使用 R 中 usmap 包中的 plot_usmap 在同一地图上绘制州和县边界

Question

I would like to create a map of the US showing both state and county boundaries (ie state boundaries in a different color). I typically do this using either shape files that I import or using ggplot2 's map_data function. However, I face three obstacles.

1) I cannot install gdal and geos in my computing environment so that precludes the use of any shape files or GeoJSON files (my attempts to map county level shape files loaded using fastshp have not been successful but I'm open to any solution that can reproduce the map below but with state boundaries included).

2) I need to include Hawaii and Alaska, so that excludes the use of map_data from ggplot2 .

3) I need the map to include both state AND county boundaries, which makes the use of usmap package problematic as its a wrapper function for ggplot2 but without the ease and general ability to customize to the level of a raw ggplot2 object.

4) Also, cannot make use of sf package bc it has a non R library dependency ( units package depends on C library libudunits2 ).

What I need: A map that can project Alaska and Hawaii and display state and county boundaries using contrasting colors and I need to accomplish all this without resorting to any packages that rely on rgeos , rgdal , and/or units .

What I've tried thus far plot_usmap from the usmap package:

library(dplyr)
library(stringr)
library(ggplot2)
library(usmap)
library(mapproj)
devtools::install_github("wmurphyrd/fiftystater")
library(fiftystater)

county_data<-read.csv("https://www.ers.usda.gov/webdocs/DataFiles/48747/PovertyEstimates.csv?v=2529") %>% #
  filter(Area_name != "United States") %>%
  select(FIPStxt, Stabr, Area_name, PCTPOVALL_2017) %>%
  rename(fips = FIPStxt)
crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests)
state_map <- map_data("state")

plot_usmap(data = county_data, values = "PCTPOVALL_2017", color = "white") + 
  geom_map(data = crimes, aes(map_id = state), map = fifty_states, color= "red") + 
  geom_path(data = state_map, aes(x =long , y=lat), color= "red")+
  expand_limits(x = fifty_states$long, y = fifty_states$lat) +
  theme(legend.position = "none") +
  theme_map() #no go

plot_usmap(data = county_data, values = "PCTPOVALL_2017", color = "white") + 
  geom_map(data = crimes, aes(map_id = state), map = fifty_states, color= "red") + 
  expand_limits(x = fifty_states$long, y = fifty_states$lat) +
  theme(legend.position = "none") +
  theme_map() #no go

plot_usmap(data = county_data, values = "PCTPOVALL_2017", color = "white") + 
  geom_map(data = crimes, aes(map_id = state, color= "red"), map = fifty_states) + 
  expand_limits(x = fifty_states$long, y = fifty_states$lat) +
  theme(legend.position = "none") +
  theme_map() #no go

What I suspect is happening is that one layer (the original ggplot code) is projected using a different CRS system than the other layer -generated by plot_usmap . That second layer results in a very small red dot (see circle in map below). Not sure how to re-project without geos/gdal installed. See the map below with the black circle highlighting where the red dot is.

Answer 1

Ok after some suggestions from the package author and some of my own tinkering around I was finally able to get my desired output.

This approach is ideal for folks looking to generate a US map w/ Alaska and Hawaii included who...

1) Do not have the ability to install non-R packages in the environment their R engine is running on (eg lack admin access)

2) Need to map both county and state boundaries using contrasting colors

library(dplyr)
library(ggplot2)
library(usmap)

#Example data (poverty rates)
county_data<-read.csv("https://www.ers.usda.gov/webdocs/DataFiles/48747/PovertyEstimates.csv?v=2529") %>% #
  filter(Area_name != "United States") %>%
  select(FIPStxt, Stabr, Area_name, PCTPOVALL_2018) %>%
  rename(fips = FIPStxt)

states <- plot_usmap("states", 
                     color = "red",
                     fill = alpha(0.01)) #this parameter is necessary to get counties to show on top of states
counties <- plot_usmap(data = county_data, 
                       values = "PCTPOVALL_2018",
                       color = "black",
                       size = 0.1)

Using the layers meta info already embedded in the data from us_map

ggplot() +
  counties$layers[[1]] + #counties needs to be on top of states for this to work
  states$layers[[1]] +
  counties$theme + 
  coord_equal() +
  theme(legend.position="none") +
  scale_fill_gradient(low='white', high='grey20') #toggle fill schema using vanilla ggplot scale_fill function

Using just the raw data obtained from the us_map package

ggplot() +  
  geom_polygon(data=counties[[1]], 
               aes(x=x, 
                   y=y, 
                   group=group, 
                   fill = counties[[1]]$PCTPOVALL_2018), 
               color = "black",
               size = 0.1) +  
  geom_polygon(data=states[[1]], 
               aes(x=x, 
                   y=y, 
                   group=group), 
               color = "red", 
               fill = alpha(0.01)) + 
  coord_equal() +
  theme_map() +
  theme(legend.position="none") +
  scale_fill_gradient(low='white', high='grey20')