electricsheepafrica/africa-owid-female-teachers

Female Teachers | Africa (Our World in Data)

🌍 1,785 observations · 54 Africa countries · 1970–2024 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 1,785 observations of Female Teachers data across 54 Africa countries, spanning 1970–2024.

About the source

• Source: Our World in Data
• Publisher: Our World in Data
• License: cc-by-4.0
• Topic: Female Teachers

Geographic coverage

54 Africa countries · top rows shown below, sorted by row count:

Country	Rows	First year	Last year
TGO	52	1971	2023
LSO	52	1970	2023
MUS	51	1970	2023
MLI	50	1971	2023
BFA	50	1971	2023
CIV	50	1970	2023
NER	49	1971	2023
BEN	48	1971	2022
MAR	48	1971	2023
SWZ	48	1970	2023
TZA	47	1970	2023
BWA	47	1970	2022
GIN	47	1975	2023
TUN	46	1976	2023
CMR	46	1972	2023
...	39 more countries

Schema

Column	Type	Description	Example
country_name	string	—	Algeria
country_iso3	string	—	DZA
year	int64	—	1971
Share of primary school teachers who are women	float64	—	25.99941

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-owid-female-teachers")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

kenya = df[df["country_iso3"] == "KEN"]

Time-series for a single indicator

sample = df.sort_values("year")
sample.plot(x="year", y="Share of primary school teachers who are women")

Citation

@misc{africa_owid_female_teachers_2024,
  title        = {Female Teachers | Africa (Our World in Data)},
  author       = {Our World in Data},
  year         = {2024},
  url          = {https://ourworldindata.org/grapher/female-teachers},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-female-teachers}}
}

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 Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa 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/electricsheepafrica

---

Provenance: ingested 2026-06-03 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/female-teachers