如何创建美国各县的传单等值线图
How to create a leaflet choropleth map of US counties
使用下面的代码,我得到了包含美国县数据的数据框
library(raster)
library(leaflet)
library(tidyverse)
# Get USA polygon data
USA <- getData("GADM", country = "usa", level = 2)
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE)
我的目标是创建一个 Avg_yield
的交互式传单等值线图,所以首先我要加强我的美国多边形数据
library(rgeos)
library(maptools)
library(ggplot2)
states.shp.f <- fortify(USA, region = "NAME_2")
然后我对我的数据集进行子集化并将其与强化的合并:
mydata2<-mydata[,c("COUNTY_NAME","Avg_yield")]
colnames(mydata2)[1]<-"id"
## merge shape file with data
merge.shp.coef <- merge(states.shp.f, mydata2, by = "id")
但现在我有一个包含每个县名很多次的数据集,而且一些县有不同的 Avg_yield
值。处理这些数据以使用传单代码的正确方法是什么:
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(data = USA, stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydata$Avg_yield),
popup = paste("Region: ", USA$NAME_2, "<br>",
"Avg_yield: ", mydata$Avg_yield, "<br>")) %>%
addLegend(position = "bottomleft", pal = mypal, values = mydata$Avg_yield,
title = "Avg_yield",
opacity = 1)
这样做的最佳方法是将多边形对象转换为 sf 对象
st_as_sf()
这里有一个工作示例:
(我确实为多边形使用了一些其他数据,我认为你的太精确并且需要大量资源,而且我让它与 shiny 一起使用)
library(leaflet)
library(tidyverse)
library(ggplot2)
library(sf)
library(shiny)
USA <- st_read(dsn = '[your path]/cb_2018_us_county_500k.shp')
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE)
states_sf <- st_as_sf(USA)
mydata2<-mydata[,c("COUNTY_NAME","Avg_yield")]
colnames(mydata2)[1]<-"NAME"
## merge shape file with data
states_sf_coef <- left_join(states_sf, mydata2, by = "NAME")
ui <- fluidPage(
leafletOutput("map", height = "100vh")
)
server <- function(input, output, session) {
bins <- c(0, 5, 10, 15, 20, 25, 30, 35, 40)
mypal <- colorBin("YlOrRd", domain = states_sf_coef$Avg_yield, bins = bins)
#Sortie map
output$map <- renderLeaflet({
leaflet()%>%
addProviderTiles("OpenStreetMap.Mapnik")%>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(
data = states_sf_coef,
fillColor = ~mypal(states_sf_coef$Avg_yield),
stroke = FALSE,
smoothFactor = 0.2,
fillOpacity = 0.3,
popup = paste("Region: ", states_sf_coef$NAME_2, "<br>",
"Avg_yield: ", states_sf_coef$Avg_yield, "<br>"))%>%
addLegend(position = "bottomleft",
pal = mypal,
values = states_sf_coef$Avg_yield,
title = "Avg_yield",
opacity = 1)
})
}
# Create Shiny app ----
shinyApp(ui = ui, server = server)
使用下面的代码,我得到了包含美国县数据的数据框
library(raster)
library(leaflet)
library(tidyverse)
# Get USA polygon data
USA <- getData("GADM", country = "usa", level = 2)
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE)
我的目标是创建一个 Avg_yield
的交互式传单等值线图,所以首先我要加强我的美国多边形数据
library(rgeos)
library(maptools)
library(ggplot2)
states.shp.f <- fortify(USA, region = "NAME_2")
然后我对我的数据集进行子集化并将其与强化的合并:
mydata2<-mydata[,c("COUNTY_NAME","Avg_yield")]
colnames(mydata2)[1]<-"id"
## merge shape file with data
merge.shp.coef <- merge(states.shp.f, mydata2, by = "id")
但现在我有一个包含每个县名很多次的数据集,而且一些县有不同的 Avg_yield
值。处理这些数据以使用传单代码的正确方法是什么:
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(data = USA, stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydata$Avg_yield),
popup = paste("Region: ", USA$NAME_2, "<br>",
"Avg_yield: ", mydata$Avg_yield, "<br>")) %>%
addLegend(position = "bottomleft", pal = mypal, values = mydata$Avg_yield,
title = "Avg_yield",
opacity = 1)
这样做的最佳方法是将多边形对象转换为 sf 对象 st_as_sf()
这里有一个工作示例: (我确实为多边形使用了一些其他数据,我认为你的太精确并且需要大量资源,而且我让它与 shiny 一起使用)
library(leaflet)
library(tidyverse)
library(ggplot2)
library(sf)
library(shiny)
USA <- st_read(dsn = '[your path]/cb_2018_us_county_500k.shp')
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE)
states_sf <- st_as_sf(USA)
mydata2<-mydata[,c("COUNTY_NAME","Avg_yield")]
colnames(mydata2)[1]<-"NAME"
## merge shape file with data
states_sf_coef <- left_join(states_sf, mydata2, by = "NAME")
ui <- fluidPage(
leafletOutput("map", height = "100vh")
)
server <- function(input, output, session) {
bins <- c(0, 5, 10, 15, 20, 25, 30, 35, 40)
mypal <- colorBin("YlOrRd", domain = states_sf_coef$Avg_yield, bins = bins)
#Sortie map
output$map <- renderLeaflet({
leaflet()%>%
addProviderTiles("OpenStreetMap.Mapnik")%>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(
data = states_sf_coef,
fillColor = ~mypal(states_sf_coef$Avg_yield),
stroke = FALSE,
smoothFactor = 0.2,
fillOpacity = 0.3,
popup = paste("Region: ", states_sf_coef$NAME_2, "<br>",
"Avg_yield: ", states_sf_coef$Avg_yield, "<br>"))%>%
addLegend(position = "bottomleft",
pal = mypal,
values = states_sf_coef$Avg_yield,
title = "Avg_yield",
opacity = 1)
})
}
# Create Shiny app ----
shinyApp(ui = ui, server = server)