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

Data types in R


Before we get into data structure concepts, let's look into data types provided by the R programming language. A basic data structure with a homogenous data type is based on a contiguous sequence of cells to enable fast access to any particular dataset. All homogeneous types support a single data type.

For example, in Figure 3.1 we have a numeric, logical, and character data type, however, it is stored as character.

Figure 3.1: Example of vector stored as character

Similarly, a matrix with multiple data types, as shown in Figure 3.2, will be coerced and stored as character data type. The array is an extension of the matrix from 2-D to n-D.

Figure 3.2: A matrix with numeric and characters are stored as 2D matrix with characters data type

All elements of a homogeneous data structure must be the same type, so R attempts to combine the different data types to the most flexible type in a priority order as shown in Figure 3.3:

Figure 3.3: Priority order of data types during coercion...