2 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. a

    OpenStreetMap - Place of Worship (Polygon)

    • up-state-observatory-esriindia1.hub.arcgis.com
    • goa-state-gis-esriindia1.hub.arcgis.com
    Updated Mar 25, 2022
    + more versions
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    GIS Online (2022). OpenStreetMap - Place of Worship (Polygon) [Dataset]. https://up-state-observatory-esriindia1.hub.arcgis.com/datasets/openstreetmap-place-of-worship-polygon
    Explore at:
    Dataset updated
    Mar 25, 2022
    Dataset authored and provided by
    GIS Online
    Area covered
    Description

    This item contains places of worship layer from OSM (OpenStreetMap) in India and contains information about Buddhist, Christian, Christian Anglican, Christian Catholic etc.OSM is a collaborative, open project to create a freely available and editable map of the world. Geographic information about streets, rivers, borders, points of interest and areas are collected worldwide and stored in a freely accessible database. Everyone can participate and contribute to OSM. The geographic information available on OSM relies entirely on volunteers or contributors.The attributes are given below:BuddhistChristianChristian AnglicanChristian CatholicChristian EvangelicalChristian LutheranChristian MethodistChristian OrthodoxChristian ProtestantHinduJewishMuslimMuslim ShiaMuslim SunniSikhTaoistThese map layers are offered by Esri India Content. If you have any questions or comments, please let us know via content@esri.in.

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Share
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Click to copy link
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Close
Cite
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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