group_by dplyr功能闪亮 [英] group_by dplyr function in shiny

问题描述

在使用闪光时，我遇到了在dplyr工作中遇到group_by问题。看来，dplyr不能将来自Shiny的$ var的输入识别为表中的有效字段。

I'm having trouble getting group_by in dplyr work while using Shiny. It seems like dplyr doesn't recognize the input$var from Shiny as being a valid field in the table.

在这个例子中，我想要 ui.R来决定什么是分组。

In this example, I want the "level" input in ui.R to dictate what to group by.

在ui.RI中有：

library(shiny)
shinyUI(fluidPage(
titlePanel("Orders"),
sidebarLayout(
sidebarPanel(
  selectInput("Region_Input", label = h5("Choose a Region"), 
              choices = list("A", "B")),
  radioButtons("level", "What level do you want to see:",
                     list("item", "category"))

),
mainPanel(
  verbatimTextOutput("Level_Select"),
  tableOutput(outputId="table")

))))

在server.RI中：

In server.R I have:

library(shiny)  
library(dplyr)

OrderItems <- data.frame(Region =      c('A','A','A','A','A','A','B','B','B','B','B','B','B'),
                     item = c('Item A','Item B','Item C','Item D','Item E',
                              'Item A','Item B','Item C','Item D','Item E',
                              'Item A','Item B','Item C'),
                     category = c('Cat 1','Cat 1','Cat 1','Cat 2','Cat 2',
                                  'Cat 1','Cat 1','Cat 1','Cat 2','Cat 2',
                                  'Cat 1','Cat 1','Cat 1'))
shinyServer(
function(input, output) {

output$table <- renderTable({
  OrderItems %>%
    group_by(input$level) %>%
    summarize(count = n()) %>%
    arrange(desc(count))    
})
})

输出我期望的级别输入是类别是：

The output I expect when the "level" input is "category" is:

   category count
1   Cat 1   9
2   Cat 2   4

然而，我最终得到的是：

However, what I end up getting is:

    input$level count
1   category           13

任何关于如何解决这个问题的想法将不胜感激！

Any ideas on how to fix this would be greatly appreciated!

推荐答案

Per @ joran的评论，这应该是替换 group_by（input $ level） with group_by_（input $ level），但很难说没有可重现的例子。如果您进行了一些修改并利用 mtcars 数据，可以重现以下内容，以了解其运作方式：

Per @joran's comment, this should be as simple as replacing group_by(input$level) with group_by_(input$level), but its tough to say without a reproducible example. If you make a few changes and leverage the mtcars data, one can reproduce the following to see how this works:

library(shiny)  
library(dplyr)

shinyServer(
  function(input, output) {

    output$table <- renderTable({
      mtcars %>%
        group_by_(input$level) %>%
        summarize(count = n()) %>%
        arrange(desc(count))    
    })
  })

ui.R

ui.R

library(shiny)
shinyUI(fluidPage(
  titlePanel("Orders"),
  sidebarLayout(
    sidebarPanel(
      selectInput("Region_Input", label = h5("Choose a Region"), 
                  choices = list("A", "B")),
      radioButtons("level", "What level do you want to see:",
                   list("cyl", "am"))

    ),
    mainPanel(
      verbatimTextOutput("Level_Select"),
      tableOutput(outputId="table")

    ))))

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