Original Readme text:
Text and supporting code for Think Stats, 2nd Edition

This is a fork of the repository for ThinkStats2 by Allen Downey. The online version of this book can be found here, and in the code folder of this repository there are jupyter notebooks for each chapter that I worked on while studying this book. The chapter jupyter notebooks are the files labeled as chap01ex.ipynb, chap02ex.ipynb, etc., and if you would like to see the work I did you can just click on these files to open them.

While going through each chapter notebook, in addition to doing the exercises, I attempted to recreate many of the analyses and visualizations using functions from python packages like numpy, pandas, scipy, statsmodels, matplotlib, and seaborn. As I did this, I also built my own libraries of analysis functions. Over time, I built these into my own data analysis and visualization package which I called DataStats. The repository for this can be found here.

If you would like to recreate the environment I was using when working through this book, you will need Python 3.7 and jupyter notebook installed, and you will need to use the requirements.txt file provided to install packages with the correct version numbers.

This book was a huge part of my learning in Python and data analytics. I highly recommend it for anyone interesting in learning how to do data analysis in Python using non-parametric statistical methods. In particular I recommend forking the original repository, and going through the notebooks in it, while studying the book, as I did here. Using the two resources together you can get a ton of hands-on practice while learning.