the original hello-world example makes little practical sense -- it is unclear what really changed when moving the slider, especially when obs is large (we always see a "bell-shaped" histogram)

let's make the number of bins reactive instead; now it is very clear what the slider really controls

a histogram with different number of bins also serves as a good demo of the property of histograms (small bins --> small variance + large bias)

inst/examples/01_hello/Readme.md

@@ -1,5 +1,4 @@
-This small Shiny application demonstrates Shiny's automatic UI updates. Move the
-*Number of observations* slider and notice how the `renderPlot` expression is
-automatically re-evaluated when its dependant, `input$obs`, changes, causing a
-new distribution to be generated and the plot to be rendered.
-
+This small Shiny application demonstrates Shiny's automatic UI updates. Move
+the *Number of bins* slider and notice how the `renderPlot` expression is
+automatically re-evaluated when its dependant, `input$bins`, changes,
+causing a histogram with a new number of bins to be rendered.

inst/examples/01_hello/server.R

@@ -1,22 +1,21 @@
 library(shiny)
 
-# Define server logic required to generate and plot a random
-# distribution
+# Define server logic required to draw a histogram
 shinyServer(function(input, output) {
-   
-  # Expression that generates a plot of the distribution. The 
-  # expression is wrapped in a call to renderPlot to indicate 
-  # that:
+
+  # Expression that generates a histogram. The expression is
+  # wrapped in a call to renderPlot to indicate that:
   #
-  #  1) It is "reactive" and therefore should be automatically 
+  #  1) It is "reactive" and therefore should be automatically
   #     re-executed when inputs change
-  #  2) Its output type is a plot 
-  #
+  #  2) Its output type is a plot
+
   output$distPlot <- renderPlot({
-        
-    # generate an rnorm distribution and plot it
-    dist <- rnorm(input$obs)
-    hist(dist)
+    x    <- faithful[, 2]  # Old Faithful Geyser data
+    bins <- seq(min(x), max(x), length.out = input$bins + 1)
+
+    # draw the histogram with the specified number of bins
+    hist(x, breaks = bins, col = 'darkgray', border = 'white')
   })
-  
+
 })

inst/examples/01_hello/ui.R

@@ -1,21 +1,21 @@
 library(shiny)
 
-# Define UI for application that plots random distributions 
+# Define UI for application that draws a histogram
 shinyUI(fluidPage(
-  
+
   # Application title
   titlePanel("Hello Shiny!"),
-  
-  # Sidebar with a slider input for number of observations
+
+  # Sidebar with a slider input for the number of bins
   sidebarLayout(
     sidebarPanel(
-      sliderInput("obs", 
-                  "Number of observations:", 
-                  min = 1, 
-                  max = 1000, 
-                  value = 500)
+      sliderInput("bins",
+                  "Number of bins:",
+                  min = 1,
+                  max = 50,
+                  value = 30)
     ),
-    
+
     # Show a plot of the generated distribution
     mainPanel(
       plotOutput("distPlot")