r - 发布闪亮应用程序时出现问题 - renderWidget(instance) 中的警告：忽略附加内容；appendContent 不能在 Shiny 渲染调用中使用

Question

尝试发布 Shiny 应用程序时出现以下错误。这是我的第一个应用程序。我在网上搜索了无法弄清楚问题所在。下面的错误消息来自我尝试在线发布时。该应用程序的整个代码位于错误消息下方。在笔记本电脑上，该应用程序可以运行，但我无法在 shinyapps.io 网站上在线部署。请帮忙！

Failed to create bus connection: No such file or directory
Warning in system("timedatectl", intern = TRUE) :
  running command 'timedatectl' had status 1
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
✔ ggplot2 3.3.3     ✔ purrr   0.3.4
✔ tibble  3.1.0     ✔ dplyr   1.0.5
✔ tidyr   1.1.3     ✔ stringr 1.4.0
✔ readr   1.4.0     ✔ forcats 0.5.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

Attaching package: ‘DT’

The following objects are masked from ‘package:shiny’:

    dataTableOutput, renderDataTable

Linking to GEOS 3.5.1, GDAL 2.2.2, PROJ 4.9.2
Error in value[[3L]](cond) : invalid string in PangoCairo_Text
Calls: local ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
Execution halted

这是以下应用程序的代码：

#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#

library(shiny)
library(tidyverse)
library(leaflet)
library(DT)
library(tmap)
library(sf)

#Load all the data you want to visualize
#Import data and clean it
windturbine <- read.csv("windturbine.csv")
windturbine_df<- windturbine[!is.na(windturbine$latitude), ]
windturbine_df<- windturbine[!is.na(windturbine$longitude), ]

windturbine_sf<-
    st_as_sf(windturbine, coords = c("longitude","latitude"), 
             crs = "+proj=longlat +datum=WGS84 +no_defs") %>% 
    st_transform(crs = "+proj=lcc +lon_0=-90 +lat_1=33 +lat_2=45")

#Subset data you want in table
wind_data<-windturbine_df %>%
    select(province_territory,project_name,total_project_capacity_mw,turbine_identifier,turbine_number_in_project,turbine_rated_capacity_k_w,rotor_diameter_m,hub_height_m,manufacturer,model,commissioning_date)
turbinesperprovince <-windturbine %>%
    group_by(factor(province_territory))%>%
    count()
names(turbinesperprovince)<-c("province_territory","total_turbines")

#Total wind turbines per province
provinceplot=windturbine %>% 
    count(province_territory) %>% 
    ggplot(aes(forcats::fct_reorder(province_territory, n), n)) +
    geom_bar(stat="identity", fill="steelblue") +
    ggtitle("Number of Turbines for Each Province") +
    coord_flip() +
    theme_minimal() +
    ylab('Number of Turbines') +
    xlab('Province')

#Save the plot
ggsave("provinceplot.png",width = 297,height = 210,units = c("mm"),dpi = 300)

#Total wind turbines per project 
projectplot=windturbine %>% 
    count(project_name) %>% 
    filter(n > 50)%>% 
    ggplot(aes(forcats::fct_reorder(project_name, n),n)) +
    geom_bar(stat="identity", fill="steelblue") +
    ggtitle("Number of Turbines for Each Project")+
    coord_flip() +
    theme_minimal() +
    ylab('Number of Turbines') +
    xlab('Project')

#Save the plot
ggsave("projectplot.png",width = 297,height = 210,units = c("mm"),dpi = 300)

projects <- windturbine %>% 
    group_by(project_name) %>% 
    summarize(capacity = mean(total_project_capacity_mw),
              rotor_diameter = median(rotor_diameter_m),
              hub_height = median(hub_height_m),
              province_territory = province_territory,
              commissioning_date = commissioning_date,
              manufacturer = manufacturer) %>% 
              unique()

provincelist <- list(  "Alberta"= "Alberta","British Columbia"= "British Columbia","Manitoba"= "Manitoba",                 
            "New Brunswick"= "New Brunswick","Newfoundland and Labrador"= "Newfoundland and Labrador",
            "Northwest Territories"= "Northwest Territories",  
            "Nova Scotia"="Nova Scotia", "Ontario"= "Ontario",
            "Prince Edward Island"= "Prince Edward Island",    
            "Quebec"="Quebec")

# Define UI for application that draws a histogram
ui <- fluidPage(navbarPage("Wind turbines in Canada",id="main",
                           #tabPanel("Home",includeHTML("readme.html")),
                           tabPanel("Map", leafletOutput("turbinemap",height=1000)),
                           navbarMenu("Data Tables",
                                tabPanel("All data",DT::dataTableOutput("table")),
                                tabPanel("View projects per province",
                                         sidebarLayout(
                                             sidebarPanel(selectInput("selection","Select a province to view", choices =provincelist, selected = 'Alberta')),
                                             mainPanel(h4('Project summary by province'),tableOutput("summary"))
                                         ))),
                           tabPanel("Plots",
                                sidebarLayout(
                                    sidebarPanel(
                                        radioButtons("plottype", "Plot projects",
                                        choices=c("By Province" = "province","By Project" = "project")
                                        )
                                ),
                            mainPanel(plotOutput("turbinePlots")                        
                                ),
                                ))))

    
                        

# Define server logic required to draw a histogram
server <- function(input, output) {

    output$table <- renderDataTable(datatable(
    wind_data,filter = 'top',
    colnames = c("Province", "Project name", "Total project capacity(MW)", "Turbine identifier", "Turbine No.in Project", "Turbine rated capacity(kW)","Rotor diameter(m)",
                 "Hub height(m)","Manufacturer","Model","Commissioning date")
    ))
    output$summary <- renderTable({
        subset(projects,province_territory == input$selection)
    })
    
    output$turbinemap <- renderLeaflet({
    mymap <-tm_shape(windturbine_sf) + 
        tm_dots(col="indianred1",popup.vars=c("Project Name"="project_name","Total project capacity(MW)"="total_project_capacity_mw"))
    tmap_leaflet(mymap)
   })
    
    output$turbinePlots <- renderPlot({
    if (input$plottype == "province"){
        windturbine %>% 
            count(province_territory) %>% 
            ggplot(aes(forcats::fct_reorder(province_territory, n), n)) +
            geom_bar(stat="identity", fill="steelblue") +
            ggtitle("Number of Turbines for Each Province") +
            coord_flip() +
            theme_minimal() +
            ylab('Number of Turbines') +
            xlab('Province')
        
    } else if (input$plottype == "project"){
        windturbine %>% 
            count(project_name) %>% 
            filter(n > 50)%>% 
            ggplot(aes(forcats::fct_reorder(project_name, n),n)) +
            geom_bar(stat="identity", fill="steelblue") +
            ggtitle("Number of Turbines for Each Project")+
            coord_flip() +
            theme_minimal() +
            ylab('Number of Turbines') +
            xlab('Project')}
    }, height = 800)
    
}
        
# Run the application 
shinyApp(ui = ui, server = server)

标签： rshiny