city_shape_analysis.R

library(tidycensus)
library(tigris)
library(tidyverse)
library(sf)
options(tigris_use_cache = TRUE)
sf_use_s2(FALSE)

top_places <- get_acs(
  geography = "place",
  variables = "B01001_001",
  geometry = TRUE,
  year = 2021,
  survey = "acs1",
  keep_geo_vars = TRUE
) %>%
  filter(LSAD == "25") %>%
  slice_max(estimate, n = 50)

us_tracts <- tracts(cb = TRUE, year = 2021)

intersect_within_ratio <- top_places %>%
  split(~NAME.x) %>%
  imap_dfr(~{

    num_overlaps <- nrow(st_filter(us_tracts, .x, .predicate = st_overlaps))
    num_within <- nrow(st_filter(us_tracts, .x, .predicate = st_within))

    tibble(name = .y,
           inter = num_overlaps + num_within,
           within = num_within) %>%
      mutate(ratio = inter / within) %>%
      rename(City = name,
             `Overlaps or within` = inter,
             `Within only` = within,
             `Ratio` = ratio)

  })