Functional Data Structures in R: Advanced Statistical Programming in R

Description

Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. You’ll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. You’ll discover how these so-called functional data structures are different from the traditional data structures you might know, but are worth understanding to do serious algorithmic programming in a functional language such as R. By the end of Functional Data Structures in R, you’ll understand the choices to make in order to most effectively work with data structures when you cannot modify the data itself. These techniques are especially applicable for algorithmic development important in big data, finance, and other data science applications. What You'll LearnCarry out algorithmic programming in R Use abstract data structures Work with both immutable and persistent data Emulate pointers and implement traditional data structures in RBuild new versions of traditional data structures that are known Who This Book Is For Experienced or advanced programmers with at least a comfort level with R. Some experience with data structures recommended. Front Matter ....Pages i-xii Introduction (Thomas Mailund)....Pages 1-2 Abstract Data Structures (Thomas Mailund)....Pages 3-23 Immutable and Persistent Data (Thomas Mailund)....Pages 25-66 Bags, Stacks, and Queues (Thomas Mailund)....Pages 67-133 Heaps (Thomas Mailund)....Pages 135-187 Sets and Search Trees (Thomas Mailund)....Pages 189-245 Back Matter ....Pages 247-256