使用 zip_choropleth 时如何显示邮政编码？

Question

我创建了给定县内邮政编码的分区统计图。但是，我被要求标记所有邮政编码（它可能很混乱，但这是他们想要看到的）。有没有办法直接在地图上添加所有标签？类似于在美国等值区域地图中标记所有州？

我本质上希望所有“区域”都被标记。

这是我的代码：

编辑：这是有效的代码。非常感谢斯坦勒的帮助！

library(tidyverse)
library(maps)
library(ggplot2)
library(ggmap)
library(mapproj)
library(choroplethr)
library(choroplethrZip)

df <- structure(list(region = c("45001", "45002", "45003", "45011", 
"45013", "45014", "45030", "45041", "45044", "45050", "45052", 
"45069", "45111", "45140", "45147", "45150", "45174", "45202", 
"45203", "45204", "45205", "45206", "45207", "45208", "45209", 
"45210", "45211", "45212", "45213", "45214", "45215", "45216", 
"45217", "45218", "45219", "45220", "45223", "45224", "45225", 
"45226", "45227", "45229", "45230", "45231", "45232", "45233", 
"45236", "45237", "45238", "45239", "45240", "45241", "45242", 
"45243", "45244", "45246", "45247", "45248", "45249", "45250", 
"45251", "45252", "45255", "45033", "45051"), value = c(3, 20, 
1, 11, 155, 7, 28, 1, 2, 1, 3, 5, 1, 20, 1, 73, 1, 52, 26, 15, 
106, 109, 52, 8, 55, 1, 185, 69, 30, 99, 104, 35, 35, 9, 20, 
96, 51, 182, 75, 3, 82, 133, 60, 246, 42, 13, 79, 217, 128, 146, 
125, 71, 30, 10, 19, 62, 24, 21, 31, 1, 51, 3, 28, 0, 0)), row.names = c(NA, 
-65L), class = c("tbl_df", "tbl", "data.frame"))

fip=c(39061)

ohiocounty_map <-
  map_data("county") %>%
  subset(region == "ohio") %>%
  mutate(County = str_to_sentence(subregion)) %>%
  group_by(County) %>%
  filter(County %in% c("Hamilton"))

# get zip codes
data("zip.map")

myzips <- zip.map %>%
  filter(region %in% df$region) %>% 
  rename(zipcode = region) %>% 
  group_by(zipcode) %>% 
  summarise(across(everything(), ~mean(.x, na.rm = TRUE)))


choropleth <-  zip_choropleth(df, state_zoom = "ohio", county_zoom = fip, 
                              title = "Population by Zip Code in Hamilton County", 
                              legend= "Number of Clients")

choropleth + geom_polygon(data=ohiocounty_map, aes(x=long, y=lat, group=group), alpha=0, 
                          color="black", 
                          size=0.2) +
  guides(fill=guide_legend(title="Number of Clients")) +
  theme(plot.margin = margin(r=.8, l=.5, t=.6, b=.8, unit="in"), plot.title = element_text(hjust=0.5, face="bold", size = 15)) +
  coord_cartesian(xlim=c(-84.9, -84.25), ylim=c(39, 39.33), expand = FALSE) + 
  geom_text(data = myzips, 
            stat = "identity", 
            check_overlap = TRUE,
            aes(x = long, y = lat, label = zipcode))  

Answer 1

实现此目的的一种方法是引入

zip.map

并按您想要的邮政编码进行过滤。现在您已经有了邮政编码的经度和纬度数据，并且可以使用

geom_text

或

geom_label

将其添加到现有地图中。

library(tidyverse)
library(maps)
library(ggplot2)
library(ggmap)
library(mapproj)
library(choroplethr)
library(choroplethrZip)

df <- structure(list(region = c("45001", "45002", "45003", "45011", 
                                "45013", "45014", "45030", "45041", "45044", "45050", "45052", 
                                "45069", "45111", "45140", "45147", "45150", "45174", "45202", 
                                "45203", "45204", "45205", "45206", "45207", "45208", "45209", 
                                "45210", "45211", "45212", "45213", "45214", "45215", "45216", 
                                "45217", "45218", "45219", "45220", "45223", "45224", "45225", 
                                "45226", "45227", "45229", "45230", "45231", "45232", "45233", 
                                "45236", "45237", "45238", "45239", "45240", "45241", "45242", 
                                "45243", "45244", "45246", "45247", "45248", "45249", "45250", 
                                "45251", "45252", "45255", "45033", "45051"), value = c(3, 20, 
                                                                                        1, 11, 155, 7, 28, 1, 2, 1, 3, 5, 1, 20, 1, 73, 1, 52, 26, 15, 
                                                                                        106, 109, 52, 8, 55, 1, 185, 69, 30, 99, 104, 35, 35, 9, 20, 
                                                                                        96, 51, 182, 75, 3, 82, 133, 60, 246, 42, 13, 79, 217, 128, 146, 
                                                                                        125, 71, 30, 10, 19, 62, 24, 21, 31, 1, 51, 3, 28, 0, 0)), row.names = c(NA, 
                                                                                                                                                                 -65L), class = c("tbl_df", "tbl", "data.frame"))

fip=c(39061)

ohiocounty_map <-
  map_data("county") %>%
  subset(region == "ohio") %>%
  mutate(County = str_to_sentence(subregion)) %>%
  group_by(County) %>%
  filter(County %in% c("Hamilton"))

# get zip codes
data("zip.map")
myzips <- zip.map %>%
  filter(region %in% df$region) %>%
  rename(zipcode = region) %>%
  group_by(zipcode) %>% 
  summarise(across(everything(), mean)) # without this line, there would be a lot of zip code labels

choropleth <-  zip_choropleth(df, state_zoom = "ohio", county_zoom = fip, 
                              title = "Population by Zip Code in Hamilton County", 
                              legend= "Number of Clients")

choropleth + geom_polygon(data=ohiocounty_map, aes(x=long, y=lat, group=group), alpha=0, 
                          color="black", 
                          size=0.2) +
  scale_fill_brewer(palette="OrRd") + 
  guides(fill=guide_legend(title="Number of Clients")) +
  theme(plot.margin = margin(r=.8, l=.5, t=.6, b=.8, unit="in"), plot.title = element_text(hjust=0.5, face="bold", size = 15)) +
  coord_cartesian(xlim=c(-84.9, -84.25), ylim=c(39, 39.33), expand = FALSE) + 
  geom_text(data = myzips, 
            stat = "identity", 
            check_overlap = TRUE,
            aes(x = long, y = lat, label = zipcode))