Share of population living in urban areas
What you should know about this indicator
- Countries classify their territory into urban and rural areas using their own criteria. Some base this on administrative status; others use population thresholds, density, employment structure, or some combination. Because these criteria vary so widely, similar places can be classified differently from one country to the next.
- The UN has historically collected data using each country's own definition, which reflects how governments plan and maintain continuity with earlier statistics. But it means the figures do not always measure the same thing across countries.
- For international comparisons, the UN's 2025 revision adopted the Degree of Urbanization (DEGURBA) framework alongside its traditional national-definitions estimates. DEGURBA applies the same population density and settlement size thresholds everywhere, so that similar places are classified consistently regardless of which country they are in. Our charts using DEGURBA data are a better choice when comparing across countries.
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Sources and processing
This data is based on the following sources
How we process data at Our World in Data
All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.
At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.
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Citations
How to cite this page
To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:
“Data Page: Share of population living in urban areas”, part of the following publication: Hannah Ritchie, Veronika Samborska, and Max Roser (2024) - “Urbanization”. Data adapted from United Nations Department of Economic and Social Affairs, Population Division. Retrieved from https://archive.ourworldindata.org/20260601-150752/grapher/share-of-population-urban.html [online resource] (archived on June 1, 2026).How to cite this data
In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:
United Nations Department of Economic and Social Affairs, Population Division (2025) – with major processing by Our World in DataFull citation
United Nations Department of Economic and Social Affairs, Population Division (2025) – with major processing by Our World in Data. “Share of population living in urban areas – UN national definitions” [dataset]. United Nations Department of Economic and Social Affairs, Population Division, “World Urbanization Prospects 2025 - Percentage Urban and Rural by National Definition” [original data]. Retrieved June 1, 2026 from https://archive.ourworldindata.org/20260601-150752/grapher/share-of-population-urban.html (archived on June 1, 2026).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.
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://ourworldindata.org/grapher/share-of-population-urban.csv?v=1&csvType=full&useColumnShortNames=falseMetadata URL (JSON format)
https://ourworldindata.org/grapher/share-of-population-urban.metadata.json?v=1&csvType=full&useColumnShortNames=falseExcel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/share-of-population-urban.csv?v=1&csvType=full&useColumnShortNames=false")Python with Pandas
import pandas as pd
import requests
# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/share-of-population-urban.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://ourworldindata.org/grapher/share-of-population-urban.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()R
library(jsonlite)
# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/share-of-population-urban.csv?v=1&csvType=full&useColumnShortNames=false")
# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/share-of-population-urban.metadata.json?v=1&csvType=full&useColumnShortNames=false")Stata
import delimited "https://ourworldindata.org/grapher/share-of-population-urban.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear