,Census Block Groups from 2020. Redistricting Data (P.L. 94-171).,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,,Geography: Block Groups,Current Vintage: 2020,P.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 Status,Data downloaded from: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html,National Figures: data.census.gov,Public 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.html,

,Census Tracts from 2020. Redistricting Data (P.L. 94-171).,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,,Geography: Census Tracts,Current Vintage: 2020,P.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 Status,Data downloaded from: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html,National Figures: data.census.gov,Public 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.html,

,District-wide 2020 Redistricting Data (P.L. 94-171).,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,,Geography: District of Columbia,Current Vintage: 2020,P.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 Status,Data downloaded from: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html,National Figures: data.census.gov,Public 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.html,

,District-wide 2020 Redistricting Data (P.L. 94-171).,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,,Geography: District of Columbia 2022 Wards (State Legislative Districts [Upper Chamber]),Current Vintage: 2020,P.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 Status,Data downloaded from: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html,National Figures: data.census.gov,Public 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.html,

,Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data.,,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,Geography: Census Tracts,Current Vintage: 2018-2022,ACS Table(s): DP05,Data downloaded from: Census Bureau's API for American Community Survey,Date of API call: January 2, 2024,National Figures: data.census.gov,,The United States Census Bureau's American Community Survey (ACS):,This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.,,Data Note from the Census:,Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.,,Data Processing Notes:,

,Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data.,,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,Geography: District of Columbia,Current Vintage: 2018-2022,ACS Table(s): DP05,Data downloaded from: Census Bureau's API for American Community Survey,Date of API call: January 2, 2024,National Figures: data.census.gov,,The United States Census Bureau's American Community Survey (ACS):,This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.,,Data Note from the Census:,Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.,,Data Processing Notes:,

,Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data.,,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,Geography: Census Tracts,Current Vintage: 2018-2022,ACS Table(s): DP03,Data downloaded from: Census Bureau's API for American Community Survey,Date of API call: January 2, 2024,National Figures: data.census.gov,,The United States Census Bureau's American Community Survey (ACS):,This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.,,Data Note from the Census:,Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.,,Data Processing Notes:,

,Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data.,,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,Geography: 2022 Wards (State Legislative Districts [Upper Chamber]),Current Vintage: 2018-2022,ACS Table(s): DP05,Data downloaded from: Census Bureau's API for American Community Survey,Date of API call: January 2, 2024,National Figures: data.census.gov,,The United States Census Bureau's American Community Survey (ACS):,This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.,,Data Note from the Census:,Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.,,Data Processing Notes:,,

,Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data.,,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,Geography: District of Columbia,Current Vintage: 2018-2022,ACS Table(s): DP03,Data downloaded from: Census Bureau's API for American Community Survey,Date of API call: January 2, 2024,National Figures: data.census.gov,,The United States Census Bureau's American Community Survey (ACS):,This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.,,Data Note from the Census:,Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.,,Data Processing Notes:,

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