Book Image

R Data Structures and Algorithms

By : PKS Prakash, Achyutuni Sri Krishna Rao
Book Image

R Data Structures and Algorithms

By: PKS Prakash, Achyutuni Sri Krishna Rao

Overview of this book

In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth. Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort.
Table of Contents (17 chapters)
R Data Structures and Algorithms
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface

Exercises


  1. Generate an adjacency matrix and an adjacency list for the following graph:

  2. Generate a DFS and BFS tree for the preceding graph.

  3. Prove the following hypothesis: An acyclic undirected graph with n nodes has no more than n-1 edges.

  4. Find the MST for the graph given in Figure 8.13 using Prim's and Kruskal's algorithm. Do they give the same MSTs? If no, in what type of situations do they give different MSTs.

  5. Starting from vertex B, can you obtain single-source shortest paths using Dijkstra's algorithm? Do the edges obtained in question 4 of Exercises overlap with the edges obtained using Dijkstra's algorithm? If yes, explain the logic behind the overlap.