r - Filter Data Range based on User Input -

i have shiny app plots 2 variables in scatter plot , filters based on user input. trying user can filter data based on range specify. however, want filter applied if field filled out, , return data if field empty (null). example, if launch code have attached, want user able check specify data ranges checkbox , when put in 4.8 in min x input box, data filtered out no data points less 4.8 considered. sample code have prepared below attempt @ i'm trying commented out near middle.

#check packages use in library { library('shiny') #allows shiny app used library('ggvis') #allows interactive ploting }  alldata <- iris  #establish options drop down menus { specieschoices <- unique(as.character(alldata$species)) } # ui  ui<-fluidpage( titlepanel("explorer"), fluidrow( column(4,        wellpanel(          h4("apply filters"),          selectinput(inputid = "species", label="select species:", choices = sort(specieschoices), selected="setosa", multiple = true, selectize = true)        )), column(8,        ggvisoutput("plot1") ), column(4,        wellpanel(          h4("data variables"),          selectinput(inputid = "x", label="select x-axis variable:", choices=as.character(names(alldata[,1:4])),selected='petal.length', multiple = false),          selectinput(inputid = "y", label="select y-axis variable:", choices=as.character(names(alldata[,1:4])),selected='petal.width', multiple = false)        )),  column(4,        wellpanel(          checkboxinput(inputid = "datarange", label="specify data ranges", value = false),          conditionalpanel(            condition = "input.datarange == true",            wellpanel(              numericinput(inputid = "minxdata", label="specify x axis min", value = -9999999999, step = 0.1),              numericinput(inputid = "maxxdata", label="specify x axis max", value = 9999999999, step = 0.1),              numericinput(inputid = "minydata", label="specify y axis min", value = -9999999999, step = 0.1),              numericinput(inputid = "maxydata", label="specify y axis max", value = 9999999999, step = 0.1)            ))        )) ))  #server server<-function(input,output,session) {  #set reactive variables ranges filtereddata <- reactive({  minx <- input$minxdata maxx <- input$maxxdata miny <- input$minydata maxy <- input$maxydata  # apply filters m <- alldata %>% filter(   `species` %in% input$species    ###############this part need   #this works hardcoded hypothetical user input of x=petal.length , y=petal.width   ,   petal.length >= minx,   petal.length <= maxx,   petal.width >= miny,   petal.width <= maxy    #this not work   # ,   # as.symbol(input$x) >= minx,   # as.symbol(input$x) <= maxx,   # as.symbol(input$y) >= miny,   # as.symbol(input$y) <= maxy   #####################################################  ) m <- droplevels(as.data.frame(m)) m })  vis <- reactive({  #plot data visualization customization xvar <- prop("x", as.symbol(input$x)) yvar <- prop("y", as.symbol(input$y))  p1 = filtereddata() %>%   ggvis(x = xvar, y = yvar) %>%   layer_points() %>%    # specifies size of plot   set_options(width = 800, height = 450, duration = 0) })  #actually plots data vis %>% bind_shiny("plot1") }  #run shiny app display webpage shinyapp(ui=ui, server=server) 

update:

i think i'm on right track this, min x , min y filters out data if changed >= 0, , other filters not if changed.

  paste0("`", input$x, "`") >= minx,   paste0("`", input$x, "`") <= maxx,   paste0("`", input$y, "`") >= miny,   paste0("`", input$y, "`") <= maxy 

i have discovered answer based on unrelated post approached how processed data in different way worked me. downloading png shiny (r)

the change within filtereddata posted below.

#set reactive variables ranges filtereddata <- reactive({  minx <- input$minxdata maxx <- input$maxxdata miny <- input$minydata maxy <- input$maxydata <- which(names(alldata)==input$x) xvariable <- as.numeric(alldata[,a]) b <- which(names(alldata)==input$y) yvariable <- as.numeric(alldata[,b])  # apply filters m <- alldata %>% filter( `species` %in% input$species, xvariable >= minx, xvariable <= maxx, yvariable >= miny, yvariable <= maxy ) m <- droplevels(as.data.frame(m)) m })