100+ datasets found
  1. Dataset for Stock Market Index of 7 Economies

    • kaggle.com
    zip
    Updated Jul 4, 2023
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    Saad Aziz (2023). Dataset for Stock Market Index of 7 Economies [Dataset]. https://www.kaggle.com/datasets/saadaziz1985/dataset-for-stock-market-index-of-7-countries
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    zip(1917326 bytes)Available download formats
    Dataset updated
    Jul 4, 2023
    Authors
    Saad Aziz
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context:

    The provided dataset is extracted from yahoo finance using pandas and yahoo finance library in python. This deals with stock market index of the world best economies. The code generated data from Jan 01, 2003 to Jun 30, 2023 that’s more than 20 years. There are 18 CSV files, dataset is generated for 16 different stock market indices comprising of 7 different countries. Below is the list of countries along with number of indices extracted through yahoo finance library, while two CSV files deals with annualized return and compound annual growth rate (CAGR) has been computed from the extracted data.

    Number of Countries & Index:

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F90ce8a986761636e3edbb49464b304d8%2FNumber%20of%20Index.JPG?generation=1688490342207096&alt=media" alt="">

    Content:

    Unit of analysis: Stock Market Index Analysis

    This dataset is useful for research purposes, particularly for conducting comparative analyses involving capital market performance and could be used along with other economic indicators.

    There are 18 distinct CSV files associated with this dataset. First 16 CSV files deals with number of indices and last two CSV file deals with annualized return of each year and CAGR of each index. If data in any column is blank, it portrays that index was launch in later years, for instance: Bse500 (India), this index launch in 2007, so earlier values are blank, similarly China_Top300 index launch in year 2021 so early fields are blank too.

    The extraction process involves applying different criteria, like in 16 CSV files all columns are included, Adj Close is used to calculate annualized return. The algorithm extracts data based on index name (code given by the yahoo finance) according start and end date.

    Annualized return and CAGR has been calculated and illustrated in below image along with machine readable file (CSV) attached to that.

    To extract the data provided in the attachment, various criteria were applied:

    1. Content Filtering: The data was filtered based on several attributes, including the index name, start and end date. This filtering process ensured that only relevant data meeting the specified criteria.

    2. Collaborative Filtering: Another filtering technique used was collaborative filtering using yahoo finance, which relies on index similarity. This approach involves finding indices that are similar to other index or extended dataset scope to other countries or economies. By leveraging this method, the algorithm identifies and extracts data based on similarities between indices.

    In the last two CSV files, one belongs to annualized return, that was calculated based on the Adj close column and new DataFrame created to store its outcome. Below is the image of annualized returns of all index (if unreadable, machine-readable or CSV format is attached with the dataset).

    Annualized Return:

    As far as annualised rate of return is concerned, most of the time India stock market indices leading, followed by USA, Canada and Japan stock market indices.

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F37645bd90623ea79f3708a958013c098%2FAnnualized%20Return.JPG?generation=1688525901452892&alt=media" alt="">

    Compound Annual Growth Rate (CAGR):

    The best performing index based on compound growth is Sensex (India) that comprises of top 30 companies is 15.60%, followed by Nifty500 (India) that is 11.34% and Nasdaq (USA) all is 10.60%.

    The worst performing index is China top300, however this is launch in 2021 (post pandemic), so would not possible to examine at that stage (due to less data availability). Furthermore, UK and Russia indices are also top 5 in the worst order.

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F58ae33f60a8800749f802b46ec1e07e7%2FCAGR.JPG?generation=1688490409606631&alt=media" alt="">

    Geography: Stock Market Index of the World Top Economies

    Time period: Jan 01, 2003 – June 30, 2023

    Variables: Stock Market Index Title, Open, High, Low, Close, Adj Close, Volume, Year, Month, Day, Yearly_Return and CAGR

    File Type: CSV file

    Inspiration:

    • Time series prediction model
    • Investment opportunities in world best economies
    • Comparative Analysis of past data with other stock market indices or other indices

    Disclaimer:

    This is not a financial advice; due diligence is required in each investment decision.

  2. d

    Economic Data | Global Economic Indicator Service | 34k macro-economic...

    • datarade.ai
    .csv, .xls, .txt
    Updated Feb 19, 2021
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    Exchange Data International (2021). Economic Data | Global Economic Indicator Service | 34k macro-economic indicators | updated 24/5 [Dataset]. https://datarade.ai/data-products/economic-indicator-service-exchange-data-international
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Feb 19, 2021
    Dataset authored and provided by
    Exchange Data International
    Area covered
    Equatorial Guinea, Cuba, United States of America, Mali, Morocco, Gabon, Nigeria, Malawi, Eritrea, Qatar
    Description

    The Economic Indicator Service (EIS) aims to deliver economic content to financial institutions on both buy and sell-side and service providers. This new service currently covers 34,351 recurring macro-economic indicators from 135 countries ( as of December 16, 2019 ) such as GDP data, unemployment releases, PMI numbers etc.

    Economic Indicator Service gathers the major economic events from a variety of regions and countries around the globe and provides an Economic Events Data feed and Economic Calendar service to our clients. This service includes all previous historic data on economic indicators that are currently available on the database.

    Depending on availability, information regarding economic indicators, including the details of the issuing agency as well as historical data series can be made accessible for the client. Key information about EIS: • Cloud-based service for Live Calendar – delivered via HTML/JavaScript application formats, which can then be embedded onto any website using iFrames • Alternatives methods available – such as API and JSON feed for the economic calendar that can be integrated into the company’s system • Live data – updated 24/5, immediately after the data has been released • Historical data – includes a feed of all previous economic indicators available We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. The calendar includes the following. • Recurring & Non-recurring indicators covering 136 countries across 21 regions. • Indicators showing high, medium, and low impact data. • Indicators showing actual, previous, and forecast data. • Indicators can be filtered across 16 subtypes. • News generation for selected high-impact data. • Indicator description and historical data up to the latest eight historical points with a chart.

  3. t

    Economic Activity YoY-2024-05-16

    • tipranks.com
    Updated May 16, 2024
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    (2024). Economic Activity YoY-2024-05-16 [Dataset]. https://www.tipranks.com/calendars/economic/economic-activity-yoy-6019
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    Dataset updated
    May 16, 2024
    Variables measured
    Actual, Forecast
    Description

    The 'Economic Activity YoY' in Portugal measures the year-over-year change in the level of economic activity, reflecting the overall health and growth of the economy.-2024-05-16

  4. Weekly Economic Calendar - for the week commencing 16 July 2018

    • data.nsw.gov.au
    • researchdata.edu.au
    pdf
    Updated Nov 14, 2025
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    NSW Government (2025). Weekly Economic Calendar - for the week commencing 16 July 2018 [Dataset]. https://data.nsw.gov.au/data/dataset/3-17097-weekly-economic-calendar---for-the-week-commencing-16-july-2018
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    pdf(19934)Available download formats
    Dataset updated
    Nov 14, 2025
    Dataset provided by
    Government of New South Waleshttp://nsw.gov.au/
    Authors
    NSW Government
    Description

    Weekly Economic Calendar shows future release dates of key economic data and publications used by NSW Treasury for monitoring and analysis.

    Note: This resource was originally published on opengov.nsw.gov.au. The OpenGov website has been retired. If you have any questions, please contact the Agency Services team at transfer@mhnsw.au

    Agency

    • Treasury
  5. A02 SA: Employment, unemployment and economic inactivity for people aged 16...

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated Nov 11, 2025
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    Office for National Statistics (2025). A02 SA: Employment, unemployment and economic inactivity for people aged 16 and over and aged from 16 to 64 (seasonally adjusted) [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/employmentunemploymentandeconomicinactivityforpeopleaged16andoverandagedfrom16to64seasonallyadjusteda02sa
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 11, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Labour Force Survey summary data, including employment, unemployment and economic inactivity levels and rates, UK, rolling three-monthly figures published monthly, seasonally adjusted. These are official statistics in development.

  6. U

    United States FRB Cleveland: 16 % Trimmed Mean CPI: YoY

    • ceicdata.com
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    CEICdata.com, United States FRB Cleveland: 16 % Trimmed Mean CPI: YoY [Dataset]. https://www.ceicdata.com/en/united-states/trimmed-mean-cpi/frb-cleveland-16--trimmed-mean-cpi-yoy
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    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Apr 1, 2017 - Mar 1, 2018
    Area covered
    United States
    Variables measured
    Consumer Prices
    Description

    United States FRB Cleveland: 16 % Trimmed Mean Consumer Price Index (CPI): YoY data was reported at 2.206 % in Oct 2018. This records an increase from the previous number of 2.164 % for Sep 2018. United States FRB Cleveland: 16 % Trimmed Mean Consumer Price Index (CPI): YoY data is updated monthly, averaging 2.573 % from Dec 1983 (Median) to Oct 2018, with 419 observations. The data reached an all-time high of 5.094 % in Sep 1990 and a record low of 0.749 % in Oct 2010. United States FRB Cleveland: 16 % Trimmed Mean Consumer Price Index (CPI): YoY data remains active status in CEIC and is reported by Federal Reserve Bank of Cleveland. The data is categorized under Global Database’s United States – Table US.I040: Trimmed Mean CPI.

  7. U

    United States Unemployment: Age 16 to 19

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). United States Unemployment: Age 16 to 19 [Dataset]. https://www.ceicdata.com/en/united-states/current-population-survey-unemployment/unemployment-age-16-to-19
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    May 1, 2017 - Apr 1, 2018
    Area covered
    United States
    Variables measured
    Unemployment
    Description

    United States Unemployment: Age 16 to 19 data was reported at 664.000 Person th in Oct 2018. This records a decrease from the previous number of 686.000 Person th for Sep 2018. United States Unemployment: Age 16 to 19 data is updated monthly, averaging 1,154.500 Person th from Jan 1948 (Median) to Oct 2018, with 850 observations. The data reached an all-time high of 2,527.000 Person th in Jun 1983 and a record low of 228.000 Person th in Oct 1951. United States Unemployment: Age 16 to 19 data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G016: Current Population Survey: Unemployment.

  8. t

    ZEW Economic Sentiment Index-2024-07-16

    • tipranks.com
    Updated Jul 16, 2024
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    (2024). ZEW Economic Sentiment Index-2024-07-16 [Dataset]. https://www.tipranks.com/calendars/economic/zew-economic-sentiment-index-6164
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    Dataset updated
    Jul 16, 2024
    Variables measured
    Actual, Forecast
    Description

    The ZEW Economic Sentiment Index for the EuroZone is a leading indicator that measures the economic outlook of institutional investors and analysts for the next six months.-2024-07-16

  9. F

    Employment Level - Persons At Work 1-34 Hours, Economic Reasons, All...

    • fred.stlouisfed.org
    json
    Updated Nov 20, 2025
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    (2025). Employment Level - Persons At Work 1-34 Hours, Economic Reasons, All Industries [Dataset]. https://fred.stlouisfed.org/series/LNU02032194
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Nov 20, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employment Level - Persons At Work 1-34 Hours, Economic Reasons, All Industries (LNU02032194) from May 1955 to Sep 2025 about hours, 16 years +, household survey, employment, industry, and USA.

  10. d

    SASP Target 16 - Economic Disadvantage - Dataset - data.sa.gov.au

    • data.sa.gov.au
    Updated Jul 2, 2015
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    (2015). SASP Target 16 - Economic Disadvantage - Dataset - data.sa.gov.au [Dataset]. https://data.sa.gov.au/data/dataset/sasp-target-16-economic-disadvantage
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    Dataset updated
    Jul 2, 2015
    License

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

    Area covered
    South Australia
    Description

    Increase by 2 percentage points the share of total household income earned by low income South Australians.

  11. Population 16 years of age and over by the relation with the economic...

    • ine.es
    csv, html, json +4
    Updated Feb 28, 2025
    + more versions
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    INE - Instituto Nacional de Estadística (2025). Population 16 years of age and over by the relation with the economic activity, sex and age group [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=65948&L=1
    Explore at:
    json, txt, html, csv, text/pc-axis, xlsx, xlsAvailable download formats
    Dataset updated
    Feb 28, 2025
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2006 - Jan 1, 2024
    Variables measured
    Age, Sex, Type of data, National Total, Relationship with the economic activity
    Description

    Economically Active Population Survey: Population 16 years of age and over by the relation with the economic activity, sex and age group. Annual. National.

  12. Population 16 years of age and over by the relation with the economic...

    • ine.es
    csv, html, json +4
    Updated Jan 26, 2024
    + more versions
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    INE - Instituto Nacional de Estadística (2024). Population 16 years of age and over by the relation with the economic activity, sex and province [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=3988&L=1
    Explore at:
    xls, txt, csv, text/pc-axis, html, xlsx, jsonAvailable download formats
    Dataset updated
    Jan 26, 2024
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2021 - Oct 1, 2023
    Variables measured
    Age, Sex, Provinces, Type of data, Relationship with the economic activity
    Description

    Economically Active Population Survey: Population 16 years of age and over by the relation with the economic activity, sex and province. Quarterly. Provinces.

  13. Persons, by income decile per consumption unit and relationship with...

    • ine.es
    csv, html, json +4
    Updated Nov 20, 2013
    + more versions
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    INE - Instituto Nacional de Estadística (2013). Persons, by income decile per consumption unit and relationship with economic activity (persons aged 16 years old and over). [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=4668&L=1
    Explore at:
    html, csv, txt, xlsx, xls, text/pc-axis, jsonAvailable download formats
    Dataset updated
    Nov 20, 2013
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2004 - Jan 1, 2012
    Variables measured
    Type of data, National Total, Age semi-brackets, Relationship with the activity, Decile of income per unit of consumption (year prior to the interview)
    Description

    Living Conditions Survey (LCS): Persons, by income decile per consumption unit and relationship with economic activity (persons aged 16 years old and over). Annual. National.

  14. N

    Income Bracket Analysis by Age Group Dataset: Age-Wise Distribution of...

    • neilsberg.com
    csv, json
    Updated Feb 25, 2025
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    Neilsberg Research (2025). Income Bracket Analysis by Age Group Dataset: Age-Wise Distribution of Economy, IN Household Incomes Across 16 Income Brackets // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/f3496638-f353-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 25, 2025
    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
    IN, Economy
    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) 2019-2023 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 Economy: 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, 10(16.95%) households with a householder aged between 25 and 44 years, 26(44.07%) households with a householder aged between 45 and 64 years, and 23(38.98%) 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 45 to 64 years bracket. This distribution hints at economic disparities within the town of Economy, 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) 2019-2023 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 Economy median household income by age. You can refer the same here

  15. Population aged 16 and over by Autonomous Community and relationship with...

    • ine.es
    csv, html, json +4
    Updated Jan 26, 2024
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    INE - Instituto Nacional de Estadística (2024). Population aged 16 and over by Autonomous Community and relationship with economic activity in the current quarter according to their relationship with economic activity in the previous quarter [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=8284&L=1
    Explore at:
    txt, json, csv, text/pc-axis, html, xls, xlsxAvailable download formats
    Dataset updated
    Jan 26, 2024
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2021 - Oct 1, 2023
    Variables measured
    Sex, Type of data, Age semi-intervals, Autonomous Comunity, Relationship with economic activity in the current quarter, Relationship with economic activity in the previous quarter
    Description

    Economically Active Population Flows: Population aged 16 and over by Autonomous Community and relationship with economic activity in the current quarter according to their relationship with economic activity in the previous quarter. Quarterly. Autonomous Communities and Cities.

  16. Population 16 years old and over in relation with the economic activity, sex...

    • ine.es
    csv, html, json +4
    Updated Oct 24, 2025
    + more versions
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    INE - Instituto Nacional de Estadística (2025). Population 16 years old and over in relation with the economic activity, sex and age group, by Autonomous Community [Dataset]. https://ine.es/jaxiT3/Tabla.htm?t=65292&L=1
    Explore at:
    csv, xlsx, json, txt, html, text/pc-axis, xlsAvailable download formats
    Dataset updated
    Oct 24, 2025
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2002 - Jul 1, 2025
    Variables measured
    Age, Sex, Type of data, Autonomous Communities and Cities, Relationship with the economic activity
    Description

    Economically Active Population Survey: Population 16 years old and over in relation with the economic activity, sex and age group, by Autonomous Community. Quarterly. Autonomous Communities and Cities.

  17. g

    Population aged 16 and over according to economic activity, sector of...

    • gimi9.com
    + more versions
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    Population aged 16 and over according to economic activity, sector of activity and sex. | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_5b7d0d403ba18847fd3ce2aa69a6ff1b931be6c0/
    Explore at:
    License

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

    Description

    🇪🇸 스페인 English Exploitation of microdata, tabulation, production and dissemination of data corresponding to Aragon of the EPA carried out by the INE.

  18. Data from: Longer-Run Trends and the U.S. Economy

    • clevelandfed.org
    Updated May 16, 2023
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    Federal Reserve Bank of Cleveland (2023). Longer-Run Trends and the U.S. Economy [Dataset]. https://www.clevelandfed.org/collections/speeches/2023/sp-20230516-longer-run-trends-us-economy
    Explore at:
    Dataset updated
    May 16, 2023
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    Area covered
    United States
    Description

    Loretta J. Mester-President and Chief Executive Officer-Federal Reserve Bank of Cleveland-The Global Interdependence Center Central Banking Series, Dublin, Ireland , May 16, 2023, 8:15 a.m. EDT

  19. g

    Uncertainty rate – Populations aged 16-84 who have experienced economic...

    • gimi9.com
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    Uncertainty rate – Populations aged 16-84 who have experienced economic crisis, share (%) | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_http-api-kolada-se-v2-kpi-u01507/
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    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    kommun ra_det-fo_r-fra_mjande-av-kommunala-analyser-kolada region

  20. Percentage of persons with disabilities, 16 to 64 years old, by province,...

    • ine.es
    csv, html, json +4
    Updated Jan 14, 2010
    + more versions
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    INE - Instituto Nacional de Estadística (2010). Percentage of persons with disabilities, 16 to 64 years old, by province, relation with economic activity and sex [Dataset]. https://www.ine.es/jaxi/Tabla.htm?tpx=58358&L=1
    Explore at:
    txt, xls, csv, xlsx, text/pc-axis, json, htmlAvailable download formats
    Dataset updated
    Jan 14, 2010
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Variables measured
    Sex, Province, Economic activity
    Description

    Disability, Independence and Dependency Situations Survey: Percentage of persons with disabilities, 16 to 64 years old, by province, relation with economic activity and sex. Province.

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Saad Aziz (2023). Dataset for Stock Market Index of 7 Economies [Dataset]. https://www.kaggle.com/datasets/saadaziz1985/dataset-for-stock-market-index-of-7-countries
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Dataset for Stock Market Index of 7 Economies

Time Series Dataset for Stock Market Indices of the 7 Top Economies of the World

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zip(1917326 bytes)Available download formats
Dataset updated
Jul 4, 2023
Authors
Saad Aziz
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

Context:

The provided dataset is extracted from yahoo finance using pandas and yahoo finance library in python. This deals with stock market index of the world best economies. The code generated data from Jan 01, 2003 to Jun 30, 2023 that’s more than 20 years. There are 18 CSV files, dataset is generated for 16 different stock market indices comprising of 7 different countries. Below is the list of countries along with number of indices extracted through yahoo finance library, while two CSV files deals with annualized return and compound annual growth rate (CAGR) has been computed from the extracted data.

Number of Countries & Index:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F90ce8a986761636e3edbb49464b304d8%2FNumber%20of%20Index.JPG?generation=1688490342207096&alt=media" alt="">

Content:

Unit of analysis: Stock Market Index Analysis

This dataset is useful for research purposes, particularly for conducting comparative analyses involving capital market performance and could be used along with other economic indicators.

There are 18 distinct CSV files associated with this dataset. First 16 CSV files deals with number of indices and last two CSV file deals with annualized return of each year and CAGR of each index. If data in any column is blank, it portrays that index was launch in later years, for instance: Bse500 (India), this index launch in 2007, so earlier values are blank, similarly China_Top300 index launch in year 2021 so early fields are blank too.

The extraction process involves applying different criteria, like in 16 CSV files all columns are included, Adj Close is used to calculate annualized return. The algorithm extracts data based on index name (code given by the yahoo finance) according start and end date.

Annualized return and CAGR has been calculated and illustrated in below image along with machine readable file (CSV) attached to that.

To extract the data provided in the attachment, various criteria were applied:

  1. Content Filtering: The data was filtered based on several attributes, including the index name, start and end date. This filtering process ensured that only relevant data meeting the specified criteria.

  2. Collaborative Filtering: Another filtering technique used was collaborative filtering using yahoo finance, which relies on index similarity. This approach involves finding indices that are similar to other index or extended dataset scope to other countries or economies. By leveraging this method, the algorithm identifies and extracts data based on similarities between indices.

In the last two CSV files, one belongs to annualized return, that was calculated based on the Adj close column and new DataFrame created to store its outcome. Below is the image of annualized returns of all index (if unreadable, machine-readable or CSV format is attached with the dataset).

Annualized Return:

As far as annualised rate of return is concerned, most of the time India stock market indices leading, followed by USA, Canada and Japan stock market indices.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F37645bd90623ea79f3708a958013c098%2FAnnualized%20Return.JPG?generation=1688525901452892&alt=media" alt="">

Compound Annual Growth Rate (CAGR):

The best performing index based on compound growth is Sensex (India) that comprises of top 30 companies is 15.60%, followed by Nifty500 (India) that is 11.34% and Nasdaq (USA) all is 10.60%.

The worst performing index is China top300, however this is launch in 2021 (post pandemic), so would not possible to examine at that stage (due to less data availability). Furthermore, UK and Russia indices are also top 5 in the worst order.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F58ae33f60a8800749f802b46ec1e07e7%2FCAGR.JPG?generation=1688490409606631&alt=media" alt="">

Geography: Stock Market Index of the World Top Economies

Time period: Jan 01, 2003 – June 30, 2023

Variables: Stock Market Index Title, Open, High, Low, Close, Adj Close, Volume, Year, Month, Day, Yearly_Return and CAGR

File Type: CSV file

Inspiration:

  • Time series prediction model
  • Investment opportunities in world best economies
  • Comparative Analysis of past data with other stock market indices or other indices

Disclaimer:

This is not a financial advice; due diligence is required in each investment decision.

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