Python Data Science Handbook

I loved his Statistics for Hackers talk: https://speakerdeck.com/pycon2016/jake-vanderplas-statistics...

These types of books are always interesting to me because they tackle so many different things. They cover a range of topics at a high level (data manipulation, visualization, machine learning) and each could have its own book. They balance teaching programming while introducing concepts (and sometimes theory).

In short I think it's hard to strike an appropriate balance between these but this seems to be a good intro level book.

I used the Kernel Density Estimation (KDE) page/blog at my very first job. It was immensely useful and I've loved his work ever since.

VanderPlas' handbook remains remarkably relevant despite rapid ecosystem changes. His focus on fundamentals - NumPy, Pandas, Matplotlib - rather than trendy libraries is why. The tools change, but understanding data structures, vectorization, and visualization principles doesn't age.

This book was absolute fire for getting started with data science in 2017-2018, Jake is a great teacher.

He's a great writer and I miss his blog. He had an awesome post on pivot table that I think is now a part of this book.

Interesting choice of Pandas in this day and age. Maybe he’s after imparting general concepts that you could apply to any tabular data manipulator rather than selecting for the latest shiny tool.

This is one of the few books that I read cover-to-cover when I was starting out learning Data Science in 2020/21. Will recommend.

I wouldn't say it's a handbook because it's more like an introduction. But it's pretty well written.

it's written 8 years ago though, there is a 2ed of the book by the same author.