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...

In 2020, around 28.8 percent of the global population were identified as Christian. Around 25.6 percent of the global population identify as Muslims, followed by 14.9 percent of global populations as Hindu. The number of Muslims increased by 347 million, when compared to 2010 data, more than all other religions combined.

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...

From 2022 to 2060, the worldwide population of Muslims is expected to increase by **** percent. For the same period, the global population of Buddhists is expected to decrease by **** percent.

The RCS-Dem dataset reports estimates of religious demographics, both country by country and region by region. RCS was created to fulfill the unmet need for a dataset on the religious dimensions of countries of the world, with the state-year as the unit of observation. It covers 220 independent states, 26 selected substate entities, and 41 geographically separated dependencies, for every year from 2015 back to 1900 and often 1800 (more than 42,000 state-years). It estimates populations and percentages of adherents of 100 religious denominations including second level subdivisions within Christianity and Islam, along with several complex categories such as "Western Christianity." RCS is designed for easy merger with datasets of the Correlates of War and Polity projects, datasets by the United Nations, the Religion And State datasets by Jonathan Fox, and the ARDA national profiles.

In Sweden, a large majority of the population define themselves as Christians. Based on a representative survey reflecting 7.9 million of the Swedish population, *** million of these define themselves as Christians, with ******* of these being very religious.

World religion data in this dataset is from the World Religion Database.The map shows the percentage of the majority religion by provinces/states and also included in the database is Christian percentage by provinces/states. Boundaries are based on Natural Earth, August, 2011 modified to match provinces in the World Religion Database.*Originally titled

The World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide since 1945. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950, etc., through 2010). Percentages of the states' populations that practice a given religion are also provided. (Note: These percentages are expressed as decimals, ranging from 0 to 1, where 0 indicates that 0 percent of the population practices a given religion and 1 indicates that 100 percent of the population practices that religion.) Some of the religions are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also provided.

The project was developed in three stages. The first stage consisted of the formation of a religion tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. To develop the religion tree we prepared a comprehensive literature review, the aim of which was (i) to define a religion, (ii) to find tangible indicators of a given religion of religious families within a major religion, and (iii) to identify existing efforts at classifying world religions. (Please see the original survey instrument to view the structure of the religion tree.) The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. This created a dataset that included multiple records for some states for a given point in time. It also contained multiple missing data for specific states, specific time periods and specific religions. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources and imputing data for the missing cases.

The National Religion Dataset: The observation in this dataset is a state-five-year unit. This dataset provides information regarding the number of adherents by religions, as well as the percentage of the state's population practicing a given religion.

Data on religion by gender and age for the population in private households in Canada, provinces and territories.

At the end of 2023, the population of Israel reached almost 9.7 million permanent residents. Jewish residents formed the largest religious group, with just over 7.15 million people. The Muslim population in the country, formed the largest religious minority at over 1.7 million individuals. Conversely, the smallest religious group was that of the Druze with about 151,000 people.

This Religion and State-Minorities (RASM) dataset is supplemental to the Religion and State Round 2 (RAS2) dataset. It codes the RAS religious discrimination variable using the minority as the unit of analysis (RAS2 uses a country as the unit of analysis and, is a general measure of all discrimination in the country). RASM codes religious discrimination by governments against all 566 minorities in 175 countries which make a minimum population cut off. Any religious minority which is at least 0.25 percent of the population or has a population of at least 500,000 (in countries with populations of 200 million or more) are included. The dataset also includes all Christian minorities in Muslim countries and all Muslim minorities in Christian countries for a total of 597 minorities. The data cover 1990 to 2008 with yearly codings.

These religious discrimination variables are designed to examine restrictions the government places on the practice of religion by minority religious groups. It is important to clarify two points. First, these variables focus on restrictions on minority religions. Restrictions that apply to all religions are not coded in this set of variables. This is because the act of restricting or regulating the religious practices of minorities is qualitatively different from restricting or regulating all religions. Second, this set of variables focuses only on restrictions of the practice of religion itself or on religious institutions and does not include other types of restrictions on religious minorities. The reasoning behind this is that there is much more likely to be a religious motivation for restrictions on the practice of religion than there is for political, economic, or cultural restrictions on a religious minority. These secular types of restrictions, while potentially motivated by religion, also can be due to other reasons. That political, economic, and cultural restrictions are often placed on ethnic minorities who share the same religion and the majority group in their state is proof of this.

This set of variables is essentially a list of specific types of religious restrictions which a government may place on some or all minority religions. These variables are identical to those included in the RAS2 dataset, save that one is not included because it focuses on foreign missionaries and this set of variables focuses on minorities living in the country. Each of the items in this category is coded on the following scale:

0. The activity is not restricted or the government does not engage in this practice.
1. The activity is restricted slightly or sporadically or the government engages in a mild form of this practice or a severe form sporadically.
2. The activity is significantly restricted or the government engages in this activity often and on a large scale.

A composite version combining the variables to create a measure of religious discrimination against minority religions which ranges from 0 to 48 also is included.

ARDA Note: This file was revised on October 6, 2017. At the PIs request, we removed the variable reporting on the minority's percentage of a country's population after finding inconsistencies with the reported values. For detailed data on religious demographics, see the "/data-archive?fid=RCSREG2" Target="_blank">Religious Characteristics of States Dataset Project.

Among the people surveyed in 26 countries around the world, a slight majority of the baby boomer generation were Christians. By comparison, only 42 percent of Generation Z stated that they were Christians. Millennials was the generation with the highest share of people stating that they had a religious belief other than Islam and Christianity.

Overview

The World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide from 1945 to 2010. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950,…, 2010). The data record percentages of the state’s population that practice a given religion. Some of the religions (as detailed in the Codebook) are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also specified in the Codebook.

The project was developed in three stages. The first stage consisted of the formation of a religions tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources, and imputing data for the missing cases.

Please see column description in the PDF file

Citations

Zeev Maoz and Errol A. Henderson. 2013. “The World Religion Dataset, 1945-2010: Logic, Estimates, and Trends.” International Interactions, 39: 265-291.

Data Sets

The WRP contains three datasets: the national religion dataset, the regional religion dataset, and the global religion dataset.

The National Religion Dataset. The unit of analysis in this dataset is the individual state, observed at five-year intervals. This dataset provides information regarding the number of adherents by religion, as well as the percent of the state’s population practicing a given religion.

The Regional Religion Dataset. The unit of analysis in this dataset is the region, observed at five-year intervals. This dataset utilizes the COW regional designations with one modification: the Oceania category for COW country code numbers 900 and above.

The Global Religion Dataset. The unit of analysis in this dataset is the global system, observed at five-year intervals. This dataset aggregates the number of adherents of a given religion and religious group for all states, globally.

Acknowlegement

Foto von James Coleman auf Unsplash

India Census Dataset

This dataset provides comprehensive census data at the district level for India. It includes detailed demographic, religious, educational, and workforce-related attributes, making it a rich resource for socio-economic analysis.

1. Columns and Descriptions

A. Basic Information

District_code: A unique numeric code for each district. State_name: Name of the state to which the district belongs. District_name: Name of the district.

B. Population Data

Population: Total population of the district. Male: Total male population in the district. Female: Total female population in the district.

C. Literacy Data

Literate: Total number of literate individuals in the district.

D. Workforce Data

Workers: Total number of workers in the district. Male_Workers: Total number of male workers in the district. Female_Workers: Total number of female workers in the district. Cultivator_Workers: Number of workers engaged as cultivators. Agricultural_Workers: Number of workers engaged in agricultural labor. Household_Workers: Number of workers engaged in household industries.

E. Religion Data

Hindus: Total number of Hindus in the district. Muslims: Total number of Muslims in the district. Christians: Total number of Christians in the district. Sikhs: Total number of Sikhs in the district. Buddhists: Total number of Buddhists in the district. Jains: Total number of Jains in the district.

F. Education Data

Secondary_Education: Number of individuals with secondary education. Higher_Education: Number of individuals with higher education qualifications. Graduate_Education: Number of individuals with graduate-level education.

G. Age Group Data

Age_Group_0_29: Population in the age group 0–29 years. Age_Group_30_49: Population in the age group 30–49 years. Age_Group_50: Population aged 50 years and above.

2. Key Highlights

Number of Districts: 640 Number of Columns: 25 Non-null Values: All columns are complete with no missing data. Detailed breakdown of population by gender, age group, literacy levels, and workforce distribution. Religious composition and education statistics are also included for each district.

3. Potential Use Cases

Data Analysis and Visualization:

Explore patterns in population distribution, literacy rates, workforce composition, and religious demographics. Machine Learning Applications:

Build predictive models to classify districts or forecast demographic trends. Social Research:

Investigate correlations between education levels, workforce participation, and religion. Policy Planning:

Help policymakers target specific demographics or regions for intervention. Educational Insights:

Analyze the impact of education levels on workforce participation or literacy.

4. Dataset Overview

Total Rows: 640 Total Columns: 25 This dataset provides a unique opportunity to understand India's socio-economic and demographic composition at a granular district level.

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."

This 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, and 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 #8 (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.

This dataset shows the Worker Population Ratio (WPR), in percentage terms, for major religions, based on usual status (ps+ss). For years before 2017-18, the data was obtained in different quinquennial rounds of NSSO conducted from 2004-05 (NSS 61st) to 2011-12 (NSS 68th round). From 2017-18 the data is sourced from the annual report of the Periodic Labour Force Survey (PLFS) conducted by the Ministry of Statistics and Programme Implementation. The data highlights the proportion of the working population within major religious communities.

This study, designed and carried out by the Association of Statisticians of American Religious Bodies (ASARB), compiled data on the number of congregations and adherents for 236 religious groups in each county of the United States. Participants included 217 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao and National Spiritualist Association congregations, and counts of congregations and adherents from Bahá'ís, three Buddhist groupings, four Hindu groupings, four Jewish groupings, Muslims and Zoroastrians. The 236 groups reported a total of 344,894 congregations with 150,686,156 adherents, comprising 48.8 percent of the total U.S. population of 308,745,538 in 2010.

Visit the "/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.

Table showing the numbers and percentage of resident population (all ages) broken down into six faiths, plus no religion and any other religion. Data is taken from the Annual Population Survey (ONS).

The data covers: Christian, Buddhist, Hindu, Jewish, Muslim, Sikh, any other religion and no religion at all.

95% Confidence Intervals are shown.

Or alternatively, faith data from the 2011 Census is able to show numbers for each of the main religions.