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Thomas Mailund
Functional Data Structures in R
Advanced Statistical Programming in R
1st ed. 2017. xii, 256 S. 55 SW-Abb., 2 Farbabb. 235 mm
Verlag/Jahr: SPRINGER, BERLIN; APRESS 2017
ISBN: 1-484-23143-0 (1484231430)
Neue ISBN: 978-1-484-23143-2 (9781484231432)
Preis und Lieferzeit: Bitte klicken
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 youŽll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. YouŽll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. YouŽll 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 , youŽll 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 YouŽll 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.
1: Abstract Data Structures 2: Immutable and Persistent Data 3: Bags, Stacks, and Queues 4: Heaps 5: Sets and Search Trees 6: Conclusions Bibliography
Thomas Mailund is an associate professor in bioinformatics at Aarhus University, Denmark. He has a background in math and computer science. For the last decade, his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. He has published Beginning Data Science in R, Functional Programming in R and Metaprogramming in R with Apress as well as other books.