Mailund, Thomas
Functional Data Structures in R :advanced statistical programming in R - New York Apress 2020 - 1 online resource (XII, 256 pages 57 illustrations, 2 illustrations in color.)
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. You will: 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 Implement data structures in C/C++ with some wrapper code in R Build new versions of traditional data structures that are known.
9781484231449
2019754301
Computer programming
Data structures (Computer science)
Mathematical statistics
Programming languages (Electronic computers)
Programming Techniques
Probability and Statistics in Computer Science
Programming Languages, Compilers, Interpreters.
005.11 / MAI/F
Functional Data Structures in R :advanced statistical programming in R - New York Apress 2020 - 1 online resource (XII, 256 pages 57 illustrations, 2 illustrations in color.)
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. You will: 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 Implement data structures in C/C++ with some wrapper code in R Build new versions of traditional data structures that are known.
9781484231449
2019754301
Computer programming
Data structures (Computer science)
Mathematical statistics
Programming languages (Electronic computers)
Programming Techniques
Probability and Statistics in Computer Science
Programming Languages, Compilers, Interpreters.
005.11 / MAI/F