16  Making Maps With ggplot Using Location Data

Sometimes we have map data that come in the form of location data where the latitude and longitude (Chapter 4) of each participant or location is listed in the data set.

Below I describe the process of working with such location data. Location data can easily be combined with shapefiles (Chapter 8) in ggplot.

16.1 Call Libraries

Show the code 
library(readr) # read CSV

library(dplyr) # data wrangling

library(sf) # simple features

library(ggplot2) # maps

16.2 Use read_csv to Read Text File with Client Data

Show the code 
clients <- read_csv("./location-data/clients.csv")

16.3 Only Clients in Ann Arbor Area

Show the code 
clients <- clients %>% 
  filter(latitude <= 42.33 &
           latitude >= 42.22 &
           longitude >= -83.8 &
           longitude <= -83.65)

16.4 Convert Clients to sf Object While Indicating Coordinate Reference System (CRS)

Show the code 
point <- st_as_sf(clients, 
                  coords = c("longitude", "latitude"), 
                  crs = 4269) # A2 is NAD1983

# write to shapefile

st_write(point, 
         "./shapefiles/clients/clients.shp",
         append = FALSE) # replace; don't append

16.5 Read in Shapefile(s)

Show the code 
city_boundary <- read_sf("./shapefiles/AA_City_Boundary/AA_City_Boundary.shp")

WashtenawRoads <- read_sf("./shapefiles/Roads/RoadCenterlines.shp")

AnnArborRoads <- st_crop(WashtenawRoads, 
                         city_boundary) # crop to only get A2 roads

16.6 Map

Show the code 
ggplot(city_boundary) +
  geom_sf(alpha = .5) +
  geom_sf(data = AnnArborRoads, 
          color = "darkgrey") +
  geom_sf(data = point,
          aes(color = program),
          size = 3) +
labs(title = "Ann Arbor",
     subtitle = "Location of Program Clients") +
  scale_color_viridis_d() +
  scale_fill_viridis_d() +
  theme_minimal() +
  theme(plot.title = element_text(size = rel(2)), 
        axis.text = element_text(size = rel(.5)),
        legend.position = "bottom")