Python Data Structures and Algorithms

Implement classic and functional data structures and algorithms using Python
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Python Data Structures and Algorithms

Benjamin Baka

4 customer reviews
Implement classic and functional data structures and algorithms using Python
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Book Details

ISBN 139781786467355
Paperback310 pages

Book Description

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

Chapter 1: Python Objects, Types, and Expressions
Understanding data structures and algorithms
Python for data
Summary
Chapter 2: Python Data Types and Structures
Operations and expressions
Built-in data types
Sets
Modules for data structures and algorithms
Summary
Chapter 3: Principles of Algorithm Design
Algorithm design paradigms
Recursion and backtracking
Runtime analysis
Amortized analysis
Summary
Chapter 4: Lists and Pointer Structures
Arrays
Pointer structures
Nodes
Finding endpoints
Singly linked lists
A faster append operation
Getting the size of the list
Improving list traversal
Deleting nodes
Clearing a list
Doubly linked lists
Circular lists
Summary
Chapter 5: Stacks and Queues
Stacks
Queues
Summary
Chapter 6: Trees
Terminology
Tree nodes
Binary trees
Summary
Chapter 7: Hashing and Symbol Tables
Hashing
Hash table
Summary
Chapter 8: Graphs and Other Algorithms
Graphs
Directed and undirected graphs
Weighted graphs
Graph representation
Graph traversal
Other useful graph methods
Priority queues and heaps
Selection algorithms
Summary
Chapter 9: Searching
Linear Search
Binary search
Interpolation search
Summary
Chapter 10: Sorting
Sorting algorithms
Bubble sort
Insertion sort
Selection sort
Quick sort
Summary
Chapter 11: Selection Algorithms
Selection by sorting
Randomized selection
Deterministic selection
Summary
Chapter 12: Design Techniques and Strategies
Classification of algorithms
Technical implementation
Complexity classes
Summary
Chapter 13: Implementations, Applications, and Tools
Tools of the trade
Data preprocessing
Machine learning
Data visualization
Summary

What You Will Learn

  • Gain a solid understanding of Python data structures.
  • Build sophisticated data applications.
  • Understand the common programming patterns and algorithms used in Python data science.
  • Write efficient robust code.

Authors

Table of Contents

Chapter 1: Python Objects, Types, and Expressions
Understanding data structures and algorithms
Python for data
Summary
Chapter 2: Python Data Types and Structures
Operations and expressions
Built-in data types
Sets
Modules for data structures and algorithms
Summary
Chapter 3: Principles of Algorithm Design
Algorithm design paradigms
Recursion and backtracking
Runtime analysis
Amortized analysis
Summary
Chapter 4: Lists and Pointer Structures
Arrays
Pointer structures
Nodes
Finding endpoints
Singly linked lists
A faster append operation
Getting the size of the list
Improving list traversal
Deleting nodes
Clearing a list
Doubly linked lists
Circular lists
Summary
Chapter 5: Stacks and Queues
Stacks
Queues
Summary
Chapter 6: Trees
Terminology
Tree nodes
Binary trees
Summary
Chapter 7: Hashing and Symbol Tables
Hashing
Hash table
Summary
Chapter 8: Graphs and Other Algorithms
Graphs
Directed and undirected graphs
Weighted graphs
Graph representation
Graph traversal
Other useful graph methods
Priority queues and heaps
Selection algorithms
Summary
Chapter 9: Searching
Linear Search
Binary search
Interpolation search
Summary
Chapter 10: Sorting
Sorting algorithms
Bubble sort
Insertion sort
Selection sort
Quick sort
Summary
Chapter 11: Selection Algorithms
Selection by sorting
Randomized selection
Deterministic selection
Summary
Chapter 12: Design Techniques and Strategies
Classification of algorithms
Technical implementation
Complexity classes
Summary
Chapter 13: Implementations, Applications, and Tools
Tools of the trade
Data preprocessing
Machine learning
Data visualization
Summary

Book Details

ISBN 139781786467355
Paperback310 pages
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