[shiny 1]

Shiny应用程序分为两个部分：用户界面定义和服务端脚本。

1. 在教程的后续章节，我们将解释代码的细节并讲解如何用“反应性”表达式来生成输出。现在，就尝试运行一下例子程序，浏览一下源代码，以获得对shiny的初始印象。也请认真阅读注释。

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")

    )
  )
)

2.下面列出了服务端的代码。从某种程度上说，它很简单——生成给定个数的随机变量， 然后将直方图画出来。不过，你也注意到了，返回图形的函数被 renderPlot包裹着。函数上面的注释对此做出了一些解释，不过如果你觉得还是搞不明白，不用担心——后面我们将更进一步解释这个概念。

#定义绘制直方图所需的服务器逻辑
# 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$bins) change 
它是“反应性的”，因此当输入(输入$bins)发生变化时应该是自动的 重新执行
  # 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")

    })

}

3.创建shinyapp

# Create Shiny app ----
shinyApp(ui = ui, server = server)