tidycensus (version 1.6.7)

get_decennial: Obtain data and feature geometry for the decennial US Census

Description

Obtain data and feature geometry for the decennial US Census

Usage

get_decennial(
  geography,
  variables = NULL,
  table = NULL,
  cache_table = FALSE,
  year = 2020,
  sumfile = NULL,
  state = NULL,
  county = NULL,
  geometry = FALSE,
  output = "tidy",
  keep_geo_vars = FALSE,
  shift_geo = FALSE,
  summary_var = NULL,
  pop_group = NULL,
  pop_group_label = FALSE,
  key = NULL,
  show_call = FALSE,
  ...
)

Value

a tibble or sf tibble of decennial Census data

Arguments

geography

The geography of your data.

variables

Character string or vector of character strings of variable IDs.

table

The Census 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 for which you are requesting data. Defaults to 2020; 2000, 2010, and 2020 are available.

sumfile

The Census summary file; if NULL, defaults to "pl" when the year is 2020 and "sf1" for 2000 and 2010. Not all summary files are available for each decennial Census year. Make sure you are using the correct summary file for your requested variables, as variable IDs may be repeated across summary files and represent different topics.

state

The state 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.

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.

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.

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 decennial Census to be included in your output. Usually a variable (e.g. total population) that you'll want to use as a denominator or comparison.

pop_group

The population group code for which you'd like to request data. Applies to summary files for which population group breakdowns are available like the Detailed DHC-A file.

pop_group_label

If TRUE, return a "pop_group_label" column that contains the label for the population group. Defaults to FALSE.

key

Your Census API key. Obtain one at https://api.census.gov/data/key_signup.html

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

Examples

if (FALSE) {
# Plot of race/ethnicity by county in Illinois for 2010
library(tidycensus)
library(tidyverse)
library(viridis)
census_api_key("YOUR KEY GOES HERE")
vars10 <- c("P005003", "P005004", "P005006", "P004003")

il <- get_decennial(geography = "county", variables = vars10, year = 2010,
                    summary_var = "P001001", state = "IL", geometry = TRUE) %>%
  mutate(pct = 100 * (value / summary_value))

ggplot(il, aes(fill = pct, color = pct)) +
  geom_sf() +
  facet_wrap(~variable)


}