Data Structures with Python: Get familiar with the common Data Structures and Algorithms in Python

by Dr. Harsh Bhasin

Length: 573 pages
Edition: 1
Language: English
Publisher: BPB Publications
Publication Date: 2023
ISBN-10: B0C16YFVWQ
Sales Rank: #0 (See Top 100 Books)

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Develop a strong foundation in Data Structures and Algorithms and become a skilled programmer

Key Features

Explore various data structures and algorithms and their applications.
Learn how to use advanced data structures and algorithms to solve complex computational problems.
An easy-to-understand guide that gives a comprehensive introduction to data structures and algorithms using the Python programming language.

Description

Data structures are a way of organizing and storing data in a computer so that it can be accessed and manipulated efficiently. If you want to become an accomplished programmer and master this subject, then this book is for you.

The book starts by introducing you to the fascinating world of data structures and algorithms. This book will help you learn about different algorithmic techniques such as Dynamic programming, Greedy algorithms, and Backtracking, and their applications in solving various computational problems. The book will then teach you how to analyze the complexity of Recursive algorithms. Moving on, the book will help you get familiar with the concept of Linked lists, which is an important foundation for understanding other data structures, such as Stacks and Queues, which are covered in detail later in this book. The book will also teach you about advanced data structures such as Trees and Graphs, their different types, and their applications. Towards the end, the book will teach you how to use various Sorting, Searching Selection and String algorithms.

By the end of the book, you will get a comprehensive and in-depth understanding of various data structures and algorithms and their applications in solving real-world computational problems efficiently.

What you will learn

Get familiar with the fundamentals of data structures such as arrays, linked lists, stacks, and queues.
Understand the basics of algorithm analysis and complexity theory.
Explore different approaches to the algorithm design, such as divide-and-conquer, dynamic programming, and greedy algorithms.
Work with common data structures such as arrays, linked lists, stacks, queues, trees, heaps, and graphs.
Discover sorting and searching algorithms, including hash tables and string algorithms.

Who this book is for

The book is aimed at Computer Science students, Software Engineers, and anyone interested in learning about data structures and algorithms

Cover Page
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewer
Acknowledgement
Preface
Errata
Table of Contents
1. Introduction to Data Structures
    Structure
    Objectives
    Introduction
    Data types
    Types of data structures
    Game of clones
    The game of clones revisited
    Conclusion
    Multiple choice questions
    Theory-based questions
    Application-based questions
2. Design Methodologies
    Structure
    Objectives
    Greedy approach
    Divide and conquer
    Backtracking and dynamic programming
    Longest common sub-sequence
    Conclusion
    Multiple choice questions
    Programming/application
    Further references
3. Recursion
    Structure
    Objectives
    Exponentiation
    Tower of Hanoi
    Rabbit problem
    Generating binary numbers
    Lists
    Numbers
    Conclusion
    Multiple choice questions
    Programming
    Further references
4. Arrays
    Structure
    Objectives
    Introduction
        Memory map
    Address in column-major
    Inserting and deleting
    Operations on arrays
        Linear search
    Problems
    Conclusion
    Multiple choice questions
    Programming
5. Linked List
    Structure
    Objectives
    One-way linked list
    Traversing
    Insertion and deletion
    Two-way linked list
    Traversing
    Insertion and deletion
    Cyclic list
    Stacks and Queues
    Reversing a linked list
    Concatenate lists
    Check cycle
    Conclusion
    Multiple choice questions
    Theory
    Problems
6. Stacks
    Structure
    Objectives
    Introduction
    Implementing two stacks using a single list
    Types and uses
    Reversing a string
    Expressions
        Evaluation of postfix
        Infix to postfix
        Infix to prefix
    Problems
    Conclusion
    Multiple Choice Questions
    Problems
7. Queues
    Structure
    Objectives
    Introduction
    Algorithm and implementation
    Circular queue
    Doubly-ended queue: DEQueue
    Generating binary numbers using a queue
    Stack using two queues
    Stack from a single queue
    Scheduling
    Conclusion
    Multiple Choice Questions
    Problems
8. Trees-I
    Introduction
    Structure
    Objectives
    Definition and terminology
    Representation of a Binary Tree
        Traversal
        Post-order traversal
        Pre-order traversal
    Binary search tree
        Insertion in a BST
        Deletion
        Leftmost node
        Rightmost node
    Conclusion
    Multiple choice questions
    Numerical/problems
9. Trees-II
    Structure
    Objectives
    AVL trees
        Insertion
        Deletion
    Insertion in an AVL tree
        Deletion from an AVL Tree
    B Trees
    Conclusion
    Multiple choice questions
    Theory
    Numericals
10. Priority Queues
    Structure
    Objectives
    Introduction to priority queues
        Structure of heap
        Operations
    Inserting an element in a heap
    Deletion
    Heap sort
    Problems
    Conclusion
    Multiple choice questions
    Programming
    Further references
11. Graphs
    Introduction
    Structure
    Objectives
    Representation
    Traversals
    Depth First Search
        Breadth First Search
        Topological sort
    Spanning tree
    Kruskal’s algorithm
    Conclusion
    Multiple choice questions
    Numerical/application based
    Programming
12. Sorting
    Structure
    Objectives
    Bubble sort
    Comb sort
    Selection sort
    Insertion sort
    Radix sort
    Counting sort
    Merge and merge sort
    Partition and quick sort
    Conclusion
    Illustrations
    Multiple choice questions
    Theory
13. Median and Order Statistics
    Introduction
    Structure
    Objectives
    Introduction to median and order statistics
    Median of medians
    Median using heaps
    Median using insertion sort
    Median using partition
    Conclusion
    Solved problems
    Multiple choice questions
    Applications/implementation
    Bibliography
14. Hashing
    Structure
    Objectives
    Hash tables
    Storing information
        Sorted sequential array
        Linked list representation
        AVL trees
    Hashing
        Hash function
        Collision resolution
        Selecting hash function
    Collisions
    Collision resolution
        Linear probing
        Quadratic probing
        Separate chaining
    Solved problems
    Conclusion
    Multiple choice questions
    Theory
    Problems
    Programming
15. String Matching
    Structure
    Objectives
    Introduction to string-matching
    Brute force method
    Rabin Karp
    Knuth–Morris–Pratt algorithm
    KMP method
    Conclusion
    Multiple choice questions
    Theory/applications
    Find errors/special cases
    References
Appendix 1: All Pairs Shortest Path
    Introduction
    All Pairs Shortest Path
Appendix 2: Tree Traversals
    Introduction
    In-Order Traversal
    Pre-order traversal
    Post-order traversal
Appendix 3: Dijkstra’s Shortest Path Algorithm
    Introduction
    Dijkstra’s shortest path algorithm
Appendix 4: Supplementary Questions
    Arrays: Level 0
    Arrays: Level 1
    Stacks
    Linked List
    Trees
    Graphs
    Application based
Index