This dataset provides annual GDP data for all recognized countries from 2015 to 2025, sourced from the IMF. Figures for 2015–2024 are reported values, while 2025 contains projections as the year is not yet complete. For some countries (such as Afghanistan and a few others), certain years are missing due to data not being reported. The dataset is well-suited for: 1) Trend analysis – Study global GDP growth patterns over the past decade. 2) Forecasting models – Train machine learning models to predict future GDP values. 3) Country comparisons – Compare economic performance between countries or regions. 4) Time-series learning – Practice ARIMA, Prophet, LSTM, and other forecasting techniques. 5) Impact studies – Analyze the impact of global events (e.g., COVID-19) on GDP. 6) Correlation analysis – Link GDP with other indicators (population, inflation, CO₂ emissions). 7) Regional studies – Examine differences between continents or economic blocs (EU, ASEAN, G7, BRICS). 8) Inequality measurement – Compare GDP distribution across developed vs. developing economies. 9) Visualization projects – Create dashboards, heatmaps, or choropleth maps of GDP data. 10) Educational use – Use the dataset in economics, finance, or data science courses as a teaching resource.

This dataset provides values for GDP 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 annual GDP data for 196 countries from 2005 to 2025, measured in USD billions. Data is sourced from the International Monetary Fund (IMF).

Coverage: 196 countries + header row Time span: 2005–2024 (reported), 2025 (projected) Notable trends: The data clearly shows the impact of the 2008 global financial crisis and the 2020 COVID-19 pandemic on world economies. Missing values: In some cases, GDP values are unavailable because countries did not report them.

Usability

Trend analysis — Study global and regional GDP growth patterns across two decades.

Forecasting models — Train ARIMA, Prophet, LSTM, or other models to predict future GDP.

Comparative studies — Benchmark economic performance between countries, continents, or economic blocs (e.g., G7, BRICS).

Impact assessment — Analyze the effect of global events such as the 2008 crisis and COVID-19 on GDP.

Correlation research — Combine with other datasets (population, inflation, CO₂ emissions) for cross indicator analysis.

Visualization projects — Build dashboards, choropleth maps, or interactive charts to illustrate global growth.

Educational use — Teach concepts of macroeconomics, time series data, and forecasting in classrooms.

Investment & policy insights — Support macro level decision making, financial market analysis, or policy research.

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

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.

🧾 About Dataset

🌍 Global GDP by Country — 2024 Edition

📖 Overview

The Global GDP by Country (2024) dataset provides an up-to-date snapshot of worldwide economic performance, summarizing each country’s nominal GDP, growth rate, population, and global economic contribution.

This dataset is ideal for economic analysis, data visualization, policy modeling, and machine learning applications related to global development and financial forecasting.

📊 Dataset Information

• Total Records: 181 countries
• Time Period: 2024 (latest available global data)
• Geographic Coverage: Worldwide
• File Format: CSV
• File Size: ~10 KB
• Missing Values: None (100% complete dataset)

🎯 Target Use-Cases:
- Economic growth trend analysis
- GDP-based country clustering
- Per capita wealth comparison
- Share of world economy visualization

🧩 Key Features

📈 Statistical Summary

Population Overview

• Mean Population: 43.6 million
• Standard Deviation: 155.5 million
• Minimum Population: 9,816 (small island nations)
• Median Population: 9.1 million
• Maximum Population: 1.43 billion (China)

🌟 Highlights

💰 Top Economies (Nominal GDP):
United States, China, Japan, Germany, India

📈 Fastest Growing Economies:
India, Bangladesh, Vietnam, and Rwanda

🌐 Global Insights:
- The dataset covers 181 countries representing 100% of global GDP.
- Suitable for data visualization dashboards, AI-driven economic forecasting, and educational research.

💡 Example Use-Cases

• Build a choropleth map showing GDP distribution across continents.
• Train a regression model to predict GDP per capita based on population and growth.
• Compare economic inequality using population vs GDP share.

📚 Dataset Citation

Source: Worldometers — GDP by Country (2024)
Dataset compiled and cleaned by: Asadullah Shehbaz
For open research and data analysis.

This dataset contains annual Gross Domestic Product (GDP) data for all recognized countries covering the years 2020 to 2025. Disputed territories are excluded. The dataset is compiled from IMF sources and is well-suited for studying global economic trends, forecasting, and analyzing the growth or decline of individual economies over this period. 2025 year data is estimates and will be available next year.

🌍 Country-level GDP (1975–2025)

This dataset provides annual GDP data (in billions of USD) for countries worldwide from 1975 to 2025.It includes both active and historical entities such as USSR, Yugoslavia, and the divided countries Sudan and South Sudan.

  📊 Columns

Column Type Description

year int Year of observation

country string Country or economy name

gdp_billion_usd float GDP value in billions of USD

entity_status string Indicates active or… See the full description on the dataset page: https://huggingface.co/datasets/ByNadiia/gdp-by-country-1975-2025.

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

The Global 15x15 Minute Grids of the Downscaled GDP Based on the Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990 and 2025, are geospatial distributions of Gross Domestic Product (GDP) per Unit area (GDP densities). These global grids were generated using the Country-level GDP and Downscaled Projections Based on the SRES B2 Scenario, 1990-2100 data set, and CIESIN's Gridded Population of World, Version 2 (GPWv2) data set as the base map. First, the GDP per capita was developed at a country-level for 1990 and 2025. Then the gridded GDP was developed within each country by applying the GDP per capita to each grid cell of the GPW, under the assumption that the GDP per capita was uniform within a country. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

Gross domestic product ranking table.

Time series data for the statistic Total Credit To Non-Financial Sector (% of GDP) and country Saudi Arabia. Indicator Definition:Total Credit To Non-Financial Sector (% of GDP)The indicator "Total Credit To Non-Financial Sector (% of GDP)" stands at 101.90 as of 03/31/2025, the highest value since 09/30/2021. Regarding the One-Year-Change of the series, the current value constitutes an increase of 12.10 percent compared to the value the year prior.The 1 year change in percent is 12.10.The 3 year change in percent is 15.14.The 5 year change in percent is 25.34.The 10 year change in percent is 103.80.The Serie's long term average value is 79.46. It's latest available value, on 03/31/2025, is 28.24 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2012, to it's latest available value, on 03/31/2025, is +157.32%.The Serie's change in percent from it's maximum value, on 12/31/1999, to it's latest available value, on 03/31/2025, is -26.11%.

Comprehensive socio-economic dataset for Thailand including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

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

Comprehensive socio-economic dataset for Slovenia including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

Time series data for the statistic Gross Domestic Product, Nominal, Seasonally Adjusted, Domestic Currency and country Morocco. Indicator Definition:Gross Domestic Product, Nominal, Seasonally Adjusted, Domestic CurrencyThe indicator "Gross Domestic Product, Nominal, Seasonally Adjusted, Domestic Currency" stands at 409.67 Billion as of 3/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 6.93 percent compared to the value the year prior.The 1 year change in percent is 6.93.The 3 year change in percent is 27.75.The 5 year change in percent is 35.53.The 10 year change in percent is 54.94.The Serie's long term average value is 311.26 Billion. It's latest available value, on 3/31/2025, is 31.62 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 3/31/2014, to it's latest available value, on 3/31/2025, is +66.89%.The Serie's change in percent from it's maximum value, on 12/31/2024, to it's latest available value, on 3/31/2025, is -1.37%.

Comprehensive socio-economic dataset for Palestine including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

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