There are more levels of detail for borders in the United States than most other countries. Since I live in the US and travel extensively in this country, it seems logical to focus on this geographic region.
Note that the 48 contiguous states are the focus here. The standard border sets (e.g., map_data) leave off Hawai`i and Alaska. This limitation is treated, in part, in the Shapefiles chapter.
The detail levels include the entire country, states and counties. This is a very useful set of boundaries.
There are a few things needed to setup the environment.
Click on the button to see the code. You’ll find similar buttons throughout this document.
## Set an option for the read_csv function
options(readr.show_col_types = FALSE) ## Suppress warning msg
## Initialize the Standard Libraries
library(readr)
library(ggplot2)
library(dplyr)
library(gt)
## Initialize sitemaps & plainmaps
library(sitemaps)
library(plainmaps)
## Map Libraries
library(mapdata)
library(sf)
## Initialize for Sitemaps
column <- site_styles()
hide <- site_google_hides()It’s always good to make sure things are running OK before heading into a big, complex project.
Note that the coord_fixed(1.3) statement makes the height/width relationship appear appropriate. Without this statement, the map will appear distorted.
The code here has not been simplified. Later, you’ll see that there is a function (region_plot as part of theplainmapspackage) that “hide” a lot of the code details, making it easier to get basic border outline plots.
## Extract some data.
usa <- map_data("usa")
## Plot the data as an outline map.
ggplot() + geom_polygon(data = usa,
aes(x=long,
y = lat,
group = group),
fill=NA,
color="red") +
coord_fixed(1.3) +
labs(x = "longitude", y = "latitude")
All the US states, except Alaska and Hawai`i, can be handled by extracting outline data using the map_data function.
## Extract the set of US states.
states <- map_data("state")
## Remove just one state (california) from the set.
cal <- states %>%
filter(region == "california")
## Create the state map.
CA_map <- ggplot(data = cal) +
## Draw the border and fill it with color
geom_polygon(aes(x = long,
y = lat,
group = group),
fill = "peachpuff3",
color = "black") +
## Adjust for lat/lon distortion
coord_fixed(1.3) +
## Suppress the axis titles (lat, lon)
labs(x = "", y = "")
## Show the state map.
CA_map
We’ll use the previous map of California and show just the general Southern California area.
The theme statement draws a dark line around the entire map area. Without this, the top of the Southern California area is without a boundary line. This cleans up the appearance.
## Trim the map created in the previous chunk.
SoCal <- CA_map +
coord_cartesian(ylim=c(32.4,35.0), xlim=c(-121.5,-114.0)) +
theme(panel.border = element_rect(linewidth=1,
color="black",
fill=NA))
## Show the map.
SoCal
We can use multiple filter statements to save multiple state boundaries from the states collection.
## Use data (states) from a previous chunk.
## Extract three adjacent states.
WA <- states |>
filter(region == "washington")
ID <- states |>
filter(region == "idaho")
OR <- states |>
filter(region == "oregon")
## Create a plot the three states.
PNW <- ggplot() +
## Draw the outline and fill each state with a color
geom_polygon(data = WA,
aes(x = long,
y = lat,
group = group),
fill = "peachpuff3",
color = "black") +
geom_polygon(data = ID,
aes(x = long,
y = lat,
group = group),
fill = "goldenrod1",
color = "black") +
geom_polygon(data = OR,
aes(x = long,
y = lat,
group = group),
fill = "lightsalmon1",
color = "black") +
## Adjust for lat/lon distortion
coord_fixed(1.3) +
## Suppress the axis titles (lat, lon)
labs(x = "", y = "")
## Output the map.
PNW
This code chunk adds county-level boundaries to a state map.
## Extract the state outline.
states <- map_data("state")
NM <- states |>
filter(region == "new mexico")
## Extract the county outlines.
counties <- map_data("county")
NM_counties <- counties |>
filter(region == "new mexico")
## Create the map as layers.
NM_map <- ggplot(data = NM, mapping=aes(x = long,
y = lat,
group = group)) +
## Draw and fill the state outline
geom_polygon(fill = "lightsalmon1") +
## Draw county lines & don't change the color
geom_polygon(data = NM_counties,
fill = NA,
color = "black") +
## Adjust for lat/lon distortion
coord_fixed(1.3)
## Output the map.
NM_map
It is often important to emphasize the location and extent of counties within a state. Using a color overlay is a straightforward way of doing this.
In the following chunk, the basemap and data are carried over from the previous chunk.
A table generated so you can see the county names. Note that these names are all lower case.
## Uses the data and the map created in the previous chunk.
## Get a list of the county names.
county_names <- data.frame(unique(NM_counties$subregion))
## List the county names for reference.
colnames(county_names)[1] <- "County"
gt(county_names) |>
tab_source_note(source_note="Source: Extracted from map data")| County |
|---|
| bernalillo |
| catron |
| chaves |
| colfax |
| curry |
| de baca |
| dona ana |
| eddy |
| grant |
| guadalupe |
| harding |
| hidalgo |
| lea |
| lincoln |
| los alamos |
| luna |
| mckinley |
| mora |
| otero |
| quay |
| rio arriba |
| roosevelt |
| sandoval |
| san juan |
| san miguel |
| santa fe |
| sierra |
| socorro |
| taos |
| torrance |
| union |
| cibola |
| valencia |
| Source: Extracted from map data |
## Select several of the counties.
selected_counties <- NM_counties |>
filter(subregion %in% c("los alamos","santa fe"))
## Overlay the selected counties on the previous basemap.
NM_map +
## Add an overlay
geom_polygon(data = selected_counties,
mapping=aes(x = long,
y = lat,
group = group),
fill = "peachpuff3",
color = "white",
linewidth = 0.7)