Create input$selection to subset data AND radiobuttons to choose plot type in Shiny

server <- function(input, output) {

    output$plot <- renderPlot({
        if(input$select=="Trend")
            plot(forecast(fit, #Confidence Interval %
                          level = c(input$range)),
                 sub= "Confidence Interval 70% ~ 90% or Determined by user", 
                 ylab= "Y Axis Variable",
                 main= "Forecast Linear Structural Model @ Trend-Wise",
                 ylim = c(0,400))
        else
            plot(forecast(fit2,
                          #Confidence Interval %
                          level = c(70,90)),
                 sub= "Confidence Interval 70% ~ 90% or Determined by user",
                 ylab= "Y Axis Variable",
                 main= "Forecast Linear Structural Model @ Level-Wise",
                 ylim = c(0,400))
    })

}

server <- function(input, output) {

    output$plot <- renderPlot({
        if(input$select=="Trend")
            method <- fit
        else 
            method <- fit2
        plot(forecast(method, #Confidence Interval %
                      level = c(input$range)),
             sub= "Confidence Interval 70% ~ 90% or Determined by user", 
             ylab= "Y Axis Variable",
             main= "Forecast Linear Structural Model @ Trend-Wise",
             ylim = c(0,400))

    })

}

library(shiny)
library(plotly)

### 1. Create some sample data
myrows<-sample(letters,12)
exdata<- data.frame(mycat=rep(myrows,2),yr=rep(1:2,each=12),KPI_1=rnorm(24),
                    KPI_2=round(runif(24,1,20)),KPI_3=rbinom(24,6,0.5))


ui <- fluidPage(

  sidebarPanel(
    uiOutput("c1"),uiOutput("c2")),
  mainPanel(
    column(6,
    checkboxGroupInput("comp", "Categories",myrows,myrows,inline=TRUE),
    actionButton("go", "Update"),
    textOutput("txt"),
    tableOutput("head")),
    column(6,
    plotlyOutput("plot3", height = 300, width = 700)))
)

server <- function(input, output) {
  ### 3. Server part
  mydata <- eventReactive(input$go,{
    res<-subset(exdata,mycat%in%input$comp)
    return(res)
  })

  output$txt <- renderText({
    paste("You chose", paste(input$comp, collapse = ", "))
  })
  output$head <- renderTable({
    mydata()
  })

  conrolsdata <- reactive({
    unique(as.character(mydata()$mycat))
  })
  output$c1 <- renderUI({
    selectInput("cat_1", "Variable:",conrolsdata())
  })

  output$c2 <- renderUI({
    selectInput("cat_2", "Variable:",conrolsdata())
  })


  output$plot3 <- renderPlotly({

    if(is.null(input$cat_1)){
      return()
    }

    y1<- mydata()$KPI_1[as.character(mydata()$mycat) %in% input$cat_1]
    y2<- mydata()$KPI_2[as.character(mydata()$mycat) %in% input$cat_2]
    x0<-c(1,2)
     #use the key aesthetic/argument to help uniquely identify selected observations
     plot_ly(x = x0,y = y1, type="scatter",mode='lines+markers',name="Firm1") %>%
       add_trace(y = y2, name = "Firm2", mode = 'lines+markers') %>%
       layout(dragmode = "select")
  })

}

shinyApp(ui, server)

library(ggplot2)
library(Cairo)   # For nicer ggplot2 output when deployed on Linux

mtcars2 <- mtcars[, c("mpg", "cyl", "disp", "hp", "wt", "am", "gear")]

ui <- fluidPage(
  fluidRow(
    column(width = 4,
           plotOutput("plot1", height = 300,
                      # Equivalent to: click = clickOpts(id = "plot_click")
                      click = "plot1_click",
                      brush = brushOpts(
                        id = "plot1_brush"
                      )
           )
    )
  ),
  fluidRow(
    column(width = 6
    ),
    column(width = 6,
           verbatimTextOutput("brush_info")
    )
  )
)

server <- function(input, output) {
  output$plot1 <- renderPlot({
    ggplot(mtcars2, aes(wt, mpg)) + geom_point()
  })

  selected_points <- reactiveVal()

  # update the reactiveVal whenever input$plot1_brush changes, i.e. new points are selected.
  observeEvent(input$plot1_brush,{
    selected_points( brushedPoints(mtcars2, input$plot1_brush))
  })

  # show a modal dialog
  observeEvent(selected_points(), ignoreInit=T,ignoreNULL = T, {
    if(nrow(selected_points())>0){
    showModal(modalDialog(
      title = "Important message",
      paste0("You have selected: ",paste0(rownames(selected_points()),collapse=', ')),
      easyClose = TRUE
    ))
    }
  })

  output$brush_info <- renderPrint({
    selected_points()
  })

  output$click_info <- renderPrint({
    nearPoints(mtcars2, input$plot1_click, addDist = TRUE)
  })
}

shinyApp(ui, server)

A = 1
B ='am'

# This does not work
mtcars2 = subset(mtcars, B %in% A)

# This works
mtcars2 = mtcars[mtcars[,B] %in% A,]

data_vals = data_vals[data_vals[,input$filt1] %in% input$checkboxGroup1,]