Learn R As a Language

Learning a computer language like R can be either frustrating, fun, or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges, in what I call playgrou...

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Hlavný autor: Aphalo, Pedro J.
Médium: E-kniha Kniha
Jazyk:English
Vydavateľské údaje: Boca Raton CRC Press 2020
CRC Press LLC
Vydanie:1
Edícia:Chapman & Hall/CRC The R Series
Predmet:
coding language
CRAN
Data analysis workflow
Data manipulation
Programming & Programming Languages
R (Computer program language)
SCI-TECHnetBASE
Scripting
Statistical Theory & Methods
Statistics & Computing
STATSnetBASE
STMnetBASE
Tidyverse
CRAN
Compound Statement
Data Sets
FALSE FALSE
Data manipulation
IDEs
Execution Time
Scripting
coding language
Residual Standard Error
Tick Labels
Character Vector
FALSE TRUE FALSE TRUE FALSE
Scatter Plots
Min 1Q Median 3Q Max
Data analysis workflow
Data Frame
FALSE FALSE FALSE FALSE FALSE
File Names
Speed Dist
Tidyverse
CSV File
Logical Vector
Apply Functions
Character Strings
Model Formulas
Numeric Vectors
FALSE FALSE FALSE
Col1 Col2 Col3 Col4
Plotting Area
Menu Driven User Interfaces
ISBN:0367182556, 036718253X, 9780367182533, 9780367182557
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Shrnutí:Learning a computer language like R can be either frustrating, fun, or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. Although rarely mentioned separately, fluency in a computer programming language involves both writing and reading. The parallels between natural and computer languages are many, but differences are also important. For students and professionals in the biological sciences, humanities, and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2020 and beyond. Features R as it is currently used Few prescriptive rules—mostly the author’s preferences together with alternatives Explanation of the R grammar emphasizing the “R way of doing things” Tutoring for “programming in the small” using scripts The grammar of graphics and the grammar of data described as grammars Examples of data exchange between R and the foreign world using common file formats Coaching for becoming an independent R user, capable of both writing original code and solving future challenges What makes this book different from others: Tries to break the ice and help readers from all disciplines feel at home with R Does not make assumptions about what the reader will use R for Attempts to do only one thing well: guide readers into becoming fluent in the R language This book teaches how to use the R for data analysis. It focuses on how to use R to flexibly explore and analyse data to efficiently and reliably extract information. Using this book, the reader will become confident and reasonably independent in the use of R when faced with new challenges.
Bibliografia:Includes indexes
Bibliography: p. 327-329
ISBN:0367182556
036718253X
9780367182533
9780367182557
DOI:10.1201/9780429060342