Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance, Second Edition [2 ed.] 9781484294864, 9781484294871
Master functions and discover how to write functional programs in R. In this book, updated for R 4, you'll learn to
315 70 3MB
English Pages 166 Year 2023
![Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance, Second Edition [2 ed.]
9781484294864, 9781484294871](https://dokumen.pub/img/200x200/functional-programming-in-r-4-advanced-statistical-programming-for-data-science-analysis-and-finance-second-edition-2nbsped-9781484294864-9781484294871.jpg)
Table of contents :
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General Ebook Solution
Table of Contents
About the Author
About the Technical Reviewer
Acknowledgments
Chapter 1: Introduction
Chapter 2: Functions in R
Writing Functions in R
Named Parameters and Default Parameters
The “Gobble Up Everything Else” Parameter: “...”
Lazy Evaluation
Functions Don’t Have Names
Vectorized Functions
Infix Operators
Replacement Functions
Untitled
Chapter 3: Pure Functional Programming
Writing Pure Functions
Recursion As Loops
The Structure of a Recursive Function
Tail-Recursion
Runtime Considerations
Chapter 4: Scope and Closures
Environments and Functions
Environment Chains, Scope, and Function Calls
Scopes, Lazy Evaluation, and Default Parameters
Nested Functions and Scopes
Closures
Reaching Outside Your Innermost Scope
Lexical and Dynamic Scope
Chapter 5: Higher-Order Functions
Currying
A Parameter Binding Function
Continuation-Passing Style
Thunks and Trampolines
Chapter 6: Filter, Map, and Reduce
The General Sequence Object in R Is a List
Filtering Sequences
Mapping over Sequences
Reducing Sequences
Bringing the Functions Together
The Apply Family of Functions
sapply, vapply, and lapply
The apply Function
The tapply Function
Functional Programming in purrr
Filter-like Functions
Map-like Functions
Reduce-like Functions
Chapter 7: Point-Free Programming
Function Composition
Pipelines
Chapter 8: Conclusions
Index
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