警告：$ 中的错误：$ 运算符对于 Shiny Web 应用程序中的原子向量无效
Warning: Error in $: $ operator is invalid for atomic vectors in Shiny Web app
我正在尝试在 Shiny 应用程序中使用 Plotly 创建交互式地图，允许用户通过方框 select 和套索 select 在地图上 select 区域，然后它可以 return GoogleVis 动态图表，显示 Shiny 应用程序中 selected 区域的统计数据。但是说到GoogleVis的输出函数：
output$motionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "countyMap")
selectedCountyCases <- as.integer(unlist(selected[3]))
selectedCounties <- subset(totalComfirmed, totalComfirmed$cases %in% selectedCountyCases)
gvisCasesDataSubset <- subset(gvisCasesData, countyNames %in% c(selectedCounties$countyNames))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
})
它给出了错误：
Warning: Error in $: $ operator is invalid for atomic vectors
96: renderText [/Users/b.w.h/Documents/JHU/Summer 1/COVID-19 Modeling Project/County Polygon Visualization with Shiny/USMapWithCountyPolygon/server.R#114]
95: func
82: origRenderFunc
81: output$brush
1: runApp
这很奇怪，因为当我在控制台中检查时，我试图用“$”子集化的数据框不是原子的。
is.atomic(totalComfirmed)
[1] FALSE
为什么会这样？这是我的完整 ui 和服务器功能：
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("motionChart"),
verbatimTextOutput("brush")),
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)
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$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
names(totalComfirmed) <- c("countyNames", "cases")
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases$countyNames, covidCases[11,ncol(covidCases)])
gvisCasesData <- melt(data = setDT(covidCases), id.vars = "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)
colnames(covidDeath)[6] <- "countyNames"
totalDeath <- covidDeath[,ncol(covidDeath)]
v <- reactiveValues(data = totalComfirmed)
observeEvent(input$countyFill, {
if (input$countyFill == "Map by total confirmed") {
v$data <- totalComfirmed;
v$zmin = 100;
v$zmax = 12000;
v$hover <- with(covidCases, paste(countyNames));
}
if (input$countyFill == "Map by total death") {
v$data <- totalDeath;
v$zmin = 0;
v$zmax = 1600;
v$hover <- with(covidDeath, paste(countyNames));
}
})
observeEvent(input$submit, {
req(input$submit)
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "countyMap") %>% add_trace(
countyName <- covidCases$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=v$data,
colorscale="Viridis",
zmin= v$zmin,
zmax= v$zmax,
text = ~v$hover,
marker=list(line=list(width=0),opacity=0.5)
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
%>% event_register(event = "plotly_selected")
);
countyPolygonMap;
## generating the interactive plotly map
})
output$motionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "countyMap")
selectedCountyCases <- as.integer(unlist(selected[3]))
selectedCounties <- subset(totalComfirmed, totalComfirmed$cases %in% selectedCountyCases)
gvisCasesDataSubset <- subset(gvisCasesData, countyNames %in% c(selectedCounties$countyNames))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
})
#output$brush <- renderText({
# selected <- event_data(event = "plotly_selected", source = "countyMap")
# selectedCountyCases <- as.integer(unlist(selected[3]))
# brush <- selectedCounties
#})
output$statePolygonMap <-renderLeaflet ({
statesAbbr <- subset(statePolygonData, input$statesInput %in% statePolygonData$STUSPS);
## 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
})
}
shinyApp(ui, server)
感谢您的帮助！
当我运行
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$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
names(totalComfirmed) <- c("countyNames", "cases")
然后尝试is.atomic，我得到
is.atomic(totalComfirmed)
# [1] TRUE
您从 data.frame 中提取了一个列，默认情况下 returns 只是一个原子向量。然后当你尝试做
totalComfirmed$cases %in% selectedCountyCases
您会收到错误消息，因为 totalComfirmed 没有任何列。也许你的意思是
totalComfirmed <- covidCases[,c(which(names(covidCases)=="countyNames"), ncol(covidCases))]
也是totalComfirmed打错了吗？应该是totalConfirmed？
我正在尝试在 Shiny 应用程序中使用 Plotly 创建交互式地图，允许用户通过方框 select 和套索 select 在地图上 select 区域，然后它可以 return GoogleVis 动态图表，显示 Shiny 应用程序中 selected 区域的统计数据。但是说到GoogleVis的输出函数：
output$motionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "countyMap")
selectedCountyCases <- as.integer(unlist(selected[3]))
selectedCounties <- subset(totalComfirmed, totalComfirmed$cases %in% selectedCountyCases)
gvisCasesDataSubset <- subset(gvisCasesData, countyNames %in% c(selectedCounties$countyNames))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
})
它给出了错误：
Warning: Error in $: $ operator is invalid for atomic vectors
96: renderText [/Users/b.w.h/Documents/JHU/Summer 1/COVID-19 Modeling Project/County Polygon Visualization with Shiny/USMapWithCountyPolygon/server.R#114]
95: func
82: origRenderFunc
81: output$brush
1: runApp
这很奇怪，因为当我在控制台中检查时，我试图用“$”子集化的数据框不是原子的。
is.atomic(totalComfirmed)
[1] FALSE
为什么会这样？这是我的完整 ui 和服务器功能：
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("motionChart"),
verbatimTextOutput("brush")),
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)
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$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
names(totalComfirmed) <- c("countyNames", "cases")
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases$countyNames, covidCases[11,ncol(covidCases)])
gvisCasesData <- melt(data = setDT(covidCases), id.vars = "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)
colnames(covidDeath)[6] <- "countyNames"
totalDeath <- covidDeath[,ncol(covidDeath)]
v <- reactiveValues(data = totalComfirmed)
observeEvent(input$countyFill, {
if (input$countyFill == "Map by total confirmed") {
v$data <- totalComfirmed;
v$zmin = 100;
v$zmax = 12000;
v$hover <- with(covidCases, paste(countyNames));
}
if (input$countyFill == "Map by total death") {
v$data <- totalDeath;
v$zmin = 0;
v$zmax = 1600;
v$hover <- with(covidDeath, paste(countyNames));
}
})
observeEvent(input$submit, {
req(input$submit)
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "countyMap") %>% add_trace(
countyName <- covidCases$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=v$data,
colorscale="Viridis",
zmin= v$zmin,
zmax= v$zmax,
text = ~v$hover,
marker=list(line=list(width=0),opacity=0.5)
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
%>% event_register(event = "plotly_selected")
);
countyPolygonMap;
## generating the interactive plotly map
})
output$motionChart <- renderGvis({
selected <- event_data(event = "plotly_selected", source = "countyMap")
selectedCountyCases <- as.integer(unlist(selected[3]))
selectedCounties <- subset(totalComfirmed, totalComfirmed$cases %in% selectedCountyCases)
gvisCasesDataSubset <- subset(gvisCasesData, countyNames %in% c(selectedCounties$countyNames))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
})
#output$brush <- renderText({
# selected <- event_data(event = "plotly_selected", source = "countyMap")
# selectedCountyCases <- as.integer(unlist(selected[3]))
# brush <- selectedCounties
#})
output$statePolygonMap <-renderLeaflet ({
statesAbbr <- subset(statePolygonData, input$statesInput %in% statePolygonData$STUSPS);
## 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
})
}
shinyApp(ui, server)
感谢您的帮助！
当我运行
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$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
names(totalComfirmed) <- c("countyNames", "cases")
然后尝试is.atomic，我得到
is.atomic(totalComfirmed)
# [1] TRUE
您从 data.frame 中提取了一个列，默认情况下 returns 只是一个原子向量。然后当你尝试做
totalComfirmed$cases %in% selectedCountyCases
您会收到错误消息，因为 totalComfirmed 没有任何列。也许你的意思是
totalComfirmed <- covidCases[,c(which(names(covidCases)=="countyNames"), ncol(covidCases))]
也是totalComfirmed打错了吗？应该是totalConfirmed？