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About this data

World regions according to the International Labour Organization
Broad regions as defined by the International Labour Organization (ILO).
Source
International Labour Organization – processed by Our World in Data
Last updated
January 1, 2023
Date range
2023–2023

Sources and processing

This data is based on the following sources

International Labour Organization – ILOSTAT

Retrieved on
February 3, 2026
Retrieved from
https://ilostat.ilo.org/

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.

Read about our data pipeline

Reuse this work

  • 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 (see below). 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.

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: World regions according to the International Labour Organization”. Our World in Data (2026). Data adapted from International Labour Organization. Retrieved from https://archive.ourworldindata.org/20260619-184650/grapher/world-regions-according-to-ilo.html [online resource] (archived on June 19, 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:

International Labour Organization – processed by Our World in Data

Full citation

International Labour Organization – processed by Our World in Data. “World regions according to the International Labour Organization” [dataset]. International Labour Organization, “ILOSTAT” [original data]. Retrieved June 19, 2026 from https://archive.ourworldindata.org/20260619-184650/grapher/world-regions-according-to-ilo.html (archived on June 19, 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.

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://ourworldindata.org/grapher/world-regions-according-to-ilo.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/world-regions-according-to-ilo.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://ourworldindata.org/grapher/world-regions-according-to-ilo.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/world-regions-according-to-ilo.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/world-regions-according-to-ilo.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/world-regions-according-to-ilo.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/world-regions-according-to-ilo.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/world-regions-according-to-ilo.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear