Our World
in Data
Oxford Martin School logoUniversity of Oxford logoGlobal Change Data Lab logo

PopulationLong-run data

Population by country, available from 10,000 BCE to 2023, based on data and estimates from different sources.

Data source

HYDE, Gapminder, UN

Unit
people
Last updated
2024-07-15
Next expected update
2026-07-15
Managed by
Lucas Rodés-Guirao, Fiona Spooner, and Pablo Rosado

  • Population is the most commonly used metric throughout Our World in Data. It is used directly to understand population growth over time, and indirectly to calculate per-capita indicators, making it easier to compare countries of different sizes.

  • We construct this indicator by combining multiple sources covering different periods.

    • HYDE v3.3 (2023): historical estimates from 10,000 BCE to 1799.
    • Gapminder v7 (2022): for 1800-1949.
    • UN World Population Prospects (2024): for 1950 onwards, including 2100 projections.
    • Gapminder Systema Globalis (2023): additional source for former countries (Yugoslavia, USSR, etc.)

  • Breaks in the data may occur at the boundaries between sources due to their methodological differences.

Show moreShow less

  • You can read more about the sources and methodology in our dedicated article. We also provide a table of sources showing the source we use for each country-year.

  • We calculate geographical aggregates (continents, income groups, etc.) by summing individual country populations. For years before 1800, we rely directly on HYDE's values for continents to ensure historical consistency.

Data sources

PBL Netherlands Environmental Assessment Agency – History Database of the Global Environment

This database presents an update and expansion of the History Database of the Global Environment (HYDE, v 3.3) and replaces former HYDE 3.2 version from 2017. HYDE is and internally consistent combination of updated historical population estimates and land use. Categories include cropland, with a new distinction into irrigated and rain fed crops (other than rice) and irrigated and rain fed rice. Also grazing lands are provided, divided into more intensively used pasture, converted rangeland and non-converted natural (less intensively used) rangeland. Population is represented by maps of total, urban, rural population and population density as well as built-up area. The period covered is 10 000 BCE to 2023 CE. Spatial resolution is 5 arc minutes (approx. 85 km2 at the equator), the files are in ESRI ASCII grid format.

Retrieved on
January 2, 2024
Retrieved from
https://doi.org/10.24416/UU01-AEZZIT
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
Utrecht University/PBL Netherlands Environmental Assessment Agency - History Database of the Global Environment (HYDE v 3.3, 2023).
Klein Goldewijk, C.G.M., Beusen, A., Doelman, J., Stehfest, E., 2017, Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953

Gapminder – Population

Gapminder's population data is divided into two chunks: One long historical trend for the global population that goes back to 10,000 BC. And the second chunk is country estimates that only reaches back to 1800.

For the first chunk, several sources were used. You can learn more at https://docs.google.com/spreadsheets/d/1hkLbEilJbl630IG68q-aQJlUjuTFm9b_12nQMVd1sZM/edit#gid=0. For the second chunk, Gapminder uses UN population data between 1950 to 2100 from the UN Population Division World Population Prospects 2019, and the forecast to the year 2100 uses their medium-fertility variant.

For years before 1950, this version uses the data documented in greater detail by Mattias Lindgren in version 3. The main source was Angus Maddison's data, which CLIO Infra Project maintained and improved. Note that when combining version 3 with the new UN data, the trends for a few countries didn't match up in the overlapping year 1950.

Minor adjustments were made to the years before and after to smooth out discrepancies between the two sources and avoid spurious jumps in Gapminder's visualisations.

Visit https://www.gapminder.org/data/documentation/gd003/ to learn more about the methodology used and the data from back to 10,000 BC.

Retrieved on
March 31, 2023
Retrieved from
http://gapm.io/dpop
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
Gapminder Population v7 (2022)

United Nations – World Population Prospects

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

United Nations – World Population Prospects - Interim Update

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

This is an interim update containing revised medium-variant estimates and projections for Togo.

Retrieved on
March 31, 2026
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

Gapminder – Systema Globalis

Data by Gapminder on population and other indicators. It provides data on former countries and regions.

Retrieved on
March 31, 2023
Retrieved from
https://github.com/open-numbers/ddf--gapminder--systema_globalis
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
Gapminder - Systema Globalis (2023)

Citations

How should I cite this data in a news article?

If you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World in Data

How should I cite this in an academic article or report?

HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World in Data. “Population – HYDE, Gapminder, UN – Long-run data” [dataset]. PBL Netherlands Environmental Assessment Agency, “History Database of the Global Environment 3.3”; Gapminder, “Population v7”; United Nations, “World Population Prospects”; United Nations, “World Population Prospects - Interim Update”; Gapminder, “Systema Globalis” [original data]. Retrieved June 12, 2026 from https://datapage-v2.owid.pages.dev/grapher/population

All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately. This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.

All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Related research and writing

The image features a simple illustration of a person represented by a circular head and a body, with a simplified figure holding a tool or pointer attached to an arrow. The central figure is enclosed in a larger circle, symbolizing focus or emphasis. Below are three rectangular blocks representing different roles or categories, forming a flowchart-like structure. The overall color scheme is muted in shades of gray, creating a minimalistic design. The background is a light gray, enhancing the visibility of the elements.

What are the sources for Our World in Data's population estimates?

Edouard Mathieu and Lucas Rodés-Guirao

Related charts

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Download full data

Includes all entities and time points

Download displayed data

Includes only the entities and time points currently visible in the chart

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://datapage-v2.owid.pages.dev/grapher/population.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://datapage-v2.owid.pages.dev/grapher/population.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://datapage-v2.owid.pages.dev/grapher/population.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://datapage-v2.owid.pages.dev/grapher/population.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://datapage-v2.owid.pages.dev/grapher/population.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://datapage-v2.owid.pages.dev/grapher/population.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://datapage-v2.owid.pages.dev/grapher/population.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://datapage-v2.owid.pages.dev/grapher/population.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear