# Population - Data package This data package contains the data that powers the chart ["Population"](https://ourworldindata.org/grapher/population?country=~OWID_WRL&overlay=download-data&v=1&csvType=filtered&useColumnShortNames=false) on the Our World in Data website. It was downloaded on October 05, 2025. ### Active Filters A filtered subset of the full data was downloaded. The following filters were applied: country: , OWID_WRL overlay: download-data ## CSV Structure The high level structure of the CSV file is that each row is an observation for an entity (usually a country or region) and a timepoint (usually a year). The first two columns in the CSV file are "Entity" and "Code". "Entity" is the name of the entity (e.g. "United States"). "Code" is the OWID internal entity code that we use if the entity is a country or region. For normal countries, this is the same as the [iso alpha-3](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3) code of the entity (e.g. "USA") - for non-standard countries like historical countries these are custom codes. The third column is either "Year" or "Day". If the data is annual, this is "Year" and contains only the year as an integer. If the column is "Day", the column contains a date string in the form "YYYY-MM-DD". The final column is the data column, which is the time series that powers the chart. If the CSV data is downloaded using the "full data" option, then the column corresponds to the time series below. If the CSV data is downloaded using the "only selected data visible in the chart" option then the data column is transformed depending on the chart type and thus the association with the time series might not be as straightforward. ## Metadata.json structure The .metadata.json file contains metadata about the data package. The "charts" key contains information to recreate the chart, like the title, subtitle etc.. The "columns" key contains information about each of the columns in the csv, like the unit, timespan covered, citation for the data etc.. ## About the data Our World in Data is almost never the original producer of the data - almost all of the data we use has been compiled by others. If you want to re-use data, it is your responsibility to ensure that you adhere to the sources' license and to credit them correctly. Please note that a single time series may have more than one source - e.g. when we stich together data from different time periods by different producers or when we calculate per capita metrics using population data from a second source. ## Detailed information about the data ## Population Population by country, available from 10,000 BCE to 2023, based on data and estimates from different sources. Last updated: July 15, 2024 Next update: July 2026 Date range: 10000 BCE – 2023 CE Unit: people ### How to cite this data #### In-line citation 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 #### Full citation 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”; Gapminder, “Systema Globalis” [original data]. Source: HYDE (2023); Gapminder (2022); UN WPP (2024) – with major processing by Our World In Data ### What you should know about this data * 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. * You can read more about the sources and methodology in our [dedicated article](https://ourworldindata.org/population-sources). 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. ### Sources #### PBL Netherlands Environmental Assessment Agency – History Database of the Global Environment Retrieved on: 2024-01-02 Retrieved from: https://doi.org/10.24416/UU01-AEZZIT #### Gapminder – Population Retrieved on: 2023-03-31 Retrieved from: http://gapm.io/dpop #### United Nations – World Population Prospects Retrieved on: 2024-07-11 Retrieved from: https://population.un.org/wpp/downloads/ #### Gapminder – Systema Globalis Retrieved on: 2023-03-31 Retrieved from: https://github.com/open-numbers/ddf--gapminder--systema_globalis #### Notes on our processing step for this indicator ### Combination of different sources We construct our long-run population data by combining multiple sources: - 10,000 BCE–1799: historical estimates by HYDE (v3.3). - 1800–1949: historical estimates by Gapminder (v7). - 1950–2023: population records from the United Nations World Population Prospects (2024 revision). **Geographical aggregates** - For most years, we calculate aggregates by summing the population of member countries. - We do this based on [our definition of continents](https://ourworldindata.org/world-region-map-definitions#our-world-in-data) and the [World Bank’s income groups](https://ourworldindata.org/grapher/world-bank-income-groups). - The only exception is before 1800, where we use HYDE's estimates for continents (but not income groups). For most of the years, we've estimated regional aggregates by summing the population of countries in each region. We've relied on [our continents](https://ourworldindata.org/world-region-map-definitions#our-world-in-data) and [World Bank income group definitions](https://ourworldindata.org/grapher/world-bank-income-groups). The only exception is before 1800, where we've used HYDE's estimates on continents (but not income groups). **World** - Before 1800: we use data from HYDE. - 1800-1950: we estimate the global population by summing all available countries in the dataset. - After 1950, we rely on estimates from the United Nations World Population Prospects.