下载按钮在 Shiny 上不起作用(writexl::write_xlsx 中的错误:)

Download button not working on Shiny (Error in writexl::write_xlsx:)

你能帮我调整下面代码的Download按钮吗?您会注意到,我正在通过 datatable 生成 table。我想下载这个生成的table,但是当我按下下载时,我看到控制台给出了以下错误:

Warning: Error in writexl::write_xlsx: Argument x must be a data frame or list of data frames[No stack trace available]

如何在我的代码中进行调整?

执行table 下面的代码:

library(shiny)
library(shinythemes)
library(dplyr)
library(tidyverse)
library(lubridate)
library(DT)
library(writexl)

function.test<-function(){
  
  df1 <- structure(
    list(date1= c("2021-06-28","2021-06-28","2021-06-28"),
         date2 = c("2021-07-01","2021-07-02","2021-07-03"),
         Category = c("ABC","ABC","ABC"),
         Week= c("Wednesday","Wednesday","Wednesday"),
         DR1 = c(4,1,0),
         DR01 = c(4,1,4), DR02= c(4,2,3),DR03= c(9,5,0),
         DR04 = c(5,4,0),DR05 = c(5,4,0),DR06 = c(5,4,0),DR07 = c(5,4,0),DR08 = c(5,4,0)),
    class = "data.frame", row.names = c(NA, -3L))
  
  
  
  return(df1)
}

f1 <- function(df1, dmda, CategoryChosse) {
  
  x<-df1 %>% select(starts_with("DR0"))
  
  x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
  PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
  
  med<-PV %>%
    group_by(Category,Week) %>%
    summarize(across(ends_with("PV"), median))
  
  SPV<-df1%>%
    inner_join(med, by = c('Category', 'Week')) %>%
    mutate(across(matches("^DR0\d+$"), ~.x + 
                    get(paste0(cur_column(), '_PV')),
                  .names = '{col}_{col}_PV')) %>%
    select(date1:Category, DR01_DR01_PV:last_col())
  
  SPV<-data.frame(SPV)
  
  mat1 <- df1 %>%
    filter(date2 == dmda, Category == CategoryChosse) %>%
    select(starts_with("DR0")) %>%
    pivot_longer(cols = everything()) %>%
    arrange(desc(row_number())) %>%
    mutate(cs = cumsum(value)) %>%
    filter(cs == 0) %>%
    pull(name)
  
  (dropnames <- paste0(mat1,"_",mat1, "_PV"))
  
  SPV <- SPV %>%
    filter(date2 == dmda, Category == CategoryChosse) %>%
    select(-any_of(dropnames))
  
  if(length(grep("DR0", names(SPV))) == 0) {
    SPV[head(mat1,10)] <- NA_real_
  }
  
  datas <-SPV %>%
    filter(date2 == ymd(dmda)) %>%
    group_by(Category) %>%
    summarize(across(starts_with("DR0"), sum)) %>%
    pivot_longer(cols= -Category, names_pattern = "DR0(.+)", values_to = "val") %>%
    mutate(name = readr::parse_number(name))
  colnames(datas)[-1]<-c("Days","Numbers")
  
  
  datas <- datas %>% 
    group_by(Category) %>% 
    slice((as.Date(dmda) - min(as.Date(df1$date1) [
      df1$Category == first(Category)])):max(Days)+1) %>%
    ungroup
  
  m<-df1 %>%
    group_by(Category,Week) %>%
    summarize(across(starts_with("DR1"), mean))
  
  m<-subset(m, Week == df1$Week[match(ymd(dmda), ymd(df1$date2))] & Category == CategoryChosse)$DR1
  
  maxrange <-  range(min(0, datas$Numbers, na.rm = TRUE), na.rm = TRUE)
  maxrange[2] <- maxrange[2] - (maxrange[2] %%10) + 35
  
  max<-max(0, datas$Days, na.rm = TRUE)+1
  
  plot(Numbers ~ Days,  xlim= c(0,max),  ylim= c(0,maxrange[2]),
       xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
  
  if (nrow(datas)<=2){
    abline(h=m,lwd=2) 
    points(0, m, col = "red", pch = 19, cex = 2, xpd = TRUE)
    text(.1,m+ .5, round(m,1), cex=1.1,pos=4,offset =1,col="black")
    return(as.numeric(m))
  }
  
  else if(any(table(datas$Numbers) >= 3) & length(unique(datas$Numbers)) == 1){
    yz <- unique(datas$Numbers)
    lines(c(0,datas$Days), c(yz, datas$Numbers), lwd = 2)
    points(0, yz, col = "red", pch = 19, cex = 2, xpd = TRUE)
    text(.1,yz+ .5,round(yz,1), cex=1.1,pos=4,offset =1,col="black")
    return(as.numeric(yz))
  }
  
  else{
    mod <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
    new.data <- data.frame(Days = with(datas, seq(min(Days),max(Days),len = 45)))
    new.data <- rbind(0, new.data)
    lines(new.data$Days,predict(mod,newdata = new.data),lwd=2)
    coef<-coef(mod)[2]
    points(0, coef, col="red",pch=19,cex = 2,xpd=TRUE)
    text(.99,coef + 1,max(0, round(coef,1)), cex=1.1,pos=4,offset =1,col="black")
    return(as.numeric(coef(model)[2]))
  }
  
}

ui <- fluidPage(
  ui <- shiny::navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
                          br(),
                          

                          tabPanel("PAGE 1",
                                   fluidPage(
                                     fluidRow(
                                       column(4,
                                              wellPanel(
                                                uiOutput('daterange'),
                                                downloadButton("dl", "Download"),
                                              )),
                                       column(8,
                                              tabsetPanel(
                                                tabPanel("Table", dataTableOutput('table')
                                                         
                                                ))
                                       ))))))


server <- function(input, output,session) {
  
  data <- reactive(function.test())
  
  output$daterange <- renderUI({
    tagList(dateRangeInput("daterange1", "Period you want to see:",
                           min   = min(data()$date2),
                           max   = max(data()$date2)),
                           
                           tags$script(HTML('
                setTimeout(function(){
                  $("#daterange1 input")[0].value = "No date selected";
                  $("#daterange1 input")[1].value = "No date selected";
                }, 50);
            ')))
  })
  
  data_subset <- reactive({
    req(input$daterange1)
    req(input$daterange1[1] <= input$daterange1[2])
    days <- seq(input$daterange1[1], input$daterange1[2], by = 'day')
    df1 <- subset(data(), as.Date(date2) %in% days)
    df2 <- df1 %>% select(date2,Category)
    All <- cbind(df2, coef = apply(df2, 1, function(x) {f1(data(),x[1],x[2])}))
    All<-tidyr::pivot_wider(All, names_from = Category, values_from = coef)
    All<-All %>% mutate(date2 = format(ymd(date2), "%d/%m/%Y"))%>%
      mutate(sum = rowSums(across(2:last_col()), na.rm = TRUE)) %>%
      mutate(across(everything(), ~ replace_na(as.character(.), '-')))
   
   All<-datatable(All, options = list(columnDefs = list(list(className = 'dt-center', targets = "_all")),
    paging =TRUE,searching = FALSE, pageLength =  10,dom = 'tip',scrollx=T),rownames = FALSE) %>%
      formatRound(c(2:3), digits=0)                         
    
   All
    
  })
  
  output$table <- renderDataTable({
    data_subset()
  })
  

  output$dl <- downloadHandler(
    filename = function() { "data.xlsx"},
    content = function(file) {
      showModal(modalDialog("Wait", footer=NULL))
      on.exit(removeModal())
      writexl::write_xlsx(data_subset(), path = file)
    }
  )
  

}

shinyApp(ui = ui, server = server)

Table生成:

做一个电抗导体data_subset,returns一个dataframe/tibble,然后在renderDataTable中应用datatable东西:

data_subset <- reactive({
  req(input$daterange1)
  req(input$daterange1[1] <= input$daterange1[2])
  days <- seq(input$daterange1[1], input$daterange1[2], by = 'day')
  df1 <- subset(data(), as.Date(date2) %in% days)
  df2 <- df1 %>% select(date2,Category)
  All <- cbind(df2, coef = apply(df2, 1, function(x) {f1(data(),x[1],x[2])}))
  All<-tidyr::pivot_wider(All, names_from = Category, values_from = coef)
  All %>% mutate(date2 = format(ymd(date2), "%d/%m/%Y"))%>%
    mutate(sum = rowSums(across(2:last_col()), na.rm = TRUE)) %>%
    mutate(across(everything(), ~ replace_na(as.character(.), '-')))
})

output$table <- renderDataTable({
  datatable(
    data_subset(), 
    options = list(
      columnDefs = list(
        list(className = 'dt-center', targets = "_all")
      ),
      paging = TRUE,
      searching = FALSE, 
      pageLength = 10,
      dom = 'tip', 
      scrollx=TRUE
    ),
    rownames = FALSE
  ) %>%
    formatRound(c(2:3), digits=0)
})