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.

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.

Whereas the population is expected to decrease somewhat until 2100 in Asia, Europe, and South America, it is predicted to grow significantly in Africa. While there were 1.55 billion inhabitants on the continent at the beginning of 2025, the number of inhabitants is expected to reach 3.81 billion by 2100. In total, the global population is expected to reach nearly 10.18 billion by 2100. Worldwide population In the United States, the total population is expected to steadily increase over the next couple of years. In 2024, Asia held over half of the global population and is expected to have the highest number of people living in urban areas in 2050. Asia is home to the two most populous countries, India and China, both with a population of over one billion people. However, the small country of Monaco had the highest population density worldwide in 2024. Effects of overpopulation Alongside the growing worldwide population, there are negative effects of overpopulation. The increasing population puts a higher pressure on existing resources and contributes to pollution. As the population grows, the demand for food grows, which requires more water, which in turn takes away from the freshwater available. Concurrently, food needs to be transported through different mechanisms, which contributes to air pollution. Not every resource is renewable, meaning the world is using up limited resources that will eventually run out. Furthermore, more species will become extinct which harms the ecosystem and food chain. Overpopulation was considered to be one of the most important environmental issues worldwide in 2020.

This database presents population and other demographic estimates and projections from 1960 to 2050. They are disaggregated by age-group and gender and cover approximately 200 economies.

This dataset was kindly made available by the World Bank.

This dataset presents essential statistics related to global population dynamics. It includes information such as the year, economy, economy label, absolute population values in thousands, and urban population percentages. The dataset covers the period from 1950 to 2050, providing insights into population trends and urbanization patterns across various economies. The columns in data set is

Year Economy
Economy Label
Absolute value in thousands
Absolute value in thousands Missing value
Urban population as percentage of total population
Urban population as percentage of total population Missing value

Population:😮

• A population is a distinct group of individuals, whether that group comprises a nation or a group of people with a common characteristic. In statistics, a population is the pool of individuals from which a statistical sample is drawn for a study. What is the types of population?
• And while every population pyramid is unique, most can be categorized into three prototypical shapes: expansive (young and growing), constrictive (elderly and shrinking), and stationary (little or no population growth). Let's take a deeper dive into the trends these three shapes reveal about a population and its needs.
• The global growth rate in absolute numbers accelerated to a peak of 92.9 million in 1988, but has declined to 81.3 million in 2020. Long-term projections indicate that the growth rate of the human population of this planet will continue to decline, and that by the end of the 21st century, it will reach zero.

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.

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

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. To provide areas in West Africa that may be particularly exposed to climate stressors owing to future high population growth.

this is the data of Top 10 populated countries of world as on 30 March 2024 with history of their population from 1955. it also have forecasted population values of these countries from 2025 to 2050.

here are the detail of columns

1: year:1955 to 2050

2: India: (population in millions)

3: china: (population in millions)

4: USA: (population in millions)

5: Indonesia: (population in millions)

6: Pakistan: (population in millions)

7: Nigeria: (population in millions)

8: Brazil: (population in millions)

9: Bangladesh: (population in millions)

10: Russia: (population in millions)

11: Mexico: (population in millions)

Acknowledgement This Dataset is created from https://www.worldometers.info/. If you want to learn more, you can visit the Website.

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

There are 5 datasets:

1. World_population(1955-2023).csv
2. World_population(1951-2020).csv
3. World Population Projections(2020 -2100).csv
4. World Population by Region(2020).csv
5. World Population Forecast (2020-2050).csv

1. World_population(1955-2023).csv:

This dataset consists of World Population from 1955 to 2023

Year: Year is from 1955 to 2023 Population: Count of the world's population Yearly % Change: Percentage of yearly change in population Yearly Change: Increase in Yearly Change in Population Median Age: Median Age of Population Fertility Rate: Fertility Rate from 1955 to 2015 with an interval of 5 years and from 2015 to 2020 yearly. Density: Population Density is in (P/Km²)

2. World_population(1951-2020).csv:

This dataset consists of World Population from 1951 to 2020

Year: Year is from 1951 to 2020 World Population: Count of the world population Yearly Change: Percentage of yearly change in population Net Change: Change in Population Density: Population Density is in (P/Km²) Urban Pop: Count of Urban Population count Median Age: Median Age of Population Urban Pop%: percentage of Urban Population% Fertility Rate: Fertility Rate from 1955 to 2015 with an interval of 5 years and from 2015 to 2020 yearly.

3.World Population Projections(2020 -2100).csv

This dataset contains world population projections from 2020-2100 Year: From 2020-2100 World Population: Count of World Population Yearly Change(%): Percentage yearly change Net Change: Net change in population Density(P/Km²): Population Density is in (P/Km²)

4. World Population by Region(2020).csv

This dataset contains the Population across regions in the Year 2020 Region: Name of Region Population(2020): Population in 2020 Yearly Change(%): Percentage yearly change Net Change: Net change in population Density(P/Km²): Population Density is in (P/Km²) Land Area(Km²): Land Area of Region in Km² Migrants(net): The count of Migrants, has a negative value which indicates the count of people who migrated from that region to another region. Fert.Rate: Fertility Rate Med.Age: Median Age of Population Urban Pop %: Urban Population Percentage World Share: World Share of Population

5. World Population Forecast (2020-2050).csv

This dataset contains the population forecasts from 2020-2050 with an interval of 5 years. Year (July 1): Year Population: Total count of the population Yearly % Change: Percentage Change in population yearly Yearly Change: Yearly change in population Median Age: Median Age of Population Fertility Rate: Fertility Rate Density (P/Km²): Population Density is in (P/Km²)

Dominican Republic DO: Population Projection: Mid Year data was reported at 12,542,490.000 Person in 2050. This records an increase from the previous number of 12,508,980.000 Person for 2049. Dominican Republic DO: Population Projection: Mid Year data is updated yearly, averaging 8,231,374.000 Person from Jun 1950 (Median) to 2050, with 101 observations. The data reached an all-time high of 12,542,490.000 Person in 2050 and a record low of 2,352,968.000 Person in 1950. Dominican Republic DO: 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 Dominican Republic – Table DO.US Census Bureau: Demographic Projection.

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.

In 2050, the three East Asian countries Hong Kong (SAR of China), South Korea, and Japan are forecasted to have the highest share of people aged 65 years or more. Except for Kuwait, all the countries on the list are either in Europe or East Asia. By 2050, 22 percent of the world's population is expected to be above 60 years.

This database presents population and other demographic estimates and projections from 1960 to 2050, covering more than 200 economies. It includes population data by various age groups, sex, urban/rural; fertility data; mortality data; and migration data.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F11723377%2F59bc70fb3d13d9f954e317aacbfd2bd6%2FPopulation.png?generation=1681981140865261&alt=media" alt="">

The population data from the United Nations is a dataset that contains information on the estimated population of each country in the world for various years between 1980 and 2050. The dataset includes the following columns:

• place: Name of the country or region
• pop1980: Estimated population for the year 1980
• pop2000: Estimated population for the year 2000
• pop2010: Estimated population for the year 2010
• pop2022: Estimated population for the year 2022
• pop2023: Estimated population for the year 2023
• pop2030: Estimated population for the year 2030
• pop2050: Estimated population for the year 2050
• country: ISO 3166-1 alpha-3 code of the country
• area: Total land and water area of the country (in square kilometers)
• landAreaKm: Land area of the country (in square kilometers)
• cca2: ISO 3166-1 alpha-2 code of the country
• cca3: ISO 3166-1 alpha-3 code of the country
• netChange: Annual net change in population (in thousands)
• growthRate: Annual population growth rate (as a percentage)
• worldPercentage: Percentage of world population
• density: Population density (in persons per square kilometer)
• densityMi: Population density (in persons per square mile)
• rank: Rank of the country by population

The dataset provides a comprehensive overview of the population of each country over time and can be used to analyze population trends, make population projections, and compare the population of different countries. The dataset can also be used in combination with other data sources to explore correlations between population and various social and economic indicators.

Before 2025, the world's total population is expected to reach eight billion. Furthermore, it is predicted to reach over 10 billion in 2060, before slowing again as global birth rates are expected to decrease. Moreover, it is still unclear to what extent global warming will have an impact on population development. A high share of the population increase is expected to happen on the African continent.

United States US: Population Projection: Mid Year: Growth data was reported at 0.450 % in 2050. This stayed constant from the previous number of 0.450 % for 2049. United States US: Population Projection: Mid Year: Growth data is updated yearly, averaging 0.700 % from Jun 2001 (Median) to 2050, with 50 observations. The data reached an all-time high of 0.980 % in 2006 and a record low of 0.450 % in 2050. United States US: Population Projection: Mid Year: Growth data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.US Census Bureau: Demographic Projection.

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.