aes non dynamique

shinebright/app.R

@@ -8,6 +8,12 @@
 #
 
 library(shiny)
+library(dplyr)
+library(ggplot2)
+library(DT)
+
+View(diamonds)
+# diamonds <- read.csv("data/diamonds.csv")
 
 # Define UI for application that draws a histogram
 ui <- fluidPage(
@@ -18,32 +24,60 @@ ui <- fluidPage(
     # Sidebar with a slider input for number of bins 
     sidebarLayout(
         sidebarPanel(
-            sliderInput("bins",
-                        "Number of bins:",
-                        min = 1,
-                        max = 50,
-                        value = 30)
+            sliderInput("Price",
+                        "Prix des diamants:",
+                        min = 300,
+                        max = 20000,
+                        value = 3000),
+        
+            selectInput(
+              inputId = "colorFilter",
+              choices = c("D","E","F","G","H","I","J"),
+              label = "Choix des couleurs à filtrer",
+              selected = NULL,
+              multiple = FALSE,
+              selectize = TRUE,
+              width = NULL,
+              size = NULL
               ),
+            radioButtons(
+              inputId = "rosePoint",
+              label = "Colorier les points en Rose ?",
+              selected = NULL,
+              choices = c("oui" = "pink","non"="black"),
               
+              ),
+        ),
         # Show a plot of the generated distribution
         mainPanel(
-           plotOutput("distPlot")
-        )
+           plotOutput("diamondPlot"),
+           textOutput("txt")
         )
+    ),
+    DTOutput(outputId = "DiamondTable")
+    
 )
 
 # Define server logic required to draw a histogram
 server <- function(input, output) {
 
-    output$distPlot <- renderPlot({
-        # generate bins based on input$bins from ui.R
-        x    <- faithful[, 2]
-        bins <- seq(min(x), max(x), length.out = input$bins + 1)
+    output$diamondPlot <- renderPlot({
+        diamonds %>% 
+          filter(price > input$Price) %>% 
+          filter(color > input$colorFilter) %>% 
+          ggplot(aes(x= carat,y= price)) +
+                   (aes(color = input$rosePoint))+
+          geom_point()
+      
         
-        # draw the histogram with the specified number of bins
-        hist(x, breaks = bins, col = 'darkgray', border = 'white',
-             xlab = 'Waiting time to next eruption (in mins)',
-             main = 'Histogram of waiting times')
+    })
+    output$DaimondTable <- renderDT({
+      diamonds %>% 
+        filter(price > input$Price) %>% 
+        filter(color > input$colorFilter)
+    })
+    output$txt <- renderText({
+      paste("You chose", input$rosePoint)
     })
 }