58 datasets found
  1. Decennial Census: Redistricting Data (PL 94-171)

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • catalog.data.gov
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Decennial Census: Redistricting Data (PL 94-171) [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/decennial-census-redistricting-data-pl-94-171-e1360
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Public Law 94-171, enacted in 1975, directs the Census Bureau to make special preparations to provide redistricting data needed by the 50 states. It specifies that within a year following Census Day, the Census Bureau must send the governor and legislative leadership in each state the data they need to redraw districts for the United States Congress and state legislature. To meet this legal requirement, the Census Bureau set up a program that affords state officials an opportunity before each decennial census to define the small areas for which they wish to receive census population totals for redistricting purposes. Officials may receive data for voting districts (e.g., election precincts, wards) and state house and senate districts, in addition to standard census geographic areas such as counties, cities, census tracts, and tabulation blocks. State participation in defining areas is voluntary and nonpartisan.

  2. Decennial Census: National Redistricting Data

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Decennial Census: National Redistricting Data [Dataset]. https://catalog.data.gov/dataset/decennial-census-national-redistricting-data
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The 2010 Census National Summary File of Redistricting Data provides population counts for all persons and for persons 18 years and over by race (63 categories) and by Hispanic or Latino origin, as well as counts of all persons and persons 18 years and over that are not Hispanic/Latino cross-tabulated by race (63 categories). It provides the total housing unit counts and the counts of occupied and vacant units.The National Summary File of Redistricting Data is an extract of selected geographic areas (e.g., states, Congressional districts, and state legislative districts) previously released in the 2010 Census Redistricting Data (Public Law 94-171) Summary Files. In addition, this product provides summaries for the United States, regions, divisions, and other geographic areas that cross state boundaries, such as American Indian areas, metropolitan statistical areas, and micropolitan statistical areas.

  3. Data from: Congressional Districts

    • data.ca.gov
    • gis.data.ca.gov
    • +4more
    Updated Jul 28, 2025
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    Caltrans (2025). Congressional Districts [Dataset]. https://data.ca.gov/dataset/congressional-districts
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    zip, kml, csv, arcgis geoservices rest api, geojson, htmlAvailable download formats
    Dataset updated
    Jul 28, 2025
    Dataset provided by
    California Department of Transportationhttp://dot.ca.gov/
    Authors
    Caltrans
    License

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

    Description

    The 119th Congressional Districts dataset reflects boundaries from January 03, 2025 from the United States Census Bureau (USCB), and the attributes are updated every Sunday from the United States House of Representatives and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). 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. Information for each member of Congress is appended to the Census Congressional District shapefile using information from the Office of the Clerk, U.S. House of Representatives' website https://clerk.house.gov/xml/lists/MemberData.xml and its corresponding XML file. Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. This dataset also includes 9 geographies for non-voting at large delegate districts, resident commissioner districts, and congressional districts that are not defined. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 119th Congress is seated from January 3, 2025 through January 3, 2027. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The TIGER/Line shapefiles for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The boundaries of all other congressional districts reflect information provided to the Census Bureau by the states by May 31, 2024. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529006

  4. 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

  5. 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
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    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.

  6. H

    50-State Redistricting Simulations

    • dataverse.harvard.edu
    • search.dataone.org
    Updated May 2, 2023
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    Cory McCartan; Christopher T. Kenny; Tyler Simko; Shiro Kuriwaki; Garcia, George, III; Kevin Wang; Melissa Wu; Kosuke Imai (2023). 50-State Redistricting Simulations [Dataset]. http://doi.org/10.7910/DVN/SLCD3E
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 2, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Cory McCartan; Christopher T. Kenny; Tyler Simko; Shiro Kuriwaki; Garcia, George, III; Kevin Wang; Melissa Wu; Kosuke Imai
    License

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

    Description

    Every decade following the Census, states and municipalities must redraw districts for Congress, state houses, city councils, and more. The goal of the 50-State Simulation Project is to enable researchers, practitioners, and the general public to use cutting-edge redistricting simulation analysis to evaluate enacted congressional districts. Evaluating a redistricting plan requires analysts to take into account each state’s redistricting rules and particular political geography. Comparing the partisan bias of a plan for Texas with the bias of a plan for New York, for example, is likely misleading. Comparing a state’s current plan to a past plan is also problematic because of demographic and political changes over time. Redistricting simulations generate an ensemble of alternative redistricting plans within a given state which are tailored to its redistricting rules. Unlike traditional evaluation methods, therefore, simulations are able to directly account for the state’s political geography and redistricting criteria. This dataset contains sampled districting plans and accompanying summary statistics for all 50 U.S. states.

  7. a

    2020 Census State Redistricting Data (Public Law 94 171) Summary File

    • delaware-census-2020-delaware.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Sep 10, 2021
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    State of Delaware (2021). 2020 Census State Redistricting Data (Public Law 94 171) Summary File [Dataset]. https://delaware-census-2020-delaware.hub.arcgis.com/datasets/2020-census-state-redistricting-data-public-law-94-171-summary-file
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    Dataset updated
    Sep 10, 2021
    Dataset authored and provided by
    State of Delaware
    Description

    The 2020 Census State Redistrict Data Summary File pages 99 - 113 include the data dictionary reference name and table number and contents that identifies the data dictionary reference name.

  8. 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File

    • registry.opendata.aws
    • dataverse.harvard.edu
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    United States Census Bureau, 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File [Dataset]. https://registry.opendata.aws/census-2020-pl94-nmf/
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    License

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

    Description

    The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File (NMF) is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022] https://doi.org/10.1162/99608f92.529e3cb9, and implemented in the DAS 2020 Redistricting Production Code). The NMF was generated using the Census Bureau's implementation of the Discrete Gaussian Mechanism, calibrated to satisfy zero-Concentrated Differential Privacy with bounded neighbors.

    The NMF values, called noisy measurements are the output of applying the Discrete Gaussian Mechanism to counts from the 2020 Census Edited File (CEF). They are generally inconsistent with one another (for example, in a county composed of two tracts, the noisy measurement for the county's total population may not equal the sum of the noisy measurements of the two tracts' total population), and frequently negative (especially when the population being measured was small), but are integer-valued. The NMF was later post-processed as part of the DAS code to take the form of microdata and to satisfy various constraints. The NMF documented here contains both the noisy measurements themselves as well as the data needed to represent the DAS constraints; thus, the NMF could be used to reproduce the steps taken by the DAS code to produce microdata from the noisy measurements by applying the production code base.

    The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data initially collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File.

    The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2020 Census Redistricting Data (P.L. 94-171) Summary File --are provided.

  9. d

    2020 Redistricting Data for DC (District-wide)

    • catalog.data.gov
    • opdatahub.dc.gov
    • +3more
    Updated Feb 5, 2025
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    City of Washington, DC (2025). 2020 Redistricting Data for DC (District-wide) [Dataset]. https://catalog.data.gov/dataset/2020-redistricting-data-for-dc-district-wide
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

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

  10. a

    2020 Census State Redistricting Data - Total Population for Blocks /...

    • hub.arcgis.com
    • gis-kingcounty.opendata.arcgis.com
    Updated Sep 22, 2021
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    King County (2021). 2020 Census State Redistricting Data - Total Population for Blocks / blocks20 pl94totalpop [Dataset]. https://hub.arcgis.com/datasets/2297c03f93ab42e4a9cac05c66753aea
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    Dataset updated
    Sep 22, 2021
    Dataset authored and provided by
    King County
    Area covered
    Description

    US Census 2020 File01 (Tables P1 & P2), (P1) Race - Total Populationlation, and (P2) Race + Hispanic Origin. A unique logical record number (LOGRECNO in the geographic header) is assigned to all files for a specific geographic entity. This field is the key that links records across all four files. Besides the logical record number, other identifying fields also are carried over from the geographic header file to the table files. These are file identification (FILEID), state/U.S. abbreviation (STUSAB), characteristic iteration (CHARITER), and characteristic iteration file sequence number (CIFSN). The geographic header is standard across all electronic data products from the 2020 Census. Note that some fields in the Redistricting products are not filled. For example, the CHARITER field is used in other 2020 Census products; in the 2020 Census State Redistricting Data (Public Law 94-171) Summary File, it is always coded as 000, GEOIDs are related to Blocks. For tables P1 & P2 details refer to the online census documentation: 2020 Census State Redistricting Data (Public Law 94-171) Summary File

  11. c

    2020 Redistricting Data for DC Census Block Groups

    • s.cnmilf.com
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +3more
    Updated Feb 5, 2025
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    City of Washington, DC (2025). 2020 Redistricting Data for DC Census Block Groups [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/2020-redistricting-data-for-dc-census-block-groups
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

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

  12. TIGER/Line Shapefile, 2020, State, Nevada, Voting Districts

    • datasets.ai
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +1more
    23, 55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2020, State, Nevada, Voting Districts [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2020-state-nevada-voting-districts
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    23, 57, 55Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Nevada
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation.

    Voting district is the generic name for geographic entities such as precincts, wards, and election districts established by State governments for the purpose of conducting elections. States participating in the 2010 Census Redistricting Data Program as part of Public Law 94-171 (1975) provided the Census Bureau with boundaries, codes, and names for their VTDs. Each VTD is identified by a 1- to 6-character alphanumeric census code that is unique within county. For the 2010 Census, Kentucky and Rhode Island are the only States that did not provide voting district boundaries as part of Phase 2 (the Voting District Project) of the Redistricting Data Program and no VTDs exist for these States in the 2020 Census data products. Note that only Montana and Oregon do not have complete coverage of VTDs for the 2020 Census.

  13. a

    Community Reporting Areas (2020) - Redistricting Data 1990-2020

    • data-seattlecitygis.opendata.arcgis.com
    • data.seattle.gov
    • +1more
    Updated Aug 17, 2021
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    City of Seattle ArcGIS Online (2021). Community Reporting Areas (2020) - Redistricting Data 1990-2020 [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::community-reporting-areas-2020-redistricting-data-1990-2020
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    Dataset updated
    Aug 17, 2021
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    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

    Community Reporting Areas with selected 1990, 2000, 2010, 2020 P.L. 94-171 redistricting data. This includes group quarters population (institutionalized/non) from the 1990, 2000 and 2010 summary file to be consistent with the available 2020 data.For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File.

  14. A

    ‘King County Census 2020 blocks with PL 94-171 Redistricting Data’ analyzed...

    • analyst-2.ai
    Updated Aug 22, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘King County Census 2020 blocks with PL 94-171 Redistricting Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-king-county-census-2020-blocks-with-pl-94-171-redistricting-data-c348/51d2fc82/?iid=009-232&v=presentation
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    Dataset updated
    Aug 22, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    King County
    Description

    Analysis of ‘King County Census 2020 blocks with PL 94-171 Redistricting Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a7f057a4-8a34-418b-a6cf-88bc9eae6e73 on 13 February 2022.

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

    Census 2020 blocks in King County with selected P.L. 94-171 redistricting data.


    For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File.

    Important note: The Census Bureau advises analysts to aggregate blocks together to form larger geographic units before using the 2020 Census data.

    Background: The Bureau used a new tool, called Differential Privacy, to inject statistical noise into the 2020 Census data in order to protect privacy. The resulting noise can cause substantial inaccuracy at the block level; combining data for blocks and other small geographies reduces the inaccuracy. For more information see Redistricting Data: What to Expect and When (census.gov), 2020 Census Data Products: Disclosure Avoidance Modernization.

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

  15. A

    ‘Census 2020 Tracts with PL 94-171 Redistricting Data for 1990-2020’...

    • analyst-2.ai
    Updated Jan 27, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Census 2020 Tracts with PL 94-171 Redistricting Data for 1990-2020’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-census-2020-tracts-with-pl-94-171-redistricting-data-for-1990-2020-35b6/4ad40774/?iid=011-758&v=presentation
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    Dataset updated
    Jan 27, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Census 2020 Tracts with PL 94-171 Redistricting Data for 1990-2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e285af75-b5b5-4738-84ec-644ef7a03bef on 27 January 2022.

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

    Census 2020 Tracts with selected 1990, 2000, 2010, 2020 P.L. 94-171 redistricting data - includes a row for city totals.


    For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File.

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

  16. a

    2020 Census State Redistricting Data - Voting Age Population and Housing...

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Aug 24, 2021
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    King County (2021). 2020 Census State Redistricting Data - Voting Age Population and Housing Status for Blocks / blocks20 pl94voteagepophousing [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/kingcounty::2020-census-state-redistricting-data-voting-age-population-and-housing-status-for-blocks-blocks20-pl94voteagepophousing
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    Dataset updated
    Aug 24, 2021
    Dataset authored and provided by
    King County
    Area covered
    Description

    US Census 2020 File01 (Tables P3, P4, & H1), (P3) Race for the Population 18 Years and Over, (P4) Hispanic or Latino, and Not Hispanic or Latino by Race for the Population 18 Years and Over, and (H1) Housing Units Occupancy Status. A unique logical record number (LOGRECNO in the geographic header) is assigned to all files for a specific geographic entity. This field is the key that links records across all four files. Besides the logical record number, other identifying fields also are carried over from the geographic header file to the table files. These are file identification (FILEID), state/U.S. abbreviation (STUSAB), characteristic iteration (CHARITER), and characteristic iteration file sequence number (CIFSN). The geographic header is standard across all electronic data products from the 2020 Census. Note that some fields in the Redistricting products are not filled. For example, the CHARITER field is used in other 2020 Census products; in the 2020 Census State Redistricting Data (Public Law 94-171) Summary File, it is always coded as 000, GEOIDs are related to Blocks. For tables P3, P4, & H1 details refer to the online census documentation: 2020 Census State Redistricting Data (Public Law 94-171) Summary File

  17. Decennial Census P.L. 94-171 Redistricting Data (Block) (Tarrant County)

    • hub.arcgis.com
    Updated Aug 12, 2021
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    North Central Texas Council of Governments (2021). Decennial Census P.L. 94-171 Redistricting Data (Block) (Tarrant County) [Dataset]. https://hub.arcgis.com/datasets/NCTCOGGIS::decennial-census-p-l-94-171-redistricting-data-block-tarrant-county/about
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    Dataset updated
    Aug 12, 2021
    Dataset authored and provided by
    North Central Texas Council of Governments
    Area covered
    Tarrant County,
    Description

    These data do NOT reflect changes resulting from the 2020 Census Count Question Resolution Operation (CQR). For the revised data, see 2020 Decennial Census Notes and Errata. This dataset includes unaltered 2020 Census Public Law 94-17 data (P.L. 94-171 Redistricting Data) for census blocks within the Tarrant County. For more information including field descriptions, see 2020 PL Summary File Field Names and 2020 Census State Redistricting Data (Public Law 94-171) Summary File.

  18. A

    ‘Urban Centers and Villages with PL 94-171 Redistricting Data for 1990-2020’...

    • analyst-2.ai
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com), ‘Urban Centers and Villages with PL 94-171 Redistricting Data for 1990-2020’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-urban-centers-and-villages-with-pl-94-171-redistricting-data-for-1990-2020-5eee/3d4240a2/?iid=026-093&v=presentation
    Explore at:
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Urban Centers and Villages with PL 94-171 Redistricting Data for 1990-2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/6c085efa-1087-4b81-a3b6-970dbb6863b6 on 27 January 2022.

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

    Urban Centers and Villages with selected 1990, 2000, 2010, 2020 P.L. 94-171 redistricting data. This includes group quarters population (institutionalized/non) from the 1990, 2000 and 2010 summary file to be consistent with the available 2020 data.


    For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File.

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

  19. California Schools and Legislative Districts

    • data.ca.gov
    • gis.data.ca.gov
    • +4more
    html
    Updated Dec 7, 2022
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    California Department of Education (2022). California Schools and Legislative Districts [Dataset]. https://data.ca.gov/dataset/california-schools-and-legislative-districts
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    htmlAvailable download formats
    Dataset updated
    Dec 7, 2022
    Dataset authored and provided by
    California Department of Educationhttps://www.cde.ca.gov/
    Area covered
    California
    Description

    This web map of California legislative districts includes the geographically defined territories used for representation in the California State Assembly, California State Senate and the US House of Representatives from California. These three boundary layers are derived from the US Census Bureau's 2018 TIGER/Line database and are designed to overlay with the California Department of Education’s (CDE) education related GIS content.

    The 80 California State Assembly Districts represent the geographically defined territories used for electing members to the lower (house) chamber of the California State Legislature. The current state assembly boundaries were determined by the California Citizens Redistricting Commission following the completion of the 2010 United States Census and will remain valid until 2020.

    The 40 state senate districts represent the geographically defined territories used for electing members to the upper (senate) chamber of the California State Legislature. The current state senate boundaries were determined by the California Citizens Redistricting Commission following the completion of the 2010 United States Census and will remain valid until 2020.

    The 53 congressional districts within the State of California represent the geographically defined territories used for electing members to the U.S. House of Representatives. The current U.S. Congressional boundaries in California were determined by the California Citizens Redistricting Commission following the completion of the 2010 United States Census and will remain valid until 2020

  20. a

    2020 Census Block King County - Redistricting Data 2020

    • hub.arcgis.com
    • data.seattle.gov
    • +2more
    Updated Aug 17, 2021
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    City of Seattle ArcGIS Online (2021). 2020 Census Block King County - Redistricting Data 2020 [Dataset]. https://hub.arcgis.com/datasets/SeattleCityGIS::2020-census-block-king-county-redistricting-data-2020?uiVersion=content-views
    Explore at:
    Dataset updated
    Aug 17, 2021
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    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

    Census 2020 blocks in King County with selected P.L. 94-171 redistricting data.For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File. Important note: The Census Bureau advises analysts to aggregate blocks together to form larger geographic units before using the 2020 Census data. Background: The Bureau used a new tool, called Differential Privacy, to inject statistical noise into the 2020 Census data in order to protect privacy. The resulting noise can cause substantial inaccuracy at the block level; combining data for blocks and other small geographies reduces the inaccuracy. For more information see Redistricting Data: What to Expect and When (census.gov), 2020 Census Data Products: Disclosure Avoidance Modernization.

Share
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U.S. Census Bureau (2023). Decennial Census: Redistricting Data (PL 94-171) [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/decennial-census-redistricting-data-pl-94-171-e1360
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Decennial Census: Redistricting Data (PL 94-171)

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Dataset updated
Jul 19, 2023
Dataset provided by
United States Census Bureauhttp://census.gov/
Description

Public Law 94-171, enacted in 1975, directs the Census Bureau to make special preparations to provide redistricting data needed by the 50 states. It specifies that within a year following Census Day, the Census Bureau must send the governor and legislative leadership in each state the data they need to redraw districts for the United States Congress and state legislature. To meet this legal requirement, the Census Bureau set up a program that affords state officials an opportunity before each decennial census to define the small areas for which they wish to receive census population totals for redistricting purposes. Officials may receive data for voting districts (e.g., election precincts, wards) and state house and senate districts, in addition to standard census geographic areas such as counties, cities, census tracts, and tabulation blocks. State participation in defining areas is voluntary and nonpartisan.

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