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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 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
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
- 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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TwitterThis study aimed to investigate the genomic diversity and population structure in the Muslim community of Telangana, India, using 23 autosomal microsatellite genetic markers. We also examined genetic relatedness between Muslim and non-Muslim populations of India. A sample of 184 randomly selected unrelated healthy Muslim individuals from the Telangana state were included in this study. The genotyping of 23 autosomal STR markers included in PowerPlex® Fusion 6 C multiplex system (Promega)was done. A total of 273 alleles were observed in the studied population, and locus SE33 showed 37 observed alleles, which is the highest number of observed alleles among all the studied loci. Among all the studied loci the most polymorphic and discriminatory locus was SE33, with the values of polymorphic information content (PIC) = 9.411E–01 and power of discrimination (PD) = 9.865E–01. Observed heterozygosity ranged from 6.630E–01 (D22S1045) to 9.239E–01 (SE33). Discrimination power, exclusion power, matching probability and paternity index for all the studied loci were 1.00E + 00, 1.00E + 00, 2.01E–28, and 5.68E + 09, respectively. The studied Muslim population showed genetic relatedness with non-Muslim populations i.e. populations of central India, Jharkhand, and Uttar Pradesh, suggesting the conversion of Hindus during the Muslim invasion. Neighbor-joining (NJ) tree and principal component analysis (PCA) revealed that the studied population showed genetic affinity with communities of Jharkhand, Madhya Pradesh and Uttar Pradesh states. The genetic data of this study may be useful for forensic, medical, and anthropological studies.
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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.
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:
- 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
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: ThrowbackDataThursday 201912 - Religion.csv | Column name...
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Census: Population: by Religion: Muslim: Uttarakhand data was reported at 1,406,825.000 Person in 03-01-2011. This records an increase from the previous number of 1,012,141.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: Uttarakhand data is updated decadal, averaging 1,209,483.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 1,406,825.000 Person in 03-01-2011 and a record low of 1,012,141.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: Uttarakhand data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE003: Census: Population: by Religion: Muslim.
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TwitterThis study, designed and carried out by the "http://www.asarb.org/" Target="_blank">Association of Statisticians of American Religious Bodies (ASARB), compiled data on 372 religious bodies by county in the United States. Of these, the ASARB was able to gather data on congregations and adherents for 217 religious bodies and on congregations only for 155. Participating bodies included 354 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao, Zoroastrian, American Ethical Union, and National Spiritualist Association congregations, and counts of congregations and adherents from Baha'i, three Buddhist groupings, two Hindu groupings, four Jewish groupings, and Muslims. The 372 groups reported a total of 356,642 congregations with 161,224,088 adherents, comprising 48.6 percent of the total U.S. population of 331,449,281. Membership totals were estimated for some religious groups.
In January 2024, the ARDA added 21 religious tradition (RELTRAD) variables to this dataset. These variables start at variable #12 (TOTCNG_2020). Categories were assigned based on pages 88-94 in the original "https://www.usreligioncensus.org/index.php/node/1638" Target="_blank">2020 U.S. Religion Census Report.
Visit the "https://www.thearda.com/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data sources.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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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.