100+ datasets found
  1. N

    White Earth, ND Population Breakdown by Gender and Age Dataset: Male and...

    • neilsberg.com
    csv, json
    Updated Feb 19, 2024
    + more versions
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    Neilsberg Research (2024). White Earth, ND Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/8e8e96eb-c989-11ee-9145-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 19, 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
    White Earth, North Dakota
    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) 2018-2022 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 White Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for White Earth. The dataset can be utilized to understand the population distribution of White Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in White Earth. 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 White Earth.

    Key observations

    Largest age group (population): Male # 10-14 years (17) | Female # 40-44 years (13). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 White Earth population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the White Earth is shown in the following column.
    • Population (Female): The female population in the White Earth 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 White Earth 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 White Earth Population by Gender. You can refer the same here

  2. N

    Earth, TX Population Breakdown by Gender and Age Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). Earth, TX 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/e1dd3d1f-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
    Texas, Earth
    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 Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Earth. The dataset can be utilized to understand the population distribution of Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Earth. 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 Earth.

    Key observations

    Largest age group (population): Male # 65-69 years (51) | Female # 10-14 years (76). 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 Earth population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the Earth is shown in the following column.
    • Population (Female): The female population in the Earth 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 Earth 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 Earth Population by Gender. You can refer the same here

  3. d

    Gridded Population of the World, Version 4 (GPWv4): Basic Demographic...

    • catalog.data.gov
    • data.nasa.gov
    • +2more
    Updated Aug 23, 2025
    + more versions
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    SEDAC (2025). Gridded Population of the World, Version 4 (GPWv4): Basic Demographic Characteristics, Revision 11 [Dataset]. https://catalog.data.gov/dataset/gridded-population-of-the-world-version-4-gpwv4-basic-demographic-characteristics-revision
    Explore at:
    Dataset updated
    Aug 23, 2025
    Dataset provided by
    SEDAC
    Area covered
    World
    Description

    The Gridded Population of the World, Version 4 (GPWv4): Basic Demographic Characteristics, Revision 11 consists of estimates of human population by age and sex as counts (number of persons per pixel) and densities (number of persons per square kilometer), consistent with national censuses and population registers, for the year 2010. To estimate the male and female populations by age in 2010, the proportions of males and females in each 5-year age group from ages 0-4 to ages 85+ for the given census year were calculated. These proportions were then applied to the 2010 estimates of the total population to obtain 2010 estimates of male and female populations by age. In some cases, the spatial resolution of the age and sex proportions was coarser than the resolution of the total population estimates to which they were applied. The population density rasters were created by dividing the population count rasters by the land area raster. The data files were produced as global rasters at 30 arc-second (~1 km at the equator) resolution. To enable faster global processing, and in support of research commUnities, the 30 arc-second data were aggregated to 2.5 arc-minute, 15 arc-minute, 30 arc-minute and 1 degree resolutions.

  4. N

    International Falls, MN Population Breakdown by Gender and Age Dataset: Male...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). International Falls, MN 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/e1e84768-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
    International Falls, Minnesota
    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 International Falls by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for International Falls. The dataset can be utilized to understand the population distribution of International Falls by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in International Falls. 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 International Falls.

    Key observations

    Largest age group (population): Male # 65-69 years (337) | Female # 40-44 years (306). 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 International Falls population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the International Falls is shown in the following column.
    • Population (Female): The female population in the International Falls 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 International Falls 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 International Falls Population by Gender. You can refer the same here

  5. E

    Estonia EE: Sex Ratio at Birth: Male Births per Female Births

    • ceicdata.com
    Updated Mar 14, 2018
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    CEICdata.com (2018). Estonia EE: Sex Ratio at Birth: Male Births per Female Births [Dataset]. https://www.ceicdata.com/en/estonia/population-and-urbanization-statistics/ee-sex-ratio-at-birth-male-births-per-female-births
    Explore at:
    Dataset updated
    Mar 14, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 1997 - Dec 1, 2016
    Area covered
    Estonia
    Variables measured
    Population
    Description

    Estonia EE: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.060 Ratio in 2017. This records an increase from the previous number of 1.058 Ratio for 2016. Estonia EE: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.058 Ratio from Dec 1962 (Median) to 2017, with 21 observations. The data reached an all-time high of 1.068 Ratio in 1962 and a record low of 1.052 Ratio in 2012. Estonia EE: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Estonia – Table EE.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;

  6. M

    Mexico MX: Sex Ratio at Birth: Male Births per Female Births

    • ceicdata.com
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    CEICdata.com, Mexico MX: Sex Ratio at Birth: Male Births per Female Births [Dataset]. https://www.ceicdata.com/en/mexico/population-and-urbanization-statistics/mx-sex-ratio-at-birth-male-births-per-female-births
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2002 - Dec 1, 2017
    Area covered
    Mexico
    Variables measured
    Population
    Description

    Mexico MX: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.050 Ratio in 2017. This stayed constant from the previous number of 1.050 Ratio for 2016. Mexico MX: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.050 Ratio from Dec 1962 (Median) to 2017, with 21 observations. The data reached an all-time high of 1.050 Ratio in 2017 and a record low of 1.050 Ratio in 2017. Mexico MX: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;

  7. I

    Iceland IS: Sex Ratio at Birth: Male Births per Female Births

    • ceicdata.com
    Updated Jan 15, 2018
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    CEICdata.com (2018). Iceland IS: Sex Ratio at Birth: Male Births per Female Births [Dataset]. https://www.ceicdata.com/en/iceland/population-and-urbanization-statistics/is-sex-ratio-at-birth-male-births-per-female-births
    Explore at:
    Dataset updated
    Jan 15, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 1997 - Dec 1, 2016
    Area covered
    Iceland
    Variables measured
    Population
    Description

    Iceland IS: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.053 Ratio in 2016. This stayed constant from the previous number of 1.053 Ratio for 2015. Iceland IS: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.053 Ratio from Dec 1962 (Median) to 2016, with 20 observations. The data reached an all-time high of 1.066 Ratio in 1972 and a record low of 1.042 Ratio in 1997. Iceland IS: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Iceland – Table IS.World Bank: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;

  8. H

    Mexico - Age and gender structures

    • data.humdata.org
    geotiff
    Updated Aug 26, 2025
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    WorldPop (2025). Mexico - Age and gender structures [Dataset]. https://data.humdata.org/dataset/bbc47914-bb57-4bc4-91bc-33514254b669?force_layout=desktop
    Explore at:
    geotiff(924860606), geotiff(924714292), geotiff(924300023), geotiff(925394647), geotiff(925390641), geotiff(924691730), geotiff(925213420), geotiff(925361285), geotiff(924676413), geotiff(924684406), geotiff(924847968), geotiff(925389829), geotiff(925185864), geotiff(924857284), geotiff(924280482), geotiff(924296945), geotiff(925356121), geotiff(925399201), geotiff(924882829), geotiff(925363348), geotiff(924856714), geotiff(924703947), geotiff(925182086), geotiff(924700552), geotiff(924870928), geotiff(924726361), geotiff(925393360), geotiff(925375285), geotiff(924696293), geotiff(925384443), geotiff(925368944), geotiff(924291673), geotiff(924666551), geotiff(924291622), geotiff(924290587), geotiff(924661594), geotiff(924299727), geotiff(924894867), geotiff(924685587), geotiff(924301963), geotiff(925372124), geotiff(924871240), geotiff(925187322), geotiff(924890407), geotiff(924312040), geotiff(924850860), geotiff(925401039), geotiff(924841936), geotiff(924297321), geotiff(924873447), geotiff(925393895), geotiff(925372514), geotiff(924310768), geotiff(924838264), geotiff(925165882), geotiff(925173103), geotiff(924293976), geotiff(924296924), geotiff(924711389), geotiff(925179932), geotiff(925370029), geotiff(925225472), geotiff(925383113), geotiff(924861951), geotiff(924843902), geotiff(924289166), geotiff(924283247), geotiff(924294137), geotiff(925173820), geotiff(925193470), geotiff(924286742), geotiff(924834873), geotiff(924687508), geotiff(924278886), geotiff(925180647), geotiff(924342231), geotiff(924689453), geotiff(925175966), geotiff(924700324), geotiff(925178904), geotiff(924343918), geotiff(924308937), geotiff(925171876), geotiff(924856268), geotiff(924850203), geotiff(924679789), geotiff(924690434), geotiff(924288990), geotiff(924295622), geotiff(924288642), geotiff(924851848), geotiff(925187709), geotiff(924872704), geotiff(925383782), geotiff(924698935), geotiff(925381501), geotiff(925204457), geotiff(924315602), geotiff(925369736), geotiff(924321181), geotiff(925382867), geotiff(924309802), geotiff(924307669), geotiff(924861026), geotiff(925383068), geotiff(924869084), geotiff(924668718), geotiff(924704950), geotiff(924858805), geotiff(924270189), geotiff(925180814), geotiff(925191904), geotiff(925156454), geotiff(924858406), geotiff(925339827), geotiff(924684702), geotiff(924292400), geotiff(924288058), geotiff(925145566), geotiff(924853232), geotiff(925365250), geotiff(924851312), geotiff(924854374), geotiff(925387607), geotiff(925173594), geotiff(924853328), geotiff(924677384), geotiff(924697913), geotiff(925386256), geotiff(925163001), geotiff(924857454), geotiff(925375687), geotiff(925380009), geotiff(925187243), geotiff(924672198), geotiff(924658222), geotiff(924714956), geotiff(924894055), geotiff(925199109), geotiff(925385293), geotiff(925180327), geotiff(925412310), geotiff(924676403), geotiff(924297352), geotiff(925384153), geotiff(925190629), geotiff(925178614), geotiff(925383631), geotiff(924858613), geotiff(924695461), geotiff(925384267), geotiff(925347225), geotiff(925372338), geotiff(925178661), geotiff(924708277), geotiff(925187285), geotiff(924726495), geotiff(924861587), geotiff(924695978), geotiff(925158638), geotiff(924844017), geotiff(924861008), geotiff(924280504), geotiff(925155663), geotiff(925171265), geotiff(925191475), geotiff(925151597), geotiff(925364601), geotiff(924291382), geotiff(924694239), geotiff(925200137), geotiff(924294219), geotiff(924699159), geotiff(924700115), geotiff(924854029), geotiff(924737120), geotiff(924699971), geotiff(924290576), geotiff(925170485), geotiff(924847193)Available download formats
    Dataset updated
    Aug 26, 2025
    Dataset provided by
    WorldPop
    Area covered
    Mexico
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  9. H

    Slovakia - Age and gender structures

    • data.humdata.org
    geotiff
    Updated Aug 26, 2025
    + more versions
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    WorldPop (2025). Slovakia - Age and gender structures [Dataset]. https://data.humdata.org/dataset/cc69f9e0-1efc-414c-a036-12c36964b3e3?force_layout=desktop
    Explore at:
    geotiff(36492459), geotiff(36397173), geotiff(36475919), geotiff(36491729), geotiff(36396380), geotiff(36476179), geotiff(36520976), geotiff(36475739), geotiff(36476651), geotiff(36492201), geotiff(36521703), geotiff(36475356), geotiff(36521094), geotiff(36520890), geotiff(36492338), geotiff(36397870), geotiff(36435803), geotiff(36475202), geotiff(36396874), geotiff(36436313), geotiff(36436364), geotiff(36490825), geotiff(36492254), geotiff(36478833), geotiff(36477841), geotiff(36435742), geotiff(36436315), geotiff(36394442), geotiff(36489116), geotiff(36492887), geotiff(36522065), geotiff(36522134), geotiff(36492542), geotiff(36494426), geotiff(36519496), geotiff(36396890), geotiff(36522862), geotiff(36435252), geotiff(36434403), geotiff(36477833), geotiff(36479678), geotiff(36398509), geotiff(36435938), geotiff(36397258), geotiff(36522583), geotiff(36521697), geotiff(36397118), geotiff(36436647), geotiff(36521089), geotiff(36492833), geotiff(36435296), geotiff(36434433), geotiff(36477721), geotiff(36492025), geotiff(36493389), geotiff(36394816), geotiff(36437036), geotiff(36475182), geotiff(36492657), geotiff(36395809), geotiff(36520546), geotiff(36493819), geotiff(36435940), geotiff(36489939), geotiff(36476761), geotiff(36492004), geotiff(36396217), geotiff(36520199), geotiff(36522880), geotiff(36521349), geotiff(36395504), geotiff(36395920), geotiff(36477072), geotiff(36519762), geotiff(36476293), geotiff(36476578), geotiff(36493060), geotiff(36492831), geotiff(36476341), geotiff(36476767), geotiff(36435078), geotiff(36397310), geotiff(36478797), geotiff(36493488), geotiff(36520813), geotiff(36398406), geotiff(36521902), geotiff(36478240), geotiff(36396771), geotiff(36490969), geotiff(36476828), geotiff(36435886), geotiff(36433146), geotiff(36478199), geotiff(36495085), geotiff(36396269), geotiff(36474217), geotiff(36437718), geotiff(36520191), geotiff(36521557), geotiff(36435753), geotiff(36522601), geotiff(36521992), geotiff(36522545), geotiff(36394817), geotiff(36491864), geotiff(36395446), geotiff(36437001), geotiff(36398677), geotiff(36492445), geotiff(36435006), geotiff(36432971), geotiff(36478516), geotiff(36433829), geotiff(36436887), geotiff(36475749), geotiff(36480119), geotiff(36476019), geotiff(36492456), geotiff(36395610), geotiff(36521542), geotiff(36520709), geotiff(36475297), geotiff(36521816), geotiff(36493375), geotiff(36492113), geotiff(36396199), geotiff(36435652), geotiff(36396416), geotiff(36437009), geotiff(36492939), geotiff(36434591), geotiff(36395131), geotiff(36437350), geotiff(36477987), geotiff(36520025), geotiff(36399190), geotiff(36520884), geotiff(36396117), geotiff(36521100), geotiff(36519857), geotiff(36520852), geotiff(36434977), geotiff(36434892), geotiff(36395559), geotiff(36436690), geotiff(36476950), geotiff(36519648), geotiff(36438080), geotiff(36489496), geotiff(36473427), geotiff(36395626), geotiff(36492190), geotiff(36477111), geotiff(36475845), geotiff(36437452), geotiff(36492630), geotiff(36477546), geotiff(36435936), geotiff(36495351), geotiff(36434408), geotiff(36395062), geotiff(36434814), geotiff(36494302), geotiff(36490290), geotiff(36476016), geotiff(36475738), geotiff(36521500), geotiff(36398149), geotiff(36490316), geotiff(36397158), geotiff(36400013), geotiff(36398373), geotiff(36396295), geotiff(36436586), geotiff(36492815), geotiff(36520952), geotiff(36397131)Available download formats
    Dataset updated
    Aug 26, 2025
    Dataset provided by
    WorldPop
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  10. N

    Blue Earth County, MN Population Breakdown by Gender and Age Dataset: Male...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). Blue Earth County, MN 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/e1d2e877-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
    Blue Earth County, Minnesota
    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 Blue Earth County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Blue Earth County. The dataset can be utilized to understand the population distribution of Blue Earth County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Blue Earth 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 Blue Earth County.

    Key observations

    Largest age group (population): Male # 20-24 years (5,400) | Female # 20-24 years (5,130). 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 Blue Earth County population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the Blue Earth County is shown in the following column.
    • Population (Female): The female population in the Blue Earth 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 Blue Earth 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 Blue Earth County Population by Gender. You can refer the same here

  11. H

    Japan - Age and gender structures

    • data.humdata.org
    geotiff
    Updated Aug 26, 2025
    + more versions
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    WorldPop (2025). Japan - Age and gender structures [Dataset]. https://data.humdata.org/dataset/153070db-91a1-4ada-9814-463d849855ca?force_layout=desktop
    Explore at:
    geotiff(240637720), geotiff(240628121), geotiff(240625303), geotiff(240628734), geotiff(240940466), geotiff(240945268), geotiff(238392704), geotiff(240941282), geotiff(240941643), geotiff(238430945), geotiff(238396336), geotiff(240628921), geotiff(238422953), geotiff(238437169), geotiff(240944212), geotiff(240625654), geotiff(238443036), geotiff(240943018), geotiff(238755013), geotiff(240947941), geotiff(238408901), geotiff(238748735), geotiff(238781344), geotiff(238399385), geotiff(240636071), geotiff(238778677), geotiff(238439986), geotiff(238426035), geotiff(238428857), geotiff(238753407), geotiff(240946482), geotiff(238399359), geotiff(238437333), geotiff(238440520), geotiff(238389199), geotiff(238765387), geotiff(240629029), geotiff(238755476), geotiff(238783195), geotiff(238763887), geotiff(238415011), geotiff(238408442), geotiff(240627928), geotiff(238414265), geotiff(238404256), geotiff(240628247), geotiff(238398017), geotiff(240955746), geotiff(238766728), geotiff(240628635), geotiff(240938694), geotiff(240947974), geotiff(240629755), geotiff(240948328), geotiff(240647194), geotiff(238753871), geotiff(238411505), geotiff(240944554), geotiff(238778567), geotiff(238434896), geotiff(238447397), geotiff(238763089), geotiff(240623787), geotiff(240633927), geotiff(238427700), geotiff(240632636), geotiff(238766680), geotiff(238428510), geotiff(240618532), geotiff(238758180), geotiff(240941629), geotiff(238766668), geotiff(238765033), geotiff(240941309), geotiff(238439066), geotiff(238407184), geotiff(238409908), geotiff(238444784), geotiff(238442140), geotiff(240627438), geotiff(238423592), geotiff(240944641), geotiff(240943228), geotiff(238411658), geotiff(238769983), geotiff(240942961), geotiff(238759690), geotiff(240631743), geotiff(238393443), geotiff(240621909), geotiff(238423066), geotiff(240629631), geotiff(238750166), geotiff(238413727), geotiff(238446380), geotiff(238440857), geotiff(238443374), geotiff(240948281), geotiff(238442359), geotiff(240641559), geotiff(238449412), geotiff(238749073), geotiff(238388152), geotiff(238413027), geotiff(240949159), geotiff(238437955), geotiff(240619940), geotiff(240627678), geotiff(238760518), geotiff(240961900), geotiff(240636830), geotiff(240626242), geotiff(238757856), geotiff(238758238), geotiff(238417958), geotiff(238393866), geotiff(238403528), geotiff(238389901), geotiff(240951080), geotiff(240636930), geotiff(238440143), geotiff(240629531), geotiff(240947858), geotiff(238394029), geotiff(238441462), geotiff(240628431), geotiff(238405989), geotiff(238777151), geotiff(238760807), geotiff(240625398), geotiff(238417974), geotiff(238447974), geotiff(238395230), geotiff(240622147), geotiff(238752272), geotiff(240952513), geotiff(238776173), geotiff(240631790), geotiff(240941873), geotiff(238435388), geotiff(240632535), geotiff(238438794), geotiff(238401627), geotiff(240946356), geotiff(238752970), geotiff(238437403), geotiff(238447857), geotiff(240952765), geotiff(238431833), geotiff(238444413), geotiff(238451031), geotiff(238766885), geotiff(238411254), geotiff(238429420), geotiff(238415339), geotiff(238447377), geotiff(238398368), geotiff(238752147), geotiff(238449699), geotiff(240947621), geotiff(238387898), geotiff(238764271), geotiff(240938963), geotiff(238757442), geotiff(240958971), geotiff(238414072), geotiff(240628908), geotiff(240944159), geotiff(238763191), geotiff(240946745), geotiff(240941545), geotiff(240940271), geotiff(240630379), geotiff(238413462), geotiff(238769619), geotiff(238747737), geotiff(238434070), geotiff(240940532), geotiff(240947345), geotiff(240623603)Available download formats
    Dataset updated
    Aug 26, 2025
    Dataset provided by
    WorldPop
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  12. E

    Egypt EG: Sex Ratio at Birth: Male Births per Female Births

    • ceicdata.com
    Updated Jun 15, 2020
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    CEICdata.com (2020). Egypt EG: Sex Ratio at Birth: Male Births per Female Births [Dataset]. https://www.ceicdata.com/en/egypt/population-and-urbanization-statistics/eg-sex-ratio-at-birth-male-births-per-female-births
    Explore at:
    Dataset updated
    Jun 15, 2020
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 1997 - Dec 1, 2016
    Area covered
    Egypt
    Variables measured
    Population
    Description

    Egypt EG: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.060 Ratio in 2017. This records a decrease from the previous number of 1.061 Ratio for 2016. Egypt EG: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.061 Ratio from Dec 1962 (Median) to 2017, with 21 observations. The data reached an all-time high of 1.066 Ratio in 2012 and a record low of 1.060 Ratio in 2017. Egypt EG: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Egypt – Table EG.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;

  13. H

    Switzerland - Age and gender structures

    • data.humdata.org
    geotiff
    Updated Aug 26, 2025
    Share
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    WorldPop (2025). Switzerland - Age and gender structures [Dataset]. https://data.humdata.org/dataset/0dc14f55-734d-47e2-88b6-7e97308d8452?force_layout=desktop
    Explore at:
    geotiff(28774080), geotiff(28797742), geotiff(28813491), geotiff(28797110), geotiff(28795525), geotiff(28836688), geotiff(28796662), geotiff(28833004), geotiff(28832833), geotiff(28796647), geotiff(28795152), geotiff(28774650), geotiff(28797978), geotiff(28836404), geotiff(28776610), geotiff(28793763), geotiff(28798361), geotiff(28795748), geotiff(28795361), geotiff(28774639), geotiff(28774642), geotiff(28811912), geotiff(28813736), geotiff(28795671), geotiff(28797215), geotiff(28812283), geotiff(28794854), geotiff(28796119), geotiff(28834824), geotiff(28811118), geotiff(28773444), geotiff(28793604), geotiff(28771177), geotiff(28800003), geotiff(28797385), geotiff(28814330), geotiff(28834289), geotiff(28835378), geotiff(28834056), geotiff(28834200), geotiff(28834257), geotiff(28834600), geotiff(28776257), geotiff(28833281), geotiff(28797030), geotiff(28812070), geotiff(28795090), geotiff(28796166), geotiff(28773390), geotiff(28794594), geotiff(28773665), geotiff(28794257), geotiff(28810016), geotiff(28833732), geotiff(28795099), geotiff(28774098), geotiff(28794117), geotiff(28834847), geotiff(28776467), geotiff(28795712), geotiff(28813450), geotiff(28833250), geotiff(28834280), geotiff(28795384), geotiff(28811375), geotiff(28834260), geotiff(28777232), geotiff(28795331), geotiff(28772101), geotiff(28811598), geotiff(28795416), geotiff(28797258), geotiff(28797833), geotiff(28796954), geotiff(28775015), geotiff(28834584), geotiff(28796406), geotiff(28812175), geotiff(28835860), geotiff(28775299), geotiff(28797686), geotiff(28811589), geotiff(28796226), geotiff(28773346), geotiff(28776713), geotiff(28795809), geotiff(28796703), geotiff(28834538), geotiff(28795922), geotiff(28775247), geotiff(28833188), geotiff(28794343), geotiff(28796904), geotiff(28795189), geotiff(28775975), geotiff(28833585), geotiff(28812864), geotiff(28810468), geotiff(28773130), geotiff(28793303), geotiff(28774276), geotiff(28812551), geotiff(28796383), geotiff(28796396), geotiff(28834606), geotiff(28810932), geotiff(28796453), geotiff(28832921), geotiff(28775160), geotiff(28795791), geotiff(28837155), geotiff(28835842), geotiff(28793268), geotiff(28774399), geotiff(28774105), geotiff(28776429), geotiff(28813245), geotiff(28793167), geotiff(28796368), geotiff(28796628), geotiff(28812597), geotiff(28812990), geotiff(28774874), geotiff(28810789), geotiff(28775606), geotiff(28775512), geotiff(28798951), geotiff(28811766), geotiff(28796275), geotiff(28839475), geotiff(28797685), geotiff(28774055), geotiff(28810609), geotiff(28774130), geotiff(28835709), geotiff(28834570), geotiff(28797213), geotiff(28810797), geotiff(28811506), geotiff(28796556), geotiff(28797548), geotiff(28797457), geotiff(28833107), geotiff(28835999), geotiff(28795264), geotiff(28810723), geotiff(28798118), geotiff(28776031), geotiff(28813367), geotiff(28811248), geotiff(28798402), geotiff(28793782), geotiff(28794679), geotiff(28810773), geotiff(28812142), geotiff(28793107), geotiff(28793662), geotiff(28810862), geotiff(28794375), geotiff(28772590), geotiff(28774751), geotiff(28835712), geotiff(28795103), geotiff(28811459), geotiff(28814232), geotiff(28815067), geotiff(28834012), geotiff(28813389), geotiff(28796037), geotiff(28794098), geotiff(28836858), geotiff(28835977), geotiff(28775544), geotiff(28794046), geotiff(28795957), geotiff(28836577), geotiff(28774997), geotiff(28794106), geotiff(28795517), geotiff(28814280)Available download formats
    Dataset updated
    Aug 26, 2025
    Dataset provided by
    WorldPop
    Area covered
    Switzerland
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  14. g

    Statistics Bureau, Female Population by Age in selected Prefectures, Japan,...

    • geocommons.com
    Updated Jun 25, 2008
    + more versions
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    Burkey (2008). Statistics Bureau, Female Population by Age in selected Prefectures, Japan, 2005 [Dataset]. http://geocommons.com/search.html
    Explore at:
    Dataset updated
    Jun 25, 2008
    Dataset provided by
    Burkey
    Statistics Bureau, Ministry of Internal Affairs and Communications
    Description

    This dataset displays data from the 2005 Census of Japan. It displays female population by age, selected age ranges, percentages of age ranges, average average, and median age in the selected prefectures in Japan for the year 2005. Only 30 of the 47 prectures were displayed in the data source. There are also 2 other datasets that break this data up by total and male figures. This data comes from Japan's Ministry of Internal Affairs and Communication's Statistics Bureau.

  15. A

    Montserrat - Age and sex structures

    • data.amerigeoss.org
    geotiff
    Updated Jun 7, 2022
    Share
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    UN Humanitarian Data Exchange (2022). Montserrat - Age and sex structures [Dataset]. https://data.amerigeoss.org/ro/dataset/edd91b44-9467-42ee-8141-581e7e6b411d
    Explore at:
    geotiffAvailable download formats
    Dataset updated
    Jun 7, 2022
    Dataset provided by
    UN Humanitarian Data Exchange
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  16. N

    Black Earth Town, Wisconsin Population Breakdown by Gender and Age Dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Black Earth Town, Wisconsin 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/e1d29298-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
    Black Earth
    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 Black Earth town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Black Earth town. The dataset can be utilized to understand the population distribution of Black Earth town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Black Earth town. 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 Black Earth town.

    Key observations

    Largest age group (population): Male # 65-69 years (37) | Female # 50-54 years (31). 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 Black Earth town population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the Black Earth town is shown in the following column.
    • Population (Female): The female population in the Black Earth town 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 Black Earth town 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 Black Earth town Population by Gender. You can refer the same here

  17. Italy - Age and sex structures

    • data.amerigeoss.org
    geotiff
    Updated Jun 7, 2022
    + more versions
    Share
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    Cite
    UN Humanitarian Data Exchange (2022). Italy - Age and sex structures [Dataset]. https://data.amerigeoss.org/bg/dataset/worldpop-italy-age-and-sex-structures
    Explore at:
    geotiffAvailable download formats
    Dataset updated
    Jun 7, 2022
    Dataset provided by
    United Nationshttp://un.org/
    Area covered
    Italy
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  18. H

    Uruguay - Age and gender structures

    • data.humdata.org
    geotiff
    Updated Aug 26, 2025
    Share
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    WorldPop (2025). Uruguay - Age and gender structures [Dataset]. https://data.humdata.org/dataset/26817d3b-0018-481b-9122-c0051a1413c1?force_layout=desktop
    Explore at:
    geotiff(103933362), geotiff(104292763), geotiff(104294648), geotiff(103939773), geotiff(103986725), geotiff(103942188), geotiff(103811226), geotiff(103808290), geotiff(103802797), geotiff(103805507), geotiff(103992638), geotiff(103984063), geotiff(104297869), geotiff(103805188), geotiff(104294409), geotiff(103984257), geotiff(103982334), geotiff(103800574), geotiff(104301304), geotiff(103803789), geotiff(103986621), geotiff(104294716), geotiff(103941070), geotiff(103933947), geotiff(103943224), geotiff(103990263), geotiff(103932852), geotiff(103986681), geotiff(103932308), geotiff(103944834), geotiff(103991920), geotiff(103933205), geotiff(103939295), geotiff(103982713), geotiff(103809380), geotiff(104293248), geotiff(103937062), geotiff(104297564), geotiff(103979800), geotiff(104300198), geotiff(104304571), geotiff(103930676), geotiff(103931160), geotiff(103810821), geotiff(103951576), geotiff(103982357), geotiff(103805107), geotiff(103948987), geotiff(104297601), geotiff(104297177), geotiff(103809622), geotiff(104292919), geotiff(103802513), geotiff(103940377), geotiff(104296525), geotiff(104300711), geotiff(103988684), geotiff(103986341), geotiff(103950454), geotiff(103944758), geotiff(103941599), geotiff(103811491), geotiff(104293880), geotiff(103987252), geotiff(103943247), geotiff(104295961), geotiff(103984934), geotiff(103803449), geotiff(103808309), geotiff(103939238), geotiff(103934712), geotiff(103803192), geotiff(103929496), geotiff(103984530), geotiff(103937330), geotiff(103805634), geotiff(104294350), geotiff(103990137), geotiff(103944317), geotiff(103942481), geotiff(104294510), geotiff(104300645), geotiff(103933680), geotiff(103992330), geotiff(103944649), geotiff(104292818), geotiff(103810189), geotiff(103983918), geotiff(104294253), geotiff(103806678), geotiff(104304016), geotiff(104291215), geotiff(103805757), geotiff(103933360), geotiff(103808984), geotiff(104295239), geotiff(103928953), geotiff(103983559), geotiff(103980312), geotiff(103935578), geotiff(103812271), geotiff(103932129), geotiff(103988364), geotiff(103984923), geotiff(104294835), geotiff(103989570), geotiff(103934089), geotiff(103942659), geotiff(103942677), geotiff(104302634), geotiff(103983272), geotiff(103928274), geotiff(103807351), geotiff(103805565), geotiff(103984079), geotiff(103806055), geotiff(103816861), geotiff(104297539), geotiff(103927621), geotiff(103940894), geotiff(103932217), geotiff(103798875), geotiff(103804688), geotiff(104294598), geotiff(104304425), geotiff(103930086), geotiff(103807549), geotiff(103991353), geotiff(103944045), geotiff(104293365), geotiff(103804125), geotiff(103945345), geotiff(103948488), geotiff(103981366), geotiff(103941505), geotiff(103932174), geotiff(103944308), geotiff(103982823), geotiff(103809547), geotiff(103806721), geotiff(103941557), geotiff(103983988), geotiff(104299145), geotiff(103805064), geotiff(103941003), geotiff(103807168), geotiff(103944031), geotiff(103987760), geotiff(103928746), geotiff(103943658), geotiff(103946696), geotiff(104294228), geotiff(103931486), geotiff(103930204), geotiff(103943178), geotiff(103932632), geotiff(104291688), geotiff(103803885), geotiff(103927772), geotiff(104294597), geotiff(103938150), geotiff(103929027), geotiff(103949432), geotiff(103937098), geotiff(103943299), geotiff(103981710), geotiff(103937589), geotiff(103939261), geotiff(103985865), geotiff(103942673), geotiff(103982711), geotiff(103946585), geotiff(103927798), geotiff(103806950), geotiff(103930424), geotiff(104296468), geotiff(103931264), geotiff(103978592), geotiff(103943531), geotiff(103935213)Available download formats
    Dataset updated
    Aug 26, 2025
    Dataset provided by
    WorldPop
    Area covered
    Uruguay
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  19. A

    Togo - Age and sex structures

    • data.amerigeoss.org
    geotiff
    Updated Mar 27, 2025
    Share
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    Click to copy link
    Link copied
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    Cite
    UN Humanitarian Data Exchange (2025). Togo - Age and sex structures [Dataset]. https://data.amerigeoss.org/fr/dataset/dda4ed1f-2bb3-4c1c-b0b0-4e57399fe006
    Explore at:
    geotiffAvailable download formats
    Dataset updated
    Mar 27, 2025
    Dataset provided by
    UN Humanitarian Data Exchange
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  20. Iraq - Age and sex structures

    • data.amerigeoss.org
    geotiff
    Updated Jun 7, 2022
    Share
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    Email
    Click to copy link
    Link copied
    Close
    Cite
    UN Humanitarian Data Exchange (2022). Iraq - Age and sex structures [Dataset]. https://data.amerigeoss.org/id/dataset/worldpop-iraq-age-and-sex-structures
    Explore at:
    geotiffAvailable download formats
    Dataset updated
    Jun 7, 2022
    Dataset provided by
    United Nationshttp://un.org/
    Area covered
    Iraq
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Neilsberg Research (2024). White Earth, ND Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/8e8e96eb-c989-11ee-9145-3860777c1fe6/

White Earth, ND Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2024 Edition

Explore at:
json, csvAvailable download formats
Dataset updated
Feb 19, 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
White Earth, North Dakota
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) 2018-2022 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 White Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for White Earth. The dataset can be utilized to understand the population distribution of White Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in White Earth. 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 White Earth.

Key observations

Largest age group (population): Male # 10-14 years (17) | Female # 40-44 years (13). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 White Earth population analysis. Total expected values are 18 and are define above in the age groups section.
  • Population (Male): The male population in the White Earth is shown in the following column.
  • Population (Female): The female population in the White Earth 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 White Earth 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 White Earth Population by Gender. You can refer the same here

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