I have written a Shiny app where I am sampling from a poisson distribution. I have rewritten the function for each time I want to output a plot or summary of the data. I would rather only use the function once and then have all plots and summaries refer to the single time the function was called, otherwise the results will not be identical across the outputs. When I tried to call the function once and store the results as a variable to be used by ggplot I got the error that ggplot cannot use reactive data and I was not able to coerce it into a data frame.
I tried variations of:
mydata <- reactive({
x <- input$x
y <- input$y
z <- input$z
Muts <- as.data.frame(rpois(100,(x*y*z)))
Muts
})
However they did not work, as ggplot could not use the input. I think I am not using the reactive function correctly. Any help to reduce the redundancy in the code and ensure that the plots and summary are all using the same single underlying data are much appreciated. Thank you in advance.
My current code:
server.R
library(shiny)
library(ggplot2)
# Define server logic required to draw a histogram
function(input, output) {
output$distPlot <- renderPlot({
x <- input$x
y <- input$y
z <- input$z
Muts <- as.data.frame(rpois(100,(x*y*z)))
# draw the density plot
ggplot(Muts, aes(Muts)) + geom_density()
})
output$distPlot2 <-renderPlot({
x <- input$x
y <- input$y
z <- input$z
Muts <- as.data.frame(rpois(100,(x*y*z)))
Muts <- as.data.frame(Muts)
ggplot(Muts, aes(Muts)) + geom_histogram()
})
output$summary <- renderPrint({
x <- input$x
y <- input$y
z <- input$z
Muts <- as.data.frame(rpois(100,(x*y*z)))
summary(Muts)
})
}
Your idea was right, but a reactive is essentially a cached function that need to be called to retrieve it's return values, so mydata() is correct and mydata just return the function itself (not the return values).
library(shiny)
library(ggplot2)
# Define UI for application
ui <- fluidPage(
# Application title
titlePanel(""),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
sliderInput("x",
"Number of bins:",
min = 1,
max = 50,
value = 30),
sliderInput("y",
"Number of bins:",
min = 1,
max = 50,
value = 30),
sliderInput("z",
"Number of bins:",
min = 1,
max = 50,
value = 30)
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("distPlot"),
plotOutput("distPlot2"),
verbatimTextOutput("summary")
)
)
)
# Define server logic
server <- function(input, output) {
mydata <- reactive({
x <- input$x
y <- input$y
z <- input$z
Muts <- data.frame(x = rpois(100,(x*y*z)))
Muts
})
output$distPlot <- renderPlot({
Muts <- mydata()
ggplot(Muts, aes(x = x)) + geom_density()
})
output$distPlot2 <-renderPlot({
Muts <- mydata()
ggplot(Muts, aes(x = x)) + geom_histogram()
})
output$summary <- renderPrint({
Muts <- mydata()
summary(Muts)
})
}
# Run the application
shinyApp(ui = ui, server = server)