9 datasets found
  1. c

    Internet Connectivity

    • data.clevelandohio.gov
    Updated Aug 21, 2023
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    Cleveland | GIS (2023). Internet Connectivity [Dataset]. https://data.clevelandohio.gov/datasets/89c639f534684dbaab9218d2227580ba
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows computer ownership and type of internet subscription. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

    This layer is symbolized to show the percentage of households with no internet connection. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B28001, B28002 (Not all lines of ACS table B28002 are available in this feature layer)

    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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • 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 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

  2. c

    Employment

    • data.clevelandohio.gov
    • hub.arcgis.com
    Updated Aug 21, 2023
    + more versions
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    Cleveland | GIS (2023). Employment [Dataset]. https://data.clevelandohio.gov/datasets/employment
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows hours worked, and those unemployed and not in labor force. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

    This layer is symbolized to show the percentage of unemployed population within the civilian labor force. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B23020, B23025

    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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • 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 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

  3. c

    Poverty Status

    • data.clevelandohio.gov
    • hub.arcgis.com
    Updated Aug 21, 2023
    + more versions
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    Cleveland | GIS (2023). Poverty Status [Dataset]. https://data.clevelandohio.gov/datasets/poverty-status
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows poverty status by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Poverty status is based on income in past 12 months of survey.

    This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B17020, C17002

    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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • 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 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

  4. d

    Demographic Characteristics of DC Census Tracts 2018-2022 5-Year ACS

    • datasets.ai
    21, 3
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    District of Columbia, Demographic Characteristics of DC Census Tracts 2018-2022 5-Year ACS [Dataset]. https://datasets.ai/datasets/demographic-characteristics-of-dc-census-tracts-2018-2022-5-year-acs
    Explore at:
    21, 3Available download formats
    Dataset authored and provided by
    District of Columbia
    Description

    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:

    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Data processed using R statistical package and ArcGIS Desktop.
    • Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  5. e

    Comercio Externo - Datasets - Datos.PR

    • datos.estadisticas.pr
    Updated Jan 30, 2025
    + more versions
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    (2025). Comercio Externo - Datasets - Datos.PR [Dataset]. https://datos.estadisticas.pr/dataset/comercio-externo
    Explore at:
    Dataset updated
    Jan 30, 2025
    License

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

    Description

    Archivo con datos del comercio externo de bienes de Puerto Rico. En específico, para cada mes, cada tipo de bien y cada país origen/destino, se presenta el valor de los bienes importados o enviados a Puerto Rico, y el valor de los bienes exportados o enviados desde Puerto Rico. Este se desglosa por método de envió: por avión versus por barco. Además para ciertos tipos de bienes se incluye la cantidad del bien exportada. Los tipos de bienes se clasifican según el sistema de 10 dígitos del Harmonized Tariff Schedule y del Schedule B. Se provee también clasificaciones por el North American Industrial Classification System (NAICS), Standard International Trade Classification (SITC) y End-Use. Los países origen/destino incluyen todos los países del mundo, incluyendo los Estados Unidos. También, se incluye como país las Islas Vírgenes de los Estados Unidos. Este conjunto de datos se prepara usando como fuente de datos el U.S. Census Bureau. Nota aclaratoria: Todos los años, el censo revisa los datos de los últimos 3 años y se publican en el mes julio. Por ejemplo, en Julio 2022 se publicaron los datos revisados de 2019, 2020 y 2021.

  6. d

    Demographic Characteristics of DC (District-wide) 2022 1-Year ACS

    • datasets.ai
    21, 3
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    District of Columbia, Demographic Characteristics of DC (District-wide) 2022 1-Year ACS [Dataset]. https://datasets.ai/datasets/demographic-characteristics-of-dc-district-wide-2022-1-year-acs
    Explore at:
    3, 21Available download formats
    Dataset authored and provided by
    District of Columbia
    Description

    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:

    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in September. The layer always contains the latest available ACS 1-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Data processed using R statistical package and ArcGIS Desktop.
    • Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  7. c

    Housing Units in Structure

    • data.clevelandohio.gov
    Updated Aug 21, 2023
    + more versions
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    Cleveland | GIS (2023). Housing Units in Structure [Dataset]. https://data.clevelandohio.gov/datasets/housing-units-in-structure
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows housing units in structure by tenure (owner or renter). This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

    This layer is symbolized by the percent of housing units that are single-family detached homes. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B25024, B25032 (Not all lines of ACS table B25032 are available in this layer.)

    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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • 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 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

  8. d

    Demographic Characteristics of DC Wards 2018-2022 5-Year ACS

    • datasets.ai
    21, 3
    + more versions
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    District of Columbia, Demographic Characteristics of DC Wards 2018-2022 5-Year ACS [Dataset]. https://datasets.ai/datasets/demographic-characteristics-of-dc-wards-2018-2022-5-year-acs
    Explore at:
    3, 21Available download formats
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    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:

    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • Boundaries come from the US Census TIGER geodatabases. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Data processed using R statistical package and ArcGIS Desktop.
    • Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  9. c

    Disability Status

    • data.clevelandohio.gov
    Updated Aug 21, 2023
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    Cleveland | GIS (2023). Disability Status [Dataset]. https://data.clevelandohio.gov/datasets/disability-status
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Cleveland | GIS
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Description
    This layer shows disability status by sex and age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

    This layer is symbolized to show the percentage of elderly (65+) with a disability. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

    Current Vintage: 2019-2023
    ACS Table(s): B18101

    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. For more information about ACS layers, visit the FAQ. 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:
    • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
    • 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 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
    • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
    • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
      • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
      • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
      • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
      • The estimate is controlled. A statistical test for sampling variability is not appropriate.
      • The data for this geographic area cannot be displayed because the number of sample cases is too small.

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Click to copy link
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Close
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Cleveland | GIS (2023). Internet Connectivity [Dataset]. https://data.clevelandohio.gov/datasets/89c639f534684dbaab9218d2227580ba

Internet Connectivity

Explore at:
Dataset updated
Aug 21, 2023
Dataset authored and provided by
Cleveland | GIS
License

Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically

Area covered
Description
This layer shows computer ownership and type of internet subscription. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

This layer is symbolized to show the percentage of households with no internet connection. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.

Current Vintage: 2019-2023
ACS Table(s): B28001, B28002 (Not all lines of ACS table B28002 are available in this feature layer)

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. For more information about ACS layers, visit the FAQ. 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:
  • This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
  • 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 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
  • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
  • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
  • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.
  • Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.
  • Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:
    • The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
    • Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.
    • The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.
    • The estimate is controlled. A statistical test for sampling variability is not appropriate.
    • The data for this geographic area cannot be displayed because the number of sample cases is too small.

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