Dataset Description

This dataset contains the population statistics of countries and dependencies sourced from Wikipedia. It provides the latest figures of population estimates along with each country’s share of the world’s total population.

Columns Included:

• Country – Name of the country or dependency
• Population – Estimated total population (as per Wikipedia data)
• % of World – Share of the global population

Source:

The data was collected using Python libraries:

• requests for fetching the HTML page
• BeautifulSoup for parsing and extracting the table
• pandas for cleaning and structuring the data

Use Cases:

• Exploratory Data Analysis (EDA)
• Visualization of global population distribution
• Practice dataset for data cleaning, preprocessing, and feature engineering
• Building beginner-friendly machine learning projects with demographic data

Notes:

• Data is directly scraped from Wikipedia and may change over time as updates are made.
• Useful as a starting point for population-related research, data visualization, or ML practice projects.

Here are some interesting statistics about the world from Wikipedia

• This dataset provides a comprehensive snapshot of global country statistics for the year 2023. It was scraped from various Wikipedia pages using BeautifulSoup, consolidating key indicators and metrics for 142 countries. The dataset covers diverse aspects such as land area, water area, Human Development Index (HDI), GDP forecasts, internet usage, and population changes.

Key Columns and Metrics:

• Country: The name of the country.
• Total in km2: Total area of the country.
• Land in km2: Land area excluding water bodies.
• Water in km2: Area covered by water bodies.
• Water %: Percentage of the total area covered by water.
• HDI: Human Development Index, a measure of a country's overall achievement in its social and economic dimensions.
• %HDI Growth: Percentage growth in HDI.
• IMF Forecast GDP(Nominal): International Monetary Fund's forecast for Gross Domestic Product in nominal terms.
• World Bank Forecast GDP(Nominal): World Bank's forecast for Gross Domestic Product in nominal terms.
• UN Forecast GDP(Nominal): United Nations' forecast for Gross Domestic Product in nominal terms.
• IMF Forecast GDP(PPP): IMF's forecast for Gross Domestic Product in purchasing power parity terms.
• World Bank Forecast GDP(PPP): World Bank's forecast for Gross Domestic Product in purchasing power parity terms.
• CIA Forecast GDP(PPP): Central Intelligence Agency's forecast for Gross Domestic Product in purchasing power parity terms.
• Internet Users: Number of internet users in the country.
• UN Continental Region: Continental region classification by the United Nations.
• UN Statistical Subregion: Statistical subregion classification by the United Nations.
• Population 2022: Population of the country in the year 2022.
• Population 2023: Population of the country in the year 2023.
• Population %Change: Percentage change in population from 2022 to 2023.

World population point data for use with GIS mapping software, databases, and web applications are from Caliper Corporation.

🌍 Countries and Dependencies by Population (2025)

This dataset provides a comprehensive list of countries and dependent territories worldwide, along with their most recent population estimates.The data is sourced from the Wikipedia page List of countries and dependencies by population, which compiles figures from national statistical offices and the United Nations Population Division

📄 Dataset Overview

• Country/Territory Name Includes sovereign states, dependent territories, and regions with limited recognition.
• Population Latest available estimates, primarily from national censuses or UN projection.
• Percentage of World Population Each country's population as a percentage of the global total.
• Date of Estimate The reference date for the population figure.
• Notes Additional information, such as inclusion or exclusion of certain region.

🧠 Potential Use Cases

• Analyzing global population distribution and trends.- Creating visualizations like choropleth maps.- Normalizing other datasets by population for per capita analysis.- Educational purposes in demographics and geography.

📌 Notes

• The dataset includes territories and regions with limited recognition to provide a complete global perspective.
• Population figures are based on the most recent estimates available as of 225.
• Data may be subject to revisions as new census information becomes available.

World Population by Country (UN Data 2022-2023) This dataset contains population estimates for countries and territories from the United Nations (2022-2023), sourced from Wikipedia. It includes: - Country names - Population estimates for 2022 and 2023 - Percentage change - UN continental region and subregion - Source: Wikipedia - Image Source: https://imgbin.com

World sub-national boundaries with population counts for GIS mapping software are from Caliper Corporation.

This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds.

columns are individual-id, sex and population

Context

The kernel aims to extract data from Wikipedia's list of countries by category, and visualize it. The database itself, contains a HUGE amount of analyzed data at different categories, waiting anxiously for someone to present them elegantly ( 😏 ), and compare the trends between the different countries.

               <img src="https://github.com/Daniboy370/Machine-Learning/blob/master/Misc/Animation/VID-out-Wiki.gif?raw=true" width="550">

Content

The list contains 143 analyses of countries with respect to a specific criterion. Practically, I will refer to several criteria that I found interesting, however the reader is free to add as much as he pleases :

The well processed data should be able to provide such a visualization ( for example ) :

                      <img src="https://github.com/Daniboy370/Uploads/blob/master/Kaggle-Dataset-Wiki.gif?raw=true" width="600">

Pipeline

Choose criterion >> Extract data >> Examine & Clean >> Convert to dataframe >> Visualize :

                      <img src="https://github.com/Daniboy370/Uploads/blob/master/VID-Globe.gif?raw=true" width="400">

\[ \text{Enjoy !}\]

A dataset listing Florida cities by population for 2024.

Context

I always wanted to access a data set that was related to the world’s population (Country wise). But I could not find a properly documented data set. Rather, I just created one manually.

Content

Now I knew I wanted to create a dataset but I did not know how to do so. So, I started to search for the content (Population of countries) on the internet. Obviously, Wikipedia was my first search. But I don't know why the results were not acceptable. And also there were only I think 190 or more countries. So then I surfed the internet for quite some time until then I stumbled upon a great website. I think you probably have heard about this. The name of the website is Worldometer. This is exactly the website I was looking for. This website had more details than Wikipedia. Also, this website had more rows I mean more countries with their population.

Once I got the data, now my next hard task was to download it. Of course, I could not get the raw form of data. I did not mail them regarding the data. Now I learned a new skill which is very important for a data scientist. I read somewhere that to obtain the data from websites you need to use this technique. Any guesses, keep reading you will come to know in the next paragraph.

https://fiverr-res.cloudinary.com/images/t_main1,q_auto,f_auto/gigs/119580480/original/68088c5f588ec32a6b3a3a67ec0d1b5a8a70648d/do-web-scraping-and-data-mining-with-python.png" alt="alt text">

You are right its, Web Scraping. Now I learned this so that I could convert the data into a CSV format. Now I will give you the scraper code that I wrote and also I somehow found a way to directly convert the pandas data frame to a CSV(Comma-separated fo format) and store it on my computer. Now just go through my code and you will know what I'm talking about.

Below is the code that I used to scrape the code from the website

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3200273%2Fe814c2739b99d221de328c72a0b2571e%2FCapture.PNG?generation=1581314967227445&alt=media" alt="">

Acknowledgements

Now I couldn't have got the data without Worldometer. So special thanks to the website. It is because of them I was able to get the data.

Inspiration

As far as I know, I don't have any questions to ask. You guys can let me know by finding your ways to use the data and let me know via kernel if you find something interesting

Mbouda Population 2023
This dataset falls under the category Traffic Generating Parameters Population.
It contains the following data:
This dataset was scouted on 2022-02-14 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://worldpopulationreview.com/world-cities/mbouda-population

Introduction

iPhone Users Statistics: With the active installed base of iPhone users soaring past the 1.5 billion mark, Apple’s influence on the global consumer technology landscape is undeniable. It’s more than just a phone; it’s a cultural signifier, a secure ecosystem, a powerful engine for a nearly 400 billion dollar company. Apart from all, Apple remains a premium brand.

While Android controls he volume of the global smartphone market, the dedication, purchasing power, and platform loyalty of the average iPhone user create a level of unparalleled market value.

These data for 2025 give us a clear idea of a tech company solidifying its premium position, deepening its penetration in the world’s most lucrative markets, especially in India, and leveraging its software and services to turn device owners into lifetime customers.

In this comprehensive report, I’d like to discuss the figures behind the millions of daily activations, billions in revenue, and the demographic changes that are changing the global population of iPhone users. Let’s get into it.

Context: This is a list of countries and dependencies by population, offering a detailed snapshot of the world’s population distribution. It includes the latest population estimates, percentages of the global population, and the date of each estimate.

Sources: The data is collected from "List of countries and dependencies by Population" from Wikipedia.

Inspiration: The inspiration for this dataset stems from the need for accessible, up-to-date demographic data to analyze population trends across countries.

Introduction

Agriculture Statistics: By 2050, the demand for food is projected to increase by almost 70%, in line with the rapidly growing global population. A study conducted in the United States revealed that approximately 9.9% of the world's population still suffers from hunger, highlighting the significant challenge of feeding around 20 million people. Given the uncertain environmental changes, technological innovation in agriculture has become crucial.

The agricultural industry has undergone a remarkable transformation in recent years, largely attributed to technological advancements. From drones to automated tractors, technology has played a pivotal role in enhancing the effectiveness, sustainability, and precision of agriculture. This article aims to delve deeper into agricultural statistics.

Mombasa Population 2022
This dataset falls under the category Traffic Generating Parameters Population.
It contains the following data: Mombasa Population 2022
This dataset was scouted on 2022-02-13 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://worldpopulationreview.com/world-cities/mombasa-population

Nepal NP: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.065 Ratio in 2016. This stayed constant from the previous number of 1.065 Ratio for 2015. Nepal NP: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.057 Ratio from Dec 1962 (Median) to 2016, with 20 observations. The data reached an all-time high of 1.071 Ratio in 2002 and a record low of 1.045 Ratio in 1987. Nepal NP: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nepal – Table NP.World Bank: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;

This dataset contains the population data for countries as of 1 July 2023, sourced from the United Nations via Wikipedia. Includes country names, population figures, percentage change, and continental regions. Ideal for demographic analysis, research, and visualization.

This dataset is extracted from https://en.wikipedia.org/wiki/World_population. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

CONTEXT

Population typically refers to the number of people in a single area, whether it be a city or town, region, country, continent, or the world. Governments typically quantify the size of the resident population within their jurisdiction using a census, a process of collecting, analysing, compiling, and publishing data regarding a population. According to the United States Census Bureau the world's population was about 7.55 billion in 2019 and that the 7 billion number was surpassed on 12 March 2012. According to a separate estimate by the United Nations, Earth's population exceeded seven billion in October 2011, a milestone that offers unprecedented challenges and opportunities to all of humanity. - https://en.wikipedia.org/wiki/Population

CONTENT

• Year - Years from 1-2018 A.D.
• Afganistan...Zimbabwe - Country's Population

FILE INFO

• Population.csv - Population by Country starting from year 1 in CSV File
• Population.xlsx - Population by Country starting from year 1 in XLSX File