Books

Books

In addition to the software we’ve written at RStudio, we’ve also authored these guides to our tools.

R for Data Science

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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R Markdown: The Definitive Guide

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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Deep Learning with R

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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blogdown: Creating Websites with R Markdown

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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bookdown: Authoring Books and Technical Documents with R Markdown

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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ggplot2: Elegant Graphics for Data Analysis

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how to use the grammar to build graphs, and how ggplot2 implements the grammar in R. Some of the code details may be out of date.

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Advanced R

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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R Packages: Organize, Test, Document, and Share Your Code

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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Hands-On Programming with R

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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R Graphics Cookbook

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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Dynamic Documents with R & knitr

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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Reproducible Finance with R: Code Flows and Shiny Apps for Portfolio Analysis (Chapman & Hall/CRC The R Series)

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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