The population rate of change of San Jose, CA was 1.56% in 2011.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

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Demographics and Population Datasets Involving San Jose, CA

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    San Mateo County And California Crime Rates 2000-2014

    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.

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    Richmond, California Census Data

    opendata.ci.richmond.ca.us | Last Updated 2017-01-25T20:58:31.000Z

    Census data from Bay Area Census and US Census.

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    Demographics For Unincorporated Areas In San Mateo County

    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.

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    Vital Signs: Jobs – by county

    data.bayareametro.gov | Last Updated 2018-07-10T01:43:42.000Z

    VITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED June 2016 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2015 http://www.labormarketinfo.edd.ca.gov/ METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City, and Woodside are considered southern San Mateo County. The number of sub-county collections of cities varies from one (San Francisco, Marin, and Napa counties) to four (Santa Clara County). Estimates for sub-county area are the sums of city-level estimates from Longitudinal Employer-Household Dynamics (LEHD) data. To correct for limitations in LEHD estimates, the 2014 estimates were increased to 2015 values preserving the spatial distribution of jobs calculated from LEHD. County employment data from EDD was used to adjust the LEHD estimates. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

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    Economy and Education Indicators, San Bernardino County and California, 2005-2014

    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).

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    Labor Force Demographic Characteristics by Commuting Mode Split: 2012 - 2016

    data.cambridgema.gov | Last Updated 2019-09-17T17:16:51.000Z

    This data set provides demographic and journey to work characteristics of the Cambridge Labor Force by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time leaving home, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Labor Force consist of all persons who live in Cambridge who work or are actively seeking employment. For more information on Journey to Work data in Cambridge, please see the full 2015 report (https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).

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    Vital Signs: Jobs – by subcounty

    data.bayareametro.gov | Last Updated 2018-07-06T18:06:45.000Z

    VITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED June 2016 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE U.S. Census Bureau: LODES Data 2005-2014 http://lehd.ces.census.gov California Employment Development Department: Current Employment Statistics 2014-2015 http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City, and Woodside are considered southern San Mateo County. The number of sub-county collections of cities varies from one (San Francisco, Marin, and Napa counties) to four (Santa Clara County). Estimates for sub-county area are the sums of city-level estimates from Longitudinal Employer-Household Dynamics (LEHD) data. To correct for limitations in LEHD estimates, the 2014 estimates were increased to 2015 values preserving the spatial distribution of jobs calculated from LEHD. County employment data from EDD was used to adjust the LEHD estimates. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

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    Vital Signs: Jobs – Bay Area

    data.bayareametro.gov | Last Updated 2018-07-10T01:43:55.000Z

    VITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED June 2016 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2015 http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City, and Woodside are considered southern San Mateo County. The number of sub-county collections of cities varies from one (San Francisco, Marin, and Napa counties) to four (Santa Clara County). Estimates for sub-county area are the sums of city-level estimates from Longitudinal Employer-Household Dynamics (LEHD) data. To correct for limitations in LEHD estimates, the 2014 estimates were increased to 2015 values preserving the spatial distribution of jobs calculated from LEHD. County employment data from EDD was used to adjust the LEHD estimates. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

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    Concentrations of Protected Classes from Analysis of Impediments

    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).

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    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2013-02-08T20:03:40.000Z

    basic characteristics of people and housing for individual 2010 census block groups