The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is the principal federal agency responsible for measuring labor market activity, working conditions, and price changes in the economy.
The BLS dataset is used on the occupation and industry pages, showing the publicly available expected growth numbers in both number of employees and salary.
The American Community Survey (ACS) is conducted by the US Census and sent to a portion of the population every year.
The American Community Survey (ACS) Public Use Microdata Sample (PUMS) files are a set of untabulated records about individual people or housing units. The Census Bureau produces the PUMS files so that data users can create custom tables that are not available through pretabulated (or summary) ACS data products.
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.
Census Bureau conducts surveys of the United States Population, including the American Community Survey
The ACS dataset is used on the location, occupation and industry reports. Although the ACS dataset includes some data on occupations and industries, Data USA is mostly using the ACS dataset for demographics on the Geography reports.
The ACS PUMS dataset is used throughout the site where specific data cross sections are not made available through the preformatted ACS dataset. ACS PUMS data is the cornerstone of the occupations and industry data used throughout the Geography, Occupation and Industry reports. Data USA also uses ACS PUMS to compare a location's current stock of graduates versus students currently pursuing high education degrees (provided by the IPEDs dataset).
DataUSA provides access to the CBP data through our API.
Due to sampling constraints, there is often a high margin of error when looking at data for smaller geographies. Apply caution when drawing conclusions from small geographic areas (for example: small counties, places and particularly tracts).
The PUMS dataset is complex. While we have computed aggregations of the data, we run manual spot checks in an attempt to validate our aggregations and calculations. We do not have an independent, automated validation process to verify every calculation, therefore please use particular caution when using the PUMS data on this site.
Similar to the ACS dataset there are sometimes sampling biases when looking at data from a specifc slice of data. Due to the way the data is aggregated, ACS PUMS data is only availabe for the Nation, States and Public Use Microdata Areas (PUMAs).
Wage values are adjusted using the ADJINC variable from the PUMS file.
There are four main universes of tables: "workforce", "full-time" and "part-time". The default and most prevalent universe for our PUMS data uses the workforce universe. The conditions for this universe:
In addition, the above criteria full-time universe rows must have WKHP >= 35, whereas part-time universe rows have WKHP < 35.
The other universe is everyone five years of age and older (that is the only restriction). This universe is only used for visualizations showing birthplaces for a location from PUMS.
Another caveat to note is that when we display top statistics from PUMS data, such as highest average wage, or most common occupation, we will typically only show the top values where several (>= 5) records are collapsed.
For more detailed technical information on the PUMS aggregation methodology, please visit our technical PUMS Aggregation Methodology page.
A collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute to look at the many factors that influence health
The CHR data is used on the geography reports in the health section.
With regard to granularity, the CHR dataset only includes State and County level data. Population estimates for 2016 CHR data are based on 2014 Census population estimates, and 2015 CHR data are based on 2011 Census population estimates.
Additionally, certain indicators are collected at larger time intervals than others, so it is important to note the "Collection Year" in the tooltips, as new reports may utilize older collection data.
Part 1 of the Annual Homeless Assessment Report to Congress (AHAR) provides Point-inTime (PIT) estimates, offering a snapshot of homelessness—both sheltered and unsheltered— on a single night. The PIT counts also provide an estimate of the number of people experiencing homelessness within particular homeless populations, such as people with chronic patterns of homelessness and veterans experiencing homelessness.
Homelessness data is featured in the Health section of the geography reports.
The Freight Analysis Framework (FAF), produced through a partnership between Bureau of Transportation Statistics (BTS) and Federal Highway Administration (FHWA), integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. Starting with data from the 2012 Commodity Flow Survey (CFS) and international trade data from the Census Bureau, FAF incorporates data from agriculture, extraction, utility, construction, service, and other sectors. The FAF data give a picture of which goods are shipped from one region of the US to another region, according to type of commodity, mode of shipment, value, and weight.
Freight Analysis Framework data is used in the Transport section of product reports, as well as the Economy section of geography reports.
DataUSA only provides information from the subset of FAF data where both the origin and destination of the shipment are in the United States. Original product codes (using the SCTG standard) are provided, as well as code equivalents from the NAPCS product code standard. The crosswalk used to apply the NAPCS codes is available here.
IPEDS is the Integrated Postsecondary Education Data System. It is a system of interrelated surveys conducted annually by the U.S. Department of Education’s National Center for Education Statistics (NCES). IPEDS gathers information from every college, university, and technical and vocational institution that participates in the federal student financial aid programs.
The IPEDS dataset is used throughout all the reports but is the cornerstone of the course and university reports. These reports center around a particular postsecondary course or university, combining data from IPEDS with related occupation and industrial data.
State Health Facts provides free, up-to-date, health data for all 50 states, the District of Columbia, the United States, counties, territories, and other geographies.
Various health indicators are featured in the Health section of the geography reports.
The O*Net Skills is a dataset containing detailed descriptions of the required and used skills for specific occupations. The O*Net dataset is sponsored by the United States Department of Labor.
The O*Net Skills dataset is used on both the Occupation and Course reports giving a detailed breakdown of the skills required for the specified occupation or course.
Some occupations do not have directly corresponding data available in O*Net. For more detailed technical information on how we handle these cases, please visit our O*Net Aggregation Methodology page.
USA Spending provides a big-picture view of the federal spending landscape.
Department spending is featured in the product reports.