Plot sexe

app.R

@@ -132,28 +132,37 @@ server <- function(input, output, session)
       theme(axis.title = element_blank())
   })
 
-  # observe({
-  # output$plot_age <- renderPlotly({
-  # filteredData() %>%
-  # (
-  # ggplot() +
-  # aes(x = Age, y = ..density..) +
-  # geom_histogram() +
-  # geom_density()
-  # ) %>% ggplotly
-  # })
-  # })
-  # observe({
-    # leafletProxy("map", data = in_bounds()) %>%
-      # clearShapes() %>%
-  # })
-  # Use a separate observer to recreate the legend as needed.
-  # observe({
-  # Remove any existing legend, and only if the legend is
-  # enabled, create a new one.
-  # leafletProxy("map", data = quakes) %>%
-  # clearControls()
-  # if (input$legend) {
+  # Sexe
+  data_sexe <- reactive({
+    if (input$choice_ghm %>% is.null)
+    {
+      GHM %>%
+        filter(Age <= input$slider_age[2] & Age >= input$slider_age[1], 
+               date_entree <= input$slider_date[2] & date_sortie >= input$slider_date[1],
+               CP %in% in_bounds()$Codepos)
+    } else
+    {
+      GHM %>%
+        filter(Age <= input$slider_age[2] & Age >= input$slider_age[1], 
+               GHM %in% input$choice_ghm,
+               date_entree <= input$slider_date[2] & date_sortie >= input$slider_date[1],
+               CP %in% in_bounds()$Codepos)
+    }
+  })
+
+  output$plot_sexe <- renderPlot({
+    data_sexe() %>%
+      ggplot() +
+      aes(x = 1, fill = Sexe) +
+      geom_bar() +
+      coord_flip() +
+      scale_fill_manual(values = c("Homme" = "lightblue", "Femme" = "pink")) +
+      theme(axis.title = element_blank(),
+            legend.position = "none",
+            axis.text.y = element_blank(),
+            axis.ticks.y = element_blank())
+  })
+
   # pal <- colorpal()
   # proxy %>% addLegend(position = "bottomright",
   # pal = pal, values = ~mag