Closed MicheleTobias closed 2 years ago
TidyCensus has the following options for the dataset parameter:
dataset = c("sf1", "sf2", "sf3", "sf4", "pl", "as", "gu", "mp", "vi", "acs1", "acs3",
"acs5", "acs1/profile", "acs3/profile", "acs5/profile", "acs1/subject",
"acs3/subject", "acs5/subject", "acs1/cprofile", "acs5/cprofile")
But what do these mean? The Census' Data Table contains the answers (but, WOW! is this a lot of data that's hard to read).
sf1 - Decennial Census Summary File 1 - detailed tables focusing on age, sex, households, families, and housing units
sf2 - Decennial Census Summary File 2 - population characteristics, such as sex, age, average household size, household type, and relationship to householder such as nonrelative or child. The file includes housing characteristics, such as tenure (whether a housing unit is owner-occupied or renter-occupied), age of householder, and household size for occupied housing units
sf3 - Decennial Census Summary File 3 - in-depth population and housing data
sf4 - Decennial Census Summary File 4 -
pl - Redistricting Data ("Public Law 94-171")
as - Decennial Census for American Samoa
gu - Decennial Census for Guam
mp - Decennial Census for The Commonwealth of the Northern Mariana Islands
vi - Decennial Census for The U.S. Virgin Islands
"acs" is for the American Community Survey (yearly census updates) 1, 3, or 5 refers to the year return interval for that dataset (1-Year, 3-Year, or 5-Year)
acs1 acs3 acs5
In the Census' Data Table, the Decennial Census tables start with dec>
and ACS starts with acs>
"profile" - data profiles as counts and percentages
acs1/profile acs3/profile acs5/profile
"subject" - "Subject tables provide an overview of the estimates available in a particular topic"
acs1/subject acs3/subject acs5/subject
"cprofile" - comparison profiles = like the profiles tables, but also has comparisons to the previous year
acs1/cprofile acs5/cprofile
PR has separate tables
The Tidy Census package can include the geometries for the rows it returns, so this issue is solved.
TidyCensus R package resources: