Pydata Book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
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| Pydata Book | 19,408 | 12 days ago | 4 | other | Jupyter Notebook | |||||
| Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media | ||||||||||
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Readme
Python for Data Analysis, 3rd Edition
Materials and IPython notebooks for "Python for Data Analysis, 3rd Edition" by Wes McKinney, published by O'Reilly Media. Book content including updates and errata fixes can be found for free on my website.
Follow Wes on Twitter: 
2nd Edition Readers
If you are reading the 2nd Edition (published in 2017), please find the
reorganized book materials on the 2nd-edition branch.
1st Edition Readers
If you are reading the 1st Edition (published in 2012), please find the
reorganized book materials on the 1st-edition branch.
IPython Notebooks:
- 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: Introduction to Modeling Libraries in Python
- Chapter 13: Data Analysis Examples
- Appendix A: Advanced NumPy
License
Code
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.
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