Question

我正在尝试创建一个闪亮的应用程序，用户可以在其中上载.csv文件，然后对该数据框应用过滤器，然后使用ggplot2进行绘制。不幸的是，当我试图从应该上传的.csv变量创建一个选择输入菜单时，偶然发现了一个问题。

要创建一个简单的示例，我们可以将diamonds中的ggplot2数据集导出为.csv文件：

write.csv(diamonds, "diamonds.csv")

然后创建闪亮的应用程序：

library(shiny)
library(shinyWidgets)
library(ggplot2)

ui <- fluidPage(
    titlePanel("test shiny"),

    # Sidebar with a slider input for number of bins
    sidebarLayout(sidebarPanel(
        fileInput('file1', 'Choose file to upload',
                  accept = c(
                      'text/csv',
                      'text/comma-separated-values',
                      'text/tab-separated-values',
                      'text/plain',
                      '.csv',
                      '.tsv'
                  )
        ),
        tags$hr(),
        pickerInput(
            inputId = "caratx",
            label = "Choose carat",
            choices = c("Select all", unique(user_data$carat)),
            multiple = TRUE
        ),
        selectInput(
            inputId = "clarityx",
            label = "Choose distance: ",
            choices = unique(user_data$clarity)
        )
    ),
    mainPanel(plotOutput("endplot"))
    ))

# Define server logic 
server <- function(input, output) {

    output$endplot <- renderPlot({
        inFile <- input$file1

        if (is.null(inFile))
            return(NULL)

        user_data <- read.csv(inFile$datapath, header = T,
                              sep = ",", quote = input$quote)

        validate(
            need(input$entityx, 'Please select at least one carat'),
            need(input$indicatorx, 'Please select at least one clarity')
        )

        if (input$caratx %in% "Select all") {
            user_data <- user_data %>%
                filter(carat %in% input$caratx)
        } else {
            user_data <- user_data %>%
                filter(carat %in% input$caratx) %>%
                filter(clarity %in% input$clarityx) 
        }

        user_data %>% 
            ggplot(aes(x = `cut`)) +
            geom_point(aes(y = price), color = "red") +
            geom_point(aes(y = depth), color = "blue")
        })
}

# Run the application 
shinyApp(ui = ui, server = server)

这是输出：

Error in unique(user_data$carat) : object 'user_data' not found

有没有办法使这项工作成功？

非常感谢！

Answer 1

您要解决的实际问题应通过将user_data变成反应式并使用uiOutput + renderUI呈现输入来解决，如@kwiscion正确注释。

但是不幸的是，您的代码还有其他一些错误，使其无法再现：

样本数据集应为diamonds，而不是cars
input$quote在您的代码中不存在，因此我删除了对其的引用
您需要为代码中的某些功能添加library(dplyr)
input$entityx和input$indicatorx不存在

以上4个错误与您的问题无关，但使回答问题变得越来越困难。将来，请尝试确保您发布的代码正确且可重复。

下面是您的问题的答案，它解决了上面的4个问题，并实现了@kwiscion的两个建议

library(shiny)
library(shinyWidgets)
library(ggplot2)
library(dplyr)

ui <- fluidPage(
  titlePanel("test shiny"),

  # Sidebar with a slider input for number of bins
  sidebarLayout(sidebarPanel(
    fileInput('file1', 'Choose file to upload',
              accept = c(
                'text/csv',
                'text/comma-separated-values',
                'text/tab-separated-values',
                'text/plain',
                '.csv',
                '.tsv'
              )
    ),
    tags$hr(),
    uiOutput("caratx_input"),
    uiOutput("clarityx_input")
  ),
  mainPanel(plotOutput("endplot"))
  ))

# Define server logic 
server <- function(input, output) {
  file_data <- reactive({
    req(input$file1)
    read.csv(input$file1$datapath, header = TRUE,
             sep = ",")
  })

  output$caratx_input <- renderUI({
    req(file_data())
    pickerInput(
      inputId = "caratx",
      label = "Choose carat",
      choices = c("Select all", unique(file_data()$carat)),
      multiple = TRUE
    )
  })

  output$clarityx_input <- renderUI({
    req(file_data())
    selectInput(
      inputId = "clarityx",
      label = "Choose distance: ",
      choices = unique(file_data()$clarity)
    )
  })

  output$endplot <- renderPlot({
    req(file_data())

    validate(
      need(input$caratx, 'Please select at least one carat'),
      need(input$clarityx, 'Please select at least one clarity')
    )

    user_data <- file_data()
    if (input$caratx %in% "Select all") {
      user_data <- user_data %>%
        filter(carat %in% input$caratx)
    } else {
      user_data <- user_data %>%
        filter(carat %in% input$caratx) %>%
        filter(clarity %in% input$clarityx) 
    }

    user_data %>% 
      ggplot(aes(x = `cut`)) +
      geom_point(aes(y = price), color = "red") +
      geom_point(aes(y = depth), color = "blue")
  })
}

# Run the application 
shinyApp(ui = ui, server = server)

Answer 2

您需要

user_data反应式（https://shiny.rstudio.com/tutorial/written-tutorial/lesson6/）
使用pickerInput（https://shiny.rstudio.com/articles/dynamic-ui.html）渲染renderUI。

（下面是完整代码）

当您要计算并在以后使用取决于用户输入的值（在您的情况下为user_data）时，必须通过将计算放入reactive({ })中来使其成为反应式。然后，您可以引用类似于函数的值，即user_data()。因此，您的情况应该是：

user_data <- reactive({
      read.csv(input$file1$datapath, header = T,
               sep = ",", quote = input$quote)
    })

user_data() %>% ...

此外，还必须将其从renderPlot()中拉出才能起反应性作用。

要根据执行期间计算出的值进行输入，必须使用renderUI()在服务器端呈现输入：

ui.R

...
uiOutput('caratxui'),
...

server.R

...
output$caratxui <- renderUI({
        pickerInput(
            inputId = "caratx",
            label = "Choose carat",
            choices = c("Select all", unique(user_data()$carat)),
            multiple = TRUE
        )

    })
...

完整代码：

library(shiny)
library(shinyWidgets)
library(ggplot2)

ui <- fluidPage(
    titlePanel("test shiny"),

    # Sidebar with a slider input for number of bins
    sidebarLayout(sidebarPanel(
        fileInput('file1', 'Choose file to upload',
                  accept = c(
                      'text/csv',
                      'text/comma-separated-values',
                      'text/tab-separated-values',
                      'text/plain',
                      '.csv',
                      '.tsv'
                  )
        ),
        tags$hr(),
        uiOutput('caratxui'),
        selectInput(
            inputId = "clarityx",
            label = "Choose distance: ",
            choices = unique(user_data$clarity)
        )
    ),
    mainPanel(plotOutput("endplot"))
    ))

# Define server logic 
server <- function(input, output) {
    user_data <- reactive({
      read.csv(input$file1$datapath, header = T,
               sep = ",", quote = input$quote)
    })

    output$caratxui <- renderUI({
        pickerInput(
            inputId = "caratx",
            label = "Choose carat",
            choices = c("Select all", unique(user_data()$carat)),
            multiple = TRUE
        )

    })

    output$endplot <- renderPlot({
        validate(
            need(input$entityx, 'Please select at least one carat'),
            need(input$indicatorx, 'Please select at least one clarity')
        )

        user_data() %>%
            filter(carat %in% input$caratx) %>%
            filter(clarity %in% input$clarityx | 
                    input$caratx == "Select all") %>% 
            ggplot(aes(x = `cut`)) +
            geom_point(aes(y = price), color = "red") +
            geom_point(aes(y = depth), color = "blue")
        })
}

# Run the application 
shinyApp(ui = ui, server = server)

r-创建反应式过滤器，该过滤器应用于闪亮的上传的CSV文件

2 个答案: