I am trying to create a map that has the name of the 'community' showing the boundaries of multiple zip codes. Data that I have is similar to below. Where the variable is the name of the community and the numbers are the corresponding zipcodes.
Tooele <- c('84074','84029')
NEUtahCo <- c('84003', '84004', '84042', '84062')
NWUtahCounty <- c('84005','84013','84043','84045')
I was able to make a map of the entire area I want using
ggmap(get_map(location = c(lon=-111.9, lat= 40.7), zoom = 9))
Attached is a picture of what I want.
If you are not familiar with R, the first line is loading the 'zipcode' package into the current R session. The second line is using 'data' function to extract the 'zipcode' data from the package as a data frame called 'zipcode'. The last line is calling the data frame to return the data.
To see it yourself, go to Google Maps and search for a city name or even a zip code. You will see a pinkish highlight around the border. Based on your zoom level, as you zoom out, Google will highlight the whole area, not just the borders, in the pink color.
A ZIP Code is a 5-digit number that specifies an individual destination post office or mail delivery area. ZIP codes determine the destination of letters for final sorting and delivery. Each ZIP Code designates a collection of delivery routes used by mail carriers and areas serviced by the USPS.
You have a decent foundation for this already by having figured out the shapefile and how it matches the zips you want to show. Simple features (sf
) make this pretty easy, as does the brand new ggplot2
v3.0.0 which has the geom_sf
to plot sf
objects.
I wasn't sure if the names of the different areas (counties?) that you have are important, so I just threw them all into little tibbles and bound that into one tibble, utah_zips
. tigris
also added sf
support, so if you set class = "sf"
, you get an sf
object. To keep it simple, I'm just pulling out the columns you need and simplifying one of the names.
library(tidyverse)
library(tigris)
library(ggmap)
Tooele <- c('84074','84029')
NEUtahCo <- c('84003', '84004', '84042', '84062')
NWUtahCounty <- c('84005','84013','84043','84045')
utah_zips <- bind_rows(
tibble(area = "Tooele", zip = Tooele),
tibble(area = "NEUtahCo", zip = NEUtahCo),
tibble(area = "NWUtahCounty", zip = NWUtahCounty)
)
zips_sf <- zctas(cb = T, starts_with = "84", class = "sf") %>%
select(zip = ZCTA5CE10, geometry)
head(zips_sf)
#> Simple feature collection with 6 features and 1 field
#> geometry type: MULTIPOLYGON
#> dimension: XY
#> bbox: xmin: -114.0504 ymin: 37.60461 xmax: -109.0485 ymax: 41.79228
#> epsg (SRID): 4269
#> proj4string: +proj=longlat +datum=NAD83 +no_defs
#> zip geometry
#> 37 84023 MULTIPOLYGON (((-109.5799 4...
#> 270 84631 MULTIPOLYGON (((-112.5315 3...
#> 271 84334 MULTIPOLYGON (((-112.1608 4...
#> 272 84714 MULTIPOLYGON (((-113.93 37....
#> 705 84728 MULTIPOLYGON (((-114.0495 3...
#> 706 84083 MULTIPOLYGON (((-114.0437 4...
Then you can filter the sf
for just the zips you need—since there's other information (the county names), you can use a join to get everything in one sf
data frame:
utah_sf <- zips_sf %>%
inner_join(utah_zips, by = "zip")
head(utah_sf)
#> Simple feature collection with 6 features and 2 fields
#> geometry type: MULTIPOLYGON
#> dimension: XY
#> bbox: xmin: -113.1234 ymin: 40.21758 xmax: -111.5677 ymax: 40.87196
#> epsg (SRID): 4269
#> proj4string: +proj=longlat +datum=NAD83 +no_defs
#> zip area geometry
#> 1 84029 Tooele MULTIPOLYGON (((-112.6292 4...
#> 2 84003 NEUtahCo MULTIPOLYGON (((-111.8497 4...
#> 3 84074 Tooele MULTIPOLYGON (((-112.4191 4...
#> 4 84004 NEUtahCo MULTIPOLYGON (((-111.8223 4...
#> 5 84062 NEUtahCo MULTIPOLYGON (((-111.7734 4...
#> 6 84013 NWUtahCounty MULTIPOLYGON (((-112.1564 4...
You already have your basemap figured out, and since ggmap
makes ggplot
objects, you can just add on a geom_sf
layer. The tricks are just to make sure you declare the data you're using, set it to not inherit the aes from ggmap
, and turn off the graticules in coord_sf
.
basemap <- get_map(location = c(lon=-111.9, lat= 40.7), zoom = 9)
ggmap(basemap) +
geom_sf(aes(fill = zip), data = utah_sf, inherit.aes = F, size = 0, alpha = 0.6) +
coord_sf(ndiscr = F) +
theme(legend.position = "none")
You might want to adjust the position of the basemap, since it cuts off one of the zips. One way is to use st_bbox
to get the bounding box of utah_sf
, then use that to get the basemap.
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