📚 Python for Data Analysis - Data Wrangling with pandas, NumPy & Jupyter

Welcome to the repository for Python for Data Analysis - Data Wrangling with pandas, NumPy & Jupyter by Wes McKinney! This repository contains notes, summaries, and exercise solutions to help you understand and apply the concepts presented in the book.

📖 Overview

• Author: Wes McKinney
• Published: August 2022
• Description: This book is a comprehensive guide to using Python for data analysis, focusing on data wrangling, cleaning, and manipulation using the popular pandas and NumPy libraries. It also covers essential tools like Jupyter notebooks for interactive coding and visualization.

📝 Notes

This section contains organized notes from the book, summarizing key concepts and important points.

Chapter 2: Python Language Basics, IPython, and Jupyter Notebooks

• Chapter 2 Notes

Chapter 3: Built-in Data Structures, Functions, and Files

• Chapter 3 Notes

Chapter 4: NumPy Basics: Arrays and Vectorized Computation

• Chapter 4 Notes

Chapter 5: Getting Started with pandas

• Chapter 5 Notes

Chapter 6: Data Loading, Storage, and File Formats

• Chapter 6 Notes

Chapter 7: Data Cleaning and Preparation

• Chapter 7 Notes

Chapter 8: Data Wrangling: Join, Combine, and Reshape

• Chapter 8 Notes

Chapter 9: Plotting and Visualization

• Chapter 9 Notes

Chapter 10: Data Aggregation and Group Operations

• Chapter 10 Notes

Chapter 11: Time Series

• Chapter 11 Notes

Chapter 12: Introduction to Modeling Libraries in Python

• Chapter 12 Notes

Chapter 13: Data Analysis Examples

• Chapter 13 Notes

🤝 Contributing

Contributions are welcome! If you have any additional notes, solutions, or resources to share, please create a pull request.

1. Fork the repository.
2. Create a new branch (e.g., feature/your-feature).
3. Make your changes.
4. Submit a pull request.

📄 License

This repository is licensed under the MIT License. See the LICENSE file for details.