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

Exercises


  • In a jump search algorithm, the optimum number of jumps required to attain the minimum cost of comparisons is, where n is the length of the input vector. Can you derive it? Also, what is the cost of comparison for the worst case, when the number of jumps is .
  • Evaluate the cost of searching an unsorted and a sorted (sorting based on frequency) vector, where each element has an equal probability of being accessed during the search operation, under the following conditions:

    • pi = 1/n, where i is the element in the given vector

    • pi = 1/n2 , where i is the element in the given vector

    • pi = 1/2n , where i is the element in the given vector

  • Implement the hash function in R using the mid-square method for four-and six-digit integers.

  • Implement the dictionary ADT using a hash table.