Adding checkboxInput to RShiny - r

Question

I'm really new to using RShiny and I'm struggling to add a Checkbox. There are a few stages to the task I've been given but I'm currently stuck on this step. My aim currently is to create a webapp which displays a boxplot graph with the x-axis (categorical) and y-axis (numerical) variables being dependent on a selectInput. So far I've gotten this to work but now I need to add a checkbox such that when it is clicked on, the boxplots split up into separate plots by categorical level. I've tried a few variations of code but I'm not really getting anywhere and the best I've come up with I think is the following:
library(shiny)
library(palmerpenguins)
library(dplyr)
library(ggplot2)
data <- penguins[,-2]
colnames(data) <- c("Species",
"Bill Length (mm)",
"Bill Depth (mm)",
"Flipper Length (mm)",
"Body Mass (g)",
"Sex",
"Year")
data.numeric <- data[, c(2:5, 7)]
data.categorical <- data[, c(1,6)]
ui <- fluidPage(
headerPanel("Penguin boxplots"),
selectInput("ycol",
"Numeric Variable",
names(data.numeric),
selected = names(data.numeric)[3]),
selectInput("xcol",
"Categorical Variable",
names(data.categorical),
selected = names(data.categorical)[2]),
checkboxInput("split",
"Split Levels",
value = FALSE),
mainPanel(
plotOutput("plot1")
))
server <- function(input, output){
reactive({ if (input$split){
output$plot1 <- renderPlot({
selectedData <- reactive({
data[, c(input$xcol, input$ycol)]
})
plot(selectedData())
})
} else {
output$plot1 <- renderPlot({
par(mar = c(20, 4.1, 0, 1))
selectedData <- reactive({
data[, c(input$xcol, input$ycol)]
})
plot(selectedData())
})
}
})
}
shinyApp(ui = ui, server = server)
as you'll see, the code here isn't intended to actually split the graphs up, it's just there for me to be able to test the code until I can get the if and else statements working - then i'll facet the plots appropriately. So really, my issue is getting the if and else statement to work.
Any help would be really appreciated! Thanks folks

Answer 1

You can try something like this for server.
I would recommend avoiding nesting output and reactive expressions inside other reactive expressions, and duplicating output$plot1.
Instead, you can simplify, and include an if/else inside your renderPlot to show different visualizations depending on checkbox. I added a bit to demonstrate differences in plotting with different checkbox states.
Certainly, additional reactive expressions could be helpful, depending on what else you may want to include in your app.
Edit: Replaced plot with ggplot geom_boxplot and uses facet_wrap.
server <- function(input, output){
output$plot1 <- renderPlot({
selectedData <- data[, c(input$xcol, input$ycol)]
if (input$split) {
ggplot(data = selectedData, aes(y = .data[[input$ycol]])) +
geom_boxplot() +
facet_wrap(~.data[[input$xcol]])
} else {
ggplot(data = selectedData, aes(x = .data[[input$xcol]], y = .data[[input$ycol]])) +
geom_boxplot()
}
})
}