2 datasets found
  1. D

    Census Tract Top 50 American Community Survey Data

    • data.seattle.gov
    • hub.arcgis.com
    • +1more
    application/rdfxml +5
    Updated Feb 3, 2025
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    (2025). Census Tract Top 50 American Community Survey Data [Dataset]. https://data.seattle.gov/dataset/Census-Tract-Top-50-American-Community-Survey-Data/jya9-y5bv/data
    Explore at:
    application/rdfxml, csv, json, application/rssxml, tsv, xmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Description

    Data from: American Community Survey, 5-year Series


    King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 of over 50 attributes of the most requested data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.

    The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades.

    Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

    Vintages: 2010, 2015, 2020, 2021, 2022, 2023
    ACS Table(s): DP02, DP03, DP04, DP05


    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:
  2. D

    Race by Age Groups (B01001A-I)

    • data.seattle.gov
    • hub.arcgis.com
    • +1more
    application/rdfxml +5
    Updated Oct 22, 2024
    + more versions
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    (2024). Race by Age Groups (B01001A-I) [Dataset]. https://data.seattle.gov/dataset/Race-by-Age-Groups-B01001A-I-/3uqx-3u65
    Explore at:
    csv, tsv, application/rssxml, json, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Oct 22, 2024
    Description

    Table from the American Community Survey (ACS) B01001A-I sex by age by race - data is grouped into three age group categories for each race, under 18, 18-64 and 65 and older. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.


    Data on total number of people by each race alone and in combination by each census tract has been transposed to support dashboard visualizations.

    King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.

    The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades.

    Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

    Vintages: 2010, 2015, 2020, 2021, 2022, 2023
    ACS Table(s): B01001


    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:
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb(year)a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 'https://www2.census.gov/geo/tiger/TGRGDB20/tlgdb_2020_a_us_areawater.gdb.zip' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit; margin:0px; padding:0px;' target='_blank' rel='nofollow ugc noopener noreferrer'>2020 Areal Hydrography boundaries offered by

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Close
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(2025). Census Tract Top 50 American Community Survey Data [Dataset]. https://data.seattle.gov/dataset/Census-Tract-Top-50-American-Community-Survey-Data/jya9-y5bv/data

Census Tract Top 50 American Community Survey Data

Explore at:
application/rdfxml, csv, json, application/rssxml, tsv, xmlAvailable download formats
Dataset updated
Feb 3, 2025
Description

Data from: American Community Survey, 5-year Series


King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 of over 50 attributes of the most requested data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.

The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades.

Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

Vintages: 2010, 2015, 2020, 2021, 2022, 2023
ACS Table(s): DP02, DP03, DP04, DP05


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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