示例程序Tabsets展示的是如何用選項卡（tabs）來組織輸出。要運行這個例子，就執(zhí)行下面的命令：

> library(shiny) > runExample("06_tabsets") 

選項卡面板（Tab Panels）
選項卡（tabsets）是由調用tabsetPanel函數(shù)創(chuàng)建的，在這函數(shù)中，又需要用tabPanel函數(shù)創(chuàng)建選項（tab）列表。每一個選項卡面板是由輸出元素組成的，這些元素在選項卡中垂直排列。
在這個例子中，我們修改了原來的Hello Shiny程序，增加了一個摘要和數(shù)據(jù)表，兩者分別渲染到它們各自的選項卡中。下面就是用戶接口的代碼：

library(shiny) # Define UI for random distribution application  shinyUI(pageWithSidebar( # Application title headerPanel("Tabsets"), # Sidebar with controls to select the random distribution type # and number of observations to generate. Note the use of the br() # element to introduce extra vertical spacing sidebarPanel( radioButtons("dist", "Distribution type:", list("Normal" = "norm", "Uniform" = "unif", "Log-normal" = "lnorm", "Exponential" = "exp")), br(), sliderInput("n", "Number of observations:", value = 500, min = 1, max = 1000) ), # Show a tabset that includes a plot, summary, and table view # of the generated distribution mainPanel( tabsetPanel( tabPanel("Plot", plotOutput("plot")), tabPanel("Summary", verbatimTextOutput("summary")), tabPanel("Table", tableOutput("table")) ) ) )) 

選項卡和反應式數(shù)據(jù)（Reactive Data）
將選項卡引入用戶接口的時候，應該強調為共享數(shù)據(jù)創(chuàng)建反應表達式的重要性。在這個例子中，每個選項卡都提供了對數(shù)據(jù)集的查看方式。如果對數(shù)據(jù)集的處理比較費時，那么用戶接口的定義可能變得很慢。下面的服務端腳本展示的是如何用反應表達式一次性計算數(shù)據(jù)，其結果被三個選項卡所共享。

library(shiny) # Define server logic for random distribution application shinyServer(function(input, output) { # Reactive expression to generate the requested distribution. This is  # called whenever the inputs change. The renderers defined  # below then all use the value computed from this expression data <- reactive({ dist <- switch(input$dist, norm = rnorm, unif = runif, lnorm = rlnorm, exp = rexp, rnorm) dist(input$n) }) # Generate a plot of the data. Also uses the inputs to build the  # plot label. Note that the dependencies on both the inputs and # the 'data' reactive expression are both tracked, and all expressions  # are called in the sequence implied by the dependency graph output$plot <- renderPlot({ dist <- input$dist n <- input$n hist(data(), main=paste('r', dist, '(', n, ')', sep='')) }) # Generate a summary of the data output$summary <- renderPrint({ summary(data()) }) # Generate an HTML table view of the data output$table <- renderTable({ data.frame(x=data()) }) })