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
Learn Carry out algorithmic programming in R Use abstract data structures Work with both
immutable and persistent data Emulate pointers and implement traditional data structures in R
Build 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.
