The dataset contains general information about world countries as well as information about their flags, economy, and geographical location.

File description:

world_flags_2024.csv - dataset data_description.txt - full description of each column.

Source:

The dataset contains 41 columns: 8 of them are numeric-valued, others are either Boolean or nominal-valued. In the CSV file fields are separated by commas.

Note: Possible errors or inaccuracies in the interpretation of blazon images or other symbols on flags are not intentional, but arise from a lack of awareness on the part of the author.

Data fields:

Country - Names of all sovereign states as of 2024.

FlagUrl - Link to country's flag on Flagpedia.net.

AspectRatio - Aspect ration of the flag. Format: Height:Width.

LatestAdoption - Year of the last changes in the flag design.

White - 1 if white color present in the flag, 0 otherwise.

Red - 1 if red color present in the flag, 0 otherwise.

Blue - 1 if blue color present in the flag, 0 otherwise.

Black - 1 if black color present in the flag, 0 otherwise.

Yellow - 1 if yellow color present in the flag, 0 otherwise.

Green - 1 if green color present in the flag, 0 otherwise.

Orange - 1 if orange color present in the flag, 0 otherwise.

OtherColor - 1 if any other color present in the flag, 0 otherwise.

StripesEqual - 1 if all the stripes that make up the flag have equal width, 0 otherwise.

StripesVertical - 1 if stripes are arranged vertically, 0 otherwise.

StripesHorizontal - 1 if stripes are arranged horizontally, 0 otherwise.

StripesDiagonal - 1 if stripes are arranged diagonally, 0 otherwise.

StripesOther - 1 if the direction of stripes is mixed, 0 otherwise.

SingleColor - 1 if the flag is single color, i.e. there is no stripes, 0 otherwise.

LeftTriangle - 1 if there is a triangle on the left hand side of the flag, 0 otherwise.

Canton - 1 if there is an insert with an image in the top-left corner of the flag, 0 otherwise.

Cross - 1 if the flag contains a cross, 0 otherwise.

Crescent - 1 if the flag contains a crescent, 0 otherwise.

Sun - 1 if the flag contains the sun, 0 otherwise.

Bird - 1 if the flag contains a bird, 0 otherwise.

Stars - Number of stars on the flag.

Circle - 1 if the flag contains a circle, 0 otherwise.

BlazonOrOther - 1 if the flag contains a blazon or any other symbol, 0 otherwise.

Continent - Continent where the country is located. Note: Some countries have their parts located on multiple continents. For those countries the continent where the majority of its territory is located is chosen. Example: Russian Federation and Turkey.

Landlocked - 1 if the country has no direct access to an ocean, 0 otherwise.

TotalArea - Area of the country in km^2.

Population - Population of the country as of 2024.

Capital - Name of the capital of the country.

CapitalPopulation - Population of the capital.

HighestPoint - The highest point of the country.

LowestPoint - The lowest point of the country.

Religion - Dominant religion. If multiple, the most popular is chosen.

Currency - Name of the currency of the country.

CallingCode - Calling code of the country.

GDPPerCapita - GDP per capita in USD as of 2022. Zero if unknown.

HDI - Human Development Index as of 2022.

Gini - Income inequality: Gini coefficient as of 2023.

References:

1. https://www.un.org/dgacm/sites/www.un.org.dgacm/files/Documents_Protocol/officialnamesofcountries.pdf
2. https://flagpedia.net
3. https://www.worldometers.info
4. https://www.britannica.com
5. https://ourworldindata.org
6. https://www.jetpunk.com/info/capital-cities-by-population
7. https://wisevoter.com/country-rankings/religion-by-country
8. https://assets.pewresearch.org/wp-content/uploads/sites/11/2012/12/globalReligion-tables.pdf
9. Header image generated by leonardo.ai

Inspired by:

https://www.kaggle.com/datasets/edoardoba/world-flags https://www.kaggle.com/code/mscgeorges/country-flags-analysis

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

Beliefs and attitudesb'*' toward Ebola, the Ebola vaccine, and vaccines in general, North Kivu, Democratic Republic of the Congo, 2021.

Sociodemographic characteristics of the surveyed community members, North Kivu, Democratic Republic of the Congo, 2021.

About Dataset

The bible is considered a sacred book by Christians. It has a rich & varied history. The first section of the bible (the Old Testament) was originally written in Hebrew and tells the story of the Israelite people. It also includes books of religious law, poetry, and prophesy. The second section of the bible (the New Testament) was originally written in Greek and tells of the life of Jesus Christ and development of the early Christian church.

In the 1600's, the Protestant Reformation drove translations of the bible into local languages. This particular translation was authorized in 1604 by King James I of England for use by the Church of England. It has since grown to become the most popular English version of the bible.

Inspiration

This would be a great dataset for Natural Language Processing (NLP) techniques. Aspects of the bible that would be interesting to identify and explore with NLP:

• The Old Testament contains many examples of a Hebrew literary technique called parallelism.
• There are interesting examples of chiasmus in the bible, where there is symmetry in the text that can even span chapters.
• King Solomon, reported to be the wisest man on earth, authored the book of Proverbs. In the initial chapter, he references the "riddles" of the wise man. Are there riddles to be discovered here?