Books
by Hadley Wickham and Garrett Grolemund
This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it.
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by Yihui Xie, JJ Allaire, and Garrett Grolemund
R Markdown is an authoring framework for reproducible data science. R Markdown blends text and executable code like a notebook, but is stored as a plain text file, amenable to version control. With the click of a button, you can quickly export high quality reports in Word, Powerpoint, interactive HTML, pdf, and more.
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by Javier Luraschi, Kevin Kuo, Edgar Ruiz
In this book you will learn how to use Apache Spark with R using the sparklyr R package. The book intends to take someone unfamiliar with Spark or R and help them become intermediate users by teaching a set of tools, skills and practices applicable to large-scale data science.
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by Francois Chollet And J.J. Allaire
Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples.
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by Yihui Xie, Amber Thomas, Alison Hill
With blogdown, you can easily create websites and blogs straight from R Markdown documents. blogdown integrates R Markdown with static website generators, so that you can generate web pages dynamically.
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by Yihui Xie
This book explains how to use bookdown to write books and technical documents. The bookdown package is built on top of R Markdown. It inherits the simplicity of Markdown syntax and adds features like multi-page HTML output, numbering, and cross-referencing.
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by Hadley Wickham
An introduction to the grammar of graphics, how to use the grammar to build graphs, and how ggplot2 implements the grammar in R. Some of the code details may be out of date.
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by Hadley Wickham
An explanation of R for advanced users. The book explains R as a programming language, covering topics such as S3 and S4 methods, scoping rules, performance and much more.
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by Hadley Wickham
Turn your R code into packages that others can easily download and use. Bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy.
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by Garrett Grolemund
An introduction to programming in R. The book uses three hands-on projects to teach every aspect of R programming, from loading data to writing fast, vectorized functions.
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by Winston Chang
A cookbook of techniques for creating effective graphics with ggplot2 and base R. This book will teach you how to use R’s software to solve a wide variety of data visualization problems.
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by Yihui Xie
An introduction to the knitr package, which lets you embed R code into pdf and html documents to create reproducible, automated reports.
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by Jonathan K. Regenstein Jr.
A unique introduction to data science for investment management that explores the three major R/finance coding paradigms, emphasizes data visualization, and explains how to build a cohesive suite of functioning Shiny applications.
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