The global number of internet users in was forecast to continuously increase between 2024 and 2029 by in total 1.3 billion users (+23.66 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 7 billion 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 the Americas and Asia.

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

This table shows whether people aged 16 or over have ever used or never used the internet by a range of variables such as age, ethnicity, pay, occupation, qualifications, and disability. The question asked in the Labour Force Survey is "When did you last use the internet?" This question is only asked to people aged 16 and over. The first time this data was available was 2011 Q1. At borough level the data showed ever used or never used. For London and Rest of UK the data is broken down by a range of indicators, including age, ethnic group, weekly pay, occupation levels, qualification levels, and economic activity. The APS sampled around 333,000 people in the UK (around 27,000 in London). As such all figures must be treated with some caution. Data was supplied directly by ONS under request from the Greater London Authority. Numbers rounded to the nearest thousand. Other Internet Access data can be found on the ONS website. This is national data based on the Opinions and Lifestyle Survey.

The percentage of households with internet access in Central & Western Europe was forecast to continuously increase between 2024 and 2029 by in total 3.2 percentage points. After the seventh consecutive increasing year, the internet penetration is estimated to reach 96.21 percent and therefore a new peak in 2029. 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 Northern Europe and Russia.

United States US: Fixed Broadband Internet Subscribers: per 100 People data was reported at 33.853 Ratio in 2017. This records an increase from the previous number of 33.002 Ratio for 2016. United States US: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 24.639 Ratio from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 33.853 Ratio in 2017 and a record low of 0.256 Ratio in 1998. United States US: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Telecommunication. Fixed broadband subscriptions 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 includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

Nigeria NG: Fixed Broadband Internet Subscribers: per 100 People data was reported at 0.039 Ratio in 2017. This records a decrease from the previous number of 0.058 Ratio for 2016. Nigeria NG: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 0.037 Ratio from Dec 2005 (Median) to 2017, with 11 observations. The data reached an all-time high of 0.062 Ratio in 2010 and a record low of 0.000 Ratio in 2005. Nigeria NG: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Telecommunication. Fixed broadband subscriptions 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 includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

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

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

Please cite the following paper when using this dataset: N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2

Abstract The world is currently facing an outbreak of the monkeypox virus, and confirmed cases have been reported from 28 countries. Following a recent “emergency meeting”, the World Health Organization just declared monkeypox a global health emergency. As a result, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, an open-access dataset of Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

Data Description The dataset consists of a total of 255,363 Tweet IDs of the same number of tweets about monkeypox that were posted on Twitter from 7th May 2022 to 23rd July 2022 (the most recent date at the time of dataset upload). The Tweet IDs are presented in 6 different .txt files based on the timelines of the associated tweets. The following provides the details of these dataset files. • Filename: TweetIDs_Part1.txt (No. of Tweet IDs: 13926, Date Range of the Tweet IDs: May 7, 2022 to May 21, 2022) • Filename: TweetIDs_Part2.txt (No. of Tweet IDs: 17705, Date Range of the Tweet IDs: May 21, 2022 to May 27, 2022) • Filename: TweetIDs_Part3.txt (No. of Tweet IDs: 17585, Date Range of the Tweet IDs: May 27, 2022 to June 5, 2022) • Filename: TweetIDs_Part4.txt (No. of Tweet IDs: 19718, Date Range of the Tweet IDs: June 5, 2022 to June 11, 2022) • Filename: TweetIDs_Part5.txt (No. of Tweet IDs: 47718, Date Range of the Tweet IDs: June 12, 2022 to June 30, 2022) • Filename: TweetIDs_Part6.txt (No. of Tweet IDs: 138711, Date Range of the Tweet IDs: July 1, 2022 to July 23, 2022)

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used.

This data is used for a broadband mapping initiative conducted by the Washington State Broadband Office.This dataset provides global fixed broadband and mobile (cellular) network performance metrics in zoom level 16 web mercator tiles (approximately 610.8 meters by 610.8 meters at the equator). Data is projected in EPSG:4326. Download speed, upload speed, and latency are collected via the Speedtest by Ookla applications for Android and iOS and averaged for each tile. Measurements are filtered to results containing GPS-quality location accuracy. The data was processed and published to ArcGIS Living Atlas by Esri.AboutSpeedtest data is used today by commercial fixed and mobile network operators around the world to inform network buildout, improve global Internet quality, and increase Internet accessibility. Government regulators such as the United States Federal Communications Commission and the Malaysian Communications and Multimedia Commission use Speedtest data to hold telecommunications entities accountable and direct funds for rural and urban connectivity development. Ookla licenses data to NGOs and educational institutions to fulfill its mission: to help make the internet better, faster and more accessible for everyone. Ookla hopes to further this mission by distributing the data to make it easier for individuals and organizations to use it for the purposes of bridging the social and economic gaps between those with and without modern Internet access.DataTilesHundreds of millions of Speedtests are taken on the Ookla platform each month. In order to create a manageable dataset, we aggregate raw data into tiles. The size of a data tile is defined as a function of "zoom level" (or "z"). At z=0, the size of a tile is the size of the whole world. At z=1, the tile is split in half vertically and horizontally, creating 4 tiles that cover the globe. This tile-splitting continues as zoom level increases, causing tiles to become exponentially smaller as we zoom into a given region. By this definition, tile sizes are actually some fraction of the width/height of Earth according to Web Mercator projection (EPSG:3857). As such, tile size varies slightly depending on latitude, but tile sizes can be estimated in meters.For the purposes of these layers, a zoom level of 16 (z=16) is used for the tiling. This equates to a tile that is approximately 610.8 meters by 610.8 meters at the equator (18 arcsecond blocks). The geometry of each tile is represented in WGS 84 (EPSG:4326) in the tile field.The data can be found at: https://github.com/teamookla/ookla-open-dataUpdate Cadence The tile aggregates start in Q1 2019 and go through the most recent quarter. They will be updated shortly after the conclusion of the quarter.Esri ProcessingThis layer is a best available aggregation of the original Ookla dataset. This means that for each tile that data is available, the most recent data is used. So for instance, if data is available for a tile for Q2 2019 and for Q4 2020, the Q4 2020 data is awarded to the tile. The default visualization for the layer is the "broadband index". The broadband index is a bivariate index based on both the average download speed and the average upload speed. For Mobile, the score is indexed to a standard of 25 megabits per second (Mbps) download and 3 Mbps upload. A tile with average Speedtest results of 25/3 Mbps is awarded 100 points. Tiles with average speeds above 25/3 are shown in green, tiles with average speeds below this are shown in fuchsia. For Fixed, the score is indexed to a standard of 100 Mbps download and 3 Mbps upload. A tile with average Speedtest results of 100/20 Mbps is awarded 100 points. Tiles with average speeds above 100/20 are shown in green, tiles with average speeds below this are shown in fuchsia.Tile Attributes Each tile contains the following adjoining attributes:The year and the quarter that the tests were performed.The average download speed of all tests performed in the tile, represented in megabits per second.The average upload speed of all tests performed in the tile, represented in megabits per second.The average latency of all tests performed in the tile, represented in millisecondsThe number of tests taken in the tile.The number of unique devices contributing tests in the tile.The quadkey representing the tile.QuadkeysQuadkeys can act as a unique identifier for the tile. This can be useful for joining data spatially from multiple periods (quarters), creating coarser spatial aggregations without using geospatial functions, spatial indexing, partitioning, and an alternative for storing and deriving the tile geometry.LayersThere are two layers:Ookla_Mobile_Tiles - Tiles containing tests taken from mobile devices with GPS-quality location and a cellular connection type (e.g. 4G LTE, 5G NR).Ookla_Fixed_Tiles - Tiles containing tests taken from mobile devices with GPS-quality location and a non-cellular connection type (e.g. WiFi, ethernet).The layers are set to draw at scales 1:3,000,000 and larger.Time Period and Update FrequencyLayers are generated based on a quarter year of data (three months) and files will be updated and added on a quarterly basis. A /year=2020/quarter=1/ period, the first quarter of the year 2020, would include all data generated on or after 2020-01-01 and before 2020-04-01.

This portion of the GapMinder data includes one year of numerous country-level indicators of health, wealth and development for 213 countries.

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

Variable Name , Description of Indicator & Sources Unique Identifier: Country

1. incomeperperson : 2010 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. [Main Source : World Bank Work Development Indicators]

2. alcconsumption: 2008 alcohol consumption per adult (age 15+), litres Recorded and estimated average alcohol consumption, adult (15+) percapita consumption in liters pure alcohol [Main Source : WHO]

3. armedforcesrate: Armed forces personnel (% of total labor force) [Main Source : Work Development Indicators]

4. breastcancerper100TH : 2002 breast cancer new cases per 100,000 female Number of new cases of breast cancer in 100,000 female residents during the certain year. [Main Source : ARC (International Agency for Research on Cancer)]

5. co2emissions : 2006 cumulative CO2 emission (metric tons), Total amount of CO2 emission in metric tons since 1751. [*Main Source : CDIAC (Carbon Dioxide Information Analysis Center)] *

6. femaleemployrate : 2007 female employees age 15+ (% of population) Percentage of female population, age above 15, that has been employed during the given year. [ Main Source : International Labour Organization]

7. employrate : 2007 total employees age 15+ (% of population) Percentage of total population, age above 15, that has been employed during the given year. [Main Source : International Labour Organization]

8. HIVrate : 2009 estimated HIV Prevalence % - (Ages 15-49) Estimated number of people living with HIV per 100 population of age group 15-49. [Main Source : UNAIDS online database]

9. Internetuserate: 2010 Internet users (per 100 people) Internet users are people with access to the worldwide network. [Main Source : World Bank]

10. lifeexpectancy : 2011 life expectancy at birth (years) The average number of years a newborn child would live if current mortality patterns were to stay the same. [Main Source : 1) Human Mortality Database, 2) World Population Prospects: , 3) Publications and files by history prof. James C Riley , 4) Human Lifetable Database ]

11. oilperperson : 2010 oil Consumption per capita (tonnes per year and person) [Main Source : BP]

12. polityscore : 2009 Democracy score (Polity) Overall polity score from the Polity IV dataset, calculated by subtracting an autocracy score from a democracy score. The summary measure of a country's democratic and free nature. -10 is the lowest value, 10 the highest. [Main Source : Polity IV Project]

13. relectricperperson : 2008 residential electricity consumption, per person (kWh) . The amount of residential electricity consumption per person during the given year, counted in kilowatt-hours (kWh). [Main Source : International Energy Agency]

14. suicideper100TH : 2005 Suicide, age adjusted, per 100 000 Mortality due to self-inflicted injury, per 100 000 standard population, age adjusted . [Main Source : Combination of time series from WHO Violence and Injury Prevention (VIP) and data from WHO Global Burden of Disease 2002 and 2004.]

15. urbanrate : 2008 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) [Main Source : World Bank]

When asked about "Attitudes towards the internet", most Mexican respondents pick "It is important to me to have mobile internet access in any place" as an answer. 56 percent did so in our online survey in 2025. Looking to gain valuable insights about users of internet providers worldwide? Check out our reports on consumers who use internet providers. These reports give readers a thorough picture of these customers, including their identities, preferences, opinions, and methods of communication.

The World Telecommunication/ICT Indicators Database contains time series data for the years 1960, 1965, 1970 and annually from 1975 to 2020 for more than 180 telecommunication/ICT statistics covering fixed-telephone networks, mobile-cellular telephone subscriptions, quality of service, Internet (including fixed- and mobile-broadband subscription data), traffic, staff, prices, revenue, investment and statistics on ICT access and use by households and individuals. Selected demographic, macroeconomic and broadcasting statistics are also included. Data are available for over 200 economies. However, it should be noted that since ITU relies primarily on official economy data, availability of data for the different indicators and years varies. Notes explaining data exceptions are also included. The data are collected from an annual questionnaire sent to official economy contacts, usually the regulatory authority or the ministry in charge of telecommunication and ICT. Additional data are obtained from reports provided by telecommunication ministries, regulators and operators and from ITU staff reports. In some cases, estimates are made by ITU staff; these are noted in the database.

The World Telecommunication/ICT Indicators database contains time series data for more than 180 telecommunication/ICT (Information and Communication Technologies) statistics. It covers fixed-telephone networks, mobile-cellular telephone subscriptions, quality of service, Internet (including fixed- and mobile-broadband subscription data), traffic, staff, prices, revenue, investment and statistics on ICT access and use by households and individuals. Selected demographic, macroeconomic and broadcasting statistics are also included. The data is for the years 1960, 1965, 1970 and annually from 1975 to 2017. The WTI Database also includes: Economy yearbook pages featuring in the Yearbook of Statistics. These pages show data in economy tables allowing readers to view the evolution of telecommunication services by economy. Statistics are provided for the ten-year period 2007-2017. The latest (2017) data on ICT access and use by households and individuals. Data are presented in tables and broken down by socio-demographic variables, such as age, sex, income and education level etc. Please note: The World Telecommunication/ICT Indicators database is a relational database which must be used with the associated Software Application. In order to search and extract data from the Data file, users will need to download and install the Application and the Data file to the same folder on their personal computers. The database must be installed by first launching the executable (ending in “.exe”) file.

Tanzania TZ: Fixed Broadband Internet Subscribers: per 100 People data was reported at 3.225 Ratio in 2017. This records a decrease from the previous number of 3.326 Ratio for 2016. Tanzania TZ: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 0.059 Ratio from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 3.326 Ratio in 2016 and a record low of 0.007 Ratio in 2005. Tanzania TZ: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank: Telecommunication. Fixed broadband subscriptions 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 includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

Abstract

The World Bank conducted an in-depth analysis of the digital economy in Indonesia through the Digital Economic Household Survey (DEHS). The plan to survey 6,600 households was disrupted due to the pandemic. Thus, the DEHS dataset contains 3,063 households (HHs) out of planned 6,600 HHs (46%) from 311 enumeration areas (EAs) out of the planned 660 EAs.

The datasets contain household and individual data. Separate data files are provided for particular modules containing matrix-style questions. All household-level datasets contain the variable "hhid" as household identifier, whereas individual-level datasets contain both "hhid" and "hh_memberid" to identify individuals. These variables can be used for merging purposes across data files.

There are 6 modules available in these dataset: Module 1 contains general household-level information, including demographics, dwelling and ICT device usage. Module 2 asks on internet access and use, including device ownership, social media use, internet affordability, side effects and digital skills. Module 3 contains information related to service delivery, including government services, social assistance, education and health. Module 5 probes information related to household e-commerce activities as buyers and digital on-demand services. Module 6 focuses on use of digital finance in the household. Lastly, Module 9 collects information related to household enterprise activities, which includes e-commerce activities as sellers.

Geographic coverage

The survey is representative of major island regions in Indonesia (Sumatera, Java, Nusa Tenggara, Kalimantan, Sulawesi, Maluku, Papua).

Analysis unit

Individual, Household

Sampling procedure

The survey uses Stratified Four-Stage PPES (Probability Proportional to Estimated Size) Sampling. As Primary Sampling Units (PSUs), districts in each region were stratified into 'rural' or 'urban'. Villages are Secondary Sampling Units (SSUs), while hamlets and households are Tertiary Sampling Units (TSUs) and Ultimate Sampling Units (USUs), respectively. Eligible villages are defined as villages with internet signal, regardless of the quality of the signal (4G, 3G, or 2.5G), based on Podes 2018 data.

Sampling deviation

The survey did not deviate from its sample design. However, the survey was unable to obtain its full sample (only 3,063 out of 6,600 households) due to early termination of the survey because of COVID-related restrictions.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The DEHS questionnaire includes the following modules:

Module 1: General Information (01_DEHS_Questionnaire_General_Module_final_070620_eng.pdf) Module 2: Internet Access and Use (02_DEHS_Questionnaire_internet_access_and_use_final_070620_eng.pdf) Module 3: Service Delivery (03_DEHS_Questionnaire_Service_Delivery_final_070620_eng.pdf) Module 5: E-commerce (05_DEHS_Questionnaire_e_Commerce_final_070620_eng.pdf) Module 6: Finance (06_DEHS_Questionnaire_Finance_final_070620_eng.pdf) Module 9: HH Enterprise (09_DEHS_Questionnaire_HH_Enterprise_final_070620_eng.pdf)

Note: The initial survey design also included module 7 (last mile internet service delivery) and module 8 (community retail price). However, both modules were ultimately dropped in order to save enumeration time, and reduce respondent fatigue.

Uzbekistan UZ: Fixed Broadband Internet Subscribers: per 100 People data was reported at 10.405 Ratio in 2017. This records an increase from the previous number of 8.733 Ratio for 2016. Uzbekistan UZ: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 0.412 Ratio from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 10.405 Ratio in 2017 and a record low of 0.011 Ratio in 2003. Uzbekistan UZ: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uzbekistan – Table UZ.World Bank: Telecommunication. Fixed broadband subscriptions 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 includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

Thailand TH: Fixed Broadband Internet Subscribers: per 100 People data was reported at 11.889 Ratio in 2017. This records an increase from the previous number of 10.483 Ratio for 2016. Thailand TH: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 4.381 Ratio from Dec 2001 (Median) to 2017, with 16 observations. The data reached an all-time high of 11.889 Ratio in 2017 and a record low of 0.003 Ratio in 2001. Thailand TH: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank: Telecommunication. Fixed broadband subscriptions 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 includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

Jordan JO: Fixed Broadband Internet Subscribers: per 100 People data was reported at 4.829 Ratio in 2016. This records an increase from the previous number of 3.496 Ratio for 2015. Jordan JO: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 2.868 Ratio from Dec 2001 (Median) to 2016, with 16 observations. The data reached an all-time high of 4.829 Ratio in 2016 and a record low of 0.008 Ratio in 2001. Jordan JO: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank: Telecommunication. Fixed broadband subscriptions 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 includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

The population share with mobile internet access in North America was forecast to increase between 2024 and 2029 by in total 2.9 percentage points. This overall increase does not happen continuously, notably not in 2028 and 2029. The mobile internet penetration is estimated to amount to 84.21 percent in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.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 population share with mobile internet access in countries like Caribbean and Europe.