Luxembourg had the highest average monthly salary of employees in the world in 2024 in terms of purchasing power parities (PPP), which takes the average cost of living in a country into account. Belgium followed in second, with the Netherlands in third.

The "**Salary Data Worldwide**" dataset provides insights into wage statistics across different countries and continents. It includes information on median, average, lowest, and highest salaries, categorized by country and continent. This dataset can be valuable for analyzing salary disparities and trends worldwide.

Columns:

country_name - The name of the country. continent_name - The name of the continent where the country is located. wage_span - The frequency of salary data (e.g., Monthly). median_salary - The median salary in the country/region. average_salary - The average salary in the country/region. lowest_salary - The lowest reported salary in the country/region. highest_salary - The highest reported salary in the country/region. This dataset is a valuable resource for conducting global salary analyses, understanding salary distributions, and making cross-country salary comparisons. It can be used by data analysts, researchers, and policymakers interested in labor market trends and salary-related insights.

Usage: This dataset is suitable for exploratory data analysis (EDA), statistical analysis, and creating data visualizations to better understand salary data trends across countries and continents.

Acknowledgments: The data sources for this dataset may vary, and it's important to cite the original sources when using the dataset for analysis or research.

Worldwide, Luxembourg has the highest net national income per capita, reaching nearly ****** U.S. dollars in 2021. Norway and Switzerland followed behind. When adjusting for purchasing power parity (PPP), Bermuda has the highest average income or wealth per adult worldwide.

Luxembourg had the highest average annual wage in Europe in 2024, at approximately ****** U.S. dollars when adjusting for purchasing power parity (PPP). Greece, which had an average annual salary of less than *******U.S dollars a year, had the lowest among the countries provided in this statistic.

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

The average for 2021 based on 71 countries was 27.53 percent. The highest value was in Colombia: 43.7 percent and the lowest value was in Slovakia: 19.1 percent. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

Uruguay was the Latin American country with the highest average monthly salary as of 2024, with a net value of around ***** U.S. dollars per month, followed by Costa Rica, with *** U.S. dollars per month. Employment development areas in Latin America Following the recuperation in this sector after the job losses endured throughout the COVID-19 pandemic, the unemployment rate persists in its endeavor to stabilize. Informal employment remains as the predominant actor across most Latin American countries, serving as a primary avenue for economic sustenance. Notably, the construction sector has experienced substantial growth, outpacing other relevant industries like tourism and hospitality. Poverty Throughout the past two decades, poverty levels in Latin America remain unchanged. Honduras takes the lead as the country bearing the highest poverty rate, with nearly half of its population dwelling in these circumstances. Across the region, the prevalent delineation is that of individuals classified within the non-extreme and lower-middle poverty strata, characterized by modest income levels.

This dataset provides a comprehensive collection of salary information from various industries and regions across the globe. Sourced from reputable employment websites and surveys, it includes details on job titles, salaries, job sectors, geographic locations, and more. Analyze this data to gain insights into job market trends, compare compensation across different professions, and make informed decisions about your career or hiring strategies. The dataset is cleaned and preprocessed for ease of analysis and is available under an open license for research and data analysis purposes.

Education Level: 0 : High School 1 : Bachelor Degree 2 : Master Degree 3 : Phd

Currency : US Dollar

Senior : It shows that is this employee has a senior position or no.(Binary)

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

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

According to the survey, Erlang and Elixir are the programming languages that are associated with the highest salaries worldwide in 2024, with an average of around *** and ** thousand U.S. dollars respectively.

𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝗳𝘂𝗹 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗼𝗳 𝗚𝗹𝗼𝗯𝗮𝗹 𝗦𝗮𝗹𝗮𝗿𝘆 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 🌎💲

Hello Kaggle Community!👋 Take a look at my new project on Global Salary Analysis. My goal is to uncover Insights and transform Numerical Data into Narratives. I prioritize data cleanliness for Optimal Utilization. This balanced approach serves both technical and Non-Technical Audiences, making Data easily Understandable. Then, I explore the comprehensive Dashboard to Derive Meaningful Conclusions from the Analysis. I have also created a separate sheet dedicated to a Full Map Visual to take a look at the bigger picture which is Fully Dynamic with the help of Data Validation. Also I have created a button by basic VBA code to navigate to the map sheet and come back to the Dashboard sheet. 📊📈

𝗗𝗮𝘁𝗮-𝗗𝗿𝗶𝘃𝗲𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗶𝘀 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱:

1. 𝗖𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 𝗧𝗼 𝗪𝗮𝘁𝗰𝗵 𝗢𝘂𝘁: 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲 𝘁𝗼𝗽 𝟭𝟬 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗵𝗶𝗴𝗵𝗲𝘀𝘁 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝘀𝗮𝗹𝗮𝗿𝗶𝗲𝘀. Switzerland might be a lucrative career move. With the highest average salary ($11,293), Switzerland could be an attractive option if you're open to relocation and have the necessary skills for the job market there.

2. 𝗖𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 𝗧𝗵𝗮𝘁 𝗠𝗶𝗴𝗵𝘁 𝗡𝗼𝘁 𝗔𝗻 𝗜𝗱𝗲𝗮𝗹 𝗖𝗵𝗼𝗶𝗰𝗲: 𝗟𝗼𝗼𝗸 𝗼𝘃𝗲𝗿 𝘁𝗵𝗲 𝘁𝗼𝗽 𝟭𝟬 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗹𝗼𝘄𝗲𝘀𝘁 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝘀𝗮𝗹𝗮𝗿𝗶𝗲𝘀. Unfortunately, we have some countries that might not pay you much according to your skillset.

3. 𝗟𝗼𝗼𝗸 𝗔𝘁 𝗧𝗵𝗲 𝗕𝗶𝗴𝗴𝗲𝗿 𝗣𝗶𝗰𝘁𝘂𝗿𝗲: 𝗧𝗮𝗿𝗴𝗲𝘁 𝘆𝗼𝘂𝗿 𝗷𝗼𝗯 𝘀𝗲𝗮𝗿𝗰𝗵 𝘁𝗼 𝗡𝗼𝗿𝘁𝗵 𝗔𝗺𝗲𝗿𝗶𝗰𝗮 𝗮𝗻𝗱 𝗘𝘂𝗿𝗼𝗽𝗲. Based on the high average salaries, these regions might offer better compensation for your skills and experience.

𝗡𝗼𝘁𝗲: All Salaries are stated in a monthly format and in USD.

DataAnalytics #DataAnalysis #DataAnalyst #DataStorytelling #BusinessIntelligence #DataVisualization #DataDrivenInsight

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

As of 2024, Morocco had the highest average monthly salaries in Africa. Employees in the country earned around ***** U.S. dollars per month. South Africa and Tunisia followed, with average monthly salaries amounting to ***** U.S. dollars and ***** U.S. dollars, respectively.

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

Switzerland Dairy Products Wages and Salaries jumped by 7.9% in 2019, from a year earlier.

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

Graph and download economic data for Population Growth for High Income OECD Countries (SPPOPGROWOEC) from 1961 to 2014 about OECD Economies, income, population, and rate.

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.

This dataset provides values for HOUSEHOLDS DEBT TO INCOME reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.