Mapping with geom_sf(): Assigning labels to data points when you don't have distinct x,y columns in dataframe

Question

I am working to create a map in ggplot2 using the geom_sf() function. The data for the map is from a KML file (downloaded from GoogleEarth), so when I read that into R, the lat/longs for each datapoint are in a combined 'geometry' column rather than individual lat/long columns. I need to add labels for each point onto my map, but since everything is in the 'geometry' column, I do not have the proper inputs for the aes() function, when it asks for 'x' and 'y' values.

My data is currently arranged like this:

Name Description    Island           BeachName Density                       geometry
1  C28             St. Croix          Boiler Bay       B POINT Z (-64.57273 17.75859 0)
2  C27             St. Croix           Brown Bay       A POINT Z (-64.57583 17.75935 0)
3  C39             St. Croix Buck Island Reef NM       C POINT Z (-64.62571 17.78738 0)
4   C1             St. Croix     Sandy Point NWR       C POINT Z (-64.89964 17.67955 0)
5  C10             St. Croix       Rainbow Beach       A POINT Z (-64.88799 17.72994 0)

I have tried using geom_text():

stc_plot <- ggplot() +
    geom_sf(data = stc_land, color = "grey40", fill = "grey80") +
    geom_sf(data = stcdens, aes(size = Density)) +
    geom_text(data = stcdens, aes(label = Name)) +
    labs(size = "Nesting Activities per Year") +
    scale_size_discrete(labels = c("<25", "25-100", "100-500")) +
    theme_classic() +
    theme(legend.position = "bottom")

And I get an error:

     Error in `check_required_aesthetics()`:
! geom_text requires the following missing aesthetics: x and y

Is there a way to get the geometry column to be read out for labels? Or would I need to split that column so that the lat/longs are separate? The geometry column has worked fine for all other aspects of creating this map, its just the labeling that is giving me trouble...

Answer 1

You need to substitute your ggplot2::geom_text() for ggplot2::geom_sf_text() - the sf part is important.

For an example consider this plot of 3 semi random North Carolina cities (did I mention I <3 the nc.shp file?)

library(sf)
library(ggplot2)


shape <- st_read(system.file("shape/nc.shp", package="sf")) # included with sf package

cities <- data.frame(name = c("Raleigh", "Greensboro", "Wilmington"),
                     x = c(-78.633333, -79.819444, -77.912222),
                     y = c(35.766667, 36.08, 34.223333),
                     population = c("high", "medium","low")) %>% 
  st_as_sf(coords = c("x", "y"), crs = 4326) 

ggplot() +
  geom_sf(data = shape, fill = NA) +
  geom_sf_text(data = cities, aes(label = name))