100+ datasets found
  1. 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

  2. USA 2020 Census Population Characteristics - Place Geographies

    • data-isdh.opendata.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Jun 1, 2023
    + more versions
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    Esri (2023). USA 2020 Census Population Characteristics - Place Geographies [Dataset]. https://data-isdh.opendata.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.

  3. 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.

  4. 2020 Census Tracts

    • catalog.data.gov
    • data.oregon.gov
    • +2more
    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 Tracts [Dataset]. https://catalog.data.gov/dataset/census-tracts
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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 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 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 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, no land area.

  5. Decennial Census Housing, Tenure, & Households 1980 - 2020

    • data.cambridgema.gov
    Updated Aug 9, 2022
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    Census Bureau Data Recompiled by Cambridge Community Development Department (2022). Decennial Census Housing, Tenure, & Households 1980 - 2020 [Dataset]. https://data.cambridgema.gov/Neighborhood-Census-Data/Decennial-Census-Housing-Tenure-Households-1980-20/veht-2mkm
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    kml, xml, xlsx, csv, application/geo+json, kmzAvailable download formats
    Dataset updated
    Aug 9, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    Census Bureau Data Recompiled by Cambridge Community Development Department
    Description

    Block level data from the 1980 through 2020 decennial censuses recompiled to align with neighborhood boundaries. Include data for total population, total housing stock, renter and owner-occupied housing, households, and families.

  6. U.S. projected state population by state 2040

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). U.S. projected state population by state 2040 [Dataset]. https://www.statista.com/statistics/312714/us-projected-state-population-by-state/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2024
    Area covered
    United States
    Description

    According to a population projection based on 2020 Census Data, in 2040, California's population will amount to ***** million inhabitants.

  7. Census Data

    • catalog.data.gov
    • datadiscoverystudio.org
    • +3more
    Updated Mar 1, 2024
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    U.S. Bureau of the Census (2024). Census Data [Dataset]. https://catalog.data.gov/dataset/census-data
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

  8. d

    Census Tracts in 2020

    • catalog.data.gov
    • anrgeodata.vermont.gov
    • +4more
    Updated Feb 4, 2025
    + more versions
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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.

  9. a

    2020 and 2021 Population Estimates by MPO

    • hub.arcgis.com
    • gis-fdot.opendata.arcgis.com
    • +1more
    Updated Aug 9, 2023
    + more versions
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    Florida Department of Transportation (2023). 2020 and 2021 Population Estimates by MPO [Dataset]. https://hub.arcgis.com/datasets/e7f6ef5f6ca14d72be65248c5bdb92f7
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    Dataset updated
    Aug 9, 2023
    Dataset authored and provided by
    Florida Department of Transportation
    Area covered
    Description

    Each year, the Forecasting and Trends Office (FTO) publishes population estimates and future year projections. The population estimates can be used for a variety of planning studies including statewide and regional transportation plan updates, subarea and corridor studies, and funding allocations for various planning agencies.The 2020 population estimates reported are based on the US Census Bureau 2020 Decennial Census. The 2021 population estimates are based on the population estimates developed by the Bureau of Economic and Business Research (BEBR) at the University of Florida. BEBR uses the decennial census count for April 1, 2020, as the starting point for state-level projections. More information is available from BEBR here.This dataset contains boundaries of Metropolitan Planning Organizations (MPOs)/Transportation Planning Organizations (TPOs)/Transportation Planning Agencies (TPAs) in the State of Florida with 2020 census population and 2021 population estimates. All legal boundaries and names in this dataset are from the US Census Bureau’s TIGER/Line Files (2021).BEBR provides 2021 population estimates for counties in Florida. However, MPO/TPO/TPA boundaries may not coincide with the jurisdictional boundaries of counties and can spread into several counties. To estimate the population for an MPO/TPO/TPA, first the ratio of the subject MPO/TPO/TPA that is contained within a county (or sub-area) to the area of the entire county was determined. That ratio was multiplied by the estimated county population to obtain the population for that sub-area. The population for the entire MPO/TPO/TPA is the sum of all sub-area populations estimated from the counties they are located within. Note: Baldwin County, AL’s 2021 population from the US Census annual population estimates (2020-2021) was used for estimating Florida-Alabama TPO’s population Please see the Data Dictionary for more information on data fields. Data Sources:US Census Bureau 2020 Decennial CensusUS Census Bureau’s TIGER/Line Files (2021)Bureau of Economic and Business Research (BEBR) – Florida Estimates of Population 2021 Data Coverage: StatewideData Time Period: 2020 – 2021 Date of Publication: July 2022 Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

  10. 2020 Decennial Census: T01001 | TOTAL POPULATION (DEC Detailed Demographic...

    • data.census.gov
    Updated Sep 24, 2023
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    DEC (2023). 2020 Decennial Census: T01001 | TOTAL POPULATION (DEC Detailed Demographic and Housing Characteristics File A) [Dataset]. https://data.census.gov/all/tables?q=BILL%20HUNT
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    Dataset updated
    Sep 24, 2023
    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, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, access Improvements to the 2020 Census Race and Hispanic Origin Question Designs, Data Processing, and Coding Procedures..Data users may observe implausible and improbable data within this product and compared with other 2020 Census data products. For example, it is possible for a detailed group to have a larger count in a tract than in its corresponding county. For more information, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Aggregating data, such as geographies and sex by age data, diminishes accuracy and increases the likelihood of inconsistent and improbable results. For guidance on creating custom aggregations from Detailed DHC-A data, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Counts showing an "X" are suppressed for one of two reasons: (1) the count was negative or (2) it is an alone count larger than its equivalent alone or in any combination count. If the suppressed count is an alone count, data users should use the equivalent alone in any combination count, if it is available..Table T01001 provides population counts for racial and ethnic groups at the nation and state levels. For county, tract, and place levels and American Indian/Alaska Native/Native Hawaiian (AIANNH) areas, Table T01001 provides population counts for racial and ethnic groups that met minimum population counts. For more information on the minimum population counts and accuracy, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Washington, D.C. and American Indian/Alaska Native/Native Hawaiian (AIANNH) areas may show data when there should not be any displayed. This is due to postprocessing to ensure counts for statistically equivalent and coterminous geographies are consistent. For more information, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Source: U.S. Census Bureau, 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A)

  11. a

    California Census 2020 Outreach and Communication Campaign Final Report

    • dru-data-portal-cacensus.hub.arcgis.com
    • data.ca.gov
    • +1more
    Updated Jun 29, 2023
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    Calif. Dept. of Finance Demographic Research Unit (2023). California Census 2020 Outreach and Communication Campaign Final Report [Dataset]. https://dru-data-portal-cacensus.hub.arcgis.com/documents/ea6bf917f7894bb0a1f66c0e4994d77e
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    Dataset updated
    Jun 29, 2023
    Dataset authored and provided by
    Calif. Dept. of Finance Demographic Research Unit
    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.

  12. 2020 Decennial Census: F_REGIONS | Components of Coverage for the Household...

    • data.census.gov
    Updated May 19, 2022
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    DEC (2022). 2020 Decennial Census: F_REGIONS | Components of Coverage for the Household Population in the United States by Census Region (DEC Decennial Post-Enumeration Survey) [Dataset]. https://data.census.gov/table/DECENNIALPES2020.F_REGIONS?q=census
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    Dataset updated
    May 19, 2022
    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
    Area covered
    United States
    Description

    0 or 0.0 Not applicable.-9999.9 Represents or rounds to zero.DSE: Dual-system estimate.Census counts are rounded. As a result, counts may not sum to totals shown. The census count for the West Region includes additional rounding to protect the count of the resident population in the Remote Alaska Type of Enumeration Area (TEA). The PES did not evaluate the coverage of the population living in Remote Alaska..A negative (positive) estimate of net coverage error indicates an undercount (overcount)..Standard errors are below the estimate..Source: U.S. Census Bureau, Decennial Statistical Studies Division, 2020 Post-Enumeration Survey (May 2022 Release).Post-Enumeration Survey estimates are subject to sampling and nonsampling errors. For information regarding data collection, definitions, sampling error, nonsampling error, and estimation methodology, see: Post-Enumeration Surveys.

  13. Decennial Census Population, Race & Ethnicity 1980 - 2020

    • data.cambridgema.gov
    csv, xlsx, xml
    Updated Aug 8, 2022
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    U.S. Census Bureau Data recompiled by Census Bureau or Cambridge Community Development Department (2022). Decennial Census Population, Race & Ethnicity 1980 - 2020 [Dataset]. https://data.cambridgema.gov/Neighborhood-Census-Data/Decennial-Census-Population-Race-Ethnicity-1980-20/rqau-pwa4
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Aug 8, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau Data recompiled by Census Bureau or Cambridge Community Development Department
    Description

    Data from the 1980 through 2020 decennial censuses recompiled to align with neighborhood boundaries. Include data for total population, race and Hispanic ethnicity.

  14. Population Estimates Statewide & County Current (Census)

    • data.pa.gov
    Updated Mar 28, 2022
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    US Census Bureau (2022). Population Estimates Statewide & County Current (Census) [Dataset]. https://data.pa.gov/Census-Economic/Population-Estimates-Statewide-County-Current-Cens/hv5f-e4e3
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    csv, application/rssxml, xml, tsv, application/rdfxml, application/geo+json, kmz, kmlAvailable download formats
    Dataset updated
    Mar 28, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    US Census Bureau
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The population and housing unit estimates are released on a flow basis throughout each year. Each new series of data (called vintages) incorporates the latest administrative record data, geographic boundaries, and methodology. Therefore, the entire time series of estimates beginning with the date of the most recent decennial census is revised annually, and estimates from different vintages of data may not be consistent across geography and characteristics detail.
    When multiple vintages of data are available, the most recent vintage is the preferred data.

    The vintage year (e.g., V2021) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified.

    Additional estimates files may also be accessed via the Census Bureau application programming interface (API).

    Additional information on the Census Bureau's Population Estimates Program (PEP) is available on the PEP's homepage Census Bureau's Population Estimates Program.

    Notes: For vintage 2019: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. All geographic boundaries for the 2019 population estimates are as of January 1, 2019.

    For vintage 2021: The estimates are developed from a base that incorporates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates. The estimates are developed from a base that incorporates the 2020 Census, Vintage 2020 estimates, and 2020 Demographic Analysis estimates.

    For population estimates methodology statements, see http://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html">http://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html.

    Sources: U.S. Census Bureau, Population Division Annual Estimates of the Resident Population for Counties in Pennsylvania: April 1, 2010 to July 1, 2019 (CO-EST2019-ANNRES-42) - Release Date: March 2020

    Annual Estimates of the Resident Population for Counties in Pennsylvania: April 1, 2020 to July 1, 2021 (CO-EST2021-POP-42) - Release Date: March 2022

  15. f

    1990 - 2020 Population Change (State of Georgia, multiple geographies)

    • gisdata.fultoncountyga.gov
    • opendata.atlantaregional.com
    Updated Nov 3, 2021
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    Georgia Association of Regional Commissions (2021). 1990 - 2020 Population Change (State of Georgia, multiple geographies) [Dataset]. https://gisdata.fultoncountyga.gov/maps/59dd97445d884cd6998336f84ba6ba77
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    Dataset updated
    Nov 3, 2021
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset is published by the Research & Analytics Group at the Atlanta Regional Commission to show population change by utilizing the 2020 redistricting data and comparable data for 2010, 2000, and 1990 across multiple geographies for the State of Georgia. For a deep dive into the data model including every specific metric, see the Data Manifest. The manifest details ARC-defined naming conventions, names/descriptions and topics where applicable, summary levels; source tables; notes and so forth for all metrics.

    It should be noted:The 2020 redistricting release is not as detailed in terms of data compared to ACS estimates; data include total population, population by race and ethnicity, and "voting age" population (i.e., adults) by race and ethnicity, adults are subtracted from the total population to show children (ages 0-17); total number of housing units, occupied housing units, and vacant housing units. Percent and change measures are calculated over four different Censuses.These data are expressed in terms of 2020 geographies such as the new 2020 Census tracts. This means that that historical data for geographies like cities have been estimated to the 2020 boundaries. For example, the city of Atlanta, which has made multiple annexations since 1990, has a higher estimated 1990 population of 400,452 (2020 boundaries) than the 394,017 reported in the 1990 Census (1990 boundaries).Due to changes in block geographies and annexations, 2010 population totals for custom geographies such as City of Atlanta NSAs may differ slightly from the numbers we have published in the past.The procedure to re-estimate historical data to 2020 blocks often results in fractional population (e.g., 1.25 instead of 1 or 2). Counts have been rounded to the nearest whole, but to be more precise, all aggregation, percent, and change measures were performed pre-rounding. Some change measures may appear curious as a result. For example, 100.4 - 20.8 = 79.6 which rounds to 80. But if rounded first, 100.4 rounds down to 100, 20.8 rounds up to 21; 100 - 21 = 79.Asian and Pacific Islander categories are combined to maximize compatibility with the 1990 release, which reported the two groups as a single category. Caution should be exercised with 1990 race data because the Census Bureau changed to the current system (which allows people to identify as biracial or multiracial) starting only in 2000.The "other" race category includes American Indian and Alaska Natives, people identifying with "some other race" and (for 2000 forward), people who identify as biracial or multiracial.For more information regarding Decennial Census source data, visit 2020 Census website

  16. US Census Bureau States And Counties Poverty Estimates 2020

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). US Census Bureau States And Counties Poverty Estimates 2020 [Dataset]. https://www.johnsnowlabs.com/marketplace/us-census-bureau-states-and-counties-poverty-estimates-2020/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    2020
    Area covered
    United States
    Description

    This dataset contains poverty estimates at county level based on US Census Bureau program, Small Area Income and Poverty Estimates (SAIPE). The estimates are for counties and states in the United States, for the entire population and for three age groups of population.

  17. d

    Boundaries: State of Texas Census Tracts (Based off 2020 Census)

    • catalog.data.gov
    • data.austintexas.gov
    • +2more
    Updated Apr 25, 2025
    + more versions
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    data.austintexas.gov (2025). Boundaries: State of Texas Census Tracts (Based off 2020 Census) [Dataset]. https://catalog.data.gov/dataset/boundaries-state-of-texas-census-tracts-based-off-2020-census
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    Dataset updated
    Apr 25, 2025
    Dataset provided by
    data.austintexas.gov
    Area covered
    Texas
    Description

    A census tract is a geographic area defined by the U.S. Census Bureau for the purpose of collecting and analyzing demographic data. Typically, a census tract contains a population of about 1,200 to 8,000 people and is designed to reflect homogenous social and economic characteristics. Tracts are used in various statistical analyses and are updated every ten years with the decennial census, allowing for a detailed understanding of population trends, housing, and economic conditions within specific communities. These files do not include demographic data, but they contain geographic entity codes that can be linked to the Census Bureau’s demographic data, available on https://data.census.gov. Terms of Use This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. It does not represent an on-the-ground survey and represents only the approximate relative location of property boundaries. This product has been produced by the US Census for the sole purpose of geographic reference. No warranty is made by the City of Austin regarding specific accuracy or completeness.

  18. P

    Census 2020 Table P3 12011 Place

    • data.pompanobeachfl.gov
    • geohub-bcgis.opendata.arcgis.com
    • +1more
    Updated Feb 28, 2023
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    External Datasets (2023). Census 2020 Table P3 12011 Place [Dataset]. https://data.pompanobeachfl.gov/dataset/census-2020-table-p3-12011-place
    Explore at:
    html, csv, arcgis geoservices rest api, zip, kml, geojsonAvailable 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 P3 – 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.

  19. P

    Census 2020 Table P3 12011 Block Groups

    • data.pompanobeachfl.gov
    Updated Feb 28, 2023
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    External Datasets (2023). Census 2020 Table P3 12011 Block Groups [Dataset]. https://data.pompanobeachfl.gov/dataset/census-2020-table-p3-12011-block-groups
    Explore at:
    zip, html, geojson, csv, 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 P3 – 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.

  20. C

    2020 Census Redistricting Data Extracts (PL 94-171)

    • data.wprdc.org
    • catalog.data.gov
    csv, html, pdf
    Updated May 21, 2023
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    University of Pittsburgh (2023). 2020 Census Redistricting Data Extracts (PL 94-171) [Dataset]. https://data.wprdc.org/dataset/2020-census-redistricting-data-extracts
    Explore at:
    pdf(437652), csv(87772), html, csv(634625), csv(11809)Available download formats
    Dataset updated
    May 21, 2023
    Dataset provided by
    University of Pittsburgh
    License

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

    Description

    Chris Briem of the University of Pittsburgh Center for Social and Urban Research has been producing extracts from the Census Bureau's PL 94-171 redistricting file.

    On August 12th, the U.S. Census Bureau released the first detailed data from the 2020 Decennial Census of Population and Housing. Before this, the only data that has been released from the 2020 Census has been total population counts by state needed for the reapportionment of congressional seats. The data just released is known as PL 94-171 data and includes the final census enumeration of the population by race and ethnicity for counties, municipalities, and smaller levels of geography.

    PL 94-171 data is used in the redrawing of the boundaries for federal, state, and local legislative districts, a process known as redistricting. This data includes housing unit counts, occupancy status for housing units, population totals, and population by race Hispanic/Latino origin, voting-age population (age 18+), and group quarters counts. The Census Bureau will be releasing additional data, including more detailed population and household statistics from the 2020 Census in the future.

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DVRPC (2025). Decennial Census Data, 2020 [Dataset]. https://catalog.dvrpc.org/dataset/decennial-census-data-2020

Decennial Census Data, 2020

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
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

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