Inspired from this, you could do:
ui.R
shinyUI(pageWithSidebar(
headerPanel("Dynamic number of plots"),
sidebarPanel(
selectInput(inputId = "choosevar",
label = "Choose Cut Variable:",
choices = c("Nr. of Gears"="gear", "Nr. of Carburators"="carb"))
),
mainPanel(
# This is the dynamic UI for the plots
uiOutput("plots")
)
))
server.R
library(googleVis)
shinyServer(function(input, output) {
#dynamically create the right number of htmlOutput
output$plots <- renderUI({
plot_output_list <- lapply(unique(mtcars[,input$choosevar]), function(i) {
plotname <- paste0("plot", i)
htmlOutput(plotname)
})
tagList(plot_output_list)
})
# Call renderPlot for each one. Plots are only actually generated when they
# are visible on the web page.
for (i in 1:max(unique(mtcars[,"gear"]),unique(mtcars[,"carb"]))) {
local({
my_i <- i
plotname <- paste0("plot", my_i)
output[[plotname]] <- renderGvis({
data <- mtcars[mtcars[,input$choosevar]==my_i,]
if(dim(data)[1]>0){
gvisColumnChart(
data, xvar='hp', yvar='mpg'
)}
else NULL
})
})
}
})
It basically creates htmlOutput
plots dynamically and binds the googleVis
plots when there is data in the subset.
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