# R Data Structures and Algorithms

 Learn Understand the rationality behind data structures and algorithms Understand computation evaluation of a program featuring asymptotic and empirical algorithm analysis Get to know the fundamentals of arrays and linked-based data structures Analyze types of sorting algorithms Search algorithms along with hashing Understand linear and tree-based indexing Be able to implement a graph including topological sort, shortest path problem, and prim’s algorithm Understand dynamic programming (Knapsack) and randomized algorithms 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. See how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examples Find out about important and advanced data structures such as searching and sorting algorithms Understand important concepts such as big-o notation, dynamic programming, and functional data structured 276 8 hours 16 minutes 9781786465153 21 Nov 2016
 Introduction to data structure Abstract data type and data structure Relationship between problem and algorithm Basics of R First class functions in R Exercises Summary
 Getting started with data structure Memory management in R Exercises Summary
 Data types in R Object-oriented programming using R Linked list Array-based list Analysis of list operations Exercises Summary
 Stacks Queues Dictionaries Exercises Summary
 Sorting terminology and notation Three Θ(n²) sorting algorithms Shell sort Merge sort Quick sort Heap sort Bin sort and radix sort An empirical comparison of sorting algorithms Lower bounds for sorting Exercises Summary
 Searching unsorted and sorted vectors Self-organizing lists Hashing Exercises Summary
 Linear indexing ISAM Tree-based indexing 2-3 trees B-trees Exercises Summary
 Terminology and representations Graph implementations Graph traversals Shortest path problems Minimum-cost spanning tree Exercises Summary
 Dynamic programming Randomized algorithms Exercises Summary