[rhizome31]

I have the paperback version and I have read the Jupyter, Numpy and Matplotlib chapters as well as most of the Pandas chapter (I haven't read the scikit-learn chapter at all). So far I like it. It's well written, well edited, overall a good quality book. It's really focused on the tools and it shows you how they work with small, contrived examples. This is good because you can use it as a reference, pick up pretty much any section and understand it. However it doesn't teach you much about the process of data science, which would require larger examples. In other words it's focused on the how but not on the what and why. Maybe a more accurate title would be Python Data Science Tooling Guide. In my opinion it should be perfect for people who've already done some data science in another environment and are switching to Python. Other people might need to seek additional guidance elsewhere.

[dansmerino]

What would you recommend for someone who has the skills with pandas and numpy but struggles with the what and why?