34 datasets found
  1. z

    Median Gross Rent As A Percentage Of Household Income (Dollars)

    • zipatlas.com
    Updated Dec 18, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zip Atlas Inc (2023). Median Gross Rent As A Percentage Of Household Income (Dollars) [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Median Gross Rent As A Percentage Of Household Income (Dollars) Report based on US Census and American Community Survey Data.

  2. US National Rental Data | 14M+ Records in 16,000+ ZIP Codes | Rental Data...

    • datarade.ai
    .csv, .xls, .txt
    Updated Oct 21, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    The Warren Group (2024). US National Rental Data | 14M+ Records in 16,000+ ZIP Codes | Rental Data Lease Terms & Pricing Trends [Dataset]. https://datarade.ai/data-products/us-national-rental-data-14m-records-in-16-000-zip-codes-the-warren-group
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Oct 21, 2024
    Dataset authored and provided by
    The Warren Group
    Area covered
    United States of America
    Description

    What is Rental Data?

    Rental data encompasses detailed information about residential rental properties, including single-family homes, multifamily units, and large apartment complexes. This data often includes key metrics such as rental prices, occupancy rates, property amenities, and detailed property descriptions. Advanced rental datasets integrate listings directly sourced from property management software systems, ensuring real-time accuracy and eliminating reliance on outdated or scraped information.

    Additional Rental Data Details

    The rental data is sourced from over 20,000 property managers via direct feeds and property management platforms, covering over 30 percent of the national rental housing market for diverse and broad representation. Real-time updates ensure data remains current, while verified listings enhance accuracy, avoiding errors typical of survey-based or scraped datasets. The dataset includes 14+ million rental units with detailed descriptions, rich photography, and amenities, offering address-level granularity for precise market analysis. Its extensive coverage of small multifamily and single-family rentals sets it apart from competitors focused on premium multifamily properties.

    Rental Data Includes:

    • Property Types
    • Single-Family Rentals
    • Small Multi-family Units
    • Premium Apartments
    • 16,000+ ZIP Codes
    • 800+ MSAs
    • Pricing Trends
    • Lease Terms Amenities
  3. a

    Housing Rent (by Zip Code) 2019

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +1more
    Updated Feb 26, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2021). Housing Rent (by Zip Code) 2019 [Dataset]. https://opendata.atlantaregional.com/datasets/GARC::housing-rent-by-zip-code-2019
    Explore at:
    Dataset updated
    Feb 26, 2021
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana Mean (average)t Aggregate (total)ch Change in absolute terms (value in t2 - value in t1)pch Percent change ((value in t2 - value in t1) / value in t1)chp Change in percent (percent in t2 - percent in t1)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2015-2019). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

  4. z

    Gross Rent As A Percentage Of Household Income

    • zipatlas.com
    Updated Dec 18, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zip Atlas Inc (2023). Gross Rent As A Percentage Of Household Income [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Gross Rent As A Percentage Of Household Income Report based on US Census and American Community Survey Data.

  5. a

    Housing Rent 2023 (all geographies, statewide)

    • opendata.atlantaregional.com
    • hub.arcgis.com
    Updated Feb 21, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2025). Housing Rent 2023 (all geographies, statewide) [Dataset]. https://opendata.atlantaregional.com/maps/1921d8abd32c4768994af9c02e5d1895
    Explore at:
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    These data were developed by the Research & Analytics Department at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.For a deep dive into the data model including every specific metric, see the ACS 2019-2023. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e23Estimate from 2019-23 ACS_m23Margin of Error from 2019-23 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_23Change, 2010-23 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)CCDIST = County Commission Districts (statewide where applicable)CCSUPERDIST = County Commission Superdistricts (DeKalb)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2019-2023). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2019-2023Open Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/182e6fcf8201449086b95adf39471831/about

  6. a

    ACS 2020 Housing Gross Rent

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +1more
    Updated Apr 21, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2022). ACS 2020 Housing Gross Rent [Dataset]. https://opendata.atlantaregional.com/maps/c778e37a11b54024a622480dd5c4e854
    Explore at:
    Dataset updated
    Apr 21, 2022
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

    For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    s

    Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

    Suffixes:

    _e20

    Estimate from 2016-20 ACS

    _m20

    Margin of Error from 2016-20 ACS

    _e10

    2006-10 ACS, re-estimated to 2020 geography

    _m10

    Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

    _e10_20

    Change, 2010-20 (holding constant at 2020 geography)

    Geographies

    AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

    ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

    Census Tracts (statewide)

    CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

    City (statewide)

    City of Atlanta Council Districts (City of Atlanta)

    City of Atlanta Neighborhood Planning Unit (City of Atlanta)

    City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

    City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

    County (statewide)

    Georgia House (statewide)

    Georgia Senate (statewide)

    MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

    Regional Commissions (statewide)

    State of Georgia (statewide)

    Superdistrict (ARC region)

    US Congress (statewide)

    UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

    WFF = Westside Future Fund (subarea of City of Atlanta)

    ZIP Code Tabulation Areas (statewide)

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

    Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

  7. a

    Gross Rent 2022 (all geographies, statewide)

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +1more
    Updated Mar 1, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2024). Gross Rent 2022 (all geographies, statewide) [Dataset]. https://opendata.atlantaregional.com/maps/df8e3df1abe14b30b109448223062a55
    Explore at:
    Dataset updated
    Mar 1, 2024
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    These data were developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. .
    For a deep dive into the data model including every specific metric, see the ACS 2018-2022 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e22Estimate from 2018-22 ACS_m22Margin of Error from 2018-22 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_22Change, 2010-22 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2018-2022). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2018-2022Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/3b86ee614e614199ba66a3ff1ebfe3b5/about

  8. a

    OCACS 2015 Housing Characteristics for ZIP Code Tabulation Areas

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • data-ocpw.opendata.arcgis.com
    Updated Jan 22, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    OC Public Works (2020). OCACS 2015 Housing Characteristics for ZIP Code Tabulation Areas [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/OCPW::ocacs-2015-housing-characteristics-for-zip-code-tabulation-areas
    Explore at:
    Dataset updated
    Jan 22, 2020
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    US Census American Community Survey (ACS) 2015, 5-year estimates of the key housing characteristics of ZIP Code Tabulation Areas geographic level in Orange County, California. The data contains 406 fields for the variable groups H01: Housing occupancy (universe: total housing units, table X25, 3 fields); H02: Units in structure (universe: total housing units, table X25, 11 fields); H03: Population in occupied housing units by tenure by units in structure (universe: total population in occupied housing units, table X25, 13 fields); H04: Year structure built (universe: total housing units, table X25, 15 fields); H05: Rooms (universe: total housing units, table X25, 18 fields); H06: Bedrooms (universe: total housing units, table X25, 21 fields); H07: Housing tenure by race of householder (universe: occupied housing units, table X25, 51 fields); H08: Total population in occupied housing units by tenure (universe: total population in occupied housing units, table X25, 3 fields); H09: Vacancy status (universe: vacant housing units, table X25, 8 fields); H10: Occupied housing units by race of householder (universe: occupied housing units, table X25, 8 fields); H11: Year householder moved into unit (universe: occupied housing units, table X25, 18 fields); H12: Vehicles available (universe: occupied housing units, table X25, 18 fields); H13: Housing heating fuel (universe: occupied housing units, table X25, 10 fields); H14: Selected housing characteristics (universe: occupied housing units, table X25, 9 fields); H15: Occupants per room (universe: occupied housing units, table X25, 13 fields); H16: Housing value (universe: owner-occupied units, table X25, 32 fields); H17: Price asked for vacant for sale only, and sold not occupied housing units (universe: vacant for sale only, and sold not occupied housing units, table X25, 28 fields); H18: Mortgage status (universe: owner-occupied units, table X25, 10 fields); H19: Selected monthly owner costs, SMOC (universe: owner-occupied housing units with or without a mortgage, table X25, 45 fields); H20: Selected monthly owner costs as a percentage of household income, SMOCAPI (universe: owner-occupied housing units with or without a mortgage, table X25, 26 fields); H21: Contract rent distribution and rent asked distribution in dollars (universe: renter-occupied housing units paying cash rent and vacant, for rent, and rented not occupied housing units, table X25, 7 fields); H22: Gross rent (universe: occupied units paying rent, table X25, 28 fields), and; X23: Gross rent as percentage of household income (universe: occupied units paying rent, table X25, 11 fields). The US Census geodemographic data are based on the 2015 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

  9. a

    Housing Affordability (by Zip Code) 2015

    • opendata.atlantaregional.com
    Updated Jun 1, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2018). Housing Affordability (by Zip Code) 2015 [Dataset]. https://opendata.atlantaregional.com/datasets/57722e3a78644734955a9c3b7ac7c8de
    Explore at:
    Dataset updated
    Jun 1, 2018
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from American Community Survey 5-year estimates for 2011-2015 to show housing affordability data (housing costs relative to income) by zip code in the Atlanta region.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. ACS data presented here represent combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2011-2015). Therefore, these data do not represent any one specific point in time or even one specific year. For further explanation of ACS estimates and methodology, click here.

    Attributes:

    ZIP = Zip code (text)

    ZIP_dbl = Zip code (numeric)

    Total_Population_2010 = Total Population, 2010 Census

    Total_Population_2011_2015_ACS = Total Population, 2011-2015 American Community Survey (ACS)

    HousUnits_MonthOwnerCosts_toInc = #, Housing units for which Selected Monthly Owner Costs as % of income are computed

    Sel_Mo_Own_Costs_30pct_of_Incom = #, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household income

    Pct_Sel_Mo_Own_Costs_30pct_Inc = %, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household income

    HousUnits_Compute_RentPctIncome = #, Housing units for which Gross rent as a percentage of income is computed

    Rent_Pct_of_Inc_More30Pct = #, Gross rent as a percentage of household income (GRAPI) is 30% or more

    PctRent_PctIncome_More30Pct = %, Gross rent as a percentage of household income (GRAPI) is 30% or more

    HousUnits_OwnRent_Compute = #, Housing units for which SMOCAPI or GRAPI are computed

    HousCosts_Units_30pctMore_Inc = #, Housing costs (GRAPI or SMOCAPI) are 30% or more of household income

    PctHousCost_30pctMore_Income = %, Housing costs (GRAPI or SMOCAPI) are 30% or more of household income

    last_edited_date = Last date the feature was edited by ARC

    Source: U.S. Census Bureau, Atlanta Regional Commission

    Date: 2011-2015

  10. a

    OCACS 2020 Housing Characteristics for ZIP Code Tabulation Areas

    • data-ocpw.opendata.arcgis.com
    Updated May 5, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    OC Public Works (2023). OCACS 2020 Housing Characteristics for ZIP Code Tabulation Areas [Dataset]. https://data-ocpw.opendata.arcgis.com/datasets/ocacs-2020-housing-characteristics-for-zip-code-tabulation-areas
    Explore at:
    Dataset updated
    May 5, 2023
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    US Census American Community Survey (ACS) 2020, 5-year estimates of the key housing characteristics of ZIP Code Tabulation Areas geographic level in Orange County, California. The data contains 406 fields for the variable groups H01: Housing occupancy (universe: total housing units, table X25, 3 fields); H02: Units in structure (universe: total housing units, table X25, 11 fields); H03: Population in occupied housing units by tenure by units in structure (universe: total population in occupied housing units, table X25, 13 fields); H04: Year structure built (universe: total housing units, table X25, 15 fields); H05: Rooms (universe: total housing units, table X25, 18 fields); H06: Bedrooms (universe: total housing units, table X25, 21 fields); H07: Housing tenure by race of householder (universe: occupied housing units, table X25, 51 fields); H08: Total population in occupied housing units by tenure (universe: total population in occupied housing units, table X25, 3 fields); H09: Vacancy status (universe: vacant housing units, table X25, 8 fields); H10: Occupied housing units by race of householder (universe: occupied housing units, table X25, 8 fields); H11: Year householder moved into unit (universe: occupied housing units, table X25, 18 fields); H12: Vehicles available (universe: occupied housing units, table X25, 18 fields); H13: Housing heating fuel (universe: occupied housing units, table X25, 10 fields); H14: Selected housing characteristics (universe: occupied housing units, table X25, 9 fields); H15: Occupants per room (universe: occupied housing units, table X25, 13 fields); H16: Housing value (universe: owner-occupied units, table X25, 32 fields); H17: Price asked for vacant for sale only, and sold not occupied housing units (universe: vacant for sale only, and sold not occupied housing units, table X25, 28 fields); H18: Mortgage status (universe: owner-occupied units, table X25, 10 fields); H19: Selected monthly owner costs, SMOC (universe: owner-occupied housing units with or without a mortgage, table X25, 45 fields); H20: Selected monthly owner costs as a percentage of household income, SMOCAPI (universe: owner-occupied housing units with or without a mortgage, table X25, 26 fields); H21: Contract rent distribution and rent asked distribution in dollars (universe: renter-occupied housing units paying cash rent and vacant, for rent, and rented not occupied housing units, table X25, 7 fields); H22: Gross rent (universe: occupied units paying rent, table X25, 28 fields), and; X23: Gross rent as percentage of household income (universe: occupied units paying rent, table X25, 11 fields). The US Census geodemographic data are based on the 2020 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project GitHub page (https://github.com/ktalexan/OCACS-Geodemographics).

  11. f

    ACS2020 Housing GrossRent RC

    • gisdata.fultoncountyga.gov
    • hub.arcgis.com
    Updated Apr 21, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2022). ACS2020 Housing GrossRent RC [Dataset]. https://gisdata.fultoncountyga.gov/maps/GARC::acs2020-housing-grossrent-rc
    Explore at:
    Dataset updated
    Apr 21, 2022
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

    For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    s

    Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

    Suffixes:

    _e20

    Estimate from 2016-20 ACS

    _m20

    Margin of Error from 2016-20 ACS

    _e10

    2006-10 ACS, re-estimated to 2020 geography

    _m10

    Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

    _e10_20

    Change, 2010-20 (holding constant at 2020 geography)

    Geographies

    AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

    ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

    Census Tracts (statewide)

    CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

    City (statewide)

    City of Atlanta Council Districts (City of Atlanta)

    City of Atlanta Neighborhood Planning Unit (City of Atlanta)

    City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

    City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

    County (statewide)

    Georgia House (statewide)

    Georgia Senate (statewide)

    MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

    Regional Commissions (statewide)

    State of Georgia (statewide)

    Superdistrict (ARC region)

    US Congress (statewide)

    UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

    WFF = Westside Future Fund (subarea of City of Atlanta)

    ZIP Code Tabulation Areas (statewide)

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

    Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

  12. a

    Gross Rent 2021 (all geographies, statewide)

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +1more
    Updated Mar 10, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2023). Gross Rent 2021 (all geographies, statewide) [Dataset]. https://opendata.atlantaregional.com/maps/62914a19b3ac43b99a1fbe251b9d40f8
    Explore at:
    Dataset updated
    Mar 10, 2023
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

  13. f

    ACS2021 Housing GrossRent ARC21

    • gisdata.fultoncountyga.gov
    Updated Mar 10, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2023). ACS2021 Housing GrossRent ARC21 [Dataset]. https://gisdata.fultoncountyga.gov/maps/GARC::acs2021-housing-grossrent-arc21
    Explore at:
    Dataset updated
    Mar 10, 2023
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

  14. z

    Mortgage Status By Selected Monthly Owner Costs As A Percentage Of Household...

    • zipatlas.com
    Updated Dec 18, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zip Atlas Inc (2023). Mortgage Status By Selected Monthly Owner Costs As A Percentage Of Household Income [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Mortgage Status By Selected Monthly Owner Costs As A Percentage Of Household Income Report based on US Census and American Community Survey Data.

  15. l

    Los Angeles Index of Neighborhood Change

    • visionzero.geohub.lacity.org
    • geohub.lacity.org
    • +4more
    Updated Oct 13, 2016
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DataLA (2016). Los Angeles Index of Neighborhood Change [Dataset]. https://visionzero.geohub.lacity.org/datasets/57e9231c3bd34d44ae49b309b0cb440e
    Explore at:
    Dataset updated
    Oct 13, 2016
    Dataset authored and provided by
    DataLA
    License

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

    Area covered
    Description

    The Los Angeles Index of Neighborhood Change is a tool that allows users to explore the extent to which Los Angeles Zip Codes have undergone demographic change from 2000 to 2014. Created in 2015/2016, the data comes from 2000, 2005, 2013, and 2014. Please read details about each measure for exact years.Index scores are an aggregate of six demographic measures indicative of gentrification. The measures are standardized and combined using weights that reflect the proportion of each measure that is statistically significant.Measure 1: Percent change in low/high IRS filer ratio. For the purposes of this measure, High Income = >$75K Adjust Gross Income tax filer and Low Income = <$25k filers who also received an earned income tax credit. Years Compared for Measure 1: 2005 and 2013 | Source: IRS Income Tax Return DataMeasure 2: Change in percent of residents 25 years or older with Bachelor's Degrees or HigherMeasure 3: Change in percent of White, non-Hispanic/Latino residentsMeasure 4: Percent change in median household income (2000 income is adjusted to 2014 dollars)Measure 5: % Change in median gross rent (2000 rent is adjusted to 2013/2014 dollars)Measure 6: Percent change in average household size Year Compared for Measures 2-5: 2000 and 2014, Measure 6: 2013Sources: Decennial Census, 2000 | American Community Survey (5-Year Estimate, 2009-2013; 2010; 2014)Date Updated: December 13, 2016Refresh Rate: Never - Historical data

  16. Vital Signs: Home Prices – by metro

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Sep 24, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zillow (2019). Vital Signs: Home Prices – by metro [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Home-Prices-by-metro/7ksc-i6kn
    Explore at:
    application/rssxml, xml, csv, tsv, json, application/rdfxmlAvailable download formats
    Dataset updated
    Sep 24, 2019
    Dataset authored and provided by
    Zillowhttp://zillow.com/
    Description

    VITAL SIGNS INDICATOR Home Prices (EC7)

    FULL MEASURE NAME Home Prices

    LAST UPDATED August 2019

    DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

    DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

    Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

    For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

    Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

  17. a

    ACS2021 Housing GrossRent NPU

    • opendata.atlantaregional.com
    Updated Mar 10, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2023). ACS2021 Housing GrossRent NPU [Dataset]. https://opendata.atlantaregional.com/datasets/acs2021-housing-grossrent-npu
    Explore at:
    Dataset updated
    Mar 10, 2023
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

  18. a

    ACS2020 Housing GrossRent AAA

    • opendata.atlantaregional.com
    Updated Apr 21, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Georgia Association of Regional Commissions (2022). ACS2020 Housing GrossRent AAA [Dataset]. https://opendata.atlantaregional.com/datasets/acs2020-housing-grossrent-aaa
    Explore at:
    Dataset updated
    Apr 21, 2022
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

    For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    s

    Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

    Suffixes:

    _e20

    Estimate from 2016-20 ACS

    _m20

    Margin of Error from 2016-20 ACS

    _e10

    2006-10 ACS, re-estimated to 2020 geography

    _m10

    Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

    _e10_20

    Change, 2010-20 (holding constant at 2020 geography)

    Geographies

    AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

    ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

    Census Tracts (statewide)

    CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

    City (statewide)

    City of Atlanta Council Districts (City of Atlanta)

    City of Atlanta Neighborhood Planning Unit (City of Atlanta)

    City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

    City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

    County (statewide)

    Georgia House (statewide)

    Georgia Senate (statewide)

    MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

    Regional Commissions (statewide)

    State of Georgia (statewide)

    Superdistrict (ARC region)

    US Congress (statewide)

    UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

    WFF = Westside Future Fund (subarea of City of Atlanta)

    ZIP Code Tabulation Areas (statewide)

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

    Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

  19. a

    Housing Affordability Index in the United States-Copy-Copy-Copy-Copy-Copy

    • uscssi.hub.arcgis.com
    Updated Nov 10, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Spatial Sciences Institute (2021). Housing Affordability Index in the United States-Copy-Copy-Copy-Copy-Copy [Dataset]. https://uscssi.hub.arcgis.com/maps/799e364bc9ef4d1a8c1f725a71d280e4
    Explore at:
    Dataset updated
    Nov 10, 2021
    Dataset authored and provided by
    Spatial Sciences Institute
    Area covered
    Description

    This map uses a two-color thematic shading to emphasize where areas experience the least to the most affordable housing across the US. This web map is part of the How Affordable is the American Dream story map.

    Esri’s Housing Affordability Index (HAI) is a powerful tool to analyze local real estate markets. Esri’s housing affordability index measures the financial ability of a typical household to purchase an existing home in an area. A HAI of 100 represents an area that on average has sufficient household income to qualify for a loan on a home valued at the median home price. An index greater than 100 suggests homes are easily afforded by the average area resident. A HAI less than 100 suggests that homes are less affordable. The housing affordability index is not applicable in areas with no households or in predominantly rental markets . Esri’s home value estimates cover owner-occupied homes only. For a full demographic analysis of US growth refer to Esri's Trending in 2017: The Selectivity of Growth.

    The pop-up is configured to show the following 2017 demographics for each County and ZIP Code:

    Total Households 2010-17 Annual Pop Change Median Age Percent Owner-Occupied Housing Units Median Household Income Median Home Value Housing Affordability Index Share of Income to Mortgage

  20. a

    OCACS 2019 Housing Characteristics for ZIP Code Tabulation Areas

    • data-ocpw.opendata.arcgis.com
    • hub.arcgis.com
    Updated Sep 14, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    OC Public Works (2021). OCACS 2019 Housing Characteristics for ZIP Code Tabulation Areas [Dataset]. https://data-ocpw.opendata.arcgis.com/datasets/ocacs-2019-housing-characteristics-for-zip-code-tabulation-areas
    Explore at:
    Dataset updated
    Sep 14, 2021
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    US Census American Community Survey (ACS) 2019, 5-year estimates of the key housing characteristics of ZIP Code Tabulation Areas geographic level in Orange County, California. The data contains 406 fields for the variable groups H01: Housing occupancy (universe: total housing units, table X25, 3 fields); H02: Units in structure (universe: total housing units, table X25, 11 fields); H03: Population in occupied housing units by tenure by units in structure (universe: total population in occupied housing units, table X25, 13 fields); H04: Year structure built (universe: total housing units, table X25, 15 fields); H05: Rooms (universe: total housing units, table X25, 18 fields); H06: Bedrooms (universe: total housing units, table X25, 21 fields); H07: Housing tenure by race of householder (universe: occupied housing units, table X25, 51 fields); H08: Total population in occupied housing units by tenure (universe: total population in occupied housing units, table X25, 3 fields); H09: Vacancy status (universe: vacant housing units, table X25, 8 fields); H10: Occupied housing units by race of householder (universe: occupied housing units, table X25, 8 fields); H11: Year householder moved into unit (universe: occupied housing units, table X25, 18 fields); H12: Vehicles available (universe: occupied housing units, table X25, 18 fields); H13: Housing heating fuel (universe: occupied housing units, table X25, 10 fields); H14: Selected housing characteristics (universe: occupied housing units, table X25, 9 fields); H15: Occupants per room (universe: occupied housing units, table X25, 13 fields); H16: Housing value (universe: owner-occupied units, table X25, 32 fields); H17: Price asked for vacant for sale only, and sold not occupied housing units (universe: vacant for sale only, and sold not occupied housing units, table X25, 28 fields); H18: Mortgage status (universe: owner-occupied units, table X25, 10 fields); H19: Selected monthly owner costs, SMOC (universe: owner-occupied housing units with or without a mortgage, table X25, 45 fields); H20: Selected monthly owner costs as a percentage of household income, SMOCAPI (universe: owner-occupied housing units with or without a mortgage, table X25, 26 fields); H21: Contract rent distribution and rent asked distribution in dollars (universe: renter-occupied housing units paying cash rent and vacant, for rent, and rented not occupied housing units, table X25, 7 fields); H22: Gross rent (universe: occupied units paying rent, table X25, 28 fields), and; X23: Gross rent as percentage of household income (universe: occupied units paying rent, table X25, 11 fields). The US Census geodemographic data are based on the 2019 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Zip Atlas Inc (2023). Median Gross Rent As A Percentage Of Household Income (Dollars) [Dataset]. https://zipatlas.com/zip-code-database-premium.htm

Median Gross Rent As A Percentage Of Household Income (Dollars)

Explore at:
Dataset updated
Dec 18, 2023
Dataset authored and provided by
Zip Atlas Inc
License

https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

Description

Median Gross Rent As A Percentage Of Household Income (Dollars) Report based on US Census and American Community Survey Data.

Search
Clear search
Close search
Google apps
Main menu