Input/Output Validation in R Shiny

It is good practice to validate the data before you visualize it in any form such as a table or plot. Shiny offers a simple and intuitive way to do that. As a result, the user does not see a confusing error in red, but an informative message that tells him the reason for the missing content.

In the following somewhat artificial example, we have a dropdown menu with the column names of a dataset. We use the standard data set

library(shiny)

ui <- fluidPage(
    titlePanel("Validate"),
    sidebarLayout(
        sidebarPanel(
           # Dropdown menu with additional empty choice
            selectInput("col", label = "Column",
                        choices = c("",colnames(mtcars)))
        ),
        mainPanel(
            plotOutput("hist")
        )
    )
)

server <- function(input, output) {
    output$hist <- renderPlot({
        colname <- input$col
        # Plot a histogram of the values in the chosen column
        hist(mtcars[[colname]], main = paste('Histogram of', colname), xlab = colname)
    })
}

shinyApp(ui, server)

Validation

To validate variables, Shiny offers the

validate(
    need(colname != "", "Choose a column on the left.")
)

The new server function with the input validation now looks like this:

server <- function(input, output) {
    output$hist <- renderPlot({
        colname <- input$col
        validate(
            need(colname != "", "Choose a column on the left.")
        )
        hist(mtcars[[colname]], main = paste('Histogram of', colname), xlab = colname)
    })
}

The new message is much more informative and therefore makes the user interaction more intuitive. For more details see the documentation and/or this article on the topic.