This dataset provides values for 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.

The Gross Domestic Product (GDP) in the United States expanded 2.10 percent in the second quarter of 2025 over the same quarter of the previous year. This dataset provides the latest reported value for - United States GDP Annual Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Which countries have economically grown the most in the last years? And in the last decades? This dataset collected from the Word Bank website in Data Bank gives some informations about this questions based on the GDP rate, with '' representing missing data.

The Gross Domestic Product (GDP) in the United States expanded 3.80 percent in the second quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - United States GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The "GDP DATA" dataset presents annual GDP figures (in USD) for 142 countries spanning from 2005 to 2022. Each row represents a country, and each column corresponds to a specific year's GDP, allowing for easy analysis of economic growth trends, comparisons across countries, and time-series forecasting.

Potential Uses and Analyses:

Time-Series Analysis: Identify long-term growth patterns, detect anomalies, and forecast future GDP using models like ARIMA, Prophet, or LSTM.

Comparative Economic Analysis: Compare GDP growth rates across countries or regions to understand relative performance over time.

Clustering and Classification: Group countries with similar GDP trajectories using machine learning techniques such as k-means or hierarchical clustering.

Correlation Studies: Analyze the correlation between GDP and other indicators such as population, inflation, or education (if combined with external datasets).

Policy and Investment Insights: Generate insights for economic policy-making or investment planning by identifying high-growth economies or recession trends.

This dataset is well-suited for economists, data scientists, policy researchers, and educators aiming to explore macroeconomic trends or build predictive models based on real-world data.

In 2023, South Asia recorded the highest real gross domestic product (GDP) growth rate in the Asia-Pacific region at seven percent, at least 2.7 percentage points higher than other subregions. East Asia reported a real GDP growth rate of about 4.3 percent, while Southeast Asia's real GDP growth rate was around 4.1 percent that year. In 2025, South Asia was forecasted to remain the subregion with the highest real GDP growth rate at six percent, while Southeast Asia was projected to rank second at around 4.7 percent.

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

Germany DE: GDP: Growth data was reported at -0.305 % in 2023. This records a decrease from the previous number of 1.806 % for 2022. Germany DE: GDP: Growth data is updated yearly, averaging 2.230 % from Dec 1961 (Median) to 2023, with 63 observations. The data reached an all-time high of 7.418 % in 1969 and a record low of -5.694 % in 2009. Germany DE: GDP: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;

In the second quarter of 2025, the growth of the real gross domestic product (GDP) in China ranged at *** percent compared to the same quarter of the previous year. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. Real GDP is adjusted for price changes and is therefore regarded as a key indicator for economic growth. GDP growth in China In 2024, China ranged second among countries with the largest gross domestic product worldwide. Since the introduction of economic reforms in 1978, the country has experienced rapid social and economic development. In 2013, it became the world’s largest trading nation, overtaking the United States. However, per capita GDP in China was still much lower than that of industrialized countries. Until 2011, the annual growth rate of China’s GDP had constantly been above nine percent. However, economic growth has cooled down since and is projected to further slow down gradually in the future. Rising domestic wages and the competitive edge of other Asian and African countries are seen as main reasons for the stuttering in China’s economic engine. One strategy of the Chinese government to overcome this transition is a gradual shift of economic focus from industrial production to services. Challenges to GDP growth Another major challenge lies in the massive environmental pollution that China’s reckless economic growth has caused over the past decades. China’s development has been powered mostly by coal consumption, which resulted in high air pollution. To counteract industrial pollution, further investments in waste management and clean technologies are necessary. In 2017, about **** percent of GDP was spent on pollution control. Surging environmental costs aside, environmental issues could also be a key to industrial transition as China placed major investments in renewable energy and clean tech projects. The consumption of green energy skyrocketed from **** exajoules in 2005 to **** million in 2022.

The indicator is calculated as the ratio of real GDP (GDP adjusted for inflation) to the average population of a specific year, where GDP is expressed in millions and population is expressed in thousands. Real GDP is published without decimals. GDP measures the value of the total final output of goods and services produced by an economy within a certain period of time. It includes goods and services that have markets (or which could have markets) and products which are produced by general government and non-profit institutions. It is a measure of economic activity and is commonly used as a proxy for the development in a country’s material living standards. However, it is not a complete measure of economic welfare. For example, GDP does not include most unpaid household work. Neither does GDP take account of negative effects of economic activity, like environmental degradation.

This layer is part of SDGs Today. Please see sdgstoday.orgGross Domestic Product (GDP) is one of the most commonly used measures for tracking national accounts and economic activity. Tracking growth over time can provide insights into the growth or decline of a nation’s economic activities following global/national events, policy changes, and other large-scale phenomena.The OECD's quarterly national accounts (QNA) dataset presents GDP growth data collected from all the OECD member countries and some other major economies on the basis of a standardised questionnaire. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis from 1960 or whenever available. These indicators include measures such as GDP expenditure/output and industry-based employment rates. All available OECD QNA measurements are made available to the public here.For more information, contact STAT.Contact@oecd.org.

This dataset provides values for 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.

United States US: GDP: Growth: Exports of Goods and Services data was reported at -0.329 % in 2016. This records a decrease from the previous number of 0.410 % for 2015. United States US: GDP: Growth: Exports of Goods and Services data is updated yearly, averaging 6.733 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 18.850 % in 1973 and a record low of -8.794 % in 2009. United States US: GDP: Growth: Exports of Goods and Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual growth rate of exports of goods and services based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude compensation of employees and investment income (formerly called factor services) and transfer payments.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the world’s people live in a country with a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

VARIABLE DESCRIPTIONS: UNID: ISO numeric country code (used by the United Nations) WBID: ISO alpha country code (used by the World Bank) SES: Socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174) country: Short country name year: Survey year SES: Socioeconomic status score (1-99) for each of 174 countries gdppc: GDP per capita: Single time-series (imputed) yrseduc: Completed years of education in the adult (15+) population popshare: Total population shares

DATA SOURCES: The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita: 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. Maddison population data in 000s; GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls. 2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm 3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/ Total Population 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.
2. United Nations Population Division. 2009.

Thailand TH: GDP: Growth:(GDP) Gross Domestic Productper Capita data was reported at 3.641 % in 2017. This records an increase from the previous number of 2.974 % for 2016. Thailand TH: GDP: Growth:(GDP) Gross Domestic Productper Capita data is updated yearly, averaging 3.845 % from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 11.332 % in 1988 and a record low of -8.734 % in 1998. Thailand TH: GDP: Growth:(GDP) Gross Domestic Productper Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth rate of GDP per capita based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

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.

Italy IT: GDP: Growth data was reported at 1.502 % in 2017. This records an increase from the previous number of 0.858 % for 2016. Italy IT: GDP: Growth data is updated yearly, averaging 1.986 % from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 8.207 % in 1961 and a record low of -5.482 % in 2009. Italy IT: GDP: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

Costa Rica CR: GDP: Growth data was reported at 5.112 % in 2023. This records an increase from the previous number of 4.551 % for 2022. Costa Rica CR: GDP: Growth data is updated yearly, averaging 4.551 % from Dec 1961 (Median) to 2023, with 63 observations. The data reached an all-time high of 9.201 % in 1992 and a record low of -7.286 % in 1982. Costa Rica CR: GDP: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;

This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the countries in this dataset have a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

VARIABLE DESCRIPTIONS:

unid: ISO numeric country code (used by the United Nations)

wbid: ISO alpha country code (used by the World Bank)

SES: Country socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174)

country: Short country name

year: Survey year

gdppc: GDP per capita: Single time-series (imputed)

yrseduc: Completed years of education in the adult (15+) population

region5: Five category regional coding schema

regionUN: United Nations regional coding schema

DATA SOURCES:

The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita:

1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls.

2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm

3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/

4. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.

5. United Nations Population Division. 2009.

Explore the World Competitiveness Ranking dataset for 2016, including key indicators such as GDP per capita, fixed telephone tariffs, and pension funding. Discover insights on social cohesion, scientific research, and digital transformation in various countries.

Social cohesion, The image abroad of your country encourages business development, Scientific articles published by origin of author, International Telecommunication Union, World Telecommunication/ICT Indicators database, Data reproduced with the kind permission of ITU, National sources, Fixed telephone tariffs, GDP (PPP) per capita, Overall, Exports of goods - growth, Pension funding is adequately addressed for the future, Companies are very good at using big data and analytics to support decision-making, Gross fixed capital formation - real growth, Economic Performance, Scientific research legislation, Percentage of GDP, Health infrastructure meets the needs of society, Estimates based on preliminary data for the most recent year., Singapore: including re-exports., Value, Laws relating to scientific research do encourage innovation, % of GDP, Gross Domestic Product (GDP), Health Infrastructure, Digital transformation in companies is generally well understood, Industrial disputes, EE, Female / male ratio, State ownership of enterprises, Total expenditure on R&D (%), Score, Colombia, Estimates for the most recent year., Percentage change, based on US$ values, Number of listed domestic companies, Tax evasion is not a threat to your economy, Scientific articles, Tax evasion, % change, Use of big data and analytics, National sources, Disposable Income, Equal opportunity, Listed domestic companies, Government budget surplus/deficit (%), Pension funding, US$ per capita at purchasing power parity, Estimates; US$ per capita at purchasing power parity, Image abroad or branding, Equal opportunity legislation in your economy encourages economic development, Number, Article counts are from a selection of journals, books, and conference proceedings in S&E from Scopus. Articles are classified by their year of publication and are assigned to a region/country/economy on the basis of the institutional address(es) listed in the article. Articles are credited on a fractional-count basis. The sum of the countries/economies may not add to the world total because of rounding. Some publications have incomplete address information for coauthored publications in the Scopus database. The unassigned category count is the sum of fractional counts for publications that cannot be assigned to a country or economy. Hong Kong: research output items by the higher education institutions funded by the University Grants Committee only., State ownership of enterprises is not a threat to business activities, Protectionism does not impair the conduct of your business, Digital transformation in companies, Total final energy consumption per capita, Social cohesion is high, Rank, MTOE per capita, Percentage change, based on constant prices, US$ billions, National sources, World Trade Organization Statistics database, Rank, Score, Value, World Rankings

Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kazakhstan, Latvia, Lithuania, Luxembourg, Malaysia, Mexico, Mongolia, Netherlands, New Zealand, Norway, Oman, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Saudi Arabia, Singapore, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Kingdom, Venezuela

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