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 | ★★☆ | [The Algorithm Design Manual](https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693), by Steven S. Skiena | The book is written in more readable text. Some find it comprehensive than other books. You can also find some good resources (including the author's own video lectures) on its [official website](http://www.algorist.com). |
 | ★★★ | [Algorithms](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X), by Robert Sedgewick and Kevin Wayne | This book is neatly categorized, coupled with elaborate explanations and fantastic illustrations. It is used in some IOI training camps as a textbook. |
 |     | [Algorithms and Data Structures in Action](https://www.manning.com/books/algorithms-and-data-structures-in-action), by Marcello La Rocca | This book provides a different approach to algorithms, balancing theory with a more practical angle, with a section per-chapter focusing on how to apply algorithms to real-world use cases that can be found in your daily work, or in competitive programming; it also presents a blend of classic, advanced, and new algorithms. |
+| *** | [Grokking Data Structures](https://www.manning.com/books/grokking-data-structures), by Marcello La Rocca | This fun, friendly, and fully-illustrated guide makes it easy to learn useful data structures you’ll put to work every day. |
 | ★★★ | [Algorithms](https://jeffe.cs.illinois.edu/teaching/algorithms/), by Jeff Erickson | A free electronic version of a self-published textbook licensed under CC by 4.0. This is a well written book from lecture notes of theoretical computer science courses at the University of Illinois. Covers the main paradigms of backtracking, dynamic programming, greedy, and particularly graphs in depth. |
 
 ### Books for Mathematics