Book Image

Python Data Structures and Algorithms

By : Benjamin Baka
Book Image

Python Data Structures and Algorithms

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 (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
5
Stacks and Queues
7
Hashing and Symbol Tables

Data preprocessing


Collection of data from the real world is fraught with massive challenges. The raw data collected is plagued with a lot of issues, so much so that we need to adopt ways to sanitize the data to make it suitable for use in further studies.

Why process raw data?

Raw data as collected from the field is rigged with human error. Data entry is a major source of error when collecting data. Even technological methods of collecting data are not spared. Inaccurate reading of devices, faulty gadgetry, and changes in environmental factors can introduce significant margins of errors as data is collected.

The data collected may also be inconsistent with other records collected over time. The existence of duplicate entries and incomplete records warrant that we treat the data in such a way as to bring out hidden and buried treasure. The raw data may also be shrouded in a sea of irrelevant data.

To clean the data up, we can totally discard irrelevant data, better known as noise. Data with...