Python-Mini-Projects 🐍

A collection of small Python projects designed to demonstrate problem-solving skills, programming concepts, and practical applications. This repository includes projects across various domains such as mathematics, data processing, automation, web scripting, games, and simple machine learning experiments.

Each project is self-contained, well-documented, and structured to showcase coding style, algorithmic thinking, and Python proficiency. Ideal for learners, portfolio display, or anyone looking to explore Python project ideas.

Key Highlights:

• Math Projects: Algorithms, calculations, and problem-solving exercises.
• Data Processing: Scripts for file handling, data manipulation, and automation.
• Games & Fun: Mini games and interactive programs.
• Automation: Tools and scripts to automate everyday tasks.
• Web Scripting: Small projects interacting with web APIs and scraping data.
• Machine Learning Experiments: Beginner-friendly ML implementations using popular Python libraries.

🗂️ Repository Structure

python-mini-projects/
│
├── math_projects/
│   ├── brand_insurance/
│   ├── company_walls/
│   └── expression_maximizer
│
├── data_processing/
│   ├── binary_string_classifier
│   └── nlp_preprocessing
│
├── games/
│   └── snake_game/
│
├── web_scripts/
│
├── automation/
│   └── pdf_merger/
│
└── ml_experiments/
    └── covid_drug_comparator/

🚀 Getting Started

1. Clone the repository

git clone https://github.com/sobhankohanpour/python-mini-projects.git

2. Navigate to a project folder

cd python-mini-projects/Math-Projects

3. Run the Python scripts

python project_name.py

Each project folder contains a README.md with instructions, requirements, and usage examples.

📓 Running Notebook-Based Projects

Some projects come with .ipynb notebooks instead of .py files.
To run them:

1. Open the notebook using Jupyter Notebook, JupyterLab, or VS Code.
2. Install required dependencies listed in the project’s README.
3. Execute the cells sequentially to reproduce the results.

Alternatively, you can run the notebook online using Google Colab without local setup.

💡 Contribution

Contributions are welcome! Feel free to:

• Suggest new mini-projects
• Improve existing code
• Fix bugs or enhance documentation