#### Overview of this book

Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Preface
Free Chapter
Python Objects, Types, and Expressions
Python Data Types and Structures
Principles of Algorithm Design
Lists and Pointer Structures
Stacks and Queues
Trees
Hashing and Symbol Tables
Graphs and Other Algorithms
Searching
Sorting
Selection Algorithms
String Algorithms and Techniques
Design Techniques and Strategies
Implementations, Applications, and Tools
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# Summary

In this chapter, we discussed various ways to answer the question of how to find the ith smallest element in a list. The trivial solution of simply sorting a list to perform the operation of finding the ith smallest element was explored.

There is also the possibility of not necessarily sorting the list before we can determine the ith smallest element. The random selection algorithm allows us to modify the quicksort algorithm to determine the ith smallest element.

To further improve upon the random selection algorithm so that we can obtain a time complexity of O(n), we embarked on finding the median of medians to enable us to find a good split during partitioning.

In the next chapter, we will explore the world of strings. We will learn how to efficiently store and manipulate large amounts of text. Data structures and common string operations will be covered too.

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