Learning RStudio for R Statistical Computing

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Book cover

“Learning RStudio for R Statistical Computing” will teach you how to quickly and efficiently create and manage statistical analysis projects, import data, develop R scripts, and generate reports and graphics. R developers will learn about package development, coding principles, and version control with RStudio.

This book will help you to learn and understand RStudio features to effectively perform statistical analysis and reporting, code editing, and R development.

The book starts with a quick introduction where you will learn to load data, perform simple analysis, plot a graph, and generate automatic reports. You will then be able to explore the available features for effective coding, graphical analysis, R project management, report generation, and even project management.

Book review

“Learning RStudio for R Statistical Computing” is not another book about R. It shows how to use proficiency R through RStudio capabilities.

First three chapters may be useful for new RStudio users: they describe how to install R and RStudio, the features of the R Console and of the Editor, the object browser and the plot window. I think I didn’t learned something new by reading this first chapters. By the way, their reading wasn’t useless: I reorganized my information about RStudio in a more structured way, while tables with shortcuts are fantastic!

Chapter 4 is about R Projects. I began using R Project some days before I read this book, so this was not a new argument to me. By the way, I learned new and useful information, particularly from the “Tips and tricks” sections. At the moment, I am not using some version control system, but I appreciate this great opportunity provided by RStudio. The book explains in a very clear way and to non-experienced users how to integrate R and SVN.

Chapter 5 is the core of the book. The title “Generating Report” hides the extended opportunities provided by RStudio and well described here. I was looking for a simple way to get a report from an R script, without encapsulate it in a Markdown or a Sweave document. I already have the solution in my RStudio, but I didn’t know. Reading the book I knew Notebook, the simple way to generate a report from an R script. For more structured reports, R scripts can be encapsulated in Markdown, Rhtml or Sweave documents. The book compare this great opportunities provided by RStudio.

Chapter 6 contains some useful hints about using RStudio. If you already use RStudio, may be you already know most part of topics of this chapter. But also experienced users may find something new: I discovered Roxygen2, an R extension that helps to document functions.

In conclusion, RStudio is not a simple editor for R. It is a true IDE with a lot of useful tools. “Learning RStudio for R Statistical Computing” by Mark P.J. van der Loo and Edwin de Jonge is a useful book, both for new and experienced users, to discover these tools.

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