Plot from different datasets upon different inputs using conditional statement

[Prashanth Kumar]

I have recently started working on shiny, for my school project I am developing a Shiny application that plot the graph using ggplot upon selected inputs.

Now, one of my requirement is that, upon selecting certain inputs in the front-end I have to plot the graph using certain dataset. Say I have 3 different datasets, and 4 inputs then,<br>

   

if(input$A = 1 && input$B = 2 && input$C = 3 && input$D = 4){
      //Plot using Dataset1
    }
    else if(input$A = 1 && input$B = 2 && input$C = 3 && input$D = 4){
      //Plot using Dataset2
    }
    else if(input$A = 2 && input$B = 3 && input$C = 4 && input$D = 4){
      //Plot using Dataset3
    }

I figured out that for this sort of logic to work, I need a submit button in the form, I've checked a couple of examples online, but dint properly understand how to apply it in my case.

Now, when I try to plot the data using if condition using reactive as below, I am getting `Error:could not find function "g"`
What am I doing wrong here? and how will I be able to plot this information upon Submit button?

I'd appreciate it, if you could please take a look at my code below and help me.

Here's a sample dataset you can use to reproduce the example -

**UI.R**

   

 library(shiny)
    library("RMySQL")
    library(ggplot2)
    library(plotly)
    # Database Connection and the fetch
    dataset <- read.csv("dataset.csv", header=TRUE)
    dataset$X <- NULL
    dataset$sex <- sub("^$", "Unknown", dataset$sex)
   
    fluidPage(
      fluidRow(
        tags$head(
          tags$style(HTML("
          .shiny-output-error-validation {
            color: #48ca3b;
            font-size: 14pt;
          }
          body {
            -moz-transform: scale(0.9, 0.9); /* Moz-browsers */
            zoom: 0.9; /* Other non-webkit browsers */
            zoom: 90%; /* Webkit browsers */
          }
        "))
        ),
        titlePanel("Define census"),
       
        sidebarPanel(
         
        dateRangeInput('dateRange',
                       label = 'Date Input',
                       start = as.Date("1967-01-01"), end = Sys.Date()),
       
        selectInput("region", label = "Region",
                    choices = c("All",levels(dataset$region)),
                    selected = "ANI"),
       
        selectInput("species", label = "Species",
                    choices = c("All",levels(dataset$species)),
                    selected = "ANI"),
       
        selectInput("sex", label = "Sex",
                    choices = unique(dataset$sex), multiple = TRUE,
                    selected = unique(dataset$sex)),
       
        radioButtons(
          "standard_cat_options",
          label="Standard Category",
          choices=list(
            "All",
            "Multiple Select"), selected="All"),
        conditionalPanel(
          condition = "input.standard_cat_options != 'All'",
          selectInput(
            'standard_cat',
            label = "Select categories", multiple = TRUE,
            choices=unique(dataset$standard_cat)
          )
        ),
       
        radioButtons(
          "age_cat_options",
          label="Age Category",
          choices=list(
            "All",
            "Multiple Select"), selected="All"),
        conditionalPanel(
          condition = "input.age_cat_options != 'All'",
          selectInput(
            'broad_cat',
            label = "Select age category", multiple = TRUE,
            choices=c("adult", "adjuv", "juv", "pup", "orphan", "W", "YOY", "SA1", "SA2", "SA3", "SA4", "SA5", "SA", "mature", levels(dataset$broad_cat))
          )
        ),
       
        selectInput('x', 'X', names(dataset), names(dataset)[[2]]),
       
        selectInput('y', 'Y', names(dataset), names(dataset)[[8]]),
       
        submitButton("Submit")
        ),
      mainPanel(
        column(12, plotlyOutput("plot1")),
        hr(),
        column(12, plotlyOutput("plot2"))
       )
      )
    )

**Server.R**

   

library(ggplot2)
    library("RMySQL")
    library("mgcv")
    library(plotly)
    function(input, output) {
     
    # Database Connection and the fetch
      dataset <- read.csv("dataset.csv", header=TRUE)
     
      dataset$X <- NULL
      dataset$sex <- sub("^$", "Unknown", dataset$sex)
     
      # dataset1 <- read.csv("dataset1.csv", header = TRUE, fill = TRUE)
      # dataset2 <- read.csv("dataset2.csv", header = TRUE, fill = TRUE)
      # dataset3 <- read.csv("dataset3.csv", header = TRUE, fill = TRUE)
     
    # DataBase disconnected
    # Using the datafram created with name data
    # as in the given data Date is of String type so converted to "Date" type
   
    dataset$date <- as.Date(dataset$date)
   
    #reactive variable initiation for the various inputsinstall.packages('rsconnect')
   
    reactive({
    #if(input$region == "ANI" && input$species == "Ej" && input$sex == "Unknown" && input$standard_cat == "All" && input$broad_cat == "YOY"){
     
    if(input$region == "ANI"){
      l <-  subset(dataset, region %in% input$region)
         
     
      k <- subset(l(), date >= as.Date(input$dateRange[1]) & date <= as.Date(input$dateRange[2]))
     
      m <-
          subset(k(), species %in% input$species)
       
     
      n <-
        validate(
          need(input$sex, 'No data exists, Please select Gender input')
        )
        subset(m(), sex %in% input$sex)
       
     
      o <-
          validate(
            need(input$standard_cat, 'No data exists, please select a Standard Category')
            )
          subset(n(), standard_cat %in% input$standard_cat)
       
     
      g <-
          validate(
            need(input$broad_cat, 'No data exists, please select an Age Category')
          )
          subset(o(), broad_cat %in% input$broad_cat)
       
      }
    })
   
    #output plots
   
      output$plot1 <- renderPlotly({
        p <- ggplot(g(), aes_string(x=input$x, y=input$y)) + geom_point(alpha=0.4)
        ggplotly(p)
      })
      output$plot2 <- renderPlotly({
        q <- ggplot(g(), aes_string(x=input$x, y=input$y)) + geom_smooth()
        ggplotly(q)
      })
    }

Thank you.