100+ datasets found
  1. T

    GDP by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 29, 2011
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    TRADING ECONOMICS (2011). GDP by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/gdp
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jun 29, 2011
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

    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.

  2. T

    PRIVATE DEBT TO GDP by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 27, 2017
    + more versions
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    TRADING ECONOMICS (2017). PRIVATE DEBT TO GDP by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/private-debt-to-gdp
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    May 27, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

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

  3. A

    ‘Life Expectancy vs GDP, 1950-2018’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 13, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Life Expectancy vs GDP, 1950-2018’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-life-expectancy-vs-gdp-1950-2018-00c5/88f28a02/?iid=004-308&v=presentation
    Explore at:
    Dataset updated
    Feb 13, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Life Expectancy vs GDP, 1950-2018’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/luxoloshilofunde/life-expectancy-vs-gdp-19502018 on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    Context

    Life expectancy at birth is defined as the average number of years that a newborn could expect to live if he or she were to pass through life subject to the age-specific mortality rates of a given period. The years are from 1950 to 2018.

    Content

    For regional- and global-level data pre-1950, data from a study by Riley was used, which draws from over 700 sources to estimate life expectancy at birth from 1800 to 2001.

    Riley estimated life expectancy before 1800, which he calls "the pre-health transition period". "Health transitions began in different countries in different periods, as early as the 1770s in Denmark and as late as the 1970s in some countries of sub-Saharan Africa". As such, for the sake of consistency, we have assigned the period before the health transition to the year 1770. "The life expectancy values employed are averages of estimates for the period before the beginning of the transitions for countries within that region. ... This period has presumably the weakest basis, the largest margin of error, and the simplest method of deriving an estimate."

    For country-level data pre-1950, Clio Infra's dataset was used, compiled by Zijdeman and Ribeira da Silva (2015).

    For country-, regional- and global-level data post-1950, data published by the United Nations Population Division was used, since they are updated every year. This is possible because Riley writes that "for 1950-2001, I have drawn life expectancy estimates chiefly from various sources provided by the United Nations, the World Bank’s World Development Indicators, and the Human Mortality Database".

    For the Americas from 1950-2015, the population-weighted average of Northern America and Latin America and the Caribbean was taken, using UN Population Division estimates of population size.

    Acknowledgements

    Life expectancy:

    Data publisher's source: https://www.lifetable.de/RileyBib.pdf Data published by: James C. Riley (2005) – Estimates of Regional and Global Life Expectancy, 1800–2001. Issue Population and Development Review. Population and Development Review. Volume 31, Issue 3, pages 537–543, September 2005., Zijdeman, Richard; Ribeira da Silva, Filipa, 2015, "Life Expectancy at Birth (Total)", http://hdl.handle.net/10622/LKYT53, IISH Dataverse, V1, and UN Population Division (2019) Link: https://datasets.socialhistory.org/dataset.xhtml?persistentId=hdl:10622/LKYT53, http://onlinelibrary.wiley.com/doi/10.1111/j.1728-4457.2005.00083.x/epdf, https://population.un.org/wpp/Download/Standard/Population/ Dataset: https://ourworldindata.org/life-expectancy

    GDP per capita:

    Data publisher's source: The Maddison Project Database is based on the work of many researchers that have produced estimates of economic growth for individual countries. Data published by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update”. Link: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 Dataset: https://ourworldindata.org/life-expectancy

    Inspiration

    The life expectancy vs GDP per capita analysis.

    --- Original source retains full ownership of the source dataset ---

  4. T

    GOLD RESERVES by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2014
    + more versions
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    TRADING ECONOMICS (2014). GOLD RESERVES by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/gold-reserves
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    May 26, 2014
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

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

  5. w

    Income Distribution Database

    • data360.worldbank.org
    Updated Apr 18, 2025
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    (2025). Income Distribution Database [Dataset]. https://data360.worldbank.org/en/dataset/OECD_IDD
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    Dataset updated
    Apr 18, 2025
    Time period covered
    1974 - 2023
    Description

    The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.

    Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.

    Small changes in estimates between years should be treated with caution as they may not be statistically significant.

    Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

  6. T

    United States GDP

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States GDP [Dataset]. https://tradingeconomics.com/united-states/gdp
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    xml, excel, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    United States
    Description

    The Gross Domestic Product (GDP) in the United States was worth 29184.89 billion US dollars in 2024, according to official data from the World Bank. The GDP value of the United States represents 27.49 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  7. w

    Global Financial Inclusion (Global Findex) Database 2017 - Nepal

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Nov 1, 2018
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2018). Global Financial Inclusion (Global Findex) Database 2017 - Nepal [Dataset]. https://microdata.worldbank.org/index.php/catalog/3306
    Explore at:
    Dataset updated
    Nov 1, 2018
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2017
    Area covered
    Nepal
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    National coverage

    Analysis unit

    Individuals

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

    Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    The sample size was 1000.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

    Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

  8. Business Funding Data in El Salvador

    • kaggle.com
    Updated Sep 13, 2024
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    Techsalerator (2024). Business Funding Data in El Salvador [Dataset]. https://www.kaggle.com/datasets/techsalerator/business-funding-data-in-el-salvador
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 13, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    El Salvador
    Description

    Techsalerator’s Business Funding Data for El Salvador

    Techsalerator’s Business Funding Data for El Salvador provides a comprehensive and insightful collection of information essential for businesses, investors, and financial analysts. This dataset offers a deep dive into the funding activities of companies across various sectors in El Salvador, capturing and categorizing data related to their funding rounds, investment sources, and financial milestones.

    If you need the full dataset, reach out to us at info@techsalerator.com or https://www.techsalerator.com/contact-us.

    Techsalerator’s Business Funding Data for El Salvador

    Techsalerator’s Business Funding Data for El Salvador delivers a thorough overview of crucial information for businesses, investors, and financial analysts. This dataset provides an in-depth examination of funding activities across various sectors in El Salvador, detailing data related to funding rounds, investment sources, and key financial milestones.

    Top 5 Key Data Fields

    Company Name: Identifies the company receiving funding. This information helps investors identify potential opportunities and allows analysts to monitor funding trends within specific industries.

    Funding Amount: Shows the total amount of funding a company has received. Understanding these amounts reveals insights into the financial health and growth potential of businesses and the scale of investment activities.

    Funding Round: Indicates the stage of funding, such as seed, Series A, Series B, or later stages. This helps investors assess a business’s maturity and growth trajectory.

    Investor Name: Provides details about the investors or investment firms involved. Knowing the investors helps gauge the credibility of the funding source and their strategic interests.

    Investment Date: Records when the funding was completed. The timing of investments can reflect market trends, investor confidence, and potential impacts on a company’s future.

    Top 5 Funding Trends in El Salvador

    Infrastructure Development: Investments are being made in infrastructure projects such as roads, bridges, and energy initiatives. These projects are crucial for the country’s economic development and stability.

    Technology and Innovation: There is a growing focus on technology and innovation, with funding directed towards tech startups and digital transformation projects to drive economic growth and modernization.

    Agriculture and Agritech: Agriculture remains a vital sector, and funding is aimed at enhancing agricultural practices through technology and sustainable solutions to improve productivity and efficiency.

    Renewable Energy: Significant investments are being directed towards renewable energy projects, including solar and wind energy, to promote sustainability and reduce dependency on non-renewable resources.

    Education and Workforce Development: Funding is being allocated to educational programs and vocational training initiatives to improve literacy, enhance skills, and support workforce development.

    Top 5 Companies with Notable Funding Data in El Salvador

    Tigo El Salvador: A leading telecommunications provider, Tigo has received substantial funding to expand its network, enhance digital services, and support technological advancements.

    Grupo Calleja: This retail giant has attracted investment to support expansion efforts, improve operational efficiency, and invest in digital transformation.

    Banco Agrícola: The financial institution has garnered significant funding to enhance its banking services, expand its reach, and promote financial inclusion.

    Industrias La Constancia: Known for its manufacturing capabilities, this company has secured funding to support growth, innovation, and expansion of its product offerings.

    Fundación Salvador del Mundo: A prominent non-profit organization, it has received funding to support community development projects, education programs, and healthcare initiatives.

    Accessing Techsalerator’s Business Funding Data

    To obtain Techsalerator’s Business Funding Data for El Salvador, contact info@techsalerator.com with your specific needs. Techsalerator will provide a customized quote based on the required data fields and records, with delivery available within 24 hours. Ongoing access options can also be discussed.

    Included Data Fields

    Company Name Funding Amount Funding Round Investor Name Investment Date Funding Type (Equity, Debt, Grants, etc.) Sector Focus Deal Structure Investment Stage Contact Information For detailed insights into funding activities and financial trends in El Salvador, Techsalerator’s dataset is an invaluable resource for investors, business analysts, and financial professionals seeking informed, strategic decisions.

  9. w

    Global Financial Inclusion (Global Findex) Database 2017 - Madagascar

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Oct 31, 2018
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2018). Global Financial Inclusion (Global Findex) Database 2017 - Madagascar [Dataset]. https://microdata.worldbank.org/index.php/catalog/3287
    Explore at:
    Dataset updated
    Oct 31, 2018
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2017
    Area covered
    Madagascar
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    Sample excludes unsafe or inaccessible regions, representing about 25% of the population.

    Analysis unit

    Individuals

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

    Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    The sample size was 1000.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

    Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

  10. T

    GDP ANNUAL GROWTH RATE by Country in AFRICA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2025
    + more versions
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    TRADING ECONOMICS (2025). GDP ANNUAL GROWTH RATE by Country in AFRICA [Dataset]. https://tradingeconomics.com/country-list/gdp-annual-growth-rate?continent=africa
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    Africa
    Description

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

  11. o

    Large Landfill Sites (Historical data)

    • data.ontario.ca
    • catalogue.arctic-sdi.org
    • +2more
    csv, xls
    Updated May 24, 2023
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    Environment, Conservation and Parks (2023). Large Landfill Sites (Historical data) [Dataset]. https://data.ontario.ca/dataset/large-landfill-sites
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    xls(None), csv(None)Available download formats
    Dataset updated
    May 24, 2023
    Dataset provided by
    Ministry of the Environment, Conservation and Parkshttp://www.ontario.ca/ministry-environment-and-climate-change
    Authors
    Environment, Conservation and Parks
    License

    https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario

    Time period covered
    Jan 23, 2014
    Area covered
    Ontario
    Description

    Data with the following information for large landfills:

    • landfill capacity
    • fill rates
    • estimated remaining capacity
    • engineering designs
    • reporting and monitoring details

    This dataset was last updated in 2014 and contains out of date information. It has been replaced by the Ontario landfills dataset.

  12. N

    Median Household Income Variation by Family Size in Country Club Hills, IL:...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Median Household Income Variation by Family Size in Country Club Hills, IL: Comparative analysis across 7 household sizes [Dataset]. https://www.neilsberg.com/research/datasets/1acf7cd1-73fd-11ee-949f-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Country Club Hills, Illinois
    Variables measured
    Household size, Median Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across 7 household sizes (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out how household income varies with the size of the family unit. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median household incomes for various household sizes in Country Club Hills, IL, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

    Key observations

    • Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, all of the household sizes were found in Country Club Hills. Across the different household sizes in Country Club Hills the mean income is $88,306, and the standard deviation is $31,659. The coefficient of variation (CV) is 35.85%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
    • In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $46,212. It then further increased to $100,776 for 7-person households, the largest household size for which the bureau reported a median household income.

    https://i.neilsberg.com/ch/country-club-hills-il-median-household-income-by-household-size.jpeg" alt="Country Club Hills, IL median household income, by household size (in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Household Sizes:

    • 1-person households
    • 2-person households
    • 3-person households
    • 4-person households
    • 5-person households
    • 6-person households
    • 7-or-more-person households

    Variables / Data Columns

    • Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Country Club Hills median household income. You can refer the same here

  13. T

    Iran GDP

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Iran GDP [Dataset]. https://tradingeconomics.com/iran/gdp
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    Iran
    Description

    The Gross Domestic Product (GDP) in Iran was worth 436.91 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Iran represents 0.41 percent of the world economy. This dataset provides - Iran GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  14. N

    Age-wise distribution of Hill Country Village, TX household incomes:...

    • neilsberg.com
    csv, json
    Updated Jan 9, 2024
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    Neilsberg Research (2024). Age-wise distribution of Hill Country Village, TX household incomes: Comparative analysis across 16 income brackets [Dataset]. https://www.neilsberg.com/research/datasets/85c8459b-8dec-11ee-9302-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 9, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Hill Country Village, Texas
    Variables measured
    Number of households with income $200,000 or more, Number of households with income less than $10,000, Number of households with income between $15,000 - $19,999, Number of households with income between $20,000 - $24,999, Number of households with income between $25,000 - $29,999, Number of households with income between $30,000 - $34,999, Number of households with income between $35,000 - $39,999, Number of households with income between $40,000 - $44,999, Number of households with income between $45,000 - $49,999, Number of households with income between $50,000 - $59,999, and 6 more
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across 16 income brackets (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out the total number of households within a specific income bracket along with how many households with that income bracket for each of the 4 age cohorts (Under 25 years, 25-44 years, 45-64 years and 65 years and over). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Hill Country Village: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

    Key observations

    • Upon closer examination of the distribution of households among age brackets, it reveals that there are 0 households where the householder is under 25 years old, 27(9.44%) households with a householder aged between 25 and 44 years, 120(41.96%) households with a householder aged between 45 and 64 years, and 139(48.60%) households where the householder is over 65 years old.
    • The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 65 years and over bracket. This distribution hints at economic disparities within the city of Hill Country Village, showcasing varying income levels among different age demographics.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Income brackets:

    • Less than $10,000
    • $10,000 to $14,999
    • $15,000 to $19,999
    • $20,000 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $59,999
    • $60,000 to $74,999
    • $75,000 to $99,999
    • $100,000 to $124,999
    • $125,000 to $149,999
    • $150,000 to $199,999
    • $200,000 or more

    Variables / Data Columns

    • Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
    • Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
    • 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
    • 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
    • 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Hill Country Village median household income by age. You can refer the same here

  15. T

    Vietnam GDP

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 3, 2025
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    TRADING ECONOMICS (2025). Vietnam GDP [Dataset]. https://tradingeconomics.com/vietnam/gdp
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1985 - Dec 31, 2024
    Area covered
    Vietnam
    Description

    The Gross Domestic Product (GDP) in Vietnam was worth 476.39 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Vietnam represents 0.45 percent of the world economy. This dataset provides the latest reported value for - Vietnam GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  16. T

    GDP FROM AGRICULTURE by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 23, 2016
    + more versions
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    TRADING ECONOMICS (2016). GDP FROM AGRICULTURE by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/gdp-from-agriculture
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset updated
    Feb 23, 2016
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

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

  17. N

    Income Distribution by Quintile: Mean Household Income in Grant township,...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Income Distribution by Quintile: Mean Household Income in Grant township, Grand Traverse County, Michigan [Dataset]. https://www.neilsberg.com/research/datasets/949a4a4c-7479-11ee-949f-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Michigan, Grant Township, Grand Traverse County
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Grant township, Grand Traverse County, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 22,447, while the mean income for the highest quintile (20% of households with the highest income) is 203,020. This indicates that the top earners earn 9 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 313,194, which is 154.27% higher compared to the highest quintile, and 1395.26% higher compared to the lowest quintile.

    Mean household income by quintiles in Grant township, Grand Traverse County, Michigan (in 2022 inflation-adjusted dollars))

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Grant township median household income. You can refer the same here

  18. T

    United States Government Spending To GDP

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Government Spending To GDP [Dataset]. https://tradingeconomics.com/united-states/government-spending-to-gdp
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1900 - Dec 31, 2024
    Area covered
    United States
    Description

    Government spending in the United States was last recorded at 39.7 percent of GDP in 2024 . This dataset provides - United States Government Spending To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  19. T

    Ghana GDP

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +14more
    csv, excel, json, xml
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    TRADING ECONOMICS, Ghana GDP [Dataset]. https://tradingeconomics.com/ghana/gdp
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    Ghana
    Description

    The Gross Domestic Product (GDP) in Ghana was worth 82.83 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Ghana represents 0.08 percent of the world economy. This dataset provides the latest reported value for - Ghana GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. T

    China GDP Growth Rate

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Apr 16, 2025
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    TRADING ECONOMICS (2025). China GDP Growth Rate [Dataset]. https://tradingeconomics.com/china/gdp-growth
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Apr 16, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 2010 - Mar 31, 2025
    Area covered
    China
    Description

    The Gross Domestic Product (GDP) in China expanded 1.20 percent in the first quarter of 2025 over the previous quarter. This dataset provides - China GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Share
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TRADING ECONOMICS (2011). GDP by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/gdp

GDP by Country Dataset

GDP by Country Dataset (2025)

Explore at:
269 scholarly articles cite this dataset (View in Google Scholar)
csv, json, xml, excelAvailable download formats
Dataset updated
Jun 29, 2011
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
2025
Area covered
World
Description

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.

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