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 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

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.

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.

This dataset is about books. It has 1 row and is filtered where the book is Life in the world of women. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about books. It has 2 rows and is filtered where the book is Women in the First World War. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about books. It has 1 row and is filtered where the book is Women of the land : their story during two world wars. It features 7 columns including author, publication date, language, and book publisher.

Context

This dataset compiles valuable information on how different countries worldwide rank concerning conditions and opportunities for women. It aims to shed light on the status of women's rights and gender equality across the globe, making it a valuable resource for researchers, policymakers, and organizations advocating for gender equality.

Content

This dataset contains three main columns:

1.**Rank:** This column provides the ranking of countries based on their performance or score in terms of conditions and opportunities for women. Rankings range from 1 (indicating the best country for women) to the total number of countries included in the dataset.

2.**Country:** This column lists the names of the countries under evaluation. Each row corresponds to a specific country, allowing users to identify which country the data pertains to. Examples of entries in this column include "United States," "Sweden," "India," and more.

3.**Score:** The "Score" column comprises numerical values or scores reflecting the overall assessment of each country's performance regarding conditions and opportunities for women. These scores are likely calculated based on factors such as gender equality in education, employment, healthcare, political representation, and legal rights. Higher scores generally indicate better conditions for women, while lower scores suggest room for improvement.

Use Cases:

• Researchers can analyze this dataset to identify global trends in gender equality, allowing for cross-country comparisons and the identification of areas where countries excel or need improvement.

• Policymakers can utilize this data to make informed decisions and track progress in achieving gender equality goals.

• Advocacy groups and organizations working on women's rights can leverage this dataset to support their initiatives and promote gender equality on a global scale.

• Data enthusiasts on Kaggle can explore this dataset for data visualization, machine learning, and statistical analysis projects aimed at uncovering insights and trends related to women's well-being and opportunities.

Data Source:

https://ceoworld.biz/2021/06/11/the-worlds-best-countries-for-women-2021/

Acknowledgments:

If applicable, acknowledge any individuals or organizations that contributed to collecting or compiling this dataset.

By publishing this dataset on Kaggle, you are contributing to the open data community and providing a valuable resource for data-driven insights into gender equality worldwide.

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.

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

Context : The ICC Women's T20 World Cup is a (generally) bi-annual cricket tournament for women's international teams. This dataset looks at the editions in 2014, 2016, 2018, 2020 and 2023, in which 10 teams have competed. This dataset contains both match overview data and ball by ball data, as well as a players list.

A handful of matches are missing from the source data (as far as I'm aware, the 2nd, 6th, 9th and 11th games from the 2014 world cup). Runs/Wickets additions contain the wickets taken and runs scored by each player in these missing matches, but this information is not in any of the main files.

Notebooks - To see some charts based on this data go to - Match overview : https://www.kaggle.com/code/acidbear55/women-s-t20-world-cups-data-visualisation - Ball by Ball : https://www.kaggle.com/code/acidbear55/women-s-icc-t20-world-cup-ball-by-ball/notebook

Sources - All this data was taken from https://cricsheet.org/downloads/ , under BY EVENT, and from 'ICC Women's T20 World Cup'. Originally the data came as one json file per match, which has now been combined into a single CSV file.

Python code used to clean and create the csv files can be found at : https://github.com/annaFlett/T20WCData

Any feedback is much appreciated :)

The study used an explanatory sequential mixed method design. This method is appropriate for examining the employment status of STEM graduates in terms of gender as well as the time it takes for graduates to secure their first job after graduating. The method is also employed to look at how staff in higher education supports female graduates in their search for employment after graduation. By design, this study collects data in a sequential fashion, starting with quantitative data and moving on to qualitative data that provide context for the quantitative data.Both primary and secondary sources of data were employed in the study (See Figure A). While information from secondary sources was gathered using Eric, Scopus, and Google search engines, information from primary sources was gathered through questionnaires and interviews. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) was used to conduct the analysis. Using the keywords employment status, duration of job search, and gender-responsive support of higher education, the first 221 articles were collected. Only 15 articles were chosen when PRISMA used the inclusion and exclusion criteria to filter out publications gathered between 2012 and 2024. The information gathered from secondary sources was utilized to triangulate the findings of the primary data sources. The following figure shows the data sources.Figure A: Data sources for the study (see the Description Word Doc. in the dataset)Based on the explanatory sequential mixed method design, quantitative data analysis was first carried out. In order to determine whether there were statistical differences in the employment status and the time it took for male and female STEM engineering graduates to find jobs, the chi square test was employed. An analysis of the degree to which higher education institutions assist female graduates in their job search was also done using an independent samples t-test. The viewpoints of academics from these related universities and prospective employers of STEM graduates were captured through the use of qualitative data.

This dataset is about books. It has 1 row and is filtered where the book is Laboring women : reproduction and gender in New World slavery. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about book series. It has 1 row and is filtered where the books is The religious world of antislavery women : spirituality in the lives of five abolitionist lecturers. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Despite the steady rise in literacy rates over the past 50 years, there are still 750 million illiterate adults around the world, most of whom are women. These numbers produced by the UIS are a stark reminder of the work ahead to meet the Sustainable Development Goals (SDGs), especially Target 4.6 to ensure that all youth and most adults achieve literacy and numeracy by 2030. Current literacy data are generally collected through population censuses or household surveys in which the respondent or head of the household declares whether they can read and write with understanding a short, simple statement about one's everyday life in any written language. Some surveys require respondents to take a quick test in which they are asked to read a simple passage or write a sentence, yet clearly literacy is a far more complex issue that requires more information. For the UIS, the existing dataset serves as a placeholder for a new generation of indicators being developed with countries and partners under the umbrella of the Global Alliance to Monitor Learning (GAML). GAML is developing the methodologies needed to gather more nuanced data and the tools required for their standardisation. In particular, the Alliance is finding ways to link existing large-scale assessments to produce comparable data to monitor the literacy skills of children, youth and adults. This involves close collaboration with a wide range of partners.

Data on female inmates of the Cologne prison ´Klingelpuetz´ 1941-1945. Topics: Date of birth, occupation, detention date, release date, transfering department, offence etc. Daten zu den weibliche Insassen des Kölner Gefängnisses ´Klingelpütz´ 1941-1945. Themen: Geburtsdatum, Beruf, Haftantritts-Datum, Entlassungs-Datum, überweisende Dienststelle, Vergehen u.a.

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

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.

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.

The difference between the earnings of women and men shrank slightly over the past years. Considering the controlled gender pay gap, which measures the median salary for men and women with the same job and qualifications, women earned one U.S. cent less. By comparison, the uncontrolled gender pay gap measures the median salary for all men and all women across all sectors and industries and regardless of location and qualification. In 2025, the uncontrolled gender pay gap in the world stood at 0.83, meaning that women earned 0.83 dollars for every dollar earned by men.