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.

This layer was created by Duncan Smith and based on work by the European Commission JRC and CIESIN. A description from his website follows:--------------------A brilliant new dataset produced by the European Commission JRC and CIESIN Columbia University was recently released- the Global Human Settlement Layer (GHSL). This is the first time that detailed and comprehensive population density and built-up area for the world has been available as open data. As usual, my first thought was to make an interactive map, now online at- http://luminocity3d.org/WorldPopDen/The World Population Density map is exploratory, as the dataset is very rich and new, and I am also testing out new methods for navigating statistics at both national and city scales on this site. There are clearly many applications of this data in understanding urban geographies at different scales, urban development, sustainability and change over time.

This aggregate data collection is an extract of the International Data Base (IDB), a computerized central repository of demographic, economic, and social data for all countries of the world. Data available in this collection include total midyear population estimates and projections (1950-1985), percent urban population, estimates and projections of crude birth rate, crude death rate, net migration rate, rate of natural increase, and annual growth rate, infant mortality rate and life expectancy at birth by sex, percent literate by sex, and percent of the labor force in agriculture.

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.

****Web Scraping using Python**** --Worldometer website. --Scrape the Worldometer website using the Beautiful Soup and Requests library. --Collect the data of Country wise Population, World_Share(%) and 'Land_Area_Km². --Analyze the data by using matplotlib and seaborn library. --Make a Scatter plot by using Seaborn and Matplotlib of 'Population(2020) vs Land_Area_Km². --Create a Line plot of Country vs Land_Area_Km² for top5 countries by population. --Create a Line plot of 'Country wise Population(2020)' of top5 countries based on population.

The Africa Population Distribution Database provides decadal population density data for African administrative units for the period 1960-1990. The databsae was prepared for the United Nations Environment Programme / Global Resource Information Database (UNEP/GRID) project as part of an ongoing effort to improve global, spatially referenced demographic data holdings. The database is useful for a variety of applications including strategic-level agricultural research and applications in the analysis of the human dimensions of global change.

This documentation describes the third version of a database of administrative units and associated population density data for Africa. The first version was compiled for UNEP's Global Desertification Atlas (UNEP, 1997; Deichmann and Eklundh, 1991), while the second version represented an update and expansion of this first product (Deichmann, 1994; WRI, 1995). The current work is also related to National Center for Geographic Information and Analysis (NCGIA) activities to produce a global database of subnational population estimates (Tobler et al., 1995), and an improved database for the Asian continent (Deichmann, 1996). The new version for Africa provides considerably more detail: more than 4700 administrative units, compared to about 800 in the first and 2200 in the second version. In addition, for each of these units a population estimate was compiled for 1960, 70, 80 and 90 which provides an indication of past population dynamics in Africa. Forthcoming are population count data files as download options.

African population density data were compiled from a large number of heterogeneous sources, including official government censuses and estimates/projections derived from yearbooks, gazetteers, area handbooks, and other country studies. The political boundaries template (PONET) of the Digital Chart of the World (DCW) was used delineate national boundaries and coastlines for African countries.

For more information on African population density and administrative boundary data sets, see metadata files at [http://na.unep.net/datasets/datalist.php3] which provide information on file identification, format, spatial data organization, distribution, and metadata reference.

References:

Deichmann, U. 1994. A medium resolution population database for Africa, Database documentation and digital database, National Center for Geographic Information and Analysis, University of California, Santa Barbara.

Deichmann, U. and L. Eklundh. 1991. Global digital datasets for land degradation studies: A GIS approach, GRID Case Study Series No. 4, Global Resource Information Database, United Nations Environment Programme, Nairobi.

UNEP. 1997. World Atlas of Desertification, 2nd Ed., United Nations Environment Programme, Edward Arnold Publishers, London.

WRI. 1995. Africa data sampler, Digital database and documentation, World Resources Institute, Washington, D.C.

Analysis of ‘Population by Country - 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tanuprabhu/population-by-country-2020 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

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

--- Original source retains full ownership of the source dataset ---

The total population in the United States was estimated at 341.2 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - United States Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Dataset

This dataset was created by Walter Maffione

Contents

This dataset merges 1972 data on social and military expenditures in 132 nations selected from WORLD MILITARY AND SOCIAL EXPENDITURES, 1974 (see Data Source) with information on demographic attributes of the same nations in 1972 obtained from WORLD POPULATION, 1973 (ICPSR 5032), collected by the United States Bureau of the Census. Military expenditures as well as international peacekeeping, public education, public health, and foreign economic aid expenditures are presented as both raw and per capita measures. Other information includes number of teachers, school age population per teacher, illiteracy rates, number of qualified physicians, population per physician, infant mortality rates, and population per soldier.

The United Nations Energy Statistics Database (UNSTAT) is a comprehensive collection of international energy and demographic statistics prepared by the United Nations Statistics Division. The 2004 version represents the latest in the series of annual compilations which commenced under the title World Energy Supplies in Selected Years, 1929-1950. Supplementary series of monthly and quarterly data on production of energy may be found in the Monthly Bulletin of Statistics. The database contains comprehensive energy statistics for more than 215 countries or areas for production, trade and intermediate and final consumption (end-use) for primary and secondary conventional, non-conventional and new and renewable sources of energy. Mid-year population estimates are included to enable the computation of per capita data. Annual questionnaires sent to national statistical offices serve as the primary source of information. Supplementary data are also compiled from national, regional and international statistical publications. The Statistics Division prepares estimates where official data are incomplete or inconsistent. The database is updated on a continuous basis as new information and revisions are received. This metadata file represents the population statistics during the expressed time. For more information about the country site codes, click this link to the United Nations "Standard country or area codes for statistical use": https://unstats.un.org/unsd/methodology/m49/overview/

According to latest figures, the Chinese population decreased by 1.39 million to around 1.408 billion people in 2024. After decades of rapid growth, China arrived at the turning point of its demographic development in 2022, which was earlier than expected. The annual population decrease is estimated to remain at moderate levels until around 2030 but to accelerate thereafter. Population development in China China had for a long time been the country with the largest population worldwide, but according to UN estimates, it has been overtaken by India in 2023. As the population in India is still growing, the country is very likely to remain being home of the largest population on earth in the near future. Due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades, displaying an annual population growth rate of -0.1 percent in 2024. Nevertheless, compared to the world population in total, China held a share of about 17 percent of the overall global population in 2024. China's aging population In terms of demographic developments, the birth control efforts of the Chinese government had considerable effects on the demographic pyramid in China. Upon closer examination of the age distribution, a clear trend of an aging population becomes visible. In order to curb the negative effects of an aging population, the Chinese government abolished the one-child policy in 2015, which had been in effect since 1979, and introduced a three-child policy in May 2021. However, many Chinese parents nowadays are reluctant to have a second or third child, as is the case in most of the developed countries in the world. The number of births in China varied in the years following the abolishment of the one-child policy, but did not increase considerably. Among the reasons most prominent for parents not having more children are the rising living costs and costs for child care, growing work pressure, a growing trend towards self-realization and individualism, and changing social behaviors.

Context

Learning Web Scraping in order to build my own datasets, and this is the first one in the learning process. Let's try and build great datasets in the future for better analysis and predictions.

Content

Scraped the data on March 10, 2020, from https://www.worldometers.info/world-population/population-by-country/ Dataset represents the population count country-wise for a specific time period.

Acknowledgements

Firstly, Thanks to the Content creator on the website https://www.worldometers.info, who provides reliable data on the internet. Secondly, To the Tutor who taught me how to scrape websites.

Inspiration

Is this dataset valuable? Where can we utilize this dataset in data science?

Abstract (en): This data collection contains demographic statistics for the populations of 171 countries or areas throughout the world between 1966 and 1974. The data were prepared by the Statistical Office of the United Nations using as primary source a set of questionnaires sent monthly and annually to statistical services and other appropriate government offices. Data include total population by country or area for the years 1966-1974, for males and females, divided into 18 age groups. Other data include ethnic group, urban/rural code, and year, type, and reliability of source document. The populations of 171 countries or areas throughout the world between the years 1966 and 1974.

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key health statistics from a variety of sources to provide a look at global health and population trends. It includes information on nutrition, reproductive health, education, immunization, and diseases from over 200 countries.

Update Frequency: Biannual

For more information, see the World Bank website.

Fork this kernel to get started with this dataset.

Acknowledgements

https://datacatalog.worldbank.org/dataset/health-nutrition-and-population-statistics

https://cloud.google.com/bigquery/public-data/world-bank-hnp

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Citation: The World Bank: Health Nutrition and Population Statistics

Banner Photo by @till_indeman from Unplash.

Inspiration

What’s the average age of first marriages for females around the world?

These data are a collection of demographic statistics for the populations of 125 countries or areas throughout the world, prepared by the Statistical Office of the United Nations. The units of analysis are both country and data year. The primary source of data is a set of questionnaires sent monthly and annually to national statistical services and other appropriate government offices. Data include statistics on approximately 50 types of causes of death for the years 1966 through 1974 for males, females, and total populations.

Country Population (Admin0) using aggregated Facebook high resolution population density data (https://data.humdata.org/organization/facebook).The world population data sourced from Facebook Data for Good is some of the most accurate population density data in the world. The data is accumulated using highly accurate technology to identify buildings from satellite imagery and can be viewed at up to 30-meter resolution. This building data is combined with publicly available census data to create the most accurate population estimates. This data is used by a wide range of nonprofit and humanitarian organizations, for example, to examine trends in urbanization and climate migration or discover the impact of a natural disaster on a region. This can help to inform aid distribution to reach communities most in need. There is both country and region-specific data available. The data also includes demographic estimates in addition to the population density information. This population data can be accessed via the Humanitarian Data Exchange website.

A report on global press freedom in 2020 revealed that ** percent of the world's population lived in a country with total press freedom. Conversely, ** percent lived somewhere without any press freedom at all. Lack of press freedom often means that a country's government regulates what can and cannot be published, putting consumers at risk of being given incorrect or biased information or missing out on certain news topics entirely.

The decline of press freedom

Press freedom is falling on a global level. This is happening not only in countries notorious for poor press freedom scores like Russia, Cuba, and Eritrea, but also across Europe. Press freedom in the United Kingdom has overall declined since 2016, and the same is true of the situation in Austria, Serbia, and Slovenia. Germany’s press freedom score surpassed ** in 2016 and has remained above that level ever since, even reaching ***** in 2021. The drop in press freedom in Europe has been partially attributed to the rise of right-wing populism, and government intervention is increasingly a problem.

Impact on journalists

Limited freedom of the press compromises the safety of journalists and their ability to do their work. The dangers faced by journalists are significantly higher in countries with poor press freedom, notably Mexico, which is the most dangerous country for journalists worldwide. Female journalists also regularly faced gender-based violence and abuse, and close to ** percent of respondents to a global survey on the subject admitted that they reacted to sexist abuse at work by censoring themselves.

The 1965 National Fertility Survey was the first of three surveys that succeeded the Growth of American Families surveys (1955 and 1960) aimed at examining marital fertility and family planning in the United States. Currently married women were queried on the following main topics: residence history, marital history, education, income and employment, family background, religiosity, attitudes toward contraception and sterilization, birth control pill use and other methods of contraception, fecundity, family size, fertility expectations and intentions, abortion, and world population growth. Respondents were asked about their residence history, including what state they grew up in, whether they had lived with both of their parents at the age of 14, and whether they had spent any time living on a farm. Respondents were also asked a series of questions about their marital history. Specifically, they were asked about the duration of their current marriage, whether their current marriage was their first marriage, total number of times they had been married, how previous marriages ended, length of engagement, and whether their husband had children from a previous marriage. Respondents were asked what was the highest grade of school that they had completed, whether they had attended a co-ed college, and to give the same information about their husbands. Respondents were asked about their 1965 income, both individual and combined, their occupation, whether they had been employed since marriage, if and when they stopped working, and whether they were self-employed. They were also asked about their husband's recent employment status. With respect to family background, respondents were asked about their parents' and their husband's parents' nationalities, education, religious preferences, and total number children born alive to their mother and mother-in-law, respectively. In addition, respondents were asked about their, and their husband's, religious practices including their religious preferences, whether they had ever received any Catholic education, how religious-minded they perceived themselves to be, how often they prayed at home, and how often they went to see a minister, rabbi, or priest. Respondents were asked to give their opinions with respect to contraception and sterilization. They were asked whether they approved or disapproved of contraception in general, as well as specific forms of contraception, whether information about birth control should be available to married and unmarried couples, and whether the federal government should support birth control programs in the United States and in other countries. They were also asked whether they approved or disapproved of sterilization operations for men and women and whether they thought such a surgery would impair a man's sexual ability. Respondents were asked about their own knowledge and use of birth control pills. They were asked if they had ever used birth control pills and when they first began using them. They were then asked to give a detailed account of their use of birth control pills between 1960 and 1965. Respondents were also asked to explain when they discontinued use of birth control pills and what the motivation was for doing so. Respondents were also asked about their reproductive cycle, the most fertile days in their cycle, the regularity of their cycle, and whether there were any known reasons why they could not have or would have problems having children. Respondents were asked about their ideal number of children, whether they had their ideal number of children or if they really wanted fewer children, as well as whether their husbands wanted more or less children than they did. Respondents were then asked how many additional births they expected, how many total births they expected, when they expected their next child, and at what age they expected to have their last child. Respondents were asked how they felt about interrupting a pregnancy and whether they approved of abortion given different circumstances such as if the pregnancy endangered the woman's health, if the woman was not married, if the couple could not afford another child, if the couple did not want another child, if the woman thought the child would be deformed, or if the woman had been raped. Respondents were also asked to share their opinions with respect to world population growth. T

The Africa Population (Live) counter shows a continuously updated estimate of the current population of Africa delivered by Worldometer's RTS algorithm, which processes data collected from the United Nations Population Division. From https://www.worldometers.info/world-population/africa-population/