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.

As of 2010, Christianity was the religion with the most followers worldwide, followed by Islam (Muslims) and Hinduism. In the forty years between 2010 and 2050, it is projected that the landscape of world religions will undergo some noticeable changes, with the number of Muslims almost catching up to Christians. The changes in population sizes of each religious group is largely dependent on demographic development, for example, the rise in the world's Christian population will largely be driven by population growth in Sub-Saharan Africa, while Muslim populations will rise across various regions of Africa and South Asia. As India's population is set to grow while China's goes into decline, this will be reflected in the fact that Hindus will outnumber the unaffiliated by 2050. In fact, India may be home to both the largest Hindu and Muslim populations in the world by the middle of this century.

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

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.

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...

World Religions Across Regions

Analyzing Adherence Across Regions, States and the Global System

By Correlates of War Project [source]

About this dataset

The World Religion Project (WRP) is an ambitious endeavor to conduct a comprehensive analysis of religious adherence throughout the world from 1945 to 2010. This cutting-edge project offers unparalleled insight into the religious behavior of people in different countries, regions, and continents during this time period. Its datasets provide important information about the numbers and percentages of adherents across a multitude of different religions, religion families, and non-religious affiliations.

The WRP consists of three distinct datasets: the national religion dataset, regional religion dataset, and global religion dataset. Each is focused on understanding individually specific realms for varied analysis approaches - from individual states to global systems. The national dataset provides data on number of adherents by state as well as percentage population practicing a given faith group in five-year increments; focusing attention to how this number evolves from nation to nation over time. Similarly, regional data is provided at five year intervals highlighting individual region designations with one modification – Pacific Ocean states have been reclassified into their own Oceania category according to Country Code Number 900 or above). Finally at a global level – all states are aggregated in order that we may understand a snapshot view at any five-year interval between 1945‐2010 regarding relationships between religions or religio‐families within one location or transnationally.

This project was developed in three stages: firstly forming a religions tree (a systematic classification), secondly collecting data such as this provided by WRP according to that classification structure – lastly cleaning the data so discrepancies may be reconciled and imported where needed with gaps selected when unknown values were encountered during collection process . We would encourage anyone wishing details undergoing more detailed reading/analysis relating various use applications for these rich datasets - please contact Zeev Maoz (University California Davis) & Errol A Henderson _(Pennsylvania State University)

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

The World Religions Project (WRP) dataset offers a comprehensive look at religious adherence around the world within a single dataset. With this dataset, you can track global religious trends over a period of 65 years and explore how they’ve changed during that time. By exploring the WRP data set, you’ll gain insight into cross-regional and cross-time patterns in religious affiliation around the world.

Research Ideas

• Analyzing historical patterns of religious growth and decline across different regions
• Creating visualizations to compare religious adherence in various states, countries, or globally
• Studying the impact of governmental policies on religious participation over time

Acknowledgements

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

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: WRP regional data.csv | Column name | Description | |:-----------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------| | Year | Reference year for data collection. (Integer) | | Region | World region according to Correlates Of War (COW) Regional Systemizations with one modification (Oceania category for COW country code ...

This statistic illustrates the projected growth of major religious groups from 2015 to 2060. In 2060, it is projected that there will be about *** billion Muslims worldwide, compared to *** billion Muslims in 2015.

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.

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.

Content

The World Religion Project 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 for every half-decade period. Some of the religions are divided into religious families, and the breakdown of adherents within a given religion into religious families is provided to the extent data are available.

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. To develop the religion tree we prepared a comprehensive literature review, the aim of which was to define a religion, to find tangible indicators of a given religion of religious families within a major religion, and to identify existing efforts at classifying world 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. This created a dataset that included multiple records for some states for a given point in time, yet 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.

Acknowledgements

The dataset was created by Zeev Maoz, University of California-Davis, and Errol Henderson, Pennsylvania State University, and published by the Correlates of War Project.

As of 2020, Christianity was the largest religion in the world, with around *** billion believers. In the second place was Islam, with around *** billion adherents.

This dataset represents the popular baby names for each religion with genders.

In 2022, ** percent of Hindus and Buddhists worldwide lived in Asia-Pacific. In comparison, ** percent of Jews lived in North America, and **** percent lived in the Middle East and North Africa. Christians were more evenly divided around the continents.

The 2008 Conversion Recontact Survey, conducted by the Pew Research Center's Forum on Religion & Public Life, is a follow-up to the 2007 "U.S. Religious Landscape Survey." One of the most striking findings from the Landscape Survey was the large number of people who have left their childhood faith. The Landscape Survey found that more than one in four American adults (28%) have changed their religious affiliation from that in which they were raised. This number includes people who have changed from one major religious tradition to another, for instance, from Protestantism to Catholicism or from Judaism to no religion. If change within religious traditions is included (e.g., from one Protestant denominational family to another), the survey found that roughly 44% of Americans now profess a religious affiliation different from that in which they were raised.

The Conversion Recontact Survey is designed to offer a fuller picture of this churn within American religion, with a special focus on the reasons that people change religious affiliation. The Conversion Recontact Survey is based on follow-up interviews with Landscape Survey respondents, including those from the largest segments of the population that have changed religious affiliation as well as those who still belong to the religious faith in which they were raised. Interviews were conducted by telephone with a nationally representative sample of 2,867 adults living in continental United States telephone households. The survey was conducted by Princeton Survey Research Associates International (PSRAI). Interviews were conducted on landline telephones in English and Spanish by Princeton Data Source (PDS), LLC from Oct. 3 to Nov. 7, 2008. Statistical results are weighted to correct known demographic discrepancies. A full report on the survey's findings, "Faith in Flux: Changes in Religious Affiliation in the U.S.," is available on the Pew Forum's "http://www.pewforum.org/2009/04/27/faith-in-flux/" Target="_blank">website.

Census 2021 data on religion by highest qualification level, by sex, by age, England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

This dataset shows population counts for usual residents aged 16 years and over. Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

Quality notes can be found here

Quality information about Education can be found here

Religion

The 8 ‘tickbox’ religious groups are as follows:

• Buddhist
• Christian
• Hindu
• Jewish
• Muslim
• No religion
• Sikh
• Other religion

No qualifications

No qualifications

Level 1

Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

Level 2

5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

Apprenticeship

Apprenticeship

Level 3

2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

Level 4 +

Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

Other

Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

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."

Comprehensive ranking dataset of the top 100 YouTube channels in the Religion category. This dataset features 100 channels with detailed statistics including subscriber counts, total video views, video count, and global rankings. The leading channel has 80,900,000 subscribers and 44,224,167,508 total views. Each entry includes comprehensive metrics to analyze channel performance, growth trends, and competitive positioning. This dataset is regularly updated to reflect the latest YouTube channel statistics and ranking changes, providing valuable insights for content creators, marketers, and researchers analyzing YouTube ecosystem trends and channel performance benchmarks.

Islam and Christianity form the two dominant religions in Nigeria. The basis of traditional religions was systematically exterminated in the religio-cultural life of the Nigerian people after their contact with colonialism. Approximately 90 percent of the Nigerian people have since preferred to be identified with either Islam or Christianity.Nigeria’s contact with Islam predated that of Christianity and European colonialism; its spread was facilitated into Sub-Saharan Africa through trade and commerce. The northern part of Nigeria is symbolic to the history of Islam, as it penetrated the area through the Kanem-Borno Empire in the 11th century before spreading to the other predominately Hausa states. Islam was then introduced into the traditional societies of the Yoruba-speaking people of south-west Nigeria through their established commercial relationship with people of the North, particularly the Nupe and Fulani.Christianity reached Nigeria in the 15th century with the visitation of the Roman and Catholic missionaries to the coastal areas of the Niger-Delta region, although there were few recorded converts and churches built during this period. Christianity soon recorded a boost in the southern region given its opposition to the slave trade and its promotion of Western education. In contrast to the smooth process Christian evangelization underwent in the South, its process in the North was difficult because Islam had already become well-established.Given the philosophy of Islam as a complete way of life for a Muslim, Islam has always been closely attached to politics in Nigeria. The emergence of particular Islamic groups was significantly influenced by international events, particularly the 1979 Iranian revolution and the corresponding disenchantment from the West. These developments shaped Nigerian national politics of the period as Muslims radically redefined their political interests in line with religion and began to clamor for the incorporation of the Sharia legal system into the country’s judicial system. Nigeria then tried to harness opportunities accruable from other Muslim countries by becoming a registered member with the Organization of Islamic Conference (OIC) in 1985. This inflamed Christians and nurtured the fear of domination by their Muslim counterparts and the possibility of a gradual extinction of their religio-political strength in the national political structure. The distinct religious separation has also instigated violence in present-day Nigeria, including the Sharia riot in Kaduna in 2000, ongoing ethno-religious violence in Jos since 2001, and the 2011 post-election violence that erupted in some northern states. Nigerians’ continued loyalty to religion compared to that of the country continues to sustain major political debate, conflict, and violent outbreaks between populations of the two faiths.

ISO3 - International Organization for Standardization 3-digit country code

AREA_AFF - Geographic area affected by disease

DT_START - Date health event started

DT_END - Date health event ended

TYPE - Type of disease group

DISEASE - Name of disease

NUM_DTH - Number of people reported dead from disease

NUM_AFF - Number of people affected from disease

SOURCE_DT - Source creation date

SOURCE - Primary source

Collection

This HGIS was created using information collected from several websites. EM-DAT, the World Health Organization, and news reports provided information about the outbreaks.

The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe Analytics is not responsible for the accuracy and completeness of data compiled from outside sources.

Sources (HGIS)

Egunganga, Vincent, Ami Sadiq, and Hir Joseph. All AfricaHIR JOSEPH, "Nigeria: Lassa Fever Returns Vicio." Last modified March 09, 2013. Accessed April 16, 2013. http://allafrica.com/.

EM DAT, "Country Database; Nigeria." Last modified March 2013. Accessed April 16, 2013. http://www.emdat.be/.

World Health Organization, "Global Health Observatory; Nigeria." Last modified 2012. Accessed April 16, 2013. http://www.who.int/en/.

Sources (Metadata)

Encyclopedia of the Nations, "Nigeria Country Specific Information." Last modified 2013. Accessed March 28, 2013. http://www.nationsencyclopedia.com.

Kates, Jennifer, and Alyssa Wilson Leggoe. The Henry J. Kaiser Family Foundation, "HIV/AIDS; The HIV/AIDS Epidemic in Nigeria." Last modified October 2005. Accessed April 16, 2013. http://www.kff.org/.

United States Embassy in Nigeria, "Nigeria Malaria Fact Sheet." Last modified December 2011. Accessed April 16, 2013. http://nigeria.usembassy.gov.

World Health Organization, "Global Task Force on Cholera Control." Last modified January 18, 2012. Accessed April 16, 2013. http://www.who.int/.

World Health Organization, "Meningococcal disease: situation in the African Meningitis Belt." Last modified 2012. Accessed March 14, 2013. http://www.who.int/csr/don/2012_05_24/en/index.html.

This statistic shows the top 25 countries in the world with the largest number of Christian population in 2010. In 2010, the United States was leading the ranking with about 243 million Christians living in the country.

Metron is interested in taking a data science approach to gleaming deeper insights into matters of spirituality, religion and extranormal experience. Data scientists at all levels of experience are encouraged to participate in this analysis.

This data set contains several public files of religious and spiritual texts. Also included is a “wildcard” file on the subject of machine super intelligence. This file is licensed under a Creative Commons Attribution-Share Alike 2.5 Switzerland License. More information can be found at: https://creativecommons.org/licenses/by-sa/2.5/ch/deed.en

Metron is interested in various text analysis techniques that can further an understanding of concepts that assist in furthering development of a body of knowledge on the topic of comparative religion and spirituality. Also other interesting observations that will fuel further lines of inquiry and questions are highly desirable.

Suggested Analysis Types: Scatter plot analysis - Metron would like to see a scatter plot of frequently recurring words in the texts If possible, can this be taken to the level of deriving conceptual correlations? Example, we may be able to state that “unconditional love” was the primary concept conveyed from the dataset. Followed by “communion” etc.

Word cloud analysis - create a scatter plot that uses a horizontal position indicating most popular words and a vertical position that indicates (some other type to be defined of) popularity.

Topic modeling - identify common topics found in the set of documents. Drill down to most common words per topic.

Word & document frequencies (tf-idf) - word frequency measurement and comparison across all documents. Charts of the highest tf-idf words in each text within the corpus.

Word dendrogram cluster - graphical representation of hierarchical word clusters.

Pairwise correlation - Words most correlated with other words in chart format.

Sentiment analysis - the most common words in texts associated with sentiments. Example: sentiment = creation. Associated words: God, genesis, Ein Sof, Allah, primordial, etc.

Word Network using tf-idf as a metric to find characteristic words for each description field rather than using counts of words.

Note: the above techniques can be found in “Data Science from Scratch - First Principles with Python” and “Text Mining with R - A Tidy Approach” both books from O’Reilly publishing.

The files are:

St. Augustine City of God 108 Upanishads 7 Tablets of Creation vols 1 and 2 Advaita Vendanta Aryan sun myths Autobiography of a yogi The Book of Illumination”

Attributed to Rabbi Nehunia ben haKana Bhagavad Gita Bible KJV Collected Fruits of Occult Teaching by A.P. Sinnett Epistle to the Son of the Wolf

Hidden Nature-The Startling Insights of Viktor Schauberger HILDEGARD OF BINGEN: SELECTED WRITINGS History of Zoroastrianism by

Maneckji Nusservanji The Philosophy of the Kaivalya Upanishad Kitab-i-Iqan (Book of Certitude) Knowledge of the Higher Worlds Rudolf Steiner Kularnava Tantra The Life of Buddha Machine Super Intelligence The Planet Mars and its Inhabitants By Eros Urides (A Martian) THE NATURE OF THE GODS. M. Tullius Cicero (“nature-gods”) OCCULT THEOCRASY BY LADY QUEENBOROUGH Urantia Book The Book of the People: POPUL VUH THE DHAMMAPADA VEDIC HYMNS Vedic Hymns, Part II Secret Instructions of the Society of Jesus THE CHALDEAN ACCOUNT OF GENESIS THE KITAB-I-AQDAS THE PATH OF LIGHT The Buddha's Way of Virtue The Yoga Sutras of Patanjali: The Book of the Spiritual Man by Patañjali The Vedanta-Sutras with the Commentary by Ramanuja The Kybalion Buddhism, in Its Connexion with Brahmanism and Hinduism, and in Its Contrast