Book Image

Learning RStudio for R Statistical Computing

Book Image

Learning RStudio for R Statistical Computing

Overview of this book

Data is coming at us faster, dirtier, and at an ever increasing rate. The necessity to handle many, complex statistical analysis projects is hitting statisticians and analysts across the globe. This book will show you how to deal with it like never before, thus providing an edge and improving productivity. "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. "Learning RStudio for R Statistical Computing" is stuffed with feature-rich and easy-to-understand examples, through step-by-step instructions helping you to quickly master the most popular IDE for R development.
Table of Contents (13 chapters)

Further reading


If you want to write reproducible reports, it is nearly inevitable to have to learn at least one markup language. All languages discussed here—Markdown, HTML, and LaTeX—are available in open source. For Markdown, the website of John Gruber (www.daringfireball.net) offers a nice overview of the syntax. The Markdown renderer of RStudio is actually based on the sundown library of Vincent Martí, which has some extensions. An overview is given at rstudio.org/docs/r_markdown. The knit r package offers an extensive set of options to control how code chunks are parsed into the final report as well as features such as code externalization that have not been discussed here. Full documentation can be found at Yihui Xie's website, http://yihui.name/knitr/ (click on the Options tab). To learn about LaTeX, the Not so Short Introduction to LaTeX (Tobias Oetiker et al.), included in nearly every LaTeX distribution, is a good place to start. The Guide to Latex by Helmut Kopka and Patrick...