Context

This dataset provides country-level GDP (Gross Domestic Product) in current US dollars from 2000 to 2025, mapped to the seven classic continents (Asia, Africa, Europe, North America, South America, Australia, and Antarctica). It is designed to make global economic data easier to explore, compare, and visualize by combining both geographic and temporal dimensions.

GDP is one of the most widely used indicators to measure the size of an economy, its growth trends, and relative economic performance across regions.

Source

Data Provider: World Bank Open Data

Indicator Used: NY.GDP.MKTP.CD → GDP (current US$)

License: World Bank Dataset Terms of Use (aligned with CC BY 4.0)

Note: 2024–2025 values may be incomplete or missing for some countries, depending on World Bank publication updates.

Dataset Structure

Name of country → Country name

Continent → One of the 7 continents

2000–2025 → GDP values in current US$ (float, may contain missing values NaN)

Format: wide panel data (one row per country, one column per year).

Inspiration & Use Cases

This dataset was prepared to make economic analysis, visualization, and forecasting more accessible. It can be used for:

• Time-series forecasting (predicting GDP growth into the future)
• Cross-country comparisons (e.g., comparing GDP trends of India vs. USA vs. Brazil)
• Continent-level aggregation (summing GDP by continent per year)
• Data visualization (heatmaps, line charts, world choropleths)
• Machine Learning applications (e.g., clustering countries by GDP trajectory)

Citation

If you use this dataset, please cite:

Source: World Bank, World Development Indicators (NY.GDP.MKTP.CD). Licensed under the World Bank Terms of Use.

Graph and download economic data for Gross Domestic Product for Least Developed Countries (NYGDPMKTPCDLDC) from 1960 to 2024 about , and GDP.

This dataset simulates a set of key economic, social, and environmental indicators for 20 countries over the period from 2010 to 2019. The dataset is designed to reflect typical World Bank metrics, which are used for analysis, policy-making, and forecasting. It includes the following variables:

Country Name: The country for which the data is recorded. Year: The specific year of the observation (from 2010 to 2019). GDP (USD): Gross Domestic Product in billions of US dollars, indicating the economic output of a country. Population: The total population of the country in millions. Life Expectancy (in years): The average life expectancy at birth for the country’s population. Unemployment Rate (%): The percentage of the total labor force that is unemployed but actively seeking employment. CO2 Emissions (metric tons per capita): The per capita carbon dioxide emissions, reflecting environmental impact. Access to Electricity (% of population): The percentage of the population with access to electricity, representing infrastructure development. Country:

Description: Name of the country for which the data is recorded. Data Type: String Example: "United States", "India", "Brazil" Year:

Description: The year in which the data is observed. Data Type: Integer Range: 2010 to 2019 Example: 2012, 2015 GDP (USD):

Description: The Gross Domestic Product of the country in billions of US dollars, indicating the economic output. Data Type: Float (billions of USD) Example: 14200.56 (represents 14,200.56 billion USD) Population:

Description: The total population of the country in millions. Data Type: Float (millions of people) Example: 331.42 (represents 331.42 million people) Life Expectancy (in years):

Description: The average number of years a newborn is expected to live, assuming that current mortality rates remain constant throughout their life. Data Type: Float (years) Range: Typically between 50 and 85 years Example: 78.5 years Unemployment Rate (%):

Description: The percentage of the total labor force that is unemployed but actively seeking employment. Data Type: Float (percentage) Range: Typically between 2% and 25% Example: 6.25% CO2 Emissions (metric tons per capita):

Description: The amount of carbon dioxide emissions per person in the country, measured in metric tons. Data Type: Float (metric tons) Range: Typically between 0.5 and 20 metric tons per capita Example: 4.32 metric tons per capita Access to Electricity (%):

Description: The percentage of the population with access to electricity. Data Type: Float (percentage) Range: Typically between 50% and 100% Example: 95.7%

The average for 2023 based on 64 countries was 0.97 percent. The highest value was in the USA: 26.3 percent and the lowest value was in Andorra: 0 percent. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Gross domestic product ranking table.

The average for 2024 based on 58 countries was 58042 U.S. dollars. The highest value was in Singapore: 132570 U.S. dollars and the lowest value was in Barbados: 19946 U.S. dollars. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

ABOUT

The Global GDP Per Capita Dataset provides a comprehensive record of annual economic output per person across various countries and regions. It includes key economic indicators such as GDP per capita (adjusted for inflation and purchasing power parity), country codes, and yearly data points. This dataset is valuable for economists, researchers, policymakers, and analysts interested in studying economic growth, income distribution, and global development trends.

Key features of the dataset:

✅ Covers multiple countries and regions worldwide
✅ Provides annual GDP per capita data from 1990 to 2023
✅ Adjusted for inflation and purchasing power parity (PPP, constant 2021$)
✅ Sourced from the World Bank - World Development Indicators
✅ Useful for economic analysis, policy-making, and financial forecasting

This dataset serves as a crucial resource for understanding global economic trends, comparing living standards across nations, and making data-driven decisions in economic research and policy development.

FILE INFORMATION

The dataset consists of structured records related to GDP per capita, compiled from the World Bank’s World Development Indicators (WDI). Each file contains country-level economic data, including GDP per capita values in constant 2021 international dollars (PPP). This allows researchers, economists, and data analysts to study economic growth patterns and trends over time. The file type is CSV.

COLUMNS DESCRIPTION

• Entity – The country or region name.
• Code – The country code (ISO Alpha-3 format or OWID custom code) [NOTE : missing value if there is no ISO Alpha-3 code].
• Year – The year of the GDP observation (1990–2023).
• GDP per capita (PPP, 2021$) – The economic output per person, adjusted for inflation and cost of living.

This dataset provides valuable insights into economic trends over three decades, helping researchers analyze global income levels, economic development, and policy impacts.

Graph and download economic data for Gross Domestic Product Per Capita for Least Developed Countries (NYGDPPCAPCDLDC) from 1960 to 2024 about per capita and GDP.

Gross domestic product is the total income earned through the production of goods and services in an economic territory during an accounting period. It can be measured in three different ways: using either the expenditure approach, the income approach, or the production approach. This indicator denotes the percentage change over each previous year of the constant price (base year 2015) series in United States dollars.

The average for 2023 based on 55 countries was 66.08 percent. The highest value was in Luxembourg: 217.77 percent and the lowest value was in the USA: 11.01 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

Graph and download economic data for Financial System Deposits to GDP for Trinidad and Tobago (DDDI08TTA156NWDB) from 1960 to 2021 about Trinidad and Tobago, deposits, financial, and GDP.

Overview

This dataset provides a comprehensive collection of time series data sourced from the World Bank Open Data Platform, covering a wide range of global indicators from 1960 to the most recently published year. It includes economic, social, environmental, and demographic metrics, making it an ideal resource for researchers, data scientists, and policymakers interested in global development trends, economic forecasting, or socio-economic analysis.

A tutorial on how to combined the dataset topics together into one large dataset can be found here

Why this Dataset?

My motivation for this project was to curate a high-quality collection of datasets for World Bank indicators organized by topics and structured in time-series, making them more accessible for data science projects. Since the World Bank’s Kaggle datasets have not been updated since 2019 https://www.kaggle.com/organizations/theworldbank, I saw an opportunity to provide more current data for the data analysis community.

Dataset Collection Contents

This collection brings together more than 800 World Bank indicators organized into 18 topic‑specific CSV files. Each file is structured as a country‑year panel: every row represents a unique combination of year (1960‑present) and ISO‑3 country code, while the columns hold the topic’s indicators.

The collection includes datasets with a variety of indicators, such as: - Economic Metrics: GDP growth (%), GDP per capita, consumer price inflation, merchandise trade, gross capital formation, and more.
- Social Metrics: School enrollment (primary, secondary, tertiary), infant mortality rate, maternal mortality rate, poverty headcount, and more.
- Environmental Metrics: Forest area, renewable energy consumption, food production indices, and more.
- Demographic Metrics: Urban population, life expectancy, net migration, and more.

Usage

This dataset is ideal for a variety of applications, including: - Economic forecasting and trend analysis (e.g., GDP growth, inflation).
- Socio-economic studies (e.g., education, health, poverty).
- Environmental impact analysis (e.g., renewable energy adoption).
- Demographic research (e.g., population trends, migration).

Topic datasets can be merged with each other using year and country code. This tutorial with notebook code can help you get started quickly.

Collection Methodology

The data is collected via a custom software application that discovers and groups high-quality indicators with rules-based logic & artificial intelligence, generates metadata, and performs ETL for the data from the World Bank API. The result is a clean, up‑to‑date collection of World Bank indicators in time-series format that is ready for analysis—no manual downloads or data wrangling required.

Modifications

The original World Bank data has been aggregated and transformed for ease of use. Missing values have been preserved as provided by the World Bank, and no significant transformations have been applied beyond formatting and aggregation into a single file.

Source & Attribution

The World Bank: World Development Indicators

This dataset is publicly available and sourced from the World Bank Open Data Platform and is made available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. When using this data, please attribute the World Bank as follows: "Data sourced from the World Bank, licensed under CC BY 4.0." For more details on the World Bank’s terms of use, visit: https://www.worldbank.org/en/about/legal/terms-of-use-for-datasets.

License

This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Feel free to use this data in Kaggle notebooks, academic research, or policy analysis. If you create a derived dataset or analysis, I encourage you to share it with the Kaggle community.

Explore global financial development data including remittance inflows, bank assets, loans, insurance premiums, stock market indicators, and more. Analyze trends in India, Qatar, Saudi Arabia, and other countries with the World Bank dataset.

Remittance inflows to GDP, Foreign bank assets, Global leasing volume, Private debt securities, Bank Z-score, Loans requiring collateral, Stock price volatility, Bank cost to income ratio

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

Follow data.kapsarc.org for timely data to advance energy economics research.

Graph and download economic data for Deposit Money Bank Assets to GDP for Viet Nam (DDDI02VNA156NWDB) from 1992 to 2021 about Viet Nam, deposits, assets, banks, depository institutions, and GDP.

The Gross Domestic Product (GDP) in World was worth 111326.37 billion US dollars in 2024, according to official data from the World Bank. This dataset includes a chart with historical data for World GDP.

The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. Gross domestic product (GDP) is a monetary measure of the market value of…

The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.

For further details, please refer to https://datatopics.worldbank.org/world-development-indicators/

The average for 2015 based on 40 countries was 10.35 GDP per kg of oil equivalent. The highest value was in Dominican Republic: 18.55 GDP per kg of oil equivalent and the lowest value was in Turkmenistan: 3.42 GDP per kg of oil equivalent. The indicator is available from 1990 to 2023. Below is a chart for all countries where data are available.

Graph and download economic data for Gross Domestic Product for Italy (MKTGDPITA646NWDB) from 1960 to 2024 about Italy and GDP.

Fork this notebook to get started on accessing data in the BigQuery dataset by writing SQL queries using the BQhelper module.

Context

World Development Indicators (WDI) by World Bank includes data spanning up to 56 years—from 1960 to 2016. WDI frames global trends with indicators on population, population density, urbanization, GNI, and GDP. These indicators measure the world’s economy and progress toward improving lives, achieving sustainable development, providing support for vulnerable populations, and reducing gender disparities.

Content

World Development Indicators Data is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.

Acknowledgements

“World Development Indicators” by the World Bank, used under CC BY 3.0 IGO.

Data Origin: https://bigquery.cloud.google.com/dataset/patents-public-data:worldbank_wdi

Banner photo by Joshua Rawson-Harris on Unsplash