Python Libraries Learning Repository

This repository contains my learning journey with various Python libraries. Each folder within this repository corresponds to a specific library and contains code examples, exercises, and notes that I used to understand and practice these libraries.

Libraries Covered

• Matplotlib: 2D plotting library for creating static, animated, and interactive visualizations.
• NumPy: Numerical computing with powerful array objects.
• OOP in Python: Object-Oriented Programming concepts in Python.
• OpenCV: Computer vision and image processing.
• Pandas: Data manipulation and analysis.
• Seaborn: Statistical data visualization built on top of Matplotlib.

Repository Structure

The repository is organized into the following folders:

.
├── Matplotlib/
├── NumPy/
├── OOP/
├── OpenCV/
├── Pandas/
└── Seaborn/

• Matplotlib/: Contains examples of various plots like line plots, bar charts, histograms, and scatter plots.
• NumPy/: Includes exercises on array creation, manipulation, mathematical operations, and linear algebra.
• OOP/: Contains code demonstrating the principles of Object-Oriented Programming such as classes, inheritance, polymorphism, and encapsulation.
• OpenCV/: Includes scripts related to image processing, video processing, and object detection.
• Pandas/: Contains scripts and notebooks that cover data manipulation, DataFrames, series operations, handling missing data, and more.
• Seaborn/: Showcases the use of Seaborn for statistical plots such as boxplots, violin plots, and heatmaps.

Usage

To explore any of the libraries, navigate to the respective folder and run the Python scripts or Jupyter notebooks. For example:

cd Matplotlib
python matplotlib7.py

If you're using Jupyter Notebook then:

jupyter notebook example_notebook.ipynb

Contribution

This repository is primarily for personal learning, but contributions are welcome. If you want to add new examples or improve existing ones:

• Fork the repository.
• Create a new branch (git checkout -b feature-branch).
• Commit your changes (git commit -m 'Add some feature').
• Push to the branch (git push origin feature-branch).
• Open a pull request.