73 datasets found
  1. i

    Richest Zip Codes in New York

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in New York [Dataset]. https://www.incomebyzipcode.com/newyork
    Explore at:
    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    New York
    Description

    A dataset listing the richest zip codes in New York per the most current US Census data, including information on rank and average income.

  2. i

    Richest Zip Codes in Virginia

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in Virginia [Dataset]. https://www.incomebyzipcode.com/virginia
    Explore at:
    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    Virginia
    Description

    A dataset listing the richest zip codes in Virginia per the most current US Census data, including information on rank and average income.

  3. Personal Income Tax Statistics By Zip Code

    • data.ca.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +1more
    csv, pdf
    Updated Apr 24, 2024
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    California Franchise Tax Board (2024). Personal Income Tax Statistics By Zip Code [Dataset]. https://data.ca.gov/dataset/personal-income-tax-statistics-by-zip-code
    Explore at:
    pdf(38561), csv(191164)Available download formats
    Dataset updated
    Apr 24, 2024
    Dataset authored and provided by
    California Franchise Tax Boardhttp://ftb.ca.gov/
    License

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

    Description

    This dataset contains data from California resident tax returns filed with California adjusted gross income and self-assessed tax listed by zip code. This dataset contains data for taxable years 1992 to the most recent tax year available.

  4. i

    Richest Zip Codes in South Carolina

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in South Carolina [Dataset]. https://www.incomebyzipcode.com/southcarolina
    Explore at:
    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    South Carolina
    Description

    A dataset listing the richest zip codes in South Carolina per the most current US Census data, including information on rank and average income.

  5. Median Household Income GIS

    • data-sccphd.opendata.arcgis.com
    Updated Aug 24, 2022
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    Santa Clara County Public Health (2022). Median Household Income GIS [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/median-household-income-gis
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    Dataset updated
    Aug 24, 2022
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Table contains median household income for households residing in Santa Clara County. Data are presented at county, city, zip code and census tract level. Notes: Data are presented for zip codes (ZCTAs) fully within the county. Data are capped at $250,001 for geographies with median household income of $250,000 or higher. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B19013; data accessed on May 16, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographymedHHinc (Numeric): Median household income

  6. f

    Geographical grouping (by ZIP code) of households within Davidson County...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 5, 2023
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    Dana M. Brantley-Sieders; Kang-Hsien Fan; Sandra L. Deming-Halverson; Yu Shyr; Rebecca S. Cook (2023). Geographical grouping (by ZIP code) of households within Davidson County according to median household income. [Dataset]. http://doi.org/10.1371/journal.pone.0045238.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Dana M. Brantley-Sieders; Kang-Hsien Fan; Sandra L. Deming-Halverson; Yu Shyr; Rebecca S. Cook
    License

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

    Description

    Households within Davidson County (the greater metropolitan Nashville area) were grouped geographically according to ZIP code. The percentage of the metropolitan population residing within each ZIP code, and the median annual household income for each ZIP code was calculated based on data compiled by the U.S. Census Bureau (2006–2008 American Community Survey) for all ZIP codes within Davidson County.

  7. F

    Median Household Income in the United States

    • fred.stlouisfed.org
    json
    Updated Sep 9, 2025
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    (2025). Median Household Income in the United States [Dataset]. https://fred.stlouisfed.org/series/MEHOINUSA646N
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 9, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Median Household Income in the United States (MEHOINUSA646N) from 1984 to 2024 about households, median, income, and USA.

  8. INCOME Total and Mean and Median Household Income in 1999 COS 2000

    • catalog.data.gov
    • gstore.unm.edu
    • +1more
    Updated Dec 2, 2020
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    U.S. Department of Commerce, Bureau of the Census, Geography Division (Point of Contact) (2020). INCOME Total and Mean and Median Household Income in 1999 COS 2000 [Dataset]. https://catalog.data.gov/dataset/income-total-and-mean-and-median-household-income-in-1999-cos-2000
    Explore at:
    Dataset updated
    Dec 2, 2020
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

  9. f

    Data_Sheet_3_High-income ZIP codes in New York City demonstrate higher case...

    • frontiersin.figshare.com
    txt
    Updated Jun 20, 2024
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    Steven T. L. Tung; Mosammat M. Perveen; Kirsten N. Wohlars; Robert A. Promisloff; Mary F. Lee-Wong; Anthony M. Szema (2024). Data_Sheet_3_High-income ZIP codes in New York City demonstrate higher case rates during off-peak COVID-19 waves.CSV [Dataset]. http://doi.org/10.3389/fpubh.2024.1384156.s003
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Frontiers
    Authors
    Steven T. L. Tung; Mosammat M. Perveen; Kirsten N. Wohlars; Robert A. Promisloff; Mary F. Lee-Wong; Anthony M. Szema
    License

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

    Area covered
    New York
    Description

    IntroductionOur study explores how New York City (NYC) communities of various socioeconomic strata were uniquely impacted by the COVID-19 pandemic.MethodsNew York City ZIP codes were stratified into three bins by median income: high-income, middle-income, and low-income. Case, hospitalization, and death rates obtained from NYCHealth were compared for the period between March 2020 and April 2022.ResultsCOVID-19 transmission rates among high-income populations during off-peak waves were higher than transmission rates among low-income populations. Hospitalization rates among low-income populations were higher during off-peak waves despite a lower transmission rate. Death rates during both off-peak and peak waves were higher for low-income ZIP codes.DiscussionThis study presents evidence that while high-income areas had higher transmission rates during off-peak periods, low-income areas suffered greater adverse outcomes in terms of hospitalization and death rates. The importance of this study is that it focuses on the social inequalities that were amplified by the pandemic.

  10. Low and Moderate Income Areas

    • catalog.data.gov
    • s.cnmilf.com
    Updated Mar 1, 2024
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    U.S. Department of Housing and Urban Development (2024). Low and Moderate Income Areas [Dataset]. https://catalog.data.gov/dataset/hud-low-and-moderate-income-areas
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

  11. INCOME Total and Mean and Median Household Income in 1999 BGs 2000

    • catalog.data.gov
    • gstore.unm.edu
    • +1more
    Updated Dec 2, 2020
    + more versions
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    U.S. Department of Commerce, Bureau of the Census, Geography Division (Point of Contact) (2020). INCOME Total and Mean and Median Household Income in 1999 BGs 2000 [Dataset]. https://catalog.data.gov/dataset/income-total-and-mean-and-median-household-income-in-1999-bgs-2000
    Explore at:
    Dataset updated
    Dec 2, 2020
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

  12. z

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

    • zipatlas.com
    Updated Dec 18, 2023
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    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.

  13. i

    Richest Zip Codes in Missouri

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in Missouri [Dataset]. https://www.incomebyzipcode.com/missouri
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    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    Missouri
    Description

    A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.

  14. ACS 2020 Income

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    Updated Apr 20, 2022
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    Georgia Association of Regional Commissions (2022). ACS 2020 Income [Dataset]. https://opendata.atlantaregional.com/maps/b45c8096a0564f98977beb8ef4fd100a
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    Dataset updated
    Apr 20, 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

  15. Share of zip codes where all homes were affordable in selected U.S. markets...

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Share of zip codes where all homes were affordable in selected U.S. markets 2019 [Dataset]. https://www.statista.com/statistics/1018471/affordable-zip-codes-usa/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    This statistic shows the share of zip codes where all homes were affordable in selected markets in the United States in 2019. In 2019, 100 percent of homes in **** percent of Pittsburgh zip codes were affordable for buyers earning the local median income.

  16. a

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

    • uscssi.hub.arcgis.com
    Updated Nov 10, 2021
    + more versions
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    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

  17. Share of zip codes where all homes were unaffordable in selected U.S....

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Share of zip codes where all homes were unaffordable in selected U.S. markets 2019 [Dataset]. https://www.statista.com/statistics/1018484/unaffordable-zip-codes-usa/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    This statistic shows the share of zip codes where all homes were unaffordable in selected markets in the United States in 2019. In 2019, 100 percent of homes in **** percent of San Francisco zip codes were unaffordable for buyers earning the local median income.

  18. g

    Median Household Income | gimi9.com

    • gimi9.com
    Updated Mar 1, 2025
    + more versions
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    (2025). Median Household Income | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_median-household-income-fc29b/
    Explore at:
    Dataset updated
    Mar 1, 2025
    License

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

    Description

    These Socioeconomic Indicators are from the American Community Survey, 2014 5-year estimates. They are at Zip Code level for Oakland, Macomb and Wayne Counties.

  19. Average Household Income in the United States

    • dbechard-open-data-gisanddata.hub.arcgis.com
    Updated Jun 26, 2018
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    Esri (2018). Average Household Income in the United States [Dataset]. https://dbechard-open-data-gisanddata.hub.arcgis.com/maps/6d7b0a1dcad847be820c3d1424f79dd8
    Explore at:
    Dataset updated
    Jun 26, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of June 2023 and will be retired in December 2025. This map shows the average household income in the U.S. in 2022 in a multiscale map by country, state, county, ZIP Code, tract, and block group. Information for the average household income is an estimate of income for calendar year 2022. Income amounts are expressed in current dollars, including an adjustment for inflation or cost-of-living increases.The pop-up is configured to include the following information for each geography level:Average household incomeMedian household incomeCount of households by income groupAverage household income by householder age groupPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

  20. u

    INCOME Total and Mean and Median Household Income in 1999 COS 2000

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Feb 15, 2008
    + more versions
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    Earth Data Analysis Center (2008). INCOME Total and Mean and Median Household Income in 1999 COS 2000 [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/a6a7f492-8dc3-4a3f-89dc-821a4b548d61/metadata/FGDC-STD-001-1998.html
    Explore at:
    shp(5), kml(5), xls(5), json(5), geojson(5), csv(5), gml(5), zip(1)Available download formats
    Dataset updated
    Feb 15, 2008
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    2000
    Area covered
    West Bounding Coordinate -109.05078125 East Bounding Coordinate -103.002449035645 North Bounding Coordinate 37.0003128051758 South Bounding Coordinate 31.3322792053223, New Mexico (35)
    Description

    TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

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Cubit Planning, Inc. (2024). Richest Zip Codes in New York [Dataset]. https://www.incomebyzipcode.com/newyork

Richest Zip Codes in New York

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Dec 18, 2024
Dataset authored and provided by
Cubit Planning, Inc.
License

https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

Area covered
New York
Description

A dataset listing the richest zip codes in New York per the most current US Census data, including information on rank and average income.

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