BINF_tut

---

Project maintained by sarbal Hosted on GitHub Pages — Theme by mattgraham

Week 10: So shiny!

Objectives

Let’s make something interactive! Shiny is an R package that makes it easy to build interactive web applications (apps) straight from R. This lesson will get you started building Shiny apps right away. You will learn how to:

• Build a user interface
• Add control widgets
• Display reactive output
• Use R scripts and data
• Use reactive expressions

Setting up

You will be creating a shiny app, so there is no need for a notebook this week.

What’s Shiny, precious, eh?

• Shiny is an R package that makes it easy to build interactive web apps.
• Shiny apps are interactive ways to display/showcase or work with your data. See here: https://shiny.rstudio.com/

Start off by installing the shiny package:

install.packages("shiny")

Then load the package.

library(shiny)

RStudio makes it very easy to build an app. Simply click on the “File” dropdown menu, then “New File” and then “Shiny Web App…”. A pop up box will ask you for an “Application name”, call your app whatever you wish (e.g., my_app). Select the “Single File (app.R)” radio button. And then pick your working directory (click Browse on the final box). When you are ready, click “Create”.

This will generate a folder with your app name, and a file called “app.R”. We will be working with this file. It should have two functions: ui and server. They should be pre-filled with a histogram drawing app. You can test it out by running in the command console (make sure you are in the working directory where your app is):

runApp("my_app")

Reactive == Interactive

• Reactivity is the ability of a program to compute outputs from user inputs
• The program ‘responds’ to user defined changes
• Three components:
  1. Reactive Inputs
• Triggers that cause values to be set in the environment
• actions from buttons, selections, uploads, forms, etc.
  1. Reactive Outputs
• Outputs displayed on the browser
• graphs, plots, tables, etc.
  1. Reactive Expressions
• expressions that take in the reactive input and convert it to a reactive output

Two main functions: ui and server

• User interface function (ui) defines the structure of the page
• Placing a function in ui tells shiny where to display your object
• Add an R object to your user interface, the object will be reactive if the code that builds it calls a widget value
• a widget is a web element that your users can interact with
• See the example below:

  ui <- fluidPage( 
    
  titlePanel("Random numbers: normal distribution"),   # Title panel
    
  # Inputs
  sidebarLayout(
    sidebarPanel(
      textInput("one", "Mean", value=0),
      textInput("two", "Standard deviation", value=1),
      textInput("three", "Number of repeats", value=10000),
      textInput("caption", "X-axis label"),      
      actionButton("add", "Run"),
      checkboxInput(inputId = "obs", label = strong("Show individual observations"), value = FALSE),
      sliderInput("bins", "Number of bins:",  min = 1, max = 100, value = 5) 
    ),
      
    # Result display
    mainPanel(
      textOutput("check"),
      plotOutput("distPlot"),
      tableOutput("table")
    )
  )
  )
  

• The server function (server), where all the action happens
• Where you tell shiny how to build your objects
• it builds a list named output that contains all of the code needed to update the R objects in your app
• Note, each R object needs to have its own entry in the list, and you do so by “defining” the element. Each ouput element needs to be matched to its input element in the ui. . E.g., element “check”: – output$check in server matches textOutput("check") in ui

server <- function(input,output,session) {
  # Reactive input 
  observeEvent( input$add,{
    x <- as.numeric(input$one)  # This input comes from the first number box (Mean)
    y <- as.numeric(input$two)  # This input comes from the second number box (Standard deviation)
    n <- as.numeric(input$three)  # This input comes from the third number box (Number of repeats)
    label <- as.character(input$caption) # This input comes from the text box 
    
    # Reactive expressions
    d <-  rnorm(n, x, y)
    bins <- seq(min(d), max(d), length.out = input$bins + 1)
    m <- mean(d)
    sdd <- sd(d)  
    # Reactive output
    output$check <- renderPrint("Done!")
    output$distPlot <- renderPlot({
      
      # Draw the histogram with the specified number of bins
      hist(d, breaks = bins, freq=F, col = 'darkgray', border = 'white', xlab=label)
      ld <- density(d)
      lines(ld, col=4) 
      abline(v=x, lty=2, lwd=3, col=4)      
      if (input$obs) { rug(d) }
      
    })
    output$table <- renderTable({
      data = cbind( m, sdd)
      return( data ) 
    })  
  })
}

Run!

shinyApp(ui = ui, server = server)

Widgets (input)

• go in the ui function

function	widget
actionButton	Action Button
checkboxGroupInput	A group of check boxes
checkboxInput	A single check box
dateInput	A calendar to aid date selection
dateRangeInput	A pair of calendars for selecting a date range
fileInput	A file upload control wizard
helpText	Help text that can be added to an input form
numericInput	A field to enter numbers
radioButtons	A set of radio buttons
selectInput	A box with choices to select from
sliderInput	A slider bar
submitButton	A submit button
textInput	A field to enter text

Output functions

• go in the ui function

Output function	Creates
dataTableOutput	DataTable
htmlOutput	raw HTML
imageOutput	image
plotOutput	plot
ableOutput	table
textOutput	text
uiOutput	raw HTML
verbatimTextOutput	text

Render functions

• go in the server function

render function	Creates
renderDataTable	DataTable
renderImage	images (saved as a link to a source file)
renderPlot	plots
renderPrint	any printed output
renderTable	data frame, matrix, other table like structures
renderText	character strings
renderUI	a Shiny tag object or HTML

Test yourself!

1. We can modify the different bits of code in the ui and server functions to change the display and functionality of the code. Copy the above functions into this app. Run and play around! Increase the number of repeats, change the number of bins, and test different inputs.
2. Try different functions. Currently we are using the random “normal” generator. Make one for the Poisson distribution, and two others (see which here). Make sure you change the inputs needed accordingly (ie add more input boxes, change text).

[Solutions next week]

Resources and other

https://shiny.posit.co/r/getstarted/shiny-basics/lesson1/index.html

Back to the homepage