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

Summary


Computational power has been continuously increasing in the last couple of decades, and so does the amount of data captured by different industries. To cope with data size, faster and efficient information retrieval is an eminent requirement.

In this chapter, you were introduced to ADT and data structure. ADT is used to define high-level features and operations representing different data structures, and algorithms are used to implement ADT. A data type should be atomic, traceable, accurate, and have clear and concise characteristic properties for efficiency along with unambiguity. You also learned the basics of R, including data type, conditional loops, control structure, and first class functions.

The computational time taken by an algorithm is most important objective considered while selecting data structures and algorithms. The next chapter will provide the fundamentals for the analysis of algorithms.