100+ datasets found
  1. 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement...

    • icpsr.umich.edu
    Updated Oct 24, 2023
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    Abowd, John M.; Ashmead, Robert; Cumings-Menon, Ryan; Garfinkel, Simson; Heineck, Micah; Heiss, Christine; Johns, Robert; Kifer, Daniel; Leclerc, Philip; Machanavajjhala, Ashwin; Moran, Brett; Sexton, William; Spence, Matthew; Zhuravlev, Pavel (2023). 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File (NMF) [Dataset]. http://doi.org/10.3886/ICPSR38937.v1
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    Dataset updated
    Oct 24, 2023
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Abowd, John M.; Ashmead, Robert; Cumings-Menon, Ryan; Garfinkel, Simson; Heineck, Micah; Heiss, Christine; Johns, Robert; Kifer, Daniel; Leclerc, Philip; Machanavajjhala, Ashwin; Moran, Brett; Sexton, William; Spence, Matthew; Zhuravlev, Pavel
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38937/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38937/terms

    Time period covered
    2020
    Area covered
    United States
    Description

    The 2020 Census Demographic and Housing Characteristics Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS_2020_DHC_Production_Code/das_decennial/programs/engine/primitives.py at main uscensusbureau/DAS_2020_DHC_Production_Code (github.com) The 2020 Census Demographic and Housing Characteristics Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] ), which added positive or negative integer-valued noise to each of the resulting counts. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the Census Demographic and Housing Characteristics Summary File. In addition to the noisy measurements, constraints based on invariant calculations --- counts computed without noise --- are also included (with the exception of the state-level total populations, which can be sourced separately from data.census.gov). The Noisy Measurement File was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The noisy measurements are produced in an early stage of the TDA. Afterward, these noisy measurements are post-processed to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these noisy measurements to enable data users to evaluate the impact of disclosure avoidance variability on 2020 Census data. The 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004). These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information. The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access. Please see the Globus "How to get Started" page for more information.

  2. D

    Decennial Census Data, 2020

    • catalog.dvrpc.org
    csv
    Updated Mar 17, 2025
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    DVRPC (2025). Decennial Census Data, 2020 [Dataset]. https://catalog.dvrpc.org/dataset/decennial-census-data-2020
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    csv(45639), csv(12201), csv(1628), csv(3138210), csv(48864), csv(278080), csv(51283), csv(194128), csv(20901), csv(530289), csv, csv(292974), csv(1102597), csv(9443624)Available download formats
    Dataset updated
    Mar 17, 2025
    Dataset authored and provided by
    DVRPC
    License

    https://catalog.dvrpc.org/dvrpc_data_license.htmlhttps://catalog.dvrpc.org/dvrpc_data_license.html

    Description

    This dataset contains data from the P.L. 94-171 2020 Census Redistricting Program. The 2020 Census Redistricting Data Program provides states the opportunity to delineate voting districts and to suggest census block boundaries for use in the 2020 Census redistricting data tabulations (Public Law 94-171 Redistricting Data File). In addition, the Redistricting Data Program will periodically collect state legislative and congressional district boundaries if they are changed by the states. The program is also responsible for the effective delivery of the 2020 Census P.L. 94-171 Redistricting Data statutorily required by one year from Census Day. The program ensures continued dialogue with the states in regard to 2020 Census planning, thereby allowing states ample time for their planning, response, and participation. The U.S. Census Bureau will deliver the Public Law 94-171 redistricting data to all states by Sept. 30, 2021. COVID-19-related delays and prioritizing the delivery of the apportionment results delayed the Census Bureau’s original plan to deliver the redistricting data to the states by April 1, 2021.

    Data in this dataset contains information on population, diversity, race, ethnicity, housing, household, vacancy rate for 2020 for various geographies (county, MCD, Philadelphia Planning Districts (referred to as county planning areas [CPAs] internally, Census designated places, tracts, block groups, and blocks)

    For more information on the 2020 Census, visit https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html

    PLEASE NOTE: 2020 Decennial Census data has had noise injected into it because of the Census's new Disclosure Avoidance System (DAS). This can mean that population counts and characteristics, especially when they are particularly small, may not exactly correspond to the data as collected. As such, caution should be exercised when examining areas with small counts. Ron Jarmin, acting director of the Census Bureau posted a discussion of the redistricting data, which outlines what to expect with the new DAS. For more details on accuracy you can read it here: https://www.census.gov/newsroom/blogs/director/2021/07/redistricting-data.html

  3. USA 2020 Census Population Characteristics

    • disasterpartners.org
    • datalibrary-lnr.hub.arcgis.com
    Updated May 26, 2023
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    Esri (2023). USA 2020 Census Population Characteristics [Dataset]. https://www.disasterpartners.org/maps/ebeb65deb5c14f4d8849fd68944b7ee6
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    Dataset updated
    May 26, 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.

  4. a

    USA 2020 Census Population Characteristics - Place Geographies

    • hub.arcgis.com
    • city-of-vancouver-strategic-plan-dashboard-cityofvancouver.hub.arcgis.com
    Updated May 25, 2023
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    Vancouver Online Maps (2023). USA 2020 Census Population Characteristics - Place Geographies [Dataset]. https://hub.arcgis.com/datasets/8fe7368fd2024ed183572566a8fe96c3
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    Dataset updated
    May 25, 2023
    Dataset authored and provided by
    Vancouver Online Maps
    Area covered
    Description

    This CSV file shows total population counts by sex, age, and race groupsdata from the2020 CensusDemographic andHousing Characteristics. Thisisshown by Nation, Consolidated City, Census Designated Place, Incorporated Placeboundaries. Eachgeographylayercontainsa common set of Census countsbased on available attributes from the U.S. Census Bureau. There are alsoadditionalcalculated attributes related to this topic, which can be mapped or used within analysis.  Vintageof boundaries and attributes:2020Demographic andHousing CharacteristicsTable(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this file.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDatethe Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layerThe United States Census BureauDemographic andHousing Characteristics:2020 Census Results2020 Census Data QualityGeography &2020 CensusTechnical DocumentationData 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 & UpdatesData 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. ForCensustractsand 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 metersor larger (mid tolarge sizedwater bodies) are erased from the tractand block groupboundaries, 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 tomore 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 layercontainsall 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 beidentifiedby 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 theDemographic Profile and Demographic andHousing 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 usingdifferential privacy techniquesby the U.S. Census Bureau.

  5. Estimating Confidence Intervals for 2020 Census Statistics Using Approximate...

    • registry.opendata.aws
    Updated Sep 17, 2024
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    United States Census Bureau (2024). Estimating Confidence Intervals for 2020 Census Statistics Using Approximate Monte Carlo Simulation (2020 Census Production Run) [Dataset]. https://registry.opendata.aws/census-2020-amc-mdf-replicates/
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    Dataset updated
    Sep 17, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

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

    Description

    The 2020 Census Production Settings Demographic and Housing Characteristics (DHC) Approximate Monte Carlo (AMC) method seed Privacy Protected Microdata File (PPMF0) and PPMF replicates (PPMF1, PPMF2, ..., PPMF50) are a set of microdata files intended for use in estimating the magnitude of error(s) introduced by the 2020 Census Disclosure Avoidance System (DAS) into the 2020 Census Redistricting Data Summary File (P.L. 94-171), the Demographic and Housing Characteristics File, and the Demographic Profile.

    The PPMF0 was the source of the publicly released, official 2020 Census data products referenced above, and was created by executing the 2020 DAS TopDown Algorithm (TDA) using the confidential 2020 Census Edited File (CEF) as the initial input; the official location for the PPMF0 is on the United States Census Bureau FTP server, but we also include a copy of it here for convenience. The replicates were then created by executing the 2020 DAS TDA repeatedly with the PPMF0 as its initial input.

    Inspired by analogy to the use of bootstrap methods in non-private contexts, U.S. Census Bureau (USCB) researchers explored whether simple calculations based on comparing each PPMFi to the PPMF0 could be used to reliably estimate the scale of errors introduced by the 2020 DAS, and generally found this approach worked well.

    The PPMF0 and PPMFi files contained here are provided so that external researchers can estimate properties of DAS-introduced error without privileged access to internal USCB-curated data sets; further information on the estimation methodology can be found in Ashmead et. al 2024.

    The 2020 DHC AMC seed PPMF0 and PPMF replicates have been cleared for public dissemination by the USCB Disclosure Review Board (CBDRB-FY22-DSEP-004). The PPMF0 and PPMF replicates contain all Person and Units attributes necessary to produce the 2020 Census Redistricting Data Summary File (P.L. 94-171), the Demographic and Housing Characteristics File, and the Demographic Profile for both the United States and Puerto Rico, and include geographic detail down to the Census Block level. They do not include attributes specific to either the Detailed DHC-A or Detailed DHC-B products; in particular, data on Major Race (e.g., White Alone) is included, but data on Detailed Race (e.g., Cambodian) is not included in the PPMF0 and replicates.

  6. P

    Census 2020 Table P2 12011 Block Groups

    • data.pompanobeachfl.gov
    • geohub-bcgis.opendata.arcgis.com
    Updated Feb 28, 2023
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    External Datasets (2023). Census 2020 Table P2 12011 Block Groups [Dataset]. https://data.pompanobeachfl.gov/dataset/census-2020-table-p2-12011-block-groups
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    zip, kml, csv, geojson, html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Feb 28, 2023
    Dataset provided by
    cjennings_BCGIS
    Authors
    External Datasets
    Description

    2020 Census P.L. 94-171 is the first detailed data release from the 2020 Decennial Census of Population and Housing. The web layer is based on an extract for Table P2 – Hispanic or Latino, and Not Hispanic or Latino by Race at the block group level geography of Broward County, Florida. The data extract was then joined to the 2020 Census TIGER/Line Shapefiles.

    For details on field names, table hierarchy, and table contents refer to TABLE (MATRIX) SECTION in Chapter 6. Data Dictionary, https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_StatesTechDoc_English.pdf" STYLE="text-decoration:underline;">2020 Census State Public Law 94-171 Summary File Technical Documentation.

  7. P

    Census 2020 Table P4 12011 Place

    • data.pompanobeachfl.gov
    • hub.arcgis.com
    • +2more
    Updated Feb 28, 2023
    + more versions
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    External Datasets (2023). Census 2020 Table P4 12011 Place [Dataset]. https://data.pompanobeachfl.gov/dataset/census-2020-table-p4-12011-place
    Explore at:
    kml, html, arcgis geoservices rest api, geojson, csv, zipAvailable download formats
    Dataset updated
    Feb 28, 2023
    Dataset provided by
    cjennings_BCGIS
    Authors
    External Datasets
    Description

    2020 Census P.L. 94-171 is the first detailed data release from the 2020 Decennial Census of Population and Housing. The web layer is based on an extract for Table P4 – Hispanic or Latino, and Not Hispanic or Latino by Race for the Population 18 Years and Over at the place level geography of Broward County, Florida. The data extract was then joined to the 2020 Census TIGER/Line Shapefiles.

    For details on field names, table hierarchy, and table contents refer to TABLE (MATRIX) SECTION in Chapter 6. Data Dictionary, https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_StatesTechDoc_English.pdf" STYLE="text-decoration:underline;">2020 Census State Public Law 94-171 Summary File Technical Documentation.

  8. 2020 Census Block

    • catalog.data.gov
    • data.oregon.gov
    • +3more
    Updated Jan 31, 2025
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (2025). 2020 Census Block [Dataset]. https://catalog.data.gov/dataset/census-blocks
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    This data layer is an element of the Oregon GIS Framework. 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. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces

  9. d

    Census Tracts in 2020

    • catalog.data.gov
    • anrgeodata.vermont.gov
    • +3more
    Updated Feb 4, 2025
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    City of Washington, DC (2025). Census Tracts in 2020 [Dataset]. https://catalog.data.gov/dataset/census-tracts-in-2020
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    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.

  10. TIGER/Line Shapefile, 2020, Nation, U.S., 2020 Census Urban Area

    • catalog.data.gov
    Updated Aug 11, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2025). TIGER/Line Shapefile, 2020, Nation, U.S., 2020 Census Urban Area [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2020-nation-u-s-2020-census-urban-area
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    Dataset updated
    Aug 11, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Area covered
    United States
    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. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the urban footprint. There are 2,645 Urban Areas (UAs) in this data release with either a minimum population of 5,000 or a housing unit count of 2,000 units. Each urban area is identified by a 5-character numeric census code that may contain leading zeroes.

  11. 2020 Decennial Census: P12D | SEX BY AGE FOR SELECTED AGE CATEGORIES (ASIAN...

    • data.census.gov
    + more versions
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    DEC, 2020 Decennial Census: P12D | SEX BY AGE FOR SELECTED AGE CATEGORIES (ASIAN ALONE) (DEC Demographic and Housing Characteristics) [Dataset]. https://data.census.gov/table/DECENNIALDHC2020.P12D?text=age&t=Age%20and%20Sex&g=050XX00US48071,48073,48193,48149,48027,48029,48185,48063,48187,48021,48145,48221,48147,48181,48183,48217,48019,48139,48097,48053,48099,48055,48175,48013,48177,48015,48213,48091,48051,48171,48005,48209,48163,48085,48041,48121,48167,48123,48001,48089,48201,48161,48039,48159,22023,48031,48035,48199,48113,48157,48347,48423,48225,48467,48349,48425,48309,48265,48223,48259,48379,48459,48337,48339,48251,48493,48297,48373,48453,48255,48299,48331,48257,48455,48411,48333,48291,48491,48293,48325,48401,48449,48407,48361,48481,48285,48321,48287,48367,48289,48245,48281,48313,48439,48471,48231,48473,48395,48397,48477,48497,48499
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    DEC
    License

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

    Time period covered
    2020
    Description

    Note: For information on data collection, confidentiality protection, nonsampling error, subject definitions, and guidance on using the data, visit the 2020 Census Demographic and Housing Characteristics File (DHC) Technical Documentation webpage..To protect respondent confidentiality, data have undergone disclosure avoidance methods which add "statistical noise" - small, random additions or subtractions - to the data so that no one can reliably link the published data to a specific person or household. The Census Bureau encourages data users to aggregate small populations and geographies to improve accuracy and diminish implausible results..Source: U.S. Census Bureau, 2020 Census Demographic and Housing Characteristics File (DHC)

  12. a

    Population Density in the US 2020 Census

    • hub.arcgis.com
    • data-bgky.hub.arcgis.com
    Updated Jun 20, 2024
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    University of South Florida GIS (2024). Population Density in the US 2020 Census [Dataset]. https://hub.arcgis.com/maps/58e4ee07a0e24e28949903511506a8e4
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    Dataset updated
    Jun 20, 2024
    Dataset authored and provided by
    University of South Florida GIS
    Area covered
    Description

    This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain 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.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 map 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.

  13. P

    Census 2020 Table P4 12011 Block Groups

    • data.pompanobeachfl.gov
    • geohub-bcgis.opendata.arcgis.com
    • +1more
    Updated Feb 28, 2023
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    External Datasets (2023). Census 2020 Table P4 12011 Block Groups [Dataset]. https://data.pompanobeachfl.gov/dataset/census-2020-table-p4-12011-block-groups
    Explore at:
    csv, geojson, html, zip, kml, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Feb 28, 2023
    Dataset provided by
    cjennings_BCGIS
    Authors
    External Datasets
    Description

    2020 Census P.L. 94-171 is the first detailed data release from the 2020 Decennial Census of Population and Housing. The web layer is based on an extract for Table P4 – Hispanic or Latino, and Not Hispanic or Latino by Race for the Population 18 Years and Over at the block group level geography of Broward County, Florida. The data extract was then joined to the 2020 Census TIGER/Line Shapefiles.

    For details on field names, table hierarchy, and table contents refer to TABLE (MATRIX) SECTION in Chapter 6. Data Dictionary, https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_StatesTechDoc_English.pdf" STYLE="text-decoration:underline;">2020 Census State Public Law 94-171 Summary File Technical Documentation.

  14. C

    California Census 2020 Outreach and Communication Campaign Final Report

    • data.ca.gov
    • dru-data-portal-cacensus.hub.arcgis.com
    • +1more
    Updated Jun 29, 2023
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    California Department of Finance (2023). California Census 2020 Outreach and Communication Campaign Final Report [Dataset]. https://data.ca.gov/dataset/california-census-2020-outreach-and-communication-campaign-final-report
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    html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Jun 29, 2023
    Dataset provided by
    Calif. Dept. of Finance Demographic Research Unit
    Authors
    California Department of Finance
    Area covered
    California
    Description

    More than 39 million people and 14.2 million households span more than 163,000 square miles of Californian’s urban, suburban and rural communities. California has the fifth largest economy in the world and is the most populous state in the nation, with nation-leading diversity in race, ethnicity, language and socioeconomic conditions. These characteristics make California amazingly unique amongst all 50 states, but also present significant challenges to counting every person and every household, no matter the census year. A complete and accurate count of a state’s population in a decennial census is essential. The results of the 2020 Census will inform decisions about allocating hundreds of billions of dollars in federal funding to communities across the country for hospitals, fire departments, school lunch programs and other critical programs and services. The data collected by the United States Census Bureau (referred hereafter as U.S. Census Bureau) also determines the number of seats each state has in the U.S. House of Representatives and will be used to redraw State Assembly and Senate boundaries. California launched a comprehensive Complete Count Census 2020 Campaign (referred to hereafter as the Campaign) to support an accurate and complete count of Californians in the 2020 Census. Due to the state’s unique diversity and with insights from past censuses, the Campaign placed special emphasis on the hardest-tocount Californians and those least likely to participate in the census. The California Complete Count – Census 2020 Office (referred to hereafter as the Census Office) coordinated the State’s operations to complement work done nationally by the U.S. Census Bureau to reach those households most likely to be missed because of barriers, operational or motivational, preventing people from filling out the census. The Campaign, which began in 2017, included key phases, titled Educate, Motivate and Activate. Each of these phases were designed to make sure all Californians knew about the census, how to respond, their information was safe and their participation would help their communities for the next 10 years.

  15. TIGER/Line Shapefile, 2022, Nation, U.S., 2020 Census 5-Digit ZIP Code...

    • catalog.data.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    Updated Jan 27, 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, Nation, U.S., 2020 Census 5-Digit ZIP Code Tabulation Area (ZCTA5) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-nation-u-s-2020-census-5-digit-zip-code-tabulation-area-zcta5
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Area covered
    United States
    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. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2020 Census.

  16. Series Information for 2020 Census Block State-based TIGER/Line Shapefiles,...

    • catalog.data.gov
    Updated Aug 7, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division (Point of Contact) (2025). Series Information for 2020 Census Block State-based TIGER/Line Shapefiles, Current [Dataset]. https://catalog.data.gov/dataset/series-information-for-2020-census-block-state-based-tiger-line-shapefiles-current
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    Dataset updated
    Aug 7, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Description

    This is a series-level metadata record. 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) System (MTS). The MTS 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 blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

  17. D

    2020 Census Block Groups; PA, NJ, DE & MD

    • catalog.dvrpc.org
    • staging-catalog.cloud.dvrpc.org
    • +2more
    api, geojson, html +1
    Updated May 23, 2025
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    DVRPC (2025). 2020 Census Block Groups; PA, NJ, DE & MD [Dataset]. https://catalog.dvrpc.org/dataset/2020-census-block-groups-pa-nj-de-md
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    xml, geojson, html, apiAvailable download formats
    Dataset updated
    May 23, 2025
    Dataset authored and provided by
    DVRPC
    Area covered
    Pennsylvania, New Jersey
    Description

    USE geoid TO JOIN DATA DOWNLOADED FROM DATA.CENSUS.GOV The TIGER/Line Shapefiles are extracts of selected geographic and cartographic information from the Census Bureau's Master Address File (MAF)/Topologically Integrated Geographic Encoding and Referencing (TIGER) System (MTS). The TIGER/Line Shapefiles contain a standard geographic identifier (GEOID) for each entity that links to the GEOID in the data from censuses and surveys. The TIGER/Line Shapefiles do not include demographic data from surveys and censuses (e.g., Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program). Other, non-census, data often have this standard geographic identifier as well. Data from many of the Census Bureau’s surveys and censuses, including the geographic codes needed to join to the TIGER/Line Shapefiles, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/). Block Groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people, and are used to present data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number. For example, blocks 3001, 3002, 3003, . . . , 3999 in census tract 1210.02 belong to BG 3 in that census tract. Most BGs were delineated by local participants in the Census Bureau’s Participant Statistical Areas Program (PSAP). The Census Bureau delineated BGs only where a local or tribal government declined to participate in PSAP, and a regional organization or the State Data Center was not available to participate. A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within the census tract. Within the standard census geographic hierarchy, BGs never cross state, county, or census tract boundaries, but may cross the boundaries of any other geographic entity. Tribal census tracts and tribal BGs are separate and unique geographic areas defined within federally recognized American Indian reservations and can cross state and county boundaries (see “Tribal Census Tract” and “Tribal Block Group”). The tribal census tracts and tribal block groups may be completely different from the standard county-based census tracts and block groups defined for the same area. Downloaded from https://www2.census.gov/geo/tiger/TIGER2022/BG/ on June 22, 2023

  18. P

    Census 2020 Table P2 12011 Blocks

    • data.pompanobeachfl.gov
    • geohub-bcgis.opendata.arcgis.com
    • +1more
    Updated Feb 28, 2023
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    External Datasets (2023). Census 2020 Table P2 12011 Blocks [Dataset]. https://data.pompanobeachfl.gov/dataset/census-2020-table-p2-12011-blocks
    Explore at:
    csv, html, geojson, zip, kml, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Feb 28, 2023
    Dataset provided by
    cjennings_BCGIS
    Authors
    External Datasets
    Description

    2020 Census P.L. 94-171 is the first detailed data release from the 2020 Decennial Census of Population and Housing. The web layer is based on an extract for Table P2 – Hispanic or Latino, and Not Hispanic or Latino by Race at the block level geography of Broward County, Florida. The data extract was then joined to the 2020 Census TIGER/Line Shapefiles.

    For details on field names, table hierarchy, and table contents refer to TABLE (MATRIX) SECTION in Chapter 6. Data Dictionary, https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_StatesTechDoc_English.pdf" STYLE="text-decoration:underline;">2020 Census State Public Law 94-171 Summary File Technical Documentation.

  19. A

    2020 Census for Boston

    • data.boston.gov
    csv, pdf
    Updated Sep 8, 2023
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    Planning Department (2023). 2020 Census for Boston [Dataset]. https://data.boston.gov/dataset/2020-census-for-boston
    Explore at:
    csv(4944), csv(34702), pdf(713107), csv(94470), csv(34556)Available download formats
    Dataset updated
    Sep 8, 2023
    Dataset authored and provided by
    Planning Department
    Area covered
    Boston
    Description

    2020 Census data for the city of Boston, Boston neighborhoods, census tracts, block groups, and voting districts. In the 2020 Census, the U.S. Census Bureau divided Boston into 207 census tracts (~4,000 residents) made up of 581 smaller block groups. The Boston Planning and Development Agency uses the 2020 tracts to approximate Boston neighborhoods. The 2020 Census Redistricting data also identify Boston’s voting districts.

    For analysis of Boston’s 2020 Census data including graphs and maps by the BPDA Research Division and Office of Digital Cartography and GIS, see 2020 Census Research Publications

    For a complete official data dictionary, please go to 2020 Census State Redistricting Data (Public Law 94-171) Summary File, Chapter 6. Data Dictionary. 2020 Census State Redistricting Data (Public Law 94-171) Summary File

    2020 Census Tracts In Boston

    2020 Census Block Groups In Boston

    Boston Neighborhood Boundaries Approximated By 2020 Census Tracts

    Boston Voting District Boundaries

  20. V

    Census 2020 Block

    • data.virginia.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +4more
    Updated Mar 14, 2024
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    Fairfax County (2024). Census 2020 Block [Dataset]. https://data.virginia.gov/dataset/census-2020-block
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    geojson, zip, kml, csv, xlsx, txt, gpkg, arcgis geoservices rest api, gdb, htmlAvailable download formats
    Dataset updated
    Mar 14, 2024
    Dataset provided by
    County of Fairfax
    Authors
    Fairfax County
    Description

    The 2020 decennial census blocks within Fairfax County. This data was acquired from the US Census Bureau, with fields slightly customized by Fairfax County Department of Management and Budget, Economic, Demographic, and Statistical Research unit.

    Contact: Department of Management & Budget

    Data Accessibility: Publicly Available

    Update Frequency: As Needed

    Last Revision Date: 1/6/2023

    Creation Date: 1/6/2023

    Feature Dataset Name: DIT_GIS.DSMHSMGR.FEDERAL_CENSUS_2020

    Layer Name: DIT_GIS.DSMHSMGR.FEDERAL_BLOCK_2020

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Abowd, John M.; Ashmead, Robert; Cumings-Menon, Ryan; Garfinkel, Simson; Heineck, Micah; Heiss, Christine; Johns, Robert; Kifer, Daniel; Leclerc, Philip; Machanavajjhala, Ashwin; Moran, Brett; Sexton, William; Spence, Matthew; Zhuravlev, Pavel (2023). 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File (NMF) [Dataset]. http://doi.org/10.3886/ICPSR38937.v1
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2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File (NMF)

Explore at:
Dataset updated
Oct 24, 2023
Dataset provided by
Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
Authors
Abowd, John M.; Ashmead, Robert; Cumings-Menon, Ryan; Garfinkel, Simson; Heineck, Micah; Heiss, Christine; Johns, Robert; Kifer, Daniel; Leclerc, Philip; Machanavajjhala, Ashwin; Moran, Brett; Sexton, William; Spence, Matthew; Zhuravlev, Pavel
License

https://www.icpsr.umich.edu/web/ICPSR/studies/38937/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38937/terms

Time period covered
2020
Area covered
United States
Description

The 2020 Census Demographic and Housing Characteristics Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS_2020_DHC_Production_Code/das_decennial/programs/engine/primitives.py at main uscensusbureau/DAS_2020_DHC_Production_Code (github.com) The 2020 Census Demographic and Housing Characteristics Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] ), which added positive or negative integer-valued noise to each of the resulting counts. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the Census Demographic and Housing Characteristics Summary File. In addition to the noisy measurements, constraints based on invariant calculations --- counts computed without noise --- are also included (with the exception of the state-level total populations, which can be sourced separately from data.census.gov). The Noisy Measurement File was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The noisy measurements are produced in an early stage of the TDA. Afterward, these noisy measurements are post-processed to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these noisy measurements to enable data users to evaluate the impact of disclosure avoidance variability on 2020 Census data. The 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004). These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information. The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access. Please see the Globus "How to get Started" page for more information.

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