Download the filtered data
Downloading files is achieved using the pair of functions downloadButton()
and downloadHandler()
. These two functions pair together similarly to how output and render functions are paired: downloadButton()
determines where in the UI it will show up, while downloadHandler()
needs to be saved into the output
list and has the actual R code to create the downloaded file.
This exercise is part of the course
Case Studies: Building Web Applications with Shiny in R
Exercise instructions
Add the ability to download the data that is currently viewed in the table as a CSV file. Specifically:
- Add a download button to the UI with ID "download_data" and a label of "Download".
- Add a download handler to the server (line 31).
- Give the downloaded file a name of "gapminder_data.csv" (line 33).
- Write the filtered data into a CSV file (line 50).
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
ui <- fluidPage(
h1("Gapminder"),
sliderInput(inputId = "life", label = "Life expectancy",
min = 0, max = 120,
value = c(30, 50)),
selectInput("continent", "Continent",
choices = c("All", levels(gapminder$continent))),
# Add a download button
___(outputId = ___, label = ___),
plotOutput("plot"),
tableOutput("table")
)
server <- function(input, output) {
output$table <- renderTable({
data <- gapminder
data <- subset(
data,
lifeExp >= input$life[1] & lifeExp <= input$life[2]
)
if (input$continent != "All") {
data <- subset(
data,
continent == input$continent
)
}
data
})
# Create a download handler
output$download_data <- ___(
# The downloaded file is named "gapminder_data.csv"
filename = ___,
content = function(file) {
# The code for filtering the data is copied from the
# renderTable() function
data <- gapminder
data <- subset(
data,
lifeExp >= input$life[1] & lifeExp <= input$life[2]
)
if (input$continent != "All") {
data <- subset(
data,
continent == input$continent
)
}
# Write the filtered data into a CSV file
write.csv(___, file, row.names = FALSE)
}
)
output$plot <- renderPlot({
data <- gapminder
data <- subset(
data,
lifeExp >= input$life[1] & lifeExp <= input$life[2]
)
if (input$continent != "All") {
data <- subset(
data,
continent == input$continent
)
}
ggplot(data, aes(gdpPercap, lifeExp)) +
geom_point() +
scale_x_log10()
})
}
shinyApp(ui, server)