错误：“闭包”类型的对象不可子集

Question

我正在尝试借助滑块更改 2 个 ValueBoxes 中的值（属性“pf_score”和“ef_score”每年的平均值），滑块的时间为 2008-2016 年。 输出如我所愿可见，但我也看到一个错误“'closure'类型的对象不是子集”

更新：我无法通过单击 Run-App 来运行整个代码。我收到错误“找不到函数 df1”。我必须先单独读取所有数据帧，然后单击 Run-App 才能看到 UI。

server.r

require(shiny)
require(dplyr)
require(shinydashboard)

shinyServer(function(input,output){
  
  df <- read.csv("hfi_cc_2018.csv", header = T)
  
  summary(df)
  sapply(df, function(x) sum(is.na(x)))
  #Replace Null Values
  df[is.na(df)] <- 0
  df[,5:ncol(df)] <- round(df[,5:ncol(df)], 2)
  
  #adding selective columns new df1
  #https://stackoverflow.com/questions/10085806/extracting-specific-columns-from-a-data-frame
  df1<- df[, (names(df) %in% c("year","pf_score", "ef_score"
  ))]

output$select_years <- renderUI(
{
   card <- df1 %>%
              filter(year == input$years)
   output$pfrank = renderValueBox(
     valueBox(round(mean(card$pf_score),1),
              "Personal Freedom Score")
   )
   output$efrank = renderValueBox(
     valueBox(round(mean(card$ef_score),1),
              "Economic Freedom Score")
   )
}
)
})

ui.r

require(shiny)
require(shinydashboard)

shinyUI(
  
  dashboardPage( 
    dashboardHeader(title = "Human Freedom Index", titleWidth = 300),
    dashboardSidebar(
      sliderInput("years","Select Year:",
                  min = min(df1$year),
                  max = max(df1$year),
                  value = min(df1$year),
                  step = 1),
      selectInput("variable","Select Freedom Factor:",
                  choices = colnames(df1)
                  )
    ),
    
    dashboardBody(
      uiOutput("select_years"),
      fluidRow(
        valueBoxOutput("pfrank"),
        valueBoxOutput("efrank")
      )
    )
  )
  
)

Answer 1

此类错误在：Error in <my code> : object of type 'closure' is not subsettable

中讨论

在这种情况下，看起来您将 card 作为纯数据框，而您需要 reactive 以便在您移动滑块时重新计算它。此外，renderUI 的表达式可以简化为一个列表。例如，

ui <- shinyUI( ... )
server <- function(input, output) {
  card <- reactive({
    df1 %>%
    filter(year == input$years)
  })
  output$select_years <- renderUI(
    c(renderValueBox(valueBox(round(mean(card()$pf_score), 1),
                   "Personal Freedom Score")),
      renderValueBox(valueBox(round(mean(card()$ef_score), 1),
                   "Economic Freedom Score"))))
}
shinyApp(ui, server)

还要注意，新版本的 Shiny 稍微简化了语法。代码可以直接进入app.R，你需要定义ui和server。

Answer 2

您可以使用observe() 代替renderUI 来呈现值框：

require(shiny)
require(dplyr)
require(shinydashboard)

   df <- read.csv("hfi_cc_2018.csv", header = T)

   summary(df)
   sapply(df, function(x) sum(is.na(x)))
   #Replace Null Values
   df[is.na(df)] <- 0
   df[,5:ncol(df)] <- round(df[,5:ncol(df)], 2)

   #adding selective columns new df1
   #https://stackoverflow.com/questions/10085806/extracting-specific-columns-from-a-data-frame
   df1 <- df[, (names(df) %in% c("year","pf_score", "ef_score"))]

 #UI  
 ui <- dashboardPage( 
    dashboardHeader(title = "Human Freedom Index", titleWidth = 300),
    dashboardSidebar(
      sliderInput("years","Select Year:",
                  min = min(df1$year),
                  max = max(df1$year),
                  value = min(df1$year),
                  step = 1),
      selectInput("variable","Select Freedom Factor:",
                  choices = colnames(df1)
      )
    ),

    dashboardBody(
      fluidRow(
        valueBoxOutput("pfrank"),
        valueBoxOutput("efrank")
      )
    )
  )

#Server
 server <- function(input,output){

   observe({
       card <- df1 %>%
         filter(year == input$years)
       output$pfrank = renderValueBox(
         valueBox(round(mean(card$pf_score),1),
                  "Personal Freedom Score")
       )
       output$efrank = renderValueBox(
         valueBox(round(mean(card$ef_score),1),
                  "Economic Freedom Score")
       )
     })
 }

#Run app
shinyApp(ui, server)