electricsheepafrica/africa-mali-west-and-central-africa-administrative-boundaries-levels-0-d9f606c6

West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements | Africa (Mali official open data)

8,301 rows - 1 Africa country - 2016-2025 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official XLSX resource from Mali as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• —Source: West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements
• —Publisher: OCHA West and Central Africa (ROWCA)
• —Resource: wca_admin-0-1-2.xlsx
• —Format: XLSX
• —License: CC BY 4.0
• —Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Indicators or Resource Contents

• —west-and-central-africa-administrative-boundaries-levels-02-and-settleme-85eb6031 - West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements - area sqkm
• —west-and-central-africa-administrative-boundaries-levels-02-and-settleme-c1eed9a4 - West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements - center lat
• —west-and-central-africa-administrative-boundaries-levels-02-and-settleme-ba076f9e - West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements - center lon
• —west-and-central-africa-administrative-boundaries-levels-02-and-settleme-17c1e800 - West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements - shape length
• —west-and-central-africa-administrative-boundaries-levels-02-and-settleme-9c8e8760 - West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements - shape area

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mali-west-and-central-africa-administrative-boundaries-levels-0-d9f606c6")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MLI"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_mali_west_and_central_africa_administrative_boundaries_levels_0_d9f606c6_2025,
  title        = {West and Central Africa - Administrative Boundaries (Levels 0–2) and Settlements | Africa (Mali official open data)},
  author       = {OCHA West and Central Africa (ROWCA)},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-west-and-central-africa-administrative-boundaries-levels-0-d9f606c6}}
}

License

Released under CC BY 4.0.

Original data (c) OCHA West and Central Africa (ROWCA). 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 Hugging Face. 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 2026-08-13 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/b20cd345-93fb-43bd-9c6e-7bc7d87b63eb/resource/8e794cb5-eff7-4fe8-896f-6b9bc6c1c00e/download/wca_admin-0-1-2.xlsx