Context

This dataset includes some of the basic information of the websites we daily use. While scrapping this info, I learned quite a lot in R programming, system speed, memory usage etc. and developed my niche in Web Scrapping. It took about 4-5 hrs for scrapping this data through my system (4GB RAM) and nearly about 4-5 days working out my idea through this project.

Content

The dataset contains Top 50 ranked sites from each 191 countries along with their traffic (global) rank. Here, country_rank represent the traffic rank of that site within the country, and traffic_rank represent the global traffic rank of that site.

Since most of the columns meaning can be derived from their name itself, its pretty much straight forward to understand this dataset. However, there are some instances of confusion which I would like to explain in here:

1) most of the numeric values are in character format, hence, contain spaces which you might need to clean on.

2) There are multiple instances of same website. for.e.g. Yahoo. com is present in 179 rows within this dataset. This is due to their different country rank in each country.

3)The information provided in this dataset is for the top 50 websites in 191 countries as on 25th May 2017 and is subjected to change in future time due to the dynamic structure of ranking.

4) The dataset inactual contains 9540 rows instead of 9550(50*191 rows). This was due to the unavailability of information for 10 websites.

PS: in case if there are anymore queries, comment on this, I'll add an answer to that in above list.

Acknowledgements

I wouldn't have done this without the help of others. I've scrapped this information from publicly available (open to all) websites namely: 1) http://data.danetsoft.com/ 2) http://www.alexa.com/topsites , of which i'm highly grateful. I truly appreciate and thanks the owner of these sites for providing us with the information that I included today in this dataset.

Inspiration

I feel that there this a lot of scope for exploring & visualization this dataset to find out the trends in the attributes of these websites across countries. Also, one could try predicting the traffic(global) rank being a dependent factor on the other attributes of the website. In any case, this dataset will help you find out the popular sites in your area.

The Top Websites in the World

How They Change Over Time

About this dataset

This dataset consists of the top 50 most visited websites in the world, as well as the category and principal country/territory for each site. The data provides insights into which sites are most popular globally, and what type of content is most popular in different parts of the world

How to use the dataset

This dataset can be used to track the most popular websites in the world over time. It can also be used to compare website popularity between different countries and categories

Research Ideas

• To track the most popular websites in the world over time
• To see how website popularity changes by region
• To find out which website categories are most popular

Acknowledgements

Dataset by Alexa Internet, Inc. (2019), released on Kaggle under the Open Data Commons Public Domain Dedication and License (ODC-PDDL)

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. See Other Information.

Columns

File: df_1.csv | Column name | Description | |:--------------------------------|:---------------------------------------------------------------------| | Site | The name of the website. (String) | | Domain Name | The domain name of the website. (String) | | Category | The category of the website. (String) | | Principal country/territory | The principal country/territory where the website is based. (String) |

Designed and produced by the World Wide Web Foundation, the Web Index is the world’s first measure of the World Wide Web’s contribution to social, economic and political progress in countries across the world. http://thewebindex.org/about/ Scores are given in the areas of universal access; freedom and openness; relevant content; and empowerment. First released in 2012, the 2014-15 Index has been expanded and refined to include a total of 86 countries and features an enhanced data set, particularly in the areas of gender, Open Data, privacy rights and censorship. The Index combines existing secondary data with new primary data derived from an evidence-based expert assessment survey. The Web Index provides an objective and robust evidence base to inform public dialogue on the steps needed for societies to leverage greater value from the Web. It is published annually and resources permitting, it will continue to be expanded to cover more countries in the coming years. It will eventually allow for comparisons of trends over time and the benchmarking of performance across countries, continuously improving our understanding of the Web’s value for humanity.

Content

I collected data from here by country and with the help of a little bit of data wrangling, I could convert the data into the JSON and CSV format. The dataset contains 2 files:

countries.json: The top 50 most popular websites by each country, the ranking order is stored by indexes. sites.csv: General information about every website on the list, such as: * Daily Minutes on Site: Estimated daily minutes on site per visitor to the site * Daily Pageviews per Visitor: Estimated daily unique pageviews per visitor on the site * Ratio of Traffic From Search: The ratio of all referrals that came from Search engines over the trailing month * Total Sites Linking In: The total number of sites that are linked to this website

Acknowledgements

Source: Alexa.com.

As of October 2025, China has the world’s largest online population, with approximately 1.3 billion internet users. India, currently the most populous nation, ranks second with about 1.03 billion users. The United States follows in third place. Worldwide internet usage As of October 2025, there are more than six billion internet users worldwide. However, user distribution varies significantly by region. In 2024, Eastern Asia alone accounted for 1.34 billion internet users, while Africa and the Middle East reported considerably lower figures. As expected, urban areas also exhibited higher rates of internet access compared to rural regions. Internet use in China It is no surprise that China ranks first among countries with the most internet users. Driven by rapid economic development and a strong cultural embrace of technology, 91.6 percent of China’s estimated 1.4 billion residents are online. As of the third quarter of 2024, about 91.8 percent of Chinese internet users were active on WeChat, the country’s most popular social platform. During the same period, Chinese internet users spent an average of five hours and 33 minutes online each day.

In November 2024, WhatsApp.com was the most popular website in Spain by time per visit, with an average session length of approximately ** minutes and ** seconds. YouTube.com ranked second, with an average of ** minutes and ** seconds per visit. Despite being the leading website by total visits and unique visitors in the country, Google.com ranked fourth in engagement time, with ** minutes and ** seconds per session.

The average for 2023 based on 177 countries was 72.46 percent. The highest value was in Bahrain: 100 percent and the lowest value was in Burundi: 11.1 percent. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

About the Dataset

This dataset contains Quality of Life indices for various countries around the globe, extracted from the Numbeo website. The data provides valuable metrics for comparing countries based on several aspects of living standards, which can assist in decisions such as choosing a place to live or analyzing global trends in quality of life.

OBS: The code to generate this dataset is presented on: https://www.kaggle.com/code/marcelobatalhah/web-scrapping-quality-of-life-index

Columns in the Dataset

1. Rank:
   The global rank of the country based on its Quality of Life Index according to Year (1 = highest quality of life).

2. Country:
   The name of the country.

3. Quality of Life Index:
   A composite index that evaluates the overall quality of life in a country by combining other indices, such as Safety, Purchasing Power, and Health Care.

4. Purchasing Power Index:
   Measures the relative purchasing power of the average consumer in a country compared to New York City (baseline = 100).

5. Safety Index:
   Indicates the safety level of a country. A higher score suggests a safer environment.

6. Health Care Index:
   Evaluates the quality and accessibility of healthcare in the country.

7. Cost of Living Index:
   Measures the relative cost of living in a country compared to New York City (baseline = 100).

8. Property Price to Income Ratio:
   Compares the affordability of real estate by dividing the average property price by the average income.

9. Traffic Commute Time Index:
   Reflects the average time spent commuting due to traffic.

10. Pollution Index:
    Rates the level of pollution in the country (air, water, etc.).

11. Climate Index:
    Rates the favorability of the climate in the country (higher = more favorable).

12. Year:
    Year when the metrics were extracted.

Key Insights from the Dataset

• The Quality of Life Index aggregates multiple indicators, making it a useful single metric to compare countries.
• Specific indices such as Safety Index or Health Care Index allow for focused analysis on areas like security or healthcare quality.
• Cost of Living Index and Purchasing Power Index can help determine the affordability of living in each country.

How the Data Was Collected

• The dataset was built using web scraping techniques in Python.
• The data was extracted from the "Quality of Life Rankings by Country" page on Numbeo.
• Libraries used:
  • requests for retrieving webpage content.
  • BeautifulSoup for parsing the HTML and extracting relevant information.
  • pandas for organizing and storing the data in a structured format.

Possible Applications

1. Relocation Decision Making:
   Use the dataset to compare countries and identify destinations with high quality of life, safety, and healthcare.

2. Global Analysis:
   Perform exploratory data analysis (EDA) to identify trends and correlations across quality of life metrics.

3. Visualization:
   Plot global maps, bar charts, or other visualizations to better understand the data.

4. Predictive Modeling:
   Use this dataset as a base for machine learning tasks, like predicting Quality of Life Index based on other metrics.

kaleidoscopic-country.com is ranked # in US with 0 Traffic. Categories: . Learn more about website traffic, market share, and more!

As of July 2025, mobile phones accounted for **** percent of web page views in Saudi Arabia. The United Arab Emirates ranked second, with mobile devices generating approximately ***** percent of web traffic. Poland, Portugal, and Malaysia saw less than ** percent of their national internet traffic coming from mobile devices. Additionally, Russia ranked last for mobile internet traffic as of the middle of 2025, as ***** percent of the total internet traffic in the country came from smartphones and internet connected mobile devices.

countries-ofthe-world.com is ranked #72280 in US with 221.93K Traffic. Categories: Education. Learn more about website traffic, market share, and more!

In August 2025, Google.com was the most visited website worldwide, with an average of 98.2 billion monthly visits. The platform has maintained its leading position since June 2010, when it surpassed Yahoo to take first place. YouTube ranked second during the same period, recording over 48 billion monthly visits. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

a-nation.net is ranked #66134 in JP with 28.09K Traffic. Categories: Online Services. Learn more about website traffic, market share, and more!

katseye.world is ranked #42250 in US with 0 Traffic. Categories: . Learn more about website traffic, market share, and more!

Context

I've been exploring on how to use https://pypi.org/project/google-play-scraper/ and as one of my initial pet projects, I extracted the Facebook Google App reviews of the top 40 countries with most Facebook users as stated in this website https://wisevoter.com/country-rankings/facebook-users-by-country/ .

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2F2fbcdd42770c3f8492e505fbd7d685bd%2Ffacebook2.png?generation=1699794691453126&alt=media" alt="">

Im currently extracting the top 31st to 60th countries and will add to this dataset as soon as it finishes.

Note

Images generated using Bing Image Generator

edu-nation.net is ranked #754 in AE with 531.05K Traffic. Categories: Distance Learning, Education. Learn more about website traffic, market share, and more!

Countries with the highest speeds demonstrate examples of efficient infrastructure and investment in digital technologies, providing their citizens with fast and stable internet. In contrast, countries with low speeds face numerous challenges, especially economic ones.

Explore the Times Higher Education World University Rankings 2026 below. Trusted worldwide by students, academics, governments and industry experts, the list of the best universities in the world includes 2,191 institutions from 115 countries and territories.

Context

This data set consists of the list of countries by the number of internet users in 2018. The data was collected from Wikipedia, and then I just created a Comma Separated Value format with the help of Microsoft Excel.

Content

This is a trivial data set which has 6 columns and 215 rows containing the country name, population, population by rank, internet users, internet users rank and percentage.

Inspiration

I want to find what are the important features that contribute to the rank of countries based on internet users. Also, I want to create a model that can predict the rank given the population and internet users.

Context

A listing of the top 1-million websites according to Alexa.com.

Content

Rank and Site name

Acknowledgements

Fork from: https://github.com/mozilla/cipherscan/tree/master/top1m