,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:,

,

Age, Sex, Race, and Ethnicity variables from the 1-Year ACS,,Contact: District of Columbia, Office of Planning. Email: planning@dc.gov,Geography: District of Columbia,Current Vintage: 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: 2022 Wards (State Legislative Districts [Upper Chamber]),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:,

,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:,,

,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:,

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