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我正在尝试自动编辑 csv。我希望 Shiny 应用程序的用户能够选择他们想要在 csv 中清理的选项。为了澄清，我希望他们能够单击一个按钮，然后更新 csv，然后单击另一个按钮并再次更新，同时保持原始更新。目前，我正在查看只有两个按钮的情况，首先我会单击“加载”按钮来加载并查看 csv；然后我想单击“已清除电子邮件”按钮以附加一列已清除电子邮件的新列。最终，我想添加更多按钮。

我的代码当前因错误而崩溃：

.getReactiveEnvironment()$currentContext() 中的错误：如果没有活动的反应上下文，则不允许操作。（你试图做一些只能从反应式表达式或观察者内部完成的事情。）

我的代码如下：

用户界面

    ui = fluidPage(
       sidebarPanel(
           fileInput('file1', 'Choose file to upload',accept = c('text/csv','text/comma-separated-values','text/tab-separated-values','text/plain','.csv','.tsv')),
           checkboxInput('header', 'Header', TRUE),
           radioButtons('sep', 'Separator',c(Comma=',',Semicolon=';',Tab='\t'),'Comma'),
           radioButtons('quote', 'Quote',c(None='','Double Quote'='"','Single Quote'="'"),'Double Quote'),
           actionButton("Load", "Load File"),
           actionButton("Email", "Clean Email")),
           mainPanel(tableOutput("my_output_data"))
       )

服务器

           server = function(input, output) {

             ###Load CSV File
             data1 <- reactive({
               if(input$Load == 0){return()}
               inFile <- input$file1
               if (is.null(inFile)){return(NULL)}

               isolate({ 
                 input$Load
                 my_data <- read.csv(inFile$datapath, header = input$header,sep = input$sep, quote = input$quote,stringsAsFactors =FALSE)
               })
               my_data
             })
               output$my_output_data <- renderTable({data1()},include.rownames=FALSE) 

             data2 <- reactive({
               if(input$Email == 0){return()}
               inFile <- input$file1
               if (is.null(inFile)){return(NULL)}

               isolate({ 
                 input$Email
                 my_data <- read.csv(inFile$datapath, header = input$header,sep = input$sep, quote = input$quote,stringsAsFactors =FALSE)

                 ###CLEAN EMAIL BUTTON FORMULA
                 email_clean <- function(email, invalid = NA)
                 {
                   email <- trimws(email) 
                   email[(nchar(email) %in% c(1,2)) ] <- invalid
                   email[!grepl("@", email)] <- invalid
                   bad_email <- c("\\@no.com", "\\@na.com","\\@none.com","\\@email.com",
                   "\\@noemail.com", "\\@directcapital.com", "\\@test.com", 
                   "noemail")
                   pattern = paste0("(?i)\\b",paste0(bad_email,collapse="\\b|\\b"),"\\b")
                   email <-gsub(pattern, invalid, sapply(email,as.character))
                   unname(email)
                 }
                 Cleaned_Email <- email_clean(my_data$Email)
                 my_data<-cbind(my_data,Cleaned_Email)
               })
               my_data},

               {
               if(input$Load == 0){return()}
               inFile <- input$file1
               if (is.null(inFile)){return(NULL)}

               isolate({ 
                 input$Load
                 my_data <- read.csv(inFile$datapath, header = input$header,sep = input$sep, quote = input$quote,stringsAsFactors =FALSE)
               })
               my_data}
             )
             output$my_output_data <- renderTable({data2()},include.rownames=FALSE)  

           }



     shinyApp(ui = ui, server = server)

谢谢！

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