Overview
- A unique book on learning and using functional programming in R
- Author is an expert at using and programming with R
- R is a popular open source programming language for statistical analysis and data science
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (6 chapters)
Keywords
About this book
In Functional Programming in R, you’ll see how we can replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn't use recursion when loops are more efficient and how you can get the best of both worlds.
Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions.
What You'll Learn
- Write functions in R including infix operators and replacement functions
- Create higher order functions
- Pass functions to other functions and start using functions as data you can manipulate
- Use Filer, Map and Reduce functions to express the intent behind code clearly and safely
- Build new functions from existing functions without necessarily writing any new functions, using point-free programming
- Create functions that carry data along with them
Who This Book Is For
Those with atleast some experience with programming in R.
Reviews
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Functional Programming in R
Book Subtitle: Advanced Statistical Programming for Data Science, Analysis and Finance
Authors: Thomas Mailund
DOI: https://doi.org/10.1007/978-1-4842-2746-6
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Thomas Mailund 2017
eBook ISBN: 978-1-4842-2746-6Published: 27 March 2017
Edition Number: 1
Number of Pages: XV, 104
Number of Illustrations: 6 b/w illustrations, 1 illustrations in colour
Topics: Programming Languages, Compilers, Interpreters, Programming Techniques, Software Engineering