Learning RStudio for R Statistical Computing.

Table of Contents; Learning RStudio for R Statistical Computing; Learning RStudio for R Statistical Computing; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Support files, eBooks, discount offers and more; Why Subscribe?; Free Access for Packt account holders; Preface; What this book covers; What you need for this book; Who this book is for; Conventions; Reader feedback; Customer support; Downloading the example code; Errata; Piracy; Questions; 1. Getting Started; RStudio at a glance; Installing RStudio; Installing R; Installing R on Windows and Mac OS X.

Installing R on LinuxBuilding R from source; Building R using Windows; Installing RStudio; Installing RStudio Server; Installing R packages; Overview: A first R session; Keyboard shortcuts; Getting help; What if I uninstall RStudio?; Further reading; Summary; 2. Writing R Scripts and the R Console; Moving around RStudio; Keyboard shortcuts to move around RStudio; Features of the R console; Executing commands; Command history; Command completion; Completion of functions and arguments; Object completion; Completion of filenames; Bracket and quote completion; Keyboard shortcuts for the console.

Features of the source editorA few words on code quality; Editing R scripts; Keyboard shortcuts for file navigation; Keyboard shortcuts for code editing; Syntax highlighting; Adjusting the syntax highlighting theme; Indenting code; Commenting code; Find and replace; Folding, sectioning, and navigation; Code folding; Keyboard shortcuts for code folding; Code navigation; Keyboard shortcuts for code navigation; Code sections; Code execution; Keyboard shortcuts for code execution; Summary; 3. Viewing and Plotting Data; Viewing data and the object browser; Plotting; Zoom; Export; Navigation.

Interactive plotting with the manipulate packageThe manipulate function; Using more options of manipulate; Advanced topic: retrieving plot parameters from manipulate; Summary; 4. Managing R Projects; R projects; Creating an R project; Directory structure and file manipulations; Version control; Introduction to version control; Installing GIT or Subversion; Version control for single-person projects; GIT; Subversion; Working with a team; Further reading; Summary; 5. Generating Reports; Prerequisites for report generation; Notebook; Notebook options; Publishing a notebook; R Markdown and Rhtml.

Workflow for R MarkdownAn extended example; An introduction to Markdown syntax; Rhtml; Code chunks; Chunk syntax and options; RMarkdown: .Rmd files; Rhtml: .Rhtml files; LaTeX: .Rnw files; RStudio's chunk support and keyboard shortcuts; LaTeX; Further reading; Summary; 6. Using RStudio Effectively; Additional features for function writing; Function extraction; Function navigation; Introduction to package writing; Prerequisites; Basic structure and workflow; Creating the package directory structure; Documenting functions with Roxygen2; Building your package with devtools.

A practical tutorial covering how to leverage RStudio functionality to effectively perform R Development, analysis, and reporting with RStudio. The book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudio functionality to ease their development efforts. Familiarity with R is assumed. Those who want to get started with R development using RStudio will also find the book useful. Even if you already use R but want to create reproducible statistical analysis projects or extend R with self-written packages, this book shows how to quickly.

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