100+ datasets found
  1. V

    ACS Demographics by Tract

    • data.virginia.gov
    Updated Jan 24, 2025
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    Arlington GIS Portal (2025). ACS Demographics by Tract [Dataset]. https://data.virginia.gov/dataset/acs-demographics-by-tract
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    geojson, arcgis geoservices rest api, html, zip, kml, csvAvailable download formats
    Dataset updated
    Jan 24, 2025
    Dataset provided by
    Arlington County, VA - GIS Mapping Center
    Authors
    Arlington GIS Portal
    Description

    Public demographics data for Arlington County, VA using census tract geometry. Includes fields noting if the statistic is reliable. Data pulled from US Census Bureau, American Community Survey 5-Year Estimates. Table layer has no associated geometry and can be joined to the corresponding tract year.

  2. 2021 American Community Survey: B24090 | SEX BY CLASS OF WORKER FOR THE...

    • data.census.gov
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    ACS, 2021 American Community Survey: B24090 | SEX BY CLASS OF WORKER FOR THE FULL-TIME, YEAR-ROUND CIVILIAN EMPLOYED POPULATION 16 YEARS AND OVER (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2021.B24090
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

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

    Time period covered
    2021
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  3. 2022 American Community Survey: S2408 | Class of Worker by Sex for the...

    • data.census.gov
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    ACS, 2022 American Community Survey: S2408 | Class of Worker by Sex for the Civilian Employed Population 16 Years and Over (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2022.S2408?q=S2408
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

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

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2018-2022 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  4. D

    Census Tract Top 50 American Community Survey Data

    • data.seattle.gov
    • hub.arcgis.com
    • +1more
    application/rdfxml +5
    Updated Feb 3, 2025
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    (2025). Census Tract Top 50 American Community Survey Data [Dataset]. https://data.seattle.gov/dataset/Census-Tract-Top-50-American-Community-Survey-Data/jya9-y5bv/data
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    application/rdfxml, csv, json, application/rssxml, tsv, xmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Description

    Data from: American Community Survey, 5-year Series


    King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 of over 50 attributes of the most requested data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.

    The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades.

    Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

    Vintages: 2010, 2015, 2020, 2021, 2022, 2023
    ACS Table(s): DP02, DP03, DP04, DP05


    The United States Census Bureau's American Community Survey (ACS):
    This 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. 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:
  5. d

    ACS 5-Year Demographic Characteristics DC

    • datasets.ai
    0, 15, 21, 25, 3, 57 +1
    Updated Jun 22, 2022
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    District of Columbia (2022). ACS 5-Year Demographic Characteristics DC [Dataset]. https://datasets.ai/datasets/acs-5-year-demographic-characteristics-dc
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    8, 3, 25, 57, 0, 21, 15Available download formats
    Dataset updated
    Jun 22, 2022
    Dataset authored and provided by
    District of Columbia
    Description

    Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. Current Vintage: 2018-2022. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. 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. Boundaries come from the US Census TIGER geodatabases. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 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). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  6. d

    ACS Housing Characteristics DC Experimental

    • datasets.ai
    • opendata.dc.gov
    • +2more
    0, 15, 21, 25, 3, 57 +1
    Updated Sep 14, 2024
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    District of Columbia (2024). ACS Housing Characteristics DC Experimental [Dataset]. https://datasets.ai/datasets/acs-housing-characteristics-dc-experimental
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    25, 3, 21, 0, 57, 15, 8Available download formats
    Dataset updated
    Sep 14, 2024
    Dataset authored and provided by
    District of Columbia
    Description

    Experimental Occupancy status, Units, Year built, Owner/Renter (Tenure), Mortgage/Rent costs variables. Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data. This includes a limited number of data tables for the nation, states, and the District of Columbia.

    Please visit the following webpage for details. https://www.census.gov/programs-surveys/acs/data/experimental-data.html

    Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. Current Vintage: 2020. ACS Table(s): Housing - Experimental. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: March 18, 2022. National Figures: data.census.gov. 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. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  7. d

    LANGUAGE SPOKEN AT HOME FOR THE POPULATION 5 YEARS AND OVER (C16001)

    • catalog.data.gov
    Updated Jan 31, 2025
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    City of Seattle ArcGIS Online (2025). LANGUAGE SPOKEN AT HOME FOR THE POPULATION 5 YEARS AND OVER (C16001) [Dataset]. https://catalog.data.gov/dataset/language-spoken-at-home-for-the-population-5-years-and-over-c16001
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Table from the American Community Survey (ACS) C16001 of language spoken at home for the population 5 years and over. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): C16001Data downloaded from: <a href='https://data.census.gov/' style='color:rgb(0, 97, 155); text

  8. D

    2020 Census Block Groups Top 50 American Community Survey Data with Seattle...

    • data.seattle.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    application/rdfxml +5
    Updated Feb 3, 2025
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    (2025). 2020 Census Block Groups Top 50 American Community Survey Data with Seattle Neighborhoods [Dataset]. https://data.seattle.gov/dataset/2020-Census-Block-Groups-Top-50-American-Community/b7dx-wq67
    Explore at:
    xml, csv, tsv, json, application/rssxml, application/rdfxmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Area covered
    Seattle
    Description

    U.S. Census Bureau 2020 block groups within the City of Seattle with American Community Survey (ACS) 5-year series data of frequently requested topics. Data is pulled from block group tables for the most recent ACS vintage. Seattle neighborhood geography of Council Districts, Comprehensive Plan Growth Areas are also included based on block group assignment.


    The census block groups have been assigned to a neighborhood based on the distribution of the total population from the 2020 decennial census for the component census blocks. If the majority of the population in the block group were inside the boundaries of the neighborhood, the block group was assigned wholly to that neighborhood.

    Feature layer created for and used in the Neighborhood Profiles application.

    The attribute data associated with this map is updated annually to contain the most currently released American Community Survey (ACS) 5-year data and contains estimates and margins of error. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Vintages: 2023
    ACS Table(s): Select fields from the tables listed here.


    The United States Census Bureau's American Community Survey (ACS):
    This 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. 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:
    • 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 <span style='font-family:inherit; margin:0px;

  9. d

    ACS 5-Year Social Characteristics DC Ward

    • datasets.ai
    0, 15, 21, 25, 3, 57 +1
    Updated Jun 22, 2022
    + more versions
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    District of Columbia (2022). ACS 5-Year Social Characteristics DC Ward [Dataset]. https://datasets.ai/datasets/acs-5-year-social-characteristics-dc-ward
    Explore at:
    15, 57, 3, 8, 25, 21, 0Available download formats
    Dataset updated
    Jun 22, 2022
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    Household type, Education, Disability, Language, Computer/Internet Use, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber]). Current Vintage: 2018-2022. ACS Table(s): DP02. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. 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. Boundaries come from the US Census TIGER geodatabases. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 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). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  10. 2022 American Community Survey: B24080 | Sex by Class of Worker for the...

    • data.census.gov
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    ACS, 2022 American Community Survey: B24080 | Sex by Class of Worker for the Civilian Employed Population 16 Years and Over (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2022.B24080
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

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

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  11. d

    OCCUPATION BY MEDIAN EARNINGS IN THE PAST 12 MONTHS (B24021)

    • catalog.data.gov
    Updated Jan 31, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). OCCUPATION BY MEDIAN EARNINGS IN THE PAST 12 MONTHS (B24021) [Dataset]. https://catalog.data.gov/dataset/occupation-by-median-earnings-in-the-past-12-months-b24021
    Explore at:
    Dataset updated
    Jan 31, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Table from the American Community Survey (ACS) B24021 occupation by median earnings. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B24021<div style=

  12. D

    Selected Economic Characteristics (DP03)

    • data.seattle.gov
    • hub.arcgis.com
    application/rdfxml +5
    Updated Oct 22, 2024
    + more versions
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    (2024). Selected Economic Characteristics (DP03) [Dataset]. https://data.seattle.gov/dataset/Selected-Economic-Characteristics-DP03-/8qgt-awdb
    Explore at:
    json, csv, application/rdfxml, application/rssxml, xml, tsvAvailable download formats
    Dataset updated
    Oct 22, 2024
    Description

    Data from: American Community Survey, 5-year Series


    King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 from the U.S. Census Bureau's demographic profile of Selected Economic Characteristics (DP03). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.

    The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades.

    Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

    Vintages: 2010, 2015, 2020, 2021, 2022, 2023
    ACS Table(s): DP03


    The United States Census Bureau's American Community Survey (ACS):
    This 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. 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:
    • 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

  13. A

    ‘Income - ACS 2015-2019 - Tempe Tracts’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Dec 10, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Income - ACS 2015-2019 - Tempe Tracts’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-income-acs-2015-2019-tempe-tracts-ceb1/d959d0db/?iid=003-039&v=presentation
    Explore at:
    Dataset updated
    Dec 10, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Income - ACS 2015-2019 - Tempe Tracts’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/67536dc9-838b-44c0-bfaf-55ba748711ce on 11 February 2022.

    --- Dataset description provided by original source is as follows ---

    Notice: The U.S. Census Bureau is delaying the release of the 2016-2020 ACS 5-year data until March 2022. For more information, please read the Census Bureau statement regarding this matter.

    -----------------------------------------


    This layer shows household income ranges for households, families, married couple families, and nonfamily households (as defined by the U.S. Census). Data is from US Census American Community Survey (ACS) 5-year estimates and joined with Tempe census tracts.


    This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online).


    Layer includes:

    · Total households (of various types including households, families, married couple families, and nonfamily households as defined by the U.S. Census)

    · Household income brackets

    · Household median income in dollars

    · Household mean income in dollars


    An 'N' entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).


    Data is from US Census American Community Survey (ACS) 5-year estimates.


    Current Vintage
    : 2015-2019

    ACS Table(s): S1901 (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 Census update: December 10, 2020

    National Figures: data.census.gov

    --- Original source retains full ownership of the source dataset ---

  14. 2022 American Community Survey: B24090 | Sex by Class of Worker for the...

    • data.census.gov
    + more versions
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    ACS, 2022 American Community Survey: B24090 | Sex by Class of Worker for the Full-Time, Year-Round Civilian Employed Population 16 Years and Over (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2022.B24090?tid=ACSDT5Y2022.B24090
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

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

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2018-2022 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  15. d

    Demographic Characteristics of DC (District-wide) 2022 1-Year ACS

    • datasets.ai
    21, 3
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    District of Columbia, Demographic Characteristics of DC (District-wide) 2022 1-Year ACS [Dataset]. https://datasets.ai/datasets/demographic-characteristics-of-dc-district-wide-2022-1-year-acs
    Explore at:
    3, 21Available download formats
    Dataset authored and provided by
    District of Columbia
    Description

    Age, Sex, Race, and Ethnicity variables from the 1-Year ACS

    Contact: District of Columbia, Office of Planning. Email: planning@dc.gov

    Geography: District of Columbia

    Current Vintage: 2022

    ACS Table(s): DP05

    Data downloaded from: Census Bureau's API for American Community Survey

    Date of API call: January 2, 2024

    National Figures: data.census.gov

    The United States Census Bureau's American Community Survey (ACS):

    This 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. 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 September. The layer always contains the latest available ACS 1-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. 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 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).
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Data processed using R statistical package and ArcGIS Desktop.
    • Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  16. A

    ACS-ED 2014-2018 Children-Enrolled Public: Demographic Characteristics...

    • data.amerigeoss.org
    • s.cnmilf.com
    • +1more
    Updated Feb 18, 2022
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    United States (2022). ACS-ED 2014-2018 Children-Enrolled Public: Demographic Characteristics (CDP05) [Dataset]. https://data.amerigeoss.org/dataset/acs-ed-2014-2018-children-enrolled-public-demographic-characteristics-cdp05-7aead
    Explore at:
    kml, geojson, arcgis geoservices rest api, zip, csv, htmlAvailable download formats
    Dataset updated
    Feb 18, 2022
    Dataset provided by
    United States
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACS


    Annotation values are negative value representations of estimates and have values when non-integer information needs to be represented. See the table below for a list of common Estimate/Margin of Error (E/M) values and their corresponding Annotation (EA/MA) values.

    All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

    -9

    An '-9' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.

    -8

    An '-8' means that the estimate is not applicable or not available.

    -6

    A '-6' entry in the estimate column indicates that 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.

    -5

    A '-5' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.

    -3

    A '-3' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.

    -2

    A '-2' entry in 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.

  17. d

    Technology Access Computers - 2017-2021 - ACS - TempeTracts

    • datasets.ai
    • data-academy.tempe.gov
    • +8more
    15, 21, 25, 3, 57, 8
    Updated Dec 8, 2022
    + more versions
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    City of Tempe (2022). Technology Access Computers - 2017-2021 - ACS - TempeTracts [Dataset]. https://datasets.ai/datasets/technology-access-computers-2017-2021-acs-tempetracts
    Explore at:
    8, 21, 25, 15, 3, 57Available download formats
    Dataset updated
    Dec 8, 2022
    Dataset authored and provided by
    City of Tempe
    Description

    This layer shows Technology Access by Household.

    Data is from US Census American Community Survey (ACS) 5-year estimates.

    This layer represents the underlying data for several data visualizations on the Tempe Equity Map.

    Data visualized as a percent of total households in given census tract.

    Layer includes:

    Key demographics
    • Total Households
    • % With a Desktop or Laptop Computer
    • % With only a Desktop or Laptop
    • % With a Smartphone
    • % With only a Smartphone
    • % With a Tablet
    • % With only a tablet
    • % With other type of computing device
    • % With other type of computing device only
    • % No computer
    Current Vintage: 2017-2021
    ACS Table(s): S2801 (Not all lines of this ACS table are available in this feature layer.)
    Date of Census update: Dec 8, 2022
    Data Preparation: Data table downloaded and joined with Census Tract boundaries that are within or adjacent to the City of Tempe boundary
    National Figures: data.census.gov
  18. d

    POVERTY STATUS OF THE POPULATION (B17001)

    • catalog.data.gov
    Updated Jan 31, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). POVERTY STATUS OF THE POPULATION (B17001) [Dataset]. https://catalog.data.gov/dataset/poverty-status-of-the-population-b17001
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Table from the American Community Survey (ACS) B17001 poverty status of the population. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): <a href='https://data.census.gov/all?q=b17001' style='font-family:inherit;'

  19. d

    ACS 5-Year Housing Characteristics DC Ward

    • datasets.ai
    0, 15, 21, 25, 3, 57 +1
    Updated Jun 22, 2022
    + more versions
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    District of Columbia (2022). ACS 5-Year Housing Characteristics DC Ward [Dataset]. https://datasets.ai/datasets/acs-5-year-housing-characteristics-dc-ward
    Explore at:
    0, 57, 15, 21, 25, 3, 8Available download formats
    Dataset updated
    Jun 22, 2022
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    Occupancy status, Units, Rooms, Year built, Owner/Renter (Tenure), Mortgage/Rent costs, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber])Current Vintage: 2018-2022 ACS Table(s): DP04. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. 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. Boundaries come from the US Census TIGER geodatabases. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 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). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  20. d

    Demographic Characteristics of DC Wards 2018-2022 5-Year ACS

    • datasets.ai
    21, 3
    + more versions
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    District of Columbia, Demographic Characteristics of DC Wards 2018-2022 5-Year ACS [Dataset]. https://datasets.ai/datasets/demographic-characteristics-of-dc-wards-2018-2022-5-year-acs
    Explore at:
    3, 21Available download formats
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data.

    Contact: District of Columbia, Office of Planning. Email: planning@dc.gov

    Geography: 2022 Wards (State Legislative Districts [Upper Chamber])

    Current Vintage: 2018-2022

    ACS Table(s): DP05

    Data downloaded from: Census Bureau's API for American Community Survey

    Date of API call: January 2, 2024

    National Figures: data.census.gov

    The United States Census Bureau's American Community Survey (ACS):

    This 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. 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. 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 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).
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Data processed using R statistical package and ArcGIS Desktop.
    • Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

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Arlington GIS Portal (2025). ACS Demographics by Tract [Dataset]. https://data.virginia.gov/dataset/acs-demographics-by-tract

ACS Demographics by Tract

Explore at:
geojson, arcgis geoservices rest api, html, zip, kml, csvAvailable download formats
Dataset updated
Jan 24, 2025
Dataset provided by
Arlington County, VA - GIS Mapping Center
Authors
Arlington GIS Portal
Description

Public demographics data for Arlington County, VA using census tract geometry. Includes fields noting if the statistic is reliable. Data pulled from US Census Bureau, American Community Survey 5-Year Estimates. Table layer has no associated geometry and can be joined to the corresponding tract year.

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