57 datasets found
  1. USA Bureau of Labor Statistics

    • kaggle.com
    zip
    Updated Aug 30, 2019
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    US Bureau of Labor Statistics (2019). USA Bureau of Labor Statistics [Dataset]. https://www.kaggle.com/bls/bls
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Aug 30, 2019
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    US Bureau of Labor Statistics
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    The Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

    Content

    Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

    Update Frequency: Monthly

    Querying BigQuery Tables

    Fork this kernel to get started.

    Acknowledgements

    https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

    https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

    Dataset Source: http://www.bls.gov/data/

    This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

    Banner Photo by Clark Young from Unsplash.

    Inspiration

    What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

  2. Bureau of Labor Statistics Monthly Unemployment (latest 14 months)

    • legacy-cities-lincolninstitute.hub.arcgis.com
    • resilience.climate.gov
    • +5more
    Updated Aug 16, 2022
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    Esri (2022). Bureau of Labor Statistics Monthly Unemployment (latest 14 months) [Dataset]. https://legacy-cities-lincolninstitute.hub.arcgis.com/maps/993b8c64a67a4c6faa44a91846547786
    Explore at:
    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: May 2025 (preliminary values at the county level) The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: July 18th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and County NationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS"s county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova. As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties. To better understand the different labor force statistics included in this map, see the diagram below from BLS:

  3. Occupational Employment and Wage Statistics (OES)

    • catalog.data.gov
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). Occupational Employment and Wage Statistics (OES) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oes
    Explore at:
    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

  4. F

    All Employees, Federal

    • fred.stlouisfed.org
    json
    Updated Aug 1, 2025
    + more versions
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    (2025). All Employees, Federal [Dataset]. https://fred.stlouisfed.org/series/CES9091000001
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 1, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for All Employees, Federal (CES9091000001) from Jan 1939 to Jul 2025 about establishment survey, federal, government, employment, and USA.

  5. F

    All Employees, Manufacturing

    • fred.stlouisfed.org
    json
    Updated Aug 1, 2025
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    (2025). All Employees, Manufacturing [Dataset]. https://fred.stlouisfed.org/series/MANEMP
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 1, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Jul 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

  6. Occupational Outlook Handbook

    • catalog.data.gov
    • gimi9.com
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). Occupational Outlook Handbook [Dataset]. https://catalog.data.gov/dataset/occupational-outlook-handbook-51009
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Occupational Outlook Handbook (OOH) is a nationally recognized source of career information, designed to provide valuable assistance to individuals making decisions about their future work lives. The Handbook is revised every two years. The OOH offers information on the hundreds of occupations that provide the majority of jobs in the United States. Each occupational profile describes the typical duties performed by the occupation, the work environment of that occupation, the typical education and training needed to enter the occupation, the median pay for workers in the occupation, and the job outlook over the coming decade for that occupation. For information on occupations, please visit: https://www.bls.gov/ooh/

  7. Current Employment Statistics - Employment, Hours, and Earnings - State and...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated May 16, 2022
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    Bureau of Labor Statistics (2022). Current Employment Statistics - Employment, Hours, and Earnings - State and Metro Area [Dataset]. https://catalog.data.gov/dataset/current-employment-statistics-employment-hours-and-earnings-state-and-metro-area-b02b3
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Current Employment Statistics (CES) program produces detailed industry estimates of employment, hours, and earnings of workers on nonfarm payrolls. CES State and Metro Area produces data for all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, and about 450 metropolitan areas and divisions. Each month, CES surveys approximately 142,000 businesses and government agencies, representing 689,000 individual worksites. For more information and data, visit: https://www.bls.gov/sae/

  8. Occupation, Salary and Likelihood of Automation

    • kaggle.com
    Updated May 24, 2020
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    Larxel (2020). Occupation, Salary and Likelihood of Automation [Dataset]. https://www.kaggle.com/andrewmvd/occupation-salary-and-likelihood-of-automation/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 24, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Larxel
    Description

    About this Dataset

    This dataset combines automation probability data with a breakdown of the number of jobs and salary in each occupation by state within the USA. Automation probability was acquired from the work of Carl Benedikt Freyand Michael A. Osborne; State employment data is from the Bureau of Labor Statistics. Note that for simplicity of analysis, all jobs where data was not available or there were less than 10 employees were marked as zero.

    How to Cite this Dataset

    If you use this dataset in your research, please credit the authors.

    Salary Data

    @misc{u.s. bureau of labor statistics, title={Occupational Employment Statistics}, url={https://www.bls.gov/oes/current/oes_nat.htm}, journal={U.S. BUREAU OF LABOR STATISTICS}}

    Automation Data

    @article{frey_osborne_2017, title={The future of employment: How susceptible are jobs to computerisation?}, volume={114}, DOI={10.1016/j.techfore.2016.08.019}, journal={Technological Forecasting and Social Change}, author={Frey, Carl Benedikt and Osborne, Michael A.}, year={2017}, pages={254–280}}

    License

    License was not specified at the source.

    Splash Banner

    Photo by Alex Knight on Unsplash

  9. d

    Current Employment Statistics (CES), Annual Average

    • catalog.data.gov
    • data.ca.gov
    Updated Jul 23, 2025
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    California Employment Development Department (2025). Current Employment Statistics (CES), Annual Average [Dataset]. https://catalog.data.gov/dataset/current-employment-statistics-ces-annual-average-1990-2019
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    Dataset updated
    Jul 23, 2025
    Dataset provided by
    California Employment Development Department
    Description

    This dataset contains annual average CES data for California statewide and areas from 1990 to 2023. The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States. CES data reflect the number of nonfarm, payroll jobs. It includes the total number of persons on establishment payrolls, employed full- or part-time, who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

  10. US Unemployment Rate by County, 1990-2016

    • kaggle.com
    zip
    Updated May 22, 2017
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    Jay Ravaliya (2017). US Unemployment Rate by County, 1990-2016 [Dataset]. https://www.kaggle.com/jayrav13/unemployment-by-county-us
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    zip(12879595 bytes)Available download formats
    Dataset updated
    May 22, 2017
    Authors
    Jay Ravaliya
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    Context

    This is a dataset that I built by scraping the United States Department of Labor's Bureau of Labor Statistics. I was looking for county-level unemployment data and realized that there was a data source for this, but the data set itself hadn't existed yet, so I decided to write a scraper and build it out myself.

    Content

    This data represents the Local Area Unemployment Statistics from 1990-2016, broken down by state and month. The data itself is pulled from this mapping site:

    https://data.bls.gov/map/MapToolServlet?survey=la&map=county&seasonal=u

    Further, the ever-evolving and ever-improving codebase that pulled this data is available here:

    https://github.com/jayrav13/bls_local_area_unemployment

    Acknowledgements

    Of course, a huge shoutout to bls.gov and their open and transparent data. I've certainly been inspired to dive into US-related data recently and having this data open further enables my curiosities.

    Inspiration

    I was excited about building this data set out because I was pretty sure something similar didn't exist - curious to see what folks can do with it once they run with it! A curious question I had was surrounding Unemployment vs 2016 Presidential Election outcome down to the county level. A comparison can probably lead to interesting questions and discoveries such as trends in local elections that led to their most recent election outcome, etc.

    Next Steps

    Version 1 of this is as a massive JSON blob, normalized by year / month / state. I intend to transform this into a CSV in the future as well.

  11. Bureau of Labor Statistics Mass Layoffs Data

    • datalumos.org
    Updated Apr 17, 2025
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    United States Department of Labor. Bureau of Labor Statistics (2025). Bureau of Labor Statistics Mass Layoffs Data [Dataset]. http://doi.org/10.3886/E227061V1
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    Dataset updated
    Apr 17, 2025
    Dataset provided by
    United States Department of Laborhttp://www.dol.gov/
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The Mass Layoff Statistics program is a Federal-State cooperative statistical effort which uses a standardized, automated approach to identify, describe, and track the effects of major job cutbacks, using data from each State's unemployment insurance database. Establishments which have at least 50 initial claims for unemployment insurance (UI) filed against them during a consecutive 5-week period are contacted by State agencies to determine whether those separations are of at least 31 days duration, and, if so, information is obtained on the total number of persons separated, the reasons for these separations, and recall expectations. Establishments are identified according to industry classification and location, and unemployment insurance claimants are identified by such demographic characteristics as age, race, sex, ethnic group, and place of residence. The program yields information on an individual's entire spell of unemployment, to the point when regular unemployment insurance benefits are exhausted. It provides databases of establishments and claimants, both of which are used for further research and analysis. Data available Monthly data report summary information on all establishments which have at least 50 initial claims for unemployment insurance (UI) filed against them during a 5-week period. Data are available for 50 States, the District of Columbia, and Puerto Rico, as well as by industry. Quarterly data report on private sector nonfarm establishments which have at least 50 initial claims filed against them during a 5-week period and where the employer indicates that 50 or more people were separated from their jobs for at least 31 days. Information is obtained on the total number of persons separated; the reasons for separation; worksite closures; recall expectations; and socioeconomic characteristics on UI claimants such as gender, age, race, and residency. These characteristics are collected at two points in time when an initial claim is filed and when the claimant exhausts regular UI benefits. In between these points, the unemployment status of claimants is tracked through the monitoring of certifications for unemployment (continued claims) filed under the regular State UI program. Data are available for 50 States, the District of Columbia, and Puerto Rico, as well as by industry. Coverage Monthly, quarterly, and annual data for 50 States, the District of Columbia, and Puerto Rico. Monthly data are available since April 1995; quarterly data since second quarter 1995.

  12. Occupational Employment and Wage Statistics (OEWS)

    • catalog.data.gov
    • data.ca.gov
    Updated Jul 23, 2025
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    California Employment Development Department (2025). Occupational Employment and Wage Statistics (OEWS) [Dataset]. https://catalog.data.gov/dataset/occupational-employment-and-wage-statistics-oews-4b4c4
    Explore at:
    Dataset updated
    Jul 23, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    The Occupational Employment and Wage Statistics (OEWS) Survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). The BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OEWS survey make these estimates possible. The OEWS survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for approximately 830 occupations. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series. The OEWS estimates are published annually. SOURCE: https://www.bls.gov/oes/oes_emp.htm

  13. Employment Projections

    • catalog.data.gov
    • data.wu.ac.at
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statistics (2022). Employment Projections [Dataset]. https://catalog.data.gov/dataset/employment-projections-c37a6
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Employment Projections (EP) program develops information about the labor market for the Nation as a whole for 10 years in the future. For more information visit: https://www.bls.gov/emp/

  14. d

    Department of Labor, Office of Research (Current Employment Statistics NSA...

    • catalog.data.gov
    • data.ct.gov
    • +3more
    Updated Aug 9, 2024
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    data.ct.gov (2024). Department of Labor, Office of Research (Current Employment Statistics NSA 1990 - Current) [Dataset]. https://catalog.data.gov/dataset/department-of-labor-office-of-research-current-employment-statistics-nsa-1990-current
    Explore at:
    Dataset updated
    Aug 9, 2024
    Dataset provided by
    data.ct.gov
    Description

    Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

  15. O

    Employment and Labor Force - Annual

    • data.mesaaz.gov
    • citydata.mesaaz.gov
    application/rdfxml +5
    Updated Sep 4, 2020
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    Economic Development (2020). Employment and Labor Force - Annual [Dataset]. https://data.mesaaz.gov/w/f7ya-r76p/c963-au5t?cur=q7naPUufrhp&from=HTJy7vlIDlB
    Explore at:
    csv, application/rdfxml, json, tsv, application/rssxml, xmlAvailable download formats
    Dataset updated
    Sep 4, 2020
    Dataset authored and provided by
    Economic Development
    Description

    Historical information on the Employment Dataset shows several current and historical annual statistics regarding population, the labor force, employment and unemployment in the City of Mesa. Monthly labor force, employment and unemployment information is at https://citydata.mesaaz.gov/External-Data/Employment-and-Labor-Force-Monthly/3vbg-xf63.

    Sources: Population Data - United States Census Bureau -https://www.census.gov/topics/population/data.html Employment Data - Bureau of Labor Statistics - http://www.bls.gov/data/ Local Area Unemployment Statistics (LAUS) - https://www.bls.gov/lau/ To see how these terms are defined and what they include, please visit the Terms Glossary from the United State Department of Labor’s Bureau of Labor Statistics (BLS), which can be found at the following web address: http://www.bls.gov/bls/glossary.htm

  16. Data from: Quarterly Census of Employment and Wages

    • icpsr.umich.edu
    Updated Oct 22, 2015
    + more versions
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    United States Department of Labor. Bureau of Labor Statistics (2015). Quarterly Census of Employment and Wages [Dataset]. https://www.icpsr.umich.edu/web/NADAC/studies/36312
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    Dataset updated
    Oct 22, 2015
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/36312/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36312/terms

    Area covered
    United States
    Description

    The Quarterly Census of Employment and Wages (QCEW) program is a cooperative program involving the Bureau of Labor Statistics (BLS) of the United States Department of Labor and the State Employment Security Agencies (SESAs). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by State unemployment insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Publicly available data files include information on the number of establishments, monthly employment, and quarterly wages, by NAICS industry, by county, by ownership sector, for the entire United States. These data are aggregated to annual levels, to higher industry levels (NAICS industry groups, sectors, and supersectors), and to higher geographic levels (national, State, and Metropolitan Statistical Area (MSA)). To download and analyze QCEW data, users can begin on the QCEW Databases page. Downloadable data are available in formats such as text and CSV. Data for the QCEW program that are classified using the North American Industry Classification System (NAICS) are available from 1990 forward, and on a more limited basis from 1975 to 1989. These data provide employment and wage information for arts-related NAICS industries, such as: Arts, entertainment, and recreation (NAICS Code 71) Performing arts and spectator sports Museums, historical sites, zoos, and parks Amusements, gambling, and recreation Professional, scientific, and technical services (NAICS Code 54) Architectural services Graphic design services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, book and music stores Book, periodical, and music stores Art dealers For years 1975-2000, data for the QCEW program provide employment and wage information for arts-related industries are based on the Standard Industrial Classification (SIC) system. These arts-related SIC industries include the following: Book stores (SIC 5942) Commercial photography (SIC Code 7335) Commercial art and graphic design (SIC Code 7336) Museums, Botanical, Zoological Gardens (SIC Code 84) Dance studios, schools, and halls (SIC Code 7911) Theatrical producers and services (SIC Code 7922) Sports clubs, managers, & promoters (SIC Code 7941) Motion Picture Services (SIC Code 78) The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit NAICS industry at the national, state, and county levels. At the national level, the QCEW program provides employment and wage data for almost every NAICS industry. At the State and area level, the QCEW program provides employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. Employment data under the QCEW program represent the number of covered workers who worked during, or received pay for, the pay period including the 12th of the month. Excluded are members of the armed forces, the self-employed, proprietors, domestic workers, unpaid family workers, and railroad workers covered by the railroad unemployment insurance system. Wages represent total compensation paid during the calendar quarter, regardless of when services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging, and in some States, contributions to deferred compensation plans (such as 401(k) plans). The QCEW program does provide partial information on agricultural industries and employees in private households. Data from the QCEW program serve as an important source for many BLS programs. The QCEW data are used as the benchmark source for employment by the Current Employment Statistics program and the Occupational Employment Statistics program. The UI administrative records collected under the QCEW program serve as a sampling frame for BLS establishment surveys. In addition, data from the QCEW program serve as a source to other Federal and State programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses QCEW data as the base for developing the wage and salary component of personal income. The Employment and Training Administration (ETA) of the Department of Labor and the SESAs use QCEW data to administer the employment security program. The QCEW data accurately reflect the ex

  17. Data from: Local Area Unemployment Statistics

    • data.dathere.com
    • data-dathere.dataops.dathere.com
    csv
    Updated Jul 25, 2025
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    U.S. Bureau of Labor Statistics (2025). Local Area Unemployment Statistics [Dataset]. https://data.dathere.com/dataset/local-area-unemployment-statistics
    Explore at:
    csv(4801174), csv(4788043), csv(4810648), csv(4793023), csv(1845128), csv(4836677), csv(4466614), csv(4783189), csv(4843692), csv(4785781), csv(4085274), csv(4796908), csv(4782783), csv(4834794), csv(4786086), csv(4790323)Available download formats
    Dataset updated
    Jul 25, 2025
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    U.S. Bureau of Labor Statistics
    Description

    Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

    These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

  18. Local Area Unemployment Statistics (LAUS), Annual Average

    • catalog.data.gov
    • data.ca.gov
    Updated Jul 23, 2025
    + more versions
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    California Employment Development Department (2025). Local Area Unemployment Statistics (LAUS), Annual Average [Dataset]. https://catalog.data.gov/dataset/local-area-unemployment-statistics-laus-annual-average
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    Dataset updated
    Jul 23, 2025
    Dataset provided by
    Employment Development Departmenthttp://www.edd.ca.gov/
    Description

    This dataset contains the Local Area Unemployment Statistics (LAUS), annual averages from 1990 to 2024. The Local Area Unemployment Statistics (LAUS) program is a Federal-State cooperative effort in which monthly estimates of total employment and unemployment are prepared for approximately 7,600 areas, including counties, cities and metropolitan statistical areas. These estimates are key indicators of local economic conditions. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS. Estimates for counties are produced through a building-block approach known as the "Handbook method." This procedure also uses data from several sources, including the CPS, the CES program, state UI systems, and the Census Bureau's American Community Survey (ACS), to create estimates that are adjusted to the statewide measures of employment and unemployment. Estimates for cities are prepared using disaggregation techniques based on inputs from the ACS, annual population estimates, and current UI data.

  19. Wage Estimates

    • kaggle.com
    zip
    Updated Jun 29, 2017
    + more versions
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    US Bureau of Labor Statistics (2017). Wage Estimates [Dataset]. https://www.kaggle.com/bls/wage-estimates
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    zip(4529907 bytes)Available download formats
    Dataset updated
    Jun 29, 2017
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Authors
    US Bureau of Labor Statistics
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context:

    The Occupational Employment Statistics (OES) and National Compensation Survey (NCS) programs have produced estimates by borrowing from the strength and breadth of each survey to provide more details on occupational wages than either program provides individually. Modeled wage estimates provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical location. The job characteristics include bargaining status (union and nonunion), part- and full-time work status, incentive- and time-based pay, and work levels by occupation.

    Direct estimates are based on survey responses only from the particular geographic area to which the estimate refers. In contrast, modeled wage estimates use survey responses from larger areas to fill in information for smaller areas where the sample size is not sufficient to produce direct estimates. Modeled wage estimates require the assumption that the patterns to responses in the larger area hold in the smaller area.

    The sample size for the NCS is not large enough to produce direct estimates by area, occupation, and job characteristic for all of the areas for which the OES publishes estimates by area and occupation. The NCS sample consists of 6 private industry panels with approximately 3,300 establishments sampled per panel, and 1,600 sampled state and local government units. The OES full six-panel sample consists of nearly 1.2 million establishments.

    The sample establishments are classified in industry categories based on the North American Industry Classification System (NAICS). Within an establishment, specific job categories are selected to represent broader occupational definitions. Jobs are classified according to the Standard Occupational Classification (SOC) system.

    Content:

    Summary: Average hourly wage estimates for civilian workers in occupations by job characteristic and work levels. These data are available at the national, state, metropolitan, and nonmetropolitan area levels.

    Frequency of Observations: Data are available on an annual basis, typically in May.

    Data Characteristics: All hourly wages are published to the nearest cent.

    Acknowledgements:

    This dataset was taken directly from the Bureau of Labor Statistics and converted to CSV format.

    Inspiration:

    This dataset contains the estimated wages of civilian workers in the United States. Wage changes in certain industries may be indicators for growth or decline. Which industries have had the greatest increases in wages? Combine this dataset with the Bureau of Labor Statistics Consumer Price Index dataset and find out what kinds of jobs you would need to afford your snacks and instant coffee!

  20. US Bureau Of Labor Statistics Injury And Illness Data By Industry

    • johnsnowlabs.com
    csv
    Updated Nov 5, 2018
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    John Snow Labs (2018). US Bureau Of Labor Statistics Injury And Illness Data By Industry [Dataset]. https://www.johnsnowlabs.com/marketplace/us-bureau-of-labor-statistics-injury-and-illness-data-by-industry/
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    csvAvailable download formats
    Dataset updated
    Nov 5, 2018
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    2016
    Area covered
    United States
    Description

    This dataset contains non-fatal injury and illness data by industry from US Bureau of Labor Statistics for 2016. The industries are classified according to the North American Industry Classification System (NAICS).

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US Bureau of Labor Statistics (2019). USA Bureau of Labor Statistics [Dataset]. https://www.kaggle.com/bls/bls
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USA Bureau of Labor Statistics

USA Bureau of Labor Statistics (BigQuery Dataset)

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317 scholarly articles cite this dataset (View in Google Scholar)
zip(0 bytes)Available download formats
Dataset updated
Aug 30, 2019
Dataset provided by
Bureau of Labor Statisticshttp://www.bls.gov/
Authors
US Bureau of Labor Statistics
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

Context

The Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

Content

Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

Update Frequency: Monthly

Querying BigQuery Tables

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

Dataset Source: http://www.bls.gov/data/

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Clark Young from Unsplash.

Inspiration

What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

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