Electric Sheep Africa
Africa's ML dataset infrastructure.
We build and maintain the largest open collection of machine-learning-ready
datasets on the African continent — thousands of datasets spanning health,
agriculture, energy, finance, education, governance, and more, covering
all 54 countries.
What makes ESA datasets different
Every dataset in this collection goes through ESA's data pipeline:
Cleaning
Missing value markers unified across formats (N/A, null, none, -, unknown,
no data, #N/A → NaN). Columns with >80% missingness removed. Duplicate
rows and malformed entries resolved.
Normalisation
Column names lowercased and snake_cased. Datatypes enforced. Units and
categorical encodings standardised across datasets from the same source
family.
Augmentation
Datasets enriched with contextual features — geographic identifiers,
temporal markers, cross-source linkage keys — where source data is sparse
or inconsistently structured.
Provenance tracking
Every row carries esa_source and esa_processed fields. Every dataset
ships with a full BibTeX citation traceable to the original publisher.
ML formatting
80/20 train/test splits using a fixed random seed (42). Saved as
Snappy-compressed Parquet. Loadable in one line via the datasets library.
Use our data
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/DATASET_NAME")
train = ds["train"].to_pandas()
To request a dataset not yet in the collection, email
kossi@electricsheep.africa.
Support our work
ESA is a non-profit. If our datasets have been useful to your research or
product, consider supporting us.
Nigeria — Kuda Bank · Account: 3003437130 · Electric Sheep Africa
United States — Lead Bank · Account: 217143145453 · ACH/Wire Routing:
101019644 · Bank address: 1801 Main St., Kansas City, MO 64108
Electric Sheep Africa · Lagos, Nigeria ·
electricsheep.africa
