I recommend combining this book with McKinney's Pandas book and the author's excellent YouTube presentations at PyCon and PyData. Start with "Statistics for Hackers" by Jake VanderPlas and then look for his others.
I agree in principle that a better plaintext format could be interesting, but I don't see how embedding graphs etc could be easily done without a special interface of some kind.
That said I can imagine a mode where you simply have any editor open on one half of the screen and a browser that autorefreshes on the other.. this is more or less how I work with Emacs and Evince when working on Latex and it's great. Synchronising vertical position with the cursor position might be a challenge.
jupyter nbconvert --to python
Still a bummer that O'Reilly stopped selling books directly. There's been so many recently published books that I'm interested in that I can no longer purchase.
Nice tip about ebooks.com. I also was an Ora non DRM orphan.
The OP book is relatively recent (2016). The majority of code still runs as mentioned. Only a few commands/functions mentioned generate deprecation warning. This book is also covers packages and ML exhaustively. I have gone through this book cover to cover and enjoyed it. This is the first and only book that I found that covers data analysis with Python comprehensively. I wish author had covered data cleaning aspects little bit more.
Release date slated for October 2017.
Out of curiosity, what sorts of material had you hoped he'd cover on data cleaning?
It is a great compliment to Wear McKinney's "Python for Data Analysis" it is more like a recipe book than the internals as Wes' book is. Also, JVP includes more than just Pandas and NumPy goodies.
Highly Recommend, and fork to create your own curated handbook.