There was not a single industry where women earned more than men on average in Russia in 2021. For example, in the mineral resources extraction sector, the average wage of men was nearly **** thousand Russian rubles per month, compared to **** thousand Russian rubles of women. The lowest difference between male and female average monthly wages was recorded in the education sector, at *** Russian rubles. In the information and communication industry, men earned roughly **** thousand Russian rubles per month more than women.

Employees in the private sector in Denmark generally earn a higher average monthly salary than employees belonging to the public sector. In 2021, men in the private sector earned around 47,800 Danish kroner on average, while women in the private sector earned 42,400 kroner on average. Men also earned a higher monthly salary than women in the public sector that year. The highest average earnings in Denmark are found in the financial and insurance industry.

Throughout the displayed period, the average monthly income among the Peruvian population has consistently been significantly higher for males compared to females. This income disparity between genders has persisted across all the years, accompanied by an upward trend until 2020.

Average and median gender pay ratio in annual employment income and in annual wages, salaries and commissions. Data are available by National Occupational Classification (NOC) and age group.

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 Jamaica. 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Jamaica, the median income for all workers aged 15 years and older, regardless of work hours, was $35,805 for males and $30,625 for females.

Based on these incomes, we observe a gender gap percentage of approximately 14%, indicating a significant disparity between the median incomes of males and females in Jamaica. Women, regardless of work hours, still earn 86 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

- Full-time workers, aged 15 years and older: In Jamaica, among full-time, year-round workers aged 15 years and older, males earned a median income of $41,885, while females earned $52,019

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.24 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.

https://i.neilsberg.com/ch/jamaica-ia-income-by-gender.jpeg" alt="Jamaica, IA gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022
• 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 Jamaica median household income by gender. You can refer the same here

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 Normal. 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 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Normal, the median income for all workers aged 15 years and older, regardless of work hours, was $40,786 for males and $24,067 for females.

These income figures highlight a substantial gender-based income gap in Normal. 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 town of Normal.

- Full-time workers, aged 15 years and older: In Normal, among full-time, year-round workers aged 15 years and older, males earned a median income of $70,229, while females earned $57,535, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 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 Normal.

https://i.neilsberg.com/ch/normal-il-income-by-gender.jpeg" alt="Normal, IL gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022
• 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 Normal median household income by gender. You can refer the same here

Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2024 about personal income, personal, median, income, real, and USA.

Belgium Average Monthly Salary: Female data was reported at 3,869.000 EUR in 2021. This records an increase from the previous number of 3,821.000 EUR for 2020. Belgium Average Monthly Salary: Female data is updated yearly, averaging 2,863.000 EUR from Sep 1999 (Median) to 2021, with 23 observations. The data reached an all-time high of 3,869.000 EUR in 2021 and a record low of 1,907.000 EUR in 1999. Belgium Average Monthly Salary: Female data remains active status in CEIC and is reported by Directorate-General Statistics - Statistics Belgium. The data is categorized under Global Database’s Belgium – Table BE.G036: Average Monthly Salary.

AMI: Female: Thanh Hoa data was reported at 5,617.000 VND th in 2021. This records a decrease from the previous number of 5,631.000 VND th for 2020. AMI: Female: Thanh Hoa data is updated yearly, averaging 4,351.000 VND th from Dec 2011 (Median) to 2021, with 11 observations. The data reached an all-time high of 5,631.000 VND th in 2020 and a record low of 2,868.000 VND th in 2011. AMI: Female: Thanh Hoa data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G053: Average Monthly Income: Wage Workers: By Provinces: Annual.

Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap as of 31 March 2017. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

You can also:

• https://gender-pay-gap.service.gov.uk/Viewing/search-results?t=1&search=&orderBy=relevance">explore this data on a dashboard
• https://data.gov.uk/dataset/54219db1-dd98-49d9-a383-a5978bb0aeb9/gender-pay-gap">export all national gender pay gap data

Wages in Ukraine decreased to 14577 UAH/Month in January from 17453 UAH/Month in December of 2021. This dataset provides - Ukraine Average Monthly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Saudi Arabia Average Monthly Wages: Saudi data was reported at 10,016.900 SAR in Dec 2023. This records an increase from the previous number of 9,857.100 SAR for Sep 2023. Saudi Arabia Average Monthly Wages: Saudi data is updated quarterly, averaging 10,185.550 SAR from Jun 2016 (Median) to Dec 2023, with 31 observations. The data reached an all-time high of 10,599.879 SAR in Mar 2021 and a record low of 9,583.100 SAR in Sep 2022. Saudi Arabia Average Monthly Wages: Saudi data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.G026: Average Monthly Wages (Discontinued).

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

Between March and May 2025, the average income for women working in Lima, Peru amounted to around 1,794.6 Peruvian soles per month. In turn, the average monthly income for men stood at 2,448.7 Peruvian soles, about 654.1 soles more than women. Average salaries in Lima, Peru According to the employment survey carried out by Peru's National Statistics Institute (INEI, for its acronym in Spanish), the average income of legal workers based in the Peruvian capital does not only vary by gender but also among different age groups and economic sectors. For instance, an employee aged 45 or more can earn around 66 percent more a worker who is up to 24 years old. In turn, service sector workers have higher monthly salaries than employees in manufacture or retail. Employment in Peru More than half the working population in Peru is considered self-employed, one of the highest shares in Latin America. Even though Peru's unemployment rate has remained below four percent since 2009 (except for 2020 and 2021, due to the COVID-19 pandemic), the share of people out of employment in Lima was considerably higher than the national average.

Austria Average Annual Income: Gross: Employees: Women data was reported at 29,831.000 EUR in 2022. This records an increase from the previous number of 28,545.000 EUR for 2021. Austria Average Annual Income: Gross: Employees: Women data is updated yearly, averaging 21,525.000 EUR from Dec 1997 (Median) to 2022, with 26 observations. The data reached an all-time high of 29,831.000 EUR in 2022 and a record low of 16,284.000 EUR in 1997. Austria Average Annual Income: Gross: Employees: Women data remains active status in CEIC and is reported by Statistics Austria. The data is categorized under Global Database’s Austria – Table AT.G023: Average Annual Income.

Data Series: Average hourly earnings of employees by sex and occupation (local currency) Indicator: I.13 - Gender gap in wages, by occupation, age and persons with disabilities Source year: 2021 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

Salary by Profession and Country Over Time

Salary Differences by Country and Profession

By Kelly Garrett [source]

About this dataset

This dataset contains survey responses from 882 data professionals from 46 countries who took part in the 2021 Global Data Professional Salary Survey. Our goal was to understand how much database administrators, data analysts, data architects, developers and data scientists make across the world in 2017-2021.

The survey covers three years of salary trends, allowing you to compare and contrast movements over time. It also includes an optional postal code field which can be used to identify global regions with specific salary trends. In addition, all questions asked this year were also asked in 2017 and 2018 so that you can easily track changes in compensation over three years.

The spreadsheet contains anonymized responses which are provided as public domain making it available for any purpose without attribution or mention of anyone else. With this dataset at your disposal you'll have access to the detailed salary information needed to make informed decisions about your career development!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

• Start by familiarizing yourself with the columns in this dataset. The columns range from age of respondent to country of residence. It also includes salary information for each year (average annual income for 2017, 2018, and 2019). Read through each column header carefully to understand what you're looking at.

• Explore some basic summary statistics about the sample group such as median salary levels by profession or average age by nationality are interesting ways to get acquainted with this data set quickly. Excel's native statistical tools may be used here if you're using an excel file version as your source material; otherwise, you can use any programming language or statistics software that supports importing an exportable CSV (Comma Separated Values) format file or conversion thereof into something manipulable form like a spreadsheet or table structure within your preferred platform..

• You'll then want to identify which factors might be influencing salaries such as experience level, gender and geographical location etc., and attempt some correlation testing between those features against salaries across different job roles or countries over time - where possible without having external datasets available terms of area data points matching up perfectly between thematic dimensions presented within the Respondents' Survey Results tab.. Subsets may also prove relevant when carrying out deeper statistical testing—for example isolating particular participation sets like Ireland alone versus looking at just Europe/Middle East/Africa region altogether..

• Finally look at how these factors have changed over time - it's worth bearing in mind that seasonality might play a role here too depending on where respondents originally reside so it could still be relevant if larger trends towards comparing yearly cohorts differs more widely than expected based purely national economic condition context changes during particular quarters throughout those periods tracked in our findings report � comparison purposes if looking country-by-country instead just individual profiles without taking overall stimulant effects into account e.g higher education qualifications among ~2 yr cohorts vs ~3 yr ones across different populations: Comparing annual amounts doled out employers making ultra-quick transitioning easier tracking changes alone isn't feasible because they're normalized

Research Ideas

• Analyzing regional salary gaps amongst data professionals within the same country, or between countries.
• Evaluating trends in salary rates over time by reviewing changes in year over year responses.
• Generating employer profiles by comparing the salary range of employees at different organizations and industries, as well storing demographic info of individuals who participated in the survey (i.e age range, gender etc)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: 2019_Data_Professional_Salary_Survey_Responses.csv

File: Data_Professional_Salary_Survey_Responses.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Kelly Garrett.

Gender pay gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap annually. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

Gender Pay Gap legislation introduced in April 2017 requires all employers of 250 or more employees to publish their gender pay gap annually. The gender pay gap is the difference between the average earnings of men and women, expressed relative to men’s earnings.

Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CES0500000003) from Mar 2006 to Sep 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.