Shiny 在用于开发闪亮应用程序（闪亮、传单、R studio）的数据集中不处理任何数据。错误：下标超出范围

当我在Shining应用程序中使用的数据集没有数据时，会出现一个错误：下标超出边界-应用程序保持空白，没有我的地图。我希望，即使在发生错误时，地图也会显示，但带有任何标记。我该怎么做

您好，我正在使用R Shining和传单开发一个应用程序，该应用程序提供一个带有标记的地图，每次我单击一个标记时，都会出现一个包含该特定标记信息的表格。此外，我还通过if/else语句开发了一个侧栏，以便搜索我想要的信息。通过解释，我可以搜索有关特定年份、该年份的某个期间、特定情况以及该情况的状态的信息。 一切运行正常，但唯一的问题是处理数据集中丢失的信息（我没有一年中特定时期的数据）。当我没有数据时，会出现“下标超出范围”错误。我希望除此之外，地图显示，但没有标记。所以，只有简单的地图。我已经开发了if和else语句，但它们并不成功。即使出现闪亮的错误，我如何保留地图？
是否需要在服务器中更改某些内容？还是用户界面

服务器代码：

pal <- colorFactor(c("lawngreen", "red", "darkgray", "yellow", "orange"), 
                   domain = c("Confirmed negative", "Confirmed positive", "Don't know", "Likely negative", "Likely positive"))

shinyServer(function(input, output) {
    data_for_map <- reactive({
    if (input$disease_choice != "All") {
      if (input$disease_quarter != "All") {
        if (input$disease_status != "All") {
          data_to_plot <- pig_data_long %>%
            filter(disease == input$disease_choice, status == input$disease_status,
                   quarter == input$disease_quarter, year == input$disease_year)
        } else {
          data_to_plot <- pig_data_long %>%
            filter(disease == input$disease_choice, quarter == input$disease_quarter, year == input$disease_year)
        }
      } else { 
        if (input$disease_status != "All") {
          data_to_plot <- pig_data_long %>%
            filter(disease == input$disease_choice, status == input$disease_status, year == input$disease_year)
        } else {
          data_to_plot <- pig_data_long %>%
            filter(disease == input$disease_choice, year == input$disease_year)
        }
      }
      } else {
        if (input$disease_quarter != "All") {
          if (input$disease_status != "All") {
            data_to_plot <- pig_data_long %>%
                filter(status == input$disease_status, quarter == input$disease_quarter, year == input$disease_year)
            } else {
              data_to_plot <- pig_data_long %>%
                filter(quarter == input$disease_quarter, year == input$disease_year)
            }
          } else {
            if (input$disease_status != "All") {
              data_to_plot <- pig_data_long %>%
                filter(status == input$disease_status, year == input$disease_year)
            } else {
              data_to_plot <- pig_data_long %>%
                filter(year == input$disease_year)
            }
          }
      }

output$map <- renderLeaflet({
    leaflet("map") %>%
      setView(lng = -3.64, lat = 57.36, zoom = 7) %>%
      addTiles() %>%
      addCircleMarkers(data = data_for_map()[[2]],
                       radius = 4,
                       color = "black",
                       stroke = FALSE,
                       fillOpacity = 1,
                       popup = ~(slapmark)) %>%
      addCircleMarkers(data = data_for_map()[[1]], 
                       color = ~pal(status),
                       stroke = FALSE,
                       fillOpacity = 1,
                       popup = ~(paste(quarter, disease, status, sep = ": ")),
                       layerId = ~(paste(slapmark, disease, status, sep = "-"))) %>%
      addLegend("bottomright",
                colors = c("lawngreen", "yellow", "orange", "red", "darkgray"), 
                labels = c("Confirmed negative", "Likely negative", "Likely positive", "Confirmed positive", "Don't know"),
                title = "Legend",
                labFormat = labelFormat(),
                opacity = 1) 

  })

 output$clicked = DT::renderDataTable({
    point = input$map_marker_click
    if (!is.null(point)) {
      point_slapmark = strsplit(point$id, "-") [[1]][1]
      data_for_map()[[1]] %>%
        filter(slapmark == point_slapmark) %>%
        select(-latitude, -longitude) %>%
        DT::datatable(data_for_map, options = list(dom = 'ltipr'),
                      class = "display", callback = JS("return table;"),
                      style = "default")
    }
  }) 
 })

pal%
addCircleMarkers（data=data\u for_map（）[[2]]，
半径=4，
color=“黑色”，
笔划=假，
fillOpacity=1，
弹出=~（slapmark））%>%
addCircleMarkers（data=data\u for_map（）[[1]]，
颜色=~pal（状态），
笔划=假，
fillOpacity=1，
弹出=~（粘贴（季度、疾病、状态、sep=“：”）），
layerId=~（粘贴（slapmark、疾病、状态、sep=“-”））%%>%
addLegend（“右下角”，
颜色=c（“绿色”、“黄色”、“橙色”、“红色”、“黑色”），
标签=c（“确认阴性”、“可能阴性”、“可能阳性”、“确认阳性”、“不知道”），
title=“图例”，
labFormat=labelFormat（），
不透明度=1）
})
输出$clicked=DT:：renderDataTable({
点=输入$map\u标记\u单击
如果（！为.null（点））{
点_slapmark=strsplit（点$id，“-”[[1]][1]
_map（）[[1]]%>%
过滤器（slapmark==点\u slapmark）%>%
选择（-纬度，-经度）%%>%
DT:：datatable（地图的数据，选项=列表（dom='ltipr'），
class=“display”，callback=JS（“返回表；”），
style=“default”）
}
}) 
})

您可以尝试创建一个简单的map对象，只需如下设置视图即可

output$map <- renderLeaflet({ 
  leaflet() %>%
  setView(lng = -3.64, lat = 57.36, zoom = 7)
})

---

嗨，谢谢你的帮助！它不起作用。。。我不知道我是否真的需要使用代理。。我想对你说。。出现错误并显示“下标超出范围”时，运行基本映射

leafletProxy("map")  %>%
   addTiles() %>%
   addCircleMarkers(data = data_for_map()[[2]],
                   radius = 4,
                   color = "black",
                   stroke = FALSE,
                   fillOpacity = 1,
                   popup = ~(slapmark)) %>%
  addCircleMarkers(data = data_for_map()[[1]], 
                   color = ~pal(status),
                   stroke = FALSE,
                   fillOpacity = 1,
                   popup = ~(paste(quarter, disease, status, sep = ": ")),
                   layerId = ~(paste(slapmark, disease, status, sep = "-"))) %>%
  addLegend("bottomright",
            colors = c("lawngreen", "yellow", "orange", "red", "darkgray"), 
            labels = c("Confirmed negative", "Likely negative", "Likely positive", "Confirmed positive", "Don't know"),
            title = "Legend",
            labFormat = labelFormat(),
            opacity = 1)