Book Image

Web Application Development with R Using Shiny Second Edition - Second Edition

By : Chris Beeley
Book Image

Web Application Development with R Using Shiny Second Edition - Second Edition

By: Chris Beeley

Overview of this book

R is a highly flexible and powerful tool for analyzing and visualizing data. Most of the applications built using various libraries with R are desktop-based. But what if you want to go on the web? Here comes Shiny to your rescue! Shiny allows you to create interactive web applications using the excellent analytical and graphical capabilities of R. This book will guide you through basic data management and analysis with R through your first Shiny application, and then show you how to integrate Shiny applications with your own web pages. Finally, you will learn how to finely control the inputs and outputs of your application, along with using other packages to build state-of-the-art applications, including dashboards.
Table of Contents (14 chapters)
Web Application Development with R Using Shiny Second Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Code editors and IDEs


The Windows and OSX versions of R both come with built-in code editors, which allow code to be edited, saved, and sent to the R console. It's hard to recommend that you use this because it is rather primitive. Most users would be best served by RStudio (rstudio.com/), which includes project management and version control (including support for Git, which is covered in Chapter 7, Sharing Your Creations), viewing of data and graphics, code completion, package management, and many other features. The following is an illustrative screenshot of an RStudio session:

As can be seen, in the top-left corner, there is the code editing pane (with syntax highlighting). The clockwise move from there will take you to the environment pane (in which the different objects loaded into the session can be seen); the viewing pane containing various options such as Files, Plots, Build, Help, and the console (again, with syntax highlighting). In the middle, there is one of the most useful features of RStudio—the ability to view dataframes. This function also comes with sorting and filtering by column.

However, if you already use an IDE for other types of code, it is quite likely that R can be well integrated into it. Examples of IDEs with good R integration include the following:

  • Emacs with the Emacs Speaks Statistics plugin

  • Vim with the Vim-R plugin

  • Eclipse with the StatET plugin