About this dataset

Context

The dataset presents median household incomes for various household sizes in San Diego County, CA, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, all of the household sizes were found in San Diego County. Across the different household sizes in San Diego County the mean income is $114,248, and the standard deviation is $29,606. The coefficient of variation (CV) is 25.91%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $52,320. It then further increased to $136,905 for 7-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/san-diego-county-ca-median-household-income-by-household-size.jpeg" alt="San Diego County, CA median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

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

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 San Diego County median household income. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in San Diego County. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In San Diego County, the median household income for the households where the householder is White increased by $25,148(30.03%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $83,738 in 2013 and $108,886 in 2023.
• Black or African American: In San Diego County, the median household income for the households where the householder is Black or African American increased by $4,794(7.55%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $63,531 in 2013 and $68,325 in 2023.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Diego County.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 San Diego County median household income by race. You can refer the same here

Comprehensive demographic dataset for San Diego County, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This dataset contains data included in the San Diego County Regional Equity Indicators Report led by the Office of Equity and Racial Justice (OERJ). The full report can be found here: https://data.sandiegocounty.gov/stories/s/7its-kgpt.

Geographic data used to create maps in the report can be found here: https://data.sandiegocounty.gov/dataset/Equity-Report-Data-Geography/p6uw-qxpv

Filter by the Indicator column to select data for a particular indicator.

User notes: 10/9/25 - for the report year 2025, data for the following indicators were uploaded with changes relative to report year 2023: Crime Rate: As of January 1, 2021, the FBI replaced the Summary Reporting System (SRS) with the National Incident Based Reporting System (NIBRS), which expands how crimes were recorded and classified. This report uses California’s version of NIBRS, the California Incident Based Reporting System (CIBRS), obtained from the SANDAG Open Data Portal. Crime rates are not disaggregated by jurisdiction, as in the previous Equity Indicator Report. Internet access: The age group variable was incorporated to account for notable disparities in internet access by age. Police Stops and Searches: refined methods. Agency data was aggregated to San Diego County because data was available for all agencies; previously data was available for three agencies. Analysis of RIPA data was updated to exclude stops where the stop was made in response to a call for service, combine transgender women and transgender men into a transgender category, and limit to contraband found during search. Used term “discovery rate” instead of “hit rate.” Removed comparison to traffic collision data and instead compared to population estimates from the American Community Survey. Jail Incarceration: new data sources. The numerator data for the average daily population data in jail was obtained from the San Diego County Sheriff's Office. Population data to calculate the rates was obtained from the San Diego Association of Governments (SANDAG). The terms for conviction status were corrected to "locally sentenced" and "unsentenced" for sentencing status. For jail population data, East African was reclassified as Black and Middle Eastern as White to allow for calculation of rates using SANDAG population estimates.

8/1/25 - for the report year 2025, the following change were made: Business Ownership: the minority and nonminority labels were switched for the population estimates and some of the race/ethnicity data for nonemployer businesses were corrected. Homelessness: added asterisks to category name for unincorporated regions to allow for a footnote in the figure in the story page.

7/11/25 - for the report year 2025, the following changes were made: Beach Water Quality: the number of days with advisories was corrected for Imperial Beach municipal beach, San Diego Bay, and Ocean Beach.

5/22/25 - for the report year 2023, the following changes were made: Youth poverty/Poverty: IPUMS identified an error in the POVERTY variable for multi-year ACS samples. In July 2024, they released a revised version of all multi-year ACS samples to IPUMS USA, which included corrected POVERTY values. The corrected POVERTY values were downloaded, and the analysis was rerun for this indicator using the 2021 ACS 5-year Estimates. Youth Poverty: data source label corrected to be 2021 for all years. Employment, Homeownership, and Cost-Burdened Households - Notes were made consistent for rows where category = Race/Ethnicity.

5/9/25 - Excluding data for the crime section indicators, data were appended on May 9, 2025 and the report will be updated to reflect the new data in August 2025. The following changes in methods were made: For indicators based on American Community Survey (ACS) data, the foreign-born category name was changed to Nativity Status. Internet access: Group quarters is a category included in the survey sample, but it is not part of the universe for the analysis. For the 2025 Equity Report year, respondents in group quarters were excluded from the analysis, whereas for the 2023 Equity Report year, these respondents were included. Adverse childhood experiences - new data source.

Prepared by: Office of Evaluation, Performance, and Analytics and the Office of Equity and Racial Justice, County of San Diego, in collaboration with the San Diego Regional Policy & Innovation Center (https://www.sdrpic.org).

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in San Diego County, CA, 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 San Diego County, CA 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 San Diego County households based on income levels.

Key observations

• For Family Households: In San Diego County, the majority of family households, representing 23.99%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 1.22%, have incomes falling $35,000 to $39,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In San Diego County, the majority of non-family households, accounting for 12.63%, have income $75,000 to $99,999, 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 3.37%, earn $35,000 to $39,999, 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 San Diego County, CA (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 San Diego County, CA
• 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 San Diego County, CA
• 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 San Diego County, CA

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 San Diego County median household income. You can refer the same here

Comprehensive demographic dataset for Mission Hills, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in San Diego County: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 39,082(3.37%) households where the householder is under 25 years old, 426,405(36.76%) households with a householder aged between 25 and 44 years, 412,538(35.57%) households with a householder aged between 45 and 64 years, and 281,797(24.30%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the county of San Diego County, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• 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
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 San Diego County median household income by age. You can refer the same here

Comprehensive demographic dataset for Talmadge, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Comprehensive demographic dataset for Old Town San Diego, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Comprehensive demographic dataset for San Carlos, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

As included in this EnviroAtlas dataset, community level domestic water demand is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by Census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Specific to San Diego, CA, Urban Water Management Plans (available via data.ca.gov and individual providers) and an average of available Residential Gallons Per Capita per Day (R-GPCD) data (available through the California State Water Resources Control Board (CSWRCB)) were used. Within the EnviroAtlas community boundary, provider estimates range from 61 to 362 GPD. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Certificate number and property addresses for active Transient Occupancy Tax (TOT) vacation type certificates. Properties located in the City of San Diego that are rented to Transients for less than one month are required to obtain a Transient Occupancy Registration Certificate. This includes short-term residential occupancy properties of any kind (i.e. houses, condos, rooms, or spaces) rented directly by the owner/operator, by property management companies or via internet travel services. The short-term residential occupancy properties are generally issued a “Vacation” type TOT Certificate. In general, the data available in this dataset is the same information that is displayed on the TOT Certificate. For additional information on Transient Occupancy Registration Certificates and the Transient Occupancy Tax, please visit our website at sandiego.gov/treasurer/taxesfees/tot/.

Comprehensive demographic dataset for Horton Plaza, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Data about property the City of San Diego owns, including the cost, month and year of purchase and the acreage and usage of the site.

Comprehensive demographic dataset for Rancho Encantada - Stonebridge Estates, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

About this dataset

Context

The dataset presents the median household income across different racial categories in San Diego. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of San Diego population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 58.23% of the total residents in San Diego. Notably, the median household income for White households is $110,137. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $120,095. This reveals that, while Whites may be the most numerous in San Diego, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/san-diego-ca-median-household-income-by-race.jpeg" alt="San Diego median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Diego.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

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 San Diego median household income by race. You can refer the same here

Comprehensive demographic dataset for Mission Beach, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Quarterly surveys of physical, chemical, and biological parameters in ocean water using a Remotely Operated Towed Vehicle (ROTV). The City’s Ocean Monitoring Program (OMP) conducts quarterly surveys using a ROTV. The ROTV houses multiple sensors used to monitor physical, chemical, and biological parameters to assess water quality and the fate of treated wastewater effluent across the San Diego coastline with high spatial resolution. In the initial phase of ROTV monitoring, efforts were focused on corroborating ROTV data against traditional water quality monitoring data by surveying across the traditional sampling grid. Future surveys will be conducted adaptively with monitoring efforts focused on the location of the treated wastewater effluent, when observable. Please note: ROTV data have been preliminarily reviewed by Marine Biology and Ocean Operations staff using automated checks and some manual review. Inaccuracies in the data may persist due to subtle instrument problems or the lack of appropriate validation data, and subsequent review may result in future revisions to the data. See ROTV parameter definitions for a description of variables by file name and for data qualifier (QARTOD flag) definitions. Data qualified as “bad” or “suspect” have been excluded from this dataset.

This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," [1]. These files include electricity demand profiles for 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], [3], that produces realistic patterns of residential power consumption, validated using metered data, with a resolution of 10 minutes. Households vary in size and number of occupants and the profiles represent total electricity use, in watts. The files also include in-home plug-in electric vehicle recharging profiles for 348 vehicles associated with the 200 households assuming both Level 1 (1920 W) and Level 2 (6600 W) residential charging infrastructure. The vehicle recharging profiles have been generated using the modeling proposed by Muratori et al. [4], that produces real-world recharging demand profiles, with a resolution of 10 minutes. [1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming. [2] M. Muratori, M. C. Roberts, R. Sioshansi, V. Marano, and G. Rizzoni, "A highly resolved modeling technique to simulate residential power demand," Applied Energy, vol. 107, no. 0, pp. 465 - 473, 2013. https://doi.org/10.1016/j.apenergy.2013.02.057 [3] M. Muratori, V. Marano, R. Sioshansi, and G. Rizzoni, "Energy consumption of residential HVAC systems: a simple physically-based model," in 2012 IEEE Power and Energy Society General Meeting. San Diego, CA, USA: IEEE, 22-26 July 2012. https//doi.org/10.1109/PESGM.2012.6344950 [4] M. Muratori, M. J. Moran, E. Serra, and G. Rizzoni, "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, vol. 58, no. 0, pp. 168-177, 2013. https://doi.org/10.1016/j.energy.2013.02.055

Comprehensive demographic dataset for Ocean Beach, San Diego, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.