About this dataset

Context

The dataset presents a breakdown of households across various income brackets in United States, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for United States reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of United States households based on income levels.

Key observations

• For Family Households: In United States, the majority of family households, representing 14.18%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 2.01%, have incomes falling $150,000 to $199,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In United States, the majority of non-family households, accounting for 10.55%, have income Less than $10,000, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 3.26%, earn $150,000 to $199,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in United States (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in United States
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in United States
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in United States

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income. You can refer the same here

Individuals; Tax filers and dependants by total income, sex and age groups (final T1 Family File; T1FF).

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Georgia, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Georgia reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Georgia households based on income levels.

Key observations

• For Family Households: In Georgia, the majority of family households, representing 14.01%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 2.17%, have incomes falling $150,000 to $199,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Georgia, the majority of non-family households, accounting for 11.42%, have income Less than $10,000, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 2.66%, earn $150,000 to $199,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Georgia (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Georgia
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Georgia
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Georgia

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Georgia median household income. You can refer the same here

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are geography-specific; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% income threshold of Nova Scotian tax filers. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Cheboygan County, MI, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,996, while the mean income for the highest quintile (20% of households with the highest income) is 193,369. This indicates that the top earners earn 13 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 337,648, which is 174.61% higher compared to the highest quintile, and 2251.59% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Cheboygan County median household income. You can refer the same here

U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

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

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

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

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Little Falls, NY, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Little Falls, NY reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Little Falls households based on income levels.

Key observations

• For Family Households: In Little Falls, the majority of family households, representing 18.7%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $100,000 to $124,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Little Falls, the majority of non-family households, accounting for 14.5%, have income $50,000 to $59,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.47%, earn $100,000 to $124,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Little Falls, NY (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Little Falls, NY
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Little Falls, NY
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Little Falls, NY

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Little Falls median household income. You can refer the same here

This dataset offers a granular view of disposable income trends within Canada, and is available at the Dissemination Area level - enabling marketers to zoom in on micro-level trends within Canada's diverse regions. This level of precision allows for targeted campaigns that resonate with local audiences. Some key features of this dataset include income segmentation and shelter cost insights.

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

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Jul 2025 about savings, personal, rate, and USA.

Distribution of income between married spouses or common-law partners by characteristics of couples, including gender diversity status of couples and presence of children for married spouses or common-law partners.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in New Oxford, PA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,744, while the mean income for the highest quintile (20% of households with the highest income) is 131,423. This indicates that the top earners earn 9 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 170,217, which is 129.52% higher compared to the highest quintile, and 1154.48% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Oxford median household income. You can refer the same here

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

UK residents by broad country of birth and citizenship groups, broken down by UK country, local authority, unitary authority, metropolitan and London boroughs, and counties. Estimates from the Annual Population Survey.

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

This data shows count of employees by 100 regions within Australia over 12 years (2002 - 2014). In 2002, there were 8.5M workers, rising to 10.3M in 2014. Maps show percent change in count of employees over preceding four years eg 2010-2014.Parent data - Employee $ DATA by detailed occupation, by location (SA4), by year; #Changelog:v6 - added new csv file including SA4 names and States.Data from: http://118.138.240.130/viewSA4fullList2010-14.htmlv4.3 - added jpg combining three maps; 2006, 2010, 2014.v4.2 - added link to full database of underlying data now added to figshare (m9.figshare.4522895)v4.1 - add index.html, background20-12-16.pdf - Nectar.org.au archive of site at http://118.138.240.130; amended data totals to include AU GDP per ABSv4 - add description of SQL to extract published data from parent DB.v1 - 3. Minor edits.#descriptionThis dataset is an aggregation of all Australian Salaries and Wages by location and over 12 years in four year snapshots (2002, 2006, 2010, 2014). Some data excluded which was not allocated to a SA4 location. Source Data from ATO; Australian Tax Office.#file_descriptionHeadcountRaw.csv provides total data (employee count). Includes total counts per SA4 location, and percent change between each of the years; 2002 - 6; 2006 - 10; 2010 - 14 eg 101 means 1% increase. This file also contains the SQL query to extract this file from the parent DB.HeadcountRaw_display.csv provides data (employee count) to visualise at (1) National Map.gov.au or (2) Aurin.org.au. This only includes the data for SA4 regions which can be visualised. See #datavis below for explanation of image files.#MethodParent DB CSV files loaded into MariaDB on Nectar Infrastructure (refer NCRIS). SQL to extract this subset of data from parent DB is included in the header of HeadcountRaw.csv. Access through http://areff2000.net16.net.#sourcedataATO Data request at: data.gov.au IdeascaleOriginal data (parent data) at: data.gov.auParent data description: "Individuals data for 2001-02, 2005-06, 2009-10 and 2013-14 income years. Table 1: Salary and Wages income, by Occupation and SA4 location Table 2: Sole trader business income, by Industry and SA4 location." Sole trader data not included in this sub-collection.#current_analysisSee analysis in progress for:=> Individual income by occupation / location at: http://areff2000.net16.net (offline) or http://118.138.240.130 (Updated: 11.11.16) #datavis -How To To view on National Map (data.gov.au mapping tool). 1. Save data as csv. Data (loaded here), currently at: http://118.138.240.130/sa4_deltaHeadcountRaw_display.csv2. Open http://nationalmap.gov.au. 3. Click 'Add Data'. 4. Drag csv file onto map. 5. Click Done. 6. Select Year in control panel (lower left of screen). Raw shows count of jobs. Year shows % change from four years earlier. 7. Click on region (SA4) to see data for that region.#Data_formatYear | Occupation | Location (SA4) | Count of Workers | $ of Workers * Year: [2002, 2006, 2010, 2014]* Salary and Wages; 200,000 lines (summary only included here)* Sole Proprietors; 100,000 lines (not included here)* Occupation: Description at Australian Bureau of Statistics. (3,216 lines) (link below)* SA4 Location descriptions at: http://stat.abs.gov.au/itt/r.jsp?databyregion#/. SA4 definition/description at: http://www.abs.gov.au/ausstats/abs@.nsf/0/B01A5912123E8D2BCA257801000C64F2?opendocument #dataTotals - Salary and WagesYearWorkers (M)Earnings ($B)GDP USD($B)20028.528540020069.4372746201010.24811142201410.35841450Table 1: Aust. Salary and Wages 2002 - 2014.GDP info from: Trading Economics (link below).#datavis1. Three Chloro images made at aurin.org.au (AU researcher login required). eg Chloro12_2014 is 12 colour chloropeth, for 2010 - 2014, Chloro12_2010 is 2006 - 2010, Chloro12_2006 is 2002 - 2006.Please cite images as: Ferrers, R., ATO - User uploaded data (2016) visualised in AURIN portal (map visualisation chloropeth) on 25.8.2016. Viewed online at: https://dx.doi.org/10.6084/m9.figshare.4056282.v22. Red/Orange (year.tiff) images made at nationalmap.org.au (NM), where 2014.tiff is percent difference 2010 - 2014, 2010.tiff is 2006 - 2010, 2006.tiff is 2002 - 2006. Three scale files explain colours on each year.tiff, where related scale is [year]NM_scale.tiff.3. A new #datavis - scatter plot - is available (linked below) at github: http://areff2000.github.io/2017/03/28/plotly.html (Mar '17).#usageThis #datavis was used in a University of Melbourne Library Hackathon - Hack for Good (25.8.16) - https://twitter.com/ValueMgmt/status/769041449862168577Slides attached below: (see Canva link; Ferrers, Li, Kreunen and Lindsay (2016). L^2 Local Livability Index. Online at: https://www.canva.com/design/DAB8-48tlEw/view)https://twitter.com/ValueMgmt/status/770144651953135616