Obtain data and feature geometry for the American Community Survey

get_acs(
  geography,
  variables = NULL,
  table = NULL,
  cache_table = FALSE,
  year = 2022,
  output = "tidy",
  state = NULL,
  county = NULL,
  zcta = NULL,
  geometry = FALSE,
  keep_geo_vars = FALSE,
  shift_geo = FALSE,
  summary_var = NULL,
  key = NULL,
  moe_level = 90,
  survey = "acs5",
  show_call = FALSE,
  ...
)

Arguments

geography: The geography of your data.
variables: Character string or vector of character strings of variable IDs. tidycensus automatically returns the estimate and the margin of error associated with the variable.
table: The ACS table for which you would like to request all variables. Uses lookup tables to identify the variables; performs faster when variable table already exists through load_variables(cache = TRUE). Only one table may be requested per call.
cache_table: Whether or not to cache table names for faster future access. Defaults to FALSE; if TRUE, only needs to be called once per dataset. If variables dataset is already cached via the load_variables function, this can be bypassed.
year: The year, or endyear, of the ACS sample. 5-year ACS data is available from 2009 through 2022; 1-year ACS data is available from 2005 through 2022, with the exception of 2020. Defaults to 2022.
output: One of "tidy" (the default) in which each row represents an enumeration unit-variable combination, or "wide" in which each row represents an enumeration unit and the variables are in the columns.
state: An optional vector of states for which you are requesting data. State names, postal codes, and FIPS codes are accepted. Defaults to NULL.
county: The county for which you are requesting data. County names and FIPS codes are accepted. Must be combined with a value supplied to `state`. Defaults to NULL.
zcta: The zip code tabulation area(s) for which you are requesting data. Specify a single value or a vector of values to get data for more than one ZCTA. Numeric or character ZCTA GEOIDs are accepted. When specifying ZCTAs, geography must be set to `"zcta"` and `state` must be specified with `county` left as `NULL`. Defaults to NULL.
geometry: if FALSE (the default), return a regular tibble of ACS data. if TRUE, uses the tigris package to return an sf tibble with simple feature geometry in the `geometry` column.
keep_geo_vars: if TRUE, keeps all the variables from the Census shapefile obtained by tigris. Defaults to FALSE.
shift_geo: (deprecated) if TRUE, returns geometry with Alaska and Hawaii shifted for thematic mapping of the entire US. Geometry was originally obtained from the albersusa R package. As of May 2021, we recommend using tigris::shift_geometry() instead.
summary_var: Character string of a "summary variable" from the ACS to be included in your output. Usually a variable (e.g. total population) that you'll want to use as a denominator or comparison.
key: Your Census API key. Obtain one at https://api.census.gov/data/key_signup.html
moe_level: The confidence level of the returned margin of error. One of 90 (the default), 95, or 99.
survey: The ACS contains one-year, three-year, and five-year surveys expressed as "acs1", "acs3", and "acs5". The default selection is "acs5."
show_call: if TRUE, display call made to Census API. This can be very useful in debugging and determining if error messages returned are due to tidycensus or the Census API. Copy to the API call into a browser and see what is returned by the API directly. Defaults to FALSE.
...: Other keyword arguments

Value

A tibble or sf tibble of ACS data

Examples

if (FALSE) { # \dontrun{
library(tidycensus)
library(tidyverse)
library(viridis)
census_api_key("YOUR KEY GOES HERE")

tarr <- get_acs(geography = "tract", variables = "B19013_001",
                state = "TX", county = "Tarrant", geometry = TRUE, year = 2020)

ggplot(tarr, aes(fill = estimate, color = estimate)) +
  geom_sf() +
  coord_sf(crs = 26914) +
  scale_fill_viridis(option = "magma") +
  scale_color_viridis(option = "magma")


vt <- get_acs(geography = "county", variables = "B19013_001", state = "VT", year = 2019)

vt %>%
mutate(NAME = gsub(" County, Vermont", "", NAME)) %>%
 ggplot(aes(x = estimate, y = reorder(NAME, estimate))) +
  geom_errorbar(aes(xmin = estimate - moe, xmax = estimate + moe), width = 0.3, size = 0.5) +
  geom_point(color = "red", size = 3) +
  labs(title = "Household income by county in Vermont",
       subtitle = "2015-2019 American Community Survey",
       y = "",
       x = "ACS estimate (bars represent margin of error)")

} # }