ggplot2映射为空白

Question

我正在使用与加拿大统计局的具有不同形状文件的其他脚本类似的代码。但是，我无法使用简单的脚本来处理省级地图。我认为问题很简单，但我看不到。

setwd("D:\\OneDrive\\lfs_stuff")
project_folder<-getwd()
data_folder<-project_folder
library(tidyverse)
#now start the map
library(rgeos)
library(rgdal)
library(maptools)
library(sp)
library(mapproj)
library(ggplot2)
#get test data
mydata<-read_csv("map_data.csv",col_types=list(col_character(),col_double()))
print(mydata)
# shape file came from this link for a digital shape file
# http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/2016/lpr_000a16a_e.zip
target_url<-"http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/2016/lpr_000a16a_e.zip"
url_file<-"lpr_000a16a_e.zip"
download_target<-paste0(project_folder,"/",url_file)
    download.file(target_url,download_target,mode="wb",quiet=FALSE)
    unzip(download_target,overwrite=TRUE,exdir=data_folder)
provincial_shape_file<-gsub(".zip",".shp",download_target)
provincial_shp<-readOGR(dsn=provincial_shape_file,layer="lpr_000a16a_e")
#convert it to the reqired data structure. the id vbl will contain the provincial codes
prov_base_map<-fortify(provincial_shp,region="PRUID")
map_data_1<-merge(prov_base_map,as_data_frame(mydata),by="id")
map1<-ggplot()+
geom_map(data=map_data_1,map=map_data_1,stat="identity",
aes(map_id=id,x=long,y=lat,fill=(pch),group=group),
colour="black",size=0.3)+
coord_map()
print(map1)

形状文件的下载位于脚本中。 mydata文件如下所示

"id","pch"
"10",0.667259786476859
"11",5.63186813186813
"12",2.12053571428572
"13",-0.563697857948142
"24",0.150669774230772
"35",1.15309092428315
"46",0.479282622139765
"47",1.70242950877815
"48",1.84482533036765
"59",1.96197656978394

Answer 1

Here's one way with sf (though I think the ultimate issue is not having the id being identified correctly):

library(sf)
library(httr)
library(tidyverse)

read.csv(text='"id","pch"
"10",0.667259786476859
"11",5.63186813186813
"12",2.12053571428572
"13",-0.563697857948142
"24",0.150669774230772
"35",1.15309092428315
"46",0.479282622139765
"47",1.70242950877815
"48",1.84482533036765
"59",1.96197656978394',
         stringsAsFactors=FALSE,
         colClasses = c("character", "double")) -> xdf

# cross-platform-friendly d/l with caching built-in
try(httr::GET(
  url = "http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/2016/lpr_000a16a_e.zip",
  httr::write_disk("~/Data/lpr_00a16a_e.zip"),
  httr::progress()
)) -> res

fils <- unzip("~/Data/lpr_00a16a_e.zip", exdir = "~/Data/lpr")

ca_map <- st_read(grep("shp$", fils, value=TRUE), stringsAsFactors = FALSE)
ca_map <- st_simplify(ca_map, TRUE, 10) # you don't need the coastlines to be that detailed
ca_map <- left_join(ca_map, xdf, by=c("PRUID"="id"))

ggplot(ca_map) +
  geom_sf(aes(fill = pch)) +
  viridis::scale_fill_viridis(direction=-1, option="magma") +
  coord_sf()

的标题属性

顺便说一句，尽管我简化了shapefile（为了更快地绘图），但我还是会寻找省份的轻量级GeoJSON版本，因为您抓到的省份是 super 细粒度的海岸线，您绝对不需要它。