Dataset

This dataset was created by Ifeanyichukwu Nwobodo

Contents

"Between October 2011 and November 2012, Pew Research Center, with generous funding from The Pew Charitable Trusts and the John Templeton Foundation, conducted a public opinion survey involving more than 30,000 face-to-face interviews in 26 countries in Africa, Asia, the Middle East and Europe. The survey asked people to describe their religious beliefs and practices, and sought to gauge respondents; knowledge of and attitudes toward other faiths. It aimed to assess levels of political and economic satisfaction, concerns about crime, corruption and extremism, positions on issues such as abortion and polygamy, and views of democracy, religious law and the place of women in society.

"Although the surveys were nationally representative in most countries, the primary goal of the survey was to gauge and compare beliefs and attitudes of Muslims. The findings for Muslim respondents are summarized in the Religion & Public Life Project's reports The World's Muslims: Unity and Diversity and The World's Muslims: Religion, Politics and Society, which are available at www.pewresearch.org. [...] This dataset only contains data for Muslim respondents in the countries surveyed. Please note that this codebook is meant as a guide to the dataset, and is not the survey questionnaire." (2012 Pew Religion Worlds Muslims Codebook)

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...

Pew Research Center’s “World’s Muslims” dataset is based on a survey conducted between October 2011 and November 2012. The study explores the religious beliefs, practices, social attitudes, and political views of Muslims across multiple countries, providing insights into diversity within the global Muslim population.

COVID-19 in Muslim vs. Non-Muslim Countries

A Comparative Study of 50 Muslim-Majority and 50 Richest Non-Muslim Countries

About Dataset

This dataset contains information on COVID-19 cases and deaths in 50 Muslim-majority countries compared to the 50 richest non-Muslim countries. The aim of the dataset is to investigate the differences in COVID-19 incidence between these two groups and to explore potential reasons for these disparities. The Muslim-majority countries in the sample had more than 50.0% Muslims, while the non-Muslim countries were selected based on their GDP, excluding any Muslim-majority countries listed. The data was collected on September 18, 2020, and includes information on the percentage of Muslim population per country, GDP, population count, and total number of COVID-19 cases and deaths. The dataset was transferred via an Excel spreadsheet on September 23, 2020 and analyzed using three different Average Treatment Methods (ATE) to validate the results. The dataset was published as a preprint and is associated with a manuscript titled "Fifty Muslim-majority countries have fewer COVID-19 cases and deaths than the 50 richest non-Muslim countries". The manuscript can be accessed via the following Link The sources of the data are also provided in the manuscript. The percentage of Muslim population per country was obtained from World Population Review and can be accessed at Link The GDP per country, population count, and total number of COVID-19 cases and deaths were obtained from Worldometers and can be accessed at Link

More Datasets

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Columns

Research Ideas / Data Use

• Comparative analysis: Researchers can use this dataset to compare the COVID-19 cases and deaths between Muslim-majority and non-Muslim countries. This can help to identify any disparities or differences in the response to the pandemic.
• Trend analysis: Over time, this dataset can be used to track the changes in the COVID-19 cases and deaths in Muslim-majority and non-Muslim countries. This can help to identify trends and patterns that may inform future research.
• Geographical analysis: This dataset can be used to explore the geographical distribution of COVID-19 cases and deaths in Muslim-majority and non-Muslim countries. This can help to identify hotspots and areas that may require special attention.
• Demographic analysis: Researchers can use the data to explore the impact of demographic factors on the spread and severity of the pandemic in Muslim-majority and non-Muslim countries. This can help to identify any patterns or correlations that may inform future research and policy decisions.
• Economic analysis: The data can be used to explore the economic impact of the pandemic on Muslim-majority and non-Muslim countries. By comparing the GDP and other economic indicators in these countries, researchers can identify any patterns or trends that may inform economic policy decisions.

Acknowledgements

if this dataset was used in your work or studies, please credit the original source Please Credit ↑ ⠀

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. More Information

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.

Context

This is believed to be an unbiased fact-based dataset to get a better understanding of how much damage that the Islamic extremists are doing to the world.

Content

These are not incidents of ordinary crime involving nominal Muslims killing for money or vendetta. Incidents of deadly violence that are reasonably determined to have been committed out of religious duty - as interpreted by the perpetrator - are only included. Islam needs to be a motive, but it need not be the only factor.

For example, the Munich mall shooting in July, 2016 was by a Muslim, but it is not on the list, because it was not inspired by a sense of religious duty.

The incidents were collected each day from public news sources. There is no rumor or word-of-mouth involved. Although every attempt is made to be accurate and consistent, we are not making the claim that this is a scientific product.

Acknowledgements

This dataset is available here on Kaggle, thanks to TheReligionofPeace.com

Inspiration

The point of this dataset is not to convince anyone that they are in mortal danger or that Muslims are innately dangerous people (they are not, of course). Rather it is to point out the sort of terrorism that some of "Religion of Peace" believers produce. It should be acceptable to question and critique the teachings and phrases interpretation particularly those that are supremacist in nature.

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.

This dataset contains the estimated religious composition of 198 countries and territories for 2010 to 2050.
The data is sourced from PEW RESEARCH CENTER . In original dataset the number and the percentage share of followers for some religions as "<10000" and "<10%". Because of technical limitations of the visualization tool, these values had to be changed into "10000".

data/rounded_population.csv

This file contains the number followers by religions and region for 2010 to 2050 | Column Name | Description | |-----------------|-------------------------------------------------------------------------------------------------| | Year | The year for which the data is recorded. | | Region | The region to which the country belongs. | | Country | The name of the country. | | Buddhists | The estimated number of Buddhists in the country for the given year. | | Christians | The estimated number of Christians in the country for the given year. | | Folk Religions | The estimated number of followers of folk religions in the country for the given year. | | Hindus | The estimated number of Hindus in the country for the given year. | | Jews | The estimated number of Jews in the country for the given year. | | Muslims | The estimated number of Muslims in the country for the given year. | | Other Religions | The estimated number of followers of other religions in the country for the given year. | | Unaffiliated | The estimated number of people with no religious affiliation in the country for the given year. |

data/rounded_percentage.csv

This file contains the percentage share of followers by religions and region for 2010 to 2050 | Column Name | Description | |------------------|------------------------------------------------------------------------------------------------| | Year | The year for which the data is recorded. | | Region | The region to which the country belongs. | | Country | The name of the country. | | Christians | The percentage share of Christians in the country's population for the given year. | | Muslims | The percentage share of Muslims in the country's population for the given year. | | Unaffiliated | The percentage share of people with no religious affiliation in the country's population. | | Hindus | The percentage share of Hindus in the country's population for the given year. | | Buddhists | The percentage share of Buddhists in the country's population for the given year. | | Folk Religions | The percentage share of followers of folk religions in the country's population. | | Other Religions | The percentage share of followers of other religions in the country's population. | | Jews | The percentage share of Jews in the country's population for the given year. | | All Religions | The percentage share of all religious groups combined in the country's population for the year. |

The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.

This dataset contains the Arab-West Report special reports that were published in 2004.This dataset mainly contains the writings of Cornelis Hulsman ,Drs., among other authors on topics related to Muslim- Christian relations and interfaith dialogue between the West and Islamic world. Additionally this dataset contains reports pertaining to certain Muslim –Christian incidents and reports about allegations of forced conversions of Coptic girls. Some of the articles addressed the issue of missionaries.Further reports address monastic life and recommendations of Arab-West Report's work by other social figures.Furthermore, the dataset included commentary on published material from other sources (reviews/critique of articles from other media).Some of the themes that characterized this dataset:-A description of the history of the conflicts around the development of the convent of Patmos on the Cairo-Suez road.-An overview of a book titled “Christians versus Muslims in Modern Egypt: The Century-Long Struggle for Coptic Equality” by S. S. Hasan.- Rumors of forced conversions Of Coptic girls: A report by Hulsman stated that the US Copts Association published a press release on March 25, 2004 with the title “Coptic Pope Denounces Forced Conversion of Coptic Girls.” He criticized that the US Copts Association for not making much of an effort, if any, to check the veracity of the rumors.- A Glimpse into Monastic Life in Egypt: A Visit to St. Maqarius Monastery:- Another report covered the incident in which a priest and two members of the church board of Taha al-ʿAmeda died after an accident with a speeding car driven by a police officer.- A critique of Al-Usbuʿa newspapers: the author accused the newspaper of cherry-picking statements by Coptic extremists, who are much disliked in the US Coptic community and who have no following. He considered that quoting statements from such isolated radicals gives readers the impression that they represent much more than a few individuals. It has all appearance that al-Usbuʿa has highlighted these radicals to create fear and harm the reputation of US Copts in Egypt.- A number of reports highlighted a visit and the speech delivered by the Archbishop of Canterbury, Dr George Carey (Lord Carey) at the Azhar entitled “Muslims/Christian Relationships: A New Age Of Hope?”- A report covered the first visit made by Archbishop Rowan Williams to the Diocese of Egypt since he became the Archbishop of Canterbury. The archbishop met with President Mubarak, Dr. Muhammad Sayyed Tantawi, the Grand Imam of the Azhar, Pope Shenouda and also laid the foundation stone of Harpur Community Health Centre in Sadat City.- Updates on the developments of AWR’s work to create an electronic archive of information pertaining to relations between Muslims and Christians in the Arab-World in general and Egypt in particular.Additionally, this dataset also provides updates of the then-under construction - Center for Arab-West Understanding (CAWU) web-based Electronic Documentation Center (EDC) for contemporary information covering Arab-West and Muslim-Christian relations.- A report discussed the misconceptions of Christians in Islam.- An editorial commenting on the assassination of Theo van Gogh resulted in a debate in Dutch media about the limits of the freedom of expression.- An article calling on the western readers to be careful with Christian persecution stories from Egypt, they may be true but also may be rumours.-The Muslim World And The West; What Can Be Done To Reduce Tensions?-Text of a lecture for students and professors of different faculties at the University of Copenhagen, , about plans to establish the Center for Arab-West Understanding in Cairo, Egypt.- Escalations following the alleged conversion of A priest’s wife to IslamThe list of authors’ featurd in this dataset goes as follows:Cornelis Hulsman, Drs. , Wolfram Reiss, Rev. Dr. , John H. Watson, Kim Kwang-Chan, Dr. , Kamal Abu al-Majd, Fiona McCallum, Mary Picard , Jeff Adams, Dr., Rev., Jennie Marshall , Marcos Emil Mikhael, Usamah W. al-Ahwani, Sawsan Jabrah and Nirmin Fawzi, Hānī Labīb, George Carey (Lord), Rowan Williams, Lambeth Palace Press Office, H.G. Bishop Munir Hanna Anis Armanius, Eildert Mulder, Rīhām Saʿīd, Tharwat al-Kharabāwī, Geir Valle, Janique Blattman, Iqbal Barakah , Munā ʿUmar, Dieter Tewes, ʿAmr Asʿad Khalīl, Dr., Janique Blattmann, Vera Milackova, Tamir Shukri, and Christiane Paulus All reports are written in English, though some reports feature Arabic text or cite Arabic sources.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

Recent issues on politics have been dominant in Indonesia that people are divided and become more intolerant of each other. Indonesia has the biggest Muslim population in the world and the role of Islam in Indonesian politics is significant. The current Indonesian government claim that moderate Muslims are loyal to the present political system while the opposing rivals who are often labelled’intolerant and radical Muslims’ by Indonesian mass media often disagree with the central interpretation of democracy in Indonesia. Studies on contributing factors and discourse strategies used in news and articles in secular and Islamic mass media which play a vital role in the construction of Muslim and Islamic identities in Indonesia are, therefore, recommended.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Iran, Islamic Rep. is 1005.

Mode of data collection

Landline and mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

This dataset contains the Arab West Report special reports published in the year 2003. The majority of the material in this dataset focuses on in depth analysis of Muslim-Christian relations in Egypt, however, Judaism is also the subject of a great deal of analysis in these reports. A number of the reports address relations between religious minorities such as 'dhimmi' status, and the complex relationship between national identity and religious identity. A number of reports are also media critique, a staple of AWR’s work.The AWR reports in this dataset also describe the early work of AWR, and introduce several of its early board members and affiliates. Authors include:- Cornelis Hulsman, Drs.- Sunni M. Khalid- Jeff Adams (Dr. Rev.)- Larry F. Levine (Dr.)- Victor M. Ordonez- Michael Reimer (Dr.)- Wolfram Reiss, (Rev. Dr.)- Johanna Pink (Dr.)- Nirmīn Fawzī- Hedda Klip- Munīr Hannā Anīs Armanius (Bishop)- Cassandra Chambliss- Adam Hannestad- David Weaver- Konrad Knolle (Rev.)- Usamah Wadi‘ al-Ahwani- Marjam Van Oort- Nawal al-Sa‘dawi- M.E. van Gent- Subhi ‘Uwaydah, (Rev. Dr.)- Andreas Van Agt, (Dr.)Institutional authors include AWR Editorial Board, AWR Board of Advisors, Center for the Study of Christianity in Islamic Lands (CSCIL), and EKD Presservice. All reports are written in English, though some reports feature Arabic text or cite Arabic sources.Team including job titles:Sparks, MA M.R. (Center for Intercultural Dialogue and Translation (CIDT))Adams, Rev.Dr. J. (Religious News Service from the Arab-World (RNSAW))Levine, Dr. L.Khalid, S.Reimer, Dr. M. (American University in Cairo)Ordonez, Dr. V.Reiss, Rev. Dr. W.Pink, Dr. J.Fawzi, N. (Religious News Service from the Arab World (RNSAW))Klip, Rev. H. (Swiss Reformed Church)Hannā Anīs Armanius, Bishop M. (Episcopal Church)Chambliss, C. (Intern-Center for Arab-West Understanding (CAWU))Hannestad, A.Weaver, D. (Church World Service, USA)Knolle, Rev. K. (German Reformed Church in Cairo)Al-Ahwani, U. (Religious News Service from the Arab-World (RNSAW))Oort, M. Van (Roos Foundation)Al-Sa'adawi, N.Gent, M.E. VanUwaydah, Rev. Dr. S. (Coptic Evangelical Church Ismailia, Egypt)van Agt, Dr. A.EKD Press ServiceCenter for the Study of Christianity in Islamic Lands (CSCIL)AWR Editorial BoardAWR Board of AdvisorsHulsman, Drs. C. Mr. (Center for Intercultural Dialogue and Translation

The FIFA World Cup, simply called the World Cup, is an international association football competition contested by the senior men's national teams of the members of the Fédération Internationale de Football Association (FIFA), the sport's global governing body is taking place in Qatar from 20 November to 18 December 2022. It is the first World Cup to be held in the Arab world and Muslim world, and the second held entirely in Asia after the 2002 tournament in South Korea and Japan.

I am sharing the “FIFA World Cup" Tweets Dataset with the research community containing large Tweets. The dataset consists of a total of 100000 tweet IDs of the same number of tweets about the FIFA World Cup that were posted on Twitter from 14th Dec 2022 to 15th Dec 2022.

The dataset was collected using Trackmyhashtag, an easy & affordable platform.

Each Tweet contains different types of data:-

• Tweet Id
• Tweet URL
• Posted time and date
• Tweet Content Other metadata

I hope researchers find it helpful. If you need more datasets, let me know.

Ibn Kathir wrote a famous commentary on the Qur'an named Tafsir al-Qur'an al-'Adhim which linked certain Hadith, or sayings of Muhammad, and sayings of the sahaba to verses of the Qur'an, in explanation. Tafsir ibn Kathir is famous all over the Muslim world, and among Muslims in the Western world is one of the most widely used explanations of the Qu'ran today.

Ibn Kathir was renowned for his great memory regarding the sayings of Muhammad and the entire Qur'an. Ibn Kathir is known as a qadi, a master scholar of history, also a muhaddith and a mufassir (Qur'an commentator). Ibn Kathir saw himself as a Shafi'i scholar. This is indicated by two of his books, one of which was Tabaqaat ah-Shafa'iah, or The Categories of the Followers of Imam Shafi.

pdf's were downloaded from : http://www.quran4u.com/Tafsir%20Ibn%20Kathir/Index.htm

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15070006%2Fda30b3bab0ba1ad16529f6b0be33f2c3%2Fxian.jpg?generation=1698558286455813&alt=media" alt=""> Great Mosque of Xi'an - China

Context & Inspiration

Seize this invaluable opportunity to immerse yourself in the sacred verses of the Quran, a source of profound wisdom, spiritual guidance, and cultural significance in the Islamic world. Whether you're a dedicated researcher, a passionate data enthusiast, or simply an individual with a thirst for knowledge and a desire to connect with diverse cultures, this dataset opens doors to a treasure trove of information.

By exploring '**The Holy Quran - English Translation Dataset**' sourced from online Quranic resources, you not only gain access to a comprehensive English translation but also a deeper understanding of the Islamic faith, its historical context, and the values it embodies. This endeavor goes beyond data analysis; it's an invitation to engage with a rich cultural heritage that spans centuries, fostering cross-cultural appreciation, and illuminating the shared human experience.

Unearth the profound beauty and timeless depth of the Quran's verses, and embark on a transformative journey of enlightenment through the power of data analysis and exploration. Let your exploration of this dataset inspire a greater appreciation for the wisdom and teachings contained within, ultimately enriching your understanding of Islam and its global impact.

Disclaimer

Please use 'The Holy Quran - English Translation Dataset' responsibly and with utmost sensitivity. This dataset contains sacred and religious text, and its contents should be handled with the highest level of respect and consideration. It is important to note that the dataset provides the original English translation sourced from online Quranic resources, and it is not intended for any form of misuse, misrepresentation, or disrespectful usage.

We urge all users to approach this dataset with a deep understanding of the religious and cultural significance of the Quran. Any analysis, research, or exploration should be conducted in a manner that respects the sanctity of the text and the beliefs of those who hold it dear.

Furthermore, it is crucial to recognize that this dataset serves as a reference tool and does not endorse any particular interpretation or religious viewpoint. The dataset's purpose is to facilitate the study and understanding of the Quran's English translation, its historical context, and its cultural relevance.

We kindly request all users to exercise discretion, empathy, and cultural sensitivity when using this dataset. Please be aware of the potential impact your work may have and take every precaution to ensure that it promotes understanding and goodwill among all individuals, regardless of their beliefs or backgrounds.

Census: Population: by Religion: Muslim: Assam data was reported at 10,679,345.000 Person in 03-01-2011. This records an increase from the previous number of 8,240,611.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: Assam data is updated decadal, averaging 9,459,978.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 10,679,345.000 Person in 03-01-2011 and a record low of 8,240,611.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: Assam 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.

Singapore Population: Religion: Female: Islam data was reported at 233.800 Person th in 2015. This records an increase from the previous number of 231.478 Person th for 2010. Singapore Population: Religion: Female: Islam data is updated yearly, averaging 231.478 Person th from Jun 2000 (Median) to 2015, with 3 observations. The data reached an all-time high of 233.800 Person th in 2015 and a record low of 185.804 Person th in 2000. Singapore Population: Religion: Female: Islam data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G002: Population by Religion .