42 Python Data Science Piscine

Welcome to my repository for the Python Data Science Piscine at 42. This intense 5-day bootcamp focuses on mastering Python through hands-on projects in data analysis, image processing, object-oriented programming, and more.

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📚 Contents

🧠 Day 0 – Python Basics

Basic Python syntax, data structures, script handling, and reimplementing core functions.

• ex00: Hello script
• ex01: Format date/time output
• ex02: Type detector function
• ex03: NULL type handler
• ex04: Even or Odd checker
• ex05: String character analysis
• ex06: Reimplement filter + filter words by length
• ex07: Encode text in Morse code
• ex08: Custom tqdm progress bar using yield
• ex09: Create and install a Python package

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📸 Day 1 – Arrays & Image Manipulation

Using NumPy and image libraries to work with arrays, transformations, and color filters.

• ex00: Compute BMI and apply limits
• ex01: 2D slicing of nested lists
• ex02: Load image and display RGB array
• ex03: Zoom on image and reshape
• ex04: Rotate image using transpose
• ex05: Apply color filters (invert, red, green, blue, grey)

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📊 Day 2 – Working with DataTables

Explore real-world datasets with Pandas and visualize them using Matplotlib/Seaborn.

• ex00: Load CSV and display dimensions
• ex01: Display life expectancy for a country
• ex02: Compare population between countries (1800–2050)
• ex03: Scatterplot of GDP vs life expectancy in 1900

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🧱 Day 3 – Oriented Object Programming

Dive into class design, inheritance, decorators, and vector math with OOP.

• ex00: Abstract Character class + Stark subclass
• ex01: Baratheon & Lannister classes + factory method
• ex02: Diamond inheritance in King class
• ex03: calculator class (scalar operations)
• ex04: Vector ops (dot product, add, sub) via decorators

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🧬 Day 4 – Data-Oriented Design

Higher-order functions, statistical operations, decorators, and dataclasses.

• ex00: ft_statistics() with dynamic kwargs (mean, std, etc.)
• ex01: Closure with function chaining (outer/inner)
• ex02: Function call limiter (decorator)
• ex03: Student dataclass with login and random ID

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🛠️ Technologies Used

• Python 3.10
• NumPy
• Pandas
• Matplotlib / Seaborn
• PIL / OpenCV (image manipulation)

✅ Evaluation

Each exercise is submitted via Git and evaluated through peer reviews and automated grading (Deepthought).

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🚀 Author

Quentin – Student at 42 Perpignan

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Feel free to explore the code, try the exercises, and suggest improvements!