R 闪亮的传单不'；无法使用动态菜单正常工作_R_Dynamic_Shiny_Leaflet_Dynamic Data Display

R 闪亮的传单不'；无法使用动态菜单正常工作

r dynamic shiny leaflet

R 闪亮的传单不'；无法使用动态菜单正常工作,r,dynamic,shiny,leaflet,dynamic-data-display,R,Dynamic,Shiny,Leaflet,Dynamic Data Display,我为这个问题挣扎了一段时间，但没有成功。我想建立一个闪亮的互动应用程序表和地图。它结合了不同的数据集。其思想是能够选择所需的数据集，过滤该数据集中的数据，并将其渲染到地图上我设法建立了一个交互式菜单和反应过滤功能，但我有问题的传单地图。当我在一些数据集之间切换时，它会崩溃。我只能在localisations macro或localisations micro之间切换，但在micro和macro之间切换时它不起作用（见下图）问题与错误有关：警告：总和错误：参数的“类型”（列表）无效，但我现

我为这个问题挣扎了一段时间，但没有成功。我想建立一个闪亮的互动应用程序表和地图。它结合了不同的数据集。其思想是能够选择所需的数据集，过滤该数据集中的数据，并将其渲染到地图上

我设法建立了一个交互式菜单和反应过滤功能，但我有问题的传单地图。当我在一些数据集之间切换时，它会崩溃。我只能在localisations macro或localisations micro之间切换，但在micro和macro之间切换时它不起作用（见下图）

问题与错误有关：

警告：总和错误：参数的“类型”（列表）无效

，但我现在知道如何修复它

我还在

observerEvent

if（inpud$data.type==“本地化”）{}。。。。。
else if（输入$data.type==“Micro”）{}。。。。。
else{}

但也不起作用

以下是该应用程序的示例：

library(shiny)
library(leaflet)
library(dplyr)


#### UI
ui <- fluidPage(

  titlePanel("Map"),

  leafletOutput("map"),

  fluidRow(
    column(2, offset = 0, style='padding:10px;',
           radioButtons("data.type", "Type of  data", c("Localisations", "Micro", "Macro"))),
    column(2, offset = 0, style='padding:10px;',
           uiOutput("position")),
    column(2, offset = 0, style='padding:10px;',
           uiOutput("kind"))
  ),

  dataTableOutput("table") ## to check the filtering

)


server <- function(input, output, session) {

  ##### data #####


  sites <- data.frame(Site=c("Site1", "Site2"),
                      Lat=c(54, 56), 
                      Long=c(16, 18)) 


  micro <- data.frame(Site=c(rep("Site1",4), rep("Site2", 4)),
                      Position=c("Micro_pos1","Micro_pos1", "Micro_pos2", "Micro_pos2"),
                      Kind=rep(c("blue_fiber", "red_fiber"), 4),
                      Amount=c(5, 46, 64, 32, 54, 38, 29, 31) )  

  micro <- full_join(micro, sites)

  macro <- data.frame(Site=c(rep("Site1",4), rep("Site2", 4)),
                      Position=c("Macro_pos1","Macro_pos1", "Macro_pos2", "Macro_pos2"),
                      Kind=rep(c("Cigarretes", "Pellets"), 4),
                      Amount=c(3, 16, 4, 12, 14, 18, 19, 21) )  

  macro <- full_join(macro, sites)    


  #### dynamic menu ####

  ### position
  output$position <- renderUI({


    switch(input$data.type,
           "Micro"=radioButtons("position", "Micro position:", 
                                                       choices = c("Micro_pos1", "Micro_pos2")),
           "Macro"=radioButtons("position", "Macro position:", 
                                               choices = c("Macro_pos1", "Macro_pos2"))
    )
  })

  ## kind

  output$kind <- renderUI({


    switch(input$data.type,
           "Micro"=checkboxGroupInput("kind", "kind of micro:", 
                                                             choices = c("blue_fiber", "red_fiber"),
                                                             selected = c("blue_fiber", "red_fiber")),
           "Macro"=checkboxGroupInput("kind", "kind of macro:", 
                                                     choices = c("Cigarretes", "Pellets"),
                                                     selected=c("Cigarretes", "Pellets"))
    )
  })


#### reactive table to filter data to map ####

table <- reactive({


    if(input$data.type=="Localisations"){

      return(sites)
    }  

    else if (input$data.type=="Micro") {

      if (is.null(input$position))
        return(NULL)
      if (!is.null(input$position))

        micro <-micro[micro$Position==input$position,]
      micro<-micro[micro$Kind %in% input$kind,]

      micro <- micro %>% 
        group_by(Site, Lat, Long, Position)%>%
        summarise(Amount=sum(Amount))
      micro
      }

  else if (input$data.type=="Macro") {

    if (is.null(input$position))
      return(NULL)
    if (!is.null(input$position))

      macro <-macro[macro$Position==input$position,]
    macro<-macro[macro$Kind %in% input$kind,]

     macro <- macro %>%
      group_by(Site, Lat, Long, Position)%>%
      summarise(Amount=sum(Amount))
    macro
    }
  })


#### table with filtered data ####
output$table <- renderDataTable({
  table()
})



#### base map ####


  output$map <- renderLeaflet({
    leaflet(sites) %>%
      setView(lat=55, lng=17, zoom=6) %>%
      addProviderTiles(providers$Esri.WorldImagery) %>%
      addCircleMarkers(lng=~Long, lat=~Lat, label=~Site, 
                       labelOptions = labelOptions(noHide =T))
  })




  ##### and now it gets complicated :( ####

   observeEvent( c( input$data.type, input$position, input$kind), {

    if(input$data.type=="Localisations"){

      leafletProxy("map", data=sites) %>%
        clearMarkers() %>%
        clearShapes()%>%
        addCircleMarkers(lng=~Long, lat=~Lat, label=~Site,
                         labelOptions = labelOptions(noHide =T), fillColor = "red")
    }


     else {

        if (is.null(input$position))
           return(NULL)
        if (is.null(input$kind))
          return(NULL)


        leafletProxy("map", data=table()) %>%
        clearMarkers() %>%
        clearShapes()%>%

        addCircles(lng=~Long, lat=~Lat, label=~Site, color="white", fill="white",
                   labelOptions = labelOptions(noHide =T),
                   radius = ~Amount*1000) %>%
        addLabelOnlyMarkers(lng=~Long, lat=~Lat, label=~as.character(Amount),
                            labelOptions = labelOptions(noHide = T, direction = 'top', textOnly = T, textsize="20px"))

     }



  })

  ### server end
}

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

库（闪亮）
图书馆（单张）
图书馆（dplyr）
####用户界面
ui问题在于时间：

从micro切换到macro时，input$kind仍设置为仅适用于micro的值
然后调用table（）来创建映射。它过滤宏[macro$Kind%在%input$Kind，]

中，这将导致一个空集，因为input$Kind包含的仍然是红色和蓝色的纤维，而不是“Cigarretes”和“小球”

您可以使用更新选择框

output$kind <- renderUI({


switch(input$data.type,
       "Micro"=checkboxGroupInput("kind", "kind of micro:", 
                                  choices = c("blue_fiber", "red_fiber"),
                                  selected = c("blue_fiber", "red_fiber")),
       "Macro"=checkboxGroupInput("kind", "kind of macro:", 
                                  choices = c("Cigarretes", "Pellets"),
                                  selected=c("Cigarretes", "Pellets"))
)
})

然后更改表格功能：

  table <- function(){


    if(input$data.type=="Localisations"){

      return(sites)
    }  

    else if (input$data.type=="Micro") {

      if (is.null(input$position))
        return(NULL)
      if (!is.null(input$position))

        micro <-micro[micro$Position==input$position,]
      micro<-micro[micro$Kind %in% input$kind,]

      micro <- micro %>% 
        group_by(Site, Lat, Long, Position)%>%
        summarise(Amount=sum(Amount))
      micro
    }

    else if (input$data.type=="Macro") {

      if (is.null(input$position))
        return(NULL)
      if (!is.null(input$position))

        macro <-macro[macro$Position==input$position,]
      macro<-macro[macro$Kind %in% input$kind,]

      macro <- macro %>%
        group_by(Site, Lat, Long, Position)%>%
        summarise(Amount=sum(Amount))
      macro
    }
  }

要使数据表具有反应性，可以执行以下操作：

  output$table <- renderDataTable({
    input$button
    table()
  })

output$table非常感谢@ge.org的努力，但是带有summit按钮的解决方案不适合我的应用程序，因为在真实应用程序中，我有更多的类别，用户每次更改summit都会很尴尬。但是多亏了你关于时间安排的评论，我通过编辑observeEvent
绕过了这个问题。对于每个数据类型，我将其分为三个单独的条件。在负责微观和宏观的条件中，我添加了新条件，以省略input$kind
中的错误类别。这会在控制台中发出一些警告，但似乎不会影响整个应用程序
以下是新代码：
library(shiny)
library(leaflet)
library(dplyr)



#### UI
ui <- fluidPage(

  titlePanel("Map"),

  leafletOutput("map"),

  fluidRow(
    column(2, offset = 0, style='padding:10px;',
           radioButtons("data.type", "Type of  data", c("Localisations", "Micro", "Macro"))),
    column(2, offset = 0, style='padding:10px;',
           uiOutput("position")),
    column(2, offset = 0, style='padding:10px;',
           uiOutput("kind"))
  ),

  dataTableOutput("table"), ## to check the filtering
  textOutput("kind.of")
)


server <- function(input, output, session) {

  ##### data #####


  sites <- data.frame(Site=c("Site1", "Site2"),
                      Lat=c(54, 56), 
                      Long=c(16, 18)) 


  micro <- data.frame(Site=c(rep("Site1",4), rep("Site2", 4)),
                      Position=c("Micro_pos1","Micro_pos1", "Micro_pos2", "Micro_pos2"),
                      Kind=rep(c("blue_fiber", "red_fiber"), 4),
                      Amount=c(5, 46, 64, 32, 54, 38, 29, 31) )  

  micro <- full_join(micro, sites)

  macro <- data.frame(Site=c(rep("Site1",4), rep("Site2", 4)),
                      Position=c("Macro_pos1","Macro_pos1", "Macro_pos2", "Macro_pos2"),
                      Kind=rep(c("Cigarretes", "Pellets"), 4),
                      Amount=c(3, 16, 4, 12, 14, 18, 19, 21) )  

  macro <- full_join(macro, sites)    


  #### dynamic menu ####

  ### position
  output$position <- renderUI({


    switch(input$data.type,
           "Micro"=radioButtons("position", "Micro position:", 
                                                       choices = c("Micro_pos1", "Micro_pos2")),
           "Macro"=radioButtons("position", "Macro position:", 
                                               choices = c("Macro_pos1", "Macro_pos2"))
    )
  })

  ## kind

  output$kind <- renderUI({


    switch(input$data.type,
           "Micro"=checkboxGroupInput("kind", "kind of micro:", 
                                                             choices = c("blue_fiber", "red_fiber"),
                                                             selected = c("blue_fiber", "red_fiber")),
           "Macro"=checkboxGroupInput("kind", "kind of macro:", 
                                                     choices = c("Cigarretes", "Pellets"),
                                                     selected=c("Cigarretes", "Pellets"))
    )
  })


#### reactive table to filter data to map ####

table <- reactive({


    if(input$data.type=="Localisations"){

      return(sites)
    }  

    else if (input$data.type=="Micro") {

      if (is.null(input$position))
        return(NULL)
      if (!is.null(input$position))

        micro <-micro[micro$Position==input$position,]
      micro<-micro[micro$Kind %in% input$kind,]

      micro <- micro %>% 
        group_by(Site, Lat, Long, Position)%>%
        summarise(Amount=sum(Amount))
      micro
      }

  else if (input$data.type=="Macro") {

    if (is.null(input$position))
      return(NULL)
    if (!is.null(input$position))

      macro <-macro[macro$Position==input$position,]
    macro<-macro[macro$Kind %in% input$kind,]

     macro <- macro %>%
      group_by(Site, Lat, Long, Position)%>%
      summarise(Amount=sum(Amount))
    macro
    }
  })


#### table with filtered data ####
output$table <- renderDataTable({
  table()
})


#### base map ####


  output$map <- renderLeaflet({
    leaflet(sites) %>%
      setView(lat=55, lng=17, zoom=6) %>%
      addProviderTiles(providers$Esri.WorldImagery) %>%
      addCircleMarkers(lng=~Long, lat=~Lat, label=~Site, 
                       labelOptions = labelOptions(noHide =T))
  })


  #### updating the map #####

   observeEvent( c( input$data.type, input$position, input$kind), {



  if(input$data.type=="Localisations"){

      leafletProxy("map", data=sites) %>%
        clearMarkers() %>%
        clearShapes()%>%
        addCircleMarkers(lng=~Long, lat=~Lat, label=~Site,
                         labelOptions = labelOptions(noHide =T), fillColor = "red")
    }


     else if (input$data.type=="Micro") {

        if (is.null(input$position))
           return(NULL)
         if (is.null(input$kind))
          return(NULL)

###########################################################
  ####### and here 4 new line that did all the job #########
       if (input$position %in% c("Macro_pos1", "Macro_pos2")) 
         return(NULL) ## new line
       if (input$kind %in% c("Cigarretes", "Pellets"))
         return(NULL)
  #################################################### 



        leafletProxy("map", data=table()) %>%
        clearMarkers() %>%
        clearShapes()%>%

        addCircles(lng=~Long, lat=~Lat, label=~Site, color="white", fill="white",
                   labelOptions = labelOptions(noHide =T),
                   radius = ~Amount*1000) %>%
        addLabelOnlyMarkers(lng=~Long, lat=~Lat, label=~as.character(Amount),
                            labelOptions = labelOptions(noHide = T, direction = 'top', textOnly = T, textsize="20px"))

           }

     else if(input$data.type=="Macro") {

       if (is.null(input$position))
         return(NULL)
       if (is.null(input$kind))
         return(NULL)

###########################################################
  ####### and here 4 new line that did all the job #########
       if (input$position %in% c("Micro_pos1", "Micro_pos2"))
         return(NULL)
       if (input$kind %in% c("blue_fiber", "red_fiber"))
         return(NULL)
  ##############################################

       leafletProxy("map", data=table()) %>%
         clearMarkers() %>%
         clearShapes()%>%

         addCircles(lng=~Long, lat=~Lat, label=~Site, color="white", fill="white",
                    labelOptions = labelOptions(noHide =T),
                    radius = ~Amount*1000) %>%
         addLabelOnlyMarkers(lng=~Long, lat=~Lat, label=~as.character(Amount),
                             labelOptions = labelOptions(noHide = T, direction = 'top', textOnly = T, textsize="20px"))

     }

      })

  ### server end
}

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

库（闪亮）
图书馆（单张）
图书馆（dplyr）
####用户界面
ui%
addLabelOnlyMarkers（lng=~Long，lat=~lat，label=~as.character（Amount），
labelOptions=labelOptions（noHide=T，direction='top'，textOnly=T，textsize=“20px”））
}
})
###服务器端
}
#运行应用程序
shinyApp（用户界面=用户界面，服务器=服务器）

  output$table <- renderDataTable({
    input$button
    table()
  })

library(shiny)
library(leaflet)
library(dplyr)



#### UI
ui <- fluidPage(

  titlePanel("Map"),

  leafletOutput("map"),

  fluidRow(
    column(2, offset = 0, style='padding:10px;',
           radioButtons("data.type", "Type of  data", c("Localisations", "Micro", "Macro"))),
    column(2, offset = 0, style='padding:10px;',
           uiOutput("position")),
    column(2, offset = 0, style='padding:10px;',
           uiOutput("kind"))
  ),

  dataTableOutput("table"), ## to check the filtering
  textOutput("kind.of")
)


server <- function(input, output, session) {

  ##### data #####


  sites <- data.frame(Site=c("Site1", "Site2"),
                      Lat=c(54, 56), 
                      Long=c(16, 18)) 


  micro <- data.frame(Site=c(rep("Site1",4), rep("Site2", 4)),
                      Position=c("Micro_pos1","Micro_pos1", "Micro_pos2", "Micro_pos2"),
                      Kind=rep(c("blue_fiber", "red_fiber"), 4),
                      Amount=c(5, 46, 64, 32, 54, 38, 29, 31) )  

  micro <- full_join(micro, sites)

  macro <- data.frame(Site=c(rep("Site1",4), rep("Site2", 4)),
                      Position=c("Macro_pos1","Macro_pos1", "Macro_pos2", "Macro_pos2"),
                      Kind=rep(c("Cigarretes", "Pellets"), 4),
                      Amount=c(3, 16, 4, 12, 14, 18, 19, 21) )  

  macro <- full_join(macro, sites)    


  #### dynamic menu ####

  ### position
  output$position <- renderUI({


    switch(input$data.type,
           "Micro"=radioButtons("position", "Micro position:", 
                                                       choices = c("Micro_pos1", "Micro_pos2")),
           "Macro"=radioButtons("position", "Macro position:", 
                                               choices = c("Macro_pos1", "Macro_pos2"))
    )
  })

  ## kind

  output$kind <- renderUI({


    switch(input$data.type,
           "Micro"=checkboxGroupInput("kind", "kind of micro:", 
                                                             choices = c("blue_fiber", "red_fiber"),
                                                             selected = c("blue_fiber", "red_fiber")),
           "Macro"=checkboxGroupInput("kind", "kind of macro:", 
                                                     choices = c("Cigarretes", "Pellets"),
                                                     selected=c("Cigarretes", "Pellets"))
    )
  })


#### reactive table to filter data to map ####

table <- reactive({


    if(input$data.type=="Localisations"){

      return(sites)
    }  

    else if (input$data.type=="Micro") {

      if (is.null(input$position))
        return(NULL)
      if (!is.null(input$position))

        micro <-micro[micro$Position==input$position,]
      micro<-micro[micro$Kind %in% input$kind,]

      micro <- micro %>% 
        group_by(Site, Lat, Long, Position)%>%
        summarise(Amount=sum(Amount))
      micro
      }

  else if (input$data.type=="Macro") {

    if (is.null(input$position))
      return(NULL)
    if (!is.null(input$position))

      macro <-macro[macro$Position==input$position,]
    macro<-macro[macro$Kind %in% input$kind,]

     macro <- macro %>%
      group_by(Site, Lat, Long, Position)%>%
      summarise(Amount=sum(Amount))
    macro
    }
  })


#### table with filtered data ####
output$table <- renderDataTable({
  table()
})


#### base map ####


  output$map <- renderLeaflet({
    leaflet(sites) %>%
      setView(lat=55, lng=17, zoom=6) %>%
      addProviderTiles(providers$Esri.WorldImagery) %>%
      addCircleMarkers(lng=~Long, lat=~Lat, label=~Site, 
                       labelOptions = labelOptions(noHide =T))
  })


  #### updating the map #####

   observeEvent( c( input$data.type, input$position, input$kind), {



  if(input$data.type=="Localisations"){

      leafletProxy("map", data=sites) %>%
        clearMarkers() %>%
        clearShapes()%>%
        addCircleMarkers(lng=~Long, lat=~Lat, label=~Site,
                         labelOptions = labelOptions(noHide =T), fillColor = "red")
    }


     else if (input$data.type=="Micro") {

        if (is.null(input$position))
           return(NULL)
         if (is.null(input$kind))
          return(NULL)

###########################################################
  ####### and here 4 new line that did all the job #########
       if (input$position %in% c("Macro_pos1", "Macro_pos2")) 
         return(NULL) ## new line
       if (input$kind %in% c("Cigarretes", "Pellets"))
         return(NULL)
  #################################################### 



        leafletProxy("map", data=table()) %>%
        clearMarkers() %>%
        clearShapes()%>%

        addCircles(lng=~Long, lat=~Lat, label=~Site, color="white", fill="white",
                   labelOptions = labelOptions(noHide =T),
                   radius = ~Amount*1000) %>%
        addLabelOnlyMarkers(lng=~Long, lat=~Lat, label=~as.character(Amount),
                            labelOptions = labelOptions(noHide = T, direction = 'top', textOnly = T, textsize="20px"))

           }

     else if(input$data.type=="Macro") {

       if (is.null(input$position))
         return(NULL)
       if (is.null(input$kind))
         return(NULL)

###########################################################
  ####### and here 4 new line that did all the job #########
       if (input$position %in% c("Micro_pos1", "Micro_pos2"))
         return(NULL)
       if (input$kind %in% c("blue_fiber", "red_fiber"))
         return(NULL)
  ##############################################

       leafletProxy("map", data=table()) %>%
         clearMarkers() %>%
         clearShapes()%>%

         addCircles(lng=~Long, lat=~Lat, label=~Site, color="white", fill="white",
                    labelOptions = labelOptions(noHide =T),
                    radius = ~Amount*1000) %>%
         addLabelOnlyMarkers(lng=~Long, lat=~Lat, label=~as.character(Amount),
                             labelOptions = labelOptions(noHide = T, direction = 'top', textOnly = T, textsize="20px"))

     }

      })

  ### server end
}

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