license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- 1K<n<10K
tags:
- tabular
- asia
- our-world-in-data
- learning-outcomes-vs-gdp-per-capita
- owid
- long-run-series
- time-series
pretty_name: Learning Outcomes Vs Gdp Per Capita | Asia (Our World in Data)
Learning Outcomes Vs Gdp Per Capita | Asia (Our World in Data)
🌏 1,594 observations · 47 Asia countries · 1990–2024 · Repackaged by Electric Sheep Asia
TL;DR
This dataset contains 1,594 observations of Learning Outcomes Vs Gdp Per Capita data across 47 Asia countries, spanning 1990–2024.
About the source
- Source: Our World in Data
- Publisher: Our World in Data
- License: cc-by-4.0
- Topic: Learning Outcomes Vs Gdp Per Capita
Geographic coverage
47 Asia countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---|---|---|---|
ARE |
35 | 1990 | 2024 |
ARM |
35 | 1990 | 2024 |
AZE |
35 | 1990 | 2024 |
BHR |
35 | 1990 | 2024 |
BGD |
35 | 1990 | 2024 |
BRN |
35 | 1990 | 2024 |
CHN |
35 | 1990 | 2024 |
IRN |
35 | 1990 | 2024 |
CYP |
35 | 1990 | 2024 |
GEO |
35 | 1990 | 2024 |
IDN |
35 | 1990 | 2024 |
IRQ |
35 | 1990 | 2024 |
IND |
35 | 1990 | 2024 |
JOR |
35 | 1990 | 2024 |
ISR |
35 | 1990 | 2024 |
| ... | 32 more countries |
Schema
| Column | Type | Description | Example |
|---|---|---|---|
country_name |
string |
— | Afghanistan |
country_iso3 |
string |
— | AFG |
year |
int64 |
— | 2000 |
Harmonized test scores among all students |
float64 |
— | 355.0 |
GDP per capita |
float64 |
— | 1617.8264 |
Population |
float64 |
— | 20130334.0 |
World regions according to WB |
string |
— | Middle East, North Africa, Afghanista… |
Data quality & caveats
Harmonized test scores among all studentscolumn has 90.7% null values (filtered to non-null in this dataset).
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepasia/asia-owid-learning-outcomes-vs-gdp-per-capita")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
indonesia = df[df["country_iso3"] == "IDN"]
Time-series for a single indicator
sample = df.sort_values("year")
sample.plot(x="year", y="Harmonized test scores among all students")
Citation
@misc{asia_owid_learning_outcomes_vs_gdp_per_capita_2024,
title = {Learning Outcomes Vs Gdp Per Capita | Asia (Our World in Data)},
author = {Our World in Data},
year = {2024},
url = {https://ourworldindata.org/grapher/learning-outcomes-vs-gdp-per-capita},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-learning-outcomes-vs-gdp-per-capita}}
}
License
Released under cc-by-4.0.
Original data © Our World in Data. When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.
About Electric Sheep
Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.
Browse the full collection: huggingface.co/electricsheepasia
Provenance: ingested 2026-06-06 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/learning-outcomes-vs-gdp-per-capita