Convert to single-file app.

- For examples 1-11, use the code and descriptions from shiny package verbatim.
- For example 12, use the code in the revised datatables article.

001-hello/Readme.md

@@ -1,4 +1,3 @@
-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$bins`, changes,
-causing a histogram with a new number of bins to be rendered.
+This small Shiny application demonstrates Shiny's automatic UI updates. 
+
+Move the *Number of bins* slider and notice how the `renderPlot` expression is automatically re-evaluated when its dependant, `input$bins`, changes, causing a histogram with a new number of bins to be rendered.

001-hello/app.R

@@ -0,0 +1,59 @@
+library(shiny)
+
+# Define UI for app that draws a histogram ----
+ui <- fluidPage(
+
+  # App title ----
+  titlePanel("Hello Shiny!"),
+
+  # Sidebar layout with input and output definitions ----
+  sidebarLayout(
+
+    # Sidebar panel for inputs ----
+    sidebarPanel(
+
+      # Input: Slider for the number of bins ----
+      sliderInput(inputId = "bins",
+                  label = "Number of bins:",
+                  min = 1,
+                  max = 50,
+                  value = 30)
+
+    ),
+
+    # Main panel for displaying outputs ----
+    mainPanel(
+
+      # Output: Histogram ----
+      plotOutput(outputId = "distPlot")
+
+    )
+  )
+)
+
+# Define server logic required to draw a histogram ----
+server <- function(input, output) {
+
+  # Histogram of the Old Faithful Geyser Data ----
+  # with requested number of bins
+  # This expression that generates a histogram is wrapped in a call
+  # to renderPlot to indicate that:
+  #
+  # 1. It is "reactive" and therefore should be automatically
+  #    re-executed when inputs (input$bins) change
+  # 2. Its output type is a plot
+  output$distPlot <- renderPlot({
+
+    x    <- faithful$waiting
+    bins <- seq(min(x), max(x), length.out = input$bins + 1)
+
+    hist(x, breaks = bins, col = "#75AADB", border = "white",
+         xlab = "Waiting time to next eruption (in mins)",
+         main = "Histogram of waiting times")
+
+    })
+
+}
+
+# Create Shiny app ----
+shinyApp(ui = ui, server = server)

002-text/Readme.md

@@ -1 +1 @@
-This example demonstrates output of raw text from R using the `renderPrint` function in `server.R` and the `verbatimTextOutput` function in `ui.R`. In this case, a textual summary of the data is shown using R's built-in `summary` function. 
+This example demonstrates output of raw text from R using the `renderPrint` function in `server` and the `verbatimTextOutput` function in `ui`. In this case, a textual summary of the data is shown using R's built-in `summary` function. 

002-text/app.R

@@ -0,0 +1,64 @@
+library(shiny)
+
+# Define UI for dataset viewer app ----
+ui <- fluidPage(
+
+  # App title ----
+  titlePanel("Shiny Text"),
+
+  # Sidebar layout with a input and output definitions ----
+  sidebarLayout(
+
+    # Sidebar panel for inputs ----
+    sidebarPanel(
+
+      # Input: Selector for choosing dataset ----
+      selectInput(inputId = "dataset",
+                  label = "Choose a dataset:",
+                  choices = c("rock", "pressure", "cars")),
+
+      # Input: Numeric entry for number of obs to view ----
+      numericInput(inputId = "obs",
+                   label = "Number of observations to view:",
+                   value = 10)
+    ),
+
+    # Main panel for displaying outputs ----
+    mainPanel(
+
+      # Output: Verbatim text for data summary ----
+      verbatimTextOutput("summary"),
+
+      # Output: HTML table with requested number of observations ----
+      tableOutput("view")
+
+    )
+  )
+)
+
+# Define server logic to summarize and view selected dataset ----
+server <- function(input, output) {
+
+  # Return the requested dataset ----
+  datasetInput <- reactive({
+    switch(input$dataset,
+           "rock" = rock,
+           "pressure" = pressure,
+           "cars" = cars)
+  })
+
+  # Generate a summary of the dataset ----
+  output$summary <- renderPrint({
+    dataset <- datasetInput()
+    summary(dataset)
+  })
+
+  # Show the first "n" observations ----
+  output$view <- renderTable({
+    head(datasetInput(), n = input$obs)
+  })
+
+}
+
+# Create Shiny app ----
+shinyApp(ui = ui, server = server)

003-reactivity/Readme.md

@@ -1,5 +1,5 @@
-This example demonstrates a core feature of Shiny: **reactivity**. In `server.R`, a reactive called `datasetInput` is declared. 
+This example demonstrates a core feature of Shiny: **reactivity**. In the `server` function, a reactive called `datasetInput` is declared. 
 
-Notice that the reactive expression depends on the input expression `input$dataset`, and that it's used by both the output expression `output$summary` and `output$view`. Try changing the dataset (using *Choose a dataset*) while looking at the reactive and then at the outputs; you will see first the reactive and then its dependencies flash. 
+Notice that the reactive expression depends on the input expression `input$dataset`, and that it's used by two output expressions: `output$summary` and `output$view`. Try changing the dataset (using *Choose a dataset*) while looking at the reactive and then at the outputs; you will see first the reactive and then its dependencies flash. 
 
 Notice also that the reactive expression doesn't just update whenever anything changes--only the inputs it depends on will trigger an update. Change the "Caption" field and notice how only the `output$caption` expression is re-evaluated; the reactive and its dependents are left alone.

003-reactivity/app.R

@@ -0,0 +1,102 @@
+library(shiny)
+
+# Define UI for dataset viewer app ----
+ui <- fluidPage(
+
+  # App title ----
+  titlePanel("Reactivity"),
+
+  # Sidebar layout with input and output definitions ----
+  sidebarLayout(
+
+    # Sidebar panel for inputs ----
+    sidebarPanel(
+
+      # Input: Text for providing a caption ----
+      # Note: Changes made to the caption in the textInput control
+      # are updated in the output area immediately as you type
+      textInput(inputId = "caption",
+                label = "Caption:",
+                value = "Data Summary"),
+
+      # Input: Selector for choosing dataset ----
+      selectInput(inputId = "dataset",
+                  label = "Choose a dataset:",
+                  choices = c("rock", "pressure", "cars")),
+
+      # Input: Numeric entry for number of obs to view ----
+      numericInput(inputId = "obs",
+                   label = "Number of observations to view:",
+                   value = 10)
+
+    ),
+
+    # Main panel for displaying outputs ----
+    mainPanel(
+
+      # Output: Formatted text for caption ----
+      h3(textOutput("caption", container = span)),
+
+      # Output: Verbatim text for data summary ----
+      verbatimTextOutput("summary"),
+
+      # Output: HTML table with requested number of observations ----
+      tableOutput("view")
+
+    )
+  )
+)
+
+# Define server logic to summarize and view selected dataset ----
+server <- function(input, output) {
+
+  # Return the requested dataset ----
+  # By declaring datasetInput as a reactive expression we ensure
+  # that:
+  #
+  # 1. It is only called when the inputs it depends on changes
+  # 2. The computation and result are shared by all the callers,
+  #    i.e. it only executes a single time
+  datasetInput <- reactive({
+    switch(input$dataset,
+           "rock" = rock,
+           "pressure" = pressure,
+           "cars" = cars)
+  })
+
+  # Create caption ----
+  # The output$caption is computed based on a reactive expression
+  # that returns input$caption. When the user changes the
+  # "caption" field:
+  #
+  # 1. This function is automatically called to recompute the output
+  # 2. New caption is pushed back to the browser for re-display
+  #
+  # Note that because the data-oriented reactive expressions
+  # below don't depend on input$caption, those expressions are
+  # NOT called when input$caption changes
+  output$caption <- renderText({
+    input$caption
+  })
+
+  # Generate a summary of the dataset ----
+  # The output$summary depends on the datasetInput reactive
+  # expression, so will be re-executed whenever datasetInput is
+  # invalidated, i.e. whenever the input$dataset changes
+  output$summary <- renderPrint({
+    dataset <- datasetInput()
+    summary(dataset)
+  })
+
+  # Show the first "n" observations ----
+  # The output$view depends on both the databaseInput reactive
+  # expression and input$obs, so it will be re-executed whenever
+  # input$dataset or input$obs is changed
+  output$view <- renderTable({
+    head(datasetInput(), n = input$obs)
+  })
+
+}
+
+# Create Shiny app ----
+shinyApp(ui, server)