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

Linear indexing


Indexing is defined as the process of associating a key with data location. The basic field of a data index includes a search key and a pointer. The search key is set of attributes that is used to look up records from a file and the pointer stores the address of the data stored in memory. The index file consists of records, also known as index entries, of the form shown in Figure. 7.1:

Figure 7.1: Example of index entries

Indexing helps in organizing a large dataset. A database has the following generic properties:

  • The records are in a structured tabular format

  • Records are searched using single or a combination of keys

  • Aggregation queries such as sum, min, max, and average are used to summarize the dataset

Indexing in databases is used to enforce a uniqueness into records, which helps in speedy access of data. A database can have several filesystems associated with it by using indexing. This is shown in Figure 7.2 using a store database example. The store database consists of...