Historical chart and dataset showing World population growth rate by year from 1961 to 2023.

The world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolongued development arc in Sub-Saharan Africa.

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

Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

"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."

This is a hybrid gridded dataset of demographic data for the world, given as 5-year population bands at a 0.25 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). More detailed can be found on the page of the original version (https://doi.org/10.5281/zenodo.3768003).

This release increases the resolution to 0.25˚ and is explicitly designed to match with the grid definition of the ERA5 climate reanalysis dataset. For pre-2000 population data, the ISIMIP Histsoc data was upscaled from it's native 0.5˚ resolution.

World Population Data Set

The population explosion has been a serious topic for years and this data set helps us to analyze that on a granular level.

This dataset contains data about the population count and census data for each country in the world. The data set spans from 1950 to 2013. This data set is acquired from "data.world" website and all the credits go to them

Unadjusted decennial census data from 1950-2000 and projected figures from 2010-2040: summary table of New York City population numbers and percentage share by Borough, including school-age (5 to 17), 65 and Over, and total population.

Midyear population estimates and projections for all countries and areas of the world with a population of 5,000 or more // Source: U.S. Census Bureau, Population Division, International Programs Center// Note: Total population available from 1950 to 2100 for 227 countries and areas. Other demographic variables available from base year to 2100. Base year varies by country and therefore data are not available for all years for all countries. For the United States, total population available from 1950-2060, and other demographic variables available from 1980-2060. See methodology at https://www.census.gov/programs-surveys/international-programs/about/idb.html

Computed prospective ages for 1950-2100 for all countries and regions based on 2017 Revision of the UN World Population Prospects.Content:1. codebook.pdf contains a brief overview of the dataset, its background and a description of the cases and variables.2. methods.pdf is a (draft but complete) write up of the calculations used to create the dataset.3. 2017_prospective-ages.csv is the human readable form of the prospective age dataset containing the calculated prospective old-age thresholds for 241 countries and regions, for the period 1950-2100, for men, women and both together, as well as the proportions of the population (male, female and total) over these thresholds.This figshare fileset is published directly from the github repository ProspectiveAgeData. For an application of this data see the factsheet on ageing in the Middle East and Northern Africa which will be published in Population Horizons journal.

The dataset contains year-wise historically compiled data from the year 1950-51 to 2021-22 on the total population in India, the estimated total quantity of milk produced and its per capita availability in India

Note:

The data from the years 1950-51 to 1979-80 in the dataset is of quinquennial period i.e. data is available for every 5 years period

As of July 2024, Nigeria's population was estimated at around 229.5 million. Between 1965 and 2024, the number of people living in Nigeria increased at an average rate of over two percent. In 2024, the population grew by 2.42 percent compared to the previous year. Nigeria is the most populous country in Africa. By extension, the African continent records the highest growth rate in the world. Africa's most populous country Nigeria was the most populous country in Africa as of 2023. As of 2022, Lagos held the distinction of being Nigeria's biggest urban center, a status it also retained as the largest city across all of sub-Saharan Africa. The city boasted an excess of 17.5 million residents. Notably, Lagos assumed the pivotal roles of the nation's primary financial hub, cultural epicenter, and educational nucleus. Furthermore, Lagos was one of the largest urban agglomerations in the world. Nigeria's youthful population In Nigeria, a significant 50 percent of the populace is under the age of 19. The most prominent age bracket is constituted by those up to four years old: comprising 8.3 percent of men and eight percent of women as of 2021. Nigeria boasts one of the world's most youthful populations. On a broader scale, both within Africa and internationally, Niger maintains the lowest median age record. Nigeria secures the 20th position in global rankings. Furthermore, the life expectancy in Nigeria is an average of 62 years old. However, this is different between men and women. The main causes of death have been neonatal disorders, malaria, and diarrheal diseases.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

The increased world population is among the fierce problems the world is facing right now and it will get uncontrolled in the coming future if proper steps for its betterment were not taken immediately. This world has observed the fastest growth during the 20th century. In the 1950s world population was 2.7 billion, By the end of this year it will cross 8 billion. This dataset is uploaded with the assumption to use your Data Science, Machine learning, and Predictive analytics skills and answer the following questions. 1. Which countries have the highest growth rate. 2. What are the densely populated countries in the world. 3. Keeping in view all the variables in mind which countries should take serious steps to control their population.

Historical dataset of population level and growth rate for the Jingmen, China metro area from 1950 to 2025.

South Asia is one of the most densely populated regions in the world. This dataset comprehensively collects historical materials related to the population of South Asia and previous research results (see data description documents and references for details), carefully examines and estimates the population of South Asia (now India, Pakistan, Nepal, Bangladesh) from 640 to 1801 AD, and connects it with the population census data of British India from 1871 to 1941 (Nepal's data comes from Nepal's census data) and the United Nations World Population Prospects data from 1950 to 2020, obtaining the population of South Asia for a total of 22 periods (640, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1595, 1750, 1801, 1871, 1901, 1921, 1941, 1960, 1980, 2000, 2010, 2020) from 640 to 2020. Next, based on geographic detectors, select the dominant environmental factors that affect the spatial distribution of population, collect historical data on the distribution of residential areas (see data description document and references for details), and use a random forest regression model to spatialize the population size. On the basis of excluding uninhabited areas such as water bodies, glaciers, and bare/unused land, and determining the maximum historical population distribution range, a 1km resolution population dataset for South Asia from 640 to 2020 was developed. The leave one method was used to test the model, and the variance explained was 0.81, indicating good model accuracy. Compared with the existing HYDE historical population dataset, this study incorporates more historical materials and the latest research results in estimating the historical population; In using random forest regression for historical population spatial simulation, this study considers the changes in South Asian settlements over the past millennium, while the HYDE dataset only considers natural elements and considers them stable and unchanged. Therefore, this dataset is more reliable than the HYDE dataset and can more reasonably reveal the spatiotemporal characteristics of population changes in South Asia during historical periods. It is the basic data for the long-term evolution of human land relations, climate change attribution, and ecological protection research in South Asia.

This U.S. Geological Survey data release contains datasets that combine past data with future projections of nitrogen sources and nitrogen export to the Chesapeake Bay watershed for the years 1950-2050. To help understand the effect of human and environmental changes over this time period, data for nitrogen sources from wastewater, agricultural fertilizer and manure, and atmospheric deposition are combined with datasets of population and land use. These datasets were used in conjunction with a previously calibrated SPAtially Referenced Regression On Watershed attributes (SPARROW) modeling tool to estimate the mean annual loads of total nitrogen to the Chesapeake Bay and nontidal stream reaches in the watershed at a decadal timestep from 1950-2050. SPARROW model output of incremental and total loads for each reach in the Chesapeake Bay watershed are reported in this data release.

Between 1944–1950, almost eight million expellees arrived in West Germany. We introduce a rich county-level database on the expellees’ socio-economic situation in post-war Germany. The database contains regionally disaggregated information on the number, origin, age, gender, religious denomination and labour force status of expellees. It also records corresponding information on the West German population as a whole, on the pre-war economic and religious structure of host and origin regions, and on war destructions in West Germany. The main data sources are the West German censuses of 1939, 1946, 1950 and 1961. Altogether, the database consists of 18 data tables (in xsls format). We have digitized the data as printed in the statistical sources, adding only an English translation of the table head (along with the original table head in German). Each data table has two tabs: The first tab (named “source”) lists the reference(s) of the printed source, the second (“data”) contains the actual data. Please consult the readme file for an overview of each data table’s content and the paper for additional information.