How to Scrape UNESCO UIS Education Data

Export official cross-country education and SDG observations from the UNESCO UIS Data API. The UNESCO UIS Statistics Scraper provides a bounded connector to the authoritative publisher while preserving stable identifiers and source URLs on every row.

Start with a small, reviewable query

{"indicators":["READ.PRIMARY"],"geoUnits":["USA","IND"],"startYear":2015,"endYear":2025,"maxResults":500}

Run a small sample before expanding the result limit. Inspect identifiers, dates, null values, units, qualifiers, and source fields in the Apify Dataset. Export as JSON for nested fields or CSV and Excel for review. For recurring ingestion, upsert on the publisher stable record dimensions instead of assuming every run is append-only.

Build a reliable data pipeline

The Actor uses direct HTTP requests, bounded inputs, transient-error retries, and explicit empty-result failures. It does not require a browser or paid proxy, so scheduled runs remain inexpensive. Keep the input in an Apify Task, send completion through a webhook, and load the dataset into a warehouse or dashboard. Store collection time downstream so source revisions can be distinguished from newly published records.

Interpret the source responsibly

Official publication does not remove the need for context. Preserve footnotes, status fields, dataset type, reporting period, and source attribution. A missing value is not zero, and a revised record is not necessarily a new event. For legal, medical, financial, safety, protection, or public-policy decisions, confirm material findings with the publisher and a qualified specialist.

This workflow is designed for education researchers, policy teams, and development analysts. It is an independent integration and is not affiliated with or endorsed by the source institution.

Preserve the dimensions behind every value

An education statistic is meaningful only with its indicator code, geography, year, sex, education level, unit, and published qualifier. Keep those dimensions in the exported row instead of flattening the result to country, year, and value. Use UNESCO's codes as stable keys and add human-readable labels for analysis. Footnotes and metadata should travel with the observation or remain joinable through an indicator key. When requesting multiple indicators, validate each one separately before combining them because coverage and units differ. A bounded export is ideal for a first schema review; expand years and countries only after the resulting table has clear uniqueness rules.