85 datasets found
  1. Projected global median age 1950-2100

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Projected global median age 1950-2100 [Dataset]. https://www.statista.com/statistics/672669/projected-global-median-age/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    Worldwide
    Description

    This statistic shows the median age of the world population from 1950 to 2100. By 2100, the global median age is projected to be 41.9 years of age.

  2. Global population distribution 1800-2100, by continent

    • statista.com
    Updated Mar 17, 2025
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    Aaron O'Neill (2025). Global population distribution 1800-2100, by continent [Dataset]. https://www.statista.com/topics/776/population/
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    Dataset updated
    Mar 17, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Aaron O'Neill
    Description

    Between 1800 and 2021, the total population of each continent experienced consistent growth, however as growth rates varied by region, population distribution has fluctuated. In the early 19th century, almost 70 percent of the world's population lived in Asia, while fewer than 10 percent lived in Africa. By the end of this century, it is believed that Asia's share will fall to roughly 45 percent, while Africa's will be on course to reach 40 percent. 19th and 20th centuries Fewer than 2.5 percent of the world's population lived in the Americas in 1800, however the demographic transition, along with waves of migration, would see this share rise to almost 10 percent a century later, peaking at almost 14 percent in the 1960s. Europe's share of the global population also grew in the 19th century, to roughly a quarter in 1900, but fell thereafter and saw the largest relative decline during the 20th century. Asia, which has consistently been the world's most populous continent, saw its population share drop by the mid-1900s, but it has been around 60 percent since the 1970s. It is important to note that the world population has grown from approximately one to eight billion people between 1800 and the 2020s, and that declines in population distribution before 2020 have resulted from different growth rates across the continents. 21st century Africa's population share remained fairly constant throughout this time, fluctuating between 7.5 and 10 percent until the late-1900s, but it is set to see the largest change over the 21st century. As Europe's total population is now falling, and it is estimated that the total populations of Asia and the Americas will fall by the 2050s and 2070s respectively, rapid population growth in Africa will see a significant shift in population distribution. Africa's population is predicted to grow from 1.3 to 3.9 billion people over the next eight decades, and its share of the total population will rise to almost 40 percent. The only other continent whose population will still be growing at this time will be Oceania, although its share of the total population has never been more than 0.7 percent.

  3. census-bureau-international

    • kaggle.com
    zip
    Updated May 6, 2020
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    Google BigQuery (2020). census-bureau-international [Dataset]. https://www.kaggle.com/bigquery/census-bureau-international
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    zip(0 bytes)Available download formats
    Dataset updated
    May 6, 2020
    Dataset provided by
    BigQueryhttps://cloud.google.com/bigquery
    Authors
    Google BigQuery
    Description

    Context

    The United States Census Bureau’s international dataset provides estimates of country populations since 1950 and projections through 2050. Specifically, the dataset includes midyear population figures broken down by age and gender assignment at birth. Additionally, time-series data is provided for attributes including fertility rates, birth rates, death rates, and migration rates.

    Querying BigQuery tables

    You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.census_bureau_international.

    Sample Query 1

    What countries have the longest life expectancy? In this query, 2016 census information is retrieved by joining the mortality_life_expectancy and country_names_area tables for countries larger than 25,000 km2. Without the size constraint, Monaco is the top result with an average life expectancy of over 89 years!

    standardSQL

    SELECT age.country_name, age.life_expectancy, size.country_area FROM ( SELECT country_name, life_expectancy FROM bigquery-public-data.census_bureau_international.mortality_life_expectancy WHERE year = 2016) age INNER JOIN ( SELECT country_name, country_area FROM bigquery-public-data.census_bureau_international.country_names_area where country_area > 25000) size ON age.country_name = size.country_name ORDER BY 2 DESC /* Limit removed for Data Studio Visualization */ LIMIT 10

    Sample Query 2

    Which countries have the largest proportion of their population under 25? Over 40% of the world’s population is under 25 and greater than 50% of the world’s population is under 30! This query retrieves the countries with the largest proportion of young people by joining the age-specific population table with the midyear (total) population table.

    standardSQL

    SELECT age.country_name, SUM(age.population) AS under_25, pop.midyear_population AS total, ROUND((SUM(age.population) / pop.midyear_population) * 100,2) AS pct_under_25 FROM ( SELECT country_name, population, country_code FROM bigquery-public-data.census_bureau_international.midyear_population_agespecific WHERE year =2017 AND age < 25) age INNER JOIN ( SELECT midyear_population, country_code FROM bigquery-public-data.census_bureau_international.midyear_population WHERE year = 2017) pop ON age.country_code = pop.country_code GROUP BY 1, 3 ORDER BY 4 DESC /* Remove limit for visualization*/ LIMIT 10

    Sample Query 3

    The International Census dataset contains growth information in the form of birth rates, death rates, and migration rates. Net migration is the net number of migrants per 1,000 population, an important component of total population and one that often drives the work of the United Nations Refugee Agency. This query joins the growth rate table with the area table to retrieve 2017 data for countries greater than 500 km2.

    SELECT growth.country_name, growth.net_migration, CAST(area.country_area AS INT64) AS country_area FROM ( SELECT country_name, net_migration, country_code FROM bigquery-public-data.census_bureau_international.birth_death_growth_rates WHERE year = 2017) growth INNER JOIN ( SELECT country_area, country_code FROM bigquery-public-data.census_bureau_international.country_names_area

    Update frequency

    Historic (none)

    Dataset source

    United States Census Bureau

    Terms of use: 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.

    See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/united-states-census-bureau/international-census-data

  4. Global Urban and Rural Population Trends

    • kaggle.com
    Updated Jun 8, 2024
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    hrterhrter (2024). Global Urban and Rural Population Trends [Dataset]. https://www.kaggle.com/datasets/programmerrdai/global-urban-and-rural-population-trends
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 8, 2024
    Dataset provided by
    Kaggle
    Authors
    hrterhrter
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This comprehensive dataset, derived from the United Nations World Urbanization Prospects 2018, provides detailed insights into the global demographic shifts from 1950 to 2050. It covers a wide range of data points including total, urban, and rural populations, alongside growth rates and urbanization trends across different regions, subregions, and countries.

    Dataset Files WUP2018-F01-Total_Urban_Rural.xls: Population counts for urban and rural areas as of mid-2018, including percentages. WUP2018-F02-Proportion_Urban.xls: Historical and projected percentages of urban populations from 1950 to 2050. WUP2018-F03-Urban_Population.xls: Urban population figures from 1950 to 2050. WUP2018-F04-Rural_Population.xls: Rural population figures from 1950 to 2050. WUP2018-F05-Total_Population.xls: Total population figures from 1950 to 2050. WUP2018-F06-Urban_Growth_Rate.xls: Annual urban population growth rates from 1950 to 2050. WUP2018-F07-Rural_Growth_Rate.xls: Annual rural population growth rates from 1950 to 2050. WUP2018-F08-Total_Growth_Rate.xls: Total population growth rates from 1950 to 2000. WUP2018-F09-Urbanization_Rate.xls: Changes in the rate of urbanization from 1950 to 2050. WUP2018-F10-Rate_Proportion_Rural.xls: Changes in the proportion of rural populations from 1950 to 2050. WUP2018-F18-Total_Population_Annual.xls: Detailed annual total population data from 1950 to 2050. WUP2018-F19-Urban_Population_Annual.xls: Detailed annual urban population data from 1950 to 2050. WUP2018-F20-Rural_Population_Annual.xls: Detailed annual rural population data from 1950 to 2050. WUP2018-F21-Proportion_Urban_Annual.xls: Detailed annual urban population percentages from 1950 to 2050. Potential Uses This dataset is invaluable for researchers, policy makers, urban planners, and sociologists interested in understanding the dynamics of urbanization and its impacts on global development. The data can be used for:

    Analyzing trends in urban and rural growth. Forecasting future demographic shifts. Planning for infrastructure, services, and resources in rapidly urbanizing regions. Studying regional differences in development and urbanization.

  5. Projections of population in Italy 2030-2050

    • statista.com
    Updated Apr 15, 2025
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    Statista (2025). Projections of population in Italy 2030-2050 [Dataset]. https://www.statista.com/statistics/573324/population-projection-italy/
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    Dataset updated
    Apr 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Italy
    Description

    Projections estimate that the population in Italy will decrease in the following years. In January 2025, the Italian population added up to 59 million people, but in 2030 Italians will be 58 million individuals. Twenty years later, the population will be around 52 million people. Low birth rate and old population The birth rate in Italy has constantly dropped in the last years. In 2023, 6.4 children were born per 1,000 inhabitants, three babies less than in 2002. Nationwide, the highest number of births was registered in the southern regions, whereas central Italy had the lowest number of children born every 1,000 people. More specifically, the birth rate in the south stood at 7 infants, while in the center it was equal to 5.9 births. Consequently, the population in Italy has aged over the last decade. Between 2002 and 2024, the age distribution of the Italian population showed a growing share of people aged 65 years and older. As a result, the share of young people decreased. The European exception Similarly, the population in Europe is estimated to decrease in the coming years. In 2024, there were 740 million people living in Europe. In 2100, the figure is expected to drop to 586 million inhabitants. However, projections of the world population suggest that Europe might be the only continent experiencing a population decrease. For instance, the population in Africa could grow from 1.41 billion people in 2022 to 3.92 billion individuals in 2100, the fastest population growth worldwide.

  6. I

    India Population Projection: Single Year

    • ceicdata.com
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    CEICdata.com, India Population Projection: Single Year [Dataset]. https://www.ceicdata.com/en/india/population-projection-single-year/population-projection-single-year
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2039 - Mar 1, 2050
    Area covered
    India
    Variables measured
    Population
    Description

    India Population Projection: Single Year data was reported at 1,667,873,933.000 Person in 2050. This records an increase from the previous number of 1,658,330,351.000 Person for 2049. India Population Projection: Single Year data is updated yearly, averaging 1,394,461,787.000 Person from Mar 2001 (Median) to 2050, with 50 observations. The data reached an all-time high of 1,667,873,933.000 Person in 2050 and a record low of 1,019,001,911.000 Person in 2001. India Population Projection: Single Year data remains active status in CEIC and is reported by CEIC Data. The data is categorized under India Premium Database’s Demographic – Table IN.GAI001: Population Projection: Single Year.

  7. Easing population to 4 billion by 2200 would help people and nature data...

    • figshare.com
    xlsx
    Updated Jul 18, 2025
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    Mark Keegan (2025). Easing population to 4 billion by 2200 would help people and nature data files [Dataset]. http://doi.org/10.6084/m9.figshare.25487545.v1
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    xlsxAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Mark Keegan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The past century of increases in human population and resource consumption has produced some undesirable effects, ranging from environmental degradation to climate change to political unrest. We are accustomed to seeing these dependent variables charted with time on the x-axis. But this study presents metrics of biodiversity, consumption, and pollution and their extremely strong correlations when charted against human population size. Then we suggest that a more rapid yet non-coercive lowering of global Total Fertility Rates to 1.75 by 2050, and holding there, will produce many benefits for current and future generations of our own species and for nature. Among these benefits are reduced CO2 emissions, habitat recovery, protection of wild species, and reduced conflict over scarce resources.

  8. World Population Growth

    • kaggle.com
    Updated Nov 5, 2020
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    Mohaiminul Islam (2020). World Population Growth [Dataset]. https://www.kaggle.com/mohaiminul101/population-growth-annual/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 5, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Mohaiminul Islam
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Context

    In demographics, the world population is the total number of humans currently living, and was estimated to have reached 7,800,000,000 people as of March 2020. It took over 2 million years of human history for the world's population to reach 1 billion, and only 200 years more to reach 7 billion. The world population has experienced continuous growth following the Great Famine of 1315–1317 and the end of the Black Death in 1350, when it was near 370 million. The highest global population growth rates, with increases of over 1.8% per year, occurred between 1955 and 1975 – peaking to 2.1% between 1965 and 1970.[7] The growth rate declined to 1.2% between 2010 and 2015 and is projected to decline further in the course of the 21st century. However, the global population is still increasing[8] and is projected to reach about 10 billion in 2050 and more than 11 billion in 2100.

    Content

    Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. Annual population growth rate. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

    Statistical Concept and Methodology

    Total population growth rates are calculated on the assumption that rate of growth is constant between two points in time. The growth rate is computed using the exponential growth formula: r = ln(pn/p0)/n, where r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods. For information on total population from which the growth rates are calculated, see total population (SP.POP.TOTL).

    Acknowledgements

    Derived from total population. Population source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision, ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme.

  9. Development of the world population until 2050

    • statista.com
    Updated May 25, 2023
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    Statista Research Department (2023). Development of the world population until 2050 [Dataset]. https://www.statista.com/study/135072/demographics-of-india/
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    Dataset updated
    May 25, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The statistic shows the development of the world population from 1950 to 2050. The world population was around 7.38 billion people in 2015.

    The global population

    As shown above, the total number of people living on Earth has more than doubled since the 1950s, and continues to increase. A look at the development of the world population since the beginning of the Common Era shows that such a surge in numbers is unprecedented. The first significant rise in population occurred during the 14th century, after the Black Death had killed approximately 25 million people worldwide. Subsequently, the global population increased slowly but steadily until it reached record numbers between 1950 and 2000.

    The majority of the global population lives on the Asian continent, as a statistic of the world population by continent shows. In around 100 years, it is estimated that population levels on the African continent will have reached similar levels to those we see in Asia today. As for a forecast of the development of the world population, the figures are estimated to have reached more than 10 billion by the 22nd century.

    Growing population numbers pose an increasing risk to the planet, since rocketing numbers equal increased consumption of food and resources. Scientists worry that natural resources, such as oil, and food resources will become scarce, endangering the human race and, even more so, the world’s ecosystem. Nowadays, the number of undernourished / starving people worldwide has decreased slightly, but forecasts paint a darker picture.

  10. Population of USA (2050-1955)

    • kaggle.com
    Updated Apr 26, 2022
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    Anandhu H (2022). Population of USA (2050-1955) [Dataset]. https://www.kaggle.com/datasets/anandhuh/population-data-usa
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 26, 2022
    Dataset provided by
    Kaggle
    Authors
    Anandhu H
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Area covered
    United States
    Description

    Content

    The current population of the United States of America is 334,464,117 as of Saturday, April 16, 2022, based on Worldometer elaboration of the latest United Nations data. This three datasets contain population data of USA (2020 and histIndiaorical), population forecast and population in major cities.

    Attribute Information

    • Year - Years from 2020-1955
    • Population - Population in the respective year
    • Yearly % Change - Percentage Yearly Change in Population
    • Yearly Change - Yearly Change in Population
    • Migrants (net) - Total number of migrants
    • Median Age - Median age of the population
    • Fertility Rate - Fertility rate
    • Density (P/Km²)- Population density (population per square km)
    • Urban Pop %- Percentage of urban population
    • Urban Population- Urban population
    • Country's Share of World Pop - Population share
    • World Population - World Population in the respective year
    • India Global Rank - Global Rank in Population

    Source

    Link : https://www.worldometers.info/world-population/us-population/

    Updated Covid 19 and Other Datasets

    Link : https://www.kaggle.com/anandhuh/datasets

    If you find it useful, please support by upvoting ❤️

    Thank You

  11. T

    Global population survey data set (1950-2018)

    • data.tpdc.ac.cn
    • tpdc.ac.cn
    zip
    Updated Sep 3, 2020
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    Wen DONG (2020). Global population survey data set (1950-2018) [Dataset]. https://data.tpdc.ac.cn/en/data/ece5509f-2a2c-4a11-976e-8d939a419a6c
    Explore at:
    zipAvailable download formats
    Dataset updated
    Sep 3, 2020
    Dataset provided by
    TPDC
    Authors
    Wen DONG
    Area covered
    Description

    "Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."

  12. d

    Data from: West Africa Coastal Vulnerability Mapping: Population...

    • catalog.data.gov
    • dataverse.harvard.edu
    • +2more
    Updated Aug 22, 2025
    + more versions
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    SEDAC (2025). West Africa Coastal Vulnerability Mapping: Population Projections, 2030 and 2050 [Dataset]. https://catalog.data.gov/dataset/west-africa-coastal-vulnerability-mapping-population-projections-2030-and-2050
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    Dataset updated
    Aug 22, 2025
    Dataset provided by
    SEDAC
    Area covered
    Africa, West Africa
    Description

    The West Africa Coastal Vulnerability Mapping: Population Projections, 2030 and 2050 data set is based on an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster but at a coarser 5 arc-minute resolution. Bryan Jones of Baruch College produced country-level projections based on the Shared Socioeconomic Pathway 4 (SSP4). SSP4 reflects a divided world where cities that have relatively high standards of living, are attractive to internal and international migrants. In low income countries, rapidly growing rural populations live on shrinking areas of arable land due to both high population pressure and expansion of large-scale mechanized farming by international agricultural firms. This pressure induces large migration flow to the cities, contributing to fast urbanization, although urban areas do not provide many opportUnities for the poor and there is a massive expansion of slums and squatter settlements. This scenario may not be the most likely for the West Africa region, but it has internal coherence and is at least plausible.

  13. o

    Data from: World Urbanization Prospects

    • data.opendevelopmentmekong.net
    Updated Aug 11, 2017
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    (2017). World Urbanization Prospects [Dataset]. https://data.opendevelopmentmekong.net/dataset/5fd09cc9-ac77-4969-bdad-7581aeb2171f
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    Dataset updated
    Aug 11, 2017
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    World
    Description

    This report presents the highlights of the 2014 Revision of World Urbanization Prospects, which contains the latest estimates of the urban and rural populations of 233 countries or areas from 1950 to 2014 and projections to 2050, as well as estimates of population size from 1950 to 2014 and projections to 2030 for all urban agglomerations with 300,000 inhabitants or more in 2014. The annex tables in these Highlights provide data on the estimated and projected urban and rural populations, the percentage of the population that live in urban areas and the annual growth rate of the percentage urban for 233 countries or areas of the world. The tables also show the rank and annual growth rate of urban agglomerations with 5 million inhabitants or more in 2014.

  14. Z

    Hybrid gridded demographic data for the world, 1950-2020

    • data.niaid.nih.gov
    • zenodo.org
    Updated Apr 27, 2020
    + more versions
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    Chambers, Jonathan (2020). Hybrid gridded demographic data for the world, 1950-2020 [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3768002
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    Dataset updated
    Apr 27, 2020
    Dataset authored and provided by
    Chambers, Jonathan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    This is a hybrid gridded dataset of demographic data for the world, given as 5-year population bands at a 0.5 degree grid resolution.

    This dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4) with the ISIMIP Histsoc gridded population data and the United Nations World Population Program (WPP) demographic modelling data.

    Demographic fractions are given for the time period covered by the UN WPP model (1950-2050) while demographic totals are given for the time period covered by the combination of GPWv4 and Histsoc (1950-2020)

    Method - demographic fractions

    Demographic breakdown of country population by grid cell is calculated by combining the GPWv4 demographic data given for 2010 with the yearly country breakdowns from the UN WPP. This combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP. This makes it possible to calculate exposure trends from 1980 to the present day.

    To combine the UN WPP demographics with the GPWv4 demographics, we calculate for each country the proportional change in fraction of demographic in each age band relative to 2010 as:

    (\delta_{year,\ country,age}^{\text{wpp}} = f_{year,\ country,age}^{\text{wpp}}/f_{2010,country,age}^{\text{wpp}})

    Where:

    • (\delta_{year,\ country,age}^{\text{wpp}}) is the ratio of change in demographic for a given age and and country from the UN WPP dataset.

    • (f_{year,\ country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country, and year.

    • (f_{2010,country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country for the year 2020.

    The gridded demographic fraction is then calculated relative to the 2010 demographic data given by GPWv4.

    For each subset of cells corresponding to a given country c, the fraction of population in a given age band is calculated as:

    (f_{year,c,age}^{\text{gpw}} = \delta_{year,\ country,age}^{\text{wpp}}*f_{2010,c,\text{age}}^{\text{gpw}})

    Where:

    • (f_{year,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for given year, for the grid cell c.

    • (f_{2010,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for 2010, for the grid cell c.

    The matching between grid cells and country codes is performed using the GPWv4 gridded country code lookup data and country name lookup table. The final dataset is assembled by combining the cells from all countries into a single gridded time series. This time series covers the whole period from 1950-2050, corresponding to the data available in the UN WPP model.

    Method - demographic totals

    Total population data from 1950 to 1999 is drawn from ISIMIP Histsoc, while data from 2000-2020 is drawn from GPWv4. These two gridded time series are simply joined at the cut-over date to give a single dataset covering 1950-2020.

    The total population per age band per cell is calculated by multiplying the population fractions by the population totals per grid cell.

    Note that as the total population data only covers until 2020, the time span covered by the demographic population totals data is 1950-2020 (not 1950-2050).

    Disclaimer

    This dataset is a hybrid of different datasets with independent methodologies. No guarantees are made about the spatial or temporal consistency across dataset boundaries. The dataset may contain outlier points (e.g single cells with demographic fractions >1). This dataset is produced on a 'best effort' basis and has been found to be broadly consistent with other approaches, but may contain inconsistencies which not been identified.

  15. Forecast of the total population of Africa 2020-2050

    • statista.com
    Updated Jul 25, 2025
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    Statista (2025). Forecast of the total population of Africa 2020-2050 [Dataset]. https://www.statista.com/statistics/1224205/forecast-of-the-total-population-of-africa/
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    Dataset updated
    Jul 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Africa
    Description

    According to the forecast, Africa's total population would reach nearly 2.5 billion by 2050. In 2025, the continent had around 1.55 billion inhabitants, with Nigeria, Ethiopia, and Egypt as the most populous countries. In the coming years, Africa will experience significant population growth and will close the gap significantly with the Asian population by 2100. Rapid population growth In Africa, the annual growth rate of the population followed an overall increasing trend up to 2013, reaching nearly 2.63 percent. This was followed by a drop to 2.32 percent by 2023. Although population growth was slowing down, it was still growing faster than in all other regions. The reasons behind this rapid growth are various. One factor is the high fertility rate registered in African countries. In 2023, a woman in Somalia, Chad, Niger, the Democratic Republic of Congo, and the Central African Republic had an average of over six children in her reproductive years, the highest rate on the continent. High fertility resulted in a large young population and partly compensated for the high mortality rate in Africa, leading to fast-paced population growth. High poverty levels Africa’s population is concerned with widespread poverty. In 2025, over 438 million people on the continent are extremely poor and live with less than 2.15 U.S. dollars per day. Globally, Africa is the continent hosting the highest poverty rate. In 2025, the countries of Nigeria and the Democratic Republic of the Congo account for over 23 percent of the world's population living in extreme poverty. Nevertheless, the share of the population living in poverty in Africa is forecast to decrease in the coming years.

  16. Countries with the largest projected urban population in 2050

    • statista.com
    Updated May 28, 2025
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    Statista (2025). Countries with the largest projected urban population in 2050 [Dataset]. https://www.statista.com/statistics/875076/countries-with-biggest-urban-population-projection/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    Worldwide
    Description

    This statistic shows the twenty countries with the projected largest urban populations worldwide in 2050. Forecasts estimate that the urban population of China will be **** billion people in 2050.

  17. U.S. - seniors as a percentage of the population 1950-2050

    • infosenior.care
    Updated Sep 22, 2023
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    Statista (2023). U.S. - seniors as a percentage of the population 1950-2050 [Dataset]. https://infosenior.care/statisca1/www.statista.com/statistics/457822/share-of-old-age-population-in-the-total-us-population/index.html
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    Dataset updated
    Sep 22, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, about 17.3 percent of the American population was 65 years old or over; an increase from the last few years and a figure which is expected to reach 22 percent by 2050. This is a significant increase from 1950, when only eight percent of the population was 65 or over.

    A rapidly aging population

    In recent years, the aging population of the United States has come into focus as a cause for concern, as the nature of work and retirement is expected to change in order to keep up. If a population is expected to live longer than the generations before, the economy will have to change as well in order to fulfill the needs of the citizens. In addition, the birth rate in the U.S. has been falling over the last 20 years, meaning that there are not as many young people to replace the individuals leaving the workforce.

    The future population

    It’s not only the American population that is aging -- the global population is, too. By 2025, the median age of the global workforce is expected to be 39.6 years, up from 33.8 years in 1990. Additionally, it is projected that there will be over three million people worldwide aged 100 years and over by 2050.

  18. M

    Mexico MX: Population Projection: Mid Year

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Mexico MX: Population Projection: Mid Year [Dataset]. https://www.ceicdata.com/en/mexico/demographic-projection/mx-population-projection-mid-year
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2039 - Jun 1, 2050
    Area covered
    Mexico
    Variables measured
    Population
    Description

    Mexico MX: Population Projection: Mid Year data was reported at 150,567,503.000 Person in 2050. This records an increase from the previous number of 150,471,915.000 Person for 2049. Mexico MX: Population Projection: Mid Year data is updated yearly, averaging 99,775,434.000 Person from Jun 1950 (Median) to 2050, with 101 observations. The data reached an all-time high of 150,567,503.000 Person in 2050 and a record low of 28,485,180.000 Person in 1950. Mexico MX: Population Projection: Mid Year data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Mexico – Table MX.US Census Bureau: Demographic Projection.

  19. f

    Data_Sheet_1_Projecting wheat demand in China and India for 2030 and 2050:...

    • frontiersin.figshare.com
    docx
    Updated Jun 21, 2023
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    Khondoker Abdul Mottaleb; Gideon Kruseman; Aymen Frija; Kai Sonder; Santiago Lopez-Ridaura (2023). Data_Sheet_1_Projecting wheat demand in China and India for 2030 and 2050: Implications for food security.docx [Dataset]. http://doi.org/10.3389/fnut.2022.1077443.s001
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    docxAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    Frontiers
    Authors
    Khondoker Abdul Mottaleb; Gideon Kruseman; Aymen Frija; Kai Sonder; Santiago Lopez-Ridaura
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China, India
    Description

    IntroductionThe combined populations of China and India were 2.78 billion in 2020, representing 36% of the world population (7.75 billion). Wheat is the second most important staple grain in both China and India. In 2019, the aggregate wheat consumption in China was 96.4 million ton and in India it was 82.5 million ton, together it was more than 35% of the world's wheat that year. In China, in 2050, the projected population will be 1294–1515 million, and in India, it is projected to be 14.89–1793 million, under the low and high-fertility rate assumptions. A question arises as to, what will be aggregate demand for wheat in China and India in 2030 and 2050?MethodsApplying the Vector Error Correction model estimation process in the time series econometric estimation setting, this study projected the per capita and annual aggregate wheat consumptions of China and India during 2019-2050. In the process, this study relies on agricultural data sourced from the Food and Agriculture Organization of the United States (FAO) database (FAOSTAT), as well as the World Bank's World Development Indicators (WDI) data catalog. The presence of unit root in the data series are tested by applying the augmented Dickey-Fuller test; Philips-Perron unit root test; Kwiatkowski-Phillips-Schmidt-Shin test, and Zivot-Andrews Unit Root test allowing for a single break in intercept and/or trend. The test statistics suggest that a natural log transformation and with the first difference of the variables provides stationarity of the data series for both China and India. The Zivot-Andrews Unit Root test, however, suggested that there is a structural break in urban population share and GDP per capita. To tackle the issue, we have included a year dummy and two multiplicative dummies in our model. Furthermore, the Johansen cointegration test suggests that at least one variable in both data series were cointegrated. These tests enable us to apply Vector Error Correction (VEC) model estimation procedure. In estimation the model, the appropriate number of lags of the variables is confirmed by applying the “varsoc” command in Stata 17 software interface. The estimated yearly per capita wheat consumption in 2030 and 2050 from the VEC model, are multiplied by the projected population in 2030 and 2050 to calculate the projected aggregate wheat demand in China and India in 2030 and 2050. After projecting the yearly per capita wheat consumption (KG), we multiply with the projected population to get the expected consumption demand.ResultsThis study found that the yearly per capita wheat consumption of China will increase from 65.8 kg in 2019 to 76 kg in 2030, and 95 kg in 2050. In India, the yearly per capita wheat consumption will increase to 74 kg in 2030 and 94 kg in 2050 from 60.4 kg in 2019. Considering the projected population growth rates under low-fertility assumptions, aggregate wheat consumption of China will increase by more than 13% in 2030 and by 28% in 2050. Under the high-fertility rate assumption, however the aggregate wheat consumption of China will increase by 18% in 2030 and nearly 50% in 2050. In the case of India, under both low and high-fertility rate assumptions, aggregate wheat demand in India will increase by 32-38% in 2030 and by 70-104% in 2050 compared to 2019 level of consumption.DiscussionsOur results underline the importance of wheat in both countries, which are the world's top wheat producers and consumers, and suggest the importance of research and development investments to maintain sufficient national wheat grain production levels to meet China and India's domestic demand. This is critical both to ensure the food security of this large segment of the world populace, which also includes 23% of the total population of the world who live on less than US $1.90/day, as well as to avoid potential grain market destabilization and price hikes that arise in the event of large import demands.

  20. g

    OECD, Total Population (in Thous), Global, 1980-2007 & Projections through...

    • geocommons.com
    Updated May 5, 2008
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    data (2008). OECD, Total Population (in Thous), Global, 1980-2007 & Projections through 2050 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    May 5, 2008
    Dataset provided by
    data
    OECD
    Description

    Total Population (in thous) 1980-2007 and projections through 2050 Original file went back to 1950. Null data of ".." was changed to be -1

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Statista (2025). Projected global median age 1950-2100 [Dataset]. https://www.statista.com/statistics/672669/projected-global-median-age/
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Projected global median age 1950-2100

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6 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2019
Area covered
Worldwide
Description

This statistic shows the median age of the world population from 1950 to 2100. By 2100, the global median age is projected to be 41.9 years of age.

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