- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Mean Job Proximity Index?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Mean Environmental Health Hazard Index?
The population count of San Diego County, CA was 3,283,665 in 2017.
Demographics and Population Datasets Involving San Diego County, CA
- API performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000Z
Violent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.
- API data.livewellsd.org | Last Updated 2017-09-10T03:32:38.000Z
The number and percent of the population stratified by race/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.
- API datahub.smcgov.org | Last Updated 2018-10-25T21:45:46.000Z
Demographics, including median income, total population, race, ethnicity, and age for unincorporated areas in San Mateo County. This data comes from the 2012 American Community Survey 5 year estimates DP03 and DP05 files. They Sky Londa area is located within two Census Tracts. The data for Sky Londa is the sum of both of those Census Tracts. Users of this data should take this into account when using data for Sky Londa.
- API data.livewellsd.org | Last Updated 2017-09-10T04:19:08.000Z
Source: U.S. Census Bureau; 2011-2015 American Community Survey 5-Year Estimates, Table B22002, B22007, B17024.
- API results.livewellsd.org | Last Updated 2018-12-06T23:01:40.000Z
Indicators Trend Data for Goal Measures
- API data.communityvitalsigns.org | Last Updated 2016-03-01T19:43:41.000Z
This dataset contains high school graduation rates from 2010-2014 for San Bernardino County and California (from California Department of Education, California Longitudinal Pupil Achievement Data System, Cohort Outcome Data by Gender Report), and percentage of the adult population age 25 years and older with a bachelor's degree or higher, median household income in the past 12 months (adjusted annually for inflation), and unemployment rate for the population age 16 years and older, for San Bernardino County and California from 2005-2014 (U.S. Census Bureau, American Community Survey 1-Year Estimates, Tables B19013, S1501 and S2301).
- API data.sandiegocounty.gov | Last Updated 2019-03-30T01:05:58.000Z
Leading Causes of Death in San Diego County, by Gender, Race/Ethnicity, HHSA Region and Supervisorial District. Gender and race/ethnicity are at the county geographic level. Notes: 1. Rank is based on total number of deaths in each of the National Center for Health Statistics (NCHS) "rankable" categories. The top 15 leading causes of death presented here are based on the San Diego County residents for each year. 2. Cause of death is based on the underlying cause of death reported on death certificates as classified by ICD-10 codes. 3. Deaths for specific demographics or geographic area may not equal the total deaths for San Diego County due to missing data. § Not shown for fewer than 5 deaths. Source: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System. Prepared by County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2018.
- API data.austintexas.gov | Last Updated 2019-07-29T17:26:04.000Z
A new component of fair housing studies is an analysis of the opportunities residents are afforded in “racially or ethnically concentrated areas of poverty,” also called RCAPs or ECAPs. An RCAP or ECAP is a neighborhood with significant concentrations of extreme poverty and minority populations. HUD’s definition of an RCAP/ECAP is: • A Census tract that has a non‐white population of 50 percent or more AND a poverty rate of 40 percent or more; OR • A Census tract that has a non‐white population of 50 percent or more AND the poverty rate is three times the average tract poverty rate for the metro/micro area, whichever is lower. Why the 40 percent threshold? The RCAP/ECAP definition is not meant to suggest that a slightly‐lower‐than‐40 percent poverty rate is ideal or acceptable. The threshold was borne out of research that concluded a 40 percent poverty rate was the point at which a neighborhood became significantly socially and economically challenged. Conversely, research has shown that areas with up to 14 percent of poverty have no noticeable effect on community opportunity. (See Section II in City of Austin’s 2015 Analysis of Impediments to Fair Housing Choice: http://www.austintexas.gov/sites/default/files/files/NHCD/Reports_Publications/1Analysis_Impediments_for_web.pdf) This dataset provides socioeconomic data on protected classes from the 2008-2012 American Community Survey on census tracts in Austin’s city limits and designates which of those tracts are considered RCAPs or ECAPs based on these socioeconomic characteristics. A map of the census tracts designated as RCAPs or ECAPs is attached to this dataset and downloadable as a pdf (see below).
- API data.kcmo.org | Last Updated 2013-02-08T20:03:40.000Z
basic characteristics of people and housing for individual 2010 census block groups
- API datahub.smcgov.org | Last Updated 2016-08-10T18:35:32.000Z
Employment and unemployment data by city for places in San Mateo County. CDP is "Census Designated Place" - a recognized community that was unincorporated at the time of the 2000 Census. 1) Data may not add due to rounding. All unemployment rates shown are calculated on unrounded data. 2) These data are not seasonally adjusted. Methodology: Monthly city and CDP labor force data are derived by multiplying current estimates of county employment and unemployment by the employment and unemployment shares (ratios) of each city and CDP at the time of the 2000 Census. Ratios for cities of 25,000 or more persons were developed from special tabulations based on household population only from the Bureau of Labor Statistics. For smaller cities and CDP, ratios were calculated from published census data. City and CDP unrounded employment and unemployment are summed to get the labor force. The unemployment rate is calculated by dividing unemployment by the labor force. Then the labor force, employment, and unemployment are rounded. This method assumes that the rates of change in employment and unemployment, since 2000, are exactly the same in each city and CDP as at the county level (i.e., that the shares are still accurate). If this assumption is not true for a specific city or CDP, then the estimates for that area may not represent the current economic conditions. Since this assumption is untested, caution should be employed when using these data.