U.S. Census Bureau QuickFacts statistics for San Diego city, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in San Diego: 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 21,786(4.17%) households where the householder is under 25 years old, 215,194(41.21%) households with a householder aged between 25 and 44 years, 171,107(32.77%) households with a householder aged between 45 and 64 years, and 114,059(21.84%) 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 city of San Diego, 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 median household income by age. You can refer the same here

Gender by Age by City, San Diego County. Source: U.S. Census Bureau; 2012-2016 American Community Survey 5-Year Estimates, Table B01001.

Graph and download economic data for Resident Population in San Diego County, CA (CASAND5POP) from 1970 to 2024 about San Diego County, CA; San Diego; residents; CA; population; and USA.

Population by Age, Sex and Ethnicity by City of San Diego Council District from the 2020 Decennial Census

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

About this dataset

Context

This list ranks the 18 cities in the San Diego County, CA by Multi-Racial Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Multi-Racial Black Population: This column displays the rank of cities in the San Diego County, CA by their Multi-Racial Black or African American population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Black Population: The Multi-Racial Black population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total San Diego County Multi-Racial Black Population: This tells us how much of the entire San Diego County, CA Multi-Racial Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

This data collection was produced by the San Diego Association of Governments (SANDAG) and donated to the University of California, San Diego Social Science Data Collection (SSDC) for archival retention and public dissemination. The data consists of 1990 April 1 Census Bureau population and housing data and annual SANDAG intercensal estimates of population and housing data from 1991 through 2000. The data have been designed for comparability with historical census data, and these estimates may be used to evaluate changes occurring over time. Estimates are available for the San Diego region, major statistical areas (MSAs), subregional areas (SRAs), census tracts, cities, zip codes, County of San Diego Planning Areas, and City of San Diego Community Planning Areas. Almost 400 variables in the dataset include: Total Population, Population in Households, Housing Units by category, Households by income level, Median Household Income, Employment by broad sector, Occupation by broad category, and land area. Population estimates are available by sex/age/ethnicity. The data use 23 age groupings and four ethnic groupings. The four ethnic groups are Hispanic, non-Hispanic White, non- Hispanic Black, and non-Hispanic Asian. These groups are defined based on comb ined responses to two questions on the U.S. Census form, one concerning race and another concerning Hispanic origin. Those who wish to analyze the data with statistical software or merge the data with GIS boundary files may, from the SSDC files page, download the the original data files as they were distributed by SANDAG, or the merged data files created by SSDC staff, or create subsets and download those in any of a number of popular formats (e.g., SPSS, SAS, csv, etc.). Those who wish to quickly view the statistics in spreadsheet form may wish to use the links below to Excel spreadsheets created by SSDC staff. These spreadsheets do not contain all the data, but do contain the most often used variables and are easy to read and use . Those SANDAG maps and administrative digital boundary files that are available to everyone are available here through SSDC. The UCSD Library GIS Lab has additional digital boundary files that can be used only by UCSD faculty, students and staff.

This dataset features polygon representations of 2020 US Census Bureau census tracts, focusing specifically on census tract numbers for the City of Carlsbad. Originally sourced from San Diego Geographic Information Source (SanGIS), with coverage spanning San Diego County, the dataset has been customized by clipping to the City of Carlsbad boundary line. This tailored dataset serves as a convenient reference for census tract boundaries within Carlsbad.Point of ContactU.S. Census Bureau4600 Silver Hill RoadWashington, DC. 20233-7400 geo.tiger@census.gov301-763-1128

This dataset presents a detailed overview of demographic information from the 2010 Census, focusing on the level of Carlsbad neighborhoods. It delves into smaller, more localized regions within the City of Carlsbad, offering insights into population distribution, racial makeup, family structures, household types, and housing details. Tailored for the visualization and analysis of local demographics, this dataset is especially valuable for discerning trends within specific Carlsbad neighborhoods. It is designed to provide a comprehensive look at the social and housing landscape at the neighborhood level within the City of Carlsbad."It's important to note that the original dataset was sourced from the San Diego Geographic Information Source (SanGIS) and San Diego Association of Governments (SANDAG). Initially covering census tracts for the entire San Diego County, we refined the dataset by clipping it to the specific boundary line of the City of Carlsbad. This process was undertaken to tailor the dataset to the unique demographic profile of Carlsbad, making it more pertinent for local analyses and mapping.Point of Contact:Operations ManagerU.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch4600 Silver Hill RoadWashington, DC 20233

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads shapefile includes all features within the MTS Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in the MTS that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.

Population by 5-year Age Groups by City of San Diego Council District from the 2020 Decennial Census

Households by Household Income Range, by City. Source: U.S. Census Bureau; 2012-2016 American Community Survey 5-Year Estimates, Table DP03.

Commute to Work by City. Source: U.S. Census Bureau; 2012-2016 American Community Survey 5-Year Estimates, Table DP03.

Population by Sex by City of San Diego Council District from the 2020 Decennial Census

This dataset comprises 2010 census blocks as polygons for the County of San Diego. A census block is the smallest geographic unit used by the United States Census Bureau for the tabulation of100-percent data (data collected from all houses, rather than a sample of houses). Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks are typically bounded by streets, roads or creeks. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be limited by other features. The population by census blocks varies greatly. Topologically Integrated Geographic Encoding and Referencing (TIGER) is a format used by the US Census Bureau to describe land attributes such as roads, buildings, rivers, and lakes, as well as areas such as census tracts. TIGER was developed to support and improve the Census Bureau's process of taking the Decennial Census. The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. TIGER data was used as the basis for this Census Blocks dataset, which was then edited by SANDAG, and then further edited by SanGIS. TIGER blocks were adjusted to match local GIS data including parcels, municipal boundaries, and roads. Some blocks were merged with adjacent blocks. The ocean blocks were removed.Point of Contact:Operations Manager, Operations ManagerSanGIS5510 Overland Avenue, Suite 230San Diego, California. 92123webmaster@sangis.org(858) 874-7000

Housing Units by Type by City of San Diego Council District from the 2020 Decennial Census

U.S. Census Bureau QuickFacts statistics for San Pablo city, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Population by City of San Diego Council District from the 2020 Decennial Census

The number and percent of the population by race and ethnicity. API refers to Asian/ Pacific Islanders and include Asian, Pacific Islander, and Native Hawaiian. Other Race includes American Indian or Alaska Native, 2 or more races, and other. Source: U.S. Census Bureau; 2011-2015 American Community Survey 5-Year Estimates, Table B03002.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.