My background

What to expect during this workshop

The workshop will run for 1 hour.

• Combines slides, live coding examples, and exercises for you to participate in.

• Ask questions throughout!

What is Shiny?

What can you build with Shiny?

Packages required

Assuming that you already have R installed, you will also need to install the {shiny} R package:

install.packages("shiny")

and load it into R:

library("shiny")

We’ll also need some data so we’ll install the {palmerpenguins} package:

install.packages("palmerpenguins")

Packages required

…which has data about penguins!

library("palmerpenguins")
head(penguins)

  species    island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
1  Adelie Torgersen           39.1          18.7               181        3750
2  Adelie Torgersen           39.5          17.4               186        3800
3  Adelie Torgersen           40.3          18.0               195        3250
4  Adelie Torgersen             NA            NA                NA          NA
5  Adelie Torgersen           36.7          19.3               193        3450
6  Adelie Torgersen           39.3          20.6               190        3650
     sex year
1   male 2007
2 female 2007
3 female 2007
4   <NA> 2007
5 female 2007
6   male 2007

Structure of a Shiny App

Shiny apps come in two parts:

Structure of a Shiny App

• Single file app (called app.R)

• Multiple file app (including reusable modules)

• Shiny app as an R package

Structure of a Shiny App

Single file app:

library(shiny)

# UI ----------------------------------------------------------------------

ui <- fluidPage()

# Server ------------------------------------------------------------------

server <- function(input, output) {
  
}

# Run app -----------------------------------------------------------------

shiny::shinyApp(ui, server)

*Other options instead of fluidPage() exist.

Exercise 1

• Open up your IDE of choice.

• Make sure you have the {shiny} package installed.

• Create an app.R file.

• Add ui and server elements, as well as shiny::shinyApp(ui, server).

• Check it works.

Building the User Interface (UI)

What’s included in the UI?

• Contains elements such as:

  • layout structures (sidebars)
  • inputs (text boxes, sliders, buttons)
  • outputs (plots, tables)

Layouts

There are many layouts within Shiny and its extension packages. We’ve already seen:

ui <- fluidPage()

User inputs

• Text Input (textInput()): Allow users to input text data using a text box.

• Numeric Input (numericInput()): Enable users to input numerical values using a slider or numeric input box.

• Checkbox Input (checkboxInput()): Provide binary options for users to select/deselect.

• Select Input (selectInput()): Offer users a dropdown menu to select from multiple options.

• File Input (fileInput()): Enable users to upload files such as CSV, Excel, or text files.

• Action Button (actionButton()): Trigger specific actions or events when clicked by the user.

Outputs

• Plot Output (plotOutput()): Display interactive plots generated from R code.

• Table Output (tableOutput()): Present data in tabular format, allowing users to explore and interact with the data.

• Text Output (textOutput()): Show text or character strings dynamically generated based on user inputs or reactive expressions.

• UI Output (uiOutput()): Dynamically generate and display UI elements based on user inputs or reactive expressions.

• Download Output (downloadButton() / downloadHandler()): Provide functionality to download data, plots, or files generated within the Shiny application.

Exercise 2

• Inside the fluidPage() function, add a title panel, sidebar, and main panel.

• Add a drop down menu with selectInput() to choose by Island.

• What happens if you use checkboxGroupInput() instead?

• Bonus: add additional user options! See: mastering-shiny.org/basic-ui.html

Reactive programming with Shiny

Reactive programming with Shiny

We use a reactive() element which reacts to a user input:

filter_data <- reactive({
    penguins[penguins$species == input$species, ]
  })

• We access the user input using input$inputId.

• We can use this reactive element in other server functions using filter_data(). Note the brackets.

• See also observe() and observeEvent().

Generating outputs

We can add outputs to the UI using e.g. plotOutput("outputId"). But we need to make outputId…

output$penguinsPlot <- renderPlot({
    plot(filter_data()$bill_length_mm, filter_data()$bill_depth_mm)
  })

Exercise 3

• Add a reactive() in the server to subset the data based on the user input you created.

• Create a bar chart of number of penguins per species. plotOutput() also works for {ggplot2} plots!

• Check your app runs.

• Bonus: the default Shiny app styling is fine. Install and load the {shinythemes} package. Try adding theme = shinytheme("cyborg") to the UI.

• Browse: rstudio.github.io/shinythemes

What do we mean by deployment?

Traditional deployment

Shinylive deployment

Shinylive deployment

See posit-dev.github.io/r-shinylive.

install.packages("shinylive")

shinylive::export("app", "site")

Tips for building Shiny apps

• Build tests using shinytest2.

• Building apps as packages helps with dependency management.

• Learn a little bit of HTML, CSS, and Javascript.

• Modules are a good way to reuse bits of UI and server code across the application.

• Start with pen and paper… (think about user experience!)

Additional resources

• Mastering Shiny: mastering-shiny.org/basic-ui.html

• ShinyUiEditor: rstudio.github.io/shinyuieditor

• Shiny for Python: shiny.posit.co/py

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