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

Terminology and representations


A graph (G) is a network of vertices (V) interconnected using a set of edges (E). Let |V| represent the count of vertices and |E| represent the count of edges. The value of |E| lies in the range of 0 to |V|2 - |V|. Based on the directional edges, the graphs are classified as directed or undirected. In directed graphs, the edges are directed from one vertex towards the other, whereas in undirected graphs, each vertex has an equal probability of being directionally connected with the others. An undirected graph is said to be connected if all the vertices are connected with at least one edge. If the vertices are indexed, then it is said to be a labeled graph, and if the edges are associated with some value (cost or weights), then it is said to be a weighted graph. Adjacent vertices (P and Q) connected by an edge are termed as neighbors (P, Q), and the connecting edge is termed as an incident. Figure 8.1 represents undirected, directed, and labeled (with weights...