Finding ACS variable names for tidycensus in R

Hello!

I am working on a research project that involves collecting 28 variables from ACS data. I have been working with tidycensus and have figured out my R code to get me what I want in Rstudio, but I cannot find an extensive list of variable names to input in the get_acs(....variables=XYZ) function. When I use the load_variables function, I feel like I am either not getting the full list or the variable is too granular. For example, I need to know what percentage of people have a bachelor's degree or higher at the census tract level, but the ACS5 variables break it down too far (age, gender, etc.). I found a couple for my table, but not for all of the ones I need. I have looked to see if the online ACS data tables had it listed next to the variable description and couldn't find it.

My ask is: does anyone know the ACS variable names for these? and/or where I can find them on the census website? I'm looking for 2021 ACS 5-year estimate data. 

Indicator_Calculation ACS_Name
Percent labor force employed DP03_0004E
Percent employed Armed Forces  DP03_0006E
GINI coefficient of income equality B19083_001E
Population who are foreign-born and moved to US in previous 5 years per 1000 population
Percent population born in a state that still resides in that state
Percent voter participation in a Presidential election (Precinct level data)
Percent labor force employed
Percent population not employed in farming, fishing, forestry, extractive, and tourism industries
Average sales volume divided by number of businesses 
Percent employed Armed Forces 
Percent housing units that are not mobile homes
Vacant rental units per 1000 population
Hospital beds per 1000 population
Percent housing units built before 1970 or after 2000 
Number of hotels/motels per 1000 population
Number of public schools per 1000 population
Number of actual connections per 1000 households 
Percent population with broadband internet subscription 
Absolute value of population change base year/current year
Percent population with college education or more
Percent population between 18 to 65 years old 
Percent households with at least one vehicle
Percent households with telephone service available
Percent population that are proficient English speakers
Percent population without a sensory, physical, or mental disability
Percent of the population (under 65) with health insurance coverage
GINI coefficient of income equality
Percent of absolute difference between male median annual earnings and female median annual earnings divided by annual income 

Thanks very much!

-A stressed PhD student

Parents
  • Very good question. Field desc are often terrible and you would need the universe. I don't have the answer but have wanted to do a mapping with all the field names. There are pieces of the puzzle here and there but no comprehensive data dictionary.  I still load a desc file for every single table I want to pull. I pull some of that data (although at the county level, also no R just API). for example; https://api.census.gov/data/2021/acs/acs5?get=B29002_001E,B29002_002E,B29002_003E,B29002_004E,B29002_005E,B29002_006E,B29002_007E,B29002_008E,NAME&for=county:* 

    pulls all the ed levels for all counties. I am not an expert here, but I am fairly sure that asking for foreign born and moved at the tract level will give you null values or -99999999 or -666666666 etc. as diff tables respond differently (R may do this much better).  So, I think that understanding what data is available before you tie yourself to a specific variable is critical. I think I may have around half of your list with table and field name if that will help. I usually spend time on this over the weekend and I have a new grandchild keeping me busy.  Again not an expert but I could give you around 100 ACS field names for everything I pull, might give you around half of what you need.

Reply
  • Very good question. Field desc are often terrible and you would need the universe. I don't have the answer but have wanted to do a mapping with all the field names. There are pieces of the puzzle here and there but no comprehensive data dictionary.  I still load a desc file for every single table I want to pull. I pull some of that data (although at the county level, also no R just API). for example; https://api.census.gov/data/2021/acs/acs5?get=B29002_001E,B29002_002E,B29002_003E,B29002_004E,B29002_005E,B29002_006E,B29002_007E,B29002_008E,NAME&for=county:* 

    pulls all the ed levels for all counties. I am not an expert here, but I am fairly sure that asking for foreign born and moved at the tract level will give you null values or -99999999 or -666666666 etc. as diff tables respond differently (R may do this much better).  So, I think that understanding what data is available before you tie yourself to a specific variable is critical. I think I may have around half of your list with table and field name if that will help. I usually spend time on this over the weekend and I have a new grandchild keeping me busy.  Again not an expert but I could give you around 100 ACS field names for everything I pull, might give you around half of what you need.

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