#### 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
Other Books You May Enjoy

# Bubble sort algorithms

The idea behind the bubble sort algorithm is very simple. Given an unordered list, we compare adjacent elements in the list, and after each comparison, place them in the right order of magnitude. This works by swapping adjacent items if they are not in the correct order. The process is repeated n-1 times for a list of n items. In each such iteration, the largest element is arranged in the end. For example, in the first iteration, the largest element would be placed in the last position of the list, and again, the same process will be followed for the remaining n-1 items. In the second iteration, the second largest element will be placed at the second-to-last position in the list, and the process will then be repeated until the list is sorted.

Let's take a list with only two elements, {5, 2}, to understand the concept of the bubble sort, as shown in...