About this dataset

Context

The dataset tabulates the population of 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 San Francisco. The dataset can be utilized to understand the population distribution of San Francisco by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in 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 San Francisco.

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 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 is shown in the following column.
• Population (Female): The female population in the 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 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 San Francisco Population by Gender. You can refer the same here

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

Pinterest, founded in 2009 and headquartered in San Francisco, California, is an image-oriented social media platform. As of February 2025, 70.3 percent of Pinterest audiences were female and over 22 percent were male. Around 40 percent of Pinterest users, or Pinners, as they are affectionately known, are women aged between 18 and 34 years. The stamp of approval from U.S. consumers Pinterest generally garners a largely favorable user response. July 2023 saw Pinterest score 73 out of a possible 100 points with the American Customer Satisfaction Index (ACSI), surpassing LinkedIn, X (formerly Twitter), Instagram, and Facebook in terms of user approval. Another achievement that puts the service ahead of Facebook, Snapchat, and X is the 23.2 percent year-on-year growth in users in January 2024. What are Pinners searching for? Pinterest is mostly about creative ideas, such as DIY projects, lifestyle ideas, home decor, and recipes. Beauty, travel, wellness, and dating-related terms are topics that users also like to search for. Imaginative hairstyles and hair colors were prominent search terms in 2022, with the term "lavender and pink hair" experiencing a significant year-on-year increase.  In the last few years, interest in train travel and travel photography has also risen on the platform.

Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012, 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File. Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

Sex, length, and mass of adult M. beryllina collected in Suisun Bay, California from 2012-2013. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv acquisition_description=Fish survey data\u00a0were collected by beach seine in the Suisun Bay region of the San Francisco Bay-Delta by Susanne Brander and Bryan Cole. Sampling methodology is fully described in Brander et al. (2013).

Laboratory spawning trials were used to determine the relationship between sex ratio and egg production. Adult inland silversides were placed together in 95 liter circular tanks and allowed to spawn on an artificial spawning substrate (polyester yarn clumps). Substrate was removed daily and inspected for eggs; fertilization was determined by coloration. Full details are provided in White et al. (2017). awards_0_award_nid=542383 awards_0_award_number=OCE-1435473 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=1435473 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 cdm_data_type=Other comment=Sex, ID, and mass of fish in trials J. W. White and S. Brander, PIs Version 4 August 2017 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.713206.1 infoUrl=https://www.bco-dmo.org/dataset/713206 institution=BCO-DMO instruments_0_acronym=Purse-seine instruments_0_dataset_instrument_description=Used to collect samples instruments_0_dataset_instrument_nid=713214 instruments_0_description=A purse seine is a large wall of netting deployed in a circle around an entire school of fish. The seine has floats along the top line with a lead line of chain along the bottom. Once a school of fish is located, a skiff pulls the seine into the water as the vessel encircles the school with the net. A cable running along the bottom is then pulled in, "pursing" the net closed on the bottom, preventing fish from escaping by swimming downward. The catch is harvested by bringing the net alongside the vessel and brailing the fish aboard. instruments_0_instrument_name=Purse-seine Fishing Gear instruments_0_instrument_nid=675173 instruments_0_supplied_name=Beach seine metadata_source=https://www.bco-dmo.org/api/dataset/713206 param_mapping={'713206': {}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/713206/parameters people_0_affiliation=University of North Carolina - Wilmington people_0_affiliation_acronym=UNC-Wilmington people_0_person_name=J Wilson White people_0_person_nid=516429 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=University of North Carolina - Wilmington people_1_affiliation_acronym=UNC-Wilmington people_1_person_name=Dr Susanne Brander people_1_person_nid=712930 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=University of North Carolina - Wilmington people_2_affiliation_acronym=UNC-Wilmington people_2_person_name=J Wilson White people_2_person_nid=516429 people_2_role=Contact people_2_role_type=related people_3_affiliation=Woods Hole Oceanographic Institution people_3_affiliation_acronym=WHOI BCO-DMO people_3_person_name=Hannah Ake people_3_person_nid=650173 people_3_role=BCO-DMO Data Manager people_3_role_type=related project=Goby size-selection projects_0_acronym=Goby size-selection projects_0_description=Description from NSF award abstract: Many marine fish species change sex during their lifetimes, and many of them are targets of commercial and recreational fishing. The timing of sex change in these animals is often related to body size, so populations typically consist of many small fish of the initial sex (usually female) and few large fish of the other sex (usually male). In nature, smaller fish are at a greater risk of mortality due to predation, but fishermen tend to seek larger fish. Thus fishing that targets larger individuals may skew sex ratios, removing enough of the larger sex to hinder reproduction. However, the extent to which size-selective mortality affects sex-changing fishes is poorly understood. This research will explore the effects of size-selective mortality on the population dynamics of sex-changing species using an integrated set of field experiments and mathematical models. It will provide the first experimental exploration of the sensitivity of different sex-change patterns and reproductive strategies to selective mortality. The results will advance our knowledge of the susceptibility and resilience of sex-changing organisms to different types of size-selective mortality and will reveal how sex-changing species can recover after size-selection ceases, as in populations within marine reserves where fishing is suddenly prohibited. The findings will inform fisheries management policies, which do not currently consider the ability of a species to change sex in setting fisheries regulations. This project will consist of a three-year study of the effects of size-specific mortality on sex-changing fishes. Field experiments will use three closely related rocky-reef fishes that differ in sex-change pattern and are amenable to field manipulation and direct measurement of reproductive output. The species include a protogynous hermaphrodite (a female-to-male sex-change pattern common among harvested species) and two simultaneous hermaphrodites that differ in their ability to switch between male and female. Two types of experiments will be conducted on populations established on replicate patch reefs at Santa Catalina Island, California: (1) sex ratios will be manipulated to determine when the scarcity of males limits population-level reproductive output; and (2) experiments cross-factoring the intensity of mortality with the form of size-selection (i.e., higher mortality of large or small individuals) will test the demographic consequences of size-selective mortality. In concert with the field experiments, size- and sex-structured population models (integral projection models) will be developed for use in three ways: (1) to evaluate how different types of selective mortality should affect population dynamics; (2) to predict outcomes of the field experiments, testing/validating the model and allowing direct prediction of the ecological significance of short-term selection; and (3) to fit to existing survey data for a fourth species, a widely fished, sex-changing fish, inside and outside of marine reserves. Part (3) will evaluate whether and how quickly the mating system and reproductive output of that species (not directly measurable in the field) is recovering inside reserves. This integrated set of field experiments and models will yield novel insight into the effects of size-selective mortality on the population dynamics of sex-changing marine species. projects_0_end_date=2018-02 projects_0_geolocation=Southern California, Santa Catalina Island projects_0_name=Impacts of size-selective mortality on sex-changing fishes projects_0_project_nid=516431 projects_0_start_date=2015-03 sourceUrl=(local files) standard_name_vocabulary=CF Standard Name Table v55 version=1 xml_source=osprey2erddap.update_xml() v1.3

Rate of deaths by age/gender (per 100,000 population) for motor vehicle occupants killed in crashes, 2012 & 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Safety Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

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

About this dataset

Context

The dataset tabulates the population of San Francisco township by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of San Francisco township across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 53.44% of total population being male. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the San Francisco township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender 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 Race & Ethnicity. You can refer the same here

Identifications of M. beryllina individuals collected in Suisun Bay, California and used in trials for spawning experiments conducted from 2012 to 2013. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv acquisition_description=Fish survey data\u00a0were collected by beach seine in the Suisun Bay region of the San Francisco Bay-Delta by Susanne Brander and Bryan Cole. Sampling methodology is fully described in Brander et al. (2013).

Laboratory spawning trials were used to determine the relationship between sex ratio and egg production. Adult inland silversides were placed together in 95 liter circular tanks and allowed to spawn on an artificial spawning substrate (polyester yarn clumps). Substrate was removed daily and inspected for eggs; fertilization was determined by coloration. Full details are provided in White et al. (2017). awards_0_award_nid=542383 awards_0_award_number=OCE-1435473 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=1435473 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 cdm_data_type=Other comment=Fish IDs that were used in each trial replicate J. W. White and S. Brander, PIs Version 4 August 2017 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.713225.1 infoUrl=https://www.bco-dmo.org/dataset/713225 institution=BCO-DMO instruments_0_acronym=Purse-seine instruments_0_dataset_instrument_description=Used to collect samples instruments_0_dataset_instrument_nid=713233 instruments_0_description=A purse seine is a large wall of netting deployed in a circle around an entire school of fish. The seine has floats along the top line with a lead line of chain along the bottom. Once a school of fish is located, a skiff pulls the seine into the water as the vessel encircles the school with the net. A cable running along the bottom is then pulled in, "pursing" the net closed on the bottom, preventing fish from escaping by swimming downward. The catch is harvested by bringing the net alongside the vessel and brailing the fish aboard. instruments_0_instrument_name=Purse-seine Fishing Gear instruments_0_instrument_nid=675173 instruments_0_supplied_name=Beach seine metadata_source=https://www.bco-dmo.org/api/dataset/713225 param_mapping={'713225': {}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/713225/parameters people_0_affiliation=University of North Carolina - Wilmington people_0_affiliation_acronym=UNC-Wilmington people_0_person_name=J Wilson White people_0_person_nid=516429 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=University of North Carolina - Wilmington people_1_affiliation_acronym=UNC-Wilmington people_1_person_name=Dr Susanne Brander people_1_person_nid=712930 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=University of North Carolina - Wilmington people_2_affiliation_acronym=UNC-Wilmington people_2_person_name=J Wilson White people_2_person_nid=516429 people_2_role=Contact people_2_role_type=related people_3_affiliation=Woods Hole Oceanographic Institution people_3_affiliation_acronym=WHOI BCO-DMO people_3_person_name=Hannah Ake people_3_person_nid=650173 people_3_role=BCO-DMO Data Manager people_3_role_type=related project=Goby size-selection projects_0_acronym=Goby size-selection projects_0_description=Description from NSF award abstract: Many marine fish species change sex during their lifetimes, and many of them are targets of commercial and recreational fishing. The timing of sex change in these animals is often related to body size, so populations typically consist of many small fish of the initial sex (usually female) and few large fish of the other sex (usually male). In nature, smaller fish are at a greater risk of mortality due to predation, but fishermen tend to seek larger fish. Thus fishing that targets larger individuals may skew sex ratios, removing enough of the larger sex to hinder reproduction. However, the extent to which size-selective mortality affects sex-changing fishes is poorly understood. This research will explore the effects of size-selective mortality on the population dynamics of sex-changing species using an integrated set of field experiments and mathematical models. It will provide the first experimental exploration of the sensitivity of different sex-change patterns and reproductive strategies to selective mortality. The results will advance our knowledge of the susceptibility and resilience of sex-changing organisms to different types of size-selective mortality and will reveal how sex-changing species can recover after size-selection ceases, as in populations within marine reserves where fishing is suddenly prohibited. The findings will inform fisheries management policies, which do not currently consider the ability of a species to change sex in setting fisheries regulations. This project will consist of a three-year study of the effects of size-specific mortality on sex-changing fishes. Field experiments will use three closely related rocky-reef fishes that differ in sex-change pattern and are amenable to field manipulation and direct measurement of reproductive output. The species include a protogynous hermaphrodite (a female-to-male sex-change pattern common among harvested species) and two simultaneous hermaphrodites that differ in their ability to switch between male and female. Two types of experiments will be conducted on populations established on replicate patch reefs at Santa Catalina Island, California: (1) sex ratios will be manipulated to determine when the scarcity of males limits population-level reproductive output; and (2) experiments cross-factoring the intensity of mortality with the form of size-selection (i.e., higher mortality of large or small individuals) will test the demographic consequences of size-selective mortality. In concert with the field experiments, size- and sex-structured population models (integral projection models) will be developed for use in three ways: (1) to evaluate how different types of selective mortality should affect population dynamics; (2) to predict outcomes of the field experiments, testing/validating the model and allowing direct prediction of the ecological significance of short-term selection; and (3) to fit to existing survey data for a fourth species, a widely fished, sex-changing fish, inside and outside of marine reserves. Part (3) will evaluate whether and how quickly the mating system and reproductive output of that species (not directly measurable in the field) is recovering inside reserves. This integrated set of field experiments and models will yield novel insight into the effects of size-selective mortality on the population dynamics of sex-changing marine species. projects_0_end_date=2018-02 projects_0_geolocation=Southern California, Santa Catalina Island projects_0_name=Impacts of size-selective mortality on sex-changing fishes projects_0_project_nid=516431 projects_0_start_date=2015-03 sourceUrl=(local files) standard_name_vocabulary=CF Standard Name Table v55 version=1 xml_source=osprey2erddap.update_xml() v1.3

About this dataset

Context

The dataset tabulates the data for the San Francisco, CA population pyramid, which represents the 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 San Francisco, CA, is 16.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for San Francisco, CA, is 24.1.
• Total dependency ratio for San Francisco, CA is 40.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for San Francisco, CA is 4.1.

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 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 for the selected age group is shown in the following column.
• Population (Female): The female population in the San Francisco for the selected age group is shown in the following column.
• Total Population: The total population of the 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 San Francisco Population by Age. You can refer the same here

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

About this dataset

Context

The dataset tabulates the population of San Francisco County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of San Francisco County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 51.4% of total population being male. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the San Francisco County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of San Francisco County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for San Francisco County Population by Race & Ethnicity. You can refer the same here

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