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Web Application Development with R Using Shiny

By : Chris Beeley, Shitalkumar R. Sukhdeve

3.8 (4)

Buy this Book

Web Application Development with R Using Shiny

3.8 (4)

By: Chris Beeley, Shitalkumar R. Sukhdeve

Buy this Book

Overview of this book

Web Application Development with R Using Shiny helps you become familiar with the complete R Shiny package. The book starts with a quick overview of R and its fundamentals, followed by an exploration of the fundamentals of Shiny and some of the things that it can help you do. You’ll learn about the wide range of widgets and functions within Shiny and how they fit together to make an attractive and easy to use application. Once you have understood the basics, you'll move on to studying more advanced UI features, including how to style apps in detail using the Bootstrap framework or and Shiny's inbuilt layout functions. You'll learn about enhancing Shiny with JavaScript, ranging from adding simple interactivity with JavaScript right through to using JavaScript to enhance the reactivity between your app and the UI. You'll learn more advanced Shiny features of Shiny, such as uploading and downloading data and reports, as well as how to interact with tables and link reactive outputs. Lastly, you'll learn how to deploy Shiny applications over the internet, as well as and how to handle storage and data persistence within Shiny applications, including the use of relational databases. By the end of this book, you'll be ready to create responsive, interactive web applications using the complete R (v 3.4) Shiny (1.1.0) suite.

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Free Chapter

Beginning R and Shiny

Installing R

The R console

Code editors and IDEs

Learning R

Loading data

Data types and structures

Base graphics and ggplot2

Introduction to the tidyverse

Installing Shiny and running the examples

Summary

Shiny First Steps

Types of Shiny application

A minimal example of a full Shiny application

Widget types

The Gapminder application

Advanced layout features

Summary

Integrating Shiny with HTML

Running the applications and code

Shiny and HTML

Custom HTML links in Shiny

A minimal HTML interface

Including a Shiny app on a web page

HTML templates

Exercise

Bootstrap 3 and Shiny

Summary

Mastering Shiny's UI Functions

Shiny's layout functions

Streamlining the UI by hiding elements

Beautiful tables with DataTable

Reactive user interfaces

Progress bars

Progress bar with shinycssloaders

Modals

Alternative Shiny designs

Summary

Easy JavaScript and Custom JavaScript Functions

JavaScript and Shiny

Shinyjs

Extendshinyjs

Responding to events in JavaScript

htmlwidgets

rCharts

d3heatmap

threejs

Summary

Dashboards

Applications in this chapter

Flexdashboards

Sidebar application with extra styling

Using the grid layout

Full dashboard

Info boxes

Summary

Power Shiny

Animation

Reading client information and GET requests in Shiny

Custom interfaces from GET strings

Downloading graphics and reports

Downloadable reports with knitr

Downloading and uploading data

Bookmarking

Interactive plots

Interactive tables

Linking interactive widgets

Shiny gadgets

Adding a password

Summary

Code Patterns in Shiny Applications

Reactivity in RShiny

Controlling specific input with the isolate() function

Running reactive functions over time (execution scheduling)

Event-handling using observeEvent and eventReactive

Functions and modules

Shinytest

Debugging

Handling errors (including validate() and req())

Profiling R code

Debounce and throttle

Summary

Persistent Storage and Sharing Shiny Applications

Sharing over GitHub

Sharing applications using Git

Persistent data storage

Database using Dplyr, DBI, and POOL

SQL Injection

Summary

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Downloadable reports with knitr

This same function can very easily allow your users to produce custom reports in HTML, pdf, or MS Word ready to be downloaded to their machines, using the knitr package (http://yihui.name/knitr/). knitr is a user-contributed package that allows reports to be generated dynamically from a mixture of a static report formats interleaved with the output from of R.

So, for example, titles and text can be fixed, but each time the report is run, a different output will be produced within the document depending on the state of the data when the output is generated. knitr can be used with the R Markdown format. Here is the simple R Markdown document within the Google Analytics application:

# Summary report  
## Text summary  
This report summarises data between `r strftime(input$dateRange[1], 
    format = "%d %B %Y")` and `r strftime(input$dateRange...