_vars)] + fig, axes = plt.subplots( + nrows=len(loop_vars), figsize=(12, 3 * len(loop_vars)), sharex=False + ) + if len(loop_vars) == 1: + axes = [axes] + for idx, var in enumerate(loop_vars): + var_data = dt_ridges_loop[dt_ridges_loop["rn"] == var] + offset = 0 + for iter_bin in sorted(var_data["iter_bin"].unique(), reverse=True): + bin_data = var_data[var_data["iter_bin"] == iter_bin]["roi_total"] + sns.kdeplot( + bin_data, + ax=axes[idx], + fill=True, + alpha=0.6, + color=plt.cm.GnBu(offset / len(var_data["iter_bin"].unique())), + label=f"Bin {iter_bin}", + warn_singular=False, + ) + offset += 1 + axes[idx].set_title(f"{var} {metric}") + axes[idx].set_ylabel("") + axes[idx].legend().remove() + axes[idx].spines["right"].set_visible(False) + axes[idx].spines["top"].set_visible(False) + plt.suptitle(f"{metric} Distribution over Iteration Buckets", fontsize=16) + plt.tight_layout() + fig = plt.gcf() + plt.close(fig) + all_plots[f"{metric}_convergence_{pl}"] = fig + return all_plots + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> None: + # Generate all plots + solution_ids = self.pareto_result.pareto_solutions + # Clean up nan values + cleaned_solution_ids = [ + sid + for sid in solution_ids + if not (isinstance(sid, float) and math.isnan(sid)) + ] + # Assign the cleaned list back to self.pareto_result.pareto_solutions + self.pareto_result.pareto_solutions = cleaned_solution_ids + figures: Dict[str, plt.Figure] = {} + + for solution_id in cleaned_solution_ids: + fig1 = self.generate_waterfall(solution_id) + if fig1: + figures["waterfall_" + solution_id] = fig1 + + fig2 = self.generate_fitted_vs_actual(solution_id) + if fig2: + figures["fitted_vs_actual_" + solution_id] = fig2 + + fig3 = self.generate_diagnostic_plot(solution_id) + if fig3: + figures["diagnostic_plot_" + solution_id] = fig3 + + fig4 = self.generate_immediate_vs_carryover(solution_id) + if fig4: + figures["immediate_vs_carryover_" + solution_id] = fig4 + + fig5 = self.generate_adstock_rate(solution_id) + if fig5: + figures["adstock_rate_" + solution_id] = fig5 + + break # TODO: This will generate too many plots. Only generate plots for the first solution. we can export all plots to a folder if too many to display + + if not self.model_outputs.hyper_fixed: + prophet_decomp_plot = self.create_prophet_decomposition_plot() + if prophet_decomp_plot: + figures["prophet_decomp"] = prophet_decomp_plot + hyperparameters_plot = self.create_hyperparameter_sampling_distribution() + if hyperparameters_plot: + figures["hyperparameters_sampling"] = hyperparameters_plot + pareto_front_plot = self.create_pareto_front_plot(is_calibrated=False) + if pareto_front_plot: + figures["pareto_front"] = pareto_front_plot + ridgeline_plots = self.create_ridgeline_model_convergence() + figures.update(ridgeline_plots) + + # Display plots if required + if display_plots: + self.display_plots(figures) diff --git a/python/src/robyn/visualization/response_visualizer.py b/python/src/robyn/visualization/response_visualizer.py new file mode 100644 index 000000000..6be3980df --- /dev/null +++ b/python/src/robyn/visualization/response_visualizer.py @@ -0,0 +1,206 @@ +from pathlib import Path +from typing import Optional, Union +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import logging +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.visualization.base_visualizer import BaseVisualizer + +logger = logging.getLogger(__name__) + + +class ResponseVisualizer(BaseVisualizer): + def __init__(self, pareto_result: ParetoResult, mmm_data: MMMData): + super().__init__() + logger.debug( + "Initializing ResponseVisualizer with pareto_result=%s, mmm_data=%s", + pareto_result, + mmm_data, + ) + self.pareto_result = pareto_result + self.mmm_data = mmm_data + + def plot_response(self) -> plt.Figure: + """ + Plot response curves. + + Returns: + plt.Figure: The generated figure. + """ + logger.info("Starting response curve plotting") + pass + + def plot_marginal_response(self) -> plt.Figure: + """ + Plot marginal response curves. + + Returns: + plt.Figure: The generated figure. + """ + logger.info("Starting marginal response curve plotting") + pass + + def generate_response_curves( + self, solution_id: str, ax: Optional[plt.Axes] = None, trim_rate: float = 1.3 +) -> Optional[plt.Figure]: + """Generate response curves showing relationship between spend and response.""" + logger.debug("Generating response curves with trim_rate=%.2f", trim_rate) + + if solution_id not in self.pareto_result.plot_data_collect: + raise ValueError(f"Invalid solution ID: {solution_id}") + + try: + # Get plot data for specific solution + logger.debug("Extracting plot data from pareto results") + plot_data = self.pareto_result.plot_data_collect[solution_id] + curve_data = plot_data["plot4data"]["dt_scurvePlot"].copy() + mean_data = plot_data["plot4data"]["dt_scurvePlotMean"].copy() + + logger.debug("Initial curve data shape: %s", curve_data.shape) + logger.debug("Initial mean data shape: %s", mean_data.shape) + + # Scale down the values to thousands + curve_data["spend"] = curve_data["spend"] / 1000 + curve_data["response"] = curve_data["response"] / 1000 + mean_data["mean_spend_adstocked"] = mean_data["mean_spend_adstocked"] / 1000 + mean_data["mean_response"] = mean_data["mean_response"] / 1000 + if "mean_carryover" in mean_data.columns: + mean_data["mean_carryover"] = mean_data["mean_carryover"] / 1000 + + # Add mean carryover information + curve_data = curve_data.merge( + mean_data[["channel", "mean_carryover"]], on="channel", how="left" + ) + + if ax is None: + logger.debug("Creating new figure with axes") + fig, ax = plt.subplots(figsize=(16, 10)) + else: + logger.debug("Using provided axes") + fig = None + + # Define custom colors matching the R plot + color_map = { + 'facebook_S': '#FF9D1C', # Orange + 'ooh_S': '#69B3E7', # Light blue + 'print_S': '#7B4EA3', # Purple + 'search_S': '#E41A1C', # Red + 'tv_S': '#4DAF4A' # Green + } + + channels = curve_data["channel"].unique() + logger.debug("Processing %d unique channels: %s", len(channels), channels) + + for channel in channels: + logger.debug("Plotting response curve for channel: %s", channel) + channel_data = curve_data[curve_data["channel"] == channel].sort_values( + "spend" + ) + + color = color_map.get(channel, 'gray') # Default to gray if channel not in map + + ax.plot( + channel_data["spend"], + channel_data["response"], + color=color, + label=channel, + zorder=2, + ) + + if "mean_carryover" in channel_data.columns: + logger.debug("Adding carryover shading for channel: %s", channel) + carryover_data = channel_data[ + channel_data["spend"] <= channel_data["mean_carryover"].iloc[0] + ] + ax.fill_between( + carryover_data["spend"], + carryover_data["response"], + color="grey", + alpha=0.2, + zorder=1, + ) + + logger.debug("Adding mean points and labels") + for idx, row in mean_data.iterrows(): + channel = row['channel'] + color = color_map.get(channel, 'gray') + + ax.scatter( + row["mean_spend_adstocked"], + row["mean_response"], + color=color, + s=100, + zorder=3, + ) + + # Format point labels + formatted_spend = f"{row['mean_spend_adstocked']:.1f}K" + + ax.text( + row["mean_spend_adstocked"], + row["mean_response"], + formatted_spend, + ha="left", + va="bottom", + fontsize=9, + color=color, + ) + + logger.debug("Formatting axis labels") + + # Custom locator for x and y axes + def custom_tick_formatter(x, p): + if x == 0: + return "0" + return f"{int(x)}K" + + # Set axis limits matching the R plot + ax.set_xlim(0, 120) + ax.set_ylim(0, 150) + + # Set major ticks + ax.set_xticks([0, 30, 60, 90, 120]) + ax.set_yticks([0, 25, 50, 75, 100, 125, 150]) + + ax.xaxis.set_major_formatter(plt.FuncFormatter(custom_tick_formatter)) + ax.yaxis.set_major_formatter(plt.FuncFormatter(custom_tick_formatter)) + + # Grid styling to match R plot + ax.grid(True, alpha=0.2, linestyle='-', color='gray') + ax.set_axisbelow(True) + ax.spines["top"].set_visible(False) + ax.spines["right"].set_visible(False) + + ax.set_title("Response Curves and Mean Spends by Channel") + ax.set_xlabel("Spend (carryover + immediate)") + ax.set_ylabel("Response") + + # Adjust legend to match R plot + ax.legend( + bbox_to_anchor=(1.02, 0.5), + loc="center left", + frameon=True, + framealpha=0.8, + facecolor="white", + edgecolor="none", + ) + + if fig: + logger.debug("Adjusting layout") + plt.tight_layout() + logger.debug("Successfully generated response curves figure") + return fig + + logger.debug("Successfully added response curves to existing axes") + return None + + except Exception as e: + logger.error("Error generating response curves: %s", str(e), exc_info=True) + raise + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> None: + pass diff --git a/python/src/robyn/visualization/transformation_visualizer.py b/python/src/robyn/visualization/transformation_visualizer.py new file mode 100644 index 000000000..01c36b858 --- /dev/null +++ b/python/src/robyn/visualization/transformation_visualizer.py @@ -0,0 +1,390 @@ +# pyre-strict +import logging +from pathlib import Path +from typing import List, Optional, Tuple, Union + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from robyn.data.entities.enums import DependentVarType +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.visualization.base_visualizer import BaseVisualizer + +logger = logging.getLogger(__name__) + + +class TransformationVisualizer(BaseVisualizer): + def __init__(self, pareto_result: ParetoResult, mmm_data: MMMData): + logger.debug( + "Initializing TransformationVisualizer with pareto_result=%s, mmm_data=%s", + pareto_result, + mmm_data, + ) + super().__init__() + self.pareto_result = pareto_result + self.mmm_data = mmm_data + + def create_adstock_plots(self) -> None: + """ + Generate adstock visualization plots and store them as instance variables. + """ + logger.info("Starting creation of adstock plots") + try: + # Implementation placeholder + logger.debug("Adstock plots creation completed successfully") + except Exception as e: + logger.error("Failed to create adstock plots: %s", str(e)) + raise + + def create_saturation_plots(self) -> None: + """ + Generate saturation visualization plots and store them as instance variables. + """ + logger.info("Starting creation of saturation plots") + try: + # Implementation placeholder + logger.debug("Saturation plots creation completed successfully") + except Exception as e: + logger.error("Failed to create saturation plots: %s", str(e)) + raise + + def get_adstock_plots(self) -> Optional[Tuple[plt.Figure, plt.Figure]]: + """ + Retrieve the adstock plots. + + Returns: + Optional[Tuple[plt.Figure, plt.Figure]]: Tuple of matplotlib figures for adstock plots + """ + logger.debug("Retrieving adstock plots") + try: + # Implementation placeholder + logger.debug("Successfully retrieved adstock plots") + return None + except Exception as e: + logger.error("Failed to retrieve adstock plots: %s", str(e)) + raise + + def get_saturation_plots(self) -> Optional[Tuple[plt.Figure, plt.Figure]]: + """ + Retrieve the saturation plots. + + Returns: + Optional[Tuple[plt.Figure, plt.Figure]]: Tuple of matplotlib figures for saturation plots + """ + logger.debug("Retrieving saturation plots") + try: + # Implementation placeholder + logger.debug("Successfully retrieved saturation plots") + return None + except Exception as e: + logger.error("Failed to retrieve saturation plots: %s", str(e)) + raise + + def display_adstock_plots(self) -> None: + """ + Display the adstock plots. + """ + logger.info("Displaying adstock plots") + try: + # Implementation placeholder + logger.debug("Successfully displayed adstock plots") + except Exception as e: + logger.error("Failed to display adstock plots: %s", str(e)) + raise + + def display_saturation_plots(self) -> None: + """ + Display the saturation plots. + """ + logger.info("Displaying saturation plots") + try: + # Implementation placeholder + logger.debug("Successfully displayed saturation plots") + except Exception as e: + logger.error("Failed to display saturation plots: %s", str(e)) + raise + + def save_adstock_plots(self, filenames: List[str]) -> None: + """ + Save the adstock plots to files. + + Args: + filenames (List[str]): List of filenames to save the plots + """ + logger.info("Saving adstock plots to files: %s", filenames) + try: + # Implementation placeholder + logger.debug("Successfully saved adstock plots") + except Exception as e: + logger.error("Failed to save adstock plots: %s", str(e)) + raise + + def save_saturation_plots(self, filenames: List[str]) -> None: + """ + Save the saturation plots to files. + + Args: + filenames (List[str]): List of filenames to save the plots + """ + logger.info("Saving saturation plots to files: %s", filenames) + try: + # Implementation placeholder + logger.debug("Successfully saved saturation plots") + except Exception as e: + logger.error("Failed to save saturation plots: %s", str(e)) + raise + + def generate_spend_effect_comparison( + self, solution_id: str, ax: Optional[plt.Axes] = None + ) -> Optional[plt.Figure]: + """Generate comparison plot of spend share vs effect share.""" + + logger.debug("Starting generation of spend effect comparison plot") + try: + # Get plot data safely + logger.debug("Extracting plot data from pareto result") + plot_data = self.pareto_result.plot_data_collect[solution_id] + + # Safely get bar and line data + try: + bar_data = plot_data["plot1data"]["plotMediaShareLoopBar"].copy() + line_data = plot_data["plot1data"]["plotMediaShareLoopLine"].copy() + y_sec_scale = plot_data["plot1data"]["ySecScale"] + + logger.debug( + "Processing plot data - bar_data shape: %s, line_data shape: %s", + bar_data.shape, + line_data.shape, + ) + + # Convert y_sec_scale to float safely + if isinstance(y_sec_scale, pd.DataFrame): + y_sec_scale = float( + y_sec_scale.iat[0, 0] + if len(y_sec_scale.columns) > 0 + else y_sec_scale.iloc[0] + ) + elif isinstance(y_sec_scale, pd.Series): + y_sec_scale = float(y_sec_scale.iloc[0]) + else: + y_sec_scale = float(y_sec_scale) + + logger.debug("Y-scale factor: %f", y_sec_scale) + except (KeyError, AttributeError, IndexError) as e: + logger.error( + "Error accessing plot data for solution %s: %s", solution_id, str(e) + ) + return None + + # Transform variable names safely + bar_data["variable"] = ( + bar_data["variable"].str.replace("_", " ").str.title() + ) + + # Create figure if no axes provided + if ax is None: + logger.debug("Creating new figure and axes") + fig, ax = plt.subplots(figsize=(16, 10)) + plt.subplots_adjust(top=0.80, left=0.15, bottom=0.1, right=0.95) + else: + logger.debug("Using provided axes for plotting") + fig = None + + # Set background color + ax.set_facecolor("white") + + # Set up colors + type_colour = "#03396C" # Dark blue for line + bar_colors = ["#A4C2F4", "#FFB7B2"] # Light blue and light coral for bars + bar_colors = bar_colors[::-1] # Reverse colors + + # Set up dimensions + channels = sorted( + line_data["rn"].unique() + ) # Use line_data for consistent ordering + y_pos = np.arange(len(channels)) + + logger.debug("Processing %d channels for visualization", len(channels)) + + # Plot bars for each variable type + bar_width = 0.35 + for i, (var, color) in enumerate( + zip(reversed(bar_data["variable"].unique()), bar_colors) + ): + var_data = bar_data[bar_data["variable"] == var] + # Ensure alignment with channels - safely get values + values = [] + for ch in channels: + ch_data = var_data[var_data["rn"] == ch] + if not ch_data.empty: + values.append(ch_data["value"].iloc[0]) + else: + values.append(0) + + logger.debug( + "Plotting bars for variable '%s' with %d values", var, len(values) + ) + bars = ax.barh( + y=[y + (i - 0.5) * bar_width for y in y_pos], + width=values, + height=bar_width, + label=var, + color=color, + alpha=0.5, + ) + + # Add percentage labels to right of y-axis + for idx, value in enumerate(values): + y_position = y_pos[idx] + (i - 0.5) * bar_width + percentage = f"{value * 100:.1f}%" + + ax.text( + s=percentage, + x=0.02, + y=y_position, + ha="left", + va="center", + fontweight="bold", + fontsize=9, + transform=ax.get_yaxis_transform(), + ) + + # Safely get line values + line_values = [] + for ch in channels: + ch_data = line_data[line_data["rn"] == ch] + if not ch_data.empty: + line_values.append(ch_data["value"].iloc[0]) + else: + line_values.append(0) + + line_values = np.array(line_values) + line_x = line_values / y_sec_scale + + logger.debug("Plotting line with %d points", len(line_x)) + # Plot line without label + ax.plot( + line_x, y_pos, color=type_colour, marker="o", markersize=8, zorder=3 + ) + + # Add line value labels + for i, value in enumerate(line_values): + ax.text( + line_x[i] + 0.02, # Added offset to move labels right of dots + y_pos[i], + f"{value:.2f}", + color=type_colour, + fontweight="bold", + ha="left", # Left align since we're positioning to the right of dots + va="center", + zorder=4, + ) + + # Set channel labels + ax.set_yticks(y_pos) + ax.set_yticklabels(channels) + ax.tick_params(axis="y", pad=5) + + # Format x-axis as percentage and show labels up to 70% + ax.xaxis.set_major_formatter( + plt.FuncFormatter(lambda x, p: f"{x*100:.0f}%") + ) + ax.set_xlim(0, 0.7) # Set x-axis limit to 70% + xticks = np.arange( + 0, 0.8, 0.1 + ) # Create ticks from 0 to 70% in 10% increments + ax.set_xticks(xticks) + ax.tick_params(axis="x", labelbottom=True) + + # Add grid + ax.grid(True, axis="x", alpha=0.2, linestyle="-") + ax.set_axisbelow(True) + + # Remove unnecessary spines + ax.spines["top"].set_visible(False) + ax.spines["right"].set_visible(False) + + # Set title at top position + metric_type = ( + "ROAS" + if ( + self.mmm_data + and hasattr(self.mmm_data.mmmdata_spec, "dep_var_type") + and self.mmm_data.mmmdata_spec.dep_var_type + == DependentVarType.REVENUE + ) + else "CPA" + ) + + logger.debug("Setting plot title with metric type: %s", metric_type) + + # Set title at top + ax.set_title( + f"Share of Total Spend, Effect & {metric_type} in Modeling Window*", + pad=20, + y=1.45, + ) + + # Create legend with single ROAS entry + bars_legend = ax.get_legend_handles_labels() + line_legend = [ + plt.Line2D( + [0], + [0], + color=type_colour, + marker="o", + linestyle="-", + markersize=8, + label="ROAS", + ) + ] + + # Combine legend elements in reverse order + handles = line_legend + list(reversed(bars_legend[0])) + labels = ["ROAS"] + list(reversed(bars_legend[1])) + + # Create legend below title + ax.legend( + handles=handles, + labels=labels, + bbox_to_anchor=(0, 1.05, 0.4, 0.1), + loc="lower left", + mode="expand", + ncol=3, + frameon=False, + borderaxespad=0, + ) + + # Add axis labels + ax.set_xlabel("Total Share by Channel") + ax.set_ylabel(None) + + logger.debug("Successfully generated spend effect comparison plot") + if fig: + plt.tight_layout() + plt.subplots_adjust(top=0.80, left=0.15, bottom=0.1, right=0.95) + return fig + return None + + except (KeyError, AttributeError, IndexError, ValueError) as error: + logger.error( + "Error generating spend effect plot for solution %s: %s", + solution_id, + str(error), + ) + if ax: + ax.text( + 0.5, + 0.5, + "Error generating spend effect plot", + ha="center", + va="center", + ) + return None + + def plot_all( + self, display_plots: bool = True, export_location: Union[str, Path] = None + ) -> None: + pass diff --git a/python/tests/__init__.py b/python/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/python/tests/component_tutorials/e2e_test/tutorial3_modeling_compare.ipynb b/python/tests/component_tutorials/e2e_test/tutorial3_modeling_compare.ipynb new file mode 100644 index 000000000..2ff51433a --- /dev/null +++ b/python/tests/component_tutorials/e2e_test/tutorial3_modeling_compare.ipynb @@ -0,0 +1,844 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Robyn: Marketing Mix Modeling Application\n", + "\n", + "This notebook demonstrates the usage of Robyn, a Marketing Mix Modeling (MMM) application. \n", + "We'll go through the main steps of performing robyn_inputs and robyn_engineering.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1. Import Required Libraries. Define Paths.\n", + "\n", + "First, be sure to setup your virtual environment. Be sure to switch over to your new environment in this notebook. \n", + "\n", + "-```cd {root_folder}```\n", + "\n", + "-```python3 -m yourvenv```\n", + "\n", + "-```source yourvenv/bin/activate```\n", + "\n", + "-```cd Robyn/python```\n", + "\n", + "-```pip install -r requirements.txt```\n", + "\n", + "\n", + "Then import the necessary libraries. Make sure to define your paths below.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pandas as pd\n", + "from typing import Dict\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "from robyn.modeling.model_executor import ModelExecutor\n", + "from robyn.modeling.entities.enums import NevergradAlgorithm, Models\n", + "from robyn.modeling.feature_engineering import FeatureEngineering" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.1 Load Mock R data\n", + "\n", + "We need to set the base path for the data directory.\n", + "Create a .env file in the same directory as your notebook and put in define the path to the data dir.\n", + "for example: ROBYN_BASE_PATH=.../Robyn/R/data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the simulated data and holidays data\n", + "dt_simulated_weekly = pd.read_csv(\n", + " \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/robyn/tutorials/resources/dt_simulated_weekly.csv\"\n", + ")\n", + "\n", + "dt_prophet_holidays = pd.read_csv(\n", + " \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/robyn/tutorials/resources/dt_prophet_holidays.csv\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup MMM Data\n", + "\n", + "We will now set up the MMM data specification which includes defining the dependent variable, independent variables, and the time window for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def setup_mmm_data(dt_simulated_weekly) -> MMMData:\n", + "\n", + " mmm_data_spec = MMMData.MMMDataSpec(\n", + " dep_var=\"revenue\",\n", + " dep_var_type=\"revenue\",\n", + " date_var=\"DATE\",\n", + " context_vars=[\"competitor_sales_B\", \"events\"],\n", + " paid_media_spends=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_S\", \"search_S\"],\n", + " paid_media_vars=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_I\", \"search_clicks_P\"],\n", + " organic_vars=[\"newsletter\"],\n", + " window_start=\"2016-01-01\",\n", + " window_end=\"2018-12-31\",\n", + " )\n", + "\n", + " return MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec)\n", + "\n", + "\n", + "mmm_data = setup_mmm_data(dt_simulated_weekly)\n", + "mmm_data.data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Preprocessing\n", + "\n", + "We will perform feature engineering to prepare the data for modeling. This includes transformations like adstock and other preprocessing steps." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "hyperparameters = Hyperparameters(\n", + " hyperparameters={\n", + " \"facebook_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"print_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"tv_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.3, 0.8],\n", + " ),\n", + " \"search_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"ooh_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"newsletter\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " },\n", + " adstock=AdstockType.GEOMETRIC,\n", + " lambda_=[0, 1],\n", + " train_size=[0.5, 0.8],\n", + ")\n", + "\n", + "print(\"Hyperparameters setup complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create HolidaysData object\n", + "holidays_data = HolidaysData(\n", + " dt_holidays=dt_prophet_holidays,\n", + " prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + " prophet_country=\"DE\",\n", + " prophet_signs=[\"default\", \"default\", \"default\"],\n", + ")\n", + "# Setup FeaturizedMMMData\n", + "feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "featurized_mmm_data = feature_engineering.perform_feature_engineering()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.visualization.feature_visualization import FeaturePlotter\n", + "import matplotlib.pyplot as plt\n", + "\n", + "%matplotlib inline\n", + "\n", + "# Create a FeaturePlotter instance\n", + "feature_plotter = FeaturePlotter(\n", + " mmm_data, hyperparameters, featurized_mmmdata=featurized_mmm_data\n", + ")\n", + "# Extract the list of results\n", + "results_list = featurized_mmm_data.modNLS[\"results\"]\n", + "# Plot spend-exposure relationship for each channel in the results\n", + "for result in results_list:\n", + " channel = result.get(\"channel\")\n", + " print(f\"Processing channel: {channel}\") # Debugging line\n", + " if not channel:\n", + " print(f\"Skipping invalid channel: {result}\")\n", + " continue\n", + "\n", + " try:\n", + " fig = feature_plotter.plot_spend_exposure(channel)\n", + " plt.show()\n", + " except ValueError as e:\n", + " print(f\"Error plotting {channel}: {str(e)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(featurized_mmm_data.modNLS[\"plots\"].keys())\n", + "\n", + "for result in featurized_mmm_data.modNLS[\"results\"]:\n", + " print(result.get(\"channel\"))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_data = featurized_mmm_data.modNLS[\"plots\"].get(\"facebook_I\")\n", + "print(plot_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "\n", + "# For MMM Data\n", + "def debug_mmm_data(mmm_data):\n", + " print(\"=== MMM Data Debug ===\")\n", + " print(\"\\nMMM Data Specification:\")\n", + " print(f\"Dependent Variable: {mmm_data.mmmdata_spec.dep_var}\")\n", + " print(f\"Paid Media Spends: {mmm_data.mmmdata_spec.paid_media_spends}\")\n", + " print(f\"Paid Media Vars: {mmm_data.mmmdata_spec.paid_media_vars}\")\n", + " print(f\"Organic Vars: {mmm_data.mmmdata_spec.organic_vars}\")\n", + "\n", + "\n", + "# For Hyperparameters\n", + "def debug_hyperparameters(hyperparameters):\n", + " print(\"=== Hyperparameters Debug ===\")\n", + " print(\"\\nHyperparameters structure:\")\n", + " for channel, params in hyperparameters.hyperparameters.items():\n", + " print(f\"\\nChannel: {channel}\")\n", + " print(\"Thetas:\", getattr(params, \"thetas\", None))\n", + " print(\"Alphas:\", getattr(params, \"alphas\", None))\n", + " print(\"Gammas:\", getattr(params, \"gammas\", None))\n", + " print(\"Shapes:\", getattr(params, \"shapes\", None))\n", + " print(\"Scales:\", getattr(params, \"scales\", None))\n", + "\n", + " print(\"\\nLambda:\", hyperparameters.lambda_)\n", + " print(\"Train size:\", hyperparameters.train_size)\n", + "\n", + "\n", + "# For Featurized MMM Data\n", + "def debug_featurized_data(featurized_mmm_data):\n", + " print(\"=== Featurized MMM Data Debug ===\")\n", + " print(\"\\nFeaturized data shape:\", featurized_mmm_data.dt_mod.shape)\n", + " print(\"\\nFeaturized data columns:\", featurized_mmm_data.dt_mod.columns.tolist())\n", + "\n", + " # Basic statistics of the featurized data\n", + " print(\"\\nFeaturized data statistics:\")\n", + " print(featurized_mmm_data.dt_mod.describe())\n", + "\n", + " # Check for any transformations that occurred\n", + " print(\"\\nData types:\")\n", + " print(featurized_mmm_data.dt_mod.dtypes)\n", + "\n", + " # Check for any missing or infinite values\n", + " print(\"\\nMissing values count:\")\n", + " print(featurized_mmm_data.dt_mod.isnull().sum())\n", + " print(\"\\nInfinite values count:\")\n", + " print(np.isinf(featurized_mmm_data.dt_mod.select_dtypes(include=np.number)).sum())\n", + "\n", + "\n", + "# Combined debug function\n", + "def debug_all_inputs(mmm_data, hyperparameters, featurized_mmm_data):\n", + " debug_mmm_data(mmm_data)\n", + " print(\"\\n\" + \"=\" * 50 + \"\\n\")\n", + " debug_hyperparameters(hyperparameters)\n", + " print(\"\\n\" + \"=\" * 50 + \"\\n\")\n", + " debug_featurized_data(featurized_mmm_data)\n", + "\n", + "\n", + "# Usage:\n", + "debug_all_inputs(mmm_data, hyperparameters, featurized_mmm_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Setup ModelExecutor\n", + "model_executor = ModelExecutor(\n", + " mmmdata=mmm_data,\n", + " holidays_data=holidays_data,\n", + " hyperparameters=hyperparameters,\n", + " calibration_input=None, # Add calibration input if available\n", + " featurized_mmm_data=featurized_mmm_data,\n", + ")\n", + "\n", + "# Setup TrialsConfig\n", + "trials_config = TrialsConfig(\n", + " iterations=2000, trials=5\n", + ") # Set to the number of cores you want to use\n", + "\n", + "print(\n", + " f\">>> Starting {trials_config.trials} trials with {trials_config.iterations} iterations each using {NevergradAlgorithm.TWO_POINTS_DE.value} nevergrad algorithm on x cores...\"\n", + ")\n", + "\n", + "# Run the model\n", + "\n", + "output_models = model_executor.model_run(\n", + " trials_config=trials_config,\n", + " ts_validation=True, # changed from True to False -> deacitvate\n", + " add_penalty_factor=False,\n", + " rssd_zero_penalty=True,\n", + " cores=16,\n", + " nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE,\n", + " intercept=True,\n", + " intercept_sign=\"non_negative\",\n", + " model_name=Models.RIDGE,\n", + ")\n", + "print(\"Model training complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.tutorials.utils.data_mapper import load_data_from_json, import_input_collect, import_output_models\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "# Load data from JSON exported from R\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_Pareto_50_iterations_1_trial_InputCollect.json\"\n", + ")\n", + "raw_output_models = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_Pareto_50_iterations_1_trial_OutputModels.json\"\n", + ")\n", + "\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "r_output_models = import_output_models(raw_output_models)\n", + "\n", + "# Extract individual components\n", + "r_mmm_data = r_input_collect[\"mmm_data\"]\n", + "r_featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "r_holidays_data = r_input_collect[\"holidays_data\"]\n", + "r_hyperparameters = r_input_collect[\"hyperparameters\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# new anytree\n", + "\n", + "from anytree import Node, RenderTree\n", + "from dataclasses import is_dataclass, asdict\n", + "import pandas as pd\n", + "\n", + "\n", + "def build_tree(data, parent_key=\"\", limit_trials=True):\n", + " \"\"\"\n", + " Recursively build a tree structure from a dictionary, list, or dataclass.\n", + "\n", + " Args:\n", + " data: The data structure (dict, list, or dataclass) to traverse.\n", + " parent_key: The base key path for nested keys.\n", + " limit_trials: Whether to limit the output to the first trial.\n", + "\n", + " Returns:\n", + " A tree node representing the structure of the data.\n", + " \"\"\"\n", + " if is_dataclass(data):\n", + " data = asdict(data) # Convert dataclass to dictionary\n", + "\n", + " if isinstance(data, dict):\n", + " node = Node(f\"{parent_key} (Dict)\")\n", + " for key, value in data.items():\n", + " full_key = f\"{parent_key}.{key}\" if parent_key else key\n", + " child_node = build_tree(value, full_key, limit_trials)\n", + " child_node.parent = node\n", + " return node\n", + " elif isinstance(data, list):\n", + " node = Node(f\"{parent_key} (List)\")\n", + " for index, item in enumerate(data):\n", + " if limit_trials and parent_key == \"trials\" and index > 0:\n", + " break\n", + " full_key = f\"{parent_key}[{index}]\"\n", + " child_node = build_tree(item, full_key, limit_trials)\n", + " child_node.parent = node\n", + " return node\n", + " elif isinstance(data, pd.DataFrame):\n", + " node = Node(f\"{parent_key} (DataFrame)\")\n", + " for column in data.columns:\n", + " dtype = data[column].dtype\n", + " column_node = Node(f\"{parent_key}.{column} (dtype: {dtype})\")\n", + " column_node.parent = node\n", + " return node\n", + " else:\n", + " dtype = type(data).__name__\n", + " return Node(f\"{parent_key} (dtype: {dtype})\")\n", + "\n", + "\n", + "# Assuming output_models and r_output_models are instances of ModelOutputs\n", + "python_tree = build_tree(output_models)\n", + "r_tree = build_tree(r_output_models)\n", + "\n", + "# Visualize the trees\n", + "print(\"Python ModelOutputs Structure:\")\n", + "for pre, fill, node in RenderTree(python_tree):\n", + " print(f\"{pre}{node.name}\")\n", + "\n", + "print(\"\\nR ModelOutputs Structure:\")\n", + "for pre, fill, node in RenderTree(r_tree):\n", + " print(f\"{pre}{node.name}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# from anytree import Node, RenderTree\n", + "# from anytree.exporter import DotExporter\n", + "# from dataclasses import is_dataclass, asdict\n", + "# import pandas as pd\n", + "\n", + "\n", + "# def build_tree(data, parent_key=\"\", limit_trials=True):\n", + "# \"\"\"\n", + "# Recursively build a tree structure from a dictionary, list, or dataclass.\n", + "\n", + "# Args:\n", + "# data: The data structure (dict, list, or dataclass) to traverse.\n", + "# parent_key: The base key path for nested keys.\n", + "# limit_trials: Whether to limit the output to the first trial.\n", + "\n", + "# Returns:\n", + "# A tree node representing the structure of the data.\n", + "# \"\"\"\n", + "# if is_dataclass(data):\n", + "# data = asdict(data) # Convert dataclass to dictionary\n", + "\n", + "# if isinstance(data, dict):\n", + "# node = Node(parent_key)\n", + "# for key, value in data.items():\n", + "# full_key = f\"{parent_key}.{key}\" if parent_key else key\n", + "# child_node = build_tree(value, full_key, limit_trials)\n", + "# child_node.parent = node\n", + "# return node\n", + "# elif isinstance(data, list):\n", + "# node = Node(parent_key)\n", + "# for index, item in enumerate(data):\n", + "# if limit_trials and parent_key == \"trials\" and index > 0:\n", + "# break\n", + "# full_key = f\"{parent_key}[{index}]\"\n", + "# child_node = build_tree(item, full_key, limit_trials)\n", + "# child_node.parent = node\n", + "# return node\n", + "# elif isinstance(data, pd.DataFrame):\n", + "# node = Node(f\"{parent_key} (DataFrame: {data.shape})\")\n", + "# for column in data.columns:\n", + "# column_node = Node(f\"{parent_key}.{column}\")\n", + "# column_node.parent = node\n", + "# return node\n", + "# else:\n", + "# return Node(parent_key)\n", + "\n", + "\n", + "# # Assuming output_models and r_output_models are instances of ModelOutputs\n", + "# python_tree = build_tree(output_models)\n", + "# r_tree = build_tree(r_output_models)\n", + "\n", + "# # Visualize the trees\n", + "# print(\"Python ModelOutputs Structure:\")\n", + "# for pre, fill, node in RenderTree(python_tree):\n", + "# print(f\"{pre}{node.name}\")\n", + "\n", + "# print(\"\\nR ModelOutputs Structure:\")\n", + "# for pre, fill, node in RenderTree(r_tree):\n", + "# print(f\"{pre}{node.name}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from typing import Dict, Any\n", + "\n", + "\n", + "def compare_model_values(py_output, r_output):\n", + " \"\"\"Compare key values between Python and R model outputs\"\"\"\n", + "\n", + " print(\"1. Basic Model Configuration Comparison:\")\n", + " basic_attrs = [\n", + " \"train_timestamp\",\n", + " \"cores\",\n", + " \"iterations\",\n", + " \"intercept\",\n", + " \"intercept_sign\",\n", + " \"nevergrad_algo\",\n", + " \"ts_validation\",\n", + " \"add_penalty_factor\",\n", + " ]\n", + "\n", + " # Add debug prints\n", + " print(\"\\nDebugging attribute types:\")\n", + " for attr in basic_attrs:\n", + " py_val = getattr(py_output, attr, None)\n", + " r_val = getattr(r_output, attr, None)\n", + " print(f\"{attr:20s} - Python type: {type(py_val)} | R type: {type(r_val)}\")\n", + " print(f\"{attr:20s} - Python value: {py_val} | R value: {r_val}\")\n", + " print(\"-\" * 50)\n", + "\n", + " print(\"\\n2. Trial Results Comparison (Descriptive Statistics):\")\n", + " if py_output.trials and r_output.trials:\n", + " metrics = [\n", + " \"nrmse\",\n", + " \"decomp_rssd\",\n", + " \"mape\",\n", + " \"rsq_train\",\n", + " \"rsq_val\",\n", + " \"rsq_test\",\n", + " \"lambda_\",\n", + " \"lambda_hp\",\n", + " \"lambda_max\",\n", + " \"lambda_min_ratio\",\n", + " ]\n", + " # Convert trial results to DataFrames\n", + " py_trials_df = pd.DataFrame(\n", + " [\n", + " {metric: getattr(trial, metric, np.nan) for metric in metrics}\n", + " for trial in py_output.trials\n", + " ]\n", + " )\n", + "\n", + " # Aggregate R trial metrics\n", + " r_trials_df = pd.DataFrame(\n", + " [\n", + " {\n", + " metric: getattr(trial, metric, pd.Series([np.nan])).mean()\n", + " for metric in metrics\n", + " }\n", + " for trial in r_output.trials\n", + " ]\n", + " )\n", + " # Ensure R trial data is numeric\n", + " r_trials_df = r_trials_df.apply(pd.to_numeric, errors=\"coerce\")\n", + " # Calculate descriptive statistics\n", + " py_desc = py_trials_df.describe()\n", + " r_desc = r_trials_df.describe()\n", + " # Print descriptive statistics\n", + " print(\"\\nPython Trial Descriptive Statistics:\")\n", + " print(py_desc)\n", + " print(\"\\nR Trial Descriptive Statistics:\")\n", + " print(r_desc)\n", + " # Calculate and print differences\n", + " diff_desc = py_desc - r_desc\n", + " print(\"\\nDifference in Descriptive Statistics:\")\n", + " print(diff_desc)\n", + "\n", + " print(\"\\n3. Hyperparameter Comparison:\")\n", + " if hasattr(py_output, \"hyper_updated\") and hasattr(r_output, \"hyper_updated\"):\n", + " py_hyper = py_output.hyper_updated\n", + " r_hyper = r_output.hyper_updated\n", + "\n", + " # Find all unique keys\n", + " all_keys = set(py_hyper.keys()) | set(r_hyper.keys())\n", + "\n", + " print(\"\\nHyperparameter Values:\")\n", + " print(f\"{'Parameter':30s} {'Python':>15s} {'R':>15s} {'Diff':>15s}\")\n", + " print(\"-\" * 75)\n", + "\n", + " for key in sorted(all_keys):\n", + " py_val = py_hyper.get(key, \"N/A\")\n", + " r_val = r_hyper.get(key, \"N/A\")\n", + "\n", + " if isinstance(py_val, (int, float)) and isinstance(r_val, (int, float)):\n", + " diff = abs(py_val - r_val)\n", + " print(f\"{key:30s} {py_val:15.6f} {r_val:15.6f} {diff:15.6f}\")\n", + " else:\n", + " print(f\"{key:30s} {str(py_val):15s} {str(r_val):15s} {'N/A':>15s}\")\n", + "\n", + " print(\"\\n4. Data Shape Comparison:\")\n", + " data_attrs = [\"all_result_hyp_param\", \"all_x_decomp_agg\", \"all_decomp_spend_dist\"]\n", + "\n", + " for attr in data_attrs:\n", + " py_shape = getattr(py_output, attr).shape if hasattr(py_output, attr) else None\n", + " r_shape = getattr(r_output, attr).shape if hasattr(r_output, attr) else None\n", + " print(f\"{attr:20s} - Python shape: {py_shape} | R shape: {r_shape}\")\n", + "\n", + " print(\"\\n5. Total Effect and Effect Share Comparison:\")\n", + " if py_output.trials and r_output.trials:\n", + " for i, (py_trial, r_trial) in enumerate(zip(py_output.trials, r_output.trials)):\n", + " print(f\"\\nTrial {i+1}:\")\n", + " # Extract decomp_spend_dist DataFrames\n", + " py_decomp_spend_dist = getattr(\n", + " py_trial, \"decomp_spend_dist\", pd.DataFrame()\n", + " )\n", + " r_decomp_spend_dist = getattr(r_trial, \"decomp_spend_dist\", pd.DataFrame())\n", + " # Check if the DataFrames are not empty\n", + " if not py_decomp_spend_dist.empty and not r_decomp_spend_dist.empty:\n", + " # Compare total effect\n", + " py_total_effect = py_decomp_spend_dist.get(\n", + " \"xDecompAgg\", pd.Series([np.nan])\n", + " ).sum()\n", + " r_total_effect = r_decomp_spend_dist.get(\n", + " \"xDecompAgg\", pd.Series([np.nan])\n", + " ).sum()\n", + " total_effect_diff = abs(py_total_effect - r_total_effect)\n", + " print(\n", + " f\"Total Effect - Python: {py_total_effect:.6f}, R: {r_total_effect:.6f}, Diff: {total_effect_diff:.6f}\"\n", + " )\n", + " # Compare effect share\n", + " py_effect_share = py_decomp_spend_dist.get(\n", + " \"effect_share\", pd.Series([np.nan])\n", + " ).sum()\n", + " r_effect_share = r_decomp_spend_dist.get(\n", + " \"effect_share\", pd.Series([np.nan])\n", + " ).sum()\n", + " effect_share_diff = abs(py_effect_share - r_effect_share)\n", + " print(\n", + " f\"Effect Share - Python: {py_effect_share:.6f}, R: {r_effect_share:.6f}, Diff: {effect_share_diff:.6f}\"\n", + " )\n", + " else:\n", + " print(\n", + " \"Decomposition spend distribution data is missing for this trial.\"\n", + " )\n", + "\n", + "\n", + "# Run the comparison\n", + "print(\"Starting detailed value comparison...\\n\")\n", + "compare_model_values(output_models, r_output_models)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming r_output_models is an instance of ModelOutputs\n", + "convergence_data = r_output_models.convergence\n", + "\n", + "# Accessing attributes of ConvergenceData\n", + "moo_distrb_plot = convergence_data.moo_distrb_plot\n", + "moo_cloud_plot = convergence_data.moo_cloud_plot\n", + "errors = convergence_data.errors\n", + "conv_msg = convergence_data.conv_msg\n", + "\n", + "# Example: Print the convergence messages\n", + "print(\"Convergence Messages:\", conv_msg)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from PIL import Image\n", + "import io\n", + "import binascii\n", + "from typing import Optional\n", + "\n", + "# Assuming convergence_data is an instance of ConvergenceData\n", + "# and contains hexadecimal strings of image data\n", + "\n", + "\n", + "def display_image(data: Optional[str]):\n", + " if data:\n", + " # If data is a list, join it into a single string\n", + " if isinstance(data, list):\n", + " data = \"\".join(data)\n", + "\n", + " # Convert hexadecimal string to binary data\n", + " binary_data = binascii.unhexlify(data)\n", + "\n", + " # Open the image using PIL\n", + " image = Image.open(io.BytesIO(binary_data))\n", + "\n", + " # Display the image\n", + " image.show()\n", + " else:\n", + " print(\"No image data available.\")\n", + "\n", + "\n", + "# print(\"moo distrb plot:\", type(moo_distrb_plot))\n", + "# print(\"first 10 elements in moo distrb plot:\", moo_distrb_plot[0:10])\n", + "# print(\"moo cloud plot:\", type(moo_cloud_plot))\n", + "# Assuming convergence_data is an instance of ConvergenceData\n", + "# Display the moo_distrb_plot\n", + "# display_image(convergence_data.moo_distrb_plot)\n", + "# # Display the moo_cloud_plot\n", + "# display_image(convergence_data.moo_cloud_plot)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# # Function to print model output summary\n", + "# def print_model_output_summary(model_name, model):\n", + "# print(f\"\\n{model_name} Model Output Summary:\")\n", + "# print(f\"Number of trials: {len(model.trials)}\")\n", + "# print(\n", + "# f\"Average models per trial: {len(model.all_result_hyp_param) / len(model.trials)}\"\n", + "# )\n", + "# print(f\"Total unique models: {len(model.all_result_hyp_param['sol_id'].unique())}\")\n", + "\n", + "# print(\"\\nMetrics Distribution:\")\n", + "# metrics_df = model.all_result_hyp_param[[\"nrmse\", \"decomp.rssd\", \"mape\"]]\n", + "# print(metrics_df.describe())\n", + "\n", + "# # Additional validation to debug model output\n", + "# print(\"\\nColumns in result_hyp_param:\")\n", + "# print(model.all_result_hyp_param.columns.tolist())\n", + "\n", + "# print(\"\\nSample rows of metrics:\")\n", + "# print(model.all_result_hyp_param[[\"sol_id\", \"nrmse\", \"decomp.rssd\", \"mape\"]].head())\n", + "\n", + "# # Show shape of result dataframes\n", + "# print(\"\\nDataFrame Shapes:\")\n", + "# print(f\"result_hyp_param: {model.all_result_hyp_param.shape}\")\n", + "# print(f\"x_decomp_agg: {model.all_x_decomp_agg.shape}\")\n", + "# print(f\"decomp_spend_dist: {model.all_decomp_spend_dist.shape}\")\n", + "\n", + "\n", + "# # Print summaries for both output_models and r_output_models\n", + "# print_model_output_summary(\"Python Output Models\", output_models)\n", + "# print_model_output_summary(\"R Output Models\", r_output_models)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# def print_data_structure(data):\n", + "# print(\"Columns:\", data.columns.tolist())\n", + "# print(\"\\nFirst row:\", data.iloc[0].to_dict())\n", + "# print(\"\\nShape:\", data.shape)\n", + "\n", + "\n", + "# # Assuming you want to print the structure for the first trial\n", + "# first_trial_r = r_output_models.trials[0].decomp_spend_dist\n", + "# first_trial_python = output_models.trials[0].decomp_spend_dist\n", + "\n", + "# print(\"R exported data structure:\")\n", + "# print_data_structure(first_trial_r)\n", + "\n", + "# # With Python calculated data\n", + "# print(\"\\nPython calculated data structure:\")\n", + "# print_data_structure(first_trial_python)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mytestenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.15" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/e2e_test/tutorial4_pareto_e2e_test.ipynb b/python/tests/component_tutorials/e2e_test/tutorial4_pareto_e2e_test.ipynb new file mode 100644 index 000000000..c0a45bab8 --- /dev/null +++ b/python/tests/component_tutorials/e2e_test/tutorial4_pareto_e2e_test.ipynb @@ -0,0 +1,355 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test Pareto Optimizer\n", + "\n", + "from robyn.modeling.pareto.pareto_optimizer import ParetoOptimizer\n", + "from robyn.tutorials.utils.data_mapper import (\n", + " import_output_models,\n", + " import_input_collect,\n", + " load_data_from_json,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load data from JSON\n", + "inputCollect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_InputCollect.json\"\n", + ")\n", + "outputModel = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_OutputModels.json\"\n", + ")\n", + "input_collect = import_input_collect(inputCollect)\n", + "output_models = import_output_models(outputModel)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mmm_data = input_collect[\"mmm_data\"]\n", + "# display(mmm_data.data.head())\n", + "# Display Model Outputs\n", + "\n", + "output_models = output_models\n", + "# display((model_outputs.trials[0].result_hyp_param))\n", + "\n", + "hyperparameters = input_collect[\"hyperparameters\"]\n", + "# display(hyperparameters)\n", + "\n", + "featurized_mmm_data = input_collect[\"featurized_mmm_data\"]\n", + "\n", + "holidays_data = input_collect[\"holidays_data\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Add after model training\n", + "print(\"Model Output Summary:\")\n", + "print(f\"Number of trials: {len(output_models.trials)}\")\n", + "print(\n", + " f\"Average models per trial: {len(output_models.all_result_hyp_param) / len(output_models.trials)}\"\n", + ")\n", + "print(\n", + " f\"Total unique models: {len(output_models.all_result_hyp_param['sol_id'].unique())}\"\n", + ")\n", + "\n", + "print(\"\\nMetrics Distribution:\")\n", + "metrics_df = output_models.all_result_hyp_param[[\"nrmse\", \"decomp.rssd\", \"mape\"]]\n", + "print(metrics_df.describe())\n", + "\n", + "# Additional validation to debug model output\n", + "print(\"\\nColumns in result_hyp_param:\")\n", + "print(output_models.all_result_hyp_param.columns.tolist())\n", + "\n", + "print(\"\\nSample rows of metrics:\")\n", + "print(\n", + " output_models.all_result_hyp_param[\n", + " [\"sol_id\", \"nrmse\", \"decomp.rssd\", \"mape\"]\n", + " ].head()\n", + ")\n", + "\n", + "# Show shape of result dataframes\n", + "print(\"\\nDataFrame Shapes:\")\n", + "print(f\"result_hyp_param: {output_models.all_result_hyp_param.shape}\")\n", + "print(f\"x_decomp_agg: {output_models.all_x_decomp_agg.shape}\")\n", + "print(f\"decomp_spend_dist: {output_models.all_decomp_spend_dist.shape}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 3. Create ParetoOptimizer instance\n", + "pareto_optimizer = ParetoOptimizer(\n", + " mmm_data, output_models, hyperparameters, featurized_mmm_data, holidays_data\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 4. Run optimize function\n", + "pareto_result = pareto_optimizer.optimize(pareto_fronts=\"auto\", min_candidates=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 5. Check results\n", + "print(\"Pareto Optimization Results:\")\n", + "print(\n", + " f\"Number of Pareto fronts: {len(pareto_result.pareto_solutions)} - {pareto_result.pareto_solutions}\"\n", + ")\n", + "print(\n", + " f\"MediaVecCollect: {pareto_result.media_vec_collect.shape, pareto_result.media_vec_collect}\"\n", + ")\n", + "print(\"\\Hyper parameter solutions:\")\n", + "print(pareto_result.result_hyp_param)\n", + "\n", + "print(\"\\nAggregated decomposition results:\")\n", + "print(pareto_result.x_decomp_agg)\n", + "print(\"\\result Calibration:\")\n", + "print(pareto_result.result_calibration)\n", + "print(\"\\nx Decomp Vec Collect:\")\n", + "print(pareto_result.x_decomp_vec_collect.shape, pareto_result.x_decomp_vec_collect)\n", + "print(\"\\nCarryover percentage all:\")\n", + "print(pareto_result.df_caov_pct_all.shape, pareto_result.df_caov_pct_all)\n", + "print(\"\\Plot Data Collected\")\n", + "# print(\"NUMBER OF PLOTS Data collected for:\", len(pareto_result.plot_data_collect[\"2_4_8\"]))\n", + "# print(\"Plot data for solid 3_206_6\", pareto_result.plot_data_collect[\"2_4_8\"])\n", + "\n", + "# 6. Validate logic\n", + "assert pareto_result.pareto_fronts == \"auto\" or isinstance(\n", + " pareto_result.pareto_fronts, int\n", + "), \"Invalid pareto_fronts value\"\n", + "assert not pareto_result.result_hyp_param.empty, \"Empty result_hyp_param DataFrame\"\n", + "assert not pareto_result.x_decomp_agg.empty, \"Empty x_decomp_agg DataFrame\"\n", + "\n", + "print(\"\\nAll assertions passed. The optimize function is working as expected.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(pareto_result.x_decomp_agg[pareto_result.x_decomp_agg[\"sol_id\"] == \"5_221_9\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Clustering" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.modeling.clustering.clustering_config import ClusteringConfig, ClusterBy\n", + "from robyn.modeling.clustering.cluster_builder import ClusterBuilder\n", + "from robyn.data.entities.enums import DependentVarType\n", + "import plotly.io as pio\n", + "\n", + "pio.renderers.default = \"iframe\"\n", + "\n", + "cluster_configs = ClusteringConfig(\n", + " dep_var_type=DependentVarType(mmm_data.mmmdata_spec.dep_var_type),\n", + " cluster_by=ClusterBy.HYPERPARAMETERS,\n", + " max_clusters=10,\n", + " min_clusters=3,\n", + " weights=[1.0, 1.0, 1.0],\n", + ")\n", + "\n", + "cluster_builder = ClusterBuilder(pareto_result=pareto_result)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results = cluster_builder.cluster_models(cluster_configs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Cluster result Validations (graphs)\n", + "print(cluster_results.top_solutions[\"sol_id\"])\n", + "cluster_results.wss" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.plots.top_solutions_errors_plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.plots.top_solutions_rois_plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.cluster_ci.clusters_confidence_interval_plot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process Pareto Clustered Results for Allocator" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.modeling.pareto.pareto_utils import ParetoUtils\n", + "\n", + "utils = ParetoUtils()\n", + "filtered_pareto_results = utils.process_pareto_clustered_results(\n", + " pareto_result,\n", + " clustered_result=cluster_results,\n", + " ran_cluster=True,\n", + " ran_calibration=False,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# One Pager Results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.reporting.onepager_reporting import OnePager\n", + "from robyn.visualization.pareto_visualizer import ParetoVisualizer\n", + "\n", + "\n", + "visualizer = OnePager(\n", + " pareto_result=filtered_pareto_results,\n", + " clustered_result=cluster_results,\n", + " hyperparameter=hyperparameters,\n", + " mmm_data=mmm_data,\n", + " holidays_data=holidays_data,\n", + ")\n", + "visualizer.generate_one_pager(top_pareto=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "visualizer = ParetoVisualizer(\n", + " pareto_result=filtered_pareto_results,\n", + " hyperparameter=hyperparameters,\n", + " mmm_data=mmm_data,\n", + " holiday_data=holidays_data,\n", + " featurized_mmm_data=featurized_mmm_data,\n", + " unfiltered_pareto_result=pareto_result,\n", + " model_outputs=output_models,\n", + ")\n", + "\n", + "visualizer.plot_all(True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Allocator" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.15" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/e2e_test/tutorial4_pareto_e2e_test_with_allocator.ipynb b/python/tests/component_tutorials/e2e_test/tutorial4_pareto_e2e_test_with_allocator.ipynb new file mode 100644 index 000000000..539a5daf7 --- /dev/null +++ b/python/tests/component_tutorials/e2e_test/tutorial4_pareto_e2e_test_with_allocator.ipynb @@ -0,0 +1,425 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test Pareto Optimizer\n", + "\n", + "from robyn.modeling.pareto.pareto_optimizer import ParetoOptimizer\n", + "from robyn.tutorials.utils.data_mapper import (\n", + " import_output_models,\n", + " import_input_collect,\n", + " load_data_from_json,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load data from JSON\n", + "inputCollect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_InputCollect.json\"\n", + ")\n", + "outputModel = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_OutputModels.json\"\n", + ")\n", + "input_collect = import_input_collect(inputCollect)\n", + "output_models = import_output_models(outputModel)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "mmm_data = input_collect[\"mmm_data\"]\n", + "# display(mmm_data.data.head())\n", + "# Display Model Outputs\n", + "\n", + "output_models = output_models\n", + "# display((model_outputs.trials[0].result_hyp_param))\n", + "\n", + "hyperparameters = input_collect[\"hyperparameters\"]\n", + "# display(hyperparameters)\n", + "\n", + "featurized_mmm_data = input_collect[\"featurized_mmm_data\"]\n", + "\n", + "holidays_data = input_collect[\"holidays_data\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Add after model training\n", + "print(\"Model Output Summary:\")\n", + "print(f\"Number of trials: {len(output_models.trials)}\")\n", + "print(\n", + " f\"Average models per trial: {len(output_models.all_result_hyp_param) / len(output_models.trials)}\"\n", + ")\n", + "print(\n", + " f\"Total unique models: {len(output_models.all_result_hyp_param['sol_id'].unique())}\"\n", + ")\n", + "\n", + "print(\"\\nMetrics Distribution:\")\n", + "metrics_df = output_models.all_result_hyp_param[[\"nrmse\", \"decomp.rssd\", \"mape\"]]\n", + "print(metrics_df.describe())\n", + "\n", + "# Additional validation to debug model output\n", + "print(\"\\nColumns in result_hyp_param:\")\n", + "print(output_models.all_result_hyp_param.columns.tolist())\n", + "\n", + "print(\"\\nSample rows of metrics:\")\n", + "print(\n", + " output_models.all_result_hyp_param[\n", + " [\"sol_id\", \"nrmse\", \"decomp.rssd\", \"mape\"]\n", + " ].head()\n", + ")\n", + "\n", + "# Show shape of result dataframes\n", + "print(\"\\nDataFrame Shapes:\")\n", + "print(f\"result_hyp_param: {output_models.all_result_hyp_param.shape}\")\n", + "print(f\"x_decomp_agg: {output_models.all_x_decomp_agg.shape}\")\n", + "print(f\"decomp_spend_dist: {output_models.all_decomp_spend_dist.shape}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# 3. Create ParetoOptimizer instance\n", + "pareto_optimizer = ParetoOptimizer(\n", + " mmm_data, output_models, hyperparameters, featurized_mmm_data, holidays_data\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 4. Run optimize function\n", + "pareto_result = pareto_optimizer.optimize(pareto_fronts=\"auto\", min_candidates=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pareto_result.plot_data_collect" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 5. Check results\n", + "print(\"Pareto Optimization Results:\")\n", + "print(f\"Number of Pareto fronts: {pareto_result.pareto_solutions}\")\n", + "print(\n", + " f\"MediaVecCollect: {pareto_result.media_vec_collect.shape, pareto_result.media_vec_collect}\"\n", + ")\n", + "print(\"\\Hyper parameter solutions:\")\n", + "print(pareto_result.result_hyp_param)\n", + "\n", + "print(\"\\nAggregated decomposition results:\")\n", + "print(pareto_result.x_decomp_agg)\n", + "print(\"\\result Calibration:\")\n", + "print(pareto_result.result_calibration)\n", + "print(\"\\nx Decomp Vec Collect:\")\n", + "print(pareto_result.x_decomp_vec_collect.shape, pareto_result.x_decomp_vec_collect)\n", + "print(\"\\nCarryover percentage all:\")\n", + "print(pareto_result.df_caov_pct_all.shape, pareto_result.df_caov_pct_all)\n", + "print(\"\\Plot Data Collected\")\n", + "# print(\"NUMBER OF PLOTS Data collected for:\", len(pareto_result.plot_data_collect[\"2_4_8\"]))\n", + "# print(\"Plot data for solid 3_206_6\", pareto_result.plot_data_collect[\"2_4_8\"])\n", + "\n", + "# 6. Validate logic\n", + "assert pareto_result.pareto_fronts == \"auto\" or isinstance(\n", + " pareto_result.pareto_fronts, int\n", + "), \"Invalid pareto_fronts value\"\n", + "assert not pareto_result.result_hyp_param.empty, \"Empty result_hyp_param DataFrame\"\n", + "assert not pareto_result.x_decomp_agg.empty, \"Empty x_decomp_agg DataFrame\"\n", + "\n", + "print(\"\\nAll assertions passed. The optimize function is working as expected.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Allocator" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "## Step 1: Setup and Import\n", + "\n", + "# Import necessary Robyn classes\n", + "from robyn.allocator.entities.enums import OptimizationScenario, ConstrMode\n", + "from robyn.allocator.budget_allocator import BudgetAllocator\n", + "from robyn.allocator.entities.allocation_config import AllocationConfig\n", + "from robyn.allocator.entities.allocation_constraints import AllocationConstraints\n", + "from robyn.visualization.allocator_plotter import AllocationPlotter\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Make sure to use the correct model ID from your pareto results\n", + "available_models = pareto_result.result_hyp_param[\n", + " \"sol_id\"\n", + "].unique() # or 'solID' if that's the column name\n", + "print(f\"Available models: {available_models}\")\n", + "# Initialize allocator with a valid model ID\n", + "select_model = available_models[0] # Use first available model\n", + "\n", + "# Initialize budget allocator\n", + "allocator = BudgetAllocator(\n", + " mmm_data=mmm_data,\n", + " featurized_mmm_data=featurized_mmm_data,\n", + " pareto_result=pareto_result, # Get ParetoResult from import_output_collect()\n", + " select_model=select_model,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create base constraints matching R example\n", + "channel_constraints = AllocationConstraints(\n", + " channel_constr_low={\n", + " \"tv_S\": 0.7, # -30% from base\n", + " \"ooh_S\": 0.7,\n", + " \"print_S\": 0.7,\n", + " \"facebook_S\": 0.7,\n", + " \"search_S\": 0.7,\n", + " },\n", + " channel_constr_up={\n", + " \"tv_S\": 1.2, # +20% from base\n", + " \"ooh_S\": 1.5, # +50% from base\n", + " \"print_S\": 1.5,\n", + " \"facebook_S\": 1.5,\n", + " \"search_S\": 1.5,\n", + " },\n", + " channel_constr_multiplier=3.0,\n", + ")\n", + "\n", + "# Configure max response scenario\n", + "max_response_config = AllocationConfig(\n", + " scenario=OptimizationScenario.MAX_RESPONSE,\n", + " constraints=channel_constraints,\n", + " date_range=\"last\", # Use last period as initial\n", + " total_budget=None, # Use historical budget\n", + " maxeval=100000,\n", + " optim_algo=\"SLSQP_AUGLAG\",\n", + " constr_mode=ConstrMode.EQUALITY,\n", + " plots=True,\n", + ")\n", + "\n", + "# Run optimization\n", + "result = allocator.allocate(max_response_config)\n", + "\n", + "# Print results\n", + "print(\n", + " f\"\"\"\n", + "Model ID: {select_model}\n", + "Scenario: {max_response_config.scenario}\n", + "Use case: {result.metrics.get('use_case', '')}\n", + "Window: {result.metrics.get('date_range_start')}:{result.metrics.get('date_range_end')} ({result.metrics.get('n_periods')} {mmm_data.mmmdata_spec.interval_type})\n", + "\n", + "Dep. Variable Type: {mmm_data.mmmdata_spec.dep_var_type}\n", + "Media Skipped: {result.metrics.get('skipped_channels', 'None')}\n", + "Relative Spend Increase: {result.metrics.get('spend_lift_pct', 0):.1f}% ({result.metrics.get('spend_lift_abs', 0):+.0f}K)\n", + "Total Response Increase (Optimized): {result.metrics.get('response_lift', 0)*100:.1f}%\n", + "\n", + "Allocation Summary:\n", + "\"\"\"\n", + ")\n", + "\n", + "# Print channel-level results\n", + "for channel in mmm_data.mmmdata_spec.paid_media_spends:\n", + " current = result.optimal_allocations[\n", + " result.optimal_allocations[\"channel\"] == channel\n", + " ].iloc[0]\n", + "\n", + " print(\n", + " f\"\"\"\n", + "- {channel}:\n", + " Optimizable bound: [{(current['constr_low']-1)*100:.0f}%, {(current['constr_up']-1)*100:.0f}%],\n", + " Initial spend share: {current['current_spend_share']*100:.2f}% -> Optimized bounded: {current['optimal_spend_share']*100:.2f}%\n", + " Initial response share: {current['current_response_share']*100:.2f}% -> Optimized bounded: {current['optimal_response_share']*100:.2f}%\n", + " Initial abs. mean spend: {current['current_spend']/1000:.3f}K -> Optimized: {current['optimal_spend']/1000:.3f}K [Delta = {(current['optimal_spend']/current['current_spend']-1)*100:.0f}%]\n", + "\"\"\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Scenario 3: Default Target Efficiency (Target ROAS or CPA)\n", + "print(\"\\nScenario 3: Target efficiency optimization\")\n", + "\n", + "# Create constraints matching R's implementation\n", + "default_channel_constraints = AllocationConstraints(\n", + " channel_constr_low={\n", + " channel: 0.1\n", + " for channel in mmm_data.mmmdata_spec.paid_media_spends # -90% from base for all channels\n", + " },\n", + " channel_constr_up={\n", + " channel: 10.0\n", + " for channel in mmm_data.mmmdata_spec.paid_media_spends # +900% from base for all channels\n", + " },\n", + " channel_constr_multiplier=1.0, # Don't extend bounds for target efficiency\n", + " is_target_efficiency=True, # Flag this as target efficiency scenario\n", + ")\n", + "\n", + "# Create configuration for target efficiency scenario\n", + "target_efficiency_config = AllocationConfig(\n", + " scenario=OptimizationScenario.TARGET_EFFICIENCY,\n", + " constraints=default_channel_constraints,\n", + " date_range=\"all\", # Use all dates like in R version\n", + " target_value=None, # Will use default 80% of initial ROAS or 120% of initial CPA\n", + " maxeval=100000,\n", + " optim_algo=\"SLSQP_AUGLAG\",\n", + " constr_mode=ConstrMode.EQUALITY,\n", + " plots=True,\n", + ")\n", + "\n", + "# Run optimization\n", + "result3 = allocator.allocate(target_efficiency_config)\n", + "\n", + "# Print results matching R format\n", + "print(\n", + " f\"\"\"\n", + "Model ID: {select_model}\n", + "Scenario: {target_efficiency_config.scenario}\n", + "Use case: {result3.metrics.get('use_case', '')}\n", + "Window: {result3.metrics.get('date_range_start')}:{result3.metrics.get('date_range_end')} ({result3.metrics.get('n_periods')} {mmm_data.mmmdata_spec.interval_type})\n", + "\n", + "Dep. Variable Type: {mmm_data.mmmdata_spec.dep_var_type}\n", + "Media Skipped: {result3.metrics.get('skipped_channels', 'None')}\n", + "Relative Spend Increase: {result3.metrics.get('spend_lift_pct', 0):.0f}% ({result3.metrics.get('spend_lift_abs', 0):.0f})\n", + "Total Response Increase (Optimized): {result3.metrics.get('response_lift', 0)*100:.0f}%\n", + "\n", + "Allocation Summary:\n", + "\"\"\"\n", + ")\n", + "\n", + "# Print channel-level results\n", + "for channel in mmm_data.mmmdata_spec.paid_media_spends:\n", + " current = result3.optimal_allocations[\n", + " result3.optimal_allocations[\"channel\"] == channel\n", + " ].iloc[0]\n", + "\n", + " print(\n", + " f\"\"\"\n", + "- {channel}:\n", + " Optimizable bound: [{(current['constr_low']-1)*100:.0f}%, {(current['constr_up']-1)*100:.0f}%],\n", + " Initial spend share: {current['current_spend_share']*100:.2f}% -> Optimized bounded: {current['optimal_spend_share']*100:.2f}%\n", + " Initial response share: {current['current_response_share']*100:.2f}% -> Optimized bounded: {current['optimal_response_share']*100:.2f}%\n", + " Initial abs. mean spend: {current['current_spend']/1000:.3f}K -> Optimized: {current['optimal_spend']/1000:.3f}K [Delta = {(current['optimal_spend']/current['current_spend']-1)*100:.0f}%]\n", + "\"\"\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create visualizations for each scenario\n", + "max_response_plotter = AllocationPlotter(result)\n", + "target_efficiency_plotter = AllocationPlotter(result3)\n", + "\n", + "# Generate plots\n", + "max_response_plots = max_response_plotter.plot_all()\n", + "target_efficiency_plots = target_efficiency_plotter.plot_all()\n", + "\n", + "# Display plots\n", + "print(\"Max Response Scenario Plots:\")\n", + "print(\"-\" * 50)\n", + "for plot_name, fig in max_response_plots.items():\n", + " display(fig)\n", + "\n", + "\n", + "print(\"\\nTarget Efficiency Scenario Plots:\")\n", + "print(\"-\" * 50)\n", + "for plot_name, fig in target_efficiency_plots.items():\n", + " display(fig)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/r_exported_data/r_tutorial3_modeling_compare.ipynb b/python/tests/component_tutorials/r_exported_data/r_tutorial3_modeling_compare.ipynb new file mode 100644 index 000000000..01b1a9f65 --- /dev/null +++ b/python/tests/component_tutorials/r_exported_data/r_tutorial3_modeling_compare.ipynb @@ -0,0 +1,839 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Robyn: Marketing Mix Modeling Application\n", + "\n", + "This notebook demonstrates the usage of Robyn, a Marketing Mix Modeling (MMM) application. \n", + "We'll go through the main steps of performing robyn_inputs and robyn_engineering.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1. Import Required Libraries. Define Paths.\n", + "\n", + "First, be sure to setup your virtual environment. Be sure to switch over to your new environment in this notebook. \n", + "\n", + "-```cd {root_folder}```\n", + "\n", + "-```python3 -m yourvenv```\n", + "\n", + "-```source yourvenv/bin/activate```\n", + "\n", + "-```cd Robyn/python```\n", + "\n", + "-```pip install -r requirements.txt```\n", + "\n", + "\n", + "Then import the necessary libraries. Make sure to define your paths below.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pandas as pd\n", + "from typing import Dict\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "from robyn.modeling.model_executor import ModelExecutor\n", + "from robyn.modeling.entities.enums import NevergradAlgorithm, Models\n", + "from robyn.modeling.feature_engineering import FeatureEngineering" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.1 Load Mock R data\n", + "\n", + "We need to set the base path for the data directory.\n", + "Create a .env file in the same directory as your notebook and put in define the path to the data dir.\n", + "for example: ROBYN_BASE_PATH=.../Robyn/R/data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.tutorials.utils.data_mapper import load_data_from_json, import_input_collect, import_output_models\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "# Load data from JSON exported from R\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_Pareto_50_iterations_1_trial_InputCollect.json\"\n", + ")\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "\n", + "# Extract individual components\n", + "r_mmm_data = r_input_collect[\"mmm_data\"]\n", + "r_featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "r_holidays_data = r_input_collect[\"holidays_data\"]\n", + "r_hyperparameters = r_input_collect[\"hyperparameters\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup MMM Data\n", + "\n", + "We will now set up the MMM data specification which includes defining the dependent variable, independent variables, and the time window for analysis." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Preprocessing\n", + "\n", + "We will perform feature engineering to prepare the data for modeling. This includes transformations like adstock and other preprocessing steps." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# hyperparameters = Hyperparameters(\n", + "# hyperparameters={\n", + "# \"facebook_S\": ChannelHyperparameters(\n", + "# alphas=[0.5, 3],\n", + "# gammas=[0.3, 1],\n", + "# thetas=[0, 0.3],\n", + "# ),\n", + "# \"print_S\": ChannelHyperparameters(\n", + "# alphas=[0.5, 3],\n", + "# gammas=[0.3, 1],\n", + "# thetas=[0.1, 0.4],\n", + "# ),\n", + "# \"tv_S\": ChannelHyperparameters(\n", + "# alphas=[0.5, 3],\n", + "# gammas=[0.3, 1],\n", + "# thetas=[0.3, 0.8],\n", + "# ),\n", + "# \"search_S\": ChannelHyperparameters(\n", + "# alphas=[0.5, 3],\n", + "# gammas=[0.3, 1],\n", + "# thetas=[0, 0.3],\n", + "# ),\n", + "# \"ooh_S\": ChannelHyperparameters(\n", + "# alphas=[0.5, 3],\n", + "# gammas=[0.3, 1],\n", + "# thetas=[0.1, 0.4],\n", + "# ),\n", + "# \"newsletter\": ChannelHyperparameters(\n", + "# alphas=[0.5, 3],\n", + "# gammas=[0.3, 1],\n", + "# thetas=[0.1, 0.4],\n", + "# ),\n", + "# },\n", + "# adstock=AdstockType.GEOMETRIC,\n", + "# lambda_=[0, 1],\n", + "# train_size=[0.5, 0.8],\n", + "# )\n", + "\n", + "# print(\"Hyperparameters setup complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# # Create HolidaysData object\n", + "# holidays_data = HolidaysData(\n", + "# dt_holidays=dt_prophet_holidays,\n", + "# prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + "# prophet_country=\"DE\",\n", + "# prophet_signs=[\"default\", \"default\", \"default\"],\n", + "# )\n", + "# # Setup FeaturizedMMMData\n", + "feature_engineering = FeatureEngineering(r_mmm_data, r_hyperparameters, r_holidays_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from PIL import Image\n", + "import io\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Assuming plot_data is a list of bytes\n", + "plot_data = r_featurized_mmm_data.modNLS[\"plots\"].get(\"facebook_I\")\n", + "\n", + "# Convert the list of hex strings to a single bytes object\n", + "binary_data = bytes.fromhex(\"\".join(plot_data))\n", + "\n", + "# Convert binary data to an image\n", + "image = Image.open(io.BytesIO(binary_data))\n", + "\n", + "# Display the image using matplotlib\n", + "plt.imshow(image)\n", + "plt.axis(\"off\") # Hide axes\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from PIL import Image\n", + "import io\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Assuming plot_data is a list of bytes\n", + "plot_data = r_featurized_mmm_data.modNLS[\"plots\"].get(\"search_clicks_P\")\n", + "\n", + "# Convert the list of hex strings to a single bytes object\n", + "binary_data = bytes.fromhex(\"\".join(plot_data))\n", + "\n", + "# Convert binary data to an image\n", + "image = Image.open(io.BytesIO(binary_data))\n", + "\n", + "# Display the image using matplotlib\n", + "plt.imshow(image)\n", + "plt.axis(\"off\") # Hide axes\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "\n", + "# For MMM Data\n", + "def debug_mmm_data(mmm_data):\n", + " print(\"=== MMM Data Debug ===\")\n", + " print(\"\\nMMM Data Specification:\")\n", + " print(f\"Dependent Variable: {mmm_data.mmmdata_spec.dep_var}\")\n", + " print(f\"Paid Media Spends: {mmm_data.mmmdata_spec.paid_media_spends}\")\n", + " print(f\"Paid Media Vars: {mmm_data.mmmdata_spec.paid_media_vars}\")\n", + " print(f\"Organic Vars: {mmm_data.mmmdata_spec.organic_vars}\")\n", + "\n", + "\n", + "# For Hyperparameters\n", + "def debug_hyperparameters(hyperparameters):\n", + " print(\"=== Hyperparameters Debug ===\")\n", + " print(\"\\nHyperparameters structure:\")\n", + " for channel, params in hyperparameters.hyperparameters.items():\n", + " print(f\"\\nChannel: {channel}\")\n", + " print(\"Thetas:\", getattr(params, \"thetas\", None))\n", + " print(\"Alphas:\", getattr(params, \"alphas\", None))\n", + " print(\"Gammas:\", getattr(params, \"gammas\", None))\n", + " print(\"Shapes:\", getattr(params, \"shapes\", None))\n", + " print(\"Scales:\", getattr(params, \"scales\", None))\n", + "\n", + " print(\"\\nLambda:\", hyperparameters.lambda_)\n", + " print(\"Train size:\", hyperparameters.train_size)\n", + "\n", + "\n", + "# For Featurized MMM Data\n", + "def debug_featurized_data(featurized_mmm_data):\n", + " print(\"=== Featurized MMM Data Debug ===\")\n", + " print(\"\\nFeaturized data shape:\", featurized_mmm_data.dt_mod.shape)\n", + " print(\"\\nFeaturized data columns:\", featurized_mmm_data.dt_mod.columns.tolist())\n", + "\n", + " # Basic statistics of the featurized data\n", + " print(\"\\nFeaturized data statistics:\")\n", + " print(featurized_mmm_data.dt_mod.describe())\n", + "\n", + " # Check for any transformations that occurred\n", + " print(\"\\nData types:\")\n", + " print(featurized_mmm_data.dt_mod.dtypes)\n", + "\n", + " # Check for any missing or infinite values\n", + " print(\"\\nMissing values count:\")\n", + " print(featurized_mmm_data.dt_mod.isnull().sum())\n", + " print(\"\\nInfinite values count:\")\n", + " print(np.isinf(featurized_mmm_data.dt_mod.select_dtypes(include=np.number)).sum())\n", + "\n", + "\n", + "# Combined debug function\n", + "def debug_all_inputs(mmm_data, hyperparameters, featurized_mmm_data):\n", + " debug_mmm_data(mmm_data)\n", + " print(\"\\n\" + \"=\" * 50 + \"\\n\")\n", + " debug_hyperparameters(hyperparameters)\n", + " print(\"\\n\" + \"=\" * 50 + \"\\n\")\n", + " debug_featurized_data(featurized_mmm_data)\n", + "\n", + "\n", + "# Usage:\n", + "debug_all_inputs(r_mmm_data, r_hyperparameters, r_featurized_mmm_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def convert_r_data_to_python_format(\n", + " r_mmm_data, r_hyperparameters, r_featurized_mmm_data\n", + "):\n", + " \"\"\"\n", + " Convert R imported data to match Python's expected format\n", + " \"\"\"\n", + " import pandas as pd\n", + " import copy\n", + "\n", + " # Deep copy to avoid modifying original data\n", + " mmm_data = copy.deepcopy(r_mmm_data)\n", + " hyperparameters = copy.deepcopy(r_hyperparameters)\n", + " featurized_mmm_data = copy.deepcopy(r_featurized_mmm_data)\n", + "\n", + " # 1. Fix column names in featurized data\n", + " if \"dep_var\" in featurized_mmm_data.dt_mod.columns:\n", + " featurized_mmm_data.dt_mod = featurized_mmm_data.dt_mod.rename(\n", + " columns={\"dep_var\": \"revenue\"}\n", + " )\n", + "\n", + " # 2. Convert date column to datetime\n", + " featurized_mmm_data.dt_mod[\"ds\"] = pd.to_datetime(featurized_mmm_data.dt_mod[\"ds\"])\n", + "\n", + " # 3. Update lambda in hyperparameters\n", + " hyperparameters.lambda_ = [0, 1] # Change from 0.0 to [0, 1]\n", + "\n", + " # 4. Ensure all numeric columns are float64 (except competitor_sales_B which should be int64)\n", + " numeric_cols = featurized_mmm_data.dt_mod.select_dtypes(include=[np.number]).columns\n", + " for col in numeric_cols:\n", + " if col != \"competitor_sales_B\":\n", + " featurized_mmm_data.dt_mod[col] = featurized_mmm_data.dt_mod[col].astype(\n", + " \"float64\"\n", + " )\n", + " featurized_mmm_data.dt_mod[\"competitor_sales_B\"] = featurized_mmm_data.dt_mod[\n", + " \"competitor_sales_B\"\n", + " ].astype(\"int64\")\n", + "\n", + " return mmm_data, hyperparameters, featurized_mmm_data\n", + "\n", + "\n", + "# Convert the data\n", + "converted_mmm_data, converted_hyperparameters, converted_featurized_mmm_data = (\n", + " convert_r_data_to_python_format(\n", + " r_mmm_data, r_hyperparameters, r_featurized_mmm_data\n", + " )\n", + ")\n", + "\n", + "# Verify the conversion\n", + "print(\"=== Verifying Conversion ===\")\n", + "print(\"\\nChecking column names:\")\n", + "print(converted_featurized_mmm_data.dt_mod.columns.tolist())\n", + "\n", + "print(\"\\nChecking data types:\")\n", + "print(converted_featurized_mmm_data.dt_mod.dtypes)\n", + "\n", + "print(\"\\nChecking lambda parameter:\")\n", + "print(converted_hyperparameters.lambda_)\n", + "\n", + "print(\"\\nChecking a few rows of numeric data to ensure precision is maintained:\")\n", + "numeric_cols = converted_featurized_mmm_data.dt_mod.select_dtypes(\n", + " include=[np.number]\n", + ").columns\n", + "print(converted_featurized_mmm_data.dt_mod[numeric_cols].head())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "# Setup ModelExecutor\n", + "model_executor = ModelExecutor(\n", + " mmmdata=converted_mmm_data,\n", + " holidays_data=r_holidays_data,\n", + " hyperparameters=converted_hyperparameters,\n", + " calibration_input=None, # Add calibration input if available\n", + " featurized_mmm_data=converted_featurized_mmm_data,\n", + ")\n", + "\n", + "# Setup TrialsConfig\n", + "trials_config = TrialsConfig(\n", + " iterations=2000, trials=5\n", + ") # Set to the number of cores you want to use\n", + "\n", + "print(\n", + " f\">>> Starting {trials_config.trials} trials with {trials_config.iterations} iterations each using {NevergradAlgorithm.TWO_POINTS_DE.value} nevergrad algorithm on x cores...\"\n", + ")\n", + "\n", + "# Run the model\n", + "\n", + "output_models = model_executor.model_run(\n", + " trials_config=trials_config,\n", + " ts_validation=True, # changed from True to False -> deacitvate\n", + " add_penalty_factor=False,\n", + " rssd_zero_penalty=True,\n", + " cores=16,\n", + " nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE,\n", + " intercept=True,\n", + " intercept_sign=\"non_negative\",\n", + " model_name=Models.RIDGE,\n", + ")\n", + "print(\"Model training complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.tutorials.utils.data_mapper import load_data_from_json, import_input_collect, import_output_models\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "raw_output_models = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_Pareto_50_iterations_1_trial_OutputModels.json\"\n", + ")\n", + "\n", + "r_output_models = import_output_models(raw_output_models)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.tutorials.utils.data_mapper import load_data_from_json, import_input_collect, import_output_models\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "# Load data from JSON exported from R\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_50_InputCollect.json\"\n", + ")\n", + "raw_output_models = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_50_OutputModels.json\"\n", + ")\n", + "\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "r_output_models = import_output_models(raw_output_models)\n", + "\n", + "# Extract individual components\n", + "r_mmm_data = r_input_collect[\"mmm_data\"]\n", + "r_featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "r_holidays_data = r_input_collect[\"holidays_data\"]\n", + "r_hyperparameters = r_input_collect[\"hyperparameters\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# new anytree\n", + "\n", + "from anytree import Node, RenderTree\n", + "from dataclasses import is_dataclass, asdict\n", + "import pandas as pd\n", + "\n", + "\n", + "def build_tree(data, parent_key=\"\", limit_trials=True):\n", + " \"\"\"\n", + " Recursively build a tree structure from a dictionary, list, or dataclass.\n", + "\n", + " Args:\n", + " data: The data structure (dict, list, or dataclass) to traverse.\n", + " parent_key: The base key path for nested keys.\n", + " limit_trials: Whether to limit the output to the first trial.\n", + "\n", + " Returns:\n", + " A tree node representing the structure of the data.\n", + " \"\"\"\n", + " if is_dataclass(data):\n", + " data = asdict(data) # Convert dataclass to dictionary\n", + "\n", + " if isinstance(data, dict):\n", + " node = Node(f\"{parent_key} (Dict)\")\n", + " for key, value in data.items():\n", + " full_key = f\"{parent_key}.{key}\" if parent_key else key\n", + " child_node = build_tree(value, full_key, limit_trials)\n", + " child_node.parent = node\n", + " return node\n", + " elif isinstance(data, list):\n", + " node = Node(f\"{parent_key} (List)\")\n", + " for index, item in enumerate(data):\n", + " if limit_trials and parent_key == \"trials\" and index > 0:\n", + " break\n", + " full_key = f\"{parent_key}[{index}]\"\n", + " child_node = build_tree(item, full_key, limit_trials)\n", + " child_node.parent = node\n", + " return node\n", + " elif isinstance(data, pd.DataFrame):\n", + " node = Node(f\"{parent_key} (DataFrame)\")\n", + " for column in data.columns:\n", + " dtype = data[column].dtype\n", + " column_node = Node(f\"{parent_key}.{column} (dtype: {dtype})\")\n", + " column_node.parent = node\n", + " return node\n", + " else:\n", + " dtype = type(data).__name__\n", + " return Node(f\"{parent_key} (dtype: {dtype})\")\n", + "\n", + "\n", + "# Assuming output_models and r_output_models are instances of ModelOutputs\n", + "python_tree = build_tree(output_models)\n", + "r_tree = build_tree(r_output_models)\n", + "\n", + "# Visualize the trees\n", + "print(\"Python ModelOutputs Structure:\")\n", + "for pre, fill, node in RenderTree(python_tree):\n", + " print(f\"{pre}{node.name}\")\n", + "\n", + "print(\"\\nR ModelOutputs Structure:\")\n", + "for pre, fill, node in RenderTree(r_tree):\n", + " print(f\"{pre}{node.name}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# from anytree import Node, RenderTree\n", + "# from anytree.exporter import DotExporter\n", + "# from dataclasses import is_dataclass, asdict\n", + "# import pandas as pd\n", + "\n", + "\n", + "# def build_tree(data, parent_key=\"\", limit_trials=True):\n", + "# \"\"\"\n", + "# Recursively build a tree structure from a dictionary, list, or dataclass.\n", + "\n", + "# Args:\n", + "# data: The data structure (dict, list, or dataclass) to traverse.\n", + "# parent_key: The base key path for nested keys.\n", + "# limit_trials: Whether to limit the output to the first trial.\n", + "\n", + "# Returns:\n", + "# A tree node representing the structure of the data.\n", + "# \"\"\"\n", + "# if is_dataclass(data):\n", + "# data = asdict(data) # Convert dataclass to dictionary\n", + "\n", + "# if isinstance(data, dict):\n", + "# node = Node(parent_key)\n", + "# for key, value in data.items():\n", + "# full_key = f\"{parent_key}.{key}\" if parent_key else key\n", + "# child_node = build_tree(value, full_key, limit_trials)\n", + "# child_node.parent = node\n", + "# return node\n", + "# elif isinstance(data, list):\n", + "# node = Node(parent_key)\n", + "# for index, item in enumerate(data):\n", + "# if limit_trials and parent_key == \"trials\" and index > 0:\n", + "# break\n", + "# full_key = f\"{parent_key}[{index}]\"\n", + "# child_node = build_tree(item, full_key, limit_trials)\n", + "# child_node.parent = node\n", + "# return node\n", + "# elif isinstance(data, pd.DataFrame):\n", + "# node = Node(f\"{parent_key} (DataFrame: {data.shape})\")\n", + "# for column in data.columns:\n", + "# column_node = Node(f\"{parent_key}.{column}\")\n", + "# column_node.parent = node\n", + "# return node\n", + "# else:\n", + "# return Node(parent_key)\n", + "\n", + "\n", + "# # Assuming output_models and r_output_models are instances of ModelOutputs\n", + "# python_tree = build_tree(output_models)\n", + "# r_tree = build_tree(r_output_models)\n", + "\n", + "# # Visualize the trees\n", + "# print(\"Python ModelOutputs Structure:\")\n", + "# for pre, fill, node in RenderTree(python_tree):\n", + "# print(f\"{pre}{node.name}\")\n", + "\n", + "# print(\"\\nR ModelOutputs Structure:\")\n", + "# for pre, fill, node in RenderTree(r_tree):\n", + "# print(f\"{pre}{node.name}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from typing import Dict, Any\n", + "\n", + "\n", + "def compare_model_values(py_output, r_output):\n", + " \"\"\"Compare key values between Python and R model outputs\"\"\"\n", + "\n", + " print(\"1. Basic Model Configuration Comparison:\")\n", + " basic_attrs = [\n", + " \"train_timestamp\",\n", + " \"cores\",\n", + " \"iterations\",\n", + " \"intercept\",\n", + " \"intercept_sign\",\n", + " \"nevergrad_algo\",\n", + " \"ts_validation\",\n", + " \"add_penalty_factor\",\n", + " ]\n", + "\n", + " # Add debug prints\n", + " print(\"\\nDebugging attribute types:\")\n", + " for attr in basic_attrs:\n", + " py_val = getattr(py_output, attr, None)\n", + " r_val = getattr(r_output, attr, None)\n", + " print(f\"{attr:20s} - Python type: {type(py_val)} | R type: {type(r_val)}\")\n", + " print(f\"{attr:20s} - Python value: {py_val} | R value: {r_val}\")\n", + " print(\"-\" * 50)\n", + "\n", + " print(\"\\n2. Trial Results Comparison (Descriptive Statistics):\")\n", + " if py_output.trials and r_output.trials:\n", + " metrics = [\n", + " \"nrmse\",\n", + " \"decomp_rssd\",\n", + " \"mape\",\n", + " \"rsq_train\",\n", + " \"rsq_val\",\n", + " \"rsq_test\",\n", + " \"lambda_\",\n", + " \"lambda_hp\",\n", + " \"lambda_max\",\n", + " \"lambda_min_ratio\",\n", + " ]\n", + " # Convert trial results to DataFrames\n", + " py_trials_df = pd.DataFrame(\n", + " [\n", + " {metric: getattr(trial, metric, np.nan) for metric in metrics}\n", + " for trial in py_output.trials\n", + " ]\n", + " )\n", + "\n", + " # Aggregate R trial metrics\n", + " r_trials_df = pd.DataFrame(\n", + " [\n", + " {\n", + " metric: getattr(trial, metric, pd.Series([np.nan])).mean()\n", + " for metric in metrics\n", + " }\n", + " for trial in r_output.trials\n", + " ]\n", + " )\n", + " # Ensure R trial data is numeric\n", + " r_trials_df = r_trials_df.apply(pd.to_numeric, errors=\"coerce\")\n", + " # Calculate descriptive statistics\n", + " py_desc = py_trials_df.describe()\n", + " r_desc = r_trials_df.describe()\n", + " # Print descriptive statistics\n", + " print(\"\\nPython Trial Descriptive Statistics:\")\n", + " print(py_desc)\n", + " print(\"\\nR Trial Descriptive Statistics:\")\n", + " print(r_desc)\n", + " # Calculate and print differences\n", + " diff_desc = py_desc - r_desc\n", + " print(\"\\nDifference in Descriptive Statistics:\")\n", + " print(diff_desc)\n", + "\n", + " print(\"\\n3. Hyperparameter Comparison:\")\n", + " if hasattr(py_output, \"hyper_updated\") and hasattr(r_output, \"hyper_updated\"):\n", + " py_hyper = py_output.hyper_updated\n", + " r_hyper = r_output.hyper_updated\n", + "\n", + " # Find all unique keys\n", + " all_keys = set(py_hyper.keys()) | set(r_hyper.keys())\n", + "\n", + " print(\"\\nHyperparameter Values:\")\n", + " print(f\"{'Parameter':30s} {'Python':>15s} {'R':>15s} {'Diff':>15s}\")\n", + " print(\"-\" * 75)\n", + "\n", + " for key in sorted(all_keys):\n", + " py_val = py_hyper.get(key, \"N/A\")\n", + " r_val = r_hyper.get(key, \"N/A\")\n", + "\n", + " if isinstance(py_val, (int, float)) and isinstance(r_val, (int, float)):\n", + " diff = abs(py_val - r_val)\n", + " print(f\"{key:30s} {py_val:15.6f} {r_val:15.6f} {diff:15.6f}\")\n", + " else:\n", + " print(f\"{key:30s} {str(py_val):15s} {str(r_val):15s} {'N/A':>15s}\")\n", + "\n", + " print(\"\\n4. Data Shape Comparison:\")\n", + " data_attrs = [\"all_result_hyp_param\", \"all_x_decomp_agg\", \"all_decomp_spend_dist\"]\n", + "\n", + " for attr in data_attrs:\n", + " py_shape = getattr(py_output, attr).shape if hasattr(py_output, attr) else None\n", + " r_shape = getattr(r_output, attr).shape if hasattr(r_output, attr) else None\n", + " print(f\"{attr:20s} - Python shape: {py_shape} | R shape: {r_shape}\")\n", + "\n", + " print(\"\\n5. Total Effect and Effect Share Comparison:\")\n", + " if py_output.trials and r_output.trials:\n", + " for i, (py_trial, r_trial) in enumerate(zip(py_output.trials, r_output.trials)):\n", + " print(f\"\\nTrial {i+1}:\")\n", + " # Extract decomp_spend_dist DataFrames\n", + " py_decomp_spend_dist = getattr(\n", + " py_trial, \"decomp_spend_dist\", pd.DataFrame()\n", + " )\n", + " r_decomp_spend_dist = getattr(r_trial, \"decomp_spend_dist\", pd.DataFrame())\n", + " # Check if the DataFrames are not empty\n", + " if not py_decomp_spend_dist.empty and not r_decomp_spend_dist.empty:\n", + " # Compare total effect\n", + " py_total_effect = py_decomp_spend_dist.get(\n", + " \"xDecompAgg\", pd.Series([np.nan])\n", + " ).sum()\n", + " r_total_effect = r_decomp_spend_dist.get(\n", + " \"xDecompAgg\", pd.Series([np.nan])\n", + " ).sum()\n", + " total_effect_diff = abs(py_total_effect - r_total_effect)\n", + " print(\n", + " f\"Total Effect - Python: {py_total_effect:.6f}, R: {r_total_effect:.6f}, Diff: {total_effect_diff:.6f}\"\n", + " )\n", + " # Compare effect share\n", + " py_effect_share = py_decomp_spend_dist.get(\n", + " \"effect_share\", pd.Series([np.nan])\n", + " ).sum()\n", + " r_effect_share = r_decomp_spend_dist.get(\n", + " \"effect_share\", pd.Series([np.nan])\n", + " ).sum()\n", + " effect_share_diff = abs(py_effect_share - r_effect_share)\n", + " print(\n", + " f\"Effect Share - Python: {py_effect_share:.6f}, R: {r_effect_share:.6f}, Diff: {effect_share_diff:.6f}\"\n", + " )\n", + " else:\n", + " print(\n", + " \"Decomposition spend distribution data is missing for this trial.\"\n", + " )\n", + "\n", + "\n", + "# Run the comparison\n", + "print(\"Starting detailed value comparison...\\n\")\n", + "compare_model_values(output_models, r_output_models)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# # Function to print model output summary\n", + "# def print_model_output_summary(model_name, model):\n", + "# print(f\"\\n{model_name} Model Output Summary:\")\n", + "# print(f\"Number of trials: {len(model.trials)}\")\n", + "# print(\n", + "# f\"Average models per trial: {len(model.all_result_hyp_param) / len(model.trials)}\"\n", + "# )\n", + "# print(f\"Total unique models: {len(model.all_result_hyp_param['sol_id'].unique())}\")\n", + "\n", + "# print(\"\\nMetrics Distribution:\")\n", + "# metrics_df = model.all_result_hyp_param[[\"nrmse\", \"decomp.rssd\", \"mape\"]]\n", + "# print(metrics_df.describe())\n", + "\n", + "# # Additional validation to debug model output\n", + "# print(\"\\nColumns in result_hyp_param:\")\n", + "# print(model.all_result_hyp_param.columns.tolist())\n", + "\n", + "# print(\"\\nSample rows of metrics:\")\n", + "# print(model.all_result_hyp_param[[\"sol_id\", \"nrmse\", \"decomp.rssd\", \"mape\"]].head())\n", + "\n", + "# # Show shape of result dataframes\n", + "# print(\"\\nDataFrame Shapes:\")\n", + "# print(f\"result_hyp_param: {model.all_result_hyp_param.shape}\")\n", + "# print(f\"x_decomp_agg: {model.all_x_decomp_agg.shape}\")\n", + "# print(f\"decomp_spend_dist: {model.all_decomp_spend_dist.shape}\")\n", + "\n", + "\n", + "# # Print summaries for both output_models and r_output_models\n", + "# print_model_output_summary(\"Python Output Models\", output_models)\n", + "# print_model_output_summary(\"R Output Models\", r_output_models)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# def print_data_structure(data):\n", + "# print(\"Columns:\", data.columns.tolist())\n", + "# print(\"\\nFirst row:\", data.iloc[0].to_dict())\n", + "# print(\"\\nShape:\", data.shape)\n", + "\n", + "\n", + "# # Assuming you want to print the structure for the first trial\n", + "# first_trial_r = r_output_models.trials[0].decomp_spend_dist\n", + "# first_trial_python = output_models.trials[0].decomp_spend_dist\n", + "\n", + "# print(\"R exported data structure:\")\n", + "# print_data_structure(first_trial_r)\n", + "\n", + "# # With Python calculated data\n", + "# print(\"\\nPython calculated data structure:\")\n", + "# print_data_structure(first_trial_python)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mytestenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.15" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/tutorial2_feature_engineering.ipynb b/python/tests/component_tutorials/tutorial2_feature_engineering.ipynb new file mode 100644 index 000000000..7c6fb2753 --- /dev/null +++ b/python/tests/component_tutorials/tutorial2_feature_engineering.ipynb @@ -0,0 +1,929 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "53f2f84a", + "metadata": {}, + "source": [ + "# Robyn: Marketing Mix Modeling Application\n", + "\n", + "This notebook demonstrates the usage of Robyn, a Marketing Mix Modeling (MMM) application. \n", + "We'll go through the main steps of performing robyn_inputs and robyn_engineering.\n" + ] + }, + { + "cell_type": "markdown", + "id": "6fd474b7", + "metadata": {}, + "source": [ + "\n", + "## 1. Import Required Libraries. Define Paths.\n", + "\n", + "First, be sure to setup your virtual environment. Be sure to switch over to your new environment in this notebook. \n", + "\n", + "-```cd {root_folder}```\n", + "\n", + "-```python3 -m yourvenv```\n", + "\n", + "-```source yourvenv/bin/activate```\n", + "\n", + "-```cd Robyn/python```\n", + "\n", + "-```pip install -r requirements.txt```\n", + "\n", + "\n", + "Then import the necessary libraries. Make sure to define your paths below.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "5930e4b4", + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "eb8146e8", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-11-14 14:03:56,040 - robyn - INFO - Logging is set up to console only.\n", + "/Users/yijuilee/robynpy_release_reviews/robynvenv/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import os\n", + "import pandas as pd\n", + "import pyreadr\n", + "from typing import Dict\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "from robyn.modeling.model_executor import ModelExecutor\n", + "from robyn.modeling.entities.enums import NevergradAlgorithm, Models\n", + "from robyn.modeling.feature_engineering import FeatureEngineering" + ] + }, + { + "cell_type": "markdown", + "id": "442024b2", + "metadata": {}, + "source": [ + "## 2.1 Load Mock R data\n", + "\n", + "We need to set the base path for the data directory.\n", + "Create a .env file in the same directory as your notebook and put in define the path to the data dir.\n", + "for example: ROBYN_BASE_PATH=.../Robyn/R/data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "408ad24b", + "metadata": {}, + "outputs": [], + "source": [ + "# Read the simulated data and holidays data\n", + "dt_simulated_weekly = pd.read_csv(\"resources/dt_simulated_weekly.csv\")\n", + "\n", + "dt_prophet_holidays = pd.read_csv(\"resources/dt_prophet_holidays.csv\")" + ] + }, + { + "cell_type": "markdown", + "id": "54d0c5ac", + "metadata": {}, + "source": [ + "## Setup MMM Data\n", + "\n", + "We will now set up the MMM data specification which includes defining the dependent variable, independent variables, and the time window for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "223d0d0f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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DATErevenuetv_Sooh_Sprint_Sfacebook_Isearch_clicks_Psearch_Scompetitor_sales_Bfacebook_Seventsnewsletter
02015-11-232.754372e+0622358.3466670.012728.4888892.430128e+070.0000000.00000081250097607.132915na19401.653846
12015-11-302.584277e+0628613.4533330.00.0000005.527033e+069837.2384864133.33333379015491141.952450na14791.000000
22015-12-072.547387e+060.000000132278.4453.8666671.665159e+0712044.1196533786.66666783001974256.375378na14544.000000
32015-12-142.875220e+0683450.3066670.017680.0000001.054977e+0712268.0703194253.33333381228832800.490677na2800.000000
42015-12-212.215953e+060.000000277336.00.0000002.934090e+069467.2480233613.3333337105985689.582605na15478.000000
\n", + "
" + ], + "text/plain": [ + " DATE revenue tv_S ooh_S print_S \\\n", + "0 2015-11-23 2.754372e+06 22358.346667 0.0 12728.488889 \n", + "1 2015-11-30 2.584277e+06 28613.453333 0.0 0.000000 \n", + "2 2015-12-07 2.547387e+06 0.000000 132278.4 453.866667 \n", + "3 2015-12-14 2.875220e+06 83450.306667 0.0 17680.000000 \n", + "4 2015-12-21 2.215953e+06 0.000000 277336.0 0.000000 \n", + "\n", + " facebook_I search_clicks_P search_S competitor_sales_B \\\n", + "0 2.430128e+07 0.000000 0.000000 8125009 \n", + "1 5.527033e+06 9837.238486 4133.333333 7901549 \n", + "2 1.665159e+07 12044.119653 3786.666667 8300197 \n", + "3 1.054977e+07 12268.070319 4253.333333 8122883 \n", + "4 2.934090e+06 9467.248023 3613.333333 7105985 \n", + "\n", + " facebook_S events newsletter \n", + "0 7607.132915 na 19401.653846 \n", + "1 1141.952450 na 14791.000000 \n", + "2 4256.375378 na 14544.000000 \n", + "3 2800.490677 na 2800.000000 \n", + "4 689.582605 na 15478.000000 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def setup_mmm_data(dt_simulated_weekly) -> MMMData:\n", + "\n", + " mmm_data_spec = MMMData.MMMDataSpec(\n", + " dep_var=\"revenue\",\n", + " dep_var_type=\"revenue\",\n", + " date_var=\"DATE\",\n", + " context_vars=[\"competitor_sales_B\", \"events\"],\n", + " paid_media_spends=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_S\", \"search_S\"],\n", + " paid_media_vars=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_I\", \"search_clicks_P\"],\n", + " organic_vars=[\"newsletter\"],\n", + " window_start=\"2016-01-01\",\n", + " window_end=\"2018-12-31\",\n", + " factor_vars=[\"events\"],\n", + " )\n", + "\n", + " return MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec)\n", + "\n", + "\n", + "mmm_data = setup_mmm_data(dt_simulated_weekly)\n", + "mmm_data.data.head()" + ] + }, + { + "cell_type": "markdown", + "id": "ea1fa54e", + "metadata": {}, + "source": [ + "## Feature Preprocessing\n", + "\n", + "We will perform feature engineering to prepare the data for modeling. This includes transformations like adstock and other preprocessing steps." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "0d1d1118", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hyperparameters setup complete.\n" + ] + } + ], + "source": [ + "hyperparameters = Hyperparameters(\n", + " hyperparameters={\n", + " \"facebook_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"print_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"tv_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.3, 0.8],\n", + " ),\n", + " \"search_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"ooh_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"newsletter\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " },\n", + " adstock=AdstockType.GEOMETRIC,\n", + " lambda_=0.0,\n", + " train_size=[0.5, 0.8],\n", + ")\n", + "\n", + "print(\"Hyperparameters setup complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "948cceb8", + "metadata": {}, + "outputs": [], + "source": [ + "# Create HolidaysData object\n", + "holidays_data = HolidaysData(\n", + " dt_holidays=dt_prophet_holidays,\n", + " prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + " prophet_country=\"DE\",\n", + " prophet_signs=[\"default\", \"default\", \"default\"],\n", + ")\n", + "# Setup FeaturizedMMMData\n", + "feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "fbac563a", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-11-14 14:03:58,356 - robyn.modeling.feature_engineering - INFO - Starting feature engineering process\n", + "2024-11-14 14:03:58,359 - robyn.modeling.feature_engineering - INFO - Starting Prophet decomposition\n", + "2024-11-14 14:03:58,359 - robyn.modeling.feature_engineering - INFO - Starting Prophet decomposition\n", + "/Users/yijuilee/robynpy_release_reviews/robynvenv/lib/python3.9/site-packages/prophet/forecaster.py:187: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " self.holidays['ds'] = pd.to_datetime(self.holidays['ds'])\n", + "2024-11-14 14:03:59,094 - cmdstanpy - DEBUG - input tempfile: /var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpswsvpq2h/8wo33geu.json\n", + "2024-11-14 14:03:59,104 - cmdstanpy - DEBUG - input tempfile: /var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpswsvpq2h/oortjd4i.json\n", + "2024-11-14 14:03:59,105 - cmdstanpy - DEBUG - idx 0\n", + "2024-11-14 14:03:59,106 - cmdstanpy - DEBUG - running CmdStan, num_threads: None\n", + "2024-11-14 14:03:59,106 - cmdstanpy - DEBUG - CmdStan args: ['/Users/yijuilee/robynpy_release_reviews/robynvenv/lib/python3.9/site-packages/prophet/stan_model/prophet_model.bin', 'random', 'seed=54643', 'data', 'file=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpswsvpq2h/8wo33geu.json', 'init=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpswsvpq2h/oortjd4i.json', 'output', 'file=/var/folders/gm/g5cpl7110m96nfd1qr1xwnwc0000gn/T/tmpswsvpq2h/prophet_model3dpx7qk0/prophet_model-20241114140359.csv', 'method=optimize', 'algorithm=lbfgs', 'iter=10000']\n", + "14:03:59 - cmdstanpy - INFO - Chain [1] start processing\n", + "2024-11-14 14:03:59,106 - cmdstanpy - INFO - Chain [1] start processing\n", + "14:03:59 - cmdstanpy - INFO - Chain [1] done processing\n", + "2024-11-14 14:03:59,169 - cmdstanpy - INFO - Chain [1] done processing\n", + "2024-11-14 14:03:59,240 - robyn.modeling.feature_engineering - INFO - Prophet decomposition complete\n", + "2024-11-14 14:03:59,242 - robyn.modeling.feature_engineering - INFO - Starting model runs for paid media variables with different exposure metrics\n", + "2024-11-14 14:03:59,242 - robyn.modeling.feature_engineering - INFO - Fitting spend-exposure model for facebook_I\n", + "2024-11-14 14:03:59,260 - robyn.modeling.feature_engineering - INFO - Fitting spend-exposure model for search_clicks_P\n", + "2024-11-14 14:03:59,270 - robyn.modeling.feature_engineering - INFO - Completed model runs for 2 channels\n", + "2024-11-14 14:03:59,271 - robyn.modeling.feature_engineering - INFO - Feature engineering complete\n", + "/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/robyn/modeling/feature_engineering.py:82: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", + " dt_mod = dt_mod.fillna(method=\"ffill\").fillna(method=\"bfill\")\n", + "2024-11-14 14:03:59,289 - robyn.modeling.feature_engineering - INFO - Filled 0 missing values\n" + ] + } + ], + "source": [ + "# Setup FeaturizedMMMData\n", + "featurized_mmm_data = feature_engineering.perform_feature_engineering()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1be81245", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-11-14 14:03:59,338 - robyn.visualization.feature_visualization - INFO - Initializing FeaturePlotter\n", + "2024-11-14 14:03:59,339 - robyn.visualization.feature_visualization - INFO - Generating spend-exposure plot for channel: facebook_I\n", + "2024-11-14 14:03:59,506 - robyn.visualization.feature_visualization - INFO - Successfully generated spend-exposure plot for channel facebook_I\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-11-14 14:03:59,604 - robyn.visualization.feature_visualization - INFO - Generating spend-exposure plot for channel: search_clicks_P\n", + "2024-11-14 14:03:59,767 - robyn.visualization.feature_visualization - INFO - Successfully generated spend-exposure plot for channel search_clicks_P\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.visualization.feature_visualization import FeaturePlotter\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "# Create a FeaturePlotter instance\n", + "feature_plotter = FeaturePlotter(mmm_data, hyperparameters)\n", + "# Extract the list of results\n", + "results_list = featurized_mmm_data.modNLS[\"results\"]\n", + "# Plot spend-exposure relationship for each channel in the results\n", + "for result in results_list:\n", + " channel = result[\"channel\"]\n", + " try:\n", + " fig = feature_plotter.plot_spend_exposure(featurized_mmm_data, channel)\n", + " plt.show()\n", + " except ValueError as e:\n", + " print(f\"Skipping {channel}: {str(e)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "33b864e2", + "metadata": {}, + "outputs": [], + "source": [ + "from utils.data_mapper import load_data_from_json, import_input_collect\n", + "\n", + "# Load data from JSON exported from R\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Feature_InputCollect.json\"\n", + ")\n", + "\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "\n", + "# Extract individual components\n", + "r_mmm_data = r_input_collect[\"mmm_data\"]\n", + "r_featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "r_holidays_data = r_input_collect[\"holidays_data\"]\n", + "r_hyperparameters = r_input_collect[\"hyperparameters\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "1601822d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0. 1272202.89877032 447056.27859032]\n", + "[ 0. 1272202.89877032 447232.65809817]\n" + ] + } + ], + "source": [ + "print(featurized_mmm_data.dt_mod[\"events\"].unique())\n", + "\n", + "print(r_featurized_mmm_data.dt_mod[\"events\"].unique())" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "695db7bb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " trend season holiday events\n", + "count 2.080000e+02 2.080000e+02 2.080000e+02 2.080000e+02\n", + "mean 1.772974e+06 -4.203860e+03 4.491105e+04 8.265669e+03\n", + "std 2.839704e+04 6.756266e+05 1.790185e+05 9.335788e+04\n", + "min 1.715494e+06 -1.050359e+06 -3.372642e+05 0.000000e+00\n", + "25% 1.748984e+06 -6.738105e+05 0.000000e+00 0.000000e+00\n", + "50% 1.774054e+06 -5.964066e+04 0.000000e+00 0.000000e+00\n", + "75% 1.798442e+06 6.469059e+05 0.000000e+00 0.000000e+00\n", + "max 1.814898e+06 1.218389e+06 1.054990e+06 1.272203e+06\n", + " trend season holiday events\n", + "count 2.080000e+02 2.080000e+02 2.080000e+02 2.080000e+02\n", + "mean 1.773156e+06 -4.203883e+03 4.493476e+04 8.266517e+03\n", + "std 2.839524e+04 6.756344e+05 1.790962e+05 9.336189e+04\n", + "min 1.715453e+06 -1.050414e+06 -3.374564e+05 0.000000e+00\n", + "25% 1.749216e+06 -6.738250e+05 0.000000e+00 0.000000e+00\n", + "50% 1.774229e+06 -5.961828e+04 0.000000e+00 0.000000e+00\n", + "75% 1.798672e+06 6.468962e+05 0.000000e+00 0.000000e+00\n", + "max 1.815024e+06 1.218388e+06 1.055051e+06 1.272203e+06\n", + "All statistics are within the specified tolerance.\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Assuming featurized_mmm_data and r_featurized_mmm_data are your DataFrames\n", + "# and they have been defined and populated with data\n", + "# Calculate descriptive statistics for both DataFrames\n", + "python_stats = featurized_mmm_data.dt_mod[\n", + " [\"trend\", \"season\", \"holiday\", \"events\"]\n", + "].describe()\n", + "r_stats = r_featurized_mmm_data.dt_mod[\n", + " [\"trend\", \"season\", \"holiday\", \"events\"]\n", + "].describe()\n", + "print(python_stats)\n", + "print(r_stats)\n", + "# Define a tolerance level for comparison\n", + "tolerance = 1000\n", + "\n", + "\n", + "# Function to compare two DataFrames\n", + "def compare_stats(python_stats: pd.DataFrame, r_stats: pd.DataFrame, tolerance: float):\n", + " # Iterate over each column and statistic\n", + " for column in python_stats.columns:\n", + " for stat in python_stats.index:\n", + " python_value = python_stats.loc[stat, column]\n", + " r_value = r_stats.loc[stat, column]\n", + " # Assert that the values are within the specified tolerance\n", + " assert abs(python_value - r_value) <= tolerance, (\n", + " f\"Difference in {stat} for {column} exceeds tolerance: \"\n", + " f\"Python value = {python_value}, R value = {r_value}\"\n", + " )\n", + "\n", + "\n", + "# Compare the statistics\n", + "compare_stats(python_stats, r_stats, tolerance)\n", + "print(\"All statistics are within the specified tolerance.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "bc55ff39", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0. 1272202.89877032]\n", + "[ 0. 1272202.89877032]\n" + ] + } + ], + "source": [ + "print(featurized_mmm_data.dt_modRollWind[\"events\"].unique())\n", + "\n", + "print(r_featurized_mmm_data.dt_modRollWind[\"events\"].unique())" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "27318df8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape of 'yhat' from modNLS1: (628, 6)\n", + "Preview of 'yhat' from modNLS1:\n", + " x y yhat channel models ds\n", + "0 3623.012233 1.371590e+07 1.404919e+07 facebook_I nls 2016-01-04\n", + "1 4129.816153 1.885156e+07 1.595491e+07 facebook_I nls 2016-01-11\n", + "2 3623.012233 1.191019e+07 1.404919e+07 facebook_I nls 2016-01-18\n", + "3 3002.690585 1.062042e+07 1.169716e+07 facebook_I nls 2016-01-25\n", + "4 0.000000 0.000000e+00 0.000000e+00 facebook_I nls 2016-02-01\n", + "\n", + "Shape of 'yhat' from modNLS2: (628, 6)\n", + "Preview of 'yhat' from modNLS2:\n", + " channel y x models yhat ds\n", + "0 facebook_I 1.371590e+07 3623.0122 nls 1.362829e+07 2016-01-04\n", + "1 facebook_I 1.371590e+07 3623.0122 lm 1.362829e+07 2016-01-11\n", + "2 facebook_I 1.885156e+07 4129.8162 nls 1.553468e+07 2016-01-18\n", + "3 facebook_I 1.885156e+07 4129.8162 lm 1.553468e+07 2016-01-25\n", + "4 facebook_I 1.191019e+07 3623.0122 nls 1.362829e+07 2016-02-01\n", + "\n", + "Description of 'yhat' from modNLS1:\n", + " x y yhat ds\n", + "count 628.000000 6.280000e+02 6.280000e+02 628\n", + "mean 3643.433191 4.094398e+06 4.057864e+06 2017-07-03 00:00:00\n", + "min 0.000000 0.000000e+00 0.000000e+00 2016-01-04 00:00:00\n", + "25% 0.000000 0.000000e+00 0.000000e+00 2016-10-03 00:00:00\n", + "50% 2786.666667 1.216576e+04 1.198107e+04 2017-07-03 00:00:00\n", + "75% 5586.666667 5.218813e+04 4.762294e+04 2018-04-02 00:00:00\n", + "max 17146.666667 4.866198e+07 5.011075e+07 2018-12-31 00:00:00\n", + "std 3914.957323 8.843079e+06 8.794932e+06 NaN\n", + "\n", + "Description of 'yhat' from modNLS2:\n", + " y x yhat\n", + "count 6.280000e+02 628.000000 6.280000e+02\n", + "mean 4.094398e+06 3643.433191 4.009451e+06\n", + "std 8.843079e+06 3914.957321 8.813852e+06\n", + "min 0.000000e+00 0.000000 0.000000e+00\n", + "25% 0.000000e+00 0.000000 0.000000e+00\n", + "50% 1.216576e+04 2786.666700 1.171085e+04\n", + "75% 5.218813e+04 5586.666700 4.873835e+04\n", + "max 4.866198e+07 17146.666700 5.228846e+07\n" + ] + } + ], + "source": [ + "# Convert 'yhat' lists to DataFrames for comparison\n", + "yhat1_df = pd.DataFrame(featurized_mmm_data.modNLS[\"yhat\"])\n", + "yhat2_df = pd.DataFrame(r_featurized_mmm_data.modNLS[\"yhat\"])\n", + "\n", + "# Print the shape and a quick preview of 'yhat' DataFrames\n", + "print(\"Shape of 'yhat' from modNLS1:\", yhat1_df.shape)\n", + "print(\"Preview of 'yhat' from modNLS1:\")\n", + "print(yhat1_df.head())\n", + "\n", + "print(\"\\nShape of 'yhat' from modNLS2:\", yhat2_df.shape)\n", + "print(\"Preview of 'yhat' from modNLS2:\")\n", + "print(yhat2_df.head())\n", + "\n", + "# Describe the numeric columns to compare distributions\n", + "print(\"\\nDescription of 'yhat' from modNLS1:\")\n", + "print(yhat1_df.describe())\n", + "\n", + "print(\"\\nDescription of 'yhat' from modNLS2:\")\n", + "print(yhat2_df.describe())" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "310fadad", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Channels in modNLS1: ['facebook_I', 'search_clicks_P']\n", + "Channels in modNLS2: ['facebook_I', 'search_clicks_P']\n", + "\n", + "Structure of 'results' in modNLS1:\n", + "{'channel': 'facebook_I', 'model_type': 'nls', 'Vmax': 526584669.26527345, 'Km': 132172.89890426732, 'aic_nls': np.float64(-63.03286895577898), 'aic_lm': np.float64(-65.13153318475403), 'bic_nls': np.float64(-56.920377345082365), 'bic_lm': np.float64(-62.07528737940572), 'rsq_nls': np.float64(0.9813499753637182), 'rsq_lm': np.float64(0.9804068584994678), 'coef_lm': 3761.5919579945594, 'rsq': np.float64(0.9813499753637182)}\n", + "{'channel': 'search_clicks_P', 'model_type': 'nls', 'Vmax': 805350.7410810068, 'Km': 272820.351177426, 'aic_nls': np.float64(-36.82819579713845), 'aic_lm': np.float64(-38.85764187253047), 'bic_nls': np.float64(-30.715704186441833), 'bic_lm': np.float64(-35.80139606718217), 'rsq_nls': np.float64(0.9671527949952451), 'rsq_lm': np.float64(0.9666656067125566), 'coef_lm': 2.8424388952904276, 'rsq': np.float64(0.9671527949952451)}\n", + "\n", + "Structure of 'results' in modNLS2:\n", + "{'channel': 'facebook_I', 'Vmax': 526584613.89144605, 'Km': 132172.88416270798, 'aic_nls': 4919.796321898356, 'aic_lm': 4925.541463325076, 'bic_nls': 4928.965059314401, 'bic_lm': 4931.653954935772, 'rsq_nls': 0.9813499752588166, 'rsq_lm': 0.9872272725551, 'coef_lm': 3761.591959740263}\n", + "{'channel': 'search_clicks_P', 'Vmax': 805351.3854787427, 'Km': 272820.57777331315, 'aic_nls': 2862.7294769239734, 'aic_lm': 2863.0409938566836, 'bic_nls': 2871.8982143400185, 'bic_lm': 2869.15348546738, 'rsq_nls': 0.9671527952260608, 'rsq_lm': 0.9867200734795085, 'coef_lm': 2.8424388960432783}\n", + "Preview of 'yhat' from modNLS1:\n", + " x y yhat channel models ds\n", + "0 3623.012233 1.371590e+07 1.404919e+07 facebook_I nls 2016-01-04\n", + "1 3623.012233 1.371590e+07 1.404919e+07 facebook_I lm 2016-01-04\n", + "2 3706.666667 1.209650e+04 1.079521e+04 search_clicks_P nls 2016-01-04\n", + "3 3706.666667 1.209650e+04 1.079521e+04 search_clicks_P lm 2016-01-04\n", + "4 4129.816153 1.885156e+07 1.595491e+07 facebook_I nls 2016-01-11\n", + "\n", + "Preview of 'yhat' from modNLS2:\n", + " channel y x models yhat ds\n", + "0 facebook_I 1.371590e+07 3623.0122 nls 1.362829e+07 2016-01-04\n", + "1 facebook_I 2.503921e+07 6650.1138 lm 2.501501e+07 2016-01-04\n", + "2 search_clicks_P 1.209650e+04 3706.6667 nls 1.053597e+04 2016-01-04\n", + "3 search_clicks_P 1.264816e+04 3786.6667 lm 1.076337e+04 2016-01-04\n", + "4 facebook_I 1.371590e+07 3623.0122 lm 1.362829e+07 2016-01-11\n", + "All comparisons passed within the specified tolerance.\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "\n", + "def compare_modNLS(modNLS1, modNLS2, tolerance=1e-1, percent_tolerance=5):\n", + " # Print available channels for debugging\n", + " channels1 = [result[\"channel\"] for result in modNLS1[\"results\"]]\n", + " channels2 = [result[\"channel\"] for result in modNLS2[\"results\"]]\n", + " print(\"Channels in modNLS1:\", channels1)\n", + " print(\"Channels in modNLS2:\", channels2)\n", + "\n", + " # Print the structure of 'results' for debugging\n", + " print(\"\\nStructure of 'results' in modNLS1:\")\n", + " for result in modNLS1[\"results\"]:\n", + " print(result)\n", + "\n", + " print(\"\\nStructure of 'results' in modNLS2:\")\n", + " for result in modNLS2[\"results\"]:\n", + " print(result)\n", + "\n", + " # Compare 'results' section\n", + " for result1 in modNLS1[\"results\"]:\n", + " channel = result1[\"channel\"]\n", + " result2 = next((r for r in modNLS2[\"results\"] if r[\"channel\"] == channel), None)\n", + " assert result2 is not None, f\"Channel {channel} not found in second modNLS\"\n", + "\n", + " # Compare R-squared values separately\n", + " assert np.isclose(\n", + " result1[\"rsq_nls\"], result2[\"rsq_nls\"], atol=tolerance\n", + " ), f\"R-squared (NLS) mismatch for {channel}: {result1['rsq_nls']} vs {result2['rsq_nls']}\"\n", + "\n", + " assert np.isclose(\n", + " result1[\"rsq_lm\"], result2[\"rsq_lm\"], atol=tolerance\n", + " ), f\"R-squared (LM) mismatch for {channel}: {result1['rsq_lm']} vs {result2['rsq_lm']}\"\n", + "\n", + " # Compare coefficients\n", + " for coef_key in [\"Vmax\", \"Km\", \"coef_lm\"]:\n", + " coef_value1 = result1.get(coef_key)\n", + " coef_value2 = result2.get(coef_key)\n", + " assert (\n", + " coef_value2 is not None\n", + " ), f\"Coefficient {coef_key} not found for {channel}\"\n", + " assert np.isclose(\n", + " coef_value1, coef_value2, atol=tolerance\n", + " ), f\"Coefficient {coef_key} mismatch for {channel}: {coef_value1} vs {coef_value2}\"\n", + "\n", + " # Convert 'yhat' lists to DataFrames for comparison\n", + " yhat1_df = (\n", + " pd.DataFrame(modNLS1[\"yhat\"])\n", + " .sort_values(by=[\"ds\", \"channel\"])\n", + " .reset_index(drop=True)\n", + " )\n", + " yhat2_df = (\n", + " pd.DataFrame(modNLS2[\"yhat\"])\n", + " .sort_values(by=[\"ds\", \"channel\"])\n", + " .reset_index(drop=True)\n", + " )\n", + "\n", + " # Print preview of 'yhat' DataFrames\n", + " print(\"Preview of 'yhat' from modNLS1:\")\n", + " print(yhat1_df.head())\n", + " print(\"\\nPreview of 'yhat' from modNLS2:\")\n", + " print(yhat2_df.head())\n", + "\n", + " # Compare 'yhat' DataFrame\n", + " assert yhat1_df.shape == yhat2_df.shape, \"Shape mismatch in 'yhat' DataFrame\"\n", + "\n", + " # Select only numeric columns for comparison\n", + " numeric_cols = yhat1_df.select_dtypes(include=[np.number]).columns\n", + "\n", + " # Use describe to get summary statistics\n", + " desc1 = yhat1_df[numeric_cols].describe()\n", + " desc2 = yhat2_df[numeric_cols].describe()\n", + "\n", + " # Compare each statistic separately\n", + " for stat in desc1.index:\n", + " for col in numeric_cols:\n", + " val1 = desc1.at[stat, col]\n", + " val2 = desc2.at[stat, col]\n", + " if not np.isclose(val1, val2, rtol=percent_tolerance):\n", + " print(f\"Mismatch in {stat} of column '{col}': {val1} vs {val2}\")\n", + " raise AssertionError(f\"Mismatch in {stat} of column '{col}'\")\n", + "\n", + " print(\"All comparisons passed within the specified tolerance.\")\n", + "\n", + "\n", + "# Example usage\n", + "compare_modNLS(featurized_mmm_data.modNLS, r_featurized_mmm_data.modNLS)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "e039a32c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dict_keys(['results', 'yhat', 'plots'])\n", + "\n", + "Key: results\n", + "Type: \n", + "Number of items: 2\n", + "Sample item: {'channel': 'facebook_I', 'model_type': 'nls', 'Vmax': 526584669.26527345, 'Km': 132172.89890426732, 'aic_nls': np.float64(-63.03286895577898), 'aic_lm': np.float64(-65.13153318475403), 'bic_nls': np.float64(-56.920377345082365), 'bic_lm': np.float64(-62.07528737940572), 'rsq_nls': np.float64(0.9813499753637182), 'rsq_lm': np.float64(0.9804068584994678), 'coef_lm': 3761.5919579945594, 'rsq': np.float64(0.9813499753637182)}\n", + "\n", + "Key: yhat\n", + "Type: \n", + "Number of items: 628\n", + "Sample item: {'x': 3623.01223287033, 'y': 13715898.6058832, 'yhat': 14049191.042750835, 'channel': 'facebook_I', 'models': 'nls', 'ds': Timestamp('2016-01-04 00:00:00')}\n", + "\n", + "Key: plots\n", + "Type: \n", + "Sample keys: ['facebook_I', 'search_clicks_P']\n", + "Sample item: spend exposure yhat\n", + "6 3623.012233 1.371590e+07 1.404919e+07\n", + "7 4129.816153 1.885156e+07 1.595491e+07\n", + "8 3623.012233 1.191019e+07 1.404919e+07\n", + "9 3002.690585 1.062042e+07 1.169716e+07\n", + "10 0.000000 0.000000e+00 0.000000e+00\n", + ".. ... ... ...\n", + "158 0.000000 0.000000e+00 0.000000e+00\n", + "159 0.000000 0.000000e+00 0.000000e+00\n", + "160 0.000000 0.000000e+00 0.000000e+00\n", + "161 9068.007406 3.220052e+07 3.380801e+07\n", + "162 0.000000 0.000000e+00 0.000000e+00\n", + "\n", + "[157 rows x 3 columns]\n" + ] + } + ], + "source": [ + "print(featurized_mmm_data.modNLS.keys())\n", + "\n", + "for key in featurized_mmm_data.modNLS:\n", + " print(f\"\\nKey: {key}\")\n", + " print(f\"Type: {type(featurized_mmm_data.modNLS[key])}\")\n", + " if isinstance(featurized_mmm_data.modNLS[key], list):\n", + " print(f\"Number of items: {len(featurized_mmm_data.modNLS[key])}\")\n", + " if len(featurized_mmm_data.modNLS[key]) > 0:\n", + " print(\"Sample item:\", featurized_mmm_data.modNLS[key][0])\n", + " elif isinstance(featurized_mmm_data.modNLS[key], dict):\n", + " print(\"Sample keys:\", list(featurized_mmm_data.modNLS[key].keys()))\n", + " if len(featurized_mmm_data.modNLS[key]) > 0:\n", + " first_key = next(iter(featurized_mmm_data.modNLS[key]))\n", + " print(\"Sample item:\", featurized_mmm_data.modNLS[key][first_key])\n", + " else:\n", + " print(\"Value:\", featurized_mmm_data.modNLS[key])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "6c6d3f4c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "No data found for channel facebook_S.\n" + ] + } + ], + "source": [ + "channel_name = \"facebook_S\" # Example channel name\n", + "results = featurized_mmm_data.modNLS.get(\"results\", [])\n", + "channel_data = next((item for item in results if item[\"channel\"] == channel_name), None)\n", + "if channel_data:\n", + " print(f\"\\nData for channel {channel_name}:\")\n", + " print(channel_data)\n", + "else:\n", + " print(f\"No data found for channel {channel_name}.\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/python/tests/component_tutorials/tutorial3_modeling.ipynb b/python/tests/component_tutorials/tutorial3_modeling.ipynb new file mode 100644 index 000000000..579507e6b --- /dev/null +++ b/python/tests/component_tutorials/tutorial3_modeling.ipynb @@ -0,0 +1,475 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Robyn: Marketing Mix Modeling Application\n", + "\n", + "This notebook demonstrates the usage of Robyn, a Marketing Mix Modeling (MMM) application. \n", + "We'll go through the main steps of performing robyn_inputs and robyn_engineering.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1. Import Required Libraries. Define Paths.\n", + "\n", + "First, be sure to setup your virtual environment. Be sure to switch over to your new environment in this notebook. \n", + "\n", + "-```cd {root_folder}```\n", + "\n", + "-```python3 -m yourvenv```\n", + "\n", + "-```source yourvenv/bin/activate```\n", + "\n", + "-```cd Robyn/python```\n", + "\n", + "-```pip install -r requirements.txt```\n", + "\n", + "\n", + "Then import the necessary libraries. Make sure to define your paths below.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pandas as pd\n", + "import pyreadr\n", + "from typing import Dict\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "from robyn.modeling.model_executor import ModelExecutor\n", + "from robyn.modeling.entities.enums import NevergradAlgorithm, Models\n", + "from robyn.modeling.feature_engineering import FeatureEngineering" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.1 Load Mock R data\n", + "\n", + "We need to set the base path for the data directory.\n", + "Create a .env file in the same directory as your notebook and put in define the path to the data dir.\n", + "for example: ROBYN_BASE_PATH=.../Robyn/R/data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the simulated data and holidays data\n", + "dt_simulated_weekly = pd.read_csv(\"resources/dt_simulated_weekly.csv\")\n", + "\n", + "dt_prophet_holidays = pd.read_csv(\"resources/dt_prophet_holidays.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup MMM Data\n", + "\n", + "We will now set up the MMM data specification which includes defining the dependent variable, independent variables, and the time window for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def setup_mmm_data(dt_simulated_weekly) -> MMMData:\n", + "\n", + " mmm_data_spec = MMMData.MMMDataSpec(\n", + " dep_var=\"revenue\",\n", + " dep_var_type=\"revenue\",\n", + " date_var=\"DATE\",\n", + " context_vars=[\"competitor_sales_B\", \"events\"],\n", + " paid_media_spends=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_S\", \"search_S\"],\n", + " paid_media_vars=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_I\", \"search_clicks_P\"],\n", + " organic_vars=[\"newsletter\"],\n", + " window_start=\"2016-01-01\",\n", + " window_end=\"2018-12-31\",\n", + " )\n", + "\n", + " return MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec)\n", + "\n", + "\n", + "mmm_data = setup_mmm_data(dt_simulated_weekly)\n", + "mmm_data.data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Preprocessing\n", + "\n", + "We will perform feature engineering to prepare the data for modeling. This includes transformations like adstock and other preprocessing steps." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "hyperparameters = Hyperparameters(\n", + " hyperparameters={\n", + " \"facebook_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"print_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"tv_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.3, 0.8],\n", + " ),\n", + " \"search_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"ooh_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"newsletter\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " },\n", + " adstock=AdstockType.GEOMETRIC,\n", + " lambda_=0.0,\n", + " train_size=[0.5, 0.8],\n", + ")\n", + "\n", + "print(\"Hyperparameters setup complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create HolidaysData object\n", + "holidays_data = HolidaysData(\n", + " dt_holidays=dt_prophet_holidays,\n", + " prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + " prophet_country=\"DE\",\n", + " prophet_signs=[\"default\", \"default\", \"default\"],\n", + ")\n", + "# Setup FeaturizedMMMData\n", + "feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "featurized_mmm_data = feature_engineering.perform_feature_engineering()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.visualization.feature_visualization import FeaturePlotter\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Create a FeaturePlotter instance\n", + "feature_plotter = FeaturePlotter(mmm_data, hyperparameters)\n", + "\n", + "# Plot spend-exposure relationship for each channel\n", + "for channel in mmm_data.mmmdata_spec.paid_media_spends:\n", + " try:\n", + " fig = feature_plotter.plot_spend_exposure(featurized_mmm_data, channel)\n", + " plt.show()\n", + " except ValueError as e:\n", + " print(f\"Skipping {channel}: {str(e)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Setup ModelExecutor\n", + "model_executor = ModelExecutor(\n", + " mmmdata=mmm_data,\n", + " holidays_data=holidays_data,\n", + " hyperparameters=hyperparameters,\n", + " calibration_input=None, # Add calibration input if available\n", + " featurized_mmm_data=featurized_mmm_data,\n", + ")\n", + "\n", + "# Setup TrialsConfig\n", + "trials_config = TrialsConfig(\n", + " iterations=2000, trials=5\n", + ") # Set to the number of cores you want to use\n", + "\n", + "print(\n", + " f\">>> Starting {trials_config.trials} trials with {trials_config.iterations} iterations each using {NevergradAlgorithm.TWO_POINTS_DE.value} nevergrad algorithm on x cores...\"\n", + ")\n", + "\n", + "# Run the model\n", + "\n", + "output_models = model_executor.model_run(\n", + " trials_config=trials_config,\n", + " ts_validation=False, # changed from True to False -> deacitvate\n", + " add_penalty_factor=False,\n", + " rssd_zero_penalty=True,\n", + " cores=8,\n", + " nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE,\n", + " intercept=True,\n", + " intercept_sign=\"non_negative\",\n", + " model_name=Models.RIDGE,\n", + ")\n", + "print(\"Model training complete.\")\n", + "\n", + "# TODO fix graph outputs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming model_outputs.trials[0] is already an object from your model\n", + "trial = output_models.trials[0]\n", + "\n", + "\n", + "# Function to check if an object has a 'shape' attribute\n", + "def has_shape(obj):\n", + " return hasattr(obj, \"shape\")\n", + "\n", + "\n", + "# Get all attribute names of the object and print their shapes if they have a 'shape' attribute\n", + "attribute_names = [\n", + " attr\n", + " for attr in dir(trial)\n", + " if not callable(getattr(trial, attr)) and not attr.startswith(\"__\")\n", + "]\n", + "for attribute_name in attribute_names:\n", + " attribute_value = getattr(trial, attribute_name)\n", + " if has_shape(attribute_value):\n", + " print(f\"{attribute_name}: Shape = {attribute_value.shape}\")\n", + " else:\n", + " print(\n", + " f\"{attribute_name}: No shape attribute, Type = {type(attribute_value).__name__}\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming model_outputs.trials[0] is already an object from your model\n", + "trial = output_models.trials[0]\n", + "\n", + "\n", + "# Function to check if an object has a 'shape' attribute\n", + "def has_shape(obj):\n", + " return hasattr(obj, \"shape\")\n", + "\n", + "\n", + "# Get all attribute names of the object and print their shapes if they have a 'shape' attribute\n", + "attribute_names = [\n", + " attr\n", + " for attr in dir(trial)\n", + " if not callable(getattr(trial, attr)) and not attr.startswith(\"__\")\n", + "]\n", + "for attribute_name in attribute_names:\n", + " attribute_value = getattr(trial, attribute_name)\n", + " if has_shape(attribute_value):\n", + " print(f\"{attribute_name}: Shape = {attribute_value.shape}\")\n", + " # Check if the attribute is a multi-dimensional array with more than one column\n", + " if len(attribute_value.shape) > 1 and attribute_value.shape[1] > 1:\n", + " try:\n", + " # Attempt to print column names if it's a structured array or DataFrame\n", + " columns = (\n", + " attribute_value.columns\n", + " if hasattr(attribute_value, \"columns\")\n", + " else attribute_value.dtype.names\n", + " )\n", + " print(f\" Columns: {columns}\")\n", + " except AttributeError:\n", + " print(\" No column names available.\")\n", + " else:\n", + " print(\n", + " f\"{attribute_name}: No shape attribute, Type = {type(attribute_value).__name__}\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "best_model_id = output_models.select_id\n", + "print(f\"Best model ID: {best_model_id}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from IPython.display import Image, display\n", + "import base64\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "\n", + "\n", + "# 1. Display the MOO Distribution Plot\n", + "if \"moo_distrb_plot\" in output_models.convergence:\n", + " moo_distrb_plot = output_models.convergence[\"moo_distrb_plot\"]\n", + " display(Image(data=base64.b64decode(moo_distrb_plot)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 2. Display the MOO Cloud Plot\n", + "if \"moo_cloud_plot\" in output_models.convergence:\n", + " moo_cloud_plot = output_models.convergence[\"moo_cloud_plot\"]\n", + " display(Image(data=base64.b64decode(moo_cloud_plot)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 3. Print convergence messages\n", + "if \"conv_msg\" in output_models.convergence:\n", + " for msg in output_models.convergence[\"conv_msg\"]:\n", + " print(msg)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 4. Display time series validation and convergence plots\n", + "if \"ts_validation_plot\" in output_models.convergence:\n", + " ts_validation_plot = output_models.convergence[\"ts_validation_plot\"]\n", + " display(Image(data=base64.b64decode(ts_validation_plot)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "best_model_id = output_models.select_id\n", + "print(f\"Best model ID: {best_model_id}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from utils.data_mapper import (\n", + " load_data_from_json,\n", + " import_input_collect,\n", + " import_output_models,\n", + ")\n", + "\n", + "# Load data from JSON exported from R\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_InputCollect.json\"\n", + ")\n", + "raw_output_models = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Pareto_OutputModels.json\"\n", + ")\n", + "\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "r_output_models = import_output_models(raw_output_models)\n", + "\n", + "# Extract individual components\n", + "r_mmm_data = r_input_collect[\"mmm_data\"]\n", + "r_featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "r_holidays_data = r_input_collect[\"holidays_data\"]\n", + "r_hyperparameters = r_input_collect[\"hyperparameters\"]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mytestenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/tutorial4_pareto.ipynb b/python/tests/component_tutorials/tutorial4_pareto.ipynb new file mode 100644 index 000000000..71baabe55 --- /dev/null +++ b/python/tests/component_tutorials/tutorial4_pareto.ipynb @@ -0,0 +1,190 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test Pareto Optimizer\n", + "import sys\n", + "\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")\n", + "\n", + "import pandas as pd\n", + "import json\n", + "from typing import Dict, Any, List\n", + "import numpy as np\n", + "from datetime import datetime, timedelta\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.modeling.entities.modeloutputs import ModelOutputs, Trial\n", + "from robyn.modeling.pareto.pareto_optimizer import ParetoOptimizer\n", + "from robyn.data.entities.enums import (\n", + " DependentVarType,\n", + " PaidMediaSigns,\n", + " OrganicSigns,\n", + " ContextSigns,\n", + ")\n", + "\n", + "from robyn.tutorials.utils.data_mapper import (\n", + " import_output_models,\n", + " import_input_collect,\n", + " load_data_from_json,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load data from JSON\n", + "inputCollect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_Pareto_2000_iterations_5_trials_InputCollect.json\"\n", + ")\n", + "outputModel = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_Pareto_2000_iterations_5_trials_OutputModels.json\"\n", + ")\n", + "input_collect = import_input_collect(inputCollect)\n", + "model_outputs = import_output_models(outputModel)\n", + "display((model_outputs.hyper_bound_ng))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mmm_data = input_collect[\"mmm_data\"]\n", + "# display(mmm_data.data.head())\n", + "# Display Model Outputs\n", + "\n", + "model_outputs = model_outputs\n", + "# display((model_outputs.trials[0].result_hyp_param))\n", + "\n", + "hyperparameters = input_collect[\"hyperparameters\"]\n", + "# display(hyperparameters)\n", + "\n", + "featurized_mmm_data = input_collect[\"featurized_mmm_data\"]\n", + "\n", + "holidays_data = input_collect[\"holidays_data\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 3. Create ParetoOptimizer instance\n", + "pareto_optimizer = ParetoOptimizer(\n", + " mmm_data, model_outputs, hyperparameters, featurized_mmm_data, holidays_data\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 4. Run optimize function\n", + "pareto_result = pareto_optimizer.optimize(pareto_fronts=\"auto\", min_candidates=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 5. Check results\n", + "print(\"Pareto Optimization Results:\")\n", + "print(f\"Number of Pareto fronts: {pareto_result.pareto_solutions}\")\n", + "print(\n", + " f\"MediaVecCollect: {pareto_result.media_vec_collect.shape, pareto_result.media_vec_collect}\"\n", + ")\n", + "print(\"\\Hyper parameter solutions:\")\n", + "print(pareto_result.result_hyp_param)\n", + "\n", + "print(\"\\nAggregated decomposition results:\")\n", + "print(pareto_result.x_decomp_agg)\n", + "print(\"\\result Calibration:\")\n", + "print(pareto_result.result_calibration)\n", + "print(\"\\nx Decomp Vec Collect:\")\n", + "print(pareto_result.x_decomp_vec_collect.shape, pareto_result.x_decomp_vec_collect)\n", + "print(\"\\nCarryover percentage all:\")\n", + "print(pareto_result.df_caov_pct_all.shape, pareto_result.df_caov_pct_all)\n", + "print(\"\\Plot Data Collected\")\n", + "# print(\"NUMBER OF PLOTS Data collected for:\", len(pareto_result.plot_data_collect[\"3_206_6\"]))\n", + "# print(\"Plot data for solid 3_206_6\", pareto_result.plot_data_collect[\"3_206_6\"])\n", + "\n", + "# 6. Validate logic\n", + "assert pareto_result.pareto_fronts == \"auto\" or isinstance(\n", + " pareto_result.pareto_fronts, int\n", + "), \"Invalid pareto_fronts value\"\n", + "assert not pareto_result.result_hyp_param.empty, \"Empty result_hyp_param DataFrame\"\n", + "assert not pareto_result.x_decomp_agg.empty, \"Empty x_decomp_agg DataFrame\"\n", + "\n", + "print(\"\\nAll assertions passed. The optimize function is working as expected.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(pareto_result.x_decomp_agg[pareto_result.x_decomp_agg[\"sol_id\"] == \"5_221_9\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Only export this to a pickle file if you plan to use the results and the mmm_data in another notebook" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pickle\n", + "\n", + "with open(\"pareto_result.pkl\", \"wb\") as f:\n", + " pickle.dump(pareto_result, f)\n", + "with open(\"mmmdata.pkl\", \"wb\") as f:\n", + " pickle.dump(mmm_data, f)\n", + "with open(\"holidays_data.pkl\", \"wb\") as f:\n", + " pickle.dump(holidays_data, f)\n", + "with open(\"featurized_mmm.pkl\", \"wb\") as f:\n", + " pickle.dump(featurized_mmm_data, f)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.15" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/tutorial5_calibration.ipynb b/python/tests/component_tutorials/tutorial5_calibration.ipynb new file mode 100644 index 000000000..f7d812b75 --- /dev/null +++ b/python/tests/component_tutorials/tutorial5_calibration.ipynb @@ -0,0 +1,1300 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Robyn: Marketing Mix Modeling Application\n", + "\n", + "This notebook demonstrates the usage of Robyn, a Marketing Mix Modeling (MMM) application. \n", + "We'll go through the main steps of performing robyn_inputs and robyn_engineering.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1. Import Required Libraries. Define Paths.\n", + "\n", + "First, be sure to setup your virtual environment. Be sure to switch over to your new environment in this notebook. \n", + "\n", + "-```cd {root_folder}```\n", + "\n", + "-```python3 -m yourvenv```\n", + "\n", + "-```source yourvenv/bin/activate```\n", + "\n", + "-```cd Robyn/python```\n", + "\n", + "-```pip install -r requirements.txt```\n", + "\n", + "\n", + "Then import the necessary libraries. Make sure to define your paths below.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "base_path = \"/Users/yijuilee/project_robyn/robynpy_interfaces/Robyn/R/data\"\n", + "python_path = \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\"\n", + "sys.path.append(base_path)\n", + "sys.path.append(python_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/yijuilee/robynpy_release_reviews/robynvenv/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "import os\n", + "import numpy as np\n", + "import pandas as pd\n", + "import pyreadr\n", + "from typing import Dict, Any\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.data.entities.enums import AdstockType\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters\n", + "from robyn.data.entities.calibration_input import CalibrationInput\n", + "from robyn.modeling.entities.modelrun_trials_config import TrialsConfig\n", + "from robyn.modeling.model_executor import ModelExecutor\n", + "from robyn.modeling.ridge_model_builder import RidgeModelBuilder\n", + "from robyn.modeling.entities.enums import NevergradAlgorithm, Models\n", + "from robyn.modeling.feature_engineering import FeaturizedMMMData, FeatureEngineering\n", + "from robyn.calibration.media_effect_calibration import MediaEffectCalibrator" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.1 Load Mock R data\n", + "\n", + "We need to set the base path for the data directory.\n", + "Create a .env file in the same directory as your notebook and put in define the path to the data dir.\n", + "for example: ROBYN_BASE_PATH=.../Robyn/R/data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " ds holiday country year\n", + "0 1995-01-01 New Year's Day AD 1995\n", + "1 1995-01-06 Epiphany AD 1995\n", + "2 1995-02-28 Carnival AD 1995\n", + "3 1995-03-14 Constitution Day AD 1995\n", + "4 1995-04-14 Good Friday AD 1995" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def load_data() -> Dict[str, pd.DataFrame]:\n", + " if not base_path:\n", + " raise EnvironmentError(\"Please set the ROBYN_BASE_PATH environment variable\")\n", + "\n", + " simulated_weekly_path = os.path.join(base_path, \"dt_simulated_weekly.RData\")\n", + " prophet_holidays_path = os.path.join(base_path, \"dt_prophet_holidays.RData\")\n", + "\n", + " result = pyreadr.read_r(simulated_weekly_path)\n", + " dt_simulated_weekly = result[\"dt_simulated_weekly\"]\n", + " result_holidays = pyreadr.read_r(prophet_holidays_path)\n", + " dt_prophet_holidays = result_holidays[\"dt_prophet_holidays\"]\n", + "\n", + " return {\"dt_simulated_weekly\": dt_simulated_weekly, \"dt_prophet_holidays\": dt_prophet_holidays}\n", + "\n", + "\n", + "data = load_data()\n", + "data[\"dt_simulated_weekly\"].head()\n", + "data[\"dt_prophet_holidays\"].head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup MMM Data\n", + "\n", + "We will now set up the MMM data specification which includes defining the dependent variable, independent variables, and the time window for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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DATErevenuetv_Sooh_Sprint_Sfacebook_Isearch_clicks_Psearch_Scompetitor_sales_Bfacebook_Seventsnewsletter
02015-11-232.754372e+0622358.3466670.012728.4888892.430128e+070.0000000.00000081250097607.132915na19401.653846
12015-11-302.584277e+0628613.4533330.00.0000005.527033e+069837.2384864133.33333379015491141.952450na14791.000000
22015-12-072.547387e+060.000000132278.4453.8666671.665159e+0712044.1196533786.66666783001974256.375378na14544.000000
32015-12-142.875220e+0683450.3066670.017680.0000001.054977e+0712268.0703194253.33333381228832800.490677na2800.000000
42015-12-212.215953e+060.000000277336.00.0000002.934090e+069467.2480233613.3333337105985689.582605na15478.000000
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" + ], + "text/plain": [ + " DATE revenue tv_S ooh_S print_S \\\n", + "0 2015-11-23 2.754372e+06 22358.346667 0.0 12728.488889 \n", + "1 2015-11-30 2.584277e+06 28613.453333 0.0 0.000000 \n", + "2 2015-12-07 2.547387e+06 0.000000 132278.4 453.866667 \n", + "3 2015-12-14 2.875220e+06 83450.306667 0.0 17680.000000 \n", + "4 2015-12-21 2.215953e+06 0.000000 277336.0 0.000000 \n", + "\n", + " facebook_I search_clicks_P search_S competitor_sales_B \\\n", + "0 2.430128e+07 0.000000 0.000000 8125009 \n", + "1 5.527033e+06 9837.238486 4133.333333 7901549 \n", + "2 1.665159e+07 12044.119653 3786.666667 8300197 \n", + "3 1.054977e+07 12268.070319 4253.333333 8122883 \n", + "4 2.934090e+06 9467.248023 3613.333333 7105985 \n", + "\n", + " facebook_S events newsletter \n", + "0 7607.132915 na 19401.653846 \n", + "1 1141.952450 na 14791.000000 \n", + "2 4256.375378 na 14544.000000 \n", + "3 2800.490677 na 2800.000000 \n", + "4 689.582605 na 15478.000000 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def setup_mmm_data(data: Dict[str, pd.DataFrame]) -> MMMData:\n", + " dt_simulated_weekly = data[\"dt_simulated_weekly\"]\n", + "\n", + " mmm_data_spec = MMMData.MMMDataSpec(\n", + " dep_var=\"revenue\",\n", + " dep_var_type=\"revenue\",\n", + " date_var=\"DATE\",\n", + " context_vars=[\"competitor_sales_B\", \"events\"],\n", + " paid_media_spends=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_S\", \"search_S\"],\n", + " paid_media_vars=[\"tv_S\", \"ooh_S\", \"print_S\", \"facebook_I\", \"search_clicks_P\"],\n", + " organic_vars=[\"newsletter\"],\n", + " window_start=\"2016-01-01\",\n", + " window_end=\"2018-12-31\",\n", + " )\n", + "\n", + " return MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec)\n", + "\n", + "\n", + "mmm_data = setup_mmm_data(data)\n", + "mmm_data.data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Preprocessing\n", + "\n", + "We will perform feature engineering to prepare the data for modeling. This includes transformations like adstock and other preprocessing steps." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Hyperparameters setup complete.\n" + ] + } + ], + "source": [ + "hyperparameters = Hyperparameters(\n", + " hyperparameters={\n", + " \"facebook_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"print_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"tv_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.3, 0.8],\n", + " ),\n", + " \"search_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0, 0.3],\n", + " ),\n", + " \"ooh_S\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " \"newsletter\": ChannelHyperparameters(\n", + " alphas=[0.5, 3],\n", + " gammas=[0.3, 1],\n", + " thetas=[0.1, 0.4],\n", + " ),\n", + " },\n", + " adstock=AdstockType.GEOMETRIC,\n", + " lambda_=0.0,\n", + " train_size=[0.5, 0.8],\n", + ")\n", + "\n", + "print(\"Hyperparameters setup complete.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Create HolidaysData object\n", + "holidays_data = HolidaysData(\n", + " dt_holidays=data[\"dt_prophet_holidays\"],\n", + " prophet_vars=[\"trend\", \"season\", \"holiday\"],\n", + " prophet_country=\"DE\",\n", + " prophet_signs=[\"default\", \"default\", \"default\"],\n", + ")\n", + "# Setup FeaturizedMMMData\n", + "feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Add Calibration Step" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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channellift_start_datelift_end_datelift_absspendconfidencemetriccalibration_scope
0facebook_S2018-05-012018-06-10400,000421,0000.85revenueimmediate
1tv_S2018-04-032018-06-03300,0007,1000.80revenueimmediate
2facebook_S+search_S2018-07-012018-07-20700,000350,0000.99revenueimmediate
3newsletter2017-12-012017-12-3120000.95revenueimmediate
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" + ], + "text/plain": [ + " channel lift_start_date lift_end_date lift_abs spend \\\n", + "0 facebook_S 2018-05-01 2018-06-10 400,000 421,000 \n", + "1 tv_S 2018-04-03 2018-06-03 300,000 7,100 \n", + "2 facebook_S+search_S 2018-07-01 2018-07-20 700,000 350,000 \n", + "3 newsletter 2017-12-01 2017-12-31 200 0 \n", + "\n", + " confidence metric calibration_scope \n", + "0 0.85 revenue immediate \n", + "1 0.80 revenue immediate \n", + "2 0.99 revenue immediate \n", + "3 0.95 revenue immediate " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.data.entities.enums import CalibrationScope, DependentVarType\n", + "from robyn.data.entities.calibration_input import CalibrationInput, ChannelCalibrationData\n", + "from robyn.calibration.media_effect_calibration import MediaEffectCalibrator\n", + "import pandas as pd\n", + "\n", + "# Create sample calibration data with explicit tuples\n", + "channel_calibration_data = {\n", + " (\"facebook_S\"): ChannelCalibrationData(\n", + " lift_start_date=pd.Timestamp(\"2018-05-01\"),\n", + " lift_end_date=pd.Timestamp(\"2018-06-10\"),\n", + " lift_abs=400000.0,\n", + " spend=421000.0,\n", + " confidence=0.85,\n", + " metric=DependentVarType.REVENUE,\n", + " calibration_scope=CalibrationScope.IMMEDIATE,\n", + " ),\n", + " (\"tv_S\"): ChannelCalibrationData(\n", + " lift_start_date=pd.Timestamp(\"2018-04-03\"),\n", + " lift_end_date=pd.Timestamp(\"2018-06-03\"),\n", + " lift_abs=300000.0,\n", + " spend=7100.0,\n", + " confidence=0.8,\n", + " metric=DependentVarType.REVENUE,\n", + " calibration_scope=CalibrationScope.IMMEDIATE,\n", + " ),\n", + " (\"facebook_S\", \"search_S\"): ChannelCalibrationData( # Tuple for combined channels\n", + " lift_start_date=pd.Timestamp(\"2018-07-01\"),\n", + " lift_end_date=pd.Timestamp(\"2018-07-20\"),\n", + " lift_abs=700000.0,\n", + " spend=350000.0,\n", + " confidence=0.99,\n", + " metric=DependentVarType.REVENUE,\n", + " calibration_scope=CalibrationScope.IMMEDIATE,\n", + " ),\n", + " (\"newsletter\"): ChannelCalibrationData(\n", + " lift_start_date=pd.Timestamp(\"2017-12-01\"),\n", + " lift_end_date=pd.Timestamp(\"2017-12-31\"),\n", + " lift_abs=200.0,\n", + " spend=0.0,\n", + " confidence=0.95,\n", + " metric=DependentVarType.REVENUE,\n", + " calibration_scope=CalibrationScope.IMMEDIATE,\n", + " ),\n", + "}\n", + "\n", + "# Create the CalibrationInput object directly since keys are already tuples\n", + "calibration_input = CalibrationInput(channel_data=channel_calibration_data)\n", + "\n", + "# Convert to DataFrame\n", + "df_data = []\n", + "for channels, data in calibration_input.channel_data.items():\n", + " df_data.append(\n", + " {\n", + " \"channel\": \"+\".join(channels),\n", + " \"lift_start_date\": data.lift_start_date.strftime(\"%Y-%m-%d\"),\n", + " \"lift_end_date\": data.lift_end_date.strftime(\"%Y-%m-%d\"),\n", + " \"lift_abs\": f\"{data.lift_abs:,.0f}\",\n", + " \"spend\": f\"{data.spend:,.0f}\",\n", + " \"confidence\": f\"{data.confidence:.2f}\",\n", + " \"metric\": data.metric.value,\n", + " \"calibration_scope\": data.calibration_scope.value,\n", + " }\n", + " )\n", + "\n", + "df_calibration_input = pd.DataFrame(df_data)\n", + "display(df_calibration_input)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-10-24 20:35:58 - robyn.calibration.media_effect_calibration - INFO - Initializing MediaEffectCalibrator\n", + "2024-10-24 20:35:58 - robyn.calibration.media_transformation - INFO - Initializing MediaTransformation\n", + "2024-10-24 20:35:58 - robyn.calibration.media_effect_calibration - INFO - Starting calibration process\n", + "2024-10-24 20:35:58 - robyn.calibration.media_effect_calibration - INFO - Calibration complete. Mean MAPE: 0.9883\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Estimated model coefficients:\n", + "tv_S: 0.4199\n", + "ooh_S: 0.0953\n", + "print_S: 0.2304\n", + "facebook_S: 0.3176\n", + "search_S: 0.4428\n", + "newsletter: 0.4061\n", + "\n", + "Calibration Results:\n", + "facebook_S: MAPE = 100.00%\n", + "tv_S: MAPE = 100.00%\n", + "facebook_S + search_S: MAPE = 100.00%\n", + "newsletter: MAPE = 95.33%\n", + "\n", + "Overall Model Calibrated: False\n", + "\n", + "Detailed Channel Information:\n", + "\n", + "Channel: facebook_S\n", + "Lift Period: 2018-05-01 00:00:00 to 2018-06-10 00:00:00\n", + "Expected Lift: 400,000.00\n", + "Spend: 421,000.00\n", + "Confidence: 85.00%\n", + "Actual Values Sum: 14,049.49\n", + "\n", + "Channel: tv_S\n", + "Lift Period: 2018-04-03 00:00:00 to 2018-06-03 00:00:00\n", + "Expected Lift: 300,000.00\n", + "Spend: 7,100.00\n", + "Confidence: 80.00%\n", + "Actual Values Sum: 947.11\n", + "\n", + "Channel: ('facebook_S', 'search_S')\n", + "Lift Period: 2018-07-01 00:00:00 to 2018-07-20 00:00:00\n", + "Expected Lift: 700,000.00\n", + "Spend: 350,000.00\n", + "Confidence: 99.00%\n", + "Actual Values Sum: 22,346.47\n", + "\n", + "Channel: newsletter\n", + "Lift Period: 2017-12-01 00:00:00 to 2017-12-31 00:00:00\n", + "Expected Lift: 200.00\n", + "Spend: 0.00\n", + "Confidence: 95.00%\n", + "Actual Values Sum: 154,694.00\n" + ] + } + ], + "source": [ + "import logging\n", + "from typing import Dict\n", + "\n", + "\n", + "# Define the coefficient function locally in the notebook\n", + "def get_model_coefficients(mmm_data: MMMData) -> Dict[str, float]:\n", + " \"\"\"Get approximate coefficients for channels based on data.\"\"\"\n", + " coefficients = {}\n", + " dep_var = mmm_data.mmmdata_spec.dep_var\n", + "\n", + " for channel in mmm_data.mmmdata_spec.paid_media_spends + mmm_data.mmmdata_spec.organic_vars:\n", + " # Calculate simple correlation coefficient\n", + " corr = mmm_data.data[channel].corr(mmm_data.data[dep_var])\n", + " coefficients[channel] = abs(corr) # Use absolute correlation as coefficient\n", + "\n", + " return coefficients\n", + "\n", + "\n", + "# Configure logging to show debug messages\n", + "logging.basicConfig(\n", + " level=logging.DEBUG, format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\", datefmt=\"%Y-%m-%d %H:%M:%S\"\n", + ")\n", + "\n", + "# Get model coefficients\n", + "model_coefficients = get_model_coefficients(mmm_data)\n", + "print(\"\\nEstimated model coefficients:\")\n", + "for channel, coef in model_coefficients.items():\n", + " print(f\"{channel}: {coef:.4f}\")\n", + "\n", + "# Initialize calibration engine with coefficients\n", + "calibration_engine = MediaEffectCalibrator(\n", + " mmm_data=mmm_data,\n", + " hyperparameters=hyperparameters,\n", + " calibration_input=calibration_input,\n", + " model_coefficients=model_coefficients, # Add this parameter\n", + ")\n", + "\n", + "# Perform calibration\n", + "calibration_results = calibration_engine.calibrate()\n", + "\n", + "print(\"\\nCalibration Results:\")\n", + "# Access channel scores specifically\n", + "for channel, score in calibration_results.channel_scores.items():\n", + " if len(channel) == 1:\n", + " print(f\"{channel[0]}: MAPE = {score:.2%}\")\n", + " else:\n", + " print(f\"{' + '.join(channel)}: MAPE = {score:.2%}\")\n", + "\n", + "print(f\"\\nOverall Model Calibrated: {calibration_results.is_model_calibrated()}\")\n", + "\n", + "# Print detailed channel information\n", + "print(\"\\nDetailed Channel Information:\")\n", + "for channel_tuple, data in calibration_input.channel_data.items():\n", + " channels = channel_tuple if len(channel_tuple) > 1 else channel_tuple[0]\n", + " print(f\"\\nChannel: {channels}\")\n", + " print(f\"Lift Period: {data.lift_start_date} to {data.lift_end_date}\")\n", + " print(f\"Expected Lift: {data.lift_abs:,.2f}\")\n", + " print(f\"Spend: {data.spend:,.2f}\")\n", + " print(f\"Confidence: {data.confidence:.2%}\")\n", + "\n", + " # Get actual values from data for this period\n", + " date_col = mmm_data.mmmdata_spec.date_var\n", + " mask = (mmm_data.data[date_col] >= data.lift_start_date) & (mmm_data.data[date_col] <= data.lift_end_date)\n", + "\n", + " if isinstance(channels, tuple):\n", + " actual_values = sum(mmm_data.data.loc[mask, ch].sum() for ch in channels)\n", + " else:\n", + " actual_values = mmm_data.data.loc[mask, channels].sum()\n", + "\n", + " print(f\"Actual Values Sum: {actual_values:,.2f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "20:35:59 - cmdstanpy - INFO - Chain [1] start processing\n", + "2024-10-24 20:35:59 - cmdstanpy - INFO - Chain [1] start processing\n", + "20:35:59 - cmdstanpy - INFO - Chain [1] done processing\n", + "2024-10-24 20:35:59 - cmdstanpy - INFO - Chain [1] done processing\n", + "2024-10-24 20:35:59 - robyn.modeling.feature_engineering - INFO - Prophet decomposition complete.\n", + "2024-10-24 20:35:59 - robyn.modeling.feature_engineering - INFO - Processing tv_S\n", + "2024-10-24 20:36:00 - robyn.modeling.feature_engineering - INFO - Processing ooh_S\n", + "2024-10-24 20:36:00 - robyn.modeling.feature_engineering - INFO - Processing print_S\n", + "2024-10-24 20:36:02 - robyn.modeling.feature_engineering - INFO - Processing facebook_S\n", + "2024-10-24 20:36:02 - robyn.modeling.feature_engineering - INFO - Processing search_S\n", + "2024-10-24 20:36:02 - robyn.modeling.feature_engineering - INFO - Feature engineering complete.\n" + ] + } + ], + "source": [ + "featurized_mmm_data = feature_engineering.perform_feature_engineering()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from robyn.visualization.feature_visualization import FeaturePlotter\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Create a FeaturePlotter instance\n", + "feature_plotter = FeaturePlotter(mmm_data, hyperparameters)\n", + "\n", + "# Plot spend-exposure relationship for each channel\n", + "for channel in mmm_data.mmmdata_spec.paid_media_spends:\n", + " try:\n", + " fig = feature_plotter.plot_spend_exposure(featurized_mmm_data, channel)\n", + " plt.show()\n", + " except ValueError as e:\n", + " print(f\"Skipping {channel}: {str(e)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-10-24 20:36:03 - robyn.modeling.ridge_model_builder - INFO - Collecting hyperparameters for optimization... {'prepared_hyperparameters': Hyperparameters(hyperparameters={'facebook_S': ChannelHyperparameters(thetas=[0, 0.3], shapes=None, scales=None, alphas=[0.5, 3], gammas=[0.3, 1], penalty=None), 'print_S': ChannelHyperparameters(thetas=[0.1, 0.4], shapes=None, scales=None, alphas=[0.5, 3], gammas=[0.3, 1], penalty=None), 'tv_S': ChannelHyperparameters(thetas=[0.3, 0.8], shapes=None, scales=None, alphas=[0.5, 3], gammas=[0.3, 1], penalty=None), 'search_S': ChannelHyperparameters(thetas=[0, 0.3], shapes=None, scales=None, alphas=[0.5, 3], gammas=[0.3, 1], penalty=None), 'ooh_S': ChannelHyperparameters(thetas=[0.1, 0.4], shapes=None, scales=None, alphas=[0.5, 3], gammas=[0.3, 1], penalty=None), 'newsletter': ChannelHyperparameters(thetas=[0.1, 0.4], shapes=None, scales=None, alphas=[0.5, 3], gammas=[0.3, 1], penalty=None)}, adstock=, lambda_=0.0, train_size=[0.5, 0.8], hyper_bound_list_updated={}), 'hyper_to_optimize': {'facebook_S_thetas': [0, 0.3], 'facebook_S_alphas': [0.5, 3], 'facebook_S_gammas': [0.3, 1], 'print_S_thetas': [0.1, 0.4], 'print_S_alphas': [0.5, 3], 'print_S_gammas': [0.3, 1], 'tv_S_thetas': [0.3, 0.8], 'tv_S_alphas': [0.5, 3], 'tv_S_gammas': [0.3, 1], 'search_S_thetas': [0, 0.3], 'search_S_alphas': [0.5, 3], 'search_S_gammas': [0.3, 1], 'ooh_S_thetas': [0.1, 0.4], 'ooh_S_alphas': [0.5, 3], 'ooh_S_gammas': [0.3, 1], 'newsletter_thetas': [0.1, 0.4], 'newsletter_alphas': [0.5, 3], 'newsletter_gammas': [0.3, 1], 'train_size': [0.5, 0.8]}}\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + ">>> Starting 5 trials with 2000 iterations each using TwoPointsDE nevergrad algorithm on x cores...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Running trial 1 of total 5 trials: 100%|███████████████████████████████████\n", + "2024-10-24 20:37:54 - robyn.modeling.ridge_model_builder - INFO - Finished in 1.86 mins\n", + "Running trial 2 of total 5 trials: 100%|███████████████████████████████████\n", + "2024-10-24 20:40:21 - robyn.modeling.ridge_model_builder - INFO - Finished in 2.42 mins\n", + "Running trial 3 of total 5 trials: 100%|███████████████████████████████████\n", + "2024-10-24 20:43:18 - robyn.modeling.ridge_model_builder - INFO - Finished in 2.95 mins\n", + "Running trial 4 of total 5 trials: 100%|███████████████████████████████████\n", + "2024-10-24 20:45:31 - robyn.modeling.ridge_model_builder - INFO - Finished in 2.20 mins\n", + "Running trial 5 of total 5 trials: 100%|███████████████████████████████████\n", + "2024-10-24 20:47:32 - robyn.modeling.ridge_model_builder - INFO - Finished in 2.00 mins\n", + "2024-10-24 20:47:32 - robyn.modeling.convergence.convergence - WARNING - 'mape' column not found or all zeros. Assuming model is not calibrated.\n", + "2024-10-24 20:47:32 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2024-10-24 20:47:32 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n", + "2024-10-24 20:47:32 - matplotlib.category - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model training complete.\n" + ] + }, + { + "data": { + "image/png": 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iGJQiIiIiIiIiIqISx6AUERERERERERGVOAaliIiIiIiIiIioxDEoRUREREREREREJY5BKSIiIiIiIiIiKnEMShERERERERERUYljUIqIiIiIiIiIiEocg1JERERERERERFTiGJQiIiIiIiIiIqISx6AUERERERERERGVOAaliIiIiIiIiIioxDEoRUREREREREREJY5BKSIiIiIiIiIiKnEMShERERERERERUYljUIqIiIiIiIiIiEocg1JERERERERERFTiGJQiIiIiIiIiIqIS99oHpQ4cOID27dvDxsYGKpUKGzZs0EgXEUyYMAHW1tYoU6YMAgMDcfnyZY089+/fR1BQEExNTWFubo5Bgwbh4cOHhW73yZMnGDlyJCpUqAATExN07doVCQkJL3v3iIiIiIiIiIj+J732QalHjx7Bw8MDP//8s9b06dOnY86cOZg/fz6OHTuGsmXLolWrVnjy5ImSJygoCOfOncPu3buxZcsWHDhwAEOGDCl0ux9//DE2b96M1atXY//+/bh9+za6dOnyUveNiIiIiIiIiOh/lUpEpLQrUVwqlQrr169Hp06dAGT3krKxscHo0aMxZswYAEBycjIsLS0RGhqKnj174sKFC6hTpw4iIiLg4+MDANixYwfatm2Lf//9FzY2Nvm2k5ycjEqVKmH58uV49913AQAXL16Es7Mzjhw5gvr16xervikpKTAzM0NycjJMTU1fwhEgIiIiIiIiInq9FTceoleCdXrpYmNjER8fj8DAQGWZmZkZfH19ceTIEfTs2RNHjhyBubm5EpACgMDAQOjo6ODYsWPo3LlzvnIjIyORkZGhUa6TkxNsbW0LDUqlp6cjPT1deZ+SkvIydrNUNWvWDAAQHh5eqvUgInobXbt2DaGhoRq9e4tLpVIVubygPM+zTkHvi8qnLW9h9SlO3sLyFLV+QekqlarI8vIuz7tOYe+fd52CXjn5dHR0Cl0HAHR0dIp1zImIiN4GOf1ssrKyICIa/+a88i5/nn9zXrnfZ2VlaWyzoFfuPLnrmztd278VK1ZEUFAQKlSoUGLHsbS80UGp+Ph4AIClpaXGcktLSyUtPj4elStX1kjX09ND+fLllTzayjUwMIC5uXmB5WozdepUfP3118+7G681BqOIiF6dr7/+GrGxsaVdDSIiIiJ6zTx+/Bjjxo0r7Wq8cm90UOp18/nnn+OTTz5R3qekpKBatWqlWCMiInqdffHFF/j111/x+PHjFy4j7y9vxclX3PWLs05xy3iePNq2W1Qebb9A5k0vrC5518n7K2ZBZWj7tbM474mIiOj1kNPDOPe/AKCrq6uxPPcrd8/lgv4uqEdz3vTc73P+trGxQXBwcIkdg9L0RgelrKysAAAJCQmwtrZWlickJECtVit5EhMTNdbLzMzE/fv3lfW1lfv06VMkJSVp9JZKSEgocB0AMDQ0hKGh4QvuDRER/a9xcHDA9OnTS7saRK89bcMotA2lyDukInf6s2fPNIZzaFuvoLRnz57lW17Y8JDiDB0pbLiItjoUtI/a8j3PUJLCAqcFBXDzpuXNU9jfz/OZFyetuPX4rwHz4h6L4hwnbfX9L8OtixqWXNAr5+ZZ2w23tvS8/wL5b9pzl6Wjo6O8tOUpbB2VSqWUnXd5UYGD4mynsO0Xto6241LYMSxsOHZxhn7n/TyL+ryJ3kRvdFCqRo0asLKyQlhYmBKESklJwbFjxzB8+HAAgJ+fH5KSkhAZGQlvb28AwN69e5GVlQVfX1+t5Xp7e0NfXx9hYWHo2rUrACAmJgY3btyAn5/fq98xIiIiIlLk3KASERHR2+W1D0o9fPgQV65cUd7HxsYiKioK5cuXh62tLT766CN88803cHBwQI0aNfDVV1/BxsZGmaHP2dkZrVu3xuDBgzF//nxkZGTg/fffR8+ePZWZ927duoWAgAD88ccfqFevHszMzDBo0CB88sknKF++PExNTfHBBx/Az8+v2DPvERERERERERFRwV77oNSJEyfg7++vvM95ZlNwcDBCQ0Px6aef4tGjRxgyZAiSkpLQqFEj7NixA0ZGRso6f/75J95//30EBARAR0cHXbt2xZw5c5T0jIwMxMTEaDzTY9asWUre9PR0tGrVCr/88ksJ7DERERERERER0dtPJXza5iuTkpICMzMzJCcnw9TUtLSrQ0RERERERET0yhU3HqJTgnUiIiIiIiIiIiICwKAUERERERERERGVAgaliIiIiIiIiIioxDEoRUREREREREREJY5BKSIiIiIiIiIiKnEMShERERERERERUYljUIqIiIiIiIiIiEocg1JERERERERERFTiGJQiIiIiIiIiIqISx6AUERERERERERGVOL3SrsDbTEQAACkpKaVcEyIiIiIiIiKikpETB8mJixSEQalXKDU1FQBQrVq1Uq4JEREREREREVHJSk1NhZmZWYHpKikqbEUvLCsrC7dv30a5cuWgUqlKuzovJCUlBdWqVcPNmzdhampa2tUheuOxTRG9XGxTRC8P2xPRy8U2Rf/LRASpqamwsbGBjk7BMd45aQAAQoxJREFUT45iT6lXSEdHB1WrVi3tarwUpqamvJASvURsU0QvF9sU0cvD9kT0crFN0f+qwnpI5eCDzomIiIiIiIiIqMQxKEVERERERERERCWOQSkqlKGhISZOnAhDQ8PSrgrRW4FtiujlYpsiennYnoheLrYpoqLxQedERERERERERFTi2FOKiIiIiIiIiIhKHINSRERERERERERU4hiUIiIiIiIiIiKiEsegFBXq559/hp2dHYyMjODr64vjx4+XdpWIXqkDBw6gffv2sLGxgUqlwoYNGzTSRQQTJkyAtbU1ypQpg8DAQFy+fFkjz/379xEUFARTU1OYm5tj0KBBePjwoUaeM2fOoHHjxjAyMkK1atUwffr0fHVZvXo1nJycYGRkBDc3N2zbtu2560JUmqZOnYq6deuiXLlyqFy5Mjp16oSYmBiNPE+ePMHIkSNRoUIFmJiYoGvXrkhISNDIc+PGDbRr1w7GxsaoXLkyxo4di8zMTI084eHh8PLygqGhIezt7REaGpqvPkV9pxWnLkSlad68eXB3d4epqSlMTU3h5+eH7du3K+lsT0T/zbRp06BSqfDRRx8py9iuiF4xISrAypUrxcDAQBYvXiznzp2TwYMHi7m5uSQkJJR21YhemW3btsn48eNl3bp1AkDWr1+vkT5t2jQxMzOTDRs2yOnTp6VDhw5So0YNSUtLU/K0bt1aPDw85OjRo3Lw4EGxt7eXXr16KenJycliaWkpQUFBEh0dLStWrJAyZcrIggULlDyHDx8WXV1dmT59upw/f16+/PJL0dfXl7Nnzz5XXYhKU6tWrWTJkiUSHR0tUVFR0rZtW7G1tZWHDx8qeYYNGybVqlWTsLAwOXHihNSvX18aNGigpGdmZoqrq6sEBgbKqVOnZNu2bVKxYkX5/PPPlTxXr14VY2Nj+eSTT+T8+fMyd+5c0dXVlR07dih5ivOdVlRdiErbpk2bZOvWrXLp0iWJiYmRL774QvT19SU6OlpE2J6I/ovjx4+LnZ2duLu7y6hRo5TlbFdErxaDUlSgevXqyciRI5X3z549ExsbG5k6dWop1oqo5OQNSmVlZYmVlZXMmDFDWZaUlCSGhoayYsUKERE5f/68AJCIiAglz/bt20WlUsmtW7dEROSXX34RCwsLSU9PV/J89tln4ujoqLzv3r27tGvXTqM+vr6+MnTo0GLXheh1k5iYKABk//79IpJ9zurr68vq1auVPBcuXBAAcuTIERHJDhTr6OhIfHy8kmfevHliamqqtKFPP/1UXFxcNLbVo0cPadWqlfK+qO+04tSF6HVkYWEhv/32G9sT0X+QmpoqDg4Osnv3bmnatKkSlGK7Inr1OHyPtHr69CkiIyMRGBioLNPR0UFgYCCOHDlSijUjKj2xsbGIj4/XaBdmZmbw9fVV2sWRI0dgbm4OHx8fJU9gYCB0dHRw7NgxJU+TJk1gYGCg5GnVqhViYmLw4MEDJU/u7eTkydlOcepC9LpJTk4GAJQvXx4AEBkZiYyMDI3z2MnJCba2thptys3NDZaWlkqeVq1aISUlBefOnVPyFNZeivOdVpy6EL1Onj17hpUrV+LRo0fw8/NjeyL6D0aOHIl27drlO/fZrohePb3SrgC9nu7evYtnz55pXFwBwNLSEhcvXiylWhGVrvj4eADQ2i5y0uLj41G5cmWNdD09PZQvX14jT40aNfKVkZNmYWGB+Pj4IrdTVF2IXidZWVn46KOP0LBhQ7i6ugLIPo8NDAxgbm6ukTfvua7tPM9JKyxPSkoK0tLS8ODBgyK/04pTF6LXwdmzZ+Hn54cnT57AxMQE69evR506dRAVFcX2RPQCVq5ciZMnTyIiIiJfGr+niF49BqWIiIjolRs5ciSio6Nx6NCh0q4K0RvN0dERUVFRSE5Oxpo1axAcHIz9+/eXdrWI3kg3b97EqFGjsHv3bhgZGZV2dYj+J3H4HmlVsWJF6Orq5pvNISEhAVZWVqVUK6LSlXPuF9YurKyskJiYqJGemZmJ+/fva+TRVkbubRSUJ3d6UXUhel28//772LJlC/bt24eqVasqy62srPD06VMkJSVp5M97rr9oezE1NUWZMmWK9Z1WnLoQvQ4MDAxgb28Pb29vTJ06FR4eHpg9ezbbE9ELiIyMRGJiIry8vKCnpwc9PT3s378fc+bMgZ6eHiwtLdmuiF4xBqVIKwMDA3h7eyMsLExZlpWVhbCwMPj5+ZVizYhKT40aNWBlZaXRLlJSUnDs2DGlXfj5+SEpKQmRkZFKnr179yIrKwu+vr5KngMHDiAjI0PJs3v3bjg6OsLCwkLJk3s7OXlytlOcuhCVNhHB+++/j/Xr12Pv3r35hq16e3tDX19f4zyOiYnBjRs3NNrU2bNnNYK9u3fvhqmpKerUqaPkKay9FOc7rTh1IXodZWVlIT09ne2J6AUEBATg7NmziIqKUl4+Pj4ICgpS/ma7InrFSvtJ6/T6WrlypRgaGkpoaKicP39ehgwZIubm5hozSxC9bVJTU+XUqVNy6tQpASA//PCDnDp1Sq5fvy4iItOmTRNzc3PZuHGjnDlzRjp27Cg1atSQtLQ0pYzWrVuLp6enHDt2TA4dOiQODg7Sq1cvJT0pKUksLS2lb9++Eh0dLStXrhRjY2NZsGCBkufw4cOip6cnM2fOlAsXLsjEiRNFX19fzp49q+QpTl2IStPw4cPFzMxMwsPDJS4uTnk9fvxYyTNs2DCxtbWVvXv3yokTJ8TPz0/8/PyU9Jyptlu2bClRUVGyY8cOqVSpktaptseOHSsXLlyQn3/+WetU20V9pxVVF6LSNm7cONm/f7/ExsbKmTNnZNy4caJSqWTXrl0iwvZE9DLknn1PhO2K6FVjUIoKNXfuXLG1tRUDAwOpV6+eHD16tLSrRPRK7du3TwDkewUHB4uISFZWlnz11VdiaWkphoaGEhAQIDExMRpl3Lt3T3r16iUmJiZiamoqAwYMkNTUVI08p0+flkaNGomhoaFUqVJFpk2blq8uf/31l9SuXVsMDAzExcVFtm7dqpFenLoQlSZtbQmALFmyRMmTlpYmI0aMEAsLCzE2NpbOnTtLXFycRjnXrl2TNm3aSJkyZaRixYoyevRoycjI0Mizb98+UavVYmBgIDVr1tTYRo6ivtOKUxei0jRw4ECpXr26GBgYSKVKlSQgIEAJSImwPRG9DHmDUmxXRK+WSkSkdPpoERERERERERHR/yo+U4qIiIiIiIiIiEocg1JERERERERERFTiGJQiIiIiIiIiIqISx6AUERERERERERGVOAaliIiIiIiIiIioxDEoRUREREREREREJY5BKSIiIiIiIiIiKnEMShERERERERERUYljUIqIiIj+p9nZ2eHHH3/8z3n+q9DQUJibm7/SbQDAhg0bYG9vD11dXXz00UevfHuFadasWanXgYiIiEoPg1JERET0Vrp58yYGDhwIGxsbGBgYoHr16hg1ahTu3bv33GVFRERgyJAhL61u2oJcPXr0wKVLl17aNgoydOhQvPvuu7h58yYmT578yrcHAOHh4VCpVEhKStJYvm7duhKrAxEREb1+GJQiIiKit87Vq1fh4+ODy5cvY8WKFbhy5Qrmz5+PsLAw+Pn54f79+89VXqVKlWBsbPyKaputTJkyqFy58ivdxsOHD5GYmIhWrVrBxsYG5cqVe6XbK0r58uVLvQ5ERERUehiUIqI3lp2dHRwdHeHh4QF7e3t07NgRf//9t5IeGhoKMzMzqNVq5TVy5EglPTIyEq1bt0bNmjXh4+ODhg0bYsOGDRrru7m5wdnZGfb29vj888/x9OlTje1XrlwZGRkZyrJ9+/ZBpVIpw1HCw8NRpkwZqNVquLu7o1GjRjhz5ozGfvTv3x9VqlSBWq2Gk5MT+vbti8ePHyvp69atg7e3t5LevHlzZGVlAQD2798PPz8/qNVq1KlTBw0bNkRCQoJGuZ6ennBwcECjRo2wdOnS/37g31A+Pj4IDw9/peXt378f3bt3h6urK7y8vBAcHIyzZ88Wu8zw8HDs2LGjwPSVK1dCrVbD1dUVrq6u+P777zXSFy1aBAcHB9SqVQuDBw/WODdzmzJlChwdHaGjo6NxzgOAiCAkJAS1a9eGm5sb/P39lbQBAwbA3d0darUadevWRVhY2H8uM68bN26gffv2cHR0RJ06dTB37lwlbcuWLXBycoKDgwO6dOmClJQUAEBsbKzSRlxdXdGtWzcMGTIEBgYG2LVrF5o2bQpbW1u0adMGe/bswa1btzB+/HiN7aampqJXr14oW7YsqlSpgp9//lkjPW/PpqSkJLz33nuoVKkSTE1N0bx5c5w+fRqJiYmwtLREp06dsHnzZtStWxdGRkYwMzODhYUFXFxcULZsWVy/fh0ff/wxVCoVVCoV1Go1bG1toVKp8Mknn+DSpUtQqVTYtGkTmjVrBmdnZzg7O2PAgAGoVasWjhw5olwTypUrB319fVSuXBl9+/bF3bt3Nep++fJltGjRArVq1VICQM2bN4dKpcLevXtRr149GBoawt7eHj/99BMA4Mcff4SdnR3Wrl0LNzc3WFhYwNTUFF988QWsra1RoUIFjBw5UjnHnj17hr59+6JChQrQ19eHnp4e7O3tsWjRIly7dk35zC0sLJT9DQ0NzTd878GDB+jXrx8sLCxgbGyMNm3a4PLly0p6zhDHnTt3wtnZGSYmJmjdujXi4uKUPOHh4ahXrx4MDAxgYGCAhg0b4vr16wCAhIQEjBs3Dl5eXlCr1QgICMAff/xR4PmYV1JSEqZNm1Zg+u3bt9GqVSs4OjrC3d0dXbt2xZ07dzQ+iwYNGqB27dqoW7cuzp07p6T179+/wGvU8ePHUb9+fXh6esLZ2RnTp09X0jp37qzxPaejo4NNmzYBAH7++We4ubkpbWPOnDnKegkJCejSpQvc3d3h7Oycr+fe/v37UbduXbi4uKBOnTo4cuSI1rpFRESgYcOG8PDwgFqtxt69ezX219/fXzlXR48erXx/lYQnT56gU6dOqF27Njw8PNCiRQtcuXJFSS/smlbYfgHAL7/8AmdnZ7i5ucHDwwNPnjwBUPjnERISgkqVKilpQUFBBdZ927Ztynnq6uqK33//XUlr1qwZatSooZQza9asl3K8iIhKhRARvaGqV68up06dUt6vXbtWzMzM5OjRoyIismTJEunYsaPWdaOjo6VChQqyadMmZdmtW7ckNDRUREQWLFggTk5OcvXqVRERefTokXTp0kX69OmjsX1vb29Zs2aNsiwoKEh8fHxk1KhRIiKyb98+8fDwUNK///578fLy0qhLcHCwzJo1S0REnjx5Ig0aNJDvvvtORERu374tFSpUkGvXrin5IyMjJSsrSzIyMsTCwkIiIyOVtIsXL0pqamq+ckVETp06JbVr15bvv/9e6zF5HWVkZLy0sry9vWXfvn2vrLyQkBB55513JCIiQp49eyYiIkeOHJHGjRvL2rVri1XmxIkTlXNHm0OHDklcXJyIiCQlJUmtWrWUOly9elWsra0lLi5OsrKypH379vLTTz9pLefYsWPyzz//SNOmTWX9+vUaaT/++KN07txZ0tPTRUSU7YmIPHjwQPn75MmTYmFhoezri5aZW1ZWlnh5eclff/2lLIuPjxcRkdTUVKlcubJcuHBBRERGjhwpY8aMEZHsdvP48WNlnSFDhggAmTJlitbtDB48WCwsLCQrK0tEstuyiYmJTJw4UWJiYmTOnDmiq6sru3btUtapXr26RnsKDAyU9u3bS0REhFy6dElGjx4tFSpUkLZt28rAgQOlfv36oqurKxMmTJDw8HCxtraWjz76SESy27WNjY1MmjRJ4uLilOOxcOFCUalUcuLECRER8fT0FHNzczl48KCIiGRmZoq7u7t8+eWX8ujRI0lMTJRKlSrJuHHjJCAgQD755BNp0aKF+Pv7a+xvgwYN5Ndff5X09HQ5cuSIAJCFCxdKXFycLFq0SGrUqCHu7u5y7949sbW1lejoaJk1a5ZYW1uLo6Oj3Lp1S4KDg6VcuXIyaNAguXDhgmzevFmMjY1l4cKFIiKyZs0aqVSpklStWlXWrFkj+/btkz179sjKlSslMzNT1q5dKwAkJiZG4uLi5LPPPpMlS5ZI06ZNNc75Dh06iLOzsxw4cECioqKkVatWYm9vL0+fPhWR7Ou6vr6+BAYGSkREhERGRoqzs7P07t1bRLKvGWZmZjJmzBiZMGGCdOrUSUJDQ+X69esSEREharVa/vjjD3n06JFyfo0dO1Z69OihnMuFiY2NFTMzswLT4+Pjlc9LRGTMmDESHBysvPf395clS5aIiMjq1avFx8dHSQsODi7wGuXh4SEbN24UEZF79+5JpUqV5Ny5c/nyRURESIUKFZS2lpSUpKQlJydLtWrV5OTJkyIi0rt3bxk/fryIiDx8+FA8PDzk+PHjIpL9fVi9enU5f/68iGS3sdztP0dWVpZUqVJFdu/eLSIiMTExUq1aNaU9duzYUWbPni0iImlpaeLq6ipbt27Vuo8FuXPnznPlzy0tLU22bt2qtPW5c+dK06ZNlfSCrmlF7deGDRukQYMGyvFNTEyUzMzMfNvP+3kUdY3PkZWVJRYWFnL69GkRyT7vDA0NJSUlRURE63WWiOhNxZ5SRPTW6NKlC4YNG4aZM2cWmXfatGkYOHAg2rdvryyzsbFBcHAwAGDSpEn4/vvvUaNGDQCAsbExFi5ciLVr1+Kff/5R1hkwYAAWL14MAEhOTsbRo0fRunXrArfbunVrxMTEFJhuaGiIRo0aafyqr6uri/Llyyt5vLy8oFKpkJqaipSUFFhZWSlpjo6OMDEx0Vq2Wq3G7Nmz8d1330FE8qXfunUL7777Ltzc3ODu7o6vvvoKAJCYmIguXbrAzc0Nrq6uWLBggbKOnZ0dJkyYAD8/P9SoUQPffPMNAODw4cNwc3PTKL9Zs2bYuHEjAGDnzp1o1KgRvL29Ua9ePezbtw9Adg8HFxcXDBo0CGq1GuvXr8fff/8NtVoNNzc3DBw4EB4eHkpvgvj4eHTv3h316tWDm5sbvvzyS2V7Oeu5urpiwIAByMzMLPC45/bbb7+hTp06yjaPHTtWZHmbN2/GpUuXsGnTJvj4+EBHJ/vrtX79+tixYwd++OEH5TlGcXFxaNWqFerUqYPAwED07NkTISEhiIqKwvz58/Hnn39CrVZj0qRJ+erWsGFD5fM2MzODk5MTrl27BgBYs2YNOnToACsrK6hUKgwbNgwrVqzQuo/16tVDzZo1tabNmDED06ZNg4GBAQBonF+5H8KdnJz8UsrMLSwsDIaGhujWrZuyzNLSEgCwfft2eHp6wsnJCQAwYsQIZf8MDQ1RpkwZANk9dnJ6zTg7O2vdjrOzMx48eIDExETs378f9+7dQ2ZmJgICAlC7dm188MEHePfddwvsfXDo0CEcP34cq1evho+PDxwcHDBz5kzo6OggPT0djRs3RkxMDHr27Imvv/4au3fvRv/+/ZXyrK2toa+vj3LlysHKyko5HidPnoRKpYK3tzcAoHbt2sjMzESjRo0AAP/88w/OnDmDoKAgGBsbY8GCBfD09MTEiROhp6eHatWqYfHixdi3b5/Gs6lOnz6Ntm3bwsDAQDl+p06dgpWVFdauXatcU8qXL48ePXooxzUlJQWffPIJbGxsAGQPtVuwYAGcnJzwzjvvoF27dkrPksTERNy5cwfz5s1D165d0axZMwQEBKBHjx4a17DKlSvDysoKRkZGSv3+/fdfuLq6onfv3ti0aRPS09NhZmaGWbNm4caNG/jnn3+U6ywAZGRkIDExEUOGDMEXX3yBXr16ISwsDKmpqejWrRuSk5OxY8cOxMfHw8zMDMHBwahYsSKGDh2KzZs3o2/fvspQTEtLS0yfPh3u7u747bfflG2EhITAwcEB3t7e+PLLL2FnZwcAGDZsGFJTU6FWq+Hj45Pv3LC0tFQ+LwDw9fVV2mhiYiJOnDiBPn36AAC6du2KmzdvavTcKUju53E9evQIBgYGGt8LORYtWoQ+ffoobc3MzExJe/TokUbvyZzzAgDKli2LJk2aKL1pf/nlF/Tu3VtpQ4aGhlofwn/v3j3cuXMHgYGBALLPWXNzc2zfvl2pd861Ii0tDRkZGbC2ti5yf1NSUhAaGoqWLVuiRYsWReYviJGREdq2bQuVSgUg+5qc83kABV/TitqvGTNmYOLEicrxrVSpEnR1dfNtP+/n8Txyf+YpKSmoUKECDA0Nn7scIqLXHYNSRPRW8fX11RgOsW/fPo1u9Dk3hZGRkfDz89NaRmJiIm7dupUvvUKFCnBwcMDJkyeVZQ0bNsS1a9dw+/ZtrFixAt26ddP6H9McK1euVG44tUlOTkZ4eDi6du0KAMqQv+rVq6Nz586YMWMGbt26BSB7GMz7778PR0dHtG3bFpMnTy7yIcm+vr7KzWNeffr0gbe3N86ePYszZ87gww8/BAB88MEHcHR0xNmzZ7F371588803OHr0qLJeUlISjhw5goiICKV+DRs2RHp6Ok6cOAEg+/k+MTExaNeuHa5evYqQkBBs27YNkZGRWL58OXr37o309HQAwIULF9CvXz9ERUWhY8eO6NGjB2bNmoWzZ8+ib9++GsMfg4ODMXLkSBw/fhynTp3CiRMnsHr1ajx9+hQ9evTAzJkzER0djV69euH06dPKevPnz8eECRO0HqPRo0cjLCwMUVFROHnyJFxcXIosb86cOZg1axZUKhU+//xzqNVq9OzZE127dsW9e/cwatQo/PnnnwCADz/8EPXq1cP58+fx+++/Kzf1arUaw4YNQ1BQEKKiogqsX47z58/jyJEjyk3TjRs3UL16dSXdzs4ON27cKLSMvFJSUpCQkICNGzfC19cXvr6+WLVqlUaecePGoVatWujSpQvWrl2rBOD+S5m596lSpUro2bMnPD090blzZ1y9erXA/YuLi1OCg0+fPoVarUbFihXx77//AoDW4CsAJb1+/fqYNWsWjIyMMHr0aDRu3BhA9nXj4MGD2LNnj3LtuH37NmbMmIHx48fj9OnTePjwISpUqAATExOYmJjA2NgYd+7cgbu7O4DsthwQEKDsV1paGgIDA6FWq/HBBx9oHcJ08OBBjZtXMzMzPHr0CA0bNoRarUa3bt3g5uamBJb+/vtv7Nq1C2XKlMGePXswfvx4JS138Nzb2xvLli0DAOWGPD4+XjmuuQMXuc+bjIwM3LhxA02bNsXmzZuhr6+vUV9ra2skJiYCgHLzPHv2bGUY0/O4ePEifHx8oKenh549e6J58+YYN24czp8/jwoVKihD7I4cOQJdXV2cPHkSJ0+eRFBQEDZs2IDExERMmjQJ5cqVQ3BwMC5duoTly5fj/PnziIuLw6pVq9C3b19UrVoV4eHhqFu3Lpo0aYLPP/8cM2fOxJgxY5TzcuvWrVi9ejUiIyNx4sQJjSDG/PnzUa5cOURFRSnXt4I8e/YMP/30Ezp27Agg+8H71tbW0NPTA5AddLC1tS1WO12yZAm++uor2Nraonbt2pgyZUq+4G5aWhpWrFiBQYMGaSxfs2YNXFxcYGdnhzFjxsDT0xNA9nmxfPlyZGVl4c6dO9i5c6eyr9rO2UePHuWrV8WKFWFtbY2//voLQPaQt5iYGKWcH3/8EatXr4aNjQ1sbGzQr18/Zft5paenY926dejatSs8PT1x+vRpTJ48GadOnVLyfPzxxxrf6blfOT8gFGb27NnK55FD2zWtqP06f/48Tpw4gYYNG8LHx0djWGSOgj6P1atXw8PDA82bN1d+kMlLpVJh1apV6NKlC6pXr45GjRrh999/17g+jBs3Dm5ubujRo4dynSQiehMxKEVEb5W8N6H+/v6IiopSXh9//PFL32bfvn0RGhqKxYsXY+DAgfnSY2JilP80X7x4UeO5EDlmzJgBd3d3WFpaomrVqsrzV3R0dLB27Vr8/fffaN26NQ4fPgwXFxfll/Uff/wR0dHR6N69Oy5dugRPT08cOnSowLoWdJP+8OFDHDp0CKNHj1aWVapUCQCwZ88eDB06FEB2L4cuXbpgz549Sr7evXsDyL45qVmzJmJjYwFk9yJbsmQJAOD3339HUFAQ9PT0sGPHDly5cgVNmjSBWq3Gu+++Cx0dHeXGrGbNmmjatCmA7BtVPT095Xj4+/ujVq1aALJ/9Q8LC8OoUaOUXgtXrlxBTEyMsl5OwKZly5YavXiGDRumtScSAAQEBKBv376YPXs2YmNjYWJiUmR5T548QeXKlbFt2zacPXsWERERmDx5Mnbu3Ilnz57BxcVFCRiGhYXhvffeAwBUqVIFHTp0KPDzKsi///6Ljh07Yv78+ahatepzr1+QzMxMZGZmIi0tDceOHcOqVavw8ccfawTgpk2bhn/++Qd//fUXPv30U43nrL1ombnz7t27F1999RVOnTqFVq1aoXv37sWqu4GBAaKiopCQkKD00rtw4UK+fB999BF+/PFHGBkZ4dSpU9iwYQPKli2rcbPn7++PTz/9FFWqVFGuHTY2Nhg7diy+/fZbPHz4ENbW1kraqVOn4O7ujtWrV+OLL74AAI3gdGZmJg4cOIDVq1cjIiICDx48yNfT7Pr167h8+bJG4MfQ0BAGBgZwdHTEqVOncOPGDaXHB5Ddnrt06YKoqCj4+/vj22+/RVRUFC5fvowmTZoo+X7//XccO3YMarVaa/10dHTyXRsyMjIgIjh16hR27NiB1q1bIykpCfPmzVPyqFQqZGVlISEhAbNnz4aOjg5q166Njh074smTJzh27JhGr6HC2Nvbw97eHkD289rs7e2VAJuxsbHyYPpTp04hKytLeYbY9OnTcffuXYgIwsLCMGjQIISGhuLo0aNKr5jatWtj69at8Pf3R1ZWFt577z0sX74cYWFhOHv2LB4+fAgDAwMlUBgWFobu3bvD1NQUKpVKuf49DxHBiBEjYGFhgVGjRj33+nlNmzYNU6dOxY0bN3Du3DmMHz8e58+f18izZs0a5bltub377rs4d+4cYmJisGzZMqW37vfff4+HDx/C09MTvXv3RrNmzZSAmbZzduLEiVrrtnHjRixevBienp6YPXs2GjVqpJTzyy+/oFevXrh9+zauX7+OP//8E7t379ZajqWlJT777DMMGTIEly9fxqxZs+Dr66uRZ9asWRrf6blfefPmNWXKFFy5cgVTp07Nd2y1XdMK26/MzEzExsbiwIED2LFjBxYsWIAtW7YU+XkMGzYM165dUwJuPXr0UHpG55aZmYlvvvkG69atw/Xr1xEWFqbxvLilS5fi4sWLOHPmDBo3box33nmn0H0nInqdMShFRG+ViIgIuLq6FpnP29u7wIe2Vq5cGVWqVMmXfu/ePVy+fBleXl4ay/v164c5c+bAyMgIDg4O+cpzdHRU/tP8119/KcNAchs7dizOnDmDS5cu4cSJE5g/f75GupOTE4YOHYoNGzagfv36ykNTAaB69ero378/li5dir59+yq/7GoTERGBypUr/6cZvnLfFAPQGIajq6ur9FwJDg7GX3/9hbS0NPzxxx8YMGAAgOybtRYtWmjcTNy6dUs5dgUNP8y7/Zyb6KNHjyrlXLlyRWMIX2H1LsjatWsxbdo0ZGRkoG3btli5cmWR5eX0FoqOjka7du2gr68PBwcHuLi4AMgeslfQkJXi1ivH7du3ERgYiC+//FJjmJutra3Gzc21a9dga2v7XGWXL18eJiYmyvAiOzs7NGzYEBEREfnyBgYGIjU1tcgHuT9Pmba2tvD09FSOW9++fXHy5ElkZGRo3b/cvU5yGBgYYPjw4TAxMcEvv/yCtLQ0jfQ+ffpAV1cXZcuWRadOnbBgwQI8e/ZMo/ffvn37EBISgnv37mntKeXl5YX4+HjlYd6VK1fG5cuXMWbMGPj4+GDMmDF49uwZPv/8c2W/2rVrBwsLC+jr66NXr154+vQpnj17pmxzyZIl8PT01Oh5ZmtrC29vb2zduhVHjx5FcnKy0jMJyB7Ke+7cOWXIa1hYmBLcKVu2rJIv54HlUVFRWL58ubIsZxtZWVmIj4+HiCjnTVRUFPT09NC1a1eUKVMG+vr6sLa21jhOOQ4cOICaNWtCRNC5c2e4uLigU6dOGoH6nKBf7n3OzcjICM7OzsjMzMSVK1eU68q9e/cQFxenDLcTERgZGSlt/uzZs5g9e3a+8jw9PdG0aVO0bdsWrq6uuHTpEnR1dXH37l2l16u+vj7atWunlFtQW3zeNgpk94i8efMmVq1apXym1apV0+jdJyK4ceNGke307t27WL9+vfIDQM2aNVG/fn0cPnxYI9+iRYvy9crJzc7ODr6+vkrwpGLFiggNDcXp06exe/duqFQqpe1pO2e1ffYA4OHhgR07duDUqVNYtmwZbt++rZTz888/K8PiK1eujLZt2xb4MPf169ejadOmGDZsGAYNGoRdu3blO19etKfUzJkzsW7dOmzfvr3AWTTzXtMK2y9bW1v06tULurq6qFixItq2bZvv+Gj7PKysrJTAc8OGDeHp6am1x11UVBRu376tBJfr1q2LqlWrKr3GqlWrBiD73Hz//fdx9epVZYg4EdGbhkEpInprbNy4EfPmzdPo7VOQTz/9FIsXL8bWrVuVZfHx8UovpvHjx2P06NFKr5/Hjx9jyJAh6Ny5s9JTJ4eNjQ2mTp2K77777j/vg62tLebOnYtJkyYhLS0Nt27d0rjxePDgAWJjY1GrVi08fPgQ27dvV4IzaWlpuHDhQr765Thz5gw++ugjfPbZZ/nSTExM0KRJE43Z3HKG+AUGBuLXX39Vlq1bt65Yz/iwsbFB3bp18fHHH6Ny5crKf+ZbtWqFPXv2aAzDO378uNYyHB0dkZGRgf379wPIng0qp5eYiYkJ/P39NWbCun37Nv799184OTkhMzNTGRqxZ88ejeFMBcnMzMQ///yjBBbeffddHD9+vMjy9PT0cP/+fbi6umLHjh1KOefOncP9+/fx3XffKUGZwMBA5fk4cXFxGgFGU1PTfD1ocouLi0NAQAA+++wz5UYvR9euXbFp0yYluDB//nz07NmzyH3Oq1evXsoMgPfv38fx48fh7u6OjIwMjWffHD9+HImJiQU+R6o4ZebVpk0b/Pvvv8oQ1W3btsHZ2Rn6+vpo3bo1Tp48iYsXLwLI7oGRs3/Xr19XZqzMysrC6tWr4e/vj/T0dLRq1QoHDhzAzZs3sWPHDgwYMAB2dna4dOkS5syZg9jYWMTHx2PXrl0YO3YsLl26hPPnzyM1NRWrV6/W2lMqMDAQfn5+6NSpE3bt2oUHDx5g8+bNCAoKwpo1azBz5kz4+fnhzp07mDhxIho0aIAtW7bg22+/BZD9fKyKFSviwIEDuHXrFhITE7FkyRJl+GCO7t274+7du0hJScHw4cNRq1YtJSh+5coVDBkyBPfv30ePHj2waNEiVKtWDTt37sSAAQM0buYTEhI0egEBUHr9devWDefOnUNiYiJCQkLw559/IisrC9u3b0fZsmWxa9cuZGVlKUO8PDw88n1uOb1A27Vrh4EDB6Jhw4a4c+cOVqxYoQQNq1evDpVKhS1btuDOnTtae9g5ODigY8eOmDt3LpKTk3H69Gn06dMH5cuXV4aqeXl5IT09Xek5lZGRoQxdCgwMxNy5czFu3Djs2bMHf/zxB27fvo3Lly/D3d0d+/fvR8WKFXH//n1cvXoVmZmZ2L59O7KysjBz5ky0adNGKWf16tVITU2FiGDhwoVKHU1NTZGWllZoD8EPP/wQV65cwfr16zV64FWuXBleXl7KUMq1a9eiatWqSg+xglhYWKBs2bLK7G93797FsWPHNH6AuXLlCk6cOIFevXpprJu7N9WdO3ewd+9epe3du3dPecZUTq/BESNGAMjuAbtv3z5lWPX27du1fvYANGY+/PXXX1G2bFk0b94cQHYALaftP3r0CPv27SvwhyN/f3/89ttviImJQadOnbBo0SLUqlVLo4fzi/SU+uGHH7BixQrs3r1b4xlSRV3TCtuv3r17K/uVlpaG8PBwjeNT0OeRM3QYyJ6ZMCoqKl/PNuD/A5g5vT2vXLmCf/75B46OjsjMzFRm2QWyzyNLS0tUqFBB6/4TEb32SvjB6kREL0316tWldu3a4u7uLrVq1ZL27dvL4cOHlfQlS5aIqampeHh4KK/u3bsr6cePH5cWLVpIjRo1xNXVVfz8/JTZjUREfv31V3FxcREnJyepWbOmjB07Vp48eaKx/dyz/+XIPbtO3tn3RLJnNcq9LO8seSIizZo1k5kzZ8q1a9ekZcuW4uDgIB4eHuLi4iLffvutiIikpKRIhw4dxMHBQdzd3cXZ2Vk+/vhjZca64OBgsbGxEQ8PD3FwcJCGDRvK77//XuDxvHXrlnTp0kXq1KkjHh4eMmHCBBHJnk2qc+fO4urqKi4uLjJ//vwCj0HeGen++usvASDz5s3T2Nbu3bulfv364u7uLk5OTtKrV68Cj9fBgwfF3d1dXF1dJTg4WBwdHZVtJiQkSFBQkLi4uIirq6v4+vpKVFSUiIgcPnxYPDw8xNXVVQYMGCAeHh5K3ebNmydfffVVvmPw5MkTady4sbi4uIiHh4cEBgbKzZs3iyzvr7/+koEDB4qIyLhx48TDw0N69OghQUFB0rFjR2U2NZHsmddatmwpzs7OEhgYKD169JCJEyeKSPYMemq1Wjw8POTrr78WEZE2bdpIRESEiIi89957YmxsrHFOL168WCl74cKFUrNmTalZs6YMHDhQmbEsr8mTJ0uVKlXEwMBAKlSoIFWqVJHExEQREbl79660b99eXFxcxMXFRX7++WcRyZ6BskGDBsqxadCggYSFhf2nMkVEvvrqK43zY+fOneLh4SHu7u7SuHFjOXPmjJK2ceNGcXR0lFq1aknHjh2Vma82bdokbm5u4ubmJi4uLtK3b1+5e/euXLt2TYKDg8XS0lL09fWlWrVq8sEHH8jdu3c1joetra0MGjRI2rRpI8bGxmJlZaXMGJYj7+x7KSkp8sEHH4iNjY1SdlBQkNy4cUOZ+XPt2rWiVqvFwMBAjI2NpVy5cuLq6io9evSQXbt2ibu7uxgaGgoAsbOzk8WLF+eb2e2PP/4QU1NTASCurq5y48YNEcmeIdTFxUUcHR2lXLlyYmBgIEZGRuLk5CTvvfeeRjv69ddfpVatWlK7dm1p1KiRAFDO3czMTBkxYoRUqFBBdHV1xcDAQPr16yfffvut2NrayujRo8XJyUnMzc3Fzs5OmUVMRGTUqFHKTGabNm0ST09PqVixoujr64uurq6Ym5uLk5OTMtPdpEmTxMrKSlQqlXh4eCiz73Xt2lWp7/3798Xf3190dXWlTJky0qpVK5kxY4a0a9dORLKv60ZGRuLu7i7u7u5Sp04d6d+/vwBQrokmJiair68vOjo6UrZsWZkwYYIkJSWJp6enxMfHy969e8XHx0caN24sX3zxhTRs2FDmzp2rMfvexIkTxd7eXry8vGT8+PFSvXp1Je29994TR0dH8fb2FhHN68mhQ4cEgDg5OSlttFOnTsq6Fy9elPr164uDg4N4e3trnN+Fzb63e/du8fLyUq71eWdR/fzzz6Vfv3751hsyZIg4OzsrbSp329u2bZvY29uLk5OT1K1bV/bv36+x7vTp08XZ2Vk5Z3NmqouIiJA2bdoo+UJCQsTBwUHs7e2lffv2yjkqkj2jXYMGDZRr/aeffqrMhFccqampsnr16mLnz+vmzZsCQGrWrKl8HvXq1RORoq9phe1XWlqa9OvXT5ydnaVOnTr5vk8K+jz69eunbM/Ly0tj3zZu3CiDBg1S3i9fvlxcXV2V778///xTRLJnSvT29lbSmjdvrnzvERG9iVQiBTxghIiI6DWQmpqKcuXKAcgeftihQwf8888/BQ7BKC1jx47FrVu3MGnSJNjb20NEEB0djSNHjmDIkCEFrjdmzBiYmJggJCSk5CpLz83a2hqTJ09WngdG/01ISAjs7OzQv3//Etvm4cOHMWrUKEyaNAktW7aEnp4e7t27hzVr1uCdd95BlSpVtK4XHR2Nd955R+OB569C//790b9/fzRr1uyVboeIiOh1old0FiIiotKzdu1azJo1CyICPT09LF269LULSAHZD6vftWsXxowZg+vXryMjIwNqtfqlPOSYSs/jx49x+PBhJCQkKENQ6c3UsGFDbNiwATNnzsSECROQnp6OihUronfv3vlmsiMiIqKSwZ5SRERERAX48ccfMXnyZAQHB+OHH34o7eq8NcLDw2Fubg61Wl3aVXltbNiwAWq1WutkGERERG8rBqWIiIiIiIiIiKjEcfY9IqK3lJ2dnTJrXA4fHx9lOu6QkBBUqlQJarUazs7O6NChg8aMPs2aNYOBgYHGFPRXr16Fjo4OOnXqpCybNGkSXF1d4eHhAScnJ4wdO1ZJU6lUcHNz05i2W9u01SEhIVCpVDh48KCy7KefftJ43sytW7fQs2dP1KxZEw4ODmjatKkyBff8+fOV8suXL48qVaoo73NmzPtfsWXLlpf6TBpt5aWkpOCbb76Br68vPDw80LhxY8yZM0fjXCtKSEgInjx5ojXtyZMn6NSpE2rXrg0PDw+0aNFCY5asxMREtG7dGg4ODnB1dcWBAwcK3M6iRYvg4OCAWrVqYfDgwcpsY3k9fvwYvXr1gr29PWrXro01a9b857SScuzYMXh4eKB27dpo3ry5MnuhNt988w1q1aqFWrVqYfz48cVKi4iIQIMGDWBsbKzR9gsybtw41K5dGy4uLvj8888LzRsaGvrKn6f2pp3DISEhCA0N1Vru85xvhZ0XDx48QFBQkPI5jRs3rtj7XZTnaZ9btmyBk5MTHBwc0KVLF6SkpAAArl27Bl1dXY3vjuLMoEpERG8eBqWIiN5i6enpWLRoUYHpQUFBiIqKwrlz52BkZISvv/5aI93d3R1Lly5V3i9evBje3t7K+zVr1mD79u2IiIjA6dOnER0djT59+miUcfDgQY1puwuattrOzg6fffaZ1rRHjx6hWbNm8PT0xNWrV3H58mVMmDAB7du3R3R0NIYNG6aU36FDB4wdO1Z57+/vX+RxKm3PcyNc2mJjY+Hv7w8LCwvs2rULp0+fxubNm5GWloY2bdogLS2tWOV8/fXXBd7QA8CQIUMQExOD06dPo2PHjhoPGB83bhzq16+Py5cvY8mSJejdu7fWYFNsbCy++uorHDx4EFeuXEFCQgIWLlyodXszZ86EoaEhrly5gp07d2LEiBFKAPVF04rr7t27z5U/t6ysLAQFBeHHH3/EpUuX0LZtW3z00Uda8x44cAArVqzAmTNncP78eezcuRNbt24tMs3a2ho//vgjZs2aVWR9IiMjsWbNGkRHR+PcuXMYNGjQC+/bq/ImncN5Ffd8K+q8GDhwIDw9PXHp0iWcO3euwHPm/v37eN5BFcXdt4cPH2LQoEHYsGEDLl++DBsbG0yePFlJL1eunMZ3R61atZ6rHkRE9GZgUIqI6C0WEhKCyZMn4/Hjx4Xm09HRgb+/P65fv66xPDg4GL///juA7JucVatWoXfv3kr6v//+i/Lly8PIyAgAoKenBw8Pjxeqa4cOHZCRkYH169fnS1uxYgUsLCw0glYBAQEYMGAApk+f/tzbWrJkCdRqNTw8PODj46PMqrV06VK4u7vD3d0d7dq1U3oWhIaGIjAwEL169YKbmxt8fHxw9epVAECLFi00eiuEh4fD09MTQPbMgYMHD0a9evXg7u6OIUOG4OnTpwCye6J9+OGH8PPzQ8uWLZGRkYERI0agdu3aqF+/PkaPHq3Ru2Pp0qXw9fWFl5cXmjRpgtOnTwOAsp6DgwPq1atX7J5hd+7cQcuWLeHm5gZ3d3cMGDCgyPJEBMHBwVi8eDFGjhwJMzMzAIC5uTk+++wzDBgwQOOmcsGCBXBwcICnpycmT54MlUoFABg2bBgAoHHjxlCr1Rq98QDAyMgIbdu2VfLXr19fY+azv/76Symjbt26sLGxwf79+/Pt45o1a9ChQwdYWVlBpVJh2LBhWLFihdbjsWrVKqXMGjVqoFmzZsq5+KJphUlMTMRPP/2EBg0a/KfATWRkJPT09JTg69ChQ7F582atwZJVq1ahb9++KFu2LAwNDTFw4EDleBSWVrVqVdSrVw+GhoZF1kdfXx/3799HUlISAMDe3r7Y+3Lt2jWYm5vjq6++gpeXFxwcHHD48GF8/PHHUKvVcHV1RXR0tJL/RdrEm3YO51Xc862w8+LKlSs4ceIEPvnkEyV/QQ96X716NRwcHPD555/j7NmzRdbvefZt+/bt8PT0hJOTEwBgxIgRBbZPIiJ6ezEoRUT0FvPw8IC/v3+RPRzS09OxZcsW9OjRQ2N5tWrVYGVlhWPHjmHXrl3w8fGBhYWFkt6zZ0/ExsaiZs2a6NevHxYvXpyvl0HOTZtarS6015JKpcK0adPwxRdf4NmzZxppJ0+ehJ+fX751/Pz8EBkZWei+5RUeHo5JkyZh+/btOH36NA4cOIDKlSsjOjoaY8eOxfbt23HmzBk0aNBAo2dDREQEpkyZgrNnzyIwMBDfffcdAGDAgAEaQ22WLFmCgQMHAgBGjx6Nxo0b4/jx4zh9+jSysrIwe/ZsJe+lS5dw4MAB7N27FwsXLsTly5dx7tw5HDx4EGfOnFHyHT58GCtWrMCBAwdw8uRJfPvtt0pwcOHChYiJicG5c+dw6NAhnDx5UmN/1Wo1bt++ne84LFu2DDVq1MDZs2dx5swZfP/990WWFx4eDi8vL3h4eODMmTNo3Lgx/Pz8EBISglGjRqF3797KEMzo6GhMnDgRBw4cwKlTpzTOi/nz5wP4/150lStXLvQzmz17Njp27AgAuHfvHjIyMjRuou3s7HDjxo186924cQPVq1cvMl9ReV80La/U1FT88ccfaN26NZo0aYL4+Hj8+uuv2Lhxo5KnR48eGkOWcr9u3rxZZL3LlSsHU1NTrZ/5y9qPwpiYmKB8+fJo2bIl7t+//9zrJycnw9vbGydPnsS4cePQqlUrdOjQAVFRUQgODlZ6c75om3jTzuG8ivs5FXZenD9/HlWrVsXw4cPh7e2Nli1b4tSpU1q3N3ToUBw9ehS2trZ4//334eHhgSlTpiA2NlZr/v/aPuPi4pSeo48ePULdunXh5eWFSZMm5fteICKitwODUkREb7nJkydj9uzZWod4/Pnnn1Cr1ahYsSIePHiA7t2758szcOBALFq0CIsWLVKCLTmsrKxw9uxZ/Pnnn3Bzc8Mvv/yCBg0aKL2BAM3he0X14gkICEC1atWwePHiF9zbom3duhV9+/aFtbU1AMDY2BjGxsbYt28fWrdujSpVqgDI/tV+7969yo2Qn58fatSoofyd83yTzp074+jRo4iLi8PDhw+xZcsW5eZ4w4YNmDFjBtRqNTw9PZVhZDn69OkDfX19AEBYWJjyXl9fH8HBwUq+jRs34vTp0/D19YVarcYHH3yA+/fvIy0tDWFhYejXrx8MDAxgYGCQ7zOKioqCjY1NvuNQv359bN++HaNHj8bGjRtRtmxZpR4FlRcZGakEFocMGYKpU6fi77//Rnx8PJKTkwFkD/W6e/cu9u7dizZt2ijHefjw4c//YQGYMmUKrly5gqlTp77Q+q+L27dvw9LSEnPmzEFISAguXryIb775Bi4uLhr5Vq1apTFkKferWrVqpVT74klPT0fLli2xY8cO9OnTB4GBgbh//z4SEhJQtWrVYpVhZGSkPLfKx8cHJiYmyjlXr149XL58GcCLtwmew9nDhY8fP46ePXsiMjISH3/8Md55550Chw9WrFgRw4cPx/79+7F9+3Zcu3YNtWrVwpIlS15ZHa2trXHr1i1ERERgz549OHjwoBI4JyKitwuDUkREbzk7Ozv07t0b33zzTb60nGdKXb9+Henp6Zg4cWK+PJ06dcLOnTtx+vRpBAQE5EvX1dVFgwYNMHbsWBw+fBixsbEaQ2ye17Rp0zBp0iSNIYdeXl44cuRIvrxHjhyBl5fXC2+rMDnDbnLkDFEEsvc559f8MmXKoFu3bli6dClWr16N5s2bK8/NEhGsXbtWCSrExMRgwYIFSjkmJibF2n7OkKPcAYq4uDiUKVOmyHoXxM/PD1FRUfD19cW6detQt25drT0R8panq6sLAEhISECjRo2gUqmUHiBA9jNocveme9565TZz5kysW7cO27dvh7GxMQCgQoUK0NPTQ3x8vJLv2rVrsLW1zbe+ra2txpDUgvIVlfdF03KztLTEqlWr4ODggKCgILz//vs4fPhwvuf1PG9PqbzbT01NRXJystZA5MvYj8KcOXMGWVlZsLe3x5gxYxAcHIwWLVrgp59+yhcsLUjuIYK6uroFtrv/0ibepHM4r+J+ToWdF7a2tqhSpYoSnGvTpg2ePn2ab/h2brGxsZg2bRratWuHixcv4ueff9b60Pv/2j6tra2hp6cHQ0NDpfdZ+fLlMXDgQI2JMIiI6O3BoBQR0f+AL7/8EsuWLdM6pAfI/k//b7/9hp9//hlxcXEaaUZGRpg1axbmzJkDHR3Nr40TJ05ozIh08eJFZGRk/KceHV5eXmjUqBHmzZunLOvVqxfu3bunDJkDgL1792Lx4sUas/0VR/v27bFs2TJlPx8/fozHjx/D398fO3bsUI7R/PnzERAQoNzAFmbAgAFYsmQJQkNDNW6+O3XqhO+++065kX7w4IFGT6ncmjdvjuXLlyMjIwMZGRn4448/lLQOHTpg2bJlyhCYrKwsnDhxAgAQGBiIZcuWISMjA0+fPi1274XY2FiYmJige/fumDt3Li5duoSHDx8WWp5arVaeDWNpaYljx45BRLB582YAwMqVK+Hk5ARdXV00b94cO3bsUG5Oc4Y75ShXrpzSM0WbH374AStWrMDu3bthbm6ukdatWzelvIiICNy6dQtNmzbNV0bXrl2xadMmxMfHQ0Qwf/589OzZU+v2cpcZGxuL8PBw5ab7RdNy09XVRfv27ZWHifv5+WHKlClwcHDQOK+ft6eUt7c3MjIylF6ICxYsQPv27TWCObn3cenSpXj06BHS09OxePFi5XgUllZctWvXRnJyMrZt2wYA+PDDD2Fvb4+pU6di8ODBz1VWUV60Tbxp53BexT3fCjsvvL29YWpqqgwRPn78OERE6/kVFhYGPz8/dOnSBTo6Oti4cSMOHDiA4cOHaw3cPc++tW7dGidPnsTFixcBAL/88otyziUmJio9t9LT07Fu3TrlWX1ERPR20SvtChAR0atXsWJFfPjhh5gwYUKBeTw9PdGtWzdMmTIFc+fO1Ujr0qWL1nXu3buH999/H0lJSShTpgx0dXWxfPlyVKpUScnTuHFjjcDOqlWr4OjoWGh9v/32W+XhtwBQtmxZhIeHY/To0ahRowb09PRgbW2NTZs2wd3dvdCy8mrSpAkmTpyIVq1aQaVSwcDAAGvWrIGrqytmzJiB1q1bA8h+ntavv/5arDLr1asHXV1dXLlyBS1btlSWz5o1C+PGjYNarYaOjg709PQwffp0rQ9/Hjp0KM6ePYs6derAwsICPj4+SoCscePGmD59Ojp37ozMzEw8ffoU7dq1g4+PDwYPHozo6GhlvcaNG2s8Z0utVmPbtm35es6Eh4fjhx9+UHqfzJgxA2ZmZoWW17x5c0yYMAEXLlzAwoULMXLkSGRmZqJVq1bYtm0batasqQyxcXV1RUhICBo3bgwTE5N859Do0aPRokULGBsbY9euXTh69Cg2bdqE3377Df/++y9Gjx6NmjVrKr05DA0NcezYMQDAd999h759+8LBwQEGBgZYtmyZMgwyt5o1a+Lrr79Gw4YNAWQ/XH7o0KEAsofTtW3bFlFRUQCAsWPHYuDAgahVqxZ0dXXx008/oWLFiv8prSBly5ZFUFAQgoKCcO/ePfz999+F5i+Mjo4Oli1bhqFDh+LJkyewsbHRmDGzbdu2mDRpEnx8fNCsWTP06NEDbm5uALJ7Zb3zzjvKsSkoLSYmBgEBAXj8+DHS0tJQtWpVfPHFFxgxYoRGXczMzLB582aMHTsWn332GYyMjNC0aVNMnz4dbdu2xd69ezWuDf/Fi7aJN+0czquw823+/Pm4ffs2Jk2aVOh5oVKp8Pvvv2Pw4MFIS0uDoaEh1q5dq/VB9uXKlcPixYvh7Oxc7M+msH2bMGECbGxsMGzYMJQrVw6//fYbOnXqhMzMTLi6uioTaxw6dAgTJkxQrk/NmzfH+PHji10HIiJ6c6jkeed5JSIiolciNTUV5cqVQ0ZGBoKCguDt7a0x4+DrICYmBr1798bYsWPRuXNnGBoaIjU1FRs3blRmSNPm4cOHKFeu3HNPL09vt9DQUFy7dg0hISElts3X/RwOCQmBnZ0d+vfv/0q3Q0RE9Drg8D0iIqLXRGBgINRqNdzc3GBqaooPP/ywtKuUj6OjI3bv3o1z586hadOmcHd3R6tWrRAfH6+1BxjR64bnMBER0euDPaWIiIiIqFRERUUhKSkJzZo1K+2qvDbCw8Nhbm4OtVpd2lUhIiJ65RiUIiIiIiIiIiKiEsfhe0REREREREREVOIYlCIiIiIiIiIiohLHoBQREREREREREZU4BqWIiIiIiIiIiKjEMShFREREREREREQljkEpIiIiIiIiIiIqcQxKERERERERERFRiWNQioiIiIiIiIiIStz/AVeh8mkqaB1GAAAAAElFTkSuQmCC", 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", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Setup ModelExecutor\n", + "model_executor = ModelExecutor(\n", + " mmmdata=mmm_data,\n", + " holidays_data=holidays_data,\n", + " hyperparameters=hyperparameters,\n", + " calibration_input=None, # Add calibration input if available\n", + " featurized_mmm_data=featurized_mmm_data,\n", + ")\n", + "\n", + "# Setup TrialsConfig\n", + "trials_config = TrialsConfig(iterations=2000, trials=5) # Set to the number of cores you want to use\n", + "\n", + "print(\n", + " f\">>> Starting {trials_config.trials} trials with {trials_config.iterations} iterations each using {NevergradAlgorithm.TWO_POINTS_DE.value} nevergrad algorithm on x cores...\"\n", + ")\n", + "\n", + "# Run the model\n", + "\n", + "output_models = model_executor.model_run(\n", + " trials_config=trials_config,\n", + " ts_validation=False, # changed from True to False -> deacitvate\n", + " add_penalty_factor=False,\n", + " rssd_zero_penalty=True,\n", + " cores=8,\n", + " nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE,\n", + " intercept=True,\n", + " intercept_sign=\"non_negative\",\n", + " model_name=Models.RIDGE,\n", + ")\n", + "print(\"Model training complete.\")\n", + "\n", + "# TODO fix graph outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "decomp_rssd: Shape = ()\n", + "decomp_spend_dist: Shape = (10000, 34)\n", + "elapsed: No shape attribute, Type = float\n", + "elapsed_accum: No shape attribute, Type = float\n", + "iter_ng: No shape attribute, Type = int\n", + "iter_par: No shape attribute, Type = int\n", + "lambda_: No shape attribute, Type = float\n", + "lambda_hp: No shape attribute, Type = float\n", + "lambda_max: Shape = ()\n", + "lambda_min_ratio: No shape attribute, Type = float\n", + "lift_calibration: No shape attribute, Type = NoneType\n", + "mape: No shape attribute, Type = float\n", + "nrmse: Shape = ()\n", + "pos: No shape attribute, Type = bool\n", + "result_hyp_param: Shape = (2000, 34)\n", + "rsq_test: No shape attribute, Type = float\n", + "rsq_train: No shape attribute, Type = float\n", + "rsq_val: No shape attribute, Type = float\n", + "sol_id: No shape attribute, Type = str\n", + "train_size: No shape attribute, Type = float\n", + "trial: No shape attribute, Type = int\n", + "x_decomp_agg: Shape = (24000, 29)\n" + ] + } + ], + "source": [ + "# Assuming model_outputs.trials[0] is already an object from your model\n", + "trial = output_models.trials[0]\n", + "\n", + "\n", + "# Function to check if an object has a 'shape' attribute\n", + "def has_shape(obj):\n", + " return hasattr(obj, \"shape\")\n", + "\n", + "\n", + "# Get all attribute names of the object and print their shapes if they have a 'shape' attribute\n", + "attribute_names = [attr for attr in dir(trial) if not callable(getattr(trial, attr)) and not attr.startswith(\"__\")]\n", + "for attribute_name in attribute_names:\n", + " attribute_value = getattr(trial, attribute_name)\n", + " if has_shape(attribute_value):\n", + " print(f\"{attribute_name}: Shape = {attribute_value.shape}\")\n", + " else:\n", + " print(f\"{attribute_name}: No shape attribute, Type = {type(attribute_value).__name__}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "decomp_rssd: Shape = ()\n", + "decomp_spend_dist: Shape = (10000, 34)\n", + " Columns: Index(['rn', 'coef', 'xDecompAgg', 'xDecompPerc', 'xDecompMeanNon0',\n", + " 'xDecompMeanNon0Perc', 'xDecompAggRF', 'xDecompPercRF',\n", + " 'xDecompMeanNon0RF', 'xDecompMeanNon0PercRF', 'pos', 'mean_spend',\n", + " 'total_spend', 'spend_share', 'spend_share_refresh', 'effect_share',\n", + " 'effect_share_refresh', 'rsq_train', 'rsq_val', 'rsq_test',\n", + " 'nrmse_train', 'nrmse_val', 'nrmse_test', 'nrmse', 'decomp.rssd',\n", + " 'mape', 'lambda', 'lambda_hp', 'lambda_max', 'lambda_min_ratio',\n", + " 'solID', 'trial', 'iterNG', 'iterPar'],\n", + " dtype='object')\n", + "elapsed: No shape attribute, Type = float\n", + "elapsed_accum: No shape attribute, Type = float\n", + "iter_ng: No shape attribute, Type = int\n", + "iter_par: No shape attribute, Type = int\n", + "lambda_: No shape attribute, Type = float\n", + "lambda_hp: No shape attribute, Type = float\n", + "lambda_max: Shape = ()\n", + "lambda_min_ratio: No shape attribute, Type = float\n", + "lift_calibration: No shape attribute, Type = NoneType\n", + "mape: No shape attribute, Type = float\n", + "nrmse: Shape = ()\n", + "pos: No shape attribute, Type = bool\n", + "result_hyp_param: Shape = (2000, 34)\n", + " Columns: Index(['facebook_S_thetas', 'facebook_S_alphas', 'facebook_S_gammas',\n", + " 'print_S_thetas', 'print_S_alphas', 'print_S_gammas', 'tv_S_thetas',\n", + " 'tv_S_alphas', 'tv_S_gammas', 'search_S_thetas', 'search_S_alphas',\n", + " 'search_S_gammas', 'ooh_S_thetas', 'ooh_S_alphas', 'ooh_S_gammas',\n", + " 'newsletter_thetas', 'newsletter_alphas', 'newsletter_gammas',\n", + " 'train_size', 'rsq_train', 'rsq_val', 'rsq_test', 'nrmse_train',\n", + " 'nrmse_val', 'nrmse_test', 'nrmse', 'decomp.rssd', 'mape', 'lambda',\n", + " 'solID', 'trial', 'iterNG', 'iterPar', 'ElapsedAccum'],\n", + " dtype='object')\n", + "rsq_test: No shape attribute, Type = float\n", + "rsq_train: No shape attribute, Type = float\n", + "rsq_val: No shape attribute, Type = float\n", + "sol_id: No shape attribute, Type = str\n", + "train_size: No shape attribute, Type = float\n", + "trial: No shape attribute, Type = int\n", + "x_decomp_agg: Shape = (24000, 29)\n", + " Columns: Index(['rn', 'coef', 'xDecompAgg', 'xDecompPerc', 'xDecompMeanNon0',\n", + " 'xDecompMeanNon0Perc', 'xDecompAggRF', 'xDecompPercRF',\n", + " 'xDecompMeanNon0RF', 'xDecompMeanNon0PercRF', 'pos', 'train_size',\n", + " 'rsq_train', 'rsq_val', 'rsq_test', 'nrmse_train', 'nrmse_val',\n", + " 'nrmse_test', 'nrmse', 'decomp.rssd', 'mape', 'lambda', 'lambda_hp',\n", + " 'lambda_max', 'lambda_min_ratio', 'solID', 'trial', 'iterNG',\n", + " 'iterPar'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "# Assuming model_outputs.trials[0] is already an object from your model\n", + "trial = output_models.trials[0]\n", + "\n", + "\n", + "# Function to check if an object has a 'shape' attribute\n", + "def has_shape(obj):\n", + " return hasattr(obj, \"shape\")\n", + "\n", + "\n", + "# Get all attribute names of the object and print their shapes if they have a 'shape' attribute\n", + "attribute_names = [attr for attr in dir(trial) if not callable(getattr(trial, attr)) and not attr.startswith(\"__\")]\n", + "for attribute_name in attribute_names:\n", + " attribute_value = getattr(trial, attribute_name)\n", + " if has_shape(attribute_value):\n", + " print(f\"{attribute_name}: Shape = {attribute_value.shape}\")\n", + " # Check if the attribute is a multi-dimensional array with more than one column\n", + " if len(attribute_value.shape) > 1 and attribute_value.shape[1] > 1:\n", + " try:\n", + " # Attempt to print column names if it's a structured array or DataFrame\n", + " columns = (\n", + " attribute_value.columns if hasattr(attribute_value, \"columns\") else attribute_value.dtype.names\n", + " )\n", + " print(f\" Columns: {columns}\")\n", + " except AttributeError:\n", + " print(\" No column names available.\")\n", + " else:\n", + " print(f\"{attribute_name}: No shape attribute, Type = {type(attribute_value).__name__}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best model ID: 2_1962_1\n" + ] + } + ], + "source": [ + "best_model_id = output_models.select_id\n", + "print(f\"Best model ID: {best_model_id}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image, display\n", + "import base64\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "\n", + "\n", + "# 1. Display the MOO Distribution Plot\n", + "if \"moo_distrb_plot\" in output_models.convergence:\n", + " moo_distrb_plot = output_models.convergence[\"moo_distrb_plot\"]\n", + " display(Image(data=base64.b64decode(moo_distrb_plot)))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 2. Display the MOO Cloud Plot\n", + "if \"moo_cloud_plot\" in output_models.convergence:\n", + " moo_cloud_plot = output_models.convergence[\"moo_cloud_plot\"]\n", + " display(Image(data=base64.b64decode(moo_cloud_plot)))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DECOMP.RSSD converged: sd@qt.20 16316.603 <= 46763.906 & |med@qt.20| 87396.98 <= 239675.85\n", + "NRMSE NOT converged: sd@qt.20 0.000 <= 0.001 & |med@qt.20| 0.06 > 0.05\n" + ] + } + ], + "source": [ + "# 3. Print convergence messages\n", + "if \"conv_msg\" in output_models.convergence:\n", + " for msg in output_models.convergence[\"conv_msg\"]:\n", + " print(msg)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 4. Display time series validation and convergence plots\n", + "if \"ts_validation_plot\" in output_models.convergence:\n", + " ts_validation_plot = output_models.convergence[\"ts_validation_plot\"]\n", + " display(Image(data=base64.b64decode(ts_validation_plot)))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best model ID: 2_1962_1\n" + ] + } + ], + "source": [ + "best_model_id = output_models.select_id\n", + "print(f\"Best model ID: {best_model_id}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mytestenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/tutorial6_allocator.ipynb b/python/tests/component_tutorials/tutorial6_allocator.ipynb new file mode 100644 index 000000000..48b85bc8d --- /dev/null +++ b/python/tests/component_tutorials/tutorial6_allocator.ipynb @@ -0,0 +1,557 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Robyn Budget Allocator Demo\n", + "\n", + "This notebook demonstrates how to use the Python implementation of Robyn's budget allocator.\n", + "It shows how to:\n", + "1. Load and prepare data\n", + "2. Configure the allocator\n", + "3. Run optimization scenarios\n", + "4. Analyze and visualize results\n", + "\n", + "## Step 1: Load Exported R Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Step 1: Setup and Import\n", + "import sys\n", + "import os\n", + "import pandas as pd\n", + "import numpy as np\n", + "from typing import Dict, Any, Union, List\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")\n", + "\n", + "# Import necessary Robyn classes\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.modeling.entities.modeloutputs import ModelOutputs\n", + "from robyn.data.entities.hyperparameters import Hyperparameters\n", + "from robyn.modeling.pareto.pareto_optimizer import ParetoResult\n", + "from utils.data_mapper import (\n", + " load_data_from_json,\n", + " import_input_collect,\n", + " import_output_collect,\n", + " import_output_models,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load data from JSON exported from R\n", + "# raw_input_collect = load_data_from_json(\n", + "# \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/dh_Pareto_InputCollect.json\"\n", + "# )\n", + "# raw_output_collect = load_data_from_json(\n", + "# \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/dh_Allocator_OutputCollect.json\"\n", + "# )\n", + "\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_forAllocator_2000_iterations_5_trials_InputCollect.json\"\n", + ")\n", + "raw_output_collect = load_data_from_json(\n", + " \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/test_forAllocator_2000_iterations_5_trials_OutputCollect.json\"\n", + ")\n", + "\n", + "# raw_input_collect = load_data_from_json(\n", + "# \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/tutorials/data/Allocator_InputCollect.json\"\n", + "# )\n", + "# raw_output_collect = load_data_from_json(\n", + "# \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/tutorials/data/Allocator_OutputCollect.json\"\n", + "# )\n", + "# raw_output_models = load_data_from_json(\n", + "# \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/tutorials/data/Allocator_OutputModels.json\"\n", + "# )\n", + "\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "r_output_collect = import_output_collect(raw_output_collect)\n", + "# python_model_outputs = import_output_models(raw_output_models)\n", + "\n", + "# Extract individual components\n", + "mmm_data = r_input_collect[\"mmm_data\"]\n", + "featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "holidays_data = r_input_collect[\"holidays_data\"]\n", + "hyperparameters = r_input_collect[\"hyperparameters\"]\n", + "pareto_result = r_output_collect[\"pareto_result\"]\n", + "# Print data summary\n", + "print(f\"Data loaded successfully:\")\n", + "print(\n", + " f\"- Data timeframe: {mmm_data.data[mmm_data.mmmdata_spec.date_var].min()} to {mmm_data.data[mmm_data.mmmdata_spec.date_var].max()}\"\n", + ")\n", + "print(\n", + " f\"- Number of paid media channels: {len(mmm_data.mmmdata_spec.paid_media_spends)}\"\n", + ")\n", + "print(f\"- Channels: {mmm_data.mmmdata_spec.paid_media_spends}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 2: Set up Budget Allocator\n", + "\n", + "Initialize the budget allocator with the selected model and data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# select_model = r_output_collect[\"pareto_result\"].pareto_solutions[\n", + "# 0\n", + "# ] # Taking first solution as example\n", + "# print(f\"Selected model: {select_model}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in raw_output_collect[\"clusters\"][\"models\"]:\n", + " print(i[\"solID\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Override\n", + "select_model = \"3_216_3\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "r_pareto_result = r_output_collect[\"pareto_result\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "# Set display options to show all rows and columns\n", + "pd.set_option(\"display.max_rows\", None)\n", + "pd.set_option(\"display.max_columns\", None)\n", + "# Assuming r_dt_hyppar is your DataFrame\n", + "r_dt_hyppar = r_pareto_result.result_hyp_param[\n", + " r_pareto_result.result_hyp_param[\"solID\"] == select_model\n", + "]\n", + "print(r_dt_hyppar)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 3: Run Different Optimization Scenarios\n", + "\n", + "### Scenario 1: Default Max Response" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Hyperparameters raw output:\", hyperparameters)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming `hyperparameters` is an instance of the `Hyperparameters` class\n", + "\n", + "# Iterate over each channel and its hyperparameters\n", + "for channel, params in hyperparameters.hyperparameters.items():\n", + " print(f\"Channel: {channel}\")\n", + " print(f\" Thetas: {params.thetas}\")\n", + " print(f\" Shapes: {params.shapes}\")\n", + " print(f\" Scales: {params.scales}\")\n", + " print(f\" Alphas: {params.alphas}\")\n", + " print(f\" Gammas: {params.gammas}\")\n", + " print(f\" Penalty: {params.penalty}\")\n", + " print()\n", + "\n", + "# Print other attributes of the Hyperparameters class\n", + "print(f\"Adstock: {hyperparameters.adstock}\")\n", + "print(f\"Lambda: {hyperparameters.lambda_}\")\n", + "print(f\"Train Size: {hyperparameters.train_size}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(hyperparameters.adstock.value)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.allocator.entities.allocation_params import AllocatorParams\n", + "from robyn.allocator.entities.allocation_result import (\n", + " AllocationResult,\n", + " OptimOutData,\n", + " MainPoints,\n", + ")\n", + "from robyn.allocator.entities.optimization_result import OptimizationResult\n", + "from robyn.allocator.entities.constraints import Constraints\n", + "from robyn.allocator.optimizer import BudgetAllocator\n", + "from robyn.allocator.constants import (\n", + " SCENARIO_MAX_RESPONSE,\n", + " ALGO_SLSQP_AUGLAG,\n", + " CONSTRAINT_MODE_EQ,\n", + " DEFAULT_CONSTRAINT_MULTIPLIER,\n", + " DATE_RANGE_ALL,\n", + ")\n", + "\n", + "\n", + "# Create allocator parameters matching R Example 1\n", + "allocator_params = AllocatorParams(\n", + " scenario=SCENARIO_MAX_RESPONSE,\n", + " total_budget=None, # When None, uses total spend in date_range\n", + " target_value=None,\n", + " date_range=\"all\",\n", + " channel_constr_low=[0.7], # Single value for all channels\n", + " channel_constr_up=[1.2, 1.5, 1.5, 1.5, 1.5], # Different values per channel\n", + " channel_constr_multiplier=3.0,\n", + " optim_algo=\"SLSQP_AUGLAG\",\n", + " maxeval=100000,\n", + " constr_mode=CONSTRAINT_MODE_EQ,\n", + " plots=True,\n", + ")\n", + "# 0.7 is the lower bound\n", + "# 1.2 is the upper bound for the first channel, and so on\n", + "# $70 - $150\n", + "# let's say $100, budget allocator is about increasing decreasing media budget, advertiser wants to know how much to spend on each channel\n", + "# you cannot be infinitely increasing budget, so you have to set constraints\n", + "# 0.7 - 1.2 means you can increase by 20% or decrease by 30%\n", + "# Boundedx3 = 3x increase or decrease, so 90% lower bound, 150% upper bound.\n", + "\n", + "print(\"\\nInitial constraints:\")\n", + "for channel, low, up in zip(\n", + " mmm_data.mmmdata_spec.paid_media_spends,\n", + " [0.7] * len(mmm_data.mmmdata_spec.paid_media_spends), # Expand single value\n", + " [1.2, 1.5, 1.5, 1.5, 1.5], # Per channel values\n", + "):\n", + " print(f\"{channel}: {low:.1f}x - {up:.1f}x\")\n", + "\n", + "# Initialize budget allocator\n", + "max_response_allocator = BudgetAllocator(\n", + " mmm_data=mmm_data,\n", + " featurized_mmm_data=featurized_mmm_data,\n", + " hyperparameters=hyperparameters,\n", + " pareto_result=pareto_result,\n", + " select_model=select_model,\n", + " params=allocator_params,\n", + ")\n", + "\n", + "## Step 3: Run Optimization\n", + "max_response_result = max_response_allocator.optimize()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Step 4: Analyze Results\n", + "print(\"\\nOptimization Results Summary:\")\n", + "print(\"-\" * 50)\n", + "print(f\"Model ID: {select_model}\")\n", + "print(f\"Scenario: {max_response_result.scenario}\")\n", + "print(f\"Use case: {max_response_result.usecase}\")\n", + "\n", + "results_df = pd.DataFrame(\n", + " {\n", + " \"Channel\": max_response_result.dt_optimOut.channels,\n", + " \"Initial Spend\": max_response_result.dt_optimOut.init_spend_unit,\n", + " \"Optimized Spend\": max_response_result.dt_optimOut.optm_spend_unit,\n", + " \"Spend Change %\": (\n", + " max_response_result.dt_optimOut.optm_spend_unit\n", + " / max_response_result.dt_optimOut.init_spend_unit\n", + " - 1\n", + " )\n", + " * 100,\n", + " \"Initial Response\": max_response_result.dt_optimOut.init_response_unit,\n", + " \"Optimized Response\": max_response_result.dt_optimOut.optm_response_unit,\n", + " \"Response Lift %\": (\n", + " max_response_result.dt_optimOut.optm_response_unit\n", + " / max_response_result.dt_optimOut.init_response_unit\n", + " - 1\n", + " )\n", + " * 100,\n", + " }\n", + ")\n", + "\n", + "print(\"\\nDetailed Results:\")\n", + "print(results_df.round(2))\n", + "\n", + "# Print additional diagnostics\n", + "print(\"\\nOptimization Parameters:\")\n", + "print(f\"Total budget: {max_response_allocator.constraints.budget_constraint:,.2f}\")\n", + "print(\"Bound multiplier:\", max_response_allocator.params.channel_constr_multiplier)\n", + "print(\"\\nConstraint Violations:\")\n", + "violations = np.sum(\n", + " np.abs(\n", + " max_response_result.dt_optimOut.optm_spend_unit\n", + " - max_response_allocator.allocator_data_preparer.init_spend_unit\n", + " )\n", + ")\n", + "print(f\"Total allocation adjustment: {violations:,.2f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(max_response_result.dt_optimOut)\n", + "print(max_response_result.mainPoints)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.visualization.allocator_visualizer import (\n", + " AllocatorPlotter,\n", + ")\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "# Initialize plotter with just the essential data\n", + "plotter = AllocatorPlotter(\n", + " allocation_result=max_response_result,\n", + " budget_allocator=max_response_allocator\n", + ")\n", + "\n", + "# Generate all plots\n", + "plots = plotter.plot_all(display_plots=False, export_location=None)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Scenario 3: Target Efficiency\n", + "Optimize allocation based on target ROI/CPA." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# from robyn.allocator.constants import (\n", + "# SCENARIO_TARGET_EFFICIENCY, # Import this instead of SCENARIO_MAX_RESPONSE\n", + "# ALGO_SLSQP_AUGLAG,\n", + "# CONSTRAINT_MODE_EQ,\n", + "# DEFAULT_CONSTRAINT_MULTIPLIER,\n", + "# DATE_RANGE_ALL,\n", + "# )\n", + "\n", + "# # Create allocator parameters matching R Example 3 for target efficiency\n", + "# allocator_params = AllocatorParams(\n", + "# scenario=SCENARIO_TARGET_EFFICIENCY, # Change scenario\n", + "# total_budget=None, # When None, it will use all available dates\n", + "# # target_value is optional - when None:\n", + "# # - For revenue (ROAS): defaults to 0.8x of initial ROAS\n", + "# # - For conversion (CPA): defaults to 1.2x of initial CPA\n", + "# target_value=None,\n", + "# date_range=\"all\",\n", + "# # Use default constraints\n", + "# channel_constr_low=[\n", + "# 0.1\n", + "# ], # Lower constraint for target_efficiency typically starts at 0.1\n", + "# channel_constr_up=[\n", + "# 10\n", + "# ], # Upper constraint for target_efficiency typically goes up to 10\n", + "# channel_constr_multiplier=3.0,\n", + "# optim_algo=\"SLSQP_AUGLAG\",\n", + "# maxeval=100000,\n", + "# constr_mode=CONSTRAINT_MODE_EQ,\n", + "# plots=True,\n", + "# )\n", + "\n", + "# # Initialize and run allocator same as before\n", + "# target_efficiency_allocator = BudgetAllocator(\n", + "# mmm_data=mmm_data,\n", + "# featurized_mmm_data=featurized_mmm_data,\n", + "# hyperparameters=hyperparameters,\n", + "# pareto_result=r_output_collect[\"pareto_result\"],\n", + "# select_model=select_model,\n", + "# params=allocator_params, # or allocator_params_custom\n", + "# )\n", + "\n", + "# # Run optimization\n", + "# target_efficiency_result = target_efficiency_allocator.optimize()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# ## Step 4: Analyze Results\n", + "# print(\"\\nOptimization Results Summary:\")\n", + "# print(\"-\" * 50)\n", + "# print(f\"Model ID: {select_model}\")\n", + "# print(f\"Scenario: {target_efficiency_result.scenario}\")\n", + "# print(f\"Use case: {target_efficiency_result.usecase}\")\n", + "\n", + "# results_df = pd.DataFrame(\n", + "# {\n", + "# \"Channel\": target_efficiency_result.dt_optimOut.channels,\n", + "# \"Initial Spend\": target_efficiency_result.dt_optimOut.init_spend_unit,\n", + "# \"Optimized Spend\": target_efficiency_result.dt_optimOut.optm_spend_unit,\n", + "# \"Spend Change %\": (\n", + "# target_efficiency_result.dt_optimOut.optm_spend_unit\n", + "# / target_efficiency_result.dt_optimOut.init_spend_unit\n", + "# - 1\n", + "# )\n", + "# * 100,\n", + "# \"Initial Response\": target_efficiency_result.dt_optimOut.init_response_unit,\n", + "# \"Optimized Response\": target_efficiency_result.dt_optimOut.optm_response_unit,\n", + "# \"Response Lift %\": (\n", + "# target_efficiency_result.dt_optimOut.optm_response_unit\n", + "# / target_efficiency_result.dt_optimOut.init_response_unit\n", + "# - 1\n", + "# )\n", + "# * 100,\n", + "# }\n", + "# )\n", + "\n", + "# print(\"\\nDetailed Results:\")\n", + "# print(results_df.round(2))\n", + "\n", + "# # Print additional diagnostics\n", + "# print(\"\\nOptimization Parameters:\")\n", + "# if target_efficiency_allocator.constraints.budget_constraint is not None:\n", + "# print(\n", + "# f\"Total budget: {target_efficiency_allocator.constraints.budget_constraint:,.2f}\"\n", + "# )\n", + "# else:\n", + "# print(\"Total budget: Unconstrained (Target Efficiency Mode)\")\n", + "# print(\"Bound multiplier:\", target_efficiency_allocator.params.channel_constr_multiplier)\n", + "\n", + "# print(\"\\nConstraint Violations:\")\n", + "# violations = np.sum(\n", + "# np.abs(\n", + "# target_efficiency_result.dt_optimOut.optm_spend_unit\n", + "# - target_efficiency_allocator.allocator_data_preparer.init_spend_unit\n", + "# )\n", + "# )\n", + "# print(f\"Total allocation adjustment: {violations:,.2f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# print(target_efficiency_result.dt_optimOut)\n", + "# print(target_efficiency_result.mainPoints)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# from robyn.visualization.allocator_visualizer import (\n", + "# AllocatorPlotter,\n", + "# )\n", + "# %load_ext autoreload\n", + "# %autoreload 2\n", + "# # Initialize plotter with just the essential data\n", + "# plotter = AllocatorPlotter(\n", + "# allocation_result=target_efficiency_result,\n", + "# budget_allocator=target_efficiency_allocator\n", + "# )\n", + "\n", + "# # Generate all plots\n", + "# plots = plotter.plot_all(display_plots=False, export_location=None)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.15" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/tutorial7_clustering.ipynb b/python/tests/component_tutorials/tutorial7_clustering.ipynb new file mode 100644 index 000000000..487592e83 --- /dev/null +++ b/python/tests/component_tutorials/tutorial7_clustering.ipynb @@ -0,0 +1,179 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.modeling.clustering.clustering_config import ClusteringConfig, ClusterBy\n", + "from robyn.modeling.clustering.cluster_builder import ClusterBuilder\n", + "from robyn.modeling.entities.pareto_result import ParetoResult\n", + "from robyn.data.entities.holidays_data import HolidaysData\n", + "from robyn.data.entities.enums import DependentVarType\n", + "import logging\n", + "# Set the log level to DEBUG\n", + "import os\n", + "import logging\n", + "log_level = os.environ.get('LOG_LEVEL', 'INFO')\n", + "logging.basicConfig(level=getattr(logging, log_level.upper()))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "import pickle\n", + "\n", + "# load the variable from the file\n", + "with open(\"pareto_result.pkl\", \"rb\") as f:\n", + " pareto_result: ParetoResult = pickle.load(f)\n", + "with open(\"mmmdata.pkl\", \"rb\") as f:\n", + " mmm_data = pickle.load(f)\n", + "with open(\"holidays_data.pkl\", \"rb\") as f:\n", + " holidays_data:HolidaysData = pickle.load(f)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_builder = ClusterBuilder(pareto_result=pareto_result)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "configs = ClusteringConfig(\n", + " dep_var_type= DependentVarType(mmm_data.mmmdata_spec.dep_var_type),\n", + " cluster_by = ClusterBy.HYPERPARAMETERS,\n", + " max_clusters = 10,\n", + " min_clusters = 3,\n", + " weights=[1.0, 1.0, 1.0]\n", + ")\n", + "cluster_results = cluster_builder.cluster_models(configs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.wss" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.plots.top_solutions_errors_plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.plots.top_solutions_rois_plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.cluster_ci.clusters_confidence_interval_plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(\"clusters: \", cluster_results.n_clusters,\n", + "\"\\nerror weights/balance: \", cluster_results.errors_weights,\n", + "\"\\nboot_n: \", cluster_results.cluster_ci.boot_n,\n", + "\"\\nsim_n: \", cluster_results.cluster_ci.sim_n)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(cluster_results.cluster_ci.cluster_confidence_interval_df)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_results.top_solutions['sol_id']" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.modeling.pareto.pareto_utils import ParetoUtils\n", + "\n", + "utils = ParetoUtils()\n", + "new_pareto_results = utils.process_pareto_clustered_results(pareto_result, clustered_result=cluster_results, ran_cluster=True, ran_calibration= False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from robyn.data.entities.enums import AdstockType \n", + "from robyn.data.entities.hyperparameters import Hyperparameters\n", + "from robyn.reporting.onepager_reporting import OnePager\n", + "\n", + "visualizer = OnePager(pareto_result=new_pareto_results, clustered_result=cluster_results, hyperparameter=Hyperparameters(adstock=AdstockType.GEOMETRIC), mmm_data=mmm_data, holidays_data=holidays_data)\n", + "visualizer.generate_one_pager(top_pareto=True)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/tutorial_data_mapper.ipynb b/python/tests/component_tutorials/tutorial_data_mapper.ipynb new file mode 100644 index 000000000..0e5972c54 --- /dev/null +++ b/python/tests/component_tutorials/tutorial_data_mapper.ipynb @@ -0,0 +1,298 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load Exported R Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "import pandas as pd\n", + "import numpy as np\n", + "from typing import Dict, Any\n", + "\n", + "# Add Robyn to path\n", + "sys.path.append(\"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src\")\n", + "\n", + "# Import necessary Robyn classes\n", + "from robyn.data.entities.mmmdata import MMMData\n", + "from robyn.modeling.entities.modeloutputs import ModelOutputs\n", + "from robyn.data.entities.hyperparameters import Hyperparameters\n", + "from robyn.modeling.pareto.pareto_optimizer import ParetoResult\n", + "from utils.data_mapper import (\n", + " load_data_from_json,\n", + " import_input_collect,\n", + " import_output_collect,\n", + " import_output_models,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Export Json data on R notebooks" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# import json\n", + "\n", + "# # Specify the paths where you want to save the JSON files\n", + "# input_collect_path = (\n", + "# \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Allocator_InputCollect.json\"\n", + "# )\n", + "# output_models_path = (\n", + "# \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Allocator_OutputModels.json\"\n", + "# )\n", + "# output_collect_path = (\n", + "# \"/Users/yijuilee/project_robyn/original/Robyn_original_2/Robyn/robyn_api/data/Allocator_OutputCollect.json\"\n", + "# )\n", + "# # Save each component to a separate JSON file\n", + "# with open(input_collect_path, \"w\") as f:\n", + "# json.dump(InputCollect, f)\n", + "# with open(output_models_path, \"w\") as f:\n", + "# json.dump(OutputModels, f)\n", + "# with open(output_collect_path, \"w\") as f:\n", + "# json.dump(OutputCollect, f)\n", + "# print(f\"InputCollect exported successfully to {input_collect_path}\")\n", + "# print(f\"OutputModels exported successfully to {output_models_path}\")\n", + "# print(f\"OutputCollect exported successfully to {output_collect_path}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load json data.\n", + "* InputCollect\n", + "* OutputModels\n", + "* outputsArgs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load data from JSON exported from R\n", + "raw_input_collect = load_data_from_json(\n", + " \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/tutorials/data/Allocator_InputCollect.json\"\n", + ")\n", + "raw_output_collect = load_data_from_json(\n", + " \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/tutorials/data/Allocator_OutputCollect.json\"\n", + ")\n", + "raw_output_models = load_data_from_json(\n", + " \"/Users/yijuilee/robynpy_release_reviews/Robyn/python/src/tutorials/data/Allocator_OutputModels.json\"\n", + ")\n", + "\n", + "# Convert R data to Python objects\n", + "r_input_collect = import_input_collect(raw_input_collect)\n", + "r_output_collect = import_output_collect(raw_output_collect)\n", + "python_model_outputs = import_output_models(raw_output_models)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## InputCollect" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Extract individual components\n", + "mmm_data = r_input_collect[\"mmm_data\"]\n", + "featurized_mmm_data = r_input_collect[\"featurized_mmm_data\"]\n", + "holidays_data = r_input_collect[\"holidays_data\"]\n", + "hyperparameters = r_input_collect[\"hyperparameters\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Output Collect" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pareto_results = r_output_collect[\"pareto_result\"]\n", + "\n", + "cluster_data = r_output_collect[\"cluster_data\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pareto_results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display(pareto_results.pareto_fronts)\n", + "\n", + "display(pareto_results.x_decomp_agg)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ModelOutputs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model_outputs = python_model_outputs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(cluster_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(cluster_data.cluster_ci)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display(cluster_data.n_clusters)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display(cluster_data.clusters_pca)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display(cluster_data.clusters_tsne)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(pareto_results.plot_data_collect.keys())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get plot data for a specific model\n", + "model_id = list(pareto_results.plot_data_collect.keys())[3]\n", + "model_plots = pareto_results.plot_data_collect[model_id]\n", + "\n", + "# Access plot1data (Media share comparison)\n", + "media_share_data = model_plots[\"plot1data\"]\n", + "bar_data = media_share_data[\"plotMediaShareLoopBar\"]\n", + "line_data = media_share_data[\"plotMediaShareLoopLine\"]\n", + "scale = media_share_data[\"ySecScale\"]\n", + "\n", + "# Access plot2data (Waterfall)\n", + "waterfall_data = model_plots[\"plot2data\"][\"plotWaterfallLoop\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(model_id)\n", + "print(model_plots.keys())\n", + "\n", + "for key in model_plots.keys():\n", + " print(\"This Key: \", key)\n", + " print(\"Has these keys: \", model_plots[key].keys())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mytestenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/python/tests/component_tutorials/utils/data_mapper.py b/python/tests/component_tutorials/utils/data_mapper.py new file mode 100644 index 000000000..15a1f22ee --- /dev/null +++ b/python/tests/component_tutorials/utils/data_mapper.py @@ -0,0 +1,379 @@ +# data_mapper.py +import json +import pandas as pd +from typing import Any, Dict +from robyn.data.entities.enums import ( + AdstockType, + DependentVarType, + ProphetVariableType, + ProphetSigns, +) +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.convergence_data import ConvergenceData +from robyn.modeling.entities.modeloutputs import ModelOutputs, Trial +from robyn.modeling.feature_engineering import FeaturizedMMMData +from robyn.modeling.entities.pareto_result import ParetoResult +from robyn.modeling.entities.clustering_results import ( + ClusteredResult, + ClusterPlotResults, + ClusterConfidenceIntervals, + DimentionalityReductionResults, +) + + +def import_input_collect(data: Dict[str, Any]) -> Dict[str, Any]: + adstock_type = data.get("adstock", "geometric") + if isinstance(adstock_type, list): + adstock_type = adstock_type[0] + dep_var_type = data.get("dep_var_type")[0] + if isinstance(dep_var_type, list): + dep_var_type = dep_var_type[0] + mmm_data_spec_args = { + "dep_var": data.get("dep_var")[0], + "dep_var_type": DependentVarType(dep_var_type), + "date_var": data.get("date_var")[0], + "paid_media_spends": data.get("paid_media_spends", []), + "paid_media_vars": data.get("paid_media_vars", []), + "organic_vars": data.get("organic_vars", []), + "context_vars": data.get("context_vars", []), + "factor_vars": data.get("factor_vars", []), + "window_start": data.get("window_start")[0], + "window_end": data.get("window_end")[0], + "rolling_window_length": data.get("rollingWindowLength")[0], + "rolling_window_start_which": data.get("rollingWindowStartWhich")[0], + "all_media": data.get("all_media", []), + "rolling_window_end_which": data.get("rollingWindowEndWhich", 0)[0], + } + mmm_data = MMMData( + data=pd.DataFrame(data["dt_input"]), + mmmdata_spec=MMMData.MMMDataSpec(**mmm_data_spec_args), + ) + holidays_data = HolidaysData( + dt_holidays=pd.DataFrame(data.get("dt_holidays", {})), + prophet_vars=[ProphetVariableType(v) for v in data.get("prophet_vars", [])], + prophet_country=data.get("prophet_country"), + prophet_signs=[ProphetSigns(s) for s in data.get("prophet_signs", [])], + ) + + print("Raw hyperparameters data:", data["hyperparameters"]) + # Group parameters by channel + channel_params: Dict[str, Dict[str, list]] = {} + for key, value in data["hyperparameters"].items(): + if key == "train_size": + continue # Skip train_size as it's not a channel parameter + channel, param_type = key.rsplit("_", 1) + if channel not in channel_params: + channel_params[channel] = {} + channel_params[channel][param_type] = value + + # Convert grouped parameters to ChannelHyperparameters objects + hyperparameters_dict: Dict[str, ChannelHyperparameters] = { + channel: ChannelHyperparameters( + thetas=params.get("thetas"), + alphas=params.get("alphas"), + gammas=params.get("gammas"), + # Add other parameters as needed + ) + for channel, params in channel_params.items() + } + + # Initialize the Hyperparameters instance + hyperparameters = Hyperparameters( + hyperparameters=hyperparameters_dict, + adstock=AdstockType(adstock_type), # Ensure adstock_type is defined + lambda_=data.get("lambda_", 0.0), + train_size=data.get("train_size", [0.5, 0.8]), + ) + featurized_mmm_data = FeaturizedMMMData( + dt_mod=pd.DataFrame(data.get("dt_mod", {})), + dt_modRollWind=pd.DataFrame(data.get("dt_modRollWind", {})), + modNLS=data.get("modNLS", {}), + ) + return { + "mmm_data": mmm_data, + "holidays_data": holidays_data, + "hyperparameters": hyperparameters, + "featurized_mmm_data": featurized_mmm_data, + } + + +def import_output_collect(output_collect: Dict[str, Any]) -> Dict[str, Any]: + """ + Import and process OutputCollect data separately. + + Args: + output_collect (Dict[str, Any]): The OutputCollect data dictionary + + Returns: + Dict[str, Any]: Dictionary containing processed pareto and cluster data + """ + # Create ParetoResult + try: + pareto_result = ParetoResult( + pareto_solutions=output_collect.get("allSolutions", []), + pareto_fronts=output_collect.get("pareto_fronts", 0), + result_hyp_param=pd.DataFrame(output_collect.get("resultHypParam", {})), + x_decomp_agg=pd.DataFrame(output_collect.get("xDecompAgg", {})), + result_calibration=( + pd.DataFrame(output_collect.get("resultCalibration", {})) + if output_collect.get("resultCalibration") + else None + ), + media_vec_collect=pd.DataFrame(output_collect.get("mediaVecCollect", {})), + x_decomp_vec_collect=pd.DataFrame( + output_collect.get("xDecompVecCollect", {}) + ), + plot_data_collect=_convert_plot_data( + output_collect.get("allPareto", {}).get("plotDataCollect", {}) + ), + df_caov_pct_all=pd.DataFrame( + output_collect.get("allPareto", {}).get("df_caov_pct", {}) + ), + ) + except Exception as e: + print(f"Warning: Error creating ParetoResult: {str(e)}") + pareto_result = None + + # Process cluster data if available + cluster_data = None + if output_collect.get("clusters"): + try: + clusters_dict = output_collect["clusters"] + + # Process PCA results if available + pca_results = None + pca_data = clusters_dict.get("clusters_PCA") + if pca_data: + pca_results = DimentionalityReductionResults( + explained_variance=pd.Series(pca_data.get("pca_explained", [])), + df=pd.DataFrame(pca_data.get("pcadf", [])), + plot_explained=( + pd.DataFrame(pca_data.get("plot_explained", [])) + if pca_data.get("plot_explained") + else None + ), + plot=pca_data.get("plot"), + ) + + # Create plot results + plot_results = ClusterPlotResults( + top_solutions_errors_plot=pd.DataFrame( + clusters_dict.get("plot_models_errors", []) + ), + top_solutions_rois_plot=pd.DataFrame( + clusters_dict.get("plot_models_rois", []) + ), + ) + + # Create confidence intervals + cluster_ci = ClusterConfidenceIntervals( + cluster_confidence_interval_df=pd.DataFrame( + clusters_dict.get("df_cluster_ci", []) + ), + boot_n=clusters_dict.get("boot_n", [0])[0], + sim_n=clusters_dict.get("sim_n", [0])[0], + clusters_confidence_interval_plot=pd.DataFrame( + clusters_dict.get("plot_clusters_ci", []) + ), + ) + + # Create final clustered result + cluster_data = ClusteredResult( + cluster_data=pd.DataFrame(clusters_dict.get("data", [])), + top_solutions=pd.DataFrame(clusters_dict.get("models", [])), + cluster_ci=cluster_ci, + n_clusters=clusters_dict.get("n_clusters", [0])[0], + errors_weights=clusters_dict.get("errors_weights", []), + clusters_means=pd.DataFrame(clusters_dict.get("clusters_means", [])), + wss=pd.DataFrame(clusters_dict.get("wss", [])), + correlations=pd.DataFrame(clusters_dict.get("corrs", [])), + clusters_pca=pca_results, + plots=plot_results, + ) + + except Exception as e: + print(f"Warning: Error processing cluster data: {str(e)}") + import traceback + + traceback.print_exc() + cluster_data = None + + return { + "pareto_result": pareto_result, + "cluster_data": cluster_data, + } + + +def _convert_plot_data(plot_data_collect: Dict[str, Any]) -> Dict[str, pd.DataFrame]: + """ + Convert plot data collections to DataFrames while maintaining R's structure. + + Args: + plot_data_collect: Dictionary containing plot data from R + + Returns: + Dictionary of converted pandas DataFrames + """ + converted_data = {} + + for model_id, model_data in plot_data_collect.items(): + try: + converted_data[model_id] = {} + + # Convert each plot type (plot1data, plot2data, etc) + for plot_type, plot_content in model_data.items(): + if plot_type == "plot7data": + converted_data[model_id][plot_type] = pd.DataFrame(plot_content) + + if not isinstance(plot_content, dict): + continue + + converted_data[model_id][plot_type] = {} + + # Convert each component within the plot type + for component_name, component_data in plot_content.items(): + try: + if isinstance(component_data, pd.DataFrame): + converted_data[model_id][plot_type][ + component_name + ] = component_data + elif isinstance(component_data, (list, dict)): + converted_data[model_id][plot_type][component_name] = ( + pd.DataFrame(component_data) + ) + else: + # For scalar values, store as is + converted_data[model_id][plot_type][ + component_name + ] = component_data + except Exception as e: + print( + f"Warning: Error converting {component_name} in {plot_type} for {model_id}: {str(e)}" + ) + + except Exception as e: + print(f"Warning: Error converting plot data for {model_id}: {str(e)}") + + return converted_data + + +def import_output_models(data: Dict[str, Any]) -> ModelOutputs: + # Debug: Print the keys and a brief summary of the data + print("Debug: R output data keys:", list(data.keys())[:5]) + # Print the shape or length for each key + for key in list(data.keys())[:5]: + if isinstance(data[key], dict): + print(f"Data for {key}: Keys = {list(data[key].keys())[:3]}") + # Check the content of resultCollect + result_collect = data[key].get("resultCollect", {}) + print(f"Debug: resultCollect keys for {key}: {list(result_collect.keys())}") + print( + f"Debug: Sample resultHypParam for {key}: {result_collect.get('resultHypParam', [])[:3]}" + ) + trials = [] + convergence_data = None + hyper_bound_ng = pd.DataFrame() + hyper_bound_fixed = pd.DataFrame() + hyper_updated = {} + for trial_key, trial_data in data.items(): + if trial_key == "convergence": + convergence_data = ConvergenceData.from_dict(trial_data) + elif trial_key == "hyper_updated": + hyper_updated = trial_data + elif trial_key == "hyper_fixed": + hyper_fixed = trial_data[0] + elif trial_key == "train_timestamp": + train_timestamp = trial_data[0] + elif trial_key == "cores": + cores = trial_data[0] + elif trial_key == "iterations": + iterations = trial_data[0] + elif trial_key == "intercept": + intercept = trial_data[0] + elif trial_key == "intercept_sign": + intercept_sign = trial_data[0] + elif trial_key == "nevergrad_algo": + nevergrad_algo = trial_data[0] + elif trial_key == "ts_validation": + ts_validation = trial_data[0] + elif trial_key == "add_penalty_factor": + add_penalty_factor = trial_data[0] + elif isinstance(trial_data, dict): + result_collect = trial_data.get("resultCollect", {}) + result_hyp_param = pd.DataFrame(result_collect.get("resultHypParam", [])) + print("Shape of result_hyp_param:") + print(result_hyp_param.shape) + print(f"Debug: result_hyp_param DataFrame for {trial_key}:") + print(result_hyp_param.head()) # Print a few rows + print("Data types in result_hyp_param:") + print(result_hyp_param.dtypes) # Check data types + + result_hyp_param.rename(columns={"solID": "sol_id"}, inplace=True) + x_decomp_agg = pd.DataFrame(result_collect.get("xDecompAgg", [])) + print(f"Debug: x_decomp_agg DataFrame shape: {x_decomp_agg.shape}") + x_decomp_agg.rename(columns={"solID": "sol_id"}, inplace=True) + lift_calibration = pd.DataFrame(result_collect.get("liftCalibration", [])) + decomp_spend_dist = pd.DataFrame(result_collect.get("decompSpendDist", [])) + decomp_spend_dist.rename(columns={"solID": "sol_id"}, inplace=True) + hyper_bound_ng = pd.DataFrame(trial_data.get("hyperBoundNG", {})) + hyper_bound_fixed = pd.DataFrame(trial_data.get("hyperBoundFixed", [])) + trial = Trial( + result_hyp_param=result_hyp_param, + x_decomp_agg=x_decomp_agg, + lift_calibration=lift_calibration, + decomp_spend_dist=decomp_spend_dist, + nrmse=result_hyp_param.get("nrmse", 0), # Newly added + decomp_rssd=result_hyp_param.get("decomp.rssd", 0), # Newly added + mape=result_hyp_param.get("mape", 0), # Newly added + rsq_train=result_hyp_param.get("rsq_train", 0), # Newly added + rsq_val=result_hyp_param.get("rsq_val", 0), # Newly added + rsq_test=result_hyp_param.get("rsq_test", 0), # Newly added + lambda_=result_hyp_param.get("lambda", 0), # Newly added + lambda_hp=result_hyp_param.get("lambda_hp", 0), # Newly added + lambda_max=result_hyp_param.get("lambda_max", 0), # Newly added + lambda_min_ratio=result_hyp_param.get( + "lambda_min_ratio", 0 + ), # Newly added + pos=result_hyp_param.get("pos", 0), # Newly added + elapsed=result_hyp_param.get("Elapsed", 0), # Newly added + elapsed_accum=result_hyp_param.get("ElapsedAccum", 0), # Newly added + trial=result_hyp_param.get("trial", 0), # Newly added + iter_ng=result_hyp_param.get("iterNG", 0), # Newly added + iter_par=result_hyp_param.get("iterPar", 0), # Newly added + train_size=result_hyp_param.get("train_size", 0), # Newly added + sol_id=result_hyp_param.get("solID", ""), # Newly added + ) + trials.append(trial) + model_outputs = ModelOutputs( + trials=trials, + train_timestamp=train_timestamp, + cores=cores, + iterations=iterations, + intercept=intercept, + intercept_sign=intercept_sign, + nevergrad_algo=nevergrad_algo, + ts_validation=ts_validation, + add_penalty_factor=add_penalty_factor, + hyper_fixed=hyper_fixed, + hyper_updated=hyper_updated, + convergence=convergence_data, + select_id=data.get("select_id", ""), + seed=data.get("seed", 0), + hyper_bound_ng=hyper_bound_ng, + hyper_bound_fixed=hyper_bound_fixed, + ts_validation_plot=data.get("ts_validation_plot"), + all_result_hyp_param=pd.concat([trial.result_hyp_param for trial in trials]), + all_x_decomp_agg=pd.concat([trial.x_decomp_agg for trial in trials]), + all_decomp_spend_dist=pd.concat([trial.decomp_spend_dist for trial in trials]), + ) + return model_outputs + + +def load_data_from_json(filename: str) -> Dict[str, Any]: + """ + Load the exported data from a JSON file. + """ + with open(filename, "r") as f: + return json.load(f) diff --git a/python/tests/integration/test_feature_engineering.py b/python/tests/integration/test_feature_engineering.py new file mode 100644 index 000000000..0eb84355d --- /dev/null +++ b/python/tests/integration/test_feature_engineering.py @@ -0,0 +1,320 @@ +import pytest +import pandas as pd +import numpy as np +from datetime import datetime, timedelta +from robyn.data.entities.mmmdata import MMMData +from robyn.data.entities.holidays_data import HolidaysData +from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters +from robyn.data.entities.enums import AdstockType, DependentVarType +from robyn.modeling.feature_engineering import FeatureEngineering + + +@pytest.fixture +def sample_data(): + """Create sample data for testing.""" + dates = pd.date_range(start="2020-01-01", end="2022-12-31", freq="W-MON") + n_rows = len(dates) + + return pd.DataFrame( + { + "DATE": dates, + "revenue": np.random.uniform(1000, 5000, n_rows), + "tv_S": np.random.uniform(100, 1000, n_rows), + "facebook_S": np.random.uniform(100, 1000, n_rows), + "custom_context": np.random.uniform(10, 100, n_rows), + "newsletter": np.random.uniform(0, 100, n_rows), + } + ) + + +@pytest.fixture +def sample_holidays(): + """Create sample holidays data for testing.""" + return pd.DataFrame( + { + "ds": pd.date_range(start="2020-01-01", end="2022-12-31", freq="M"), + "holiday": "test_holiday", + "country": "US", + "year": [ + d.year + for d in pd.date_range(start="2020-01-01", end="2022-12-31", freq="M") + ], + } + ) + + +@pytest.fixture +def basic_mmm_data(sample_data): + """Create basic MMM data specification.""" + mmm_data_spec = MMMData.MMMDataSpec( + dep_var="revenue", + dep_var_type="revenue", + date_var="DATE", + context_vars=["custom_context"], + paid_media_spends=["tv_S", "facebook_S"], + paid_media_vars=["tv_S", "facebook_S"], + organic_vars=["newsletter"], + window_start=pd.Timestamp("2020-01-01"), # Convert to Timestamp + window_end=pd.Timestamp("2022-12-31"), # Convert to Timestamp + ) + return MMMData(data=sample_data, mmmdata_spec=mmm_data_spec) + + +@pytest.fixture +def basic_holidays_data(sample_holidays): + """Create basic holidays data specification.""" + return HolidaysData( + dt_holidays=sample_holidays, + prophet_vars=[ + "trend", + "season", + "holiday", + ], # These are the variables we're testing + prophet_country="US", + prophet_signs=["default", "default", "default"], + ) + + +@pytest.fixture +def basic_hyperparameters(): + """Create basic hyperparameters configuration.""" + return Hyperparameters( + hyperparameters={ + "tv_S": ChannelHyperparameters( + alphas=[0.5, 3], + gammas=[0.3, 1], + thetas=[0.3, 0.8], + ), + "facebook_S": ChannelHyperparameters( + alphas=[0.5, 3], + gammas=[0.3, 1], + thetas=[0, 0.3], + ), + "newsletter": ChannelHyperparameters( + alphas=[0.5, 3], + gammas=[0.3, 1], + thetas=[0.1, 0.4], + ), + }, + adstock=AdstockType.GEOMETRIC, + lambda_=[0, 1], + train_size=[0.5, 0.8], + ) + + +def test_feature_engineering_initialization( + basic_mmm_data, basic_holidays_data, basic_hyperparameters +): + """Test if FeatureEngineering initializes correctly.""" + fe = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, + ) + assert fe.mmm_data == basic_mmm_data + assert fe.hyperparameters == basic_hyperparameters + assert fe.holidays_data == basic_holidays_data + + +def test_prepare_data_with_custom_context( + basic_mmm_data, basic_holidays_data, basic_hyperparameters +): + """Test if _prepare_data handles custom context variables correctly.""" + fe = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, + ) + + dt_transform = fe._prepare_data() + + # Check if all expected columns exist + assert "ds" in dt_transform.columns + assert "dep_var" in dt_transform.columns + assert "custom_context" in dt_transform.columns + + # Check if date transformation worked correctly + assert pd.api.types.is_datetime64_any_dtype(pd.to_datetime(dt_transform["ds"])) + + +def test_feature_engineering_with_different_context_vars( + sample_data, basic_holidays_data, basic_hyperparameters +): + """Test if feature engineering works with different context variables.""" + mmm_data_spec = MMMData.MMMDataSpec( + dep_var="revenue", + dep_var_type="revenue", + date_var="DATE", + context_vars=["custom_context"], + paid_media_spends=["tv_S", "facebook_S"], + paid_media_vars=["tv_S", "facebook_S"], + organic_vars=["newsletter"], + window_start=pd.Timestamp("2020-01-01"), + window_end=pd.Timestamp("2022-12-31"), + ) + + mmm_data = MMMData(data=sample_data, mmmdata_spec=mmm_data_spec) + fe = FeatureEngineering( + mmm_data=mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, # Use the fixture + ) + + result = fe.perform_feature_engineering() + assert isinstance(result.dt_mod, pd.DataFrame) + assert "custom_context" in result.dt_mod.columns + + +def test_feature_engineering_no_context_vars( + sample_data, basic_holidays_data, basic_hyperparameters +): + """Test if feature engineering works without context variables.""" + mmm_data_spec = MMMData.MMMDataSpec( + dep_var="revenue", + dep_var_type="revenue", + date_var="DATE", + context_vars=[], + paid_media_spends=["tv_S", "facebook_S"], + paid_media_vars=["tv_S", "facebook_S"], + organic_vars=["newsletter"], + window_start=pd.Timestamp("2020-01-01"), + window_end=pd.Timestamp("2022-12-31"), + ) + + mmm_data = MMMData(data=sample_data, mmmdata_spec=mmm_data_spec) + fe = FeatureEngineering( + mmm_data=mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, # Use the fixture + ) + + result = fe.perform_feature_engineering() + assert isinstance(result.dt_mod, pd.DataFrame) + + +def test_invalid_context_var(sample_data, basic_holidays_data, basic_hyperparameters): + """Test handling of invalid context variables.""" + mmm_data_spec = MMMData.MMMDataSpec( + dep_var="revenue", + dep_var_type="revenue", + date_var="DATE", + context_vars=["nonexistent_var"], + paid_media_spends=["tv_S", "facebook_S"], + paid_media_vars=["tv_S", "facebook_S"], + organic_vars=["newsletter"], + window_start=pd.Timestamp("2020-01-01"), + window_end=pd.Timestamp("2022-12-31"), + ) + + mmm_data = MMMData(data=sample_data, mmmdata_spec=mmm_data_spec) + + with pytest.raises(KeyError): + fe = FeatureEngineering( + mmm_data=mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, # Use the fixture + ) + fe.perform_feature_engineering() + + +def test_feature_engineering_with_prophet_disabled( + basic_mmm_data, basic_hyperparameters +): + """Test if feature engineering works correctly when Prophet is disabled.""" + # Initialize FeatureEngineering without holidays_data + fe = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=None, # Explicitly disable Prophet + ) + + # Run feature engineering + result = fe.perform_feature_engineering() + + # Check that Prophet variables are not in the output + prophet_vars = ["trend", "season", "holiday", "monthly", "weekday"] + for var in prophet_vars: + assert var not in result.dt_mod.columns + assert var not in result.dt_modRollWind.columns + + +def test_feature_engineering_with_empty_prophet_vars( + basic_mmm_data, basic_hyperparameters, basic_holidays_data +): + """Test if feature engineering works when prophet_vars is empty.""" + # Modify holidays_data to have empty prophet_vars + holidays_data_empty = HolidaysData( + dt_holidays=basic_holidays_data.dt_holidays, + prophet_vars=[], + prophet_country="US", + prophet_signs=[], + ) + + fe = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=holidays_data_empty, + ) + + result = fe.perform_feature_engineering() + + # Check that Prophet variables are not in the output + prophet_vars = ["trend", "season", "holiday", "monthly", "weekday"] + for var in prophet_vars: + assert var not in result.dt_mod.columns + assert var not in result.dt_modRollWind.columns + + +def test_prophet_enable_disable_comparison( + basic_mmm_data, basic_hyperparameters, basic_holidays_data +): + """Test and compare results with Prophet enabled vs disabled.""" + # Run with Prophet enabled + fe_enabled = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, + ) + result_enabled = fe_enabled.perform_feature_engineering() + + # Run with Prophet disabled + fe_disabled = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=None, + ) + result_disabled = fe_disabled.perform_feature_engineering() + + # Compare results + assert len(result_enabled.dt_mod.columns) > len(result_disabled.dt_mod.columns) + + # Core columns should be present in both + core_cols = ["ds", "dep_var", "tv_S", "facebook_S", "custom_context", "newsletter"] + for col in core_cols: + assert col in result_enabled.dt_mod.columns + assert col in result_disabled.dt_mod.columns + + # Prophet columns should only be in enabled result + prophet_vars = basic_holidays_data.prophet_vars + for var in prophet_vars: + assert var in result_enabled.dt_mod.columns + assert var not in result_disabled.dt_mod.columns + + +def test_feature_engineering_with_prophet_enabled( + basic_mmm_data, basic_hyperparameters, basic_holidays_data +): + """Test if feature engineering works correctly when Prophet is enabled.""" + fe = FeatureEngineering( + mmm_data=basic_mmm_data, + hyperparameters=basic_hyperparameters, + holidays_data=basic_holidays_data, + ) + + result = fe.perform_feature_engineering() + + # Check that specified Prophet variables are in the output + prophet_vars = basic_holidays_data.prophet_vars + for var in prophet_vars: + assert var in result.dt_mod.columns + assert var in result.dt_modRollWind.columns diff --git a/python/tests/integration/test_robyn_e2e.py b/python/tests/integration/test_robyn_e2e.py new file mode 100644 index 000000000..1ae5fe04b --- /dev/null +++ b/python/tests/integration/test_robyn_e2e.py @@ -0,0 +1,164 @@ +# # pyre-strict +# import pytest +# import pandas as pd +# from unittest.mock import MagicMock, patch +# from pathlib import Path +# from robyn.data.entities.mmmdata import MMMData +# from robyn.data.entities.enums import AdstockType +# from robyn.data.entities.holidays_data import HolidaysData +# from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters +# from robyn.modeling.feature_engineering import FeatureEngineering +# from robyn.modeling.model_executor import ModelExecutor +# from robyn.modeling.entities.modelrun_trials_config import TrialsConfig +# from robyn.modeling.entities.enums import NevergradAlgorithm, Models +# from robyn.modeling.pareto.pareto_optimizer import ParetoOptimizer +# from robyn.allocator.budget_allocator import BudgetAllocator +# from robyn.allocator.entities.allocation_config import AllocationConfig +# from robyn.allocator.entities.allocation_constraints import AllocationConstraints +# from robyn.allocator.entities.enums import OptimizationScenario, ConstrMode +# from robyn.visualization.allocator_plotter import AllocationPlotter + + +# @pytest.fixture(scope="session") +# def test_data(): +# resources_path = Path("python/src/robyn/tutorials/resources") +# dt_simulated = pd.read_csv(resources_path / "dt_simulated_weekly.csv", parse_dates=["DATE"]) +# dt_holidays = pd.read_csv(resources_path / "dt_prophet_holidays.csv", parse_dates=["ds"]) +# return dt_simulated, dt_holidays + + +# @pytest.fixture(scope="session") +# def mmm_data(test_data): +# dt_simulated_weekly, _ = test_data +# mmm_data_spec = MMMData.MMMDataSpec( +# dep_var="revenue", +# dep_var_type="revenue", +# date_var="DATE", +# context_vars=["competitor_sales_B", "events"], +# paid_media_spends=["tv_S", "ooh_S", "print_S", "facebook_S", "search_S"], +# paid_media_vars=["tv_S", "ooh_S", "print_S", "facebook_I", "search_clicks_P"], +# organic_vars=["newsletter"], +# window_start="2016-01-01", +# window_end="2018-12-31", +# ) +# return MMMData(data=dt_simulated_weekly, mmmdata_spec=mmm_data_spec) + + +# @pytest.fixture(scope="session") +# def hyperparameters(): +# return Hyperparameters( +# { +# "facebook_S": ChannelHyperparameters(alphas=[0.5, 3], gammas=[0.3, 1], thetas=[0, 0.3]), +# "print_S": ChannelHyperparameters(alphas=[0.5, 3], gammas=[0.3, 1], thetas=[0.1, 0.4]), +# "tv_S": ChannelHyperparameters(alphas=[0.5, 3], gammas=[0.3, 1], thetas=[0.3, 0.8]), +# "search_S": ChannelHyperparameters(alphas=[0.5, 3], gammas=[0.3, 1], thetas=[0, 0.3]), +# "ooh_S": ChannelHyperparameters(alphas=[0.5, 3], gammas=[0.3, 1], thetas=[0.1, 0.4]), +# "newsletter": ChannelHyperparameters(alphas=[0.5, 3], gammas=[0.3, 1], thetas=[0.1, 0.4]), +# }, +# adstock=AdstockType.GEOMETRIC, +# lambda_=0.0, +# train_size=[0.5, 0.8], +# ) + + +# @pytest.fixture(scope="session") +# def holidays_data(test_data): +# _, dt_holidays = test_data +# return HolidaysData( +# dt_holidays=dt_holidays, +# prophet_vars=["trend", "season", "holiday"], +# prophet_country="DE", +# prophet_signs=["default", "default", "default"], +# ) + + +# @pytest.fixture(scope="session") +# def featurized_mmm_data(mmm_data, hyperparameters, holidays_data): +# feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data) +# return feature_engineering.perform_feature_engineering() + + +# @pytest.fixture(scope="session") +# def model_outputs(mmm_data, holidays_data, hyperparameters, featurized_mmm_data): +# """Fixture to create and store model outputs""" +# model_executor = ModelExecutor( +# mmmdata=mmm_data, +# holidays_data=holidays_data, +# hyperparameters=hyperparameters, +# calibration_input=None, +# featurized_mmm_data=featurized_mmm_data, +# ) + +# trials_config = TrialsConfig(iterations=10, trials=5) + +# output_models = model_executor.model_run( +# trials_config=trials_config, +# ts_validation=False, +# add_penalty_factor=False, +# rssd_zero_penalty=True, +# cores=8, +# nevergrad_algo=NevergradAlgorithm.TWO_POINTS_DE, +# intercept=True, +# intercept_sign="non_negative", +# model_name=Models.RIDGE, +# ) +# return output_models + + +# @pytest.fixture(scope="session") +# def pareto_result(mmm_data, hyperparameters, featurized_mmm_data, holidays_data, model_outputs): +# """Fixture to create and store pareto optimization results""" +# pareto_optimizer = ParetoOptimizer(mmm_data, model_outputs, hyperparameters, featurized_mmm_data, holidays_data) +# return pareto_optimizer.optimize(pareto_fronts="auto", min_candidates=1) + + +# @pytest.mark.skip(reason="Disabling this test because it was implemented incorrectly") +# def test_feature_engineering(featurized_mmm_data): +# assert featurized_mmm_data is not None, "Feature engineering failed, no features generated." + + +# @pytest.mark.skip(reason="Disabling this test because it was implemented incorrectly") +# def test_model_execution(model_outputs): +# assert model_outputs is not None, "Model execution failed, no output models returned." +# assert model_outputs.select_id is not None, "No best models found" + + +# @pytest.mark.skip(reason="Disabling this test because it was implemented incorrectly") +# def test_pareto_optimization(pareto_result): +# assert pareto_result is not None, "Pareto optimization failed, no result returned." +# assert len(pareto_result.pareto_solutions) > 0, "No Pareto solutions found." + + +# @pytest.mark.skip(reason="Disabling this test because it was implemented incorrectly") +# def test_budget_allocation(mmm_data, featurized_mmm_data, model_outputs, pareto_result): +# # Budget Allocation +# select_model = next(iter(pareto_result.pareto_solutions)) +# allocator = BudgetAllocator( +# mmm_data=mmm_data, +# featurized_mmm_data=featurized_mmm_data, +# model_outputs=model_outputs, +# pareto_result=pareto_result, +# select_model=select_model, +# ) + +# channel_constraints = AllocationConstraints( +# channel_constr_low={"tv_S": 0.7, "ooh_S": 0.7, "print_S": 0.7, "facebook_S": 0.7, "search_S": 0.7}, +# channel_constr_up={"tv_S": 1.2, "ooh_S": 1.5, "print_S": 1.5, "facebook_S": 1.5, "search_S": 1.5}, +# channel_constr_multiplier=3.0, +# ) + +# max_response_config = AllocationConfig( +# scenario=OptimizationScenario.MAX_RESPONSE, +# constraints=channel_constraints, +# date_range="last", +# total_budget=None, +# maxeval=100000, +# optim_algo="SLSQP_AUGLAG", +# constr_mode=ConstrMode.EQUALITY, +# plots=True, +# ) + +# result = allocator.allocate(max_response_config) + +# assert result is not None, "Budget allocation failed, no result returned." +# assert len(result.optimal_allocations) > 0, "No optimal allocations found." diff --git a/python/tests/unit/modeling/pareto/test_hill_calculator.py b/python/tests/unit/modeling/pareto/test_hill_calculator.py new file mode 100644 index 000000000..147a8dad2 --- /dev/null +++ b/python/tests/unit/modeling/pareto/test_hill_calculator.py @@ -0,0 +1,259 @@ +# pyre-strict + +import unittest +from unittest.mock import Mock, MagicMock +import pandas as pd +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.modeling.pareto.hill_calculator import HillCalculator + + +class TestHillCalculator(unittest.TestCase): + + def test_empty_media_vec_collect(self): + mock_media_vec_collect = pd.DataFrame(columns=["type", "solID"]) + mock_mmmdata_spec = type( + "MockMMMDataSpec", (object,), {"window_start": 1, "window_end": 2} + )() + mock_mmmdata = type( + "MockMMMData", (object,), {"mmmdata_spec": mock_mmmdata_spec} + )() + + mock_model_outputs = type( + "MockModelOutputs", (object,), {"media_vec_collect": mock_media_vec_collect} + )() + + media_spend_sorted = [] + select_model = "model_1" + + # Create an instance of HillCalculator with the mocked data + hill_calculator = HillCalculator( + mmmdata=mock_mmmdata, + model_outputs=mock_model_outputs, + dt_hyppar=pd.DataFrame(), + dt_coef=pd.DataFrame(), + media_spend_sorted=media_spend_sorted, + select_model=select_model, + ) + + # Invoke _get_chn_adstocked_from_output_collect + chn_adstocked = hill_calculator._get_chn_adstocked_from_output_collect() + + # Assert that the result chn_adstocked is an empty DataFrame + self.assertTrue(chn_adstocked.empty) + + def test_no_matching_solID(self): + # Mock the media_vec_collect DataFrame with non-matching solIDs + mock_media_vec_collect = pd.DataFrame( + { + "type": ["adstockedMedia", "adstockedMedia"], + "solID": ["non_matching_model_1", "non_matching_model_2"], + "media_1": [0.1, 0.2], + "media_2": [0.3, 0.4], + } + ) + + # Mock the MMMData and ModelOutputs + mock_mmmdata_spec = type( + "MockMMMDataSpec", (object,), {"window_start": 1, "window_end": 2} + )() + mock_mmmdata = type( + "MockMMMData", (object,), {"mmmdata_spec": mock_mmmdata_spec} + )() + + mock_model_outputs = type( + "MockModelOutputs", (object,), {"media_vec_collect": mock_media_vec_collect} + )() + + # Create HillCalculator instance with mocked data + hill_calculator = HillCalculator( + mmmdata=mock_mmmdata, + model_outputs=mock_model_outputs, + dt_hyppar=pd.DataFrame(), + dt_coef=pd.DataFrame(), + media_spend_sorted=["media_1", "media_2"], + select_model="model_1", + ) + + # Invoke the method and assert the result + chn_adstocked = hill_calculator._get_chn_adstocked_from_output_collect() + self.assertTrue(chn_adstocked.empty) + + def test_valid_matching_solID_and_window_slicing(self): + # Mock the ModelOutputs media_vec_collect DataFrame + mock_media_vec_collect = pd.DataFrame( + { + "type": ["adstockedMedia", "adstockedMedia", "adstockedMedia"], + "solID": ["model_1", "model_1", "model_1"], + "media_1": [100, 200, 300], + "media_2": [400, 500, 600], + } + ) + + # Mock MMMData with window specification + mock_mmmdata_spec = type( + "MockMMMDataSpec", (object,), {"window_start": 1, "window_end": 2} + )() + mock_mmmdata = type( + "MockMMMData", (object,), {"mmmdata_spec": mock_mmmdata_spec} + )() + + # Mock ModelOutputs + mock_model_outputs = type( + "MockModelOutputs", (object,), {"media_vec_collect": mock_media_vec_collect} + )() + + # Initialize the HillCalculator with mock data + calculator = HillCalculator( + mmmdata=mock_mmmdata, + model_outputs=mock_model_outputs, + dt_hyppar=None, # Not used in this test + dt_coef=None, # Not used in this test + media_spend_sorted=["media_1", "media_2"], + select_model="model_1", + ) + + # Invoke the method under test + chn_adstocked = calculator._get_chn_adstocked_from_output_collect() + + # Expected sliced DataFrame + expected_chn_adstocked = pd.DataFrame( + {"media_1": [200, 300], "media_2": [500, 600]} + ).reset_index(drop=True) + + # Assert the result matches the expected DataFrame + pd.testing.assert_frame_equal( + chn_adstocked.reset_index(drop=True), expected_chn_adstocked + ) + + def test_get_hill_params_with_normal_input_data(self): + # Mock setup + mock_dt_hyppar = Mock(spec=pd.DataFrame) + mock_dt_hyppar.filter.return_value = pd.DataFrame( + { + "media1_alphas": [0.5], + "media2_alphas": [0.7], + "media1_gammas": [0.3], + "media2_gammas": [0.4], + } + ) + + adstocked_data = { + "media1": pd.Series({"min": 100, "max": 200}), + "media2": pd.Series({"min": 150, "max": 250}), + } + mock_chn_adstocked = MagicMock(spec=pd.DataFrame) + mock_chn_adstocked.__getitem__.side_effect = adstocked_data.get + mock_dt_coef = pd.DataFrame( + {"rn": ["media1", "media2"], "coef": ["coef1", "coef2"]} + ) + # Input preparation + media_spend_sorted = ["media1", "media2"] + mock_mmmdata = Mock(spec=MMMData) + mock_model_outputs = Mock(spec=ModelOutputs) + # Instantiate HillCalculator with mocks + hill_calculator = HillCalculator( + mmmdata=mock_mmmdata, + model_outputs=mock_model_outputs, + dt_hyppar=mock_dt_hyppar, + dt_coef=mock_dt_coef, + media_spend_sorted=media_spend_sorted, + select_model="model_1", + chn_adstocked=mock_chn_adstocked, + ) + # Invoke function + result = hill_calculator.get_hill_params() + # Assertions + assert result["alphas"] == [0.5, 0.7] + assert result["inflexions"] == [130.0, 190.0] + assert result["coefs_sorted"] == ["coef1", "coef2"] + + def test_get_hill_params_with_chn_adstocked_none(self): + # Create mock data + mock_chn_adstocked = pd.DataFrame({"media1": [100, 200], "media2": [150, 250]}) + + mock_dt_hyppar = pd.DataFrame( + { + "media1_alphas": [0.5], + "media2_alphas": [0.7], + "media1_gammas": [0.2], + "media2_gammas": [0.3], + } + ) + + mock_dt_coef = pd.DataFrame( + {"rn": ["media1", "media2"], "coef": ["coef1", "coef2"]} + ) + + # Mock MMMData and ModelOutputs + mock_mmmdata = Mock() + mock_mmmdata.mmmdata_spec.window_start = 0 + mock_mmmdata.mmmdata_spec.window_end = 1 + + mock_model_outputs = Mock() + mock_model_outputs.media_vec_collect = pd.DataFrame( + { + "type": ["adstockedMedia", "adstockedMedia"], + "solID": ["model1", "model1"], + "media1": [100, 200], + "media2": [150, 250], + } + ) + + # Initialize the HillCalculator with the mock data + calculator = HillCalculator( + mmmdata=mock_mmmdata, + model_outputs=mock_model_outputs, + dt_hyppar=mock_dt_hyppar, + dt_coef=mock_dt_coef, + media_spend_sorted=["media1", "media2"], + select_model="model1", + chn_adstocked=None, + ) + + # Mock the method _get_chn_adstocked_from_output_collect + calculator._get_chn_adstocked_from_output_collect = Mock( + return_value=mock_chn_adstocked + ) + + # Execute the get_hill_params function + result = calculator.get_hill_params() + + # Assertions + assert result["alphas"] == [0.5, 0.7] + assert result["inflexions"] == [120.0, 180.0] + assert result["coefs_sorted"] == ["coef1", "coef2"] + + def test_get_hill_params_with_empty_media_spend_sorted(self): + mock_mmmdata = Mock() + mock_model_outputs = Mock() + dt_hyppar = pd.DataFrame( + { + "media1_alphas": [0.1], + "media1_gammas": [0.2], + } + ) + dt_coef = pd.DataFrame( + { + "rn": ["media1"], + "coef": [1.0], + } + ) + chn_adstocked = pd.DataFrame() + + hill_calculator = HillCalculator( + mmmdata=mock_mmmdata, + model_outputs=mock_model_outputs, + dt_hyppar=dt_hyppar, + dt_coef=dt_coef, + media_spend_sorted=[], + select_model="model_1", + chn_adstocked=chn_adstocked, + ) + + result = hill_calculator.get_hill_params() + + # Assertions + self.assertEqual(result["alphas"], []) + self.assertEqual(result["inflexions"], []) + self.assertEqual(result["coefs_sorted"], []) diff --git a/python/tests/unit/modeling/pareto/test_response_curve.py b/python/tests/unit/modeling/pareto/test_response_curve.py new file mode 100644 index 000000000..82bc32f38 --- /dev/null +++ b/python/tests/unit/modeling/pareto/test_response_curve.py @@ -0,0 +1,223 @@ +import unittest +from unittest.mock import MagicMock +import pandas as pd +import numpy as np +from matplotlib.figure import Figure +from robyn.data.entities.mmmdata import MMMData +from robyn.modeling.entities.modeloutputs import ModelOutputs +from robyn.data.entities.hyperparameters import ChannelHyperparameters, Hyperparameters +from robyn.data.entities.enums import AdstockType +from robyn.modeling.transformations.transformations import Transformation +from robyn.modeling.pareto.response_curve import ( + ResponseCurveCalculator, + ResponseOutput, + UseCase, + MetricDateInfo, + MetricValueInfo, +) + + +class TestResponseCurveCalculator(unittest.TestCase): + + def setUp(self): + # Mocking the dependencies + self.mock_mmm_data = MagicMock(spec=MMMData) + self.mock_mmm_data.mmmdata_spec = MagicMock() + self.mock_model_outputs = MagicMock(spec=ModelOutputs) + self.mock_hyperparameter = MagicMock(spec=Hyperparameters) + self.mock_transformation = MagicMock(spec=Transformation) + + # Instantiating the ResponseCurveCalculator + self.calculator = ResponseCurveCalculator( + self.mock_mmm_data, self.mock_model_outputs, self.mock_hyperparameter + ) + + def test_calculate_response(self): + # Mock data setup + self.mock_mmm_data.data = pd.DataFrame( + { + "spend_metric": [1, 2, 3, 4, 5], + "date_var": pd.date_range("2020-01-01", periods=5), + } + ) + self.mock_mmm_data.mmmdata_spec.date_var = "date_var" + self.mock_mmm_data.mmmdata_spec.paid_media_spends = ["spend_metric"] + self.mock_mmm_data.mmmdata_spec.paid_media_vars = ["exposure_metric"] + self.mock_mmm_data.mmmdata_spec.organic_vars = ["organic_metric"] + self.mock_mmm_data.mmmdata_spec.rolling_window_start_which = 0 + self.mock_mmm_data.mmmdata_spec.rolling_window_end_which = 5 + select_model = "model1" + metric_name = "spend_metric" + metric_value = [100, 200, 300, 400, 500] + date_range = "all" + dt_hyppar = pd.DataFrame( + { + "sol_id": ["model1"], + "spend_metric_alphas": [0.1], + "spend_metric_gammas": [0.2], + } + ) + dt_coef = pd.DataFrame( + {"sol_id": ["model1"], "rn": ["spend_metric"], "coef": [0.5]} + ) + # Mock the transformation methods + self.calculator.transformation = MagicMock() # Ensure transformation is a mock + self.calculator.transformation.transform_adstock.return_value = MagicMock( + x_decayed=np.array([1, 2, 3]), + x_imme=np.array([0.5, 1, 1.5]), + x=np.array([1, 2, 3]), + ) + + response_output = self.calculator.calculate_response( + select_model, + metric_name, + metric_value, + date_range, + False, + dt_hyppar, + dt_coef=dt_coef, + ) + + self.assertIsInstance(response_output, ResponseOutput) + self.assertEqual(response_output.metric_name, metric_name) + + def test__which_usecase(self): + usecase = self.calculator._which_usecase(None, None) + self.assertEqual(usecase, UseCase.ALL_HISTORICAL_VEC) + + usecase = self.calculator._which_usecase(None, "selected") + self.assertEqual(usecase, UseCase.SELECTED_HISTORICAL_VEC) + + usecase = self.calculator._which_usecase(10.0, None) + self.assertEqual(usecase, UseCase.TOTAL_METRIC_DEFAULT_RANGE) + + usecase = self.calculator._which_usecase(10.0, "selected") + self.assertEqual(usecase, UseCase.TOTAL_METRIC_SELECTED_RANGE) + + usecase = self.calculator._which_usecase([1.0, 2.0, 3.0], None) + self.assertEqual(usecase, UseCase.UNIT_METRIC_DEFAULT_LAST_N) + + usecase = self.calculator._which_usecase([1.0, 2.0, 3.0], "selected") + self.assertEqual(usecase, UseCase.UNIT_METRIC_SELECTED_DATES) + + def test__check_metric_type(self): + self.mock_mmm_data.mmmdata_spec.paid_media_spends = ["spend_metric"] + self.mock_mmm_data.mmmdata_spec.paid_media_vars = ["exposure_metric"] + self.mock_mmm_data.mmmdata_spec.organic_vars = ["organic_metric"] + + metric_type = self.calculator._check_metric_type("spend_metric") + self.assertEqual(metric_type, "spend") + + metric_type = self.calculator._check_metric_type("exposure_metric") + self.assertEqual(metric_type, "exposure") + + metric_type = self.calculator._check_metric_type("organic_metric") + self.assertEqual(metric_type, "organic") + + with self.assertRaises(ValueError): + self.calculator._check_metric_type("unknown_metric") + + def test__check_metric_dates(self): + + all_dates = pd.Series(pd.date_range("2020-01-01", periods=5)) + self.mock_mmm_data.mmmdata_spec.rolling_window_start_which = 0 + self.mock_mmm_data.mmmdata_spec.rolling_window_end_which = 5 + + metric_date_info = self.calculator._check_metric_dates(None, all_dates, False) + self.assertIsInstance(metric_date_info, MetricDateInfo) + self.assertEqual(len(metric_date_info.date_range_updated), 5) + + metric_date_info = self.calculator._check_metric_dates( + "last_3", all_dates, False + ) + self.assertEqual(len(metric_date_info.date_range_updated), 3) + + metric_date_info = self.calculator._check_metric_dates( + ["2020-01-01", "2020-01-04"], all_dates, False + ) + self.assertEqual(len(metric_date_info.date_range_updated), 4) + + with self.assertRaises(ValueError): + self.calculator._check_metric_dates("invalid_range", all_dates, False) + + def test__check_metric_value(self): + all_values = pd.Series([1, 2, 3, 4, 5]) + metric_loc = slice(0, 3) + + metric_value_info = self.calculator._check_metric_value( + None, "metric_name", all_values, metric_loc + ) + self.assertIsInstance(metric_value_info, MetricValueInfo) + self.assertTrue((metric_value_info.metric_value_updated == [1, 2, 3]).all()) + + metric_value_info = self.calculator._check_metric_value( + 10, "metric_name", all_values, metric_loc + ) + self.assertTrue((metric_value_info.metric_value_updated == [10, 10, 10]).all()) + + with self.assertRaises(ValueError): + self.calculator._check_metric_value( + [1, 2], "metric_name", all_values, metric_loc + ) + + def test__transform_exposure_to_spend(self): + metric_name = "exposure_metric" + metric_value_updated = np.array([100, 200, 300]) + all_values_updated = pd.Series([1, 2, 3, 4, 5]) + metric_loc = slice(0, 3) + + self.mock_mmm_data.mmmdata_spec.modNLS = { + "results": pd.DataFrame( + { + "channel": ["exposure_metric"], + "rsq_nls": [0.9], + "rsq_lm": [0.8], + "Vmax": [1000], + "Km": [10], + "coef_lm": [1], + } + ) + } + + updated_values = self.calculator._transform_exposure_to_spend( + metric_name, metric_value_updated, all_values_updated, metric_loc + ) + self.assertIsInstance(updated_values, pd.Series) + + def test__get_spend_name(self): + self.mock_mmm_data.mmmdata_spec.paid_media_spends = ["spend_metric"] + self.mock_mmm_data.mmmdata_spec.paid_media_vars = ["exposure_metric"] + + spend_name = self.calculator._get_spend_name("exposure_metric") + self.assertEqual(spend_name, "spend_metric") + + def test__get_channel_hyperparams(self): + dt_hyppar = pd.DataFrame( + { + "sol_id": ["model1"], + "spend_metric_thetas": [[0.1]], + "spend_metric_shapes": [[0.2]], + "spend_metric_scales": [[0.3]], + } + ) + + self.mock_hyperparameter.adstock = AdstockType.WEIBULL + + channel_hyperparams = self.calculator._get_channel_hyperparams( + "model1", "spend_metric", dt_hyppar + ) + self.assertIsInstance(channel_hyperparams, ChannelHyperparameters) + + def test__get_saturation_params(self): + dt_hyppar = pd.DataFrame( + { + "sol_id": ["model1"], + "spend_metric_alphas": [[0.1]], + "spend_metric_gammas": [[0.2]], + } + ) + + saturation_params = self.calculator._get_saturation_params( + "model1", "spend_metric", dt_hyppar + ) + self.assertIsInstance(saturation_params, ChannelHyperparameters) diff --git a/python/tests/unit/modeling/ridge/test_adstock.py b/python/tests/unit/modeling/ridge/test_adstock.py new file mode 100644 index 000000000..cf9740c9e --- /dev/null +++ b/python/tests/unit/modeling/ridge/test_adstock.py @@ -0,0 +1,31 @@ +import pytest +import numpy as np +import pandas as pd +from scipy.signal import lfilter +from robyn.modeling.ridge.ridge_data_builder import RidgeDataBuilder + + +def original_geometric_adstock(x: pd.Series, theta: float) -> pd.Series: + y = x.copy() + for i in range(1, len(x)): + y.iloc[i] += theta * y.iloc[i - 1] + return y + + +@pytest.mark.parametrize("theta", [0, 0.5, 0.8, 1]) +def test_geometric_adstock(theta): + x = pd.Series(np.random.rand(10_000)) # Random test data + + # Instantiate the RidgeDataBuilder object (without requiring real data) + dummy_data = None + ridge_builder = RidgeDataBuilder(dummy_data, dummy_data) + + # Call the actual function from the RidgeDataBuilder instance + optimized = ridge_builder._geometric_adstock(x, theta) + + # Compute the expected output using the original function + original = original_geometric_adstock(x, theta) + + assert np.allclose( + original, optimized, atol=1e-6 + ), f"Mismatch found for theta={theta}" diff --git a/python/tests/unit/modeling/test_feature_engineering.py b/python/tests/unit/modeling/test_feature_engineering.py new file mode 100644 index 000000000..fc9cc1699 --- /dev/null +++ b/python/tests/unit/modeling/test_feature_engineering.py @@ -0,0 +1,266 @@ +# # pyre-strict + +# import pytest +# import pandas as pd +# import numpy as np +# from unittest.mock import MagicMock, patch +# from pathlib import Path +# from prophet import Prophet +# from robyn.modeling.feature_engineering import FeatureEngineering, FeaturizedMMMData +# from robyn.data.entities.mmmdata import MMMData +# from robyn.data.entities.hyperparameters import Hyperparameters, ChannelHyperparameters +# from robyn.data.entities.holidays_data import HolidaysData +# from robyn.data.entities.enums import AdstockType + + +# @pytest.fixture(scope="session") +# def test_data(): +# resources_path = Path("python/src/robyn/tutorials/resources") +# dt_simulated = pd.read_csv(resources_path / "dt_simulated_weekly.csv", parse_dates=["DATE"]) +# dt_holidays = pd.read_csv(resources_path / "dt_prophet_holidays.csv", parse_dates=["ds"]) +# return dt_simulated, dt_holidays + + +# @pytest.fixture +# def feature_engineering_setup(test_data): +# dt_simulated, dt_holidays = test_data + +# mmm_data = MagicMock(spec=MMMData) +# hyperparameters = MagicMock(spec=Hyperparameters) +# holidays_data = MagicMock(spec=HolidaysData) + +# mmm_data.mmmdata_spec = MagicMock() +# mmm_data.mmmdata_spec.date_var = "DATE" +# mmm_data.mmmdata_spec.dep_var = "revenue" +# mmm_data.mmmdata_spec.paid_media_spends = ["facebook_S"] +# mmm_data.mmmdata_spec.paid_media_vars = ["facebook_I"] +# mmm_data.mmmdata_spec.window_start = pd.Timestamp("2015-11-23") +# mmm_data.mmmdata_spec.window_end = pd.Timestamp("2015-12-21") +# mmm_data.mmmdata_spec.interval_type = "week" +# mmm_data.mmmdata_spec.day_interval = 7 +# mmm_data.mmmdata_spec.context_vars = ["competitor_sales_B"] +# mmm_data.mmmdata_spec.organic_vars = ["events", "newsletter"] +# mmm_data.mmmdata_spec.factor_vars = [] +# mmm_data.data = dt_simulated.copy() +# mmm_data.mmmdata_spec.get_paid_media_var = MagicMock(return_value="facebook_I") + +# holidays_data.prophet_vars = ["trend", "season", "holiday"] +# holidays_data.dt_holidays = dt_holidays.copy() +# holidays_data.prophet_country = "AD" + +# hyperparameters.adstock = AdstockType.GEOMETRIC + +# feature_engineering = FeatureEngineering(mmm_data, hyperparameters, holidays_data) + +# return feature_engineering, mmm_data, hyperparameters, holidays_data, dt_simulated, dt_holidays + + +# def test_initialization(feature_engineering_setup): +# """Test initialization of FeatureEngineering class""" +# feature_engineering, mmm_data, hyperparameters, holidays_data, _, _ = feature_engineering_setup + +# assert isinstance(feature_engineering.mmm_data, MMMData) +# assert isinstance(feature_engineering.hyperparameters, Hyperparameters) +# assert isinstance(feature_engineering.holidays_data, HolidaysData) +# assert feature_engineering.logger is not None + + +# def test_perform_feature_engineering(feature_engineering_setup): +# """Test the complete feature engineering pipeline""" +# feature_engineering, *_ = feature_engineering_setup +# result = feature_engineering.perform_feature_engineering(quiet=True) + +# assert isinstance(result, FeaturizedMMMData) +# assert isinstance(result.dt_mod, pd.DataFrame) +# assert isinstance(result.dt_modRollWind, pd.DataFrame) +# assert isinstance(result.modNLS, dict) +# assert "results" in result.modNLS +# assert "yhat" in result.modNLS +# assert "plots" in result.modNLS + + +# def test_prepare_data(feature_engineering_setup): +# """Test data preparation method""" +# feature_engineering, _, _, _, dt_simulated, _ = feature_engineering_setup +# result = feature_engineering._prepare_data() + +# assert "ds" in result.columns +# assert "revenue" in result.columns +# assert "competitor_sales_B" in result.columns +# assert len(result) == len(dt_simulated) + +# if not pd.api.types.is_datetime64_any_dtype(result["ds"]): +# result["ds"] = pd.to_datetime(result["ds"]) +# assert pd.api.types.is_datetime64_any_dtype(result["ds"]) + + +# def test_create_rolling_window_data_with_both_windows(feature_engineering_setup): +# """Test rolling window creation with both start and end dates""" +# feature_engineering, mmm_data, _, _, dt_simulated, _ = feature_engineering_setup +# dt_transform = pd.DataFrame({"ds": pd.to_datetime(dt_simulated["DATE"]), "revenue": dt_simulated["revenue"]}) +# result = feature_engineering._create_rolling_window_data(dt_transform) + +# assert all(result["ds"] >= mmm_data.mmmdata_spec.window_start) +# assert all(result["ds"] <= mmm_data.mmmdata_spec.window_end) + + +# def test_create_rolling_window_data_with_no_windows(feature_engineering_setup): +# """Test rolling window creation with no window constraints""" +# feature_engineering, mmm_data, _, _, dt_simulated, _ = feature_engineering_setup +# mmm_data.mmmdata_spec.window_start = None +# mmm_data.mmmdata_spec.window_end = None + +# dt_transform = pd.DataFrame({"ds": pd.to_datetime(dt_simulated["DATE"]), "revenue": dt_simulated["revenue"]}) +# result = feature_engineering._create_rolling_window_data(dt_transform) +# assert len(result) == len(dt_transform) + + +# def test_create_rolling_window_invalid_dates(feature_engineering_setup): +# """Test rolling window creation with invalid date ranges""" +# feature_engineering, mmm_data, _, _, dt_simulated, _ = feature_engineering_setup +# dt_transform = pd.DataFrame({"ds": pd.to_datetime(dt_simulated["DATE"]), "revenue": dt_simulated["revenue"]}) + +# # Test start after end +# mmm_data.mmmdata_spec.window_start = pd.Timestamp("2015-12-31") +# mmm_data.mmmdata_spec.window_end = pd.Timestamp("2015-01-01") + +# with pytest.raises(ValueError): +# feature_engineering._create_rolling_window_data(dt_transform) + + +# def test_calculate_media_cost_factor(feature_engineering_setup): +# """Test media cost factor calculation""" +# feature_engineering, _, _, _, dt_simulated, _ = feature_engineering_setup +# dt_input = dt_simulated[["facebook_S"]].copy() +# result = feature_engineering._calculate_media_cost_factor(dt_input) + +# assert len(result) == 1 # One media channel +# assert pytest.approx(result.sum()) == 1.0 # Should sum to 1 +# assert all(0 <= x <= 1 for x in result) # Values between 0 and 1 + + +# def test_run_models(feature_engineering_setup): +# """Test model running for media variables""" +# feature_engineering, _, _, _, dt_simulated, _ = feature_engineering_setup +# dt_modRollWind = dt_simulated[["facebook_S", "facebook_I"]].copy() +# result = feature_engineering._run_models(dt_modRollWind, 1.0) + +# assert "results" in result +# assert "yhat" in result +# assert "plots" in result + + +# def test_hill_function(feature_engineering_setup): +# """Test Hill function transformation""" +# feature_engineering, _, _, _, _, _ = feature_engineering_setup +# x = np.array([1, 2, 3, 4, 5]) +# alpha = 2 +# gamma = 3 +# result = feature_engineering._hill_function(x, alpha, gamma) + +# assert len(result) == len(x) +# assert all(0 <= r <= 1 for r in result) + + +# @pytest.mark.parametrize( +# "adstock_type,params", +# [ +# (AdstockType.GEOMETRIC, {"thetas": [0.5]}), +# (AdstockType.WEIBULL_CDF, {"shapes": [1.0], "scales": [1.0]}), +# (AdstockType.WEIBULL_PDF, {"shapes": [1.0], "scales": [1.0]}), +# ], +# ) +# def test_apply_adstock(feature_engineering_setup, adstock_type, params): +# """Test different adstock transformations""" +# feature_engineering, _, hyperparameters, _, _, _ = feature_engineering_setup +# x = pd.Series([1, 2, 3, 4, 5]) +# params_mock = MagicMock(spec=ChannelHyperparameters) +# for key, value in params.items(): +# setattr(params_mock, key, value) + +# hyperparameters.adstock = adstock_type +# result = feature_engineering._apply_adstock(x, params_mock) +# assert len(result) == len(x) + + +# def test_apply_adstock_invalid(feature_engineering_setup): +# """Test invalid adstock type handling""" +# feature_engineering, _, hyperparameters, _, _, _ = feature_engineering_setup +# x = pd.Series([1, 2, 3, 4, 5]) +# params = MagicMock(spec=ChannelHyperparameters) +# hyperparameters.adstock = "INVALID" + +# with pytest.raises(ValueError): +# feature_engineering._apply_adstock(x, params) + + +# @pytest.mark.parametrize( +# "prophet_vars", +# [ +# ["trend", "season", "holiday"], +# ["trend", "season"], +# ["trend", "holiday"], +# ], +# ) +# def test_prophet_decomposition(feature_engineering_setup, prophet_vars): +# """Test Prophet decomposition with different variables""" +# feature_engineering, _, _, holidays_data, dt_simulated, _ = feature_engineering_setup +# holidays_data.prophet_vars = prophet_vars + +# dt_mod = pd.DataFrame( +# { +# "ds": pd.to_datetime(dt_simulated["DATE"]), +# "dep_var": dt_simulated["revenue"], +# "facebook_S": dt_simulated["facebook_S"], +# "competitor_sales_B": dt_simulated["competitor_sales_B"], +# "events": dt_simulated["events"], +# "newsletter": dt_simulated["newsletter"], +# } +# ) + +# with patch("prophet.Prophet") as mock_prophet: +# mock_prophet_instance = MagicMock() +# mock_prophet_instance.fit.return_value = None +# prophet_output = pd.DataFrame( +# { +# "ds": dt_mod["ds"], +# "trend": np.ones(len(dt_mod)), +# "yearly": np.zeros(len(dt_mod)), +# "holidays": np.zeros(len(dt_mod)), +# "yhat": np.ones(len(dt_mod)), +# } +# ) +# mock_prophet_instance.predict.return_value = prophet_output +# mock_prophet.return_value = mock_prophet_instance + +# result = feature_engineering._prophet_decomposition(dt_mod) + +# expected_columns = [var for var in prophet_vars if var != "season"] + ( +# ["season"] if "season" in prophet_vars else [] +# ) +# for col in expected_columns: +# assert col in result.columns + + +# @pytest.mark.parametrize("interval_type", ["day", "month"]) +# def test_set_holidays(feature_engineering_setup, interval_type): +# """Test holiday setting for different interval types""" +# feature_engineering, _, _, _, _, dt_holidays = feature_engineering_setup + +# if interval_type == "day": +# dt_transform = pd.DataFrame({"ds": pd.date_range(start="2015-01-01", end="2015-01-10")}) +# else: +# dt_transform = pd.DataFrame({"ds": pd.date_range(start="2015-01-01", end="2015-12-01", freq="MS")}) + +# result = feature_engineering._set_holidays(dt_transform, dt_holidays, interval_type) + +# assert all(col in result.columns for col in ["holiday", "ds", "country"]) + + +# def test_set_holidays_invalid_interval(feature_engineering_setup): +# """Test invalid interval type handling""" +# feature_engineering, _, _, _, _, dt_holidays = feature_engineering_setup +# dt_transform = pd.DataFrame({"ds": pd.date_range(start="2015-01-01", end="2015-01-10")}) + +# with pytest.raises(ValueError): +# feature_engineering._set_holidays(dt_transform, dt_holidays, "invalid") diff --git a/python/tests/unit/modeling_pareto/test_pareto_utils.py b/python/tests/unit/modeling_pareto/test_pareto_utils.py new file mode 100644 index 000000000..7eb7be89f --- /dev/null +++ b/python/tests/unit/modeling_pareto/test_pareto_utils.py @@ -0,0 +1,85 @@ +import numpy as np +import pandas as pd +import pytest +from robyn.modeling.pareto.pareto_utils import ParetoUtils + + +@pytest.fixture +def test_data(): + return pd.DataFrame( + { + "nrmse_test": [0.1, 0.2, 0.3, 0.4, 0.5, np.inf], + "nrmse_train": [0.15, 0.25, 0.35, 0.45, 0.55, 0.65], + "decomp.rssd": [0.2, 0.3, 0.4, 0.5, 0.6, np.inf], + "mape": [0.05, 0.1, 0.15, 0.2, 0.25, np.nan], + } + ) + + +def test_calculate_errors_scores_default(test_data): + result = ParetoUtils.calculate_errors_scores(test_data) + expected = np.array([0.0, 0.1443376, 0.2886751, 0.4330127, 0.5773503, 0.4714045]) + np.testing.assert_almost_equal(result, expected, decimal=2) + + +def test_calculate_errors_scores_custom_balance(test_data): + result = ParetoUtils.calculate_errors_scores(test_data, balance=[2, 1, 1]) + expected = np.array([0.0, 0.1545743, 0.3091487, 0.4637231, 0.6182975, 0.5590170]) + np.testing.assert_almost_equal(result, expected, decimal=2) + + +def test_calculate_errors_scores_ts_validation_false(test_data): + result = ParetoUtils.calculate_errors_scores(test_data, ts_validation=False) + expected = np.array([0.0, 0.1361372, 0.2722745, 0.4082483, 0.5443118, 0.4714045]) + np.testing.assert_almost_equal(result, expected, decimal=2) + + +def test_calculate_errors_scores_all_infinite(): + inf_data = pd.DataFrame( + { + "nrmse_test": [np.inf, np.inf], + "nrmse_train": [np.inf, np.inf], + "decomp.rssd": [np.inf, np.inf], + "mape": [np.inf, np.inf], + } + ) + result = ParetoUtils.calculate_errors_scores(inf_data) + expected = np.array([0.0, 0.0]) + np.testing.assert_almost_equal(result, expected, decimal=2) + + +def test_calculate_errors_scores_single_row(): + single_row = pd.DataFrame( + { + "nrmse_test": [0.1], + "nrmse_train": [0.15], + "decomp.rssd": [0.2], + "mape": [0.05], + } + ) + result = ParetoUtils.calculate_errors_scores(single_row) + expected = np.array(0.0763763) + np.testing.assert_almost_equal(result, expected, decimal=7) + + +def test_min_max_norm(): + series = pd.Series([1, 2, 3, 4, 5]) + normalized = ParetoUtils.min_max_norm(series) + expected = pd.Series([0.0, 0.25, 0.5, 0.75, 1.0]) + pd.testing.assert_series_equal(normalized, expected) + + +def test_min_max_norm_constant_values(): + series = pd.Series([5, 5, 5]) + normalized = ParetoUtils.min_max_norm(series) + expected = pd.Series( + [5, 5, 5] + ) # Should return the same values since they are constant + pd.testing.assert_series_equal(normalized, expected) + + +def test_min_max_norm_single_value(): + series = pd.Series([10]) + normalized = ParetoUtils.min_max_norm(series) + expected = pd.Series([10]) # Should return the same value since there's only one + pd.testing.assert_series_equal(normalized, expected) diff --git a/python/tests/unit/test_calibration_input_validation.py b/python/tests/unit/test_calibration_input_validation.py new file mode 100644 index 000000000..bef47201d --- /dev/null +++ b/python/tests/unit/test_calibration_input_validation.py @@ -0,0 +1,464 @@ +import pytest +import pandas as pd +from datetime import datetime, timedelta +from src.robyn.data.entities.calibration_input import ( + CalibrationInput, + ChannelCalibrationData, +) +from src.robyn.data.entities.mmmdata import MMMData +from src.robyn.data.validation.calibration_input_validation import ( + CalibrationInputValidation, +) +from src.robyn.data.entities.enums import DependentVarType, CalibrationScope + + +@pytest.fixture +def sample_mmmdata(): + data = pd.DataFrame( + { + "date": pd.date_range(start="2022-01-01", periods=10), + "revenue": [100, 120, 110, 130, 140, 150, 160, 170, 180, 190], + "tv_spend": [50, 60, 55, 65, 70, 75, 80, 85, 90, 95], + "radio_spend": [30, 35, 32, 38, 40, 42, 45, 48, 50, 52], + "temperature": [20, 22, 21, 23, 24, 25, 26, 27, 28, 29], + } + ) + + mmm_data_spec = MMMData.MMMDataSpec( + dep_var="revenue", + date_var="date", + paid_media_spends=["tv_spend", "radio_spend"], + context_vars=["temperature"], + ) + + return MMMData(data, mmm_data_spec) + + +@pytest.fixture +def sample_calibration_input(sample_mmmdata): + """Create a sample calibration input with actual spend values.""" + data = sample_mmmdata.data + tv_spend = data.loc[ + data["date"].between("2022-01-01", "2022-01-05"), "tv_spend" + ].sum() + radio_spend = data.loc[ + data["date"].between("2022-01-06", "2022-01-10"), "radio_spend" + ].sum() + + tv_channel_key = ("tv_spend",) + radio_channel_key = ("radio_spend",) + + return CalibrationInput( + channel_data={ + tv_channel_key: ChannelCalibrationData( + lift_start_date=pd.Timestamp("2022-01-01"), + lift_end_date=pd.Timestamp("2022-01-05"), + lift_abs=1000, + spend=tv_spend, + confidence=0.9, + metric=DependentVarType.REVENUE, + calibration_scope=CalibrationScope.IMMEDIATE, + ), + radio_channel_key: ChannelCalibrationData( + lift_start_date=pd.Timestamp("2022-01-06"), + lift_end_date=pd.Timestamp("2022-01-10"), + lift_abs=2000, + spend=radio_spend, + confidence=0.85, + metric=DependentVarType.REVENUE, + calibration_scope=CalibrationScope.IMMEDIATE, + ), + } + ) + + +@pytest.fixture +def sample_multichannel_calibration_input(sample_mmmdata): + """Create a sample multichannel calibration input.""" + data = sample_mmmdata.data + combined_spend = ( + data.loc[ + data["date"].between("2022-01-01", "2022-01-05"), + ["tv_spend", "radio_spend"], + ] + .sum() + .sum() + ) + tv_spend = data.loc[ + data["date"].between("2022-01-06", "2022-01-10"), "tv_spend" + ].sum() + + return CalibrationInput( + channel_data={ + ( + "tv_spend", + "radio_spend", + ): ChannelCalibrationData( # Changed from 'tv_spend+radio_spend' to tuple + lift_start_date=pd.Timestamp("2022-01-01"), + lift_end_date=pd.Timestamp("2022-01-05"), + lift_abs=3000, + spend=combined_spend, + confidence=0.9, + metric=DependentVarType.REVENUE, + calibration_scope=CalibrationScope.IMMEDIATE, + ), + ("tv_spend",): ChannelCalibrationData( + lift_start_date=pd.Timestamp("2022-01-06"), + lift_end_date=pd.Timestamp("2022-01-10"), + lift_abs=1000, + spend=tv_spend, + confidence=0.85, + metric=DependentVarType.REVENUE, + calibration_scope=CalibrationScope.IMMEDIATE, + ), + } + ) + + +def test_check_calibration_valid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=pd.Timestamp("2022-01-01"), + window_end=pd.Timestamp("2022-01-10"), + ) + result = validator.check_calibration() + assert result.status == True + assert not result.error_details + assert not result.error_message + + +def test_check_date_range_invalid(sample_mmmdata, sample_calibration_input): + # First create the validator + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + # Then use the static method to create modified input + new_calibration_input = ( + CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, + ("tv_spend",), + lift_start_date=datetime(2021, 12, 31), + ) + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + new_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_date_range() + assert result.status == False + assert ("tv_spend",) in result.error_details + assert "outside the modeling window" in result.error_message + + +def test_check_lift_values_invalid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + new_calibration_input = ( + CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, ("radio_spend",), lift_abs="invalid" + ) + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + new_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_lift_values() + assert result.status == False + assert ("radio_spend",) in result.error_details + assert "must be a valid number" in result.error_message + + +def test_check_spend_values_invalid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + new_calibration_input = ( + CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, ("tv_spend",), spend=1000 + ) + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + new_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_spend_values() + assert result.status == False + assert ("tv_spend",) in result.error_details + assert "does not match the input data" in result.error_message + + +def test_check_confidence_values_invalid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + new_calibration_input = ( + CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, ("radio_spend",), confidence=0.7 + ) + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + new_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_confidence_values() + assert result.status == False + assert ("radio_spend",) in result.error_details + assert "lower than 80%" in result.error_message + + +def test_check_metric_values_invalid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + new_calibration_input = ( + CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, ("tv_spend",), metric=DependentVarType.CONVERSION + ) + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + new_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_metric_values() + assert result.status == False + assert ("tv_spend",) in result.error_details + assert "does not match the dependent variable" in result.error_message + + +def test_check_obj_weights_valid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=pd.Timestamp("2022-01-01"), + window_end=pd.Timestamp("2022-01-10"), + ) + result = validator.check_obj_weights([0, 1, 1], True) + assert result.status is True + assert not result.error_details + assert result.error_message == "" + + +def test_check_obj_weights_invalid(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + result = validator.check_obj_weights([0, 1, 1, 1], False) + assert result.status == False + assert "length" in result.error_details + assert "Invalid number of objective weights" in result.error_message + + result = validator.check_obj_weights([-1, 1, 11], False) + assert result.status == False + assert "range" in result.error_details + assert "Objective weights out of valid range" in result.error_message + + +def test_validate(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + results = validator.validate() + assert len(results) == 1 + assert all(result.status for result in results) + assert all(not result.error_details for result in results) + assert all(not result.error_message for result in results) + + # Test with invalid input + invalid_calibration_input = ( + CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, + ("tv_spend",), + lift_start_date=datetime(2021, 12, 31), + lift_abs="invalid", + spend=1000000, + confidence=0.5, + metric=DependentVarType.CONVERSION, + ) + ) + + invalid_validator = CalibrationInputValidation( + sample_mmmdata, + invalid_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + invalid_results = invalid_validator.validate() + assert len(invalid_results) == 1 + assert any(not result.status for result in invalid_results) + assert any(result.error_details for result in invalid_results) + assert any(result.error_message for result in invalid_results) + + +def test_multichannel_validation(sample_mmmdata, sample_multichannel_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_multichannel_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator.check_calibration() + assert result.status == True + assert not result.error_details + assert not result.error_message + + +def test_invalid_channel(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + invalid_input = CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, ("nonexistent_channel",), lift_abs=1000 + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + invalid_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_spend_values() + assert result.status == False + assert ("nonexistent_channel",) in result.error_details + assert "not found in data" in result.error_message.lower() + + +def test_invalid_multichannel_combination(sample_mmmdata): + invalid_combination = CalibrationInput( + channel_data={ + "tv_spend+nonexistent_channel": ChannelCalibrationData( + lift_start_date=pd.Timestamp("2022-01-01"), + lift_end_date=pd.Timestamp("2022-01-05"), + lift_abs=1000, + spend=300, + confidence=0.9, + metric=DependentVarType.REVENUE, + calibration_scope=CalibrationScope.IMMEDIATE, + ) + } + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + invalid_combination, + window_start=pd.Timestamp("2022-01-01"), + window_end=pd.Timestamp("2022-01-10"), + ) + result = validator._check_spend_values() + assert result.status is False + assert "not found in data" in result.error_message.lower() + + +def test_edge_cases(sample_mmmdata): + # Test with empty calibration input + empty_input = CalibrationInput(channel_data={}) + validator = CalibrationInputValidation( + sample_mmmdata, + empty_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator.check_calibration() + assert result.status == True # Empty input should be valid + + # Test with None calibration input + validator_none = CalibrationInputValidation( + sample_mmmdata, + None, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result_none = validator_none.check_calibration() + assert result_none.status == True # None input should be valid + + +def test_date_boundary_cases(sample_mmmdata, sample_calibration_input): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + # Test exact boundary dates + boundary_input = CalibrationInputValidation.create_modified_calibration_input( + sample_calibration_input, + ("tv_spend",), + lift_start_date=datetime(2022, 1, 1), # Exact start + lift_end_date=datetime(2022, 1, 10), # Exact end + ) + + validator = CalibrationInputValidation( + sample_mmmdata, + boundary_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + result = validator._check_date_range() + assert result.status == True + assert not result.error_details + + +def test_validate_with_multichannel( + sample_mmmdata, sample_multichannel_calibration_input +): + validator = CalibrationInputValidation( + sample_mmmdata, + sample_multichannel_calibration_input, + window_start=datetime(2022, 1, 1), + window_end=datetime(2022, 1, 10), + ) + + results = validator.validate() + assert len(results) == 1 + assert all(result.status for result in results) + assert all(not result.error_details for result in results) + assert all(not result.error_message for result in results) diff --git a/python/tests/unit/test_holidays_data_validation.py b/python/tests/unit/test_holidays_data_validation.py new file mode 100644 index 000000000..e0694673b --- /dev/null +++ b/python/tests/unit/test_holidays_data_validation.py @@ -0,0 +1,83 @@ +import pytest +import pandas as pd +import numpy as np +from datetime import datetime, timedelta +from src.robyn.data.entities.holidays_data import HolidaysData +from src.robyn.data.validation.holidays_data_validation import HolidaysDataValidation +from src.robyn.data.entities.enums import ProphetVariableType, ProphetSigns + + +@pytest.fixture +def sample_holidays_data(): + dates = pd.date_range(start="2023-01-01", end="2023-12-31", freq="D") + df = pd.DataFrame({"ds": dates, "country": "US", "holiday": "New Year"}) + return HolidaysData( + dt_holidays=df, + prophet_country="US", + prophet_vars=[ProphetVariableType.HOLIDAY], + prophet_signs=[ProphetSigns.POSITIVE], + ) + + +def test_check_holidays_no_issues(sample_holidays_data): + validator = HolidaysDataValidation(sample_holidays_data) + result = validator.check_holidays() + assert result.status == True + assert not result.error_details + assert not result.error_message + + +def test_check_holidays_with_missing_values(sample_holidays_data): + sample_holidays_data.dt_holidays.loc[0, "holiday"] = np.nan + validator = HolidaysDataValidation(sample_holidays_data) + result = validator.check_holidays() + assert result.status == False + assert "missing" in result.error_details + assert "holiday" in result.error_details["missing"] + + +def test_check_holidays_missing_required_column(sample_holidays_data): + sample_holidays_data.dt_holidays = sample_holidays_data.dt_holidays.drop( + "country", axis=1 + ) + validator = HolidaysDataValidation(sample_holidays_data) + result = validator.check_holidays() + assert result.status == False + assert "missing_columns" in result.error_details + assert "country" in result.error_details["missing_columns"] + + +def test_check_holidays_invalid_column_name(sample_holidays_data): + sample_holidays_data.dt_holidays = sample_holidays_data.dt_holidays.rename( + columns={"country": "country name"} + ) + validator = HolidaysDataValidation(sample_holidays_data) + result = validator.check_holidays() + assert result.status == False + assert "invalid" in result.error_details + assert "country name" in result.error_details["invalid"] + + +def test_check_prophet_valid_input(sample_holidays_data): + validator = HolidaysDataValidation(sample_holidays_data) + result = validator.check_prophet() + assert result.status == True + assert not result.error_details + assert not result.error_message + + +def test_validate_all_checks_including_prophet(sample_holidays_data): + validator = HolidaysDataValidation(sample_holidays_data) + results = validator.validate() + assert all(result.status for result in results) + + +def test_validate_with_issues(sample_holidays_data): + sample_holidays_data.dt_holidays.loc[0, "holiday"] = np.nan + sample_holidays_data.dt_holidays = sample_holidays_data.dt_holidays.rename( + columns={"country": "country_name"} + ) + validator = HolidaysDataValidation(sample_holidays_data) + results = validator.validate() + assert not all(result.status for result in results) + assert any("missing" in result.error_details for result in results) diff --git a/python/tests/unit/test_hyperparameter_validation.py b/python/tests/unit/test_hyperparameter_validation.py new file mode 100644 index 000000000..f57076c91 --- /dev/null +++ b/python/tests/unit/test_hyperparameter_validation.py @@ -0,0 +1,123 @@ +import pytest +from src.robyn.data.entities.hyperparameters import ( + Hyperparameters, + ChannelHyperparameters, +) +from src.robyn.data.validation.hyperparameter_validation import ( + HyperparametersValidation, +) +from src.robyn.data.entities.enums import AdstockType +from src.robyn.data.validation.validation import ValidationResult + + +@pytest.fixture +def sample_hyperparameters(): + return Hyperparameters( + hyperparameters={ + "channel1": ChannelHyperparameters( + thetas=[0.1, 0.9], + alphas=[0.5, 3.0], + gammas=[0.3, 1.0], + shapes=[0.0001, 2.0], + scales=[0.0001, 1.0], + ), + "channel2": ChannelHyperparameters( + thetas=[0.1, 0.9], + alphas=[0.5, 3.0], + gammas=[0.3, 1.0], + shapes=[0.0001, 2.0], + scales=[0.0001, 1.0], + ), + }, + adstock=AdstockType.GEOMETRIC, + train_size=[0.6, 0.9], + ) + + +def test_check_hyperparameters_no_issues(sample_hyperparameters): + validator = HyperparametersValidation(sample_hyperparameters) + result = validator.check_hyperparameters() + assert result.status == True + assert not result.error_details + assert not result.error_message + + +def test_check_train_size_valid(sample_hyperparameters): + validator = HyperparametersValidation(sample_hyperparameters) + validator.check_train_size() # Should not raise an exception + + +def test_check_train_size_invalid(sample_hyperparameters): + sample_hyperparameters.train_size = [0.05, 1.1] + validator = HyperparametersValidation(sample_hyperparameters) + with pytest.raises(ValueError): + validator.check_train_size() + + +def test_hyper_names_geometric(sample_hyperparameters): + validator = HyperparametersValidation(sample_hyperparameters) + all_media = sample_hyperparameters.hyperparameters.keys() + names = validator.hyper_names(all_media=all_media) + assert set(names) == set( + [ + "channel1_thetas", + "channel2_thetas", + "channel1_alphas", + "channel2_alphas", + "channel1_gammas", + "channel2_gammas", + "lambda", + "train_size", + ] + ) + + +def test_hyper_names_weibull(sample_hyperparameters): + sample_hyperparameters.adstock = AdstockType.WEIBULL_CDF + validator = HyperparametersValidation(sample_hyperparameters) + all_media = sample_hyperparameters.hyperparameters.keys() + names = validator.hyper_names(all_media=all_media) + assert set(names) == set( + [ + "channel1_shapes", + "channel2_shapes", + "channel1_scales", + "channel2_scales", + "channel1_alphas", + "channel2_alphas", + "channel1_gammas", + "channel2_gammas", + "lambda", + "train_size", + ] + ) + + +def test_check_hyper_limits_valid(sample_hyperparameters): + validator = HyperparametersValidation(sample_hyperparameters) + validator.check_hyper_limits("thetas") # Should not raise an exception + + +def test_check_hyper_limits_invalid(sample_hyperparameters): + sample_hyperparameters.hyperparameters["channel1"].thetas = [-0.1, 1.1] + validator = HyperparametersValidation(sample_hyperparameters) + with pytest.raises(ValueError): + validator.check_hyper_limits("thetas") + + +def test_validate_all_checks(sample_hyperparameters): + validator = HyperparametersValidation(sample_hyperparameters) + results = validator.validate() + assert all(result.status for result in results) + + +def test_validate_with_issues(sample_hyperparameters): + sample_hyperparameters.train_size = [0.05, 1.1] + sample_hyperparameters.hyperparameters["channel1"].alphas = [-1, 11] + validator = HyperparametersValidation(sample_hyperparameters) + results = validator.validate() + print("The results: ") + print(results) + assert not all(result.status for result in results) + assert any("train_size" in result.error_details for result in results) + assert any("hyperparameters" in result.error_details for result in results) diff --git a/python/tests/unit/test_mmmdata_validation.py b/python/tests/unit/test_mmmdata_validation.py new file mode 100644 index 000000000..29ab54674 --- /dev/null +++ b/python/tests/unit/test_mmmdata_validation.py @@ -0,0 +1,110 @@ +import unittest +import pandas as pd +import numpy as np + +from src.robyn.data.entities.mmmdata import MMMData +from src.robyn.data.validation.mmmdata_validation import MMMDataValidation + + +class TestMMMDataValidation(unittest.TestCase): + + def setUp(self): + # Create a sample MMMData object for testing + data = pd.DataFrame( + { + "date": pd.date_range(start="2022-01-01", periods=10), + "revenue": [100, 120, 110, 130, 140, 150, 160, 170, 180, 190], + "tv_spend": [50, 60, 55, 65, 70, 75, 80, 85, 90, 95], + "radio_spend": [30, 35, 32, 38, 40, 42, 45, 48, 50, 52], + "temperature": [20, 22, 21, 23, 24, 25, 26, 27, 28, 29], + } + ) + + mmm_data_spec = MMMData.MMMDataSpec( + dep_var="revenue", + date_var="date", + paid_media_spends=["tv_spend", "radio_spend"], + context_vars=["temperature"], + ) + + self.mmm_data = MMMData(data, mmm_data_spec) + self.validation = MMMDataValidation(self.mmm_data) + + def test_check_missing_and_infinite(self): + result = self.validation.check_missing_and_infinite() + self.assertTrue(result.status) + self.assertFalse(result.error_details) + + # Introduce missing and infinite values + self.mmm_data.data.loc[0, "tv_spend"] = np.nan + self.mmm_data.data.loc[1, "radio_spend"] = np.inf + + result = self.validation.check_missing_and_infinite() + self.assertFalse(result.status) + self.assertIn("missing", result.error_details) + self.assertIn("infinite", result.error_details) + + def test_check_no_variance(self): + result = self.validation.check_no_variance() + self.assertTrue(result.status) + self.assertFalse(result.error_details) + + # Introduce a column with no variance + self.mmm_data.data["constant"] = 1 + + result = self.validation.check_no_variance() + self.assertFalse(result.status) + self.assertIn("no_variance", result.error_details) + + def test_check_variable_names(self): + result = self.validation.check_variable_names() + self.assertTrue(result.status) + self.assertFalse(result.error_details) + + # Introduce a duplicate and an invalid variable name + self.mmm_data.mmmdata_spec.paid_media_spends.append("revenue") + self.mmm_data.mmmdata_spec.context_vars.append("invalid name") + + result = self.validation.check_variable_names() + self.assertFalse(result.status) + self.assertIn("duplicates", result.error_details) + self.assertIn("invalid", result.error_details) + + def test_check_date_variable(self): + result = self.validation.check_date_variable() + self.assertTrue(result.status) + self.assertFalse(result.error_details) + + # Test with 'auto' date variable + self.mmm_data.mmmdata_spec.date_var = "auto" + result = self.validation.check_date_variable() + self.assertFalse(result.status) + self.assertIn("date_variable", result.error_details) + + # Test with non-existent date variable + self.mmm_data.mmmdata_spec.date_var = "non_existent_date" + result = self.validation.check_date_variable() + self.assertFalse(result.status) + self.assertIn("date_variable", result.error_details) + + def test_check_dependent_variables(self): + result = self.validation.check_dependent_variables() + self.assertTrue(result.status) + self.assertFalse(result.error_details) + + # Test with non-existent dependent variable + self.mmm_data.mmmdata_spec.dep_var = "non_existent_var" + result = self.validation.check_dependent_variables() + self.assertFalse(result.status) + self.assertIn("dependent_variable", result.error_details) + + # Test with non-numeric dependent variable + self.mmm_data.mmmdata_spec.dep_var = "date" + result = self.validation.check_dependent_variables() + self.assertFalse(result.status) + self.assertIn("dependent_variable", result.error_details) + + def test_validate(self): + results = self.validation.validate() + self.assertEqual(len(results), 5) # Ensure all 5 validations are performed + self.assertTrue(all(result.status for result in results)) diff --git a/python/tests/unit/test_model_builder.py b/python/tests/unit/test_model_builder.py new file mode 100644 index 000000000..464090415 --- /dev/null +++ b/python/tests/unit/test_model_builder.py @@ -0,0 +1 @@ +# TODO diff --git a/robyn_api/python_helper.py b/robyn_api/python_helper.py index a2a6de085..572b301eb 100644 --- a/robyn_api/python_helper.py +++ b/robyn_api/python_helper.py @@ -1,4 +1,4 @@ -### Copyright (c) Meta Platforms, Inc. and its affiliates. +### Copyright (c) Meta Platforms, Inc. and its affiliates. ### This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. import pandas as pd @@ -51,17 +51,17 @@ def asSerialisedFeather(modelData): # Create an in-memory bytes buffer modelDataFeather = io.BytesIO() - + # Convert the input model data into a DataFrame and then to Feather format, # writing the binary data into our in-memory buffer pd.DataFrame(modelData).to_feather(modelDataFeather) - + # Move the buffer position to the start of the stream modelDataFeather.seek(0) - + # Read the binary Feather data from the buffer modelDataBinary = modelDataFeather.read() - + # Convert the binary data to a hexadecimal string and return it return binascii.hexlify(modelDataBinary).decode() @@ -148,13 +148,16 @@ def plot_outputgraphs(OutputJson,argumenttype,graphtype,max_size=(1000, 1500)): else: warnings.warn("Graphtype does not exist") -def load_modeldata(sol_id,InputJson,OutputJson): +def load_modeldata(sol_id,InputJson,OutputJson,dpi,width,height): """ Loads the model data for the given solution ID. Args: sol_id: The ID of the solution to load. InputJson: A dictionary containing the input data for the model. OutputJson: A dictionary containing the output data for the model. + dpi: The dpi of the rendered images. + width: The width of the rendered images. + height: The height of the rendered images. Returns: A dictionary containing the loaded model data. """ @@ -170,15 +173,14 @@ def load_modeldata(sol_id,InputJson,OutputJson): 'InputCollect' : json.dumps(InputJson), 'OutputCollect' : json.dumps(OutputJson), "jsonOnepagersArgs": json.dumps(onepagersArgs), - 'dpi' : 100, - 'width' : 15, - 'height' : 20 + 'dpi' : dpi, + 'width' : width, + 'height' : height } # Get response onepager = robyn_api('robyn_onepagers',payload=payload) return onepager - def create_robyn_directory(path="~/RobynOutcomes"): """ Creates a directory for Robyn output files. @@ -195,11 +197,11 @@ def create_robyn_directory(path="~/RobynOutcomes"): print('No path specified. Using default arugments') else: print('Using specified path') - + #if path ends with '/' add it to the end if('/' != path[-1:]): path = path+'/' - + ##check path to see if is a valid directory isExist = os.path.exists(path) if not isExist: @@ -208,9 +210,9 @@ def create_robyn_directory(path="~/RobynOutcomes"): print('Path did not exist. Creating path:',path) else: print('Path exists: ',path) - + return path - + def writefile(datset,path,sol_id): """ Writes a file to the specified path. @@ -228,7 +230,7 @@ def writefile(datset,path,sol_id): out_file.close() print('Onepager written to path:',imagepath) -def load_onepager(InputJson,OutputJson,path,sol='all',top_pareto=False,write=False,max_size=(1000, 1500)): +def load_onepager(InputJson,OutputJson,path,sol='all',top_pareto=False,write=False,dpi=100,width=15,height=20,max_size=(1000, 1500)): """ Loads the one-page summary for the given solution ID. Args: @@ -238,6 +240,9 @@ def load_onepager(InputJson,OutputJson,path,sol='all',top_pareto=False,write=Fal sol: Optional. The solution ID to load. Defaults to 'all'. top_pareto: Optional. If True, loads the one-page summaries for the top Pareto models. Defaults to False. write: Optional. If True, writes the one-page summaries to files. Defaults to False. + dpi: Optional. The dpi of the rendered images. Default to 100. + width: Optional. The width of the rendered images. Default to 15. + height: Optional. The height of the rendered images. Default to 20. max_size: Optional. The maximum size of the rendered images. Defaults to (1000, 1500). Returns: None. The function renders the one-page summaries and displays them using the `display()` function from IPython. @@ -246,7 +251,7 @@ def load_onepager(InputJson,OutputJson,path,sol='all',top_pareto=False,write=Fal print('Fetching one pager data for top models') for i in range(len(OutputJson['clusters']['models'])): sol_id = OutputJson['clusters']['models'][i]['solID'] - onepager = load_modeldata(sol_id,InputJson=InputJson,OutputJson=OutputJson) + onepager = load_modeldata(sol_id,InputJson=InputJson,OutputJson=OutputJson,dpi=dpi,width=width,height=height) image_data = binascii.unhexlify("".join(onepager)) if(write==True): writefile(datset=image_data,path=path,sol_id=sol_id) @@ -259,7 +264,7 @@ def load_onepager(InputJson,OutputJson,path,sol='all',top_pareto=False,write=Fal if(sol in OutputJson['allSolutions']): print('Fetching one pager for specified solution id') sol_id = sol - onepager = load_modeldata(sol_id,InputJson=InputJson,OutputJson=OutputJson) + onepager = load_modeldata(sol_id,InputJson=InputJson,OutputJson=OutputJson,dpi=dpi,width=width,height=height) image_data = binascii.unhexlify("".join(onepager)) if(write==True): writefile(datset=image_data,path=path,sol_id=sol_id) @@ -267,21 +272,23 @@ def load_onepager(InputJson,OutputJson,path,sol='all',top_pareto=False,write=Fal image.thumbnail(max_size, Image.Resampling.LANCZOS) display(image) else: - warnings.warn("Sepcified solution id does not exist. Please check again") - -def write_robynmodel(sol,path,InputJson,OutputJson,OutputModels): + warnings.warn("Sepcified solution id does not exist. Please check again") +def write_robynmodel(sol,InputJson,OutputJson,OutputModels,path=False): """ Writes the Robyn model to a file. Args: sol: The solution ID to write. - path: The path to the directory where the model is written. InputJson: A dictionary containing the input data for the model. OutputJson: A dictionary containing the output data for the model. OutputModels: A dictionary containing the output models for the model. + path: Optional. The path to the directory where the model is written. Returns: None. The function writes the model to a file. """ - updatedPath = create_robyn_directory(path) + if(path!=False): + updatedPath = create_robyn_directory(path) + else: + updatedPath = OutputJson['plot_folder'][0] if(sol in OutputJson['allSolutions']): writeArgs = { "select_model" : sol, @@ -300,6 +307,3 @@ def write_robynmodel(sol,path,InputJson,OutputJson,OutputModels): # Get response respJson = robyn_api('robyn_write',payload=payload) print('File written to path: ',updatedPath) - - - diff --git a/robyn_api/robyn_python_notebook.ipynb b/robyn_api/robyn_python_notebook.ipynb index 2a008d715..e5886ec97 100644 --- a/robyn_api/robyn_python_notebook.ipynb +++ b/robyn_api/robyn_python_notebook.ipynb @@ -35,7 +35,8 @@ " - [2-4: Fourth (optional), model calibration / add experimental input](#2-4-model-calibration)\n", " - [Step 3: Build initial model](#step-3-build-initial-model)\n", " - [Step 4: Select and save the any model](#step-4-select-and-save)\n", - " - [Step 5: Get budget allocation based on the selected model above](#step-5-get-budget-allocation)" + " - [Step 5: Get budget allocation based on the selected model above](#step-5-get-budget-allocation)\n", + " - [Step 6: Model refresh based on selected model and saved results](#step-6-model-refresh)" ] }, { @@ -67,7 +68,7 @@ "\n", "The Robyn API accepts arguments in the following categories:\n", "\n", - "1. **Data Frames**: These are the input datasets like training data, holiday data, and calibration data.\n", + "1. **Data Frames**: These are the input datasets like training data, holidays data, and calibration data.\n", "2. **Robyn Array Objects**: Objects such as `InputCollect`, `OutputModels`, and `OutputCollects` created within Robyn.\n", "3. **Simple Strings or Arrays**: These include arguments like `dep_var`, `select_model`, `adstock`, `paid_media_vars`, etc.\n", "\n", @@ -309,7 +310,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "a3225e51", "metadata": {}, "outputs": [], @@ -330,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "27086d93", "metadata": {}, "outputs": [], @@ -340,7 +341,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "beeb12c0", "metadata": { "scrolled": false @@ -360,7 +361,8 @@ "http://127.0.0.1:9999/robyn_allocator\n", "http://127.0.0.1:9999/robyn_write\n", "http://127.0.0.1:9999/robyn_recreate\n", - "http://127.0.0.1:9999/hyper_names\n" + "http://127.0.0.1:9999/hyper_names\n", + "http://127.0.0.1:9999/robyn_refresh\n" ] } ], @@ -384,17 +386,17 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "426c8f0a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['3.10.5.9008']" + "['3.11.1.9001']" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -414,7 +416,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "23443ed2", "metadata": { "scrolled": true @@ -460,14 +462,14 @@ " 0\n", " 2015-11-23\n", " 2.754372e+06\n", - " 67075.04\n", + " 22358.3467\n", " 0.0\n", - " 38185.4667\n", - " 7.290385e+07\n", + " 12728.4889\n", + " 2.430128e+07\n", + " 0.0000\n", " 0.0000\n", - " 0\n", " 8125009\n", - " 22821.3987\n", + " 7607.1329\n", " na\n", " 19401.6538\n", " \n", @@ -475,14 +477,14 @@ " 1\n", " 2015-11-30\n", " 2.584277e+06\n", - " 85840.36\n", + " 28613.4533\n", " 0.0\n", " 0.0000\n", - " 1.658110e+07\n", - " 29511.7155\n", - " 12400\n", + " 5.527033e+06\n", + " 9837.2385\n", + " 4133.3333\n", " 7901549\n", - " 3425.8574\n", + " 1141.9525\n", " na\n", " 14791.0000\n", " \n", @@ -490,14 +492,14 @@ " 2\n", " 2015-12-07\n", " 2.547387e+06\n", - " 0.00\n", - " 396835.2\n", - " 1361.6000\n", - " 4.995477e+07\n", - " 36132.3590\n", - " 11360\n", + " 0.0000\n", + " 132278.4\n", + " 453.8667\n", + " 1.665159e+07\n", + " 12044.1197\n", + " 3786.6667\n", " 8300197\n", - " 12769.1261\n", + " 4256.3754\n", " na\n", " 14544.0000\n", " \n", @@ -505,14 +507,14 @@ " 3\n", " 2015-12-14\n", " 2.875220e+06\n", - " 250350.92\n", + " 83450.3067\n", " 0.0\n", - " 53040.0000\n", - " 3.164930e+07\n", - " 36804.2110\n", - " 12760\n", + " 17680.0000\n", + " 1.054977e+07\n", + " 12268.0703\n", + " 4253.3333\n", " 8122883\n", - " 8401.4720\n", + " 2800.4907\n", " na\n", " 2800.0000\n", " \n", @@ -520,14 +522,14 @@ " 4\n", " 2015-12-21\n", " 2.215953e+06\n", - " 0.00\n", - " 832008.0\n", " 0.0000\n", - " 8.802269e+06\n", - " 28401.7441\n", - " 10840\n", + " 277336.0\n", + " 0.0000\n", + " 2.934090e+06\n", + " 9467.2480\n", + " 3613.3333\n", " 7105985\n", - " 2068.7478\n", + " 689.5826\n", " na\n", " 15478.0000\n", " \n", @@ -536,19 +538,19 @@ "" ], "text/plain": [ - " DATE revenue tv_S ooh_S print_S facebook_I \\\n", - "0 2015-11-23 2.754372e+06 67075.04 0.0 38185.4667 7.290385e+07 \n", - "1 2015-11-30 2.584277e+06 85840.36 0.0 0.0000 1.658110e+07 \n", - "2 2015-12-07 2.547387e+06 0.00 396835.2 1361.6000 4.995477e+07 \n", - "3 2015-12-14 2.875220e+06 250350.92 0.0 53040.0000 3.164930e+07 \n", - "4 2015-12-21 2.215953e+06 0.00 832008.0 0.0000 8.802269e+06 \n", + " DATE revenue tv_S ooh_S print_S facebook_I \\\n", + "0 2015-11-23 2.754372e+06 22358.3467 0.0 12728.4889 2.430128e+07 \n", + "1 2015-11-30 2.584277e+06 28613.4533 0.0 0.0000 5.527033e+06 \n", + "2 2015-12-07 2.547387e+06 0.0000 132278.4 453.8667 1.665159e+07 \n", + "3 2015-12-14 2.875220e+06 83450.3067 0.0 17680.0000 1.054977e+07 \n", + "4 2015-12-21 2.215953e+06 0.0000 277336.0 0.0000 2.934090e+06 \n", "\n", - " search_clicks_P search_S competitor_sales_B facebook_S events \\\n", - "0 0.0000 0 8125009 22821.3987 na \n", - "1 29511.7155 12400 7901549 3425.8574 na \n", - "2 36132.3590 11360 8300197 12769.1261 na \n", - "3 36804.2110 12760 8122883 8401.4720 na \n", - "4 28401.7441 10840 7105985 2068.7478 na \n", + " search_clicks_P search_S competitor_sales_B facebook_S events \\\n", + "0 0.0000 0.0000 8125009 7607.1329 na \n", + "1 9837.2385 4133.3333 7901549 1141.9525 na \n", + "2 12044.1197 3786.6667 8300197 4256.3754 na \n", + "3 12268.0703 4253.3333 8122883 2800.4907 na \n", + "4 9467.2480 3613.3333 7105985 689.5826 na \n", "\n", " newsletter \n", "0 19401.6538 \n", @@ -558,7 +560,7 @@ "4 15478.0000 " ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -580,7 +582,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "f4914f85", "metadata": { "scrolled": true @@ -662,7 +664,7 @@ "4 1995-04-14 Good Friday AD 1995" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -685,7 +687,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "5232c068", "metadata": {}, "outputs": [], @@ -712,7 +714,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "786eb4d5", "metadata": { "scrolled": true @@ -722,14 +724,14 @@ "# Build the payload for the robyn_inputs()\n", "payload = {\n", " 'dt_input' : asSerialisedFeather(dt_simulated_weekly), \n", - " 'dt_holiday' : asSerialisedFeather(dt_prophet_holidays), \n", + " 'dt_holidays' : asSerialisedFeather(dt_prophet_holidays), \n", " 'jsonInputArgs' : json.dumps(inputArgs)\n", "}" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "b32c8e28", "metadata": {}, "outputs": [ @@ -744,10 +746,10 @@ { "data": { "text/plain": [ - "dict_keys(['dt_input', 'dt_holidays', 'dt_mod', 'dt_modRollWind', 'xDecompAggPrev', 'date_var', 'dayInterval', 'intervalType', 'dep_var', 'dep_var_type', 'prophet_vars', 'prophet_signs', 'prophet_country', 'context_vars', 'context_signs', 'paid_media_vars', 'paid_media_signs', 'paid_media_spends', 'paid_media_total', 'mediaVarCount', 'exposure_vars', 'organic_vars', 'organic_signs', 'all_media', 'all_ind_vars', 'factor_vars', 'unused_vars', 'window_start', 'rollingWindowStartWhich', 'window_end', 'rollingWindowEndWhich', 'rollingWindowLength', 'totalObservations', 'refreshAddedStart', 'adstock', 'hyperparameters', 'calibration_input', 'custom_params', 'version'])" + "dict_keys(['dt_input', 'dt_holidays', 'dt_mod', 'dt_modRollWind', 'xDecompAggPrev', 'date_var', 'dayInterval', 'intervalType', 'dep_var', 'dep_var_type', 'prophet_vars', 'prophet_signs', 'prophet_country', 'context_vars', 'context_signs', 'paid_media_vars', 'paid_media_signs', 'paid_media_spends', 'paid_media_total', 'exposure_vars', 'organic_vars', 'organic_signs', 'all_media', 'all_ind_vars', 'factor_vars', 'unused_vars', 'window_start', 'rollingWindowStartWhich', 'window_end', 'rollingWindowEndWhich', 'rollingWindowLength', 'totalObservations', 'refreshAddedStart', 'adstock', 'hyperparameters', 'calibration_input', 'custom_params', 'version'])" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -772,7 +774,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "fef697d8", "metadata": { "scrolled": false @@ -801,7 +803,7 @@ " 'tv_S_thetas']" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -882,7 +884,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "c39af576", "metadata": {}, "outputs": [], @@ -937,7 +939,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "fa628f26", "metadata": {}, "outputs": [], @@ -951,7 +953,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "1231bf0e", "metadata": { "scrolled": false @@ -967,10 +969,10 @@ { "data": { "text/plain": [ - "dict_keys(['dt_input', 'dt_holidays', 'date_var', 'dayInterval', 'intervalType', 'dep_var', 'dep_var_type', 'prophet_vars', 'prophet_signs', 'prophet_country', 'context_vars', 'context_signs', 'paid_media_vars', 'paid_media_signs', 'paid_media_spends', 'paid_media_total', 'mediaVarCount', 'exposure_vars', 'organic_vars', 'organic_signs', 'all_media', 'all_ind_vars', 'factor_vars', 'window_start', 'rollingWindowStartWhich', 'window_end', 'rollingWindowEndWhich', 'rollingWindowLength', 'totalObservations', 'refreshAddedStart', 'adstock', 'version', 'dt_mod', 'dt_modRollWind', 'xDecompAggPrev', 'unused_vars', 'hyperparameters', 'calibration_input', 'custom_params', 'dt_inputRollWind', 'modNLS'])" + "dict_keys(['dt_input', 'dt_holidays', 'date_var', 'dayInterval', 'intervalType', 'dep_var', 'dep_var_type', 'prophet_vars', 'prophet_signs', 'prophet_country', 'context_vars', 'context_signs', 'paid_media_vars', 'paid_media_signs', 'paid_media_spends', 'paid_media_total', 'exposure_vars', 'organic_vars', 'organic_signs', 'all_media', 'all_ind_vars', 'factor_vars', 'window_start', 'rollingWindowStartWhich', 'window_end', 'rollingWindowEndWhich', 'rollingWindowLength', 'totalObservations', 'refreshAddedStart', 'adstock', 'version', 'dt_mod', 'dt_modRollWind', 'xDecompAggPrev', 'unused_vars', 'hyperparameters', 'calibration_input', 'custom_params', 'dt_inputRollWind', 'modNLS'])" ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1001,7 +1003,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "62851b2b", "metadata": {}, "outputs": [], @@ -1030,7 +1032,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "44659966", "metadata": {}, "outputs": [], @@ -1043,7 +1045,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "f0b2319e", "metadata": {}, "outputs": [], @@ -1062,15 +1064,16 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 21, "id": "5bde5767", "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", "text/plain": [ "" ] @@ -1105,7 +1109,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 22, "id": "0d947b1f", "metadata": {}, "outputs": [], @@ -1126,10 +1130,10 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 23, "id": "5646f67e", "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [ { @@ -1149,7 +1153,7 @@ "output_type": "stream", "text": [ " |======================================================================| 100%\n", - " Finished in 1.02 mins\n", + " Finished in 0.82 mins\n", " | | 0%" ] }, @@ -1165,7 +1169,7 @@ "output_type": "stream", "text": [ " |======================================================================| 100%\n", - " Finished in 1.01 mins\n", + " Finished in 0.82 mins\n", " | | 0%" ] }, @@ -1181,7 +1185,7 @@ "output_type": "stream", "text": [ " |======================================================================| 100%\n", - " Finished in 1.02 mins\n", + " Finished in 0.86 mins\n", " | | 0%" ] }, @@ -1197,7 +1201,7 @@ "output_type": "stream", "text": [ " |======================================================================| 100%\n", - " Finished in 1.05 mins\n", + " Finished in 0.87 mins\n", " | | 0%" ] }, @@ -1213,18 +1217,16 @@ "output_type": "stream", "text": [ " |======================================================================| 100%\n", - " Finished in 0.95 mins\n" + " Finished in 0.86 mins\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "- DECOMP.RSSD NOT converged: sd@qt.20 0.097 > 0.065 & |med@qt.20| 0.21 <= 0.59\n", - "- NRMSE converged: sd@qt.20 0.019 <= 0.062 & |med@qt.20| 0.11 <= 0.15\n", - "Total run time: 5.26 mins\n", - "Picking joint bandwidth of 0.0237\n", - "Picking joint bandwidth of 0.00744\n" + "- DECOMP.RSSD NOT converged: sd@qt.20 0.077 > 0.067 & |med@qt.20| 0.19 <= 0.59\n", + "- NRMSE converged: sd@qt.20 0.014 <= 0.056 & |med@qt.20| 0.11 <= 0.15\n", + "Total run time: 4.38 mins\n" ] } ], @@ -1243,7 +1245,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 24, "id": "33171b0d", "metadata": { "scrolled": false @@ -1251,7 +1253,8 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "" ] @@ -1266,7 +1269,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 25, "id": "d5246fb4", "metadata": { "scrolled": false @@ -1274,7 +1277,8 @@ "outputs": [ { "data": { - "image/png": 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\n", 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0Nq01jRVgjtZxDbl3wsUnzZPrn+pq7rsEMunjzJvJVGBB25BPTGBWDF4f0vWntne5ZbiBAJo48YYA59PfGRUuuXF9e3nkWf761QA/uwCM98ntS5F7Rcr9bmrl+51Sd/6/AyJZ/KuUaByEjZfnI5ODyQP6V0kyt4igiuLSQxhCVZJONp9eK5iLabhXkjEkYIJU8bquQNeL5rWnmQwJlyFYhVHvnr/WuipC9mt0cVOaScWrp9EdhdX1tpdtG13PtHCgkElj9BWPr9vDc2sWoQyqQwA68OD0x71g6vrcespFG0TKYiSCD97IqaS5U6ba2qZMcS7gSeufb2rKFBwtLr1OitXjKLjbToUJ7e+uAqWBxIMkkPsIA7g5GK3dKtdamlt5ppZMrtDyO/BA68d6yLm6lk8m3hSNLchVfgbmb+8W9M9q2bc31noc0azKjJICFDjcF74/H+ta1G7dDClZb3stdDfvdSt7DYJixL9Aozx61VnSy8QWxWKZg0RyCBggn2Paq9siX2lCbVlIEJO2ViVJWrmkW9jBA81nKZEc/M7Hpjt7VxNKCur3X3HepSqOztyv7xdI0w6bC6NLvLtngYAqG31G8l1l7Z4QIgSPunIA6HPv/WtSKaKdd0UiSLnGVOafWbnq3Jas1VOyioOyRgxWmrL4gknklJs8sfv8FccDb61ur90fShvun6UL90fSlKXMXGCiLRRRUFhRRRQAUUUUAFFFFABRRVW/vo9Pt/OkVmydoVe5ppNuyFKSirstUVXtr2K5sxdLlUwSd3bHWmWWo29/v8hiSnUEY/GnyvXTYnnjpruW6QfeNV7y/t7BFa4k2hjgAAkmorrVbS0h81pA25QyKp5YH0oUJPZA5xV7vYvUVWsb2PULYTxBgMkEN1BqzSaadmUmmroKKKKQyG6to7u2kt5c7HGDg81nR+H7eKwe2WSTLuHLnGcjpxWvVc31sLsWpmXzj/DVxlNK0TOcYPWXoZMGgeRqUUqXIKxkMQR83/6qTTtVubnWHgdlMR3YGOmOmKsppEq6yb0zjYWLY53cjp9KupaWlrK9ysaRu33nJx/+qtpVE99dDnhSkn7q5Un95ZoqOWaOGBpnb92q7iRzxVa11S2u7eWZCyrFy+8YIFYKLavY6nOKdmy7R2qnY6lb6gH8ktlOoYYNXKTTTswjJSV0c1ZKdV1eSS7typjGflyACDwD6/8A1q6N/u/lWVqWtjT7tYfILjbuY7sdfSsFbu8uLyS9hV9wYZ25YLnoPpXU6cqmuy6HEqsKPu7u+p2tFRW7SPbRtMu2QqCy+hqWuR6HcndXCsPxI08cELxSlE3EEK2CT2NblUNR06PU0j/elChOCBke9aUmozTZlXi5U2o7lXw/BdJbvLcOxSTBRWOT9fxrZqK2jSG3SKNtyoNuc56VLSnLmk2VShyQUQoooqDQKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAa6LIjI6hlYYKkZBFc3o2rQjWJdLt7BIIQz4Kdcjuw/z2rpqijijWR5BGodjgsFGT9TVxkkmmiJRbaaMey1y5uddlsXtgsalgDzuXHc/X+tT6/qsuk2kcsMSuzvty+dq8e1auBknAye9c34xvPs9nbxCMs0jkhj0GB/8AXrWHLOokkZT5oU276m3p12b7ToLlk2GRdxX0q1WL4elePQFnn4jAZ17kL1/xqkPFL39rL9gt5EljIJ3Lu+Q98D3qXSbk1HZMaqpQTlvY6SWVIYnlc4RAWJ9hXHax49Wwu4IrayMqsMuZG2kjOMLjvVLVp9T1y7tbeGVoZFHltHuKKW7sfw7VBrGoeVD9k0uDyZY5vmn4LtjjjP3efSumlh0muZXZlKvd3Tsjqde8N2mutFdTzy27RoQSMfd6856Yrlvh9cldbu4DcvKjxnaMkhiD97npx/OrOlR+I9Sv7S4lujNa4CT/ALwbNv8AErL3YjvjvS+EdR8PW+sXsFlDPAzKds1xICGVT0Hp+PWqtKNOUG7+nQu6lJSWh1Vt4e0201STUYYStw+TnccAnqQO2a0ZYkmieKRQ6OCrKRwQe1Yfie91O30+GTSVL7n+d403kDHGBzwfWtTTJLqXTLeS9QJctGDIuMYNcclJxU2zZNX5UhtlpFjp0EkNpAIkk+/gkk9uprL0LwvHoVzPcJcNOzpsRSu3Aznn1PStDU9d03R2iW+uViaX7owTx3PHQe9V/Eep3Wn6N9qsIxKxZRu27gqn+LA69vzqouo9P5hNRWvYw4bnxBqOuI8ZkjijcB1HyoozyCD1PWtw+GNKOujWPIP2rdu++du7GN2PWs67vtevfB8N1aQtHfOw3iNfm2ZPKg+vFa2gvqB0W3bVeLrnduwDjnGcd8VpUckrqy6WRFONtHr1M6TR7Hw4LrVLVZWmYFY1ZsqhY/y+tV9Ahm1u3n/tdFuoEcGPzQCVbvj2xiuimFtqtjNFHLHLG4K7kbIB/CsTwvpeq6fcXJviqwsAFRWBBb+8PTihTvTbk/e/ElwftFb4RIfEk39q3FhHYqI4VcIq53DaOMj0OP5VUtbO917UhfPIsQiZckAjpzhf8962tX12x0gTZKNe+UWWMDlz2BPbNc1N45v7LT91xZ2zXDPhTGxVAMZ5B5Jq4Rk1enGxE1HmSnL5He1j61ri6W8cMarJcON20novTP51R8I3msXsUs2ohzA6q0TSKFJJ649sYrR1bw7p2tTQzXkbmSLgMjlSV9DjqKwUYwqWnqvI3blOHu6Mnj1S2+z20k8iwNOoZUc81yXiaWLUNdjgjcqYwIWZvu5z/wDXrX8Uacfsa3dtC8jwqEMaD+D1x7Vh/ZRq9hD5gSDVd2NjKV81egz2DY/OuihGK/eL/hjlrSm7wf8Aw5qaIbJ9edYLmRjGG27kxv7HnNdZXFJbS6HppltUjfUt22Uqd7RJ/u/UD866bT7uV9Jhub8LBIV+fd8o9uvTNZV43fMttjWg1FW26l0SIZDGHXeBkrnkfhTq5XS7KG48STX0N4WVWZ9pUhjnjr6f/Wqr4iudUGqNGGmgtxgRtHkAjHJz61KoXlyp9BuvaHO0b9z4j0q0v2s57pY5VHzZB2jvgnpmtGCeK5gSaCRZInGVZTkGvJJYYpIZJHeaW488qXJyNoHX3Of5V33hCa3GkJaRiRZIhucP3LEnI9q0rYdQhzIKdfnlZlSXxTcWd3LHNaKyBiqrkqRg9z3psNzctfT6tFP5tuiGQxB+duOFK9sevtWg2radfal/ZU9sZMMVDuoK7h+v41XabTvDdw4Mkk0jjBXj5F9/eqVrWUdWvvMZc17uV1f7v8zJ8PpJcavFKYzMC5Z2PIBPOc1a8UXLW8q2dmkccSjzJUCAb27c1anvnn1a2g0u4QIyqwjjIA9TuH07VzOp2UgvLiO6naGQljl2Pz+n5+tbRXPNSl22MW+WDgur3Ox8P3loLeOzjdzKV3ncOCTyQPpWtd3cVlbmaUnaDjAGSTXI+HZVsbhftSgnaf3hP+rGM/Qj3rqN9nrFm6o4kjzjuCprkrQSnd7HTQqOVOytfoUbjxNaxBPKjeQkZYfd2/8A161mWO8tSrDMcqcg8cEVxMlp/Y00U2qLuTf8qJhjJjr16DpW9J4o082EksMpEgQlEdDyewqqlJaezV/MKVWWvtXbyMPWLa0sr+OzgjlOAHmlZgcKTwAO54qjrUEPmQQQFjHCCS7dX3YOcUQajHc3Rnu45ZPmy4BALVq+IW01zbzQoxnMalcNhAvbI7n2rrV4yindnHpJSkrI55ZHiBLsXjA6HqKtCZoWVozj0IqCTZOSXzknJxxSBlkiygI28YNbbnN5lrzQxyQAT1AHFNZQw5Y5+vSoHYxIjSfxZA/D/wDXViSSNnTyoyg2gHLZy2OT7UhNdR6X11YW80NpK0bzYzIeSMelTRX9zbXKTFg0wGHLKAX9d31qir3UTiVgyoSTGxXGcehq7FbCe7SG4mdJpSuCRu64xnnPepko9TVOdkrjrC9NlcSTLEpV1KbCTwp9DTYb6SxkE6F1TcFIHOR1wfXip7OyI8Q/ZPNElvvaNgw4YAdPrkVprZGa9awnswLFHLAYI2+jbuuTWUpxT+RpGnJ216/iZGqfZ7byLq0kX7PMN6IeWXB6EelTHWLi/s52lDm2YBCigAKf4cflRH4XR7y6H22J7dNzBIjukHoCO3pVJLhbbcyKpTaV2uMgiqXLJaatBO8H2TFXST9kivbZGmV2KsmzJUj+Yqd43sZdkqrueLDoB93cOn1FWfs17bpDqoCxopGEAK4H09D/AFqKae0uLg3c5dS3LxqmQT7HPANCk2+6Jklbs/61Mu6ENvbRFJGeVmO5T0QDp9c1sGxg/spL9bjKtgKmzkE9QfpVS3itZZEW5gaSN8bdrFSMnqPWug0mazvI300Wm2FRuG5s556n0NKrNxV0OlGM9Hv89y7bR2+p6IkO6QxlQhJ4YEf/AKqZ9istN0yS1knKJNkF3PJJFaMMMdvEsUSBEXoBXL67dveaiLOOAl4m2qQeWyPSuKnecrJ6bnfVtTgpNXexuaTpq6dE+JvNMhByBgY7YrQrlNUur/T9M0+LzGhcq27bweMYGfpXR2MrzWFvLIcu8asxxjkipqQfxt3uXRnH4ErWJ2+6fpQv3R9KG+6fpQv3R9KxOgWiiigAoqo2qWaXwsmnAnP8OD19M+tSLeW7XJt1mQzDqmearlfYnmj3J6KyP7Xl/tr7F5A2btued3Tr9K16JRcbXFCcZ3t0Ciig5wccmpLMe11mW41h7NoAqAsAecjHc1qT28VzEYpow6HnBrntP1qdNSki1FRHu4H7vBU54GfSulrarHlkrKxz0Zc8Xd3I1giSDyFjURY27R0xVHyLTQ7Oe5jjcgDJ5yT6D9ah/tw/239g8g7d2zdnnOM5x6VrOiyIUdQysMEEZBFS+aPxbMpcs9Y7rT0OTvri515IXt7V9sZKkDnDH39MYrTufD0dwyMshj2xhNmMjgcc1rwQRW0YjhjWNBzhRinj7xq3WasoaJELDp3c9WzF0Gzu7Jpo7ghU4Kx7gee59q26x10aVdcN9542bi2Od3Tp9K2Kmq05XuXRTjHlatYx9VtdRnu4XtJCsYHZ9u056n1rYHTnrWZrV5cWdorW68scF8Z20/R3u5LENeZ3k/KWGCV96bTdNNkxcVVcVe7+4veYnmeXvXfjO3PP5VmXWn2lvdNqcrSDYd5UdC3QUx9GkOqtepcYySwBHIOMdfSorS1voLO8N8pmQpkRs+7cfX2pxSWqkTOUnpKPe3yG3XiVVWM20W4nO4ScY/KqKR6h4ht5oXmARWDgsvG7049jTdP0xtTlZ8LFCpAYDPP0zWhFdQaPf/YIoXcOy75GbnJ6YFdDUYaQXvHLGU5tSqP3Szp62lrappEtws0oUqykHBzzgVn6hBPpkhFpERZlcv8AxBuxDE1rjSbcaj9ty+/O7bnjPrUeq6rDp+yOSEy+YDleMY/GsYy973db7nROHuPn0ts/IZoP2VreV7eBojuw2W3fTmtC5uobSLzJ3CLnH1NU7uCSTSgunAR7sMAvy5BpkemyXWlxwX7t5qksGDZI9s9+Kh8snzN9fmXFzjHkitbb9CvrF/GI4GjginjlU4kYZ46YB7GqOkX9vZx3TNE4Awcg5PXAH1rpbe2jtbdIIx8idM8ms/XUhj0qU7ACzA/KAMtnvVwnFr2djOpTmn7W+q/yL1lexX9sJogwGcEN1BqxWV4e2f2UuwMPnbdnufb2rVrGaSk0jppScoJsiuIzPbywq+xnQgEdR71zob+xLWa3aVJZpuNsbY8sY6/XmmahK1j4gM5ZnwQ+AccEdPpVK7jtrmR7qK5CvISxikU5B9N3SuunTstdmcFasm3Ze8tN+hs+GlQRzMs25jjMeCNvvW9XM+Ei5N1vCg/Lj17101YV1+8Z1YX+EgooorA6QooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiikyfSgBaKTJ9KMn0oAWikyfSjJ9KAFopMn0oyfSgBaKTJ9KMn0oAWiqeq3NzaaVdXFpAZriOJmjj67iBWJ4M1nVNYsbiTUoNpSQLHIIym8Y54PpWiptwc+iFfWx09YXiPxCdCW32W4laUnlm2gAY/XmtzJ9KjmhiuFCzQJIoOQHUEA/jSg4qV5K6FJNrQS1nF1aQ3AUqJUD7W6jIzUi/wAX1qrqd9/Zumz3Zj3+UuQucZPQVS8O602s2ssjwiOSN9pCnIORmjkbi5paBzJPle5s1m6vpC6rHEDKYzGSQduQc+1aOT6UE4GSKUZOLuglFSVmRW9ultax268oihee9cb4yt/7GsYJ9OcWcTykSrCxRnbHy9OoHPFHi+fVbDU7fUIrt47LKqmx+A3JOV/iyKxra0l1ixvDcX8Vw0g3W8T3GHaXPBCk8HGRj3rto02rVG9DCcl8CRtarrMtj4e07VrBIZp5lCS3Zjycgc/iSCPwqvc32k6ron9ozNHaagEzIv3Vc5x9Oeo71a0zQr698JTaVfFrRTIDb7gMjBzgjuM5965m70uS3L6bK3nFG8smMEbselbU4wbaT1T/AAMaraSutGadv4wTw3BDbvYtMk587zFfblOmR69Kk8WtbaPqFubHSEBu1MjyopDO2fuj+ZHvXSaFoVvDoOnW99YxSTW4LJ5qhmQlie/Q8ir39uac2qf2b56m6zgLg4zjOM9M47Vg6sVUvCN7Xv5mypr2fK2YviCLW7Lw5Zw6KJvMVh53lgGQAjPA+vpW9oxvjo9qdSAF4Yx5oGOv4d6wfGS+Im+yf2J5oTJ8zySA27jGc9uv9aXxN/wkf9l2A04uJuPtRt8bt2B0/wBnOf0qLc8Yq61b9fmaL3b26E/i7Q7C/smv7qOdntI2IWFsF167TwePf61neHvEc9zfxRSSRpaMNioo4Q4+UA9fbmr+j63f6hbXMDxRvcxQ5VsY3N05Huaq6BpVzd3ElzqcEkZjZSgKCMMR14A6dKtLlhKNTp/WhhKTk4ypkXj3XtX0T7E+nsscDkh5Cob5uynPQYz9aguvEWp6itpEbXyLS9gTflezDDEN0AH/AOvrU2i6bqS+JLgXtu72zb/MaUZV+cqeeCa6LW9LOrad9lWTyiGDA4yOOxHpRzU4csWk/P8ArsX704trTyM3wrDp9ibuG31KO5lyC4VdoUDIyPXr1roYLmC6QvBMkqg4JRgea5zTPDun2IuomvRJcvAY5cOo8tT1OOo7dalsreHw5pN5eJN9r6E7MAccAdT681lUUZybTbenQqDlFJNaCeIPCiaxcLdQz+TPwG3DKsB/WtK00OwtrRYHt45yAu95UDFiO/NZlp4xtJoMTr5VwSVVMkqT257DtVfwlq+vajeXkeq2xSJBlSYtm1s/dHrx/nmnKNZQtJ2SCPs3K63OrZ0iUFmVF6DJwKZdLK9rKsD7JShCN6GvN/G+tm61EWqIwgtSysT/ABP3P07V2XhfVbfU9Dha3MrGACKTzMbtwAqZUJQgqjKU1JuJjjW7vw7N9mv4nlD4f5pclRyDjrmn+IIvMSDVdK3y+c2WkjG4DA4OOoP+FM1TVLDXdVXSGgYr5myO6jYEhvYd17da2S1v4Z0REiR5lVtvLDLMeTn0rZvlcXb3n07nPypxcW/dX4HKtHq2grDfMm1pAeWG7bns3pmtPShqPiKzm+1THy1cGOQqMbucjjqKuaJq93rF1PDdW0bWpUn7nC89Dnr/APWqTWbm80vy/scQitI03Hag2++fQVUpyb5WlzdyFCKjzauPYp6DLb2Osz2s06+cf3a7QdpIPIz61qauunawr6PJeiO5yGCo3zAjn+XasHwvYRancSX0rMfJlBCjjLdcmsy6hnl12VzC0VzJMSFzt59s03TUqjd9UvxCM/Z00raM1f7P0bwyY4Hjnu5MeYS7gKM+3Tt0q7/bGn6TYw3FnZHdck5Xdgjb1559eKpp4ZnvtL8qSRYbpZNyq/OFx0OOmetSavo1tp2jWj3EsrtABF8gA35JPfp1PNJuEmoybbBKok5pJD9Lg+2auNWjni+ztI3U4YMRjZj15p2paVpmo6zJB/aDR3LnJQLkbsdM/TtWeNBj1TQ7ebS96CIyF4pTks2eSD68Yq74c0qaW7kv9QimWSNgU8z5dxxySPahtK8lLbQaje0bXvqZslhLoV9LdwyQ3CWfz7fM+bnjkDpjPNY4nOpahLcTJmad8qoyc57Cumv9C1GPUkn0tsxyNuMhcDZk8g+oq1rWjXz3wvLMAiNAERCFZMf3frWkasbq71aIlTlyuy6mDZvLALguXaJYTG8bNjPOFHtg8/hV3TNbOn2bxx24MjkkyFvbjj2qrBpGtS2z3N5BKWeQ4Dcvj1IqZmu9VubWzVEUIAgAXGMDkk/hVy5Zb6rqYe/F22fT5j4rka5cxabeyM8hYtHJjO045B6cEUzVrCwtHW1tZpHlUASEkEAjt9f5V0eiaK2nNJLOsbzNwrKMlR35965zTo21PxHcxXVm8UbmQrhsFCD79ayjNczcXojWVKXIr/E+5WltYbextiGV5pCzSFSeOmF+tRwzLJLDa+WvmzSbEf0J7H2zitjV9EW2s2mt5vM2fLJkjKnPHSsRLdxbSzFgyoQMk4OTnGPyraElKN0znlFxlaSIo0XzndpCHxjaBncf6UshaJ8lV2ZxkGm20sTMNjB25GB1/Kn3y7bckqylSCwPX8q16kdRk4SZHCEFl+6SO1Ptt7W5JVjswGbtz0qOLy2AeJsjHc9PrUoilCEgYQEbiG4B7f1oYvIs29hLrEpt4ZRHKFLAtnBx2OOnWm3qNoGp2dvLGZzGqO7ZIDfMeF9h0/CtLSdYTS4dhtxI7tksCAQvpnvUU6xeKdWfYjwSpGdnOQwB/i/unntWHNJSfMvdOqCg4JLWR1kw0+yLahJGiORndj5m+g9a5/WPEFrfW8dqgmSZm3bSBjA9T/npUN7Y6isUMM6u/JMYyXxntmqbWsVtMq6lZEhTkdQ4+hB59eayp0or3m7sqpWk7xtZenUbpt/Pp+rrIsayReWQRyMZ9/rVy/tbV7JtSVpF82TH2fA4OecH0/Co9LR7qSa1ib/XJjnpwcjP5frVhPB941+s0tzGIiPmAyWHsO1aTlCMrt2f5mdOM5xsldfqdHpd5DqWmqwjwMbHjY5xjiuP02eyv9VntruE20RyI8ORsIPQk1qWzNoGqG1VTN5m0En5Sc+lZt9Z3mpXVw8yeW6AvISmFworOnFJuz0exrUqcyipK7RqaHeSpLNFPaKtvaxswbZ8yYOcZPXPNOh8Rxtcj7NYqm9hv6bmyfam+FyWknJf92sYDITwf/1Yrct7SzW3k+wpEgfPzx4ODj19qyqOEZu6NKanOCcXb8y4xIRioywHA9TWFol9c3l9MLmFNyr98R4KHP3c/wCelLa6Vf21ndoJh5kgAQKx/E57E0lgV0G2eTUZ1iErAKmc8j6VCjFRkk7stynKcW00upZ1TU7K2njtrqDzs4Y5UEL781rDGBjpVR7WzvzFcPCk2ACj9cjqPrVrJ9Kxk1ZJHRFSu29ugN90/Shfuj6UjE7Tx2oUnaOO1QaDqKTJ9KMn0oAzn0S0fVBfnf5gIbaD8pYdDTItDhi1Zr4SuSWLBMcAn3rUyfSjJ9K09pPuZulB628zHj1eR9caz+zrtBKbv4uO/wBK2abgbt2wbume9Lk+lTJp7Kw4Rkr3dxaKTJ9KMn0qSzntTu9ITWo1u0k81MbnH3R3GR3rXsdSttRVzbuTsOGBGDVe+0Sy1C5WeeNt4GDtbG4e9TWGmW+mhxbo2XPJZsn6VvKUHBb3OeMZqbelmWvKj83zfLXzMY345x9afSZPpRk+lYHQLXLtr9+t+0X2dMB9uzac9ema6fJ9KTncflrSEox3VzKpCUrcsrDqTORxzTJlaSCSNSUZlIDDtkdazNE0u400TedIrb8YVTxx35qUlyt3KcmpJJaGVd+IL5BNCyCNyflIXBTnnrTNO1q7jula5nZ4FUlgRnIxxj3ziukvba1nTzbq3WQRAsCeorLhnsb22vZEsAJBGSy/3h169uldUZwcfhOKUKkZq8zVsdQg1CEyQk8HDK3BFUNda/2xx2iuY3yHMY5z6e1ZfhOB3uZ7k7tqrsGOhJ5/TH611mT6VlNKlU01N4XrUtdLnHw6hqcMiWMJO9HI24DEn0+laF5bxafqSahPIzb23CNVyc4559KTU1g0u+W6iiYzSbmG5vlU9z+tTafBcahC41KJpI8hoy/ynPfGO1buStzrRdfM5Yxd3TerW3ZGp9tthapctKqROAQXOKxNY1HzLwWqWcU+ADGzDcSSOo9RWjqGkx31vFCpMIiPybRkAemKtW1qlrBFEq7vLXaGOM1zxlCPvbs65xqT93Zdyro015NasbxSCGwhZdpI+lTz6na210tvI5DtjtwM9M1ayfSqc+m21zdLcSRkuuOjcHHTNTeLk3L8CnGcYJRd35lPXNQvLExNboPLxlmK5GfQ+lVLpbjXNIiuY02yRsQYweG9x/n1roj8wIK5B6g00jbHtVcAYwBVRqKKVlqiZUXJu70fQqaPFcQabHHcjDrnA7gds1YvLj7LaSz7S2xc4Hepsn0oPIwVyDWbleV2aqNo8qZlWUkGtwO9xapuQ7M9fyNNk8O2ZjIQyK2DglsgntmtVFWNdqRhV9FAAqjqmp/2fGoEZaSTO3ngYrSM5OVoaGMqcFC9XXzIdE0yawMzTFMvgAKc9K16ydFuL6eORrpWKHBRmXbn6e1auT6VNW/O+YugoqmuXYWikyfSjJ9KzNhaKTJ9KWgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiioxcQtO0AmjMyjJjDDcB6460ASUUUUAFFNkkSJd0jqi+rHApVYMoZSCDyCO9AGB4m0S71hLcW0yKIydyOSAc4549K0tJ02DS7JbeFRkffbu7Y5NXqav8X1rR1JOKh0IUEpc3UdXK+Pp549AEMSvsmkCyOpPyqOcH64xXVVBe2kV/ZTWs2fLlQo2Dg80U5KM1JjkrppHmSrFN4DSxjv4XuluPO8qRsFF5G1Se/f8AE1HovhPUNTv1W5Q21vH8zSgbg3PRT0P1FTG18OW88tuur3HmBivmtD+7BH07e9dTBcW/hDRFNxN9oadi0SRdDwOh9OnPvXpzqOKahu/I5Ery97ZGb4y1GEajFDHKxkhXDg8BSeRz61lz6vqaTJO6iOc8rP5AV2GPXHIrXbS7XxrB/aMANlcq+yUEb1fgc9ucYrM1fS9Z0e2UtOzW24RgiTO4j7uQfpSpuCSg913IqRldzWzN3TtP1DUdTtNZa4CxOFdhkgjAwVA6YJH61aj8NWGnau2q3F3hPMLokpCqrn379TiqEvju0t44rW3iaa6EKlyRsjU9x6/lT9Ssx4x0vT3W4jtblGZxC53Bh0Jx17cGudqpf3vdi9PkbRUOmr3OqE6z2zyWkkcpwQpVgV3fUVwdveeIZtdt7aS7dJw4LQySKvy9T8vcYzWn4XlsNJlutPN20ku4s0hTbH8o5xz9eT6VmzeF7fxB4mGt6Xq8bQCZHmAyXRlxwv1A7/rRTjGm5KW3dob99Jpm3beGLiDxU+qm7Uwl2cKM7jkfdPbH+FbepalbaVaG5umITIUBRkknsKwT4gv7fVGhuIBsL7RHtwQM9j3qj8QNaNklrZNZpNHNmRmckY2nGFI6Hnr71Ps5znFS/pBGpHllyHXWN9BqNml1bMWjfpkYIPcEVyXirX9StLxoLSYQIoDRsoBMh/HtniufW71GHTXltTPDp0+6MDflVzzj689ayvskQbErZIwflbjBGcV0UsNGMm3qjKdZuNtjpL7wpc2dlcavc3OZXUO8QXkMxG4E55Aya2fA1spsLuViSsjiMoR8vA/XrW5o+pW2s6YsiBTxsljPO046c9q5zW/Ez2t7HpmhqoeNisipDkFv7oH55rLnqVE6TWv5GjjCLVTobGoeFrK+uoZgTAqAK0cagBgDn8K5+68S6xb67dW4KeSjsioYwQoHQg+tamgaXrUGqyXd/MfLkQll8zduJ5HHbFRa1e6RNeXNr5RS4ceW12ig7W+n6H8aUPi5X7yt9xM9I8y90yLzQr3xSPN2Rwu+HMxjwrYGAMiuu8P6HHomhx6eWEjcmV1GNzHr/h+FYSpqHh+BtPgZXkn+cOqnqeML+VWNAvp9QtL3T5rx/tJB8suSSB0PPfmqq88oaP3UTSkovld2y9pfhi20uaaaOZpJHUpGzKMxj29/eue0mZ9N1K5ttVG+3bKSKw3DcDwcV1Wh6dcadBKk8itvbIVSSF//AF1gak8GoeJfssim3+fyi45LHsSP89qmnJylJSd13FVVoxklZ9jr4hFHbL5IRYguVC8DFcJe6lrerR3EaxSNDtIaOKLIA/qa7DUdM+2aK+nxSmPKBVY89MdfyridS1m88G2sGnWclvc3LyNJMCCwj6YUAHPPWpw6Tb5dX5/mbVU3ZPRF3T9O1mz0m2a1hlilmZmlAIDZzhcg9Bjt+dS+NQ0aWEshzIVKMP4c8EmtDUPFselpYJcWM7XFzEsrxJjMYPXr1Oc8e1c7qN7Nd6+Z1HngSDyo8blIHQY9+9bU+eU+eStv8zGryQjy33sZYSXS75tWt7uYSsSGdmBJ3dj611VrerHYC6v83VreL8ke4PuOeTz0x/Oq3ibXvD1/ZC0lM8siyg/6MoBUgYJyeCO1dDpul6XLoNnDFGZbQIJIzJ97nnJ9+aKlT3U5xsNUZX0ldotW1zY22lxTK0Vva7QV3YUDNZ/ie4u/7HR9PiNxHI4EnlfMSmOox74qr4k8O3WrxWaWcsccUIKmJyQo9CMelR6Lod/o9perNeRxK8eyMh/lDf3uelc8IwSU769jaTk/ca0Oci1aWay+ynckDNv2Ec56c/4VqvrlzaWNlDZ3O4IhLllyc5+6c9gKsWmiQ2VjcXmqRCUtgRiOTJ5756Z96vafo+kahaRukciFGO4F/mb6+orpnUp7taHHGnO9ouza/AqeK77VYjaLaNLDGU3s0RxlvTPoP60+W+WHQhf2SRrfsyxzPs53YyxA6c1L4xt7prS3kty/kRMfMVeg9CfYf1rBsTLc2NztyyQL5jKD36bsVNOMZU0+39al1ZSjUa3Ll/qt6dP0+ad2Erq7YQ7cgHhuO9Nur/8As3UzcLG7F1LJu4zuX735npWl4fvLHVbZLG6t4jLB80YcA7h6j39aPEsp+2QwzWsb2wAKll5OeuD2pppT9ny9yZR932l+xkafcC306/nct+8QQIF5LM2T0+g61nlnkAiCsAW+6epPSrXnxRyT20CrJbtJ8rsPmwM4I9O9QXaKx43be2e9dEVq33OWT2XYfZaha6Pcs9vYKLwrs85pCQueuFqGUTuy3kxZlkc/MxzuI6/zp8Wh3c1sbxUAgClvMZgBx29ajSWRrUW1wS6x8wkH7mT8w9wf501a94/MuTbXvfITy1cbYkVAeeKSC3y+4tjIxTzKkL7Bkj+8BxUbiONzJvwPTPH5VRjrsdXbaLbR2UF5IGaeNDJ5SsMPg5H+RUCeK4rObMmnx75Dl5IsLkf1NKnh542guk1CAQAK/m9Md+KwLnzLy+JmkaQFj83oM84FcsYxqN3dzrcpU7aW+7XzO807XLLVJpIrdn3oM/MuMj1FYmuXF/c3ktj5e6MEFUVMkjsc9a19MsNMsYHvbNG2uhJYkk4HUYPTpXJWzXNxqdze2SzeYWMmRywUnofWsaUY87cdl37m1eUnBJvft2Jok1nQzLP5SwwSqqqxAZs9efTr+lO0XVrqxa4eQyTh1JCFyfmHOfpXW2scl7pSJqMQLuPnVhjPPH0PSuUl8ManJeEQ7IlRuG8zGOeCMc1pGpCd1OxEqc4crp3sdJouoNqtu080CK8bbQyjg8ds1pB45CyBlYjhlBzj61zOv/23bXVs1jIVtY4wXdcKoYH5i/tirHh63tXuJru1vluE5TCqQRnnnNc0qacedM6ozkmoWv3Zl3OntbanceYHt7QlhvUcbT0A9e3FP8MXSxam1sZ9vmKSEI4Y+3vjNaPieWYxxWywlkc7t2CTuHQCqEvhO6OoWs9rciOMbWcuSHQjk4x1roU1Kn77tf8AQ5FTcavua2/U1vENrdXFskkEu2OLc0g3FeMdfw5rPtpLDxZapA73CT2oBLkAFgRgnv1xXRXtzBaWrSXH+rPykYznPbFUtEh0pIpX02ER7mw+c59uvaueM2qd7bbM65Rj7S1990aFtbx2ttHbxAiONQq5PYVLRWNYapd3OrS20sAWNd3Y5XHTJ96yUXK7NZTjBpdzYb7p+lC/dH0ob7p+lC/dH0qCxaKKKACiuR0KG/TxHO0yTBfn8wtnB54+tddWlSHI7XuZ0586vawVHHPFNu8qVH2nDbWBwfenSIJI2QkgMCMjqKxdC8PnR55pDcebvAUALjgHqfeklFxbb1Kbd0ktDcqG7My2kptwDMEOwH1qaipWg2rqxzegy629/J9uWXyNp5lUDntiukooqpz5ne1iYQ5Va9zF8S2upXVgiaa7K4fLqr7Cwx6/Wr+lx3UOmW8d6++5VMO2c8/XvVukbdtO3AbHGfWjnbioj5bS5gZgqlicADJNU7LU7a/kkWBmyoyQwxkeoqlo8OprNONQZmiIwA7A5Pt7Yp9s2k6beSwxyBJTwdxOB7ZNXyJXW78jH2knZ7LzNeijORkUVidBzut6neWupwW9u6BGUHaQDuJOMHPQVrvp1ubOa3jRYRKMMUFV73Q7a+vUuZGcMuAyqeGx0rTraU1yxUTCNNuUnPbocnqGganHDElhcs3zFnCv5fPY1vXV7/ZWlCe5zK6Kqtt/ibp/Or1RzQxXELRTIrxsMFWGQaTquVuYqNJQT5Clp2oWus2ok8tdysQY3wSpHf8A+vUWvRajLbxDT2cEN84RtrEduagg0iDT9Qe6SdEghBfy1HKjHQ+1NfxZZ7gscMzMck5AGB+daKPv3pq6MedcjVXRmla3Iijt7W7uI/thQbl3DJNXawYNPt9WvE1VXkT5gWiIH3l9/wAq3qyqJJ6b9TanJta7dAorG1i+1C1uoEtItyMOTs3bjnp7VsDJAyMH0qXFpJ9yozUm49haa/3fxFOpr/d/EVJY6myNsjZwpbaCcDvWVfW+pSanE9vIRCMdGwB65HeteqcUknczjJybVrWMLStaub++MLwoIyCcrn5frWreWqXds8bKhbB2FhnacdanCqucADPJwKiuo2ltJo0++yMq/Uiqck5XirExg1BqbuZfh+1uLZJvNnSRSQAqSbwCOp9q2qwPDdhdWZuGuIzGG2gAnqRmt+nW+N63Fh9Ka0sFFFFZG4UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVyVn4Me18Yya2b7dGXeQR7TuJYEYJ9Bn9BXW0VcKkoXS6iaT3CiiioGcV8SdJnv9EjuoXYi0Ys8QUncDgZ/D+Wak+G0zP4X8pyd0UzgAtn5eDwOwzmul1Z7uPSrl7Bd10E/djGef8AGuZ8GaLd200uoXiyRMwMaxuuCwOCSa7Iz5sO4t7PQxd1UVkdlTV/i+tOpq/xfWuM2HVj+JNc/sDTRciDzndwiqTgA4JyT+FbFZ+q32l20SRapLAscxwqTDIb8P61dO3Mrq5Mtjx2WVLm4eVYljEjFtidBk9BntXReHrGTWtRjtr155rVEJKlzhMDAx6dhXRXSeDr6+ud80H2i3iJkWJyoUL3AHBI9q0/DV9pNzYtDpRYJEfmRwQ/Pc565r0qmIfJpFr9DljS97Vmra2lvZW6wW0SxRL0VRiuU1df+Ei1EQWFzFcRxDDqr48s55Y+v1Ga624jaW2ljR9juhVX/ukjrXm8Xg3xDY200sE0fn/cCwSkFl6k5OPQcVy4flu5OVn5mtaLa5baFe9/snU9SextbJbOW2YxfbZWO2TbkEOO2T0PJqBbmy0jX7LNzLdRw7HkliXGD6LnkgcfrVA3k8Yne9LO54Lcbg2cZY9x+tbWi2ul6fpEsuo6ckxuGBt1Jw5UjlgeoX39a9GS5Y2d2ct7u51mnWuha9b3d3awupnDRS7shlJHOB0Gc5yKqWCaZ4T0e/u7O6+3uHUPhxwc4UcdOp5rX0K008aEq2MLxQTglgzZbJ4OT+FeafaLGK71DTLkTpGH2pKoBYFGONydDn68Vx04+0co3dlbQ6G+VJpI6vwt4k1XXNclF1axm0VWZWWP/VEdAG75qxqWt6fqlrOJtLW4Nv8APF5w3DqAScdOtUrfXU0HRtOh0tPtMMu93lnBXndyoA6H86xbu+vNT1uEaeEtDNhGijOFfJ+Yt6jFaKkpTcrWXT5GcqjVop6nRwX1nr+njSp1jsCCGiaMgKWB6YP16VleI9Ki0uSxs03MPKYtMF5Zi3cDoPSt+TwRZl4zbXMscQPzKx35HsT0/Wsm8udT1e4ljksCTCxHyRncgz90nvSpyjzXg9OqIqKSjaS1H6T4j0fw7BBaFZpJJ3zNMgyqHOB168elaHiHwn5/mX2kqyX7SbmAlKgg53Y9Cf8AGuZ1bS30gWsr2pLMgkLSjcqPk8DtkcHnNdj4Vur19Ge61OfMRbdHJKw+73JPpU1VyfvYP/gmlN3XJJFeXRtXn8NWdpNcg3UbEyBpD8w5wC3cjimf8IxFplhJesJLu6RN/lE5Qv3OOp+lZ+qahJrPiiG0tmAjVhHG6tn3LjH+eK2pdZvrC6uZbyJzaQg5AT8Fwe+Tj86n94kknvrbYTcHLVeV9yx4f1abULYm9EaS7yI/4TIMdgfSuYaz1rT9dvmsLKVI/mCMse4BCcjaT3qDW7+3uHg8RIZsCZYjb4+ZWUbuG6AYrW0u21DWNZtteguGSyl+fazncoHBTb06g8/jVKPs7y2T6Pv2HrJJduv6jILbxPfJKksk0SyRnJkIUEdhx0Jq/ougw20kb6hIj3wbesYlzgduO9UfE8mp2167mWQW0nEe1vlxjkEDvS6JoMxmttVupxCu4OqN94+nJ6A0Sv7Pmukn2M4/Hy2bt3Oql1Gzgu0tZbhFnfG1CfXpXBeIbKey8VC5sklJmIkR+o3nIOD2x79Ks+J7zTzq1zuE6TRptLgjaXA4464qLT4JJvC981xdGC2kkQxM2SrkZyAB1B4/KilT9mlPv+pc6jk3EqW99ai+fStXaUXAcCO4yJBCSMkZzkg8dK6bRpdF08Sy/wBpQyPkDe67No9s1DpHhXSLjS0uG2TXDhv9ITKlfbB9PcVi65punaZcw2SXkjXL8nIzjPQcetU3Co3BNolxcLTtctaVoOk3Ot3EUlk0sL7iitISIwD7djXc5htLb+CKGJfoqqK5q6l1XS49OtrC3byxCgb5NxZv7pPaugv7JNR0+W0lJQSLgleoPX+dc1ZuTTb0N6N0mupiv4nVtSit7NY7iElVZ1JJJPp9Kr+LdYtYkeydZjJGBJlAMZwcA5NWtF8KW2lXgvBcSSygEAEAAZ6nFSeJNI0vULOQXckVtcSp5cc7NtIPbvzVRlSVRcuxLjUcHzPc5zw/4phkshbXMPnWcjALxymTyCO/NZ/iG3bT/EU0cDMoJDJtypAI6D6VX0S1i0jz5AVnmVf3Clcxhsj5vc45FW7jUrnUJv8ATJd7rnAKgY+mK7VDlqNx2OSU1y237HQaV4jjv0Om6moO+JsyjgEAc7vfrzVCWWx0qGVtIupWnlIUu6/dXrgZHriq968t3GiabYhJZUWOWRY/nlI6jPQDp/Wkv9Fn0+xsnuEPnOG8z5s4OeB+VZqEE+1+g5Tk43Wtuo/SLZoUl1d1LJbMNqrxuc+voBmrOu63Le6XbssARxKRIc528cfnz+VWLDxPp1ppS2d5FIAqlGMcYww6Z+tUdQzYuBZXBe3njV1cYO9f/wBdCTlUvJa9BSfLBWd09/U2fDuh272aXtwvmNPHjy2Xhef/AK1Y+sarHJfGxS3SGC2YqmF+bPQn6GtKPxJdQ2tmfLWRPLzIxU/MQSCBj0AqSXWNA1HJubIksdpdohnHrkHNZLnU3KSv+ho/ZyhyxdjnHluLjT45Y5pDZ7ygGcAOOSMfrmqq2V/DC15OG+yZCo7Y+cn0H4HNXrmaBv3Nogjswcxxq2QPf3PvVWV3njihcnZFnav1Oa643ORuN2hrmMhSfmBPapZrS5nt1lMTfZYshX42g96YAVQIV4U5XI6Zrf1Sxi1DQrG5tkR4YFYyIh+VTjk49QQaUp8rQ6cbptdDn7aN44n8xxs9M8D3rp9OGjPHDYuHa5lVSZR03dcA1ykECTyqkTNh3CjA9/TvV2z0vX/D169zcxRS20TMI5CQwJPRgByPx9aVVJq17MulF3cmrrqd3p9xY4NnaSA+UOnPPqc96swWlva7/Igjj3nLbFxmuZjzZaMupwxmK4mO3DchASeVHvgdaraKurQ3UUymRoJm3SOxyhGeSSeh61wujdNpnZGta0ZR18uxNe+KrsXklvbW6LscrlgWY4OOR2qlaRyaDri6hqVy3+kozmNAS3zf3s9APx6V0Gu6/Y+H4I7p4DLJcNsXygMtjrk0jvoevRWE9w8YedN0Eckmx2HcYzzzVRklH4bJlOEm7812a1xBDf2TwyfNDMmCQex9KqaPotvo0UiQvI7SEFmcjPHQcVogBVAAAAGABWVq+sf2c8ccao8jckMegrmhzS9yPU2m4wXPLoa1FUNP1ey1LKW86NKqgvGDytX6hpp2Zaaaujn/ABRfLDBHbNFu8z5tx7Y9Pese3W909ItR3PFZ5DMQ33hnGNvfPauj1SbS5biK1vl3vnK8H5c+pHrV2eyt7mzNpLEDAVC7OmAOmK6o1VCCjbc45Ueeo5X2OYsvEmo6j4iSO2gJsGfaQY+QuOWLdjXX1WsbC3062EFsmxMknnJJ9Sas1hUlGT91WR1QjJL3mI33T9KF+6PpQ33T9Kj+0QrIkLSoJWGQhYZP4VmWS0UUUAFFIWVSAWAJ6AnrS0AFFFFABWDqHiCWz1mOyS2DoSoJJO5s+lb1NMaM4copcdGI5FXBxT95XImpNe67DqKxbDXje6tJZ/ZyijdtbPPHqO1ad7cizsprgjPlqTj1olCUXZhGpGSclsT0Vg+HdRvb9rg3BDIuMHAGD6VvUTg4S5WFOanHmQjsqIzscKoyT6CuR1RbO9gnvrJ33qw8xWGBg8ZFda6LIjIwyrDBHqK5SXThpN3JLcsDYsSoRTlnB6DHt1z7VtQaTvfX8znxKbSVtPyNPwzLLJpjCWUvtcqoPVRgcVoajdmysnnVN5XAA7c+tM0pbQWCNZKRC+W56575q4QGBBAIPUGs5te0bsawi1SSvrY5WxuJtT1pJhcKjKcmPefujqAO9X9SvtTg1aGG2hLQNt6JkNzzk9sVjafcR23itk+zlQ0rRqufuE9/8+tdrW1ZqMlppYwoRcoPXW5jWL6qdWlFwrfZ/m6gbfbFbNFQvdW8U6QvNGsr/dQtgmueT5nojpjHkVm/vOT06GV/EsqKQ6b3EhJyGTnOfXtTNd0mOzv4Db7UiYd2JK88k+1bdp4fS01X7Wk52AkqmORn39KmvE0vUVaWWdGEH3mR+g9DXX7Zc6a2scXsX7Np73G6lfDSbCE2kKFGOB/dA6/rVi21JJNKW+nXyl25Yde+OKnt5La6tgYSkkP3QMccdqdPbxXFu0Ei5jYYI6VzNxtZrW51qMr80XpbREdlfQX8JlgYkA4IIwQas1nKdO0KBY3lWFZGyC7ZLGtAEMAQQQeQRUSSvdbFwbtaW4tNf7v4inU1/u/iKkspWes2F/dS21tcK8sfUYIz2OPWraXEMkzRJKjSJ95AwJH1FY2meGbfSNQmvYpZJCVYIhx8oPOPeqHh628zWZrlg67Qxx6Fj0JrodODu4vRHO6kouMZLVnWVy9pdzyeI5GaV1jVnLBjwFGeCO1dRUbwxurhkGHG1uOorOE1G91uVUpubTT2IrS/tr4ObeTdsPIwRVms/TLGztBIbSTzNxwzbw2MduK0KmaSful03Jx97cKKKKksKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKwPF41k6L/AMSTf5/mDzPKxv2c/dz74qoR5pJXE3ZXN+iszw9/aI0K1/tb/j92/vM4z14zjjOMZrTpSVm0NBRRRSAKav8AF9adTV/i+tADq5bxrpNncac2p3LzKbRD8sWPnBI456c966mvP9R8bXVtrF7YXemxSWqloxE2QzDsSTkEH6d66MPGbneHQzqNJanKXE8E9vCscQjAGVz1HtW9p+qW3hGztLpbWS5ub+PfIXfYqIrEYXjn1/KuXuLlbi7kZLWO3TgrHFnao9Oa2YPE9xb6VDYSWNnMYDuikuItxQHnof5161SDlFK3qrnFTtBneaN4lOrag9v9lMabSytuyQB/e9OtYfjjxZHDaiy0rUQLtZtswhPzKoB43ducdK5WXV7rVb/z5LhUlI58sbAMew/rWZcIsdw+8IJCMnPfPv3rGGFipqT+4v2ztys6C3tmeOHVNQsPtVjcfMfNOBITn075Fa+m6Rd69qy3lzCUsSc5GAu1eFRR6cYrHabxD4htbJFgmmtYZQFEUQVOmOoxwBXZ6JbXmhadfz3kZ8tF3rErZzgHJHp2qasnGO65tiYx95LXlLmr6nBpdmbOzeNLvYBDEF6c46dPXFcXqdzqF1bSxXlquRiSWQ24WTA6EnHSug0tLPxTevfzQyQywMoZUfKP3HbParXi+aMWsEEl1HEsjENG7Y3j1+grCm1CahbXqXPmlFyvoYGk2kWoeEbtI42lmtn3RxrkFSRyR65649qrw6XAmhTyXUptLmeQLE0yn5lXBIwBkDJ5PsKmbxVp3hSK2tNNgjvDKPMuZVlPXpgcdf8APetHxRqej3zmzke4F7EmV2JwCQDtb9PpW1581rOzdxcqUb9Uje8PWUmn6DFD9pjuGG5lZWynPIAPpXN+FNf1We91J9YuFNrboXcttGxs9Fx1GM+vb1rL0Wa6ivl0+O8MEV0HjGW+UsVOCB65xVy+0K80TRLmYxLNLcYgYICwjjPJP1yB9Kh04pyjJ6y2KjUcknFaI0pb628bafcWSM9oYSJlkbkYH94cev8AnFVLkWNp4bj0SG5a5DHzGnQjCndnGPT2rT8N6PBF4WYXEbwSXanzmc4OOg69BjnHvWhpnh20sEbzMXLlgwd0Hy46YrN1IQbS2T0X/BKcakkvPqYlhfWvhmdNN2faDuzLcDAKlscAeg44zW94jsJdS0WaCF9r5D4zgNg5wa5jVtA1G28QrcafE00Usnm5YAqrZyQ2e1S+IPGqpps8NlbOZJCYg78AKQctjrTcHOUZU9X1FGVk4z+RS0q0a60abN1BHDau0jIx+6COWOPp/Oui0nxNoraRm3mYR2u2IqYipJxxhffBridFnuTaXBtYPODxFJ49hcbD61bSxOm+EjLFp7bpbn95K+4nao4PsMkit6tNSdpPqZU5cqbS1sbOu2l1q9zDqNtdRtp5jwN8mwIwzng96y9Kk/4Sm0TT4pnjmtS0oEwyrIcDjHcHt71kXUiz2FukqnAkdghGQOF5+tS6Tqc1hfx3ECgFAQQehB7GrVNqFlutiOeLleS33O51fw3pd1pSLfzeS0SKrXYYKxwMck8H8aq6n/Yum+GodMjlEihN1uofLMc/eyPcmlv7u18TeHZyrPHNagTtGBnkA8e461yljaw3+lXdxGsxubYrgKwKsjdeOvGCePWuanBte+3o9jecla0Fujaytz4OMInhsxFKTmSTaJgBk/jk/oKwNM04aprNmxvY8blOXJJIU/dHvx0NTXNvOdOtZJVEUZJWPdxuwck4+p60+3sSZIPsV1HNdBfMaKNwHjIPofTg11JKKdnvc5uZtrTYa2t6tr11cxzeZshcssMaY8sZxzj+tekaVL5umW5MqyuI1DsGDfNjnJ9a4ibUNX1DVDpDL5UpxHIiKP3gxy5PcY/CtDw9qFlYXsumhpJDNIV84gKpI44HX8a5q0OaGitbXQ6Kc7Tu+vcoJqviH+1rkRzSPEjkYjUOg54xx0qCe6uvEl9NHdeXC1pE7JhSN2MZUgnqa2fDd1pKavdRW01w8iowUugClQecY6/jisXWdSTUb/7VHG8fAGCc8DofatI6zso2stzKTajeT36FG1ksLK2kW4uBDK5VbaIt99u4GewHNaOmT2a6nE93DE0bjy2354B43deK57WtGgu7m0+3JcQvFh9oUAshwe/HarVv5lxeRwxqqIc7nc4UD610SipLfcwtZprc7jxBYRxW9qsF1b2cKsQEkk8sFj3Hqa5+z1GS1guILiM3quwZUnlOEbuQetO8TQXt/qMZZGltVUfZ5I1yu3AyQR3yKoq8MiT+bMI2ihaYLjO/Hb2rClD92uZ3/r7zWrJ8/uIk1GWyuZRLDaeUroN8XZW74/xrZ1Gzgfw1ZXljDIAoCHPJC89ce/f3rG0MQ6ncbhFJKkWXePHXAJAPsa2F8YNHp8sLQpFNtxAYV+VfqD6UTUk0odBQ5Xfn6mLb3uqW8U9iA0dq67iHTBOf7p64PT0rIiluZY5EJ8oE8YXkfnW0LxQpub7zbjAzgP8AM/sSelZh8m7YpFlgedjEbgPfFbx0voZXbXkT23k29rBHA/mrsBLFdvzHqMfWpZb3zbiPZCibF2nAxvPqfeqTQFcBD8uOlEBLXsUIkjjDH5nk6D8aqy3JtduxvaxfWYsba3sZFliUF2crht57H0+lVLLU7qCyMCSbYMklccNnqD6iqwBm/doA5JwAO5pwjdIiCMEcAd6zUIpWY3N3utDesjodnex30V63lou9IPLJKnGMZrU1nUZbrQ0vNOmZYt+JCPlYdsfnVKDSNBjntLS5uzHeTRBhavMAxJH5/h7VvS2lhp2iywvFm1RSzqTkt3/OuGco8yerfmd8YT5WtEjJmu1v/B7TzMXnhwCTx8+cfjwaztKge+tZYjeLDHIQER2++wOelTxxwa7pRgsI/sqW77pI5G4ORw2fwNRRQaPEkTJdzMUI8xRHy565GegrWNkmlvftsc89Wm+3e1yhrFuIrYWnmLcpGxLrt+VW6ZH4VEPBLeKNR0/W/tIs44giNCkfaM8GM5+UH+ea6+WbQ9Nlj1GedIvtGShduOepxWhqF6LHSZ72KPzhFEZFRP4sCodeaSUVr3/M6KNPlbbf9dCn4km1KDSt+mKzTbwGKLuYL3IH5Vlpod9q1ra3d44humXEysvJAPBwOhx2q14U8RT+ILO4kmt0jeFwoZCSrZGe/cVb0ltTa5m+2hhHjjcAOc9vask5U046JouajNpO7TMzRvDk2la686FjBhlDMR909B9elWrGfWm8QSx3EbC0BbqoCgfw4PetY6jZ+VNILiNlhBMm05xUem6rbaojtb7xsOGVxgj0qZTnK8pLyHGEVZKXmLcaVaXV0lxKhMi46Hg46Zq1M0iwSNEoaQKSqnuccCn0VhzN2ubKKV2upyGmeJL63eVdYilwcFMRbSPUdsiutR1kjV1OVYAg+1clH/aGqeJ3ttRst1pGX2koVCr2IbvniuuACqAAABwAK3rqN1ZWf4GVLm1u9Ab7p+lYlx4fW41qPUPtBUAqxTbzlemD6cVtt90/Shfuj6VjGbjsayipbi0UUVJRiarokuoahDcJcBFUAEHOVwc5FbdFFU5tpJ9CIwUW2uoUUUVJZzvjCa8t9OhltZmiQSYk2NhjnpzV/wAP3zaho0EsjFpQNkhI6sKvzwRXMLQzxrJG3VWGQaIIIraFYYI1jjXoqjAFauadNRtqZqL5+a+gqwxpI0ixoHb7zBRk/U05lV1KsAykYII4NLRWRpYigt4baPy4IkjTOcKMVLRRRe4JW2CuWsbDVb3UbiLVld7Tkjc3AbPylMdOM11NVru9t7FfMuJNgY4HGSTWkJNXUVqzOpFPWT0RLb28VrAkMKhY0GAKkpsciTRLJGwZGGQR3FOqHe+patbQ56/0GefXEvbeRI0LKzHoVI6n3zXQ1yGvapI2txW1teNF5eFbkqqt7nvxiuuU5UHIOR1HetqqlyxcjGk480lEWsi90GK81NLxpnXG3cgHXHTntWvRWUZOLujWUFJWYjKGUqehGDWLbeG4II50aZ3EqhRwBtAOfxPStuinGco6JilTjJ3kirp9hHp9uYo2ZsncWbualnuIbWIyzyLGg6sxqWqWp6cmp2nkO7JhgysOx/yaE+aV5MLcsbQRV1HSbXXY4JhOwCg7XjIIZTWpFEsMKRJ91FCj6CobCyTT7OO2jYsEzyepJOTVmiUm/dvogjG3vW1YU1/u/iKdTX+7+IqCx1JwD25payLnS7ibWEu0nAjBU9TkY7D61UUnu7ETk4rRXNemTRiaCSIkgOpXI7Zp9MmR5IJER9jspCt6HHWktynsZ+kaSdM80tLvL4HAwABWnWRoen3dis32mQEORtUMW+prXq6rvJ63M6KSgklYKKKKzNQooooAKKKKACiiigAooooAKKKKACiiigAooooAKrRahaT3ctpFcRvPD9+MHkVZrmbSO4t9TUvaXG21a6Z3CZEgllDLt9eOT6Y5oA3YdRs7i7mtYbmN54f9Yinlf89ParNcz4ftb211B4pRc7EE3mmVRs3GTKGM+65J/DPNdLg/3jQAtFN2n+8f0o2n+8f0oAdRTdp/vH9KNp/vH9KAHUU3af7x/Sjaf7x/SgB1FN2n+8f0o2n+8f0oAdRXEax4c8QXfje11G1vtlkhQ580jy1H3l29Dnn8+a7XB/vGtJwUUmne/wCAkx1FQ3EyWtvJcTSlYo1LM2OgFZltqVv4j0y7jsbiWNyhjJZcMhIODUqLav0BtXsbAYMMgg9uKRf4vrXA+HjH4Pv5tP1G8Ly3DJhYVJjj64LE9znsOnWu9UH5vmPX2q6lPkemq7ijK5yqX/iM+NDbNA39m7iP9X8nl44bd659/atzWNM0/UbNv7QhDpEC4YcMvHJBFO1e8k03Sbm8jQyvEm4J6/8A1u9eU3+u6zcaquqNdSRAjbEsbER4AwRtPB68/WuilTlWalHSxnKSjo9SxejQyhntbe9VtwXypJBsK+u7BIz6Vs3virSLuCFv7Dinuo1XZ54G1SO2eSQPpXK2ep3Nrcu8ci/OPmjdAyN9VPFdNZ6z4emuhNqWlLHcHl5UG5N2Ou33+ldtSFrXTdvP/hjmjLonYw59Vh8Ra1usdMWC6mIV0R9xkbHX0x/+s1o+DvEUM3iBvDV9pMDMskmJnIYh09iOBgcf/XqLxBqlhPcxajo96onbaiQbCjxFR97gYx0rDlupLrUTe3kkcuoAL+8SPYRt6Hjv3zVcnPDltZW87plXUZOT3O4nv9c0nxXPcXsxi0aLLFfl2eVjC7VHO7OB9fares+LLa78Oedplxh5n8ohhtdB34/Ln3rzC4eSe+aS5naSSQ5MkhJP4mun0Wx0u6e3sriSS2l3YMiDcJST0OfunsD0rOWHjG0pdOyG6jei6mPc3c1jahI7mSISsMhGK5x0zj61be71HVTbQXbtJMgESM/DEE8ZJ6/U108HhCTSdcW/vLu3OnW5LmSbrjsCCMZ561ka5dQazrkrWEbyLL8oZTkyEDGQMcVpGpGcvdXzMpRcY6ll/BV3a6YdSnJN3CyukEeG2gHkn1PfApkUumX3mT6mrrqUgKi4UfIOMB2Ud/oPetnxfF4kZLK20lZzbPD5cojwTu6YY+mO/wBawr/wodBtYw+pWzyMCxjfKH8Ouf0rGnPnV5y1e1jScXH4djPsZYrLUoLuSEXBhcMqhyASDxzXUL40vdNvXGrW0nlvnZGse1k59+ormbfXvsV1YRWVpaXM8QAM2wsZCTnABxjGcZxmux8U6NFfNHqN1eRx2ioA245K+uzHUmnV5XJKotGKKlFXTOLv/EGqa7P5N1KXgaXdHCqAAE8KOOT171Dc3GsxX9pILqeMWihEXeQYwp5BH+NdG3hmy1LSY7jw80ks0cxEnnvtfGOB2Axwa6200MnR/LvBE2oSW5iluNgYnIxycc44+uKJV6cEkl8ilCcne55tqGu6tfWQsXuZZI2k3knqfbI7d8VpPZrL4Vhlt13zWrE3rkfNj+E+4HP5VvWWg6joujagn7uYzbV8qMFht6FsEdcVY0Se203w1d3IjVni3NLGjAs2OBu9KmVVJXprZ9CVFt8suw3wFd2smjXAjt1hMUmJJc8SZGck+3THarOu+KbbTbkWTWzzpJHl3VwODnp61nxXkPiHwveIqR6alu4ZsD92e/YD/OKsaRouk6toUULT/ajE5HmICjISc7RnnHNYSjDnc5p77f8ABNbysoxME6JLrGnxXWlK0pWRkkjkKqV6Ywehq8fDF5o9rPemeF9kJBQLnOeDkHjA5P4VBb+OYLGaTTdP0vy4YchWeTBODjJGOv410N0lz4l8OQS258lnbc0bnhsZHXHTPIrWc6sWubSLMlThZpbkHgmDbaXMpjxucKJD1YAdPw/rWBqthd6Z4ieZXVCzmWJo+OCeBj9K7XQ9KbSdP8hpSzsxd8dAT2H5Vfe3jkZWkVWZTlSygkfSuf2/LVlJapmnsXKmo7M88A1HxBr7QaqrW8VujB5PL2hAPUnjmuaRJhe3N1NbNFEHIyFJVSTwAe/Ga6HxHrWoi5dbsukYcqIPuqQD+p75q5bat4ds/DudQaWYXBVpYPKLFT2x9PXNdylKEU0t+iMNJSa/FmVpusalpt1b3EZlktpAUSJmJVwDggDsQanm8Gaza2d9M2oW8WxD9nLPjc2eMk/dP58132mGwk0+2OntH9mMYeEIAMKe+Otcb4mv1vtdS3WceQm1A+7K5J5Ppxn9KxhVlOdoq3c0nBQjrr2Oc0O51TwzLvuVjNxNh1ZmEh2HsSCcZIzxzXc+HJYNYkuDc6Var5bB1dIsDJzwc964+/t1udft9Ns7tZURhEsrgBdxOW+ozXeW+r2WmXMGitLK0qBYzLtG3ceme9ViHeN0tX+QQ+K8tjH1kw654ihtdrqqP5Jdep5547YOal1nQbLR9O+0QmZjuC/MwwPfpXRXEOn6cJ9VkRUZVLPKFycf4muO1rXLXXTEYPORIchvNA7+w+lZUpSk4qN1Fbk1YKMZOerZpafr8cHheVYcR3cWVRX53MeciuUNwjCYNgTyg+Zhcbs89uOaleeX7MsZRRGpO0hMDJ68jr0FUbiFTKz28x37QCSBgnr07V1wpqLb7nPKbkkuxt6Ys1owtjeLbx3a8srZG1hgE+9VvDViL/WpIJ7dmSBGc54XcOAG9iapwveb2S/jaJo1VFVo9pwP5/WtCC+niURRzuq4PyBuMHrxRKLs7bsSkoytJXKbzXiiX7QYWMxO9RGpA9hxwPpVGz0WWNrrVEnj2wMAYiMMQ+R1qzq9zPaRJKLZvJJ5kKkg84PPbFPCvJE3kPkPgnnhvStFdLQSk0ry6jrdfPlIllWMEcZBIBA6fjTEG6TaVz6+1QqZ494I+fOAPSrNnqd1Ylkif5XI3KwB59RnoaGn0JsT+SbOfyXjYPwctwRkZH86Ibye2uDLbSPG6EjcO/8AjR9r1C8nkllWW5jjHEp/gHuanGr3SWEdomz5H3K3lgsv04qHe21wsk7mrqXhe0k1S28SX95LGwEUksKJndIoGMHt0HFHia+hv47S4gmLREMpjPBU8dRWZqOsavc2US3TMYHPDGMAMR74qLwpGniG7mgufkWIlgY2wSvTvWEYOK55vb8jqnN1PditGdXLpVyuj2senxohdQ06xNt3kgc570y6sNK0TShNfhmdtoJD87vQe1dHHEIokjQkIgCqPQCua8S+Gm1W5+1Pd7IEj+fIyVAycrXJTqc0rSdkbzopLmSuznfHL6dqejaVdWjspy6RoAMBeM59wQK6nwk8y+HopLh2+zCNTEZSMhAO/txXNaL4ZgvdT3RyB7WEhzHOmWfjgHHGM1peH5L29uLvTtRmdreWJkCcYB6fLjoMV0VUvZ8ie2pEJ+8pPqQpqup6jeXEOlnNqjnAt0CgDsc+9dVZXsbRx2dzcxNe7MSIHGc9/wAaxIv7I8E5Sa6neW5IP3MkKOnA+pqjbWkf/CRwXNq0k0EsgljbHUNznPtz+VRKMZrRWS2fcOZ03du7enoTXWjajY6ksdirzW8qhWJAwVJ5Vvaruj2t7Ya3NBHbslmzMWJGRgfdIbv/APrro5GWKNpJJQiKMlmwAKSKRJ4xJFMJEPRlIINYOvJxs0aqhFPRkc2oWcE3lS3MaSf3S1Qalq0Wm+WHRpGfJwvYCs7WNAafz7u3kZpSN3lkDk9+ah0KaPVYDbX+JpITuj3rzt+tNU4cvPv3IdSpzOGzex0kUizRJKn3XUMM+hp9NCYAAYgDoABRtP8AeP6VzHWK33T9KF+6PpTWB2n5j09qVQdo+Y9PagB1FN2n+8f0o2n+8f0oAdUEd7bTXDwRzxvKn3kDZIqXaf7x/Ssix8Ow2OpverPIxO7ahA+XPXnvVxUbO7Ik5XVkbNFN2n+8f0o2n+8f0qCx1FN2n+8f0o2n+8f0oAdRTdp/vH9KNp/vH9KAHUU3af7x/SjB/vH9KAHVTv8AToNRRUmLDYcqynBFWtp/vH9KQA7j8x/Smm07oUoqSsxIIEtoEhiGEQYAqSm7T/eP6UYP94/pS3GlbQ5TW/Dk02pve24XymG9+eQQOcDvmtDw7q7aikkBgEawqoUqSeOmD78Vt7T/AHj+lNWNIzhSF3HOAAMmt3V5ocsl6GCpcs+aLJKKbg/3j+lG0/3j+lYG5El5bS3D26To0qfeQHkVPWTa6FFa6k14szkksVUgcE9ee9am0/3j+lXJRT91kQcmveRl6nra6ddxwGAvuAZjnGBnHHrWsDkZqvNFbvNH53ltIOU3hc/hU20/3j+lEmrKyCKld3Y6im7T/eP6UbT/AHj+lQWOpr/d/EUbT/eP6Ujg7fvHt6UAPrN1jWoNGhjeVHkaRiFVMduvWtDaf7x/Sq95p1tqEQju4xKgOQD2NVDlv72xMr293cktLqO9tIrmHPlyKGXIwamqOOFYY1jj+RFGFUAAAU7B/vn9KTtfQa21HUVFFLHOCYp1kAOCVIODT9p/vH9KQ9x1FN2n+8f0o2n+8f0oAdRTdp/vH9KcOnXNABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUVxXj7xRq/h0WI0y0SRZi2+R4y4yMYTA6E5P5cVpTpupLljuJux2tFQWU0txY2800RhlkjVnjP8AAxGSPwrnkg12LxTLczzldNUsxLSDyxHjgY7EetEYXvrawpStbQ6iisODxh4fubmK3h1OF5ZW2qADyfTOMc9vWtyplGUfiVhpp7EN1HBLaTR3IUwMhEm44G3HOa5q2sdPudAvbfw1dKZHYb38w5PsSeQCM4p/j06t/wAI466UjNubFxsGW8vBzj9M+1Zvw6ewi0xmNyP7RlIE0bnbgZO0L68frXTCLVJzT67f5mcrOVjT0fwrEkMM+qxrNdxvlTvJCgdAfXHWnaprB1HS9Qt/Dt5HNqUX8MZ+YDIDbc8E9aoeIfEkV3eXXhpFkgeYeT9r3YCMRnkddvYn3NVfh5o1hayXN3HqMV3dL+7Kw52xqfqATnHXpVuL5fa1N+i6CVl7sTofCQ1f+wwNa3/aN7bfMxv2dt2O/X8K53x1qOjlVtEiWa9hJX5GKiIEZ5xwe3Fd/Xk3jm3gtfEknkxOplQSuWPDMe6/l+dLDWnWu9OugVdIWOdwJXjjGd7thT2zWlp9gmpS5u7tba1tog07YJLKGxxj+I5AqvbwvNaPchCsMbhGfHAJGRWtDpctlocbyGMtqL/LHuBfy+CvHu39BXpzlpa5xr0MHW4dOtbyGLSLm5uScuWZAu0dlx1JHc/St69v9A0n+zPN0eG8ujbq908dwdqk9RjkFuvXpxWyvw484R3AvWgkaDDxMgba+PXPTPauTso1FvN910ZmXIHDAEjNRGUKism3Y0m3DVoq2trBd3iIJSoll2K0q/dBOATj+Qr0O/8AC1voekx3OnRTTXVuQS7nd3yW29Dj07fhXFLB9nnt5ocBoXEgAHXbyM+2cV2a6nrGpeHdSNxHImIwVdIyhHzcge2M1FdzvFp6EwlFp3RJp99H4x0ibSr52juVAfzFA+YZ4OP5irdhpeleCNPmu7i5dy5AMrrk+yqBXB6bpl5fX7tprfv7ZBJhWw2CccGq+p6X4kkMl1qi3DCIgOZJAxA7EKD09/es3RTlyKVl2NITdrta9z0fWQfEugRXGlXaeSX3tuYoGAyCD6YPY1zqeG9Z1O8WO4n3QpHtS63CRNo+6Bzk81k2VxJrNtpehWURglhMjuHf5Jj1LfUDJ5461q2OvN4fsL6yEoe63fuwuGjjbo3P+elJQnTXLDf+tRScZSvLYlsNN0keH7/RrTUI7jUo90zyLEQWwRlVPccY4PequmW0N54fnhup2ggtH8zzGUsuH42gDvkcY9axdO0O61u9ZbF0WQAyMWbaAMjkY+tO1LTr/S79rO8mLMxD5Dkq+f4vc1ryq7jza7kyd1e2h6BphsrPwpczaHIGKqzF5eDvA75/l0rmrTxpqluDFNtuFOfmcYccdiPT6U/wpNp8ematbahe7Y5FBMYzwo43D1OSOPYVsaZDp66Jetoz/bLg4D+bH8wB7bSOmM/WudqMHJSV9f61LvJpOLtp/Why9rq00VhexRXksd1PtVME4Pzckt2OOM+9aCeF9bttP3oGWWcGOWGNxkL2yc859KxNU0u4spFaSF4UnyY9/t147VK/ivWNN0a0tLKUr5LHfKy7yQT8o56AdK6ZRk9adtTGFmrSL2rD/hGtCbR57r/Sr11ldI1+RIxxyfUkdvSsmO28QWSzNCt5DZOgM3JCn0/pXoFrYad4v0uw1PUrJDcKuCA5GCDyDg8jPOD61d1y4sH0qa1l1G3tvMG1SzjqOcYzz9K5o4iz5Wru+p0OnpdM4uzFja6LBNPpsU2pSeY8U7qPlGSASf4uc9a2PBmpsIplvdQj2s4SKKSUbs98DsOlY2mQNezrB5qIqndvkOFXkfz9KtQeGLC78QTwQ6tGyK5cxqh39eRnpx6itKig04yfn3/4Ywpym3dEusavfp4tJiu5IrW3dFK54xxuyvfvW9c+MNNttTSzJdwSFeVBlUJ9f61i+O7djcWrWsqxTFWEmUzleMHPqKxNXs9O07U7e0hluJZGhWSR3A28j8+eT7ZqI06dSMbroaSnODlZmxr2j3OuaxcTWV5aXKxgARNNzGR/Djtz3rlZLeWeK5t9Ssbq0JUeVuIBLBuc+3Haptb0xrXT7K5hnG+diwgBx8g6HP17VAzyQ2pnESvzgqxPH5da6qaaiknoYTkt7assaVpcmj6hb6ndvJBbDIjQKd8g24wP9nkc/lVmxt4L65hhkmaMMQquE3YY8DI9Kzp/FXk2UOn6pAbyeWUfZ2kk2+QnRiSOfTAre8O3uj6bG11qKt5vmjyWPIHHOB6j/ClPnScmtfIpxu1roaepaLZ6Ctne21qZJ0PzSOSVyO5Xpk/0rjni1a6kutQvYWdRLiSdWBB3E7eOoGOPauwfXNUsXa4lAntpiQm8jyyOowR7VS8SakwFlHFbC3tJIRPsVQMuc5/L+tZUnNNJ636jm07tfcYuka/qjJPYbXmtHYRpbXEecrjnHcA/pin65p9ndTRnRJPKiiXDpIxDFifvAn7w7fh703wDHe6z4nuZ57d4rS3+fO3o2RhM98jJP0966N9L0ea+nawvQVt0aR4CCc7ecKx7dqucowqWX4fqNqdjmNVtbt5ont5CtqVwkbSc5Xg59frUWiK2n3324ASfK22NxnDHoT64NNsri6vDN58jKqr8gPCqT2A7Vu+E9GbVftTNJtjiOwMORu/rWk5KEHzbGK5m7R3M+S4lnwZppJX/AL0jFj+tdxapaWXhNbyazEp8rcyuoycnpnsK43UWisrgpbW5d0lKN5j8vzg4H8P611MnjC0hhESWDvbqoU7mH3cc8d656ylJR5UXScYtuTJrHXbS90i7iewCpDES0K8q61xcr/eEEIhgB+VUPCj0rR1fTruwS4u5QqWTvuUqwAIPIwvXv0xUWmagb20W0jtwoeReDGA7HoOe45qqcYxTlHZkVZSdlJbGerArnOfXmnTTxRssnkB8gghiQBx7d6v6/Zw2CpFaxrHdpgTtkbXJ5wAe44rKtTOf9c+TjkVtFqSuZtWdy3DL5afLGSrDkOcUyErLdhW/dB2wMAkLnp70ssm2Is2SR2p2kXUC67YfaADmZQB1HXAz+JoeibFBXZY029gvdVt9PDyTFpcNEmfl/vH2x3roxpel+Er2TU3mnlklDLFEcHGeT/Tk1cn1fStOvLqSKzUXIyHdI1UyHPQnrVO91XStZ0tGv45YpRIyoIzuYHHUe3TrXFKU5taNR6nZBU4J8rTZetPFMN1p0t0bZ0aOQIU3AgkjI5/A1fGq2x0k30wKQ4IZSMnrjHvXJ6hosVx4Jm/s+7YKsvnymUbd20fdwOnY1a8IXNlqHhxdHumLSxjayO2NwJJG3vx/Ss50ocrlHo/wNYym3q90aWg6xod1NJb6cPJkPzFXXaW+nrVbxRdTaDDHd6baRq8rkSzFCwUdenbP9K5XWvsXhzxB5WnwuWi2M3mtkA9cDv6V31jfWXiTRn25McqmOaPkFSRyP1605wUGqiu4vuEXzXg9GjKgg0nxtp8FxOSLqFQsohYqUJ5xz29K0LfU9N0y7h0WFZF8vEanGVBPQE9c/wCNP0Pw9aaCkwtmldpSCzSEE4HQcfWrT6TZPqAvmgBuByGyevrjpmsZTg243fL0NeWVk1v1Ga1Zvf6TPBF/rCAVGcZIOaq+GrK6sNPeO5XYWkLKpPI4FWNc1X+x9P8AtIh81i4RVzgZPqfwqXSdQGqabFdiIx78gqTnBBxwfSpvNUvK4Wi6l+tixcO8dtK8ab3VCVT+8cdK5/wsgd7qZrYRtkAOAQOeqgGuloqYztFx7jlC8lLsFFY2trqpmg+wF9nfYQPm9/atdN2xd+N2OcetS42Sd9xqV5NW2Fb7p+lC/dH0ob7p+lC/dH0qSxaKKKACimTSrDC8r52opY49AM1h+HvFEWvzTxLbPC0YDjLBtyn+Rq1CTTktkJySdjfoooqBmB4k1+bRDbiK3WTzcks5IHHYY781t28vn20UpQoXQNtPUZGcU540kADqrAHIyM806rbi4pJakpO7bYUUVgaVa6xFq08l5KzQEHq+QxzxgdqIxum77ClKzStub9c3pdhrcPiGee7nLWrbusmQ393C9sV0lFEZuKa7jcbtPsFIPvGlpB941BQtZPiGbUYLBW05WL7wHKLuYL7D61rVBd3lvY25nuZVjjHG4+tVB2kna5MleLV7GVLqt7Y6HbT3UAN0/wArhuAOvJx3x2rNk0/UtY1S21AHy4GCsDv5jA6gD3IJ/GtDVtQuZrS3l0wCeCXOXVN+fQYP41tQFzbxmVQshUblHQHHIrfm5I8ySu7nPy88uVt2Vv6uYnifSb7VIrcWcwUIxLIXKg56HI9P61s2kUkNpDFLJ5kiIFZ/7xA5NZN/p+pT61DPBNtgXb/Hjbjrx3zW5Wc37kY3NYaybtYKKKKyNTG1DQ2vdTjuxcbFG3IxyMHtWzRRVSm5JJ9CIwUW2upzvjHWNQ0bTIptPhDs8m15ChYIMeg9elamjXdxfaNa3V3D5M8sYZ48EYP0PT1q9RVOS5FG2vcq2twpr/d/EU6mv938RWYx1IzKilmYKoGSScAUtVNTsRqWmz2bOUEq43AZxzmmrX1E9tCeGeK4jEkMqSIejIwI/SkuFSS3kjd9iupUtnGM8Vn6Do39i2bwmbzWd97EDAHGOB+FSavpz6jBGkcgQo2cN0NXaPPZPTuRJy5L217DNH0f+y/NJm8wyYHC4AArUqG0gNtaRQly5RQu496mqZycpNscIqMUkrBRRRUlhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFcT8S9Z1LStDiisISUuy0U04UkxjHQY6E88+1aU4OpNRXUTdh1hpfiNfHE19Ldl9MZ3OfOyrJg7VCdiDj8q667t4ry1ltZuY5kZGAOCQRg1594WuLfwJ4ejuNfuzA2osskVsEZjGAOcjHB5GfwrSv8Aw9d634kstdsNSjNiwjkRgxyqjn5exB/qc101IXnq7JbO29iFojkNW8ON4d8T2MNrb3F5GzJIu9f9YQ33flHGMCvZK4Hxtr2s6Nrtl9nuFgsnUFcgFXOfm3d8AYrvEdZEV0YMrDIIOQRU4iUpQhKQQSTaRheI/E+maH5VtfpLL9oU5SNc4ToSeR61yH/CJ6Rrd6v/AAj+tRMIsGZHJZkGeCvT/Peu71Xw/pmtmJtQtVmaLOw7ipweo4PT2rz0+Hdb8J+IZ77SYJZrSJCwYkENH1KsByTn0HYVph5R5bQlaX4MU1rqtD0abRtPuJTNNaxPOYzEZio3lSMHn6VR8PeGLLw+1w9tJNI8uFLSkcKOgGPrUPg/Xr3XrCeW8gRDHJtWRFIVxjPf0qfVfFOnaLfR2l2ZfMk+YlFyEBOAT/8AWrnaqpukirxtzG5XnPxIvAb6ytBD8yRmUyHvuOMf+O12es67aaJbRzXId/MbaixjJPevN/HOqW2o6razWwyhtVbcRg8knB+lbYOm/aKTWmpFaS5bGEszQwuI9wEgAdV/iAOR+tauoaZFaWtlJHfJcT3ESObZAS6bhnjHb9axi3ybl6U63edbuF4FlMgYbSgJIbtjFes090zjXZnR6Drx8P3F6968qB4mGJMnbIOQWHXOePxrndLvXntpS7ASNKzMAoA55OAOnJNOvIru71WUXcjb8N5rTvxleuSfQCquwhBLYrHE+3AU5Kn685pRhFNvq7DlrGzNt5LHyoGiWdJAuJ2mPyg99oHbvnvXp+l6tpjQQ2Meq29xNHGqH94MscfrXlmmS2F9eW9lqweC3c4eSOTGG+pH3c9aTWNPsNO1Tdpd19ptuGQqc7Ofu579ua5qtJVGoNv+vMunJwXMeqtJonh5XbFtZ+c/zBEwWPuBzXmniQWqajNqNtqUdyl3Ix2qCHUejZ7dhUNm0N3f7r+SWNJXy8i4JUk9TntUC6Fdz3Ll0kEBYgTKu5W542noc+1FKiqcruWoTqcy20IbKd47qO6t96TxtlGA5Bra0Xw9J4hlvFe7jgbaWHILFic/d/u9a565nFuojhWWOWKTJl3kHA6DHYgjPWu98B6VHcpFrZvJJZV3o6FMEOeuTnng5/GtK8+SDktBU43aMRrceCLx8ahHPdSoYgIQQYlOCWPvxwPfNdV4X1SK8srlbqX7RLCC6pIu5gmOcE9ea4fxDbpPrt5Iqv5LXDEEHnGef612ekDSbXT7y60EyTX4iKpFcMN5IGeF7568elYVknTTe7tr/WxUHeehzcH9mS6u1utlIiXJEahZcmLcRgqMc49/etzwpb6hpOq3y3FpIlssZ82Rkx93kbT3zk1n6bqWrrqNlLdRRW6PLs3yWyRA8/MckDnFJa22rabqhnhvWng8zdNcRyl4ioOW39umeD+FOd2nHy73JjpZmRqBurjUJbyad5wzM212PygngY9AMdKuWsV1fX8UVipszdKEaNQSpU/eJzzjvXW2kPhrU5vt8EoiWJwGjY+WpbqMg/09Ks+ML6ax0JmsnCXMpCIy/e29Tg/Spde7UFHXzGqbtzSZTsraDwjpF7PeXnmiVwmIByDyBjnrz+lcXp+hxeIruUNdfZ/Jj3ksoO5c+uRg0ttPFomitJfwC6OoHCWrSFcKh/1hI5BzwPxrc/sW2vdJTWbJorWxMG9omyzIw4Iz3yfX1q1endt6vqN7JpbGNcNJbWyslvJIjNhQBwSB6+1PkvILW4trvRLmbeIgzB1wyP3B4wR+dX9FtjrNpdQksrWqGWMDnJPb8wK5I3UqsyJkO5ByB0z6VtFKTa7HPGLSudRolw+oeJoZdXkY725WVThiR8q47Dp7VDrWpz69r7TWVsTHBCVVTgEqpyT/APW5pltDrEGuWct8C128iP8AvmBPUY3enHY+1dF4j8KQfbpNUF1HaWuAZgqHcG9Vx3P86xcoRqJvtp2Nkm4tGH/aOnXnh8W9xETd28hWF4j2bk7s9s1hWV7c3skkYjjEMZOOeh/rUrWy+W8dudob5S2Ooo062i0q2uZzNHcO2EWIMRt/2jj0roSUU7GLfMX7HStIvb2FdSsRe5wAmWTYSeRx94Zx7U3XzealcpDeKIHgyqRrFtCAnpj8BzU3hLUNvieKS48pYDuyZOiHHGD654rW1C51S48UT5sYZniR2tlZByo5Vgf4vXHNZSk41PRd/wCvmaRUuTcTwq0mlX50y7iV0mcKyMM7GA4NV/Emof2lqMjomxIQY156gE8n071raVbanrGjXtzcQLHfn5YLho/Ldx36flnHeuGXUJykoS2SZHyjRSqyyFs4IB6g59QfeoppSqOXVBJS5VHodDYeIpLPSzYiSKJHGVdFw35j16ZrMSeAeZICQm4oD6+uKrpp91Y3TJeQtE6jGxxz9fpSSWwMkjK/Q8oBW6jFarqYy1dm9ibUI7SexUxXuJdm542jb7w7AjjnrVyy15odAt9HgMsbh2Z5QQA2STtGOf8A9VULaKKUSIxYyADYijOTnnP4ZrXihsZ9JVYLKNNRifLOAfmiHU9eTUztZJ66lJ2TS0Li6uY9OeG8t1uPNTaJBhZOP9rHOOK5uPUrmBhcrbxyGI5ETqCDj1BrpNJ1EGa00m5s7ee0Z2HmP99GYnkdvSofEmiWujIrC8Mk8rE+SV/h9azi4xlytb/18h2bipJ3sYep6xceIZWvpmMcCn5Y2YERgkDA9asWlylvKjxSjfHgqRzyO9Ysl1Y27NBO20OnEadfbHpzV7TGsn0+Xy7aYTscKxmGAfcY55+ldDilGyWgpXlqzSv7261a733DJI8a8EKBgepqruMYDKPxptihijuUuY/mkIIw3Kkd/p7VcvbdLB4EW4WQTRCUDowB7EdqnRe6jN3eu5F5zNljGSccIgyagjjjikWXYFkXBBHYimzXBjP7tmTIIJ+vUUya3ujZRiE4wckK2CR2qrCSN3U9I1qyt2u47V7jd08s7zz3I61b0DTrnX8TXiJbiIKriOLaG9QB0B9frVfTLvVWiaOOed5WTMu1iScdT/8AXrotFvb7UNIu4EZvOjGI5ieue2fX/GuOpKcY9PU2pqnJ2s/87DfEN/p+kaTLo1vdR2t3cRERBgSOeMscHGeRk15/bLcaI7+Y4F/BOCsJG/bj1YHH4V2k/g8X8LX2orNJdxD93GJc7wOQG/HPQ1WsYQviGO9nsy11I+fmBUZPG4LRSlGMWk79/X/I1qTXu3Vi7oEP/CU6dNPrenxNLny47jy9jMuO30PetKXTH0Dw/cx6JG7XBO7LfOx6An3IHQVm+FoPFEetXjaxJIbUg43uCpbPBQDoMZ/StzXYtQlt4xYMwIb5wjbWI7c1yzf7zlurfgdD0he2v4mD4a1PUV1JodWuJFaVflSbglieMDt39O1aNzaaha6tPqfmGSCNWk2qxywA+5ip4vD8c1xb3t4zm6VVMgU/KzDua26mdWPNePXcmFNuNpeqOQjvbzxZo11AkccUkboeCdrjrtz61NpWoTaXNb6PPHvZW2Fg33c8gAY5AzXTpGka7URVGc4UYpkiQJIJ5FjVxwJGABHtml7WLvG2hXspaSvqS0UVQi1izm1BrJHPmqSPu8EjqAawUW9jZyS3L9FcW/hzWX1a5mNwpV5t6SmU5A7cdsV2YBAAJyfWrnBRtZ3IhJtu6sDfdP0rmLabxAfFjxyI/wDZ24j7o2bMcEH16V07fdP0oX7o+lKMuW+l7lSje2otFFFQUHWq9rYWlj5n2W2ih8w5fy0Ayaravqw0qKNvKMjSMQBnAGKs2N2l9Zx3MYKq46HqO1XyyUb9GRzxcuXqixVOfVbG2vY7Oa6jS4kxtjJ5OelW2YKpZiAAMkntWBd+G7HVtVi1UXDkfKWWNgVfb05ogot+9sOTfQ0L7WrHTriOC5lKvJzwpOB6n0rQ61nX+iWOpXEc9zGxdBjhsBh1wa0elEuWytv1Bc13fYKKpat9r/s6T7DnzuMY647496xNL8QXEd3Fpt9C7TF9nmE8jPQEf1qo0nKPMiJVVGXKzqKy9b1V9LiiaOIOZGIyx4GK1KoatpaatarC8jRlW3KyjPP0qafLzLm2KqKTi+XcsWdyLuzhuAu0SKGxnOKmH3jVfT7JNPsYrWNmZUHVupPU1ma/qt5pskAtoQwfksyk5P8Ad4pqPNO0ROXJC8jcqlqumQ6tZG2mZlG4MrL1BFWomZ4Ud12MyglT2PpT6hNxd0W0mrM4nU72bw/Lb6ZpkxCRLucsoJZmOefb6etdohJRSwAbHIFYmrW+hS6pAL+eOO7fG1DJt3jtmqujajqF3r9zE8qSW8e4Mq42rz8uMV0yXPBNdN/M54twnZ7PY6eisnxBa393YLHYOVcOC6h9pYfWpLeWTS9Djk1GQvJEnzkfMSc8D3PQVhye6mnr2Nuezaa07mlRXJXMmqazfW91pcsiW6EKyl9uxgcncO4Ix611tOcOW12EJ82wUUUVmWFFFFAGPrL6ok0P2FWKY52qD83v7VqMzLBucfMBkhf6VJTX+7+IqnK6StsQoWk3fc5zw54qbXb64t2tPKEa71IbPGcYPof/AK9dLUEC2qSyi3EIkzmURgZz74/rUxzg4GT2p1HFy91WQ43S1YtFYOh3uq3N7cJfRFY1HGY9u1s9B61vUTi4uzFCSkroKKKKgsKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKK5Xxvqmt6XZWr6PCzb5CJZFi8wrxwMe/PPtVwg5yUUJuyuY3iP4fXviHxUbya9UWL7cncfMjAGCqjGOvOfeu503T7fStNt7C1UiCBAiBjk4HqaTS5rqfSrWW9i8q6eJWlj/utjkVw3jDx3qHhbxHEktuBpnyf8siWmB+9tOeo549uetdC9rXtSXQnRanTeIvCdj4ka3e5kmieHIDREcqeoOR7VtW8EdrbRW8QxHEgRB6ADArmrT4g+HdSjhFpqAEs4xGJImUBj0DHGBzxWP4F1bXLvXL221J55Y1QlvMHEbhsYHpnnj2pOlVcHzaKPRhzJP1NxvGdivigaH5M2/eIvO427yM4x1/GsLxP4k1O91D+ytFSeOSOZkZomAeQgdB6DrWr4qv9G8MXEGszaWtxqErbI2XAPA5JJ46cZxmuV8X65b67pNs2hoIr29AM5VMS46BNw9T6dcD1rehTi3GSjp57XIm3tcu3uv+KLbUrbTdyC5EaZSNFYyMRkk/jn06V2d1oGn6tLBdahaq9xEB0YgeuDjqM+teLL4e8R6QgkvbK4jQnCsfn+bqOmTXrnhfxH/bCm3kt2imjiViS24N0B/HNViafLFSp203aJi/eaka+o6VZatbrBeQiRFbcvJBB9iK8++IGgG1mtL21RUtFiW32D+AjOPzz+lenV5N8QGe58WrEhdtkCIEJzgkk8D8qxwbk6iSehVVLluc7a/K+GxtPUntT4rme3mWa2keORWyrRHGKiA+QoGznjipIswrsYdTnIr2GcPmW7rWbbTRc2bW6XN1JH5MpcZjjyMsFIOS3QZGB161zLXL22XWQKOpLdqvXdxHJC4EXUgYb/PWsPTtIk1W/u7aa/ht1SJpcO2S5HRVA71UIpJtm0UmjqdNdNaZbe3MZkZSV3uFDEdgT3PpTLS4n3qrBQFGORyay4dHksrdUiJb5slzjrW5ZTyWs32oQRzOqkDf2JGNwx3FTLS9jNqOyN2aGOfwxbMyxpK80gMxA3YGMAe3WjTfFy6V4dk06wSRbpZNwmfDKQTyQO3bAPrVObRfsGk29y92jm5QTRqqkDZjqSe/sKueHPEGi6bZyWmoaeJPtEhMsxRWG3+EEdTg5/OuWSThtzalwupNXsZ1zZSXlmt9POjz3RaTy8ckBiCxPuc4qbSda1K4sY/DenRBC8hKyI5VyOSQT6e9JbmTxTe300EUVqsMXmspyESMcYGB6Dp9am0DxHonh6eS5EV/PcSLsGURVVeuevciqldxatdrp27DgnfyOkPg6f8A4RxDMVGoIzO/zFsrz8ufX3rg1iljvYb6J332zrJwv3eeM46elem6zdPrPhVdQsXdIVBlkQ8MVXORx1wR+NeZXF7e6nF5ERcWUTjjbgAnuxHXvjNZ4aU5J83f7hTilL3TZvtQfWXik1O9iinUYh81CqsrHk5AwOg5roTZR6D4eniF1HcT34CnYMoFHXHr161zFy8OrXtkl7J5TrHHAZwM8Djc3rXZaN4TttPjeDUrmGV5XHlIjlcYHOO5J/pU1XGCSenkEU5X5d+5xWg6TqV/rn2J0kjjKku7RnaoxkN+Pb612/jG3Fl4RhijJZoHjRJGGSOxJ+oqK/07WZPFtu2n3irZQ7P3az4Eaj7wKd8/1rAtfG2oLqVzBrgjlsJGaOSJEGYxyPlx1/H61Lc6slONtNbGiUYpp9dDlLuS3axhhAd78zs7yMcJsbAC/XIznpzW5oX2q2uU0+a6MVmzkXMUjgR7Tw34+h9cVk3CwNqhmSTzrbcTGxHIXsCOxFX7ydrCc2dyHjmXBEZ9xx09RiuySurGDk1sjvYvCMdpo19Fpt5I810gCySNxsBztyPX1pfDfhCHTl+0ahFFNd7spn5hGB0x7+9ZfgOTULi8mYzSGziXaVZiVyegA9q2oNb1KTxU+ntagWwYr9w5CgcNn3/rXmVPapyhzX6s6YuGkmjK8R2tnoepDVLmSWdLibctsqgHcBk/Nn7vHpWlpmsReJbO6ivbZVtfL3lgT8oz3PqMZ/CsnxjrVtNq0ejT2S3EaFWJDlXDHspHTg989au6Jrtva6VcxzWiR2tsihREM5BONpz1P/16pxk6SbWpDcVUsnZHFS3ungztFO6xKxEW6M7nHb2H41peEdBs7q2u9Qubxk8g4K7flHGQxPf6VSv4bCaZ1sY5IrRxxG3VPUDk123hi3W90CezmtEgtywCtEmzfx19yMDmumtNxp3WhlTUXJpHBstwuqfZILeSdQCWeNCQQB94e31rbsvBt7qcKX3nC367EdTuOOhHoDW1rsMek6UthaTkvJJvlBPzEdunbiuW0/VNfuL1bWwmuMIeIk6AZ6nNHPOcOaDt6iSjGVmiVfEl/wCF72KxmEyIWDvG6jAUnBPPOOD0qaTXEPjSS7lVtkMrbfly2FBAGO2fXtmoNQ1P+2tUiu5rJWNjGHwQDwpG4keme1Qatqi6zdzXAh8lmOFAABA9yOtNQTd3HVrUbaSsu47xD4lXWGEzRLbBEKhc7mJ+uOfpWCtxc20LTKSqzxGEnI79fp0q74u1mxsEtdPFmge3yrywAAyvgbm+mfzqTR77Sm0y7iuED/aIk8lmHC85J9j/AIVtBctNWjp/X/DhJO92XvB1jPca/bzRhmWBgzv2A6cn3rq9Q0i50/Wm1KzQJbL+9dgw+UdXGD68/nXE2+nyRafJfQ3MXlo4UIrncc9GArtFvrzVvAN3JKFkmAZGPQlQRk/XFc1fm51JPTYcLNWfqYuq6pFeXUd/ZWxtpUb5jkHLfwnH4GrHjO6t7nRrO9X5rswBiw+7jv8ArmuQeC+nvYordmLSfdBfHI69fau3uYLdfBUNrfGCW92HylQhjtLdMjjpVSjGEoWJV3FtnmIghv5FupSxbOCBxnFdVp1wLGKB7SNEkQ5JaMH5vXmskWdtZrkicwoclEG52Oeg9PqelbWn27a6sc+lW85iV/LdJAMxt6EjjGMc8V01JK2uxMryV4lHUJpJbw3J+WWVyWVeAe9aGozJqF59sWLymIClAcgADA/SpLiCaylmtZrSIv8AddnQFk9Cp7fUVGkKiHk4JBOSazutGjGUtCuII5GUsOAPXqakgB1HUPscJVAckc4UADJ/kaTymIwhycdzVXRIjp/iGC4vw4t0JZthDEjHA/xpvZscEm9WTG4vDNE1qTGVcEkHGB9a7y4n1yLV7WKCMtblU3MqDa/94k9u9QWfhvbq6TokT2BPmIS2crjIGPyrra8+vXi2rK52UaUrO+gUmBnOOaWiuA7TmW8TXC+Kv7LNqoh37NxJ3dM7vTFbC6xp76idPW6Q3Q6x89euM9M+1ZXinw7ca59ma2mjjaLIYSZwc45yPSmL4csdIlbWZJZ5pLaIyMpIwzBeW9eee/eupqlKKeztt5mKc032OmormPDHi5dfnmt5YFt5lG9FD53L3/EcfnXSSSxwrulkRFzjLHArCdOUJcslqaKSauh9YHijQJ9dt7dIJ0jMTElZAdrZHt3H9a3wQRkdKKUJuEuZDklJWZnDdo2ggEtcNbQgZ7vgVzNrrdhDJJfvYn7YXwAjnYc9Tz0NdrI6Rxl5GVUHUscCuE1Z9NuNVMFqVTcxV2fiPd6g+ldWHtK6aOTENxs0dWZpNW0Iy2bGJ5k+XJwQc8jP4EZpNEtLuzsmju3yxbKru3bR9av28Qgt44hjCKF+UYHFSVzuejitjoUNVJ7iN90/Shfuj6UN90/Shfuj6VmaC0UUUARXFtDdReXPEsidcMM0+ONIY1jjQIijAUDAFOop3drCsr3MTxa0Q8M3gmkdFZQoKDJJyMD6E9fauU+HurzLeyaV5O6F90u8Z/dkADntg/zr0G5tYLy3e3uIlkicYZGHBqOysLTToBDaQJDGOyjr9T3reNWKpODW5Di3NSLNFFFc5oFQm1tzci4MEfnAYEm0bvzqainewWGGWMSCMuu8jIXPOPpTwcjIrzvxLCx8UvHGzb5SmCeuSMYHt/8AXra0y/tvDpTSb+6LXEj7gEBKRhuACffr+NdEqFopp3b6GEa15NNHVVHLKkKSSysFRF3Mx7CpKingjuYZYJV3RyLtYe1c6tfU2d7aFbT9WstU3/ZZd5T7wKkH681erN0vRLTSDIbfzGaTGWdsnA7VpVU+Xm93YUOa3vbnGeK/Cdzq2qRXtngllCSqzY6dDWnpWhQeH/MvZ7ouRHtYlcBRxn681a1bxHpuizww3krK8oyAq5wOmT7VfuLeG+tGhk+aKQdQfxBFbOrU5FGXwmfJHmcluJZ3tvfQ+bbyb1BweMEH6VJPBFcwtDMgeNxhlPeoNP06DTYDFDuIY7mZjkk1l+JJNZja3/stZChzvMagnd2zntWaipTtF/eU5NQvJGxaWcFjD5VvGETOcZzk1PTIfMMEfnACXaN4HTOOafWbbb1LSSWgUVQ1LWbPSvL+1OwMmdoVcnA6n6VLd6hb2enm9kYmEKGBUZLZ6Y/Onyy003FzLXXYtUVS0zU4NVtftFvuADbWVhgg1amZ0gkaNN7qpKrn7xxwKTTTsxppq6H01/u/iK5Lwbrutavc3iana7I4wCreUU2tnlOetda/3fxFVUg4S5WCd1c4q2t7bwt4geW6u5JfNU4CJ0DHq5zz07fWu1jkSWMPG6ujchlOQazdY0O21ZAz/JOowsmM8ehHcVPpenjTbFbcSGQgli2Mcn0FaVJRnFSb94ygpRk1bQu0UUVgbBRRRQAUUUUAFFFFABTZJEijaSR1RFGSzHAA+tOqK5toLu2kt7mGOaCRSrxyqGVh6EHgigCKLUrGZ9kV5bu3osqk9cevvVqvMNK03TNJs766stJ06Kf/AISdbYSC0TKxm5jG0HHGOo9CAR0qOHXPFVxp0Vz/AG4iNPpd3fhRZRkRtC6hVGeoYMN2cnjjGaAPU6jaeJZlhaVBKwJVCw3EDrgV55b+KvEN7r3mwQT/AGKK8gtXiEMQgKukZdjIzhw+ZMqAMEADBJzVvxK13D4ru7rTooG1KLRgLZpQuVZp9pClsDcQcAEgE4BoA7hp4kmSJpEEj5KoWALY64HepK87sbxtTvvDk948s19a6xNbs13ZLb3EINpK2xwOM4IOV+VhtNeiUAFFFFABRRVa71CysApvLy3tw33TNKqZ+mTQBZopsciTRrJG6ujDKspyCPY06gAoyPWijA9KADI9aMj1owPSjA9KADI9aMj1owPSjA9KAEyPWuL8Q/Eey0HVZLBrG4naPAZkYAbiAcc+xHNdlKxjhd1jLsqkhR1Y46V5j4e1TTfHGu3Ftruj2RuDHuidVZW+U8qTnkgd/rXTQhF3nNXSJk+iKmq/GC5hv5JNN0+OaxSPISXIkdtueoOBg8dD0qXwXqz/ABa0HULbxPp0XlWk6NDPb7oxuIOQMk8gfo3NQePtO0W5DXejXFmsunoI7uCI42oCFDemF6H6iud0vWPEfhrRjq+lxPJpzPhmZd8BJ43HB7EYzXpKlTlSvSVpaWvv/TI5nezPRV+HHhrRyLt7i4itYGD+XJKNgAPQnGTz75rtLS8tr2AT2s8csbdGRsiuFudZm174VDVdSsmhnfBCx5UZD4V+einrzWd8LdHvBe3WrNJttSphAz/rHyDnHt6+9cc6cp05TqS1i7DvaVkj0bUdMsNWthb39tFcRBtwWQZwfUV57omm3V149c3Wlm3trZiVWNNkce3iPB6HoPr1q/8AEbxHqujT6fbaZKYDMGdmVQzMQQAoB+v41q+CL/Xb+xuH1yJ1KuPKaSLy2bjkYwOAcc1MFOnRc+j8wdpSsbGu6k+k6Lc30UPnPEuQmeOoGT7DOazPBl/HqemTXn2CC1laYq7QrhZMYOR+dVr/AOIOjW0uoW0Syz3FpG527MLIV6qG9ue3Y1i6L8Tku7i3tptKWJXlEbNDJkLk4GBj86UaFR02lH5g2r3uej5HqK8h8Z2a6Z4kme3vXaecmchQQYw2Rjdn6/hXfeNYtbl8K3ieHWK6idu0oQH25G4KTwGxnFedXFte2vguOXxGhm8T5K2ySyEyeSWABk28MRliMn09K0was+a++luvr6Cqq6Ma1Q+dHu4jLAOQMlVzyQO+B2qaRo5LhxbymSNWIQkbSRngkdqx7TU9QXUFsL2yjRijOkqdSB3OOPauj0i3juGuocwRytA8okmOANuD1/h4zXqz93VnG1rYxzqN3aQ3GmxOBDM++SLYrFm7HJGfyqgLO1ttTkvreSfapJVJkAbcRznHbJNdK1hYLZRXizxy30sjE+VLuCxgYGR6k/oKyLt4XyyyR5+6SW4z2FOMl0K5nsa1pDLcvDagBpJWCjPHJrqtD8FXMl9LHq0Dx2qKR8sgG857Y7Yz6Vy1naXl6jm2tpZmjTe4jGSOK0r3xBrdzp9tbrdtCYOrREozcDG498frmueqpv3YNImHKtZHeeI/DZ1iG0S2mjg+zgqFK/LtOOmPTFcf4m8JWuh2lvcxXBk3NscSdSxycjHQcdKv+H/HcsMws9eYMWOY7pUAAGP4gP5it7WNPtPGGkRyafdxlo3Jjk5256FSOorhjKrRkozfunQ1Gabjucr4NtLi51+S6so47eyzi4iDfKVIOF2nk/8A661/FOgeHdJ0V7hNMiE7OEiKluHP49AMnHSt/wAOaBHoOn+VuWS4kOZZAOp7Aewrjob9/FPixrSTc1p5h3W8pO0InB4HfP45NNTdSq5Rfur8Qtyxs92TeHPEiaZYzWd6ZZIv+WKqB8vqP61m6VrGn+HtWvPs0E9ypiKpv2oOxwRzn6/pVrxToZ0a5W4hI+xzuQqgH90cdCf5Vu+G9Pt5NMa91XTbWNkBVZpIQpMQHU5/nWkpU1Bz3UjKKnzcr6HD3l62pyfbfsUNugxGfIQhM8n88VNpXhh9avBdHUIrZElUEyZ3E9flPrWv4q1HTdUt7KHR5UaGAsxEa7U5GMY9f8axZtM1W0sxJd2s0UCuUUyDGCeTj8utbxk3DT3WS/dk3ub/AImivdI1JmtGmUSAyCdc8cncCRVLwh4f0vxAl411KzNHhVjRipGc/N7+305rtJbi8ufBbTR2nmXUlrjyWXO4kYPHfI5xXG+GtWtvC2lXb3NqwvZnxErA7mAH8QP3QCfxrnhOcqTUfiWmhqqcYyv03Kl4miaRfx2llbSXssEp8yS4YhXIP3QFxn/PWup1nSPD+pa9Y3F/dtb3rombfcBv7qDxx6ds1ytvLq+oawNZ0/T/ACyrEu8EZZC3ViQ2eo9P51ciNrrN++p3+pQpNEQfJXAMu0ZAHPHYZq5RejvsvV3YlK2ltz05VVRhQAOvApstxDAAZpo4wTgF2Aya84+26/4rBVLfasDbsREoMt0ySeSK6PVPDF1qgsme8USRQrHKWBOT3Ye9cLoKDSnI19q2nyo0Ljw3pd1rMeqyRsbhSG4f5WI6Ej16flWJ4k1bT7zQ9TsLMFZyPvKm0Ehhk59q62CFLS0ii3ZWJAm5u+Biqtvolha3kl1FABLJnOTkDPXA7ZpQqJO8ru2xUot/D8zyjR4EhtnS6L7y4KMh3BRjkYP59a7Dwt4imVntr+WGKzgjAWRyE2nOAMk855/KsXULB01Wa1t289/MZRsXkn0xWDdSpZTT29wh82JihXGfmHFepKEays+pwwlKMr2NnW5tas7+SW+iEqzyN5Mucqy9gpHbGKuWun6s+kfa9IuN0kjKsscD4kUYzjJx3PasnQNT1NtElsZplmt5Tsiidg7pjrtHUDkY+nFd9oraZpBSw81heT7WkWQZwxHC5xgfSsqspU42tqvy/Q0UYuoc3q18LXTotN2ImqzBftssaKN+edpbuemaq38UWh2NvDeWCT3simbcXIVB0CnH3+mSK6DxJ4Tn1jUIru0eCPcgSXfkdD97jrxx+FY2raBJeTJDpmoxXUtnAqNDuw42nnaOh6+tTTnBpa+pU4u7bXoc3qdvBrMy3F2kcrF97s3y8d+BWvd6d4em0CC4tTKl26+WUiYbUYDklT049PWr/h7w7Hqtvdm+guVEYAQqdpJ5yvI69Ki0CTSrOK4tdStTJHIwYMyklSOMY7Yya2lU6Rv7vYyimlq9+5maekMdpErS28xHBjUk4Hqenr+legaE8cXhtjdQxw2yBicjAZMZJP61iadY+HLKDU7qzlOoyQRFvKlXO1RyMcDPPeqNj4nTVdPvbDWSwt5YyqtCoyp9Bj/PFYVb1U7LZr1+40hFU5Xb3Kltb2/iDUJItNVII5OBuOdi++eefast5Tpsl5YSA+ajMgZDwGHfHpWp4W0P7XetHDKyqpEjSFeRg8Djoa0/HcVwLgt5MUVq4XM3lgbz6M3X8K250qnszNQTi5M43Qmk1K7e1tyXbYZMMccAcketdd4e16GyjksFhit45VZjLHkuZCPvH1qtpfhZbG1h1bTJ1ncIzSSRNjyyM8AHnpUGpSWU1wbi3imhuZG3sAymMDuRxnJPbtTm41W49P1E24O60f5mVJeSQKxJLl+pJz+NLawTSO7sPvDKjPQVFOUEqRn5lb7y9akY3T3Fsts21SwBzwc9MGt+hl6FiSO4hlxFIMBehGQaZZvEmowveqZYC4Ei5IyD9K7m30iy0yxkutZjieRfmVA2eB2A7nNcneT2NzqLSw2nkQ5G1BgEcflWEKqndJadyuRwSctz0+0uLa5t0e1dGhA2rt6DHap8j1rmfDFjLaQz3QmjmjkT5Y42zk9efQ9qqQeL5Z5rqx8tBfFG+zjYQPMwcIc968x0W5Pk1SO+NXRcy1ZNd+JNRg8YxaWloptmZVztO5gRy4PTA/pXV5HrXOeEbrWru3uG1iNxtYCJpI9jH1GMdOldJgelTWST5Utu3U0hqrhketMkRJY2jkCsjgqynoQe1PwPSjA9KxLPOv7F1LRfHETaRZSCycqNxG5AhxvBY9O/v0rsdZ0r+1YolEwjaNiRkZBzWngelLgelbyryk1LqjP2cWnF7MhtYFtbWKAOWEahcnvipsj1owPSkwPSsW76lpWVjG8T6Q2s6V5K3KwmN/My/wBw4B6/nXGXGgz2dlbNaEXmd2+W3yyg56fgP51v6r4Y1DUfEf2oXSi0YAHLHKADlQvQ/wD161rK1tPDli7XF2MO+S78DOOABXbCp7OCUXfyOacOeWqsu5Z0aW7m0qB79dlwQdwIwcZ4JHbir+R61zHiWLWL1bOXRJWaE5JMMgXJOMEnuK6OBZBbxCYq0oQbyBwWxz+tcs46c3fp2N4vp2HsRtPPahSNo57UMBtPHahQNo47VmWVtQ1G10y0a5upNkYIHAyST0AFLY39tqNol1ayB4n6HGCD3BFM1PS7bVrNrW6UlCQwKnBBHcUunadbaXZJaWykRrk/Mckk9STV+5yeZOt/It5HrRketGB6UYHpUFBketGR60YHpRgelABketJketZ2vTX1vo1xLpse+6UDaAu4gZ5IHc4qv4YudSu9IEuqRlZ95Clk2sy9iR+dXyPk5yebWxtZHrRketGB6UmB6VBRj6zrml6RJG90FkueiIihpAPXnoKQ6VpGtzW2seWXYqrKdxAbHTcPas+/8E2+o6+2ozXL+S5DPDt5JAxgNngcV00EEVtAkMMapHGoVVA4AFbycYxXI3fqZpNt8y0H5HrWXc6/aWmqLZOHLtgFgOFJ6ZrUwPSs6XRLKfU1vnjYzLg43fKSOhIrOHJf3hz5re6aOR60uR60mB6UuB6VBZzmveErTXNQivZriWMooV0QA71Bzj26msiHxTfz6pAsflRW28IYsDG3OOSfatrxdI0WlKUu0t/3g3AvtLj0FV9O8NWVzYWdw0oZymXaFsrJznr+ldtOUVTvU1Wy8jlqKTnaB0+R60ZHrRgegpcD0riOoMj1oyPWoY7i3mleKOaJ5I/vqrAlfqKmwPSgDP1PR7LVvL+1KxMedpVsHB6j6VYls7aezNpJGrQFQuztgdKsYHpRgelVzSslfYnlW9itZWVtp1uILWMJHnOM5JPqSaz9d8RW+hLD5kUkzyk4VCBgDqcn6itnA9Kq3um2WooqXltHMqHK7h0NOLXNeeoNO1okltcx3drFcRE+XKgdc9cEZqRyNvX0oVFRQqqFVRgADAAocDb09Kh+RQ7I9aMj1owPSjA9KADI9aMj1owPSormJprWWJH8t3Qqrj+EkdaAJMj1FLketc/4Z0S70hbj7VMjiQjaiEkDGeee5roMD0q5pRlZO5MW2rtWDI9aMj1owPSjA9KgoMj1oowPSigAoorn/HF/eaX4K1W9sLlLa7hg3RzPjCHI5OQRVQjzSUV1A0ho2nCJ4xaR7HuheMPWYMGD/XcAfwqNNA0qOFIUsohGlvJbKozxE5BdfoSB+VfM0/xX8ewylP8AhIo5P9qKCJl/PbTY/iz49kkVP+EhVMnG57eIKPqdter/AGTW7r8f8iOdH0ofCmhHVINS/s2H7VCE2PzgFBtUlc4LKOAxGQOhqvqPhz+0vEJurkW0+nT2Js7m2mjJLfPuBBzgc/y4rN+GGsanrnguK91a9jvLozSKZYwuCAeB8oAqDXtc1nSNS1K5ka7iswrxWGFgaB5BDuywx5mchz1A+XHfny6kHCbg+haNYeFo7S/0f+zVgt7GyuZLqZW3vLLI0TRg7yTnh+ScngCukrF0Ca6E2p2F1dSXbWVyI0nlVVZ1aJH52gDILEcAcYraqACiiigArgtcC2fifUr2X+wrgfZYmKX7sXgjBI4ARsBmPTqTXe1wPiD+yo/El3cSNqEjQm1kntoVTy5592IEyed3OcdMAE0AbHgZFGi3Ekcto0Ut3LIkdpu2Qg4ymGAK4OeMDrXTVzngzyv7LuyPtX2s3kv237SFD+fxu+58uMbcY7V0dABRRRQAUUUUAFFFFABXm9z4i8IeEfGssRsvs80rbJrzf8kbN8xAXPA6ZI6V2+vw3Fx4d1KG0aRbmS1lWJo/vBypxj3zXzZpngyVfD2p6jqgu4WgliSFkQ7SzEhgwYdenI6fjXo4OjCak5ystrepEnY7jx94AMGntf6VfxmwnJd/NmVQoPzLg/xg+nXp1rrvhLaWNj4Seytr17qUTGS43x7QjMBwo/u8de/NcHr3iTT9X8L6Po9vay24sVC7mk3AYG3GP4uOc8YrtvhNbRQaXest1HI8jruhXO6PAPJ+vtxxW9dT+rWm9mSmubQ3vE/i6x8PTQWlzaSXHnIWdVxhUzjv1+ldBaiEWsX2dFSEqCiqu0AHnpXF/Ek3Mdtp8ttpcN0RIcyvb+aY+mBj0Pv6V1+lzXFxpVpNdwCC5eJWkiH8DEcivPnFKlGS636/oWnqzlvEfgM694lttVGoNCiBBJHtycKcjac8Z/8Ar1naXa+NrLxjqd9fPLPpiLM6x+cCkowTGqL1B6dh365r0QnAJwTj0rifDXxAj1zxBNpc9vHbuQxh+c5OOqnPfHPHoa0p1KsoNWukvuQnZMy/h+LbWtb1LVLjSIorkc+bHu8sF87l2sSM+v1PSu6j0TSkuI50060SWEny2WJQV+mBWgAB0AGea4/xT/wk/wDa1p/Y3mfZu/l4xvzzvz2xj9alzdapo+X5h8K7nY1w3xA0qHyI9UTf9pysJAI2kckEj9OPWu4Gdo3Yz3xXm3xDS9/tm2mdGFmsW2Nx93cSSQfQ9KMKn7VWZNX4GcmkUkmWfaG6AD/GtPw7YRavqX2CZ2WG5hkjYp16ZH6gH8Kx7iO4UCdHO04BT+tbPg3X4NE1TbcQs8dyViDqBmMk9fXHI6V69Xm5G47nHTV5IZrun6DottJaRaz9svlYRNCF27D3JI9AMY9TXKXrWs0NnEsZ3W10Zy4bIYEAbceo2g5z3NXvFdjDa+MNSt4gyRrKWCs2SN3zE/TJOK5yadUuzbruB4HtmtKMfdTvfqbNa6HXWevXmlia506Zo/MQws23jnnj3HY1Vg1TVpY3tI3aSOVxLIzjLMR/tHkjPb1plmbLUITDLeRWaxIGJkUsSR2UD7x/Krd9dWPnJHo0MxgiiUbpyFLP3OO2TSsr2tqRqolS6uJTcKrhVkQfdHY16D8MNU82O9050XcpE4cdWz8pz9MCuDls2LLdzykyNgsFXj6Ctfw3ba3HdJc6MGyzbH2Mp6EH5x2XnrWVeKnScQpys9D2ivL/AB1qVpB4hWzhtzFKqBpZUUDezdOnJwO9dR4z8R3vh2xtpbW3jdpXKvJICVTAzjjuf6Vzut6TfeIF07xKkLfNbKrWwUlozk/MPUc/XpXnYWHLJTls7/edFV3i0Gqa0Nf8MhCJonspIhKrnIlBBAJP1HSuj8OKmseDhZ3JdoyHt2O7kr9fx/Sue0PVYdNS8sL/AE/zUcM0qsOflXOCpHt+FdH4Y8RWepILOO1SyePmOFTkMvqOB+NXWi4waitE73M6ck2m2O0TwZpmjIxYG6kLhxJOB8uOmAOK6L5XXsyn8Qa5/wAUXljNp1zpr6nDa3LKDhmPTIODjnmpfCdg2n6HHG11HciRjIrRklAD2BNcs1KUeeb1Nk0pcqRlePYtWNvazafJOIUZvNWAkEHjBOO3Wuc0rwVPrNs98dVhZ3Xcyr87byM4c54PT1r067tlvLOe2csqTIyEqeQCMVx114Wl0Xwpq8VnqwhurlAFnkPlKoB6ZHQkEjPvW9GvaHInZ37EyheV3sYP9m+JdE01pJEnS3jDKyCXcoDcH5QenP8AWsXTNMt7bT/tAuWNy77DCUwAgHDZ+tbPh/W9U8H6ZBZX7R3wnbz1IuPMEcZ42hu5yCfQV3lr4dsotVOpo0hL5dYzjaC3U/rXTOs6d+brs11MXT5tIs5jwNrj/wBqz6N9nBTDSeapOVIAGGHau5vb2306zkurqQRwxjLNjNcra6jr3/CV3sAsFEGJMfudowAdh398nHfvUujpqWv2V9Z69BJ9nbbtZk8tg2c4H0wK5a0FKXO9FpfU1g+VcqK/imaDxD4YS+sbz9zDL80bKRvPTaR688fWm+ANfvNRjfTriEGO1iG2YZz1xtbPf/Cujs/D2nWWlPpyRF4HO5/MbJY+ufwHSrllY22n24gtYhHGDnA7n1J71Dqw9m6aV9dClGXNzMrSaJZtczXUaGO5kVgJAT8pIxuA9a80v/C2p6ZqduhtBehyCCiFkfB6N6e9euVk+I9di8PaS17JGZGLBI0HG5j0yew4ooVqkZWWtwnTja+x5p4y0NNE1vzbVwiXCmVERdvlY4wCO1ejWuhWk01rqUjSvOI0YljgOwUfMR61V8N6rD4u003N7p8O+CXau5dy5wDkZ6VY8T+Il8PWUcqwiaWViqIW2jjqa0nUqSapfaWhKjH4nsaD6nZW1xFazXKJPJ91CeTnp9K5G60vUdI8SpNpdvJKjncpK5Xn7yk9q5y7h8Q+Lr221TTbURKrLE5SXCB1Odxz1GCPXpXaWN54ifxZLBcxMLAFgT5eEC4+Uhu5Jx+tNU/ZLRrbVEy9/fvoQ6Z4smj1NrTVz5ZkYKg8vGxieh9vetXxHb6Wtl9t1GNysJ48o4ZiT0qe68Pabe6nHqE8BadMfxEBsdMjvipNRfTbq0mtbue22H5WDyAbT278HNYucXJSgmu9i1F8rjJ3PP4dXsdCulutJgebz1IkF03KDPKDH8zntXdyaJpd7bMDZRR+aAWMahWHfqK4+38FanvkDeSqKpKNvyHPb6ZroPDWh32mTyT3UqgOm3y1Ytznqf8APet67hbmjLVfiY0+a9pR0OX17VX0xm0izDW0EUhzsY7392bPesLxJf6l4j06106WVdkDBtxBPmHBGWP0Nehv4MtLjVHurxzPEWLiM5ByTnBIPIrnPiRdHRRp8FrAiW0gdigG1Nwxzx1ODW1GrBzjGKu+4uSok2cxFrOpeD9FSKwkjaS4wjSOu4Ltz0U8Z579hWxol7PqHhYR6nFEZppjJbyhVVzHjBYgdRuyB9D6V3E/h/TPEvh+zW+tSm6OOUFAEdG2+31xiq174M0aNLaXzJLW3s4ghVW4ZQc8k855PPfNS8TTlurO5UqUuS1yiNAs7bw6yPfLFc3RSQGVcYx2wOcdeagn8JXdvaQSQ7bmVmJYxHgDjbjPXvzWb4inW71e5nt5i8bgbH5GBjp7d6i0DxBfaffKssk0tvEhBjLnHsOatRqcvMnrvY57wbs+hsSeGtYuLlWvpVECpkzPLu8tR1GKy9Tj09dTdbEsIeNvXA456811c/i6wl0WaRl/etG48k5IzjoSOxrgNP1kJqaPdWkNzF0KNkfjRR9o7uS26DqRjtBnX+HtVttItpBMszNK4OVHAUDGf510S6BpjasNWEGbk/MG3HbnH3sdM4rkdI0+bWvEZuX2C1jIYx5OAvQIB6V6GOBXJiHyy916vc6MOm467dAooorjOoKjmuILcKZpo4wxwu9guT6DNSVzviPw6PEEkJju1jaHKspXcMH2zweKuCi5Wk7ImTaWh0VY+s+IrPR4nDOstyuMQK2G59fQVqW8QgtooQxYRoEBbqcDFYdx4TtLnW21CWVmRm3tAVBVjjHX09qqnyc3v7CnzW90v6Lqqazpq3aRNFlirKTnBHv3rLu9N1mTxRFdQ3BFmGU/6zAVR1Xb3zz+ddDDBFbQrDBGkcajCqgwBTi6B9hZdxGcZ5xQp8sm4oHG6SbHVyXjK9sw9vZXCTbh+98yMj5R06Hr3rrayde0VdYtkC+Ws8bZV2XPHcf59KKMoxmnIVVNwaRd0+1istPgt4WLRovysep75qzWMtxb+GtIt4rydnIyo2qSSevA9BWrb3EV1bxzwsHjkXcrDuKmafxdO44tWt1Ht90/Shfuj6UN90/Shfuj6VBYtFFFABRRRQAUhIAJPQUtUJta0631FLCW5Vbl8YTB79AT0GaaTewm0tyho3ii21m+mtYoJIyilkZsHcoOPw6itme4gtkDzzRxKTgNIwUZ/GorXTbKymlmtrWKKSU5dkXBNZfibw6dfitwtz5LQsT8y7gQevHrxWv7uU9NET7yjrqzeBBGRyKKr2NqLKxgtVdnEMaoGbqcDFWKye+hYUVga94ss9AuYreeGaWR13kRgfKM4HU+1XtF1m31yw+126uoDFGVxypH/wCsVbpzUedrQnmV7GjVC11exvL2S1gnDSp1GDzjrg96v1l2Wg2VhqEl3CH8xs4BbIXPXFKPLZ83yCXNdWNSiiioKOC8cWN3JqMVyebfYEQj+E9SDXTaO1tp3hm2kc+TBFDvcyHp3J/nWLq3iC8tPFUVhIIRZMyDbIoIZT/ET25z+VdPqFtbXWnXFvd4Fs8ZWTnGF+vauuo37OEZbeRzwS55STItK1mw1qB5rCcSqjbWGCCp9wau7037Ny78Z255xXH2p07wtoNxcaMzXbSTKsjyt09M4AwP8an0ixn1a7g1uRxEGbcUwc5HHB/unFTKlHWV7LzK9o9EldlvR/DC6Vqs159qaQMGCLtwcE55PeugoorGc5Td5GkYqKsgorNt9dsrnUnsI2fzVJAJX5WI6gGtKlKLjuNST2CiiipGFNf7v4inU1/u/lQA6iuXu77Xk8Wx28MDGwLKOI8qU/iJbsRzXUVcoONvMmMr3CiiioKCiiigAooooAKKKKACuT+Jg3fDfXR/06n+YrrK5b4jjPw81sf9Ox/mK1ofxY+q/MT2PlIw8mk8mtDysnik8qvseYyPoT4Krt+HcA/6eZ//AEKutm8MaRcX095NaeZJOGEitIxjYsmxm2Z27ivylsZxxmuX+Dg2/D+Ef9PM3/oVdRqHiTTtM1BrK4eTzUs5b19qZCRoQDn3OeB3wa+RxX8efqarYt6bpdrpNs0FojhWcu7SSNI7scDLMxJJwAOT0AFXKoaVqiapDKwt57aWGTypYLhQHjbAYZwSOQwPBPWr9c4wooooAK878S6jaWniua9bS7GZ9P8As6uXnKTStISFKDO07d3VumTyK9ErgvEus2Ftrt0LjR9IuI7QQfaJLplE7iQ4/dgqc7RycmgDoPCVsbXRdpis4t0rP5drMZguefnkPLv6mt2s3RLe0t7WYWM1rJbtOzKLaNFRM4+X5OCR6nmtKgAooooAKKKKACiiigDK8R6lc6ToVze2kHnTRgYUgkDJwSQOw61yWp61d6x8LNSu7612SEeWNgKhxuX5wD29foay/jLqGrww2NnbCWPTpQWlkjyA7g8ISO2Ocd/wry5tRvZY4Rc3c84iUIgklLBVHQDNevhcLzU4z03uZSepasovt7fZ4raV7jlh5fzZUdflxnjk5rp9B13UPBurw+dZSCK5VfMikTazpkgFc85zn69KoeE/FP8Awjd691Dp8EzSgKWckMq5yQpHHP07V749ra3jQzz2sTyR/NG0iAsh9iela4qvyPllG8X5kxjfUsDkZpaKK8M3CvKvG3hi50PWofEfh+K6e5lnZ5QkYlEbkdQuM85PtW9478Vaz4evLCLTLJZY5gWZ3jZ97A/cGOhrs4HeW3jeSMxuygshP3SRyK6qbnQtU6PoS7PQraPLeT6NZy6jEIbx4VaaMfwtjke1W1/i+tOpq/xfWuZu7uUOrj/iB/aD6bbw20JezdmN0ypuK7cFfoM5yfYetdZPPFbQSTzSLHFGpZ3c4CgdSTXz/wCJde1LUPHV1PBqxuNIl+SJEuCIzHtHGzuc89K7MHSc6l10M6j91l6R0SFcvkdMZzT7K7On6lHfRQwyyRr8izLuXd2bHqPWqmfKtmLDKkVGs4khVU37y3Py8D059eteva6scEU1qhYNIu0jl1C9ttkV05bzpMZlbOSR3NULuWwkQAxsssfKHZ0Poa1JZ5TbrCxaTyx8oLZ298D0rnLgXBuWa4hMTNzjOeKuN3uaR1dzR0m1ildndM54TccD3qXUbiLTrSNrdkbc+SOCSMdj/nrVPS5nvL2LS7dGkmdtqKB378+nU1d8T+G7rw68N3cyW08Vw5WE277g+ByelDa50m9yuRt3Ol1zw6PDXh6TU5bsywTlI4UdMOoc7st/tYGOPU1D4RttSj1DT9XsYXkjlJVCEJDrnawJ7Y56+ma5i5vZ7tLaHV3vpILiMSxFpT05CsM8Yz+ma9J+FCyQ21/aq7m2j2FVJyAxzk/U8Vy1XKnRblq/02Lsm0loa174tnj8ZJoTaekluzrGS2SzZGdwHTA/oa3dftr260l4tPfZNkHAbaWHoDWkY0MgkKLvAwGxyB9a5Dxp4mu9MjW00ll+25DSEpu2rjoAeCTxXlw9+cVTVmv6ubSsovmZmeGtbkg13+zNQtzJLMfK8yRR5iHH3STyRXQyaRpHhyafW28xEjBIQcqu7jCj8cfjWZpvhifV7iw1/UpJLe7YJJPbhMZZeAevy5ABIrrr6zg1CzktLmMPDKMMtXWqR5/de+9iIQaWvTY881eHStXs7zxBZz3JYMoktygGxzgAk+mK3/BmsRS6LLB5BiSyXLMG3Bgckn69eK47VLVtKvriwtRNDAsn8bHL+jHoCPSvTdHezm0qKS1EZjdfmKxhNzdDkfWta9lSS3XTyM6es2V9E8Q2+tPMkcUkTRgNh8HKnvxU2uaPHremtaSStF8wdXUZwR7d6sWenWen7/slvHDvOW2jrWHbeKmm8SPpktuscfmNGrEnduHr9cVypNycqS21Nr2SU+pwkeqWNlqwsbmxjvrOzkkVXIw7HPXOcYz2PFekaD4itdchby1MM6fehY5IHqD3FcnfQ6XoXiaSK2sxcmZdsscp3Abzyq/p1z1p1pqOk+HdXu2t7W6kYExKXkXA55AH4d/Su2rBVY3Sd7aGEZ8rtc9DrG8SLqb6co0suJN43+WcNt9vxxWlZXcd/ZQ3UWdkqhgGHIqevOi3CV7bHU1zIpaSLxdKtxfnN0F+fp+Gcd8Yq7WNr3iO20HyBNFJK8uSFTHAHU8/Wmav4r07RrC0u7jzXS6GYljTLEYBzz06iq9nOTTS3BNLS+xuVw2ueIdI1bVJPDuo2k4gEwT7Qr4KyDocenOM/pWvqXjXSNNtbWeR5JFuoxLGEXnaehOcYpdPttC8SNDrkdmGmDY3MMEMPUA4OOOa0px9n7807dPUmTvomaml6Za6Pp8dlaKVhjzjcckknJJNcxqljpnjPUESC+lilt1IP7vIdM8lc+/f9K7Ss6x0Sw025luLaIq8nHLEhR1wPSohU5W5X94JRbslsYM0ut2Ov2djYW7DTUCKoEYKsv8AEWbsev8Ak119eXax461iy8WNDZNDLpsbBQmz5XGOSW65znp6d67PXLnVJvD0VxpUciTybGZVALqpGSAPXpWtSlL3L2V/61FGSV7ai+LNYk0fRmlt5Y0uXYLHv5PXkgd8CvL7iKWWeJLwMrTbWy65OGP3sfrXoEnhu48R6NYPq80sF7EGBKqMlSe46ZwBT9b0fR9NittQngmka3EcSIr/AH9v3d35VtQqQp+6tXr/AMAyqxcve6G3DaSadoa2ttIZJYLfZG7/AMTBeCfxrzNvEOv/AGZo5LidlLhix6g+mR0HtXp2l6jHqtgl1GjIGJBVuoIODWfr+lXV5DGLAqnzlpFB2bz2JI64rKjUUJOM195VVOUbxL+lSzHRrWW8JWUwq0hfgg45zVdtX0e9sbi582K5htR5jjZu245yAf0NQabqlrqMLaXJI8sohKSOwwJOMMQa5Tw7s02bV5DJHdQQ27CSJTu80A8Y9uuT70o0r8zejQ/abW2Ow0HxFba/FM0EUkbwkBkkx0PQ8fSuOu9f19lu7bUbbbBISmHhKhDngK3f9a2fCuraeui39zb6atotu26QRMWD8cYJ/wAim6pqq674dmkjiML28yllZx0Oenr9K0hFQqNcul1v0IqSvDfUTwwNPvJTBJYK0iDzRJIdx7DHTisaJ7LUNTvIL24EQdZAs7DjdnAOO1ULG98T6Kxmjik+zzH5SYg6N6YxUK6dqMV3dSX8sYl6mMuCzFjk8DpjuK6lC0pO+/mc7VoK/Q3dL8MWt/pt4trqsVxcAEbYxhAccZzzz61z8WnG1v5La6ws8bYEQG7c393Irs/BsNna291NGzNesPmiz/COm365rltVvRqF6109skMrfe8vPJ9896VOc3UlHoOfLyKS3Z3Phy/c25S9WG3kd8RDYIzJ/wAB/Suhrmj4fj1NrC9F4xUQx7vl5bA4IPbNdLXm1eVu6OylzJWYUUUViageRXHaf4Q1Cwk1KRNRUPcQvHGy5BJJzub3+nrXXq6vnawbBwcHODTq0hUlBNLqS4qW5z3hPSNQ0mznjvpgxdwyIHLBOOeT61S8darHbWCWSXLx3EjByiA8pyOSOnP8q66snVfDmm6zcRT3kTM8Y25Vyu4ehrSFROrzzJlB8nLEpeC766vNGK3IZhE+xJWJO8de/p0qn4i8K3upXkl1a3EfzEHY5IPTGM+ldVbW0Npbpb28YjiQYVR0FS0vbONRzhoL2acVGRS0i0nsdJtrW5m82aNMM+Sc/n6dKu1l69cX1rphksELS7gCQu4qvcgflU2jzXdxpcMl6mycg7gRgkZ4OO3FQ4trnZSkk+UNT0m11aFI7lW+Q7lZWwRVm2t4rS3jghXbHGu1R6CqWsauukwxuYTK0jYAzgce9W7O5W8s4rlFKrIoYA9RQ1PkV9gTjzNLcmb7p+lC/dH0ob7p+lC/dH0rMsWiiigAooooAKxrrwzYXespqchl81SrFA3ysV6E/kK2abJuMbbDhsHB96qMnF6MTSe46iuG8ErriavejURdeVs+YzE48zPbPtnpXc1VWnyS5b3FGXMrhRRRWZRn6joem6s6PfWiTMgwpJIIHpxU9hp9rplqttZwrFECTtHqe5PerNFVzSta+grK9wpB940tIPvGpGYfiPR7vVVt/ssyqIydysxA578elbFtG8NtFHI5kdECs5/iIHWpaKtzbio9iVFKTl3MbUvDNhqmoxXtx5gkQAFVbAcA5Gf/AK1alzbx3VtJBKCUkUqcGpaKTnJ2u9g5Vr5mdpmj2+mQyxozSeacsXxz6DFXZX8mB3VC2xSQq98DoKkoocnJ3YKKirIwvD+vS6w86y26x+WAQyEkc9j71u01URM7FVcnJwMZNOpzabvFWCKaVm7lGHSLGC/e9jhAnbOTk4BPUgdqvUUVLbe40ktgooopDCmv938RTqa/3fxFADqKKKACiiigAooooAKKKKACiiigArnPHztH4F1hkIDC3OMgHuPWujrnPHoz4F1gf9O5/mK1o/xI+q/MT2PmyYvPIXkILdMhQP5U2MNFIrpgMpyMgH+dXDFzSeVX1VzC57t8KZHl8DxNIQW8+XkKB/F7U7VvBV9e6vd3UGryeVdwXCvFLGmFd1jVACF3bRsHfPHuaT4VLt8ERD/pvL/6FXbV8vif40vU3WxkaHZ3kL395fxxQ3F7OJTFFIZFjCxqgG4gZPyZ6d616KKwGFFFFABXmnjO4MPiOQR6hpbv5aH7G1kj3A467ijcHtnFel1wWvC0vvFdzaahe2GlRxQRvFLPaws9znOTvlBGFwBgc0AbfgpnbQN0kDQMZWJRo4UI4HaL5fz5roq5vwROJtDl2JbeVHdSRxT20AhS5UEASBRxz0yODjiukoAKKKKACiiigAooooA4H4vJcyeC/Lt7Vpw1zHvZVLGIDJ3YHqePxrypvCuoLoel3Ftaz3E10HMsUa7jEd2EBUcrleefX2r2b4g6zcaVoBito23Xm6EzZIEQK9eO/pXz9PqOr6THK2jXc9tcv8kjwPtZkzyM9eoFe5gFN0rKy1MpNXPRrXwG2kahaTeIbmxtdOyC7NOF3nH3AOuc9fbNeuTahbwaTJqEbCa3jhMoMRDBlAzwa8H0Nta+IR07TNa1ILLaxuBcOgJ5xgNyNzHAHrXYzeJX8DW58M2lstx9lTaZ7g43M3zZ2D+HnpmscRSnOSjJ3kunSwJqJY0Xxlrmv+Loo7VAtluHmW4AYJH3YtjOf/1V6XXzvot7fWXimymsEdpWmX93EPvqW+ZeO2K+iKwxtNQlHlVlYdN3WoUUUVwGgU1f4vrTqav8X1oAq6tpsGsaTdadclhDcRlGKnBGe4rwHVPCqeGfFt0kk6ygoiRSSgBsdcjtz/SvaPG410+GZx4eLi+3DmPG/Z32579PwzXhFzpV9cyk6hf3M92CRK1yS5B7gZ6V6+XppN82nYxq2tZm5H5jwutysQQcDBPT39KRBGnyx4CnnrnNKq4tjDjcuzac85GMc1WjhW3CqvyogwB6AV3nERTWwS5e7MjCTAwc4UY6cd6asGqLdW+qXVta3NpBsaSGNtyAFsESA8gnp+IrWtYTe3kVjBuZ7p1RVb7pPJH07mtXSvB+v3ralBcWZsx9lkiR5D8ruSMAHuDjr2qJ1IxXvM2ppvoebalcPp14l/bwFI2dhIqHgA8Y56da2tP8T2lk9hb6msMuk3EiTSW80fmKAeCwxypA9PxzT9RsoNJhaDVJoftYkKNbKRJsUDksRkA5wAPrXPXw06+ntfJid9mA6D5N3P3R16jHPvXR7s1qaLc9Y8W6BbeO9SsE8PajZobOExmJ1ZAEyCGQgc49PpXo9obLTVg077RAtwUHy/KrSHGC2B3OK5i/8Gwafp8tzpckkMpADLNPgKndQ31x1Pak03wRI9zZ6jdagWdSsjIvz9PugPnp0/pXhzcJwS5tFtpqWpSvaxr+KhrRgt/7J8zG4+b5WN3t17dasR6Fb3clpf6jCGv0RPMKthSwHcDg4NbNFcntGopLQvkV7sK5jWNS1mLXI7Szh/cuAFby9wJPU57Y/pW3/a2nf2n/AGb9tt/tu3d5HmDfj6frUNzrun2upR2Es+2dyOMEgZ6AntmnTTT+G/8AW4p6rexzWheFNRIvYddmMsEhBQCYsS4J+cHtx/OrPjDRtngw2dhKbeGGRWYZJ3rnkE/U5/CuuprosiFHUMrDBVhkEVft5Oakw5Eloc34Ekb/AIRqO3eWSVrd2j3v6dQB7AHFah0HTzq39peSftGd2dxxu6Zx61ehghtohHBEkcY6Ki4H5Vzlp42sZr0wXKG2Rm2xyOchjnGDxxR785SlBC0SSnuctdeKbDU9cN3aaWDNby7d0rkmXacA7R0Pp17Vl+IFvdN1TzdUiYtO/m4DY3rnkAjoccV6tbaPptneTXltYwRXExzJIiAM341V1/w5ZeIoIY7tpUMLFkeJgCM9RyCK6IYmEZJJafiRKi3d3GanqEtr4VN7o8CyERK0Kqu4BTjnA64FHhTUb/U9FW41GHy5d5VTs271HRsfmPwrUs7SGwsobS3UrDCgRATngVPXG5R5XFLrv1NrO9zjvH63bW1l9msFuFDks/leYVPGBj0P9Kg8bwNP4EhurmyjW5hEZIHHk5wGx+gx/hXcVFc20N5bSW9xEssMi7XRxkEVpCty8umzE4at9zznR9Jt/Hfha2W5k+zXenuYFkijH3MAgEdOmPyrvtJ0u30bTIbG1UiOJcZPVj3J9zTtO0yy0m1+zWFukEOS21e5Pc+tW6VWs5tpfD2HGNjlPE/ie60K/gRLdWgKhiWBJfnkA9sV0Gnahbatp8d3bEtDIDjcMEdiCKTUtMtNWsza3kXmREhhyQQR3BFYS+IdK0LVrfw7BayoilY968qrNyM5OT1GT700ozglFe8vyJ1i7t6E2keH9I0/UpjFOs1xj/UyMrGMZz06+nJro64vTPD+oW/jGS+kQC3Ekj79w+YNnA9e9dpSrbr3r6BT22sFRXFtDdwNDcRLJG3VWGRUtFYXsaFK5uLPQ9KeZkEVrAv3Y19+gHuTUej6za65Zm4td4CtsZXGGU1x3xBbUZNStbaETtbSRfKiA7XfcfTqeldppOl22k2K29rD5QPzOMkktjkkmuiVOMaak3qzNSblZbIbHotlBJPLbxeVLMrKXBJ2564HauWsvA11b6dqsH29EnurdreKSMH5c9z9eBx713DAlSAcEjr6VzPhnw/qGkX91Pd3SyJINoCsTvOc7jnof8acKklGXvdvmJxSasit4D8J3nhnS7u21C4im+0SbhFHkooxg9QOT347CqHjC4awntdIstPRIJCJcohy75IwMf55Fd/SEAkEjp0pKu/ae0lqOUFJWOev1uvD/h2KLTVaR1fDuU3FQcknA9+KxNR05W0X+1bsyw3lwf8AVBeCxJ5x1GQM10Mus3MevrYC3BiLBc87iCPvfStW6s7e+gMNzEskZOcH1q1UlTs2t9bmLhGpdLpocz4S06O1s21WeZQCGC88Io6k/lVXxPr2lzRwJDaw3vJbeWKhfUcYOTXWS6bbSaY+nhPLt2QptTjArhNd0S208R2sTySS4Lu74GR0AH5GtKUo1KnNLf8AQmonSp2Wx2mi6na6nYRyWo2KihGjx9w46VpVyHgiMQrdRhz/AAnae/XmuvrlrRUJtI3pT54JsKZNGZYZIw5QspUMvUZHUU+isjU5Xwl4WuvD9xdS3F2kolAVVjzg4P3jnvXVUUVc5ucuaW4kklZBRRRUDCiiigAooooAint4bmPy54kkTOcOuRmpFUKoVQAoGAB2paKLhYRvun6UL90fShvun6UL90fSgBaKKKACiiigAooooAKKKKACiiigAooooAKQfeNLSD7xoAWiiigAooooAKKKKACiiigAooooAKKKKACmv938RTqa/wB38RQA6iiigAooooAKKKKACiiigAooooAKwPGoRvBuqhywUwHJUZPUdq36wfGgz4O1Qf8ATA/zFaUv4kfVClseASwxiQ+UWZfV1AP6E0iRIXAkLBe5UZP5VbMXPSjyvavprnJzHsfw0WNPB8QiZ2XzpeWUA/e9iaxvFtxFa61c3Om3f+ltBcQ3Kxzv56N5G4fJ0ESqN2R/GVI6nO38Nl2+EIh/02k/9Crqvs8IuDceVH5xXYZNo3FfTPXHtXzmI/iy9Tqj8KMDwmLZDqsGnSK+mxXYW1KSb0AMUZYKcnjeW/EmujqOGCK2iWKCJIo16IihQPwFSVgUFFFFABXJapqSWviW4TXA66WIE+xj7H50bOc72LBSQwwABwMHvXW1wXiS81TStZvHV0S3uZbWSF5NRjgGIzmRQGYfe6fzoA6DwnPf3Gjs18ZmUTuttJNCIpJIR9xmUAYPXsOADio9Pu7p9XRpLiR47lrpTC2NsflSBV28ZHGc+pNP8Ki8eyvbq8TZ9qvHnhUTrMBGQuMMpIxwelaH9j2HnzzC3Akn/wBYwYjPIJxzxkgE4645oAy9F11dU8Q38SXSPEsSmKADlMO6sx9zgH2GPeuh3H+6f0pggjFw04UeayhC3qASQP1P51JQA3cf7p/Sjcf7p/SnUUAN3H+6f0o3H+6f0p1FAHAfFnS77UfC6z2s2yG0cyzwlsCRcYB9yPT39a8TaKR9IkuEaBniOwLuAfJ5BK9SPf2ruPiT8SY9RuJNE0ueWO1iZ47p2QATMDjAPXAIPpmvN7O4WQyOqtlV/nxmvo8FTnCiuYyluO064u1Uq7MGDbkOPmzW/pM+u3vjSG8t1+2X1zLl1dA6uCfmDA8BcfljiufhkaGUN1I9a+gfhakU/hj+0DZW0FxNK6NJDGFMiqcAnHvmrxdX2UHK1+gkrsij8N6f4U8RSeIb3VFhtPMfyoimDufPy8HkDJ4A/lXcW11Dd20dxbuJYZFDI6EEMPWsrxN4atvE1jHb3EskLRPvjkjxkHGDweowavaTpkGjaVb6fbljFAu0FzknnJJ/EmvAqTU4qUneX6GiVti3uP8AdP6Ubj/dP6U6isChu4/3T+lIrH5vlPX2p9NX+L60AG4/3T+leBa4tvc+MtSv7eaZo5pGwsvY5Gfw449q7n4q+PdX8ERaa2mWMMqXDP5k1wrMi7cYTgjBOT+XFec3F+uqXD6gq7PtTedsyDtLckcehOPwr18DRlFe0ezMKr0sRavPPHZLFA+GLfMFPzYx/KoLW6m+zjz4ml+Q7lC5JqvPAZtR88SdwcfSpxcmBGeZtseQOnevTtpYxtpY29I1GNkl+xyFSF8uQDIdQf4T3FXU8Ta3Z6dDp2m3co/eM6BPncjGdozn5RgnFY91od+vhxtcgsZPs88Yk+0RYORnHzYOccc5p/hK9iuvE8epardx24tM3UuAse/ZjCqowMnjgds1jKMGnK17fmOMWncrw6RP4kuHhQFpyrzu5GWIHLHHcn075rgo5LhbpldSq+nTHpzXrWva/ZfaJ4fDWnNZ3V8oRpzKRJlmGVjAJC57ketU9I+HFpca2dN17XbS11J0LJZwTCSUt1G7PHvjJJq4V1CLc9F26+exrFdjL/4TjW9S0gWeoXJuIQ6n94Bn5Rgcj698816F4E1y/gs7uIhprS2tjKkZH3WJ4APpyfyrpPDngDR9AsI4JIIr64WUy/aJ4V3BjjoOwGK6aG1t7ff5MEcW85bYgXcfU4615dfFUpJwhHQrkd73MCy1vUNV0O9mtrdVu4/ljKcqx9s9x/hVnw3Lqslg51RJN+/92XUKxGO4+tXLLVNOup5LWznjZ4s7kUY7849efSrkpcQuYgDIFO0HoTjiuKct48trhFbO9zkf+ECtv+E0/wCEi+1z/wCt8/7PtH38Yzuz09sfjWjP4XtZ9dGpu8pywcxcYLDpz6cDik8NXOtTyXI1SNwgxtMiBSG7georoD1H1qqlSpGVnLZW+Q0ozV7Cbj/dP6Vzdt420+68TPoaQziVXaMSkDazrnI657Hn2rpqzotB0uHVn1SOyiW9fO6YDnnqfTJ9azg4K/MvQt36F/cf7p/SsDUvCGl6nqEV5LFLGynLpEQqyc55H+FdDRUxnKLvF2BpPcbuP90/pRuP90/pTqKkY3cf7p/Sjcf7p/SnUUAN3H+6f0o3H+6f0p1FADdx/un9KNx/un9KdRQA3cf7p/SqMukafPqUeoSWMbXceNspHIx071oUU02tgsMRjsHyn9KXcf7p/ShPuCnUgG7j/dP6Ubj/AHT+lOooAbuP91v0o3Efwn9KdRQBj6Z4lsdVvJLW3Eu9AWBZQAwHGRzWtuP90/pVKy0XT9PuZbi1tljlk+8QSeOuB6fhV+rny39zYmPNb3hu4/3T+lG4/wB0/pTqKgobnnOw59eKNx/un9KdRQA3cf7p/SoZ7W3uWVp7ZJCvQsoOKsUU02thNJ7lOzsLawL/AGaApv6nOT+pq1uP90/pS/xfhS0Ntu7BJJWQ3cf7p/Sjcf7p/SnUUhjdx/un9KNx/un9KdRQA3cf7p/Sjcf7p/SnUUAN3H+6f0o3H+6f0p1FADdx/un9KNx/un9KdRQA3cf7p/Sjcf7p/SnUUAMZjtPynp7Uqsdo+U9Palb7p+lC/dH0oATcf7p/Sjcf7p/SnUUAN3H+6f0o3H+6f0p1FADdx/un9KNx/un9KdRQA3cf7p/Sjcf7p/SnUUAN3H+6f0o3H+6f0p1FADdx/un9KNx/un9KdRQA3cf7p/SkDHcflP6U+kH3jQAm4/3T+lG4/wB0/pTqKAG7j/dP6Ubj/dP6U6igBu4/3T+lG4/3T+lOooAbuP8AdP6Ubj/dP6U6igBu4/3T+lG4/wB0/pTqKAG7j/dP6Ubj/dP6U6igBu4/3T+lI7Hb909vSn01/u/iKADcf7p/Sjcf7p/SnUUAN3H+6f0o3H+6f0p1FADdx/un9KNx/un9KdRQA3cf7p/Sjcf7p/SnUUAN3H+6f0pw5HTFFFABWL4tRpPCmooqlmMJAAGSeRW1WP4rGfC+oj/pkf5itKXxr1RMvhZ4m9u8b7XRlb0YYNIsDOwVVLMegAyTVwxZNHlV9Dc87mPUfAETw+Fo0dGVvOk4YYPWk1rxNf6JfSNPYQNZFJfJUTHzpNke8vjGAmcJ6gkHvin+AxjwxGP+msn86S68JzXur6ldXGqF7e/hMDRfZ13xR7cBUfPADfP05PXtjwK/8WXqehD4UaWi6hdXgu7e/igjvLOYRS+QxZGyiuCMgHo4HPcGtWs3R9Lk06O4e5uzd3dzL5s03lhAxCqoAUdAFUfrWlWJYUUUUAFcpfaFqp8R3mpWsGkXKXEcca/bg5aMKDkDAOASc11dFAGJ4Y0m60exuYrr7MrTXTzrHa58uMNj5VBHHOT+NbdFFABRRRQAUUUUAFZ2v3V7Y6BfXWm2/wBovYoWeGLGdzAccd/p3rRqG8uorGynu5yRDBG0rkDOFUZP6CqjutLgfIviSWS/uppru3NvqE0gkk2xeUrZzklexJ9ODWzZwzW/gu3iWKONDduJZFBzcEAEZPcJnGP9qt3x/wCLtA8ZQQ3lva3NrqVqSqiWJWEsZxjLA8EckA+prkX1O8l0mKEOxSAkRpk4XPJIHuepr6uDlOEbq3kYsniW0Mqpcz+SpOPMEZfb/wABHJr0Lwpq2oeGdUsNLtdThudNuJo5SyJ+7ZZAvPI3Aj+Yrxy1uZ/Mf7ckjp/Dj5SG9q98tILPV/h5Y6/4e0YrqFqiQxKRvZQhwWC9HI5IyP5Vji0opKWqenS1+gLyPVqK5/wbdazd+HYpdcjZLsuwG9NjMnYsOx610FfNTjyycexsgoooqQCmr/F9adTV/i+tAHBfFgadfeG00m8luI5ppBNA0KhtpTuwJGV5x6/lXkNnbrpWmxxszSmPqemSTn8Otd58ctO1iaPS7+0MjWUG9JBHwUkYjaT3IOMfh71wscu+xBYEyeXlkYYJOK+gwatQVnuc9W9xkTCVtyqQM9OuKW4thcoIy20E8tjO33xVa1llljbChcHtxV6N2MbEgEopY++K63oZvQ0fDeta54LumtTCt9plwBJJEAZInTB3Mp6KfXPpyKxL62/tGO71CC2WBBOCyR8Rx792FUfgfpiu+03x/oNj4Il0qW1vIZJhJCRGRKSHXmTJwO/Spfhrb6SlzqNjdzR3q3USlFMJMciJls/NznnpjtXL7Rw5qjjZ/mbdjhtI0syXWn+bJKEkkQDyx85G7GVz3zXSal8M7zTNUmvh4gthqzyiWxgE4SW4fdycsQQ2PTPPevQvDPivRNb1Eafbaelq1uhNruVeVHXbj7p74qr4s+GsfijxNa6udSkt1jVEliEe4kKxI2nPynn39a55YuSqWn7unqOMepr+BbXXbTw4kXiCR3u/MYoJH3usfGAx7nr+GK6WiivInLmk5dzUyNN8OWWl30l1AZC7ghQxyEB5OK16KKJScndsSioqyCkPUfWlpD1H1qRi0UUUAFFFFABRRRQAUUUUAFFFFAHIeIbzxND4itItMhdrMhfuxhlY5+bee3H0rr6KKuU+ZJWtYSVmFFFFQMan3BTqan3BTqACiiigAooooAKKKKACiiigAooooAKKKKAE/i/ClpP4vwpaACiiigAooooAKKKKACiiigAooooAKKKKAEb7p+lC/dH0ob7p+lC/dH0oAWiiigAooooAKKKKACiiigAooooAKKKKACkH3jS0g+8aAFooooAKKKKACiiigAooooAKKKKACiiigApr/d/EU6mv938RQA6iiigAooooAKKKKACiiigAooooAKyfEwz4bvx/0y/qK1qzfEGP7BvMruHl9M4zV0/jXqRP4WeS+VR5VXnjVmyqbR6Ak0ixgMCV3D0zjNe9c8jmO98Ert8OIP8Apq/8625L21hnMMtxEkoiaYozgEICAW+gyOayvCW3+wk2oFHmPwCT3rJ8TaFLdalfz2VnumudHnheQD/WNuj2xkn1AbA6cmvDrfxJep61L4EdRYajZ6pai6sbmK4gJIDxtkZHUVarD8O+ZPPq1+bee3hu7oSRR3ERjfAijQkqeRllPX0zW5WRoFFFFABRRRQAUUUUAFFFFABRRRQAU10WSNkdQyMCGVhkEehp1IxCqWYgADJJ7UAfJvjOxs9F8aalp9ncRvFHO20RqQI8nOznuvTjjisZ76SJN0b5J9q6X4hRaHd+LbzVNH1iG+ju5WkkREZTE3APJGGBOSCK5ixxFfqJrSO6hPBSTcFPHXKkEEdevavsaTvTTe9jJmhaOb2zDXCq4ycZ4r2bV/idaeCrLQtLsdNS4U2UUsyiQRmJSB8u0A/OeuD6j1rxXT4bmLWLc27KgEqlS33FGe+eMCunbWrGT4jSazBDLJaLfG4USKGZlzk8HgZ5wO2R6Vz16MaklzK6V2JOx9MRSCaFJAGUOoYBhgjI70+orW4ju7SG5iJMcyLIhIwcEZFS18uzYKKKKQBTV/i+tOpq/wAX1oA8i+J3jEjXh4Xk0/Fqginkuix3jP8AEi9CAMjnqc9K4FpIS5+zszLngsMH8u1ez/E/RxqPhn7SvlB7WQSMzABivIIB+pBx3xXzxBqzfa5IdnlYJw+7kY4wa+hwPLOl7q23MJq7OhSQS/6tgxHUDtSySvAztC22QcjgYHfv/Ws7T3WGYsSTuGBitAgPOBIqlJBt5HBB4zXW1Yzaszd0pJNf8O2loos5riO7kEMOxUkZWVcnOADznvn8q9d8OeFLHR44Lo2sa6j5ISRkJKg452joPwrh/B3gHUF+wXs0iwWkciyqkmTKwB3D2GT6816rctKlrK0CB5ghKKehbHA/OvFxlVN8kHobQXVnGWHw+Fl40bWlvF+zLI00cCx4IZgeM9MDJrrdT1CHStMub+cMYoIy7BRknHYVy/gfUvE1/NejXYJFiTGxpIfLIfJyoHcf5zXYSxRzxPFKivG4KsrDIIPUEVy1nLnSqO9uxcbW0MPwt4pg8T208kVvJBJA4V0cg9RkEEfjW/VPTtKsdJtzBYWsVvGW3FYxjJ9TVyspuLk+RWQ1e2oUUUVAwpD1H1paQ9R9aAFooooAKKKKACiiigAooooAKKKKACiiigAooooAan3BTqan3BTqACiiigAooooAKKKKACiiigAooooAKKKKAE/i/ClpP4vwpaACiiigAooooAKKKKACiiigAooooAKKKKAEb7p+lC/dH0ob7p+lC/dH0oAWiiigAooooAKKKKACiiigAooooAKKKKACkH3jS0g+8aAFooooAKKKKACiiigAooooAKKKKACiiigApr/d/EU6mv8Ad/EUAOooooAKKKKACiiigAooooAKKKKACs7XRnQ7sf8ATOtGqmpwPc6bPDGu53XAGetXB2kiKnwOx5v5XtR5XtW7/wAI/qH/AD7/APj4/wAaP+Ef1D/n3/8AHx/jXre1h3PE9nU/lZueFl26Ig/6aN/Otqs7RLWWz05Ypk2uGY4znvWjXlVXebaPZopqmrhRRRWZqFFFFABRRRQAUUUUAFFFFABRRRQAVjeK9Gm8Q+FtR0m3ujazXUJjWYZ49jjscYPsTWzVHWdTTRtFvdTkieVLWF5iidWCjOBVwbUk47gfP+ufCceEPAlxqN/eefq5uESJLckxBT1XkZJwCc8dK88VpkAUghh7c11njHx9e+LtRhnkV7aCFAEtkmLIGyTu6DJOR+VcxeX2bkFhiN+mTjAr6ygqvL+91b/qxk/IvWkjI3lkg884OcV6L8MZPD2pak2lX2k213NcMXjuvvEFRnaR6YBPv37V5ZNZXWka1Np9+jR4+Rx/ssOGH4EGvVvgpLplj4kv7FIHnuZ0LQ3bKBtROCpXnbnOc57AVli0lRlJdugLc91VQqhVACgYAA6UtFFfKmoUUUUAFNX+L606mr/F9aAPK/i74zTTVTQEtFmkmjWd5Gcrsw3ygDuTg14jPfm4G6aEB92QyDbkd8+teu/HdLArpjkOuoKkhDBPlaPI4J9dxGPx9a8a00XE8yKQZYQ3zBuQP8K+mwEYqgpJGUtzpbFIDEh2kYUEFjj86nW4ghvILi6EktoJFDrEwDFc8gZ71g/2vEbx7REbIJXd2JH/AOquv0ebSbfRNVS/083VwbLz7ZiSNkgYADjpksOfYjvW1ROKu0Z21PdfD3ifSvEkEjabMzGLAeORCrLnpwfofyraryT4LfaG0bWbr7IDKHVIpW48whSdmO2CRz/te1dh4Q1LX7+e7XV4GWNMbWeLy8N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\n", "text/plain": [ "" ] @@ -1297,7 +1301,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 26, "id": "7e84ead5", "metadata": { "scrolled": false @@ -1305,7 +1309,8 @@ "outputs": [ { "data": { - "image/png": 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\n", 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1/YT2k2iXU6CCEp5d38yhznMYUHAQn5gT04HbnyFpXY5ZiT6nk0gkdejEfQ0AejjxNfXuqtBrt3KTdjIuXI82PIwHJHGweg6dq1LrxFr/AMOVj07S9ZhuY7cieWGAh4ldv4WJ5YEYOR1J9s15I0jucsxJ9zQ0jt95mPbk0AfQWmfEeHxn4Qvp9Ua3s9c09crKiY+0RMcFFPVMnAP/ANc1jan8VZLCWOz0uO0uZ2iVprtolaWSUDgluxQcA9TjNeLpNLEGEcjKGGGCnGR700MVIIJBFAHtnhX4p6493b6VFMDtZpI1kbKMcElHZudmM8+pos/ivqWq68dQ1fVE0+ytGEkSxrhgpOPkQf6wkcHd0HP18WS4mjlWVJXWReVYHkU15Hkcu7FmJJJJ60AfR+p/G+01hYrTSrKYLNlZI3YCSVTwVBB+Tg5DZ7fWrmmfEDwf4Js50ttRm1OSZhvMS7UQ/wAK4PGcZywHbtwB8yCR1XaGIGc8etOknlmKmR2YqNoJPQUAfZul/EbQtWiup4ZJEtoYTOszrw6DG4jHTBOOevavOW+NOp30V+tnaiMNJthkRA7RH+6B0fPB3Hjk+1fPsOo3tvDLDBdzxRTDEiJIVDj0IHXrUcVzPCGEUzoGxuCsRnHI/WgD2q01ONNRGoX2pNBeysHG1vmkkXlmVj91u3Py8HrjB6vQfHHhPWvFeo39tpl3bSfZ2cXijeQ4XDSFAPlbnAY/pk181T3U9zKZJ5pJXIwWdiTj0rV0bxZrfh97h9Lv3t2uI/KlKgHevoc0Ae//AA88e6NZate6dfalLGZHJ3zsBFvBOSST94jknp2561D4/wDiLoup2dnc6Pqk0jQXLI0IUoFIxiT1B/uk8cnpXzrHf3MMryRSFGdWU4HBU9Rj0qITyhGUOwVvvAH7319aAPrjUPiTBbaLpdxaQs0l0MSC5IR124BXjq5J4OMfyqh4f1Cz8J+Jby01K+lEU+DI0gCpG7DcDL/t4OCR8o/l8yNr+qM8Tteys0ShIyTnYAMACoU1S+UyH7TKxk+9vYtn65oA+m77412lt4nFrbWD3OlouXmT/WOD0kQdCufXB/lW9oPxY8Oa5N5DSSWcwJD+fgIvoS/TB7f0yK+QUvbmJt0c7oc5ypxTxqN0pfZKU3j5wvAc+p9TQB9VeP8A4pDwldWcVpDBcRXEZcShwwcHgbcHHHB56/rXI6N4lbULi1v9X06TUkLM8W58PIRkkKeFdAedp+77dK+fWnlcnc7Nnnk1Yk1W+kijiN1KI4htRA2Ao74HbPf1oA+pl1nxN4x0NJNNhiSNZ9rmIgLKrdPvdVXowxz+YrsNK0W18O6VOtosMd00fmSSHLDdg4752A5wPT3r42TxZrsUM0Mep3Ecc+PNCOR5mDkZ/Hmpbjxp4juhJ9o1e6l82JYZN0n3kXoD64oA9hfX7zVpBLrVxel4Ji8ca4z5ecu6ngIwIG0Hn8BXqfgjxBcazBcxyacLWGFgYyoKgA87WBwdw7nGDntXyXJ408RS2s9tLqkrwzsjyIwUhmUYB6dcdT375q1afEXxZY3cd1bazcJOiBN/BLKOgbOcgehoA+1JW2RO25VwpOW6D6+1eAaz4hv9WvXtbnURdFJ28tlbdCTnDbMcjgYXI6598+Z6n8UvGesWs9rfa3LJbT5EkQRVUg9uB09q5y31jUbS8N5b3csVwRjzFbBxjBH0xxigD6/tviF4ft7Zbe4uZYp4oAVSc7nlYDlFb+NweD7n61yej6xqHjPX5NbmvP7MsNMOZSz7TagclDngsw6k8Y/AV83XOtX106vJKNyrtyBjvn8PwqSbxDqc9mto1ywgGdyLwH5z8/8Ae/GgD6Md7nxVHrF3f+JbMaVp8pd5UfzIQe21RzgL6/xdMnNYWo/F+WOCPS7KSWC2TYqzM/8ApO0cKCTwSxwSR0HFeE2mrXtjBPBbzskc6hZFHRgDnH51WaZ3IJPTpQB9bv8AEqFvDAmsp7W61O3VBfcEJbHHzMw6kZ4yOAT1rU0X4jaLrDWMaOyyXKDceqRyHpGT6nr09M4zXx3HqV1FjZJtAUoABwAeop1tq1/ZzNNb3cscjAgsrYPIwfzHFAH2/deIdKtNP+3PfQtAyNIhjcMZAvXaB1x7V5zpOu6LD4sbWZry9jlmYiS3b5jCG4zI4PzR9MAdP+A18zjWdQW2+zi6kEW7eFz0PqPT8KaNWvsk/aZCScnLUAfWV18XNCg8RLp0YeW0HDXiHKsc4+QDlwDwf0zW14p1u5j8HyatoU0c0W3e08WHIj7sg6Ej36c+lfGDX90wYecwBbdxxg+3pWxonjrxN4dtmttJ1i4toGfzGiBDIWPBOCCOe/rQB9JeD4k13WofEN5fvBfZ2SWpbBaTb0Vs8ptw2wdDnsK7nXNKTXNHuLITtEZBtEiHuD0PqMjkV8SjxBqqtCyX06GCQyxbXI8tzyWX0OfSr0XjjxPDbSW8euXqRPKZmVZSPnIwT+NAH2N4Z0+HR9DhtI70XQVmBkDgqGzyqjsAc8VWv/GFhFpGqXmnML6WwUl4o+p9x/eX3GehxXx1N4r12eBYH1O4EKtvEaNsXd03YHGccZptj4l1bTtwt7xwpIO08gYORj0/CgD6p8IXmmfECGHW77TfK1GzcI4GfLl7o3+0O4B6H1GK72NgVxnJHWvjC8+JXiu70+3sRqhtreCTzVW0jWHL/wB5igBJzzzVSTx54pkaRv7cvEaVt0rRyFDIfViOv40AfbMs8MAUzSpGGYIpdgMsegGe9SV8Oah4w8Q6rI8l/q1zcl23kSPld2MAgdAfpVpfiJ4wWN4x4j1La67GzOSSPTNAH2olxBK7pHNG7RttcKwJVuuD6GlmuIbaLzJ5Y4owQNzsFGTwOTXwyniXWo5ZZU1O5WWVg0jrIQzMOjE+o7HqMmrGqeM/EetpLHqWsXd1HKwZ45H+UkDAO3oOKAPt2G5guVZoJo5QjFGKMG2sOoOO9Ks8LySRrKjPGQHUMCVJ6ZHbNfC9r4i1qxgkgtNVvIIpf9YkUzKH4xyAeeDinx+KNcijlRNVugJTucmQksexJ65Hb0oA+6CQASTgDqTSggjIr4YTxZ4hSOaNdb1DZM26VTcMQ575yec/rWi/xH8XvbSW39vXYgkg+zmNWAAj9B6emRzjigD7Wor4eufGvia806GwuNcvpLaFt0aGU/KcYHPXge9Mh8YeI7eeCaPW78SQYERM7HaB6ZoA+3jd2weVDcRB4VDSrvGUHXLeg+tVdU1mw0nSX1K6uFW2ChlZTnfnoF9Sa+KJ/FWu3Ooy38uqXJuZs+Y4fG8E5IIHBGQOOnFJP4o1y5006dPqlzJZ7dvks+VA3bsAdhnmgD7a0nV7HXNMh1HTrhZ7aYZV1/UH0IPBFYuueP8AQdAuJbe8uHM0a/djXILf3Aem7HOPSvj7TvE+uaQ8bafq15beXu2iKUqBu+9x05wM/So73xBq+ouWvdQuJ2IXJkfPQYB+uO/WgD7h0vVLPWdNg1CwnWa1nXcjr3/wI6EVcr4Zi8W+IILVLaDV7uKCNXVY45CqgPw3A9afaeMvEtjj7Nr2ox4QoMXDHCkYwMn0oA+4HljjKh3VS52qGONx9B6mnblAySMetfCMmu6vLNFNJql40sQxG5nYsnfg5460HXdXa3S3bU7wwoSyxmdioJOScZx15oA+7simTXENvDJNNKkccYLO7HAUdcn0r4Vn8QazcsrT6tfSFehe4c47evufzoTXtXjE+zVLwfaMed+/b95jpu55xQB9xRavp09ytvFfW0kzLvWNJQSRxzj8RVpXVs7WBwcHB6Gvgdbq4QkrPKpY5JDkZPrViPWNTiBEeo3aBmDHbOwyR0PXrQB95U1nVELMwVVGSScACvhdvE2vNu3a1qJ3KVObp+QcZHX2H5VA+tarIkiPqV4yynMgadiHPvzzQB91zXEMHlvNNHGrHapdgASegGaSa8trd1Sa4ijd/uq7hSfpmvhGTUr6aNY5by4kRcbVeViBjpgE0k+oXtyxae7nlJxkySFs46dTQB93T31pbCYz3MUYhj82Xc4GxOfmPoODz7VS0PxFpniK2kn024Egiba6kYZe4JHoRyPaviB9U1CVpWkvrlzKuyQtKx3rxweeRwOD6U221G9snL2t5cQOerRSlSfyNAH3VqWq2Gj2Ut5qF1HbW8QBeSQ4Az0pDq+nK1upvrcG4QyQ/vB+8QDO4eoxzmvhm51XULxt11fXM5wBmSVm6dOp9z+dRpf3ccTxLcyiN1CMu84Kg5A+lAH3pHNHNGskUiujKGVlOQQehHtUQvrU3kloLiI3EaCR4t43Kp6Ej0r4Yi13VoJI3i1O8jeJSiFJ2BVTngYPA5P5019Z1OSYzPf3JlIKmTzW3EHqM5zQB92SXMEMJmkmjSIDJdmAGOvWi3uYLqCOe3lSWKRdyOhyGHqK+EG1S/aKOJr24aOPJRGlYqueuBnipIdc1a3/ANTqd5H8rL8k7DhuWHXv3oA+7WmjWVYmkUSOCVQnkgdcDvT6+Dm1rVHlglbUbsyW4xC5mbdGM5+U545q8/jLxLJpkenPrl+1pG25IjO2Ac5+vegD7h8xCWAYZUgEZ6GmQ3ENwHaGVJFVihKMGAYdRx3FfCg1zVlLkanegu4dz57fMw4BPPJHY0W+t6raJIltqV3CsvEgjmZQ3Trg89BQB94U1ZEdmVXVmU4YA5IPvXwufE+vNbfZzrN+YcY2G4fGM5x19eajs/EGsWEzzWmqXkEjnLMkzAsfU89aAPu3IzjPPpRkZx3r4XuPE+vXU8k0+s6hJLKnlyO1y+WX+6Tnke1Ng8Sa5bNI0Or3yNKhjci4bLLnODz680AfdLSIihmdVUkDJOBk8ClyM4718IDW9VCqv9pXe1SCAZmwCORgZqW78Sa5fXAuLrWL+aYLtDyXDkgemc0AfddNMiBlUuu5s7Rnk464r4f/AOE08TiZph4g1ISNGIiwuXBKDgDrVBdZ1NJBIuoXQkAIDiZsgHrg54zQB94ZFMe4hjgad5UWFAS0hYBQB1JNfDNx4m127jjjuNYv5Uj+4HuGO36c00+I9aNvHb/2reeRGMLEJmCjnPTOOvNAH3SJY2RXEilGxtYEYOemKcWVcZIGTgZ9a+DYtW1GBkaK+uEKZ2ESn5fp6VNP4g1m6hiiuNWvpY4X8yNZLh2CN0yMng8UAfdafcH0p1fL3wW8Wa5c/EGx0651G4uLeWJ0YTSliFVSwAznjPP9a+oMn0oAWikyfSjJ9KAFopMn0oB9qAFooooAKKKKACiiigAooooAzNeuYodKuIWuTby3EUkcUg3DDbGOcgEjABOfauU8FNaf2rtiSx80W53PBcXLseVzxKoGPxzXX627xaFqEkc5t5FtpGWYKSUIU/NgcnHWuY8LWl4mtC4/tX7XZNbFlD6k85JbYR8h6bcMN3cEcCgDrrm+tLNolubmKFpW2xh3A3H0H+e9RnVtPUXBN7B/o7BZvnHyE8YPpzWJ4gtrw6vHPAs7Brfy41jiDq0m8HbJkHCkd+OnXIFV7TTpJiY54LqH7JbuskiJhnk8zcNhIw2QCe/3/WgDrEmjlZgjqxXG7BzjIyP0Ip9YOhLe211JaTQbYQgctsPDELgbujcEr7bB61uYb+9+lADqKbhv736UYb+9+lADqr36htOuVaJpVMTAxqoYvweADwc+hqbDf3v0psjCKNpJJQiKCWZsAADuTQB8KapbtBrNzA0LQkSsNjDBUZ7jtTYbaa4trib7PM9vbAF3RSQmTgZPRQTXTeObiLVvHWq3NuyiN7mR0IJwwzjcC3PPXB/Diude81C1E9izuiuwMkQ4BOOCR34P60AJJYRHRE1BJCHMxiaM9+M5X1AHX6iqfkOCgZSpfG0EdQe4q7Fa3U8UQjQsq5OD0Hv6YroJrRNcksXuZobfc4QPHFjMfdzjrtPA/LtQByslnMlz5KoWYnAwOtL9huNgfZlCdu7PAPv6V2ulCfw/q2pW8htLprmFrcK0YdJlOMkHsAPmB45HsRU134O1CLwvFqenXMdyjXXlNB0lXP8Aq3IPUNg9OOB74AOHj0u8llWJIHMjttRQOWPtUSWVxLvMUTSBAS20ZwB1J9B716Hp/gfxf4p1e0toLXy4mVS91jbGiqcZdh1YHPyjnj8aNS8Far4c1rULdoZp50TIVUx5xP3cD+NSMscfT1oA86NtMC/7tiEbaxAyAfTNWE0jUJIVmWzmMbkhG2HD4649cd66PR9EI0uW5uryS2jlZQsQQnKZ/wBYw6HByAOuTxWumralptpFbxXhu9PhlPl5/wBUhwN/+5xxjpk557gHns1tNbTPDPG0cqHDI4wyn0I7VYi0m+mVXW2k8tiAJCpCc+rdBXp3izwpb6trNg2nJLam8hiKrena0UjjISRj9/jG1vcA+2E/iLW9K0OfwtfzTRQ2915ixuuCsqnnI7qDyF9eaAOU1fw/qeiXKwX9nNA7qHQOhG5T0I+tRDR7/wC1y2r20kc0QJlWQbTGAM/Nnp/XIr3n4V+KNL1awk0zxDJ5/wBg/wBKtZLld4Xb95s9RyRhTx6eldF40hfXrt1hsbI6beQKy6gcRiQj7rPL/CVYgBD1z+QB8vPZXCPIpibMeN/H3c9K0o/CmtTWLXkVhM9uu7MioSvy/e5HpkfmPWvU9F8AweH5r2+1W+SO4gheSCyuGEckg6Ek9OcnA6sBx1zTvCWp3tzplzp2lXLwRyArKDiPMQH33H8IwTlup4HsQDxo6fcBNwTdjGdvOCeg/GoDFIM5RhjrkV7VBpltpF7P/Zk9hfpdhozNCgYRI2MiNTzG+7HJ9ePZvjbwfrF7f6RAZNOWAWZYQRTACMLkuWOfvtySQeTkDpQB4wkMko/dxs3OPlGeafDZ3FxcLBFC7Ss4QKBzuJwB9c17B4Dm0vw5cXsMiOgv4HRrlU3S28WCUkXHBOeoHPHsc5+g2fhQan5OvX9wt61yPmt0VoxGerOSeGPHAzj36UAcV/wgfin7b9kGh3pmMZlCiE8oP4vpUd14R1Sy06K+uYhFFNIY4i+R5hHXb6gZGcV9javrml+F9BGoXlzttI1WOM53NIcfKoJ5JOP5muDfTvD/AMWryG6jkurf7FgqmOJIsnGCP9Wd2QR1x+YAPm7XfDd94evRa3nlM5VW3RNuXkZxnHUZ5HaqcumXkCI8tu6LIMruGM19LWXgh9f1HU7bULm0gvrMBIjGqyGPIxwnTy9uAM/MCPrnFufA3h/Sr1R4q1RredgFURt5ixheEkkY9ATwBjp6c4APGG8HapH4dtNbmVI7W8kaK3Vjh3K9Tj+7159qyPsM63cdtIjJI5AAYY69K+xr7wZ4YbwzaW96UGnWKeYJmcAFPvNuPTaevH4YrgtU+H1l8RPFi6pYajZnTIiqGa1UD5ABiPZ13Ds/TH0xQB883Gmz215NauAZIiQdoPOOvbP50+DSbi5QeV80hbZ5eOSeuPyr6y8UaGdHnttW0TRYbjUXAt5714vOlK4AAYHru6F+uPrkeS+KdLs7bXIbLTNNltHQlWCvtEJ6uiMBnGScFuo/CgDymLSXbVo9PlkRHZwjFfm2k9jjv7U280w2k0kPnJI8bEHb049/WvcPDPhG38I397rGq6M14IkEVuXA8oM33ORlWBHJftx3Ip154ddteXxDofhaMWVxEPke382NB91n2nhnJ47jB3d8gA8at/CuozQ2sz+XBFcqWV5WwFA/vemRyPUV0Mnwi8SxxRXP+hvp8yCSO+jnDQ7fUsOnHt7DJ4r0DxfJB46vF0vSrDytYjjXzY4WxHLIo6rjqEAwD0PT0Nd1oFinhf4UG31uwaSMbi0RB3SFjwzZ/wBXyf8AgOAevFAHzLqPhTUdPnaPakqiIzBkYfdBwcjsR3B571BbeH7u502W+UxiKNtuC3zM390Dua9k0TwPqesa7HMtvIdLuWJaRzlSw4Lk9Mr0A6N+eKGk/DzWLjXNT0YWDpDbZDBzsVkzkKG/ut94Hrxj1oA8w0jwpqetxebaRr5KyiF5pGCRo7fdBY9M8/lWrN8ONVttdg0ee4tI7yWPdsaTG18ZEZ7Bjxjtz1r0TVbSLwfrVvol5YXc8aqpa4gXazJ38tfusOcFm578dKr6x4d1bW9VGv2enNJaRARhQpdAIwAFbHZF/iGc/XIAB5tH4M1Fo7p5dsBtzgrKCDnOCD6YPGT3qZfBhfSILpdSt2uHkZJoVyfs2Dhd5/2j0xnjFe323w8fxD4EeW0muYr1+EE7fu5kH3sd9rHkFumPxrN8P+Ao/C/jOz02+s31GOWLByv3tw5I7MsfqcHPPHGQDzSD4Wao+hSavNeWkNuHESIzEyNIc5Uj+HGM5JHBBquvw9nk0KPUYdStbiWR9n2WBtzxnJADnoM4PTIGOeor17xn4D8TLPJpuiFpdIukxsBJ3kc7JR+Gd/rj6VynhzwZr1x4evYNOgla7EgRg2AUB42EnhWyOe4GDQBwi+A76cI1rKs64bzNqndGV+9kdxweR6c4q7ZfDO+1G0kvba9t/sETL5t05wkat0J9cAHIGTnAHUV0moJrXguCAatbMgn3ReWp2hFz864HVTxhuhIPWpNc0VrNLTUbTVpU0u9UzFG/dPGQcOpUfL16MOtAHEyeEYLS/uPtGoiWwhIZJoV2tcRk4VkU/wAuop2r+EbPT9GsL2DUzM92zkL5fHljAD8HOM7hyByD9a6+Pw/H4nvrXw7ExsZId2ZWjZhvI3DIHO8jv0x29YtD8Py3N2kk12G0rTAXLZDlAWxs29Cxcg88DqehoAz/APhVU114aXVrC93/AGVtmoqygqhOCGjI+8MEAjqOvINUbL4U+I7y1mvPKhW1hYB5PMHIPQr/AHvoOc8da7DFv4f8J30Auria71GQKYwCsVqFfIZm/icnPzLnH1JrmdVtdWuLqwhtbi7aERmVRg7sj74X+8w69s9fegDmtR8NPa6l9jtZXuGzjPl4yMZJHsK6nQfhLd6xpmo38upQ2tvZQ+cZXjJVhjO3/ZIA59OK1PCeo6datqbR3Vw+qsgjtzOgKAZyXducsuBjocnNHiDW/EVrpA06dJY7UMXe32kfZ95z85/5abs556Z96AOS8L+A7nxT/aYttQs4Xs4t8aTSBTOT0VSeB75Pp9RW1LwH4g0yeOGewl810DhNpzjOOn1H49q3bPwjfXYjTS/N3vmQj7wbaCXIHqB0A68966TX9b1SWz0KVb2XztNRdgblo1zxMzDrnA47EYHrQB5vD4caNbxb95IZ4o/3USqCWkJ4Df3RjPv/AEgi0RjbLLKZIzI37vKYDKPvHJ757d+a6XxHpWrXCTeIrS8+3Wks5E8yEbhKeSZB78kHpitzwVrbT6np8UVvbRorqYxeENFERyWJb+Dg8jkHpQBk+LfhnL4el0lbSWe8W8tEnkLRFCpP3gVPK9sDr1q/ofwu0y/muRqmtyadHbQNLKXiBKc7VDehz2744rvte+OegSaxFbw6I2opaylorqTAG7GAyLjOO/PYevTj/GHibT769Gr2s0vnTkvIkPJ83G1sOf8AlmFxjPIPHagDiW8Io2qT2cF9GyR5KzP8qsMdc9j3x1rtU+CT3+jRT6Zq0L6h5Anns5WAaNCMqfqR24xkc1gaHJdswjtLYeRPKAodf3bsMcY7seOe/wCda1j4rsrO7vLKWyvV3EqrrJtaMk5fK9wem0nGM+vABVu/gj4nstGbVZ5LJbYQ+cf33zIOuCPXHYZp2k/Arxhq1iLsR2lrG6b4hcTYaQHpwoOOOea6SPxvbNbw6JeTt/ZyOHiZCC6k8hgD90r/AM8zxg+uCMTSdd17UvEAhttUNlp8Z8tEeZkjKbgSmR3B+bP1+lAFBfgv4lbV30sG1N0i72XzlGV6bhk5I/mKr2Xwo1O8nvI11PTcWsZkLeaQHAOGKkjBAPU8e1dj8RbyHQdesNTsNWnuL+FgbmdFxH5wA3NGehY9COg/MDttburS78NWWoadpKFdaCT3FxCCQJF52L6HOTyMcHr1oA8b0z4O+JdSs5dQP2a102NWcXdzJtVlAJ3BQCcdulTeDfhLc+Kbme3n1W2sJ4kJEEgJkc9iF/u/7WfXivR/h98R7Wzm1Cw1aaGy0mLLI9wfm3M2MDHXdySOgqv4/wBW0HwhqsFz4bJe8MglKQ4aJWxncDzk4wNvTn8KAPLvEPw8l0i48i01O0vZkUtcRRkjyccH5iAGGeMjpg1Z0L4QeJ9elVIYoIY3iMqTzSgIQPpknJ4yB9a7uw8ReD9d0HVJNRitLHWFi82KQkmFXPO2IdQ2eq8gn2GKx/DuvN4S1e11nVpbmWxfMqeWw8xj0ChujZP3k7d/cAxb/wCCviTTJ4obmexaaYZjhglMkjcdlwCRnAJ9/QGqmufCTxBoE1rFeSWYaeIynbLnywDg547eorvtY1aPUtauPFmn6ubiPepWEIRKygcbY/8Apn3OcH3zg22+Lvh7xFJBpHiywRYNu1riMlirno4x0GMZHPPrjFAHAeIfhDqGk6DFrWnalZ6pYuVTfAxBZj/dB7A8cnPesjw38Ntf8VTPHpqQfJEZMyybAQDjA9Tnj8q908JeKfDL6rdeFoEmvbK5Vnkv5V+SVlGWyn8CBQPm45H0NU9T+KPhzwy0qeEdPt7j5gbjahRXPQBT2A6k9PbnNAHlT/BTxstlNdrpoMcWSEMgEjr6hTz+HWrGj/BHxLrmgw6nY3OnN5khTyWmIZQO5OMD6deler3fxt8OXOk+TdWV4z3EJjlt0IBDngqDxxjo30rm/CHxW0vw/I1s+nXDm6kBecyAbF7KQRg7RnkYyfTsAee2fwm16/1eTT7WazneIKWeKXKtk4OzONwU9SOO/Nadz8BvGcMsqRJY3Ij3ZaK4HYZxggHJyMCvWtX8aeH/AA4r6zoFrDcPcMGum5UqM8IF6oWPOcY4zzXnd9d+IdNv21uHVJrfS78Msu6bBdeC6lv4myRhx9OORQBzy/BvxLNo6X1o1rduZvJktreTdJEe27jAOePbvRJ8F/FFsYI7yTTra4uFLQW0lyPNkIx8oAHXn168dSK7DQvGF5pel3cOnW0sl1KqiS5h++iAcRovQuOSW7DPpWl4Zk034i+M7O51PUJBqNtHiaFDlZzGeFQjovQtxyc4oA8yb4SeMDbG6g0uSe2LhEdB8z5OMhD8wGepI4pv/CqfE5lvIlggd7SVIJdkytmRhwq4+8exx0r2rxP8SLjw14kuJpL23vLAq0ccETApxkAEjlX3dT0x+FeeeH9TGs3y4tro5kxG8WNwQnhFU9ZN2MNngevUgGBP8G/GFpAs15a2trEzBA090ijcTgDr6/pz0q1afAvxvdPGDZQQq6lt0swAXBxg989x7U/xH4n8SXuuR2F7fM00Vwyje3Af7pBB6YA247n9fR9c+KWpeGdS06ytrOCOxhgjElu7eY3QZUuCdr+x6Dk+wB5/B8AfGc0kiMLGIxkDc8xw2e6kDn9KxNY+FHifQo5p76K2S0iAxc+ePLcnoqnuxz0+vpXtcnxYtNS03UGuxLY2DoYY5rdg0scuOm77rbucY7D8uN8RWketeH9K0zR9bF8JZTIIogQkTnoI1+8W6gg8Ak9D1AOasfgd4o1TT0vdPudMuIXOARcEHpznK8EHjHt6Vlj4W60fE8nh37Xp51FccCfMeT/CWxw2OduM16A/j3V/h7FBoGnCC5isiBNGR5ixscbotw5BBzz0yTj2wL64Gq6o/jS2nOmQ+fwnmEOk2eUVv4z3J6AfgKAMLX/hD4p8M6YdR1KO0W2U4Zo5t+0noCAO/b6isTS/Bup6vOIrQwHPG5n2ruxkJn+8egHrj1r2rRvGa/EmC58N+IJEtRNj7HeIApjmAwFdTwzHk+n04NU9H1HQPDMX2ezkttRvdNnO9myYY1HcHrIS2cN0UnjtkA4Wf4NeIraznlluLD7TDEJ2sklLTqh/iZccD16kVm2vw01i60ifUftFlEluoe4SWXa0SE4Vjxgg+2T7V6n4slEt5Y+NfDk8wUyEzxM2TBc8fJgZO5x8vPy/nirmmeJPDmo+GL7StdaDTTeT53Qx4eKQ8/OgzgKeBngjtxmgDy7Svg74l1y1gudLk0+5ikyHIn2+SRzhwR3zxjNMu/hJr9hriaVeXOnQyugYSGclFJ+6rED5STxz9enNe0eFNQ0j4aqdEv8AVjKJ5AymBfMjVjjDE9csCGIHAAHc13+oWOhzGHXr027Lax+al0xG0JjIJPRgOo/SgD5kufgZ4zswZLiOwjgVWeSdrobIwO54z+nasZ/hpr/9lrqFusFxCrbbhUfDWxJ4Lg9FI5DDI9cYNew+OvipDc6jHpGnXGNPk27514M2fQ9lU8EEZPPpg9VDq+leH/D8ul6ZdWMuoG1815Sv7mVyMkbjnJ25IU+gHHSgD5usfh9rN0YfPNvZJK2Fe5YqAOm44BIXPG7p+ANaWo/B/wAW6Tpcmo31tbw28chRiZxwP757Bfc13V74zu9eudJiZVku7FyxZogJducqWUAhwMZKAenGel22+Kmpar4mGl6sttHp8r+TLBJEDEVbhgx5ONvIPv37AHmnhz4Waz4s08XOjXdhNIrlZoHlMbxDPytyOVPJBHpW9bfs+eMpbpY5n06CLvKZywH4AZzXd+Mnj8C6fFo/gi4jiu7tjNcOHDS4/gBY/wAGDgAdOD35Twh8U7+20y20m/IvtTST7j5EnlcfJ/tPk8e3X1oA88l+AvjaFdxt7R8vsCxzhiffpwPc1bm/Z68YxwK8cumyyFiCizkYGBg5I+o/Cu71v4h+IfDd9d2uoXAjZ5FLMIw5hJAICL/dIxnOcfU1gaj8afEN3OsduYLWJtsp8sAnaOysex6nP06ZoA4rXPhB4g8Psq3tzpxZ+VWKYsxUdWxt4A96r6l8J/FOkwR3F5b26W8iB0lE6sDnovHfHP0r0B/iymsarBHrGm29yqOuEdCiwsOwYckOOx4zj0rqfiV488PNpMGnrKHvCVdjGA0lmCPbjcfukcgc5oA8Ls/AN7e3UVsmpacsskgGWlOxUPSQsBjaTx/9bmuku/gH41tlZljsrhQ2P3M+SR64IHFS6d47ih1i2uYtIsbYQyCQBE+QY4KnJOVAy20dGJIro9Y+NWrXGranbW5S2sZE8u3OMMg6q27rucZGOMZ9RQByF98D/FWmRTT3smnQ28UauZTOSrE8bBxktnjGKrad8G/FeqwQTWcdpKku4FhPxEy9Vfj5T0475r2CLxPbRfCuVDqVrdXUiDNrcHc1sjcbfVmXGfbr0xmj8MvHgm0+80nVbmGzt0R/KuY2CurfxfnkEHkk8UAR/Cf4Ta/4T8VSavqN/apBHG0QjtX8zzyeoJI+UAj65Fe4Vxfw/s7O1tr8WWuxaj+9w6wt8qejEH+JhyT0OPauyw3979KAHUU3Df3v0ow3979KAHUU3Df3v0pQCOpzQAtFFFABRRRQAUUUUAFFFFAHP+JotVmk0yPS1Rw1wy3CzAmExmN+JAOozj8cUzQtGvLC/M0+naBboYyu+wtykmcjjJ7f/Wro6KACiiigAoopMD0FAC0UmB6CjA9BQAtNkjSWNo5EV0YEMrDIIPYilwPQUYHoKAPmHx1o9zpGs3V7/Y0FnCshWN51LIp52oSeJSV5X0/CsHw5oV3fz3Dz6bLeXQj82MspkESt/wAtHx98E8YzxnPOMV9N+K/CNh4v0YWV2WjkjcyQTp96J+mfcdiKxfh9oV/4WS5sLxbeC0MmIQSN0sgGSynrtxzg89enNAHCeGksovCGt6d4i0AoryIFSJcPHJ0VGc/dIOWA6AE+uDyutDRrfTrq2tNLjt1274pZ3O6LHqw4fdzhQMDPp19s8Ttd+ItIVfDUttdW7TmO7WMrljwBnPG319RjHFV774Z6Jr8Mr3Mm2ZkAItGAjhuAMM6D8MbTx7UAedfDvw94c1iB77xGjmWKP7QpZ/3ZhGB85HftjuCO4rsfB+r+GtU1fU/DFvpsSQTIZVVn3OUBwA2emM5UL90fnR4a8CT6Zb3+jal5MOnSuoSUMA8sw5R4z9OoPft1Nc74E8MWn/C07i4AkaK0MkkZdSBI4O3ftHKNycg8Ht7AHq8+veHvDtxa6PNfWtnIU/cwE4wo7nsB9etcK+var4z8WWr6CixQ2hLRXBAzGCcFpPYgEBO/6it8XfBumSoutxrP9tmkVHhQ4WUgdSx4UgD6HGKt+DNC/wCER0V/E93fSzxS24leOOIq8rN/z0zx8vAB4Hfp1ANT4iT6Rp/h+e3XSLK+vmbzRCwCKrkY8x8cgHGB6kAV5p4Z0htG8NXs+u2dzbSaltFtldjeWhDMzoeCucdeW/WvUPDmjaZ4g1N/EuJhvdhJaS/Mqy9G+b+NemB0B+mBa8ear4eh0w6bq0SXc8+DDbA4O7s27on1PXB4PSgClB4J0fX/AA3pT22omcwqfLvFXduRzl0Cn7o9B/D+edDV/CHg68uoLXUrS2N/PEIYZHb9+wQcEMeSQO/f3qfwbb6bYeFkvLeSQRTAzzS3PynPQk9gBjtwetRNoeheLNQtdet7lpEQgOqEgSFDlQQeVweeMZoAkj+H/hmz0u6s7PTYrVJ1XfLGfnyv3W3HuDz7nrVU+FdF1rwtb2Wl3x8mCVnWeNvMDSdHLL0JPP07cVueJbC51Lw5fWdmYxPNEUG/uD1GexIzg9jWR8P/AA1ceHdBaO+Ja7nfexY5ZVAwqtjgkDuP1oA4pfDOheMdZFrZC7tGsgB+/wAyLMq4QuwPKyDoM8e3BA35/hFov22M2jPb2TKPPjBJkZh0Kv2z3rvYrS3glmligjSSZt0rKoBc4xknvxUuB6CgDyHR/g19i1u8W4upGsHRgsofDSA/dXaOm08knr+Jxu2nwq04Wzre3czzSZ3iA7I89FIX2x9D3r0HaPQVy9l4Z1C28ZXOryamz20inEf8TA9EYdNq9Rjn9cgHKy/Bu3S2tvsuo+TcRu0rSeX8qP1BjGfl6AHOfXtVDTfghE0qX19fNDc72ZUj+fye42t3O7kk+uPevSvE2k3Gs6HNZ2lx5Er4PosgH8DEcgH2/wDrVPoenTaXo1tZ3Ny11LEuGkb+Q74HQZ54oA8e1zS2n0//AIRUyy3V6lyWBhztiJHzRxbuSxGGJPA5xzyfRrOA+CvAgaDSoBcwRBpYrUYXd0LMepAHJPsa6L+zbL+0f7Q+yxfbDH5fnbfm2+mapeJNHl1vRJrK3uDbyPgg/wAL4/hbvtPfH/1qAPLvCHibT1+Isdu2kXcU92hCOCSqSN8zOq9TE3UMc4+nNdR4uXw1r/iK10a/jlS/jIEd3Gv+rkP3VI/iB9wQDXUaFoMek2Fqk7Lc3kEXlfaWQbghOdinrsHYe1ZTeDZH8ep4ja9yqJhQR844x5YPTZ39f50AQ+MPDGkv8PpdLmuJrWytUDI65c7geNw/iyT09fTFZvwus/DWl2L2ekTyvqGM3KXLDzV9uONuTnj1Ga9CeKOWNo5EV0YFWVhkEHsa8917w2vhaeLVfDunsX34CKvmJbk9WVOpLdOuBk+vABY8eeLrC3S68PxXFwL9oQ7/AGcZK5+6jDqQ3Q45AOazdB0+XXvhzdxGCR9Qj+WORSAsuzlEVjyyLnGD7+2OisfCGmrrMXii/thBfCPzWiZwyQSEfOwb6fgOa6faqWx+zRxn5SY1HCk9unagDzbw9Fcar4NuPC1xdC2virNGsvBmjzllKHlVzlcDtz9ew0zRdQsPCQ0sakVvBEVjnC7hDnoq56hegzzXNeE/Dt/d+Jb3WtctGilWXdGp+VfN6EqO6gYAOefeug8X6Pqmr2MEel3YgKShnTcU3ejbhz8p5x3/ACoAz/BfhiHwqskt+9qmoXsmxBuyQBzsVjycnLYFUPFWn+KPEOutpMaLFpZAbLDMMiernqWz/D9PrWVeCfXvEMiahBf/APEph/etCn7yQJznbnCM55BXt9MjMsPHN5oEl1reptPcRXU/lLEDlJcYOQcYBVeNo6nrxQB67o+nDSNHtdPEzzC3jEYd+pA/kOwHpXnHjd/Hnh27vdZ0ZjeQvhflXfsT+ECL1B/iHr78W/HfiOa9sNKttIWcx36pPlcp5yHoikc7gcEgenvXd2iT6fo0f2yV7y4ghzJIkfzSEDnA9aAPNJfEPi298G6Xq2owQadKJtkjMoDSE8KxUjITqGUcnr0r1HTooodOt44VgWMRrtFuMR9P4R6V5boWl3PjvW9QvNRuJ47WN8oUbJ5ztQcbVKjg49a67Xdfg8Gxabp9ppjPCw2qBwoUcbVPO5+elAHWYwuFwMDA9q4SC5vfBt1qGp+JdWV7SeUJCg+ZpnJGGVf4MDjaOOPYZ4fT/iH4lsfHl6dYglNnuZTbbdoRV7KD0IzkE/e/Hifx1r0PjLwnPMml3Ky2k6mBxnaqPwd/GFfA6e/fkEA9NuPGvh611GwspNTh86/UNBg5GD0LHouTwM9TW8qImdqqu45OBjJ9a8Ze10eHRvDHiLUPDzm8WNUWIsUikSP7hkBHL4GVHf6Cu6it/Ek/i+K/E2zSHiDeXIMbUI+4U6+Znnd/+qgDZ1nw3pOv+T/admlx5RyobuP7p9R7V5Z4y8Na7Jp10b9Ea1t5QLSSMAx2/GAyoPuptwpHrg9snsIvFF94lTV9O0m2a0u4lJhlcZ4BwVb+455x1/SqvgzxJq8uqtoGqWpleDcpkzukiA6eYc4Ppnr9eaAMyz8Ja+ngOD7KDBqMqbCoIFxFARgIsp564Y55xxx0rjNU8LSeDNAl0xtS8/U7uVHu0iUmCOLkKzDqzZOR/Kug1HxB45vfiZeaZp+YYYQyRRhfkCAZ3c9WYdGPAOOnd7Raj45tm0i9tvI1uxVmt7mZMnA42zgdCc5B9eaANy48C6nrWheH1kuI7K5sYfLwyBvKPaVQBjecDIPHv1zgWdr4m8HXmtStDa7mi3tOxD7AcgSIx5MjHPydCf16n4ba28tidFv7qSa6t8+S03zM8a8H5v4sH9Mda5T4haDNomv/ANtXWoySabcv9wH94G6kH+8APu+nT6gHOx+APEsWgweJ9EngNwzmR1iIV9oP+uYHjcedyf8A1xXW+GdD0+60K5udb1uBdQuHNtHJkFopW6Owbq5yfbHv06G2s9M8ZfDk2XhydrROcLKM5k6kSgfeBzk/h6YrzHT/AA7KlpJpUXnzanFMYw6kO5iXIeNOxG7n1A7nsAdB4B8C+KfCXi65u9R1C0isI1ZpZPMDB4++FPKg4HJ6Ee3Od4q8PT+ItZN54UhF1bTznz4gvlyK54wf7sRA3A/XuMHW8UaXrGga3pWstdqrXEYjltIzvCkKA6Hdw8QX+Hrn866y41vw94P0bdpEKPPeJ9ojQ56H7pcnlVHYH0wPWgCr4F8E6BosOpaZJdw6nqEirHexkfKidQgXuAep659OleP/ABD0W8k1jUJLVLZLC3l8t1sxiCIHp8o5IOME9A2RXp3hLwlqN5rlp4nSX7JC+W2jgFDydif3ZM556Y47V0l9YaF4H0/UNfWzeZ2XbHACDyT/AKtB2Bbnv09sUAeFP4Ke00q3tYreaO/vY0kPnx7ZPm6Dntkdscdecir3hvR4NNtpdPOnxaxqcjKBlS/kAHOYl6SdCS3THHIyD6dHNN8UPCEV5axwQ3EEzRSK33JMgblDcsuMjI7471U0HV9B0jWrnwppssi60UMCarcxbg04H+rA6qB27H37gHl3iW21eLxKZo7eO3NpGpuIbaMARpgAsyj5fmzg9wx5qtewtqMjySzpplncMJJGuCXUd1eR8ZdgcgLjJr1y30uTwDoF/r+oWv2vUnYpa2pfeELfe+b/AGjlj7cDris2bwxd/E3TNI1N7SC2tipiZkXy8AH/AFhX+IdQB2OexyADxhfDBuvKk+2LKs77YSP+WhJwQo657kHGMj1FdN4xsPEOgWNpNLbiBkhVY2jUCRoxwHfH8R6MD6DvXWX2haRaeJ7bwXotjPGAWia/PzSyyMMtknoqDHpnBweav6D8Jdfi1K1k1a6hktUlIeLzC6eWDyCp+8H6gduc0AcB4X0S2+IWhXkM139k1G2UyJGeI5Aq5Z1ycBugIOBjnNJ4Q+IHijwAIdOdEu9Ld2McEvIOcg7G6qM84+tey/8ACn9Ij1yS6t5pIrSb/WxLw6gdERh0X1zk8VxPizwj4QstUk0l9dc6iF+0OsuMBj1WRxyu8YCgDj8RQB5j4n0vWb/WmvXsWhS6Jlh2qFUrk5K9gOD9AD6VrxXS6z4dg0jRrAXWp26kHaNxwvJ2f3lwDk4z26AZ9Di03RfGVvb6HDeXcGoRWwtxN5eI2kQErG6dQqrgbuM/XGcNfAl98Nr3T9SdZJpZJAWaE8ghuIkcfcJ6liMY47GgDzxfCur215Ha6raHT5ZnAX7V+7wM4J56c96l1fz3ZNLnkDQacGRFXkHB/eFT2yec9T19q9j8SeAIfHt/b+J7bU5rSwdWN0smS9uV+/t/vDAwMcDtxxXMaD4P8JpBfLqOoTG6kfZaoi7AE/hkkPIAbgH0oAzrbxno0WgWunRaXDa3CsDNOPmRmUAoiZOVQ8lsdc9eag8M+GdE8Wxaxq2sMljDCPNj+ykAht3KLF1deRg9uM5pmhaXpU2tzWXiK2eOD542NumCVDfNs/uhTjnkntXQyfCLxCl5Jb6MzLaKd5kMmwSgghWRupO3qp4H40AccPHV5plq1lotlbxQyERTNLCryTKv/LNm67PXvnpir2ja/p2hafc39paob+6U7nlw2zI+aNVIxhjwTzkcdzVvxD4Lm0HUBprr5juqpM0abFkbqshznKDoT3I6VBZfDHWZdT0+e6RTpt+QsT52hyTjaQeFOMkHv2z0oA4mbV2v9SN/fR24RSdsMce1AM52KB0Azxk10+sfEn+1Zowmm2gSBFjt2eBWMSj+FRjBB75B55GK9XH7P2hi4ijN3M9ngmUniUn+EA9Mev4+vGZ40+GHgzR9MtLG3kuLa/ZG3TAb9yZ+9IOAADgZXnHY0Aec6ZrXhzT7eW9vLi9udUnGRDDjZDJyNzu33hjjaARjv0xZ1pdR8YNp2nWkBs7GGMrEpU+WFHzHnG4qFy2TxknGOK0tS+Hll4Shs0uoxcXjr5pnlBaFgw4WNR97b1JPXPQDmuk8L6W/xDS5kg10x3NvCIEd1/f+WBwQy4wpOR64/CgDjLP4i3Xhu4h0bQoo5rK2LRI91CrtJuPzEd13d+fQduc3XIrDQootR0XVpob6Zz51tGCDABwR5o4JByNo4I59h3Vz4F0/4b+H59S1lYNQ1a6DQWdqCQg3Dkue+3r25/DEngL4f2c2g3fiDxjCq6dMmbdJBtduwcKPunsMctn0xQByPh7w7ffEW1eGWe2t3hKIlzMRGNx+7FjqxIBbjoR78QS6vq3hu4vvDGj6qlzbrI0C3MSA/NjDGL+JWI+U4PI/A12mt2Ok3Nrb2XgiweSyjVlmaPc8j7uXznlSg6Hv74qax+A51azsL2bUZrORyfPR4wW8rPybB/CSvXOaAOJh8AwweHZPEeqeI4N4IjEFrmWXzTnCk8AYA68jg88Vj2Xhme7tZJbu7js7Io8sdzO5WNuw2d5WY5GB0PXvXr0Xw4a2vLzwp9lnlsr2Pm+YfMgHKyKegAbgp1bPPbGNoXwQ1m+mm0/Xb2S3srRyI2j+dWyc5iB+6COT7++aAPNIdKe8NvosWrRskso2qX+VHxgEjoPQ9677wx/wgfh+4hkn8QXIu7EF5CEJWQg8CEjlMnqDyQO1a1/8BJ9MvpLvSrl7uCM7oofMEcrA9F3dAQed3f278toPwvvJ/EpTWLKdbBifNlx5QUD/AFh3EYUp6nr260AdFoWhaT9p1bxRqOv2UOnXkMsMR80/vWYEMgA+by+RkEbu3ueRtdLna6fQvtMN2bkjyEibcJ8n7iEcISBnPXjPbi/d/DCSa4DaVNLd6Y8hiinhXLF8/Iu3qhx1JGD+VddqvwqvPDPhyzvdCjefWVcGURtkp6GNe7Z6t6ZOO4AOT8T+Ajofkzx6vaLc2iK1zbmbEkWT8qlujY4GV5BI46GsqJbC48Ymx0ScLZ3UXlXF5MfKjBIzKSDyseeNp5z74rpbj4Z+JdR121bXbeRpbt90mwhwWJ/eEMOEGDnnv0rofEPwUex0pYfDxa5dmIbzGCuR/DuPQgc5PXOO1AGB4a8Rad4Gj1bSWmt9Wt54mzGCRGzD7gB/vHPIOCMdiMHCk1LQ472C7vLRSNhaGFZChx3ctyT8wxtOT1IPQhbjwodISE3mj3UrNuWF5FKLOVHzFgePkORjqe3TNM0r4cax4nnWW4eGx08uqLdTMETcfulVPJJ6beO31oAvHxrY+JLqHTb3So8wIY7e6t18uYRjqCMhQFGevVcjIPNW/HOsongqw0XQtdiv7UHz7iGAFVjPVVGeiDGdnXJz7VhePfAP/CCTwRQGe9+0w5MmzCK38SqRySOOD61m+DNG09tVZtWvZ7e7AzDGE/5adVDk8AHgc+v4gAqQabHeaat9c3At5VyYxJn9/wCrL6AcDHft3x0Np8RHt2t4V0eJnERg85DslwRgkD7oYc4YjJBwfWtx/h1eaqsuq3TraafCfLmklJjY89AD1CnsOpIArBg8FXui6iLuB01K0uCyRFk5kPAKlD/y15BC54ODk8UAXXvtDstFJ8P6jJBqbt5mSvlRxq3BKtnKejZ69uOteDUfDs15pttq8Mtu1tzc3UY2grnJCDqTnox6g8DgCrlx8GPG19PJqTrD5k7ZVTIqtzjBZeijsR29KdL4Ov8AS9FtofFMP2SJztjuCoeRVU87ucnH8I9PwoAhnRPE/jeW70uZrh5ZBJHABsMwzhdqj/V8dQfr0Oa6nU4vB3wh1D7fIX1XxK0W+Kz3ARwu3Vyf4RzxnJ9Oua4vR9Kl8N6tb61o+pZjhDOHJweOGcr/AHCp+6f6ZqH/AIRK58W2useJVvpLueB/MkiK5lkU9JG7BR3HoM0Abes/FHSPEdhZTeIvCImvmfBuLeRov3Wf+WZ6l/rxj61gQ+GT4o1+aXw4sjRvysLY3lsZIPYAdz0z+VWPAUE+q+JIbPULeO7sEDSTLc5MKoBhpC3VF25wR3xXofgubQ/BVzd31tqDXtvcuYY4kQBxEDnewPQAdAPvfhgAHl154K1XSM2s5K6gwyIUyJMEbuR1PHXHA/PFvwdpFgJra61+HOnrLtadyVhVf4+RzkcHI4zXR+MoL7xD4gvdc0S6upxtARwpEnknhdgH3Vycdic89TXKWnh3xn4gnj0hYZ54G+cxqwCICQCf9kZAz9KALvjODTofEianoXlnSbgLJbzRpgAgY2gH+IHkk9TVfQ9J8OXNpdQXkt4+pysyxRQgbgO2VP3yx6lfugdzmu3g8KQt4WuPC+hmSTW4JGnNw4ws5A2zIgP3OMAFuuO1Ubn4Zv4b0fSdUvUmivS580RudsYH3BvHKv244P8AMA89tltC0llcySIFfjyyTGg/iDY5/EZ5qB9KjTVEjjlkkIbYjJ0dh2RugwOuf/r11t98L/HNnfpeRaS9xEW81ViK8Z5IKZ+XNXfE0t74ihtmgsLSw1CFRFcTRr5UcpB3B1U/dA6Fu5A7DFAHUfBnwvHD4gudXt9VlSNY9q2zcSSqeu4dCgPQjv6d/dK4H4WeGb3RvD4utYjjOoXHKtnc6RdQpI4688e3pXe4HoKAFopMD0FGB6CgBaKTA9BS4A7UAFFFFABRRRQAUUUUAFFFFABRRRQBha5e3trd2xiM8Vmql7iaOBZAPmUDOTwMbicZP5VQTVNWmj3RybzcxmeNY4gWhUSBSBn73BHX3+lbt9pFrqE0cs/m5UbSEkKh1znawHUZH+cmmwaLaWz3LxeaDOrL/rCfLUkkhP7oySeP6CgCPR9UF+ZFklTzuGESj7q4Aznvk5P0K+tam4eh/I1Ut9MtrW7a4iVlZkCBdx2qMAcDtnaufoKuUAN3D0P5GjcPQ/kadRQA3cPQ/kaNw9D+Rp1MllSCF5pWCxopZmPYDkmgARht6HqexrmPE/g+LxLf2k8t3NHFGCksYBOV6/If4WPQn0+lb2n6hBqELvCsqFG2ukqFGUkAjIPqCD+NXKAMDRvC9hodpdwW0lyWucq0xOHC8hQCBxgHg9e9VPD3hifw3Y36216ZrmfJi8xCI1IB2llHUn+I966qigDzaDwnr/iC3ifXb+aFoJz5asNzbSfmYY4ByPlPYfhWxJpmvW/jWK5smjTTnVfOfb99VABEndn9G7fnnsaKAILmC3vIGguYFmib7ySJuU/gakYRvGY2TchG0qVyCPTFPooAht4YLS3jt7eFYoYxtRETAUegFY2o+E9G1XV11G8tjI+3EkZH7uUj7pdcckdv/rCt+igCrdWdpe2EljcQB7aRNjR7SBj09qqaHolloFm1vaLIS7bpJZOXc+pOOw4rVooAazDaeD+Ro3D0P5GndaKAG7h6H8jRuHofyNOooAbuHofyNG4eh/I06igBu4eh/I0bh6H8jTqKAG7h6H8jRuHofyNOooAbuHofyNG4eh/I06igBu4eh/I1leI7C41bRprO0uXt5pBwwBww7qT1APQkc1oXl3HY2klxKHKJjhFLMSTgAAdTkiqR1y1ElukkdzG8uOHhYeXubau/+7kjAoA4XxFo/ieLw7pmhWrPdIx/eSAFl3ZyIm7iID+I9cdsAG14t0rWtJ+HkFlos9xNLAw88jOSnJOMchQcYA7V21hq1tqLyJB5gKAMN6Fd6nIDLnqpwefar1AHD3OreKLDwRpsxtGk1Jgq3Uhj3snodg67uAfTPNZPg668WXfj3UJdWimgtvL/AHsR5VD/AAJ6epBX8etenUUAefa3r19rupX3h3S4Jradf+WmCrShfvKx6opyNrd/xrA8V+EdVt7CzvL6ZdQgtEXcAhUQHOTwOqnu3U9/UeuiKNZWlEaCRgFZwBkgdAT+JpxAIIIyDQBzdokuueDYfItzpVy0OICI/wDUnGMr3AI6Hg4NT+E9LvdG0RLW/uTNJuLKgyyxD+6GPJHfn1reooA8N8f6x4m0/wAcIljDc2tunMIgTnaT8zp/C7uTypyRivWIoNQ1Hw3FHfslvqbRZ82OPd5UmOGAPRhnt3zitaSGKYoZIkcxtvQsoO1vUeh5qSgDk/C/hd9O02WHWBDdSSTLIEKeYE2nj5mGTzzz0z9aZ4r8M32tT2n2C6SC3Em6eMpgbj/y0wB85wMYPH6119FAFSe3E9m0G7a+0bJDEDsYDhgCMZB5rmtC8NarZaNqVne6tKJLosI3iyxjJ6uC3OW6kdvrzXYUUAeb+FdC8TaHrc2nzMp0yUM0jRZEagjAKHG7zM9c8fpWZeaR4p8IXskPh5ZLsXgwH8v7wGc57BwCTuPU/lXrdFAGL4cW+OlQT6vCg1Fk2s4T5ymcqHI7+oHGazJf+EjTxyjQQRDS3Ub3CfKyAcljjd5gPQdMfjXW0UAee3p8Q2Pi3Uhoei28f2mLd5pTh+P9Zv6bs5GzoTyfWtK2sNV1nwNLaa3ZwXF46nyY7tT82PumTHRvp+PeuwooA5TwFZ6hpvh4Wl/ai3RHIgTZh9vfdjjrnHtVScanZ/ENZLLRohb3KATXAT/WL/Exf+Eg4+X+LjrxjtqKAMDxfo8uv+HZ7GAIZCQ4WROGwegP8JPTNY03gVNY8PW0GsTM2pwphZ0BwAOVR/8AnoB79a7iigDE0jSp9C8OCxtZvtF0iMUabITeecY7LntXI+FvEN9rF7f+GfEtlLKH3rl0wwxywYDovTa309jXf3moWtgYBcShGnlWGJepZicAAf5xVeK/09r5BEmbqZniJWP5iI2IJY/3QeMnjJ460AcKPCmteE7+3Hhp2lt5XCkFcBQD8qyDuuCcsOc/r3K6Lpg1j+2TYQjUzGI2uAh3Eemf69cVp0UAQXUFve2sltcwiWCRdro6ZDCnxLHDEkUUeyNAFVVXAAHQCpKKAKosrMX5vxbILsp5Zm2fMV9M1Y3D0P5GnUUAN3D0P5GuEHwq8PN4vl1+dZp95Li1kGUDnqxPU+wPSu9ooAytK0DSdF5sLJIpCuxpdpLsM55Y8mr9xFBdW8kFxEJIZFKujrkMD2NTUUARQxw28CQwxiOJFCqirgKB2FYOo+DdDvbUxpZLbOGZ1khTaQzdSexGcHB44FdHQeaAPLZfhze2uiT+Q0E9+9yspCqVJVcgbXPKsThj2OMe59G0xLuDTLeK/mE92qASyIhAZquUUAQTQW9wrLNAkispRg8eQVPUHI6e1ch488Ct4yXTxFqUtmLWT5k2lkKnqwXs47Gu2ooArwJ9ls44UaWYxRhQ0pJZ8DGWPqe5rk9DbUPEV7cr4k0aPy7Sffbs8ZHlP/cH98Ywd3Q/ljtKKAMXxRb6bdeHbwapaSXFskZdljQlx7r6H3/PiuC+Fnhiysr+71fTmnt7csYzAcvuJ52l8YZV7Y5yeff1frUcEENtCsMESRRL91EUKB9AKAOD+JcVm8WnyXGkvd5l2MxyFZMg+UccncenuPwPXzWVnq+ii0u7IrbzRKDA64MfHA46Ee3TFaBAbqAec80tAHnOlrpHgjxXHoum6VdMLkBWmclnAPICDHzICCWP+FdH4vstY1HTI49HuGjdZAZEVjGzjth+2Dzjv+h6AxRtKshRTIoIViOQD1wfwFQXuoWth5P2iUIZpVijXqWZjgAD/OKAEsluIrO2jvJvOuVQCWRUKh2xycVZ3D0P5Gql5qUNncQQtFPLLLkqsMRfABAJOOg5HNJDq9pcTxQRMzySGTChT8oRipJ9BkYB79qAMO8vvEq+NLe3t7RTpRXltvylf4mZuoYHovf8eIPGB8QT3draadYJdafMCs0TD5ZD3WQn7i46Ed/oAexooA4T4cJdW1vqEFxprwATZMzgh2b+4c/e2jA3dK0vEHhm61nXNPvodSlt47c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\n", "text/plain": [ "" ] @@ -1328,7 +1333,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 27, "id": "c4d41344", "metadata": {}, "outputs": [], @@ -1354,7 +1359,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 28, "id": "79e4e9b1", "metadata": { "scrolled": false @@ -1365,61 +1370,61 @@ "output_type": "stream", "text": [ ">>> Running Pareto calculations for 10000 models on auto fronts...\n", - ">> Automatically selected 6 Pareto-fronts to contain at least 100 pareto-optimal models (108)\n", - ">>> Calculating response curves for all models' media variables (540)...\n", - ">> Pareto-Front: 1 [18 models]\n" + ">> Automatically selected 6 Pareto-fronts to contain at least 100 pareto-optimal models (122)\n", + ">>> Calculating response curves for all models' media variables (610)...\n", + ">> Pareto-Front: 1 [16 models]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " 00:00:02 [=========================================] 100% | 18 \n", - " 00:00:00 [=== ] 5% | 1 " + " 00:00:01 [=========================================] 100% | 16 \n", + " 00:00:00 [======= ] 16.7% | 2 " ] }, { "name": "stderr", "output_type": "stream", "text": [ - ">> Pareto-Front: 2 [20 models]\n" + ">> Pareto-Front: 2 [12 models]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " 00:00:02 [=========================================] 100% | 20 \n", - " 00:00:00 [==== ] 9.09% | 2 " + " 00:00:01 [=========================================] 100% | 12 \n", + " 00:00:00 [== ] 3.57% | 1 " ] }, { "name": "stderr", "output_type": "stream", "text": [ - ">> Pareto-Front: 3 [22 models]\n" + ">> Pareto-Front: 3 [28 models]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " 00:00:02 [=========================================] 100% | 22 \n", - " 00:00:00 [==== ] 7.69% | 1 " + " 00:00:02 [=========================================] 100% | 28 \n", + " 00:00:00 [=== ] 5% | 1 " ] }, { "name": "stderr", "output_type": "stream", "text": [ - ">> Pareto-Front: 4 [13 models]\n" + ">> Pareto-Front: 4 [20 models]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " 00:00:01 [=========================================] 100% | 13 \n" + " 00:00:01 [=========================================] 100% | 20 \n" ] }, { @@ -1433,108 +1438,37 @@ "name": "stdout", "output_type": "stream", "text": [ - " 00:00:02 [=========================================] 100% | 21 \n" + " 00:00:01 [=========================================] 100% | 21 \n", + " 00:00:00 [== ] 4% | 1 " ] }, { "name": "stderr", "output_type": "stream", "text": [ - ">> Pareto-Front: 6 [14 models]\n" + ">> Pareto-Front: 6 [25 models]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - " 00:00:01 [=========================================] 100% | 14 \n" + " 00:00:02 [=========================================] 100% | 25 \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "Creating directory for outputs: /Users/yuyatanaka/Desktop/Robyn_202401291703_init/\n", + "Creating directory for outputs: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/\n", ">>> Calculating clusters for model selection using Pareto fronts...\n", - ">> Auto selected k = 9 (clusters) based on minimum WSS variance of 5%\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in rnorm(sim_n, mean = boot_mean, sd = boot_se) : NAs produced\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - ">>> Collecting 108 pareto-optimum results into: /Users/yuyatanaka/Desktop/Robyn_202401291703_init/\n", + ">> Auto selected k = 3 (clusters) based on minimum WSS variance of 6%\n", + ">>> Collecting 122 pareto-optimum results into: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/\n", ">> Exporting general plots into directory...\n", ">> Exporting pareto results as CSVs into directory...\n", ">>> Exporting pareto one-pagers into directory...\n", - ">> Generating only cluster results one-pagers (9)...\n", - ">> Plotting 9 selected models on 1 core (MacOS fallback)...\n" + ">> Generating only cluster results one-pagers (3)...\n", + ">> Plotting 3 selected models on 1 core (MacOS fallback)...\n" ] }, { @@ -1548,79 +1482,9 @@ "name": "stderr", "output_type": "stream", "text": [ - ">> Exported model models as /Users/yuyatanaka/Desktop/Robyn_202401291703_init/RobynModel-models.json\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00582\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.0038\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00299\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00271\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00215\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00177\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00276\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.0069\n", - "Picking joint bandwidth of NaN\n", - "Warning in min(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to min; returning Inf\n", - "Warning in max(data$x, na.rm = TRUE) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Picking joint bandwidth of 0.00357\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n", - "Warning in FUN(X[[i]], ...) :\n", - " no non-missing arguments to max; returning -Inf\n" + ">> Exported models as /Users/yuyatanaka/Desktop/Robyn_202408081618_init/RobynModel-models.json\n", + "Warning: Removed 1 row containing missing values or values outside the scale range\n", + "(`geom_text()`).\n" ] } ], @@ -1631,7 +1495,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 29, "id": "7bfaff31", "metadata": {}, "outputs": [ @@ -1639,15 +1503,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "5_181_7\n", - "1_222_8\n", - "1_202_4\n", - "1_202_9\n", - "1_216_5\n", - "1_223_5\n", - "1_210_5\n", - "1_218_4\n", - "1_214_6\n" + "3_216_3\n", + "3_206_5\n", + "4_182_3\n" ] } ], @@ -1658,7 +1516,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 30, "id": "9c5b8e28", "metadata": {}, "outputs": [], @@ -1691,7 +1549,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 31, "id": "93583977", "metadata": { "scrolled": false @@ -1706,7 +1564,8 @@ }, { "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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wYWdnZ/BGN0oHbjlz5gzEDm3fvj0+Ph78643kPHfuXHl5+eDBgyFkBXLcvn17aGiov7///v37YaMlJyenAQMGaDQauEav1+/bt09eDtJezj/++MPHxyc6OrrZR3bu3Lns7GyIF0IIdevWLSwsDJzxFy5cKC0tBUng4h07dri4uPTt27eFNpCZmXnu3LmBAwfC3GIKhUKhUCgUSltzM4Y7atjWR/6z5YmJ9r/am5uy4Z6Wlnbu3LmmF9izb9++UaNGPfPMM0OGDHn++ee7du26bt06ezFa7/dtdOVNO4ybTafZqrhWDdxcRi1js9mWL18OC8LAw4VNl240U6jbXbt25ebmwrcN/D9o0KDOnTv/leJQKBQKhUKhUG6Cm4xLhk2LIHwCZjrCeZiTihCC+algOILBJwhCszMyNRqNTqeD6+UL5OmtcCMhpE+fPm+//fZPP/00bty46OjoL774AiEEhnKjlGUZ7LGXByxaWXi4sdm77M9DLgghURThTLPpQAwPnGmhBiRJahTrIuclp9ko5UalaATEtMAx0wSDwWCfpn1JG0nS6EE0TQomMMjpUKudQqFQKBQK5fZwkx73W4jNZpMkSa1Wt+ZiMJrlaaYUCoVCoVAoFMo9wp033FvJn/tFNbj26arh16LpipaouRVsWom8UqcM+N1vUjgKhUKhUCgUys1y5y0w2S5s9hNCPimvki4Hn9yS3OWgkUa5N5Wq0UELYrf1t9C1ZAZgKX1541WO42Bl/Ua3tFJI2BzXnr9e8y3L38JP130of5FWZorsinDTyd4qWqiB1tRzCwm2KdeSren5lt87+9v/ouStv731ra41V95cG2754kaxcE1PXuv2mz7f8ivZ7Ptyc+X9i3fdWo3RcqZ3RbIUCuWu46963GGCadOTEAwtSZL9HFaTyVRfX48Q4jjO1dUVNUxtrK2tValUrYyWab0YrQTWdnRwcGh0vrq62tnZGeSXF3XRaDSwDCJCyGKxWCwWFxcX+ZbKyko3N7ebM20huLyVUUDXkhlkcHd3l5fTsS8FYLPZzGazs7Mz/FlXV2e1WjHGrq6uza4E3xa0LL9ch5Ik1dTUSJKkVCpBYJ7nDQYDLCoKNH0KEKBv/xQIIfZNEYYROI7jeb62thZO2mcqSZJ9c7JarfAJBOI5ODjI6/zwPK/X6+XadnFxubl2KAgCbIBwE/dKkqTX6+3rRKZRPV/rWcuvD5Si0dTz1sPzvLwnwHW5Vhtoer5Ri23aBvR6vbOz8+2cbtFCnaOGnYzl2SzylYSQqqoqULlarVbe9aK2tlaj0dhvZNa0DaMG/ckwjLu7u3yyaQuENCVJgncfVAr8ajKZzGazh4cHsnvW8C7ICVqtVvjmt9lssMIsy7KgruEuvV4Pdzk4OMBueoBeryeEyFcCjd4XOU0nJ6cb3bitqSqTRZIbrbxCgFz/N6cx4EZ7bQxTeuxltu90mq0reF7waBQKhX2O1+JamqoFOSkUyr3GTRq7oB8XLlwYFBQ0a9YsCFwBpYMx3rBhQ58+fU6cOBEWFta9e3dQqRUVFe+//35YWBhCCGMcEhJy3333MQxz/Pjx/Px8jHFiYqK/vz9s5SNPUS0tLc3MzBw8eDCkDPmCmpZnT544cSI7O3v69On2M0RbWYScnJyDBw9KknTffff5+fnJnzF79+69fPmys7Pz+PHjHRwcMMZHjx49f/681WqdOHGiv79/QUHBgQMHqqure/fu3adPH0EQNm/eXFxc7O3tPWrUKJ1Oh/536yI5tkeO+ZGrCwQ+depUYWHh+PHjW4gCupbMUDOiKIIMXl5eo0ePdnJy2r17d3Z2tn0piouLt2/fbjabExMTe/TocerUqXXr1nl5eXEcN2vWLBcXl0ZzYe3rH07aRyvBn4QQnucPHDjQv39/+478puX39vYeMWKEi4vL8uXLi4qKlEplaGjo5MmTy8rKNm/ebLPZ4uLiEhMTGYZp9BSg6o4fP+7k5BQTEyPPRa6srPzoo4/eeOMN6L83bNjg5uY2bNiwTz/9VJIksAjVavWUKVNcXFy2b99+6tSpd955B24vLy9/44033nnnHY1Gs2XLFoPBwHFcnz59unbtSgj54osvBEFwcnKCrKdPn+7u7m4f0yXX4aBBg+wfN8xChm5Yr9evWLFi7ty5arVaXgvoum0YLqutrf3jjz9KS0sTEhJgpVH5NZHrefTo0QEBAWlpaWvXrrV/1iDzd999N2DAgOjoaDBEiouLDx48OGPGjEbtUK5M+8ZsX4qamppNmzbNmDFD/rK9oTYAiTc6jxBq1GJLSkq2bt0KbaB///48z8OvTk5OgwYNguZn34DtW6bcYmVh7GeZnzp1ysnJqXPnzuTaCyW1UOdy0RBCy5cvnzRpkpOTk16vhyvj4+N79epls9nWrl1rs9lUKtWpU6emT58+dOjQ48ePp6amajSacePGeXl5gbZs2oZLS0v//e9/BwcHq1QqFxeX+++/X6PRMAzz+eefi6Jo3wI9PDzy8vIOHz6s1+sdHBxGjBgRGBiIMT527FhmZqbJZHJzcxs1apSLiwvGeOfOnampqfat/c0333zttdeCg4M/+eQTjLGTk5PFYunSpcvo0aMZhtmzZ8+uXbvCwsJg3aphw4ZFRUVJkrR79+7c3FyMcWBg4JgxY8BlsH379traWvl9kSTpiy++AGlVKtWwYcNCQ0NbqG37Ok9KSjp//ryPj8+IESPgo86+Ke7Zs8fFxSU+Ph5ukev/pjVGaWnp+++//8Ybb/j6+kJfs3DhwqioqClTpsAt9n0fxvizzz4jhEBdRUZGjh07trS09MMPPwwNDWUYxmazBQcHT5o0SX43r/VeNNVUHh4eQ4YMgUfz1ltvPfPMM1FRUdetNAqF8neG3DjgkszNzX3yySdXrlwJe3lCF04IMZvNX3/9tclkqqysNBgMYJARQlJSUn766Sc5kS+//LK0tDQ3N3fRokWEkPz8fNjKRwbuOnLkyM6dO5sKYP+nwWAoKyu71gX2+wdBmnIRamtrv/vuu/r6+rKysi+//JIQAmVJTk7+4YcfQOY1a9YQQrKyskD4M2fOfPnll5IkLV68uLS0VBTFt956y2Qypaen//zzz4SQ9evXb9u2TZa/NcCVq1evPn78OMh2QzLDejKEkNTU1OXLlxNC1qxZc/DgwXPnzn3//fdQirVr1xJCrFbrRx99dOXKFYPB8OmnnxJCtm7devbs2RakkusfVrNpWvlwvrq6esmSJTdX503lX7du3ZYtWwgh3377rX1ev/76a0pKCiHkgw8+KC0t5Xn++++/h6fwzjvvVFdXw2UHDhw4ffq0nCMhJDs7e+rUqYcPH4aTP/7444ULF3ie//e//y0nvmnTJnhwS5YsmTNnDkyDJoQsXrz42WefJYSsWLHi999/J4RUVla+8cYbJSUl9fX1H3/88XWf7JEjR3bs2NH0vAzP88XFxY0qVv5TXr5JXsnH/oINGzYcPXqUEPLpp59WVlY2W89ffPEFIWTLli3nzp1rJMPOnTtnzZoFe5wRQsrLy1944YXNmzc3FbKpYI0uOHPmzIoVK+QLbqgNQLmanrdvsWAb/fLLL9AGFi5cWFtbu3nzZnhq69at2717N2nSUOWW2cL7CD+tWLEiNzdX/vNa8l+rzuWkvv/++3fffRduaXolUFRU9Prrr+v1+ry8vHfeeUcQhD179mzatEmWv2kbPnbs2MqVK+H2HTt2gDqqqan55JNPGhUHjM78/HxCyOXLl9944w1BEA4ePPjll1/W19cTQvbt2/ftt9+ChD/99FPT1g4jUfZvx5tvvllUVEQIWbp0aVpaGpzMycn55ptv4NF/8MEHcHLRokXwIH766aeNGzcSu/fFZDJBUySEFBYWLly40Gg0ylm00MjPnz+/dOlSQsimTZtg3wyoJblmnnjiCShvo/q/CY0BN549e3bixInp6elwwblz56ZOnXr+/Hn4s1HfV11dba8H3njjjZqamlOnTi1btow0RwslbaSplixZIuvnDRs2PPPMM8eOHSM30rlQKJS/HzcZ1IEx3rJly4wZM2DwHSEEmxwdOHCgoqLCarWq1Wq9Xg+7HQGFhYXBwcGowYMCw5oGgyEhIUEURUdHR9hk9MyZM3q9HhKsqKjYv39/SUmJJEmVlZUlJSUpKSlVVVUY40OHDh05ckQQBIRQeXm5u7t7QUFBXV1dUlLS5cuX7b0RDMOwDdh7izHGycnJPj4+Go1GHhKFQcnCwsKEhARBEIKDg/Pz8xFCQUFBc+bMQQgFBATU1dVhjOfMmePt7c0wjEKhsFqtGRkZvXr1Qgi5uro23YFVFMXc3FzobMxmc0ZGBtTD4cOH5VJcvXpV3szohmQGnzdC6MKFCyCDu7t7TU1NYWFhfHw8lOLKlSsIoZSUFG9v75CQEEdHxxdeeAFaQF5eXnJycqP5rPCIof6Li4ttNhvLsmlpaTk5OXLdHjly5NSpU7Aw6M6dOwsKCkpLS+Hevyi/q6srz/NWq1Wn0/3xxx+ZmZkIofr6+rq6Otj3SqvVGo1GlmXlp6BUKuVql0fJ5caWnZ09atSoq1evSpJktVpra2tDQ0Pz8/PtQw5gZ1xCiNVqdXR0rK2txRiXlZWVlZXBFlpGozEqKgqqd9CgQSaTqbS0VI7fQA3u57y8vJycHLm8UIfl5eW1tbVXr17Nzs4+d+4cwzDnz5/ftWsX7J4LW4lhjHNzcw0GQ6M2jDFm7bA/X1FRkZ2dDY5DJyenmpqaZusZapgQcuXKFXjW8IxKSkpOnDjRqVMnKEVxcfH69esNBkPnzp3R//qt4aWAsCKMcWZmptVqhd27du3aVV5ejhAqKiqCaDfSMGLQ+jYAydqfB194amqq3GKff/75+vp6g8EAbUCtVsPoR3x8PDhxq6urG7130DKvXr1aUlLCMExeXt6pU6fsLzhy5EhqairDMOnp6WfOnIEGLI+KNJX/WnUOpTYajdu2bUtLS4ONDsrKyppeKQgCz/P//e9/x40b5+zsvH379vHjx7MsO3z48LFjx8q5N23DBQUFMCApimK/fv3y8vLgkdm3QHiLt2zZMmDAgKCgIEEQOnbsOGTIkPz8/OTk5EceeUSj0fA8P2TIkJqaGthJumlr9/X15TguNzdXrVbbbDbY31qn01mtVlBfsKceQkihUECO1dXVHTt2BAHGjRsHzw789PL7Ul9fX1xcDCMDPM/7+/urVKqCggJk1yM0beTw065du2DQz83NDXbmlgemUlNTt2zZ4uHh4evr26j+jUbjTWgMoKioyNfXF1qUIAjp6eleXl6yfpb7Poj8LCwstK8rR0dHq9VaWFgYGBho3xTl4xZK2lRTBQUFEUKqq6uzs7NnzJiRlZWFKBTKvc0Nh8rAQOGVK1f0en2vXr0OHjxoNpsdHR0zMjKOHDnSqVOnFStWeHh41NXVLVu27P3335cV1pUrV2JiYiorKzUazbFjxwRB8PDw8PHxgV9TUlJgZNweCO3o2rUrQujkyZPHjh27//776+rqNm/e7OPjYzKZNm7cOGXKlKVLl7700ksrVqwIDg4OCQnZunXr1KlTAwICYNB548aNGRkZWq3WZrMFBQU9+OCDcphgeXk5DI+Komg2m+V8bTYbBHqmp6fDZ4lKpSKE1NTU7Nu3r0ePHgghhUJhNBozMzM9PDycnJwiIyNPnDjh6el55coVecRWhhCyf//+UaNG+fv7b9++XaFQhIaGLl26NDg42Gg0bt26deLEiYIgQB+MMb4hmUlDqElsbOzx48c9PDyuXLnSv3//ixcv2mw2+1Lk5OSYTCZ4QGPGjDGbzbt27Ro7duzly5dLS0snTZrUtP6Liop69uwpSdLPP//coUOH7Ozs8vLy3r17r1mzxtHRMS8v79KlSw8++GBRUZFGo0EIQaTTX5Q/Jydn6NChFy5cOHny5NSpU7dt28bzfJcuXdzc3I4ePRoUFMRxnL+/v/1TcHNz8/HxIU1GkKE7zMjIGDt27I4dO8rLy9VqtdFoVKvVBQUFRqOxsrJSqVRWVVWdOHHimWeeqaurs9lsnTp10uv1rq6uJ0+e9PT0BDsyNjZ2z549bm5uHh4eQ4cORQjt27cPRpbALNbpdBqNppERAHXYu3dvi8Xy73//e/LkyR4eHps3bzYajV5eXhs2bHj44YePHDlisVimT5/+008/RUZGBgcHy20YIXThwoVNmzY5ODgIgqBSqaZOnert7S2/hvDWMAwD0bSowfKzr2ebzWaz2Xbv3i0/64kTJ4qiuG3btkGDBp05cwbCghFCM2fOZFm2Udw51Gp6erqjo+OgQYMuXbq0bdu2Z555ZsuWLUaj0dPTc+PGjTNmzJDD0EG2G2oDTc+DDXTlyhX7FqtSqdzd3aENqFQqNze3MWPGgJDnz58fOHAgavK9UVJSolQqOY7btWuXwWDw8PBYu3bt1KlTEUJr1qxxcHCorq4uLCyED3InJyfSECzXVH5IvNk6Rw17SiQkJDg7O8MXTk5OTtMrOY47efKkg4NDQkKCzWYrKyu7cuXK0aNHhwwZAlE6qAlw8urVqzExMfZTbhBCFRUVBoNB9vo7OzsTQoqKiqZMmUII4ThOFMXBgwdfvHhRrVY7OzvD60kIUSqVer1ep9NZLJZGrR2cF8XFxR4eHhDSXVFRYTKZ/Pz8zGZzYWGhJEk1NTUcx23atCkiIoIQEhMTs3Tp0rNnz8bGxoaEhISEhEiS1K1bt0bvy549e1QqFex0QQhRqVQQF44xrq+v//HHH3meZ1mW5/mBAweCQ4dlWQi28fT0ZBjGYrGAmwM12O7e3t4vvPDCypUrFQpFfX091D8kq9Vq5dZyoxqjsLAwKirKYrHA5y586sOV9n0f6NWSkhJ3d3e5rgwGA3QEXbp0qayshNfBzc0N8mq2pKBAmmqq+vp6eKf27dsXHBwcFBR06NAhWUgKhXJvcsOGOyivw4cPDxo0SKVSqVQqo9Ho4eEBhmlYWNilS5c6dOhQXl4eGRlpH3FeV1d3/PjxCxcuZGRkTJgw4R//+AfHcRBWC47A559/nhACDhLIyMPDo0uXLiNHjmQYpqqqqlevXr169SopKQkJCRk8eHBubu62bdsMBoO/vz9k0b9//w4dOuTn54MjBHIfO3as3LvL0fMYY6vVajQag4KCMMZmsxnOi6LIcVyXLl32799vNpv37Nkjf1oghDZt2pSWlvbZZ5/Bn2lpacuXL58/fz7LslarNS8v77vvvnNxcYmNjW0UH8xxnJubW01Njbu7e15e3vPPP19RUREREQGl2LFjB8wolQcobkhmYhf3DzI4OTlFREQYjUboWuRSXL16ValUPvzww2vXrj127FhcXNyQIUNGjx6NEPrggw9qa2tl7x2k7OHhERkZOXr06L1792o0msGDB9tstl9++aVHjx6XL19++eWX1Wr1qlWrGIYJDw/38/Pz8fGBeNC/KL+zs3NYWFhKSsrMmTPj4+NdXV33798fExNjtVqTk5M3b948YcIEtVoNtiY8hccff1yhUDSdowxPwWAweHl5xcXFnTp1KiYmBr4xamtrL1++vGrVqoyMjKioqH/84x/u7u6XLl1iWTYiIgImlhUXF3fq1MloNDIMk5iY6OLismbNmtDQ0KFDh4IFkJOTs2rVKvBEjhkzJiYmpkOHDvZZQxsePnz45cuXAwMDBw8ejBAqKCh46KGHEEIXLlyora2FCiSEsCzbv3//oKAguQ1LkhQREfHSSy/Jz8XeS52XlxcaGgrH8P0M+drXM5iMkiQNHjwYnvV77703ceLEQ4cOhYeHh4SE5ObmwlMAK9NgMDSaoQEHHTp0AG8fWJkqlQpjPGPGDITQokWLIOrA19dXLvgNtYFG52EKJkIoPz8fWuy6deuSkpL69+9v3wY0Go3NZlMqlRs3bnR0dOzRowexm10A+YaGhoaGhqrV6rNnz77yyisIobVr12ZkZHTu3PnixYuvvvqqWq3+/fffPT09ExISunTpIk/MbSo/DBc0W+eAk5OTk5NTUlISBChf68r9+/dDynV1dSUlJYMHD05ISFi5cqWbm5unp6fUZAEWMLUhNh3OyIu01tbWXrlyBVpgfX39/fff7+3tLX9AIoSgLMXFxfJkEqhtURTho4XjOPvWHh4eDn5oo9GYlZW1e/duhFBubu6IESNUKlVxcXFFRcX69esrKioEQZgzZw4Mzri7uz/++OMbN25MS0sbNWqUl5cXwzB9+vRxcnKC92XYsGEcx1VVVcEETZDEYrHAnARCiEajeeKJJ+Qiw1sM0ubl5bm6usKVBoMBXl7Zcg0MDMzJyYHrdTqds7NzUlKSPPvWZrPdhMaAqK0ePXoYDAYYCOrSpUteXh68F4cOHZL7vrq6Oi8vr7q6Ormurly5MmbMGIZhqqurjx8/npWVJYqiQqGYNWsW7DN4rZI2q6lgCMtkMl26dGnBggUQvoVaN4mLQqH8Xbkxwx0UrtFoPHz4cGFhYVpa2qVLl2BEz2AwhIWFiaLo6uoaHh6elZUFgTFgkxkMBq1WCx3nqlWrNBoNeINgMtySJUsee+wxV1dXea4bdMCFhYU6nQ726UQI9erVCwad6+rq/vvf/4LPvrq62sPDQ6/X+/v7d+jQAXyo4KoEdu/efenSJa1Wa7VaAwMDJ0yYAP2BxWIxGo3goyotLQV7CxRi9+7dHR0dKyoqQkNDw8LCoANQKpVz5sxhWTY5OXnAgAEY4wEDBjg6OqalpXXo0GHPnj3/+te/tFrt999/n5ubCz4neQIfOJkgFL5Tp04sy+p0utraWrkUVVVVsKwEXHxDMkuSxLJsWVnZzp07QYbFixfn5eX17NnT0dGxqqoqNDQUBrJZloX5l0OGDDl06FCvXr0mTZoEObIsK7uyZJkLCwsdHR0JISkpKfX19aWlpeANVSqVM2bMWL58eVhY2PTp0yVJqquri42NlS2Dvyj/999/n5OTA2EzYGGwLJuenq7X61977bX8/PwdO3b06dMHGsmAAQN0Ot3x48fj4+MbrTgBF5hMJlizKDo6+tdff3V1dQ0JCUEIlZeXz507t1u3bhcuXDh8+LCHhwchpKKiwtvb28vLy2g0HjlyJC4u7vLlyzAU4OfnFxUVFRkZuWTJkvXr18+YMaOoqOixxx7r3r17o0xRg/9VrkNJkgoKCvr27Qsl8vHx+eqrr3x8fOrq6hwdHaurqwcMGAAVEhQUJLdhkD8zM3P79u3gcVcqlRMmTADzjmGY8vLy6OhoQgh8dDk5OYEM9vUMoT4KhWLy5Mlwl06nS0lJOX78+Lx5806cOKHT6XieB+uwrKzMx8en2dV+nJycwPNaXV0NE3P9/PygFLW1tY6OjuXl5eBYvYn3rqnMcF5usQMHDkxJSTl9+rTcBnbu3JmQkKBUKvfv35+VlQWhX/beU7DAQDOkp6dfunTpm2++gXiGqKgohmGgDYeGhk6cOHHfvn3+/v6S3Qz4pvKThumbTetc/gSFFwRiJCorK+Pi4uQrweyDKIjIyEi4oFOnToMGDUIIdezYMSsry9PTs5EzFdqAXq9nWRZeRoRQSUmJnFqjFlhUVCQv7AMhFjCKVVlZKadmsVhsNpuPj8/p06chAkRu7dnZ2Z06dUII1dTU+Pn5QasYN24cuKsLCgp69+792GOPWa3Wr7/+2tPTEyGUnZ1dVVWVkJAwe/bsI0eO/Pjjj6+//vqRI0c6dOggvy/r1q2bMWOGXq+HTgG0jdlshmThE27FihXQDnme79evX48ePaC5gndfbiSwvIH9u1ZWVgb6DTXsAw31f+TIkbq6upvQGNXV1SqVqkOHDhkZGVlZWY6OjvAhBF6qpKSkoqIi6Pvg67q6utq+rmD0RqlUvvHGG40Sb7mkTTVVUFAQQig1NfXixYvff/99bW1tbW2t1WqFEeBGYwUUCuUe4WYM9507d06cODExMVGSpMOHD5eXl3t6esoOnkuXLo0cOXLnzp0jRoxADaZwUVGRi4sLjA/269dv6dKlffv2BZ/l8uXLZ8+eDfax/VocCKGCggJHR0eO42pra/V6vbe3N8b4u+++S0hIGDp06NatW/38/MrKysD0AWsDXEewggSkNnDgwN69e+OGNblkZceyrJOTE3Ryqampw4cPB2ltNtuVK1ciIiI6deqUlJTUrVs3g8GwdOnS5557DiGk0+nc3Nx+/vlnWKlDo9G4u7vn5+d37NhRXtHCZrMhO6cIlMXZ2Tk/P99isdx3332EkG+//bZ3797Dhg3bunUrBFPCSCtcfEMyQ6+WnZ0ty8CyrMFguHTpUkREBEIoKSkpJiYGIRQUFARuv4KCgtDQ0DVr1nTt2jUqKqqwsNDBwcE+WBYoKCjQ6XTgn3vkkUe8vLwKCwtVKhUEgD722GNr1qyBJTtqamrAVwo33midY4zt5ec4Tq/XL168+LHHHlMqlRcuXOjcufP58+dhdQWO4yDm/ttvv50wYYK/v7+Dg4ODgwOYTfadGVRmUVERDPq7urqGhobu378fjDCr1eru7i6KYpcuXbZu3Xru3LmYmJiCgoKwsDBXV9eMjAyj0Thr1qxDhw6NHTt2165dFoslKCiIYZixY8f+8MMPCCH7eF+ZRr0ptGGGYbKzs4cNG4YQ2rNnT35+/iOPPFJSUlJUVKRSqUpLS11dXY8cOQLWmH0bxhiHhITMnj1b9pXaW4qwph7EsXh7e4MzslE9nzhxYsqUKStXruzZs2eXLl1AHkhh7dq1586d8/PzS0hI8Pf3xxgXFhZCYIl9TcIB2C67du2C1Tl27NhRUFBgX4qamhpYlegm3rum50eOHGnfYouKivz8/C5cuABDFhzHWa1WpVJ57ty5kydPvvTSS/abFciYTCa9Xg9m64gRI0aNGmU2m3Nzc6OionJzc4OCgh577LFVq1YdP368rKysa9euYHuBqNeS/1p1jhoM0KqqKrBHG10JbTs9PT0oKAiGTVQqleySr62tjY6Obtp+5MgNNzc3+YPqjz/+GDp0KLRh+xZICPH09KyqqjKbzZD1gQMHtFptWFjYwYMHMcZgpx46dCg0NFSpVIKLwb61JyUlDR48mBBSU1Pz+OOPyysYQrUUFxcHBgaKoqhSqTp27Lhly5ZHHnmktrY2LS0tISEBIdSvX7/t27ebTKarV68KghAYGGj/vphMJigvy7KHDh3y8/OTA0hUKhWE90BeUFJoSCqVClbEqqurKy0tnTJlCmoYSUANwUsQTgkhSVVVVTDyA0s5oRvXGMXFxTqdzt/fPy0t7cSJE4mJiVevXgXn97Zt2+z7Pvgcqq6ufuKJJ+S6kiQJnlej1ggZNVtSoJGm2rdv38SJExFCKSkp77zzjru7uyAImzZtKisrA4OeQqHcm9zAiBtpmLCYnp4+aNAgV1dXd3f3gICACxcuuLi4WCyW3Nzc48ePX7lyRavVmkwmV1dXcPkghK5cuQKj/JIkgepPT09HCC1evNjPz8/X17esrAwhZDAYwOoFvVZdXV1VVSUIQnV1tclkAj3O87y3t7fFYtm8ebNGoykpKXFwcCgtLQVVXlRUBKpQ7sV1Op2Hh4e7u7uHh4dsmxJCtFqtr69vampqenq6g4NDSEgIxDdLknTw4MHy8vIjR4507NjRw8PDwcEhODg4MzOzpKSktrY2JiamV69eZ8+era+vT09Pj4mJiYyMLCsrKyoqOnr0qNVq7dixo8ViAWcMatDXfn5+e/bs8fLyggmRgiDIpVCpVBUVFWC03ajM4FMkhISHh1dUVIAMNputY8eOMCcSSgHTqtzd3Y8cOVJUVHTy5Mn4+PiIiIjk5OSKiopNmzZ1795dkiRYQrtp/UdERBQUFBBCkpKS1Gp1enr6smXL6urqWJZVKpVmsxkmsMq94I3WOULIXn6TyRQbG6vVapOTk/Py8s6cOZOYmNixY8fU1NSKioodO3Z07twZY9y7d+8zZ87U19efPn26V69euGG+mn2Lhbb3Z1tnGG9v74MHDwYGBtbV1UH8AIwIRURE7N+/HyF06dIld3d3Ly+vtWvXwhQ3g8GgVqsHDBiQnJxcUFBQWVm5adOmxMREi8WSl5cHTvry8vKKigpRFCHeo1EdVldXQzQz2KCwdiHG+Pfff6+rqzMajVAD+fn5YM81asMqlQoq093d3c3NDb7T5KGhtLS0oqKijIyM/v37I4TAIWdfzzqdztvbu3PnzkeOHKmoqNiyZUtkZGR8fPyrr7769NNPBwUFvfTSSwEBARBFkJeXB09QEARY8UOuTBcXl/z8/NzcXJjjYbVa5VIYDAaDwSCPL93Ee9dIZgcHB/C4yy32xIkT8fHx4eHh0Aa2b98eFRVlNBq///77cePG6fX6mpoaiLeRJ04ghCwWS2lpqclkCg8PBwnT0tJgBios+lFXVwfDTcXFxfazXJqVv4U6h8aPEKqpqamoqAAbvemVhJCCggJwaYNjuKys7NKlS8eOHQNfstSwYGijNpyfn19XV1dRUVFZWblx40ZnZ+fu3bvX1NTAUipyC4SBwe7du69bt66iogLqasSIER4eHsHBwdu3b6+pqUlLS8vNzX3ggQegtXt4eNi39rq6Ogjqq6mpcXBwgLmwZrMZosYvXrzo4+MD6wrA22cymWJiYurr66F1QVSeg4NDv379Gr0vZrO5oKCA5/mKioqUlJSUlBSwSuV3083NDRq5h4cHfA5BVURHR1dXVxcXF+/evTs+Pl6hUJjNZvsFAHJycuSl0+3rPzo6OiUl5SY0BgSPKZXK06dPFxYWhoWFZWRk+Pn5GY1G+77P398/OzvbYrGA2wjqCvYwyc/Ph7kH8FzkGczXKum1NFVoaOiRI0dYlg0PD3dzc/Py8sIYw3oJTT9TKRTKPcING+6lpaWDBw+G0X+EEJjdLMs+/PDDu3btstlsjzzyCOyh4+zsbLPZDh48iBDy8PCQg9cRQsOHD4dpPQqFora2dunSpWvWrOF5/sSJE0VFRahBZffs2RO2F1Gr1dDzYYxnz569Z8+ec+fOzZkzx9HRMTAwMDg42MPDA1b8UKvVEJBw3ShAhmFGjRqVmZmZk5Mzffp0WDsZPCuwEJharYb5mizLjh8/HjrImTNnchzXtWvXrl27Xrx4ceTIkR07dnRycrr//vu3bNlSUlLy+OOPsyybmZl55MgRudIQQv7+/vHx8YMGDYIz9qVwcHAICAiA0fOWxbaX+aGHHmJZ1mKxQCC7l5fXfffdBzLMmzdPo9HYlwK6qOHDh6tUqi1btsycOdPBwaFHjx7h4eGrVq3q27dvYmLixYsXZZlBDJiWWllZCV6uvXv3jh8/3t/ff/To0Z07d16xYoWXl1diYqKjo2NUVFR6enrTjrA1dV5SUoIQ8vLyGjt2LMj/5JNPQmhHUVHRH3/88fjjj2s0mt69e4eGhq5cuTI2NnbUqFGEkJ49e8JTGD58eGRkZNOxY/jTzc0tNjYWznTu3HnatGngzI6Pj5fdtL169QIvXWxsLCw6MWzYsNjYWKPRCEND/v7+06ZN27Vr19q1axMSEoYPH26z2UJCQjZs2LBq1apVq1b99ttvtbW1hYWFJ0+etK9DGAcvLS0dMGAAOMvHjh2LMd60adOIESN69+7N8zz4BTt06ABtoDVtGKo6JibGy8sLViaBb7OTJ08WFRUxDDNy5Eio54cffhghlJCQAM+6X79+/fr1AyPDaDT26NED3MyQl6+vL4zSWK3WzZs3w5ohUEVKpTIuLm7kyJFQaffdd59cCliCCd7Qm3vvGskMbbtpi01ISIA2EBMTM2zYsNLSUl9f36SkpGXLlsF3V0ZGxuHDh2WZQS2kp6dHR0cnJiZu2bLFz89v/PjxCKFJkybBTHofH59evXolJCRkZGTIoTI3Uedy24O56aIoxsbGNrpSFMXQ0FAw3DHGHMdNnz49KSmpoKBgzpw5uLm9deCMv7+/IAirVq1at26dj4/P7NmzEUIcx3Xo0EFugatWrQIH8Pjx46Oion777beSkpK5c+fC83rwwQdBGJ7n582bB26C6OjoRq29T58+Go1GFMXevXvDZyTLsvn5+WlpaQihyMhIiELEGHt7e/ft27empkapVM6fP7+kpOS3337jef7JJ59kGCYwMLDR+8LzfHBw8Pr161euXAnvOPikW4j3gArX6XSDBg3auHFjhw4d+vXrhxDKz89PTU2VL4iLi7Pf9Umu/8TExJCQkBvSGFDbnp6eMPoRFxcH0V+hoaHR0dElJSVDhgyR+z5/f/+AgACbzdanTx9YuwkWikEI+fn58Ty/atWq1atX//LLLzt27Gg6daFRSVFzmkqj0dTW1j7wwAMQggXn7V08FArlHuSv7pzaLFlZWadPn542bdotT7md0HJ8ISEkKysLtg2Srr2bUpuKdN0IyKbXt1LmNoqtvG6VNv3V/iRp2DGRYZjDhw/DFOFbKGr7jyi9tRLW1tZmZmbCehftpOCtadK3+b1rfeW0/sq2a8M3J0/b0UoZmr7mtyTHttYYFAqF0kbc8KoyEBdoH8BNGvYBBZdAcXHxrl27IORR3qJZ+t89C+U/7ZcPhxXBIXRBTlzugOVMid2Go009rMRuf8fWYC+YnLsc+9g0/FHOV/7gwQ3zwOB2KKxarZZXgpNTEO12km+2FK3v2tH/ViaEidvLcK1SwPRfeZUP+9nATWWW6x83LBcopybfCBff0F7czdZ5I/lblhYuaPoUAJvNxvP8tapLfgr2tp3cjOWTjS6TxUN2a6Q0WvwenMTkfxc2kevQ/rxkt2EnbpiKbd/80I00hkZVZP+M0P+2E/sr5ZP20sq3GI3G8PDwRmI0ej2bLUVrZEbXaANNZW62gHIbkJ+ILEbTNiy3zKavg31ScNxoqmILwl+rzhs1gKZ13qyKa/ruNGrD9iW1T61RC7zWmyInIteAfFmzrf1aSr5pA7iWQrCXuen7Iuuo1tS2/OoxdjtqN6rkpqLa1/9NaAwolyy/rKuvVS2NHp/985LLe92SNqupWqhzCoVyb3IrPe6gIouKikpLSyEQlkK5nZCGbcMVCkXTubYUSvuHtuHbCa1tCoVy19EmoTKUu3HI9W6UmdJG3KWN4S4Vm0KhUCiUVnLrDfem0QIUyu3kRsOlKJT2Bm3DtxNa2xQK5S6CetwpFAqFQqFQKJS7AOoXp1AoFAqFQqFQ7gKo4U6hUCgUCoVCodwFUMOdQqFQKBQKhUK5C6CGO4VCoVAoFAqFchdADXcKhUKhUCgUCuUugBruFAqFQqFQKBTKXQA13CkUCoVCoVAolLsA7ibukSRJkiT5T4Zh2u12S4QQURTlP1mWbee7bEiSRAhhWRbZbQMpCMLNVTI8KY7j5GM5nZbTbP0OlI2SbTZ3eAqNKh+eC5S09RnBMcaYYZibeJSCIECOTeVpBN2Dk0K5UURRJISAwmmZG3q/7LXiX6RRj3BzelXWXdfVzK0sJuilRurRfouV9t9zUSiU28at2YAJTLe/ns5t4G4xyO5glbY+67ulMm+Uu6g9Uyh3He3q/Wo7JdauikmhUP423JjhDjouMzPz7Nmz8KdKperVq5e/v3+bSXiTgKjV1dWHDh2y2WwIIScnp4EDB2q12vZpboJUFy5cKCsrGzRoEMMwFotFqVQyDLNv3z5fX98uXbq0XnK4MjU1taKiYtiwYQqFoqCg4MSJEz179gwJCZEkacOGDTExMREREc2maTKZHBwcWpNRdnb2qVOn4uPjQ0JC5KTg4OzZs6WlpSNGjKipqTl48ODAgQPd3Nzk3cVPnDhhNBqHDh3ayrJkZGScO3cOznh7ew8cOLA14tljsVi2bNkycOBAR0fH/fv39+vXz9XV9VpV2voaoFAowPnz5zMyMiZMmHBdp3sr3y9Zk5SVlQ0dOvSv2MFNewStVtuyErhWIvv27VOpVP369du7d6+/v38LmlnW4S2kCXopMTHR398f0iGEHDp0qKysDC5wc3MbOHCgUqlsnz0XhUK53ZAbged5Qshrr71mn0JAQMCRI0cIIYIgiKJos9kEQZBvkSSJ53me52HsDxIRRVEQBJ7nYQy05SshTfkkZAS5yLc3zReOk5OT7UWNi4vLzMyUJAlSa3qXKIogg71gcFLOTpYHTkJe8i1QitakY58dpEkImTlzplqt5nn+l19+efPNN+Eky7Jz5syB61tZS/Ck3n//fYzxxYsXCSH/+Mc/EEKvv/46IaSmpgYhtGjRIkKI1WqFBKEsVqv1hRde2Lp1K6QpZyfLDIUFCgoKAgMDEUJffvkl3Guz2XieB7GfeuopPz8/QsjRo0cRQtBIoMiEkDFjxoSGhoqiCALIP8mVLB/Dr6+88or9o3z88cflX0F4kL/pM5WvKSgoQAht27bt/PnzCKEDBw5AcRo1p0Y10PSpQQ3IOVIoFEKIKIoREREIoYMHD8o6ljRR1/bvl9VqhcskSbLZbPavWCNNEhgYCMdN9YN83FQ32tNsjxAVFZWXlwfSynrbPil7BS4IgsViEUUxPDy8T58+hBCEkKyZ7XU+/Ll8+fK3334bynVdvbRy5UrSoOtEUYyOjraXc/DgwUajEQSDyrEvo30/Qm6kD4Irmxa22Zpsmi+FQrkj3IwDg+O4sLCwwsJCs9lcVFRkNps///xz1BB5rFAo7IMRMcYcx3EcJ3sd4JhlWY7jwLuAEJIkyf5KOAnHkKa904JlWchF9u82zRdQKBQODg5btmzheT4rKys/P/+pp56CW2Ac0/4uSAdkkB0b8knITs5LPgnyyLdAKVqTDkJIvkwOlJw0adLbb7/NcdyPP/5YWVmpUCgIIe+9996ECRNQg7+nNbUkp8ay7KVLlxBCV65cUSqVJ06cQAjl5eVpNJrY2FhCiFKphAShLJWVlT/++KOrqyvDMPYPRZYZCgsUFhZWVlbm5OQ8++yzgiAolUqFQsFxnEKhQAjpdDoPDw94CjqdDk7KuLi4eHh4MAwDAsj1AzVmfyw/9NDQ0OLiYp7n33vvvf/+978HDx6E4oPwLMs2faZyk+M4TqvVggxeXl7PP/98SEgIPC+5OUEMfaMaaPrUoAYgx+u8KhTKPQC8F5cvXy4vL2cYZtmyZfLLguzUddP3S/ZGY4wVCoWsz+GWpppEplld0bSvaQr0CL///jvP88nJyRkZGR999BH0XLLetk9KLghIpVKpGIZxd3d3dXVFCL3zzjuyZrbX+ZDgTz/9VFFRoVAoRFG8rl5Sq9X2pVMqlXPmzDGbzWazef369QcOHNi0aRMIA5Uj63/0v/0IupE+CK60Lyxc2WxNNs2XQqHcEW7GcBcEASHk7++vVqv9/PwSExMLCwsRQgzDbNu2bciQIf/+979RgzbPy8t75JFHhg0btmrVKjj56KOPbt68eeHChZMmTcrMzMQYg17LzMx8+OGHJ0+enJ6eDmrliSee2LVr148//nj//feDp4QQwvP8J598MmDAgLfffru2thYhhDG2z1fOGg4EQYA+oFOnTh999NHx48ezsrJYlm0qLcRvjBs37tlnnzUYDKjhc2Ljxo3Dhw9/9dVXa2pqMMZJSUkTJ05MTk4eN27cN998IwjCm2++OXv27Pz8fITQ6dOnZ8yYcfz48QcffPC1116DMVlIXE6nrq4OCrhr167hw4c//PDDZ86cAZ1us9mUSuXq1avPnj27ZcuWt99+GyFkNpuhzlmWbWUtgQru0KGDIAg1NTVWq9VgMEyePBkuOHnypI+PT2RkJAxDT5kyZdy4cbt370YIvf/++zzPP/HEEwcPHuQ4LicnZ8aMGTNnziwsLIQ0P//88zfeeOOzzz6bOnXqggULEEKPPvpofn4+x3G//fbbsGHDnnzyyStXrkA7AbFJg7urUSsihOzYsWPkyJFr1qzBGG/evPmxxx6DAeJDhw7NnTu3vLxcfprgtYK+5KmnnmJZNicnByH08ccfv/XWWx999NGLL74Iz3Tw4MFyS0AIiaL43nvvTZs27dy5c+BVQgiBqw8a7U8//TR48OCffvoJHsHChQttNtsTTzxx+PBhjuM2bNhg/9SgBuQcG7U3CuUeBF6lxYsXR0REPPnkk8nJyTU1NSzLwntxrffr4MGDzz///OrVqxFCubm5Dz744MWLFxFCGOOVK1c2q0kQQvD+bt68ef78+ZWVlQihkydPzpo1q6SkpKSkZNasWcOGDYM0mwV0Eej/vn37xsfHnz59GiF04sSJGTNmrFmzZsKECdXV1UVFRdOnT5f1HnQEmzdvHjFixLZt2yARhBB4rxFCLMvKfYder8cYr1279uzZs5s3b37rrbc4jtu8ebN9D4Wa6CW5gIDNZtNqtWq1Wq1WDxo0yN3dHapCFMWFCxcOHTp09+7dIBhCaOfOndCPQFla0weBkOfPn581a9bFixeffPLJp556CuoT2fXaUJPg57LPl2o8CuVOckP+eRjIe+uttzw9PX/44Yc1a9YsXrwYIbRw4UJCyC+//KJWq8eMGRMWFvboo48SQgwGQ8eOHfv37//AAw8olcpffvmFEOLs7Mxx3P333x8SEhISEpKTk0MIOXnypIODQ8+ePRMSEjiOS0pKIoT4+fm5urpOnTrVz88vMDAwPz+fEDJv3rzAwMDJkycHBARMnjyZELJy5Uo5Xxi4hPFEQsiJEydUKtX27dvh5PHjxxFCGzduJISsWLFCvuuRRx4hhOzZs4fjuP79+3fq1Kl///4wJvjhhx8qFIrRo0cHBgZ2797dZDKtXbsWIdSjR48hQ4YghHr27DllyhSVSjV48GBCyM6dOxFC4eHhY8aM0Wg0kydPhvFH+3R69OhhNBr37NmjUCimTp2akJAQGBh45coVQshjjz0WHh6+Zs0aV1dXPz+/d999lxDi6ur69NNPE0JSUlKuW0tFRUWEEHlAs1OnTu+8805KSoqzs/OJEyeCg4OLi4tnzpzZrVs3Qsjp06cVCsWAAQN69Oih1WpTUlIWLFjAcVxcXNzhw4dLSkrCwsLi4+P79esXERFRWFhICJk2bRpCqHfv3tOmTRs2bJhSqezbt29RUdHHH3+MEBo+fLiPj09MTAwh5OWXX46MjISHq9Fojh8/TuxCZebNm4cQGjJkSL9+/RBCq1atgpGBDRs2EELGjRsXHBwsD+MSQl555ZXQ0FAo1Pbt2xFCa9euJYRMmTIFIdStW7c333xzw4YNSqXSviUQQmbPng01HxsbixD6448/MjIyEEKHDh0ihDz33HM6nW7kyJFKpfKDDz4ghDz55JMKhaJr164pKSmLFi2Sn1qvXr2qqqrkGujRo8e//vUvGLy+oZeIQvk7AV/UgiB07dp1/vz59fX1CKGtW7fCT88//3yz71e3bt0OHjzo4eGxYMECQkhKSgpCaPfu3YSQ9957r6kmiY6OhlAZUOww3eX3338nhEyYMKFDhw5ms7lTp079+vWDvmb58uXyxYB9jwDvvsFg8PHxue+++wghGzduBL09duzYtLS0Ll26yHoPNCqYsL179x4+fDhCaOrUqYQQFxcX0My7d+9WKBTQdyQmJkqStH79ehcXFz8/vw8++GDLli3X1UtQFtB1kiR179590KBBq1atWrt27dy5cxFC586dI4Q89NBDgYGBY8aM0el0a9askSRp27ZtKpUK+hFfX9/a2toDBw60pg8yGAxJSUnQhd13330Y49mzZ5MmvTbU5IwZM+R8161b16huKRTK7eRmDPeFCxfam/6ff/55TU0NIaR79+5gvG7ZsoVhGL1eD97T+fPn5+XlHTp06OrVq6IowvtPCIHv+6+++ooQMnz48LCwMMilS5cugwYNIoR06tRpyJAhhBAI8AC1HhcXFxwcnJycnJaWlpKSQgjp0aOHnC/LshUVFbKo9oY7IQQcEqtXr4Z05LsQQlardeTIkWBonj171sHBARwhHMe99dZbhJDs7GyE0Pbt2/fv389x3OHDhwkhOp0OJHz55Zc7dOhACAE37Q8//EAI+frrrxFCFRUVVqu1UTpbt2795ZdfEEIrV668cuXKgQMH6urqIJ24uDiokGeffRbEjoqK+te//kUIGTFixHVrae/evVB8UNZPP/30mDFjli9f7uPjw/N8nz59fv3119GjR48ePRqEgVrleR4htGnTJrPZ7ObmBp8EixYtQghBTTo7Oy9evJgQMnv2bG9v7+rqakLIvn37/P39wZzdv3//hQsXCCFLly6FD8J//etfLRjujzzyiKenZ3l5OSEkOjo6ISGBEBIaGvrGG28QQrp27friiy+ShjBQQshbb72lUqn69u0Ls0t79Oih1+sJIY8++qi3tze0wG7dujVqgUajESH00UcfEULWrVsH9XP58mWtVpuamgq+qI8//pgQ8tJLL0VHRxNCCgsLPT09T548SQhhGMb+qS1ZskSugdraWmL3gUSh3JuAAQeugYMHD1qt1k6dOj311FOEEBgRbfp+eXl5nThxghDi7e0N1nxaWppGozl48CC5hiaRDXf5OzkuLu75558XBCEiIuLNN9+0Wq0IoXnz5kFfU1BQYH8xsTPc1Wp1ZGTkgAEDwsLCWJaFTHft2sVx3Jo1a0iD3ga14+Tk9P333xNC+vTpA1P59Xq9p6fn+PHjCSGdOnUCzTxo0CC573B0dDxz5gwhZMiQIaDDu3btel29BO4kOcY9MTFR7mEDAwP37NlDCCkuLkYI/frrr4SQSZMmJSYmEkL+85//yP3Ivn37rFbroUOHWtMHbdy4MSMjg2XZb775hhDy7LPPwjxdyEXutQsLC0tKSuzzHThwIKGGO4Vy57iZUBmz2RwQEFBbW3vo0CFHR0cHBwcXFxez2axUKg8cOIAxvv/++yVJunjxopeX17Rp03744Yfg4OB//OMfBQUFDMMYjcZhw4ZZrVZnZ2c3Nzcw30tKSqKiomDaX3x8fGVlJSHEZrP16dNHEAQnJyeMMZhZTz75ZGFhYWJiYp8+fQ4fPmyz2TiOk/MVRfHy5cvof6MXwCEkimJtbS1EKCKEFAqFfBdCKCsry2AwwBSozp07G43G6OjogoICURTj4+PNZnNwcLBOp7t8+bLFYhEEoXPnziBYYmKiIAguLi4Qjgl5DRgwwGw2R0ZGchxXVlZWWVlpn46zs/O5c+f69OnTuXPnGTNmhIaG/vjjj+CpgvmgkiRBcAsUmed5CNIoLi6+bi3JQ64wfh0XF3fw4MF9+/aNGTOG4zg3N7eff/6Z53nwG4WFhbm5uT3zzDNRUVEQ1wgWeUVFhSiKlZWVEJqJMa6trYWxWrPZ7OXl5ezsLAiCXq+XJKmsrIwQMmjQoLNnz06cOPG5555rFM5+rVbUoUMHT09Pq9UaERFhNBoJIQ8//PC6devOnDmTk5Pz6KOPooZgfQBjrFKp1Gr1s88+u2PHDmdnZ0jH09PTxcXFZDI1aoHZ2dkGg4Fl2YiICLPZ3KdPH9SwJjRUKbSHTp06mc3mTz/9FNx48D1QWVlZWlpKCJGfmpubm30N6HQ6URTpIg8UCiEkJSWltrZ20KBBKpXq0qVLa9asEUXRYDBc6/0qLS0FBQUKEwbWILUBAwa0rEngxpkzZ65aterAgQNZWVmPPPKIUqmcNm3ajz/+CH0NBC7KQ6+NUlCpVCqVKjExMSkpCdanIoTANwDP8xUVFbLeq6urg6Tq6+uDg4NtNpuzs3NwcLDZbEYNUaMIoZqamg4dOkDfYTAYYmNjoURms9lms6lUquvqpUary9fV1c2ePVsQhBdffNFqtYaHh0uSlJOTo1QqH374YYzxhg0bqqurQZPb9yMmkwnK0nIf5OTklJ2dbbFYMMa9evXied7f3x/mnnp5eU2fPh167aeffrq4uLi0tFShUMj5VlVV2Ww2ORSKQqHcZm5ydS2O43ieHzBgwOTJk5988smLFy8qlUqDwTB48OADBw5s27Zt2bJlYWFhoiguXbo0KSnps88+y8zMfP755+HejIwMlUrFcZzBYIBFwZRKZU1NDcxGKi4uBqUJNhbMXEQIgRKfN2/eqVOnVq5cCU5Z0Ef2+Xbs2BEhZD/PxtXVFWbkgLUXExODELJarfJdS5YsCQwMJISA8ScIwvz5848dO+bt7U0Iqaqq0mg0giAYjUYvLy+QDeKtIdoPJJRnSiGEcnNzNRpNXV2dIAjOzs46nc4+HSh1WFjYnj17du3a9fTTT69cufK3335DDVH1sLuQWq1WKpWQJtSASqW6bi3JgDxhYWE2m23t2rW9e/dGCA0bNuzw4cNpaWmDBw9GCP3++++9evXy9vZ+9913IXeIQ3V2doYpmGq1eu/evQcOHPjll18mTZoEwkCEqDyfFaSdNm3aI488Mn369NmzZ9vvlNToQEahUOj1erlQcE3//v1LSkoWLVrk5ubWpUsXZGe4WywWPz+//fv379q1a+HChV5eXnJPD2VXq9X19fXyM126dGlwcLBKpRJF0Wg0ajSa8vJymDcmy+Pg4CBJUl1dnUajOXToEAz0w7JrTk5Onp6e9k9Nr9fDJx9p2AuGTk6lUGCm408//fTwww9v2LBhw4YN3377Lc/zBw4ccHd3v9b75eLiAtNVYVTTYDDIn8HTp09vQZPIwEqyL7/8co8ePUJCQgRBWLZsGfQ1WVlZ0NfYLxtgzzfffLNnz57ly5f36dNHViPyPHWYKirrPZh+yrIs9A4IIb1eD52RHO2tUCgMBgP0HY8//viRI0dgartCoVAqlUaj8bp6qemEWpjM+sEHHzAMM2nSJIZhPDw8bDbbhx9+eODAgTVr1nz00UcIoS5duuzbtw/6kdWrV2/dutXJyQm1og/y9PTkOA4hRAhRKBQwER+KI/faly5dev75593d3Xmel/NduHChPAv2FjUiCoVyA9yM4Q5BjeAYfv/991mWff3111mWHTBgwPnz5xmGSUpK+vLLLz09PUtLSzt37rxv376wsDBfX19PT0+EkIODw08//bR48eIXX3xRkiQYE3zssceSkpI+/vjj//znP3v27IEAaBgbhUxJw453EyZMWLBggZOTU2xsrFqt9vHx6du3r5zvokWLXFxcZFHBt7pp06bVq1d/8803n3zyyaxZs7y9vRFC/fr1u3DhAtz19ddfu7i4TJs2LTk5efHixQsWLPjxxx8DAwMdHBxGjBixYMGCNWvWzJkzR6vVghtDNtPBV4QaXDuowdB87bXXfv311w8//BAKrtPp7NPRaDRjx45dvXp1YmKi2Wzu1asXQgiWTZA9TxCSfujQIagHKHtrakk+Bgmjo6ODg4MtFkt4eDhCaNCgQTabzWQywZoqEO3drVu37OxsuFer1WKMV61alZ+fP3z4cLPZXFxcbDKZXnrpJXAywepmcnaCIEBGaWlp0dHROp3u4sWLIK1cJ6RhCNi+FWk0muzs7H/+859LlizZt2/fuHHjEEIJCQnR0dHLli17/PHH4evI/lFardaysjJ5kTjIF9ohdLr2z/Srr75ydnZ2dXXt3r37+++//9tvvz3//POkYZlkWNpMo9EkJiYuXLhw9erVc+bMOXv2rEajgc+SX375pby8fNy4cfZPf9SoUahhVITO0KJQ4BUoLCw8derU1KlTJ06cOHHixKeeeiogIODLL79Uq9V9+/Zt+n7B9NOrV6/27Nnz119/XbFixXvvvSe/0S1oEgBs4q5du3br1i09PX3u3LkY48LCQrmv8fHxAXVaUVGxfv36qqoqWVTQReXl5aBG4EVGDZoTtHf//v0tFous92AsdPz48UlJSd99992CBQsuX76s0WhQgypACE2fPl3uO8BXjRBycXE5evRocnLy8OHDz58/z7Jsy3rJvmJhQUmEkEqleu+999LS0tatWxcREeHn55eRkcFx3GeffXbw4EGFQrF06dK+ffvK/Yi7uzuUtOU+SKvVDh48GEaPIUdYkZPjOPte28fHx8XFJSAgwN/fX843KSmJ4zh75UyhUG4rNxRYA+bXe++9FxUVBZHNhJBXX31Vq9VmZmbW19eDvdWlSxcIkhZFEZzZCKHJkyfn5+dLkuTt7T1nzpyRI0eqVKoVK1aQhmi5r776ysnJydHRERYFlySpS5cuoNCzsrJ0Ot2uXbsIIcePHx82bBhCKCIiAoLXjUbjE088AfnCYuHyCGlqaqq8jphOp3v77bfNZjNoW/u7kpKSwGJ+6623EEJBQUEQKS6KYkVFxWOPPYYQ6t69O0xpWr9+vU6ngziKTp06vf/++4SQTz75BGLT9+/fz7LswoULvb29u3btmpWVBfLYpwNClpaW/vOf/4SVvxYuXGgwGAghr732Wq9evQghO3bsUCqVMFsoNjb2nXfegdq+bi3JMe6kIcQT5g9AXI3BYHB1dR05ciTUT1FR0dixYxFCc+fOjYmJgTSfeeYZhNCWLVsIIUuXLnV1ddVoNF988YXFYiGEPPLIIxBbSQjZtm1beHj4pUuXCCHbt28PDAx0c3N7+umn/fz8Kisr33333R49ehBCTp065enpCRMS7GPc+/TpA6vLP/nkk2azGZZWeP755xmG2b9/v1wKOca9S5cuEMkDkeVyOiBPo2cKlUwIycvL69evn1Kp/PDDD6F+srOz3d3dIcq2sLDwgQceQAjdf//9RUVFsLb0c889hxDasWNHXV0dROx07949OTkZErTPkc5MpdzLgBr57LPP/P39L126xPO8yWQSBGHmzJmdOnXS6/XFxcXwTd70/dq9e3dWVlZwcHCHDh2+//57Hx8fCDfftm1bU00SHx9vH+MO+S5atMjf3//s2bPkf/uaKVOmwJoHycnJCoXi2LFjhBC4PTU11d3dfceOHeR/1cjevXshEhLKtWLFClnvwfrrVqv12WefRQg98cQTvXv3njhxIrHTzE37DiiISqV69NFHeZ6Xe8Zr6SX7yamEkISEBJj2ChFHXbt2hRq4ePFiQkICQujBBx8sLS2FSEW5H3nnnXesVusff/xx3T4I5mglJSW5u7unpqYSQr744gsfHx+oWPBbQU3Cqgnnz5+HMdsHH3ywrKyMqj4K5Q5yM15DiBdXKpXyWrBWqxVjDMOIPM83DUwURRHiCiRJ8vPzW7BgwXPPPQdLHzb6ikAN44+QLIx1EkKsVqv9FnSCIHD/uzlfs/mCFwF8PFxzm/k1vUtqbp9qOTuoNQhbtJcQPLharXb//v2jRo26fPlyhw4dmq06OR3ZYSzHb8h1q1KpUMPSkAghOZcbrSUAAuXlqrZYLI1WFAapINgUsoZqkQdPSYMvCn6SJAkug1ugJSC7pwwToQghUBZ4Co0Es9lsctCRvTD/+Mc/tm/fDnO8kN1orH2ra/QEZXmu9UzlCoeyMwxzQ81J/hUqpGmOFMq9jNlsZlnWXpnDfkOw6jlq8f2yVxryThTX0iRNs27aidjrE9KwX4esNJrVRfJ50OryvfZ6D4CCyF1AI83ctO+wF++6esleDVqtVoizt69PtVoN4jXbbcn9yL59+0aPHt2aPggKArUBa27a10AjzXytIlAolNvMdTambv4ejpNVFbzkoFKJXSS6rMLgACaywAWVlZUVFRVwpb2ma3SLnCzkIu9PIe+JIx83my/AMIz9xhb22q3pXfaa2l4Y2eiX+wA5TVlCOeAbNvyDuUrXSkeUJLZJdiCYXLeEEFnj2/dYrawlexp1bPbXkIY9OCC6XVbTUC3yDkQQSQ/Z2Stu+1vk+Hh7oxbK0ugp2EtFCIFQV4xxWVnZjBkzDhw48NJLL8HUT/tuw77V2WMvTwstEIogi9FCc7JPljRscWX/K+26KBR7IG7EHpZl4eR136+mSqMFTdIUe+XWqK+Bt76R6dmsLmp6vqnek1UB6EwQTBav2b5D1uGt10sy9jofasm+PmFjPtTgvpGzhgkDsBJXy31Q077MXsE2rcmm+Tb7OCgUym3gZgz3a2H/MssKWj4Aw5QQ8uijj/bs2RM1bOTWwi3N0vSWZvO97r1N77L3fDcrTMuJg0IPCAh48MEHIT5HLiBBCP+/9scMw5CG/P7Ug01SvpZmbGUttZKm5b3p7G5OMHmqKPSFKpXq/ffff/XVV280HfvUriVPswm2/Hxb37QoFEpTWvl+3URH0EJe9pr85mi2/2p0YE+zfUezt7RSLzVKvOnt9onLxzC23GwfhG6kL2tak03zpVAodwo6wY5CoVAoFAqFQrkLuJUe91bC8zws3HH7s74NEEIgiPDPEHaCtmaXV1oEFqMWvpAYhGwS8XNUjQ5xZ+5hlwYsr36tYXEKhUKhtEyjPohCofzNuAMW0t87RBhj/D9R14gcLdbn1loUDG7JcMfYxIuxng6jQtwRhNa0vajtkL9326BQKJS2plEfRKFQ/mZQ12ZLyGu//JUZORqO0SrY6xnuCCGk4poZhYA1yxBCDMNca5iC2K3d3uyqOBQKhXIPIoqi/aoyraEt5l/C+omoYZunlq+UZ/60Jlmq7SmUew1quLcEqE55SS+woW80kEMiSCJEIi2FyiCEJdL8dIOmWp402a2DzqGkUCiURsir1sh/tmANy/Z6W0SY2Ltd7MVoKlJrlkCQj6m2p1DuQehr3zygxIuKip577rn777//3//+d319/YEDBz7++GOEkLx1aKPrb+1MX0jt0KFD33333ZIlS65evQrn5SXA5Mv0ev3Vq1dhtePs7Gx78eTLmspMoVAo7R6CyPX+NecVARv3yJEjsOVzo01SG+lDuBhUa0lJSV1dHWqiz0nr/jUVAyGUn5//448/Ll68ODk5uVmrXe5BLl++bDQac3Nz5dzl/VmbWvyXLl2C0lEolHsHarg3DyjN5cuX+/j4vPPOO5cuXTpx4kRsbCzsAsgwDGz4DDsQCYKAMYb/b6EMoKyXL19uNpslSfrll18MBoMgCMXFxdDHVFdXV1RUQHiM0Wj84osv8vPzRVGEPbphT2+McU1NTW1tLfXNUCiUuxCM8PX+NZkTBAq8tLT022+/hZ1BGYapqanR6/UY4/Xr12/dupXneVEUQYfDPhLV1dUY42PHjuXn56Mmhjtu3b9GQE9x4MCB48ePcxy3ffv2M2fOiKIIeRUWFsqefovFkpmZuWHDBtj5G2NcUFBACNm6devmzZvhmqKiIrhekqTS0tJ169ZVV1c3FZVCofyNoaEyLWEymSIjI3v37t27d2+e548ePXru3LnY2NgLFy4sXLjQ19fXwcFhwoQJu3btcnR0PHjw4BtvvNG9e/dbFXcInwGRkZEvvvgiQujrr78uKCjYuXPn5cuXx48fn5iY+Omnn1oslmeeecbBwSE5OXndunUg0oEDB5544okdO3YolcrY2Nj//Oc/Wq127ty5gYGBdHSVQqHcRRDBjK5jlRKEWcz9zx5GsIvT2bNn77vvvoyMjP79+1+4cOH7779XKpXPPvvsnj17GIbR6XQRERHZ2dlmszk0NHTx4sUmk+m5555zd3dvVklaRMIT0rJvBmOsYTCD/+cMQsjBweHpp5/u3r37rl27Ll26tHHjRq1WGxYWduTIkU6dOs2bN89msy1cuNBgMGi1WqPRWFRUlJWVtWnTptjY2BMnTqjV6gkTJmzZsmXfvn2dO3eeP3/+ihUrLly4UFhY2HLEPIVC+ftBDfeWGDNmzGeffXb8+PHExMTp06ebzeaamhqE0IoVKxISEgICAn7//Xe1Wn327Nn777+/f//+27Zt6969+62yjMGJcuHChUmTJmk0mjFjxlRVVXXq1Omll1764osvlEplZGTkiBEjOI6rqKgICgqaM2fO4MGDT5486e7unpKS4uXl5e3tvWPHjgkTJlRUVOzYseOJJ56gjhkKhXK3QCS+ds8zpL4U4Wt0VRgTwcx5dNEN+BBzakQIatgwSBTFysrKkJCQ8+fPFxYWpqSkPPfcc87OzmazecaMGRhjpVLJ87wkSTabzdHR8cUXX9y9e3daWlrHjh2bDSx8NbPqj1IjxzFSc0oUIyQR5KTAy7p5hzsoJfLnkgOgcnmef/bZZwMDA/39/f/1r3/l5uZOnjz5hx9+WLBgwaJFi/Lz84uKigYPHpyQkPDuu+8yDHPx4kWGYZYsWZKZmenn5+ft7W02m48ePbpgwYIff/xx7969hJDPP//8hRdesNlst6y6KRTK3QA13JsHjO/ExMTY2NhNmzbt2LHD09NTo9EolUoIkZwzZ46Tk9P+/futVquPj8+MGTNSUlLWr19/C2UAV01QUBBsg+ft7b1hwwbYdLZjx47R0dHV1dXff//99OnTlUqlKIpms5nneZVKpdVqi4uLrVZrnz59li1bdvz4cbVaPWbMGNS6lQooFAqlPYAxq4mcQngTwtfyhmAkCYzGDTMc/NVwI+Z5fu3ate7u7vn5+b6+vr6+vp6enk5OTgih48ePu7q6KhQKjUbDsqwoinq9fsmSJZcvX547d64ois3qyfu9HWJ0Cg43vz4YRkhCSMVgDyWHEMJ2kiCEOI6bP3/+sGHDXF1dGYYJDw+vr6+vqal58803tVqtUqmsrq7u3r27g4NDTEwMxliv1ycmJiKEIiIiMjIybDYbz/OlpaVvv/22h4eH0WgMDAxECMXFxdGVHymUew1quDcDzPsRRXHJkiXx8fEzZ86sq6vLzs6OiopCDV1CWlqav7+/2WzGGGs0Gp7n6+vr22LnIJ7n/f39XVxcEEKhoaGbNm0aPHhwenp6eHh4SEiIr6/vmjVrHnnkEZ7nq6urKysrKysrH3jggZ9//tnV1RUhFB0dfd999zk4OFit1lsuG4VCobQhmFGFjLyhG1DDIolJSUlPPfXUiBEjiouLN2/e7ODgcOjQIZVK5evrq1AoSkpKPD09T548mZmZqVarq6urH3/88aNHj1ZUVLi6ugqC0DTpwR6awUhzA3LYYbVaXVxcfH19EUL19fXV1dV+fn6xsbHTpk07efKkk5NTeHj4pk2b4uPjDx8+PGzYsICAgNTUVFdX15ycnNLS0pqamgEDBnTt2vWhhx5KSUmJjY399ddfg4KCdu3aNXDgwBupHwqFctdDw52bQV4NXafTvfvuu8OHDz906NCIESOsViusNjBs2LAPPvjg66+/1mq1oijW1tbC5FT49RaKgRDq0aMHuP8JId26dfPx8fnxxx9nz54dHh6+c+fOzZs3v/TSSxzHhYWFxcXFnT17NiIiQqfTubi4DBo0CCE0duzYXbt2rVy5Mjg4+BbKRqFQKLcDIrXqXxMMBkPXrl15nvf19dVoNMOGDTt37lxKSkqnTp0iIyMLCwtjY2OPHj2KMR43blz//v2//PJLhmH69Onj4uLi4eGBmoxPSgSJ1/vXNIoGEunYsaO/vz9CiBCiUCg6duzo5uY2ePDgV199taSkxMHBISoqys3N7ffff580aZJKpYqLixs/fvw333zj4OAwfPjwq1evKhSKESNGvPbaayUlJX5+fiNGjFi2bFnfvn09PT3bqOIpFEr7BNOg55bJy8srKSkJDQ319vYuLy+vra2FUc78/PyAgIDXX3/9pZdeMhqNERERNTU1ZWVlXbp0sb9dJOTd5Jy8uuvvnFrPi1EeDgsSQliM79mdUykUCoVCoVAo14KGyrQEISQ4OBh81YQQLy8vLy8vhNAvv/xSV1cXHh4eHh4eFBQEv7q7u7u7uzdNBCOE8XUM8RauabRGDezAx7IsBPPAhlDyGsAQ5AMTs+T9Am9u3ygKhUK5e4GF22UdyDAMTDllWRbWcQc9CQoTrpGPURvsnGq/tRPkDjtvyHszgaK23+dVVuOiKIKeByGhCPLxLZSTQqG0f6gx1xIQMyNbw2AZMwzz6KOPpqam2my20aNHI4REUQRN2uxiiyIhgkQw09LOqQxCgkTE5kY/GiVovwOfrLKbbpFtr82pZqdQKPca9poTdKC9woRje3dGm7o2mqpxEMM+06aKWv4VDuyvb3QvhUK5d6Bv/nWwV7iyy0SpVPbt21c+Dwr3WntlOyk5V7XieqEySM0yOiV9HBQKhUKhUCiU5qEx7jcDacB+WLP5KxGqNtt4iWDUkuGOMZEIUrGMq1pBo9spFAqFQqFQKE2hhjuFQqFQKBQKhXIXQGMz2hxCUGtWiSENU1QpFAqFQqFQKJSmUI87hUKhUCgUCoVyF0A3YKJQKBQKhUKhUO4CqOFOoVAoFAqF0ipomIIMrQqZ21kV1HCnUCgUCoVCuQ6EEELu6aloBCGCkChKoighOisPIYSQJBF0e6uCxrjfemDDpjstBeUuhjYhyl+ENiEK5a8jSUQiBCOEMEIEsSyDEDJbeY1KcadFu92IogTF//8zksQLkvoe23+GECJKRNatmMEMxjZeIISolLepVVDD/dZjtVo5jms/+5USQgRRVLSbbfYkSbLZbGq1+k4L8iftrX4QQlarVaFQNN2F904hiiJqT1vw8jyPEFIo2kvfKUkSarI75h2EEGKz2ZRK5b1gu1ssFqVS2X4q/0YhhIiieFdvg9re3scbpfXvb2Z+6dEzV5wcNZOHdGvNYnG3jdv1Fohmq2QRzG/+uN1RoZk8pPvF3OJZY3r/9XTv3rdAlKStR84Herpk5pU8NDpBkqTboIvuvmpq/xBC2s/7jBDCGOH29HmGMSKSdKel+H/aW/0ghBAh7crialfCIITam7uhvcmD2qVIbYTUnpTJzXG3P6y/pfwwZnXmUlFhea1KwQmixLHM8fO5Ft4W6OVy22W8Dm39FvCieCTtyonUk1tP57goI8NDFWotZ7JYS6vqblUW7b8VQZMorzaeOJ+v4FiCiIJlS6tqc0srPZy0ZdUGhNDtKQM13NsEXiJsSzul3lYIIYJEkNRe5JEkwktEcbPygJ+DEEIkCbMsRohIEiESZhiMGYIQkURECPwpwTHLYoQlUUQIMU3cxu2tfhBCvESwSBimvYgkigQhxLaolOA3jBDHtDMzn0KhUG4QUSIci1ftSdl48Iybk1aUJCXHWnhx1pj4e2EgqxGiSF757veSMunBvqNnjI3s0dURIZRyIY9rN8OwtwFJIiyLz18peuuHzYHerlabaDBb9HX1j4zrzbKMgrt9VUEN91uPTZI+T82zSe3JadrOJtRIosSwf2E4SSKYZRVaB95kJETi1FqFxsFmqhNtVoSxUuvIKlU2k0GwWlSOTgzLWY11RJJUOidCkM3UnIegndUPkQhuV+Yv+EJarCIGI6sgBTlp5sUFqFmmXY0jUygUyg3BsQxC6N//GP/vf4yXT245fPbo2dzOHbzumFh3AokQtZLbsujJVTtOGa01zy75roOT96MTeqkVqtvlYm4XsCwjETKkZ+eV7865VFTuolMM7BZZXKFfuvU4IYjcxqqghvutpMEZjIoMFouE2pXp1a4giOCbtesIkRRqjaHwaub2NXEPzlPpXPJ2bbuwcUXXh5/265ogCfzFNYvzk//oOecF/x59jn/xfl1RXu+n31A7ux377HnMcAlP/ItIBLVqN9s7B7779CGDkUWQVBzb/kc8KRQKpWVESWIZZsnmo8lnr7g6aiWE5o/v2zc2lME4p6jyTkt3W2EwFnhp2bqUOou5X3iQJT7Ui3Rasj77iWkdGXy3zi25CSSJIIzO5xQ/9eXvZoPVahEXPGqeOrTrjJE9c4oq2Nvo+6OGe5ugYLCIqOF+TQhBNz3aSBDDsczpnz4rTjvW+9Hn665mn/z2PUcvv6OfvvLAt+srss6dXb7Iyb9D8icvPfjLfv3l81dTkuImzlJyisKkPWoXVwXGhAG7vX0/nvYtXVMYjEQGc+28VikUCqVVYISQi04d4OmoVauXbjk6um9klxCfAG/XjLzSOy3b7cYmiYfSztaUFXg73hfp1WFMn07PzY49cf6KePfPMGk9hBCWYfKuVggBuo/vG7ngvfTTWaUzRjKh/h6Z+aW3M4DqHvpaui630FNI6L+2+SdJotLB6eQPn1ZknXMKDEEcW5x+wqNz7OztqUpHp6LTx2vysqMnPzrhhy2SRIyVZY6+gc4BwaaqipqCHEf/IEffIFEQ7ngp/t7/KBQK5W4HrDANqyWs2pPVBbg7KjiWEGLjhXswxp0gXG+1unn5bjuVsXJvikh4iUh3n3vpL4IRQsjN0ym0HmGzIGgv+XrpCCHSbV979y7wuN+2BYkhF7r+cbsGY95SH9RniFdk19O/fkdEwSkguHLl4uQvFxpKiyx1+pip81iFIvfwLqXW0cHdS7Ra3MMiBatFn5+t8/YnoghTWu90MSgUCoXSfpEIYRDen56RnHwkpEPIPx8ebay3YozvTfNAxeLJw3tbJUwEq1Kt9HLV3WmJ7gAQFxTlF/TkA8M0XM3MgTFjhnSSCGFv+1q0bZWfJEmwPhEhRJIkcGbDMfxp/6u8kpH9MULIarXyPC/b03I68oEMLALaNB042ejeZhdO0uv1paWlFovl3nwt7xYwZiSbNSh+IKdSEUkUzOaAnv1DBow++d9/a1zdkSipXVz1BVeSv3wn9sF5Sp2L1WRwDe5UX1VuqihzC4uQJOle8xFQKBQK5eYQJZHTONbw6Ms1f7AMA+7VOy2UPbdpmJMgxItEsNoIYi314mMfrn57yW5BlO4pewlMx3M5RS98+tt/d5z7bseJ33aevP1WO2o7j7u8BL39F2qj40Zn7O8qLCzkOA6c33q9PiIiwv7KpuvbY4ztd4eRL0hPT/f29g4ICLjWvZBFVVXVp59+6ubm5uHhMXbsWC8vL+p3b79gzFvqCUGYYRkFZywvCu4/vP9LH66dOVSh1Yo264GPXuj68JNxD84z66uQJDkHheQl7UWEdBo9sexsansPbadQKBTKnYbBGCE0tGdnV1cXZ42iymDs2MELY+ygVrYn2/02dWeCKK3Zc6qu3sJgzLJ4RHzElcLy+pgOzL03k68emx0cqq9ke0W5eNvqzHfEVrzFhjuUwWKxbNy4UaFQjB07NjU19cKFCw888ICPj09+fv6xY8e0Wm1QUNCpU6emTp2q1+sPHz6sUCgmTpxICFmzZo1arR4/fvzatWtZlp02bVpSUtKRI0fefvvtjIyMs2fPTpo0SafTbdy4sXPnzt26dYNMMcaVlZVr1qyJiIgYNGiQXq/fvHkzxnjatGkYY4Zhjh8/furUqSlTpnh5ea1fv95oNE6dOlWr1cpi22y2IUOGjBgx4sSJE2lpaaNGjZIk6Sb2icQN8tya2qRcA4wZSeCtBj3GjCQIe954QucXxJtNHfqNOP3rdxUZZxRqTc7+raM//tlmMijUWqtBb6oodfQKqK+uuOnVbCit5M9v8rbPov3QDuW5Z8f0KZRbCEGIIwJGnAIxTirlhSslf6RkOTu0h22/CUJYstRIVj3nHNLWmWGMwwJcFRxLiMSwii+em/jLzhMWm+12LqXSTvBinKpq3SaODsVWpm8vt4aQkNsqQ5t43JOTkzt27KjVavft26dSqcaMGbNnz56ZM2emp6cHBARUV1fn5eV16tTp4sWLRqPRx8fHwcEhNTWVYZiePXuaTKbz58/37dtXkiS9Xu/p6Tlo0CCj0VhZWTl27NgDBw7Ex8ebTKaQkBBBEOQ9ltPS0oYMGcIwTH19vV6vHzt27IULF1JSUgIDA7OzsyVJmj59+uHDhyMjI11dXfv06VNWVhYSEiLH23Acd+rUKchlyJAhCCGGYSRJEgThRsuOEeJttltYmRR7CCBJWg/v4P4jRZtN5xMw+PUvLm7+rduz72pc3BiGDR00xlqnV2ociCgGxg/UuHp2GjnJWF6sdHIO7DMEs2x729r27wQhxGazsSzTphOXYIv19rPuZOu3TL89wFO4OcOdYZi7ceNxCuXWAjHu+1Kz1u1P83HVldUYR/SOcHbUtBcXM5EQZm25e+sv/uo2aUubfqUTQtRK7rt/TduXmqlglf5OxGK2Th3aI/3S1UsF5W2Xb3sDY4wQYRSObo6+B1IOcVi9Jw2dvnj15Vkjb/O6DLdYQWOMBUFQKpXR0dEajcZqtfr7+3t7e0dGRhoMhqCgoJCQkMzMTJZl/f39CwsLg4KC3NzcHB0dT58+nZWVVVlZWV9fP3jwYJVKxTAMy7KOjo42m62srCw+Pt7Hx6dTp041NTXdu3d3dXWV4+YxxtHR0Tt27IiLi+vcuTPP81u3bs3MzHzggQcQQkVFRWVlZampqS4uLn5+fmDQjx07FqSVE2FZVq1W63Q6i8Vy08Un9r63dvJ6/60gGGNOrbXU1Xh07OIb28tqqBV53q9rn47Dx1tqqmwmY8zUOV0VT2KGQQiZKkq6Pvy0JArOgcEqJ1fBau756HPWOj2rUiPSrhexuqsjtQjsZtVmVrV9uF17sN1lMdqJPDJ3dSuiUO4s8OaEebr0DvHVubqquCKzle8dHSII0s5jF+6wcA0Q0UwseoRQWxscvCC8+u3OrKxCUcs6iLZd38e0v4HGNocQghBTYrg6erBP37h+1XWmQ6k5XSM6oNvutbn1oTIsy1oslpqaGkmSysrKMMbe3t65ublxcXFiAwghq9XKcVxFRQXDMCaTyWazBQQExMfH63Q6QkhBQYFarcYY8zzP87ybm1tubq6Pj09ubm7Xrl1LS0thNqp9Fz5r1qzdu3cfP37caDSOHDnS29vbZDIRQpydnf38/Hr27Jmbm8vz/NChQ8vKylatWvXQQw9BCvCxERcXN3LkyNLS0uPHj0dFRSGEGIZRKpU3UQkKuItQ2/0WQwjhlKr8o/v2L3zON7bXoNe+UDo4nvjvxxd+/7nX3JdjH5yLMLYZ6yRRdPDwTvr8NSKRQa9+lnt4V/pviwN6DYif9/LpFV8zSmXUhFmW2mrMtN+1Ze5ejYgxVqlUir+yLW6rkQfc7jgQVtd+PO6ASqW60yJQKHcrmGUQQn3v6+E/MjqgqurdTy9bBUIIqbfamPajnyWJCNa2dvdijHmJv5xpfubZ6Q517Ge/7t1/4KKro05Qtaft4W8HGCHE8NrEiKjEOD9zvVBaIA6Pj0C3ffj31g+Jgv978+bNSqVy2LBhp06dOnz4cN++fcEIhnFYlmXBoc6y7IYNG7y9ve+//35RFDdv3szz/OTJk11dXQ8dOtS3b193d/dTp05FRUWVlZV9+eWXgwYNcnJyKi8vxxjbj+dWVlauX7/ex8enc+fOeXl5mzZt8vT0DAkJsVqtUVFRFy5cWLZsWffu3X19fTds2CCK4uDBgxmGkTtanU534MCB9PR0jUYzbty4m/ackT93Tm1HXre/EYRhFVaD/uhX7/Z+8rX8o3+UnU9llZrcwzuHvLno3NolHYc/oHH1ILxNqXXM2rE2Y8uqiHHTGY4rTjsW1HdodXZGTd6lmvzs2OnzbSYDvpf2e7vN/DmK1Zbfre3tFWuH8gB37xcghXJnkSSJYZhtR9LXn7oUbrUYGVdXRxXGuN1Y7RghRCSBCPWo7ZdUZ5CSc6z64Jc1HlatTVH9zk+lfh5OT84acE9pGDAYo7q4iJIkSpLEiP0SPXlRVNz2BaZvfagMQsjX13f27NkYY7VaHRAQYDKZdDodQqhHjx4Y4/j4eIQQISQwMDA9PX3cuHFhYWFg1s+YMYMQotVqPTw8goODFQoFy7IdOnSA/+vq6pycnAgh8fHxoiju2bMHYtAVCsWoUaOCgoI0Go1SqXR1dQ0NDXV0dGRZFt69oKCguro6Z2dnyMJmszk5OaWmpoJf32Kx9O3b96233rJYLBqNRqPRoLvZ5fm3hSBGoagpyHHw8nEJCvWOetk7usfRr98L6NFP5+M/7L3FGhd3IvCMQllfVZ57eLdftz6wUhbGGEkiq1KVZ57Runt5RcQay++5fe8oFAqF0npYzCCE5naJf7V/H8ZBWVNjgzNMu3L6EIEIFoTafJljTAjHOJjziieMjRHcw8f1iQnwcjl1Pl+S2pfPok0Bs9DPwwUhJIqSg1rVJdgPfrrNCw21SRMkhGg0GrVaTQhhGAaiX9D/LgEJ670ghHQ6nVKphHXWNRqNVquFi9VqNQxAK5VKOACrXV4tQaVSqdVqtVqtUqlEUXR2dlYqlXCvs7Oz/eA1xhisdkKIWq2GdJRKJQip0WhYltVqtW5ubhqNpr05zygAzEWQbLy+4MquV+fteHl2ReZZTqXOO7Jn89OTD338CpFEhLEkiZxKM+StRS5BYYLNTBDx79kvP/kPr4jY8ovp7uFRf7z7z7KLp1mVmrTvMHcKhUKh3Clgxvnvx87WIUmhYNIvF6Zk5iGEpPbUcRCRR0QkvKWtPe4CQk4aS/cAqU7BEwtSYY5rs12A2jm8INZbbSzLIIREiZhtPEJEo1TcTtu9TVYPaLRYO2rOgQ1n5CUd7cNDW/B2yz+xLAvLv1zrgusKFhsbGxsbe6MpUO4gGGPMsSonl3GLVqct/yoveS/Dcj6xvQa/9sW252dUXb7oE9uTN9czCoXSwYm31jMsJ5jrPTpHj/7k54rMs6bqCn1BDstxl3au94nucadLQ6FQKJR2Clhmj0/ryWIWITSkT7AgSndkm8yWIDwiBAn1iFW3aaQ7g1BuhZFVuGfsO63RKObc3+cedHGKksQyzLHzV578dO2ip8cM69WZVWhf/mqD2WK+r1937rbM7ALu8LJff8VKhkmuwE2suW6//SrDMNReb+dghCRJdPD0IQIvWM2IEFahVDu5Wg21RBIRQohhBKuFiAJCmIgCw3IIIYSxJIpqJ9fSc6muweF1hXmekXG5h3aJNjNmOATrn1AoFAqF0gQV9+cMeI7hOAYhhASxnXjcMUIISSJCROLrEeveppmpFOwXz8y0CEYGIQFjB7UCY9yeNqK6LRCEEDKZbdOH9fr01z9W7j/99YKZLz06aurijbqUrF4xwbdNkPb07XiDsHbcxO3y7FiWZanVfheAsWSz6bz9O/QdvvbhoYWpRwJ6DQhMGCiYjCse6OHg6e3XNWH3a/Mu792scHBECPH1Jr7ehDHmlKqqyxerc7PCBo1Wu7hd3v27U0AHpdYJQmvudKkoFAqF0u4AozT3Cjp18SpCpLrOvPHImYLaak9nx/bjbCYSjwhBfH0b92WESGjjrrIvV+/5evUfny3fPf31JZV6o1LBtZ+quG3ojeY+0QFL33uyMK+05/NfrU/L4vKqCcvczqXc6UYbbYJEbvdkhbsLQhC+iVZOEBGlnvNf9u3ZzyUwxMmvA0Fk2Ac/VGZf9Ovam7da4h56SuvuxdusAs9HTpiFELIYDYQQzsExavIcm80W2HcYq3Xwiuxqs1kJYu5BpdOmSITQZk+h3Ev8bZc9FiXCsfibdQd4xtK9S+DXv6z7MSl3cLcOTowmyNsFIXSHB2wxQggRUUBIkoR6hJi23JwE15lNBnTh8YlDMUbbj5wf0C1MEKW/54O/NhDRPbhbpLHe5u/huObfj53OqTJbhY+fHl+mr6usrrttklDD/VYC7Zhj8JwYP8K0mx3WCBFFsf3shihJksALStXNrJEPs5OViV0Eq0W0WRFCbKw/d18/m8lIJFHRfYrE8yJvQwhxPYIRQoLFjBHCbBCrUPDmesx6KQd35etNkijIwyztrX4QQjabjeO49rMuOISlXXdoSyLEUcEqYEb47ZCLQqHcWf7GLzpBCItqA6t3wpJ54Lhhm65s+OGfDz331XqDyXqnZWtA4glBiK+HxSHbLh+VUllSbV2+/RhCyGQVvhve85t1hwK9XFSKdtRvtjWEEIxRTSVesPjQqk9Hunp4D/HwRgi9t2RrVFjg7XRZ3UOVfttgMe7t79K+NJokova035BotbAq9V9IgCCkRUj7/386OTUcK+zOI4RUTY4J0jk2Tq+d1Q/hbVhxMx82bQYopfbRpImIicTA8yISIqT5Z0ckhBmECJIkxDCwxQKSpLZ40CyNuaLckxDehDnVny/X3wt4p+N8mWVnD7z3fb1ZFD3MRKNReLvqSLtYAxFi3AVEwOPetipIxSIPVH0i24oQ6tVBxdusY/p2KSzXXymqbNN82xWwc2peXR5vSdUqxycdT914OO0fE+47e05VVH16UGzMbZOEGu5tAi9INxd53xYQQgRBUijaizySJFkESfuX7FLc4p83dG+7qx+EkEWQlIzUnjzuErqex50ghBGptgg7cyutotQ2EX+EYTmVztlmMdtMRo7jFFpHRqGwGWolUbB7sgSznEKttZkMrEKh0Dry9SbRZuHUWk6tsRrriN289lsjFiEIIY5l7gvx8NQq/7bRAxTK/1K57VGnbnOZ4BHEYr7TstxiWIYhhMyaOGrkkIHvfnV+yjivj54ZhxAa1y/m4KnLCKH2MEWKSDxCBPHmtpZFFNBVhcu4kSEEo7ScXIEnof6eVXrTPRgbqUXKc1es7371c56BPZ1adjr3Vyx6RTmE8NLtG4ehhnubwGDUXgJlECLtTB6E25c87a5+GuRpPyIRjBC6jjwSQQzG9bx4sKDGxAssxrdWoxMisQqVqaLk6LcL/bv1jpr0CBFM59Z+XnrhdN9n3nLw8BF5K8YMQoThFMbykgsbV8TPe6X0fOq5tUtips4NjB+YtXNZ9t5Nff/5js7HXxR4fOusa4yQhJCCwf38XT21iG5ZSrk3IM51WaylSkJ/z09VSSIsx+WXVKQW/yHs75B87uJL00doVQqWbTellQRECBHq2zwjjC4VVy18fBTD4zWHUxiGuQdnNIErLaFLh13fvFSgryHJYpmHrdxW+0jimLBw45Wy/NsmCTXcKRTKLQNjpFUwBLHszcw+bjlpFkni/k9eZiQxc+W3/h0jLLU1V7b+5ujtl/b128Pf/x4pFQgRIooaF+fT375bkvyH7rm3S6pKK04lVYV1ihwwvPp0cuXpZNZicFAqBCTeQttaNtzbz7cWhdLWECJ9pRw9CvtGEdF6N69Q1ywSIRjj1MzCbckZDw5MdHRTf75y75YDWQmxwV2CPe+0dA1IPEKE2OpxG8e4I5b919iBS5df1jvUvDppIFGyzL3omyAIYT1ff1VfMToh+vylg6XnqkWbVMecc/cIuVR0++SghjuFQrmVwJJKGN1SjzshrEpVlX3RYqx94JsNdSVXFRqt0tn1ge83V2VfOPH9x6IoMgwjCaLCwbH4XFr+iUNqDx9RkiSMXYJC62trjFXlVpPBo1OMYLVKGEvkVroIwXBvF4GvFMptg4ivqx/SYadoySb97WwJQgjLMGknks+kZTrptAE625xuXgKx5pWer/fuC1fc8WgZIgmISESob2s5CCHltbVlBquZ4etNIhIl1G6CgW8bhCCMSUUx8+WKi6cvF5w4V+igxC7OmigvYrbc1hHyv9vL1iytH7mGWFU6zE2htCsIQhhjS61e5Pm1s4a5dewy+LXPXYLC9Fev7FrwWL/n3lU5OlkNeswwCKGMzb9GjHmw7GIakiSJt+l8AjWuHlU5GYxC6ejlI/I2+npTKH8dTEiEVChaAxFpNx7oWwfskDp/9oPzZ0uSIGVlifl1552VAZhIxy6fR6g9xLgTJPIIEQKryrSl44DBSINQ/2hFTbXt9z1H5o3v24aZtVfAMvQJ4P45I+7Y2UvFJQZJqRoVFxoW0aWksu52DkH83Ya3mqX1hjjGmFrtFEr7hGFZa50+7qEnrXU1mdtWK7QOamfXhCcWZP+xxVRRijDDqtSFKUmW2urQwfdZamskgZckSemgc3DzLD511LNTNMNypB34ySiUvwESZiKE/I7CVYRZ5m+3qgxgtJoIQgzH/fOrTa98t/uJzzeeuFSsVbePJb8IIhKPWRUR2nxmMGFwfc+gulh/jcIoEA7fY9HtgCRJCKGjZ7JfXbHRK9CF0THfvTK5oth73f4MnYNKvI11ck943AVBkFfplr3v9m542dFeW1vL87yHhwedXkahtB8wQoQQpc5J7erRffY/BYvZWqsvTkvmNA5dH3oqY/NKY0WJb1w8xkxx+vG8I3vzjuxFCJ1a9qXOv4PS0YlTazO2rkp84f2KrLO43azVQ6Hc1YiI2a+ImynVIiJIuH3YsrcOQSQciz9bcuF84cW5E3qJykJPtWN9dSmHSxFyvdPSAQSJVqxyIqIVoYa9XtsGhhB8rrC2zqwgrjNGdVK1p0XYbhsYY0JI5yDPaFftjoPHBnUKiO/sG/+6LyJox/EL3G3sWf7+hntpaemRI0fGjx/P8zwhRKvVGgwGhmEcHBwQQiaTSZIknU6HEKqrqztz5oxSqaSGO4XSvsBY5G3OAcEqR6dfx/eymeoGvfZ55aULKT99rnZ25bQOHuFRR/7zlm9cfOTY6V6Rcaby0tO/fttp1KSCEwcFq1nl5Ky/ekXn7W+p00uCQD3uFMpf4c8FT4lkYF3yeSOSpFu4RlM7gWUwQujRsfHHstQ/rj2m10tOOvbjZx9gserEpdI7LR1AiGhjVC5IEpCIUFsajlaLdH/nhO69XBFCKSlV9WbRSXfP2e4MgwkhEcE+37wy/UplZY/QMKso/VZYOybARcnc4lXUWubvbLiD8Z2VlXX8+PGYmJht27YNGTLE29t77969HMeNGTMmJyfn9OnTNpttwoQJkiTt2LHDaDQmJCT8xXzbW7wNladl2ps8qP2J1Bph4JK2E5tIEqtQDVrwyanlX/l17e3XtTfGmDfXl1083fOR5zi1hlMqEULOAcFuoZ1NFaVmfZVraISxvETp4OQa3KnTyIkaV4/A+AFady8iCG0kJBT/jj873MCdFYPydwUaloKv7W9LP2cLRkT6+7U1UZI4lvnvvs0mCx8Q7CxwbGJcxw+WZg8d4Or6l3YPvHUQRCQBq5yRyBORR2wbGu4CES5WZMcI3THG2dV5oVKkKP2drcdrAU53VzfPHm6eCKGMWutjp8q/V6hiWSzeRsv971z10G9169bNbDa7u7t37NixW7duGzduTEhIqKqqOnPmDEJo6NChNpstIyNDqVTOnDkzPT29vv7PJVFFUbRab3hFfYyx1Wrleb797J5DCBFFUQ4WuuMQQqBiSfuIk2tv9YMQstlsgiC0E8MLYyyKIkKIZdkWHplEkJLFZrOVEEIIIm0wcCvyNufA0KFvfoUZhjfXi4I15sG5cQxrMdRa9NXxjy8QbVbeYjZVlSnU2oTH/2U11HpH9/DlOMxyQ976ylhe3PWhpwWrRbDd+uZHECIEmc1mXkmsIrmz60ISQnieF29qnymO45TKv1vYA+VWQwjCWLL5SpWc6IUIwu2lu7vFsFYm92opZlB85w6vTO8/Os5cVJedlddOtguVEBGxyoVIPBGtCDu0XU7OjpqHx/RCCEmSNH1kjz+zvycX0gLbXSSExdhfwz0e5jLYXV109bbq/HZkrLQRNpvNarVyHOft7U0IMZvNu3fvZlk2MTERY+zo6FhXV6dQKBiG0Wg0Hh4eRqMRIYQxhjM3l6lCoWhnO6cKCoXiTgvyJzDDQ61uH06L9lc/CCGMsVKpbD/ffrLh3sI1EkEMRiobuHtvvdeZSBKn1pxZ9d+TP3wS1GfIgFc+Vju52EzG7S883GP2Pzv0HVJfVa7WuRQc3Xfwoxc9OscNe/trzLJHv36XYdm+/3ynNj/n4pZf+zzztmizMrf63cTwD2OVSsWp1Awhd3aRY0IIwzAqlaqdfPtR/n5ghOqJykSUTwtHEZPQPpwwtxKOZRBC7z428uftexBGs0aPEEQpposGZXucu9wuQmUIIYQIrMqZSDySbBg5tmVeaGvy2SE9OzuqVYIoFVfV5RaWuOraMMf2DMaYwxgh5KlkF8d6YYxzJHI7e+u/v+HOMExlZWV9fb3VasUYBwUFde/eXa1WE0KqqqrArQ4epvT09CtXroCxLkkSy7I31+21w3HqdiUPrZ/r0t6qqDURIBihtrDX/4QQTqXW52enr1zc/4UP0ld9n39kT5cHHj786YKKjHRWqZQkiVUqbWZj2oqve817+cqB7efW/9Sh71BHT19bvVGfd7n0fKp/j0SMmTb9HJIf2x1/du2tCbWGmxsDIQ3ccnluD3ej/BIhLMYGQfxdM3S+tBaJNpFR311FsAckb1Z+rFTOmTAWjkVRlCRitdkwbg/jxZhIIpJEpNQhU5nEWwhBCIltsVQgxthstb33087lW47MHR45evjggqtl879aPyIuMjrY+5bUxF33FoCkBKN56eUDfXUdG0JlbqIUN6Gl//6Gu4uLi4uLS2VlZXBwMEKoZ8+eGzdu5Hl+0qRJGGOtVksIUavVwcHBGzZskCSpV69eqGFvWwqF0h4gCCGEBYs5duq87rOfuZp6mOEUhSmHrYY6z4g40WbFCDEsZ6wqJZLQdcaTCKGrJw506DOUEJFVKIzlJebqii7jZ7IKhWiz3OHCUK4BIQSG41oPxliSJEmS7qIuvxFQ6puLa7pjEEJYpLLpOwtFW8WOI0QJYVGS8N34FORQQAiBaHqBKEkIIZZhCCEKBQOWmUSIKEl38rMYM0QUkSRipZNYdxXzZlGSMJLaYjl3lmWqa40PDunRwcdl3je/P1nFT53Uf9qMYet+Pdijo68oiX89z7vuLRAJUrH4fK1tWZ4eKdhIjAQiIRidvsG3gGFu2J309zfcGYaZNGmS/KdarZ4+fTocw8Iyzs7O8OfUqVPly+4uTxWF8vcGYyzyFreOkQHxA64c3FmTeyl+3isaV/eB//p45yuPIEIQZkSbTecb4ODus2paf6uh1i20s3t41IVNKxw8vCz6SkffoIwtKxEhURNmSSKP/naLYPwNuIkODCHEsizLsnevqwWMxXY1x+b6ECJh7ILrJln2b9JOJCynZNn2Ex16c1xLfvnBEEIQwizLwsAdZu7sTBaECIMkkVW7SoRnkMhxDG6znXnUKqVWi6YO76ll+I9W/pFeWutZZwt2dxEJ4thb0HTvurcAE4QwMhGMEB7vp7PlVMBykBzHsW2vi+6aavorSJJkP9YP7hmYaSd/ZIPnBmJDqdVOobQ7CMEIV+dkHPr4la4PP+UaHM6bjKLISzwPLzZmWYzQwNc+S//1O7O+SjCblA6Oic+/Lwn8+fXLnAOCa4oLjBWlPrEZHp2iRauFLgpJodwcsBwkL2JnYhxgO0tIyN3nab+7IQhhIgoIY6x2IiL/51LuDQt13vLsPJwdu3XoXVBWNXZon7FD+9QbrZnFpTxPks/ktEF2dwFgmwdouC/jPO93U+3Kkm7nZ+vd6qW4IcAWl81xhmHg21q25uEAzlOrnUJpl2CGUxz8+BW/7n07jZpUX12BMEKShDkOTHDRZhGslrOrf+g+6xmVg45TazHLKLWO+rxszLBqZzedb4DKydlSV4OZu9s1SKHccTBCuYJumzLhmfr1DBKle8OWaFcQ0YYwwyidkcQT0YZQG+7BJErkxS9WXSmpkkSxts6gdVTtScpbtPqQk4OqjXJs52CMCEL+au7ZUJdKkTD4tm4dTF82CoVyK2EwvvX/CFGoNSWnk4vTjl3atmrJkI65+7dodE6YEN6gl6wWjbPrvrefupr8h1rn9MuEXkWpST1mPSOYjCyDs3dv6DhgpHtwx9L0E4Kh1j04HAm2NhGSfvNT7iVqBSlJ0TUHuWOprTZGoLSExCOEYB13JNzw0tU3AraJksqxCNWW5l8tGjT3w4XfLrcaXTNzS9i2XDy+PUMQIoTU8tLw5KL55yp1LEPXcadQKHclEkEmXjTyAofxjU0zbBmCGLMFufr0e+sbmL/oGtq5Rl8nEqb7P9/XBgRXlJVGznxW6+blM3CMJqSLk1+Qwi/YYLEiiy1w1FTs4Y802qCxMxRqLXHyqDPf4jgZBmEJIQWDpLtwch6FcuMQgnBnVDrDcvZdh1kjJcLeVocjBSHwuCPMqCBUxtambgMFIn6Oof/ZmBIYVBQVFHH6is3CHOzTcYCtbT8Y2i8iIRzGKXrzH/m147t4mUWJruNOoVDuMkBrOavY0SHu1luvxTAhhA334YYlIkREURKsZiQKGDOK2ImCzSLxvCJ8nCTwIm9VRkwXbVbRasWMM0KIi+4gWMxEkpSdH5AkSbDUY8zc2rUXYAUwjmWclZxEiERQy+lT3zzlrgYjJCLkRPTjrUemOY+3ioKWtui/ApEQZkynvmEdfNQRk+HPFq9HCCMk8QhjxKkQg+xi3NsETsmt/HyWWRBrKsWcPH2NVBji2tUslCedO9dGOd4V1PKSVsu9FuZSfb78dr4B1HCnUCi3ALBFXVSKKZ292zwzwYYYDWJk9aVrckWjnUGc7Y5d2kCg/5kT1vqPFpgf3wbyUChtCEGIQaha1NZg54XGpSw/TaITR/4ytquHWadAdcRkREhrppgS0YYxi1kVwiwR23aVW4JQjanWzdH5Sl3tY5+sUjsawzyvvjAz5o6vrHOnYDFGCA3w0CQPDu6qU+y+vblTw51CodxKxLYPF7GJBImiUnnnTQUiEYZliIQEgWc5Lr3cUGMTOEQQZjDGkihijAkiDMsRUUSIEMyoFVwfHx10d9Rqp9yNEIQZhI7xnp/oHjpkelNpGyXS9VVvARj9OVugVSqUSDzCGDNKhNk2jnEnRCBTXtgxdqing0bl4m5UK7Qa9jJCne/ZeZIYIYKQp5J1ZvHOCrNZlFgaKkOhUO5S2LY3RiGL25DR9WExQqjeYtFqNSJBv18uO1dh1Gk1vNVKRIHTOEiCjVWorMZahUaLEbZYzDokdr+/h1rB8TxfX1+v0+nu3jXIKfcqBCFMJN6GlUeUcWNFQdEO3sW7FvJnYIxgIbyptbcgjCQbwgxmFQynIaK5LSVEDMt8+sz4lOzUFRtPWXlFl2DPl6f0rLMqbnTHtL8NhCCE0elay7tZVSdM5G1J5G5jf0Q7DAqFQrlhoMcqLi6Oj4/38/M9fvwYi5GWxW5aNVtTduil6TvnDLNdOefu7Hzply83Tkm4tPw/nu5upvSkNdP7r161CiH04Ycfuru7X758GbWHDdQplFYDFsoAdOU509q5js+WC6yCTk79ixCJEJ4INoRQK6fOE8GGEEaMAikcEF+PEGqzfeWwhRfeWbusngjOnqohCVEBrr5vLD1nEW23YbOh9omEEEZoR3n95hJTvIuKoNu6p989WukUCoXyVwBT+5NPPuncufNLL700d+48q41HCDMah2Pf/1sXENpl0pzzm1cZyooLUg4Pf++7jJ3rrqYdZZRqnhePHjuGELqcne3s7Gw2t62rjEK55WBECEJOkn4wyXJmBJPNhmmozE1DEEKIiDySBCKB4c4gRBAh14mZkXiEGcQosEJLhPq2FpI3CBdyrtYaa2eP7LLw6aFvzhyi4th7dh0taO4qBk/wdVzcxd1PzfHS7auKe85wv5ZnixAiiuI9O+5DoVBuCIhvycnJefDBB994443S0pKKykqlSmWp01vq9H7dEvy69Ul8/j1Oq53w3y2MQuno7e/kF8Sb6507djFZrLU1NXW1tbGxsfX1bdzjUii3GnA3nuY99jkNW2Jb6sWXChi13ZIm9wSSDUkiEq1/BmEg8Lu39DkEGzBhVoEVWtSWhjshRK3ifnphYkcf5YczB0eHBfMC3z3ancPKe3aoECblvhDqur6Xr5+KceSY22i3/31j3O2Xa7A/vtZsMIwxbKdK13mgUCjXRZIklmXHjBkzf/58dw8Pc73ZZrMhzAlWs2i1nPzhU95c33PO890eflqwWVJ+/IxIos430Gau9/DxDeoQfPTYUV9fXwcHB57n73RRKJQbAxY92S8EfqXre7l2HhHCRPz3NSbaHIIQJiJPJAGJNiJaMKdBCIs1OVjtxGg8Gy1a9f9IPMYMYjis0P4ZHN82pgtYRH5BAQtmTvszZ4mTJELu+U81BiObSJ7LqgnWW71u4+zU/2PvrOP0qK7//7n3zszj+6xLdrNx27iSkAS3ELRIWpxChVIqUJdf5VtaKtAWKF6c4u4SJCQhQBLi7rLJujw6cu/5/TG7SwiR3c1awrxfvMKz88wzc+fOnZkz557zOUesx31P47vlcyqVqqmpwb787g0NDa+++uqmTZs8q93Dw+OguB73a6655qc//en0adMGDBxIRFwIzfArco6+7ncz/vbglnlvK8fW/cHz/vtqKK9w1QuPimAoMyMjOyf7xRdfnD59ujfF53E44j4jS6h2lLXuXuOUjXbAs9oPFWWBHEgLTlPsXOOcX6VWPQG4iZD7wvW4c4PpweYY906EiKRULbesr6wQpIt7Sm7fXH/HloZHdybWxi1/FxaRPWIN96qqqhbrvKqqyh1tNTU1y5cvr66u3ss6j8fjL7/8cigU+uCDD5YsWQIvV8zDw+OAuLeIBx98cMCAAVdccUVNTXVBYUGqsUEPhvRAON1YR9LRfIGajavn/P0XViJmxRulYytF4UgkI5Lx5FNPjRkzhojciT4Pj8MIDgIwQy3/ZeKx3wYvXyhzhRcoc2iQtEhJkpZyhR1Jkdko6zYA2F8xJiUtMA7GmGhRlelEY5oxJgT3JLD25Jny+IK61NWlkSK/sLowVuZIe092A10+/PDDFStW5Ofnn3POOR999NHy5csLCgrOPvtszvmyZcvWrVvXr1+/k08+WSnljsJUKhWLxY477rjRo0dXVVUdYhsYYz3Kbe+158D0tPag5zWpRzUGPak9AwcOPPnkk9Omef+99wZ9vtd/8x01aca4S6597RdXKSknf+9XmaUDqteteOiMMdGSvv2mn7rq9Wf0VCIvP7++vqG0T5/a2lrHcdDRR8Sa6cBtenh8DgEMEaeuTE8fq+2M2HXd3aDDH2k3ibi7pZSUAyfl1G8G1H4drMp2LXVmhNBaHUmPjsG9t55eECryiUt7Z7xRG9i4I95lez+iDHfXaq+tra2vr7/mmmvee++9xYsXJxKJa6655q233iovL+ec9+nT5+yzz37kkUf2/FVeXt7UqVMfffTRhoaGb3zjG+5yKaVptrmoAWPMNE3btnvOi6mbd6tpPeVcE5HbsT1kWqOn9Q8Ay7Icx+khhhdjTEoJQAjRE04ZY8yNC3ccp9vbM3Xq1Llz51bX1Jx6yikAxl/xw60UKh44eOYtj0nbKp1ygrKt0/76wK6ln/Qac1SkqHfJhOlRPvWEY6e//NKLgvPf/e53/fv37/D8VCKybds9a21F0zTDMDq2PR5HGIoxDjxI4xfnnHer+RiX5ADa/kKxPVqB63EHKXJMAKSkspOUricrwYzIl8LcCQApC5wDYFrnJqd67I+fDcwCYCqyqUvDV3qQsdJR1NXVFRcXAxg0aNDixYv79+8PwH06Zmdnl5SUWJaVnZ2NZi8XY6yhoWHIkCEjRoxYsWLF/PnzZ86cCUAIEQgE2tcGXdd7zgw4ETmOo+t6dzekCTdsye/3d3dDmuhp/QOAMWYYRs9592sx3Lu7IU24PdMT7Eul1Pjx4wF89tlnmzdvLho9pbE2bsYbC0aM1wzf+jef80ezikYfNeiUc7Z/9F71uhUlRx0n7NSSxYvPOPMspdT06dPRCW+wRMQ59/l8PeTdz+MIwx2vn7GS2cbY26x7Yg7r/hf6wxgCXFUZmwCSaQAkU3DSkKbTsFXPG7HvdyLHdp3xTA9S58e4e3yZ8rQTEbhhfUPd9sazfV33vD6iDHf3KVVSUrJo0aLc3Ny5c+dOmzZt4cKFGRkZCxYsOO2002zbTqfTAJLJpFJKKeX+pLGx8dlnnz3jjDPS6XQ0Gt1rg+1oRk+bp+5R7fH656D0tC5qecXt7oY00aPaI6WcM2fOeeedF2tsHH/JNWUXX0sEgObf+vtlT91nhDNO/uOdwdyCFc8/xBjP7N2/fvf2F7d+Om3KZMaYewvqjAPpaUPI40iCEYFhilxfkG78me+KIdaqbwLUSZomXw1IWowxIiInBYDS9UwPgJSsXavnjdinsAy5qjIA0wKex71buOqz3Vf1L0gqbVPCEn4vObW9EJHP55syZcrrr78+ZMiQ0tLSiRMnvv7662VlZbm5uT6fr7CwUAjRv39/zrmmaUIIIUTv3r2nT5/+9NNPl5eXH3XUUd7TzsPDozW4MrKVlZX33HPPvPnzPn72UVgW1zRlW4zzi575qM/RJ61789lkdUXu4JGRwpL6HVsrPn7/huuu1TSNMcY59+42Hj0LUvuVMWnGTU492/roV/K1V7Txi3lv1qwR6dE+SJoQPqb5YCUBqGQVjxTzSJFTsxoAsC/5KWmBCQDQ/CAb1J7QOI9DgD6M8fKNH1xVkDohPyMpu04i7IjyuKPZCde7d+/vfOc77pI9P2dnZ2dnZ7uz2y+99NKyZcsikUgsFvv6178+aNCgQYMG7bUdDw8PjwPgBu3MmjUrnkhOHD1y/Kxv6uEMKxmD40y74cZ1bzy7Zd7bZ976pLTMhu2bhG407t4eyYiEsnNTqVS7I/E8PDqR/WiYfJlGJSw97xtidS9rDXCq98hsJwQwkGMyoYMJtwaqStcxEeBZvWTjNgD7TB74PMZdGFCKlGQ9JprxyIcIDPeXBXq//dcpg37u7z1k4dquS9E+0gx3FyJyFWPcuac9PwPgnCulTjrppGOOOcZdGAqF3NVcH1h3N9/Dw+Owwb2r1NbWZOcX1OzY4qRTrsPSbKyXtu0LZ1SvXTZ05jd2fPphMCvHSiX9kawf/exXEY1u+uvfQqGQ5yPw6CmQAuPm5je5kaEXTzmAnokDrgF/8l+w0zfkeeOJqtSHNv1Qbwp098Zzu5AWhMH0sLIaAZDVCMb1grHmptfJSTPNv49oGWkDAgCEj0F5HveuhQB+YW4q5TO3VjcurEvrXTjwj0wj1Z2/bgmE3fOz+4FzHgwGMzMzo9FoZmamruvuap7V7uHh0SYYY3V1daW9e8+bPz+9YXnVprWhnAKhG8maypEXfHPqj/6w6oVHlWNNuPJH/Y47PV6+Ne0LjR4ywLKdZcuWtXgTPDx6CKnP7k4uvx8ADlAdjDEANQjF4Te1aAwGlPJM9nbCAICcFBNB7ouSGQOg0g1gzCicoFI1KrEL+GIZJgLcsPgWjzsT5KQ//86js2FMAW9WOI2kPbOj9h8b64NdWIDpyPS4e3h4eHQBUkohxH/+85+FCxdOOmpybUNjVmGvrXPfDOUUzLvtD4UjJ1SvXxXOKxRCKDO15b1XcwcONaJZtrULzWE2Hh49AwLjICJSZDYCaIqf3hfuwL0w9W40vOPH9ulxX8bDsl6JbO4JQrYXshPMCDFfBu3hcRe5w8isl4ndItpvHxY52cSEJED4GNdhxeHP6oamf/UggIGZUp69RntZ5WaZu2vlGOrCVybvyeHh4eHRTtwZvGuuuSadTv/tLzdOvebnLL/3R4/etWXl0rJLf7jw2Uerdu0cfsX1jYlkwrK3rVqWMXJycdnYpStWhkKh0aNHu6UnuvsgPDyanbh2gpyUStWSFQNj+8tSbU5OnX+CtmInIrtZBNL0PL3thcH1uBshbmS4oTLKrGdcY8LgvkzZuP1LPyEASkpdMwQDEz5wTTmJ5m88ugJJCHNpm4kzM1O/H5qX8pJTPTw8PHo+rtc8Nzf3zTffBPDkxtoNVQ2/uOdxRUrz+U9+fyljjDEubQvAqP/3Z8VZ1O+77L77DE3TNaHIjZRpetgyLyveo9sggJHVQE6a7JhKVoh91P1pWZUxqA/E8EyUfTe8pSr1rqJRnhfwUCA7yfQQfFFKVgIgKw4tAEDLGSxr1wH48onQyamxsTaBUcLgQier6yp3fsVhAEgFNPHukIbg2jV52ohjwv6Pd3fdO5NnuHt4eHgcEo7jANA07cL+mWxAtruQlHIjUF23On0uc/25McSbFn1JoZkInraVR5ejzDg5aZWul4lqkTlwP/5bkoxpSP89cG7Q6f1MZIVlvmer633A/gx9j4NCTpJrIWFErPqNAMhOcl8mAJE9zN69ENhb7YeAoIZ7K/TfL4zvHmdwrisr0fyNdwq6ABLAKH8ipurW1ifvr6kb1YUBLJ7h7uHh4XFItFjYbI+HK2sOYXcLLbm+eaUUgW1sSLoxCExw5gYWK0cxke3X8/3Ci5/x6A4IAJkNgBKREhnbBkw+oBEo/Sqdz9JbZOFKMfxU6RUAajcMANkpGCHmy4DrOHdMlpEBQMsakF7z1F7muPuHo2gj8upjSRM+LjR4xVO7FFbl0APb+MV6zuZ4+r6qxn/neh53Dw8Pj8OQvW7ezJUN41wpZTuOzzAaTOefC7eakjiDk04RKcaYEQg1xBpP6p39rUmDFJCKx4koEol0zzF4fAUhgEGZdVwPabnDZe16YL+a7gKA8v0y8XhR8Un3Jk59zfe1mU4cnrO3fTSpyiR4sIgZGcpOACBlMX8mASyYR9JSVoIb4b3Nd+XYzDizJOTzU4ppJFPddQRfNRTAGd8Qlz/fqp+o5efxVF8fOeRVTvXw8PA4DGFf/I+IGLBjx47x48f3Kipauvgzvy5s6RCDlUq+8tPLHz530kPnTCQm5t/y69/MOGrrtm0cOProo08++WR3g55epEdXwABApWp4IE/LGeLUuYb7vu1wBhBhvL2uRE/4NF2XJilvlB4SZKeaVGXsOEmLpAVfFgN0f6bSgiqxe8+VGRiApJn6S0nypTEhn2YoJsj2DPeuggBQyGBnZ8SFHRurN9zcx9KE3mX79wx3Dw8Pj85CSgnghhtuKCsr+/kvfnHzP2/2cQalhOGL796h+3wn/PqW0/5yn/AZAZ+vsrZh08aNu3bvtizL5/MdSSa7W+HOPaKWD+7nbm2XRwsMgErsRrgXzxyk6jfud0UCAUzGb/Od/pI15Mrc2E2ph203K6PLGntEwQDASTHNz7UgpENWnKQVCmXZQD2P5Pg0FdsJ7CHlzgCAkWRCe7hCrYgpv6ZLxw2VOXJuGj0WzgBSw4P8vl678hGzFQknfgD51I5vQJftqWvY36OuSbuh+VsiOpIeih4eHj0QIhJCSCmrq6tPOOGEaVOnPvzwI4225JwL3Wjctb1x147Fj/ynbst6rvs0XyBz0PD6utply5aVlJTk5eW5Oa9HBm5R6pb6dy1B/J6YfY+BAZCJqnA4259VKq0kmQ0A9mkIEgCVekif/ppdUhTik53VUPb+VvZoDWSnmOaDHiSS0mwU5Ky0I5PmVv18k/w4MC6VqPri6gwA4/pf64ovX7RrXoPy67rnce9amAByVEMonF+lfP/blY45XVe59ki7ae4vqaulcmrLn176l4eHR2fDGDNNM5VK/eQnPzn22GP/dcs/w7qQ0gGBpMwbMnLYmRctfuQ/DTs220RlI0elksm1a9YOGzbMMIwjwxvteklWrFhx2223rVq1CsDjjz++YcMGAJZlPfzww/G4J2PXA2CMAMOsmp3KWWRn+wMZdt1GAF+Wcm+Ks1ZsqL11hB7fkA7/VT8jrVxZU++pekBIgfZ9USuZYtzHtAAYo3StBufeav+AADujV/Y56qLdpsLnb0VNAlWS8f/FCzXb0oRBEMrxDPcuQhHA2Nt16tItmVb2CJtoQV260fEKMLULpdTu3bu/vNxxnMrKSsdxysvLXSdWQ0NDdXX1ng54eLGkHh4enYDP55NS3n333e+///5zzz+Xsh3dF7DTyWBewaRv/XTC1TfkDRsd27nVtOwRI4avWbNmZ/nOsWPHplKpI8O5wBgjokQicckll3zwwQepVGr37t1z584FsGPHjnnz5h36YR7WHdVzvEgS8FvVN5b7frbVF4lkmW5+6pdgDAxQzLg1de/3M7YtSok79FMSJABQzziQttLKU7DXOu05VMb3l+8LO8W0ADcCTPgpVW1ZqX+MLHlmfO7orJDBqCqZwBemMxgArqxjw8k3pxd/s5fWoLhw0u1uV1vp8BHbc66C1uBKgq1K0NsxA+FeUZjH+GMB3QD2mxbSsRxRqjKO46xcuVJKmZ+fr+s6gIqKivz8fKXU8uXLjz76aFeUraGhYcmSJYZh5ObmVldXG4aRkZFhmqbP52vRY+7uQ/Hw8DjsYYw5jqNpWjgcdu9F4GCcm/FGI7dX+eL55Z8tmH7DjY07Nmf0KjXNdP8BAz594fH6WPzCCy549tlnj5gwEsbYUUcdVVtbm5+fbxhG7969DcMgIl3X+/fvf4gRjEopKeXh21dE1M3td33AjBMRktVn5Wov+LIaKcjq1isClNzbFCQFJpRjEZFieoGmhqhyZWcpglJyv4ZpD8ZNRDkoRMQ5czM0lFJtk9AhBa7ZW94maRkDZkI5e3WUslOKaxIGhKHi5SnF/VpYKJmriSdCc0obtyhFpKTiaJnzkFbioQHVyDaIIJimnJQiQMou8McqRULwlq449A12/1XQFghQRKND7HuhbRrXAnBmZTRs9RsgpaRibTyKdry0HFEWqqZp27dv37x5M+f8sssuW7BgwbJly3r16nXKKaf4/X4pZWVlZSwW++ijj+rq6qZPn75r167XXnvNsqyTTjpp+/btU6ZMWbFihWVZU6dObdFdbgc97d3Ra8+B6WntQc9rUo9qDA6r9gghANxwww3nnnuubdv333+/SqdeuPb8027+37AzL9r4/mtPX3Hq4NPOy+o7MF652y+4rhuugVtRUeHegtpxsKyZQzmoDsRtyZw5c7Zs2ZJOp8PhcEZGxsqVK4UQxcXF7hIAjuPYtt3WZrs/OVwe+V+GiBzH6c6wKOEDiKTNnNgmO5gI9/91KbMq80X9VlMClrlX1h2RYkJXycZf6+cd21gwK8d+0rknmP6FaQN2GrzrUvQ6Ctdwdy/VA0BEuiZs25ZS2pYlidowUpUDXyS1+ik4aeo7E2YSvEWEhIEkKRvEBDElAoHGTd8U52ZuoDsHphgPTYvYqR1bTcuBssHspp8oaStV4QSf2xTbKfXfanrMTJoSMNPgnW7XKUUBn9bUFbalDllTqPuvgjZD00L6UYEVKfSCL6uyKhb320rapumIttyLiMgwjLY6i48ow52IOOdXX331Sy+9tGHDhng8/r3vfW/27NmbNm1y+6WxsXHbtm2XXHLJokWLkslkMBg866yzPv300/r6er/fP2/ePMMw+vfvj+aaKZZltaMZ6XTacZyD3gW6DPeScKcgegJux/Ycq6Kn9Q8A0zR7lPuhlQ+2LsO2bbTaT9YFHLR/Tj/99KVLl6bT5pgxo8ura4+54UbNH/BHMmbe/Ehs986cAcPMWMPU6/5f1ohJN04YvqumrqSk5N///rdpmm6cSVsvFiIyTVMp1Y4faprWgdeC2/h4PL527dpzzjnnrbfeKi8vDwaDjLFdu3b16dNnzyeWruvt27Xf7+8595N24E7LdNfe7fL5DJz3mswTO2dj8J+Sw+wsoHBY7abZAY2ghb/0CwKY5dPfEKP7iGzN72PCb2jwGYAePBw97q692Mr7rd/v1zTN5/e3bR8kwWAxIo6ABmjhLwQqk0wxpIV/FUULhL9O0gI+4NpoAH4tCNynHVPIa84QSfijezQ6XcGD360erKxEFcv4mRbQnWRAA0SwC+RN3DrQfr9f13Wfr41dsR+69SpoTwWCNKHGVtGcbB9y366zcjM1rvkCwhCdfy86ogx3pVTfvn2JKCsrq6GhoaioCEC/fv3q6upcl4xt27quG4aRk5OTTqfr6uref//9devWnX/++f369bvnnntCodAxxxzT4m5v31NESqnres+xctxnZ88xTN2p7Z7Tnp7WP2geQj3HcHdb0qOGNNp7eXYGB+ifltiP3bt3uysEwpHek46Nx2IArHgsXVsle/c3/IFwbsHyue9edu0V/YF58+ZNmDBB07T2VVF15691XW+H4d6xo8598QgGg9u2bdu6datpmkcfffSyZctOPPHE+++/f/LkyanUoWbUuQE2h6/h3q0SZwSw5PJHYCczek1Gqj4O/dw8/lKVmYd+o6x6J1GlhfJBak9z3O1tIrrY+mBasLBa4Vr9ohspOhiQbm2mw41W9n/LgTf92bZQGYCBHBPSbP6zaQMEkGMKLXju0vh7IvY/p9fpjdt/4vOdU3CmIuKM3ZvsV+YMOSNd6ehRjRTAiDHmmLUIvpsI/LaPoRlaapPmdyy3lV0Q5d7SFR01dLtb6K9tXeYQaYz9dpPzafXI9/uGITPrLNNwFNyx5BnubSWRSDDGGhoaRo8evXDhwszMzAULFkydOnXbtm1SSjeKfdmyZevXrw8EAoZhnHTSSaWlpbt27Ro3blwsFhs2bFjLphhj7bNUNE3TNK3nWF1olqXr7lY0wTkXQvSc9qCH9Q+ah1DPsUVaVPy6uyFNuI6ZnnPKDtA/UkohxJ133nndddcppe67557Lr7o6WV+jBSO1m9a8/vNvpmqr+k496aQ/3LHh2f8u2bVtcn7g7HPPu//++/v37++6HtqHlLKH5Oq4QTtnnnnmxx9/PHTo0HA4PHXq1MzMzHPPPTcUCp166qnRaPTgW/HoFBgAsuJO7VoG2Mn684wt3xzEz1/ZWKj6PGhWO7VrtVD+XiKP7l1JY/QX8zFEzlwn8QzG/4icwZ9/6fElGAdAyoZymv90e5UAxpUVg97AgmGDv24O/0bjXddmSxhwCBwYERYhswJWY8v9xa21mqUabu9d840BIyKCxXYEZMrdsncK2gIpMG5ueIUHc/Vek9EWs7vBgakIhl/ZOccGVlt+hq66AHrKk7hD4JyXlpYC6N27d15e3uTJk994442ysrI+ffq46aqFhYXTpk1bv369bdvjx48fMWLEq6++KoQoKysDUFZWNmnSJBxyBG13vzvuTY9qDLz2tIIeOIS89hyA/bXH9Us5jnP77be/+uqr9/33v48+9qhgAGPC51/3+jNFoyZ844k5NRvXVK5dphu+vkefWFFe/vqbb44bN66oqKjdOu7UzKEdVkeiadrUqVNzcnIAFBYWAujXrx/nvFevXj1n5uSriHJkskqmapzYTpWs7qtZueHoNwp9vmCuzBoud84HsE87QUpnEe/bQMF8gW/qy3LS5fDM9v3SbA5KC8reSxGSuR53Zf2wX+T1ydl/8i14JFn6WWgiQQoGAPcOD//WetZOm9zdFABAKeTKum8XpkOC7bBgcj9zXwm8k9A2GIDkknuTKx4FsD+xzr0QYAAuKxQ/1j6VWpT5sweiLk/ruvttj3DJdBRCiOHDhwMYPXo0gKKiou985zvuV0OGDAEwePBgAOedd17LT1pWaGhoCAQC2dnZ6Hmpbx4eHocjrrOZiO67774pU6bceuutRYWFABjjdiI+8KSzQ/lFdiopAoFwbpFjpnevWY4+R69auXLm6afX1NS4Zu6RQUtAS0vUvhuReFhHuRzmEMBIWsxq8EHyik8rpPg+u+LvCbq0JHR+L8G1k1PLHwpN/vlePkgFcCDm4Hrj4p+komdm4r+Bt61kGXAOb1es8FcFaZO0QJKUyURgz65S0gyQeVmfIDLYbj14WfCyByLaWEgJIQCu+bkWVKla4PMYG6bs3RTZkIoW2jjvs4a/p8RRXCqAN/nyvbPQCojAGDlpkimVqARaZkIO0nvuBTEtCmBZSrsmwEzTSsnWGf0dwhHlcccXFdldgaG9lqA5xtp9kEgpXUmj1atXDxkyJBAI9Cg3lYeHx+EO53zKlClr1679x803/+j66y1FDJCOnTdsdCivaM7fftHnqOOz+wzIGT99dN9eZWXDU8nk/PnzL7nkkqVLl6In5eAeCntWTt0zssiz2rsRApDY2Wjk/7/s6xqr1n5qZb2ljxGcBwXP0WEUjlVmg3TLMH2pJGqa2ApWEicdwGI+sF7p8Aow7Q8CAJJpKBvSgmPt9RXseKOIvFMjEoT1gSH97c0TRRVgKCIAL1TTb7QzVLoWzUr5CmBIzebDrthRQNL5pDa1w9YMKOVZL22DAFC6luyESlWqZCUYa03xX3eVBXXWbNlH133wZTAn2bkt/SJHmuG+54PBDVLfawmaY6xd348Qwn2cTJ48eeTIkfAeJB4eHh2H6yCoqam56KKL/nrTTRMnTkpYTjAzmzHOGD68+ZfBnLxpN9yYbqjNGzPl6ptu+WjunPETJu7ateuEE0547rnnurv5Hkcsro1np+p+rF14G//a/fbwnKr51wY39Alwqei7yypfMHtHs/ukNr8JfCGEwDVtokjfmbrnuKiSwBXWjEWiP+Ao7+m5bwgASZOkRcohx2xZCEABwoltYLlfX8OqCGO1mqfrfjuINwDgpABsS9PTzuBY2jUNm2026SQgAoJn6/zpidljsjITts1Ve3TwvsIQAJWuJyupEhUqXg4AOLjj3CEC8IsNqdswRdMIegZIkuo6D8uRZri3G9fv3t2t8PDwOKJwA0Kuv/56t1TzO2+/LUite+s5IcS2ee+seenxguFjVz33kJWMh/3GO6+/Y5nm+HHj0um0m9Xa3c33OIIhBsRT8TfEyBMLlKhfd9TOx/8vcz0DBGef1CSerPNrecPj5Qvd+kwtP3M/Bcm80J5XFOAAlqOwUgWBLqz5fhhCjgllQ9n0BfOaAMBJ2YozrmdwGMLXR1YoXxaa7DOamskuy447se1AU+9zgIjPsD+7s2/cL/j5ucaQzEjatpm0Wzbp0UpUqhpccH+2U7+F0Krec+3mXKGKeQrcgBYgzkHtTElqB57h3kTLNK6Hh4dHh6CUEkLU1dWtWbOmvr7+4osvvvW22+DYCx64tbG2eseyhTyU8dF/bnzvLz+NNzYawfCCefNGjR7Tq1dRbm7u/PnzL7zwwu4+Ao8jGAIgY9svw6L7xhT+MPXc5rRKh/q4dsv1A7NnZDHW/+TcxpU8vh2Mtzjd3XiYRiWe1I+utoUAHsv8eFJ8PmB4L5oHQpqkLFLOF0JlAA7YtjVMi702JpgJOHrIEkGuB9Ek+qPGh9kt/VLhmmXY4/1JKepPFWOjALAwphanDJ1Jcg13j7agkrtFqFArHGdVr2JAawoRuEnDf+1jfY8+clgImsGED6rrOv+ISk718PDw6Dm4YdzRaHTevHkt8rJxS373kddNqXp/60cnf+vHTLgyM0gm6r/77W+dPazIVur6G2743rXXBvx+InAhvFwzjw6HEYEhWLf6374qf+TKeYVfPx/DHxQFpwKKcEnvKIBndgzfaE35Rm1labh3yyB0P1Qg/APfFc+mtGk+XBTama5dC3BvlB4ActJwbADkSrnvgbRTeYYqLfADgBbgehBaEGjqcQmsY/0jZjKDpFtciQBO6ZfYKFabcUEm/ry+IVSp38egZIvyjHcqWgMjwGnYITL7+wtGY8PzjlJaq1WPB/jiJq8j7oNGTAt05VuTZ7h7eHh4dCKc8z0l3oO6+Omkfp8H5rkTfUREFDI07ga/AwG/v+VLF/cn7sSgJ8bi0SHEzKQV6N0bqCucHq9IjszwA2CAQxAMKxPy95k/sMp3/bZUEhN7DjgiFaZUQDAAb9CQArZxLBR5tvu+cWPcLTdIptlw/7yQk6GS76UzlmxmN/QD14JcDzHN737FmLAUnb+j9GZWXGLXKyPHnfsQKnG3ODZdFbmgP0oCYgcLOMrRutDpe3hDBNYs0hnbLiK9Ze7wny7dsXVJ7IlR4aAmsP9XHwIYGIC/b8FAfdw5gqAFmRaE7LoEAy9UxsPDw6Pr4Aw5fi03oOUG9NyAnusXuX4tN6DnBQ2Dod50Yg7Vp60G024wnQbTbrBUylFoFpd0N+JZ7R6HiGQa4PxLnPBNdhEDTo6kFjdeVxAOA2AMGgMj9bshOduHrbl4/W9JyT2q/xCA3k7FM9btI0IA6BfJCS+J8VDJrtPDOxxxUowLxgVkes/FBHCVnpOK3r5DAmBGiBlh13B3rUeN5Co7Y7v0I1XpBmG7BVeHqZ3HRgHgVwMzbhoUTltmV0ZrHF4ogtozeJ0xAmOMSaC6sTIUjj7FJ/xPO+aSaF1QcCI66O3VJtxTaSzTBzIGiADTA+jCzGDP4+7h4eHRpRCBMSalsh3b7/MRQYE42OKa1KMrdgSULYIh5Tgg4pzFEqkTBxScM6igurY2HAz6/X4iqq+vDwQCfr+/uw/F4/CEiBiDXbfRDurhMACeO3rgWffBnw1gT29jSfGopLCc8k/0kmlumUlGAIOhUsNpt8EYwPJ1puwUWmHufEUhgEE6acX9glGzqkzTdwwg2wxr4uhMDQATBphgmg9NMe6kCfHCCN5/bpWM1/AoAOKAVNpPrFeySr4JoFBHYUaoWtqQXZcfeXjx+UwQERiLf3ZPOJixqNeFlyypmxHve0sw+/RcbYy4azQuBOvLSB001kgBR/kTA3k9hA/Mz7RgV4bKeB53Dw8Pj67DNZm2b98+fvy4XkVFixYtYgxKKsbQ2Nj4yE++9bcZ4z95f3Z5yqnmgc8++fi+718ct6Sy0oX5BZdeeimAJUuW5Obm3nHHHThSVN49uhwSgDLNS5Kv/jSvFoAwAix/DOOf+/JcyfBKX8lvMr69ZdsiAOTK54EBKOdZf9DPqnUA4I7s1ZfEXwIPePbEATCcWJYOJgxyUsDn6iUMSKZi38pufGxkGACLFBuFE/geb1AM7Oze4SF+x4rtZs2/lEoVqtqoXwewPiV/tw2SFMiTg9wbt5vXxq0VMRPNo9raOd9c/9KierOQJ8/BSqXn5mkYGQ39Ydn2h3c7YOwA0jJuxrCP4f78dTPVCsmCAGd6wAuV8fDw8DgycU3tG264YcSIEb/61a/++c9/AlDSAbDhvVftmt0TL/nu4jtvNBhim1cv+OevVbxB13UzncovLFi5cqWUcunSpZFIxLK8h7RH+2EArPjZiXdPyA8A4FB71Xtvisggul9Me7MOcBqIiab3TmAbz/uzdm6jQwAG+uwip8JTIdwfxBhAG+zQX33npET4y8V6lJME1wgAKT13eOT4vzFfFAAYc3/7ccz/kSzi6Wo0C/Bzsq/zXfZYlR/A2pjzxw3ppFTNOu7emfgcSQTg9s31P11VDUASAAiQrFz67WL97ZFsPMplIJcAyhq0urbm1q1pdxrkoJhmUnHDfdf9PFSmS1TFPcPdw8PDo4sgIiGElLKmpub444+fMmXKI488AkDXNABbN6wrPea0URd+y3EcO5Vc+/qzeYNHBrLzSMp02hwyZEhhYWFVVdWqVavGjRvnON60uEc7cX3nsXTyCT5ht1YM10z/ohAeAwgoMNi3+mRoNctUzWoGAMq1aaJO7Sm0IkNnAJ4y+zwjJnnu3n2iAMb4vFprzPqStyMnceGDnQD20OgBDMb+3NDv/t2yKWPSCO+1kVu3pm6N9THIav4FLGKv8dFbLQGgX0ic3iuchuhKp+/hgptIGtJ4vaUAcAYix7aTC1RBQ902lihP6pnCnw2AZQ2YZWw8Juqa+vu1vwkA45U2rtzdZ5kxhAsGgGkBkFeAqUP5cmUld4lXccnDw6OLYYyZpplKpX7yk58cf/zx//jHPwA4UgKINcaE0JRSvnBGorpiwtU3DDnzG3YywQRnAGds0qRJS5YssW17yJAhnuHu0W7ccJctTvBK41vbpStgsreTkTXbln8vy7kyXJHe/gkDAMahAAxMrX8YT2ZqDMBT6eKH9WOg0t4D9cu4kRX9QvrdwbnPscd4IMey059/0/SJnkn3Wt1oA1zRF7y2rpRU3wBPiYBjxt1lAJRSlzjzjo0SgGEh7X+jcnK5bTtecuoXoObo9uWN5oRMHwESYDI5F/3Pifx2V+VGJHYJPcj8OQxA0fTj5epb8jawPaoW7GObBAANNr2WyEpqmeA6AMb0rswMPvwMdyKSUiqlWj7TF0FzmfGW1VoE1NxJaldJTSm113J49VM9PDw6H5/PJ6W855573n///RdeeEEpZRgGAJ/fDwbGmXRsrmn+cKZjNgtQMGbb9rhx45599tm+ffvm5uZ6hrvHIcAApMxYL54YGGj+e5+QssEq+81KbH4HUC1eeSbNoNaU8jctkBgtt8A2WyKwPVpwo9R7+fil4a0LrMyTnYsrEEHzu5OLbcZnZTSekqs1JfjuoRnFGUDyJ/39/y7YlY5XolnVx6dS/0++MjUKABzwa5rkGvM87l+CAZKwOeGMyvCx5nzfVzB0Om3sXzvXjJUzPcg0H4h4uEhlDVu95sM6BwDf3zh2B3mmzn4YWNOHql0rWmQPZoFc4IsKvp3G4We4u3VMXF1k9zP7ImjWTWtZbcOGDZWVle4S12qvq6vjnFdXV7dsxN24Vz/Vw8Oj82CMSSmFEJFIZPfu3aZpuvecxoYGAL1KSnavWLR7+SKzsd4XzZK2yThnQrg/JMKwYcMef/zxcDicm5vreiU8PNqBAAEYUDfvqfDsTIH9BfW6fq/1SXlR9chtFoPdqJotziX6wLNxpaUIwLeiNT9x3lTWF3IuPdAcYD27Kn3uZzWptFnk1zaz3EppoDlL0rXC7XTtXwp3nZKtgdQ+lPAJWQwDQoay4i3LHKUqWdQh176kH2xWD8jRGsUVvFPwOS19eXlp5MOadJXpCEA69ves1+/I32Ylqqzdi0QwF+77KSg65MzrN/H7yh0wJvdSkGzZJgOUytPxl8DcvqrSXSiyB7NQcdccFA47w10pVV1d/f7772/cuBFAKpV67bXXampqampqqqqqUqlUZWWlUqquri6dTr/xxhvr1q0DUFVV5TjO9u3bX3vtNcbYZ599ds8998yfP//OO+9MJBLbt29/4403pJRSyiVLlmzZsgWHHEXTo6z/PeWfewI9qjHoef3j0qOa1DO7qOfQpv5x17zhhht+/vOfn3LKKVdddVVDQ8PoMWNidXUjTz4rtnX9az+/cuQFVxmBsJIOOY7ZUKekBFFVdVVOTk4ikQgGg5zzxsbGA+/CO2Ue+4UxANmNa8ZHmuad970WALBiDXPN3NWUj3Q1NRvuuxF9j4YqIgB+TQ9wKHvvnEsPtws/rE19UmvCTvSLBP+SsSo/tREttldz9y+RBQnCl/VMFADO15r0q9gIyRgABQFgkyg6xbhhbZozEMC2WMbzaihTaXh8EQIEww/7ZT25M7Y6bjFApurHyc19+k8xYzucXQtFRh8AAJNgorAsHSh6u9oEoLF9lxNzy+AlCQtSmWkjq2mptEBdNwV6+Om4P/nkk2VlZa+//vrll1++YMGC3NzcxYsXRyKRaDS6devWxYsXn3nmmRUVFaZpMsbKy8vz8vLC4XB1dfWuXbtycnLmzJlTWFjo8/n8fn84HE4mk0uWLCkoKPjwww+HDh36xhtvfO1rX3Mcx/XNt898V0r1KI02NxaIt7qQb2ejmunuhjTR0/oHzUOo5zSpR41nAO7g6TlDqK39o5SaMWPG/PnzTdM86qijADzx5JOGzwgVlpxw04OidlfeiAmaP6CkkzNw2PG//qcvEg1Fxb333NurV6958+YNHDgwnU4nEon99QMRuUOoHba795L2VYDAGNl3W2VO5sQfAPsrw+tGBWQY/LHhvOyjapms5xEoEMAGmBt+rtcKPgjAU4ncl8X5j5IXYL03ruU3IdNfGAg4y2O+/Kzva1tl9QY0+9rdWrM2N2ZVj/lvo5wWFYpI7HE2FIEztqnR/mv9oO9nzMmGIi4AJGCU88xgU6wAritiW/2bHbtAw0ElyL9aMMAi2py0+4Z0dy4iZdvXGd+8ITSmRIjGVLVruDPOGSlEy/4v+FQ6Vk24ZksivazRObto70RhRRCMr4zJi2PT5xR82rwb1pX9fpgZ7kqp0tLS448/3rKs7du3b9mypbS0dPXq1aeccgoRGYbhetbD4XAwGKyoqCgrK8vKytq+ffv69esTiYT77fDhw4cMGTJmzJiKioqqqqry8nIhxPbt20tKSo455pjBgwe74e9KqXQ63Y5nmGVZSqmW8Jtuh4gcx+k5Vo5SyrZt0zQPvmqX0NP6B4Bt20TU0wz3njOkbdtGT0oub0f/KKXGjBkDoKKi4qWXXjr+hBN9gWBsR3m0V2l04GDbNHcunh/KK8zuOzAlad4zj8789sXTp0199913J02a5PP5OOdCiFQqtc+NE5ErFtnW2xcRaZrmBtx7HOGQ86g1tCwwEiAFtt+xS2CMXVTil0bcTlT7AUEKjA9Or73RWA92NYBy6X8Vw+A0aZ54dmMLblecURACULsw5tN8c9QoTSWOhgK427kAxZVY52Q6as8fNeE+A/qFxRk5aTNpwklzEQTQy9r5F/V6oTHVXf+0LIbAJmmNPMxMuk5GEgTD2rh98vyd700tHhY2AOw05T1i+lU8PKhwbEP5YhHpBQBgHASmH13Ui298BuqKZTE6Z8HOxjMHRYT7ZvuF81Jrqk0yyzCC3XFYh5vhTkSRSMQ1ixljgUAgKytrzJgxpaWls2fPLi0tHTZsmFIqPz8/Go0yxhYuXJhMJkOhEGMsGAzm5uYWFBRIKR3HsSzLcRxd10OhUG5ubn5+vt/vbwmCB8A5Dwbbc1Y457qu9xyrC4DjOJrWU861a5IGAoHubsjn9Kj+AcA5Nwyj5zg+3beanjOk3ZOl63p3N6SJ9vWPmwp/zTXXPP/880W9es15d3Z2Tl9zeTn8Rrxix5u/+taJv/13dv8h6568e2l1xbSSrDPPOfexxx4bNmxYOBx25wMPcBEJIXw+36EemMcRCgNAbLi58uTwaCDMiPaXVOca4uVOZA4bf1a6rmVJnLQ6lj8AADA17FyLBdKazJscyT3lxtUTIKJKi6I6Y3bSEPwecWwjjJfIJuZjTXa7CtoNz5RuHRUZCyL+xRPBGUBqSIA/NSCWXlypHItrQQDF5vYf4IOWnnaIFupD+pK/pNmL79FCwlE2qRxduIM3nao/h3YWh8souwxWnIeaDHf3ElCDz//nyg3nVldMzOk7KGKsjJmTs75wm3XPyPgM7VnfMz7K7IbjOexi3AGk02nOeTwez8vL6927dyKRaGho0DQtGo1u3Lhx0KBBixYtys3NXbRo0aZNm2zb1jQtmUwOHDjQDYxJJpPhcHjt2rU1NTUbNmwIBAKZmZmJRCKVSgkh3ACbQ2xhu2NsOgmvPQemp7UHPa9JXnsOTDvao5TinC9evHjx4sU1NTXDy0a8N/udYMAvfIG6Levf/eMPuabpoXCyplII3n/qieU7t7/+xhvjxo0rKipyHOfAAS17Smx5eHwJAqBSdf8wHz8vWAm3+tJ+cIPAlsXpUnlO3LIBOBCA/bZ/0nT7UqYcAJPC9BsxT6Xru6LthxvE2OgPtr1WkYggBSNjdIjSltmUmuquIO2Q03BebjpbY/vLEmYAD2RL5TAn5V7VW3nOM9pUaslOkOYl7JLn2SjAUT3G49PtuG8wg8PGE+OL/rut4c5NdQCGmWsf4k8V+7jKHh4YcDoP5gHuGycDgGD+L6LX/mwTemnOW0f3HpMZcKpXUbIaQFN8OwAg12Bf4yu1/c9UdSqHmeGuadrEiRMBTJ06NTMzc8qUKUKIcePG+f3+SZMmHXPMMYWFhTNmzAAwbty4QCAwceLEAQMG9O7du6ysbOzYsYyxCRMmBIPBmTNnuv9mZGQcddRR7vLc3NxRo0bBS+ry8PDoZNybTGlp6QsvvJCdnU2ggoJCpUgYvnjFjiEzL8zuN8RKxn0ZmY5l7Vq9jHFt1apVxx57bHV1dY+aHfI4/CAAcFLVcT1LGREAB/CRczAAA0KiT0CsS8rmX5MlSXHN/Vka+kZe6DieFuEXcE3qRlsmHMrWSDppy593mb76xuRDxPWWVZhM72CZLyeKzH0lp7rlftIKV23Pe4sGMqfRAQD1gTbiav0ypqR7CnyMJvkTy+IKh51V15m4nZOt85PzgssarSfKYwDMdMzUMgBoOUOip9/HjJC7LgOIlAZ6vHf5xdtvAahvUPObNY3vXGdufhOAK+7uEIHxzSl5f3oIC+Z0y3EdZg8AxlhOTg6AvLw8d8kxxxzjfggGg25kS//+/QEYhuF+RUSZmZkACgoKCgoK3JWHDRsGICurKSP4uOOOcz+4a3p4eHh0Kq7h7t6Ubr755lis8bTTZ35UXe8kGksmHlOk1JpXnmQMRiCUP/mkwt2ry8rK3v9w7rx5855//vm//vWvo0ePdmUlu/s4PA4/3FiWJXH8yP/DJ1SodE959i/h6oj3C4o3w69mxqqAK3VIwJiQXHSrP1PyIQJYk3RO5d/7EBVDvRj3PXD7Qefs0fEFI8NI2VZQjxTIygJrZUs/KYCr5DzW/6+VJQsk+bR9RC0RYHB8kgpkq6KLnLj74uTYyVIWa+lsWwv9WsyFLQhjuvIYDwQRQPsfWV2Bm0mwOm6vakzP6hVaFdMB/MWelIiMvx2QYEJ8IZ6QgcDE+aW5saVzUb9hnjH0vcWLr67b4t9DiFNjDMAHdc711vRL/F18QE0cfu9mexU9bSmZ1DI13JJl6EqXMMZaVmhZ2f3g/rvncm9y2cPDo2twU1pff/31+++//43XXzcCAXDhj2SS49jpJADGuEwn80Yf9e2/3vzR3DnjJ07cvXv3iSee+Nxzz3V32z0OY9wH5NIE326UhPRWyZBoQJ9wyGfVo/mdc2h63df9G1wDIiiEJvQK+/NSoB4thAQ/uyCYI6RFXBd8l1bwff2SLWm3rwhEkFZaUr7BQ2Kv4ksAwNysMOCX/QJT7RUkHR0AxMmpj/7LngN3X93JYdoQrXG0s4k169V0P4x1r9UONAmxv7gr9p0VdecURX41OAfAPPQt1wrQJIL6xb5iAqRU5pB0dLDa8HIdsT9WZm7lOYZd17Lem5WJBlv6GIoR51r35PEffob7XhLFLSWTWoI+W1LEOOctdZrcf1tWdj+4/+653AuS8fDw6BqEEPF4/KKLLho7duwrr7yyddvW1O7tW+bP5prOGCcpXUdCQNfefm22aVrjx45Lp9Oeo93jEOEgAEOtDb9gc3ICoYMa265w+yv6Uf8QJ8KJKyYAuUyUPC9HMBCgeoX8/8CrpenN6DlWYw/A7YhlDeZb1WllxZjQmTAkN/6nHb2wkQCACc6YkjjL/uTxgQm/mzL8pe246apXlobOxirHSrsrlDq7JvJdLfvRoOp9xX+LD9poftka7XoIgF2x2Nr2fsuf3YJrC2b4/SdjY2zLu+tSRMDF6XcuoU/RdCF8qb+JOBeBognJXYun8dqZxi7y56p0g/ulTTRrYfncOvvrOenntSfl/gusdiqHn+Hu4eHhcbjjTgwuWLCAMfbiiy9edtllixYvqd+wYvVLj2mGzsH8GZlC10mpcCi0cMFHo8eM6dWrKC8vb/78+bNmzeru5nscxri29fT0J9eqDyAMkDqwx8pN2tvtL/63PKoynmAAKP2SNvHH5rFu1G9Q4GK2tJ+1BcDeMdpfYdyyqf/aVPfzNQ1cJRXTlPDnsvRMtcxQpiKk6rda9ZsV17JVrDTsAw5k4iaktkT0Mx23yo/6nxpxr3Y8oJpSKsGEP/K3xn5PVyiA7bPkZ9dBBMDc+Fpy6X/dtnVXQ9xAr2/0Ct4in/70wzvPWxJPANekX/ya2ACA73Owcg7AP2Cmlaxh837/uPHquJKByWSdW+e20VYcyDB0ptK5soHrnhykh4eHx1cDdzLw+OOPr6qqapnxe3db3bTfDG1oiClix/7xbnCWTCYTlvz6ZVecO6rEUer666+/9tprXZ1Hz+/u0U6IgeE9Kz8nYIwC9i8F2YTr3js5Ex+aH6ecUxgA4lGndpjeCPRyEyqfNaaWgB3lxbjvgdsPIY0dlR2AUw6hQxiapt9qPZoRvoAz/+urFjy0I/lCxgdP8TFUG70q2hSTvReKwBk+S7JZ2ndnU2QoAHKedgYJvfBbcAADgM1YHuLnsW0+fiaAnnEeOLopkuSLsCwBoHY1aH08vaxWY9SvX6Bv4f7XB6DlDuXBHHPNU/LYvyVsO7zrfQAgFtHY3Gm9+0UExVKKJPS9yzN1DZ7h7uHh4dE97GV8jyuI/Hn6QNH0wGVNsn0KOUFDERhjiuDz+aRSjDHmRfZ5tB0CGOemwo+dU68M7RgFKHYQTTt3mPULB+9L/ieACUAJuP+s5HunFSuwMkUkmPq9cd4kreYoQIJ7VoWLYIxAvx6UxbluVzRowmDcYFxPskBYpZ/YGX+8Jvy6McpKPvOIOUbVBK7qB7kvw93t/6FBJIzMClsMBcBEqazM4wmAE8BAgrEkC//R/2Z+iXB33cUHu1eTAUDZkD2gmC5jf9ps5tfmnKlvem20L+nYV9vnvhl0CpvLX+0DUmBcFE+P7nj/2cC0ezavfVkTbqKtwVCW4QfgOCYjx/O4e3h4eHylyfRpmT6tOXtwrxran7vQRFMaDwFMSumWOwXgOA6aq1N1C26uv5cv1JNx/evVpp000wOybLTaMcv8WbsoGEymCwGA9bbLdSMOgKAAXsaqIjLZec0+TGFghX4DQNqMc6Er4RdcPes/9rkltNFumNmw+O+DozT+5WNXbjGC+1VybNI01PC48dqgeCkwHhA30mtgDJjBXUUNBugBn+Oeke53tgMgkiCnu1sBQD22yzrJCl6pV5+Qk5wXy9kufQXBgxfvM/qf5jOMrKzeH6RrKwN6xElBC75XndyWNC8vzYJjQdpMD3XBAXwZz3D38PDw6BE0P3GbHt+u1hUDllQnZ1eaupWybYsxzkg5mj6+KPukouCePvvu1Xd3TXbPXu/hMEYAy9HZf50HyozJaJWRxxTAmXwofM726uL7SwGyHteOrjIn3ABwxhyw3/E5enIbMF2wHmI3djPu5VAVq/7j6upvjxo63Ekkuc6EDqEJ3fdBHc3Ms39nvVDU7yQI/tuRfd1O27+nnDjYjEAVpZp82LZ0NJ8bp0FuULlf018xc19cUnfXiGhE4915GtwdK0lSdlcTmiGAz8iSE7QKZcVmb65iQe0ddYeffw8A218PMQ7AyBqArAGTJD02OKFvqnfstKYF79lSvzJmXl6aZUuTlNNdhruXnOrh4eHR/RARA2prax9++OG77rpr9uzZnDGSkjNWUVP74B23z1m+bkmd9Wl53ZJ66+1Plr77zjsA3nnnnaeeeso0TQCvvPLKK6+80l3tZ4xVVVUtWrSosbHRsrxaPD0RSU3Jo34kp9vLI4EwWmfeEQCmMiM5/6vWJADY74thLzr9AcXAFDDYSA2yt8CbaWnGLY26ZfOC/2yskBqY3QiucwAiNMnZcGufxqeGaxF/YI0ZXdhgC3aQ4BYCA+gd/5RH0/1cS/1b1invBqcASoG7b2NcM0zFXqmI1doKQPdLW5PT/R53IoDd0qv2FNqoqfRvlm19YeuO47EURhg4yNBnICg7R7CLivV8u1I5JoCBIePswhAAOCbAoBnd0s2ex93Dw8Oj+3FddB988MHll18eCAROOeWUE088kQGJROLXl52/+tNPGucfdfxv/hWMRHW/8eYdfwiWDcKlZ/3fH/8458MPV6xYMXjw4CuuuCIrK+uMM85A15akcFu+bNmyBx980LKsb3zjG+vWrbv88stblHlbv5327b2liMfhSJe1n7lR14oY8G6N+sSe/NNQvlskpzWCfcSCp2F9rt+v6OtcsSHWpgJjJCFLEenAM3zsZ1qfP9lJpgXoYDI1PY1WVnEhIsZARGjFCXOLD+np6rN5+QDtGDMdZ9wggOAbisqJmeVminRfaHa9uGtT9fAgnVcUuaBXWBL4vnpOAhqcueGjb6uXl5Dd4GjPmv0u0GtBShJjIChymG80r/pN/2BY481H1N4eORjuXOD+hy4BjJQDZbdyYHfWVUAKYA3JmElKBHIHsrpXY8Nm0piT/RnUPPQP9GsITvSJVVTFBp9u1ysq+s2gTHcilEuTcQFiRATGWprejqNox8XiGe4eHh4e3Y97u1+5cuU3v/nNK6+8ctq0aUTENa2xYne/o44Z8ccHnr/0+F0rFg05fdamd1+qWv5paPo0AAMGDFi3fv3WrVuFEP369SsoKHCrznVly5VSQoinn346Go32799/1KhRCxYsaGhoaClN3UqISLZxbp0xJqWUUiql4Jaz6e6aL23FPeouOGUO0cd15rioL0Nn/6viq9iwnxlRRxLIaYXbnRQ3SjRzGC0Avm4r7duJFwLBAZIGSdv0MbGBFTyGPj9LxsMhv1LOYWS4M8acJo3Fg9juRGTompRSESkpJe1Dc33P1RXTBibX3l/zsC92dtpKgQlJUMRM5qOUyc0djAemFhb+YlvNikrzlNwAlHQk7dtwJ9IEO9qoe9eukk6/elv9Cm9OMDNAE5VjS0ZS6ibpJaj/ab8AMXKczo1RUYqE0KVbwlJJ+WX5SQaStpLScZyWPPsD0ElXAQfFFU1Zpv87MLLAX/uX3Jpz9d5P1o46VeiWJEYH6SWHKKDxhxtzPhYzZ5r1JsEgxaCk4tJKgAtHQkkpDK6UIqUAchxJXLW+hW6GUlt9HIel4e46eJRSex1tS15Uu7d5KFvw8PDwaDeu+Ttv3rxPP/30mWee+d3vfnf99ddbjlNUXPLbW/4+46QzIgXFpVOOT1TtXvvqU0WTjrOSCSJinI0dOzYej69YsaJXr16BQMBxHF0/eOpVB+Leh88555z77rtv586da9euHTNmTEZGRltvpy0l89qEpmm6rh/W923HcTo1P0ECAviwJnXinJ2PTCm+pCQSRv3xah0Pn8Y15uoJHgwCIDNKXtlR3i+N4QHdJG7oIT+DMHRAjPUnT3DWMe1UTeOt22APwh11rRx7mqZzzoWmtUaNtVGpuBKRxg2cJGk+jQH+kNB0g9mUrjVFcHRu9I2j9Dm16aNzQxCaIfb9CqWTAuNTxM6H0g9o+ul9ddyozUmz6eDcZ2gAMxhjvkAKbEvCzouEQnrnasW6LziaEJxzLjS+r70xRoxk6+9FHX4VuFH+cQsbkjYLFfBQKN/a2SeYHs6rYfg0wfnBYsXdw5qcFfhIOUkeTDNctqT6ZwOiE7L9NudMGLqhu28kQgjOOcAMQ+edfy86zJwTLntWSHVf1NwXZXf5nm4bpdxpDSil3Ione33b8tlTQvDw8OhG3DTTr33ta2+88cbdd9/95JNPOo7j1uyurWzwZ2Sa8ZjZ2LjhnReKRk8ceOp5GiPGWDKRHD16dG1t7YYNG0aPHt0tLXddHuPHj//DH/4wa9asESNGnH322V0pM0+kADh169Nrn+uynXYUXRAn4z7mp2X5fzU8N8JJEv0tuuZ663XSMlu5BSKlAH845w/1fe8qJyB9k++cW9IjADAwmzDd33Cb+VCGW0eS2uBx7Am08hS0RENgz//tBwWAkrfgmF+GrmBVS4gc6AH3K8Y0slMyUcGMCAOm5gR+OSh7aNjAASY+iAAYmq+3s7PadF6rSu92BGn+5q9IETjXiesTPtj6RmUagNOZg6pV3SUdkNPKwdBZVwGpAMffcrb05Qme2X9BoxwZ/3QWloEFW2P7uqfj3Fz2SOrOgFO/JY2ndzb6jYDc9Uli8e080htu13/xQDr+KL7E4We4W5a1atWqVCr1/PPPA2CMCSFcg7u2trZlibuyW9mEiFxfjusB2vPbls/19fWxWGz37t3o2vBQDw8PD/ceJaWsrKwcNmzYMccco+u6lNIwdNuykrHY6X9/KHfwiNUvP75l3tvLnn5gyf3/eOvFZ5cuXco4HzJkyJIlS7Zu3Tp27NhkMtkOp/Uh4gbnvPfee8uWLauqqnrrrbdefPHFLo3YIQJgb/8w/tGN3V/uvUfS4CjB2I1luWf3yhCMWelG6EHWasl1RiAAvnAexW1FgPyMl65TmQAIHASlh2JKONJLSm6CAVC0WmYm/YVo2CzTtVxrUiBhXFNWTJn1COQCeL8q/uMVVc4Bh60blMO1wM+NWWctrv/ukkomLcZ1NI19BiIIXRdGRKg6p2e8OCkHyunG67FFRvPHoVVFuoNov631df/YHaiJDAJTremjphJautZbJJkZz9Px2yE5hcv+1vjaN428kZFj/9yJrT8gh5Ph7trTmzZtikQi6XR63bp1RLR+/fq33347nU4vXbr01ltvTSaT27dvf/31193Ax88++2zz5s2MsQULFixcuJAxtmXLljfeeENK6TjO+vXrZ8+eLaVcunTp7bffnkqlVq5c2SFN7VGe+56m0dajGoOe1z8uPapJPbOLeg6H3j9urLYQ4oMPPrjssst+8pOf9OrVS9f1F198cdmSzy4/7dgld/xx5+KPIoXFvY86Lr9sDBOazx/w+XzJZLK4uHjbtm2LFi0aNmxYPB5vaUyXnbKW6PyioqI333zz17/+dWVlpetG6SoYAJWqBRFUtyvQ9SBcb+Cc6tSED7btSjuOkovrU09Xpr++Mbg9OhawW2tVMQhAGvk389du7KNAxixr3rn+XQAAEkRpX/6Z2vcWJzUA0pODdEckM74Wf+Ob2UkzWavqN/FAc8qHFlDxXbCTCPcCUJ5W/1peVW9L7N/IZYAEdJ0t5b0/Kre+1zccYbb8wnsXgRuKsXsH6yfkBNDhNZhItTXXlcghJbvxPdrVt6+w8U417FAJgvmDafcA3bR82W2TyiT5t9DXX7d79dbwx2GZWPNY4Jg/ZRz/NxEpAbpHdPNwinF3/eXLly8/66yzkslkRkZGTU3Nq6++Onz48Jdeemn8+PGhUCiRSCxZsqSwsHDOnDnDhg17/fXXL7nkko8//njHjh1+v3/evHmJRCI7O/vDDz8cMmTICy+8MHbs2Ndee23YsGG6rgcCgezs7MrKyvz8/Famme+TPSNwegJudFDX++H2h2qmuxvSRE/rHzQPoZ7TpB41ngG4g6fnDKEO6R8iUkrde++9M2bMAPDGG29UVVX9+te/fv+9d6+84sqb//Db4edc0mfaKf6MaOR7v57/wK19G7cNHTrU0DVd14cPH75ly5bMzMxQKNTSOe1O9mrrwHP3MmrUqHvvvTcnJyedTluWFY1G27HrdsIYAJWsIDtB0mRc6zFVaHoEr1QkMnVeHNAY8HZ1+hfL6rMcGLl5YFqru4kBICPam8XDqgbIv8Z8lQXPAQYwkCIyjMAi1nuX44M35dECE5ckXsaA79asq6L6TXzI15oWG2GVqCCSvkgxgBn5oVdO6JOpCxzoXDAOQItebD99yvjjruufZS42fWKPXAIiEjqBn5TjIMDQ4dl67cj5VpK61eOuCIKx12rUzVV93i9S5MseYJjP6s/lwQDTeetuEQQwst8OTtkUyz/GUQ2xGr8e0bIGgwjUbWWCDyfD3Z1KjkajQgj3Icc5Hzt27LHHHvvss88WFRWNHDmyqqqqvLycc75jx47evXsff/zxpaWl69atmzFjRigUWrBgwbZt22zb3rFjR2lp6XHHHTdx4sQ5c+YEg8GysrJIJJJMJrdu3Zqfnw+AiNLpdDtGv2VZbp5ZJ/RBeyAix3F6jpWjlLJt21We7gn0tP4BYNu2GzvR3Q1pwjVMe86Qtm0bPSmkrQP7p6SkZOnSpQA0TWOMffLpQh9nZ3zrBzsmnJ2TlQndZ8bqazas7Dv91JMHFpJSDzz4kN/vP+6445LJJGPsiSeecByHiGzbbsc8gCtxYBhtSy50B+oxxxzTu3fv3r17O47Tr18/Xde7MNefAeQkKgmM0vXdVRWlB+J2/9eLI7OKI1CO3P3pjKzBD+ZFT6leW6xb2Lf24L4hQPMF3vFN3Lop+cNhzkd8UJHK6gcAUGA6F7+znh0grgYiPeW21d0QyZfZqHGZE7L02XGzkRlNr7JMDzvVq7kR0iK9AGT5xMyCg49YBjh6xtfU0mh+PURhQlqBJsO9OfKe64bum1sRs2Adn6V33IVHAEtveFnLHqxlD2nDK3FT5dRuvkvX29DICvnCCBYwPZRXt4j3mwm05dWeicu0tY128v+tD2/csfF//gj0IBjrxoiVw8Zwd58BjuP4fD73AelGqAcCgXQ6HQgEUqmUlFLTtFAolJ+fX1BQ4Pf7XRMfzc94x3EikUheXl5BQUFL/rKU0rZtVxDKNM2WHFbOeTAYbEdTOee6rvccqwudr1rQJty+DQQC3d2Qz+lR/QOAc24YRs+JTnEvip4zpN2T1cXaKQegY/vHvb/t3Lnzjjvu+P0f/iA0zbYauW5snvPmoodvHzzjvBHnXh7fuuG/v/1b6XcvP/HEk955551kMnnWWWftaSgLIXw+X4e0p/Xk5eVt376dMcY5Lykp6boBwxiUw+M7OaQ063mk2HO4u7h9MD7TB8CuXR9785oBJ/z7gynHZr77mSN6A2CkWudMZQQww7/QP/Lh3f7rBqb+6L/wuHSfXwAETlBc+H6ffhJsJlDCoZoFOVwI1PwO8VVCErvC990H9SFn5Q5o2P4Rc4v+ANwIq2QFkMsjJQCIoADRiu7hWsDRAulEgy8TzElCtNwAGYiI6yHdeGR746e1DYun5nXQQZC78eRnd/kHnqFlDwEpsNZ4KIiUA+XQQUQzOx73RYE1d+mF+XwSe0mIK5kR4cKfrNmQUZbdvOLBm8aIwPTLxPKwXH62PaW3rNSNEPNnNe+ke+gpT+KD4uaY+ny+mpoatyxfMplUSlmWxTlPJpOBQGD16tXBYDAzMzMWi6VSKSGE64XKy8t74YUXnn32WZ/PF41GY7FYOp3WNO2999575ZVXTNMsKipas2ZNTU1NVlZWTk7OITa1p1UD8dpzYHpae9DzmuS158B0bHvcDJwf/ehH9913n2v7Ct1IVO6a++//58/MXvTgrRUrFm3/ZE5uJPTAI/9Lp1Jvv/22K9/eIqLVWdVM9oP73vLqq69efvnlDzzwwAMPPPDII490ZXgVY4BMV6fNNDNYug5At/v5ehQv7WpYlwJP7LQay1ntqnwNsWQdgm2x7VwTxciewCtPNXY5iraxrDgMNHU0Cd03jw9eZ/r3WHuPH3/FrHZ38Jm2JcFCukD2cJDDjIj7LfNFKV1LTpoHsuHKabTCgAQALcC4wZwE0vWklAj3/vwrEIQBxsf6kr2DRseOf1I2E0Yb48IJygHJrr8S2RcbWuxzpsh1pIcAcF8UdpL52hTFRwDIn7M1lr6+v++qSIXJfdzIgFvNtpvoQV7Gg+L6k3w+XzqdzsjIuOCCCyKRyMiRIzVNO+aYY4LB4MyZM6PR6FFHHbVq1aoJEyZomua6dUePHu2658vKysrLy9evXz9+/PhYLDZ8+PCCgoJx48Zxzs8991wiSqVSQ4cORU9yLnp4eHx1cFNUf/vb365YsWLYsGG27QifwTi306lIfvHxv7rlnT98P1VfbadT/YaPbli3bOXKFbbjHHXUUd3dcNTV1Y0YMeIPf/hD9+w+ufu6yPePS87/Wbqio7zt1BQm2xHb6lZmLaz41/jQ4MRWx4rbNWsUgFQND+QAALXS/mBcKfDAsXzriew1w/jZv81H+oeHuzHuRDAY3eY/K6+x922AYs2PTyIwlt7wkmzcFhr3/SMy8YAA+lK5U0YExjSz6nnz3xN8tznRgYLrTGuaAWN6iKQlAjmMtzomjbk/DDChkZO2dn4kQgUiawAA5k6YkBKaEVfsvFx5xsAoSHXMy5J7xpRDMk3KbtsvlSQlm1Nau+7UW4oEZwJQRJyxp3amEmzy5boBgAezAcWNjOYmHRx3QqouPOiyLb3uDKBMq6jh/jBjUE53BbjjMPK4ozkFavLkyevWrdM0rbS0VNO0aDTKOXej0ocNG+ZGwhx77LGBQEDX9czMTABENHLkyLKyMqVUr1693G/T6XR2dvaECRNcX/7QoUM550qpQCDQo8KdPTw8vjq4qrVnnXXWv/71r3Q6zTkDIC0zq8+AaO9+D5011k4m+h07IyO/8O2n/zegb593Zs+ecdppTz31VLdL2RYWFq5Zs+bvf//7XXfddd9997VUo+x8iAHrG5Ov61Pv9p9eaaqD12lsHax1AQw9HEk0NOLvZ0iqWKoXjKVEBVI1kCZrMl9aDwEwcobZdeudZO3JWDvASOHzqpjk18QOizdLF36OtWW2tfV9AEee1Q6A7T9RwGfVnYD1GcJhGX217IFcb/a460EALFTY1oxPJnzgOpyUtetTHi5ieggkmw104sKQENnMKunwEDllw7Eh22S4A2QDgOqy+wAASMKsRbuHvLX5ts31BKYId+20n/dP5YZBAA8VgRswQkBr7xEMBCDH0LZb7E9bUFG7yxc41KCMQ+fwM9yzsrL69++P5vnZPUPY3ZliN291z+VumVU3mbWlYFNBQcGwYcPcjbgrBAKBKVOmwHO3e3h4dBPuvWjixImGYbg5uAAgRN2W9Y07t574u1u5pm94+4U+J5x12lXfP3vmDNO0tmzZ8swzz/zrX/9CNyntuHfm/Pz8H//4x0cdddTw4cMHDhzYlSLuEojG1v/FvH9zYMgKsyV+4xA2CQDYlZZ3bm6IO+rQN9iNcOC5Sb2mZWoN5Ysjo65Q6TpZswaMN6XwtvosEeMA6otPOd+5YHXFtsf8Jy2zmyJ9GcjhgR+Zr/w2sARgn2tkMwaQbNjqfujoI+tmlCIAr1fETp6/44tFeJoOdUVS3OQ/L+ZAhIuiM/4rsgY0ia7rQRDxUD6AVmssMreSEdMCsn6TjG3TC8Y0LXf3SKSYCOj68tqGK1bEYh02aAkAKcf9ry2/I3KFWbvWcCfQzwZm/ah/5sCQLhg4Qy+eHCoaYUQB8FA+92Uw4QdaraZEREBIo8vkgie2pdc3xIKRfNes7MTDOBiHn4XKOXfD0F3zek/FYrfckpsatZeScUsx7ZaCTT6fLzMzs2VNN12y5+hmeHh4fGVx7e+W7Nvcwqy6bZtBauwl12b0Kq3duFZxccqsWYsWL+7fv386nb7ooos2b97shtl0fWvdSctRo0bZtr148eKdO3dOnz69RRigsyGQAPJjy78V3Pyr8JpwfBvcWIVDwLXDPq1Pf29JxfKYBUD1pJyKNsEY6xfUgmaFbaeM4slM99u7FzEt2Jwr2Wr7gzEAoYLh77GhO036ozjzQzMbgAIYkeRGGSrH8R0A9rQYyU7Ihi2wEoddOdWDQowBNLcm8c6uRkkO9jhs91DnJ/13Gae6qvYisz+aVEpdjzuJYIG7mVbvjwAwX9TevVglKvSS6Xt/zaAJvT4Vf7jc3JHqUHOZHCgLbqhM668D5QBoY4DNoaIxNiXL//2BWTPyQx9WJ+bH5CN5K3+m3lFGPgN4sIAZEeZWnG01DIAemoDtp4RihTrJUBFrXtxdHH6GOzpuOrhH5bd5eHh4uHDOLcuqqqrSNS3eUH/dhbMKevdOVFf+98RB2+a+VTRyvF+IJQs/mzd37llnncU5nz17tuuG6BaPuysY/9xzz91xxx1jx45ds2bNL3/5y67ZNQF+wTel8afd2Tx31J98c8YlFqJ5grvduMEPg8P6SYWhYr8GgB2GYR5uF6yJmT9aE9uxdZEvmMui/fW80ebmN8E4b86VbCXu8YcN/Xd4q6R2QRBmltbk1lVgOpkrwmP/VVNAAHhT1DUA2bCFnKSyE3TEFcYSUAC+lvxgTvLXOlP4kiknnMQoXhXRDQB71gVjephAIlQIoC2GMAHg/iy7YgkjqeUMAfaQVyfigA3eS3O+XRrp4BAv5ZC02uRxJ1KkZJO2TOfjdqIi+snKqjcrkw6BgMd2xL61rDHWuFvT/G5msAgVMj3ENFfRrvUFDOCI8GhR80D/ZBbFKFTcOQfRBg5Lw72jJmF7jtyeh4eHh4t7XyotLb300kvdCcRQRhRZhZN/+U+juP+Y7/8+c/SUusbGhkRq+jHHZGRknHPOOYZhfPe73+3eArcrVqxwM4iOO+64FStWKKW6oDEECMEfL0/e0lAciBSu0YesQQ4AOrRHm9vufEPcOiLPNdzbIHjeY3AdU8sbU4/tlqmKJcKfyY2QljfS2vUJuGh7jDtApAG/L6ovXf/fF+Q9Xws3ABAgAuNkbQqPvKG61FLkake6OLXrSEnINKjzDHfqpjgcBrAx5vKkmdyRdD3uTc0QIAAXYelD9v3CnwmgOV+XAWCaj2lBFshuansbdgduRFSyUssfxcRekezEAYtEL826a6hvcFhHx/mESTpQdpPHvfUtVjaoi0Jl3Cmy5THr5o31IcE1Bgb8ZGA2l+Z5WwqXhsczrhEgsgZGjrlRRPsCrY91YQBIC4Q1rdDcwewkj/RqWd5dHE6qMh4eHh5HPG5Q37Bhw37/+98TEIpkPPXQPe9vqg76yvRLv2anUk4qbiv0z+4/POtoqai4uPjmm29Gs4pCdzX40ksvvemmm/74xz9u27btqquuchOKOtt25wBJtdvEd+kjf2DCP9InWnrvh5GW3K8dgpCFJAiGNyqT/9na8PbkXkHBD189lGxdfL2XP7JuCyIlDBCZ/ZgeYsJoCpVp2wlSgNiYe6wdv69vqMGvtcRlEZiey63+qDOJNVmURGCwq9cIfxbzZZLZyLRA56iLdNOZYQykXk33ujTym7/sin9vYHAPDSICIK0YEwYYd9V1Pv+hMJjmb3pxan3b3fgMXwZI6QXjAYDkXpLqTBjKsVIKQpHRccYdKYek1UYT/Isx7p18/bjbFmBXl2ZMzvYBUISBYePhMbnTPhywU68AQEpyze/rd/IXf9S67WsB0oKp+i0k0yJU1MZfdzye4e7h4eHR43DT6N1SUxlKntU/FwBIIqKDtyhwk+AAFBwHmsYZd2ybce4azbZta5rWBan2box7v379/vWvf73zzjsXX3zxgAGuUF1XPNzS0P9Z2li3bBX8M5Xwr1C5sGNMb1sY6z6pseXC6uSSBuvobP9hogtJBNZS/YgzAHRifuTEXLNuRS3POxGAiPYTGX2Y8DHN32ZHNROAvKp21MToLA0Z56dD44MgMAFpi9B4a+2inPqImARSjHHXVFWNW0VumUo3kNmAUEFHHy8AkDQhLdbGyJ9DhwFQ9j/tsY16jmnGgPyWr1yD+m/WWH+o8FeAbKlHxQBAhArDk3+hZbplZ9sqLONnwRwta/C+vxaGQdaVq61JvsYfD8yVHTVoyYGy2xytTjZATdoynYw7ITYiw7h3TNMYYwCR6hfUruaLhotafJ7G28qKY1+AaQGmB2XDZnAdTYWZPY+7h4eHh8ceMMZaqvkSd+fewZhoCt8mbIulPq2I+UMZXBMgZtupgDRP6ZMNQBFpmtZllWVdz/q2bdvuvvtuAO++++7MmTNPPPFEt0ZyZ+8cXEOyjjlxCvX7ScbW8g33K+cPQj8kJ5/7xnFSbsiyqcGROEwkUQiMKUtwTtBa1EZMYk7dNkpVawVjAPBADg9kkyvt19oqmC3bBwPP16lKZD/Ejh1tauPdREwCGJge4HasKW+vKXwmptK1Rsk0a+tsZcUEOtrzShJMWFvfS697LnraPR233dY3gKqVdn3igYvEJIUBvPnwXG38l+TgIXoUbsxS01EzAEwPBUZc2rSFNrzcMgDMCOu5ZSKzL4AvG/1S+PwU35ZWIdNCU+jOIXY3AYB0SLZRDpKUG9ZPsotUZSTR1pRT4td0zliToBFlavg3PZ8SZWjp6TZb7e4pCzLhk3XreSCPdZ98ewvd3wIPDw8PjwPA4NpCZFn2e++9d9zxJ/gMfVvMfHrlzvKFj6frargQ/ryi0VOmbZv9wvBhQydPnlJXV/fqq69OnDhxxIgRnR2yopQSQjz11FONjY233Xbbiy++eNddd5100kldFHDPuUzXMTuJUHFZurrM/BTSBHAoRqL7bB8W0a8bmj0gZOAwyAYjgDGrfsN7N64bcMXpA8tAkGCC8V9tMOPrPruTmSo6yF3VP/hr5CTbsQ8GgOhXAzLqyxsTDQsH+EcC4IADCMAKFP1yR+CiBjo2CkXEwWS8nFLVeuF4a+u7ZDW2tLOjjtlFJSudmtUdu81WQiQfbvxrcXJJfvoLEjECBLDz7QX9eT0wgn/5qEmC8bZ1BeMAfP1O0fJHMV907/AbAADX/Faq/sd9/AE7BIB3VFeTDbKbxXIOvjbAQE2ll4g63XB3O/eTOvPCRbvfPbp4UEiXBMEITBBRjc0DbnDLIcD0EJhwqlcZJdM6pM2HSI+/HXl4eHh85XGVW+69997vfOc7tm0B4Izp5Kx98u5Fd/zfJ7f9fs2Td3Oib1111Q9+8APG2KJFi775zW8+++yz6Hxxd9dA79u3b319/aJFi5YvX15aWrpq1aply5Z1usoNEeNQ6Tpiggm9Ri+8h0+rTLvuxvbj5rp9XJe+tCQyOKRTj09OVQSAtpWv+unuvJkr+Kf1FhgcpQB8FpM7G6p5Zl9oTTMwgRGXBsd8B0Cb3O3N0JgwjuvT5wHx8sQM940SDOQwZOi0qFH9aWMKgHIlZeK7lJ3UcoaBCTJjHXSsX26RYqyLJpf2QqXrxvLK9ZmTf1lfFpMA4+6oY6QA/MZ6+utqIQD+5cHIRPteYJgR0bIGAft21WvCF4tVnZ+LmUVREHXUoCXlkJTkXsutfBtvcrRTc2R8J05ZuVfrW1WJEr/WL6g1Xa3uDmVKOEkRyAXQzjdGBoCY5oMQsn6zCPcCWq++31l4hruHh4dHj8ZVaKmvr7/lllui0agr1k5KCX/gjNue+vacrQNOOGPkhVelTHP0mDG2badSqVWrVg0ePNjv74BQ71YSDoeHDBnywQcfRKPRPn36vPTSS++8846UnSwCyACCile65WxMf8H3jUvXWX4A6hDcjQoE4KHtjd9cUmkTEfX0UBnFGCj58trVcwvOP52tnbf6QwITnAN0dbFxRbTODpYKoNmcaacMCwFgfFXMesZ/sj3pN5L797RgOBO/Cy0/NYfZigRjAGT9JhEu4v4scKGaPO4dCwNA0iJldks0U3Uy9n/+WRsiY+5MDdiWcgDWVImJMQdYKvOrjF4dv9d9W42ciIwBM/XE9mVv/vqT2kQHVggiaYOcZl2gVm2WyGkK1WlrvdW2476fXNAr8u8RuRpjTYFKbjOsGMk0bzLc2wdzQ52YFiAnzdss4tkpfIVCZQ48X+yWXO1ePTUPDw+PfcI5/89//jNmzJh0Op1MpgJ+PwCSysiI7lz4oZ1M9Jt2SnL39ty8/MyM8LZt27Zs2TJ8+HDTNLumbQBOOumko48+OplMvv322zNnzszOzu6CXQMMCiqxU0SKAeT5tHxqSKJjhJbzfNr6utQndebUbL9DpPXYRwMpwTiVLyzfteKkSZfdF9kZe+dHbOA9Wt54EF1UoJGxJeYflAE0x1e0W2yHNMber0leu1JOzxvy7yxzbIaPAIA4gykix+u7zuwTgLsjkFOzRmQPI8YZ18lsCZXpaKRN0tln6Ehnsylu/1E760XjmePNdUAp3AKnBM7E7rT9HXXm3wMNBYBibU+HPAD7PEzGiJSWPyrjrIdfef+tZz/8aMHxQ/SM3ocaJueGoSiHlGwy3FtZBLfZ494FOu7u4ZVFjKY/Pxf2YSrdQGaMhwv3WLHtkALjTAuCpGipd9utN4OvisfdHb4t87ZfnsDds96qh4eHRw/BTfHctGnT6tWr7777bsdxMjOjSikpJRhjgm+Z+07B8HG+SJSUdBx78lGT582bFwwG+/bt6zhdIqKsFIAnnnhiwYIF99xzz4oVK55++ulEItEl1aAYkZSN290pbA30YeqP080lAMQhlOp0Hca/GJhlMrYpaXVQUzsRBjQue+ynxfYjZXqo93QqPmbVwicAsgmfNFgb6uv94TbW6dzPXgAMDRkDA+zD8upGW+25RaYHHTtVY6mndsZNBYBZ1av8OYMYACaU2XAouz4ApGy4/t0uR6QqzmOryqKRx+V/hwcUAN5c+qsyZX8q84O+QBc2hxEpRIeWTvlBMl7dWL8DALU2MP1ANPVwGz3uTQUuu0THHcCLu+IL6018Pg4IgGzYTMoW0X5AW5VP94bpIWZE4MsEul8a9qtiuDPGampqXJU0NLuIXFxf+/Lly//5z3++9dZbjuN4FVU9PDx6CK75++STTz777LNnn3323Llzb7rpJs55NDOTcZ5uqKvZuCa/bIyyLc65lHLUqFGPPPJIaWlpVlZWp0eqAEBTCepUKiWEWL169c9//vN0Op1Op7tCUgaAkipVIzJ6A2Cc5+pcpGuAQ3q4uj8NCPb85F7TcwIAukUgv1WQBONOzRqnYnFw1FUaQMAHxZdfY59ipmM1Dr9iSdWSOIxQW8v97AP3fWZKduCVycX/HlM4KGSgOWOVAdADwkmmJH17WcXTFWmY1b7EjkTGwJU2Cc3flJzaCY9WUjYpp8vDjglAWWr5HXiuV68R9alkOu0eYFNkef8Ae4Qe7Sfi6EIzizEOUjOz6R7jLSO+vcN2LS2Afe50PzBNVUxtxjgYb7OIZBtpCmUn/HBl9csVCQBSKYDcQ7crluh5Iw9ZB8YtfRXi/qzmesPdfDc48g1396GyePHiO++8c+XKlUop27bXr1/f8hVjrLa2dsGCBddee61Sau7cuXv65j08PDy6EXcacMyYMeedd14kEtE0rSA/f8P69W+98pI/EEjV1TqpeGbv/o6ZZoylUqlBgwa9//77QoiMjIyuDJU5/vjj33777dNPP33nzp0FBQU5OTmdv2cGAKQix/yff+DZAADnkcjZ/02UAHQoxVMlAcB/tjQArG9AVz36SckA0I45Nf6SK3f12ZiwGdA/4p+jijclHQeoSqUyKQ5fdvO6h0pAsCFh4wf9M3v5RfMmGQFc86csqyQgZvWKrEgKrLj3fW3EqNW9f7LaEkZI2a6OTcea1wwAlA3VPR53magWmmHk9LvZGv/bbRpcRU4CgEzNuUguCGvtSP9tPwwA41kamx519Ib1LcsObYsgx3SFYppqKrUCkjaEzriOTjbcXVJKjc3wTcj0ARCcA8z1r9u7PtGKJgHAIcy/NXWhHubBXOaLdkBzD5mvSoy7ruuRSCSZTG7evLmgoOCzzz4bNGhQS/iXrutCiB07dgwfPjwajaL5UdQ+1zs107GH0G689hyYntYe9LwmUZOwl9eefdOp7XHLG82YMWPGjBnJZPKCCy64+uqrH37g/kceeeqkv9xfEW8M5uTrwbBSkjEWiUQyotGhQ4cWFBQ0NjbW1ta2dSy1I1zQ/cnAgQNvuukmV/1m5MiROFhaUUdBpLTsQQxQAIezODRhYaL4GkjG2v90UyAB9tC2xjrTOS6nT1TvwZVTGVcAr1z0ceToF6ucPw+SgD4iGnok9ZcCdX1Iz35phCitjEkjKoBDPAg3jLw87fxqdc03SiIn5gb2jPtnwuCQpKybynLMhu3mxy86Q/7fldH8K3obNbWZGenyQzzQfeCaldKCcsj1+ncdDMD9bOJyX8n9um5z45167e9QjHFFxIHNCbXAKTvfl9WljQIAShL7O2ZcaG0dBlKsI6a9pMkYJ+mAHMBo1SuStBnXicvOTk5tmhzj/M7ReVFNgMja+q5eNJ77MpWdkPWbjbzhAA79vY4LA0znvow9dtttHPmGu/vk6Nev38CBA8ePH//aa68JIaZMmdLyFRFlZGTMmjXr7bffXrdu3emnn+4qH7u++XbszrIsV9i4w4+lfbglGHvOHIJb09GyrB5iePW0/gHgdk4X1LxsDYwxN1Ra07SecMrcS8z93EPa0wX9496OQqHQq6++GosnLrv00j4nnnX/il15g8pOv/kRJ5lIp1PFpX0fnD1bOs6iRYsMw3AcRynlOt1bGexO7arc5B51fX39I488snXr1gsuuCCRSJx44ontOMz2QVIy4apia6f5dgXidaCSQ3m2uhfeeUWhXy3Z/b+djd/rm9lhRSg7AaZUumJZ7uDTfp6XUeLXAASCORel3+XWN8AGTvFX1ekGjA7wFLpvL2lFj++MPVEe++yY0mERg9BsxggfSEI5WbqRWvtQ0l947sTTzwUWNMizqo9fEXkGALFO0NWUdpPsoDA6Qyd+XzQFaMyn0k16H4jgTFrRJ7SDMIwRufMzrzUaN9FpswJZcN3wnd+mZpgg+r01ZRCrH0ZJYqFD3BoAkmliHCTRao87lA2uQ8jODpVxEQyFPg2AU7W8/pXLoif9yz/kfKfiM+7PEk0Vag/lDHAAevGUoDCYEemWNOi9OPINd5d0Om3bNue8qKho5cqVxx9/vLvcfeRs3749Foudc845jY2N77//fllZGedcCNE+y0kp5brwO/IADgEichyny8ooHhSllFLKMIzubkgTPa1/ABCRYRg9xHAH4A7mnjOkXXrOEOqC/pFSBoPBp59+uqam5tvf/g44NM41f2DLh2+sePahiVfd0GvC9FUfvPL9R5f+8te/Li4u/tvf/nbRRRcVFxd3gdvb9VPce++9dXV1gwcPHjp06D333DNhwgR39rIrYAxgnBSYNpNvPMdZCXb6oWzPDeb++aDsV2qR6Io0gfZCBMZUw8akwoyhw2dk+EGSAKbp7wcmmvW+vjn0ytr6q3xR0RGxue44yjfEyXnBj2pTX3iTITDhXo/cie+KrXku85TbZLOieYKHKqWeD7fafAfa1gxoFhzsEgPxCyj7zMRsFZkCTJ/MdpwcWgoMAynGBICELQdQDdeGoMvdsz6OM3N4Q/lukOqQS5+kKfQASJJyWrE9AhhJmwkNpJHs3NxuReAMyxrNG9dUPzypWK57DqTS617wD73A3rWQB/N4qMit49v+fTAGQMsdruUOb/mze/mqGO5+v3/NmjUNDQ2MsVgsFgqFsMekcGZm5rvvvrtu3bpEIjFmzBjOuVKq3SIzrJmOPIBDo0e1x+ufg9LTushtidee/dHZ7VFKaZq2ZcuWH/zgB+eccw7nDMrRg+Hdy96c9+8/ZPcf8sHff3HaLf+rW7pgaHHW8y+8cOEFF2zdujUjIwNfTMTvPJRSvXv33rhxIxE9/fTTWVlZhmF0TajMXkh//s7k0n7Aob9FxRM1d/g/LCw6FT23ABMBzC7/hIWL1qJXniWzdS4BDebi7JPvq+r9w0j6pm3q29FM+CJA1hJ7OwABAABJREFUBwQ8ExDW+DMTixbVp4sD2p6bZNwHxgGVWnKXnjPUKJlGRIxhSFjc0asqWFEHaUF0fGEBUhYIpOyuO0VEAJRtXZh8x581BEAyOvjTCnN8X0QF46QA/s3wzjPk/6R2UkseQFe1TYKJ5/rsalz7Mjk/5Xs4N1yN+XaMZGWnbF8uJ7BWS8SQssF0cNn8QtVpU5EgDra60Xxqt/NQ4w5r+5zw0b9Jr3lC1m+U9ZtEtBSMQzk4hMC5JogA1a6aZR1PT3HpdTbhcPicc84RQgwcOPDkk08GUF1dvW3btp07d27bts3n882aNSs7O3vChAnDhw9HVz3tPDw8PA6Ma/42NDRce+21OTk5LfroQjfKF39UPH7qGbf87/hf/sNJpw2fMXLUqGQy+cYbb0ydOjUjI6NrAsDcyclvfOMbl156aVFRUTgcPuOMMwKBrhTCA5oLsu+MDL/MPmNjGmivsdDyq+8sr1u48q08tZOaPcc9DlIAqHJxvZ579Tr+cW0CjBEBzDcqKLX4jgYpJmnVQguACSJ56CZki0b21OxASPDPFxPANeaLWrs+tbbMDo75NhhnIBCyBC4vtIrtncqxGTrehCNlAUSdX+hn7/2ajetVZpWvBICR2ffazcaft5gEpogA5FJjqbOb6eEublXTKfJnm3qmjO8CPi/YxFmbrXZXrlwpeZ3vyhf0SUzGXdn+g/9SWeAa43pnnxcOBqDEL64dnKe2vqOUExx3jcgpi390k0rX6gXjARySu70FxnqI1Y6vjuEOYOjQoeFwOCMjIzc3F8Ann3zy1FNPvfTSS0899dT27dv9fv8xxxwzZMiQnhA16+Hh4eHSMv3y5z//eebMmQ0NTXrYjm06llm1Zul/Tx26Y+GHOX0HJh288PxzeXl5GzduHDBgwNNPP30oSfatJ5FIPPbYYzfddFNeXt4Pf/jDvn37/uMf/0gmk90yJeLX9ZUoWBF304Xbvx1L4ZN06B791Ln1Omu2YHocTEgltcTO7cEh82sTA0IGAAEC9ImierZ48Od9jcezFztMAGAdMQxcvZ2rllZctGh3UirVsk0CEwYTvuRnd/FwL1/fEwGAcbdG62yzZDGVMCfWWrOvbW3q6lCZpgh3s/5ycfnD6f4AMg3jMrFyfk3KkopzDtDtNVlv6mO44AR0pcvdLRhcyTIuD163pCHlttaN9nqyPPbIjhia/2wVjAFIEFss+iQVB9mtPHkkbSZ0cA2qc0Nl3FeRqbmh24cGUise9ZddxBgPDDnP2v6BU7NGL5kKoNtzSTucr0qoDAA3+qVFAvL0008//fTP4yBbhBc8X7uHh0dPIxwOjx49+r777nNvUEoRKUVKar7A1B/+ceH9N/c9buboWVfNykg2NDTU19W9/vrrn332GWPs/PPPl1JqWqfc6qWUQognn3zy/fffnzlz5k033dS3b98tW7ZcfvnlgUBgz1CZPUtTK6VaIsHc23KHNMYtfZPLrZvtJ0f6jwZ87XtxcKVKGGN/zNl+Q7lxd13utBJ0Q9DPQSEFxhHbmYxVlI2a9kY4OiCsAeBQgPBH8rHj3ZQiZjXwSG+gY2JzXb2dbSlnbnXy5uG5Qb/mWnJExPQgpGVvm5N5xiMtzZNgGvD/akv7smlTZL1Erw53WjZFUbvmexeq/8RsmVIqPxAAkAoUfUt74dJREZ8QABTJP1UXXBUYcx4s1RFRW63HPfqsgH99YNjrDZgAKPfVnbHfr6nJNsSlJRFFJNoyGCJ2bTZyK3gGZKsNd2VDGEyprpgJIZUibm2bw2TK1/90gIzSY3m4F0BuXbaeEJXesXyFjFT38bDnA8NxHCmlW3HJrZzqWe0eHh49EKWUK/nipsByTc/ODQh/MKvvoPFX/CCzpG+scndOUfFxxx33zjtvT5o0SQhx1llnLVy4EJ2fDLBx48aysrJZs2ZVV1dHo9EHHnjguOOO2ytJY8/S1HumD3XgLdfdok/3X64WDBJ1aDbl2wORzvCN4Oar7DcH+yyA2r+pToQAyPrNVroxv3TsydlGkzVGIMAfznk41WfygsRrjQF/Rq+O2qXbycflBI7OCfoFw+d2MjHhIzupF000eh+9lwU9KMiZMmGnO6oZe0Cur71r1Es+3ylgWHU3mk+elCUA8GAeS1eV+Hm16SQdhzN2nF4xAdvBjS62GRljilTAH/mp9nFZcrk78eSqdp6UF/pBv0wAotUvNwxwgLBVkUGpzSwP1Oq6ENJiXIPQOnsmxHXEfn9N8ncff5JRMFJk9AZJJnzB0Vf7h5zfMUEyPY8j86haA+fcfQpqmtYDnSkeHh4ee+JGutfW1gJ44Zmnf3ndz8qOPXnHorn3nzI0XV+T1XdQ2G8898ILeXl548aNq6ys/Pjjj/v27YvOD5WRUq5cuXLevHk1NTXhcHj+/PnvvvtuS3i9u/etW7fefvvtc+bMAfDYY4+tW7cOgGVZDz74YDwe76CGMABCDyzWBy2qjuPQQmVswrK472L7o+ujOwDWI2PcGQCnZqWeNeD+7c7yRgtgiprfV3zRWpG7rMJZbxpaKFc1r3+IuCbg/w3NeWdKcYa2Z4y7gh7k0T7+4ZdA+Fsk81zlmT/1Ez9Nv+BIN0a4Q0cjudHt1IWGe9NbXCC562v6hqKAAMD9WbadIuD/tjiDZu96rII9mrN0mr0SPNz1NpabHXsNzT0v+QYDRFP2B/5vaE6mzuttxdvyGsoAS3Eh9DynBqrVYvnKAdfANerAUBmiL9dRcl9Vl8cVS9dovhChaXwFhl8SGn9dh+26h/HVNdw9PDw8Dhdcz/SJJ5540kknERCJRoMBf8aQMUf96MZw/2FTfvYPFs6MJ9Oapp9yyqmBQODUU0/Nz8+/9NJL0Zk6la7LY9q0aUOHDl2wYMH5559fW1s7d+7cZcuWuYa7a7WbpvnRRx/NmjVr9+7ddXV1VVVV8+bNA7Bjx44FCxZ0nN+ESYDp4h7/zOt3hAG0TwxPEcB4hSnPqRyzjhWG0NhBzetoGAegdn1qF0z6zsr69XETTUYL4wD8uSdrm7+es/MovZoC+QzowCCSXWm5JWl/Hm7BGEiBG5kz7gsMPb+lCQCYmzuY4R+ltsFOdVQD9oCaoqg7Wb3ki7vkAHbY/G7fzLTiAJgvQzMisnr5hZtvOq7+1bDOmNUguiEzFUBT59dHh7+ULKi1CVw0hTMB5326e1mjiWaFmYOiAAF7Ce+7UpSen3wb0FtrMiqbcZ1xvSMLMDG2bw860Y/6hs4JVttaxJX36rA99lS+QjHuHh4eHocpruF+8cUXAyDgxJNPKTvxlCcWbR574Xn65ZebsXrbsjJ9/KyjZgKQSp1xxhlnnHGG+9vOm1F0W7XnvvaiJTZmxowZ0WjUMAylVJ8+fYQQbjGHfv367embb+vkgFtW1q2XBxCBkwgNFo1rrKStIKDaIaSiAAakJIKUetyY+nFF6Z/yFLlO5U5gj/a3EVdApn7T9sKZYzLDw0OClCIwBWIgqWeN1OOPZ34Q21Uu/YWCSJHCIVcXdQgGZz9bVfX8rvj6E/sU+gSBNVUOVgpacK8DIUAwLI3rjxjf+LnDcglKEWMd1JOMQUo3xp0cSxFBqbaeb3cIoRXDzy2KR0QSAiSXyuzv4utfd6RP59AiDFT30qWjNN9jgQAiF8XMFDOCiggtTuBO44tXAQiKg2mZAy/dNPLemvSFBX4Gmleb/t3amgxBVaZDSikQa8VgUGCMnLSUaeg+mYK0Fblxe8ztin0UZibFOFfSAhfgGimbCKTUge3pg14FjHG7apmzc0Fg9NVNNb+oSZ+UM1yUz6xAMq1naQTal2O+81DNo4KIAFKKGNq293ZIP3uGu4eHh8fhgZQSbq1WKQs4//HEfgBBKfAiEDXbB6SkTMTjgUBA0zTHcdxycm6hsXbXlTsAbvz9Xgv3dPPruh6NRhcvXqyUys7O9vv90Wh05cqVmqYVFxebphmJRAA4jmPbdpueYS1ldF0pDwLTeOQ8WnaSL8OW/Rw71Y4gVwIEqSwRuMf/7h3KfDGR9QczaXdahqFbudk9s22DcSg75aQHhUMf9M8gM5Y23RBkAuNgAUePVpWvgiM1kWFbDpR96E53RdA1NiPHp5EyHNsiRzFmWxaabC+11y4UEORUlRJ3aMdfZBvZUqUsU3RU5DHjkKaSJgArnZQOwTbbesZbX/mYiHyGblmWlBJWkjduG+OLcseyFJNalGcN0zJK+MjvlD83I1y+kmwLImDaEtLq7ITZL14FACnoAcMIj6EtK+rNC7LAOP+gMvZJvb1oakm2UKZpKqA1kuwExoiGJ5aN04bfHThjYqo2KSGstCIuuGHZtpTSsS1H7mGqkmKGZltJpQBo0jJNBUqb4Ae6gg5yFZBkRtjcMsfZ8BwbcB6MCJTjvglwUFqx92pSI5NWkS8zLQGrzWPgUFBEwm/Ytu1ICVKmmRZtucG6xRbbKh7gGe4eHh4ehwct1vAexjdzp8IZYwD7rKIxYoiBWSFd16WUjLGWksB7fu5YDvwm4Kb+b926taKi4mtf+xqadd937drVt2/fvez7drRQKeX3+5vaoBxwrVBXA63l0BmED/yLzzgigmLgB/H/SSdX8Fxt067EwrHRS7VAH+0Qiy8eYF+HULmZJJIktUDEr4GJYLPONIEUmN/2R6l6FdP9/nAmEzrQMWefQBf18V/UJwvNKaicMQA+n29fK4MBI7Iwje3wqRKhcT8PcOb+pJ3mLBEBTQVKSbKkchRg6NzQObRAO06Tay8eNKLMHck+n8/QOHyRcQ1znizWw8FJjCT8fv9Jt3AjBMCK9tEb10lKcX80YGgg0QXBG1+4CoiIMZXZ+zb590jmdPgGAGpKXsYtPD7IqEOgqE2V0Rwgx94xIZx63SqD5gQ0cBEg4owzn2FomqYbvi8MLJJgUJzZQoOmM05+AQQCBzXcD3QVkAMGh1IOlE8H9xsgDYwrgAM74taVq+PPSd+AjHylgYv2jIF2o4gYY4Zh6JoGJgKBQJsM9/bhxbh7eHh4HB64U8kbN2789NNP0RxB7s7Sbt606ZV3P7h92a5nNta+/NLLL7zwghDCtu37779//vz5ABobG++///4VK1a0/LDLSKfT99xzT3V19SuvvBKPx2Ox2NChQ1esWFFUVJROd6zSCAMgowN+X9t3oynB+Zdy2RhjBzGkCGCCV1nqzvTYo8wVN4TWAOyQEl07BQLAnFRay/zOBv52rXRF0wG0tJb5orJ2HQ/kMNGRL2wMzJ3caRGOOcBcv7u0UMezvhf7J5YD0DjnjB+SLv4XSuEQKZsRurIAk3uw2fG1gzP9LYfBjRBIAmSUTLV2zFWpGuZWq+16GBjAQ0X97O39eCUDSMrjc/1X77z5rZd/95ftNqPWTu8QwJW5npesE0Wz0rMJrU2XIWWDMSZ8aCq2emiXj6v/n6ohqxHO3neMKhv53MxgNgJ5HZvL0WPxDHcPDw+Pw4AWP9mVV1551113odlTSEScsauvvuqB//43L7/g7YfvvuCC8y+44IL77ruPMXbVVVddd911AD799NOrrrrq2WefRfMLQNfgCkF+/etfLy0tjUajQohjjz02MzPzvPPOC4VCbux7R+2LGAOgZQ/8Q2LshzUS4J9XCHJjjR0ztfIxlaptWfJlFAHgK2LW95LHVvqKa8y2B7F0CQqAVbue5z/akJUlvhjM70YRhApImjyY2+GmDNvj31aSNnLNdALAwm3rP9mwiAHUjkBk9ye7P3UW/OnzJdImEGTnFvr5QivAQOkHxLE3piegOVe1OVaNaQVj7aoVKr6b+TKbVu9qGAFMM+pDfX+2on5hjBjXltfWJSqWb47Ff7UiZqrWNksCXMXfFqPeosG/TDwuiaOV511JxjgTRrPhfmgwBsAxY9JOKefzFGcOgFRZRH9msFns7KZg4Z4CpUcwnuHu4eHhcRhARKZpfve73122bFmvXk3K3G4Bow8++ODd994vLimxErH5zz72zuuv3n7HHU888YTjOGPGjLFt2zTN5cuXDxo0yO/3d33LDcMYOXLkscceO3369EAg4Nau7tOnD+e8sLCwwwN4fIHsC/mSCLPRXBEdaNKGdOrWxuf/Sdata1myLwhAQNdPkMvfC06ZunsiSB54or8bIDBA2akQpX7WLzA2YnzZEhOhQjDBA7lNP+hQ2mgdyRv0Cx5UoyTUq1s2n7Vge8W6Nxjb87WqVbhr76zavHTbKmXFAEA5rjVP1BEGYmthgHxDDFvgFLhx4IBrXHIAWtYgboTsXQu4P7sLm7Q3xER2Rt6z26sf322B0YQFje/ZvaaK3edE61PEWzkeGADwLLuqv2F/qg+VrbfClQ1wCIM6xHAHB+C3a4N2AzUZ7p+/kGdobGQwqTlx+HM6Yl+HAZ7h/jldPH3s4eHh0Xo454lEYsSIERdffHFDQwOaffDpdPr2228//2vnJuJxy7Iu/f0/pp1wUkNdXXFxsZQyJydn0KBB27Zt27x58/Dhw02z1SVUOhTVDJrvtHt+7ihc8UEKFvwTL58ZrEZTGVEXAiDrNqp0vbKTB9gIZwxEI8PiMfFMwGmoVXrbGtnqOIRDgxggzdQ4XnXTEKFxgPZUCXE97oWMMR7MBQ5N0/7QcMMcduuFH8t8kd7xg+o7g1l9n/r4JbXqIWJti0FyJWOecQb9NHAlWTEASpoQGhMadaHHnTEGJcda62aGGr8QRsU4iESkWGT0kbFdzJcBoDs87m6bWMgX/Hq4urdf25lGRro8r/Sofob9ZN7yTJ2DVGtevQSgEDjV+vTScPlPfZekSACt0kwhaaGjPO5ExBjs+jf4yAd8J2p2PZr71FVufamGblu9M2CESBgAvgoud89w/xx3Gtoz3z08PHom0Wj0+9//vmEY7m1KSqmUeuCBB0488cQrr/ymI6UeDI4+9uQVK1feduutP/7xj9PptFJq8uTJ8+bNC4VC/fr1cwU0uh7eDPbQiGz53GEwANAyegfNKpGq2qsJAJzKJQAoXXvAbRAYC3EqZHUTU0v+EV7MuNY684ug7Nic/2fv/rTpz05GOcnZoqzCCn1pZwyACBeBayyY1zWN2T8EiKsDm2aaCxZW2/MTvo+O7XPJxJPiH9+Chk1NGvCtw13vQ9lrkZWxy2IAyDEZ18ENyGZFnc6HgcFM3OC8853MauxVoJckGBe5wyA0rgW7qkVfghQHEtGhP1Nv/ag3C+v8wdSdg3oP56UnNm6bm1Jove1HRNmqfqBPrWEF6SY5k1Zcs67qi/B1yEyIBJCu/J+YcpfvNGUnWgQ2FQhgj+6yHt1cEQqGFeth02KdxpFmuLtSoC0eHaWUbdvJZNJdfuDIzp07d6bTaa+KqoeHR49FKSWldK1ev98vhHjwwQf/+te//ujHP3756SfWfzSneveuyy+55K9/+9uYMWPi8bhSatSoUQ8//HCfPn2ysrLaIzt4OMEUwHTt5dDx39iaD9pDPZoxkLQqPmNcqHQ9gP2ZVJIAYH6ddWH63MGovkxfCrTCY00EMLISdvnHTv3mVv3kEGjyOEp1uTp/QcoPQGIvhzt4KJ+kzfXI5z/oDhgpgF3o33ZJ49Nf35z9Zu55BeFgaPC5O3mulahBWxrHQQBOZhttQkq5hnuaCYMJg5wum0oiME5WrF6LmiK095eMAzAKxnIjA0IDusv/ywAEhpznpGrLVzwbbVw70/o4UjjGXzj8p9tDN25xwJg8+PgkArhK3MuPm039HlaPhew6AOzAP3RnWJTDwJnwQUngEIsiEQNgJ4NW1RateJ3KZYDaQzem1M8mRxT5sr86ttuRZri7iVAtHh3OeTqdrq6udpe7TzvTNJcsWYI9NBksy3rttddeeumlJ598cteuXe2oA+Lh4eHRBXDOHcdxZZtXrlz5zjvvnH/++ZMmTfL7/b5AMDM396E//ry2ptqyrDfeeMPv9yeTyUGDBr333nuapkWj0Y5WcelxKADs/7N33gFWVNcf/9475fXtfZfdpS2w9F6kdxEELKgxduwaNYkmMRoTk/jTGI0aS4yiggaxF7CiAoL0Jh2Wzi5s76/OzL2/P+7uc6UuS9m3cD9/wNt582bOnJl759xzzz0Hoej275WpRl2lFtTFyVTtY5ZBPRnMV1K/7SiIzVt8+NhsfdDT+b2aNOun45wAzk0QeraiZWCY/gri0Y4imph6cLkH/l6NywGas5yk0Gepo83bRidn6dppKTYOdWcAE53372QxqA+AaQzCcJ9orvlD6KMYagGAFYBiI4p+NhenUjBmmZPUOxaEEnHYkAkEgJrUjdpjQfWzJtLhEMo5o64Uz4AHrtzov2LJ7oUZ1xNXEvGkVSoxXxV7T+JIlv8b2mE3jxlPt+hGNRr5KDGTi6wyp8OUUgCY7K9lT/upc5fpEHIBUAkBZ/9spz+WXFqjJihAs84snT3OqTzujLEVK1Zs3LixY8eOQ4cOnT9/vs/nGzx4cCAQWLt27dq1a9PT08ePH7906dL333//z3/+c0JCgggSrays3L9//+23375z587du3enpqaeiuHehDpYZxQpz/GJNHkQeSJFlDA4j+URroeYmBjTNBljixcv/u677959910AH37w/ncr16lpGdX78rjXd8MNN1x88cX/+9//4uLioqOjO3fu3KpVq5KSksrKyvBxzkkUANTVR6v8I10BMrUuaSHnICRYsMzpSWWxreEtBHCsd7xQTbZu3YnlWz19rqjsV8u4UyH8BMY7Bwgsk1sBXpex7gzaECI8g3gPzrN90ze2P8CVI4QjVHH1uSf8x5kT5vgwUAXY7Oh8u+JYWPOXjrG/I1Ba6Xw/TSzkzq5162wbBycg2GrGjDa+SKRVQDqsEFF0ruicnSXDXdRMCJmBDSTTFGsqGn4tnIaOxJjJbyvRrQGgmeI3CKGcc73dpI77F79S1i4lrf1wAJ72t7neKbdv4rigMQ8EAWCa/bC/0uZ9Rxk8HPZkhCuWHveuMZMoKqFqfRzUKXncAYQC1RpV33N+3a0qFehMwwIQYnKYvlJFhIRx3oxj1LPGOWW4A1i9evVll122ZMmSgoKCAwcOjB49urKysqioaNu2bVOmTPnkk0+qqqq6det28ODB+Ph4UcEYQExMTHp6+rx583RdHzZsGABCiAizOVkBCCHBYFCkejj9l9ckml6Z78wgpjhEKcfmlgWIPP0ACIVCJ1Uj44xCCAkXKImEWxYuExghM2NnXz9/+tOfbDYbIeS222676aabvF4v4/zCCyeMmnLZA8vy//jpD7dl23VdUxTFNM2PPvrI4XCsX78+nDvy+OtTKaVnqE7T2YFwDkLb68ajvi8pmVq3lXNOoJWs3RByPqze8Df+aS+A4eh9tLAJRjqrR9PPv1J6Z5DaxruEOTdhGTDPkhGpB0pHK3uhUXCLHNVA5BYIjYTlenbCNLOW6lH22CwALhUvkE/b1A4A0ukJrcB6TEI04CnbRSV2+zIjoAHcDIDqRLHhrIXKcHCicF/po8rarq4OOEbcgprQ5SzJc2w4CKH6jV27bVy2flhcewDcmTTYVuHyfg5cAG6BHNcC5ACBYQTvxrId0VWDcel31J8MMBByokEp5xaBDVRr3FrWE10FUGgov3Hd8nf79kzvJuCnoUO1Yd2zzXtJpXlR4vmSUgbnmOFuGMbAgQNTU1P79OlTVlbWoUOHzMzM4uJiALm5uYmJia1atRIFZm02G6U0HPKuKMqkSZM2b968YcOGH374YeTIkcJsaprjU/wqogz3iBpIMMaarNszQaTpB5H3CIk7FTm37HyWhzGmquqKFSt+85vf/PrXv546daqiKJqiWKZ53603f/ztopgoz52rl82dO3fevHkPPfRQdnb2E088ccUVV6Snp4ddFccicoaLpwADFBLTetvBLWkmYlQCzkEptwzDW/Qb85LK6vJkTw0AQo/nOAyEgpWI7kZLPrTNc9Budc7eE5/c5FaIW2fciBRy5zHPd8qYmzhc5BgTAhGwXE/Y5W2V2huC8+1JGfC05uAU5BbbZtQ6gAtP9oGL5b5vrZTtVmJXwDrM497YIUDTIeCMqHb/oYfpd/DcD4Ae9Yx16yuaszUJwQYkx88f1VVxJonRHUns8VX+3u4GT1GVxrR3bgarqEtTbXEkaNVVuSLHnU0S60YtUEqoCmFlkUY46Y+BmLEpMJX3SY9BqqvY3DkYnBMihC8JsXcLqif4q6gzHhAe9yacpIVxThnuqqru2LGjd+/eO3bsaNeuXWVlpWmaIvGC2EF40MOudNM0RUD8vn37Nm3adPHFFycmJq5duzZsWep6U2LUGGOapkWO1QWAUqqqkXKvhaEcUV69iNIPAMaYruuRY0KJYuAR9UgDiJxH6Czrx+/333zzzfHx8Q888EDnzp07duwIYG9BwdIflsTndEl0OwI+/zfffOPxeD7//PPLLrvs0KFD8fHxkaOuM4qwDlRP2tXB8VcetH6XqVicU1Bau59V7f3LkJ6tS79P37eDMYtS5aj2BwOhwMsV0YvIZe/ZF6fyPDS+rAszwQycecOdcaIQrGAZTyudfmnBpdKIjREQQsVp+L3xmS3malCVMAuUzrcPdgadF5yMPaeCAcpfq1+ew8cegqsrwM0QiEIU21mrnMoBhaA4hPVK7+GM2o/V6JsvNukwGKjbkwKAc0YAW8YFt+1qe2d+4LetHYzzEw7sNGLdyC4dH0xc4njc7u8IjKaiRtkJMEEUKCqva2LHt/WPh3g4PDW77rfxJa4xP5THDuZBkLqatS5VuTfL2bmwgNniIkXjZ55z6koppcFg8N///jdjLDMzUxjliqLoui5McLvdzjl3u92FhYXl5eW6rquqqihKmzZtHA7H008//emnn/bq1esUX8ARMoMfRspzfCJNHkSeSFKe43PW5BFn2bZtm9PpXLhwYUZGxg8//CC+2r17t93pUp3ukdfeyqiiUNqtWzev1/vll18OGTLE4/E0VyLIswwBGKDpepSm7vWFuLBXCPKL95cG2bBW2XucuXN5R2pUhpPKHe0Y2GNoFcRVGJX7a98FRQaOue/P4XUe93rv7xnGNEPtldookbwkIq32MFyxM82lJPdGXUoQ6xX7uCdDPcEN3mjRxaRHSujQB9WP9GQFAKjlB6VEteHsGe7EAWO5lXyvdkWVYQFgPKJVT0UHJaLeASWuzTjkrawKApweV/Pi+eWWsZ4nB4iWpvt1sxaNG2ZxZhGqgOqNz/V5TPkJB9C+Ytk/Ejb1iXF4A7XglNTNc/IUm/L3Tu5UVJtaFBopXMsngryMp45pmq1bt+7Ro0dMTAyACy64gBCSlJSUlJQkdhg9ejQAzvmvfvWr5cuXHzhwwOFw+P3+YcOGjRkzZsCAAQ6HQ3heI8fZKZFIJAIxO1xYWBgTE8MYa9WqVW1trfhq/769+QUFLuj/vvGSBw/sd7ndH3zwweWXX7579+7Jkye/++67l19+efgIzXoRZxpCAO5IfgivJbr7EuRQRS33+wZscf2l3f03cOvZ2jaVyuhJRhmzxStHc/cSMIBeZCsaYs4vdU54IZR0bQjJJ56uEGnwTLDQWcgproAB9Erfl1e501X0PGaMeyQg1mu6Ut0D/qBnXCA2AbSrk6+trjiZEQcHocwKPq2OGY5/JloFQFdYQQIFigpu1O1zhuEABcpNoio2l6Yg4odMOMyesSf8Wlmu6J05JoCz48wMEHCAmCHvr5WVg11jHzLGTFXM3uCsMe5zboEoEItTxedTEB/guwPgqUPvtG25quZZ0Imon1srN3h+aWG6Yqe6u37nc59zynAHoKqq2y3u3/GMb0VRYmNjA4GAzWYLBoOapnHOPR4PzosXm0QiacGEl0CIzkpkdu/fv/+HX3z1YSjh7emTNq1be8+9927dsqWysjI2NnbevHmrV6+mlF522WWWZUVUVNgZgBCA2ZMH04O2wDYTOapV8c8lC11q5qU9h1GidnPxH8xahEL0GFG3YuHdOP0AzKXb1UkjyE476dfIc3PL5FaInflQmTp7ywqpNvcZP9epQgAQ1WbveFn93xag3GjbOcn7HsjYRh5FxAL5A7X/VYZ+7vZ+yGPTAMsyQClRdH7qFTobhwLmo47J/m9z6RoXfTCih0xHQMABmp6QaS9ZQDChMWMOK1h9n74cLqNfcFBHZW9vmIxo9IQTjMwihIqsMpxZRGm6ijhAWOA/rHctGTZDWQurQgTQM84VQj4qCry26dDnuptqkd8QThvnVKiMpmmDBw8+4WtJ2OW5ubmjRo0aPHjwqFGjEhISwsa6tNolEklkInqn9PR0seZ+9+7dHo9H5IGZN3furNffUMBZMKTpenJS0vDhw7/55pt+/fopinLxxRevXr0a50P/RgBwbvNoroT39+wduh6bFvxresnLcwdmxrjjANyfQWbUPGua1rFXDhIAa32O5baebVD2DpvV0Vm/9YRwk1uhMx/jzi1CgdDz2rj/YDAOTyUeqXBLeGoJB4B0G3r4N5y8j5xMDv6wQu+/WO0MgFkGiALFcdZi3AEYULKDewaohUckg4x4OAdgS+rxfwf190sYQE4Yrs45+5x3LWG2K+y7kkMFjZ1g4BxUI0QD2Gkoa8D5cjPBY3MVayn36dfUmD8J/WONEQh4Nd0NXRru5wHCTSX+jah4WYlEIjkqwuxu3749pbRNmzYlJSUTJ078+OOPH3rooRGjRr/75hszpg6Mc9s7dOkKjo8//jgxMbFHjx5FRUUrVqzIzs5GfZT8OQ0BsxSQgOrpZ+ahcPW95R3ajP9XTlwi5wyAy+GO4bXcEDVojqINTijA/17V+i3nBE1RfabZmLV4db9lBpgFywTObAgFB2BWv6f0WYpMnFQq9GaEKGL4wwgBsMPW9ib9Ji8DGmf91i1GVOg/fLM6BFcHjSAAWCEQEeN+llJwMlA3q31HHTBLG4H6a2k5cAtQYzO+CaX+c68PADtS9/VdhPjPINrV1qUbArY5Ud/3rV0JqMrxbxcRQ2cG2iBUBk0e4XACcMb+4n3z/qi9h5TE12xjd9YGUDdCZ3dkOl9ILzGJQnRP+OznPOev4U4pVRRF/Hvue6EkEsk5AWPMbre//fbbQ4YMmTFjRmJiosvliomJ6dOnz39ffdXTvtulf3nW4XBYzNJ1fdy4cQ6H46KLLkpOTr7mmmtQnwDnfIB7WsXtfPsD3xPPjhzD4zpZnBNCAVRx/X77tXssN45Rs1NsqjbhVIhPj7+DXvpD9bEXsv50PgCAZYKbvM7FeKZeK5xDAbiJSf5FU5zFZ/BMZwYxzKhWot7Qhu31WWisUccBmFaoitNPq/482bcIYnEqoUR1AGepEAcjisuonKUPfUfpjZMp+xoZEArAk3WzI28wybc41CNTsv/cHAqaZpDadAqmOEyrMfFI4ucMVIWigvNTX5/KfSXjsT3dwZJVdp21mATK6k/DO7qUAWqRRXWi6C1t+qPpnNvBjhKJRHJOIXJetW/ffubMmQA452PGjBkzZgznfMqll6xrOzSNhBjjoVBowoQJYoexY8eOHVsXSXxeOCkIBaDFtvemDkwZ81SqJwmMKZTWZYok5L/6RRfCk1Of+fFwOAOhT9iXeYzvvNqNi0jO1AAfEk0ak2+RM4MzCyzscT8jecXFETnoo763SFQ2gKOuso1YxKrHFNWYYq0z/KlwJzVGuWKF476AdbN68z+dj+cYJQBgBUEo0ZycWcBZcbgSalhmolESb2+BZqJo/57WE7X8qx0/gHTkzCKEhtsBt4Ks6oAS1xb1VZZs/sLPtKU9Xf2u844Ypm+fjqAFWyMWpzJCVUJVLmLcmyqveC5qfFVvOiZN4zHJduXf1rtulgu0JuDgeLuUdygq6mR3ASJ5/Hlh056/HneJRCJpoXDODcMQFScYY6ZpEkJ0y3qsS8xd3VIVSkQ914Y7NLfIZxFCAdg7XBp/6SfEk8k5FzVShfXgpOxqZV1M7R4xC380OIBeZG9bUmmj9G7z284OhkbaxSLS2jLAz6glzQEYhn8LSa5RE87YWc4UwuxIs2mvmzO7sgM4GU2VmvR70valqF98amYDYMwkhEJ14AzPcoRRwcqZ9u+a5//u2QZAbWFeXgJmgSjUnbrjwNYKC4SqdVY7ZwCMgmVV8+9kvlKgPiDeqByh7HUrWM2TtyCpEQHrpO63VAVpECpzCuz0WQ9qlxVaOtEcFWpcha9GnMfkfPrG6rWFhxyO6FP16rcopOEukUgkLQxCiKqqYomOiPczTZNxTiixAG/IZJyLOqkix7yqqpxz0zTPgxj3eoQf8fAsYRyEvmb76oKq7wBy9GhdogB4trrNUlf/KBL4S+j93h4DJ3TmCnPFCoAqnIU4O4NrJUV4RlHAulX55UaSihYYsAEAmsunRvl9lQAaE+RAwQGkU9+TgVlL7d0/MtsBYJYJQqnqADtLhjsI5WaQMZPYPGf8XGcCAg64k3LfKsGotf6KyoOhTa9zZojn26zaxwIVYgWIqJ20H9H/xMhq4PeubcP9K0Fsx7UaeTjGnVCNKBo4q781Tel5hAyHvLU5qjfepoNaf3Hf9M/qLAAA9TOWpCNVNbgeDZwvAe6QhrtEIpG0RITtLmLWxWdVVSlVNpfUPrlqrwGqqioHRBG68D7nRahMQ464XgKUO7KKAqH6v44Gtx6tyf3R1QuU/6B2KvIZqLchToAVIiBc1E/FmYq5FUcttZTltLXD5joj5zjDWADV8LDnpn9UpKJxWXFE5EY6r7ovOPcquqW7uRMAsYIAIVq9x/3M53lRCPWHfA+pU37gWWgpy4J/BgHA43Kv1nZWeqteWzDTXPygUVtUt264toCHargZRP0i1e0k+R8YVsVxnXPvqMBKQDl2OqYG5wh73E8tq4wYrQ31Lf8UM5OcdoAesqUtMRIAmIy7NW3joOi+biugJ5xXtux5dbESiUTS4hFe84MHD15yySU33XQTY2zHjh0jRozo0qXLHx64PybWBars27fv3nvuIcA333zz61//mnPu9XrHjh37xRdfAGDsvJpY/gkGAlhvu8b9LjgI3DyOiy4LFUlKCFR7yHbVuyUEOGGddwKAW0EoKsLFU88MdSYsKl/yv9zOqQCgLct6FBeg2g/orZYHY9DIqrQgAMpNslTtdK++4VbjOwCEBQlVoOj8bHncFUKqTGsO7VumxKAlLockhAAsoWsrlM3zPXlx7TfEmYKyreJLq/YQD9XCCiB8aWYgh1a6CA6RhP08qlFXzBnnFqgCReGc8VNZnMo5AOoritU1DQDsd5jf3WUuAkBhERA39+vMD2eiuLamn6hFIQ13iUQiaUkIs/vOO+8sLy9fsWLFX//6182bNx84cGDQoEFp6WnBoBkTHfXYY4+99+67APbu3btw4UJCyLXXXltSUjJw4MDzucYc4wAoicr81MzCMaOGOIiyQH9rfGgttJiDSsKBRqdl54aP2KLBWZ3H/czYdcINmWSVTQ9+69HEaryWdUMJ5QxwXm8tuYKtRv0VHR/hlV/Isye6/hiwJfiMEADOTFANIqPIKWcvaQycEI0b14YWdnMTtDS9AxAiq/Y4v5aQtuuNrP53bU6eUFO2HQCYwQIVJrOY6QdAwQAM86+ap78XB/zZGPhH/XKwAD9xhiUL4ISohGjgDLzpC2wsUAAv0iGvOkW1VDKGb5tmLAZAKb4vD/1l88GgxVRnUpNP0RKRhvtPnEfRnxKJpMUizG7G2KOPPnrzzTdXV1fv2LEjMzMzKyvrrjvvpJSsW7Z05aLvUjMyOOeapqWmps6aNWv58uWff/55TEzM+Wy4UzCAjFfzH/fN5ORYCSgIABi1VLUzxfV86M2bokrQuJclNwPUFsO5dUbrAYmI9r3M84k+kLecsp0NoZwBuIKtuSn0ZfjPxuCHmsAq37QN+501CoDw7BKqgVn81Av9NAIDNIHXPOV/pYNLRQsNq+YchOipfbWuN9XmTL0Nl37tjwdg+MqUQGk0q+KG76edrSClGgC3pvoZGnPFnFlgjFANigrG0PT5PQ5KwYNvos9yrZPYVGrP+D4U7+MA6LyS0Gt5BxzMT6Mz0SjRzhGk4f4TpG5RhTTfJRJJ5CL6qJtuumnYsGH33nvvgw8++MMPPwQCgVmzZl177XWxDm3puzNvu+OOxMQEQojD4VixYsV1113Xv3//1NRUxphIKHl+Ikq1t6cVt/s/IzjCnuBMRFwYHDcHRm5zdaYKHcm2dtAq0TjfKrf8xB4Lzs5oPSBhuH/BO9ztnH5kGu4WxAFHuwWh1BAaZXKJlcQDgxtfC75SqLdazNIBgJmgGqE6wOsXQZ5ZFEJqTGykbSzVCaBl+twJAPfA3zuG/yMW3OmO/ziUBXASKC8Ksq9cI1ioFgADBTBX7fN3jARwrW3nPb6PQLTjHVk8jJzV5XEnKsCbPKAS9QoQqB5f/dVkdyUAAux0dZ1mXLLPawA0J1r/RUyVzayFM1VcWNNO1OJowT04Y0xMGXPOGWPiZSY+N9zecAfGmMihdlTrPD8/PxAInLe+KIlEEvkIfzljbM6cOU8//fR999330EMPPfDAA4sWLXrvvfeLS0vnfTQ3kQQGjhpfXlLi9/tVVS0rK7v66qvXrFmzcOFCSul5G+CO+gSQQT12Pu1UEjDx06Q/B7dAKKEKAD/De1bPInsmqPmhPmhxtQ040sw/DOGnD1BbDNiZ9bgTEAA1/urWtLolRlkDYIQC2OPMvc0Yl+83QZQTlqclnANoG9o9WNlzkbrn3tBXAGAZhKhQNM6sU6vQeWLEgZ08tIkn3+y83SD6mTzbGYcQSjgjIP9O2POryjcsDjVYsoXF3hJ9/x7LCcAiKoDv1Y6foDOA7krpeGOVMBpPYCRxC5zVzYT8lFXm5CUEB8B8RX+v/Pe0jFih6iw74VbAa1gApqfof8sI1KpRiqo37RQtlBZsuFNKheuIEEIpFQa3+Nxwe8MdDh069OOPP4Z3FnDOQ6HQ559/Pnfu3HfeeefgwYMigVozXZZEIpEcD0qp3+/ftGnTzTffPG3atC1btjzzzDPr1q3zB/yqpm1dt2rZV58N7dtz5eo1f/nLXxhjaWlpb7311rBhwx555BEA53P/JhY4+hXPnY5bPi8z8VN9dwKimCUb/dveA7cowXXWd+m8BqryrP3i/1Qm4ISGu0gHafqpPRZgYGfQ4y6Cj68KLvg3/wi0RZos4gWc7LDlm/aKQAiNSNrDCQH4YjPpbdfkodh7s/EtAM4tomigKsA4O7PFCighAFSYhTQmT0lX0Ojs/pGKGAF2T0wc5F2uBIrhLcrRA1U0qjzEUReDwPsGN12l7wKwgWS+oY5oTIVazi3OOYgKqnLOm5xVRjwS1dVFeTQd0dlC1YmK+Tb/XwcXAFSYqCjfp0VnNe34LZeWarhblvXuu+/OmDEjGAzu27fv3//+97Jlyzjn69evf/rpp7/88kvO+fz58z/44APLshYuXPjCCy/k5+fruv7jjz/+97//3bJlC+pnnAkhlZWV+/fvv/322y+44IK9e/eeotOdEBJRbnspz/GJNHkQeSJJeY7P2ZSHEMI5d7lc3bp169Kly8UXXzx+/PiBAwdOnDhxyuTJQwYNmnbL7dc//78XX3klPS3ttttuq6ysTElJAfDXv/71+++/f+eddxRFOW8Nd3GT4jSkKIGDPj8AzhnAmb+0+rvfVs69tnbB76zqA26KN0KvdOSHoEankRoXGmuFczNA7cLjLn5yRvQsrqJVqCBX856J458F6i5BMz5mM9o5CBphi3BCATYj2PF5+6RqLXa1lQKAcAZFI1QHa7pntzFwjrKgGWDcT529Apte4XOUcyDkjBAOsOjMF5QRHxeGVteSxfET50V926ZmHQANDCA3+L/6k30tgO+VDrfbbxArgE/wWDML3CKKRqgCbvGm3heLKID5ZbVjeszvwZk4rWpzD7a2eeDjwO1bauYU1LhjWnHg7CxNjhBaXnlYMVO8bdu2hISEIUOG7N+/f8uWLddff/38+fMLCwsVRbn77rtnzpxZUlKSn58/ZsyYnTt3VldXT5s2befOnZmZmYSQKVOmzJs3Lzc3N7xIKyYmJiMjY968ebquDxs2DICYjDaMk57uJIQEg8GICiTlnFuWZVlnI/6vMXDOg8Fg5FgPkaYfAMFgMHJWEIoanAAi5JYRQkKhECLGc3z29SOejX/961+PP/643W6/5557VFUtLS0FIfc/cP/WGit35IQJMcGKwkPZ2dm5ubkXX3xxMBjMysr6v//7v8LCwuM/XZRSTTtuGGtLpu6a9ehnzHeT7UlAAiUEINXf/ob5SzwjHveuecGqyGPR2VtZUlvVZYPrieBsl1sFWik4fjFUAuFxdyXwn7LKnDbqHqy6G0cB9qKvbWun80JYDEqkvGxOEs3mHmOuA/ECjsZ1diTZKGpLCha6h12npZcDhFtQdEJFvnDhcT/NNWsZQIGCgDFmaf5rfVPjFL2VceASpaSu4GgLhwEKJQVx/Z7eSxNCrTslpt8S/FewphoQofBsD0nQaGIW0Ip4u5j7gW7HPR4HiMgqA6KCagCvn6w66b6RAuDG1yUBHpMDwsUhNHvUciPmk+3B3+ZYS0q9A3xlNLq/iJNu2dMfJ0PLM9zF+6Z9+/Zbt25duXJljx499uzZ8/LLL1uW1a9fP0rpc889V1lZSSlt27ZtRkbGunXrevXqlZiYmJiYuH///m7duonP4UMBUBRl4sSJW7Zs2bBhww8//DBy5EjxYmuaI038KqIM94gaSAhhIsdpGmn6ASD0EzkihePQIuSWSXkAJCYmPvXUUwBESdT/+7//E9uNYEXRnl1Rwzo/+NDDXp8vJydn0KBBoVCotLT097//PYDj+CNEsdWzI38zQQBAj+pMih1GPtCPEBglG8ziH2Mu+VCNaeNd/4pavWebien6Df9Tk9oDidzrtCrROGOQmwGiukGV057Hve7shHDOCKHg7C/+HrfFZl4IUyzha2kQAKoz8SWrd/cqDEqqs4+PA+UchN5mLYqlpUvU4Qo3LYBwi1AdyinFUh8fxjklZEO1sTdIu7r0/HLvbpK0VE8fJJKznIlTnkUIAGqb7K78vmpXhb/6rk5R80pHOitXjIRlQNGsqr/bL4k1Mp8GBtN9rwRe4uxCQrUTXLXIJEMVcmr3hQLg9IqiV5397wcywCxOFWqLAug/dlV0io16vrOn1f5tlvMSBS08aOkkaXmGu6C6unr06NEVFRXz5s3r2LHj4MGDCwoKAoHAjh07fvWrX73yyiuBQEAYZG63e+fOnRkZGVu3bo2NjTVN0zAM0zRFtXDxrt23b9/GjRsnT56ckJCwdu1axpjYrutNCR9kjGmaFlHvP0qpqkbKvRb3JaK8ehGlHwCMMV3XI8QqBSBKb0bUIw0gch6hs6wf4VZYu3bt2LFjU1JSFixYkJiYGAqFFEUpKi6+feolq9es7jtnzrRLLnnpxRfnz5//0EMPDRky5M9//vNvf/vbzMzMyNFbM0AAgGj2ffbstwo8v8rkSRrxbXhDS+2txrQBZ8QWi+q9xRY2KZkm0QH+tn2439vmV4CFRhjIpp+oTkLU02i4C4t2TWXghV2VD3eISl37V6QNtre7aJC1vY+mtNSXOAEA6oibRfr1KLUPSkIjLa/WZj5Uey924BX/K5QPZJwrig6qcn6m0kEqhDCgR4x+h2PHPRtwt5N8r3UxtbRB3ABpkQsMGkI5A9G6OYyvKl4KBvbF0f8bg6HtuHckC3DqghXcQNI7EDeAGGrGs33MChLVfiLnuQVwomggCniTK6dygFiV+8awrTTeXictYNoS++DAHxOKbVr7KQmVZaSGOZJa4sj1VIisN3HjoZR++OGHX3755dSpU1NTU1977bUNGzYkJCQwxt5+++2UlBRCiM1mM02zdevWpaWlzz77bCgU0jRNmNQOh0PMCIua4W3atHG5XE8//fSnn37au3fvU3wBR8gMfhgpz/GJNHkQeSJJeY7PWZZHpIX54x//eM0112RnZz/88MNCBkVR5n38UVR222F3P/TIA/dXVFTk5+ePHz9+5cqVa9euTUpKysjIiCi9NQeEcw6i2HXP3/fbvim34D8YyP/BnvtLLhJhuJN93rKOCl4KvJaoBAF8bh/werAd6pMwHh9uBYnuIFSBFQROT4g75+DAV0W1bxw0D+1fFVj3UqhgCQf+Y80ZxvMARWmR0b2EAdAdF1obvEaQN0a7hICzXweH/s8xLo2XTDWWUCvIOCOKTqgGxnBmFqcSziiQZuy65uDzbxRiu9dyIZRm4yJAvMXDOQAltoO3YAUHIZ60rg7DH6oFJxoArv3R+/Ztrn0ANvOkK52/CfFGtAIR406Fg4A2LcZd9FTlxdvmuC+qtmegbpEDFFtUVTD4t3a2S5O1pXl5xBarOOIAnFcu95Y5WAfi4uKuueYa0zQdDkdaWlr79u2dTieAKVOmhEIhh8MBID09Xex82WWX+f1+sTE+Pp5zPn78+OXLl+/du9dut/v9/uHDh48ePXrAgAEOh0M4zyLH2SmRSCRhhIFummZtbe299967YsWKGTNmoC7CHtNvvXXMdbdMvPqGocOHa7puWZZhGISQZcuWjR49OqKmlZoNboGoydR/t3u76h5q7PhEtUfbskaItCVKVGaoam9KsOAavsqiHCDD2Y6DVAMSG+PV46afqC5OdW41utrqiaAEBLivbext7RT967+EnMnwlxFuOo1KvS4LXos0ICkANeo28ztn7EUEg8mJg2UAWHOM9sk2dxUte90++WaLUc4I1UE1gJ0Jj7sInD4YYp9u2j+sfPPvEn9QbOPG+ZfeolUDAwhnLT7SXUx9uFMJONXd8GT/2bnMW/0Kxy8IwBiZElpGnUMAlHDHO9qwFxjsJzymyCpDFUAMt5pyXxiHQrCs0viNftUgOKPq1y4QRbM44Sz4VgluWsuK3UnUEfvTlZwftNRnTlQEdDgcwtclrHbxShMG+mGIPRtuiYqKSkpKSkhISE5O1jSNc+52uyNk+Z1EIpEcB5/PZ5om59xms4V9DSL6OT9vx5aP30rPzPK43Z06dfrhhx86dep08ODBysrK22+/vaysDPU++3ODk11aIHY2iPaod+a0zX/zrnha73azz+KFgdAXpZYrro1m1uwtPfS1vT+jCoDrQwsfIQsA0EY4WLkZJKqdao46jzs9sWAnlJ8AhmU5VMVTtNRWvmFG7nO3mRP2lxy4FNfsdnVGvSeyGWn66g6qK4rusqpWe1leTRAnHIIQdSLbeIFaeEBJu89xW2GQadyAYiOKBsaImHlo6rK0o37FCUDo64fYH/cwV3KXx8y3u9n8brMyQxNFRCPFWGz6LRBubGcidcYTWxSo5lYVJ/OKtI+MBefTTjuRACBNDV1iLoXhQ3hVz9HkAMQkESOKLo5PhOF+/If8CPkJpQDbURvs4CSZDgX16ThBFC22NYo3Bizel+Tb7W6oLqDZlhscLvZZEaOlOmDC2mmophN0fz//SW5ubm5u7nF2k0gkksjEbreLqD9hvgNQFIVxTgjJ6pJ710dL33nwpuuuu+6OO+649dZbX3rppdzc3GXLlmmaNmvWrPvuuy/SVmMLwrXzGg8hxDRN0zRPpt9mIFCzxgR8FRsOHsjuctO/jL4rVhf9ua17ysqim6Nj/2XWfHqo5iXn9GUG0wEDqhkK2Di4aR7PvUoIGAM3GVROdSvotTi4aYCcwFMvslod7xKpcuuG0gHJcTf8+HIoeeDobuP++vWKYEHcWp4aUNzgMEyDNp/tLm4BAErpSbu9COW2aASqXjrAVhWVrhyUolFy7GMQEPJ0aLbbvGQLaTPQ3GR4NcYZB7U44ZyZoSAYuGWclBc8LL+qqkfKb3GuK6q3puxKsimzy+TtW79aX7B3mZq7Qc/txqyQxWgEGAxNagVhOEBgiyN6FNM8ADawpGcdN74YDDgd9lqf7x7tql8FktoBbah3ZuhVPdjPZCnMDOm6zRQtllksXD2LM6LophEEtyxGuMUAYhoheqK2cHgr4ByKxnylV5XNuaxHIme5pmWIWCmi6rbW4ys3z7q5x91XJizl0CyAG6ETNrQzBONc11TGGOMcgGGYSiOG6w1RFOVkb1xLNdxPHVE/VSRFPqwkk0QikUQmIvukWDc/f/789evXezweAKWlpQkJCf996cUt5T606VZTXS2skEAgsH379jvuuGP37t1du3bdvXs3ItU90QSvIWlAo3+kgBC93QRHuwm3bfCl2bUfCgsnJmt9E1xzetF5BTQQDDJvYazSWlU1AO87Ry82st8E6qb+jy0KwDiziKoT1cGtAAFAaGMcgceSnwEKrFWbF8zcGTVxyx9Cxno66b2eHjZfmZUXmtiXrU7DKIhYmua7oWHhmyIDAbHHcW/hXa3Kpuw4dCCY3M5JrWMGPRAAZSaBFtvaZrwSej2dtTIYcSg6oTrAAIsQgJCTcr4eX34VnFDyO/+71Y4f0fbpldu3//GAPYRWu1y53QhBZCS2alIr+OnXAINqV+M6ck8mgFLimalf+GgwlOlAkHM7C8TrCgBG9QrqiWemre5XIOLUR7hPCRg4J4pKCEAoOBOu8pNxujMAZs0BT6AgKr2zRUAoqTshYEsfFFj3Eir3KIaPxLYVN6/ZPO4//3B2coudv4Z7BDqcJBKJpJHceeedv/jFL6KjoxcvXlxeXt6vX781a9Z069nrkSlTCouK7rjzrqysLACzZ89u27Ztp06dqqurly9ffvfddze34MeEECLCfk4KSmkTXFYW54QggVfPP+Cb0Su1a5SdgUxNcU5NcQZ2uy82Vg5lq2yO3xGgSEteZrTiBI2QjRDOFM1BNTthIUoAVW1k6O1RD04BcKZtm/nXxCsujB+mRl+jxedwoFd8dK/qTwLB9Q5tFAhUVW3eqNemZlXiANGjM8uW/SN909srqZpAPiQ09ThGSQgYq9z+X3e3YZrVESUKqy4nRNHsqmYHZwoBJYCqnKw2xNqPY8hPA2YouO+7+KzBsCWkxyRWlfo6sqJ2tAIkXlMiwnBHU1tBPQoAz/C/c6ICaO/g11oLeGAYSFKMyl4OvNI26nEAJbD/0n77k6a7PxUPdl3aYkIbjmgpAIUA4KpqJyKvMeF1beFEMyHhViACXypC/sfVidfRtK4EXFGJEJVzGp+jxnUIbnodhGvR2RSAqjVXjLu4pLDzV1WVszAJc/4a7hKJRNISEa+3K664Iicnx+Vy5eTkBIPBOXPm2O2OAQMGzPnm+zd/WP/YtZMppRwYM2aMWAJ033337dq1a8iQITiGmdhyaUK1MkoIwH+fE39dq5j+sXaIOjEcXsa3uXvlli9p7U5gqgPACLYlwTpAcD1OtBKRM8aZBUUnis4Nv5DshI7AY6ck4gQEoZrutat6jbgHCRMBgJmEqkZS39qlfyVUs2vO+rOc1NWfZk5lYZiz5622thOIaq9d+DuzcJ3SNvWoehYLEwMWdiAF1Ba0Qrc7brmpRuuJEFM0KAo44yKrzMlr41jyMw5KyD/3+HaFBr+WMwXgfTz0afr5fuLtxAuBduCsuSI0juQUa/ZRm1jiiUyn+l9rtma0BnI0Fuxj7KAaBcA5tpBWRUbd52MJAUIYMzmzOFHrJp34ie/LYa2AcaIQ7DQcT2mTrmJAw6panIEqeuYQ34bXqO6hMW1//vXZ5jC187OS3F96nSUSiaTlwRjr2bNnTk4OY8xms/Xr18/hsDPGBnXJefzmaRoY55wA2dnZSUlJANLS0oYMGSIX3wvE3H2mQ+sfZxe11DkHJfihkl0RmPCS2X2WPlIhANCf77/dWiic38c+HgcAKwRCiKJBsXPT/9N5moQIG/4qv3i2e5KhJ3JugZnCJtBjW8P0Es6J6jzFszQrBIDiaaWlD9KSe70TO+1PhbE4btpNhbO/h+a0R3EAtrlq321+onETVAdRwcOVU08blMDg7B/7Qq2jY4gnkYFExWV3q/rBSUxVDQeMnDNwYY8TxXFQTSnz+QAUmur/6ZOKaTSAWF39vfVlW5TV7Xysg0C0FA6qAgDVmlCAiYj6XDX7LrPv7+oSW8LfUQC2thMQ8lreIjWmzc+/Pi+QhrtEIpG0PMTK1FAoJJxV4bpyxDASYIHDrEcs/BIl58S/zS17pCC87DQcPAsMiqEOZ9yf9CtmeKaAmhyoVBM2sQQLJ05Xwq0AiAJFJ6qNWwGg6fYEBwghPsbv3Of+Knq85oplRAGtCwKhnlaqpxUIiHri1HyRDueMGeCsMirnDV9Gjclpg/zovH4AIxTpIqEHg++loVrTbFfwta1YiclJOHtJ0/KFn0g68hTmXuEpA3FyAFGp79mGf0a65JM4AM0803GaIZyAAYSyP7hvfKW2FYDdluth+9XVShQAj67/1vqiM4pwwueaWeCMKCoAomjcMnDi3/wMkcGpa8Wit6OXawTgDbLHk7rxnpLUlSg6tcfgZI/e8pGGu0QikbRIVFXVdV3Etopycqqqqpp2yM9KQlZ4i4gdp5SKQNhzLE7mVCANEjYSAJy5FfJx9qEbaj/sjQKoLgJ8b+9xKbmuNGCAKOz40xVmkFBKqE5UO+o87k2Ec4Dz4hBv49vye205lCjCWZ0jknPqiKfuFBBK1KPkPm5hEEKJAkInRAWu8H0dDNUCP4ViiBskvLgAKkLWXLVfNXE5ddsT1odDscvHFVpvuJ+JAkw6JdOrP8yKjgNRAcCVQjzpnBBNUesFPHcgYk2oqh+wtVlqxAFwIjTcWJ+gEQCMk4Va9z2GrRFHskRACwBQlTOjSbKgyOcv97QTCSZ/9iVnABztJmkpvev8+ucZ0nCXSCSSFoaIeFm6dOmAAQOee+45AM8//3y3bt369e8/YdzYfQcPbdy6ffSI4bmdO//ud78DcPXVV+/bt48Qcv/99//6179G5FWfjQw4BdonJD0a+uDB2tkcNgAOhYCZRl2eymNojAMAq/e4Q7FzMwCgyYYdJSAE2XY6m77b2qkCoHWnJsJqUaKyKNXqi1O2bPNRxEV0SUh+rvbFBLMY4YsEttSE5pf4SL3ffW0Nv8cxvQJOEFpBY7zBAOWMKBpwmg13oWsfw9sHKn6s8mrxOQAIs+DInKzsGMe3JtdFypxjLYhQzgD770Kf3m4tAtDRKpjpfyGaGADAjIdsV34USIOw748NZxYIrcs8QzU0xXAHWOhv1uD/6OMAsMPWPBACwN7hUs+IfzTlyC0fabhLJBJJC4MQUllZefXVV8fGxj7yyCPffPNNenp6x44dbbpt9aqVcTGeZUuXlRQXDx0yJCMjIxAIfP7555qmffjhh//617+mTZsWPkjzXkWkISIfKmj8E9HXH9AzhHa6k5J/Wh/E23ScMFjGDIAoRNGJGjbcmyYGwHmFgV0V5Yq3UI3vAuAn65wQAFpKHxqVAa3le9xRv+AgtsN6K2F/ZQWA8HrRNZX+icsObKv2UzAANYahEGiUgod+5brlZW9mFHxMET5gWlc59XTY0pY4e5Vx9eqCgD1J8aRyCEcv5a40QlWutPwgpaNBOQNwId90UXA5AIWFohGkhHJAUahfcVdYCk6oY26BkLr7SrUmD6g+t9oQZwrqh20NEAlmbNQW07Qjt3Sk4S6RSCQtCVGlaOvWrT169Pjiiy8uuuiiH3/8cerUqe++++4ll17ypz89kpMYu3HjxoxWGekZGXfffbff78/IyFi/fv2vf/3r1157bcCAAYwxabUfDcIBm26bFXPl484rAFhAqhKczFY5FI7jebY5AG4FCFWIohPFxk8hVIZxgJBX8/23r9xGWIDGdwAaDBrE4rw2F3pG/pMIm7XF30rCAaKQV+Ku+3tRtMgpQgmCFr8oJfrCzIwlfgeIwoFBatHrxmsxugJCD+gZewybwk2u2ACQ0+pxF0Eju/3sArq/i4vAlUHEKQAluhWxRRPFjvq5gnMJMXY9YG8938wA8N/q1Huj7gFhALgW9e/QrGuUjQCU45vuzAKoUBeoUh8q03hdcQDcDP7JN/tSx0EA9Ogufn7s7DbnOC3AcBeVkk64WyNnfo+1T3j91knLJ5FIJGcRkXC6f//+H330UWVl5aZNm4Qtnp+f/9GHH11x1VV+YPPmzV6f/6233rr66qtjYmIqKiouvfTSysrK8ePHW5Ylg2SOCiHg4E5XzL/5h9f6vwRAgVIt8RVcUB4I4kSORm4GQRTUxbg33eMuktx8XsYctftiWC2JyhbS/UxU1a6400/hFJGFBYDS9OT2c8spmCWS+80+5J+ycN0M661rDv0He78EkMQqBmOXriiAfqf53QRro48riogXosppNNwVAgp2XZrt05gfTD0aqgNchH9AS+qlJfWAHs1xDgyZDocTAmCts+etfMpub+iRg66s1HaglAOEqoOsvBx2qBFHscKaIVRv4n3xFk7H8lx7CMe0U5ut6FKzE+mGe8Oypg1fNkd+FgWrjr8Pjj07HF6/JV9pEokkwgknD77yyisHDRp0wQUXUEoXL16ckpKSmJxSUFH7+9//bsHChe+///7+/fsrKioKCgq6d+/esWPHxx57TC5OPTaEcg6ol7fNnJiZKszHIj31Fly+qzaIo0zZ/wxuBkAVouhQbMxousddIYRx/q+Ojr+lVtY6WynKUZff8eOmp2xhUM4A/RdRFS9W/ZNTjXMAfGmtGixc49n5Zsm2uR8vnEG4tdDnfl6/SOEMwPWhb6eaK7zEIcaxRNH4aYxx52xdZcDPuFqzTxWZwushioPYok7XiSKTbM2CUVtp8r95X78mpgrQGOMA/59j1EdGGxwnZWddNkgLhIpxDlFUbp3cfRE2WFFN5Ze2AX41Guda9p7TQKQb7oSQdevW7dq1Cz+3uRva6OKz1+stLS09cnvDz36/v6io6KgnKi8v//jjj3fs2CFnkCUSSYQjYl0efPBBl8v14osvio0LFy4cMHAA59ym0meefnrjjz8G/AFCiK7rMTEx//3vf5955pkXXnihuLhYURTpoTg6hAJgna5lbS4WE/ExCu/J9tkb86o0A4ACQolqAwueihSU0B5upX1gB4vLPUpWDQAgJ6xD2YIQS2+zPO4p3m9JqIoScJCrEswHrPn6qGdqJs291v2bH4sLv/HHvWIfL9JFLrf3/D6U6KCcCzOG6rBCwKmu1BVjs/8dCg5ZVlxYWUyClUpiN/zsuOfUkOkwxEW2U2vn8P/1snun136c6XIC4OCANcsx/g2zM46bax8AuEUIERFQICpnoZOSQZjp39bod9tvqoWO07Ns4Zwiclu+eK8UFBS88847lFKfz3fgwAHxVSgUOnTokLCwDcM4ePAgIaS8vHzz5s1FRUVieygUKiwsDH8W+5eVlW3btg1AbW1tw3PV1NR89tlnSUlJS5cuXbNmDY4dUSORSCTNC+dcUZQdO3b83//9348//ti1a9f3338fwNatW9u3b08IcbicXbp1Hzt+/KRJE8eOHWuz2QBomta3b9/u3btfc801IuN7c19H5ELBKbjIGZJEA2+YM9vrBk4U2sutAFEU1GXSYOBNSSsuTjC3yPvOwdpQ6VYtriNw/NpP5wYEAHenveGevPTgQbGwcaSad6G6z9CSOjiCPV3mF0W+JBJoRyqg2QG86Jz6BIa6ud8iKq/zuDcpe0kDuEgPanhnrF/5m46ZrWmZr7ZYT+oGnINRMUeFAByIsdvc/oMvbs+v0pOppxXqDHo1k5XFcu+Jj1LncRcZ1086VEY0gQJ/KN2OBIcD54vuT4LITYEp5oK3b99eW1tLKf3666+Liopat249YsSId9991+fzde3atV+/fnPnzq2pqenZs2daWtrq1at37drVrl27gQMHvvfee7W1td26devTp4/43LNnz3bt2kVFRS1YsCA2NrZHjx7h6eZgMFhbWzto0KDc3NzS0tKwAE0z3xljEbX2i3MuRGpuQepg9TS3IHVEmn5Qr6LmluInhDCR80gLeSJHRWdZP4wxSmlFRcWNN97IGKupqYmJiWGMTZ06tVPHTuCsotL/6KOPvp8SE7DYQw895Pf7b731VrfbrSjKE0888dlnn9XU1ERHR5umKcIMDuOoG88zxK3kADRF78b2Aif2oHMzCKJaHIyonFvgDOSko5LEif+wtWJ8LC4xKqzorJM9QsuEmIDqiv9f7JXkoOvrbOSH+LfbCia4MuMdcZQ6XlI+i6mJS07peK3/dVN7TwUogY+pUJS6hhf2uJ+KEJyBUGvftzN23hGX8pCB1pQoijtNfHn+eH5NZ/Kt9PKCnZVXuxMVdwoABQyg//C9rqitgM4qrOO4fTm3RHp1BhCqnmxFWwoGKJf7F4xhVUTtzblFTr4dndtEruEuXh4DBgyorKzMysoCYJrm999/f+DAgdatW19wwQX79+/fsWMHpXT06NHz5893uVydO3ceP378vHnz1q1b17lz5x49esybN2/NmjVdunTp3r37J598kpGRMXv27BEjRowYMSJstXPOExIShg0b9tZbb5WXl1911VVCAMaYYZz0CJ4QYhiGcImdVn00HbHuNnLmEDjnpmkKLTW3LEDk6QeAaZqIGPuJECLkUVU1ErQkmhh+HgvXvPI0i3769+/fv3//8J+BQOC+++4zTYsZhmWGKsor//jInwEUFhYqivL4448bhlFYWDhq1KhRo0aFQqFQ6ChWDudcVdUIefCaHQ5CAMMWd41y4+/9tu5usGOGp4g8GAFQRSFQdL2GW5xZ9XnWTw6TsQSHcwxbBarRqAwALT1T+4khhDIGxXOHvunp6hyOzC9KjNu3W2VpaVR3A2gbHWVV5NW646HYFKoAeMD6qsI7qzY+zgWOhhU6T0VXnIOgLH9VdEp37P6sqiZfazX0PPP3EgJA9fTSq+8KLXNGx0KxgVlCBSolxDruqmsCAJZleDT9v/uqV9fiWUUzT/K+EM5B0Mqfl6k5wn9KGhK5hrvA7/cHg8HKysoVK1bs378/Pj7e7/enp6cDyMzMXLp06d69ew8dOpSdna0oSnZ2NoDU1NSioiLxSktPT9+/f/+QIUMAZGRklJWVJSQkhEKhhh5xQkhFRUV2dnZubu7WrVuXL18+ceJEAE0uMcg51zQtogx30zQ1rSmvkDOBSBMkpu8jgUjTj0DX9cixn1RVBRA5j7RovLquN7cgdZx9/Yj5wCeffPJ3v/vdXXfd9dRTT+m6Xjfe0237Ny37zW9+s2rpkpra2gceeEBRlKeeeqqysvKZZ5555plnDMPQdT1y5k8iHK675tABV5q27gA7bnQpNwOUap+WWR18LJUSzgwCO8BPzpTkXKVkYR97xfv/CmSM9ERlgh97vHAOIarcT4i1Lih9mvC3KizlUmW7IypZfKuk9Hsyn367v81V0ZNvAWOguaQsGNig6BM+KvS+cdCYpeiEn1KoDAcIVYpqq6+qGvBQ14kjkzxF70xw1oUqWU2YPGm5UN39hG9WMFgTanOjBoCAcUKBD21DdyH5UYAfN8qaWYau6Rz4pND7L0UlJxvCRBRw6zk+oLvLOQpgJGJehBFDC1CIZVkHDx6Mj4//5S9/GQqFkpKSVqxYsWvXroULF7Zr165Tp07Tpk1LSkoC8P333+/cuXPPnj09evRYtGjR9u3b8/LyevfuLT7v3LkzPj5+/PjxUVFRK1euFEcWMQk+n+/tt9/Oz8+vqKiIjY1t7iuWSCSSYyJmC0tLS1944YVXX331008/XbJkiciIpSjK5s2bbpt+Y9BbY3c41q9fL+ID9+3b9/HHH0+aNAmApmnSam8MQkkqVaZaK1KpH8c1wDlg54FdQTp5ffCDQwGXpptNzAjJfRYqVj7HraB7wB/q/f7nASJLesZgxVuQX7TnqmTlCcdK5skEwAA1vt0h5lxo9Nhg6yTuzAKt64v2i0HVbbXG18W+IFRinZLhLpalrqtlC8z0jmmtEZ8bd9W39k6Xh2U7LxDFsBwJNf7qYMirJXYVW4XTe62e8za64URhgZSbQSjrqoLD452apjNxXxr3FDPOQUiZz/cYG7rNnvuTTJIGRPrj6HA4cnJycnNzi4uL16xZM2TIkMTExNatWy9cuLBjx45JSUlRUVHvvvtuXFxccnJydnb2ihUrRo4cmZaWlpaWtnTp0lGjRmVkZKSmpi5dunTcuHHR0dFut/uCCy4IBALh/I+U0vT09BEjRnz22WdlZWUDBgyQbzWJRBLhbN++vX379jfddFOPHj3EmnvLsgghs2fP7n/B4JjEJACapvn9flVV9+zZU1paOmbMGNHjNbfsLQmV0Jn+//QhhTjR4lTLDOqEXJmhT0qL8TGFnGQNJg5wzg3QK1cffGvb9rhhj0BzgJ+kw74FQzigRLfRbe5Llmx/ZlNeNitGbEeIOCRH/DRt5zTf7JHWFmG4LyXtXnROqYbtwfZx/gmZDlU3Ty3GnYJzILl6y1Ps47ToJHCuxbaljgQh22m4vpaBGK3aiKIRqqrxHcVGcf1D2I5LzVUAyHEbgsINH1PeP+S9JN2j23TzJNNBAgiaoWHBtQNdp7ra+Fwl0kNlnE5nv379AIRDzwH069dPbAQwcODAgQMHis9jx44N7zNgwIABAwYc+blt27ac8+HDh3/88ccbN250u921tbVXXnll+/btb7311vDPpe0ukUgiE+Fxr6yspJSaphkVFSUC1lVVtRh76KGHl61ec9dddzHL6tev36xZs9LS0kpLS1u3bv30008DuPfee0XVi+a+jpYBUe3lsKmMO4CGyxPFJ1L/ByEIhgKZTu0/HVSryGEQxSFSuTfa8GacK4RsqzG+Lar8dceRSB/GOSPnj68XIOCMqp7EnLEVu2cWtrnNcLWLa83FeElx94miM/f+mmbex3EVAdIUfytewhW7BfhNblGdnprHXbSInvtm9Ez01G3i7Pys8kOISjQ30T3UmSj+ppwBmGitv9SsACZxxkCPGjskgtxNTrQObr3WZAGm0pPJKkPBAZJCvC/4X4vzPIHI9y43B5FuuKM+hYJwJglEkLQozHSyn8XqMcbYhRdeOGbMGLHFbreLFYrSHSWRSFoETqeTEKKqajAYFEH2qqqaluVwOHx+PwDOudPpnDFjRjAY/Pvf/56bm7tnz559+/Zt3Lixe/fu4dX5kmNDABDFdrXjV7+2si4BrAbWypG6Y1YwSrfNLseMDf45moeYjUic1wBhskQFDj1cM3PAoBvrCrmeV3BGiRJI6n9X+SfjU7JiajmxxQJizShBfOcy7ojSY8TSlqv03RdXP2YkTLloxaEtfu2NkGeIU2T+acpTzcEBlITYl6W2CX0nxAMc7PxNZkIUotqVqKzDIvuDime/ZWQB2nG7DsMynJr+Tu+UoSvLkwPqOGpwgJzMfTGD1XqoQnMnA+fTbEejaQFGqrCkRVhLXd4nShVFadpnYfpTSm02m8vlcjqdLpdLfCvTKUgkkshHdGVt27bNy8tbt27dunXrsrKyQqFQZWUl6qtNi5WywjpfvXq1w+FITk7OysqKi4sTu0kaC8F2tVW+5eCAyD8qrOlqk/kZ5/XFIjngpuyjMvLHHyvyDEcRcyiWj/+0e2POwwFkFX3xe7LIntABwHnlbgcgbDQlvoseKO5X/o09vn1dEkbOAWgxbRRCqGIXu3LVrlOsNmO/KgocCFh7TbvCjCYniBUB7q/vr/qD7RdqbJuwMOcphBDNocblAHU1BDgBgKAjeYrvonU1Jv35QnzGf/aUE2aEqGpXiEdTC01VZUbjB6AWCID3/SnT7dOJXSw4PI9vxDE43/oFiUQiadmIecLMzMzRo0f36tUrJydn0qRJM2bM+MUvfqEqCiHEChlVlZVhk/H111+//PLLO3To8O2331ZUVHTq1KlZxW9x0AdDn1zA9xBAA8A54wzAdWuLblhXRBpU61PAFwRiDEX5W8coFwzLOMmQa0ItYMaeir0d7gAiItVps6DGtSPOpLJtHymi8lF9NkDqTlM86USpS/+1BSm/c93s02L/1DH25a5xnZw8ZBkETTTzRNGWA2UHR7h80THJ1kl6iM8tOAD3gD/YO14GoKFC3Zq208/WVlqHaZn+XFkOGCsCUfdsqfhrh6jhcWqtaTRSlbyubCr/ttZx0J4tSq9KjqQFhMpIJBKJ5DAIIS+99NI111zTrVs3ABdffPGQIUNETEF2lx7//M+rVFFFeO5vfvOb1q1bq6r6+9//3uVyiRxcMk6msVDlLuMbyxgc5J1UyyCqroBUmlhbFawyrf1+M9OhMgYKBAz/BbGuQZ09V8Wz4LqAYQbsjT6JiCVYXlp9e2D4mvQ0AAw47wI1CAW3iO5Ro7PJ3q/VmDaAMNwpAMWdSm3RYHX1aMtp1Mv28b+JWjmtQwxAcRCVVUbjFf4zOFcJIcBvi55GXAcoYymzjhHDfT5AAGipfev/ajAaMoNvuRd2TxjH2U9JGi2O9w/WDI53pNtVYWgr3FgX8iwoM/7XncKjlxaansNPcRTEYhCVACDjgmtG0eUgo07vhZ0zSI+7RCKRtDDqqokrypAhQ6KjowGkp6d36dJFvGBbpyVPGDUibJrn5uaK4lC9evXq0KHDeevKbQIcALeKXDkjf2Stvz34bL5FglW1y/6mFK36c25SVcDY7Q2hPoQmEPRPS8BV8WRJqbLKSlKOX6rmsBMxk3P2476No1zejjHR/Dy02hugJHSizmTiECsjhe3IiS3a0fXasEGZrZs3B7/aa2g1FjZ6sbDGYechXveDo2Ad76lnUNXi7fOiy1Zndb0M52OQ0hFwhiM6Ck5wiba3g4OKB54BdoXsC1q3bCheURFAfUMwmNnBbv6mjWdBhfVhMZzUbEwIEyXwmuz3G4u+rzSmmT9crB04r3LnnxTS4y6RSCQtEs45Ywz10Rpibb1lWQ6wUDDEHc6GlebEPmKFTzPK3LKoW53KvI+3ZgVt0zqUrKj99M/eglUpmnZDn75Wz+T2bh31C7E44dusmNYM/znEqwLd5sJq7Gm4RakdwMSDr41P7KXZR/HzrOLPTxAKQE8fZGszXonKDG8Rt8LZ/Ragbq1qOz34nP+1CSX/+FU5W17DFhR4lqUx69gDHuXYM0yKohbU1IzdpP631xODottwDirno442dNFUfVdQ2V4cmhAvltCAggQZT7erg+McACgIAfyGNTHar2Q7r9wU3LAXlyTBPJGT2OJQFfp2fu0TO6untE8O+qtMVzpQvy5Z8nNkDy6RSCQtElGMQlEUVVXDa+sVRVFUzSAKabCmXyxXFX82t9QtDqJRZahWeFXRmzkLf2m0Gq13ve7ZQud2L5ueHZtuV1Hv4yWKfcCBzksqzLGJjnLiFpXeGzW7odpZ5a6a5Y/Hlq9r024IzusAawJAje8UPebf1BYV3lJHvRuYA4RqX9kHLCDtkzWWohOuOX1cpcdQOAc2VofMo801WZyD4IlNe7225NwOQ8H5eZfMp1EQBuiqtsmnXL6+sjJkAqAEfotn2dW7smO21gRRF6QOnYfWBz0HQxgVr3aJdnktckIPMQUsxjLdjtd6RPc99GVV3ue6Jw1AvRNf8jNkJy6RSCQtEuFE/+KLL3r37v3f//4XgGVZ999//4RJFx8sLAIhf/zjH2fPnk0I+eqrr0aNGlVaWhr+leQk0N2HlvyjfO0bwWHPXqzdMYf0/o0xbI8vlOc18ryiKiQFUGtyprlsCi5J1J5xrwv6K3CiUjXgnBDi3/qu9eml/9u574aM53l8l/ABJYdDKAgRwdDVavyvnLf8Kc3fK4r8IkX5T+tQMFBNjgiUsTgHsKTcP3Th/u/L/KhPIFMHZ5QQo3LPpF1/fytXi7U7uVz+cQwIwFVXls1sZzN2+xkADoQ4d1Ls9Rt/2FoGgIn4GWo9UpL8Un7omhTliXZ6IFBz4oMTDijDbAU3bLylfNFDjg6X2DtcIr44w5fVIpG9g0QikbQ8RKrH4uLiW265pV27dn/605/WrVs3c+bMzz7/vLK09O7bbgGwdOnSgoKCysrKadOmDR06NC4urmHwjKSR2LJGe3rdFjPt8/icCRmourOswyWOwiHuwL2by57fUwlhC3KmWL63WhV2dqtuBX31cjVUdeJDEwKA7/60utWFD6c/1qZVd0Ko9DGeAJFkRnftpYljogyN0gQVPaK4EjqKgSjmLjq49K5x9lrziEEU5wTQKraPNDYMbt0R4DJI5hgQArD4Lq2MQ1918nePdYitDko21ISWlvkTbAoHFBAK+GHbxmItxu0ErV2KYvoacwIf6HdbN+TVmvFXzvcM/nN9zVppox4FqRSJRCJpqXi93rZt27722ms9e/YsLi5esGDBP598cumypStWrLAsKyEhgVJ65513jho16pFHHoH0JjYJR9fr3AN+B8UGbj3eJenDjqF/1bzogj/TZa8x6mIGODNjzIop8b54FV4L9yuXruIZAFgjgl4Mb4ma0vf/OjrvTZd358QIHTkVdlPgyx2GHSDlFh4uyTygpYEfvg6SEgBIsikf9E0dmeAIb6k/FgX4a6X2d5J+yQjh52+E0okQq+Fj2ilGTUbogI0AAAFsFI/trLA4nu+axDgnhBMgFPS+nFF8Vyv9UIj9Ym/SblsbsOCxhqMcsDgIoduqQ1fsT65JG0btsZyZjS+AcB4iDXeJRCJpeYhs7q1bt87JyXG73VVVVePGjUtNTX322Wd/85vf1tbUhIJBm8322GOPzZ49+9JLL0W9k765BW+BcA7OKDhAs210att0p/8Q81X8oV3Mg+1j6ywMFlhHMt+tzbQAjfCP9EHfoC3q8lIfF2bqgeJoT8z0VFua0wb5Vj4xhAOU0iolaomVJsqe/q0ic6fWCjx4mLkn/vzgUO2cg7Vu9QjVEsI4u78080DSGApLznUcH6ZonrisWdt3PX3AAMA4QhwZdu2GzKhMh6rU9y2KUTvK40uzEQ387er4A0rykfdFwBuENh0MmMzwtfE46zfLnuqYnINdRDiCk3N+rM8Ndz7qPhKJRBLJCCs8Ly8vLy/v008/tdlsn3766d/+9jfTND/59JPs7NYM8Pl8tbW111xzzVNPPVVTUyNs/eYW/PAeuBklaSyEgFCAiFBcU08xuWX4yjJtaOe2gYMBhHnnqP0frmpPAZ2Si9S9MWYZgCNz6jWAcwCBoi+ULs94OzEOLodVjYMAUOyr1fbdXBQgLgUDo5h6tFAZwUeHan+1+tBLe6tQH/UefvKqLaWzd93IWALox71Z5z2cA7Al5m4oLnxqZxUDVIoQ44/mxF6V4bl7Y8mmmqC4MyVK7Gve7FqOOJ1emxSKCxXX5Wc/AgLuM0IK4Rzo7wp9Rt+0e1JFgfuze20tjHPQcBe3XLzVwi+qwz6LPY+zj0QikUQyoqfavn27ZVmTJk1q3br11q1bt23b9tprry1YuKi6ptrldJqmOX369FmzZh04cGDOnDmUUpE+snlp+FZucW9oAqiqDs2jBEt3BvH0zjIGTgEw02HVDnQbBJwB/2d+dGvgSwDKcdJiCG+8r/SfyoU/GlGUcH4uvpHPGMoTvpkT6XaA6gTfZ+0aWLME1HVYOkgCcGBkgjPdqb5TUItwmpL6Jy+GBObW/r2HzQ9A4c3fOiIXzijAYnPHm5smJyoGQAnhHE6FeFT64p7KdZVBAOCBHVr2LRXdAoZFQWa2Ku4a2AhqO+zJZpwD+PhQbcfvDhzyhwiQYhT0Dm5S4zoCkO7243OudROBQCA/P19Y5OXl5ZWVlaJ5FhcXl5WVCbv84MGDPp8PgNinqqpKbK+srCwvL29xLxKJRHIeInqtfv36HThwICcn57333hs3btyOHTu6d+8+5IJBEy66iHNUVlYmJSUxxh588MFbb721pKREUZRm9E0YhgGgtrY2PH7w+XyRMJY4WYg7XfUd2lKL3/xYHGCcAJal3BKa/1hysYibDiquCvMEy0w5OACjpiiFen+RogLSbXQyEGWitT6TlwMgQIjoJsjRXeYcN2ZG/aNn8gVxdgAqIZxZVsUuMANAVflerxpDXCmAzGFyXAgAWFFtelh5L+YoNgCcVxps6uqivFrjluzo+kgkHrR4KzuJVgCgjNtriB1HjogI4Zw9s+PQkOIPospWG8A9O4yVJEuNTmeQN+IEnDsFmDjnhmEsWrRo9+7dAwYMSExMXLBggaIoY8aMqa2t/f77771e70UXXWSa5tdff52amjpu3LiSkpIvv/xSUZSJEyfu27fvxx9/NAxj3Lhxbdu2ZYw1OeGx8Nyf3qs7FaQ8xyfS5EHkiRRRwkDKU39SznlSUtLcuXP/8Y9/XHrppT169OjRo0dhYeG+/ILfP/QwIZg2bVpOTg6l9Nprrz1w4MDevXsTExPPvqgiCvHVV1/t0qXLoEGDnnnmmcGDBw8bNqyysvLxxx9/8MEHRfHXlgFnIFSNamVVHWjTDmPTooIWcyoKZ1ZrqzDsWCx1tr60YvibtVZ3t2pxrhz2hHCG+kyRVvm2d5xLnAk3g/PjFAmSHA4htWq0h9pUAODPBXJ9+oRHWYArjsO0yMAP+a1fpHmQBoATEKu2oOyjSxIveq0sqffk9YFfuwZe6ozn53X6/MZAAFBPumKPKTq4KSp7kI3iQMBcWOZjiH2pW1L9Xo5BtUuWtrKrSheAPVSdS/VLXuBBDu0n5XJOCUGw9OWiB13+La5DRkH6Bc8V8Amx3aBqcvB6Qs4Rw1242IPBYCAQmDJlitvt/u6773r06FFRUbF27dpBgwaNHz9+9erVe/fudTqdAwcOzMjIUFV1y5YtV199dXl5eV5eXigUGjt2bCAQ2Lt3b9u2bQFYlhUIBE72lUwICQQCmqZFTqETzrllWaoaKfeacx4MBhEx4a2Rph8AoVDINM0IMU8JIZZlAWheZ21DeUKhEABd1yNEnubVT6dOnWbNmgWgoKAgLi7urrvuArBm0xY9q9Vdd90VDAaLi4ujo6OffvppxpiYbDwWnHNVVW0222kUTzhBtm3bVlZWZpomgKSkpN27dw8fPry8vNw0TV3XT+X4Z3uUSwgAPbpVTf7SXCc+6JfuVADAsIxfa7+cGkoZCwBItWG7n27xsu5u5SjiiTTt3AJQ5S3n9hQn6pZcnr0LOX00V08VP+G/VHjKgX1K0jK1x6PkZ+sd677yW1evOfRaz5RWdsWuEJWAeYtC3hIUr97k7r28Mtg5isMeS3ACR6+4zPDzFhG9cz1noxUQCkBxpzg9qb/bsKeNrf8USmM05c8dE9KdmsFhMO5UCADd8sXqQhpONccWkgL6s1w+INhncv+qt7Kdutrmpj/kefe7Q9dpW9pHuUAcLati8OFPxVlpCxFkrJwKwvnk8Xh69eq1ePHi9PR04WVXVXXgwIEFBQWrVq3Ky8ubMGFC3759P/roo0OHDvXs2dPhcLhcLs75oUOH7Ha7y+Xy+/0ej0ccU1EUp9PZNHk0TVOUSHn8OOemaWqa1tyC1CFmxu12e3MLUkek6QcAIUTX9cgZ+4UN0+YWpA6hmVM0+E4jzasfy7IMw3jmmWceeOCBu++++7nnnpv/7beP/vWvUyZOvPe++2bMmOFyua655hq/36/rusPhOMviUUoty8rJyRk8eLAIlYmLi0tISKipqdF1vXXr1sFgUEhlmmYTxqvCC3D2Ggu3oDqZLdGsLrCCQbeqhIKmQtVCn/GO0m+QYWOhQIjo3GL/pl+0pn0DQQ7eMHc+h2K3Di6BGUDmaIflu5NNbmX3/cs0fIapREyTPynEbT37IU8kupPJLBYIUMU2UdmfHFxqBi9QbSYY4xwhxi0OB8WKEt9ub+hQrX/6uqp/d4ruEevxle/zUI6dc9Na3/xv9dtEjQQMEMsHcrwmzDlXVSUUCpqmGQqFGOeRY7ufpVbALaY67faY+ANrXto3dbDua20n92TYwYx3DnpfO+j7tFeixo3ZSn8z2Pn2oN+ktmnavt3BBUH/hVDUcIZHwq3rN7HOOw482/9CJPWK3vzyO/k1W0MfpzpGBkxCTH8LKkDGOLepihEyTNPklhkIGSfVijnnTTAXzxHDXXjcq6uri4qKhg8f/vnnn2dkZPTu3VtVVcbYjh07hg0blpaWVlFRsX379n79+q1cubKoqMjpdC5dutTn87ndbk3ThJszEAiED9u0wROp5/Rd36kSUfJI/ZyQSFPR2fQlNAYpT0NUVS0pKXn++ednzJjxyCOPXHPNNVs2bZx08eQtWzaXl5dv3br1z3/+MwC73d6MGlMURZh3ANxut6IomzZtcrlc8fHxwg0PgBDShMEPred0inscOAcBdSZRoyZkhW7aWDspyXZpejQBm2ys7OXJBlUUECT3uHHzy6o+3VLaMMZ/MkSYCQJz48tWbZEje3SlP7TWp12QpIEQqlDacuyVhgjlN4OjwQoSQigFKCZoBy4y3tniu3fOnmBF0Gjv1n7VJiZgcULRO9Yxo0dyR4+6tCJQGvIQApt3z1eugZWB9Gt9G9so67zRowgBVZTjz3jUZ7OghBBKKSLJcD9LrYBzQmB4sq+wrxzayUb3KBUhVhLiiTrlhHxd7DWRrBPrTWVgBm13B+WEkmH28mHGtyHOCaUA4yAEMBjdXH7ohhgbbTuOKZ5ptj2Kc611qFyJaUsIQEkLMtzBOQgllBBCQEgT7kITuuVzxHAPe9wJIe++++7kyZMzMjLef//9UCh02WWXeTyezz77rEOHDp07d9Y07b333uvUqVP37t0NwxBp1EaNGrV//36Px0MpFV72yLEJJBKJ5FgIY2Lbtm3t27e/8cYbP/744+3btzsczrLCQ3aHY8WKFdnZ2fHx8c0tJtDAI2sYRlxc3JYtWwYNGhS22gEoitIEw10E25zFHlsFQDxJPkV3sapVXiWt1rhcUdLUwPP+V12eX0DVKKCldttFYtfsLZrcPccGJRxYwaERBJ92Ti31730yWED1+Pv9742PGgpFtStKhMVfnBzNN2nJAVKhx+3Sur64z7e+ltzQyn3f5pKpmbGtbCoHcqK0nChw4Nkuie2jHYSSXYY+NfrRW63vr9j2dq0Fd2JnXSUEjYoQE3GwERVaibPXCjQAwcTumXu+7REd3B8dNSO/2r+/9skOcX3jXE/kJmqaSohrUGhTT2cq1XJ0kGI1/jv7yGm6TrWfNEbM4Fulf+zaZQJxJClAYkrnX5W8ENBAozNVBVBsLagh8LpMU6pCKaGKrtOzUHw3sh6+U0E8sr179+7du7fYcvnll4sPqamp06dPD+952223iQ+apom6JACysrIAhONkpOEukUgiH2G4V1VVUUpN0/R4PH6fb+y48b/45S/vvevOZcuXDx827JZbbvnlL385dOjQU1lzf+qEo+MIIe3bt1+yZEl8fLzL5TrFECOx8vXs9dicgxBii4Hm5jUH7mjdK0PxAzAYL4S7NdUpwABKFF/66OlbQ/GZ1qhYhXFQAnDOCFGCFYWm9u9Q/ytr9N7RZbf555nuiQCOEp3dQmjepSYWh0Kwj8dea7stx1Kf6Bg1OtEZZIwwbnFOQZZW+KM1pbNH/1WbGPGT2pqyu+MrHtRDgY0fw5msxHVgDMqJWoZ4zH4q/BJJt+tstQIOECWhsxIoW70/b8GhaDtFqq4AaOvSHmgXC4Bx5dHA2xpN5+hAgB0s5gb77QODyNTAAcotThSsfWaMspd0uhjcAlG0zGHl61+xZQ5X3GniYlpQVpnwU8Hr/zwLwrec+YjGwRizLEvo0LIsEXsqVh8yxsTDLT6L/RvuA1mDSSKRtECcTichRFXVUCgUMkLZWZlffP11ZmZmbGzsli1bkpOTX3vttWbs2YRpPnjw4MGDBwOYOHGiruu33nqr3W6/5JJLYmNjm0uwJkEAUEe8anMHKvfdnWmbmh4FYE6o7S+d91AqcpwwQGmflNHb2pMXUPBT9XauADzg+1vpP7/x/ald+Q/flJBFVjo86c11MecAwkqyE2s/Yu5vFzsmyQngt21jMxyqQgghuG9T6ev7qwGsrPBvqzUA1tm34dmEvYldrwpZIcUeTWwxOE66fclPEADEnerW9Y/ytj+SV3NFmntqihsA41hVGSgIWJRgH4sKKHXrA1tRbxqv2uszCRgFY0QhVXnP7yqZm/s4NBdjHIAW30lzJVNbNLFFgbMWZLU3F+ea4U4pVZS6VfzhiVcROkkpFXHD4rPYv+E+iLxYZ4lEIjkOor9q27ZtXl7emjVr1q9f3yqjFedc0/WFCxf27NEDQI8ePfx+v3C3S8fEqUIIOCOKDtXNag7UmLw0aIKzd0vRhlQDIQZQcAB6bNtnzTmXuCs5oJA6fxwAn6/yAPcMbNOV7ftq3I6oZa4BmqpYiCT/bYtCaLuVGnwv8GyOUsUBBs6Ar8uNV/dXM84Vgi4eHcBzuyuf3FWNUMVBy1bmaEVdyYonnbpSiKodJdG45OhwSogZ32W0ciBFRwe3rbWjbkLpgc2lM/dXvpwfnIJrS9UkUfqqlRp8J/TCAGcgCFodYpSFCta+8ag1ZEvsBQBnVAG4EtVKSeiouFMAUZ9VtoQTcK4Z7hKJRHL+IGZpMzMzx4wZ06dPn9zczqNGjSKEbNy0ecuWLaNGjUpLS3vllVc6d+6sKIplWdIxcRrgDADTo1zB4ucKydRVhZzQ61wH7wh9DSJKuxMAiOvQzoGk0gWilDcACxTAylDcBZ4najPGFhXv7BzcOcDhA7X/9CtJk7BTjLC2JiIgPHDUX7Bn+Yu3bCzP91tz+qROTnUBSLUrxSY1vWVXqjfOYZ0Bbu99rz1nKjlW5SbJkXBOACOp7yDvsv/kRi2pDJm8rpSYS8X84tpX9lbeaCzM4iXCALeImmMV2Lx75+/eNWTx7vxPrq8uWDOibdfLYw2AKKKYAVHcFzyid7kRwPET+0gE506Mu0QikZyfEEJeeumla6+9tmvXri63O2ix+ISEh//0MICpU6cmJiaKlT+Rk9CzZSNmdN2p3LsrHsGKigJS7v+Fur6SHwB1EACEcs6oLaYwts+DW9S/pfB2Dso4OAjA9/hCuqLExKQTlc/lr8ToxFSj5Zv4FOFEraFuxQppADF8NV//+sKCVdMyswvMrIFRdSOi+9rG1lp0X3VZoWXrHBcNEGfHS4lI59qC0pg0MxyAEt+J7phBAuWfFgWeB2yEAHiuewYUOMyQc+dKk1wplipT1RaAxr75TTc17qDywOykXz4wusNsdxtdDFXrE+JrSd0NC4AcvTYK2V1IJBJJC0Y40SmlF1xwQd0WIDk+3pOeCkBV1eHDhzejeOcqWmzbyk2v9im65K+u9jO/1aK9u0c7XQ0WCHIA8Smd39kYO6HSaOfQGUT9VNKj5IuXHTYady11xnv2zVV63QOCCFvr2PIgVKEExDLAWfX8uxhn8QN/978d/9rMRv91h/FQTgwB0uwqQEpKCv8v9E7f6OEAZITMyUMAqDFt4EgoO7gu1ZmmAOLpbVO1hhevI12uLVVdXDzMnCmejJghf2ZWKCahwzwjyeNyee1w8MOfdc4sWBaUSCnNEeFIw10ikUhaPJxzEcVOCNEosZhlWZYo5hre3twynisQBYA9azgLPdg7qWOfuKyclY6L6Y4p2T6L1M30E1AAnuSuv934SSzrCCTQesO8V/nXvVoNh+qk7jS/t9QelQ7awjJpRCJUATjRnL4Nr5tF6+Ku/M4CyI7ZH/y4+FFvlz+2iyKU7vMG3ygif6zdcp2+VYQJkzpHu9WsorcoCAVnijuZOxNjd6+Y1mq6Sjg4A1EqNrzh3/SWfc8CGH4owuHOQRQ9ayQADvQHAD7qhwM3Z8deme6xuBjK1h+WyEFUY5HTQxKJRNLiEcvuhXXOOddtdZV3G26XnEaoK8Xd42YrbchThYm66b2990BkjKHhSGkRCRCf+3Do40nmegBURMYDLwQ674oZCEBJ7EJtbupIBPBT4hlJE6FEc5tlW/ybZroveIQ6YlVHrJXY03Vw4R87JlBugrPiEHt8R/G/S6MWxU4EmNR4E+GMEEKj29KqXS5VARiIwrxFvDwvdtwLqiPOqs0nVG+4Pzjj4Ixjl9f87pAvSpWW5ykh1SeRSCTnCCJpDKW0uLg4bMQ3t1DnJhwcnIVM87fr9/8+J66tgzJmNRgfEQBE0Y3EnrsKthq8Lp63KGDdpd+4z9EeAI3vSlUn1T3h/SVNhypEsfnWv0Idifb2F4MzAqDNhFusH/7WyoCig9Bkh31YFP91df8FseMBJh28TYRQACSlB+cwjYB4dI3iDcxX4sj9RdToZ2Munq3EdQjvCUJBKAGhBLG68vWwzNFJTgCK9CY0FWm4SyQSyTmCMNOfeuqptLS0++67zzRNWZviDEFAQKhNUbpE25NtKgfYzxc4Ms4B+LMnXrg37YvyukiY/PJDg/m2NloQgJ7YyT3gD0pMG1gyd/WpQhSdW6FQwVJnz9tAqJjBUDNHmkDt6uf9W96uXfZ4Jq39clCrPjyvv4cDqswk01QIB5DUHYTC9AkzMrj/Oz3jAoCDUFvWKGqLEnv+9BsAQJxGxyQ6dfm0nxrScJdIJJJzAc658LU/99xzL7/88gcffLBo0SJKqagxJzkTKITM6582INZOjvAgEjAOpMbEx8C/qMIUCyHb+Ta+yt/NiIoBoOgeR89bqTOBM0t63E8BkchH5YEKPX2QnjUcYCAUnBOqOrv80rfxjcDWOf6Nb/i3fcBAZtb88wK1CIAiV6Y2DfGc64k0KpMFK8EZLDO0b4Gt9WiAgJvg7FihXxywuAwLO1Wk4S6RSCTnDtu3b2/Xrt0tt9zSs2fPHTt2NLc45z5ZTs2jUhxhehMQAEp0m0f1ZZfzHzkoAWIrN7fTA6otCuAAB7NkYpPTg+JQU/s4e95GqAaOevXD2e3GhGuXx176ia37zeq+zx7cXv0J7xBl1xjkWOkU4AA0PbWvWb4DhBrFawnV1eReAAAKQo+lXAIoRCr+VDlnDfejzg43nDU+cgZZTihLJJKWi+jBqqqqhJc9KioqGAyiPl+k5AzBjuVBJJRwxt2tRujFA8o+IQAB7vENmBF1OQDGGEBAFWk/nioiGbhqixr+uK31WKA+tFoolmrUHgtA73SlVrN70Y41c2MnQ3fx8A6SJsAZQPS0AcahVf5V//RveUeJa6d40sGZzIh/Fjg3Vdwgme7hG0WhQQDhz4wxxhjqX2/SfJdIJC0Xp9MpMsn4/X5N0yD7tDMMPY4HkXMCBJP6/qPAsTfIAobxti/N78wAwOVo6nRDVMcxvuEAt0WlBxP7P1Lxwu/JQm5POTdNn7MHAUAd8fZ2k8zClf7Ns2xZowEikyOdHc7Np5cQkp+fzxizLCsUCgHwer2EkPLy8srKSmGvV1ZWlpaWEkIWLly4ZMkSznl+fr7YrbnFl0gkkpNG9F1t27bNy8tbtmzZ+vXr09PTm1uo8xphnTtbDX4y2G1OQUDV2ES+cYTLi3P11dvMHMtqJOCMgKPDlQMrvhnHtsKRQgC5IPgU4SykxuZ4Lnoz5uK3be0mAnUlDiRnmnOtAJNwqy9dunTHjh0ZGRnt2rUrKirq37//V1991b59+82bNzPGxo0bt2vXrh9//DEUCk2cODEvL49znpKSsmDBgpSUlBEjRng8HpzC/LLw5Z/WyzolpDzHJ9LkQeSJFFHCQMpzDCzLIoRkZWWNGzdu0KBBkydPHj16tNjY3KKdpxBCOKDGt72ULClXJ6qFi588+FB0z9chozTOCMdRKgWgp/Sqju9qEZuNqmAWqLQyTxHCTR+ozZY9urklOb84pwx3YbVXVVXt3Llz3LhxX375ZU5OTm1tbXFxcZs2bXbs2NGlS5eysrINGzYoijJ27Fifz1dUVDRixIhgMFhdXd2vX79WrVrZ7XbxnrMsKxAInOw7jxASCAQ0TRPVTyIBzrllWaoaKfeacy5CbyNkBj/S9AMgFAqZphkh9hYhRKQlEWU4m1scEELENJqu6xEiTyToR1EUm81mGEYwGHzqqaduuOGGnJwc8VQriuLz+RpzEM65qqo2m+0MC3v+QADAnnCPe5fy422V5au0jlcoST3AuQwFPqsQAs6I7nF1uRbMAOTI6TQhMm/W1f2VOj1LRJCxcroIBALV1dVz58612Wxut9vj8ezcuTMqKkpV1QULFthstgEDBjDGHA6Hz+dzuVy1tbWEkD59+nz88ccHDx7s379/fHw8AEVRnE5n02TQNE1RImU0zzk3TVNEu0YCYkWB3W5vbkHqiDT9ACCE6LoeOWO/sGHa3ILUITSj6/oJ9zw7NK9+hMOitrZ21qxZY8eOzcrK8vv9+/fvT01NjYmJycvL83q9PXr0OOrKH8mZhnAGorRN6+Rb/axt5HOO9pOaW6LzFUIB7uxxc/2fkdKbtXyIDDo6y5xThrsIXo+Njc3Ozh4wYMCuXbs0TevYseO77747ZcqUUCjUpk0bu92uKEp5ebllWYZhWJYlotvtdnu/fv1Wrly5d+/ehIQExliTwxVIPaf9AptMRMkj9XNCIk1FQhIpz7FoXnkIIYyx66+//sMPPxw4cODChQs//PDDt99+e8mSJc8888x7773XuXPnnj17MsYiZyh4HkEIAKXLDe6cy1RPRr1vUtIshFdPylsgacGcg/24ruu9evX64IMPgsGgy+XSNK1du3YJCQldunTZvn376tWrU1NTk5OTXS5XYmJiYmJiVlYW5zwuLu6zzz6Li4vr06ePqGPS3NchkUgkJ0AE5+zevXvz5s2HDh2qrq7++uuvy8rKLr/88mAwuHPnzoKCgilTpsg+rfkgABRbtOrJAJcVUpsdGdEhafGcUx531Du90tLSbr31VrHF4XAMHz4cgK7rl112mdjYqlUrAFFRoiovJk+eDODmm29ueBCJRCKJcEQAzJ49e7Kzs1NSUnJzcysqKlJTUz/++OP09PRFixaNGDHi4MGDSUlJEbWK4/yDy7h2iURyWjg3+xGx3FDEUqM+qBqAZVkiGlW4qXg9ImCm4U8kEomkpRAKhcJLNWpqai6++OKUlJTJkyfv3bsXwPTp01955RXUx+JLmgMirXaJRHJaODe7ElF/JDw1HP6gKIpYQBaOSRUoinLYTyQSiSTyEV1ZXFxcMBhUVbW8vJxSarPZnnrqqbKysvT09IMHD06bNm3RokWWZVFKIyEPj0QikUiajLRTJRKJpGXTsWPHPXv2PPDAAxs3buzevTuAioqKRYsWjR49mnNeU1OjqqqMAJRIJJJzAGm4SyQSSUtFpJSJjY19/PHH//Of/9xzzz0DBgwAcODAAUpp+/btBw0a9Pnnn0+aNEm426X5LpFIJC0auVxJIpFIWjAiwO+qq6666qqrxBbOefv27Z988knOeb9+/ebOnStWpspQQIlEImnpyH5cIpFIWjxiYX04hF0UtRD/qqoqQ9slktOFnLUKIzUR5myqQhruEolE0uIR3vQjI2EirViVRNKi4Zybpsw+BwCMc9OSqgAAxrh5FnMSylCZ008EviMjTaRIm7KPNP1EmjyRhtTPCTl/VHQOXGlLv4SWLv9JYbepcdGu5pbicJrlFjhs+mlURYt+itxOW6zHedZOR+QU6mmBcy4qiou1YgDCmdda9ON46jTUDADGmPiTUiry04Xn9Jtb0majoU4YY5xzkbSUMSbSlUr9hNuUeGyEigghlmUJXZ3PKhIPDwDLsggh4nPDXogxdm5oSbSOcDcbbinhb8PXfthXktNFw/78sL49/L4TLVQ8ii36eYtMGt8KEHk+snODxrSCw7afXqThfqZo6e9IiUTSggh3OA39BedhL3QeXrJEchgNewPZHM495Gjs9OD3++fNm1dYWAggLy9v1apVhJDy8vLS0lI0WDF2HiI0s2/fPvHnypUr33jjjWXLlgFYsmRJfn4+gP3794dCoeaUslkROlm6dCmAPXv2fPHFF+KBWbp0qdQPgI0bN86ZM+f999/ftWtXIBD47LPPZs6ceejQoWAw+N1335mmyTkXD9j52dB27doFgBDyww8/rFmzRszSLFmyZPXq1YSQ6urqBQsWnBta2rt377x583w+H37eUgRhPaxYsWLBggXNJuU5jejPRUVen883b9684uJi8VVZWZn4PH/+/HfeeWfevHmVlZXNJ+k5SyNbQbg3aDZBz12O0wrKy8uFHVhdXT1v3rySkhKcgS5XGu6nipiQ+uKLL+x2+/z58ysqKg4cOLB///59+/YVFRV5vd7mFrDZYIxZljVv3jyPx/P999/X1NT4/f7Vq1d369YtPj6+pKSkuLh406ZN5eXlBQUF7Cwu7Igoampq1qxZI3RSWVm5ePFiTdM+//zz2traQ4cOSf0AcLvdGRkZ+fn5xcXFu3btqq6uzs3N1XV9165dpaWlP/74Y3l5eXFxccu1R5sG5zwYDL755pvvv/8+gNWrVxcWFu7evTsvL2/79u2HDh3au3fvli1biouLi4uLzwEtlZSULF682O12z58/3+v1fv/995qmffrppwAa6mHNmjWVlZWc840bN6K+f5acOg3780WLFnm93q+//tput3/11Vd+v7+mpubJJ5/cvn07gLi4uNTU1DVr1gSDweaW+lyjka1g1apVRUVFe/fu/fHHHyFbwenjhK3gH//4x44dOwDMnTvX6XR+9913tbW1p10MabifEiLUrLq6OjY2dvTo0RkZGaWlpVlZWe3bt9+zZ49lWVlZWTgvw9yFZkKhUNeuXYcNG5aYmFhbW2sYRiAQCIVCOTk5fr+/T58+NpstLy8vMzPTbre3XJPiVAiFQoFAIBgMdujQoaysrHfv3qNHjwZQUlLSr18/qR8ArVu3Hjx4cFZW1sCBAysqKmpqaqKiouLj4y3LGjBgQFlZ2Z49e3r16iU8zc0t7FlCzIBXVVVlZmYmJCQA8Hq9EydO7N+/f3FxcXV19aRJk/r16ydM2P79+5eWlrZcLYknnzE2evTo4cOHc87z8/P79u0r6sJaltVQD4FAwGazxcXFde3aFTLG9zRxWH+enp6+d+/exMTE0aNHp6amVldXl5WVde3aVdyp3r17t2rVavTo0cnJyedtr3XaaWQriI2NBVBRUdGvX7+OHTsKj6/ktNCYVtClSxdd130+X2pq6siRI9PT00tLS0XI+2mURHZqp4Hq6mqn02lZVlRUlNPp3L179+bNm6OiokKh0KuvvlpTU4OWPD3dNIRx4HA4OnbsWFRUVFZWlpCQQAjp0qWL1+t99913U1NTP//8c865w+HYvHnzRx99xDk/37QEQNO0zp07e73ejz76qLa21ul0Msaio6NjY2O/+uorqR9x1evWrUtKSgIQHx/fvn37devW/fjjj/Hx8Z988klsbKzD4Xj77bc3bNhw/qhItK+kpKQ+ffoId5plWQBsNhvn3O/3E0JUVXU4HGICJy4uruVqSVxscnJyamrq0qVLY2NjTdO02+2Msfj4eL/fn5SU1Lt3b6GHbdu2hUKhnTt3rl27FtLXeJpo2J8XFhZWVFQ4nU5d1y3Lio+Pr6qqys7ObtWqlWmaAEKh0LZt27Kzs5tZ6HOLk2oF7dq1e/XVV+fOndulS5fmFvzcoTGtIDMz0+/322y2wsLCvLy8vLw8YQGeXqThfhpwOByGYSiK4vP5OOejR4+eOHEiAErp4MGDV61ahfPPcA/j9XoXLVo0fvx4TdP8fv/w4cNHjRoVGxvr8/luueWWnJycYDCYmZmZmpq6bdu2cE6e84dQKDR8+PDRo0fHx8fX1taKMX1NTY3H47nxxhulfoRref369bm5uQCioqJGjBgxceLE8vLytLS02267zeVy+Xy+QYMGFRYWer3eFudOPhU454FAQDiVRcod0zQJIbquiwxFgUAgOzt7+vTpLV1Lov/My8srLi4eNmwYAJGTqra2VoxVwnpITk4ePXr0+PHjRZii9LifXkR4xpgxYxITE/1+v6Io4Vsgnj0ANTU1hYWF6enpIi9Wc4t87tCYViBqJO/Zs+eOO+645JJL8vLycF7O+Z9Rjt8KACiKcsEFF6xbt87j8cTHx592AWSndkoIQyouLu7AgQNbtmzZs2eP2+0GsHv37tjYWJfLVVJSYrfbm1vM5kHM373++usJCQkiQsbv97///vtbt24tKytzu92Msd27d7dp06a2ttbv9+u6jvOpixG9sNfrFTopLi7u1KnT0qVLN27cWFVVpSjKea4fgTBGnU6npmkAtm3btmjRohUrVghtVFZW1tTUZGdnFxYWhjMhnj+Ih6G6uhqAoiiLFy/esGFDVFSU3W5ftGjR5s2bRZ64lq4lMXjLz89/7733OnToUFhYmJCQsGrVqk2bNlVVVWmaJuJ/hGcrOjp60aJFK1euFBbMeesxOe007M+9Xq+qqgcPHhRvvaioKEKIYRhiDX11dXVcXJzU/Omlka1AjFc554cOHSotLZV34fTS+FZw4MCBoUOHWpblcrlwul/cLawHj0BEaxkzZsyyZcsGDhwYExNjWVZMTEzr1q2jo6MLCgp69+6N88/eEr1MIBCIiYnZsWPHZ599Vltbm5WVlZOTs3LlynHjxolBak5OjghWtiyrXbt251XuKhH3lpWV1aFDh5UrV44aNSouLq5Tp05r1qyZNGkSgPNcP6i3uizL6tOnj8PhADBixIjy8vJQKDRo0CAAoVCoS5cuiYmJhYWFrVu3djqd59uLym639+nTB8CgQYOqqqoopV27du3WrZuwYvv16wfAMIxzQEuBQCA+Pv67775bsWJFcnJyx44dV69effHFF4tv7Xa76GkHDRpUU1NTW1s7YMCAZpX3nOLI/jwUCo0bN27p0qUDBw4UcdWtW7cW4TFOp7NPnz4tcYgY+ZywFfTq1QvAoEGDhDNo4MCBzSrvOcVJtYLY2NiPPvqof//+0dHRp72/lXncJRKJRCKRSCSSFoAcEJ8exARKeBQkPoiNzSpX82NZlmmaYeWIbEph/YQ3nm+h2w1pqBPxWWyX+gnT0L9gWVZYG+HtDVvf+UZYGw01c+5pScSPis4EP28pgobXLjveM0S4P8fR3nqHdeyS045sBZFAI1vBmetvpcddIpFIJBKJRCI5VRhjvL589ZHRYuGvTuUU0nCXSCQSiUQikUhaAGpzCyCRSCQSiUQikbRgGGOU0jfffHPx4sVOp/PCCy8cO3Zs2DkuEpmUlJQwxpKTk4VjnlLaBO+7jHGXSCQSiUQikUhOlR07djgcjuzs7FdffXXJkiW0HmGgv/nmm0VFRQAopYqiNK2oqvS4SyQSiUQikUgkp4rD4bjyyis7d+6clpa2atWqLl26vP/+++Xl5VdffbWiKD/88ENpaWlubu6SJUs++OCDG264oVevXieb6Fl63CUSiUQikUgkklOFc15WVhYMBhMTEysqKvLz8wcNGtS3b9+3335b13W3252UlLRv37633367devWM2fOLC4uPlm/uzTcJRKJRCKRSCSSU4UQEhsba7PZgsGgrutdu3blnK9evdo0zfj4+G7dul1xxRUVFRWWZcXFxWmaVlJSgpOs8SwNd4lEIpFIJBKJ5FQxDOPrr7+eO3fuu+++O2zYsP/+97+bNm3q37+/z+fjnFdUVMybN09V1eTk5KlTp06ePFlUWj2pMsPScJdIJBKJRCKRSE6VmJiYb7/9dtasWf379x84cGCXLl327Nmzf//+6OhoQkivXr02bNjQtm3bgQMHvvjii/n5+YqinOz6VJnHXSKRSCQSiUQiOf0YhqEoypE+9WAwaLPZmnBAabhLJBKJRCKRSCSnDZEr5rCMMeE/j/ptI5GGu0QikUgkEolE0gKQMe4SiUQikUgkEkkLQBruEolEIpFIJBJJC0Aa7hKJRCKRSCQSSQtAGu4SiUQikUgkEkkLQBruEolEIpFIJBJJC0Aa7hKJRCKRSCQSSQtAGu4SiUQikUgkEkkLQBruEolEIpFIJBJJC0Aa7hKJRCKRSCQSSQtAGu4SiUQikUgkEkkLQBruEolEIpFIJBJJC0Aa7hKJRCKRSCQSSQtAGu4SiUQikUgkEkkLQD3ZH3DOLcvinIe3EEIURSGEHGv/o37FOTdNU1XVw761LIsxdvxjNg3GmGVZmqYBME1TnCJ8Rap6uCoa7hP+eVjg48gp9my4RfxKXDKlVFGUhp8bKX9Yk0L/4fNalkUIofQkxmDiCOKSw4c97HqPI0ATdmh4RsFhWlIUpeEliG8PU++xnhmJRHIWOLIVn+nfnrDPORLDMA7rTE6W45+0CSKdCqZpAjhMb6Zphl/BR76Djnw3nWzPedj7UZzlhHdQdNoNld9QTvHmFZKE92GMiXfZcQ4o3m5i/2PJIC75FO+7RNJSIA1N8NPOyfZxjLGz0PDCUjW5Cz7LfTeOLfMpStJ4hZ9wz1PXSfgUh53r7DwVEokkomiWhh9RVnvjEYJxzjnnDZV2igI3/ucNb9ZpuXGNfws0FDJib5BEcho5CcNdNImampr33nuvsrLSbrcDCAQCUVFRl19+eXR09FHbTFVVVXR09JHHKSoqmjt37qRJk5KTkxv+cMGCBevXr2/fvv3EiRNxmtqhOMjmzZsXLlx4xx13EEJmz56dmpo6YsQIAH6//7PPPps4caK4ovBPZs6cmZqaOm7cOPHzLVu2fP/995dccklSUtKx5BT/rlmzZtmyZcI3IBwVl156aVZWVnFx8UcffZSRkXHRRReVlJR8+OGHrVq1mjBhQiOvwjCMYDDodruXL1++ffv2q6++Wjgevvnmm4yMjI4dOzamuxT7rFy58sCBA1OnTqWUVldXu91uSuns2bPbtWvXr1+/Y+k8vOexDn7kvQ6fcdmyZQcOHLjssssopWJLQy05HI7hw4d36NAhrMl9+/Z98cUXuq5Pnjw5Pj5eOHIOHjz4ySefTJkyJTU1VXbQEslZQ7TZRYsWFRQUTJs27aQc50f2AI3/7Qn7nMPgnM+YMaNv377du3dvchdx1H6skd+eRoT8H3zwgc1mmzhxYrh755x/8skn+/fvF2Z6cnLyRRddFBUVFb7eJUuWrF69un379hdddJE41Mn2nO+//35WVlbfvn0BhEKhUCjkdrt/+OGH/Pz8adOmHevn27dv/+KLLyZMmJCTkwOAMTZ79uzS0lLOuaZp06dPt9vtxcXFH3zwwUUXXZSZmck537lz565du8aPH3/Yy0sIuXv37i+//NLpdE6aNCk+Ph7AsZ7ABQsWbNq06dJLL01LS5OvBsm5D280wsbav39/u3btws1GVdXs7Ozdu3dblhUKhUzTFJNWnHO/33/jjTd+8sknjDHTNE3TNAxD/Ms5X7x4MYDFixeLI4tf3X333U6n0263OxyOSZMmBYNBMVkmDisOIg4ufiUOGN4idhPbhbScc8ZYIBAwTfOf//wnAMbY3//+d1VVo6OjFy5cyBj73//+N3bs2FAoFD4OY4wxduGFF2qaFj7UpZdeKvodxthdd911pJyMMXFpf/jDHwDoum6z2Ww2m6qq8+fPN01z6tSpAC6++GLDMC6//HIAkydPFqc77NLCW4RaGGNr16697LLLqqqqVq5cGRsbSyn9y1/+wjkvKSnp0aPH5s2bxeU3vFniTyGVOLJpmoFAgHN+9dVXa5pmmuaLL754//33ix1iY2Pvvfdey7KCwWBYe+G78/zzzz/wwAPhQ4Vvh9iz4b0W+4e/DYVCnPPbbrstPT1dfBb/Ci1pmiYUFRMT8/XXX4sz/uc//0lJSXG73W63u1WrVh999JHY/vXXXwP49ttvw0+jRCI5C4ie7aqrroqPj/d6vaJXObJPbkj428N6AMZYuLMNd1O8vtMThz2yz2n4rdg//FJo2BWIwJJHH31U9HUN3wLhnzeUtpH9mBDysDdaWAPhQzV8H4VlO+xl1Ph3meiH27Zt279/f17fbYqdO3XqBMBut9tsNkppr169ysvLxU259tpro6KiHA6Hx+MZMmTI/v37GWNffvnlYT2nkCT8XhBXEb4cANdffz3nfPXq1dOmTRODhBtvvDEjI0O85cXzEJaHc/7VV1+lpKTY7fb4+HhxosrKSmEkUEo9Hk9VVZVhGIMHDwYwdOhQYdBfccUV//znP/kRLy/O+auvvpqamup2u+12e0pKypw5czjnV155pXgCxSWIPV9++WWPx6OqaocOHcT1HvZAhm9x+AEIX/Kx9N9I60IiaRZOwvkhBsStWrXKy8szDGPkyJFDhw41DGPPnj3Z2dmUUk3TRJCZiF0uLi5+77334uLiRIyaoiiqqiqKIgLadF2PiYnRdR2AZVmU0qVLl/773/9+5ZVX/H7/66+/Pnfu3NmzZ4d/K/5tGLRHKRUHDA+vxW5ie9g5QQix2WyKokRHR2uaRgiZP3/+V199ddlll82aNYsQMmvWrN/+9reapjHGxHFEXN31119vGEZeXh6l1DCMrVu3jh49OjExcfHixc8///yRcoZ/rqpqu3btioqKAoFAIBAwDGP06NGKovz4449PPfXUJ598wjlfs2bN008//fHHHxuGIaIJxYWIuxLeIpRJCFm8ePGKFSuioqIWL158+eWXz58//+WXXwYwa9asgQMH5ubmisDBhjdL/EkICYc2Kopis9kAXHfddc8++6yiKLNnz66trRXDsKSkJDEk0HW9ofNDqHTOnDler1dVVc55+PhCQs55SUlJ+F4L30n4W3Go6OhoMVMRJqylYDBYXFzsdrv/9a9/AVi/fv1tt902derUmpqasrKyvn37XnHFFQcPHhRWvjD0G//QSiSS00VMTExSUhIhRPQqh/XJDRH9s/hWBDeHewBCiOiH0aCbQn2stjjskX1Ow29FFxR+KRzmj4+Ojo6JiRF9ndj5sJ83lPY4/VjDb4WQDb8NHy0s/2Hvo7Bs4ZdR+Bob+S4T/XBSUlJcXFzDC6SU2u32W2+91e/3BwKBL774Yu3ate+//z4h5LHHHps1a9acOXN8Pt/y5cs3bNhw4403EkJ0XT+s52wYAR++wPDlPP/881dddRWAJUuWrFq1qlWrVgCioqKSk5PFW76hw1vcjoceeqhr165+v79///533XUXgEOHDqWlpR06dMiyrOrq6qioqL1799bU1BQUFOzcuTMvL6+goGD//v1i57AahTZ27do1ffr0a6+9tqamZs+ePYmJid9//z2A2NhY8QSG9wTw3HPPXXnllWIs8cEHHzR8F4eV2fBehF+vDc94mP4bY11IJM1FU54/4dUwDMMwDNQvZFm5cuXYsWOHDRu2aNEi0dU+9NBDgUDgyiuv/O677zjnN954Y25u7sMPP+z1egHwei9O+LDiaKJzv+KKK1auXClG5+LIX3755ciRI2+99dba2loAhJA333yzc+fOv/3tb0OhkDjgtGnT3nnnnccff3zAgAHCx0AI2bBhw8iRI++9997i4mIhOSEkPz+/rKwsMTFxy5YtoVBo2LBhhmE07F4B9OrVKyYmZubMmZzz1atX79q164orrgAgTtdQzqFDh6J+YIP6BTQxMTHhS+OcX3nllQUFBU8++eSMGTNuvfXW8GdN0zZs2DB69OixY8du27ZNvBQPHDhw9dVX9+3b97vvvlNVNS8v7/nnny8uLh49erTP56uurs7Pz3e73cFg8NNPP73tttvELRDnEn3WjBkzpk+fDmD79u1jx45duHAh5/zhhx/+85//DODgwYNFRUUzZsxYt27dnDlz7rnnHkJIMBj0+XxPPPHEwIEDv/nmG9Qv2wUwc+bMdevWzZ49+1e/+pUYXbz22mvdu3efPn16YWEhIeQPf/hDMBi86qqrvvrqK1VVFy9ePGzYsP79+7/77rthnQjlhxFaio2NBRAVFdW1a9eSkhIATz31VHp6+lNPPQVA1/XnnnvO4XCIUUrY09OEh1YikZwiYgLNZrNt3LhxwoQJy5cvv+yyy6ZNm1ZQUID6Fh02lL/66qv+/fv/4he/EKNuEemnqur69euHDx++a9cuAG+88cZll10mWvSmTZsuuuiibt26Pffcc5zzN998U/Q5d999N6XU6/Xee++9Xbp0efvtt0X84cSJE1944YXx48fPnj1bnF0IyRgrLy9/4IEHhg4dunr1atGjlpeX33PPPV27dn3++eeFhKKfPFY/Nn/+fErpW2+91b1797Fjx4qZ4fC3y5Yt27Jly6hRo/7zn/8MHjw4Pz8fwHPPPde1a9fLLrts06ZNAP72t7/deeeds2bN6tatm+i+AKxataox7zIAM2fO7N69+5tvvin8u4fdCMMwxHAIQPfu3WNiYsrLywH84x//uPnmmy+88ELTNHNzc5944olvv/127969brc73HOKC9+5c+ekSZN27tzJOb/++uv/9re/cc6//vrrq6++uqKiYvfu3cLCfv755w8dOtS1a1fUr0/95JNPBg4c+Nhjj4XVqChKKBQKBAIjRowwTfOaa67ZunWrYRi7d+9WVfWuu+4SPnsAlNJAIPD/7N11nBTl/wDw55mZzevuTuD66O4QkFZBBRNFsX4KtmKLHcBXxQIUMEAkpLvjjuOCC667Yztm5vn98cC6UiLc7d3C5/315Xfd23h2dvaZz3zmM58pKysTBMHJyWn58uVjx46VSCSWT235Hj/55JPAwEC6tfL19T169Ohnn32G/rkdoQE6IWTKlCl79ux56623GhsbBw4cSKyq/OmDn3nmmSeeeGLZsmWJiYk7d+4sKioaPHjw888/bzQa6bpqvfzpUvryyy/pt5mbm0sX2qXRBWyJQGdphx1HjuMOHDjQv39/lmWdnZ2HDh36119/YYz9/f0ZhomNjXVzc+vXr9/Jkyf79ev33nvvvfzyy+jCL4qiXVb69u07YcKEUaNGPfnkk5s2berVq1dkZCRCqK2tbefOnU8++WRISMivv/46adIkhNA333zz8MMPDxw4cPfu3TQ3IIriyZMnH3rooZKSEpVKde+999bX19fU1IwbN66+vl6j0bz33nsymUwUxTlz5syZM+fw4cNPPfXUBx98cM8999CEhPW+tSiKkZGRkZGRO3bswBifOXPGaDROnDgRITRgwICLxhkeHo4uhPsIIYlE0tLS8s4773z++ecfffTR6tWrRVGMjo6WSqWBgYG+vr7h4eFSqdTf39/f37+srGzcuHFKpdLFxWX06NG1tbUtLS1Dhw7Nzc2NjIwcPXr0qVOnHB0dvby8ZDJZVFTUxIkTjxw5MmfOnPfff3/Lli3e3t4JCQk0N2D9pURERPz00081NTXnzp3buXPnxo0bMcaLFy+mGfdDhw6tWbOGlqN4eHhERkaKoujs7Lx06dKioiKdTnfvvfdWVVXRGB0h5Ovr6+Dg4OnpGR4ejjF+/vnn582bl5qaeuTIkWHDhjU3N0dGRhJCIiMjPT09c3NzBw8e7OPj4+HhMXPmTFoTdem2x7KUvvzyy7fffnvr1q2zZs1CCBUUFAQHBysUCrqG+Pn5+fv70xeBiRKAzkWjIpVKtXXr1scff9zJyWnjxo3PPPMMQoimJ6k///xz7NixwcHBBQUFo0aNQhcmeRpD79+/X6VSIYQKCgp27dqFMdZqtaNHj8YYDxgw4JVXXlm7dm1AQIBCofD09KRzy4wZM3bs2DFgwIC5c+euXLmSZdm9e/cuXLjQxcXFx8fHMjxBEJydnRcvXtzU1KTRaCZMmFBUVKTVaocPH/7XX3/17t174cKFjz/+OD2Q++KLL152HouKivLx8dm5c+e99947ePBguVw+a9asqqoqWrodGRnp5OTU0NCwZ8+eJUuWREZGurq6Llq06KmnnkpNTc3MzKRbqIqKimXLlq1ZsyYmJubRRx+lcWdTU9PVt2V33HEHQuiHH3647777QkND161bd+rUKescEP0KZDLZiRMnPvvss2XLlj355JNqtfrOO+9Uq9VarbZv3740nBVFcdCgQYSQvLw8Ou1TdFb39fU9e/YszU+vWLHiiy++wBh/++23GRkZNF119OhRqVRKU+yJiYkIIUdHx6ysrO+//97Pz+/ll19eu3at5RAxx3GiKKalpdEdM4Zh9Hr97t27q6ur3d3d09PTJ06caDabg4ODk5KS+vfvP3LkSA8Pj507dz788MP0GO9Fq1lmZqafn59cLqefxcHB4bJl63SNGjBgQFFR0WuvvfbBBx/07NmTroGWByCEcnNzlyxZcvDgQQcHh9tvv/2xxx4LCwv74IMPli9fjjH+3//+Z738Mcavvvrqk08+Sb/NiRMn0hY9luhCrVbPnj27vLz80tQ+ADbyn4trLmTKBw0a1K9fP3rP8OHDe/ToQW+npKTQmrzy8nJvb+9jx44RQg4cOED/mpqaSveJDx065ODgQP9qXXe4YsWKuLg4pVI5ePDg6upqQsiePXtYlv35558JId988w1CqKmpqXfv3sOGDSOE/P777wih+vp6Qkh0dPT48eMJIadPn0YInTx5ct26dQihmpoaQsgDDzzAMAzdyU5LSysuLs7Pzx84cKBGo3nhhRfGjh1L347mjWhh5auvvuru7l5VVTVz5kw67MuOs66ujlyoJieEvP322wghmUymUCg4juvduzfdj4+Jifn+++8JISaTKTY29rvvviOEfPzxxxjj1tZWnU7n6Oi4du3azZs3089ICBkwYMCiRYsIIUuWLOnWrRt968rKyhMnThBCxo8fT8t+UlJStmzZQi5U59Pxsyz7559/fvXVVxzHzZgxo7q6mp5gRAj5v//7v4SEBELIqFGjnnrqKUIIz/PdunUbN24cISQzMxMhtHPnTst3TQgZOXLk008/TQhpa2vDGL///vuEEJpLW716tVar9fDwOHLkCCGkoqLizJkzhBB6aGXlypWEkKeffjo+Pt66xp0uJYVCQdfD7777jlYu9urVa9CgQZaFSQiJj48fPHgwIWTnzp0IIbouQZUhADZDf4xz584NDw8nhBw/fpxhGDqbLViwwNXV1Ww2NzU11dTU0Ml20KBB9PTQ/Px8mp545ZVXYmNjCSH79++XSCR0injjjTfoSYo0Z3/XXXdlZGQcOXKEzucjRoygc05ZWRlC6IcffiCETJ06lcajbm5uc+bMuXScbm5ud999NyGkpaUFIbRmzZqtW7cihGh2+fPPP0cItbS06HS6K81jNL9OK/eWLFmSnZ197Ngxnuerqqq8vb3pX//66y+WZemsSwjJyMiora0lhCxfvpxuVZ944gk/Pz9ayd2nT5/4+HhCyO7du/91W6bVagcPHkwfr9fr/f39b7/9dvLPGvcBAwZgjOnkGRoaevLkSUJIZWUlwzA//PADPYuALnyM8ebNm8+cOWM9c9Jvc8KECePHjy8rK5NKpQ4ODo2NjQMGDKALPDo6euHChYSQpUuXWrY7CxYs8PDwaGhoIIRERUXRhU8LwQkhNPSPj4/38vLiOK6oqCgrK4tup3bv3o0QOnr0KCHEaDQePHhQr9d/8skn8+fPV6vVo0aNevHFF8mFjRd9tQEDBtA9EEtsQP89d+7cqKgonU5HLpTFnzlzxtfXt1evXhKJZNOmTY2NjVlZWZbH0+Uwfvz4kJAQQsiJEyfoF00IiYiIePzxxwkhiYmJ1su/trY2IyODrsb026QnhsXExNDoIj09HSFEz8iyrvUHwGbap1SrqakpIiLCbDabTKakpKS2tjaEkFqtFkWxurpaFEVvb++FCxcmJiampaXR08Mv2nnAGKenpy9fvnz27NlZWVlHjx5NT0+nuXl66mdqaqpOpwsLC+M4Li8vz8HBYe/evRjj6dOnI4TogVe9Xp+SksLzvEwmo7UfKpWKYRg3Nze9Xk8nAoSQKIopKSlhYWFffvnlXXfdtXfv3p9++qmhoeGll15CFxLnNHs0Z86c5ubmP//8c+PGjfR0UkLIlcZpSSrr9frQ0NDa2lqdTmc2m48dO8aybENDgyAILS0toig2NTXxPN/a2iqKYktLC8bY1dVVqVRqNJqKiora2lqWZZ2cnPR6/aFDh15//XVCiFar5Xm+trZWFMWAgIBevXrt27fPbDb36tXroYcecnV1ffbZZ+nRXvq9chw3efLkgwcP/vrrr7NmzRIE4dNPP+3Ro0dSUpJlmYuiaDQa1Wq10WikuzSpqamWpWd9SMT6kbSgJS4uTqfTeXl5ubi4lJWV0Ttra2sFQQgMDKysrJw1axbtEmM5pHsRvV4fHBysUqkyMjJcXFyampqUSiVCSKFQqFQqmszgeV6r1ba1tfn5+SHIuAPQNdAuTz169DCbze7u7qIoajSaAQMG+Pn50bS0wWDw8/MzGo2hoaFVVVXBwcF6vd5SmkyjMRr00D1wPz+/J554Yu3atUlJSbT+kDYVUKlURqOxvLxcKpXef//9GOP169fr9XqtVisIQmRkJD3L0DIwjLHJZOrbt69er1coFCzLNjU1lZWVsSwbHBys0+kSEhIYhqmsrKRh/WXnsfr6ekEQJk6c2Ldv3/nz58fFxb322mt1dXUajUYURTrL0YUQHBxMUzxRUVFr1qwZMWLE/Pnz6Yyn1Wr9/Pzc3d0NBkOPHj0sWwdBEK6+LSsoKDCbzf7+/kajUSaTBQYGGgwG64VPj3g88MADOp3uzTffbGtrUygUhBAnJydRFBsbGzHGdNlWVlYSQugXZP0K9IuYNGmS2Wz+5JNPBg0aNG7cuKVLlzY3N991113owkxLCFGpVHSPBSFkNBr9/f2dnZ1poYtlVPRYyhNPPLFu3bphw4a99NJLPM8rFIq4uLhevXrp9frAwEA/P7/CwkKEEMdxtAL2l19+WbBgwdy5c1Uq1cqVK3/77TfLxgshpFAo6J4VXT2qqqqamprQPzcB9EO98MILcrl8z549M2bMeOaZZ6ZMmfLtt99aXocyGAzu7u7047AsGxsbazabLedcyeVy6+VfVlYWGxtr+TYtx34t0YVCoaADu4EfEAA35PoDd+sDUgqFor6+np7+UlxcTPsq0l+Oj4+PIAjJycmlpaU///xzjx49aGEfsqotob+B48ePz507t7i4GCGUkJAQExNDiwXpaUO5ublKpbK5uZnn+bCwMLVaPXr06Pz8/CNHjqxatYrGiLTExbrjjYODA43/FApFQUEBLX2jZ3w2NDQcOXLknnvuOXny5IIFC5YvX753717LqOi/Q0JCoqOjX3/9dYZh+vbtS5976ThzcnIuWjgcx1mOb+IL14+wnNdifVoV7QyQmZmZl5e3evXqCRMmyGQyWkuqUCgWLly4aNEiuqhZlvX19WUYhlYELl269L777qurq4uOjt69e3dbWxvdeyEXCtNvu+22b775pqCgYN68ebRaMTIykgbH9AQd+m+FQkEPpNL517L0LjqFi37LMpnMzc2NEFJTU6NUKo1GY1tbm6+vr0wmI4S4uLiwLLtq1arx48cPGTLku+++o80fL1pbLK/Psmxzc3NiYuI999yzcOHCtLQ0hNC0adPOnDmzf/9+qVTKcdxff/1VXl5+//33owt7U9e3ugIAbpD1r5jesFQYOjg4rF279tChQ7T1E8dxra2tMpmMVhhmZGQ4ODhYXofWHkgkksrKSnpClNlsfvPNN7OyslatWtXS0vLKK69Yz06enp4mk2np0qV5eXmbN29etGiRRCIhhEgkkosuKkQIkUqlubm5CoWCzvP0hFpBENRqtVKprKqqEkXRz8+P9k+87Dzm6enJsqyfn9+vv/56+vTpRYsW7dixY9OmTU5OToIguLu70w0NxpjjOIlEwjDMzJkzX3vttddff/2ZZ56hM55MJqutrdVoNHK5nFZ4I6vKjStty1asWBEREUFDTJpAaWxstC50sV74CKGXXnrJxcXljjvuoIH74MGDv/rqK57nlUolxnjp0qUeHh4pKSkajebS+fy22247e/bs119/feedd0ZERHz44Yetra0JCQnon1VPdFFY3te67QG6sLnBGD/yyCM5OTmff/45z/Mcx/n4+DzyyCOPPvqoQqFoaGioqamJjY1FCNE+Lb/++mtAQEBwcHBFRcWWLVtuu+22ffv2WVYMhNCdd96ZmZl55swZungfeOABWkhpvQmgN6qrq8PDwx0dHX/44QeE0MGDB2+77baLilgs6y09J5WuOZbgXqvVjhkzhi7/lStXxsbGzpw58/XXX6ffpslkspy5ax1dwJYIdKLrD9xNJpPRaKS358+ff+zYsWefffbFF1/ct2/fU089hRBSKpUsyy5ZsuTAgQN6vd7Ly+vo0aP5+fn0KTShQn9d9Lc0bdq00NDQ22677dNPP50zZ05aWtoDDzyALpxv/sorr3z00Uevv/56XFwcbcF+/Phxmvx+//33HR0dEUJGo9GSfSGE6HS6fv36OTk53X333R9++OGSJUssO8osyy5dujQ5OdnFxcXNzW3FihXvvPMOPQXHsqdOf6V33303bbmYkpJCj75dOk4aVlr/kmtqat5+++3PPvvss88+++ijj86dOyeXy2lXSvoWlqEOHz5cFMUtW7bs37+fnq40cuRIFxcXOuYPP/wwNDQUIeTm5lZSUvL666/rdDqpVHrq1KnS0tJp06Y5Ojrm5+c/+eSTNDeDrCaplJQUlUrl6emZmpoaGRmp1+vpQQOEkNlspvkST0/P3bt3//nnnxhjnU5nGZ4l+rfw9PTctWvXH3/84e7uPnXq1IULF3722WczZszw8vIaOXIk3YYtW7astLSUnibFcdzWrVvp0U904dQ06xek99DZ8LXXXpPL5S+88IIgCHPnzk1MTJw8efIHH3zw9ttv33333ePGjaNlsujCgYLrXmkBANfN8iu2tHRECAmCoNfrWZZNTEykFQ4IoQceeODYsWOLFi2aN2/e1q1bY2Ji6OFHQkhYWJizs/OLL7748ccf//LLLzR/0djYGB0dvWzZMq1W6+LiEhYWhhByd3ffvXv3hg0boqKioqOjt27dmpGR8fTTT+/bt08qlWo0mksPwdFJe9myZe+9997s2bMdHBx69uw5YMAALy+v6dOnf/bZZ88+++yUKVM8PDwcHR2nT59+2Xnsyy+/LCkp2bBhQ0JCwuHDh+nGxd/fn5Y+Llu2rKSkRC6XE6t+4cXFxSEhIYWFhXv37qUzp0KhqK6ufvTRR999991du3ZNnToVWTVgudK2bPHixU5OTrNmzTp69Ohrr7326KOP0lM8L/qYls0Hy7Jvv/322bNnv/nmG4zxhx9+WFVVNXLkSLptWr9+/ZtvvimTyfR6vfXMSYft5+fn6+tLTyrt16+fRqMZN24cLb+xvL6Hh0dJSckrr7yCLhx3tQyA5o8sS8Dd3X3RokXvv//+q6++unDhQoZhgoODv/7667fffvvll1/u3r17cnIyjZgFQfj+++/pRpPjuGeeeebAgQP0UDDdTyCEzJkzJzExcerUqZ9++ukDDzywY8cO2kzZYDBYxkAX5tSpU+mZqS+++CItqXr88cfb2tqsFxqNVWg0bzkRlp5QixAaM2bMsWPH0tPTv/nmm/fee0+hUBQVFQUHB1u+TfqFWpbJZbePANjUdZTX0Pl36tSptPaOlpr99NNPgYGB/v7+q1atIhc6p7722muOjo47duxYvnw5vYzC3Llz6bPS0tIiIyPT09PJhU7hhJCCgoLp06dLpdLY2FhaQEkI2bFjB8uyX3zxRVRU1NChQysqKmjg+/LLLzs7Ow8YMCA7O5vOSn369Fm8eDEh5Ny5cwEBAbt27SKEbNu2LSgoaOjQoW+//XZwcDCtVzMYDNOmTcvMzBRFsa2tberUqREREbQbuqV4mn7M3bt3BwUFvfzyy/SeK43TUllOCPniiy98fX0VCgWtHZRIJOvWrSOE9OvXjx7Foye/0xp3QsjGjRtDQkJ8fHxWrlxJF+bhw4eTk5MdHByWLl1KD8U2NTUNGjQoPDy8tbWVEPLWW299/PHH9OmffPKJi4vL119/bRmGpTvv0KFDadOG5cuXBwYGtrS00Ke89dZbtKpv3759np6e8+bNI4RYll5RUVFAQMDevXutP/LevXu9vLzmzp1LCFGpVAsWLJDL5cOHD8/MzCSEmEym1157zcnJaffu3RqNhl4cauHChYMGDfr8888JIYsWLRoxYgRdPvTfixcv7tu3b3NzMx3S+++/7+vrS7/K5ubml156yc3NzcfH5/3336dlQoSQI0eOBAQEHD9+nECNOwA2RH+zCxcu7N+/PyHk1KlToaGhp0+fJoQsXbo0Ojr60vbkn3/+ubOzM419CSFvvPHGiBEjaM3xt99+6+7u/sADDyxevLhXr170t7x+/fr4+HiJRPLwww/TevHdu3db5pzi4uKxY8c6Ojo+/vjjGo2G5/moqKhly5aRf7YAp+fqvPnmm6NHj/bz87PUoGdnZ48aNUomkz377LO04kUURbVafaV5bOfOnXq9ftGiRa6urh4eHkuXLqUVm6+++qqTk9ORI0dOnToVEBBQVFREX//QoUNxcXFhYWGvvfZabGxsY2PjI4880r179/fee8/BwWHhwoX03Kp/3ZZlZWXRwm4acL/wwgvjxo2bNWsW+Wc59YgRI5577jlCCN1rGjp06JAhQ+im7dSpU5MmTZLJZKmpqbT1MLnczEn//cUXXwQGBhqNxtra2sDAQNorXRCEwYMHv/fee4SQxsbGQYMG0fMQ3nzzzeHDh9NhjBkzhm416H/Sw9rz5s2TSqWvvvoqzQERQj7++GOFQjF69GhatEPvPHHixJ133knXhBMnToSHh0+fPp0OnqLrT0tLy9NPP61UKmNjY9euXUsHvHDhwoEDB1r2Q2jB1bvvvuvi4uLr67t8+fJt27Y999xzdKfOMrw777yTXkjxyJEjISEhtAh+4sSJL7300kXLn64GBw8etHybcXFxBQUFhJDevXtbRxeW7eN1/JoAuEH/4cqpV4/+LzpeeR0Hki59Fq2k3LNnz9ixYwsKCmju+QZf88Z1xGva8vXb3Y0P2PIKYmdc5BwAcBO7xgmqvSZeukl9+OGH6Vmt9E46s93Ituwa3/qij9AFtyZ2N8l3wWUIbnHt8/vBFzqqEkIsZWrI6hwXepCOPuBfX8TyFHrbaDSazWaaLbaUXli/5lVqJyy1bpd9mOW9LK70OtZ/unSc/7J0/o3l1Szl4Nb3XDTIS4ckiiJBSBQvM3jLY+j/X/r5rn23zTIMdMnCtxQ7Wh550eD/FcZYFAmh5zMgZOmNQwihPQUQQoT+QxCcoApA13eVidfSJMB6frjspHeVv179rf91RkXXMI9ZRn7ZIV36juRC7pk2CqupqbFUE9Eb17gts9y4lg9rvV24dNt09YjzGl/8WqbxS8d8pe2+ddRuWW6XvsVFS+NKY7joa7Is1Wt3pcVu+U+I2kFXc3Hx3HW76OpF1rctVdf/+gOwfhHLg8PDw+fPn+/r62v9ItavefWXpa952Ydd46gufcxlx3ndLK92lRtXGrzlMZi5zDCszuP5+9+XfcC/+teFf+mN/5RWYS6MHyOErZ7I4r/vt/o/AECXdpWJ19Ik4NI70RUmvUv/+q9vffUb6BrmsUunsitNmJc+YPLkyb169bJ8Uhp3XuO2zHLjWj7sjWybbvwB1o+8aMzXst2/yge8xk38Zb+m/+Qqix1CdtA1tU+pDOhEIiGXy7ZfBkaIvVx83xUYzYJZEDHGV8uoY4QIwRgrpBzMqAAAAAC41bRbxr3jEEJoh6muuftLOjsL3Kozawzmf104BCGOwd5Oco7tiovxREFjYY1KwjFX2ZHEGAkCcVJKRicHOMo5Qi5zDAEAADodPZnyooYwXXxbBgCwC3YQuGOMr3QRn85F6+BYhhEJQQS1R9XMrQvj8//c4GMAAKDT0S7GF+my2zIAgB2xg8C9ayKEMBeiSAZjmnUnVz393HKKkuUaFjQBQ/+Tngpz2em+Q1lGhTHmOI6Oh36QK5UMWn/Miz4C6ry6QNpk99Kex1d3UYsDujRoSszuuh8AAAAA4OYGgfv1EAlhMD6cWfzZmj31LSqWZcf3j3vijiFSCXeVyhl62TZ62xLj0gQMjRFtH7VfOirrwNc6ELe+bR2aWz6CJZq3vmH99EvvbF/XMvJLh2QdmhNCrJcG/dOlI7/0Rrt/FgAAAACAS0Hg/p/RXPtvu9PnvrdapTVwHEMI2ncq/1hOybcv3e3kIEeXBHM0+Nu4cWNWVhZCaOjQoQMGDEAINTQ0rFq1KjQ0dOrUqVqt9tixYyNGjLBZope+0aZNm+iFqMLCwu65555NmzZFRERUVVW5uLj07t3bMnhs1Wddr9crFAp6f0VFxU8//TRkyJD+/fsXFxd7eXk5OTnRh1nHx5eG7+0b7/I8/8MPP0gkkvvuuw9drrWR9TCsB5Cenp6SkmL56969e0+cOPHggw96enrm5uZ269aNBuhX+Qjt/lkAAAAAAC4LKgH+GxqlNbZpn1+6wWTm3V2UjgqZs1Lu4eb4+6703/ecZjC+tMcLrUXZuHGjr69vbGzs77//npGRUV9f//nnn0dERDQ0NHz11Vd6vX7JkiWWB9vmsyCE1q9f7+Pj07179+Dg4LNnz3722Wf5+fnvvfeeVCrV6XQ5OTk0KtXpdGfPnmUY5uzZs2+//bZer0cINTQ0LFu2LD4+fuPGjTt37qyqqtq/f395eTnd8SgsLCwrK8MY8zxfUVFhMpkwxjk5OfRGe30Keunpzz//3NXVlRDy9ttvE0JaW1vz8/PpA+jIafyt0Wjy8vIQQhjjlpaWkydPbt26FV0os9m5c+eJEydiY2MXLVpUWVl56tSpjIwMlUpFP0JGRoZGo8EYa7XayspKeoO+cnt9FgAAAACAq4CM+38jEsJivD/9XH2zWi6V8DwNsgmLsFTGrd+b8cDEfpe2XKSxXWRk5IMPPogQam5uNpvNhw4dSkpKmjRpEkLo66+/PnPmTGBgoC0/Cx1VWFjYQw89RO9ZsWKFyWQqKCgwGAyOjo7fffddTU3N4MGDhw0b9u6776pUqrFjx4qiuGPHjnnz5gUGBur1+ra2tgkTJqSmpjY1NWVnZ+/bt2/Lli2PPfYYQmjt2rVNTU1PPPFEUVHRmjVrPvnkk+PHj584ccLf3//BBx+Uy+XtEvLSF6moqJgyZUp4ePiBAwcKCgoWL17s7u6elJR0xx13fPnll2q1eujQobGxse+8845SqYyMjLzvvvveeecdhJDRaEQX9mHq6uqcnZ0nTZrk5+cnkUiysrKysrLMZvOiRYv+/PPPvLw8k8m0aNGi119/3cPD4+GHH161alVzc3P//v1vu+02KIgHAAAAQEeDUON6tKi0F13JjRDEMUyzSneVK5jm5ORMnjyZhrmpqalmszkxMZHneUKIt7d3fn6+jRsO0FGdO3duwoQJ06ZN+/TTT++9996JEyc+//zzU6dO1ev1Go3m3nvv3bt376FDh3r37v3FF1+EhYUNGTLk3nvvDQwM5Hk+ODh4zpw5r7zyyvPPP+/u7m42m+fPn//ggw/m5OQEBgbef//98fHxubm5GOOnn37awcHhyJEj9913X1lZWX5+vqVG/AbRwH3BggVbtmy58847NRoNx3E9e/b86KOP1Gr1zp07JRLJ3XffvWPHjvr6+vj4+I8//ri+vv748eO3337722+/LZPJEEL0zNpp06Z5e3vPnTt369at7u7uCoXigw8+CAgIUKvV/fr1e/TRR7VabX19fUBAwIsvvnjmzBmE0D333LN161aDwdBeHwcAAAAA4Eog4/7f0PYxqbHBEpbFCCGMaLTGcYxObeobF8qyzKX9xS257aeeemr79u07duxISUlRqVRlZWVRUVEIIbVaHRAQYKnusNFnwRghFBoa+umnn3p6eiKEampqDAZDa2urXq+vr6/Py8v77rvvunXrplaro6OjEULdunUrLy+nWWqGYWpqaqKiot5+++0TJ05s3LgxIiLCyclJq9W6ubkVFhZu3LgxLy/v3nvv9fT0dHZ2NhqNLS0t33zzjUKhcHNza8dPodVqBUF44oknHnzwwSVLljg6OqakpCCEwsLCSkpK8vPzq6uro6OjpVJpZGSkWq0ODAxsbW1NSkqSyWT0c9GK/Nra2qlTp06bNu27777btm1bcnKyIAgeHh5Go/HYsWOnT58uLS2VSCSBgYEYY4PBkJWVVV1d3b17d5ZlIXAHAAAAQEeDjPt/wzAYIZQUEzR5aGJzqwZjzLIMx7Ktar2Xq9Ps2/oQhERy+SJ1g8GAEJo1a1ZlZeXRo0eHDh26d+/ejIyM9evX19TU9O3bt7y83JafhQaaDQ0NmZmZZ86cOXfunNls1ul0HMe1trZ27969X79+8+fP9/b2jo+P//33348dO/bTTz85OzsXFBSo1WqGYbRa7VtvvZWZmVlUVBQYGGgwGMxmM8/zbW1t6enp06dPHzNmTFNTk9Fo1Gg0rq6u8fHx8+fPT01NdXBwQO3Uj4V2b/zqq692796dk5Pj7OysVCp//vnno0ePnjlzZty4campqfPnz/f395dKpW1tbSzLNjY2du/e/ddff921a9e+ffsQQmazGSF09OjRzz777MyZMzS4b25uZhjGYDBUVlZWVla+8sor4eHhLS0ter3eZDLFxsYOGDDgiSee8PX1lUgkcIoqAAAAADoaBO7/GY13P35y2kNTB+qN5jaNvlml6R7qu3LRnOSYIHpJpoueQkO6YcOG0WKYBx98UK1WR0VFzZ49+6effqqurl64cKFCoZg2bRq60IXQBuioUlJS1q1b9/XXX2/YsEEqlQ4fPlwikQwePNjPz8/f3//jjz8OCQmJiIhITU39448/hgwZ4urq2qNHj+rqanShav/7779vaWkZP358RESEm5ubv79/YmLibbfdtmrVKjc3tyFDhvj6+tLo9rbbbvv0009NJpObm1t75acxxjKZ7IUXXjh16tRvv/02ceJEPz8/pVK5a9eu2bNnh4aG+vn5ffzxx+Hh4V5eXrGxsRKJpGfPntHR0dHR0UePHqX1/bSV5KxZs0JCQr7++uuEhITk5OTu3btjjOPj43v37t2tW7fPP/986tSpPj4+cXFxhJDIyEgfH5+PP/44IiKiXT4IAAAAAMDVwfH962EphskoqKhuVClkkoTIAA8Xh0uLZK76Iu2To23WmjQG87++FEGIY7C3k5xju2Ji+NDZusIalYRjrrI+YowEgTgpJaOSAhzl3JWWdnZ2dnFx8e23346gVyMAAAAAbiJQ4349MD4fESZFByVFn79TEMVLc+3WBEGgF/exXD+VXnaUXrL0Rq6ciq981ad/Rc+ORQhhjFmWpWOgQ7W+jKj1bZ7naVU3/SyCINCPIIqidZRMr6hqOYBAq8Atl1m9+CNgxGDMYHyV/UiMEcGIuVwgTggRBIFeQMrb25vnecu7W0ZOH8YwDO0AQx9vPUJ04cqpLMtaHnbRg+mnoE+hn50uk+tc+gAAAAAA1wwC9+uEMSbkfNkMQQRjfPWoHSF00SU5kdVlR9GFuPk6RiISIojkX0NHgi6fn7a+4KhlkJZ/W4Zkfdv6KdaB70VFPpc2ybH+vBcx8aLOyEtF5nJdeS68F0a8QDgOX5qVp3sO9La3t7e3t7f1J7KMnEbYdJyXXdqXXjn10gdbwvSLgn4AAAAAgA4Fgfv1w9gSw3VmwlUp5Rj87zlfghCL8SUt5ruKYC8HhZSlPXmuBGMkikQuZaXc1cJlQoglKQ4AAAAAcNOAGncAAAAAAADsAGTcbwbXuO/VVbPtCCFECCLX+jkuX+YOAAAAAHBzg4w7AAAAAAAAdgDqgAEAAAAAALADELgDAAAAAABgByBwBwAAAAAA4DrZsuwcAncAAAAAAACuky2vwwiBe/uzXIu066Mtzzt7FNdKEARBEDp7FNeKXh/XLtAr2nb2KK6VHS1YZFezAbhG9JLJnT2K/8COfjL2NRchWLYdyY6WrSiK9fX1NpsWIHBvf0aj0V421aIo2tFvg+d5e5l3CCF2tGknhBiNxs4exbUSBMFefl/IrmYDcI0EQbCXiQjBXNSRYNl2HPtatjzP5+Tk0MVrgwkf+ri3P1seMbmlwILtOLBsOwgsWAD+E/jJdBxYth2EZdmwsDCpVIpsspAh4w4AAAAAAMD1wBj7+/tznI1S4RC4AwAAAAAAcJ3MZrPN3gsCdwAAAAAAAK4Ty7I2ey8I3AEAAAAAALgeoihWVFTY7Jx1CNwBAAAAAAC4HoSQ2tpak8mEbNJVBgJ3AAAAAAAArhPHcTZr2gOBOwAAAAAAANfJlpfEgcAdAAAAAACA68EwTHBwMPRxBwAAAAAAoEvDGHt7e9ussQwE7gAAAAAAAFwnm7WUQRC4AwAAAAAAcN1sdmYqgsAdAAAAAACA6yOKYllZGW0HaQOcbd7mVkMI6vhWnu2ADtIuhor+OVob7twCAAAAAFweIaSxsTEkJEQqlRJCOjr7DoF7+2MwZln7OJTBcfYxTkoqYRCE7AAAADoMz/MYY+sTDQVBIIRwHMRL4Ips2ccdVsT2RPe0qloMeTmNHMMQRIhICCIYY4wZRIhIRIwQZhiEsOUphIgYYcww9D8QRhgz9M4Oj1LtKn1NiIgQXTgkIdQ9wENJiL2MHQAAQFdnCdAteVNCiM26hQD7ZYMLplpA4N7+9CaxpkXHYYZgrFA6sJzEqNOZTFqW5RRKR0JEnVZ9/qEEsRynUDoKAq/XaliW5aQyUeBNRp1EKkMIm81GW57xYC9EQqL8nTt7FAAAAG4qGOM1a9Y4OjpOnDiRhmIY4/Xr17e2tt53330MY0/HqIHNMAwTFhYmk8mQTc5ShcC9/TEYSVmGZVmGZdZ/9+GJfVtnP/1GfK9BLQ21S16f5+bhdd8zbxFCRFGUSmU15UVfvb8wvueAmY++WF6ct/6Hz3oPGTf89pl7N601m0xDbpuuUbfBZHERkRAG9mcAAAC0E1EUGYbZvn17dXW1KIpKpXL48OEY4+3bt7e0tCgUiv379w8bNow+rLMHC7oWjLGbm5vNVgxY/zqEIAhKR6fDOzZsX7fSwyfgf+/8n8Dza75a3FRffebEwc1rvpErHREhJqPh89fnOzi57Nm09uSBbdmnDjt7eJ06tLO5vjb3zAlP30CTyUTPc4V/LvoHAAAAaC8Mw4ii2NraOm/evPHjxzc3N2OMBUHQ6/USicTNzW3YsGH0YZ09UtAViaJos/eCVbBDYMwQUawuL5l2/9Mvf7ZaKpU3VJc11JQ/8uKHk+55POvUIZbjOIm0srSQEPLYK5+88sXaqB4prU0NwWGxEqns3NnTiKA+w27jzSYolQEAAADa0WUrknmep2emymQy2h6EEHLkyBFBELKysv766y9k2/gM2BFb1rhD4N4hMIP1Ws3k2fMnz56/Z9MaJ1d3uYOzyWSSSuUOTs4sx5mMeswwWnWrTqN6cvqAZW8/I5HJw2Lj92xa4+0fnHv6WHzvQetXfNFUX81JpJBhBvZOpCdeAwBAF3DZjBjHcQzDMAxjNpsFQcAYcxwXHh4+Z86chx9+WKVSoUsy7pBZAwghURSLi4tt1scdAve/kXaNLUQiKpWOBVmnVi15a9oDzyiUDkQUMcMQQjBCGDGiKLAsazTqH35+sVyh3LJ2ef8RE2fNe7F7cj+CUF1l2Zlj+7b9/gPLciKBXXxgr0SREEIYjDHGgihafmIiIYIgiuI/fnEEIUEUBVGEIP9W1r5TMQAWdL2qqKiYNWtWS0sLssqg0+J1qVS6evXqPXv2SCSSurq6uro6T0/PH3/88Y8//pDL5eifGXdBEDiOe+utt/73v/8hSMbfwgghbW1tgiAgm6TeIXD/G8YYY9wuC50QwnFSjbp16dvPzJ7/6rDxd3CcBDO4tam+sa5aEASZQung6Ozs5ql0dB424c4eKQM0bc2iKPQaMrYkL9PbL4jnzX2HjW9uqNXr1AzDQtId2CNCEMNgjHF1Q2ubRs8yjOUnRi93wDDYes3GCLEMwzJw7vGti7bhwxhDGASujyAINISy/KfZbBZFkd7geV6v1585c8ZsNls/i+bOp06d2tbWxnHcxIkTq6ura2pqpk+frtFotFrt5MmT0T9T7HQqKywsLC8vRwjRPL3lrzzP03WY53nr+8FNyZYnP9xaXWWsO7NedISLEFJcXOzr6+vg4NAObyQSmVyxfsUXpQXZG1d/tW7F5+9+91dcyoCPXnhIFMWHF77fVFe15I0nH1rwrk9AyOwR0YigR1/+mGW5opyMguy0h19YvOfPNRnH9jo6uckVDkaDHk6IAXZHFAnD4PV7M778bV+bRo8RSo4NfnPuBH9PF4TQ4cziZz7+dcG9o2eMTLG0CeIF8alPfquobf7pzfudHeTQp/9mZWm0d+lUjDGuqqpiGMbPz6+TRgfsmKXtumXVYlnW0oid3pBIJA4ODpeuePTfTz/9NEKovLw8MzOzublZpVI9+eSTFz3MmkKhoH0A6b8t72u5YBNcuelWAIF7+9Pr9VlZWb1797akcyx/IoSYTKYdO3bU1dWxLDty5MjAwEB0Y7VrDMsY9Tpvv6Cx0+/XadUcJzGbDNMffIaTSJxc3QeNmdLSWBca3UOmcHjslU/X//h5j+T+qf1H6HVqQsSkvkMdnVx7DR7T1tzQZ/h4hAgDZXQIIYRoahZbLl4FujAatf+w+ejD76xmGCThOEJIen5FVlH1lo/nOTnIH37353BPlxeW/dkt3C8u3M9k5qUS7pWvNu1PP+flrHz8w19WLZojiqK9XIQYXAtajXDixImkpKRLrw1O/3ry5Mnc3FyTyRQfH9+nTx/ovgf+E4zxhg0b5HL52LFjBUFgWXbr1q1HjhyZMmVKS0vLoUOHwsLCEhISCCFms5lm4q1XMPqfO3bsePjhh2tqauglVO+9995ly5YxzMWbYpqz53me7oiuW7fOwcFh7Nix9E/fffddUlJS3759V61a5e3tPWbMmEt3U8HNgWGYiIgI6OPebuhP5ciRI5s2bWptbR0wYADGeP/+/ePGjRNFkQbxbW1tlZWV8+bNKy0traqqCgoKupGCGYKQSAjP88Mmzhw97T6GYQhCquZGnhdmPvayKAgaVavC0fneJxep21qkcuW8Vz4z6nV6nQYj7O4TMCg4oq2l2cXDa/ZTi/Q6jcFgoFddbcdlYu+gArqLE0XCYFxW2/zuj9ulEtZJKeNFESHk5CA/kVn8xS/77pvQ19lBsXnJk6Oe+OJ4dklcuB9CmBByPKf0gyemDEiKqG9SI4RYiNhuInQqrq2tXb169blz5/r27RsREbFt27b+/fs7OztbptyTJ08+9NBDUql006ZNhJAuGLVflPrp4m610ZaXl1dWVhqNxvj4eH9/f4RQaWnp0KFDfX195XJ5bGxsRkZG3759WZalf72UwWCYP39+Y2Oju7s7rXX54YcfBg4c+MADD1z0SIlEghBycHDgOK61tbWyspLn+bi4uMDAwP3798tkMo1Gk52d7ezsnJubm5CQ0LkHkW61NcGWGIZxdna22WR18wfu9LtPSEhoa2tLSkrKysqKjY2lZ5mgC8dq3d3dw8LCNmzYwHHcqFGjbvAdOQY7yCUcwwgmrdF4/iKpCimHMGPWtmCMHJVSRIhJ06yUsggho6oBM4yjQooQQoSIZp2TgwwRYtI2SxhWqpBeyDV3AEsS2y5cGC2tnEYduFz+hb0ssM4iEkIQOVNQWVxe7+HuZDDzhBCWYQQkcFLubEl1dnG1u7NSEEU/T1etwYQQknCMwcQzDJr3/mqt1rjuw0eigrzgSls3E1q27uPj069fvyFDhuTl5fn5+XEcR6Mfy0a6d+/ef/31l8lk6tevn6WWxmg0durY/8FsNtvR6bOEEJ7n6ULu+kRRNBqN1xcACYIgk8kyMzNnzJih0+nOnj3r6+ur0+mam5sLCwt79uzp7+9vMBi6deumUCiqq6tff/11R0dH6yw4vZ2fn19dXc2yrFarRQixLMswzKefftrU1HRRep6enHrkyJEZM2bk5OTMmDHDaDSeO3fO09OzpqZGLpe7urp269aNZdmNGzfefffdRqOxE5PuN7Jsbc8e19vreCIhRCKRWEq5rtHNH7hTtM2Th4dHenp6cXFxQkICulCTRLcNY8eOLSwszMzMPHjw4IgRI67vXegP0tNFnhwpYTEmiIiiSAhhMIMZRhQEgs5XdjLM+e+JiKJIxPP3ECISESPMMIxIRLrP2T6f/ybx934GyzG1KkOnbDoZjLyd5PDNXBYh51uCcCzr7CgnIjGaeIPJzDCYlTIIYYyQSBAiBGPMMox4YTMmiIRlsFpnnDWml5uT8rXlm/ctexphRGA36eZCv24PDw9CSF5eXkBAgEKhsFQwCoLQs2fPsLCws2fP7t+/f8qUKUqlklYtd5FAme5+iKLYdYZ0dXTp2Uu4hjFmGOa6ly3dx6PNYej5oBKJZOTIkdnZ2Zs3b77rrrv27Nkzd+7c1tZWo9GYmZmpVCrpgXf6dEIIx3GFhYU00W4ZAyGkqanpzJkztEek5e1EUZTJZPX19RKJRKfT0fc1m80Y48rKyoiIiLS0tOjoaKVSGR8f39LS4ubm1onrzA0uWxuzu/UWXW+Z+3WEebdK4C6Kok6no0fHzp49GxcXRydf+teKiorTp09PmzZNqVRmZ2ff4D4xx2C5hMUYYYwdHBQSCdLpRJPR6OzpyDFIIMjMI61GhxEmiCgUjgo5MpqQVqPjJJxUKhUEUa/Xy2VKROcgjO3gR2ZzhBCTuXOaTjAQSF6OSIgoEo5l6F7ovvRzy9YdJKIoiKJCJqW/J45jzCY+0Ns1JTa4qn6LIJKiivoxfbohhDiWQSyjkEpG9e0eF+G/5UgOLZMgcILqTcdkMpnN5vj4+D179iQnJwuCYAmezGbzhg0bpk6dOmjQoObmZhon0XCqs0f9D6IodrUhXQXP8/YyWkIITWNf33MxxoGBgVVVVSqVyt/fn2VZlUoVFhbWu3fv3377rba2Nj4+3tnZuaGhISQkZPXq1QqF4tLXqampSUhI0Gq1dKcRY9zU1DR//vyXXnrpsu/72GOP6fX6sLCwqqoqrVbr7+8vk8mio6Nvu+22EydOnDhxYtCgQcOHDy8rK4uOju7EjPuNLNtOYUfrrSAIpaWl3bt3l0qlNng7+9ibuXHOzs719fX19fU07y6VShmG4S4IDw/38PD4+OOPt27dmpqaeoM7eQQhQaTxBvPO66+ndo87fGCfmeenTZgQFRzaOz7+6XmPMixn5nmJVLb+t18SY2I///hDBydFcWHh3Dl3b9qw3tfNYcumDet/W+vkLDfzPAGXQAhh3Gn/AAtCtwciYTDmWEarN/287eSE//vf80v+6BcX9tz9Y7V6Iy8KLMMwDFPXrPb3cXts+uBAbzelQhowaoHWYBqYFIEQmvve6u3Hzs4c3XPqgq+T73wzNTaYYRhBEOGg081HqVQePXrU3d3daDRGRESwLCuRSOhUrFAoUlNTf/zxx88++ywsLIzWvne1dcAyBdmFW2e0dB8vMTHxt99+27p1a0xMzPbt26VS6R9//DFz5sy+ffvqdDpnZ2eEEN1XVKvVoijSpo0WPM/7+fm9+uqrPM83NTU1Nzc3NTWNGTPmySefFC9hMplEUaQnuYaGhtL3jYqK2rNnT0xMzKOPPlpeXp6QkLBgwYI1a9YMGDAAdeoFm26dNcH2RFHUarU26+PePm3L7YX1NuDQoUNFRUUKhUKv148cOTIgIMBoNNKTgm9Qq0bfrDN7ejqv/O7HRS8tTOnVuzA/78+d+1d++3VjY+2enbuSklN//OU3ndZQV1tz2/CBQ4eP3LNz+w9rfs86k1FRVtrc1Lj40y/efeP1SdPuSO3VU6+3m6K0WwSDkb+r8urTL7G3+jyDwaBUKv/TswhBgihyF7q+lNY0rd2ZtmHfGQ8X5dRhyTNH91TKpQihD1bt/Hbj4aLKRoVMMiAh4s1HxvfpEYYQKq9t/vjn3ffe1qdnt2CE0NLfD6TEBPWLD1vy636NwbjgnlEsgy+bbTebzRzHdbVg7kp0Op1cLoef8EVouw96Y/369bQ7h1QqnTx5MsdxNK7qsj8f2oqkXTYWNnArzEUXsWzoLSlbs9lsvQQKCwtnzpz5119/eXl5Xdq2iD59586dmzZtMplM3bp1e+SRR+Ry+aX7kPRlH3nkEV9f3zfeeMPydnT1tqzkXSRz3C7L1mbsa701m80nT55MTk62FP516Nt1/spkS9ZN3H18fDDGUqnUZDLRI2IXNWG9bgQhBmNBIMVFhc+9+Oq8p57o1b2bRq1+/9039QjNmjLt2ZdeM5t5hmWNRmNEZNTLb7xbV1er0agMBn1UbOzpU6fST6VhhMYN7VfZarCXAAXcOmgqhGEwjdpPni37esOhrHNVkUHeHzw5ZXBSJH0Y3SIuvHfU3WN71TapJCzbLcxXwrH0Jxbs6/75szMQQjQ6f3z6YPrK8+8YYnkjWPdvVtYnY4WFhdFMFS1pJYTQxttdMNcO7IJltbGEyxKJhK5Oln/zPH+Vp4uiOGrUKOtOFVdZGy0XWrLsANC119JOng4D1uebG8uyNvt+b63AnaILNyoqKioq6kp/vaHXRwgzjEatf+q5F7w8HX/8bqWLm5uvn5+GF75Z9o1C6RCfEKdSaTHGUTGxwWFhCZGBKT173TbxNp1G9/WyL0aPHX/k0IHBw0d+8dV3fQYMCgkNM5lM8IMHXYEgEoQQy2CMkYnnN+zP/Gnrifpm9ag+3Z6/Z1RUsPf5hwkiyzJ0MyaIYoCXa4CXK/0T7e+OaEJFEFmGof/JCyKDMcNgXhARLXkHtwCWZXv27HnZP8GkB9qR9erEcZyXl9dVjoMxDCMIgiXKv3pM5ubm5uTkhP5ZI2F5/KU3wM2HYZjo6Gjo497hrCuoOqJjqCiKjo6OJ09kLHpp4ZLl3zs7uxiN/LFD+wcPGymRYlEQ5EpFdmZGaVHh75u3fvrh4p9X/HzXPbO8fLw5Trpnx7aykuJjRw5lZ51596PPDQbDf+0WBEA7Ov9TIYhlMEKotkn1/eaj24+e5VjmnrG9Jw9JdHNWItpfnyCMsfVVk2jrGEIIRhjj8308EUIYYwn391ptidQhZL/VWJoEINtefRDcguiGPjAwcMWKFa6urujKq9y1bHNZluV5/sUXX6QPhs30LQtjLJfLIePe4Tq0vT8hRCqVtLY0PjH3gTfe/fCO22+rbjOqVKrKysqklF46ncCwrLeTdEdJicAL08aP/eXnnwvz8xiMx40Y/NGnS4NCQ1uamiZOmb7h91/UajXHcXCUDXQKeuIpRwN2jI5ll/y8/eThjOL4KP8X5owZ1687fRgviCyDGYwv27uRgVN6wZVBsA5sTCKRtMu1kGg+3sPD48ZfCoBrBzNm+yMIEVFUKmVfLVmSdeb0F59+EBXTva2ttbmpUa1q8w8MJCJqaWqaOHFySGhYS3Ozj1/A9i2b+g8eijA6fbbo1Iljk6ZM5SSSPTu2ubm7Ozg6WDeaBcAGLL1iMMYcyxhM/B/7MqYs/PqpT35TyiRr37l/xWuzadQuioSQ810gO3vUAABwTayP89wg++p/AjoIPcPeNm7djHuHYlhWpzWGhIY9NG++WqWiV8ZSKBSzH5grVygEUZDKZLE94gKDgn9Y8/vXSz4bO2HSoCHDNGqjKIjDR49xdXG8bcKkhvq6iZOnQa4d2JggiAzLYIxZjGqbVGt3pv22O10pl04eknDPuD4uDnKEkCgShBDDYAba2gMA7E07HueBDTQQRTE/Pz8hIcE2zaZurXaQttGq0bcaRQYhJ2cHuQQxCBGEGlv0mGEcHWVtrTqECMOybq7y5hY9x3HuThKNAWk0GowxJ5EoFNLWVo1UKnF1kak1vNFgxBAbIfT3JTQ7+1qaDEYBN2M7SIVCQXvF0DszC6u+/uPQqbyyYG+3uZMHDe8ZTSvXaSF7J8br0A4SdC5oB9lxoGVhx4Fl23HMZvOJEydSUlKgHaS9wghJGMwwjFal0ZDzx+M4ToKIqG7VSFgWYQYR0tyo5jiO8Ob6Rj3DsFIJhxAiIq9VmxRSjhCxuVHNsqxUwiLYubpQTWh9o7PcfLtRokgEUaQnfRBENu7PWrXtRFlN07DU6OUv3Z0QEUAfxtNeMVcoZAcAAABAR4PAvf1JGOLtJGMYBqGunpIRRQEhxDB2cC48xshkoldpkXTujgy+WfqLE4Lo/ziOdXJUNrVpV209vvFgliCId4xMmT78Th/38z3OaKt16PcCAAAAXEoqlUJXGfvGMdgu6lswwQh1ZtnDf0KHCRnfG2fVKwYjjDIKKn/cfOTgmeKoIO8nZgyZMjSJPowXRIbBTAe2XwIAAADsG8uysbGxcrkcQR93+9XZZdjXCkpwbjVWFz3FvCDuOpH3/aYjJdVNfbqH/Pja7PgIf/owUSQIUuwAAADANbBlF38I3AG4JQiiyODzVy9oVml/3ZX+y640QtDtg+K/fO4OH3cneqq6SIjlaqYAAAAA+Fe2PDANgTsANzNLhTrLMAihgvK6b/44fPBMkY+70zMzR4zuEyuXShBCGo1WqVRiBrNQFgMAAAD8FyaTyWYXT4XAHYCbE700EssydCbZeiTn5+0nc0tqByRGfPncHb27h9CH8YKIoSM7AAAAcF0EQcjJyUlOToZ2kACA/4z2iiGEsAyDEG7V6H/dmfbbntM6g2nK0MT3H58c6O2K/tkrph0vIggAAACAjgOBOwA3iX/2isG5pbVrdpz660h2sI/7/RP63TkyhV5BSRBEDL1iAAAAgHZiy8vLQOAOgN2z7hVDCDlwuvDbPw/nldUlxwR99fzMnt3OV8XQXjEs9IoBAAAA2o/NCtwRBO4A2DV6xVOaPtfqjb/tSV+zPU1jME7o3+O9v6tikEhE6BUDAAAAtDuWZbt37w593AEAV3RRr5iymuZv/zy0+1SBi5Piwdv7j+vfw0kpQwiJhCCCMMb0YQAAAABod1AqAwC4PJEQIv7dK2bPqfw1O06dyivr3T108fzJg5Ii6cN4QWQZDFeZBQAAADoaY8PsGATuANgBcj7LTliGQSzW6I0b9p9Zvf1ki0o/rn/3l+4bG+bvgf7ZK6azhwwAAADcErRarUwmgz7uAABECBJEkWMZjDHCuLi68ZcdaX8eOOPh6jhjeMrMMT3pFZQEUcQIMwz0igEAAABsRxCEvLy8lJQU6OMOwC3NqlcMgxA6cbb06/WHMguruoX5fvTktIFJEfRh53vFQBU7AAAA0BmgVAaAW5p1+txoFtbvPb16x8mGFvWYPt1fum9MRKDX+YcJIstCrxgAAACgMwmCYLP3gsAdgK6CptgROp8+r25s+3Hzsa1Hs2VSyb1je90+KNHNWYn+LmTH0JEdAAAA6FwYYycnJ5p0h3aQANwS/r7oKUYIoSOZxWt2nDp4pjApKvDVB24b3acbfRjtFYPhoqcAAABA18AwTHR0tEwms83bQeAOQKchCCFCREJYhuFYbDCZtxzOXrnlWF2LZlhq9K/vPBQd7E0fKYoEesUAAAAAXZAoijZ7LwjcAegctEIdYcxiXNXQ+uuu9N/3nFbIJdOHJc0a09vZQY7oiacIMQyGQnYAAACga2JZ1mbvBYE7ADZl6RVDK9TPnKv6+o+DaXnlIb4ebzw8fnjPGBqj04ueQrwOAAAAdHFtbW1SqdQ2vWUgcG9/BCGREGyT698ShLAtzoUA7UAUCUGEZRiMkUjIhv1n1mw/WVzdNLJ37Pev3Nsj3I8+jKe9YuCipwAAAECXJwhCYWGhs7Mz9HG3VyxGnK0OmkBo1/URguj/GAYjhBvbNKv+OrHxQCbB5M6RqUuHJnu7OyG46CkAAABgn6CPu31TG4SqVpUtLoiDkSgSBxnn46bo8PcC/93fvWIQRhil5ZWv3Zm2+2R+dLDXMzOH3z44gT6MF0SGwQz0igHgZkEI4XmeZVnL5tz6nkv/CgCwa9DH3V7RQyT1KtPxc00cw4iEECJihPEls7MoigzGCGMiigghzDCIEIIIxv9hHscYG81CmLejj5uCJmtBF0EIEURRgjHHYl4Qd57I/e7PIxX1LX3jwla+Pjsuwp8+DHrFAHBTwhhLJJLL3kM3Exf9FQBgvzDG7u7u9PxU6ONulzBCHItZjKWcRK50FHizQa+l1egIIUIQRkjm4GQ2GUVRkCodESEmkxEhJJHKTEYDxrRN4DW8EcYC9BvpYgSaPmcYuUzW2Kb9bVfaL7vSCSJThyTdPbaXp6sjQkgkhBDCMnDRUwBuTm1tbcuXL588eXJkZKQoigzD0HuGDRuWmppaV1e3atWqqVOnhoeH26AiFgDQoRiGCQsLk0qlNno727zNrUYUCCeRVJcXLZw9evX/3mc5Ka1gJgQhQhhOsvyDF/KzTkmlip+WvL12+Ycsy6nbmn/99iOpVCYKIkHo2v8BXQEhRBQJQYhlGYxxXlnt05/+NvHZ/20/fva5u0fs/OKJp+4a5unqKBIiigRjbItKKgCAzdF2zv/73//8/f2///775uZmjLHZbP7yyy9DQ0PXr19fXV393XffBQYG/vzzz01NTZ09XgBAO4A+7naPYRij0fjF6094+wUd2LYuIDRy2Pi7VG3NGCMHR5cTB7buWL9y4OgpBdlpep3G2KwvL84rL8x1cfVAGBM45dSuiCIhhLAXLnr615GcNdtP5pTUDEyM+PLZGT27hdCH8YLIMtArBgDbEQQBY2zLOnJCCMMw9fX1QUFBs2bNWrlyZWNjo7u7u8FgGDNmTK9evbRabXp6erdu3aZMmfLrr79WVlZ6eHjYPukuCALDMJDpB6C9QB93+0YQkUhlZQVZGKO5L36gUbXKZAq9XsOyLMJYq2nb+ccqJxd3jLFW3ebu5avXaJobaoryMu+au1AqlRsN+s7+BODf0V4xtOIFIdyq1q3ZmbZ+z2mD2Tx5cOL78ycHeLki6BUDQOex5aaUoiF4S0uLg4MDz/O+vr5arZYQ4ujo2KtXr4KCgpKSkttvv33JkiVeXl7Hjx/38fGxPMuW47T9kgHgJkYIaWxs9PPzs80vCwL3DkAQwlirUWnVbU9OH+AfGrlg8XcYYUHgnV09Nv78v5CoHg5OLmpVa0x8zx3rV7p4eDbWVvkEhuaeOY4QTu43zGQ0QC6kc9GGMPj8l4msK1v+2SsG55TUrN2R9teR7GBf94cmDZg+PJleWclgMEplUugVA0Bn2bVrl7+/f/fu3W0cGTs5ORkMBo7jmpqaQkJC6Fs3NDT8/vvvjz76qJub24wZMzZt2uTt7R0QEIBscjbbRTZv3hwfHx8SEgIV9gDcOFEUS0tLPTw8bNPHHbKAfyM0O9pOGJY1Go2Pvvyx0sFpz8Y1MoUSY9zcUHNk18Zeg8Zo1W2q5kZXd6875i4Yf+dcrVolk8pOHdyxb/Pa2spSiVSKbHL9JnBZ9IfHsQzLMhzLsAxD69fJhQp1jmUEQdx9Kn/Wqz888Naq+hbVNy/O+mPx3DtHpWIGC6IoiCJmMBGJIIjtuFIBcCu4xqn4Sg8jhNB6008//XTHjh3Ihp3aGIYRRdHX1zc/P3/Xrl1nzpzx8PAoKipSq9Uvv/xyQEBAbW2tWq3Ozs6eOHGiyWRydXXtlND5jTfeSEtLQwjxPG9ZhtbLE2YtAP4TKJXpHHT2bIdpFCMiis6u7kpHp8Fjp1aXFapbWzhO4urunXF8b0FW2ssPTUAIVZac65Hav1tir6K8M6rWpqDwmLDouPKi3Lqq0oCQCLPJBGmQTiESwmCs0hrW7UmvalTJpNywlOie3YIRQghjjJFKa9h0KGvjwczmVu3wXjEfPjmFVsVQ57t8EiKTSuBsBQD+K8sMTJuxXOWR1hO19byNMcYY0wIVmUzWoaO97KgwxnPnzv3ss8/uuOMODw+PAwcO9O3bVyKRHD58uLCwcMGCBWFhYcuWLXv00Uc9PT1FUbR94O7i4kI7YFh3pbTeAkIaHoD/BPq4XxOaEqATNL3nsret7xRF0Ww206n8oomJEFJYWOjn5+fo6HiDA8MIm80m38Awb9+g2cOjEcYLP/jh4PZ1GUf3znn6jTf+t16mUCx96+khY6d7ePsZ9Lrtv6/oM/Q2paPzif3bTEadh7c/z/Mwa3YKQgiDcW5p7X1vrjqRU0Ir2V1dHN9+dMLj04eUVDd9veHg0cyS6qa2wryKb9958MHb+yOEBEHEGNc2t81+fUV0iO+S5+5gGPz1+gMfrtpl0hm/XjRnXL/uvCBCmTu4KV121kWXTNHWU7HJZGIYhuM4dMlUjDGuqKhgGIaWkVxFQUFBcHCwXC63vAjP8xzHtba21tXVxcTEiKIo0pPH2/Vo6r++ICHEz89v8eLF9D8jIyPnzJlDr7gUHR0tlUpTU1NTU1PRhSi5Q9Pblx2tJcg4e/ZseHg4XYYtLS11dXWxsbGEkNzc3LCwMIUCLu0HwL9jGMbHx+eyE1pHsOPA3Tq/cumdl31AbW1tVVVV7969rV+HEGIymbZv397Q0MAwzIgRI4KCgtANLH2MEEYix0kff+3TjT/9LzaxT2KvwScPbguJjJXJ5d2SessVygl3PhQVl8JynMmoj4iND4nq5uDoEtktwcHZNTAsymwyXXLNJlprffESYCA10n4IQQQhtdYw/8NfT2QWe3u5iIQwGGl1pueXbDhwurCwsr5fXPjL9499+auN907sv3jVjpTY4KSoAIEQKcvMfW+Nm0K+//S591fueOm+MduP56bEBgW7O3u7OSKaiQfgZnTtM7DlRk5OjpeXF51pLWiK/cSJE/n5+SaTqXv37v369bs0707vSU9PX7JkydChQ2fPnk0Iqays/PHHH5977jmz2bxmzZrs7OwXXnhBKpVyHNfuVzuSSqXXcmCWPiYtLW306NHNzc0SiUQQhN27d2dlZX3//fe0qYsNZm+M8WXbS8vl8tLS0vfff3/kyJGzZ8/WarUbN27MyMh49NFHVSrVV199NWHChMmTJ6POKMEHwL5gjIOCgmx2VTV7DdzNZvPvv/+uVqvvvffe6urqzZs3p6SkDBgwID09ff/+/VFRURMmTNi6datWq50yZcq+ffvy8vImTpzo6OiYkZGRlpbWv3//xMREyzHBtra2qqqqefPmlZWVVVdXBwcH30gKRBCJiSeCYJAqXR5Y+IHRoK+rq41JHhjXe7ha1UoIaWtrGzzhbpPRoNHoMMYDb5up12k0Wt2oGQ+JgqjVqi87URKExH+OCmNsNAlGs+0O0NzcBFHkWOZYdsmBjHOens5mMy8SJIgiw2CdWl9Y0fD7+3PD/D1yy2olLLfy3QdHPvFFWl55cnQgDcoXPz65R7jfnDdXmngBIVTXrPb1dImNCUqNDSaEwLWWwM2HpnKPHz9+6NChyZMnBwQE/PLLLzKZbNq0aSqVav369YSQu+++u6amZteuXTNnzmxubt60aVPPnj0lEsnmzZtlMtmUKVPc3Nys4+BTp0499NBDUql08+bNtLsi+mfJNcMwJpOpurp62bJle/furamp8fPz27Nnj8lkUigU2dnZ3bt3nzdv3pYtW4xGY1tbW0NDA812t9en5nleFMVrvNjK559/3tzc7O7ubjabaQX8b7/9dtddd/Xs2ZP2ZGyvUV0FPRBBb1sOTajV6srKymXLlh08eLCurs7NzW3KlCkKhSIjI0Mmk3333Xfbtm2rqKgIDg62ZTEP/aLtpcK+3Q/mdChYth2HECIIwvWN9jp+XPYXuNMpPj8/39fXd+TIkVVVVVlZWQ8//PDWrVtra2sdHByefvrpH374oaGhoampaezYsUVFRWazec6cOfn5+RKJRCaTTZo0af369ZbAnRDi7u4eHh7+xx9/sCw7evToGxyhs4M03M+ZZRhB4M2mVkc54+vsgggixOzj6IwQIgSZzSbOUcYwCl7gRcEkcXZEBJnNRo7jsIvz5T424hiskP7j+8IY8QJxc7TRxbpuEc0qLW80I0dCEDLzgsFklnIcYZlgP7cwfw+EUHV9m5uzkhDi7+mq0Rnp3pQgiD3C/T76edfKNXtbTizV6I1FVU2Rgd7/9+nvDnLpzNE9BUFkoVQG3ETo/KlWq+vq6h544AG9Xn/o0KEhQ4aoVKqTJ0+Gh4fPmDEjMzMzOzub5/kePXpIpdKTJ0/ef//9RUVFhYWFffv2NZlMGRkZw4YNE0WRZVm6AevTp89ff/1lMBj69+9P52eMsdFotLwvy7JtbW1qtVomkymVypqaGh8fn2nTpp06daqhoSEwMHDHjh07d+4MDg6WyWQffvjhH3/8YTAYbL98MMaiKObm5rIs29LSQj8dwzA8z8+dO9fX19dsNts+mU3fMT8/X6/Xq1Qqugyrqqp8fHwEQdi8efNDDz1kMpmee+45Dw8Pf3//oKAgg8Fgs1749AA4y7J2EbHRcM2WV965EbBsOw4drclk+q/LlhAilUr/a1rB/gJ3Ou9069atoKDg4MGDiYmJ5eXlS5YswRj37dvXbDZ/8sknbW1tLMuGhYV5e3tXVVUlJiY6Ozv36tWroqIiLi7O2dnZ29vb8lJ02zBmzJiioqKsrKxDhw6NGDHiRsbm6ijtJpNiRJQOCgcOYYRURqQ36BmGoXuRLMs6OEo1aqMgii4uCkKQqk3Pcqyjo1TVpr/sVC4QopSyroorxuhwMLO9ODkoGI6jC1TCMSwjFQliOWZ/euFtzyxNjAxAGJvMvCgSgoizUs5gbBZFCccghO4d16eytuX5pX++//ikNW/eN6xnTHSw9/Gcspmje8LhZnCToTOns7NzaGjoH3/8MWrUqKamptOnT/M8P2TIEJlMtm7duoKCgjvuuMPFxcXNzc1gMERFRbm4uKSkpCCEAgMDVSpVY2MjQojGhRhjQRBSU1PDwsJyc3MPHDgwefJkBwcHum2zfl9HR0eFQoExNplMfn5+DMNIJBKaBXd2dp46dWppaanZbN65c+e8efPuueces9lsSTnfOLPZfNGQLotuwl9++eX169e7urryPE8nAaPR+P777/fq1at9jwNcZRg8z190EH/OnDkymczBwYEevvD390cISaXSlStXrl27dtiwYe7u7ufOnfPy8sIYy2Qym01f9LQEm5Uc3KDLLtsuC5ZtxxEEoaamJigo6Dp+0bdExp1qbGwcOnSoSqXasmVLt27dBg4cWFFRodfrCwsLn3vuua+++kqv19PV1NnZOTc318/Pj1ZVmkwmnudNJpMoivQEHXouVHp6+vTp0+VyeU5Ozg02lhFEYjDxMpls394DB/buFgRh4pRpPeJ76HVGjDHHSVpaWv/csHfYyDGOTk5rf/6Nk0jGTpjY2tK6ZfP+0WPH82b+0jcXCWExEuWX2ZnDUIPYTlgGE4L69gjt1SPkeHapt7uTKBIGIyPPm8zo/ccmBXi7Hs0qOZlbdiSz6P63Vu1LL/B0caisbw30dkUIrdt7etqw5KG9Yj5dvaehRbNwyYaj3z1X26x2c1IgBO09wU0IY6zVat3d3efMmfPjjz96eHjcddddCoVCo9EcPnx42rRp6enparXa0dFRr9e7u7uXlJQkJSUVFBS0tbUFBQWZzWZBEGhejU5iZrP5jz/+mDp16oABAxobGy0HRZl/XkhBoVD4+fk9/vjjPXv2HDx4cFpaWnJyMq080Wq1hw8fzsrKmjNnjkKhCAoKio6O7rwlhJ555pkdO3ZoNBq5XC6KIq3enDlzpi2v53oppVLp5OTk7+//+OOP9+nTZ/Dgwfv37y8uLs7IyLjjjjtKS0u3bNkSERHh5+dHD4bYcmw2vtjtjaBrpr2MFsGy7TA0cPfz85NIJDZo8GqvgbtcLl+3bp3BYLjjjjvq6uq+/vrroKCgMWPGMAzz448/BgQEcBynUCh4ng8NDc3Kyvriiy9Gjx4tkUgUCgXDME5OTtbrRHh4eEVFxUcffeTu7j558mSGYW7wWBKDMcdxK777avvmTUoHRUy3bj17J+u1BoKwu6vsi4//991XS7KKq/Jzz27asI7n+R7xCeWlpaeOHZk0daqqzcQwF0+U+MKpqDcyKnB1NETwcHH44v9m3PP6inPldQgjJBKZXPry/ePmThmIEBo/IM7EC4Mf+WTVD9t8uocUVjSMe3oJIWjSkIQfNh594Ys/BFF8/r5x0cHeLo4K/7EvMBLuzw8eEQk98RW+PnBTIYRIJJLc3NxffvllxIgRYWFh69atM5vN06dPj4yM/PnnnwMDA6OiojDGLMvKZLLw8PDPP/+8R48ePj4+DMPQOg2WZS2hIcdxvXv3XrFihU6nGzlypJOT05W2gr169RIEoXv37izLenl5MQzTp08fhULBcVz//v3Dw8O7deum1+tpjsa6yPvGmc1mURSvpdEkIWTgwIE///zzSy+9pFarCSHTpk378MMPGYYRBME2CZfLZi5FUTSZTFFRUbNmzUpISGAYJjY2NjIyMiwsbMCAAQaDQaPR9OvXD0FWCIBrY8t9jI5tRNXRBEGgM771vHzZOdr6TrolOHjwYGFhoVKp1Ol0o0aNCgwMNJlM13i+0dW1aPQaM+LN5kfuu7tn7z633X57bPcErVqDMHF2dvh66bLFb70WFh65df/RrZv+LC0ubGpsHDZqzM6/tsx5+NHo2Gi1SnPpGiASopCy3k7yGx+eNXrMwV4uf20ymRBC7fIdXQXt417d2LZiy7GaRpWUY0f37Ta6TzdCkEhEQSBSCVtZ3/LNH4cnD01MiQnam16w/chZB6Usr7R298kCXhAenTYoIcLf191p2/G86cOSUmKD6SsLgkgQYpgutwMmiqLBYFAqlZ09kGtCyx7sJZ7Q6XRyudxe8kbXzWw209DQuh3kv07FCCFBEH7//Xee5xFCEolk6tSpHMfRHo43OC8RQmbOnDl06NBHH320swJ3dGFzw/N8Xl6em5vbv/a4bHeXDdxHjhz59NNPT5gw4bKP78Qfl33NRfZVzgHLtuOYzebjx4+npqba5sqp9ppxp4vGcpoFnZTpnRzHXbrgLr2THtSQSCRms9m6jLIdFjpBDMNoNOoDe3dlnTn95Scfrl6/acDAAa1tGp4XlUrly2+8u/anFTxvDgoO2fTH73KFoqyk2MPLUy6XVVVUeXl7m0wme4lLbj4MxoQQf0+XF+eMsdxJo3kWMyyDCCGB3m5vPjIBIUQIGpYSPSzl/LH42iZVQUX9X4dzftxyTG80h/t7rt+XUVrb3Lt7qL+Xi+Xk1PPnymOagYevGtg9eoAY/fMiPpfGyoSQS++MjIykp6CxLEuPdlo6yVz9t0ELbCwnsFoeTwihBR5tbW16vb79PuX1oKeochwXFxeH/rlj04laW1tpHsRkMkkkEksvecvCtyzbzh0nAHaBXneC7mbYoserXWfcu6ZWjV7DY7WqbcPvv95935zn5j/u5ePzzgcfNje1YYb183ba8teu119csGnnPgdHpx+Xf+Xu7lFXWyOVybIyTxv1hrcWf+Lg6HjRydSQcUe2yrhThBBBFDHGhCCMEfvPjCkhhBdElmEYBovi+UdedH2l8tqmY9llZ85V5pTU1DS2uTkpU2KDkqKCUmODIwI9rR/Z6Zl4+8rEQMYd/CsaxP/2229hYWE9e/b814uw/if/KeNu0Vmh8GUzlytXruzbt290dHT7LpkbZ19zkX1lhWHZdhxae0YvZGYD9ppxv3HWLULbdz4lhHCspKaqsqqyPNjdOTIqpramRiHBbu6ura0qvYmYTCaWYRDCJqPx8aceq6lpef+NV/sPHhwZFVOQl5t1JmPIiJE6rdZeQpObEsaYu/L+DMZYwp3/K8Ngek4CIYj+D2GECArydgse6XHHyBSEUEVdS25p7d60cyv+Orbkt32ODvLoQO8hKVG9ugf7e7pCJh7cyqyTFO0VRNIfz4wZM9r3ZW9EVxiDxezZs+mNLjUqAOyX5WrENnDrBu4dmfzAgih4+/qvXfmjVq3ZvnXzex9/kZ6RdSYjc+LkafSgpNFoQAgRQnR64ZefVqT06uPh4ZWdmcmbzTK5HI6C2COMEb4QdBNEzGaB5RAhiGOZIB+3IB+30X26IYRqm9RHs4tP51es/OvY+yt3uDkpkmOCkqIDe8aGRAR6Wq+SnZ6JB8AGOi52pCeAQmx6KdqJEnIDALQXW1Yu3LqBe8fBGJlMJh8fn8+//v6pRx+YeuesGVNu/2r5d4f275k64y5BIEqlMigkFGOEMebNfEVZ6cQp01zd3H9b85Onl09icopRf/lu7sCOWApsrDPxGGNfD6cpQxKnDElECFXUt+SW1O1LL1j51/Glv+13VMqignwGJ0f27h4S4HVJJv58t35YNQC4JvZSBGh77XiqLgBAFMXy8vKwsDDb1PZAjXv7a9Xo24wig7FMJqNbDr1ex7Icy7L0+n8Mw7AsazabEUKIIE7C0cwQRdvPX/SaUOOObFvjfoOuUp9Hu9PQTLz1/XXN6qNZxafzK7OKqqoaWl2dlCnRgUnRQamxwZFBXtaPbPdMvH3VPkKNO+hc11fj3lnsrlbYjuYiWLYdx76WLXSVuRnQJKtOr8cIkfONBcwms5kWUgiCwAsCvtDV20Qj+POl0fTGxd86bQMObgIYIxZfkolH2MfdafKQxMlDEhFClfWtuaW1+9IKVm09vnTdfge5LCrIe3ByZJ8e0J0GAAAA6FqgVMa+sRi5O0gY3J45NoIQx0JcdlOxrolH/8zEB3q7Bnq7juodixCqb1EfyypJy69Yvf3kRz/tcnFUJMcEJkYFpnYLjg7yhpp4AAAAoHPZ8uRUKJVpfzqdTqlQIHsInqBUpoPcyGG+izLx1utRVX1rblntvrRzZ85Vtmr0jgpZZJDXkOSo85l45joz8fZ1CBVKZUDnglKZjmNfcxEs245jX8tWEISamhp/f3/bTPUQuLe/jthU0x6D7Q4C9w7SjpPOlWriG1o0tDvNmXNVVQ2tLo6K5As18dHB3taPFESRkKtl4u1rQofAHXQuCNw7jn3NRbBsO47dLVtb9nGHwL392dGmGgL3DtIRk87VMvENrXmldfvSCzIKKls1BkeFJDLQe1BSZJ+40AAvV+7fauLta0KHwB10LgjcO459zUWwbDuO3S1bvV7v4OBgm7eDwL392dGmGgL3DmKDSedKmfjGVs3RrOL0/MrMwqqqhlYnpTwpOiA5Oig1NiQm5PKZeESIHU3oELiDzgWBe8eB4LLjwLLtOJBxt3t2tKmGwL2D2HLSuUomvrqhLa+sbl9awelzlW1qnVIujQz0GpQc1TcuJMDLzRLxC4Ko1+uVSqVd9ImHwB10LgjcOw4Elx0Hlm3H4Xm+oKAgMjLSNvEJdJUBwL5doTsNYVnW38vF38tleM9ohFBjq+ZYdkl6fsVvu9M+XbObZuKTooN6xgbHhPg4Oiotp1H8a008AAAAAChCSHNzM82EQh93AMB/Y90nXrTKxHu6Ok4YGD9hYDxCqLqxLb+sbl/auV92nvp6/UGFTBLq7z48NbZvfKh1Jp4QRAiBPvEAAADAVUAfdwDAjbpSn3iWYfw9Xfw9XYalRiOEmlTao5nFx3OKf997+tM1exyVsqTowKTowJ6xwbGhvtbROmTiAQAAgEvxPG+z94Ia9/ZnR1WtUOPeQbpyfd7VauIb2wrK6/alnUvPL29V65VyaXiA56CkyH7xYQFerhKO/fsVOi8TDzXuoHNBjXvHgTrsjgPLtuMIgtDY2J2SA8oAAQAASURBVOjl5QV93O2VHW2qIXDvIHY06RCCeEHQ6/VOjg7W0XCzSns0qyQ9vyKzsKq8ttlRKU+KCkyODkyNDe4W5mv9CjbOxEPgDjoXBO4dB4LLjgPLtuNAVxm7Z0ebagjcO4jdTToGg0GhVBJy+Ux8TWNbQXn9vvSC9LyKZrVOKZOGB3gMSorsHx8e4G2ViUeIiJZMfEel4iFwB50LAveOA8Flx4Fl23Fs3McdatwBAAghhGmofWl3Gobx83Tx83QZkhKFEGpR6Y5mF6flVWzYf+aLX/Y6KGWJkYHJMYEpsSE9wnwxAzXxAAAAbi0cZ7twGjLu7c+OcmyQce8gdpctuEomhiBklYn/Rx69tklVUF6/Ny0/Pb+iWaVTyiRhAZ6DkiL7x4UH+LhKOyYTDxl30Lkg495xICvccWDZdhye53NycmJjY2UyGbSDBAB0sitk4hHLYF8PZ18P58HJkQihFrXuWHZJel7Fn/szv/xln1IhTYyiV2wN7hHuB5l4AAAANyVCiFqtFkXRNm8HgTsA4D/4u088QqJVJt7NSTmuX49x/XqgC5n4fekF6/ae/vbPI3IZF+bvOSgpsn98WKC3q1Ty97QjdnxNPAAAANChoI87AKCru1wmnhBCLsrEt2r0x7JK0vMrNh3MXPLrPoVcmhQdkBwdlBITHBfhx1yaicfY+k4AAACgi6OFx7YBNe7tz46qWqHGvYPYV31e+9Y+XqUmvq5ZVVDRsD/9XFpuWZNKK5dIQv09BiVG9k8IC/Jxu8ZMPNS4g84FNe4dB+qwOw4s244jCEJra6ubm5ttpnrIuAMA2tPFmXiEiEhEQlgG+7g7+7g7D0qMQAi1afXHskrS8iu2HMle+vt+hVyaGOmfHBOUEhscH+EPmXgAAAB2AWPs4OBgswQNZNzbnx3l2CDj3kHsK1tgm0zMVTPx6nMV9fvTz508W9ak0iqkklB/j4GJEQMSwgN93GT/zMSbebOE4zDGdpF0t6PZAFwjyLh3HMgKdxxYth0H+rgDAG5CV8jEiyzD+Lg7+bg7DUyMQAiptIZj2SWn8sq3Hsn537oDcpkkITIgOSYoJSY4IdKfYbDswp4bZOIBAAB0BbZMJEHGvf3ZUY4NMu4dxO6yBZ2YiblKJr6+WX2uon7f6XOnzpY1telkUi7M36Nvj5DByVFBPu4y6cU18Qhd/Aqdzo5mA3CNIOPecSAr3HFg2XYcnuczMzN79OgBfdztWFeKHADo0q6Sifd2d/J2dxpwIRN/PLs0La9sx/G8b/48IpdJEiL8U2KCU2KDEiIDoCYeAABApyCE6HQ66ONuxwhBZp4wTPsdysCItY+CXgBuFEYIM5hB7EV94p0d5KP6xI7qE4sQqm9WF1Y27Es/t/FA5vebjsilkhA/9/4J4QMTI4N83OT2kIkHAID/hBBCCLEcvqP/iRCi99DbMMt1FlseVoXAvT0RgjBGtW3GvOomlkbuhIiiwDDs30l4QgRBwBjRO0VBQAgxLIsIEUWRuVzVCoNRn2gvVwcpQQh+lOAWcaVMvCgINBPfPyEcIaTWGY/nlJzKLd95PO+bPw5LpWxiREBybFByTHBSFGTiAQA3A1qAgTEWRZHGiBedoA8he+diGMZmXwEE7u2LIIQNJrGuVc8xjEgIwzAKBye9Sm19LoGjs6soitrWNoSQ0tEZEaJrUzEsK1c66FTqS797BmMzL154eRt+GgC6DEsm3iSKgijSiB5j5KSUjewVO7JXLEKooUV9rrLxQPq5TYeyfth0VCblgn3dByZEDEyKCPJxk0v/LpeETDwAwI5gjDUaTXFxcUJCAkJIEISzZ89qNBpXV9fQ0FCFQoEQ0ul09lLCfpNhWTYmJoae92KDDQoE7u0PY8SxmGMYhLFRrzuwf0vPgaMlUindURYEYdsvy2VK5cBRkzFmju3ewLKS3oPHaNStJ/bsSR00WuDNF33xDNTJAHABPv+LOP+TsGTiGYbxcnPycnPqHx+GENLojMdzSk/lle06mffNn4elHJdwoU/8JZl4QgiBTDwAoGsihGi12g8++ECtVg8ZMmTy5MkGg2Hbtm11dXX79u1buXJlt27dHnroofHjx0+dOpXneY6D0M7W5HI5ZNztGyGIF3hnN8+Nq7/auX5Fcr8RHMKCICgcnL7/+JU9G9cghERB6JbU7+juzYSIIZHd6qvLC7LT+g6faDYZGeYfBTPQ9weAK7Guib9Q84kwRo5K2YheMSN6xSCEGlo1hZUN+9PPbTmc9ePmYzIpG+Lr3j8hYmBSRPD5TPz5CRcy8QDc9OyrHJwWyRQXFycmJk6bNm3RokWTJk1SKBQLFiyoq6vr1q1bbGzs0aNHdTqd2Wzu7MH+ZzbowWIbtuzQCIF7hyAikSnkdZWlu//82cnFHWOMCEEYiaJYkJX28herS3KzTx3a6RMQEhYdp1W31deUpx/ePXrqbIztZjYBoEuhpTP4kpp4hmG8XB29XB37xYUhhLR64/Hs0lN55XtO5X278bCU5XpE+KXGBqfEBCVFB1on3UWRiJCJB+CmY18bWRra1tbWRkVFCYIQExOjUqmcnZ3NZvOmTZtiY2MZhunXr19lZaXBYOjswf5n9vVdXIUgCDbbCYHAvUMQRGRy5dZfv49J6K1VtZqMBplcgQjGCI+ccs8Hz92PMX7xk1WcRFpaeFYuV9ZXlTu7e7ASSUNtlYu7J2++uFoGAPCfXCkT76CQDe8VM7xXDEKokWbiTxduOZz94+ZjUpqJjw8fmBQR7OOukEmY68rEX3g3hOGUFAC6HqPRyPO8za5z2S4YhqEtZcxmM8uyGGOVSlVRUfHggw+azWaJRGIwGOwubOB5Xq/XOzk5dfZAbpQoivn5+XFxcXK5HPq42yuZXFGYk95YW3HPE68tefNJhdJRFEUiCqIoVpWcC4+J02pU2acOzXjw2e5JfZ1c3VsaapWOzn+s+NJkNMx5apFC6SiKQmd/CABuBlfIxBOGwZ6ujp6ujn1pJt5gOpFTevJs2d60gu82HpFwbFyEf0pscEpMYHJU0LVn4gVRZK3+IPyzsy8hhBdElmGsn8sLouXYPccyIiGCILIsw9jbZhiALk4QBJZl165dm5aW9sUXX9hFOTidvPz8/Pbt2xcSEpKXl+fo6CgIQkNDgyAIoijS9uH0cor2gn4Rp06d+vzzz3/66Sd7uQrklRBCjEajzapluvoq20Eu3SWyLPEb31USRVEqlZ3Yv+3wro1FeVmNdVXrfvh89lOvMxg3NdRkntj/9vJNFSX533/0ysR7Hpsw65GWhtpfvvmwe3LfgJCIypJzpQXZCb0HG/Q6u9t7BqDru5CJx+iiTLxcOiw1elhqNLqQiT+QUbT1SM7KLcckHBvs49Y/IXxQUmSw7yWZeHQhtY4xIYRlGKOJr21SYQYHers6KeWC1WyOMZZwLPpngyiO/UcDYAZj5pLH3DrIPxdXJ44E2CnrEnba7Jx2TiSEiKLIsmxjY2NFRUVnD/Na0ZFHR0fv3r37iSeeWLRo0bJly+bNm+fu7n7HHXewLMvzPELI1dXV8vjOHO5/odFoioqK0CUBmKVFfTsGZjeTmy1wp79MjDHDMHQ31HJtAsv99Gd8UezejqsFxthkMsYk9Bp/58OtzfWq1sbQmB7nstKqygsHj5uuUDoue/sZdWuzh7cfx3JGnXbfX79GxaU4uXmUnsvhebNUJrflWQ4A3LLwNWTidTQTn1u2//S57zcd5TgmPvx8d5rkf9bE0zT5lsPZH/60Mz2vgmOZQUlRz84aMjgllm6FGIyb1boVm49NHBgfGeQlioRhsJnnV249UVnXKmGZiCDvO0emFFc1rtubcffYXv6eLvZ75hadchFCLMvS27TPMbngSjk2O/28oOu4aMtu+U+MsUQiQQixLEtv2As68ieffJImqh977LHNmzenpaWxLNvU1DRs2DCE0JQpU+iD7Sh7zTCMVCpFl/zqLR3r7Wg2kMlk0FXmOmGMLWstDdnb2tpaWlpCQ0Mt99PzPHx9fS0RPEIoLS1t//790dHRo0aNusEvAGNsNhoS+wwdOHpKXXXp1+8tHHH7rK2/fpd54sCI22fNfur1r99bKFcoZj32vsmoRwg11VX3Gz7R0cnl8Lb1bh7eYTHxZpORwRiCdwBs5kqZeKVcOjQ1emhqNEKoqU1bWNlw8HTh9uO5K7cel3JskK97/7jwQUkRQT7uDgrpxoOZs1790Wg2OyrkCJFNhzKPny3Z+OGjvXuEEkIEUZy9aMWug1m/7U7f8OEjXq6OBCGzWVj514n0nDJNi2rooITbB8Xf/txXZRX1mw9lbfjwEVdHpZ3G7papmI6f3i4oKIiKirJcYlCtVmOMHR0drZMp1dXVmzdvxhhPmjTJ29vbTj8+6Cw8z7/zzjsymey5557jOO7YsWNvvfXWsGHDhg0b9sEHH7S2tn766adyudxSZHIjl6mne6S2udC9JZ1nMplefvnlTz75hL6vXC5ftGjRggULBEG4+jWAbvzztiMalIuiSHdFNm3atHHjxjfeeMPf399kMr377rsIoZdffnn37t0rVqxYuHBhXFxcV54KWJaNioqyWR93fDMld0VRrKqqysjIiI2NjYqKys3NbWlpSUhIaGlp4TguLS0tJCQkPj7++PHjf/7554IFC+ihJYxxY2Pj+vXr586du2/fPkLIsGHDLBcn+0/oipVT2nSiqIlBSBAEzDBSqcxsMkqkMoZlTQaDRCZjWQlChDebed6MEOI4ThAEfIEoCkT8x5fCYDw2NcDTWd7ux85pVZy97KCbTCaEEN1B7+IIITzP20tSRxRFg8FgL1fuMJvNHMfZcga/bFG7zmA6kVN2Kq8s81xlYVUjg3FyTNDuE/nnKuvdnJS8IBCCZBKurkk1bXjyL+8+xDI4v7x+2gvLD339zIj5Xzx398iZo3vygmipk5n9xorHpw+pbVJ9s+Hwlk/mxd/9zstzxt41OtX6MXakpaXlzJkzDMMMHjy4sbExIyMjJSVFp9PJ5fK8vDyDwTB8+PBvv/2WYZiHHnqIzpx01v3222+nT5+OMf7jjz/mzJmDul4Onud5URTtYiKi7KKSmyKEGAwGejmh63guxjgjI0OlUqnV6pCQkLi4uIMHDzo4OKSkpPA8jzH+9ttv77///m+++ebIkSOrV69u9/HbwM6dO0ePHu3i4kKnQdpJ5tChQ4mJiZ09tP/sxIkTCxYs+P3330+dOuXm5tbY2DhhwoTc3NyioiKz2ezj41NfX5+UlCQIQkRERGcP9mpojbtcLrfN29nHj/na/f7777179z5y5Ii7u/vevXtTUlJqamrq6upycnKSkpL2798fGhrq6enp4+NjvYjlcrlcLs/Ozg4MDPT390cXsvXXh2Oxg0zCMedT5gQhOSdDCBEkSBVSQgQk0nAZyTkJQogggrnzoTNBCKOLw2h6jppAo/nr2s+C09wAuG7MFTPxUUNToxBCDS3qumb1z9tP5pbVyqWSVo2eZbBUwvGCoFBIC8rraxrbAr1dS6sbg33cXJ2U3UJ9m9q09MUFQWQYZl96gUZn6tMjdNPBrIYWdWFFg1ajb9HokB2WudP4+8CBA0ajUSaTZWVlNTY21tTUmM3msrKy6upqmUxmNBrPnDkTGhqq0+ksT6QBuqenZ1ZWlr+///jx4y0he5c68Y4G7vaS76BJhK6283MloijyPH99X7coihzHlZSUDB482GQynTlzpnv37lVVVStXrrz33ntnzpx5/PhxPz8/qVTKMMyJEycWLlxoMBhuZFtvKZq/7lf4T+gHPHToEI3XLaVoBoPh6aefTklJMZvNV/k4hBBBELrILhwhRCqV5uXl0a/Mzc2tb9++f/75p16vDwgIeO2111xdXefMmVNRUbFv37758+fT3PyNfFkd6rrXW1o0+F9/nl3iK2wvPM+npKQMGDDAw8Ojpqame/fuffv2ra2trauri4yM7NOnT3Nzs9ls9vf3DwkJUSgUdANDCHF0dJw5c+auXbtyc3OHDh2akpJyfRl3hDFCyMdN0c9BzmBMyPlVjWVZ6wMbGCFe4BmGYRiG53mEMMexhBBBEDmWvWxkbhJJner6W7R6Osikki66xgNgL2i5rCgSQSQMgyy7w15uTgzDeLo6siyDCDm/A04QQQgRunUnCCEzL9CuMgzD0HsEQWQZjDH680DmkJQoQsiYvt2W/X4gaurrPs4Ktqtupa6OzpyBgYEhISFKpTI7O1uhUAwfPtzHx+fcuXOenp5JSUlNTU1qtTooKEiv16MLuVK69Zo8efLp06e3b9/u7e09adIkGmd0qSvLmM1m2pivswdyTWjg3tmjuFY0ALq+r9sS2PE8bzKZWJZlGGbs2LGTJ09et25dUVGRWq2mnQfpngwt0rjBXRp64tyNvMK1o29EfxEX1fHTO//143Sd9Zae6MJxnCiKdBWl/2ZZdv/+/a+++qpMJvvzzz+DgoJmzJixc+dOHx8fiUTSpXbgrYmiqNFormN1sq4kvHY3VeCOMab5G3p5AolEQn//hBCFQkFzZQzDGI1G+vVbzlgtKytrbGwcN27coEGD9u7dm5SUdH0rt+UbEwkhhEgkUg93iUZHdDqt9QuKouji4mQ08nqDwdXViRCkatOwLOvs4qhSaS//xd9YQdPNUw4FgM2db2+AECKIYbAlAd+s0uWUVG8/ejajoLJFrfNwdgz0cq1tUjsrFTQ1zzGMwWSOCfEJ8HZFCHm5ORpMZo5lGlvUCpkEISSTcgghg4nPLqq+e3QvjLGZF759+W6lQjbjpW/pTGB3P166KaIZQYPBQBtm09iRptkEQTCZTBKJRKfT0VNXLWeyGgyGkydPDhkyJDk5ecOGDWq12t3dnRBis2PQ14JGG1Aq0xHoynMjX3ePHj22b9+u0WgmTJjQ0NBw5swZmhRXKBQGg2HIkCEIIZ7n+/bt+/HHH7ffwG1nz549I0aMkMvldF+X53me5z/55JP4+PjOHtp/lpGR8cQTT3Tr1m3btm3ffvttRESE0WjEGJeWlvI8n5iYaDKZjh075ubm5uDg0EV2OS5LEISKigo3Nzda5t7R7OPHfI0kEklxcfHPP//MsuyECRMqKytpQp0e2cQYm81mQRAcHR3PnTvX0tLi5uZGn+jt7X348OG8vDyz2dy/f3/akeYGj6DJ5fKy0pLPflk9dMSonn366bTnY3dRFBVK5frffouK6dYjrvu6tb9wEsltt09qbWnduW3L2PG3m+HqSwB0AYQgkYiE0HaNGKPzu+ZpeeUncsqOZhcXlNc7KmQJUQF3j+09MDEiyMftl11p97z+o8ZglLAMQlijN3q4ODx790iWwQihmBDf8tqWR95alVNa83rUeITQmp2nEiMDvN2c2rSGqBBvhFB1Y9v4//vf3SOSC8rqBiREIITs7rKtNPbSaDS//fabq6tr//7929raaK6EZjppmM7zvEwmO3ToUFJSkiXhpFQqTSbT6tWrBUHw9/enUXtXmw8tverswi01Wto28ejRo05OTsHBwSdOnAgKClq5cuWUKVP8/f1ra2sdHR0RQgzD6HQ6s9l8g7s0Nj6XiS6ZQYMGvfjii++9954lRFm8eHF8fDw9B+zqJ6d2nXOZ6OGO+vp6nuednZ0jIiK2bt06e/bssrKymJiYffv26XS6xx577PTp0+vXr3/yySct/QA7e+CXJ4qiyWSi2QcbjPOmOjnVbDYfOnTI1dU1OjrawcFBpVI5OTnxPG80GhFCjo6OKpVKqVRyHFdeXq7T6Wi9F8/zYWFhUqk0MzPT09MzODj4BofRotZreaTX6aaNH3WuIM/Xz//Hteu7de+h1+sRIUpHh7ycs6MH91n16x/BIcHvvvG6IAqvv7O4vKR0z85tby7+UNWmbveaOW8nuexypTJwcmoHgZNTO06Hnpx6oXswQghZn4pa1dB6PKds5/GzhZWNRhPv7+k8rFfMoMSIyEAvqeT8hp+2d1y3N2Pxyu3NbTqCUIifx8tzRozo3UOkh/sw/vNA5mPvrX75odsemzYYITTz1R9mjEgekBDx/NINP7xyD0IIY/zxz7s/XLn9qxfvnjw0sStvq67E+hzB8PDwwMBArVYrkUikUqlGo0EIyeVyy/mdNLVGn8gwTFRUFMa4oKDAaDTGxcV1zc9uNptFUbRNau3GwVxkjUbqn3/++eHDh3/99Vf7CtzRhR8XIWTXrl3bt2+XSqXjx48fMGDAtUwUXWqep4H7nj17Xn/99b179172WzCZTHaxuUcImc3mEydOpKSk0OIOuHLqfyMIQnJyMkKIEOLs7IwQkkgklt8VvUcUxeDg4L179+bk5Dg4OGi1WgcHh9DQ0JSUFNQ+e0tEIpEWVVaYzeaKZt2E4QPTTx7v2StBqxUZhsGILF/2hdlkdHP3KDxXmJCc0tLUVF5aumPrlvvnzkNdr4UCADc9QoggEozR+YueYoQQUuuMx7JLTp0tO5pTUtukCvBySY0JnjoseUBCuFL+9+aEF0SMEe05QwiZNixp2rCkgvJ6jmXCAzxF3swLAndh33jS4IRJgxMsz13z1v30xo+v3mu589m7Rzx79wiEECF2PBsYjcbIyEh/f39RFC3Xlqf5TnShThchFBkZ+eOPP9J9cplMFh4ezrJsdHR0p4wZ3BwsCSl6pJ1WTtMD6fQHRYvgO3uY14OOH2M8atSoUaNG0TvtcfeeovsSlr6QEomEZk5o20rL/TZuI3YdMMZKpdJmxTw3VeDOcVyfPn0s3UwtazO5cB01eg895kIbu1qe254X6MLYaDRGd+uWmJraI9Qvpnv326fMaG01YIydnB13/LW1oaF+yPCRdTU1IeGhv61epXRwLCsu9vL2kkgkleUV3j6+JpOpi6+mANi7v5PrGDEYcyxGCBnNfGl10+5T+Ycyiqob21gWxwT73D+hX0pMUIiv+z+ee6G9jHWvRowxzbtHB3vTh+mMJqVVbzuREIwQudAqynqOsvzkL3qM3aEfJD4+ntavWx/jtkzFlgcTQu67776LXoHWS3TlklbQlV10LRdL5o5hGBrTu7q6+vr6dtbwbtxFBUX2+0tRKBSBgYEIIdqrA12YHOiOFs/zlvu7OIZhIiMjbdbH/aYK3DHG9Jxxy39e5YYgCJZV/8ZPLb8Iw7Atzc11NdWDh40oyM8rPJeXlJJi0PMmo+HnFd8ueveDTxe/izFOTo7rP3iIu4dXbXWVs4vrZx++a9Dr3/rgEydHJ6FrXCUBgJuMeOHyqOcvVYIRQqiiruVIZvHJ3LK0vHKDiY8J9u4XHzYwMTI5JtD6ubwgMJimBa44YdCUvaU25qLgm/n7PRG63NR06WPslPUR+ct+TMs91j1PLB0zIHMBOgKN6efMmXPvvfciqyM/9uUm+IHQL6Jv375r1661l2Ldq7Plp7DLtfYqrv2YUcctZSIShUKxc9th3mz+bc1Psx+cu23zxuGD+zo7SvftO7Zl44aM02mN9fVF5/LjEpOeevKx0qqmD956rf/goVHRMQV5udlnMoaMGKXTXqG9DADgv6AtYciFsnVLT5hWjT63pHb7sbPpBRWtKp2jUt6zW/Cbcyd0C/X1dHW0PF0khGblMcLcNU8adposb0fXPhXbafAE7Bescl0Ey7I3R9SObHvc42ZbfbtIsGsy82Hhkfm5uY8+8fS2zRsXf7rkeHpmbnZOr34D5j/9nE6n3bxhfVhEpEKuUBuFX35akdqnn4eHZ9aZDLPJLJcrbqYzhgHoFP/oCWOVnzpzrvJ4TtnRrOL88jq5lEuIDLxjRMqgpKgQXzfLc62z8gzGdp/97gxdZCoGAAAb0Gg09NpeNnivmy1w7woYBpsMhu5x8c+/sujt11+eftesO6ZOWv79igP7d8+YNfOdjxY7YfQgIVPvmOnu5a7XG6qrKidPv8PV1e33X1Z7+/omJKcYDQbY7AHwX13UE4bF5+fQ6sa2U7nlO47nFpTXGUxmHzfnoanR/zdrRGSgF+2njhAixFKB/felUgEAAICrEwShsLAwKSlJLpdDO0i71KrRtxpEBmOFUskwiBCk1+lYluM4Tq/X0dp6uUIh8Dxd9BKJROD58xdgo8X3oti+Na4+ztAO0qagBVvHubQdpOXSpKzVeaI6g+lYdsmp3LKj2SVV9W2+7s6p3YJ69wgbmBjhpPy7kR8viBghWrbeEaPV6XRyudwuzq8C1wjaQXYc+5qLYNl2HPtatmaz+eTJk8nJydAO0l5hhCQsZjA26bUYY0IQy2BEBN4kSDkWcSxCiIgCx55vE01E4fxNIiKCWIww286beUjfg5vMRT1hWBYjhMy8UFrTtPdUwYGMwsr6FgYzkUFes0b37tktOMzf4x/PvVxPGAAAAOA6iDZsKAKBe/uTMMTPBXJsALQ/USS8IDIMYdm/G65XN6qOZBadPFuWlleu1Rujgr17dgt+6q5hvbqFWD/3fMP1801hOmX4AAAAbjYYYxcXF5sVL0DgDgDous73hEEIEYQxZhiskMsQQiqtIa+0dsfx3FO55U0qrYNClhoT9MoDY7uH+Xm7/d0T9p89YWBfGgAAQDtjGCY8PJzW8UIfdwDArYggJIpWPWHQ+eR6dlH1kayik2fLz5bUSlgmPipwytDEQUmR4QGeludCTxgAAAC2ZMvDuBC4AwC6BEIQoR1hCGIYzF4oNqttUqXnV+w4fja3tE5vMHm6OAxOiXp8+pCoIG8HhfQfzyXQEwYAAICtQR93AMCtgvaEIQhxLHM+PY6R0cwfyy49ebb0eE5pWU2zl5tjamzw/BlDBidFujgqLM8VBBFd6AmDESTXAQAA2BohpLW11dvbG/q4AwBuThc3XGcxQkgQxLLa5v2nz+1NL6iobUEEhQd4Th2a1LtHSLi/l+U4pMlkYlmOhuoslK0DAADoVKIoFhcXu7i4QDtIAMBNRSREFAmDMcP8XbZe16w+kll0Kq/8VE5Zq1YfGeiVEhs8b+rgPt1DrLMXvCBgjBnM0FNUoS8MAACALgJq3AEAN4N/9oRBDMYMixFCap2xoLxu14m84zmljW1ahVSSFBWwcPboHuF+vh7Olqf/syeMfVwmDAAAwK2G53mbXc8UAncAQDsjCBGRiISwltw4Rgih3NLaY9klx3PKsouqGIzjIvzHD4gbnBwVFeRlea51Vh56wgAAAOjiMMYeHh42u84rBO4AgHZA8+o0uc4wGF9o7VLfos4oqNx27GxuSa1Gb/R0cRiQGDF38oDoIG9Hpczy3PMdZTDCGHMsROsAAADsA8MwYWFhNHCHPu4AgC6NECIScr7hOjqfXOcF8Xh2yYnc8uPZxUVVjZ7OjsmxgY9MGTg4KdLdxcHyXEEUCUEs9IQBAABgz0RRtNl7QeAOAPhvLu4JgzFCSCSkvLb54OmiPWn5ZbVNgkhCfd1v6x/XLz4sPMCLZfDfzyUIIYQxYm3Y+BYAAADoIBxnu3AaAncAwDWh1ec04LaUrTe2aY9mFp/KLT+eU9Ks0oUFeKbGBj94e/++PcI4zronjIgxoj1hoB8MAACAmwYhpKGhwc/Pj7VJEwUI3AEAl3elnjBag6mwon7nybxjWaUNLWqphEuI9H/6ruEJUQH+ni5/P50m1zHCiBbSAAAAADcbURRLS0s9PDygjzsAoHOI53vCYOueMOfK649ml5zIKT1TWEUI6RHuN7pP7KDEyG5hvpYnEkIES6d2SK4DAAC4Bdgm105B4A4AQIT8XbnOMJi50BOmoVWTVVi17VhudlG1Wqd3d1L2S4iYPb5vTLC3i6PC8vS/G65DTxgAAAC3GLPZDH3cAQAdjvaEEQSRsUqui4ScyCk9cbb0eHZpYUWDi5MyOTrwgYn9BidHers5WZ5r3RMGGq4DAAC4NWGMfX19oY87AKBDXNoThmUYndlUXtdy+EzR7lP5JVWNvCAG+7qN6BX72oO3hQd6SS5UqENPGAAAAMAawzAhISHQxx0A0J4u2xOmRa0/kll0Mrf8WFZRs0oX7OueGhtyz5he/eLDZdK/J4cLPWGgbB0AAAC4mNlslslktnkvCNwBuGmRy/WE0RtNRVWNu07kH8ksrmtWSyVMbKjvI5MG9IoLC/R2+8dzLyTXoScMAAAAcCVSqdRm7wWBOwA3m8v2hCmubDyaXXLibOnpggpBFGNDfIf1jB6YGBEf4Y8QQkhAiCUECaIIPWEAAACAa0QIqa6uDgwMtM1lmCBw7xCEIFudXnxD6CDtYqjofFW2fYyWrgA2HOo/ytYtPWEaWzU5xbXbj589c66yTaN3dVL27hG6+LEpMaE+7s5KyzN5QTAYDA5KpaVyvSsvZHv5cVGkgwcMO1cAANC5RFEsLy/39vbmOA76uNsljBFrJx3xOM4+xklJaG22PQwZYyxhbZmx/juzjhA6nV9xIqf0eE5Jfnm9s1KeEB3wwIS+g5OjvKx6wiCEECL0RBoJx4gcQ0vfuz4Ji7GdDBUhxDHYXmYDAAAA10cqldpskw+Be3siCGGEVHqhvLmNoT03CDq/+4XP30Y0yLJ8wX9XEmOEESEEI4zxhRRdB68GoigihBh7aA+CEeZ5M0KI4yQEdfWMKyFEFMUOuSLD+Q9PEEIsw8ikEo5lNTpDs0qdVVh5JKOwsLJOrTN7uDr36hE2ZWS/8ABPXw9nURS1elNLtcqyBtL/WUZrNptlUr7rL1iEkCAIDMPYRR0PRthoMkokpg4aLSEk0MNBKeNIh08VwC4RK3QlvFKrabv4QQHQZZlMJujjbp8IQRg3qkzHCpskDCMSgjGWSGUmowEhxDAMJ5FijEVBMJtNGGNCCMtxHCdBCPFmkyAIMrnCbDKKgsByHMYMz5thPgXoQsN1jBDLshKOpftaLW2awvKa4sqaovKaNo3e3cUxNMC7T1JCTFiAm7MDwtggiOlFzab8BoTON1y/yuvDmtYROm7BYoxMAhmXHKCUcXTm6Yh3AXaNnqpifdoc/MwBaHcY48DAQJudnwqBe/vDGElYzGIk5aQ8b26oLvX2C0IIGY36utoKQohc6eDq7iWKAsNwGlWrRtWCEHZx93JwdK4qyffw8ZcrHTSqVoE3O7t6CIIAE+0t6MKeOyGEXo6Uk0slBCGVRltR05RbXJlfUtmq1rIM4+vlNrJfYmiAj6ebs4NcZuIFk8ms1Rvp8zHGcsm/J/7pu3Tcx7llddyCpcfl4EsDl0X3GFtbW9966y1nZ+f/+7//c3BwYBimpKTkww8/DAsLe/LJJ1Uq1RtvvBEcHPzoo486OTkhCOsBuC4Mw1jOTLXBjwjbLLd/K6Bz5dmyppOFTZxEwpuMyz948fDODePveviB/3v75MHt7z87GyHUI7X/O8s3tzTWKh2df/jk1W2//4AQeuqtr7x9A35a9nZcysD7nl7067cfyRWOY2bcp25tZpgOqLgAXRVNrjMYcxzLsSzDMKIoVtU3F5VXF1fUllbVm3nez8s9LNAnKtQ/1N9HJpVghHhBMPOCIIrnr2P6398UttkdoUMz7maBjE7y93dXwtdnS2azWRRFm/Vsvj6iKDIMs2bNmoCAgPr6elEU77jjDkJIWlpaQEDA7t27WZZVKBQ+Pj4qlUqr1U6dOpU+pdOHbTAYlEpl5w7jGhFCeJ632fUybxAs244jiqJOp3N0dLTN20HGvUMIouji6Lx93YqS/Kx3v/9rzf/eVbe1VJYU9B85adyM+13cvbTqVolUajTom+pr7nn85R4pA4IiYv5Y8cXAUVPO5aSXFORUlxXdOfd5nVqFsR0UoIMbZNl/xhjLpBKpRGLm+ZY2TWV9U1ZBaVl1vV5vlMulYQG+00b3D/DxcHdxknCc0Ww2m3m94e/kOlzNFABAd+R4nuc4rlevXsXFxYWFhfT+nj17Njc3NzQ0DB06NC8vr1+/fufOndu9e3dnDxkA+2bLfQwI3DsERpiIYm1FSUT3xJryooef/8DTx/9cdnrumePFeWdmP7XINyDUZDIY9JrC3Ixz2WnpR3Yv+OAHiUzR0lgvlSnO5aT7BoV7BwSrW5sgj3YTEwkhhLAMI5VwLMsyGOuNpnNl1UXltUWVNdV1zVIpF+Lv1S8xNiYswNfTnWUxIcjM8wajSWcwXriUKawiAIC/0TlBFEWe52kQTw/c0Zx6QUHBwYMH+/fvHx0d/cQTTzg7OwcGBiI76VIAQBdECKmoqAgNDYU+7nYMY8zzZkLEkwe2nzq4w8s36INVOz19/Kc/8ExDbeUfP36e0n8EIYgIYmS3xBG3373268W7N64eNHrKV+89N/z2WSV5mTEJvT5YcF//kbenDhxt1GsxTKld3oWrlJ7v73FRPG31x/PJdYZhlFIJy7E6vbGhRVVUUZtdUFrT0MKLoquTQ2x4wG2Denp7uLg6ORJEjCaz0WSyvBrGmIV4HQDwTzRMz83NzcrKmjFjhtFo1Ol0Go1Gq9UyDMMwzPr166dMmfLZZ5/99ddfDzzwwOOPP3769GkPDw+1Wr1u3bp77rnHNpEHADcTURSrq6v9/f2hj3v7u9AL7zLLlBBC28y1U9aBsCwnEjF14Kjn3vt24ZwxOWmHuyX3Sx04qrGuKj/zlEbV6ubh3VhbOWjstDHT7q0sPVdbUeIbFPbG/9afPrLH0cW9przYNzD08K6NiX2HIozgNLQujhAklUgsrdB5QeR53rKmiYSwDMOxrCCKHMsxDMNg3KLWZJ8rrahryiuuaGnVuDg7RAb79U6IDg3wcXN2xBiJIjGbebVWhy50h+i0jwdAu7rKVIwQEgQBIdQh3VRvChctH5pK5zhOEASe51mWTUtLW758+R133NGtW7e33npLKpXee++9R48elUqlERERL774IkLonnvuycjI2LRpk1wuT05OLi4u/uijj+68806E0EXbwa5Q+w5AFyeRSKCP+42y3umx3LY0sr10+WKMaaahXfaWaJ9HL7+g7JOHzmWna1WtHl5+S796ujgvUyZXcJzEycW1trJE4E3/e/v/HJxcTh3c3nPwGISQyajPzTgWk9i7rCDHNzC0sqSAN5sYhrWna0XeirBEwpwrqz6ZXdDYog4L9O6bEOPt4ao3mRmECEFymVRnMDS16hwU8haVJreoIq+ksk2jZTDDMMzg1B6RIX6+nm4iQVq9wUkpt5StI4RhkwnsmnWMbrl9lakYQch+VYQQunwsS88SZ7MsS/8kk8noOYh9+vRRKBQMw8TFxbW0tNTX1zs5OQ0cODA6Ojo6OloURbPZ7OPjExkZeezYMQcHB5ZlL824wxQEwL+iu9O2cdMG7tbbA8tttVqt0Wj8/PysH0mnv9ra2j179sTHx8fHx9947I4ZRqdR9R02/vjeLQvnjB424c7AsKg75y74cOEDCKOFH/7Y2tz42rypb3+9ceLdj771xJ1RcSkDRk4SBaGiuKCuquyeJ17Vqlp3blgVlzpQ6eCs06qgsUyXRRCSStiNe45v2HXMxJsRQscz83YdyXhoxpiePaJ4nscMLquq/+rXbUVlNdFhAaIoerm7RAT5RocF7juRtefw6QAfjyG948uq69//+temVvWzD0xNjYs0maCFP7B7F133x3K7trbWxcVFqbxMPxye57dt28ay7Lhx41A7ZVJuJhjj3377TS6XT5w4kebCjx49evLkyccff3zbtm2HDh2KiooSRRFjLIqiIAgJCQn0iadPn160aNGRI0cCAgImTZq0YMGCwMDAAQMGIKsUfltb29q1a0ePHh0TE2NJtGdmZsbExHTxLjoAdCKGYYKDg2kfdxvMVzdt4F5YWGhZjoWFhUFBQTKZrK2tLS8vT6/Xh4aGWrIIGOO2trZt27alpqaeOXNGp9P16dPnBg8OMgwWed7Z1f3Zd5c31FQEhccYDfr4XgM/WLkdIewXHK7Tql/4aKWDs/Pk2fNT+o/w8gt0cHIxGnTunj4zHnpWr1WnDhjp6ePvHxJpMupZiNq7KpEQuUx6Ord4/c4jDIMVcikiCDNMU6t69eZ9oigWldeWVtWVVNchggb16n4mr/SN+Xf7e7srZNLSqrpWlebd/5vz7vLfe8VFpecUpnSPCA30+Wnz3rioYI5lCbLplUwhOPp317WMOmgax9gOqucwxtXV1RzHeXt7I4Sqq6tZlvXx8amoqCgvLw8KCvL397c8mM66f/75Z3BwsF6vX7169axZsyBwt6CLoqSkpLGx0WAw0AXY2tra2trq6Oi4b9++iIgIg8GQk5MTGRmJ/lnxcvLkyalTp6pUKmdn5+bm5i+//LK0tHTjxo30ryzLSqVSlmVPnjzJcdyhQ4foKyCEsrKyvvzyy6VLl3bKRwbALmCMfXx8bHao8GYL3OnUtnPnzqqqKplMNnXq1IMHD1ZWVspksunTp2OMs7Ozq6urc3JyLOkKhBDP8waDIS4uLigoSKVSoRvbZyIE8QJBDDbr9JxUHhwVZ9TrEEImk9nTPxQhpNFoWJYLCIsxGQ1GoykkOt5sMul1eswwErnS3cHZYDBijCPjehoNBrOZt4Pt861KEEU5Yg6lnzWazI4OClEUCUEib+ZYtqyq/sc/dnePDO6bFCuRcMF+XiP7Jb/5/+zdd3wURfsA8Gd292ru0gshBRKS0AmhF+lNBEFARcSG2F/1ffW1V+yvYq+8KHZREQVFJXSkh95CEtITIAHSy7Xdnfn9MbC/exNASnK5I8/3o3wud3u7s7Nzs8/OzsweXSgIgt3pqqmzmU2mp+6avnzTzjZhQdFtwv7YsGtgz469Osd//+fGqtr6kMAAWaEeO/KMMSxlf+v0COML+cqpaL/pr8D4PO5e24eO167Z2dkbN24EgLFjx1JKV65cKQjCuHHjnE7nwYMH9+7dO3z4cPfGXQCoqqrq379/dHR0ZmYmYD8NN/zslpWVNWPGDLvdfvjw4djYWKvVOm7cuIcffjg2NrZTp061tbV9+/bdt29fTU1NXl6eLMuqqhqNxldeeaW6ujooKMjlchFCrFbr6tWrFy1a1KdPH6fTaTQaCwsLy8vL6+rq7r333o0bNxYWFsbHx8uyXF1dPXz4cEVRPPZUSIR8kaIoHrsrdVkF7rxeO3HihKqqt91229atW3fu3CmK4m233bZhw4Zjx47pdLqOHTuOHz9+4cKF7t8KCQkZO3bsd999d/z48RkzZlx8CggBgGCrvndCqCgQBkApZYwRYhQEgTFGKQUAQfAjhDDGCPEDAEopAaMgiAwYO7WAP2WUMSYIpkvMk7/Bz/o+ErGde0Bbi6CMmY16o8QfbkocClUUKhKi04kuBe6cMvSua0eIgvDwmyfbhphTEkMsJn1cuKlDTJhLVgBAJ0lvZ+cDpYO7tq0d1+epNxeaA6wArFNMYGybYJeseGxnfWn8GWuxEiuQC4vACSFOp0un0zXTYaQMAsw6vqVm2cAlEARBUZScnJybbrqpsrLywIEDjLGbb765oqIiLy9PUZSrr77a5XIVFRV17NhR+woAXHfddZs2bfruu+94Lw7+q3c4HF5yjUIIkWWZV+YeThKl1Gg0VldX22w2l8tVV1cnyzIPF3r27Gmz2VRVXbNmzb333kspPXjw4MyZMxVFAQBJkjIzMwVB4M1S2o489thjkZGRsizr9frq6mq+Zv7gm8rKSgD47rvvGGMFBQU8jvdAL17GmNPp5OfH5t7WpeNzWsiy3NIJOS+Yt82HMeZyuXiYd6FfNBgMFzqV02UVuHP19fUhISEAEBkZmZ6ezmeojYiIcDqdZrM5PDzc6XQGBAQAwOnomZSVlQUHB9900035+fk7d+6cOHHixQVM/DtmoxQiiPzplXq9QRAFYMzpdOr0en5moip1uU6NPmQMRFEUREF2yUDAZDK5nE5FpTpJJIIgu2TvOyOj/6eqNCjALyTADMAUhSqKatTrRIFIklhrc8S0CTQbBEaZ1c9gNurCAkxUpW2CLZEhFptTBsbMRv36//5r6mOf/pi6+dnZV1qMUtHxiiVrdwdbDaH+RqeieuzgY4eEv8UYBJh1FsOF1ZlOh91gNDb3pYZ3HjlKqV6v1+v1VqtVEARVVQ0Gg8VikSTJYDAYDAabzebn5wduVbHD4airq7vqqquuuuqqRYsWVVRUBAcHM8ZMpmZuwrgQkiS1yJNT+dV1+/btjx49WlNTExsbq9PpampqSkpKpk6dmpqaevz48Z49e/r7+zscjl69ei1evNjlclFKTSbTPffcs2jRopCQEN7iDgAul+u///1v3759HQ6HyWTavn37M888Y7FY8vPzKyoqevXqBQD+/v7btm3btWvXpEmTDAaDB2oJ3jvfqw73Ofjc0z0xb5uJoijFxcXx8fF6vR6ng7wwPLNiYmJ27NhhMBj27t07duzYLVu2EEJ27949efJku93ucDgIIfX19XA6WOHlY+nSpVdcccXRo0fDw8MvMdMZA4UykQBjcDQ/z263S5IU2Tb6yJEjDoeDUWr284toE8kAgDEiQH2tzW63hYaGMiAH9u+Lio6xmEwVlZWySw4JC1EU6oXNaQgACIBCmcMpzxg/4Kc1O+sdzgA/IwARBFJZa0vuFNu/W3ydzRlgMUWFB63edigyyL/W5ggO8Ms7WhZgMeUUn3hv4epnZk/IP3pydP/O85ZsqaqxdYgKq7M5QwKtDkWl1HPtIthV5m/x3/WFtlUplEkq0+YJbXJee9QYYzxqX79+fX19fZs2bQBg3bp1drs9LCxMFEXeWuxwOOB0VcznNFy3bl1SUpLJZDIajVarFbzsJlsL4u15KSkpL730EmPsueeeW7FixZAhQ5YuXbp69eq5c+fabLbAwEBCCL9GCg4O1r775JNPrlmzpry83Gq1yrJst9tnzJgxbtw4bYGQkBCj0dilS5cXX3xx6tSpRqNx9erVU6dOnTp16po1a7p27Qp4IBA6C8bYyZMntXGVze2yCtwBgDEmSdLIkSNTU1P79+/fpk2bIUOGrFixYuDAgUFBQYIgtGvXThTF7t27g1vvyTZt2owfP37VqlXR0dH9+vVrgntJjImSVF1VdeOUCTnZhwEg7UD2jKkT8rIPA0DfAYP+WLPRZrMBQJsgy60P3i9K4ldffLZw8W+ffvTewCuGvvzS85/O/8Ri8b/j3jvKy2pxcjTvRCnT6yRFpSs2H0yMiaiusx8vrxYFgVKWEBvx8n1TIkMDam1Om8N19dDkn1fvvO+FL9586qbocOtNz342eVjP2ddcoajqoOueGzi42/jB3Y8cr5zy4Hv1TtdnL8z2M+ntTlnw7GkSz8l/i1x4oEx8ZBRpMxk8ePCff/5pNBp79+5NKeWv+/bte+TIEX9/f94YD6erYv6Az2uvvTY1NbW+vv7KK6/U6XR4L8gdIUSv17/00kv8z7FjxxJCZs+ePXv2bP6ONiyVMcb78/C+PT179ly8ePErr7yyd+/e4ODgqVOnPvXUU3B6DnhRFFVVdTgciYmJX375JQAwxkaNGqWqKqV01KhRPtG5AqEWJEkSzuN+kXjGhYaG3nTTTQDAGAsLC+OvASAgICAgIIBS2rlz5yVLluzbt89qtdbW1t54441JSUm33XZbg/VcNEapwaAvLMgLbxP5/KtzY2LbRbRp89k3P5hN+ueefKLfgEE6vcDqmdFoeOONd35ZtPD2e+4HgJ3btlxz7fU7t6cdyCrIycp66oWXq6vsPtPzuJWhlOl1IgP415s/FJeWL3r9nooa26pth05UVHeKixzZt0tUeGC9w6UTBaesRIUH/vCfe05U1SZEh5VVO9781/UWs0FR6YLnZx2+bXy7yBA/k6FLfNt1Xz7pdClxbUOdLsXDUTtCTUubYnzixIn8HffXvAejxWIBgLffftvlcgGAwWC4//77DQbD5MmTG6wHnZF75mh3LQRB4JdA5DQexw8fPnzw4MFFRUUmk4lP5sMY4x/xZURR5J0TtIslPjE8Xjsh9Lc8eXF7uQXunNbSoA0J1V4DgCAIlNJrrrlGOz3wJnZVVQkhTdK8zRjTG0hBXl76gf2PPHDPtTfMfOaFV3v3Tck+nE9V9ZbZd9vqnQaD4Xjp8ayM9CsnTHI5nQRAr9eXlpQajcZdads6JCa1iw4rr3YCpZeeHtS0VEqNep2sqP/4zzc2u+ubl+6w+pnCgvy7xkcxYIQQRVFtdpcgEAYgEGJ3ygFWU1iQxeaUVcY6xISpKnO6FEJIclKMwynzsaqRIQGCQBxOnMEdXT7cH/Opvda6KQLAv/71L21h3k7BF+OhZ0sk2Se555Usy/yOrvunqqrqdLoOHTrA6e7O7l9RVbW+vt79SYVnXDNCqDE++ISPe/HA7+XybM3l8bd2+9X9tdYOxEN5jr8vSVJTdUohhFCVGo3GSVOvfe3tD3787utD6fsNAlv45YLOXbu1iQx2uVyyLFuslo8//6xNVJQsO1WAcRMm7d6RNuiKYfv37olLSLjphpnrVq0wm80UY3dvQikzGXR2p3z7nM8ByOdzbjebDPUOp0tW6h1Om8NVb3O6ZMW9W7NAiKKo9XYX7zjhcMqyohBCGIM6m1M9fRJ1yYodo3Z0edEe5+n+WgsQ3eth7e4iXwx/CBeBZ9qAAQMeffRR+N/JNPn1Eu8b435RxJeJj49/4YUXfGUsIEJehRASEhLisf4Rl2fg3rIYABEEh0Mx+/nNuvPeWTOm9ejZ69jRozYX271ze78BgykFQsBoNEo6SSDgdNhFUXIAJHbstDT1z+CQkOCQ4Lzsw/EdEpYs/oHfRMYuhl5CVanJqK+utd/09KchgZZ5T9+ik0SHSxb5pSD/TyCNYw5CiBbKaxeQhID7wnwNntwdhNDlhFcmCQkJEyZMOOOn7hdI7l8JDw+fOnUqjqdC6OLwqVc9AwP3pkcAqKpaLPo9u3bcf+dtv65Yk5WR3qlLt9LS8prq6s7detjtClVpYX6+IiuMMUEQeeymqorTqW7dtLF7z96MsfYdEmSXzCcHbel9QgAAKqV+ZsOJipoZT83v2D7i/UdvZIy5ZFXEA4QQ8hraM0MuCN7aReiiefIOIQYczUIQhJoa1y233+lnsVxz5ehp029MSIovOVokCEJwSAghpLys7NqJY08eP64nxG6zOx0OADCZTBkHMwry88aPHx0T2/77r7/s1iPZ39/KO9+39D61dqpKLWZjcWnFDU/OG9Sjw9x/Xe9SFEWlzTfTH0IIXQTesn6h38IWIoQuDqU0Ly+P94/wAN94hpZvqaqzVzspATAajZWVFUePFHfq3JUQVldbf/LE8Zh27QkhiiwXFxVGx8QajYYjR44AQFR0NKWsvr6upro6JibKJdNDB/cnJHU0mbCPe8tTVervZ8wqPD5rzoJJw3o+efuEOpvzcpps4XLal2bCH8AUYLqwTsA2m81oNGJIdDmRZblFHsB0cXzrQTaUUofDYTabWzoh5wXztvn4Vt7KspyWlta7d2+TyYQPYPJVjAERiM1mt1j8uyf3stnqgYHJ7NchqaPT4aCMiZKuY5duTofDJasxse0BwOl0AgE/izUgIMjhdAoC6dN/oMPuUFSV4BTbLUpRaaDVtO9w8R0vfjnzqgEPzRxbXWcHAIGQy+ayl536H50VY5hDCCGEzsCTrTMYuDc9SYBQi4H3oGCMMSb7WQ0ABIBRSq1WI1+MUsVi0cPpgaf+Bv4+Y4z5G4wAjFLZZJYIaa4rTj5BGJyebaCZttJU+GNEAIBPM+yx7VJKLUbdpv35d7zwxb9njrlv2pA6hxJmNZz7kpoxRqkqir7x+2KMuVwuo9Ho/cUAAFRV4cNCPL9pnYiX0AghhBry5CnJNwIL3yIAMxkEQv728qvlx+9T8dTE9i2dkPMiAQEAnc5zqaWUCoJu877cWS9+/fI9k2aM7UMpsxjP51fDFIVJUssf4vPBGBVUMHkwYy+FolBJEvFJrwghhLyBKIodOnTw2DzuGLg3C8Z84yHnvtDA+v88mVrGQKVUEoU/Nh984M2f3nxwytQRPRWVnucEMoz5Ut76VicQnrc+8ftCCCHUGvj7+3usDRQDd4TOgDIqicJPa/Y89fHS/z45Y0y/TopKJdE32qQRQggh5DGenEQEA3eE/gdjQCkVReHz37a8/u2qz5+9eUjPBBWjdoQQQgidiScDd4xFEPofjDFRFN77Yd1b36/54aXbh/RMUFRVxKgdIYQQQo1QSnNzc51Op2c2hy3uCJ3CGKOMiYLwyhepi9bs/vk/d3Zq10alVMLHgCOEEELoTBhjtbW1vNEd53FHyEMYAAMQBeGJj35dvSNz6dy74yJDVJViWztCCCGEzgHncUfIo/j85QIhD7790+7Moj/fuS88yMp7urd00hBCCCHk1UTRc08XwcAdtXbaja3bX/62oKR82Zv3BvmbVcrOc+ZHhBBCCLVaoigmJibiPO4IeQJlTCCEMnbTc1/W1Nv/fOc+o15HKRMFnCccIYQQQn/PZDJhiztCzY5SJgjE7pRveGaBJIpL3rhbJ4mUMQGjdoQQQgh5H+wMgFopSqkgEJvDNeWx//r7GX967Y5TUTs+kxMhhBBC502WZeap56Vj4I5aI5VSQRBOVtWNf+ijdpEh38y5TSCEMcCoHSGEEELnT1XV7Oxsj83jjoE7anVUSkVBOHqyetIj8/p0avffJ2ZQyihjGLQjhBBC6EI5HA7e4u6BdncM3FHroqpUFISc4pOTHvlkTL+Ob/1zKmNMEAi2tSOEEELIy2HgjloR/kClAzlHpzw+f/ro3i/edbWq0pZOFEIIIYR8mF6vx1llEGpiikolUdiZUXjLC18/eP3we6YOoYzhI5YQQgghdNFEUezYsaPRaAScxx2hpqKqVBKFNTuz7n5t4Zw7Jtw0vp+qUpz2ESGEEEKXSJI8F05j4I4uf7ytffnW9AfeXPT2v6ZNGtKD95lp6XQhhBBCyOd5rJ8MYB93dNlTVFUShUWrd//jjR8/fuyGSUN6qBSjdoQQQgg1DZfLhfO4I3SpGIBKqSSKX/+Z9vQnvy58adbY/p0VlYoCFnuEEEIINQFVVTMzMz02jzt2lWkW2HW6xTHGKGWiKHy8+K93f1z/02t39EyKoZRK2NaOEEIIoaajqqo2j3tzd5vBwL3pMcZklQrncc+EARBCRJxCvKnx348oCnO/Xf3F71t+nXt35/ZteE/3lk4aQgj5GEqpqqo6na7Bm4QQHqO4v0aoFaLUc1NLY+DelPiV1tFK54Gik5IgUEYZADk1aoGcXoYyYAAgEKIy4m+SrugcYTJI/EoNK75LxxhjAAIhL3z25y/r9y5/5x/tIkNUyjBqRwihiyAIgtCoh6H7O40/RahVMZlMHovf8MfW9GSFVdtc1fVOhyqqotkJ+hq7Um1zVdtc1TZZJkYqWRRiclCpxiY7qWg0SPD/8T26JPzaSSDkkQ9++WPzwT/fvq9dZIiiUhFnfkQIoQvE715u27Zt7ty5LpfL/c3MzMzS0lL+jvtrhFobURQ7d+7ssXncMXBveoSAQMDkZ96zZdX91/T+6b+vS5IgEtBJouqyv/rP62eP7fTPawfMf/XfRr3us7eef/bpZxRFOXny5PPPPw+eveFymdH6lt37xg870gtXvn9/VHggtrUjhNBF4AF6aWnp77//HhcX98477wCAoiiMMYfD8dRTT+Xl5THG7Hb7U089lZ+fr30FIdR8MKBpFpKkLzt+7NPXn+yU3H/V0m92/LXCZPFXVUUQpS69Bo28+kZBFAVRzMnYb9bD4fyi3JycFStWtGvXTlXVlk67r6KUEUJkRb35+S/zj5X99uY9gVazShm2tSOEmhBjrJWEp7wppKCg4Kqrrrr22mtNJpMsy7zbzKZNmzp06BASEkII0V63dHo9qpWUAXSePNlbDAP3pscYEyXxxLHi7n2veOaDH3v0G3aypFin0zHKJJ3uhrufvPmfz0W1T5w266Hq6srQ0IjQ0LDiI0W7d++55ZZbRFHEDjMXgTImCMQlqzc887ndKf86954Ai4kyjNoRQk1MkiRRFFs6FZ5TUVFhsVhUVQ0PD6+trSWEHD9+XBTFm2++2c/Pr6amRhCEW265pcHQ1cseDsZF7ux2u8eu5XBwatMjhLicjg6dk7v3vSL7wM7CnEPjrr3N6XQAIZQqsuz844f5fhb/yJg4ldLvl//QJbFdQUFRYmJiamqqKIrjx4/3wHRCvo5SPgIVCCG8Wb2qzn79UwvahPh//sxMSRQpYzhbD0KoyZWVlel0uqCgoJZOiIdYrVabzSaKYllZmcViIYR8/fXXeXl5VVVVAwYMUBQlOzu7pqamU6dOzzzzjCAIreH8xRgrLy/39/fHUbkIAFRVPXToUK9evUwmkwfKvw+UOY/dl2zKDTEmCILDXv/us/f2HDiia6+B9roaQgghoqrImfu2d+41gBASEBx28/1PPfnE4xUVFWazKTU19csvv8zLyyOE4G24s6GMAYAgEFEghBCVUlEglbW2SY/MS4gO/er5WwQiKColjb5FKaP01DSr/DX/EyF0Ps6/hjyfxc6xjNf2RVEUBQCeeOKJX375BQAu+56NPP5o3779b7/99ttvv9XX1xNCDh48OG3atGuvvTY+Pj4iImLatGnTp0/v0KFDhw4d+Jnrso/aAcDhcNx8882ZmZmSJOGwNASe7SrjAy3uHqsF+IaapN5hjJnMlo9ffii8bew/nnmnsuy43mAUdXrZ6aypLC8/URrfMdnptLtcri7dku3O0oqK8uTk5JSUlH379hUWFsbHxzfFDl2GKD3Vjn4g96jdqXRuH2E1GwtLK6578rNhvRLnPjAFAIhAhEaPwBII0d7DO5wIXYTz/9mcz5JnW0argVskBKSUUkolSdISoyiKKIqCIMiyLMuyJEknTpyoqanxcMJaBA/EY2Jixo8fv379+ieeeMLhcOTm5k6ePDk+Pr53796iKFqt1vbt23fs2JE3xnvnFVeTY4wdO3aMT7OjKIokSTxu4xPe8/KjlZwWTivyCE9exvtA4H78+HFJkkJCQniNoF3Ta//yxVRVlWVZu09xjmWMRmPj84GqqllZWVFRUQEBAZeYYAZMbzBl7t+x+tfvAgJDZgxpf+cTr6uyvGvjyn+9NO9YUY7DVhsSHqnIMgAosvz+R+/dOetWs5/fjz/+6HA4YmNjLzEBlyvGmNFo2LAn57n5v+ceKVNUtU2o/4wxfVK3po8f2PWFuyaoKqWMvfxF6h8b9v/w6h0JMWGUMkKAEJK69dA/5v5w0/j+z8++6s2Fq9/6PNUaZA2wGn99457o8MBW0kqE0KWor68vLy+PiYnhfzauZrXK1m63m0ymv12GV8UNfnqEkPz8fEEQ2rVr5/FdbDhhOSGEd91mjOl0Ov5ap9Npkf1ljx+vIUOGDBkyhDFmtVpjY2Pvuuuu+vr6adOmTZo0CQBUVW3btq22fIum13MMBgPfWb1er73pXn5aW6f/Vs7Pz89jF2neXvs4HI4vvvhi8uTJfPQ6f5O/cP8XAEpKSkpLS/v27dv4U22ZEydO5OTkDB061H0TjDGn05mamlpdXb1t27YRI0a0b98eLqECIgAAjBCYcusDssupKnJoWKSqKh2791EUl8nPetX02XqDkTEqSaLNXj90yJBu3bsbjcahQ4cGBwd36NAB48jGGAO9Trdpz+Hrn/q8vKbeZNARIFmFxx9/5dtpU6544a4JLkXRS9Kyv/Z//Wdaj3bhd/1n4eoPHuRR+8mq2jte/W5s307zftnYv0v73p1iZ17Zr6iidkdGgb+fsaX3DCFvp6qqKIpLliyxWCzuLQtnrGydTueOHTsGDx7Mo9szLqOq6ubNm4cNG+Ye9FBKBUHYsmVLQUGB0+lMTEy84oor+Jse2Ee+ob17927cuPHOO+/kUzIfP378008/vfLKK/v06fPSSy9VVla+9tprgiAoiqIoivaQc2/Gbxpc4gmFUirLsp+f35tvvvnoo4/yI7Jw4cJbb731ww8/NBgMqqo2yWBNSinP20tcT3PjiZQkyWazffLJJxMmTOjUqRMAZGdnL1q06L777mOMffTRR1deeWXfvn09VoZRS+HzuBsMBvDItav3Bu68rK9fv/7w4cNWq/X3338/dOjQmDFjUlJS/vjjj7y8vHHjxiUlJaWmpmZnZ19zzTUmk2nHjh27d+8eOnRo586d//jjj/z8/PHjx3fo0IEvP2nSJLPZHBAQsG/fPkppSkoKj48JITU1NSUlJffee++RI0dKSkri4uIupTpmjNgdjnYJ3Tv2HMQfq1RXW00ISejWt7amKiA4YtQ1t9hqa4gAlIKi0JkzpgMAZey2227ja8CovYFTB4OQd75fW1ZdFxzgpyhUpRQYGEICikorj5yobBsaCAA7MwtvuarfU7PGd77+hcqa+pBACwDkHS0f17/zgmduuvXFrw8XnfjXjBGj+nR8/ZuV4wZ09vczqpSKWKsidBaMMUEQjh49umrVqttuu+3gwYPLly/v0KHDlClTMjIyVq1a1aVLl9GjR2dlZa1YsaJXr16DBw8uKSn573//m5CQMG7cuPT09DVr1nTr1m3kyJHp6emrV6/u2bPn4MGDLRbL8ePHMzMzR44cKQiCVunt3bt39uzZBoMhNTWVb9ozuykIgtPpPHToEGNsy5YtI0eOZIxlZWV16tTp8OHDISEh/v7+EydOFEWRNzxLkuQr7e5N0vSr1+vT09OfeeYZq9Wq0+n42fOrr74aP3789OnTL3397htqwrU1Ez4sVZKkvXv3GgyGLVu2dOzYUZblLVu2dO/ePT8/3+FwdOrUKSMjIyEhwUvGMfvWNDg+l1pPDnXw3nqH19f9+vUrLy8PCgrq3LnzwIEDly1bFh4ezhibPXv2oUOHioqKGGOzZs36888/+/XrFxAQMHny5OXLlxNCDAbDrbfempqa6nK5jEbjrFmzfv/999GjR69fv75du3ZXXnmle0/KkJCQxMTExYsXE0KuuuqqS0y5US9GBpsFAFWuAgLAINgsATDGHNZgP5esqEpdgJ+eEFAp8zfrbQ6X2agXCOHtIq1qorHzxCgTBFJSVlVQWqHX6VSVUkodTlkniWaTcc/h4szC49HhQQBQWW2Ljw4hAKEBlup6R0ighTHWv2v7/l3bl5bX7D185J/Xj6CUFR2vWL7l0JI37gIA0qhDPEJIw89JUVFRY8aM6d69e3l5+cMPP/zVV18dPXo0MzPzjjvuSE9Pr6qqOnjw4F133fXHH38cPXrUbrffdNNN69evz8rKys7OvvPOO1NTUzMzM3Nycu66664///zz2LFjJ06c2LVr17Rp07TQnFfIgwcP/vPPP+vr66+44gqtd43T6WzWtm1KqdFozMjIiImJueGGG3799deamhqDwTBo0CBJkpYuXXrkyJGioqL8/PyUlBRVVb/88svMzEw+WLP5UtUk+EjfS7z+oZSaTKb9+/e7XC5CiMPhAAB+ufXKK69s2rTp0hv1tdRqfcS9Fr/Gq6ysLCsrq62tvf/++1evXl1YWOhyuRRFKS8v79u3b2RkJAD89NNPDofD4XB4w1103rmAT/vTsik5Hz5REjT8vtZFVFOMMb1ef6FRn7dnCr/qMhqN+/fv37NnT1xcXGVlZXJystls7tOnz6ZNm/bt27d379527doxxvr27WuxWBITE7Ozs4cMGWK1Wvkl76hRoywWS+fOnUtLS3Nzc5OSkoxGo5a/hBBFUUaPHl1UVLR///6NGzeOGTPmolMLAMH+hq4GnUgIA2CMAhCBEL4xUSABJon/fAVCgBBgTC+dqlJxEvezIgAAkiiKRCBwaqiDyaATCGEMJFGUTp+WJJFnK1DKREGgjDHGCAOV0uue+uzqId17dYoBgL/25MREBAVZzdjcjtD5MxqNNpvtrbfestvtVVVViYmJfn5+/fr1O3nyZFFR0QcffKDX63v06NGrV6+AgIDevXvv27cvMTHRZDINGDAgLS0tKSnJZDKlpKTY7fbc3FxZloODg7WV86o4OTk5Li4uKytr06ZNoaGhfn5+jLHmbs6glBJCZFkmhAiCwKtiURRFUVy2bJnBYBgwYAClND09/fDhwyaTyWAwBAcHm0wmn6ixL72rBg8vLBYLvwbgjYt8nSaTKSQkpAmbGxVF4S36TbXCJicIgsPhkCSJMcZ3XKfT8d5ElZWVCQkJmzdvnjZt2h9//GEymSIjI3m5aulUA6WUF+mWTsh54QXAVwJ3SmlVVdXFVQgX8RVvzxRe4xw6dCg8PPyf//znzz//HBAQkJ6e3qZNm/T09KioqD59+gwbNiwrKwsADhw4EBMTk5ub27Vr17179/bv3z8rK6tz58579+7t169fVlZW//79Z82aVVhYmJubGxcXp40CPnbs2I4dO66//noAyMrKusSLY/5NBkBV1Wg2A4DT4STkVH8PP8NZ71p6w2/bOwkEGGNhQdakdmE7MousZqOLqYQQnSRW1tq6d2ibnBjNQ/CIkIDsIydLymtKK2qCAsynro4A/vnOL/FtQ1+++2q+ws17cwd2v6QOUQi1NoSQ4uLigoKCxx57bN68eRaLZd++fUlJSRkZGdHR0QkJCVdeeWVOTk54ePhvv/3WsWPHPXv2dOzYMSsrKykpaceOHYmJibm5uYmJiQcOHOjatevQoUNdLtf69etHjx7N42bexvbjjz9Onjy5b9++x44d06piz5y/27Vrt2vXrgMHDkiSZLVaAWDXrl01NTUzZ87Mzc3t06dPYGAgb2W//vrr7777bg8kyavk5eVt3bq1pqbG39+fMSbLst1uf/bZZydOnNjSSWsBa9eu9ff3V1U1IyPj5MmTAwcOrKio6Ny585AhQzZu3Lh9+/ba2toZM2bwYc0tnVgAX2vDBgBCiK+kVlGUvLy8oKAgPjamuXl7W6NOp7NarYmJifv371+3bl1CQkJ0dLQsyx999JEkSe3bt7fb7R988IHL5QoKCqqtrf3qq6+6d+/eqVOn6urq+fPnd+/evWvXrlVVVfPnz+/Vq1dgYKAgCMOHDz9w4ADvoMbFxcVFRUW9+eaba9eu7du3b5P0qlRVNSzM+uWn895/8z8BAUY+jIkQYnM4brnllmHDhpWXlyuK8thjjz3zzDOyLJ88efL5558HAJwU9kwIAKEqfeKWcR2iw4+XV/PeMmVVdXpJfPLWsUH+ZpUyABjZp+Mv6/Z2mzbn6iu6+5uNt734zW8b9xeUVHz432WrtmeGD3/o29QdAJBZeDyubahv9aJDqGVZrdaYmBi9Xv/5559HRUWFhIQkJCR89NFHx44dCw4Ojo+P/+ijjzIzM3kT7KeffmoymZKSkmJjY/n4xa5du7Zr1+7DDz80m81xcXGKovTr189ut4uiyOdp0el0RqNx0KBBCxcufPfddxMTE61Wq8euriml4eHhDofjjTfe6NWr18GDBzMzM9esWfPTTz89+eSTkiQ988wzCxcuTE5OttvtDoeDt7BSr6eqqtPpvPT1KIoSHx8/d+5ci8VSVlZWXl7udDoffvjhcePGqaqq8hq5KbZSV1fXJKtqVnV1dYqi6PX6jh07vvzyy3x4bk5Ojl6vnz17dlJS0vr163/88ccnnnjCZrPB+T3ZoLl57eMRzsjnUqv1QfJAslvLrKuNrVu3Ljs722w222y28ePHx8TE8JkTLn3NVXX2KrtiMpvS9+2bctWoqdfP+GD+J2UnaihA23D/Rx54cOuWzW3btg0PD3/ooYfmz59vs9kefvjh3bt3y7J8yy238Hu1l56M88HvOfjKvTOn02kw6NPzS9/4euWGvblOl9wzKfr+a4dfNbgrY7zbESOErN2ZtfVA/j9vGGExGRb8tqVP53Zmo/7b5WkuRXXV2adPHNivS7tvU7eP6J0UFRYIwKAZ+rjzHm9e0tDytyilDofDbDa3dELOC59L21euuGw2m9FovMzmlGjCDruU0oULF/JZRPR6/fXXX++FbWza/lJKBUGYMmXKyJEjH3jggaY6ZTSrJqyLeD4cOHBg2bJlsiwPHDhw7Nixl75ad75SF9lstuHDh3/yySe9e/c+x2Le0LVd4yt5y/nWOVSW5bS0tN69e3vmyaleV0U25p4LZ5wS+IL+1VYSFxcXEBCg0+lkWeY3/vjJ9dIznTHQ6XQV5eUvPfdkfIdEs9mPUmAAoijW1bn27ds35/nnBwwcSCndt29fVFRUVVVVcXHxnj17Xn/9de8/DbQgQojD4ewaF/nV87ceOVGlqGp0eJAk/v8TtvlRHtmn48g+HflXZk8axF+8cNf/3My96cp+2lo9ln6EfFqDH9qlV8V8ncnJyZRSAOBPq2lQUbfIPjbYtPYOb2R1Op2yLHs4Yd6AD1Pu3r179+7d+Tu0FU90aLfbKeWjqJh287ZB+fGeqB01K0JIYGAgj99a9XSQmgYV6CX+q71o3749n6/9HJu72AQDZQyAvPPJvPkffVRXV8uvCERBrK6tBWB33X13bW3tkiVLevbs+cknn0RGRhYVFSUmJqampgqCcNVVV3nVZbpXEQSBUkYIiQ4P5O80GF1KCFEppZRJokgIKCoVBEIAFPVUByRREASBKCoVBewng9AFaPKqGABEUdSiwHNszmPOFm/xd3iQ2qlTJz5nSCvER6byW7V8FG9Lp6hlCILQs2dP7WGxDaILPLO0NoIgJCQkeGwmUx8I3JuJew+qJm8zoJSa/fwSYsPr6+q0hnxKqU7S1dfX33vvvaFhYXPmzNm8efNbb70lSdL333/fpk2b1NTUkydPdurUKT4+HmP3sxEEwoBfGgEBaDwnjCgI4un3pNOvdNL/nGC09xFCLYu6jerx8uZb3o1nzpw5vHJunWFrg4fLtk5Go3HevHkGg4E/hqmlk4NanjbZiQe03p8f70refHUQo9ROqU6nE0WRARiMRqPJGBjgZzKZ+/XtO+nqq/nj9+Lj4xVFqaioiIyMTElJiYiIKCwsbI70XE4IgECIgENLEfJ9gpuWTst58fPz449IRK2Zn58fnxGypROCvIInL+N9o6L0UZIgVFdXVZRXWAEWfffNA3fO8tOL11133bXXXZecnMwf7UEpfe+996ZNmxYTE7N58+aysjL3J4ojhBDyKnyKsJZOBWphvjXtCWpWjLHy8nKPNbrjLZ7mIgiCzS5PnDyVUlZrl+M7JABARb3yr38+GBhgraurv//++/liQ4YM6d69u8lkGjZsWFBQUIcOHbCfDEIIeSferbmlU4FaGBYDpKGU5ufn84eyeSB+w5LX9Krq7FUOVSACZcxq9SMEqmvqLX5mSU/qq20RAUbdmTpYt0iw7lvTQbpcLgDw2PiPS+FbU1n51jRhOB0kall8+nZf6S2DdVHzwbxtPr6Vt7Is79y5s2fPnjgdpK8iBEx6SSAEAGS7DQAsBom6HA4H5e/zSYu1ES18MmA+1xh/znYLJh4hhBBCCJ0/Tw5OxcC96ekIs1gMjdvYiPawH+F/sl2L1HFwOkIIIYSQDyGEhIeH8xAO53H3VeQsz/Xxjbv7CCGEEELoPAiCEBsb67GOPdjzEiGEEEIIoYuE87gjhBBCCCHkA3Aed4QQQgghhLwdY+z48eMea3THwB0hhBBCCKGLQSktLi7mM1Z7YI51DNwRQgghhBC6SNhVBiGEEEIIIR+Ag1MRQgghhBDydoIgtG3blk8H6YF53DFwRwghhBBC6GIQQtq2beuxZ2hi4I4QQgghhNBFwq4yCCGEEEII+QAcnIoQQgghhJC3o5QeOXJEURTPbA4Dd4QQQgghhC4GY6y0tFSWZcB53BFCCCGEEPJm2FUGIYQQQgghH+DJwakemrymVdHr9R6YyLNJCIIvXbl5bK6lS0cI8eT19yUihOj1+pZOxfkSRdFXfl/gU7UBOk+iKPpQzYl1UfPBvG0+vpW3oih26NDBY/O4Ew90x2kNGGOUUkEQCCGMMcaYIAg8b/G0fXEopTwbCSH8Nf8Z86zWXmP2XgStZLqXW0opAGC5vRTuBVVVVUIIz08ssb7L/TdyxjdVVeU1lQ9F897D/SejvUMp5XFb40/R+WuQe7zQ8ipIFEUst5eI1wDu76iqynO7ucstBu7NBc/QyBdhuW1amJ8IIXSZadmKHa+0LhW/8qmtrf3xxx+LiooA4ODBgxs2bCCEnDx5srS0FDwyyvhywrMrMzPzxx9/rK6uBoCMjIyff/7Z5XIBQFVV1e+//+5yuSilOTk5gNl7IXhe1dTUFBQU8BdYbpvQ+vXrf//9d97ZceXKlRs3biSEVFZWYon1Re51e3FxMX/HvXaqqakBgHXr1n344Yfr1q0DAH7bCp0PLSd//vlnPh0Hx/Nz7dq1cLrmd/8UnY8z5m1JSck333zzxRdfrFixgjG2fv16LLcXjRCSnp7udDrhf3ObRymNS3XTwsD9UvFjlpqa2q5du/Xr15eXl1dWVlZXV+fm5paVlfG7US2dRh9DCDl+/PiuXbs6dOiwZs2ampqanTt3tm3b9rfffgOAgoICxtjevXtPnjxZV1eH2XtBtOK6ZcsWAFi+fDmW20vH82rnzp0AEBISkp+ff+DAAZfLVVFRsW/fvvLyckrpnj17sMT6Fu3H0r59+3Xr1tXW1kKj2slmsx0+fHj8+PEdOnQA7GB2Ifg1rXvdDgA1NTXZ2dnjx49PTEysqKjYtWuX9ikGl+evcd5SSq1Wa8+ePaOiogoKClwuV2ZmJpbbi8AYU1V1x44dH3/8sTZxu5bbf/75p91uT0tLa9Zyi4H7JeFdxKqqqiIiIgYMGNC+ffuKiorw8PC2bdseOXJEVdWoqChCCP4qzh8/WYqieOWVV/bp00cQhGPHjvXr12/gwIEGg4ExJklSp06dqqqqiouLu3Tpgtl7/nhxLS8vr6ur69y5c01NTWRkJJbbS8c7OsuyzBtgEhISqqurx44d26tXL7vdzhjr1KlTdXU1llgf4l639+/fPyYmpqamhh84rXZijNlstpqamry8vLCwMMAA6Lzxev7EiRN9+/bldTuPgVwuF28+aNOmTUVFRZ8+fbRPMW/P0xnzlhBisVi6d+8uy/J1113ndDqx3F4cQoiiKP7+/l27duXt64QQLbdNJlN+fv6AAQOatdxi4N4E6urq9Hq9qqp+fn5+fn5Hjx7Nzc319/d3Op3z5s2rrKwEvDl+3ngpDw0NDQkJWbduXXh4uKqqOp2OUurv768oSkBAwJo1a0JCQoxG4/fff797927t/jU6N95UUFBQcOWVVwYFBTkcDiy3TYUQkpGRYTQay8vLN2/erNfr+YBUg8FgMBjWrl2LJdYXaXV7YGCg0+nkB47XTn/99VdISEhAQMCAAQOsVuvSpUtVVcVW4QtSV1dnMBh43e5wOBhjer1+4MCBVqt12bJltbW1RqNR+5QPpm/pJPuMBnkLAIyxkpISQkhQUJAgCIMGDcJye3F0Ol3Hjh11Oh0vkIwxntu8ojhx4oTZbG7WcouBexMwm81Op1MUxdraWkrpyJEjJ0yYwBjT6XRXXnklv4GONc7543l16NAhp9M5aNAgAHC5XIIg1NbWEkJiYmLuueceo9HocDhGjx7N24+xweBv8SHwOTk5q1evXrp06S+//FJbW6soCpbbJkEIiYqKGjJkyIgRIyilsizzeRtsNltsbCyWWB+l1e3V1dUGg0E7aocOHbLb7cOGDSsrK+vVq9eAAQPCwsLq6uq0SZnQ+TCZTE6nUxCEmpoak8lECLHZbCkpKQMHDgwNDbXb7Yqi8E+NRiNgw/CFaJy3hJDDhw9bLBZCSE1NTUpKCpbbi8Mv4LXSSAjhuc0ritDQUJvN1qzlFgP3S8In0QsKCiotLd2+fXtRUZHVaqWUZmVlhYaGmkymrKysgICAlk6mL+G/h4KCgh9//DE8PDwvLy8iImLHjh1paWkOh4NP5V5aWlpfXx8fH5+RkUEIkSQJK52/xSeuio2NnTRpUmJiYnh4eGRk5LFjx7DcXjo+e11gYGBqauq6deuCgoKsVuuKFSv27t1rMpkA4NixY1hifUuDur2wsNDf37+4uJhSWlhYqNVOiqL8/PPPO3fuLC8v5z8iDC7PB8+liIiI7du3p6Wl8T5mxcXFWn6WlZV17dp18+bN27Zt4zU/tgqfpzPmbWFhIQDwIg0Aqqpiub0UhJD6+noAUBSluLg4IiIiLS1t27Zt9fX1cXFx27Zt0yIW7OPujfiF7Pjx43NycoYPHx4QEEApbdOmTWxsbHBwsNPpTElJAV971FGLI4QkJSXt2bPn8OHDoaGhvXv3LiwsnDRpkvZpjx49goODZVlOTEzksRE6HyaTqXPnzsOHD7/yyivNZvO4ceOw3F46fs7r37+/TqczGAzdunXr0aOHJEkBAQG9evUCAEEQsMT6HPe6fdiwYVarNT8/X1VVQRC02ikmJqZ37965ubkTJ05sMNc7OjfGWEhICK/br7nmGpfLVVBQEB0dnZKSkpeXN3bs2ICAgL59+xYVFfGaH+ui89c4b/nUYQkJCfHx8QDAy21eXh6W24vAs2vw4MEWi0VRlIKCAp7bRUVFEyZM8PPz69u3rxaxNEe5xU5jCLUujR8bgRBCCCGfgOfvpsGH/WlXQdqQBT6jM7pQjDFFURRF4RlIKXXPSS2fcdbCi8C7M7oX0VZYbvk+amWsQSk6Y6HiD8PT/lRVVfsif9aj9qa2gHaT9Gwl9nwKMC/87mu4kB098wqx18H5c/+N8Hw7Y+2EFdHFca/befa652eDmh9dkMZ56z4sHsvtJdJqUfdyq73TrOUWW9wRQshL4YNXEUIIucPAHSHUivBQuKqqKjU1lU+ySwgZN25cYGAgf0oAY4zPnmYymXirCSFEEIRNmzYlJSWFh4fz9axYsaKqqop/8fDhw/X19T169AAAURQZY7wNRhRF3k7P18Bfi6KoJWPjxo1dunQJDAzUZnXgi/Fgnf+7cePGkpKSiRMnms3murq6nTt3Dh48WBAE3jOVp5BvVJvrgK8ETk9GztfDG4F0Ol12dnZ9fX3Pnj3xqgAhhHyO1NIJQAghz+HRam1t7fr1648cOQIAkZGRgwYNCgkJ4Z+6XK5PP/30H//4BwDwIJtLTU01m808cP/6669XrFhBKV2/fv17772XkZFx5MgRPpwXAAghWnSuDSdwf635448/oqOj+aa1GJovxuP4r7/++vfff5ckKT09/YUXXqirq/v111+HDx+uLaClsMFznRpsi2+dXx7s37+/tLQUA3eEEPJFGLgjhFoRHtHGxMTMmzdvyZIlqqpee+21ALB8+XJFUa6++uo9e/b89ddf/fv379Onz8qVKysrK6+66qrAwEA/Pz8+GykAHDhw4M477xw+fPjSpUsdDoefnx8hZPny5VFRUT169CgtLV2zZk1ERMTo0aO3bdtWU1MTERGRnJy8fv36ysrKq6++mrfr8yehZGZm7tu3b8KECVlZWQ6Ho0+fPlu2bImIiOjQoUN5efnatWvffPPN2NjYe++9d//+/e3btw8ICNiwYYPT6RwzZowsy6tXr66oqLj22muPHDnicDiOHz8eHBzcs2fPbdu2hYWFHTx4cPDgwaGhoYSQ9evXl5eXT5s2zc/PD6e1QQghH4WBO0Ko1eHdURwOhyzLjLFPP/105cqVqqrW1NTwR98VFxcDgKIoBoPh66+/fvDBB90Hpw4fPvzjjz/+448/Hn74YX9/fwBYuXJlaGiow+FYsGDBqlWrunXrtmzZspCQkJUrV/7111/PPvtsWlral19+yZ+uxy8VAMDhcHz77bcOh6OkpKR3797Lli3r3bv3zz//PHv2bAAoKipKSEiIjY2llM6dO5dvPTs7u6SkpLCwsE2bNi6XS5ZlvV7/448/RkZGfvXVV1artaqq6ttvv/3zzz8rKyuLi4sPHz786KOPrl+//uuvvxYEISAgQOtIgxBCyOfgrDIIodaI9xLR6XQAcPDgwQULFixcuHDnzp09evQYM2bMtGnT+vfv369fv/Ly8traWnDrykIpnTBhwiuvvJKUlPToo4+WlpYKgtCnT5/PPvssOjq6oqLi5ptvNplMtbW1lZWVZrN5zpw5w4cP37RpU7t27ZKTk9etW8efB8lX9eyzz/7www85OTlxcXEmk2nXrl0hISFdunQBAIPBYLfbAYA/NthsNsuyHBgY+P7778+YMePw4cO9e/fu169fWVlZTU0NpbRbt24ff/xxVFQUf1bi9OnT586dW1NTAwA7d+6MiYnp2bPnmjVrbDabexcghBBCPgQDd4RQK+X+zOp9+/bt2bNHEASdTnfixIny8vIff/xx8+bNkZGR7kNFAUBRlJdffvnkyZPTp08HgGPHjul0urZt2wKA2Wx2OBxz586VZTkgIEAURVEUQ0NDeRfz2NjYUaNG3XzzzXwsKV/bgQMH9u3bJ8tyUFBQVFTU559/zge5AkD79u2Li4uXL1+ek5Pz+OOP5+TkCIIQFBRkMBj0er2fn9+yZcs2bdrUtm1b3ogeFRVFCPHz8+ODUCMjIw0Gg8FgAAC+9dGjR19//fX43FaEEPJdGLgjhFopRVGcTichZPLkyXPnzn311VcnT57cpk2b8vLyH374Qa/XHz58uKamhjday7LMe5jo9fp+/fr95z//mThxYpcuXbp161ZVVcWfK+5wOAghsiynp6erqlpWVsYn/OYT18iy/Ndff9XU1BBC+KoIIX/88cfTTz89atQoSZJ69uyZm5vbp08fAKCUms3mBx544Isvvrjnnnv69OmTlJTkdDodDgcfQasoik6n4ymsra212+08DXa7nTHmdDplWVZVlb85btw4l8u1bt06l8sliqLL5WrBbEcIIXTRcDpIhFArVVNTwxgLCAgAgIqKCv6ccACorKzk3cGzs7P9/Pz0en1oaGhZWZnFYjEajfy7VVVV9fX1bdq0EUWR91ThnePDwsLsdntRUVFoaKhOp1MUxWKx8Gbv48ePV1dXJyUlwenJbSoqKoxGY319fVhYmMPh+Ouvv/7888+3337bvStLTU1NfX19ZGQkACiKUlFRER4eXl1dLYqixWLhKTSZTLzvTUBAwIkTJ0JCQqqqqqxWKyGkuro6NDTUfev19fUulysoKMjT2Y0QQuiSYeCOEGrtKKVap/PGkzaeY/nzp829eMZJGBljBw8e/Ne//vXMM8+MGDFCW/+5v9VUW0cIIeQrMHBHCLVSvPbTItrGr7Xqkb92D3kbfOS+TINKVfuW+yYar8TlclVWVkZERJwjkXA68m6cwgbpbBypN/gKhu8IIeSLMHBHCCGEEELIB+DgVIQQ8grYjIIQQujcMHBHCCGvgN1XEEIInRsG7gghhBBCCPkADNwRQgghhBDyARi4I4QQQggh5AMwcEcIIYQQQsgHYOCOEEIIIYSQD8DAHSGEEEIIIR+AgTtCCCGEEEI+AAN3hBBCCCGEfAAG7gghhBBCCPkADNwRQgghhBDyAdJFf5MxxhgDAEJICz6pm1J6/gmglAKAIJzhcoXvzhk/ugjnvzaeJA3fl0tJTON91I6U+yYuYs2NNW0ZaJBObbWU0qY6Lgihi9a0leTZaDXYBdXtzUSrlLy5CnI/ibR4jv0t30otQl6INAiVzlODWEpVVVEUmy5Vf79FD7vMYsdz7M7572mDJS+zLEIIeS3PXEK4n9c8cI5rKr5VFTPGmjt296Fjh9D5uJjAXful5efny7Lcvn17vV7vgZ8fnOlHnpeXZ7Vaw8LCzufrOTk5er0+NjbWfT38dWVl5dGjR7t27XqOvTiffeTL1NfXFxYWdujQwWAwnHv5goKC+vp6Xq1QSiMjI4OCgk6cOFFfX9++ffuLyNL8/HxBENq1a6el9uTJkydOnOCbkCQpJibmb1P1t3vKF6CU5ubmSpIUFxd3Pt86t5qamqNHj/LV8tsOQUFBQUFBRUVFMTExJpPpoteMELoU/KddUlJSX18fHx/frHFhXl6eJEmxsbG5ubn+/v7nqNtlWdbpdM2UDO28cPz48aCgoIiICPBIlHn+eGIcDkd+fj6cbr0ODg4+z7Ohh/HU2u32goICACCE6HS6+Ph4XtU3d64qiiJJF9+/ACHvwi6QqqqMsYyMjIkTJ/I1DBo0KC0tTftIURSXy8Vfaxq8KcuyLMuqqrpcLkopY8zlcimK4r4V7R1VVVVVXbNmzQcffOB0OrWF+RpCQkLuv/9+vhil1OVyybLcIM18PYcOHRJFMSUlxWazUUr5dimldrtdUZT3338fAPj6ZVnW1tN465RSvgBfg4a/6XK5GGMrV64EgPT0dEqp0+nkO86T5/4tSunAgQPdD8dbb73FGLv99tsjIyP5bvKNumeRtpvuq1IUxeFwqKrao0eP4cOH8+X5LsyZM8d9E1dccUVmZialVFVVflz4qhrvqftRaFwGtm/fPmLECL7OyZMnZ2VlaZnAE+Z+fBsUAP6RtgDfxBdffNGgcE6fPn3Lli0AsGHDBsYY30G+CfeVnK2YIYSaBK9JZs2aFRsba7PZVFV1Op28IuI/Xv7Ta/DDP+On7O9qsO7du48YMYIx5u/vr9Xt7jUVpfTIkSMvv/zykSNH2Okq+ow1lSzL2pv8lKG9PuOZQsMT9tlnn8XGxgJASEjI448/brfb+dZ5FaStWauItJNag9faLmuvG5xBzpjOxrnEP9IW4F/Zvn27+3VUdHT0119/zU7X0o1zpvG+84Q1OEbsTNUp/7NBxcv/dE/n2Y4vY2zr1q3uNfykSZMqKip4rp77HMH+9+TivkyDrHMveHyZjz/+eNWqVTzlDY6dllpFUfjazrhmhLzKhTWcMMYIIXV1dePGjcvNzd2+ffuBAwcIIf379z927JggCPyelE6nEwSBnW7LZ4xpb/L+bZIkSZIkCIJOp+OX2jqdThRF/hXGGP+Iv0MIEQTh1VdfPXjwoF6vp5Tyj/gaJk6cmJKSoqVNp9Od7cJ68+bNlNK9e/empaURQngFQQgxGo2iKIqiyKs/xpgkSdp6GmxdVVVCCF+ANxXwr/Cd0ul0Op2O7y9v4SaE6PV6vmaePPemBUKILMtTpkw5dOjQoUOHMjIybr31VgDo16/fxIkTCSGiKOr1er6we4bw5LknQBRFg8EgCIJerzcaje47rqpqdHT0li1bDh06tGHDhi1btrz++uv8u/y48FU12FNFUbSj4N4rkSegtLR0xIgRNptt3759aWlpBw8eHD9+vM1m03IGALTjSyltUCr4R9oCPK+mTJmSmZm5c+dOQRBeeeWVrKysd955JygoaOLEiaGhoQDAd5BvQisk2knLvZixi+oAhhA6B71ebzKZ+E9Pr9fziojXD/yn1+CHf8ZP/7YGMxgM/JbgpEmTtLpdq6n411NTU+fPnx8VFQWne4Y0rqkAQJIkrY8EP2U0WNsZd5NX8r///vsdd9zxwAMPZGVl3X333a+//vqyZct4bcarIO2EpVVE2kmtwWs4XfnzqqnxGaRxOs+YS/wjbUc4QRBMJtNHH33ETyJJSUkPPfTQyZMnCSGN6/Az7jtPmHaM3I+I+1lbW9J9v7R6mKfzbMfXPbVGo/HDDz/MzMz88ssvf/vttzfffJMn9dznCO287J5C9zhByx+t4KmqCgDl5eVPPvkkL1qNj52WWh4A8Bs47mtuUKIQ8gYXFrjzPgyfffbZyZMnly1b1rdv327dui1fvvyNN97Qfjm//PLLk08+mZWVpf3ACCE///zz448/npaWxn/tX3755ffff79z584nn3yyuLhYVdXXXntt6dKl2l2z9PT0xx9//LfffuMB5YYNG7KysrZv3/7NN98QQl555ZUtW7a8++67W7ZsGTNmTEJCAt/00aNH58yZ89lnn7nH0/wjAPj8889vvvnm2NjYVatWwekbizU1Na+99tqSJUt0Oh3/iRJCli5d+u9//3vRokW8Bte2/tVXX4miWFFR8dZbb7322mu8cuR5QildsGDB888/X1RUxK8KVFXV6XR2u/3pp59et24dABw7duzJJ5/My8sDtwE6iqJERER07ty5c+fOnTp1CgkJAYDOnTsPGjRIkqTU1NTnnnuOV0DPPffcmjVreJrffPPNt99+2263awnYt2/fU089dejQIYPBwJfXqKpqMBgGDhzYuXPnIUOGTJkyZd++fTxb0tLSnnzyyY8//ri2trbBnkqStH//fn4UtDoaTp/V3nrrLX5Ye/To0a9fv8WLFxcUFPz22287dux455136uvrASAvL+8///lPaWmpIAiLFy/WSgUAHD58+LXXXtuxY8fLL79cVlbGVx4QENCxY8fk5GRKaWxsbFJSUmRkZEBAwOjRo4ODgwHg+eefP3DgwNdff/3OO+8QQg4dOvTss88eOnSI7yYhpHHZQwg1FcaYoih6vf7QoUPPP/98cXHxnDlzUlNTBUH44Ycf3nrrrdraWgA4cODAnDlzGn/KqwXe9HM+NdiQIUMSExPBrab66KOPXC5XWVnZokWLbDbbo48+6nQ6JUnSzhfuNRUAfPrpp7/++it/vXz58v/+97/wvzV8gzMFx6O6OXPmTJgw4ZFHHklKSnrxxRd37NgxYcIE/ul333332GOP/fHHH+612fbt2996660tW7bMnTs3LS3t9ddfT09Pnzt37v79+wGgrq7u/fff37x5M+9+434GaZzOefPm8VyaO3eulksAsGjRou++++7XX3+dP3+++0GhlHbr1o2fRO644w6bzXbkyBF+edAgZwghv/76a4N9f+ONN/bu3btkyZJXXnmlvLycb6vxWRsA3nnnnYMHD27YsOH555/nJzJCSEZGxpNPPvnWW2+dPHnyjMe3QfYyxuLi4jp27Hjrrbf27dt3/fr1jDGdTudee4PbOeKll16qqqrigcfzzz9/7Ngxrcy4xwkAsGzZsu+///7YsWNz5sxZsWIFP+8vWLBAUZR33303PT1dkqSvv/5aO3Y82KitrX3jjTe+/fbb/fv3z5kzR1EU9zU3KFEIeYULap/n99dGjhyZkpLCK/Hc3NzDhw+fPHmyqqqKMfb888/7+/tHRERERERs3ryZMeZ0Om+77TaLxRIdHW2xWD766CPG2BVXXAEAgwcP1uv1HTt2vOGGG2JiYgBg8eLFjLG1a9eGhIRERESEhIS8+OKLjLGPP/5Yp9MZjcbZs2fzX2xISEhMTMxXX30VFxd3zz33MMb27t0bGRkZFhYWFBQ0e/Zsdvp2J//3+PHjALBu3bq5c+cGBQXxW2BVVVUjR44UBKF3797t2rXjzfmvvPJKZGRkQkKC0Wi86667Gmy9oqIiLi4uJCQkODg4JiYmIyODd7aZPHmy1WqNiIjo1KlTRUXFhg0bBEEoLCy87rrrJEk6cOAApfTAgQNRUVFbtmzRcpIx1rt378mTJ6enp+/fvz8nJ8fhcDDG7r777vDwcErp8uXLAeCll156/fXXAWD9+vV1dXXDhw8PDAwMDQ0dM2ZMdXU1pfSvv/6yWCwBAQGDBw82Go1Tp05lbl1lnn322bZt227atOngwYNr164FgH/961+MsQULFhBCIiIidDrdVVddRSn95JNPdDqdwWC48847d+/eHRgYyI/Cyy+/zE7fe+XrHDRoUL9+/djpm6culyshIeG6667LzMwEgOXLl1NKb7/99qCgoPr6+hdeeEErFbzTy9KlSwEgMTExLi6uuLiYHyZ+tVNZWQkAn332Ge/7tHHjRgDYsmULv9SJjIzs0aMHAIwdO3b8+PEmk6lNmzYnT55kjD333HPuZY+v8IKKN0LojPiv/q677oqLi2OMff/99wDQt2/fNm3aiKI4bdq0vn37AsANN9zAGPv666/P+OnMmTMZYxUVFaNGjTp3DXbttdcyxgICAu677z7mVlNJknT99ddnZmZGR0eLohgTE+N0Ojdu3KidL7Saitfw9957r9Fo5LsQHBx8++23M8bmzJmj1fD33nsvO32O4Phrfo3xwQcfuHef4Gu+/vrrLRZLmzZtdDrdu+++yxhbsmQJAMTFxSUnJ3/00UcAEB8f36FDh6ysrPDw8GnTplFKeefJ7du3l5SUJCQkaGeQ9PR0xtjdd9+tpTMoKOiee+5xOBwjR44MCAjgucRPr9OmTQOAdu3aXXfdddpB2bFjh8lk+uCDDw4ePHjgwIH+/fu3b9++urqaMbZ+/XotZ1544YUz7rvT6bRYLCEhISkpKZIkDR48+MSJE6qq3nrrrdpZ+7///S/fXERERHx8/NChQwEgJSXF4XBs3749LCysc+fOISEhnTp1Kisrs9lsI0eO1I5vXV0dz1V+RNLS0gwGw19//cV3NiEhYdSoUYyxp59++ozniISEhPbt2+fn51977bX8DNulS5f8/HxK6bp167S9mzNnDmPsjjvu0Ol048ePDwoKEgRh7dq1jLFrrrlGEITAwMDU1NS77rrLz8+PH7sPPviAMVZVVTVmzBhBELp3785bzRRFOWOJasqfE0KX5sICd/7bGzx4cP/+/XkF16tXL34BMHfuXIfDAQDffPMNY2zixIljxoxhjP322288kmOM3X///byTw7Rp04KDgysqKtavXw8Ar776KmMsNDT0wQcfZIwNGjRo0KBB/Lt6vb6mpoYxNmLECN7f0el0tmnThq+cMdatW7cnnniCbzEqKooxxmPTAwcOMLca/D//+U/nzp0ZY3v27DEYDDx65qcf3kF/+PDhvKGld+/e3bp1y8vL27Zt288//8y3MmLECF7NTZ8+PTQ0tLa2lifjqquuYoz99NNPALB7927GmMlkevvtt3fs2KHT6SZOnCgIwvbt29lZfvmU0mHDhmkXUR06dKisrGSMPfroo7xaZIw9+OCD/KL/8ccfZ4x99tln2uWWn58f7844atSoyMhISunhw4etVmuDwP2VV15xv1S78847CwsLKaWff/75woULtXXyzY0YMYKfLAcNGjR48GB+FAwGAz8KPLZmjPXr12/IkCG8syZPTPfu3UeOHMkYi4mJee655/g7//jHPxRFcS8Vo0ePZoylpqZKkvTxxx+75wwvUdXV1QCwYMEC/mZaWlpAQMDOnTsZY3q9fsqUKYyxmTNnAkBeXt6ePXsAYNu2bTabzX0rV155pVZcEUKXqEHg/uuvv+p0uh9++IExZjAYkpOTGWP33ntvdHT0OT6NiYlhjH355ZfnrsEsFsu0adMYYx07dnzqqacYYwsWLHCvqRhjH330UceOHXlI7X6+0GoqnuCtW7eaTKZDhw7l5+cbDAYeEXbv3r1xDa/htdDJkycFQeABq6IoWrOCoijPPvtsQUEBYywlJYVvd/ny5ZIkvf/++4yxFStWaDUbY+y2227r0aMHY+ytt95q06YNY2zmzJnuZ5AJEyYwxjZt2mQ0Gnk6+Q2Nn3/+uXEu3X777YGBgTk5Oczt1LZz506z2axV78OHD1+zZg3/4hVXXMFT+Ouvv0qS5HQ6+/Tpo+07byaTZTkuLq5Pnz6MsYyMDABYsmQJH1mknbWNRmN9fT1v1+dHMzU1FQD27dvHByZt3Ljx2LFjCxYsqK+v55dtWsr5gdM68aelpRmNxkmTJj3yyCNXXXUVAPz222/8Rs0ZzxE8V3lu8DOsn58fLxUDBgzQjjvvpvvss89ardbdu3erqhoaGnrHHXcwxrKzs8PCwvihf+qppxocu4ULF/IzCGNs5MiRZrOZMTZ06NDGJarBkDaEWtAF93EHAJPJxBskFEX55ZdfNmzYwFtWioqKRFF84IEHwsLCfv/999zcXADIzc0VRXHMmDGKokydOlVRlJMnTzocjpiYmKCgIN4nfty4cZTShIQEfodUluU9e/aEhYXNmDHD5XJlZGQwxmRZ5kOX+J04ftHPTlfQAFBcXNytWzc+3LO6urpjx47gNvnuunXrMjIy2rZtO2rUKKfT+dVXXwHA0aNHBUFISUlRVXX69Ol861dfffXBgwfj4+PvvPNO3r+cnR71oqpqenr6gAEDLBaLXq8fN25cTk4OAJSWloqimJycrKpqSUnJPffcU1tbK8vy77//bjAYYmNjtWlSeOWl5Sffl2uuuSYrKyszM3PNmjW8CuZL8j55L7zwgslkslqtzz77LKW0uLhYEIS2bdtGRkbW19enp6cDwMmTJ5OTkwEgMTGxY8eOdXV17kfNbre3adNm37598+fP1+v111xzDU/SrFmzUlJSnnnmmf/85z9Go5HnJN9NPohn9+7d/Cg4nU5ep2tlQBRFh8PBd4oP7rHZbLz/680337xw4cLdu3dnZWXdf//9hw4dkiSpQanghYeH/n9b5LRD7HK5Ro8eTSk1mUydOnWKi4vT6/VBQUF2uz0vL69B2ZNlWevIiBBqQrw+5BfqoaGhEydOZIzFxMTw0TW89mj8qclkUlX1yJEj51mDabXl7bffrtVUvBcyPxfU1tbyFnHtfKHVVLyrdN++fdu3b//dd98tXLiwffv2vOF/8uTJDWp4fnPPfQdNJhOfV4CPm4TTPelFUXzxxRezsrJuv/32Q4cOBQUF8XRqtRmPp/lrxtjs2bPz8/OzsrL+/PPPGTNmMMb27dvnfgbJy8tjjPFmcp7O2NjYjh07HjhwwD2XtP420dHRHTp04CcUnlReA//3v//dvXt3aGhoQkLCyJEjeeK1nLnxxhsVRcnLy5syZYq273wgAe97OX36dEppYmKiv79/QUHBwYMH3c/aDocjJyeHEFJdXc0npYiLi+N/pqSkWCyWIUOG9OrV6+jRo6IoFhQUiKLYIOUNpiH666+/vvnmm5KSkq+//vrqq69OT0/X6XRnPEcMHTqUj0V2P8M+/fTT/NBox51SWlRUZLfbo6KievToIQhCbGwsbwPibTr8Ri4fOsWPHe9+ycfm9erVi8cANputvr7ePQLRShSeSpD3uLAJknhlcfXVVz/yyCOHDh3q2rVru3btAgICHA6Hy+XifRMnT57coUMHnU7HJ6Xib6qqqtfr7XY7Y4yHd3B6CIg2nolfSQCAy+Xq1KnTlClTCCEGg6FNmza8P7per9cGi/Dua8yth6IgCLIs86EzixYt6tevX48ePfgkUIcPH96/f//dd98dHBwsCEJaWhpvceeX13xwZE1NDd/0888/379//xUrVnz//fdXX331sWPHIiMj4fT4IVEUXS4Xz42amhqeDJ4qPvBl48aNhBCr1QoAt91226ZNmx577LGvvvqKX6I0Hg7F2waSkpL4n7x9muPDcLdt28Yvk1auXMnbm41G43333QcARqOR3/Hg+85z0uFwNKgl+VcSEhJ69OixZMmSG2+88cCBA9HR0Q8//PB77733+OOPd+vWrbCwkGeytqdOp1M7CkajsU2bNrwA8PwfPHjwxx9/XFRUxGdd2L9/f35+/pNPPkkIGTt27CeffPL0009HRUV16tRp3759iqI0KBUcHw90QRUiv57h3Te1AsPLiXvZ441b579ahNCF4r2B+WteM7j/6M74Ka9kDAbD+dRgPCQFAPeaSptMUBRFq9VKCJFl+Yw1laqqkiSNGjVq6dKllNLhw4cbjUZVVV966aUrrrgiNTW1QQ2vJZWfGrp06bJmzZoHHnhAEISTJ0/OnDnzjjvuuPbaa5OTkwVBuPHGGyMiIrRzAQDw0ahauwbfhQEDBkiS9MUXX+zYseOBBx4ghAiCoH2rtrZWkiR+4hg9ejRP54gRI3j7sVbPm0wmflXD95qfNxs0AMXExKSkpLzzzjs333zzFVdcceutt/Isdc8Zk8n01FNPpaSkrFy5ku97SUkJP72eOHGCJ9jlcplMJrPZ7H7WBgB+RtM6rPPbpLW1tUOGDNm5c+dPP/20YsWK5557LikpKTAwUKfTaSnv3bu3+xf5Yf3ll19Gjhyp/cmbjc54juAndJ5L2hnW4XBMmjTJPU7Q6XR+fn58hCs/L2jXNvxfq9VKKe3Ro4coivzYOZ1OcAs8RFHkgb4kSWcrURfzI0GoGVxYizsv5bNnz46Ojp42bVpaWtqePXuuu+66qqqqqKgo3uISHx//8MMPZ2Rk8OvmPn36AMCzzz6bmZn54osvJiQkWCwWLfzi69Re8Go6Pj6+rq7u4YcfTkhIWLlyZdu2bQHAaDTm5+cXFhby+kWLgLUgdfTo0WvXrt2yZcunn3565513ahMIAMDWrVtLSkrmzZv36quvvvzyy2+//XZ6evru3bt5V5B33313586d77zzjtlsppTec889a9asefjhh2+//XY4/XM1GAx5eXlFRUXXXnvtypUr//zzzzVr1ixZsmTSpEkAwHv8v/322wcPHrz66qvz8vL8/Pz4DC0vvfTSDz/8wG872Gy2zMxM3gDA3AbOarditVYfvlFRFGVZ/uc//zl8+PChQ4c+/PDDqqoOGDDAZrNdc801d9xxx+LFi3n70+DBg9esWbNp06bPPvvs4MGDgYGB7keNny3q6uoopa+//np1dTUfWrp48eLBgwc/8MAD/v7+2jS3RqMxOzu7uLi4c+fO9fX1/CisWLGCHwXtzPHoo48CwNSpU/msMtdff31sbOyNN95IKb3iiitSUlJSU1P/8Y9/MMZ4f8oGpYIXgLPN6qAViQaHmFfiWv6451J8fHyDrWhTAF1QCUcInQ2vSbQXWr3t/uY5PuX/pqSk2O32c9Rg6enpvAbTvrt48eJBgwbxmorfFzUajRUVFevWrSOEJCQknK2mAoAHHnggPT09IyOD97QEgLvuumv16tVaDS8IwokTJ3Jzc7U6mcd8L7/88q+//vr+++9nZGQ88sgjq1atatu27dGjRw8ePHj33XfPnDmzvr6enJ5HhTfGa/vOazZ+5XDHHXe88847SUlJgwcPBoDJkydrZ5Bffvnl6quvbpDOf/zjHwDQp08frZ7/6aefeOs4jy8bD/fkFwOU0unTpycnJ7/00ku1tbU6na59+/Y8Zzp06JCamhoZGXnPPfesXbvWfd8ZY1ar9aOPPtqwYcOCBQscDkf37t379esHbmftzp07t2/fnm/d/RBbrdbly5ffd999N99886uvvsrfT05OdjgcWsr5TRj3GxrayYjPwAgASUlJ5z5H9O7dWzvDTpgwYc+ePZIktWvXTjvuK1euDAsL05oCtaIIAHzaiX379qWnp6enp2vHji/Ae/689957aWlpb7/9tslkMhgM7hGIe4lqqt8RQpfqArvWnOqRnJ2dPXXqVF6U+/Tp8+mnn/IGlRUrVkRHRwNAcnLynj17+JvffPMNb9IYMmTIwYMHGWODBg3iPc7XrFkDALwHc8+ePfmg0uLi4lGjRgFAQEDAZ599xlfy+eefAwAflAMA2pCRdu3aPfLII4yx6urq6dOnA4DJZJo3bx6/5uaGDh3au3dvWZb53UPegM370/NBn7GxsTwEV1X1559/jo+PB4CwsDA+fkXbOh8ydeedd/Ksu+eee7Q52j/88EP+hKAZM2bY7Xa+X3zgUVRU1KxZsxhjO3fuBIDVq1czt8GpnTt3vvHGG9npLnT8/QcffDA+Pp6dnoK9sLCQD/rk3dyffvppnoDbb7+9oqJCVdXy8nLeX3DChAlRUVG8j6DWx/2xxx6LiIjgIzgZYzfddBNf5xdffGEwGAgh48aNMxgMfCL2BQsWAMD06dPLy8t5o4h2FKjbNL2MsbS0NK3VZOLEibxHE+91+uyzzwqCsHXrVr68e6nYtWsXY2zZsmUAwLfYYLVVVVUAwHuXMsa2bNlCCOHjEADg7bffZozdeuutHTp0YIzt37/fZDItW7aMMbZ8+fIGZQ97JSLUJHhNctttt/F7WYsWLQKAY8eOMcaCg4N5vfT888/zUUZ8zE/jT3nvBVVVn3nmmXPXYHwIU9u2bR966CHG2CeffGI0GnlNpdPpCgoK8vPzg4KCRFGsq6s7duxYg/MF/d+pvrt06RIfH8/bR3jitRr+nXfeYYzdd999MTExvO5yn9Lg448/5q2tcXFxX331FWPMZrPNmDEDAJKSknr16sUH6PNxXPzUxl/zmo3XwLw7+C233MJOz1V/7733up9B6OnJ793TKcvyc889p+VSeXk5Y+yaa67h502+j1qvcQBYsmQJ318+UvbNN99kjBUVFWk5M3/+fErpjz/+qO077z4uy3JUVNRVV13Vs2dPAJgzZw4/1u5nbV63q6oaHh7+2GOPMcZ4B6dVq1YVFhZqT/O45ZZbTpw4wRhzP76VlZXuqeXzuPPUajPNs7OfIzIzM/l+aWfYW265pbKyUlVV9zhh3rx5lNI777wzISGBb4g3mTPG6urqrrvuOgD44Ycf7rnnHgBITEzs1avXoEGDeM6/++67/M0pU6YYDAZZls9dohBqcRccuDO3SKuoqEibCEVTWVmZkZGhjcTnC5eXl2dlZWnRalFRUX5+PmOsvr4+IyODd6EpKCgoLS3lC6iqmpmZqcWafD2ZmZllZWWMMe0FYyw3N5dXFlxOTs7Ro0fZ/w4lycjIOH78uHsis7Oz+QBNxlheXl55ebksy4cOHeLv1NbWZmZmlpSUNNj6yZMn+QIFBQV8jAs7XYcyxo4dO5adnc3frK2tzcjIcDgclNLS0tLDhw8zxhwOR1ZWls1mc09eXl4eP8O5Z9fx48d538f8/Hz+XcZYVlZWTk4OX6CwsJAvoH1FVdWsrCy+OZ42LWEnTpzIycnRHt5ks9kyMjL4tAP5+fn8ISbZ2dna8H8t5xVFaXAUGqRTVdXc3Fx+KN13qq6uLjs7231saINSUVdXl5GRoT1byp2qqhkZGXwWBcYYv03BS0hGRkZFRQVjrKSkhLeQORyOw4cP85Q33gpCqEnwn3ZJSQkfGVlTU5ORkcHr8+zsbF4Dl5WVnfvT3NxcrU44nxosJydHq9sLCgoa1FRHjhwpLCzUgr+z1VSMsdLSUvfKnDWq4Y8fP84nKmm8y/zMxecM0BbIzMysq6urq6vj++tem/GaX3uQH2Ns3759Op2Od4PRdt/9DHKOdLrnEmPs6NGj7n9ydrs9MzOztrZWS2FmZibPqzPmTIN9V1U1LCzsvffeq6+v1841ZzxrM7cjwnt+81GbjLHc3NwGR7NByjW8PuepbeAc54jGZ1itzLjvXUlJibbRvLw8HgkwxmpqajIzM/maGxy7ioqKjIwMfmXy4YcfhoSEnE+JQqhlXeR01/xmonbzSOtowUfwaMvw17x7d4M3z4G5PQD5fJa/lG81XvJvU6u96Z4J7kuypn6AMzvdk7tBArT3L26L586lv81P94w699rOWCqanGe2ghC6RFrdcp41WONP3d+50Jr//M9H7ks2qO7+Ft+1+fPnf/7557yhinca4efdxmeQM66hQS6d53bPkTON951SarVa//3vf7/44ovuXznPXGpwaPifjc9Qf5vsv629G59hL+6M38D69etHjBgxYsSIAQMGzJ8//4Ybbvjwww8vNGJByMMuskRq9Q6/8HXvcc5OXw1rxZ33inZ/k38R3IYf8Tfd6/EGK3FfQHtxxm81/qW5L9/gHV5z8cqUnh72esb1NPgK/1SrOLQ3tTrFfb8a7+M50uaeLez0IBv3sV/atsCt56iWY+6ba7C2Bn+6p9l9gQZ70eAoaNwzqsEyDVbYuFQ0WKCBBnnSOPfOWGzOWPYQQk2lQb3E32z8qzz3p3B6rOrf1mDudXuDmooQoKpKVRUYIwD8MRCMqgIhwFiD/9j/VomNa/izVUfuZy4tktPeOeP+un9KCFm3bl11dfWSJUsMRqNKKd8bIESlVKUUCAEgWkpPvXla41w6WzrdK0z3M0XjOvyMZ7fevXvzmTrdxxM3PmvDmc687qddLZJufIY6W2o1f3uOaHCGPePenbHgQaOSqR07xtjQoUMXL15cW1v7+eefz549+7XXXjtjYhDyKviASYQQQgghhHzAhU0HiRBCCLUYxoAQOHIYDm6C82kNZQySh0Gb+FNf9CxVpYRAVoVtx4kaiZC/bSRjAMOjg6KtRgbgsbTSc/bYuezR/73L0WrzAfkQDNwRQgj5CgZA4GQRbP0NRAng74JhSiEqEdrEn/qiZxGBCIQU1jp+zy3TC+cVuHcJ9ou2Gj2Z2FbeG6SV7z7yRRi4I4QQ8imCBHrj+QbuZ4rMtG7oHmhhlQgxSsJ5Bu5Co/Rc0ODUM373or+OEPJCGLgjhBDyLadHdP5t4H6mQVzuITtt/mlDGJweKHseSzZ2KTE3xusIXX7wJhFCCKHWgkftLpdrw4YNR48e5VOIaB+dz7/uMzpof7r/24RJBYDKyko+kbxG227jd9w/AoDa2tq6urqqqqoGU6e7r7/Jk40QalbY4o4QQqhV4BHqiRMnvvvuu9ra2lWrVt14442dO3fmn2rzDP7tvxrtzzN+eolUVZUk6YcffmCM3XfffWfc7tlSwm3evFmW5eTkZEmSrFar+/uCIAwcOPBsa0MIeS0M3BFCCLUKlFJRFFevXh0aGvrQQw/l5+cvXrw4Jibm/fffP3DgwKxZs/r37//oo49ee+21fn5+n376aUpKyv3337927VoA6Nev37PPPhsUFHTnnXfu2LFjypQpq1atYoxVVFSsWLHi3//+d3R09BNPPDFhwoQJEyY0Ye95URT1en1GRsa8efOCgoK6du26fPnyF154obS0dOHChQEBAdo7AQEBc+bMMZvNjz/+eFVV1dtvv11RUTF9+vTq6mp/f//i4uLXXnuNMfbss8/OmzdPkqROnTq9/PLLfn5+Dz30UGBgIGAEj5AvwHncEUII+QhGgQiwbx0sm3e+g1OnPAhdBp36IgAAfP/99/3794+JidHpdABQVlZ29OjR0NDQ995776677vryyy/nzJnz4Ycf9uzZ8+DBgzExMS6Xq0OHDhkZGcnJySdPniwtLQ0LCwsLC3O5XLt27bJYLOPHj//4448nTZq0ZMmSRx55RK/X6/V6AKCMCYSsKij/+lDJeQ5O/Wev2J7hVj53JX8k+bx58wICAkRRDAoKKigocDqdnTt35n1gIiMj8/LynE5n165dT5w4IYpi+/btKysrT5w4IQhC3759//rrL51OFx8fb7FYzGZzYGDgypUrrVZrYGCgw+Goq6tr165dZWXlsWPHbr31Vg9090cIXTpscUcIIdQqaB3ca2pqdDodY+zYsWOhoaGrVq1KS0uLiYkxm829e/eWJCkhISEhISE0NPTNN98MCAi45pprDhw40K1bt/Lycr6e7OzswMDANm3afPPNN3/88UenTp0AoG/fvhaLpWmbw0RRdLlcXbt2jYyMrK2tNRgMbdu2LSwsDA4OTkxMrK6uNhgMkZGR1dXVWVlZP//8syAII0aMMJlMCQkJ5eXlTqeTUqrT6Uwm08svv5yZmfnEE09QSh0OR2Fh4eLFiwkhkyZNAmxuR8hHYOCOEEKoVeBdZYKDg//8888ePXps2LBh165dycnJ7dq1u/HGG1999VVZlh0OBwDIsnzixIlevXplZWUNHz5cp9PZbLZDhw6VlpYePXp06tSp3377rSzLKSkpEyZMmDlz5pYtW4xGY319PZy+PGiqNMuyLAiCLMuyLLtcLsaY0+mUT+PvOBwOQkhiYuKYMWOCgoJsNtuuXbuysrIyMjL4+zabbd26dU888cSKFSvKy8v9/f0VRUlKSho2bFhISEhlZWVTpRYh1NzwvhhCCKFWQRRFxtj48eMTEhJuuummtLS0f/zjH717916/fv2XX345dOhQVVXDwsIAIDg42Gg0AsDAgQOvu+46AJgyZcr8+fNXrlx55ZVX+vn51dTU9O7dOykpyW63z549W1EUq9UaHBzchKnl0X94eHhYWJjFYjEYDCEhIcHBwX5+foGBgf7+/to7ZrM5ODh49OjR33zzzdy5cwMDA8ePHz9//vzt27d36tRJr9eHhob279//mWeeqaqqio+Pj4iI2Lp1a9++fb///vs333yTd3BHCPkE7OOOEELIRzRFH/fzp6rqG2+8cc899wQFBf1PKs6vTf0S+7gjhFBj2FUGIYSQryHkvGLbsyzDI+/G7Vb8TUIIH6m5ePHixMTEgIAASql7pK59V1ve/d8zpALgouNw96efum/0jC/O5nwWuNgEIoQ8CgN3hBBCPoUxUBX+6m+WpPSMD089x7Tr/E0+v8r06dPPtuIzzuB+xhUyBgpjwvk9ObXxMg0uGP72xd8mGCHk0zBwRwgh5FMkHZit59dVhoGku5RNXfpIU51IrHpJT86rq4yE4TVC6JywjztCCCGfYq+D2vLz637CwD8UjH7NnqSzq5PVCrt8ngF5qElnksRmThFCyIdh4I4QQgghhJAPwK4yCCGEfAsDxs53wCeBSxga2gQY/H2PHg32lEEInRu2uCOEEEIIIeQD8AFMCCGEEEII+QAM3BFCCCGEEPIBGLgjhBBCCCHkAzBwRwghhBBCyAdg4N70HA4HpbSlU3GKqqqqqrZ0Kk5RVdXlcrV0Kk7xqpyhlDocjpZOxf9TFMV7hq3LsizLckun4hTGmKIoLZ2KU7wqZ7yQV+WPV5Ucr6qKvSpnAM/gZ+dV5ylKaavNGZwOsul5z2/e2zDGvCcc9DZeVWy86jB5VWLAm9LjPSnxTt6WP96THm+rir0qMV5VFXsbr8qcVltssMUdIYQQQgghH4CBO0IIIYQQQj4AA3eEEEIIIYR8AAbuCCGEEEII+QAM3BFCCCGEEPIBGLgjhBBCCCHkAzBwRwghhBBCyAdg4I4QQgghhJAPwMAdIYQQQgghH4BPTm0ejIGXPNOLJ8N7EuPlOUNO/Y8QugwwAO+obk6lBBPTmFclBrwsPczt3xbn4Zwh5w4VvDCc8BQM3JsBISCKLZ2I00QJwGtiUVECIEC8IzVelTMIoaZGAETiJdUNEEIkr0mMRAjxmsR4Vc4AgESI6DXJkbwmJQAgevhInXtToghE8JpwQgTiuQ4sGLg3A0WGOgUE0Suuk1UKACB6R58oRQWqgl7f0ukAgMY5QwAYSBLoDS2XJoRQk1EZ1MmKzjt6hDLGFEXRMa+IMxRFUVXVQLyigcmrcgYA7C7VICiC4BXFRlVVABC9oymQUup0qSZJ9cC2BMbMquNcQRSlQClI3hHEUkpUBiajZ7bmHft82aAUBEHMOSyvX0V0Oq+4icMYAKjecVXKGGOMubyjQmyYM4SA0yn0SJHGXNWSqUIIXTLKmEDISYfy6f6jirc0ygFjzEtalhljDEDwjsSAN+UMAKiUCgIh3nE3lscQXpEUAAaMUiY2/xlcBRJKXA9lfiWqrrO1ZAvACPu7VnnPIERwOXQpY2DQJKAqCM1+lYWBezOw17OSY+Algbu3YYx5wy+tMULA6WDt4lo6HQihpiEzOFrndDEQvOLuJ/INXnUV4W08kDkEQAHiEmR2shgUxzm6oBB+n7zFEQEcNlJf7bENYuDeDIgAOh0G7mfGmFdcIjdGCFDViwYnIIQuDQHQiYRh4I4uBGOAgfvZeCBzCAABohMISDoA6sm+4xeJCKBTPNDQrsHAvXl41Xhnr+LNeYKHDKHLy6maGAN3dN7wJHAOnskcxjd06ozs/cfD0+n0+ksZhFqIqqqyLDPGAIAxJssyHyd0tmUURaGUAgCllL9ACCF06RilVFXcYyNGVf4no5RRVVusZdKHvBU9fanBAGSVan8qlPHXlDHqa9dqrShwZ+c8Ntqn514MtRKMMVEUdTodvy1ICNHpdKIouhePBstIksQnIhAEwUtmJEDIC2FVjC4IY1RntpiDwwkR4XRLit7iTwSRMar3sxqsAYwxIERn9sMGc+RO0EkAAAyIQHQBZsGgY4wBAcliEHQSUCZIoqCTfKBZ301rCS/4iAqtHbRxg6j2KXZuQ7y0/PHHHy+//LLNZgMAm832yiuv/P7774QQrQ2eELJ69eonnniirKzM5XLNnTv34MGDALBnz55NmzbBmYoZQq2cVhXz39EZq+IGL1BrxhjVGc1FW9ekzXtNttcJOh1VVclozF2zzFlbrTP55f31Z9bynyWDUXU5juzYJOh0eMmHGJyacObg0XJZpSCJlfXOOUt2bDpcQkx6h6x+vDZ9X3EZ+BmyT1RnHKsAnehD7e6tpY87IaS4uDgmJoafNtwbRPkchWlpaVu2bImLixs3bpzZbMZzRqulMiYSsnTJklm3367X64uKiubNm/ePf/zjjz/+UBTlu+++Gz9+vCzLOp1u8+bN06dPVxQlIyNj/Pjx6enp+fn5H3zwwdKlSwcOHAjYZIjQ/+LVb1FRUWxsLH+nQVVMCCksLExNTQWAiRMnRkVF4RQfrRmjVG+xFqf9dTx9d1C7xKzli7tcc5PO5FdVkLP5veeu/Ty1/mTJiYy9ej//2tKjir3eXnGCCCKAy2tmUEQtgzFGDLr5mzIOHa95e3KfOrvrtfXpwzu2XXroiNWor3G4jtXY046Ud44OST9eHRNg9tI5M87i8m9x58HTli1bPv7447S0NEVRnE7n7t274XTITggpLy8/cODAv//97zZt2mzfvl1rVUWtEP/5Wq3WlStX/v7772vXrj1+/PiuXbtOnDjx6KOPfvjhh3C6mfCXX3655ZZbqqqqCgoKtm/ffu211zLGsrKyysrKrrzySvCap2Yg5A14pVpWVvbJJ5/8/vvvJ06cAIDdu3fzm1q8NgaAFStWzJw589Zbb129ejXWw60dY5LRdCJjrzUypt+dD1UV5TqqKqmqHNuzLSA6HoA5a2siuvaO6TfUUVV+4tCe2EEjCfGWKdhRS6GMCZKYUVzukGnXcH8BoKiqLsJiuqpfwq294ggBh6LelNK+U6h/zrHKSrurd8co6pK957EGf+vyD9x5a014eHhCQoLVaj18+LDT6SwsLAS3GUnNZrOfn9/OnTsDAgJ4WylqtQRCGGOjRo9OSkoaMGDA448/HhYW5nQ6U1NTMzMz6+vrAUCn0wHAww8//Morr+zevTs4ODglJeX7778PDg5eu3btuHHj9u/fb7fbW3pXEPIivEHEYrG0b98+KioqOztbVdXCwkI+5psQwmvjqKioHTt2ZGdnX3XVVdqbqJUiRLbXRyb3rzlSsPXDVwOi4wKi2xdvW29tGx0c39FlqzcFBpfu31Gyf4e9qtwcEl5/vKS+rFTQ6bGne2smEMJUGhNsmZHcDgCAsRP1Tpus/Ovz9ZsLy3p0iADKvtydf6zGnl9ZnxwZuCe31Lfqmcs/cOfCw8PDw8M7deqUn59fUlLCo3N+l5Yx5ufnN2PGjOrq6jVr1hw4cKClE4u8gqqqt95667JlyxhjTzzxxPjx41NTUwMCAuD0BDJRUVGEkFtuueX666+/9957U1JSJk+efOLEidra2ieffJK3zTeeiAah1sxoNIaEhPTo0aO+vj47O7tz585Wq5W3rPNz54QJE8LCwtLS0tatW+dyubSWeNQaEWCUSQaDvaq8Iv8wIYKt/PjJzL3RfYa4bHVMVfxC27Tp3tsS1oYIAqU0768/D/36nWK3EQ9Oqo28EWMWk84mK5QBiMLJeueB49Xv3jCozOb8YXPWmO6xMYHmhFCLU6WltY5Ptx1etL8I9JJKfaOqaS2Bu8vlkmVZEITo6OhDhw4FBAQwxvi0fYyxgoKCtLS0UaNGzZo16/jx45RS37r8Qk2LEFJQUODv7//5559nZWXl5OSMHTu2pqbm0UcfdTqdAKDX6wkhLpfrtttumzx58r333ksIeeSRR4qKimJiYsrLy2+66aadO3eqqtpgIhqEkCzLANCxY8e8vDxeCauqyl/YbLZVq1Z169btjjvuMBgMdXV1WBW3ZoQIQOmxPVs7TZg+7rXP6stKi7aurSrO2/DG48cP7jq8Yokqu+KHT4juO7T+xDFBFDtedb3OaLZXniRSaxm/h86KMoEQQQCgLNJiHBYXDhZDl3D/CruLEfjHuJ4qBb1AJEKeHdnt0Ilq8NanujfWWgJ3s9mclZVVUVHBTxImk4kPUeXatm1bXFz8+eefL1q0qEuXLoIg4HwgrZbKGAB8//33ffv2nTlzpizLMTExt9xyy4MPPjh//vxJkybZ7fbXXntNluXFixcvWrTI4XA89thjNputrq5u/fr148ePZ4zl5+cbDAb3iYwQQpzD4di6dWtUVFRBQUFcXJwgCHwqVUEQzGazXq//6quvFixYEBgYGBwcjINTWzVKiSSKemNVUV51cYGzrqZNcv/Rz380as6HYUndO46/ljGmOB2Fm1eFd+0lGUy1pcWKy0FECbvKIABgDGSVAmUdQiw7j1TUlddlldVGWIxEEKpKKjNO1PSPC7crak55nSgIQIivlJrWclVqNptnzZplNpu7dOnSsWNHAMjLyysvL9fr9S6Xq2PHjtddd11mZmZwcHBERAT871wHqFURCAHGHnnkkaNHj65du3bhwoUWi+Xtt9+++eabp0yZct9995WVla1bt+7ee+8tLi5OTk5etGiRTqd7+umnKysrw8PDo6OjR40aNWfOnNmzZ/MrQAw7EOJ4vTpt2jSn0ylJ0o033mg0Gvft28fvfIqi2L1792HDhsXFxTmdzsTERMBJIVs5QqhLjh8+IeO379a99u+O46ZawiJle50gSda2sbxZnVGVUmYJjwxo227HgreC2ydZItpS2eVb84SgpsdALwltrCZFVSODLLN6x9357caRCRGTuseCw+VQqL9BCguxxFfVv7c568HBHXkLfUsn+ry03ulT/vrrr+zsbLPZbLPZxo4dq01PdkkNPJSCIDi3bmTLfiE6HV70N+a97WeEgNMh9Bukm3pDg08uKM0Xt4OUUofDYTabL/SLzUSWZUmSvORIuVwuANDr9S2dEAAAxpiiKHx0covzqpy5OLIs//TTT7zzjF6vv+6660RRvPSCRxkTCMmvsv0nLd/FQPCFx6ajM2NMkCQiiFRVBVFUZRd/UzQYqeziAYyo06myDIQIogQEqKJcysnXe09SXsADmUMAFCARgvzq3rclxQnkElpRCYAggEoBACQBKAABoBQYACEgEKaoRBROXeOpF3t7nAjgtKlXTBNHzQSqQvOPr2gtLe7QqMANGzZs2LBhDRYAbOBBAHB6cjpt1n8+IkJ7AgClVHuTL89nftTe51/EsoRQY1pNyxjT6XQ33njj2RZogcQhb0MIVRQABQgoqnKqVBCiOB1aCVFdLiAEGKM8rMeSgzgGTKG8ODCZAgFgp0sHY0xhhBBGGTDteU2+oRUF7g1OA3wsFH/N23jwPIE0DcoDIcR9UnYevjd40/19LEsInU2DZ6MqiqL9yX9Q+PNB/+P/C4z7e6TxAr4UfCGPaFg0GpUa8r9v+oRWFLg3wMdCNdfaCcEa5Ky8M2f4IfPOtCF0+ZKacwIQwn/ZzbeBC8K8JkTgHUm8JDHgTTkDbo2y3sD7jlRzZw45/Z/PnJRPJdJz6Wy9gXszYhRkGQCwj/sZMK+qFN0QArIMqtLS6UAINQ0GIFPmPX3ciXckg8PEnBVj3pQaL9P8mUMAFABZYKC4QHadtY/7qR4vzZuY80IEkF1APffMFgzcm4HeSELDiOQNM1IR/iMjXlExEgYMKCWC6C2Jcc8ZQsDlJBZrC6cLIdREJAJhJp1CCPGWSMwrGpYJ4acmr0jMad6SGEKAUkouZUBk0zl9pP7/RYtjjI/jasZNEAAVSKhAIKgNKL4wOxARwGlnJovnNthqZ5VpPraaGiMhRBRa/FxByKknd4qi2OLHmRBQZEVVVYPR4A2JOUPOMEb0OtAbPJ8enFXmHLxq7hScVcaHOJzOepnqDXpviHoYY4qi6nRe0FhGiCIrlKpeUnK8KGcAgBC7zWYwGr1iZkBCtPOUN5RhypjT4TCZzc2fGCIA9VMc52jj48/PlCRveEQuoarqZGDyD/TM9rzjp3KZ0enAZPKCHz0AgHbB7hXpoRRUFXQ6r0iMV+UMQqipCYQEGCRJ5w2ndgAAVSSidzzRkwqgqkSn94rEgDflDADo9KJRL3lJQy8TCQAQL3mwDGMOKho99IMSQf937SOUgpfkDACz2z22LW/5qVxWGANV9ZbypKoAAKJ3nLpUFVQVvKSCPmPOeEdljRBqEipj3lH3AWNMZcw7zgqgMqYy5h0VsXflDACoDFTmLc/i4U/y9pIyTBlTPdjr7G8eZEopUOotp2xKPXlLxEt+uZcd7xkKfXrW25ZOBwB42SBxr8oZhFAz8OhcD3/HexJDvCkx4JWJ8ZL0NJrDsCV5OmfOfXb2wnDCU7znKhchhBBCCCF0Vhi4I4QQQggh5AMwcEcIIYQQQsgHYOCOEEIIIYSQD8DAHSGEEEIIIR+AgTtCCCGEEEI+AAN3hBBCCCGEfAAG7gghhBBCCPkADNwRQgghhBDyARi4I4QQQggh5AMwcEcIIYQQQsgHYOCOEEIIIYSQD8DAHSGEEEIIIR8gtXQCLlOMAWMtnQgAAGAMCGnpRCCEUAvwqpoYE3NGXpUY8LL08GR4T2K8Kmc8mRgCDIABnCWaYvxTD8HAvRkIAohiSyfiNEkCSls6EQgh5GkEQC+Rs51qPYwQopcEL0mMThIkQr2kScercgYADCIRRW/pjCBJ3pISABBFwSASLyk2oiiIAvNgsSFnjdoBQBRB8Fw4jYF70yM2G6uuYqLgwQuwM6YDgDEGhAQGgeBFP36EEPIAmbJSm0uSvKLlggFTFVWSvOKcq6gqpape5xVtp16VMwDgcLj0MhG8Iz5VKQUA0TvO4JQxl9NlVLwlMYxS0SONpEwQQl3VesUB5Cz7rqpE1IMxwgOJAQzcmxilIAhC1iH591+ITtfCt5QIAVlhoaH6WfdCYCD2mUEItRKUMYGQ4w719bRCFwPBk7exz4Z4QyK8khfmjPckiZ+1vaR7ivdkC/Dmb+KBnCGMqkbrY9nfdD6xh+r8BNaoIYAIgtOuv2IqjLwRqApCs19LYODeHJi39AVjFJgn7yUhhJAXYW7/tXxS0Bl5Wc4wxrylfxV4TcjOMWCMeUtfGQYeKjqMb+YccR07FWt5ilfc8kAIIYQQQgidGwbuCCGEEEII+QAM3FsXSqmqqvy1qqqyLDO3+zuMMVmWZVlWFAUAFEXhCzPGtG8hhBBCvohRlaoKADBKqaLw/wCAMcbf5x+1ZBKRt1IoU+mpeEl1e0093p0J+7ifovXc8qIuXE2NMSacHpzOGBNFscGIbEKITqfTFtCG+RNCPDN2GyHUyrWGqhi1DMb0lgBRp3NUV+rMfjqzH1AGAI7qSkESdWY/V10NVRSdyY8qLgzfkTsCIFmMIOqZzUkARJMeCIDdBQIR9Dpw2T2ZGB9ucVdV1b09mLccM8YURaGUAgClVHvh3mCsLeyOEMKXuVxPFZRSQsj27dv//PNPACCErFy58rHHHispKeGfAsCxY8eeeOKJe+65Z8GCBYSQb7755qeffgKA+vr6H374Afj0kggh5IZXsLxyUFWVno54GlTR0KiuPuN9PEIIYwyjdtTEGBP1xpxVS9Pmvc4oLU77a/2rj2x8++lN7z4n2+urjxTs/up9V12t3s96dPdmV30t8Y4ZGJEXYAIhCoN3V+z9fkcu0QkgCcv2Ffy4PRf0kkNW/8o6BqLgyeDIh4um1mDM24N5LU8IkSSJtysLgqC94EseP348PT1dW5hjjFFKt2zZ8u677/7yyy91dXWXX3jKAARBcDgct99+O4/F169fP2PGjM8+++z666+XZZkv9tdff73//vubN2/evXt3fn7+ihUrfv7554KCgu3bt2dkZGgXQgghpOEVLK9URVHUbus1qKLBra4+cOBAZWVlg/t4vOItLCycP3/+/Pnzjxw5AthYgJoCo1Rv8c9Z+9vJzH3hXZIP/fadNSIqYfSk8C49S/dvByDFaetVl+Nk1n4exJ/rUTuolVEB/CTybOqebiH+RZX1a7JKKusdW4vKjlTbjlTUF1XZSmsdTCCerKd8OHBftWrVL7/8AgCVlZVff/11VlYWABQUFCxYsGDXrl0AsHfv3jVr1gDAgQMHFi5cWFtby18vWrSINzPzUwIhpLy8/MCBA//+978jIyN37NjBm3xacNeaFt+XepvtlltuqaioiIyMBIAlS5bcdtttFRUVJSUlJSUl/FybmZk5ZcqUF1988aOPPjp06FCfPn06dOhQXFz8xx9/3HfffdqFEEIIwem6JSsr6/PPPz9+/DgALFu2bOXKlQBgs9kWL168dOlSVVWPHz/+22+/1dbWVldXf/vtt9nZ2YqipKam/vnnn7zVQGuDB4AVK1bMnDlz1qxZa9euvZzqYdSCiCAoTrujoixu6PjOE2dUFeYSUYwffpWjqqLj+OuNQcF6P0vCmKmCpDu2Ny0wNt4/qp0qu1o61cgrCESwOV1XJkaM7tvhhuR2B0ur6p3K4HZh4zu2rahzbCk6eU2XKAJAPDitqe/FYbwqP3z4sKqqiYmJhw8f3rZt27BhwzIyMsrKykpKSq666qrdu3eXl5dv27YtJCQkPz8/PT29a9euO3fupJSWlZV17NhxxYoV4NaWYzabLRbLjh07rFbrwIEDW3L3mgcBcDocM2bMuOGGG/gFzCOPPPLyyy/v3r3barUGBQXxpvTNmzdv3Ljx9ttvf/rpp5OTk7ds2XLy5MmcnJyoqCibzVZcXIw3rxFCHO/NUltbm5mZOWDAgLKysq1bt0ZHR1sslv3795eUlHTv3l2v1+/duzcjI6O+vh4AUlNTu3btWlBQkJ2dHRQUpKrq9u3b4XRXPV69REVFbd++PTMzc/z48YQQrHNQE2BMECVKVVd9LVVVe8VJxW6ryMss2b8zdtBIAuCsqT6culhx2BW7zegfWLp/h87oh9eNCAAIY7IgTujWvri0cu6GQ9O6xZgMug35J9fllpbWOdr6m3Mq605W2yRJ9Fhx8b3Andfj4eHh1dXVlZWVgYGB2dnZ69evz8rKstlsbdu2Xb16dWlpKaW0Y8eOPXv2rK6uHjBgQHJy8ogRI2RZ7tOnT3JycmBgoLYqxpifn9+MGTNqa2vXrl27f//+lt3BJsd3MyAgYMqUKaqq8j9jYmIYYzfffPOdd95ptVpdLhel9P7779+6desvv/yyevXqyMjIa6+9dtq0afX19f7+/q+//vpTTz1VXl7Ou5+29D4hhFoYvzNpNBr9/f0zMzNjYmKKiop27ty5ffv20tLSqKiozMzM3bt3q6oaEhIyfPhwRVFiY2NTUlLGjBkTExPTt2/f7t278+qI38rjrydMmBAREbFjx461a9e6XC6scFATYAwAonpfkbdh+ZYPXhD1ep2ftao43xLexhIRpTjs7QaPMgeHmYJCGVNPZOw7tOTrspx0ndGEQ1QRABAgskqP19iLKusXHSgOCbEMiwtrH2QRCFEpW3yg6MMth2tcCnjqYWK+F7hzOp1uzJgxISEhv/76a2xs7LBhw8aNG0cp3bt378iRI/39/RVFkSSJUqrX6ysqKgDg+PHjOp1OFEWXyyUIAu/azkdKFRQUbNu2beTIkbNmzTpx4sRl2ZOb76/2p8vluvXWW6dMmXLfffepqmo0GgVBWLFiBSGkffv2Op1OluXrr79+8ODBOTk5ERERPXr0sFqt6enp2ACGEOJ47J6cnDx48OAlS5Ywxvr06TN+/PjExMQNGzZ06dKlU6dODodDr9e7XC6dTldVVQUAlZWVlFLGmNPpFEWRurHZbCtXruzatevs2bONRmNdXR1WOKgJCILidFgjo7tNvS1x7DV+oRGiwXAyY1/bXoOpy0VV1RoZ0+uWByoLsg0W/6D2Se2HjqvIyxT1hpZON/IChDBFLq2s6ZPUduGMKzYWnACnclVyuyuTIouq6iSB3N0vwWKQyqvtHquqfC9w560v1dXVqampe/bs6devX5s2bbZs2ZKbm2swGOx2+/79+wMDA2VZppQqitK+ffv09PTPP/88JydHkiRFUfgEMnyYFB9K1bZt2yNHjixYsGDRokVdunThYX1L72jTEwTBbrfbbDYA+PbbbxcvXlxbW/vQQw9RSufPn79//36n0zl58uSZM2cmJSUZjUZFUebNmzd8+PDw8PAjR47Y7Xar1drSO4EQ8gq8LVyW5S1btqxcubJt27Z9+vTJysrauXMnAFit1p07d/IZZl0ulyzLFotFFMUFCxasW7dOa0SglPKxrXwIjdlsNhqNX3755WeffRYYGBgcHIzTy6BLx6hqsAbkrvmtPC9DMpqJIPmFtilN3+0XEs6AAQFB0hVuWW0MCAyIibdXltWXHZf0egDmqSZU5K0YowBmgb64as/JY5V7j1XEB1tAIKpL+Tm9eEj7cIteyq2os7lUSfJcOO1787jzSrxt27YjRoxwOBxxcXGMsZCQkPDw8ICAgHHjxlVWVo4cOVIUxbCwMEmS9Hr91KlTS0pKEhISFEVJSUkRRXHs2LF5eXllZWW8ablTp07XXXddVlZWcHBweHg4nL51eznh+dahQwf+55EjR3r16rVkyRJRFF9//fWdO3eGhYV98sknU6dOFQTh7bffBgBJkmpqaoYNG2axWBYuXJiQkNCjRw88jyKE4HSV4ufnN2LEiOLi4g4dOuh0OpPJRCmNiYmJiYkJDQ0NDw+3WCyyLPOHQowdOzYnJyc6Opr/GRgYGBMTs2fPHh7Hi6LYo0ePoUOHxsXFuVwuXllhbYMuHSGiq762w8irD/7y5baPXuk5815BFP3bxuqt/oyqwIAQojgc5uDw4LikIzs3VRfn9bzxXld9HSGXWySALgwhoKpUb75zSI9Xfv7eEhT83MhuIKt8PqyYQHNcqPXJ1H09gv0ig/yYp2Yj8tXpU874kI7zjCn5Yn/99VdOTo7ZbLbZbGPHjo2JibmglZwZpSAIzq0b2bJfiE4HLZu3hIAss9Aw/ez7hIBAYAxa+hTIH8VqMHjF/Uc+h7SXPFiKUupwOMxmc0sn5BQeaXlJzORyuQBAr9e3dEIATj8pQntOWcvyqpyB083ncCG1KKX0xx9/5I9q1uv106ZNazBd70WmhDGBkPwq23/S8l0MBGw4RYwRURJEkQHjj02VDEZVdp06TTMmSDr+/FRB0gmCQFWFURXnhWygFbbcEUoVo+X5/O/ij+8BvR+oKn9uF0gCKBQAQJLAaaMDpwijZgJVQWj2oML3Wtw5bcZGLXx3fxP+t53GfUltsWHDhg0bNsx9nQ0Wuyzxli2tiz9/k3cz5TuuLaD9yc/E2vstlXKEkHfSak6tk2GDarnBwu7vCIIwY8aMs62wmROOWhNCGFUUVSGn/iKK0/7/DeqEUEXm71PZRU9NZ4QlEAEAEEIcCmUKpYQKwHixYDLlVRRTKCjUk00Dvhq4w/9W6+5B+bmX1N5xf5wQb+NpDecJLfLWHonS4P0GLdDa+xiyI4TO6IxVMZx3baw9S9X9OU3NklDU2v1PyWrYDUb7rHUEA+iCEHL6P/b/7/z/C8+WFx8O3C9Rcz5O6PQRblnEO5KBEEJn16zd1QgBAbCrDLoAFEDA0+ZZtMLMIQQY4QGVAGcc88Df92Cs1XoD92ZEVXA6gKre0McdXM4WTgZCCLUEBuBQqJOBCNDiU/yeur3ewqk4BRNzLowR4tEn2J+DV2UO4d3YvKM10GM5I6hU0VHqcoLTBpQAa1SXEAGcNlDk5k/LKRi4Nz1msZL4RCJJLR+4qwr4BzIRjzJCqNUxCCQpyKwA8ZIWd8qo4B2zlDBgfCqVlk7IKd6TMwCgUlVs/vGF54kBAwDiNb3tvS1zPJAzhFHVYPRrGwdGF0imMzUCCOCys4Awvnhzpwd8d1YZb2ZzOI1Gg5dUQioAUCp6Rw91nFXmbHBWmXPwqrlTcFYZHyLLLp0ggPe0XDAViFdUOAAUFBUkryjGAF6VM0CdDsFgbOlUaHiE5hVVMXhd5lAveRgRBXA4XWaDh6pir6nRLieqAqoI3hArMwBKveTGFkIIeRJj4FCo3gtqYjh1yUd1Oq8ITxWFqio1eEVavCtnAMCmUKNEvWQ+BlU99YiDlk4IAG9gUqjZOxoK+PwiHnnsEQMgwrmfxkUpKDJg4O7DzjGIwdMpAezgjhBqtQTiLWPpmDclRiDAvCYxXpUzcDoxXpIePvWglyQGvClngJxKj0e2dHp750qM5/LFC4JLhBBCCCGE0N/BwB0hhBBCCCEfgIE7QgghhBBCPgADd4QQQgghhHwABu4IIYQQQgj5AAzcEUIIIYQQ8gEYuCOEEEIIIeQDMHBHCCGEEELIB2DgjhBCCCGEkA/AwB0hhBBCCCEfgIE7QgghhBBCPgADd4QQQgghhHwABu4IIYQQQgj5AAzcEUIIIYQQ8gFSSyfgMsUYMNbSiQAAAMaAkJZOBEIItQCvqokxMWfkVYkBL0sPT4b3JMarcqZlE8MACDAC/AhRTyYFA/dmIAggii2diNMkCSht6UQghJCnEQC9JIB3NFwQQrwnMTpJ0BHmJYnxqpwBAKMkiKK3dEaQJG9JCQCIomCUBC9pCRRFQRSgBYsNOfUPAQAQBZA8F2hh4N70SFUFLS8DUYSWvTAlQBijoiS0iwODoUWTghBCnsMACIBdZfvLakVJ8oYmQsYYVVVRavlzLgFQVVWlVKfTtXRaALwpZwCAADicTr3eRbwgPuVHCgBEUfSSMuxyuYwG2RsSQykFxoSWaiRljApijKsivK4ERIkosmgNhagOnunj4BU/lcsHpSAIQu5h5ZdFRKdr4VtKhIAss7Bw8Z5/gsGAfWYQQq0EY4wQUuZQ3997xEVBgBZuRTmFeEk6TrdTekliwJtyBoABI97T/u9lvCtzWq7YEEZdBvOtVdsn7v+aGgIER6007AaI6gCMAmn2awkM3JuBKIHRBN4QuIsSGAwYryOEWiFCwCwJEvOawB35An7V19Kp8FKYORxhIEmCTqcDgx8YzMAoSJ67f4WBezNgDBj18GCFMyFekAaEEGoxlAHlg8daOiXIVzBv6fzvjTBzOMKAMmD/H+x5NNbyonEPyAMYY+x08WKMqarK3Eobf0dVVUopAFBK6emBrRRHuCKEELo8MMbo/wdbjP/p9of2uiUSh3yBW+Ghbq89sOXLP3B3D1Xd32z8jqIol314Sgjh97n4DS9RFN1ve/F3RFEUBIExJggCfwEAgnD5FxWEULM6z7Mabz5o7sSg1osxIggG/0AiSjyClwwGvcUfgAFjRBT1ZgtfTNDpsWcIOgPGiCgCIcCYqJMEvcQrNyJ6ohvL5RaNMcYopTwHecjOQ1V2Gl+s8U+RECJJ0mUcnvKcqa6uPnbsGAAQQqqrq/fv3699CgB2u33v3r07d+7My8sjhOTk5BQUFBBCVFXNzc1tydQjhHxNg/t7cLriPWNjijvefOCBFKLWiDFB0qmyq3DTSld9LZEknclcfaTg6M6NRBCJJCkOe+mBXcCYIEn1J0tU2YXjxJA7xpgg6WRbPVUUkKTC8tqc0ipJJymUlRw94oEEXG5xKiFEEAR+euAhe01NTXFxMTmNL2az2eD0uYT/W1xc/Pnnn+/cuRM8dbPDw3gL+r333jtnzhwAKCoqGjp0aHJy8r///W843RNm48aNKSkpffv2ve+++2pqap588smnnnqqvLz88OHD7777LpyemgohhP6W1mjCXzPG8vLyVFXV3lcURVEU+N+q2OFw/Pzzz0uXLuWV0mVZG6OWJIiK077rqw+O7d2es2oJU+mJzP37f1xwdPeWoi1rdUZTzprfMpYtPJm1X2cyF25eLdttl3GLHrpQjKoGi3/pgR37f1qg1+nqHa53N2fO355b4VAq6+qXLVsGzd+1+LIqjowxh8Nx6NChmpoaAKiqqioqKpIkSZIkl8t16NCh8vJyADh8+PAXX3xht9vhdI+Rqqqq1atXDx8+PCcnZ/PmzYSQy6zPDAOgjL322mtLliwJDAwEgI8++ig0NHTr1q0//PBDaWkpb9/au3fvbbfdtmnTpl9++WXr1q19+vRp27Ztfn7+zz//fPPNN+NwcoTQeVIUpbCwsLCwkBDidDrz8/PtdrvRaFQUpaioKDc3lxDyxx9/pKamal/hMfrSpUuTkpKio6O/++47wMAdNSnGmKjXl2eni5Ju9AsfgiAUblldkXsopt/QYY+9XpS2rrIgRzKae1x/h+p0Ht2z1dom2i+sjSq7WjrhyEswQaevKsor3LpWZ/KTBCivqh/SPvz6blHHqmzr16698srxHoiULqtZZRhjX331ldVq3bFjx3XXXffDDz9ERUV169bt+PHjq1evNhgM69evnzVrVk1NzbFjx5xOp9Fo5F+klLpcrsjIyHHjxjkcDri8unQzxgSAqsrKsrKy6667zuVyAcDQoUNvuummhISEkJAQ3pGdELJ9+/b169evWrXqs88+i4iIOHLkiCAIubm5iqL06tXL/ZYFQgidEaVUEIR169bl5eXp9fqRI0cWFxfv2rVr2rRpx44d27NnT1lZmcPhUFW1pqbG6XQ2+LrD4TCbzd27dw8ODobLqypG3oAAKC6nf9sY8n/s3Xd8FkX+OPDPbHl6ei8kIYGEFnoHBUWw4dnA7umd3bvTn/XO0yvqeed5nuWrp6ec5RTPLghKUQEBpZcQShrpvT9Jnjxtd2d+fwysD0lAQJLsk3zeL168Nk82z87O7s58dnZmVhBE2dxZX22NjLFHxRJR0vw+1evRfF5nZakgiqrPE546jHetYZqGHWYQY4QwBsBGXHxNRf5BTVXNslThbJPtor2mWs4cEp+Q0Adh0oAqEzVNi4+Pv+6660aNGlVRUZGamrpw4UKTyaRpWmho6FVXXZWUlOTxeLKzs6dPnx4eHs6jVcZYZGTkwoULly1btmTJEkVRYGBNosJPo9DQ0H/+85+xsbG8u8vFF1+cnZ19++23z5w5MzY2lu/16NGjX3rppV/96lePP/742LFjZVlOTk52Op3JycmPP/74o48+6vf7sQEMIXQCvMAxm80LFy687LLLampqCCE/+9nPkpKSFEURBOGCCy4499xz29rapk+fPmXKFDjarM5j9Kuvvrq4uPjpp58uLy//0d7wCJ0SQoCqanjqsNp9O/JXflCXu9McGmEJjyz65vPC1R93NjVIFmt4akbVjo3W8EjF62ks3P/9i3/ydbQJkoQzzCBCgGpqWHKaIElUU3yUxUSFehT1cIdfa6q2h4Y99Ze/vP7664qi9GrBNaACd8ZYdHQ0ADgcDlVVw8PDVVWVJIlSGhcXRym1WCyCIHg8Ht7qzBFC6uvrZVm+7rrrbrjhhpycHN5i1H/70StEUWSM+Xw+/Xbw2WefLS4ufumllyilJpMJADIyMq699tpf/vKXvHPRc889d++995aUlISFhZnN5urq6tzcXL3TKkIIdcdLmJCQEJvNZjKZRFG02Wx8AitKaVhYmCRJiqLYbLaOjg592Iw+Pr6urm7BggW/+93vmpubW1tbscBBZxTRFL8jNnHcdXc2F+dFZ45mwIbNuzR29MTOpvqYzNGUaonjp5/7hxdcDbWW0DBLSERM1tjq3d/LNscPc0SiQY1oih8YAyCEgUDpI/PH/WZCUq0liin+hT+7pLa2tr6+vlcLrgHVVUaW5b179wqCUFJSsmDBgtraWj4jis/n4y09brdb0zSLxVJRUdHR0RESEsL/kBCyYsWKCRMm1NfXJyQk8ApmgMXu+gQ7/GHCli1b/vznP7/33nv5+fmjRo06fPhwTEzMq6++evDgQYvFYrVaLRYLpfSrr75KSkqKiYmpq6uz2Wy8HxFCCB0PLzxramqKi4utVmtycjJjjLeV8IYDTdNUVeUhe2Fh4cSJE3lhyxgzmUzbt2+vqqoymUxmszk0NBR6mgQModPEmGS2OMsPV+/+bt4fnvrmz4/Yo+ML134amjhk2LyfrXrwRpPVwRhzVhQDY5awKNXvs0CU19kMAICvHkIA0LVEYozSXZVNqTPjNFlOSkyy2+293WVjQAXumqZlZGRUV1fPnj07JiYmMzNTFMWwsLARI0bwjB43bpzNZrNarRMnTuzo6ND7uMfGxl566aXr1q1LSkrij24HalWhP8F5//33Ozs7L7vsMgDwer133333DTfc8Oabb86YMYMQsmrVKh7lL1u27E9/+pPNZnvllVdCQkLGjBmDQ1QRQifAy4fExMT8/PykpKRx48bV1dVZrVYAGDFiBACEhISIosjbUFpbW/1+vx64y7K8ePHib775prGx8bzzzpMkCQscdCYRoqmKPSbB19H22W3Xhg1JHzJtTlPhgYLVnxSt+XTo3IuskVGCKDYWHDCHRcSPnbL3vVfaKkpGX/Fz1efF0xD94Jg3dsGO2rZfpMT6x4z+y+N/iomNi4qK6tWCa0A9hfT7/Rs3bpw/f/6JV+MNQl988cXu3btDQkI6OjquvfbazMzMM5ACSkEQfFs3s5WfEVnu5y5xhICisOgY0y13C2HhjFIiCHxenaioqLq6Oo/Hw2fPHDJkSFNTk8ViCQkJaW5uJoTwYWEA0NDQEB0dLQhCdXW12WzmPZFOG29mM5vNZ2DvfjLe4GeQ6aIppXxMXn8n5AhFUSRJMkjAxBtreW+ufscnMZRlub8TAmCwnNHxGmvr1q1Dhw6Nj4//0aeXzz33HN8Rs9n861//+ozkLWVMIKTU6X56e6mfgQAwcOo59BPxedz9vpaSgoj0TEGSRdnUUVfld3VEpmdSVWUMqOIDQmSr3dPSqHg9YUmpqt9nkPKwf+GNNAAPrvxuJtys5F1w4H1qDvW0O03nXCWfd0PJ4aKYuHi9N0cvGVAt7pIkZWVl+f1+WZZ5ByP9fR9wdCJhHqpqmrZw4cKFCxfqf8vfT8R/22870Jt4VkRFRfEf4+PjA38bExMDAJRSvoJe18bGxgIAYywpKQnwokUI/RheRAwdOtRsNvOSJLAEDlwAAErp/fff3+Ub+E21/kYOhM4kQqiqCJIUP3aK6nUzxlSfJyQukSRKqscNhAAwyWIFxjTFb42MtgmC6sOoHQVgjEiSyeyA1iMf2C2yRghjLH3YcOj9SGlABe6CIKSkpOg/6hnXfYGP1AxckxBikMbXXhVYceo5oNesgQv6+l3eotI/6UYIBZXApoFTKorBMM/B0IBFCGPM73YdfVejoPn9DPz6acl7QRBCqKIAVnyoO8YYVX/4iR6NrDQVBBHncT81J3+jMzgvxcCKMzAHuleoJ/4cIYRO4ORv9bFsQf3imBPveGchnpzouEj3JUJIH5wzAy1wN0od0CcH76TS0O/JQAgNPgYpigkBgrOBoFNkjJPXoDBzAIAcibAIEOFooNV3+TLQAndDoBR8PmAUaL8OiBII+BXw+/G1EQihQYgB+FTqw8GpPSGYJ8fDAAjmzXFg5gAAAGHULzBVUcDvASKD3wsBPWd6GwbuZxQfCxsTJ86eQ0SpvwtGAlSjNjuTjTXpBEII9SoCBAAcEjlnSAQYY74BBkA1KoqGSIxGKTAwSGIMlTMAoKiqJPZ6N+WTRCkfdWaIxDDGVE2TJUPEjXyYXr/lDANVlNOihoH9Z0SyML+XJgwToY+eRwyo6SANwu31WiwWgxRCGgBQKhqj6sLpII8Hp4M8AUNNeojTQQYRxe+XRQFEQ8QZAABUA8EQBQ4wCpoGkiFOYwAj5QyA5vOKZkt/p0LHIzRDFMVgtMxhFIghYhsK4PX5beY+KooNU6INJFQDTTNIMw9oGnZJQwgNQgzAq1KTMUpixpiqUlk2RHiqqlTTqNkQaTFWzgCAR6UWySivTtc0CoZqYFKpzRgNBZRSSqkk9edhIsAIv7OiFFQFMHAPZkYaFWqQZCCEUJ8TCBijlwEwIyVGIMAMkxhD5QwcTYxB0sMIABglMWCknOGjzvs7MUfHpJI+jbUMcU+JEEIIIYQQOjEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhg4I4QQgghhFAQwMAdIYQQQgihIICBO0IIIYQQQkEAA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhg4I4QQgghhFAQwMAdIYQQQgihICD1dwIGKMaAsf5OBADAkWQYJzEGyRlC+jsFCKFex7Dw6wljJ5MzrI9KSUNlDRgsPViDH4/REgN9lxIM3HuBIIAo9ncijpKMdIhlGUQRg2aEUB8gACaRgDHKG0KISTJKYmSJSBr5sZK4r9JKCMgmg+QMAIBsxhq8Z6IIstkoNbgoGugwiSIIfXekjHRODACMASFCbbVWXMgkyQj3gpQyAADBEFca1Sgwpsn9mDMEGAVRFidNAbsDNK2fkoEQ6kWMASHQptDvylqJaIiimAFQSkWh/7unEkI0jVJGpePEPQSYXzClu2snNucy0UR6PfeYQCkIxgjCCMh+P5Fkg4SnhFEAANL/pw0AEMZkVQGTqQ8bl4+PUQGMkTOEEMUnJWZC1qQjRU8vw8D9jGIMCCE1VdqalVQ2GaG24Gh/J0DHGFP7sUAkBCgFs0XIzAJHiHEOEELoDGLACJB2hS4/3ORnIPTlY+zgJzDaIdvPbzkw8dDbVHaIrHcrEAIgEmKc0ljqu2cNP+5Im5sx8oYYKWQUAIAYI2eIQHxucc7VkDUJGAXS67egxjkKA4gggtkCsmyckshA+uR+9LiOBO6GediHEOo1BMAiCaJhAndmpIjwBIkRGGiSYJJlMNtAtkEvB+6G07+VlMFh5nTHW/0luc82iIF7b2DGGjZhKP2eJ3hcEBo0GAPeW9Ag17xBksEdNzEMKAPGGDB65N+gwgx1h2UwmDk9YrQv4woDdA9CqP8wxjRNY0cvuS4/9vghpZQvM8YY3gMghH4UY+xoucF/YpQG/kpf7o/EISNiDDTG+D/+CWWM9rSMZ81gM7gC9xNEWowxVVUpHWRNC4McY4QQURT59Ars2B91XT4UBIEvE0J+dF4GhFB3J77p1TRNG0gDxxkjgmAJixBlE99xyWQ2h4Qe+ZUomuwOvizIJixSEEdMomg3izazaDEBIZQxwWISLDJlDBgIsiSYJH4REWlwBXJowB5vGtC8oS/zSKvH6JwQIkmSYIAh/6hvMABBkgAgJyfH6/UCACHE5/Pt27fvyApHYwtVVXNyclRV5Z/v2rWro6MDAJqbm2tqavia/bILCBlfYIyuL/Oi+HgXjiiKonEmevtpGGOCLGuKUrz+i86GGtFklkzm9trKyu0bCSFEkhSPuzZ3JzAmSLKroUZT/Bi7D3IMAARSVOdcuad0VU7Z1qJan6IKJmlLUe3ukgZBlkASKpraC2udRBZVympaO7Hf+aAyYONUvVk0cLmtra2ysrJLdM4rj4qKijfeeGPnzp2AcdhgwBgB8Pv911xzzYQJE37xi194vd729vbFixePHz/+rrvu0u/ufD7f5ZdfPmHChNtvvx0Avvzyy0cfffTZZ58FgHfffXf9+vUAgA9qEOoRf4rFY/TA5crKys7Ozi6xO1/2er2ffPLJsmXLeKN7sJfGgij6XR173n25pTjv4LJ33E11HfXVBas+LN+yrnTzWtnqOPzN5/lffNCYnytbrBVb1ikeN8H2o0GOMSCkpt2zq7p1e2XzjR9v8yj0ja1Fawtr/7evfH1BjVfVnv++4I1dJa0epcXj+yK/GiSBBvmVgk7ewCwgKKX79u3r7OzUl10uFwC4XK6DBw8eOHBAURR9ZUKI0+n85ptv5s2bV1JS8v333x+vVR4NGIyBCFBZUSFJUk1NzVdffXXw4MF169aVlpZWVlY6nU6n08mDjK+//rqhoaGgoOCrr77atGlTUVHRddddV1dXV1VVVVhYuHjxYkopPqhBqEeEkOLi4oqKCn41FRcXl5eXE0Lq6up2795dXFwc2LrMY/Tly5ePHDkyJSXlvffeg2AP3BkTRMndXO+ISTj3Dy/aYxPqcnfV5my3R8XPf/LVmpxtzorDktU29upbNb+veu/WkPhke0yCpvj7O92oPxFCQKVzhic8fu2seRlxt01ODw+zOj3+x88f99g5o9/dW9bq8s5Oi7kqe0hti2tjScOFmYlAGT6oGTwG2qwyvFFnzZo1bW1tubm5ixYt2rhxY2tr6/79+xcvXgwAeXl5bW1thYWFV1xxhR5yUUoVRYmNjZ0/f77f7wcADMUGNiIQDSBt6NClS5f+/e9/z8zMzMzMXLlyZXZ29vvvv//Pf/4zMjJS0zRRFFtbW6OiojIzM8PDwysqKkJDQ/Pz861W65YtW8aPH282m/t7VxAyIl66Hjp0aNeuXYyxOXPmaJq2efNmAJg7d67H4ykoKCgsLPR6vaNHjw68+/X5fGazefTo0RERERDsRTEhmuILG5IRnjKso66KqioRJVtoWPPh/IaDe832EEtIuOJyOcuLBUlWfZ7w1GGMaoIkM03Dzg+DGgFN0dzVLe/sLXvwrJHA4IG5o5hA6l1em0kyS2J5a6csCKFmWZaE2FAr8HA/qO9y0UkL5jKxGx6119XVmUyma6+9dtSoUTt27LDb7ddee21GRkZNTY0gCGPGjLn66qt5dK4PSYyMjLzkkkuWL1/+n//8x+fzAXZ+GAT4vDCqqn7//fcdHR38ZPjiiy/+9a9/nXfeefrjmgsvvDAvLy8iIqK4uFjTtEsuuaSwsHDBggU5OTlJSUmLFy9evnw54AmD0LEEQVBVtaKi4vrrr1+4cOHhw4dLSkpuuOGGiy66qLq6mlK6cOHC8847r6mpKfBPAODqq68uKSl5+umny8rKBsTETYSqiiDLjQX7W0oLUqbNiUjLbCrc/+3fHw5JSLHFxIWnDK3a/b01PFLxehoLcre8+CdfR5tgjBdvo/7CAERZrGp1iYSMSI1SvX5FpZTB/20tvG5cSmS4XdFYaYuLMmaXpKfWH3hta6FCjDXZKOo9Aypw53w+n8PhAIDw8HC322232wEgNDRUVVVJkiIjI30+X0hICF+Zx/r19fWiKF533XU33njjvn37sPPDYMCbsyRJWrFixejRo997773Q0NDLL7+8rKwsJiYmNzdXFEVBEKKjo9etW/evf/1r5syZLpcrJibm008/tdlscXFxRUVF06dP/+STTyilJxhph9DgRCmVJEkURYvFwm+MJUmyWCyiKIaEhEiS5Pf7bTYbAOiXj8fjqampWbBgwe9+97uWlpbW1tZgv7IYY6LZ0tlQu/ONf4646GprRHTZpjXp5yy85P8+aCo80Fx4YMi0uec++ryrocYSGm4Ji4wZOb569/eyzRHUe41+IsoYCMKu6tYLshKYSgkhsln6/crdGZGOWcMSmNf/2/nZv56RWd3uZgCXjkyqc3nqWzuJKOBJMxgMqPCU1w1DhgypqqraunXr5s2bp0yZUl5evnXr1h07dsTGxvr9fq/XSwjh7an6dH6CIKxcuXLnzp179uxJTEzEPu4DHqNUBMjZt++8887bunVrTk5OdHT08OHDt2/fvn79+vr6+ujo6OLi4paWlsOHD99///3Z2dmHDh3Kzs7m04Zu2LBh+vTpABAXF6eqKr/96+99QshAGGMmk8lut69Zs+arr76Kjo6OiYlZvXr1unXrTCaTIAiKoqiqqk/oxK8gk8m0Y8eOjRs3btu2zWw2h4aGwtGCPUgRQaCKP+d//x5/ze3D5l+qKX5NVcwhYfaoeEqp6vMBIa3lRQBgCY+ULDZLeASjA2gqTHRaGAMQyfcVjVnRoUSjolV+a2thXIjlgUungCgwBpTSnVXNqREOSYD4EKtNknBw6uAxoAJ34HNvCcL8+fNramrmzp0bHR19zjnn1NTUnHPOOWFhYaGhoRkZGZIkTZo0SVVVv9+vKIrf74+JibnssstKSkrCwsImT55MCMEW94GNCIIGkD127JAhQ2bOnJmVlTVv3rxzzz13xIgR8+bNW7hw4fDhw2+77bZPPvlk2LBhhJCxY8fefvvtZ511FiGktLS0urp62rRpWVlZb7311owZM0RR1DQtqMMLhM4sfjnMmDFDluWYmJhx48aNHz/eZDLFxMRMnDgxISEhPDw8ISFh2LBhvBDmRFFcvHixz+erra2dO3euJElB3fDMKJXMltqcbeVbvqncsXH1w79oyN83ZNrcsk1rvnrsjuhhI0OSUoggNhUeNIdGxGdPaSzILf/um5jMbNXnxeJkUCMAlHZ41RCzBALp6PC+uKUwv7H9N+9sfH1zHjGJhMLO6pZJSRHjkiKf3ZSnUhYVamOU4lkzGAT3U8gf1WNTKO8Js2zZstzc3JCQkI6OjmuvvTYzM/MMbI9SEATf1s1s5WdElrGTYnf93DhNCFAKZovp1ru1+ERR04go1tTUJCQk8FRRSuvr6xMSEhhjzc3NVquVd7Wqra1NSEjg3+H1et1ud0REBJ8lIzU1VZJ+6iBvSqnX6+XdBoxAURRJkgxyK8JHpJhMpv5OCMDRN7XJstzfCQEwWM6cWOCF32X5+eef5ztisVh+9atfnZG8pYwJhJQ63U9vL/UzEKDfuv8SQhRPp7u50e9qB0IccYkh8ckddVWdTfXRw8cAMEap5vcRIkhWq6e1WfV6QhNTVL+vH68+gVGXbD+vNefW/Hc02SGywfX82ThPUFvc/jCLLIqComr1Lm+9y0sZC7eahseEgsbcimaRBUEUy5o7ou1mh9UEWq8fKeNkjoEQAXxubfaV4rzrgWog9Po7KAbarDIcY4xH57x/ZOAyAAiCQCm9/PLLL7/88i5/gm3tgwcBoJomCEJiYiIcnXVOEAQetRNCoqOj9ZX1DwHAYrFYLBb+eUZGRn+kHaGgwR9G8XJVX+ZXE7/o7r///u5/Ase+iyN4McZkW0hkWCQRRADQFJ+/02WLiguJT1Y8bj5jt2SxAmOaoljDo4gg9G/UjowjMsQCGgXGZElIjgpJjg0FIEApKBoQsFkkoIxpNC0mFChlKsWzZpAYmIE7f0d9j8t8gdccgesHroYGi6Nv0tW72OqvdQxcDvyQ04N4bH5A6MQCy9UuRXHghRb4+QArihnVFO+R9y4TQniv9yNvSOU5QCn/FVUVCPI+/egM+iEWZ8AUjSkMAMjRE4RRRgAIAaZoQHD60EFkYAbuJwMLR8QFPmMJPCv05e6nygl+hRA6JYPhIuq6j8fb50GQFejkBZ4OhACBY04P0tNqaDAYvIF77yJ4/3t8/dvHHQ8NQoMGOfoPnbwjmfZDaTn48g/riBPAzOmizy8TDNx7AaWg+AEYDk7tAevXWoAPThVEPDQIDXgMwE9Z/w5ODUYCoz7KVFUFxQcgQ18MTiUGOkT9W0l1dbSvjEEYLnMMkDNEAMUHVO2zDWLgfkbxDospadKV1xJRMsIpxSekN8iIW03TgDJZllk/5gxjIEokLIIPC+u3ZCCEeg3vVBAhCzeOjCOSZICS+Mj8B0bovk8IqKrGGDvedFgEmEKkJO9EyAwVhF6fHo0Bo5ohcgYAgIDi88myySA9uAxVgzPGFMVvMpuNcEFRRoExofencPlxhDBV0aKGiABA+uJIYeB+RvEpBWPihCGphrjOjjLAqQ0AwAA0ygTBEAUiaBoG7ggNSPzKdsjCOUMiQDRMNdcnU8WdFEZB00A68cyboQAZfVNEUsNUUgCgKpokiwapGwwQIf+AAaiKZpKNcqyoYV5FxABUr88EfdSPyDAl2kBCKWgaGOMWGTQNAMAgjRmqCpoGZnN/pwN76SE08DEAn0pNxiiJGWOqSmVjBD2qSjWNmo+fFgZAgJG+6RjBGKgqGOPdCAAAfi8IFqzBe0Ap+L0gGeN9I5QCpfCTX6JyZlANNBWgj2IbY+zzwGOcEZA8GcZJjHFyBiE00BmqvDFOYn60JCZH/uur5Bona8Bg9RTW4MdjrMQIfZkSY9xTIoQQQgghhE4IA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhg4I4QQgghhFAQwMAdIYQQQgihIICBO0IIIYQQQkEAA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhI/Z2AAYoxYKy/EwEAcCQZxkmMAXOGkP5OCkKoVzAAYxQ3R1KCienOUIkBg6WHBfzf74yWM90TQ/oruujb7WLg3gsIAVHs70QcJRnpEEsyEMEogbKhcgYhdKYRAEkwSHEDhBDZMImRBSIwoyTGUDkDALJARMEoyZEMkxIAEAUDHSlRICJ0S0t/pU4UQei7DiwYu5xRjAEhQkmRunsHkSQjNC0zxgCAGuNao5QCgNKH5/cJMMaAEKqqQlq6OGdefycHIXTG8AdpTV71k6IGRgxR4AAApVQwTOnHGDNIYsBIOQMAqqqJokCMUWnyGtw4idE0KkmGaJcMzBkCzEekVMV5Ze0Gwe8BIvbpgwFCiN9nypoGE88FRqH3CxwM3M8oxoAQ4myl+3OILBshcOeMkg4AxphB7iIAAAhhfi8IIAIG7ggNHAwYAeKhsKfe5WdMMEoZSIySEABMzPEw6N6Qi44wZuYIwNxE7lSbryzaDa5WJsp92meGCMTXSaKTAHgQ2OsbxMC9FwgCmExgpMDdQAzVp5wQAAaS3N/pQAideQTALBHCiGECdzBY2IOJ6QFjzCAt3AZkzMwRgGlEMIEAshlMFhD7tr8DEYBpIPRdOI2Be+8w1ChMQzFanuBhQmjgOlISGyhwR0aHFcIJGDNzjgxUZQGhV58mlG+u77ZolF5lCBkBpVTTtMAfeb/8QIwxTdN4BzvGmL5C9zURQgj1KkYpY0fLXsYYpXrQ9sMyNtCgYwUG2oHLlLEjp4yB7/YHReDOB+J0+UT/HyGOj9YSRfHIiF5KBUEQBCEwIucPCkVRPDImhhB9TJVxBlchZExYFKMzizFqcoTIFhtjDBgjgmgODddnhjDZHYIkM0YFSRIk7LyKfkAAyNEZe/RlBiCYZSIKwBgRCDFqnW7QZJ0Ab+PUC3q+rNcHgf/rqxFCCCGBjaP8Rx57BX7evV5BgwchpKmpKTc3l58YgiDk5eUVFxfrETk/Z1pbW3fv3s0/aW1t3bVrF/9VcXFxZ2dnfyUeob7XY+HZ4/+BRTEcWzgH9prVP8eiGP04xiSztWbP1qaiQ6LJLEiS6veWfrvK39EmyCYiCHX7d3mczZLJ4m1r9TibiSQZtxEV9TFCOjz+IwMrCGn3+AGACGRPWUOLywuy5Oz0tbg8IBADnjLBF7jzNk69oOfLen0Q+D//FWOsqqqqtbWV/yGvDNxuNyHE5XLpX9ilXkGDCg8XDuzfP2nSpHHjxr3++usA8Prrr48aNWr8+PGbN28GAFVVAaCiouLss8+ePHnyPffcAwDPP//8Y489tmrVKkLIX//617a2tv7dEYT6kl548uA7MArv8j//ldPprKiogKOFMwC4XC5CiNvthqOPvAL/pB93DRkcY1SyWMu//7piy7qir5a1lhVSVd399osNefuKvl5OVbWxIPfQ5++VffeVZLU15Oe2lBZKZusPnWrQYMUYgFl+dlPemsI6kCQwS89uyltdUAsOy9ayxpe2FH1yoAJM0rbK5ty6NpAlarwWhCAL3BljHo/nwIEDTU1NAEAp3b17t8fj6ezs7OjoUFW1s7OTMeZ2u1VV3bt3b319PSGkoqLC7XY7nc7du3cTQgoKCt59992DBw++9dZbPp/P6XTu3buX1yuVlZWNjY2Aj24HFQYMgBCyY8eOX/3qV6tXr3700UcB4D//+c+XX375yCOPPPnkkwCgqioh5N///ndCQsLOnTuXL1+en5/v8/kuv/zyvLy8jRs3jhw5MjExMbCLPEIDmKqqZWVlhw8f5kF2UVFRWVkZIaS+vh4A+E2s2+1mjJWUlBw6dIgQ4nQ6a2pqAGDXrl0ul8vr9b755pt5eXn//e9/i4uLCSG7d+/u6OgAgJaWltLS0v7dQWRolBFZLlzz2YQbfz3q0utLNnzprCwWZdO5f/o/QZTKvvtK9flGXnpdSFxyU+FBT2tj4vjpfle7YTs/oL7BADSRbMyvLmxuD7VITCAb8qoLm9rDLDJQVt3uuXdW1tBIR1l1c22HZ05GnOZVROO1IATZrDKMsffeey8yMnLjxo2//OUvd+zY0d7e7nQ6HQ6Hw+FQVXXfvn0XXXRRdXU1pTQ/P7+urm7GjBkOh8Plcu3bt0/TNEqpyWRqbGxsaGhobW1tb2/funWrIAg+n2/YsGHvvPPOJZdcEhERIRrn1aeotxEQBYEx9stbbmGMLViw4JZbbgGAxYsXv/766y6X66677gIAWZYB4Nxzz73hhhtSU1PDw8MdDoff7y8vL4+Kitq7d++8efMAAM8cNODx4R8bNmyoqanx+XyUUpvNlpubazKZXC5XdXX12Wef/frrr//iF78oKyuLiIjYs2ePKIp2u91sNlsslu+//76lpaW+vn769OktLS0NDQ2NjY1ut3vLli3Nzc3V1dXz58//6KOPEhISkpKSTCaTMWegQ/2MAFAWEp/UWl7kcbaExCWrXm9IXBIhhIiir63VFhHVWlJoCglzNdSExA8RRBEAGMWGlUGNEEL96rCY0J+PH9rhU8CvDo8J+/mEoa1ePwhEIJBb5ww1SWWt7vRIBwiCSChQwzXjBtndJ2MsPDz8iiuuSEtLq6ioKCsrS01NPXz4sNVqNZlMlFKn01lWVsbHDiYlJU2aNCk8PJwQkp+f7/F4kpOT9+7dm5KSMnny5HPOOWfq1KlOp7O9vT0pKWn//v1Op3PWrFljx47Fp7SDE2OsoqLiwIEDiqIAgN1u37x5865du8xmMxx9CHPeeeeNGjXq1ltvnTlzZnJy8owZM2pqarKzs5ubm/Pz86+88sqysjLAGWbQgMaLR1EUzz///Hnz5tXW1u7fvz86OpoxVl5ePmzYsMbGRlEUDx8+3NnZabFYzGbz5MmTk5OTCSENDQ3FxcWpqamlpaWKokyZMmXOnDnTpk2LiooqKChITU2tqakpLy8fOnTowoULJUnSN4fQsQhQmjB++o4lzx745M3Y0RPCkofWH9hzaNnS+oN7iECiR4xryMuRrTZfWwsA2/SP3zbk5YgmMw5RHdQYkyUhKTrEo6iUAZGE5OgQj6ISAFDp7LTY78sbQ8xSQ6cXAG79eMv2iiaQRKOF7kEWuFNKY2JiKKVWq1VVVVVVS0pK4uPjU1NTCwsLJUnKzMyklEZFRY0bN04UxS1btlRWVlosFr/f39HRUVZWNnLkSL/fryiK2+1WFEVRFJfLVVZWNmLECLPZbLPZDPUiaNRneHCQmppaW1u7evXqgwcPfvjhh4cPH/7yyy+feeYZAJAkiYfjTz/9dHV19SuvvMIYu+qqq95+++1du3ZNmDAhPz9/9OjR7733HmDgjgaBsLAwURRVVbVYLKqqVlVVqao6fPhwn89XUFAwe/Zsj8cTGxublJQ0bNiw3NzcnJwcs9ns9/s1TSsuLk5JSbFYLLwc9vl8fr+fUlpSUpKUlBQWFuZwOBRFwaIY9YwxQZS87a11+3ee9+eXZt37+MFl7zjiksZdd6ezqiQ6c4xosljCIub94f+sYZGCJKseT+aFi6t2bBIEEfvBDnKMAVPpkeaAo8sECGhajM302o1nxTgsZlFw+dTbpw5blV8DAmEGG9QcfMWi2+0WBKGtrS06Ojo1NTUrK4s/gZVlubCwMCsrKycnJyEhYceOHbzzTHt7u9/vT01NHTJkyIgRIwRBsNlspaWlPF4PCwtLTU0dOXKkKIqiKHo8HmzdGXQY6BH5vffeu3z58ra2tpCQEJ/P9/77769cudJmswHAnj17AGDbtm1PPPHEfffdl5OTwzsJVFdXNzY2Tpw4kTEWExPj9XoB2wjRIOD1ejVNUxSFMTZ8+PC0tLSkpCRJkqKjo3Nzc7Oysg4ePJiQkFBRUdHa2hoREVFXV+f3+yMiItLS0rKysmw2m8VicTqdVVVVTqfT5XKlp6dnZWU5HA6TycSHqyJ0PIQQTVGAEEtohDk0glGttbSwcue35zzyODAm2x0A4HE2tdeUhyUPBWD2qDggYLQIDPWLwPo5cJkCKB3eoqaO4TGhACwp1EoIAcaMVp0HWeAuiuKYMWMAYPz48REREVOnTj1w4EBsbKzFYpkyZcqECRMSExMnTZoEACNHjiwsLBw2bNjo0aOjoqLGjh2bkpKSm5ubmZkZEhIyYcIExtjkyZPNZnNmZmZOTk5WVlZERERmZiZg1DXYkCPX7qJFi7799tvLL7/8wQcfTElJeeCBBx588MHXX3/98ccfdzqdV1xxRVtb27JlyzwezxVXXDFp0qSGhgZBED7//PORI0empaURQr788suFCxf29/4g1Lt4CTls2LDQ0NCkpKS0tLQRI0Z4PB6n05mSkhITE3PBBReEhobOnDnTYrGkpKQoiuJ0Oi+++GKbzZaVlTV58uQDBw7ExMRYLJZZs2a53e5Zs2ZRSqdPn8673ERFRY0YMYKPKkGoB4RoqmKLiolIy9z68hP7/vfq0LMvdMQnKm73Z7deLUhy6oxzVY/b09LsaWuNy54kWW273/m/6GGjgAHW7giOfSWXviyKQmO7p6nTN2porMMs/+Gr/ROTIoAQMFjoTgb8Y6M+HdhEKQiCb+tmtvIzIuPrHnpgrHFmhIDfJ2SPl6/7Bf/A7/c7nc7Y2Fh9ynZCSHh4uKqqra2tkZGRra2t/LGMKIqxsbGiKLa1tZlMJovF4vF4mpqaUlJSTiMhlFKv18ub9o1AURRJkgxypPx+PwCYTKb+TggAAGNMVVWDxJTGyRljXdcAlDGBkFKn++ntpX4GgoFfgoh+AiaaLC0lBaIshw9J11SFqmprWVFE2jBBkhmlTNOoqkpWK1WVjrrqsOQ0dhKdGI12MhuKMTNHAOYm8hi18XdF7wqdTiZK5MTRFwGvojEGVlkEAK+qMQZWkwgMVMoUjVpMEtVoWWtnRnTIjwdyRACfW5t9pTjveqAaCL0+QUWQzSoDR88b/X9KaeBcwvw9l/zHwF8RQvhc3XyeYE3T9M/h6CQJXV4FggYbPuNQbGwsPx8opREREfxzSZJiYmIAIDo6ustfhYWF8QWbzZaSkoKnEBok9EIYeL8FTYOjsyrpVxDvpK7/KvDFebxwDhwNIgiCpmmBhXbf7xQKKkT1eaMyRjDGFJ+HACGiGDtqgurzME0DQogkSbLMNI2IUsTQTM3n7e8EI2NgYJElAD6p+zHLkkgkUQLGRIFkxIeBYsRpiIIvcO/yXg999j19KhheVXT5FRz7Rnr+K71i6LImGpz093DxU6XLj4FhCqe/eReOvgAS8BRCg0ZgUQzHToSqX0FdftV95S7DT7EoRqeEEKJ6PQBAiAAAwJji6SSEHOm5zN+/Swgwpnk9gCcV0gW2ox+zDOxozxjm14x5ygRf4I5Q7+kSLgT+2CVM6b4OhhoIIdTXjl9on2A1hI5HP1EMe8pg4I4QQmjAImCU8YjMSCkBwyQGjJQzYLzMMQ6j5Yx+2gRc46Q/rvi+3iIG7r2AMdA0EAQcnNoD/uDSIAgBTQOccx2hgYgBaIypDASDzAJIjDFIVi+AjZAYziA5AwAEGJ/+zwjpCawqjZEexhgFYyQGfjhtBGAqYRplQFXQFADWp9EXEUFTgPVdIDHwZ5Xpe+6mJrPbJYhGmGozcMRYvx9ooqoqHwBqhMQcyRlBAKuVRMX0b2pwVpkTMM7cKYCzygQVl9dX6/JJshEKHGCMaZrG3wXbvwgQVVM1jZpMhjiNjZMzAECAeLwes8lMhP4v/fiRAgBJlIxw78ko8/l9VovVCInh043oo2IoECtVEryNhNG+bnEnhGmKzxRiiU3sm6dHhrhUBhqHg0RH9/9FDwABD5KMgACARokhbmmMlTMIoTPOLJBh4VYiGSI8BQDQVBCNUedSjWqaIBvmls84OQOgmJlssRilcuDtuMQQlSYAU7xEtlj6OxkcA0qPnXvRAhDST0kB6vUBQN+cNka5VAYUSo90lTECTQMAEHt9YtGToqqgaSCY+zsdAHBszhijaRkhdAYxAD9lBglOGWMqZbJBSmLKNMqMURAbK2cAwE+ZQJlggBZ3ANAoA8NU4JQyP2UGiRopZZQyKTDOYkD661EApUBVgD66pAxyCAYcfTqqfseTYZzEYM4ghPqKcUamgpES0y8j+E7AgIkxSHoM9WTYaDnTNTEE+i11pE8zxhitwgghhBBCCKETwsAdIYQQQgihIICBO0IIIYQQQkEAA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhg4I4QQgghhFAQwMAdIYQQQgihIICBO0IIIYQQQkEAA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBKT+TsBARAgIeEeEEEL9TCD9nYKjCCECMUpqBEKYUdJirJwBAIGAcdJjnJQAgECIcS4oY0VZggB9eKQwcD+jKAVBEA/mKuvWEFkGxrquwBhIkvTz24TIKGCsL480QggNEpQxgZA6j/pKTqUCRADoVhb3OQYMGDFGmc8YAwCDJMZQOQMAlFKBEKPUzjyKMExiKGNCn0XMjFHJdKNzx4TidVS2CowG/lIAEAwSRBFB8LlNUy6C2ZcD1UAQe3uDGLj3Ar+PNTfB8QN30NT+SBZCCA0iKoNGt+JjYIjAHYAYIxkAwIMdgyQGjJQzAGCoNjWjHak+zRzGqEy8ne3QUgsmG9BjAncDZY0ggNdNPK4+2yAG7r2AEJDlEwXuhikUEEJooCIAskCYYQJ3FBQYM8yzCOPp08xhQAUiCBLIJpBMcGyLu4EQAWS1L7vuYODeOxg78q/HzxFCCPU+FvAPoZOBp8oJ9HHmMP7f8QIqo+jrtBmpd/9xUErZyWXKyax2vHUYYye/oTOCbxEA6LEPgAI/5Onpy1QhhFCP9CLrZNb8KetQSk9yQ2gQYYwENmoSQgThyCdH+m9gRYl6cExJw0cvBPkTlSAI3AVBOMlHMyez2vHWIYTwDfVZlEwEgQ/y6DLUI/BDnp6+TBVCCPWIF5InueZpr8MYEwRBEAQs9NAPCBFkWfV5BVEEIIQQqqqKu1P1egCYIMlM04ggAWNH+z4jBADAAIh8dLQoIV5F7fQpflX7IXwnJOgKmiAI3MvLy2tra/lyYFHeZdnv97tcrhOvoyhKR0dHj/WBz+fbvn17Q0NDH/TfYowxAK/He+edd0ZERHz66adHPmQMAF599VW73f7b3/4WAA4cOHD55Ze/8847hJAPPvjgvffeAwBN03o7hQgh1EVbW1tBQcEJClh9oa2t7UfXaW9v77EoI4QcOHDg0KFD2M8YcYwxQRQrd2za/I/fF65dJlksntamLS/9efM/H9355nOibK7Ytv675/7QVlViCYso+nqZt90piL0+swcKAoQQSXxnx+Gy1k6wyOsP1139/vc3f7p9aU6Z3yT9+ZvcP3y93w/g8ilv7S4BWaRB0lhg9MC9vb39v//9b3t7OwD4fD69KPf7/V2W6+vrDxw4oCiK/nngMl+noaFhz549hBBV/WFeF8aY2+1esWJFZWXlypUrCwoKoJd7p1BKCcDbb7+5Zs2aW2+99f/9v//X1tZGCCGEVFZWPvHEE08++eR77723adOmzZs3T506ddOmTW1tbdu3b582bRqlFOszhFBf0jSNUvrxxx8XFhYSQrxeL/+cEOL3+7ssK4qyd+/ezs7OE6xDKd26dWuXwJ13j9mwYUNhYWFOTs7XX38N3XoSosGHibLJ1VBTvG7lvD+/1NlU15i3r6OuesjUuZe+8unMX/9RU3zttVUZ8y5x1VU3F+fJFqs5JIxi89agRwGoSD7eW7Yyv1okAIKQU9v6xhXTPr5z/i+nDy+vaUkMtU4bElnW2L67umVkTCilBppN6MSMG7jz8nrr1q0VFRU2m+3zzz9/6aWXtm3bRildtmzZa6+9tn//fsbYypUrX3/99ZKSEqvVumPHjjfeeCMnJ4cxtmzZsn//+9+HDh1ijH322WevvfZaQUGB2WwODw/fuXNnbm4uBMxl63K5mpqaFi1adMkll3g8nt7eNR55uz2eZ5555h//+EdYWBi/M+HPiCdOnDh37tzx48dLkuT1eqOjoy0Wy969e0NDQ4cNGyYc7WCDEEJ9gJdLtbW133//vcPh2Lt37yuvvPLBBx9QSvfu3fvqq69+8cUXlNL9+/e/9tpr69atE0Wxqqrq7bff/vzzzxlje/bs+fe//7169Wq+/Oqrr65du1bTtPDw8KqqqjVr1miaFthQkp+ff8EFF1x33XWyLLO+nDQaGRMDIgiazweMhialylab4nZ5252NBftLNnypeDoBBFE22aJiQRBayw9HpA13xCYyvN8b3HjRUd/qTgm3/WxkklvRQBQKGjvWl9TvyKsGUWAai7Ca4xzWVo+/qt0zPT1OkAQhOBrcDRy48/J6xowZ8+fPj42NHTdu3E033ZSXl1dVVWW32++++24AKC0tFUXx5z//+fbt2zs6OhISEm655Zbi4uIDBw5ER0ffeeedeXl5+/fvj4mJufPOO/ft20cpXbVqVW1t7dixY3nfcQBgjMXExIwdO/aDDz5Yu3btsGHD+mbX7r//gauuuuqll15KSkpKSEjgVVdSUlJ8fPykSZPq6+tnzpw5YcKEpUuXjh079ttvv50zZ85f/vKXQ4cOAQ5XRQj1FT7GJikpacGCBRMmTAgNDb3nnns6OzurqqrKy8t//etfp6amOp3OvLy8X/7yl83NzZWVlQBw6623yrJ88ODB6urq3/zmN5TSAwcO1NTU3HPPPT6fr7a2try8/PPPP586daoemvMCed68eWvXrn399dcTExNxeA8CQjS/L2xIelhy+vI7L3NWFA+Zca6rrsrT3NBwKCfnf6+KJrNoMuV+tEQQJdXj9rQ27X7zOUGSALoMS0SDCCEEKE0ItUwbGqtojAABTWv2+MpaOz/ZV/7xzuLkhPDvShvWFNa0eZXEEOt/thdtyKsGOTiG1hg3cOdUVeWPU3ft2vWvf/0LANrb20eOHCmKYnZ2dm1t7f79+1999VVJkgBg3LhxsixnZGSUl5dnZ2fLspyZmXn48OGxY8fKspyVlVVfX9/a2iqKIl+fI4R4PJ5Zs2bNnz9/yJAhmzdv7oMjx1sDNm3a9Le//e3vf/+7JEmaphFC9u7de/jw4ZKSkvj4+Lfeemvu3LnvvPPO5MmTLRbLoUOHqqurX3rpJb03PEII9RleRjU3Nz///PNVVVXt7e3p6em8KNY0rbq6+pVXXmlsbFRVNTs722w2Z2dnV1RUpKenE0ImTJhQUlLCl8eMGePxeOrr6zVNM5lMet8/QoiiKBkZGRdddNGcOXN27tzZ3t6Osftgx5ggye015T53x/gbfmUNjy777qvsxb+Ydd8TU297yNfW2nz40PD5l0+55QFgTLbavO1Ov9tVuWOjyR7CDDvzN+obDKiiAYAoEFC0dxbPePj8cb+bO+qL/BqbQP54XvYvJ2e4FdWnUZskfnW4rr7dQ4JhdITRA3feLl5YWBgXF3fPPff4/f7IyMi9e/e2t7fv2LEjJSVl0qRJ9913X1ZWFgDs2rWrtbX18OHDI0eO3LFjR0tLS15e3pgxY3bs2NHa2pqfnx8eHn799dczxngXGkVRVFVVVbWhoWHp0qUREREJCQlms7m3d4r3ca+pqbn11lvffPPN8ePHU0r5vURDQ4PH4xk6dKjNZqurq2OMpaWlfffddyNGjKCUXnjhhS0tLZRSnHIBIdT3ampqqqurH3roobi4uNDQ0OLi4ra2tm3btgmCMHz48Hvuuefss8+Ojo7etWuX0+ncuXPniBEjioqK2tvbt27dOnLkyMLCwvb29j179phMppkzZ86dO/fbb79Vj1IUhVL63nvv8VsCh8MhiiKc3Bw1aKBiAESS2qvKw5PTRlx4UcTQ4a2lhU2FBzsb6wXZJJrMAEyUJUdcYmdTnWxzhCUNjR87xd/RTgQBZ5hBfPIYQSCKX9tQUg+UmkXBIotUo1GhVgBQNCoJZOGIxDi7xedTgQTBrKJGD9xNJlN0dPTIkSPz8vLWr1+fnZ2dmJhosVjefvvtiIiIIUOGaJr20ksvEUKioqIEQfj444+nTJmSkZHBK4CpU6dmZmZqmrZ06dKZM2eGhYWJojh37tySkhJBEGRZliRJkqS0tLRRo0a98MILu3btmjp1am/XE4wBAfjXyy8XFRVdd911drtdUZRrr7126dKl8+bN8/v9kiR9++23559/PiGkvLx8586dl1xySUhIyHvvvZecnCyKIm/66tVEIoRQoOjo6LS0NLvd/sYbb2RkZERGRmZnZ7/11ludnZ2RkZHDhw9/5ZVXysrK7Hb70KFD33vvvZiYmPT09BEjRrz11lvR0dGZmZkjR4586623YmNj09LSKKUTJ04UBEGSJF4Uy7JsNpvnz5+/YsWKV199dcyYMXa7HVsoBjkCwFQlIm148+H83W8vaSrIjR871VVfk//F+7kf/Uc0WULihwiSqXzremtEdNyYSQ0F+yp3bLJHx1FNxZndEQC4/ZpXVUWb6Zvi+v9uLXx1++FpyZGCKDLKPjtYOW9YfFqk/c1dJU2dPrvVxBgzfmg1eJ9Crl27Ni8vz263d3Z2XnrppUOHDj0DX0opCIJv62a28jMiyz2/OVWS5F/dL0THfv3VV4VFRW63W5Kke+6558svvxw6dGh2dnZDQ8P7779/zjnnjB07FgDq6+vz8vLmzp3b0dHx/vvvX3jhhUOGDNE76P8o3tFINMbTH97xqQ+eaZwMQ+UMpdTr9dpstv5OyBGKokiSZJCbQz4Piclk6u+EAAAwxlRVlWW5vxMCYLCcOW3/+c9/+I6YzeabbropsB/jaaOMCYSUOt1Pby/1MxAwggtmjDHJZG6rLitZ/2XipJlxoycCsKqdm1sO52VdfLXJHsIY66itFGU5bMjQ6t1b3M0NQ+dcSBX/6U0ScvLV6yDUp5nDGJXNd7Vunpb/BZVtwul2fMpraE8MtYTZLVSlS3YejrSaFk8YCooGBA7Vtw2PDpFN0gd7S0fFho1NjmKKeso7SATwubXZV4rzrgeqgdDrQUUQBO78RNGnQQzs8siX+QonXqf7ckNDQ0dHB2+9TkhIsNls+vecflpPJXA/yR0//cQAgMHCUwzcjwcD9xMwVHg6mAP3Li+D61L8dlk+mXUIIZqmVVRU8PUFQUhNTQ3c4mmfgRi4DzCMMVE2mUPDlE6X4nUTILLdIZkt3rZWpmlAQJBNQJmm+GWbXZBkX0fbaZ88GLifQDAG7iCJQCloDAiA3QyUUbdP4HshiaBqjAGxmUDVwK+ezs1enwfuZ6Bto7fxsyRwUrDA8yYw1D7BOt2X4+Li4uLium+oz2iqqs/2L8sy7/3CO6+rqiqKIt8d/ppxURQZY5qm4XSQCKF+oTeLBH4SOLQ0cPkk1xFF8cw87UQDGiFEU/ydjXWECEQQAMDv6vB1tAmCyCMtze8nAEQQFHcnMBYUQwxR36CKygseBqB1eAFAEoj+K4EQQkDt9AkEhCC5YQuCwL2XBD5q6Jfba1EUxYDt6k2/hJDA9jxCiD5C64w8REYIIePo96IYBQVCCBEDpoMTBAI9NNURbNhCx9LDcRIQsnf5VZfPDW7wBoJYQyCEUL/DohghhE7e4A3cexFjP/zr8VcIIYR6H2VAGQD2cUcnjU/7hnrUp5nDgDKQ5WAoAAEAAElEQVRgjAGjR/4ZFqN9Gdph4H5G8TNaksFiheMPTsVneQgh1NsIgF0WZAbi0Xfe9W9iGDPMxOK8ajJGYoyVMwDAgBDCjHGvR4AAgHESw/oycmeMSoIsy2BxENlm3MCdCIyIIPNZN/oid4JgVpmg425vNxM4/hBSQqxW6KvY3VBzp+CsMseDs8qcAM4qczyGyhkD8vr8blUzyMFiDFRVlWVDNJapqqZpmtlsiDPHUDkDAB6Px2y2CMbo9KxpFABE0RCNfZQyn89rtVr7cJvEyvySqnSPhymllDJJMkoN7tPAGhbeN5szyqUyoMgysVoNcdEjhNBgJRIIM0miYSJCKoEgGiIxTCKaSiSTIRIDRsoZADBpktkiGeURAG9mJoYI3AGYj0nmvj5trGA+zq2CkR7UMI+3z7ZllEtlQGEMNO1EberGaMhECKEBjAGojBkl5GFMpUw2RPsgqJRpjBkjLcbKGQBQGZMoM0qLO2UAYIwHw0ApUxnr48c0BKDn7uOUAqVgkKn2aJ92wTfGPg88hGB0jhBC/YsYqEnOQIkhRkoMGDIxBkkPCfi/3/VbzvQYTfEoyyCBVt8mwyCNEQghhBBCCKETwcAdIYQQQgihIICBO0IIIYQQQkEAA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhg4I4QQgghhFAQwDennnmEEGKQt3kBGCclgDlzfIbKGTBe5vR3Eo5hnPQYJyXGZLT8MU56sMA5AUNljnFSAsbLmUGbGMIY67ONDWyUUn7w9AWet8Y5t/peYFZ0yY1Bnj+UUjh6tfPM6X7yDMKc0c8TABAEQf9REIRBnjMAoO+4nhXdlwVBCFxzEOLnDM8HPGd0vMDRs4VnES9wBvk5E1jIwLHnDAzueoqfM3BsUYw1OARcLF1KG+jpLOqN/MHAvbcM2nLwJGH+dIEZgk4gsKrQF+BorYknTxeYIYG6nzzoJGGOHc+gzZnuOx74Sd9kC/ZxPzMYY7t37+7s7ASA+vr60tJSQojL5XK5XHC0ih1seJ60trYCQEtLy3fffbdt2zYAaGxsxPwpLS3dsGFDfn4+ALS0tOTk5PCrvaioyOl0AkBzc7Oqqv2byL7X1ta2bdu2LVu2HD58GADKyso2bNhQUFAAAIWFhYM5ZwghLS0tfKGoqKisrIy36OjLXq83Ly8PABhjzc3NMCgvKwBobW3Fq6kLfp4UFRURQhRFycnJ+fbbb1tbWymlhw4dgsF9zrS2tvK6ibeYYj3OaZqWm5v73Xff7du3z+v1trW1YQ0OR+Py9vZ2RVHg2NKmL0se7OP+U/FHjWvWrGlpaSkqKrrkkkv27t3b1NTkcDhaWloIIZmZmYPt3pQ/J1q1alVnZ+fBgwevueaar776ShAEi8Wiquru3bsHef643e4vvvgiKSnJbDZ3dnauXLnSZDK1t7dPnTr1u+++S0xMPOussw4dOjRx4kRJGlxXqM/nq6qqamtr27Rp0/333//5558nJydbLBan0/n9998PzpzhT2O//PLLoqKi+++//9ChQzt27BAEQZIkTdM2b94syzIAqKq6adMmxtiQIUPy8vJmzZo12C4rAOBXkyzLeDVxvHo6dOjQnj17NE0zmUxut3vr1q3R0dFut7upqem7774DgMF5zvDMWb16tSRJFouFMbZmzZrm5masxwGAUlpXV+d0Ordt2/bHP/7x66+/ppRardbBXIPz+5OSkpLXXnvtz3/+s6IoK1asMJlMbW1ts2bN+vzzz81mc9+UPIOuIDuzePemzs5OQsj111+/Zs2ampqakSNHut3uQ4cORUVFjRkzBo52exokeJ643e6oqKiLL7549erVbW1tmqYNHz580qRJbrc7IyMjNTV10OYPAHg8HkmSpkyZMmTIkNLS0uzs7IkTJy5btqyuru6iiy7Kz88/ePDg0KFD7Xa73gN1kIiNjV20aNG2bdsSEhIURZFledq0acnJyaWlpRdffHFeXt5gyxleI9bX12uaZrfbAaC+vn7RokUNDQ0VFRWyLC9evLixsbGqqiohIeHSSy/NycnxeDwzZ8401MitPqBn1JgxY/Bq0vH99Xq9ixcvrq+vr62tFUUxOjp6wYIFYWFhubm5l1122d69ewfnOcP5/f4RI0ZMnDjR7/czxrAe5yRJWrBgQUNDQ0xMTHh4uMvlGjdu3MSJEwdzDc4fbNbX10dERABAY2PjmDFjJk2atGzZsqqqquzsbL7cByXPoMju3uZ0OiMiIjRNi4mJsVqt+fn5u3fvdjgcqqp++umnPp8PBtOzJF7022y26dOnu1yu5uZmh8MRHh5eXFy8ZMkSSZKKior27NkzaPMHAERRDAkJ2bx58+rVqzs7OyMiIiilMTExDofjiy++8Hq9ZrO5uLh43bp1fFRQf6e3jzDGKKVOp7OysjI5OVlV1dDQ0M2bN69YsSIpKWnZsmWDMGf41RQfHz9//nxRFPmHsizbbDZKqdfrNZlMZrPZ4XBQSj/77LOwsDCLxfLFF18UFxfDILusAMDpdEZGRuLV1MXEiRPNZnNOTk5ERERISIjX6/3444+LiorCwsI++uij0NDQwXnO8FgqMjLy8OHD77zzTnl5eUxMDNbjOlVV9+7dm5ycDACRkZFYgwOALMszZsyIjo5WVbWtrS0qKkrTtISEhIqKitjYWH7y9EHJg4H7GSDLMmNMFEW/3w8As2fPnj9/PiFEVdXY2Njdu3fDoDmtdYwxVVVXrVo1depUQRBmzZp11VVXjR8/vrS0dO7cueedd95gzh/+fOa6666zWCytra2iKAqC4PV6w8LCLrvsslGjRnk8npCQEEppcXGxPnh/wOPPavLy8uLi4kRRpJRef/311157rclk8vl8ixYtGrQ5AwBer5cvEEL0OXYkSeJVgs/nS09PX7RoUUREhMvlSkhIKC4udrvdg60BVZIkfhbh1aTj+7tlyxar1ZqZmRkVFXXjjTdeccUVVVVVKSkpixcvHsznjM/nmzt37lVXXTV27Njq6mpCCNbjHCHE7XbX19cPHz7c6/Wec845ixcvxhocjjYw8eKXUspPGKvVqmmaKIp9U/Jg4P6T8IMRGRlZWlra3NxcXFxssVjsdrvT6eTNzDExMXqNO3jwE/STTz5JTk5OT09XFGXVqlXNzc2VlZU2m81msw3a/OE509TUtGLFiqamppaWlvT09F27dvGn2LIsR0VFVVZWpqSkWK3W8PDwQdWYwSMGj8djtVrhaC41Nzc7nU6z2RwVFVVRUTE4c4Zzu90AoGnaoUOHSkpKLBaLLMsHDhyoqKhQFEUURZvN1trampycHBYWxoP7/k5y3+EnT1RU1N69exsaGvBq4niEsXv37uLi4tmzZ2uatmfPngMHDuiDmx0Ox6A9ZxhjmqZ98cUXvO7OzMwsKSnBehyOXiMdHR0WiwUA9FzCGhwACCE+n48/1svJyamvr6+pqcnIyNi9e3eflTwYuJ8BkiRNmzbtnXfeycrKioqKUhSFMZaRkWGxWDZu3Dh58mQYTHOd8s6mnZ2d1dXVW7du/b//+z/G2PTp05cuXRobG5ucnDyY84ff6WVkZNjt9g8++GDKlClJSUmhoaEfffTRggULAKClpSU+Pj4+Pr6mpqaysnLEiBH6NLEDnt4tJD09HQCGDx9ut9vff//9GTNmmEymlpaWhISEwZkzACDLcmpqKgBMnz59z549NTU1Y8eOHTNmTE5OTnV19ZQpUwCgsbExMzMzMTHx+++/j42NtdvtgypIZYwlJiaGhYV9+OGHeDVx/JoqLS2trKx87rnncnJy5syZs2PHjoKCgunTpwNAQ0PDYD5nbDbb1KlTed2UmJg4adIkrMd1hJAJEyYAgN1u13MJa3AA4EVxdHQ072x2zjnnREZG9mXJM+ieGyKEEEIIIRSMBlHbQ6/i3Z70uyC+wD/s13T1J3oUYP50E5ghx8ucwXlTHbjXmDOB9IslME+650+XDwcbPGe643miZwueM4FOpigezPWUvoA5o+sxW/qy5MEW9+MKPAz6gDB9Yoce1//Rp0W8U50oiuzoK+5/ejoDX7TLv18QhEH1OBghhBBC6ORpmsZDOz3MC/yV/uEJor7+goE7QgghhBBCQQBfwNQD3hze3Nz80UcfqarK5/2ZP3/+4cOHzznnHD55HyFE0zQA4M3nPp/P6/WGh4fzJ5K8zZsvi6LIhyTy904vW7bsqquuKikpGTVqVExMjH63p0/xRgjhjeh8gc+Lx+8F+Tfry5RSSZL27dvn8/mmTJlCKW1tbV26dOmoUaMWLFgwCN82ghBCCCH0o5YvX56UlDRlypSqqiqv1zts2DC9lX3t2rX79+8XRTE9Pf3iiy/mr6kGAN76zpd5MKZ3BuY/BvZ60H+lt+vzWE7vHxEY0Z0SDOx6wA+ez+crLi7euHHjhg0b+CxRGzZsMJlM/MjxidtFUeRPW959992amhoA4K8i5weGL+txNgAUFRV98803brd748aNbrebx/R6zxb9EPJP9Gc0fJn/qB9j/uUAkJeXl5OTw3/r8/m2b9++efNmCOiGhRBCCCGEeGhUUFDQ3Ny8efNmt9u9YcMGvT8MD9U2bty4ZcuW0tLSpUuXrlmzRo/3+Dp8OTBaC2yf1V+vof+KB3g8SNOj9i4R3SnBFvce8JxNTEx89tlnP//8c03TrrjiisbGRrPZ/OWXX3o8nssuu0ySpM8//7y5ufmmm25qbGzctGlTR0fHsGHD9uzZs3PnztmzZ0+YMGHr1q379++fPHnyxIkT+TcrinL33XePGjXKbDbv2bNn48aNV199dX5+fmdn51lnnfXNN98kJSWNHDly69atYWFhCQkJW7duveiii9auXTt58uTm5uYvv/zysssuGzp0KACsWLGisbHxlltusdls/AVde/fuXbRo0SOPPLJmzZr+zD6EEEIIIaPib0pSVTU3NzcyMpKHVfrIw5CQkCeffHL06NFLly4tKChYuHAhj/d+/vOfa5q2atWqtra2Cy64ID4+/ptvvmGMVVZWXnbZZZGRkdXV1Z9++un48ePPPvvs/fv3e73e6urqmJiYWbNmlZeXb9iwISoq6sILL5Qk6eDBg19//fVll12WlpZ2MiMkA2Hgflz8xsvtdmuaxjulFBYWtra2Hj58OD093efzrVixwmaz2e322bNnezyelpaWurq60tLSCy644O2333a73atXr168eHF5efn48eP1r+3o6GCMeTyelStXaprmdDrnzJmzdu3amTNnrlq16q677uLr5OTkjBs3bunSpWPGjNm8eXN6evpLL71kNpuXLFnypz/9acuWLStWrLBarcuXL7darXv27MnNzT3//PMBoK2tbXAO9EYIIYQQOgEeIo8ZM2bLli0jRoxob29PSEg4dOhQWlqazWbj7fGapv3mN7+JjY212Wz333//5s2bV65cabVaw8LCfD6fy+UaPXp0WVlZfHz8V199xd+529jYeM899zz55JMAsHnz5tDQ0JaWliVLlsTHx9fV1Y0ePXrJkiXnn39+S0sLf136yy+/7HA4/vOf//z2t78NCQk5pdgdu8qciN5HRRAEVVWjo6NffPHF66+/vqqq6sCBA/Hx8SNGjNi8eXNSUtKsWbNuuOGGlJSUhQsX8hdHh4eHt7W1vf7664qiqKqqdzfnD0cIIX/+85+XLl3K3zvtcDi2bdsWFxc3fPhwAJgwYUJnZ+fevXsTExPXrl07fPjwtrY2t9s9ceLE+vr6kpKSgoKCuLi4zMzMHTt2AMBnn33W3t7OX6iB/doRQgghhI5HFMW77rpr+vTp9fX1iqJ89tlnW7du1X/LGLv88suHDRs2YsSIMWPGbNu2LSEhITMzc+fOnbGxsd9+++3atWt5zxmHw8FjudbW1g0bNiQkJPz73/++5ZZbtmzZwhibPHny888/n5qa6vf74+PjX3/99fLyckJIXl6eqqoTJkyoq6srKSmBgNl+TwYGeSdLVdWwsDAec5vNZlmWhw0bdtFFF91www0A4HQ6CwsLDxw48Nxzz2VmZvJ17r333ltuueXDDz/kh4p/D59iUtO0DRs2fPPNN6qqRkZGJicnv/nmm7xhnlIaFRWlqur+/fsvvPDCFStWjBo1ymKxhIeHn3POOTfffPPQoUM1TcvMzFy4cOHVV1/t9/svvfTShISEL7/8Ek7x8COEEEIIDSo8Etu4ceO4ceMKCgrOP//85uZmPq4UAAgh55133hNPPJGTk5Ofnx8REZGenr5w4cLFixdnZWX9/e9/Hzp06BtvvAEAmqatW7du/fr1mqalpKTU1NTk5ubu2rUrNjaWMRYVFcUYM5vNPp9vwYIFTz/9dGFh4fr166OiokJDQ88555xf/OIX/E3hp9TkioH7j9Dnz+fTyPCBwIqiLFiwoLOzc8WKFR0dHQCQlJS0bNky/qucnBxZlmtqar755pucnJxLL700KSlJH19sNpt5WL9jx47nn3/+4osvFgRhwoQJ1dXVvCs8H9OQkZGRlJSUnZ0dHR2dmpqamZmZnZ29fPnywsJCWZYvuuiizs7O5cuX85cPjx49+uqrr163bh0AhISE9GuGIYQQQggZFO+X4vP5KisrR40aNWHChJUrVyYmJvJJ/Pg6jY2NgiAsWrTorbfemj9/vtfr/fzzzz0eT01NzWeffaaq6jXXXAMAZrN53759zz333HnnnTdmzJjJkyffd999jY2NCxYs8Pv9fPIS/p27d+9etWpVdnb2jBkzhg0bxiO6goIC/cU+J59+nMf9R3g8HgCwWq2U0s7OzpCQEP2Ttra2zs7OxMREAFBV1ePxhISEOJ1Oj8cTGhpqtVq9Xm9dXV1qaiqffEYUxS+++KKgoOC2224TBIGvYLfbOzs716xZs2XLln/84x/6XRc/5Far1eVy2Ww2PrVQZWXlkCFD+Drt7e0ulysxMdHn86mqarfbW1tbrVbr559/XlJS8sgjj/At9l/OIYQQQggZEaVUVVWTyQQADQ0NUVFRegztcrlMJpPJZKKUNjU1xcbG6hEXANTV1VFK+fJTTz21aNGiIUOG8P7xhJD29vaQkBBCiB4rdnR0OBwOQkhZWVlkZGRoaCjfemBEd0qwxf1HWK1Wq9UKAIIg8MZs/gljLCwsLDExkd/5SJLEhxeEh4cnJCTY7XZBEGw2W3p6Oj8V+LfZbLYPP/wwNzfX4XAIgmC32xljJSUlS5YsufLKK/WJPwHAZDLx7fI1eQJSU1P1uYRCQ0P51s1ms91u1zQtIiKipqbm1Vdfxd4yCCGEEELHIwgCj9oBIDY2ljd08pZvh8PBfyUIAu/0okdcjLH4+PjExEQ+mzt/o47NZuNztPM1+YIePfI4HgDS0tJCQ0P1V/foEd2pwhb3U9DlcUaX1+Ty3+r5qS8H/onP5+PN9nwKdjjaA8fj8Tgcjh43F7jRLstdvpx34+no6JAkqfu3IYQQQgihLrpHdz2GdvzDwGWXy2WxWAJnZO/e70X/pMeg8TRSi4E7QgghhBBCQQC7yvS1Hu+UzuDtkz6aFiGEEEII9ZJ+CbewxR0hhBBCCKEggC3uCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhBBCKAhg4I4QQgghhFAQwMAdIYQQQgihIICBO0IIIYQQQkEAA3eEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoC0mn8DaWUMab/KAgCIeTMJenMY4xRSgGAECIIRr9X0TStS5ZqmgYBief5f8b3pZe+Fnrao+74MRJF8VS/XD+4+ib4jpzGV53qRo1/5iPUe/RLTyeKYperjxcp3ZdP/J1n5OL9ifXU8a7xkynNuqwfFPUOQihYkMCi7bTxAu6nf09v4Duol7OapvVqSBekArPFyEeziy5JDaKUIzTgBV6PRrg2jZAGhBD6iU4tcOdNJpWVlaWlpTwUlmV55MiRYWFhvZbCn0Rv48nNze3o6MjKyoqOju7vRJ2I3+/ftm3bqFGjoqOjeeIZYzk5OR0dHcOGDUtMTASAvLy8xsbGlJSUtLS0M7jp8vLy8vLy+Pj4zMxMOLnmsZPRfY+6rMA/bG1t3b9//9SpUy0Wy0l+M/9Dt9u9b98+k8k0ceJE/uUlJSVOp3PChAm90RzON9rR0bF///7s7OyQkJAzvgmEDI5fBS6XKzc3V1VVXkwJgjBjxozq6uqWlpZx48bxq8/n85nNZv5XgcvH+87a2tqioqKzzjrrp1y8P7Ge0vfu4MGDo0ePdjgc+q9+tDTrbvfu3VFRUWe2rEYIDWrsVCiKwhj7wx/+EPgNY8aM2bt3L2NM0zRN0/x+v6qq+p9QShVF8fv9mqbxT/iyqqp+v58/zeyypv4hX5N/p/7njDH+t4qi6Gt23y7/QkppQ0PD5ZdfzpuTMzIyXnnlFf6dqqry3eH7xf+Wf4miKJqm6R/yLfKVKaVdNt1jegLT4Pf79fTzH/medlmff0NlZSUAvP/++3puK4oyYsQIALjlllv4N8ydOxcAHnjggR/Nc/3D4+Uk/wbG2IsvvhgVFQUADofjwQcf1JPa/Uh1TzzPHL5+YDJ63KPuecV3c+XKlQCQn5/PUx6YgC7LgcnesGHDhAkT+Hl41llnbdmyhTF2++23Dx06lGe7foi750mPx+J4+6Kvxr/w+++/B4Dvv/9eTwlCgwe/NHbu3NmlNuno6LjjjjvCwsL45fOXv/xl1apVvNh56qmnVq9erZe9XS5nSqnH41FV9fnnnwcAn8/HP2QBhTMLKIf5d/ZY5LKTqKfY0UJbT0NgPcU39+233wLAt99+ywJKeF6affDBB5RSt9utFxq8yGI91QVJSUn33Xcfw4ICIXSGnM5zQ0JIWlrawYMHa2trDxw4UFxc/Mwzz/B7AEEQZFkWRZEdbcgnhEiSJMuy/oySL4uiKMsyb6qBo40cfE39Q74m/87AR5z8byVJ4g0ePW4XAHj/y9tuu+3rr7/esWNHQ0PD0KFDn3rqqerqakKIKIqSdKSLvyRJPLLnXyJJkiAI+od8i5Ik8UTqm9a31SU9On19Pf38R76ngeszxvg3mM1mSZJMJlNgbtvtdofDUV9fDwB1dXVOpzMkJIQnnj/8PV6e6+k/Xk7y/pr79u2777777rnnnvr6+j/+8Y/PPvvsJ598wpPa5UjphykwB3jm8PX1ZBxvj46XV/xv+cqyLOtZF5hvesr5b5uamhYsWDBs2LCGhoZt27bt3bv3X//6FwDY7fawsDCe7fyo9ZgnPR6L4+2Lvhr/QkmSQkND9fMHoUGIXwVvvvlmbW1tdXV1TU2N3W4/++yzb731VlmWW1pa/v73vzscDkEQGhoa/v73v4eEhAiCwLuw88s58PqyWCyiKFosli6XVfdyGAB4Uda9GAl0vHqKF1xd0tC9nkpKSrrpppuSkpLgaFmhl2Z8u1arVS80ZFnmO9K9fAsLC7PZbGc46xFCg9jpBO6qqoqiOGrUqPj4+NGjR1944YWFhYUAIIrili1bfv7zn7/11lt6VNfU1PTII4/cfPPN33zzDQAwxh5++OHNmzcvWbLkN7/5TVVVFSGEUsofkj788MP33nsvf77JGHvssce2bt26fPnyO++8c//+/XC0w/pbb7113XXXvfLKK36/HwAIIYHb5avxTtt79+5dtWrVm2++OXHixJiYmI8++mjLli3JycmEkP/9739/+9vf+B799a9//fDDDwHg/vvvX7169SOPPLJu3bqXX375rbfe4it88MEHTz/9NCGksbHxwQcf/O1vf9va2qrvo54en8+nJ5LXRhUVFffee++dd965detWACgsLHzwwQerqqqeeOKJJ554wuVy8e8nhLz66qv3339/ZWWlqqqBQ74EQejs7JwzZ05LS4vP58vLy/N4POPGjfN6vQAgSVL3PAeAF1544YYbbli6dCn/8Xg5yf+vra2llC5atCg2Nvahhx568803U1JSGGMPPfRQlyPFw+XAHACA999//1//+ldBQcEdd9zx4Ycf8g+77JE+vrbHvAIA/nikrq7ut7/97QsvvEAIqa+vf+CBB7Zt2wYATqfzj3/8I28D42sSQl588cWQkJDXXnstJiZm2rRp+/fv5811/NDn5ubefffdH3/8sV6DdsmTw4cPP/TQQ/qxaG9vB4D33nuvy77oNwl8r5uamvgZy9vPTuPyQWhg4MVsampqfHx8YmJiQkICISQyMjI1NVXTtBdeeEHTtD/+8Y87dux4++23VVV97LHHdu7cKUnSa6+9dtNNN+3cuVMv/BsaGv7f//t/S5YsoZSqqsq/n1+5zz777H//+1/+CS+HAWDHjh033XTTww8/XFZWBgHFSKDu9VRRURH/WkLIkiVL9DTAsfUUv0+wWCwZGRm8b48gCIGlmdlsrq6uvuuuu6qrqwFg1apVjz32GC8ovvrqq5tvvvnxxx9vamrSs6jLEF6EEPpJTql9Xn8EGR8fv2LFio0bN37yyScA8Pvf/54xtmLFipCQkOzs7ISEBN6Rw+12T5w4MTs7e9KkSaIofvzxx4wxh8Nht9tnz54dHh4+duzYqqoqSumhQ4fi4+OHDh2anp4eHh7On2nGxcUlJCScf/75NpttxIgRNTU1jLEHHnggMTFxxowZYWFhN9xwA2Psiy++0Lerd/PgSX333XcBoLKykj+i5XvBH2tec801qamp/JOUlJSf//znvL0kNDR09OjRK1eu/OMf/8jrFcaY3W6///77XS7X5MmT09LShg8fPm3atMbGxi7puemmm/jW+cPW/Pz88PDwESNGJCcnh4WFFRYWbt++HQBmzJgxdepUAPj1r3/NE3DfffcRQiZOnMg7fnz22Wd6bjPGhg4d+uijj44aNSonJ+fdd99dtGjRxRdffOeddzLGVq5c2X3f58+fHxUVNWbMGEEQnnnmGcZYbGxsYE7W19ezo12JKKVOp3PSpElms/m1114rKCjgG/X5fGFhYYFHqqGhob29Xc+BqVOn8hy44447CCEXXnhheno6AHzxxReMsXvvvTdwj/ihv++++7rnFd/NtWvXAkB2dvbkyZNFUbzzzjt9Pl90dPTPfvYzSumqVasAYNeuXbwi5H9y9tlnT548mR3tL8SOPlt/5JFHrFbrvHnzhg0bBgBr165ljJ133nl6njz11FOMMX4nqR+Lu+66q/u+rFy5kjFWX18/ZcoUvteTJ092uVy7du2yWq3btm1j+AQcDT68fNuzZ4/dbn/iiSc2bdq0bt06XnTcfvvtCQkJqqredNNNoigOGTJk7dq1v/71r0VRTElJ2bRp06OPPhoVFZWdnR0REbFmzRpKaX19/eTJkx0Ox5w5c+Li4mw2m9vt1rdy33336ZPV2Gy23//+97t27XI4HGeddVZ6enp6enpVVRU79jI8Xj316KOP8hXuvffe6Ojo7Ozs8PDwb775hjE2YcIEvZ763//+x452ldm0aRPrVpqtX79+165dALB7927G2MMPP2wymRhjL7/8MgDwbvFnn302T3NWVtYjjzzCsKBACJ0hpxO4P/XUU4Gh/+9+97u6ujrG2NSpU+fMmcMY++KLLyRJcrlcdXV1APDAAw80NzevXr06Ly+Pt9CcffbZjLGKigoAePXVVxljl1xySVJSEi/a0tLSLrjgAsbYiBEjpk+fzhjbuHEjAHz99deMsezs7KysrIMHD+7evfurr75ijE2bNk3frizLra2telLfeOMN3nbLjkZ17Gjgfscdd0yaNIl/MnHixN/85jeMsaioqJ/97Gf8Q1495OTkFBQUWCyWwsLC999/X7/VCQkJeeuttwLTs2fPHl4HsKNldEFBwRtvvMF/5BFtYWGhJElPP/00TwAf4cTb3XmbzZtvvgkAy5cvZwGBe0pKyrPPPnvllVe+8847f/jDH/76179eccUVt99+e5c8l2XZ6XRqmvbSSy/xTJg0aRL/bWZmZmBOrlu3Tv9+ni1NTU0PPfRQeHi41Wq97bbbeH/TLkfq448//uijjwJzgO/dgw8+GB4ezqvthISEO+64gzHWZY8+/fRTxtiYMWO65xVPxldffQUAL7/8MmPsL3/5CwBomvarX/1q9OjRjLG///3vaWlpfH39vmjWrFkzZszQG7/1I/vII484HI78/HzGWHJyMk/Piy++qOfJzJkzGWObN28OPBYRERGMsd///veB+3LzzTczxngPHL4Jh8Px2WefFRYWms1mDNzR4KQH7oEDN++55x7G2IMPPjh27FjGWGVlZUxMDA98S0pKYmJitm/fzp+R8sj48ssv56UTb1A/ePAgY2zhwoWiKHq9Xna0ZAgsh81mc2FhIX8QumbNmurq6mXLljmdThZQvLPj11MNDQ2MMV4r8TRcdtllF154IS+B9Xpq//79jLFt27aFhobu2rWLPxsMLM3Wr1+/b98+WZZzc3MZY0888QR/RLls2TJetPIU8p76GLgjhM6s0+kq4/F4EhMTKyoqPv30U6vVOn78+Li4OI/HQwj57rvvRFFcuHChqqoHDhyIjY0977zz/vnPf0ZFRf3jH//gM9q2t7dfeumliqIkJiZGRETwYrS0tHTixIk8XJszZ05lZSVjzOv1zps3j1IaFxdHCOGdQ6677rqCgoLRo0dfcskl9fX1vArRt6soSn5+Phzt4G42mxljHo+HN8oqiuL1enl/RB7/8eeYel+Ozs7OqVOnMsYURZk4cWJqaurSpUuXLl2ampo6fPjw/Px83hfTZDJ1dHQcOnQIAK6//nqenoULF1ZXVx/JVkEAgMzMzPnz5//lL3+ZOXMm70PJh72ec845qqpmZGS43W4AaG5uFgRh0qRJPp9v/vz5AKA/LOYopWazeebMmbt3796wYQNvSNb7fQbu+6FDhwRBuPPOO7/88suf/exnOTk5fMhpZ2fneeedp+ckr4ogoD8P7wBaVlb27rvvLlmy5KmnnhJF0el08iOVkJAQFhZWWlpaUVEhCILZbOY5kJeXx788MTExPT2dMRYXF+d2uz0ejyiK3feox7ziKeH5f8EFF/h8vgkTJoiiWFFRcccdd5SUlBw4cGDlypXXXnstzwq9R5AkSV6vV++44na7+VNvt9udmpqqp6elpQUA7rjjji55wmfD0I+Fx+MBAJfLpe9LfHx8Z2cnANTU1AiCwI+7y+XKy8tTFAVncEeIUvr22283NjbW19c/8cQT/EN+sXd0dDDGmpubKaWdnZ38yd6hQ4ckSbrxxhtFUVy2bBnvauJ0OgVBGDZsmN/vX7hwIa8mAIAPMgksh/lTrzFjxsTHx19wwQXp6ekbN27k/dR5IRCYti711IQJE2JiYgCgtLRUlmWehuXLl/OemQsWLAisp/iuKYoiCEJra2uP5TOvNTh+23DZZZdJknTHHXc88sgjFouF36UghNCZdTqj6xhjJpMpLCzsiiuuuOiii2666abJkyenpKS43e6pU6fefvvtfOx/cnIyAKxevXrlypWbNm164YUX7rzzzs2bN4uiWF5ezqNnt9vNp/+TJKmzs5PHu83NzXxwDy8N+XgmxhgflvS73/3u7LPP/u677/7zn//ceOON5557LmMscLspKSkAwL9q7NixJpNpzZo1d9xxBwC8//77L7744jvvvJOZmcnbP3j463a7A8c/6T0vL7roouXLl1NKL7roIv5bq9X68ssvC4Lg8/mys7MB4Le//e3s2bO///77N95446abbpo3b15SUpKqqpIkrV279sILL/zVr3517bXX7tixQ38JFN8XvX6y2WyUUq/XazabeU/r7oNcRVEcOXLk008/HRISMn78eL3zvcfj0ffd7/enpqY6nc7x48cnJCTceeedBw8e5PcGcHQYq/6WJf6hpmmSJC1fvvzee+9tbm6OjIy88sorZ86c+c033zz55JOBR8rj8YSEhCiKYjabX375ZVEUfT7fyJEjeVYHztZMCDGZTJqmBe4R/xL92AXmFQuYaL+1tTUjI8Pn8/F+6ny+xddff/3AgQOPPfaYvhd85fPPP//JJ5+srKwcMmQIANxzzz0ej+e9994jhOjraJomyzKlNCsri+fJoUOHeIze47HQzxx9X/jJabFY+HH3eDyTJ0/2eDw4ITRCvFM7n2OXHdvRnF87fHAqL3McDkdUVJSqqvfff392drbf7+cN9vwK5QNAGxsbA7+EF1B6OXzJJZcAwOTJk7dv3/7111+vWrXqhRdeyMzMvOuuu7q/naN7PTVp0qT09HSr1aooip6G0NBQi8WyatWqzz//fPPmzS+88MIdd9zBh9bwL+lePvM94kWHKIrt7e18B++6664lS5Y8++yzXq/3f//7H74wBCHUG04/+PD5fJTSv/3tbz6f7y9/+Yssy+PGjauurp4zZ47b7X7nnXeSkpJqamomTJjQ3Nx89dVXDx06lE8t4nA4Xn311c8+++yZZ57x+XxTpkwBgKuvvnr9+vXvvPPOhx9++MUXX/DmVT2c0oecAsA111zz+uuvL1iw4OKLLwaA2NjYMWPGVFVV8e2+++67vFlFFEVN07Kzs2+44YY777zz008/5eG7y+WKi4sDgFGjRuXm5n788cfPPPPM4cOH9YH/vLTl/999991FRUXFxcV33303AMyYMYO35k6YMOG5557jgfg111yzZMkSnh5BEPg+8qTyrhQ333yz1WplAW8TDNwpSmlkZGRmZuY///nPb7/99uGHH4aA1nR9fa/XO3r06MbGxqioqIyMDK/Xy7fOBwno+56YmNjU1FReXn7llVeOHTu2sbFRjy8DN/rD4RcExtjFF1/scDiuvfbajRs3/uMf/9iyZcvChQsBICQk5N///jc/Un6/f9q0aTxmTUtL4znAd1O/IeERs9/vF0UxIyMjcI94Mq6++mr92Ol5FZjtDz300IYNG55//vnk5GR+mG677baXX345Kytr1qxZeh7yZP/617+22+3XXXfdpk2bnnvuuTfeeIPfs+kNb+ToFM4ul6vHPAnMlsCwgxzFd23KlCn6cX/++edlWbZarTjgDCEA0Odn7PKckA/rXLduXUNDA59AffXq1SaTKSYmhs9p+/nnn+/duxcA+CsX/vjHP65du/a5556zWq36JdylHL7zzjsB4J133rnsssvGjRv3y1/+EgB4009RURHvcd4leXo95fV6//rXvxJCMjMzIyIieBqWL19+8OBBl8uVnZ3N66n09HR9snlCiKqqISEhw4cPDyzNKKXx8fGCICxZsmT16tX//e9/HQ4HY+zrr7+eOnXqvHnzOjo6+AM9OM7AWYQQOn2n1LGGl9GPPvpoampqU1MT//Cuu+4CgMLCwpaWliuvvBIAEhISPvvsM/6o8amnngoNDQWAefPmHThwgBd5V1111YwZMwDghRde0Av9xx57jEdUjz76KB80mZKSwocT8S4ZfNTjqlWrxo8fDwDJycnvvvsuY6ypqWnRokV8u8uWLeN/y44Ovuzs7HzwwQd5BbB48eKioiL+q8bGxrPOOgsAHnroobFjx/KxiWazmY/m5FO7aJo2derUsWPH8oehlNLnn3+eN/w//PDDHR0dlNK1a9fq6Vm6dKn+0JYxdvjw4VmzZgHA5ZdfnpycvGTJktzcXEEQtm/fzhh7+umn7XY775Z94MCB0aNHA8ADDzwAAB999BEL6OM+ZMiQp556ilKampo6b948xtjs2bPvvvtuxlhjY6O+7zzPfT4fPyJjx44955xz5s6dyxhLSUnhA4h5Tq5evVr/fp7Ur7/+mo+7stvtDz30EG/zTkhI0I/U888/z3ftueeeC8wBxhjvic77LI0bN27x4sWMsb179wbu0Ycfftjl2Ol5xZPx5ZdfiqJ4//33A8Dw4cP37NnDU7hu3TpBEH75y18GZgg72qU1Ly+PPwyx2+2PP/44H9N2zz33jBkzhq88fvz4q6++mjF222236Xkye/ZsxtjGjRtlWdaPBe9Vdc899wTuC/9bTdP04/7AAw/4/f7t27fj4FQ0aOl93G02Gx9Jrw8Zf/DBB/nV5/P5br75Zjg61P7GG2/kZfihQ4eGDx8OAOecc87hw4f5hfz6668TQoYPH37TTTfxLnAsoNu6Xg7zYrm8vPzqq6/m9Rd/VMgYu/vuu9PS0nhxyv/vsZ46dOgQY2zLli1ZWVk8DcXFxYyxJ598ktdT5513Xk5ODl/HZrPxV0Pk5uZ2L59///vfA8D8+fPvuOOO5ORkxtiHH34YHh5uNpuvvvrq8PBwXtcMHz4c+7gjhM6gUwvcuY6OjoaGBn0eD1VVa2trXS4X/219fb3H4wlc3+VyNTY28vU1TYuNjX3xxRcZY3yoEAsooJ1OJx9pxDU0NPDQUFGU2tpaXpozxlRVbWho0Ld4vO0Gamtr4+V74OZ8Ph//sL29nW+3rq6uy9d2dHTwJ6E6p9PZ0tIS+EmP6dE3wXfT6XS2tbX5/f7a2lper/DBu/qaHo+Hf21tbW2XHdHzoampia/T3Nzc1tZ2gn2vr6/nh4ZvnU8Iw7rlZGCG+P3+xsZGfWd7PFI95kBbWxufXoanUD+CPe7R8fLK6/Xy3HA6nYFzSuzZs0cUxTVr1rBuNZ9+HJuamgKPUXt7e2B6+JjUwDzhg5V7PBZd9kX/2y577fP56urq9LeuIDQI+f3+urq6LiUPv/r4tclLPx7Qd1nm1yDHV+bT3TLG+OxhXXQvh1taWgJLIZfL1aVY7rGe6uzs5L/tkgZ2bD2l751+jQeWZvqrl/SCUS/JW1paeDobGhp4MRtYqCKE0E93TA+Bn954r/fE4H2R4eik2vqHAGC1Wh9++OEnn3wycDWeGr6sf9ijwC/kyz1uNzBV+jd32aLeWeXk+ysH/jkAEEK67GDgV3Xf1sl87SmNeuxx30/1S6DbYeJdR2w220MPPdTlSHXPgZPfoxPkVZfd4W+Gevrpp9966y1VVfPz8wP71XTfip7s46XnNPLkR3cHIXSqulyzJ1PmdxFY8py4FDr5NJy4aDrJyx9LCYRQHzjNwakQUFbqPwaWpHrBF/hGTz448oILLsjKymKMUUoDu33r/YwDX5AJAQV04FQD+pfDsSV499I/8Jt5J2z9c/1P9N92rwa6fBK4co87GLjpHr9Z35HA7+myZvfBqd2/5AR53r3Hdo85Gaj7XjDGzj///O5HqnsO9FiP9rhHJ8grPWGBu1ZWVhYbG/vaa6/xaZK7J1vfChz/tIFjzwE9TwKzoscT4HgHKDC1gNAgdoLC6njLPV6zJy4Au3xVjyH7jxbdPV7Oehp6LJr0lBwveV0+7HG107u1QAih4zmTLe4IIYQQQgihXtIPU9rxAUZ9v110qvr9SPFRy3hviRBCCCEE2OKOEEIIIYRQUMCXyJx5Ho8niB4pMMa6TMBsfHy6hv5OxclijCmK0t+pOAWKogRdgoPofKCU6q8AQ0En6K6O4wmuq+Z4FEUZAG+oDbo64njw6ugbpzM4FZ2YkY/3wIA53Kswe3sb5nDwwmNnNHhEjAOPRd/AFneEEEIIIYSCAAbuCCGEEEIIBQEM3BFCCCGEEAoCGLgjhBBCCCEUBDBwRwghhAyNMYYj/xBCgIE7QgghZGSaphFCACCIJhpGCPUSnA4S9R8GQPo7DQghZGyiKAIAIYSH7wihwQxb3FE/wagdIYROiDexf/nll5dccsmiRYu2bdsG2O6O0OCGLe6on2DUjhBCx0cpJYQcPnz4N7/5TWlpKQDU1dWtWrUqJCSEMYat7wgNTtjijvoaH2JVW1z38dPLFJ/CAAddBRMGgEcLoT7Ao/O6urrKysrY2NiQkJDy8vLm5mZCCJaZCA1aGLijvsarnPXvbFT9qiRLTMOmo2BC8GEJQn1CEATG2OTJk6+66qqGhoaOjo5FixalpaVRSgUB626EBinsKoP6FKVUIEJNUW3Z/vJ7ltxFBEIYxoHBgQEDII2qr1nxj7SG9HdyEBrgeMu6xWL597//feGFF1oslksvvRSHqCI0yGHgjvoUIQQIfPPW+rFzR4dEhTDKiICVUHBgAALAY1WHoiTT35JHU3xgh1Av4zF6SEjIDTfc0N9pQQgZAta8qO/wLptV+dVVhTVzrjsLu2kGEQpMALKjs3VLR8tvYjP6OzkIDSKMMUVRVFXFMhMhhC3uqO/wwP3rt9aNO2dMaHQo9tQMJgw0YH+uzvtlTGqiyUIZE/B5PRp8+qWbCiFEluUz/p0DoMsN7oWhDIy9AMMfEQzcUR+hGiWiUH6govZw3VW/vxKnMwsiGqMiET5prW5SfHfHDqV47FBvYoxpmmbA1mVCiKIocLT3eX8n5ydRVZVPN9nfCTl9hBC/388Y46N4+zs5p8+wJ/wpwavj9IiieKotmBi4HxdjTFXV0/hDVVUVRQmWtuQ+KzIYZSbR9NUb6yacP84eZvf5fKedRYqiiKIYLFXOaZ9I/UUvfPmPDBgw8DL29+rCh+OHWRjxqopopMxXFCWI7gMppbyI6O+EHEOSJONkICGEvyvUgHjCDJu8k8cYM9RBPz2SJFFKg/1w8PpXkoI+HsOr4zQ2dBpbCfoTpfec9tNJRVFkWQ6iwF0QhF4vMhgAgZKc0ubqlusfv4YxZjKZTvuqUFVVluVgqXL4lXnGn3T3Hl6L6Anmvdv/r7YozmS5PDpZY2ARTf2awB4EUQhCKdU0LYjOh35h2KPJE2bY5J08clR/J+QnGRh7AYbvm3GS8Oo4jQ2dxl9h4I56HzvyCsBv3t4w6YIJtlAr9m4PFhQYMKhWPP9tqngzfZIEhJLgfgaKEEIIBS8MnlCvo5QKolC8p6SluvXsa2bxNv7+ThQ6KQSIQMjfagtnhUZNsYdTxgR8/xJCCCHUT7DFHfU6PlP712+tn37ZVLPNHOwjogYP3klmr9v5bXvTqqwZlDEM2hFCCKF+hA2fqHcxyggh+dsKOlo6pl82lTFGCJ51QYIBAPy5Kv+G6CEpJhsQwOZ2hBBCqB9hCIV6HdXo+v9+O/1nUy12M2MMW9uDAgMQCPm8tbZa8fy/uAwGjGDUjhBCCPUrDNxRL6IaJQLJ31rgau2cccV07N0eLPj4Uy+lT9UWPJKYZRFEit1kEEIIof6GURTqRYIgAIN1/91w1lWzZLMU7C9lGDwoYwTghbqiOMl8ZUQiBXxPKkIIIdT/cHAq6i18zsd96/f7veqkCycwxgTs3R4MNMZMglipeP7bXPlBxhQAAMCwHSGEEOp/GEih3kKAUI1+9/GW6ZdOMVlNDOckCRKEgEjEP1fnXxAWO84WRrGYQAghhIwBW9xRr6AaFUShaGexq8U19ZLJwAB7twcFBmARpW9aa3d2tq7Pmo19mxBCCCHjwFgK9Qo+d/vG/22ectEk2Sxj7/agQAEYgMLg8dr8X8WmR0smxhiWEQghhJBBYKWMzjzGGAFSlV/dUtMy5ZLJwAA7yQQFBkwAeLulUpCkW6NTKQCOSUUIIYSMAwN31AsYAIHNH36fOXV4SKQDX5UaFBiAAKRVU16sK/pTYpZICOBzEoQQQshIMHBHZxillAiktc5ZdqB89uIZANi7PThQYATgqdqCbJPjXEcsNrcjhBBCRoODU1Gv2L5iR+KwhJiUGMYYNrcbHwUmANnnblvtrF+eOolRTRCxcEAIIYSMBZtC0RkmCILf68/5Zv/sxTOBAaPY3SIYMCAAf6jOuyF6yHBbmJdq/Z0ghBBCCHWFgTs6k5jGAGDnl3tCo0MyJqQzYNhPxvj4i1GXtdbU+b2/ic1QNBWfkSCEEEIGhEEVOmMYYyCApqh71uydunAyEMCXLhkfA8YYtGvq32oKfpuQ6RBElVEBDxtCCCFkPNiNFZ0xjDJBFIp2FXs7vRPmjwMclhoMKAORkH81lMSbLFdGJjIAEdvbgwEDYAx4RzQCQAjebCGE0MCHgTs6Y3iY/t3HWydfOEGURUopBu4Gx4CJhJT73O82VfwvYzIORzAyPVJnwAgQkQDeYSGE0GCDgTs6MxgDQqC+rKGpqnnx764AAGwBND7KQCTwp+q888PixtvCNcawub3fHa8pnS8fXQQfZY0+rd6n1fjUok7/oXZ/q0JfGxcbbRLxjWcIITRQYeCOzgxGKRGFrZ9tT8tOCYsNxeZ24+Nh+saOpt2dzk2jzmY4cXs/OZmmdIWyCo+a71JK3f5yt1rj0xp8aodKTQJxSMJQqzzSYUqxyVZRAIzaEUJo4MLAHZ0BjDFBENzt7sO7ixf97nJggHO3G59AiMbYn6rz7onPiBBlbG7vbTxA1xhoDCj7kab0Wp9a49UOdfgLOv2NXs2pUomATRSiTeIQqzg3yjI6xDTULodJgk3EO2SEEBosMHBHZwBjjAjk4KZDZrs5LTsVA3fjo4wJhPynqZwA/DwqRWMMm9vPuB6b0gVRkOUfpu3hTekFnUppp1LmUWq9ap1Xc2nULAihkpBulyaFmYfEyykWKdkqxZrFHjdEGVBgACDhQUQIoQFtcAXujDHGjgzAEwSBUsrf6ykIAl/gv8Wg81TxXjHbV+ya9rMpAEApFbAV0MAoABBoVPz/qi9+KWWcWRAoMDzpTxsvUwI7pgvkyEJgU7qfsgafVutVSto9pYon3+Vv9GltChUBbNKRpvQ50dYxDnOaXQ6XBKvY9ZgwAP5Cs4BvBgAQCOAMngghNBgMrsCdEBIYlAd2wuafY8h+GhhlQEj5/nJvpzd7zmgAINi73dgIMALk6drCibbwOaHRFJvbT11ga7pAiABdO6ZTgDqvmufyF7mUco9S5VHrfFqHSk0COASSGWKeFGZOscpDTq4pXQDCu9Z0C+YRQggNIoMrcHc6nQcOHKCUxsXFZWVlFRcXFxcXp6SkZGZmNjU1xcTE+P3+xsbG5OTk/k5pkCEEti3fMXxyhjXESjVsbjc0CiAA2eduW91W92XmTAo4CeSPYCfRmt6u0jqvWu1VD3eqBzr8FR5/i59qDGwiiTQJKRZ5dqR1TKg53S6HCiCrfpPV2mUT3ZvSyQBtSuePN/s7FQghFJQGV+CuKEpTU5PT6dy6det999335ZdfpqWldXR0tLS0rF+//pprrlmzZk10dHRycjJWLSeJUUYE0t7UXnaw4hd/vxHzzeAYHJm584/VeTdEDRlqtuGY1O6ORuqMAfQ4zQtlrMqjHuxQCjv9pW5/tVer96oKY1aRJFtMmQ55WrgjxWZKsUopFqlr4M2oW2ESY5QdmTOVACFksDSlBxYRXYoLLD0QQuhHDa7APSYm5rLLLtuyZcu8efMURRFFcezYsWlpabW1tVFRUfn5+SEhIbNmzfqJ9UeXDjkG91NTSwAA9n6dG50UFZcWq3/SqwZXDp9RfM7Hz1prahXf/QnDoaf3pBontSfpp+cwA+Bznx87zcuR7/RorNanVnu14k4lt8NX5labfBoQcIhCjFlMtYrTIu1jQ02JFim8p8GhNOBrAYACIYQIhAhBls1nBiHk0KFDu3fvvvHGG7/66qvKyspbb70VAN54441hw4bNmTNH0zRR7Lnj0CBEKQWDlSEIof41iAJ3PjK1ra2tpqZm2rRpLpcrMjJyx44d+/fvnzNnTm5u7nfffXfffffp61NKvV7vqRaXhBCv1xtETUeMMUrp6deUBIDB7rV7Zl81U9EUv9ffB9O3e71eSmkQ5bCmaZLU/9caAxAAXFR7sirvkZgMs09xMU089k6LEOL3+wFA0zR9JLfBqaoqiuIxbbcAGvthlhWNAWUMAERCBML7pRzZN4kQk0BEgRDCB+0yr8YaFZrfqRa51TIvrfZqNV61U9XMBOJkIcsuLgyXUq3mVKuUZpcl3k7OAJimappfYdrRTfNmetLtPWSMMZ/Ppw+FNwiz2dzbVy4vFRsaGjZv3uzxeAAgNDS0qKiIv/Ph8OHDI0aMgCC8b+w9fJpdvtDfaUEIGUX/BxN9hheCeXl5sbGxoihqmnb11VcLgrB+/fqamprQ0NDLLrtsxYoVP//5z/n6hBCz2XwatYiqqiaTKVheP/RTwkoePZflllONjZo1UhREi8XSB/UupfT0Dk2/YIypqirLcj8nA4AyJhPhL1UHM6yOxbEplIGVSMd7wa3JZOrjFJ42Igg8cOdDbBmACACCAACUUsqYVRSOtHczyl/xC+TI5alptManVnQoNT610KXscfqa/KqPEocsRMpCqt10TrRtbKhpqE0Ok4nph4uaAWMaZf6AXukEQOJF6glPTUoppdRo2dsHVxPfRHh4+JVXXrls2TIAkGV59OjR7e3tJpNp5MiRgV1oFEUxYLSq39ZC7wfThBCTyVRWVuZ0OseOHatpmqZpZ/D7VVXVNC1YStEe6YfDaLfBp4rXwvzpSvDqy6ujt/Xl1SFJ0qm2nA6iwJ0fA6/XGxoaCgDNzc2bNm2aMWNGa2vryJEjIyMjMzIydu7c+d13382ePZs3Ap1eO7RwNIw4wzvQm07vNoMAIQLZs3Zv+rg0R5idaj+h5f5UiKIYXA/T9ZazfkQBZIBCb+cnbXUrhk8ngkAAekwTz9t+T/DJEwRBliQ42t0FANpU+s+iFhMhv8+MkAC+aHBvbHQzAr9KCxtilas86oZmV5lbbfBpJW6lRaEREmlVqJeyBzIiUm1SmlVOtUk97r8GwF9TQAgRRTiNs5DPPxtE2XtmmUwm3m4CAJqmJScn8z6K0dHRgYGLYfOHJ6y3k8efgi5fvvy+++5ra2u7+eabn3nmGUEQzmC1wjcRXPVUd6IoGqF0/Yl4d4DgqtR61DdXRx/os6vj9HpnDLrAPTExMSYmBgCGDx9eWVn58ccfL1q0yG63R0dHM8YWLFjw/fffK4ryE9tHg6urzOndHPOXLnU6O8v2V17z2CIA6LNOuzzNAz6HzzQGQH5buf/ayKRMi0MDJh6nrd0YqT0pPFI3CaTSo0SZRJso8E/+VthyfXJojVd9urDlppTQz2o6omThQLvyy5wGwqDUo7hVbW60/awoy06n59/jYrPspt/nNd+RFjomxKx/ucYYHO3uwhHelv/Tzrsgyt5eoucApdRutzudTpvNZrFY9MCdEGKErmU94onvg+T5/f6HH364srLSZrO99tprV1111fTp089suWfYTD4llNIBsCNGPudPXp9dHX3AyHth3JT1Et6Nkjv33HPPPfdcvjxnzhwAiIyMvOSSS/onZcGGUUZEkr+10GIzDxmZDNg51cD4TO2ftlRX+D3vpk+mR6YzCUp8yhcKjAHIhDCAPxS2vl/dmWqTnxkVNSHMktvuYwBf1ndWedSlVe0r6t3VXmV2lHV+jDXNJlsFodmvdqhscZIjxiTudHrHhJjfq+o4L8Y2JsTsp4w3sxDSw7BddGapqpqUlOR0Ot1ud1RUVEtLS3+n6Mf1wX2XHp3zVwQG9pA5g4F7cDV/HI9hmkV+koGxFzCAWiUMfnUMusC9y2Rk/EfeQ47/PwCeu/UNnku7Vu+ZeMEEAMDp2w2Lvye1U1P/Wlv4x8QshygF0RSQ+hzq+kBPvqDPbv5hdcdT+a2SJJS4/As7/MPtskAg1iSm2qDap96SGnZTSsgv9zYMs8kSgSsTHPyv3qnsaPRpUbIoE/JiifNwp7JkXCxlYBqcU730rYiIiJtuugkApk+fLorikCFD4OirrGFAPGf/iQghfBTEM88888ADD3g8nuuvv37atGmAmYMQGoSBe+AtVOAcW/qbUw17j2UoDBghpLGisa2xbfRZI6EP+8mgU8cEIH+rLcww2y+NSKRg9Khdb1PvcQ71Ko+6p82X5/IXdyp1PvVAux8ATAKolMRbxH+Oic6wyVEmscGn/SG/+fGsSJtI/jk6ek6U9a9FLa+Utd2VFqYypjAmEhAI1Pu1BIUqlG1r9U6PsBwZuop6EyHEarUCAO+RqAejA6CP75nC8+SKK66YNm1aS0tLdnZ2f6cIIWQUgy5wR2cE0xgRyY6VuxOHJYTHhmFzu2Hx96QecLd/0lq9cvgMBgFDOI0hsE098KWkvE29U6OVHrXMre5t8+W2+2p8qkYhVBISLNIwu3xVomOIVXosr2lZnTvZJj2eFTk13AIAzYr2m/2NDw2LcEhCi59OCjMDwPhQ82G3wl94dHSWGbCLwj3p4W0q/X1e0/uTEoix8gYNapTSpKSkpKQkIz+1Rwj1MQzc0Snjw1L9Xn/R7sMLbjkPsLndqPT3pP6+6tDPo1KGWxy8s3t/p4vPTQkMmABEOLZNXWNwuNO/p82X7/KXdCpVXtWrsRBJHOmQz422DnOYhtvlZMsxBddbY6NvS1WGWOWRISaFgkjg/+1vvDDWNipE7lBptVd9trj1xTEx37V4Z0aaAYAA+CjTGACAV2MdGh1ml9Ns8r9Knb9JD9fYYHmJKTI43n1oYMw3ghA6UzBwR6eMUSaIQklOmebXRkzPBByWalSUMZGQ95urGlTvA/HDKfRPu12Pberi0VeTtipahUct7lR2O315Hb4GPyWERcpiilWeGWmdEm7OsJsiZKHLF1L2wwTqFoEsiLUDgMZAFqBdoRIhG5rda+o7J0VaHsqIuC4p5J79DRfH2S+OczAGAoE0m+yQBACYEm62CoQB3DM0/NWyNp/GLBi2I8PATu0IoS6C+7UFxuR2uy0WS7AUuKfxAib+3HbpHz+ITo664Pb5fM773kthdx6Pp2/e9HRG9NcLmPiF7dSUuXmb/z5k9AVhcSc5JpW/ROMnviGoSz/1QCqFApd/V5s3r0MpdStVXhUAomRhdKhptMM0zGEaZpejTV2bGOnRb9Oj/x8SrChEFEU+Nb3h8Vcy22y2/k4IOh1n5OowAkVRJEkKllL0eBRF4e/j6++E/CQGeUnfT4dXR9/AFnd0ygghrtbOqryq835xDv+gnxOEesKb25+szh9rC70gLK5Xx6TqbeoAIHSb+8Wt0XK3WuxWdrZ697f76/2aREi0SRhqky+Os00JtyRbpZBj33dEA2aSgaNfKxznTCMA0rGjyjX2w68E8sO36ZE9hSOJ1NiRBPNWfGxtRwghZGQYuKNTw9vX96zZG50cFZcWyygLjnbOQYZH7bs7navb6r/Omg29M3G73lVdJF2HOVR51F1O74EOf1GnUuFR3BqLkIUxoebLE+2ZdlOWwxQud31KozFgwAgQgXRtUz9VXeLv7t8mdFuTdPsrhBBCyGgwcEenhgChGj2w+dCkCyYQQihjGO0YECGEAvtt5YG7YtOSTZYzMia1xynV9a7q1V61xK3sa/Nvb/VUelWFsnBJSLbKk8Mtvx4aNqxbP3XeKK63qQd+FUIIIYR6hIE7OgW8ub3yUFVHc8f488YCADa3GxAP01+tL1WA3RGbrv20qF1vVu/SHUVl7FCHstPpPdjhL+701/k0s0CG2eRp4ZabQkyZDlOKtWvxEtimjs3bCCGE0KnCwB2dAt7dIufrfRkT0s02M6MMJ4I0GgoMCFT5PS83lL45dKKZCBRO4anI0TAdKOs6AwwFKHMrhzuVnU7vXqev1qdKhMSYxeF2001DQqeEW+LNohxwPnSZ+wWwTR0hhBD6aTBwR6eACERTtPztRVc+eCnw6WUwDjMaBgIhj1Udmh8WM90RcZIzyQQ2q1v4O0UJAICPsgPtvu1O36F2f5Hb71SoQxTGhMoL4+xZIaZRDlNYt4kaNfbD3C/YrI4QQgidQRi4o5PFZ4Es2F5osZtTxgzhr2Hq70ShY1BgAiFr2ur3uJ3rs2ZTxo4XtPNIHQImgdGbww+71cMu/14329nqqfepMiHxFnGkw/yzhIjxoeYYk9h9/pbAruqSUafQQgghhIIdBu7oZDHKiEhyvslNH5smm2SqUUEMjrnqBwkGjDFwMfVP1Xm/S8iMls0aMPHYRyI0YG71wObwIpeypdWT2+4v7FTqPIpDImPDLJfG20c6TKNCTI5uczVS7KqOEEII9TkM3NFJYYwJotDR4qopqj3nhrMBAJvbjYYyEAn5Z01Rgmy5LmoIH6LaZQpzfTb0FoUe7vTntvm+a/GWuFXGWLRJzHKYbksNG2+DWLNkCXiJRpdm9RNMqY4QQgih3oOBOzopvLm9aGeR2WZOGJYAAIZ9qdjgxCdTz/e4/tdctXz4dI0xlTHTsdOrt6t0e6t3h9N7qEMpdysU2FCrPC3C8vMhIWNCzLHmoy8rVRWVMmxWRwghhIwGA3d0UngAuPfr3HHzsuHovJD9nSh0BGOgAhBg91fm3hg9ZKQ1BAB4V/QKj5rf4d/a6tnp9DUrmkMUUm3y7EjLo8Mj0myyLSAk19vmFcoAQMJmdYQQQshgMHBHP44BI4R0NHU0VTb/7J6LoXdew4lOFX8jEp/tUSbknaZyjWi/T8yq92nft3h2On15Hf4ar+qQhPGhphuSQ8aEmseEmLp8A58EJvBlpXhoEUIIIWPCwB39OKYxIpK93+yLSoqMSYnG6dv7UWCfdd7pnLeL53S4HqnMH02HXr69vt6vRMlihkO+LjlkVqQlwSwJx84Dg5PAIIQQQsEIA3f0Y9iRfjIF24tGzhrBP0F9jPc4F44dEtzk0za3eLY7faUubY2SN8QSdrYjbkSIOD7MPMwu9/jnBDusI4QQQkELA3f0I/h87Q1ljc3VLePPywacT6ZPdJlnXZ/IpdarHXL5Njd7trV62xQaJgvjQ6zhIe2pqrphxMwoSQ78c5wHBiGEEBpIMHBHJ+XQ1vy4tBhHuIO/hqm/kzNgBb7BVG8a91HY1urZ3OzJbfeVe1SLQCaFmW9JCRsbas5yyAB0dv6+J5NGRkmyn1EBiIBTwSCEEEIDEQbu6Efw9vX9Gw7MXjQD2JF5Ifs7UQOK3jrOG9f5G0y9lOV1+Hc6veubPBVu1SqSNLt8fqz93GjrEKssBRyBe8oPDJEcl0YkasBMBKf6QQghhAYsDNzRifD29YayBl+nL2NiBhDsJ3PG6J1hAl9iWutT1zV6trV481y+DpUNt8tzo6wT080TwsxyQM5TBipjJoF872r5ur1hfdZsBtgZBiGEEBrgMHBHJ8Lb13PW5camxYRGh1CNCiK26Z4+CsAYnwpGb1yHVoUe7PB/2+Te3OJpV2iMWRwbav5zVvT4MFOI9ENu67PB8P9lQvyMPlx54IH44Qkmi8aYiF2YEEIIoQENA/cTYeyU50/R+3+fxt/2C3ZUj78lAmGMleSUTTx/PF/HIPtlkGScDJ69KmVAQCI/zIBf6FK+aXTvdHoKXQoFmBRm/uWQ0CnhlvSACWEYY9rRQP9ICM8ACFDGRCI8U1sYJkg3Rw9RGRWBnJE8CRzAEFyZ3N9JOGWGSjMOXEEIoaCAgftxMcZUVT2NP1RVVVGUYHmxKGNM07Qef0U1Kpvl6oKa1nrniJlZlFKqUaB9nMAeKIoiiqLBQw0+xpTwlnWqiYIIjFW5lH3t/nXNnt1ORQVItEiTQuVfp4SMdMg2kwgEQGM+v58BkKOhFOGdagK+WWPMTIS9ntZ3Gis+TZ8iadR/RmNARVEgqCI5RVGCaMw0pZQXEf2dkGNIkhQsGYgQQoMZBu7HRQiRZfnH1+tGURRZloMocBcEQZJ6OBOYyAghxbtLE9LjQiNDAEAUxT5PYA9UVZVl2bBxBu8PIwek7qDTva7WtbPVW9TptwhkZpT1ocyQKeGWOLPY5a+ICOYfy2MRgAA8UlpwS+zQ7JAICmD6kb84Nfwu4PRO/v4SRHEnpVTTtODKXoQQQgaBgTs6Lj4O9cDGgzOvnA4MKMUO7j0LHGYKvE8LAadCc9t9XzW6t7R4vCpNsZtmRFj+kBmRYZf1zuja0Zna9b/6Ufw9Sq83lHVq6n3xGTR4WpoRGgAGzOVGCBkA+4J7YSgDYy/A8EcEA3fUM973oLGiyePyZEwYivPJ9Ii/kTRwzvU6n7qm3r2l1Xuow08ZmxFpvTc9fHKIlGS36H+lx+unOq8mD9Mr/J5/1he9lTbJRAR6UtE+QsGE998z1BgAjhCidyQzYPJOiaqqlFIjRyc/ihDi9/v5Q+OgPhyGPeFPCV4dp0cUxVPtoIGBO+rZkflkvsmNSY0Jiw3D+WR0gdOu628k3dfm29TsWdPgbla0OLM4Jdxyd1rYqBCTSfj/7J13fBVV2sefM/X2e9N7gIQAofcuIB0bNkTFirxWbFjWXfuuZRVXXV3Xuq4rdtkFBERQUKpSpQeSEEJ6z+1lyjnvHycZLwnEJEAa8/242eHeuTNnZs7M/M5znoIAgCiKGlbHtPV58BFCAI8VHrrEHj/WGkmt72fruHR0OggIoQ7ildcY2rAO27zmQwjpRA5mp4PjOIxxZ78cVOae0mG1c6HfHa2gFXvp9B1F55xA6uzreXvzhkwdBF1oCuxMUE+uaYoJbK0JfFfh2+MKVYTUflbx2iTLmEhjz7C0MJiASjAhRDjj84cJYRD6X23x4aD7ne4TMIBubdfpqnTYBw5tWIdtXvNB9bR3Q86IrnEU0OF9M5qJfne0Dbpw1zkFhBDEoPLj5c5yV/9J/aBL3IqtAxMgJ9c0rZHxbmdwVbl3Z21IYFCmVbi7h2NilNFWn3Nd+wnU/RC1JjlRg2YAAAKnKj9bfOT55H42ltMTt+vo6Ojo6Jxv6MJd57Qc+SUnpluMyWbqRLn2zhYN4k0BwCmrayr8P1YFD7pDHIKJ0cbnMqPGRhoN9a7/BEAlhDlHsQCEMAg9UXh4iMlxiSMe66pdR0dHR6dLgDEGgM6Si6/d0YW7zimoyyez6fDoy4ZDvb97ezeqLWhkX4fCgLKtJrC8zJfnl6MFZmSEYWGPmL5Wkas/H+EFTblzI6YxAIPQD+7KDe7KH/qMx4ToPjI6Ojo6Ol0DKtnPQxNh69CFu05D6M1TVVztd/rSh6YBnBf5ZNST7esVkrKi1L+x2n/UK8cI7KxY02MZEYNsYoP1W5EZpqUQIISACyuPFh58Mql3omBQgbC6ctfR0dHR6cxQsaGq6saNGx0Ox9ChQ9u7RZ0DXbjrNITa1/f9sD86NdoR58AYd9UJLFrzKNy+XhxUNtcE/lfiPe6Xkwz8xGjjX/pE9TDxDdaHM8kM09JGEmAReqb4SC+D5bqoFN1JRkdHR0enC0AzSN58883Lly9nGObpp59+5JFHurDkOFvowl3nZOrzyRzbkzfwwv4AgEgXlIla/nVquXbJeGW5b31l4IAnGC1wl8aZnukd1df6W0FSRXNeb9uTQWX6Rk/Vd66yDX0uIFCfUVJHR0dHR6fTQgX6rl27VqxYwXGcoiiLFy9euHCh0WjUfWaaRhfuOidRl08mv7K2zDVgUn/oQn4yjfOvV0nqzzXBpaWeLI8cI7LjI41/6hWRUZ/MkQannlPn9aahmWQCWH248MDjib0TeIOeSUZHR0dHp8vgcDh4ng8Gg6FQqGfPnjQHvK7am0YX7jonQYAgQNnbs6OTI80Oc9cY+NJ8L1r+dYWQtRX+VeW+X12SiYVZseb70yKG2n/zX1cIMPX5HNsTQhiEni4+3EM03xCVqoKu2nV0ziMIIbQsaHs3REfn7EPr3WZmZv71r399+eWXo6Ki/vGPfwiC0DVUxzlFF+46J0FfEoe3Zg2aOgg6eT4ZmiKGDTOZ76gN/q/Uu7E6YGKZ0RGG9wfH9rfWVUYK93fnOsAR00wymz1V39SWre0zDhOCQC+4pKNzvkDlC1UwupTR6ZLQXn3nnXfOmzdPFEVBEEA3tzcDXbjr/AZ9PbirPa5Kd/qQHtBp/WQwARymv4/55C+LPZtqglUhdUK08YXMqEnRJu3AVEIAENvm/utNQDPJeIn6SOHBPyT26iaYdCcZHZ3zB/ooLisry8vLGzZsmCiKunbX6apgjK1WK9R7vbd3czoBunDXCYMAIDi8JcsR54hJiSaYdC7hjutTNDIIGIDSkLK+MvBFiacqpPY087d3s82INZvrJxDU3/LDdLhjpJlknis+kigYbo3upmeS0dE5f6Dy5YcffliwYIHT6Rw0aNBXX30VFxenyxqdLgn1mQG9AFOz0YW7zm9QB/ecnbk9BnYDavXpOFboJlHro04p6yr9/yv17naGYgX2ykTz9BhzirGuq2slljqsBxCV6Zs8VctrSr/vM17PJKOjc15BRcxbb7114sSJ6OjoTZs2ffPNN//3f/+nC3edroo+m9QidOGuUweNgvLWeCtOVE67dQp0Bj8ZfHIVpCyPtKLct6rMxyE0JtLw8ZC4zPqUjlp90w5+TDSTjA+rDxTsfyopM0Uw6k4yOjrnIRaLBepLwVNHAl3c6OjogC7cdTRoHGr+wQKWY+PT4qBjvyfUsMQvIUz+V+pdXurL8UmDbOKfMiKnxRj5eoVOU7B3WPt6QwhhEHqk4EA/o+36qGQ9k4yOzvkGNas/8cQTRUVFu3btuvPOO2fNmqWnl9HR0aHowl2nDirTD2850mtkBiDomA7udSZ2AI5BAHDALX1Z4vm+0m/nmIvizG8MiIkTWbqm+luKmA53FKeDyvRVrrJNnur1NJNMp2m7jo7O2YE+inv37r1u3TqPxxMZGdneLdLR0elA6MJdpw7EIFVRTxwsuOqR2dDxHNy13I4AEMDk60L3ygr/UY80NtLwUmbUpGgTXY1WWerILuyngyZ8LFdCjxUeeiGlbxxvwECYjnQJdHR02gyMMc/zVLXrKWV0dHQ0dOGuAwB1+WSO780XjHxynyRaP7W92wQQptdpcw55pM+LPd+VeaJE/uI481sDYqMFBgAIACF1VU47nWSnEAQsoEcKDkywRl3mSNBd23V0zme0VBtaNncdHR0dOBPhTgjRgtz1x0pnB2PMsMzBzYcTe8YLRgGrmGHb2Z8SA2BCNEeXFWW+L4rdWV55TIThr70cUxMddatpVZY6cx+kmWQ+rS7cH3BtypyI9XtKR+e8R38I6OjoNKb1wh0hxLLsWWyKTntBCGE4RlXUwqyiC2+cCO36wiAAmBAGIQaAQagwoPyv1PtVsZdnYVas+fX+sXEiC1IQE0Kb2TEmBs4IKtMLpeBfio++02OwjeV0JxkdHR0dHR2dxrRGuFN/u+rq6tWrV48aNcpgMHTr1k13wuu8EEwAoCS7NOAO9BreE9ovEaRKgEV1FZF2OUMfFrh/rg1kmPk/9oq4KNZMG4UJ+BVi5ju3iT0cQgiD0L0n9s6OiJ9kjdadZHQ6BdSRowH6W0BHR0fnnNJi4U7dY4qLi1999dVgMJiSknL8+PHRo0f37du3U5SHwBjTMQb1INRybNEPNZ/C9m5mm0Mge2dOYkaCYBTafgwWno5dAviu3P9Rfk1hiFwQafxieHxv82+52GlV1E7qxX5KMBAWoXcrjlcooS+SRqiEMOdh99PphJyPz0kdHR2d9qbFwp1K26KiohMnTlx99dUAkJCQUFpa2rdv31MaYDoa4UMLGvRDdSp9CZ2fryKGZQBB1raj464aDfUJ3dtm16TevRsAvBg+OuFaeaLKX11xaaL13dGZMQILYc4zXUmvU+hxZQe9i8tyvkgfaWBYDLqLjE4nAGN8/PhxVVURQhhjhJCiKHa7PSkpSZ991dHR0Tl3tFi4U+E7fPjwiy666Mcff7Rarf3797/++uvhZE3cYcnOzs7Ly0tOTu7fv39lZeXx48dHjhwZCoVcLldMTEwoFKqsrExJSWnvZrYpLMfWltYG3IEeg3pAm4xetKSNCIBFKCegflXgXJ1fHhX0XG5RR6awqXGmGIFVw9Y5101qFxBCBODegn3zo7sNNztUIKyu23U6A6qqfv3114FAgOd5g8EAAIFAYNCgQbpw19HR0TmntFi40ycyy7Jz586dNm3aDz/8MHLkSEFoB/+KVuDz+dauXZuWlub3+71e77fffmsymfx+/6BBg9avX3/dddd99913sbGxKSkpneJwzgoYY5Zl9/90MCo50hFnxxgjdG4HYNQxhprPf/XIH+ZV7yiuSFO899rRwBieYXivrNbKJKqru3pTX/aXS7NljB+Kz1AIYUG3t+t0Dnief+yxxwDA6/Xu3btXFEWXy+VwOOB8nbfU0dHRaRta6eN+5MiRTZs29ejRY/PmzbW1tTzPZ2RkdHwf92AwyDBMnz590tPT8/LyBg0aNHjw4OXLl0uSFB0dnZWV5XA4xo4de4aqvXOl3WUQAwDHfj2ePjQd6hp/rvaFARioywOzxSm9m1OZXVY5lPE/E8Gmm0QZmAAmoAIgxDGoCVfvznWGT9laAsAitMfnfL/yxDe9x4gMQzqMaO9E55bSBfpDZ4QQIsvyW2+95ff7nU6n1WodMGDA8OHDzx+rh46Ojk7b00of94KCgtTU1J9++umqq66yWCw5OTkZGRkd38edZdno6Og9e/YcOXIkNTXVbrdjjGNjY/1+/+HDh7ds2fLggw9qK2OMg8FgK95AwWCw449hKAQTVmAr8ysrCyqn3z4lFApilZwL/Uity0aOkTF8Wx36tMB1vLRsAuu/0cEkGfkAJlUBGYAgAASgYhwMBgOBwOm2Rs9wZxEHhBBFUXie/+0TAASgEHLvib13RiRngugN+DuOk4wsywCgKEp7N6S5yLLMcVxn6Q8YY0mS2rsVDRFFsaWPLISQ1+vlOO7ZZ59du3ZtRkbGTz/9BCdnm8EY04chwzA0MQBNItxguUGqAB0dHR2d09FKH/eRI0d+8MEHLperR48eW7ZsueSSS6CTGOrmzJnDMMxPP/3kcrlsNhvDMJIkIYSMRuMtt9yyYsWKm2++ma6JEKK+my1FVdVWvAXbBVpoqfhwidluTkpPJIQA//u/aj6E0KwpwDCMguG/5b4Ps8tdtTVTRGlRIu/gzQGCvJgwDPBhupXBmOd5URRP22yMRVHsFP0NAKhACRfuCiECw/yx8FAkJz6U3EfFxNiRIm/piRUEob0b0lwYhulcwp0Q0kT3bhdacfYIIREREWlpadnZ2ampqc899xwNdgrfFJXs2nL45w2Wu8xEhI6Ojs45pZU+7g6H4+GHH6af9O3bly50ZKmq5Z7fsGHD2LFjq6qqxo0bt3XrVpZly8vLBw0aFBER0aNHjx07dmzatGnChAnUCNS6FwnDMCzLdoqXEL1kR7blZI7tgxACcjYzuGMAFoDW6Pqi1Lckp9xdVXWZVbkwibcJRp8KHkIQANdojzRZZxPdiZ7hs9XONiDclIgBBIAN7splrtLve40HhJgO5stPm9qRb+cGsCzbifrD73bvzgJNyTVt2jRq+3jmmWeioqLg5J6zYsWKQ4cODRo06OKLL96xY8ehQ4fmzJljsVh27dp14MCBa6+9VlGU7OzsYcOGFRYWFhcXjx49uv0OSEdHR6cT0PrKqTk5OceOHQMAWZZHjBgRHx/fkV0b6TsmPT29sLDwf//73+zZsxMSEqKjo1esWDFv3jyGYWj7p0+fvnXrVlmWw+2jraAjn4oGSEGp/Hj55BsnAgABgs7YYaMuwyMgBoFC4L+l3g+OlirumkuMyuRUwcgZ/BhcMmEQnIly6URnmPoA1C0DICBVirQwf9+LKf1SRKNebunMoWe4E/WH9m7CWUOW5cWLF0uSJMtyRUXF5ZdffuWVV2qOgi6Xq7q6+u6770YIVVZW5uXljR49+ttvv73ooouys7NHjx69evXqKVOmHDt2bOjQoT/99NP48ePP30oaOjo6Os0DtfQtogWn3n///ZMmTUpISHC73ZdeemmPHj06i2P3ucbv9xsMho5/KggmiEGHthz+ccnGO/9xO8u1coYhHEwA1Wv/z0u8H+WUB2uqrrTiiQ7OyHFeTDAm6PcGBxjjyMjI9PT0060QCAQMBkNnebtrPu5a0vqrc7cnC8bXUwcqhHAd7yioB3YncpXpdD7uwWDQZDK1d0POJpIk/fWvfx09evT06dNp/AlCqKqq6v33309LS5sxY0ZlZSUAZGRkrF+/PiYmxmw2p6en//DDD3369Nm3b5+iKP369evZs6c2AOuww5tOd3ecjs5115wOWZap52R7N+SMaBwH1UnR745W0Iq9tNLibrfbMzMzFyxYEBMTo33Y8aUqhBnnqA2+ceXU8ydAihCCAGVtOZrUK5HjWaziM3G0VslvGWO+qQj880hpsKZqtlmZnMqLLO9Twa1ibYXzE6raXy8/ViKFPk0bgXVbu05nBmOsquqqVaskSWJZdvfu3Xa7ffr06doj1Gg0XnrppSzLrl+/vlu3btHR0YqiWCyWmpqaiIgIVVXNZrMkSfv27TMYDJrLJQAQQoLBYAfU7gghGrpNAxXauzlnhKIoncWl83TQy0Hqae/mtB5CiKqqnSgfwCnR747WIQgCx7VMirdSuEuS5Ha7n3rqqeTk5Orq6gULFvTt27dTWNzDQ6AaLMP5FCBFCEEMkkNySW7J1PmTAVrv3R5e/fS7qsDbR8uqKiqvsChTk3kDZ/RhIiln6hjTBaD5H3f7nG+VH1ueMUZkGJWQ8/yc6HRqqKc+DcRHCC1atGjs2LEAwLIstYM4nc74+Pjo6OiKigpVVQOBAMdxVVVV6enpLpcrJSWlpqYmNTU1PT396quvfuedd1JSUgwGA/2t0Whs7+M7NfQV2wWMo4qitFQudEB4nscYdwETb9e4HPrd0Ta0MqtMVFTUSy+95Pf7Q6GQ1Wq12WzQSSzuOnUQQAwqySkN+kJpQ3oAQCu822kpJQYBi9B2l/y3w2UF5WWXGKVZKYKFM3gxeM57KzsFAwCAH6u3H//1Dwm9+xmtumu7TqdGVdW1a9fKshwbG4sQCoVCLMtmZWUNHDhQM7ZxHLdy5crk5ORAIDBixIgvvvgiPz8fIdS9e/fPPvussLCQ4ziz2ayqKsuy/fv3X7Zs2dy5czu46aSzmxI1OldkyOno7LZ2Stc4CtDvjraiNUMKQojFYvn5559/+OEHhNDUqVOnTp3akQ9S53Tk7MpN6pVoMBpacfk06XnUr/ztaOXuE6UzxOBDCZxDNPowuHUrexiEEARw74l9/Uy2BTHddNWu09khhNTW1hJC1q5dGwqFRowYQXPpDhw4kBZjBoC4uLjJkycfPXp01qxZPM9PnTr1yJEj06ZNo2+NI0eOTJ8+PRAIjBs3jhAyfvz47Ozs88dTUUdHR6d1tLJy6qFDh15//fXFixezLPvQQw8lJCT069evU7jK6FCoY8yRn7PHXjUaAAiBZipJAoAJsAhYhEok/GZu9bq84pHE91o8F28QvRi5VaJb2cNRgRg4YUl14a9+1/re4zAhumjX6exwHDdv3jwA+P777+fPnz9x4sSioqLS0tIGq3Xr1q1bt250OTU1NTU1tcGy0WikK7Asm5mZ2XYHoKOjo9M5aaUTDw0+sFgsLMsqitLZgyrON6h9vba0NuAOdO/fjRDCNE9LYgBEgEWgAvwjz/np0ZJ02fnnSKaXxeDDyKUSBLrf9klgIBxiDnpqnynOWpI2LIITMCFMhymSqqPTauhjf+DAgR9//PHOnTvz8vKmTp0KJydJCK+QSgjRjPENlulPdNOPjo6Ozu/SGh93Qkj//v1vuummN998EwBuuOEG6teoP3M7DQQAwaHNWZGJEZGJEZIk/W5wDwEgBBgEgGBlReBvB4sNrqoHIsiweDEEqFYlrC7ZG0Hd/WSC7yrcd1dsj7GWKBV0JxmdLgIN3nrooYeOHj1aXl5+yy23REdHN3gRhC8jhLQ6WQ2WG6+so6Ojo3NKWmNxp8/Za6+9NjExkRAyceLEs90qnXMLAUAAx37N6z6wW92/m0QlwCJACPZ75b8eKsstLp1nU6Z04xHDulUCQDpN1cq2BQNhAf2h8JCDFx6M66noru06XQVCSE5OTnx8fHV1tcFgSEtLq62tlSSJvhT0eCcdnfMKLaNlJypi3XlpsXCnD2WXy/XMM8/wPM8wzLJly5566imHwwG6yaQzQAhhGOSp9lQVVs+8fTo0mf8fE0AALIIqmbyWU706t2gK53swmbcKBq9KQNWt7KeFRqB+4yxd6Sz9IWMMixAdL+nodAEwxp9++ukVV1yxefPmqqoqs9kcDAYzMzPnzJmjC3cdnfMNhBDHcRzHdZnEMh2ZVgr3/Pz848ePL1++HAAuv/zyysrKyMjIs986nXMAwQSxqOBQIcuzcT1iCZDTyUlqaAeAz4q9/zhUlBioeSma6WExelXwKEQPP20CmrW9WAr+ofDQq6kDkkUzBj3Hjk7XgWXZZ599FgB69+7N8/zhw4crKyunTJkCuvlGR+d8gmrCqqqq119/3e1233vvvRkZGfro/ZzSyuBUh8NBCHn11VcxxjzP7927d9euXRMnTkxOTtYDjDo49HY6vO1oxvB0ACDqKcbHal3eGDjsU545UFpYUjrfoVyQKkqAXDJhkJ40pikIgEoIAvi//F8vj0i4yBEflCRD5y8RoqMTDiFEluX3339/5MiR//rXvxITE2VZnjlzpv4K0NE5f0AIqap62223ffPNNwDwyy+//Pjjj2azub3b1ZVp8eOVyj6e5xcsWNCjR4/09PT58+czDKMoCp0i0YdZHRzEIFVVTxw80WtULwhL6UAhdT4eoAC8kFN73fpDKTWFb6ag8ZFGD4YQ1g3tvw8mhENocWlOiKh/SeqLddd2na4I9Zk0Go2lpaV2u/3+++8/fPgwdKEiLDo6Ok1Db3aXy/X9999HRkZGRUVlZWXl5eWB/hw4l7TY4k5FXnx8fHp6ekJCwgcffNC3b985c+Y0WEGnY0JlelFWMcuxKX2SAAAxiOC6G6ze0I421gSf3ldkdla+EIMyLAYvBq+CdcneHDAAi9BmT/W/qvJX9RrLIaQS3N6N0tE5+xBCoqOjY2JiVq1adf3112/btm3o0KGgvwJ0dM4bEEKEEKvVOnLkyI0bNwJA//79u3Xrpqv2c0qLhTstT71t27aCgoK9e/dWV1fX1tZu2bJlzJgxhBCaIEynw0Id3A9tzorrHmuwGLCKaSUmraySSyVPH6rceKzwenPwom4iRoxTL6jUbAgQIFClSvec2PtsUmZvgwUDYQDpyl2n60EF+uWXX37xxRfzPK8oCn3+634yOjrnFTzPL1my5P333/f5fLfeeqvNZtP95c4prdTZHMfJsrx+/foFCxZUV1fTHECqqp7dxumcfRAiGBccLhw2awjUv3pVQjgAFsGqisBz+wt6eKteT+DjDEavCkD0VI8tgJrb7z9xYKwl6vqoFEwIgxD53XSbOjqdEDp9V1hY+P7776elpfXq1Ss5OVmrjaqjo9NB0GT0uYgZpRtMSUn585//rH2oq/ZzSotPLsuyhJARI0bYbLaLL764f//+BoNh1KhRegGmjg/BhGFQZWG1p8qTOaYPAACDVAIixzhVWLiv/Omth26E6qe7Gxwi51YJAqLb2ZuPSggL6O/lx3KC3ldS+mPQw+p1ujJ0lvzZZ5+12+2CIMTGxtI8Y7oFR0en40C1maIooVDo3L2SMMYY42AwGAwGz9EudDRaKbVZlr3iiivGjRvH8/ysWbOMRiPoro0dHup2dnxfvi3GZokw08wnHIO+rQjM2nC06vixNxLxlGijRwUZ64b2lkEjUDd6qt4sO/ZR2jALy4GetV2nS0Nf1YIg+Hy+vLy8AwcOxMbGtnejdHR0foOa2NesWZOZmdm9e/d3332XEHIuHNCZMM76xnUa0OJTTPuBz+d7++23H3rooa1bt/7nP/+pqKig1pdz0USdswW9o7K2ZmWO7UNTx0gEHjlY8di2I/OYqme7iSaB86iY0RVnCyEADELlcuie/H3PJffta7SqhDD6WdTp0jAMw7Lsyy+/HB0djRBSFOXKK68khOilE3V0OgJUktXU1Dz++OO5ublOp/MPf/jD/v37EUIY64FXnZgWC3d6vfft27d+/fq5c+cmJSUlJSXt3r1b+0qn44Ig5A+VF1SnDenOIrTXJc/amJeTk/P3OHlqlNGNQcV6JdQWQwAwEIXgW/J2z3LEXhuVrOj5H3XOAyoqKj766KNvv/327rvvfvzxxzmO++CDD2hS5/Zumo6OTp2ZVZblQCDA87woin6/3+12g56rsZPTmnSQGOPMzMzU1NS1a9du2rQpPT39+uuvBz0coWNDMEEMOroz1+4wJmckvnfC9fqv+XMNvjndhBAGt0JYXWq2Cuok86fiLEDw1+T+GIDTVbtOV4cQ8txzz0VERGCMDx48qChKbW3tXXfdBfqLQEenY8AwDCEkLi7ujjvuePLJJyVJWrBgwYgRI/SUL52dFgt3er1tNtuLL774yy+/8DwfFRXF8zzoPu4dG0wIAyh/e7YlLfGOY679ew//JQ4NsBtcCsFY5fTJ7VahAmER+m9tybKa4nV9xrMIYUJAvxF0ujoY46ysrPfff59l2WuuueaZZ56ZMWMG/Up/EejodBDozfjAAw/MnDkzEAgMGjRIl+xdgBZcQjq3IknShx9+eP/997/11lsTJ06UJOn5558/ePAg6MkEOjCYEJZBSJKP5la8ajCF8rLf7Mb1sYlOhege7a0GE8ICygp4Hik88M/ug1MEo0oIo6sWnfMAjLEsy7/88svPP//McVxycvKePXuOHTsG+iy8TofkHAVldhb69OkzZMgQaoNv77Z0Ndr+lLbA4k79pQ4fPvzZZ5+99tprS5Ysufnmm+12+x133EHTQeoxSR0TlQALAAj9fXvBBgbP72ucFsX5VfCreuqY1kMAAIEfq7cd33NvXM8LbTHU+t7e7dLRaSOmTJly+PBhhNDEiROXLl3q9/uHDRuWnp5+LnJF6+i0GtohaZ88bzsnHbcwDHN+Hv45RQvsaTMN3DLhDgA+n4/n+QEDBsTExLjd7jfeeOOctU3nLKAQ4BBUy7Aoq+LIxl0LEpnxsWa3pKJWpwLVqQ9IZQHde2JfD9H0QFy6HpCqc17B8/yTTz55yq/0uXidDgWVqsePH4+OjrZareendteGLjpnBa0XEUJqa2tra2tjYmJsNlvb7L3FT1hVVWkygV27drnd7k8++eS11147fvw46FllOhgEABPgEOxxyxdtzOULj11XXRTbI05iWIT1ykpnBHWSeasib6/f9U73IQiA1R+KOucZuBH6LLxOR4MQEgwGb7755qFDhw4fPnzr1q16MkSdM4f2IqfTmZeXV1paGgwG21ICtMDiTu0offr0eeaZZxRFufnmmwkhoVAoISFBFEXoijFJrX4Pta87HQIg9cnFl5b5ntiec6slON2qfhdS7ImRWFY6hVd7EyewfU8vBmAR+slT9VppzvKMMVaWUwlhqfPMqSD1tGkrzwDa1M7V4M7VWuh4p7cVT2/dsq7TwVFVlWXZ5cuXf/zxx1arNTs7+5lnnlm7dq3edXVagWZlxxi7XK7a2tpAIIAQavvu1ALhTlscGxt76aWXNrFCl4EQoihKK36oKArLsu34aMAEEIDAMy8crf3i0PHH7aExsead2woMVqMt0iIFJcScdKU6WlQxxlhRlCZOPv22XfobBsIjJjfku/34nhcTM/sbrEFJYhFqwoBDO1Inujvome9E7zba4M5yhn+3e7cLHMd1lhOoo9MiaMcO9z8+P71l2h5qnugyp5r6srvd7pqammAwCAAsy7aLCabF6SAJIY2nmbpkxANCiKa5bCmyLPM83166BwPwAATgrn3lB47l/y2OJJlMXoarKa6OSYriRR6ruPHF6lCBxQghjuOaOPmKovA8315dLoDVG0/svSk6dU5MqkqIQRCaXp++JFrXl9oF+iTqRA2GTqU7Mcaqqnau06uj0xmhuuqyyy676aabvvzyy549ez733HMMw2B8ipegztlFC4el8x7t3ZxWoo3xVFV1Op1OpzMQCDAMQwVee02ctqYAU+e9Bl0elQCLoFoht2wvgMqSV5NZA8f7CMi1Xk+Nt8/o3oqs6OkfWwcBoC4xN+ft6mWwPJHYRwU9+aOOjo5OxwUhZDQa//Of/zz33HMOh8NqtUKnmk7svNBwWIxxp1aMCCFJktxud21trSzLhBCO49rd0VHvvl0HhQCL4IhfueynnNjqohdTeZ7jgioWBa62pBYBOOLsWMW61GwdKiEcQn8uOVIhS+92H4wBGL3Sko6Ojk7HhsqslJQUmlKmvZvT9aEn+dixYzfddNPMmTP/9a9/QceL6mka6kUiSVJ5eXl+fn5ZWZksy9SdvSMcSIst7jodE5UAh2B9dfCh7ccuQbU3phi9BBFCqDd72fGymNRoXuSloKRPEbYCFQiH0Jc1RZ9XF33Xe5yBYbHuJamjo6PT4UEIaWJLf2i3AdTQ/thjjy1duhQAtm3bNmDAgJEjR2KMO/JcR3jkg9/vd7vdXq+Xxqd1BCt7OB33JOo0H+oh8+8i731bsu4QnTcnmNwYCCEIgGEYOSRXFVXH9Yhr72Z2VlRCWEC7fM4/FB76V9rQ7qJJr5Cq02q6ZETQ+UOXyYfdNQ6kmYeA6jnX7WkdHbltLUI7ClVVDx48aDQa4+Pjg8EgrancwaGN93q9RUVFBQUFTqeT+vk008reQdNB6nRAaLJ2FsHLubVL9uc+F6NkWo1OlWgDMoZlqotrCIHIhEhF7liJLDoFGAiLULkcuilv11+SMsdZolS91tJ5gyRJZz3nEiGEzrq2lwkHISSKYgcXCh0t1ZVGp8u5dDo6Vy6m0yFJEkKosx9Lu2QeOxepdeiFUFWV47iFCxcuXLgwEAgMHTp06tSp9KsOZbemUAcYSZK8Xq/T6fT7/TSslmXZFuX7VxSldbUsWmHK0YV7J4Z2EBbB00eqvjmY+1oSSjSKbpVokSAEE5ZnS3JKbFEWS6Q55As1SASp0zQECBAIAb4hb+fsiIQbo1MVQrhO+3rQaREY49raWvoEP7tbJoRIknR2t9l8JEmKjo6mxTc6Mh3zHa8td8DmtZTOewh03MuyrMlkCgQC1JNBVdV2HA+fCW1f24F6rdDU1WfrpGl3BxW+d911V0ZGRklJydSpU2NiYujIpONcHarXMcahUMjpdLrdbjoIpKiq2oqBTZtVFNGFe2eFABACDIKHDlZsOXLsjRTWIXC+MNUOAIBAVdTq4prk3kmEED2dTEuhtZbuy99rZfgXk/thXbWfZyCEHA4Hz/Nn8XFMFQbHtduzt7q6ur123Xw6bCYKeuE6bPNaRDt2wjOHzlx98MEHn3/++YwZMx566CGj0djejWo91JG6jXd61vdIN6htdvr06XSBJmM5u/s6c/x+v9Pp9Hg8dH5PS9GrJbJskXDnOK7NHgsd7lTqNAcCgAAQgvv3l+/OPvZmN97AsQF8kmonhHA86yp3+d2BhJ7xiqx23pnEdoEa1/9WlrvL5/yxzwUE9ESaOjrnOx3HZHiGUHXSSV8KNDX4ypUr77nnHkEQtmzZgjF+6qmnFEXpgALxd2kzSy01tHu93hdeeGHPnj0TJ0587LHH4Ox5GYUfBa35QxVwu7uWhXd1VVVdLpfb7aZeMVqAwRlegrZ8MnS+Lq5Dbe0IwcJ95ftzjr2WygscGzpZtdP1WI6rKqo2WAwmuwmrLfDW0qHJH1c6y96uyPu211gby9H8j+3dLh0dHZ3zHaq0srOzASA6OrqkpGTXrl2t25SW6qSD5zw5i7zzzjsvvvgiwzBr166Ni4ubP3/+uaiR1BFq/mh6nf4NBAJut9vtdtOM7J03T8B50U27EnRMxyC4Z2/5wZxjr3bjBJ6VMGl8IRGDVFUtzS1LSI9neZbgLmIoagNoQGpW0LOoYP8/ug3qZbCocIozrKOjo6PTXkyePDkuLq6kpMRoNM6bNw9aZTkOV+1dZjrldNDzc+DAAQBISkoCgN27d0MXmkfSoEdEjxdj7HQ6CwoK8vPzKysraW6Adh9UnAm6GulM1NnaARbuKzt87NjfunE8x51StQMAYlDQG3TXuGNTo4mqO7g3F5UQBlCtKl+bu/O+uPSZ9jiFEFY/fTo6OjodAyqyR40atXr16qeffnrNmjVz585taRw5zRmybdu2MWPGZGZm/ve//+1Q0ZPnAnp01113ncFgKCwsTExMvOWWW6BLZEmiNEjY7/f7y8vLjx07VlJS4vF4AIDjuLPiGNO+6K4ynQYCQKAuGnV/bt5rqRx3etVOY0EqTlQKBtERH6HIbZ1qqpNCAFiEQhhfnv3zNHvsvXHpqh6QqqOjo9PBoG+0YcOGDRs2DFqe3JCu73K5Fi1atH37dp7n77zzzr59+2ZmZnZhnxl6XDNnzvzhhx8OHTo0cuTIwYMHQ5cQ7uHe6oqiuFwuj8cTCARUVaUuMXSw16n1uoYu3DsNNF/7k0eqt2Yde6Mbz3Gn9pCpgwDDMmXHyiLjHaKRD+qJIJsBAcCEIATz8namCKZXUvpj0Ast6ejo6HRQJElSFMVgMLRUelIXZ7/fX1tbK4qi2Wyura0tKyvLzMzsGtquCQgh48aNGzduHJybbO7tAk3nT73YvV4vzefIMIxW9LQrXdZOP8w6T1AIsAhez3OtOpT7SiprOI1fO4UQQCwKeoPOSldCRoKi6PlkmgUmhEXo/hMHPKr6YdrQutQ97d0qHR0dHZ1TQp2VW2Ewpjm8ExISrr32WkKI2+2+6qqrRo4c2YnM7RhjWZYVRWmpJKV5yhVFoZnvz13zWlTAqEU0OGS/319WVlZQUEArntLjon5TXUmva+gW906ASoBD8FGh9/29Oa8lgEPgAk3Y2gEACC8IpQVlqoSjk6OwgnX5+bvQeqgvl2b/7K3+rvc4ATEYiJ5GRkdHR6dLQgX6M888M23aNK/XO3nyZEEQ2rtRzeUM0yy2QWjmOR3/0GiEYDDo9Xo9Hk8oFMIYU38YbZ0uKdkpunDv6KgEWATrqoOLd+f8OVpOMokNqyydCoRQ+YmKiASHYBTkkKxb3JtGBcIi9Fl14b8qT3zXe1w0J2CiO8no6OjodHEQQuPHj6fLncVvhLZz7969b731VkJCwqJFixwOB9Wp1EWkdbMQZ6ttdGHr1q0Mw4wZM+asbDP8uoRCIZqF3e/3ay7sLMt2YaXeAF24d2ioat/nkR/+OWeRzd/PZnQ3T7XLklyeV9F7ZE+GYerKNemcBhUIC2iDu/KPhYe/zBjRQzRR63t7t0tHR0dH55xDPTq00MYODnXmycvLu/baa48ePQoARUVF77//PrU3t6L+FPVpOYsZEhVFefTRR999910AuOeee1588cUGtvDmEC7WqX09FAr5/X632x0MBmmt067qwv67dA5frvMTAsAiKJPw7T/nzeVcF0Q2S7XTsFR3tUeWlcikSEVWoDM8jNoLlRAW0D6/67bje97qPmi0OZJa39u7XTo6Ojo6bQH1OWkD1a4oCvUsb3odWZab8A6nXx04cODo0aPJyckmk2nv3r0ul4thmNra2scff/yGG2748ccfoXlaVovgZFn2zF3SVVUVRTErK+vjjz+mp/Tjjz8+cuQIwzBNH3WDJkFYSv5AIFBRUUGzsJeUlNBypwzDdGEX9t9Ft7h3UGjK9hCBW3cUDJMq5ySbnM1R7QAECMezpdml1gizLcYmBaROYUVoF2g0arEUvO7YzscTe1/iiKfW9/Zul46Ojs455PyUO+2OZg5vwifnd9ehaQ379++flpaWl5cHAMOGDXM4HBjjxx577L333gOAH3/88bvvvhswYEDTsbZ0F9XV1b/88ktSUhJNDdlAN7cUjLHdbjcajbW1tQAQGxtrt9ub9kFq8C3NDxMKhXw+n9frpf7rcLJ9Hc7vPqwL9w4KTf746MEKvqrknlRDs2ztFAIEk8rCqthuMQiQ7idzOmiqR6ciz8ndfk1k8oKY7rpq12kDMMaqqjZnRrs5CS5Ot47m6qqP23XCoamsaU6V9m7L73AmCvIM1efZhQpTWZZfe+21PXv2XHrppfPmzWugVmmDZVl+8803Dx8+/H//93+jRo06pd6lwj09PX3p0qVfffVVTEzMzTffTFNbHjx40GAwxMTEFBYWZmVlNS3cqXtMYWHhDTfcsGnTJovF8u6771533XX06dS67Dosy0qSlJqa+uabbz788MMMw7zyyivJycm0yzU+LXCyh5Isyz6fz+/3BwKBUCikpWanxvsuk4X9zNGFe0eEura/X+DZnnP870msjBhoXn8lhLA866py+1y+pF6DVL3u0mkgQBAgmeAb8nYNMNmeSeqDdb92ndZBMCDmpIUm1iVEEARBEBRF0dIgEELoa5K+nDR/U57nZVmG+ld1g3Xo/D7P83Qk0OC9qOXHaP4Mtc75AFVCfr/fZDK1d1uaQtOsrQgYDf9JR4g3pW148803//CHPwDAihUroqKiZs6c2VgcP/vss88//zwAfPvtt5s2berZs+cp208fAkOGDBkyZAj9RFVVo9E4ZsyYbdu2FRYWJicnDxo06JRyWQNjzHHc5s2bN23alJycXFxc/NFHH11//fUcx7ndbpvN1rqDpQ+ryy+/fMaMGQBgNBpPdznogqqqoVAoEAh4vV7qvK496OimtB+2rj1dEt3HvcOBCWERbK0NvbYn908xxCoKMibNffAQ4HiuqrCaNwiWSIuq6okgTwEBAEAI4Ja83QJi3uo2WCVEP1E6LYBgIBgIAYIRx1O9jji+/nMMBNd1tDCoKWv9+vVvvvkmx3GCIPA8T+3igiDQWWCGYejnwWBw69atPM83XkdbliRp8+bNwWCQ5/kGdbw/+uijO++8c9++fedVsgWdJqDdoKamZuHChTNmzHj44YdDoRA0WxIRQqiL9rnoTnQsGr5lhBB1bm6F7Ka/zcnJUZQOYbqi6vmnn35iWTY5OTkYDK5fvx7qvdUpLMsqivL111+bzeb4+PiKiorNmzc3WCccmoudxpXS5wZC6Nlnn3333XefeeaZFStW9O7dG5rMyUjPTEREBABUVVURQhISEmpqaq6//vpp06Y9+eSTkiRBqxQzQghjbDQajUYjNUNoG9EuhyRJtbW1JSUlJ06cyM/PLy0t9fl8NP86x3ENnmY6DdCFe8eCACBAlTK5b3v+7eZAH6vgU3ELLhICjHFpbmlCWjzHc3q/bwwBwEAQwB35v1YqoS97juQQYhDSU7brNBfEIo5HHI84DnG8Up3tWXene+W1ofwf6z/nEccDc9J8JjU1VVRUPPvss0aj0ePx/Otf/8rKyuI4LhAIfPnll4WFhXT5008/LS4uZln24MGDX3zxRUFBAcdxPp/vyy+/LC4u1pZLS0t5nj98+LAkSUeOHKEaRVVVlmX/+9//er3eJ5544u233z5x4kQrEk3odD3o6+Ddd9996623duzY8be//Y3m/WiOzwztvRzHUVF1dt8sdOPhs0kAsHnz5sGDB/fp02fhwoXNHy3Q32ZlZY0dO3bEiBEXXXRRVVXVWWxq66CtuvLKK1VVLSoqioyMvPLKK+FkVU3v3Isuusjn85WVlUVFRdFEik0MPGjOR3re6Gpms/n2229/+umnhw4d+rtTDXTvM2bMeOqpp/r373/RRRe98MILTz/99Oeff37gwIHnnntuxYoV0Lzu0RjNs4XuhbYkFAp5PJ6Kioq8vLy8vLzS0tKamppAIKCJdV2vNxP9gd6BoAGpDIKH95YMkasuijO4FMK2RE8yLBP0BZ0VzoyRGRhj3cG9AYTm6gH0YMH+wwHPt73G8gjpKdt1mgshwLA4UKlW7APE0oAS/9631fJ9wLK+jX8ggUdYczzBMhCFsaexjnQgqnYTMgyjKIrRaIyKilqzZo0oim+99dZf/vKX//znP7IsZ2VlLVq06Ouvv+Y47ssvv5w/f/6vv/7as2fPN954449//OMnn3yiKMobb7zx6KOPasv3339/fHz88uXLVVVNT0+nxi0AYFk2EAiYzeaFCxdGRER0fG9mnTaA9o1jx44BQGxsbFFRUXZ2NjRDJ1EJ6HQ6//nPfwLA3XffTbOGnxVjNt1Ofn5+QUHBqFGjRFGksYmPPfZYdna2xWJ55513Lr300hkzZjTH65o26Y033ti7d29ERMT333//1ltvPf3004qitOPwlarYm266yWazHTp0aOLEiVSUNzgchNDTTz+dnJxcWFh45ZVX9unTp2lfl8ZojnZ0Xu53W0Xb8Oyzzz788MMWi4VeCACIiooqKipq6ZgnPK5A6xuKolCf9WAwGAqFJElCYXSBZI604aTxBOu55LwT7uGjQDrHpLlSaYaE9ppco27WHxZ6jxQU/TNV8BLEoBZ0BkIIx3JFx4sFoxiZEKFIHWKWsEOhEsIh9Hjx4c2e6h96j7eyHAHQVbtOsyGIQdhXFjz8GbAiAACWsTMfOANiOBJyBo98yZoTCFZA9gu9ruAiehJcp9upHElMTBw/fvzUqVPLysqOHj3q8/kOHToUFxd33XXXBYPBsrKyX3/9dcqUKVu2bNm3b9+oUaNuvfXW9evXr1mzJiEh4Zprrvnhhx9WrFiRmJg4Z86clStXFhQULF26tKqqas2aNVo0qqIoV1111datW5944glCyIsvvti+p6xD0QYez/QVQ98m7VUE55RgjFmWvfHGG5ctW1ZUVJSWlvZ///d/zWxkIBC45ZZbqAl2x44dn3/+ucFgOPMmUTPzsmXL7r77bo/HM2LEiK+//joyMpKGcmpVdUKhkOb63PQGtXBGqH+Pt4teDxcSWpdDCF155ZXU1t64H9J/OhyOhx56SNtI8/uqNjhvRV5LjLHVaqVxMrfffvv27duLiooGDx48ZcqUJtpwykOgtgmMMc25HggEJEmi/jx0hfC0MNAZ9Lqmy6Eu1QdBAIAAASAAhIBhCYOAYQjbhvf6eSfcw0OYw58CDYaJbQ8hwCKU41f+vu/449FE5NmASlpYsQBYjinNLYuIjxCNYtAXRIwuSX9DAcIh9ELp0VW1pd/3Hu/geL3Qkk7LQAxRVS66v/WiDwEACCAGfDteC+7/gKghPnm8ZcqbjGiuE+uEEKyGV1GgYk6SpGPHjm3bts1kMgWDQagPJDUYDKqq8jzvdDpHjx6dmJhYWloKACzLqqpK1zEajYqiaOsHAoGhQ4dWVFRs37591KhRkiTR2fPNmzcPGDDgrbfe+vrrrzdv3nzJJZfIstyhRGTbQ42R9GSe03rv4cKxLSMjG2igxvulRz1x4sRNmzbt3bt32LBhffr0+d0N0sCMrKysn376KSIiAiG0cePGrKysoUOHnuGZ1IY37777bllZWUxMzE8//bR27dp58+ZhjJ999tmFCxeWlJRcd911F198Mcuyzd/Xgw8+uHPnzkOHDl166aV33333Kc3P1DJ9jq4O3SyNAA7fBfXhbsIcro36aF9t5u6aM/rSgtQbb5YaLunnl1566bp1644cOXLBBRckJSU12PIpbep048FgMBgMejwe6hmvWdbpmlrO9Y6s1H/T6ASpGBFALAMMAyxDGEQYBhhECEEqBkxXwBBSkNMn1Hi5Wi831cSYzUBIWxTOOe+Ee0VFRU5OzujRo1mWPXLkyLFjx7p169a3b9+Kioq4uLhgMFhZWZmamtrGrSIAGEDBcO/uohmMa7Dd5FJIS1U3wzJ+t99V6Ro4eYCqqLqTTDgKIRxCr5flLqkq/K732FheJAC6atdpDTQsFeiLiDENu5ePG0JCLr7bZCSYiSIDQkDglG5qNKGHJEnV1dVDhgzZsWNHQkLCrl273nvvvcrKyjvvvLN///7R0dHFxcVWq3XDhg0ej+fYsWOLFi1asmTJBx98cOTIkUWLFn3xxRfvv/9+Tk7OwoULKyoqZsyY8dlnnw0ZMkTLJOPxeBYvXpyWllZcXHzzzTdrLjTnM5p60KJ1m5+0pEGAXWPCN1JdXf3222/n5ubOnz9/woQJZ0W7N2cquPG3JAwt9FNV1X79+vXr14+m3jObzfSHkiRpqTwaW6y7d++emZn5yy+/AMCoUaNSU1ObEIsNYkybaDA9OXa7HQBoAqWYmJi1a9cuXLjQbrc/99xzY8aM6d69e1VV1YYNGxISEi644AJo8pLRJmVkZGzZsqWqqio+Pr6xTtWm2ZveVKuhUbyPPfbYRx99lJmZ+Z///Cc9PZ3uKLwxmjd/AwOi5u3W/N0hhPbv3//JJ5/ExcXdeuutkZGRjY+r6Q1qK2OMBw8eTBO6N57iCHeAkWVZkiTqAyNJEp3xo3pdFMUOZVkndf9rZDiHOpF9ku0cEYYhBKsMy0gy6w8x/hDnlxh/iPWH2FofV+Xmajx8tZev9vC1XlaSWUmBQAji46TUhDZyTz7LUSYdHKfTuXLlSqvVKorilClT3nnnnV69esXFxSUnJ69fv/7aa69dtmxZfHz8mDFjzuR+9vv9BoOhRfYtmv/xheyanw4eebUbH4QWm8oJJoKRL84u2fvDgWm3TkYsar7L1bk2QbUUjHFkZGR6evrpVggEAgaDofkXSCaYR8y/KvNfLs1Z1WtMhsHSlrZ2+hzneb5tdnfmUJOJpgI7PrIsa4kIziIY46qqKrvdTvO6nPyl9nwmAAhRexImUGdipyufQkgxDLN79+6BAwfu3bv30KFDY8aMSU1NVRTl888/v+CCC/r161dVVfX555+PGDFi1KhR2dnZW7duveCCCzIyMqqrq7/++uvJkyf36tWLLk+ZMiUjI+Pw4cN9+/bdtm1bbGysxWKhD674+PgdO3Zs3bp1xowZffv2bZBbo7q62m63i6J4dk9Xh4WeE7fb/dxzz+3du3fSpEl/+tOfACAYDDbH36PBuyAUCiGETnl3eL1ei8Vy3333vfnmmwBgt9vp1EeLUmI3zr/RxJoYY1qJk/on0AXqVaKJdfo5NeJSpUhXAACe5zdt2nT06NGBAwdOmDCBOktoUKFJEUXxwIEDH374IULorrvuGjx4cOvyfDc4TGpXPnjw4N13333w4MF77rnnjjvuGD16dFlZmaqqGRkZR44ccbvdM2fO3L59OwC88847d9xxR/iuaZHRBp05/JKd8lWOMT548GBCQkJMTMzZ1e60bUuXLp0zZ47VavV4PNdcc80XX3wBTV7QVr8j6JAyPz9/8uTJ1D19wYIF7733nuYyRBdUVX355Zd37tw5efLkhQsXwulHLFq3aeBiRL1fAoFAIBCQZVmWZdrTws3q1BuQEHKqB2YbEe7ZQup0OjBMnTdLuOEcE8AYYQIqRoRAUGZcfs7l41x+zunlaryMK8B7A5zLz3r8nDvAufzIGwQGAccAxwLHAseAKJIoixxlkyNM8g0zxRGZxraxuJ8vwp120+Li4lAolJaW9r///W/ChAlffvnl9OnTMzIySktLDx48mJiYWFVVNXHixDO8k1sqK6kE2FIbumvjob/FSglGIYRbrNwJIYKB3/ntHqzikZcOlwNy8/1kOqZwT0tLO90KzXzjUhQADuCz6sKnSo4s7TlqsNHW9iG77Rsa1VKo6asTjTTO0eklhFRWVp5GuDdcF4AAMNRF5nQrabPkoVBIkxrhT5vwO/F0y+EHS5epVrjtttsCgQAAGI3GN954w2w2a+uEp0MGgOrqaofD0YkGZi2isXGanuG//vWvf/zjH6mp9bXXXsvJyfn0009Hjx797rvv0gIxp9MxCKF9+/a98847drv9wQcfjI6OlmW5wfOnpqbm9ttv//HHHydOnHjixInDhw9HRUUVFxd/9tln1113XYP+2fxIKqqw6V8lDFVVqXLSDOoQ5ofQYPvUAurz+bQUorQfchy3ZcuWDz74ACHE8/ytt946fvx4muIDTh4/0E9MJhP9kGXZYDBIa3txHEeLz9N/huc50bKdhC/Tb095pF6v1263Hz9+fMCAAag+J0lFRcXatWuvvvrq2NhYj8eTnJx84MCB8K57SuF+upNMP3S5XPPmzdu2bZvdbn/nnXdOmU+91dBb9e2337777rsjIiKcTufkyZO///77xh1SluUffvghFApdeOGFdrtdkqRW3JK0a61YseLyyy9PTEysra3t3bv3hg0baEg6wzC0Pa+88sojjzxCf/LVV1/NmTOHDtJO1wlpf6M29VAopNnUWZalJhLa/Ro8WOjnAND4gam5ALVaWWnbO6W7OQAg9JtGR6je7xyBgpE/xAQlJiAxQZn1h5hAiHUF2Fov5/RxtV6u1svV+nhPgJUURlZAUkBWQFJBxWAWwWoEi0G1GlWLUbEZ1AirEmmRIyxKpEWJtMp2k8qxmGMIx5KkpBSzxdq6o2spnUZMnCG0uyQlJQHAvn37jEajxWKJjo7ev3//4cOHL7zwwr17927ZsuWBBx7QfoIxDgaDrehnwWCw+Q8CDMAA8WH0xJ7CuYIngTe4gyG25RHK9J4pz6/IHNdHkiT6dG7mb8/iY+usQM88VSGnhJ7h37dIASgE2zjxa2fxEyVZHyQPGMyIHr+fa1u3gU5ncacPX0VR2rshzeXcWdwJIZpbanN+0ZzNSpJECAkEAtqUPd0L1TSyLGvLNK6LSqLwz6l0o59TazrG+F//+lf4LgKBgFakqUENJkIILXQS/qEoih3qIdBqTqe/Dxw4AABxcXFer/ell16qrq5mWfbbb799/vnn33777VPWsqUXqKqqas6cOTk5OQCwb9++ZcuWhZ8oqpxefvnl//73vxaLZdWqVUlJSSzLFhcXp6enDx8+vPGQ4JQ+LVQn0atMVZFmRKdo4X0NNhK+0FgY0UmeH3/88ZdffjEajbNnz+7evTt9O6iqmpuby3Gcw+Gorq4+fPjw5MmTg8FgAz2n9Xyv16tpetrlOI7zer3hj+IGMq6BZNeEO4XKfSr9DQaD3W5XVTU1NfW666779NNPAeCuu+4ym82JiYkGg6G8vBwA+vXrR30wfvdmP+UK9G5as2bNt99+GxUVdeLEiTfffHPmzJno7EUj0L5x7bXX/ve//926dWtsbOzDDz9MT5fmnEPXfOKJJ15++WUAuOGGG9555x1RFFvRBrrNQYMG9e7d++jRowAwZMgQGmmquZUDwLZt2xBCKSkpBQUFBw8enDNnTgNTHcZYkiQq0CVJkusJt9wLglBUVLRu3TqM8bRp07SO9LuNpJ1QFEVVVX/3J9StRVPn9GRplvK6vwgQIpggjAFrtnMMQZnxBDiXj3Vrf/2cJ8DS/7wBzhNkPQHkDQIA8CywTJ3hnGXBKOA4hxRhUSLMcoRFcZikCAu2GFSzQTWLKl0wChgAMEGE1O2XEKDGe0kmkqwY20pKnS/CHeofN7QU8FVXXeXz+ebMmUMfaiUlJREREddcc82KFStuueUWuj5CqHWB86qqNv8tqBLCM+itY7Wis+qK7mYfAZFvsfGbEOB4tqKgEgGK6xaDMNIKsjSzwR3N4s7zfBNT+dTE8rsHqAIxMeyKmuJHS7L+lTZ0si1Wwaq5zQU0NbJ2IuFOT2wnssgyDHOOhLvP56MK4yzOTFIl3UAmhv9TW25wV55yHW1NWkxH+2fThVca319n/ey1F36/nwpEzQxMD+2mm25avnx5WVlZ//79J0yY8M9//jM6Otrn81VXV59uU/SVkZOTU1RUZLfbCSGbN2/2er20Zk04dCMGg8Hr9V5//fU9evTYv3//3XffnZGRAfVe9ZrtHGNMpbn2lyokzelZM09CmBynV/x3+2EDx2JRFIuLi7/66qtQKCTLciAQWLRoEdWRPM8PHjx4x44dwWDQbDYPHjyY+sidbi9ab6SbdTqd1dXVSUlJoiiers4RCSN8yw3M+dqR0qpkf/nLX2bPni2K4qRJk1RVHT169BtvvLFkyZL4+Pjnn3+eYRgt5KClnZbul77W6TKdsIKz1/9pwyIiIlauXLl3796kpKQG8QB0+cSJE59//rnVajUajV988cXtt99+wQUXtOJFTIf93bt3//rrr19//fWkpKSHHnpIOyjtuObOnbtq1aqCggKLxTJlyhRFUUKhECEkVA+duKCmCk2sa5n16SvM5/N9+umnBw8eBICysrJ7772XjhB+R4gTQud5srOzIyIiExISQpJ0akdzBADAhqlzqtSpH0tQYgISG5TYgMQEJMYXYl0+1unjnH7O6eNcXs7p47whVlYYWa2zmtMFngWLASwGYjaosXYpLQ6bDYrDrDrMisOk2M2Kw6w4LIpZUFmWcAyhf4EoPMcQYFQMGCOVAMbIHeCojR/gt5YTAgghi9VCHwtn1/PqdJwvwp2ezcrKymXLls2ePVuW5erq6vXr148ZM6ampqZPnz4Oh6Nbt24mk2njxo0TJ07Uiu62Yl+aRaFZKwOcCOLPj5Y8EcsQlmHUZhdJDYcQXuBLsksdcXZrhDXoC7Zo2HcmE1jngiZmVCn0rdz0RhRCeMR84yxdVHTo/bRhk20xKhCOaZ/xSUeb02ga2tTO1eBzN/I8F3fHudhmi5yFmv+A6lwQQgoLC+m4iD2ZsWPHLl26NCcnZ8KECREREdu2bcvNzU1JSbn33nvhNL2dftivX78hQ4bs27fP7/ffcMMN1AlB62904f7779+yZUtxcfGAAQOuueaaQYMGAQCtNdPAcK5pd2iUnUPrFeEiL/zQmnUGoD4OjwDDsoFAaN336yVJMZmtwWCwrLxSklVBEAiAouCKymqOF71e78yZM0eMHBUIhhh08hgVNfQqpB7Mx44d+/TTT0tKSgYOHHjttdfa7fama5Q2PkZta+Gynvpj+P3+zMxMQRDy8/M5juN5/vrrr7/mmmtsNlv4dQk/e830PqIjqClTptxxxx0ff/zxgAEDXnjhBTrNdRYNK1TsGo1Gmqy9gZKjy5GRkSkpKYWFhR6Pp1u3bnFxcc1pf2PoZB0ADBgwIHzOTetC9JDnzJnDcdy+ffsGDBiQkZFx4sQJOmiEk5MgaTQYaAEAz/NFRUXFxcUOh4NhmOLi4oqKisjIyFNed1qRpt7DHPkD0kf//nDv3j1Wi+nWW24aPnyookgsA+GO5hgjFYOqIneAd/s5d4B1+Tm3j3UFOE+A8wYYb5D1BDhvkPUGGE8QQjKwTJ2xnP5lGTCJONYu2c2K3aQ4zEqEWbGbFYtBNYnYJKpmEZsMqknEBl5FqG7v1HZOMGAAoKZ0jEIqUlQOSQyDUPjogmUa3oOk3vXx26Wr6VTGRRdd1Aba/XwR7pSqqqpAIPD111+npqZec801RUVFy5cvv/rqq00mU3x8PCFk+vTpW7duPbu38ekgADRE8pmDpSOwq5/V2IpMMhTEICkgVRfX9BqRrqrnRT6Zpu8Nmq99aU3xo4UH3+sxZKotph0zP55FY63O6WgbO4dOx4cmfKSuJpoopH2jX79+Q4cOpdF1H374YX5+fkJCQmpqan5+Pp2j0ISLZrUhhFgslqeeemrx4sUDBw58+OGHy8vLqecbDsPhcCxZsqS4uDg5OdlisRw6dEjLNhjegGaaz+t91aH+D9RbKEEz9YVL6norIE2OQaizL0KAkPr2+//cvn07x7IBj8disVxz5cyYCF6SJEHg8/PzVy77RFVVAwdHD+0E5SKLkccYEwKEeikQwACE0PNQty+MCcfxa9asPXIkOzIqavOWbb17Z06dOkWSFeZUKl87jdrt2WA0QquxUh8hjuNqa2u/+eaboqKiKVOmjBw5kvqV1dTUUA8ZjuNMJpMoioIgUJf95pvYSH32SZvN9s477zz//PNWqzUvL6+wsDAlJeV3f94iNEN14yE6/cpqtb7yyivPPfdcMBi87777evXqFR730kxIfTlb+k/NZ0lzT9dqHqmqOmrUqNGjR1OTJT1jp+uEp+yWkiQlJiZmZmZu3boNEAwfPiIxKSUYlAgwmNT1N6jvihxDEEsYRBBgk8mwZfOWPTs3mm2xTi9etmanLWFEULL4gownwNX6OKePc3o5p5+r9XKeACcpSFaRZi+XFSAAFhHMBjAbVLNBibNjk6hajSoV6HaTtqAYRcwyhGUIxwDLEJYlVGrTUUGdaw1G3gBH6hp8irsJaIYZRBiG/G63os+KVatWrVy58tChQ//73/82bdo0aNCgc22qO1+EO+3QmZmZmZmZ2ocTJ06cOHEiXR4/fjwAOByOiy++uG2ahAnhEFpbFThYUPL3JN6LW1ZuSYNgwhv4ivwKKRCKS4tTld+Zuury0MyP/60t/kPRoQ/Thk2yRtMM7u3dLh0dnVPTOC9eqwkXyuEbJIS43W5NS5lMpoEDB6qqWlNT0yDGLrxVoihu3rx5yZIlAODxeHJzc6OiomRZFgQhfEc+n89qtfbv319RFOomru1aO7RTms8bJ8EAqPfirUtOVxdphxABCLMR1i3UGw4xYIIkBYUUJiQzkoIUlfP4gruP2bnYSwjwsoJRVFy2e1jNFhtCDMuyZWWyHH0TxgSIXKzg7/c5TEaeRarIEwOPRR4beGIQVKOA6wP+aMOIyGOTARt4icUeAy8bBMxzVCEhjFF96D9BCARBVBSFYRAADcZoeKUEQSguLi4rK+vZs6fFYmEYZtmyZRs3bjQYDP/+978jIyP79esXCAQ4jtO8y1wuF6ovbkXtayzLGo1G6mZDLfTUca6xYtb+EkIiIyMfffTRt99+OzExcfHixbNnz6bG41bPtDegiVk12v4xY8asXr1aOxXN6fyNjfeHDh366KOP+vbtO3fuXEmSvF4vjZGg4THhbXA6nRCWFBWaHDdq1v/6/slglXA8f83c63r16gWgjhg2NNIuqIrEMAyuy2sOBBAGUBTkCgi1XtblZ50+zhcSD+eMU3r0dvMOBayHieVPS6K8QeQLAkLA1TuaswywLIgcibAodurBYlLsZtVhVqxGxSRgk1hnOKd/eZZoNwK9C+g4EwgiAJiAqiCiIDrsDNfoCAHTyHDeahBCkiQdOHDAbDYnJydnZWVt3bp10KBB59pad74Id4rmREjvT20Z1TvM0VFy20wiMwiFCLx4oPhaqxwpGjwtLbcUBmJQ2fEKR7zDYDIocqeJKTwXUNX+eXXR40WH/p02fKI1SgXCnQ9zEDo6nZZz9Mht8PoM96eiXivah401Fv3EYDBs3ryZegUcOHDgwIED06dPp1HC4RunEcO0ylWYowuwLGs2WxHD+P1+jmOxqsqyrHn01uW+QMAggurS1QEBCElMUGZCIUZSmKDMhGQmJCNJZrxB5AsxviDrC3GBEOsPsQGJ9UuMP8QEZFaSWRUjRQUVA8aACWAMJOp5QMCywHFQqMCxvcCwEArRtsUwxgFQn8T6jdW0ScAywDLA1C0QjiWmuuA8bBYVq1GJtCEccwMTG+WRnUm97Y6EUaXViGNYk0gsRoVlAGNQCSDE/bp317rv11ssttmzZ8fGxsmyghCiBW4wUY0G465dOz/++ONgMJiQEH/33XfHxMRUVlYKgmC1WsvKyqqqqrTwAKPRWF1dTQiJjo6mGTkJIdROjzGmgQ3h0LBXzWMq3HUKY2w2m7/77rtXXnnFYrHk5OS88sors2bN0qJ6NDHQYJagaUHfoopOCCFNfjSeLTzd7ugnWtLPwsLC++67r7y8fOPGjSdOnLj88suNRiPthKhRjdLTl3wCqPOwQoAIgxieZwghWFXRb2VBMYsAoaAl3hI/c4Y/xLh8+EgBDsgGT4Ct9XI1Xq7Wy9d6uRov7/SxksJISp3VPCQDYiKNRuAImEQSY0EiFzIbVKtBtVNpblLqnVtUs0FpYC9nGcKguoGBZjIPSIyfWsObtJojAGiVMbT5YIwFQRg2bBitRhwXFzdlyhQ4946m55dwRydXQAg/ueFTmW3QEkwIg9Dfj9UanZUzuwneM1DtDMMoklJ2rKzXqAyGZUiInLcFUzXV/kTR4U/Sho+1Rim6atfpJJxudlVzY+1EGUWbCalPMr1s2TKz2Txz5kwIUyet2yD1XWn+YzzcnbfBr6hvutFolCTJ7/dT+ai5x4RbzUVRYFkOEJIkWZEVQAgBFgSuprriyy/WeN3OUDBgNJkvvezyhMRkSVIxIFWFgES9eFmPn3UHWE+A8/gZb4jzBxlviFZ+0f6ioAQGI3AstcEDVoGWWKcKm2AMRGZI0GETTAbgWVXgiMgTnsVBv7uqsqSmoswmcKoaMhuF4aOH8QKvKipiEBBQMVJUpGBGURlZpYGAbEhGNIOeL8h6Amwp5jBBDAsqBkyA5YZB1DBFAZ8Af/2GmATJYsRWo2I1qnajYrcokRbCI9fXn27z1pYpwayamtpHHnlI5IFhMB2rqAREEbZu+dFZWx0RGZ177Pive/dffvnl/fsPzMk9Vl1d07179549ewYCAVVVTSbT5s2b16xZgzGePn36pEmTwhO+obBqSlCfDIqmxmo8y0EFQEREhMfjycjIsFgs5eXlERERgUDgu+++Ky0tveaaayIiIsKdfDRbXtN9km65aV//xtC+SnsajaWGMMlO905zqNMI5mAw6PP5JEniOG7Tpk0Y4+7duwcCgXXr1uXk5MyfPz8lJaXJzC0IAEh9BkWGISxL40Hr5kyCIamkqFIwmByOyKAETh9f4+VqvJzTw9V4+Vof4/axLj/rCfKeAOfyMyG5LjELxwLLAs8QnsMOixRhViIsSoRZcZhlu0k2izILAYuRRNp4kwGbRdUg0DjshpNIhCACoGJQME0vw2iZ0VH91BSC+pd6uDsZaXEuvqavC/zeUA3qH87Tpk2z2+3FxcXTpk3r3bt3S59drZjk6Wpvgk4BJoAQygvgL48UPR4NBLFAmpVI7pQwHFNTUqPIanRKtCIp56dMJfV+7f+pOvHnkqNL0oePtUTqtnadNgAToN69KmlW+QX6rKcvafpWpgYFnuep2mgg36nhkC63Ts52cLZv3x4fHx8MBrdv3z569Gg6gGl1tLHVaqUJdlpkhaHiLDxWkv6W47i5c+cihCoqKnr16jVx4kTEsAzL8bxACAFCCME8xxaXFO/f9yvPMyOGDYmMsGNVlhTWG8T/+WztzzuzGN7KCBEqE3FMIj0zk6tc4PLzTh/nCzEqBhWDrIJK6sQKAjCJYODBKIDRAFEOMIpgFMAgqEXHD1eU5XHgHzIwvbLs+PHcgwZekYK1V18xa9OPa6orSwBwWlqPRxc+xHEsAkL7F8exBSekv/3tX85SJ0ihiTNmLLhyoKL4VVVlWY5hGKKZXev9DQj+TU6pGEIy6w0xgSC7dMUPh44UccYYFaw9+46y2JPcfhKQGF9IdAWh2AXeIKgYeCrjUAIb83c2DjPYdyhU9uqK+Gg7jjDLDlPIapAQ9sZEEYO9B284jtWg1SClJlgMXOiqy2f26dWtrLxqyNBhUVHRIUmKMFkqKiuXr1hZXFzEsewnn3zSs2fPzMxMv99PEzSR+mpBCCFqb6Z2+lNefXp9JUkaPnz4Pffcs23btiFDhsydO/fjjz/+8ssv/X7/zz///Pzzz8fFxdG7kvYiv9+vKIoWHXtKTpw4ERkZabW2MpN3g2G5qqrUPZ1CJXtBQYHRaKT5RkVR7N+/f2RkZHV1NULIYrHk5+dv2bJlwYIFgiAAYuqFLKkPUCAICAKMEEagIsAESCDEeIOsP8h6Q6w3yLgD4rZdx48eVzmT3WjvFlCMIQVkFWQVFBUkBVgGrEawGCHCDinxYDUQm0mlKRQdFiXCrFoNAYtRNRk4BmGWqUvSQocEABYVg6KSumjUekM5U6/C0Tm2jreIpvPcN8BsNl922WU0whhaUvW21ejCvR2gkzhv5FQNIu7+VoNTxa2+zgQTlmeLjhTbY6y2SGvIHzo/ze0YCIfQu5XH/1aa82X6yOFmhwqE1VW7zjlAEzq02hLPIkIIJsCzSMa/mX1Qo1g9ipYbVFEUOokPAH6/f/fu3bSiu2a0oykLysvL//73v/M8v2jRIpvN9rv51zoRqL6c56hRo8rLywsLC+mHNTU1X3zxhdfrbVEiTjoK4nleEASDwaCqanMKcdCTzDBMbW2twWCwWCxUq6kqDgT8ACAIYkJCkslsNZmtq1evIVjiWBB4BiEAxAHiMGE2bdqWnV8LQvymw1EpaSO9UpRfNpXXqEXeheKQWOAQYQFU2O+EXT8piCgIJJ6XrUbM4VoDcUcbJAY7edYjsj6BDRkFNcImmEQQOAXhgMApZgPDMnJh7rdQVa0AKgjEy4oKNTXIaJR9/qN7ScCVT+QAwzBHD+9Z+c1SQRAJ/u3EcRyfkprOciUGo8FkiVz57Q+qohKCZUVRT7YQa6Ze6ofwm1swAozVwn2rOb9X9PF+ny86YWTfxAFOogRZzs8wfpb1c6yPYwKyIYRtQdUaVG3uoOgnEYR1ICZtwz6MCaMSVhCA5QAp2GEBi+GBQOoVAaXGyPs35CbtLfdxxGkzWCycunv3r6oqAVEFDlVWlnucJUYBsRzv84eW/ndZZuYRSQoxdQ4nhCaE9fl8BQUFPM9369aNusU3cfWpLu/evbvVaj1y5Mi6det4no+Li8vOzn799de7d+8eCoU4jjMYDLIs79u3z+fzDR48ODIykiZS1NxuaYqhXbt2rV+/Pjo6evbs2dHR0Q2KYIRPDoTP7Wv57LWQDOr8Qz1htNUIITzPFxQUHDhwwGq10kztNIVGfHxCTU2N3+83mkyqSg4dyvp66TKEMEdjNFkCiAHgCLCAWAxCCNsDOCKIHUHs8Cs2d0Co9bEuH+/0sU4vEACbNZ61ACJQXa0qktPIuo2sy8G4DazLILhNvN9sUC0G1SzW5TgXGIJ9QLzgLEO1BMmKSggwDEcIIYBobhmtIzboVB2ZFjk+0f6glddo/l4YhvH5fJdffnlL6yvrwr2twQAMwEGvsim/eHEMFyCIOYMZHsQgOaRUFlalDelBCDkPlSoBwISwCP21NPujqhNLe44aaLLrql3n3MEhqHNTAACA/a7QHw5XV8n4yYyIyxLMv61HiIoblg9kGCYQCKxYsWLixIlJSUler3fVqlUTJ06Mioo6dOhQUVHR0KFDe/furZVV4jju9ddfnzNnjiRJf/nLXxYvXhyei7ALoGU313LPI4QCgcDevXtra2sb+Ok2DcMwNpstNja2vLw8Ly/PZrOlp6dTi+zpXsD0ivj9/sOHD1M7fUxMLAHk9/sjHPbMzEyMlVDQT5V6ha9UUlinj3H5WJefC6gWzCcrTGIQxWP+KnFgFGFgexWsLwSVgIGHSBvwIuetyQbVqYaqTZx3TO/YSItq5PwcuLy1J7IO7g74vUAU0WbOzOzFswiACj7myP5st9srGkzp6Rksx6sqHM464nQGRDECY+z0qD3SegQl1uvzJqemHzmaJ8kSAkaWlB490kpLyxVVPXnYSERRCAYDNTU1JcXFNIEdwzDp6ekOR4SqKvB7T0tCCMOySakZBw8edPuk+PgUGWx7D+SxLKLJtnlEIhkSbQZAiBAWA0uAkVUkSxhYEyPGYi5KZSKRGJeTX+vyC4wQIQdNHtXB23upCDwYVh8EWcI8i1kk8YwsgIvHZZxayiklRoZj7SMkT4miOM2GAIOdFSW5IUnBhFFVgglwHOd0ug8eOkSds/fvP9i3b6YgCuT0TlO0XwmC4HK5nE4nz/OBQCAYDJpMJlmWjx8/TldQFGX37t1URh87dqx///5ms1nzxqHuK6Wlpb/++ivV1u+8887o0aPD4+VQWEFZOntGw2e1WQLangY++uHt5Hm+oqLi4MGDFovF5XJXVVX37deP43hCsM1mGz16dEVFeXlZSXr3hJTkhNrKXH+Qcfk5l591B/gQjpTZGIWNl9kEhYmRsSCrnII5GTMEwGoAm5nYjUp6vBRpRUH3iexDmzlchYOlURapX+9EQiQGYQYUBCqDVCBEJYCDyOdHHgwqqYuo1rR43WwVg34TNaexX3RwmhPV0IDq6mqt8HAzYVnW5XLRzCgtQhfubQ0hAAheP1oxnvWnGI2uM/Bup/lkKk9UhvyhhJ7xitx1THHNhM7AsQg9UXR4pbN0ba9x3UST7teuc44gACxCpUHlF6ePZhdVCDyXU/trTRBYdPPe8pdDUckGTiJExaSPRci08mr9aFp7E7zzzjuEkDfeeOORRx759NNPVVV9/fXXH3300f379/fp0+e11157/vnnIyMjNXshy7JOp3PIkCHz58/vYqod6vNMAwCVQQBACElKSnrvvfdasbVPP/3U6XS63W7qaTB48OCpU6cGAoEm8sYYDIZdu3bn5B4TDWYgKoNUVQ6wJIAVDoEydOjw3v3HFFUJJTV8udPgdvFeD3L7wOmHoARyCFgGeBaQSnzOAhwoSEsULrgwLdIq2YyK3UywVJudtVMJVkfaRbPFOmJkZigorfluO8vxg0f2Opb1i8JiQCwg7tLLru7evUcgGDQajXt27971a7YKoj+gjhw99sJJF/p83meeeSbg9/Ac4/H4Ro0c/uCDDx44cCAUCmVlZa1du9ZoMAQCgREjRvzf//1fg2kZQojRaPzxxx937tzJsixN8CKKYigU6t69+2233UZjPRucGTpupCeNDqhYlvV6vTt37qytre3Xr1+vXr0wxnXRfydlrgTqlQEACGgIISYEIyBYVWw2y2uvffDdzrUR0SkuL7762vlDR076ZvWPv+4/Pqz/+KS04RU1UOURKlwmX8guk9QA9XVGIDIA9koWV4moxtq/Z0aaNdLsT4hUrGIQESUq0r537+4Xnj8gCEIohGJiHbfffltkZIwkKVAvg+tjGeuS3tD5MoogCLm5ucuXL3c6ndOnTx8/fjy1prMs6/f7H3jgAUVR6Em47bbbevToIcuyNidmMBh279796quviqIYDAaTkpKee+658AHnabIJnfQhtd+H39raChhji8W6ffv2rCNHecEgyWpGz7RHH7rXaOAxwbIChLBOt39fVrnCJ4cgsbia87t5pxuq3FDlBkUFjgUOAcOAmYNomxJrk6JsgWhbKNoi24yqxahYjarFoETYmC+/+OxY6XLBYAoGpSkzrr1+3g0+v59hWABEUz7W9Q3Q5PhJ9xTDMLSGlyAIWgWoTkqLXGUoqampZ7LHFsWz6sK9TaHusL965H3FZYtjeD8+U4GJGFRyrMwR7zBajEro/HJwx/UPkntP7Nvhq13Xe3wcL2IAXbXrnCMIAcRCUVD5Z77bwCIEIGGS7ZM5FvEMckr43RPuVCOnEOJTyc3J1r42AXCdcqeWs6ysrNjY2BtvvHHDhg0rVqxISkq6+uqrV69evW/fvj59+tx3331vvfWW0+mMioqC+owTTz/99Jdffvnuu+9OmDChV69e0KpCLR0TOjvscDiWLVvGMEy/fv3g5BDDZm6HSp958+YtXbp06NChRqPRZrO5XK4NGzZoqdnChGxdlSKWZaj6KjiR63dXCDwAYwzKMZwpg9jii0ni0b0Jq/MHcD/E+oNMQEJ+CQw8WAQ/h6s4UmPn3BeO7ZkYhZOiVG9tzs9b1ptNwsWzpnVPdYeCPoQYBQNCxj49JhFgOV4gmAQC/jfffvfnbT/zPJeYmIBYXpI9sixHRkVzHOdy1UqSxDKwbdsWl6s2MjLS5XLt3LFj0MCBCKHu3bvn5OQoiuJwOGbOnOn3+3v27CmK4rZt2xRFMZvNPp8vNjbWYrHU1NSER1DQk5mfny9JEg0AUBTFYDCEQqGcnJzy8nKqMhsnNqGOIgDg8/m0pJbUOqiqqsvlatalqft/BAAEE2/QN3n61aWVwdKS4tHDu8+c2Ofw4e8PbX7bwEDZng2zBt8+eNIIny+kENblYytcfIWTL3MK5U7e6RPcwWh3IKYmAJ9sAn4LGASjgccWgxJrl5KisFXMNCRf563NV4kzsUdvlYgeV7VRJAgAE/pfw0r1UO/FgYk3Lj5xwYLbMcaiQXS6XEDq7Mcsy06aNGnVqlW0hqvVag0vtUsIcbvdiYmJAwYM+PXXXw0Gw7Rp02jwaNNeOo07MBXuWo4XGpFJnxwBvy+tR/LsS6bs3L41Pjp61JhJBZVcebVS4RYKq4wFlUKpMzGo9HH7wOMHSQGzAaKtcpRVSU2VY+xyfIQca5fjHFKkRRV4zLOEo/8xRP0twTlT61L2HSoQTDGiQVSIjxfNHm/A5/ezzRaUNMYAAHieb/7N2zFphXB3Op0Wi6UV+9J8pZqPLtzbFHorfpRXPZIJJhoNZ2JuBwCGZeSQXJpb1ndsH2pS6jJv9N8FA2EBEYCb83YXSP61vcc5WL4dqyzpnA8wCLBKhtvF78ckAgAQAAY9frjq5WOuICZTY03LhsdZeKZuTEmIihuW8FBVlTq400LxdJk6ZCckJNAE4dQITUWDy+Xas2fPDTfccMMNN7z00kslJSWpqaktzVzRYaFGpsGDB0uSJIoiFe6afbeZG6HPvaqqqtWrV0dFRTkcDkVRfD4fIcThcHAcjxCoKq3ljggAxxGqXVxuT3lFTWR0woHckOS4DOz9MJ+i8ClBiFcZzmgAMwJVBpGXeyWGkiKDyTESp1Qs/fxtFtcgpYohwUsGvxgdHatiYLr16JZw2brv13+9dPnoMWMGDRwsyRJCCAgGhBHIfr/PZDLl5mYfPLDfZrMwDFNRUeFwOPr06cMwzMUXXxwVFUmdqhVFGTx48M8//1xTU4Mx7tWrF61PdNlll9lstqqqqmHDhiUnJweDQRrlPGzYsD179rhcLofDMXz4cFJf0sjv93McZzabg8GgJEnjx4/fu3dvSUmJ3W4nhFRVVSGE+vbta7FYaOL5BqdUFMXCwsL169cLgjBz5kyHw0Hdrz0ej+afDWFp0ekPm8jHTwjhRJ5hmKTEuPvuvaeysio+Pl40GH7dl+0JsmazpabSuWvPgeEjx7JMQODAYlBTokMMAywiBMATYGu9rNPHuXxstUcsqRXLnUJJrVjjEWtLxAMFoGA7y9/LRAMP0n6Je26pbDPKFiO2GRSrUbWZqF1ZtRhUq1E1iirHEIahmekxyyCEAsAymCBZCXIso2IgBAEiBJiLL7k0vWdPWZL79s3keUFVT7r76Lm67bbbcnJy7HZ7cnKyLMvNTwBFx5AECAAiwNJQTo4lLAOYgKIiVWVCCqrymJMG3pWvXO6Vo9YXp/57Dy53ckEJRAFEDgQOoqxSn4xQSrSUGBmKsioOs0xLh3IsUfFvBUppFhdZQZKCSF1GRYIACMFGo2H0qBHH83L9qhzhcPTtm6mqCtcSTan1itNNcHUiNDen5v9EC1hqA3Th3nbQybnCIN5aWPEXBxMk9R+1dnMMx1QWVBGMo7tFy5J8/hiaFYKNiPFj9YZjO2WAtb3HCYjBALpq1znX0LuWYAIAhABDyJ97R46NNNRI+LJ4s4VDskIQqq+pE/ZDhJCiKJmZmatXr3733Xdzc3MXLVr0+eefv/fee7m5uQsXLvzuu+84jvN6vTQuimp6h8Oxffv2rKwsnuctFktiYmKDuLcuACFk5MiRcKqEjM3fgtVq7du37+7du71eb0xMTFJSstfrLSuvfOqpp6dMuXDSxAkMwjxHEAKXjyutEUtr0bLvCkrckcicFsKPKt1A5UEKgt1AukcqBlR24sh67M+R3VnDR/b8v6tv5FnssBlVbPrlu9rsnOOA+G7d0xjeEVS4vXv3frt6VUlJqcfrAUKOHj36+ON/ioqKCitiXZeGODc3l1q7qYsFy7IXX3xxRkYGQojG0VLj9/Dhw+++++5du3b17dt34sSJtDPY7fYbb7yRDvy0XN0AMG3atO7dux89enTIkCEJCQmLFy/+6aefTCZTWVmZ0Wh85plnJk+eLElSamrq4sWL9+/fn5GRAQDLly9PTk6+5JJLUH1tV1KfdZR2P5fL9fTTTx8/fpxhmAMHDrz22msIIRqNoIUl0AUIy8BjMpkwxsFgEOrni7QLJIpiTU2N2+1OTk4WRTE1NUWSJFWRBYEjWCFYRgg4jgUATBDCSCVQ74eDAIBlSHyEkhwlsywh2CupSFaRojIeP6lw8dVeY4WTL6/lav2cLyg6ffhEuej2i34JAIBjQOCBZ4Gr+4/wHLYb1UirHGlRjJw3xoFjHcRmwmaRpqtXzQZV4AjGoGKMCYwYNpgACviDGKsI1cVc1uUnREhRMCA0YMAgRVVCoVPY2k8uf/tb4C+tacUywABGoHI88QVZp49z+TmnjyurFYqqxcJqsaTa4AmggIRUSJQVsBlInIOM6OmPc0jJ0aGkyFBSZMhqUnmWCBzmWUIAKSpSVOSXGJqSXvNx0ZzRUf3ZrfsGIVmWpkyZEhERUVBQMHLkyN9LK6nTnqDOPjDqgPj9foPB0NjqQO3BT2RV5edmP5kiupVmJY87HQQTg8Ww45udUkgZd/XokK/1+WRaGgp9rsEYR0ZGpqenn/JblRBWkssQvi5vVxIv/jttOI9QR7a103hzqsM6BZqfYns3pLlQE9dZf8dgjKuqqux2exMzv3VRFiwCQARjtcn4cGpEdzqdn3/++bRp0zIyMmpqar7++uspU6b07NkzOzs7PT09Nzc3MjKSqnNCiMlkstvtX331lcfjueaaa6xW65lnlamurrbb7S2tr35OOcPKqVTxZ2dnv/LK3ywWy9Rp07t1S/nwg7d37djG86JCuPseeNQRP+xAHjlRZSquFgurxAo3YzYBiwBUMHPVBjU3WL1nWL+oWVOHJEQSkXE/++yfC4tKDUazopJ7772vX/8Bq1d9W1FZ1S01paysFGN18uTJqamp1dXVzz//fE1NDQDQbDayLN999939+vWjlmzNJm00GleuXPnBBx/Q2FBJkhwOxxdffBEfH0/dJERRVFXV7/fbbDbNdNeiILlPPvnkxhtvpGZ7qu+nT5++atWqVjx88vLyhg4dSmd+ZFkuKyuz2+1Qr++pcKf5T2idTgAoLy/ftGmT3W4fM2aMlk2ftlwQhEOHDn3yySd+v3/YsGHXXnst3ZQgCJ988sm6descDkdNTc2sWbPmz5/v8Xga94R6yzTQwR1C1N8FE6KyDIgCR83nkoK8AdYbZD0BLqSKHj/xBjlvUKhygSfAeoKcJ8DS/yQFYQIqzXoJoGJgCdjNxFFXDEiJsCiRFiXKKkdaZLtJcphlkQeECMeielM90OpJtHiniokmiX+LzKwT6ATVF8EltJYQRipBGCNvkKlwCVVurqyWr3QbKt1clVuocvOVbgAAkQeBAwNP4h1ySnQwOSqQGCVF2+oaZhRwna8LRg1cgOqSnbf8OUErVdEre9L5b/QAbPwJtU1AI1eZk9MWNfTIanET24RWuMokJye3OhloS9Et7m0EBmAQqpDIT4UV99pAJugMs5YyLBPwBquKa/qO74OVM3aW7ySoQFiEDgU98wr2TnPELU7pD/Uhg+3dNJ3zEdrtZIUAkNPlf/xtZYQwxg6H4+677wYARVEiIyPvuOMOutyrVy9Jknr37r19+/a///3vgiBIkjRq1Kj77rtv7ty5UO8I2yVtYGdYaJCek169er333ruFJ3IEDlc7Q7V+K7ZNIPb+QbbP4jUDZGRz+yAgQYQFUmKUJFtZYfYPRpLvq9w9afKwuVfPDvgybVYLL8qygmTFLJpjMaqVVQariqri1atWf/XVlyzLHnA4Hn300bS0NJrb2+v1+v1+amn2+Xy1tbV9+vTJyMjgeV4URUEQBEHgeZ7q8quvvvrDDz/cv3+/0Wj0+/2XXHIJtX9TSktLb7311t27d1922WVvvPGG0WhsnGDklIdPxTTHcQUFBQBgsVicTieVHcFgUFGU8GEA3SDGmIr78DO/e/fuvXv3duvWrbCwsKamJiYmJjc3FwBmzpxpMBhoQAKdFmjsEuD1eufOnbtnzx5RFG+99dY//vGPgUBAURSaIy8QCCxfvryyspJWoh0wYMDQoUODwSDLsiNHjtyzZ09VVVW3bt0uuOCCU0bKQnhAJKqbHxAEQRQNoVDI7/erwAD1a0FEFIhRlFJi8LFjB7esXwmIufiS2d3GpIUkFROECVIxUlQSUk2bfzny7Q87OUO8wkSCEJfcY5AnyLv9bIXT6PSDpIDAgciBwIPAgVEAkxAw857EaC7KBjajbLeoVoMiCkRgMccSniM8i1mmzjGdHoSKkawysoJkFWSF8QXZWh9X7eFrvHyVhyuvFVx+NhBCkoIkBUIK2IwQZcWJkaEBqUp8pJQUGUyKDCVESkYRCywROMyyRFWRoiIZI5efQ6hh4s5T6ooGHk2Ne5Q262IwGGhaJ81XpEGum/CFxnuhQzie57UYFXIyDSpRhG/qlBs8ZbN1dOHeVhCCEFpa4nb4XAOjBZ9WfqB1G8OEN/JlR4tVWYnrEdtlfF6bhhZG3eqtvvH4rnvj0x+M70lrSzDnyahFp6PSorkuRVEkSRIEgWEYKmtoqjhZllmWlWV51KhRn332Wfj69C3Yihim8wqMcUiGn4+Yswq4girzEfTHmlgrw4LIAY8gKSI0ZYA/PT4Q7wglRKoiqv74P1v37D3QLz1t+tSJRpOF440EIQUjTBSOA4IVIJhglWEYnuePHcsVBMFsNldWVi5duvTOO+9UVdVsNvfs2XPQoEE///yzz+e74IILLrzwQuqDrvn7hjcvKSnpkUceufHGG6kzyYQJE7TBGELoxRdfXLt2rdVq/fDDD/v37//ggw+Ga244jd2d2rbpt5dccskHH3xQUFBgMBgEQbBarXfddZfRaNTmVKmZnOYO1waBVJFv2bJl1qxZXq9X2/KwYcOeeuqplJSU6667ThTFBnlCwjUfwzB79uz59ddfaeTGv/71rxdeeCEmJoYabhVFCQQClZWVpaWlMTEx4ZKOhtg++OCDhYWFPXr0oGEe4cOVU4o2Gud98ODB7du3p6SkjB8/nmUQqc+GjDEQhqus8b/5z4/LyssBSH5R7eOP/8kgiggIxxCexcCTSCE4orfyw//WhCoDshQaO3bMXdcvcvtZT53BnnX5uWoPV+kSqt1ctZevcILbbyBgzK4AWQFZqSvtaRSpuCcGnggc5lhSb2UHACKrjKQwIRmFZBSUwR8EhIDn6kqN8hxYjWrvFBRjC9kMrsRIOcqqOEyKw6I4TApL3dO1+FEC4a4vCAHLnFajQ71i1hYaS2Q6BmProZOWy5Ytq6mpmTdvXlRUlKbdwxV8441ou0MI0ZyqWlYZTa/Ti64taDM2FPoYpJlbw9scflDhu9OlvC7c2wgGIYnAV8fKbnAAMAxRGkattQwEhJCiIyVxabGiUZSCXdwXjToWcwgtqy19sGD/X+J63hifrgIwgM7IUqej0+bQ96UW26cpMy2uSyu/Qv95JmVEzx8IAYZhAiHy6vLEkloQOEiNIcMSfHFWZ99UuU+y4rAoIo9FDmOCQgoCiLzt9ofmej1Go4Hn+ZAkIQCs4p82b/75559jY2NLS0upmqGJMtLT03ft2sVxnNVq3bdv37p162699dadO3cSQp555pmNGzcyDDNt2rQGpuhwr30asXfDDTeUlJSsXbt26NChd999d3igpyRJdPxGXczDt6MVZ2lQpYVKK+2rgQMH/vDDD1u2bBkyZIggCBaLJSkpiQ756PpUokGYhZUKKYZhaMUrURRlWTYajaIoZmdnv/nmm6FQ6N///vesWbPS09PDD6fBG6dHjx52u720tBQAJk6cSAOs6e5EUTSbzffcc8/ChQuPHj16xRVXzJw5k2EYmt9GkqQ+ffr079/f7/fT7PJUwGl7aSAQMcZGo/Ho0aPvvPOOx+MBgEAgcNVVV/l8vvozQziW8fu9bnet1WIEgNqaar/PZxBFTAgDiAAigPxBJblbr3k33r5t2za7wzF79uWYcCZRthkVliEsQwAB9RRXMROU1L++9GpFjcSZkiRsHTRickJy3yoX9ga5gESlOSMpSFIYSWHCvHqAZ8EkqA4zFjgi8thiUCMsSqRFjrQoDrMcH6FYjeqJ/FyOwRk9u4kCo6pEwYzawD293qDOoIaO6eESNlz1Qn2sJL0ENIW8lj9e+0qT4/QnixYteuONNxBCmzZt+uabb1rhLUn7v9bNmkl4lIVSjyzL2oxNOKfsFY3PRtdGF+5tgUqARbCq3Md73SOSOB8mZ1jelGGYkD9UVVg1bNaQ30o1dlGoGzEC+HtZ7pvleR/1GDZJtCsEc7po1+mKhKt5nWZC3+B2M0wf6uKQ1Ds5GGcPJUZKRpHIClIxdVpAkswBokGCMkLIbrcSQhACrKpWq3Xnzp2ffPIJx3HZ2dk0vQ9NBp+WlkaDEH799VeTyXT48OHhw4f/9NNPd911l9PpvPfee19++WXaDBqBoGnrBuqW/vPRRx999NFHtQ8ZhqFyvEePHpovQXh1HiqstZW1H1IZvWfPniVLlowYMeL6668HgLS0tLS0tAbraI7yS5YsWbt27ezZs+fMmRO+WVmWd+zYgRCiFYV8Pp/P5xs9evTbb7+9ZMkSABg0aNDKlSuTk5Mb13ek209JSVmyZMk//vGPyMjIJ598soGXMyFk1qxZmzdvLikpGT58OP1Qy51Ho4AcDke4LVYTbTSbDW2YZjw+fvy4z+dLSEiorq7Ozs6mp522hHpaR0dHDxgwYMeOHYSQMWPGxMbG0qtZN78BgBBSFXnChPHjxo1hWZbuDgBJGAgw1HxPfdMBiM0sDOrX/ZtvlnOeIzaL5ZoLRvToVqqoMkJIkhE1q0sKklVGVevex4TQlKMgcJjniMASgccihwHqElOqmDCssGzZ8pWrVhOCZl100eWXX6HIMsMgaKTRw/uPdh60DymadxYV6FSd04XT3jZhW/Z6ve+//77ZbGZZdvPmzXv27Bk1ahQ9nw3M6k1spwlvrlMeS/gyvXEax2OQ+qKktFdIkkRrPtCrebqz0bVFvP56aBsIAPrfidoxgmTkjZJ8RuZ2Qggv8gWHCwUjH50cpYSUzlmbrFnQqFMVyP0n9v/irfmm1+i+Rpvb77fqXVdHR+dkGAZuurACkRDPgqQwkopcPoRQfYwgAPrNuwABADXu/vTTTz/++GO/fv1owC7N+kL9dKOjo6+55hqz2Wyz2ebNm7d69eqioqL4+PjJkye/9NJLZWVlERERixcvnjlz5qRJk2il299tJFWZ4YZwKlwqKioIIWaz2el05uTkQL19HSG0evXqp59+Oioq6qWXXho8eLDmXXPo0KGLLrqovLwcIXT06NGBAwfa7fapU6eG6xiol/6ff/75TTfdBABLly5lWfbKK68MhUI7duxISkrq3r17bm6utvKECROSk5MXLFjw5JNPiqIYHR29b9++PXv2pKSkUE+bBkdED2fKlClTpkwJ/zB8GWOcmJiYmJgY/kNtRNF0+CxVZlogLMuy/fv39/l8R48eJYRMnz6dfkvPJ90vwzC33nrrqFGjOI4bMmRIeXl5bW1tamqqwWAID7ukpS5p+pTfJhPgpBhzQois4Esvu8JgshQXlUyYOCE2Ib3WKwHwAMAgghCIPDYK5LdKT9qG6gNG65Iwylz951gUDXnH89d9v57nBULITz9uGDlieGpqanhjwv2RNHnKsiwdVXIcJwiCFkrRhCtdg/5wyhUEQRgwYMAvv/wCAElJSampqQ28U2gvCo85bj6t8AjQ+gbtHg16iNYlJEmSJCkUCmkWejrG0xR8eBu6jJrX1c85RyXAInTUr+ZVVd8ayfnVM0omAwC0NkTx0eLYbrGCUTiTfDIdHOrUXi6HbsrbJSJmbe9xUZygEMJ3ab8gHR2dVkMIhCQmAAxVVOzpp+UwxiaTaffu3Z9//rkgCBs2bMjIyEhNTT1x4gR15FBVdcqUKYMGDRIEwWg0xsTErFq1ateuXcOGDRswYMDzzz8PAKFQiGVZGuXZTFnQ2AJKs8rMmjXriy++8Pv9SUlJNGSZKo8jR47ccsstNK17KBRatWqV2WymoaXLli0rLy+Pi4vz+/1//vOf6U/ee++9BQsWhOcKo/Jl48aNCKGkpKSioqKVK1deeeWV11133cqVK2NjYz/66KPbbrvtlVdeAYAhQ4b88MMPVCclJiaGQqHi4uKEhISePXvC6RUYleb0JITb8jWo5iMnp8duvLVTSkx6Hqg8NZvNADBhwoTnnntu7dq1mZmZV155Ja0/FW6RBQBBEDweT3FxcXFx8Z49e4qLi4cPH37NNdeYTCZt+BH+93SXDyFECOZ57sorrqAqX1EkBEQ7RAJAMPxOggh0UuQoAQCCjUaDw+GoqKhACNntdhp4oI1AAE6yphsMBs2gTm3qzZfpzdHNgiB8/PHHzzzzjNPpXLRoUWJiYgPPKG1E9LubOiucrm9owwmtS2gr0JkZ2gdC9WhWeQg7n3D6y90p0IX7OYfmbl1d6k5RfckG0XOGYamEcDznLHc5K9wDJvZXpK4ZlkoAMACH0M/e6tuP751pj1uc2h/qP5Tbu3k6OjodFpoeuzlrMgxTW1sry7LD4XA6nUajcf78+Tt37szIyPB6vQaD4eKLL9aM6BjjQYMGDRo0iEqBxx577Mknn3S5XPPnzx8/fvwp1WozoYpt6tSpr7zyytNPPz127Fjq7kK1RUFBQVVVVUxMjNvtrqio8Pl8FouFPvbHjx8vimJ5eTkAGI1GqgL/+9//LliwIPy9QAcGkyZNevfdd4uKigDgmmuuWbdu3bJlyyIjI0tLSx977LGff/45MzOzuLj4tttu43lekiSe51977TWHw1FaWnrvvff269cvfJbglCcTwhTe6VZomma+zgghF1100UUXXUT/SWvHal9RXb548eKXXnrJZrOxLGu3281m88qVK/v27Tt9+nQaQkDjehvI3PC/Dfbo8/loon1VVU0mEw3EhPqMN80kfHdUaFKxPmjQoL59+zqdzpiYGJrUn1rTqV4/pTU9XMiG0wpJQH+SkZHx6aefau5V4R4yiqK8/fbb33///WWXXXbTTTdRudzG2qOJ3dHWNvCtpyEckiQFg0Eq4qmPDU3mcdIcS2czxuvC/ZzDICQDrMyvnGdFuO5+OIPNEWB4pjCryBJpscfYFVnpem4yGAiDEAPwXsXxxWU5TyVm3hidoieQ0emqNH4BN/YlbeD9rHPmIIRkWc7MzOzevXtpaSnP80OGDOnVq9fo0aMbvP41WyNVWgaDAQBmz549btw4r9fbvXv3M2wJ3UVJScmrr76an5+fk5NTU1Pz5Zdf0lwuo0ePnjVr1po1aziOmz17dmxsLPXJIYRMmjTpP//5z9q1a2VZ/uKLL8rKygghtAJGuBChhvA5c+YghH755ZcxY8bMmjVr9erVtMAqIcRkMnEcN3/+fK09VJklJSW999574WfsDI/0bEFVL8MwZWVlTzzxxLFjxy688MI//elPPM+j+hCRdevWOZ1OlmWrqqoAwGQy+f1+s9kcHx9vs9no1dTKSIV71dO/mplWc1Pheb6srGzlypVer3fkyJEXXHABjSSG3zsz2na0wsmhUEgUxT179lRUVFgsltLS0qKion//+9+rV68eNGjQn//8Z4fD0cSmmrPTVqC5ZoVHMtCpm3/+858PPPAAx3GrVq2y2Wxz587tUOVfGjw8oX4AybKs0Wg0Go30K+pqJctyMBgMBAKhUIiKewgzxncKBa+/A84tNLByn1sifu+AODaAW1MTIRzEIDkoFxwu6ndBJmIRkVpZa7DDgoEIiAFCFp7Yt9ld9UX6iGHmCBWInkBGp2NCMEEMAgREJc1xWtMsgprzAFUbNO0jfXnQGjrht3Z48uwGuZB1Wgd1e4iNjb3vvvuys7MzMjKGDx8uCEJ5efldd921ffv222+//cknn9QUDLU3u93ub7/9NiYmZty4cdHR0dHR0Y3jNVsKtYgfOXJk9+7dUVFRwWBw3759ZWVlPXr0UFXVZrN9/fXXK1asiIiImDlzpmYppCJj7ty5NM3/sGHDVq5cmZGR8fTTT8PJ5m26Psuy2soY42nTpj3wwAPLli2LiIh48cUXaUIb2i3DTa20s2m5azoOdLTz8ssvf/jhh4IgbNy4sU+fPlRQIoQYhrn00ks3bNhQVVUVERGRkZFRVFR00003zZo1CwBMJlMTm4VGGU60UlPvv//+/v37RVE8cuRIampqjx49qN39lLckqc/1SbNIMQwTERFRUVHBsmxKSgrHcTabbfv27XRE4Xa7Kysr/X7/pk2bHA7Hn//85wbJQCl0xELCsgmd7sxAoxxEv8spY6Bp59y0aRMAxMXFFRcX79+/f+7cuR2tP2icUhHRcxLuK08vcSgUCgQCgUCACnrNGN+2TW4xunA/t6iEcAh9W+pNBSlSEJzKGeWTIYQIIp9/sJBhUELPeDmkdDHvdgxgYrhKKfhMwQGUHL8+84JoTujIVVF1zk8Irit5DgQ4nsMEY5VwPKcoSljVxFPPYmsvD62ebmlpaWVl5cCBA7XVqOOy5p3Jsmx5efnrr7/O8/yiRYvsdvuZ1089z6FmRarSevfuPXbsWO2rJ554Yvny5Waz+dlnnx0wYMBVV12lpTwPBAI33HDDt99+CwCLFy9etGhR094jzW8MAAwZMmTUqFE0OnDGjBmJiYma17jZbKZJYxr/UCvx+MADDzzwwAMNthkO1ZFaEhuWZRcvXnzPPffExMSYzWY6gGy8/Q4+w3P8+HGEUFxcXGFhYUFBAQ1MpDlt7rzzzoiIiKysrJkzZ9L41F69ekGYrg23rTZwB0enynCiKMrmzZurq6ttNpvX6w0EAikpKbRiFO1L4Y43dC+01DFN9Mnz/Mcff/z2228LgvDII49cddVVV1555Z49e7788ss5c+Y4HI6//e1vKSkpRUVFBw4cON3xUhmtLZ9SPdOpJC3n7O9CZx5o1sjG39IPr7/++jVr1hQXF9tstkmTJjVoSccnfCwK9fZ1ag2hTlb0Mmk63u/3Q31FZ1SfJ6rjGOM7x7xA58Lv9xsMhrrcuoQQhOZuzR/nL54ZY/Sq5ExGqQQTwcBv/HyLI94xeOrAsxWW2hHmvGgvNDPsPr97SWX+qMTUp0ZOAuo208g9JhAI0AJvbd3KVkEdBFtRdby9oNXvWpHEt72gb6lzMXFcVVVlt9sb5LZjWCY8j1Px0eLlr63y1npn3Tl94IUDwrfQ2A6HMa6srNy6deuwYcPS0tKOHj1aWVnZt2/fioqKqKioTZs2DRgwID4+/pZbbnnwwQfpXDz1W/jjH/94zTXXhEKhpUuXLl68mFZrat1xVVdX2+12mkGli0EIyc3N1RwYmliNECKKot1uj4iIoNpUU8kzZszYsGGD3W6vra196aWXHnnkEc2Iu3nz5hkzZphMJkmSDAbDiRMnjEZjY7+m1rUcIXTixIlXX33VarUuWrQoMjIyXGLSHtiEFNOS1TSzVDtNz6IVZuqwBtTTQV9b//vf/2699Va32929e/fvv/+eRtCejlZfKXr+EUJvvvnm/fffDwBjx4799ttv7XZ70z/ct29fXFxcfHw8IeTo0aNTpkwpKyvDGPfp0+eHH35ISkoCALfbbbPZduzYMWvWrJqaGrPZvGTJkiuuuOJ07+WDBw9mZ2cPGjSI+kQ1aCfG+K233nrxxRcTExP/8Y9/jBkzpvkX93Tnh36+fv36NWvWzJ49+4ILLjjdmp3u3QGn8UukNnjqTkMT14S7xZ/SoyY5OdlqtbZNmzv0YLqzgwkwCB31K+Uu95BIXsJwRqqdEE7kqktqXFXuIdMHK1LXMbdT53WRQd+6yr53VV7uSLg8tjucRrXr6LQX1LzqqnQf35vPcAwQglWy9r3vjx84wXLMksc/m73oUkecQ5VVrKpxPeLi0+OIWpdaTns9PPnkk717996xY8cjjzzy6quvDh8+XBTF48eP//LLL926dVu/fv0jjzxC5+XpTumvOI6rqakZMmTI/PnzO5etq+OgWUZ5no+MjHQ4HOHmZM0Ufdddd+3cudPn8w0ZMmTevHkQJpdjYmJEUayurgaAPn360NH4WRkxUinQrVu3v//97+Efagu/uxda86j5+psORehkQqdT7VCfnOfKK6+Mi4vLy8sbN27ciRMn/vrXv06aNOmGG26AME8VelrOZHylybX77ruPDrOnT59ut9u1OM7GPwkEAo888shHH32UkpLy6quvXnTRRRhjp9NpsVgURXG73YFAgLbQZrMRQkaOHPnjjz/u2LEjMzNz3Lhx0Cj7EO2cGzZsuO666yoqKpKSklatWkVzg9LLR4X+9u3bH3nkEZ7n9+zZ89RTT61cuVIUxVMeu9b4d955Z9++ffPnzx85cuQp10SN0n12FqtZczilMV4QBJPJRGsLUO0eCAR8Pl+4WzwdIbeL7VsX7ucQqjt31ARtIW+MIATImYpQhmFOHCqMTIiwRVnlkHx2NG19ptk6ozfdZl1C2jrFcTZ2c1owEBGxMsHvVZwokgIL49K78waPqsbroag6HQ0CCCFnuWvL19t4kQcEiqRUnKgUDDzLsT6nf9vSXxzxDqzikD80avaIxJ4JCvxWZoFOYQ8fPvyuu+5at25dVlbW8OHDFyxYkJ2djTFOT0+/5557/va3v1ksFjq5D/VhhYSQp5566quvvrrrrrsmTJhAZ/y70ruzbVAURRRFh8OhWdkbyBR6tq+44opevXrl5uaOHz+eFn7XzN59+vRZvHjxhx9+6HA4nn76aY7jzqKtmooAzbrfiuvbip90RskeTigUGjdu3Lhx47Zt23bJJZf4/f6PPvrI6/XeeeedDca3rTg51JtcqzBKP5w6dSpdCFft4RunvukbNmz45z//GRkZefTo0T/96U/5+flDhw598MEHX3rpJYZh7rzzzp49e9IW0i2EQqGBAwdSf7lTqmfa095+++2KiorExMTi4uKVK1cOHjxYW4Fup6amRpIkq9UaCAS8Xq+iKLQuQeOjo3t54YUXnnjiCQBYvnz5xo0be/fufcouTQe99KvO3mdOR/g51+a4EEIGg8FgMNDxlSzLfr+fKnhJkhonqGkbdOF+DqGe2ZvKXcPNDMcwWCHsGVxchmGCvmBJdumQGYMBgABpZd0leg/TuswIAcNQx1tgGQAEBAMhgAnBGFSVqCpiGDg3N2q9ewxXJAU+rDxhY/mHEjJsLO9VJOO52J+OzpmBGKSqamq/5Hvfu0v7cMUbq9f/e4MckjPH97n99fmiqc4FRRNhv/0cIUIIDYyjL2yHwxEIBFiWVVU1Li5OkiSj0aiqqsfj0bwqGYZxuVy7d++eN2/evHnzXnrppZKSktTU1AbRqzpNQBVSTExMRERE+Dz+6YyL/fr169evH5wsoejCggULrrvuOuoX2yILd3Po+D7lHQ2EkM/nE0Xxxx9/9Pv9KSkpxcXFq1atuvPOO8/QFHq66IXw2FBq5NYcaRo0DAAkSTKbzQcOHLjnnntoPsoZM2YghMaPHw9hCTTpBumWEUKn3C/dYO/evRFCtbW1DMNQTxvtMGlLLrjggssuu2zdunUWi+WWW26xWCynG1vSPX755ZdGo9Fut1dUVHz//fe9e/c+3Xmjh6zNY5wPD59wY7xmiRcEweFw0KIKwWDQ7/f7/X5tgrRt0J8R5xAE4MVwqKJ2lpnIgBC0/jlCCOFF/vi+E6JJiOseI0u/48TZ4Mf1DUKAEHAsYlhgGGAQyDL2B4nXq4QkEggQnx97PMTrx34/yApWZFCxacYUJi4GFOVME+KcDAbgAPEMs81Ttby2bKQl4vKIRBWIjFXu5AEJhjoXIxKWLTd8WUenLSGYKKSu+CJC6JJ7ZqYP7uF3+wdM6ieaRC1D6yltZqIobtq0yefzlZaW3nnnnTk5OQzDKIoSDAapz7HH4+E4rqKi4pdffpkxYwaVcQ6HY+fOnVlZWTzPWyyWxMTE8OqPOk1ARYbD4YiKiqJpHH/XZYIKKe1V3eDbYDAoCAJdoauaHtsYTQi2YvqCzk5wHDdixAiWZYuLizHGEydOhDOekkIIbdu2ze12jx8/3mKxaN0mXFWzLBsIBLRsg9qHADBlypR77rln2bJlVVVVdJ6ntLT022+/Xbx4MZymEzbt/0bXnzJlCg1xAYD9+/c3Hlja7favv/76l19+iY6O7tu3bxO9lI5MZsyYceDAgUAgEBERET6cON1PtJvirIR2dBYaO8EzDEMTTUZERGCMA4FAW4ax6cK9KVo3ZKfPdEwIg+DnmqBVCfUwskEVn2H6dqyqBVkFSb0TOIEL+UOnvbtoNqv6BcSywHOIZQnGoKhEknClS62qJrUu7PaQgB8HQkSSEM8DyzIGEVktjN3CxscyBhEZDMggIrsNVPWsqHYVCAGgpVFMDOvD6peVhbuC7hujU8aYHG5VYRGqBWwFQAQIIYi6vyPkwwohYGE5TAgGAEIYAAIkiLERseQMRkRtAKmnvRvSXEh9QrT2bkhzOUen93e3iaCuTEn/CX0BAGOsyApiTuv1iBCSJGnUqFGyLM+fPz8pKWnixIksyyYkJFx44YX03XDZZZdZrdabbrqpvLy8tLSUOlOaTKY//OEPX3/9tdvtvu6666iF/kzemo3PWBd7B2vu7GazmWZNCf+qOT8/3WrULxw6v5NJxyE8C2Er5CD9+fTp05cuXbpmzZqhQ4fOnz//dPby5kDHD6+88sqjjz5KCJk3b97bb78drt21hZdffvmbb75JSUl57rnn0tPTtTzoAGAwGP7xj3/cf//9n3322TPPPBMIBACgf//+NGd8K8I36Q2bk5Mjy3J0dLTL5frxxx8bh7sQQgRBmDBhAjRDW2OM//jHP8bExBw/fvyKK64YPHhwEz+hX9XU1OzZs2fAgAFxcXHnlXYPR+sGUD90DH/CtEUDOtHruY0hhLTOrBUIBAyiiBFj4NCD+yv9hXkPJvK1KrQ6moxgwot8RUHlrtV7LrxxgmAQTn3VqJ86AkAIWBZxHCDAbi+udarV1aSsAtc6ISQhlkEGA5jNyGJmHHYUYSdmEysaEM/VG+MRIBTuMHNW3NwJgAmQCEgBUBEcDnr/5yzx8xwTYY9muWtVUzTi1oF/AxMcpLB3RKSkpKUBAALIC/neqjoRIupTcb1UIM+WZr8bn0kEblHR4dmOhKnWaImorfQaahOInlXmHHPusso4nU6bzdYgq0xjaHbIpoPFqZLw+/2fffYZLWgvSZIgCDQ/DBUfsizzPE+Ls+zfv/+vf/2rKIqSJI0YMeL++++nB0hzt53JcdXW1prN5gbX91ycwLaHEHLs2DFJkgghoihGR0efrpBNq+l0d8fpOEd3TYugyi83N/eFF16ora19+OGHx40b1yI5SCuPnsUUSXTv1dXVU6ZMOXr0qM1mq6ioWLNmzcyZM7XE6tRDZt26dTNmzBAEQZKkG264YcmSJQ3ywGgH8sILL2zevHnixImPPPIIqi/m1WCnv/uOoFvLy8ubNm1aXl4eALz66qsPPvhg49PVxHxRc469ia+ys7OvvPLK/Pz8hISEL774YtiwYQ0mSfS7o23QLe6nBSHUOrElyzIn8AgxIQLH3P7LzEhlOR5I67sAA5zAFR4qjO8RZ42wSkHpFMYeQoBhkMADICJJuKpayS9Qyyux0wWqiiwmNi5W6JaKHDbGZmOsFuBYKs2BYFVWWIYhNESVjlXCPVHOkmGJA7QafD9hf18kRrsDGz2V1zgS1ljQ/yF7CZbXsKHLEb8dS+8xcYuZ6l84NZ3nFUI4hN4qKfhzSl+Z4FdKc/+Y2KsWK5zR9M/KvHSTdWpEHAYQWj8magtIfemH9m5Ic6EitRM1GM6N7tQSblBDYFOrNu8WQQiJojh58mS32202m1mWVRSFbpzaCGgRHI7jZFkeOHDgZ599pv2Wlmei6v/Mbb0cx3Wu69t86FxEVFRUVFTUKSNQdToI9J7y+/0LFy5cu3YtAOzcuXPTpk1paWmtC/mlKe3Dzd6tbpjZbKaVsAghycnJqampWi5/reUVFRVQX5OovLwcGs0Y0GkfhNCf/vSnVjdGg242LS3tm2++Wbt2bbdu3WbPnn26NX/38Gk7d+zYcfDgwYsuuig+Pr7prNCqqnIc949//OPQoUNRUVG5ubkfffTRsGHD9DurXdCF+zkBE+AQHPDI1U5Xv3hOwmdkEEYM8tX6Kk5UjbpseEMBQf/JcUjgiT+gHMuX8/KVomKECbJb2dhYYehAJioKGQTE8YAQqApRMZEkCBHN+4VgHF6IAuAs+4+rAGZAP2H/E6RKBbKWeIYieD42va/RulQu+//27jw6qipdAP23z1RzKqnMA5lIIAaQgMySBJDBFkG0RVGccWqVvl67vbfbpX3bp/28rmc73NYr0Np6nQ0gijKrhDkQUAgEkEASMs+p1Fxn2u+PDdXpIMqQkBR+v+VyFZWqU/tM+3xnn2/vbeAgkvBBStuoOoSIJuAigT9JZQAQCOlQ5RHmiH1eJwF4cdCwyqA3TjCUuztalOCfU67QgPIDuK0doe4opYIgZGdns3YpOGPaFzjdFMcS30PDwLP+ajgE5M+ilFqt1qioqO5TY2JsMTCxRGGn01lVVWU2m61Wa319fUVFxQUH7uwEucjThPVwMBqNzz33nNlsrq6uzsjIYHPKhj7DAvT8/PyJEyfu2rXLaDTedtttrDN6j3tF9i3WVL958+bly5dnZGQ8+OCDERERcEFHZvee06ECn+9C2OZ9//33H3roIVVVr7jiivXr1ycmJv7sLW5iYiKcnp4iKioK8K64n2Dg3idYOF3a7k2hwUhR9OoX3txOdSpZpGN7Ksx2c0xKjBI83S2VUtaCRynVmluVw0e1ugYqy0JKknHCWD4xnouMBAKgalTXQdOpGmBfATjdS/VSoUCNhK/hNE2lUcB1AURGWLOJpVNTZhPLH/Q2CvBnLrqeqlHAy0DNQKTTdxIBXd/U1TrVpjepsldX863RVbL3hZaK4dYotmiM21EYoZSyRI6f/SQOMHIBQkNtoIGPtY7Hx8dPmzZtyZIlPp+voKBg/Pjx/d7rlxCiadqkSZOWLFly2223rV27duvWrcuWLbvllltYszQL3NPS0lauXLlly5a0tLSJEycCgCAIgUCgx+SA7Hb98OHDt956a2trKwDU19e/+uqrF5alTLrN+HvBDxbYll+yZImmaREREYcOHVq+fPlvf/vbn5gggg1Z89hjj504cWLlypU33njjo48+ionW/QUvDH2CDfv4fbt3hJnwhKMXkSdDOKIElPof6jPyMjieAxlOjSZtNICiKseOywcO6U4nFxtnGDuaTx/EmUxACFUUGgicXkQ/BOuMDpQHYuOEo37PYW8r2EgnRwFoHhVl0BWA72ngIWLvAn0D9Y4FkwwqAZCB8qcHi+QI2Hn+N/GZLk39Q+2hKbbYdlV+PnnIy21VR/yeHJNVP9c8BYQGBDYKW3+XAqH+xwL011577aqrruro6LjvvvvYlDf93vGXDXr47bffbtu2LTExsamp6Z133rnllltCBWMN84mJiQsWLAAANmPaU0899d57702YMOGtt95KTExkDdssGt61a1dHR0dcXJzH41m/fj3rzdLjR88xIr/4jcOaybOzs3fu3Onz+XRdZ1ND/ARWHpvN9tZbb7388svsiQHg46x+goF7n+AIqABVLu8kkWpw4Q3DVKeSUaqvaAgGlEFXpChBhRAgBgNVVfngYXn/QeoPirlDjNMK+Nho0HWqqDQY/GcX1f5DTze0y1Rf0Vm/y90xzRbzK8G2H+R0EGYSiwzUCRpPyBRi7gBtK/VPIaRClx3A+Si1w6mOfg5BsvMSAAiE8AT8unaF0TbWHnuzLr/WXLEkfRTe8iOEUPiSJOn+++9nrwdO6gXHcXa7HQCcTielNDo6Gs4Y15/NScQmOfr4449fffXViIiItWvX/uUvf3n99de7Z8sUFhbGxcU1NjYCwM0338z6u/domL9ktyvst1544QVZlsvKyhYtWnTttdeeyzg8rMwsah84e+oXCAP3vtKpUp/flxwJMr2IEJoABVpdVp2cnWgwSbKqc4KgHq8M7CqliiyNHC7l5hCzmaoq9flPtamT/h9hRQcqAGfk+EN+14qOehPHPxafmWGwEEoLqZkD4gddBkgAQaTkTehSgA4DQwYIPJA/045O0O7mLTWyv1OVR5rtWUbLi43HNEqnRcRRoO2qTGXl147kz52Nn7bX3Rqdgo3uCCEUvtgzqIvsVNqLWAh7/fXXP/300+vXr09OTn7mmWfO/BjruS4IQm1t7bZt2yRJYultrN8qWxfWNp+VlfXFF18sXbp0+PDhixcv7rEcNoZjS0tLcXFxZGTkjBkz+nQ7sDuExMTEjz76iOX2wLm1nXcfDXOA7KlfJhwOsvd5fT6L2by9I/j8jkP/b4JGuQvtK0OBEzhPp2fLR9smz58UlRofbGoJbt2pN7eIeVdKecM5k4nKMrCx4S7iLPrp7uTnWWQAADPHd6rKamdjud91TUTctIgYAiRItdAtDDn9HwXYQH0mINOIGYB2Ad1AvWN16erYRE9SnEtTRprtAPB5ZwMBckNUokdXD/pcVwlm0WCoUwK1sn+S1THAA3ccDrKv9d1wkG1tbXa7/WeHgzwv3TuxnVdhfrRBji0NANjE7OeyqPb2drvd3osj6P2ihN3ZcTYDfMC7c9Trw0GeyeVyhTJDemCXzk8//fSpp57q6upSFIUQYrFYPvzwwylTpnQ/Z396pEUAaGpquvvuuzdt2gQAzz333NNPP31hPXTPXWj5vfhDeHZcGtji3vvYFf6AKxhJVJsoXPAI7pRSQRIqdh9zDIqJTot379gjl34vpA+y3D6fi4yggSD1B06NuT4AUAAKYOQ4ndJvXa1fu1qTRePjCVlJotGnawCUO+NBANtQtxCrDuACHQBsQO4ndhdRO3V1iOHUuBA60HlRSeyFlRMmWh0+v18EGCSZBkkmGNhRO7r86fTUaajr53IysmfrLM4OxdxwOgRnbXhspPbQcHI8z4uiyKZL7HGJFQQhdA+AqfMI9S7WfTM01U73P7GEE5fL9fLLL1dWVkZGRsqy/Oyzz951110JCQk9Ul9CeTVshNnui2K38Tt37ty0aVNSUlJHR8fnn3++ePFiu93ep+korHgDoUcBOl8YuPc+Nrbi0S5fMlEoiITSC8hdoZTyIt/V7Gyo6Zgwfbi76HO5pd187TVCViaV5VOJMT854culpAOVCCcR7rDftdrZFNC1X0cljbbYVUq9unpmyN5dB+gAp+5tNIBW0ACoFQjLkueAcEA0SgGAJ4QC6PRUT18dKFDgBsZ9C/pl0XUAAgSAUiKKVNdB14kgUFU9NXYT+/8ZByd7Js5apBRFCb1gD9xZCB56PqPrOnvH7/eXlpay2RBVVQ09sOZ5vqmp6bXXXhNF8YknnrDb7Rc5oyr6WZfN5r08sh36ei3YaCpn+4nuUbimaYFAoLCwMCEhITRVU3fsnvzMhbA3U1JSIiMjm5qadF1PSkoym82XJom8d3/iMjiimAF+dmDg3vt4ApRCiydwtUS0C85hocDzXEVZrYP6zdu+1WLjrHfdypmMuiwDIUQUQKf/nNCU5yghQIHo+j/jBkqBIwCkV+Y9PUsZgQIVgDNzfIMSWNvZdCzoudoWPT0izsTxfl0DgJ+O2gH+5XEEAeAB9NOvQ9n6fKg/ULfXHPR/Nj/6JeJ5cjq1jADIFSc8//uW7nRZ7l1oKpjU/WSj/9oEzgaGO378+NatW+fNm+dwONavX280GtlT9ebm5q+++mrixIm5ublHjx5ta2u76qqrPvvsM9atrby8vK6ubvTo0Tk5OSx2Z2H9q6++euutt8qy/Nxzz7300ks/MaBbeBmwTw9CU2X1d0EuFluRgRydnAs2MVl/HfO6rpvN5n/7t3975plnnE7nk08+OXr0aLZhz+sAVhTlqquueuWVV959912Hw/Hss8+GZmfrs7L3CTw7LsAFdO3AwL2XUQCJI62K7gwEMkyCegFzk1MKFHiRdzr98r79Q7guLn+qYeRwCMrU4+P9AQKUCoJuMobuCTiXh6ga5YhuNgHHga4DxwHHgU6JqlBJgD4I3dlQjyZO6FDlz52t33ud2UbLvyUMThZNfl3z/VxDO0Lhh1LC81pbu3LwMPA8UAqa7v2/j5XDR4HnXc/9f/qj9/OxMVRVQdOE9FQ+IxW0Uw/cQtPNrFmzhhBSUlJiMpkqKysppSaTafz48atXr7bZbG+++eYzzzzz8ssvT5gwYfPmzTab7e2333788cfLyspyc3NfffXVv/zlLw6Hg7WsU0pFUezo6MjLy1u0aNFlE7UjFBZYVtttt902adIkt9s9fPjwUD7MeS2HEKKq6j333HPPPfewd8IxakcX4MJ6T2Hg3vtEAtV+JRDwx9o47bzGgaQUOI6y1nSOeNd/k0677PcsEHnRuGGzd+pk3uW2rf0GREGsrvVOmeSdejXx+UHXzVtLxJY24vPpVovrxtm21eud991GZMW+8svAiCsCI3JIUO7FVHgdKAfEwgleXV3X1bzV1ZYgGRfFpmUbrQqlHl1l+S299XMIDRSUAiFaa5v/87VgkAAAVFWrqycGAxEE6nYHvlzPxcVSTQV/wPirGUJmOgU1VAewB+s8zw8aNCg/P/9vf/tbdHR0W1vbjh07xo8fP3HixBMnTrS3t3d1dV199dWTJk0qKSm58847/X6/pmmDBw9evHjxG2+80dXVxUamY8HBn/70p6KiokcffXTy5MlsMOZwb0NlBuwdCEuBGLDFO3fs+U9/l+JisQHX+3d36LqelpYGp9PYLnirsk6iLJIL012DZ8elMXBLFqZ0AJ7njrqCYtBvEyQ/PeeplygFUSBev6G2Xo2Lce/Z5ztaGffAbaI90rL8C2o0AqVabHTHQ3cRRYl6f7mclQGKCgDA8+65M7WICPvy1XqUHQA4n1+3mG2b1mnRUYGRucQf6K2onYXsZk5Qqb7d3faNq00i5Jbo5CvNdp2C79xyYxAKVxxHNU0cmh352gvsDQLgXvqu74MiXZYNE8baX/gvzmQ83YRCqaaFTj3WFdVsNs+bN6+0tHTJkiV+v1+W5ZSUlJycnJaWlk2bNsXGxgaDQQCIjIz0+XxsrAyTyeRyueLj41VVlSSJXdpZgntXV9e+ffsWLly4cOHCF198saGhITU1NZQEj/rCBbSQaZrG8pUHVEDDjqJwP1TYWvRvGVi7+8WEemwtQlF7+O6Uft8XvWWAnx0YuPcyAqDr4OBgWqR4HocwpVQUhNb2qL9/KLS2ciJfS0y+X82OSEukJ076x4wSm1tB04AQoijmXaWa3SanpXBuD3AcUEo03fjDcam+sfOafK69Q7dZDT8c5z0+19xZJBC8+Kg91E/UwglBXdvj7fymq0Wh+tSI2AlWh0C4gK7BBc4xhVC4oRRU9dRLINb775SuzNVdHsPk8cRkpIryz1FPSfcvUY7j2tra1q9fb7PZVFUdN25cR0cHuzywP40dOzYpKcnj8bS3t8+cOfPrr79esmRJZ2fnvffe6/P5eJ73eDzs86z3amRkZGlp6eHDh0VRtFqtSUlJ6umCoYFjQMXrqC+wtJatW7cqilJQUHDm/ErnaMBGimhAwSSqXsYBBHV6fazhlgSzXzufWJbnjQcOS5XVOgWusyvBYkkeMwT8fiUtRY+yn2pcBwCOMxyp8I8bRYIysBw4SnWzyXCkQk4fpEVYAYjQ0Wlb8w3leSqJoGmnh2q8QDpQDsDCCRwhu9ztrzSfWOtsGmeN+l1CdoEtRqPUr6sEo3b0i/Kvk50ZJo4zzZpGzGZQVeC4H50HjbW4x8XFjR8/vq6u7t57750zZ47FYjGZTCNHjoyJiZkzZ87x48cXL16ckZFRWFgoiuIDDzzAcdyNN96YkJAwbdo0Xddnz55ttVobGhrq6+vr6uo6Ozv/8z//MyEhQRTFO++8kwWIeO0fIEKtj2+++eb8+fNfeeWV/i0P6iNs8NZnn322sLBw+vTpv/vd71jP1Mum+RkNNNji3vsIgE+nPp2exwVUp0A4arOCpvEAmqJHpcWRaJvqchNOB01nA89RgyQ0NmvRDjXSTjTt1HAxHOE8HhIIBHOyiKwAx3Fev/PmGyLWfi1V1qhpg4isAiFUk89rLViVwwMxc4JbU7a62rZ52lVKJ1kdk2wOKyf4dc2L6ewIAVBFBaCnQvaz4zhOVdURI0aMGDECABRFufnmmwFA0zRVVSdMmDBhwgT2ycjISE3TbDbbgw8+CACqqmZnZ8uyPGTIkN27d//P//yPJEmyLI8bN+63v/3t/Pnz4XSyL0btAwfLvS4qKnrkkUcAYMWKFaIoPvbYY2dOeMf23cCZNxSdO7bjqqqq3nrrLavVajAYli1btnDhwvHjx/fizIYIdYeBe5/gzvdZhsATReloaOAHpxlane7MTGXWNAgE/hkVE0Io1SVJqqnRzQbdYuJ8ASpJwHEEOM7l4Z0eNSOLo4SjnJIQGxiWJdSetH6zue3W6dDZTDiOjxoMRDiXpneWGGMkPE+IU1O+6WrZ6+nkCJdvi77KHGnjBb+ueXSVYMiOEMOd6zMnQogsy4qiGAwGjuPYRINsMiY2BySL3lhejaZpoSmZFEXheV5RlPHjx3/44YehBbLh8FjKO4Z9AwrbHfv37yeEDBo0qLa2tri4+LHHHuvRENs9/X0gp9WiH8X2l9VqjY2Nraur8/l8CQkJdrsd8NkX6jMYuPc3SoEQIgjez9fwunZy4e17v9gzccHVEUkxEEpPp0AUjXACGCxCVxBEK5jsEFSEllbi8wTiTVJjA9dc7W/dRbpa1JY2S32FvO3VdoOS2NIgrax2j0wWBAcXmUE4AErPFmGwfBoOwEQ4IOSk7Nvt7ijzuxyCOMuekGexGwgX0DUcNAahi8HmWmIX9e4Nct3nZ2F/7T5CBfsTa7MPDRHNAj5s1RvIrrnmmr/+9a81NTU8z7MHLD3iOUKIy+U6fPjwiBEjLBYLxu7hhc2oEBsb+5e//OW///u/g8HgY489lpOTw27CL375oYFf8TRHIQTTsHpdIBAAgOPHjwcCgZ+pgqlOCIBk8K3/Wmtqsd1207cf70jISMibnhf0KYTnQVco6MTnIR1tqhk0zcWfPKFrXiXSqMtBoa2DDwYCSQ5B5oxBsz/OyPERPG8z+oyBJCsRraIrKPj0YHYGpxGqK2drblc1jeM5A+EFQvy6Vu537fZ0Nsj+NKP5amvMUKOVJySgazrQH5kKsg/ouu5wOAYPHny2D/j9fqPRGC6XN0ppaC7MsMCagdmknmFBUZRQKNyLdF1va2uz2+2sq1lvLZZSyiY5760Fnq/29na73c6GrEHn6wLOjs2bN+/cuTMvL2/27Nnd43L2uqKiYtGiRaWlpZMmTVq2bFlmZualmYW+j86aS4w9pxogB7Msy6qqms3m8/3i2a4RZx4tvVDKvhR2146zOfPsYPlsA+TZJra4X0r/2tpNdcoZddEkF3+j1jQ67ltQVlKp6+LQCUM8rY2c1kV9bbLPTeUuqiu8IFMnAU7SHEYixfCiw2Kz0mERqm60CxIIgqKBGQTJYpCDukJ0UdFB13QbF+SABIJsiKkeRaFACRAewMTxAsfXyf7vvc7vfE4CZJgp4qaopATJQAECug4UCI7ziBBC54lSOnXq1KlTp8IZsRe7f/vrX/+6bdu22NjYb7/9tqio6I9//CO2poUjXdclSZIkqbdS29nRUlxcvHfv3nHjxhUUFFz8MtEF6z6ca7/fRGHgfmlQAKBEJFQFqgMAEAK8yez93lj5beNJi23urIbjFT8U7542RY2p2MLr7poGSTanpUmlqiaKolDjnxWVkSgZDR77BFF3GmvWbFsdaU8Xhs9IOr6jknAk46pB3i7fgdXfDckfbLabNNZNTQZCWQLuvxSFAuWBGDlBB+pS1QNeZ3nAVa8EE0Tjr+wJV5hsdl4MUM2v62wUyH7ZZAghFO7YaEI/ke3AGtfZOJ6YDhG+QqOw98pOZJk2a9asmT9/vt/vNxgMq1evnjlzZm9l4KBzx8J0j8ezbNkyWZYffvjhyMjI/o3dMXC/BCgQngInyK2aGEUFE0dA0zizawdfVlxbJqdOqK0+qZV8LQyblJ0cWx6IvbauwVF26Iexd+bLSXdsfatkyrBdXV3G4O7vhoyLcUVONlR8Un2oPedX95ev3d9QbvK0u2WPfMW07D1F+wSDaHFYNUUjhAMAON1lLtS+zgFIhJMI16HJ5T73915nddBv4/ghJusNUUkJopFlxbh1hQ2Q0XNMO4QQQufjbJEce//JJ588duzYgQMHZs+evWDBAmxuD1+9GMmxAP2jjz4KBAIpKSn19fVr166dOXNmvydp/NKwmZhkWV60aFFRUREAbN++/dNPPzWbzf0Yu2Pg3rcIAAVCNF907fuS55hiTm2PvjbobFb9jcauo00HuJL61H1r7O1ey+BpI664tlA43ugMRLlcXHRulq4qPi1m6GizJSbBmnWdZ/VzmjHX2LWf4zluzL0JWY76pMj2mk7JbBAkoWZ/HaWQd8MIxa+Egm0Wr8OpYJ3Xgfo07YeAq8zXVR30aUCHmyIWRkeni0aLKAV0LUh1SikOF4NQ3/npyIxlwMPpoWYuVaFQP2D7NyMjY82aNT/88ENOTo4kSZcmwR0NcOzYKCgo+Oijj+rq6gAgLy8PBkCSxi8NG9S1srJyy5YtdrtdEITNmzeXlZVNnDixH4f7xMC9j1FNlyIjGzZYWr/WOaPkr/G31/pipnKBaL4uGIyQhluPVVTGN1YER80xUS3Iu6scoichmTsYHKzpcYSDwdFHal25pZ/vmVk4mHediPDvcaXMj7VG+js9nXVdQwoGd9R1tVV31JXVj/71KF2jmq4TjrDGdZFwEiEahSYlUCP7D/tdJ4NekeOTJeO8qMTBRouZE3SgPkVxa9jEjtCF0IGyc0c7h7wyNi96IBBgF+AzH3wLghDqtxoaPQZdxiilBoPhyiuvBAzL0GksInzooYc8Hs/mzZsLCwvvuusuwCEmLzmWAZWYmJiVlbVjxw4AGD58eHp6ev/eYGPg3ncoABDRrPs7acs+QjWdM3Cq35Q2QuQmezaujSiIq/+GbNkaf8/8fQ0NGe5OlVC5K/EmxZpl1JqTTrzdwY3lgx2aRoJSkih2VOyoLpwFLmO6uWWbL+reQ1/u50U+ZWRK87E2V5MrdkjcsR0nJi0YI3ACzxGV0oCu1cjeI353TdDXpgUlwg8xWm9yJKcbLJG8qFBdobpXPzUhKzaxI3SOQg+y2D9Entd1XQMQOV7R9dDYTWcOwcSi9oaGhqSkJADQNI2NV8NmXmQ50E1NTa+++qooik888QSbhgkv1Zc3lv6OEzChH/W73/3ud7/7XeifeIRcYuz0jIyMXLp06SuvvCLL8uOPP56YmIg57gMFu3z2zl0U1YEIAIpcszXYuM9pzzHzQYPnmOYY3NGZ7tn8mXV6gZrWFCg+Smz2rk4+dVh0yuh0UAOaFK0TSREdVDASTjD6f+jymGOuypqcRsqeXxmMnNIecWNq7f/zwzfrG08aCu8bRVWN6nrGyJTJt435/E9rTxxpgIyISqfrRNDXqgY4INGClG2yzjMlxQqSieN1gKCuuXWFRRUsXsdmPYTOnUAIcPyp+JzAAY/zP+oOtanKM0lD5zmSQu+DTjXWEx0ATjemtra2Pv744/Pnz582bVpkZOTBgwczMzNNJhML3QRBePXVVxcsWCDL8vPPP//SSy+xB7X9spqoj7CsWY7j2Ey3DO5l9KM0Tes+RRe69FiAPmzYsLfeeou90+9PxjBwPyX04KMXdgnViWCgisdX/iFHNeOQubw9q1WZaVRq3Ec6vaVVMTdMrRMSKz//euRoyJyameyvSMyeZbDxqgKOhk/dsdcaaGerXwjoZjM07dtQHmnq9Hb5bbEGXQnSIHWJBZldRbHX/kF0qQGDGtS0EwF/dUfdsVHm3UUlvjuz4wRjpsGcb3MkS6YYQdIBFKprgcWdPAAAIv9JREFUlHp0FQAwhR2hC0MBeEIalcAOT4dACKWgEvqXhh8OeDsBuHuq9v23EkiRTArVVarnGm25pgiN0u4nm67rmqa1t7dv3779hhtuWLly5UMPPWSxWEIDj4ii2NbWlpeXd//992PUfllikTr0ViMRuqz1bg0Qer6HFcv5YrfZ0C1W7EcYuJ9CCCkrKzMYDEOHDr3YZfGS5mn2freUs6SZsmYDLwKnaNTeXqKQk43SrILvTwarStdfkT8zdmhLsnOLM/PXYE4Umr/WbUM7U263N30BvMUVd2OEMahC7PC51+7dVWm1mybeep0zIJcfPeS3R1FjYuW2tQ0/WPTr4i0WsBt50ukamZcmdArpwZj0jEQS1HQCsq67dZWlreNA7AhdJEop4fg62f/31mojxxMAWdePB7w8x0uE61KVf7SeTDWYFEq9unp3dOowkx1AZ0M7sYz2+Pj4CRMm3H333e+9997+/funTJkSGxvLctnZVeG//uu/ioqKHnvsscmTJ2dnZwM+HL+MsH7Jfr9/6dKl69atu+GGGx5++GHMkEGXDLbcX7Ae01r3LwzcT427VF5efvDgQXZMDx069ELb3SkAAU0J7n7OGJNJhywAxUsVBWrqg9t3yUG1JXlI7daTJpGbece02GRHMJgj26YZaNCg+vW4aZKuUCDu9IcUoDHpckBR9qvDupJV76/9FWpwY8AU4GU506fJisE8yzFYz53Cx3jUtCFxqdExJgVUoHR+giZr/oCsAxCcNQmhXsURounaGHPkhiFXAwBQCjz3TG35i00VAV2faY//bPA4iyACZcE61ajeo7c3pdTr9Wqalpubu3///tTUVEEQgsEgz/Mcxzmdzn379t1+++233377iy++2NDQkJqaqqrqQLhUoIvH2uo++OCDJ554QhTFTZs2SZL0wAMP9OPwFOgXgoU0Tqfz7bfftlgs9913HxvCCOuWcISB+6lew+3t7TfddFNzc3Ntbe1FBO4AAMHjq5pbXb60KerRQ8TtDlZUdVXWtpsdzdYE0uZJHZ2SlJvi1GldR7tM9ADoCoWArntV2atrLlX1qbJXU3yqBhQkqvOUSjoXqWqJlNh5IZIzWIlopDpPOOIHlQh2jWgB1Ul1AgAuGU49hmVd6M5J6BnQAMEmFv6JD4SeNYeF8CotDIwWhfPSR1v4bMvUASjVAYACcLr+bPIVV1ujOzRlTmSChRMUXWPn35lfZrUKy5PJz89///33Z82aBQChCdujoqL27dt35MgRURRtNltycnIfdU4Nu118eWCb/eDBgwAQGxvb0NCwffv2Bx54AMduR32NECLL8m233bZ+/XoAKCkp+cc//oH1QJjCwB3gdP8PjuMMBoMkSQDAcZymacFg8LyObF1TJaP5cFX9G3WDoX1Po51TCaXZDu+wFJ3jLRbJEmkBSjVXA9EpDyAAGAgxUGIhvJXjbYI0WDJZCWfRwa6DiXASxxs5TiAci8J1AB2ozkIHADa4hc1mM5tMF1P1D7T2HkqpJEl+v/9sHwgEAgPtZuMnUEpVVRVFsb8Lcq4URYHTUzmGBUVRBEHo9eOB3UCGss9//DMAAHCtNQYIUXQtoMk/UQg2kcfdd9/t8XgEQbjzzjvj4+OdTqfT6WQ/YTabn3jiiZUrV7pcrltvvZUlxPf6elFKA4FAj7EmJUkaUJXAZYl1Wpg1a9Y//vGPhoYGm8125513Aia7oz7G0gqOHTu2bdu2qKgoSmlRUdFf//rX6OhobHQPRxi4AwBwp4XaelkcbzQaz2s5lEocx2VOuOuR1FYpKoLEREomiQdiACoSwusg6iAQjiOERe08ECE0xyk7ec44g0IN56G/nK0l77yK2v27mqaFho4eINjAC2f7q67rBoMhXKobNsxfGAXubMOyO9iwwHFcHwXuXq+X4zie53/6xlgGANA5jjuXs2jMmDEAoKpqfn6+pmlHjhx5/fXXRVFUFGXcuHGLFy9esGAB+3U2zkxvrMq/IIRIktRj/4bL2RTW2IF0/fXXr127dsOGDXPmzJk4ceJA6OuGLm/s7E5KSkpISDhx4gQAXHXVVRaLBR/1hKmztiT9crCod+vWrUaj0efzGQyGiRMnnjkxyrkLBALnG/GfKsm/xuiX5kI6MAP3n+b3+41GY7iEGmHX4i7LMoRV4N53Le5tbW12u52Ntt5bi9U0TdM0SZJYJdOjnZv9ld3s9dER3t7ebrfbQ/k56Lz07tnRj+2dfXTWXGKKorB2nP4uyEW5BNcIdqTt2bPnpZdeMplMTz311EWmBP+osLt2nM0APzvCKVzrUxMmTFi+fLnFYpkzZ85FNoGwB9ynlvCTO56c8c8BepgghHoJ61QDpxMkVFUNZa2wMR8wZeWyxx6nsMe8/V0W9IvAYtBx48YVFRX1eBOFHQzc/5kYsHDhwl5cJp4SCKGfRQgJr+dd6OJhyI76BbtdDE0B1t/FQRcILxj/1JszpyKEEEIIDRgsvMGGxXCHgfs/YciOEEIIIYQGLAxVEUIIIYQQCgMYuCOEEEIIIRQGMHBHCKFLChNMEUIIXRjMcUcIobPq6urq3d4vbCzIfozdw2hOXIQQQj1g4N77OI4Lrxa18CothGE34vDawuFVWuizAnMcZ7fbVVXt3eX3+5RnFovlMpghpb+E3dlxNpfHihBCwu5y8KMum93R30XoHQN8RXDm1N6nadplU5v0u1DzJKWUjUHb4zXg2LQXgW1JdriebQuHZhG+mOmEf7G6z03Yva2939vd0XkJVS/dRw1m5w7uxEuse60F3eolvAT0l1DMg2fHpYGBOxq4+nE+cIQuJTzUBzLcOwihgQPvTXsNuwVSVbWoqGjNmjW6ruNN0cVgF8uDBw9WVFQAQENDw9KlS8vLy9nrJUuWHD58GACcTueePXsA4OTJkzt37uzfMocRdnA2NjYuXbp09+7dcHqrnrmFS0pKgsGgpmmbNm3y+Xyh76KfwDaRy+V67733Nm3aBACqqn766adfffUVpTT0Wtf1H374obKykhCyc+fOqqoqwM078BBCurq6tm7dCgClpaXffPMNe/+bb745cOAAnJ68D/W1M2utzs7Ojz/+WFEUAKiqqlq9ejXg7rhUutdyGzduBIC9e/fi2XEJYODey3bv3p2SkmI0Gvfs2cPSDPq7RGGJRe21tbXvvPNOQ0MDABQXF8+cOXPv3r0ej2fnzp0zZ84sLS31er3BYLC2tlbX9a1btyYnJ7Onpf1d/PAgy3JxcfGvfvWrqqqq9vZ2tlV7bGGXy1VVVSUIQnFxsdlsNhqN2Pp47mpraydMmCDL8t69e48cOZKcnGwwGMrKysrLy5OSkgwGw8GDB51Op9frbWxsrK2tTUxMxM07oLD6pKur68MPP9y1axcAdHV1rVu3jlUyGzZs6OjoALzXuoRCtVZ1dXVbW5soilu3bq2srASAkpKSsrIywN1xaXWv5Qgha9aswbOjr2Hn1F7DwnRK6bhx45qbm2trawFzWC+CruuiKE6fPl0QBEVRUlNTMzIyWlpajh8/npaWlpmZ2dDQ4HK5JEkSRXHVqlWTJ09OS0vDuOccsa00Y8aMmJiY8vLy+vr69PT0zMzM1tbWHls4Ojp6/fr1JpPp6quvxs17jthWGjZsGKW0vr7ebDYHAoGxY8e2tbVVV1eLojh+/Pjm5ub29nZJkurq6o4ePTpv3jyDwYAXuYGG7cpp06bt2LEDAKKjo9PT0wOBgCRJ6enpZrMZsJ6/VLrXWvv379d1XRCEoUOHsgaymJgYr9cLuDsule61XG1tbXR0tKqqeHZcAtji3pt0Xdc0Tdd1nudZ/ww8ZC8M6x+ZkJBgMpkopcFgkOM4TdOsVqvL5eJ5XtM0s9msKArP899//31dXV0wGOzvUocZSZJiYmIOHTqkKEp0dDQ7ertvYZPJpOt6bW1tWVlZIBAAbDs5H2xblZeXsxSLYDBIKeV5nlIaCARYLzqe510u1549e9xut6Io+IBuoGEVuN1uT05OlmUZAGRZHjp06PHjx6uqqlJTU1mSBrpkWK1VXl4eDAbj4uLcbndmZmYwGDx27FhkZKTFYunvAv6yhGq5LVu2CILg9/vx7LgEMHDvTeyqDACyLLNDFgOdi0FPM5lMLJpsamqKj49nr9va2ljsfsUVV/z2t7/9+uuvfT4fi/j7u+BhIJQtWlVVNXfuXIfD4XQ6z9zCRqPRaDT+4Q9/8Hg85eXlbPCZ/i57eGA9NIYPH/7AAw/U1NSwI1mWZUKIJEm6riuKoqoqz/M333zz5MmT16xZgwNiDExsx/E8DwCEELPZ3Nzc7Pf7JUnCpplLqXutNX/+fABQVZW1NbS1tQmCwPYRumRCtdyDDz54/PhxALBYLHh29DW8TvQaNvhRVFTUypUrS0pKHA4HYOB+cQghiqJ4vV6e5z0ez5dfftnQ0JCZmdnV1bV69eqWlhabzcYecRBCRo4cuWrVKk3T+rvUYSMYDC5ZssTv92/evJlS6vf7V69e3X0Lt7a22mw2juP8fv+sWbM2btzY2dkJeFSfA9Z2HggEioqKdu7cmZ2dHR0d/dlnn+3YsSMxMdHhcHz22We7du2y2WyiKLrd7iFDhrhcru+//x7vPAcgtlNYGobH43E4HH6/3+122+129ia6ZFit5fP5Nm/e7PP5OI7z+Xypqan79+/Pyspqb2/v7wL+gnSv5UpKSlJSUvx+f2RkJJ4dfQ0vEr1v7969BoNhxIgR/V2Q8MbSqVtaWgAgLi5OluWtW7eOHj3a4XB0f+33+9vb21m31BMnTmRmZmKjyzkKBAIHDhzo6OgghBQUFEiSVFxc3H0Ljxo1Kjo6uqamJjExURTF2tpai8XicDgw0/3c7d27VxTFkSNHwr/WDKHXLS0tgiA4HA6Xy9Xe3p6RkYGbdwCSZbm2tnbw4MGtra0Wi8XtdvM8L0lSIBCIi4vDXXbJ9Ki1BEHo6OiIiYmprKwcMmRIZWVlZmYm7o5LLFTLscfgeHb0NQzce1noGMWDFV1O8Hi+AN1rA/ixqZdwqyKEwhrGPJceBu69r/vkYegincvMqaH6Aqf2PF+hzCL2mELTtDO3cPfNizPhna8eUwme+br7EQ7YnX0AC83Q3ON93GWXWI9ai1VQbO/gJaBf9KjNusOzoy9g4P5TLptbyUsccoX75kIIDUDdb3KwhkEI/TJh4N6HWMNA95TrgdMecPEl0TQtdDPwsxdRTdMw9RwhdI5UVYXTTydYSx4bZvdnv3hmrYsQQpeTARFEDkDsfqaiouL++++fO3fuunXrzvxr6J6n+z/Z/9nF44svvvjiiy/g9IOkjo6Od955B7rNAHxed02hOUF/9Ftn+xO74J08ebKpqUnXdfbTzc3NTz/9dPcBK8/8eo9Fnbl2n3322ebNm7ds2fL3v/899GG2/EOHDp08eTL0T0ppVVXVypUrAWc/Rgj9JFZFvPLKKzNnzrzmmmseffRRAFizZs0HH3zgdDpLS0vhdA3Towb+0VoXIYQuMxi4/zh2JXjvvfcmTZr05JNPrlixoq6uLpRa1+NZLSFEVdVQ2zObZoUthM0KxC4hpaWldrsd/jWxFQDYEHtw+sJDKWWtTZqmybIcGhieNW+zpBdN00JTG7DPhIoUiu9DQTPHcd9+++2hQ4dCv2u322+++ebujeWhr3dfx+4bpPsqh8Yz7uzszMnJyc/PJ4QEAgG3281+YsWKFQ0NDaE1JYQkJCRUVFS43W4c7Q4h9LP8fv/dd9/90ksvscB9xIgRhYWFJSUlW7dupZQuX768vr6+R8eAHrUuQghdloT+LsCAZjKZ2trarr322jfffJOFvxs3bmxsbBw/fvzixYv37Nnz0ksvjRgx4o9//OObb77J8/y2bdsWLVo0ffr0N954Y/fu3VFRUdOmTYPTtwH79++fO3cuAHz00UcffPDBHXfccf3113/88cculysqKmrRokVbtmx5//33c3JyJEkqKyubO3duTU1Nfn5+VlbWyy+/vHjx4qVLl27btu3hhx+eOHHia6+99vzzzxcXFx85cuSRRx5ZtmzZV1999cgjj0yYMOHZZ5/1+/3//u//PnToUFVVjx492tjY6PP5UlJShgwZAgBut3v79u3R0dFvvvlmV1dXQkJCUlLShg0bXnnllWPHjq1du7atrW3atGmHDx9WVfWFF16QJOntt9/+4osvHnzwweuvv/5///d/S0pK7Hb7jTfeWFlZ2dzcbLFYVqxY4fV6Z8+eHR0dvXv37ubm5pEjRxYVFX322WcPPPDAnDlzIiIiDh06NHHiRHbv0b97FiE0kLHh5CRJioqKAoATJ040NTWVlZUdOXIkKSnpwIEDXV1dwWBw2bJlw4YN+4//+A9Jkli9FKp1EULosoQt7j+ORZaLFy92uVwPPPDAsmXLBEHQNK2jo+Pee+8tKys7ePDgihUrZs2a1draum7dOp/P5/F48vPzd+zY0dDQUFpaeueddyqKwkJ21vAcCATi4+Pr6uqKi4sfe+yxo0eP1tbWTps27eGHH/7+++/9fj9rYp8zZ47T6Rw0aNDkyZOTkpKqqqrKy8tTUlK2b9/e3t7++9///osvvpBl2WQynThxYv/+/ePHj6+urt69e/fChQtXrFjxww8/dHV1TZ8+PS0tDQBkWX7jjTeKi4uXL1/+wQcfsJxRVVVbW1sppY2NjbNmzTpy5IjP57vqqqu2bdumKEogELjuuus++eSTSZMmBQKBqqqqEydO7Ny5c+HChV9++eWGDRsOHTp0xx13sIcAfr+/o6NDFMW77rqroKBgzZo1sbGxOTk5M2bMOHny5Pbt2++4447ly5e3tLTExMSwQdmxxR0hdDahrLw33njjN7/5zQcffAAATqdT07TRo0fn5uZOmjQpKytrzJgxq1evnjFjRktLy9q1axsbG/fs2dO91kUIocsStrj/OJY0Ul1d/fzzz+u6vnDhwquvvlqSpHHjxl1zzTX79+8vLy9nOS05OTlWq1UUxRtuuMFqtX700Uf19fXZ2dkzZsxoa2uTZRkA2DBVqqoaDIbKysqMjIzrrrsuPT2dTZq4d+9eQRAAQJbla6+9Njc3VxCEBQsWxMbG5uXlrVq1qrGxcdy4cWVlZTNmzLjmmmu2b99eW1s7ZcqUTz75hOO4ESNGlJSUiKKoquqoUaNkWc7Ozr755psBgFJqNpvfeOONd999NyEh4dprr2WdRDmOMxqNwWAwJydn3rx5Bw4cmDdvXktLy5EjR2RZnj179tSpU0tLS2+44Ybjx48ritLZ2SkIgqqqo0ePbmlpycrKmjlzZktLSzAYNJvNPM8bDIaysrLS0lKDwWA2m5OSksaPH9/Q0MBxnKqqeXl5bN1ZHg42tyOEzobVDxzHvfDCC+PHj2dRuCiKVqs1MTHR6/WmpaUlJSUNHjz44MGDiqLk5ORERkY2Njb2qHURQuiyhC3uP44liH/88ccPPfTQ888/z57YiqK4du3aP/3pT/v37y8sLLTb7YWFhcOHDx88eLDb7ZZl2e12O53OIUOGHD58+E9/+tMnn3wSGh6b53lRFF0uV05OTkVFxe9///ulS5fu3r37o48+Kigo8Hq9iqLIsuz3+3Vd9/l8LHN98ODBnZ2dhw4dGjlyZHZ29rvvvvvUU0/V1NQMHTp07Nix3377bWJioiRJSUlJCQkJM2bMGDJkSGxsrMvlCqWqA4AgCCaTyWQysdsDtnZer1fTNI/Ho+t6IBDw+XxOpzMYDMqy7PF43G53MBjUdd3lcsmyPGjQILb8tLS0/Pz8AwcOPPPMM59++qkgCD6fT9f1Tz75pLq6euzYsaxN3eVyvf766xaLZdCgQddccw0rVWdnp8lkAmxxRwj9HDabvSRJoUYNr9fLcVxRUVFNTY3H41m1ahXP89OmTRs+fHhqampmZuaRI0e617oIIXRZwsD9xxFCeJ5/+umnR44cGQwGH3300fT09K6urvz8/KioqPvuuy8xMXHRokVff/11VVVVbGzs8OHD7Xa73W7Pzc212+2/+c1vbDbbbbfdlpKSElqmw+FoamqyWq2PPvqoKIp33333woULR4wYsX379oKCAlmW09PTs7OzOY4bNWpUZGQkAHAcl5WVFRMTYzAYCgoK7rjjDo7jnnzySYfDYTAY7rnnnnHjxgFAVlbWdddd93//938mkyk+Pn7kyJGhSxfLjbnlllsKCwtD/zSZTHl5eXa7PS8vj+M49jopKSkrKys1NTUtLc1kMo0ZM4bjuJEjR1qt1uTkZLZ8g8GQmpr64IMPRkRE3H777XFxccnJyRkZGfPmzfP5fB0dHWPHjgWA2bNnx8fHZ2dns29ZLBaO4wKBAMvewRZ3hNDZsPohLy8vJiYm9GZqampKSkpubm5hYSGl9LrrrktLS2M1cHV1dXx8fGRkZI9aF+sZhNBlCYf4OA9FRUVsrAM4zzmG2Ie///7777777r777jvHL1JKN27c+M477zzyyCMFBQXdR14Pu/lHWltb33nnnSeeeILn+fAqOUJo4Au7KhEhhC4M5rj/FDYIOnvN83xaWhrrQsr+yf5KCGEp7KE5Vtk/2YUkBABycnJaWlrYkI7sYyyTvvuwjKGvs29RSqdMmVJQUACnE+VDX4RuE9SHisr+eS6TK7Gf6P5z0O3ixwrG83z3knRffmjtQt8KLSRUTraJ2HICgcDUqVMFQcAhZRBCP6vHZM9slFuO41ilB6enkAvVwD3qJaxkEEKXK2xxRwghhBBCKAxgjvt56N4Af2HO9+u6rnfvZhq+QtNCIYQQQgihC4Mt7gghhBBCCIUBbHFHCCGEEEIoDGDgjhBCCCGEUBjAwB0hhBBCCKEwgIE7QgghhBBCYQADd4QQQgghhMIABu4IIYQQQgiFAQzcEUIIIYQQCgMYuCOEEEIIIRQGMHBHCCGEEEIoDGDgjhBCCCGEUBjAwB0hhBBCCKEwgIE7QgghhBBCYQADd4QQQgghhMKA0N8FQAghhBBClwNKqa7r7DXHcYSQHn8FgB5vnvtiCSEcx/V4ny2NfaDHL2qaxn4u9K0ey9E07Udfn7m00DvnvnZnlrn7O+w1z/PnuykI+xmEEEIIIYTCRShqv8Tf7V/Y4o4QQgghhC4Ka5A+cuTIqlWrrFarJEmzZ88eNGgQPY3n+WPHjhmNxpSUFABgrc6EEPZXAKCUhpqxQ63XrIm6srJy06ZNV1555aRJk0LfIoRUVFTExMRERUWVl5dv2bJl9uzZaWlprCQul2v58uVNTU2FhYWTJ09mn29sbPzyyy9HjBgxceJEp9O5YsWKrKysKVOmsNfZ2dmFhYUAcOjQoa1bt86cOTMrK0vTNJ7nDxw4sHXr1qlTp3755Zdms9lgMITWLlSYgwcPxsTEJCYmsgK0t7evWrUqISHh+uuvZx9g78THx8+ZM2fPnj1Hjx69/fbbBUE4r7sIzHFHCCGEEEIXhYXax48fT09Pv/XWWydMmLB69WpVVVlmCMsJaWxs9Pv9HMex7BEWrbIPsM+E4ldCCHvNQvmampqbbrqpsbGxtrY2FCh3dnZ+8MEHwWDQ7Xbv3r179uzZO3fulGWZLeHo0aNpaWmPP/74qFGjWNlkWV63bt306dO9Xm9DQ8O6desKCwvb2tqamprY6/b29vr6epfLtWPHjptvvrm0tNTv97NitLS0jBs3rrm5edCgQQsWLAitHZxuvHe73e+//77f72fvqKq6atWqGTNmmEymvXv3EkIURWHvmM3mffv2DR8+3G63u93u893O2OKOEEIIIYR6gSAIWVlZ8fHx8fHxhw4dYlnmX331ldPpXLBggdls3r59e0lJyU033aQoSm1t7ciRI6urqxsbG10uV01NzfXXX5+YmAgAjY2NXV1dOTk5FRUVZrN56tSpiqIoihKK7GVZrq+vHzJkiMFgaGtru+KKK9LS0mpra6urq4cMGQIAbrd7z549Tqdz1qxZ7Fsulys+Pj4zM9NqtX799dcpKSnZ2dk2m23Pnj1JSUnZ2dlms/nEiROjR482Go2EEKPRGGoLlyQpISHh5MmTobUrLy9n5aGUCoJQUlKSm5sbutnQNG3OnDnx8fEcx5WXlwMApTT0zpEjR8xms8PhuIAtjC3uCCGEEEKoF4iiuGXLlnXr1u3YsSM9Pd1gMHzzzTcOh2PixImbN2+ur6+PioqaNGnShg0b7Hb7li1bgsHgrl27vvvuO03T8vPz9+7dy1rHIyIiysrKdF0vLS3leZ5SumPHjoqKiqioKAAghPA8P3z48JiYGFVVvV6vxWKhlGqa5vF4AIBSarfbZ86cOXz48A0bNmiaRimNjo52uVxr1qwpLi6ur683mUws5m5oaDCZTADA8lvMZrOiKG+88YYsy2a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\n", 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\n", 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\n", "text/plain": [ "" ] @@ -1802,10 +1603,10 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 32, "id": "fd2566e4", "metadata": { - "scrolled": false + "scrolled": true }, "outputs": [ { @@ -1815,12 +1616,13 @@ "Fetching one pager for specified solution id\n", "Using specified path\n", "Path exists: /Users/yuyatanaka/Desktop/\n", - "Onepager written to path: /Users/yuyatanaka/Desktop/5_181_7\n" + "Onepager written to path: /Users/yuyatanaka/Desktop/3_216_3\n" ] }, { "data": { - "image/png": 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\n", 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mhCTLAZhIDwPb+fegDTHQUU0MMDmnUAFFFFABRRRQAUUUUAFFFFABUF3apeWzQOzKrdSuM/rkVPRQBjv4a094pItjCOQglQR6EY5HPU8nJ9CKuHTot0bK8q7N2Qr43AnOD6jNXKKAKP2KeFttrNCkLY8xZYmdjgBeCGGOAOxqW0sktN5V5ZGfGWkbccDoM+351ZooAKKKKAOO8Vz39vqGitbXnkW76pFFPGB80obOFz2Xg5HfiueiuPEAsZrk6n58tlrU0coDFBKMoEjVRnK5JULn+LPUV6Q9nFO26QBiH3DIBwR0I96QadbjOEUZfecKOW/vdOvv1q7oizOc8L6oNU0cNmZpLdzBI8rBi7AAlsj13dO3TtW1VmPT4IlKxgICSxCqACT1PA60/wCxp/eanzIXKynRVz7Gn95qPsaf3mo5kHKynRVz7Gn95qT7ImfvNRzIOVksP+oT6VJSIoRAo6AYpazNAooooAKKKKAEP3lpaQ/eWloAKKKKACiiigApD/WlpD/WgBaKKKACiiigAooooAO1Iv3B9KXtSL9wfSgBaKKKACiiigAooooAQf1paQf1paACiiigAooooAyfEfhyw8UaQ+nagreWWDq6HDIw6MDXN/DXwjpug6PHqFv5kl3ewKZJZCOFznaoHQV3LnCMfQVjeExjwrpPvZxH8xWinJQcb6GbjFzTtqEXhyKLTLbTvtdw1rbrCFjIX5jG4cE8d8AHtitqiiobb3LSS2CiiikMKKKKACiiigBsiCSNkJIDAjIODWUvhyxQNgOGZNjN8uSc9en6fd9q16KAM+PR7aG2SGFpYghBUo+CMDGB7YJpTYzwEfYZoosgB/OjaTIHTGGXHf1q/RQBVisY4rprjfIzEEKrtkJk5OPqQP6Yq1RRQAjKHUqwBUjBB71h6JoZ0jVtYmTAtrqSJ4h5jOw2xhTuLc9R6nit2kH3moAWiiigAooooAKKKKAIoxH5k205bcN/PQ4H9MVLUUQj8ybYfm3Df9cD+mKloAKKKKACiiigApF6t9aWkXq31oAWiiigAooooAoa1o1j4g0e50rUoBNaXC7XTJHfIII6EEAg+1YvhD4faB4I+0NpMM3nXGBJNPJvcqOig9hXU0UAIKWkH9aWgAooooAKKKKACkXofqaWkXofqaAFooooAKKKKACiiigBB0paQdKWgAooooAKKKKACkX7opaRPuigBaKKKACiiigDE1PQzqXiGwvJCPssFrPE4WRkfc7RFSpXBHCNnkdfetBdNtUuUuFjYSIu1fnbaB/u5xkZIBxwDgcVbooAQdBS0DoKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAReh+ppaReh+ppaACiiigAooooAKQdTS0g6mgBaKKKACiiigAooooAQ/eWlpD95aWgAooooAKKKKACkP9aWkP9aAFooooAKKKKACiiigA7Ui/cH0pe1Iv3B9KAFooooAKKKKACiiigBB/WlpB/WloAKKKKACiiigCC9bZY3D/wB2Nj+hqj4bXb4b0oellD/6AKsau2zRr5vS3kP/AI6aj0JduhacvpaRD/x0VX2SftGjRRRUlBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSD7zUtIPvNQAtFFFABRRRQAUUUUARRCPzJtn3tw3/XA/pipaii8vzJtn3tw3/XA/pipaACiiigAooooAKRerfWlpF6t9aAFooooAKKKKACiiigBB/WlpB/WloAKKKKACiiigApF6H6mlpF6H6mgBaKKKACiiigAooooAQdKWkHSloAKKKKACiiigApE+6KWkT7ooAWiiigAooooAKKKKAAdBRQOgooAKKKKACiiigAooooAKKKKACiiigAoqrf3jWcSMkLSszEbQwXAALE5PsDVGXXGjXeto7A7yo3AEquct7dDx9KANiiqltdvO11viVFhk2Kd+dw2q2T6dah0q9nu1kW5VEkTadqqRgEe+QR1G4HB9qANGiiigDh/EPjKbQr6OBtrefdrbRIqZPJxk+wzz+HrVDUfiHc6brNnpskRd7ldwdVXC9f4Sct0OcDgYJ60ninwVJr+si8867heGUMpgn2qyh1cgj3Kjntx6VTufA+o3mr2eozXIL25UuFiQbtrsy7WzlPvYbH3gK60o26HK3K5oaR4+utYVTCip8hZtwB2/NgDg85wTx6V0mj6vd3t/5MxQpsJ+Vcc8Vxw8D3KatBfjCNFK7lFVVBBGFUc8AD8/aup0Wzns9Q82dAqbCM5B549KGo8rBOXMjqKKi+0xf3v0NH2mL+9+hrlszpuiWkHU0oOQCOhpB1NIYtFFFABRRRQAUUUUAIfvLS0h+8tLQAUUUUAFFFFABSH+tLSH+tAC0UUUAFFFFABRRRQAdqRfuD6UvakX7g+lAC0UUUAFFFFABRRRQAg/rS0g/rS0AFFFFABRRRkCgDO187fDmpt6Wkp/8AHDUulrs0y0X0t4x/47XmvxW8fS6ZCmjaPNbu91E4uZVIkKL93YOwJyevStb4ceLtT8R+GLx5raKW+siIkIPlrLlcrnrg+uPyrd0pKnzGCqxdTlPQKK5KbxDqEfgCz1VVV7+5SFP3cJcB5GCkqmRnGeBkZ45qrp3inU59f0m3mUNaXkYTcto6Bm8t2Z95OFIZCvlnnqc1Hs5F+0R29FFFZmgUUUUAFFFFABRRUN3Oba2eURmRhgBAQMknA5P1oAmorJbWXCki0fhljxvXlyDx+BHWp9P1CS9kmDQeUqBcHfkkkHI/Aj8aAL9FZ1rfTy6lLbyqiphjHhTyFbH3uQ3uOCOnPWtDd7H8qAFpB95qN3sfypob5m4P5UAPopN3sfyo3ex/KgBaKTd7H8qN3sfyoAWik3ex/Kjd7H8qAI4vL8ybZ97cN/1wP6YqWoYmj8ybYDu3DfweuB/TFRX1zNbwxvDGrkyor7yRhSwBI45PPAoAt0Vw/jPWJrPVdITY8tut/A4W2UvKT82V2g5OQc4wOnU9Brf8JdD/ANAXXv8AwWyf4UAdFRXO/wDCXw/9AXXv/BbJ/hR/wl8P/QF17/wWyf4UAdFVPULmW0sZp4UiZk5Jlk2Io7ljg8AegrJ/4S+H/oC69/4LZP8ACsfxN4tsl8OX89zoWvSJbxm4Cm1mgG5PmXLjBUZAOaAOmfVpUOk5s3Av3CPucAwkxs+COpPy4/zitSvAfh/8XdS13xKmn61pjXcY3T2xsoZHkhdV29NxLDaSMnuc969c/wCEvh/6Auvf+C2T/CgDoqK53/hL4f8AoC69/wCC2T/Cj/hL4f8AoC69/wCC2T/CgDoqK53/AIS+H/oC69/4LZP8Kx/EviZbvS4YY9O1e2Zr60/ez2bxRj/SI87mPQdqAO5H9aWucl126h0eG8AgmLTEF40O10ycFV3ZGcYzk4647V0O72P5UAOopN3sfyo3ex/KgBaKTd7H8qN3sfyoAWkXofqaN3sfypqtweD1PagB9FJu9j+VG72P5UALRSbvY/lRu9j+VAC0Um72P5UbvY/lQADpS00Nx0P5Uu72P5UALRSbvY/lRu9j+VAC0Um72P5UbvY/lQAtIn3RRu9j+VNVvlHB/KgB9FJu9j+VG72P5UALRSbvY/lRu9j+VAC0Um72P5UbvY/lQAo6CimhuBwfyp1ABRRRQAUUUUAFFFFABRRRQAUUUUAV7uygvRGtwgdI33hWGQTgj+tOa0t2+9DGeGHK+vX88mpqKAKUmnK1x50U80GSC6xFQJCMD5sg9gB9KntrS3tFZbeFIgx3EIMZNTUUAFFFFAHmHxFnuIvEegCGW4j/AH5KrE0g81/MiG1NvBk27uHyu3dxnkJr+paZeeNdBht9aliu5STEUmZYggdlYBRw7u3y4bgBCeO/pYhRixK8knPNL5Ef939TVXI5TzXQLi80jWbPTLkteK7S20cwdtq7SWcgHJYBsKSTxt4613VX/s8X9z9TR9ni/ufrT5kHKyhR2q/9ni/ufrR9ni/ufrT5kLlY9P8AVr9BSjqaUDAwOlIOprM0FooooAKKKKACiiigBD95aWkP3lpaACiiigAooooAKQ/1paQ/1oAWiiigAooooAKKKKADtSL9wfSl7Ui/cH0oAWiiigAooooAKKKo3+s6bpmBe3sMLHojP8zfRep/AU0m9hN23Lo/rS1hjXbu640zRruYZ4muf9Gj/wDHvnP4LR9g129/4/NVjtEPWKwi+b/v4+f0UU+XuLm7GvcXMFrEZbiaOGIdXkYKB+JrJ/4Se0nO3Tbe71Js4zaxfu8/9dGwn61Jb+GdKhlE0lt9quB/y2u3Mz/gWzj8MVrgADAo91B7zMP/AIqO+7WWmRn1zcS/+yqP/HqX/hGLa4O7U7m71Juu25lxH/37XC/mDW3RRzPoHKuph6v4P0HW9PjsbzTofJiO6IRDyzGe+0rjFW9G0TTtAshY6Zapb24+baMksT1JJ5JrRpP4z9KOaVrX0DlV72MyXw7pU2nx2Elrm1jhMCR+Y2AmQfXqCoIPUY4NFt4d0izvYLy3sY454IRBEwz8qDjpnGcEjPXBPNalFHM+4+VdgoooqRhRRRQAUUUUAFQ3VtHeWz28ozG+Nw9ec1NRQBAtnbKioIIwqkEDb0x0qCbTEdw8E0tq2MMYNo3jtnIPTJ/M1eooAhjtLeGeSeOFFlk++4HJqaiigApB95qWkH3moAWiiigAooooAKKKKAIojH5s2wfNuG/64H9MVIQD1APeo4jGZJtg+YMN/wBcD+mKloAyNU0KHUJrCaMxwva3Uc5YRjLqm7C59PmNa+KKKACiiigAqNo0lSSORFdGyGVhkEEcgipKRerfWgDD0PwZ4c8N3U9zo+kW1nPOMO8anOOuBnoPYYFbtFFABRRRQAVm63pQ1nThaGQRgTwzEldwIjkV8Y99uPxrSooAqxadZRQrFHZ26RowZVWJQAQSQQMdckmrVIP60tABRRRQAUUUUAFIvQ/U0tIvQ/U0ALRRRQA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\n", "text/plain": [ "" ] @@ -1831,7 +1633,7 @@ ], "source": [ "#write one pager to specified location\n", - "load_onepager(sol='5_181_7',write=True,InputJson=InputCollect,OutputJson=OutputCollect,path=robyn_directory)" + "load_onepager(sol='3_216_3',write=True,InputJson=InputCollect,OutputJson=OutputCollect,path=robyn_directory)" ] }, { @@ -1844,31 +1646,29 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 33, "id": "1bcdaa54", "metadata": { "scrolled": false }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Using specified path\n", - "Path exists: /Users/yuyatanaka/Desktop/\n", - "File written to path: /Users/yuyatanaka/Desktop/\n" + ">> Exported 3_216_3 as /Users/yuyatanaka/Desktop/Robyn_202408081618_init/RobynModel-3_216_3.json\n" ] }, { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - ">> Exported model 5_181_7 as /Users/yuyatanaka/Desktop/RobynModel-5_181_7.json\n" + "File written to path: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/\n" ] } ], "source": [ - "write_robynmodel(sol='5_181_7',path=robyn_directory,InputJson=InputCollect,OutputJson=OutputCollect,OutputModels=OutputModels)" + "write_robynmodel(sol='3_216_3',InputJson=InputCollect,OutputJson=OutputCollect,OutputModels=OutputModels)" ] }, { @@ -1881,11 +1681,9 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 34, "id": "aa2048ac", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1896,7 +1694,8 @@ }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "" ] @@ -1906,7 +1705,7 @@ } ], "source": [ - "load_onepager(sol='5_181_7',InputJson=InputCollect,OutputJson=OutputCollect,path=robyn_directory)" + "load_onepager(sol='3_216_3',InputJson=InputCollect,OutputJson=OutputCollect,path=robyn_directory)" ] }, { @@ -1921,7 +1720,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 45, "id": "ca1b3b1b", "metadata": {}, "outputs": [ @@ -1931,7 +1730,7 @@ "['tv_S', 'ooh_S', 'print_S', 'facebook_S', 'search_S']" ] }, - "execution_count": 31, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } @@ -1952,12 +1751,12 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 36, "id": "94e313ac", "metadata": {}, "outputs": [], "source": [ - "select_model='5_181_7'\n", + "select_model='3_216_3'\n", "\n", "allocatorArgs = {\n", " \"select_model\" : select_model,\n", @@ -1972,7 +1771,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 37, "id": "5f853452", "metadata": {}, "outputs": [], @@ -1990,7 +1789,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 38, "id": "337eb394", "metadata": { "scrolled": true @@ -2000,10 +1799,10 @@ "name": "stderr", "output_type": "stream", "text": [ - ">>> Running budget allocator for model ID 5_181_7 ...\n", - "Automatically picked date_range = 'last_4'\n", - "Date Window: 2018-12-10:2018-12-31 (4 weeks)\n", - "Exporting to: /Users/yuyatanaka/Desktop/Robyn_202401291703_init/5_181_7_reallocated_best_roas.png\n" + ">>> Running budget allocator for model ID 3_216_3 ...\n", + "Date Window: 2016-01-04:2018-12-31 (157 weeks)\n", + "Excluded variables (coefficients are 0): facebook_S\n", + "Exporting to: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/3_216_3_reallocated_best_roas.png\n" ] } ], @@ -2014,7 +1813,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 39, "id": "06ee665a", "metadata": { "scrolled": false @@ -2022,7 +1821,8 @@ "outputs": [ { "data": { - "image/png": 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\n", 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Arg38q8n715OO+Neh10NmGaM0UVwG4ZpCeKWg9KADNGaKKADNGaKKALFgR/aNr/13T/0IV7FuHqK8dsP+Qlaf9d0/9CFex16mA2kctfdCbl9RRuX1FLRXonOJuX1FG5fUUtFACbl9RXN+NyDoAwf+W6f1rpa5rxx/yAB/13T+tY4j+FL0Lp/EjznNGaKK8A7wzRmiigBCaXNBooAM0ZoooAM1o6Af+Kg0/wD67rWdWjoH/Iwaf/13Wrp/GvUUtmes7lx1FG5fUUvaivojzhNy+oo3L6ilooATcvqKWiigAooooAKKKKACiiigAooooAKKKKACijrSYFAC0UmBRgUALVTU/wDkHy/h/MVawKqamB/Z8v4fzFAHPUUUUAFFFFAAaKQ0tABRRRQAVPZf8fsH++KgqeyH+mwf74oA6aikwKMCgBaKTAowKAFopMCjAoAo6v8A8eX/AAMVg1u6uB9i/wCBisKgAooooAKD2opD2oAWiiigAooooAt6Z/yEIvx/ka6Kud0wf8TCL8f5GuhwKAFopMCjAoAWikwKMCgBaKKTAoAWikwKMCgBaKTAowKAPOPFP/Ix3X/AP/QRWPWx4pH/ABUd1/wD/wBBFY9etT+BHlVPjYUUUVZAUd6KTvQAtFFFABRRRQB2/gj/AJB91/12/wDZRXU1y3ggD+z7r/rsP/QRXUYFeXW/iM9Oj8CFopMCjArI1FopMCjAoAWvLtc/5Dt9/wBdmr1DAry/XP8AkO33/XZq6sL8TOXE/CihRRRXecIUUUUAAopBS0AFFFFABXf+Df8AkBn/AK7P/SuArv8AwaB/YZ/67P8A0rnxPwHRh/jOhopMCjArzj0BaKTAowKAFoo6UUAFFJgUYFAC0UmBRgUAZviL/kXdQ/64N/KvJ+9er+IQP+Ee1D/rg38q8o715OO+Neh10NmFFFFcBuFB6UUh6UALRRRQAUUUUAWLD/kJWn/XdP8A0IV7HXjlh/yErT/run/oQr2LAr1MBtI5a+6FopMCjAr0TnFopMCjAoAWua8cf8gAf9d0/rXSYFc344A/4R8f9d0/rWOI/hS9C6fxI85ooorwDvCiiigANFIaWgAooooAK0dA/wCRg0//AK7rWdWjoH/Iwaf/ANd1q6fxr1FLZnrVFJgUYFfRHnC0UmBRgUALRSYFLQAUUUUAFFFFABRRRQAUUUUAFFFFABRQRnvik2n+8aAFopNp/vGjaf7xoAWqmp/8g+X8P5irW0/3jVPUx/xL5fmPb+YoA5+ijHvRj3oAKKMe9GPegANFIR70uPegAoox70Y96ACp7L/j9g/3xUGPep7If6bDyfvigDpqKbtP940u0/3jQAtFJtP940bT/eNAC0Um0/3jRtP940AUdX/48v8AgYrBrd1cf6F94/fFYWPegAoox70Y96ACg9qMe9IR05oAWijHvRj3oAKKMe9GPegC3pn/ACEIvx/ka6Kuc0wf8TCLk9/5Gui2n+8aAFopNp/vGjaf7xoAWik2n+8aMH+8aAFoopCD/eNAC0Um0/3jRtP940ALRSbT/eNG0/3jQB5x4p/5GO6/4B/6CKx61/FA/wCKiuuT/B/6CKyMe9etT+BHlVPjYUUY96Me9WQFHejHvSY96AFoox70Y96ACijHvRj3oA7fwR/yD7r/AK7f+yiuprlfBA/4l91yf9cP/QRXU7T/AHjXl1v4jPTo/AhaKTaf7xo2n+8ayNRaKTaf7xo2n+8aAF7V5drn/Idvv+uzV6ftP9415hrg/wCJ5fcn/XNXVhfiZy4n4UUKKMe9GPeu84Qoox70Y96AAUUgHvS496ACijHvRj3oAK7/AMG/8gM/9dn/AKVwGPeu+8Gj/iRnk/65/wClc+J+A6MP8Z0VFJtP940bT/eNecegLRSbT/eNG0/3jQAtFIBjuTSnkdcUAFFJtP8AeNG0/wB40ALRSbT/AHjRtP8AeNAGb4i/5F3UP+uDfyryfvXq/iEf8U9qHzH/AFDfyryjHPWvJx3xr0Ouhswoox70Y964DcKD0ox70hHHWgBaKMe9GPegAoox70Y96ALFh/yErT/run/oQr2OvHLAf8TK15P+vT/0IV7DtP8AeNepgNpHLX3Q6ik2n+8aNp/vGvROcWik2n+8aNp/vGgBa5rxx/yAB/13T+tdJtP941zXjcf8SAcn/Xp/WscR/Cl6F0/iR51RRj3ox714B3hRRj3ox70ABopCPelx70AFFGPejHvQAVo6B/yMGn/9d1rOx71o6AP+Kg0/k/69aun8a9RS2Z612opu0/3jS7T/AHjX0R5wtFJtP940bT/eNAC0Um0/3jS0AFFFFABRRRQAUUUUAFFFFABRRRQAUUUnPtQAtFJz7Uc+1AC1U1P/AJB8v4fzFWufaqmp5/s+Xp2/mKAOeooooAKKKKAA0UhpaACiiigAqey/4/YP98VBU9l/x+w/74oA6aik59qOfagBaKTn2o59qAFopOfajn2oAo6v/wAeX/AxWDW7q+fsX/AxWFQAUUUUAFB7UUh7UALRRRQAUUUUAW9M/wCQhF+P8jXRVzumf8hCL8f5Guh59qAFopOfajn2oAWik59qOfagBaKKTn2oAWik59qOfagBaKTn2o59qAPOPFP/ACMd1/wD/wBBFY9bHin/AJGO6/4B/wCgisevWp/AjyqnxsKKKKsgKO9FHegAooooAKKKKAO38Ef8g+6/67f+yiuprlvBGf7Puv8ArsP/AEEV1HPtXl1v4jPTo/AhaKTn2o59qyNRaKTn2o59qAF7V5drn/Idvv8Ars1eoc+1eX65/wAh2+/67NXVhfiZy4n4UUKKKK7zhCiiigAFFAooAKKKKACu/wDBv/IDP/XZ/wClcBXf+Dc/2Gf+uz/0rnxPwHRh/jOhopOfajn2rzj0BaKTn2o59qAFooooAKKTn2o59qAFopOfajn2oAzfEX/Iu6h/1wb+VeT969X8RZ/4R3UOn+ob+VeUd68nHfGvQ66GzCiiiuA3Cg9KKQ9KAFooooAKKKKALFh/yErT/run/oQr2OvHLD/kI2v/AF3T/wBCFexc+1epgNpHLX3QtFJz7Uc+1eic4tFJz7Uc+1AC1zXjj/kAD/run9a6Tn2rm/HGf7AH/XdP61jiP4UvQun8SPOaKKK8A7wooooADRSGloAKKKKACtHQP+Rg0/8A67rWdWjoH/Iwaf8A9d1q6fxr1FLZnrXaik59qOfavojzhaKTn2o59qAFopOfaloAKKKKACiiigAooooAKKKKACiiigAooJx2zSbj/dNAC0Um4/3TRuP900ALVTU/+QfL+H8xVrcf7pqvexvcWjxIvzNjGT70Ac3RV7+ybv8Aup/31R/ZN3/dT/vqgCjRV7+ybv8Aup/31R/ZN3/dT/vqgCiaKunSrr+6nX+9S/2Td/3U/wC+qAKNFXv7Ju/7qf8AfVH9k3f91P8AvqgCjU9l/wAfsH++Kn/sm7/up/31UltptzFcxyMq7VbJw1AG3RTdx/uml3H+6aAFopNx/umjcf7poAWik3H+6aNx/umgCjq//Hl/wMVg10OoQyXNt5ca/NuB5OKzP7Ju/wC6n/fVAFGir39k3f8AdT/vqj+ybv8Aup/31QBRoPar39k3f91P++qQ6VdcfKnX+9QBSoq9/ZN3/dT/AL6o/sm7/up/31QBRoq9/ZN3/dT/AL6o/sm7/up/31QAzTP+QhF+P8jXRVj2Wn3EF2krqu1c5w3tWvuP900ALRSbj/dNG4/3TQAtFJuP900ZP900ALRRSEn+6aAFopNx/umjcf7poAWik3H+6aNx/umgDzjxT/yMd1/wD/0EVj112t+HNQ1DV57qBYvLfbjc+DwoH9Kz/wDhD9W/uwf9/P8A61elCpBRSbPNnTm5N2MGit7/AIQ/Vv7sH/fz/wCtR/wh+rf3YP8Av5/9ar9rDuT7KfYwaO9b3/CH6t/dg/7+f/Wo/wCEQ1XJ+WD/AL+f/Wo9rDuHsp9jBore/wCEP1b+7B/38/8ArUf8Ifq392D/AL+f/Wo9rDuHsp9jBore/wCEP1b+7B/38/8ArUf8Ifq392D/AL+f/Wo9rDuHsp9jZ8Ef8g+6/wCu3/sorqawvDWmXWlWk8dyq7nk3DY2eMAVubj/AHTXnVWnNtHoUk1BJi0Um4/3TRuP901maC0Um4/3TRuP900AL2ry7XP+Q7ff9dmr0/cf7pridS8L6ld6nc3EaxeXJIWXMmDj8q6cPJRk7s58RFySscvRW9/wh+rf3YP+/n/1qP8AhD9W/uwf9/P/AK1dntYdzj9lPsYNFb3/AAh+rf3YP+/n/wBaj/hD9W/uwf8Afz/61HtYdw9lPsYIoreHhDVf7sH/AH8/+tR/wh+rf3YP+/n/ANaj2sO4eyn2MGit7/hD9W/uwf8Afz/61H/CH6t/dg/7+f8A1qPaw7h7KfYwa7/wb/yAz/12f+lc9/wh+rf3YP8Av5/9auq8O2FxpmmG3uFG/wAxm+RsjBxWFecZQsmb0ISU7tGxRSbj/dNG4/3TXCdotFJuP900bj/dNAC0UgOexFKeB0zQAUUm4/3TRuP900ALRSbj/dNG4/3TQBm+Iv8AkXdQ/wCuDfyryfvXrur28t7pF3bQr+8liZV3HAya4T/hCtY/u2//AH9/+tXm4ynOck4q500ZJLVnO0V0X/CFax/dt/8Av7/9aj/hCtY/u2//AH9/+tXF7Cr/ACs2549znaD0rov+EK1j+7b/APf3/wCtSHwVrGPu2/8A39/+tR7Cr/Kw549znqK6L/hCtY/u2/8A39/+tR/whWsf3bf/AL+//Wo9hV/lYc8e5ztFdF/whWsf3bf/AL+//Wo/4QrWP7tv/wB/f/rUewq/ysOePcxbD/kJWn/XdP8A0IV7HXndr4O1eG8gldYNqSKxxL2BB9K9C3H+6a9HBwlBPmVjnrSTtYdRSbj/AHTRuP8AdNdxgLRSbj/dNG4/3TQAtc144/5AA/67p/Wuk3H+6axvE2n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sbxHyzaPvQECIuY050cXboURMcSCs+J4VII6SF5zl4vVK6xnQLbvsssxDhSXErYEf+5dkLV96qgeDg9p68cAbpb4PY42hOtZaay1iUcwoaTWVGLegGi8fe34CnKJHSwg99kHFbn7rjdIePK5hElOtA+1fL6XWEmRBcwEzcizwindoJPLS/CQMSGlmDGGOdlvtPe3xjMWTDWUX6W7ocSYGgeOOO05J7aEirD2E2SEjL4cwxDbYYAOQSqLZuGQtVUW4xRxL1hlIBBKBRCARSAQSgUSgjwigfa0feBJhrwZWM8OPERrxvl4Su9Vt2EBubHoRGe5z8naSvPnNbxaghOMZpxS2YUZy24tJxtYRkSgRkmcBgJkREIO2EsCWJMS39thjD2oRWWducgI2YNgFbtsJMbu0xYQbHqWLRQV2aNu6uw6SQVsxVDslxKDXkqCzwfBkbVcJGdTNXbtiEGg0WpiS4L7U8ukyye52d7Fkdy02OLYFAih3hb1tia3S70BwmSQS28PRWSLMfe4WaivMecz1K1+01X53GmzPsELYsOs9XXri5Vc7++NtWm++SuuzJ9J6TVaYDPQYaaEiEuNUF2iuRwo+CxMs06uoboXNAmGn5ycWNi4tVyI72gS4q0Vi8C5tYinyAg4ZwURFWDjFa7iWNzbWuyVhVQ+1MpJp7K0v7UGMQpVS2+8ehikgBOiJS2llwUEuxvumjInDwsarzFE7ZOLQcoLKk7FXigYFZ6R6cQiQjz1Ir6mp/bXGoDwOy6d4xZZClRKtyKoJ0ScgeagKbRQ25khM2lfV5Z9EIBFIBBKBRCARSARmGIH/PfGvMpiewrJDZ7E3HytESoihmMgu1hVJ+IYdyKvt4G75XZuI9wEW/ni8Fp9G67EoDnvueR5u3A7h9kESygnz0aJBPKC4pktOU6q8NBk8FRekAZvnSmcAis+ffckll6DgeD8PMYUeApDxORR8lwbbxAmgs29961vDGGdfm8EjCYezXww+TRuDPQqgzXKCDO7r+yoWJB4OeBGWAEn2YHhs4CR2ieJTZbM+ZDwEQMfx5gDK3QgQoFaJFIRARHpoYHM8F7Vd3XK3TRwOkihRPMRAo11a/9iqTgAynN8WCSIdPNwYv103zvbrWxLwGVu0WB1B25LAI44wGC1WKQxGRoGGvhO2cCpGhkJf88Q+meHSLc89nP2+UiiBADe2y4JYpFIKW+HtJGEeDi058G0v8f2ZRj0lx9IegGy/O2TqSi2tIissfEoqz22C7mt+GmHQYhiqrzAmziHvrAi4voqr3q2GsXDLP7RepGKq61I6xVG/2nY0M8VXLvhrw1UN1XArOVblM5wIJAKJQCKQCCQCiUCvEOgdce9JdZCbQrB6EivxvMg+peKlSVvMhX/96197jxCbD7IeYq1rK2obA2FYxJdwVXM1XE3eU3xRQrgarqatC9eVq3mq6l3eXH53e4FQ6vhdT5rDsKpYZHf++efjnVzUeCrWjr7bdE7YEcybWGOqOlPjUpJ4ItHtZbdJuo1sXU9VshruVm1jZPMkgb83DXBxUAQIzii49WGjtsaYKm7CiL6m6wwlWZPXbjXgQvqb29OoP2MSgUQgEUgEEoFEIBFoBYHaLt7eHriLo6RChhwu8Zi4hceEQBBxPAZ5ctchgIz6+h6/+Pbbby/ss9nxXXPCIUmVMGGBojAuQ6DcJVBiBAjH5pbgapIwLDQIhzFhJwHyRU8oCfmSNmQopCGEpaUw4mtl7ip19a5bZEpGwnEZNkQ4Ugljfl06at8nKZmKKQZHkW3gCSc9mVIKYmGGvCKe19mWFZ+z9LFL38xxlgXNRTLyquYrXD3ocRmYhEnlUqBqZDVVKUUQ2WKP7FjbqKeoctehsBCOgLBAQa9oLtmVmIKnW9UkRbIul2p8CVOiyJFpREbZIxyoKoVL58ixYFiUlAAzorACkarcykAikAgkAolAIpAIJAL9gkD/eNz7ZgqPMopTiFrflAz5VDYOYY3xUu90C4vaErY/ZLqSKZAIJAKJQCKQCCQCiUAiMHMh0BniHm5OvklgVcMzF3aDylruXkfx9UK1hAeVnZ0yBiCOau49ueqrMj2FLZDiFswFQlW0556SZHwikAgkAolAIpAIJAIziEBtJ0D7j+CUXVSztp06GE9woDpjuo2sk5mRy0Lm6jIql00CM5Jvn9M22hOqAsMIKxSEu5UskSFZLkugali3kVWBOiWNtxpjis4SqFNS4kugTsBl3CoCJdCYXYkBiD051aPuUc90lRQBgaLHXi+Hyyr+JdNiajWmf8NVq6qae4qvygg3ipWYOsl+vCxZlEAoL5clUJdpNb4arhOrXvavWIt2FgNK7iVQbvVWVUnYk6oiUMY0MUW4GlkNl1RNAkVJTzJVhUW4MVBNXu5WI3sKF/11qRrji0AEymXR3BhTbvVXYICyGCC1/VXq1JMIJAJtQ2BGiXtsjK4zN7YOG2jq7vpIi++rOHzwpMbWuzzuzr7s4ft6cVmnqtvIOhmXxQPaeKt5DD7HKl8GrMvIpQ+ix0ZnGpRFDLOrdsZIGmWMsIkkAs0z7faujUOtpGWGXLwhUGewtMoCScURkAUBOpWiSJIRLpUSl77GQ6zIVG3rNrIqEOEWxYpwt/ZTUmdtqGV/SSigCpzjlnOUNy5DTKFKASPGuRpDQEYiBWjzKwEapM/pFCVxt5rWbiWXBMhXkS8aKPFVHEpKqhIoaktMYwAgVQsbBZrE0M8kyesyaozXdJW0aif7iUXfEajDv0mm3d5ig6PbW3WRjbaFgPhq2/C1JdbCNpooGQLOaiEsFxbQQoiRCSV150hSF9l42aJYJCTcLebusse54FAnWWdtlKJx9JM89BQ7XUZbhUnV1PitiWh+gQBJ3V+8SMlDOCKdRWrMBIRDeWNrj5jQXNc1JKmO4cU8Cn3SinDJMQI99Ze6UhQ9PQXo73aUboxX3uq4HcUvY0gxrxojUqtz1OXeEzJFrNSyGMKwdShyqaDG2ilpewqol6olsii5UNtlZr2dPanK+EQgERiqCPTl5VRYGF+MI9/61rd8jM9Huw0oMRkIiD/11FO9K+m3b/ySjm97G3p4N02uBx10UHzRnLBvCG6++eYCxPyWkIAvCcb3CmlwRC4+5ug3KTfYYIPQHPm6S2fISHj11Vf7sqTPesRdCUVOt8JC2MdGfHuRti233NLn/0RGQh8KlK/PLPp4pW/Ay+uKK67waRfsx6u0PkYZhfKhEp8+LN9/9NtM22yzjXdJ63IPtWFwHVYiHXiAD6V7W9erqHVpy2UoMT376KQf+/RpwvjapuRRlmuuuebKK6+0wd1nLsELOt/XN0/7MuO6665LBiw+Ue+zhuUbPpLA32cct9pqKx/cDD1yFHD4mo1vwPu1LDaL7LK0Vi8OMQQC51JHYsiEQOPZXZGN9ouUyvcW/QBWWLvOOuuIBLUv5fvEp2+ob7HFFnL0OUhzIcB9VdMnXNQ745XXRyrJRI2QV3Hx27SUhEkHH3wwBDbs+ha+T3n6GOUXvvAFH4t0aJDRlnzQ08cfAev3mLwwrTFEvEbu529VulTxMwK+5u6Dp8ouuW9WglouWPvGG2+stbMzfPkiHQVD2iQRE2digafzr371K1mrJnfZTKAJjATiIEzskksu0Sw1SCBEQ62L1xh8ax+YQFCbGIavD8kr4NKWVN8OO+xQ11pkUbUhDIuYEhaIUjCY/GmnnebbnfGTxhHzqqGVP3W2hc3lfmkbPoSqT2moPnWqov1Kg8a59957ax4+P6oN6Ji+9+qWH1B74IEH9BpDzQc+8IHQHwqFHQV/popXhFIKMQE1sdbbsOR1mIda51BYHRN8QTVqR4M0LNRZS5UOq1ExI0Y/SqyjtCtdwA8vdJWg1mCipWnknu1A2HhIks3f+c53NGAC6tddgw+dvgnrY6mYtOEUwnq3SD9Y4dOrCKtLX4b1/dbQoHlXW7shWtvQF/bdd1+/6cYA9hgbQ75uDJd1dATVpKRs0DcJ+w4vKHQNA7us6/pLtRT0E2BJT0cIdDtKS1jijQ8xemvPMW77yKzuUB1D4hPD1ZgwHnrGdpbrg7JjCc2wrUOmjANRyy7L3EfeVwHEq2L6VZCpjQY9zuAQtSOgfZLsqcgRb/FzyCGHqJH4lrE+5adRYuAC/v777+9HRapfyO0Jt4xPBBKBoYyA8aK3hxHKYVD2wze+5Gg2pUFM6MFgjjnmGN95NNDwrIhEEZxxRD9xGjLORx55JK5GyVFHHeXS3By/IlQEIpX5AGEqkREoecUllxVVVZmqAD3mnjhCJ0kCDgn9PhFfjuTsER9lMfP5YVSXqKHfKBUwGZxwwgkCfuf18MMPF3CYdP0oKcuFaZbEz51S23Wz+1PjXYYR9al1XxgUqJnV9cHB10yuvWwauiJgUeST8GL82qtRviTh7IGkVD6Qf9hhhxGmkP0EMFF8XcBX8P28EX4s7PCNfAZLYoq1bBBT8Om6P40GFVQMEBnhEhPypY7i0t1ivEARjkC39tOMvGohAqxVBAGSfl1LwKSoLVmE+KVYl6eccoplFV6iwdCvaMorXtiZwfi9gCNyNJX6gS1qIxId9JNYwirUJ/kjEgP4wQ9+IIxm+Tkw3+aPeIwEZcf1MSFTdURqKhAT9suvRTJuNZ4Dw2p8AURkhDU/ZLQqUw03AdO3/E866STCqi9MwstdVuNxPjFgCTBDc+SLW1jCAUSkuwV/qxcxVTsjVfVcvSus1x977LF4YSQU02h2JKnaFjaTjFuNbSNyRE91SWFfOI3K1QYs6sTINGR6OvfUhot8NJu6NtxoPPkm9pe7xgSjIi4uRlsqtRO1UGetX1c4+uijSZbRTxaGIHRNdw6dkamP52qKYhhm/LEaEYaJeIHqwQ1h+NU7RBqcFV9Aherp+nuEtWTrW2Gtt7G16wtaQlhOxo9IYPMCDuNJdQxnvPWA/oVQxi/ZnX/++b5nRZLm0uNKf5G2Worrr7+eZOBv6CiYl1FI2R2NozTJuvgYk1Vi3bjtl/ui2ROISimjitEjbGbDBRdcEMZQG7kb5+uQ8ft0YTwZvak692n2hx56KD1xxDfT1FFj7YRAKWkUJCKpFTDUyMgSS1iMMYolIaBVYO3WGC4LRHErz4lAIjCsEJi+Z7px1QIgngO/48NDHM95yYgxPZg2cCxDOb+OW+XL1gQ4xuLHayR3yXVkYMLseY4NQyRxffHGKU8bBSikypCKXpA0kwn4DUsBtwxt+KuBjyT+6veSTEW0Gbt53wmIj4PDgwc0DuGIpJAMDVyVTLVNOeJZJUCVJwaUc5OYU8VwGsXvkvoBIOUSY27DgOXL04N14ZRs45eiNgoYCiOMicaDbHdRQLe42M3lZm6GuQRdfDcmDHvN3trfUhYBgBjZ1157bWK8p5RIG0nEM5J8fDvS9A+N+KlaBTSRY4d4D+N50MM2tMmHIyXhDuQiEhn4hM3WEg6Yy1fVYCSKEMY4m86xZwE2mK0pl0UkF1mz+7UjklAu0K394q2dGBbW8pMx3gGcbbfdVkKfped/0kiiqSggmqhe1IVMXMZD7WpGUcAoiOmZ71BFm27F4yW8swJaafzilTC3Pf0CaopkAKsBmM75eolZ81BCANp8is7k1bufFRMZh+xgrgG7W8VQ5RJgMJTMu+w000ftCysp6PiM2aklcxlGUwkNEr4GZO1vKWPc5X7mfJUdfGT9qh0jRlTjo7nSrJFTrvsQk1wqDYBbl99USav4K1dRFRkxCTIRaaXkYAmdpRRaCBnayLjlaDS7J5tDvrFtBIyYlqauzdOse/LEQ16MHEEnEE7WYnAEIq8mbZi1iq9Q7IxxJtowY2hoNF5kE/vjFq5mTOAi1YTIAydqByyqWCPn1q1aqwjGGcXRhqP6Ivc4R0GENVSShhqSDFtllVWUy13DFKdviDmDSxYGxo985COaE2E+5vgpa4veDTfc0GgGMbZxCXtUJYkxubG1i0HxNWzCelZoiFzAVR3D9XcFVzS1YPAR9lyLSSzRg6r9xS32dFuKKCxVBfMYRqJE7jaO0m5V43XeSMI8Q4TGzKkvLFAdQwwXDOCCKaNKPOANbWFGFNNZcgN7dRwAiCOEy9wHcDFgNHpHR3ZpLlNlNMDEZRwweS3YrHUZnTwQU7PkKdEr4Qk9I4Z5zYRr4C16MpAIJALDE4Feb5UxoBglcSCDWjzOxqIMVYZIT5D9hCoPhznGiMNnw1VTBiyTgSkHb8Aj0ZeYEmKGAz3WaxgVMEiVmjCYGhOlEsPZw8OEM9FsdsSl0AuORk+HOXL22msvviWTiiHbqMppYZiOee70009nWzw2JeAWtTHQm6pXXnnlmFSUouTLNoMmlmCCFBAfrFqRzbvxg6YG8T322IPvFh8yfIPCrByzryKbhEIb5bLj2TU3m8VNG2guw2DFVMsMc4kdL9Yq8WyUYX4WlM0gNfGYkxissAE7DKEUc4xMIxBndByGZgtZmKHN3BRi28Z9BYEG5G1qErZxgm2UI5QUqguTuuRhqlsRgDNyw2wThuWT57NcPh4uMwZBQU8F+PaYR48tIhKGkb21XyrwajMsYS3o/GAq95j6RX3U0Yc//GE2e/YtCweXrU0p6GYQL+WNH+5ldgiUc8RgzJTjFsyGDGvtBIiZVdaQh4mGFDyDsCfmGoO0wIEAlg+rVVddlXl8qBqMrB3wsapRlYB1BrgGUGwQUC9kNAkYMkl3oIqpoNOSNUW1r6XpAnZQfPnLXz7wwAM/8YlPmKHhrKaiiaplXjdiLp3tEYrVC5TYxnLt0C3kiZFyEVMXL5V4K2oNVZPwZMNv8dpq4kGWNYnf0JVcqoK/cPw6b7SrAFMtoHo77rijXPhxVbpaoBMOSiFS2SFAWJiGbtuAjOpsC5u7bdsADHlrJ4+JAs/SBlSEpaZcWOWRiC5PVXULQcFfjtU2bBlACSj0XI3BDzZr/FqdVZMqZr9S9xbzSCVHeMaYAIpoV1E7mhNMcDL9sWpt+S1nXoDG0S+Qd2YPbcEa5cJ41S1eW7Uk0PwAyGw1qMUaXVWuBqmFCODuCKU2j60SE0mDsUVaGizA6lo7TOgXb/OJwYeMXlO4u2Ff+5djjOE0R1NhBs+FTVmSGJBlYRHueVS1vxg8dYdqKWJolYWjV6O0hiFJGb1VPYjEsKeM2yIttssYosUqtdmkxMSoAqha9pWD8a5Iak7VcUBTjx5RnfuiCOAFfsBlNavLawmqm4aoHQaDiOaeWpdbDvlq0pD3WMliUitirZ4l3rxjvjBoWJi5DGGBPBKBRGAYItBr4h6Dl+EDhzCyOFBPI7uRxX5K7IdLwBBj0Az3M0xjnDVqoz6eNnI5mzs99TOZGV6dDYWmf45V41G4XaWSEbXGPh4IGgyIsfPVpEK/3wfF7UzYcjd5EJDW3k1Dmzk4xvEw1Tho9hImQCwinY250pqzhQ3QEW8cZw82g16bHRHHsrRgktkFBbdzQ1hGpknCwpiB4VURGOyyeoRaBoenxMxtb65cFMociS+aIRB3U07M3NLi0HvuuWckdBnzQehUZPOHcNhsKop4RcPPcBQUEPPz5FoMbC0PzBye+ZqMoyBqIVIRhqRKtORAYlA6k41UNDuoxfW5OeHvmbL1kpq1+GG/3fAWQlg7Eu9JNGErK3O2LMKYPtsf1gavUlI1rjFYNtithGuiHbKAGBIvPibIKO83vvGNwCQMqDsDRJGRJG8gwNldhTW5mvjZr6GqDj9Pq9IVXzxJZ+Xi6uObVMvqF+PBqq0YNQB1h3+QYQMNGpWmsuyyy7Lc8iDWmVTJCIbgxY2CT3iywY1HrQap/WhOFloWLRBjBv+cFi5sH0hUBA0YknyjRCKjvUUFBW9TKe5qySRDrBrPyFinaWyWK5hcLO0UlpgfLfagRiRstZ/A30sdTBKjXKHQWRcjwADEAnp6jdauVQhEKcgLk4xUjW0gFFZtKzYHVt22bVhp8HKUXKljuNAGVKgiWKnanc9pjRXpsNoqMTXFjICo2zaMJasjdWe3g3LpILqtOiptuLeYh/0yhYDWEggY01gVtaMWFEHd2ZgUm9fDWq3C+Fkd/cJsquKgWYwGLC21Wq8uoLFJRUBftgLUGcGi1GoT2zOMRKrXdNQeSGqWktAQPFVVhifCIGDwqbZ2xlCFZKtf1JMS+pkd2shXx/DPfe5zgfZHP/pRXBNTN55Aks3Krt2qqdJf4FwthbJXR7ZejdL0V0fvGO1ZaMaxmHTLNirjlfFNt4oxxAptt912EwOi6qhSBzglUAIgbDkjqshon7ECt7WszH3EDAXOhnd+BMmBpndTotZK7ag1I5jkNPfUuiSRXI7GYRZq29ZIUU0KaBj8yle+ovrUdRjpnEcikAgMTwR6R9xjSuAGMHh5nMcZZsAyUBq5jDjGSiOLKYpbMfy+MDUyOtw1YHm9TJjHDpkwiBN25q7gU7QRJabnyMLZQIbUGuwEYr5Ba0zMeAZtxx9/vOmHnyPmXR4pczAyhA2YqEzYpTqNp4yUu2kPN8Ku2OCu+Y9weEm5Tqu0w5DNQkM8uqNQjJHWNMNIE5Xh2LJBpFTuRkYMc4SS0F8MEFAKUwjc2IZemD9MLbLmtmSP0gEwbJYWlzILmvLFy5SAoZxyODDJvChr8pKbjymP7DDI9dZbz9LFYsZk6a7Z10tOqJKNE+ijyQNVRRyDTFCFa27Y9b4mT7D6KsSdfjpN4Yqjcq21XIoEOECEMTYONjzYbERnmYDDyN7ar1wooxoMa5Xd2gZFwI9holqhBDqF5fi36uPUlJFtP1FeliAZVhGRexV2ml1Ki80ABJ4eoWBpaB89liUf+9jHFNBzg1jVmGvxG60IPQUIMZdagiaqKSKIystUBMWre9q/BoktVXOEkkO+zoGhrBmmxoEMfPEw5O1mD2D5QRECt1QTVzpVIqN3hAat1KMkszWd8LcVwboiShp8LnK38tSuIlyNl1yDUXAvxrkroCnqMvqgJiHryMV6rOCvtSipjhnaouqZpOnKBZNW+27h01EKXlVP8OEZjZ9CdxvbQKxpq7ZVbZak2rbVNeYnklrNQMCh1KyKNsAH7xLpFB+FUo9dUq+eolzdtuGoCMU3hvA1wEdVRleKxL3FHEQSRsHLmKD3FQyNHkYtKw1iVWu1ruroFxpeLUDXn6JT8iiRvGTBEUCPHm2JXpXXTkRGLhqMp5Rs0M2Fw0hnh0wZE8uAamtHEyVXfHkZjekRg38Hfex2DMcpNQnPEjFvjfxHP/qRkZY874n+Ve0v6reuFOGqiMbcq1GaYYwso7chCCAitQfNW0Yap7UZoAwLMYbEBjaNvDqqMJ68hOVQcFhppca0KjIKBTf1JVNOK6NBzH2xZiAfA4jkeoccjc802OxeNAtEDWr2PfVoI5Us5KVNnnzyybpAbLax1DQG2r5vVHRo6sRCW1V/hhOBRGCYINAX4m7C5pZDm0weRjEDJc5nvAMZXoslmw5N/zxYYiKen88wFJ4hCTlKDesmCUOVsEfwZtMYNAN3YQETKvJk7jFaGXP5NoyeXidFmFBnDA8TMmqTMXTiFpJQaDDFTWM+EIPLmqQlpNNgKhBZMNVsTbkY7o34DglrzWfmey5DB0boAboZyz4HDwQkNPcET5WKd41rRKRUMsVsYiqKIkcukR17BJB1Xk9jOsZgDWDVwY+CmEobRDzGYpMQQCKhM4ZHVVyaZqII3v3i8zbExy3TCSXxMRaowhn1DFKugAhfiJlvJHe4NPSH815Y7rw7AtUDCDQouwmMtWyj03RI2IGrWcDwY6FrLJQpgSh4r+yPaqpay3hmaC2qVUDrolzBMVr80p4ol6wy/0V5YzatWl7CQNNEzXPBKfnJfPFDSyOgaZkU3ZXc6osrndNdpIxUopWPPRj049MaCQC1EHRWQs1J+5c7WhBqS3YCcnSUGBhKBRaao31KZQLmoVT7eoo5no9Qb/JsR6uWUEsOngQZTZR5sffALQiHksDZLZeyUx3U2oMR+VbjcSk1hVrpgHYLUAhPKwRNV6S7upW2pB1WW0tXIf5XirBEy2cqs9ksO20YYi6tcLRhxMvXSBjQUxuItl21rdisQiWsa9tAsNZVNG7USMsq9Eu9RBtwy8t/n/nMZ7Rw/D6qNXIPHJwb2zBJ/dq6wuhEvwWMUhhDIBltWC69xbxkKi1g9RFZ65uldowM2ph3xz/96U/LpVir21ZHP8mL5dWAxiO5u9IqtUJZhvHsAr8qJow+IpQh6ZJ7RdPSj4yKMX4yVakd9mJpfnpuXWvH12M892CtTnndGA58I7kWpbNYTEpIlfWA9uA5lQ02Rngaor/g2VYL6qiUwqIRx1WzNIRY66M0eamqo7cZx7ihWrUW9Wt1zQar9OhKSiSg7MpbRhW17IimVUrqUlhJ68YBI2eoMumUuU8uapa8PuvpjQ4SevQXGmLlEzFxjvqVaWOPDgGprG+Nz9IanD2WkZdbBh8PFVW3MhqpNNfGkaeaUYYTgURgaCNQY9stHjHGGQTN9KZ51Moog/1wBhizUBljsWnV1IWnmioISMLzRL/IGLINagYdA1C8X3XccccZ7k385hJiZjK8WSAGUK5BYyJhZwpjiMfD8HVinsPKyHxggkQC4q6xz2XRIGB8t65gqnOQ4LgrLT0mGJZIwg+KDlLLQl49xcRszJcSuou8emQsF8UxS4V55s4yOouP6cEtHJrNcikHfFBAICA3yohqGIXByJVCA/4khrCsnY3sYbCsicWtIAceBZiYycPcrAkKNssRSyCJ17KQTp4nDz0UzbyCZXK5BVlnQ0wezFNxJgCMTSrTahQ/7kbp5MJUltMsFxUEKMZYRPkAixoRplbAQWGk6q39spCEt9jkVKwVw37+QjHeqzMHq31NBZlAXFAQdVfKq8kFpS78SfJysNakq6LFWJyo08DTMgDL0WaYLTlUkXiSqgD+LoXVPnxM2JYimre07EH9LSBN/0ikHDVR9e5Q6bKQXeBQMIStePUS+bqUivGyUEEAlFZxZKe/kKQwAsKOENYSHFoFSZFRTUAjrP0H6adfI5RvNR4ZIo/K0K9r2M8mrbWojWqf//zn3UUBESzNu9paqFIvpQ1HdtqY1TjSLwulEBmlUBBhLSSISwg3tuGIr9pmoYKJAjbaQGnbVnHaNrM1ciODOlI1LoHv0Ry2F21AFcjR0lqrxh05fTWSYnPBn/JqG9bpZGpvmG6imJS7BKOjtOFeYa41Rl4sdJQxoVpSgBuFDD6aEGshZg0plSVcGf2qSkKVc0SiwgKKj8F7zMXFYERCuxWN2dqPW8wgj7YqEUzE28Kk3rVh8TZveHFCP9Va7PL3SrpSo7kqpdraZaSnGMY1S5hbrzrrEd2O4W5pM5Ij6/JiA5MMcQquOWkh1f7CYD2OJdVSVBtMr0Zp41519BY2fLHHwhIa8lVqynHfGEM8hASF3MWXmBgVY8h1K44AHAIuq8gY/NUUwNVdmfs0ThgqKWAVkAEOrUj7oUGPqKudyKLb1hX5Qq/I8MuYhhRBcSRhre4mUpVpQsQiScjnORFIBIYVAr0m7iiIOdKsGUOe4cxoYraw2dS8bkj1eNTojI+aqPBgow9A0Y5wTge4Xi40YQtLaMoxH/PdmieQSAxDfEzzKDKFBJCnmMvF0891jTZxlRmy+f/wKvrROwmNtuGINdhFXj2dCfDTYAnImU2cLOFCNjXKi5/DAG32sjtccrfEGCiRV8XEYJjhkmutyrEQEZFuMc+TYgnL2EoVYdmJZDC/Oxc+p46dEgZ6k+h0bY4cUU8lNQ/ZPwN2A7250y0WcrjKlD+Gd5xVCBZYvIkoiXyjsiQxtbNB2bEWufPJmQbs/oSztCYedyl0xi2wHGI+UgEZUxEx8GL8qgD1MU8jBDIydalxOkt5Ja87erIf5SKpck32Ya1n2ay1ujNBel6MFnDaIRx4tsc7XkTmiFJeXqsoL+81thHI12UalxihUtAJZ9VnLhSvtagIAYaBBXnFuenxkFok0NSRAGFTJhkbBhBfL14DyjdA3RLPeC5bUPCbwooNvrRTnm+QgaEGJqAuAnkMQ+OP2ucLx0FVPehwu2hLBGiWRKRzt0eAievoiQgZrECkQ6lN5lXjbTpScG3Gmge7Qm133313OrU6dS0+nnTRU/CPVsqDXtqw7CRhP23EKFScaikQGs0Ad+nW2ojs1ma3ND9rNoFq246NBxpb6fWSo4+WTKUNwEcbMFxYSmmZ0NPv9F+qVESg19iGbY4ydlm3oGLGHH53ZssaIM3bcLf2wxxZDF9DCOjmsZiv1oLaYZUnHmGtKiAjR804Rj9vccCQTN0RpYC8lqYvGEvtSImxQuuVr+bnsPWCJ1iFauEeQRiidSUCKh0UDq1Lt9I4tVJmxFAJTCRbjtXWrmYBosuwLQ4tqqcxPBarllKW2XI0euuMWggoeKC77S+lFFbLDCNZV+S6Swg0jtI0V+N1anq0FsN1jNvh0jZSxRiivFq4dsu2EhNrpzoDAnD9og4ZsBgZ+DIkL3Mf4u5QC8oCeWkDMUUwktTVjtzrila9DDO0CnUR8VYaaspco9lHPcbgLN7EUU2b4UQgERhuCNQIaL+XmefGAIoX9rvmwaCwyXxjdHaXU8cqJZyjA2dwEzOa3OrJHrQVlQl/at1k1lOSGYzvg5E95Riq4owIVjdG95RkCMRXAWwert6dbsGbt+FeqWrMq5q8Gq6TbHKrTrJcojUt9rs+KC+5VNNWw0WgBPp818KPB8SKBY3rVkm3kSXfbgN1Seouu03S58gWlbco1mczWkyotSPcVoM89BZdg8SqFo1PsUQgERieCIzpbbENbY7wTEhbLgXCJRDP7uMZvRgskHARi+zC/SA+kkQkd4V48o6IkSoG1sgoMo3IkCmSIe/SXeG6+Ljb7blY4m7JPaylpKqnaC6RxTZpwypFwID5unhK6rIryiMj8gFLIzh1Cesu6Ym0zBCIcMhUb1VzqRosXC6llYQkszn8uM2Ey924VcxzK/AXiIQk4y5JgZKQQJOjamTN+tfaUjU+krslsppLxEeMcGMSkRyZfIQhGWdixfJQSEMJVGW6zKnVi7viI0DY4VIkAeHQFpeR3DniRZa8Iolzt3pEhjbnEIiENNTye60LFP2NATLSRo4hX8J18UVSIHIJbdW8hMMeAt22YXcdJXnIuxQZ+sutRlNLTLGEsLD4Lq2vqi0641bVvJAUE6oIRHYliQbc2O9CPoyUkbSRb2TqXC5JRjj093RutD8SFvly2ShJxt2Sqcu60a8o4cgPayMmUgnTGYcwAfEliXj2V+WrxXGXvKMoEZA8tIUe8hHjFsmiLSRddin4X3xJFQLuhjZnMdXIUEW+akARC+Hm57q8IqPIwrmYGhaWu26JiUJVZepiiPGOx4MyYUcI0FPyjRi3KKyqikt3S2SXgma1EwLdnmkTX5DRPBrnxGJbtxoyMhFIBIYDAq8y3T4U1QhioDHKlDErBhqPgz2rjQ8+NFfbON6FfKh1dhTlzVXV3W2uuU64bZdRItlVC8XUuhhiYsrw7TKKU2KKwdNNWyRDSbWy3Ap7qsZEZGNGRY9AZEqmiImhip4SE2KhudusqwoJuIy0YVJN9WvTf5HsNpdq2pD0+N7+E7tfigYJSxkLVYqYKEskNEeWvPoWCONLXnVKqma41Wh5yEcxGd+Tnjq1vbqss6FXaVO4PQioI+On3Rr217Unx+Gci26or9klZa9LeQNqOAOSZU8EEoHBj0DfiXu1bDH8VWOGc7hbNLqNbESpRbHGhGJ6lbZOuO6yW/0DETkj+c5I2oEoy1DSOTNiOzPaPJTaTJYlEUgEEoFEoA0I9PgCXJO8TZDuetv96KOP9loVByenhce7PvPiPUV3i1+zWyWRnLwX4DyjrMrELW89Cnjz0mtn7nJBVWWahCO51/nPP/98WyaqknHLe6h1OVZl+itcfL1FodxF2kTk6+NKXWxjjF/b8ZJclBFuxBTfdnNpA0av4fqKS8REKUJt87RFMgJe5/IJC2+PSSvGISPflfNqXcSEzarPdxIixrl6SOLSA2WvAPpmvC/SuGS2eGp98oWbUExNdddXRy7u+oU/MT6t4OVj7aT6MFq8Q/JqecXE655eoROmp5xJeiXXV6IjX7fq0laF4wM4kVaJwpJI4qMcfk/qkEMOsQ/ebviDDz7YR9wdWrJPQ5TsBHp1RO5AVrkSsq2aPC61SS1TfAj7/IX3QKpiwh4XwNZ3Ay+66CJiIVkn04fL0AOK6KGtaIj20Irk4JGZGW3uFr3+qvdulWdkIwK1ntY12jTeyphEIBFIBAYbAr0m7kGY/OpN/PCK1+3RKSzcxmLPdn2+w/QZuw4Kfel2TMRyMKfq/oTQ7DMLvn4AJsTU9w1Exp6BbpVUIyO5hNT6IEbsDgy4ibHKzt3Q3NywSFJk4rJ6jkyrWZdc6gLlMnL32ZYNNtjAW1Dou1t4uS9C+FiBzeW+TCKGzbidT5cEx3XpfTsczjdt8HvMmB75OpgnSZO0ZCJ3STwI9lFF34CzFvIFDzGSq6/4qiOxLpU1eYuEYJNl6VX0uCuVb5iwXynwS6aqGt+e87EFyt2yz5hyh3JZFUiiEoV9jUQ78e2LUOLsoFnyKC8xMWzDp/1mii/HYfD0RC1Aw2dbfATDx/sxbwTUrZI2sAo7nVl+wQUX2CpDYdUSYVwZhr6643tEPhfjg0jCPknhyyoajNcSqoWtmfj/jzBGXBErgbhlzaM4IutabIgxW8ssyUnGJ1AiEzKWc8cee6xvPjLJN3x8BIbNdRVRcvz/pv2/qyJTAvSQUOO+vFHtcUXg/6WvXNQVuSpfDVdS9BjsSVWjnogp8SVQVHcrUKe/CM+MgaivmdHymdRmgCfmM2ndpdmJwDBEoNfEPUgJCuJ7cDZi+g6J78viW/gcyhV3kRIsQZgzPmgWZPGSmFwF0BHE3RfT0AjTMGaJupEX9iFkAWzMR9DiS3k0+CRWGVhDCX5PpkRKKJV8ffCO69QHs9wSwwwe3xDjbo8snNlAWHyQgKj4CEviFhn5Shu3yAtwiAY3JSmtjIJXOUeMu8UqixmHVGEwJuojd2iZ73nxqYv3JUcbK32qTEy4q70ecOCBBypsfH2ZKt7iD3/4wz465puM8bk92mQtrTVSk7RR5MjaKsu7wnKnJ8gi2LFbhLt8o5P9qgD1jI+dUc4M9oce1gqoTQ8NfPtMvcOZgCQs8b02JJiGqEfcWo7xXTMfQ5Sv7xv6YkN8qj8UEqazlDd+PYfn3mcZNSS0OyAKVEn6yIaWRo8ShdO9pA2sqHVLrfk+t+/5yJTxYUn8MBAl6kt5ld1dFBb4MoKqj136PmAQ99BT6HLUO83qgvJq/QYmERNsGLaMoUHLoUEAPjKNuz5Op5tIFZVCW9nEHMWEnkhfqQOvpZqVDz3SOltz0hY5Ort0doQqZ3URMc4k9Y54DlZkXOpuPt+p1CLlVbCNvlCSR9Uor1zYE4Fq7lHLYiSMli8tI4uGEggYZR29u4qe5OJ1qNAcknKkU0zYVm2BUdJqr69qIN9YO8WMDCQCiUAikAgkAkMGgb58VUbhETX+0eBMPkeNDfihH2TI15R5tbE0PHXDDTfErhBxHkSsxS+e+uKvz1RjdZiTuRxHxP84g9FW/MnXavFaT/NN2GIEcFYCfjUGCUNSLRVkbVcGJdiDWZ9mSmLaRjptrbGKwHji1VjkD/GlwYeuZW2vBSLOt8paHBEVwBerH0DEJCjnxlYQtxREvsiuj6bjdtzAvil+xRVX+EgwBmnngx+I4bjlpea4RQHdsp5hjM82+8AFloaO+Lg7SsFskW4JWLHElyLtfuGHFmmp4EwYLVZktjGAJGLtFr6rROwUQyaU+OCmQnWb1nfoxTsIyxrOwFQEMYpMIT2ellDLtshIDBokO5WIOuNqysI8AVRPLUtLwMtbfvoxNEPG5+oYBkx1JzIONY4owzy+Sh5VTL/4WHhgZqyizSFH3wyVF0Ak//jHPx4cFw5aCPujCLKIT5tTqwjypbCkjfKKoZY8ZHBfl2wLS6wEXDrswFFB4jUzzFiM7LRGBVQRQQ1Fxqf9CXgwogl97Wtf8wtHSLYq9hNUcvEAQftnf9S4hCpXC6dcG2aAhw+++w55eGKrnqiAUfFVfc2O1w5Ffi1Y8+Kz0xnslqxItg9yK5qHJNowRuvT2nKxpLTiohOwvsyNLtvno19ccsklvjwthlUe0SiC3LUZqyxNWnlVtFvWY8DRs3Qf2fn1JXp0N6svP+sT4OsF3//+93Vev2yl06l0D1XWXXddj1lI6mLRgH0zW+4eBO255556FpP8GAL75aJQKoI2u+n0EY9K/CCDBYyiuRu9w/rKATpgGi7Y7FGPWoCh3sQ2vc/QoRQ+tW5l61mELslsbUCvh4/xx/MoGpiq7Hqors0ACvXZYklBOAOJQCKQCCQCicAQQKDXHndlNvtyrqMC9i6bxbkqEQLcwnSLI5qzEQhUzLTqV4FQWJRaKlN7vLaPcCMxJmBch4zfqthjjz3QUPzAZO+3QjBjlyimAwdCofzKo1k/vLD8mhzqfrJbvqbqIApccTaimNHDVSm5GR3fEvOFL3xBElM+SsoeLMpvB26++ebWGwxjMA2EWYiXoLN4ABLjU8o77rijtEiktPQz2C28hxlIOXs+97nPMR5RQ+nQeqwODZUWX0FPMS3MOOByBhECigrbZCJ3MXiPFYjcsRPxyk4eXMLYIQFZY5kYj7WBH1gRQ4YepASG1gzdpo3i0EDSGRNiXjyCwMlizWCfepC8uJSEcrQJ0/XrQkonRz+hAkzUk3kh4KwIzugaFoXzKbvFTJAk9esuq3i1YRW/EkIMwz7ooIPs//F7InIhoxRRQM8Borx0qgLk2C062czFLizGrfDs4q/77LOP3TI0a2N1aWl2cMbbDxMsHOkMS9jpFiMtHiCvgEyydKGfnWpNY44iyIukxmlZIgsyshajmTkjspqT+mUJSXejxjFLNa5GeMoZDxw/UGV1YcGpdJouiskqzVXN0tN40OZA03FfFFb71PJdqi8k2zYk6yXLORWhOhRf03WWu0w1EkTfOgHNpdkeGzYoo6YoiVIQUCmUENZDdQp2atjYfLxDIqAxQAMINGhv1reaosWGVieg4uKtA7ZVe6v+C1srHz3CwjiSR+kUR0DWDLA80Dagx2zoWWPAQUEYqYsh/SR1Q3VNUvcEL7pv7aFQWqC2Cg01q8jR6+OpkQU/DZ5EKZEWW3qfYSRqLSzJcyKQCCQCiUAiMJQQ6B1xD36DAJl6zamI7E9/+lOeM4iYLDEAU35M4ViCaZi8g7sUredDRdwlNA2jDmKQgHAk81xiBgToMcdzZyI6/KC4EWpLGKtzFw+QVipOO4EIS4IFchmiEfxw9CPokohEVjAq/AkjR5vYhtB7FMB+NqPmCFw4QYO4i8fLwzHMdRpp8RhpEfegd0gDXsjdHj9HihPHT2zGi7bOysJLCo0oe2krsnDwj3oagFPiZHRCjBjzwosszCT6IxV7MGkeRPwGIbPVB0mSNZt5Xj1b6CmtsiumTdJQRYmCK9OJj4IRXcOfZE1D5OsWpgUfPF5AForPWrwTWVSVYY/s3FVGBqCYIgUoEUkM8YI/GeUSGXTZuktxrAHUqaLRKXd0MFgmYRr8nCFVws6q2P4W/Iw2kugdyViB8NqqWdgSk2OkDaxcinQorIwE3HVULSHz5S9/2QYeVFK5YEsMPpoKlzDDihKWyx3rpQqPRArxXWaoslK/0mpXSi2Gr1cprO6Qy2984xsap4Ry50jWWrD2/fbbD84aNrUSdntoMKqYq9hPexI+9NBDVTH+qoF5dqFCGS87bZIeTdeKDhTgssLRrYSlUgSAWNLwyqOzmC4l2jzo6HdXS5CLpuvSiisYsLDiF6usmjQ5IMhCO9EkiGmxBDR15dLCsWTZCaP1Xj/QGKK6C4YMdlcPpYFy9ahjBnrUMkMvsIIFqQcaAb7fBFU1+rtWity7FA8Q+Vo4qTIlpRAIMBFpYRwavvSlL2lRRX/0vmJJKVcGEoFEIBFIBBKBIYBAr4m7MpuG+dhMzPypfJBohLkfwUUUUCVTrwkY2TK1m2URGlSbbxshNpuiHSRN83zbOAGWhu5gxmZ6c7OEqAbygSfx6LvEBSl3F7ulWXxM2/QgmjgNGSZZBqAvwpEjpsVnzCdnOmeVjPgvaZAF+ohXYQAsRK14KyWPaR4/sMZQLgsG/vtIy2yWyA4BIobwyYiz3FnC8KQK8N0GXUNKeIUloaewB2FF8IACb44FgBgyhMnIDgsJM9hgBSLsIICqBq9if1WbyyZpQzLOMIE2DqQ4agd6fJxcp9/61rcwzviqTGCoaHCTb5SOhRBmA/REBrtCZ7lOuULFOGQBH7e0B/QX1GKwWDmyEANDEy3kLBIUkIwk1HYlfTW58gLWheqQnf1UWCAqr9RU0eyWFYj6lRFgNQ8a3HIUrIRDLQ1B9UImLFEESoDs8Y6Sci1TwiSRihN7pdSOyzg0OYTSExWrJi1Ta0dkQafxUMtOZpDUJDRsMRRa72ldcre/RaYi2W+RgLbi/Tg0GUXQQiRk7as5Vf5okFz1WhHJDTfcEAIYv8as1FSJFGY2VLF/NlhvWCGANFqsFQsZ+njrLWJlQQYU4km6tPqKHqqkUQrVHfZIFcUPtBH30MkYaQmjwlSx0GMTCqO3iqHWLfZo1cTqyiVHDUlBKJe29A7sX0YefejOCLeRQaUAXI0oQtSplqN/0al/qQ7nKEX0estCjdnuLxosZdlAQ9RF9D4oVaDNYCKQCCQCiUAiMHQQ+B9fab1MCI3n0TFP40OIlwnV3GzeRQ5QDZzA5IrwoTtumbmxGZOrABrkHFwEESFpV7c52/N9Uy9yg/2gAuLxA4QAjUBB5IIYycg0b25mKjGEjA3BNmTK+8gAflB0QTzeQ97j/uKBM/1LS9LCQLz9A7iFSxqiLDyL6IIw6lPSogiRHVZKknIMVREsPJwxD3YSQC94OvkyFVPBKXE3IA1O44m/3O0WEOkuGasOhQICcGzSJeaWlQmOEgnxEj5XxUevGeYRBDck1ogzYcaw6iktVYgyZqOmLK6IMQZtZSQiZeOK5RYQMD8e02rxWRiWMwmYSscG1UGGBpF2HtuvQo+7jLT5WE25ZQ1gFSStSDCWslOoAYhUBF5b8TaWIG2solO88moqAnDGC+1lirdacS9bt5WXpFuWYWTwbJxSLkCOtAUrlw6EL6ojLoslAFEKflxmW0toKpDRYnFTRaDQIYkzSe0qZGwQ55IXr2Wqr6hfZguLVCNIf3ivNQmty0ZwRfNgBA2VhY9OakUEtF7y9n7w3ws0HjLVDpUFjGxQXstLmQJBC9EA9BpOdA0GVhRaD1gPW4OhuWIkIRaLLhBZ+WywwQaeKelWWmkUTU9UWGsPHUeMslu8KSBj6A+TQlLWNAtbKlhDCiDreiJVCmXbjMJajWg/8fDKcy3m0cBs9RIHlNQ7q4JDszzQo1Ny8hbGnO70U6VVWA0yT3+EvM1ytEV31gLVuE4XFjKetUzy+oH1Z2jQhOgUhozco3aidUWqPCcCiUAikAgkAkMGgVfn7BbLY4pFMjx55yb3MUGX6IIt6eg1RmieDnc4ModZ0mmiDa+eafVXv/qV2RorQlKxHFTAdGtWPvLII53xD2wefTG1Ix+mZxrsUfZg3Wet5WLfMIUIB0ITmlE6gTCJZ9rX0PnvzdzeLhWP9nmS7jm+sLmcQsTCesOXapB7HBHx4ihVHDzAIV/0IsyWlvtTWneJKQVT6RGQuyLYu+IuzoGihT3YElJLj/LahOAWiPCn0K9oKAglCstgZaGWH5fNmA0yxEKSDrm45SzsaQBSovgYGEaIiwQdURaafQ6yp7TMIBnacCOH75QzzAuFIkO/kuJe1XULMaXG5u0b5shEc/FOHFESB5M8WlGznhuoaJQaU8f8gOzFQWTLpUyVDgPzsIU8Dm2BZLeMSA2AAD1RBBZGxRGzDHC2crNeUiK5aA82YqlK8SSZjUBbiVlFxAoH/w6Toixk4lKOJZW0xRKZIuhaKfwVWWWpRO5qRDZyJxwHScqZEfSRkbGbSx2pX8RakrCBEns/ZG0dBSjUU0uIjOwkQeIttPQRAp45aHtAs1aUi5jXcvvfX/YT00hYKHeZqn32s9n2KnWnAYiHp0aumKpJEqsRjTa0MExAvchUF9BlQOHQ0cQj7pqfSsduNQbFp1ASXNkDAWGqFFYv0BTpxJW1beViOYjIO0dvtfygE5u3FrWxh7wGIF+LtP+Vp+shWJjEThvuC1Yqkf1ot1dgNWzLS42KZp1LZ4ezu4YUUNjsrk3q2jb6RynIQFUu2j+B0KB5MFuzMW7IMV66UJaqMRlOBBKBRCARSASGBgKvMp4+FAYVQAvCXSoQdMQkjffgqRTilxEfkygqYH4NnlSN5zsMvynSQxI1dxdHoSESEkAEI+yWgLyqGsJ4yTmhC48RKUcHBsMextAcawO3GC8+EsaZ5UHa4rKkjYyiXAQE6IklCl6FtqKYwVMpR4OigNW8KJQqFIY2RkZxeCXBhakUS/CkOgJU8CkyEWglbUniSUgYWWJYK+s6Ekkn5AMr4ajckkShHCpRcTx/iDpSIgxPiUSGNpqVLgooLUykqtZLUShQyisVMS5zeoImVsWE67zp1bTCkTt+z8uOAUdbqrOEWGzTQlKFWe4MBOe6Q0IgiCSjIKVcpX5DnljEyJ1k4CmsUJEFoqks6DJOKYwfu+ugEyO3uvNWaF3WqlsS8JZ4CasVoV60EDL0yDTsLAZLpW27q1FF8RnvIOkclaKbMJVVXbZMozD2OElbdApEKQQCTMkJlNborkuWEJCRpwoeyESptRA82/KeQGkGVayoolNd6IPst5xmnqUImdAgocZQWqD4wLZaitBQRoaiX9o8EoFEIBFIBBKBoYpAH4m72TomcrhUwz3B1IpMT2kjvrmGxrslpgQa9dTdKgaU+BIotwTwie9+97v2efOpcwPvvvvuxMQHIN0mqSYv4SJZAuVWY6BOplyWQGOSElNkSqDc6jYQRM0t8s6lohuFi8ISqJMp8SVQJ9DKZUlbAj2lss3DQ4MvfvGLGF4jIy/JSwF70tMYX9I2CdSlKpIWNp5g8Elb1IkkBlI7uHyJyEvAJVWRFxPhJjE9FaGapGiuBopACVTv9jZMiSSK42OOHOdV4m4XVtFW8opAuVQKaT3DIWzzEvk6gSJZVEWgGi8sMlppNb4uSV4mAolAIpAIJAJDAIE+EvchUPK+FSGYga329gl40M/dzukYpKFvCjNVPyLgsYallM+P9KPOGVEVrcVywsMZO0ziMs62jHNRx4acGclipk4byw876Gxg05sCmZm6RGl8IpAIJAKJQCIwoAgkcR9QeFN5IvAqAkOblaLgClgq21K2bJIpkRlIBBKBRCARSAQSgRlEIIl7XwDEUeIpf7KTvsA3kGnCiTuQOfRadzDauscy3Ub2WvWQSBBdqQ6fIVGyLEQikAgkAolAItDPCCRx72dAU10ikAgkAolAIpAIJAKJQCIwEAjkR9MGAtXUmQgkAolAIpAIJAKJQCKQCPQzAknc+xnQVJcIJAKJQCKQCCQCiUAikAgMBAJJ3AcC1dSZCCQCiUAikAgkAolAIpAI9DMCSdz7GdBUlwgkAolAIpAIJAKJQCKQCAwEAkncBwLV1JkIJAKJQCKQCCQCiUAikAj0MwJJ3PsZ0FSXCCQCiUAikAgkAolAIpAIDAQCSdwHAtXUmQgkAolAIpAIJAKJQCKQCPQzAmP6pq/uVxL7rKTuV1f6rFbCOlV9MylS9UFbH5LMiIW9TdtnYHub0XCWLyBHUyyXMOnHxhkID/L2NpybQZY9EUgEEoFEIBEYOAQG9geYpkyZMnr06D5bP3C/gtnTjzVW46vhbouAPDkG7sdTB0g/tYrTj1Ry4KqpW9gHKLJXbRWG/QjgAJWI2pnFzoFDIDUnAolAIpAIJAJDCYFeE3dUAMXB1ZwBgZdjrs6NPKY5aaDhlVdeGT9+fCG+EePSQduYMa0+DZDRSy+9RFVvFwl1FpbLyZMnhxmt1LRUjrqy9JTw5ZdfZuTYsWN7EmiMpxwakyZNAviECRMaBaYbI60jMu0VsE00Uxj2hHndSr744ouzzjprt7daiWwRK2IKpfZb0dmTTJNS9JQEAlUwNQCXDvKg1oS0Z5dQolzFxa2etPUqnk7Z0amVNkkYbbKJQN5KBBKBRCARSAQSgZkLgWYTf11JEBEx//nPfxZffHE8af6uQ2CRRRa55557sJOJEyfiKwKREFP529/+dsUVV4hxYBvuOjsIXHfddUsttZSzMA7kfP311y+xxBLoyLiuY6uttrr77rvFSyvrSOVSICwRDoX//e9/2fKXv/xFDFURSUZATBxSuewypKbttttu+8Mf/hD5hoBbDH7ooYc++clPoptzzTXXvvvu+/TTT0cSaaVyhBJJxD/77LO/+tWvnnvuuX/+858LL7zwP/7xD/FAIBbZhVikjVzWXHPNAw88UDjsdMsRRaMwLiWPhPT/5je/eeCBB1x+/etfX3fddcPgUB6pQm3kGBoiecSHzFFHHTXvvPMGqrPNNtuuu+766KOPEibpkKlzyDuLD/0lsgiE/rDhm9/85oYbbigMtL/+9a+llmmQnOTpp5/+qU99KhRGLlWDQ1U1JhIWNFyut9563/nOdwQkDw3OLuMQBjU9m2222bbbbisyDIu7dTYTc4h0lmldvpLUtVUxZIqS0Fk0Czz44INvectbrr766oi0eFhhhRX0BSA7W7FssskmcTnnnHPqIFoISbk70xwFiUKFhrAtwpF1CNfFhOWXXHKJ9nbnnXeSUeqqtlAeMTvssMMf//hHGuIyVOU5EUgEEoFEIBFIBGZeBFr1aishcuOMIv/oRz/CVPbbbz8sAbVCUBZccEF3sZYAQjy/8pNPPrnzzjuffPLJbqEXxc0s7C6mghY7F+yEn3rqqT333BO7peFzXcdZZ52FnVQ9i8Wtjo6EV14AVULjwsjiqi+pCFRTid97773ZvM0227jlMkjS888//453vIOf8qc//akCfvGLX7z88ssvuOAC9tfpjAKeeeaZX/3qVz/ykY+4O/fcc4dMAYExIVbSirEeCCd0QaMUv5pL0Y+v33XXXWRmmWUWack0lsXdUtLIS3FIio9yPfPMMzL9wQ9+MPvss6uUT3/60/PMM8/3vvc9uZCPtIFDGFOwCj3F/qqFHnGoPrec1fKvf/3rsM2ZQmcNwwqBQtUNk8glFFbVRjhMLfmGMcyWS7lVtVMqlwG1NlMsDPudS0zV5oiMXEp5I1Btq2LorzOmTrP2c8stt5RKZIMl3/e//3303XJLjzjggAM+8YlPyPGEE0648MILF1100aKhaFYER8QXg+VeBAKcuhjyeopcVJ/ShQ0BSNFGQHjVVVf98Y9//L73vU+SUBV55TkRSAQSgUQgEUgEZlIEek3cUUC+cKXFCXCyD33oQ6Xkf//73zGGd73rXcE8zj77bMTrvPPOW3755Tkdr7nmmvvuuw+zcUgSjMq5JI8Yyt/+9reLPPfccy+++OLgVRzzCOJGG20k/vzzz8c7+TtRE076xx9/fOWVV67q4ea3ulhsscU4JrEWYo6bbrqJh5KG173udXd0HYg+P/Hb3vY2nCYo7LHHHsvHf8MNN6yyyioy8mCB35Qjf8sttzzjjDNIyuvee+8ViWahlSxk3imnnILuH3LIIR4XSHXqqae6JIbMgcL5oosuWn/99fm83f3KV77CsCgFbUHXZLT66quDDlasWmeddQgrLzwhzOlubfDe9753jTXWUExleeyxxxQtUlHlgANJRA3mb+o6Ij7OCmhd8bGPfSwuzznnHKsRYbkjrMIqSKUEt5MFM5SOGQsttJBIDvUll1xyueWWE4mDrrXWWuKJVWtZpcj29a9/fSw5br31VkT2ne98p1zQ65tvvhnNXXbZZdWaGGkVUzUpplxKvtdee+2///3vrgZSayHMiyycq3aGBg8NgLDxxhtzaVMosnrAodisgBtuuCHDLr300k033VR1QAOY5CNrgWirpRQU3njjjRrM2muvremGmLPjhRde8ExG1VsFwTwytbhSHfBfYIEFVlxxRZHRhgV23333ww47bL755gtkxCi4Z03LLLPM7bffrkdEq2YVg8WXtgo9SzXyjTHMc4h314Mjqt785jeDSO1AY4MNNoh2tdNOOx155JHaM9hL7pLkkQgkAolAIpAIJAIzKwJBR3p1RsdRFjsZcFkBJAzLfPe73x0QIKmYJYUIRMScdtppdmtwQ7rEuVENdzmzbdu48sorhWlwvuqqq8j8/ve/5z63/wRnQrsxY7fshXjDG94g4MCQ7AEQ4Bfnh5bEZgmaMWaR4eVFjldaaSWRaJbIX/ziF8GBMFSbHA4//PAwbIsttnBX7kohgGytttpqApzuYjjdEakPfvCDYmzgoXDppZeWcLvttnMXsZtjjjlcWgmgYgKWAawVwKJQWIHPf/7zSL/AW9/6ViWiB+XdY489BILCuuX48Ic/jN8XuJB4rBfTRQ1DgPwXvvAFhQr2+cY3vlG8sn/ta19zy4GUI6Mf+MAHxOOINmaIZEyUi5hFhS03HilgxhLykRNAr2MRpVIsD8SQ/+hHP6pE9Fj8XHbZZZRggXYNuRs7Q/B4YY8jrJfIBzsnHxqA5u63vvUtjJy1wieddJIqQzQxePFiWKLlSMKSQw89VIxj//33dymSMTZ4iMFHrXME7GsqdnLti2G5ZQBhoJG3qhEZrUiAzVpF1Wa7mJSFPKLvFkuOP/54kmGhAGbvriP02wiEAbtkucoNyRCGrc1OHgQB3ErALce3v/1twp7hOHtIIgYOVmIc85AHO5Mkd3bLcm7rrbcWiB0+uLviSGjZIPLnP/95tFXwxmaYaowlJxlLL3g+8sgj8JFQvVgDkFc0l/Qj8cRkpyqjpNESROaRCCQCiUAikAgkAjMvAq8+qTfft35gco6a069rD4mH9VgXNy3+YbM7/v3lL3+ZNvyYS/VPf/oTXoWUcFqDiUvymGOOcReP6TZHRJlTHyfGg3EvWRBDZfCzkEdMI2wrAvc8yhusTl6WAWgiFzgvI9aCe6FolhlcjwcddJDcpf3Sl76EBCOOu+22m33YIpUlnJf4urWEGJci0SCXOJB8cTKbE7h40TgM1SIBj0fLMHskW9ZINhxYK0epQGHVcfTRR4MCzeJLDnKG7cVWGesWGTHGJaqHy9JgxSKAZXrUYI2BliGv9DOAcsajX7zvMmWqJx74IhrtrlvS7rjjjvfff7+AJY3IgjBCjB3arSELDxOsIuRLwBKCM5sZaopjGNF84oknpJWvwqLmXOxKpMokDBuoUkBhB/1Q4tNVfFTbsxeYh49c6QQCVVt0mOfViN/97ncRY5OVByB4509+8hN5xQsSqiyqo7SQoLkyUl/FznhugFgrKaysSZga20W6jHr1ZNVRbHaXnSx3RsQ1GO3h4x//OD7NnkDJwpKRqtUiivP7G9/4hkcoVgKc6AAXIOmgXWNjv4WZuojGCUDrOq0Rz7YOsThRWI0Hnh7XaKLag7JIHnlZ+GkSYlhOoaUU2s08iwd1t8suu0Rb1eZlRMwqK2Kw8H322UcSmukXyZf/29/+1tMDzQCkugxmb/FpvUqMeeo6XhQJU0XmkQgkAolAIpAIJAIzLwI1LjLjh2f0/Hx2U3jcz++LQNOJkiIr2JIzYofxILKc8TiKuz0xCUwXw0O+ee693ejFU8KYCtKDITmCMPFoolPIIm02w4cMjiKv97///Zi9ndyIkdxRGZGc7u95z3v+9a9/2XXjEu/BBd2lkCXONDiqbEym+HHwVI8UMDP+cvtkLCqwcKkocUbaJAzzBFiFmZHBHdFupUAW8fVYANCJihFjNh8wxoxDWwM47JjnzcUgmRcysq7qF4/E24Tzmc98xi2EEjcNqLnzeXZ597FzW1YefvhhWZSDSQDxsoEnANgqtoe+K5q6sF0HLOpFPB8/amiJYr0UL8La80MJY6J0zuwvWIX+AMGZeSVHyAeDF+PZAsy9t+BJi0ccYlx6XIOgW9sAQaaKaV1X10JkpILI2xUTdgLHMkwtA4EG7JkHHXSKX7KOAFMdNDizWaSzw1oF8pqNHCkRH8UJqJ2VIlqIlQzG/9nPfhZK8ZpBVErUjuZHQ+RFg0r04odKR9MVx7rFLTRaQvtqCAQ4kYTBqLy1mUIFOBaE8dQo2lW0VdXh8GAHkpzu0XrtiaIZ2gywItLFxDNMvxOPwWsbyLpmENZ6h9Uqwq1q7bjMIxFIBBKBRCARSARmRgT+R7ZmxHqMJEgJJSUQ1CF8pTilvbzhZi4C3eaI2+FV/O7YJArF/UkMn8Y8anmMHIl+OUfaEojLIGFxLrdQN2HJJcRybAUJDUVA2jAVcUQKcXR80V3EjlvXgoSA5GwomUZaqcKqiC9n8WEDgiVQl13cwjUxbxyL81hC7lIbYPbaay/O1xAQ2ai/ajMBlwwQkATpjHyF68QYwH27/fbbI7724XDMK2Okwk3dxYCtc5Sawfaj45q4/gEHHMD7S4yASqTTIQsx1SPgdasaKRwx7p544omesXhKYOXgQQfNYSoZ2Vn2cDNT67FMTy2EqrATHw0eHJlGjo1ZiwdCsbngKb5UYh1KDKAnwGxUWI2RkFhIFgNseUe+XcKKQKzl7PCR0Gq2JJfKXTupOPKtjhTK0vSXv/wlZGKnGXAIE6MHlVdT2olLZRETrVcuLp032GADKzcOfgL6l54iiS6j+3DDiyRDWwgL55EIJAKJQCKQCCQCMzsCfSfueJ4jyo+Q4S78i5gu57r3F8XjKAgW5yuf35///Ge7GvAJ21eC/KEUiEvhNOQjhhuSVxWZ876gyNgsHh+/42+WCz7N0YgbcZ3a28BzzPVIFTpoDzrl9idwb//whz8khu7YDM0MDMn+BM5OCZlNjGF4UvCbKIh9CNyrttDYaUADn6u7iD5hZtuawpONn0loHwvb3GUng1lOQ5SFJUEZnSNQvVvEbLORl409bKPfawB2jEDJJg24hT2Sh355CYvn8veupF3LCKjnElhdQM2S0Bx5EZakHG6JYbyM7ACxOLFHBWnmIQYsWCweeHCtWzzfsG+HY54jn+c+PM32kFhxwYTfV0YKSDOFxUhFsMcG1OIZ6ewJQ1BkOWKWHMxwszVccQhbrlCo+N6+FRaw6cWWqmghrJKKEvojIEapw07VrZbVKQ088V485ZaWHflyAMEThmIzPY7A5IgjjmCDvMh4a0ISAWd3GaYqlcLjCPkqrCKodE9O4t0GZa9mUVovDdTy/VsOaXv2F3nMQtIeGIFIFbk4y0VD9RAGwt6pcHgiBFtPJCTB8gmUtspsCy1mlJhYEoiRu8ajFbFQM4itaB7aCNADmTAVsFHMQDIi85wIJAKJQCKQCCQCMysCmFZvD7xBEi/D4a8CwXg2fO31PgFUTCQeg5fAhU/R1zwEPNBHPeMF0HCl43M0INDO8fpgwRHLsblZPM7BDYw+umUbDA5tj7J4fkrUXKTtK87xWmG8nMq/iwnhi1gaSSReKuQMw4ut9vGBcL5Jd6M4chG2f13asEHpkEWRyCKmxUsafJ0fFNMSbzc/SYahawKYokiBeOHSq4fxQRK7t0UiVe4ywK5udEqMI/gcpmhBYuuIGOA4+1YjYXstCGBvwrZAINlQRXaDiim7VwvCbNugrXCQTpL2zHDNCihXFM1udcVXKSIdUVNWQXbmoKT0Y4H2kFBuw0yAyQY4WGiRh55LPnv7vwUsqERa3iidHC1jgqfGO8ewctfywLvFFAoffPDBsd0cmbapSYz3g/F1qmRtk4kYZDdWIDLVQtSdSMDaqSLgDQGbjoqdimyRg+PS4BVYxtvSQyxaUWSKzlZt9kUjBzC1Q61CEs8BJCFMm4MB0Va9Gy3eVz6J0QBqVROSzo4AWdW4a4eYGMktTaNEcI6XQcVDIBoqgVrKriPM826r5Mcdd5w4e5NiwRmaRZa2Gi/p+thRibHAk8QCT3L7ahTZMsCCU1VqoiIVzTYnKy5iFEoYJY2W0GVCnhKBRCARSAQSgURgZkXgf9u7zfotHsqKA2HeAp7X4yXcisLx/Q3cyGVEIlie3XNGYl3ICq6PZ4iMD19g7TgfPhfCnNwXX3wxhsEMGhA4FEQ4srPxwIGSUkgbT6RbODEfP66JymB7kvDWI1V2I8gOYbV4CJcnZiO57NBNCYkRQJhIhv6SEberJQSWjw7y9brrwKqxZPsZsKXNN9+cAeQdYTDmjbVjfni5hwA2Ltv3wk5+aCVFbWHFPBQNRIg1jsVVzMmNWkFSLjY58BzbMEPeKoUeWNEPIosE+YrkDse5GSYgHsdFFtlGAxyY7QMvwt4SpjC4Lw1i7OyHko0owCePN3P3wtZKgGuWbehpfB6xVqSuTNF6ysPTLIYfNxghnD1dgYa919KGPVHL4OKcjqoEtYIoY2jgVGYh5G1M78qh9rUfiyJVH5ybkWpKTLQQvmptBmNmoYckklh1YMlVO5WXfs2PsNqkp7RD2qo2W6qxUwNwZphVkzWPUoQlzoFhtRQiVR/6q8GwIQRCPsLecFUFMPRibsSoZfarlFiXsgGw7rK/mjyUqHqLPWsVm3+UQnOSUdhPoNpWI201hgA0NDwQWU1ZPYJOp+N3p8pdzSBWHdqJpsgq7dOCQcuJ3POcCCQCiUAikAgkAjMpAn0h7o1FraMmdZeN8i3GFD0lUE1YiE6JxC9xXG5d3AVrR8rDgSp50HeSjalKcoE6fhPCzry/FOLuVeFuraoKtB7uVlW3kVX7q+HW8yqSVf0lXALE+qY/NGClvPK2G4VXODKNW9UsquFiWF2gakajhjrhni4tAyzwLI1iJVDV2ZikercabpSMmGopWpHvSY/4avIIN8Y0Jq8a4K4FocWAVxqU2lpLq9b+Yz3TmDZjEoFEIBFIBBKBRGBmQeB/23Z7azE24IhUOAHqgC44qhwC54iYuOvSEakixrnkGzFdOmqnopwA/RKGqlquXfniIgIRyU8vzI263377+a1KTnE7tv2SpbTUFklKgsFHXi5L7hHglYyMQm0Iu8WHbUu9W7EVJIRZVTOla0NIyIsXCLVxS0zk5Vy9S6wcJEOVGGIuQ0OJlFCMeAEmCZN0WcwrdwmIdwiUI+TrLmVUUCUvXARc0i9V0V/T+P+LWc0x9EcBKXHp7EVbnzkX4KoPARoiF2fCUYSSb8SQdJCU0FlYoFrkosGtMJKYg1jdEfHURpUxg6OdKvESlqKVVKEwSlHERDZKShLWhrDLaomKvIzC/pJFCVSTh53lVmPWjTGNyYsBiuZuoOTBkTc0wryIKblkIBFIBBKBRCARSARmRgT6x+M+qEoefM62kH60yl55zM/RjzqHvCqgxUsIg6Gk+DEG7+XOQqwHg1UDaoMNOfEy64DmksoTgUQgEUgEEoFEoG0IDCniztfoKMysJ3dp28DNjBKBziKgO6SvvbNVkLknAolAIpAIJAL9iMCQIu4Fl37nK/2usJiagbYhkJXYNqgzo0QgEUgEEoFEIBEYCASGJnEfCKRSZyKQCCQCiUAikAgkAolAItBBBPr+cmoHjc6sE4FEIBFIBBKBRCARSAQSgeGGQBL34VbjWd5EIBFIBBKBRCARSAQSgZkSgSTuM2W1pdGJQCKQCCQCiUAikAgkAsMNgSFO3H0EsLFGfW3Ge4riy7nxe9tFpjF5xiQCicCMI6D3+XJrfMY+emLfdNLQJHnzu33LMVMlAkMbgf7qm/R0OwUHes37pruN8/LQhj1Llwi0iEC+nNoiUCmWCCQCiUAikAgkAolAIpAIdBKBoelxDw/c888/f9JJJz333HOx7rd89wOrwP7lL3953XXXCTz44IMTJ068/vrrTz75ZJeW+HEIn3baaTfddJNAqBLIIxFIBPoFgXCk3XbbbV//+tf333//Aw888MYbb6RZX3NLHwwB5+h9YsrdEAgzxPuRqRNPPPHRRx8VE503kjjX3Y34SJjnRCAR6BaB6HrT7ZvSVnulziWhIyLjrvCtt94ac2vcatI3u1LX+runcJLr10cdddQpp5zSrZEZmQgMcwSGJnGPSvVLmX713e93+g2a0aNH+2Gm+OnT2WabLX5X9fDDDycpHD/wSSYOkZg9Wi+Q832AmedEoL8QiD71wAMPXH311XqcBfaRRx758MMP66c6qRhnMs7x61FiZB13QyAsEe+nYS+++GKLczEuHZHEWbh6Nztyf1Vf6hnCCLTYN6O7OUev7LZv6oBPPfXUlVdeSSy6bZO+ScBBYMyYMeSPOOKIO++88+yzzz7rrLNcovXOeSQCiUAgUOskQ/UwCmDkc8wxB38en9wzzzxjgt9ll10Q9znnnPOSSy7517/+xR+w1lprkQHCn//8Z6PMtttuu9JKK80yyyxB7ocqOFmuRKCzCKAI6623Ho87z9xnP/tZC2z2XHXVVX/5y1823XTTdddd9w9/+MMqq6yy9NJL86nvvPPOt99++yOPPKIXI/ouX3jhBfGLL7743HPPbcqXVsK77rpr6623XmyxxfT0n/3sZwLlbmcLm7knAjMRAk365rvf/e511lnn2WefPf3003VDz6XvvffeJZdcUt9E0/XKnXbaycx78803n3vuufPOO68OqOAo+B133NFT3yR/5plnjh8/3oBwwgknULv55pvr+8cee+z9998/E+GWpiYC7UFgKHvcIYgTWPc/8cQTnrsZOM444wwPAS+//PK7777byt7wxAdvsr/22mtR9lNPPRUDsNaXUCB8D+2phswlERhuCHCHn3POOe95z3vWX399/PuNb3yjTWsegnlWfswxx/C33XLLLdzwnG0XXXSRTW7VXuyWXXD6rANjmGuuuS644IKHHnpom222Oe644zxqM/3H3ccff9wIMNywzfImAjOCQPO+yeFF+aWXXursufQNN9wQfVOfxb/1Yl34kEMO0R8vvPBCbjLdvHnfRNwXWWQRTrSDDz7Yynz22WfH2qmyYXW77baTC4EZKU6mTQSGGAJDnLirLX0eC+e323fffVdbbbX77ruPG0D82muvvdRSS22//fa870g86rD77rsvt9xyTz/9dNRxEvfAIc+JwEAggIuvsMIK++yzzwEHHGAhbdbnvXvXu971ne98Z+ONN+Y+n2+++eK5uR6qC+vI0YvXWGON4AokHRx1dsRafuMTf/rTn1566SV0H5t3Cw+wMs/n7ANRfalzCCMw3b7piTR6bYrU+wTKDLvqqqvqfXzwCy644He/+90ddtjBfKp365u8Zj31TUT/rW99q36N9H/yk5+MlTZVm2yyicducM65eAg3tixaHxAYyltlwGFAceZ3X3jhhZ31/4iJSONFjAj4gYnfVhl7ZmKHTBCFPgCaSRKBRKAVBPRHT9jf/va3E+YvN7sj2bqkSxxdx+Q4D86NRogRjl5MIKZ2nbQcOIEn+Jtttpln9PPMMw9hMrFod27FnpRJBBKBQKBJ39Tj3HW2K0bP0kl1VTHVGTb6HVX6oMO6Wt+0/6153yTmWxHUzj///N4x42XzOM6Gt6yURCARqENgKBN3A0q8tWY4EDCCGBSE7aY13Lh87LHHjj/+eBthzfo88d6WW3HFFd016zuTrAMrLxOBRKC/EDC7n3feeboksu7rE7vuuiuCvt9++1lC33PPPQcddJD30uyZwemDHJRe7GE6h9/rX//6r371q85PPvmkvuy9lGuuuUYv5nRfffXVPXn3hM3Zvttg//1ldupJBIY8Ak36Jm/63nvvjbjb5r7XXnvpv56bmUC9eaIbmjdNtUsssYSXyoj997//9Vh7+eWX9zCtSd/kOPPKmWdutrYfdthh9rXaQB9fhNtggw2GPNpZwESgtwgMZeIeL7sYYszunruBxiJ+0UUXRei5B1x+9KMfNa+7K8zzh7ib6V1a+pOPeENYbzFN+UQgEWiCQPQp/WvNNdfUPU3be+yxxzLLLCMJKuDB1+c+9zmXtrei8ra0LbvsspLom9GLPVXXf7fYYgukQUAkar7RRhshDX//+9+p4rnfbbfdaPa83l0sn+bsyE1qJG8lAoHAdPum98jf8pa3EP7CF77g3TD9C2tfYIEFItIMq1/r0V/5yldsUveyqdmWr51LvknfpM1eed+N0Nmxdg41H4r1ZqpNrTvuuKO7+rJzHolAIhAI5A8wZUtIBBKBQYeA+T6p9qCrlTQoEejacZ59MxtCItBBBIayxx2sFvqe3yEBDqt2njkjjrCzI56hC0RMuStJhN3qYN1k1onAEEZAp9M9o4s5h1NNv4vO6FLAZQTiLEag9M1qchoiLYHQWXd3CCOZRUsE+heB6fZN2ZWuKqzHlb7pMnpr9NO4nG7fJBCSum10YQEx5mLnPBKBRKCKQHrcq2hkOBFIBBKBRCARSAQSgUQgERikCOTWsUFaMWlWIpAIJAKJQCKQCCQCiUAiUEUgiXsVjQwnAolAIpAIJAKJQCKQCCQCgxSBJO6DtGLSrEQgEUgEEoFEIBFIBBKBRKCKQBL3KhoZTgQSgUQgEUgEEoFEIBFIBAYpAkncB2nFpFmJQCKQCCQCiUAikAgkAolAFYEk7lU0MpwIJAKJQCKQCCQCiUAikAgMUgSSuA/SikmzEoFEIBFIBBKBRCARSAQSgSoCSdyraGQ4EUgEEoFEIBFIBBKBRCARGKQIDH3i7ifZ/Aab33Xrcw3Er741Jo+fl4v4IiPS0SicMYlAIlCHgJ6ib8aPJtbdavGy9Ls6+dAckcIlixKok8/LRCARqCIwcH2zmotwZOQsrHuWHloCdfJ5mQgkAvnLqX1sAwaa+GX1PqbPZInA8Eag2oOq4RlHpX+1zbg9qSERmLkQqPagari/SoGUjxpV7zQciIz6y+DUkwgMKgTqO8+gMq5fjLnhhhuuu+66UGVoqK3ou46IESz+eOEQcI674Q684447HnzwwbhV9GDtjzzySNF8zTXXPP300+4+9thjhAWKkkiS50QgESgI6B160LPPPnv55Zffc889sQaOjulcxCLGZR/65vXXXx998Iknnrj22mtD7V133fXiiy8W/RlIBBKBOgS67ZsiozNGP5IkLiOtMIEyk5Z584EHHiBQ4ktGwdqje06ePNns+cwzzxgEbrvtNj2UmEjTrkDIlIQZSAQSAQiMGdoo/PCHP/zzn/9sRFh11VX333//cePGBUWIUhsUquv+CBcBd0ePHk3yN7/5zRve8Iadd945bsVQgp0feOCBd9555z777DPXXHOdc845N99880c/+tGLLrpooYUWev3rX0+sqBraIGfpEoFeIRA96OGHHz744INNz3rljjvu+MEPfrDaGSkkFjFoQR/65t133/3pT3966623/tOf/oRAvPLKK+uss85ZZ50lr1lnnbVXBqdwIjBMEOipb5rLynQWMtW+GeGYLt2NwK9//eulllpqp512issAUF9+8sknzz//fB0zUv3gBz/44x//+M53vvMjH/mIyRrL/8QnPmGxffHFFy+77LK0lXyHSRVkMROB6SIwND3uMbLo/FdfffXPf/7zX/7yl7j1Cy+88PLLLyMK//nPf/75z3/GiGB2//vf/z5p0iRIYeFcgDfddBOvuUvjxb333ityzjnnnH322TH18AEYWdziJFhiiSWOPvroU0899dZbbzXu8OTxwUu73nrr5XAz3ZaXAsMWAZO3HuRp1SyzzPLXv/51r732eu6556p9M5Ahwx9PzATf275ppX3kkUfiAQYBet72trc9+uijfPCYxNxzz82AYQt+FjwRaIJAY980J5K3zDZv/utf/7rvvvt0KIe+qUPpm3ouNzmXua46ceJEt2LeNOeOHz9eWrPtU089JUA5eb3+xhtvHDNmjLAZ0+xpgiZggc2/tsACC+iqlG+66aaS0OacRyKQCFQRGJoe9+jtRg0jxbnnnsuZ9+Uvf1mxrfW/9rWv8bc99NBDYhZffPELLrhgySWX/NnPfrb77rvzEBikjEErrbTSt7/9bU/w9957b5TdYLTKKqtccskluPuee+4Z8CHoyy+//HLLLRc84PbbbzceGdfEvPTSSxMmTMgRp9rOMpwI1CFgXkcFbGJ5e9ehb37961/XiVAEnvL3ve99lsSSWA9jBnqfOd4yu8W+qRuusMIKs802m2fuBoF///vfCy64ID6x2mqr6Z5yqTMmLxOBRKAgUNc3xSPfxx577BxzzMFvdcQRR/zjH//wCIvDC19fa621vvWtby288MJXXnml58+6nlnSvEnSOlnaE088kTd9zTXXNCd6NP2Xv/zFttJ9991XJO6uYy622GLmYpLmZf3dCGACnX/++XVe/L5YlYFEIBEIBIamx13Z+LyNHeg4h/oHPvCB448/Xoxndp7LGzLsckELzjvvPCOI2d2TO5R97NixnOgnnXSS4cPlVVdd9Za3vMWDvPnmmw+r2GabbT73uc/RHA/+jFkUOgxP/HnI/eqrr47Z4wTf+973rAfChkA5z4lAIlAQMFsLezC14YYbHnbYYR/60Ic8v7KcNklH3zz99NP54C+99FJdUkfThZFvTvRe9U1JdFUa1lhjDYxB10bZee7laMHAAALFpAwkAokABBr75mWXXSZeV0LNTzjhhLe+9a38XIi7nmXWs/dMt/U0GwvH13VkznLLY/PmPPPMg9xLq8eZHM2VuqFz9Dtn4ZhGzaHCSy+9NC/YG9/4Rv30da973a9+9SuMnwa3smoSgUSgisCQJe7GCOv19ddf32R/6KGH2jNjD4zRxzqeS2DllVc2HPCaowuW+B/72Mcs8eFiVJp33nmNRAaU559/nqMd+7dh3QglEuknE+MIgm64EcnlsMgii9iWJztDFZ2IgoeGIZaDTrW1ZTgRgIC+6ayLffzjH0cCtttuO5O05+OYgb654oorelbm0Tkx/U7k+9//ftO8ub9XfVNnxwAo0dkt4D0NW2aZZXRP+oOLZF0kAolAHQKNfdM+FrOYyc4TZtOl3sQ/JZW+yVm+ww47mCjNgLoVtq2fWnKbN/nmzZvmRJLmVusBmumxAeaQQw5ZdNFFTcqenokXqatSQmCLLbbYaKONOM5Muzq7LDwri4R1duZlIjCcERiaxD3osvHF26K2ynCfG0GMEQiBDTBYwsknn8yPzoeHxxtKPOMzdmgHxAw9zi49v7NH1isyGL9xxPttscedAEl3Pb63gZ7jwV1DDDEjkazDaTGcW1WWPRFoggAS4O4ZZ5zxhS98wSvd3HUucYLom3as6af4un5kE405nox1si7Wq775i1/8wrraCyq6JCrAdefBfXTtJrblrURgOCPQ2DeDyiPfHnyZDbnYPWHWNznF7G/hovLI2iJcQj2UsJnRZhiSuq2ODEwfdos97sK6sOU0Zq8n6piE9c3f//73+r6wuxbVAvbq5Ew6nNthlr05AkOTuMca3bCy1VZb/fjHPz7ooIOs47FqDF4khm2TDE7Pk2fUOOCAAzy1x9QNRmZ6aXEI07yBiQedR5DngC/Bg/szzzwz0DSm+EIFboF8fPKTn5SKJ89OXI/jPelD6O2xCRucm1dA3k0EhhsCOpoetPHGG+tZ++2339/+9jedETXnt9M37VvTp6yHeeJtq0UUdF7yYnrVN32qgh79Wiovw1ml8+Hp2rLQeYcb5lneRKAVBOr6pi3pu+yyix4U614OLwx+22239QrKj370I32T28stnZeMHoq+W2ybN3/6059acsdzbA+9bVGTe3BxLrMPf/jDJk0xCLo30Ajo415KocQXIT1b8+KZN1LICEglvhXjUyYRGCYI1J5eDe2iKqB1fDjU0WtP6Gxwj4FGwd3ykI5bTpjbIOg7z4EhwxBWkOEeiBEt9JR4yUPMgCWjYAk8iJwQRSYDiUAi0BMCelZM4bbK2Atb7ZuS6Er6lOm/dMkSKAqn2zdJhkxM/xx+6HtJnoFEIBHoFoHSN93lROcUj7e8QtgWU3OfvmkSJGkfaQkUbaHB5EiySr7LvBmS1UuzsAWAeOsBfT8Gh6IwA4lAIgCBIf7KduHiMRwYPgwERhODiMHCWUw8TBeO8QIoZS97GWti+Ig1gCRkhCM5bcYXh0g6HcHaqwsGkZGKTB6JQCIAga6+UltRm9ddClT7pv5S7UrRJYn11DerkEbX0z2DN7hV+q9bWLuzyOiVxEJejhF2S6CqMMOJwLBCoPRNAZ1Ip4seBIToOwKx+nWp40SvjICY0n0iVUyOdQAWsQiUy3DbuxSgUCCO0j2ZVGZbkXVq8zIRGA4IDH2Pe7UWDQHB4MvIUr07I2Gae9LZ5NaM5JhpE4GhhMDA9c1Aqadu2FP8UMI2y5IIzCACVtcYc/FtzYi2fulx/aJkRkqRaROBDiIwlIm7p+rHHHOMDz7q5L5WYWdeOACMQUh2LNbD2xereQOTmiDcuLgXz/HgY1h27/l6XYhR4rtyXrr3Lvyb3/xmkbbO+00Kn7Cwdc+Hb32j2pcohc8++2wfu5U2hxso5THMEdDRdDE/faDvhPNsk002WXfddcHiVl0HjK7avG9KqCNLSBt5YS+g29eu633lK1/xhlzkaCiwn95PNuIfXjT3i8jvfe97vY7izTkfh/XKnddg7ID3jL58vW6Y11QWf7gh0FPf1LlAEXd1MZfC0TfFx5QaHTBuRb8u6JVH3+5K5f0T/c5rJxKS1Ptcej2MvK3ttrwLkNQ99USfl/B6qy9Q5axa8MzAMEdgKD9pQty9226bLJZgi56vTBgL1LeRQkxUvLDDUOJSpCMuY3wRFm9wcfaWqo/P0ON9nUhrMDr88MNxd9+sxQluueUWI453a4477jgs/4orrsAAfNTW57HIxPv1kVEkz3MiMDwRiG7oM00+0qpH6CxHHXWUb1BAo7EDion4xluBHgIhoFea/qN/+bVUvc8WuDoHoS7s/XKReqt3XXRMPddPNPjFBn38wgsv1KMtvG11Y2EYGVnkOREYJghEs2/sm3qWo25yjL4JGfHRPYVDrMAVCv3EuC3ycVev/+EPf6j3RUK/nMojZsd8SaJHS2XqdLbA1m1zVi3gZCARgMBQ3uOu/3uxff/99/dNGPO0n0Q1pqDX4f/2JRnfgeF184uMO++8s0/E+Mllow+XGw+6r9Vi2z4HaaEf9N178d/4xjeMIL5XxUFIlc9NkvfVGj/Cyn3ozdcNNtjApzB85O7xxx/3/quPZhiefDArfsSRPeSz2SUCiQAEzMr6oO4p7NfNsG0BPc7Po3KK+yQc35uvWAjstNNOCLce19g3PUOjB+3Wlx3hwNOjfUbaQzafqrBgtjAg9tvf/lbfpy1k9tprL9+l9tkZXVVCYXd1eYttYZbIzjmPRGAYItBK3/TZVp9o8x1332ozpepius9nP/tZHcoPqPlhk+ibwcLxci+FU2t97mmYz6/FVKgz6tq2yxOGMwFueL/DSon1s19EMUHrxb5Ck7PqMGyHWeSeEBjKPNJYYArHCRDx+++/3xDjmfjvfve7HXfckUOOa82H5zw6xxg8sgeQJb7vshuGvv/97/PJGVkMK4YSU7ipnYChxE+7FfJtcMEPCPgdCp+m8UtM7nrL3mfdefXkzkMv7Aec0QU/NVcS9lQZGZ8IDB8ErGy5yd/znvf4KqsfPrNTxTPx//73vzqs3znWoSyJ9R1dVce0+vWBuca+CS5U+/Of/7wPR6LmurYnbHq0VTrH3t57740xBIHw6Wh72PjUJdFtsXMkQ/dcdtllfSbSUGAnm901Hs379UcZDZ+KyJImAnUItNg3dUy/EU5Y39RPdR+udKqQ9VBo6vTDZ1tuuaU+5Ys0flOcE22PPfbw8ym6LRmPxG2A8XlW/T2SmHMlt2I3JogxZeuYOasGOHlOBAKBoUzcDQFm6C9+8YsLLLCAHbR+2i2caqeddhpnubnZhG1QwKfjOzDW/ab2gw8+2KVNdbz1xprwBARYOLpAuOIob2xDcSvOm222Gce8ccqgY9iyxwaTkKQMao3JMyYRGD4IWAzb2BpPtLbffnuucQ/N9VAPvvRN/jmfdccJrIGdHSTr+mbshPFFi912223zzTf3AWmd3aUfWjryyCMtv/EDD+j1OL3VUy89kfe9IOzj8Xq0d1EMDj5HjbIjE1bjfmiGDcSyqxasMjCsEGi9b5or9SlfW//Od76je3qty2faq/Mmr/zXvva1N73pTZ5uYfB8WIStrnVevc+C2Sfhg6xDmCrPt931+ypB3GMydStn1WHVArOwzREYysTduGCqfve73821Zv+rLe9isIGPfOQjHr4vvfTSwjbJ2BVjk6shw9AQdLzqGhcZeuCITPDEx9xvfDFC2QlDgF/f+MVzwD0gF653LMSSYM011+TX59KTdu2117bNpnll5N1EYPggoFsh1qbt1VZbzTZWBde/dBPd05Nxq2gbz/w4i7X3RRdd5G70u2rfDKx0wFVXXVV3ttLW4xAC7IH/z11ZWHhLEk53MbotefvaLRIwA5vZLBUIyNfOHI/OcHf54g1Yu3gaIpc8JwLDB4FW+qYnY/qmN0N0E31Tf4nOVYcS15UdceZHXczuNZoJS2KKNG96EG39jL7H87RYipsoPQrz+Joqb6qYT3NWrUM1L4c5AkOcuCPWnOvmdZO6p3g8fFbzts3wqLnl0Z7H8Xbm4ffRDmyV4R7w2E4SL+h4dy3ogrv8BN/85jdt7IvN8R7NG7aMVjbz4QE8CjbnGYBsxVtmmWWMU0YoBEKA/8/Q8+9//5uDn56kAsO8y2XxAwG7Vix09aBdd93VIylMGu22wf2+++7zeEo3savN1yf0U50I2+6pbyIBlGD/PO7RW32ewk8ac/uZ7xF6j93xAxpcxkpb1vbR+uCMeF+SYY8e6pm+PbXEWMLBL8AG56yvRGC4IdBi3zRRWmBj297v8hPI++yzj8Ww2dDkWOZNnYg7zCfdMHj9VIdymIWt0sVIte+++9ryvuGGG+L9vgJHxgY5xJ0Y2G1p8wQsZ9Xh1gKzvM0RGMrE3UPz9ddfP4YAD9NdGmXwbC/A2Vlr9c8Z73fXPRb0dimfHAFPzDnODRPO4X0HX4wg6IWH6ZLYABOP9vCJPffc01utn/nMZ7gHMAC/Do0ouKwNTl2fy/CZSKsC+2vp58mjDc9oXiV5NxEY2gjoGgrI242p6w4LLbSQzoWym7x1opindVvM29rYkphPThJ7zxr7Jj1uUUKb6T8867qbbu6BmDdQxQRdIOkhGLefS55163M+P1l44OaWQcB6W6a4O6e7cSCMdCuPRGD4IBDNvsW+6WGyjmbRazI1OdqMaj+M/uUoiFGIkRPQeWPuE2NTu0szo4A5Wtd2Nv9i+dIaEGKfjHnWgjwej+esWiDNQCJQ8yolCoGAudxOWUOJy3S2ZatIBNqDQCt97atf/apXzJv0zRjHWmTbPeXYU3x7cMhcEoHBhkArPeLRRx/1vTXOcovknuxHx/XNxu4pXhaYfU8JMz4RSAQaEeixpzWKzowxHo5XBwVhw0S40q3+HTFwxIBiI42Hd+52jTC1z0sTjl13Ufa4JZVLYdqcaTBghQZhhzAZZ8lJCojM4WlmbD9p88AhoFPoYtE99Y5ab+zqj/pUhGUdHcelrWvN+2Z0wGJtUU6/sLsOuUSOFAqLJy8+LsOGiBcjvmjLQCIwrBAo3Uepo1/oESLr+qa74nnK/byg51TRlULMvFntQcSqANITdyNeEpcyEi+hgCPkI1+XApEkbglLJRwDSFV5hhOBIY/AMPK46+TR28sgoueXcLWmQzJiquGqjHC5VQJ1AnmZCCQCLSIQnajalarhoqQaWQ0XgQiUWyUgvoRLoC5VXiYCiUAjAtFfqr2mGq7KV+Or4apMt+E64XJZAt2myshEYHgiMJSJu+W710Pjy812tdp9HnXsi29+L8k7o7anl1r3Jrs9695hFYPf+yCdn4qw2Y5YkQnHQKz7I9InKbzH5r1VlzHEeO3GW242zorPQadAl4FEoCAQ/cLX1vWUeFoVH1MPAX3Tt5vi5ZCIaaVv0umorsOrfbNk7c1XW3JtghdD3ot0Lqt9vEhmIBEYhgjoFCa4VvpmSHo5RPf0OrjXUQIuX2fyQQgvq9jFHjEkHaVvCkcW3m31XopLYmJ8ZMbXnDxbi1R+bc07JzG3RkyeE4FEIBAYysQdh/7ABz4Qu2UMK145fcc73uFj6r7xbLYW48vQfpUNECi+j1t5De6QQw4xjvgVGJ+k9WPLHgL6SRffpKvzzcelL2F997vfNTz52ow32yT0uNBuP5+qeOc73+m9VckprxL9bHaJQCKgu3nA7adbvDzqi5C2r3h3zRsmFtInnniiD8LoSiZsP59kIW3h/aEPfWgG+2bkiMofcMABPizj+7DeZlEReisDXMox+2m2zESg9b7pBVZdxg+emEZ1K997gN6ll1561FFHYeReDdej9evGnhUxvifj91W8Ha6DW72j7AceeKA31D/1qU+ZtX1RygciKSGm7zcqyZpKBIYzAv9v59kQA8IYxBPgC+5+kdHXJPwsswIeccQR5mzkwOeifT2aa0Ekju4Ndyt+zniDET89f/lf//pXxMI0TyAmdZ+P9AG7ghIBn6PxXZo//OEPISMhRuJjdrwOfutRKhS/yGcgEUgECgK6xnvf+16dyGdkuOh0Gd3Q9x/9vKKfSPOZpl/84heE/QZq874ZCvVTHKJ0t7q+aeIndtZZZ+n13qJDC8TQfNlll/nUTDEpA4lAIgCB6fZNvzUec6Jvp6LXvOOBmy7mF8pNtb4SY67UyxzVvunSvHzCCSf4hZP4UruEVPkgrO8p86n5UrOVPHebLGydP/PMM8Oe0J/nRCARgMBQJu44tLHDL7odeuihnr/7zDNqzsHGuW6J7yMVyu9hvbOBxq8n8przArr0ow8+7o6FS+JDdcaaGKROOumkO++8k4DL2IHjA1g+NGuUEekI3kC5x4JB8SNh3M1zIpAIFAS8haaL+Z66HuonDqyxTf+WwbbNuOU3mCx9CaP1Tfpm0eZXF44//nhTvq7X2DejG0b3tAzQYXVPnAC98KxfBy96MpAIJALN+6YnYBbJ+pqO48fRfAJS7/PrKHDzHPvKK6/0yJobnrOMgP5Y+iYBPfHFF19E2bnPfMo9Ypx9CZ573s8bm3xtYPOgWyo/jMj77m7ZZiOcRyKQCAxl4h61a7b+29/+5hvqnuVx7BkXEGuLfneNMsG5PafD5m2r5VMX7yeWNtxww8MOO8wIZRgy1sTULsbXaoXFGLYoodyYErTApbv252y99dZ+QiLfds/elQg0QUA/0kc847LlzK4Yz809/uK9048ctplh2HqTrtSkbxb9nqdz1yEcYrrtm+JxBa4+T+fxBi55q24/yxDduejJQCKQCDTvm34AwRwKpXvuucdO0a222kpXDReYXyKX1naXPfbYQ9c2ObqMvhkbR6XyLhk6rqvGQpqAgMV2BGjWf4nZb2Ni1f2F3XLOIxFIBAKBoUzcTf9oOrZtD6ut7QpsEy2OztmGMbhrlb/YYouJsfnVA3SP+TB77MEtDgMbabbbbjsP7LAHaY0dhp6y9I/ByyXqHwMNncav/fff//vf/76338qolE0tEUgEGhHQcbyIhm17ZhXd064VPVE/cnDa+bk0D768I3700Uc36ZtBDpwLM2jsm3GLP89vIds1ixzwFPohNj+qevHFF3scVxbnjXZmTCIw3BBo3jd9uN1sqBPZ0W6rjFe8vPOtn4o0w3q+7UfKfbzVhjS4iaz2zUBSpElWvEsMXsDUKUbH54+3TxWP9zTMVlW75oYb+FneRGC6CAxl4q7wKLXtMX6YzdM3+2EMK6i8keXyyy8/6KCDfDSGM8DzOG4DQ4ZdNKi892POO+88bjkjUVB2k7qDttjjLhyDjrHmN7/5DXc+9i/mn//8p326lOMcBrL4iE0knG41pEAiMNwQ0DU41ZTavnNb231JxpZWne7nP/+5refHHXeczWz6kVkcRWjSN5EASmIfrbAjeEC1b3pfXLw3W7zxYic9ebTAA7fcJzPcWl2WtxUEmvdNvDw2mmLtXh83yfo4jG1vOLdVMReYGdB3Gkyp8qKqusc9co9p0aTp0pYYc66X0S2hvdais1uxWwx4c8xjsbIPvhWzUyYRGCYIDGXibnQwBPB8m/s9bT/nnHNsqjOyINzGBaTcq6Wq+ZJLLvG7zV5p92r8tttua2+MrTK4OElJ/Nw6JcRoK3vckQAxHgsiBEar7bffnrYf//jHXIZWApYEdujGd2bCqUA4j0QgEagiYF7Xs3SlNdZYw/ZWrDo6nfdM7Hr3AahNN930/PPPt4O2ed80/eubZR9tcIK6vuljNRYJ9r95R8XWdl98slr49re/7UU6u+r1WWZEwqqFGU4EhicCzfumd05sB/U0zGaYww8/3Hzn62q4u1W36dJDs6985SsmPhtNo1uVvlkFk6M9mL3t8qeccooN8dxqp59+urnYE7P3v//9v//972VBoVTZN6vQZTgRGMqfgzRqeOJmgIhu7/Gf1Xww6YiP6sfmjRSEXbrLCYfoC3MkkK82ERSBQHUQKfO9gLshb6kQuVTTZjgRSASqCOgveoruGZ2Ii86GluhcbsWkblVsmd1K3yRDW6SKXEKtcNyiudorZeGWJO6WIaJqXoYTgWGLQJO+WaZFcyix2OKiZwk7zKRAq06vLhv7pkh6nM2Y+qAjp05o5JEItIjAUCbu3UJQpnN3jRfVubzIkxEODlGVLwIRKLdKQHyEqzF1qfIyEUgEekKgdEk9iEx1kRxJqvFNelm5VQKSl3AJ9GRGxicCiUAdAtPtm+SLjHCvelkRjkDdZZ0leZkIDHMEhh1xH+b1ncVPBBKBRCARSAQSgUQgEZhJERjKe9xn0ipJsxOBRCARSAQSgUQgEUgEEoFGBJK4N2KSMYlAIpAIJAKJQCKQCCQCicCgQyCJ+6Crkl4ZZC+gt2l7lSSF24BAfmewDSAP/iy8EG/X7+C3c1hZqFK8RjmsipyFbUTAG7SOxviM6SACyWdaBD+Je4tADVIxDT2ZwSCsG5WiagahYWlSOxHIZtBOtFvMS8fMvtkiVkNYLJvBIKxclZJ8ppV6SeLeCkopkwgkAolAIpAIJAKJQCKQCHQYgSTuHa6AzD4RSAQSgUQgEUgEEoFEIBFoBYEk7q2glDKJQCKQCCQCiUAikAgkAolAhxFI4t7hCsjsE4FEIBFIBBKBRCARSAQSgVYQSOLeCkopkwgkAolAIpAIJAKJQCKQCHQYgSTuHa6AzD4RSAQSgUQgEUgEEoFEIBFoBYExrQjNRDLD7RtP8b25/ILSYGuiw/CzViO7jiYVMdz6JiiiGQCmCSx5q80IRKUMtzFz1KjpOOmGGyCagYY33Erd5r7W2+xUR3TP3iacqeWnO3U2lm6oEffh9uMaWvkrr7xiUI5hqLGCM6b9COiHKkW+w4qxaYQTJkxogvbkyZOH2y+exHA0Xc7UBLS81b8I6JIqRY1ojf2reTBrU+rx48c3aYd+kSqGrMFcin60DSAxFgVT7EfNqWpGEBiefGbcuHFjxvSOio9Mwjcj7azjaVWfH+mcZZZZOm5JGlBF4KWXXsJihxVxrxY/w4EAMjR27NgmhCmBaj8CiPvorqP9WWeOgweBIO665+AxKS1JPtNiG5jO47MWtaRYpxDQ0B2dyj3z7QmBrJeekBlW8dkMBmF1Z6UMwkppv0nZDNqPeeQI+RKohkW69PCn3I1AnhsRSOLeiMlgjyltvSdDpyvQU8KMTwQSgRlEoHnva353BrPO5IlAItAEgea9r/ndJmrzVq8QiAfR0BZwPPjgg/atCYQS2wc8E3vsscciRrj6HoLLXuU1VIWTuM8ENVsdUKK5M7oaWVp2BEofmAnKliYmAjM5AqUnlt5XYpQs++ZMXr1p/kyMQOmJ2TcHQy1GLfz73//+wQ9+gKzbSfjDH/7wgAMOOPjgg59++umoLHf33Xffb3zjG9dccw2bt9lmm89+9rNh/LnnnutSmGQID4ZCdcSGJO4dgb13mQYRj5YqXLdCFW8T7bPPPvvMM88I6BvV14xcDrc3AnsHbkonAjOAgN6nS0bf1Ps4hB566KGychZvE232zRkAOJMmAn1EoHnfpNRrSNk3+whu75NFdTz55JNYO4e6gRFH/89//vOTn/xk1lln/eMf/2jYNISecsopq622GkIvHrmXCp8Jxn/OOefE63xlgO29FUMkRRL3QV2R012hEtAB7rrrrv3222/vvfe+//77UYfFF1/8kksuiYLttddehx9+uHDZOjaoC5zGJQIzDwJ6nynkjDPO+POf/8zqe++998ADD/z6179+6qmnmm/c9a2A22+/ff/998++OfPUalo6FBBo3jd1TxzxX//6V/bNdla20fLxxx/ffvvt3/jGNyLlyyyzzLe//W01Nddccz3//PMsEZ5tttkQd2EOR8JLLLHEsssue/PNN4tBbFyqu3baPDjzSuI+OOulZpUGqqE3X6Fq/b4ldPTRR3/rW9865JBDBHgRcPfnnnuOBk3/sssuW2CBBYRzkVrDNI9EoJ8QiPnjuuuuO/nkkyPMIWTKOemkkxD3hx9+GDOwqD7qqKP0Tc+Cs2/2E/CpJhGYDgLT7ZtmQ4tqXRJxzL45HTT76TbM1QsWvsgii/gUnsv4uBPKfsUVV2y55ZbuGjMdf/rTn7gg77jjDkxm9tlnF2845Z2ce+6555tvPpynnyyaidWMmYltHwama9yxQuUb6HaFirXbObPKKqtcfvnl8Pjud7+rxW+00UZPPPGE/iDJ6quvbgk7DKDKIiYCbUVA3zSvoOa77bYbR5G8d91117BAZGxXM9+85S1vsXgWn32zrdWTmQ1jBJr3TawRNo888kj0Tbww+2bbGgu0+RNVkIBDXey5556bbbYZV7pNAWI+/elPH3PMMT/72c84QeaYYw4uyI033hibv/vuu+N75zHYts3gwZlRetwHZ73UrIrG3WSFSkaD1vT/+te/ekx/1VVXeWqvcS+44IL33XffCy+8gDG89a1vRS8GbyHTskRgpkVAX1t55ZX5jYoTiBvv/PPPX2ihhRZddFHFQt/1TZ0x+2b7K7k6wVfDLMEPVFlEOpfqc0vY3fZbmzn2LwJN+uZiiy0mL9NizJtXXnllzpv9C34TbVhNzane9Tu+wva7b7DBBvHKqYHU+Hn22Wd/8IMftPXXb6HY0Y7e4DB///vf7YZff/31X3zxRWJN9A+TW0ncB3tFm0WqK1StuaxQY+7RBzw/+sQnPrHHHnt47Vp5DEmc7t788Ka2pp/z0GCv47Rv5kRAz4rDDKQEZp1bbrnl2GOP1Rk53TFC8fPOO+/HP/7x7Jvtr+EgB5FvNazK1I7KEinsLFzME47aLDEZmBkReLVndm03ZX+3fdO8qW9+6UtfynmznVXMs247gBqxQyY+L2PM5N2wd+Cf//yn/mh74WGHHYbQ2/f73//+V2/1u7/WVwsvvLANCO00ddDmlcR90FbNq4aZRTRlh2vh6gpV0xc///zzxz6wkHE2Ztkho+mvuuqqxqZ8LXWw13HaN9MioEs6wnyfStA9zTpLLbUU1q4n2s1po1qwQzLZN9tQz9CWC+fFRRddFK70athdvtibbrrpU5/61HnnnafuLrzwws985jNhmLvf/OY3uTxchp42GJxZDBACXV2zx76JBfqYiaxz3hwg/BvVxlDppbutttrKXY8+Dj30UH7JcKKrCMPme97znve///3eXv3IRz5CxnchEffPfe5zXvrXJXffffcQLqNuYy7DIeZ/nobhUNqZtIx1K1RfrrBC3WKLLSxDLVI9SFp++eW9YUNsk0020fStSk1O99xzj53ueEO8qDqTlj3NTgQGOQL2w3gOxkhvh+t0tsq4NMFcffXVb3jDG7x/kn2znTVodjcG+pSWTcxvf/vbjYol7Jb5XrxNtJ6K+ALdCius4D0E356zyxmNu/HGG0888cQPf/jD7TQ48xo4BLrtm15K+cc//uETJfa56ZtWdzlv1lWBPmTlWhfZX5ezzDJhySWXnDZ1iv2E2267bVWt1ZTvWq+99toiCTivueaagqjOPPPMI2bFFVf046qs6/+jts6baRzZSdz7vwH0o8ZYVtatUD1mKtu8BIxNH/vYx3yQzoLVatXWdmtTNvz+97+32d2oxO3nMlT1o22pCgLhWA0oqmExWALwVYrDLYcnJCEpXsVljQQaM+85atDTLZWrFNttt92tt95qF2ZUtCq2QdMbq9k321bFKkJ38/E4nMCwqYJ8jlPYWwduxbDJr2EPIX+HFw9uu+02L8DZUyvgZTjxb37zm/Nt/rbV18Bl1Lxvuus5jH0y2Te7rYIahX31WUW39/shcuSo7reqzzLbXKG9IvCqKRHjazQDbVs/FG+AVbz60yEDnEuqH0AEMHUb2U1X8oh5awAzS9WtIaBSyvQffr7W0qXUkEKAu9fh8ZdSZd9sT9XGgtmv0Z1++um77LKLTCNsBYW4u6tv8rPi67bPelL/61//+s477+Tj8AONf/vb3/xeo1fluhx7Nfd8e2zOXNqPgJZgXR0/6JN9s+Afs9WTj9zx4rOPjho9duD87iXHamDqtGkWVBPGj69GDnh45MipUybNOucC8yy4bBR/wHOc4QzS4z7DEL6mQJW/Fuz/vzGyyAIPCO3hPYpLEwwnrviYmUQKSBITj1RB6/vdrGE7sUX3NsR4vWadddaxCU/YFznXW2893lZ3zQeexnrs7lHgO97xDvtoPQCxwUkVuGuz00477VR7XPjau1P9XjWpsIrA1KkD2Te7Ov6okSOn6HJdrnd0z/cRhCdOfGXc2HETJ9X65pjRo6dMtYtjyuhRAhzDI0dMq/03agCezyote4Yt7dQfsfNoANVwxHhiaS+TnRL2GfqZW0Ol33/hlfd6nJ1O/PT6crXxZHhAETAGmtY8Eh6IXKimVk/Q78ogYIjWNydPmqSPTJpUq+vadDml9pWhUbV5c0p0SWm9XjYAVlkQDt7HrTbJMO+Wq357z41nj5/1dbFfZQBA6F5lrS1MMzZ274zvPs0Mx3Lkv/Li00utstl6W+0fxZ9hlQOuIIl7v0E8oPOkkYWhsqij4C4NN+LLNgxi5Ul9v5UtFf1/BGqjy9SpRxxxBKcdXm6lJGzvrDBB1cGH5xebfUvEz/GstNJKuY/2/+PX7qsaSx6wozxU7ppv/jflIOhjR48bMfL/jbGjR9Uu2zwzDVjRB6PiGIcNmMbGxrCYG264wU822uP+m9/8xnsIts/aSGNzrS3v3pk766yzymA7GIs35GxSI6avgS5WXY9zOWbM2LpMgy7WSdbJDPlLlaGM4ybMPsts846fdc72E3cTa3TAtkGNuI8aOVqR5RjFb1vWfc5owDtMny3rW0KOZ6Sqb2lnJJVMcThtbkaU9C2tl7J5lfqWtm+pNG5U1VaQ+GTNzNLW+1bYxlRqOT5M4fG6N2Y0OR8BFIaG9w1i1cTj/vnPf3655ZbD2v0klkjP32299aqNLbZeWKSBHmmHDHoKUl09NuKmzbS/g7Bq8pSpZ157v3P7oVa/6KOjEY2BizHzvjxxyjtWWOgNC8w+cdKU9pd64IrWimZDsfHQLgiedb5zbbKEVQRPPJ+6n2b0wxd+1c5nc22CRxR8eM7ngHwZ0DZ38jKSdshApyDK2KQ4QNNWW4G3H2V4P8aMHf/EQ7fc/o/fjx0/e5s5ouFIWdrPESe98vybVv/gvIusMHnSK4PwbUi1MHb8BI8jpkzxb3KbK0U77Joj2krh7BdXWEWW6yS9vr3+fkU2RvV2jhhqxL3N/bCMYlqbEd9Y0GRwLML9GIiG3uZSK2N8Wl5rE3b0Y4lmFlW+R+GtX/toVYGv+oTHTg+MukDifevq5z//+aWXXmpXjI2znHz20nglDi3wOqNXGKFHfvigB5neDk/90himTht5w31PvDJxyoD63bs11bDQ1T/a2kEU89kXJ6261HwjTEFjRuqi3do2VCP1R5i/7nWv00Pj7YII86zrdF5GtHvtAx/4gO1qviWy4YYbWmwTs5bea6+9pPUJXcweOEOsbzYfZ9xV3jY3CaTQk7CXX3jinpvO5t/lx2inAbFzps1jgiH/pReeWGL5jRTcVNFmjtgKvLURq2s98+rA1fbR49V8W7G1n2QiR9NTreA1Dv2/p6b9lMN01DBgOhINt9vdVxsM6OeIPkDQLxbINwb6NhtgpkEO2k/cgVYmtjYXuV/qawaVgJ1Xz07ZKHuE6XQZMcFQ7Z31e2/XXnutN+HmnHNO22rto/WVaI/mrXyq8jNoz8ySPMBps7UynW382JpPo/fj4wya2inibku/AseD345gPoO4zUjyKK+V87ve9a7QU8IeEu64446Y+ju7jrjr59Yj4FvRAltuuWVcdmSRGVl35NyBdtLVH8eMGTd+1rnHzzqXzeXtLLi+Kbs21zJS6D0XRZY1wDuA+fQgHoQmTc/k/rzfVSe9ptH9aUFruoYacW+t1AMihcw5BkR1z0oj007l27Ndw+KOTl7G/WpY4R999FGPnt/3vvf5iL5fg0PcueRtp6nbRzssYBoEhfSxAv/ab4hMTQLtngem+YJN+4eEXqPbNXYNFDpqW53X3jL0DnCEbViaNqK2W8vnRF6ZaBWn8zoQKaaTnOK94dpLilNrDykGYo03DVebaTbR9ro6+5qg1gym+jJ37V9fdfQlHY+XZLX3w9t4yKxW0k6MRW0sZWY14Ai0dfPlgJcmM0gE2ogADhC/vCPPEhawaerJJ5/89re/zb9uH62n8E899RQej77bR7v00ktj87HDso3GZlaJwOBCoGutWyPJA/HP62a2InjIQvmr4RpTHzl2zOhZxo+ZMN7umLH2tYkhFpKuCdc2u6HzA2EVpQOxHhhctZrWJAKJwIAjkB73AYc4MxiqCHjy7vVTs7wCRpjHzttvZ555ph9f3HnnnQ866KCtt97ajnYOeFtsfRw69tGi8t5qHaqwZLkSgeYIcDhisA888cJTL7yCLLfV51l7/2ySz0i0e3vhiBGTp06be7bxi847WxS/OUR5NxFIBBKBnhBI4t4TMhmfCPSIQHjO7J3deOONQ6iEYx+t1+DW7zrirl+0jUDdPtr0wPUIcd4YugjYKqDln3/Tg1fd+cjsE8bZOtDOstojUet37XV++6TL8y9PXGuZBXfaYKb5kZd2VkrmlQgkAq0jkMS9daxScqZEYEA3FNoYEx530JSwgEztjXF21yGGgIAdMrV9tAP5sZFcDMyUzXT4GT3LuDFzzjpu1vFj9ZZ2ln5Ae19PBantvRk1QpF7Esj4RCARSARaRCDHkRaBSrGZFYEBJbLVB+4lLOCTO44CWbkVkeWyCGQgERhuCODrXT8l2+73hi2r2+5wr72DWytse5cow61FZXkTgWGCwP+4xTApcBZzWCFgy4ofUuHqHlC/eyOk8XHoAV0zNGYqRo5egW1/vt0ak5GJQCKQCCQCiUAi0L8IJHHvXzxT22BBAFPHX70V6pdK+bnbTNw78jheGfnyV1555STug6UVph2JQCKQCCQCiUC/IpDEvV/hTGWDDAFE1q8jtZ+428vOzd9mAh3EfZDVQJqTCCQCiUAikAgkAv2GQBL3foMyFQ1CBHDZcrTTvMi0nTnKqyOZtrmMmV0ikAgkAolAIjCcEcgfYBrOtZ9lTwQSgUQgEUgEEoFEIBGYaRBI4j7TVFUamggkAolAIpAIJAKJQCIwnBFI4j6caz/LnggkAolAIpAIJAKJQCIw0yCQxH2mqao0NBFIBBKBRCARSAQSgURgOCMw1F5OjZ+obH+NytergfKNczsN6MgriZGpc3z3sJ3lbTEvtsXn24upLSbsFzGZ0hPnflHYohI5dqoLsBDgTeyMimgiMEC3om/Wch+gDHpW24k8tbpay+tqBl1nvzY0yA6D5Wt9s9ZH2oxSm7ML7LvqJAaEqJp2V8og7JuAGDWq9jPSr71X39YOGs2gzY2hK7taA1BU55F+l2uQHaxSKWGnc1egrSZ2INMYMbvmh67W2NZKUV59s7cfoBtqxN3vzHdB39amJjOZdqDBdZWyI/nK1BcPoe3obZtrT92w0FcgGRn4OLcn38glMm1njiXf+MGp9mdt9Bk3blyTfKPBNBEYiFtGxImTp/jJyiBNA5FFE51tbnVhiZYuXx1zxNTJEydOhkATCztyy2A5ZvTYDvbN9pe6i7jXxswR06ZMnDjJTN1mG/TNJtxdgzFutNmkaVOnjBs9VkOVe0yf7TQg+mac25ZvFFORDUgAHzlqdNuybjEjlTJqTMf6JiPVSJsrJbLUN60gJ7W9UhRW3+ztj6kPNeLenDq02Hb7INa1Tq39PGebWawcDcdNRuQ+lGW6SZRRjmhxfCK9zUWernkhEHXByC542v3LqZF7m5GJxjBhwoQ2t4cWa0RdOFoU7kexkaOnjho9aiQvbycorDbQ5mZQc9/EImrU2AkTxnSk1M2rr+ZwHDlSY2Bqra22d1HNtg5USq1OakUeMXLMhAmj20/cm9eIWjBuNJfp97s4oh5pyoYNRKaOaKtvJYrT5qFSdgpbI2ojRwB8EBL3qYj7iBEaaq3B+sXx9lZKZ/hMV6XUhqMRI8bXZs9Bt5pq7HrNHm03SmdMIpAIJAKJQCKQCCQCiUAikAh0BIEk7h2BPTNNBBKBRCARSAQSgUQgEUgEeodAEvfe4ZXSiUAikAgkAolAIpAIJAKJQEcQSOLeEdgz00QgEUgEEoFEIBFIBBKBRKB3CCRx7x1eKZ0IJAKJQCKQCCQCiUAikAh0BIEk7h2BPTNNBBKBRCARSAQSgUQgEUgEeodAEvfe4ZXSiUAikAgkAolAIpAIJAKJQEcQSOLeEdgz00QgEUgEEoFEIBFIBBKBRKB3CCRx7x1eKZ0IJAKJQCKQCCQCiUAikAh0BIEk7h2BPTNNBBKBRCARSAQSgUQgEUgEeodAEvfe4ZXSiUAikAgkAolAIpAIJAKJQEcQSOLeEdgz00QgEUgEEoFEIBFIBBKBRKB3CCRx7x1eKZ0IJAKJQCKQCCQCiUAikAh0BIEk7h2BPTNNBBKBRCARSAQSgUQgEUgEeodAEvfe4dWT9MiRI3u6NbTjB23BB61hA90ehm3BewJ2eAISpR6cZR+cVvXUfvo9fpgXv+A5mJtoMXIgAoO54MO8cc4sxR8zEO2ygzqnTp06bdq09htQ8m1/7nLsSKaKHMfgbOswGTVqFAu74Gk3RFEjcW5na5Tj5MmTFbydmUZemkHzfKMu2m/Y5MldY0L7K2PEiE7kKdNaxlOmTBkxberkKVNHDT6fgk45dmz0zRpEbUapzdlFg++qkxG6wIgRUzXIUaPa7egZPXp0k64Hky7bmoj0/61pU6eMHjuu1lBfbQVtnbijGbS5MXRlV+ubijpl8uSRo5pVSv8j3oLGqVOnjBk7rqsxMLZ2tJCoP0U6kGnXiFmbnkaM6Jo921opyqtv9pZEdWCC789KTl2JQCKQCCQCiUAikAgkAonA8EBgqHncm/v8Bq5O5Rtrpt6unGbQJMs1ObY508hRkeOYwSIMaHIWhrUDmkuj8qiRNtdLNIYxY8a0Od/G4ncboy66jR/oyGkjuvpmVzsY6Lzq9HflWTvVxQ/oZS27kSNrHtaRo8aMabtrt4WyRUPo6pssbS86I7pyrOXa7kqRYVcX6KqUtmY+/SqBRnOX/PRV9EGiq2125dtVH22vESa3vxnIs+ZhHTHCQK2H9gG2AU1SmzBHREOtVQqABjS7OuWd4jMqpTYcdVWKJ8d1Vg3Cy5nAxEGIWqNJGlxj5HCIGbQFH7SGDXSrGLYF7wnY4QlIlHpwln1wWtVT++n3+GFe/ILnYG6ixciBCAzmgg/zxjmzFD+J+0B0zNSZCCQCiUAikAgkAolAIpAI9DMCSdz7GdBUlwgkAolAIpAIJAKJQCKQCAwEAkncBwLV1JkIJAKJQCKQCCQCiUAikAj0MwJJ3PsZ0FSXCCQCiUAikAgkAolAIpAIDAQCSdwHAtXUmQgkAolAIpAIJAKJQCKQCPQzAknc+xnQVJcIJAKJQCKQCCQCiUAikAgMBAJJ3AcC1dSZCCQCiUAikAgkAolAIpAI9DMCSdz7GdBUlwgkAolAIpAIJAKJQCKQCAwEAkncBwLV1JkIJAKJQCKQCCQCiUAikAj0MwJJ3PsZ0FSXCCQCiUAikAgkAolAIpAIDAQCSdwHAtXUmQgkAolAIpAIJAKJQCKQCPQzAknc+xnQVJcIJAKJQCKQCCQCiUAikAgMBAJJ3AcC1dSZCCQCiUAikAgkAolAIpAI9DMCY/pZX6fVTes62m/F1KlT5SzfOLfZgPZn2gVz7aTgI0eObHN5W8mObaNGjSp2CrSSqn9l2p+pHNVI/5aiRW2aQfOWEHXRorZ+FHu1b7a/Ml4rQ5tzjpYeaNcaw+DrngbLkSOjb9YGTMdrULXvb5szVUKl7Cpr9NB2j5kGw+bgtn/cAMSokaOjIgKZ5hYOxN12N4Oupt5V2BEAHzmi3c1guhjWrHq1UqJOhn7frPXM18ahrl7Q7kqZ7tTZWGtDjbhPnDhxypQpjeUc6BhtXL5djb6ttS7frqY20OX7f/q1M5lOmjTplVdeUermdO3/pWzjBWRGjx7NSKY6XLYx8xFgkWObkZGjQ6W0Od8AFjOYMGFCE5AnT56sOpoIDMQtUEycPGVq7T8soa19U3E0PAY4BqJoPeqcNlLzq/XNSa+8PGlK+0vdo2Gv3dAbZxk7WnuY2lUtLl+7046/namU2pg5pVbkTlSKFjh+/Pgm3D0aTDvQr+QxbeqUseNHvzKxNononmayys0BD2oG8miCyUBYMG1EV9+c+MqkroYwctTogchlRnTWKmXCmMmTJnfRmXZXivkr6mVGitDbtJZPCqvIk6ZMm/Tyy+2vlHHjxo0Z0zsq3jvp3iLSfnnDU/szlaMGB3rjT5snafnKEUNtZ6nlKF9QNydq7TSpp7wYCRwHg3uSGaB4U0L7G4OSzjrrrG3Ot0UAx3YdLQr3o9jYKdNGj9ECRrSfwqqIOPqxONNVpd2NHj11lllmGTNuwmzjBp9Pr8v3bC1juurqmqONJtMtVD8KvFYnbV1NaXsqpVZklTJ20D0FiXGjH0FuSdU0j4NGzTJhFrnroPzP7Tw0A9m1mbiPGlVr8oo8buyocWNmU/x2FrmVvDBnyIwb/2rfnNbeSukMn+mqFEUeN2bk2Nlm8zCwFaA6KzMTmNhZgFrMvf28sEXDBk4sijxoCz7IzRvoehk4/TOd5kHbRAcUycHc/gezbcO2Uga04N0qz2bQLSydjcxK6Sz+LeaexL1FoFIsEUgEEoFEIBFIBBKBRCAR6CQCSdw7iX7mnQgkAolAIpAIJAKJQCKQCLSIQBL3FoFKsUQgEUgEEoFEIBFIBBKBRKCTCCRx7yT6mXcikAgkAolAIpAIJAKJQCLQIgJJ3FsEKsUSgUQgEUgEEoFEIBFIBBKBTiKQxL2T6GfeiUAikAgkAolAIpAIJAKJQIsIJHFvEagUSwQSgUQgEUgEEoFEIBFIBDqJQBL3TqKfeScCiUAikAgkAolAIpAIJAItIpDEvUWgUiwRSAQSgUQgEUgEEoFEIBHoJAJJ3DuJfuadCCQCiUAikAgkAolAIpAItIhAEvcWgUqxRCARSAQSgUQgEUgEEoFEoJMIJHHvJPqZdyKQCCQCiUAikAgkAolAItAiAkncWwQqxRKBRCARSAQSgUQgEUgEEoFOIpDEvZPoZ96JQCKQCCQCiUAikAgkAolAiwiMaVFuZhGbNm1aR0ztVL4dKWzJVKkHbcEHrWEFvQEKdNVJZ3rByJEjmxeqI5XSkUyb49CGu12l7moLbcisl1l02TadptJLlTOTeEdqZRD2TThoBF2NYWaqvhm3NYpcO3eIrjQpwjCsjioait9+BKbbN6sWRnioEfcpU6a0H3dQTp06tavG202YItP2F1mOoFZq5z40u8aG2O8xLBw9enS0h0Cp37NoorD9OTImMp08efKoUR14kqYZjBnTbDyJBtMEtIG4xarJxoTonQORQVOdaqTp/QG52cUHat1zxLSpkydPGTW91dSAGNFUqcFy9KhO9s2m1g3ITe1AY+iqlCm1ShnV1nWLXmAwbDJQs824MSAl71nptKlTxowaE0N0+zto9M0299AoZm0knDYC4CNHdWB86LlCandUyqjRr1YKcNqMT+TY5kxj4qy1wxEjdM6p7a0UhTVv9nbKbjbRNq/gwXm3OXUYOJuhb1iMY+By6VZz+zONHM0EcXRr1SCJZGH78VH2yNS5zTjIcdy4ce3Pt5Vidq61jB6JvXYdrdjZjzKv5treZhCZ1kbCkaPHjRvd7ibYAny15czIEaVvttnCDlaKIr9aKW0u8/QqBSZjx46dnlR/358GjREaqtx10Klt7ybKI+v+LlUzfTEO1YjayBEG6hEjO+BhaWYfF+S02ohR+iaAmsv3+93onv2utonCyLFW5BEjxowbN2rwVUqj8YOu3TSaOFPEtHuNOGhAGbQFH7SGDXTVDduC9wSsB9I93Rry8YOzMQxOq9rWGIZ58QvOwxyHQVr8TjwkLE2i84GZpPhJ3DvfVNKCRCARSAQSgUQgEUgEEoFEYLoIJHGfLkQpkAgkAolAIpAIJAKJQCKQCHQegSTuna+DtCARSAQSgUQgEUgEEoFEIBGYLgJJ3KcLUQokAolAIpAIJAKJQCKQCCQCnUcgiXvn6yAtSAQSgUQgEUgEEoFEIBFIBKaLQBL36UKUAolAIpAIJAKJQCKQCCQCiUDnEUji3vk6SAsSgUQgEUgEEoFEIBFIBBKB6SKQxH26EKVAIpAIJAKJQCKQCCQCiUAi0HkEkrh3vg7SgkQgEUgEEoFEIBFIBBKBRGC6CCRxny5EKZAIJAKJQCKQCCQCiUAikAh0HoEk7p2vg7QgEUgEEoFEIBFIBBKBRCARmC4CSdynC1EKJAKJQCKQCCQCiUAikAgkAp1HYEznTRgqFox87WhzgSLbdmba/hxnpHQdsfa1tjByRizvQ1r59iHVkE8yauTI+Nfukr7WDtqZb62k/m9nln3Ki4nDq1JqjaFPSA3xRNrr6Nq/9hZz5IhahrpKO7ONksq2nZn2Ia/aeNlVKX1IO0NJpk1TL7KeISW9TBwllWsv03VSPIl7/6BvSJ4yZcrkyZPbPDZPe+3on2K0pkUZlVTOxNtc3tYMrEmFYYxkqsuwtvXkMyg5tetoMziDvEZmENI+J1cLL7wy+eVJU9rPZqdNnVprA+3la6NHjXz+pUlTar1zkHbP6BevTJr6/MuT2DilayTpc/32NmFnKmXkSIVV5EFbKb2FccbloxlMmzrplRefGm0CnTplxnW2rkEzINxm4j561GiFVeRa1u0dFlpEJqyaPPFFdtamzTZXijls2tRRbSfur7z4tCIP2kpprLuRbSY0jRb0b8wrr7yCQPevzha1Pffcc+0HU46TJk0aP358m7OW3bhx42aZZZYWwemU2EsvvTRx4sQ2D5Gy0w7Hjh3b5nyBLMc55pijI2iPGjVqwoQJTbLWUB1NBAboFlp4+8NPT51a8+UMUBY9qVXe0WMQ6fb6ckaOmDxl6hvmn2OOWcb2ZNhgiH/giReefuGV0aNHjehaY7TJJOBMmsyfiEK1KcfIZuSIKVOmvm628YvOO1tb8+3KzLBgjtBDe8rapGnI6unugMWr+JEvv/Dk4w/dMnr0uGltbAcGgnDojBkzpr2tj4Nv4nyLrDBhtnnQYsUfMGz7rLhm1VOP3PnCs4+OHj22nZXC4lf5zDiNoX2HeWHKlEmzzbnA3Asu05FKQaW0w14VeKgRdxXv6BUE/SXcZFjsryy61YObdopAcyt3a9LgicxKaVtdIAeOJtl1qm92ubx7pCxNDJ7xW9MmTxw5BntuBsuM59KThkHePTvVN0dMmTRiNNbemSbRqUqZLtqdMEy/mDZdw3pq3jMYH1NXZxrBiBFdaNeKP4OlGIDknawUxZk4ecS43pHYfsOgU5Uy3amzsYQdQqjRkH6K6QME/ZRzZ9Roap1aqChwp8bczmDdm1xViqrpCD4dybQVbDrYN6d2aH58edLUsSOmjq7RxHYfo+wg79nD2m5rusuPg6Uj1WK/yuipI8eM6QBnw4kGbaV0yDCQ8LN6SF4LtPOYNHGi7Dg725lpV17TRnre82rfbHepWyvsyK6tpZY27TbPpDnplZfHjp61NTv7UcrzWHUSY0K7S92HYgw14t4HCDJJIpAIDG0EsNiOHDX23PWvI7kP8kxrT0I6YWJWSidQb5YnItvs9sDci5cRZ65XEgcGie601h6edqRS7PasvbLenU0Z9z8EEqD/YZGhRCARSAQSgUQgEUgEEoFEYNAikMR90FZNq4bV1sZ5DDIEslIGWYWkOYlAIpAIJAKDHYGcOlupoaH2cmorZR5iMp3aSz3EYOzf4mSl9C+eM6k2zcA8lFPRoKq+eCkoK2VQVUr7jclm0H7MW8kxp85WUEri3gpK7ZMxmtTNKI0x7bNmuObUiHljzHDFZviWu7ENNMYMX3Sy5IlAIpAIJAJtQSC3yrQF5tYyCR7g7PBhXWfp8PiuiFqMxaiYOIfKIikgvtwq4cb4oqc1o4adFMSqmLsEQTUmQC5Qu1tFu1RcXWTI01YEqlVTF19khh36g7XAKqjaBlx22yqiTqMQpU4jsjSYEk+seivC5afNBisSHbYLSlV4izWBXnScCMetum4YyesiS9UIlK5XFw4ZyYtAyToDHUcgqpUZUUHFHpelHiMct0LMuSRprN+QL/EC2TcLsN0GAs8CaZEJJBv7JgGouuso3UqMI9IKVON7Chf5qp6S+5AMJHEfLNWqzWEGt9xyi9Yp4BNyzoyrxvhc0csvv3zFFVf4UaGwu0gK1L5m9NoH4Eq4Gi8L8Xfcccd1110neWnugwWCQWBH32qhinapuLpIl8pX6ivCdTLu1skMAkjShBobUDXVnhg1VY2J+n3wwQdvuOEGkEWSaAyES0W75bI0kuqtCP/9739/8sknE/SeEECewF5gFPArV2ICvQC2WgsF+SrsdZFRd1QJlKqpC4dMVUlPFmZ8+xHobauo1mOEG+tXvMgSL5B9s3nN9rYWaIMqnB3VfheYx91qfE/hIl/V09zUmf1uEvdBUYOmeXY8+uijxx57LFYt8MMf/vCmm2566qmnfvCDH1x77bV333334YcffuGFF2qjukcx+vrrrz/qqKP+85//PPTQQ7/97W//8Ic/4P0EfvOb35x22mnC999//6mnnvrrX//aD+O9+OKL4imJ7IqSDAQCfa6Fiy+++IwzzpD88ssv/9GPfvT4449TCPZf/OIXL7zwgjo66aST3BKppgiIEXb++c9/fv7550sorB7//e9/i1dlaj8WV1lTAOns0UqrOOKII8477zx2WgyX7hl1Wvqm9hDr7ahfd8k7awORFvv85S9/ec8995ifOlvkwZl7VMRll1123HHHPf3001deeeWPf/zjZ5999uqrrxbz2GOP4VUq4t577wVg+Y3eVvomV0gU+dJLL/3JT37yxBNPGCpVyoknnmjgdUvdqSY1a5jNvjmomkffWkV1vP3HP/5RxucHHnjAFJx9s7dV3IdaQLJNjr/73e/wnOjCMW/iLfoauvL888//7W9/UzUqhT2XXHJJk77pZyjJGBxMr4YC4TCptwWZWeSTuA+KmtKItbN55plnrbXWWmSRRcwfW2211Y033miqWHfddZdYYonnnnvuk5/8pFlE4/abEdEoTVr33XffNttsgxCYxuaff/6FF174mmuuMe685S1vkUqXuPXWW+ebb74FF1xQ/M0337zSSisJm5mGfMvuQ732rRZwNZRr5ZVXVjvGmg9+8IOGD4815pprrg033PC///0vyi6AruFwamHLLbdUKRjAVVddtdFGGyHruBofoYSSG7Cs03bYYQc1awBiUh8Kkkn6EYFWWsUnPvEJlfjMM8+U33MRbuybalxXNUttv/32+KX1uW4bbcDkdNtttwmjjEE6h/bE04cKir6w7LLLrrPOOnqKnvXud7/77LPPfuMb32jYhPxCCy203XbbcUyMHevXamtHi31TXXjKoXsaGDfddFOUXdXozhtvvDG6oIfOOeecurAq1jfVXfbNgHcwnHvVKqJPRd803iKOZtgYn9W+PmjqNPZm3+xtzfaqForyRx55xHAnrZnuwx/+cMyb+pphUAfUJaMPitfjXPbUN0PelIom0WMEGPK7CZK4l1bU+cCYMWNwd4146aWXXnTRRddcc01DzOyzz64pzzLLLNw/BhfOJI0y+olbWDg/E4643HLLIeurr766YmAAlqrnnHMOhz3WvuKKK5rbsAGDFH7pcoEFFiBWHjB1vuSDyYLWayGshioysdRSSxlZbJPgZTfo4BDqzqWllHpccsklLcCso0i+/vWvf9vb3mbMWmGFFRZbbDEV/brXvU49qjK3LMYQhZ/97GeoP3YiiyRwg6F1tNIq8MXSN/XZur656qqrzjrrrLqkJRyX0p133ikcbWCZZZYRqZNqAG9+85vD4x59fDCUfVDZYCScY445DJI6Ed8E6MzW0DYGWv3yz6kCXSbQa7FvrrHGGlz4VgJrr7324osvTqeq0W2F5557bl3Ypc4722yzYRLqLvvmoGoSjOlVq4i+ee655+qh0lr1xfh81113mWGNvdk3+1a/vaoFWRgwV1ttNfsCuBR1qzJvWj6ZFt19xzveoQ++6U1v+uc///n2t7+9276p53o6bShA7vk6VZ8YbMcIMISnziTufWuiA5XKApTj3AwkA5OEmV7jQ/L4aD/2sY8h3DyyZUYXNtnzHJx11lnGGmnNZ1x6pn++qJ122sldenQMO+MnTJigNfMxoIZatvgh3KyVbkaOXtWCjCDpwCewrt122830jz28853vNOKccsopqo+M2lQvvAIRNsaFhSRVyhve8IYPfehDp59+ujoyBu26665bbLGFRReZUt0hn+dOIdBiq9ASWKjH1fVNz8po0KM9Uiv1GyyTMIKIOEqohaCbnSrj4M8XOA403TzNWkwLpAK8FfqUQc/dru5YqwVHhJv3TUtlSvhBQqcz/XqisVRytbPJJpvoy7bDWXjvsssu2TcD28Fz7moU028VYXDpm8ZbzpHYiYG1G28N0dk3+1ytLdZCjJByMbVJYj1cnTc95tLLzJt8JdEfVZB68bxLksa++a53vSvmWQtsfknzr5XY+PHjQ3+fyzLIEyZxH1wVZKrA8HgCjj76aGOKgM1bt99+OyfcH//4RyOLRl/1lNt6ccIJJ2joZhrbxTzktRlG8/X4D5uXSuvXPRyIO1/7ySefbB+OKWpwFXuQWdPbWuAbMM0jaij4r371K75245F9sfbXIvGev3tRgdNOvUD+mGOO4SPk44nxSx15ys9n8NOf/pTbnqveIKWaOCHcKmPcIENoOJrTvFVYb2PhOppag45AXd+84IIL9FMM0mOWqF+zi75MUi1j89qGTZye28SsMxwhbqHM3KVGSCBb4ehKPHMmbKwLG3OGOSTVlHEvlLXSN3Vb1af/Igd0qiDDaVSi5Bwf9t16F2WzzTYzIHtfKPtmCxXVVpFetYromx7O6I86HTeWfe3OHn9pS1G/2Tf7UH+9qgX6jX46F0dV3bxpf1rsHdDR0BtzImbvMVdPfROlsd1At0WWYv6lfGhPnUP5aUIfWl7HkyB8Zh3uH/O3bTPswQgRAk0cj+eW0xxdBjlwV7snadaxK8McY+5B0MXrCSSNSgSC6Ecq8S6Lu7fj5R2cBvShFqBqPoA21h4VB2p1ZxuMLXfLL798PJZV3lKzhNWjvJAMYcw+XOwhgzqUWh6cKA03q1ppFTDR76LHqdNu+2a1fqMNOEf7wR4w+6z35k3L9GysgxK4DImEsXYx4oUNesY6gVILrfdNFeGBJJ1FQ3TP0pepVafZN+Ew2I7etooYb9Uv2lc3Pkf9Zt/sQxX3qhYKmQF1dd5EgfRBK3MLad6uWEW30jd1W9U677zz9sHymStJEvfBWF8aNBbYK8u8NYUa8j9pu9JG8jo9dZe90j8MhWcErpLWGOSbFeutt16ysaHRhErNtl6cat9EIvugofW8hptkH8AsSXrqm0UgwCyXJTDcQJ7pytt6TfGtGJ+9gJTjc7/Xcuu1ULIuSQQefvhhm2S8aoLSxCKcWBGIJOWyBIqqoR1I4j5E6re4iIZIeYZQMbgKwuc3hMqURekFAtk3ewFWe0Wzb7YX78GYW7aBwVgrr72dUij74DSyU1Ylce8U8plvIpAIJAKJQCKQCCQCiUAi0AsE8uXUXoCVoolAIpAIJAKJQCKQCCQCiUCnEEji3inkM99EIBFIBBKBRCARSAQSgUSgFwgkce8FWCmaCCQCiUAikAgkAolAIpAIdAqBJO6dQj7zTQQSgUQgEUgEEoFEIBFIBHqBQBL3XoCVoolAIpAIJAKJQCKQCCQCiUCnEEji3inkM99EIBFIBBKBRCARSAQSgUSgFwgkce8FWCmaCCQCiUAikAgkAolAIpAIdAqBJO6dQj7zTQQSgUQgEUgEEoFEIBFIBHqBQBL3XoCVoolAIpAIJAKJQCKQCCQCiUCnEEji3inkM99EIBFIBBKBRCARSAQSgUSgFwgkce8FWCmaCCQCiUAikAgkAolAIpAIdAqBJO6dQj7zTQQSgUQgEUgEEoFEIBFIBHqBQF+I+9SpUydXjmnTprWYYSRsUbiIdatfJBMoLGLCU6ZMcRm3uk1VhFsJFA1Fcyup+lcmylLALiY15qLsVTRCQKSjKkyGthIZ+stlVbIxXNPVMsKhuWpSSd6oucREqp6KWVfjkaoNtVPNVylchoXNrS2FKoGqnoikoQpRkcxAIpAIJAKJQCKQCCQCjQiM7IkkNYo2iaFk5MiRTQT6fAutGTWqL6uLPucYCQeuREPVsBksVyZPBBKBRCARSAQSgUQgEWiOQO84cbD822677dRTTz3ttNP+8Ic//O1vf3vmmWew9uYLgLj773//W8JeuRix9hdffLGxDE8++SQDHnzwQbdC4c0333zeeee5fOqpp/70pz85Cze3qlFtiYl1yEsvvSTmlltuueiii3pldtHT50BYHmUBmuPss89++umne4L6wgsvVC+yi4RxFnn55ZeLZHzEKAvcREZxHnroIZfEOIObmFq0XXbZZcSAz5ieEA7hRx999Pe//31UUMRcddVVf//733vKJWTo7EkzgTPPPPOuu+6iIYTjrN7PP//8Aa2dv/zlLzfeeGNYfs0110AsGsbDDz8s/Oyzz/ZUqGo8a+m54447wv4w/uWXX/7HP/5RFctwIpAIJAKJQCKQCCQCPSKAQLR+TJo0ifDee+9dVbfmmmvec889mNPEiRNDgIxA7CgQdgvRcfn9739fwldeeUWkS/I2HtRJunSIJ0Pyy1/+MroWuyzEONx13n///anaa6+9hEPhpz/96UUWWcRlUNVLL71UOBKGYcwQ4xDoyuTVXCIy7ImsCSC4H//4x++99153P/KRj8w666yRC4Uh6VwSShU6S2TcchYTOqOwJb7YICDSuaARMaEqiHJBe5VVVrnvvvsIOKiVpOQ4ZsyYj33sY1SFhRihwDLLLPO2t71NZCAg8MUvfpG2173udS+88ILLY445xiUxSwKX1EpVVStSFkXbGmusIeacc86R6oILLhAm7AgEXDpocL777rvJfPSjH40YSiZMmLDNNtvIIpIUy6UV1kIkpLNoFukg7EyJs1sHHXSQAOFAQLx6X2yxxYhFRrQ53HVZPUTSL231biipxoSAs6Mkf/Ob37zeeuu5FPn617+eGerF5U9+8hPh//73v3GrmBoJ65B0aRWq3boLT8JWpDfccIMaefzxx6N1RcI8JwKJQCKQCCQCiUAi0C0CvfO4oykOHHHJJZf8z3/+g/z961//uvrqq8844wye4LFjx7pVZEaPHi0sV7eQNpezzz47mYh0KYzKSFKVdOkQL+ETTzzxox/9aO6553YZakUK40/Y+SyzzPKb3/wG4wmdlM8333zEXM4xxxwlI/LCdIavOuzpyuTVXKr2RNYkOaHR0yWWWMLd973vfV//+tcZGbmH5XHprkAodxYWUz3ibtjgTIO7VRvCKmdGEghVRYPI2WabzZMNxbzkkkt4lw8++GDCGCdJd0uOGOF73/veSChy/PjxtM0zzzzQK9oExo0bB5y55pqLt9gl4khgoYUWCpkoYFWtmKo2Ckm+4Q1v+NKXvuTsLmFH1Wz5IqlLLbXUhhtuyJ0chNXSDlvddttto6SSFMsDNy1EQoCHZrkQcFQlmc14kYQDN2Kl3sN42hzlbpTLWST90pa75InVpCvyIeDskArOzswGlIBHDdo8eXXh8v777wfdAgssEChVTQ1jqjHkSVoBuqV23NJxPvvZz3pO8sEPflA/IgAr5zwSgUQgEUgEEoFEIBHoFoG+EHe8GePh5sRCVlhhBQTavgjaf/jDHxZnPE/5CSecIJIkv/X222+PcXIxhiNT5FlnnbXpppvaAfLNb37zO9/5TkhaDOy000677LKLLRZkvvWtb/GGfuYzn7n44ouDDiJSAuggInXAAQc899xzbpGU3C3KBRCjyEUY/bJtZrPNNsO8n3/+eZIO+zH23HNPNJcSlxI6//a3v333u9/NfassDzzwwPHHH88Puskmm1CCqJGhlhj2yVqW/+53v3PpLkl22kGB31tmiIkjSNgPfvADBVRYyhW2ZFdKivyJVKIdd9wRQcfhbF+hQXZxVhYkjw2cvh5uXH/99eLx+K997Wsbb7zx0UcfzbaQjCTw+fOf/6zI9pzQHJgQiAPvXHbZZfHja6+9Vsx11123zjrrMLWklUqpv/e974U8DVVtUSiR5AM3aydFQ0CBJknoibTvec977rzzzn/+858if/WrX80777zsZ89Xv/rVsDyU8MoDX6XbdqVFySJKBGq1ViTpdEuk5zYf/vCH7TkBi0jCUd2s0tKi/cAwjAxLZLTbbrspiEYo7e233+6uo9RCyBM+4ogj1Ndhhx0WLTks0dQ1Hlmj2m9961tXXXVVW6cIX3HFFe985ztDVSNudTFs0JilIv+FL3zBw6J11113/fXX/+tf/+rZjn5EQN2FwXlOBBKBRCARSAQSgUSgGwTQhdYPzIMw4jX//POfdNJJNjEfeuihaA1CI/5DH/oQT3xoQw3tMBFGTJdbbrmFF154q6224tzlK0W/7H5hyuqrr77BBhsIYHgkbQIhiRitvfbaeAzejN8grCuvvDL/d/AzaUmilZyvAigUuizgwISC/TDGWoJLXiSiht69613vssNhrbXWQr/sSJaKnTgTezBXYpg3M3iI+UTlzj1MhhIx7mLz7Le3wTqBwZysqC2n6Ve+8hV3P/WpT0m7xRZb2EYigHyLRCUDK6xU5Nvf/nZqBX7605+6iy+Wkr7pTW+yTQVndRelRoJj60Ukty9cRmiiVIwPGIVBB3akFguM3RfKwk63rCioYoy7AlYCIhkfCj/xiU8wHru1HPJygsUAhvqWt7yFL5kYFq7UBPjLY5eLKq5qe//730/s/PPPF3nTTTcdeeSRAoHbaqutFrVDQGU5xwb3H//4x8LsiU07aqFY/o1vfMMtDwE8VWCJHfCqg0L+bPFYfp3kggsuOOecc2pIiy+++NJLL203DrE99thjxRVXlLVnCMAs7eeRRx5xN0xSfPhoCZtvvrmWqXRs8zyn1IKWI4Y8Ws8Ata85KYWEItWCdnvrrbd+7nOfs977+c9/rjbhyWyrCAInn3xyHW6WIiXGmoGMJsGGY4891tpAFmqcco1HzIEHHhgCznkkAolAIpAIJAKJQCLQEwI1F2nrR5A/rm7MoxxIMHZOCYKCvYU21IcfUTj87qiwMGaPaApstNFGSKoA5zcyuvXWWwsHCwzvqR0Rv/71r3nouWmDghdSSBKVR9fwHo5eJAzFF2mLRZW4c4GzFu/ntXWX65fBFgyc3wLcwyLZsN9++wmce+653j4UQKzdFUA3l19+eQEHDidHAS5zd/nphb/97W8Ls4rn2wYSXFwkoslzLCBrhwB+bJETd+1QR5FFcpNLGyW104NaHnemYsnuBuuNu0EZV1ppJYjZic4ji9QSOOWUU0I/Bv+Od7xDKmXZZ599BPhx8VcB2Moa0RSGVch/8pOfxLOVznZzRBnyngngr7HHXfXFWiVWVnzM1ZqizfqENu8PqCCudAuqQCNws/Xc3bA/AmzeYYcdHnvsMQsnqyO3rCuK5VZBxNBZDUPAceWVV1qSxTqwUVKmWDux2OfjCY+wPeJRUy4LqpSceOKJ7kZezri+RZGYeDpkiYJtV+U9LXF35513tjwINFRulMWCDbwerVglAhDF1+o0MM9zYp2mWgM3j3foJI/ZR+kgqdZiXcQG2+VV9FFHHSUv8KojgWgeBTcxeSQCiUAikAgkAolAItCIQF8ezeNnGCq2Yd+FPQb8jlggvuLAdcohMzE4EOLitVE0xb6CiOT2Rn3QKW9J8oDSQxK9I4nWIPeoj++HcJqKd6ZTINLKl6+X25KnFum0JIg3OPEeMnGQRKoQevSXo5fBVhectfZI8Ge7hZyxx2U4Ozmnbb3gnMYCqZWcAdLGrhWawwDPBKTl36XQDhPWErBrhQ/e8oOYTfZuvWZF7S83OboGLmKcwQi0SDSulJQAz3FsIkKgg2hWNQjHaofTmuudZ9olJL1XypGP8VvbkGFtpGK5wga2AnX2SMsSdJ8A5iotWJQO7GKcvR5KZsstt6TN9uuArk4bfCQBoDVDwY2DmVjY4EyAHvt/vP9gsYTsYvBiQF1nuSwsachHDSqIMA2NZWS55M5WSqpJ/RKj0yFQbT8eJsT3Z+IWtLUxTxKk1eQclprqrtQC+XibljGeugQmXYpHMsbiyqLF4sRdSjRmef3iF79QX1Z0zGZM4GZdwRKc3nMSqxoaIEkgPiZDzGpHAaOkngCwBJiaRxTEOY9EIBFIBBKBRCARSAR6QmBMTzeax+McwTZsSv7ABz5gWzD5IH+orTA+GgEMJmiKzQbYUqhFaAhQ4hKzD+rpkgz3s4RIFd8kIkiSR1YMJSiULHhS8VFbdDAexAvz9pU9hEk4lDtL5S4HrTCWjFNizBgtvs4eehzyOvzww0ly3uOUXKc/+9nPCPC8iqRNpjhc0SlAoYTYmwDWyCSWO5OPI0yqJlEokjiu7GId4i7NzPAlwSippxPcwDQoHXlKqhpc8iXj6xEpO25azxaQXc5+u4mQfrckj4QsR1LpEQlbjLOqjRjiaJ+Jz+bwW3O9K44k1DJGmJ/YVig6ma2KlVe4aIuXUymUl6r3UAVoto7AjSoaSl5hjFUTYzzWYLAFjLpAdtVs1XJJFLykldClyuJHr5MUb+0UNahtMKBkJ8DI0n4sz+QoMlpF6LROk1aktocxaxKY9Omnny5r8h4OhHxY4hxFCGRYctxxx0ml+RGzZLJVTOmsP11WcVNGWVuaFiTFEKMHkiKlskfI4ynrAZEBfthJVR6JQCKQCCQCiUAikAj0hMD/yG5PEo3xyB9GyAFpawe/I+e3TQjEuKLRQSwTLeMIx6JE8kyjR5///Oe9nmgzTLAiW41tt0CR9913X25dDIakPR4ILpaDMNn1gZmh7MK2haBrMnW45MG1FYR33P4Knv7tttsuuBTN4XUmg26iZR4F8NpSZTGAJ+F59rXbOY292axsF7JXVIOS2pGCB+O4PKPSMobP1XYaXE3YgWA5OJgp2XXXXSm0NRyZtiRA2twiwzxpI3lXotqJDYyXEaA4nu22F2kfBddvKSnLYcXsRvYWZeHfhYYSUU5GQkQfsFQFMgJdOdcstw3ddhr7OtSC4tSxW6bKWum4jfFXgLBfLqCjmWF2cqsOPmNPM9B0K6JGbWGVJFXcAnwGxEEbMTvaLUs8JOF6F8NsZamzXELQRaqwBCCIb6MktDUhSwWbl8iEHiUKzFWHsgSqXj/QluiMqnFWKLu2fMBRxbmUFoEutVDk4exutLRSEAEVxza4xZeLNtxwQwsSyzZrCeWireBmH5RljILrC4GkJwxaMp0A54C3ymW8BSe1dDrTEHnlORFIBBKBRCARSAQSgWYIoA6tH2gNYZ9VCVIeenGR+N45T7A90CJ9bBsLR45DM+aNv/JZ2ohi8zECKh5VIonQo/uxcRlhshjAjRBrn/UgJjtKiCHroQoZwpzwabfQIGdsGDe1eQYTih3ksXvEbmlJOLltOqdB7r4/E0p8XYT3VyQKFbRVjE3Y/Kl2MGO0dk3wN/P4xiuwHMa2qSB5klNiI7i0mCjlYhTKXexTGBe0SVqAYQ4BLN/2aMRdEq97shnLFF9KCkyXPj2pFHZ3CMPBORQi0DifRwpiIqG7bnGKUwhkNN3mDXeVnZ0CCKut/+7uvvvuVinx8m6A6a7HC4wUUHaVQpuFlhIhyiL5uaWS1tLI3g9367Spa2LeOsDp4xevwBW4Lbroolza7ob9AlEEX5fHX88//3wxzKha7uM8CmW95NGHuw6729Vv7HG34iplDEn7kbQHaGt+v/zlLyOJtZ+YQJsXvLQf9cWSMIYltjNpCfi3pRrwI21VPlqC13atXtwtaUODBRK4SpPmp3cZW9Upb8StGmPPDIXEPMHwtrSwmrJDzGOlkkvYk+dEIBFIBBKBRCARSASaIPDq/goMqfWji5TW9kOHozSc1iW5u2LQFJwMBZc3sYgkg9CgcZy4dhVjgWIwTg5L9FESOoOeChSFGFjscBBDj0sayl3UB7nkwuS2pIFTNmJwu+LIxBd5/SVhjDN7BGRUzYXmKBECJxBFIEmz5IRpjrLQUBRGOO4Ks0SSsDaKg7ZabPhuYEGAWBzVkgorV9XmkImyUMiM19K9+rfAYgMG0h8glLoIC6kVYHlJW8rCPGEJBdhWlSmaq6kAWLRVrariJvcqpJGcgIN+yERM0R+Wx1acsLyqmXCdJCc3uiyewmpJpQJR6K+iGtk5E7DAsBKwygIUnMutOnk5quWqQJFkJxCigFKRrBaKWLG2JKmLiaYVzUxZ2NwIV0mbgUQgEUgEEoFEIBFIBOoQ6Atxr1PhEjHCkguvjcsiVi4JiESwuNv51G0ncOmzJHg8pykxl8G2S5KipG8BemTnkLzorAbibjUmDChlqcsXYwsOTcBR1gZ1Yi6DuNvPw2vOhU+yuTGNGprEyDoK1Sjjlkh3m8g0poqYktZlYFJiutXWiFtPmkt8t3rK3WqgW8kSWbKuJimRJRB3XeLcWp1vAdHgqGtmdfJVna2EKSRWbWaNMa3oSZlEIBFIBBKBRCARSASaINDHzbU17vPaQXvQoCAuouvorEuRxAiEjFdLfe3RJhB+UB8lxNojVSSs0xBpSxnqLsU3iaFQjiFQrKrmEvZUb4VwxJdMS6CwdgIlVblbDYQG2+K9vEuSWjERSaxqQ6RqLEWTeHp6ku/KpCXW3qihpC0WlhiBsKdqVUEgClgVqIarGdFTvSTW02W3kmGGJCXrakaNqMZdqWxt8lUfl1WO3pN8VWcJ92QnAfodIRA6G2OIVTVUwyWLDCQCiUAikAgkAolAItAEgXoW1UR04G4hMYjOwOlPzYlAIpAIJAKJQCKQCCQCicDMjsD/tpK3uST2nPB94us8lOGkbLMB7cmubgt1ezLNXBoRsHNpaLe0xiJnTCKQCCQCiUAikAgMMQQGhcd9iGGaxUkEEoFEIBFIBBKBRCARSAT6HYE+7nHvdztSYSKQCCQCiUAikAgkAolAIpAINEEgiXsTcPJWIpAIJAKJQCKQCCQCiUAiMFgQSOI+WGoi7UgEEoFEIBFIBBKBRCARSASaIDDEibt3QxsL76XY+BhfOYupEysydfF5mQgkAv2CgN7njWE91BE9sW9qmydvfrdvOWaqRGBoI9BffZMeHbAnrJr3TXcb5+WeVGV8IjCsEMiXU4dVdWdhE4FEIBFIBBKBRCARSARmVgSGpsc9HHjPP//8SSed9Nxzz8W63/J90qRJKuqXv/zlddddJ/Dggw9OnDjx+uuvP/nkk11a4schfNppp910000CoUogj0QgEegXBMKRdtttt33961/ff//9DzzwwBtvvJFmfc0tfTAEnKP3iSl3QyDMEP/yyy+feOKJjz76qJjovJHEue5uxEfCPCcCiUC3CETXm27flLbaK3UuCR0RGXeFb7311phb41aTvtmVutbfPYWTXL8+6qijTjnllG6NzMhEYJgjMDSJe1TqK6+8ctlll7344ou+Fu8XT33Ge+zYsW7NNtts48aNEzj88MOdhWeddVYBMnEIY/ZovUDO90DIIxHoRwSiTz3wwANXX321HmeBfeSRRz788MPxqw5idFUyzvG7bGLkXn7zIS7FCEyYMOHiiy+2OI9LMZHEue5uduR+rMFUNVQRaLFvRndzjl7Zbd/UAZ966qkrr7ySmL7cvG8ScNAzZkztt2WOOOKIO++88+yzzz7rrLNcovXOeSQCiUAg0LEfYGpDBRgFMPI55piDP49P7plnnjHB77LLLoj7nHPOeckll/zrX//iD1hrrbXIsOfPf/6zUWbbbbddaaWVZpllliD3bbAzs0gEhiECKMJ6663H484z99nPftYCGwhXXXXVX/7yl0033XTdddf9wx/+sMoqqyy99NJ86jvvvPPtt9/+yCOP6MWIvssXXnhB/OKLLz733HOb8qWV8K677tp6660XW2wxPf1nP/uZQLk7DBHOIicCfUOgSd9897vfvc466zz77LOnn366bui59L333rvkkkvqm2i6XrnTTjuZeW+++eZzzz133nnn1QHZgILfcccdPfVN8meeeeb48eMNCCeccAK1m2++ub5/7LHH3n///X0rQqZKBIYwAkPZ467acAIL/SeeeMJzNwPHGWec4SHg5Zdffvfdd1vZG5744E321157Lcp+6qmnYgDW+hIKhO9hCNd9Fi0R6CACnOXnnHPOe97znvXXXx//fuMb32jTmodgnpUfc8wx/G233HILNzxn20UXXWSTW7UXu2UXnD7rwBjmmmuuCy644KGHHtpmm22OO+44j9pM/3H38ccfNwJ0sJiZdSIw0yHQvG9yeCnRpZde6uy59A033BB9U5/Fv/ViXfiQQw7RHy+88EJuMt28ed9E3BdZZBFOtIMPPtjKfPbZZ8faqbJhdbvttpMLgZkOwzQ4ERg4BIY4cQecPo+F89vtu+++q6222n333ccNIH7ttddeaqmltt9+e953JB512H333Zdbbrmnn3464E7iHjjkOREYCARw8RVWWGGfffY54IADLKTN+rx373rXu77zne9svPHG3OfzzTdfPDfXQ3VhHTl68RprrBFcgaSDo86OWMtvfOJPf/rTSy+9hO5j827hAVbm+Zx9IKovdQ5hBKbbNz2RRq9NkXqfQJlhV111Vb2PD37BBRf87ne/u8MOO5hP9W59k9esp76J6L/1rW/Vr5H+T37yk7HSpmqTTTbx2A3OORcP4caWResDAkN5qww4DCjO/O4LL7yws/4fMRFpvIgRAT8w8dsqY89M7JAJotAHQDNJIpAItIKA/ugJ+9vf/nbC/OVmdyRbl3SJo+uYHOfBudEIMcLRiwnE1K6TlgMn8AR/s80284x+nnnmIUwmFu3OrdiTMolAIhAINOmbepy7znbF6Fk6qa4qpjrDRr+jSh90WFfrm/a/Ne+bxHwrgtr555/fO2a8bB7H2fCWlZIIJAJ1CAxl4m5AibfWDAcCRhCDgrDdtIYbl4899tjxxx9vI6xZnyfe23Irrriiu2Z9Z5J1YOVlIpAI9BcCZvfzzjtPl0TWfX1i1113RdD3228/S+h77rnnoIMO8l6aPTM4fZCD0os9TOfwe/3rX//Vr37V+cknn9SXvZdyzTXX6MWc7quvvron7//H3n/AyXFc5/rwTk6bM3LOmQBBMBPMOUgiKSpRsqRryZIlZ/99He/nK9mSbF9bWaIkSqSYCWaCBIhAIuecc97F5jA7eWa/p7p2G4PFAphQO7sQq3+LQU1N9am33qrqfuv06W6usPFJ3K1U/6pgazuagT94Bi4xN/Gm/83f/A3CnTD3v/qrv2L+ct2MEyh3njANOW9yqh0xYgQ3lVGstraWy9qTJk3iYtol5iaOM24545oboe3f//73iWslgF4+Ee6WW275g2dbN1AzkC4Df8jCXd7swiGGszvX3aCGRfzQoUMR9LgH+PqlL32J8zq/ksbzh3DnTM9Xlv6Ul/kcwtLlVJfXDGgGLsGAnFPMr7lz5zI9OW3/+Z//+bhx49gFKcCFrz/90z/lK+GtSHlC2saPH88uzE05i7mqzvy9//77EQ0kyESa33rrrYiGJUuWYArP/Ve+8hUsc72eX1H5WNYT+RI9on/SDEgGLjs3uY985syZFP72t7/NvWHML1R7ZWWlzOQMy7xmRv/t3/4tQercbMrZFl87LvlLzE2sESvPcyOY7Kh2HGo8KJY7Uwlq/fznP8+vzGU+9aYZ0AxIBvQLmPRI0AxoBgYcA5zvtdQecL2iAWkGjIhzPTf1QNAM9CMDf8ged2hloc/1O0QAG6t2PHMccUjzySavoZOQOeav7CLT/NSPfaOr1gz8ATPApGN6yinGp3SqMe/kZOQrCb7KhPwkh4Q5N5N3x4LclwLSZo9f/4CZ1E3TDKhl4LJzk+rMqUqaGWfOTb7K2Srnqfx62blJAVmSaSunMAlyOBfzqTfNgGYgmQHtcU9mQ6c1A5oBzYBmQDOgGdAMaAY0AwOUAR06NkA7RsPSDGgGNAOaAc2AZkAzoBnQDCQzoIV7Mhs6rRnQDGgGNAOaAc2AZkAzoBkYoAxo4Z5Jx/DYGUL6Mtkz5/vwXA62nFebSYUENV4pj+DkCYZXCqsMVIZrJv1xZe6j52Zf9NuVNYr0GOiLMZC9zStoFBFzf6WcjK4gVhlCem5mP4+w8Ad+cyotZFgrYSrZCBKTic09NMmZAzMtb/rpCxKUtxeobFcQVJ56ppwE5QahlOHaF6zKe0CzASxmpurZacxN7mG9Am4rZ7ALAlQzkE2PXGxfoBqj6GK/D6x8PQZUPFVB/TGj745Fyscfje+jw2bfQO16laRy48oNGnPzY62dxJkp6/l5BSiPLIdO9vLiQgAotivlbncpLvuChAtpyTIHqOC8UqByEroioDJQJbFZ9k5f7G4cwhQbdtitNtsVsKKm2UDlM+tjuGICezUHpaC9IqBKYvUY6LUf08lUf3jjWGSzu9TbTadVKZY1DptXBlT4tNndVwSrkM8AgNsUe6F/i9ntLgAMzIPeH7hwZ3nHixX5VDusuYiGGFLucccmARhqocp3yGNZ7Rxg7sGqWptyLc7bc9Sape2SBIVmgYpLRi2rGKTtyqGywMCm0+lU2HygMgBKSkqyZKCmJRAIxWxWi0KnM3PT4YjweEmF7eXY7bBaw/GEQjc+NqPRGCAdDrtCpztMOm3WmLhypZAALgskQOt0CsCqNhDabYLRWJzn86qyKuz00RjgiB8Z8GMAIuOJzqpiT77bwRDIiFexX9Df2N5yWu08YlQSY6j2WMQlK5vNyXBPxFWeOgXUeMyp9GRkHOHd8TjeceZRRj3T2yzBbDQScbqEylS1QSeLAazFYyG1Y8DQThxNlTUfkMbSxRWNBJVqJwtjFeN2O4JE1cHUwjD15JcWlAzNsqcU67ks0SjcndFMLyKweNkyL2dWu8hDCWFQ4SgBLRqouLiYl8YpXA9IBmAVtFShkF5EG6zCg0ISkJiAVNhT0hpQlb/3XjlUuoaxyksHGQBqWYUELGepsHuMHJrv8/muv/56zGI/gzHAYESrrTtQd/BMi9tpVygz48bcVOgnoYEuh314Wf7+M82s1lVNI9zX9Iucm6qaD6WxWGLc4JJTjf5wVOXcRLmDlms3PUZCxl8l1KpiLxbOtgQUEovBvhgDTrutushzrMHPhQdVR9K+GAPYDEXjD189cvzgIhGGlf6SSM7o5rMHd67+rcWq0jlqHIsSXK7OeNhcuCNKqKBkWDQaDLbXW23KNBZQOR2pvG7DiyZi0ZKq8aGOplBHo0JilbPK8TwWDQEVtpvPHrA73FRxIfOZ5cRivFqHQapMuNNRDoe3tHp8zfHNdrtTFVQQmsdndTat0UhgzLR7J8wZmtncNDlXdiA2LQ60hBwifKpiv+8aeMVB7TsqFFqWrCo02BemzK4f+GhNqNnzIA/efCo7indjUmiQU5ZAaFhUaLYbqfhflVlpB6hdieQ6skvL87YqnGaTzdO3QstmQ9XaxJokVq3ZvkCrBqHoG/lnYlSVUAOwGw3DXWx9gFZO/e56sv1fIJRbH0AFnEJWu6AaLZbEZtv48/dXa1MOAC6xqjar/jhqIDSPeueTktY3lReU06pYF9YMaAY0A5oBzYBmQDOgGdAMaAZSZ0AL99S50iU1A5oBzYBmQDOgGdAMaAY0A/3GgBbu/Ua9rlgzoBnQDGgGNAOaAc2AZkAzkDoDWrinzpUuqRnQDGgGNAOaAc2AZkAzoBnoNwa0cO836nXFmgHNgGZAM6AZ0AxoBjQDmoHUGdDCPXWudEnNgGZAM6AZ0AxoBjQDmgHNQL8xoIV7v1GvK9YMaAY0A5oBzYBmQDOgGdAMpM6AFu6pc6VLagY0A5oBzYBmQDOgGdAMaAb6jQEt3PuNel2xZkAzoBnQDGgGNAOaAc2AZiB1BrRwvwxXvN2d7cJCvIdVvorV/JWvZvrC8n2dQ+28oTcZgMwhk43a5VcJg3Rf40nRPoCBJ/HwaeIfOAh7bQg4Tai9Fhg4meA0GR44qPoIiRhCYjj1MmH7qMZ0zfZASOfIoc6nTKRrsO/Ki9nIocM4VoCNLxxFqG4g02vAG+hjILnLYPVKOZIkw84snUh00toBc/Lp2QgGOadQcxoKpN2D38zsuU//fQcpCGX9JMz0AIRqkgS2ZIbN/IGZSGZ1oCG0DzRAGeBhNBhvPM5g10vtglm73e7z+SgUCASS5wNpl8slFHE8ToFwOByLxcihfDAYvJTRPvuN2p1OJzAAINkgx+12R6NRm80GfofDQQ6/UkbmJ7eoz3BdxrDX64U04MEk+AEZiUQGFMILGwC9BQUFnG7p9wt/HWg5MAxgWIXhvpgmA6e9YsI6nC5PfiIejUbCA7Cx3Qi90XAoGglZrFafrwCZGQoGHE4ngKORyMCB7fL67HZnKOCPx6Pw6vL44tFIPBZ1eryxSGRgyvduhgfuGEieLxaL1VdQDOZouH/OGslgcpD2ehxWiyMcFYtrFe99VwkZie5w2D1uRzgSC4ejVqulIN+Fyy4UjjkdNmZlJBobOHMTJIX5LkZOIBiBBZ/XKU6joaglL8/tcoB5oNELSINhm9dtj8XzBhSZvQ4jGGYAgDkcEX7Pgbb1lce9ra0NoSC9fbLNpNl6pMmRxXrk89UoLsqTYIDKTRYzPxsbGxF5fTGdqI6Z0Nzc/LOf/eypp55C95i18BPCd+fOnfX19fn5+S+//HJTU1NhYeHevXsXLFiASjbh5SYBHvTurl27vvvd7y5ZsgT5C2OAX7ly5b/8y798//vf57Ojo+PQoUM/+clPaBGic/Xq1X6/P/dQkwmRDC9evPgHP/hBQ0MDTELgz3/+85aWlgGCMBmtmWYYoNd/8YtfvPDCC1ZrX00fs7psEibD//Vf/8UQZZCQk43BgbyvmAVO5+kje3/773+xe+NHLo8XH9SAAtyF8PDe3/zfP9u1/kO3tyDob1/w83/fu3l1YUnZyYN7juzZLmAPhD4SRz/HukULfvf9v25uqPXkFx7bu23Bz7/b1lLvLSjatnJxoL3VmvMD3WV7c+CPgaQmoFytkVAAVt9//qfmySWpwB9UkuOOw257/8O93/vZ0sbmDofDNqAc74wcp9N2+Fj9//l/C9dtOerzuvwd4Z89u3rzzpOlRd4DR+t3H6xB0w+IuZmXJ85BkdiPf/fRMwvWWy0WiH3rg50vv7PF5bCR/+G6g7RlgEA1B3E3ww3/90eLN2w7BpnmJQKzzMBJwHAoHP3JMyuffW3jAFwCQZRi5YFkxOixY8eefvppxCLKxlSHpNlk35jp7du3IykuzBfIjI0EZTAIlWxydwYBjuQPPvjgueeee/HFFxHQ5LDJX7P/lNao/9lnn7322mvHjh376quvejweuZZAtW/bto0clhyIIdKAaW9vf/fdd8ePH89eCpFcti3UhVI/efLkwoULv/KVrxw9enTDhg2IYFYaU6ZMIWf+/PlodHDu2LFj0KBBhw8fhnDQkiM767JV9EUBqgbk2rVrWXrddddd7733Hk73PXv2VFVVDRCEvbYa2PT+K6+8MmPGjJKSkqVLl/K1H2nsFaTMTGb4jjvugGHWGwzOS+xyRf9ks9vbmhvWLHzltke/fGTP1hP7d+IYHlDaXSJcvfCVOx77yuHdm2uPHzpxYGd+UXFj7am2poa6M8e5QCZCU/p7w5eCUt++ZmlLY911d39q9cKXwoHA4V2bSyoHnzq0r7WprqO9xe50DihuJWcDfwyYfcv0dHk8H7z81LgZ1+QXlW1Y8uYAXGqaaLNMINHyva5VGw83NHfcfcukd5buwqVts3adzbM0rmR3u93W1NLxzrJdTzw0Z9f+muOnGvcfqcPhWlPX2tQaOF3b4nbaCU1RUleWRiDT47a/8Oamq6YOY1GxbO3B5tZAY0vAZrOeqm0BKlLeiGjLsh7Fu0uG3122+7H7Z+06ULPvcJ3Q7uo0m0K4gmGX/YW3Ns+aPLSk0PPByv0DEKriEznamkMSepqQDHQt8v13v/tdKBTCL47CxiGNxiWNt/K1116jAOnXX39dpvmJ/DfeeAMLZpoyaFPUP3r07NmzdA9fqQXPMQrvW9/61lVXXbVv3z5T05v9J3PMTxJpbdSI0Hn44YenTp06bdo0lLGsGpXMOgHhS71gI5NQBDZ08y233EKmlEdp1SULS+QZ7Cgl2uOPPz5mzJihQ4eeOHGCkBhYwm89bNiwAwcO3H777VwQIKRnzpw5/IRje/jw4UOGDJEXKzKokV1Am9mO5l7AxrkO5ptvvrmuru706dNlZWWzZ89mRYGCzx6hWVHGxJoWZAI7jApWQXxlSACVNZtcl/YomfFXVVAlgGSGa2trWSPBbcbYeuwoB4D5KZGn/inX4MJmtuPIsCEOEY6W+rPFFdXT5t1WVFKJ0HR7ffJY0QN5Bl/BKFuawb5yFw5bEmFJZfX0624rLqs+sH09Wm38zGvKq4fWnDjM5fmJs6+PGRE+GdfSVVe2c9PKyGlvaRg6ZtLsm+9rrqupO3W0qLxq0uwbCLY7umfr4BFjK4eM4NidJU52lwMmezvCVDfDfTQGGKhdYyD7ESuOJPZAextO93HT506++sb929bh41I2XA2EEq1kOK1P2S/mp5LeQQw1twXHjqyYf+242vp2FDxOdyWWJc5suqYzz4LqrW/0V5YVXD9ndHmJb+ue0x63c9aUIdWVRcdPNxHXcfWMEQQbZg9YdkTGdpjZQG3vEHGAMycNvXrGyK27T0ai8dHDy6eMH9TuDx861jDvqlF2O+o9+00c9rK3ggWT4YqyfBguK/bt3H/G63Gi25XYlwcSJaZMhllXzpg8hH7fvOsknKuDKmCKYSA/5YBI/1NxjDuHHrx6V199NZ/IsrvvvhuZuHXrViI3RowYgWpEARMXMXPmTDysRJu0trbizyYfXc6+eKzJX7duHQ2ZMGECIol0RUUFARV8RdhxRpFew6KiIryz5OPynDdvntlwxCh6GmrkQZAFALuYOWaxyybk7uhgkG/evBnw2GHDk43rnRqXLVsmFyGIobfeegs1/4lPfEJePZCC+LJVJBeQ1WFfLgb4mvzrpdPsgvcaaQ6xeNxR53CIKfbiSgXLm3vvvRdIXABhgSSXFhQGP72QHAJ06Vp6/CqhSmJ7/JTiV0DSTJAzBlj5sCKiu1nFgZ/FD/2bJUJgSBqBKtF2TZgU8V1QDGsyegpsNBzqgM0ClXzZaxfskUYG2DCiCqqsOJlhVnGwShUZDM4ezTChwgCTkebL6UaaudCjcPLX5NrZi6OhmK3G7MzS9SKsJeLtrU3FFYP8rU0OlzsSDkbCYW7Zysvahw22hFX4I8BvFceV5Dalmu5C2AbC6raWZrvLabXaHS7Ph2/8fvzMeY7Wlqrho1cvfHnstLkE/FBRZmOVc4EcRFhgyziOOBhop9XeguK21ia3L9/udBEb8+Hrz0yZe2MkGMwvKt249O3xs+ZFw2GL8Jt26e9UuTDKAZW+Z+Mbh+yMiTUr7dMxgPG4RQRtwipNzmgImEjFccnucLQ2N/iKSjAYi0a4nYD7HDrzlBxJBE7j3BRlMJgDSS7az4E4P8UuTEaZJ8a7zR6LxsjszFNzCagjEOISTaHP2dIWKPC5wojNODUyzs/Hkf43bhEBJ5sY8CKCIO3O6eQwYbO0tgcrSn0trawoCBOwMEFfe387Xu02f3D4kJK3l+6cMWkIwe4cTjLEjE8z+QifNkxBDSOHwJim5o6iAleMgRONcSnA43Eg30/VNI8aVlZW6t2x73RZsXfYoOJwNCa87+lv4ggvZJSYmyQs1q4b6NO31LXHOYbL8lvbAi6nLSRuJIgYwz0jIpKgiOFqDAExNy1ZQ5UMt3QUFrgxiJvZ57EHguE84473pGozSSJLsclEo+MYsHJuij5lzKV5MVyxx122BpVQXFw8ePBgolmQX9IJTXQBqnH06NE4yBctWsRPuAApI/Mpg2MeL6bUbWgOCs+aNQs/MWJ01apVEydORDaZhyF03iOPPIKUP3LkiBT6mRB58X3E2I3HqXH37t1EdNx///3AkzKFTCE4jJMradYn5LOx9gAtRxAT5MXNq/yF6sDD4oeLFSxjINAMUjp16hRrD2Q64G+66SYoRSgDFUohjbB4Gf+jEk3KthivbLI4kDjT3HjjjQMK4YVNgWoTdo57+UIwl82RUAc+zss2JO0ChqPIOIVnct5Ku7rUd0CaGYWtFhvxzaMmzZp+7W3Vw8fkWTpbGmoP79q0cdmbrDr6PwpFoOSf+M9itUVjkatuvmfi7Os8+UV4/E4d2b9j3dJDu7a4vfkc7lJvfU5LDtgxYLLA0U8eAA2azew/2ET34JcLPdHoAbJZOjlMdJ+L8mxWazAUxYF9w5wxI4aUMglwxu/cd2bJyn0u50CJ7uhiDyGYSJQUeLiOMXXCYCYrwmTfoVruJWjzh/GMDBCCOb4lMyzc7AMF2WVwGDgHIljFHndJA6KWbc2aNQTX4i/n4I5zDscqCTQlYh2XPOKewtwxiZQkkzS9SRl0MMVQctzeigObT8r/8R//8fLly1Hqssf5PH78+P79+++5555Ro0atX7+eXeRPKGk2szfIxBTxDGymTDR/vUSCwkhhABDe8+STT1ZWVuIPJod2sZdpE/u4XXFp43n99a9/LSM92FeCuYT9Hj+xCzZNs2lBpe1I8xUrVhAk82d/9meIeFY1WOCTOBnWRZIcYrLvvPNO4rO5UlFdXU28OwEqtAhNDzk98Fz2q4SaQUulZSDBGyzR9Tiw4ZZeAyFRPTjdYTt7hFQEPJpm8CouHV62UZcuIDsFkIxJ0LJKZnlJKxi0GRDYoy7gYV9CxVr2aE2GCetiePDJog7LybOjB4YUv0psQGWAsaW4F8WonS25PGBsxuyk8cn56aZRuuDJLyw+fXhfflEJz2zJSzB/3UFLW48a07VMebCBEfsGfHHNNIPNRHjq8J7C4lKBULhd7dfe/ckdaz7gmS10zG2f+vKKt37PSLUzAM4nKsUaGeOJzu4jXqIzM38bI4coI3Rv0N9WUFQabG912ByFJeVzb3/4ozeeKa0cTGxPxeDhzXWniZwJhwiuPa9PU4dqN6BSnvZCcGbEmtWZDPfFGBBHEmv3GGCqZnksMZrKHcn+tmZabnc6IoEOj9fnb41kRqZJAgmmp9W4+YpDVNKZMLlIL2k5nbt/YIhb2JtMBn13Zub/47jneTJ5Vkt7R6So0EtEh9vlZOZ3njtRZ26cvhA4jenJB9M1XVscPCw2a1GB5/DxhqJCH08R4QTOE2YIx1+18aiT57XYrI/fP/v1RduZWja71WbJSBCLQ7w4TEmorIfTxUl5OUdKin1t7WEOnk6HMxiKgY+rAf5AbMX6Q8T53HPLlMUr9/oDkeIiHzo+g1oEUjEnRTNtxuSU574MTMldzmfYyx20MMxj8CwBHnmXEZlJUDBlHJ7l8Tk9mZdkpit5juE2oYvsDhvP6vF6XK2xoIq5aU0Yp2BGF4e9C2tPPSernS9WDS1E1pSWlhJDglMcEUawNZKRoUbUOBEa5KOAcWPjokaoId0efPBBfK7PP/88+37yk59EfRIoT/mHHnoIfYk6JwfnOgEzslLpuf+f//kflBN2mAw9xhZfxfgz+oFPuV0M8IX5lCfzxz/+MWsM4BGBzTUEFhUApi5+YikiRTzCF905adIkfNvE6KPy+SrLXGj2YjmyOn7tAiqHz8VKJ+VTHvFEPAwPt0G1cxsATnRq5woGKyKEO1E90ibFVq5cSVsgk+AlbhKQaypZaZLJVJPSbKqlzy/HvnQ0izcQIitZSyCIgc2lFRDSucoRUuP5EDL5xiAEMwOVO30ZDIxkxoA5zDKxmLSPidBMJP2YdtJk+ODBg4wE5iAMg1yVcQBJU3zCQLr46A12Yl/hdTS2dC2cV964PlZcXtVQe3L3+g/bWhpmzLstFOhQ0jUSo2xv5ki7ETbWnN65fjn30U6/7laumNadOlZ74vA1d3xi94aPDm5fj4jDxZ3I68xYxgq05mHkPI5S/SIjJXyFxScO7NpW9H5Z9ZDC0jJ0xrZViwmSGTJ64r6tq9ubG0sqBhGTIatK1fT55SRU8gxWzW/nF0r9WzfDfTQGpL9YQBXjNnVYvZdMxKI8CJIBcHDHhvaWxnEzr+ESupLhatQnYJIQYDOZm+edOntvQDq5wEBaEXtw4MjZAp9zUEVhabE3GkUfp2PlImVlS/mRhOij9I3CEGEhxMmcOdvKI2WaWjuunz0aeGdqW46fabr3lslrtxzduvuUCMqnFmNyXgTLZbKToWaAU1qPxTuL8t2EGm3bc4rbUmdNGRqNJ/j60fqDpFvagrv2n+GROET1sAI3a7wMsgt+FmQavWMkur9cUCzFDMlweamPm30hE9hEuvMgS3kKSNHIxYoZCMWPSqBiB4YLYTgW377ndHObYFjdWb4Lo4QrToGZboqFuxSsc+fOJcEhA7mALEN/A+8LX/gCOehs0txJSQvQE/h9J0+ejIbDHSjLsCPSMznNAoACeGE3btyI4qckWhk9ip9bPpBRls/gCEUtvW5go0Y8qVRNjD4qjeB7qiMYhjspQUgBbu5ExCPfp0+fDgAgPfDAA8TcsxdubOZMr5b7KBN/KiqcUBkc/4Tao9FrampgDGwITcCAmU/y6Q44565KALMmwWeskLfUWwceMBMbQ8QUT+P59Kc/Tbcii6EOfTkQEPbaFmCzImL0cqc1o/exxx6DcDJ7Ldy/mckM80iZz372szAso9L7F1gf1U7AZ1FZ1Q33fXrRi7+YM/++EROnhxHuA6lruhDe/+n3n//ZVTffO2LC9DBhzZ2dZdXDUMmDRo5d9e5LNz3wGYrhM+0jllIxi1cRL/tVN9697oPXV779wt2f/ROn2xuPRcST3EvLywcNtWyzhIMdU66+KRjwW/sVao/mDPwxYAIWR5JQ8O4nvvbeCz/z5hfd+dhXGQwDariaULNPoAW4n/KWa8a9/9EeHinzhU/O87h4mnuGEdjZ47nQAp7p8tL8B++Y9uzrG+ZfN37i2GqiZRCugysLC/LdxI6/vWTXw3dON27GuHDvnOZAJtg+98jVz72xkbsFPv0gt4SJG/l4wkxxoaeqvODZbccmjK6qLC/ghSj9cnLvlY4uhm+f9vwbm2+9fsLEMdUId9rSa+H+zQRVyGD42dc28GShJx68mssamV297LuGdPmk+64CaZnzkxxDJMgx0+bA6pHfo4zcHblJNIgU7tdccw1u2h7G5dfkTJQKzyxHTLN4kFUkl7l0GmyIM7kXmhKli6xEt7EXXxHrrMPYkO/8RAKtT6YM+7m05Qt/pRYQolm5vICdtKBSGEUu8XA+kLdLYgSoYAMPBfgqhTufuF0pTI4seSGYVHJY0sAqPJg9mMpeF5ahN2k46wcIBBsXajCoBCF1yYYDlZAnjF9Ye2Y5kCzXZnIwZGakx160GjK5aMNalOZnyWqycaBiTV4gUmIWI3QWU+O6665jIEFyBmY5DOBueGPDsQNnWjxOe5Y3p8r2gsThcFodTtyZCl/ABDa3wz68PH/f6WbCB9L36J3rDYmQ51QaL2AKMyYZS06XG9HGq6PIjwQDqM+MPTFQyl1P44eUnGrwh7IWRk63B1ShDn8iHoMEcSmaePdoxO3xEjGAdqc559qWZkpCrS4Rfpza5kCWxJqV99EYwCyxHdXFnmP1fp7YkXmzTaBGAkodTjfGeQFTNmQmW2UyhqPxh64eOX5wETYzmpvEnVrPHFm/c9VvM4voSMaTnCZABvLUvoCJmwYLSofFosFAW73Vxs3xGXYOYxkvtbv7BUwGbMLtnGg4fO08EBC5zO3UmStNbk6NRUurx4c6moL+xiyJRUfyVBZmJfKXXhY6xOsmBAXYPo8TnDKdTH7qacZMLBoCKrs01R6wO8QQTX33i5WUDNttebEEAQvZKgezFq4QOpzesuoJZ45tInpICVSMExgnH4dvhE4paD42mVbRSGDM9HsnzP6EuOQycDzuJps9Eubhw0wYzTg3Cy6dL38lMoGth+Uedi78NeMcRgDhEHJ3AEhNzKfMQbSRySYDY0gwefAimwUyrjfdHakaWcbiQe4oAUhJLVW7zJfFSMuGyIT8qR8/kezwDCTgSYRCHhjLjwGC8EJy0Ft0NLBZZlz460DLgWEGA0s76B1o2NTioYHIymiH3wjPzSSEVC2eC61JhJEw70zleCIQMpaMrzxgJxptbSZ34HQTlyxCnUbUn4GJt7riXWBuigsFBPNkFKR7ISdqcwb+GEhuL3H5PBSfHBacyfl/qGlUJs9CITJ7AB6KgMRjH3ntjjwXcXgn0kS+QjUWS/DMGabswIGNZG/1hzigg1aOFpDLQwcXN7j9dwBh7R7NkmF/BwshcRjpzh6g/8Nwm8GwEY8+4EAqDpXp0/ZxkmM6ySqk1OvT6jCOiEyuInm0MUnkPDEzzZzkXXKTpuoeUGW9YGM5YWKQgPlqYjZ/6q9EDyQmhz3y+wvexeoFnjkUL1ZmgOQDlbFhdv0AQdVHMGgmreWjj+xnb1aM8POPKmQwli7Mz76uLC2IVUSSCYHQUC498pOKDIgkIAf4GEimaWCuf5IRKkwzoGwZ3jKtEMVFTTFyOHgk/9w14C15Gd6QmmxLdbrHG6wkVCo5f9aqrjU7ewbDA8g3cenW9GD40oVz/OuVJNwHuJjLcc/p6jQDmgHNgGZAM6AZ0AxoBj5WDAxc19THqht0YzUDmgHNgGZAM6AZ0AxoBjQDl2ZAC/dL86N/1QxoBjQDmgHNgGZAM6AZ0AwMCAa0cB8Q3aBBaAY0A5oBzYBmQDOgGdAMaAYuzYAW7pfmR/+qGdAMaAY0A5oBzYBmQDOgGRgQDGjhPiC6QYPQDGgGNAOaAc2AZkAzoBnQDFyaAS3cL82P/lUzoBnQDGgGNAOaAc2AZkAzMCAY0MJ9QHSDBqEZ0AxoBjQDmgHNgGZAM6AZuDQDV9Jz3C/dkov9ystNzO1iZdLNlwbT3esS5U2EZuIShdP6CYOU7zvAaYG5dOG+aLtpU/JwaQCp/2qaTX2Xy5Y0bV4pUC/bossWYGzyTjX5d9nCKRbAGi80Ou81KinueZFiEp4JtfsVcBcpnXI2CLFMcfH6JUVGpU0TaspYLl8QhGq7yYRK3SbDl8eRWgkMqh0DRheJXjISeWpegG60RRhVfXyWNlOj6hKlMJPIUzmTJHuity9Ra7o/dQ9MOYiwrKZzjI4W4yhdPBcvz5DsAqmW2G6oClntgkpbujGrYbXbIKwqI9ZEaCYu3gVp/SJIMACTUNl8OE0LR6+F//CFO++l533vdrtdIfvK30YJNhCyAZX3XKqCyovK5JtTFdqUw0hChQfzhW29Dq+0MuWbcXt9BWxadszC0Ig1oDIGMG7mZ5+Q1hS+EQwasSahAk8hq5AgLWffamnBhJq9Qafd6nXa3U47J7TsrUkLMat44bFCAsHmZgjZLUC123ljrhqkIIzHxdlL4dzkxaYOa8Jhs3qAq/S154wi0NJ+NY0XI1xAdTqsCC0PxNpEQtUW41WXSscAzec17RDrctjsVosqpGIMGNe8lY4BMaiyf+O9xWp3uPLVvtjVGEVxhaPIEJYJh9MLk05XvsXmsCgaRkDlIE+/qBqTLAE6bTG70+OIeuOuHCnqZwABAABJREFUMId7VeIVqLF43KFubiKqxbnI4aHtsGqzu1ixquLBYoupnpsJh8Nj4yTv9NpsDlVQGVHWuNAMVpuyt6TLV3pbbQqOogpMqOrRvrATi8Xa2tra29sVaixwMlXoV4WAMYi45IgGWuVQwakWLQZBC1S5KlDLg1qoWPN4PByCgarQMv1Fq9UuBkCIwYKCAgatQqjgxLLCMxAGab7b7ZYgM4RqzJ6WjnB9WxDhLvlUMpAwlSGki1TPis/ttPnctrq2oJOD+EWKZZAtTSk8jmAqGk+UFbgb2oOhSFxoA3WbQWxUlT2gRmIJ1HCB28nAV0gCCBkBccPprgotnmdrwuJ1OyoKPVaVWLu8esYZXc3IYvBH4oJYo+2ZYw0HW9ubTlptDuhURaPoGtXTszMRt9hssUiwo/WsWrSqoVoS8ajLWxhoqw/6GyxWZUsCyWpIoSBh+kTCDpfP6c6Phjs4d3KuUzUGhI/GcFioMsgFu7xE3OpwFRQPFqyq8qwYYxWQCs8mTPNYNOxwihWRcF1ksf2BC3fm3sGDB2tqahCapLMgqm93RbGhL0eOHLl79+4BDhUiYHL06NGnTp2KRCIKh7VyisGJYA2FQi0tLdFoVCFUOZYUGsQUCOl6KA2HwwotA5XRpVC4g42VQGFhoSSBzwzQyr22H29ctvN0kdcZ5+A7UDewFfqc86KVi7adwumu8OKA8hbjZw1EYlwGW3+orq0jalOqMdWiBao/HJs9qryyyL33dAtLI4WH58zG5CUaSKdzWcDtsh+va1focadGufhX6KxBHISjsZkjSzGO99GSQUwCPWHJ8zed3r32FaXyUhCMWlE71RPxvOqR0yKh9saaYw6HUHGqNrVQmYvRaN6oyTe2NBxuqT+jlljlUMOhvJGT5noKK04fWu10FcigESXEKp+brNyc7gJ3fln9ie1cJVIo3PtibkbC/qLy4YJJMcsy1+5/4MIdfhBDxJ8McDXMEJHxPAMfqjHkxPUBoJLOQLSxV242jhEIVq5jgJYaFULFslqDEhtoJWC1UJULd+ApkRoyVAZJNMCFO5EnuDBR7UAd4MKdYQlUAEednQNcuKOxCJUBLfEn/A1w4S6DZECrWriLY6GS2SQMGUe5RKeCCEZCZZwup1oftkSo9BM3doQYCaHeXIRLuOWRWWkVaoxxyLRYgyJUxukb4MQCtbMzAFSCpUAr6FV3W0JfCHcQMlBtdqda4W4xwmuVzk2rPe6yWBRcbPnDF+4MFHNTMwX7wIqJ0Ez0QSXKTJogSSgz2geGknGqharWmmx6MlqFZJhm1dpUYo3hgw6Wf0oM9oURCe+KgErzQWtCVRaL3Re0dkMFbfcQVVaNoEDp1oXQcJMJwOqMS6Rq8SqyRqPF2FftIlfHnbDUdRtl91FEDH+1FSi0lgRyoBPbDbVrDBjDQA0TRgdl7mm+EISEeu4gom4AyLGkdERhjPGpYIgqjYK8kFSdoxnQDGgGNAOaAc2AZkAzoBnQDKhgQAt3FSxqG5oBzYBmQDOgGdAMaAY0A5qBPmZAC/c+Jlib1wxoBjQDmgHNgGZAM6AZ0AyoYEALdxUsahuaAc2AZkAzoBnQDGgGNAOagT5mQAv3PiZYm9cMaAY0A5oBzYBmQDOgGdAMqGBAC3cVLGobmgHNgGZAM6AZ0AxoBjQDmoE+ZkAL9z4mWJvXDGgGNAOaAc2AZkAzoBnQDKhgQAt3FSxqG5oBzYBmQDOgGdAMaAY0A5qBPmbgChDuF3sAPvm8el2+lrZPWeLVWbx9k1daUguVkiBHopJvuCRNQqb7FMmFxqkaMMl4gMrWA4x8H6csZiDtegNCj2IX2leYI1kCiaSuB3JZUY8yZIJZ/pRLqBe2WmLukZ+cmZzuUSyXX4GRPD7Nqnl3LARKkBTgK4PE/PWKTlhtvM3SYeEd4sarN/gqmkOaF0rLd0qL6WntSue4qUxP8ADj3GtBznv7Bj0Cct5DKwsYc5MBb5TJ4oXYGbRS0sin4Eq8gJOjnkMQa8IwjnKiOd1tEZzLzSyTQcXZ79KN5zxLyZn0gmxIcuZ5pXPxxZibdqu16wBoVCnexmJ3OM25Cb185RWguQDUx3VAts2YduaIN06hYnAzXuQZiLS1O93HcHoxL5HwA1CBBFoTqlnazJFQZT7gcznkgccRovsgIUD2IFY2gUyzDPAgtgttd6Lre7/+Z4wK3iJrHkXy7Lb+x2fMTbQGp8hz7JDJK4h5WbLM5KtdSL+u0+i5cv2RugKE+7kzx/kEkd+rRjm/VLbfqKWjo6Opqam1tZWeczqd7e3tgUAA6cPXWCxGBXQm64dIJHIxqNmCuMj+AABG0NikDotGo0BlI2GCoRjgyaQhFAMzUMFs4r+IeZXZ1CWrhj0JFeTgCYfDdKKsKbmMzKQJNE42BNgUUIkpZVvUK7s7eQ8yAQk2Esnp5DI5TgOD8UlfQ5okGQB0NDjPnj0LgTKzra2tpqamoaEhx/D6pLrOzmBrfaDxTKSj1YLotFpDrQ2cEzg0dMZj/FEp+fFoqDMWzenJVlTMa+MdobYGYIBBnqksNo4bvI1Sbp02hxPksXBQgLdY47FoLBKUi5AEgHO3dYbaGqEx2FIHVyDnM9BUG2isiUfFYY2hZXU4gRdqbxJtYbNYosF2seRA9wC1/+am1eHoUTtoBZ/GIQ7w9EJHc108HsMB07Uoyh2xXTUByeF0+VubQkE/2lzm0tEsopvOnorHYlKsd7Q2NdacaKmv6S+cqojhSO105LUFOiOxLpWJrGxpFwdwdFo8nhc3JoHdmheO5cUSXTpeVe0p2gESSBi5DnseZ3LQgid54yeZA24SwYgojCYGPDvmZqNq4AVCnfzZjVMlSFo78FoKYuUGKsm2LAPCWDwvHBXanZ9I9+PGSRIMSTgtrR2xcJS2iBO7zWppajOO0v2n3oHnctpb20LBUNSOTDewipOpwx6Oxs82opoE0W6XvbktaJTpdlh0Nasf/uvu+X6ouvcq4cv8gTQSBMVJTnK+LIAEXLx48fHjx0X/98FGjRxWqWXRokVLlixZs2YNuufAgQMffvghX9E96M533nnH5XJR+fvvv3/q1CkKXIizD6B1mQReXV3d8uXLwdPY2MhXQIJ26dKlzc3NfGU5geI8fPgwOMk8ePAgXFH+o48+4idE87Zt2y6UpH0BGPlIV0p4x44dgzToWrZsGaigUfZgchm61ev17ty5891336WNpIGKBcr0BbxL2IQon8+3devWPXv2IItl//Lpdrvr6+tXrFjBvh6PR6ZpiGzLJQz20U9AoisPHTr0/PPPP/fcc8h3yRX433vvvRdeeGHBggUs51paWn79619T4K233uKn/kKbPQm01+ZwNRzeuvftnxxc8kz9/g02h7tm+4f733vqxIZ3HN6i01s+OL1lsbuowl9/Yu/bP41HwzRWdl/2tadgQbj56/au2//er46teUPIX85gVuux1a+xtEBKIt+tNkfbmUOHljxzaOmzyHewHV7+3OHlz3cm4rFwoGbrUhqYpPJTqDODIhxvoSWROLXxvUPLfr/n7Z/sXPBfMAlOmDy49HfBphpEMJ7gYPPZgx/8FqitJ/c7PPm1O1bsefun7bXHnN6CM1uXRgOI+Fyfz4Dt8hUe2/LRqT3r7U64EucOGHO4vW11p/YsXyCuuVhtJ7av3rDgp7uXvhKLRvLE9YRzp5gMCMtgF4A5HK5TB3e//9yPF/3+x/7WRrngSSTiq9994YMXfrZ8wa9jkXB7S+Pbv/7B+8/+aNVbv7+y5yaq3ZZ34HRi8Zb4ok2xDrESzPtoR+zdDbHNB+M+t2XjgfiG/fHifEttU+frq6PRGJNFSMycbdSF0j1Sk3hlZbTQa2lo7Vy4MbpoU/x4fQI1LJEkOvO8bsv2I/E9JxI+d15tc+K1VdGth+P5bsvR2sSR2oS754JRPXwoQTTWNncu2izYq2/tRMTvOpZ4a110xU5W+WLBA07asud44gOjDJRC5qLN0cVbYvyERN50IM5euaRXEsGygb8P1rcgzQkCMHBa9h4PvrO6+a1VTe3BuPh1Y8trHzZu2OPHE6CevhQsGiPBeuBo4zNvbHvm9W0tbSHWEomEUO019f6XFu763WtbP9pw1OtxrN9+6jevbF6waE9bewi/ewq2+7BIrmXQJZrCoQpVIZUEaaQnafTorl27zHxzd7/f//bbb1MA5bdjxw7ylZ+SjaOto7a2durUqd/85jcfeOABInPQvnfeeecNN9yABkUZo33RlOvXry8rK5s4cWIune7AY51A1bfeeuttt922ceNGXKpota997Wtf+MIXKisr+Qot5CB8P/WpT331q1+9+uqraU5FRcWYMWNYeJw+fXrIkCE5OENQBdIWFY5ef/zxx+nQUCiEEJ8/f/7MmTNpAvmgTS6ze/duFmzQO3fuXNZOJ0+eRD3n5+fTBeYYyEFCjgHUMPQmVweroEK188kwwIdNmjFJvvJxmFzvJdJyPLCUfeKJJxgSLNVYWoCNXqav/+3f/o1VB60gfd111/3whz9knORWyF4Ce0Y/GUEm/rPHpn3qb+Z97b+HX3O/v+5Y8/FdV3/533FgNxzcaLU7EcA4g4+vfmPYvPtdheWJeFweXjKqL62diM1wonTr9m+47ps/cXry6/asdngLT29e3HZqP5dAhHRMJKwO19GVC0bf/Pig6bewxoj4m7ylg8vGzuqoP91yan/hkHGJRAzhmVbFaRc2FBPqdtwdT879yg9KRk6rnnp9LNhOoMy1f/LDq5/8Tn7ViHgkzBKidudHBYPGzHj8705tXYxvPh4JwHm4vakFHe8tdOYXCx9gDjcGPNcrzh7afmjjEkOUdJ1KQR5sa9q74vVQe4vN6WpvqDmxa80j//C0y1dwfOtHbm8hh6McwhRViUWa3b5u8at3fuYbs299cNXbz7ncXrzt9aeO41z/+r89zapj78aPWhvOTrv+jr/88euPfP0frJZ+O5IoISfembf7WPy+a+yThlu3HYrVt3Sebc77+v1Of7Bz94kEnmPDad2J+rx+sq3QZ+ErIzFnmxj1ibwtB+N42VG9yPEh5dbP3+7YsC/eHhSObUYUn0drElsPidGCTjvTlDdnvM3lsNQ0JVoDnUPLLVwr6HPMBoxVu+J3z7Hfc7V97d54RzBv9/H4X33K5XFZdh5LeNyCNXzq+07F75/nuGW6feXuGP74ikLr+CHWupbO43WdwypQon0PtbfOW7ur/VhNSFxTN1ZlwNhxMPDJW8qmjfFt3NNe2xQ90xD5yycGtwfi2w52eN1ELuRw9WYAFocRm/X9FQc+9/D0264b89bSvR63IyFW2tatu8+MG1H63b+8Y93WkyfOtK7efPIrj825cc7I1xbtcbsc8ZxDTSbYuOiZnNEfabhD8r755pu4LefNm4eYe/XVV1EY119//bBhw3B27t27d9y4ccgRjrloIzDifMWn+JnPfAZ5RxjAhajlGTrL8zR14Q8mrgCEIEFZ3nHHHchlakdBkkkOqg4ZinRGZWZZ3YWtuEQOmgwGqqqqTpw4Qb133303X8+cOcOKori4eOjQoVDK7vzE4mf79u34sCdPnsxXNpoAZloxfvx47ORADVMpdFEvXmFYRekCEmUJQlZl/CShmmVIsFESePxEL7MUQbsjlPmasw0AcjF27bXXUimQZNXkA3vOnDmMDcYkzM+ePVuGowDYLJYznNQIt6x1JUvUy2qNTJZDgwYNYrEEb4xVOhrmWTLRHZMmTSosLEwOqUoXLUbYRX5mtm+6e51fnuhwa0f9qZptS1uO76qackO4vbmgejTObHzAwcZai91h7/Sc2PhuxfjZZaNnRjrapJvzfCN9880YJpH25uJhE4+seLlo6ITCoRP8tUfR4niv8f0b3iXhY4RCNLHN6WaNARRkus3uJB4F6VwxYS4u+Xg82DcQz7eKtIxHGw5uBuTI6x6JdLS0nj6A091TXEUTEokQATxWu6tw8FiHp4DIn3BHi3TDE2iAiEfcI9xD7Y25DFdmDsbCIZx6E66715hxXXOTARlsbRwz5/bmM0cJNwq1N1eOmrL9/WcrRk0uGzo21NEiFk653MTcdLY315dWDvH68i15Vc114oQSj0YrBg+/87PfCLS3uT0+Ink62psPbFkD/pETZ/mKiinAgMgMaf/OTUAjxO+Z6/C58hzWvPIia3ugc/Qgi9Oeh7sd9zZebZcjb/WeBLJ+3BCbP0QwcWYNzWQvjuIep2XHsXhpoaiVCwIAG1Jm8boEbH8wr8iXZ+nMw5/Nf3Mn2lBowktg+I9R843teW6HparEiujPpPqU98E6RDX7OweVWo6d7QTrQ9facfaPqrYu3RYfUWUdXGYhNgZgCOL753LbUp493BXDw8Bx2PICkbxAuHPycHEWpWm53Li+2NIeG1blYijKKyrgj8U7H7qppMBrc9gslSXOto74+OFup9Oa77XWt0RwdcN4LkGK5Znd1twaqizPz/e48kosdY0dLB5wqAeC0duvH5PoTITCMYJk6ps6Rg0rLinycNipa+rg5spMp2Z3+7Lbv4/dOd0gL/E/hzC6dv/+/SNHjvzGN75BBAVKffTo0aSJqUC+jxgx4o//+I/JN42wC25jJP7vf//7V155BWli/oR6JgCdDcGNNmUzf8ogQUVIHz7RuISXkAYqnsvNmzezkGA2oNjIpy/Ro1nKX2phSxEkJUECHpYNYIAcXNTsSw6fmzZtQs3LuA5QyUyc1mh6uEJrHj16FMWGDiYHR3gGWjN1qOABKh3BsoEO/cUvfoGbH8lOJrzxK4ISMKSTy4CTLobVdevW8UkBtPvChQvTqhfjbOyS8YYoB+eoUaOAB5OmHdQ8SyMpfMFGi4qKisg0C2ScoJbMNmpEncMVCXq8oKDAXF6i6el0orymT58OjTSKVcdLL73EHKFwZtWxF/bZ5HTj87JzDaLMwlRNbABIspEmxJ8gf7DQfGLPyQ3v0tUOt484bJvTK2Sl1Va/bwMBM66i8mzjxZmYKc9NMeTyxC2nIX9j/YGN8XDgzLZl7WcOe0oHF1SPEkjkIVvo9kT1jPnbX/73ve/8rHrqTe7CCi4aNB3diYfb6Ss+vvo1nNxGUE2qhwVjvIsBn24wCLs43PmNh7awxnAVlMaCfnl7wMmNC+EWv7Xd6YHS+n3rW07sYbHEV4fLd3zNGwTVoOkDzbX73v05Wsc476aKllM09eLcymwTg8dqLR89hegXcWmle2NUlAwZ4y4sjUZD9EJHS/2JnWsiwY6Daxc1nj7K8oMLL91l0/s/s5kS4yTf2dnR3sr1ASRgLBb35BeFgh3iuQrGXbP1NSeO798xdsa1rQ11BM+0tzQteelnwQ4/v2ZUIxXGw+FINBxilskZxzwVdF18Y5dzczMQiETEWcMYp6n2Zk/bxA0bQR2vrIwRElNSYNl3Mn6yoRPdCenEN+85Ht+4P1bksyqJwE5ndgo13BZIsJa4bpIdOYtM5x5E4mEQxw0tYu7I6Y6MRCJTGObAXF1iWbM3Fo3ntfgTBZ68F5ZHm9rFCiQ9gtICasTTw8/+U/Hm9s5jZxM7j8ZDkbxdxxN8EgBztllEzmBSHlFcdsv6ffEJQ61lhdaa5sShmkQ02lngtqzYEd92SFzlSKvy7M6cndFootBrHVbpjBKww2Z88D+jYusB/7Pv15UW2koLbLsPB46eCR46GaRATEyUDDeGd0aTJY7Hot0fZCEhfBfxWL7XEQyFpS1xGvU6V2w4inCfNr7iyImm7Xtrtu05HQhFIuFoIp5hjZgNhSIoVHPGkdNz+lzu+4AQ7oBEcyDWSSDfkZjIYtJIdtQA+chxYlHIQUXJTxyHRLA89thjeD1Xr15Nb5PPhlpFFMqNAAy+yvwMPtFqHO8IL7nvvvtuvPFGhgWrCKI1Vq1aBSo0EEKEBNcB8G7iz6bSSx8cL42BpsnWXbpY8q+UJ1AHhPiDieEpLS3lEsQ111wDh+ARq+y8PEB+8pOfJLaHMuh7WnH77bezizyU4/YmlAIy0XbJli+bThcqYFhjDB8+/OGHH5Y1kmOcuZjhUZmGcFnmkUce4dIBrE6bNu3BBx9EEMtYGlQp6jNdngWt2W1yXmEDhJIZqePBLzNhVaazq0fsDRUYz2yDJQkPO0wZOfjpWWbH7373O64JlJeX0/tf//rXmThgJm4KMimccXXUyIYRNhKXHjYgkSXlJzqGetM9mZyrArkWi0x79G9G3fgpnMQtJ/fRTAQcTl/ySWHZ5vaNnf/ZE2vfEvndfXfOQuopDjvy3JjqLl2HqfyKoePu/FJ+1cimozuQ4JxIkw3EI6HmozvH3f7kyBs+WbN9KXd/jr3tC8Pm3hcL4fWJ4e2mUcGW+nSfMUKHpuu3gpxIoC0eDhYPnxQL+b3lQ2Z+7p9HXvtw6ajpzcd24fgnhJ3AGC4HnN68qGjIOM6ylVOun/LIn8UjQRZLEE7YD3FBpPkpuY2XSFNOjD3+ZbGxEIJracaoS1yH4YyalyCCVtq2llSPuPqRr5UOGV17YKvD5TE6M5Mqbai49DdjH9w9XF0UTlNqj0ZCTieTJSGOup2dC5/+r0lzbiyuqJp7xyOf/MY/3f74HzM3m2pPOt0eGpBZheKpUc6uiSnnpphrF9847Jybmy6Xw0EGVw7ZQYzkDDaaiagdVWW9c7aN2Ouh5da5E+zvb4oRFVPgteB5xed912zHyl1CrQlPa3Yb1aW40ShuZt54IHGiLrHpQOxMY+f+k4mbp9NLqN7YkApxAzNDWNrD6U55mIvE8yqKLJ+Z76wotBB03hbsJLSGSBsh3FMd7wbA1IF2twckXpflusm2m6bZuG2A7Kpiy31zbbjhD51GjovYcf7wFy/fjiLsnDXWhof73qsdxCAFw50sUksKLcfrEnju0e7pbJnMEXMf+IRFVh0yR4x7VthWTnDWcUO9D95Q+u6a5hGD3NdPL3x7VUtRgb24gDu2Mz8cyGmSyfy0WvFLCHjiz4YgdxI7JQ4d1nyfa//RxvdXHnro9klM1S9+4qpVm46fbQqMGFxiM54vk/7cxJskggiYYeemmxHRmk6/iLKXmszp2sqsPP3KjnhY8a0i2fft2zdr1izEMT5jVBpSg9BhyrA6QRtxRENF8YnLEHc7mfyEmDar5qvJJmk286cMElAMHhQkkpHaUclcGSDyBCmMTEFxAm/s2LFTpkwBvKw3g1oy2IV2QQIuc8SZKR8JNCKmCGD8BHKpkwBJaAQ51AJCPtkF1U4B0iyNaBRlMsCQ+i4SLe4fhLt5JwA9CB7ZQRIqDTHLAJh+Jx+c9DKNYo2BY1sGrmTZrakjlyWpTm5IQ0YCYEh054kBRtr8TNf4heVNy6knYBLGWLmx4IExiQecdC6fBKGxBOI+B+riagyzjKMGbNMWcmQvpF5Xckn2NTdZ6YXNMXMoYBYmcdny5o69JAz+0Yunty4xgkyEbaevqK3msDO/hBh3gk/oo6Kh4wfPus3u8pzZtpQ4bDyYvZjqgyyGA/dNuosqcdZ1SX55HBJfjIxEJzEnCHQO5OXj55SPvSrYdJYQGrvbS5AMoWw0h3Bzl6+ok7iaTMVT6i3jZBINtPFImYLqkSDvqD9Zt2et4JC7Augqu9PhK2o4sKF6yg3TH/87aGctIfJt9kig3e72scYoGjI+EQ4KpLKlqdedXUn4lBvdTZCUw+VFSZEjiBZh4vH8sir8eKS78rKpTlqV9aX+ydyMxQvLKhprjqMK2Q8IrB883gKHy73yjd+NnXHNrY9+Fc8tYe5nTxxmIcwKVK7WslzWJE+3y7Y7ubDk6rK79FrAWI+JqOt1++Jo9EkjUFN5Z5sT4Vjnnz/iLPKKC1LYH1ZpnTPe6nbmbRK3qwrpmbMNbMSZjKi0EqTOaRCn9b6TiRmjrJ+/DfewULfcdYoiZzN4MD7FPSniXlXkb77HglzGsU0cP6q978Y7tXNBgOpcTpHgbheq49qFcfYR8OCMm4DB73HmccWAW1c/c6vT5bTwlB6IDYRF6xhvo6utPo/okRxv4mBgHO2ol4HvdomYmVXb2wt91qljvACraYyEop1//8WhJfl2JqkIlcliGIiZxb90Ns5CXH4rLfKePtuO1JALSJ4wQ5i702lraQu/s/zAHz9x9bSJVQTMbNlT87//5JY7rh/Dg2VcLrsxztOpTJbthnj+dEt7EKXnZ+2Ljqc5DETc6viDeYQIHtnq6mocxsRFSH1MyARaBC+ybKrEgAQkVObZZ59F8XPbqDSiFp44Exh+6C1bthDjQVwEQplHdhAXToQJX7kIgKbkWgG+fxQzd/7hycYHDxi1SHq1Bjw0GeSsXLmSNPebotLwWCNtCbbmnk4+caXDG9ERK1asABhl4BDFhnt+xowZOGU3bNiA4GNHLPRai5JMySTh14TaoyypjjTIWZ6xZsATzEIChrnMYpaBapQ6/c6zXEjTCpZGNIQ1klyEKAGWuhGWi0BF6aJ64Y0lBPvCJGxLI7TRTKduVmFJAACPefTaa6+BhJsx6H1iouh37lj9/Oc/z8NkmDKU4SvxUSUlJUy0vl6zKWzgeaYs3G6VQPsGm84c+eglFHDpqGm+8qHEi+9c8INYMFA5ad7Rla8SSIOIH3njo7sW/L/SkVM9JdXnIlXOM6f8i4WQcV/FUK6x737zhzxGhvVDQoS285hFnGAxq9PZcHBLQdUIm8tzcMnv0MfFI6eig/FM1O/fOHjW7dFwx4l14kIBijkX6w2LLRr0h/3NDk8hD3lkkdNw8E1c7+1nj42Y92B7zZFELMxTFY+ve6tm50clo6a5isr42nBgLUsLFhjEzASaaqqn3iBc3bneLOIZmtEIDuaGEwfo7rKh4ziWoX1j0TB+nqKq4Xmd8VXPfb+juX7cvLvxdgsFlOstbnd4B4+a9OGrv45EQtfc8cmOtuYzR/ZFQsG1C1+6+wvfeutX35s67zaasH7RgsM7NxYUl5cPGk7MT66XQSpo4eSHxuXWyaY28SwUnNZTR9rcTsv+Uzh9o4FQ3s3TrR9s4RJlXiiaN3+G/cUPoyjL0gIhN3Nw4uTkTGDC6GrLtJF2ntZyqj46epD1ZH189Z74tiMJkJQXCqgl+eLKAHygdwHGhqCvb000tnXecZV9y6HYsm2xsiLWg0Jq9h1s4Up3WqqKrcu3CRRjBtkqi9FLlpdXRFv9efMm2U41Jrjfd3CZ9c3V0SkjbR/ujPHQm8kjrOy490SCu2lDkc7Vu2PszP0GfXmSFxT1uoUjhIzn1TdHCXkfP9zT0Bp9e1VzJNY5c5zP7bTuORL4ZWs0FEnMn13cEco6cLxXBJfMZPHldDjGDC99ZeGucCR2z41j2/3hnQfOXjN96EsLdxLyvv9I/bptJ++/dWJ9k/+XL25Etd998zhKZn+Z6JK4LvNj/wt3AEqle5OxSbw3G5tMI5E5SaOJeYwMDyTBv44v9tFHH+XuOjazfcrlMgYRPShFasTpTrQMMAiMQakjjNBJ5ANTSp/bbrsNnZRBrJKJP90E8ICBQCe6nTRUAIlACJYQcIUmIxACmQ4kMMMbmnjChAnsQmES+N0RxIMHD8ZNS5Q5xchPF0OK5bEMk1SKoxcmIY0dr7rqKpCTwxpMXgFAEOOPl2UYCyAkh4UZ8p2GUIyVEpcIyOw7qBe2iLpYKnBrMvSaLMlMBgBrNrBRQKbJp9iFRnKQQ9XQeNdddxE5Rs9yRwEDFcAskD772c+ywoRGPrnhm19ZfhCPhIg3W5QDhGqrEF0QjRBbUrtzhb1yBLdyEh4z6sZHz+5aWTXpOpzEFeOvxisc8TfjDx5/1x/hSO7LM2zPxlGdzekZc9Ona3Z+iGovHDRWPKDdYi0ffzXrDRG6w1PboxEAE8hOSVYa4qbVvLyKSdcQU+70FRYOHe8tG+zwFlCMxvasQOl31hKugpIxtzxB6AuS111UzkNmzu5ePXzufdzvy3UMBHHFxGsIcw+3N3IfMIMctAWDcQTwuHRbyciprFL4JKBfaJlcbdCSiEfKh4/nyMytnDjcRM3cqxePufNLhk27Dqlid7pn3v2Fw5uXotrLho2L5hahZIIIOG4EmHf3YztWLXL78kdOmRVob2VRUVI56O4vfDsc4GlUtlDAP+P6Oz2+grMnj9zyiT8ikIwFSV/3ex91FKM1Gu+8c7adp7VwN+rEoUJH3nmVfffxxLWT7HQSypIyPL8FfXz/NXhb+1D7XthGquYZ5zwnkZ9umW6ra+6cPspKqElrRx4JwMgNnKh2nh5DBgtSjuvckzplhBXRSQgQIT6ThhOUIh4403cbxsFJ0MuOo1y7y5tqwLsDYg/FuV5BANLJhgRlwMmtwOKp+dxB4xFksjgBqrwbeGiFWI1wuQC0fXwgOY8JSeTUMZ7ifDv3oeLexuN+3/Ulm/cF8j3WKaO9UH3/9SU7DgfmTMr3ua38mkt4Xb3MeTMUvfeW8Ss3HvN5nJPHVbV3hBEcHcHIjXNGjBzSygMiHXZbKBR9/N5py9cdGVRRMG5EWTiSsweUnUep+aXfdIaJwExw8OV8gAwSh+OkNJnk8IkQQbRRgF+5FxDZQYKfyDGNmAm5F6EXTz/9NBKWwuSYv6aeYC8c2+yOKeoijQAigeIBDPlIYayRyZaxpqQhqGe0KbI7LajAY0cAINokDL4CA1QIX3BKpU4mJSlDDsW4kgB+uS8J1h4yn59S2diR+zUJVZfGU9mFMuwlmUQ+0l5ycL2TQNPTg1KmJ5chTRlYJYEypgDFKJw6VHZkd2KZuH833Tb2aBR2yIEreseEQYJ8MvkJVGa6x76pfGV3EKK2oZQt9Tb2ME6TuS0VVlncggfCMStpxybMQyC0QyaziWIZVMQudAe1sLiS4yoDI0x15vnfP7/ho91nCr3ObB6thbRFJeMwZmQjIvkaCwWQlUR6MOgSwm2Zh2ObMUSMRwYnLrCB8OoxFYu2nfQ4xSXdHpxf9CsHLm5b9xYi2Qlnl4pW3GwKkkScAB58wihmh68Q/NwPKrGJUHhGVGfC7skHsMCf8tkMSoOR2J0zh246XN8WiHZd+r0ovvN+EMdRuxPhLqoDObEaBPOEA+TAJL+i3QlhJx+XvNyTNCWRzOLWVauN6x5pQe0Ix2aOLKsodO8/0+J2yojq8yCl9oV304qIr3gsYne4BIxwkB5iajI50b6iLVabK78wGgrKtVNqZs8rRafT9ddNrD5R77eL4N1MNuamt6AIvoL+dvHwIJc7blDHYQSoyPdwKOAmfsbpCrS3ZDY3gcVk5K0xn7p21KQhJXKWpYsVhDC2e+1z7/7qiwa3mTVXVEtwNhiCRrQXoeG44Ym65v5OBCUbOhKNyeNlOBtkqinFyq1qxFURXgxWu9/uEAFywnRqGyOdOBPELjsRW8J84RksMo0Ulo9hkTEzMk15vgKVT64hBIX7LrWaRL9YY9HgiEm3tTYcbW04nhax1ILspiaeIQNjKHWWQwh6lh8wCSoOGASigEpI9jgPkxF3U3CJgLTYlxiVeGfqDAM1EgoMn3ijp6D8zOF1Tlc+szzVdl5QjrAiwlGMl1jk4X3nmJzv5Z7gzmBI2ORXngIZCCW47YGGZLAxXJ3ugknznqg/Ke4jEg1Of6MjC/JdqE5/gIfbWLkbFTXvdFidDkKOxaGpzR9mJBfluyLROD9lcMoDFMRyKXX87E9MnvcZgTOzBhutGxAed8kzhy+T8OS05IhPXO9mAZmQcqpHptqv4jgYDktxSe8ifaR98uVPfJKDemOTabUALm2NGiUkyRiKCkFGJl9RbOwrIclVhwlPqli5L59sl65Fya/UYjIpazRRQaxU5MllZKWSVfKRs2ZzlOBJywgwZO3JrAJbMslPyem0LKstDFFc+cEmAwBILNXkp5wpZLIxYGCehOwFtQByby3ib6VSRjyfHMR5sjjDn68iNEX8YExP/Kyc1HIyzkWlchPuhgR4AAckmSeFOMyjiQX/DOwk/JTpUuos5ALtYvbmCjNQY5FufznIeeZje6NAbrXJxQ+UctYRAcrdB2rjZbRgtMaIP+HOy+42djU/R/9xL7I80IkrGJy0BWMMehEqY3jFaEsiHuCdR0m9kCNo51cDMCJkjKHK3EzgYgdryDihiMkopqaQ76GO9j+YuclzHuFA+qQRkW0dQpzxVUj2rqmJmCMFE+eTlZNvaCdqp2r+eE4LURNgk2kTj4yTkegoL+UvruJcPsISMB1JTAodeQGTooCUrAbD8Cehin3DXXdF54TUnpVIPzqf/AAYwLd3cMuqOSo6W/1COJmE99w/J9+pvq1dnC+YiBw7cLdzyA6Eoh1B8bw78lnUMQaa2/C/gLw/Buv5PAwg4X4+sAH0zRhVXV0le9EEZw43M2H+lLNEMqRkqMmQkssAzPypR35fY06GR13JtZuQepRJzu9reJew3wMGc1sWNvP5mpy+hKm+/ulCVlHtUrjLqpML9DWYHNg3daSoiz6wdD86Ienw2k+a0gDU46nh3ahMSOfhN/YQDaEp3fpYfs3BpwnJqL4XJkWB5HPWubaQm/xDDsAmVdENo8cMPDcfwW2OiqT9cp9EmpuVyv7F106OOSXJ7D8eTWjKEsmNoZeSOupcFWbmuawcpszaBbzues1MMsxM+aP5U3LTuvfrw/97VGceG87Dcz7W837qQ2iXMS1hmGAobYInTf65eXoZS337c/LMk9JcfCLTk6hP6xpmn8Lt8gP1aR3auGZAM6AZ0AxoBjQDmgHNgGZAM5AlA1q4Z0mg3l0zoBnQDGgGNAOaAc2AZkAzkAsGtHDPBcu6Ds2AZkAzoBnQDGgGNAOaAc1Algxo4Z4lgXp3zYBmQDOgGdAMaAY0A5oBzUAuGNDCPRcs6zo0A5oBzYBmQDOgGdAMaAY0A1kykPlTZcwHa5DgvuABcmtwlnTo3TUDmgHNgGZAM6AZ0AxoBjQDA5OBDIW7FOuySVqyD8yu1ag0A5oBzYBmQDOgGdAMaAb+kBjIULgj1nmZTnNzM+/g5LWUvIu+uLg4Wc0PHI7EtQBjGziQLkTSjfEKgCrBJwO+sDkDJycZJ2m1wBQalDjVwhv41mg1z8rlT7wgZKBuYAMhY0dCHagwBS6J0ITK1wGLthuqIFawqxqpWoOgU2twwPZLEjA6RfQSr9ZKyhxoyS6QAioP3B7AaCWZXZ8DH6qBUMzLrjGgsN9FgIZCc3mcPfrn1W8qG5GurbSFu1TnZ8+e/fnPf97Q0MAb4Hm5+l/8xV8MWOHOGzdZY/AGaZCny07OygOPd3DwGs6BDxVOYFJChVvFk1Ap4+DkxUNAlZtCqHIsKTSIKcjkxbeMBDaFloGKWYUGMSVxZt9XvJu9Ixy12aw0O3tr3RY4K6ic6byd2263RqIJoPLGxEQWb//uRthX/yNegpFoJJYIRGKC2KRXh6ioUiWxQAVhOBqLxhyhKK9OFO8VV7VhSq024OQBYM4hDAaVLPCiXIaUGK/KGk/DAZm9uQTvyw1FrDbxvuqBvCXiebzQNxL2h4PxhKNDQcv7prX0C68yj0Yk1IhtABML1HBQQHVEfXDLypoX/apihaEuXmukbuO9yLzdmc9EIpaXMF7Nqsg4J2LDkrIbQVlgJOIxKR6yxJi2cOecjRjasmXLnDlzRo0a1dTUhNO9paUlSxx9tDtqeMiQIR6PB5BK+OojnGBzOp2VlZW8o36AQ5UMVFdXMwxiMePV1X1EigqzDABYdbvdQFUoXuVYUmiQtjKzCgsLWbmxzFBoGagcgJLfnJo9rxj0+XzZ2JFH7lGVBbNHV/jcDhVKowuOctGGDALh0HLfVaMrXHabQo0lRYZCickZMRyLDy3NDwyPdYRiye/8y6az2FeoVcSguhMur2ANReNjqgvz3fZIPOGyW7PXmmYbGfMKZxBmUdduh63A4yjNd7EcUgnVEAcK35LLcGLl5kh+O6XJS6oJ0c3egorhE+dZrA6Fy2AxilLFkGI5S2ciVlo9AX2ZXzTIZnfKI3OKO1+6mFqJiWiLx8KVw2b6CiuLymqttrSl1yXQqh7wllgkVDl8hsPljUfDdqfHmPyXqD+NnzpZ+ip1KCDZHS6fy1vEiLXaHAqhSh8NK/Y0mnfJooyBqMvHKL1kqZR+THv0oAA4Jk6bNu2111674447nnnmme3bt3/5y19OqbacFwLtyJEjKyoqSCic0mgsFKHCcwPY0Ov5+fmsMbCsCioIgQrrapuP2YKCAlRm95JUTb/Sajaar8acYYWGo9pDoRCXhhSaBSfWFA4A2VOMAa5lKb+OAVrlUFldZNf7QhyMG1TkdFhRw8r8Ocb6x8YQUieHYc9ps1UVe5CtdiHalKlXSaDCAY+7KZboHF6W73XZUW8Kz48Md44kdptN4SRiRVTsczW0h3wuh9OOV0+ZbYhVyCqwEO4uh7WpPXS0rs1hU7zGwL7C6clpKcj1llA0czaNAY6+HD7xFnyZmdu5YE+mEl3DMfmCXzLPwGJ+8aBYNFRcNcZqRc+oGUZ9ANWSiEeLK8dEgqPDgWYjukPZkSQWj9kVrgS4aBMLF5WPbms64XAX2B0qhXsfzM2Y01Pkb6k9unup0+VNcAlmoG7MpkgwUFw+GoAM02y6P23hTpUcwYcOHfr4449zcJw/f/6MGTNmzpxJvtpjJQaz35h+hOBzQQDdRjp7g9ICqgWNpfBoCzapLIk+Uuhxl3IQzGqFOwaZfrCKG1thpzOu4IHmq+omQMIqy6H6+nqFvQ88aU3hAMAUZBYVFXEJi2WGQsuysxR2E6YY/6DNntIGf/h4vR+VqdDjHo8Zi2p1opVgBo/T7nLYTtb7HQ4W1aqGZx5Xd7FltSlbqbJaYT1V6HGeaQ4Qf4KGU4WVvoZYu0PZ3ARZNJaIxhP1rcFjde1upcRy1Vws3tRtHJjEWijeyXAVFwfUjQHlRxI63R+Ood2zbH0k3NFUu/8KEO6cNmIhwno6WmqseGcU9Q39oniNYbEQfGS1O0P+pmB7nVpiORorPG9y9omGgzabs7XhWN3JHU5XvsJQGfXCPRHz+spYW9edOOD0iJiZLEd+3+1Op4f88YC/wagiK+mexoFYMr5r1y587Y888sjzzz/vcrkQRh0dHV6vd8qUKcq7RAmDaFbGtFrlyqzGoEJ1JQ0iidRCNRGqbT79gkE2EmYV2XcWpiQP2ZuSFuBT4lS7bMM4OPlU23asyQEAWoWWwal2YkpsSs4TOLBxZDptVpXCPU9ctFFIYMKKxx11beHigPC2qhNtBGSygVb8p2JDqGNSQIVSnM5qhXtep13hGsNwOMEnf2IMKBXuhJ8oZJWeYXw67UA1huuAF+4uFV3P0cjmcKvVlxw2Lco97ra4zeGig2xOt9WuUrgrhsohCTZtTtCqJ9YSQ+WoOIQIGwCFT6sB1eH08DfAhbvd6HqH0+pwege4cI+7OkQ8T9ZbGp0tD4Xjx4//xje+gWvwz//8z1FFTEVWvNyZChK1x8qsm6YNaAa6GGCUsimkQ601CUzaFECVQsW4cpsKDdJWOkZh36i1JtjrhtcXUKV9OQCUfMqxIzErZ1WhQZNYAZUxYPwpYUBYVmrNNGjiJKFqU2hKQpJ8qoHXdzyqwWdYSe4VhYBNs2qhcjjpI8uYVbgJawKquamyrfDcISF1GRT/sdwQf6qgqrfTadzmq6Kn0hDu0m934sSJZ599llvTxBUqI1KC2+mefPLJsWPHqnXsqWdNW9QMaAY0A5oBzYBmQDOgGdAMXLEMpHGVVjrUBw0a9LnPfe7WW28lZmb+/Pm33Xbb/v37ubh/xTKggWsGNAOaAc2AZkAzoBnQDGgGrgAG0hDusjXc6ke0DB537qLjgS1s3KRIml+5VnEFtFhD1AxoBjQDmgHNgGZAM6AZ0AxcgQykESojWyfV+YQJEx599NH//M//5D6GJ554ggfL8KuOcb8CB4CGrBnQDGgGNAOaAc2AZkAzcGUwkLZwR6nTMm5L5dntPE+GrzxSRrZV/nRltFuj1AxoBjQDmgHNgGZAM6AZ0AxcUQykHSpD68Ttu4nEsmXL/vqv/3rTpk0LFy7k/lQy2a6otmuwmgHNgGZAM6AZ0AxoBjQDmoErhoG0hTsPk8GzvmPHjl//+te8P5WQd97GsmbNGjJR81dMuzVQzYBmQDOgGdAMaAY0A5oBzcAVxUDawl3Gw/DGe54kw2s+keyNjY0VFRW0+g8yVIbVyIULEq4tmJlmIjmzv8aACUYCSIbUI91fCGW94LwQKmtCQJoFZJpPmehHwAAAbTIM0qA1GtG1WE1O9yNUWXUyVHKS8cv0gEKbJV30TbIF0cB4nDaLhnf/RKaZTi6cm7QYPYyWpOFNvWTJTH6UUE2EgM0NsAtrkewJqN3UmWUMVAargsuu1xP2I9QuYAaYC2EAsUcTenw125XjRA+oAj4jAT7liOVB1N3pHANTXl1cHDJ7GclmHl0kKzUK9lJSOaQLDYIQnPIv+Vdj+JyDZ0LttUXJO+YsPfARSirM7jaZEcjlaM/LM8m/sJhZPmeJCzGQ0z1IBQrSF5bJGbzkitIW7vIO1DFjxnz7298muj0QCIwbN27q1KkYVXhzqpjx5zPU4yvVkSPFU3J71KapgldN0czk2jnQ8spY8iUGfqXhFOBdkjxsRy2AtKyxcPJ4eMlZ9+EmkXC73SZO4LHcogwFwN+PqywAFBYWJrNKDndNlJSUAFLilytDqGZ9yCYz02JDVWGJDRpNGORALGh57xgNkZQCOJl8VbVnZif5taYmfqfTCZ8gBzbNkYMhM/sDaC+LxeXxmcMDFeRwugpKynlHIZLI5c3nbbQkeK2g25ffP7CZbh5fYVklf3aH04TqKywhp6C03JtfIKB6vCDkV4aT0+Xup/NDp83uKCytKCqrdPtAlaSlxAy18yZiMiHTV1CMn4Y0UPvxSAJLFpvNV1SWTCy9DDB3fhG9n9QEi9Pj7SdWzxt3MIyPqzur0+HyeovK+eOtj0h2vnoKy8T7SpPJ7y59pfwPdm6FKyl0u5x2KdGSkdvtQnUwbLwe8RRp+sjjclAy9y2mRo/bUVbsKS3yFBe4zTcNgznf5yzwidkqyrgcPo84B9EogTO5Mf2UBkxhvsvnTUYo0gMHoSQGrnjFvEms0d15BT67zy0Ght1mKSlw8lec7xDvTu4nMs1q7eJd8Oc2ut7lyMt3d81WvvrcFrdzQEzNNG5O5ayPQt2zZw8vYBoyZAjiABFAK1evXo3HfeLEibLAuXannGJHyjKT2UjLBDkMRGMsygxxniBlWiWN2jO/9kUCrfPBBx+UlpayMiGOnxrBgOLcu3fv6dOnr7vuOhTwzp07hw0bhgzisZi8nWry5MmU6Qswl7XJMmbfvn2sowheojA68uDBg8eOHQMnopNHdvLE/VmzZtFrR48epcsA3y9QYXXJkiUmq0AFXmtrK1TPnDmzuroa/KtWrRo+fPjgwYPPnj3LkKisrCQzufcvy4aSAvDDOGd1Ch5GeFVVFcMAtBB75MgRfoLk6dOnEzC2cuVKBDFPW4pEIrnHmdxYJgVDkTWkXE9KbpmkLLZHjRrFCDl+/DhlQM6o7q8xkAw4m3RnPHZs37Zh46bEo1E6y+X1nT6y/8T+7TNuuMuTX3h458aqYaO9hcXtzQ1nTxweOXlWjg+6QELmgvDkgV0czybOuam0ajBQOWltWvpWa+NZlhll1cMmXHX98f3bo+Hw6KlXh4MddaeOVg0bk4jHhPzJ3dZptdrbm+vXL14Qi0YGjRg3dvrcaKTroGdzONuaGxhLgsymht37P5ww61qn23vm6IGSimqHS+VL0VNsscGtIxxo373q3WETZxdXDY0ZaNnd7nTtW7vI5SsYPmlOLBLCpYSP58zBnVWjJvLWwH6cnijyQEuDy1dorCfFWqj+yK764/vo5yGTrykZMrr2wLamUwdHzb7V4fbFY/1wxEuR/EsUM46Ztkgk9tbSfRNGlY8aVhIIRq3WrpFss1obWwKo5FA4dvBY4/hRZXa7jYTNahkxpDgaT+RsxHOSttusuw/WHTjaaLNZkeZzpg52ux2cblDqa7eejMUS1101Au/wviP1kUh86oSqYCh6qqZt2OAi/MQ5w9kr1U6nffm6Iwj3GZMG4b7ee5izZN7UCdUgPFnTOnxwcb8jBDY6CGnuD4oZ53XZ5BIOgb56W6PHbZs+tqi+JbxsY52hj61jhuUPKnPH4mLt0S+b1ZrX2tHpdbPMEPUbqPKO1iYa2/OmjxJLD8TmloNxjytv3GBrJH5u8d0/aNOtlbel7t69G+FCYujQobNnz77vvvtQrtjJ+ICIwmCTu8sECri5uZkcMx8twlcOCgan4hMJ8qMf/ejDDz9kpsn8dNtyifLYROAuWLCgrq5u/fr11CUdlgidAwcOIONqamqWLVuGiH/55ZeBSuFXXnnl5MmTFFMO5hI45U9IdlYO4Pntb3+LYqNrJM6PPvoInMuXL+eMC1FbtmxhyYFo4xYFdDDcXtay2gImq/X19Rs2bJCsAsPv97MaDIVCAA4Gg+SvW7du48aNKONDhw6h3UmoRZKiNbCh1FlRgBDt29bWBhL6l42f0OhvvPEG5L///vsEjG3btu3w4cNQza8p2ldbTJxyPB5gsC6SjPHJiujtt98GLfgZn8BjHoH8nXfegWry1WLImTWiC7wFxZuWvb3wd/8P9zBj3un2nDm8b/Pyt/0tTR8u+K3VZlv+6q/bmxtdLs/yV39Td/IIKjnHXQO9qMnd65ZHQgF56DrHT2cCwCcO7Fz73suRcAAdv3fTSn9LY0dr07G922yMIl45nsON07/d6TywdV3DmRMcd02iuBrgcLnamure/e3/87c2Q+bm5e/s37L62N7tHEkO7dgQjUa6znU5REtVcBsNh7Z88HLI37Zn9buBtiZ0sOG09uxdvbD+5MHju9adObjDYuNiS8HeNe+teuUnLm9BfwXMUK/T4zuxY9WuZS9ZjaMZ57Z4LHJ8x2qWFvLXk9tXHd20JBaL7l76clywekXOTc7k0Wj8zSX7WtvDi1YeOnKiWfrdGVH5Xue6bSdfX7zX7bI3twZfeGdnYb67rsH/0sKdRElKAZDbQST0mdVmCUdiz7+zoyPESkn415evP3LgWOPew/UrNh4LhWJL1xzZuPN0S1uQFu05XO/gikE/HeEhBxph74PVh46cbNq86/T+I/Wsiz5cf3TDjlMtrSAMAbt/Ecoe5OCFRm9pj7646KQ/EOMaEmsJl9O2cmvD6frgrkNtB076wdmZwKttXb6pfv+xdrdLXNDL8QAwKM3zOC27j8U/2hEzrgaJ7nW7LHtPJjbsj/uDnVsOxZ12y6YD8TONif0nE0dqE47+viSWxqFBnuPxL7711lvf+c537rnnHk786C3U85kzZ+SQyoB0zri4AJHCSEmUB6uCU6dO4cIkjVcbJYfI4C2tP/3pT9vb22UtzHD8x+zy5JNPkomzkxzKZ1D7xXahsSg2dPmnP/3pO+64g4fnoHiQaORs3rwZd/Xf/M3fIIKRayhmoiYQzThcP/WpT6E+c3wAYqwj01lgsKKQvJEDTmQ6r7kFJzoYxUZ0xCc+8Qnau3XrVjzZOI8h/GLN76N8ySpLi8cffxxWYRJlyYbexaf+jW98A925du1auvLee+/lqg6qHd2JGx6fd45ZlQyAjRs56NOvfvWrwIZSuS4aO3YsTWAY3HLLLeXl5RR78MEHb7zxxu3bt5Pul6MPgBmidDSziQEppwOkMUklWi5lAA8v+yc/+UmQg5YcZl8f9XWfmoVhh9PdXHf65MFd3vxicaC15BEvcXTv1hETpj/5v/+fy+cLtLe6CUMpKdu07K38opL5n/pSJBTM8ShCSgb9bSwhHvvWv97z5LdK8Qoz6Qx/xOzbHrzjia+BkM+W+ppxM+ZNv+Gulsbaw7s2TZ57M8uSHENlnQDOhprj93zum4/88d9NmnNjNCIOZUYT2ll7+AqLYTjgb/PkF9zyiS9ygt2/dW3F4OGlVUPw0Pdpd/dmvNNqd7Q1nImGAnd/9Z/dvsIjW1biYoc3DjIHNy2fe/+TM297dO/a9/mp5eyp2iN73L6i/pqY4Adt06nDDSf25xdXiih2cmw2Lhfgg7/+c387+6H/5S2uiEXDo+feee3jf95Se8LfdNZmuyLfR+6w22rq2oOh2P/++k1zZwypbfA7DZmDSjt8svnQ8aaKEh93fKDvC7xOHO1vfLDvgVsnThlXgXrOpbOVuri3YNLYii8/OntQZf7dN44bOqgIL3s0Ft9/uOEzD0z/4idmItZZYEyfUHXDnBENzYFdB85eM30oQiPHczN5/HOo46rFyo1HH79vxoO3Tlyx4ag/EJ46vupGA+HOfbVzZwzrX4QSLY7YjlBsy76WfK9d+LCN6CnoPXomeO8Ng26/pnL5xvrKUtdD8wdfPaV0aKX3xlnlHfjmu6/MJDe5r9O40k83Jk7WdxblW00VmYh3nm5IzBhte/g6+8HTibZA5+6jiVtn2W+YYtt6OC5GdF/DuqT9NByZHPUYr8hZAi3YEOuIP7Qg+q+srIxa0h3N0iDq/NVXX500aRJuy2uuuebNN9/k1U7IUBQbfn0kJv5CVgs9dDnOHmrED3r11VcjW0nLdQU22fjKJ3iMb+c+yE99Y7f7778fJyv6cu7cuTIEgk8uL9B8lDqtRmiCBB8nEURoOwpjnx1Tr0WWlBDlvmY6dSO0HRc1D/lhhUN30HCJkwsX4ETGARU+0W3Id+wThSKvEsjCqVeUXDIDnLKBXKIBDGshySrg6VyY5Fd0JH2KrAQqgpiVEvKdtRld3GMAJCO5WDozhKY1WSO1c2WJngUDrGKTAvDGGKAJDz/8MDPi9ttvpxhBU0Qi0YR0J4KsUVo2a083we7QBY033HADo5E0SwhwsiJiY/nB4ofepwnMOIb0Aw88wK/slRla4LEvGyxJC3zKxMWQy/LyV1jkzC1zkvMvtu/5+eL8zrDZtXY5sSVHd20yIjqsaEo7IWG1p/7nLz5988NfLCqtxGd5cNu6o3u3PPiVv+1oa2Uv6jrf1OW/CXjGUVriTMsAlYFt/5Y1v/3ut8sGDZt7h1g5G3YIhIltWPw6On7o2ClcDag5diAU6MgvLiHSnTBo/PRWm52bRC+P7/wSAmx316TVVDzutLLm+KE3nvoe8TA3P/yk2+OlczGCLp950z271i3jugGR4oG2lkPbN/iKSqirevhYPyE0bg/xP5wAzsdymW+Sz8sUusjPsheC7c3lQ0cH2pucLi/LDKPtYlCVDx17YvfGkL+lcsQEyDiyddXQibNO7d+KG/si9vo2WwDj7guPb8J1D5zZt5F7IbkOwAkTPDV7Nyz/xd8XVg4Ze+19w6ffCOHNp4/gkifah7kFeIplAE5yK45g3Z0iz4+XMCUKGxv1ds1NvqY13I3iVI3ft7jQ/Vf/9v7kcZW3zhvV1hFCxhEF4XU77rpxzPb9dQh3ijmdtgWLdleW+eZOH9LUGrDbMnG4ipZ2wTaSaQG2iIsDB482rN58AqUeiUSJv69vDlSW5b/0zs5INPZHn5pN5MmJMy0E9hQVuMFPgXAUv6wV0S/pSvGTXkxGmi6xybXQU6OHlWzdc6bNHxo9vNThsB073UwwT1Ghx+tl3WQBOeI+XYTJVUgqk3PSStMJHN3jscS8aSVb97dEY4IrFmnN7ZHKUu7l4KQj2AgE4+i4d1fWjB+R73FZO4KsujMZ7Wlhu7AwPUnk+rxJtv2nxPHOxgUV7kPlFGPhooGYfuFoXiDcOaTCcuBUIkiizBoXnqLMN9pOJ3ZPTaGcL33qvLCmNDzucmITwPBHf/RHXGdHW+PeI4wBTYN2wXT3uLywlkvlcEAhCBsPK/f5EUFx8803E6VNMxDEvJAV6YxZhCaqFN82aX7iEwmCvueZNr/73e/AQAUSHroE/ygbkORGPiImgw0FhgWuACxduhQFTBUYwX+JlCRw/MUXX8S9jU6i+Qi4WmMDWAYVZbkLBOKZhpZ58+YBmFgdkEucxGG/9NJLcEUkD6xyKYM05NCoX/7yl0CG5Ixrz4xYySrKctmyZfiGgQ2ekSNH4nR/+umnWarRnPHjxyM06W7UMA35+c9/jqubcxn7ZoAWnJlBlTtCqWQJfzbYELtgIIdRh5RnMCCIAcblDmJRWM3SogxAsousTkI106kn5Njjsg+mwMNX9uUT/MCGcABfddVVsM0sYzyAHG7lxEm9FrOktIxxDMqN9KXmubEq6y4r/kfRJrfatJxCIsbR4dShvRabZeq1tzLj7U43whG5c2T3lkBH+00Pf/H9Z3/U1lSPmNuzaUVT7enGs6eNlp4jOYVakoqI/dLeV3YEwmvSnBtueOjzNUcPbP1oITeqEgvBT3kW25kj+4eNn8rqoqi80lNQGA51cMLDHf/ha7/96I1n0fRJCNJIGkOJGtLbGCvBQMfw8dPm3vlJIuzfe+aHxLUDNRqJEGpic7pCoYAYT4nO4RNnnD111FdUGg4FDu/e9Povv9dQe5oeicdFu1LdjKNyGq26oChYGEJyeQNUHNgEhYMQAGVDx2z54KU9a96vGD6+9ijjxDZm9i2shcQ4Sb8fzZqpMbPNOHfE8KmzXGNyskISPApVbR0y5dopt3266czRo1uW85WG7FzyYvnwCQXlg3HAMx4yq1EcKAkk6t6Ym7TiEtOT4t1lxf84v+l6ushse4oJ6EUINLQEtuw588m7J+07XL9s7RHuROTIzYGzrMiNP5vhH4snHHbLoeON+440IIs7kEXdj5pIsSKzmJya4M9ohiJw886cbXM7bcMHF/k7BEsMkNVbjk8ZVz5icPHPnt8wckiRx+MIhqOsvVByC97f9cbiPVFcx2lu3VQaSNPcN7k4+0PmyCElb3ywe/naw9Xl+eXFHq5dsLTgKVoskBa8t+v1RbsyQJhci0h3I+6Zn8J3hjdd7HXbiJYJEw8unu+VYCgLBc+YNga12ymWFvza0BKePCo/FO4qloL5XoowfoSUFsbT3tip2GdBsospIvU40flWS1WJlVCZxVvj4Ugn42RwmXXlrtjmg4nqEhHhk5lyR6wzrSLR86YbfZou6DQ87pz+sY6o+sd//EdTRUEhwkX0Cg0xVxDpoGAvtKbcA20kY8TJpArCEtAWRH1QhWybPIrxK15DfiI0Bc8xoTKgkvCk992sH4HFhik20bUpb1RBjezCogKJ89RTT915552YAh4i8rbbbrv77rvhgQhycnC7IjRfe+21v/zLv0THSyQpVyUKUhEIJVQ+U4cK8zIqhrgdYmD4ZBXBDbLYxKt61113zZ8//5//+Z+RyASc4It9/fXX0e7wDLcUHj16NM7vDAADko1aIEo0ILWtB6u/+tWvYJXzBHLzM5/5DKqdCy/0IAjlu73oYqjgqg5dzLKEGtOCKlllF7a0cMrWsDs1Qi9xWShdefKTYxUCoVReCKIMvTBnzhwCk5577jlIJifd6ihPdRJqBrubgE0j0hRjGPwsJ7icBY1wi3HW21OmTOEnhly6OKmIXSSfrFqhJbWeF6UgjS25vBzzor3pzE1OAjiD929ZdWzf9oNb1vC5f9PKUVOu4oxWOXTUkHFTx8+ct/LNZwiVsVqstzz8heaG2hWvPf3EX3zX39YC8mQAqaTBBkIeqGJsBH+nspNZprO4ovruz/8p93GOn3Vtw+njAMCW3eEK+ptxYI8GdpQFj2X+J/4o2NG+edlbhaWVs+ffv3PNUn9zfdmg4WlFoYizgnjOClihFo9RunMzdtdn/gToBMAc2bUpjtK12elsMUgEbALvxZNPRk2eNfPGu1hdFBSVconD6ys8sXfb0NETiIBPnV5xks1LGMSyk9jSIlaOc5cnv72x1uFyo1HRxHY77kY7jva6o3se/rP/6Ghp2PrBS4Xlg/C+n9i1/szhXUe2r+JG4FgkiEQ2eyilhDE34UFuKe1yfiHRwASRAAxJYYOviXjUV1x+1QNftrs8gyfMbjl73FNQvG3hb/0Np6/99F9APmUYGOebufw3idBJ/zvdPmeq+9MRHCi6rTPEOSmLY4V4vk06G73ISME5PWvy4Knjq3cdqG9sCYEF/6+Y5axWxUyy0k84NAt9rr/68vX/+Zs1q7ecuv360W3tNDnt9rIHNsVI4qlHnJLSGUaMIqfTceRky5xpQ5AwTlwzFiuBPVPGVU0eV81yYvu+s6Fo4tF7phJHvnTt4bJi7/zrxqzZcqK5LTyoooBFSBrc0DHIv67DSNrEmhWBsT0Q4Xbe//Pt24nk+f1b2+D5E3dNjUQTS9ccKi323Xrd2DWbjzW1hgdXFbBYMndMPQFSg0/Qdm3pkHpePcaRgxEPrwx4LrnYozirxeVSqz8QLy5wEkszpNJbVMCzWiiS3rG1uyZhDczG1Snjs/uH1P83LgmcVzwU6Zw8HMMic0iFNRDOO3a28yt3Owl5X7QpNqrakdnFMJhkCHDXh8vJEwjTHu0mxDSOX4KavDwuuxPdToAyn7jDCe0lChxpy0+ygGk6xQSi58MPP1y8eDHqHAHX0dGBHfya6CTc56TJQXDIcGdxKDFgoDsRc8gRdsRfC8Fy8WBWypwkLT/NzBQT7CV3xJ2PEEfiyKf+SZnCT+QAg082tAgK5tprrwU/PlcZZZ5iRdkXo+HUy/WKb37zm4Sg8NgQHn4CKqAm44QcAONoBy1hM3yVQ1I2M3sYqVigLlndM888I1nFpw4quOVSAPdTfvazn0WpMwaAx4qITHqWtnTNnlTqUF0GwMDjAgsw4FmGhKHdgcQlAoJ55Kgj1osIH5xUskWymaqxpGHPBMDIhNL33nsP1c6iCITMIIncLJOG3fOLSguZ2cn4TAAEDvDhQMe19z7+qW/807X3fbp65LgRE2fgGs4vKsWfffb4IRztqHZu/RQC2eObfu3toYB/++rF3vxC/EjnN6IPv8EMt8OePrz3jV/8OwEwtScOEYRNaD5REDQh2NZaf+Y4j5TBbcyhKhIOHdq+vmr4WCQ3Z3d5EsuM2wyaREWiRzo7X/qffwz4W1sbaxnwPE7RzoMpuzejjPAAk3Fk12aHw1VcVoXnibkgD7XdBXPxP6civHrewpKzx/Yh2cOBtsKyQZyB7IRNSqB0tMVKv0+f/4nbnvzbGbd9qmLomMFjpzM20lbtyhpknKfliSkvz51f3Hjq4PpXfshNq81njuSXVJ3Zt6nuyK6bv/gP7oJiEbeUxXld9EgWp7+M9wUz1/mqynzHjeCNppYgvgJiOVDDhnNPohKfuI0L8l08xeXem8ctXXO4sTnIwBc/5HAz4iIs3G9aVS4v5os1QGV5flt7qKkl0OYXExN3Gs7s7XtrccAL3c0ZS2hEelFynEO4okOpjn9iiBvXU/Pi4tpqJ1dItu2tASFxMviGjfWPyM8puItUZsDN4w4HllhF+Y66pkggHOOm1dIiJ073E7UBxLHPY48JJ3a/bVJBS77oXoc9z+vOW7MnDubZY22ElPpcFhYeDBjKyM8ssWbZO2lPFerj9M9hXX7KRDYgEOVEcSDEcQ8jkgiJgRFycGfyADtE0vXXX48zgF9xrnOVH982UTroY0JlOGcgRyjJLgrlHTMTQYbowTIhJege7ucjbGPRokW0mshsnsryT//0T0TyEIJP1SwzEMTo5uXLl7PMQBtl2alp7Q75yHQWVNxygHBEXPLYR56EA2/44P/lX/4FXzvOYGxymQJnNv54vMX447lPEW+3OAzlZDNZpYu5gmGyunDhQsAzAP7kT/4EeLiuQYUOZuXGMGBI8NwePMQ0M2dQJR9UR8+CjYc8fve736WL6XruIqD3GWz8yrBk/DNOWCzha6f3uQ7DCMkxzh69R+2MQBBCI3c+EMODUv/oo49+8IMfkJA/gTn3fPbAmc1XwKPLSyoHc2ckN03yQHQez7J1xcKrbr7X39Lws7/7o6nzbi2pFGMeQY9wuO7ex7csfweXNm65bOpNa186An/54NETuEH2p3/zZCIWu/r2hw5sW7t34wqe0xKJhFlUiFDmrkfLdTbWnqoaPprgmVXvvIAnu7i8mqiCtGrMuDBQWdKg1CfOvuGNX/77yrefn/+JL3a0NW9Y/BojHEGMVGBFQTGYZzVSf/oYMe4jJs88c/zAvs2rxkydHRY3/mZcf/o74jeJRooqhw6bMOvl736du2bHz739+O4Nh7esLCirHjJ+xrLn/mvTwmen3/wwDON0L6wY5CksdvGkfFM/pl+ngj3wPYqLGLZYOLT3w9dKBo3yFJYu/K9vIsNGXjX/wJp32+pPr3z235f94u+jYW7H5+w8ILRX6g1nDERi8cFVhdPGV/7N9xcHw7E7rhuzdXcNT2XhiSLimCOksBgoHKBQ6kSnTBhdPn5U+aKVB3lYCmI09bqyLwlaIjqIveaJ8uKZJy47j2c5c7b93vnjn39754JFex++fSIxJ1RUU+8fPqgInG8v3++028pLCXjrB6EpAMcSRQUevOw/e37dK+/tvG/+BKHPO/Nq69t5CiQI31y6lwsaFSCM9wPCCzsF7et2WY+c6th2oBWqb76q7NUlp1ZuabhzXlUgTGgbqp3VUB6XY/p3Y1CKNY9FRLSv3xsPRfLGD7XuOp74xcLonPG2ypK8EVXW11dHl22NXTuZkZzNslpBQ8WBWIGZjEyIaWyxED6OoMRjLb/2agkZzTxH6nEbKJIdVYdq51kZsnCvO8pMxB9ecKJBuFpHTq/GL5ZJeQQxSwUUG4ISGYTzEsXDSgOHMf5XhDLAqEJclqbXbTYKUBioF7N5sXzqYkeczaxJsJMuVGmWvVCNwAMqCawBksdoIj0pAFRpFvtgpgAqH2FKF1wM1SXyueEVy5zU090dDD1YBaR0VEM1ZmXzJVRpnO6GfyEg0twwQtcwYLiRVBpM04AoDgY6lGgZlhBYo4thkiZAHV/5FctwzvOF6EEaIi8TpVsRdugRVqp49+kd2fB0jcjy4GEDM5+MBJa+fEqbrI6ACnJIzrgKCZXR9dBDD8EttWRgirnIuHtl7ZF9p5s9vb2lJcW2UzvqlmAJnhiDL4Gnx6DOeZBLcQWPN07gXuVGT8Y3VyfDwYCIhBaX/tM7DjBtPA77iIqCPaeaxPPL0tubC8BQbW2uO1NYWo7kDfrbxfjx+hDKMe4hE/5143BBSwQwFl12fN4sSwj8IBpS0JTyRlmiSCcNLTnZwKPtYiwuU95VFAQC9fKIG3QwIexQykPlPeLFVWKQE+xOIKPsa4QmmbBKjAq0ewuKWKKkNQxAxkO7q4q99a3BY3XtPBIuTWIFYGpkcrY31XkLS2EyEuSZmzy80kNQT0dLPRKZdzMxBigFfvg2Xn4kdkx3E2PAaa8o8mw92uBMewwk1QYMceunOMJHg34e6E4b/I21hL+DlhgeHpJD6BTMIugN4Z60b2pJOr0jHPuL+6ddM74K2OmOASoBI1WfPLBy67KfgiS1as8rBeEcYOoaO4rwqbsc/kAEJIRJcAoiFp0uQ8DR3ShLYqDR6oDkAeQeN+fo8+yk8oV+LSofQS93tNZyhQ30qeyVXMbQ7oInYHcEIpzA872uhuYODiBlJfnEwwiLwqxoVHtHxOPiwE98dpqPcmdtHIuUD5ka6mgOttdnRqyEDRZWQfVNHTyHvqTIQ5g4flQmIy0wEIZ5omUmCLtJgYdoJFgxZGpLw9HTh9c5XRzkM18DQBTdzXGJBPcSII7bOmIgJwKeHEmjcYmgu/o0/08kYh5faUnl2K3Lf8nFK/nIpjRtiOJ0sHH9UHR1KNrpdljwuxMhE411Fnq5tVrcqNriZ0Ll8TWz57jT6aGOjusf/NtbHv13OcsywCl3ScP/xPmGcwzeXB4WjohBoCA1yEEWfPnLXybKXBZIHQrjg8I8QgTPJfvKrxzRSPAp7cg0tVCA4Bw20744Fht7dZ35zB8UJaiapvGeICpC96B1aDVThIajfkzVizCSaPkJWQ8kRfWnbQbAgAEAspKdwQxOVhcA5khDDkQBFZwUkwKOXdKuJrsdLmRVinKAscAAqiSTYmwyTQFGGl+zqznDvSVjXMcQR0djXQQS0sh0aZGvUI2QpST4+wun2TwAyI4mgVIHFfIaDinA2GADuSTW3OXKTdBGgk84WKM4OW9JpY6vnVvhCDQQPxmnHBQwryY1/HldB5ZcNdkCNoK5y6qHotPRvjyVBZyodnoJt/q5juC78fR09CU6WBza0lTt2bcIMgky4s2poIqGg0gBrmYIGMYmPe4yLWQHhZgFXO52iQsL7Js9gHQtAIF1W2FZNVOTyYlkp9Plgo3wcU7E6A94xSzwCJuSgyHdWlSWF3PTDnXgIVSGPgYt96FCMg2xO9y8OVUymbOLLSpb121LjJ+oCJhB9PKEE5Qu/SK96QwTPO6c3kkQP0NJxg2f+LxlgW4bufsf/zQAqI9P3pbKQoJbUQnTZwoCnu4AIZOTIvRSoSjQJTdzB/H8mgBEbAwB94AWz9AUAMUzW7oQ5gvkUhCfv1//fJPdzQoNnHQxsfiFPl5SwbKNWdB1+cWgv3/gmbVCIi4UgIGKN6Si46KxPLdDPOId1U5mJCokOwUiOX4zngkxKZGGcJf6mHB2niqDt/W///u/v/71ryNnSaACk2yml0Tsspn7yFEoP2WmTFM7w1FOMPL5Sj61mzv2RYIq0GpYJkHVyDWZJmH6qk1IlAFhX8BI3aYEI2FIPEAlIS3IX2VbSJv5qdtXUpJ6L2QVy1CabN8kNrkJyQVymU4GLIElE0iLzLGRS1QXq8ukTo6E5InDLuavF9v9yso31Bj6WFxlRxdxzkIhy7F9Tqj159wUsw9pyyeoJE7JcI+O6PoKVKmVu6dtLrsDAlHABlTxlhlTtZNzHlp5phVHRY7Jol25BHl+XRapcQW3LNIYBAbPjAIjce7i57nBcP7+uf7WLVIYqLJq8AsCJZkDI7whe05okHwIIE0TQ8ToF2m2m4DzRlR/qXYgJQ9s9C45aAv5QB1TYEjMNEoW6MfhLjmEVRkJI0aOsZ1DaAyhfkcoUfEpgfEpeT7HoQFR/moW7t+EOUiljgOqGA7GIhNgBnIBsJvy/gR77riWIgq8d0Qe4yMn1pynNI4YMYIoAjZ2T54AKVqTxVLcEbHORJKbOV7TqkgX1gxoBjQDmgHNgGZAM6AZ0AxcoQyk4XFPbiE3C37xi1/8yU9+QiZxMrx3hoR0yScXSzGtVXiKROlimgHNgGZAM6AZ0AxoBjQDH1sG0hDu+MVR2Nzoyb2kBMzwMhfupYM4or3JlEG0H1sedcM1A5oBzYBmQDOgGdAMaAY0A33KQNrCHdX+9ttv8770BQsW8AwQwmd5TuJjjz2GcJfKvk/hauOaAc2AZkAzoBnQDGgGNAOagY8nA2kIdxkJw1PA2SCLJ5PwJEduSyXYnZB3cnTEy8dzDOlWawY0A5oBzYBmQDOgGdAM5ICBNIS7RCMf8cE7OHlbJI/aQKwj6HkWJMEz2uOegw7TVWgGNAOaAc2AZkAzoBnQDHw8GUhbuEMTSv3s2bPXXHPNDTfcsGfPHt6Pw1feYIpw/3iSqFutGdAMaAY0A5oBzYBmQDOgGehrBtJ+HKQMmLnpppsQ60TL4Hp/6623eEAkQOVPfY1Y29cMaAY0A5oBzYBmQDOgGdAMfAwZSNvjLgPZCZL50pe+BF9PPvkkwTPyBUw6xv1jOIB0kzUD2TCg/EUhGFRr07RmJrJpb/K+yg1ivC9sJmP+mKehty8Y7gubKnqqL5qr3KYkT5qVaRVNFzbUQk1GqNZyH0FVRWNu7CA/xTYgXo90kRYbAPGVKxilaQh3GQkTDAZ/9atfrVixYujQoX/5l385bNgwu90+kKPbwWZuF+Ez7WxpMO3dLr6DidBMXLxser9gkB36DnB6aC5Zui/arrzhl2yBgh/7ArBymxhU0FTxTrrOuPHuTfFuRUUbBtkUHBq78YCNPwnVKmx3/5D1/7LV2MzaUpcBWi2bD0qFlGJdGlRoE6iCVaPt4qWK4k/ZJg0qM2cMVGGTl94bfwqxSlMKhyu6QFU3dSZ4+6zCbhEMijcHi9fGK9t4u68x2GOg7UxYVI0j9VDFW5NjnZ380T9xpbzSaEhQOIh4CbFkVXSYoELdiFdrjWEksPFPvDC70+YIM8CUjS3VhixWWyyaAGr2htMQ7jz5kbeW7t2795133vnZz372wx/+8Lnnnvv//r//j/wBGCQj1l4sbSwWnlPpcDhAqHDwKW8y2Fj/8ER8Ll8ohErzgQoPCm3KMVdYWIhxeady9qNQWjChqjIoWSWgi9f9Kux94ElrcowpQYsprmJx5aq4uDgSiSi0DDy1w1VCZaxmA1K+Nbos3z2iPN9pt6k7LyCt4laLFceLkn4R7HV2uhy2Ep9reFm+3aZQZmPZmJuWtOMVL9Y0WI0lEiVeV6Q4HoklsumgnlVwZkx0Wm3qoLLGiCeK813haLy80O20qyW2k7fW92xCFt/lGADnyArFYyALUL3vSsNDkZjbJc7smVIg9nO68ssGTUBq9F5NhrnGKLIqG0WgQGL6igbHoyGPt8hidahaaQgxyIBXCRXhHi0qH+F0FcAtz/TIkMLedkskkA3KeorjRjwa9hVVx6KhkoqxDqdH4dkTWnmgSW+NyDCPAeB0FxRVjBw9fb7D4cZ+hob6fjeLxRYO+xkDVJXlwTkN4S7bhccducarlxDETU1NqA1yeBwkmr7vG55GDQw1SQ2Pmef9UPKyQBr7X7Ioraa9WVKfXANo5eqiubkZy6rmiZiBcbG8U2jThC17XyEJfSHcUe10/f79+1VRajZfbQIa0esI9yNHjjChlJ4w1CIVR5xoNFpeXi6HVmbWUeooq5aO0JmmAKoNYZSZnQv3ShhLX2Fd0cbIAaHbaatpDtiV6kvpHFJ4ChfCPZYo9DhPNwWDkZhC8QoJTE+FB3m6JxpPhKKJPSeb955u8SodA4p6/pwZFi1et2PysMSWIw2s4gbywcRqtfiD0fvnCHEgZ9m5ZqSaYjJaomF/c91htcJd+SgSbWTCx/C2Bjtaa6x2p2izik09VJxosYjV7mprPBVsr1dLLIdihXOTg2csHLBY7bXHthzf+6HT41PiJFbRLb3YSHTGPN5Sm8NVd2Krw+kd0MLdagsHWkZMmk8zMp2bXQykLdxRQkjMf/iHfzh+/Dg2/vVf/7WxsfFrX/va1KlT1Tr2eumijLIY0+hsdlV4tMUg1hRqVmlNQiXNllFbe+4EQqmuFNqUdUio8KCQhL4Q7ihgEMr+6snOQPouQUpWkcUDX7jLOZUlhbFEZyQWt1mtCoU7flyuril06uAXB6GEyrRUNDUFc90DPksWz+2OcI8iYhKd0ViCP9XCPU6Uw7nKsktJ4R6Ld0bjYgzYrRaFYyA7aL3sjXB3xGxQGgKu0lNJL5Vll8UBD5DZk4kjE4erWn3JaYgxz3zKronn7W0I90gsFgGtFW+rovmpHqoh3OOxCH/KieXEoZBVcTKKhuh+oEYjYSveChXRHed1m7oviUQs5gBtJBJsA+cAF+6RYAdQs299GsJdLulmzZr1wgsvhMNhFDwdTIIhzitUgTIw1QYg5ZY9WaaFbpPKTmNYNm2SMCvKMmE2XKFNCamP0Eoesmx18u4mzuTMAZg2cZqJAQhSQlKIkIFuWMv4mn4vJDF7pM1efssoy7AnEKo1CxY50dVNd2FQgDQsG+mMGnyRndQ2PxmkYVkhDRdpQBbZkkw+WQvxp8atkgWeS+wqEV6iQMo/0S3CWMrlUynIipohqtSmRXjQjE2iVdU5qqEKiCCUm2JiGZIKWTUgmlCN/hrAQ95g1UBrtYl1pjrnQioDOq0ywGPsQ29ae/VaOA3hLvfH3S5leq/mdKZmQDOgGdAMaAY0A5oBzYBmQDPQFwykLdwBgYu9BxQla4geNvVXzYBmQDOgGdAMaAY0A5oBzYBmwGQgE+GuZbpJn05oBjQDmgHNgGZAM6AZ0AxoBnLDgNJos9xA1rVoBjQDmgHNgGZAM6AZ0AxoBj5+DGjh/vHrc91izYBmQDOgGdAMaAY0A5qBK5ABLdyvwE7TkDUDmgHNgGZAM6AZ0AxoBj5+DGjh/vHrc91izYBmQDOgGdAMaAY0A5qBK5ABLdyvwE7TkDUDmgHNgGZAM6AZ0AxoBj5+DGjhfqk+58GXvJOMTb7j0CzKVzLlYzHNn/hqps2SOUtIqBcCIJ8NGHyav8qcnGFLrii5avCYkMwyFDC5HSCYJXvJyCUwE7/5NbmM2aJ+SZjYetQ+cBD2AJbBV0G7eGVgInlfMcrPm5tdg79HseRd+jZtgARSIi5et2zWBUqZSYJM4JkI2cMsluOEiVDSaDIpYchMWUaQ3/0+xX4ELIDBahKxJtRzqATWAfFKRSjjTyLs+jSwmfgBKt5SeUFzztvlSvhCC8TrWy9oiEFA1ywgLZtC4sKSOWgl6EyAQLjwfbOgSm6FiTN5xxzglFWYFHWj6lnzedwykrrpNXfsuUNOvpsMm7WBy8wkwYQwv5pl+iVxIQwJT4IBNlDF37mjeL/AFJVm8jjIfgN7kYoZl33xhErM8rYpt9tNtbyFPhQKyVr49Hq9LpeLt8aS7/P5SPAGeHLsdnswGLwIzD7MBipVezyeZJzURz6oJH7edMsGPKDSKEryax9i6s00NYJBrITicQBDI6WAlIwEwCZOgbi/MYMQeLw2mH4HtmwWA4ONfN4WDH5+BSc/wW0kEumL0SjrTfETVHLcyhcbm3uRD2xzJJv5V2SCTrE7XB5vLBqJhIJdnFssLm++w+mMhkOxaNjjK4iEg+KV2C63zW4PBzt4qWiOG2sVE9PHGLJYrdFwGDwSqsdXyDv0AMPXoL8N2HwLBzp4AbXT5Y2GgvLXnKFlMIPQ4XTFImGGvNPjszsY0p3hYCARi0qcgIRG2IZbu9NNYeMN3jGn2xMTx5PzJWlOoIs5aLPDYSIOyO7OtVgc3gI4j4UDNMFiDBRaEY+EcsxqEgfQa7e7feQIVF3H3k4Ytzlc8WgkEQ3T9Xanl+bEIqHO5OYkWbkikjTOYbe6XfZINB6OxM03RVqtlgKfk2EWCMVsVovHbQ8EY3SQz+uIxRKRaMIsmYNmMnLsdo7qnNxFvV63w24DWJRVv4TB2dHpsLmcshUAtvp8jmgsEQrHyGesyR1zApVX9uY5DSRwCySnwwqxyYzBrdfjYN0XDEOpaA6TIRCO8UlHhMLneiEHgM0qjJFwntilIR6XhUVFWBxUGCd5TrslFu+MCNT9ttHXEOV05EXPh+FyWOy2vFAEXvO8Lt58KxBSOBDu5xe05tTjzlRB+kgnq0zzCRGGj+ycA9vMJF8WYy+Z2aNjGxsbkUpd5+wev2X3leqQYocOHfrud7/7ne98Z9GiRchi8FAXP73//vvf+973jh49WlBQ8MorrzQ1NRUWFu7bt++1115Dw2VXc9p7gwc1Vltb+4Mf/GDlypUSJ1bIRxlv2LBh06ZNvOx27969P//5z1taWsC8Zs0av9+fY6jgQU3u2bOHXiPR3Nz8q1/96umnn2YJIXtQNmTdunX/8R//QXPy8/Oh9KmnnpKY165dC2akZ9oEZbcDnc5IoItPnToFY4Dkc/fu3c8//zxd//vf/x7hDtoXXniBnM2bN7PwoEx2dWa1N/Ag6t13333vvfeSZwf5bW1tq1atojn9izCr5hk7i15wOBtrTzz/H3+zY+X7yHdjbopBv/79l577/l/VHN3vLShe9spT7U313sLi4/u2ffT6b602R/ZVp27BGCr2hjMnfv/vf/ncD/766X/95u71y5xur/CFxePvP/M/z3z3z37/vb989zf/4fb41rz7/IevPY0aRrJvX7XI5sztKDJW/olo9NC2NYCz2Z2bliz4/b996/nv/Xnt8QN2l1v4yAxuX/zBX9ceO8Cq4+S+7W8/9W/tLY2egqJda5cG/K1W3jee4y2RsDs9gaaallP7Reca806I+Gh437s/P/zhC8h0q80ZbDqz/aV/r9n5kc3l6ZfVBeMS1R7xN+99+6f7Fv4iEY0ADD7R6S0n94Kt8dBWm9PNuDix/p1tL3zXX3uMnyiQYzqVVAdsZOXR0y3fe2rN5t01bpdNnMXz8lDq/kDkFy9tXbBon8tha24NvfL+XqfT6nE73l52cOues26nOLoqwXBZIygL6q2paz9wtNFutyLZF6868h+/WdvUEmTJAQyAoM73HWn8/q/WbN1biw4G/C9f3rJ1T21xkfvQ8ab9RxpoWg4Aw4jdbonGO7furUM9uZy2nQfqf/CbTbsOdgEAg+T2qVd2vL70IAqeFr234ujrSw467VbWTqu2nKZHcgD1QtpdjrzDZxKtHSAUs9NmyWsPdr7yUeTDHXFEMFrpSE3nbxdHNh6Io49z1fkXwsyzW7lAlLf3BOq0a2kPGDLX74v8fmmwLSDWcm+tCT21MPDr9wNvrg6xcOtHtDQgpzKIQyrqQWovmZaKjRzyzbSZIP/s2bPbt283f5WUMwRRex988MFzzz334osv1tfXk8PWS4dkmoU1Kt2/f/+tt9765S9/+aqrrpLOS/zrS5YsaW1t/cxnPvPmm292dHSg4QDT3t6+cOHC8ePHg1ktksu2ANc1guz111//9Kc/zUoDUY7kRcewI8BQxnV1dbRlx44d1dXVR44cQYNSHq0vy1zWvpICcIKipSvByTIMPCjduXPnjh07lhwWG0hMuGWNcfz48UcfffTVV19F2cN/ZWUlCyQwI0alk1sJntSNAJVeXrp0KXhIsyO8jRgx4q677poxYwbeaxYhJ0+enDlz5t13301zzHVI6lUoLAnPTJ/ly5dPnDhx8ODBUqYDWPLPKo7h2u9Li+zbi9+3o6155RvP3v74104d3rNrzRKc6063b9OSN/ytzXc88fWVbz0T6mg/umcLnuBAe+va914eOm5ajucmHUE0TFFZ5e1PfP3Oz34zHhcuBg5/9AUHvKtvf/jBr/5t2aBh5Lc21bU11eMXbjhzrKHmhFUcAVUezS5LOO4j3NJr3vn93g0fOl2eoL+1tb72js/86e1PfLOkYnA0EvL6CrcseyPY3nLrp7+29p3ftzc3nDywraRySM3RfSyNgv4WhwOhmWOPu3Clh/3NBz/4bbCplrRYXSQSNqfn8IcvFg+f7PAU1O5cEY+Gjq5aMGb+Z9pOHzy7ezWZuI8uS4jaAmJWWm0HlzxbOem6wsHjj658hfUG57xA45lTG98ffdNj9Qc2BFvqa3d+GOloHXvb546vfSPCQsh2RV4PRwQ3t4XeWXbwodsm7D5Uj8Z1O+3Ehdlttuff3n3N9MEUWLX5BKfrrbtriws8m3aeOXSsafyoUpzZYuD3/UZ3IG2bW4PPvrnjTJ2/uNC9ZutJJPtdN4x+b8WhcCSG9nU4rMj6xasOP3r3pE07a2rq/fuPNhb63LUN/pbWUE2dH7c3h9W+B5tnQe9aLe8sP7R+Rw0+9dNn299befSxuyfsOdLIusLjshPMA6UvvLt/7rRqDi/rttc0t4UbW4O08Ux9R01dR25Y7UEF/Ys3/cDpxPLtuF3Fj+RA7HsbYxOH2wo8eZsOxls78tbsiT14nb2msXP38YTH1T9qGHSsIj7cHtl1NCrXD8K/7rZsPxJraE1cPcGxZneEa+3XTnZ+8kZPZbE1FM1z2OiW/txyJNyZKrQSV+tPf/rTDz/8EOm2evVqHMANDQ2oChzY//M//4M+QxwjxJF3yDiE3RtvvEHgAVLj17/+NZLU6Hthh4GIijp8+PC3vvUtJDV+2QuHpsy5MD91shHENTU1xcXF6OCqqipwotsCgcD06dPnz58/efJkJJp0BuPYxrt58803z5o1iyZkU2nq8MySoEKaDx8+HF0OsKFDhwIMwlHDeK/JR6jhFaYhcIX2xfWO7hwyZEiyO9a01kcJ6qX3Wd4gcMGG3r3//vvhcMqUKXiyqRRRBR5WRChOGoIsphVcHIBS9kXBDxs2bNCgQZTpI4QXM0u/nz59etSoUQh00hQDP+mKigqQMxhKS0vhn1UHhHNlQ5a5mLW+zodGpsy8efPoYjADTAJmDLAiYt6BVhWH2Uyx7E7QQvg219VUDR9TWj1k1i33VwwdFSdiJhQYM33u7PkPjpx8VTQS9bc0eguKXF7fuvdfmXnTPeNnXhvtDlPp6144Z9+4MlA9YmxbU11Bcfn0G+4MdLQJz7Qlr7hysCe/AJl+8yNfZBEyZPSkkRNn4rc+c2TfxDk3d4m27Gg6B+NyKbvdeebQ7sKyquqR41lIRCPhjtam/OKywrJKT34RiwgCZkZPmztz/gPDJ86iQHPd6fySivGzrnc4XCf2b6scNqZs0PC4mJu5EF7dreGCeww5XjZqughBEXNT1m7x1x2vnHBNxYRr+DXc1uirGO4prR488zZf+dBELGLJrbsKtKj2eCQ44rqHS0ZNKRs9raPuBJlET9td3pHXf6J0zKzCwWM6Gk6UjZszeNatJSOnEDkT7mhhL0p1NzaT/zM7E3XtlWlPcj5q80f8gejdN44uLXQfPdVKqAY2Q5EYynj2tEFXTa5uaQtx6RTXdWNrYOOOM194ZDohNAjQTBqZ/j4sjHFdHzrePG1CVb7HGY3GW9rDo4eX3HT1iLONAUPy2hDleNkfun3ijEnVo4cW1zV1oINnTKqqLs8/caY1HIvPmlwdjuRipUG9h060lBZ7Rg4pRALXNgRmTaqcMbGivNiz72gz8TMGt/E7rhsxe0rVrMmVre3E48VGDSmaMKqUqwSHT7fOmVKFoO+eHenzlf4eyD3c1c3+Tn8wb/xQq3Ha5LpBXmN7orzIMmGYddwQ6+GaTo8z79aZ9qHl1vJiy9mmzn5RwxLqifpEsc8yuMwaixsed/Db8s42x0sKrNdPcbZ0JDpCnYBkaVHfkrh1pjMa65RhM+lz07VHZnPTrC5Ha3qJkkAC1C06bOfOnUhJHKsrVqy47bbbEJHoOcJRkGsoctyWy5YtGz16NGII1c6+t99+Oy5P8tFM0lRRURFievHixUgoZIrZHtSeqZwoiYhBrLCRZl+z2GUTGGFflBmKnN0BgDcd46SpF2u7du3iCAUM0m+//TZe/0ceeQTHMMqJMpe136MA2NiRSuW+qUOlJAsMSDtz5sxPfvITZNmDDz6ILCYcgoUNgGfPng3VMIloZiGEDuZXAntgGM4zXmYAVW40v0dbev0KEnoKFzvOYNI0Fn8wyLds2cLSQpqCcC4F0JCPPvpozpw5U6dO5Svc4tgGJ5gZLQhliqVYKeTAJ7X0CinFTIzQ9ZAJb2a94EcTEyFzzTXX4I+n3xnbtAJ6WWDQQLNkirXIYqn3+8XMYoFhyaKCASCvsVAStEDissC0adO4ppEZtgtrpCNYA7BJg9TC1L6wmJlDX1BYfmUuciXaiJszOj+duYlbFe8qTl+iUF772XcKi8tvePBzkXCItpdUDUXuHNm12Waz+4rKCJRY/c7zuDJvevjJ9uZ6fsIja+JJMcHVCgFRhPixpe0T4p7UuMu7YfFrLDAi4TANNezEXL6CDUveKK8eVlhezWWBA9vWFpZWVI8Yh1Y+sntzYWl55dBRRO+n1VnMRcN410fXRd8U2hkPh8qHjfEWle7dsJxwzlCg48T+7ctf/gXNvv6hLxB0FI1GiiuHutyeY3u2oEMrho4G5Kq3nxk34zqY9xaWbFvx7pjp8xCcKQLmqCEYzdJJ39lZPmFO0+GtMe5e6D4Q0V3VU2/c9/4vY+HQsLn3Blvrg821xKi48ktGXP+IiNfvLpkCMYqKcNqy2fMrh9sd7pqDywqqR3OFg4OTw5PvKiw/uOR3LDCmPPQtbksl5L352C4uKHkKyzsTmS+EmGlYC4U50orjM53C3LxE19AVHCJkayGQm0diMdE/4EyXAu7jqCz1DK70/Z8fr2j1hx+7Z1Kbn7nJNMobO7x478H6Fxfu/epjsyJRRn38qZe2DqnMryrzNrYID3E6h4EuXHKsG1PUuHMwNRMceWZOqrLuz+sIRoNGCHOB19HaFuKToxqTHWy4t8tKfM+8vv3AsaZ7bpq3dtvpt5ftnza+st1vG1ad//6KQ1PHVxKCwjEhpQFFBJfYBBH8lzqx4XhiWHVBUb5z/c5advS4bcf2toH/9Fk/tcfQ8hjtTIwdXrTncONL7+374sNTfR779gN1rJpGDCosL3LtOdxQUugeWpWfHBN/iW5lnAigzM20O7/LqjgQdeZ5nJYZoy3r9xPnLChCFvnclqa2zkg0r9Wf194hhHt1qYVAmtqmxOThtn4JcwcYYh3JXujN23EkJptMZiiSN2WkY+3uyC/eCQwttxX5uFhq2XwgUl5krSjmXggRPJPJxrVUIfMYYOeO7UgUztppWcupxx0PK4EciDCOESi2Z555Br2LLxABhE+dkzoHF7zCqEwykWtIN6TeuHHjcB+iRWiYeehBlyCUy8rKiP3Ar2y2mQIIiOSNnAw2eESXEA/zv/7X/3rggQeIGDaZZUzTBC4I3HjjjQDAkcxPbBs3bsT1jnrIoDq5i2xgurtTNdcBiCT5+7//e9LLly9H48IwYRLAQ1YifxGdoIVbrh5QBucrUROEm0N1ZpUC0uQ8lQS00LlINzb25ZMe5FIJpN1zzz3wSZdRgJHAFYO/+7u/44IMq6b58+ezugAzv4KZwlwukCSnUqlsWoolL1ZMthQ+zSZLcUy/MyYBA3jiqe69914WkOvXrzeLXczgJfKz2dc0y/iki48dOwZXrCsYxlB94MAB5hcHCMYJgJVUJI2Yc+2yNilgFiYB4DQHkdnEPBzSoWA7/ukn/+6/CVDd8uE7voJiDogcFLktdcmLP5tx091F5ZWtjWcJSLDarPs2feT2ESORuYes676kcxBSTXGLZ1vTWT6rho1GNXaTZuMuZn9z/bBxU1lc5heVXDX/fi4UwAiS69TBnZuXvskdqyw/Uq3mvHLpzU25K053qANePBErLCl/4Kv/+5Fv/IuvqHTX6sVub764zAS3keDyl38+/cZ73N6CKdfcOn7mdd78Qrqy9vjBvRs/OrZ3C3evivN9apuBMhOopnkGFGkZMt6VKc6L8UignVgUh9sXbq3H1R0NtM36zD8y+M5sXer0ForHtuR8E6LcZm86tqtu79rh1z4Qi3DzsZXu5p5al68k2HK2fv8GQvDJP7T0uepptzh8RSz5MoZJY9m3x3S7hLVe5iYSJqP5yVKBWyG5dbKogEuUncSyOwhwprUEiYn/8grzXe+vPFzgcx071TJqSDHhNHVNAaeLSKdMNjGAwJnmODIidi3Ef4uwNNlM0Vxhp/tTWEUWlxR6GpuDKzefvHr64Hkzhg6rLqJMY0to98GGD9cfJ2AmXdAgFVWmsxF2H+YO2rw81hTjR5aiyL/zi3Vt/nBZMffdCb1BK2CPNVqB17Vo1bGKEu9Ns4dOGl1GTdz3efB4y7L1J7gGQkRN6tUCM5vrPeCRgeMyTgaWCCJHqU8bZVuwOrblULy8OC8SF3emrtgR53PScCsLqCzd2On2hVke/zrLieQNtjtCYulS6LO0BzqjcZ480ckaY3hlego72aZIizkgBmvy3KRTeha73Pe0h93lDPb+u0SGMvvCF75AqAwhKNdffz3+P8QZfkHUD/n4tjk5SJ8cQpOoCSQIuhzZgdRA6vGVjQqwhowjfALNRzwAaol8WUUP9yoGTYJI9w6ut1ysoXgIL6F2wqyJggAA+KmIRQV3TBLjwdUD6cwmuBnAv/nNb3C4AiCtimTlJk4klzjApQyVkmwoSC5QAAyoRO+Ak0wgLVu2jAAkIEmVOWbMGG6fpQwXDQhH4f4BStJSauyNg0vlyb3YUdJ+qaLdv8ldaCAJvO/UTnT7E088AXgZv04+3newMR5gHm6JjZk/fz7FJGY+8XOnjhkS0kLYjbSX/81Oke3l64kTJxh7jAc0Pesf2sV6idFiOpV7sZKTLLqbucNtylzLAhKLOgYGnyyKcLqzVOaTlXDyUiQzXHREj+l2aTuQxpZcRuaIzJQHvNidiOzORHF59ZDRE3mwSUnlYH9zIwLdDiCX+/1nvz9q8lWzbron3OH3ePPn3fUpnoLy7tP/icq028W8kD2YDOMy6e5RJNGmhxQPma/g0I71pVVDCJXhkTI4Uw0AlkBbE+Eow8ZP5ykueGDGTpvb1tywY/XiotLKq+/4BMI94G/zFZbEomkdtTgf8CdmtNhSPh8YtOTx1BN24gAUjUWKKqqxUj54RPPZ02TCLXd/Lv79f4+YNGvGjfcQkV9YVjFkzKQVrz0N/7SutHJoS90ZIt2jqIjze7lXejlToeNSR9irka5MqhOqRoguPNaI9VigbdKD34j4W/a89eOhV99TMGgMDXAXVUY6WoiDv5SpvvqNJyC5Qq31Rz56cdwdT+JljwbbeZhMqK2RB92Mnv/paNjfdubgkDl37XnzR8UjJldPvznc3iSXJZkhYjpwfcnpFE9NSWVjTDJ7uksKcYETUBzcU+jK7r3E/wwkp9NxeF/9kOqCbz8596mXtmzZc3bquEqeGYNKPlPXNmlMxZCq4v/+3XrE/bBBRZ9/eFpbR3jhisN/9MmZzW3BDMYDHSpwdg/5FI8k8jjAQRvvp5s7KLlpsiNaWODi0+mw83wZhklDcwdy7fH7JvOomSMnWgmkufOGMSs3n3A4xEn6k3dNenvZASFGGO+psEwZOScFWrEl83aZtGieaCH18tCYudMH4fJfsvYEF0VYOYQi8VAoXnemfdKYciJ5/vO3m8iZPr6C+J81W8+UFnluv3aEFO6F+e4o7uXLbRJeegh7sylnmtTiNBcdz5NkKoosD8+zByOdS7fFirwWYtxrmhKfvsUB1WlR0luFmedxVKd2EwDuby4TnKyLz5vkvGaS8z9e8Te1JUoLrdxZO6LKxgIj85rEiOFWTyaoeAxdxtt559GMrVx2R+YJZZAOSF5iNgiJQUryRA5UJmqSyBmu4BM7gVZmLlESWYzE5KkdRiOFlkUiyE8SlEGnYpPI+AULFuCU5aceGGSN8rPHT6l8lQIdhLiliYKQmoyIFDQlASeE5rPwOHjwIKZYVKA7uSyAq/jll19G4rNvKlX0WiZdwPDDigIVjod127ZtrGcQu3jZUe1f+9rXeB7OrbfeetNNN1GAklzuILYHuUk4CoIeqL1i6NNMuhh+6K9f/vKXxL2AhwhysMn1BnqdwcBajmL8REfzMBkyR44cyWKP1qH406VISXMgGUUOTvQu3IIf2AwGwCCLWSCh4xkP5KDdldSYmRHwAPKdd96RkWbMMqAybgk9+uxnP8tlAYbHpEmTlDjdZUdk1h1pyd+eVBhjvqx6eM2xg2ji2mOHygYPD3a0cSZc9dazLQ1np19/58mDu5H3RHEEO/x4tQntWPryL10eXzZzsyeMFL5DDr72sycOMXx49A2qglWE4Uq3Bdrb6k4fLyyt5AmiHBwJMtmxetHY6XM9BYWEowQD7axCxDWEHG7CV821L5u9vaVp0e/+q+7k4eN7t1QMGRkK+EGx9t3ftzWenXrtnacP7WbhxANwdq35IL+4tHrkhIaa4zx8xmU8MCf3yrgzHjMuZVjj0XCko82ZX4LfuuHAxsbD2xzeIl/FsPbaI6QJfPeUVAtKzfNzrrgVo91i2f3Wj8vGzHL6igMN4ogXDXawwDi64qUmsJ09Vjpq+tEVLyPlB029qe00ijArcSD1a6ZzU1Sd2b60iylWUeI5frp1486ak7XtVeU+hG97R4TbKFG6W3bXbt5VM2JIMVoZrzzR8PfePHbvofotPH/Gic8rV11i1EM4EMsJlEWhz8VNtKs3n6gq9+LGbmoNEXDfEYi+8t7uHfvrT9a0jRpWzB5HTzWfrGmdNYno9tj2fWcNSZKVWzr11tId0MVayu+P8LiY5tZwbUMHPnUi2jsCgtt3PjzMk3m27K0bPrgQgY+HfvXWM1PHVxT4HITQ0BbWGyJcKeebfMAin4FwnttpWbY91tTeebgmMX6I9VR9Ytm22E3T7OQEw7mfl+dxATcSKgl/oNMuHldqOXg6tuc40dedBV6LP9hZ3xIvyicWWgHUzOaXiTinHneiX4gARtwgv+677z78gsRkA4WIFCQabkvmPBKTHEQwPniOAhRGMyE+cK5v3boVZyH7opwIS0CF4D4kjkIKUAqbrVKSoFIwINMBxgNbQAsARCT5bKxAqOVP/uRPuG4AACDRIh50QzGUXC71AYISGh966CGesUMwDCEx3N0LDJjBq020DDjxXjNQ0JTc7ilFPDmEvyPxlfN2afIRjgBDSnIfJ9dMuFWAWxdYyBE6dZ2xEeHz0ksvEQcF1ch3EzNqHsw0EOdxjjHTm/AmxyFrNkiT6x+5SAMMvm0WRXzlIowSTXxpDi/2K13MyAQeaJkprM2YR1dffTVxMkSdseSgCeRAI8UuZuSKyOf+STzTNz70uUXP/Wj8VTfMuOHug9vW8Jh2VDJNe/Op73EweOTr/zBm2lzCssOhwHX3Pr7xg9d54IyDh3XmUA3ji2PxUDFkFMAIRHG4PbX7D/pbG6deezuu9/FXXYfDj/GDQ40W4ZLHxV5SMeiDzauGjp1SXFGdesh49r1GiAvPk6kcOpIYnkGjJsy+45MLn/7BxDm3TLn+zsPb1xH1TtwzON/9zfdg+M7P/5nLWyAeo19QXFI9xLLDGgkG6AgkPp7B7MGkboHedBWUCeHO058aT+FlJ8B9+LUPnVj3Frd+jr7pU05PwcjrP3lwyTMV46+umnRtNOinFanbV1BSzEobzn53QSkPf2w6sr1o2IRhc+87u3vlkKvuHDzz9v3v/6pqyg1lY2e1rXyVVdPed3+Oa3bCXX/kcBN3hH9U8XlNQYsuaQIpPGJI0bWzhv76la2zJlfdOm/krgP1Le2h668a+vi9k19fvK+02Pupuya1todmTKxCAXNb6n3zxx0/0zplHNGwKMsctRc1xh2fhIi3tYdvmDN82dqj73546LF7pxDDs3bbkdHDisYML54/bxStuGH2sLnTBxMNT7txaRPqM3JI0cKPDt0/fxyPn2f2XpIPBT9yYMezPrQ6PxpPDKrMv3nOsN+9ufu2ecMnjirZuq+utT1yzbSqR++a8NbyQ8UFrkfvHM97ZcBUUugiMr6y1L1pd+3YESWspuiaHKDt0eDyQku+hxs9O5v9ieJ82x1X2RHrPJvlukl2njlTWmBdsTOGJ/7ayTakPIm+p7MHQPEVse50WCpLWPJwWaBzz4nY7HGOOeOda/dEFq4P3zzdVeizclvqpOE8Kb9/EPYAnd4tmz12zvgrA9EcQMlp06CZKRPyM1m4E7xLTIUsbxY2dychM1F+xAzgzcVPT05ygcumKc9e0sUrxSIiElmGPuMnzl5s+Nr5SiaSiLUHaWTTZS1fWACDXKlEf3NRAjsZQGV3oEp/MGnoJU1FNIFPGb9BPhqUfHBSi1TzF4JJJQfZjTdXOqFTKW+WAQNc0UCWQ3yCEyMse1jtgIdiYKMMaVmMNMUyw8yOdBkWuJ5D2sSQQQK62Auo8Cm5hW1GlzTLSKAi0oyEDIyzCzaxRqgVT09isGEwMzvSlBy02IRDzMKAHAzkgBO2SWRjH2sEOH3pS1/iShStzsAavQGEl9cc2nuqxcOD1TLoHeOBLXh5xTNQQlJWIt7s4jVCImbCKt5q5PHxJBk5N50eb6hDeI7T3cAGwpGVBbtPNBnPeE7PAPw4eQ46Y5gbN3matZibVtJAJY0glkMLow4e4s4bgnhhijef6zsynVZlUMoz9SYNLTlU2xbkqXZp9jKkEW8kXsDEoc8l3q8ECJ7Vg0DHj84FXqMh4r66UKCdI4mdMZ/gTUERuOXSL0+eESfA1DaoQIVUF3t3nmjac6rZm9kYMOrivk8gxWMRwNPx+N1pBo9F5yTATbciuNzu4BmRPE+GR0NmpgsReT63Y/KwkrX7z/IMcnoztVYmlSIWxS1uFWDcE9dOhIzx3qUwz2vnjQQsPMixu7087t0okxcNdaROZlI1aH5cg9F/feLqW6YMBraYDGluLOEYoif3f7R5yY+It0lzb1EcdmCJu8/RtYR2MGuAgUYnfocnizPK8MEzOF0uXsDESYqLlvg3LcHQufuIUq+U/i0qHxXl+kXLGchMizSigVgmiMdQGm8p4isYiD/hMTh4OZC5Xg/nDxsJ/oBEKyjD43GIpTHeaiTu4E2VX/o9FqkYOrWt8VSgrS5dYuEHBz8wurkVL2DiD3isQ4PBiMvlEI/dJEQ2zBuaBX8SOQkejwNO2QTxw+U2jufRcKBqxFU1Rzce3b2MB3NB8uV2uujvPPI8lhDx98bRSTy7nYcMCZwR8bxI3nBE7Du/glo80eWiZi76A4+W8vjKRk+/Z8/a5xwuREWGVymBRzCPiNgRr4WyRGLiFUuoeSHlwRbjoZwinziZNA+r55DT6eGO5nn3/++bP/mdzM6bpq0cedzN+mQi+UyfnDaLmZkyIT+RNWxmGTNhFjZzlCQwi1AjsAdrHGwgGjVJAmmOcOF0SwE++SoOS4ZIojBpJbWnZYTagYRqJAEAU6XxVUpJuW5Bw8m2SIncL1DBACpgcE1AtlFilpDIISGVK/lssi1ARW7SBf2CGVSMBD7BYybkYJBNQMSAmXR/wZMw5CcsmatHg0KxJCDBr+YYTi5/pabpCx76aNxPyaAnTUOinSEUL8qA9iIlgx3MR8EBQeQ8zZ383DeW2gltN8aO6AIepUE/gI7zTaRD3JNtQoqEuZQkvnLTrQCdY8cwsFjViydmipsmIRYnuojetQhuGTlwKNSkcW4VIdTwbxxPIB9xb8zNfqAXujqN+wDAg/xFsZDgeSzckCqS0Gvko+bFDzmn1Oxc5h5O966vBhLiecAD49w+y3qDvGSxnq6wO1fRAEgx0JHpSHaOOjQMZWyMeXGjJM+c4aTJrES6EeNBgm7CQ0zHUTLH2A1gjAtRLWsJ9K7oBpYQvHzU8CzIVhiiUxRiIRSOi/UwC5I21oeibI4gQxdgZIUGKgEV9pK5JR4JNAalApUsT4KHQoIzd1hF5ec2nhVD7aKDDUq53tlhvHaUTEJTcG9LCg2E5/bKfYrel1BBKlAZMVDE4kvYfOU5OXwVA3YAbP0j3DNrOPKI04PclxNeDgaimCf0WPcmz7J8cuhhkz+Zp16j7LnC3Tvl6H9qB5KsLBlzr2kTc47AJVVj4jHRyh+BRP+S7oHNLE/CTCfZy1HSrNpM9MDZ42uOYF2kmh5gTMwU7/HTRQxcGdm0i0EvsXa1kZOZzfDvGdP2XGPJt/SPrAQelZuEGji7TlXn4Bk/m8X6ZYHRTWMX1Au5RSZw4DMbQqKLc6OBSYfJ5CI5SZt1m4AE5UlQjcbkBMqlKjkPkjkqkrCJAdBvJ5BLIc/gN5rFazLlZvSP+MI/ztumsjQTgoMM6sh6l+Ra0RMm+aTRa2iN5FZ0t8VoCG/9TN45aySpGDBJSkZloOjilmNcsh2zvMlz8q85S0ueuiAatZow+ckcJDnDc4mKzC41EwJqEqkm8ksYyc1PV5Jw73Geyw1BuhbNgGZAM6AZ0AxoBjQDmgHNwEBg4JwraCCg0Rg0A5oBzYBmQDOgGdAMaAY0A5qBXhnQwr1XWnSmZkAzoBnQDGgGNAOaAc2AZmBgMaCF+8DqD41GM6AZ0AxoBjQDmgHNgGZAM9ArA1q490qLztQMaAY0A5oBzYBmQDOgGdAMDCwGtHAfWP2h0WgGNAOaAc2AZkAzoBnQDGgGemVAC/deadGZmgHNgGZAM6AZ0AxoBjQDmoGBxcCV9DjIgcWcRnPlMGA+0XbAQgahBCkTMj0w0UqEAxObRmUykPT0YTNvYCUkQvGgZOOtigMZsIlQJgYWj+ejUYpQdM755rP/ptymibAvLJvGFTZc4lRoGWxq295trftsJKboQN3EuVLAkweRbuQDE626yfmHL9zFO/+MNzeZL2/Kvk8xyHBR+Fx5sMkNy5glnT1IacF8q5FCmyZUyYNaqKqsYQecIGTjdacKm68QoWmK4QRICZWEwqFlVqEqYULN3qDRQZ28Vo2/7K1JC8x18ZpGdZcSJTwTqjqk4kWMAjMve1G0cdaShzo+Y7zuXt3ZVjZfLVQQwi2fvP0xyuvXFDKriE/TDOAAKaGKt/MMYKi8bQeoChCKLud10coGJ2SKqcQJTt2AxyZv9O3+i3UmrBz0zV7LJmEMeKVQjRf6ApXTEW8o5kWc2cDrsW8iEecFwT0yM/7KER6EAmosysuIbbEI6Yyt9fWOtJ2XUDNW4zFeyutgiPV1jRnb5xVscZSI8aLJjI3IHf9ghTuDT7bQ6/XG43He06ngWNZNtjTY/U3B/2BzOBwej6egoEAhVEgAKvgU2pSthdXCwkKMmzxnzwLHdIwo1KySVYitrKzMHl6fWoDGaDRaVFRUUVERCoUUkqActoRaWlqaFUhjduZ7nOWFbrfDrlC0cWK09XjfXXYUMIpcDlu+2wFUu41FdXbmkvZGuPKNV0km5WWV5JgXiyfyXQJqOKpybkIC07PH246zwpqXR0+V5LsGlXiDkbjbYZWrmCxtmrszvtR1lFCcXqe9qsg7uqrQYVc5BkzAqhKsKwLhqNflEAYzXLmJ3exOb37pkB5ve80WZCcLy4TVpmzAgwdN6S2qjsWCxpt9abWabmeaM+JVQkUNx6LewipWq3a7Sy2xglWrMlY5wsciIW9hZVHlyMphNU63byCrYQaA01PkKxpUMWQKg3YgQ8XZGwm2eQvKMp+a3TPwD1a4c6Zh/PEZNja1ylXtPBFHn85ORLDb7QaswhmIZaDyqdYmBuHW5XIpF+7woFYc0HAWGJMnT5Y8gFzJppxVcayMxQYNGuR0OiORCF+V4JRG6CaFrIINgz6fz27P9ugRCMVaA5GIU6W31RDuys5hEIhoc8dsJRFXa0fE4VAp2mg29hW+kJxBE8F7He/0uR023smucBR1orOVjqK8PPzC4JwxomxQic+h1A2rdsDTR8g49HpZgcvlsNqVQkXGYb/Hy+rJyXhj0RqOJsryXVggeiAjO0CyhENtzXVHrFZlUlgikefljFD1vlNnPGbJs0UjHe1Np2x2F3q793Lp56qFKg6b0bDLU+z2FrF+sVhs6SO66B5iblrVGQRqLORw+waNmuvxldkcLlXXMWiA8uMzSt3h9BaWDY+E2sUAUOdZkWsA1PZFeU/zB8ZANBIsKh8l9stsanbXmO2pt9vOAP2fXmxra2tubkZkKOzRPjgxCI87W1NTk1qoyiUmPQ2T6Da/34/WVCgOgIplhRJTWsNge3u7cuGuFio0QmZxcTFQ1Qp3cNJ2hayKM5BxGQfLmU979rVYmjrCJxs7fC6HSo+70lUKDRTeVpe90Oc61RRwKhbuihfVdA2O9mHl+S0dkUAkhvM18w46f0/6mk7PfqlmWgVaOJawW0WITEN70KnUjc1UYsArPDTRfKfDZrdbGttDdhv+ILMd2SaUH5/p9GA0FomLoYWKzVS754WDbY1n9gx44W5JxCOse6Jhf0v9EbtDrW4Tvr9sO7h7f0zFoiF3fmmssDLY3qDW4x6NxRxZu1G6kQqvHB53h7Og09Lpbz5td7qzOtSbdo0EhxG8aQqJ5fTm9BTw19p4wuEAqhj5SjbWGNixqbyUYQ2H/eGQX8ATq+PMYf6BC3eIYZTITeHgwxQ2M2f9gj2lQUazcqiyKuVoTagKZyBQ1RJrsgpItTilNYU2Bb7ztwvGSOYZ0nDm+5+/pwnz/OxMvnH8xn/Jn8IwCUunxQiVyQRPr/uADYQmVJWizThyq/S4s6YyoGJT/KmTHbSaS5hKoXJGNBBaCBYSCXViuMsgA7XXDs0gE2wSpHKoxn11wngGqHrdRSLM3pw4F9mdA1+4M4esdoc1zqUQJ38c83ulJYNMTCkcQpiyEoNvdVisduNPnYNciBwWL8q0nDjCC5AoHOa8Tawx1LHKPBfHEXUDHv1rHD/QOIJYIpwy6Oted7Ea9yEYPPT6e9qZYk4BUkXblXV22o3QO2gGNAMfewY4zco/VUyotQYq02BfQJX2VbVduTWFwLSpK48BY7lmzAB12NVJwC5MEmTypyqwfQG163BiHlSUYVXcTQLnFbcN/CO0sn5X6Ta+4vpZA9YMaAY0A5oBzYBmQDOgGdAMXCkMaOF+pfSUxqkZ0AxoBjQDmgHNgGZAM/CxZkAL94919+vGawY0A5oBzYBmQDOgGdAMXCkMaOF+pfSUxqkZ0AxoBjQDmgHNgGZAM/CxZkAL94919+vGawY0A5oBzYBmQDOgGdAMXCkMaOF+pfSUxqkZ0AxoBjQDmgHNgGZAM/CxZkAL94919+vGawY0A5oBzYBmQDOgGdAMXCkMaOF+pfSUxqkZ0AxoBjQDmgHNgGZAM/CxZuAKFu682IzX56p9lf3FxoL5PjZe+u1w8HZh3tUtqJMvwZKvWFP7dtKLIemRT9W83JstGSFlzK8ynVxGvGfMapUFlLzEqweky36laghMxixBkgkefmXjV4mNT5m4rNk+LQA2CTK5FnCaX5PTZmbuE5I6s39NAAxaaEwGORBYNeFlnKBFVpvdem78d9rsDmHNeOuhbCNlVL+rLw284LkE84C3OZyijHxPIUVJGOOqXzqIF4bbmIbdxwfZTisoHU7+4LkrpzvRLyDPZ/9cjyfnJw918sUYUPHCwuQq0k2DwcZYtZ47VsuX5nSNWPOVN6L3s3/zabro1JenHbwclz95mOTTbhzUSdAVsjdIW7vT6hGkZhEMxkt85bQT+4BT7kpPmG8LJqu/R5BAiPRgJJMwN5vN6rAza7u0HF/lT/0+4Ls4NKae3YbkMCGL+UgOUHvM03Mlcpsy5ianzfOINSHIfgeww241pF//T88rWLgzLpF3F2oUk26FCXSPHGFNTU21tbUNDQ3hcJicaDRKLcBgCREKhXI8VQDgcrlaW1vb29ulMgNJY2OjMQq7TrGknU6n3++XZaALzEClpIlfIVGXNUWlbre7ubm5ra0NYHxlF3gDP8hjsRjAUMkAZklGPjlsOSY2uRVUDSR6nEwS5k8g56scfslps0DuE8CAUsZDMBiUKw0wgBCcZ8+ehUYyKUOL2PqXVTXkdHY6XO6O1sZgeyuykmGEwmxvOivayJSMRePxGBUxnqLhIF9ze+KFZ6F4W+vPAANxZjIfj8VMJP7m+pazJ9saakAI+lg0Eg0FLTbRTaTVsJSyFSp1ujxtTQ2REOOH9U/X3Az4AXiysfZkoL2VUy6DhwTjCsOAZK+Ua1BcECQw3NJQ28m72XvOzaTlB1PVbhcDoP82WHI4Xf7WplDQb3AroICeydnSUCMmpKXrxfIs5DoT8StduzMoXA5ra0fMH4w77ELo8NncFovFUWwWPuNxMWxIh6OdfO0vTWzgtIATGHJdgXprbI2CB9CI5EAoThm+xhNdmEXP9ccGBofD2tDUEYvHkY9y2jFuWttDNfVt9Y0dgOJrmz8kFxvRKMj7bW5KhsSwd9hA0tQaMJcWgHK7HE2tQaA6HRzr+oPNpDoB4HTaoTEY4hR5niQWw4BzpTFWG1uCNfX++sZAKCxOK/27nYeyf6FcWDu9znZhvsxBiS5evPj48eMwe7Ey2edjnFPUu+++i6wksXTp0ldfffW3v/3tr371K8Tlb37zG4/HQy3PPvvswYMHTSWafb2XtYCuRbVv2bJlwYIFL774IjygfdesWfPcc88tW7aM3SV7ZJ46dQrMlGHJQf5rxsZKA3m3cuVKjOTmqgVVS8wbNmx44YUXnnnmmaNHjwKPTIhdt24dZL755psQDuCf/exnH330UXFx8Z49e3bv3g3JOQPZg3nwwNLTTz/9/vvvk5YDEjBAgs+3336bHK/XS/qdd96hAFsPC7n5CgzIPHTo0PPPP88YQL5LaQXUhQsXQjjdTo8Dxufz8ZVGFRQUMAxyA095LZ2JhN3lObx11do3frXy5Z/Wnzhotzv3rl380Ys/2rZ0gbewZPeKd3Z99HZhWVXD6aNLf/cf0TDr6hw6eBgqifjWD15e89pTG955NhIUp1WXt2D1gqf2rVvs8RXi26bAzg/fpMCS3/3g/af+r83mIL32zV93xmOU37PqPYfTTTOVU9erQfA4Xe4D29YtfuHni577ib+tWfiGEwlQHd6x8b1nf7jkpV/+6K8+H+xo37l26YKffufM0YO+guKNS98K+FuTF7S9Gu+bTKGntq147+3f/GDd+6+KeWecLJgIbo+Plcbqt5+XmU6P7+juLQt+9n89+YWJ/hjwQLI7XKcO7V78/E8WP/djf2sjJxWWRXC+acnrHzz/kw2LXxMHDmas1bryjWdaGmtt3a6ivqGub60mUO1O6/aD7W+vbFiwvO5kHfrMunV/+0tLzy5e38RPa3a0rtreUlroONMQfm5RbSQiVoMXP9X3FVqh2BzW3cc6wPnmivr2QIxj98ptLa9/VP/Rlman03qmIfTc+7Xrd7cWeG0HTwUPnAy4nVZal/uNwYKnfe2WE0+9tOH1xbsjEQEVH3BjS8cvX1j/zOtbFyzaiUReufHoT3+/9uip5sJ895I1B9v9YdMB3w+YuZRhs7a1h19btOuXL2zYfaAWhKx/3C77+m0nnn9r228XbDp6qonM3He9yQZVsxw6dLzpubd3P/fWLuS7XPZQIJHozPc6X3hn16pNJ3xex3srD7/wzp5fvLTlh89sdDuFb8U0kvvEABXuUqWtX78ekYeHGI5QGMkiA9GMZmK2o6R37NgBcT145CclbGJnxYoVhw8fNg6q1scff/yf//mfJ02aNGfOHH5CCeXn5y9atGjQoEHk5NLpDh6Y2b59+2c+85kHHnjggw8+QKvt2rXrH/7hH0C1detW9Bk0IuaA9+ijj4J8yZIluLqrqqqmTp1aU1ODyBs9ejSeV0wp4eqyRiTmzZs3f+lLX/rEJz7xxhtvsGwAYV1d3aZNm374wx9CJp3OGmn+/Pko42PHjpEeM2YMLcoZyORWSGw7d+78zne+A4aNGzeCEFZxXcM2glhex2hpaSHNNQRA9hiHydb6Og0qlrJPPPHErbfeyiqCKxsoqtOnT3OZ6N/+7d9YVa5ataqkpIQ1Bqpd4QTJoF3Z147KicfCx3asvfnxP736vs9tXfJqoK3p5O5Nj/7tT6LBjqPb19qcrgTO7Vh0y6IXZ93xaH5JBYI4+3pTbCyriMba422NZ5/4x1/gat23/oP84vKWulOoduHKM1QmDtcbPvW1T//9L4ZMmDFh7m2t9adLB40YMWVuU+2JmsO7q0dPwlUvFF6ONgsDe9e65fd/6c8nz71lwwevO91e9FQsFpl+wx3f/N7v5t392MQ5N3oLituaG2544Im25vrj+3fkF5UUFJXKKxs5gtldDVK4ue7M4V2bvv6dp1nn7N24wpNfRBPwYaOM1yx8oaO92WqxQjUnj80fvtPeXM/FPHkZodtGzv4XwYEbF792xxN/MvvWB1e/84LL7bXabY01p1hgPPn3PwLqkd2b3L6CTUvfPHlolwieUSELMhvtme2VTCXRL9FY564jHZ+6tfLueWXLNzW3dcS2HfT/y1dGe91CwSOXWUDhyPxgQ9Otc0qKC+044BWdsZOBXD6d6OzcfsAPzulj89fvbm/tiJ9tinz7sWH+YOLQyWBja+zaacWI9dP14Zb22IhqD455Wpf7zWm3n230b9h+4mf/v0cKvK41W477fE4k79GTzTfNHfXT//PQt5+8PhKOt7WHHrhtclNLYN+RuqICT3GRh2ji3KOVNXIq9Hmca7YeLyvx/tO3bl+29khrW4ionmgssXnX6S8/OudTd09/bdFulzM5eCz3YEXQzuJVRz9z/5Rb5414Z/lBj8uOZAcH3vezjR0rN53keE2I2+cemPrdv7hl8tjya2YM4bhCZlZYsxvuInJ3AG7y2IEXlhNvJBK5/vrrcS0j3OfNm8cncgQVhXJCsyJKCAMwm8CBWyonPlFR8itpuZnFUkxQEUp3xIgR4AEGRtDK27ZtO3HixH333YfcLCwsZNnAKuKxxx4LBAKYpUyKxpOLdeFL+i/5117TQIIKGOCUAE6IAurw4cNJIy7hhOaTrq+vHzZs2IEDByj/uc997uTJk2Si4To6OoA9a9YsdmffXqu4WGYSzLQbS4988YtfRBCzQSlNIIdOnDBhwiuvvMIniwoWGDSBAkhMnNngp0AGxEqctMJMXKxFvebLvah61KhRkIZ/mtUOCQDDLSuKG2+8kQsdDAnSN9xwA9zSIvjMAKoJMmOoAANqRUUFjIGQAcAneKqrq1m2saggn1lDRWvXrp07d65cD2dcHTtiX25ytvIJLb0yKTPlLmYaZ4xRe4a9I8Z/LH7Tp7+JyrHaHYl41N/SUDFiHEERbl9h89mTZDpcnu1LXhs5bd6wSbOD7S0imiL96dlF0f+fvfsAkKSo+gAOXE5c4Mg555xzziA5KkhQEDChqBhBEBVRQQX5BBRBkChJJecgOUfJOcPBcTnx/XYfNO3M7OzM7MxsqmaZq66uevXqX6+qXr16XR3/tPyWqeJnj6ZOmTxyzvnX2enLvEpYfKdOmmCcf/remxZdZf3wgWml9LF1xQuP3vnuK8+ttvXeH7z5Ko9gnhKTxo/1t8hK69bg4BEMtvy6PmOnohCet9n3azYrQDrbXPPhrcXoxEAwZfJ7b7563w2XrbzBVnyTNDwHFeTfef2lOedfdMjwUWPfe7uGWayVxfxPRUxGotZsM419/525F1oCSlT2d994GXozZkzvM1PfD997Z6UNtn77lecnT544dPioR/5z3ag55tX0UyZPBIq8VZTUmjTPZSuFagi0vobx4ftvD599rgGDhwybMcf7b72GzxYJmX1uqvyk8eMEho0cLX7uhZek0E9p7ac18IktdZNRx5zp4xnTps9gphVZZd9s2Wb5tPSqsQpoDOu04b59ZhrX6hjz4UfTFpl30JX/eXeReQatsPiwf9z0zpCBs9x8/5jlFhmy1AJDPpo4/VPH7GqA7XBa2EybNmOnDWcfOrgPT55Rw/qMHNZ3xw1GT5wy3W7A0EGzWG/wn6HAvTNm6sABs8w9uv8H46YRgI4oXSFLVQ1EIbTvj5mw1KJznP+vh5dcdPZF5htJCR45YtCYDyc8/8r7PJCWW2LuYUP7k+7Wlwo+fu3NDxeYe/jwYQPfGzOhBm6Dyda+8mmwJrQnTjKGfDz3nLMOHdRv8pRpH340cejgYVOmTdt/19XCX3yKFR5h5YBXo6C1SHvBVTmnyuTt+v4HE2cfNXjwwL4fDx/09nvj7Qm4qO5WaHc++NoaK8wzhdPljI/9PPDEmy+99uE2Gyw2abKdaqkqLypSfoJoSwlWrp82jHkz5tDKyZWbaCunUveUAQllaLvttqOL0DupTfPNN5+CVNJTkZT4c845h7bH2p0xQAelkWSXW4lrvmTnrUEbpgApgoAxA7O/0uTwgyy1+NJLL8USLbODZVXLZMvQ3MoSLfzGG2+kgtPF6btYZWrFDxAk8GtpYY3Bk4fBVV2YsTmf2Byw6mAn5l0Tymi1DEiPh2qvyIVnnif2KIAGPR7kDO34t3/y/PPPL7bYYnyTvEVA+8TkiSeeSIOXLLT82kqsNlekxy2uqLyYsTlAKQ9JcGs5RzbcqkKE47WH2grKiqs5u7bGKmBDKsinJsa/21gCPfXUU1YacAbvUkstpdFrhjSYVHFXvq8pq8yl+bLEAkYudHBY2yWvshDo23/QIzddtshK600a99GAIbNSi/syZ/bh4tznuYduf/S2f7K1T5vqjRSuKbUXVwOTLXaaAQM+ePu1155+ZKm1t3r2/lvnWnSZeZdYkW7esl3QCuKAQUNefPTuuRZZZsDgWYeOnOOdl5975Yn7uZgPHDbivqv+zvNH4hpQaqVdy0/f/gMf/c91F/7hqJFzzmu7Al58S+jx777+8pSJExZfce2pU6cMHjr81svP7tt/wKQJ46jLl/zfz6fPaJnsKKPVFtnSKLWMIi3lyMhvZ9CQYZMnT+o/cJAtDqoweZ82efJcCy4+dMRsUyZPavWAf8sWwVpb7Yq9fgMG1zaGRL1qqWErKDohViFGJJAaPGz45Na+qQ6MK/884/j7b/rXiNHzsLjPtdCSfLoIW5RYw682ACo3aC33P92trJahxHxiPr2AanXmqUHwW7JYLmBjQL+Zb3twzEpLDH1/7NRHnx03cfKM/zz64StvTaITP/T0uNsf+WDkrP3oQy1JO+3iiz/zA//96Kx/vzl6ZMtyhaZ+3rVv3fnoB7OP7D/HyH43PziGhZjX+6yD+/zln6+/+8EUa4yODCQt7VPlpX/xA3t3zPh7Hnp5/ITJ19/+TIuHSd+Zp06Zxt/auzwM7edcdj9NkjH+smsft6ExYeKU19/+8NRz7mwRQKJQdYkt/ct/1WbMl4PCZIr5tOmDBvadOGnK8GEDhCXAJ654TF11y1OrrzAfeDsg758UWKMEzSCoH4+fOKV/ywkClhgzhg7pP3mytcTHg/r3eeyZdxZfcOTSi8xGJLy2OnhA3wefeHOxBUeNGNa/Zb1R66Xupr4pn/Y3KkQLJlVeXdTiHrWgCdGZqG7smlCibfiNpQkLItPssssuS42+4447ttlmm8gSiotwpPRLO4lLuEpwPkkOVhSUS29jVseVcqks9CGqEq8PiwdqMbeTmj068nwqq0JWMUY/o+Mq1yKHe4wYTBKJCGCVfibNFltsgXPrnI022mjPPfcUT3en31v/8AKiyY0aZb+7UnfnjFvEq10pYkyDhr81j45YZqBD94Xkn//8Z1srODziiCMo66+//rqG5irDtWOfffbBIXAqb0R8Boc18BkiJCN9nT8MVLW4SIGQBMSDvjQCHgnEFbeV8yklmnKpXVCoFtXgBKtBCh3A6gt4xjDMzzrrLMskzS0AT6sjYG666abSVFtWpMenvC5FV0gBJ66AJXIhomO1tGlNfdPwz9R671XnTJk4bul1tnr+oTvMUCCcMW2Kt42oDgMHD11xk50fuP7ieRZdvsVN4lMLR1VNgzcctnDZelXKKVhm6WOGv+W83y2y8rqzjppDYM6Flnr7pf+ahpffYHtQIDV5wkfeRl1ohbVmTJ1MsVtvt69MmzThpSfv95LoiNnnef35x+ZZdLlhs83R8j5rBZeGMHgYqlqlqCVQQab/SdJ/wIBFl1ttq88fevMlZx3wo99NmzLZ+5P9+vV/65XnFl1+NXsYFNCVNthqhXU3e/bR+yigEgwcNPi/99+x2qbbjx/7AfD/h1zbN1jr03LYj/QtnbR1+6Xt1EVPQuChNGHsB971pLyI6WfvpbXuzFneMFDEwMFD7rn2H2++8qwdjzdefPq15x4f1bogqVBis2KjOJ2zZXOzT3Xe2PK2YPhZ35x52pRJcJ40bUpr5Myb7H7QDRec+sBNl2+48/4fjXmX2MQowO5dLZ8YhsDUGR/zopi5T7+BA1uOIMlqUSZAtE0HkYAWJVNLV215M894W8u8yWA5ZPAs19z9PmV97eVG3PHoB/OMHsAGf961bzz98kSa0KABs2y19mw33DtmkXnmVuOKuCxRAQj9z1UiSdmo1prOssT8gz+3weir73r/67vPP2nyjO3WG33ZLe/cdP8H264724Hbz/POB1PfeX8y6/v8cw66+7GPdt5odusipZYlXPgw45Kot8hQxT0FIQoByYPS/POMPHCPNc644N7Hnn6biX3M2Imf22xZDTR8aP+fn3rLi69+sOm6i6+96kKP/veNoUMHTp1CY+5//2Ovb7ruYhzNjWGFPLVxj1V9Ut9kH24V+NpdWRTKIYBe2rd/P2uMvlYbLd5rGB74j6sfmzhx2qZrL0Zxd05fG7y0H236aRk+WsxQLVel43MrYYnx0/KCbMuOoXqbN2f0b3XEnzh5+k13vbTwfCNeeO2DGdM/3mydhS2AJk+evvKyc3nptwWeKgVAgei3DHkMIc4S6zPQffvVayNFFWpQGxQaGE3t8J7ivPPOyyIrTP/wS+Fw8SqmhlJGgc3M3EAmWttTKYogH/RIVvawwWNmnnnmWWGFFdZcc82rrroq5KahnOSJQ8OqhprLf+PQQw817HJq58MzfPhwerlFRViIae0eQQx7sgvYNOAk0yLrs8xiLSQBRT+e5uk3IoxnTHpvgUb+7W9/GyeA9cvt3qMAGSeY1KZ2CdTF/LHKKqtE6zeCpXZpwsdLtIzrDNiBKjxNxsFt8W+7BBuRABsg4r8O2KwpCQAJ8etdguWXX57DjDRk1cIp5CGrRSNYajRN6kX/wUOff+j2D958ZZuv/JRDNg+Zd19+dvDwUVThfv29Mv7xXIssu8x62/AnfuKOKwcNG0GtbzRXefp9+/e/99/nLLDMamttv58jTRZbdUNeKNzBTTItzA8c4t3TCWPHjH3vzdnnX6zFWswKNWgIzdjIrhHnXWolDuVTp052+EiebCPCrZIwi82KO6++eNiI0cusviE/C0wOGtqyr8gX5YUnHuTF4Z0BktYy9/TtN37sGNbuUXPMM//iy02eNKH1EI7a56FqK6Uk6iR8Xn/hv8MY1ydNgDbPqAEDB30q1djsq0YLLLXCgkusOGVSi/W92lLqkh5g1l3DRs7+3usvtS5UWjg3PA+ZddQ7r7xgf2OxFdecZ5GlJ08c3zKvt+JrzqlL0Z1FhD5EL3/kmXH8xQ/cYR4G4NlmbfHiiFqZSyVYeJ5B6yw/nP/Jfx4ZO2xQn+a/8akVCC3L6S0Pjpl1SN/lFxsK/VffmnTfU2OXXmjIAnMNnNRqCeXS8/7YKUMH02BnXm7hwa1bAy0qXnOxtVHz8Zyjh34q2y12SQ7uw4YMuPPBF196bYzNYIy1DhszWxRR04cO6i/94guPdlJKZ4kTngcP7Ddl2ox3xkwYxpI9hZW9rz+m97sffuX1t8Z+58sbSCBZc8H8rDTNaA9g1PCBb7w17tPFo5PZ+ljxamJOMlhtffvC2mCWseMmv/3++IXmpV9Nr0Fr/6zUeoQaPiXUxmR0DDZsWrIw5Yl93WRGc6JxuqjOXGWc5cJ2KNDojhTbGcplYudbT62kaLpowJYQ66yzDpWIZzYdVI+qrcrV5oKGdQsEaGY8Xm655RauRPA55ZRTWIhh4t1T1nSsWl14kVca2hugcMg2v8wyy3Ax8i6jKkhDk6uWgRrS4xmAp59+Op65GOEZEW8y8MPG1cknn2ydhknAUkAtSBiJxTsSZ7bZZpO3hhI7kgVWljR4Y1fmrgNV2xq8tuyuhOUYn9ZIUUQ+3JFCa84LKK2vy9jNsIzcfPPNLTK5x2hrrawudjN44W+66aZedbBl5AVr2yzktuYSOzcjO8uUCeNuPPe3zpa5/+rzHrv1n6PnXZiD+FV/Onri+LGLrbrBuDFvU4Y4eKyx7T6P3fbPd155tm+/gbWZ9quuqbYYOOjFR+956Aanncxy07knvvf6i8utv/16ux0y/1KrzL3YcqzpLz12j7dpnQLpOEuHzNg+bTHAfPzx8w/fMd9Sq4yca8GHrrto4rixg4eOaPGGbPBFPCjlDl3hZn3NeX+8+bKzV1hvC28XPXX/HTbLTfzvvP6ydREuaPNMBE/ed9uwEaMWWW61F5562CEzo+ea34KkqboMbXjq1Nnmmpd94rzffp/dfcX1tnz56UdefvZx57G08MnKM3USxX3hZVbZZLcvrb3N7iNGz7XgUis5CldlGwxnEfmPp9PU515kqVsu+fNdV52/xua7OIrn6Yf+wzfmuUfuvvy0nzv4aMlV1+eC3zLmTJloM72IRHeKADBD+/nXvd2/7yxeP3WAzPxzDqBZnnXlG2++N5Va/NGE6RMmT6cZb732bHc88uGrb3tnsbp9jI7DQQi4RtDL3/1g2hW3vXv9Pe+vvMQwCvoTL0xw0M2b701ZftEheH57zNS3359KrbfuuOqu90cM5VTRojd3nIHKKShx6vQZ8801Aj+/O/P2l1//gIfJsy+99+IrHGb6XHPL02dccM+o4YPmnn1W+uV9j746YtaByy8515PPvnXn/S/yL58+bUanrASxTS1eapHZn37+nd+ecdvyS8451+zDHnryjVfe+BDD/Qf08WaqN1ZZuJsLZwHwLUughecf8Y/rnrrylmc3X3eRj8ZPefjJltcm119t/i98btnllphj6UVnGz1y0NhxUz74aLLFUsv5oJ19dY4Rot1ax9jqrcTPf/7zEm+yySZ+aZ9OTaFl0jWZD2keroxUg4bj6KIrrbSSxQObK6PmTjvtxDVFcaywwnR6aZzZ4tVAel7GT6MDGKB1eSnWO6nURzywBHslgBPz6quvjjcLDMounvnJOA5Feq8k4hZjq666KmVUjeh5rN0C4hsEYB4HRYBo33339TZngOkpldeCR0VuvvnmjTfeODyOtDLbsHpZYMhCgxduvu4evGll7ljWQlrfOk0tXMAHMqhxZdkTYfFNHtMzeBVNLLfcckus2taAm5UGJrnH6ETWeJFS33FR3N2SEGvRjEL3CrQ2wZT1dzv0o/ffof5+/PEIuvJq23z+v3dfv+Qam9DgF1lx3Zlm7kM5nnX03Bvs8dUWZahpCptTn6dOHT56rvV3P4wxOLZEJ08Y64/iTkIY2u2YMsMPHj7b2jvsP3nyBPbhlhpNnbLYyhuwxLMlz7nwMiPmnG9gqzuKR41uHQyw+m+59yEP3nLV4FlHLLv6hmzqZNsbnxYXm+95ME2dR4q9XvrlfIst07It0KfPIsuuOse8Cy2y3KqTJoxHodFM5ulr0AGDBm+0034P33Hdcmtv6uXOFj+TFqBaLNxDRoxaarUNcDh5wjh/VK0Ndtin5WCZDmzK50uvKtyyyJw4Ya0td3/kjmtsUyy0zMqWZFZKs46afbM9D3n0zuvX2GLX0fMu5N0GHhRLrrLekGEtOzNNaPSqalF54haNbdrHO208+wcfTZ08hb+wUxdn3nad2e994sN1Vxg+ekS/ZRYeQrI4n8w2vN+um8zOpb7h8l2KewhPmf7x59Yffc8TY4cO6rPcoi0mbS+nOvdmw5VHzDmqv+XH4IF9+OgzGy82/yA+ErR5YcyXotfAOF7qTjvZa/uVbr7ruU3XWWyxBUc/8+K7Xv1cf/WFqZIvvPLebtssTQMW45G3ae2nL7fkXPPOPWK5JeacMGlKp1iIwTth0tRlFp8TXC++Nma91RbSDckGT979dln17fe88zDVGqOBqFVAGpMTJ0/baoNF77j/lSGD+i2z2OwfjZ8skm4+fsLUl14fu+xio5F5d8zE2UYM2n3rpSHcKWAWVKXT9IwCPkre6kUukwf9CZQUkdDe3HKiYF+M+JL6nIyy0A6dk0i1ZSIVU7KUSiKVRTlzUXSEmY0RVC71l7aEgkgxodBXQrAgDd5QGD16tMP7KmdVBam80gvQbilkwlReWhpFnFVbfLDHO0KJEogJbqVXKA1PoFqtXUbWfSDQC4NgQXXK3ErPfyPjGRG3mcuTAH4A6wI1xvxKIFkNzSeL7LRt6wSiUoarMo+CiLUN3ogfVPEmLItauDAsrF5ZuAy1th7JDkwrVe/jVtsceZq4xarKamt1xy32/JIuRUQVpCe3fmsrCB0dQSkbbLBBbDGJyfNQSRifcp1+/ZMPvvDukAH9WJIqyVWQhjHbgS0tqlir/XXSuA99167fwKHTp0yc2uJGPAhRTtiY6zdwMD2JWlwDq3jzWtIS84y4/9l3bPpXyinZ69efBt6qzs7MCx8n+Gl9Q9ELlJP6Dx7S8hriDD4zg1o0tk8x5IWC0xbD9pBhGG7h/9NHBdUvvpVy8tTpay0+xwcTpkyYMq2WCUZlZx3B/E+z1APxP3niBOZriyKqOYlqLdSmfMtrfBYn/QcNpsFz76mcyWBbnShA84x0ZO3Hr48ZzzRbKbC5auMBk46T95qs5YQWhzYwySdB4JEPwE+L42U+sNUdpWpZRUFBtKI5hg96/s2xXBFqYDWIeCvAesNb1J9ga0Uxyyxe9sVYS0O3rnx8SozWTjByFa0iqNEnTp22xzqLLj3fSKJbgwyQPT3r6Qcuu+nC79jkVvsqiv80qfYdNID9t2VgdOzj+Il8NWcaOqgvJWnK1I+9mCihAIV9oKMhHdkxrUWlq/6yUzRl9LzLTZ087oN3XnBCqJaqnshMQ/jqzPh4wqQWy7TXAgYPmmXiJK8PtijouOJEgT11GTSwT3yPqYYiWnCYOmm+xdcbPOvsEz9qeZOhWiJqhp/hQwdMmDyVA4zT0FvaetLUwYP64Q1jqoBbzvBA4Dg+aCD3hFm8zFp932x5DWPU3Evxbnr/9ae8sF4bqlFBXOGEh8xH4ycJxxA6wEsY/cgAYKePG29YrhaMz9K3DqFDR8652EtP3mz0J72fPas4pILWP9gbN9HLx7MMHGAJ1OKbLd63ovA5earzhVq+UMtTv2Zudaspk8ctvcYey6+7rzElDDoV8/g/CbuoxT14JHAhc1QlMaF95tn/dCLJxzUkHCoOZrRlpp0L04SCN+qRK7htCAeliJIq+ll0KkXjxIxllSLgwrNMwZI1j7DIIJNVJ1T5ZrKNW8zkecYDxoBpywIn1F9MulUXt365fGScB//N/A0e8IYHV4aqKrgCSfzkw81kr6As3IJLJFaxRFbjN3qKSAk8zWpRkL173RqjJ477IPQK9dIBeJWM//BdSpt1H/ux6nxSX98/aknRgfmhWmhazedU88iHtyieftbCFUGaGGtROn2LuT0jH6sLiSeNG9tsnls4m9nXPVsZbJGfSTRyvFkPTMivnKkgrYvVFi15Qqs+8Rn/WUWaEICSYcKhkJgsaHGyQQCyFnfL7p7HuQnsFRSBGZsYrS98foatRRr+LT4z3vJsF1DoRrekYtyEaaFEqzgLNU/mD8e1iI2u0KKyt8haS4UmTpnh32Z2zZZS//f6aHzLx4zDjG6Z4fBKPAdLKhKLCvxLhvn/zdq8O/zQJN/7cIKhxFrCWcqmHfxMmDjV0S1e8QiGqex4Ej/JmfOtun7zWCxVEk5Y1pne8exqsVjP0mdKyzFfIQMEv9MgzfjFGBf2wA1j4yd+YlYX7yzIlvgW3e9jFRHIcnVioEsr7p2IS0HR2i+LMUXQJuNWOAL5BFnKJgQyBjI2ssVMsBTdozhZpC+IbwLDiigoNG5xi/PgNquLgHhXcxhrqxQMlEQ12MtydTqfwUke3mAJ8xn/kaaLsJpBV3PAHPA/eVu090/O4sjXMdOK/idxg28wQG4KCsm4wmkYhwp4+yzBp2NLAYVG3+YhzXhrCXw66GHgMyZb3qdsNEfl6OMkAznjKjIU3nYSnnnui7EN/vOs5sP5vN0uXKCQERPC8qm69lltuoDa1qLmZgyR52iCVsWyJTqT8HyyLH0zAzhxHk2U2MpVC9u4atGJP+UjC7WIVhb76dNO+beFu085Ca5aOfs0qlN4Kio037g5OD8b6+TIxxcRaGpE51hKmlrFVFhCICGQEEgIJAQSAgmBhEBCoPsjkBT37t+GqQYJgYRAQiAhkBBICCQEEgK9AIGkuPeCRk5VTAgkBBICCYGEQEIgIZAQ6P4IJMW9+7dhqkFCICGQEEgIJAQSAgmBhEAvQCAp7r2gkVMVEwIJgYRAQiAhkBBICCQEuj8CSXHv/m2YapAQSAgkBBICCYGEQEIgIdALEEiKey9o5FTFhEBCICGQEEgIJAQSAgmB7o9Azz/HvfXc0JafOjZW0KwjQaQyPuvOahDv+txGxete/QzYOiJQd1YzJrNAfbkNhutCs44cthzvG1ddOGslEjTrR6/lAOJWHj9htZ6UW8ckxOtF8xMwW1D95K9elNEJmvUimHGYBepFOWMV5Tpen/JZx+Zq4S6YrCOrrXzWo+YtwuTcaqa9Wr5F2jbyLZ9MbvtptU8+YTJYrTe39WS1Bc5WPLNAtVUtkz5olklQ1aNPOWxppuC5jjLgQ0atNOsnA9kk8om4VlXXcok/7Zt1s25/AmY95L/nK+7xTVPffYhPP5RrqIqf+QCTT3tWnLz9hMGbj97jtpXTuo2VwWf+ozztc9NeChxiNbitI2Ws1rfuQS34rHt7IV5HmsbKVkRbBMDltr1GqPR5gFBfVsk/blGulIk20vno/aQp03y5e3qHSWUlzJg+o8+MTz7ZmEV2JEAofVG8hVVfUJxpFh9QrNf1cSstH2KqF0F61qQp0306EbfxwfZ6UcZq65BXt0GPfGMSqz53j1XKYf1EYKZpLTLQon7UrfqYm9nn2WdMngqGmesqAy2QfvpRnTrw6/NjLUx2GM0Z033C1Tetfe+9bvKpPVr4qluztCA3Y/qUqVMmTJ0yHrczZrTMnnUAsZXH+rLaMsJPnYTVaVMnT5syceaCL8d1hOmZZzIazzRjWkdo5PNSgKdNmYRPnRLDH8/8cctnb+t0TZ8xfZYWDbtuQmBqm6VPn2nTJrewapz6uG5jlAlepbOP0HUcAIo7JmdMa/mkfQevHq64+2DkUkst5cPvAvXq0hCnWvXrZ0Sr24U3HA4ePHj06NF1VIXxFx95LfhwZgf5xu3w4cOBUEd1EEuoufr2radMAnPgwIGzzz57HVu/cajOOuusI0aM0GR1HNdU3LBeX3HVTAMGDOgQzdaBe9VFZ5931JB+feqnus7UMof17et7pXWbGADYr+8ssw0dOMesg6wx6jaDtQh868e06zeFq/O0GTPmGzVk8rQZlNc6gkDhmjYdsHUb9LBqtTZsYD8z7eJzD+8zc/3Uw1YZMOLVtRPN1LfPLEMG9oUtunWUgbqPzzqWph896yDDFFtkTUN9S67Z5l56jS0O91naOiruyE6bPr1v0eeEa2IyMvkU6/Qhs845bdqUyePfn7lP3zqu/8Co0TvA2/9mJTbTpw2bbYH+A4dNnTyeDve/j2u/a8wIP23Q0NF4mn2+5WeZxYxcN5GfNnVan7717Zt0p/6Dho4cOnxu60yLjdqh/N+c9e+bM808ffqU0fMs21JObV3zUw4/+QTxp7fp34oQaFUO6qlfVlRqL0hEI6zvuqVxmHUjVnuXuLJn9O3fuHavK+UwDtVtCq8rb4XEZkydPEu/AYWxXfJ+xrTJs/TtHqxav7RCSD/uFdf0j2eySOsWFwWwm3A609RpM/XrJvrI1Okz9esmwh4rgK4pA92ktTvQ0etrag1GJk2aNGjQoG6hYk6Z0rIv079/N1Bl6JfWuEy5HWjtJmWN3YZuwaoFxuTJk+u75RIod9yi2fEN/eL2njBp6sBBfereNw3fdbPkfMr0lClTBeveNxvBKini1DS43iuimBTrDuyEydMGzty3m8hAi4dD//51Xrzpmx1UOMybvA46SORTSf/kX25Gps4hgwcXxHfkNlOvs0BHqGV5sWrqHDRwYBbT8UArh7XugrRdvHaaMmli3yH1RLVlsMs6Z12FYMrE8bMMHDRLHbcyMmTq5CWV0WuU7lQPT6Ger7h3eATL2vGzgCmhZWTs6Nj4GcHGhYLJ7sJqC6bdBNXEaseFVi/qOJECCromso2gXHdeg8luweonL6k1oL00XyOATTJQ0C+qvW0d3+psGp2lxWG4Tz3du3PCU18paiir1bZFe+k/BmsdfW9aisvQzALtMVHhc61ff26j7Aaw2oJE/VwZK4SokmTJVaYESpaw5dXHdhOUINpJUVhVcvnqdBJrhcUmVgsRqek+PPNkjeWlAHMpbLPbiMnskZ5GYr9d/2q367WboOvUsRsJPNC6F7Bdc8Qr2Td1wLxHfl4qhD1Vl6y3dh3pLeakEgmpJE0x5U6JSaw2AvYuiyrGYirMulsWk02dYmASY0s8zRI3AqsyNJPiXgac9Cgh0O0RML7EQKMm+XBBxco8KkiZbhMCCYG6IJDvdPlwMfHyT4vTp5iEQEKgZgSiu1XY6SpMVjMzJTMmxf1/YNEGnPBcI0eOFPYsW11l2k9kKG6tfEw+/D8FNPEm4yELKLytcBP5KlFUnqvsccnI7GlnBTKusgBO2go3jcmMAe8J/Oc//5kwYYIjX9Zee23nFOHhlVdeefLJJ1dcccU555zTLZf3F198cckllwz2pGfwW3PNNZvGbbUFZbUT+OCDD1TK2wVZZDG1/KMsnAWkbytcTKpBMRkDWaArcJWvbJ6xiM/H5MP5XJ0e7oKMZSy12zcZ/Nj2Xn/9db9zzTUXMD/66KM777xTV11wwQU7HduSDGS1E6ikb+aJ5PNm02sWKWU+nM/Y0HBWaBZoaHE1EC9mLB+TD9dAvHFZuixjqoy3d9999/777yeHs80222qrrRY4PPDAA2PHjl1vvfXisLuu0zfr/E5M41q90ZS9bvjee+9pNu33+OOPf/jhh8Ku8ePHGz0FMgYMr9pSjN+I1OrGrEiDzvvvvx9hKcVnGRsdcOolnQwz48aNUxYeKHAigxm1UJcIi/Qowo3mqiR98IrHBriC1TFjxmQpOxHDjIcs0MVRzaQxIAXjDTfcYEfe7SWXXKIWhPmOO+4QuPbaa6nvEfPvf/87pPeqq64iGG+88cbll1/uEWp+u9pFUHEb0vvss88+99xzmVTrXyFCwXOGRtY35e0KvaCLS1G+xYsx7CLjW57JLFx+JDGkZyItZRbOsjc0kCFZSd986qmnyKosN998sw4bw/g///lPkXr0I488glWRDWW4BuKV903Eu2YvKM8VtjtXivKNkklUNr6lvpnHp6pw1u7AJMYPPfSQudLU+cQTT+iDSF199dUvv/yymPPPP58xF9Q33XRTF+mbPf/l1Eraku5y5ZVXvv322yuttNLSSy997733ajwWyhVWWOHiiy+mGWyzzTbzzDMPUm+99RalR1vOO++8r7322vzzz7/55ptfccUV1P111lln0UUXveyyy9555x10ll9++X/84x/yLr744ptuuqlWJxyVMFNtmqCMZ6tDJ1Rg7LHHHtt9992HDBly6aWXsrxut912KkhvI3y77LKLKkiMMfELLLCAsaCZDpSKC4gcWI7bN99886CDDtJnLHYxs8UWW+hO//rXv6ItmoZhMeZdHNVgr0AaF1544dVXX53tnLiq0RlnnGEhd999933uc5+zg0Q7v+uuu3zWgKyuvPLKNOBVVlmF6X2vvfbSFvfccw+azZSEYsyLY6KaNHUjKcHYddddmS2vueYaB95vv/32VHmaDWOk/jV06NA8GkwjOiwc1Nr4y17SKb2gi0tRHvCSEtUVxrc8k/lwWyMJgTeSEAlbSVaqBGOPPfYwpLCnGAxJu98GDcXBXkkk2+2bOuASSyxhoB41ahQ6ZNsQbV26995745xs5+veFcKV900zEcC72gxVvm+am7beemvGV7qaNVXzpSjfxCUlKvXNPESVh0u2++c//3mT4E477bTIIouYOwwdtHkK3oEHHogyZZ1Ov8wyy+ibJLkr9M1kcW9pcfM6tXvnnXemzdAMDLK0STqlW92DuuDwR+0tJe1B4+2zzz6PPvrol770Ja37/PPPyy6vkddcsu6662p+GaWkLX3lK1956aWXWspo8EUbo/USO+XsuOOOL7zwAm2Ys4Rlg5mMooMrE4N49viNWq+nn35a4qhXg7n7H/LsTwcffLC17CabbGKKpTuCy0pDFXQV02rWFk3G8H+4bL3p4qiyJeelEbc0b/a5X/ziF7T23XbbzYFWBNisY6k599xzUwXATpj5zNAGVJE6Syc+6aSTOJ8YkpovDMWYF8fgX/8ivTR4HG677bZWy5bWXIA222wz0hKHXRagERWkLnR6L+jiUpQHvADDrjO+5ZnMwm2NJJre6M2M8sUvflGNbEP5NVwT8mxrNCPSoEABku32TdqA3optyqLh2rRi+lhrrbXOOeeciy66SOdtEJ8dJFth31RK1+wFZbgydGCbXaATpSjfOgUSlfpmHpxqw/l2Z9iipJlZTj755J///OfsnqYYFh+mWxqdqXOxxRYzb+qbZtsu0jeTxb2lxSk0d999N0V2jjnmsNQO919hGrxBnzsBJyfDqJSG/oUWWohybyTV0iJNElbkVAo9XNdC57///S8PRSlppcZin+2sVqpqSI9bS0ayxbxB91ULhv8HH3yQJrfBBhtgkn72zDPPUICGDRtG+Mx5fhXUUONTcUV0A6sL0IEFn3gAml501lln8V2mgdkWYBjGKuWyyRgWc9vFUfVR2EwaMU8AmNgNN2xFF1xwAR2F1m4A8giwHkGb6e766683AHm6xhpr+FKvZZ79Deo+AUZB0zRZJIphL4gxRd12221EAqvEBpPEW0WWXXZZFncf8aWaW40U9E3J0LFM1X/VqBN7QReXojzaeYnqUuNbnskItzWSnH322YSBMYXuy1vM2EL4jeRRnabJdh5JDJPGMn3TBGQwlMWuqeUoVs0g1AVGvuWWW46RiM0vttGKcejcmAr7Jia7Zi9oiyvyY9WkyWhstmtMpp0iRfnGzUtU6pt5ZGoI59tdW9M9rJxp8LQOUyEbKLQpcuHsTsilp01REQ0gXaFv9nbFXQfQEqx3GoYZ2kCv/bwPRMUxgFJleJ54ROu1mULFtAJjBiYokvmlFnCt4XigkzMbs2cHHU4yVHbdXhq5ahCsarMozkxmAsChsHph3rhPj6cK2+gx7qsmfZ1ERspgr9qCOp4egDAHICYBaE5lG7NTQTOzELLe1Xk23njj5mNYXLUujqp21LjYDmkErBjY0m6Z0im1hxxyCEhvvfVW2vztt99OTSchX/va1wTYk0BNyHnXkPZ44xMp2Ytx6KwYzBASDr5MILhVQaaRV199leKuItYkTO/qRbB5Val7vm9Gv7N0WXXVVdWuE3tBF5eifOMWSFTXGd/yTGbhkiOJHRibeDhnxTjssMNsPekdxjqyFB0ky97QQAGSUXRbfdO6dL755sOzFTVnHozx7zJoUxRIvlwM2w3ltgbilfRN9WLVMvigz9oFk642Q7XVN40YuCU5pOjQQw/tLCnKt0uBRKW+mQen2nC+3UkmsQQv0w91jhGWrYfufuONN5JeO2CmmFjFHXnkkQrqCn2zt7vKGH20RDj7GmU0jyGS3sMjnB5PC+cAw+GJ14GRl0JPDaL0sI6wysvLj9aA6/bPf/4zMw8Vge6OTmzfU0AZvNlEq5WqGtLjmUauRDyzqWPScMlJhnnV2oPPvTUJHYi/AVXeqMQCJKWCAoEaSqwtC0DwIy8A4WbjQsdgOj3zzDPZxihk2DbvdgqGxTXq4qhqRxyGNGLeDg8hDHcpUsdLymtVFmxsRX/729/YCdgPrOsAbpBiz6PN8BQ3KnmRg+jKS0KKQejEGPyQT7yRXmyomot4MLfrYhjmSKDDehdF36T05PumhassqtzpvaCLS1G+ffMS1aXGtzyTEW5rJPnrX/9qRcccQB6Ih/GEhBgY5YoOUkyqETF5JLOiSa9wcd80FJt66IjWmXqoS2+1nLbTayvS1oGnTR6o28Wkkr5pSrKtZ/lBGVI1w7uaurrODNVW36S0meuJkASdKEX5VshLVOqbeWRqCOfbXUeLhjZ9kGoevPR4kyb3XVZ2k6M51FxjDOk6fbOLerXW0BIpS0IgIZAhENNqdpsCCYGEQBdBIPXNLtIQiY2EQDdFICnunzQcG6RVbFzWVcZWFh23Ebb8kk5YZAy7Ec5+s/S2XSJj0A0KYhotH8GV36ygKNpt8IzVqF2wGvXNqpPlakIgWM2DKSbYC6CytghmCjCU2BUpBTxtEM9YCq7Qz4prLbyldJewBH5DPCRz6ze7bRBjebKBgHKDnzxWwXzESCZB/qmYiIwqxNM85a4TxmdWF1y59Zvhr1LCxQhEjJQCkV7AldVUxiAlIEHjLqVkZUUpbnEinK9FpAlmPA0piryN462YcpQYQGW/IgO3LtI3sY2TDBxYCbsyVEMkgv+ANLKIdxXXuhEx+ImGVmI+rCyMeRRP41Gk8UikX5HBUqRsGs9RaOW/+MzqkrEddck4z+qiallY4qi+gPQSuwSi+lnKuK2cn2pT4icrK/K6xUlw5TfCApEMh6Z48ha3fiNXc36D2wAq+xUZuJXvmziUMhL7jRo1iO0K+yb0cB48yCKc3TaIsYwsBKIFs5gIRIMGtmIEArH800AvnuarEGma8/s/Hak5RaZSEgLdDoHo5xnbBbdZfATKPy1InG4TAgmBjiOQ73T5cDHl8k+L06eYhEBPQqD58p8vMR8uRrX80+L0vTamSbaHbocvAQqes4DbtsJZ7SRwCGh229BAxkwWqJBDRy5K6bBIZ4kI8Afl0dVQVgsYy5eF+Yz/LFCcPnsk4GWDOHlTOI5MyZ7mKXckHAS9HOZ0f2+ieCEyFuKKvvHGG70rGbeK4Cbu3fOsLK9DOFYoe5rFp0CDEMiaPgsoKB+O24hxOIDjlYoTNIi3IJsxkwVKMpBx6PVxL041WsIr4Q1LwVUBw1lkMZEm9M0olNXTK9f6piMg4i1knc6b1t5N8v5DdMCsbwbD8S2LrC8HnfTbHARaJKmNKTXiO6Vv5uveymDpST/jsNP7Zp7htsIZzhJkYZZjtzqISU3vUBGniuUTCNfrardvBjM0JS91RKGpb1YLflLcSyNGuL1RTp5iDiBqZD3COkN2GLD46ACokFey6Nwu4azDlKZej9iaOaRZGiUdxBGf8/XaUIMU9zjqxLRqOg/oYJWVJTLiPZLGoR+RRqSMBekjjWQCDp/xrrczRrSI9xQbAXXQ9F4voDTxdddd5yQTb/H7vKgdPe+K0Q+iDcHYvb5CWg/R6xI0nNNKlsiDFinZN3FJlkJmJCNUVlzekxPfCJkpBqVdDvOjR3D48MMPO5yKsJGrhko4WJSuUEziXMDwlYVbemZrnxVf0DcDT1ny6WEb8U3rmxZgVPZo+nhxmUYSY6++mf9CsDEctzpv1/8KabEIddOYkPxgvkCWQq48EgiZCcnvlL5ZFYdN65tGp0Am649ZXwuGDXfZCBZpsng9oqAv65ug5oJitNQvHC1KS2Hwcm5B5Krjb3BVvm+au3Fo8HFSnw4rS+qbNTRBbz8Osi3IaGy0NNrkDjvsQOi9WUzaHFDgHXnxTnVdf/31vfhvztAfHJDi9txzz5XemaBoEkfp2yJel/jaONSHvZyuM2+44YYxyzp+QYyOVC/3sqg727OFAViMyOrrvWzDDR3XITzCBkE2RacvOVfeWANGR6M4pduhuc4AYXH0uSi/PknrIIitttpKZeV1KIETyuXyWURqjQQNOmwh2g6rPjSLeYdDmf7tVGjxjTbaSIxP0rp1PA7zXnf5Cim2e8AV0kX/9v1UZ3Q4BZLZlfQ6Nyn6prOJfDvWOTO+BkBImF01ogT0NmJPYBoNQrscFowejvfxGSnrZ5s55jDMEz/HXDZCwoM3yOie++23H/Ozbuj4HaOBGJO6ExUgJlJfa6tvOmlUlptuuomuvPHGG+sUNqaa1jej+TSow/uNDG7b/UKwHqrpjT9d9iukjZbJ5tDPS37xOE+qfTObnDjJirT7VLYBvBP7ZrUcUqYb2jezNvIhAqfuOG9NfzT9Rd80Gjgx2flaF154IWXdKSig00/ji+OmReMbXRy84tnm5I2+afKik0jgXBTHGZmzDJ4OFvMJbSU2Qksp3zfx3L2+EJy1S5cKJMW9sDli9GH0ctSjfuI1FCtIJwFRJemR+oO+YUrTHxxIpwPQ7P/+979TgukQOoNz9wop1vu+IxxaY1hgOJDrtNNOozE4rssKmNuM04KDbL2YNVNSr2kGzuOjdlPiDRxiHMNkHGF6p5o4mJIGr0TfJDcYsQdQGgw3scedpdcE8f1LabDqlEOKPi1NAt8UBLuzV+vLfFCzijjmmGMw6bsMdEQHDiraMsMKR7tT2Y2ehIFshH9UfIXUJoAqGBDry1K92qW704mZhlxRdiGvFfzqg/m+STxIBWkJWaJfaibfYSBsZt9GI1AJh9noYbHqIFQs6YY41E0ImF7JUtA4CbcK3XLLLZVCG3DkmZWPTSSdDgP6pllf37SYb6tvSkyfQOQLX/iC9HFyq0GyOX0zmk+D2hBzWJvxpMwXgvVTxkWQEhJrNuf6GZeMNo2Wgd5JP5N88gP5/DivD7JqWWtZPpETY6O+SXHvrL5ZA4fYbkLfZFw3r1EtbBwRVEvirG9SiF1A893xW265hUXMNPrVr36VCcOkwyT35S9/2bjB/wTUWd+EuWTUZbo7r07dlpaiFIoKFV83r/s8Vb5v6oCqgEkSwuipdowsqW9WO2IkV5lCxGL08eki+mKYWnUk+q507Ey8xOjohN73GiUQo5OYPPQNk5m5kAFbyiBSSLpO9x3hUF0su3HuM870XczHqbq6NLL6cJ14nMmRqMqiJ8GQhU8vpYhQBRjUdV3WDqC5cKJQJ+ZigyndiaoOmBcpQOM3NlFljDUskYYwow9ThLyMhRKg4wB4LSJQX8CDGp59Jp15ADhYUopZR8DTaHRGd/v1HGls+VmcqDI9jFWPnwN5qC+e9WqX7k4nRNT51mSJtclGTZiOsr7JXqUhVJOuRkjMIhQIay2HeZOxeFRfaSmAtF0O86MHdRlXFALCbxLFMwlnw9Y9GyfhFpwusyYTHbj0LyX6QqcuRgNgkyvTN4GpXwPQ9qOuzbFH9mb2zUCb5mG+1z31RH3N6jped9E9QQo6Kzqavb7JFZ66YwBRQasUo0ps0Be0WrrtOAKZ5NNx8+O8Tqcb2miiYloWknCDfOf2zRo4bE7fNBRQJMiwCcUXCbK+acOZMVGfNWvrfYxurEWOxtdqzEnEm2kJ/rDVeaMvZ30T5prAU8t16rsswqZObRThjjd9nkKZvol/IzY1ybRuy86a39qbkkDdSn0zj2G74WRxL4SITOsYTHpUAfOZcZ+dmLWVpk5lt341xVoQU+aIYHiP6TY0e+qpX0Ys39wKIoWk63TfQQ5tGuCQlkDvwbC1r9muTqx9RsaEiqyRJft6q09TGTiYCmDLPufVWB3YZVo1jBqhaFe40rcNXrRka3Hp4S895cw8TfdCVutIYLa2RsK8289KrWsIzlYUNnZPPvlkzNPgTfnULCOmSYhU8G341re+Rb/vFl8hrSs2nUZMc2sXW+1kQ48jwyE2+b7JjCcZUSEnpkAdVhYdUy4KBKcaItcImQ9QKuEwGz0kJvnBDLbNtUYVHDZUwnUxA5e53GTPN0ZHc4sNy05+gOCKzliyb0b3hK1Bz0YHC5+dSQYzbDezb8JHu9NRKvlCsOHFYM7HwE4pwA0jnSa+PbrgTPK5MFHL8uO8RzROO9hGeG1nxei3E/tmbRw2oW8SEL2PVm1222CDDcw70Tdt+J933nk+MU6YLSEMffx2jH5W4PRyXjQcYIDMmG1uAqy+XNw3jX7GSUsm46FSGiSMZfomTZ3dzdCB7e7yheAGodRBssniXggg6RfFw0x/oKiZnNySRfYbdj7mKNLPq9LSNla3TFAiTQyGJHJJs5c+iBSSrtN9XTjkSMD0Tg1lRRamwevMdWTbnAoQ3qWW9aCDp5WPrWq2MW4MjHYUKbr76quv7rO1VBZh078xRS4pQapvs00GEexZozNvIwtF1gjrAcsqtm0DAZqYrxO6n5Gh1tDw3FNuGPCMpBrX9E/r2nXXXWkwVBxMko1u8RXSzyrWnUMhpRZUZAP+NtxJL8Eo6JuqSFSIGdseDZWYWa+aMIiNR3S+xmFQIYcxeuBEN8QM0cpzaFptnIRDRpehheiJHHXYqo0D+pRhzUspDHj6Wlt9E/LwhLyltfRe+bCC5R/f5L6pZXVPuEEPwxTBMl8IJiEqSNGxvWCVYpyp40DXOEHqdpTzkl88zoeJl7GD+DF2dHrfrJnDhvZN6oR5zeDAal7QN3U08QY01neTEcO86dVrA+RfmIQTGKtoU62+efrpp+f7Zjw1Z1mN0/6tXe1m232Spe59oUzfxIbex9zGomdudamsSd/o3WW/ENw1u2E9vSO6Zg07zhVnDEZW437HSTWIQtfnsKDiFkXGGkNMjPUFT7vmbTditWsC2Aiuur7kd30OC9qle/XN1CsLmq9L3XZ9Wer6HOYblEGdcZAGn4/ssuHUNxvXNA20PDWO6eZQthxkTFWWpTkbsFuC6DbiI5zFZPGeNoe9rESB2jjMmG8Ez4gX0HcLz4CU0c5CPytXIMKRpSVnK9QSR3xUNgvH04jMwm7re+WLUwqG/RawFCWKj8R+JWgcS/WtYPelljVEu5IvpUtNNY0rwk2ouIJCVNrlEFfBTyuDn3CY8dkInhEP+n4zeRbmnOq3wr4Zef1m2EYtIiYis3A8qu9v4BbDSMZG1vsyVD2KsEBW2fpykqjlEQicQS2yQlnSQK5oxDypBoU7yGHGZ4N4DvrBpCKAEGG/fOr4yfCEyafJwpEyn164BdlPR5iCBG4bdEWJxX0z4jEcPCs9wn5T36yqLZLFvSq4UuKEQEIgIZAQSAgkBBICCYGEQOcgkCzu7eMei8L203Veiq7PYQE23Y7hAv7TbRdBoOsLUtfnsKApux3DBfyn266DQNeXpa7PYUFrYrggJt32QgSSxb0XNnqqckIgIZAQSAgkBBICCYGEQPdDIFncu1+bJY4TAgmBhEBCICGQEEgIJAR6IQJJce+FjZ6qnBBICCQEEgIJgYRAQiAh0P0QSIp792uzxHFCICGQEEgIJAQSAgmBhEAvRCAp7r2w0VOVEwIJgYRAQiAhkBBICCQEuh8CSXHvfm2WOE4IJAQSAgmBhEBCICGQEOiFCCTFvRc2eqpyQiAhkBBICCQEEgIJgYRA90MgKe7dr80SxwmBhEBCICGQEEgIJAQSAr0QgaS498JGT1VOCCQEEgIJgYRAQiAhkBDofggkxb37tVniOCGQEEgIJAQSAgmBhEBCoBcikBT3XtjoqcoJgYRAQiAhkBBICCQEEgLdD4G+tbH88ccfz5gxw+8srRciwtOnT+/Tp8/MM89cA82gJntbedFvlzIirr59P6tUcJXRRKFMEVmyzg3gWS38Zth2Lj/FpU+bNi3jTaNjNdo90K5cBvJ0iktJMQmBhEBCICGQEEgIJAQSAnkEZqZs5e8rCcuS16FpmdS4SjLWnKaORdSRVM3VKZOxANtYC5VJnx4lBBICCYGEQEIgIZAQSAj0EgSqVtxDs/R70003ffDBB6ussspCCy3k9sMPP7zzzjvXWmutkSNHFmif5aGMxI899tjbb7+90UYbtbUGmDBhwuDBg9siFUReeOGFBx54YKeddkIkYnB42223TZ482UrDtcgii6y00kptEen0+Ay3DNsFF1yw07kqZuDf//73/PPPv8IKK3h07733vvLKK1tvvfWgQYPeeOMNMrDZZpvNOuusxbkKYlT2yiuvXHzxxZdYYoms4gVp0m1CICGQEEgIJAQSAgmBhMBnCNCZKr+Yq11jxozZdNNNg8Q888xzxhlnoHDDDTeIoXEKT5o0iamYI8TUqVOlF54yZUr4VHgqMsIeiXeJPPTQQ+mCwlmk7MIeUbu/853v/POf/5TLJRIFVzyVQGDixInS/+Y3v8GD9CLd+r3rrrs+q+pMM1H9f/azn4lHJ36VGCnduoQjJiOuIInFF5SYpYyMfiOlxCgEfZFxW5DXbT4mKESJL7/88oYbbtivXz9szzXXXMcee2zw4zcSICivLMGSX1dE5hNE2G9rUZ9hFWX5FS+XvHlOitNHgpYyWvGM7CuuuOJ6660XPMw777xYveOOO9yefvrpwm+++WY8Cs4jS/wikoGjdOurn/zkJx4RmKhUPnEKJwQSAgmBhEBCICGQEEgI5BGozsWFYsdufcIJJ/znP/95+OGHx48fv+SSS37pS196//33F1tssW9+85us71S3AQMG0Mn4OnM3l16YJurXI5fICHsk3iVy2LBho0ePFsgiZceomPfee+///u//GPLlCgZQcEkZNREYOHCg9EOHDg1qcsUlGcoXXXQRVl077rjjL3/5y1dffRUpSqRf6WX8NPlMwhGDZkZBMvEFJWYpg0mJJZDShYLfiI/byCuNSJTdRkyW1yNVo8secMABTz311H//+1/Lj3XXXfess8566623oqxgCUF5pQ+W/LoiMp9AuExZGbfyZpyUTB8JWspoRQmT8u65554PPfSQgHaHKgq2NdwyvVtszDHHHEhJX4CtBBGZgSOlpZTEBCYqJU26EgIJgYRAQiAhkBBICCQESiJQneJOx0LlpZdeWmCBBXhK0LroxBdeeKHIUOnoZMK77bYbL4gjjzzyy1/+MsXu6quv/tznPnfttddGsoMOOugf//iH8Isvvrj33ns/+uijwgyxLtqb3x/+8IfcLX7/+99Hcccddxxz7GGHHXbLLbdIwB9m33333W+//V5//XXqqSvo/OIXv+BOQx1HLbtQEBMKIm633HJLyjF1UwKkrrrqqi222OLXv/51pFcKm/0mm2xyzDHHjB07VqRKWZb861//QnyPPfagT0eJLMQ///nPUbvgggvESKkgmwbq+Je//IWvDo+RiBfDjeSLX/xiVFMkm3qe/6gjJim19913ny0LOxgLL7xw//79ae0WSPPNN9/jjz++1157gV1BAAegwEknnfTTn/7UOsQv35VDDjnECkc8IgceeCAdWlmQKS4ruC1ZrwLepDzxxBPR/9WvfvXd737XbbSyvZFx48YB4Z577ll11VVXXnllTeOpWtuKUa6rANsoFLdAu+666yRQcYCLF/7GN74R9COZ33QlBBICCYGEQEIgIZAQSAgUIkB/qvyit0n84IMPsnAvv/zyZ555JrfmyB42V4pm6Ha8nLfffnt+z0sttdTOO+/MME8TjcTMqz/4wQ/k4h6Nm2uuuUaYtR5Bmtzaa69NL6S40+d+/OMfe0RPZbtdbrnlaIfMz7yiKYuSLbPMMpx23nnnHcTnnntuawNWedo59V0uqnAUgQeeNvTdSy+91LYAH3d+NR6df/75HlHcacn777+/mK985Su0ZFZ5/j/UdDFWEWgqfdttt+VuzkWe9kxh5YvPtCyvulhmSIlzeUeNGrXrrrvOOeecqvDRRx9xH1Jr1V9ttdU8xfy7774LkIx/MfJaS8gucPbZZwPktddeg6FIMS7hWPNw33f7ve99T6EC1jwSq86PfvQjRnrhSy65RPwuu+yCfwZ7dCBTXJY0xfWSmN6f502MlHBAmWp+xBFH4ERGkXfffTcBePLJJ7/2ta/tsMMOFhiaQxWGDBli5SPBueeeG9hCzApBjMvqBQhAszGiLcQMHz78lFNOsTZQBEVfjCL8pishkBBICCQEEgIJgYRAQqAYgRZTcQ0X2zN9mtGa/soajQJrK2WduVdYPFu7AMcPGp73Vp9++mnqL81bJLWSEV2AJkq9u/HGG4Up7jyn6dw07NAOKbt8RTxiYqcKWxgIM8NT8kIpp/9RVa+44goxzz//vKe0TCZ/irVwpMEPVV6CuHbffXech3aI/sYbbywlChYJil5zzTUp8dzirUzYkoOIvYWtttpK2LuziFD3r7/+egG+IiJVRNgrsMK03iAYjvX3339/KOKs8izfzMxU2z/+8Y/SB2/U1j//+c8yincJuMVJaPPBpF8XMzxl/ZFHHpHGbgC3cgEKsZ2EKNqtDZBvfetbKC+99NLf/va3xTDJlyzLI8UV1Ou8886jbefTc0+SkrYN/CjFWgIzIq1JvFF62mmnWeRY7VDxKeiWYTYNLr74YgksJwIKbyZoEQJgfYW4Ijy1tIin9HiNTlp+97vfiQ9YBNKVEEgIJAQSAgmBhEBCICFQjMAs1KlqL5or3fpPf/oTBY4Hy/e//32aLq093gpFjQZGdaMdUtqodPGIrzmV2lP6n0saWmAorMGAGHo8X4uTTz55gw02oHOH1zu1T0qan1x+0aTqUXB5a1gPeBVSjMUA4rxcpPQoq5EKi7nsssvY5mm0OIwzTCRGhEIsMVO9ZM8995y60LAdjGPBcPvtt4tEh6sPI7GMI0aMoGrzz5GShrrsssuy3K+zzjpKt7SIlDJiUjJkgeOWjd9ygus/szT3G146Gf/q9eyzz8ooJhhWfYUqsQWg6dMxyQqOlCpETIAmLL2VBsUdttrC7T777EP5vvnmm1nfDz74YDElywpwlJivl6pxrVG1PG+qiYg6RikKldclYMk0++yz22/xFDjA1y5WKZYutk1wa58hsLXr4hYp9K3cPv/5z6PAUcrOg+ZDx5sSUSlleeQ3XQmBhEBCICGQEEgIJAQSAiUR+OxbRSUfF0RS2uisX/3qV2l4TzzxBGs6ZwkOLTRXptPQdGWhgdHGKGoCUooXiLCnbj2lN1PdaHXioxTpWbVpfi7+J/yeKZdBzS8NVdFyKZTmJ0zRdBgltw1EJBDvrdOMWtD0iwGRdFMuGWzn4a6tLEonjxdOOzRgOi5NlO7LIcfBlH/4wx9Yr5nn2bYVxEjP4I0Ufijl1E04yG4pQgFVOtU2ChKWPnCQ2KKFtwzvdoZn65zNN9+c4w2llqOIZJYcvH1kxJ5LgEeKWniqdLd//etfeZ4w1ds0CMRUP5Yunrrc+kXKrwUPZ32e4jCxWhCjoAyrrCxoeIRDebN6aQj4WADkeeOSJKX0QT+rV9RRc5966qly2SWQzEKLc781jyq7zWNr7cG679cizSE5tjWELVEwoFxNINdRRx1lAwGwISoopCshkBBICCQEEgIJgYRAQqAAgU9svQWx5W+pX/ybKZfcWryISdujxtFTaV0ueeNXgJJH46SVihFwiWSrPuecc/7+97/z+pAgVEkByWildHdmbMm8KBnqLCXPrbJYbamnoWcjyNJPF+R0QQv/+te/jibVXJhWLX1cUa5fl9ciJT7++OO5dlBD11hjDbWgLPLx4KpBpaapO52QZwjdl6ZOXZZLAm+LOuiQToxJj9jRPeIFZP0gEk0mZymV6zcrl1rPCYdGK3L99dcXT83lC86Obp0gkre6sHhk8SM7izVjOUcXbip/+9vf7ABYruDHooIK7jAfdXTFKkL6AA2AApR+F+8jTkqB23rrrVeyrCixoF4wp0DbWCjgDcJRSla1aC+LEDHYi10RIBCA2WabjTouAWoZtvZPrHYWXXRRKDG9g4UPj+Mj1cg2yHbbbeflV9UnDMGY33QlBBICCYGEQEIgIZAQSAiUQID6VdVFjZOetZUehhxtL14r5NhNh+PY7Sm9ljO3ANWTK7kA8zyH5ngP1QusXvT0+qYXE9mqw8edBrz66qsz+nrVElnKsSUB7ZB6Sptk1xdJD0aKDk1fpLyynVNMxXAi91qkxQMjvUcRaZHgEX5okw5dEXZxgKEvyijMcYWOi6w3OPl1iOGmzwAshjsNG7kYaisnfifY4MSSgHOISBeHexq8lIz0FhtiwELtPvroo4VZsiGgXpRgLuCSyesR5xlPWaYz/lVNRldQUFkIeGeAdisXJd4aw1N1YU2njsMEUAzq0uPKMiAy4lPAugW3nE+Eo/oYLlmWpyXrleeN1Rwdh9JkpWR8iveSLsy1i7DLLoHbzFVdTTNs48UGaWxlaGL14uNuBwA1IhEvSNi0IRK2UES6Wkmmn4RAQiAhkBBICCQEEgIJgf9BoMUWTpeq6pKFEknBov8xt8sbJGnM1GIGV0Zx8Yyv1FDKKJO5xJ7SttlWpado0mUFpIzILKVI6mwYlT2lAYvJItFBH00loi8+mMkIsvvSIFtztPwUlCuGPuo3rPgCWVnCceEkKuVWdusT51p6dzZqJzJKFMindIsyltQrCg0ExEMJXFHxyJvnX4LiCwVpAqLsacZq1NEtagDPEghkTGaRJcsqWa/IUpC+ZCmRMmtlt3JJCdUw9keCjOG4jd88h4EY0ORSKY0ebZpPn8IJgYRAQiAhkBBICCQEEgKBQHU+7pGHmkVRo4mGgksLpEyLzJTsLJBpwBJkkdTNUEllzCKzlJ6G1q6s7KlwRKIjVyjBWbkCQVDevNYuV75ctxJkKrtwRjZIxW++UhLwYmdTj5RZiVn1EXEpRYKMclaoR+JDGZUXRC6BPP8S5K9Wei0EXVlYAmEIBMGoY4ZSPnuBHl+mrOJ6oVOcvmQpUWK+ddQofxt8Rl401SWIC+AwnoIiQ8zTgoaLItJvQiAhkBBICCQEEgIJgYRAhkCLRlXDFapnaGChliESt/lAnnL2lMYW8aGb5tMIe5qlzD/KIqM4t1m5GZ2SebOMBcQlztIHqYyylBGWgDOMo9DFZAqocFZ9CSKlyPwVhbYU0Fqd4FZYmqyUkhmlyRJkYbmCjt8I5MvKh/OVLVMWIiXrlRVdkrd8QcIFZeVvW9n8pB0zUhnxeFpAIZ+9oKB0mxBICCQEEgIJgYRAQiAhAIHSWnKCJiGQEEgIJAQSAgmBhEBCICGQEOhSCNRoce9SdWgoMzzU2dobWkSnEO+p9eoUMFOhCYGEQEIgIZAQSAgkBJqAQLK4NwHkVERCICGQEEgIJAQSAgmBhEBCoKMI1PJyakfLbG5+ztNM5n65VodvervlS++SWJZ2E9c9QTAcZCthGKsSZ67kwuEvjvkskDFZHJM9ygeCB6/Wqn+FPAQb1YImV57zPA9lHuWTxTE4KotOu+2Fpkv2avmURcaSrJaMB2C8wdwuS/m6pHBCICGQEEgIJAQSAgmBMgj0cIs7/SmvOZXUsQrQyacpyF6QsuC2qsQFebPbAiJ5ZrI0jQ7UhYcCIg3iuaCUgttKCq0hSyVkU5qEQEIgIZAQSAgkBBICdUegJyvuoZN98MEHPsDkc0s+BRUfAGoXxIceeujBBx/cYYcdRo0alanO5TW8kk+zyCxQvuhI5nz0f/3rX9hefvnlffyoTJZI/+KLL0rjA0axRBHps01OV/Qt2HHjxjn2Mf9IjBPTfX2pLZYiftrUqVdf+S/fsV1iyaXXXX+DdnnwPaYbbrgBVttvv71PvVYCWhT07LPPzjvvvM6IzNZXEe/3mWee8SWsuC1mIIu/5db/PP3sc3PPOcfWW23ep0/LGZoZqXyuiG+Lz3zKfDijJhD8xFO3AgrK4rOUUXdHiPow2bbbbuv7X9mjPOUUTggkBBICCYGEQEIgIVAtAj325VT6E72KsuVTo75g6sjws88+25dEARRaVzFSsoi8+uqr4wuvvg5LA+YdQQn78MMPQx20AOACIRmaQSq+Wuqpr4GKQcR7n4rw+SGR0vuMaEFeyYqv4AoRH1u9+eabX3311d/+9rd/+MMfpAzGirMEJz7yevnllytizJgxwScGKMQnn3yyNQD2PPLZI98lFaDl+0AsUiVBiMiPxn64z4EHH37yFb++5oUv/uB3v/jlL1t5aFFVi6/gjdbug7jK9YVXSw6gvfHGGxIrUaSA30gJzIhRlvCFF1743nvvSRbpI4svW2m4iy++2G1JPsXHdeyxP/3Ztza/6ex9//CTrb922IEffDhWfEm4yvMZuQJPiLkVfvvttzEmHPxcdNFFwph/6623xLsK+IyM6q7FfUpWW2hBv3KlKyGQEEgIJAQSAgmBhEDHEeixPu70KrraWWedxXDO8AkpJ5cffPDBa6211tJLL00dlKAYPmrZLbfc8p3vfIetnQb/wgsv0H1POeUUVmrfT3366afPPffco48+mrpJM954443R/MUvfvH1r3/9tttuoz0z6rORU/e32WYbevM666zDdq4UCe67777zzjvv2GOPXXjhhUuWjluO17/73e8k2HPPPXFC6T/ppJPsEuCZHtmWrzlztWUJdfzvf/87VfJb3/qWxJdddhmWVlxxRWUxgaPD2Lz55ptjqczXSYOHP5zyxwc+GLb6LvvMNKPle6inXXzS2mtcv9Emm5XkIWCcddZZDz/88GWXXfaII46wSLCWuOKKK9x++ctfvvLKK3fbbbfTTz99u+22o4tjwyeufvazn+H2kUcesT756le/eu2110pvh+HAAw9UBU/pvtk3uYqbCZ/04xtuuPmWy47ffeMh/fqNZGq/+Lq//v3cNQ899CveaSjO0hafWF1yySW/9rWvYezll18GtdXdTjvtROf2YVe32uInP/lJfNhVo0DylVde2XnnnSEZ8cEnfjQxCVluueXs2Hzxi1/0/SnNHeu3ki1ezGSKSQgkBBICCYGEQEIgIVAGgR5rcaeoMXZSIrfeemsapwDViqr98MMPg4MiVQCKGAk4llC8qKFUtK222mq99daTjMpOHec8Qwnbf//9eZ6gRi+/66677r333rnnnpuWScU/44wzFIoOInT3ZZZZ5vbbb99xxx3XWGON6667zgJA3vnnn7+kDhelK5SVl0bICM30jo2lllrqscceK8lwxn9osSzWVhFf+MIX7r//fv4wG264ISV48cUXR8dnZXfdddfvf//7uJVL+ixvycDDj/933uXWnTL+g3Fj3qaVDl9ohSeefLI1ZYmlDs49UrvDDjtsr732gqGY559/nqY+dOhQKmxgAjrlqhfFl/cIHZeCTjkGpsR33333j3/8Y3oz7Rn/mD/uuOMkKMmeyFDNb7/t2qXnn/HxTP3GjJ0yfuKMFZcY+t/H78DOLH36FGdsi8/TTjsNn5Zh1jNKlEwrAJA3kQUbwz/QNtpoIyq4qj366KPAtIejQW+88cZNNtnEGiP4JGOWSXR6YrD33nvT2n/5y1/a5VBZzMSyoZirFJMQSAgkBBICCYGEQEKgcgR6rOIOAnZoyiLlia06vKjpZ8zPbaFDaaMrcyaRixpH+X7uueeYXU844QSeDyhQ5maffXaqG4V48ODB9MtvfvObYqRfbLHFkF1llVX4S4wYMeKee+6RgKpH+ePrPHr0aCb8OeaYA9nQIAt4oNghEkedcCChSmLerbCMBYkLbiVTKA1YKXgLp2rapNUFmjRvAQb4Y445RkYF4aqAQnYbvA0fNnT8B2/1HzS0X/8Bffv1H//+WyNHDG9NU7jaCYJ+6amHHHLI73//e8seOxVUWJH2CixpolJuMbnSSispYoEFFrA+WWSRRUTao2DMZnf/4Q9/GFZ2yr0tET76QUSaElfrbsm88y7y7oczDew/c7++fYYM7vf2++OHj5zXE8cIFWcJ1bkkn3iwuSELrCTAp7azXWA1AlWOMdZg+ME8kbBaO+qoo0iRKkiT8ale8moCaCtLSlZ87vt0fZRLNnoxkykmIZAQSAgkBBICCYGEQBkE2tThyuTpFo/orFTt9ddfn+2WTZeaxcuFHsz5gRZVrLyG6kxjo1tT06mSf/3rXynxrOaHHnroLrvsggKzMa1O9ema7LJrrrmmBLS3eeaZh53YqoDfBdWNyfyOO+5gXPduJeccChyrvIyyl4EOAy6OGRdccAErOy2Waw0tcLPNNsMw9betvJYWkrkU4aJu+lV9NnhE1BRvFFC2YQy4yliyA5aDD/zi2If+/fwTD439aPz9N1y66MD3t9x6Ozxgry0eMrJ2G2irDzzwAFv1P/7xDysc3iMu+m5YshGhCvNOsYMhTSBmwfOrX/2Kf5GFkyUQtxlPOforrqTKG3zuvMuu4wesevsDb3w07sMHH3/12TEL7LjL3i1ZSujtnzBezKdW4+OkBbU7tm0RhKrN6I5Vrw1oRAnE8+O3LNEcFnLqZV1BTjI+ZbddQGzwr7J8tAiM1Zc12Cdlp38SAgmBhEBCICGQEEgIdAyBHuvjTrej83FWZkalaUGJ9sx7gS5VUheUIJRjjhDcYFhV99tvP3o/A/ZvfvMb7i7UdO4Qw4e32J7pnbQ6tnAuKIsuuqiyeNJ7L5MbNw91Ljq0NxZlxnj6KGWRm4r0w4YNk1fAb/EVDNMLBajsyqIBcyahy7alNAcp7jS0Rub8oG/twQxsc4C6TJXEBm5/9KMf8Zmx/JByoYUWUnpJNoKHVVdb/a+/PerU088c//y05ecffeQRv1NTPHhazHbEWKVwEaHaWrRsscUWoAYaRRw4lPI//elP/I6wBBzp8SM9h3tuKquuuqo0dHrvFfBHwjnlmAJt9cKPXOKShWIeP6NGjTj1zxf95oRfPvnWCwNHjTzhJ99eZeUVWvjsUwWf0Wo2AWQkKtYM4Z4OJdsXtHb8WPl4q0F1RFoNeovgoIMOWmGFFWjt4oNPrHL14c2vavZY+CxZMX7uc58jCSiXRDugS78JgYRAQiAhkBBICCQEKkSgRQGqMGl3TFasMxXH1FwvjtpcYtjjKdnFFvHaCirOVRxTM8MVZiwusTimQlINTVbMVXFMQxlIxBMCCYGEQEIgIZAQSAg0E4Eea3EPEFk6OY0IM9xSr/1WYvuUkgoosUugOKNIZHnR8GwJ4lkyWcRkqryAW2q9BALtlh4MSyxLcbkoFF9RwWLK4kXGxaT9abDF3i9cTCeL8VRePMwySwsPDkcvn15G6V1BOSobzEMjHqEgXjhiMmAjvgC9yCKNK+OqOCCvjDNmTO+DT5Tdl01fnk9Po7GQcbn1mzEcAfwEb+oST7P4IB4ZcSWQIeBRuhICCYGEQEIgIZAQSAh0HIEebnHPAApdKrvt+oGuwHBX4KGSluoufFZSl5QmIZAQSAgkBBICCYGEQFsI9BbFva36dyQ+TKphZO0InZQ3IZAQSAgkBBICCYGEQEIgIdAuAklxbxeilCAhkBBICCQEEgIJgYRAQiAh0PkIlPMh7nzuEgcJgYRAQiAhkBBICCQEEgIJgYRAKwJJcU+CkBBICCQEEgIJgYRAQiAhkBDoBggkxb0bNFJiMSGQEEgIJAQSAgmBhEBCICGQFPckAwmBhEBCICGQEEgIJAQSAgmBboBAUty7QSMlFhMCCYGEQEIgIZAQSAgkBBICSXFPMpAQSAgkBBICCYGEQEIgIZAQ6AYIJMW9GzRSYjEhkBBICCQEEgIJgYRAQiAhkBT3JAMJgYRAQiAhkBBICCQEEgIJgW6AQFLcu0EjJRYTAgmBhEBCICGQEEgIJAQSAklxTzKQEEgIJAQSAgmBhEBCICGQEOgGCPRwxf3jjz+ePn165e0g/YwZMypPXyZxFF0mQeWlpJQJgYRA+a7kqZ6u0yWgEgIJgc5CQDcs2QdLRmIyddvOaqlUbrdGYOa2elS3rlWnMw/VmWeeOdjIhzudscRAQqDnIWD6n2WWT2wQqbv1vPZNNerWCKQu2a2bLzHfBRHosRZ3g4VrzJgxd95558SJE0HPIGeCjzYQyMKSZY/efPPN5557Lv+0IGM+8ZQpUx577LFp06ZJLz5rXWFa+9ixY//zn/88//zzmQafJUiBhEBCoCQCWU/0NPpa9Cx97ZFHHpk8eXJJszqt/cUXX7zjjjs+/PDD1N1KApsiEwJ1RCCmyKwzRlcV+fjjj7/11lsKikcxM+qS0XOLGXjooYceeOCB4vgUkxBICJRBoMcq7upsvDjllFNOOOEE07mRpU+fPmGWExZwhU4gWTxyS8v/xz/+kX+KTvZUgnziDz744I9//OP48eOlFx8oB8033njjRz/60THHHPPNb37zoosu8sgQFgnSb0IgIdAWAsV9Tc/Sp8aNG/f73/9+0qRJEmR9DZHobrfffvt3vvOdn/3sZ1/96lefeuqpLL6tUlJ8QiAh0BEEYorMOmM2LV555ZV0d5TjUcyMzzzzzPnnny+moESz5w9+8IMf//jH5kor84Kn6TYhkBBoC4GeqbiHhs12/uijj+62225zzDGHkYXFzvoeEMJmd+NLaAA072uuuea1115z269fv2HDhv33v/9lwIun0jMJIOXWFXZ0hnxhjyQePHjw/fff/+qrr7pVLgXdI1kGDRp09dVXH3HEER999FEU6jddCYGEQBkEivua5XH0tdlmm+3dd9998MEHp06dikKo7PFLXfj85z9/1VVXrb/++vpm9rRMQelRQiAhUAMC0eOeffZZxikTX8xuwrRzs+qGG2644oor6qFu2cvuu+8+4bvvvvu2224zwypO9qDw3nvv3XPPPWedddbf/va34cOHm4XjaQ0spSwJgd6GQN8eWWHas/X9zTffbKZn8N5jjz38nn322TSAr33tawMGDPjVr35l+DjggAN22mmnv/zlL0suueRll1228847zzrrrNdddx0XFw4wP//5zxdeeGF2Pmp93759WQUWWWSRn/zkJ8asRRdd9LjjjlMERf/GG2+U94c//GEeSSPRyy+/bFzboPXyKJSPfJoUTggkBPII/OEPf7DWLehrOh1TumXw66+/bveM75kuvP3220fGUAJ027vuumuttdY66KCDIp6pL085hRMCCYG6IKDHmcv++te/mgftg6288so2lhnFjj/++FVXXZU6vv/++6+++urmx7nnnptq/vWvf/3JJ598+umn6e577rmn7NE3zcKmabMty5rtsuAtzZJ1aaNEpMcj0DOnt9iV23vvvZdaaikjSIwUlPWNN96YI+ytt956+OGH//a3v2UMeOKJJ/ipDx06lLXg4YcfpjSMGjXq//7v/5ZZZpl///vfhiEmwDPPPJOuYLOPVjF69OgrrrhizjnnvPjii0eOHMkSj85ee+0133zzha09ylpvvfWUpcTdd9+dSkGMPO3xwpQqmBCoAYFQvmnkrOnFfW2uuea65JJL7Gux7fGE+da3vmVdrZSY46O77bfffogccsgh+rW1uqdBswZmUpaEQEKgXQRMlCa4Cy64wAxIKbfzzMjF1MWkZaajlE+YMOELX/iC/miG3XzzzW2F7brrrshGh9U9zblf/vKXr7/++l122eW0006TK/XZdmFPCRICgUDPVNyjbtR3F6O4EYFNjqptyhc2diy33HKs7AwA3kYNnWCrrbayx2d3b4UVVhgyZIinFIV33nlngQUW4Gmzyiqr2Mt76aWXWPWMSssvvzzfGHRQszYIr74oNPQJSwLGP2YJOr2tQHnFp4Ep9bqEQFsIeKdtwQUXLNnXbLLrO/PMM49uS0XI96PoVnIx+HGZHTFiBGWirSJSfEIgIVAXBMx95kQTpV7Jmc2rqExdptqwT3FYZ9tadtllTbt6qFl44MCBdP2saJH2tGnztrv1XIZ5i3aRybyVQZQCCYEyCPRkxd0Eb3RQecPB3//+d8byJZZYwkK/f//+55xzjgn+pz/96UILLWQM2nLLLW3E847l4sKsziTPzYbxgNbOV48HLRV83nnnXW211bjc2PLjPCPssBqRRx55JJs9e6Hi6Osuo9jll1/+jW98Q3y47hmSyrRBepQQSAgstthiTHcl+5oteN1K/9Kz4hAngbjcujiqnXzyyRbhDq+gJQAzr9wnbBMCCYH6IqA/mlLNkq+88oo51Fvj0eMyw7mAHqpv+jX96dpeG8tiBFi+ONVwlfHamGTRbevLZKKWEOipCPRkxV2bcY31a1DYbLPNjBEsAbR27iu8Yi699FJO7dQFDnlebGctELbBx05gv57pjh8tY/yXvvSl008/nfp+8MEHx5s3PG6l2XbbbSnlcvHkQ4HBQCluXVEcnR7Za6+91vCEDjaS+t5Te1GqV0cQ0C/M+rPPPrt3TtrqazpmdCJ2O9Y7XSwut3qcTXk78t/73vcswvXujjCT8iYEEgLtIsDWbufZavlzn/sc4zo9Xq+US2RY1t3q1/qmrm1Tmmpuu1uf9TR6LnVf3j/96U/HHnvspptuartbSv233ee85NIAAQAASURBVKJTgoRAQqCH+2/Q1I0UMRxY5RsyQnfPGt5gYXyx2UdTF2l8iXEnSyDAeJAfULI08hqwjE0ocGTnV2NVILExi/9fW9TylFM4IZAQyCNQvq/pX3qxLmzXS0CvFOZcy4UGkeiMeWopnBBICNQXgeihtO0ttthijTXWiFW3SJepUB/UK7N5VqTpMqZFG2IOmaHZmzdFrrnmmtbqejH2pK8vk4laQqBnI9DDF7iGkqz9DCjGEYOIgSMijTIxsoTWLjKvtUcyvzL6zS5pDDeGHmMWagKIhL0BBclCtxAIagIRHymFJZBFIH+JKY7MJxAuThPFRRElyRZQSLcJgS6LgP6oT2Ev+lf0IL9xRb+TwNxfUAX9Qpow78mbfyo+6xeSFTyNsspERhZECmiKz8cUh2UpSNMuJ8VEUkxCoGsioDNyS9MZCbmL5h1TrV/TpQ4l4Fc4tHaBYu3chBjxWf+SxaXKYjzN4gMEBXlaHBkpxRc/lVGugizFkBanCWoRX8xJMYUUkxBoJgI93OJeDKUOGcpB8aOSMdWmL0mk3chKSqkkTbsFpQQJgZ6KQOogPbVlU726PgJds/dVwlUlabo+/onDXoVAT7a420b/5S9/6XBoPdNa3CGPF154Ia3drTb2roxD2eNy4LqYiM83vwW39J46rF18ti7nLu/FVnt/77///lFHHYWsR+yFSmGH+POf/+yLrQJB0yMBH3X69re/HXROPfVUWbKCCkopZiOKznMiTSTjrI8T37/wZq26BNl4lNFPgYRA10cgeqvPJmBVN4kPHgfbHuky3//+90n4eeedJ1JHy67oX9GJ+Lx56ZyFTJroBS+88IIOEv3OERZOrOMunz2V0gstjqPJeqtHbXHS0uVah458KdIXXMVpIsaJVSpl6JC+mJMCIuk2IdA1EYju5tMlTmUw7zgMituMacj0FI9IuHPZdTqnIee/hqYXZH02eigiZmHVjIz6oG5umhbjm03f/e53ne4QT6MHcZBzZrxzIESKiVzOivVyS56TeBq/uMpKCSLi85fIgjSRTG/Fv2MqzP6qE5yUpJCnlsIJgeYg0JMVd6+66/9+9UzTMzd0R7N7W9Rt9MDo+XfeeWd8/q2gW7q1kWfocVK7T0hoD+OOvPfeey9qb7/9to5trJFA35bSI7uBDqZ1VLwDIv/xj3/IgohLwNv3vlJhh9HpkEoMToJmQSnBlUfZhUJBmuDEGbonnniiw+Z/8YtfOOImOJErSsyyp0BCoOsjoJ96fU0H8XljhzhZ6JrFM7YJPKnWDb0mLjL6mu7m0jWyZDL+61//EhlpdAq6stW1d17jKw26Xiju0cscD0UbMCtHb43IMpxEz8qXkhWdBYrT4BZlwwU1RV4DCA4zTrKMKZAQ6PoIhHjzVjcDWuL+5je/8alBS1+qs57oaVw6nck3emJUKuuzkunmjoCUK2ZevVsandRMavb0qUQJzKGh1iMorxWC5a4jaCRTrvTRWx0L4e2yAk6kjykyXwo6BfAG5YI0WW+15tdb1UIFs9VCAYV0mxDoFAQ+m/M6pfiGFqozO3A9vsrmOCqmcQe3GxcUqs97q935MA5t9HmIddddN/qw+LxDm4nfi/N8ap1HK5cu7Zf24DgaNnWnynCOZwiMp1EXLn0OnfS9VDp9fqRgj/dVdvHUd9aIjBM0C0oJOuU5Cco+DuVlfEZKR9/4Tg0TheMsI3v6TQh0LwT0Vp9QOPTQQ6nsjm/63e9+JxCnqepTPr1k92zttdfeZ5991Euv0QXMzTF5+6UN+ESas2Xmn3/+0AMkM/E7BBYpZ04L77vvvk6WDON6gFOyt7bFiUJLllIJJ06bZcMzmKgFDr/4xS96sS/PSfdqrMRtL0fAqco//vGPnS2js9CkzYPxMRM90Uurv/71r30XxQcQzYxi8r01bi2Vncjsuw2h2fs17VL9WaDsSyOln+rpYZgPqDnNzzbbbMjG660ikfWLh5Kc6KoFpQSdrLeW5CQm1uitDAd0BidW+fJ6NqQEkfSbEOhcBHqy4q5jmxqpxQYXKOvhvnWqPwt7FLO+4cMYYVDQY0V6aq0fI4JffdvpchtttFEoEBEvxkfg2AXjSCxfaozeHk8d/e4sarZDp0CKcWUNzNQXg4WD7TJOlFhQSqSvhBP1siAxPjIJSM/0jlRWXAokBLoRAnoKedYrKbh6h+mZNuCb6qoQXZVpXEdzhoyY1o7VssFF7OPWI3q/bzEiknW6xRdfnHeNQcAnnOKbjjEURBa/Bb01o9YWJyVLUVy7nKiUvmmBfdZZZ/k2s2U8uz4G0pUQ6I4I6JKM35xFqeY6hS+gmWejIuSctOut5k0x0RmzPhK3PqPmE8hOlcn6ox5E/xZjJ0pXRTOM8Rk4CjILs7VZ9OZfTy/DSXEpwU/01rY4kSZ6q9Np2f4dO+E2EmfMpEBCoHMR6MmKO2T1t5iMhY0FEWNkcem9BgKrfIp7xPvlD2fFbx9QWBrHwPuEqiEpiBgjENGTqcjs3DvttJP4ICu9sLFGV/fNVGn46l111VUYQMfTSJBPH4/QLCglEpfnRKHIBj8Ud5+F4neLTsZMEEm/CYFuhIAeoVdmMhyB6D46jj1xqrnIsMMxrtti8hUYFZRRvG836neZlU4ANetwrm4UdEdGIiUmAJHFqqC4t2ZPS3KixxWUIn27nMiFf55sDq62rc8/JywFUVb6TQh0RwSItE6U51wfDFFnMrf3y0CezX1ZH4ksbO12vFmyEEFBMpfO64tOujnTmGR6bhD3CGVvjtk/9z0WTu08WGj8kVeakpzo/gWlICJxu5xIhmDWW2+//XYLADwEM+k3IdAVEOjhijuIDSU2xAXo37Rbti7dMgYFe/Gs5tlZkNLotK5oGGNH3JrCY7hBR4Cp7KSTTtptt93WX399KbPhwyNecUqxubbJJpucccYZDIdBKn5xIiBZnpPQDxQkkJGSLIqOjLJknEQaE78Aw4NPQW233Xb0Ej6FKET69JsQ6L4IMK0xcZmY/eqe5Jxgs5pbY1tF6wuuqF2+j4jJ+kg8ja0za1qkmPcKAEGkfG+VvpgTNJXiUUFfK8+JxOZ+o8EOO+zgWzP26FDIalHAWLpNCHR9BEgvXZZqbvUrbDlK7RaIqdb7JPxFo6fErxrl+4hwrKujF+hW+ohXthyucNxxx+VnZBk9VRYPVXPuD37wAyYthjNzXyjTbXESa+N8KRmqZTiRC0GOQLbFdtxxR71V1aQPPjMKKZAQ6FwEPlnUdi4TDS1d10XfDjvPclr7gQceaHSw3Odj+tJLL5mbPTUEhELMiO4KfqKv+mUYiLHDATWHHHLITTfd5MV5Md525eAusY4dWSjQ1gZs9gpVIoeZ1VZbLeZ4dCjuChJ/9NFHSxCc2BbkgOspbT6IxG9JTqQJ7d9+Ij88ewVIeW/GWmK++ebjNhM85+mkcEKguyCgdxDvpZde2hul+o6uQXHnzMbQrmfZH/ONRnWJrsryLVm+atHFaBISSCyjeZcDrg83HnHEETamvBAS3Sdy8TUv6K3hNedpW5wgpUdbCYQPT9BplxPuMd5vobsfdthhHAz8YiMbNPJVSOGEQHdBwFo6fF2+8pWvmM70He9csWezW7366qsxqalLTEkFfUSkSydCRBobXzbEvCAuozdSdPz99tsv66oCZltfIteL/eq2pjyHPZjyAquSnDz11FO6vARKCR1AiW7b5YRd34BjHeK9GuODQpEqWKhHuek3IdBZCPRki7up0bo8VHNashnXqy0bb7xxtss299xzr7zyyqCPLi1gwtbJszk14s3WLk8pBJ76RQcRyfRn5oHo1cYXYYdkcWH3Ft1pp53m16OMmt1DeXnOrb766hkniigoJW7b4oRagxNkMbDYYot5mU+hlgpMHTSD4ESCdCUEuhcCuomOQ4BXWmkl76WZvMm2vqAjqIiOs8466+R9W6XXGeOpBNFr2MnWWmst4eh09rvtrYuMmRtx83E8krG4t9IPkGqLE/EFpQTC4stwIo2RQffk2GPAocHjECcqG5wEkfSbEOhGCBBgE6tfU88888zDnhW9TD9VC12Yep2vTkEf8UhX0hHY7IXRsdL2Rgp1PwxYnprOgkJ0OkWwtbGFM595yzw7hqEkJ3pc5IpS8BYl+i3PiQRGBjSz3qouKhX1Cn7Sb0Kg8xEgxz31stVut8t5VbpxVkfdMgt3POBILPYznRypfCl5yiZ1t4z0Xrfn3po9qi8n3hNql5Os6BRICHQ1BEr21voyaS3NWUWfRbZM7+s6nNS3+olaQqDjCMR09qMf/cjpCw5FyAiW6VBZmsoDDn/jAvrPf/5TlrYmVvvnnnYFTiqvV0qZEKgLAj3ZVYZ1jW3b6jmWR/q/9belsyFGwCXgUbuL6SwZCqi5dUE/SHFd5WiODoJ+xXvaSr7lNgvY17NJJ8ZlxEEnz4lIufyWZyZLE20fFHDFUqigAk5aSkpXQqCbIJDvrVn/ItVZbxIo3ztUNHpfdHn9IjpIxItEzbYb95sMkuLe6lG7nORLyUgVBPJpYtzIysJVMScF2dNtQqBrIkB0McYObctXgFRT5WM6E3ZFp5MsUpapRfRQyWJek1di4ei/Xmjh0SomoyO9W/SjFAG35TmRICtFuK0rS5ONNoqIeslSzElbdFJ8QqA5CHyyp9ycwlIpCYGEQEIgIZAQSAgkBBICCYGEQG0I9GQfd4hYSbtqg6aSXNbl6IfBoHz6WMFXkrI8nbaeVs5JWxRSfEKgcxFo7awN7K2V0688ZW2INZp+bVylXAmBChEwkYXPTIXpq00W06XfdjN2HU7aZTUlSAjUC4Fkca8XkolOQiAhkBBICCQEEgIJgYRAQqCBCPRwi3tJ5Kzjm/zZwrAflGSmcZE86V2No19MmfHDVRzf0BhNWYlhpo48NNTUVJLPXiKxJeve/PbNs9EpPTdjoPntnhUt0Ll1x0DzR7B89TtlNMsYMMiEE3kW0/UDEGs0z82RySaMOU2QruaMHk2YDQmVLcqGyn8TalHf0awnv5zaVksT6Obrlwpti58GxfeGEkGnKdU0e4GpQWDmyXYKsL1BYvMgZ+Hmt29WdASa39wZA4pufrtnpQt0Yt1T6Z0Lfl4MKg83QVybAEsTxpwm1EIRPaY54kXkyuWw2pTNaY5quSqTvjtZ3ElhsSBCvAmgl0EwPUoIJAQSAgmBhEBCICGQEEgINAGBbmNxp53Hqksgb17Nh5uAVyoiIZAQSAgkBBICTUOgxTT16WW+i9MSm1Z6KighkBCoAQFWZr3VVUPedrN0G8Vd/R988EFHLMenQ1XMUCbSF9d88din0eK23QqnBAmBhEBCICGQEOhSCHyqmX/iUZnfW26Z/Bsz/XcpBBIzCYEeg4D+21D3nm6guAcEjz322JNPPgkLQ9hSSy0Vq5lx48adcMIJvmq+/vrri2mcKSKKS6Nn+X7lDZLGNUH5ojvrKcFQdEO7aKOrFhpDt65CoyFK9BMCdUcg09TD5GTkzM8vMZAaXlimXnvttWeeeeall156+umn55prriOPPFJvjVx15yoRTAgkBDqIgFddfRPzvvvu00l9A1Qvrvv02g0U9xik3n///Z122umtt9565ZVXKO6B7Ouvv77gggtWi7LxMT9EVpK9g7jXUGIlXJVPU20dy1Or5Gn//v0rSVbfNM3HNl9iBwWjQijyJVaYpfJkJYmXjKycZkqZEEgIQMDMHb8CLsNF1rOyQABlsje7vfnmm2+88carr7761FNPvfDCC7R2V79+/UaMGGFXefTo0YssskgCNiGQEOiyCDBf0tovv/zyb3/728cffzzFXcevO7fdQHFXZ1jEqDdgwIDQDo2AIpdYYom33347f+ihk4PCOl4GKaR41zBpVAKogiQ+//zzt9hii3nnnVdZBtwyxEs+UhBuXSWfNiISk3Eyl6JdjSgiTxOYH3300XnnnbfLLrvMNttsJqEaUMoTrDCsFK3j11Vhlo4nUzsXVAcNGnT99dc7O2y77babOHFi45R4ZVUusZVXUE/he8aMd+edd+655574z0RFoFhijUdhCKy8iJQyIdCrEIge5Dcu/aV4dNLvJkyY8PLLL//3v/99/vnnqemU9Q8++ODDDz+UftiwYXPOOefCCy+88sorL7DAAkzsbmntBTA2c8QrKDrdJgQSAsUIZF3+j3/844knnnjqqaduvvnmIhsxaXYPxZ1KERdlAhABmZFLuECThpGUxZjmY4yblSSLLKgp6MUXX1SQXBhol36+rAhnLVr8qHExwWcN3FbLUoimX5u5ga3fJpQbfEZTNq04hUYd1Vf4vffeYxITqFyigu2qfquS2Moph0ph4UGHAKAqRKVQEHCJyVNLukIejRTu5QhEH4lf3ccFkOgj+Z5ir5gdnXbO48Ui+bnnnhszZgwnz7CjM6LPN998yy677OKLL77YYotR0JkDioFVSth9soKK09QQg2zwLGCQEY5BIPhv5jBeA/MpS0Kg6yAQnUXH+d73vnfllVdecsklyy+/vD5bMIfWi+Fu8OVUYwo4br31VrZ2dk02wrXXXptxYvDgwca+a6+9FhbM4ZVjhCBlpeT4WC9Yi+mw0TJYFsc3LsZKA3EQNa6IYsrRWMXxjYsJkcjPlI0rKyg3vyl7icSWbDi2SV0+tKKSCRoaCXnN3eROlNXIZGCkMtBlMc0MdG7d1TT2DDvFAU/poSjn512AZFdJBZqomJio5l7HYuuxHn733Xep6YbioUOH2oqknbvs3M4zzzxM6SNHjizZoEqxw4YBkm9ki8Etfkumb0QkHqotkbhqMjw3gp+giasm9McmjDnF0lV30JozepBtik21olJVZY2BinBVlauqxB2sRWjtJHP//fdnvrzooovskrnN81zf0ayBWFQFXLuJKevgMPxtsMEGEt91111rrbXW8OHD55577mrHtRh82y2xjgmaXyLmFVrHKlRISqEN7cPFbAS2zSy0s0osrnvjYqKOjaOfKCcEuiwCIfxUKwFM0tGzKSY/ztDRvWTFlE5B55L+7LPPcneh8/F1oZHTyx2AxiV9mWWWYVMfMmRIPm/UHX2liI9H+YAFg9v8sqG+cCkafbuFtCIrCr46DzzwgAXqJptswvt09tlnF1aj+eefn3tqfYtO1BICPQmBUND1ms9//vPeReE9y9ZAlc9r7XWvbzdQ3GNQM47svffeWf233HLLCNuPiEDjbHJWY2ecccYOO+zATBLjXcZGCmQI2Pz9y1/+ss8++5i0egNKsci+4YYbTH6f+9zn4jZDo1sEgmcGwptvvvmAAw6IjtYtOE9MJgTqi4AhK7uoy2aTAku/bk5Hf/zxx+OAF5ouUzq7OI18jjnmWHLJJXfbbTdqrjmCLankJknQ1+l0tLhUoaGze1sQ4cSjOJNt44033mijjWxcW2mEjm5M22uvvRzjZjXCyV5i3LZFKsUnBHozAqG1P/roo1/4whccb/ib3/wGGlbjjVtyB9rdQHHPxMKQJxwKeqYnxRjU0JFFEcZoLZRxkgJ5BGJk98ubM3YA8097dtjk5+rWdbSFp+EaV4UQj8bRT5QTAlUhQCDjksvEERNKpkkHqXfeeceWtxPMHO1CWeeePnbsWJMxH3Rq+kILLbThhhsypQvYBC6efcJaHzQzyhFonIGpKhAkjjPZgnnGKS4ua665poUEqyE/HxdbFXtZ5WSzmlaepdqUTSgCS00oJWCvtvpVpW9CLZqGVaPhqg0rWqj+cuONNx588MGHH374oYceGg1UUmuvbxW6gY97VcJaSWJwN9lz1DxB769qEKykIuXT1NenqnxZ2VM1ra+AZpTbCjTBH7Gg6A76wxVQq+S2e0msVW447xIG6g5/NvwLU1nIBiNlVZvvzW/ffIt0Ss/NGGh+u2dFC3Ru3TFQrxFMRaI6ESieVr0nw5r+yCOPOOaFpu5YRktZiTm9UM29OcrjhTWdbzqvkjxEEZbSpbFi+o/f4mRVxRhkEKyqp1RFP4yCt912m4K4x1x11VXY5vPD1v6vf/3r4Ycf3nbbbePrKLHSCJ/78kUAAbWCnYryWap9qgicN3SbAg7kAfIC1bJXYXqUw8JFFNWowlzVJkNZq3mXr3FFYIlioxaNw0oRxgFFaPTGVaSqWqgsTnRPi/bTTz/9Zz/72a9+9as99tgjjqnQX4r5lEXXUBdKYPFTXaZake5OFvdqBTelTwgkBJqGgPHI8Hf11VezU9J11ltvvX/84x88/xyJxUh5yy237Ljjjrfffrs1sy3FpnGVCuoxCGSacfkakcO4JIu1YmgVmW5hKUhDdTmK0R63X8tLKVnTebksuuii22yzzYorruj1Mm4wBWWhTOVCKrskiDAKBYm7+K266LA0BsA6bdr5NtzcHYADH7bDm266iY++yKgF3UL68jVCBwiNW2woPXhutAlMRdSioQ2aKe7lIe3IU7WQvaHNgT59lAjpAh1htXxexENxL5+sI0+rqkXIOfH48Y9/7MVL1xprrIFC+fNOQpxKim4N6CXFvf3m1iQnn3wyF0bvGBk4akC5/TK6c4rAxDnuDi498MADGaV6A0pRR5Yq85zT66Mzd69mjCo4ou66664zVXdEsIMUU6XBa7/99nOYBg3ArA8Z4xpN3cTPEi9y++237w3i0b0koYtzS2BwGDOfjkZQ87IaT/3Go2L7n7dImdJZkbmn09e5wbCNsZbxR19hhRWcSMaTm0E9U1IzNBAUDvoCUW61trGMWlcLqA5bZiD573//m93dUODXPoO9hXXXXdfC26sv8IR81L3dKkgWzdRuytoSaAv0G1oExqIWDS0lhKqhRWQVqQ3qCnO1NManb29XmKXaZE1ojsprYUyIte6+++7LncyrqNRCy7CSGnm+pmrhVkH5yJrDSXGvCLoYwStK2osThRWhVwEQ6kK3rrIq1Kvh6OVe2jv77LNtshuhuBkYrYxr9CTakl1FvoCZBUifCl+IMujJHrpFjHplUjboUYBTL3yqZVLpsU0sUG3ejqfvrLoTDM3dt2+/SZMn05rdkhm/TzzxxKyzzupT2RwAmIpVUDJqpStsfjEpWh/SznmoU0N5v/CBIX7Wk05KoaDzTXeegTMZeXDlDy7UxBwk/KLpQioaHeXmg48B1iJVVsfaSkch62glJUEC8RR0pajsxhtv/M9//pPh0OaYSAg7VB6MluLJXFUSwBTZCxEwJhhtzGUcY4wn11xzjYFFDxLZZDSSj3szADf4mmnaXZPVl5XQihrqcVjMsJrGlFD8qEExzfeBrmpbrS61NjR08bcyot19bEHr09q5ydIAOBuY9Z3cygPBBylYNw18W2+9degKsgiUxwe1aN8mC1XGFSbx3FlGVqVHuwtkLDUtUFXdJe54G9ElvQwRaE+ZNKFf/4Hkg4XqmWefPeGEE8yOhIFC+cMf/jA/U9rrczISNw+np9PXeWdRwan41o0rrbQS1xe6PpW9wO8lahcSiPO4MmzdxtqgcxV3yndtTY//WMZkNao2UEODAtOkk18OVVtou+lx1YSZtAlzSiwL82Lcbt2rTaA5mjBrNGE2VAvd0FUtApWnr6QWBA8PbAEOkOH/We0BMvXVxxqIReWopZQJgYRAD0CA7wGLu4rQG7yfynuYwsTk6bA8+hOfBEZ3OpZwqAWVzFv0D8kQ7ER8KuGzEexBSfVdjSBeIc1K6p5X8oRRjvaqNkzV6NunzysvvXTGmX996pV35xk1+KD99llsiSWPPfbYVVZZhR+2+dUK8JhjjuGGTk1/8MEHmdV5wrCJcHShqXPKkpJy72iUggrGvCtSKSDFYXlVIJ52Fvgh840uPWsggQyWfABKrgIk021CoFchEL3DgMCj7Jut12GHHRZ9p5LhsRFYJcW9fVQtlX772986XZ8fZAxq7efpTSlIsMGd3evEE08k0HzcewNKUccrrrjCRryjGLpjlYNnpzX7RLPTrDoyQ8tLDKjpDz300O9+9zufS6Od33///X/4wx98ciFGNwl40N5xxx0soFWNdyFgndKlFO3qlKIV2olFR+kVMqD177333lVXXTUU4gyuvESVDyuINJKKd95+68BvHPn6gEXmWWy9J19+9vGf/GqXzdcaNduoDdZf/4MPP0TfOxLf+ta3vANNirh20NRJHZWd60tWbgTQdMkSAfMun1SPJBaT56cgY5a9ZHxzIoPnRpeVgSCQdclstZAFGs1Gop8Q6LII6Il40zvMZb9vvWwa2zDRO7Lu03zmk+LePuaax8ZrjGu1NVVtudrnrGukiNqRYyjFWN/jR/ysQX1pJTp212iK6riIWrBWeh0tq1GQKLithK4s/LK8jer7kXEcJEdA1lC2TzqZb1RJQJunZulKNdCvhIeUpskIEH6W7DPPPJMd6utf//pPf/pTDqAOaVlqqaVw4nwh29z2W4Qds2i2YwsXtuvid+GFF5bdC6OcKyjTpMIbEueec/Zrs8y90qa7jnv/zcVX3fDN/w75xre+++UD9pvEfNLqhkGWrBB4zvDFoojLiJSLq4wwYVOKs2KWWGIJr5+y0PuQkNNRuKJaoBJIgnf++edjT9FJCAO69JsQSAiURMBgEoqf8c05S7b7vCGT7d2VzNKcyJ6muMO0XUUqJptKUmZt4MwNE4ZpIIupKqBEElBVlg4mNiepICJ06HYB6WBZkd3sS7hNrlUB28Gio5pKbOYcHBWMEuNkwxCMxjVxDRJbObDOqKZPF8h2SYk1hLW7JAMLrV12ARdFSjjLJdzkNz0qxyGlrBaBaGUOwY6T4lZ+2mmnGQHuvPNOHiw///nPUfMNTp8ucmiasBe5bMp9+9vfluvSSy81XHz1q18V76u9wnvuuSfHqu9973u33HrrCp8/eszbb0waP7b/pMl9Bo9ac+11LQUff+wxPjDy2uOyp0dr192OP/54G6HrrLOOlymVbpR2pKMdsD/+8Y9HHnmkRYIS7f9gxguXzkjhn6rEyy67zNNg3m26EgIJgYRAMQKhtRtDnJPGGGE0448nsryLXTGdRsT0tJdTDcftwkQFr+qlDfpH0KyEeMnSZaTtNVlloUNjpmkvpwZKsM3gKglF3SOb8CJRAc90XF03qhm/NQtGAeW2bquV2LbolIwvWYWSEtvklg1um9++eZRK4pBP0MGwlkUhW9gUUGtouxeUVXxbSd2lIRX8ow455BDvjPpqT+tgOfPTz77A92XJJRZF1tAXFcxX0+hEU2duv++++yj6zg+1LFx8iSWmTppw37sDl9nmyzNPn9x34JD7//XXH+6+5sqrrPSLn//CMQ6EwR4Xu74FoXJjZg2xVAoKBWHsZWl026997WtinO1rKA7Oi2udxcgoHPa2LLLjAeVG0cFqWwRxq/XLnwzTVt7Oisdw7Io0jgHQNWEmbcKY0yDpyiPfnNEjPxvmS69juFNeTo1xwxi19957s7J7O0uNQJofxKqqY331sZ6muFcCZbUCDfFf/OIXVl28KmPMraSUfJrmDDf5EoXrKygFxItvLUl/+ctfcpU2v9aGUjHNSmKaMMgWsBFDlTrqw8x448aN++IXv9iRLl1Av/i2WoktplAyJnj2RffLL7/8+9//fl6T6BSJLclk89s3z0ZDcchkJgJ+NUG0QoSVbtJikM7iTSekLtKUCWfqZkw/aoQUmhFfYVheKUPHFYgZS6BkOFRqBb373nvHHv3D156+yTQ3x8LrH33sr+aYfXRAaohwmPo999zDa4WXCzcqmzPLLbccUzrPFgZyt1IefsR3r3zwlRELrfj+y0+tNV+///vDb4cMHSYvFZ8z3mqrrSZNIBaBDJwsMp8gn0aNpAkDilrkASmuVFRfraPiEiPVwbBSou2QKn8lxb0kPgBMintJZIojSWxVBspiCpXE9DzFPRsZbrzxRucXf+lLX7ITCAp4RvevBJbiNPXVx3qaq0wxXh2PMdQ61S5M15WPvB0vt3tRoBN4ebcr7CI1Eze79kyAzSyx7mVx/+VIUHeyiWB5BIwkpgGfvnL4/T777BO3WZaYIUSKyc8WmUYuvqqwQSxLX2FYXzYrK0h6V/BWMkzHjV4wdeq0n/7kyPceO2OjlWaT/u5Hzvz2Nz7cY+8D7rjjdio7hxaLEF4uXMy/8pWvcD0v6Dt0MoWe+Otffe76a+9/5ImV99x7o4037tO3nymTyu7N5uDBb4ZJFshHthWGQFsglKxgfjSrqqCSDMTcwb+fpyyXIQQjRuJ0JQQSAl0BAUONocAo8ec///lnP/vZr3/96/i6osj8CNDprHbmQWOdXvkKGWCh8UFQZ1FL36Uar0L+m5PMMcm2y+Nsh2wWbE7RnVJKSMJGG23kHXMMdEfBCJ75uNsx6A1N1ilyUrLQmB5o7Xy7999/f5ME/M866yxn3kd6r3tyIBHp8tS3h8TTj3lyx5udbGk8yx21KZ5XN/cPb4UKM2Pz6mafFuZ/IswWLmx54FQEuYS9Myp9WIDsBaNDYxbvaMU//elPeBO2D2N3OFYOdO6//OUvIl1Oj/GBLQGPHNt/7rnn4so8h/O77rpzzAcfvfHszastO+uUqR9PnDx9jeVGPn7XJYd/+zvU/oMOOshZQw6EUTUWLBZ3XzNFR3Eq5dVSBNFR6ONPPLHxZlsc8a1vvvr6G08/86x4abit86tRFu3/lFNOUQV5VUelVE1YNVVWlYVVXxgUwmBRWRAJy4VOgABG5SIoHrxAFnCBHYcCeocTkP72t7+1Rs902223nXfeeRFmirv44osjzHffhlWEfb7Ap5QjTDvXvhG+4IILZBFWhZ133vm73/0up50oOhKk34RAQqDTETDU6PWGXAPUSSedpAvT2vXTiOx09vIMJIt7Ho0U7igChL6jJFL+hEDvQIAOSns2MYRa6f3OsHCrfUE4FGvzCvU0wtIIh/InHoVQuP0Ki5EgwoFllBLxwujnw5EG5dDy3ebDuIp4BGm9fMMk0NOZz51HRNv2zSNvfN5zz90DB8/61vPPr7vo0Kktfu0tHzQdPnzoT4/97fbbbSWLykqMsryyzDXXXCJNiuJRFokljE1rde/GpDSRWHxo25G9oOIBAlIZCNJnYZSlj8oKoy+lKyoY8QWVzdJgLANEOHiQV8OVDIvEYSv5ljSZh7p42cVnBJHFjLpjII2ZgVj6TQh0IgKGEeOVNT8zliHu2muvZas1MuS33TqRvYKik497ASAlbo22P/nJT1iM2CZrG2flIgHhW1migMZExVTRhJdTAxP2rWOOOcZS1VZ4bSjVBoMpkAJhCqwtew25wqtPHRXqaDmdnBucbp/N2TXQLJ/FHG/uL/ArKJ+lkqehOjhqg6f+0UcfnVcgOkViS/Lc/PbNs9E4HKKPMNY6d8VxKHGbL1q4Qe1eUEqZ2xD1EIyQliyxk17CYZ0NXhVsuC2++OLrrbfBFZedN+Ddy9dcYfaZZ5n5noffnmW+PU77y3kzZrQYtmuYAkvCkvHQ0EDde3TUhXWf5d6EEi8P5DtdvjqQB3im+ucfddkwhk06RuPGcQjDJsykTRhzYrXZuClDEzRn9MgPEQ1qd3OfoaOG0aNyfhRBbm2IeRV1xRVXtC9HcarvCFBffSxZ3NtvXPqZN6gKvpjdfrZekyLmHvOQl6+bsE7oUrh6+UGfx1JbE3CX4rYkM7ybeBuXfJQiG4cAgTGz7rDDDooIlc6tcCxBzRnZWjTCIWAVhkMhQBbNGsIyKihfVjBGQXdEOp8YyjqnFJLDluEDWxtssIEX96Pvb7zxRj88ctB1D9+mWsPn3fUHR/2ydfO55byX4gqWrxTLNxBCec0zU2G4hopHW2SgUUowEHTyzNccBuwyyyzjQ7AKckX1I5x+EwIJgeYjoEu6aO183nyJ4oADDmB8xIbI6PjNZ6mSEpPFvRKUOpqGEDTBTlDAZX1XeAXE27o1pWUKR1tp6hvfBOtIAcNNsDEUlAjVRljcC0rJ33aKxOYZyMLNb9+saIFG45BXAfPlRrjJ7a6ywU9+xrKh5Gh27uxMxa+//roZboUVVlhvvfWWXXZZOmieZ9mp1GEYe+ChR92uuvIKgWFtGmqnjGBZjdRFOA9F9qgjgUAYIOUx6Y4Wdy2uyRq9S9AE7wUrRnJevoE6IgPylu/4HSQe2TWHWcPZA3Wh1haRJjQHrzOjSt17ohqBKFrZKzHehPEqKkuKSI/q3vp6NLL1crvo0hb3DNYskMdaOF1dDYG6i3tXq2DiJyFQRwSavMot5pwCEaMrTnTemB05enKgYla/5ZZb3njjDZZ1ZzX69q1XsX34Nt/HTduRUaTL/BrT3iorLd9aVsud+OJye21Mp7d4bciHnJTPK02j1TjypIhGS5Q1Wwh2+fp25GmDloV5ljSHUqKgfHx9w4BCsKEt0qAqIGuT0FLTZ+O8eh5fRbVIMAY2ojoBVHH3J9I1lNilFXfwsbepquVvJm0iuVf6AIcYojlmzBgBH8xrBNZRqLZ0yvVhhx3mA5NKLIY+kvXaX5IHfD7uvsDiK4lzzjlnxPRsQEISHDrhy2p8lI0CjTAJNBTDqIKv5/DU96WCxvWghtYiEa8WAd1TFq2vxbPRzC0XTwehOC7dUTOmGYc27rjjjg5ZZ1zPy7aULhllL3Y8FYl+zLWRplr2UvqEQEIgIdBQBIxvtobeeustR/EK+Cqqd/Mo8cUDWkPZqJl4F1XcQ/MDq49jeydvm222cWC2SDOB73fYuvUilGP4HL/lTDHe545rbNwOnULXXXfd3nPQYbXCFAqfxasN9PwSq1o63St91HrJJZfs7j7uPuO81lprdS/wm8ZttHLTimtoQcbPTOFWUOjiTki0crvpppvo67RtBvWVV16Zr6f3VfK7uh6Bwkgoo98ItMWtlHlFv61kXTy+JzV9x6Eu3+JBXxoC1oSmb3QR6FPgGioAQbwSVGtuO8Spp43GyqjSaGU3mqOOFSGl1EVH0DpAZquttjrhhBOAbIhr6Bt6gVK9atFFfdxDcb/55pt9Ue/9999/7733NtxwQ3ATxH//+9877bSTk3G32267K664YtNNN7VUqkq4EW+C71cBSzhvtHwXlFhfn6oC4l3ntgn+iAWVbX5T9kiJVSlIFmBbcGt6Cx/3hk6iBYXmbzFpQG9yz80YiHZnuRDIIqsNyGvklCtbVBv9HAjjvDO/ToLnBeuEdatuxylkn+JSa63DBEV9pwE0H38lKh3bZtOOVL9auCK90kM4NX2nlJ75uNdWOv6bL7TETJNlYlYb8uVzQUO75JeU5dPX9rQJ79XoX3irlxpXspqaQ0+v+1lkBWURVJLW0PFBLRThKii6htvoTbg955xznOz0ox/9yNuoIuPw1obWIhvNamC7OEsdsCgm2vEYCJJsYs0ciJpDef2aP2jwphZAO82AQi/S0VoUd+fk68xy6dUxS5XhQfaQtmjFMinjEbKIoxzpK8yVJyuL6rTLWD5LB8N4DkFBpwaGayhdibqWQsOK0LRCNWWTFQuSoDWjmqqs4nhoKM7ArEpiK2w+nEupIjoa+vkmEy6WWJWNWldIv3yyEJjyaTzFm6uO5bZbYj5BYFKXOSNPtsKwESOqX2H6LBm25YWw7Fkk4/r9999//fXXMzWJt2nJ2rTFFluwsmdpyLYwtF0xojZaScqKLg4E8/kqFKdpdExnlV7cfI2uaaKfEOjZCIRKqY5HHnkkm68P3q2//vpGPMN7Z3XzmgHvoop7Vh8zkMtt9hsBc5JF0rbbbutT2DfeeONLL71kHmpJ2nqFRpIRKQhEmoLIMrdsuj50Z/tYEZnGViZ9yUcKLRnfuMimlagggHvZQH/46U9/6rsqNaNUAxrRmuVbvAayZbIEsDEKnHHGGXzciYf+37jOH3Usw1Jtj6IK3kG0+j3++OPpank6Uc3yMfmnNYQraTVp4qqBfl2ydGLpn1a9ipc7KXyu/BLL91C5FN59990GyaFDh9q69D4DfxgjZ4aPLJqbABQsUTqx7nhTevabsdq0QKeX3rngNw3nVFBCoAkIxGTn9ch9992XRudlHiZgkQUjXhM4qUsRXVRxN4tQg5hvqYPeerRXEsOol1A5uK+55povv/zy7LPP7kRhFiOJM/QrsQ9J76okZUCMOOccn9GSpfJcBc2jOhmTBY8aelszw9Vy5XVhX/MeOXJkK0j9qs1ec3o76fzVQjxqJlJVxrx+QxQtIFVZ4zaOh2oltqrqLLzwwttvv33xBndnSWxVzKfEEMjUbhJIOF1mJj7rLBq8DQ2ezoRx1Dozx0ILLZQhZqkppSyRK4tPgYRAQiAh0GMQMHsaIU1nTsqitXtf8ZRTTlG7UOW7aTW7qOIeaDrNwBk9VAonkQEd+iuttNI888xz4okneinQDq/N39///vfzzz+/7+BoHjNQJc0QalAlKSON6c1HRipPX5yy2hKLKdQQo9AactWchQLtrQNtVDOF2jIGthU2fW1FFOTKl+hM63jaUAYaKj9OAXKVrGNBZLrtUgiEVPg1JwVjfHMp61dfffVjjz1GX1999dW//e1v+823r+lKYmNap9gRuhSAiZmEQEKgZyNgeFRBI+S5557r6+CHH364I+DEhCrffeveRV9OzQA1FVGJvD5lHhIZdkFmeJbdSJMPZ7nKB7QZao1+aSPPA+lh32qa8TuKru/LEPnqtBUGbF6NaCtZfeOb8CJRAcPhbt5QTb2gxF4isQW1jtvmt2+ejU7puRkDJds9elkYyyPlm2++aR+SPwzrhj1J75iydNgLygacTFmvSmg7t+6q1vwRLENeIEDLFkX5R00IG2Q0dOOOSmtEFTCsyYr37upYVnNksgljThOkq+ToUce2CFJNmA1pa6wMNRgagBz918dQDY9//OMfOQqKzA+eTatFfUezLm1x10tDvRbIhgPhTGsHej5cd6EMguTGQu1b3/oWH3edQas3qKBuSlaLUAh4jzHvHXfccXzcI6abVqdCtkMS/vKXv/hajS84ZGNEhdm7QrKoghcWnUZvF6sqra4r8N/beNBermwCY7NwxBZnTV7sxklvmn7lK19hX89gkTh6YmdpnxknKZAQSAgkBJqJQLx1+u677+6///5WYsZJzhrdcZouCVqXVtwzTSILqEM+XLJKdY9kuNpzzz3j0Mnml1736tSdYGBiV2Tvvff29lvd6XdNglFr5+gxOeCwOy7nogpcznbdddeuCXLiiuZtstFSBCwuX7e47bbbLrvssqeeespU5Az+H/zgB1wHM6wyk5L0WWQKJAQSAgmB3oCAMdPFwOGbP1/60pc23njj3/3udyrOkNFjTBhdWnHvIkKmse2wBDOh63QRxroUG3Z1namvb+CqN6AUdVx66aW7r2BEFbzk7epSspSYgYC5J94fjcnG+6ZXXXWVDd8nnnjC8tj7xN/97nezVyykp6/7paz3mMkpiUFCICGQEKgKAcOmec11+umnOz7rxz/+MYs7Cj3G1h5oJMW9IqlogiNXRXx04UQ6jPNVLHN7lZ2PaqVNMu+FLtw+bbJmrWVQy/yh20yXHjQFgfBvoXybe7zwzQON/7oPSDtBy9ej7fB85zvfyZaLkViPkzjp601pn1RIQiAh0EURCO2cHvKNb3zDAbjnn3/+GmusIbLnmTPSXmr7IkgOvIn8zDPPSBoW5fbz9KYUVHbVpWEcfPDBXMp6CUohCWeeeWZswxkdul2bRxX4uHuFIxqx21WhJzGsOfJzjDdN+cCwrP/whz/0Js8f/vAHx8UcddRRobVLKX1MSLT2noRDqktCICGQEKgKAfOXIZHx4vnnn998883pITfccENo7WEEqYpa10+cLO7ttxFjJJWUO6mkaY4sxiswsX1veRNfdekNKEUdeQd1dx93h3wfeOCBvaHJikW3K8TQv806ZpfYqvKFCgr6xRdf7PsVTr/9/ve/71MV2ZZOaPYaK9nXu0LbdXceCF50/CyQ1ag4JnuUAgmBLoWAITSGxH/+8582JL/whS/86Ec/wqH4njpOJsW9fQk0oa622mqRLuk3beFleeMEOsO9BL0BpajjIoss0n0FI6rAmutqq1lTfOMQyFR2RdDI6esXXXTR448/7pN+BxxwgDVh9u5BpOx5G76NwzZRrgQBIwDRIlcCtkx9RE+ubHHIJJGtJyuhltIkBJqPQBjalfuTn/zkwgsvdDza1ltvTarFhCmk+Sw1ocSkuLcPMmV0/PjxTk3pqau39iGoIAWUHIzoWLpe5S3tqFAVJxsVINRFk3DT5ww2ZMiQBvEHn1ghNIh+tyOb6esxrzz55JOOiLniiiu83u0ABNNPthp09K/LXlYPnoG6XfP1DIajV55zzjnOOGZw8R4Fn+ClllqKm8Hll1/uI7sfffTRtddeu+OOO8bglrpwz2j3nlQLMmwspZX5kMVBBx00bty4a665ZsEFF8xWnj2psgV16Y0+7sagqoYhc+fXvva1Z599FnaxkisAsd3baktsl2AlCZpcKIPNIYcc8t577+FNj6qEw7qkaXI18RwlhiT89a9/Pfnkk0XWJhgVItCgOgbPDz74oAP4C5qs5hKDTvbL3wMpBRlMI9IiocJad/dkap1dURe3MamYbARoSHvttZdDVP/73/8ec8wx119/PRf20No9lbi3verd3Vu8u/BPtPRKK8bnnnsuPP1ee+01H6OgrBvGCafF/B133OEstfiOisSVVK3CZJWQaiuNIppQSlulp/hiBDqrRWI2Iau+Fb3ZZpstuuii1pmhtYusVkg6qxbFeFYY09Ms7oakaNEy9Y/p09RYJk3+EXOXry/F6f2It0s/nzfCshgKqxWmYjpVxcSBJ02z1RninU/HOlg5sFVVp63EilPTplUTGwGsgGbdZptt3OKhRSwatlypVmLbwqogPnjm425dqoj8U4/Uq0BigVwQk88ijIg0l1xyiWMKF154YQGHjrPh+QbCLbfcwnp3++2326MwzhZk7JG3eZmEJ+gi5oUXXuASAxy7HMCxt+ubZYEAQYo05p7As0cikyrVuQiQMZJG17HDgxMnjfLOIqILLbQQsyXZ843JddddV2T0aGno9wVDRHEVJJCs/BBRnKuqGEzi3FVVrqoS45+pLuutVeWtMDHiMYlYmatRhbmqTaY5VKShRWBJRVwNbXS10OKqk2Hl1hc5ibEDHx37yOrBr51JKDjxWy1WLXVoZC3gk1msslpkTGqjGPCzmHYDPU1xb7fCNSQgH8svvzy4iU5DBbQG3rpOFh4y3qUj/V2HpYZyEpLg60VKMY50R8EInsPHveNzoQ6ip7zxxhsOGndq4TvvvOP4wp133pmSSlN3sqEvfdrTdEyKlJXDJWXlieve4h0p3fdomS2xtM466+y7774Cbm3R2OLwvaSf/exnvNizqhlboFcwfHek9I5D0bml4z8Dp+N1qYFCp5feaAZ0SXo2By390RUQ0SFeeeUVJxe9+OKLq666qjQRTzjb5UcCYlwgwzUgXyZLsNrQIpSOvkuVy3DSwUfoo9DQIjRHo2uhCtHi7cpGR+BqaYxPm4MAmKpYCe3texHo/fffv/LKK7l4Ue4rEdG22GhOLUq2uBrVIAY9TXGvBAJp6JdEoa1WLI6ncwwbNsygVvyo8piqSqycbFspg9umFUr+6Gpeb+ogSm1Vp614FVRiQweOgqLVNKujlx/0ebJRkKa+tzVIbOUMGPJ8ETreSyvIVZXwaALIvPTSS8x4VnF0dEZ3kfPNNx+UyAbTiNOZKApRCtwqWeZhD5FK+nUB83W5VSNMYrVyarJIfOqpp7799ttHH3208CmnnGLLjqHdiTGbbLIJx2IzjfiwJKmaCrotvpQrTVWtUEyk5pga6l5zWSUzhhdH4FkyQUMjYynbWeCTuo6spUlUhe8aAZka9Oqrr8pCWWeGHz169HbbbWeLjO8WZ3f4e1QJDlK6srGxQa2DmUYXgT70FNSgKiAbA1pDhzVtQYQajZW6NLqIqAUJVCONomlYQPjlcuWybylegmyFWXOTNboWmK8jVg1cU9aMYKMzQjBArLAgm/sd9HGvtsQKGSufrGmFBpjWNo6DpJ/hqipFp3wt2n3atGpmnESJUcfMx70js2xGua1Ag+oYVXjggQeOOOKIgiartkTpMe9IeAqHsGN0I8avoRY4BMOGzH/+8x/JCspqq9bdMT7q+/rrrzmF/bjjjuMDw03o2GOPdWsXghfmCSecQGu3bco/QWKzTkP1g+6IYeK5aQhQVkL8rK65bHF0dJ6vSM7u66+/vt0zCj1moi+3y5VkFaZsl1RbCZpQRNS3B1Skh2Fl1ghZPf744/fbbz9+uT5tEVq737YEpsL4JmBV3yI6ZEKuEJTunoyNMOZgFWnoErmbAhXdafjw4XoU74heglJIwh577BEqe8fHjua3flSBP7qTTDoo2EYlYuDNtscee+z1119fbrnlNthgA9/C8LaQuZ9nCEue88gZ3b0PJyy9Eisxk4BXBwwZaz5EStSyFRpjAgRZZu7Tf/To2fFsJ9cvZyTnyX7+85/XO1QHwWzboXyNYqyvBKXydGp+Wnnday6iTMZo9Aotx2Xo1PYolpcd7Be1FS2XcjHQuKaP8Wq99dYLDnlzcY+JY2E5s3kKfJ93sA6PVqi5IiljQqCDCBgGDZsGYbu4YRx0Xjvzh0jdJCS5g0V0u+xJcW+/yYxc9I/20/XuFPqPAzH0sV4Fg23l7l5fG+Xhqd+RioR+w5fd5bSKUaNGUVIdMOfInS233DLGVrLBUcQup95U+WgbymtnaQ9RervItFiD6OutTrFPPvHoeX/53T13P/raa6/PO2/LV9ssXUw5cJasKkWwwtLbZa+2BJ1bOp4xUBvndcnV6aU3gYGsGyortHbQZctUna6zVk11acFEpAcgQDLJIUuHz1zYGTa/nHfeeW7DAtIDKlhbFVrcUmvL2X1zmT55v5hHK6wCiByOQRep2f6BAtNFkwdB3rEqWDPPFYKTJdORbK1yDGhaiVE0/+x4wTzjpNEBXqHmtlAlHXeo4mQjxpcGFV2txFbFhr6gFnPOOWc+V20Si08ZXcChE7h1tD/v+YgPLSGPXr7EtsLNb988J+pSvuc64LFVF29xh33ovrv+efGZLz/3+NIrrd9/xHyPPvzwhhttJP66665z5qMDZOBQleIufVUjVZ7zjofbrXvHiyhPockjWAEz+rWYTLUteNroW91E61e4M9NoZiqkj2FNZjSuMH0NyZojk00Yc5ogXc0ZPaodz6tqdCjpgEZge8Lc2fkc7rbbbiioWlUDabuFNrQWUXp9R7Pe6OPebisWJOCQ6oxbW/ziSUzB03RrMAUC5e+rX/0q5+ZeglJIwtlnn+3Vw25a5aiCQ074C9ZFsA2mxlmrmlB33NLaiUfEQ0nY8jXWPG679aUuDppSY6b2e+/+z7HfPeCU4787bNZRex923Gaf22ffffb55uGH8x1ygZfWLnV9J5tujV5iPiGQEEgItIVAy9jaekIRvcvg6UWsq666itYuMg2kQEsW97Yk57N4gkIfpYLUbDJHobzd7rPC6heq7wqvXb70KMdodGRfot0iSiZognWkoNz86pxFWePy7y9IU99b2DbO8mpd6l20Ap+fTpHYkqA1v33zbJTEQXNYe8Ty46H77770739667XnFl9+vbU32nrYiNlnTJs0edKkueeZZ/75589IyVKD1t7Qds94aytQsu5tJW5EfJNHsIIqNMEmWlBi/jZZ3PNoZOHmyGQTxpwmSFdzRo/8bJg1UwcDYWhH5O9//zsr+y677OLwXLdZfAfpF2dvRC0KSqnvaNa9fdx145gRYxItQKrkrfR06LgyZ76SKbNIxGefffbsNgVKIkAvcYaGFin5tPmRIRt+MeZqEAMOYWgQ5aaRtR3fvXbkm4ZMcUEhVLGf8PhjD19+7ikvPPPk8qtvuOmOB46effTkiRMmTxzLGsLZXRpDjatFwe+84yyLq5BiEgIJgYRAl0WAbkYxs3b6xje+cc899/zf//2fYx9FmsRj4O2ynDeTse6tuJsRq2pL86jm54Sd+WGbiREpj7hcTqeee+65G+q9V56Hrv9U13IMMCtjV9ACo1nzslFJQ1cFchB0yiEzQKxY2hWkqug3IXFUwSHrNpTS69flAYeVKyaPZ55+6rK//9/Tj927xArrfPGbPx8xao5pUyaO/2isp1R0dKT023pLKNoZXsqXm54mBBICCYHegEAY1GntTg3++te/vswyy9x66612s81QlArDaW8AocI6dlcsYmr0NqQPnTz++ONqGzFlqh1au0Mt9tnnC/vvt993vvMdmxeVTKt8Cbwb4Ww7xMlWmSJ656NAno/7D37wg+af416MOX40K34caeI99LPOOisaul0JKSZVJoY4IXjhhReeeeaZAm7LJO6aj4LnRx991HZkEuwybQQoEmXmeO+9MX/8zVHH/+DLkydP2evQY7fZ7UtDhgybNGFsGITKUEiPEgIJgYRAQqAtBEJr95RXjGPaDzvsMO+P0dqz+LYy9s747urjTlVyUZt81sQ33nbYYYfyfsamXvOur+P+9OijDjv0sGWXW/ovZ5754osvn3323ziv502zJeXgmWeeWXzxxUs+qiQSq+SvQs+cSghWkqa+PlWVlOhb91bJlaSsYxrO38U7IbztLdl9uXOJJZbwXgsoTjrppEGDBtWl3JClIOWgbus6uzF1oVyGiK3Dys9BKkMn/4hY0keB89prr8Gq4BFltOaXOvKkOhhugr9pGQ51W5cNunETJl996dlXX/a3OedZaP0td59vocWnT50EupJ2IBIyr5Mg55knEC5Dv/wjdBr3bkP5oj3FfOfKQPNHsDwm2t1tu1NDPksdw8nHvSSYzZHJJow5TZCu5oweHfcOx6e2NpA+/fTTjmkXYHEzcYNI2AxlDKQ7NVR96ngtSoprPrK+o1m3tLjHdOhTnc6ftsXvey7eEYSReBc5KL7Em4T4S/3mNyfsu99+q6668imn/N8cs4+myhuaY5QszkV0PHKa24477vjnP/9ZeNy4cdEAEtvBEaNcYfERlkVYWeIj7FdYjFcAs7A0+TAK0gT94rASlRXxxWFVk5f6KE2ECbqhR9gl7BuNErgEIixeAo9ECssoe0FYceKzyuYrnlVWmojHudNVd95558svv1w15Yo0flU8wqhFOKogS9D3WxzGDw4jPsJyiSkIR41QiGp6GuG//OUvFlr77LOP/n/QQQfp/xiTPdIXEBGfEQ9moqCSjElJ2Pyq1HvvvWd58KUvfclB3aoGjYIWl6a4lQOEaE0VlKY4jL7SI14YpJpJA0UFszA+IxzVj3DUMVpTOGtlibMw4kgFwd/+9rfWvT56ilUllrmCvly95NKcBod+/fvffMPVR311l1uuvWyb3b+yx0E/mGe+BSeNH6vtyFUvgSJVMyGQEEgI1B0B041R1PWnP/3Jl798tu+aa64Jrd3YS2uve4k9g2A3nngoJZqWtsGSahKN9qDl0E4KLinpHM8+++y0aVNXWWlFL5CN/bBld3uzTTd5+eWXZSxIH7dyIc526yxItuTDDz8che9973uOJSJtnjr9kLFfmFfGV77ylfvuu0+YuzBNjveOsE9I2vR54YUXlM7/mx7pPHhh9vt9991XSmFfmtx///0ZbrFBefryl7+MmvCdd96JJo1NWCl2jihewsSasohDYd8Pw5UqC1900UU8VVRKmHNIvIUNH2uVX//61yrioqL98Y9/VKiwBHw8JJblhz/84QUXXCAMxm9961vIClPsvva1r/nqgXBU9uabbxamaGIsvl2PVV/Xi49lepXkv//9r7o4shpchxxyiDR+PVUpVQDXQw89ZEl94403glRl0fcReN4sd911l4pYRB155JG33347LyY8/OhHP1KiSjnA9eijj77hhhvEXHzxxb/4xS/+9a9/HXPMMXj+zW9+c8UVV/zqV7/629/+5ljGc88912eQzznnnPPPP3/55ZeHNiXbAo8SrziJ//GPf/i1UcM5RBFIIYgs4oq49NJLFadQMchiAzPf//73MQYWTGIVw8KoYVUCJXpq24fuDljipGWFtb5zrLQ43yHxACEJFH1hxy8CzSmBwPTyzcEHHxzLzttuuw04VGrx+AEX2IXJG7hCwnGo0AgrmgeXpkTzjDPOUBeFun7fekX4l7/8pY+VSiDZUUcdBRkEZXdAISgMi9pFBXnLwF9ravSsL+TDEYmI7L3horKrppehnn3m6Z8eceB5f/r5MqtvesDhv1h86RWnTrQuncxvJk0qvUESUh0TAgmBRiBgVjJJUdmpSbvvvjvDKHObGU1ZHlFdGlFoj6HZLV1ltKtZk7rj04zO+KRL0dLKuysQEWrH7rvv9sMffG+11demr/pC3GGHHrz2uht84fOf96iMoFATHSBK76G108m41gwbNowEvPLKK04/HDJkiDCNzckzlhAKEu9tRa9TICs833zz2eWhhNEjbRGQVJoT54QIU498VVFYjahH1gnCCEpP54swZY5mH6fL0ZvpfGhKAwFXhEXS7O3Oi5eYNh8H/NHGsOG7SOIRV3rEK5QDAP7F6zncMNRLWAWdlBKHpWC+rcoiEp4bXttFXMXpjhRxHim+lOlrPpiXxuJEWMV9RxNXUuJBoZRpT6XxuT4ciqHUcnayUFGipxBWa2x4CmFVE+OpQqGkODE8ZFQT4ORBOBpRDOSp8mq31157KRRZy5XVV19922231crA9wiRICtjnrhCpYeqp4rDHmAVjY2ogqfYVinxyrJKkZ1yvMoqqyBuFQRALRUFZa0sJZDtDkUrhyQI51sZHSBEK+dbHBsAAR1WsUEAuGFoKZFqEWIvo6JxJR57fuMcJAWRPZyL8UIICvF9RIwNHTpUvTBm2XbaaadZHqy33nrRsyR2IdjQ3ckopd3faGhy227KuiSAwEwfz5h5lj6Tp06/8K+/v/mqCxdbds0Ntt5jxIiRkyaO+3jGx/F51PJlkcnkKlMeokqeEk7J9NZKEtc9jfEEzTLzQt1LzBM0TJGirvCif56r8mEMazKDTPlkHXmqexqXGu3C14QxpwnSpTlMEHV3sCxoPoJqmjCXFcSXv8VbDOlMbGyIvofq15QEFvEF1NRCEa7yNDvytLZaVFVifUezbqm4wysa/rLLLtPGVJmddtqJMlfQ3nlYI/15559/0m9/85Mf/XDeBeb7xz8uuf/+h1hqaY2Gg7Y0g1Bl2NoXW2yxPMGqwoiQyIZKXjE/lgQimzn0+9b90ksvXcxJQ2NUs7iOlhMMyYsssgg3KiZ/Oi5LfCyx6ssMyhiwTqsv2WJq5pK6D8Eh28Ysi43k4w5zi3tWdoF77rztnFOP69t/4Caf++L8Cy/58bTJU1vPIytul5IxRpukuJdEpqrI+k51VRUtcRNUqzIsJcW9JDiGrKS4l0SmONIo1AUVdy3oom4x6tk9tv983HHHsanhP5S04ookxb0Yk+6quEdNjG4cDFZeeWV2RNJQRnGXPhJwbLAj887bb6+3/vqHHHLofPPNW2HGKFFigSiInAmUDGfLgJBFuQw3jDcF8UEzk1fJXJGmg2GUgeM3jBPBJJoZ822Fy1Sqta4tC+uCNFmlPDLbSSYm0kR1SoYl87TML2quSBPhkr/F1pEo1HYB9yF2cbsQe+65J0N+sFGSSBaZL64t9ugTUA3Oo+5qnVnmlJIB0m5YEa5IXyaMvkIp7gVpsI0Nv+KrCgcUGfjy5lkNgk2YIBXU7lXcvu1mqSFBK7Aars+YD8ee/cefP3zPrWtvtvNq6201y8wfT5ow3sdgA+cKKQMzKe4VYlUmWVLci00SZeBq6KMYYcoXQew1WbK4l0cpnjZhWag5uprijqWYKL1y9uMf/9g2+PHHH2/vPdSGtsbYHq+4t1XxMoLUvRX3MhUr+YjchJLEtSD8B4xH7aImF5915lsm20rSFxctV/PVoCZPe9YJbNtLLbWUrY9iBBoXU1KxK26m4piaWVLT2DwhOZYHWpa5uo70ixlr0BAcPFvb8JxZdtll8+V61HyJzTOQhUu2b/a0LoFsWLjtpmv/ftrxI+eYZ8udDpxtjrkczu51XVBkq7IKi0MwFPcK07eVrEHt3lZxxfFEvdFuCcWFZjFNHsGyciMAfIFsEV7wtNG3kCd4neUmVFw7owF+iuPzMRJosoYuNhRByWvo3rVRPcacdhWDfN2rCqMMT1lUpF1Uq6KcT4xyKO6NK0JxKmJ4bBer6E1kg/MqQ7uXu7xItscee4gn6uV7mT1tQDUUqwprkYe3qjB8stGsoDncqlp5BIrLaqDbUHFhdY9RZw2vzu3KTRQtpW7vlzdV5eMyxL3fyfWCVqrECsuqe2W7LMHAhCu21fOJJ55IcY9G6USGtVHWvgJuXfXlJ2rt/QcO8V5+UEq16l19+amBWvDslWIvBnmpv+4QlWcJgDF7lUmGJR1Wssbx5uWXAQMGvvf+Bwztj91/23rb7L3SGpt8PH3y+LEfhDs7BspwWPIRYPEso6sjnIMIBaQEShbU0MgoHf+dUrpyQzwM181nICu9oepCW80XpWv6musuY32HIzi0xW0WT+xdjV7pNWExqbIuGGZVq3sgiDe0CG0RFak78wUES7a4PkuMI2UmFY588K7giiuueP3113sjS7w07a70dIQmVKRkLQpq2pFblZVdRTpCJMvbOYNyVnynBCBY7RaSlwiJV83djBCbhBotGQVgZiu8gvgG3aqjVyrtk9ZLNCvkswkW2QJOzBzqGKMSkFW83aGngEK1tzVIbOVFGBbVqGCDuzkSq5R2+Wxc+0K1ZcU/yyz33v2fM3/3o+Gzzb3VbgePmm30pAnjWl2QPpl14FOtDoQyBy1vjQtks1e7NS1O0NB2Ly6uIKY5MlBQaP62ySNYvmhh7e632qYvIFLzrS6p9TsysHRE8GpjG8OarGAkqY1UW7maI5ONG3OyejVBupozeuRnQ7VrHdKp7J+seVSzdYidxZEJTJ9haHeGjJSVj6s93lUmk4rKA/VR/ysvr5umbLL7R3dESf+0j1GJKtYda9cWz11nL7stDtuNp5p0lnZSiW4hTVztVqSqBAztam3d8JdTfnXbdf9Yd4s9nB0zfdpkHu2MlRkp8lxD6VmWLJARrCoQ2f1WlauOiTvIfwc5iYp3VvU7vfTOBb+Dbdfp2amteKjZ1tbp/HdTBlp7zcxvvj3mvffeX2CBeYcNaTliyPnLDo1ZbbXVGNodjxZN01mTTjcFtoDtpLgXAFLilpz5+uaSSy7p+LyYyEsk6vVRbC1QWmGFFep++EnXhDYk4fnnn7eX4oMR3VEwgmdOhw7h8YZ318S57lyptYt2/uorr/zfCd/7YMyYvQ89Zu75Fpw8YRw9vl4zfWepm3WHKxFMCHQ7BFo7eIvRVyB6okk8unZL52/jPADpI3GkiVoL5+PrFUY2Y0ygZDgbizLmlV5VWClZ+qhUVSBUUtnAJxjzazY85eQ/XHH+bwf3nzbTgLn3P/Qn11x15b333efDKT7zJ0HlhnaJ09UWAg304mqryG4XbzPIQeDO4cZ5JqbdrhaNYzgwcSinIxcdNN5LUIpaMyF4QV6VjY+NQ7hBlKMKjjqNjzQ1qJQuRVaVma/NXrfccPWPv77b0JFz7vetX8451zwTx49tmbQ7z7bdpVBKzCQEui8ChmId2cfmDGsCMcplSrCYtsJZ9+ehlNmDRWbxdQxnDqWYyegXhLMmyBgWU1VYKVl6pVQSzpipsLLZnjPirgsuvOTff/vubutM2GaVSest+Ow3vrTLpCkzfNOQ1q5dXBmwWe1SoAYEkuLePmi6se+PsqpKSjTbz9DLUkRXdyKnbzDFd3+yzt+DkQhJOOCAA3xzVDW743gUVbCD6bNZvaHJHNOumtNnmvmcM3735xN/uNkOB2y7+1dm+XiaL6Hm3WN6sNCmqiUEejYCVEPDms/6+CL1QQcd5NNyuryPWDs1IV6Z8BFrn5YObd4WMZNcAOJT5V7Qj7APV1P6I3zdddedffbZEf73v/+NcoR9Q8bHpyPMFcRrlxG2YIjPjbv1bXKfCY94nPgOd4RPPfVU3+GOKePkk09+5JFHxLNV/+53v3v66aeFeXX7zLmNUGEWMd8T9OFCYZ8N8THssI6J8bVs7vjiWRWdDCGXsG+0O0tDZeHg4AEVZ3kUr+Low0dYiaxsAi5ffM9A8LFzfEb8TTfdlFVcjeLb6h6puCvSiPQB8pg7zj77rOuuv+nhe65Zfcm+EyfPeHvM5IH9Z9pyzYFbbLahs5jxgB9XZEy/HUQgucpUBGC2rKwoda9MpPd6EyAGxN4DQGY46b5VNpj2BvFumdH79Bn70YSTjv3G22+89Pmv/my+BRZunKG9t3WE7iv/ifOehEAokWxtxjReGfGmLBXZ+1fxyBERwlFlabKv8smSxcuVj8/C4qnXkTcOT4sw71DZIyxx9npuQXw2zCpI2BCBJeE4tSLCMaEI88vN4n1BPFRev+IjrFLCUWjERxiFLD7CxRVHOatUAQhZvBplXq/C2Wt+AkFQcRJEZdVl4MBBc87pG+qDJ0zxXnX/mWeaeeDAATM+nmDh4alP2AR76bcuCKRTZdqHUf+/++67l1tuOf2n/dSlUhBcHT76YannDYkLA0M2WDSkjBxRxbEirLrqqnp+DEm5hw0MNuEEgALu8+/RM5C4dQh6Q6tM6az2HKQCnkveBs++afDMM8+stdZa+TSdIrF5BrJwXdo3Pon6+muvHHfkl0fONsf2e39j0MD+kydPbNfQDgfgV7udIotTZRzl3kGpaFC7Z9iWD3S6DDR5BCtAw7AvptqmLyBS861RRetn6mDNdJqZEcOaLFNbG1F0JTKJDYosq7ChY++9947bqphpjh92o0tRcVpHExQApcR64/bbbzvgS18ZPdMTu240dPDAPq+/O/m2Z+f+64W3LbhAh0bCdKpMsfT2NIu7jl1cyYIYaeIqiG/r1mBkz+uII46wkK1hFED20wLb560tHmqIV2gUXUPeGrJYWHOVWXzxxa3Co+gaiNSQpfnYRokhCbfccotz3JdZZpmGjsINqmNUwT6y7d011lgjs6NohZIl5hPU0FKdlcVJ6H369L3/3rv+7/hvL7HCulvuvP/0qRMnT57UrtbeWQynchMCCYGaEaC1G7523HFHFATiNgIR026YpmjJFMqoxO2mN5AaG2N4rDAcyfBTYXq1kDjSlw/nGQ4bU6TPx3cwjI2oLJUd/9YGb7zxxg9+8AOnPR79kx9aL13wl+M+nvbR0NHL/Oy3v+2g1t5a6fRTiEBPs7iTJEJZWMv/vZcg7JftpszyUctIfwhrFll5QEEoxEBQea6OpMRqZq+qvJodKVFeJTJQqWbTSlTNsMjW3DQ1VJmMqWaUaNhCIRtJa6BWSRZ4ViuxlZCNNIirRYFlUWSxxErT6JoWs91Bi7tjHyno11x52UVn/GKtzfdae6NtJk0Ya4SoUGBKglPMZEEMPJPFvQCTGm6zEayGvB3PQv4RKegXHSdbIYVkcS8JlP5o+K1k77ojI3MHx5ySnBdENkG6IBCzRkHRdbnN4FURLvuuDTfc0JmPo0aNQn/Mh+M/+mjCXHOO6t+vjyarcLBtizG1oFS42krQ8fhY4XSQz/Js1Hc0ayAW5avRoKeVtC6ZaxWDKupeyUhRvkYko+NEyhdR8DS6ViWAFGSs+bbJFQw+oymbrFA2uaY1SGzNjZhlbL7EZkXXKRBHofW56Ny/XHXRqVvv+Y1lVlx94rgPna2QDo+pE8KJTEKgiyLQ5Bmhi6LQGLYo67GgdVzMT3/6U6q5zfa1115baR5Rf0cOH+LPrZkrNUQjGiG9MdA+qmTRG9YffPCBpGS0/QxFKWrLVUSmi0ZE7SZPnnzttddymMFlz65vVDDq+Pjjjz/44IPdtMpRhbfeeovDT0GTFdx2Uclrmy38t84Zff78x1//+8JTd/nSj5deftWJ48bS2tvOlJ4kBHopAvqLac6l/lnfD9NPL0UkVbsUAiEhtHYn3nz5y1/+2te+ttNOO1Hfae0ekZzYlRVwIZC09lIo1iEuTWPtg2hvznlPvtkraYhj+3l6U4rYYJo4caKjskJx7w21D0nw1jKtt5sKRlTh1VdfvfTSS3tak33M0tPn9D8cf8f1l+z79V/Ov+CiEyd8lLT2ntbKqT51QsAYTuVyoRfjucEhaV11QrcnkLGKc5EQvyeccMJ2221nr5up7utf/zpRobV7FJITIpSFe0Llu14depqPeyUIk7xqfb+IZkcEUfYKPfMq4b/CNPX1qaqk0Gw5XknieqVpgj9iAatN8IcrKLEGiS2gUO1tByU231/y4WrZkL7a9mXn+bjVr/3UE4+559Zr9vvmcSNGzTZ10qTatHbMx3RVFeeyJB/3qhArmbj5I1iejU4ZzTIGDDKkqAmnykT3fPPNN++//34egJtssokDwn2OQ9in2eaff/7KecCwJuv0U2UyDGsOVDvm1FBQE6RLc1Sr55SsCDqEJBZ1Tm3/+c9/7pstP/nJT+IgMkWQkI5oRyULzUcmH/c8GhFOFvdiTErENFQuS5TXPaP07WSk6Z5NVzeujfKcyqK/GO59K0RYpInKrWK4VNWtsFKEGH/Y2k/7wy/uu/2aA771ixEjatfaS5FPcQmBHoVA9EpfgGZADR3d54f02ccee+yhhx4SiAQ9qs6pMpUhoOmN2+Z0MzuP0J133vnoo4/mHnPllVfS2j0ysIdCXxm9lKpuCCTFvX0oCagvh73//vuSplGsLbwsiy3He4mPeyYJDz/8sDOwstu2wOma8SHMjG2+DthxwUaBvY3Xzd/+9jeYGNMvuugiYV/vo77HB/Z8O/C2225rEBqWBXFe+1//dOKdN16+7zd+PuvwkVOm1Ghrr5lJuk7NeVPGhECnIBCW8jXXXJP67juXvr7p8pl6J/1VLs9SVp64tmo2oQiMNaGUrl+EARyT9HK+lJT1ffbZZ6WVVrrjjjscjW+od4WdrutXpBJJ63a1qOJklUrq3yPT8HL517/+tdhiiznqiLxq4x5ZzQ5WiuLus8+rr7569tm2DhLs4tlDEtghnOPuEPTuaHuIKvhctnXpZptt1hHAM1Jzzz33Lrvs4mPgc801lw13RpqLL74YcRqA73VbJGy//fZVdaIqhlQeMn36XHjuX269+vwvHPazkSNnmzJ5YscNQlUw0IpgpI9RIn5rBrbaomsuqGTGzi0dSx1Er2SlKo/s9NKbw0Dskc4333xeUvKJ+7322iu+yLHtttvyljGsRQKuO7ptefQklqyhbOPBdKyg8px08KlljFo0dPeYNRCTHR+dytQUSipSbREQltH6Teub2n7/+997dc0Ed8kllyyxxBLAJyeQyVpZi6tLdluGn5ofqYUisFQzhXYzNqcW2CjuRGJUrdpm6uobYdFFC7qQVgzRCSEDR1XVRpOWmX3Ot91G7XgCfPYGH3dAaZqq2qLj2DbBH7GASZ1cT2voUFVQYneR2Gh9H+O49957LXR9HHvBBRf8z3/+w1PWyQOOrzn44IOHDx8etVMpnaKgpsW35gk7+AUjQHEyzjj9Bwy64Zp/nvvHo3c+8EfzL7DI5MkTTL7FKauNqVakCYYsfNxd6tgROZGdZ1H2sfFqOe9g+k4ZtfI862huKRD5yKaFNaKymjyaZbXTNTAQvitZZOUBUlc5bmZDvYzj8gMPPMDscuutt26++eYOUqO7jx49OgrFDGkszwCBoWPVzHN54vFUEThpqA4HuhhzOtJzy9cF5Rj6VESNyieu+SnKMXpUXgRsCTzJ0fXOOuusU045ZYEFFjjyyCPjqEdyUtwdVERk47BSfbUIriqvSLWgNboW8NE1cMWAVVwLtWt3giuoUQMXMQUl1XCrhlEfgbxkZNIjMgvXQD9lqTsC1cpf3RlIBDsLAZ1UZ2Suu+aaa7beemuvuOEkeq75wKFMdlop8R7RAOorJwj27z/gsYcfOO/UY7bc/WsLLLzYpPHjZp7FERmNmhTLgKzKZZ6mRwmBLoVAiOu///1vH9B5+umnvZxKd5933nnXXXdd+2YHHHBAaBV+XeU5R8pV+YKhPLW2ntKxGqq4K1dN1SKvcrTFTM3xMQDWdxgsYEZbVI6VxLJH2zGun3zyyQZV76EarsULQ6Pka8fiG90cSldEu+JXUP2qbptQi0C4Xlh1acUdmlwRiMvSSy+dNQNZ5Cm74oorshCw7TESkDbDTb0QyQrKAkrkobv++uszP0AfV9mjFMgQYKWA0lZbbTXrrLP2BpSijkzL7AHrrbded6xy8Pzaa685UIIHS8cFm1GBuzzHmDnnnHP8+PEvvPDCQgstxEVyySWXXHTRRbfYYovTTz/9ueeeE1a0SYv5IZOftgKUfja8sryZcmZ+5913Tvn5N1ffZJcVVl1n0vix/QcMaItgVfHBZ7VzhpnGoOSqqqzixEp3VYJScd66xKh448bVdjmMRu84jO0WVDKBRhTfUNWqZLkRqVwMNKfpzbAbbbQRR0ceEXPMMQet3Zhmx+zll1+2S8aLhhCW7YCf1KNVWhu7am1CEVGZCqtcpgXLP0K/fIKOPy1ZBKGKqmWCbYAVjva1L/rLX/7SK0nOaLdmw4PErixxMVeRoBLxKM5bYUwUUWHi2pI1pxa18VYyVx22kkvS7WBkDJpebH/yySe9//fUU08hSML8eqOZYHE6d2s7z9RiXod7B0ssk11BlgoKlaahBZXhoSs/Ckwobbfddhv1vZegFLX25uWjjz6qyiGxXbmZinmLKrCF33nnnR0UbNU3duuthn6GOq+lmu/ffffdP/zhDwztofgqwgLb601WwsXMtBUjl6v808lTpv7iyIMXWmKlDbbYeeL4DzlHR65O+cVqlBuBtjivJD6jU0niuqfp3NJVp3MZ6CWlh8qltx566KGrrbYa2Nna+ZGqvt4qXkxD1bK6y20i2BYC3J2o4EZjv6HB023cat+77rpr1113Pfzwwx3Q7lih0NpD4yqjtbdVUIpvNAJd2seds52XHS36X3nlFQZvWHz00Uc+ecOkd9VVVzmQiPrOB8u78CU3cdrCzpDEW6vJnqOVb1q1xXa18Z3iIQrbJo/ylgpav5mFNr8pu4vEQkbP8taBtTRfdmxb7jqkIiaJUN+rfUOg/DsMMfH834nHPP34A/t87diPp01hUKqjMKgC5oPzCjug0nHFwZ3lUvaOMKNoeDbzbZx8HTGvQTvL4I2TzCs0z1XTwqG1VNX0deRNN9H6DfUXz3Mbck5FI67KDV1NwK0rn7JMWHpNVtVcXIZayUfNkcnyY05JxiqPhJLEKuK3odKloOLR46UXnqdNcWGYbfY5guf77rvvN7/5DZvLbrvt9o1vfGPo0KHiY1yNBOV/qx3Py1Mr+VQt7Ps1dOuvCbWo72jWRV1lKOi22kmeEcTgle0Y0gN44JEqe/HCpkZ9zJFzZI5+oDNAJwbckhIQkZLZChSOzlMmZTwyctHyUTaNCVeYK09WFlw1VPLyxQnjkywK4LkGhguolb8NTLSUITss7rWhVL6Ukk8VpERyIlAyQSMiQWrAVV/AhlJFCBtaZQVVJbEV1jp4bnHp6NcPjHk5ES6WWN2wvAx7atyPoR8P6EevDD1ADLLKqpC9dpN5IVVD3HjNP++55cp9vvHLWWaa4eSLZkpCuxymBAmBboGAXpMpkVlvzQLdogrdgkkDYKBqdhYOzAVMYZWHJc7yCqt40CwIx62nRvKZZ/LKzyy//s1vL77hvmkDRg6e+u7hB+yxxJJL/uIXv3zkkYedA3bSSSfRqSIxapkwdAtUeyGTXVRxt5/++OOPc2SnCoSYRttQ4kkhqaLH0KRXXXVVhj1+8JzdqQjS0C3IdPmGDIGu3JhBUbM28KI9/z/Ea9AM5EKkjipL+QrG0+jMTSuU5nfmmWfuuOOO2bEhlTDZ8TRaU1NGZTtOrRIKsTqXkiTwDmIP2HTTTWsTjEqKk6Zaia2QbPDMk5WrzB577JHPVVJia5B8NPO58uF8cTWETXYa3WnTZ//x2G32OGz2OeacOOEjM04NpFKWhEBCICHQaARivD3ttNOYe77whS9kxRkVM0W5knB+sisT9ijMPUH8ogvOP/nyu5fZcj82ronjxx929O9GTXtrh513PfHE3zq3FzOhWWWcZOylQBdEoIsq7t5xdNGKvPxHI2TKpR4RrNlmm83bbxzvfI3Z2zP83b0X6F14b8QDN9SCSpQDafIS327DKIKvjiy16Wdyyetqt6A6JggcmlYo5dKrCNYnSqwNpdrqHk3ZtGpiUllRnKIdTO4cFbeqH5G11aLdXNVKbLsEJYhmwr8XRtF3Zbk6RWKz0tsNYM+BMfZZ/vL7o5ZZef1lV157wrgPktbeLm4pQUIgIdApCMQEceqpp371q19l22IusTPpHVCb+bSLyy+/nH85MyV7pVO5vvnNb5pNfLnWK0PcV4zMFCFu6D6EhHlv3Hmx6pBDDhHmj/7SSy+FS7qjgbgh+ECSeCfDKHGnnXYS/ts558w2csQDTz43zwobsbtP+HDM4FlHjlp2g12X7n/0T34sgZR+k8oOhO5ydVHFnY4OQV7s3nKzPN1ggw0ItNmaDV6YlFOjLRO9RuMkEz7uvvYSWkgjcGfFP/bYY4NyXrlpRFndlyYXpuOPPz6GgN6AUtSRj1Y0WUO19gZJRVRhudarQUU0iGysKy6/8Oy3X395u72/MXmitVOytTcI7EQ2IZAQqA8CjlyjTjBEchDwGyOwXXHxUYCwmTTCUpYMy5jFC2euidYADGeRl9ZEiXJRx+edZ94B/fq+8tJLk/oOCjWpHx4UNHSYBGLKO0DWp+aJSl0RqMVju64MdAIxyiX7PcluWtn6RvNdZer7MkSFWMW4UGHiuiRr6ItEJTlswossBeX2EoktqHXcFrdvyNirr7581Nf3pLUvttSykydOtINWMnsHI5UF/KpsUSZj02F6ObWDyMveKSNYxrZGFK6q6bO8HQ8YZAhe5f6cHS+x4xQwrMmokh0n1RaF5sykxWNOW/xUFR8D14UXXkj3cHhLVXmrShwFRRZhxs1zzj330YcenDb3Sgust3v/AQPHjx3z/t0XXHbGbxZbYsl84qpKicRNmA1pa5YWDV1dNKEW9R3NGjLb1dD8bWUxFrg8JV6uCMQysSDcFoWOx2tUfmnc6KPEjhPskRS8TOxDax988EEvQSmk0U6lDUpVDintXi0bPD///PNeTojqdH3+8UmXnjJ1+l9+f8xiy66++DIrTZ7UKK2966OROEwIJAS6CwKW9Ibc3XffndZOqQhNDvNGtFglFoezaaVl1GtVhCKNcHYh5al4MREOQ/57773nNF6+xA6N2XijjR546OEffHHrmR67dNwj/x72wrW/+cFXO661KzRdnYJAF3WVybDIPBBCFsULZFaQfDjLUveAXvH+++/rEigLZ5zUvaBuTdCoYaTIBqBuXZdKmA9JsFxxVZK+y6bxAhPx7rLsFTBm+nLkwf133PDy8/898IhfT53sPJ+ubn0oqEK6TQgkBHonAvQZE6W6Z4qNcF6NKQhnyoZAPhy5AsMgZeYViLMoONAzNfKV98nI7373u9YJoTLtv//+O+2w/euvv7bYYkv0H/iJ20wQSb/dC4HkKtOM9qLk9RJXGaNSfkhqArgN2tYsw7klnG27bBgtk7Jej6DaG5y7SsJV0L66krPQvnPQzkuvvO7aG28/acJHDVXcW4qr3lVGZ+cq4x36WN2VrFclkc1v9zxXnTJq5Rmo7+ZynnIl4bBBZEaiSrLUMY1BRusnV5kCSJsjkwVjTgEPdbntiHTFqPL666/71N2YMWMMNV61isPcHMf317/+1ZusK6+88oEHHrjOOutkaj1JVmgmz6SrLjN1E2bD5CpTLHJd3eJezHGKSQgkBHonAjHZ/PuS86ZPmbTSWptPmTi+mcun3ol5qnVCICHQdRCgtWOG467TZhZffPFFFlnkgQce8HV5mvqll15Km992223PP//8pZZaSjIrkDgrOfR1v7K7DJt10dq7Diy9jZO0y9x+i1tTnnjiia+++qqkVIf2M/TKFE4V/NWvftV7fNxDEnzBl9mjmwpGVMFhZF5OMJp3cbFt0dpnnvn9Dz689tK/rLHproMG9m/l/7MjLLs4/4m9hEBCICHQQQRoI8bq008/ffnll993330dCXbQQQfZm+LI/rnPfe7WW2895phjaO2M63HCDGU9b90IlT0f00F+UvZOQSBZ3CuCvUD6K8rT+xL1wkW8EbAHDILdpuFmnvmmKy/oN3DY8qusM2nihAadJNPxjtszpKLjOCQKCYGEQF0QoKyzUxhYnBGJIDPiZptt5pdN3cdtmN5XWGEFp8J7RGWXjMYSdpm6lJ6IdDUEkuLefot44ePrX/96pOs2Kk771apzCqfJHnHEETFY9ABdtl10QhJ8Jqz7CkZUYYnWq936dnoC3E6dNu2GKy/ZZNs9WgTMFkHui1Gdzl5iICGQEGg0Aj1mZqmwIqGvG/qkp4uD13fir7jiiquvvnr++efnFePsdor7Cy+84KM3Jl/pI1mjGyJPv8K65LN0wXD3qkVS3LugCCWWEgK9AgHTTLv1lMY1Y4YzE/rccuM1A/vPMu8iK0ydMoHWLr7d7B1P0Fp+1QVFrg5yWBciNSPQuaVjO9DrIIYdqX7GQ81Eas7YcfDrq4jwu2i3ISSQjC9HzbVuN6Mi4rXOdlPWnABuauGqL4B5fqIIMQ45aAtVWriLh3oo4m+99RafzGuvvdaJMauvvvrvf//7c845B5Ns7RdccIGvy++www5u0ZQryormENlWEXmWag4H/cZhhbGol0DjKtLoWmQtbg1WUAu3xCCMaJW3QlLc28fKSHTCCSfss88+1rhQrkFGa8jSPltdLMVHH33Ezc43mRkAakOpi1WoHDsaNOroI76Og/SVacNltX2vXAFNeRZVePLJJ//1r3/ZLclLaT7cIF6Uno3IbRWBjc+cNfvOfPvVF8y7xOrDhg4a99HY5qCNSS1bLRrBs4yxbd1W7dqNVzoKLoF2E9c9QZRebd3rxUY0PWqdUn2lZ8LZfPCj7iE/tZWOQn0/WFOJHRfDktW33AJxCjQaWoQS1cLVhBFGKfkKql2MNlm8WZXb+sUXX/zII4+EiX3XXXcdOXKkXD4b/7e//e2+++7j5s7Z3XevCkQlmiMjlS+ojmGFag7yVkeaBaT0RLVoaEWaUIvgv2QtakCvasWdNMDR2c8FUkJutF8TZL2gUQtu8VbAWEECtxJIVklKiWFKcR81apSwLNGvimmWj1Gi6ad8mvo+xTZu0dQi7QLS8aIVp4JU9hCP2lCqgY2oppoK1JC9tiyZ5OiEdiqj7iIbJ/xVSWzlldJMqoBtMwEhz2NYUmIjceX0y6dUXJw6XD6ZUaVvXyX3feLxR1575aX9dv6SL5dUkrE82QqfwgGfiq8wvWQBYzBdVcbiIjRQa/WrHqWLSdUWQyqaBnUxh6ovEgLFj5oQE925cZ26fBUIXrR++WRNe5ofHNoqVJq42kpQl/imFaGgujBckkgQz4qI5s4GWJOpgx2Z2J0YI80222xz+OGH82IPUpF49tln/9a3vpURj5EquxWQMa58ZN3DnxbSWKwaXZHm1CIapS5NUMV2M2EiWHfddddPfvKTVVZZhaAY1PxGwMrP68xrr712JKsLczUQwUy7uQyIVZ2KrVGDZiXES5YuI8WuyVNgk09BDpRgm8FVEoq6RzbhzN0CnmkzlImoZvzWLBgFlNu6rVZi26JTMr5kFUpKbJNbNrhtbd8BM8/S57TfHvXO229/bp9vTJnY2LPb8yjBAfhV6d9Q0tnTOe55GGsLN3kEK2DSRCamqqYvoNCRW4MMwUvnuBdgWHJcKkjT8dsmzCmkS/vSoAwX2eKQwNOvfDjpxhtv1PS0LAe0c16PgVd61Y8s6hhDk19PS0qp9FXpObXhlp8Na6PQbq50jnsxRFUYM0J6hgwZsswyyxx55JGDBw/mWYUiWzsD/I9//GMxbiNZcUnNiamkdGniqpYluarNkqWvrcQsew2B4LYjPNdQqCxNLjGAbWahxSU2uvTiEmtrmjK5iqsQhZbJ0rRHvNsnTRx/z39u2XGfr808wz5S7d2waTynghICCYGEQDECoXBT3ON8GAno6+zr//znPx966CGOl76adNxxx/mlWUV2iY3GmX4fkWJK6uvFJaaYnodAFYp7yI3TQx1qTmhuu+025/zvueee1kMbb7zxSSedFOgUiFcPgMyyxGbCl770pYUXXjhWyT2gUnWvwtixY4899lgfWLaFF2aAuhfRpQiGJHgxyAH2vlFnbO12w2hU4dFHH7Une9RRR+nUXQrhYIYsCTz95BMjRgwbNef806ZO7oJMJpYSAgmBhEBbCBhpY04Me7mZwvXaa6/xhGFf563A6MkT5gc/+MGGG26Y7czbuJMsKehtodqb46tQ3AOmmOydSXTqqaeuv/76DPDvv/++9yc22WST7qi7VNL2Os+yyy6rphJ3TeWmklo0Og3vEYu6bNBpdHGdTj8kwQtDFq6Y6Y7r1ajCrLPOSrw7Hc+2GAjF/aGHHxo+fOSI4cMnjBvbHaFuq3YpPiGQEOipCBi76EtqR4XI6vjss89eeeWVXGKef/55SsVGG23061//eo011sgM8KHlG+U66+2OjNUU6LIIVK24R00c2k2wHFHE7u79PN/dFd9TlVr9x7EhUfGeWseOCyibgXfbQ83qDShFHW1odl/BiCos2Hp1XAAaRaHV4v7ua0/1HTonh9BGlZLoJgQSAgmBjiEQOjcaoakbYCPw+uuvOxbmlltuufPOO23g27p3pKNNziWXXDIrMI43oFa5ssgUSAiURKBqxT2kyumhP/vZz2644QavJnh5gqkV9SRwJSHuVZGxIdirqpwq21AEZukzy/QZM00a++7oRVZ3olVvWBM2FM9EPCGQEKgjAqa8uAxNeRXIG67333//TTfd9Nhjj73yyiteNl1zzTW9HLjSSivNNddcGQP8FIRlTPb1DJMUaBeBqhV3MkpArSCJIz8B0vb222/z1pp33nnjUbtFdrsElsj621e/+tVFF100PIW6XRWawPCHH37IRc+JQ3POOWdPlYQ8jCEJTtJ11O6hhx7aHf3EogreiDrvvPN++ctfdk2d2IT32utvvPf+mLU2X3Tq1JYTTtOVEEgIJAQ6BYHQ0f0qnbZtzIwrmHnjjTeeeuopjsReNqUU8YRZbLHFtthii0033ZSVPWPYZOEKZT3vRZMlSIGEQHkEalTcGdpfeukl3rHPPPMMJZ71XTE9VV3TtTiijRgxQh310vKA9tqnFCzvOfCb6iUIhCQ4Ycm6TpXztpbugkBUwcvEXlbpmjxbWjjB/a1Xn/9o3MQRo2afMb3bWNxjau+aqCauEgIJgcoRyJR1AZbKvA5A/6agc4BhXH/uueco7hJwgPEdU99F8u6QaTEryGgWOlJS1jNMUqA2BKpW3ENB4RZ72GGHKdKRGocccogTRfK7P7WxUj5XSLw0WSDSF9yWJ1LbU11RP4y8+U5bG7WemsvZVbvssovmUMHegFLUcdVVV+2+ghFVsFfm6spiOf79VwcMGTFzv0Ezpra8B5yuhEBCICEQCNRRAUDKhWyrQfwTDxa3xskYKuPRiy++SEf3wWnKujDfdLYPu/GUhPXWW49qlNfLw3M9KHRH406AnH67GgJVK+6xvU5qTz/99OHDh48ZM4aYNsHOSvQ5jRH97HDTgFJ8sNTVkO2F/Bj1Wk2kn71B3wtBSFWuIwL2oqdOn+m//31qkUUW9vnUyVN83qt7vLmVzfR1RCORSggkBDIEsukm3E6q7XGho/vNApk1fdiwYVkpPlbDps6fkM4TNvUPPviADwzXF5+bPOCAA7zvV2D4QNA8iAJ1Bc2MVAokBOqFQNVSFatGUvujH/2oVeY/Hj16dHDToAWlUvRJJ9hceumlji7x+d/ZZpstShR/zjnn2Jnyjnbj1He+EL4t/M1vflMXbVwp9WrR5tOJBjKcHXHEEZym7L30BpTMFpasZ555Jh/3r3/963HbfPA7UmLwzG507rnnOpKsQf03OAwhEc4C7XIeKSdNnPTkk0+st8GGLU5qzGHJVa1d4FKChEA9EKi8q9ajtOpoBG9GYIGwcBdw6xbF7DeeUhji8kgg+83K9sIed5cXXnjB66Q0dQZ1725JSeWgna+44opf/OIXHcXhNrJHRvNdTHki4wqWMrIpkBCoLwJVK+5ZB/ChL2LtXEjnuH/hC19YeumlQ3bryx9qyPrViz73uc8p6/HHH/eRgtA5YhFsc0qC6KKVlB5dq5KUkcbZ5HbBbIe5rU25qbbEynkrk1KhZZ7W8VEUZE210047kQeUa0OpNpaaj22UGEPzaqutFh9mb+hI3aA6Bs/zzTfftttuW9BkdS8RwZI7Zu02+vSp48Z98Hb/Wef5eMZUk2276VOChEBCoIMImEy5v9pR7yCdBmUPJYT9+49//KNPjfIj9wk8HzDilxIlGm1icBMoyYOX9GT0ep5T1b2t9+qrr9LXaRc8CKQ3lxkVeah7r3SBBRZwCEfM/nlSeAjNRBEGz4LxM58yhRMCdUegasWdsOoSXp1m6valzLnnnpviMs888+CsrU7SQaajB9pyCkO7/oagSLo7xzIvRGbdVbyw+PKcqAKeg2wlvKGmA0euStIXp9HJMRb9vPhpg2KMTSgrukH0C8gaueh/gHUVPGroreJi6GxoKXnigM1kLA5CbXSVq5XYPLfthueYYw6HHhRUoaTE6oM1zE9IaaDiHbPynRTbBNes+/qrrwweNGD4yDmmt8pzu9XpIgma1u+6SH0TGz0Dgej4l112mQ678cYbU16j/1ZYOyOVCbjCxFmymXX0TxXsbFj4LJCla9UxZpF25plfefnlY445JuzfvmT0i9ZroYUWytLixNqDvdxWMHX8vffeY02noL/88ssUdEYEF7dbB2yMHDmSAmPT3gkwdu/tGKNf4P2Lmkt8XEoRqFyFyLhKgYRAXRCoWnEnrwpm5LZtpDOQ8kZPUVdffbWjJxVHacjK0ouw4WNjea29LogUE1Eob5moePHTFBMIaBFDYW8bzuJImW4tG9YhVc3NtQl8wY5ZzILlScVU/sijj842atRss42aMnF8DcuG8kVU8lTjVtW+kT6yVJWxmJkgVRzfnJjOLV0dO4heB1Hq9NKbz0CMA2+++Sb315133tkpsdV+U5mtuoOwl87+8YyZZnw83abbjI8nTJ7St9+M8y/+x5ZbbslsZyRhDv/KV77yjW98Y5VVVqGT0NedmeGD1uYjHuo2zCnoLoY/5vMNNtjAgcWyMFiIicPiCgqVNxQM8dELjDz1HXya0LjBeUHV6n7bhFJ6TBF1BL9qxT3Kfvfdd3XR++67z/fA9BOfzOQq06Dp38cpOSR4O0SftHrOvjAfXUuheTgYBV35mOKwLK7sC8PFCQpiGCMPP/xwbu5W5DLW1uWszttlrKDcDt4Gn4atDtKpMLum+fa3v83wYUCsMEtdkjF+2yqtrVFqY8AIrilDEvi4k39zRs2CUQkPiLsql9hKaEqDJtweeOCBs88++6STTirIVS+JVYQ2Qi1ehokdMxjqv+VX3TO07KBBLz714NRZhtqXnjR5cn3nzoL6lrwFET6rMq2pr3oZNPxmOzMlibcbqXTLqhC2dhPXPYHS8Z9pMHWnX54gGLNdIJyUT1z3pyG0yGr6Tildu3cEefzXPPKbZ73DhgJ3EYov23MlkqCJ+vftc9tDj74x5sP+/QyPLW0Szdbyi4Tr03/jTtfSQ3QTl/r6f7Im9//UKZMnTZ44aSKzyMSJE4TFTJo8dbIE02e07Kf36fvG4w+df+rJpJNRHYemZq+QLrHEEhRxVkVDDZMiBd1k5EVSEwTFvYWh/70grIjopKi6PPcbdrq4/d8c9blDWaFoNVS6gNyE0UPbdXCUaxdTQqGlGjoMNroWWrzMaKZq1U5t7ei4xZhGAfqJjaqCp9WWXZC9rVubWR45FfWSSy6xWthuu+3cMsP7YqteSvSr7WAxarRVXHG8InbffffsHdziBO3GVFtiuwQrSaDQSpJ1PI2CNIHRc8899wyLS8R0nHIlFALbamWgEsptpYkS46mP4Rkc20pZr/h8ifWimdExPcc5nnkMG1FiMU0x+UIzliLAdVRgh10/P1O/wfPMM++0ueYsk7ggb71ucWhaogMJVE5TYqusqrKUJI5Cx4mUpFxhZCq9QqDqnqy15asQuQIGOtJwJfMGP2U6INVq5ln6XX/jjdfeesesw4a2rDpaU/uhDrf8fKoW0xN8uKjlt9UC0q8/Pb+v/tJ/gFD/FhV7wMCRo0bOO3jeQQMHDh4yRES/fn37O1BulpkHzDJT32lTR8467OprrwsdgKOLup9//vm+kLjffvsV44ATzFOb/EZYmhauPuWH2pTPFfESRyD/qI5h9OtIrSQpRTSnlJKl1zGyCRXpRKBqK3rmGrIFjjfffLPestdee1mU85ENc2BDZT08McL5zF4YHVHPz1aulQuK3stsHypm5bk6khJilnQ1m0BqKzpWeNEutVGoIZeaNlQGilkKV0WSUPyoQTFhxmhmNbu1xIZI3HDDDbbdGfNs1nm5XI0qbLLpMz7uw621867mi3RWV0UbqWLEyyKbGTBqFag1zSw9lsRNHjazChJR4QqlNMtVrwDkMdApo7czVVy8ULzG5tiJyuUfw9OnTO6X++RQKOs5TOrZkY866igSstRSS3m7lBf7cccdR1QMy3EpVCBXdBVBKo3VQs3ZKympCdLVnNGjCUOEDRCjEPtpJcDWlqYJtajvaFa1ukPgCDQPmT//+c9cyti81fk///mPyJDF2oBrNxcppGqbwwQkdnpJDKmas6EtGoxZHkS57fLZmxPEllavQoDMN1TsmwAmwY7Vb0PLorXbMbv33nsFlFj5pDhxwngjjCydcmlcA25tRXcczyi343Rqo9C5peO5cxnohaXrlWrt3EOr6z/84Q8rrbRStZIz3WcW8n8t75zm//6Hnon8f/4+5sf+8Sd/PNotA/xNb3Gn8dvy1+paQ42LIfenP/2pTz47jdf7b7/97W/pBqEMUAxUxPU/hVVz04Sm7xlFALVnVKTb1eJ/Nokql21fKGAM8BbLrbfeSodeZJFF5O1IV2m36Ix4Fmg3Sx0TNGFtUEduO4tUL0SpswxydWxiHaqhDRcdlsupjWzhau3HEHZ1Sq8PkBXdiaXXsaETqYRAuwgQdTP7brvt5jyWeHGzOuGvxgOkULP+n8NlcFr4XFSLgtU6IER46623zteoOlbzOVM4IdCtEKja4q7XqCBN/bDDDnO+qSnfGyEc0EXGo25V/cRsQiAh0AwETLj5HbNmFJnKSAgkBGpCgAZMa9dna8rdpEyYbLHFt15dnNUmIZKK6TUIVG1xt0tFQX/00UdtfK+xxhorr7xyfP+oeyHW/DVG840BvaFEUtcbmrIHVDOTxixQ4YjR/PYtYKxahguyd/C2c6vfuXXv5aV3bvXJbQ0M1JCl2g6SL6JBW4VN6HT5WlSLQOXpe0ZFYNVouBpNv7beVKaha3k5Ncj5lgGP1TvuuMN7os4BXHzxxUOnL1NYF3kUq/MmNFWn11dNe3w1e0MdCVIvqWZxl+m1FY9G99vju3Bxo0dMb276tjDp4vE9o8l6Ri2ISs+oSKpFca+v2lUGiKh4I8QHh9955x3vcTtOLk5sLKbeBWNCCMyFUZEuyGHHWcqqFlN+dttxyl2NQrRmV+OqXvxkDdezq1kGrqziGRRlEvewR1H3nj1S5Zssa+IIRPVLJshH9oxwQd2jUllkVsfimOxRFwn0AHEtFrwugm2FbGRC0q0r8v/t3QecNEXxN3ATIBnJOSOCIEiQnCTnjEhSMCGKiJhQMWEExICAklFyzjnnnHPOUZCM8f2/37uSdty729u927vdvat5Ps9cb091ddWve2Z+XdPTM+a9KA422Kw1Yk3z1zJVxleRfbrMi+ejvGRVjQND+GkBQY+Q+v0iwxC0dWaRaCbT/3jqYmplDE8VR+HB2aihwUFfPoqJmOEsNy044Fsbo2bDKFRkhOz84pSm5KAW5KxVVrrupBsyVuPhbO0LTtx0i+/jpPWLvwGIb7rF+5Fj+DpWmj4uYn5a2ZDXTnbp7kJAp3VNnnLKKYtT3ZVwl9QD2a8t+BK3zm68p1hD1injy1Ndfd3wqT6kBU/rai/6ntdu3/waJitrOuIe5G/hhRfeY489fJkMuPp6V5yfMcR5/vnnfSfyhBNOsOKVnMjsCvsbMTLcsf6uj9qSP/XUUy3RyNMTTzzRydzrbke/b9Sgj5zi2p///Gdf/bT6wZlnnuk0uOqqq6688spGNHS+TLSj1ZT5qO3cv2+++WYvlsj30yw1LoRM5/syNAvDu7F9tvaLjMupC5SL+wsvvHDkkUf6VgYmp/WtwDtWWz/amr8cP/74412vIHPdddcdccQRPrLjtn366aePvetYtH747opt3qkcCysfffTRJ598svwbbrihWxBgLdZ70kknuV7dfffdHAm/wsfO37PWjF+XVuA/9NBD7ilnnXVW191TAnPXTPTGqSRx6623dt11I7x48sknfZXcieDq5y7fpV7UnNfeC3WaoCvDv5o1TdwDVr38d7/73Te/+c3rr79eL7EuZLecq/fee+8GG2xgBXrXF2dmuNP5V5ZGLDS24xEHzWISJ1BEDgbgPQSfvIkPThFoRFXHymgvLjzzzDMzzTTTzjvv/Mgjjxg6GpQ7vXVCy/qOjQaNZhJo32mnnbw9cs899wix23D3mWee2ZpOgUPHNlOrDBvDZ2tfiJytMhFW4zQfHLnvvvs23HBDVyqnc0Sexmrrxznr9szfJZdcMiis0elXv/pVT5ygwf0xdh2L1q9esTkIB4MWXwB1rfZRISOZrkAgrkUuvz4u/sUvfhFZ7Nu3OzwnrrdrrbUW+y+//HLRSSdgN95TtIXLhZPIgp6mMaMBlt/tuuuG8wI983FPjjz22GOccovvIi8GOq95YTSldw3/atY0cY+7iwGQL6dCFo2YffbZ41yNQx17ijo5BW/cA1xfpp56aiAyNR4gdKzNTRnGFw7OM888q6yyioFdeHfAAQdMN910vqkRnakphR0oHFdY65Auu+yybhVa0wPBp59++uCDD1599dUx3RDoQMubNcnVysnFNefaAgsswK+LLroIpzE40cpjxs2BYOHg2D5baxzX3M7feGtI3xZ317enmWYaVyo3YMJjvvWd1OLrwsy+hSnk6dUpmMw555yCRKAYY9exaP1yxfaZUldsfX699dZzofblTvEIp38XIeCjyHPNNRcXNBz7JRhf08k7+afP0XhVT9B9wQUX1N/cXLrungJznUdDuE2YycwLI8ALLrigu+4avNBP7N3NyyXxwgsv7CIvBjqvTSTzBSRHh381a5q4qxWspsr4XJnHSYcccshtt922xBJLyIxDnXxyhm0uKN11TWkKUnHZCN4oJWrlMmTMauQd50NTqjpTWNu5JLmdn3/++cssswx6h+5418JTZgZ3+OixKUi5Fh55wiDuaKj5gQ984IEHHuD+GO7ANRD1nKtdxQBq7G/8p9PWzcn85pdffln3Lies5hb8Ezkbq60fnjpz47t+EqAouIl9em5u7DrGrmPFwbhix4XLPfTcc89F2X2wDJWPnt8VCHT7Sepia3OWiZUYNXn00Y33FKeSS4fhn6GgO4UBcNddN3QkZ4EPbJsndumll7rodenVr+a8FpVwXnuDwgzY4bOypol7nJ+eYPrukuf4W2211Y477iim6zJU7jTlktRRCZa7BZpdpB+gQeZ8M28s8byCdrmGeraw7rrrCrcL12mdkl8kuzShEQ3BV1ttNbc37eimvsYaaxileEronB8DbnJBe3lo6zw3swuTcxUw32nllVe++OKL0ZoOP9eG368gME7O1sBKg9o8SNW+Z599NqqKRmj3uFLpBsstt9xYbX2Oc9bkkM0228yCBw8++KDYp9NZPrKOebiO4SJj7zpWThO9Pe5E3tIxchOPMIbRB1zNugUBZpu4yGANp8niClYc7OQEU5mHTt1+++3rr7++tDhXN95TOAJ/bx66PxrsccRdwxPa7rpuOOtZLty+3XbbCRALV3mo3nVecMFWPa9dw93BZbaElQ2FuLvEiPkfdthhbirmyThR8XiZcQL0Gty5OyM5rwiIbEkwOHpJ55o7JMuctHHe6vSaRqd/9tlnNRNlXdFGdZzWzTSZqc9manmsqSlNJOCUTYzBbP5qrK6Onq44ZM6Al73QOH2Vm046Eyeccdxkf9zpu8KRIRs5Hs7WAo6Byvbbb29a8zbbbOMZpshIXKlMfiMjkDZWW9/Jy3ef395///294Bi9HU3/9a9/HRMYXM3G2HWsNHok8C1MxRntIbbXxvbbbz/xCF827AoEXJC1oPYSpWa5QHWNdx3+M+w3Uwt3Z7/zzrjRSLJL7ymGHF7mPuecc8xcQtydON113QC7DoNber/WqNXMKw3UdV5En+97XosaG4cM/2o2xCisoIh3fpmlZ7ijfPrTnxb87/Dzs5hn/qiuICpQcsZYwkWHR+6FWKx9XJikY7LsGHCWL25s2tHIRGjKDY+b/PJw2T2ev2PAx3DBQ1tnmb7KZQmu2QSE3ObHjI/1HRnzZ2vV/Thz3bq0ta34Pk5a3/2M125sgYmbnAfl0twfk9ex0vTa3XnNd7PD3U8lBLC53F0I6LfmZrC8+NVdCfcR9utyHOnqe4rrBuRNcO/q64a2cH93p+teL/o9rzWNE9z5rptxbWisrAnirhqVuZSYO7XUUkvVnJNeKpp33nmN7UKs5mjn/CzmlUTn2JaWDAeBsdegxaOSGA4+3Vi2OF4S3ejF0GwuLpfE0PR0S6niZiTKz26xv+V2dikCXWp2ab6q/dV0EejwRLG5JDrc4PrmjQ0v6vs4hKM9E6Ea3GIMalGe3XbbbddddzVogKmyMXTYZ599fvWrX5lNVYaqDaodZTHWRo0lMcoGZHUjhMDYa9DiUUmMEHQdq7Y4XhIda2rLDSsul0TLq+gohcXNSJSfHWXkaBrTpQh0qdmlZav2V9NFoMMTxeaS6HCD65s3Nryo7+MQjjYdcbeCh6+BePsBQS/1IfEC/osvvvj000+fI6QCSyYSgUQgEUgEEoFEIBFIBBKBViHQBHFvVZWpJxFIBBKBRCARSAQSgUQgEUgEmkWgiakyoVpAPWLtHmEItMssOTHjvlkLUj4RSAQSgUQgEUgEEoFEIBFIBAZFoOnlIPF1b7vbJMx3twKUaTMlZ9D6UiARSAQSgUQgEUgEEoFEIBFIBIaAwFAi7ii7dbt818q3Ki0EaY3wtdZay6dwcnb7EBogiyQCiUAikAgkAolAIpAIJAKNINB0xD3myYi1+6zjJz7xCZ/p8uWCW2+9VWXV11UbqTtlEoFEIBFIBBKBRCARSAQSgUSgQQSajrjHvHZf5/I9P9909LUCn7b65Cc/qb441GDFKZYIJAKJQCKQCCQCiUAikAgkAo0jMPRVZXy60rqQjzzyyHLLLTf33HM3XmVKJgKJQCKQCCQCiUAikAgkAolAswg0PVXGRHZ1PPfcc6eeeqpvU5swc+aZZ1rcXWYcataClE8EEoFEIBFIBBKBRCARSAQSgUERaDri/u9//9saMueff75XVO+9994pp5xyjjnm+Pvf/+791Dg0aJUpkAgkAolAIpAIJAKJQCKQCCQCzSLQdMQdX1fH/PPPb56MVWU+/OEPP/DAA95PlRmHmrUg5ROBRCARSAQSgUQgEUgEEoFEYFAEmo640xjLPr700ksC7TPPPLNpM7kW5KBAp0AikAgkAolAIpAIJAKJQCIwHASaXlUmWPvbb7991llnPfbYYxNNNNFbb71lVRnrzFgOMheWGU5jZNlEIBFIBBKBRCARSAQSgURgIASaJu7YuTnupsccddRRP/7xj2eZZRbLy9irYLxNlYkxDMfjrdzx5v5AXSrzE4GhIVBOqDrFi0yGCeqglIcSgUQgEUgExioCQ5zj7oXURRZZ5OWXX3b7HKvQ8AtL+Mc//hG8vK+bwdT/9a9/SUS6r0zmJAKJQIMIOIkGOteKhpBJ1l4AyUQikAgkAonAuEKgaeIe6JjgPvHEE19//fVHH330YYcd9sQTT8gf9KbbLmTDsGJevz+LbWUoQuzVV1/93ve+98orrzha8qVDwzPPPPO1r31t/fXX33fffV977TWZkV9UZSIRSAQaQcCJY02qK6644i9/+Qv5fs+jyLzyyit9sNnm628DSTZSY8okAolAIpAIJALdiEDTU2ViFrvPpu655541DnfmBHcR8fe9r8dNsTrk4PXXX59qqqnip32E7oKUs78Ih4D8f/7zn4qHmMzYcAjajjzyyGmnnfa73/3uoYceeu2116655prE5L8jlX8TgUSgIQScNW+++aYT6kc/+pGpdxNMMIGT0dmqcJy8cca98cYbhx9++DbbbOPncccdt/TSS08zzTRxqKFqUigRSAQSgUQgEehyBJom7sXfBx988JxzzkFV11133Q9+8IMlv0MSbudY+B/+8IcLLrhAUPwzn/kMyn7SSSfZL7bYYiuttNJdd93105/+FC0QU59pppnM1xdf33TTTRdeeOHvf//7ZsjYm7tv5RwB9bvvvhtBNzuoyuDRiIUWWmj53g2/53hnDl06pEXSjESgXwTinBJB9xnm/fff//3vf//HP/7xFVZY4Re/+IUz10nnXI6CzkpsXo6pehtuuGEw+xwq94tqZiYCiUAikAiMSQSanioTN9Gnn376hz/8odD1dNNNh/L6CZ1yf207UixxO3/44YcvvfTSjTfe+KGHHsLXMXj0euuttz7iiCP++te/XnzxxRbDsQ79iSeeOMUUU9x///3L9G5//OMfcffVVltNSG/CCSc0C2jOOed0xAdi+VWl5r45dfzxx3/lK185+eSTxQjb7nUakAh0IwLBvBdffHGrym6xxRYf+chH7rnnHpPxXnjhhfnmm49HBGxO6g984AOLLrrorrvuahR9++23e0u+c6453Yh82pwIJAKJQCLQdQg0TdyFxzj51FNPvfjii5/61Kc8tn7++edjjnsc6hwI5p57btNXbrnlFhPQUXYGe0pwzDHHLLXUUox0yOR1t3/sXFhdDG/bbbfF4D2p32677bi2xx57oPuzzjqrtPifdHEt6LtMY4CPfvSjp59++qmnnupopyFQDM5EItCxCCDlbHMCmvey4IILLrHEEs8+++zll1/uOd4kk0xSqHkve3831i5S4IPNv/71ry1HG4S+Y11LwxKBRCARSAQSgdYi0DRxx1ndSsWk0d+vf/3r3/zmN91o43F2NRrdWiuHps1zgOmnn977o+bMIOhIwCqrrPLVr3415sUeeOCBVqA3WT/M9oDe4vSYt+2OO+548skn//znP/PUO7hIvwm4MdeWJTJtHtMffPDBRizbb7+9yTLWx3QoKMjQrM1SicB4RsA0GOejc9ZnmIXSzWpbcsklAeJ8tHfG2Tsr99tvP2F4lx2nc4e/Ez+eWzN9TwQSgUQgERghBJqe4x7c1F3Ty6miYswyX3yEjBumWmG5888/36I3Pu8qkiek5+0333lFESaddFLvlZo8I8RulouIu4A6coAxIPd77703uiDQjs1b8pLLqL+wfdgTCJDE6UXlReg9wf/Od77jKA3J3YfZall8fCLgbHL6eO3Eq96elXkFxTkLCieafZxWzlnM3osoxtJm1JhdUw6NT9DS60QgEUgEEoHxhsDgCyfXIBLcVLxZQNpUVEd9M9Ukk+r9taZIG3+i47fddptn7jPMMAMzHn300ccff9xIAw8wiVaY3GupSMDss88uzZEIq3sVlYOYgUPSnicQ9vjeAID79NjjGZNNNplp9BaFFAI0PbeNbmbVicAYQEBA3YlmFrvXxA2w559/fiNqA+Zg7U46I2Rn6M0332wg7aw0rh4DXqcLiUAikAgkAolA4wg0TdyFos0twYa/9a1vCWbj6yLTv/rVr6yvEpy+8bpHWrJqjzTLY3RRv95Sqm/CY3pUnhIzZyxNs8Yaa5TZQUWY8ni4Xw5FdWGATCxkIAEyNaVqTCVQI+NntAi1Bhv29TXUKMyfiUDHIqBveynFnBnPx/RtJH7zzTcXjK/Tw3tOj/89ifwsJ4iEnzUXgX5PxnIqRfGaIjJtdcwAab8yRW2/lnRsQ6RhiUAikAgkAp2DQNNTZcL0qaee2pIyVmtxK5JGZEXfvcdp5ok7VkTI2u5kMYNJjIm7r1hdma1etTDu7nKUqt7LORgFZe68887VItV0ta5+7+gEip4QqAGKgK2qs2+6RiY0FFZREn0LZk4i0C0IlPNCb/esLCahVY0P1usk6nu+1JwgSsmJ84Lavidmv5lKlSKleNWAvrVUj0a6X5mitq8lfTVkTiKQCCQCiUAi0BeBpl9ODRWmiX/oQx/ypcObbrpJ7Pmyyy476qijTBpx1L2wbzVtycG5r7vuultvvTVuooYWpsoU1u4R/DXXXHP11Vf7FqPn8m6lxXJpW/jiXuvxvQk2cpB+OuXzVFkEQhSQhnvvvTeE7dVl1o0ZutKxhVpKrE0Zeky/YQnJGgFH5RQz/lO+909REjIhRoO15G+44QaWaJEaS6rFM50IdDgCcbZaA0qvtlCV05bBur18fVu+i4xT1bnmTHRWltMn/CJp80DM2ed0iLL2clwErCxJ/s477/ShNDlRxF5m9WylQWa/lkSR3kr+p5aiqiT6yoRaApziWr+WlOKZSAQSgUQgEUgE6iEQt5kh7K2l6IZqdXNrsAyh+CgUQWpXXXVVn15yI3fXX2eddSzc7j4dVbuLW4hdplVxzjjjDJlu2DVWKSjHF5p+97vfSfDX3kzcHXbYYeWVV/79739vXQsrvltdRz5CYI9hbLbZZhtttNFVV13lJ53ovsQll1xiDr3FKNEI9RZLCNTUEvKKVLcaGXXJ8eKsCUtWpTRVCaEvlvR1pKoq04lAByLgbPXdpZ122sn59YUvfMGZe8opp4Sdlnv60pe+tMoqq1i+abfddpPZt4dHjpfRP/3pT0c6Tpm99tqLqs997nNWsBW8936LIXTRUHO2xqk3kCUU9q2lL5J9ZcISLwWxxFKzVrGsWhJH++rJnEQgEUgEEoFEoC8CTUfc3WaMA0SUTzjhhPPOO8/Xi3zJSDA77mr1hgijfkw43IpyvnsqxHXuued+4xvfQG1NmWWIm6tPLxl1WGfGVHXfVwINsfBCmow9sUMOOUSczFtxxfwLL7zQE3zue9og/7e//a1ZQ+WoDzktu+yybs8IeuiJQ0j/F7/4xS233NKK79h2sWSgWupbohRrVUG5IYH1cyx8aWXrqiXFpEwkAp2PgLPVENprJN499bK408rnEZw1LPcSqr7tvDMe9sHU8CVOnLgc2QvDewjmuwpOyTjvnCDm8rk0+Uqas8NZbCEs56ZloGgImX7P1oEsobBvLaHKhaK+JcbYrpMuGq4ARg6Wol9uueXCknAn94lAIpAIJAKJQCMINE3c44ZnboklVgSVt9pqK8s7xAyQRuobTZkw1V0/AmmYuph3UAH3YEdNmzF9xWu1lpnzM27M5Sm8nxaWxgPWXXddMT+Wu23bi3CL4ltE0jtzE000EfmoKFwzBhDdR6l9mooGW+S7r/vSk5+Eq5YoXlNLyFfnAyhVIxNqMYDJJ5/cp159TCpW2KhaEnpynwh0BQLlBPzLX/5iGp5T1QszsQarc8fp5iLjNBR0546zwyng3IlTMhxEjn141VlWzgKv33z729/23QZnOm1RKo7GGdTv2VrHEhX1raURS1wwfWTaJ5ZdMcwtjCLFzq5ooDQyEUgEEoFEoBMQaJq4x53S15diLqkPGJmu7VbEmepNtBN8Y4Nbo008LEJicefGA2S6dyL0lsdBBeIneSE6i9ObhxplUXOLRiMNJZwmf95550X0hQAFCB0Sn5Npo1wt55xzji/IGB6YVuurT2qhPAQiUWOJnzW1hHB9S6gKLzzrh//3v/99NeIxUTb3iUA3IhAnSMxBl9afY0pYnH3eqMHmnVBOGd4Ztcq57777pJ16ZNZbbz0rSApjk5EpB3GX45S0vqSHbwrGIUclCNScreUKNpAlrhg1tTRoCbFHHnlEgN9338yzVxFVMnNLBBKBRCARSASaQqBp4u6G564m0Ovb47/4xS+wWBO+rZIus9wUm7JgpIUZJggn5OZmid2iAhI4AWuRY3uPDorlZ5111u67744Nsypu3vZu8CGApvtp80Re5MxsWmKlLLVWr7OZ+/7Rj350l112wd2LnpKIMGHVkjhUZRVy+rWEjFocZUkkzJrdZ599uGAKb5jnaG6JQPci4AsJ0c89ZZLWz528aK5vJojE88sJaI+ye/nE5JOqp06r6vnokMGzGXFGtlSVE1k+sX7P1qq2fi0hUK3Fz0YscbnwyQin6tZbb42+hwHVujKdCCQCiUAikAg0gsAQl4N0CxTuOu6440zZFHL2ypc7kxtquWs2UvfoyLjLmkZiO/bYYzFp60B7VuDLrxav9JaYx+iYdLH8K1/5ype//OXgxPZBpjkrTcbsW88WvNWKLhi3mA8j6F71gloP+i+66CLvt4n8/fWvfy1UGzIRPsQGvKL64osvhiWGQIY9gVswklDYryUOUWiPptNv1GQpfW8aeERgSo/H8VVjMp0IdBcCTjSngAdWXkvF2p2Yzg7LyJhk4vIix9x3Hsm3N1vd2x19LzjBzp1rZrd7HugVF+csJU43D8ocLZg4E/ueraF8IEu8Q4J/01DV04glPttsno/3W66//nqz20N/sSQTiUAikAgkAolAgwg0HXF3y3GztJLMwQcfbHa71yIxSA9/ZVZvZg1WP6JiSEDMbVWLr0R5lxSfFvHyslos1+hWGl9ULYw5wntB3IttItl4P++8qIo98N0hU2W86yYQaO5sSBJALNZff/29997bY/Gf/exnqitKVGFKDM0sMQAolhgGRHVqsRX5gSwJYmGGj8HDxz72MZ+ZtOKNtXEQd+SmxvKiLROJQIcj4ASJl0CWXnppT5BwXGvL6O3G285WRNylxreKixcuOM7uOB1Kpp9OVWeBL0t4LGalVFcn75x87Wtfc6KFfJzs9gOdrQNZIk4R576q1VIqHdQSb6EwzMo2htkuApbHYWF1Ln5RlYlEIBFIBBKBRKA+Av+dgV1frhwNdm6SCdo633zzCUEJM3vHywuXDnUUcbRgpWXXLPBiRr6bq/uxPUewbXbaJOTU3PuLpyVBTNpdP8LnOARVisuUPu200zxz/8EPflDcJ1bVGT+tiXHBBRcI54u9FcliCVWlllJv30SRocHGJDKhH1OxCkeNJX01ZE4i0JkIxNm67bbbupiwUPeOUyxOOjk6f3Vk268XShHDiR1VsOckeUePUxJ3P+igg/bYY48ZZ5yxXA3i9Klqq2OJywWr6Cy1VAtW01UZwnGqFmNM4OlrSbV4phOBRCARSAQSgX4RaDri7r5lsx4iqip6RKm4O9YuIb/fOtqVKQJtbsyhhx7qflnu0xJuomGqRJVhD2QnMZujhN250QKae+PjE5jxYnnmqhL646dKqwoFC00u8nCfQORXLZFTaqmWqkkXGfaHSQRUR5WH/jWW1JTNn4lAJyMQZ+vhhx+O5rJTD48zRfd20tkGZe1RKli7tIKKlFOVQh+Je/rppwUaCg6q6Hu21rEkrhv2pZaiqiZRlYlTVV1RXKKvJTXF82cikAgkAolAItAvAs1F3N1y3EE9gL7yyivNHPXMF1/8wx/+IBETN+PO1G9No5/JWhFxN+a4N4+EAaoInjEoqxDYs7mFjxBEjVsyEjikzkRgmAiMwtka56BT1UWsjrWdY0kdI/NQIpAIJAKJwPhEoAniHs95TZIxYdQiiT534uVIb4B95CMfsb5KfPqn/h1xfEKcXicCiUAikAgkAolAIpAIJALDR6BnBkiDm0AUSUuXWKfFG5Y+RHL11Vf7wOEss8zSoIYUSwQSgUQgEUgEEoFEIBFIBBKBoSHQ9Kx0cXerHFoXxQprllfzaUNfLELiVR/Mfmh2jGYpdpavJo1mvaUuGNrKz9FPcL+NjaXqmF80+o5HjQww+BzPCMC/vU3QeNO3tq/yuoXtPn5sM8uoVbjF2dd4B6gv2dprae9p0bIPY3WybfVRzaOJQCLQyQg0EXGPaTDWT/TRHwukWEzNJdiaKq+//rpMHyn0syumyrDTBdoraO1qGAa0q+qol/uDzvQdUQvbjkB7B06wbS8CbXe/8d7V2r7aWtjTtsbbsUhqghZ2v9Y2aAsNa/k53lrbSnNkIhFIBLoOgSaIe7xV6RPiVijv188Reu2y37qGmdkVA4xh+lin+Dh3vw4yeajTEOjkvpq2dVpvSXsSgUQgERjzCDQ9VWbMI5IOJgLjBAHRylhopbVhy3GCXrqZCIw+Ahl3H33Ms8ZEoNMQaCLi7u4uwmRSu8+CmmjhZ+R4XjzXXHP5rmH8bK+HbBjUADKxDSo5QgJqpzn2I1RFfbX/8b8BrOrrGdrR9tbO5nFuAPeds3CwGHl1pVT59Ru0kwPM9S3Po4nAGEDAGdpFj7XHAODpQiLQmQg0TdyfffbZk046yaeXxOrcyF1H3njjDV8n7RDi3shLVC5/bQw0Ai1okw4xKFUaiU7DgHC/XcGbwL+NLDAM0ArtsmGUEVBdtLWzNb4kEB8h8pb5fffdd+2116622mq+oQaQ+rQAy68vMBLdNXUmAolAICBedvfdd88999wTTzxxYpIIJALjFoEmiHvcs81x/8lPftIvXp1wUy/fE+3XwshEYog1IllHyXAOBVBthCvcb6MBPozlJjQcDIdZVh8Y9OOXw6yifvHRQYCbWHs1rG45Hff+iy666I477njyySeRdW+Wr7nmmmQMY0a5S7CtPkqOkoltUMlGBFqoKm1rBPC+Mu+05+BN37ds3xzaZMa+79FmczpWG8Ncr4499tjf/e5355577vvf/3459eMO9Y82i0zKJwKJQOcg0ARxD6NdL7ABt/8TTjjhiSeecAV54YUXPvvZzyL08kf5xt85ODZlSdwemioyloTb7n4YYN+ue9vIIUCz01BvCbIe56NBwp133nnrrbdedtllDz/8MAYw22yz+W7arrvuuuCCCzqFo3eN8snL1PLoaaDurYFa+3SINnW1pN3HlW1aqlXni/6pFQZt+oG6RDVfExQ9wz+nokHpZ15LtLXKNvY4SY20v/e97+23336+dWgd0vpnK1/aGJmqtlGmE4FEoOUINE3cXXZxguuvvx53n2+++VybPLmTbrllqTARSAQaRADPsDk33a1LfN230i655BJfSXvggQe8mmL91pVWWumLX/wiyj7ZZJMVzQpKu9OXnNFJqLGRpy4tfzrUSKUNIjB+bEMTS79qEJyBxHq76v+1qhWCv9ZnsQNZ0jc/Br2torwtsQ1csHrzzTd32GGHnXbaaZ111mFkG9cy7gta5iQCicAoI9A0cWefS8nkk08ubrfJJpt4bPfoo49ON910kT/K1md1icC4RcBpGDwDo0KCbYiCjyrccsstyLrPor3yyiszzTSTyeu77777xz72sSpZf/vtt+EmjBcFxxWGcON1Z7rcsbYxrFW20dNC8FurrYWGUTV822gQbndeb7/99h6O7bbbbk75ju29rUUvtSUCicBACDRN3CPusvjii4u1i0x4SxWJX2qppVTQqpDMQLZmfiKQCEDA7dz92+lWzjjB9fPPP//KK68UXDcx5qMf/ejnP/95e0/DqoghAX7iAVEwGUAVnEwnAp2GgNPcTfaHP/zhSy+9dNZZZ3my3d43czoNn7QnERifCDRN3F078Aaz2x966CHP3D18P+yww5555hkrQrrKxMPB8Qllep0IjBwCQdZRbaeYfTDvm2666ZprrkHZX3zxxVlmmWWxxRbbcccdF1100fKs3ympIPnYCtEfOTtTcyKQCLQEAcNsJ+xxvZtPlXs+9re//a0lmlNJIpAIdDUCzRH3IAHHH3/8hRdeeP/9999zzz3i7vYrrrhiV6OQxicCHYsA8m3DxYN2C6hbwPHss8/2sqnJMB/60Ie22WabJZdcct555y0ukI9TNQfSBZNMJAJdhECw9htvvPHb3/72Mccc4wUV09ty4N1FLZimJgIjh0BzxF3czosym266qafw9957r4mzLiWzzjpr2DeiLCGISFRUTY8cNKk5EWgXAno48u10c07FZvL6ddddd84552DtVnFeaKGFdtlll5VXXtlctTAyyDrhKNUuy7PeRCARGCYCzmU3VvPfPvWpT+25557LLrts5AxTbRZPBBKBsYFAc8Q9fPb1FrzB9BhryspZfvnlN95445Ej065Z1sSwBpa61CLtY09VmmJtrHzLPpom992OgB4u2Fbi6/q2NddNb73rrrv0+Y9//OO//OUvvVJS1nCsUvxu9z3tTwQSAac5EJz4W221leUftt1223idLJFJBBKBRCAQaJq4YxVCemjEvvvue8ABB2AYFpjzmH7hhRd2xRHwayGySImJAWeeeaZBArKyxBJL+GirZeNXX3316aef3roZG2200VVXXWXmn08/trDeVJUIjCYCQb7VKMzm5HJOeSxuZZjTTz9dlN2Q1bvgv/rVr/T/cn65l0dwnXw+QB/Nxsq6EoERRcDVwBntZZVpppnGtw7dVfMEH1HAU3ki0HUINE3c4yJib3NNQSBcaEbCbWqREpTdknYm55x88skzzjijdScFIdB3TN379b7Z7nni+uuvH8INmkGtrUHhkRBrb+086gWgbQi0t/bifhtboYpAnD7OpuhpvpBw4okn3nzzzd4C18k91FpmmWVKJyRsQ9mR+5I5hEQbfR+CtVkkERgnCERw/Uc/+tF9993nUZuTvXqtGCcgpJuJQCJQH4Embv9xEfElCFx5gQUW8D2I3/72t7Rvt912wu3BJ+pX1tTR4BY+8TjnnHM+++yz5ta/8cYb0liLWfXMsJLGwQcf/IUvfKE6T8aFL54J1KnLeAMrKlSpjuQIHWIhzW00gPvgLeHbEXJzILW6imbSCgMJjHQ+AyCglnbx1+iBRp62aIXbbrvN4jCmxHjEZFmY7373u8stt5y57Ixkqg5DrIXWqoVmODQFtdFCu/pMU3amcCLQjQg4zZ1if/rTnywkYxkZr684Q1t41ncjJmlzIpAI9EWgCeKObeCaJsnstdde4t+i4LaicSSuLy5basTXcZq1117bJBnVxbXMNQ5xR3Esh+cQ25JSlLbIRMcioPdGX51iiikY+fzzz3t85JXTp59+Wmf+1re+ha9/4AMfcMjYxhww8jp2G8d4Q0CynIwScbZyITL9tOWpOgRUs8jYRsAJ4jT3KQbh9qOPPlrEyj2uu078sd1A6V0i0DkINEHcw2hXE4vQubJg6i4r9ta7WGONNVxo3JJbTt+FGy09ac7ADDPMIMruK62C7k899dT8888/zzzzqFfQ/eGHH5aO2kUsbPXx7eEO//d/gp31xUbuqGs05W2kLxrRY4qWN1bjiOk5gzZT49qGJll9UDM0DU2VCuYaRXQ/z8FRdguxO3E22GCDzTbbzJTWOBqSvR15kJ7clAFV4Wj6Vn12vqpZunTskiiZ6o2qa4rkz0RgPCMQp7wb2Wc+85mf//znSy+9dLL28dwf0vdEoD4CQ2QG7r7uyi4u9rb6dQztaFzLLDp52WWX+d7TzDPPvOGGGyI6++2335prrhmhCATIOhte45tjjjkaD0700PYmJwkMzYWBSrW3dlb1AtD6UdZA/tbkR+01maP5MwywHwUSqRY9WeeM08SY88gjj7zkkksMd9dZZx3DTiurhu8h2Xs+jcgJVUVYXdWfrU3zzrx86954LucjD96pdZJadV6mgbe3VjxVaG2NqS0R6F4EnIzOeu9rGb1/7nOf22KLLWKme/d6lJYnAonAiCLQNHFHQSxzYaWqvma1lgYF0fnwhz/805/+9K233hIfFSPffPPNX331VQYgQ+KUahRr93EKVrW29r7eZU4i0DgCwcL1Sd1Y59RdPTj685//jMguuOCCX/nKVzwsiinsDsWdmzDJxqvoNEleGMmbuoavo+ZmuBmc7LbbbhB4+eWX8XWeWgPK2vMkGZ8nbKe1YNoz+gg4KVTqwTK+7jPk3/jGNzLWPvqtkDUmAt2FQBPEPZi0Fdz33ntvF5fqfVe6+rOFEJgwMFnvFjrVgrUH0Ykc6RF64t9CL1LVuELAzVhHDRZuFvsRRxxx3nnnmbBuQaTvf//7H/zgB6HhDLJJdDVZrzYrlzluZViT9a1C7cT0Tvmpp55q8VajbifyKaecssIKK1Tn1AVrqSrpm6anEbG+BfvNocrWqovVuLINaC3BDf4txI02Dd0Sw+hhmH3o7Lf/NJXZoG1urGbI+DiJFZbF2v1kRlhSrS5yGrStt63atm5Y1exMJwKJQMsRaIK4x8XRq+5zzz13y+1oSmH1Ml1NN6UkhROB1iLgnurmiojHEFfsGWX30fIPfehDX/3qV9dbb73g6MHXCY+9ASd2bkob12ymynh5nY9XXHHFiiuueMcdd6AmHp0VzOGA35ef/Sac3SHTqtMcMbK1RNu4sk1j6dUtwU3f0AR9iWm/HaB+JnvK6Hf4CmmL1ZZY2BJtdWxTlyoITD755F/72teefPJJw1q1QyaIe43jzdpGSflGW42q/JkIJALdjkATxD1cdbmxBTXpdufT/kSgJQg4I9yD0Vba3Hqt5nbCCSeYzm69I9NjPKSKWsi4AaPv5JGDllTdUUp6Lg3vLINjeoyHY94pf+yxx8zfNefN95X3339/r6PEOndw8A3mRuxHQeDWiOSgMlonmmlQyQYFxoltum4MOxuEpY6YHmJmSKteDY/zqFX3o+gbrRpR17ctIPXKlndCzKPzbjpk6sDSWtvqNFAeSgQSgQ5HoGni7g7aqptoh0OT5iUCgyLg7os0OCPcVjH1Y445xlox1nNEUn3fIIhp8HViraI+g1rVRgFQCKtz2Qx+82R84ZjjvpsmcO6QWTSnnXballtu2TjT6hkKtO414tQ2tL7RQtxC1dDM6FuKtr6ZQ84ZNW3B2o3wf/Ob35xxxhlOkMipY3lrbatTUR5KBBKBDkegaeLe4f6keYnA6CAQ4bTg4l45/eMf/2gNZvPXf/azn1m9NGyoyoyOVe2tJei4t8axdrFDqz89+OCD3kbF2s2WwTyWXXZZ3z9mZA7+29tSWXsbEYjHPgLt3/zmNz2a8zBqUNbeRmuz6kQgEeg0BJK4d1qLpD0djQD2iY7j60FSkfUDDzzQ98mXX355s2Lcg8P6uBM3HlfuaJ8bNi7o+FxzzRUlZundpJF4SQkC3l5tWF8KJgJjDYFg7VZH9enxP/zhD5Zsb/n0rbEGWfqTCCQC/4tAEvf/xSN/JQIDIxB0PKLsHnAfeuih3irzCqZvppi6rVzQenx9PMyKGQgnA5sYsZRBTiATtL4cHah45icCYxUBFxBz6ozzLf7oC6m+5BA5Y9Xf9CsRSARGAoEk7iOBauocUwgUAoqO453WKT/ggAMsAeHuax03r1ry1g0YW8VNxzNlj1YvzxmqaARrJ1COjqkuks4kAoMhEE/qrA/rHY8vfelLn/rUpzLWPhhmeTwRSAT6QWCsEXf8Cc3qx9FKlgsoMRfNSt6oJtWuvkHtHDmbwv12USiOA78wuZFzcyDNYQCGPagNJPUWQTLClsL405/+ZD4M9D772c9i7d49dTReuwRmNOtAlVbz245AdP5mOwD5ZotUvc50IjBuEXChcO5YXsnHHNZdd13rw7pc5CB/3PaHdDwRGA4CY424N0Is0DVibb9ottGAcL8RrIbTtwYqi7ba2uh+1M6AOsSdjHttLAzn20lHHnnkQQcd5FNgO+200yc+8YlwDf2lxAd9B/J0oPwe/9uKQIDfbBPUgWsgTzM/EUgEgrVbbcmlY5FFFvEtcDnNnn0JYyKQCCQCgcBYI+6NcAsysbWrE6hd1bFviw3/8b9Fa2MPwYX24h/g17EhbrQGNhKHHHKI7ygJrn/nO9+xXko4K1rmaKysPAT3iwFDKzv8UtH3Yj98bakhEUgEBkLAED2uJFtvvbVlH3//+9/H1WMg+cxPBBKBRKA+AmONuNf3No8mAlUEegPf//2amJ8RCYsb7dFHH+2DQT5t+I1vfMO67FEwOH1Gy6owZjoRSAT6RcAlRb69Ge0uHS4p8TPHzP3ClZmJQCLQCAJJ3BtBKWXGIALiXkLm7qDYuscfbq7SwciPPfZYK7X5+a1vfatQ9oiT4fRjEIt0KRFIBFqNQLB2lxGvxHgn9fTTT5djy2tIq5FOfYnA+EIgiftot7e4iy2v3aON+//W5/aJtf/t7/966aWXZ5l5egfdX+3POeecvffeG0f/whe+4NG2nN5bbc+9NqPs/wth/koEEoF6CLh0eElm5513fuCBB84//3xfJUvWXg+vPJYIJAKNIZDEvTGcWiQVlB0LtERJEMHCC9UwEmk1oqTBSkchXQYk1cFJSYeDYcwIOQvGsKGOsw65if7pz0edffKhE77n7QmnmPPr3/7x66+9sueeez777LNf/OIXPdeO+esZZW9Rx081icA4QsDFjbdYu9Vjbr755nPPPdcFx8UkB//jqBOkq4nAiCGQxH3EoO2j2NUcpxR6mWKKKZZZZpk43kuqe2K9tpFIFyZNfzVdfbGymj+i6ZFwsKqzQeOJHXvs8Uf8+nOrLPz/Jpzwfc+8eOOm610y+TTzbLLJRrvsssv73/9+WMVgI2+0Pf0yt0QgEWgYAdd5Vw+Xjm9/+9tXX331eeedN+WUU8rMi0nDEKZgIpAI1EOgOybsug6GExLiFvEz9nGVrOdiZxxjLYppmqP1v2177bVX2P/000+bUR3raj/++OPHH3985D/88MMnnngi75jvSauP/oQfd99996mnnhrp22677eyzz470DTfccMEFF0T6qquuuuyyyyJ9ySWXXHPNNZE2Zrjxxhul3UJYcscdd0T+Kaeccu+990b6pJNOUp00M0444YRHH31UGubHHXfcE088Ic1UBj/zzDPSnht43eqFF16QtmaiNc5ffvllaQufWfL8tddek37llVeOOuqoN998U5qksiQNGzjO2XBcLeoNZ++//372ELbdeeed7Iz0LbfccuaZZ0aas4JYkebdRRddFOnLL7+8OH7xxRe7a0Y+x6+//vpIn3HG6bfccusF5568zPz/nHKKyf7173ctMNeUc0zx4he/tLMZ7RNNNBFnWVIdA0TB3LccATjnlgiMPQRcYPfYYw+U3WVqmmmmiavcKLvZ8rM1FSYCiUCHINAdEffCokoCfJGuBlw7BNM6Ztxzzz3orE/2oKSu5pYAf/3113HxTTfdVKlXX32VAMbMNZ/qkA5VL730UiHWL774oi9mR/5zzz334IMPRhoP9v5TpJ988klVRPqxxx6LT3v6+dBDD80222wS9GPnljgMGQqtUxZpFc0666yRZsC8884711xzueUw8sMf/rB85t11112LL764NI7LkWWXXbakV111VWlfFTUqWHvttaXD2fXWW08aoVd2/fXXx4/D8Xj1M5wNEKrOIvps23DDDZU1iaXqLH9l2jgbIwRpIx+m9ma/y2CA48stt5yfRkEzzjijBIMfeujhKaacGmV/91/+7+23//Gvf/2/d7/nvVNO/q7/e9e7g7JXn0WEqtyPBAJaKghNHeXObo1ii9FsHckGD1FFktoG5euIjSvbtJT2aglumlIrDNr0dZAvh9hT9JQTvxxtNhENqhTzhqZNKd55ZGfpWJRd0GHaaad1AXS9LXY2a1XIN2sb+byODQ3qLJUIdD4CPYtpdL6VwsbmlrggCjxjk0ssscTHP/7xW2+9VSZ+Jvob/KxBR1xbBX0LbW2w1DDFAmfX0x//+MdYsonUw1Q4nOLi34XND0fPkMsK1Q/hu0VDri4Kuh/H0+rTTz/tS1/+8qIzPr32MlO9693vefX1v116zwf2PfiChRdesMgMs676xXUGN/L4ulN9yRE6Cn+aR78JhuCOwZ4TP0bpQyheU8SQsoWwjx/bWnhe6Py4bExIq2mdIfyMEV2ruscwzwvGsOQHP/jBGWecIdw+wwwztPBCN0zbhoBtFkkEEoHORKCjI+4u8W4Y5kLg66j5G2+8IUy72267uTiakoGvu1CaFrLyyisXWtyZKLMKZQ/bvv/970sUAsFyXgShHEJakbhpVW9gg6YZwwAhmbAKyJQMOR3Gc6p6d6+TjrpGzVkVBUtm50033fS9733P7J299tr7lpuuO++GY9//7tfefM/cn/vaj7B2ksWXaKzcjz0EtHI5GTvNu461jWGtso2eFsLeWm1DNowZcRk3QwZrtzhVsPa8ngwZ0iyYCCQCAyHQ0cTd/dXV0GyNRRddVJDGxdF8CTO8V199dXMt8E6ToVdYYQXTPxyKm7GEbSBvI59OMsFu60uOxFFVI7XhWugfTpqGqiMNptmgUnsbDcNMl0obd0QRVTcuXxqi1NWg4yi7e6cgqylGP/zhDz262WGHHTzumGyyybb65Cevu37bF154cZFFFp5j9llprtpTahyJBN9VZxsJ5Y3ojHZv1gD42BrRnzKJwPhBwNlkc5357ne/a4aMd42w9mrkYvxAkZ4mAonAKCDQ0cSd/9j5zDPP3EtyeuYOmgaNhF1xxRUrrriiWdTe1ve0ugqT54mumNWcvmkX2Zh3KNH36EjnoD5hoQt9uwzgPjfbRcJ4DYEAYYTQ5po+oyIE3bQonxk/7LDDzMX3eqtx4Ntvv/2Xv/zFAm1LL7UEA0y49TAnHlyMkD01akcBgZoaqz+B43mLnICoeqh+2tSanDhbH6I8Ot4QcC47j1zMvdruLXmrBWDtkTOil7jxhnP6mwgkAgWBTifuLos2pMqV0fSYqaaaymXRC5deZ/SupFcbfZR+jjnmMGObGEYiEl98GygRCvG2gQRGOt9lXRWjyRT7emQU1C7izhiB8BGlgBAOeIXYrc6u8xx88MHxIoRDMWdaV+ltCL3rvfh9X4hGNGekEahvfIDfwtne9avLo4nAmEQgbjouL1/72tdM2rR6lbdR8XU5Y9LfdCoRSAQ6AYFOJ+4wwi+F1V0NUW3zZKaffnqczPudwsYOmUVz2mmnbbnllo3zYFdbWxvRb2/tHO8F4D+Ti0Yfh6h9hOqNu6bO8NRTT3lLzPKXJsbYVOeQfFsYYC89QmbUVzuiCNSvOo4yoBGxlEkEEoGBECgn0U477WRlXm+jTj311GIBydoHQizzE4FEoCUIdDpxD2q1wQYbYO1CpGuuuaY1Ab2NirWbLePSaf5DrPTXxvhxS1oilQwTAZ2h3DX322+/P/zhDyuttJIY2EwzzURzhsGGCW8WTwQSgYKAS03cmz7zmc9YbRZr91m9vMgUfDKRCCQCI4dApxP3oOOWEg8IZundpJF4SQkCZi2PHECpuSsQiFumWJcQuw8WIvEHHnigoR3jy6GucCSNTAQSgQ5HIFi796k+9alPmbTphVRxpRI16HDj07xEIBHodgTaM1WgWdRcE6MIQoaHlXQkytFm1ab8GECgBNrNp/r617++3Xbb+cCTt8Swdh3Dlk+ux0ArpwuJQIcg4AYk1u5qY6UED359ZQlrj8wOsTDNSAQSgbGNQHcQ9zIXWXy98LAyN6YcHdtNld7VIBCjON1AB/Dyg3dPLe3vmfVXv/pVOSi7va2mVP5MBBKBRGBoCMTjO2tS+RS0Ge3WI/bs14Wo3JWGpjZLJQKJQCLQOAKdPlWmcU9Sclwh4GbJX/dLL6GaG3P33Xf79Mkmm2wiM6JfSdnb1R9iyKR2icJpItNPWzZNu5om6x0OAsHarWm2+eabCxP85je/0aspzP48HFSzbCKQCDSLQMYjm0Us5duMAObnDirQbjvkkEPWWGMNS7BdeeWVWHthig612cpxXH3hMRIlEhmZ2qUcHccIpevdh0B8yu2ee+5Zd911N9poI6zdhSj7c/c1ZFqcCHQ/Akncu78Nx5MHEeJCB++//35z2Q899NCDDjrITdRC7BFoT8re9u5g7fz4LNq1115r+Xwft3r99devv/56hj366KNXX3112y1MAxKBphCIry5cfvnlZsh8+ctf9oXUuBDl1aYpGFM4EUgEWoJAEveWwJhKRhyBCLSL17pZ7rvvvlYIXXzxxa+55prll18eZXe0BHdH3JSsoD8ENAF+46vGJ598srZ46aWXnnzyyY9//OPnnHOOfGlcx0dqZp99dpK2/nRkXiLQWQjoqPqtD5Z5i8YaMnvvvbePQmSMoLMaKa1JBMYZAuNxjjvmZ2tjQ7e3do73AtA2BIZQu3tnzLu44447dtttNz9POOGERRZZhC/SzVL2MKCNrTAEBFrbXUfCdzq1hbVZfRPtn//8J+JuZDXPPPM8/vjjgu7e4fMm3worrDDbbLMhQ2EA+UH9CuY0qFiDAmq0tcr9cWUb0FqCG/xbiBttmr4lhtHDMPvQWXqUK4+1Zffaa68jjjjCJ0T0bRecGpkiXE2Mgm3V6qrp3rZq2xW+akmmE4FEoOUIjDXi7loZF986SJERMrHVkRnRQ1F1s3SzhSYxQBC0XbONNZDa69xrowVDQFp7TTjhhO6X++yzj3vnpz/9aW+jOmotNhhKNNuUYUCUbSGqjasaFIHGVQ1NEv4KNtsByNdpNQoFJmeeeeZojrfffnvKKaeUtlietrvzzjtNZ4opNGGzQ1qwvv3RymTq11tfSfUox20t0TaubNNYg7Z+Fec6aaezJohzvI5YI4c0QXQ25/LwFdKmo6qXhfbh8iSTTPK1r33Nd9xECpZcckmTvtTViP0jZ1sjnmqs97///Y1gmDKJQCLQdQiMNeLedQ2QBlcRcE/69//7fxO8r6dbBsFy/8PafVF81113dTc66aSTFl54YfdUG5pYLZvptiOg+WyYDUsmn3zyV199dc4557R23hxzzDHffPNtttlm+++/v/Skk04aYlhRIzajILpBI5KDyuhUre0248Q2p1s066AIDyqg6X26yBOYQSUbEQiS7crQiPCgMtE3JphgAkbqcpRvvfXWTz/9tO9C+AAzEPTqQZUUgRGyrejPRCKQCIxPBMYa9WnkCk7G/btV96Eh9JtgIY2YOgTljRThu1tUv2TIzUZ+v4ca0dy4zED465H/+mdPIHbCCXtu7e6gHlJ7x3HHHXc0SUZOcIiBijdoQCfw/mG60KCn/YoFQRkJA/QcYXWRyxlmmMF8d2vnoekIuhyHzKI57bTTttxyy8Y7vw5ga1WHTG399odBM1uIW6gatMYGBWhrULIRsdAWV5gXX3xxiy220I19GsLwzIWx2fNlJGxrxIuUSQQSgbGNwFgj7o20VmvvHI3UWCPT2gt6jfJGfgYCfcmQm1MwKgKOhp0hViX0w0yzMDRX9cTN8v/+37/32mffa2+7l8BKH1vk4yuv+M1vfZuYN8MWWmghBUOsER/ryFAeW18E6pRq4aGovYUKm1XFgGaLNCIfncd7w5i6kOqaa675wAMPrLTSSn/729/sVbrsssvOOOOMVLUL+Ua8SJnxjIArjEd83qXZZpttVlttNe/BQ8MlqPGh5nhGL31PBBKBUUCgNU8YR8HQrGKkEcCr3JwsiG6lxWDt9rao16FWpcstsKozolk/3PNnB55/zxvzrPvaXGv/8eIHPr7mupYl8Zwaa/eQhCXNBr1GGrTUX0Ugeshcc80VEyHMLgi+LmA5yyyzOKrFvb2ajVgFLdMdgoALIILulYyzzz570003/fznP4+1y7SVS1aHmJpmJAKJwHhGIIn7eG79//oewe8zzzzT4ujmIt91112O3XjjjTfffHMIWZPb+4WRRu7vvffeSFu0+6GHHoo0hm1qhLRb3QUXXGAFQGmavdr1zDPPSItmnXvuuc8995ypGoi4hQJNgJZvzuu555330P33nHbZrYuus52jE04wwVzLbDD7wst87as7EyAcszukc+twBLR4WKgbaPFg89KRWY52uBdp3rhCIC6ARpi//OUvvY263377Wa9d7wVCCViMK0DS2UQgEehYBJK4d2zTjJ5hhVT5wogXCrH2W2+91e3qlltu8cg47LjpppvuvvvuSCPxpkBE2jzmRx55JNKXXXaZtf8ifemllz711FPSlF988cXIurQbIXJv8mikkfuXX35ZGnE//7zzX3zxhck/MM0///X//vbWG//4+9sTTzLpv989wVNPPkEgY7RA6JathCd1odJwhf2Uo93iTto55hFwXdItvYbxhS984bjjjvMaxlprrSVYoPeWfjvmQUgHE4FEoFsQ+M885m4xtyV2Cq6YdNvgihYtqbFGSQRyCqepOToKP70+KLZUpVDB3d2rLN5i7W17KFUFWmuVe6SlG0Knqm3qevqpJxb+2Mpzr//V2eZfxM9nHrp7iqcvP/v4I97X+5ZqCw1QnYUITedo112ZAaAuCLTQtQZVGSmRNJe3Qfk2ivXtq8MxRsfz6KZV7T5+bGshi3Vh0f1cf4bTjqXs8K+lXNMlnn32Wd9Xkjj66KM/8IEPRGapZWiJ4dtWrbeLztmq2ZlOBBKBliPQHS+nIjpxr5Vw3Q/KG5n2QGnVnbjl+HaLwgAQlfz973/PZqiizqCWH4damC6Y0GkLInXiiSf+9Kc/3WjNFZ99+aa7L7pH7dP/+7mf/vjbWDsZP0upTCQCiUAiMHwEXOVsrj8+wPy5z33OS9U///nPXW0ic/j6U0MikAgkAiOBQBcQd5fR4I78l8DaIycyy6GRQGe86QRsuByoVulyC9OllmDtwpYmlV599dW/+MUv1l133Zf+8perr7yMGcuvuPLU00xLuFp1mJf7RCARSASGg0C5iRx00EH4+k9+8hNLtnsgI0zeqqcBwzEvyyYCiUAiMBACnU7c4/L6/PPPTzXVVOY2eKDpVUgfTjfXxfRoy1agfS+88IKFLAbyMPMbR2DURkHujqL7Yl1XXXXVV7/61Q996EOm10899dT/+ue/ppl22g023ixszlh7422XkolAItAgAq4/AkBuIi4+119/fXwVVWZecBoEMMUSgUSgjQh09AwErN1mAROxWJfUN954I15n9IKjD6qjeoimr2Mg7hAk2UYcs+rGESgxrR/84Afbb7+91RuOOuqoHtZusukE79PQEra8iTYOaUomAolAIwi4TQRr90r96quv7kV5r84vueSSLjio/KhFLhoxNWUSgUQgEegXgY4m7i6j3sh58803Z511VhdcSwf68uKGG24oyu7lwmmnndaaJ75st9RSSzna+DWXZOPC/aI2zMxxa0AMrgTaLVCz6qqr3nDDDVaK/PSnP42jg1S+vYkxEraRmyET+LexD4zbDjDMEyeLJwLDQQBlVxxB90E368b4QNjJJ58sZOD644IzHM1ZNhFIBBKBUUOg069WJlQsscQSVid0bbVS4ZRTTimBsou4W1bcRItddtmlChZCH1fnamZNGn0kJjN4ZM3Rkf6JtJX7R7sMgB4YR4G5qoWPKsLCpU120qDWSP7d735nRukee+zh6Ouvv+5WOtKwV/WrNCazVjNHM80AfaBdXEFzcJ+/oowsadxxq9C0y+bGjUzJRKBfBJxxcZ359re/ffrpp7sKIe4uSoRHLkbQryWZmQgkAonAcBDodOLON9wi6AXah2q4yKLdyMcUU0yxxRZbWHN3hx12KBDgFiFccvom4mJNW99Do5NTiPvoVNe3luDQI3q70gpVOu6nJvOKgkmlDz/88JFHHrnssstGQ0w66aR9LRzRHMbwXVdh0ohWNJByBujJxjADCYx0fjR9swa0C66RRiP1j20EnG42l6NHH33USu06v8mWPuVbqPzYdj+9SwQSgTGGQBcQd3TBW0QustNNN50LrsuuiYnmzCDuptDY+3jnKqusggU6RNg2aCORCe4yqORICLiLUNtGA8L9kTbAOwne+nr66acXW2wxwS1vI4h1rbzyyoceeuhkk03Wxrsm/AOBRrrKCHUA4I80/nUsD8fbaEDYFidCHTsdIhNbfbEGj7ZQVdrWIOY1Yu+0ZxOPemo0VH/S5mfsq/kl7b6AsuvwFpz97ne/+8lPfvKHP/yhnzGpvabgoNqK2kYS7dXWrotbI8ikTCKQCAwHgU4n7nH1WWCBBZCMaaaZZrbZZrvwwgvNsnBNlLb3gpEPeWKB+RB/OP2ghWVjBPXMM89Y5NHIas455zzjjDP23Xff1157zduom2++ubo8M2njE48WOpuqhoyAkxd5ql/c6e/UtsXDmfrCjRylilhLOM24sk1Laa+W4KYptcKgTd9Ia7Kn6GFeTRE56rK2o5mBu+22m288/+pXv1p//fXjS0bVslEwGlSaeX211Sgf9GdVf0u0Rddt0Da15w1x0DZKgUSgSxHIL6e2oeHiElydSTLKRrT2i481xrtLuW387Gc/w8633HJLq3bydK+99tpss8222morN1pjMAg0O0+jppbh/GRhjBzYORw9Qy7LADi0EYEu+gpja/uqyf0thH382OaEbdX1Ks6+Vq2VHiO6vs+O1OL0dILfcsstX/rSl0QQfFrOSgb1HWnteTGQbUO7brTWtqHZkKUSgUSgExDo6FVlCkBxBfRTIlhvpO1doMvRIp+JNiLgZokWWwJokUUWMan9pZdewpZWWmklE5y0lKO2NpqXVY9zBILSdSYIHWsbw1plW6v0RAv22lUba3ePiOuMELu5MTbzZLB2159WDT8a6T/92tZIwZRJBBKBRKAOAp0+VSZMLwGVkpAf6bhA1/EwD40mAu5V7o6mwdjuv//+NdZYQ4DTKkDSuLsmy1HWaDZH1pUIjCsE4vqDnT/22GM777zzK6+8YsHHhRZaKDh09fYxrmBJZxOBRGAsIdAdxH0sIT6GfYnH0O6abpZnnnmm79paucXeHHevF6+33npun+6d9mMYhHQtEUgE2oJAuf4cccQRP//5zzfddFMT9lgS+fmgry2NkpUmAolAyxFI4t5ySMepQpO2vQ5lkoz3wC677LJf//rXM8444ymnnGINfiuvWU/Gso9J2cdp50i3E4GRRCAC6kIG8U68BWctXbX88surM1j7SFaeuhOBRCARGFUEkriPKtxjsjKzX8TRsXZfQvUe2Lzzznv55ZdbAoizCy+8cByVdnPNoNeY7ADpVCLQLgRcVVxhUHbXlqOPPvonP/mJlWdF3L38irK7LjnULtuy3kQgEUgERgKBJO4jgeo40lkCWp5NH3744V//+tc///nP819+vH7g3unOGulxhEu6mggkAiOMQDzBMx/vySeftPisee0HHHCAb3qotlyXRtiEVJ8IJAKJwGgjkMR9tBEfM/UFHRfQ8mD6y1/+skkyPiRuxf2SXzzF3Us6E4lAIpAINItARNaVEkO3KlUJtHvQh6zvt99+Fmg/6qijvBOfgfZmsU35RCAR6C4ExhpxjxhM/TYgE1t9sZE7qnbKYz9ytdTR/B//h/GSaDyeVoWn0j/96U8tuPb973/fTdRM93g2Xce74ddex7VGDqUB0Tp12qhfGHOmU7+wZOZII+BqUya96LS+x+UiY7vjjju++c1v+kLzYYcdtswyyzAjA+0j3RapPxFIBNqOwFgj7i7cg9KR3ks/wcElR6J5sB/sNjQPauoIGdDj/FC/Rslmm8iWldq/8pWvPPDAAyJevl9rsXZBd/fX4t1Axiuu9jaywDCAne2yob0I8Br+WseeJQM1U998VGncPjwpQLWrz/RtjnGSA3m97q23/nbjTbdMPvlki330I/ohsu6bbieddJKvaHvxXY7OXMj9OEEm3UwEEoHxicBYI+6CvoM2pPgNsUYkB1U1NIFgP23kQOH+EAxwEw3ics455+y+++5LLbXUxRdfPOWUU7prNvVBytZ+wHIIraAPmBo7hIKtKtJeBLjPkZE+BdQSHUZPk7b30zaEjtcq2Iemh82Fr4cj9FSHPcEaQ2aYaRyUHjWqSFpFzaYD9vA00qGnJk0gGkL+oGlOsSr0RDrKDsHZMMxe2UEdJKOXXnvdDfv87Bvveu2Of/6/98/z0U2WXm7l3/x6Xx9UsuysuXlkbKGqKM9EIpAIJAJjFYGeO8RY9W0gv9yoLCs+ySSTDCQw0vluM6po451mCJ9qL+xB2e985zsXXnjhD37wgy222IIj8GyKilEl2t0U0W9tizDAwwEPDQoba63+QbW1HYEu+nz6EPpqHfyNlxDBptpdY5H3DeBf/vKX3/3ud6ebbrrIUYsT2aGmOn8d21rLPt98882JJ564VbbVMXsIh95++222NVjwpZdf+czWa847yY1zzDKVD2dffdtr1zw649777Gt6Hg16sgtpq66lrT0vWnudb61tDYKfYolAItCBCORbgx3YKB1nEmqOoLg7Xn311auuuupTTz11wQUXYO3ykZjOJAcdB+I4M0jHMJPhxz/+sYczxsnXXnstAB599FFdqIuQ4AVrn3/+eV/z+e1vf7v00ktfeeWVYf9vfvMb3yuIMcCvfvWrm266Sb4zwhSO22+/Xdro9Be/+MW9994rjXVZqfChhx6ShgZYHn/8cWnDEgNgq49Lv/rqq3vssYcZaNIvvPDCj370IznSlkxRFhGXfvDBBy3fFBzuzjvv3HvvvcPCG2+8cd999yVgY6GXNa2HyLaLLrrITLbI1xCHHHJIpE877bQ//elPkT7hhBOOO+64SHu/Uxg70iaOn3XWWZE+8MADzz///EhTzvFIA+G6666L9D777HPbbbdJc9wg57777pPG0X0FyXov0q+99tqee+7JWWPml19+meO+bCr/ueeekw4HOctxpeSbhudzEJdedsX73rxt3jmmeeW1v731t38vPPeEa6z8kU9sibX3zLhrFWVXXW6JQCKQCHQFAoNPLOkKN9LIEUIALcBF3B3djL2Eeswxx1h27Qtf+ILq8q45QpiPDbVI5+uvv+5rXMZ1WBq6piNdddVVK6+8cnDNoLwd7iwjWevpnK+JMdX0DN8RC8unn376ajqe4DlEJsLJ0mQQaAWBQAPCWtIxU0t+fGBYvrOMTMxf8jxKOlgpyZKmgf4YKquF/jBG7dKU2CabbDKPBSQcmnzyyaeddtre7HdNMcUUHjRF2vS2QnmnmmqqaBGHpp566jBY2qcYFAl5+VRFmvJqGgiRz7AqCMVx+eGsGqXjURs3OR429HWWg3qLUnPPPfcUU0791t/+n0cl73nPuyec4H3a463X//76629MOcVkikdUOwzIfSKQCCQC4wGBnCrThlZu7SPUITjQ4PQD9073fpuvn+66666Iwu9+97v55pvPbd4W7GEItSubU2Xai8CIPnbXvvqMyPFBBx00++yze3EZS0PZca8lllhizjnnDAE9RwcbtP8IvmKrQ+5sNfqHNlUGQTQIEa42ZMVNnb8cZBJtkQjzyvkSrjlkazxNbZBaeoq//aYBaCuVqqJv2uubqHMMAwLnvjIjlD+Q42EAy7VpUPwAJ/KraWdHWO7K8+3dv3PnzZdvsszf55jREOjdV9z25gqb/uKb3/pWNCVJBWMAIDHMjU4aohWGqUrx1l7nm7KtNMHwvUgNiUAi0GkIJHFvQ4u09oI+BAcGJe5urm7qcTv06N/3w31WSfRUXYwf5m2S8vbSVgbkHHdNGXHQIfSfRoroY6ZUoV8333zziiuuiMSL8q622moLLrgg/BELHakEgAdSSCyIu8RAMk3l63h6b1PaCDNYKeMHxgSTlmMz6QU5JiDT3saYEAirmkqzjYZycjVVNuwpzFjtxmbRvg6V/GqaTBgss9901SmskWGhp5pfk+5LwWmucUQOT9lWk68sS2Q6BGoTgUw0Mvfmc5/97HLLr/THA/Z+44Xb//V/E39kqQ2+1vsYJ2wu19LwQuaQN2gUctwSbW20DZjxxGPIaGTBRCAR6FgEcqpMxzZN2wyLm7H79F133WVijLvsKaec8uEPf5hBDhVi0Tb7suLORgDpwYFeeuklEy3M8TC/+a9//av+s/HGG++///5zzDGHyRVkdKQSdq3vUJDj+jINHtWZI5TboHxVjM01r1QGPQr6W5UcWno4tvWtsbW2DX+4XiwEo0EFal5yIlF4vJ7joxBnn332WmutZRL/zDPPTGDJw4996OHHJ59i8hmmm7paUCk/OVvNHHI6+karIu6dbNuQIcqCiUAi0HYEWnO9a7sbaUBLEHBPdYd2F8RFvG/nhbyPf/zjl1xyCdYV0aNW3SBbYm0q6WQEsO1zzz3X243C0mZFC67rVIsuuqjXIqMvNWi8PmlrUHhQseFo60vQh6Otr6njRFuNm36Wa4sBnldvV1ppJa+rChZ42xVrdxQDFoufd545sHY/FSno1Wgr+UNLjB9tQ8MnSyUCiUAnINBlEXe3fy+9iXt5O8oVPChmTHvoBDS72oaIeImDejz99a9/3T3MqiALL7wwp0CdgfaubtzRND4ILrK+xhprWAXF26jOULNl9Khll11WDJ4xfUnwaFqYdXUIAnFhcW0Rg/c05uijj/ZShIl5PhDBwohYx5VH56n+7BD704xEIBFIBEYfgW4i7i7uBx98sFXDsMnlllvu0ksv3Wijjbz0JqRn7uzoYzdmaoybYtw+zWi3JNz222//rW99i4Me38u3jRln05HRQUCnmqV3U515EZIS+Pq88847OgZkLR2LAApeKLvruQuOC7tFZkxqjyt5BGWqz/f0HFvHepSGJQKJQCIwagh0E3G3ToJA+0477eSC/vTTT3sW79Gqh6rrr78+ltD4Zb33FtDOe0Djpo5QP6giUALtFtj2ZSXzj0899VTfI1Q1VIc8IbiO5dXa64iN3KEwoI2t0AkIjBy8oZmPZUAop5yh0d9GuvbU35kI6AZiAV4/FQsQiPnDH/5w7LHHehfCUrNrrrlm9BM9JCMFndl8aVUikAh0AgLdQdzjrm9vjTmfAllsscXMusbdxWks0FZ9z8ldQbSmPidzY3DPaOO9gYXavo0GcL9AZPwDVR9JMR35S1/60le+8hWHrJ4R05BGoo/GzVsrjITyRnQyAAIkCwiNlGqhTNsRiNUzmNGUU0Zx1SDooGXBWzp5gbopDYNWkQLdgkCc71ofa/d5KXxdoN28qe9973vrrrsuL/RGG4HSZ7rFtbQzEUgEEoHRRKA7iHvc9U1t//KXv+y67xOAuKavunjX7Zprrll77bXdFZIQNNVvDB7iyynHH3881i7E7lXCeeaZB6MFZt47mwIzhROBRGAgBFxPMPK4pLz44ovmsp9++unmspsY4zPMUarv3JiBtGV+IpAIJALjHIHuIO6u+7i7ELuVwnx1PGj6/PPP7+03QfeHH34Y4wwZQUFb/UYlaTMAqC82ckfZT3m7Rhpq94xCoP2RRx4xN8brgz60vtlmmzHJodGBxV180GYaOfxDc/VBzUjX1Vd/exGIkXCrlr3r613mJAKusa4n+nlc6Kwte8QRR1x44YUelu67776rrLIKiHqvxBllz86SCCQCiUATCAzCcZvQNJKieIZLvCCNj7nceOONK6ywgs90C9LItF6hydkWh46ITiNWxN2iEckRkmHACGmur9Z9VNWAAp1l1/70pz95PcA0U2A6pOzojCU6Af+wIfhrfdBG4mgnIDASfqXO8YaAnhxXFfPOUPQ4oSLTdcYGkMsuu+ywww674447rChw5JFHekwqM2RccEbnmjPe2iX9TQQSgTGMQJd9OdVN4rXXXkM0y71B25iwK3zbOAmjxEI0DX78ZSTaHm+mNu5qI6G/r84qXOeff77vm0wzzTR77rnn4osvThggo3n7ZIxXEdoY7mVALCHaeJ/pC+lwctqOQEzxH52nK8MBStlBv/LblP5mrxX1lXeIbc5fPbmmM7fWtlhdqqYK3bgmJ2a8RObrr79+5plnWtuRJR6NehkpPqWkCWytuvy29lra2vOik22r37HzaCKQCHQyAt0RcS8I4pfB2t0bgvi6ebSRAhbDOjnh/tET+3rvex944IEf/OAH9957r1cFPvvZz7I5bvmjydo7Gai0LRHoOgRcAOP8raHRfhZfqodam37zjdd/t/+Bd95936wzz7jTjp+dc865VWruohC75Xq9lWRh2Q022MC6MfJdbexdiILRFvMykQgkAolAItA4Al1G3MOxapinmm7c7XEiWSi7dwN+85vfnHzyyRtuuKG3AiabbLK4iSZlHyc9Id0cqwi4AD766KNTTz31lFNOWfXRKxzl2lgSBIacrhYMPa+88tftd9zlvr9NO+28H7/32cev/OxXd/nMlmecedZ999330Y9+1LunvroVJrkQudTE1SauPFVTM50IJAKJQCLQOALvaVw0JbsIAXdHm+AWm81iX3311YXbTzzxRFPbsXZPsQXe4j7aRU6lqYlAIlAQcArbbrrpJhNRdtxxRwttPfnkk+aAEUCUhb3NSJG2f/zxxyPI7WhJmy4o7SpBxvKvTzzxBG3SvohET6R9OkNaJtZujuJTTz0lbVPXX1566cLzz73rtUk+svonJp1ssjk+stzfZll6t2/sbvEAAQIzZIK1q5cqF6Ia3h96cp8IJAKJQCLQLAJJ3JtFrNPl407ZG956j2XXll9++eDrln20nkPeRzu9/dK+RKAZBKzQ8tBDD51wwgnosiA3/q20pXJNirOXfv7557/5zW+i4NIW5tp9991NOpcWp7ecFPouLUbuvZeY4e0t0h/96EdB9C0G8JOf/IQA5n3ttddKB9G//fbbDz/88Gefe2GSqWd67ZWX//b2m2+99vIk08626ppr+RDEXHPNFdeZKJiUHQ65JQKJQCLQKgS67OXUlrjt3jMmX06Ne2rE0S+55BJ3dB86cR/dZptt4CbuZYujrX1xrdlGYUa+nNpeBFr7El6zHaDI6wklPVCitX1V+LmpF9kHsiry22sb9HBiXHzLLbdcZpllvGsucO55GgddCvD16aabThqH9oTNRBrC1bQeiM1HPlgE2s1EJ0Ptq6++Kt+1Qj/ho3QE771NJFP6rLPOPuHEE26/+aa3ZlpysQ13/Mff3pp0iqnuvPSULRaebI/vfUctdd47Yhu1lqOtj22DR9VFMh4tNlikjlhrz4v22pbjpToNnYcSga5GIIl7G5qvtRd0DlDohhpXaoGxffbZ57HHHtt6663je1XuxLag7OFtawlHswgypr20lQG5qoxWa++qMtEN6nceXTr6aqtYiI7XqmkbHWIbioxnm9EerYkWA5ZterhDEjbnflxz6qQdCvprFsy0006rXQwD5JROoiFMyznttNOuuuoqFH/pZZbZdJNNjj72+BOuf3yGeRZ55fkn53v/S4fv/+tpp5vh3//+F20DtSwLUf+WfEVBLRpURcYnvB6oxgbzaSvEvSXa2mgbX2DSoOMplggkAt2FQJ7b3dVetda6C8qKO+51113329/+9p577hGBO+iggyz46FBw+iprr1WRvxOBdiCAW9SJyxaL8A9bCztwI5WW2usnOsE2FFNEPOyUZlKkEfeCm/zidb9pmZrDBcTcdBcTjPPzn//8xz72MaqQ7BtuuOHUU081bQZ3X2mllfbee+9ll102FH5k4YVXOOO0hx59bPoVl1h/o42mmuoDVGH7dXAjYCv21JFs5FB0jFZ1j7icFgwbMaCOTCfbVsfsPJQIJAIdjkAS9w5voP7Nc+dzj3GLjXvDFVdcgbKLsls05sADD7RipmIoOwFb/yoyNxEYlwg4d5DUznR9CLbxRSnuSNiKX42nIxhvmrsp7FtssYXV1l1JPLVbd91177///osvvtiqjgsttNB3v/tdrL0Q7p6IgCD9+9634SablUobsT+sLUWGmWittmEaU1O8k22rMTV/JgKJQBchMNaIu9vJoJdLlJdYPMdsS1PFnXJQO/vaFkUUN0MUI+fIKaec4gOo5rluttlmv//972eaaSYygm1u2zj9QD6G+60KU/W1s34OCxlWJRb15Vt+NAwAYLtsaDsC0TGa7QDkmy3S8rZLhX0RGFo31gldQOyjWc844wxfoV5kkUVefPFFHzc1Rf473/nODjvs8Mtf/tJCMWVKeikSEYFQwoDQMzRL+nqUOYlAIpAIJAIDITDWiHsjxMLdhVjbQ9FNGRA3SM9wGS/oZV12k02POOII7br55pt/5jOfmXTSSaURMmrLtNSBWj3cbwSrgTQMJ58vtqbcH051fctG7QxoF8/oBaCdCAT4zTZBu+Dq24KZMwQEotfZxwXQPjqAdR6tEnPhhRduu+22JrjHG66e2u28887f/va3oyJv87vskK+5aBQlQ7AniyQCiUAikAgMAYGxRtwb4RZkYhsCXi0ponZ6Yj+oQjdaUa5yy7Qcu68SXnbZZe6sX/3qV82NiRmZZKhqcHbmf/yvPFgf1IzWCrQXf76McwSi78W+tS2b2joNgbiA2MewP8zzzM1C79aeuvHGG60m6egHPvABb52a2u7NVPPaveO+ySabuKqIBaDsytZQ9k5zM+1JBBKBRGCcIDDWiPuYabZ4JI2vY1f2Fmsz2dSsmEceeWSJJZb49a9/bQG4cNY9uND6MeN+OpIIJAJDQAAFt7l62KJ4XECk0fF77733rrvuQtDtXTdmm202c2N8vMncGOzc0u8x3c6HlhZccMGNN95YKfk5wBtCQ2SRRCARSARGCIFcDnKEgK2n1i3TYWy7r1DcdN0pS3zrtttuO+aYY6655ho5JrJvtNFGs88+exSkR+YQbqu5HGQuB6kLDTqlqm//HP2c1vZV5LUaeB6mOx1iWy9X79lxp+aqwkIcXfj8zjvv9MqpBd1nnHHG5ZZbbvHFF1944YWnn376GgRcZ4QG5plnnhIXCIGYgzeES02Nfj+NKHId976wDJpTlqocVDIFEoFEYGwjkBH39revO5mbbpB1+7j1utFeeumlJrKbXSoe9rOf/Sw+Ic5cfD2Ea27S7fckLUgEEoGRRKDK0eMioDYJW1Tr0RzmbRqMNRxdQ8xZ916pyPoCCyzwqU996qMf/agvNBUDI4JQBv+UW+fRRsBFqcQOinwmEoFEIBFIBNqOQBL31jeB+188py53xH7rKGJV/m0V9tNPP92Cyp5Wu9f6gpIl2GJFdkqCslfl+9WcmYlAIjAGEHCJ4IV9bK4nfS8pYupC6bfeeqtLx6OPPvrss896u9QVY7755vMJtg996EMf/OAHJ5lkkioawddx/ZoriRyH1NX3ULV4phOBRCARSATaiEAS9xaDX3Pbi5/qiFuvfdQXt8zYi4qZD2Mt9ssvv9yj/HnnnddrYRtssIHXxULYc+q4Z9fcaFtseqpLBMY3AnGSwsDpNjpIxAUh6i3x78LOEWhmxD7seeWVV6z9alSPo5sDI7gux+Qfb5TOMcccK6ywghdgDPirYXUFC1OnylbnMlLn0OgAkrUkAolAIpAI1Eegu4m7G1480nU3qu/n6BxlD0us0nDOOeeY4mJyiyWQcXGZNTNr33jjDREyi8NYiE3AzK16ySWX/OY3v+lrhdNNN11YW7xTdnTsz1oSgZFDoDyGGrkqhqPZ6aZ4UHamOmdtw1FYLRvK++4R5VJRDWk2p9mUdNTcV5Aef/zxJ5980trqf/3rX11YJp98cl9sMEl99dVXx9e99DL11FNXq5N2hfEOA508qtFcI5k/E4FEIBFIBLoIge5mhO55bbwn1dyG3ewx7CuvvPKPf/yjt0inmGKKww8/HInfZpttdAi3YXffBx988I477jD9VNjMyuvuuJj99773vfnnnz8YA0nhsbiXt9e7LurEaWpXIFB6eAda61x2ujHs7rvvto6K6SXSJTMMjvO9mnbK26rXgVBSzt8Qti/5JacksPOXX37ZY7fnnnvOx48QdGQdRzcHpiypPsMMM8w555w+kGSxF0wdcS/FIxGWQLhUJO1y1MmY17iQPxOBRCARSAQaQaBbiXvcU03o9PqmwPaHP/zhmrtsfecJ2/qV6Sf//97V8y+23pQ7fM+yL+/pudPHnVIihhDHHXfcnnvuOddcc8lZfvnlP/3pT998882vvvqq+7E7tEfYZp2aBsNgW3XuaTAA2to4FAkXc58ItBABJ5RebbrXySefbLC69tpr95w5zQSze87VAc7WQezsLfXOqdsjGwS3pnaZTjpn6C9+8YtYxZy1u+++u7G3QyFsXzU7Mp2/MuvbQJVBuzA5Uo6Ou2TZB1O3Fxe34eii494inXLKKfFy011mmWUWy7/g67bqVaLUBRC22YdhzBjUklI2E4lAIpAIJALdi0C3EneIu2+ZFL7OOuvYzzrrrO55jTfDRBNNGLfevkUGyu8r+c9//9NHB22v/vXV115+7e9v/P22O25/4/U3sHZPtN1TPb+2sJr3xpCV7bfffqGFFirT1kNbNbie992+CGfOmEHg+uuv93xJCNnjJksNOnkb7PDEhj6U7R0e9Ayv39kmmmiid5L//RuW7LXXXj5nttpqqzlzLcD6u9/9zrrmfau2kGhsuDjmzREJa7kg3yi4q4GvGjv97Q3XHQph8+XwchR84oknNno3PMDLzXVB0MFib0gjQG77r1nvpFTBJL9cmmKLdF/b3imRfxOBRCARSATGLAL93Cc631e3MTcwd033PAEq5Nj9EnGP21vs63hB4KEHHv773/8h8OemSNJtUQALjbb965//+te/e4JkESf729s9/97+29/efuOtt998++9v/eNff/vnP/75j7///Z+9t+SeGzP5d73nXZNONskEE0746luvel2sEPQXXnjh0EMPFTYr9qiiZtY7e2xFYBQSqgvHR6GuvlVE7e01IGzQi/qaNwo5nYAAN5ttgsIam4JIKRVxWSDZ6fDEE08oHsgPagCxN83zvu/+HvnSVhFH7z1jeh+G9aTiFO4B9p3/6nSu9ULdc17/+989J/jf//F3D896znKn+b/sezbF73/gAafEGmus4WxX0bbbbrvVVlttueWWrioYeYjZlyKRo6BIuak1CLc9ai5Ib7ju9DezRcLPmo28Uv1udLKQwTYCAZF9bFGkHO1XQzWT5KDwVuXrp6mqmlFfuP7R6Aytsi30sK1+pQ0eDeTHgG2taqwGcUuxRCARGE0EupK4B0Cid2JObnWCWO55kYltyxkUwWOPPPa2G2+f6P0TukX2XvMF3XqudW6X5oV6Kk5zb/yr534s7Xb73gneN8FE75t0ykkmnnniiSeZZMopp5hqqqniJj3R+yeaYKIJ3vu+94qlnXDcCd/5znfE193FTzrppLnnntud2ySZqIBhagkL4wY2qKktF2CAwUZY0nLljSh0d4RAgNCIfMtlGKDDxE265cobUdheBHSAOF+a7YHOgn5DwoO6rCLNbe8ssJGPsyD64UDFoTTBRBOZ8X3Ij3/yrv+rEPfeAr2nLTU9lL2ke373KHcK91TRu0W65/RWtXync+8J7hx/X2RONOGEbz3zzLtn7HkpnKWhjlgs1aKUc9lFRrxcXNzmNI+NRzJdImzB3Sns153e/t6zE5VXKsTsS0Ipo4Je2/rX0K/agTKpbe05zvJe9FpgG/d52pKzj5sMAwLchq+QtqGdF/22Qntti07br2GZmQgkAt2OQBcTd4TYF7xdsr3XZY0FLeFa2e+j8JpGconf5du7BAVRJAq6p/fe8Hsou6vee9/Tz2dNa/T0+3OHHXbw4NuqMmqxsKOllGmrkXTrktM3v0ZsRH/iIuH7iNYykHJ37qFRwIEUNpuP1jTSVZpV27h8exEI8NHNxg0ejmTwKmdE73Osf1DlFJDZ7+ztmormXWihHx971HveXTmJ/sseSxeO07jnCtB7Gej5+x+iLvkfxt6j4t/v+r/3/Td0/z9V7fjFL1599dW+Kir3lFNO8TTvpz/96f9I9PmB5/XFkJs2sva99vRY1XNJ6e9LyVWVLe8SLTzH8eNB7a/6UicNFt2gVWdfa6+lrT0vOtm2Og2UhxKBRKDDEehK4u5G6JqIuJta6nNFglgxTyZuk4Mi7s4xycSTuKvVlyRWtv+E+/7LGIIi9CioqVSRNXs3iZpDpTqHSrotifBrIPNG2qSofaRrqaM/DLAfzwjUwae1h5yqaKtnU15ORf4WWWQR+htHXpB86immbI1JJtZ40tI7j/w/zJre3t7AsK/tuus+++xz+eWXo5VmqH/3u99luS1MrRpc0iS5ZivmORRbyWk8Ed1S8caL1JHsWG1hWB3LmzpEW1Py9YXHj7b6OOTRRCAR6GQE3t3aS9UouyriZflF3/E2qZQjDd7z3IxNs2kk2tegwhqvS3Qq7vp9lZTHuzUFR+2nabvGLVXCMWpVq0hLCS72DVWOmg0MiIh736YZHRvajgDGydM6861HAodbbrlFnNViSk0p11eValVfjRh533aPq4dueeONN+qZpuMzMjLrWNva84htIr59batjQJ1DrbUNMsY2LbHNVVH3GzRuUse16qHWXktbe150sm1VDDOdCCQC3YVAV0bcC8RusdY2jp9N3VQINyVfamwkUZ4pt4ptNFJpyiQCnYwAErzYYouxcFA23NeLFp6tA5318hmGN1vxJgwYgp19Lc+cRCARSAQSgUSgtQh0N3F3cxW/wY8Huh+3FqzUlggkAkNDwBnqVFW2Y0ezwd3LU7K8pAytobNUIpAIJAKJwIgi0N1TZYYGjXszxl/i4kNT0o2lwnGMJEiJPRw4Ej9H06PRD2cWTyWCnGGQxQw5o0woS9WjBnsNAup1ChQzRh+BBh0330D/bFXrFH8brL2vWNEgwbZ4nTEy7ckP+WwqmvtW2kiO4tGIcV53jm01hnXC2VfFs7RajZ3Rjm08L8IepsatSoM6C6Jx225bFcBMJwKJwCgjMO6Iu6thXPVKYpQRz+o6DYHsCR2LQDGsJNrbefqa0TenvRZWa+9k24qdnWxk2laaKROJQCLQOQj8dz2EzrFpRC3B2n3K1DqSQd9HtK5OU37XXXedeuqpt99+u+DN008/7bZkWZ5HH3200+xsrT3cpJCnvtgl4RXAyy67zEeypJ966ilv3ekJDz30UP01xQl371YQsFgKL5599tmzzz77ggsu4PszzzwDkI5FoKPO1qBxzz//fHQVMHoznoU+jwrGtp9N7NGx4/XKjrLNF2QvueQS37LQ95jXOWdfnBdas9OuDGHYc889F+epqL9TtXNw694rYVqeCIwNBMYRcXf502bIK9aOvN53331+xiVybLRlfS8smmmpO+tmohpuVME5zjvvPB+zHMM4RPvy3Qft77zzTp6eddZZWLs7Ir7lXkhAl7jtttvAMiY7Q18EUHYTPGIh7YsvvpjjHYhAp52tYLS5dPziF79gmx4FRufRRRddZIkqZxYY23g2seTCCy8Mq9hz/vnnd4htsLruuusscWNpfENEhnXO2adBXRCcAqyScE3oENvCMF3LeWrpJz/PPffcDrENULklAolAexEYR8Q95jS7n2288cZLL730iy++CPq4RLa3DUandoElN9EZZ5zxIx/5iIj7NNNMc8cdd8wwwwxLLbUUENCO0TGjLbUIiM4xxxzughDw5cuNNtrIRzHdCO0ff/zxxx57bMMNN3SDHMMgBALhIP5kMT7tDhBf/+W+rdMQ6LSzFXSixZ7bzDrrrM4XH31bdNFFgYaSOrN0pHadTXEFMwpdaaWV1ltvPaFZz5Es4NMJtjnZ4bbyyiszzPK7YgSTTz5555x9+pgGfeKJJ+aZZx4JX8PtHNtAp785T5dddlltKtFRtrXlMp6VJgKJQCAwjog7hxFW9znXa+HGWMRaepx0BSwN5zAn5LTTTvP9dvOFfBBnwQUXHNvu4w3I+gc/+EFfsdX0aJbbs24w3XTT4Vu4+yGHHOIphHVFiY1JKAoC8803H8f56Mu+grJ/+tOfzF4Qo+1YBDrtbI313X33TVcx/UO3kUDZgelhTrvOJu2rTWeeeWZD05tvvhkzRviik7fdNoYxz8X2xBNPfO2116RdeTrk7Ivz/cEHH/S5vOmnnz6Ie4fYFncll2vXq+OOO+6RRx7xoZIOsW1MXiTTqUSguxAYL7Q1WsUFMbbgBDIjXtVdbTY0a92oNujdEA7xVzf1z33uc0j80LR1VymtLGrFZqM1TW+VBndEfAJz3WmnndwXBVB1jO5yqilrA4F45rDkkkuutdZavjFkEi0cOhaBd07W93TO2QpGG+R1Hj2KhYZ/+Cg238azKUzy7MiwfNVVV+21sWfVrE6wzaMADznXX3991NOjAIh1wtkHIpaA65prrrnhhhtMwUfcNWsn2BbnNdycp2uvvbbPC3pSweDOsa2pK08KJwKJQMsRGMtkpQasuFjbi0sJtEgQiH2N5Bj7GT6KLptm6rmwNxTdRFENER17Ny3+RvxpjDle3EGtzA9xb0bcTQsBArLu2b0xDBCWW2454VICYxgECAjEYgMwMZf3ySeffOCBB7gvQCsA34EI6LSolX1Hna1ghGHEPhmmF5lxB8Y2nk0gYpVXZvVhVE9g2yy4zrFNfzM/2wMKCc8EnH0GGB1y9gFq/vnnNwAzfHVJ7Bzb4ood5+ndd9+9wAILdI5t5aKaiUQgEWgXAuOIuAfEvozotiHU+rGPfSzIQbugH7V63dd5Otdcc80000znnHPOKqus4kk6uiZz9dVXx+cQESRp1OwZ5Yq4r0b+mk4gwf0zzzxTHAvZkomHmUVjGgnqE0xxlM0bheoKAt5w4GMgwGszBCAgLtuxCHTU2RowYlEwxPlmm20274Ous846nmNIt/ds+utf/8oAD9C8Z+k0Nxz17mwn2GZytsn3QgYg8kaNGdudcPZFUyLrHlBsscUW3nrysscKK6zQCbbFBQFu3g1gT5ynHYLbKFyssopEIBEYFIGxuZLGoG6nQCJQEMB44kZecsZbIhEYby3eOf62se+p2kM2U1Cg0a8Z/WZ2CHSdbFuHQJRmJAJjFYExG2et02Au1rY6AmP1EK/LdOFAIG5dY9Xfql88tcmxrwEBa4dGHK0WGWPpHv+7EAFNY+uctijGSOhIYVhkgrccHWWDVc0YWxjQgbZ1YN9z4mPtDLNJ2wPQXtsFjO29MlTtqaY7wbZR7t5ZXSKQCFQRyIh7FY1MJwKJQCKQCCQCiUAi0IOAYZJRkyHcEGaTKmgrMzBjcEinxIiCy2ZV1NQicwgujKidjSuv8agAW9Ugs8bl6tEaDdVDkW4LPkOuNIl73xbMnEQgEUgEEoFEIBFIBBKBRKDjEBiPU2U6rhHSoEQgEUgEEoFEIBHoGAREcNniBfQ99tjDp5GlYypamU8lR8TUTwnC0rHFT/nW2z3ppJNkWknJisMSlka1NkYEjEuR0FBKESuaIx0/Yy8nChYZiZJ2SNoCU08//TRJW+/Bd1mDgSNFTH7YoOqQ8VM6MiMnZKJ4KThQqSJQtEUiikvbQn+pseQUmaoBvSV6jFej/amnnmphJQKxrLNVXC2zId/PKGWNjWeffVZapn0kIk2GkqOOOurhhx+OIpRLyCySlr06/vjjo1TxMaomWUyNIn6WsoqEWLXGSBcXQj6KhHAotJjVVVddFR6ppaktiXtTcKVwIpAIJAKJQCKQCIxlBFAr8y4QxGOOOUbit7/9rXWTvRFhtol9mZIRPwEhRzq2+EkMJ7v99tux9jPOOMOiqL52Rwkqj9CTL0VIBpRyogo/qSrp+Bl7+VGwyEiUtEPSt9xyixFCGBNM0aKiBgxFLJRUq4u0vc3RkJSWiE0me3qP/9dIPyOTTAhE2aKklC3FwylWlZywsPyMsn7aFI+jPEJzlbWEl0xrLtkk/AwDfI3BOlrSMu0jEWkydFr9Ocra00xtGB+SPqJHg0ZXpBwi0Nc28oqXsn5KR0X2kQidPQ70VmRPxlaE5Ugz6brrrrM4tVJRUa+ChnY9KOSWCCQCiUAikAgkAolAIgCBIFK+0mBx1R//+Mc+fOFDH/i3yK7Q7zbbbGNpXTLiuD6Pteuuu95xxx24MhIm3+ftLC6M8Vtv1IcyfKUbfZdpAWIk3pcWfPlBFeRxzfi2xrbbbovJqe6ggw768Ic/vNFGG1kJVAjZN79XXnllA4DTTz99tdVWu+uuu4jJvPTSS61hqgq177jjjiigL2EL6vsMnBrjEyUnnHDCnHPO6dsO6rr66qt9rEPi2muvRRatjOyj6T4FfeWVV0466aRbbbXVjTfeqIrPfvazFDKMtdaWnWeeeRZeeGGlfATmrLPO8gUYjht1GM+UUjDZeuutfQ/hoosu4ubSSy+9/PLL+0gIhfKVtdFs0WHFfaVYmiUW42aGqPknP/lJC+xazZZ+9cLBZ9rgAHDIk4+GgBiF5513Hq8tbM1yboKOkcpa91boWhOsuOKKlp394x//KOb9+c9/XmMRIObLk9rCV/MQ9AMPPNAiyJ/4xCfuu+8+TyEs7MsGqPKIqarDqo1zfOxZXYssskixrfiuHS2prO04RaHGstDt0UcfveWWW2Lnhx56qPbyWUMjAcuOcwFEmkz/EdRXl/Y1DvGpDVXz/frrr5977rmNGdjQi1ZDu4y4NwRTCiUCiUAikAgkAonAeEAAe+Om5fNRwPXWW++yyy7DrrBeX8USuj7ggAMcxTXl4OjHHXec/SGHHGIyxmGHHYYpSuOFjoqy44u77bYbTkkVkveFL3wBvVPcz2OPPfb+++/HR21yfv/73/tKIDaJ2NlkKotKonSGBHfeeacZO0gzfozjMgkdR+5NjCGJB+PcBhL04LV//vOf2YkX+mnDvLFVE0L2339//B7Lx7/ZjG5imdIMFopmvHEFKoll4vQYahRnpE+dfOhDH0I91WjAUC115JFH+ggxTw0APE/gAgcJRFn7K6644uKLL6bWEIhVuLuZPIcffji/0Fw1Ko7ahn5eMIYYAYeCzgq3UwJSllN4zz33GMPQYzBgZILoay/clwswvO222zBvnpLEv40ijGQ86+A4Tk+Jpx+GGb7CuckmmxiGgVH8XnOQZzmd++67L8RooLlqG981mfGA6kDhC/TE1EXGprH222+/UrtPQ2gvwvRj/wcffHAgjOtTC0O83zfpjOXU2+yWxL1ZxFI+EUgEEoFEIBFIBMYsAsGtBXp/+tOf/vKXv0SjUUyBVfPdsXYMGP1CLsVxhXjxdcwSy99zzz1xZVwQi8UR/QQQGi3T1+5wUDFs8hNPPLF81Fb+z3/+81122QUTRfdx1tlnn12lyCXS/P3vf98X6BBKxiy66KIiuIpge4xZaKGFVKp2zI8wsjjttNP67BqTaEa7EWgjDWFpP2mQI00SOeaRuK9MTNfXx7bbbrt7773X8IA8foluBuP06IDymD2y1FJLCQ8LabOEAcLVpZT4N/LKsDXWWMPggR7gYPmf+tSnVO2nvWA2yr755pvzArXFX0OVBwJwAxfyzReZhKmCJHmfHkPc5cT2la98RWbYg4hjyULXOLGxBxothC+sDlsIoMjAx6qF7YXM99prL2D66KT4N+7umQZyDy5xegI4NG6tCqaGtYi+qn/zm9/svPPODrGtxnePBYAASZ1hww03RNm1iJYCjvGVqm3MAKCCZudzU9Mbz0DY3jDJT8hrBT0hPIqB4ju+Dv43ifvgGKVEIpAIJAKJQCKQCIwTBIJO+eIvcobjItNIpIQIrgg3hoc4YuQmnAiiY2+oGGqolE0CSsLwgrJoqLTMIIU93LB3kznhhBMKPAvhx4QNdJbCVVddFS022wSPj3B7DCGQVJMrzB7Bqm+99VYzWKhRu6rJI6Z4JEs222wzmtH03XffHZtETBW3UY5rKi6+K/iNYVOOlaLUbMPp8WYPFrBJmjHOI444YvHFFw/L7Y1VhPl9blwR8nhzKbXuuuvusMMO6K/hTXyNnl+ovIi4grGFDQxWkQGPsgyOGpFXsXZMt6qfGBml3lHQM4FeUBwmkUkVd4jts88+iLVG8fOmm27SRqiwqLx4NjMIaBetRg9MtAs9HkrYDHV+9KMfIdYGYwSopTOqk2MsASVqlQIFJGt816zBuVF8ZF3TGCEoHs86ROVVxEFHPcTA6Vky9dRTQ9hDCeMr9D2Q51FUWmqPn4Puk7gPClEKJAKJQCKQCCQCicB4QSCYnKne+J8p7CLoQsjYpOklaBl+jJkJ8WKKIr5YF1qpiEwUGaUjgPY9+uijGD/IHLJVE9LIH25nlotZ3SidgmLSeLxZHCq1IZ1K0Um/gL1ovQi92eQSOKiAsRAyY1Bh1eHK0kEElTUJG40+//zzVUQDk1guIE2DGSam3fMFy7Q5+pGPfAQxxVAFj5VF2U3FER2PsvYi6GbLGAYQRnOR/ppSHhTIMY0Hp0fueWSGvYLhNZ3SHLRxijuUR40i03J4JM5d9BOjTakormykSYYqRwHOfeBzHBsGC7btKYRZ/iA1i2n77bdnTNRIA08VMQ1du3jCoGURdFNZqEKjS3VsExdHtT0JAZdnDqYYmVRTbGMAYVsMqwBLDJjouFpUau679xMkGG9kpTj6DkComvzDQvmKh48ecYj9K9js9t9xRrMlUz4RSAQSgUQgEUgEEoExjACGjWZx0NQXEWIssxBKgV6b+DE6i/MRE6PFLzEzP4mVslV84hB2a/rND37wg+oh80zQTSwT/Q1uV45SRbOf6gp7Su0yq2k2MIAwHh9EE5tUfIUVVjD9wzujJnx7Q3TttdemKqgwDeZ2i0Abiphmg0b/7Gc/o6TUzjCSNsbLDAMkUHyxZAl1sSGeNiiIy4a1DrGHvJyAiGv0VMtK99UfpQLqQDXwBE5BG3eX9hSCBgkCVZvVKJO8owWTAF+OBN6s7aSZRyAk/bQpWOzva5uyIW+04HGBcLuOobpq7X31FKy0BWEgmM2P0BvDFKui1KD7nu6YWyKQCCQCiUAikAgkAolAQSDoVJBOpBDTQrkkgqI5KuwakddC8oL8FR5WCG7RWRJIXilVFEaEXvGgtkVYoqiKRLV2R4slzCsEVIw5NCyxxBKm/ZiwIZa89957L7bYYki82osBxLB2e6Flq6CYXh/kO5iousKw0FbdB2snoK5SHYGq5rCn5BTXoizhfvUXLwiUdFWVUjyK4rwO/YU9R6Iw6SioCMlSpBhQrSKOFmv7tY2S8MIQyDQhE5aUqkEsKip6CJTqogUNdVhlppBDISzR4JYR9waBSrFEIBFIBBKBRCARGKcIRNy3cMFhooARGgYUSjpMbYMWV1fwxZrQck1BVtla5WON8rH30/AA526WdgcOcJYYWtkk7mOvL6VHiUAikAgkAolAIpAI/A8CyGIwxZL4n8Pv/Kh/9B2p/PsfBEYfriTu2fkSgUQgEUgEEoFEIBFIBBKBLkDgvy8fdIGxaWIikAgkAolAIpAIJAKJQCIwXhFI4j5eWz79TgQSgUQgEUgEEoFEIBHoKgSSuHdVc6WxiUAikAgkAolAIpAIJALjFYEk7uO15dPvRCARSAQSgUQgEUgEEoGuQiCJe1c1VxqbCCQCiUCw4u3rAABIyElEQVQikAgkAolAIjBeEUjiPl5bPv1OBBKBRCARGEMIWJaON7EfQ26lK/0gMIRWHkKRfiru8qyxAUIS9y7vhml+IpAIJAKJQCLwzsdcqp908eV234gJbCSqP4cMGOpDz5CLZ8GWIKCV33rrrX/84x8DadPcturRaseo5kd60Dalre2slwHFqb///e8+JtXXkZLT4///IuBQfRBK2VYlqicLhH0tleZBoR609iTug0KUAolAIpAIJAKJQKcj4OvrF1988SOPPMLQIAfXXHPN/vvvH3bfeuutV1xxxfXXX+9nITRVKlbSkXj44YepqmZG+pVXXjnnnHN8iTPUFoH4aV/NKemSqBEopfomqkVqjjpUjpZEyJSfJVFTtt+fTQn3q0FmUVISIVl+RqLmZ41MVU8cqtlH273wwgtHHnnkk08+SVtRGJIh8NBDD915553VnOuuuw7ZLcIlETLa9I033oh0OVQS8hXXwSRKZknUZFbzQ2HsS37fRFVDtUhJh1Ovv/76VVddFX2b70AoAtVEXwQcVenbb79d0/+rpeqklbXVEeh7KOSfe+45p2Qcfe2115xQf/nLXy677DI5YWTfgo3kJHFvBKWUSQQSgUQgEUgEOhSBYAnPPvssliAQy0pfrReOFZJ88803MQY5qHZs0uKOL7/8ciTsSxolQiyCGN1+++033XRTRHYRJgkb6kPJe9/7XvoxeERQJg2x+Yn8yXGoh+n0fqdTmhkhpiJBx1LEoRr6EsbTEzVSS8lLL730Tg3vkh+VRi1FM4HQJp+R0qWW8K5ocBQB5Sa1lEd+0eZnmBR7Akwqkd0iX6MTJsQo4V1fy+UXj2godUmojnzBpL7lhNWrFCVXX331zDPPPM8887BTjlbmMgFbNI3WD0nOyiGmb+ghMklWcQtfyL/vfe+THwqrMnL8VGl0DFVIy6GK1xFFli4+SlftIc9Hrsnvsa+3+1U9LW0aRwu2UYva5XNBXSRDxn7eeeedZZZZJFgePbwcCgT4QoNMDR21S1xwwQXyCVQ7VRQkI6EWrkWOfWkdxsuHQOh0qNhZhB2ivPwkHGecghIf+MAHFlxwQXAFjBT21VDK1k+8r/7hPJoIJAKJQCKQCCQCnY8AJveJT3zigx/8IFPRAmxGSHKTTTa56667lllmGTmx4Rann376888/v8ACCyy77LLnnnuu4OWHPvShpZZa6vzzz5dPz6abbvrEE0/89a9/FTIUi8U21l9/fWnBwtVXX33JJZd84IEHLr/88gkmmGDNNdcM/iQiqyIsaq655qJw7rnnXm211W6++eZbbrllyimnVNww4N5771X7dtttR+yUU05hz1RTTbXxxhtL4FKeD9x4442LLLIIGxhP8+yzz37JJZfcd999M8444wYbbHDSSSchUoS33nrru+++m/Dkk0/OQZTr1FNP5fU000yz6qqrnnXWWYp/9KMf5ZH0M8888+EPf3j55ZdHAdVCGy8mmmgiPHX77be3p/CGG26gTfHpppuO/RAQml1ppZX+9Kc/GaXIX2ihhWSifSuvvPKll14KHDl0qtQY4LDDDoMJDJFjWK2xxhphOX9p4+Mdd9yB1VHIkmuvvdbTjymmmGKjjTY677zzDHVsn/rUp1TEi4Esh9vZZ5+Nec8///yAvf/++9E+bTHJJJOI42oL7JBtvJbmI4RXXHFF/F5ds802m/Tjjz8ONAASYJLa3//+959xxhlPPfUUyyGJ4nNtiy22UBwaWm3DDTeE2IknnojOopuq5i8x/Uf+xBNPDMZXX311m222sedL9BNVw4E9q6yyyqKLLnr88cdrIFSeGJ008JeG8PTpp58GIN+33HJLCvVG9iilLs2taRTZfPPN9Sj9UFkNJFOCa3oFVdqOfg4qFU3syRIXDCQArlvedttteDOE1fXggw/G3hOJhRdeuPQKfY+e+eabj9n6uV5ULIfYZz7zGTBqRHYuvvjiQNYWpV9p2TCJjxdeeKH+fPjhh7OHAQB3EgGQ2c41z0CoJQ/MaM3omUUDvxrZMuLeCEopkwgkAolAIpAIdCgCwRumnXZarHfCCSfEA2zIpSAfbo2UEMBpZDr66KOPYntf+tKXsDE8abLJJvvKV76CQCBhSyyxBI6CcOBeCApeiN9gP5/73OcooRDRQXewkMcee8xgYO2110Z8qYWLQQJCs95666Hdn//850U0ETJ0B7FGsDDCOeaYA+FGyBBNNBR3+exnP4s7EsMCaVBkueWWQ8UQTXqwZGlqEb6PfOQjZJAq6Y9//ONIP/q10047LbbYYmgoAzAzRvIFN+L1tttuO8MMMzAeu1XEtB9MlwYgUPXFL36Rm5gc49WLbzkqE+FmVQDFQglM1ICBX0YgciDGOxv9oVNxBBQgSOqVV14pBF61nL+AxXS1C0yMYTBvMIblxiRYnbEWkkcbMe1iVNOv5ZhotJoiKCMQ1llnHTmMnHTSSaUNjbBbEEHsC1/4gnEFMh2mGqFNPfXUH/vYxzhCz5e//GW4YbeMgUm0PlpvlEIPhYYWRm7MgC2d008/vZZSi0P8xZJ1JwCqCDgGikZxGtpQje96FJ3rrrsue2KqFRs++clPrrDCCsQUt7GfNp7CTaMD01HoqUtn0F66qJGDDqlebJ7MPffcQ6HBhgYKJVqcGUDjnbZT1iFV8xrzhrbwtp4800wz0W9kAmFNr5moJaz2aEFFKNRP9Gd93qBILcVywwlQ6/wqUoswv1pgxaTSr+LkooRTRnd6pk6oIVjOQT1czzQuMiAJSeegPlDtmUVDuDboPon7oBClQCKQCCQCiUAi0OkI4K82VtqjAqiPIDeOi32KGiIQDqEpiGaETrEKBAWzlI/YYTymxxx44IGYFjHESA6Wg3Zj/2grDWLPgo70C0kKXop6+qkuGgwbMGaHECl77AR3wYmPPvpoanEadEokklWUY8xC0YigIipSPDTgOn7icMxWHSJu2CA6iwwxAP0igNZj5IorIo0+qmvOOeekDZEVNEU0BWv9xHEVVCnCrSB5VaOYv/71rw844IA//vGPdDLe8ECA3CEgoGVss/lJAx4GAa4JUeOduB0Ch3eGzoCUAHbIZTTRDOyTTz65WB7xbEdtoRa2CG5YDhBpBmB1LDGwAXVfy+knrwVLq1GiOgQ6PGK/8K2wLlXE2Cwfn9a+BloFPZlqBJSEhyQoMlgwUT85rrFYSCevKdRqAsxaTX5AbSQQpFlnoERaFdKA4jhVWo3vcNbo7AlH2Ek4fLRXF/0KGhUQVh2ntBp8VKS/YbdHHHEEAzyR0CiE2abHRt/TEFo8zNDxJHRIAjQzNfLpiUdA+qGOYXBCoV7HO3bqXTh3Ta9glX4otM/aM888E5LqLZY7hGSHzuiBftZoYIAi9qzST7B/FamaPE+p4o4mdlRdEGNkXw0ONbjlVJkGgUqxRCARSAQSgUSgcxEIYoQlYAbYCSIi8spccxgwbIwHcbHhYWYyYBLCfiLcIq/inWYU4HkKir8iOsQQEeTDHvvHBWnDyYIs0ikCamKG+SQ24VU5gvTkJbAultgjVeiOgCU2iWsqIoBqmgoehqiheqozqFCFUjZpJMkhpfA5cU1K8BszJQ466CAcyMwTXuDNQuMixxgbkiRf1crShroZiqjXuAJpFuynh3mE+asK4HiqYOutsGcnh7zgK1hoQxzRaLwKOGgWI0GhLPp12mmn7b777qrACEWm6YQJDewHC5ehJMpr5FAsN+3kmGOOUQQHVREA2YMX8lFd9GgmBdlPD1ZNIctR7arlxgyOzjrrrBrRSIaFAsNgD55KrTkepmFQLkCuESGMKxOGD81sMBjjMl+45tGB4YEnDCwhgGFzP4oYlnjK4QmA4qinYQ+yCwRqFTQmcYgl6g20taPa4YN5893GI8FyVbAH1Y6HIdFn0Fab4pqJC5wS/OYp/ZpbjnZkGA3ay5iQWDyKYTavFaSWjyz36MBP2ljCQRqYESbJh616taYwOeLOyB122EGOUQG/OMVrg9VoQS2rrCagjSr8nuWqA4j8sFwnpNNYkZ1OFkoMt1hb+hULIUBe7VwAlBrN0TKW4I5hDP1QioYOUxWvalDQUfsGt4y4NwhUiiUCiUAikAgkAt2BgKAg0oBTIjdoilAlboE+YsYIlpDncccdh2UuvfTSKA7+ZDq4CRtYDnpqRgEuYjaF6LKyVOE9mBzSHCQSyUBQEFCcBtEMRFBbNAjDw3Lk4DfSIr6mOJt6IV6L0QpUMwBzEkVmDDHC+E3RgDNhpTFtQ3E2qwvvNINcjWo35Ual2JXBBtKJD3EBdROupkSs3WQV3I5HZlZQju8KriNPNAdFs4dJbFEveorGmUKtOtMqsEbsEzuEHnAElYkpzhcJIFR1ymF/+ELADCITTorlqjZJBp6GE3ikpweoJ8TCci6wUO34Oky0kcFAv5azBJ4A1GomSdMfsWe1w4ceU6tVgYsD1kjJfBW8WfsSYAOINI0GNVpYa621cEo8VYtj+dpXi9PAU37RYJRlSHbssccaD6gFW1U1q3gRsX/+kqRZkegJ7I9Ws9CNIgzwsgR7cFNjOWIaiAGqUwr+ugpPjaxMSjFsMGUI7TaNRz54rYOkvXoHAj2PDkCkCWBrCGfsx32ZNv1BvXTqUVg+OxkjH1lngNaU0G30h+h1hDWiUpRD8ve//33pFUrpOVQZulx00UVGccVyrQNtvcsbF0Y1GoIxhFUHWMzeT87SoHauQcamIxEAuOKlZyrFKR1AgqfEqj2Thsa3npoal07JRCARSAQSgUQgEUgERhkBXMXsC3OvsbRRrnqY1Qnf4ou4ID28CH45HJ0tUTIcA1pY1vBvs802Gz4mLTSpryqAi6MbnHhUZagTk51CTJwe0TdIHs1G6bIToC+gmZMIJAKJQCKQCCQCVQTQiPJTurrJ91PI2b6kQ1hA0VaEyciXE4nID8nQ4FD8tC+lJKJUZCobYlEkxOKQfXUrh6LG0GMfM3ZICmwLzVa1FQOKsERN8eJpta6+6SIWBofCqv5qugjTQzKEpWuqZrlDWLs4q0O2iMtGFSFf1UCgaFawpMmEWOSEklJpSPaq/09zhH755VAU91MijvZorPSEONRToHeragir7EsRIlE29vGzGO9n2NmvWCgpOrWpuHVVeZQt+kPenowtdJZMPyMn9pEvXexXpGpMSdeoKsXlU1LVGZKC6J78eG6AtTtqC1Ui7vGeQBl7hIain2Qo7C30P7iFhuJL44mMuDeOVUomAolAIpAIJAKdi4ApEJhE2IcWSJil0NdcrALPKFSDQLANiZr8vmWHlmMSjikH1RpDD2orZmkOBvZmJsPQlA+zFBuMB9pV+zCNryk+kC/BI+Ff53lF315Ro7zmZ/SZgRQGTx3oaI2qOj8HssosKcr1dhX17Vd1FMahvsYXYq1DmmjUlFrnmlOv31ID2T+ohXUEMuJeB5w8lAgkAolAIpAIdAECQUR+9atfWY8lzDWD1mxm6TgkgYvEofgKZvkp4bU8r99598788pCpHq3JiZ9lX0cyBg+md5tIjWkpUjXGUZO2vXRovoQZ1X31kEfovYgZBUvZUnVTiaK/lJITNnBfpp+2OFoSRbhvosiURF8ZOcXsqph0+VkS/RYvR0uiKlYyJWp8qYpZy1zjaveqPSFQNPTtFSaBmKpeBCSqaaCZdF6jhED4a6686SXRAaqWVNOEi0DRXKOwr1UhaUlHCwoRHoi1VxWWtESk9fb4smz8pMciMBbG0d+8I1HUlqNymFr9KccWOZz1aoSfYUxVjP1hZ694a3ZJ3FuDY2pJBBKBRCARSATaiwDeYP0WNuAf0hHvlPCCqUwJpMqSKYiF0KyfIs1i4RJ+OiR+KUIv0+IbMsOXEFNKgkwwrdjTE/leZlWqpgg2QxvN+JB3WyMeySRFBDUJWx8m3n/1TqcXCuUUO1UdaZZ485K8upTllyLWG7EeS6FHEnLC2mCNsZfDhjDVoiLFvJCkX461XLz1uMoqqyjip80AIzCRYyMcGjhoi5zIJMwXoVaJ0MkSrzwW/ZEIl6kNMb6wStpGYaRJyldvFFFL8YhYQUw+x0Mm9nE0bEA9q76EkjBYK9jCkWoVjtJgrwrGx0+Ya1D56L5hlYSfVZsDTJVGE0RnK77wN+SrdpKsWk5bAKKH0FYwJMaSgayKIuyhuXw5NeSrdRHzBjOxcMqhSEctJa2WOFQMU9Crt94nls9CHkVdYRVTw9/ojaVGwHpt2vcNakoVVENJqUXxUlaLVBul5NdP5HKQ9fHJo4lAIpAIJAKJQHcgYI0Oq1UgHNbXs3iFJT6QFUuCYPPen7Nohm9zYpa4gkVCBAItiEHYBzItwYGUeIESqxAdR90s30FeJnkLgGBX1uiwQggyZ10U0VZTX+yxFtN/zXVBOq3biPegKRh5fEfTai2md1vGEXe3mKBDPkKECyrrA5NCm6KeHhFIiN2yWYiXYSryrEBI1UojDHPUIVVrA6uReNdTddbr8N1TIw2+WPRGcYufWGDEhHILeghzWiTHy6wxojAvWUFfCyLDIz5a1wXH9bohrsYjxfnuEKAsSKKUxf4we3Oa4WlFczCyHIYWJ7HgDBuszINbq0ilPjxkWMK7P//5zwBRER8tTRNfVxWLtXAK2iefU4pwxCollAOWMRbA0RYWmFcvsxFH8ry29giUrIJPm3qBGUFuPqoRMmqkjWHm+VhBUkXhi/VkMFdry3DHqizxbVrCtujHcdSgBVYs0UOiV2CfzNYrAMtaxcmssMIKMNFPYKKt2cxOR7lMzE+LtFgVx6IrGLy+BEYK7fVAJF4ChdVGugHLFdQuMQzwDSNucop3CupCCrIQpL7tpa9SCM9iFZdZa20WjijFZo1or/bwUXUA6fsF3/haLZS8CAsuHzTVoNZC1Xm4Romepm/oVBrdEx5HNS43fadJBz7hhBOkHWUVFwC78sorQ9uAk9k6MKtUUVPKcySl+K6rQMmzLI7oPOBlrbVurDKkIUDBEmKMj9YZdN+o3KCKUiARSAQSgUQgEUgE2ogAaoLoIKkINBKPCuBhyJbvpOJA2AMKG18YRafMTokvfSLZ2A8ypAgagangK0g/GZlYOG1y0CPKbRzEMyKoaWl2pBMbw06QMPLIEKIphu3rlYLl2Ke1/JBOpRRRqZVhcC/cF/uxsCMNiAvl+JPVGC2gjtlwZJdddmGeBQoRR2arkQa03gcsq989ZY9IMwqIrSLBISaTJXgnhZb5wyB9JxXVo0G+VRFhsvPOOyNn2CfblFXQIayOMapgAG0QiE24FMtnMB9xfT9hG75gctYQVJYGMFo3nT0wUbX5GLgdvyzIqBa8U0EuWF8fzzN3xYL0msNUIiMWrG7HHXckTL/ivrpKEvOzjj5SjmFrJiHkrbbaSr7qbEZT2td3WC3TjhkDChcMX1BqBltQHJvUpn5yhPuBQDkaXliEsfQKc2MM2DBUMipCSXlhOEHA6MsmrUYA8vfQQw/lvvGMZeOFwI1AjIi4Zp1Hm54Q1bEh2ohCNfJCe+khOqRBERZLCftZSFJ/MKShxHur0hpCfrEKe+51oqcH8steN9OImpJmh0CHhRvYaH2HEHEd2HiJzVrBmMGgFP7GaQCsfsEUm+cUm+k0XIEzPMGrauZxX9UOqUJZ1Rlz0mw8o5dGx6uW0u56PvsNQvjoDNLfGCMfUOxRnCUsdy4ESuFXI/sk7o2glDKJQCKQCCQCiUCnI4B2IGHYHmaAH+ATyA3uy25EHDtEr6VFglFMYmYhxzdKxYPxGAyJAMLhq5YolBxMpeRQTqAwJ2FvQUoUmQCSV6CR4xCuQ5K8nwqqi4C9en2VE2tBZYwl1CKHAJqFswpD+qkIMkQemxeFdVSaKvvqd0+JyVEXCihSizahbiq1SbA84uscFzWnRD55G52BCU4vlk+zTRF72oSooSHBNn7ZqDKkERWWFvjH3VFVMniz7yuhZYgmtYojYcgfMgd/vnBQpei+oQJ2TsYQgoxMUDApFilXkVLsZAMmVzzCQZkaiHFcQaSZp4BSF22YHx8lOGgGET1IfxySUMR7DoBlKhmtaZMgEEfjK7n0hxK9guXmLIkl6xiMoZCP7NGafA+bDSEoZCfbDEUMxujUzXB6z2rCBXDBVleMtiMcbcRyOhFfg0M2C0LTGV9phQC1LIE2sovjGq3RXLXK8IBMeGFPbZGPzkAejIrzURvZMx7JDgctqc41VhELG4yjdID4ViuTyFNrT17CmIE7hhnFkqhFI+rAuqinUgZvRkqK0FktBZx4RsR+zRT9TX+GNpN0IZPHgGM8o1TUS0ODWxL3BoFKsUQgEUgEEoFEoKMRQHfMWxA7xGLRGsQRzUIZsTpUUjj20ksvxeRwLLwZa8TSBIZxC2wJo0JWxCAxVPlmPnAVccFsSg6iJgBJG7bqKP0EcBTMQ3GbTDL24sQitabEIKkRm5dJD7om2iqgK56KuGCQNGAz7MSlhEh9GIgLJjwIZ5owozjuSIxtNAgt+3zprrvu6guvqKQczA8dFOc2E4OP0tznRahVipEREMVKydsKJoTVhZkRY4w9HExNEXfHzEgKuNJGrfwgbcLYZkqQRMIwab4IpfOFsExVEAMsX0Rbha4hYOYG2ooXAk1dfhpBKWJitFkZqCRYHGVnwIgEh0ceXLAK3VSLEDIxfplxxEKMU40MMCTQQB4mqDHwZAbfoYHjemqBfYZVQIgGqh5FlzmCfeoweoUi/DXSkM9OCEOe7yxhp+oMUaQNCczJodljAR5xB4x8FKXmMiVan7PoqTQ7o43MpGI5ebYpwnePYgwJ9MDAkIVMZR55GBLoa5VMCm18YVvI2zMy8inRBKCIXqfzYOqMhxLeb5YXxMDrcYd+61BpKe5oAkrCDG1BjyqitxhEKR59W5s6iUBhkAA6bUeyphSs9GFiniRowTgH1Yuma3fg8B0ITiXtpa4wvsF9EvcGgUqxRCARSAQSgUSgQxFw+2eZwJ54HhZlKi2SITSIGImIW7xFANIkEHzI/AQzFjAqHMuDe1/6FKHETvBCGgiYaSOsa0KLnyiFAHzkmA9DEtfBp+mXxk7UK7JoT0yQVRFpHA7RQVkQdDmqRm4k2Gb6AWPQHbYh5aKV9syOuLivZqJTuBSbhW/NbWCYzWiBwcgZe3Cy2MI84xNUT2jZVBOTLlA0wswjHIYpjoYSiwiofOQJRMxQhG0R3Q+KibPiUpilqnF0IWHafAJTCBnBVSNr/aSTvPh3+MJ3hzhOM/0GJzYm4Y4GSGAxQ0Ma/szA3swDwdtWX311xA6DjK/Swp8j8I9Ab3wvFr83kvH1WSwwQrPyeUcMFJrYZJvyBVk5xmABCyPVCEM58tnA5rDTz3IUzqDALKNXAEqHYa2hlFq0ixFCfD2XnQZ+YbNXAviiA9gAJaTNSIMKU/xpMOoz1CEjIK0uW7RReEQ/5moAqQoTpdTCu+gPxFjCfmjronramWeeKVGs4lH5Uq/+A2Q9kDw04Cxh4yNKjVvL9FOjS0MYSvi99lWpoZdMkjZK4lut8KFTF4W5qrWvFmEqARApQri3hp4+ABNd2lHatLt0TSm1ay+o6mCaQB/zMVpzeDSEWghzSo0GonTSEJob3DfN9BvUm2KJQCKQCCQCiUAikAgkAgUBM/sxVyMTdLZZulaUdHWC4wYGXfQFXIMr4xAjHNzdxH3Mvu1tlxH3rj4F0vhEIBFIBBKBRKAnNA4F4d7Yi0nLicyYORBpAg6FWI1kCESmeQhRqqowCoaGHtXvLMJdZBTpq7lYJWGLUlUxmfEzDtkXsUiHLz2FB9iqOsPIKFjURrlSqZ9RpCpWdBMLyaJWIrYaPTKrYDoaBWv0hxhJ+Vi76CwxmSEf+aE/9vJl2mrMKGrlh0DIFEn5Gi40h/JokaI8SoVAlKoeiuqi9mrVoYq8RKTL0VJcoqqcgC0qUkTCz6jRT/HmMrklCjrao7pXsrovRWRW0yGjrK2kJUpafuiMvZ+leEmXsg6VdFWDTJvwv4cJ5sFb7KiwdmptjtpXi5S0hEM1lZKXH4diH8V785rYZcS9CbBSNBFIBBKBRCAR6DQEEALh29i33LZm1TYr33KDx5vCvq3fbxP0mznesBob/mbEfWy0Y3qRCCQCiUAiME4RwNq9z1emXnhPzruV8SaikJ7XDR3F20pkEUwRDpSQL22TiJ/2JrVb39r6g8oWtV6wMznb0dhEc4m986vnZcFLL73UO4tF3iFqVWqTKJI9lb0TrZSI/N68/6YVKfZUDxEOgyNRxPwstYR8FJdfikdBP4vmavEipoiNdya7S4RwOSoRpYqSkImfPSXrWlLKhsKixE+T+71JGRqEeKP54mcRjoS9FyW1jnUzvUsQgNt77dL6m/GuLRllzfj3qmsoIaB1tJFod+TYM4BJsVUzS40OFbHQ6WccjQQBSqyO4sXooi1UEYviDoUZBGywtSfjaFVnqavoJ0Myqoi0Q1G2b/GiKgQ0X8FQTugMbUVtKRJH5UtEdVWP6InMcpQeL86GwVVLSkUyYyuaaw7FT68HeP/1HdlG/yZxbxSplEsEEoFEIBFIBDoNAQwAY7OmXqxTzjzM7Mc//rFFXaTRwV//+tfm6eJt3rcLkiffe5DxOqYcaVscos1Rs5DxPwk8zzoeyIc3CNFKC9s5FHyIZu9feneTmOU4LCuJx6DyilBik0+tWmwSfsbWU1lvdZEI4UgXAUXCnmJeKCQQOZEoYn6WWkJVcadoLqrikH21eDEmbPDqpFVWpIsjBPy0j1JFiUzp+Bll61hSykZ1UcreT0xRO4YGpLwQ7qiUQIhJeGHUep3ytYt2jxVmUHmL4cj0YrEVVEKPbxgZgEVau1gkR9+Ij3DJ5BqdTIotxOxLRXE0csiouoqGtBz5xLwmG4miqhxV3DDSa74SUaOXOxWRLjqrwqV2maVqmZEOHKRtNcUdivwoaEVL49XIKTollJIZiQY9srpOlCr+qsI4tgyBiiWloqjXXhEb+XKo+CXf0j3RfJFZStVP/Pdcqi+XRxOBRCARSAQSgUSgoxAIQmCPUlukImxDEaxoEeFAsVuro2AeBARoI6ZL3oJ9F198caxhh21jORH5CwJhtRBL+6211lqrrroq9oOjYGaWiLFsn2m+wWitCWhFEfpViuVbvdHaHVtuuSUSg9mzQb61UCwMYm2N4JRyRFvRStXh/cL51h4haZNGPcP+sC3sEayNtQXJxFEEV9U4q0PWrAyPqLWIDSVkvErIQrFM6dDMDGmjCwsUqjr4FsKEH4cYrLw2Kj5NPhBQu4XwQ0MMSBz1kzGXXHIJVq0WP42ISLIkwvNyGFbHkvCxWBI++slgqiyrQoPNPPjibw1iGgvC1irROlrEEuNqB6ZhG/Ct+rLKKqvAHCmErcVMGE8DnQSsKamIsoqEm8ZdiD5yr2+EGElHLfPiEIiirfUBsXyws4oYGwIrOTZNwCQ9hDuBsH5FElY+TaUzcIcAzTKtDKMI2KUL5tJW8jG0YG3U7qdMRUjqqDGMsSAPe/Q0+cyw0A3iS8xW7T98d9TKMFZuIWlroUeM4aYanQj2lLO5WGK8x3IPpmQ6pDMUH9lQ7cl80RW1QiDTY2XDWxL3hqFKwUQgEUgEEoFEoJMQCOqAo/gYpGXmwjTE1CIYyDT2gOZaEc+ECizBEngoLDIhAorHY2P4NM6BTWKNBBQPPof3oH14G7aBxNODAiposzReRNwxKh+Qx8PoUTUbROWR8hVXXBGHC0tirWtLPVriMDSbYCBIjNiJ1rMKlVELroMmygwqzzYuhD1HHnkkToxHWrkydFpWz2hBRSgRjzwQYC0B3E5EGZVnBpOQcnbiiNYOBwLaik+Hp8YhiuDf1hAkj4fZCwN7RhGkUEXSPJKAsOKWfQy4oMpOqkw7oeQPf/iDMDl7cNkwD2mDSY0lJFFMmUFtYc47mActxrMpZycGH0rgHAn7KmKKEMP5yEvj6zR74RWGhmqEtZRVCzUZDRrIgoyWvASvQwi9NyytIC6zuIZSa51Y7JKn0UZWCOUmQg8utcMWyFpQ64BdXZqAqfoSzRg8+3UkIxnA8iiKOBTtCPmiWYLvGg4OGgjmiusGNngy0vCAcq2glCA9B436+GgAQNLnrqKxNEG0OPD1HIfsNTczwgVluWa8Gki21iNucqS0ERz0vbAEUPqVponnTkZE4aMc3T56Mgz5ZY0aGDKYkRxvakvi3hRcKZwIJAKJQCKQCHQWAiKL1pxGEcIsRAfNEgfFpfA5h9BK7BPVwNswcjFX3A7FwcsVsQi35fnwHrRPtFIOemRCxX777UcDnieOWOgFJWKNtGGrGBhGheTh2WK91qs2hcOC2fQEf+oXJpFsS31bHhuVtDAiRo4loz6KYDMWwLZiulrQPjnSgsRi+eggbXIMEjbccEP0kW3EED68zYraDlld29LjtjXXXBOdNSqgVmTa+u54FT5t1W2eon0KAk2wk9lBptkMDXwLJ1MR/QVPwlYTX2SRRQyH4AYodbFfvST9FCmPBdT9jEFL1RJMmpFYO7pGwCCBARbRZ4m60Dg6GezhxkDB14IY3AycgG+zaPpPfvITABq9cKFYqwqNqEU0tHbHHcHLOwWtxK8DWE8dtuEm4eoWmeyxPDyPNP36668PZ2kuk4xIuXyAYNubbLKJFRJBoUaO6yTWZTecM66Qqe2UgiSISnVktIjWYV7BnOMEDCEsb68D0KnRcXd9DOzA0b7GYMzQE6z1DskYCjrqmYOG1kXVhfdjw+zU+VUqEWa30COdQT9hOYNDebR4WKIVVl55ZfYbezBeo5OEttOEy5zSyjDU5510+h4kw85qKwyaTuI+KEQpkAgkAolAIpAIdC4CCERwiDAxpgqYxyJiKgexwx6wbfmIAkYlLog9yLQ5im2gkhgVJUGwRCu/9a1v7bHHHmglmoI2IamK2yQEqkUQ8RXyviAjfo8fC7tiqz7ViaSiTaEHwVKRDWkO21A0Awn12iuOtQRps2cAOisGieoZe4Q8yoWVkg9iqgiD42h81sdHbVAi/BW7FdVmDM3KMoC1ErHHt5hdPJW5wgoryMGoxEH5SzPKSJsiyF98IidsUArLJyDKGzSUqfSL8qJoKKNPYLJTFeSDwFUtKWbQoyDECMvkV2BIs4KhM2qs7msQ4zs0QP31r3/dN0fF/gn7rA+OKEGYO2CXALs9SQlFvISASfsIKzdj7hCDeeoop7RymEEJ89TCWn2GgA2HpsFggNl0BlwkFZETbU0AmQ6E+aUKOqOlFAkZRSApXXz3BSVjADX6ohOCa1RDOTFbwU1aET+1LJsBpbvyS4t7/oDQa0dVyDcwi+L28VQhlLTWI16zJza2aXHPo3R7TySij4XxxKJ9o18Bh9cAYSqB6C1sLrDLbHD7zwC9QekUSwQSgUQgEUgEEoGOQgCHqNqDEwh5mv+ATAjymbSAWGBFhWPh2WgWbioWi1Kb0OIQWlaUKI7/IRzCh95G3WGHHWImNAHMA2cygeFzn/scEqbU73//e3FEGnB3pMTcDBwlVBk8FJ1BUNSLCBLGd5mNylAiRs5IZREd8XtF2Ib7qoslhJXC1UKV4vLFWRnvECX2N998M6dCRvzVeABrZDxi5wmAKsSb1aUseUclTHjguDEGOuu5RGGcajE4gSF77KP2KAgrmSK+rBUx9QVZjptFE5OUwkE8ks19LRFgNn9DccawLUYsascv0WJTzFXqbYTwsbqvQYzvHIkWBLWyuLtvmhpymCOE2hpTaXRjNsFynJIqT048rwDyCSecgMKyzZdTw1ow2qrVSUfTaFl1aRE/gcNHm16EasMBjLqHxzIOUeVQGCbfFlArqx35RUPpEmoHJmINc7RVLciuzqavQsZRDxP0LjKovAbS/XjkJ2dNoNcciqjRowPGSKvO93ej/0R/YJ5hjMdKxBxtuUfRM/kYGGpx5sVPQyajYgM5jusnBsl8dMgQCAgs0aMIG2eeeOKJvOYF42vwH/Tnf0L9g8qlQCKQCCQCiUAikAh0PgKIAqKGOngib4I7fiBKjTcIgmJyyARmidg5JJSOb2FOeBUxgdsgOjix4jiHn9gS1osSKYJ2CFSjkjgowicBDbMCxLwRONOXyeNb6GmgRD7IjXwaZGJa2KrZI0qhgGK98rFJDAY/Q7XJY6JsY7OxB6sIBzGKqReIHZqoOlM1cHTxWh4hfMzjjrRJxjilaRXk1SgGj06xCl1WiloF6aQZ6wWIl3rRaJOzFcdoFSFpH9WxXO2GE3RKqAXjpARWpt+YPGPGOfsBGDSRKvPXq5YY53CEwuJjDACKJZrAKIJ+m7ZQo2kwXiSlVqkaxNjGWU2MF6pRs8LNwIyklkJYfSdIdZ4GgFcLylcEyDIxTo9QDA8YH9baayMyttJqPFIWPngzY7QXC4WTUecAkEKmylQLMNkDbbQ7RiOgQKlRc07BChT6iaP8VYsWp8QAowZzzcQRU2UE3YFgPANb8vTj9EaANDBJvWEY1/QTeqLJYEtScc9h2COtJ4SPlLTWI47oGxwxt4cvcNDiMgGLtTv1nA6eq8Cz6iMbGB+DOsV14+g/0mg9Ixvfkrg3jlVKJgKJQCKQCCQCYxyBQndQumDbHC6Zxfm+OeVQs4nGVQ0qaWIxnmcyd9hQ5EuiJr/G1BqxmqN9f6Kkhe/WaGaJeL+wd+gsmquo9lUYR//4xz9uvvnmKF1fgYFyin4C1XSRr9bbr0CRbDARk2EgYBRkansjpfqtV6ayRgihwRMMy+NI1+TH0YE0lOIhNrR9md6DeTfoUbUitnlHwphHQL2KNpkas2t+VpU0kk7i3ghKKZMIJAKJQCKQCHQNAsEbYo8lhN3xE8WRU0MsZFZzpOXYFKzJDyrfb2YE4GuIbF/IalhL/KRQQtmqbQyoEaat5BTJsFPtEkLR4tkiysVCCaWYTV4ihENPyFSLDzRQiUpLjVU90rYQiLQ9zSwRp0dqi85iSZGvqmVGWGLvgYborKkmobCIOSQdxUOtn7ZI0x/pIhYKZSoiXRUIzf3uyYeGanFlo5bQIy3S7PmDQLgYf1QR2qKsdLVItaLQLyearMZ4oWi+R9WlVI1Jkd+3eOl7pYqQrCnup/yqeZEOj0TxvQoSMlF8UI+KJcLwbIgnFeFCOdTXhsip8TRqrL9P4l4fnzyaCCQCiUAikAiMcQTMxzDHgJN4BuZk9gg+Yd6wKSvy0RGHkJuY8oFp4RzBdYLTBMuRtgVScmx+2ssJciYdpVSHXmNI5lSgtoXckCwyUTbkZZIx8cCblObwyCTZU1mvfkcjHVWb/03A1IXIjKP2cVRC1fbYFbGQCT1+hmsqQpplRhF78jaJkJQgac0Wc0UkzOswHyaEY61Ab9nGT1zQvCMh2PhJs2kV5sCghpET+yoC0kFAS6VhVdgTZsRevuLMtpeOBDFbyXSIcLgmP6qLHD9DQ6ldvi2qK0UkZIZJ1XSoslc8ikiHQmLVNK81is5j7pYZLFRFLWGPNOGwOYqbbaLX6R40x4u2pTXNBeqrQXFKbPUtj1pURLJ4J7NYq7FMfTH7SP+Mxx0hHDKUh8F+mizEi2JV0eBQ2dQiHfvwS9qmrIKm+kgHqqVIg4meVs8tEUgEEoFEIBFIBMYVAngDf2O+uxW+zTD2E1XyoqdpzQLGVr8234OYmbtm6JoRjn/Y5GAwOEfwGPvIL7SGnsgsh6IuP6OUKche6cPJrNNCWGaojYIhU62FkVaKROaIkSnVhYyfUXXUYuK7sUdVYaglY5PvqOng0lGvRLXeqEsmKOTHFgWjInub/EG/L8sePg76fVmqqghIyymuqSvSxZJiTPjba06PTCQcLelSJCCNn/ZkamostUgUgaIqTJLvaEn7GYQ1lEftqq7WHvzY3mJB8DSZO4yPIjTY5NgkwgYJRxFoE42MizB161GGVQ7R4FCYEaVk2qRDRiKUhxnSIeCozVH5RcahqrUmWZkrj7WHZBQkXCMvn1jpY1UN0lHKPgr2VtvTOpHjpzcNjD8lim2lSIOJJO4NApViiUAikAgkAonA2EEAscCosGE0QoBZgBO9kBCKFvKM1bu9QorH4PTeMsRoRYvlK6iINbPxe3CIUOLBDuH6fgZHQWsQL2WvuOIKL+Ep4pBhgJVYIp4ab77G4n2XXXaZhThCRjzSEo0i8X6aMWJNGCzfK5XeWTR4iCisxJW9X9Ak45A0GXVF23g5UmTXfOWglSxhkoivzWuLhBng9UdpbzfiheEFj1TBFw5yjULKwxdq+e75g6ELH2kgLNNrl/W/L0uD8cmg35dVC52BEnYLsUADFAYhYKSHFwGvzCqqgsQC/1ZuibpQTwLS3iU1jyXs98CkfCM2crgJZLaRlKPG0KC5ZcKNEp8INeogYD0cU7cDTCCUNARkwl/Tk1QjSfK2qJ0AesokQ8FoaHs5fsb3RwnYgBl4alZlKWQSMVxfi2C3UUW0r+7qgQms+va3YrlSJilRFZbTBiXNCmQvtspXXem9IQYryIOaYWpUuz7vEMx1j6p8AKj/RB9Tihgurr/xRTr6GyP1YWX1GSxfvqMcZDbQ4KDVLrnkkkC1B4VmtiTuzaCVsolAIpAIJAKJwFhBAJ/AUXzr9JOf/GSsQMIzOQgHRmKqMQKEs5oybrYDdo7HIHmIL/bmcb+vhOIx6C86gujYF2B85BJV8j0mIVKkEA/G7VArMxDwJ8RRLVgLA1BzLEdQH02Xb7lxdSFSFCJSyDG18tFxVsnHKT0KYAnegwlZSBGl88QguBoD1IVU2avIz+BkxgzYsLA9VdRi7bistCUsrWdiuRhElkc4Jc3VVT6CWhlaxDJ/KgII92kGEWqIFjPJ7Bc/m/2+bCjnMuNVjSCyxwADC+SCb4gimpgfNx1iJ7MxTqZCzwwcPhKofscUo/XFJZKKgxHgOCtrEU2l+BsNBFJ4ops0q1HtRgi0eYagFWClURRXRKMT08rqZQOFNIAu9OgJA30HF4zAwdpxfbWwByEGI9e0oybTLkVJ+LLPPvsAhL8aLgZXhpEqRdzZFsyY5RzU8Wr6GxCYTVIV2pGdmhsOLOcFBw877DCV4uUhw30KHWWhEQJtPNXuQamVRayVEvJXRHUA1AFoCArOHh4xEm40oObSquZR9DcwKtvv11JZZYAEVaoCyegGgUYj+yTujaCUMolAIpAIJAKJwFhDIFgI0omvlAf3vmuDSaCPlga3RAYGY507lFG+Zcvt4ztEGCG+guKIgns9Mb69KpNOfMhEZOtyYLS4DgKEPAnkK4vdonSoG+qJJyH3KJGlD2lGj7Afy29bhlyOue8WBGQJuqkKaxGacB8NIOELmlgyLmV5Sl+gtPoezXEUJ5NpYRlMTkV+skotQqH0+GznOuuso170TkJZArxQNQ04HMdps+JklU4Z1fi4T3zw1Yc8kVpHqR3O92UVBwKI4GDxGWMnajXEuuuuyyrklQ2g4ClaCQrsVqU2PJikgoZMylrR0pqYqGR8xxRuqGTM4wc7tOk0vYTxQAiIyNPDKSTS26WwUrvqTEP3SSlc2fKOgAIX2m1v3UOQMlgRaSM9TRyqtGnAssr/fgdXN7D2vwcaOgb91mkBr+IcMRhTXECaDRIWmJfQBFqEF9Y1Zwa/POTRA9WuObjGZZ2Qtdi8rlXtbyxhfPmeroogQKGWja+xKksVVPVni8QbQ/KF7zbNDWH61avT6upQYqF6Ac4MwvBnofEech+nTPQxWMFHJgelyXOKFwxgJMydWfqYvg1SRD++lqq9AopAkvGhM/BsZJ/EvRGUUiYRSAQSgUQgERibCCBPNr4F5xZox3GRcrTDzATkDytyCJVBX/B7wggN0ukNS8F4bMyGVNmHHnv0BWWPHKTNYtuIlBAsMVSyDBKotUXV9grGIaMFEWisiDyOZW8LSXwoLJFgTzQJY6JqP1XKvMhXRDSdF/bYUmQSIB/pqE7Z8Aij5VFEpunvMa7XPGTOT7F2mKhUcXskcpjfl2VDMRtnRXPVIpN+1no6wWzuk2Gz1fTFm7FYP1mlmVhLjBmhxD7cUZweRQw2HLW6ub1HE7g+5aiqN2jZHw0RZcWARYgRVhxX8fCajGGAVlZQcWkv3eKm5qKEgOq0BRvs6VFWjkP2ard2Pv7qKGPCMIeMtWgIp/xUiiRmzDBc3OCNMLSVgrY9iiyHZnvCkUObHAXlBIb6G53S2pr9Bh6AwsLVpQOTZ4mjDtlHW8c3DYBAD0/Rbu1OIWFd1wCDAQyjSqUKwiG+xkqDItU+FmiEfqUc0nAs1IJUMSzcV0vIOCOMdaEKSTnNbvnl1GYRS/lEIBFIBBKBRGDsIFBoB5dwCyQDjQsqhrIEG0M+UBD0Bbnx6SVFpO0J4yjBlggEKPKFutF9oXEUR1lUDEMSBsY1KXdURQqSkRnzQ5BCpFkUGaFRL54qVC8Oam4DYRQq4p204UZhiWCtmRX4riEByahdcZFU1F/twvz0m1xBicGDsLrZMiiauqRNCBEHRe+E8w0S+MJyHJewECltPLLAjgTj1Ys7slnV9jJBgW0L4q48pO/L4ppoougybSwx5UasXaDdawCivFivEK+6AigJdJCzwsPshyqIwM4qZjAbj4/vmJIHsqcNihBz1OQNjBxoQXMVhH98GolOdcVsGU8SWEKh9jV7B+Cg477ZICqCAMRMQdGU4T4EqJJWUdhABnrxHVwm6UKERbilQ8xeEThjwOaKSIOUHhgap+24447mVgnn6yHGadrOsx2+SNCgLdivCvKMjBzp2GgOy4FDP8c1okcT+LpDZEAnzXHRcYOHGAawVpczJlFESF4I3CMXnYG/Dpnuoo08eTDmjL7BUzaoOvqYPsM8dXm2wFP9jcvR31SN8cNc1dGC8bVUHUYpasGrYNj2Hx8a/vPfdy8aLpKCiUAikAgkAolAIjAGEQheIuJufgW2h5AJ0AoQok1otIRJ1fIRIKQqPjsqB9ERGZVAfZAbuCAuqCRtiDj5+Lwl8oTEmOKCsWEtuA49mJPJwQiiGKeClKDdaGvwVPJ4ZLAoxAvNlUabKCeJANGgLlTPPASq1MhmTIvBJlTgWOxXrxkdbKNBsFlZTFFdMfne4EEwFStF2sIjCYtOCtZSHhFuNfKRNlSMHjNtTKsQokZAOSLfoGII35cNtKEhlA4WOg2T8GzmQYNfEmrEVsVuGYPnaQIy+H2gKke+TLSVPTAhb04IDFFDMGpHCbSYj7RFjWi92fCYJf4KUm0EH7WrUVhdJn5p2CAqrJZQFR8ljbRpM1oHgEBWuyLwp9zYQ+t7KOFxDQ1ROz0M5h1SyzyNbnK5z76i46oO4s5mVQMQ7WaJURP9GtqYQUNoZaWUhby9eh2q6W8M0I5huVL4NHdYq1lXWmklXddEf+0eX7ENQKKtaSMGYQ1tz1ptSrnNWWDPTr7QGfIBIHZe7WM0GP94vlH6G1/goO8Bh3fGIVqQQrBrWaYaWPpZkGRG41sS98axSslEIBFIBBKBRCARaBoBdEcZtKZOyaBERaDmZ8mPRBzFqLw0ifTjc5tttllf/QMpMR447bTT8CdR1TXWWAMjLGUdirEHGioT3xpISY1JfvaV7JtTLVVztPoz0tWcasFIV49iw0YXxgBIPA5a3KmWKq5VM0u6qq3fzH4FimRJVMWq6SIwOolq1QYqGLkXCVRdza/+rMnv18h+ZfrN7Ld4qzKTuLcKydSTCCQCiUAikAiMBQRwEW4gfyXhZxCUsg8WWJWJQ+F/SaOSZIIKKxJqQybK2ldlFCyaa+RLKQlioUrwW+RScD0yQ2ccjUqlbfJDnk4/zXwQ1hWJF4cWiC1lJWxkyEeRyFEkEvbyQ2HYGfklLSGn+BsJOUWAs34yIArGXibJ0ExSws9idiTChrCqBjGZIu5C9ULRwuRRHfmiM9KlRj+LPaFQjkTsiRWByCQcBks4FGpDW03ByAyxUkQmPaFKuqZqOZTYqI1D0lHET6UiLbNoqOZI2+JoJEIJYYlQG8+LBL8JBLBFRo505Ee6WqOcqLQqL5NaW7VUScsPYTm2YnOojUx7MiSrSJZDgyaSuA8KUQokAolAIpAIJAKJQDsRMNkAEQwuiIeZuMIa/FUk1U8ECGGNo4U5SZikYXoMUkvYnJYqRQtnzHAwHSLIHCpvsoRZGeaHFMngW+VnUV54WDXHEELwnhkUhnnEQrkESZkStIVAjTyBEIu9n4LoJoqYNxIGyLcVY2hjML9CW3hUlEvQELUDChQcrH53Nuwx2cazBfNDYjBAfxQJPWQgzwDTSyBp+gcxDhJzyBYe+SnBWsYwOFSFnpCMfQgX+0ODQ7YwXo50qJUTPyMnMsPToiFkHIp8P8shCflMDSVFm58O9VTZu1VNlU+PbMIhT1gilEfBECi1VMUUjLpCQ18ZM3bImzljGo+jhKvVOdTg9p8XqxuUTrFEIBFIBBKBRCARSARGB4FgTqbEeMfR5BZzi8WVy3deMc4///nPJqMTOOGEExD0YE7BLDEkL31iUeaseyMweFKQsCBVtJnyHlXIodk+ytpHItxUylZVXtynPyQdveKKK0yzDkkC8kspP0naJGTakze1PWh32BBHy56YNzj56Ki0zaGSjtGI924jQWE4RSy0SYRhcOj3u7M9Gnt1YuQ0szwMDlNLWWuNO2qLHGLSIVM0RI2sNfVIuqonJGOvYLG/aAhtfkZO7GXawrzIibqkqxrKIYnYipgEM2TSE4ciYR/mxc9I0xn5kVnkQ5ujoYdwCJRaIj9+OiRRNNSU9dNUeH0V2uFC0RbVNb5P4t44VimZCCQCiUAikAgkAqOHQNAg7zV6eVEw21QQ09lRHzmMEC71hqXFWCwVggxZXoY8ASsACiSbRWMGPE5vzZlYwRBzws4VxKIs9W0TXy/OiCvbMGlhbC+bYtUSjiLEXp/1WiHlaDQiK3QtP/hcyXHUcwD6PQSQZhse721LaYYJeHtrVkH5fkal3hz1mqlBBRkGM1U++8kIxjNAFUHvjD1YK6RN0ndJHUKgKVTcW8KhzV6NXpokozrLqvgpyivBfQACjWY/FfeogR6vSLLBhlDyy/oqjKfHpHCL27AnyvLRc4kQ80EiZcmovYqSHNCFtXC2cgsb8Hj5ovWQjPEV2/D7aAUjCn6Fv0D25CQQUJ0xFYN5F1D7CSWLRbK/qoFyQFnrJlrKUR5551i+10mZ6nEBtTK5HDJ+gkUT0EmsTstCG7bROiRZBcbwXWbUIp8Xfpp2RT+DlZLJEprJsNZPvjBAa+q6UJIJGaNK79Q6Gh1JosEtiXuDQKVYIpAIJAKJQCKQCLQBAVxn2223tYYjwm2RkPKdVwQID0OS0D4MHsmzjofFDeWg7JhZzKjBJs3fwKKwJeyq5ouedHIJeVILooZLCcNjYOgmhidfVBtLtmYLtiff4MHAAG1VCi+8tPe7pKpjicUlETscjhLElzHeGVWpqq2+cvnllx9//PEUUhsgGgwg1igmGQIKysdr5VOIETpkVROUHTWUyRKcWC04sUzCJf4tbQ1HLkeN6GP5Vigz0G760WXs2TMKZh9wwAEcpESl/A1VHMQvKcGnzYqR5qbBjKMIvZ+Yq6qZAWFeyKHEPuipTICzP1aV4YJSHgj84Q9/YDzl3JSApFZA+oEJE9VpIK2g+firLhq00VFHHWUw41kBDSThbIkY4wFHAwFGAtM3U2mO5gD7cccdF+MBwEaCnRxnJyWUW7pRvk7CSMxevf22LMnDDz/cqAA+qqNfo+tFKlWdT8xCMkYCCDqrjJfiq7qXXHIJqwyBNI12NxTRJXjBF22nXQw/tAg93nvmfliuiBob3JK4NwhUiiUCiUAikAgkAolAGxDArrAc0Up1I5RCv6hejR24O+aNVHnf1JLkqCqSZH0VS8dYdsb6gILfyByKWfNFTwVDFfKEpOJb9MS3OQljkzgZSkobhopGq9q3QiNUz7Ao4uuYOKuQti9l+uwrtkcyvoGKFi+99NLIH1WsEmC2bqAaVWeus6VOFCGvuHoZQ4apVre03E18Qgj523jjjX2b0+uVqDamqzj2zAZrC3LNT5wVraTKQu9qZJV8GuCGYsLBCozhZvnWKS+sua6goQhUFbQ+43bbbccAi46zBKfkET3yecoF2FrX3DsA2LO99wrKF0wphwxOzEGO84u/imsRnqL7alEdKh9UNcYAPg1rRXmcGJ2lgdnqBQVVll9kP5c9GbC3ciIQ8H4sHAmm08AAdbYMpbq4qbhM1ioIFh75qdXkA5OdXPAkQX58PRd7pk11fVtWuysLMV9jZaHWURBQugH72UOhHkIh5Vqt+lVdOR71RJ8RpDds8NQCUNboZBsNurGWAoUBicEexGLYo2CDWxL3BoFKsUQgEUgEEoFEIBFoDwKIlE3dJRHpIPEoFDplfRg8LOiUPVYU879xI4QJF8SxbNYXR57kSMss/gR/ko+5ou9IITEK7VWKO+JqKLij4qnBCNXig0EoaeRYSD4qlR/aJCjEsAWY8TYf9xGgNZCISjFUCQIhxloJoXFl1esQC4u/YSqBGFrwggAKGxWFQnsCkUaC46f4Ot4c+crGhBl7mh2SExo8IvBMA6c0bMDLHWKPghI1yqliHhyY5GgYSabGkshHYRFugw0Jgxk65duMJVB/NnA/ykoUBFQB9sin1k9F/JSwFQTIwDYi347K1xZ0enKCNFNo45H8aE2HiIWkQ3ValmQYQJibfmosVXuwg9BLyLF3lAH062OGBNH9Sp8xqNDoBcBQyBFPHgJhh6o9sMeyBrb8cmoDIKVIIpAIJAKJQCKQCLQPgUIKS4ItSA++HrMp8CE8CW/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"text/plain": [ "" ] @@ -2035,6 +1835,406 @@ "plot_outputgraphs(OutputJson='none',argumenttype=allocator,graphtype='allocator',max_size=(1000, 1500))" ] }, + { + "cell_type": "markdown", + "id": "7411fd77", + "metadata": {}, + "source": [ + "## Step 6: Model refresh based on selected model and saved results \n", + "Must run robyn_write() (manually or automatically) to export any model first, before refreshing.\n", + "The robyn_refresh() function is suitable for updating within \"reasonable periods\".\n", + "Two situations are considered better to rebuild model:\n", + "1. most data is new. If initial model has 100 weeks and 80 weeks new data is added in refresh, it might be better to rebuild the model. Rule of thumb: 50% of data or less can be new.\n", + "2. new variables are added." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "cb6d4a8f", + "metadata": {}, + "outputs": [], + "source": [ + "# Provide JSON file with your InputCollect and ExportedModel specifications\n", + "# It can be any model, initial or a refresh model\n", + "json_file = \"/Users/yuyatanaka/Desktop/Robyn_202408081618_init/RobynModel-3_216_3.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "fc37510e", + "metadata": {}, + "outputs": [], + "source": [ + "refreshArgs = {\n", + " \"json_file\" : json_file,\n", + " \"refresh_steps\" : 13,\n", + " \"refresh_iters\" : 1000, # 1k is an estimation\n", + " \"refresh_trials\" : 1\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "38581da9", + "metadata": {}, + "outputs": [], + "source": [ + "# Build the payload for the robyn_refresh()\n", + "payload = {\n", + " 'dt_input' : asSerialisedFeather(dt_simulated_weekly),\n", + " 'dt_holidays' : asSerialisedFeather(dt_prophet_holidays),\n", + " \"jsonRefreshArgs\": json.dumps(refreshArgs)\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "70272838", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">>> Recreating 3_216_3\n", + "Imported JSON file successfully: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/RobynModel-3_216_3.json\n", + ">> Running feature engineering...\n", + "Input data has 208 weeks in total: 2015-11-23 to 2019-11-11\n", + "Initial model is built on rolling window of 157 week: 2016-01-04 to 2018-12-31\n", + ">>> Calculating response curves for all models' media variables (5)...\n", + "Successfully recreated model ID: 3_216_3\n", + "\n", + ">>> Building refresh model #1 in manual mode\n", + ">>> New bounds freedom: 8.28%\n", + ">> Running feature engineering...\n", + "Input data has 208 weeks in total: 2015-11-23 to 2019-11-11\n", + "Refresh #1 model is built on rolling window of 157 week: 2016-04-04 to 2019-04-01\n", + "Rolling window moving forward: 13 weeks\n", + "Time-series validation with train_size range of 51.45%-56.42% of the data...\n", + "Using geometric adstocking with 20 hyperparameters (20 to iterate + 0 fixed) on 9 cores\n", + ">>> Starting 1 trials with 1000 iterations each using TwoPointsDE nevergrad algorithm...\n", + " Running trial 1 of 1\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " |======================================================================| 100%\n", + " Finished in 0.58 mins\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "- DECOMP.RSSD converged: sd@qt.20 0.013 <= 0.046 & |med@qt.20| 0.061 <= 0.21\n", + "- NRMSE converged: sd@qt.20 0.0014 <= 0.029 & |med@qt.20| 0.098 <= 0.12\n", + "Total run time: 0.59 mins\n", + ">>> Running Pareto calculations for 1000 models on auto fronts...\n", + ">> Automatically selected 4 Pareto-fronts to contain at least 100 pareto-optimal models (111)\n", + ">>> Calculating response curves for all models' media variables (555)...\n", + ">> Pareto-Front: 1 [26 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:01 [=========================================] 100% | 26 \n", + " 00:00:00 [==== ] 8% | 2 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 2 [25 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:01 [=========================================] 100% | 25 \n", + " 00:00:00 [== ] 3.23% | 1 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 3 [31 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:02 [=========================================] 100% | 31 \n", + " 00:00:00 [== ] 3.45% | 1 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 4 [29 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:02 [=========================================] 100% | 29 \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Creating directory for outputs: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/\n", + ">>> Calculating clusters for model selection using Pareto fronts...\n", + ">> Auto selected k = 4 (clusters) based on minimum WSS variance of 6%\n", + ">>> Collecting 111 pareto-optimum results into: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/\n", + ">> Exporting general plots into directory...\n", + ">> Exporting pareto results as CSVs into directory...\n", + ">>> Exporting pareto one-pagers into directory...\n", + "Exporting charts as: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/1_107_9.png\n", + ">> Exported models as /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/RobynModel-models.json\n", + "Selected model ID: 1_107_9 for refresh model #1 based on the smallest DECOMP.RSSD error\n", + ">> Exported 1_107_9 as /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/RobynModel-1_107_9.json\n", + ">> Plotting refresh results for chain: 3_216_3 > 1_107_9\n", + ">>> Exporting refresh CSVs into directory: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/\n", + "Warning: Removed 2 rows containing missing values or values outside the scale range\n", + "(`geom_text()`).\n" + ] + } + ], + "source": [ + "# Get response\n", + "RobynRefresh = robyn_api('robyn_refresh',payload=payload)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "27fc6f2a", + "metadata": {}, + "outputs": [], + "source": [ + "# Now refreshing a refreshed model, following the same approach\n", + "json_file_rf1 = \"/Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/RobynModel-1_107_9.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "a64db14b", + "metadata": {}, + "outputs": [], + "source": [ + "refreshArgs = {\n", + " \"json_file\" : json_file_rf1,\n", + " \"refresh_steps\" : 7,\n", + " \"refresh_iters\" : 1000, # 1k is an estimation\n", + " \"refresh_trials\" : 1\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "a3d4fbef", + "metadata": {}, + "outputs": [], + "source": [ + "# Build the payload for the robyn_refresh()\n", + "payload = {\n", + " 'dt_input' : asSerialisedFeather(dt_simulated_weekly),\n", + " 'dt_holidays' : asSerialisedFeather(dt_prophet_holidays),\n", + " \"jsonRefreshArgs\": json.dumps(refreshArgs)\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "a043f146", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">>> Recreating 1_107_9\n", + "Imported JSON file successfully: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/RobynModel-1_107_9.json\n", + ">> Running feature engineering...\n", + "Input data has 208 weeks in total: 2015-11-23 to 2019-11-11\n", + "Refresh #1 model is built on rolling window of 157 week: 2016-04-04 to 2019-04-01\n", + "Rolling window moving forward: 13 weeks\n", + ">>> Calculating response curves for all models' media variables (5)...\n", + "Successfully recreated model ID: 1_107_9\n", + "\n", + ">>> Building refresh model #2 in manual mode\n", + ">>> New bounds freedom: 4.46%\n", + ">> Running feature engineering...\n", + "Input data has 208 weeks in total: 2015-11-23 to 2019-11-11\n", + "Refresh #2 model is built on rolling window of 157 week: 2016-05-23 to 2019-05-20\n", + "Rolling window moving forward: 7 weeks\n", + "Time-series validation with train_size range of 55.10%-55.54% of the data...\n", + "Using geometric adstocking with 20 hyperparameters (20 to iterate + 0 fixed) on 9 cores\n", + ">>> Starting 1 trials with 1000 iterations each using TwoPointsDE nevergrad algorithm...\n", + " Running trial 1 of 1\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " |======================================================================| 100%\n", + " Finished in 0.57 mins\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "- DECOMP.RSSD converged: sd@qt.20 0.00022 <= 0.019 & |med@qt.20| 0.056 <= 0.085\n", + "- NRMSE converged: sd@qt.20 0.00023 <= 0.0015 & |med@qt.20| 0.14 <= 0.14\n", + "Total run time: 0.58 mins\n", + ">>> Running Pareto calculations for 1000 models on auto fronts...\n", + ">> Automatically selected 5 Pareto-fronts to contain at least 100 pareto-optimal models (120)\n", + ">>> Calculating response curves for all models' media variables (600)...\n", + ">> Pareto-Front: 1 [13 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:01 [=========================================] 100% | 13 \n", + " 00:00:00 [====== ] 13% | 3 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 2 [23 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:01 [=========================================] 100% | 23 \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 3 [29 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:02 [=========================================] 100% | 29 \n", + " 00:00:00 [===== ] 12% | 3 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 4 [25 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:02 [=========================================] 100% | 25 \n", + " 00:00:00 [=== ] 6.67% | 2 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + ">> Pareto-Front: 5 [30 models]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 00:00:02 [=========================================] 100% | 30 \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Creating directory for outputs: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/Robyn_202408081630_rf2/\n", + ">>> Calculating clusters for model selection using Pareto fronts...\n", + ">> Auto selected k = 4 (clusters) based on minimum WSS variance of 6%\n", + ">>> Collecting 120 pareto-optimum results into: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/Robyn_202408081630_rf2/\n", + ">> Exporting general plots into directory...\n", + ">> Exporting pareto results as CSVs into directory...\n", + ">>> Exporting pareto one-pagers into directory...\n", + "Exporting charts as: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/Robyn_202408081630_rf2/1_105_4.png\n", + ">> Exported models as /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/Robyn_202408081630_rf2/RobynModel-models.json\n", + "Selected model ID: 1_105_4 for refresh model #2 based on the smallest DECOMP.RSSD error\n", + ">> Exported 1_105_4 as /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/Robyn_202408081630_rf2/RobynModel-1_105_4.json\n", + ">> Plotting refresh results for chain: 3_216_3 > 1_107_9 > 1_105_4\n", + ">>> Exporting refresh CSVs into directory: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/Robyn_202408081627_rf1/Robyn_202408081630_rf2/\n", + "Warning: Removed 5 rows containing missing values or values outside the scale range\n", + "(`geom_text()`).\n", + "Warning: Removed 4 rows containing missing values or values outside the scale range\n", + "(`geom_vline()`).\n" + ] + } + ], + "source": [ + "# Get response\n", + "RobynRefresh = robyn_api('robyn_refresh',payload=payload)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "20152575", + "metadata": {}, + "outputs": [], + "source": [ + "# Continue with refreshed new InputCollect, OutputCollect, select_model values\n", + "InputCollectX = RobynRefresh['listRefresh1']['InputCollect']\n", + "OutputCollectX = RobynRefresh['listRefresh1']['OutputCollect']\n", + "select_modelX = RobynRefresh['listRefresh1']['OutputCollect']['selectID']" + ] + }, + { + "cell_type": "markdown", + "id": "735acaea", + "metadata": {}, + "source": [ + "#### Besides plots: there are 4 CSV outputs saved in the folder for further usage\n", + "- report_hyperparameters.csv, hyperparameters of all selected model for reporting\n", + "- report_aggregated.csv, aggregated decomposition per independent variable\n", + "- report_media_transform_matrix.csv, all media transformation vectors\n", + "- report_alldecomp_matrix.csv,all decomposition vectors of independent variables" + ] + }, { "cell_type": "markdown", "id": "eea6f0f3", @@ -2049,20 +2249,20 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 52, "id": "6e71cc98", "metadata": {}, "outputs": [], "source": [ "recreateArgs = {\n", - " \"json_file\" : \"~/Desktop/RobynModel-5_181_7.json\",\n", + " \"json_file\" : \"/Users/yuyatanaka/Desktop/Robyn_202408081618_init/RobynModel-3_216_3.json\",\n", " \"quiet\" : False\n", "}" ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 53, "id": "221abfbf", "metadata": {}, "outputs": [], @@ -2077,7 +2277,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 54, "id": "6dfd920e", "metadata": {}, "outputs": [ @@ -2085,13 +2285,13 @@ "name": "stderr", "output_type": "stream", "text": [ - ">>> Recreating model 5_181_7\n", - "Imported JSON file successfully: ~/Desktop/RobynModel-5_181_7.json\n", + ">>> Recreating 3_216_3\n", + "Imported JSON file successfully: /Users/yuyatanaka/Desktop/Robyn_202408081618_init/RobynModel-3_216_3.json\n", ">> Running feature engineering...\n", "Input data has 208 weeks in total: 2015-11-23 to 2019-11-11\n", "Initial model is built on rolling window of 157 week: 2016-01-04 to 2018-12-31\n", ">>> Calculating response curves for all models' media variables (5)...\n", - "Successfully recreated model ID: 5_181_7\n" + "Successfully recreated model ID: 3_216_3\n" ] } ], @@ -2102,17 +2302,17 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 55, "id": "10893821", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "dict_keys(['dt_input', 'dt_holidays', 'dt_mod', 'dt_modRollWind', 'xDecompAggPrev', 'date_var', 'dayInterval', 'intervalType', 'dep_var', 'dep_var_type', 'prophet_vars', 'prophet_signs', 'prophet_country', 'context_vars', 'context_signs', 'paid_media_vars', 'paid_media_signs', 'paid_media_spends', 'paid_media_total', 'mediaVarCount', 'exposure_vars', 'organic_vars', 'organic_signs', 'all_media', 'all_ind_vars', 'factor_vars', 'unused_vars', 'window_start', 'rollingWindowStartWhich', 'window_end', 'rollingWindowEndWhich', 'rollingWindowLength', 'totalObservations', 'refreshAddedStart', 'adstock', 'hyperparameters', 'calibration_input', 'custom_params', 'dt_inputRollWind', 'modNLS', 'version'])" + "dict_keys(['dt_input', 'dt_holidays', 'dt_mod', 'dt_modRollWind', 'xDecompAggPrev', 'date_var', 'dayInterval', 'intervalType', 'dep_var', 'dep_var_type', 'prophet_vars', 'prophet_signs', 'prophet_country', 'context_vars', 'context_signs', 'paid_media_vars', 'paid_media_signs', 'paid_media_spends', 'paid_media_total', 'exposure_vars', 'organic_vars', 'organic_signs', 'all_media', 'all_ind_vars', 'factor_vars', 'unused_vars', 'window_start', 'rollingWindowStartWhich', 'window_end', 'rollingWindowEndWhich', 'rollingWindowLength', 'totalObservations', 'refreshAddedStart', 'adstock', 'hyperparameters', 'calibration_input', 'custom_params', 'dt_inputRollWind', 'modNLS', 'version'])" ] }, - "execution_count": 39, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" } @@ -2124,17 +2324,17 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 56, "id": "9bfb2ffe", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "dict_keys(['resultHypParam', 'xDecompAgg', 'mediaVecCollect', 'xDecompVecCollect', 'resultCalibration', 'allSolutions', 'allPareto', 'calibration_constraint', 'OutputModels', 'cores', 'iterations', 'trials', 'intercept_sign', 'nevergrad_algo', 'add_penalty_factor', 'seed', 'UI', 'pareto_fronts', 'hyper_fixed', 'plot_folder', 'hyper_updated', 'selectID'])" + "dict_keys(['resultHypParam', 'xDecompAgg', 'mediaVecCollect', 'xDecompVecCollect', 'resultCalibration', 'allSolutions', 'allPareto', 'calibration_constraint', 'OutputModels', 'cores', 'iterations', 'trials', 'intercept', 'intercept_sign', 'nevergrad_algo', 'add_penalty_factor', 'seed', 'UI', 'pareto_fronts', 'hyper_fixed', 'plot_folder', 'hyper_updated', 'clusters', 'selectID'])" ] }, - "execution_count": 40, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } @@ -2161,7 +2361,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/robyn_api/robynapi_enpoints.R b/robyn_api/robynapi_enpoints.R index 07816901f..f6116a828 100644 --- a/robyn_api/robynapi_enpoints.R +++ b/robyn_api/robynapi_enpoints.R @@ -41,16 +41,6 @@ hex_to_raw <- function(x) { as.raw(strtoi(chars, base=16L)) } -#* Serialize a ggplot into a hex string by first converting to png -ggplot_serialize <- function(plot,dpi,width,height) { - temp_file <- tempfile(fileext = ".png") - ggsave(temp_file, plot, device = "png", dpi = dpi, width = width, height = height, limitsize = FALSE) - png_data <- readBin(temp_file, "raw", file.info(temp_file)$size) - hex_string <- paste0(sprintf("%02x", as.integer(png_data)), collapse = "") - file.remove(temp_file) - return(hex_string) -} - #* Whether an object is a named list is_named_list <- function(obj) { is_list <- is.list(obj) @@ -63,16 +53,29 @@ is_ggplot <- function(obj) { inherits(obj, "ggplot") } +#* Serialize a ggplot into a hex string by first converting to png +ggplot_serialize <- function(plot, dpi, width, height) { + suppressMessages({ + temp_file <- tempfile(fileext = ".png") + ggsave(temp_file, plot, device = "png", dpi = dpi, width = width, height = height, limitsize = FALSE) + png_data <- readBin(temp_file, "raw", file.info(temp_file)$size) + hex_string <- paste0(sprintf("%02x", as.integer(png_data)), collapse = "") + file.remove(temp_file) + }) + return(hex_string) +} + #* Iterates recursively and helps to serialise any ggplot objects -recursive_ggplot_serialize <- function(obj,dpi=900,width=12,height=8) { - for (key in names(obj)) { - if (is_ggplot(obj[[key]])) { - obj[[key]] <- ggplot_serialize(obj[[key]],dpi,width,height) - } - else if (is_named_list(obj[[key]])) { - obj[[key]] <- recursive_ggplot_serialize(obj[[key]],dpi,width,height) +recursive_ggplot_serialize <- function(obj, dpi = 900, width = 12, height = 8) { + suppressMessages({ + for (key in names(obj)) { + if (is_ggplot(obj[[key]])) { + obj[[key]] <- ggplot_serialize(obj[[key]], dpi, width, height) + } else if (is_named_list(obj[[key]])) { + obj[[key]] <- recursive_ggplot_serialize(obj[[key]], dpi, width, height) + } } - } + }) return(obj) } @@ -138,6 +141,29 @@ transform_OutputCollect <- function(OutputCollect, select_model=FALSE) { # Add class name which is used as a checker in Robyn class(OutputCollect) <- c("robyn_outputs", "list") + # Null Treatment (When ts_validation = FALSE, val and test score need to be added) + keys_to_check <- c("rsq_val", "rsq_test", "nrmse_val", "nrmse_test") + for (lst_name in c("xDecompAgg", "resultHypParam")) { + lst <- OutputCollect[[lst_name]] + for (key in keys_to_check) { + if (!(key %in% names(lst))) { + lst[[key]] <- NA + } + } + OutputCollect[[lst_name]] <- lst + } + + for (trial in grep("^trial[0-9]+$", names(OutputCollect[['OutputModels']]), value = TRUE)) + for (lst_name in c("xDecompAgg", "resultHypParam", "decompSpendDist")) { + lst <- OutputCollect[['OutputModels']][[trial]][['resultCollect']][[lst_name]] + for (key in keys_to_check) { + if (!(key %in% names(lst))) { + lst[[key]] <- NA + } + } + OutputCollect[['OutputModels']][[trial]][['resultCollect']][[lst_name]] <- lst + } + # convert only target model data if (!select_model==FALSE) { OutputCollect[['allPareto']][['plotDataCollect']][[select_model]][['plot2data']][['plotWaterfallLoop']] <- @@ -166,7 +192,7 @@ function() { return(Robyn::dt_simulated_weekly) } -#* Provides holiday data suitable for use with Robyn models +#* Provides holidays data suitable for use with Robyn models #* This endpoint returns a dataset of holidays that can be used within Robyn models to account for seasonal variations. #* @get /dt_prophet_holidays function() { @@ -176,24 +202,25 @@ function() { #* Receives model-related data and configurations, processes them, and returns an 'InputCollect' object #* This endpoint handles the ingestion of model data and parameters, converting them into the appropriate format for the Robyn model. #* @param dt_input A hexadecimal string representing the binary content of a model data feather file. -#* @param dt_holiday A hexadecimal string representing the binary content of a holiday data feather file. +#* @param dt_holidays A hexadecimal string representing the binary content of a holidays data feather file. #* @param jsonInputArgs A JSON string of additional parameters to be used with the 'robyn_inputs()' function. #* @param InputCollect A JSON string representing the 'InputCollect' object created by the 'robyn_inputs()' function. #* @param calibration_input A hexadecimal string representing the binary content of a calibration data feather file. +#* @serializer json list(digits = 20, na = 'null') #* @post /robyn_inputs -function(dt_input=FALSE, dt_holiday=FALSE, jsonInputArgs=FALSE, InputCollect=FALSE, calibration_input=FALSE) { +function(dt_input=FALSE, dt_holidays=FALSE, jsonInputArgs=FALSE, InputCollect=FALSE, calibration_input=FALSE) { + inputArgs <- if (!jsonInputArgs==FALSE) jsonlite::fromJSON(jsonInputArgs) else NULL dt_input <- if (!dt_input==FALSE) hex_to_raw(dt_input) %>% arrow::read_feather() else NULL - dt_holiday <- if (!dt_holiday==FALSE) hex_to_raw(dt_holiday) %>% arrow::read_feather() else NULL + dt_holidays <- if (!dt_holidays==FALSE) hex_to_raw(dt_holidays) %>% arrow::read_feather() else NULL InputCollect <- if (!InputCollect==FALSE) transform_InputCollect(InputCollect) else NULL calibration_input <- if (!calibration_input==FALSE) hex_to_raw(calibration_input) %>% arrow::read_feather() else NULL - argsInput <- if (!jsonInputArgs==FALSE) jsonlite::fromJSON(jsonInputArgs) else NULL InputCollect <- do.call(robyn_inputs, c(list(dt_input = dt_input, - dt_holidays = dt_holiday, + dt_holidays = dt_holidays, InputCollect = InputCollect, calibration_input = calibration_input - ), argsInput)) + ), inputArgs)) return(recursive_ggplot_serialize(InputCollect)) } @@ -203,13 +230,15 @@ function(dt_input=FALSE, dt_holiday=FALSE, jsonInputArgs=FALSE, InputCollect=FAL #* then serializes the output for transmission over the API. #* @param InputCollect A JSON string representing the 'InputCollect' object created by the 'robyn_inputs()' function. #* @param jsonRunArgs A JSON string of additional parameters for the 'robyn_run()' function. +#* @serializer json list(digits = 20, na = 'null') #* @post /robyn_run function(InputCollect, jsonRunArgs) { + runArgs <- jsonlite::fromJSON(jsonRunArgs) InputCollect <- transform_InputCollect(InputCollect) - argsRun <- jsonlite::fromJSON(jsonRunArgs) - OutputModels <- do.call(robyn_run, c(list(InputCollect = InputCollect), argsRun)) + OutputModels <- do.call(robyn_run, c(list(InputCollect = InputCollect + ), runArgs)) return(recursive_ggplot_serialize(OutputModels)) } @@ -221,16 +250,17 @@ function(InputCollect, jsonRunArgs) { #* @param OutputModels A JSON string representing the model outputs generated by 'robyn_run()'. #* @param jsonOutputsArgs A JSON string containing additional parameters for the 'robyn_outputs()' function. #* @param onePagers A boolean flag indicating whether to generate one-pager reports; defaults to FALSE. +#* @serializer json list(digits = 20, na = 'null') #* @post /robyn_outputs function(InputCollect, OutputModels, jsonOutputsArgs) { + outputsArgs <- jsonlite::fromJSON(jsonOutputsArgs) InputCollect <- transform_InputCollect(InputCollect) OutputModels <- jsonlite::fromJSON(OutputModels) - argsOutputs <- jsonlite::fromJSON(jsonOutputsArgs) OutputCollect <- do.call(robyn_outputs, c(list(InputCollect = InputCollect, OutputModels = OutputModels - ), argsOutputs)) + ), outputsArgs)) return(recursive_ggplot_serialize(OutputCollect)) } @@ -247,19 +277,19 @@ function(InputCollect, OutputModels, jsonOutputsArgs) { #* @post /robyn_onepagers function(InputCollect, OutputCollect, jsonOnepagersArgs, dpi=100, width=12, height=8) { - argsOonepagers <- jsonlite::fromJSON(jsonOnepagersArgs) + onepagersArgs <- jsonlite::fromJSON(jsonOnepagersArgs) InputCollect <- transform_InputCollect(InputCollect) - OutputCollect <- transform_OutputCollect(OutputCollect, argsOonepagers[["select_model"]]) + OutputCollect <- transform_OutputCollect(OutputCollect, onepagersArgs[["select_model"]]) onepager <- do.call(robyn_onepagers, c(list(InputCollect = InputCollect, OutputCollect = OutputCollect - ), argsOonepagers)) + ), onepagersArgs)) dpi <- as.numeric(dpi) width <- as.numeric(width) height <- as.numeric(height) - return(ggplot_serialize(onepager[[argsOonepagers[["select_model"]]]], dpi=dpi, width=width, height=height)) + return(ggplot_serialize(onepager[[onepagersArgs[["select_model"]]]], dpi=dpi, width=width, height=height)) } #* Generates and returns a serialized image of the allocation one-pager @@ -274,11 +304,13 @@ function(InputCollect, OutputCollect, jsonOnepagersArgs, dpi=100, width=12, heig #* @post /robyn_allocator function(InputCollect, OutputCollect, jsonAllocatorArgs, dpi=100, width=12, height=8) { - argsAllocator <- jsonlite::fromJSON(jsonAllocatorArgs) + allocatorArgs <- jsonlite::fromJSON(jsonAllocatorArgs) InputCollect <- transform_InputCollect(InputCollect) - OutputCollect <- transform_OutputCollect(OutputCollect, argsAllocator[["select_model"]]) + OutputCollect <- transform_OutputCollect(OutputCollect, allocatorArgs[["select_model"]]) - AllocatorCollect <- do.call(robyn_allocator, c(list(InputCollect = InputCollect, OutputCollect = OutputCollect), argsAllocator)) + AllocatorCollect <- do.call(robyn_allocator, c(list(InputCollect = InputCollect, + OutputCollect = OutputCollect + ), allocatorArgs)) dpi <- as.numeric(dpi) width <- as.numeric(width) @@ -305,10 +337,11 @@ function(InputCollect=FALSE, OutputCollect=FALSE, OutputModels=FALSE, jsonWriteA } #* Recreates a model from data files and additional parameters -#* This endpoint reads model data and holiday data from hexadecimal-encoded feather files and additional parameters from a JSON object to recreate a Robyn model. +#* This endpoint reads model data and holidays data from hexadecimal-encoded feather files and additional parameters from a JSON object to recreate a Robyn model. #* @param dt_input A hexadecimal string of the model data feather file. -#* @param dt_holidays A hexadecimal string of the holiday data feather file. +#* @param dt_holidays A hexadecimal string of the holidays data feather file. #* @param jsonRecreateArgs A JSON string containing additional parameters for the 'robyn_recreate()' function. +#* @serializer json list(digits = 20, na = 'null') #* @post /robyn_recreate function(dt_input, dt_holidays, jsonRecreateArgs) { @@ -316,7 +349,9 @@ function(dt_input, dt_holidays, jsonRecreateArgs) { dt_input <- dt_input %>% hex_to_raw() %>% arrow::read_feather() dt_holidays <- dt_holidays %>% hex_to_raw() %>% arrow::read_feather() - RobynRecreated <- do.call(robyn_recreate, c(list(dt_input = dt_input, dt_holidays = dt_holidays), recreateArgs)) + RobynRecreated <- do.call(robyn_recreate, c(list(dt_input = dt_input, + dt_holidays = dt_holidays + ), recreateArgs)) return(recursive_ggplot_serialize(RobynRecreated)) } @@ -331,4 +366,25 @@ function(adstock, all_media) { hyper_names_list <- hyper_names(adstock = adstock, all_media = jsonlite::fromJSON(all_media)) return(hyper_names_list) +} + +#* Refresh a model from data files and additional parameters +#* This endpoint uses the 'robyn_refresh()' function to read model data and holidays data from hexadecimal-encoded feather files +#* and additional parameters from a JSON object. This process refreshes the Robyn model. +#* @param dt_input +#* @param dt_holidays +#* @param jsonRefreshArgs +#* @serializer json list(digits = 20, na = 'null') +#* @post /robyn_refresh +function(dt_input, dt_holidays, jsonRefreshArgs) { + + refreshArgs <- jsonlite::fromJSON(jsonRefreshArgs) + dt_input <- if (!dt_input==FALSE) hex_to_raw(dt_input) %>% arrow::read_feather() else NULL + dt_holidays <- if (!dt_holidays==FALSE) hex_to_raw(dt_holidays) %>% arrow::read_feather() else NULL + + RobynRefresh <- do.call(robyn_refresh, c(list(dt_input = dt_input, + dt_holidays = dt_holidays + ), refreshArgs)) + + return(recursive_ggplot_serialize(RobynRefresh)) } \ No newline at end of file diff --git a/website/docs/features.mdx b/website/docs/features.mdx index 643596c6d..fc7c04009 100644 --- a/website/docs/features.mdx +++ b/website/docs/features.mdx @@ -5,7 +5,7 @@ title: Key Features import useBaseUrl from '@docusaurus/useBaseUrl'; -An in-depth discussion of both the implementation and technical underpinnings of Robyn follows. +This documentation is updated in December 2024 on the R dev version v3.12.0 of Robyn. --- ## Model Inputs @@ -36,11 +36,11 @@ InputCollect <- robyn_inputs( Refer to the [Data Collection](https://facebookexperimental.github.io/Robyn/docs/analysts-guide-to-MMM#data-collection) section of the Analyst's Guide to MMM for a detailed discussion on best practices for selecting your paid media variables. -For paid media variables, we currently require that users designate both `paid_media_vars` and `paid_media_spends`. `paid_media_vars` refers to media exposure metrics, e.g. TV GRP, search clicks or Facebook impressions. `paid_media_spends` refers to media spending. The two vectors must have the same length and the same order of media. When exposure metrics are not available, use the same as in `paid_media_spends`. +For paid media variables, we require users to assign values to both `paid_media_vars` and `paid_media_spends`. `paid_media_vars` refers to media exposure metrics, e.g. TV GRP, search clicks or Facebook impressions. `paid_media_spends` refers to media spending. The two vectors must have the same length and the same order of media. When exposure metrics are not available, use the same as in `paid_media_spends`. -**Note**: Robyn currently fits the main model using only media spend. Exposure as modeling varibale is deprecated due to the uncertainty it introduces to the budget allocation. Robyn uses the Michaelis-Menten function to translate between spend and exposure. Despite the nonlinear flexibility this function provides, the relationship between spend and exposure is often too complex for a univariate transformation. In earlier versions, this inaccuracy in spend-exposure translation has caused unreliable budget allocation. Even though we understand the narrative of using exposure metrics, we've decided to trade it off against the reliability of budget allocation. We'll re-introduce exposure fitting as soon as we have a working solution. +Robyn currently fits the main model using a mix of media spend and exposure. When `paid_media_vars` is specified with exposure metrics, these will be prioritised and used for fitting with the fallback in `paid_media_spends`. Using exposure as modeling varibale was not enabled in Robyn for a long time due to the uncertainty it introduces to the budget allocation. The reason was that the relationship between spend and exposure is often too complex for a univariate transformation. In earlier versions of Robyn, this inaccuracy in spend-exposure translation has caused unreliable budget allocation. However, this is reactivated in v3.12.0, not only because of the interests from users, but also due to the introduction of the [new curve calibrator](https://facebookexperimental.github.io/Robyn/docs/features#holistic-calibration). While the above mentioned inaccuracy in spend-exposure translation still exists, we believe that it's mitigated through the calibration of response curve from ground truth. -Despite the deprecation mentioned above, there's still value in providing exposure metrics in Robyn. If there's weak association detected between spend & exposure, it indicates that exposure metrics have different underlying pattern than spends. In this case, Robyn will recommend to splitting the channel for potentially better modeling result. Take Meta as example, retargeting and prospecting campaigns might have very different CPMs and efficiencies. In which case, it would be meaningful to split Meta by retargeting and prospecting. +Moreover, we highly recommend users to closely examine the relationship beteween exposure and spend metrics. If there's weak association detected between spend & exposure, it indicates that exposure metrics have different underlying pattern than spends. In this case, we recommend to splitting the channel for potentially better modeling result. Take Meta as example, retargeting and prospecting campaigns might have very different CPMs and efficiencies. In which case, it would be meaningful to split Meta by retargeting and prospecting. For details see the demo [here](https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R#L311). In general, it's important to ensure that the paid media data is complete and accurate before proceeding. We will talk more about the variable transformations paid media variables will be subject to in the Variable Transformation section. @@ -333,7 +333,7 @@ As depicted in plot 4 in [session model onepager](#model-onepager) below, the k- --- -## Calibration with causal experiments +## Calibration of average effect size with causal experiments Randomised controlled trial (RCT) is an established academic gold standard to infer causality in science. By applying results from RCT in ads measurement that are considered ground truth, you can introduce causality into your marketing mix models. Robyn implements the MMM calibration as an objective function in the multi-objective optimization by parameterizing the difference between causal results and predicted media contribution. @@ -363,6 +363,57 @@ There're two major types of experiements in ads measurement, as pointed out by t Robyn accepts a dataframe as calibration input in the `robyn_inputs()` function. The function usage can be found in the [demo](https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R#L262). +--- + +## Holistic calibration + +### Rethinking calibration + +The triangulation of MMM, experiments and attribution is the centerpiece of [modern measurement](https://www.facebook.com/business/news/advanced-measurement-strategy). While there's no universally accepted definition of calibration, it often refers to the adjustment of estimated impact of media between different measurement solutions. + +In MMM, calibration usually refers to adjusting the average effect size of a certain channel by causal experiments, as explained in details above. However, the average effect size, or the beta coefficient in a regression model, is not the only estimate in an MMM system. The bare minimum of a set of estimates in MMM includes the **average effect size, adstock and saturation**. And just as the effect size, adstock and saturation are uncertain parametric quantities that can and should be calibrated by ground truth whenever possible. We believe that **holistic calibration** is the next step of triangulation and integrated marketing measurement system. + +Reach & frequency curve calibration + +### The curve calibrator (beta) + +Robyn is releasing a new feature **"the curve calibrator"** `robyn_calibrate()` as a step towards holistic calibration. The first use case is to calibrate the response saturation curve using cumulative reach and frequency data as input. This type of data is usually available as siloed media reports for most offline and online channels. The latest choice of reach and frequency data is **[Project Halo](https://wfanet.org/leadership/cross-media-measurement)**, an industry-wide collaboration that aims to deliver privacy-safe and always-on cross-channel reach deduplication. The above graphic is derived and simulated based on a real Halo dataset with cumulative spend and cumulative reach by frequency buckets. For example, "reach 3+" means reaching 3 impressions on average per person. There's certainly a gap between saturation of reach and business outcome (purchase, sales etc.). However, they're also interconnected along the same conversion funnel (upper funnel -> lower funnel), while the reach & frequency saturation curve is often more available. Therefore, **we're exploring the potential of using reach & frequency to guide response saturation estimation.** + +According to [a recent research paper](https://arxiv.org/abs/2408.07678) from the Wharton School and the London Business School by Dew, Padilla and Shchetkina, a common MMM cannot reliably identify saturation parameters, quote _"as practitioners attempt to capture increasingly complex effects in MMMs, like nonlinearities and dynamics, our results suggest caution is warranted: the simple data used for building such models often cannot uniquely identify such complexity."_ In other words, **saturation should be calibrated by ground truth whenever possible.** + +**Our approach for saturation calibration by reach & frequency**: Assuming an extreme situation where every user sees the first impression and purchases immediately. In such a case, response saturation curve equals the reach 1+ saturation curve. [Hill function](https://facebookexperimental.github.io/Robyn/docs/features#saturation) is a popular choice for saturation transformation and implemented in Robyn, where gamma controls the latitude of the inflexion point. A lower gamma means earlier and faster saturation at a lower spend level. **Our hypothesis** is that the cumulative reach 1+ curve represents the earliest inflexion and thus serves as a reasonable lower boundary for gamma for a selected channel. **As frequency increases, the reach inflexion point delays and approaches lower-funnel. We believe that the hidden true response curve lies within the spectrum of cumulative reach and frequency curves**. In the dummy dataset, we've simulated reach 10+ to represent the upper bound for gamma. The "best converting frequency" varies strongly across verticals. We believe that reach & frequency it's one step closer to identifying the true saturation relationship. Use domain expertise to further narrow down or widen the bounds. For alpha, we recommend to keeping the value flexible as in default. + +The below graphic is an exemplary visualisation of a curve fitting process, where Nevergrad is used to estimate alpha, gamma as well as the beta. Note that the distribution of alpha and gamma are often multimodal and non-normal, because they rather reflect the hyperparameter optimization path of Nevergrad than their underlying distribution. + +Reach & frequency curve fitting + +To try out `robyn_calibrate()`, please see [this tutorial](https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R#L200) in the demo. + +``` +library(Robyn) +data("df_curve_reach_freq") + +# Using reach saturation as proxy +curve_out <- robyn_calibrate( + df_curve = df_curve_reach_freq, + curve_type = "saturation_reach_hill" +) +# For the simulated reach and frequency dataset, it's recommended to use +# "reach 1+" for gamma lower bound and "reach 10+" for gamma upper bound +facebook_I_gammas <- c( + curve_out[["curve_collect"]][["reach 1+"]][["hill"]][["gamma_best"]], + curve_out[["curve_collect"]][["reach 10+"]][["hill"]][["gamma_best"]]) +print(facebook_I_gammas) + +``` + +### Customizable for 3rd-party MMM +**While the curve calibrator is released within the Robyn package, it can be used as a standalone feature without having built a model in Robyn.** The current beta version is piloting the two-parametric Hill function for saturation. Any MMM solution, not only Robyn, that employs the two-parametric Hill function can be calibrated by the curve calibrator. + +In the future, we're planning to partner with our community, advertisers, agencies and measurement vendors to further explore this area and also to expand the curve calibrator to cover other popular nonlinear functions for saturation (e.g. exponential, arctan or power function) as well as adstock (geometric or weibull function). + + + --- ## Model onepager @@ -405,6 +456,17 @@ following deepdive articles: - **"The convergence of marginal ROAS in the budget allocation in Robyn"**: [here](https://medium.com/@gufengzhou/the-convergence-of-marginal-roas-in-the-budget-allocation-in-robyn-5d407aebf021) - **"Hitting ROAS target using Robyn’s budget allocator"**: [here](https://medium.com/@gufengzhou/hitting-roas-target-using-robyns-budget-allocator-274ace3add4f) +--- +## The reach & frequency allocator (prototype) + +Reach and frequency planning is conducted frequently by advertisers and media agencies. To further harvest the power of **[Project Halo](https://wfanet.org/leadership/cross-media-measurement)** and provide more actionability for R&F data, we're experimenting on a new feature "reach and frequency allocator". It answers the question “what’s the optimal combination of reach & frequency” on a channel given a total budget and average CPM. It consumes the saturation information from R&F data and uses nonlinear optimization to find the optimal point with highest response. + +Decription of the graphic below: Given 100k budget and 6$ CPM, as well as the estimated saturation curve for reach and frequency separately using Halo data, the optimum R&F combination is 5.67M reach x 2.94 frequency, with the maximum response (sales) of 317.8k$. + +ModelResults1 chart + +It's currently a prototype and not yet available. An MVP is expected in 2025. + --- ## Model refresh diff --git a/website/docs/installation.mdx b/website/docs/installation.mdx index e3313641d..f4bb2277c 100644 --- a/website/docs/installation.mdx +++ b/website/docs/installation.mdx @@ -5,13 +5,7 @@ title: Installation import useBaseUrl from '@docusaurus/useBaseUrl'; -## Installing R ---- - -Robyn is built in R-only at the moment and requries the [R 4.0.0 version (or higher)](https://www.r-project.org/). The recommended IDE is [RStudio](https://www.rstudio.com/products/rstudio/download/). - - -## Installing Robyn +## Installing Robyn R --- There're two versions of Robyn: The stable version on CRAN and the dev version on GitHub. @@ -25,21 +19,9 @@ Install latest dev version, run: ``` remotes::install_github("facebookexperimental/Robyn/R") ``` -**NOTE**: Robyn requires an one-time installation of the Python library [Nevergrad](https://facebookresearch.github.io/nevergrad/) using the R package `reticulate`. Please refer to this [Nevergrad installation](https://github.com/facebookexperimental/Robyn/blob/main/demo/install_nevergrad.R) guide for R. +**NOTE**: Robyn requires an one-time installation of the Python library [Nevergrad](https://facebookresearch.github.io/nevergrad/) using the R package `reticulate`. Please refer to this [Nevergrad installation](https://github.com/facebookexperimental/Robyn/blob/main/demo/install_nevergrad.R) guide for R. For detailed installation and usage guide please see [demo.R](https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R). -## Getting started +## Installing Robyn Python --- -The usage guide is detailed in the script [demo.R](https://github.com/facebookexperimental/Robyn/blob/main/demo/demo.R), where you will see working examples of all major functions, including: -- Model input -- Hyperparameter setting -- Calibration input -- Model run -- Model output -- Model selection and export -- Budget allocator -- Model refresh -- Recreate models -- Getting response and more... - ---- +For detailed Robyn Python installation and usage guide please see [here](https://facebookexperimental.github.io/Robyn/docs/robyn-api). diff --git a/website/docs/robyn-api.mdx b/website/docs/robyn-api.mdx index 0e0270795..1dcf338c0 100644 --- a/website/docs/robyn-api.mdx +++ b/website/docs/robyn-api.mdx @@ -1,15 +1,53 @@ --- id: robyn-api -title: Robyn API for Python +title: Robyn Python (Beta) --- import useBaseUrl from '@docusaurus/useBaseUrl'; -Enabling Robyn for Python has been a long-standing ask from the community. Robyn has started as an experimental R package. While we understand the needs of the users, it's difficult to maintain a natively translated Python package during active development on the R-side. +## Alternative 1: Quick start for RobynPy (Beta) + +The Python version of Robyn is rewritten from Robyn's R package version 3.11.1 to Python using object oriented programming principles and modular architecture for a robust solution. It was developed by utilizing various LLMs and AI workflows like Llama. As is common with any AI-based solutions, there may be potential challenges in translating code from one language to another. In this case, we anticipate that there could be some issues in the translation from R to Python. However, we believe in the power of community collaboration and open-source contribution. Therefore, we are opening this project to the community to participate and contribute. Together, we can address and resolve any issues that may arise, enhancing the functionality and efficiency of the Python version of Robyn. We look forward to your contributions and to the continuous improvement of this project. + + +### 1. Installing the package + +Install the latest Robyn Python package version from pypi +``` +pip3 install robynpy +``` + +Install from Github using requirements.txt +``` +pip3 install -r requirements.txt +``` +### 2. Getting started + +The directory `python/src/robyn/tutorials` contains tutorials for most common scenarios. Tutorials use simulated dataset provided in the package. + +### 3. Running end-to-end + +There are two ways of running Python Robyn. + +**Option 1:** + +tutorial1.ipynb is the main notebook that runs the end-to-end flow. It is designed for majority of the users who would prefer a one click solution that runs the robyn flow end-to-end with minimal knowledge of the underlying logic. It should run without any changes required if you wish to use the simulated dataset for testing purposes. + +This notebook uses APIs available in python/src/robyn/robyn.py to set the configs, run feature engineering, run model training, evaluate models with clustering, generate one pagers and perform budget allocation. + +Change any of the configs directly in the notebook and avoid changes to robyn.py for what can be configurable. + +**Option 2:** + +tutorial1_src.ipynb runs the end-to-end flow of robyn python but with a lot more flexibility. It is designed for users who would like to have more control over which modules are and aren't run (ie. skipping clustering/one pager plots/budget allocation etc.). It should run without any changes required if you wish to use the simulated dataset for testing purposes. + +This notebook doesn't use APIs available in python/src/robyn/robyn.py but instead, calls the modules directly with the appropriate parameters. In this way, it is more flexible but still expects the users to understand the underlying logic that may change when using various parameter values. + +## Alternative 2: The Python wrapper The idea of a plumber API for Python is originally proposed by [Alex Rowley](https://www.facebook.com/groups/robynmmm/posts/1493036524797809/) from the Robyn community in August 2023. The Robyn team has assessed the proposal that is not only a great work-around for Python users to start with Robyn, but it actually allows API calls from any languages. We're very grateful for the collective wisdom of the open source community. #### Robyn API for Python beta release -The first version of the API is released on Nov.22nd 2023 on the [Meta OST summit](https://metaostsummit23.splashthat.com/?fbclid=IwAR1SRBTZGw0GIoaF0XJq_eCWFZsZbyK0KP7P4RLKoee1IVbs8H56so3giwg). This [Jupyter notebook](https://github.com/facebookexperimental/Robyn/blob/main/robyn_api/robyn_python_notebook.ipynb) shows how to call the API from Python. In the beta version, the user needs to have the Robyn R package successfully installed first. We'll work on the migitation of installation friction in the future. +The first version of the API is released on Nov.22nd 2023 on the [Meta OST summit](https://metaostsummit23.splashthat.com/?fbclid=IwAR1SRBTZGw0GIoaF0XJq_eCWFZsZbyK0KP7P4RLKoee1IVbs8H56so3giwg). This [Jupyter notebook](https://github.com/facebookexperimental/Robyn/blob/main/robyn_api/robyn_python_notebook.ipynb) shows how to call the API from Python. In the beta version, the user needs to have the Robyn R package successfully installed first. We'll work on the migitation of installation friction in the future. 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"https://registry.yarnpkg.com/side-channel/-/side-channel-1.0.6.tgz#abd25fb7cd24baf45466406b1096b7831c9215f2" + integrity sha512-fDW/EZ6Q9RiO8eFG8Hj+7u/oW+XrPTIChwCOM2+th2A6OblDtYYIpve9m+KvI9Z4C9qSEXlaGR6bTEYHReuglA== + dependencies: + call-bind "^1.0.7" + es-errors "^1.3.0" + get-intrinsic "^1.2.4" + object-inspect "^1.13.1" + signal-exit@^3.0.2, signal-exit@^3.0.3: version "3.0.7" resolved "https://registry.yarnpkg.com/signal-exit/-/signal-exit-3.0.7.tgz#a9a1767f8af84155114eaabd73f99273c8f59ad9" @@ -8532,7 +8626,18 @@ tapable@^2.0.0, tapable@^2.1.1, tapable@^2.2.0: resolved "https://registry.yarnpkg.com/tapable/-/tapable-2.2.1.tgz#1967a73ef4060a82f12ab96af86d52fdb76eeca0" integrity sha512-GNzQvQTOIP6RyTfE2Qxb8ZVlNmw0n88vp1szwWRimP02mnTsx3Wtn5qRdqY9w2XduFNUgvOwhNnQsjwCp+kqaQ== -terser-webpack-plugin@^5.3.3, terser-webpack-plugin@^5.3.7: +terser-webpack-plugin@^5.3.10: + version "5.3.10" + resolved 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graceful-fs "^4.1.2" @@ -9062,9 +9177,9 @@ webpack-bundle-analyzer@^4.5.0: ws "^7.3.1" webpack-dev-middleware@^5.3.1: - version "5.3.3" - resolved "https://registry.yarnpkg.com/webpack-dev-middleware/-/webpack-dev-middleware-5.3.3.tgz#efae67c2793908e7311f1d9b06f2a08dcc97e51f" - integrity sha512-hj5CYrY0bZLB+eTO+x/j67Pkrquiy7kWepMHmUMoPsmcUaeEnQJqFzHJOyxgWlq746/wUuA64p9ta34Kyb01pA== + version "5.3.4" + resolved "https://registry.yarnpkg.com/webpack-dev-middleware/-/webpack-dev-middleware-5.3.4.tgz#eb7b39281cbce10e104eb2b8bf2b63fce49a3517" + integrity sha512-BVdTqhhs+0IfoeAf7EoH5WE+exCmqGerHfDM0IL096Px60Tq2Mn9MAbnaGUe6HiMa41KMCYF19gyzZmBcq/o4Q== dependencies: colorette "^2.0.10" memfs "^3.4.3" @@ -9122,33 +9237,32 @@ webpack-sources@^3.2.2, webpack-sources@^3.2.3: integrity sha512-/DyMEOrDgLKKIG0fmvtz+4dUX/3Ghozwgm6iPp8KRhvn+eQf9+Q7GWxVNMk3+uCPWfdXYC4ExGBckIXdFEfH1w== webpack@^5.73.0: - version "5.88.2" - resolved 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