100+ datasets found
  1. U.S. employed women 1990-2023

    • statista.com
    • tokrwards.com
    • +1more
    Updated Jul 5, 2024
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    Statista (2024). U.S. employed women 1990-2023 [Dataset]. https://www.statista.com/statistics/192378/number-of-employed-women-in-the-us-since-1990/
    Explore at:
    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, about 75.54 million women were employed in the United States. This is an increase from the previous year, when 74.09 million women were employed, and just about a return to pre-pandemic levels.

  2. U.S. number of full-time employed women 1990-2024

    • statista.com
    • tokrwards.com
    Updated Apr 7, 2025
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    Statista (2025). U.S. number of full-time employed women 1990-2024 [Dataset]. https://www.statista.com/statistics/192354/number-of-full-time-employed-women-in-the-us-since-1990/
    Explore at:
    Dataset updated
    Apr 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2024, about 58.51 million women were employed on a full-time basis in the United States. This is a slight decrease from the previous year when there were only 58.56 million full-time employed women in the U.S.

  3. F

    Infra-Annual Labor Statistics: Working-Age Population Female: From 25 to 54...

    • fred.stlouisfed.org
    json
    Updated Sep 15, 2025
    + more versions
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    (2025). Infra-Annual Labor Statistics: Working-Age Population Female: From 25 to 54 Years for United States [Dataset]. https://fred.stlouisfed.org/series/LFWA25FEUSM647S
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 15, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Female: From 25 to 54 Years for United States (LFWA25FEUSM647S) from Jan 1977 to Aug 2025 about 25 to 54 years, working-age, females, population, and USA.

  4. F

    Labor Force Participation Rate - Women

    • fred.stlouisfed.org
    json
    Updated Sep 5, 2025
    + more versions
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    (2025). Labor Force Participation Rate - Women [Dataset]. https://fred.stlouisfed.org/series/LNU01300002
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 5, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Labor Force Participation Rate - Women (LNU01300002) from Jan 1948 to Aug 2025 about females, participation, civilian, 16 years +, labor force, labor, household survey, rate, and USA.

  5. N

    United States annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). United States annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a53c92b0-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    United States
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in United States. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In United States, the median income for all workers aged 15 years and older, regardless of work hours, was $48,138 for males and $32,546 for females.

    These income figures highlight a substantial gender-based income gap in United States. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the country of United States.

    - Full-time workers, aged 15 years and older: In United States, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,966, while females earned $54,999, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

    Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in United States.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    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 United States median household income by race. You can refer the same here

  6. Share of U.S. women working in professional or managerial occupations 2014,...

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Share of U.S. women working in professional or managerial occupations 2014, by race [Dataset]. https://www.statista.com/statistics/748554/share-of-us-women-working-in-professional-or-managerial-occupations-by-race/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2014
    Area covered
    United States
    Description

    This statistic shows the share of full-time employed women working in professional or managerial occupations in the United States in 2014, by race. In 2014, ** percent of full-time employed black women worked in professional or managerial positions.

  7. p

    Working women's hostels Business Data for United States

    • poidata.io
    csv, json
    Updated Oct 18, 2025
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    Business Data Provider (2025). Working women's hostels Business Data for United States [Dataset]. https://poidata.io/report/working-womens-hostel/united-states
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Oct 18, 2025
    Dataset authored and provided by
    Business Data Provider
    License

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

    Time period covered
    2025
    Area covered
    United States
    Variables measured
    Website URL, Phone Number, Review Count, Business Name, Email Address, Business Hours, Customer Rating, Business Address, Business Categories, Geographic Coordinates
    Description

    Comprehensive dataset containing 54 verified Working women's hostel businesses in United States with complete contact information, ratings, reviews, and location data.

  8. F

    Working-age Population for Women in the United States (DISCONTINUED)

    • fred.stlouisfed.org
    json
    Updated Jun 10, 2013
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    (2013). Working-age Population for Women in the United States (DISCONTINUED) [Dataset]. https://fred.stlouisfed.org/series/USAWFPWNA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 10, 2013
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Working-age Population for Women in the United States (DISCONTINUED) (USAWFPWNA) from 1970 to 2012 about working-age, females, population, and USA.

  9. N

    China, TX annual median income by work experience and sex dataset: Aged 15+,...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). China, TX annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/a50ace5c-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 27, 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, China
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in China. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In China, the median income for all workers aged 15 years and older, regardless of work hours, was $58,750 for males and $30,313 for females.

    These income figures highlight a substantial gender-based income gap in China. Women, regardless of work hours, earn 52 cents for each dollar earned by men. This significant gender pay gap, approximately 48%, underscores concerning gender-based income inequality in the city of China.

    - Full-time workers, aged 15 years and older: In China, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,188, while females earned $69,375

    Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.12 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    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 China median household income by race. You can refer the same here

  10. T

    United States - Self-employed; Female (% Of Females Employed)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 19, 2017
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    TRADING ECONOMICS (2017). United States - Self-employed; Female (% Of Females Employed) [Dataset]. https://tradingeconomics.com/united-states/self-employed-female-percent-of-females-employed-wb-data.html
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Jun 19, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    Self-employed, female (% of female employment) (modeled ILO estimate) in United States was reported at 4.1527 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Self-employed; female (% of females employed) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

  11. N

    Enumclaw, WA annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Enumclaw, WA annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/enumclaw-wa-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    Enumclaw, Washington
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Enumclaw. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Enumclaw, the median income for all workers aged 15 years and older, regardless of work hours, was $74,765 for males and $43,782 for females.

    These income figures highlight a substantial gender-based income gap in Enumclaw. Women, regardless of work hours, earn 59 cents for each dollar earned by men. This significant gender pay gap, approximately 41%, underscores concerning gender-based income inequality in the city of Enumclaw.

    - Full-time workers, aged 15 years and older: In Enumclaw, among full-time, year-round workers aged 15 years and older, males earned a median income of $85,991, while females earned $74,357, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Enumclaw.

    Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Enumclaw.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    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 Enumclaw median household income by race. You can refer the same here

  12. F

    Unemployment Rate - Women

    • fred.stlouisfed.org
    json
    Updated Sep 5, 2025
    + more versions
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    (2025). Unemployment Rate - Women [Dataset]. https://fred.stlouisfed.org/series/LNS14000002
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 5, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Unemployment Rate - Women (LNS14000002) from Jan 1948 to Aug 2025 about females, 16 years +, household survey, unemployment, rate, and USA.

  13. Share of women working in the highest-paying occupations U.S. 2021

    • statista.com
    • thefarmdosupply.com
    Updated Dec 22, 2023
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    Veera Korhonen (2023). Share of women working in the highest-paying occupations U.S. 2021 [Dataset]. https://www.statista.com/study/162228/gender-inequality-in-the-united-states/
    Explore at:
    Dataset updated
    Dec 22, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Veera Korhonen
    Area covered
    United States
    Description

    In 2021, 61 percent of pharmacists in the United States were women, a vast increase from 24 percent in 1980. While women made up only 13 percent of workers in all the highest-paying jobs combined in 1980, this number increased to 35 percent by 2021.

  14. N

    Norway, IA annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Norway, IA annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/norway-ia-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    Iowa, Norway
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Norway. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Norway, the median income for all workers aged 15 years and older, regardless of work hours, was $49,167 for males and $38,750 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 21% between the median incomes of males and females in Norway. With women, regardless of work hours, earning 79 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Norway.

    - Full-time workers, aged 15 years and older: In Norway, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,333, while females earned $38,750, leading to a 39% gender pay gap among full-time workers. This illustrates that women earn 61 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

    Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Norway offers better opportunities for women in non-full-time positions.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    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 Norway median household income by race. You can refer the same here

  15. U

    United States Employment: NF: WW: PB: Professional & Technical

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). United States Employment: NF: WW: PB: Professional & Technical [Dataset]. https://www.ceicdata.com/en/united-states/current-employment-statistics-survey-employment-women-worker-non-farm/employment-nf-ww-pb-professional--technical
    Explore at:
    Dataset updated
    Feb 15, 2025
    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
    Apr 1, 2017 - Mar 1, 2018
    Area covered
    United States
    Variables measured
    Employment
    Description

    United States Employment: NF: WW: PB: Professional & Technical data was reported at 4,240.700 Person th in May 2018. This records a decrease from the previous number of 4,306.800 Person th for Apr 2018. United States Employment: NF: WW: PB: Professional & Technical data is updated monthly, averaging 3,236.300 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 4,306.800 Person th in Apr 2018 and a record low of 2,169.900 Person th in May 1991. United States Employment: NF: WW: PB: Professional & Technical data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G028: Current Employment Statistics Survey: Employment: Women Worker: Non Farm.

  16. y

    US Unemployed Looking for Full-time Work: Women Age 20 and Over

    • ycharts.com
    html
    Updated Sep 5, 2025
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    Bureau of Labor Statistics (2025). US Unemployed Looking for Full-time Work: Women Age 20 and Over [Dataset]. https://ycharts.com/indicators/us_unemployed_looking_for_fulltime_work_women_age_20_and_over_unadjusted
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 5, 2025
    Dataset provided by
    YCharts
    Authors
    Bureau of Labor Statistics
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jan 31, 1963 - Aug 31, 2025
    Area covered
    United States
    Variables measured
    US Unemployed Looking for Full-time Work: Women Age 20 and Over
    Description

    View monthly updates and historical trends for US Unemployed Looking for Full-time Work: Women Age 20 and Over. from United States. Source: Bureau of Labo…

  17. y

    US Unemployed Looking for Full-time Work: Women Age 25 and Over

    • ycharts.com
    html
    Updated Sep 5, 2025
    + more versions
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    Bureau of Labor Statistics (2025). US Unemployed Looking for Full-time Work: Women Age 25 and Over [Dataset]. https://ycharts.com/indicators/us_unemployed_looking_for_fulltime_work_women_age_25_and_over_unadjusted
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 5, 2025
    Dataset provided by
    YCharts
    Authors
    Bureau of Labor Statistics
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jun 30, 1976 - Aug 31, 2025
    Area covered
    United States
    Variables measured
    US Unemployed Looking for Full-time Work: Women Age 25 and Over
    Description

    View monthly updates and historical trends for US Unemployed Looking for Full-time Work: Women Age 25 and Over. from United States. Source: Bureau of Labo…

  18. N

    Edgewater, NJ annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Edgewater, NJ annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/edgewater-nj-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    New Jersey, Edgewater
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Edgewater. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Edgewater, the median income for all workers aged 15 years and older, regardless of work hours, was $111,250 for males and $70,648 for females.

    These income figures highlight a substantial gender-based income gap in Edgewater. Women, regardless of work hours, earn 64 cents for each dollar earned by men. This significant gender pay gap, approximately 36%, underscores concerning gender-based income inequality in the borough of Edgewater.

    - Full-time workers, aged 15 years and older: In Edgewater, among full-time, year-round workers aged 15 years and older, males earned a median income of $127,672, while females earned $103,770, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

    Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Edgewater.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    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 Edgewater median household income by race. You can refer the same here

  19. F

    Infra-Annual Labor Statistics: Employment Rate Female: From 25 to 54 Years...

    • fred.stlouisfed.org
    json
    Updated Sep 15, 2025
    + more versions
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    (2025). Infra-Annual Labor Statistics: Employment Rate Female: From 25 to 54 Years for United States [Dataset]. https://fred.stlouisfed.org/series/LREM25FEUSQ156S
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 15, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Infra-Annual Labor Statistics: Employment Rate Female: From 25 to 54 Years for United States (LREM25FEUSQ156S) from Q1 1977 to Q2 2025 about 25 to 54 years, employment-population ratio, females, population, employment, rate, and USA.

  20. Share of women working in the NFL 2009-2023

    • statista.com
    • tokrwards.com
    Updated Sep 24, 2024
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    Christina Gough (2024). Share of women working in the NFL 2009-2023 [Dataset]. https://www.statista.com/study/81659/women-s-sport-in-the-us/
    Explore at:
    Dataset updated
    Sep 24, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Christina Gough
    Description

    The overall percentage of women employed in the NFL has been increasing in recent years. In 2023, a record high of 42.5 percent of employees in the NFL League Office were female.

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Statista (2024). U.S. employed women 1990-2023 [Dataset]. https://www.statista.com/statistics/192378/number-of-employed-women-in-the-us-since-1990/
Organization logo

U.S. employed women 1990-2023

Explore at:
Dataset updated
Jul 5, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

In 2023, about 75.54 million women were employed in the United States. This is an increase from the previous year, when 74.09 million women were employed, and just about a return to pre-pandemic levels.

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