Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset provides key economic indicators for five of the world's largest economies, based on their nominal Gross Domestic Product (GDP) in 2022. It includes the GDP values, population, GDP growth rates, per capita GDP, and each country's share of the global economy.
Columns: Country: Name of the country. GDP (nominal, 2022): The total nominal GDP in 2022, represented in USD. GDP (abbrev.): The abbreviated GDP in trillions of USD. GDP growth: The percentage growth in GDP compared to the previous year. Population: Total population of each country in 2022. GDP per capita: The GDP per capita, representing average economic output per person in USD. Share of world GDP: The percentage of global GDP contributed by each country. Key Highlights: The dataset includes some of the largest global economies, such as the United States, China, Japan, Germany, and India. The data can be used to analyze the economic standing of countries in terms of overall GDP and per capita wealth. It offers insights into the relative growth rates and population sizes of these leading economies. This dataset is ideal for exploring economic trends, performing country-wise comparisons, or studying the relationship between population size and GDP growth.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for GDP GROWTH RATEAND reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for GDP!S reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This is a dataset for the Exploratory Data Analysis purpose of the GDP of every country in the world from the 1980s to 2023. This dataset can also be used to forecast the countries' GDPs for the year 2024. And don't forget to upvote😄.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about countries in Europe. It has 44 rows. It features 2 columns including GDP.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Description
This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.
Key Features
- Country: Name of the country.
- Density (P/Km2): Population density measured in persons per square kilometer.
- Abbreviation: Abbreviation or code representing the country.
- Agricultural Land (%): Percentage of land area used for agricultural purposes.
- Land Area (Km2): Total land area of the country in square kilometers.
- Armed Forces Size: Size of the armed forces in the country.
- Birth Rate: Number of births per 1,000 population per year.
- Calling Code: International calling code for the country.
- Capital/Major City: Name of the capital or major city.
- CO2 Emissions: Carbon dioxide emissions in tons.
- CPI: Consumer Price Index, a measure of inflation and purchasing power.
- CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
- Currency_Code: Currency code used in the country.
- Fertility Rate: Average number of children born to a woman during her lifetime.
- Forested Area (%): Percentage of land area covered by forests.
- Gasoline_Price: Price of gasoline per liter in local currency.
- GDP: Gross Domestic Product, the total value of goods and services produced in the country.
- Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
- Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
- Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
- Largest City: Name of the country's largest city.
- Life Expectancy: Average number of years a newborn is expected to live.
- Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
- Minimum Wage: Minimum wage level in local currency.
- Official Language: Official language(s) spoken in the country.
- Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
- Physicians per Thousand: Number of physicians per thousand people.
- Population: Total population of the country.
- Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
- Tax Revenue (%): Tax revenue as a percentage of GDP.
- Total Tax Rate: Overall tax burden as a percentage of commercial profits.
- Unemployment Rate: Percentage of the labor force that is unemployed.
- Urban Population: Percentage of the population living in urban areas.
- Latitude: Latitude coordinate of the country's location.
- Longitude: Longitude coordinate of the country's location.
Potential Use Cases
- Analyze population density and land area to study spatial distribution patterns.
- Investigate the relationship between agricultural land and food security.
- Examine carbon dioxide emissions and their impact on climate change.
- Explore correlations between economic indicators such as GDP and various socio-economic factors.
- Investigate educational enrollment rates and their implications for human capital development.
- Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
- Study labor market dynamics through indicators such as labor force participation and unemployment rates.
- Investigate the role of taxation and its impact on economic development.
- Explore urbanization trends and their social and environmental consequences.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset provides information on the Real GDP per capita for 30 countries and regions across Europe, from 1995 to 2023. The dataset includes real GDP per capita data, which is adjusted for inflation (constant prices), allowing comparisons over time across different countries. This data is critical for economic analysis, providing insights into the economic performance and living standards in these countries and regions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about countries per year in Luxembourg. It has 64 rows. It features 3 columns: country, and GDP.
Explore real GDP growth projections dataset, including insights into the impact of COVID-19 on economic trends. This dataset covers countries such as Spain, Australia, France, Italy, Brazil, and more.
growth rate, Real, COVID-19, GDP
Spain, Australia, France, Italy, Brazil, Argentina, United Kingdom, United States, Canada, Russia, Turkiye, World, China, Mexico, Korea, India, Saudi Arabia, South Africa, Germany, Indonesia, JapanFollow data.kapsarc.org for timely data to advance energy economics research..Source: OECD Economic Outlook database.- India projections are based on fiscal years, starting in April. The European Union is a full member of the G20, but the G20 aggregate only includes countries that are also members in their own right. Spain is a permanent invitee to the G20. World and G20 aggregates use moving nominal GDP weights at purchasing power parities. Difference in percentage points, based on rounded figures.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for GDP PER CAPITAL reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about countries per year in China. It has 64 rows. It features 3 columns: country, and GDP.
This dataset was created by Emmanuel Justine
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).
https://www.gnu.org/licenses/gpl-3.0.htmlhttps://www.gnu.org/licenses/gpl-3.0.html
This dataset comprises 204 entries and 38 attributes, providing a comprehensive analysis of key economic and social indicators across various countries. It includes a diverse range of metrics, allowing for in-depth exploration of global trends related to GDP, education, health, and environmental factors.
Key Features:
Applications and Uses:
Research and Analysis: Ideal for researchers studying the correlation between economic performance and social indicators. This dataset can help identify trends and patterns relevant to global development.
Policy Development: Policymakers can utilize this data to inform decisions on education, healthcare, and environmental policies, aiming to improve national outcomes.
Machine Learning and Data Science: Data scientists can apply machine learning techniques to predict economic trends, analyze social impacts, or classify countries based on various indicators.
Educational Purposes: Suitable for students and educators in fields like economics, sociology, and environmental science for practical data analysis exercises.
Visualization Projects: Perfect for creating compelling visualizations that illustrate relationships between different metrics, aiding in public understanding and engagement.
By leveraging this dataset, users can uncover insights into how different factors influence a country's development, making it a valuable resource for diverse applications across various fields.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about countries per year in Costa Rica. It has 64 rows. It features 4 columns: country, country full name, and GDP.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This dataset was created by Ali Tuncay
Released under MIT
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for GDP 2021 reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
This dataset shows the estimation of GDP by various International Organizations.
It shows the country, the region, the estimate and the year of estimate
Thanks to Wikipedia for providing this information.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.