🐍 Python for Data Science (Piscine)

Overview

This repository contains the exercises and projects from the 42 Python for Data Science Piscine. The curriculum is designed to provide a deep dive into Python programming with a specific focus on data manipulation, analysis, and object-oriented programming.

The journey starts from the basics and progresses to advanced libraries like NumPy, Pandas, and Matplotlib.

📚 Modules

Module 0 - Starting

Basics & Environment Setup

• Introduction to Python syntax and scripts.
• Standard input/output operations.
• Basic data types and control structures.

Module 1 - Array

Numerical Computing with NumPy

• Understanding arrays and matrix operations.
• Image manipulation (loading, slicing, modifying pixels).
• Broadcasting and vectorization.

Module 2 - DataTable

Data Analysis with Pandas

• Loading and processing CSV/JSON datasets.
• Data cleaning and filtering.
• Statistical analysis and aggregation.

Module 3 - OOP

Object-Oriented Programming

• Classes, inheritance, and polymorphism.
• Error handling and exceptions.
• Special methods (dunder methods).

Module 4 - DoD

Data Oriented Design & Visualization

• Advanced plotting with Matplotlib/Seaborn.
• Data visualization best practices.
• Performance optimization.

🛠️ Requirements

• Python 3.10+
• Libraries: numpy, pandas, matplotlib, seaborn

pip install numpy pandas matplotlib seaborn

🚀 Usage

Each folder corresponds to a specific module and contains numbered exercises (e.g., ex00, ex01). To run a specific exercise:

cd "2 - DataTable/ex00"
python3 load_csv.py