100+ datasets found
  1. d

    California Counties

    • catalog.data.gov
    • data.cnra.ca.gov
    • +5more
    Updated Nov 27, 2024
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    California Energy Commission (2024). California Counties [Dataset]. https://catalog.data.gov/dataset/california-counties-254c9
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Energy Commission
    Area covered
    California
    Description

    Counties in California intended for the NEVI Map.Data downloaded in May 2021 from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2021.html#list-tab-VGDZBC72KXZ7CWIQNY.

  2. c

    20 Richest Counties in California

    • california-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). 20 Richest Counties in California [Dataset]. https://www.california-demographics.com/counties_by_population
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    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.california-demographics.com/terms_and_conditionshttps://www.california-demographics.com/terms_and_conditions

    Area covered
    California
    Description

    A dataset listing California counties by population for 2024.

  3. N

    Orange County, CA Population Pyramid Dataset: Age Groups, Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
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    Neilsberg Research (2025). Orange County, CA Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/orange-county-ca-population-by-age/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Orange County, California
    Variables measured
    Male and Female Population Under 5 Years, Male and Female Population over 85 years, Male and Female Total Population for Age Groups, Male and Female Population Between 5 and 9 years, Male and Female Population Between 10 and 14 years, Male and Female Population Between 15 and 19 years, Male and Female Population Between 20 and 24 years, Male and Female Population Between 25 and 29 years, Male and Female Population Between 30 and 34 years, Male and Female Population Between 35 and 39 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the three variables, namely (a) male population, (b) female population and (b) total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the data for the Orange County, CA population pyramid, which represents the Orange 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

    • Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Orange County, CA, is 26.1.
    • Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Orange County, CA, is 23.6.
    • Total dependency ratio for Orange County, CA is 49.7.
    • Potential support ratio, which is the number of youth (working age population) per elderly, for Orange County, CA is 4.2.
    Content

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

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    Variables / Data Columns

    • Age Group: This column displays the age group for the Orange County population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the Orange County for the selected age group is shown in the following column.
    • Population (Female): The female population in the Orange County for the selected age group is shown in the following column.
    • Total Population: The total population of the Orange County for the selected age group is shown in the following column.

    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 Orange County Population by Age. You can refer the same here

  4. Data from: County Health Status Profiles

    • data.chhs.ca.gov
    • data.ca.gov
    • +1more
    csv, zip
    Updated Aug 28, 2024
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    California Department of Public Health (2024). County Health Status Profiles [Dataset]. https://data.chhs.ca.gov/dataset/county-health-status-profiles
    Explore at:
    csv(570397), zip, csv(570685), csv(567843), csv(4783), csv(549726)Available download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    County Health Status Profiles is an annually published report for the State of California by the California Department of Public Health in collaboration with the California Conference of Local Health Officers. Health indicators are measured for 58 counties and California statewide that can be directly compared to national standards and populations of similar composition. Where available, the measurements are ranked and compared with target rates established for Healthy People National Objectives.

    For tables where the health indicator denominator and numerator are derived from the same data source, the denominator excludes records for which the health indicator data is missing and unable to be imputed.

    For more information see the County Health Status Profiles report.

  5. Counties In California

    • wifire-data.sdsc.edu
    csv, esri rest +4
    Updated Dec 21, 2020
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    CA Governor's Office of Emergency Services (2020). Counties In California [Dataset]. https://wifire-data.sdsc.edu/dataset/counties-in-california
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    esri rest, kml, zip, csv, html, geojsonAvailable download formats
    Dataset updated
    Dec 21, 2020
    Dataset provided by
    California Governor's Office of Emergency Services
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    California
    Description

    Feature layer of the Counties in California as used by Cal OES. Columns designating CalOES Regions, Fire and Law Mutual Aid Regions, and county name.

  6. N

    Tulare County, CA Population Breakdown by Gender and Age Dataset: Male and...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
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    Tulare County, CA Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/tulare-county-ca-population-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Tulare County, California
    Variables measured
    Male and Female Population Under 5 Years, Male and Female Population over 85 years, Male and Female Population Between 5 and 9 years, Male and Female Population Between 10 and 14 years, Male and Female Population Between 15 and 19 years, Male and Female Population Between 20 and 24 years, Male and Female Population Between 25 and 29 years, Male and Female Population Between 30 and 34 years, Male and Female Population Between 35 and 39 years, Male and Female Population Between 40 and 44 years, and 8 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the three variables, namely (a) Population (Male), (b) Population (Female), and (c) Gender Ratio (Males per 100 Females), we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau across 18 age groups, ranging from under 5 years to 85 years and above. These age groups are described above in the variables section. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of Tulare County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Tulare County. The dataset can be utilized to understand the population distribution of Tulare County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Tulare County. 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 Tulare County.

    Key observations

    Largest age group (population): Male # 10-14 years (21,955) | Female # 10-14 years (21,486). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

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

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    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

    • Age Group: This column displays the age group for the Tulare County population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the Tulare County is shown in the following column.
    • Population (Female): The female population in the Tulare County is shown in the following column.
    • Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Tulare County for each age group.

    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 Tulare County Population by Gender. You can refer the same here

  7. Live Birth Profiles by County

    • data.chhs.ca.gov
    • data.ca.gov
    • +1more
    csv, zip
    Updated Jan 28, 2025
    + more versions
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    California Department of Public Health (2025). Live Birth Profiles by County [Dataset]. https://data.chhs.ca.gov/dataset/live-birth-profiles-by-county
    Explore at:
    csv(1911), csv(320734), zip, csv(9986780), csv(8256822)Available download formats
    Dataset updated
    Jan 28, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    This dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

    The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

  8. d

    Data from: California County Boundaries

    • catalog.data.gov
    • data.ca.gov
    • +5more
    Updated Nov 27, 2024
    + more versions
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    CAL FIRE (2024). California County Boundaries [Dataset]. https://catalog.data.gov/dataset/california-county-boundaries-bd0f6
    Explore at:
    Dataset updated
    Nov 27, 2024
    Dataset provided by
    CAL FIRE
    Area covered
    California
    Description

    In late 1996, the Dept of Conservation (DOC) surveyed state and federal agencies about the county boundary coverage they used. As a result, DOC adopted the 1:24,000 (24K) scale U.S. Bureau of Reclamation (USBR) dataset (USGS source) for their Farmland Mapping and Monitoring Program (FMMP) but with several modifications. Detailed documentation of these changes is provided by FMMP and included in the lineage section of the metadata.A dataset was made available (approximately 2004) through CALFIRE - FRAP and the California Spatial Information Library (CaSIL), with additional updates throughout subsequent years. More recently, an effort was made to improve the coastal linework by using the previous interior linework from the 24k data, but replacing the coastal linework based on NOAA's ERMA coastal dataset (which used NAIP 2010). In this dataset, all bays (plus bay islands and constructed features) are merged into the mainland, and coastal features (such as islands and constructed features) are not included, with the exception of the Channel Islands which ARE included.This service represents the latest released version, and is updated when new versions are released. As of June, 2019 it represents cnty19_1.

  9. F

    Population Estimate, Total (5-year estimate) in Orange County, CA

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Population Estimate, Total (5-year estimate) in Orange County, CA [Dataset]. https://fred.stlouisfed.org/series/B03002001E006059
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Orange County, California
    Description

    Graph and download economic data for Population Estimate, Total (5-year estimate) in Orange County, CA (B03002001E006059) from 2009 to 2023 about Orange County, CA; Los Angeles; CA; estimate; persons; 5-year; population; and USA.

  10. N

    Los Angeles County, CA Age Group Population Dataset: A Complete Breakdown of...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
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    Neilsberg Research (2025). Los Angeles County, CA Age Group Population Dataset: A Complete Breakdown of Los Angeles County Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/los-angeles-county-ca-population-by-age/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Los Angeles County, California
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Los Angeles County 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 Los Angeles County. The dataset can be utilized to understand the population distribution of Los Angeles County by age. For example, using this dataset, we can identify the largest age group in Los Angeles County.

    Key observations

    The largest age group in Los Angeles County, CA was for the group of age 30 to 34 years years with a population of 798,347 (8.11%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Los Angeles County, CA was the 80 to 84 years years with a population of 166,251 (1.69%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Content

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

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    Variables / Data Columns

    • Age Group: This column displays the age group in consideration
    • Population: The population for the specific age group in the Los Angeles County is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of Los Angeles County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    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 Los Angeles County Population by Age. You can refer the same here

  11. Population of California 2023, by race and ethnicity

    • statista.com
    Updated Oct 17, 2024
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    Statista (2024). Population of California 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/306026/california-population-ethnicity-race/
    Explore at:
    Dataset updated
    Oct 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States, California
    Description

    In 2023, the number of Hispanic and Latino residents in California had surpassed the number of White residents, with about 15.76 million Hispanics compared to 12.96 million white residents. California’s residents California has always held a special place in the American imagination as a place where people can start a new life and increase their personal fortunes. Perhaps due partly to this, California is the most populous state in the United States, with over 39 million residents, which is a significant increase from the number of residents in 1960. California is also the U.S. state with the largest population of foreign born residents. The Californian economy The Californian economy is particularly strong and continually contributes a significant amount to the gross domestic product (GDP) of the United States. Its per-capita GDP is also high, which indicates a high standard of living for its residents. Additionally, the median household income in California has more than doubled from 1990 levels.

  12. Resident population in California 1960-2023

    • statista.com
    Updated Nov 5, 2024
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    Statista (2024). Resident population in California 1960-2023 [Dataset]. https://www.statista.com/statistics/206097/resident-population-in-california/
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    Dataset updated
    Nov 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States, California
    Description

    In 2023, the resident population of California was 38.97 million. This is a slight decrease from the previous year, with 39.03 million people in 2022. This makes it the most populous state in the U.S. Californian demographics Along with an increase in population, California’s gross domestic product (GDP) has also been increasing, from 1.7 trillion U.S. dollars in 2000 to 3.23 trillion U.S. dollars in 2023. In the same time period, the per-capita personal income has almost doubled, from 33,403 U.S. dollars in 2000 to 77,339 U.S. dollars in 2022. In 2023, the majority of California’s resident population was Hispanic or Latino, although the number of white residents followed as a close second, with Asian residents making up the third largest demographic in the state. The dark side of the Golden State While California is one of the most well-known states in the U.S., is home to Silicon Valley, and one of the states where personal income has been increasing over the past 20 years, not everyone in California is so lucky: In 2023, the poverty rate in California was about 12 percent, and the state had the fifth-highest rate of homelessness in the country during that same year, with an estimated 46 homeless people per 10,000 of the population.

  13. QuickFacts: California

    • census.gov
    • shutdown.census.gov
    csv
    Updated Jul 1, 2023
    + more versions
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    United States Census Bureau > Communications Directorate - Center for New Media and Promotion (2023). QuickFacts: California [Dataset]. https://www.census.gov/quickfacts/fact/table/CA/INC110223
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jul 1, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United States Census Bureau > Communications Directorate - Center for New Media and Promotion
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    California
    Description

    U.S. Census Bureau QuickFacts statistics for 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.

  14. F

    Estimate of Median Household Income for Glenn County, CA

    • fred.stlouisfed.org
    json
    Updated Dec 20, 2024
    + more versions
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    (2024). Estimate of Median Household Income for Glenn County, CA [Dataset]. https://fred.stlouisfed.org/series/MHICA06021A052NCEN
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 20, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Glenn County, California
    Description

    Graph and download economic data for Estimate of Median Household Income for Glenn County, CA (MHICA06021A052NCEN) from 1989 to 2023 about Glenn County, CA; CA; households; median; income; and USA.

  15. COVID-19 Time-Series Metrics by County and State (ARCHIVED)

    • data.chhs.ca.gov
    • data.ca.gov
    • +1more
    csv, xlsx, zip
    Updated Aug 28, 2024
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    California Department of Public Health (2024). COVID-19 Time-Series Metrics by County and State (ARCHIVED) [Dataset]. https://data.chhs.ca.gov/dataset/covid-19-time-series-metrics-by-county-and-state
    Explore at:
    csv(7729431), csv(6223281), xlsx(6471), xlsx(11305), csv(3313), xlsx(7811), csv(4836928), zipAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    Note: This COVID-19 data set is no longer being updated as of December 1, 2023. Access current COVID-19 data on the CDPH respiratory virus dashboard (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx) or in open data format (https://data.chhs.ca.gov/dataset/respiratory-virus-dashboard-metrics).

    As of August 17, 2023, data is being updated each Friday.

    For death data after December 31, 2022, California uses Provisional Deaths from the Center for Disease Control and Prevention’s National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS). Prior to January 1, 2023, death data was sourced from the COVID-19 registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023.

    As of May 11, 2023, data on cases, deaths, and testing is being updated each Thursday. Metrics by report date have been removed, but previous versions of files with report date metrics are archived below.

    All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

    The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

  16. Vital Signs: Migration - by county (simple)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Dec 12, 2018
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    U.S. Census Bureau (2018). Vital Signs: Migration - by county (simple) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Migration-by-county-simple-/qmud-33nk
    Explore at:
    csv, tsv, json, application/rdfxml, application/rssxml, xmlAvailable download formats
    Dataset updated
    Dec 12, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau
    Description

    VITAL SIGNS INDICATOR Migration (EQ4)

    FULL MEASURE NAME Migration flows

    LAST UPDATED December 2018

    DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables.

    DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration.

    Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23)

    One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.

  17. a

    California County Boundaries and Identifiers

    • hub.arcgis.com
    • gis.data.ca.gov
    Updated Sep 16, 2024
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    California Department of Technology (2024). California County Boundaries and Identifiers [Dataset]. https://hub.arcgis.com/datasets/60b7e0f3d33b4064a4b43bf14589bfe3
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    California Department of Technology
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Description

    WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:Metadata is missing or incomplete for some layers at this time and will be continuously improved.We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.PurposeCounty boundaries boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, coastal buffers are removed, leaving the land-based portions of jurisdictions. This feature layer is for public use.Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal Buffers (this dataset)Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal BuffersWithout Coastal BuffersPlace AbbreviationsUnincorporated Areas (Coming Soon)Census Designated Places (Coming Soon)Cartographic CoastlinePolygonLine source (Coming Soon)Working with Coastal BuffersThe dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the authoritative source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.govField and Abbreviation DefinitionsCOPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering systemPlace Name: CDTFA incorporated (city) or county nameCounty: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information SystemPlace Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area namesCNTY Abbr: CalTrans Division of Local Assistance abbreviations of county namesArea_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".AccuracyCDTFA"s source data notes the following about accuracy:City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the California State Board of Equalization"s 6-digit tax rate area numbering system (for the purpose of this map, unincorporated areas are assigned 000 to indicate that the area is not within a city).Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties.In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose.SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon.Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these items, or others, from the shoreline cuts, please reach out using the contact information above.Offline UseThis service is fully enabled for sync and export using Esri Field Maps or other similar tools. Importantly, the GlobalID field exists only to support that use case and should not be used for any other purpose (see note in field descriptions).Updates and Date of ProcessingConcurrent with CDTFA updates, approximately every two weeks, Last Processed: 12/17/2024 by Nick Santos using code path at https://github.com/CDT-ODS-DevSecOps/cdt-ods-gis-city-county/ at commit 0bf269d24464c14c9cf4f7dea876aa562984db63. It incorporates updates from CDTFA as of 12/12/2024. Future updates will include improvements to metadata and update frequency.

  18. F

    Estimate of Median Household Income for Los Angeles County, CA

    • fred.stlouisfed.org
    json
    Updated Dec 20, 2024
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    (2024). Estimate of Median Household Income for Los Angeles County, CA [Dataset]. https://fred.stlouisfed.org/series/MHICA06037A052NCEN
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Dec 20, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Los Angeles County, California
    Description

    Graph and download economic data for Estimate of Median Household Income for Los Angeles County, CA (MHICA06037A052NCEN) from 1989 to 2023 about Los Angeles County, CA; Los Angeles; CA; households; median; income; and USA.

  19. N

    Income Distribution by Quintile: Mean Household Income in Tulare County, CA...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Tulare County, CA // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/tulare-county-ca-median-household-income/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Tulare County, California
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Tulare County, CA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 16,835, while the mean income for the highest quintile (20% of households with the highest income) is 215,779. This indicates that the top earners earn 13 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 356,567, which is 165.25% higher compared to the highest quintile, and 2118.01% higher compared to the lowest quintile.
    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:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

    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 Tulare County median household income. You can refer the same here

  20. d

    TIGER/Line Shapefile, 2019, state, California, Current County Subdivision...

    • catalog.data.gov
    Updated Oct 12, 2021
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    (2021). TIGER/Line Shapefile, 2019, state, California, Current County Subdivision State-based [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2019-state-california-current-county-subdivision-state-based
    Explore at:
    Dataset updated
    Oct 12, 2021
    Description

    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. County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally- recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census, the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions. The boundaries of most legal MCDs are as of January 1, 2019, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CCDs, delineated in 20 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.

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California Energy Commission (2024). California Counties [Dataset]. https://catalog.data.gov/dataset/california-counties-254c9

California Counties

Explore at:
Dataset updated
Nov 27, 2024
Dataset provided by
California Energy Commission
Area covered
California
Description

Counties in California intended for the NEVI Map.Data downloaded in May 2021 from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2021.html#list-tab-VGDZBC72KXZ7CWIQNY.

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