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Python Data Structures and Algorithms

Python Data Structures and Algorithms

By : Benjamin Baka
2.7 (11)
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Python Data Structures and Algorithms

Python Data Structures and Algorithms

2.7 (11)
By: Benjamin Baka

Overview of this book

Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications.
Table of Contents (14 chapters)
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5
Stacks and Queues
7
Hashing and Symbol Tables

Summary


Graphs and heaps have been treated in this chapter. We looked at ways to represent a graph in Python using lists and dictionaries. In order to traverse the graph, we looked at breadth-first searches and depth-first searches.

We then switched our attention to heaps and priority queues to understand their implementation. The chapter ended with using the concept of a heap to find the ith-smallest element in a list.

The subject of graphs is very complicated and just one chapter will not do justice to it. The journey with nodes will end with this chapter. The next chapter will usher us into the arena of searching and the various means by which we can efficiently search for items in lists.

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