4 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. Data set: 50 Muslim-majority countries and 50 richest non-Muslim countries...

    • figshare.com
    txt
    Updated Jun 1, 2023
    + more versions
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    Ponn P Mahayosnand; Gloria Gheno (2023). Data set: 50 Muslim-majority countries and 50 richest non-Muslim countries based on GDP: Total number of COVID-19 cases and deaths on September 18, 2020 [Dataset]. http://doi.org/10.6084/m9.figshare.14034938.v2
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Ponn P Mahayosnand; Gloria Gheno
    License

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

    Description

    Associated with manuscript titled: Fifty Muslim-majority countries have fewer COVID-19 cases and deaths than the 50 richest non-Muslim countriesThe objective of this research was to determine the difference in the total number of COVID-19 cases and deaths between Muslim-majority and non-Muslim countries, and investigate reasons for the disparities. Methods: The 50 Muslim-majority countries had more than 50.0% Muslims with an average of 87.5%. The non-Muslim country sample consisted of 50 countries with the highest GDP while omitting any Muslim-majority countries listed. The non-Muslim countries’ average percentage of Muslims was 4.7%. Data pulled on September 18, 2020 included the percentage of Muslim population per country by World Population Review15 and GDP per country, population count, and total number of COVID-19 cases and deaths by Worldometers.16 The data set was transferred via an Excel spreadsheet on September 23, 2020 and analyzed. To measure COVID-19’s incidence in the countries, three different Average Treatment Methods (ATE) were used to validate the results. Results published as a preprint at https://doi.org/10.31235/osf.io/84zq5(15) Muslim Majority Countries 2020 [Internet]. Walnut (CA): World Population Review. 2020- [Cited 2020 Sept 28]. Available from: http://worldpopulationreview.com/country-rankings/muslim-majority-countries (16) Worldometers.info. Worldometer. Dover (DE): Worldometer; 2020 [cited 2020 Sept 28]. Available from: http://worldometers.info

  3. Global Religious Demographics

    • kaggle.com
    zip
    Updated Dec 19, 2023
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    The Devastator (2023). Global Religious Demographics [Dataset]. https://www.kaggle.com/datasets/thedevastator/global-religious-demographics
    Explore at:
    zip(481071 bytes)Available download formats
    Dataset updated
    Dec 19, 2023
    Authors
    The Devastator
    Description

    Global Religious Demographics

    Global religious demographics over time

    By Throwback Thursday [source]

    About this dataset

    The dataset contains information on a wide range of religions, including Christianity, Judaism, Islam, Buddhism, Hinduism, Sikhism, Shintoism, Baha'i Faith, Taoism, Confucianism, Jainism, Zoroastrianism, Syncretic Religions (religious practices that blend elements from multiple faiths), Animism (belief in spiritual beings in nature), Non-Religious individuals or those without any religious affiliation.

    For each religion and region/country combination recorded in the dataset we have the following information:

    • Total population: The total population of the region or country.
    • Religious affiliation percentages: The percentages of the population that identify with specific religious affiliations.
    • Subgroup populations/percentages: The populations or percentages within specific denominations or sects of each religion.

    The dataset also provides additional variables like Year and State Name (for regional data) for further analysis.

    How to use the dataset

    • Understanding the Columns

      The dataset contains several columns with different categories of information. Here's a brief explanation of some important columns:

      • Year: The year in which the data was recorded.
      • Total Population: The total population of a country or region.
      • State Name (StateNme): The name of the state or region.

      Each religion has specific columns associated with it, such as Christianity, Buddhism, Islam, Hinduism, Judaism, Taoism, Shintoism etc., representing its percentage and population for each category/denomination within that religion.

    • Selecting Specific Data

      If you are interested in exploring data related to a particular religion or geographic location:

      • To filter data by Religion: Identify relevant columns associated with that religion such as 'Christianity', 'Buddhism', 'Islam', etc., and extract their respective percentage and population values for analysis.

        Example: If you want to analyze Christianity specifically, extract columns related to Christianity like 'Christianity (Percent)', 'Christianity (Population)', etc.

        Note: There might be multiple columns related to a specific religion indicating different categories or denominations within that religion.

      • To filter data by Geographic Location: Utilize the 'State Name' column ('StateNme') to segregate data corresponding to different states/regions.

        Example: If you want to analyze religious demographics for a particular state/region like California or India:

        i) Filter out rows where State Name is equal to California or India.

        ii) Extract relevant columns associated with your selected religion as mentioned above.

    • Finding Trends and Insights

      Once you have selected the specific data you are interested in, examine patterns and trends over time or across different regions.

      • Plotting data using visualizations: Use graphical tools such as line charts, bar charts, or pie charts to visualize how religious demographics have changed over the years or vary across different regions.

      • Analyzing population proportions: By comparing the percentage values of different religions for a given region or over time, you can gather insights into changes in religious diversity.

    • Comparing Religions

      If you wish to compare multiple religions:

    Research Ideas

    • Comparing religious affiliations across different countries or regions: With data on various religions such as Christianity, Islam, Buddhism, Judaism, Hinduism, etc., researchers can compare the religious affiliations of different countries or regions. This can help in understanding the cultural and religious diversity within different parts of the world.
    • Exploring the growth or decline of specific religions: By examining population numbers for specific religions such as Jainism, Taoism, Zoroastrianism, etc., this dataset can be used to investigate the growth or decline of these religious groups over time. Researchers can analyze factors contributing to their popularity or decline in particular regions or countries

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    See the dataset description for more information.

    Columns

    File: ThrowbackDataThursday 201912 - Religion.csv | Column name...

  4. 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.

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