Learning RStudio for R Statistical Computing [electronic resource].

ISBN:

9781782160618

9781680153569

Title:

Learning RStudio for R Statistical Computing [electronic resource].

Author:

Van der Loo, Mark P. J.

Personal Author:

Van der Loo, Mark P. J.

Publication Information:

Birmingham : Packt Pub., 2012.

Physical Description:

1 online resource (248 pages).

Series:

Community experience distilled

General Note:

More about the devtools package.

Contents:

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.

Local Note:

eBooks on EBSCOhost

Subject Term:

R (Computer program language)

Open source software.

Operating systems (Computers)

Added Author:

De Jonge, Edwin.

Format:

Electronic Resources

Electronic Access:

Click here to view

Publication Date:

2012

Publication Information:

Birmingham : Packt Pub., 2012.

Available:*

Shelf Number	Material Type	Copy	Shelf Location	Status
005.4	1:E-BOOK	1	1:ONLINE	Searching... Unknown

Bound With These Titles

On Order

Summary

If you need to create and manage complex statistical analysis projects, this book could be a catalyst for great things. In clear, practical chapters it teaches you how to employ Rstudio s powerful features to perform R statistical computing.

Key Features A complete practical tutorial for RStudio, designed keeping in mind the needs of analysts and R developers alike Step-by-step examples that apply the principles of reproducible research and good programming practices to R projects Learn to effectively generate reports, create graphics, and perform analysis, and even build R-packages with RStudio Book Description 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. What you will learn Learn to install and run RStudio on a desktop or a web server Acquaint yourself with the latest and advanced R console features Perform code editing and navigation Learn to create advanced and interactive graphics Effectively manage your R project and project files Learn to build R extension packages Perform reproducible statistical analyses within your R projects Learn your way through getting Who this book is for

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 achieve this using RStudio.