What is it about?
I have written this book for those wishing to learn the R language. R is not only an environment for data analysis and visualization but also a full-fledged programming language. This book is not one more book about statistic tests with R but instead a book that will teach you the use of the R language in a wide range of different tasks. This requires understanding of different language constructs as well as learning to find one's way in the "R universe". The focus is on the writing of scripts used in all stages of data analysis from data import and pre-processing to the production of illustrations for publication.
Featured Image
Photo by Alejandro Escamilla on Unsplash
Why is it important?
What will you find in this book? • 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. • Coaching for becoming an independent R user. What makes this book different to others? • Tries to break the ice and help readers from all disciplines feel at home with R. • It does not make assumptions about what the reader will use R for. • It attempts to do only one thing well: guide readers into becoming fluent in the R language.
Perspectives
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. The 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.
Dr. Pedro José Aphalo
Helsingin Yliopisto
Read the Original
This page is a summary of: Learn R, July 2020, Taylor & Francis,
DOI: 10.1201/9780429060342.
You can read the full text:
Resources
"Learn R: As a Language" book website
At this website you will find under Resources PDF files with additional free chapters of the book as well as instructions on how to access the R package with the source code and data for all examples in the book. If you are curious about how I used R to create the wordcloud illustration for the book cover based on the words in the book index, step by step instructions and code are available through the site.
R package 'lernrbook'
The package with data and code for examples in the book at CRAN.
Buy the book from the publisher
The publisher's webstore, where discounts are frequently available.
Contributors
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