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3c00d34b-ea1f-4e70-8e31-0768491f05b6:metadata:0
SEN
Senegal
METADATA
Enquête Données administratives
Somme Produit
Annuelle
Effectifs
espèce animale département
définitif
En milliers de têtes
DPES/MASAE
null
null
null
CEP/MEPA
Effectifs cheptel (en milliers de têtes)
META DONNEES
a5512c61-1c55-43e5-b2b5-9575cd03fbcb
3c00d34b-ea1f-4e70-8e31-0768491f05b6
https://agridata.ansd.sn/dataset/a5512c61-1c55-43e5-b2b5-9575cd03fbcb/resource/3c00d34b-ea1f-4e70-8e31-0768491f05b6/download/metadonnees.xlsx
odc-odbl
2026-07-27T11:04:43Z

Effectifs cheptel (en milliers de têtes) | Africa (Senegal official open data)

1 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official XLSX resource from Senegal 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

Geographic coverage

1 Africa country:

Country Rows First year Last year Name
SEN 1 n/a n/a Senegal

Indicators or Resource Contents

  • This source file is packaged as a normalized tabular resource.

Schema

Column Type Description Example
source_record_id string Stable row identifier for tabular resources. 3c00d34b-ea1f-4e70-8e31-0768491f05b6:metadata:0
country_iso3 category ISO3 country code. SEN
country_name category Country name. Senegal
source_sheet string Workbook sheet name, when the source is a spreadsheet. METADATA
methode_de_collecte string Source column. Enquête Données administratives
mode_de_calcul string Source column. Somme Produit
frequence_de_production string Source column. Annuelle
indicateur_diffuse string Source column. Effectifs
niveau_de_desagregation string Source column. espèce animale département
statut_de_l_indicateur string Source column. définitif
unite_echelle string Source column. En milliers de têtes
source string Source column. DPES/MASAE
source_period_start_year Int64 First year inferred from source resource metadata. ``
source_period_end_year Int64 Last year inferred from source resource metadata. ``
source_period_label string Human-readable period inferred from source resource metadata. ``
source_provider category Publishing organization. CEP/MEPA
source_dataset category Source package title. Effectifs cheptel (en milliers de têtes)
source_resource category Source resource title. META DONNEES
source_package_id category CKAN package UUID. a5512c61-1c55-43e5-b2b5-9575cd03fbcb
source_resource_id category CKAN resource UUID. 3c00d34b-ea1f-4e70-8e31-0768491f05b6
source_url category Original source resource URL. https://agridata.ansd.sn/dataset/a5512c61-1c55-43e5-b2b5-9575cd03fbcb/re
license_id category Source license identifier. odc-odbl
retrieved_at category UTC retrieval timestamp. 2026-07-27T11:04:43Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-senegal-effectifs-cheptel-en-milliers-de-tetes-cef2d001")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "SEN"]

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_senegal_effectifs_cheptel_en_milliers_de_tetes_cef2d001_2026,
  title        = {Effectifs cheptel (en milliers de têtes) | Africa (Senegal official open data)},
  author       = {CEP/MEPA},
  year         = {2026},
  url          = {https://agridata.ansd.sn/dataset/effectifscheptel},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-senegal-effectifs-cheptel-en-milliers-de-tetes-cef2d001}}
}

License

Released under Open Data Commons Open Database License.

Original data (c) CEP/MEPA. 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 2026-07-27 via the Electric Sheep pipeline. Source URL: https://agridata.ansd.sn/dataset/a5512c61-1c55-43e5-b2b5-9575cd03fbcb/resource/3c00d34b-ea1f-4e70-8e31-0768491f05b6/download/metadonnees.xlsx

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