Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
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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.