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Get American Community Survey data for New York City

Source: R/get_nyc_acs.R
get_nyc_acs.Rd

A thin wrapper around tidycensus::get_acs() that hard-codes New York City geographies, never downloads geometry, and returns a tidy tibble keyed by geoid (lowercased) with a county column (borough name) ready for joining to the spatial objects in the nycmaps package.

Usage

get_nyc_acs(
  variables,
  year = NULL,
  geography = c("tract", "block group", "county", "puma"),
  survey = "acs5",
  summary_var = NULL,
  output = c("wide", "tidy"),
  ...
)

Arguments

variables

A character vector (optionally named) of Census variable IDs. See load_nyc_variables() or tidycensus::load_variables().

year

ACS endyear. If NULL (the default), uses the tidycensus::get_acs() default, which is the most recent vintage that tidycensus supports.

geography

Geographic level. One of "tract" (default), "block group", "county", or "puma". For "tract", "block group", and "county" the request is restricted to the five NYC counties via tidycensus's county argument. For "puma", tidycensus does not accept a county filter, so all NY state PUMAs are requested and then filtered down to the 55 NYC PUMAs using an internal crosswalk. The crosswalk vintage is chosen from year: ACS endyears up to and including 2021 use the 2010 PUMA vintage, 2022 and later use the 2020 vintage. See nyc_pumas().

survey

ACS sample, passed to tidycensus::get_acs(). Defaults to "acs5".

summary_var

Optional summary (denominator) variable.

output

"wide" (the default) or "tidy". When "wide", the variable column is pivoted out so each variable becomes its own column.

...

Additional arguments forwarded to tidycensus::get_acs().

Value

A tibble with geoid and county as the first two columns, followed by the requested variables. The ACS endyear actually used is stored in the "acs_year" attribute.

See also

get_nyc_decennial(), load_nyc_variables(), nyc_counties(), nyc_pumas()

Examples

if (FALSE) { # \dontrun{
# Median household income, latest 5-year ACS, NYC tracts.
get_nyc_acs(c(med_hhinc = "B19013_001"))

# Same, but at the PUMA level.
get_nyc_acs(
  c(med_hhinc = "B19013_001"),
  geography = "puma"
)

# Same, but one row per borough.
get_nyc_acs(
  c(med_hhinc = "B19013_001"),
  geography = "county"
)

# Race and Hispanic origin, with total population as the denominator.
race_vars <- c(
  nh_white = "B03002_003",
  nh_black = "B03002_004",
  nh_asian = "B03002_006",
  hispanic = "B03002_012"
)
get_nyc_acs(race_vars, summary_var = "B03002_001")
} # }