How to add and remove geom_smooth() trendline in a ggplot2 scatter plot of a shiny app

ggplot2

#1

Hello I have a simple shiny app that creates a scatter plot of mtcars' variables given as inputs. What I want to achieve is to give user the choice to display and hide the trendline created with geom_smooth(). I tried with if statement as you can see below but with no result. Any suggestions?

#ui.r
library(shiny)
library(ggplot2)
library(plotly)
library(dplyr)

fluidPage(

  # App title ----
  titlePanel(div("CROSS CORRELATION",style = "color:blue")),

  # Sidebar layout with input and output definitions ----
  sidebarLayout(

    # Sidebar panel for inputs ----
    sidebarPanel(


    ),
    # Main panel for displaying outputs ----
    mainPanel(

      tabsetPanel(type = "tabs",

                  tabPanel("Correlation Plot",

                           fluidRow(
                             column(3, uiOutput("lx1")),
                           column(3,uiOutput("lx2"))),
                           hr(),
                           fluidRow(
                             tags$style(type="text/css",
                                        ".shiny-output-error { visibility: hidden; }",
                                        ".shiny-output-error:before { visibility: hidden; }"
                             ),
                           column(3,uiOutput("td"))
                           ),
                           fluidRow(
                           plotlyOutput("sc"))
      )

      )
  )))
#server.r
function(input, output) {




  output$lx1<-renderUI({
    selectInput("lx1", label = h4("Select 1st Expression Profile"), 
                choices = colnames(mtcars[,2:5]), 
                selected = "Lex1")
  })
  output$lx2<-renderUI({
    selectInput("lx2", label = h4("Select 2nd Expression Profile"), 
                choices = colnames(mtcars[,2:5]), 
                selected = "Lex2")
  })


  output$td<-renderUI({
    radioButtons("td", label = h4("Trendline"),
                 choices = list("Add Trendline" = "lm", "Remove Trendline" = ""), 
                 selected = "")
  })





  # 1. create reactive values
  vals <- reactiveValues()
  # 2. create df to store clicks
  vals$click_all <- data.frame(x = numeric(),
                               y = numeric(),
                               label = character())
  # 3. add points upon plot click
  observe({
    # get clicked point
    click_data <- event_data("plotly_click", source = "select")
    # get data for current point
    label_data <- data.frame(x = click_data[["x"]],
                             y = click_data[["y"]],
                             label = click_data[["key"]],
                             stringsAsFactors = FALSE)
    # add current point to df of all clicks
    vals$click_all <- merge(vals$click_all,
                            label_data, 
                            all = TRUE)
  }) 

 output$sc<-renderPlotly({

   mtcars$car <- row.names(mtcars)
   p1 <- ggplot(mtcars, aes_string(x = input$lx1, y = input$lx2,key="car",group='car'))+
     # Change the point options in geom_point
     geom_point(color = "darkblue") +

     # Change the title of the plot (can change axis titles
     # in this option as well and add subtitle)
     labs(title = "Cross Correlation") 
     # Change where the tick marks are

     # Change how the text looks for each element



     if(input$td=="lm"){

       geom_smooth(aes(group = 1))+
         # 4. add labels for clicked points
         geom_text(data = vals$click_all,
                   aes(x = x, y = y, label = label),
                   inherit.aes = FALSE, nudge_x = 0.25)
     }
    else{
     # 4. add labels for clicked points
     geom_text(data = vals$click_all,
               aes(x = x, y = y, label = label),
               inherit.aes = FALSE, nudge_x = 0.25)
   }




   ggplotly(p1,source = "select", tooltip = c("key")) 

 }) 




}

#2

You need something like the following

if (input$td == 'lm'){
  p1 <- p1 + geom_smooth(<your options here>) + geom_text(<your options here)
} else {
  p1 <- p1 + geom_text(<your options here)
}

That is basic ggplot2 syntax. You may want to read @hadley's book (https://github.com/hadley/ggplot2-book)