闪亮 - 无法显示条形图

Question

为什么条形图不显示？如果我在较大的程序之外运行相同的代码，则会显示条形图。我得到单选按钮和图表的轮廓，但内部没有数据。我在下面包含了服务器和 ui 和数据。我对闪亮很陌生。

我在多个地方尝试过括号、逗号和圆括号。我还没有找到解决办法。

UI.r
#UI Program
library(shiny)
library(shinydashboard)
library(ggplot2)
library(ggthemes)
library(DT)

# my data
my_data=read.table("hack.csv", header=T, sep=",")
# changing date to categorical data 
#my_data$Year=factor(my_data$Year)

## Preparing sidebar items
sidebar <- dashboardSidebar(
  width = 300,
  sidebarMenu(
    menuItem(h3("Dashboard"), tabName = "dashbd"),
    menuItem(h3("Data"), tabName = "datafile"),
    menuItem(h3("Visualization of Data"), tabName = "graphs", 
         menuSubItem(h4("- Barplot"), tabName = "crime")    ),

    br(),
    br(),
    hr()
  )
)
## Preparing for the body items
body <- dashboardBody(
  tabItems(
    tabItem(tabName = "dashbd",
        fluidRow(
          valueBoxOutput("vbox1", width = 6),
          valueBoxOutput("vbox2", width = 6)),
        h2("Introduction",  align = "center", style = "font-family: 'times'; color:blue"),
        h3("Cyber crime damage costs to hit $6 trillion annually by 2021. It all begins and ends with cyber crime. Without it, there's nothing to cyber-defend. The cybersecurity community and major media have largely concurred on the prediction that cyber crime damages will cost the world $6 trillion annually by 2021, up from $3 trillion in 2015. This represents the greatest transfer of economic wealth in history, risks the incentives for innovation and investment, and will be more profitable than the global trade of all major illegal drugs combined"),
        fluidPage(
          fluidRow(
            column(
              h2("About this app ...", align = "center", style = "font-family: 'times'; color:blue"),
              h3("This app helps you to explore and visualize the motivation behind cyber attacks
                 I have used the database available",  a("here.",href="https://www.hackmageddon.com/about/"), 
                 style = "font-family: 'times'"),
              width = 4,
              align = "left"

            ),
            column(
              h2("How to use!", style = "font-family: 'times'; color:blue"),
              h3("This app contains multiple sections;  the database and several visual graphs. ", 
                 style = "font-family: 'times'"),              
              width = 8,
              align = "left"
            ),
            br(),
            br()
            )
        ),
        p()
    ),  
    tabItem(tabName = "datafile",
        box(title = "Motivation of Cyber Attacks in Italy",
            width = 12, 
            DT::dataTableOutput('da.tab'))  
    ),

#the select for barplot
tabItem(tabName = "crime",
        titlePanel(title = h4("Cyber Attacks in Italy by Year", align="center")),
        sidebarPanel(

          radioButtons("YEAR", "Select the Census Year",
                       choices = c("2017", "2016", "2015","2014"),
                       selected = "2017")),


        sidebarPanel(
          plotOutput("MyBar"))
    )  

  )  )

# Show a plot of the generated distribution
## Putting them together into a dashboardPage

ui <- dashboardPage( 
  skin="blue",
  # add this -> navbarMenu()
  dashboardHeader(
    title="MOTIVATION BEHIND CYBER ATTACKS IN ITALY",
    titleWidth = 550,
    tags$li(class = "dropdown"
    )
  ),
  sidebar,
  body
)

SERVER
    # Reading data set
my_data=read.table("hack.csv", header=T, sep=",")
#number of row of data
my_data$Year=as.factor(my_data$Year)
server <- function(input, output) {
  ## Information for dashboard tab 
  # Reading data set
  my_data=read.table("hack.csv", header=T, sep=",")
  #number of row of data
  my_data$Year=as.factor(my_data$Year)

  server <- function(input, output) {



## Information for data tab
# data table output


output$da.tab <- DT::renderDataTable(datatable(my_data, extensions = 'Buttons',
                                               style = "bootstrap",
                                               filter = list(position = 'top', clear = T, plain = F),
                                               options = list(pageLength = 1500, dom = 'Bfrtip', 
                                                              buttons = 
                                                                list('copy', 'print', list(
                                                                  extend = 'collection',
                                                                  buttons = c('csv', 'excel', 'pdf'), 
                                                                  text = 'Download')
                                                                )
                                               )
    )    )


  }
  ## Information for data tab
  # data table output


  output$da.tab <- DT::renderDataTable(datatable(my_data, extensions = 'Buttons',
                                             style = "bootstrap",
                                             filter = list(position = 'top', clear = T, plain = F),
                                             options = list(pageLength = 1500, dom = 'Bfrtip', 
                                                            buttons = 
                                                              list('copy', 'print', list(
                                                                extend = 'collection',
                                                                buttons = c('csv', 'excel', 'pdf'), 
                                                                text = 'Download')
                                                              )
                                             )  )  )


  #This is used to create the BarPlot
  server <- function(input,output){

    reactive_data = reactive({
  #Reading from the datbase for year selected
  selected_year = as.numeric(input$YEAR)
  return(data[data$year==selected_year,])

    })
    #outputting the bar data
    output$bar <- renderPlot({
      color <- c("blue", "red", "yellow")

      our_data <- reactive_data()

      barplot(colSums(our_data[,c("CyberCrime","CyberWar","CyberHacks")]),
          ylab="Total",
          xlab="Census Year",
          names.arg = c("CyberCrime","CyberWar","CyberHacks"),
          col = color)
            })
      }}


DATA
#This is the data for the query
Year,CyberCrime,CyberWar,CyberHacks,CyberEspionage
2017,60,45,12,16
2016,65,40,16,14
2015,55,38,10,9
2014,50,26,9,6

Answer 1

正如 Aurele 在 cmets 中指出的那样，您确实遇到了命名问题，但更令人担忧的是，您已经定义了嵌套的 server 函数......我将其归结为糟糕的复制粘贴工作，但这是一个工作版本.我添加了一个shiny::validate 以确保它在没有数据时不会尝试绘制条形图。

library(shiny)
library(shinydashboard)
library(ggplot2)
library(ggthemes)
library(DT)

my_data <- read.table(text = "
Year,CyberCrime,CyberWar,CyberHacks,CyberEspionage
2017,60,45,12,16
2016,65,40,16,14
2015,55,38,10,9
2014,50,26,9,6", sep = ",", header = TRUE)


## Preparing sidebar items
sidebar <- dashboardSidebar(
  width = 300,
  sidebarMenu(
    menuItem(h3("Dashboard"), tabName = "dashbd"),
    menuItem(h3("Data"), tabName = "datafile"),
    menuItem(h3("Visualization of Data"), tabName = "graphs", 
             menuSubItem(h4("- Barplot"), tabName = "crime")    ),

    br(),
    br(),
    hr()
  )
)
## Preparing for the body items
body <- dashboardBody(
  tabItems(
    tabItem(tabName = "dashbd",
            fluidRow(
              valueBoxOutput("vbox1", width = 6),
              valueBoxOutput("vbox2", width = 6)),
            h2("Introduction",  align = "center", style = "font-family: 'times'; color:blue"),
            h3("Cyber crime damage costs to hit $6 trillion annually by 2021. It all begins and ends with cyber crime. Without it, there's nothing to cyber-defend. The cybersecurity community and major media have largely concurred on the prediction that cyber crime damages will cost the world $6 trillion annually by 2021, up from $3 trillion in 2015. This represents the greatest transfer of economic wealth in history, risks the incentives for innovation and investment, and will be more profitable than the global trade of all major illegal drugs combined"),
            fluidPage(
              fluidRow(
                column(
                  h2("About this app ...", align = "center", style = "font-family: 'times'; color:blue"),
                  h3("This app helps you to explore and visualize the motivation behind cyber attacks
                     I have used the database available",  a("here.",href="https://www.hackmageddon.com/about/"), 
                     style = "font-family: 'times'"),
                  width = 4,
                  align = "left"

                ),
                column(
                  h2("How to use!", style = "font-family: 'times'; color:blue"),
                  h3("This app contains multiple sections;  the database and several visual graphs. ", 
                     style = "font-family: 'times'"),              
                  width = 8,
                  align = "left"
                ),
                br(),
                br()
                )
            ),
            p()
    ),  
    tabItem(tabName = "datafile",
            box(title = "Motivation of Cyber Attacks in Italy",
                width = 12, 
                DT::dataTableOutput('da.tab'))  
    ),

    #the select for barplot
    tabItem(tabName = "crime",
            titlePanel(title = h4("Cyber Attacks in Italy by Year", align="center")),
            sidebarPanel(

              radioButtons("YEAR", "Select the Census Year",
                           choices = c("2017", "2016", "2015","2014"),
                           selected = "2017")),


            sidebarPanel(
              plotOutput("MyBar"))
    )  

  )  )

# Show a plot of the generated distribution
## Putting them together into a dashboardPage

ui <- dashboardPage( 
  skin="blue",
  # add this -> navbarMenu()
  dashboardHeader(
    title="MOTIVATION BEHIND CYBER ATTACKS IN ITALY",
    titleWidth = 550,
    tags$li(class = "dropdown"
    )
  ),
  sidebar,
  body
)


server <- function(input, output) {

  output$da.tab <- DT::renderDataTable(
    datatable(
      data = my_data, 
      extensions = 'Buttons',
      style = "bootstrap",
      filter = list(position = 'top', clear = T, plain = F),
      options = list(
        pageLength = 1500,
        dom = 'Bfrtip', 
        buttons = list(
          'copy', 
          'print',
          list(
            extend = 'collection',
            buttons = c('csv', 'excel', 'pdf'), 
            text = 'Download')
          ) #/ buttonList
        ) #/ options 
      ) #/ datatable
    ) #/ renderDataTable

  reactive_data = reactive({
    #Reading from the datbase for year selected
    my_data[my_data$Year == input$YEAR,]

  })

  #outputting the bar data
  output$MyBar <- renderPlot({
    color <- c("blue", "red", "yellow")

    our_data <- reactive_data()

    shiny::validate(
      need(nrow(our_data) > 0, "No data for that year!")
    )

    barplot(colSums(our_data[,c("CyberCrime","CyberWar","CyberHacks")]),
            ylab="Total",
            xlab="Census Year",
            names.arg = c("CyberCrime","CyberWar","CyberHacks"),
            col = color)
  })

}

shinyApp(ui, server)

Answer 2

@mlegge 的答案很好（应该是公认的答案）——嵌套的服务器功能是主要问题。但是您可以进一步简化您的服务器功能。因为renderPlot 是一个反应式环境，您可以像这样子集调用renderPlot 中的数据：

output$MyBar <- renderPlot({
  our_data <- my_data[my_data$Year==input$YEAR,]
  color <- c("blue", "red", "yellow")

  barplot(colSums(our_data[,c("CyberCrime","CyberWar","CyberHacks")]),
          ylab="Total",
          xlab="Census Year",
          names.arg = c("CyberCrime","CyberWar","CyberHacks"),
          col = color)
})

这消除了对reactive_data的不必要分配