使用操作按钮在闪亮的 R 中添加包含现有数据框的新行

我正在构建一个闪亮的表单，它将从 textInput 字段获取数据，并将这些输入与文本文件（将通过文件输入上传）组合起来，并在主面板中显示输出。有一个操作按钮用于第一次更新数据（从文本输入中获取数据并与处理后的文本文件合并），我添加了另一个操作按钮用于添加新数据（此添加新数据的目的是添加新数据）一组数据与现有数据作为行，新的数据组将通过文件输入上传）。下面给出了示例数据集，它是纯文本格式的文件。该样本数据集可以被视为第二个文本文件。 样本数据：

#         AREA     ADC-MEAN  ADC-STD DEV  ADC-MIN    ADC-MAX    ADC-MED  
 1      12.0000  0.000644667 1.96669e-005  0.000606000  0.000671000  0.000644000
 2      12.0000  0.000610250 1.43154e-005  0.000577000  0.000624000  0.000617000

我根据场景编写了shinnyApp。我可以通过合并和输出为表格来更新文本输入和文本文件输出。但无法将一组新数据添加为行。脚本如下：

library(shiny)
library(ggplot2)
library(xlsx)
library(xlsxjars)
library(rJava)
library(shinythemes)

# Define UI -----------
# ---------------------

ui <- fluidPage(theme = shinytheme("sandstone"),

                # header
                headerPanel("DTI post analysis conversion"),

                sidebarLayout(
                  # sidebar for form
                  sidebarPanel(
                    h3("Information",""),
                    textInput("ani_id", "Patient ID",""),
                    textInput("scan_id", "Scan ID",""),
                    textInput("Tech_id", "Tech Id",""),
                    textInput("Age_weeks", "Age weeks",""),

                    fileInput("textfile", "Upload the text file"),
                    actionButton("update", "Update"),
                    helpText("Click to insert the data "),
                    br(),
                    actionButton("addEntry", "Add New Data"),
                    helpText("Click to insert new data "),
                    br(),
                    downloadButton("downloadData", "Download"),
                    helpText("Click for download the data (.csv) ")
                  ),

                  # output for viewing
                  mainPanel(

                    DT::dataTableOutput("tableDT") 

                  )   
                )
)


# Define server logic ------
# --------------------------

server <- function(input, output) {

  # process the textinput
  Frontal_Cortex_table <- eventReactive(input$update,{  


    # creating table

    aniRoi2 <- data.frame(Animal_ID = rep(input$ani_id,2), 
                          Scan_ID = rep(input$scan_id,2), 
                          Tech_ID = rep(input$Tech_id,2), 
                          Age_weeks = rep(input$Age_weeks,2), 
                          stringsAsFactors = FALSE)

    return(aniRoi2)
  })

  # process the text file and download

  textdata <- eventReactive(input$update,{
    file1 <- input$textfile
    if(is.null(file1)){return()} 
    a <- read.table(file= file1$datapath, 
                    sep="\t",
                    fill=FALSE, 
                    strip.white=TRUE)[1:2,]

    # Split the text file and shape as column
    af <- as.character(a)
    af1 <- matrix(unlist(strsplit(af, split=" +")), ncol=7, byrow =TRUE)
    ad <- data.frame(af1[1:2,3:7])
    colnames(ad)<- c("ADC_MEAN", "ADC_STD", "ADC_MIN", "ADC_MAX", "ADC_MED")

    return(ad)
  })

  # merge two function as data.frame
  mytable2 <-reactive({

    dm = cbind.data.frame(Frontal_Cortex_table(), textdata())

  })

  # add new row (?)

  addData <- observeEvent(input$addEntry, {
    mytable2 <- isolate({
      newLine <- reactive({cbind.data.frame(Frontal_Cortex_table(), textdata())})
      rbind.data.frame(mytable2,newLine)
    })
  })

  # output the data as table    
  output$tableDT <- DT::renderDataTable(
    mytable2()
  )

  # download the file
  output$downloadData <- downloadHandler(
    filename = function() {
      paste("DTI", "csv", sep = ".")
    },
    content = function(file) {
      write.csv(mytable2(), file, row.names = FALSE)
    }
  )

}

# Run the app ----------
# ----------------------

shinyApp(ui = ui, server = server)

我收到错误消息指出：

Warning: Error in [[: object of type 'closure' is not subsettable Stack trace (innermost first):
    73: rbind.data.frame
    66: isolate
    65: observeEventHandler [/Users/rahatjahan/Dropbox/Database dev/DTIApp/Ask questions.R#95]
     1: runApp

我知道，这是一篇很长的文章，但请尝试解释并提供所有内容，以免造成任何混乱。

您的意见和建议将不胜感激。

问题解决了，每次迭代都会添加新行。 新的文本数据集：

#         AREA     ADC-MEAN  ADC-STD DEV  ADC-MIN    ADC-MAX    ADC-MED  
 1      12.0000  0.000644667 1.96669e-005  0.000606000  0.000671000  0.000644000
 2      12.0000  0.000610250 1.43154e-005  0.000577000  0.000624000  0.000617000
 3     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 4     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 5     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 6     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 7     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 8     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 9     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 10     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
#         AREA     FA-MEAN  FA-STD DEV     FA-MIN      FA-MAX        FA-MED  
 1      12.0000     0.233833    0.0171773     0.201000     0.262000     0.239000
 2      12.0000     0.247417    0.0135275     0.220000     0.270000     0.248000
 3     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 4     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 5     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 6     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 7     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 8     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 9     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
 10     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
ADC-MEAN
  0.000644667
  0.000610250
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
ADC-STD DEV
 1.96669e-005
 1.43154e-005
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
FA-MEAN
     0.233833
     0.247417
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
FA-STD DEV
    0.0171773
    0.0135275
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000
     0.000000

以及修改后的代码

library(shiny)
library(ggplot2)
library(xlsx)
library(xlsxjars)
library(rJava)
library(shinythemes)

# Define UI -----------
# ---------------------

ui <- fluidPage(theme = shinytheme("sandstone"),

                # header
                headerPanel("DTI post analysis conversion"),

                sidebarLayout(
                  # sidebar for form
                  sidebarPanel(
                    h3("Information",""),
                    textInput("ani_id", "Patient ID",""),
                    textInput("scan_id", "Scan ID",""),
                    textInput("Tech_id", "Tech Id",""),
                    textInput("Age_weeks", "Age weeks",""),

                    fileInput("textfile", "Upload the text file"),
                    actionButton("update", "Insert 1st Data Set"),
                    helpText("Click to insert the data "),
                    br(),
                    fileInput("anothertextfile", "Upload another Text file"),
                    actionButton("addEntry", "Add New Data"),
                    helpText("Click to insert new data "),
                    br(),
                    actionButton("combine", "Combine the data sets"),
                    downloadButton("downloadData", "Download"),
                    helpText("Click for download the data (.csv) ")
                  ),

                  # output for viewing
                  mainPanel(

                    DT::dataTableOutput("tableDT"),
                    DT::dataTableOutput("tableDT2") 


                  )   
                )
)


# Define server logic ------
# --------------------------

server <- function(input, output) {

  # process the textinput
  Frontal_Cortex_table <- reactive({  


    # creating table

    aniRoi2 <- data.frame(Animal_ID = rep(input$ani_id,2), 
                          Scan_ID = rep(input$scan_id,2), 
                          Tech_ID = rep(input$Tech_id,2), 
                          Age_weeks = rep(input$Age_weeks,2), 
                          stringsAsFactors = FALSE)

    return(aniRoi2)
  })

  # process the text file and download

  textdata <- reactive(
    {
    file1 <- input$textfile
    if(is.null(file1)){return()} 
    #read.table(file=file1$datapath, sep=input$sep, header = input$header, stringsAsFactors = input$stringAsFactors)
    a <- read.table(file= file1$datapath, 
                    sep="\t",
                    fill=FALSE, 
                    strip.white=TRUE)[1:20,]

    # Split the text file and shape as column
    af <- as.character(a)
    #class(af)
    #af
    #nrow(a)
    af1 <- matrix(unlist(strsplit(af, split=" +")), ncol=7, byrow =TRUE)
    # typeof(af1)
    # af1
    ad <- data.frame(af1[1:2,3:7], af1[11:12, 3:7])

    colnames(ad)<- c("ADC_MEAN", "ADC_STD", "ADC_MIN", "ADC_MAX", "ADC_MED", 
                     "FA_MEAN", "FA_STD", "FA_MIN", "FA_MAX", "FA_MED")


    return(ad)
  })


  # merge two function as data.frame
  mytable2 <-eventReactive(input$update,{

     dm <<- cbind.data.frame(Frontal_Cortex_table(), textdata())

  })

  # add new row (?)

  addData1 <- eventReactive(input$addEntry, {
      newLine <<- cbind.data.frame(Frontal_Cortex_table(), textdata())
  })


  addData <- eventReactive(input$addEntry, {
    dm <<- rbind.data.frame(mytable2(),addData1())
  })

  addData2 <- eventReactive(input$addEntry, {
    dm <<- rbind.data.frame(dm,addData1())
  })

  # output as data table      
  output$tableDT <- DT::renderDataTable(
    mytable2()
  )

# the combined data set with added row  
  output$tableDT2 <- DT::renderDataTable(
    addData2()
  )
  # download the file
  output$downloadData <- downloadHandler(
    filename = function() {
      paste("DTI", "csv", sep = ".")
    },
    content = function(file) {
      write.csv(mytable2(), file, row.names = FALSE)
    }
  )

}

# Run the app ----------
# ----------------------

shinyApp(ui = ui, server = server)

希望这会有所帮助。