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.

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

Graph and download economic data for Median Household Income in the United States (MEHOINUSA646N) from 1984 to 2023 about households, median, income, and USA.

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

This dataset combines annual files from 2005 to 2017 published by the IRS. ZIP Code data show selected income and tax items classified by State, ZIP Code, and size of adjusted gross income. Data are based on individual income tax returns filed with the IRS. The data include items, such as:

Number of returns, which approximates the number of householdsNumber of personal exemptions, which approximates the populationAdjusted gross income (AGI)Wages and salariesDividends before exclusionInterest received Enrichment and notes:- the original data sheets (a column per variable, a line per year, zipcode and AGI group) have been transposed to get a record per year, zipcode, AGI group and variable- the data for Wyoming in 2006 was removed because AGI classes were not correctly defined, making the resulting data unfit for analysis.- the AGI groups have seen their definitions change: the variable "AGI Class" was used until 2008, with various intervals of AGI; "AGI Stub" replaced it in 2009. We provided the literal intervals (eg. "$50,000 under $75,000") as "AGI Group" in each case to help the analysis.- the codes for each tax item have been joined with a dataset of variables to provide full names.- some tax items are available since 2005, others since more recent years, depending on their introduction date (available in the dataset of variables); as a consequence, the time range of the plots or graphs may vary.- the unit for amounts and AGIs is a thousand dollars.

Table contains count and percentage of households with an annual household income of less than $100,000. Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B19001; 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 geographytotalHH (Numeric): Total householdslt100k (Numeric): Number of households with less than $100,000 annual incomepct_lt100k (Numeric): Percent of households with less than $100,000 annual income

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

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

This dataset contains information on the ratio of family income to the federal poverty level at the zip code tabulation area (ZCTA) level. Each column beginning with a "T_" lists the total number of families that fall into each income category. In addition, the dataset contains information on margins of error and the reliability of each estimate, to help guide decisionmakers in more effectively using the data contained in this file. There are approximately 1,000 records in this dataset. ZCTA boundaries are designed to approximate actual zip code boundaries, but are fixed to allow for consistent data analysis (whereas regular zip code boundaries change frequently). Field description metadata is available for download. For more information on poverty data from the Census Bureau, please visit American Factfinder (www.factfinder2.census.gov).

These datasets contain measures of socioeconomic and demographic characteristics by U.S. census tract for the years 1990-2022 and ZIP code tabulation area (ZCTA) for the years 2008-2022. Example measures include population density; population distribution by race, ethnicity, age, and income; income inequality by race and ethnicity; and proportion of population living below the poverty level, receiving public assistance, and female-headed or single parent families with kids. The datasets also contain a set of theoretically derived measures capturing neighborhood socioeconomic disadvantage and affluence, as well as a neighborhood index of Hispanic, foreign born, and limited English.

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.

Households by Income Group by U.S. Postal ZIP Code from the 2010 Decennial Census

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.

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

This dataset identifies selected economic characteristics by zip code tabulation areas within the United States. This dataset resulted from the American Community Survey (ACS) conducted from 2010 through 2014. The economic characteristics include employment status, commuting to work, occupation, class of worker, income and benefits, health insurance coverage, and percentage of families and people whose income in the past 12 months is below the poverty level.

Spotzi's Income dataset for the United States offers valuable insights into the intricacies of yearly income at various levels. This dataset is meticulously curated, presenting a detailed analysis of total income, types of household earnings, and the critical aspect of whether households are above the poverty level. This dataset is available at Census Block level, and allows for a holistic understanding of the economic landscape at both regional and national scales.

What is included?

Each data variable is presented as a percentage of the total population within each selected area. Please see below for a complete list of available data variables:

Income

• Individual Yearly Income: Under 10K, 10K-20K, 20K-35K, 35K-50K, 50K-100K, 100K+
• Individual Yearly Income - Female: Under 10K, 10K-20K, 20K-35K, 35K-50K, 50K-100K, 100K+
• Individual Yearly Income - Male: Under 10K, 10K-20K, 20K-35K, 35K-50K, 50K-100K, 100K+
• Household Income Earning Status: Earns Income, Does Not Earn Income
• Households Below Poverty Level

Household Earnings By Type

• Salary
• Interest Dividends
• Retirement Income
• Self-Employment

• • Individual Yearly Income: Marketers can leverage individual income data to tailor their strategies based on the financial capacities of their target audience. For example, luxury brands may target individuals with higher income brackets, while budget-conscious brands may focus on those with lower income levels.
  • Household Earning by Type: Marketers can use this data to understand the sources of household income, allowing for targeted campaigns. For example, financial services may tailor promotions based on the types of income earned, offering retirement planning services to those with significant retirement income.

• This demographic data is typically available at the census block level. These blocks are smaller, more detailed units designed for statistical purposes, enabling a more precise analysis of population, housing, and demographic data. Census blocks may vary in size and shape but are generally more localized compared to ZIP codes.

  Still looking for demographic data at the postal code level? Contact sales.

• There are numerous other census data datasets available for the United States, covering a wide range of demographics. These include information on:

  • Commuting
  • Educational Attainment
  • Employment
  • Families
  • Finance
  • Housing

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

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 23.5 percent of San Francisco zip codes were unaffordable for buyers earning the local median income.

Households by Income Group by U.S. Postal ZIP Code from the SANDAG v23 Release Population and Housing Estimates

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