Practice exercises and examples in Python to build strong foundations in data science: NumPy, Pandas, Matplotlib, machine learning, and more.

Follow these steps to set up your environment and run the exercises.

git clone https://github.com/DavFilsDev/data-science-python-practice.git
cd data-science-python-practice

python3 -m venv venv
source venv/bin/activate

python -m venv venv
venv\Scripts\activate

Install all dependencies from the requirements.txt file:

pip install -r requirements.txt

Example with the first NumPy exercise:

python numpy/numpy_intro.py

data-science-python-practice/
├── numpy/
├── pandas/
├── matplotlib/
├── requirements.txt # Project dependencies
└── README.md # Project instructions

• NumPy: Arrays, math operations, random numbers, linear algebra
• Pandas: Data manipulation
• [Coming Soon] Matplotlib & Seaborn: Data visualization
• [Coming Soon] Scikit-learn: Machine learning basics
• [Coming Soon] Mini-projects on real datasets

This repository is for personal learning, but feel free to fork it and practice as well.