Update app.R

app.R

@@ -10,207 +10,6 @@ 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)
-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
 # =============================