https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Employed Persons in San Diego County, CA (LAUCN060730000000005) from Jan 1990 to May 2025 about San Diego County, CA; San Diego; CA; household survey; employment; persons; and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of San Diego County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of San Diego County across both sexes and to determine which sex constitutes the majority.
Key observations
There is a slight majority of male population, with 50.57% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.
Variables / Data Columns
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.
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 dataset is a part of the main dataset for San Diego County Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of San Diego by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for San Diego. The dataset can be utilized to understand the population distribution of San Diego by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in San Diego. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for San Diego.
Key observations
Largest age group (population): Male # 30-34 years (68,922) | Female # 25-29 years (62,866). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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 dataset is a part of the main dataset for San Diego Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the San Diego population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of San Diego across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of San Diego was 1.39 million, a 0.07% increase year-by-year from 2022. Previously, in 2022, San Diego population was 1.39 million, an increase of 0.82% compared to a population of 1.38 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of San Diego increased by 160,441. In this period, the peak population was 1.42 million in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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.
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 dataset is a part of the main dataset for San Diego Population by Year. You can refer the same here
SANDAG provides an annual report on crime in the San Diego region. This dataset contains data from the 2009 through 2022 editions of the report. Data for 2023 is converted from California Incident Based Reporting System (CIBRS) data provided by SANDAG. Additional data comes from Arjis and DOJ OpenJustice. Some data for previous years reports is updated with new editions. "San Diego County" includes all cities and unincorporated areas in San Diego County. "Sheriff - Total" includes the contract cities and the unincorporated area served by the San Diego County Sheriff's Department. California and United States data come from the FBI's Annual Crime Reports.
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) 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. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB 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.
The San Diego, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a suite of numerical simulation codes capable of simulating three processes of tsunami evolution: generation, transoceanic propagation, and inundation of dry land. Tsunami waves are computationally propagated across a set of three nested grids (A, B, and C), each of which is successively finer in resolution, moving from offshore to onshore. Nearshore details are resolved to the point that model output can be directly compared with tide gauge observations and can provide estimates of wave arrival time, wave amplitude and simulation of wave inundation onto dry land. A Grid Resolution: 60 arc-sec. B Grid Resolution: 12 arc-sec. C Grid Resolution: 3 arc-sec.
The purpose of this project was to describe each of the native and naturalized vegetation types known to occur within western San Diego County and to provide the user a means to determine each type through direct observations of species composition. The classification presented herein is the result of a detailed analysis of data collected throughout the western San Diego County study area. Under contract to the San Diego Association of Governments (SANDAG), Biologists from AECOM, Conservation Biology Institute, and the California Department of Fish and Game (CDFG) Vegetation Classification and Mapping Program (VegCAMP) collaborated on these analyses, the definition of the classifications, and preparation of this manual. This classification study was conducted in a manner consistent with the recommendations for standardized data collection and analysis by CDFG VegCAMP (https://wildlife.ca.gov/Data/VegCAMP) and the methods used in the preparation of A Manual of California Vegetation, 2nd ed. (Sawyer; Keeler-Wolf; Evens 2009), published by the California Native Plant Society (CNPS). This projects classifications is in accordance with this larger work. A Manual of California Vegetation (MCV) is intentionally consistent within the larger context of the National Vegetation Classification System (NVCS), which has been adopted by federal agencies and nongovernmental organizations such as the US Geological Survey, National Park Service, and NatureServe. Thus each of these classifications can be compared in context with the others nationwide.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Rancho San Diego CDP, 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.
The data in this repository were collected from the San Diego, California testbed, namely, I-15 from the interchange with SR-78 in the north to the interchange with SR-163 in the south, along the mainline and at the entrance ramps. This file contains information on the field observation and simulation results for speed profile from the Dallas, Texas testbed. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Unemployed Persons in San Diego County, CA (LAUCN060730000000004) from Jan 1990 to May 2025 about San Diego County, CA; San Diego; CA; household survey; unemployment; persons; and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the San Diego County, CA population pyramid, which represents the San Diego County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
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.
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 dataset is a part of the main dataset for San Diego County Population by Age. You can refer the same here
These data were automated to provide an accurate high-resolution historical shoreline of San Diego, California suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808
These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.The purpose of the study was to provide statistically sound estimates on the prevalence of trafficking victimization and investigate the type of trafficking victimization among unauthorized migrant laborers in San Diego. Data were collected through face to face interviews using respondent driven sampling (Labor Trafficking Main Data, n=826 and Specific Trafficking Incident Data, n=826). There were sixteen interview sites spread across San Diego county. All interviews were conducted with at least two interviewers present. The study used a total of seven bilingual interviewers who conducted 826 valid interviews. Each subject was paid thirty dollars for participating in the interview, and given three referral coupons worth ten dollars each. The Respondent Driven Sampling (RDS) began with an initial set of "seeds" recruited from the target population through a combination of recruiting strangers at day labor sites and existing community contacts within the social networks of Center for Social Advocacy (CSA) outreach workers. To be eligible for participation in the study, one had to be unauthorized in the United States and be working (or have worked within) the past 3 months. Other than the seeds, all subsequent referrals had to call the project phone number to schedule interviews with their coupon numbers.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Vegetation Map of Cañada de San Vicente (CSV), San Diego County, was created by the California Department of Fish and Game (DFG) Vegetation and Mapping Program (VegCAMP). CSV, formerly known as Monte Vista Ranch, was acquired in April 2009 by DFG and is currently not open to the public as the management plan is not complete. The map study area boundary is based on the DFG Lands layer that was published in April, 2011 and includes 4888 acres of land. This includes 115 acres of private land located in the northeast corner of the map that was considered an area of interest (AOI) before purchase by DFG. The map is based on field data from 38 vegetation Rapid Assessment surveys (RAs), 111 reconnaissance points, and 118 verification points that were conducted between April 2009 and January 2012. The rapid assessment surveys were collected as part of a comprehensive effort to create the Vegetation Classification Manual for Western San Diego County (Sproul et al., 2011). A total of 1265 RAs and 18 relevés were conducted for this larger project, all of which were analyzed together using cluster analysis to develop the final vegetation classification. The CSV area was delineated by vegetation type and each polygon contains attributes for hardwood tree, shrub and herb cover, roadedness, development, clearing, and heterogeneity. Of 545 woodland and shrubland polygons that were delineated, 516 were mapped to the association level and 29 to the alliance level (due to uncertainty in the association). Of 46 herbaceous polygons that were delineated, 36 were mapped to the group or macrogroup level and 8 were mapped to association. Four polygons were mapped as urban or agriculture. The classification and map follow the National Vegetation Classification Standard (NVCS) and Federal Geographic Data Committee (FGDC) standard and State of California Vegetation and Mapping Standards. The minimum mapping area unit (MMU) is one acre, though occasionally, vegetation is mapped below MMU for special types including wetland, riparian, and native herbaceous and when it was possible to delineate smaller stands with a high degree of certainty (e.g., with available field data). In total, about 45 percent of the polygons were supported by field data points and 55 percent were based on photointerpretation.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the San Diego population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for San Diego. The dataset can be utilized to understand the population distribution of San Diego by age. For example, using this dataset, we can identify the largest age group in San Diego.
Key observations
The largest age group in San Diego, CA was for the group of age 25 to 29 years years with a population of 130,712 (9.44%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in San Diego, CA was the 85 years and over years with a population of 23,020 (1.66%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
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.
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 dataset is a part of the main dataset for San Diego Population by Age. You can refer the same here
This EnviroAtlas dataset is the base layer for the San Diego, CA EnviroAtlas area. The block groups are from the US Census Bureau and are included/excluded based on EnviroAtlas criteria described in the procedure log. This dataset was produced 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).
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).
Financial overview and grant giving statistics of California Association For Nurse Practitioners San Diego North Chap
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Employed Persons in San Diego County, CA (LAUCN060730000000005) from Jan 1990 to May 2025 about San Diego County, CA; San Diego; CA; household survey; employment; persons; and USA.