20 datasets found
  1. o

    Bureau of Labor Statistics - Salinas Non-Farm Employment Data 1999-2024

    • cityofsalinas.opendatasoft.com
    csv, excel, json
    Updated Sep 27, 2024
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    (2024). Bureau of Labor Statistics - Salinas Non-Farm Employment Data 1999-2024 [Dataset]. https://cityofsalinas.opendatasoft.com/explore/dataset/bls-smu06415000000000001/
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    json, csv, excelAvailable download formats
    Dataset updated
    Sep 27, 2024
    License

    https://wiki.creativecommons.org/wiki/public_domainhttps://wiki.creativecommons.org/wiki/public_domain

    Area covered
    Salinas
    Description

    This dataset from the Bureau of Labor Statistics's State and Metro Area Employment, Hours, & Earnings data contains non-farm, non-seasonally adjusted employment data for Salinas from January 1999 to August 2024.This dataset is part of the Bureau of Labor Statistic's Current Employment Statistics (CES) program. The CES program is a monthly survey conducted by the Bureau of Labor Statistics. It is a federal and state cooperative program that provides employment, hours, and earnings estimates for states and metropolitan areas based on payroll records of business establishments.

  2. l

    Australian Bureau of Statistics Labour Force API

    • devweb.dga.links.com.au
    api
    Updated May 5, 2025
    + more versions
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    Department of Government Services (2025). Australian Bureau of Statistics Labour Force API [Dataset]. https://devweb.dga.links.com.au/data/dataset/australian-bureau-of-statistics-labour-force-api
    Explore at:
    apiAvailable download formats
    Dataset updated
    May 5, 2025
    Dataset authored and provided by
    Department of Government Services
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    Australia
    Description

    This RESTful API provides Australian Bureau of Statistics (ABS) labour force data such as employment statistics by region, sex, age groups, and labour utilisation using original, seasonally adjusted and trend markers since 1978. It connects to an existing ABS API and improves the usability of the information queried from ABS by transforming the SDMX formatted data into a JSON format. This allows developers to consume ABS data easily by using a standard format without requiring time-consuming reformatting and transformation of the data received. Version 1.0.0 An API key will be issued if you wish to explore and understand the way this API operates. Access for this API is available via request through developer.vic.gov.au.

  3. T

    Vital Signs: Income (Median by Workplace) – Bay Area

    • data.bayareametro.gov
    application/rdfxml +5
    Updated May 2, 2019
    + more versions
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    U.S. Census Bureau: American Community Survey (2019). Vital Signs: Income (Median by Workplace) – Bay Area [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Income-Median-by-Workplace-Bay-Area/kjfs-sujy
    Explore at:
    json, csv, tsv, application/rdfxml, xml, application/rssxmlAvailable download formats
    Dataset updated
    May 2, 2019
    Dataset authored and provided by
    U.S. Census Bureau: American Community Survey
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR Income (EC5)

    FULL MEASURE NAME Worker income by workplace (earnings)

    LAST UPDATED October 2016

    DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

    DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org

    U.S. Census Bureau: American Community Survey Form B08521 (2006-2015; place of employment) http://api.census.gov

    Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2015; specific to each metro area) http://data.bls.gov

    CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.

    Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

  4. T

    Vital Signs: Income (Median by Place of Residence) – by metro

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Aug 10, 2019
    + more versions
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    (2019). Vital Signs: Income (Median by Place of Residence) – by metro [Dataset]. https://data.bayareametro.gov/w/5ubk-6knb/default?cur=_SrO6sTLT4O
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    application/rssxml, csv, application/rdfxml, xml, json, tsvAvailable download formats
    Dataset updated
    Aug 10, 2019
    Description

    VITAL SIGNS INDICATOR Income (EC4)

    FULL MEASURE NAME Household income by place of residence

    LAST UPDATED May 2019

    DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

    DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org

    U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov

    Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.

    Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

  5. T

    Vital Signs: Income (Median by Place of Residence) – Bay Area

    • data.bayareametro.gov
    • open-data-demo.mtc.ca.gov
    application/rdfxml +5
    Updated Jul 10, 2019
    + more versions
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    (2019). Vital Signs: Income (Median by Place of Residence) – Bay Area [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Income-Median-by-Place-of-Residence-Ba/hp78-6nm2
    Explore at:
    application/rssxml, csv, xml, application/rdfxml, tsv, jsonAvailable download formats
    Dataset updated
    Jul 10, 2019
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR Income (EC4)

    FULL MEASURE NAME Household income by place of residence

    LAST UPDATED May 2019

    DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

    DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org

    U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov

    Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.

    Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

  6. Sweat and Toil API

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Aug 21, 2022
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    Bureau of International Labor Affairs (2022). Sweat and Toil API [Dataset]. https://catalog.data.gov/dataset/sweat-and-toil-api-8545b
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    Dataset updated
    Aug 21, 2022
    Dataset provided by
    Bureau of International Labor Affairshttp://www.dol.gov/ilab/
    Description

    These datasets contain information on child labor and forced labor worldwide from ILAB’s three flagship reports: Findings on the Worst Forms of Child Labor; List of Goods Produced by Child Labor or Forced Labor; and List of Products Produced by Forced or Indentured Child Labor. There are 14 tables containing data from the 2015-2019 reporting cycles and 11 tables from the 2014 reporting cycle. ILAB plans to update the structure of the API. This information is also available in ILAB’s app, Sweat & Toil: Child Labor, Forced Labor, and Human Trafficking Around the World. For more information, see ILAB’s International Child Labor and Forced Labor Reports page. https://www.dol.gov/agencies/ilab/resources/reports/child-labor/findings https://developer.dol.gov/others/sweat-and-toil/

  7. 2010-2014 ACS Earnings by Occupation Variables - Boundaries

    • hub.arcgis.com
    • mapdirect-fdep.opendata.arcgis.com
    • +1more
    Updated Nov 30, 2020
    + more versions
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    Esri (2020). 2010-2014 ACS Earnings by Occupation Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/1c70912bc6c8478e838f67d217e01e51
    Explore at:
    Dataset updated
    Nov 30, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows median earnings by occupational group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B24021 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  8. M

    Vital Signs: Rent Payments – by metro

    • open-data-demo.mtc.ca.gov
    • data.bayareametro.gov
    application/rdfxml +5
    Updated Aug 21, 2019
    + more versions
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    U.S. Census Bureau: American Community Survey (2019). Vital Signs: Rent Payments – by metro [Dataset]. https://open-data-demo.mtc.ca.gov/widgets/4bdz-ebsj
    Explore at:
    json, csv, tsv, xml, application/rssxml, application/rdfxmlAvailable download formats
    Dataset updated
    Aug 21, 2019
    Dataset authored and provided by
    U.S. Census Bureau: American Community Survey
    Description

    VITAL SIGNS INDICATOR Rent Payments (EC8)

    FULL MEASURE NAME Median rent payment

    LAST UPDATED August 2019

    DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time.

    DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a

    U.S. Census Bureau: American Community Survey 2005-2017 http://api.census.gov Note: Form B25058; 1-YR

    Bureau of Labor Statistics: Consumer Price Index 1970-2017 http://www.bls.gov/data/ Note: All Urban Consumers Data Table (by metro)

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

    Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

  9. ACS Earnings by Occupation Variables - Centroids

    • mapdirect-fdep.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Oct 20, 2018
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    Esri (2018). ACS Earnings by Occupation Variables - Centroids [Dataset]. https://mapdirect-fdep.opendata.arcgis.com/maps/f58f4bebb8ed416dba8668d8cf39553c
    Explore at:
    Dataset updated
    Oct 20, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows median earnings by occupational group. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B24021Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  10. 2010-2014 ACS Earnings by Occupation by Sex Variables - Boundaries

    • hub.arcgis.com
    • mapdirect-fdep.opendata.arcgis.com
    Updated Nov 30, 2020
    + more versions
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    Esri (2020). 2010-2014 ACS Earnings by Occupation by Sex Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/7d5bd40589b948588c4a55515aa771b6
    Explore at:
    Dataset updated
    Nov 30, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows median earnings by occupational group broken down by sex. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B24022 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  11. Better Trade Tool API

    • catalog.data.gov
    Updated Apr 8, 2025
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    Bureau of International Labor Affairs (2025). Better Trade Tool API [Dataset]. https://catalog.data.gov/dataset/better-trade-tool-api
    Explore at:
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    Bureau of International Labor Affairshttp://www.dol.gov/ilab/
    Description

    These datasets match information on child labor and forced labor worldwide from ILAB’s three flagship reports (Findings on the Worst Forms of Child Labor; List of Goods Produced by Child Labor or Forced Labor; and List of Products Produced by Forced or Indentured Child Labor) with U.S. import trade data, including Harmonized Tariff Schedule Codes, to empower users to advance efforts in supply chain transparency as well as strategic sourcing priorities. There are 3 tables combining data from ILAB’s essential reporting with U.S. import trade data.

  12. T

    Vital Signs: Jobs by Wage Level - Metro

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 18, 2019
    + more versions
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    (2019). Vital Signs: Jobs by Wage Level - Metro [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Jobs-by-Wage-Level-Metro/bt32-8udw
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    csv, tsv, application/rssxml, application/rdfxml, xml, jsonAvailable download formats
    Dataset updated
    Jan 18, 2019
    Description

    VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

    FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

    LAST UPDATED January 2019

    DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

    DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

    American Community Survey (2001-2017) http://api.census.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

    Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

    Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

    Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

    In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

  13. 2022 Economic Census: EC2221LOCMINE | Mining: Location of Mining...

    • data.census.gov
    Updated Dec 6, 2024
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    ECN (2024). 2022 Economic Census: EC2221LOCMINE | Mining: Location of Mining Establishments by Employment Size for the U.S., States, and Offshore Areas: 2022 (ECN Sector Statistics Economic Census: Mining: Location of Mines by Employment Size for Subsectors and Industries for the U.S., States, and Offshore Areas) [Dataset]. https://data.census.gov/table/ECNLOCMINE2022.EC2221LOCMINE
    Explore at:
    Dataset updated
    Dec 6, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Area covered
    United States
    Description

    Key Table Information.Table Title.Mining: Location of Mining Establishments by Employment Size for the U.S., States, and Offshore Areas: 2022.Table ID.ECNLOCMINE2022.EC2221LOCMINE.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Economic Census: Mining: Location of Mines by Employment Size for Subsectors and Industries for the U.S., States, and Offshore Areas.Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-05-15.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Employment size of establishmentsNumber of establishmentsDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S., State, and Offshore Area levels that vary by industry. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 6-digit 2022 NAICS code levels for U.S., States, and Offshore Area. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector21/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - 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 applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of sy...

  14. 2017 Economic Census: EC1721LOCMINE | Mining: Location of Mining...

    • data.census.gov
    Updated Apr 21, 2016
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    ECN (2016). 2017 Economic Census: EC1721LOCMINE | Mining: Location of Mining Establishments by Employment Size for the U.S., States, and Offshore Areas: 2017 (ECN Sector Statistics Mining: Location of Mines by Employment Size for Subsectors and Industries for the U.S., States, and Offshore Areas) [Dataset]. https://data.census.gov/table/ECNLOCMINE2017.EC1721LOCMINE?q=Florida+Rock+Industries+Inc+++Georgia+Division+Offices++Forest+Park
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    Dataset updated
    Apr 21, 2016
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Area covered
    United States
    Description

    Release Date: 2021-01-28.Release Schedule:.The data in this file come from the 2017 Economic Census. For information about economic census planned data products releases, see Economic Census: About: 2017 Release Schedule...Key Table Information:.Includes only establishments of firms with payroll. .Data may be subject to employment-and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records:.Employment size of establishments.Number of establishments..Geography Coverage:.The data are shown for employer establishments and firms for the U.S., States, and Offshore Area levels at the U.S. 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 U.S., States, and Offshore Area. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists. ..Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector21/EC1721LOCMINE.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.

  15. 2017 Economic Census: EC1723LOCCONS | Construction: Location of Construction...

    • data.census.gov
    Updated Apr 21, 2016
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    ECN (2016). 2017 Economic Census: EC1723LOCCONS | Construction: Location of Construction Establishments by Employment Size for the U.S. and States: 2017 (ECN Sector Statistics Construction: Location of Construction Establishments by Employment Size for the U.S. and States) [Dataset]. https://data.census.gov/table/ECNLOCCONS2017.EC1723LOCCONS?q=M+A+BUILDING+CONTRACTORS
    Explore at:
    Dataset updated
    Apr 21, 2016
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Area covered
    United States
    Description

    Release Date: 2021-01-28.Release Schedule:.The data in this file come from the 2017 Economic Census. For information about economic census planned data products releases, see Economic Census: About: 2017 Release Schedule...Key Table Information:.Includes only establishments of firms with payroll. .Data may be subject to employment-and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records:.Employment size of establishments.Number of establishments..Geography Coverage:.The data are shown for employer establishments and firms for the U.S. and States levels at the U.S. 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 U.S. and States. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists. ..Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector23/EC1723LOCCONS.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.

  16. 2017 Economic Census: EC1731LOCMFG | Manufacturing: Location of...

    • data.census.gov
    Updated Jan 28, 2021
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    ECN (2021). 2017 Economic Census: EC1731LOCMFG | Manufacturing: Location of Manufacturing Establishments by Employment Size for the U.S., States, and Counties: 2017 (ECN Sector Statistics Manufacturing: Location of Manufacturing Establishments by Employment Size for the U.S., States, and Counties) [Dataset]. https://data.census.gov/table/ECNLOCMFG2017.EC1731LOCMFG?q=Gil's+Tire+Ctr
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    Dataset updated
    Jan 28, 2021
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Area covered
    United States
    Description

    Release Date: 2021-01-28.Release Schedule:.The data in this file come from the 2017 Economic Census. For information about economic census planned data products releases, see Economic Census: About: 2017 Release Schedule...Key Table Information:.Includes only establishments of firms with payroll. .Data may be subject to employment-and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records:.Employment size of establishments.Number of establishments..Geography Coverage:.The data are shown for employer establishments and firms for the U.S., States, and County levels at the U.S. 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 U.S. and States; and at the 2- through 3-digit 2017 NAICS code levels for Counties. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists. ..Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector31/EC1731LOCMFG.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.

  17. 2017 Economic Census: EC1742EMPFUNC | Wholesale Trade: Employment by Primary...

    • data.census.gov
    Updated Apr 21, 2016
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    ECN (2016). 2017 Economic Census: EC1742EMPFUNC | Wholesale Trade: Employment by Primary Function for the U.S.: 2017 (ECN Sector Statistics Wholesale Trade: Employment by Primary Function for the U.S.) [Dataset]. https://data.census.gov/table/ECNEMPFUNC2017.EC1742EMPFUNC?g=010XX00US&n=4238501
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    Dataset updated
    Apr 21, 2016
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Area covered
    United States
    Description

    Release Date: 2021-02-18.Release Schedule:.The data in this file come from the 2017 Economic Census. For information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments of firms with payroll...Data Items and Other Identifying Records:.Number of establishments.Annual payroll ($1,000).Number of employees.Response coverage of employment by function inquiry (%)..Geography Coverage:.The data are shown for employer establishments of firms at the U.S. level only. 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 7-digit and selected 8-digit 2017 NAICS code levels. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector42/EC1742EMPFUNC.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.

  18. 2017 Economic Census: EC1781LABOR | Other Services (Except Public...

    • data.census.gov
    Updated Apr 22, 2021
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    ECN (2021). 2017 Economic Census: EC1781LABOR | Other Services (Except Public Administration): Sales, Value of Shipments, or Revenue from Labor Charges and Parts Installed for Repair and Maintenance Services for the U.S.: 2017 (ECN Sector Statistics Other Services (Except Public Administration): Sales, Value of Shipments, or Revenue from Labor Charges and Parts Installed for Repair and Maintenance Services for the U.S.) [Dataset]. https://data.census.gov/all/tables?q=Samuel%20Glass
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    Dataset updated
    Apr 22, 2021
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Area covered
    United States
    Description

    Release Date: 2021-04-22.Release Schedule:.The data in this file come from the 2017 Economic Census. For information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments of firms with payroll...Data Items and Other Identifying Records:.Number of establishments.Sales, value of shipments, or revenue ($1,000).Sales, value of shipments, or revenue of the NAPCS products relating to this inquiry ($1,000).Distribution of sales, value of shipments, or revenue of the NAPCS products (%).Response coverage of type of repair inquiry (%)..Geography Coverage:.The data are shown for employer establishments of firms at the U.S. level only. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown at the 4- through 6-digit 2017 NAICS code levels starting with NAICS code 811. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector81/EC1781LABOR.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.

  19. 2010-2014 ACS Employment Status Variables - Boundaries

    • hub.arcgis.com
    Updated Nov 18, 2020
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    Esri (2020). 2010-2014 ACS Employment Status Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/37298cf9033741a383aa4e9c025caf58
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    Dataset updated
    Nov 18, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows hours worked, and those unemployed and not in labor force. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of unemployed population within the civilian labor force. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B23020, B23025 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 11, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  20. 2022 Economic Census: EC2200SIZEEMPEST | Selected Sectors: Employment Size...

    • data.census.gov
    Updated Dec 6, 2024
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    ECN (2024). 2022 Economic Census: EC2200SIZEEMPEST | Selected Sectors: Employment Size of Establishments for the U.S.: 2022 (ECN Core Statistics Economic Census: Establishment and Firm Size Statistics for the U.S.) [Dataset]. https://data.census.gov/table/ECNSIZE2022.EC2200SIZEEMPEST
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    Dataset updated
    Dec 6, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Area covered
    United States
    Description

    Key Table Information.Table Title.Selected Sectors: Employment Size of Establishments for the U.S.: 2022.Table ID.ECNSIZE2022.EC2200SIZEEMPEST.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Economic Census: Establishment and Firm Size Statistics for the U.S..Source.U.S. Census Bureau, 2022 Economic Census, Core Statistics.Release Date.2025-04-24.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of firmsNumber of establishmentsSales, value of shipments, or revenue ($1,000)Annual payroll ($1,000)First-quarter payroll ($1,000)Number of employeesValue added ($1,000)Operating expenses ($1,000)Total inventories, beginning of year ($1,000)Total inventories, end of year ($1,000)Range indicating imputed percentage of total sales, value of shipments, or revenueRange indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. levels only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 6-digit 2022 NAICS code levels for all economic census sectors except Agriculture (11) and Management of Companies and Enterprises (55). For information about NAICS, see Economic Census Code Lists..Business Characteristics.For Wholesale Trade (42), data are presented by Type of Operation (All establishments; Merchant Wholesalers, except Manufacturers’ Sales Branches and Offices; and Manufacturers’ Sales Branches and Offices)..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector00/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or ...

  21. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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(2024). Bureau of Labor Statistics - Salinas Non-Farm Employment Data 1999-2024 [Dataset]. https://cityofsalinas.opendatasoft.com/explore/dataset/bls-smu06415000000000001/

Bureau of Labor Statistics - Salinas Non-Farm Employment Data 1999-2024

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json, csv, excelAvailable download formats
Dataset updated
Sep 27, 2024
License

https://wiki.creativecommons.org/wiki/public_domainhttps://wiki.creativecommons.org/wiki/public_domain

Area covered
Salinas
Description

This dataset from the Bureau of Labor Statistics's State and Metro Area Employment, Hours, & Earnings data contains non-farm, non-seasonally adjusted employment data for Salinas from January 1999 to August 2024.This dataset is part of the Bureau of Labor Statistic's Current Employment Statistics (CES) program. The CES program is a monthly survey conducted by the Bureau of Labor Statistics. It is a federal and state cooperative program that provides employment, hours, and earnings estimates for states and metropolitan areas based on payroll records of business establishments.

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