9 datasets found
  1. Religious Populations Worldwide

    • kaggle.com
    zip
    Updated Dec 8, 2023
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    The Devastator (2023). Religious Populations Worldwide [Dataset]. https://www.kaggle.com/datasets/thedevastator/religious-populations-worldwide
    Explore at:
    zip(481071 bytes)Available download formats
    Dataset updated
    Dec 8, 2023
    Authors
    The Devastator
    Description

    Religious Populations Worldwide

    Religious Populations Worldwide by Year and Category

    By Throwback Thursday [source]

    About this dataset

    The dataset includes data on Christianity, Islam, Judaism, Buddhism, Hinduism, Sikhism, Shintoism, Baha'i Faith, Taoism, Confucianism, Jainism and various other syncretic and animist religions. For each religion or denomination category, it provides both the total population count and the percentage representation in relation to the overall population.

    Additionally, - Columns labeled with Population provide numeric values representing the total number of individuals belonging to a particular religion or denomination. - Columns labeled with Percent represent numerical values indicating the percentage of individuals belonging to a specific religion or denomination within a given population. - Columns that begin with ** indicate primary categories (e.g., Christianity), while columns that do not have this prefix refer to subcategories (e.g., Christianity - Roman Catholics).

    In addition to providing precise data about specific religions or denominations globally throughout multiple years,this dataset also records information about geographical locations by including state or country names under StateNme.

    This comprehensive dataset is valuable for researchers seeking information on global religious trends and can be used for analysis in fields such as sociology, anthropology studies cultural studies among others

    How to use the dataset

    Introduction:

    • Understanding the Columns:

    • Year: Represents the year in which the data was recorded.

    • StateNme: Represents the name of the state or country for which data is recorded.

    • Population: Represents the total population of individuals.

    • Total Religious: Represents the total percentage and population of individuals who identify as religious, regardless of specific religion.

    • Non Religious: Represents the percentage and population of individuals who identify as non-religious or atheists.

    • Identifying Specific Religions: The dataset includes columns for different religions such as Christianity, Judaism, Islam, Buddhism, Hinduism, etc. Each religion is further categorized into specific denominations or types within that religion (e.g., Roman Catholics within Christianity). You can find relevant information about these religions by focusing on specific columns related to each one.

    • Analyzing Percentages vs. Population: Some columns provide percentages while others provide actual population numbers for each category. Depending on your analysis requirement, you can choose either column type for your calculations and comparisons.

    • Accessing Historical Data: The dataset includes records from multiple years allowing you to analyze trends in religious populations over time. You can filter data based on specific years using Excel filters or programming languages like Python.

    • Filtering Data by State/Country: If you are interested in understanding religious populations in a particular state or country, use filters to focus on that region's data only.

    Example - Extracting Information:

    Let's say you want to analyze Hinduism's growth globally from 2000 onwards:

    • Identify Relevant Columns:
    • Year: to filter data from 2000 onwards.
    • Hindu - Total (Percent): to analyze the percentage of individuals identifying as Hindus globally.

    • Filter Data:

    • Set a filter on the Year column and select values greater than or equal to 2000.

    • Look for rows where Hindu - Total (Percent) has values.

    • Analyze Results: You can now visualize and calculate the growth of Hinduism worldwide after filtering out irrelevant data. Use statistical methods or graphical representations like line charts to understand trends over time.

    Conclusion: This guide has provided you with an overview of how to use the Rel

    Research Ideas

    • Comparing religious populations across different countries: With data available for different states and countries, this dataset allows for comparisons of religious populations across regions. Researchers can analyze how different religions are distributed geographically and compare their percentages or total populations across various locations.
    • Studying the impact of historical events on religious demographics: Since the dataset includes records categorized by year, it can be used to study how historical events such as wars, migration, or political changes have influenced religious demographics over time. By comparing population numbers before and after specific events, resea...
  2. India Survey Dataset

    • pewresearch.org
    Updated Dec 7, 2021
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    Neha Sahgal; Jonathan Evans (2021). India Survey Dataset [Dataset]. http://doi.org/10.58094/rfte-a185
    Explore at:
    Dataset updated
    Dec 7, 2021
    Dataset provided by
    Pew Research Centerhttp://pewresearch.org/
    datacite
    Authors
    Neha Sahgal; Jonathan Evans
    License

    https://www.pewresearch.org/about/terms-and-conditions/https://www.pewresearch.org/about/terms-and-conditions/

    Dataset funded by
    The Pew Charitable Trustshttps://www.pew.org/
    John Templeton Foundation
    Description

    Pew Research Center conducted face-to-face surveys among 29,999 adults (ages 18 and older) across 26 Indian states and three union territories in 17 languages. The sample includes interviews with 22,975 Hindus, 3,336 Muslims, 1,782 Sikhs, 1,011 Christians, 719 Buddhists and 109 Jains. An additional 67 respondents belong to other religions or are religiously unaffiliated. Six groups were targeted for oversampling as part of the survey design: Muslims, Christians, Sikhs, Buddhists, Jains and those living in the Northeast region. Interviews were conducted under the direction of RTI International from November 17, 2019, to March 23, 2020. Data collection used computer-assisted personal interviews (CAPI) after random selection of households.

    This project was produced by Pew Research Center as part of the Pew-Templeton Global Religious Futures project, which analyzes religious change and its impact on societies around the world. Funding for the Global Religious Futures project comes from The Pew Charitable Trusts and the John Templeton Foundation.

    Two reports focused on the findings from this data: •Religion in India: Tolerance and Segregation: https://www.pewresearch.org/religion/2021/06/29/religion-in-india-tolerance-and-segregation/ •How Indians View Gender Roles in Families and Society: https://www.pewresearch.org/religion/2022/03/02/how-indians-view-gender-roles-in-families-and-society/

  3. I

    India Census: Population: by Religion: Hindu: Male

    • ceicdata.com
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    CEICdata.com, India Census: Population: by Religion: Hindu: Male [Dataset]. https://www.ceicdata.com/en/india/census-population-by-religion/census-population-by-religion-hindu-male
    Explore at:
    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
    Mar 1, 2001 - Mar 1, 2011
    Area covered
    India
    Variables measured
    Population
    Description

    India Census: Population: by Religion: Hindu: Male data was reported at 498,306,968.000 Person in 2011. This records an increase from the previous number of 428,678,554.000 Person for 2001. India Census: Population: by Religion: Hindu: Male data is updated yearly, averaging 463,492,761.000 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 498,306,968.000 Person in 2011 and a record low of 428,678,554.000 Person in 2001. India Census: Population: by Religion: Hindu: Male data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

  4. Dataset of Global Religious Composition Estimates for 2010 and 2020

    • pewresearch.org
    Updated 2025
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    Conrad Hackett; Marcin Stonawski; Yunping Tong; Stephanie Kramer; Anne Fengyan Shi (2025). Dataset of Global Religious Composition Estimates for 2010 and 2020 [Dataset]. http://doi.org/10.58094/vhrw-k516
    Explore at:
    Dataset updated
    2025
    Dataset provided by
    Pew Research Centerhttp://pewresearch.org/
    datacite
    Authors
    Conrad Hackett; Marcin Stonawski; Yunping Tong; Stephanie Kramer; Anne Fengyan Shi
    License

    https://www.pewresearch.org/about/terms-and-conditions/https://www.pewresearch.org/about/terms-and-conditions/

    Dataset funded by
    John Templeton Foundationhttp://templeton.org/
    Pew Charitable Trusts
    Description

    This dataset describes the world’s religious makeup in 2020 and 2010. We focus on seven categories: Christians, Muslims, Hindus, Buddhists, Jews, people who belong to other religions, and those who are religiously unaffiliated. This analysis is based on more than 2,700 sources of data, including national censuses, large-scale demographic surveys, general population surveys and population registers. For more information about this data, see the associated Pew Research Center report "How the Global Religious Landscape Changed From 2010 to 2020."

  5. Indian Diaspora: Global Distribution

    • kaggle.com
    zip
    Updated Jan 19, 2025
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    Arpit Singh (2025). Indian Diaspora: Global Distribution [Dataset]. https://www.kaggle.com/datasets/arpitsinghaiml/indian-populations-per-country
    Explore at:
    zip(2866 bytes)Available download formats
    Dataset updated
    Jan 19, 2025
    Authors
    Arpit Singh
    License

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

    Area covered
    India
    Description

    This dataset provides an overview of the Indian diaspora worldwide, encompassing:

    • Non-Resident Indians (NRIs): Individuals of Indian origin residing outside India who hold Indian citizenship.
    • Persons of Indian Origin (PIOs): Individuals of Indian origin residing outside India who do not hold Indian citizenship.
    • Overseas Indians: A broader term encompassing both NRIs and PIOs.

    The data includes estimates for 201 countries, offering insights into the distribution and size of the Indian diaspora across the globe.

  6. BRAIN DRAIN| Indians Departing Homeland | 2022

    • kaggle.com
    zip
    Updated Jan 23, 2024
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    DipDS109 (2024). BRAIN DRAIN| Indians Departing Homeland | 2022 [Dataset]. https://www.kaggle.com/datasets/dipds109/brain-drain-indians-departing-india-2022
    Explore at:
    zip(13197 bytes)Available download formats
    Dataset updated
    Jan 23, 2024
    Authors
    DipDS109
    License

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

    Area covered
    India
    Description

    The dataset provides a comprehensive overview of international travel patterns, segmented by age groups and average duration of stay across various regions and specific countries. The data includes the number of departures from each region to destinations around the world, with a granular breakdown of traveler age ranges: 0-14, 15-24, 25-34, 35-44, 45-54, 55-64, and 65 and above. Each region and country listed reveals the average length of stay for travelers, offering insights into travel preferences and behaviors. The dataset covers a broad spectrum of geographic locales, including North America, Central & South America, Western and Eastern Europe, Africa, West Asia, South Asia, South East Asia, East Asia, and Australasia, with an additional category for unspecified destinations. This data can be instrumental in understanding travel trends, planning tourism services, and analyzing market segments within the travel industry.

  7. I

    India Census: Population: by Religion: Muslim: Urban

    • ceicdata.com
    Updated Apr 7, 2022
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    CEICdata.com (2022). India Census: Population: by Religion: Muslim: Urban [Dataset]. https://www.ceicdata.com/en/india/census-population-by-religion/census-population-by-religion-muslim-urban
    Explore at:
    Dataset updated
    Apr 7, 2022
    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
    Mar 1, 2001 - Mar 1, 2011
    Area covered
    India
    Variables measured
    Population
    Description

    India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

  8. [Global Dataset] Pima Indians Diabetes

    • kaggle.com
    zip
    Updated Apr 30, 2021
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    Manas Garg (2021). [Global Dataset] Pima Indians Diabetes [Dataset]. https://www.kaggle.com/gargmanas/pima-indians-diabetes
    Explore at:
    zip(9001 bytes)Available download formats
    Dataset updated
    Apr 30, 2021
    Authors
    Manas Garg
    License

    http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

    Description

    Context

    Share key insights, awesome visualizations, or simply discuss advantages of data, any observed or known properties, challenges, problems, corrections, and any other helpful comments! Post and discuss recent published works that utilize this dataset (including your own). Any and all feedback is welcome and encouraged.

  9. f

    Comparing the average time performance, in seconds, of the GLocal-LS-SVM...

    • figshare.com
    xls
    Updated Jun 21, 2023
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    Ahmed Youssef Ali Amer (2023). Comparing the average time performance, in seconds, of the GLocal-LS-SVM model to the global LS-SVM model, Glocal-SVM, and standard SVM applied to the Pima Indians diabetes dataset. [Dataset]. http://doi.org/10.1371/journal.pone.0285131.t008
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ahmed Youssef Ali Amer
    License

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

    Description

    Comparing the average time performance, in seconds, of the GLocal-LS-SVM model to the global LS-SVM model, Glocal-SVM, and standard SVM applied to the Pima Indians diabetes dataset.

  10. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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The Devastator (2023). Religious Populations Worldwide [Dataset]. https://www.kaggle.com/datasets/thedevastator/religious-populations-worldwide
Organization logo

Religious Populations Worldwide

Religious Populations Worldwide by Year and Category

Explore at:
15 scholarly articles cite this dataset (View in Google Scholar)
zip(481071 bytes)Available download formats
Dataset updated
Dec 8, 2023
Authors
The Devastator
Description

Religious Populations Worldwide

Religious Populations Worldwide by Year and Category

By Throwback Thursday [source]

About this dataset

The dataset includes data on Christianity, Islam, Judaism, Buddhism, Hinduism, Sikhism, Shintoism, Baha'i Faith, Taoism, Confucianism, Jainism and various other syncretic and animist religions. For each religion or denomination category, it provides both the total population count and the percentage representation in relation to the overall population.

Additionally, - Columns labeled with Population provide numeric values representing the total number of individuals belonging to a particular religion or denomination. - Columns labeled with Percent represent numerical values indicating the percentage of individuals belonging to a specific religion or denomination within a given population. - Columns that begin with ** indicate primary categories (e.g., Christianity), while columns that do not have this prefix refer to subcategories (e.g., Christianity - Roman Catholics).

In addition to providing precise data about specific religions or denominations globally throughout multiple years,this dataset also records information about geographical locations by including state or country names under StateNme.

This comprehensive dataset is valuable for researchers seeking information on global religious trends and can be used for analysis in fields such as sociology, anthropology studies cultural studies among others

How to use the dataset

Introduction:

  • Understanding the Columns:

  • Year: Represents the year in which the data was recorded.

  • StateNme: Represents the name of the state or country for which data is recorded.

  • Population: Represents the total population of individuals.

  • Total Religious: Represents the total percentage and population of individuals who identify as religious, regardless of specific religion.

  • Non Religious: Represents the percentage and population of individuals who identify as non-religious or atheists.

  • Identifying Specific Religions: The dataset includes columns for different religions such as Christianity, Judaism, Islam, Buddhism, Hinduism, etc. Each religion is further categorized into specific denominations or types within that religion (e.g., Roman Catholics within Christianity). You can find relevant information about these religions by focusing on specific columns related to each one.

  • Analyzing Percentages vs. Population: Some columns provide percentages while others provide actual population numbers for each category. Depending on your analysis requirement, you can choose either column type for your calculations and comparisons.

  • Accessing Historical Data: The dataset includes records from multiple years allowing you to analyze trends in religious populations over time. You can filter data based on specific years using Excel filters or programming languages like Python.

  • Filtering Data by State/Country: If you are interested in understanding religious populations in a particular state or country, use filters to focus on that region's data only.

Example - Extracting Information:

Let's say you want to analyze Hinduism's growth globally from 2000 onwards:

  • Identify Relevant Columns:
  • Year: to filter data from 2000 onwards.
  • Hindu - Total (Percent): to analyze the percentage of individuals identifying as Hindus globally.

  • Filter Data:

  • Set a filter on the Year column and select values greater than or equal to 2000.

  • Look for rows where Hindu - Total (Percent) has values.

  • Analyze Results: You can now visualize and calculate the growth of Hinduism worldwide after filtering out irrelevant data. Use statistical methods or graphical representations like line charts to understand trends over time.

Conclusion: This guide has provided you with an overview of how to use the Rel

Research Ideas

  • Comparing religious populations across different countries: With data available for different states and countries, this dataset allows for comparisons of religious populations across regions. Researchers can analyze how different religions are distributed geographically and compare their percentages or total populations across various locations.
  • Studying the impact of historical events on religious demographics: Since the dataset includes records categorized by year, it can be used to study how historical events such as wars, migration, or political changes have influenced religious demographics over time. By comparing population numbers before and after specific events, resea...
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