inst/co2emission/server.R

In unimi-dse/2fd51b52: Global CO2 emission analysis

#'
#'Define server logic
#'
#'
server <- function(input, output) {

  # import data from CSV file
  fileData <- readFile()

  #rendering Select Input widget and Country name list for user.
  output$var <- renderUI({
    countryNameList <- fileData$CountryName

    countryCodeList <- fileData$CountryCode
    names(countryCodeList) <- countryNameList
    selectInput(
      "var",
      label = "Select country",
      choices = countryCodeList,
      selected = "WLD"
    )
  })

  output$plot <- plotly::renderPlotly({

    countryCode <- input$var

    if(is.null(countryCode)){

      #assigning default value for country
      countryCode <- "WLD"
    }

    yearFrom <- input$range[1]
    yearTo <- input$range[2]
    dataRow <- fileData[fileData[, "CountryCode"] == countryCode,]
    countryName <- dataRow[,1]


    year <- as.numeric(colnames(fileData)[(5+(yearFrom-1960)):(64-(2019-yearTo))])
    co2emission <- c(as.numeric(dataRow[(5+(yearFrom-1960)):(64-(2019-yearTo))]))

    dataShow <- data.frame(year, co2emission)

    tsdata <- ts(data = dataShow$co2emission, frequency = 1, start = c(dataShow$year[1], 1), end = c(tail(dataShow$year, n=1), 1))

    #Forecast
    plotTitle <- paste("CO2 EMISSION ", toupper(countryName))
    forecastCheck <- input$forecastCheckbox
    numberOfLag <- input$lag

    if(forecastCheck){
      shinyjs::show(id = "lag")
      shinyjs::hide(id = "range")
      numberOfLag <- input$lag
      autoarima1 <- forecast::auto.arima(tsdata)
      forecast1 <- forecast::forecast(autoarima1, h=numberOfLag)
      p <- plotData(tsdata, forecast1, plotTitle, forecastCheck)

    }else{
      shinyjs::hide(id = "lag")
      shinyjs::show(id = "range")
      p <- plotData(tsdata =  tsdata, plotTit = plotTitle, fc = forecastCheck)
    }
  })

}