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R Data Structures and Algorithms
Increase speed and performance of your applications with efficient data structures and algorithms
About This BookSee how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examplesFind out about important and advanced data structures such as searching and sorting algorithmsUnderstand important concepts such as big-o notation, dynamic programming, and functional data structuredWho This Book Is ForThis book is for R developers who want to use data structures efficiently. Basic knowledge of R is expected.
What You Will LearnUnderstand the rationality behind data structures and algorithmsUnderstand computation evaluation of a program featuring asymptotic and empirical algorithm analysisGet to know the fundamentals of arrays and linked-based data structuresAnalyze types of sorting algorithmsSearch algorithms along with hashingUnderstand linear and tree-based indexingBe able to implement a graph including topological sort, shortest path problem, and Prim's algorithmUnderstand dynamic programming (Knapsack) and randomized algorithmsIn DetailIn this book, we cover not only classical data structures, but also functional data structures.
We begin by answering the fundamental 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.
Style and approachThis easy-to-read book with its fast-paced nature will improve the productivity of an R programmer and improve the performance of R applications. It is packed with real-world examples.
About This BookSee how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examplesFind out about important and advanced data structures such as searching and sorting algorithmsUnderstand important concepts such as big-o notation, dynamic programming, and functional data structuredWho This Book Is ForThis book is for R developers who want to use data structures efficiently. Basic knowledge of R is expected.
What You Will LearnUnderstand the rationality behind data structures and algorithmsUnderstand computation evaluation of a program featuring asymptotic and empirical algorithm analysisGet to know the fundamentals of arrays and linked-based data structuresAnalyze types of sorting algorithmsSearch algorithms along with hashingUnderstand linear and tree-based indexingBe able to implement a graph including topological sort, shortest path problem, and Prim's algorithmUnderstand dynamic programming (Knapsack) and randomized algorithmsIn DetailIn this book, we cover not only classical data structures, but also functional data structures.
We begin by answering the fundamental 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.
Style and approachThis easy-to-read book with its fast-paced nature will improve the productivity of an R programmer and improve the performance of R applications. It is packed with real-world examples.
414 pages, Kindle Edition
Published November 21, 2016
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