92 datasets found
  1. d

    DC Health Planning Neighborhoods to Census Tracts

    • catalog.data.gov
    • datasets.ai
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    Updated Feb 4, 2025
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    D.C. Office of the Chief Technology Officer (2025). DC Health Planning Neighborhoods to Census Tracts [Dataset]. https://catalog.data.gov/dataset/dc-health-planning-neighborhoods-to-census-tracts-24ba6
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Area covered
    Washington
    Description

    This dataset contains polygons that represent the boundaries of statistical neighborhoods as defined by the DC Department of Health (DC Health). DC Health delineates statistical neighborhoods to facilitate small-area analyses and visualization of health, economic, social, and other indicators to display and uncover disparate outcomes among populations across the city. The neighborhoods are also used to determine eligibility for some health services programs and support research by various entities within and outside of government. DC Health Planning Neighborhood boundaries follow census tract 2010 lines defined by the US Census Bureau. Each neighborhood is a group of between one and seven different, contiguous census tracts. This allows for easier comparison to Census data and calculation of rates per population (including estimates from the American Community Survey and Annual Population Estimates). These do not reflect precise neighborhood locations and do not necessarily include all commonly-used neighborhood designations. There is no formal set of standards that describes which neighborhoods are included in this dataset. Note that the District of Columbia does not have official neighborhood boundaries. Origin of boundaries: each neighborhood is a group of between one and seven different, contiguous census tracts. They were originally determined in 2015 as part of an analytical research project with technical assistance from the Centers for Disease Control and Prevention (CDC) and the Council for State and Territorial Epidemiologists (CSTE) to define small area estimates of life expectancy. Census tracts were grouped roughly following the Office of Planning Neighborhood Cluster boundaries, where possible, and were made just large enough to achieve standard errors of less than 2 for each neighborhood's calculation of life expectancy. The resulting neighborhoods were used in the DC Health Equity Report (2018) with updated names. HPNs were modified slightly in 2019, incorporating one census tract that was consistently suppressed due to low numbers into a neighboring HPN (Lincoln Park incorporated into Capitol Hill). Demographic information were analyzed to identify the bordering group with the most similarities to the single census tract. A second change split a neighborhood (GWU/National Mall) into two to facilitate separate analysis.

  2. d

    ACS 5-Year Economic Characteristics DC

    • catalog.data.gov
    • opdatahub.dc.gov
    Updated Mar 4, 2025
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    City of Washington, DC (2025). ACS 5-Year Economic Characteristics DC [Dataset]. https://catalog.data.gov/dataset/acs-5-year-economic-characteristics-dc
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    Dataset updated
    Mar 4, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, 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: District-wide. Current Vintage: 2019-2023. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. 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.

  3. d

    Census Tracts in 1990

    • opendata.dc.gov
    • catalog.data.gov
    • +2more
    Updated Jun 19, 2006
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    City of Washington, DC (2006). Census Tracts in 1990 [Dataset]. https://opendata.dc.gov/datasets/DCGIS::census-tracts-in-1990/about
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    Dataset updated
    Jun 19, 2006
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Census Year 1990 Tract Polygons. This dataset contains polygon features, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. 2000 census tracts are identical to 1990 census tracts, except in instances where multiple tracts were merged to form one new tract. Census tracts were identified from maps provided by the U.S. Census Bureau and the D.C. Office of Planning. The tract lines were created by selecting street arcs from the WGIS planimetric street centerlines, and, where necessary, heads-up digitized from the 1995/1999 orthophotographs. Polygons were generated using these lines.

  4. d

    Census Block Groups in 2020

    • catalog.data.gov
    • opdatahub.dc.gov
    • +3more
    Updated Feb 4, 2025
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    City of Washington, DC (2025). Census Block Groups in 2020 [Dataset]. https://catalog.data.gov/dataset/census-block-groups-in-2020
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    Description

    Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number (e.g., Blocks 3001, 3002, 3003 to 3999 in census tract 1210.02 belong to block group 3). Current block groups do not always maintain these same block number to block group relationships due to boundary and feature changes that occur throughout the decade. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the GEOID for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block GEOIDs are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain 600 to 3,000 people. Local participants delineated most block groups as part of the Census Bureau's PSAP. The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains one or more block groups and block groups have unique numbers within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and AIANNH areas.Block groups have a valid range of zero (0) through nine (9). Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

  5. d

    2020 Redistricting Data for DC Census Tracts

    • opendata.dc.gov
    • catalog.data.gov
    • +1more
    Updated Sep 10, 2021
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    City of Washington, DC (2021). 2020 Redistricting Data for DC Census Tracts [Dataset]. https://opendata.dc.gov/items/2049443260464bafbef97671fefd53e6
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    Dataset updated
    Sep 10, 2021
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Census Tracts from 2020. Redistricting Data (P.L. 94-171).Contact: District of Columbia, Office of Planning. Email: planning@dc.govGeography: Census TractsCurrent Vintage: 2020P.L. 94-171 Table(s): P1. Race; P2. Hispanic or Latino, and Not Hispanic or Latino by Race; P3. Race for the Population 18 Years and Over; P4. Hispanic or Latino, and Not Hispanic or Latino by Race for the Population 18 Years and Over; P5. Group Quarters Population by Major Group Quarters Type; H1. Housing Occupancy StatusData downloaded from: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.htmlNational Figures: data.census.govPublic Law 94-171, enacted in 1975, directs the U.S. Census Bureau to make special preparations to provide redistricting data needed by the 50 states.1 It specifies that within 1 year following Census Day, the Census Bureau must send the governor and legislative leadership in each state the data they need to redraw districts for the U.S. Congress and state legislatures. To meet this legal requirement, the Census Bureau set up a program that affords state officials an opportunity before each decennial census to define the small areas for which they wish to receive census population totals for redistricting purposes. Officials may receive data for voting districts (e.g., election precincts, wards) and state house and senate districts, in addition to standard census geographic areas such as counties, cities, census tracts, and blocks. State participation in defining areas is voluntary and nonpartisan. For further information on Public Law 94-171 and the 2020 Census Redistricting Data Program, see:www.census.gov/programs-surveys/decennial-census/about/rdo/program -management.htmlData processed using R statistical package and ArcGIS Desktop.

  6. d

    Census Blocks in 2020

    • catalog.data.gov
    • opdatahub.dc.gov
    • +2more
    Updated Feb 5, 2025
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    City of Washington, DC (2025). Census Blocks in 2020 [Dataset]. https://catalog.data.gov/dataset/census-blocks-in-2020
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Description

    Census blocks are statistical areas bounded on all sides by visible features (e.g., streets, roads, streams, and railroad tracks), and by non-visible boundaries (e.g., city, town, township, county limits, and short line-of-sight extensions of streets and roads). Generally, census blocks are small in area (e.g., a block in a city). Census blocks in suburban and rural areas may be large, irregular, and bounded by a variety of features (e.g., roads, streams, and/or transmission line rights-of-way). In remote areas, census blocks may encompass hundreds of square miles. Census blocks cover all territory in the United States, Puerto Rico, and the Island areas. Blocks do not cross the boundaries of any entity for which the Census Bureau tabulates data.Census Block Numbers—Census blocks are numbered uniquely within the boundaries of each state, county, census tract with a 4-character census block number. The first character of the tabulation block number identifies the block group. A block number can only be unique by using the decennial census state (STATEFP

  7. c

    ACS 5-Year Demographic Characteristics DC Census Tract

    • s.cnmilf.com
    • datasets.ai
    • +1more
    Updated Feb 4, 2025
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    City of Washington, DC (2025). ACS 5-Year Demographic Characteristics DC Census Tract [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/acs-5-year-demographic-characteristics-dc-census-tract
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    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: Census Tracts. 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.

  8. c

    Census Tracts in 1940

    • s.cnmilf.com
    • opendata.dc.gov
    • +3more
    Updated Feb 5, 2025
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    D.C. Office of the Chief Technology Officer (2025). Census Tracts in 1940 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/census-tracts-in-1940
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    Census Year 1940 Census Tracts. The dataset contains polygons representing CY 1940 census tracts, created as part of the D.C. Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Census tracts were identified from maps provided by the U.S. Census Bureau and the D.C. Office of Planning. The tract polygons were created by selecting street arcs from the WGIS planimetric street centerlines. Where necessary, polygons were also heads-up digitized from 1995/1999 orthophotographs.

  9. Census Tracts in 2010

    • catalog.data.gov
    • opendata.dc.gov
    • +4more
    Updated Feb 5, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division (2025). Census Tracts in 2010 [Dataset]. https://catalog.data.gov/dataset/census-tracts-in-2010
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for almost all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and Census 2000. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  10. USA 2020 Census Population Characteristics - Place Geographies

    • hub.arcgis.com
    • data-isdh.opendata.arcgis.com
    Updated Jun 1, 2023
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    Esri (2023). USA 2020 Census Population Characteristics - Place Geographies [Dataset]. https://hub.arcgis.com/maps/9c84c24c55a04c3b8317f37e536e6a8a
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    Dataset updated
    Jun 1, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, 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 and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  11. d

    2020 Redistricting Data for DC Census Block Groups

    • catalog.data.gov
    • opdatahub.dc.gov
    • +1more
    Updated Feb 5, 2025
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    City of Washington, DC (2025). 2020 Redistricting Data for DC Census Block Groups [Dataset]. https://catalog.data.gov/dataset/2020-redistricting-data-for-dc-census-block-groups
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    Census Block Groups from 2020. Redistricting Data (P.L. 94-171).Contact: District of Columbia, Office of Planning. Email: planning@dc.govGeography: Block GroupsCurrent Vintage: 2020P.L. 94-171 Table(s): P1. Race; P2. Hispanic or Latino, and Not Hispanic or Latino by Race; P3. Race for the Population 18 Years and Over; P4. Hispanic or Latino, and Not Hispanic or Latino by Race for the Population 18 Years and Over; P5. Group Quarters Population by Major Group Quarters Type; H1. Housing Occupancy StatusData downloaded from: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.htmlNational Figures: data.census.govPublic Law 94-171, enacted in 1975, directs the U.S. Census Bureau to make special preparations to provide redistricting data needed by the 50 states.1 It specifies that within 1 year following Census Day, the Census Bureau must send the governor and legislative leadership in each state the data they need to redraw districts for the U.S. Congress and state legislatures. To meet this legal requirement, the Census Bureau set up a program that affords state officials an opportunity before each decennial census to define the small areas for which they wish to receive census population totals for redistricting purposes. Officials may receive data for voting districts (e.g., election precincts, wards) and state house and senate districts, in addition to standard census geographic areas such as counties, cities, census tracts, and blocks. State participation in defining areas is voluntary and nonpartisan. For further information on Public Law 94-171 and the 2020 Census Redistricting Data Program, see:www.census.gov/programs-surveys/decennial-census/about/rdo/program -management.htmlData processed using R statistical package and ArcGIS Desktop.

  12. TIGER/Line Shapefile, 2022, State, District of Columbia, DC, Block Group

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, State, District of Columbia, DC, Block Group [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-state-district-of-columbia-dc-block-group
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    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    District of Columbia, Washington
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. The BG boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

  13. County

    • datalibrary-lnr.hub.arcgis.com
    Updated May 25, 2023
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    Esri (2023). County [Dataset]. https://datalibrary-lnr.hub.arcgis.com/datasets/esri::county-27
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    Dataset updated
    May 25, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, 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 and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  14. c

    REV 2.0 Eligible and Ineligible Census Tracts

    • gis.data.cnra.ca.gov
    • data.cnra.ca.gov
    • +2more
    Updated Apr 8, 2024
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    California Energy Commission (2024). REV 2.0 Eligible and Ineligible Census Tracts [Dataset]. https://gis.data.cnra.ca.gov/datasets/CAEnergy::rev-2-0-eligible-and-ineligible-census-tracts
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    Dataset updated
    Apr 8, 2024
    Dataset authored and provided by
    California Energy Commission
    License

    https://www.energy.ca.gov/conditions-of-usehttps://www.energy.ca.gov/conditions-of-use

    Area covered
    Description

    Census tracts are designated as urban, rural center, or rural through SB 1000 analysis. These designations are being used for the REV 2.0 and Community Charging in Urban Areas GFOs. Rural centers are contiguous urban census tracts with a population of less than 50,0000. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Rural communities are census tracts where less than 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Urban communities are contiguous urban census tracts with a population of 50,000 or greater. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.Data Dictionary:OBJECTID: Unique IDSTATEFP: State FIPS CodeCOUNTYFP: County FIPS CodeTRACTCE: Census Tract IDGEOID: Geographic IdentifierName: Census Tract ID Name (short)NAMELSAD: Census Tract ID Name (long)ALAND: Land Area (square meters)AWATER: Water Area (square meters)DAC: Whether or not a census tract is a disadvantaged community as defined by SB 535 and designated by CalEPA using CalEnviroScreen 4.0 (May 2022 update)Income_Group: Whether or not a census tract is low-, middle-, or high-income as defined by AB 1550 and designated by CARB and the CEC (June 2023 update)Urban_Rural_RuralCenter: Whether or not a census tract is urban, rural, or rural center as defined and designated by the CEC through the SB 1000 Assessment (2024 update)PerCap_100k_L2DCFC: Number of public Level 2 and DC fast chargers per 100,000 people in a census tractDAC_andor_LIC: Whether or not a census tract is a disadvantaged or low-income community as defined by SB 535 and AB 1550 and designated by CalEPA and CARBUCC_eligible: Whether or not the census tract is an eligible area for the Community Charging in Urban Areas GFO. For a site to be eligible, it must be in a census tract that is either a disadvantaged or low-income community, and urban, and has below the state average for per capita public Level 2 and DC fast chargers as defined by the CEC.REV2_eligible: Whether or not the census tract is an eligible area for the Rural Electric Vehicle Charging 2.0 GFO. For a site to be eligible, it must be in a rural or rural center census tract as defined by the CEC.Shape_Area: Census tract shape area (square meters)Shape_Length: Census tract shape length (square meters)

  15. v

    ACS 5-Year Social Characteristics DC Ward

    • anrgeodata.vermont.gov
    • opdatahub.dc.gov
    • +3more
    Updated Feb 28, 2025
    + more versions
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    City of Washington, DC (2025). ACS 5-Year Social Characteristics DC Ward [Dataset]. https://anrgeodata.vermont.gov/datasets/DCGIS::acs-5-year-social-characteristics-dc-ward/explore
    Explore at:
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    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: 2019-2023. ACS Table(s): DP02. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. 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.

  16. a

    Census Tracts in 2020

    • private-demo-dcdev.opendata.arcgis.com
    • opdatahub.dc.gov
    • +4more
    Updated Aug 27, 2021
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    City of Washington, DC (2021). Census Tracts in 2020 [Dataset]. https://private-demo-dcdev.opendata.arcgis.com/datasets/DCGIS::census-tracts-in-2020
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    Dataset updated
    Aug 27, 2021
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Census Tracts from 2020. The TIGER/Line shapefiles are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2020 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2010 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area.

  17. ACS Race and Hispanic Origin Variables - Centroids

    • mapdirect-fdep.opendata.arcgis.com
    • covid-hub.gio.georgia.gov
    • +7more
    Updated Oct 22, 2018
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    Esri (2018). ACS Race and Hispanic Origin Variables - Centroids [Dataset]. https://mapdirect-fdep.opendata.arcgis.com/maps/e6d218a8ba764a939c2add5c081beef9
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    Dataset updated
    Oct 22, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows population broken down by race and Hispanic origin. 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. This layer is symbolized to show the predominant race living within an area, and the total population in that area. 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): B03002Data 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.

  18. v

    VT Data – 2020 Census Tract

    • geodata.vermont.gov
    • sov-vcgi.opendata.arcgis.com
    • +1more
    Updated Aug 12, 2021
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    VT Center for Geographic Information (2021). VT Data – 2020 Census Tract [Dataset]. https://geodata.vermont.gov/datasets/VCGI::vt-data-2020-census-tract/about
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    Dataset updated
    Aug 12, 2021
    Dataset authored and provided by
    VT Center for Geographic Information
    Area covered
    Description

    This layer contains a Vermont-only subset of census tract level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, BLOCK, BLKGRP, and TBLKGRP.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual tract level, since this data has been protected using differential privacy.*VCGI exported a Vermont-only subset of the nation-wide layer to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLON: Internal Point (Longitude) INTPTLAT: Internal Point (Latitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual tracts will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

  19. Census Designated Place

    • hub.arcgis.com
    Updated Jun 29, 2023
    + more versions
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    Esri (2023). Census Designated Place [Dataset]. https://hub.arcgis.com/maps/esri::census-designated-place-3
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    Dataset updated
    Jun 29, 2023
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows race and ethnicity data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P5, P9 Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, 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 and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  20. c

    Households by Type - Counties 2015-2019

    • covid19.census.gov
    • covid19-uscensus.hub.arcgis.com
    Updated Mar 19, 2021
    + more versions
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    US Census Bureau (2021). Households by Type - Counties 2015-2019 [Dataset]. https://covid19.census.gov/datasets/households-by-type-counties-2015-2019/api
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    Dataset updated
    Mar 19, 2021
    Dataset authored and provided by
    US Census Bureau
    Area covered
    North Pacific Ocean, Pacific Ocean
    Description

    This layer shows Households by Type. This is shown by county boundaries. 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. This layer is symbolized to show percentage of households with no vehicles. 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: 2015-2019ACS Table(s): B11001, B25010, B25044, DP02, DP04Data downloaded from: Census Bureau's API for American Community Survey Date of API call: February 10, 2021National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS): About the SurveyGeography & ACSTechnical Documentation News & 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. 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. 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). 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.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes.
    All of these are rendered in this dataset as null (blank) values.

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D.C. Office of the Chief Technology Officer (2025). DC Health Planning Neighborhoods to Census Tracts [Dataset]. https://catalog.data.gov/dataset/dc-health-planning-neighborhoods-to-census-tracts-24ba6

DC Health Planning Neighborhoods to Census Tracts

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Dataset updated
Feb 4, 2025
Dataset provided by
D.C. Office of the Chief Technology Officer
Area covered
Washington
Description

This dataset contains polygons that represent the boundaries of statistical neighborhoods as defined by the DC Department of Health (DC Health). DC Health delineates statistical neighborhoods to facilitate small-area analyses and visualization of health, economic, social, and other indicators to display and uncover disparate outcomes among populations across the city. The neighborhoods are also used to determine eligibility for some health services programs and support research by various entities within and outside of government. DC Health Planning Neighborhood boundaries follow census tract 2010 lines defined by the US Census Bureau. Each neighborhood is a group of between one and seven different, contiguous census tracts. This allows for easier comparison to Census data and calculation of rates per population (including estimates from the American Community Survey and Annual Population Estimates). These do not reflect precise neighborhood locations and do not necessarily include all commonly-used neighborhood designations. There is no formal set of standards that describes which neighborhoods are included in this dataset. Note that the District of Columbia does not have official neighborhood boundaries. Origin of boundaries: each neighborhood is a group of between one and seven different, contiguous census tracts. They were originally determined in 2015 as part of an analytical research project with technical assistance from the Centers for Disease Control and Prevention (CDC) and the Council for State and Territorial Epidemiologists (CSTE) to define small area estimates of life expectancy. Census tracts were grouped roughly following the Office of Planning Neighborhood Cluster boundaries, where possible, and were made just large enough to achieve standard errors of less than 2 for each neighborhood's calculation of life expectancy. The resulting neighborhoods were used in the DC Health Equity Report (2018) with updated names. HPNs were modified slightly in 2019, incorporating one census tract that was consistently suppressed due to low numbers into a neighboring HPN (Lincoln Park incorporated into Capitol Hill). Demographic information were analyzed to identify the bordering group with the most similarities to the single census tract. A second change split a neighborhood (GWU/National Mall) into two to facilitate separate analysis.

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