R绘制分级统计图（Choropleth map）

library(ggplot2) #fortify()
library(dplyr) #full_join()

windowsFonts(font1=windowsFont('Book Antiqua'),
             font2=windowsFont('Cambria'),
             font3=windowsFont('华文中宋'),
             font4=windowsFont('楷体'))

##写入地图边界数据
x0 = rgdal::readOGR("D:/R/china-province-border-data/bou2_4p.shp")
x <- x0@data
xs <- data.frame(x, id = seq(0:924) -1)# 地图中共计有925个地域信息
xs['id']<-as.character(xs$id)
china_map1 <- fortify(x0) #提取复合数据类型中的数据

china_map_data <- full_join(china_map1, xs,type = "full")# 基于id进行连接

##导入自己的数据
mydata <-read.csv("C:/Users/.../Desktop/map_value.csv",encoding = "UTF-8")
names(mydata)<-c("NAME","value")
china_data <- full_join(china_map_data,mydata, type = "full")
#基于NAME字段进行连接，NAME字段来自于地图文件中

##获取省份中心坐标
prov_path <- system.file("geojson/china.json", package = "leafletCN")
prov_map <- leafletCN::read.geoShape	(prov_path)
prov_data <- prov_map@data
prov_names <- prov_data$name # 或者regionNames("china")

prov_centroids <- vector("list", length(prov_names))
for (i in seq_along(prov_names)) {
  prov_centroids[[i]] <- prov_map[prov_data$name == prov_names[[i]], ] %>% 
    rgeos::gCentroid() %>% 
    as_tibble()
}

prov_centroids_tb <- bind_rows(prov_centroids)#转化为数据框
prov_centroids_name <- bind_cols(prov_centroids_tb, name = prov_names)
names(prov_centroids_name)=c("cp1","cp2","NAME")

##汇总数据
china_data <- full_join(china_data,prov_centroids_name)

#以简称显示省市名称
china_data$NAME <- gsub(pattern = "省", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "市", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "自治区", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "维吾尔", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "壮族", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "回族", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "特别行政区", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "香港", replacement = "", china_data$NAME)
china_data$NAME <- gsub(pattern = "澳门", replacement = "", china_data$NAME)

#微调名称位置
china_data[is.na(china_data$value),]['value']<-0
china_data[which(china_data$NAME=="河北"&!is.na(china_data$cp1)),'cp1'] <- 115.20212
china_data[which(china_data$NAME=="河北"&!is.na(china_data$cp2)),'cp2']<-38.279605

china_data[which(china_data$NAME=="内蒙古"&!is.na(china_data$cp1)),'cp1']<-118.366455
china_data[which(china_data$NAME=="内蒙古"&!is.na(china_data$cp2)),'cp2']<-43.844183

china_data[which(china_data$NAME=="甘肃"&!is.na(china_data$cp1)),'cp1']<-102
china_data[which(china_data$NAME=="甘肃"&!is.na(china_data$cp2)),'cp2']<-39

##绘图
dev.new()
ggplot(china_data,aes(x=long,y=lat,group=group,fill=value))+
  geom_polygon(colour="grey40")+ #边界颜色
  scale_fill_gradient(low = "white",high = "red")+  #填充方式，这里是2色渐变填充
  coord_map("polyconic")+
  geom_text(family="font4",aes(x=cp1,y=cp2,label=NAME),colour="black",size=3)+
  ggtitle("各省2010-2018苹果平均产量分布")+
  theme(
    plot.title = element_text(family="font4", face="bold",hjust = 0.5,size=20),
    panel.grid=element_blank(),
    panel.background=element_blank(),
    axis.text=element_blank(),
    axis.ticks=element_blank(),
    axis.title=element_blank()
  )+
  labs(fill = "苹果年产量（万吨）")+
  theme(legend.title = element_text(family="font4",size = 15))
R绘制分级统计图（Choropleth map）

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