【发布时间】：2020-08-03 22:21:42
【问题描述】：
我正在尝试在 Shiny 应用程序中使用 Plotly 创建一个交互式地图，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，显示所选区域的统计信息在闪亮的应用程序中。这是UI功能：
library(shiny)
library(shinyWidgets)
library(plotly)
library(leaflet)
shinyUI(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),
submitButton("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")
)
)
)
)
)))
这里是服务器函数：
library(shiny)
library(leaflet)
library(magrittr)
library(rgdal)
library(plotly)
library(rjson)
library(dplyr)
library(viridis)
library(googleVis)
library(lubridate)
library(reshape2)
shinyServer(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$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases$countyNames, covidCases[11,ncol(covidCases)])
gvisCasesData <- melt(data = 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)
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(countyName));
}
if (input$countyFill == "Map by total death") {
v$data <- totalDeath;
v$zmin = 0;
v$zmax = 1600;
v$hover <- with(covidDeath, paste(countyName));
}
})
output$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$hover,
marker=list(line=list(width=0),opacity=0.5)
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
);
countyPolygonMap;
## generating the interactive plotly map
})
output$motionChart <- renderGvis({
subset(gvisCasesData, countyNames %in% c(selected))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
plot(motionChart)
})
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
})
但是，它总是尝试跳转到 GoogleVis 图表的网络浏览器，并给出错误
Error: $ operator is invalid for atomic vectors
你能帮帮我吗？
【问题讨论】：
标签： r shiny r-plotly googlevis