Price: $18.99
(as of May 12, 2024 07:06:17 UTC – Details)
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.
Salt : B077KPFDXX
Publisher : Apress; 1st ed. edition (November 17, 2017)
Publication date : November 17, 2017
Language : English
File size : 3061 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Sticky notes : On Kindle Scribe
Print length : 291 pages
(as of May 12, 2024 07:06:17 UTC – Details)
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.
Salt : B077KPFDXX
Publisher : Apress; 1st ed. edition (November 17, 2017)
Publication date : November 17, 2017
Language : English
File size : 3061 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Sticky notes : On Kindle Scribe
Print length : 291 pages