app.R

options(error = NULL)
library(shiny)
library(shinydashboard)
library(dplyr)
library(readr)
library(sf)
#library(cartogram)   # optional if you decide to do cartograms later
library(ggplot2)
library(rnaturalearth)
library(rnaturalearthdata)
library(countrycode)

# =============================
#            UI
# =============================
ui <- dashboardPage(
  
  # Use black skin for the dashboard
  skin = "black",
  
  dashboardHeader(
    title = span(
      style = "font-weight: 600; font-size: 18px;",
      "Country Representation"
    )
  ),
  
  dashboardSidebar(
    sidebarMenu(
      menuItem("Map Type", tabName = "cartogramTab", icon = icon("globe"))
    ),
    div(
      style = "margin: 15px;",
      selectInput(
        inputId = "indexChoice",
        label = "Select Representation Index:",
        choices = c("Overall", "RepresentationGap", "Ethnicity",
                    "Gender", "Religion", "Language"),
        selected = "Overall"
      )
    )
  ),
  
  dashboardBody(
    # Bring in the OCR A Extended font from Google Fonts
    tags$head(
      tags$link(
        href = "https://fonts.googleapis.com/css2?family=OCR+A+Extended&display=swap",
        rel = "stylesheet"
      ),
      tags$style(HTML("
        /* Force OCR A Extended font across the entire UI and all HTML elements */
        html, body, h1, h2, h3, h4, h5, h6, p, div, span, label, input, button, select,
        .box, .content-wrapper, .main-sidebar, .main-header .navbar, .main-header .logo,
        .sidebar-menu, .sidebar-menu li a, .sidebar-menu .fa {
          font-family: 'OCR A Extended', monospace !important;
        }
        
        /* Header gradient background */
        .main-header .navbar {
          background: linear-gradient(to right, #3b6978, #204051) !important;
        }

        /* Logo area (left corner of the header) */
        .main-header .logo {
          background: #1b2a2f !important;
          color: #ffffff !important;
          border-bottom: none;
          font-size: 18px;
          font-weight: 600;
        }

        /* Sidebar background */
        .main-sidebar {
          background-color: #1b2a2f !important;
        }

        /* Active or hovered tab in the sidebar */
        .sidebar-menu > li.active > a,
        .sidebar-menu > li:hover > a {
          background-color: #344e5c !important;
          border-left-color: #78cdd7 !important;
          color: #ffffff !important;
        }
        
        /* Sidebar menu item icons */
        .sidebar-menu .fa {
          color: #78cdd7 !important;
        }
        
        /* Sidebar menu item text */
        .sidebar-menu > li > a {
          color: #b8c7ce !important;
          font-size: 15px;
          font-weight: 500;
        }
        
        /* Customize the boxes */
        .box {
          border-top: none !important;
          box-shadow: 0 4px 8px rgba(0,0,0,0.1);
          border-radius: 6px;
        }
        .box.box-solid > .box-header {
          background-color: #204051;
          color: #fff;
          border-radius: 6px 6px 0 0;
        }

        /* Plot box spacing */
        .box .box-body {
          padding: 0 !important;
        }

        /* Footer text styling (plot captions, etc.) */
        .small, small {
          font-size: 75%;
        }
      "))
    ),
    
    tabItems(
      tabItem(
        tabName = "cartogramTab",
        fluidRow(
          box(
            width = 12,
            title = strong("Global Leadership Project (GLP)"),
            solidHeader = TRUE,
            div(style = "height: 80vh; padding: 10px;",
                plotOutput("cartogramPlot", height = "100%")
            )
          )
        )
      )
    )
  )
)

# =============================
#          SERVER
# =============================
server <- function(input, output, session) {
  
  # ---- Read CSV data and create ISO3 codes ----
  rankings_data <- reactive({
    read_csv("CountryRepresentationRankings.csv") %>%
      mutate(iso_a3 = countrycode(Country, origin = "country.name", destination = "iso3c"))
  })
  
  # ---- Read/prepare world map shapefile ----
  world_sf <- reactive({
    ne_countries(scale = "medium", returnclass = "sf") %>%
      dplyr::select(name, iso_a3, pop_est, geometry) %>%
      st_transform(crs = "ESRI:54009")  # Mollweide projection
  })
  
  # ---- Create cartogram (currently a regular map) ----
  cartogram_sf <- reactive({
    merged_sf <- world_sf() %>%
      left_join(rankings_data(), by = "iso_a3")
    # Filter out NA values in 'Overall' to avoid missing countries
    merged_sf <- merged_sf[!is.na(merged_sf$Overall),]
    return(merged_sf) 
  })
  
  # ---- Plot output ----
  output$cartogramPlot <- renderPlot({
    req(input$indexChoice)
    
    index_col <- input$indexChoice
    plot_data <- cartogram_sf()
    
    ggplot(plot_data) +
      geom_sf(aes_string(fill = index_col), color = "grey20", size = 0.1) +
      scale_fill_viridis_c(option = "D", na.value = "white") +
      coord_sf(expand = FALSE) +
      # Force OCR A Extended font in the plot
      #theme_void(base_size = 14, base_family = "OCR A Extended") +
      theme_void(base_size = 14, base_family = "Courier New") +
      labs(
        fill = paste(index_col, "Index"),
        title = "Country Representation Rankings",
        subtitle = "Map Colored by Selected Representation Index",
        caption = "Source: Global Leadership Project (GLP) & Natural Earth"
      ) +
      theme(
        plot.title      = element_text(face = "bold", hjust = 0.5, size = 20),
        plot.subtitle   = element_text(hjust = 0.5, size = 14),
        plot.caption    = element_text(hjust = 1, size = 10),
        legend.position = "bottom",
        legend.direction = "horizontal",
        legend.key.width = unit(2, "cm")
      )
  })
}

# =============================
#   Launch the Shiny App
# =============================
shinyApp(ui = ui, server = server)