ha, neat! at the moment, this is all the code it takes to do it from scratch (windy city or anywhere else!). All you'd need to do is swap out the NLCD raster for a building layer or similar (though i dont have building footprint/non-building logic as i think you linked)
![python code to create dot density map using the geosnap and tobler packages
import geosnap as gsp
from tobler.dasymetric import masked_dot_density
raster = "s3://spatial-ucr/nlcd/landcover/nlcd_landcover_2021.tif"
cols = [
"n_nonhisp_white_persons",
"n_nonhisp_black_persons",
"n_hispanic_persons",
"n_asian_persons",
]
chi = gsp.io.get_acs(gsp.DataStore(), msa_fips="16980", years=2021)
chi_race_density = masked_dot_density(
chi, raster=raster, categories=cols, scale=0.4, pixel_values=[22, 23, 24]
)
chi_race_density.sample(frac=1).lb.explore("category", cmap="rainbow")](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:ndb5mcf73s6g5fmys4u2clag/bafkreih3bwsaxclch6556mzjqijtnqk2prfqzfu2rcdl6idi4koy4mtdfu)
