Сияющий - не удается отобразить Барплот - PullRequest
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Сияющий - не удается отобразить Барплот

0 голосов
/ 01 мая 2018

Почему барплот не отображается? Если я запускаю тот же код за пределами более крупной программы, отображается барплот. Я получаю радио кнопки и схему графиков, но нет данных внутри. Я включил сервер и пользовательский интерфейс и данные ниже. Я очень новичок в блестящей.

Я пробовал скобки, запятые и скобки в нескольких местах. Я не нашел решение. 

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

Ответы [ 2 ]

0 голосов
/ 02 мая 2018

@ mlegge ответ хороший (и должен быть принятым ответом) - основной проблемой были вложенные серверные функции. Но вы можете еще больше упростить функцию вашего сервера. Поскольку renderPlot является реагирующей средой, вы можете установить для данных в вашем вызове значение renderPlot следующим образом: 

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)
})

Это устраняет ненужное присвоение reactive_data

0 голосов
/ 02 мая 2018

У вас возникла проблема с именами, как указывал Аурель в комментариях, но, что еще более тревожно, вы определили вложенные функции server ... Я исправляю это как неудачное копирование-вставку, но вот рабочая версия , Я добавил shiny::validate, чтобы убедиться, что он не пытался построить график, когда данных не было. 

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)

enter image description here

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