r - 警告：$: $ 运算符中的错误对于 Shiny Web 应用程序中的原子向量无效
问题描述
我正在尝试在 Shiny 应用程序中使用 Plotly 创建交互式地图，该地图允许用户通过地图上的框选择和套索选择来选择区域，然后它可以返回一个 GoogleVis 动态图表，显示在 Shiny 中选择的区域的统计信息应用程序。然而，当谈到 GoogleVis 的输出功能时：
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))
})
它给出了以下错误：
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$brush
1: runApp
这很奇怪，因为当我在控制台中检查时，我试图用“$”子集的数据框不是原子的。
is.atomic(totalComfirmed)
[1] FALSE
为什么会这样？这是我完整的用户界面和服务器功能：
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)
谢谢你的帮助！
解决方案
当我跑
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$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
names(totalComfirmed) <- c("countyNames", "cases")
然后试试is.atomic，我明白了
is.atomic(totalComfirmed)
# [1] TRUE
您已经从 data.frame 中提取了一列，默认情况下它只返回一个原子向量。然后当你尝试做
totalComfirmed$cases %in% selectedCountyCases
你会得到一个错误，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笔误？应该是totalConfirmed吗？
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