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Data

School enrollment rates

by level of education and gender
See all data and research on:
Global Education
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School enrollment rates

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What you should know about this indicator

  • The net enrollment rate shows what percentage of children are enrolled at the education level intended for their age.
  • It compares children enrolled at the correct level for their age to the total population in that same age group. For example, a primary school net enrollment of 90% means 90% of children between the ages of 6 and 11 years are enrolled in primary school. Children who are not enrolled in school or are enrolled at another education level are not counted here.
  • The highest possible value is 100%, which would mean all children of the right age are enrolled where they should be. High rates indicate that most children are progressing through school at the expected pace.
  • A rate of 90% doesn't necessarily mean 10% of children are out of school entirely — some may be enrolled at different levels (either higher or lower) than expected for their age, but these students aren't counted in the net rate.
  • The data comes from school administrative records that track enrollment by individual age, combined with population estimates from national statistics offices or UN sources.
Share of children enrolled in pre-primary school
Shown as the — the share of children of pre-primary school age (between 3 and 5 years old) who are enrolled in education.
Source
UNESCO Institute for Statistics (2025) – with minor processing by Our World in Data
Last updated
May 1, 2025
Next expected update
May 2026
Date range
1997–2024
Unit
%

Related research and writing

Featured image

Global Education

Hannah Ritchie, Veronika Samborska, Esteban Ortiz-Ospina, and Max Roser

Sources and processing

This data is based on the following sources

UNESCO Institute for Statistics – UNESCO Institute for Statistics (UIS) - Education

The UNESCO Institute for Statistics (UIS) is the official and trusted source of internationally-comparable data on education, science, culture and communication. As the official statistical agency of UNESCO, the UIS produces a wide range of state-of-the-art databases to fuel the policies and investments needed to transform lives and propel the world towards its development goals. The UIS provides free access to data for all UNESCO countries and regional groupings from 1970 to the most recent year available.

Retrieved on
May 1, 2025
Retrieved from
https://databrowser.uis.unesco.org/resources/bulk
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
UNESCO Institute for Statistics (UIS), Education, https://uis.unesco.org/bdds, 2025

The UNESCO Institute for Statistics (UIS) is the official and trusted source of internationally-comparable data on education, science, culture and communication. As the official statistical agency of UNESCO, the UIS produces a wide range of state-of-the-art databases to fuel the policies and investments needed to transform lives and propel the world towards its development goals. The UIS provides free access to data for all UNESCO countries and regional groupings from 1970 to the most recent year available.

Retrieved on
May 1, 2025
Retrieved from
https://databrowser.uis.unesco.org/resources/bulk
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
UNESCO Institute for Statistics (UIS), Education, https://uis.unesco.org/bdds, 2025

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: Share of children enrolled 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/20260326-120116/grapher/school-enrolment.html [online resource] (archived on March 26, 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 Data

Full citation

UNESCO Institute for Statistics (2025) – with minor processing by Our World in Data. “Share of children enrolled 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/20260326-120116/grapher/school-enrolment.html (archived on March 26, 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.

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Includes all entities and time points

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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/school-enrolment.csv?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both
Metadata URL (JSON format)
https://ourworldindata.org/grapher/school-enrolment.metadata.json?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both

Code examples

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

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/school-enrolment.csv?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/school-enrolment.csv?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/school-enrolment.metadata.json?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/school-enrolment.csv?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/school-enrolment.metadata.json?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both")
Stata
import delimited "https://ourworldindata.org/grapher/school-enrolment.csv?v=1&csvType=full&useColumnShortNames=false&enrolment_type=net_enrolment&level=primary&sex=both", encoding("utf-8") clear