5. Advanced Applications I – Dashboards | Web Application Development with R Using Shiny Second Edition

Sign In Start Free Trial

Book Overview & Buying
Table Of Contents
Feedback & Rating

Web Application Development with R Using Shiny Second Edition

By : Chris Beeley

3.5 (10)

Web Application Development with R Using Shiny Second Edition

3.5 (10)

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.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Getting Started with R and Shiny!

1. Getting Started with R and Shiny!

Installing R

The R console

Code editors and IDEs

Learning R

Loading data

Data types and structures

Base graphics and ggplot2

Advanced tasks with dplyr and ggvis

Installing Shiny and running the examples

Summary

2. Building Your First Application

2. Building Your First Application

Types of Shiny application

A minimal example of a fully Shiny application

Widget types

The Google Analytics application

Advanced layout features

Summary

3. Building Your Own Web Pages with Shiny

3. Building Your Own Web Pages with Shiny

Running the applications and code

Shiny and HTML

Custom HTML links in Shiny

A minimal HTML interface

JavaScript and Shiny

jQuery

Exercise

Bootstrap 3 and Shiny

Summary

4. Taking Control of Reactivity, Inputs, and Outputs

4. Taking Control of Reactivity, Inputs, and Outputs

What's new in our application?

Downloading data from RGoogleAnalytics

Animation

Streamline the UI by hiding elements

Naming tabPanel elements

Beautiful tables with DataTable

Reactive user interfaces

Progress bars

Advanced reactivity and data handling

More advanced topics in Shiny

Advanced graphics options

Downloading graphics and reports

Downloadable reports with knitr

Downloading and uploading data

Debugging

Summary

5. Advanced Applications I – Dashboards

5. Advanced Applications I – Dashboards

Applications in this chapter

Version one – sidebar layout

Adding icons to your UI

Using shinyBS to add pop-ups and tooltips

Adding a pop-up window to an output

Using shinythemes

Version two – grid layout (A)

Version two – grid layout (B)

Version three – navigation bar

Version four – dashboard

Notifications

Info boxes

Google Charts gauge

Resizing the google chart

Summary

6. Advanced Applications II – Using JavaScript Libraries in Shiny Applications

6. Advanced Applications II – Using JavaScript Libraries in Shiny Applications

The htmlwidgets package

The application framework

Dygraphs

Dygraphs with a prediction

rCharts

d3heatmap

threejs

Summary

7. Sharing Your Creations

7. Sharing Your Creations

Sharing with the R community

Using Git and GitHub within Rstudio

Summary

Index

Index

Customer Reviews

3.5 (10)

5 star

30%

4 star

30%

3 star

10%

2 star

20%

1 star

10%

Version three – navigation bar

Larger, more complex applications can be organized using a navigation bar along the top of the screen. The application we will look at is relatively simple to avoid generating too much code, but hopefully by the end of this section, you will be able to easily see how simple it is to organize a lot of UI elements in this way. The finished application is as follows:

Two states of the application are shown; the inputs are shown on the first tab, and the graphs are stored in a menu in the second tab (menu pictured), and the map is shown on the final tab.

The server.R file is again unchanged except that the map drawing function that we saw in Chapter 2, Building Your First Application, has been put back in.

ui.R

Let's again look at the ui.R file:

shinyUI(
  navbarPage("Google Analytics",

The page is set up by using navbarPage() instead of fluidPage() and a title for the application passed in:

    tabPanel("Inputs",
      dateRangeInput(inputId = "dateRange",
        label...

Search

Your notes and bookmarks