Polars-Learning-Path

Welcome to the Polars-Learning-Path repository! This repository is dedicated to providing resources, tutorials, and examples for learning and working with Polars, a fast DataFrame library in Rust and Python. Our goal is to help users of all levels gain proficiency in using Polars for data manipulation and analysis.

About Polars

Polars is a DataFrame library written in Rust, offering high performance and efficient data processing capabilities. It is also available in Python, providing an easy-to-use interface while leveraging Rust's speed.

For more information on contributing to this repository, please see the Contributing section.

Repository Structure

• Tutorials/: Contains step-by-step guides that cover various aspects of Polars, providing a comprehensive learning experience.
• Examples/: Offers practical examples that demonstrate the use of Polars in a variety of scenarios, showcasing its capabilities.
• Practice/: Includes exercises designed to help practice and reinforce Polars skills, catering to different levels of proficiency.
• Projects/: Features hands-on projects with real-world data, aimed at mastering Polars through applied learning.
• Datasets/: Provides sample datasets used within tutorials, examples, and projects, aiding in practical exercises and demonstrations.
• Scripts/: Contains utility scripts for data processing and analysis, complementing the learning material in other directories.

Maintainer

This repository is currently maintained by Dr.Saad Laouadi. If you have any questions, feedback, or suggestions, feel free to reach out or open an issue.

• Name: Dr Saad Laouadi

• GitHub:

• LinkedIn:

• Email:

Table of Contents

• Introduction
• Tutorials
  • Course Setup
    • Environment Setup with venv
    • Environment Setup with conda
    • Environment Setup with mamba
  • Polars Vs Pandas
    • Pandas Vs Polars: Pandas
    • Polars Vs Pandas: Polars
  • Reading Data
    • Reading Plain Text Data
• Examples
• Projects
• Scripts
• Datasets
• Presentation for Polars
• Download Data Notebook
• Download Datasets Script

Getting Started

To get started with this repository, clone it to your local machine using:

git clone https://github.com/your-username/Polars-Learning-Path.git

Prerequisites

Ensure you have Python installed on your system. You can download Python from python.org. Additionally, you'll need to install Polars. You can install it via pip:

pip install polars

Running the Examples

To run the examples, navigate to the examples/ directory and execute the Python scripts:

cd Polars-Learning-Path/examples/
python example_script.py

Contributing

We welcome contributions to the Polars-Learning-Path repository! Whether it's adding new examples, improving tutorials, or fixing bugs, your contributions are greatly appreciated.

To contribute:

1. Fork the repository.
2. Create a new branch for your feature (git checkout -b feature/NewFeature).
3. Commit your changes (git commit -m 'Add some NewFeature').
4. Push to the branch (git push origin feature/NewFeature).
5. Open a pull request.

Acknowledgements

• Polars GitHub Repository
• Polars official documentation

License

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This work is licensed under Attribution-NonCommercial-ShareAlike 4.0 International