Agenda

• Shiny!
  • template
  • ui/server

Learning objectives

• Be able to create basic interactive plots with shiny

• Understand basic layouts

The basics!

Do the following:

• Create a new R project
• Select "Shiny Web Application"
• Select the directory
• Click "create project"

[demo]

First thing - Run App!

• I like to open in the browser

• What's going on here? Talk with your neighbor and see if you can deduce the basic functionality.

UI

• The ui defines the look and feel of the app - the user interface

• Use it to define where output "lives"

• It also defines the inputs for the server, where functions are actually evaluated.

• In this case - we have defined a sliderInput, which we're calling "bins". It will take on values from 1 to 50, and will start at 30.

• Access the specific value the user selects within the server, through input$bins.

Server

• The server function takes the input from the UI and puts it in normal R code.

• In this case, we're creating one output object, called distPlot. The result is then called through the ui on line 30

• Try removing lines 39-44, and replacing it with print(input$bins)

• Feels like it should work, but it doesn't. Any ideas why?

Text output

We are no longer rendering a plot. We are rendering text.

We need to change renderPlot to renderText and plotOutput to textOutput.

Try

Does it work now?

Challenge

• Try producing essentially the same thing as the default, but use ggplot instead of base plotting.

• Reminder, the data are called faithful, and you'll be showing the distribution of waiting

Change the input

• Let's say instead of a slider, we want 5 options: 1, 5, 20, 50, or 100

• We can change the input from a slider (representing continuous intervals) to radio buttons, representing discrete choices.

• Just change sliderInput to radioButtons, and put in the appropriate choices. You can also add a selected argument for which it defaults to.

Try it out!

More complicated

• Let's say we wanted to build a plot that showed the distribution of highway miles per gallon that could be faceted by year, trans, or class.

• Let's say you also wanted to keep a slider on there to control the number of bins.

• Use radioButtons for the variables, and sliderInput for the bins.

• You'll need to create a second entry to your ui

• Use the mpg dataset (from ggplot2)

[demo]

Tables

• My recommendation: Use one of the following:

  • DT::datatable
  • reactable::reactable

• Let's build a table to go below our distribution(s) that shows mean, sd, min, and max of the corresponding distribution(s)

• You'll need to create a new output object in the server, and tell the ui where it should be rendered

• Use renderDataTable in the server and dataTableOutput in the ui or renderReactable and reactableOutput

• If you want to use {dplyr}, as I would, then you have to deal with NSE. In this case it's not that big of a deal though. Just use !!sym(input$var), where sym transforms a string to a symbol.

[demo]

Last thing for today

Change the layout

• Let's say instead of having the table below, we wanted it within a tabset

• Just create a tabsetPanel within the mainPanel, then put the output for each tab within tabPanel. [demo]

Alternative

• Instead of using a tabset with tabsetPanel, you might want to have a navbar at the top of the page, which you can create with navbarPage.

• Can be a bit more complicated - each tabset needs to include everything, including the sidebarPanel (if present), could include tabsets, mainPanel, etc.

• Essentially each tab from the navbar becomes an entirely new page.

• Make sure to move your title so it's like navbarPage("App title", or the rest of the pages won't look right

[demo, if we have time]

Conclusions

• Shiny is super customizable - just scratched the surface today

• The new Mastering Shiny book should be your guide for going deeper

• Great for building interactive plots, but you can use it for all sorts of other things too (including text and tables)

• Apps get complicated quickly

  • Consider pulling pieces out as a refactoring method to try to make code more readable/less buggy, or using shiny modules

• Next time we'll talk about {shinydashboard} for, basically, an alternative layout.