As of February 2025, 5.56 billion individuals worldwide were internet users, which amounted to 67.9 percent of the global population. Of this total, 5.24 billion, or 63.9 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 20254. In The Netherlands, Norway and Saudi Arabia, 99 percent of the population used the internet as of February 2025. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Eastern Asia was home to the largest number of online users worldwide – over 1.34 billion at the latest count. Southern Asia ranked second, with around 1.2 billion internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2024, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in African countries, with around a ten percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller usage gap between these two genders. As of 2024, global internet usage was higher among individuals between 15 and 24 years old across all regions, with young people in Europe representing the most significant usage penetration, 98 percent. In comparison, the worldwide average for the age group 15–24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

A collaborative project between SPC, the World Fish Centre and the University of Wollongong has produced the first detailed population estimates of people living close to the coast in the 22 Pacific Island Countries and Territories (PICTs). These estimates are stratified into 1, 5, and 10km zones. More information about this dataset: https://sdd.spc.int/mapping-coastal

[1] The Progress by Population Group analysis is a component of the Healthy People 2020 (HP2020) Final Review. The analysis included subsets of the 1,111 measurable HP2020 objectives that have data available for any of six broad population characteristics: sex, race and ethnicity, educational attainment, family income, disability status, and geographic location. Progress toward meeting HP2020 targets is presented for up to 24 population groups within these characteristics, based on objective data aggregated across HP2020 topic areas. The Progress by Population Group data are also available at the individual objective level in the downloadable data set. [2] The final value was generally based on data available on the HP2020 website as of January 2020. For objectives that are continuing into HP2030, more recent data will be included on the HP2030 website as it becomes available: https://res1healthd-o-tgov.vcapture.xyz/healthypeople. [3] For more information on the HP2020 methodology for measuring progress toward target attainment and the elimination of health disparities, see: Healthy People Statistical Notes, no 27; available from: https://res1wwwd-o-tcdcd-o-tgov.vcapture.xyz/nchs/data/statnt/statnt27.pdf. [4] Status for objectives included in the HP2020 Progress by Population Group analysis was determined using the baseline, final, and target value. The progress status categories used in HP2020 were: a. Target met or exceeded—One of the following applies: (i) At baseline, the target was not met or exceeded, and the most recent value was equal to or exceeded the target (the percentage of targeted change achieved was equal to or greater than 100%); (ii) The baseline and most recent values were equal to or exceeded the target (the percentage of targeted change achieved was not assessed). b. Improved—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved 10% or more of the targeted change. c. Little or no detectable change—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was not statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved less than 10% of the targeted change; (iii) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was not statistically significant; (iv) Movement was away from the baseline and target, standard errors were not available, and the objective had moved less than 10% relative to the baseline; (v) No change was observed between the baseline and the final data point. d. Got worse—One of the following applies: (i) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was statistically significant; (ii) Movement was away from the baseline and target, standard errors were not available, and the objective had moved 10% or more relative to the baseline. NOTE: Measurable objectives had baseline data. SOURCE: National Center for Health Statistics, Healthy People 2020 Progress by Population Group database.

Estimated number of persons on July 1st, by age group and gender, for Canada, provinces and territories, health regions and peer groups.

In 2024, it was estimated that over **** million people in the United States had used cocaine at some point in their life. The number of people in the United States who stated they had used cocaine in the past month has fluctuated over the past decade, but over *** million people reported they had used cocaine in the past month as of 2023. Cocaine use among teens The percentage of U.S. students in grades *, **, and ** that had used cocaine in their lifetime has gradually decreased since 1999. At that time, around *** percent of students stated they had used cocaine in their lifetime, while in 2021 just *** percent of students said so. Perhaps unsurprisingly, perceived availability of cocaine among **** graders has also decreased over the past couple decades, with about ** percent of **** graders stating cocaine was “fairly easy” or “very easy” to get in 2021, compared to almost ** percent who reported it was easy to get in 1990. The most common illicit drugs U.S. students in grades *, **, and ** reported having used in their lifetime were marijuana, inhalants, and hallucinogens such as LSD and mushrooms. Deaths from cocaine In 2020, there were ****** drug poisoning deaths involving cocaine in the United States. The number of overdose deaths involving cocaine has increased significantly over the past few years as part of the ongoing opioid epidemic. Although, it is possible to die of an overdose just from using cocaine, many overdose deaths in the U.S. that involved cocaine also involved the use of opioids. The rate of overdose deaths involving cocaine is almost ***** times higher among men than women, but both have seen increases in the rate of overdose death in recent years. Considering race and ethnicity, the rate of overdose deaths involving cocaine is by far highest among black, non-Hispanics and lowest among Asian/Pacific Islander, non-Hispanics.

TikTok, a social video app launched in 2016 used for sharing and creating video content, continues to grow in popularity. As of 2022, approximately 41 percent of users in the U.S. engaged with the popular social video app. Around seven in 10 respondents aged between 18 and 19 years were using TikTok, while usage among respondents aged between 20 and 29 years was approximately 56 percent.

TikTok global usage In 2021, TikTok had 1 billion active monthly users worldwide, a growth of 45 percent on the previous year. As of April 2021, the majority of global TikTok users spent less than one hour per week on the platform. Eleven percent of users spent five to ten hours a week on the app, and six percent were using it for ten hours or more per week.

Users' opinion: safety concerns and positive influenceOnline TikTok challenges and hoaxes have been a topic of discussion in recent years, with parents raising concerns about safety regarding content posted on the platform. As for U.S. adults’ opinions of TikTok, favorable attitudes towards the platform decrease with age. Overall, as of November 2021, 33 percent of users aged 18 to 34 years had a favorable opinion of the app, but just one in 10 users aged between 45 and 64 years felt the same. Around 20 percent of all adults had a very unfavorable view of TikTok. Despite the criticism, the platform hosts a large number of positive influencers, focusing on themes such as mental health awareness and body positivity. In 2021, one of the most followed TikTok educators and activists was Nicole Lilly Christou, with her profile @nikkililly reporting approximately 7.7 million followers in the United Kingdom alone.

About this dataset

Context

The dataset tabulates the United States population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for United States. The dataset can be utilized to understand the population distribution of United States by age. For example, using this dataset, we can identify the largest age group in United States.

Key observations

The largest age group in United States was for the group of age 30 to 34 years years with a population of 22.71 million (6.86%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in United States was the 80 to 84 years years with a population of 6.25 million (1.89%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the United States is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of United States total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States Population by Age. You can refer the same here

Proportion of population living in 1, 5 and 10km buffer zones for Pacific Island Countries and Territories, determined using most recent Population and Housing Census. Number of people living in 1,5 and 10km buffer zones determined by apportioning population projections.

Find more Pacific data on PDH.stat.

The American Community Survey (ACS) is a nationwide survey designed to provide communities a fresh look at how they are changing. The ACS replaced the decennial census long form in 2010 and thereafter by collecting long form type information throughout the decade rather than only once every 10 years. Questionnaires are mailed to a sample of addresses to obtain information about households -- that is, about each person and the housing unit itself. The American Community Survey produces demographic, social, housing and economic estimates in the form of 1 and 5-year estimates based on population thresholds. The strength of the ACS is in estimating population and housing characteristics. The data profiles provide key estimates for each of the topic areas covered by the ACS for the nation, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Although the ACS produces population, demographic and housing unit estimates,it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns, and estimates of housing units for states and counties. For 2010 and other decennial census years, the Decennial Census provides the official counts of population and housing units.

These are the key social media statistics that you need to know.

[1] Status is determined using the baseline, final, and target value. The statuses used in Healthy People 2020 were: 1 - Target met or exceeded—One of the following applies: (i) At baseline, the target was not met or exceeded, and the most recent value was equal to or exceeded the target. (The percentage of targeted change achieved was equal to or greater than 100%.); (ii) The baseline and most recent values were equal to or exceeded the target. (The percentage of targeted change achieved was not assessed.) 2 - Improved—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved 10% or more of the targeted change. 3 - Little or no detectable change—One of the following applies: (i) Movement was toward the target, standard errors were available, and the percentage of targeted change achieved was not statistically significant; (ii) Movement was toward the target, standard errors were not available, and the objective had achieved less than 10% of the targeted change; (iii) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was not statistically significant; (iv) Movement was away from the baseline and target, standard errors were not available, and the objective had moved less than 10% relative to the baseline; (v) No change was observed between the baseline and the final data point. 4 - Got worse—One of the following applies: (i) Movement was away from the baseline and target, standard errors were available, and the percent change relative to the baseline was statistically significant; (ii) Movement was away from the baseline and target, standard errors were not available, and the objective had moved 10% or more relative to the baseline. 5 - Baseline only—The objective only had one data point, so progress toward target attainment could not be assessed. Note that if additional data points did not meet the criteria for statistical reliability, data quality, or confidentiality, the objective was categorized as baseline only. 6 - Informational—A target was not set for this objective, so progress toward target attainment could not be assessed. [2] The final value is generally based on data available on the Healthy People 2020 website as of January 2020. For objectives that are continuing into Healthy People 2030, more recent data are available on the Healthy People 2030 website: https://health.gov/healthypeople. [3] For objectives that moved toward their targets, movement toward the target was measured as the percentage of targeted change achieved (unless the target was already met or exceeded at baseline): Percentage of targeted change achieved = (Final value - Baseline value) / (HP2020 target - Baseline value) * 100 [4] For objectives that were not improving, did not meet or exceed their targets, and did not move towards their targets, movement away from the baseline was measured as the magnitude of the percent change from baseline: Magnitude of percent change from baseline = |Final value - Baseline value| / Baseline value * 100 [5] Statistical significance was tested when the objective had a target, at least two data points (of unequal value), and available standard errors of the data. A normal distribution was assumed. All available digits were used to test statistical significance. Statistical significance of the percentage of targeted change achieved or the magnitude of the percentage change from baseline was assessed at the 0.05 level using a normal one-sided test. [6] For more information on the Healthy People 2020 methodology for measuring progress toward target attainment and the elimination of health disparities, see: Healthy People Statistical Notes, no 27; available from: https://www.cdc.gov/nchs/data/sta

Data source(s): - Sport England (https://www.sportengland.org/know-your-audience/data/active-lives/active-lives-data-tables) Dataset(s) used:- Exercise and Sports Levels (Children and Young People in school years 1-11)Statistic(s) used:Number of people who are active* less than an average of 30 minutes a day in the academic year 2017/18 (*moderate or vigorous physical activity).The datasets report statistics based on administrative areas (Districts). However, those areas’ boundaries have been generalised in this dataset. It is recommended that you overlay the official District administrative boundaries from the Living Atlas on top of this data, to view the accurate boundary lines.

TikTok has 136 million monthly active users in the US alone.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

Statistical open data on LAU regions of Slovakia, Czech Republic, Poland, Hungary (and other countries in the future). LAU1 regions are called counties, okres, okresy, powiat, járás, járási, NUTS4, LAU, Local Administrative Units, ... and there are 733 of them in this V4 dataset. Overall, we cover 733 regions which are described by 137.828 observations (panel data rows) and more than 1.760.229 data points.

This LAU dataset contains panel data on population, on age structure of inhabitants, on number and on structure of registered unemployed. Dataset prepared by Michal Páleník. Output files are in json, shapefiles, xls, ods, json, topojson or CSV formats. Downloadable at zenodo.org.

This dataset consists of:

data on unemployment (by gender, education and duration of unemployment),

data on vacancies,

open data on population in Visegrad counties (by age and gender),

data on unemployment share.

Combined latest dataset

dataset of the latest available data on unemployment, vacancies and population

dataset includes map contours (shp, topojson or geojson format), relation id in OpenStreetMap, wikidata entry code,

it also includes NUTS4 code, LAU1 code used by national statistical office and abbreviation of the region (usually license plate),

source of map contours is OpenStreetMap, licensed under ODbL

no time series, only most recent data on population and unemployment combined in one output file

columns: period, lau, name, registered_unemployed, registered_unemployed_females, disponible_unemployed, low_educated, long_term, unemployment_inflow, unemployment_outflow, below_25, over_55, vacancies, pop_period, TOTAL, Y15-64, Y15-64-females, local_lau, osm_id, abbr, wikidata, population_density, area_square_km, way

Slovakia – SK: 79 LAU1 regions, data for 2024-10-01, 1.659 data,

Czech Republic – CZ: 77 LAU1 regions, data for 2024-10-01, 1.617 data,

Poland – PL: 380 LAU1 regions, data for 2024-09-01, 6.840 data,

Hungary – HU: 197 LAU1 regions, data for 2024-10-01, 2.955 data,

13.071 data in total.

column/number of observations description SK CZ PL HU

period period (month and year) the data is for 79 77 380 197

lau LAU code of the region 79 77 380 197

name name of the region in local language 79 77 380 197

registered_unemployed number of unemployed registered at labour offices 79 77 380 197

registered_unemployed_females number of unemployed women 79 77 380 197

disponible_unemployed unemployed able to accept job offer 79 77 0 0

low_educated unmployed without secondary school (ISCED 0 and 1) 79 77 380 197

long_term unemployed for longer than 1 year 79 77 380 0

unemployment_inflow inflow into unemployment 79 77 0 0

unemployment_outflow outflow from unemployment 79 77 0 0

below_25 number of unemployed below 25 years of age 79 77 380 197

over_55 unemployed older than 55 years 79 77 380 197

vacancies number of vacancies reported by labour offices 79 77 380 0

pop_period date of population data 79 77 380 197

TOTAL total population 79 77 380 197

Y15-64 number of people between 15 and 64 years of age, population in economically active age 79 77 380 197

Y15-64-females number of women between 15 and 64 years of age 79 77 380 197

local_lau region's code used by local labour offices 79 77 380 197

osm_id relation id in OpenStreetMap database 79 77 380 197

abbr abbreviation used for this region 79 77 380 0

wikidata wikidata identification code 79 77 380 197

population_density population density 79 77 380 197

area_square_km area of the region in square kilometres 79 77 380 197

way geometry, polygon of given region 79 77 380 197

Unemployment dataset

time series of unemployment data in Visegrad regions

by gender, duration of unemployment, education level, age groups, vacancies,

columns: period, lau, name, registered_unemployed, registered_unemployed_females, disponible_unemployed, low_educated, long_term, unemployment_inflow, unemployment_outflow, below_25, over_55, vacancies

Slovakia – SK: 79 LAU1 regions, data for 334 periods (1997-01-01 ... 2024-10-01), 202.082 data,

Czech Republic – CZ: 77 LAU1 regions, data for 244 periods (2004-07-01 ... 2024-10-01), 147.528 data,

Poland – PL: 380 LAU1 regions, data for 189 periods (2005-03-01 ... 2024-09-01), 314.100 data,

Hungary – HU: 197 LAU1 regions, data for 106 periods (2016-01-01 ... 2024-10-01), 104.408 data,

768.118 data in total.

column/number of observations description SK CZ PL HU

period period (month and year) the data is for 26 386 18 788 71 772 20 882

lau LAU code of the region 26 386 18 788 71 772 20 882

name name of the region in local language 26 386 18 788 71 772 20 882

registered_unemployed number of unemployed registered at labour offices 26 386 18 788 71 772 20 882

registered_unemployed_females number of unemployed women 26 386 18 788 62 676 20 882

disponible_unemployed unemployed able to accept job offer 25 438 18 788 0 0

low_educated unmployed without secondary school (ISCED 0 and 1) 11 771 9855 41 388 20 881

long_term unemployed for longer than 1 year 24 253 9855 41 388 0

unemployment_inflow inflow into unemployment 26 149 16 478 0 0

unemployment_outflow outflow from unemployment 26 149 16 478 0 0

below_25 number of unemployed below 25 years of age 11 929 9855 17 100 20 881

over_55 unemployed older than 55 years 11 929 9855 17 100 20 882

vacancies number of vacancies reported by labour offices 11 692 18 788 62 676 0

Population dataset

time series on population by gender and 5 year age groups in V4 counties

columns: period, lau, name, gender, TOTAL, Y00-04, Y05-09, Y10-14, Y15-19, Y20-24, Y25-29, Y30-34, Y35-39, Y40-44, Y45-49, Y50-54, Y55-59, Y60-64, Y65-69, Y70-74, Y75-79, Y80-84, Y85-89, Y90-94, Y_GE95, Y15-64

Slovakia – SK: 79 LAU1 regions, data for 28 periods (1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 152.628 data,

Czech Republic – CZ: 78 LAU1 regions, data for 24 periods (2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 125.862 data,

Poland – PL: 382 LAU1 regions, data for 29 periods (1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 626.941 data,

Hungary – HU: 197 LAU1 regions, data for 11 periods (2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 86.680 data,

992.111 data in total.

column/number of observations description SK CZ PL HU

period period (month and year) the data is for 6636 5574 32 883 4334

lau LAU code of the region 6636 5574 32 883 4334

name name of the region in local language 6636 5574 32 883 4334

gender gender (male or female) 6636 5574 32 883 4334

TOTAL total population 6636 5574 32 503 4334

Y00-04 inhabitants between 00 to 04 years inclusive 6636 5574 32 503 4334

Y05-09 number of inhabitants between 05 to 09 years of age 6636 5574 32 503 4334

Y10-14 number of people between 10 to 14 years inclusive 6636 5574 32 503 4334

Y15-19 number of inhabitants between 15 to 19 years of age 6636 5574 32 503 4334

Y20-24 number of people between 20 to 24 years inclusive 6636 5574 32 503 4334

Y25-29 number of inhabitants between 25 to 29 years of age 6636 5574 32 503 4334

Y30-34 inhabitants between 30 to 34 years inclusive 6636 5574 32 503 4334

Y35-39 number of inhabitants between 35 to 39 years of age 6636 5574 32 503 4334

Y40-44 inhabitants between 40 to 44 years inclusive 6636 5574 32 503 4334

Y45-49 number of inhabitants younger than 49 and older than 45 years 6636 5574 32 503 4334

Y50-54 inhabitants between 50 to 54 years inclusive 6636 5574 32 503 4334

Y55-59 number of inhabitants between 55 to 59 years of age 6636 5574 32 503 4334

Y60-64 inhabitants between 60 to 64 years inclusive 6636 5574 32 503 4334

Y65-69 number of inhabitants younger than 69 and older than 65 years 6636 5574 32 503 4334

Y70-74 inhabitants between 70 to 74 years inclusive 6636 5574 24 670 4334

Y75-79 number of inhabitants between 75 to 79 years of age 6636 5574 24 670 4334

Y80-84 number of people between 80 to 84 years inclusive 6636 5574 24 670 4334

Y85-89 number of inhabitants younger than 89 and older than 85 years 6636 5574 0 0

Y90-94 inhabitants between 90 to 94 years inclusive 6636 5574 0 0

Y_GE95 number of people 95 years or older 6636 3234 0 0

Y15-64 number of people between 15 and 64 years of age, population in economically active age 6636 5574 32 503 4334

Notes

more examples at www.iz.sk

NUTS4 / LAU1 / LAU codes for HU and PL are created by me, so they can (and will) change in the future; CZ and SK NUTS4 codes are used by local statistical offices, so they should be more stable

NUTS4 codes are consistent with NUTS3 codes used by Eurostat

local_lau variable is an identifier used by local statistical office

abbr is abbreviation of region's name, used for map purposes (usually cars' license plate code; except for Hungary)

wikidata is code used by wikidata

osm_id is region's relation number in the OpenStreetMap database

Example outputs

you can download data in CSV, xml, ods, xlsx, shp, SQL, postgis, topojson, geojson or json format at 📥 doi:10.5281/zenodo.6165135

Counties of Slovakia – unemployment rate in Slovak LAU1 regions

Regions of the Slovak Republic

Unemployment of Czechia and Slovakia – unemployment share in LAU1 regions of Slovakia and Czechia

interactive map on unemployment in Slovakia

Slovakia – SK, Czech Republic – CZ, Hungary – HU, Poland – PL, NUTS3 regions of Slovakia

download at 📥 doi:10.5281/zenodo.6165135

suggested citation: Páleník, M. (2024). LAU1 dataset [Data set]. IZ Bratislava. https://doi.org/10.5281/zenodo.6165135

I’ve compiled a list of the latest social media user statistics showing just how big social media has become and where it’s likely to go in the future.

Which countries spent the most and least time on social media?

How many people are on social media? Social media usage is one of the most popular online activities and in 2021, ** percent of the population in the United States had a social networking profile, representing a *** percent increase from the ** percent usage reach in the previous year. This equals approximately 223 million U.S. social media users as of 2020. Global social media accessAccording to estimates, the number of worldwide social media users reached *** billion in January 2021. The overall most popular social network based on active users is the American market leader Facebook. In January 2021, Facebook had some **** billion accounts, followed by YouTube and WhatsApp with roughly *** billion and *** billion users respectively. The regions with the highest penetration of social media users are Western and Northern Europe. Social media audiences in the United StatesAlthough knowing how many people use social media is a powerful indicator of the tremendous influence such websites and apps have in our day to day life, how people are using them and who these users are is also telling. A report on social media usage released in 2019 shows that among Americans, younger online audiences were more likely to use social networks than older generations. Social media users in the United States use different social networks for a wide range of purposes. In a February 2019 survey, Instagram was the top social network for viewing photos whereas Facebook was more popular for sharing content.

There are currently over 1.5 billion active users on TikTok worldwide.