twin_cities_dot_map.R

library(tidycensus)
library(ggplot2)
library(mapboxapi)
library(sf)
options(tigris_use_cache = TRUE)

# Get the 2020 Census data
# Transform to a projected coordinate reference system
# to improve performance
twin_cities_race <- get_decennial(
  geography = "tract",
  state = "MN",
  county = c("Hennepin", "Ramsey", "Anoka", "Dakota",
             "Scott", "Carver", "Washington"),
  variables = c(
    Hispanic = "P2_002N",
    White = "P2_005N",
    Black = "P2_006N",
    Native = "P2_007N",
    Asian = "P2_008N"
  ),
  year = 2020,
  geometry = TRUE
) %>%
  st_transform(6505)

# Get the basemap (requires a Mapbox access token)
# https://walker-data.com/mapboxapi/reference/mb_access_token.html
basemap <- layer_static_mapbox(
  location = twin_cities_race,
  style_id = "light-v9",
  username = "mapbox"
)

# Generate the dots (faster)
twin_cities_dots <- as_dot_density(
  twin_cities_race,
  value = "value",
  values_per_dot = 200,
  group = "variable"
)

# Generate the dots (slower, but more accurate)
twin_cities_dots_erase <- as_dot_density(
  twin_cities_race,
  value = "value",
  values_per_dot = 200,
  group = "variable",
  erase_water = TRUE,
  area_threshold = 0.95
)

# Map it out
ggplot() + 
  basemap + 
  geom_sf(
    data = twin_cities_dots_erase,
    aes(color = variable),
    shape = "."
  ) + 
  theme_void() + 
  labs(color = "Race/ethnicity,\n2020 Census",
       caption = "Seven-county Twin Cities area | tidycensus R package | 1 dot = 200 people") + 
  scale_color_brewer(palette = "Set1") + 
  guides(color = guide_legend(override.aes = list(shape = 16)))