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

Bin sort and radix sort


Bin sort is one of the most efficient algorithms, wherein an input vector is split into multiple bins, and then sorting is performed within each bin. The elements are assigned to the bins based on the computations performed on each element. The bins can be a list of multiple vectors or a linked list. The current execution uses a list of multiple vectors as bins. The following R code performs the bin sort operation on a numeric vector (V) containing n elements. The maxValue variable denotes the element with maximum value within the input vector:

Bin_Sort=function(V,n,maxValue){ 
  bin <-list("binValues"=list(), "nElement"=NA) 
  ## create empty bins 
  for(i in 1:n){ 
    bin[["binValues"]][[i]]<-NA 
    bin[["nElement"]][i]<-0 
  } 
  ## add elements into suitable bins 
  bin <- addItem(V=V,bin=bin,maxValue=maxValue,n=n) 
  ## bind all bins into a single sorted vector 
  output <- bindSorted_vec(bin...