These days when you can find a package for every problem you encounter, learning about algorithms and data structures seems to be a waste of time. But finding the right package or knowing the best data structure to handle your problem most efficiently cannot be achieved without knowing about data structures. Jeremy Kubica’s Data Structures the Fun Way is a fun intro to the topic for self-taught programmers and data scientists.

The book tries to be language agnostic, using a Python-like pseudocode to describe the algorithms and data structures. Although it is relatively easy to translate the pseudocode to Python, we think at least github repo with a reference implementation in Python (and maybe in other languages as well) would come in handy. But we are happy to announce that this is the only thing we can criticize in this title!

The topics covered in the book are very well-selected and well-suited to data scientists. Almost all introductory books on the topic deal with binary search, stacks and queues, and hash tables. But this one devotes chapters to grid search, spatial trees, nearest neighbor search, and Bloom filters, too – to mention a few relevant topics to aspiring data scientists. Kubica’s style is very entertaining yet rigorous. We loved the code examples and the commentaries on the snippets, which shed light on the inner workings of the algos. We’d put this book on our previous list of algorithms and data structures books for data scientists somewhere between Grokking Algorithms and Classic Computer Science Problems with Python.

Disclaimer: We got a pdf copy of the book from No Starch for review.