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.

Graph and download economic data for All Employees, Professional, Scientific, and Technical Services (CES6054000001) from Jan 1990 to Apr 2025 about professional, establishment survey, business, services, employment, and USA.

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).

Graph and download economic data for Total Unemployed, Plus All Marginally Attached Workers, Plus Total Employed Part Time for Economic Reasons, as a Percent of the Civilian Labor Force Plus All Marginally Attached Workers for California (U6UNEM6CA) from Q4 2003 to Q3 2024 about marginally attached, part-time, labor underutilization, workers, civilian, 16 years +, labor force, CA, labor, household survey, unemployment, rate, and USA.

New Caledonia NC: Population: Growth data was reported at 1.404 % in 2017. This records a decrease from the previous number of 1.512 % for 2016. New Caledonia NC: Population: Growth data is updated yearly, averaging 1.909 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.411 % in 1970 and a record low of 0.725 % in 1979. New Caledonia NC: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Caledonia – Table NC.World Bank.WDI: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Abstract

This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS)

Documentation

Update frequency: Monthly Dataset source: U.S. Bureau of Labor Statistics Terms of use: 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. See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/bls-public-data/bureau-of-labor-statistics

BPS Projection: Population: Bangka Belitung: 0-4 Years data was reported at 133.900 Person th in 2045. This records an increase from the previous number of 133.400 Person th for 2044. BPS Projection: Population: Bangka Belitung: 0-4 Years data is updated yearly, averaging 125.550 Person th from Dec 2000 (Median) to 2045, with 46 observations. The data reached an all-time high of 133.900 Person th in 2045 and a record low of 90.100 Person th in 2001. BPS Projection: Population: Bangka Belitung: 0-4 Years data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Socio and Demographic – Table ID.GAA003: Population Projection: by Province by Age: Central Bureau of Statistics.

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: April 2025 (preliminary values at the state and 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: May 28th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData 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:

The Statistics and Registration Service Act 2007 required the UK Statistics Authority to publish a Code of Practice for statistics. Only those statistics assessed as compliant with the code will be designated as National Statistics.

The Cabinet Office has made arrangements to implement the code when publishing statistics, as set out in our standards and policies.

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.

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.

Release Date: 2020-06-09.Release Schedule:.The data in this file come from the 2017 Economic Census data files released on a flow basis starting in September 2019. As such, preliminary U.S. totals released in September 2019 will be superseded with final totals, by sector, once data for all states have been released. Users should be aware that during the release of this consolidated file, data at more detailed North American Industry Classification System (NAICS) and geographic levels may not add to higher-level totals. However, at the completion of the economic census (once all the component files have been released), the detailed data in this file will add to the totals. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.U.S. totals released in September 2019 will be superseded with final totals, by sector, once data for all states have been released. .Includes only establishments and firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records: .Number of firms.Number of establishments.Sales, value of shipments, or revenue ($1,000).Annual payroll ($1,000).First-quarter payroll ($1,000).Number of employees.Range indicating percent of total sales, value of shipments, or revenue imputed.Range indicating percent of total annual payroll imputed.Range indicating percent of total employees imputed..Geography Coverage:.The data are shown for employer establishments and firms at the U.S., State, Combined Statistical Area, Metropolitan and Micropolitan Statistical Area, Metropolitan Division, Consolidated City, County (and equivalent), and Economic Place (and equivalent; incorporated and unincorporated) levels that vary by industry. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown at the 2- through 6-digit 2017 NAICS code levels. For information about NAICS, see Economic Census: Technical Documentation: Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector53/EC1753BASIC.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.

About this dataset

Context

The dataset tabulates the population of Parks by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Parks across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 52.97% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Parks is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Parks total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Parks Population by Gender. You can refer the same here

Graph and download economic data for All Employees, Residential Building Construction (CES2023610001) from Jan 1985 to Jun 2025 about establishment survey, buildings, residential, construction, employment, and USA.

The Australian Government Department of Jobs and Small Business publishes a range of labour market data on its Labour Market Information Portal website (lmip.gov.au). The link below provides data from the Labour Force Survey conducted by the Australian Bureau of Statistics. The boundaries used in this survey are known as Statistical Area 4 regions. The data provided includes unemployment rate, employment rate, participation rate, youth unemployment rate, unemployment duration, population by age group and employment by industry and occupation.

Graph and download economic data for All Employees, Skilled Nursing Care Facilities (CES6562310001) from Jan 1990 to Jun 2025 about nursing homes, nursing, health, establishment survey, education, services, employment, and USA.

United States US: Private Credit Bureau Coverage: % of Adults data was reported at 100.000 % in 2017. This stayed constant from the previous number of 100.000 % for 2016. United States US: Private Credit Bureau Coverage: % of Adults data is updated yearly, averaging 100.000 % from Dec 2013 (Median) to 2017, with 5 observations. The data reached an all-time high of 100.000 % in 2017 and a record low of 100.000 % in 2017. United States US: Private Credit Bureau Coverage: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Businesses Registered Statistics. Private credit bureau coverage reports the number of individuals or firms listed by a private credit bureau with current information on repayment history, unpaid debts, or credit outstanding. The number is expressed as a percentage of the adult population.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

About this dataset

Context

The dataset tabulates the population of Lockport town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Lockport town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.3% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Lockport town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Lockport town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Lockport town Population by Gender. You can refer the same here

Graph and download economic data for All Employees, Federal, Except U.S. Postal Service (CES9091100001) from Jan 1939 to Jun 2025 about establishment survey, federal, government, services, employment, and USA.

Investigator(s): United States. Bureau of Justice Statistics Produces annual national- and state-level data on the number of prisoners in state and federal prison facilities. Aggregate data are collected on race and sex of prison inmates, inmates held in private facilities and local jails, system capacity, noncitizens, and persons age 17 or younger. Findings are released in the Prisoners series and the Corrections Statistical Analysis Tool (CSAT) - Prisoners. Data are from the 50 states departments of correction, the Federal Bureau of Prisons, and until 2001, from the District of Columbia (after 2001, felons sentenced under the District of Columbia criminal code were housed in federal facilities).