Update app.R

app.R

@@ -1,58 +1,642 @@
-library(shiny)
-library(bslib)
+library(lapop)
+library(haven)
 library(dplyr)
-library(ggplot2)
-
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
-
-ui <- page_sidebar(
-  theme = bs_theme(bootswatch = "minty"),
-  title = "Penguins explorer",
-  sidebar = sidebar(
-    varSelectInput("xvar", "X variable", df_num, selected = "Bill Length (mm)"),
-    varSelectInput("yvar", "Y variable", df_num, selected = "Bill Depth (mm)"),
-    checkboxGroupInput("species", "Filter by species",
-      choices = unique(df$Species), selected = unique(df$Species)
+library(tidyr)
+library(stringr)
+library(shinyWidgets)
+library(Hmisc)
+
+lapop_fonts()
+
+dstrata <- readRDS("gm_shiny_data_en.rds")
+labs <- readRDS("labs_en.rds")
+vars_labels <- read.csv("variable_labels_shiny.csv", encoding = "latin1")
+
+Error<-function(x){
+  tryCatch(x,error=function(e) return(FALSE))
+}
+
+waves_total = c("2004", "2006", "2008", "2010", "2012", "2014", "2016/17", "2018/19", "2021", "2023")
+
+
+#helper function for cleaning ts -- handle missing values at end or middle of series
+omit_na_edges <- function(df) {
+  # Find which rows have NA values
+  na_rows <- apply(df, 1, function(row) any(is.na(row)))
+  
+  # Find the first and last non-NA row
+  first_non_na <- which(!na_rows)[1]
+  last_non_na <- which(!na_rows)[length(which(!na_rows))]
+  
+  # Subset df to only include rows between the first and last non-NA rows
+  df_clean <- df[first_non_na:last_non_na, ]
+  
+  return(df_clean)
+}
+
+#custom weighted averages and CIs, to speed up computational speed vs. survey_mean
+weighted.ttest.ci <- function(x, weights) {
+  nx <- length(x)
+  vx <- Hmisc::wtd.var(x, weights, normwt = TRUE, na.rm = TRUE) ## From Hmisc
+  mx <- weighted.mean(x, weights, na.rm = TRUE)
+  stderr <- sqrt(vx/nx)
+  tstat <- mx/stderr ## not mx - mu
+  cint <- qt(1 - 0.05/2, nx - 1)
+  cint <- tstat + c(-cint, cint)
+  confint = cint * stderr
+  result = data.frame(prop = mx, lb = confint[1], ub = confint[2])
+  return(result)
+} 
+
+# helper function for mover
+process_data <- function(data, outcome_var, recode_range, group_var, var_label, weight_var = "weight1500") {
+  if (is.null(group_var)) {
+    return(NULL)
+  }
+  processed_data <- data %>%
+    drop_na(!!sym(outcome_var)) %>%
+    mutate(outcome_rec = case_when(
+      is.na(!!sym(outcome_var)) ~ NA_real_,
+      !!sym(outcome_var) >= recode_range[1] & !!sym(outcome_var) <= recode_range[2] ~ 100,
+      TRUE ~ 0
+    )) %>%
+    group_by(vallabel = haven::as_factor(zap_missing(!!sym(group_var)))) %>%
+    summarise_at(vars("outcome_rec"), list(~weighted.ttest.ci(., !!sym(weight_var)))) %>%
+    unnest_wider(col = "outcome_rec") %>%
+    mutate(
+      varlabel = var_label,
+      proplabel = paste0(round(prop), "%")
+    ) %>%
+    drop_na(.)
+  
+  return(processed_data)
+}
+
+ui <- fluidPage(
+  
+  titlePanel(""), # Leave it Empty
+  
+  sidebarLayout(
+    
+    # Sidebar panel for inputs ----
+    sidebarPanel(
+      width = 3,  # Reduce width (default is 4)
+      
+      selectInput("variable", "Variable",
+                  labs[order(names(labs))],
+                  selected = "ing4"),
+      
+      pickerInput(inputId = "pais", 
+                  label = "Countries",
+                  choices = sort(levels(as_factor(dstrata$pais)[!is.na(dstrata$pais)])),
+                  selected = c("Argentina", "Bolivia", "Brazil", "Chile",
+                               "Colombia", "Costa Rica", "Dominican Republic",
+                               "Ecuador", "El Salvador", "Guatemala", "Haiti",
+                               "Honduras", "Jamaica", "Mexico", "Nicaragua", 
+                               "Panama", "Paraguay", "Peru", "Uruguay"),
+                  options = list(`actions-box` = TRUE),
+                  multiple = TRUE), 
+      
+      
+      #this fixes a formatting issue with checkboxGroupInput below
+      tags$head(
+        tags$style(
+          HTML(
+            ".checkbox-inline { 
+                    margin-left: 0px;
+                    margin-right: 10px;
+          }
+         .checkbox-inline+.checkbox-inline {
+                    margin-left: 0px;
+                    margin-right: 10px;
+          }
+        "
+          )
+        ) 
+      ),
+      
+      #this makes slider input only integers
+      tags$style(type = "text/css", ".irs-grid-pol.small {height: 0px;}"),
+      
+      
+      
+      pickerInput(inputId = "wave", 
+                  label = "Survey Rounds",
+                  choices = c("2004" = "2004",
+                              "2006" = "2006",
+                              "2008" = "2008",
+                              "2010" = "2010",
+                              "2012" = "2012",
+                              "2014" = "2014",
+                              "2016/17" = "2016/17",
+                              "2018/19" = "2018/19",
+                              "2021" = "2021",
+                              "2023" = "2023"),
+                  selected = c("2006", "2008", "2010", "2012", "2014",
+                               "2016/17", "2018/19", "2021", "2023"),
+                  options = list(`actions-box` = TRUE),
+                  # options = list
+                  multiple = TRUE), 
+      
+      # show recode slider only for time series, cc, and breakdown (not hist)
+      conditionalPanel(
+        'input.tabs == "Time Series" | input.tabs == "Cross Country" | input.tabs == "Breakdown"',
+        uiOutput("sliderUI"),
+      ),
+      
+      
+      conditionalPanel(
+        'input.tabs == "Breakdown"',
+        selectInput("variable_sec", "Secondary Variable",
+                    c("None" = "None",
+                      labs[order(names(labs))])),
+        checkboxGroupInput("demog", "Demographic Variables",
+                           c("Gender" = "gendermc",
+                             "Age" = "edad",
+                             "Wealth" = "wealth",
+                             "Education" = "edre",
+                             "Urban/Rural" = "ur"),
+                           selected = c("gendermc", "edad", "edre"),
+                           inline = TRUE)
+      ),
+      
+      actionButton("go", "Generate")
+      
     ),
-    hr(), # Add a horizontal rule
-    checkboxInput("by_species", "Show species", TRUE),
-    checkboxInput("show_margins", "Show marginal plots", TRUE),
-    checkboxInput("smooth", "Add smoother"),
-  ),
-  plotOutput("scatter")
+    
+    # Main panel for displaying outputs ----
+    mainPanel(
+      #width = 8,  # Adjust accordingly (default is 8)
+      # Output: Formatted text for caption ----
+      h3(textOutput("caption")),
+      h5(textOutput("wording")),
+      h5(textOutput("response")),
+      
+      tabsetPanel(id = "tabs",
+                  tabPanel("Histogram", plotOutput("hist")),
+                  
+                  tabPanel("Time Series", plotOutput("ts")),
+                  
+                  tabPanel("Cross Country", plotOutput("cc")),
+                  
+                  tabPanel("Breakdown", plotOutput("mover"))
+      ),
+      br(),
+      fluidRow(column(12, "",
+                      downloadButton(outputId = "downloadPlot", label = "Download Figure"),
+                      downloadButton(outputId = "downloadTable", label = "Download Table")))
+    )
+  )
 )
 
+# Define server logic to plot various variables ----
 server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
-  })
-
-  output$scatter <- renderPlot(
-    {
-      p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) +
-        theme_light() +
-        list(
-          theme(legend.position = "bottom"),
-          if (input$by_species) aes(color = Species),
-          geom_point(),
-          if (input$smooth) geom_smooth()
-        )
-
-      if (input$show_margins) {
-        margin_type <- if (input$by_species) "density" else "histogram"
-        p <- p |> ggExtra::ggMarginal(
-          type = margin_type, margins = "both",
-          size = 8, groupColour = input$by_species, groupFill = input$by_species
+  
+  formulaText <- reactive({
+    paste(input$variable)
+  })
+  
+  outcome <- reactive({
+    input$variable
+  })
+  
+  variable_sec <- reactive({
+    input$variable_sec
+  })
+  
+  variable_sec_lab <- reactive({
+    vars_labels$question_short_en[which(vars_labels$column_name == paste(variable_sec()))]
+  })
+  
+  sliderParams <- reactiveValues(valuex = c(1, 1))
+  
+  #set default slider values - 5-7 for 1-7 variable, 2 for 1-2 variable, 3-4 for 1-4 variable, etc.
+  observeEvent(input$variable, {
+    if (max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE) == 7) {
+      sliderParams$valuex <- c(5, 7)
+    } else if (max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE) == 2) {
+      sliderParams$valuex <- c(2, 2)
+    } else if (max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE) == 3) {
+      sliderParams$valuex <- c(3, 3)
+    } else if (max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE) == 4) {
+      sliderParams$valuex <- c(3, 4)
+    } else if (max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE) == 5) {
+      sliderParams$valuex <- c(4, 5)
+    } else if (max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE) == 10) {
+      sliderParams$valuex <- c(7, 10)
+    }
+  })
+  
+  output$sliderUI <- renderUI({
+    sliderInput(inputId = "recode",
+                label = "Response values included in percentage",
+                min = min(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE), 
+                max = max(as.numeric(dstrata[[formulaText()]]), na.rm=TRUE), 
+                value = sliderParams$valuex,
+                step = 1)
+  })
+  
+  
+  
+  dff <- eventReactive(input$go, ignoreNULL = FALSE, {
+    dstrata %>%
+      filter(as_factor(wave) %in% input$wave) %>%
+      filter(pais_nam %in% input$pais)
+  })  
+  
+  cap <- renderText({
+    vars_labels$question_short_en[which(vars_labels$column_name == formulaText())]
+  })
+  
+  output$caption <- eventReactive(input$go, ignoreNULL = FALSE, {
+    cap() 
+  })
+  
+  word <- renderText({
+    vars_labels$question_en[which(vars_labels$column_name == formulaText())]
+  })
+  
+  output$wording <- eventReactive(input$go, ignoreNULL = FALSE, {
+    word() 
+  })
+  
+  resp <- renderText({
+    vars_labels$responses_en_rec[which(vars_labels$column_name == formulaText())]
+  })
+  
+  output$response <- eventReactive(input$go, ignoreNULL = FALSE, {
+    resp() 
+  })
+  
+  slider_values <- renderText({
+    if(input$recode[1] == input$recode[2]) {
+      paste0("(value: ", unique(input$recode), ")")
+    } else {
+      paste0("(range: ", paste(input$recode, collapse = " to "), ")")
+    }
+  })
+  
+  output$selected_values <- eventReactive(input$go, ignoreNULL = FALSE, {
+    slider_values()
+  })
+  
+  # SOURCE INFO WITH PAIS and WAVE
+  source_info_both <- reactive({
+    # Get country abbreviations that match selected country names
+    pais_abbr <- dstrata %>%
+      filter(pais_nam %in% input$pais) %>%
+      distinct(pais_nam, pais_lab) %>%
+      arrange(match(pais_nam, input$pais)) %>%  # preserve input order
+      pull(pais_lab)
+    
+    pais_display <- paste(pais_abbr, collapse = ", ")
+    wave_display <- paste(input$wave, collapse = ", ")
+    
+    paste0(", AmericasBarometer Data Playground\nCountries included: ", pais_display, "\nSurvey rounds included: ", wave_display)
+    
+  })
+  
+  source_info_pais <- reactive({
+    # Get country abbreviations that match selected country names
+    pais_abbr <- dstrata %>%
+      filter(pais_nam %in% input$pais) %>%
+      distinct(pais_nam, pais_lab) %>%
+      arrange(match(pais_nam, input$pais)) %>%  # preserve input order
+      pull(pais_lab)
+    
+    pais_display <- paste(pais_abbr, collapse = ", ")
+    wave_display <- paste(input$wave, collapse = ", ")
+    
+    paste0(", AmericasBarometer Data Playground\nCountries included: ", pais_display)
+  })
+  
+  source_info_wave <- reactive({
+    # Get country abbreviations that match selected country names
+    pais_abbr <- dstrata %>%
+      filter(pais_nam %in% input$pais) %>%
+      distinct(pais_nam, pais_lab) %>%
+      arrange(match(pais_nam, input$pais)) %>%  # preserve input order
+      pull(pais_lab)
+    
+    pais_display <- paste(pais_abbr, collapse = ", ")
+    wave_display <- paste(input$wave, collapse = ", ")
+    
+    paste0(", AmericasBarometer Data Playground\nSurvey rounds included: ", wave_display)
+  })
+  
+  #hist 
+  # must break into data event, graph event, and renderPlot to get download buttons to work
+  histd <- eventReactive(input$go, ignoreNULL = FALSE, {
+    hist_df = Error(
+      dff() %>%
+        group_by(across(outcome())) %>%
+        summarise(n = n())  %>%
+        drop_na() %>%
+        rename(cat = 1) %>%
+        mutate(prop = prop.table(n) * 100,
+               proplabel = paste(round(prop), "%", sep = ""),
+               cat = str_wrap(as.character(haven::as_factor(cat)), width = 25)))
+    
+    validate(
+      need(hist_df, "Error: no data available. Please verify that this question was asked in this country/year combination")
+    )
+    return(hist_df)
+  })
+  
+  
+  histg <- eventReactive(input$go, ignoreNULL = FALSE, {
+    histg <- lapop_hist(histd(), 
+                        ymax = ifelse(any(histd()$prop > 90), 110, 100), 
+                        source_info = source_info_both())
+    return(histg)
+  })
+  
+  output$hist <- renderPlot({
+    return(histg())
+  })
+  
+  
+  #ts
+  tsd <- eventReactive(input$go, ignoreNULL = FALSE, {
+    dta_ts = Error(
+      dff() %>%
+        drop_na(outcome()) %>%
+        mutate(outcome_rec = case_when(
+          is.na(!!sym(outcome())) ~ NA_real_,
+          !!sym(outcome()) >= input$recode[1] &
+            !!sym(outcome()) <= input$recode[2] ~ 100,
+          TRUE ~ 0)) %>%
+        group_by(as.character(as_factor(wave))) %>%
+        summarise_at(vars("outcome_rec"),
+                     list(~weighted.ttest.ci(., weight1500))) %>%
+        unnest_wider(col = "outcome_rec") %>%
+        mutate(proplabel = paste0(round(prop), "%")) %>%
+        rename(.,  wave = 1) %>%
+        filter(prop != 0) 
+    )
+    validate(
+      need(dta_ts, "Error: no data available. Please verify that this question was asked in this country/year combination")
+    )
+    dta_ts = merge(dta_ts, data.frame(wave = as.character(waves_total), empty = 1), by = "wave", all.y = TRUE)
+    return(omit_na_edges(dta_ts))
+  })
+  
+  tsg <- eventReactive(input$go, ignoreNULL = FALSE, {
+    tsg = lapop_ts(tsd(), 
+                   ymax = ifelse(any(tsd()$prop > 88, na.rm = TRUE), 110, 100),
+                   label_vjust = ifelse(any(tsd()$prop > 80, na.rm = TRUE), -1.1, -1.5),
+                   source_info = source_info_pais(),
+                   subtitle = "% in selected category")
+    return(tsg)
+  })
+  
+  
+  output$ts <- renderPlot({
+    return(tsg())
+  })
+  
+  #cc 
+  ccd <- eventReactive(input$go, ignoreNULL = FALSE, {
+    dta_cc = Error(
+      dff() %>%
+        drop_na(outcome()) %>%
+        mutate(outcome_rec = case_when(
+          is.na(!!sym(outcome())) ~ NA_real_,
+          !!sym(outcome()) >= input$recode[1] &
+            !!sym(outcome()) <= input$recode[2] ~ 100,
+          TRUE ~ 0)) %>%
+        group_by(vallabel = pais_lab) %>%
+        summarise_at(vars("outcome_rec"),
+                     list(~weighted.ttest.ci(., weight1500))) %>%
+        unnest_wider(col = "outcome_rec") %>%
+        filter(prop != 0) %>%
+        mutate(proplabel = paste0(round(prop), "%"))
+    )
+    validate(
+      need(dta_cc, "Error: no data available. Please verify that this question was asked in this country/year combination")
+    )
+    return(dta_cc)
+  })
+  
+  ccg <- eventReactive(input$go, ignoreNULL = FALSE, {
+    ccg = lapop_cc(ccd(), sort = "hi-lo", 
+                   subtitle = "% in selected category",
+                   ymax = ifelse(any(ccd()$prop > 90, na.rm = TRUE), 110, 100),
+                   source_info = source_info_wave())
+    return(ccg)
+  })
+  
+  output$cc <- renderPlot({
+    return(ccg())
+  })
+  
+  # Use function for each demographic breakdown variable
+  secdf <- eventReactive(input$go, ignoreNULL = FALSE, {
+    if (input$variable_sec == "None") {
+      NULL
+    }  else if (variable_sec() == outcome()) {
+      showNotification("You cannot break the outcome variable by itself.", type = "error")
+      NULL
+    } else {
+      process_data(
+        data = dff(),
+        outcome_var = outcome(),
+        recode_range = input$recode,
+        group_var = input$variable_sec,
+        var_label = str_wrap(variable_sec_lab(), width = 25)
+      )
+    }
+  })
+  
+  genderdf <- eventReactive(input$go, ignoreNULL = FALSE, {
+    if ("gendermc" %in% input$demog) {
+      process_data(
+        data = dff(),
+        outcome_var = outcome(),
+        recode_range = input$recode,
+        group_var = "gendermc",
+        var_label = "Gender"
+      )
+    } else {
+      NULL
+    }
+  })
+  
+  wealthdf <- eventReactive(input$go, ignoreNULL = FALSE, {
+    if ("wealth" %in% input$demog) {
+      process_data(
+        data = dff(),
+        outcome_var = outcome(),
+        recode_range = input$recode,
+        group_var = "wealthf",
+        var_label = "Wealth"
+      )
+    } else {
+      NULL
+    }
+  })
+  
+  eddf <- eventReactive(input$go, ignoreNULL = FALSE, {
+    if ("edre" %in% input$demog) {
+      process_data(
+        data = dff(),
+        outcome_var = outcome(),
+        recode_range = input$recode,
+        group_var = "edrerf",
+        var_label = "Education"
+      )
+    } else {
+      NULL
+    }
+  })
+  
+  edaddf <- eventReactive(input$go, ignoreNULL = FALSE, {
+    if ("edad" %in% input$demog) {
+      process_data(
+        data = dff(),
+        outcome_var = outcome(),
+        recode_range = input$recode,
+        group_var = "edad",
+        var_label = "Age"
+      )
+    } else {
+      NULL
+    }
+  })
+  
+  urdf <- eventReactive(input$go, ignoreNULL = FALSE, {
+    if ("ur" %in% input$demog) {
+      process_data(
+        data = dff(),
+        outcome_var = outcome(),
+        recode_range = input$recode,
+        group_var = "ur",
+        var_label = "Place of\nResidence"
+      )
+    } else {
+      NULL
+    }
+  })
+  
+  # Combine =demographic data frames into one df
+  moverd <- eventReactive(input$go, ignoreNULL = FALSE, {
+    dta_mover <- Error(rbind(secdf(), genderdf(), edaddf(), wealthdf(), eddf(), urdf()))
+    validate(
+      need(dta_mover, "Error: no data available. Please verify that this question was asked in this country/year combination")
+    )
+    dta_mover$vallabel <- as.character(dta_mover$vallabel)
+    return(dta_mover)
+  })
+  
+  moverg <- eventReactive(input$go, ignoreNULL = FALSE, {
+    moverg <- lapop_mover(moverd(), 
+                          subtitle = "% in selected category", 
+                          ymax = ifelse(any(moverd()$prop > 90, na.rm = TRUE), 119,
+                                        ifelse(any(moverd()$prop > 80, na.rm = TRUE), 109, 100)),
+                          source_info = source_info_both())
+    return(moverg)
+  })
+  
+  output$mover <- renderPlot({
+    return(moverg())
+  })
+  
+  # DOWNLOAD SECTION
+  output$downloadPlot <- downloadHandler(
+    filename = function(file) {
+      ifelse(input$tabs == "Histogram", paste0("hist_", outcome(),".svg"),
+             ifelse(input$tabs == "Time Series",  paste0("ts_", outcome(),".svg"),
+                    ifelse(input$tabs == "Cross Country",  paste0("cc_", outcome(),".svg"),  paste0("mover_", outcome(),".svg"))))
+    },
+    
+    content = function(file) {
+      if(input$tabs == "Histogram") {
+        title_text <- isolate(cap())
+        
+        hist_to_save <- lapop_hist(histd(),
+                                   main_title = title_text,
+                                   subtitle = "% in selected category ",
+                                   ymax = ifelse(any(histd()$prop > 90), 110, 100), 
+                                   source_info = source_info_both())
+        
+        lapop_save(hist_to_save, file)
+        showNotification(HTML("Plot download complete ✓ "), type = "message")
+        
+      } else if (input$tabs == "Time Series") {
+        title_text <- isolate(cap())
+        subtitle_text <- slider_values()
+        
+        ts_to_save <-  lapop_ts(tsd(),
+                                main_title = title_text,
+                                subtitle = paste0("% in selected category ", subtitle_text),
+                                ymax = ifelse(any(tsd()$prop > 88, na.rm = TRUE), 110, 100),
+                                label_vjust = ifelse(any(tsd()$prop > 80, na.rm = TRUE), -1.1, -1.5),
+                                source_info = source_info_pais())
+        
+        lapop_save(ts_to_save, file)
+        showNotification(HTML("Plot download complete ✓ "), type = "message")
+        
+      } else if (input$tabs == "Cross Country") {
+        title_text <- isolate(cap())
+        subtitle_text <- slider_values()
+        
+        cc_to_save <- lapop_cc(ccd(), sort = "hi-lo", 
+                               main_title = title_text,
+                               subtitle = paste0("% in selected category ", subtitle_text),
+                               ymax = ifelse(any(ccd()$prop > 90, na.rm = TRUE), 110, 100),
+                               source_info = source_info_wave())
+        
+        lapop_save(cc_to_save, file)
+        showNotification(HTML("Plot download complete ✓ "), type = "message")
+        
+      } else {
+        title_text <- isolate(cap())
+        subtitle_text <- slider_values()
+        
+        mover_to_save <- lapop_mover(
+          moverd(),
+          main_title = title_text,
+          subtitle = paste0("% in selected category ", subtitle_text),
+          ymax = ifelse(any(moverd()$prop > 90, na.rm = TRUE), 119,
+                        ifelse(any(moverd()$prop > 80, na.rm = TRUE), 109, 100)),
+          source_info = source_info_both()
         )
+        
+        lapop_save(mover_to_save, file)
+        showNotification(HTML("Plot download complete ✓ "), type = "message")
+        
       }
-
-      p
+    }
+  )
+  
+  
+  output$downloadTable <- downloadHandler(
+    filename = function(file) {
+      ifelse(input$tabs == "Histogram", paste0("hist_", outcome(),".svg"),
+             ifelse(input$tabs == "Time Series",  paste0("ts_", outcome(),".svg"),
+                    ifelse(input$tabs == "Cross Country",  paste0("cc_", outcome(),".svg"),  paste0("mover_", outcome(),".svg"))))
     },
-    res = 100
+    content = function(file) {
+      if(input$tabs == "Histogram") {
+        write.csv(histd(), file)
+        showNotification(HTML("File download complete ✓ "), type = "message")
+        
+      } else if (input$tabs == "Time Series") {
+        write.csv(tsd(), file)
+        showNotification(HTML("File download complete ✓ "), type = "message")
+        
+      } else if (input$tabs == "Cross Country") {
+        write.csv(ccd(), file)
+        showNotification(HTML("File download complete ✓ "), type = "message")
+        
+      } else {
+        write.csv(moverd(), file)
+        showNotification(HTML("File download complete ✓ "), type = "message")
+        
+      }
+    }
   )
 }
 
+# Launch App
 shinyApp(ui, server)