server.R

library(dplyr)
library(tidyr)
library(ggplot2)
library(scales)
library(grid)
library(maptools)
library(sp)
library(rgeos)
library(plyr)
library(geosphere)
#library(extrafont)
#loadfonts()
library(stringr)
library(rgdal)
library(grid)
library(gridExtra)



shinyServer(function(input, output, session) {
  
  # Which group
  
  #   output$group <- renderUI({
  #     groupNames <- groupTable[["groupName"]]
  #     opts <- selectInput("gc_name", "Which Group are you looking for:",choices = groupNames, selected=groupNames[2])
  #     list(opts)
  #   })
  
  ### --------------------------------------------------------------------- ###
  # -- Which domain within group
  
  output$reporter_country <- renderUI({
    
    #reporter_countries <- unique(trade_data$Reporter.Countries)
    reporter_countries <- avail_cntry$country
    opts <- selectInput("reporterCountry", tags$h4("Pick a reporter country:"),
                        choices = reporter_countries)
    list(opts)
  })
  
  
  ### --------------------------------------------------------------------- ###
  # Which item within domain?
  
  output$item <- renderUI({
    
    
    cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
    #cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == "Germany",]$FAOST_CODE), envir = globalenv())
    
    if (input$dataType == "Import") {

      itemList <- cntry_metadata[[2]]
      
    }
    if (input$dataType == "Export") {
      
      itemList <- cntry_metadata[[3]]
    }
    if (input$dataType == "Both") {
      
      items_exp <- cntry_metadata[[2]]
      items_imp <- cntry_metadata[[3]]
      itemList <- items_exp[items_exp %in% items_imp]
      }
    opts <- selectInput("itemName", tags$h4("Pick an Item:"),
                        choices = itemList, selected = itemList[1])
    list(opts)
  })
  
  
  ### --------------------------------------------------------------------- ###
  ## -- Which element within item
  
  output$element <- renderUI({
    
    values <- c("Value","Quantity")
    opts <- radioButtons("elementName", tags$h4("Pick an Element:"),inline = TRUE,
                        choices = values, selected=values[1])
    list(opts)
  })
  
  ### --------------------------------------------------------------------- ###

  
  ### --------------------------------------------------------------------- ###
  ##-- Set the time for export-year 
  
  output$year_data <- renderUI({
    
    cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
    
    if (input$dataType == "Import") opts <- cntry_metadata[[4]]
    if (input$dataType == "Export") opts <- cntry_metadata[[5]]
    if (input$dataType == "Both") opts <- cntry_metadata[[4]][cntry_metadata[[4]] %in% cntry_metadata[[5]]]

    opts <- sliderInput("yearData", tags$h4("Pick a year"), 
                        min = min(opts), max = max(opts), value = max(opts), step = 1, sep="",
                        animate=animationOptions(interval = 2500, loop = FALSE, playButton = NULL, pauseButton = NULL))
    list(opts)
  })
  
  ### --------------------------------------------------------------------- ###
  ## -- Subset trade-matrix data
  
  fao_data_export <- reactive({
    
    #cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == "Germany",]$FAOST_CODE), envir = globalenv())
    cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
    
    df <- cntry_metadata[[6]]
    dat <- df[df$Item == input$itemName, ]

    if (input$elementName == "Value") dat <- dat[dat$Element == "Export Value",]
    if (input$elementName == "Quantity") dat <- dat[dat$Element == "Export Quantity",]
    dat
  })
  
  ### --------------------------------------------------------------------- ###
  ## -- Subset trade-matrix data
  
  fao_data_import <- reactive({
    
    cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
    
    #load(cntry_metadata[[2]])
    df <- cntry_metadata[[6]]
    dat <- df[df$Item == input$itemName, ]

    if (input$elementName == "Value") dat <- dat[dat$Element == "Import Value",]
    if (input$elementName == "Quantity") dat <- dat[dat$Element == "Import Quantity",]
    dat
  })
  
  
#   output$mytable = renderDataTable({
#     
#     
#     df_export <- fao_data_export()
#     df_export <- df_export[df_export$Year <= input$yearData,]
#     
#     df_import <- fao_data_import()
#     df_import <- df_import[df_import$Year <= input$yearData,]
#     
# #     exp_sum <- df_export %>% 
# #       group_by(Year) %>% 
# #       dplyr::summarise(sum = sum(Value, na.rm = TRUE))
# #     exp_sum$var <- "Total Export"
#     
#     imp_sum <- df_import %>% 
#       group_by(Year) %>% 
#       dplyr::summarise(sum = sum(Value, na.rm = TRUE))
#     imp_sum$var <- "Total Import"
#     
#     #imp_sum[1:5,]
#     #rbind(imp_sum[1:5,],exp_sum[1:5,])
#     #rbind(df_export[1:5,],df_import[1:5,])
#     df_import <- fao_data_import()
#     df_import[1:5,]
#     
#   },options = list(pageLength = 10))
#   
#   
#   ### Limit the partner countries

  
    
  output$limit_partner <- renderUI({
    
    if (input$dataType == "Export" | input$dataType == "Both")    {
      df_export <- fao_data_export()
      partners <- df_export[df_export$Year == input$yearData,]

      partners <- partners %>% 
        group_by(Partner.Countries) %>% 
        dplyr::summarise(sum = sum(Value, na.rm = TRUE)) %>% 
        arrange(-sum)
      part_cntry <- partners$Partner.Countries
    }
    
    if (input$dataType == "Import" | input$dataType == "Both"){
      df_import <- fao_data_import()
      partners <- df_import[df_import$Year == input$yearData,]
      
      partners <- partners %>% 
        group_by(Partner.Countries) %>% 
        dplyr::summarise(sum = sum(Value, na.rm = TRUE)) %>% 
        arrange(-sum)
      part_cntry <- partners$Partner.Countries
    }
    

    opts <- selectInput("partnerCountry", tags$h4("Pick partner countries:"),
                        choices = part_cntry, selected= part_cntry[1:20],multiple=TRUE, width="auto")
    list(opts)
   })
  
  

  ### --------------------------------------------------------------------- ###
  ### --------------------------------------------------------------------- ###
  ## --- Outputs
  ### --------------------------------------------------------------------- ###
  ##-- Export Map
  

  

  #output$map <- reactivePlot(function() {
  plotInputMapExport <- reactive({
    
    
    shape2 <- fao_world
    
    cent <- cbind(shape2@data,as.data.frame(gCentroid(shape2,byid=TRUE)))
    cent <- cent[!duplicated(cent$FAO_CODE),]
    
    # fortifying the routes information to create a dataframe; function from ggplot's github site ... thanks to the comments section in AnthroSpace's post
    fortify.SpatialLinesDataFrame = function(model, data, ...) {
      ldply(model@lines, fortify)
    }
    
    
    if (input$dataType == "Export" | input$dataType == "Both")    {
      df_export <- fao_data_export()
      df_export <- df_export[df_export$Year == input$yearData,]
      df_export <- df_export[df_export$Partner.Countries %in% input$partnerCountry,]

      # Export data
      df_export3 <- merge(df_export,cent,by.x="Partner.Country.Code",by.y="FAO_CODE")
      tradepartners <- df_export3[c("Partner.Countries","Value","Item","x","y")]
      # correct country based on codes
      
      fao_code <- avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE
      origin <- cent[cent$FAO_CODE == fao_code,][c("x","y")]
      routes = gcIntermediate(origin, tradepartners[,c('x', 'y')], 200, breakAtDateLine=FALSE, addStartEnd=TRUE, sp=TRUE)
      routes <- spTransform(routes, CRS("+proj=robin"))
      partners <- SpatialPointsDataFrame(tradepartners[4:5], tradepartners[1:3], proj4string = CRS("+proj=longlat +ellps=WGS84"))
      partners <- spTransform(partners, CRS("+proj=robin"))
      fortifiedpartners_export <- cbind(coordinates(partners), partners@data)
      greatcircles_export = fortify.SpatialLinesDataFrame(routes) 
      # An id for each country
      tradepartners$id=as.character(c(1:nrow(tradepartners))) 
      # Merge fortified routes with usopencountry information
      greatcircles_export = merge(greatcircles_export, tradepartners, all.x=T, by="id") 
      names(greatcircles_export)[names(greatcircles_export)=="x"] <- "long"
      names(greatcircles_export)[names(greatcircles_export)=="y"] <- "lat"
      names(fortifiedpartners_export)[names(fortifiedpartners_export)=="x"] <- "long"
      names(fortifiedpartners_export)[names(fortifiedpartners_export)=="y"] <- "lat"
    }
    
    if (input$dataType == "Import" | input$dataType == "Both"){
      
      df_import <- fao_data_import()
      df_import <- df_import[df_import$Year == input$yearData,]
      df_import <- df_import[df_import$Partner.Countries %in% input$partnerCountry,]

      # Import data
      df_import3 <- merge(df_import,cent,by.x="Partner.Country.Code",by.y="FAO_CODE")
      tradepartners <- df_import3[c("Partner.Countries","Value","Item","x","y")]
      # correct country based on codes
      fao_code <- avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE
      origin <- cent[cent$FAO_CODE == fao_code,][c("x","y")]
      
      routes = gcIntermediate(origin, tradepartners[,c('x', 'y')], 200, breakAtDateLine=FALSE, addStartEnd=TRUE, sp=TRUE)
      routes <- spTransform(routes, CRS("+proj=robin"))
      partners <- SpatialPointsDataFrame(tradepartners[4:5], tradepartners[1:3], proj4string = CRS("+proj=longlat +ellps=WGS84"))
      partners <- spTransform(partners, CRS("+proj=robin"))
      fortifiedpartners_import <- cbind(coordinates(partners), partners@data)
      greatcircles_import = fortify.SpatialLinesDataFrame(routes) 
      # An id for each country
      tradepartners$id=as.character(c(1:nrow(tradepartners))) 
      # Merge fortified routes with usopencountry information
      greatcircles_import = merge(greatcircles_import, tradepartners, all.x=T, by="id") 
      names(greatcircles_import)[names(greatcircles_import)=="x"] <- "long"
      names(greatcircles_import)[names(greatcircles_import)=="y"] <- "lat"
      names(fortifiedpartners_import)[names(fortifiedpartners_import)=="x"] <- "long"
      names(fortifiedpartners_import)[names(fortifiedpartners_import)=="y"] <- "lat"
      
    }

    
    if (input$dataType == "Export") {
      lines_export <- geom_line(data=greatcircles_export,aes(long,lat,group=group, alpha=Value), size=1.5, color="Steel Blue", show_guide = FALSE)
      points_export <- geom_point(data=fortifiedpartners_export, aes(long,lat,size=Value),color="Steel Blue", shape=1)
      names_export <- geom_text(data=fortifiedpartners_export, aes(long,lat,label=Partner.Countries),color="Dim Grey", size=4, alpha=.8)
      title_exp <- "export"
      #colors <- scale_color_manual(values="Steel Blue")
      lines_import <- element_blank()
      points_import <- element_blank()
      names_import <- element_blank()
      title_import <- element_blank()
    }
    if (input$dataType == "Import") {
      lines_export <- element_blank()
      points_export <- element_blank()
      names_export <- element_blank()
      #colors <- scale_color_manual(values="#FF3300")
      lines_import <- geom_line(data=greatcircles_import,aes(long,lat,group=group, alpha=Value), size=1.5, color="#FF3300", show_guide = FALSE)
      points_import <- geom_point(data=fortifiedpartners_import, aes(long,lat,size=Value),color="#FF3300", shape=1)
      names_import <- geom_text(data=fortifiedpartners_import, aes(long,lat,label=Partner.Countries),color="Dim Grey", size=4, alpha=.8)
      title_exp <- "import"
    }
    if (input$dataType == "Both") {

      lines_export <- geom_line(data=greatcircles_export,aes(long,lat,group=group, alpha=Value), size=1.5, color="Steel Blue", show_guide = FALSE)
      points_export <- geom_point(data=fortifiedpartners_export, aes(long,lat,size=Value),color="Steel Blue", shape=1)
      names_export <- geom_text(data=fortifiedpartners_export, aes(long,lat,label=Partner.Countries),color="Dim Grey", size=4, alpha=.8)
      lines_import <- geom_line(data=greatcircles_import,aes(long,lat,group=group, alpha=Value), size=1.5, color="#FF3300", show_guide = FALSE)
      points_import <- geom_point(data=fortifiedpartners_import, aes(long,lat,size=Value),color="#FF3300", shape=1)
      names_import <- geom_text(data=fortifiedpartners_import, aes(long,lat,label=Partner.Countries),color="Dim Grey", size=4, alpha=.8)
      title_exp <- "exports and imports"
      #colors <- scale_color_manual(values=c("Steel Blue","#FF3300"))

    }
    
    if (input$elementName == "Quantity") legend_title <- "Quantity in tonnes"
    if (input$elementName == "Value") legend_title <- "Value in 1000 US$"
    

        
    year <- input$yearData
    
    p <- bgmap
    p <- p + lines_export + points_export + names_export
    p <- p + lines_import + points_import + names_import
    # exports
#     p <- p + geom_line(data=greatcircles_export,aes(long,lat,group=group, alpha=Value), color="#FF3300", size=.5)
#     p <- p + geom_point(data=fortifiedpartners_export, aes(long,lat,size=Value),color="#FF3300", shape=1)
#     p <- p + geom_text(data=fortifiedpartners_export, aes(long,lat,label=Partner.Countries),color="Dim Grey", size=2, alpha=.6)
#     # imports
#     p <- p + geom_line(data=greatcircles_import,aes(long,lat,group=group, alpha=Value), color="Steel Blue", size=.5)
#     p <- p + geom_point(data=fortifiedpartners_import, aes(long,lat,size=Value),color="Steel Blue", shape=1)
#     p <- p + geom_text(data=fortifiedpartners_import, aes(long,lat,label=Partner.Countries),color="Dim Grey", size=2, alpha=.6)
    # 
    p <- p + scale_size(name = legend_title, range = c(1,6))
    p <- p + coord_equal()
    #p <- p + colors
    p <- p + labs(title = paste(input$reporterCountry,"-",title_exp,"of",input$itemName,"in",year),
                  x=NULL, 
                  y=NULL)
    p <- p + guides(color = guide_legend(title = ""))
    p <- p + theme(legend.position = c(0.20,0.20),
                   legend.justification=c(0,0),
                   legend.key.size=unit(5,'mm'),
                   legend.direction = "vertical",
                   legend.background=element_rect(colour=NA, fill=NA),
                   #text = element_text(family = "Open Sans"),
                   legend.text=element_text(size=11),
                   legend.key = element_blank(),
                   legend.title=element_text(size=11, face="bold"),
                   title=element_text(size=14, color="Dim Grey"),
                   panel.grid.minor=element_blank(),
                   panel.grid.major=element_blank(),
                   panel.background = element_blank(),
                   plot.background = element_blank(),
                   axis.text = element_blank(),
                   axis.ticks = element_blank(),
                   plot.margin = unit(c(-3,-1.5, -3, -1.5), "cm")#,
                   #text=element_text(family = "Open Sans")
                   )
    #p <- p + theme(legend.position = "none")
    #p <- p + annotate("text", x = Inf, y = -Inf, label = paste0("Year ",year),hjust=2, vjust=-4.5, col="#5087CE", cex=8,fontface = "bold", alpha = 0.4)
    #p <- p + annotate("text", x = Inf, y = -Inf, label = "*countries with less than 50 tonnes excluded", hjust=1.5, vjust=-1.0, col="Dim Grey", cex=3,fontface = "bold", alpha = 0.6)
    p
    
    

  })
  
  
  output$export_map <- renderPlot(function(){
    plotInputMapExport()
  })
  
#   addPopover(session, 
#              "export_map", 
#              "About the map", 
#              content = paste0("Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis ornare nunc arcu, vitae consequat sapien sollicitudin vel. Donec ",
#                                "gravida eros ac ante posuere interdum. Mauris vehicula elementum dolor, ut eleifend ex accumsan et. Etiam sed",
#                                "condimentum neque, et suscipit orci. Nunc efficitur tempor suscipit. Donec volutpat tincidunt lacinia. Praesent vel sollicitudin.",
#                               "augue. Cras sit amet diam in arcu scelerisque imperdiet et at mi. Donec rutrum lacinia est, et facilisis odio vehicula quis. ",
#                               "Aliquam erat volutpat. Phasellus hendrerit efficitur ligula, eget luctus enim. In eget dignissim ipsum. Cras rhoncus ligula enim, ",
#                               "sed vehicula ligula pretium eu. Ut eget efficitur turpis. "), 
#               trigger = 'click', placement="top")
#   
#   addPopover(session, 
#              "export_timeseries", 
#              "About the time-series", 
#              content = paste0("Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis ornare nunc arcu, vitae consequat sapien sollicitudin vel. Donec ",
#                               "gravida eros ac ante posuere interdum. Mauris vehicula elementum dolor, ut eleifend ex accumsan et. Etiam sed",
#                               "condimentum neque, et suscipit orci. Nunc efficitur tempor suscipit. Donec volutpat tincidunt lacinia. Praesent vel sollicitudin.",
#                               "augue. Cras sit amet diam in arcu scelerisque imperdiet et at mi. Donec rutrum lacinia est, et facilisis odio vehicula quis. ",
#                               "Aliquam erat volutpat. Phasellus hendrerit efficitur ligula, eget luctus enim. In eget dignissim ipsum. Cras rhoncus ligula enim, ",
#                               "sed vehicula ligula pretium eu. Ut eget efficitur turpis. "), 
#              trigger = 'click', placement="top")
#   
#   
#   addPopover(session, 
#              "export_Barchart", 
#              "About the barchart", 
#              content = paste0("Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis ornare nunc arcu, vitae consequat sapien sollicitudin vel. Donec ",
#                               "gravida eros ac ante posuere interdum. Mauris vehicula elementum dolor, ut eleifend ex accumsan et. Etiam sed",
#                               "condimentum neque, et suscipit orci. Nunc efficitur tempor suscipit. Donec volutpat tincidunt lacinia. Praesent vel sollicitudin.",
#                               "augue. Cras sit amet diam in arcu scelerisque imperdiet et at mi. Donec rutrum lacinia est, et facilisis odio vehicula quis. ",
#                               "Aliquam erat volutpat. Phasellus hendrerit efficitur ligula, eget luctus enim. In eget dignissim ipsum. Cras rhoncus ligula enim, ",
#                               "sed vehicula ligula pretium eu. Ut eget efficitur turpis. "), 
#              trigger = 'click', placement="top")
  

  output$dlMap <- downloadHandler(
      filename = 'map.pdf',
      content = function(file) {
        device <- function(..., width, height) grDevices::pdf(..., width = 23.4, height = 16.5)
#       filename = 'map.png',
#       content = function(file) {
#       device <- function(..., width, height) grDevices::png(..., width = 1200, height = 750) 
      ggsave(file, plot = plotInputMapExport(), device = device)
    }
  )
  
  
  
  
  

  plotInputTimeseries <- reactive({
    
    

    if (input$dataType == "Export") {
      
      # Because fao_data_import() subset also the item, and we want them all
      cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
      
      #load(cntry_metadata[[2]])
      df <- cntry_metadata[[6]]
      dat <- df[df$Item == input$itemName, ]
      
      if (input$elementName == "Value") dat <- dat[dat$Element == "Import Value",]
      if (input$elementName == "Quantity") dat <- dat[dat$Element == "Import Quantity",]
      dat
      
      
      df_export <- fao_data_export()
      
      df_export <- df_export[df_export$Partner.Countries %in% input$partnerCountry,]
      
      minYear <- min(df_export$Year)
      maxYear <- max(df_export$Year)
      
      lines_export <- geom_line(data=df_export,aes(x=Year,y=Value,group=Partner.Countries,color="Export"), alpha=.4)
      points_export <- geom_point(data=df_export,aes(x=Year,y=Value,group=Partner.Countries), color="Steel Blue", size=2, show_guide = FALSE, alpha=.4)
      names_export <- geom_text(data=merge(df_export, aggregate(Year ~ Partner.Countries, df_export, max), by=c("Year","Partner.Countries")), aes(x=Year, y = Value, label=Partner.Countries), hjust=-0.1,vjust=-1,size=4, alpha=.4, color="Steel Blue")
      title_exp <- "export"
      colors <- scale_color_manual(values="Steel Blue")
      lines_import <- element_blank()
      points_import <- element_blank()
      names_import <- element_blank()
      title_import <- element_blank()
    }
    if (input$dataType == "Import") {
      df_import <- fao_data_import()
      
      df_import <- df_import[df_import$Partner.Countries %in% input$partnerCountry,]
      
      
      minYear <- min(df_import$Year)
      maxYear <- max(df_import$Year)
      
      lines_export <- element_blank()
      points_export <- element_blank()
      names_export <- element_blank()
      colors <- scale_color_manual(values="#FF3300")
      lines_import <- geom_line(data=df_import,aes(x=Year,y=Value,group=Partner.Countries,color="Import"), alpha=.4)
      points_import <- geom_point(data=df_import,aes(x=Year,y=Value,group=Partner.Countries), color="#FF3300", size=2, show_guide = FALSE, alpha=.4)
      names_import <- geom_text(data=merge(df_import, aggregate(Year ~ Partner.Countries, df_import, max), by=c("Year","Partner.Countries")), aes(x=Year, y = Value, label=Partner.Countries), hjust=-0.1,vjust=-.5,size=4, alpha=.4,color="#FF3300")
      title_exp <- "import"
    }
    if (input$dataType == "Both") {
      df_export <- fao_data_export()
      df_import <- fao_data_import()
      
      df_export <- df_export[df_export$Partner.Countries %in% input$partnerCountry,]
      df_import <- df_import[df_import$Partner.Countries %in% input$partnerCountry,]
      
      minYear <- min(df_export$Year)
      maxYear <- max(df_export$Year)
      
    lines_export <- geom_line(data=df_export,aes(x=Year,y=Value,group=Partner.Countries,color="Export"), alpha=.4)
    points_export <- geom_point(data=df_export,aes(x=Year,y=Value,group=Partner.Countries), color="Steel Blue", size=2, show_guide = FALSE, alpha=.4)
    names_export <- geom_text(data=merge(df_export, aggregate(Year ~ Partner.Countries, df_export, max), by=c("Year","Partner.Countries")), aes(x=Year, y = Value, label=Partner.Countries), hjust=-0.1,vjust=-1,size=4, alpha=.4, color="Steel Blue")
    lines_import <- geom_line(data=df_import,aes(x=Year,y=Value,group=Partner.Countries,color="Import"), alpha=.4)
    points_import <- geom_point(data=df_import,aes(x=Year,y=Value,group=Partner.Countries), color="#FF3300", size=2, show_guide = FALSE, alpha=.4)
    names_import <- geom_text(data=merge(df_import, aggregate(Year ~ Partner.Countries, df_import, max), by=c("Year","Partner.Countries")), aes(x=Year, y = Value, label=Partner.Countries), hjust=-0.1,vjust=-.5,size=4, alpha=.4,color="#FF3300")
      title_exp <- "exports and imports"
      colors <- scale_color_manual(values=c("Steel Blue","#FF3300"))
      
      
    }
    
    if (input$elementName == "Quantity") legend_title <- "Quantity in tonnes"
    if (input$elementName == "Value") legend_title <- "Value in 1000 US$"
    
    
    
    #year <- input$yearData
    
    p <- ggplot()
    p <- p + lines_export + points_export + names_export
    p <- p + lines_import + points_import + names_import
    #p <- p + geom_vline(xintercept=input$yearData, color="Dim Grey", alpha=.4, linetype="dashed")
    p <- p + coord_cartesian(xlim=c(minYear,maxYear+3))
    p <- p + scale_x_continuous(breaks=minYear:maxYear)
    p <- p + colors
#     p <- p + coord_equal()
    p <- p + labs(title = paste(input$reporterCountry,"-",title_exp,"of",input$itemName),
                  x=NULL, 
                  y=legend_title)
    p <- p + theme(legend.position = "top",
                   legend.justification=c(0,0),
                   legend.key.size=unit(5,'mm'),
                   legend.key = element_blank(),
                   legend.direction = "horizontal",
                   legend.background=element_rect(colour=NA, fill=NA),
                   #text = element_text(family = "Open Sans"),
                   legend.text=element_text(size=11),
                   legend.title=element_blank(),
                   title=element_text(size=14, color="Dim Grey"),
                   #panel.grid.minor=element_blank(),
                   #panel.grid.major=element_blank(),
                   panel.background = element_blank(),
                   plot.background = element_blank()
                   #axis.text = element_blank(),
                   #axis.ticks = element_blank()#,
                   #plot.margin = unit(c(-3,-1.5, -3, -1.5), "cm")#,
                   #text=element_text(family = "Open Sans")
    )
    #p <- p + theme(legend.position = "none")
    #p <- p + annotate("text", x = Inf, y = -Inf, label = paste0("Year ",year),hjust=2, vjust=-4.5, col="#5087CE", cex=8,fontface = "bold", alpha = 0.4)
    #p <- p + annotate("text", x = Inf, y = -Inf, label = "*countries with less than 50 tonnes excluded", hjust=1.5, vjust=-1.0, col="Dim Grey", cex=3,fontface = "bold", alpha = 0.6)
    p
    
    
  })
  
  
  output$export_timeseries <- renderPlot(function(){
    plotInputTimeseries()
  })
  
  output$dlTimeseries <- downloadHandler(
    filename = 'timeseries_by_country.pdf',
    content = function(file) {
      device <- function(..., width, height) grDevices::pdf(..., width = 23.4, height = 16.5)
#     filename = 'timeseries_by_country.png',
#     content = function(file) {
#       device <- function(..., width, height) grDevices::png(..., width = 1200, height = 750)
      ggsave(file, plot = plotInputTimeseries(), device = device)
    }
  )
  
  
  ### --------------------------------------------------------------------- ###
  ## -- Subset trade-matrix data
  
  fao_data_export_bar <- reactive({
    
    cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
    
    df <- cntry_metadata[[6]]
    dat <- df[df$Year == input$yearData,]
    
    if (input$elementName == "Value") dat <- dat[dat$Element == "Export Value",]
    if (input$elementName == "Quantity") dat <- dat[dat$Element == "Export Quantity",]
    dat
  })
  
  ### --------------------------------------------------------------------- ###
  ## -- Subset trade-matrix data
  
  fao_data_import_bar <- reactive({
    
    cntry_metadata <- get(paste0("metalist",avail_cntry[avail_cntry$country == input$reporterCountry,]$FAOST_CODE), envir = globalenv())
    
    df <- cntry_metadata[[6]]
    dat <- df[df$Year == input$yearData,]
    
    if (input$elementName == "Value") dat <- dat[dat$Element == "Import Value",]
    if (input$elementName == "Quantity") dat <- dat[dat$Element == "Import Quantity",]
    dat
  })
  
  
  
  ### Barchart
  
  plotInputBarchart <- reactive({
    
    
    
    if (input$dataType == "Import" | input$dataType == "Both") {
      
      df_import <- fao_data_import_bar()
      
      #barData <- dataa[dataa$Element %in% c("Import Quantity","Import Value"),]
      bars_i <- df_import %>% 
        #filter(Element == "Import Value") %>% 
        group_by(Item) %>% 
        dplyr::summarise(sum = sum(Value)) %>% 
        arrange(sum)
      # bars_i <- bars_i[!is.na(bars_i$Item),]
      bars_i$Item <- factor(bars_i$Item, levels = bars_i$Item)
      bars_i$var <- "Import items"
       if (nrow(bars_i >= 30)) bars_i <- bars_i[1:30,]
       if (nrow(bars_i < 30)) bars_i <- bars_i
      bars <- bars_i

      
      title_exp <- "import items"
      fill_order <- scale_fill_manual(values=c("#FF3300"))
    }
    if (input$dataType == "Export" | input$dataType == "Both") {
      
      df_export <- fao_data_export_bar()
    
      bars_e <- df_export %>% 
        group_by(Item) %>% 
        dplyr::summarise(sum = sum(Value)) %>% 
        arrange(sum)
      # bars_e <- bars_e[!is.na(bars_e$Item),]
      bars_e$Item <- factor(bars_e$Item, levels = bars_e$Item)
      bars_e$var <- "Export items"
       if (nrow(bars_e >= 30)) bars_e <- bars_e[1:30,]
       if (nrow(bars_e < 30)) bars_e <- bars_e
      bars <- bars_e
      
      title_exp <- "export items"
      fill_order <- scale_fill_manual(values=c("#5087CE"))
    }
    if (input$dataType == "Both") {
      
      bars <- rbind(bars_i,bars_e)
      #bars <- bars[!duplicated(bars)]
      
      fill_order <- scale_fill_manual(values=c("#5087CE","#FF3300"))
      title_exp <- "export and import items"
    }
    
    bars <- bars[!is.na(bars$Item),]
    
    if (input$elementName == "Quantity") legend_title <- "Quantity in tonnes"
    if (input$elementName == "Value") legend_title <- "Value in 1000 US$"
    
    p <- ggplot(bars, aes(x=Item,y=sum,fill=var))
    p <- p + geom_bar(stat="identity", alpha=.60, position="dodge")
    p <- p + fill_order
    p <- p + coord_flip()
    p <- p + labs(title = paste(input$reporterCountry,"top 30",title_exp,"in",input$yearData),
                   x=NULL, 
                   y=legend_title)
    p <- p + theme(legend.position = "top",
                   legend.justification=c(0,0),
                   legend.key.size=unit(5,'mm'),
                   legend.key = element_blank(),
                   legend.direction = "horizontal",
                   legend.background=element_rect(colour=NA, fill=NA),
                   #text = element_text(family = "Open Sans"),
                   legend.text=element_text(size=11),
                   legend.title=element_blank(),
                   title=element_text(size=14, color="Dim Grey"),
                   #panel.grid.minor=element_blank(),
                   #panel.grid.major=element_blank(),
                   panel.background = element_blank(),
                   plot.background = element_blank()
                   #axis.text = element_blank(),
                   #axis.ticks = element_blank()#,
                   #plot.margin = unit(c(-3,-1.5, -3, -1.5), "cm")#,
                   #text=element_text(family = "Open Sans")
    )
    #p <- p + facet_wrap(~var, scales = "free")
    p
    
    
  })

  output$export_Barchart <- reactivePlot(function(){
    plotInputBarchart()
  })
  
  output$dlBarchart <- downloadHandler(
    filename = 'top_30_items.pdf',
    content = function(file) {
      device <- function(..., width, height) grDevices::pdf(..., width = 23.4, height = 16.5)
#     filename = 'top_30_items.png',
#     content = function(file) {
#       device <- function(..., width, height) grDevices::png(..., width = 1200, height = 750)
    ggsave(file, plot = plotInputBarchart(), device = device)
    }
  )
    
  
  
})