71 datasets found
  1. a

    Census Tracts 2020

    • hub.arcgis.com
    • gisopendata-countyofriverside.opendata.arcgis.com
    Updated Sep 21, 2023
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    Riverside County Mapping Portal (2023). Census Tracts 2020 [Dataset]. https://hub.arcgis.com/maps/CountyofRiverside::census-tracts-2020
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    Dataset updated
    Sep 21, 2023
    Dataset authored and provided by
    Riverside County Mapping Portal
    Area covered
    Description

    Field Definition:GEOID - "Census tract identifier; a concatenation of 2020 Census state FIPS code, county FIPS code, and census tract code"NAMELSAD - Census translated legal/statistical area description and the census tract nameALAND - Census Area LandAWATER - Census Area waterINTPTLAT - Census Internal Point (Latitude)INTPTLON - Census Internal Point (Longitude)NAME20 - "2020 Census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"POPULATION - Total PopulationP18PLUS - Population 18 years and olderHHPOP - Household PopulationGQ - Group Quarters PopulationHOUSING - Total Housing unitsOCCUNITS - Occupied Housing Units (Households)VACUNITS - Vacant Housing UnitsVACRATE -Vacancy RateHISPANIC - Hispanic or Latino NH_WHT - Not Hispanic or Latino, White alone NH_BLK - Not Hispanic or Latino, Black or African American alone NH_IND - Not Hispanic or Latino, American Indian and Alaska Native aloneNH_ASN - Not Hispanic or Latino, Asian aloneNH_HWN - Not Hispanic or Latino, Native Hawaiian and Other Pacific Islander alone NH_OTH - Not Hispanic or Latino, Some Other Race alone NH_TWO - Not Hispanic or Latino, Population of two or more races

  2. D

    Census Tract to Municipality (MCD) Relationships

    • catalog.dvrpc.org
    • staging-catalog.cloud.dvrpc.org
    csv
    Updated Mar 17, 2025
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    DVRPC (2025). Census Tract to Municipality (MCD) Relationships [Dataset]. https://catalog.dvrpc.org/dataset/census-tract-to-municipality-relationships
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    csv(82700)Available download formats
    Dataset updated
    Mar 17, 2025
    Dataset provided by
    Delaware Valley Regional Planning Commissionhttps://www.dvrpc.org/
    Authors
    DVRPC
    License

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

    Description

    Census Tracts are statistical areas that do not always "nest" inside municipalities. The resources in this dataset provide a Census Tract identifier and lists the municipalities that each tract aligns with. This is for the entire DVRPC 9-county region.

  3. PLACES: Census Tract Data (GIS Friendly Format), 2024 release

    • catalog.data.gov
    • healthdata.gov
    • +3more
    Updated Feb 3, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). PLACES: Census Tract Data (GIS Friendly Format), 2024 release [Dataset]. https://catalog.data.gov/dataset/places-census-tract-data-gis-friendly-format-2020-release-fb1ec
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the Census tract 2022 boundary file in a GIS system to produce maps for 40 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

  4. REV 2.0 Eligible and Ineligible Census Tracts

    • data.cnra.ca.gov
    • gis.data.cnra.ca.gov
    • +2more
    Updated Apr 8, 2024
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    California Energy Commission (2024). REV 2.0 Eligible and Ineligible Census Tracts [Dataset]. https://data.cnra.ca.gov/dataset/rev-2-0-eligible-and-ineligible-census-tracts
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    arcgis geoservices rest api, geojson, zip, kml, html, csvAvailable download formats
    Dataset updated
    Apr 8, 2024
    Dataset authored and provided by
    California Energy Commissionhttp://www.energy.ca.gov/
    License

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

    Description

    Census tracts are designated as urban, rural center, or rural through SB 1000 analysis. These designations are being used for the REV 2.0 and Community Charging in Urban Areas GFOs.

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

  5. a

    2020 Census Tracts for King County / tracts20 area

    • hub.arcgis.com
    • king-snocoplanning.opendata.arcgis.com
    • +1more
    Updated Aug 19, 2021
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    King County (2021). 2020 Census Tracts for King County / tracts20 area [Dataset]. https://hub.arcgis.com/datasets/0a4fb77d7dfd447da745b744c0a14bdc
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    Dataset updated
    Aug 19, 2021
    Dataset authored and provided by
    King County
    Area covered
    Description

    This layer contains a unique geographic identifier (GEO_ID_TRT) for each tract group that is the key field for the data from censuses and surveys such as Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program. Data from many of the Census Bureau’s surveys and censuses, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/). All original TIGER/Line shapefiles and geodatabases with demographic data are available atThe 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) Database (MTDB). The shapefiles include information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The shapefiles include polygon boundaries of geographic areas and features, linear features including roads and hydrography, and point features. These shapefiles do not contain any sensitive data or confidential data protected by Title 13 of the U.S.C.Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and are reviewed and updated by local participants prior to each decennial census. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data. Census tracts generally have a population size of 1,200 to 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts. Census tract boundaries generally follow visible and identifiable features. Census tract boundaries may follow legal boundaries. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix, for example, 1457.02. The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Full documentation: https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc.pdf

  6. a

    2020 Census Tracts

    • hub.arcgis.com
    • geohub.lacity.org
    • +3more
    Updated Mar 19, 2021
    + more versions
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    County of Los Angeles (2021). 2020 Census Tracts [Dataset]. https://hub.arcgis.com/maps/lacounty::2020-census-tracts-4
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    Dataset updated
    Mar 19, 2021
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    The Census Bureau (https://www.census.gov/) maintains geographic boundaries for the analysis and mapping of demographic information across the United States. Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau releases the results of this county as demographic data with geographic identifiers so that maps and analysis can be performed on the US population. There are little more Census Tracts within Los Angeles County in 2020 Census TIGER/Line Shapefiles, compared to 2010.Created/Updated: Updated on September 2023, to merged Long Beach Breakwater land-based tracts silver polygons into bigger tract 990300 as per 2022 TIGER Line Shapefiles, and to update Santa Catalina Islands and San Clemente Islands tract boundary based on DPW City boundaries (except 599000 tract in Avalon). Updated on Sep 2022 and Dec 2022, to align tract boundary along city boundaries. Created on March 2021. How was this data created? This geographic file was downloaded from Census Bureau website: https://www2.census.gov/geo/tiger/TIGER2020PL/STATE/06_CALIFORNIA/06037/on February, 2021 and customized for LA County. Data Fields:1. CT20 (TRACTCE20): 6-digit census tract number, 2. Label (NAME20): Decimal point census tract number.

  7. l

    2010 Census Tracts

    • data.lacounty.gov
    • geohub.lacity.org
    • +2more
    Updated Sep 9, 2020
    + more versions
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    County of Los Angeles (2020). 2010 Census Tracts [Dataset]. https://data.lacounty.gov/datasets/2010-census-tracts-2/about
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    Dataset updated
    Sep 9, 2020
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    What is unique about LA County’s data?It is clipped to the ocean boundary. Raw Census data includes a 3 mile buffer into the ocean, which impacts cartography.IMPORTANT! It has been updated to the 2012 Census Geography Update, which merged Tracts 1370.00 and 9304.01 into the combined tract 1370.00. So the CT10 field actually reflects the 2012 Census update, which is used for all population products 2012 and later.How was this data created?This data was downloaded from Census Bureau website: http://www.census.gov/cgi-bin/geo/shapefiles2010/file-download and clipped to the County Boundary using ESRI’s ArcGIS Desktop. Two new fields were added in census tract data – area in square feet and shape length in feet. This dataset has unique identifier field “GEOID10” for each record and the census tract number fields “CT10” and “LABEL” (6-digit number and 6-digit number with decimal point, respectively).

  8. D

    2020 Census Tracts; PA, NJ, DE & MD

    • catalog.dvrpc.org
    • staging-catalog.cloud.dvrpc.org
    • +1more
    api, geojson, html +1
    Updated May 23, 2025
    + more versions
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    DVRPC (2025). 2020 Census Tracts; PA, NJ, DE & MD [Dataset]. https://catalog.dvrpc.org/dataset/2020-census-tracts-pa-nj-de-md
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    xml, html, api, geojsonAvailable download formats
    Dataset updated
    May 23, 2025
    Dataset authored and provided by
    DVRPC
    Area covered
    New Jersey, Pennsylvania
    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/). Census Tracts are small, relatively permanent statistical subdivisions of a county or statistically equivalent entity that can be updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP). The Census Bureau delineates census tracts in situations where no local participant responded or where state, local, or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of statistical data. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however, the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census. Census tracts occasionally are split due to population growth or merged as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow nonvisible 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. Tribal census tracts are a unique geographic entity defined within federally recognized American Indian reservations and off-reservation trust lands and can cross state and county boundaries. The tribal census tracts may be completely different from the standard county-based census tracts defined for the same area. (see “Tribal Census Tract”). Downloaded from https://www2.census.gov/geo/tiger/TIGER2022/TRACT/ on June 22, 2023

  9. Census Tracts in 2010

    • s.cnmilf.com
    • opendata.dc.gov
    • +4more
    Updated Apr 30, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division (2025). Census Tracts in 2010 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/census-tracts-in-2010
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    Dataset updated
    Apr 30, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

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

  10. New York City Census Data

    • kaggle.com
    Updated Aug 4, 2017
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    MuonNeutrino (2017). New York City Census Data [Dataset]. https://www.kaggle.com/datasets/muonneutrino/new-york-city-census-data/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 4, 2017
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    MuonNeutrino
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    New York
    Description

    Context

    There are a number of Kaggle datasets that provide spatial data around New York City. For many of these, it may be quite interesting to relate the data to the demographic and economic characteristics of nearby neighborhoods. I hope this data set will allow for making these comparisons without too much difficulty.

    Exploring the data and making maps could be quite interesting as well.

    Content

    This dataset contains two CSV files:

    1. nyc_census_tracts.csv

      This file contains a selection of census data taken from the ACS DP03 and DP05 tables. Things like total population, racial/ethnic demographic information, employment and commuting characteristics, and more are contained here. There is a great deal of additional data in the raw tables retrieved from the US Census Bureau website, so I could easily add more fields if there is enough interest.

      I obtained data for individual census tracts, which typically contain several thousand residents.

    2. census_block_loc.csv

      For this file, I used an online FCC census block lookup tool to retrieve the census block code for a 200 x 200 grid containing New York City and a bit of the surrounding area. This file contains the coordinates and associated census block codes along
      with the state and county names to make things a bit more readable to users.

      Each census tract is split into a number of blocks, so one must extract the census tract code from the block code.

    Acknowledgements

    The data here was taken from the American Community Survey 2015 5-year estimates (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml).

    The census block coordinate data was taken from the FCC Census Block Conversions API (https://www.fcc.gov/general/census-block-conversions-api)

    As public data from the US government, this is not subject to copyright within the US and should be considered public domain.

  11. b

    Baltimore City Qualified Census Tracts

    • data.baltimorecity.gov
    Updated Jun 1, 2023
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    Baltimore City (2023). Baltimore City Qualified Census Tracts [Dataset]. https://data.baltimorecity.gov/datasets/baltimore::baltimore-city-qualified-census-tracts-1
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    Dataset updated
    Jun 1, 2023
    Dataset authored and provided by
    Baltimore City
    License

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

    Area covered
    Description

    Qualified Census Tract geometries within Baltimore City Limits. Based on data from HUD published September 2024.Change Log2022-2-15:- Added FY2022 data- Metadata added- Columns renamed to a standard format- Agency names reformatted with Workday conventions2024-8-27:update the dataset and metadata to reflect the current data and descriptionData Dictionaryfield_namedescriptiondata_typerange_of_possible_valuesexample_valuessearchableCensus Tract 2010 The ID of the US census tract from 2010 Census results. Only Qualified Census tracts are includedTextIDs of QCT's in Baltimore city range from 24510030100 to 24510280500, but not by regular intervals since only tracts designated QCT are listed. The values are not integers, they are numerical IDs.24510070200NogeometryMulti-polygon shapes for each census tractThese are shape polygons, thus don't have a single value or expected rangeNo To leave feedback or ask a question about this dataset, please fill out the following form: Baltimore City Qualified Census Tracts feedback form.

  12. O

    Census Tract 2010

    • data.sccgov.org
    Updated May 2, 2023
    + more versions
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    (2023). Census Tract 2010 [Dataset]. https://data.sccgov.org/dataset/Census-Tract-2010/nxaw-7ash
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    tsv, application/geo+json, application/rdfxml, csv, xml, application/rssxml, kml, kmzAvailable download formats
    Dataset updated
    May 2, 2023
    Description

    Census tract geometry within Santa Clara County from the 2010 Census Tiger shapefiles.Feature class derived from Tiger line shapefile of 2010 census tracts for Santa Clara County and geographic identifier table, G001. Some attribute names may be when exporting as shapefile due to 10 character limitation of shapefile attribute names. THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

  13. o

    Historic Redlining Indicator for 2000, 2010, and 2020 US Census Tracts

    • openicpsr.org
    spss
    Updated May 25, 2021
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    Helen C.S. Meier; Bruce C. Mitchell (2021). Historic Redlining Indicator for 2000, 2010, and 2020 US Census Tracts [Dataset]. http://doi.org/10.3886/E141121V3
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    spssAvailable download formats
    Dataset updated
    May 25, 2021
    Dataset provided by
    University of Michigan. Institute for Social Research. Survey Research Center
    National Community Reinvestment Coalition
    Authors
    Helen C.S. Meier; Bruce C. Mitchell
    License

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

    Area covered
    United States
    Description

    The Home Owners’ Loan Corporation (HOLC) was a U.S. federal agency that graded mortgage investment risk of neighborhoods across the U.S. between 1935 and 1940. HOLC residential security maps standardized neighborhood risk appraisal methods that included race and ethnicity, pioneering the institutional logic of residential “redlining.” The Mapping Inequality Project digitized the HOLC mortgage security risk maps from the 1930s. We overlaid the HOLC maps with 2010 and 2020 census tracts for 142 cities across the U.S. using ArcGIS and determined the proportion of HOLC residential security grades contained within the boundaries. We assigned a numerical value to each HOLC risk category as follows: 1 for “A” grade, 2 for “B” grade, 3 for “C” grade, and 4 for “D” grade. We calculated a historic redlining score from the summed proportion of HOLC residential security grades multiplied by a weighting factor based on area within each census tract. A higher score means greater redlining of the census tract. Continuous historic redlining score, assessing the degree of “redlining,” as well as 4 equal interval divisions of redlining, can be linked to existing data sources by census tract identifier allowing for one form of structural racism in the housing market to be assessed with a variety of outcomes. The 2010 files are set to census 2010 tract boundaries. The 2020 files use the new census 2020 tract boundaries, reflecting the increase in the number of tracts from 12,888 in 2010, to 13,488 in 2020. Use the 2010 HRI with decennial census 2010 or ACS 2010-2019 data. As of publication (10/15/2020) decennial census 2020 data for the P1 (population) and H1 (housing) files are available from census. Updated (8/9/2023) - The Historic Redlining Score has been renamed the Historic Redlining Indicator or HRI. The HRI has also been calculated for Census 2000 boundaries.

  14. 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.

  15. US Census Demographic Data

    • kaggle.com
    zip
    Updated Mar 3, 2019
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    MuonNeutrino (2019). US Census Demographic Data [Dataset]. https://www.kaggle.com/muonneutrino/us-census-demographic-data
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    zip(11110116 bytes)Available download formats
    Dataset updated
    Mar 3, 2019
    Authors
    MuonNeutrino
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    This dataset expands on my earlier New York City Census Data dataset. It includes data from the entire country instead of just New York City. The expanded data will allow for much more interesting analyses and will also be much more useful at supporting other data sets.

    Content

    The data here are taken from the DP03 and DP05 tables of the 2015 American Community Survey 5-year estimates. The full datasets and much more can be found at the American Factfinder website. Currently, I include two data files:

    1. acs2015_census_tract_data.csv: Data for each census tract in the US, including DC and Puerto Rico.
    2. acs2015_county_data.csv: Data for each county or county equivalent in the US, including DC and Puerto Rico.

    The two files have the same structure, with just a small difference in the name of the id column. Counties are political subdivisions, and the boundaries of some have been set for centuries. Census tracts, however, are defined by the census bureau and will have a much more consistent size. A typical census tract has around 5000 or so residents.

    The Census Bureau updates the estimates approximately every year. At least some of the 2016 data is already available, so I will likely update this in the near future.

    Acknowledgements

    The data here were collected by the US Census Bureau. As a product of the US federal government, this is not subject to copyright within the US.

    Inspiration

    There are many questions that we could try to answer with the data here. Can we predict things such as the state (classification) or household income (regression)? What kinds of clusters can we find in the data? What other datasets can be improved by the addition of census data?

  16. c

    Census Tracts in City of Rochester 2020

    • data.cityofrochester.gov
    Updated Dec 14, 2022
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    Open_Data_Admin (2022). Census Tracts in City of Rochester 2020 [Dataset]. https://data.cityofrochester.gov/datasets/d9566b49caa7470cacad1ef6569c3b6c
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    Dataset updated
    Dec 14, 2022
    Dataset authored and provided by
    Open_Data_Admin
    Area covered
    Description

    Dataset Summary About this data: This layer presents the USA 2020 Census tracts within the City of Rochester boundary. The geography is sourced from US Census Bureau 2020 TIGER FGDB (National Sub-State) and cut by the City of Rochester boundary. Data Dictionary: STATE_ABBR: The two-letter abbreviation for a state (such as NY). STATE_FIPS: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state. New York State is 36. COUNTY_FIP: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county. Monroe County is 055. STCO_FIPS: The five-digit Federal Information Processing Standards (FIPS) code assigned to iedntify a unique county, typically as a concatenation of the State FIPS code and the County FIPS code. TRACT_FIPS: The six-digit number assigned to each census tract in a US county. FIPS: A unique geographic identifier, typically as a concatenation of State FIPS code, County FIPS code, and Census tract code. POPULATION: The population of a census tract. POP_SQMI: The population per square mile of a census tract. SQMI: The size of a census tract in square miles. Division: The name of the City of Rochester data division that the census tract falls in to. Source: This data comes from the Census Bureau.

  17. H

    2020 General Election Voting by US Census Block Group

    • dataverse.harvard.edu
    Updated Mar 10, 2025
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    Michael Bryan (2025). 2020 General Election Voting by US Census Block Group [Dataset]. http://doi.org/10.7910/DVN/NKNWBX
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 10, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Michael Bryan
    License

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

    Description

    PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau practices "data suppression", filtering some block groups from demographic publication because they do not meet a population threshold. This practice...

  18. m

    2020 Adjusted Tracts

    • gis.data.mass.gov
    • hub.arcgis.com
    Updated Nov 2, 2021
    + more versions
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    City of Cambridge (2021). 2020 Adjusted Tracts [Dataset]. https://gis.data.mass.gov/datasets/CambridgeGIS::2020-adjusted-tracts
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    Dataset updated
    Nov 2, 2021
    Dataset authored and provided by
    City of Cambridge
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Description

    This polygon layer contains the boundaries of the 33 Census tracts that make up the City of Cambridge for the 2020 Census. Where appropriate, the boundary lines provided by the U.S. Census were adjusted by City staff to match those lines to such features as the City boundary, street centerlines, and parcel lines.Explore all our data on the Cambridge GIS Data Dictionary.Attributes NameType DetailsDescription STATEFP20 type: Stringwidth: 2precision: 0 2020 Census state FIPS code

    COUNTYFP20 type: Stringwidth: 3precision: 0 2020 Census county FIPS code

    TRACTCE20 type: Stringwidth: 6precision: 0 2020 Census tract code

    GEOID20 type: Stringwidth: 12precision: 0 Census tract identifier; a concatenation of Current state FIPS code, county FIPS code, and census tract code

    NAME20 type: Stringwidth: 7precision: 0 2020 Census tract name, this is the census tract code converted to an integer or integer with 2-decimals if the last two characters of the code are not both zeros.

    NAMELSAD20 type: Stringwidth: 13precision: 0 2020 translated legal/statistical area description and the census tract name

    MTFCC20 type: Stringwidth: 5precision: 0 MAF/TIGER Feature Class Code

    FUNCSTAT20 type: Stringwidth: 1precision: 0 2020 functional status

    ALAND20 type: Doublewidth: 8precision: 38 2020 land area (unadjusted - matches raw Census TIGER data)

    AWATER20 type: Doublewidth: 8precision: 38 2020 water area (unadjusted - matches raw Census TIGER data)

    INTPTLAT20 type: Stringwidth: 11precision: 0 2020 latitude of the internal point (unadjusted - matches raw Census TIGER data)

    INTPTLON20 type: Stringwidth: 12precision: 0 2020 longitude of the internal point (unadjusted - matches raw Census TIGER data)

    created_date type: Datewidth: 8precision: 0

    last_edited_date type: Datewidth: 8precision: 0

  19. o

    Historic Redlining Scores for 2010 and 2020 US Census Tracts

    • openicpsr.org
    spss
    Updated May 25, 2021
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    Helen C.S. Meier; Bruce C. Mitchell (2021). Historic Redlining Scores for 2010 and 2020 US Census Tracts [Dataset]. http://doi.org/10.3886/E141121V2
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    spssAvailable download formats
    Dataset updated
    May 25, 2021
    Dataset provided by
    University of Michigan. Institute for Social Research. Survey Research Center
    National Community Reinvestment Coalition
    Authors
    Helen C.S. Meier; Bruce C. Mitchell
    License

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

    Area covered
    United States
    Description

    The Home Owners’ Loan Corporation (HOLC) was a U.S. federal agency that graded mortgage investment risk of neighborhoods across the U.S. between 1935 and 1940. HOLC residential security maps standardized neighborhood risk appraisal methods that included race and ethnicity, pioneering the institutional logic of residential “redlining.” The Mapping Inequality Project digitized the HOLC mortgage security risk maps from the 1930s. We overlaid the HOLC maps with 2010 and 2020 census tracts for 142 cities across the U.S. using ArcGIS and determined the proportion of HOLC residential security grades contained within the boundaries. We assigned a numerical value to each HOLC risk category as follows: 1 for “A” grade, 2 for “B” grade, 3 for “C” grade, and 4 for “D” grade. We calculated a historic redlining score from the summed proportion of HOLC residential security grades multiplied by a weighting factor based on area within each census tract. A higher score means greater redlining of the census tract. Continuous historic redlining score, assessing the degree of “redlining,” as well as 4 equal interval divisions of redlining, can be linked to existing data sources by census tract identifier allowing for one form of structural racism in the housing market to be assessed with a variety of outcomes. The 2010 files are set to census 2010 tract boundaries. The 2020 files use the new census 2020 tract boundaries, reflecting the increase in the number of tracts from 12,888 in 2010, to 13,488 in 2020. Use the 2010 HRS with decennial census 2010 or ACS 2010-2019 data. As of publication (10/15/2020) decennial census 2020 data for the P1 (population) and H1 (housing) files are available from census.

  20. US ZIP codes to Census Tracts

    • redivis.com
    application/jsonl +7
    Updated Dec 2, 2019
    + more versions
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    Stanford Center for Population Health Sciences (2019). US ZIP codes to Census Tracts [Dataset]. http://doi.org/10.57761/4h0s-2j79
    Explore at:
    csv, avro, parquet, sas, stata, spss, arrow, application/jsonlAvailable download formats
    Dataset updated
    Dec 2, 2019
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 1, 2010 - Apr 1, 2019
    Description

    Abstract

    A crosswalk dataset matching US ZIP codes to corresponding census tracts

    Documentation

    The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.

    **Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.

    So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.

    https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)

    Census tract definition

    A census tract, census area, census district or meshblock is a geographic region defined for the purpose of taking a census. Sometimes these coincide with the limits of cities, towns or other administrative areas and several tracts commonly exist within a county. In unincorporated areas of the United States these are often arbitrary, except for coinciding with political lines.

    Further reading

    The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.

    Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf

    Contact information

    Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.

    Acknowledgement

    This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook

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Riverside County Mapping Portal (2023). Census Tracts 2020 [Dataset]. https://hub.arcgis.com/maps/CountyofRiverside::census-tracts-2020

Census Tracts 2020

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30 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 21, 2023
Dataset authored and provided by
Riverside County Mapping Portal
Area covered
Description

Field Definition:GEOID - "Census tract identifier; a concatenation of 2020 Census state FIPS code, county FIPS code, and census tract code"NAMELSAD - Census translated legal/statistical area description and the census tract nameALAND - Census Area LandAWATER - Census Area waterINTPTLAT - Census Internal Point (Latitude)INTPTLON - Census Internal Point (Longitude)NAME20 - "2020 Census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"POPULATION - Total PopulationP18PLUS - Population 18 years and olderHHPOP - Household PopulationGQ - Group Quarters PopulationHOUSING - Total Housing unitsOCCUNITS - Occupied Housing Units (Households)VACUNITS - Vacant Housing UnitsVACRATE -Vacancy RateHISPANIC - Hispanic or Latino NH_WHT - Not Hispanic or Latino, White alone NH_BLK - Not Hispanic or Latino, Black or African American alone NH_IND - Not Hispanic or Latino, American Indian and Alaska Native aloneNH_ASN - Not Hispanic or Latino, Asian aloneNH_HWN - Not Hispanic or Latino, Native Hawaiian and Other Pacific Islander alone NH_OTH - Not Hispanic or Latino, Some Other Race alone NH_TWO - Not Hispanic or Latino, Population of two or more races

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