Book Image

Hands-On Data Structures and Algorithms with Python - Second Edition

By : Dr. Basant Agarwal, Benjamin Baka
Book Image

Hands-On Data Structures and Algorithms with Python - Second Edition

By: Dr. Basant Agarwal, Benjamin Baka

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.
Table of Contents (16 chapters)

Selection algorithms

Selection algorithms fall under a class of algorithms that seek to answer the problem of finding the ith-smallest element in a list. When a list is sorted in ascending order, the first element in the list will be the smallest item in the list. The second element in the list will be the second-smallest element in the list. The last element in the list will be the least-smallest (or, largest) element in the list.

In creating the heap data structure, we have come to understand that a call to the pop method will return the smallest element in the min-heap. The first element to pop off a min heap is the smallest element in the list. Similarly, the seventh element to be popped off the min heap will be the seventh-smallest element in the list. Therefore, finding the ith-smallest element in a list will require us to pop the heap i number of times. This is a very simple...