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示例程序Tabsets展示的是如何用选项卡（tabs）来组织输出。要运行这个例子，就执行下面的命令：

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

选项卡面板（Tab Panels）
选项卡（tabsets）是由调用tabsetPanel函数创建的，在这函数中，又需要用tabPanel函数创建选项（tab）列表。每一个选项卡面板是由输出元素组成的，这些元素在选项卡中垂直排列。
在这个例子中，我们修改了原来的Hello Shiny程序，增加了一个摘要和数据表，两者分别渲染到它们各自的选项卡中。下面就是用户接口的代码：

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")) ) ) )) 

选项卡和反应式数据（Reactive Data）
将选项卡引入用户接口的时候，应该强调为共享数据创建反应表达式的重要性。在这个例子中，每个选项卡都提供了对数据集的查看方式。如果对数据集的处理比较费时，那么用户接口的定义可能变得很慢。下面的服务端脚本展示的是如何用反应表达式一次性计算数据，其结果被三个选项卡所共享。

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()) }) })