Nothing
# create sample data
library(dplyr)
library(tidycensus)
library(tigris)
library(sf)
# download median income data
get_acs(year = 2017, geography = "tract", variables = "B19019_001", state = 29, county = 510) %>%
select(GEOID, estimate) %>%
rename(medInc = estimate) -> medianInc
# download race data
get_acs(year = 2017, geography = "tract", table = "B02001", state = 29, county = 510, output = "wide") %>%
select(GEOID, B02001_001E, B02001_002E) %>%
rename(total = B02001_001E, white = B02001_002E) %>%
mutate(pctWhite = white/total*100) %>%
select(GEOID, pctWhite) -> race
# download tract geometry
tracts <- tracts(state = 29, county = 510, class = "sf") %>%
select(GEOID)
# combine tract data with geometry
tracts <- tracts %>%
left_join(., race, by = "GEOID") %>%
left_join(., medianInc, by = "GEOID")
stl_race_income <- tracts
usethis::use_data(stl_race_income, overwrite = TRUE)
stl_race_income_point <- st_centroid(stl_race_income)
usethis::use_data(stl_race_income_point, overwrite = TRUE)
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