GoogleVis 未显示在 shiny.io
GoogleVis not displaying in shiny.io
我正在尝试创建一个交互式闪亮应用程序，向用户显示 Plotly 地图并允许用户 select U.S 中的不同县。然后它可以使用 selected 县的信息来生成 GoogleVis 动态图表。我已经在本地成功构建了程序，这里是 ui 和服务器函数：
library(shiny)
library(shinyWidgets)
library(plotly)
library(leaflet)
ui <- fluidPage(
titlePanel("Johns Hopkins COVID-19 Modeling Visualization Map"),
setBackgroundImage(
src = "https://brand.jhu.edu/assets/uploads/sites/5/2014/06/university.logo_.small_.horizontal.blue_.jpg"
),
sidebarLayout(
sidebarPanel(
radioButtons("countyFill", "Choose the County Map Type", c("Map by total confirmed", "Map by total death"), selected = "Map by total confirmed"),
checkboxGroupInput("statesInput", "Choose the State(s)",
c("AL", "MO", "AK", "MT", "AZ", "NE",
"AR", "NV", "CA", "NH", "CO", "NJ",
"CT", "NM", "DE", "NY", "DC", "NC",
"FL", "ND", "GA", "OH", "HI", "OK",
"ID", "OR", "IL", "PA", "IN", "RI",
"IA", "SC", "KS", "SD", "KY", "TN",
"LA", "TX", "ME", "UT", "MD", "VT",
"MA", "VA", "MI", "WA", "MN", "WV",
"MS", "WI", "WY"),
inline = TRUE),
actionButton("submit", "Submit (may take 30s to load)")
),
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("County Level", plotlyOutput("countyPolygonMap"),
htmlOutput("casesMotionChart"),
htmlOutput("deathMotionChart")),
tabPanel("State Level", leafletOutput("statePolygonMap")),
tags$div(
tags$p(
"JHU.edu Copyright © 2020 by Johns Hopkins University & Medicine. All rights reserved."
),
tags$p(
tags$a(href="https://it.johnshopkins.edu/policies/privacystatement",
"JHU Information Technology Privacy Statement for Websites and Mobile Applications")
)
)
)
)
)
)
library(shiny)
library(leaflet)
library(magrittr)
library(rgdal)
library(plotly)
library(rjson)
library(dplyr)
library(viridis)
library(googleVis)
library(lubridate)
library(reshape2)
library(data.table)
library(shinyWidgets)
server <- function(input, output, session) {
statepolygonZip <- download.file("https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip",
destfile = "cb_2018_us_state_500k.zip");
unzip("cb_2018_us_state_500k.zip");
statePolygonData <- readOGR("cb_2018_us_state_500k.shp", layer = "cb_2018_us_state_500k",
GDAL1_integer64_policy = TRUE);
## obtaning the state shape file data provided by cencus.gov
## for more categories of region shape file:
## https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
countyGeo <- rjson::fromJSON(file=url)
## Obtaining the geographical file for all U.S. counties
url2<- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv"
covidCases <- read.csv(url2, header = TRUE)
fips <- sprintf("%05d",covidCases$FIPS)
colnames(covidCases)[11] <- "countyNames"
totalComfirmed <- covidCases[,c(which(names(covidCases)=="countyNames"), ncol(covidCases))]
names(totalComfirmed) <- c("countyNames", "cases")
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases[,c(11:ncol(covidCases))])
gvisCasesData <- melt(data = setDT(gvisCasesData), id.vars = c("countyNames"),measure.vars = c(colnames(covidCases)[c(12:ncol(covidCases))]))
colnames(gvisCasesData)[2:3] <- c("Date", "numCases")
gvisCasesData$Date <- mdy(gvisCasesData$Date)
url3 <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv"
covidDeath <- read.csv(url3, header = TRUE)
fips <- sprintf("%05d",covidDeath$FIPS)
colnames(covidDeath)[11] <- "countyNames"
totalDeath <- covidDeath[,c(which(names(covidDeath)=="countyNames"), ncol(covidDeath))]
names(totalDeath) <- c("countyNames", "totalDeath")
destroyX(covidDeath)
gvisDeathData <- cbind.data.frame(covidDeath[,c(11, 13:ncol(covidDeath))])
gvisDeathData <- melt(data = setDT(gvisDeathData), id.vars = c("countyNames"),measure.vars = c(colnames(covidDeath)[c(13:ncol(covidDeath))]))
colnames(gvisDeathData)[2:3] <- c("Date", "numDeath")
gvisDeathData$Date <- mdy(gvisDeathData$Date)
observeEvent(input$submit, {
req(input$submit)
observeEvent(input$countyFill, {
if (input$countyFill == "Map by total confirmed") {
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "casesMap") %>% add_trace(
countyName <- covidCases$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=totalComfirmed$cases,
colorscale="Viridis",
zmin= 100,
zmax= 12000,
text = ~with(covidCases, paste(countyNames)),
marker=list(line=list(width=0),opacity=0.5),
customdata =~totalComfirmed$countyNames
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
%>% event_register(event = "plotly_selected")
);
countyPolygonMap;
## generating the interactive plotly map
})
output$casesMotionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "casesMap")$customdata
gvisCasesDataSubset <- subset(gvisCasesData, countyNames %in% c(selected))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width="automatic", height="automatic"))
})
}
if (input$countyFill == "Map by total death") {
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "deathMap") %>% add_trace(
countyName <- covidDeath$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=totalDeath$totalDeath,
colorscale="Viridis",
zmin= 0,
zmax= 1600,
text = ~with(covidDeath, paste(countyNames)),
marker=list(line=list(width=0),opacity=0.5),
customdata =~totalDeath$countyNames
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
%>% event_register(event = "plotly_selected")
);
countyPolygonMap;
## generating the interactive plotly map
})
output$deathMotionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "deathMap")$customdata
gvisDeathDataSubset <- subset(gvisDeathData, countyNames %in% c(selected))
motionChart <- gvisMotionChart(gvisDeathDataSubset, "countyNames", "Date", options=list(width="automatic", height="automatic"))
})
}
})
output$statePolygonMap <-renderLeaflet ({
statesAbbr <- subset(statePolygonData, statePolygonData$STUSPS %in% input$statesInput);
## subsetting the shape file with the selected states
leaflet(statesAbbr) %>%
addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5,
opacity = 1.0, fillOpacity = 0.5,
fillColor = ~colorQuantile("YlOrRd", ALAND)(ALAND),
highlightOptions = highlightOptions
(color = "white", weight = 2,bringToFront = TRUE))
})
## producing the map with polygon boundary on the state level
})
}
当我在本地 运行 这些代码时，它如我所愿地工作。但是，当我将它上传到 shiny.io 时，它不会在 selection 上显示 googleVis 运动图表。这是我的 shiny.io 的 link 和应用程序的日志：
https://voyagerwsh.shinyapps.io/USMapWithCountyPolygon/?_ga=2.224464666.160516643.1596758294-1394498961.1595634152
2020-08-06T23:31:34.235068+00:00 shinyapps[2621249]: the standard browser to display its output.
2020-08-06T23:31:34.235068+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.235069+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.235070+00:00 shinyapps[2621249]: To suppress this message use:
2020-08-06T23:31:34.235069+00:00 shinyapps[2621249]: or visit https://github.com/mages/googleVis.
2020-08-06T23:31:34.400619+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.235070+00:00 shinyapps[2621249]: suppressPackageStartupMessages(library(googleVis))
2020-08-06T23:31:34.235070+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400621+00:00 shinyapps[2621249]: Attaching package: ‘lubridate’
2020-08-06T23:31:34.400622+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400985+00:00 shinyapps[2621249]: The following objects are masked from ‘package:base’:
2020-08-06T23:31:34.400986+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400986+00:00 shinyapps[2621249]: date, intersect, setdiff, union
2020-08-06T23:31:34.435502+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.435504+00:00 shinyapps[2621249]: Attaching package: ‘data.table’
2020-08-06T23:31:34.435505+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400987+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.435861+00:00 shinyapps[2621249]: The following objects are masked from ‘package:reshape2’:
2020-08-06T23:31:34.435862+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.435862+00:00 shinyapps[2621249]: dcast, melt
2020-08-06T23:31:34.435863+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436223+00:00 shinyapps[2621249]: The following objects are masked from ‘package:lubridate’:
2020-08-06T23:31:34.436224+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436225+00:00 shinyapps[2621249]: yday, year
2020-08-06T23:31:34.436226+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436546+00:00 shinyapps[2621249]: The following objects are masked from ‘package:dplyr’:
2020-08-06T23:31:34.436546+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436547+00:00 shinyapps[2621249]: between, first, last
2020-08-06T23:31:34.436225+00:00 shinyapps[2621249]: hour, isoweek, mday, minute, month, quarter, second, wday, week,
2020-08-06T23:31:34.436547+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.441844+00:00 shinyapps[2621249]: trying URL 'https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip'
2020-08-06T23:31:34.666432+00:00 shinyapps[2621249]: downloaded 3.2 MB
2020-08-06T23:31:34.666434+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.736005+00:00 shinyapps[2621249]: OGR data source with driver: ESRI Shapefile
2020-08-06T23:31:34.736007+00:00 shinyapps[2621249]: Source: "/srv/connect/apps/USMapWithCountyPolygon/cb_2018_us_state_500k.shp", layer: "cb_2018_us_state_500k"
2020-08-06T23:31:34.736028+00:00 shinyapps[2621249]: with 56 features
2020-08-06T23:31:34.736029+00:00 shinyapps[2621249]: It has 9 fields
2020-08-06T23:31:34.736030+00:00 shinyapps[2621249]: Integer64 fields read as doubles: ALAND AWATER
2020-08-06T23:31:38.640171+00:00 shinyapps[2621249]: Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
2020-08-06T23:31:38.640173+00:00 shinyapps[2621249]: Please use `arrange()` instead.
2020-08-06T23:31:38.640174+00:00 shinyapps[2621249]: This warning is displayed once every 8 hours.
2020-08-06T23:31:38.640174+00:00 shinyapps[2621249]: See vignette('programming') for more help
2020-08-06T23:31:38.640175+00:00 shinyapps[2621249]: Call `lifecycle::last_warnings()` to see where this warning was generated.
2020-08-06T23:32:30.764605+00:00 shinyapps[2621249]: trying URL 'https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip'
2020-08-06T23:32:30.913856+00:00 shinyapps[2621249]:
2020-08-06T23:32:30.972639+00:00 shinyapps[2621249]: Integer64 fields read as doubles: ALAND AWATER
2020-08-06T23:32:30.913854+00:00 shinyapps[2621249]: downloaded 3.2 MB
2020-08-06T23:32:30.972614+00:00 shinyapps[2621249]: It has 9 fields
2020-08-06T23:32:30.972586+00:00 shinyapps[2621249]: OGR data source with driver: ESRI Shapefile
2020-08-06T23:32:30.972599+00:00 shinyapps[2621249]: Source: "/srv/connect/apps/USMapWithCountyPolygon/cb_2018_us_state_500k.shp", layer: "cb_2018_us_state_500k"
2020-08-06T23:32:30.972605+00:00 shinyapps[2621249]: with 56 features
为什么会这样？感谢您的帮助！
可能是因为浏览器默认禁止使用flash。它可以在 Chrome 中启用，如下所示：
我正在尝试创建一个交互式闪亮应用程序，向用户显示 Plotly 地图并允许用户 select U.S 中的不同县。然后它可以使用 selected 县的信息来生成 GoogleVis 动态图表。我已经在本地成功构建了程序，这里是 ui 和服务器函数：
library(shiny)
library(shinyWidgets)
library(plotly)
library(leaflet)
ui <- fluidPage(
titlePanel("Johns Hopkins COVID-19 Modeling Visualization Map"),
setBackgroundImage(
src = "https://brand.jhu.edu/assets/uploads/sites/5/2014/06/university.logo_.small_.horizontal.blue_.jpg"
),
sidebarLayout(
sidebarPanel(
radioButtons("countyFill", "Choose the County Map Type", c("Map by total confirmed", "Map by total death"), selected = "Map by total confirmed"),
checkboxGroupInput("statesInput", "Choose the State(s)",
c("AL", "MO", "AK", "MT", "AZ", "NE",
"AR", "NV", "CA", "NH", "CO", "NJ",
"CT", "NM", "DE", "NY", "DC", "NC",
"FL", "ND", "GA", "OH", "HI", "OK",
"ID", "OR", "IL", "PA", "IN", "RI",
"IA", "SC", "KS", "SD", "KY", "TN",
"LA", "TX", "ME", "UT", "MD", "VT",
"MA", "VA", "MI", "WA", "MN", "WV",
"MS", "WI", "WY"),
inline = TRUE),
actionButton("submit", "Submit (may take 30s to load)")
),
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("County Level", plotlyOutput("countyPolygonMap"),
htmlOutput("casesMotionChart"),
htmlOutput("deathMotionChart")),
tabPanel("State Level", leafletOutput("statePolygonMap")),
tags$div(
tags$p(
"JHU.edu Copyright © 2020 by Johns Hopkins University & Medicine. All rights reserved."
),
tags$p(
tags$a(href="https://it.johnshopkins.edu/policies/privacystatement",
"JHU Information Technology Privacy Statement for Websites and Mobile Applications")
)
)
)
)
)
)
library(shiny)
library(leaflet)
library(magrittr)
library(rgdal)
library(plotly)
library(rjson)
library(dplyr)
library(viridis)
library(googleVis)
library(lubridate)
library(reshape2)
library(data.table)
library(shinyWidgets)
server <- function(input, output, session) {
statepolygonZip <- download.file("https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip",
destfile = "cb_2018_us_state_500k.zip");
unzip("cb_2018_us_state_500k.zip");
statePolygonData <- readOGR("cb_2018_us_state_500k.shp", layer = "cb_2018_us_state_500k",
GDAL1_integer64_policy = TRUE);
## obtaning the state shape file data provided by cencus.gov
## for more categories of region shape file:
## https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
countyGeo <- rjson::fromJSON(file=url)
## Obtaining the geographical file for all U.S. counties
url2<- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv"
covidCases <- read.csv(url2, header = TRUE)
fips <- sprintf("%05d",covidCases$FIPS)
colnames(covidCases)[11] <- "countyNames"
totalComfirmed <- covidCases[,c(which(names(covidCases)=="countyNames"), ncol(covidCases))]
names(totalComfirmed) <- c("countyNames", "cases")
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases[,c(11:ncol(covidCases))])
gvisCasesData <- melt(data = setDT(gvisCasesData), id.vars = c("countyNames"),measure.vars = c(colnames(covidCases)[c(12:ncol(covidCases))]))
colnames(gvisCasesData)[2:3] <- c("Date", "numCases")
gvisCasesData$Date <- mdy(gvisCasesData$Date)
url3 <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv"
covidDeath <- read.csv(url3, header = TRUE)
fips <- sprintf("%05d",covidDeath$FIPS)
colnames(covidDeath)[11] <- "countyNames"
totalDeath <- covidDeath[,c(which(names(covidDeath)=="countyNames"), ncol(covidDeath))]
names(totalDeath) <- c("countyNames", "totalDeath")
destroyX(covidDeath)
gvisDeathData <- cbind.data.frame(covidDeath[,c(11, 13:ncol(covidDeath))])
gvisDeathData <- melt(data = setDT(gvisDeathData), id.vars = c("countyNames"),measure.vars = c(colnames(covidDeath)[c(13:ncol(covidDeath))]))
colnames(gvisDeathData)[2:3] <- c("Date", "numDeath")
gvisDeathData$Date <- mdy(gvisDeathData$Date)
observeEvent(input$submit, {
req(input$submit)
observeEvent(input$countyFill, {
if (input$countyFill == "Map by total confirmed") {
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "casesMap") %>% add_trace(
countyName <- covidCases$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=totalComfirmed$cases,
colorscale="Viridis",
zmin= 100,
zmax= 12000,
text = ~with(covidCases, paste(countyNames)),
marker=list(line=list(width=0),opacity=0.5),
customdata =~totalComfirmed$countyNames
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
%>% event_register(event = "plotly_selected")
);
countyPolygonMap;
## generating the interactive plotly map
})
output$casesMotionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "casesMap")$customdata
gvisCasesDataSubset <- subset(gvisCasesData, countyNames %in% c(selected))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width="automatic", height="automatic"))
})
}
if (input$countyFill == "Map by total death") {
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "deathMap") %>% add_trace(
countyName <- covidDeath$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=totalDeath$totalDeath,
colorscale="Viridis",
zmin= 0,
zmax= 1600,
text = ~with(covidDeath, paste(countyNames)),
marker=list(line=list(width=0),opacity=0.5),
customdata =~totalDeath$countyNames
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
%>% event_register(event = "plotly_selected")
);
countyPolygonMap;
## generating the interactive plotly map
})
output$deathMotionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "deathMap")$customdata
gvisDeathDataSubset <- subset(gvisDeathData, countyNames %in% c(selected))
motionChart <- gvisMotionChart(gvisDeathDataSubset, "countyNames", "Date", options=list(width="automatic", height="automatic"))
})
}
})
output$statePolygonMap <-renderLeaflet ({
statesAbbr <- subset(statePolygonData, statePolygonData$STUSPS %in% input$statesInput);
## subsetting the shape file with the selected states
leaflet(statesAbbr) %>%
addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5,
opacity = 1.0, fillOpacity = 0.5,
fillColor = ~colorQuantile("YlOrRd", ALAND)(ALAND),
highlightOptions = highlightOptions
(color = "white", weight = 2,bringToFront = TRUE))
})
## producing the map with polygon boundary on the state level
})
}
当我在本地 运行 这些代码时，它如我所愿地工作。但是，当我将它上传到 shiny.io 时，它不会在 selection 上显示 googleVis 运动图表。这是我的 shiny.io 的 link 和应用程序的日志： https://voyagerwsh.shinyapps.io/USMapWithCountyPolygon/?_ga=2.224464666.160516643.1596758294-1394498961.1595634152
2020-08-06T23:31:34.235068+00:00 shinyapps[2621249]: the standard browser to display its output.
2020-08-06T23:31:34.235068+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.235069+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.235070+00:00 shinyapps[2621249]: To suppress this message use:
2020-08-06T23:31:34.235069+00:00 shinyapps[2621249]: or visit https://github.com/mages/googleVis.
2020-08-06T23:31:34.400619+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.235070+00:00 shinyapps[2621249]: suppressPackageStartupMessages(library(googleVis))
2020-08-06T23:31:34.235070+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400621+00:00 shinyapps[2621249]: Attaching package: ‘lubridate’
2020-08-06T23:31:34.400622+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400985+00:00 shinyapps[2621249]: The following objects are masked from ‘package:base’:
2020-08-06T23:31:34.400986+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400986+00:00 shinyapps[2621249]: date, intersect, setdiff, union
2020-08-06T23:31:34.435502+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.435504+00:00 shinyapps[2621249]: Attaching package: ‘data.table’
2020-08-06T23:31:34.435505+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.400987+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.435861+00:00 shinyapps[2621249]: The following objects are masked from ‘package:reshape2’:
2020-08-06T23:31:34.435862+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.435862+00:00 shinyapps[2621249]: dcast, melt
2020-08-06T23:31:34.435863+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436223+00:00 shinyapps[2621249]: The following objects are masked from ‘package:lubridate’:
2020-08-06T23:31:34.436224+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436225+00:00 shinyapps[2621249]: yday, year
2020-08-06T23:31:34.436226+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436546+00:00 shinyapps[2621249]: The following objects are masked from ‘package:dplyr’:
2020-08-06T23:31:34.436546+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.436547+00:00 shinyapps[2621249]: between, first, last
2020-08-06T23:31:34.436225+00:00 shinyapps[2621249]: hour, isoweek, mday, minute, month, quarter, second, wday, week,
2020-08-06T23:31:34.436547+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.441844+00:00 shinyapps[2621249]: trying URL 'https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip'
2020-08-06T23:31:34.666432+00:00 shinyapps[2621249]: downloaded 3.2 MB
2020-08-06T23:31:34.666434+00:00 shinyapps[2621249]:
2020-08-06T23:31:34.736005+00:00 shinyapps[2621249]: OGR data source with driver: ESRI Shapefile
2020-08-06T23:31:34.736007+00:00 shinyapps[2621249]: Source: "/srv/connect/apps/USMapWithCountyPolygon/cb_2018_us_state_500k.shp", layer: "cb_2018_us_state_500k"
2020-08-06T23:31:34.736028+00:00 shinyapps[2621249]: with 56 features
2020-08-06T23:31:34.736029+00:00 shinyapps[2621249]: It has 9 fields
2020-08-06T23:31:34.736030+00:00 shinyapps[2621249]: Integer64 fields read as doubles: ALAND AWATER
2020-08-06T23:31:38.640171+00:00 shinyapps[2621249]: Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
2020-08-06T23:31:38.640173+00:00 shinyapps[2621249]: Please use `arrange()` instead.
2020-08-06T23:31:38.640174+00:00 shinyapps[2621249]: This warning is displayed once every 8 hours.
2020-08-06T23:31:38.640174+00:00 shinyapps[2621249]: See vignette('programming') for more help
2020-08-06T23:31:38.640175+00:00 shinyapps[2621249]: Call `lifecycle::last_warnings()` to see where this warning was generated.
2020-08-06T23:32:30.764605+00:00 shinyapps[2621249]: trying URL 'https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip'
2020-08-06T23:32:30.913856+00:00 shinyapps[2621249]:
2020-08-06T23:32:30.972639+00:00 shinyapps[2621249]: Integer64 fields read as doubles: ALAND AWATER
2020-08-06T23:32:30.913854+00:00 shinyapps[2621249]: downloaded 3.2 MB
2020-08-06T23:32:30.972614+00:00 shinyapps[2621249]: It has 9 fields
2020-08-06T23:32:30.972586+00:00 shinyapps[2621249]: OGR data source with driver: ESRI Shapefile
2020-08-06T23:32:30.972599+00:00 shinyapps[2621249]: Source: "/srv/connect/apps/USMapWithCountyPolygon/cb_2018_us_state_500k.shp", layer: "cb_2018_us_state_500k"
2020-08-06T23:32:30.972605+00:00 shinyapps[2621249]: with 56 features
为什么会这样？感谢您的帮助！
可能是因为浏览器默认禁止使用flash。它可以在 Chrome 中启用，如下所示：