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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

Randomized selection

In the previous chapter, we examined the quick sort algorithm. The quick sort algorithm allows us to sort an unordered list of items but has a way of preserving the index of elements as the sorting algorithm runs. Generally speaking, the quick sort algorithm does the following:

  1. Selects a pivot.
  2. Partitions the unsorted list around the pivot.
  3. Recursively sorts the two halves of the partitioned list using step 1 and step 2.

One interesting and important fact is that after every partitioning step, the index of the pivot will not change even after the list has become sorted. It is this property that enables us to be able to work with a not-so-fully sorted list to obtain the ith-smallest number. Because randomized selection is based on the quick sort algorithm, it is generally referred to as quick select.

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