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

About this dataset

Context

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

Key observations

Largest age group (population): Male # 55-59 years (337) | Female # 50-54 years (448). 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 Globe population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Globe is shown in the following column.
• Population (Female): The female population in the Globe 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 Globe 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 Globe Population by Gender. You can refer the same here

The 2015 Global Nutrition Report Dataset contains data for all the indicators that were used in Global Nutrition Report 2015: Actions and Accountability to Advance Nutrition & Sustainable Development. The data are compiled from secondary sources including United Nations Children's Fund (UNICEF), World Health Organization (WHO), and the World Bank (WB) among many others. The dataset broadly contains information on adult and child nutrition, economic demography, nutrition intervention coverage, and policy legislation in the nutrition sector.

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

Hello Everyone!

This dataset contains the information on the percentage of women and men employed in three sectors - agriculture, industry and services. It compares the data between 2015 and 2020. The data is collected for all the countries across the globe.

The data is obtained from the official website of the World Bank and it owns the information. Any credit would go to the World Bank.

Necessary data profiling is performed on this dataset before uploading it in Kaggle.

Note: Some countries may not have the complete information. If you are visualizing the data, I'd advice to filter them out for accurate results.

I developed a Tableau dashboard with this data which can be found in below link. I filtered in only the SAARC countries for my viz.

https://public.tableau.com/app/profile/mohamed.harris7159/viz/FemaleMaleEmploymentBySectors/FemaleandMaleEmploymentbySectors

Series Name: Proportion of women who make their own informed decisions regarding sexual relations (percent of women aged 15-49 years)Series Code: SH_FPL_INFMSRRelease Version: 2020.Q2.G.03This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 5.6.1: Proportion of women aged 15–49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health careTarget 5.6: Ensure universal access to sexual and reproductive health and reproductive rights as agreed in accordance with the Programme of Action of the International Conference on Population and Development and the Beijing Platform for Action and the outcome documents of their review conferencesGoal 5: Achieve gender equality and empower all women and girlsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Global Data: GDP, Life Expectancy & More

This dataset comprises 204 entries and 38 attributes, providing a comprehensive analysis of key economic and social indicators across various countries. It includes a diverse range of metrics, allowing for in-depth exploration of global trends related to GDP, education, health, and environmental factors.

Key Features:

• GDP: Gross Domestic Product (in current US dollars), representing the total economic output of a country.
• Sex Ratio: The ratio of males to females in the population, highlighting demographic trends.
• Life Expectancy: Average lifespan for males and females, an essential indicator of healthcare quality.
• Education Enrollment Rates: Data on primary, secondary, and post-secondary education enrollment for males and females, reflecting educational attainment.
• Unemployment Rate: Percentage of the labor force that is unemployed, indicating economic health.
• Homicide Rate: Number of homicides per 100,000 population, providing insight into safety and crime levels.
• Urban Population Growth: Rate of growth in urban populations, illustrating migration trends.
• CO2 Emissions: Carbon dioxide emissions per capita, an important measure of environmental impact.
• Forested Area: Percentage of land covered by forests, indicating biodiversity and environmental health.
• Tourist Numbers: Total number of international visitors, which can reflect a country's tourism potential.

Applications and Uses:

1. Research and Analysis: Ideal for researchers studying the correlation between economic performance and social indicators. This dataset can help identify trends and patterns relevant to global development.

2. Policy Development: Policymakers can utilize this data to inform decisions on education, healthcare, and environmental policies, aiming to improve national outcomes.

3. Machine Learning and Data Science: Data scientists can apply machine learning techniques to predict economic trends, analyze social impacts, or classify countries based on various indicators.

4. Educational Purposes: Suitable for students and educators in fields like economics, sociology, and environmental science for practical data analysis exercises.

5. Visualization Projects: Perfect for creating compelling visualizations that illustrate relationships between different metrics, aiding in public understanding and engagement.

By leveraging this dataset, users can uncover insights into how different factors influence a country's development, making it a valuable resource for diverse applications across various fields.

Women's Business Centers (WBCs) represent a national network of nearly 100 educational centers throughout the United States and its territories, which are designed to assist women in starting and growing small businesses. WBCs seek to "level the playing field" for women entrepreneurs, who still face unique obstacles in the business world. SBA’s Office of Women’s Business Ownership (OWBO) oversees the WBC network, which provides entrepreneurs (especially women who are economically or socially disadvantaged) comprehensive training and counseling on a variety of topics in several languages

Series Name: Proportion of women aged 20-24 years who were married or in a union before age 15 (percent)Series Code: SP_DYN_MRBF15Release Version: 2020.Q2.G.03This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 5.3.1: Proportion of women aged 20–24 years who were married or in a union before age 15 and before age 18Target 5.3: Eliminate all harmful practices, such as child, early and forced marriage and female genital mutilationGoal 5: Achieve gender equality and empower all women and girlsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

This dataset provides values for RETIREMENT AGE WOMEN reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Context

Women's football is rapidly gaining popularity. More money, more fans, more female players. FIFA plans to increase the number of women playing football by almost 20 times.

And we will be watching the countries compete :)

Content

Base table "fifa_ranking-LASTDATE"

• country_full — country full name
• country_abrv — country abbreviation
• rank — current country rank
• total_points — current total points
• previous_points — total points in last rating
• rank_change — how rank has changed since the last publication
• confederation — FIFA confederations
• rank_date — date of rating calculation

Hint

You will find it interesting to compare the successes of the national teams in men's and women's football. Here is the data with the men's national teams — Men's Ranking

Benin BJ: Women Business and the Law Index Score: scale 1-100 data was reported at 83.750 NA in 2023. This stayed constant from the previous number of 83.750 NA for 2022. Benin BJ: Women Business and the Law Index Score: scale 1-100 data is updated yearly, averaging 40.000 NA from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 83.750 NA in 2023 and a record low of 28.125 NA in 1972. Benin BJ: Women Business and the Law Index Score: scale 1-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Benin – Table BJ.World Bank.WDI: Governance: Policy and Institutions. The index measures how laws and regulations affect women’s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.;World Bank: Women, Business and the Law. https://wbl.worldbank.org/;;1. For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. 2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0. This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.

Series Name: Proportion of women who make their own informed decisions regarding sexual relations contraceptive use and reproductive health care (percent of women aged 15-49 years)Series Code: SH_FPL_INFMRelease Version: 2020.Q2.G.03This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 5.6.1: Proportion of women aged 15–49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health careTarget 5.6: Ensure universal access to sexual and reproductive health and reproductive rights as agreed in accordance with the Programme of Action of the International Conference on Population and Development and the Beijing Platform for Action and the outcome documents of their review conferencesGoal 5: Achieve gender equality and empower all women and girlsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Africa Unmet Need for Contraception Dataset

  Dataset Summary

Annual share of women with unmet need for contraception among married women ages 15–49 for African countries. Data are provided as percentages. Cleaned and reformatted for ML pipelines with Africa-only subsets in long and pivot formats.

Indicator: World Bank — Unmet need for contraception (% of married women ages 15–49) (SP.UWT.TFRT) Geographic scope: 54 African countries (ISO‑3 list consistent across this repo)… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Unmet-need-for-contraception-Percentage-of-married-women-ages-15-49.

Series Name: Proportion of girls and women aged 15-49 years who have undergone female genital mutilation cutting by age (percent)Series Code: SH_STA_FGMSRelease Version: 2020.Q2.G.03This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 5.3.2: Proportion of girls and women aged 15–49 years who have undergone female genital mutilation/cutting, by ageTarget 5.3: Eliminate all harmful practices, such as child, early and forced marriage and female genital mutilationGoal 5: Achieve gender equality and empower all women and girlsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

About this dataset

Context

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

Key observations

There is a slight majority of male population, with 50.58% 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 Blue Earth County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Blue Earth 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 Blue Earth County Population by Race & Ethnicity. You can refer the same here

This table contains 30 series, with data for years 1961 - 1971 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (1 items: Canada ...) Children born to ever-married women (10 items: Number of children born to ever-married women 15 years of age and over; total; Number of children born to ever-married women aged 15-19 years; Number of children born to ever-married women aged 20-24 years; Number of children born to ever-married women aged 25-29 years ...) Type of area (3 items: Total urban and rural areas; Rural; Urban ...).

Africa: Teenage mothers (% of women ages 15–19 who have had children or are currently pregnant)

  Dataset summary

This dataset provides the share of teenage mothers (women ages 15–19 who have had children or are currently pregnant) across African countries, standardized and made ML-ready. Geographic scope: 54 African countries. Temporal coverage: 1960–2024 (annual). Units: Percentage of women 15–19 (%).

  Source & licensing

Source: World Bank – World Development… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Teenage-mothers-percentage-of-women-ages-15-19-who-have-had-children-or-are-currently-pregnant.

'Public Policies and Social Conditions: Monitoring the transition in Central and Eastern Europe and the Commonwealth of Independent States', more commonly known as the MONEE project, was initiated by the UNICEF Innocenti Research Centre in 1992. The project aim was to monitor, analyse and disseminate information on the situation of families in the region as it entered into an era of rapid social, political and economic changes. Today regular updates and dissemination of the data continue to raise awareness of and contribute to the international debate on how economic and social policies impact children, women and families in CEE/CIS.

The percentage of female population (age 25 and over) with at least completed post-secondary education (ISCED 4 or higher). This indicator is calculated by dividing the number of females aged 25 years and above who completed post-secondary education by the total female population of the same age group and multiplying the result by 100. The UNESCO Institute for Statistics (UIS) educational attainment dataset shows the educational composition of the population aged 25 years and above and hence the stock and quality of human capital within a country. The dataset also reflects the structure and performance of the education system and its accumulated impact on human capital formation. For more information, visit the UNESCO Institute for Statistics website: http://www.uis.unesco.org/