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

Searching unsorted and sorted vectors


Vectors are simple and widely used data structures used to perform search operations in R. The simplest form of search operation performed on vectors is a linear search or sequential search. In a linear search, each element is compared sequentially within the vector, and then suitable insertions or deletions are performed. Consider an element, S which is to be searched in an unsorted vector, V of length n (indexed from 1 to n). If the element S is not present in vector V, then a minimum of n comparisons are performed, and if it is present in V at position i, then a minimum of i comparisons are performed. In both scenarios, the number of comparisons is linear, resulting in O(n) as the functional form of system runtime for sequential search in the worst case scenario. The following R code performs a linear search of element S in a vector V of length n:

Sequential_search <- function(V,S,n) 
{ 
  i=1 
  present = FALSE 
  while(i ...