Cleaned dataset from the Billionaires Statistic Dataset (2023) that can be found here.

The code I used to clean and re-structure the data is also here.

First things first: a big shout-out to Nidula Elgiriyewithana for providing the original data.

As with it, this dataset contains various information about the world's wealthiest persons in different columns that can be grouped into three different types:

• Business-related information. These columns contain data about the industry in which the billionaires' operate, their source of wealth, total wealth and position they occupy in the ranking.
• Personal information. Such as name, age, nationality, country and city of residence.
• Economic activity information. These columns are related to the country in which the billionaire resides and provide different economic indicators like GDP, education enrollment or Consumer Price Index (CPI).

Column names

• position. Ranking of the billionaire measured by their wealth.
• wealth. The wealth of the billionaire measured in $.
• industry. Industry in which the billionaire's operates their businesses.
• full_name. Complete name of the billionaire.
• age. The age of the billionaire.
• country_of_residence. Country in which the billionaire resides.
• city_of_residence. City in which the billionaire resides.
• source. The source of the billionaire's wealth.
• citizenship. The country of citizenship of the billionaire.
• gender. The gender of the billionaire.
• birth_date. The birth date of the billionaire.
• last_name. The last name of the billionaire.
• first_name. The first name of the billionaire.
• residence_state. State in which the billionaire resides (only for billionaires who reside in the U.S.).
• residence_region. Region in which the billionaire resides (only for billionaires who reside in the U.S.).
• birth_year. The birth year of the billionaire.
• birth_month. The birth month of the billionaire.
• birth_day. The birth data of the billionaire.
• cpi_country. Consumer Price Index (CPI) for the billionaire's country.
• cpi_change_country. CPI change for the billionaire's country.
• gdp_country. Gross Domestic Product (GDP) in $ for the billionaire's country.
• g_tertiary_ed_enroll. Enrollment in tertiary education in the billionaire's country.
• g_primary_ed_enroll. Enrollment in primary education in the billionaire's country.
• life_expectancy. Life expectancy in the billionaire's country.
• tax_revenue. Tax revenue in the billionaire's country.
• tax_rate. Total tax rate in the billionaire's country.
• country_pop. Population of the billionaire's country.
• country_lat. Latitude coordinate of the billionaire's country.
• country_long. Longitude coordinate of the billionaire's country.
• continent. Continent in which the country of the billionaire's residence is located.

Potential analyses

• Analyze which industries contain the biggest groups of billionaires overall and in different countries.
• Explore number of billionaires and total wealth across countries and continents and display the result in a map.
• Focus on personal information columns such as age or gender to explore the distribution of billionaires from this perspective.
• Discover if countries' economic indicators have any impact in the presence of billionaires.
• The U.S. is the country with most billionaires presented in the dataset and also the only one with attributes in the residence_state and residence_region columns. This makes the American billionaires a good focus for a specific analysis.

Bonus

If you want a challenge, you can create a dashboard using tools such as Plotly to dynamically visualize the data using one or different attributes (such as industry, age or country). I did it, leave the link below in case you want to investigate:

Dashboard notebook here

If you find this dataset informative or inspirational, a vote is appreciated for others to easily discover value in it 💎💰

Dataset Card for 100 Richest People In World

  Dataset Summary

This dataset contains the list of Top 100 Richest People in the World Column Information:-

Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain

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  Supported Tasks and Leaderboards

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  Languages

[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.

• The billionaires satatistic dataset 2023 is a ranking of billionaires from 1st (with the highest wealth) to the 2640th (the less wealthy) in year 2023. the columns of the dataset are some attributs of the billionaires as follow:

rank: The ranking of the billionaire in terms of wealth. finalWorth: The final net worth of the billionaire in Million U.S. dollars. category: The category or industry in which the billionaire's business operates. personName: The full name of the billionaire. age: The age of the billionaire. country: The country in which the billionaire resides. city: The city in which the billionaire resides. source: The source of the billionaire's wealth. industries: The industries associated with the billionaire's business interests. countryOfCitizenship: The country of citizenship of the billionaire. organization: The name of the organization or company associated with the billionaire. selfMade: Indicates whether the billionaire is self-made (True/False). status: "D" represents self-made billionaires (Founders/Entrepreneurs) and "U" indicates inherited or unearned wealth. gender: The gender of the billionaire. birthDate: The birthdate of the billionaire. lastName: The last name of the billionaire. firstName: The first name of the billionaire. title: The title or honorific of the billionaire. date: The date of data collection. state: The state in which the billionaire resides. residenceStateRegion: The region or state of residence of the billionaire. birthYear: The birth year of the billionaire. birthMonth: The birth month of the billionaire. birthDay: The birth day of the billionaire. cpi_country: Consumer Price Index (CPI) for the billionaire's country. cpi_change_country: CPI change for the billionaire's country. gdp_country: Gross Domestic Product (GDP) for the billionaire's country. gross_tertiary_education_enrollment: Enrollment in tertiary education in the billionaire's country. gross_primary_education_enrollment_country: Enrollment in primary education in the billionaire's country. life_expectancy_country: Life expectancy in the billionaire's country. tax_revenue_country_country: Tax revenue in the billionaire's country. total_tax_rate_country: Total tax rate in the billionaire's country. population_country: Population of the billionaire's country. latitude_country: Latitude coordinate of the billionaire's country. longitude_country: Longitude coordinate of the billionaire's country.

In the first quarter of 2025, almost ********** of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest ** percent of earners only owned *** percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2024, *** percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States was the country with the most billionaires in the world in 2025. Elon Musk, with a net worth of *** billion U.S. dollars, was among the richest people in the United States in 2025. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.

This dataset provides a synthetic overview of the 1,000 wealthiest individuals in the world, offering insights into the distribution of wealth across industries and regions. It is designed to help analysts, researchers, and data enthusiasts explore global wealth trends, industry dominance, and regional wealth concentration.

Whether you're conducting market research, financial analysis, or data modeling, this dataset serves as a valuable resource for understanding the characteristics of the world's top billionaires.

📊 Key Features: Name 👤: The name of the billionaire. Country 🌍: Country of residence or primary business operation. Industry 🏭: Industry in which the individual has built their wealth. Net Worth (in billions) 💵: Estimated net worth in billions of USD. Company 🏢: The primary company or business associated with the billionaire. ⚠️ Important Note: This dataset is 100% synthetic and does not contain real financial or personal data. It is artificially generated for educational, analytical, and research purposes.

The Forbes published "The Definitive Ranking of the Wealthiest Americans In 2022". And here is the top 200 list including additional information on each of the billionaires.

About Dataset

This dataset contains the top 200 richest American based on their net worth.

Columns Attributes

| Column | Meaning | | -- | -- | | rank | their rank | | name | their name | | net worth | their net worth | | age | their age | | title | their title (e.g. CEO, Chairman etc.) | | source of wealth | the source of how they've managed to get this much money | | self made score | shows how far each of these billionaires has climbed to make it to the top. According to Forbes, The score ranges from 1 to 10, with 1 through 5 indicating someone who inherited some or all of his or her fortune; while 6 through 10 are for those who built their company or established a fortune on his or her own. | | philanthropy score | this score shows how much these billionaires donates on nonprofits foundations | | residence | their residence | | marital status | their marital status | | children | their children | | education | their education |

Methodology

This dataset was acquired using a web scraping tool called Beautiful soup and scraped Forbes website

Image by pch.vector on Freepik

Description

This dataset contains statistics on the world's billionaires, including information about their businesses, industries, and personal details. It provides insights into the wealth distribution, business sectors, and demographics of billionaires worldwide.

Key Features

• rank: The ranking of the billionaire in terms of wealth.
• finalWorth: The final net worth of the billionaire in U.S. dollars.
• category: The category or industry in which the billionaire's business operates.
• personName: The full name of the billionaire.
• age: The age of the billionaire.
• country: The country in which the billionaire resides.
• city: The city in which the billionaire resides.
• source: The source of the billionaire's wealth.
• industries: The industries associated with the billionaire's business interests.
• countryOfCitizenship: The country of citizenship of the billionaire.
• organization: The name of the organization or company associated with the billionaire.
• selfMade: Indicates whether the billionaire is self-made (True/False).
• status: "D" represents self-made billionaires (Founders/Entrepreneurs) and "U" indicates inherited or unearned wealth.
• gender: The gender of the billionaire.
• birthDate: The birthdate of the billionaire.
• lastName: The last name of the billionaire.
• firstName: The first name of the billionaire.
• title: The title or honorific of the billionaire.
• date: The date of data collection.
• state: The state in which the billionaire resides.
• residenceStateRegion: The region or state of residence of the billionaire.
• birthYear: The birth year of the billionaire.
• birthMonth: The birth month of the billionaire.
• birthDay: The birth day of the billionaire.
• cpi_country: Consumer Price Index (CPI) for the billionaire's country.
• cpi_change_country: CPI change for the billionaire's country.
• gdp_country: Gross Domestic Product (GDP) for the billionaire's country.
• gross_tertiary_education_enrollment: Enrollment in tertiary education in the billionaire's country.
• gross_primary_education_enrollment_country: Enrollment in primary education in the billionaire's country.
• life_expectancy_country: Life expectancy in the billionaire's country.
• tax_revenue_country_country: Tax revenue in the billionaire's country.
• total_tax_rate_country: Total tax rate in the billionaire's country.
• population_country: Population of the billionaire's country.
• latitude_country: Latitude coordinate of the billionaire's country.
• longitude_country: Longitude coordinate of the billionaire's country.

Potential Use Cases

• Wealth distribution analysis: Explore the distribution of billionaires' wealth across different industries, countries, and regions.
• Demographic analysis: Investigate the age, gender, and birthplace demographics of billionaires.
• Self-made vs. inherited wealth: Analyze the proportion of self-made billionaires and those who inherited their wealth.
• Economic indicators: Study correlations between billionaire wealth and economic indicators such as GDP, CPI, and tax rates.
• Geospatial analysis: Visualize the geographical distribution of billionaires and their wealth on a map.
• Trends over time: Track changes in billionaire demographics and wealth over the years.

If this was helpful, a vote is appreciated 🙂❤️

The richest people in the world, yearly rank from 2002 to 2021

This dataset contains 200 rows and 7 columns.

The World's Billionaires is an annual ranking by documented net worth of the world's wealthiest billionaires compiled and published in March annually by the American business magazine Forbes. The list was first published in March 1987. The total net worth of each individual on the list is estimated and is cited in United States dollars, based on their documented assets and accounting for debt. Royalty and dictators whose wealth comes from their positions are excluded from these lists. This ranking is an index of the wealthiest documented individuals, excluding and ranking against those with wealth that is not able to be completely ascertained. (wikipedia)

About the Ranking

The World's Billionaires is an annual ranking by documented net worth of the wealthiest billionaires in the world, compiled and published in March annually by the American business magazine Forbes. The list was first published in March 1987. The total net worth of each individual on the list is estimated and is cited in United States dollars, based on their documented assets and accounting for debt and other factors. Royalty and dictators whose wealth comes from their positions are excluded from these lists. This ranking is an index of the wealthiest documented individuals, excluding any ranking of those with wealth that is not able to be completely ascertained.

Forbes Methodology

Each year, Forbes employs a team of over 50 reporters from a variety of countries to track the activity of the world's wealthiest individuals and sometimes groups or families – who share wealth. Preliminary surveys are sent to those who may qualify for the list. According to Forbes, they received three types of responses – some people try to inflate their wealth, others cooperate but leave out details, and some refuse to answer any questions. Business deals are then scrutinized and estimates of valuable assets – land, homes, vehicles, artwork, etc. – are made. Interviews are conducted to vet the figures and improve the estimate of an individual's holdings. Finally, positions in a publicly traded stock are priced to market on a date roughly a month before publication. Privately held companies are priced by the prevailing price-to-sales or price-to-earnings ratios. Known debt is subtracted from assets to get a final estimate of an individual's estimated worth in United States dollars. Since stock prices fluctuate rapidly, an individual's true wealth and ranking at the time of publication may vary from their situation when the list was compiled.

The dataset presents a glimpse into the elite echelons of global wealth, featuring prominent billionaires from diverse backgrounds and industries. At the helm is Bernard Arnault, a French titan in the consumer sector, followed closely by Jeff Bezos and Elon Musk, trailblazers in the technology realm hailing from the United States. These innovators, alongside luminaries like Mark Zuckerberg, Bill Gates, and Larry Page, have reshaped industries, propelled technological advancements, and amassed staggering fortunes. Notably, Warren Buffett, Larry Ellison, and Michael Dell represent the seasoned veterans of the tech and investment spheres, each leaving an indelible mark on their respective domains.

Diverse geographical representation is evident, with Mukesh Ambani from India and Carlos Slim from Mexico showcasing global wealth distribution. Ambani's influence extends across energy and telecommunications, while Slim's conglomerate spans telecommunications, real estate, and healthcare. Gautam Adani represents India's industrial prowess, steering his conglomerate through energy and infrastructure sectors.

This dataset underscores the intersection of wealth, innovation, and entrepreneurship, reflecting the evolving landscape of global capitalism. From disruptive tech visionaries to seasoned investors and industrialists, these billionaires symbolize the dynamism and influence of economic elites in shaping our world.

A dataset listing the richest zip codes in Mississippi per the most current US Census data, including information on rank and average income.

As of March 2025, Elon Musk had a net worth valued at 328.5 billion U.S. dollars, making him the richest man in the world. Amazon founder Jeff Bezos followed in second, with Marc Zuckerberg, the founder of Facebook, in third. The list is dominated by Americans, and Alice Walton and Francoise Bettencourt Meyers are the only women among the 20 richest people worldwide.