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

✍ Scribed by Dr. Harsh Bhasin

• Publisher: BPB Publications
• Year: 2023
• Tongue: English
• Leaves: 404
• Category: Library

✦ Synopsis

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

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.

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

✦ 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
   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
   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
    Solved problems
    Multiple choice questions
    Applications/implementation
    Bibliography
16. 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
17. 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