R-shiny: How to add a slider to filter the numeric input?

Question

So I am using mpg dataset to practice my R-shiny skills, but I encountered a problem.

I want to write a app which I could choose different variables to make graph, if it involves at least one discrete variable, then I draw a geom_boxplot, else, I will just draw a geom_point.

Now I want to add a slider to filter numeric inputs, but how?

My ui.R looks like this:

library(shiny)

shinyUI(fluidPage(

  # Application title
  titlePanel("Old Faithful Geyser Data"),

  # Sidebar with a slider input for number of bins
  sidebarLayout(
    sidebarPanel(
      selectInput(inputId = "var1",
                  label = "Choose x variable",
                  choices = 
                    names(mpg)
      ),
      selectInput(inputId = "var2",
                  label = "Choose y variable",
                  choices = 
                    names(mpg))
      ),

    # Show a plot of the generated distribution
  mainPanel(
      plotOutput("distPlot")
    )
  )
))

And My server.R looks like this:

server <- function(input,output){

output$distPlot <- renderPlot({

# browser()

if(typeof(mpg[[input$var1]]) == "character")
{
  ggplot(mpg) +
    xlab(input$var1) +
    ylab(input$var2) +
    ggtitle(paste("Plot", input$var1, "vs", input$var2)) +
    geom_boxplot(mapping =
      aes_string(x = input$var1,
                 y = input$var2))
}

else
{
  ggplot(mpg) +
    xlab(input$var1) +
    ylab(input$var2) +
    ggtitle(paste("Plot", input$var1, "vs", input$var2)) +
    geom_point(mapping =
      aes_string(x = input$var1,
                 y = input$var2))
}
})
}

Now, how could I add a slider to filter numeric input?

I am a new learner, please help me. Thank you very much

Answer 1

I'm sorry that I don't have time to flesh out this demo into a better example but hopefully this will show you the methodology:

library(shiny)
library(ggplot2)
library(magrittr)
ui <- fluidPage(

  # Application title
  titlePanel("Optional Numeric Slider Demo"),


  sidebarLayout(
    sidebarPanel(
      selectInput(inputId = "var1",
                  label = "Choose x variable",
                  choices = 
                    names(mpg)
      ),
                       uiOutput('Var1Slider'),

                      br(),
      selectInput(inputId = "var2",
                  label = "Choose y variable",
                  choices = 
                    names(mpg)[sapply(mpg,class)=="character"])
    ),

    mainPanel(
      plotOutput("distPlot")
    )
  )
)

server <- function(input,output){

  output$distPlot <- renderPlot({


    if(typeof(mpg[[input$var1]]) == "character")
    {
      ggplot(mpg) +
        xlab(input$var1) +
        ylab(input$var2) +
        ggtitle(paste("Plot", input$var1, "vs", input$var2)) +
        geom_boxplot(mapping =
                       aes_string(x = input$var1,
                                  y = input$var2))
    }

    else
    {
      mpg %>%
        dplyr::filter(get(input$var1)>input$Var1Slide[1]) %>%
        dplyr::filter(get(input$var1)<input$Var1Slide[2]) %>%
      ggplot() +
        xlab(input$var1) +
        ylab(input$var2) +
        ggtitle(paste("Plot", input$var1, "vs", input$var2)) +
        geom_point(mapping =
                     aes_string(x = input$var1,
                                y = input$var2))
    }
  })
  output$Var1Slider <- renderUI({

    if(typeof(mpg[[input$var1]]) == "character"){
      return(NULL)
    }else{
    sliderInput('Var1Slide',
                label=paste("selected:",input$var1),
                min=min(mpg[[input$var1]]),
                max=max(mpg[[input$var1]]),
                value=c(min(mpg[[input$var1]]),max(mpg[[input$var1]])),
                step = 1)}
  })
}

# Run the application 
shinyApp(ui = ui, server = server)

The key points are the use of renderUI and uiOutput to move computation to the server side. I've also added a line to the numeric graph code to show how to use the input (even if the edit is nonsensical at the moment). Let me know if anything is unclear.

EDIT :I've changed this example so that the slider values actually filter the data going into the plot.