100+ datasets found
  1. N

    counties in California Ranked by Hispanic Native American Population // 2025...

    • neilsberg.com
    csv, json
    Updated Feb 13, 2025
    + more versions
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    Neilsberg Research (2025). counties in California Ranked by Hispanic Native American Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/counties-in-california-by-hispanic-native-american-population/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 13, 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
    California
    Variables measured
    Hispanic Native American Population, Hispanic Native American Population as Percent of Total Population of counties in California, Hispanic Native American Population as Percent of Total Hispanic Native American Population of California
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.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

    This list ranks the 55 counties in the California by Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each counties over the past five years.

    Content

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

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

    Variables / Data Columns

    • Rank by Hispanic Native American Population: This column displays the rank of counties in the California by their Hispanic American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
    • counties: The counties for which the rank is shown in the previous column.
    • Hispanic Native American Population: The Hispanic Native American population of the counties is shown in this column.
    • % of Total counties Population: This shows what percentage of the total counties population identifies as Hispanic Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total California Hispanic Native American Population: This tells us how much of the entire California Hispanic Native American population lives in that counties. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  2. TIGER/Line Shapefile, 2022, County, Plumas County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Plumas County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-plumas-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Plumas County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  3. TIGER/Line Shapefile, 2022, County, Lassen County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 27, 2024
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Lassen County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-lassen-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Lassen County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  4. TIGER/Line Shapefile, 2022, County, San Benito County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, San Benito County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-san-benito-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    San Benito County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  5. N

    counties in California Ranked by Multi-Racial White Population // 2025...

    • neilsberg.com
    csv, json
    Updated Feb 13, 2025
    + more versions
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    Neilsberg Research (2025). counties in California Ranked by Multi-Racial White Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/counties-in-california-by-multi-racial-white-population/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 13, 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
    California
    Variables measured
    Multi-Racial White Population, Multi-Racial White Population as Percent of Total Population of counties in California, Multi-Racial White Population as Percent of Total Multi-Racial White Population of California
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.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

    This list ranks the 55 counties in the California by Multi-Racial White population, as estimated by the United States Census Bureau. It also highlights population changes in each counties over the past five years.

    Content

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

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

    Variables / Data Columns

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

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  6. N

    counties in California Ranked by Non-Hispanic White Population // 2025...

    • neilsberg.com
    csv, json
    Updated Feb 13, 2025
    Share
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    Neilsberg Research (2025). counties in California Ranked by Non-Hispanic White Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/counties-in-california-by-non-hispanic-white-population/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 13, 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
    California
    Variables measured
    Non-Hispanic White Population, Non-Hispanic White Population as Percent of Total Population of counties in California, Non-Hispanic White Population as Percent of Total Non-Hispanic White Population of California
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.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

    This list ranks the 55 counties in the California by Non-Hispanic White population, as estimated by the United States Census Bureau. It also highlights population changes in each counties over the past five years.

    Content

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

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

    Variables / Data Columns

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

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  7. TIGER/Line Shapefile, 2022, County, Colusa County, CA, Address Range-Feature...

    • catalog.data.gov
    Updated Jan 28, 2024
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Colusa County, CA, Address Range-Feature Name Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-colusa-county-ca-address-range-feature-name-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Colusa County, California
    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 filewith no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independentdata set, or they can be combined to cover the entire nation. The Address Range / Feature Name Relationship File (ADDRFN.dbf) contains a record for each address range / linear feature name relationship. The purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute that can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature name is identified by the linear feature identifier (LINEARID) attribute that can be used to link to the Feature Names Relationship File (FEATNAMES.dbf).

  8. Incarceration rates in selected countries 2025

    • statista.com
    • ai-chatbox.pro
    Updated Feb 20, 2025
    + more versions
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    Statista (2025). Incarceration rates in selected countries 2025 [Dataset]. https://www.statista.com/statistics/262962/countries-with-the-most-prisoners-per-100-000-inhabitants/
    Explore at:
    Dataset updated
    Feb 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    World
    Description

    As of February 2025, El Salvador had the highest prisoner rate worldwide, with over 1,600 prisoners per 100,000 of the national population. Cuba, Rwanda, Turkmenistan, and the United States, rounded out the top five countries with the highest rate of incarceration. Homicides in El Salvador Interestingly, El Salvador, which long had the highest global homicide rates, has dropped out of the top 20 after a high number of gang members have been incarcerated. A high number of the countries with the highest homicide rate are located in Latin America. Prisoners in the United StatesThe United States is home to the largest number of prisoners worldwide. More than 1.8 million people were incarcerated in the U.S. at the beginning of 2025. In China, the estimated prison population totaled 1.69 million people that year. Other nations had far fewer prisoners. The largest share of the U.S. prisoners in federal correctional facilities were of African-American origin. As of 2020, there were 345,500 black, non-Hispanic prisoners, compared to 327,300 white, non-Hispanic inmates. The U.S. states with the largest number of prisoners in 2022 were Texas, California, and Florida. Over 160,000 prisoners in state facilities were sentenced for rape or sexual assault, which was the most common cause of imprisonment. The second most common was murder, followed by aggravated or simple assault.

  9. TIGER/Line Shapefile, 2022, County, Madera County, CA, Feature Names...

    • datasets.ai
    55, 57
    Share
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2022, County, Madera County, CA, Feature Names Relationship File [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2022-county-madera-county-ca-feature-names-relationship-file
    Explore at:
    55, 57Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Madera County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  10. c

    20 Richest Counties in California

    • california-demographics.com
    Updated Jun 20, 2024
    + more versions
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    Kristen Carney (2024). 20 Richest Counties in California [Dataset]. https://www.california-demographics.com/counties_by_population
    Explore at:
    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.

  11. TIGER/Line Shapefile, 2022, County, Nevada County, CA, Feature Names...

    • s.cnmilf.com
    • catalog.data.gov
    Updated Jan 28, 2024
    Share
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Nevada County, CA, Feature Names Relationship File [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2022-county-nevada-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Nevada County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  12. U.S. San Francisco Bay Area GDP by industry 2022

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). U.S. San Francisco Bay Area GDP by industry 2022 [Dataset]. https://www.statista.com/statistics/591696/gdp-of-the-san-francisco-bay-area-by-industry/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    This graph shows the GDP of the San Francisco Bay Area in 2022, by industry. In 2022, the GDP of the San Francisco metro area amounted to about 654.73 billion U.S. dollars. About 68.02 billion U.S. dollars were generated in the manufacturing industries. The overall quarterly GDP growth in the United States can be found here. The San Francisco Bay Area’s GDP The San Francisco Bay Area, commonly known as the Bay Area, is a metropolitan region that surrounds the San Francisco and San Pablo estuaries in Northern California. The region encompasses metropolitan areas such as San Francisco-Oakland (12th largest in the country), San Jose (31st largest in the country), along with smaller urban and rural areas. Overall, the Bay Area consists of nine counties, 101 cities, and 7,000 square miles. The nine counties are Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma. The United States Census Bureau considers the Bay Area a Combined Statistical Area (CSA) with approximately 7.4 million people, including the nine counties bordering San Francisco Bay as well as Santa Cruz and San Benito Counties, making it the sixth largest CSA in the United States.

    In the ten year period between 2001 and 2011, the Bay Area saw its GDP grow considerably. In 2001, GDP was 239 billion U.S. dollars. This value rose to 347 billion U.S. dollars by 2011. Additionally, California ranked first on a list of U.S. states by GDP, with two trillion U.S. dollars of GDP in 2012. Silicon Valley, located in the Bay Area, is in great part responsible for the Bay Area’s and California’s high GDPs, as it is known as the center of the global technology industry. Companies like Google, Facebook, eBay and Apple are headquartered there.

  13. TIGER/Line Shapefile, 2022, County, Yolo County, CA, Feature Names...

    • s.cnmilf.com
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Yolo County, CA, Feature Names Relationship File [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2022-county-yolo-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Yolo County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  14. TIGER/Line Shapefile, 2022, County, Trinity County, CA, Feature Names...

    • catalog.data.gov
    • datasets.ai
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Trinity County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-trinity-county-ca-feature-names-relationship-file
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Trinity County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  15. TIGER/Line Shapefile, 2022, County, Los Angeles County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Los Angeles County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-los-angeles-county-ca-feature-names-relationship-file
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Los Angeles County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  16. TIGER/Line Shapefile, 2022, County, Fresno County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 28, 2024
    + more versions
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Fresno County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-fresno-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Fresno County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  17. N

    counties in California Ranked by Hispanic Other Race Population // 2025...

    • neilsberg.com
    csv, json
    Updated Feb 13, 2025
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    Neilsberg Research (2025). counties in California Ranked by Hispanic Other Race Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/counties-in-california-by-hispanic-other-race-population/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 13, 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
    California
    Variables measured
    Hispanic Other Race Population, Hispanic Other Race Population as Percent of Total Population of counties in California, Hispanic Other Race Population as Percent of Total Hispanic Other Race Population of California
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.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

    This list ranks the 55 counties in the California by Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each counties over the past five years.

    Content

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

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

    Variables / Data Columns

    • Rank by Hispanic Other Race Population: This column displays the rank of counties in the California by their Hispanic Some Other Race (SOR) population, using the most recent ACS data available.
    • counties: The counties for which the rank is shown in the previous column.
    • Hispanic Other Race Population: The Hispanic Other Race population of the counties is shown in this column.
    • % of Total counties Population: This shows what percentage of the total counties population identifies as Hispanic Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total California Hispanic Other Race Population: This tells us how much of the entire California Hispanic Other Race population lives in that counties. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  18. TIGER/Line Shapefile, 2022, County, Butte County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Butte County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-butte-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Butte County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  19. TIGER/Line Shapefile, 2022, County, Napa County, CA, Feature Names...

    • catalog.data.gov
    Updated Jan 27, 2024
    + more versions
    Share
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Napa County, CA, Feature Names Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-napa-county-ca-feature-names-relationship-file
    Explore at:
    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Napa County, California
    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. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

  20. TIGER/Line Shapefile, 2022, County, Plumas County, CA, Address Range-Feature...

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Plumas County, CA, Address Range-Feature Name Relationship File [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-plumas-county-ca-address-range-feature-name-relationship-file
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Plumas County, California
    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 filewith no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independentdata set, or they can be combined to cover the entire nation. The Address Range / Feature Name Relationship File (ADDRFN.dbf) contains a record for each address range / linear feature name relationship. The purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute that can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature name is identified by the linear feature identifier (LINEARID) attribute that can be used to link to the Feature Names Relationship File (FEATNAMES.dbf).

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Neilsberg Research (2025). counties in California Ranked by Hispanic Native American Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/counties-in-california-by-hispanic-native-american-population/

counties in California Ranked by Hispanic Native American Population // 2025 Edition

Explore at:
csv, jsonAvailable download formats
Dataset updated
Feb 13, 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
California
Variables measured
Hispanic Native American Population, Hispanic Native American Population as Percent of Total Population of counties in California, Hispanic Native American Population as Percent of Total Hispanic Native American Population of California
Measurement technique
To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.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

This list ranks the 55 counties in the California by Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each counties over the past five years.

Content

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

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

Variables / Data Columns

  • Rank by Hispanic Native American Population: This column displays the rank of counties in the California by their Hispanic American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
  • counties: The counties for which the rank is shown in the previous column.
  • Hispanic Native American Population: The Hispanic Native American population of the counties is shown in this column.
  • % of Total counties Population: This shows what percentage of the total counties population identifies as Hispanic Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
  • % of Total California Hispanic Native American Population: This tells us how much of the entire California Hispanic Native American population lives in that counties. Please note that the sum of all percentages may not equal one due to rounding of values.
  • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

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