Particularly curious how it compares to Wes' Python for Data Analysis, aside from the sklearn stuff.

One of the challenges with Wes book is that it is quite old (2014). A lot of commands/functions/code mentioned in the book are obsolete and removed so code fails.

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.

The Wes McKinney Pandas book has a 2nd edition coming out next month. Raw edition is already available on Safari here.

http://shop.oreilly.com/product/0636920050896.do

Release date slated for October 2017.

Good to know. I've been recommending Wes's book for a some time now to people new to data work in Python, but between the discussion here and the consistently high quality of Jake's blog posts and demos, I'll have to keep this one in mind.

Out of curiosity, what sorts of material had you hoped he'd cover on data cleaning?

Any book recommendations for a good discussion of data cleaning?

I use this along with Chris Albons similar repo of recipes (http://shop.oreilly.com/product/0636920023784.do).

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.

Chris Albons } https://chrisalbon.com