Develop, Communicate, and Collaborate With R : Harness the Power of RStudio to Create Web Applications, R Packages, Markdown Reports and Pretty Data VisualizationseBook - 2015
Harness the power of RStudio to create web applications, R packages, markdown reports and pretty data visualizationsAbout This BookDiscover the multi-functional use of RStudio to support your daily work with R codeLearn to create stunning, meaningful, and interactive graphs and learn to embed them into easy communicable reports using multiple R packagesDevelop your own R packages and Shiny web apps to share your knowledge and collaborate with others.Who This Book Is For
This book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudio's functionality to ease their development efforts. R programming experience is assumed as well as being comfortable with R's basic structures and a number of functions.What You Will LearnDiscover the RStudio IDE and details about the user interfaceCommunicate your insights with R Markdown in static and interactive waysLearn how to use different graphic systems to visualize your dataBuild interactive web applications with the Shiny framework to present and share your resultsUnderstand the process of package development and assemble your own R packagesEasily collaborate with other people on your projects by using Git and GitHubManage the R environment for your organization with RStudio and Shiny serverApply your obtained knowledge about RStudio and R development to create a real-world dashboard solutionIn Detail
RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will help you to solve real-world data problems.
This book begins by guiding you through the installation of RStudio and explaining the user interface step by step. From there, the next logical step is to use this knowledge to improve your data analysis workflow. We will do this by building up our toolbox to create interactive reports and graphs or even web applications with Shiny. To collaborate with others, we will explore how to use Git and GitHub with RStudio and how to build your own packages to ensure top quality results. Finally, we put it all together in an interactive dashboard written with R.Style and approach
An easy-to-follow guide full of hands-on examples to master RStudio.
Beginning from explaining the basics, each topic is explained with a lot of details for every feature.