This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_population_in_1800. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

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 ---

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?

This dataset contains the population data for countries as of 1 July 2023, sourced from the United Nations via Wikipedia. Includes country names, population figures, percentage change, and continental regions. Ideal for demographic analysis, research, and visualization.

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Context

Global Humanitarian Response Plan COVID-19 administrative level 1 boundaries, gazetteer and population tables for countries covered by the May update of the Global Humanitarian Response Plan COVID-19. https://data.humdata.org/dataset/global-humanitarian-response-plan-covid-19-administrative-boundaries-and-population-statistics

Content

P-codes are unique geographic (geo) identification codes, represented by combinations of letters and/or numbers to identify a specific location or feature on a map or within a database. P-code is an abbreviated term for Place Code. https://wiki.openstreetmap.org/wiki/P-Codes

Data fields:

ADM1_PCODE: Administrative level 1 (various types) P-code

ADM0_PCODE: Administrative level 0 (country or territory) P-code

alpha_3: ISO 3166-1 Alpha 3 country or territory identifier

ADM0_REF: Administrative level 0 (country or territory) reference name (Latin script without special characters)

ADM1_REF: Administrative level 1 (various types) reference name (Latin script without special characters)

Population: Most recent available total population.

Acknowledgements

https://data.humdata.org/dataset/global-humanitarian-response-plan-covid-19-administrative-boundaries-and-population-statistics

Photo by Sharon McCutcheon on Unsplash

Inspiration

Covi-19 Pandemic.

Historical chart and dataset showing total population for Russia by year from 1950 to 2025.

Introduction

Digital Marketing Statistics: In 2024, the digital marketing landscape experienced significant growth, reflecting the increasing reliance on online platforms for business engagement. Global internet users reached 5.35 billion, marking a 1.8% increase from the previous year. Social media usage also expanded, with over 5 billion active user identities, accounting for 62.3% of the global population.

Digital advertising budgets saw a 10% increase between 2023 and 2024, indicating a strategic shift towards online marketing channels. Mobile advertising spending reached a record USD 327 billion worldwide in 2023, while global mobile internet advertising spending surpassed USD 400 billion.

The influencer marketing industry grew substantially, with the global market estimated at USD 24 billion in 2024. Additionally, as of September 2024, 2.71 billion people were shopping online, representing about 34% of the global population.

These statistics underscore the pivotal role of digital marketing in today's business environment, highlighting the necessity for companies to adapt and invest in online strategies to remain competitive. So, let's buckle up because we're diving into the fascinating world of digital marketing statistics to show you why it's more important than ever.

Introduction

Agriculture Statistics: By 2050, the demand for food is projected to increase by almost 70%, in line with the rapidly growing global population. A study conducted in the United States revealed that approximately 9.9% of the world's population still suffers from hunger, highlighting the significant challenge of feeding around 20 million people. Given the uncertain environmental changes, technological innovation in agriculture has become crucial.

The agricultural industry has undergone remarkable transformation in recent years, largely attributed to technological advancements. From drones to automated tractors, technology has played a pivotal role in enhancing the effectiveness, sustainability, and precision of agriculture. This article aims to delve deeper into agricultural statistics.

Introduction

LGBT Statistics: The LGBTQ+ community, encompassing individuals who identify as lesbian, gay, bisexual, transgender, queer, or questioning, represents a diverse and vibrant segment of the global population. This community includes people of all races, ages, and socioeconomic backgrounds, contributing significantly to the cultural, economic, and social fabric of society.

Historically, the LGBTQ+ rights movement gained momentum in the mid-20th century, with milestones such as the Stonewall Riots of 1969 catalyzing change. This article will guide you effectively throughout as it covers all recent trends and analyses of LGBT from different perspectives.

Introduction

Millionaire Statistics: A growing number of individuals are becoming millionaires across the globe due to economic growth, an increase in stock markets, and entrepreneurial ventures. Studies show that by the year 2024, the population of millionaires and born and bred individuals across the globe will still grow due to the growing concentration of wealth in certain areas and sectors.

An analysis of the statistics on millionaires paints a clear picture of how wealth is being shared among the general populace and the levels of economic oppression in existence, as well as financial matters in the international arena.

This piece demonstrates the situational picture of millionaire statistics in the world, their wealth, their geographical distribution, and projections of their population in the years to come.

Introduction

Gmail Statistics: Gmail, launched by Google in 2004, has evolved into one of the most widely used email services globally, with over 2.5 billion active users as of 2025, accounting for approximately 30.9% of the global population. This widespread adoption is attributed to its seamless integration with Google services, user-friendly interface, and robust security features. In September 2024, Gmail recorded an impressive 10 billion monthly visits.

Gmail holds a significant position in the email client market, with a 30.70% share globally, making it the second most popular email platform after Apple Mail. Users send over 121 billion emails daily through Gmail. On average, a Gmail user maintains 1.7 accounts and checks their inbox approximately 12 times a day, reflecting the platform's integral role in daily communication.

Country-wise, Gmail's usage is notably high in Indonesia and India, with 82.6% and 82.4% of their populations using the service, respectively. In the United States, Gmail accounts for 41.9% of email users. The platform's popularity is further bolstered by its availability in 105 languages and its strong presence in mobile usage, with 75% of users accessing Gmail on mobile devices.

Gmail's robust spam filters block about 99.9% of dangerous links, spam, and malware from reaching users’ inboxes. Additionally, Gmail offers 15GB of free storage shared across Gmail, Google Drive, and Google Photos, catering to users' substantial data storage needs.

These statistics underscore Gmail's pivotal role in global communication, highlighting its extensive reach, user engagement, and continuous growth in the digital communication landscape. So, let’s buckle up and get ready to explore some fascinating statistics about this email giant.

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Introduction

Prison Statistics: Prisons serve as critical institutions within global justice systems, reflecting societal approaches to punishment, deterrence, and rehabilitation. As of 2024, approximately 11.5 million individuals are incarcerated worldwide, with about 10.8 million men and 700,000 women. This represents a 5.5% increase since 2012, indicating a persistent reliance on incarceration.

Incarceration rates vary significantly across regions. North America has the highest rate, with 489 prisoners per 100,000 people in 2022, down from 647 in 2012. In contrast, Southern Asia reported rates below 100 per 100,000 population. El Salvador leads globally with 1,086 prisoners per 100,000 people, followed by Cuba at 794 and Rwanda at 637.

The female prison population has surged by 57% since 2000, outpacing the 22% increase in the male prison population. This rise is often linked to factors such as poverty, discriminatory laws, and limited access to legal resources. Notably, one in three incarcerated individuals globally is held in pre-trial detention, highlighting concerns about legal processes and the presumption of innocence.

Understanding these demographics is essential for evaluating the effectiveness of incarceration as a tool for justice and rehabilitation. It also underscores the need for reforms that address systemic issues contributing to high incarceration rates. Let's explore some intriguing statistics about prisoners in the United States.

This data package includes the underlying data to replicate the charts and calculations presented in Migration or stagnation: Aging and economic growth in Korea today, the world tomorrow, PIIE Working Paper 24-18.

If you use the data, please cite as:

Clemens, Michael. 2024. Migration or stagnation: Aging and economic growth in Korea today, the world tomorrow. PIIE Working Paper 24-18. Washington: Peterson Institute for International Economics.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Introduction

Smartphone Usage Statistics: Smartphones have become a vital part of everyday life, especially in developed countries, where about 75% of people have one. Worldwide, smartphones make up nearly 90% of all mobile phones, with over 7.2 billion smartphones in use as of 2024. This growth shows no signs of stopping, as the smartphone market grew by 7.8% in the first quarter of 2024.

By the end of 2023, around 70% of the global population owned a smartphone. Many people have more than one device, pushing smartphone subscriptions past 7 billion. It’s expected that this number could reach nearly 8 billion by 2028, showing that smartphones are still in high demand and important in our daily lives. We shall shed light on Smartphone Usage Statistics through this article.

Introduction

CBD Statistics: CBD has become a global product, with its popularity growing quickly. What started as a small alternative to traditional medicine is now a mainstream trend. Today, CBD isn’t just found in oils, capsules, and tinctures. You can find CBD in many different products all over the world, such as CBD makeup, bath bombs, toothpaste, sheets, and even dog treats.

There are many different opinions about whether CBD is a miracle medicine or just another health fad. To help answer this, looking at CBD Statistics can give us a better idea of what's true. We’ve done a survey and created a reliable study to help you understand the possible health benefits of CBD.

Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025. For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset contains 18 tables which draw upon data from the 2021 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template. 17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The 18th table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole *- Data on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000. Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts greater than 10 are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero. Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7) 1. Total - Private households by tenure including presence of mortgage payments and subsidized housing 2. Owner 3. With mortgage 4. Without mortgage 5. Renter 6. Subsidized housing 7. Not subsidized housing Housing indicators in Core Housing Universe (12) 1. Total - Private Households by core housing need status 2. Households examined for core housing need 3. Households in core...