Children out of school
What you should know about this indicator
- Many children and adolescents around the world are not in school, even though they are old enough to be. This indicator shows how many are missing out on education at each stage of the system.
- It measures the share of individuals in the official age range for a given level of education who are not enrolled at that level of education.
- These children or adolescents may have never entered school, may have dropped out, or may be starting later than expected.
- A share of 10% for children out of primary school means that 90% of all 6- to 11-year-olds are enrolled in primary education.
- High out-of-school rates signal barriers to access — such as poverty, gender inequality, location, or limited availability of schools — and highlight where more targeted support is needed.
- The data comes from administrative school enrollment records and household surveys, which provide age-specific insights when compared to population estimates.
- As with all education data, results should be interpreted carefully. Differences in how enrollment is defined, inconsistencies in age reporting, and timing of data collection (such as during holidays or late in the school year) can affect accuracy.
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 children who are not in pre-primary school”, part of the following publication: Hannah Ritchie, Veronika Samborska, Esteban Ortiz-Ospina, and Max Roser (2023) - “Global Education”. Data adapted from UNESCO Institute for Statistics. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/children-not-in-school.html [online resource] (archived on March 4, 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:
UNESCO Institute for Statistics (2025) – with minor processing by Our World in DataFull citation
UNESCO Institute for Statistics (2025) – with minor processing by Our World in Data. “Share of children who are not in pre-primary school” [dataset]. UNESCO Institute for Statistics, “UNESCO Institute for Statistics (UIS) - Education” [original data]. Retrieved April 10, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/children-not-in-school.html (archived on March 4, 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/children-not-in-school.csv?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=bothMetadata URL (JSON format)
https://ourworldindata.org/grapher/children-not-in-school.metadata.json?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=bothExcel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/children-not-in-school.csv?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=both")Python with Pandas
import pandas as pd
import requests
# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/children-not-in-school.csv?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=both", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})
# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/children-not-in-school.metadata.json?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=both").json()R
library(jsonlite)
# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/children-not-in-school.csv?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=both")
# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/children-not-in-school.metadata.json?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=both")Stata
import delimited "https://ourworldindata.org/grapher/children-not-in-school.csv?v=1&csvType=full&useColumnShortNames=false&level=primary&metric_type=rate&sex=both", encoding("utf-8") clear