The first edition of this book was published in 2012, during a time when open source data analysis libraries for Python (such as pandas) were very new and developing rap‐ idly. In this updated and expanded second edition, I have overhauled the chapters to account both for incompatible changes and deprecations as well as new features that have occurred in the last five years. I’ve also added fresh content to introduce tools that either did not exist in 2012 or had not matured enough to make the first cut. Finally, I have tried to avoid writing about new or cutting-edge open source projects that may not have had a chance to mature. I would like readers of this edition to find that the content is still almost as relevant in 2020 or 2021 as it is in 2017.
The major updates in this second edition include:
• All code, including the Python tutorial, updated for Python 3.6 (the first edition used Python 2.7)
• Updated Python installation instructions for the Anaconda Python Distribution and other needed Python packages
• Updates for the latest versions of the pandas library in 2017
• A new chapter on some more advanced pandas tools, and some other usage tips
• A brief introduction to using statsmodels and scikit-learn
I also reorganized a significant portion of the content from the first edition to make the book more accessible to newcomers.