Advanced R Solutions

Regular price €56.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
#rstats
A01=Hadley Wickham
A01=Henning Bumann
A01=Malte Grosser
advanced R programming exercises
Anonymous Function
Atomic Vector
Author_Hadley Wickham
Author_Henning Bumann
Author_Malte Grosser
Base R
Category=PBT
Category=UFM
Character Vector
codes
Data Frame
Dataset
Duplicate
Env
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
error handling strategies
Execution Time
Follow
functional programming concepts
functions
ggplot2
Holds
Lexical Scoping
Lm
Logical Vector
metaprogramming techniques
NULL
Numeric Vectors
object oriented design
performance optimization R
Primitive Function
programming
R6 Classes
S4 Method
Slightly
Source Code
statistical computing
String
Sys
Var
Wrapper

Product details

  • ISBN 9781032007496
  • Weight: 420g
  • Dimensions: 156 x 234mm
  • Publication Date: 24 Aug 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
Secure checkout Fast Shipping Easy returns

This book offers solutions to all 284 exercises in Advanced R, Second Edition. All the solutions have been carefully documented and made to be as clear and accessible as possible. Working through the exercises and their solutions will give you a deeper understanding of a variety of programming challenges, many of which are relevant to everyday work. This will expand your set of tools on a technical and conceptual level. You will be able to transfer many of the specific programming schemes directly and will discover far more elegant solutions to everyday problems.

Features:

  • When R creates copies, and how it affects memory usage and code performance
  • Everything you could ever want to know about functions
  • The differences between calling and exiting handlers
  • How to employ functional programming to solve modular tasks
  • The motivation, mechanics, usage, and limitations of R's highly pragmatic S3 OO system
  • The R6 OO system, which is more like OO programming in other languages
  • The rules that R uses to parse and evaluate expressions
  • How to use metaprogramming to generate HTML or LaTeX with elegant R code
  • How to identify and resolve performance bottlenecks

Malte Grosser is a business mathematician from Hamburg, who has been programming in R regularly since the beginning of his career. He is currently finishing his PhD on machine learning for stroke outcome prediction and develops solutions in business as a data scientist.

Henning Bumann is a psychologist and statistician who enjoys making sense of data and is motivated to build data-driven solutions that are beautiful and meaningful. He prefers free programming tools to support effective and transparent collaboration.

Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science.

More from this author