tongfen (version 0.3.8)

get_tongfen_us_census: Get US census data for 2000 and 2010 census on common census tract based geography

Description

lifecycle::badge("maturing")

This wraps data acquisition via the tidycensus package and tongfen on a common geography into a single convenience function.

Data is only available for the 2000, 2010 and 2020 censuses, the Census Bureau has retired the 1990 API endpoint. To tongfen 1990 data, obtain it elsewhere and combine it with a correspondence table from get_tongfen_correspondence_us_census via tongfen_aggregate.

Usage

get_tongfen_us_census(
  regions,
  meta,
  level = "tract",
  survey = "census",
  base_geo = NULL,
  min_area_share = 0.01,
  sumfile = NULL
)

Value

sf object with (wide form) census variables with census year as suffix (separated by underdcore "_").

Arguments

regions

list with regions to query the data for. At this stage, the only valid list is a vector of states, i.e. `regions = list(state=c("CA","OR"))``

meta

metadata for variables to retrieve

level

aggregation level to return the data on. At this stage, the only valid levels are 'tract' and 'county subdivision'.

survey

survey to get data for, supported options is "census"

base_geo

census year to use as base geography, default is `2010`.

min_area_share

minimum share of area two geographies have to have in common to count as related, default is `0.01`, see get_tongfen_correspondence_us_census.

sumfile

summary file to read the variables from, either a single value used for all censuses or a vector named by dataset, for example `c(dec2010="sf1", dec2020="dhc")`. Default is `NULL`, which leaves the choice to tidycensus. Note that tidycensus defaults the 2020 census to the PL 94-171 redistricting file, most 2020 variables need `sumfile="dhc"`.

Examples

# Get US census data on population and households for 2000 and 2010 censuses on a uniform geography
# based on census tracts.
if (FALSE) {
variables=c(population="H011001",households="H013001")

meta <- c(2000,2010) %>%
  lapply(function(year){
    v <- variables %>% setNames(paste0(names(.),"_",year))
    meta_for_additive_variables(paste0("dec",year),v)
  }) %>%
  bind_rows()
census_data <- get_tongfen_us_census(regions = list(state="CA"), meta=meta, level="tract") %>%
  mutate(change=population_2010/households_2010-population_2000/households_2000)

}