an r shiny demo for ida mooc facilitation, developing data products
TRANSCRIPT
Developing Data ProductsA DEMO ON SHINY
IDA MOOC
TOH WEI ZHONG
SEPTEMBER 2015
A little bit about meGraduated 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)
Agenda for this eveningAn introduction to shiny
◦ What is it about?
◦ Motivation
Basic concepts
A quick coding demo
An introduction to shiny
Shiny: Web application framework for RWeb 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.
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
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}?
My personal examples
Condensed to a simple and intuitive UI
Use-casesQ&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
Basic concepts
Server.R and UI.RShiny 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
UI.RThe 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
UI.RshinyUI(fluidPage(
titlePanel(“This is the title”),
mainPanel(
tabsetPanel(
tabPanel(“One”),
tabPanel(“Two”)
)
)
))
UI.RshinyUI(fluidPage(
titlePanel(“This is the title”),
mainPanel(
tabsetPanel(
tabPanel(“One”,
sliderInput("id", "This is a slider", min = 1, max = 10, value = 5))),
tabPanel(“Two”)
)
)
))
User inputEach 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”)
Server.RWhat 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
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
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)
Coding demo
Tab panels
Slider bars
File import
Hyperlinks
CheckboxesRadio buttons
Images
Main & Sidebar panels
Text
Table output
Thanks! Questions?HT TP://SHINY.RSTUDIO.COM/GALLERY/
HT TPS://GITHUB.COM/TOHWEIZHONG/IDA -MOOC-SHINY
HT TPS://SG.L INKEDIN.COM/IN/TOHWEIZHONG