This document provides an introduction and demo of Shiny, an R package that allows users to build interactive web applications. It discusses how Shiny apps have two main components - a server script (Server.R) that contains the application logic and a user interface script (UI.R) that defines how the UI appears. The server script takes user inputs defined in the UI and uses them to generate outputs, which are then displayed on the UI. A quick coding demo is also provided to illustrate basic Shiny concepts like input bindings, tab panels, and rendering outputs.

1. Developing Data
Products
A DEMO ON SHINY
IDA MOOC
TOH WEI ZHONG
SEPTEMBER 2015

2. A little bit about me
Graduated from NUS, Computational Biology
◦ Statistics and computing onto biology and healthcare
◦ E.g. –omics
Data Scientist in NCS
◦ Smart Nation projects (defense and public safety)

3. Agenda for this evening
An introduction to shiny
◦ What is it about?
◦ Motivation
Basic concepts
A quick coding demo

4. An introduction to
shiny

5. Shiny: Web application
framework for R
Web application: any software application in which the client runs in a
web browser
Can be constructed from a variety of languages and APIs
◦ HTML, CSS, JavaScript
◦ Ruby, Ruby on Rails, PHP, etc. etc.

6. R and web applications?
What’s the link?
Science / communications
◦ Data visualization
◦ Interactivity on results
◦ E.g. Imagine scientific publications having a simple app to communicate
results – phenomenon like autism/anti-vax shouldn’t even occur
◦ Compared to a static report / paper

7. R and web applications?
What’s the link?
Industrial
◦ POC (to sell analytics, dashboard as endpoint)
◦ Sell
◦ “Tableau cannot do this type of modelling.”
◦ “SAS cannot do this type of visualization.”
◦ “We can.”
◦ “Wow!” factor
◦ Show senior mgmt. {deck + code} or {deck + app}?

8. My personal examples

10. Condensed to a simple and
intuitive UI

14. Use-cases
Q&A engine – “Ask a Doctor”
Call center dashboard (call volumes, repeated queries (market basket
analysis), agent performances)
… anything with analytics as frontend, shiny can serve as backend

15. Basic concepts

16. Server.R and UI.R
Shiny apps fundamentally have 2
components
◦ Server.R
◦ UI.R
Server.R consists all R commands
to be executed in the app
UI.R dictates how the UI appears

17. UI.R
The simpler half of the pair (Server.R and UI.R)
Has total control over how the UI looks like
Some of the things you can add:
◦ Text and images
◦ Sliderbars
◦ Radio buttons
◦ Checkboxes
◦ Hyperlinks

18. UI.R
shinyUI(fluidPage(
titlePanel(“This is the title”),
mainPanel(
tabsetPanel(
tabPanel(“One”),
tabPanel(“Two”)
)
)
))

19. UI.R
shinyUI(fluidPage(
titlePanel(“This is the title”),
mainPanel(
tabsetPanel(
tabPanel(“One”,
sliderInput("id", "This is a slider", min = 1, max =
10, value = 5))),
tabPanel(“Two”)
)
)
))

20. User input
Each time we add a UI component that takes in input, we assign it to an
ID.
The definition of the UI component includes an ID, which we define, eg.
◦ sliderInput("id1", "This is a slider", min = 1, max = 10, value = 5)))
◦ checkboxInput(“id2”, “Check this?”, TRUE)
◦ radioButtons(“id3”, “Which one?", c(“This”= “this”, “That” = “that”)

21. Server.R
What server.R does is to take all the inputs from the user (via the UI
components), and execute the necessary
Essentially, the basic task of server.R is to define the relationship
between the inputs and outputs

22. shinyServer(function(input,output){
output$plot <- renderPlot({
boxplot(mtcars[,input$id3])
})
})
shinyUI(fluidPage(
titlePanel("This is the title"),
mainPanel(
tabsetPanel(
tabPanel("One",
sliderInput("id", "This is a slider", min = 1, max = 10, value = 5),
checkboxInput("id2", "Check this?", TRUE),
radioButtons("id3", "Which variable of mtcars?", c("mpg"= "mpg", "disp" =
"disp")),
plotOutput("plot")),
tabPanel("Two")
)
)
))
Server.R
UI.R

24. What’s happening?
1. User select which radio button
2. User’s option is stored in “id3”
3. Server.R takes the value of “id3”, use it to generate a boxplot (render)
4. Generating and surfacing the boxplot are two different steps. To
surface the boxplot on the UI, UI.R output the boxplot
Server.R Generate Render (renderPlot, renderTable)
UI.R Surface / actualize Output (plotOutput, tableOutput)

25. Coding demo

26. Tab panels
Slider bars
File import
Hyperlinks
Checkboxes
Radio
buttons
Images
Main & Sidebar panels
Text

27. Table output

28. Thanks!
Questions?
HTTP://SHINY.RSTUDIO.COM/GALLERY/
HTTPS://GITHUB.COM/TOHWEIZHONG/IDA-MOOC-SHINY
TOHWEIZHONG@HOTMAIL.COM
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