I am trying to compile a list data sources - excluding the US Census - that cover the continental US at the state, county and ZIP/ZCTA level. Any help would be appreciated.

Additional details: I have created an R package that facilitates creating choropleth maps of arbitrary data. As an example, I have built in support for mapping data from the US Census' American Community Survey (ACS).

The feature that I am working on now is facilitating mashups / normalization of user-supplied data sets with census data. This will be very useful for my company (and I suspect any organization which generates data with a geographical component) because we constantly generate data which we aggregate at a geograpic level. For example, Los Angeles County will always have a lot of whatever you are measuring because it is the most populous county. But if you normalize that data on a per-capita basis Los Angeles might actually appear low. That's the sort of insights that I hope to facilitate.

The problem I'm having is creating examples of this feature which I can share with an audience outside my company. I obviously cannot share our internal sales data, and I am having trouble finding data sources outside the US Census that are

  1. Are trustworthy
  2. Would be interesting to make choropleths of at the state, county and zip level
  3. Would be interesting to then choropleth-ize as a mashup of ACS data (e.g. make per capita)
  4. Provide easy access to their data.

Any help would be appreciated.

  • I have two questions: 1. Would you be interested in Census Tract Lever, or Census Block Level information as well? 2. You only mention two sources of information from the Census Bureau, however, there are many more sources of information that from the Census Bureau that are not demographic alone. Would you want those too?
    – Kotebiya
    Commented Mar 9, 2014 at 22:14
  • 1. Right now I am not interested in tract or block level information. 2. I am hoping to find sources outside the census - I've been analyzing those a lot lately.
    – Ari
    Commented Mar 10, 2014 at 1:27
  • I will provide my answer later, but I am thinking that it might be better to include the US Census sources that I am aware of for the sake of others who will use this question later on.
    – Kotebiya
    Commented Mar 10, 2014 at 13:22
  • That sounds good. I have been working with the Census' ACS dataset for a while now, and then to think that that's the totality of the Census' datasets. As you demonstrate below, that is not correct.
    – Ari
    Commented Mar 10, 2014 at 18:03
  • hi, asdfree.com has R code to import and analyze about half of the microdata mentioned on this thread Commented Mar 19, 2016 at 13:46

4 Answers 4

  1. Health
    • Behavioral Risk-Factor Surveillance System (BRFSS) - A health-related survey that asks respondents about health and disease risk factors.
      • Unit of Analysis: County
    • Area Health Resource File (AHRF) - A compilation of Census Bureau demographic information, along with information about hospital utilization, health professionals, and natality/mortality.
      • Unit of Analysis: County
    • Health Professional Shortage Areas (HPSA) - An estimation of areas where the population may be underserved by healthcare systems.
      • Unit of Analysis: Varies from Census Tract to County
    • SNAP Participation - Enrollment Data for the Supplemental Nutritional Assistance Program by Year.
      • Unit of Analysis: County
    • Food Deserts - An analysis of populations that are far from stable food sources, and are thus reasoned to have low access to supply.
      • Unit of Analysis: 2000 & 2010 Census Tract
    • Food Security - Indicators of inequality of access to food sources.
      • Unit of Analysis: County
  2. Crime

    • National Incident Based Reporting System NIBRS - "The National Incident Based Reporting System (NIBRS) is an incident-based reporting system for crimes known to the police. For each crime incident coming to the attention of law enforcement, a variety of data are collected about the incident. These data include the nature and types of specific offenses in the incident, characteristics of the victim(s) and offender(s), types and value of property stolen and recovered, and characteristics of persons arrested in connection with a crime incident."
      • Unit of Analysis: County
  3. Education

    • Integrated Postsecondary Education Data System (IPEDS) - the primary source for data on colleges, universities, and technical and vocational postsecondary institutions in the United States.
    • Common Core of Data (CCD) - "The Common Core of Data (CCD) is the Department of Education's primary database on public elementary and secondary education in the United States. CCD is a comprehensive, annual, national statistical database of all public elementary and secondary schools and school districts, which contains data that are designed to be comparable across all states."
      • Unit of Analysis: Individual Institutions
    • Private School Survey (PSS) - "The target population for the survey consists of all private schools in the U.S. that meet the NCES definition (i.e., a private school is not supported primarily by public funds, provides classroom instruction for one or more of grades K-12 or comparable ungraded levels, and has one or more teachers. Organizations or institutions that provide support for home schooling without offering classroom instruction for students are not included.)."
      • Unit of Analysis: Individual Institutions
  4. Economic

    • Longitudinal Employer-Household Dynamics (LEHD) - This is an extremely useful dataset. Based on data from the Quarterly Census of Employment and Wages, the information published comes in three forms: The LEHD Origin-Destination Dataset (LODES), the Workforce Area Characteristics Dataset (WAC), and the Residence Area Characteristics Dataset (RAC). The WAC posts demographic information on jobholders by the area that their job is located; you will be hard-pressed to find this level of detail ANYWHERE else. The RAC posts demographic information on jobholders by the area that they live in. The LODES indicates the combination of the residence and worksite locations by each jobholder's job.
      • Unit of Analysis: 2000 & 2010 Census Block
    • County and Zip Code Business Patterns (CBP / ZBP) - "County Business Patterns (CBP) is an annual series that provides subnational economic data by industry. This series includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll. This data is useful for studying the economic activity of small areas; analyzing economic changes over time; and as a benchmark for other statistical series, surveys, and databases between economic censuses. Businesses use the data for analyzing market potential, measuring the effectiveness of sales and advertising programs, setting sales quotas, and developing budgets. Government agencies use the data for administration and planning."
      • Unit of Analysis: Zip Code, County, MSA, State
    • Quarterly Workforce Indicators (QWI 1,2) - "The Quarterly Workforce Indicators (QWI) are a set of economic indicators including employment, job creation, earnings, and other measures of employment flows. The QWI are reported using detailed firm characteristics (geography, industry, age, size) and worker demographics information (sex, age, education, race, ethnicity)."
      • Unit of Analysis: County, MSA, State
    • Local Area Unemployment Statistics (LAUS) - A predictive model of county-level unemployment by year. It is based on an estimation using the Current Population Survey, state payroll, and state unemployment insurance sources.
      • Unit of Analysis: County
  5. Migration

  • 1
    Excellent answer. I would vote it up but I don't have enough reputation to do so. I would accept it now, but want to leave it open for a while longer so others can answer.
    – Ari
    Commented Mar 10, 2014 at 18:03
  • what an awesome answer
    – albert
    Commented Apr 29, 2014 at 21:13
  • FRED, from the Federal Reserve Bank of St. Louis offers various economic time-series data on various geographic levels. I personally use these on a county level, where you can find data on: population, unemployment, personal income, labor force, food stamps recipients, poverty, educational attainment, median household income. They also have a very good looking (if somewhat slow...) add-in for Excel, there are various packages for various statistical software to use their data and they provide a direct way of accessing information via an API (I haven't had a chance to use it though). See more here: https://research.stlouisfed.org/fred2/

  • SEER from the National Cancer Institute has great data on a county-year level. these can be easily "converted" (I have a stata do file for that if you want it) to measures such as total county population, county population by gender, race, Hispanic origin, age groups, etc. See more here: http://seer.cancer.gov/popdata/


The Bureau of Labor and Statistics (BLS) has two economic datasets which may be of interest. The monthly Current Population Survey (CPS) of 50,000 households is broken down by region, state and select number of Metropolitan Statistics Areas (MSA).


The monthly Local Area Unemployment Statistics (LAUS) is broken down by MSA and counties.


In both cases, you will need to learn how to parse the raw data files.

Here is the crosswalk file for mapping LAU codes to MSA and counties:


HUD also provides a crosswalk file for mapping USPS Zipcodes to Census geography (tracts, County, CBSA, CD)



Here is another county level BLS dataset: Quarterly Census of Employment and Wages (QCEW). I work for this part of BLS.

QCEW provides employment and wage data by industry at the county, MSA, State, and national levels. Go to http://www.bls.gov/cew/opendata.htm to access the open data version of the dataset. Available for 2012-forward, QCEW open data is a csv-based static API.

We built it with users like you in mind. We are using it as the input for all our future QCEW data front ends, so it has to be great!

If you are doing work in R, see the link on the open data page above to our sample code page. It has R soup starter as well as examples in python, c#, javascript, and other languages.

For data prior to 2012, (back to 1975 at some levels of aggregation), see the flat files available at http://www.bls.gov/cew/datatoc.htm Many of the resources at this location are zip archives of csv files.

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