Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
If you are reading the 1st Edition (published in 2012), please find the
reorganized book materials on the 1st-edition branch.
- Chapter 2: Python Language Basics, IPython, and Jupyter Notebooks
- Chapter 3: Built-in Data Structures, Functions, and Files
- Chapter 4: NumPy Basics: Arrays and Vectorized Computation
- Chapter 5: Getting Started with pandas
- Chapter 6: Data Loading, Storage, and File Formats
- Chapter 7: Data Cleaning and Preparation
- Chapter 8: Data Wrangling: Join, Combine, and Reshape
- Chapter 9: Plotting and Visualization
- Chapter 10: Data Aggregation and Group Operations
- Chapter 11: Time Series
- Chapter 12: Advanced pandas
- Chapter 13: Introduction to Modeling Libraries in Python
- Chapter 14: Data Analysis Examples
- Appendix A: Advanced NumPy
The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license. Read more at the Open Source Initiative.