27 datasets found
  1. N

    San Francisco, CA Age Group Population Dataset: A Complete Breakdown of San...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
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    Neilsberg Research (2025). San Francisco, CA Age Group Population Dataset: A Complete Breakdown of San Francisco Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/4544744c-f122-11ef-8c1b-3860777c1fe6/
    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
    San Francisco, 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 San Francisco population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for San Francisco. The dataset can be utilized to understand the population distribution of San Francisco by age. For example, using this dataset, we can identify the largest age group in San Francisco.

    Key observations

    The largest age group in San Francisco, CA was for the group of age 30 to 34 years years with a population of 95,134 (11.38%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in San Francisco, CA was the 80 to 84 years years with a population of 16,047 (1.92%). 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 San Francisco is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of San Francisco 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 San Francisco Population by Age. You can refer the same here

  2. N

    South San Francisco, CA Age Group Population Dataset: A Complete Breakdown...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    Share
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    Neilsberg Research (2025). South San Francisco, CA Age Group Population Dataset: A Complete Breakdown of South San Francisco Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/south-san-francisco-ca-population-by-age/
    Explore at:
    json, csvAvailable 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
    California, South San Francisco
    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 South San Francisco 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 South San Francisco. The dataset can be utilized to understand the population distribution of South San Francisco by age. For example, using this dataset, we can identify the largest age group in South San Francisco.

    Key observations

    The largest age group in South San Francisco, CA was for the group of age 35 to 39 years years with a population of 5,497 (8.52%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in South San Francisco, CA was the 80 to 84 years years with a population of 1,403 (2.18%). 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 South San Francisco is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of South San Francisco 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 South San Francisco Population by Age. You can refer the same here

  3. N

    South San Francisco, CA Population Pyramid Dataset: Age Groups, Male and...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
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    Neilsberg Research (2025). South San Francisco, CA Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/527005f3-f122-11ef-8c1b-3860777c1fe6/
    Explore at:
    json, csvAvailable 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
    California, South San Francisco
    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 South San Francisco, CA population pyramid, which represents the South San Francisco 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 South San Francisco, CA, is 22.1.
    • Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for South San Francisco, CA, is 26.2.
    • Total dependency ratio for South San Francisco, CA is 48.3.
    • Potential support ratio, which is the number of youth (working age population) per elderly, for South San Francisco, CA is 3.8.
    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 South San Francisco population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the South San Francisco for the selected age group is shown in the following column.
    • Population (Female): The female population in the South San Francisco for the selected age group is shown in the following column.
    • Total Population: The total population of the South San Francisco 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 South San Francisco Population by Age. You can refer the same here

  4. N

    San Francisco County, CA Population Breakdown by Gender and Age Dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). San Francisco 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/research/datasets/e1fe177a-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable 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
    San Francisco, 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 San Francisco County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for San Francisco County. The dataset can be utilized to understand the population distribution of San Francisco County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in San Francisco 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 San Francisco County.

    Key observations

    Largest age group (population): Male # 30-34 years (50,273) | Female # 30-34 years (44,861). 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 San Francisco County population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the San Francisco County is shown in the following column.
    • Population (Female): The female population in the San Francisco 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 San Francisco 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 San Francisco County Population by Gender. You can refer the same here

  5. N

    San Francisco Township, Minnesota Age Group Population Dataset: A Complete...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
    Share
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    Neilsberg Research (2025). San Francisco Township, Minnesota Age Group Population Dataset: A Complete Breakdown of San Francisco township Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/san-francisco-township-mn-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
    Minnesota, San Francisco Township
    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 San Francisco township population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for San Francisco township. The dataset can be utilized to understand the population distribution of San Francisco township by age. For example, using this dataset, we can identify the largest age group in San Francisco township.

    Key observations

    The largest age group in San Francisco Township, Minnesota was for the group of age 60 to 64 years years with a population of 115 (12%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in San Francisco Township, Minnesota was the 80 to 84 years years with a population of 5 (0.52%). 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 San Francisco township is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of San Francisco township 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 San Francisco township Population by Age. You can refer the same here

  6. N

    South San Francisco, CA Population Breakdown by Gender and Age Dataset: Male...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
    Share
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    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2025). South San Francisco, CA Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/e201001b-f25d-11ef-8c1b-3860777c1fe6/
    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
    California, South San Francisco
    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 South San Francisco by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for South San Francisco. The dataset can be utilized to understand the population distribution of South San Francisco by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in South San Francisco. 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 South San Francisco.

    Key observations

    Largest age group (population): Male # 35-39 years (3,004) | Female # 55-59 years (2,621). 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 South San Francisco population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the South San Francisco is shown in the following column.
    • Population (Female): The female population in the South San Francisco 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 South San Francisco 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 South San Francisco Population by Gender. You can refer the same here

  7. N

    San Francisco Township, Minnesota Population Pyramid Dataset: Age Groups,...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
    Share
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    Click to copy link
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    Close
    Cite
    Neilsberg Research (2025). San Francisco Township, Minnesota Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/san-francisco-township-mn-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
    Minnesota, San Francisco Township
    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 San Francisco Township, Minnesota population pyramid, which represents the San Francisco township 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 San Francisco Township, Minnesota, is 35.0.
    • Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for San Francisco Township, Minnesota, is 34.3.
    • Total dependency ratio for San Francisco Township, Minnesota is 69.3.
    • Potential support ratio, which is the number of youth (working age population) per elderly, for San Francisco Township, Minnesota is 2.9.
    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 San Francisco township population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the San Francisco township for the selected age group is shown in the following column.
    • Population (Female): The female population in the San Francisco township for the selected age group is shown in the following column.
    • Total Population: The total population of the San Francisco township 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 San Francisco township Population by Age. You can refer the same here

  8. N

    San Francisco Township, Minnesota Population Breakdown by Gender and Age...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). San Francisco Township, Minnesota Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/e1fe17f6-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable 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
    Minnesota, San Francisco Township
    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 San Francisco township by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for San Francisco township. The dataset can be utilized to understand the population distribution of San Francisco township by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in San Francisco township. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for San Francisco township.

    Key observations

    Largest age group (population): Male # 65-69 years (67) | Female # 60-64 years (56). 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 San Francisco township population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the San Francisco township is shown in the following column.
    • Population (Female): The female population in the San Francisco township 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 San Francisco township 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 San Francisco township Population by Gender. You can refer the same here

  9. N

    San Francisco County, CA annual income distribution by work experience and...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). San Francisco County, CA annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/san-francisco-county-ca-income-by-gender/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 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
    San Francisco, California
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    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 portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within San Francisco County. The dataset can be utilized to gain insights into gender-based income distribution within the San Francisco County population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within San Francisco County, among individuals aged 15 years and older with income, there were 350.46 thousand men and 319.41 thousand women in the workforce. Among them, 200,656 men were engaged in full-time, year-round employment, while 158,204 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 3.61% fell within the income range of under $24,999, while 4.78% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 61.29% of men in full-time roles earned incomes exceeding $100,000, while 52.53% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 San Francisco County median household income by race. You can refer the same here

  10. N

    South San Francisco, CA annual income distribution by work experience and...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    Share
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    Neilsberg Research (2025). South San Francisco, CA annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/bac68587-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 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, South San Francisco
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    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 portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within South San Francisco. The dataset can be utilized to gain insights into gender-based income distribution within the South San Francisco population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within South San Francisco, among individuals aged 15 years and older with income, there were 25,031 men and 23,567 women in the workforce. Among them, 14,825 men were engaged in full-time, year-round employment, while 12,636 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 4.47% fell within the income range of under $24,999, while 8.09% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 37.69% of men in full-time roles earned incomes exceeding $100,000, while 35.01% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 South San Francisco median household income by race. You can refer the same here

  11. Decennial Census: Summary File 4

    • s.cnmilf.com
    • catalog.data.gov
    • +1more
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). Decennial Census: Summary File 4 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/decennial-census-summary-file-4
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Summary File 4 is repeated or iterated for the total population and 335 additional population groups: 132 race groups,78 American Indian and Alaska Native tribe categories, 39 Hispanic or Latino groups, and 86 ancestry groups.Tables for any population group excluded from SF 2 because the group's total population in a specific geographic area did not meet the SF 2 threshold of 100 people are excluded from SF 4. Tables in SF 4 shown for any of the above population groups will only be shown if there are at least 50 unweighted sample cases in a specific geographic area. The same 50 unweighted sample cases also applied to ancestry iterations. In an iterated file such as SF 4, the universes households, families, and occupied housing units are classified by the race or ethnic group of the householder. The universe subfamilies is classified by the race or ethnic group of the reference person for the subfamily. In a husband/wife subfamily, the reference person is the husband; in a parent/child subfamily, the reference person is always the parent. The universes population in households, population in families, and population in subfamilies are classified by the race or ethnic group of the inidviduals within the household, family, or subfamily without regard to the race or ethnicity of the householder. Notes follow selected tables to make the classification of the universe clear. In any population table where there is no note, the universe classification is always based on the race or ethnicity of the person. In all housing tables, the universe classification is based on the race or ethnicity of the householder.

  12. N

    San Francisco County, CA annual income distribution by work experience and...

    • neilsberg.com
    csv, json
    Updated Jan 9, 2024
    Share
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    Click to copy link
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    Neilsberg Research (2024). San Francisco County, CA annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2022) [Dataset]. https://www.neilsberg.com/research/datasets/b3d0ff53-abcb-11ee-8b96-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 9, 2024
    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
    San Francisco, California
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within San Francisco County. The dataset can be utilized to gain insights into gender-based income distribution within the San Francisco County population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within San Francisco County, among individuals aged 15 years and older with income, there were 339.20 thousand men and 309.39 thousand women in the workforce. Among them, 199,516 men were engaged in full-time, year-round employment, while 150,495 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 3.51% fell within the income range of under $24,999, while 4.86% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 60.45% of men in full-time roles earned incomes exceeding $100,000, while 51.09% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

    https://i.neilsberg.com/ch/san-francisco-county-ca-income-distribution-by-gender-and-employment-type.jpeg" alt="San Francisco County, CA gender and employment-based income distribution analysis (Ages 15+)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 San Francisco County median household income by gender. You can refer the same here

  13. N

    San Francisco Township, Minnesota annual income distribution by work...

    • neilsberg.com
    csv, json
    Updated Jan 9, 2024
    + more versions
    Share
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    Close
    Cite
    Neilsberg Research (2024). San Francisco Township, Minnesota annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021) [Dataset]. https://www.neilsberg.com/research/datasets/24283288-981b-11ee-99cf-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 9, 2024
    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
    Minnesota, San Francisco Township
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within San Francisco township. The dataset can be utilized to gain insights into gender-based income distribution within the San Francisco township population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within San Francisco township, among individuals aged 15 years and older with income, there were 342 men and 279 women in the workforce. Among them, 228 men were engaged in full-time, year-round employment, while 146 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 5.26% fell within the income range of under $24,999, while 6.16% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 35.96% of men in full-time roles earned incomes exceeding $100,000, while 13.70% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

    https://i.neilsberg.com/ch/san-francisco-township-mn-income-distribution-by-gender-and-employment-type.jpeg" alt="San Francisco Township, Minnesota gender and employment-based income distribution analysis (Ages 15+)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 San Francisco township median household income by gender. You can refer the same here

  14. d

    Travel Decision Survey Data 2012

    • catalog.data.gov
    • data.sfgov.org
    • +3more
    Updated Mar 29, 2025
    + more versions
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    data.sfgov.org (2025). Travel Decision Survey Data 2012 [Dataset]. https://catalog.data.gov/dataset/travel-decision-survey-data-2012
    Explore at:
    Dataset updated
    Mar 29, 2025
    Dataset provided by
    data.sfgov.org
    Description

    This workbook provides data and data dictionaries for the SFMTA 2012 Travel Decision Survey. The 2012 Summary Report, with methodology and survey instrument, is located at https://www.sfmta.com/about-sfmta/reports/travel-decision-survey-2012. Data, methodologies, and summary report for other SFMTA travel decision surveys are available on sfmta.com. On behalf of San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis (CC&G) undertook a Mode Share Survey within the City and County of San Francisco as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma and Solano. The primary goals of this study were to: • Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY2018 with a 95% confidence level and MOE +/- 5% or less. • Evaluate the above statement based on the following parameters: number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. • Provide additional trip details, including trip purpose for each trip in the mode share question series. • Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. • Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs. The survey was conducted as a telephone study among with approximately 750 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, and Cantonese. Surveying was conducted via random digit dial (RDD) and cell phone sample. This dataset incorporates respondent weighting based on age and home location; utilize the “weight” field when appropriate in your analysis. The survey period for this survey is as follows: 2012: October 2012 – January 2013 The margin of error is related to sample size (n). For the total sample, the margin of error is 3.5% for a confidence level of 95%. When looking at subsets of the data, such as just the SF population, just the female population, or just the population of people who bicycle, the sample size decreases and the margin of error increases. Below is a guide of the margin of error for different samples sizes. Be cautious in making conclusions based off of small sample sizes. At the 95% confidence level is: • n = 767 (Total Sample). Margin of error = +/- 3.5% • n = 384. Margin of error = +/- 4.95% • n = 100. Margin of error = +/- 9.80%

  15. Vital Signs: Home Prices – Bay Area

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Aug 21, 2019
    + more versions
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    Zillow (2019). Vital Signs: Home Prices – Bay Area [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Home-Prices-Bay-Area/vnvp-ma92
    Explore at:
    application/rssxml, csv, tsv, json, application/rdfxml, xmlAvailable download formats
    Dataset updated
    Aug 21, 2019
    Dataset authored and provided by
    Zillowhttp://zillow.com/
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR Home Prices (EC7)

    FULL MEASURE NAME Home Prices

    LAST UPDATED August 2019

    DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

    DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

    Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

    CONTACT INFORMATION vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

    For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

    Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

  16. Decennial Census: Summary File 4 Demographic Profile

    • s.cnmilf.com
    • catalog.data.gov
    Updated Jul 19, 2023
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    The citation is currently not available for this dataset.
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Summary File 4 is repeated or iterated for the total population and 335 additional population groups: 132 race groups,78 American Indian and Alaska Native tribe categories, 39 Hispanic or Latino groups, and 86 ancestry groups.Tables for any population group excluded from SF 2 because the group's total population in a specific geographic area did not meet the SF 2 threshold of 100 people are excluded from SF 4. Tables in SF 4 shown for any of the above population groups will only be shown if there are at least 50 unweighted sample cases in a specific geographic area. The same 50 unweighted sample cases also applied to ancestry iterations. In an iterated file such as SF 4, the universes households, families, and occupied housing units are classified by the race or ethnic group of the householder. The universe subfamilies is classified by the race or ethnic group of the reference person for the subfamily. In a husband/wife subfamily, the reference person is the husband; in a parent/child subfamily, the reference person is always the parent. The universes population in households, population in families, and population in subfamilies are classified by the race or ethnic group of the inidviduals within the household, family, or subfamily without regard to the race or ethnicity of the householder. Notes follow selected tables to make the classification of the universe clear. In any population table where there is no note, the universe classification is always based on the race or ethnicity of the person. In all housing tables, the universe classification is based on the race or ethnicity of the householder.

  17. T

    Vital Signs: Housing Permits - by city (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Aug 11, 2022
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    (2022). Vital Signs: Housing Permits - by city (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Housing-Permits-by-city-2022-/5p4w-a7t5
    Explore at:
    application/rdfxml, csv, xml, json, application/rssxml, tsvAvailable download formats
    Dataset updated
    Aug 11, 2022
    Description

    VITAL SIGNS INDICATOR
    Housing Permits (LU3)

    FULL MEASURE NAME
    Permitted housing units

    LAST UPDATED
    February 2023

    DESCRIPTION
    Housing growth is measured in terms of the number of units that local jurisdictions permit throughout a given year. A permitted unit is a unit that a city or county has authorized for construction.

    DATA SOURCE
    California Housing Foundation/Construction Industry Research Board (CIRB) - https://www.cirbreport.org/
    Construction Review report (1967-2022)

    Association of Bay Area Governments (ABAG) – Metropolitan Transportation Commission (MTC) - https://data.bayareametro.gov/Development/HCD-Annual-Progress-Report-Jurisdiction-Summary/nxbj-gfv7
    Housing Permits Database (2014-2021)

    Census Bureau Building Permit Survey - https://www2.census.gov/econ/bps/County/
    Building permits by county (annual, monthly)

    CONTACT INFORMATION
    vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    Bay Area housing permits data by single/multi family come from the California Housing Foundation/Construction Industry Research Board (CIRB). Affordability breakdowns from 2014 to 2021 come from the Association of Bay Area Governments (ABAG) – Metropolitan Transportation Commission (MTC) Housing Permits Database.

    Single-family housing units include detached, semi-detached, row house and town house units. Row houses and town houses are included as single-family units when each unit is separated from the adjacent unit by an unbroken ground-to-roof party or fire wall. Condominiums are included as single-family units when they are of zero-lot-line or zero-property-line construction; when units are separated by an air space; or, when units are separated by an unbroken ground-to-roof party or fire wall. Multi-family housing includes duplexes, three-to-four-unit structures and apartment-type structures with five units or more. Multi-family also includes condominium units in structures of more than one living unit that do not meet the single-family housing definition.

    Each multi-family unit is counted separately even though they may be in the same building. Total units is the sum of single-family and multi-family units. County data is available from 1967 whereas city data is available from 1990. City data is only available for incorporated cities and towns. All permits in unincorporated cities and towns are included under their respective county’s unincorporated total. Permit data is not available for years when the city or town was not incorporated.

    Affordable housing is the total number of permitted units affordable to low and very low income households. Housing affordable to very low income households are households making below 50% of the area median income. Housing affordable to low income households are households making between 50% and 80% of the area median income. Housing affordable to moderate income households are households making below 80% and 120% of the area median income. Housing affordable to above moderate income households are households making above 120% of the area median income.

    Permit data is missing for the following cities and years:
    Clayton, 1990-2007
    Lafayette, 1990-2007
    Moraga, 1990-2007
    Orinda, 1990-2007
    San Ramon, 1990

    Building permit data for metropolitan areas for each year is the sum of non-seasonally adjusted monthly estimates from the Census Building Permit Survey. The Bay Area values are the sum of the San Francisco-Oakland-Hayward MSA and the San Jose-Sunnyvale-Santa Clara MSA. The counties included in these areas are: San Francisco, Marin, Contra Costa, Alameda, San Mateo, Santa Clara, and San Benito.

    Permit values reflect the number of units permitted in each respective year. Note that the data columns come from difference sources. The columns (SFunits, MFunits, TOTALunits, SF_Share and MF_Share) are sourced from CIRB. The columns (VeryLowunits, Lowunits, Moderateunits, AboveModerateunits, VeryLow_Share, Low_Share, Moderate_Share, AboveModerate_Share, Affordableunits and Affordableunits_Share) are sourced from the ABAG Housing Permits Database. Due to the slightly different methodologies that exist within each of those datasets, the total units from each of the two sources might not be consistent with each other.

    As shown, three different data sources are used for this analysis of housing permits issued in the Bay Area. Data from the Construction Industry Research Board (CIRB) represents the best available data source for examining housing permits issued over time in cities and counties across the Bay Area, dating back to 1967. In recent years, Annual Progress Report (APR) data collected by the California Department of Housing and Community Development has been available for analyzing housing permits issued by affordability levels. Since CIRB data is only available for California jurisdictions, the U.S. Census Bureau provides the best data source for comparing housing permits issued across different metropolitan areas. Notably, annual permit totals for the Bay Area differ across these three data sources, reflecting the limitations of needing to use different data sources for different purposes.

  18. g

    Travel Decision Survey Data 2014

    • gimi9.com
    • data.sfgov.org
    • +2more
    Updated Sep 25, 2015
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    (2015). Travel Decision Survey Data 2014 [Dataset]. https://gimi9.com/dataset/data-gov_travel-decision-survey-data-2014/
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    Dataset updated
    Sep 25, 2015
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    This workbook provides data and data dictionaries for the SFMTA 2014 Travel Decision Survey. The 2014 Key Findings, Summary Report, and Methodology, including the survey instrument, can be found online at https://www.sfmta.com/about-sfmta/reports/travel-decision-survey-2014. On behalf of San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis (CC&G) undertook a Mode Share Survey within the City and County of San Francisco as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma and Solano. The primary goals of this study were to: • Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY2018 with a 95% confidence level and MOE +/- 5% or less. • Evaluate the above statement based on the following parameters: number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. • Provide additional trip details, including trip purpose for each trip in the mode share question series. • Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. • Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs. The survey was conducted as a telephone study among with approximately 750 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, and Cantonese. Surveying was conducted via random digit dial (RDD) and cell phone sample. All three survey datasets incorporate respondent weighting based on age and home location; utilize the “weight” field when appropriate in your analysis. The survey period for this survey is as follows: 2014: October – November 2014 A few questions in TDS 2014 were added after the survey began. In the report, responses that did not answer those questions were excluded from the analysis. The questions that were added late are noted in the TDS 2014 methodology survey instrument. The margin of error is related to sample size (n). For the total sample, the margin of error is 3.5% for a confidence level of 95%. When looking at subsets of the data, such as just the SF population, just the female population, or just the population of people who bicycle, the sample size decreases and the margin of error increases. Below is a guide of the margin of error for different samples sizes. Be cautious in making conclusions based off of small sample sizes. At the 95% confidence level is: • n = 767 (Total Sample). Margin of error = +/- 3.5% • n = 384. Margin of error = +/- 4.95% • n = 100. Margin of error = +/- 9.80%

  19. d

    Travel Decision Survey Data 2017

    • catalog.data.gov
    • data.sfgov.org
    • +1more
    Updated Oct 18, 2017
    + more versions
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    data.sfgov.org (2017). Travel Decision Survey Data 2017 [Dataset]. https://catalog.data.gov/is/dataset/travel-decision-survey-data-2017
    Explore at:
    Dataset updated
    Oct 18, 2017
    Dataset provided by
    data.sfgov.org
    Description

    This workbook provides data and data dictionaries for the SFMTA 2017 Travel Decision Survey. On behalf of San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis (CC&G) undertook a Mode Share Survey within the City and County of San Francisco as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma and Solano. The primary goals of this study were to: • Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY2018 with a 95% confidence level and MOE +/- 5% or less. • Evaluate the above statement based on the following parameters: number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. • Provide additional trip details, including trip purpose for each trip in the mode share question series. • Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. • Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs. The survey was conducted as a telephone study among 804 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, Mandarin, Cantonese, and Tagalog. Surveying was conducted via random digit dial (RDD) and cell phone sample. All survey datasets incorporate respondent weighting based on age and home location; utilize the “weight” field when appropriate in your analysis. The survey period for this survey is as follows: 2017: February - April 2017 The margin of error is related to sample size (n). For the total sample, the margin of error is 3.4% for a confidence level of 95%. When looking at subsets of the data, such as just the SF population, just the female population, or just the population of people who bicycle, the sample size decreases and the margin of error increases. Below is a guide of the margin of error for different samples sizes. Be cautious in making conclusions based off of small sample sizes. At the 95% confidence level is: • n = 804(Total Sample). Margin of error = +/- 3.4% • n = 400. Margin of error = +/- 4.85% • n = 100. Margin of error = +/- 9.80%

  20. Decennial Census: Summary File 1

    • catalog.data.gov
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). Decennial Census: Summary File 1 [Dataset]. https://catalog.data.gov/dataset/decennial-census-summary-file-1
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Summary File 1 (SF 1) contains detailed tables focusing on age, sex, households, families, and housing units. These tables provide in-depth figures by race and Hispanic origin> some tables are repeated for each of nine race/Latino groups. Counts also are provided for over forty American Indian and Alaska Native tribes and for groups within race categories. The race categories include eighteen Asian groups and twelve Native Hawaiian and Other Pacific Islander groups. Counts of persons of Hispanic origin by country of origin (twenty-eight groups) are also shown. Summary File 1 presents data for the United States, the 50 states, and the District of Columbia in a hierarchical sequence down to the block level for many tabulations, but only to the census tract level for others. Summaries are included for other geographic areas such as ZIP Code Tabulation Areas (ZCTAs) and Congressional districts. Geographic coverage for Puerto Rico is comparable to the 50 states. Data are presented in a hierarchical sequence down the block level for many tabulations, but only to the census tract level for others. Geographic areas include barrios, barrios-pueblo, subbarrios, places, census tracts, block groups, and blocks. Summaries also are included for other geographic areas such as ZIP Code Tabulation Areas (ZCTAs).

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Neilsberg Research (2025). San Francisco, CA Age Group Population Dataset: A Complete Breakdown of San Francisco Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/4544744c-f122-11ef-8c1b-3860777c1fe6/

San Francisco, CA Age Group Population Dataset: A Complete Breakdown of San Francisco Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition

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
San Francisco, 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 San Francisco population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for San Francisco. The dataset can be utilized to understand the population distribution of San Francisco by age. For example, using this dataset, we can identify the largest age group in San Francisco.

Key observations

The largest age group in San Francisco, CA was for the group of age 30 to 34 years years with a population of 95,134 (11.38%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in San Francisco, CA was the 80 to 84 years years with a population of 16,047 (1.92%). 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 San Francisco is shown in this column.
  • % of Total Population: This column displays the population of each age group as a proportion of San Francisco 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 San Francisco Population by Age. You can refer the same here

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