Polars Data Analysis Environment

A Docker-based development environment for data analysis using Polars, Jupyter Notebook, and Python 3.9.

Prerequisites

• Docker installed on your system
• Git (optional, for cloning the repository)

Quick Start

1. Build the Docker image:

   ./01-docker_build.sh
   # or
   docker build -t polars-data-analysis .

2. Run the container:

   ./02-docker_run.sh
   # or
   docker run -p 8888:8888 -v ${PWD}:/app polars-data-analysis

3. Open your web browser and navigate to the URL shown in the terminal output (usually starts with http://127.0.0.1:8888/...)

Installed Packages

• Polars
• NumPy
• Pandas
• Matplotlib
• Seaborn
• scikit-learn
• Jupyter

Features

• Python 3.9 base environment
• Jupyter Notebook server accessible via browser
• Volume mounting for persistent notebook storage
• Pre-installed data science packages
• Polars for high-performance data manipulation

Development

The project uses volume mounting (-v ${PWD}:/app) to sync the local directory with the container's /app directory. Any changes made to notebooks or other files will persist on your local machine.

License

This project is open-source and available under the MIT License.