This dataset contains country-level internet usage data from 2000 to 2023. It provides the percentage of the population using the internet in different countries over time. This data can be useful for analyzing global internet penetration, digital adoption trends, and technological growth across regions.

🔹 Dataset Information:

• Country Name & Code – Identifies each country.
• Yearly Internet Usage (%) – The percentage of the population using the internet from 2000 to 2023.
• Missing Values (No Data) – Some countries may have missing data for certain years.

📈 Potential Use Cases:

• Trend Analysis: Explore how internet usage has evolved globally.
• Regional Comparisons: Compare internet adoption across countries and continents.
• Machine Learning Applications
  • Time-Series Forecasting – Predict future internet usage trends using models like ARIMA, LSTM, or Prophet.
  • Clustering & Segmentation – Group countries based on their internet adoption rates using k-means or hierarchical clustering.
  • Feature Engineering – Use internet penetration as a predictor in socio-economic or technological development models.

📌 Source:

Modified from this source World bank group data

This dataset is valuable for data visualization, time-series analysis, and policy-making research related to digital growth.

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

The Internet (or internet) is a global system of interconnected computer networks that uses the Internet protocol suite (TCP/IP) to communicate between networks and devices. It is a network of networks that consists of private, public, academic, business, and government networks of local to global scope, linked by a broad array of electronic, wireless, and optical networking technologies. The Internet carries a vast range of information resources and services, such as the interlinked hypertext documents and applications of the World Wide Web (WWW), electronic mail, telephony, and file sharing.

Content

The following dataset has information about internet users from 1980-2020. Details about the columns are as follows: 1. Entity - Contains the name of the countries and the regions. 2. Code - Information about country code and where code has the value 'Region', it denotes division by grouping various countries. 3. Year - Year from 1980-2020 4. Cellular Subscription - Mobile phone subscriptions per 100 people. This number can get over 100 when the average person has more than one subscription to a mobile service. 5. Internet Users(%) - The share of the population that is accessing the internet for all countries of the world. 6. No. of Internet Users - Number of people using the Internet in every country. 7. Broadband Subscription - The number of fixed broadband subscriptions per 100 people. This refers to fixed subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s.

this graphs was created in R and Ourdataworld:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F1ad74af652d524e84410babe6ac5fe61%2Fgraph1.png?generation=1711651132634613&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F7c2b6427cb38f50eae417d741d09cd8d%2Fgraph2.png?generation=1711651140030127&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Ffea08aaf9fe8038659f6a081729f1bb2%2Fgraph3.gif?generation=1711651145884218&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F6cbb7538ed8f73a5bfed936ef7396a6d%2Fgraph4.gif?generation=1711651153848054&alt=media" alt="">

Introduction:

The dawn of the internet era has heralded an unprecedented age of connectivity, transforming the way we live, communicate, and interact on a global scale. As of 2020, approximately 60% of the world's population had access to the internet, marking a significant milestone in the digital revolution. From facilitating seamless communication to enabling cross-border collaborations, the internet has become an indispensable tool in our daily lives. This essay explores the multifaceted impact of the internet across various domains, highlighting its role as a catalyst for global connectivity and innovation.

Communication and Collaboration:

One of the most profound implications of the internet is its ability to bridge geographical distances and facilitate instant communication. Platforms such as email, social media, and messaging apps have revolutionized how we interact with one another, transcending borders and time zones. Whether it's connecting with loved ones halfway across the globe or collaborating with colleagues on a project, the internet has made communication more accessible and efficient than ever before. Video conferencing tools have further enhanced remote collaboration, enabling teams to work seamlessly regardless of their physical location. As a result, businesses have embraced remote work models, unlocking new possibilities for flexibility and productivity.

Financial Inclusion and Remittances:

The internet has democratized access to financial services, empowering individuals to participate in the global economy irrespective of their location. Online banking, mobile payment apps, and digital wallets have revolutionized the way we manage our finances, offering convenience and security. Moreover, the internet has facilitated international money transfers, including remittances, which play a vital role in supporting families and economies worldwide. Platforms like PayPal, TransferWise, and Western Union have streamlined the process of sending and receiving money across borders, reducing transaction costs and increasing efficiency. This newfound accessibility to financial services has contributed to greater financial inclusion and economic empowerment, particularly in underserved communities.

Education and Knowledge Sharing:

The internet has democratized access to education, breaking down traditional barriers to learning and knowledge dissemination. Online courses, tutorials, and educational platforms have made quality education accessible to anyone with an internet connection. Whether it's acquiring new skills, pursuing higher education, or accessing resources for self-improvement, the internet offers a wealth of learning opportunities. Open educational resources (OERs) and Massive Open Online Courses (MOOCs) have revolutionized the way we approach education, fostering a culture of lifelong learning and skill development. Furthermore, online forums and communities provide avenues for knowledge sharing and collaboration, enabling individuals to learn from experts and peers across the globe. This democratization of education holds the promise of narrowing the digital divide and fostering global innovation and prosperity.

Cross-Border Social Connections:

The internet has transcended cultural and linguistic barriers, facilitating cross-border social connections and fostering a sense of global citizenship. Social media platforms have become virtual gathering spaces where people from diverse backgrounds can connect, share experiences, and engage in meaningful dialogue. Whether it's forming friendships with individuals from different countries or participating in online communities centered around shared interests, the internet has enriched our social interactions in unprecedented ways. Moreover, platforms like language exchange forums and cultural exchange programs promote intercultural understanding and empathy, bridging gaps between people of different nationalities and backgrounds. By facilitating cross-border social connections, the internet has the potential to foster a more inclusive and interconnected global comm...

As of 2024, the estimated number of internet users worldwide was 5.5 billion, up from 5.3 billion in the previous year. This share represents 68 percent of the global population. Internet access around the world Easier access to computers, the modernization of countries worldwide, and increased utilization of smartphones have allowed people to use the internet more frequently and conveniently. However, internet penetration often pertains to the current state of development regarding communications networks. As of January 2023, there were approximately 1.05 billion total internet users in China and 692 million total internet users in the United States. Online activities Social networking is one of the most popular online activities worldwide, and Facebook is the most popular online network based on active usage. As of the fourth quarter of 2023, there were over 3.07 billion monthly active Facebook users, accounting for well more than half of the internet users worldwide. Connecting with family and friends, expressing opinions, entertainment, and online shopping are amongst the most popular reasons for internet usage.

The number of internet users in the United States was forecast to continuously increase between 2024 and 2029 by in total 13.5 million users (+4.16 percent). After the ninth consecutive increasing year, the number of users is estimated to reach 337.67 million users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

Internet use in the UK annual estimates by age, sex, disability, ethnic group, economic activity and geographical location, including confidence intervals.

This dataset provides historical data on the share of individuals using the Internet worldwide, broken down by country and year (1960–2023). It can be used to analyze the global digital divide, internet penetration trends, regional growth, and much more.

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) |

Description:

The "Daily Social Media Active Users" dataset provides a comprehensive and dynamic look into the digital presence and activity of global users across major social media platforms. The data was generated to simulate real-world usage patterns for 13 popular platforms, including Facebook, YouTube, WhatsApp, Instagram, WeChat, TikTok, Telegram, Snapchat, X (formerly Twitter), Pinterest, Reddit, Threads, LinkedIn, and Quora. This dataset contains 10,000 rows and includes several key fields that offer insights into user demographics, engagement, and usage habits.

Dataset Breakdown:

• Platform: The name of the social media platform where the user activity is tracked. It includes globally recognized platforms, such as Facebook, YouTube, and TikTok, that are known for their large, active user bases.

• Owner: The company or entity that owns and operates the platform. Examples include Meta for Facebook, Instagram, and WhatsApp, Google for YouTube, and ByteDance for TikTok.

• Primary Usage: This category identifies the primary function of each platform. Social media platforms differ in their primary usage, whether it's for social networking, messaging, multimedia sharing, professional networking, or more.

• Country: The geographical region where the user is located. The dataset simulates global coverage, showcasing users from diverse locations and regions. It helps in understanding how user behavior varies across different countries.

• Daily Time Spent (min): This field tracks how much time a user spends on a given platform on a daily basis, expressed in minutes. Time spent data is critical for understanding user engagement levels and the popularity of specific platforms.

• Verified Account: Indicates whether the user has a verified account. This feature mimics real-world patterns where verified users (often public figures, businesses, or influencers) have enhanced status on social media platforms.

• Date Joined: The date when the user registered or started using the platform. This data simulates user account history and can provide insights into user retention trends or platform growth over time.

Context and Use Cases:

• This synthetic dataset is designed to offer a privacy-friendly alternative for analytics, research, and machine learning purposes. Given the complexities and privacy concerns around using real user data, especially in the context of social media, this dataset offers a clean and secure way to develop, test, and fine-tune applications, models, and algorithms without the risks of handling sensitive or personal information.

Researchers, data scientists, and developers can use this dataset to:

• Model User Behavior: By analyzing patterns in daily time spent, verified status, and country of origin, users can model and predict social media engagement behavior.

• Test Analytics Tools: Social media monitoring and analytics platforms can use this dataset to simulate user activity and optimize their tools for engagement tracking, reporting, and visualization.

• Train Machine Learning Algorithms: The dataset can be used to train models for various tasks like user segmentation, recommendation systems, or churn prediction based on engagement metrics.

• Create Dashboards: This dataset can serve as the foundation for creating user-friendly dashboards that visualize user trends, platform comparisons, and engagement patterns across the globe.

• Conduct Market Research: Business intelligence teams can use the data to understand how various demographics use social media, offering valuable insights into the most engaged regions, platform preferences, and usage behaviors.

• Sources of Inspiration: This dataset is inspired by public data from industry reports, such as those from Statista, DataReportal, and other market research platforms. These sources provide insights into the global user base and usage statistics of popular social media platforms. The synthetic nature of this dataset allows for the use of realistic engagement metrics without violating any privacy concerns, making it an ideal tool for educational, analytical, and research purposes.

The structure and design of the dataset are based on real-world usage patterns and aim to represent a variety of users from different backgrounds, countries, and activity levels. This diversity makes it an ideal candidate for testing data-driven solutions and exploring social media trends.

Future Considerations:

As the social media landscape continues to evolve, this dataset can be updated or extended to include new platforms, engagement metrics, or user behaviors. Future iterations may incorporate features like post frequency, follower counts, engagement rates (likes, comments, shares), or even sentiment analysis from user-generated content.

By leveraging this dataset, analysts and data scientists can create better, more effective strategies ...

The Internet’s history has just begun

The Internet’s history goes back some decades by now – email has been around since the 1960s, file sharing since at least the 1970s, and TCP/IP was standardized in 1982. But it was the creation of the world wide web in 1989 that revolutionized our history of communication. The inventor of the world wide web was the English scientist Tim Berners-Lee who created a system to share information through a network of computers. At the time he was working for the European physics laboratory CERN in the Swiss Alps.

Here I want to look at the global expansion of the Internet since then.

This chart shows the share and number of people that are using the Internet, which in these statistics refers to all those who have used the Internet in the last 3 months.1

The chart starts in 1990, still, one year before Berners-Lee released the first web browser and before the very first website was online (the site of CERN, which is still online). At that time very few computers around the world were connected to a network; estimates for 1990 suggest that only half of a per cent of the world population were online.

As the chart shows, this started to change in the 1990s, at least in some parts of the world: By the year 2000 almost half of the population in the US was accessing information through the internet. But across most of the world, the internet had not yet had much influence – 93% in the East Asia and Pacific region and 99% in South Asia and in Sub-Saharan Africa were still offline in 2000. At the time of the Dot-com-crash, less than 7% of the world was online.

15 years later, in 2016, three-quarters (76%) of people in the US were online and during these years countries from many parts of the world caught up: in Malaysia, 79% used the internet; in Spain and Singapore 81%; in France 86%; in South Korea and Japan 93%; in Denmark and Norway 97%; and Iceland tops the ranking with 98% of the population online.2

At the other end of the spectrum, there are still countries where almost nothing has changed since 1990. In the very poorest countries – including Eritrea, Somalia, Guinea-Bissau, the Central African Republic, Niger, and Madagascar – fewer than 5% are online. And at the very bottom is North Korea, where the country’s oppressive regime restricts access to the walled-off North Korean intranet Kwangmyong and access to the global internet is only granted to a very small elite.

But the overarching trend globally – and, as the chart shows, in all world regions – is clear: more and more people are online every year. The speed with which the world is changing is incredibly fast. On any day in the last 5 years, there were on average 640,000 people online for the first time.3

This was 27,000 every hour.

For those who are online most days, it is easy to forget how young the internet still is. The timeline below the chart reminds you how recent websites and technologies became available that are integrated into the everyday lives of millions: In the 1990s there was no Wikipedia, Twitter launched in 2006, and Our World in Data is only 4 years old (and look how many people have joined since then4).

And while many of us cannot imagine our lives without the services that the internet provides, the key message for me from this overview of the global history of the internet is that we are still in the very early stages of the internet. It was only in 2017 that half of the world population was online, and in 2018 it is therefore still the case that close to half of the world population is not using the internet.5

The internet has already changed the world, but the big changes that the Internet will bring still lie ahead and its history has just begun.

Content

The data consists of the Internet and the Evolution of Broadband around the world.

Acknowledgements

The Data is collected from Our World In Data

Inspiration

What share of people is online? How many internet users does each country have?

The percentage of households with internet access in Eastern Europe was forecast to continuously increase between 2024 and 2029 by in total 6.9 percentage points. After the twenty-eighth consecutive increasing year, the internet penetration is estimated to reach 96.38 percent and therefore a new peak in 2029. Notably, the percentage of households with internet access of was continuously increasing over the past years.Depicted is the share of housholds with internet access in the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the percentage of households with internet access in countries like Southern Europe and Northern Europe.

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.

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

Abstract

The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

Geographic coverage

National Coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

Research instrument

The English version of the questionnaire is provided for download.

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: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

IPv4 Address Allocation by Country: A Worldwide Perspective

How Many IP Addresses are Allocated per Country?

About this dataset

This dataset provides information on the allocation of IPv4 addresses by country. It includes the starting and ending IP addresses for each range, the decimal values for the start and end of the range, the whois server for the range, and the country code.

This dataset is perfect for anyone interested in learning more about how IP addresses are allocated around the world. With it, you can better understand how countries are connected to each other via the internet. You can also use it to determine which countries have

• The starting IP address for the range
• The ending IP address for the range
• The starting decimal value for the traffic number of this line (IP Address)
• The ending decimal value traffic number of this line (IP Address)
• The Whois Server operating this service line (ServerName)
• The Country Code of this service area

How to use the dataset

This dataset contains information on the allocation of IPv4 addresses by country. The data is sourced from the whois servers for each country.

Research Ideas

• This dataset can be used to determine which countries have the most allocated IPv4 addresses.
• This dataset can be used to map the allocation of IPv4 addresses by country.
• This dataset can be used to determine the whois server for each range of IPv4 addresses by country

License

See the dataset description for more information.

Columns

File: GeoIP-whois.csv

• The starting IP address for the range. (IP Address)
• The ending IP address for the range. (IP Address)
• The starting decimal value for the range. (Decimal)
• The ending decimal value for the range. (Decimal)
• The whois server for the range. (Whois Server)
• The country code for the range. (Country Code)

File: ip_alloc.csv

• starting IP address
• ending IP address
• starting decimal value
• ending decimal value
• country code
• whois server

The number of internet users in Africa was forecast to continuously increase between 2024 and 2029 by in total 327.8 million users (+51.52 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 964.1 million users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of internet users in countries like Europe and the Americas.

Abstract

The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

Geographic coverage

National Coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

Research instrument

The English version of the questionnaire is provided for download.

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: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

Publisher Name: Eurostat

This data is gathered by Eurostat and is available in European Commission online for free. you can check it out by this link.

European Union is the covered area in this data set and covers from 2013 to 2021 and is a 44456 * 11 dataset.

This Data Set is containing Social media use by type, internet advertising and size class of enterprise.

This data identifies by isoc_cismt.

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GapMinder collects data from a handful of sources, including the Institute for Health Metrics and Evaluation, the US Census Bureau’s International Database, the United Nations Statistics Division, and the World Bank.

Variable Name & Description of Indicator:

• country: Unique Identifier
• incomeperperson: Gross Domestic Product per capita in constant 2000 US$. The inflation but not the differences in the cost of living between countries has been taken into account.
• Internetuserate: Internet users (per 100 people) Internet users are people with access to the worldwide network.
• urbanrate: Urban population (% of total) Urban population refers to people living in urban areas as defined by national statistical offices (calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects)

More information is available at www.gapminder.org