R is one of most popular programming languages used in statistical computing. RStudio is an easy-to-use, free, and open-source integrated development environment (IDE) to learn, apply, and develop an R program. Campbell’s book provides step-by-step procedures for developing, debugging, and building data science applications using RStudio.

The book has 12 chapters. The first is a how-to guide on installing R and RStudio for Mac, Windows, and Linux. Chapters 2 to 5 introduce the R environment, covering data and file handling, plotting, data exploration, and so on.

Chapters 6 and 7 introduce tidyverse, a powerful R package that is specifically designed for data science applications. It is actually a collection of packages, namely magrittr, tibble, dplyr, stringr, and ggplot2, which are presented with examples.

Chapters 8 and 9 focus on report creation in a variety of formats using R Markdown. Some of the supported output report formats are Hypertext Markup Language (HTML), portable document format (PDF), Word, and Microsoft PowerPoint (PPT). In addition to these formats, R Markdown has a feature called “shiny” that can be used to create web apps. Illustrations for these report generations are clearly provided.

Procedures for the creation of custom packages are presented in chapter 10, and Git-based code tools are presented in chapter 11. The last chapter provides an overview of R programming, including objects, data types, and flow control.

This book will be useful for graduate and undergraduate students and practitioners working in data science and statistical computing who have fundamental knowledge of R programming. Had the author more thoroughly covered R programming in the early chapters, it would be a more comprehensive book.

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