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Actual value and historical data chart for World Population Female Percent Of Total
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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 (21) | Female # 40-44 years (15). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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.
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/.
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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Actual value and historical data chart for World Population Female
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United States US: Population: Female: Aged 15-64 data was reported at 106,545,028.000 Person in 2017. This records an increase from the previous number of 106,254,414.000 Person for 2016. United States US: Population: Female: Aged 15-64 data is updated yearly, averaging 81,112,897.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 106,545,028.000 Person in 2017 and a record low of 54,897,168.000 Person in 1960. United States US: Population: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2017 Revision.; Sum; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.
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LivWell is a global longitudinal database which provides a range of key indicators related to women’s socioeconomic status, health and well-being, access to basic services, and demographic outcomes. Data are available at the sub-national level for 52 countries and 447 regions. A total of 134 indicators are based on 199 Demographic and Health Surveys for the period 1990-2019, supplemented by extensive information on socioeconomic and climatic conditions in the respective regions for a total of 190 indicators. The resulting data offer various opportunities for policy-relevant research on gender inequality, inclusive development, and demographic trends at the sub-national level.
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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 # 20-24 years (347) | Female # 50-54 years (433). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
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
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.
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/.
This dataset is a part of the main dataset for Globe Population by Gender. You can refer the same here
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United States US: Population: as % of Total: Female: Aged 65 and Above data was reported at 16.925 % in 2017. This records an increase from the previous number of 16.550 % for 2016. United States US: Population: as % of Total: Female: Aged 65 and Above data is updated yearly, averaging 14.035 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 16.925 % in 2017 and a record low of 10.023 % in 1960. United States US: Population: as % of Total: Female: Aged 65 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population 65 years of age or older as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.
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Germany DE: Population: as % of Total: Female: Aged 15-64 data was reported at 61.528 % in 2023. This records a decrease from the previous number of 61.854 % for 2022. Germany DE: Population: as % of Total: Female: Aged 15-64 data is updated yearly, averaging 64.197 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 67.752 % in 1960 and a record low of 61.528 % in 2023. Germany DE: Population: as % of Total: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.;United Nations Population Division. World Population Prospects: 2024 Revision.;Weighted average;Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.
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TwitterBy Priyanka Dobhal [source]
This dataset contains the rankings of the 2020 Forbes list of 100 most powerful women from around the world. This dataset includes detailed insights on each woman, such as their age, country/territory, category, and designation. This comprehensive ranking celebrates female leaders that are making an impact in their field and around the world while inspiring us to continue striving for gender parity and driving positive social change. Explore this dataset to get an idea of who are some of the top female voices right now at the forefront of progress
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
- Creating personalized stories of each woman to showcase their inspiring accomplishments, achievements and successes.
- Analyzing the age range of female Forbes 100 Power Women list to adjust marketing, staffing, and other outreach initiatives aimed at empowering women globally.
- Developing an interactive map with information about the country/territory of origin for each Forbes Power Woman, with an interactive feature that provides stories from successful women from these countries/territories that can serve as inspiration for other aspiring entrepreneurs
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: Forbes 100 Women List 2020.csv | Column name | Description | |:----------------------|:-------------------------------------------------------------------------------| | Name | Name of the Power Woman. (String) | | Age | Age of the Power Woman. (Integer) | | Country/Territory | Country or territory of origin of the Power Woman. (String) | | Category | Category of the Power Woman's achievements. (String) | | Designation | Designation of the Power Woman. (String) |
If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Priyanka Dobhal.
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This dataset contains all of the data used in the Pudding essay When Women Make Headlines published in January 2022. This dataset was created to analyze gendered language, bias and language themes in news headlines from across the world. It contains headlines from top50 news publications and news agencies from four major countries - USA, UK, India and South Africa - as published by SimilarWeb (as of 2021-06-06).
To collect this data we used RapidAPI's google news API to query headlines containing one or more of keywords selected based on existing research done by Huimin Xu & team and The Swaddle team. We analyzed words used in headlines manually curating two dictionaries — gendered words about women (words that are explicitly gendered) and words that denote societal/behavioral stereotypes about women. To calculate bias scores, we utilized technology developed through Yasmeen Hitti & team’s research on gender bias text analysis. To categorize words used into themes (violence/crime, empowerment, race/ethnicity/identity etc), we manually curated four dictionaries utilizing Natural Language Processing packages for Python like spacy & nltk for our analysis. Plus, inverting polarity scores with vaderSentiment algorithm helped us shed light on differences between women-centered/non-women centered polarity levels as well as differences between global polarity baselines of each country's most visited publications & news agencies according to SimilarWeb 2020 statistics..
This dataset enables journalists, researchers and educators researching issues related to gender equity within media outlets around the world further insights into potential disparities with just a few lines of code! Any discoveries made by using this data should provide valuable support for evidence-based argumentation . Let us advocate for greater awareness towards female representation better quality coverage!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
This dataset provides a comprehensive look at the portrayal of women in headlines from 2010-2020. Using this dataset, researchers and data scientists can explore a range of topics including language used to describe women, bias associated with different topics or publications, and temporal patterns in headlines about women over time.
To use this dataset effectively, it is helpful to understand the structure of the data. The columns include headline_no_site (the text of the headline without any information about which publication it is from), time (the date and time that the article was published), country (the country where it was published), bias score (calculated using Gender Bias Taxonomy V1.0) and year (the year that the article was published).
By exploring these columns individually or combining them into groups such as by publication or by topic, there are many ways to make meaningful discoveries using this data set. For example, one could explore if certain news outlets employ more gender-biased language when writing about female subjects than other outlets or investigate whether female-centric stories have higher/lower bias scores than average for a particular topic across multiple countries over time. This type of analysis helps researchers to gain insight into how our culture's dialogue has evolved over recent years as relates to women in media coverage worldwide
- A comparative, cross-country study of the usage of gendered language and the prevalence of gender bias in headlines to better understand regional differences.
- Creating an interactive visualization showing the evolution of headline bias scores over time with respect to a certain topic or population group (such as women).
- Analyzing how different themes are covered in headlines featuring women compared to those without, such as crime or violence versus empowerment or race and ethnicity, to see if there’s any difference in how they are portrayed by the media
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: headlines_reduced_temporal.csv | Column name | Description | |:---------------------|:-------------------------------------------------------------------------------------...
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TwitterOver the past 24 years, there were constantly more men than women living on the planet. Of the 8.06 billion people living on the Earth in 2024, 4.09 billion were men and 4.05 billion were women. One-quarter of the world's total population in 2024 was below 15 years.
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TwitterThe Second World War had a sever impact on gender ratios across European countries, particularly in the Soviet Union. While the United States had a balanced gender ratio of one man for every woman, in the Soviet Union the ratio was below 5:4 in favor of women, and in Soviet Russia this figure was closer to 4:3.
As young men were disproportionately killed during the war, this had long-term implications for demographic development, where the generation who would have typically started families in the 1940s was severely depleted in many countries.
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TwitterThe Second World War severely altered the demographic composition of many countries, particularly in terms of gender ratios across certain age groups. For age groups below 14 years, there is little observable impact of the war on gender ratios, however, some countries see a drastic change across older generations, particularly in the Soviet Union. For men in their twenties (i.e. those in their late-teens or early-twenties when the war began), the ratio drops from 98 men per 100 women in the 15-19 age group, to 68 men per 100 women in the 25-29 group.
In addition to the Second World War, these figures are affected by trends in nature and other historical events. For example, women tend to have higher overall life expectancies than men, which typically sees gender ratios widen among older generations. The impact of the First World War is also most-observable in France's gender ratios for those aged in their fifties. Additionally, the gap in ratios remains high for the Soviet Union across older age groups due to the impact of the First World War and the famine of the early 1930s, however the figures for Russia itself are even lower as it was disproportionately affected by the Russian Revolution and famine of the 1920s.
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Equatorial Guinea GQ: Population: Female: Aged 0-14 data was reported at 232,832.000 Person in 2017. This records an increase from the previous number of 225,133.000 Person for 2016. Equatorial Guinea GQ: Population: Female: Aged 0-14 data is updated yearly, averaging 86,967.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 232,832.000 Person in 2017 and a record low of 47,298.000 Person in 1978. Equatorial Guinea GQ: Population: Female: Aged 0-14 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Equatorial Guinea – Table GQ.World Bank: Population and Urbanization Statistics. Female population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2017 Revision.; Sum; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.
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TwitterUsers 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.
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Actual value and historical data chart for United States Population Female Percent Of Total
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CONTENT
Gender Inequality Index: A composite measure reflecting inequality in achievement between women and men in three dimensions: reproductive health, empowerment and the labour market. See Technical note 4 at http://hdr.undp.org/sites/default/files/hdr2022_technical_notes.pdf for details on how the Gender Inequality Index is calculated.
Maternal mortality ratio: Number of deaths due to pregnancy-related causes per 100,000 live births.
Adolescent birth rate: Number of births to women ages 15–19 per 1,000 women ages 15–19.
Share of seats in parliament: Proportion of seats held by women in the national parliament expressed as a percentage of total seats For countries with a bicameral legislative system, the share of seats is calculated based on both houses.
Population with at least some secondary education: Percentage of the population ages 25 and older that has reached (but not necessarily completed) a secondary level of education.
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Italy IT: Population: as % of Total: Female: Aged 0-14 data was reported at 12.801 % in 2017. This records a decrease from the previous number of 12.881 % for 2016. Italy IT: Population: as % of Total: Female: Aged 0-14 data is updated yearly, averaging 16.303 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 23.873 % in 1960 and a record low of 12.801 % in 2017. Italy IT: Population: as % of Total: Female: Aged 0-14 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank: Population and Urbanization Statistics. Female population between the ages 0 to 14 as a percentage of the total female population. Population is based on the de facto definition of population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.
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TwitterThis 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.
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.
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Context
The dataset tabulates the population of Blue Earth 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. The dataset can be utilized to understand the population distribution of Blue Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Blue 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 Blue Earth.
Key observations
Largest age group (population): Male # 40-44 years (125) | Female # 85+ years (156). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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
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.
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/.
This dataset is a part of the main dataset for Blue Earth Population by Gender. You can refer the same here
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Actual value and historical data chart for World Population Female Percent Of Total