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Bump the all-dependencies group across 1 directory with 8 updates #485

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a64e999
Bump the all-dependencies group across 1 directory with 8 updates
dependabot[bot] Aug 27, 2026
804bebe
Merge branch 'main' into dependabot/uv/all-dependencies-58dc03f2f0
figueroa1395 Aug 31, 2026
ceed063
Update pgm_input_data.json for pandapower>3.4
nitbharambe Aug 31, 2026
7e034a7
regenerate json files with 3.5.4
nitbharambe Sep 1, 2026
6976007
add loading attribute conversion test
nitbharambe Sep 1, 2026
495dca2
fix bus output for asym converter
nitbharambe Sep 1, 2026
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6 changes: 3 additions & 3 deletions tests/data/pandapower/pgm_input_data.json
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Original file line number Diff line number Diff line change
Expand Up @@ -319,9 +319,9 @@
"uk": 0.178,
"winding_from": 2,
"winding_to": 1,
"i0_zero_sequence": 0.05617977528089,
"p0_zero_sequence": 44941.573
"i0_zero_sequence": 5.617977528089,
"p0_zero_sequence": 4494157.3

@furqan463 furqan463 Sep 5, 2026

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Shouldn't do this, it'll make it incompatible with pandapower<3.4.0.
The problem is on pandapower side not pgm. After pandapower=3.4.0, the mag0_percent is being treated as percent instead of ratio.
In #370 a change was missed in pp_validation.py::pp_net, the mag0_percent petaramer of transformer should be multiplied with 100 when pandapower>=3.4.0 and it'll be compatible with pp versions <3.4.0 and >=3.4.0.

}
]
}
}
}
9 changes: 6 additions & 3 deletions tests/data/pandapower/pv-node/pv-node3/pgm_sym_output.json
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,8 @@
"p_to": 56756451.555671,
"q_to": 22275406.177503,
"i_to": 311.519783,
"s_to": 60971210.530577
"s_to": 60971210.530577,
"loading": 0.00313224
},
{
"id": 4,
Expand All @@ -101,7 +102,8 @@
"p_to": 43243548.444329,
"q_to": 10361765.341661,
"i_to": 229.22676,
"s_to": 44467636.130704
"s_to": 44467636.130704,
"loading": 0.00230319

@furqan463 furqan463 Sep 5, 2026

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The file was copied from power_grid_model test data, loading attribute is still not present there. Should we add it there as well?

},
{
"id": 5,
Expand All @@ -113,7 +115,8 @@
"p_to": 13243548.444329,
"q_to": 10890476.535252,
"i_to": 87.605241,
"s_to": 17146254.826118
"s_to": 17146254.826118,
"loading": 0.00090759
}
],
"voltage_regulator": [
Expand Down
124 changes: 82 additions & 42 deletions tests/data/pandapower/pv-node/pv-node3/pp_net_asym_output.json
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Original file line number Diff line number Diff line change
Expand Up @@ -107,7 +107,7 @@
"asymmetric_load": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"bus\",\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\",\"sn_mva\",\"scaling\",\"in_service\",\"type\"],\"index\":[],\"data\":[]}",
"_object": "{\"columns\":[\"name\",\"bus\",\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\",\"sn_a_mva\",\"sn_b_mva\",\"sn_c_mva\",\"sn_mva\",\"scaling\",\"in_service\",\"type\"],\"index\":[],\"data\":[]}",
"orient": "split",
"dtype": {
"name": "object",
Expand All @@ -118,6 +118,9 @@
"q_b_mvar": "float64",
"p_c_mw": "float64",
"q_c_mvar": "float64",
"sn_a_mva": "float64",
"sn_b_mva": "float64",
"sn_c_mva": "float64",
"sn_mva": "float64",
"scaling": "float64",
"in_service": "bool",
Expand All @@ -129,7 +132,7 @@
"asymmetric_sgen": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"bus\",\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"current_source\"],\"index\":[],\"data\":[]}",
"_object": "{\"columns\":[\"name\",\"bus\",\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\",\"sn_a_mva\",\"sn_b_mva\",\"sn_c_mva\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"current_source\"],\"index\":[],\"data\":[]}",
"orient": "split",
"dtype": {
"name": "object",
Expand All @@ -140,6 +143,9 @@
"q_b_mvar": "float64",
"p_c_mw": "float64",
"q_c_mvar": "float64",
"sn_a_mva": "float64",
"sn_b_mva": "float64",
"sn_c_mva": "float64",
"sn_mva": "float64",
"scaling": "float64",
"in_service": "bool",
Expand Down Expand Up @@ -226,7 +232,7 @@
"q_mvar": "float64",
"p_mw": "float64",
"vn_kv": "float64",
"step": "uint32",
"step": "float64",
"max_step": "uint32",
"id_characteristic_table": "Int64",
"step_dependency_table": "bool",
Expand Down Expand Up @@ -301,7 +307,7 @@
"ext_grid": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"bus\",\"vm_pu\",\"va_degree\",\"slack_weight\",\"in_service\",\"controllable\",\"s_sc_max_mva\",\"rx_max\",\"x0x_max\",\"r0x0_max\"],\"index\":[0],\"data\":[[null,2,1.018182,0.0,1.0,true,false,1e+34,0.1,1,0.1]]}",
"_object": "{\"columns\":[\"name\",\"bus\",\"vm_pu\",\"va_degree\",\"slack_weight\",\"in_service\",\"controllable\",\"s_sc_max_mva\",\"rx_max\",\"x0x_max\",\"r0x0_max\"],\"index\":[0],\"data\":[[null,2,1.018182,0.0,1.0,true,false,1e+34,0.1,1.0,null]]}",
"orient": "split",
"dtype": {
"name": "object",
Expand All @@ -313,7 +319,7 @@
"controllable": "bool",
"s_sc_max_mva": "float64",
"rx_max": "float64",
"x0x_max": "int64",
"x0x_max": "float64",
"r0x0_max": "float64"
},
"is_multiindex": false,
Expand All @@ -322,7 +328,7 @@
"line": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"std_type\",\"from_bus\",\"to_bus\",\"length_km\",\"r_ohm_per_km\",\"x_ohm_per_km\",\"c_nf_per_km\",\"g_us_per_km\",\"max_i_ka\",\"df\",\"parallel\",\"type\",\"in_service\",\"geo\",\"g0_nf_per_km\",\"c0_nf_per_km\",\"r0_ohm_per_km\",\"x0_ohm_per_km\",\"endtemp_degree\"],\"index\":[0,1,2],\"data\":[[null,null,0,1,25.0,0.0,0.4,9.5512,0.0,100.0,1.0,1,null,true,null,null,null,0.0,0.4,null],[null,null,0,2,25.0,0.0,0.4,9.5512,0.0,100.0,1.0,1,null,true,null,null,null,0.0,0.4,null],[null,null,2,1,25.0,0.0,0.4,9.5512,0.0,100.0,1.0,1,null,true,null,null,null,0.0,0.4,null]]}",
"_object": "{\"columns\":[\"name\",\"std_type\",\"from_bus\",\"to_bus\",\"length_km\",\"r_ohm_per_km\",\"x_ohm_per_km\",\"c_nf_per_km\",\"g_us_per_km\",\"max_i_ka\",\"df\",\"parallel\",\"type\",\"in_service\",\"geo\",\"g0_us_per_km\",\"c0_nf_per_km\",\"r0_ohm_per_km\",\"x0_ohm_per_km\",\"endtemp_degree\"],\"index\":[0,1,2],\"data\":[[null,null,0,1,25.0,0.0,0.4,9.5512,0.0,100.0,1.0,1,null,true,null,0.0,9.5512,0.0,0.4,null],[null,null,0,2,25.0,0.0,0.4,9.5512,0.0,100.0,1.0,1,null,true,null,0.0,9.5512,0.0,0.4,null],[null,null,2,1,25.0,0.0,0.4,9.5512,0.0,100.0,1.0,1,null,true,null,0.0,9.5512,0.0,0.4,null]]}",
"orient": "split",
"dtype": {
"name": "object",
Expand All @@ -340,8 +346,8 @@
"type": "object",
"in_service": "bool",
"geo": "object",
"g0_nf_per_km": "object",
"c0_nf_per_km": "object",
"g0_us_per_km": "float64",
"c0_nf_per_km": "float64",
"r0_ohm_per_km": "float64",
"x0_ohm_per_km": "float64",
"endtemp_degree": "float64"
Expand Down Expand Up @@ -375,7 +381,7 @@
"trafo": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"id_characteristic_table\",\"tap_dependency_table\",\"parallel\",\"df\",\"in_service\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\"],\"index\":[],\"data\":[]}",
"_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_changer_type\",\"id_characteristic_table\",\"tap_dependency_table\",\"parallel\",\"df\",\"in_service\",\"vector_group\",\"vk0_percent\",\"vkr0_percent\",\"mag0_percent\",\"mag0_rx\",\"si0_hv_partial\",\"xn_ohm\"],\"index\":[],\"data\":[]}",
"orient": "split",
"dtype": {
"name": "object",
Expand Down Expand Up @@ -408,7 +414,8 @@
"vkr0_percent": "object",
"mag0_percent": "object",
"mag0_rx": "object",
"si0_hv_partial": "object"
"si0_hv_partial": "object",
"xn_ohm": "float64"
},
"is_multiindex": false,
"is_multicolumn": false
Expand Down Expand Up @@ -594,7 +601,7 @@
"poly_cost": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"element\",\"et\",\"cp0_eur\",\"cp1_eur_per_mw\",\"cp2_eur_per_mw2\",\"cq0_eur\",\"cq1_eur_per_mvar\",\"cq2_eur_per_mvar2\"],\"index\":[],\"data\":[]}",
"_object": "{\"columns\":[\"element\",\"et\",\"cp0_eur\",\"cp1_eur_per_mw\",\"cp2_eur_per_mw2\",\"cq0_eur\",\"cq1_eur_per_mvar\",\"cq2_eur_per_mvar2\",\"redispatch_up_eur_per_mw\",\"redispatch_down_eur_per_mw\"],\"index\":[],\"data\":[]}",
"orient": "split",
"dtype": {
"element": "uint32",
Expand All @@ -604,7 +611,9 @@
"cp2_eur_per_mw2": "float64",
"cq0_eur": "float64",
"cq1_eur_per_mvar": "float64",
"cq2_eur_per_mvar2": "float64"
"cq2_eur_per_mvar2": "float64",
"redispatch_up_eur_per_mw": "float64",
"redispatch_down_eur_per_mw": "float64"
},
"is_multiindex": false,
"is_multicolumn": false
Expand Down Expand Up @@ -671,7 +680,7 @@
"is_multiindex": false,
"is_multicolumn": false
},
"b2b_vsc": {
"vsc_stacked": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"bus\",\"bus_dc_plus\",\"bus_dc_minus\",\"r_ohm\",\"x_ohm\",\"r_dc_ohm\",\"pl_dc_mw\",\"control_mode_ac\",\"control_value_ac\",\"control_mode_dc\",\"control_value_dc\",\"controllable\",\"in_service\"],\"index\":[],\"data\":[]}",
Expand All @@ -695,10 +704,10 @@
"is_multiindex": false,
"is_multicolumn": false
},
"bi_vsc": {
"vsc_bipolar": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"name\",\"bus\",\"bus_dc_plus\",\"bus_dc_minus\",\"r_ohm\",\"x_ohm\",\"r_dc_ohm\",\"pl_dc_mw\",\"control_mode_ac\",\"control_value_ac\",\"control_mode_dc\",\"control_value_dc\",\"controllable\",\"in_service\"],\"index\":[],\"data\":[]}",
"_object": "{\"columns\":[\"name\",\"bus\",\"bus_dc_plus\",\"bus_dc_minus\",\"r_ohm\",\"x_ohm\",\"r_dc_ohm\",\"pl_dc_mw\",\"control_mode\",\"control_value_1\",\"control_value_2\",\"controllable\",\"in_service\"],\"index\":[],\"data\":[]}",
"orient": "split",
"dtype": {
"name": "object",
Expand All @@ -709,18 +718,17 @@
"x_ohm": "float64",
"r_dc_ohm": "float64",
"pl_dc_mw": "float64",
"control_mode_ac": "object",
"control_value_ac": "float64",
"control_mode_dc": "object",
"control_value_dc": "float64",
"control_mode": "object",
"control_value_1": "float64",
"control_value_2": "float64",
"controllable": "bool",
"in_service": "bool"
},
"is_multiindex": false,
"is_multicolumn": false
},
"version": "3.3.3",
"format_version": "3.3.0",
"version": "3.5.4",
"format_version": "3.1.0",
"converged": true,
"OPF_converged": false,
"name": "",
Expand Down Expand Up @@ -1141,7 +1149,29 @@
"is_multiindex": false,
"is_multicolumn": false
},
"res_b2b_vsc": {
"res_vsc_stacked": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"p_dc_mw_p\",\"p_dc_mw_m\",\"vm_internal_pu\",\"vm_internal_degree\",\"vm_pu\",\"va_degree\",\"vm_internal_dc_pu_p\",\"vm_internal_dc_pu_m\",\"vm_dc_pu_p\",\"vm_dc_pu_m\"],\"index\":[],\"data\":[]}",
"orient": "split",
"dtype": {
"p_mw": "float64",
"q_mvar": "float64",
"p_dc_mw_p": "float64",
"p_dc_mw_m": "float64",
"vm_internal_pu": "float64",
"vm_internal_degree": "float64",
"vm_pu": "float64",
"va_degree": "float64",
"vm_internal_dc_pu_p": "float64",
"vm_internal_dc_pu_m": "float64",
"vm_dc_pu_p": "float64",
"vm_dc_pu_m": "float64"
},
"is_multiindex": false,
"is_multicolumn": false
},
"res_vsc_bipolar": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"p_dc_mw_p\",\"p_dc_mw_m\",\"vm_internal_pu\",\"vm_internal_degree\",\"vm_pu\",\"va_degree\",\"vm_internal_dc_pu_p\",\"vm_internal_dc_pu_m\",\"vm_dc_pu_p\",\"vm_dc_pu_m\"],\"index\":[],\"data\":[]}",
Expand Down Expand Up @@ -1391,7 +1421,7 @@
"res_line_3ph": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"p_a_from_mw\",\"q_a_from_mvar\",\"p_b_from_mw\",\"q_b_from_mvar\",\"p_c_from_mw\",\"q_c_from_mvar\",\"p_a_to_mw\",\"q_a_to_mvar\",\"p_b_to_mw\",\"q_b_to_mvar\",\"p_c_to_mw\",\"q_c_to_mvar\",\"pl_a_mw\",\"ql_a_mvar\",\"pl_b_mw\",\"ql_b_mvar\",\"pl_c_mw\",\"ql_c_mvar\",\"i_a_from_ka\",\"i_b_from_ka\",\"i_c_from_ka\",\"i_n_from_ka\",\"i_a_ka\",\"i_b_ka\",\"i_c_ka\",\"i_n_ka\",\"i_a_to_ka\",\"i_b_to_ka\",\"i_c_to_ka\",\"i_n_to_ka\",\"loading_a_percent\",\"loading_b_percent\",\"loading_c_percent\",\"loading_percent\"],\"index\":[0,1,2],\"data\":[[-18.918817185223649,-6.763024982689322,-18.918817185223624,-6.763024982689228,-18.918817185223563,-6.763024982689227,18.918817185223652,7.425135392501163,18.918817185223624,7.425135392501092,18.918817185223496,7.425135392501058,0.000000000000004,0.662110409811841,0.0,0.662110409811864,-0.000000000000067,0.662110409811832,0.313223720274046,0.313223720274045,0.313223720274044,0.000000000000003,0.313223720274046,0.313223720274045,0.313223720274044,0.000000000000003,0.311519782894272,0.311519782894271,0.311519782894269,0.000000000000003,0.313223720274046,0.313223720274045,0.313223720274044,0.313223720274046],[-14.414516148109676,-3.23697501731097,-14.414516148109755,-3.236975017310839,-14.414516148109548,-3.236975017310856,14.414516148109678,3.453921780553662,14.414516148109781,3.453921780553501,14.414516148109501,3.453921780553468,0.000000000000002,0.216946763242692,0.000000000000028,0.216946763242662,-0.000000000000048,0.216946763242612,0.230319167439365,0.230319167439365,0.230319167439362,0.000000000000005,0.230319167439365,0.230319167439365,0.230319167439362,0.000000000000007,0.229226759872795,0.229226759872796,0.229226759872791,0.000000000000007,0.230319167439365,0.230319167439365,0.230319167439362,0.230319167439365],[-4.41451614810968,-3.867104732241824,-4.41451614810954,-3.867104732241886,-4.414516148109746,-3.867104732241869,4.41451614810968,3.63015884508403,4.414516148109571,3.630158845084098,4.414516148109676,3.630158845084091,0.0,-0.236945887157794,0.000000000000031,-0.236945887157789,-0.000000000000071,-0.236945887157778,0.090758969676018,0.090758969676017,0.090758969676019,0.000000000000004,0.090758969676018,0.090758969676017,0.090758969676019,0.000000000000004,0.087605240807927,0.087605240807927,0.087605240807928,0.000000000000003,0.090758969676018,0.090758969676017,0.090758969676019,0.090758969676019]]}",
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"orient": "split",
"dtype": {
"p_a_from_mw": "float64",
Expand All @@ -1413,17 +1443,17 @@
"pl_c_mw": "float64",
"ql_c_mvar": "float64",
"i_a_from_ka": "float64",
"i_a_to_ka": "float64",
"i_b_from_ka": "float64",
"i_b_to_ka": "float64",
"i_c_from_ka": "float64",
"i_n_from_ka": "float64",
"i_c_to_ka": "float64",
"i_a_ka": "float64",
"i_b_ka": "float64",
"i_c_ka": "float64",
"i_n_ka": "float64",
"i_a_to_ka": "float64",
"i_b_to_ka": "float64",
"i_c_to_ka": "float64",
"i_n_from_ka": "float64",
"i_n_to_ka": "float64",
"i_n_ka": "float64",
"loading_a_percent": "float64",
"loading_b_percent": "float64",
"loading_c_percent": "float64",
Expand Down Expand Up @@ -1473,7 +1503,7 @@
"res_ext_grid_3ph": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\"],\"index\":[0],\"data\":[[9.999999999999998,-0.413182951688162,10.000000000000242,-0.413182951688386,9.999999999999785,-0.413182951688382]]}",
"_object": "{\"columns\":[\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\"],\"index\":[0],\"data\":[[null,null,null,null,null,null]]}",

@furqan463 furqan463 Sep 5, 2026

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This is the source of current error. All results in this file are being set to null. It seems the load flow not run or failed before generating this file.

@furqan463 furqan463 Sep 5, 2026

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To scope this out. This file needs to be restored and then updated in a separate PR with conversion of phase-wise results of gen in case of 3ph conversion.

"orient": "split",
"dtype": {
"p_a_mw": "float64",
Expand All @@ -1494,6 +1524,28 @@
"is_multiindex": false,
"is_multicolumn": false
},
"res_gen_3ph": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"vm_a_pu\",\"va_a_degree\",\"vm_b_pu\",\"va_b_degree\",\"vm_c_pu\",\"va_c_degree\",\"p_a_mw\",\"q_a_mvar\",\"p_b_mw\",\"q_b_mvar\",\"p_c_mw\",\"q_c_mvar\"],\"index\":[0],\"data\":[[null,null,null,null,null,null,null,null,null,null,null,null]]}",
"orient": "split",
"dtype": {
"vm_a_pu": "float64",
"va_a_degree": "float64",
"vm_b_pu": "float64",
"va_b_degree": "float64",
"vm_c_pu": "float64",
"va_c_degree": "float64",
"p_a_mw": "float64",
"q_a_mvar": "float64",
"p_b_mw": "float64",
"q_b_mvar": "float64",
"p_c_mw": "float64",
"q_c_mvar": "float64"
},
"is_multiindex": false,
"is_multicolumn": false
},
"res_load_3ph": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
Expand Down Expand Up @@ -1562,18 +1614,6 @@
"is_multiindex": false,
"is_multicolumn": false
},
"user_pf_options": {},
"res_gen_3ph": {
"_module": "pandas.core.frame",
"_class": "DataFrame",
"_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[0],\"data\":[[70.0,33.16588271275553]]}",
"orient": "split",
"dtype": {
"p_mw": "float64",
"q_mvar": "float64"
},
"is_multiindex": false,
"is_multicolumn": false
}
"user_pf_options": {}
}
}
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