electricsheepafrica/africa-morocco-repartition-geographique-des-retraites-par-region-2022-c1ec950a

Répartition géographique des retraités par région (2022) | Africa (Morocco official open data)

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

TL;DR

This dataset packages one official XLSX resource from Morocco 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: Répartition géographique des retraités par région (2022)
• Publisher: CMR
• Resource: Répartition retraités par région 2022.xlsx
• Format: XLSX
• License: Open Data Commons Open Database License
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
MAR	13	n/a	n/a	Morocco

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.	924bbe37-bbdd-4167-a534-b367bb0f5c1e:statistiques-retraites-civils:0
country_iso3	string	ISO3 country code.	MAR
country_name	string	Country name.	Morocco
source_sheet	string	Workbook sheet name, when the source is a spreadsheet.	Statistiques retraités civils
tanger_tetouan_al_hoceima	string	Source column.	Oriental
d_6527	float64	Source column.	5552.0
d_19018	float64	Source column.	17602.0
d_25545	float64	Source column.	23154.0
source_provider	string	Publishing organization.	CMR
source_dataset	string	Source package title.	Répartition géographique des retraités par région (2022)
source_resource	string	Source resource title.	Répartition retraités par région 2022.xlsx
source_package_id	string	CKAN package UUID.	a9e1b18c-6c4f-4c5f-afc9-3110f8641cff
source_resource_id	string	CKAN resource UUID.	924bbe37-bbdd-4167-a534-b367bb0f5c1e
source_url	string	Original source resource URL.	https://data.gov.ma/data/fr/dataset/a9e1b18c-6c4f-4c5f-afc9-3110f8641cff
license_id	string	Source license identifier.	odc-odbl
retrieved_at	string	UTC retrieval timestamp.	2026-07-16T21:31:48Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-repartition-geographique-des-retraites-par-region-2022-c1ec950a")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MAR"]

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_morocco_repartition_geographique_des_retraites_par_region_2022_c1ec950a_2026,
  title        = {Répartition géographique des retraités par région (2022) | Africa (Morocco official open data)},
  author       = {CMR},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/repartition-geographique-des-retraites-par-region-2022},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-repartition-geographique-des-retraites-par-region-2022-c1ec950a}}
}

License

Released under Open Data Commons Open Database License.

Original data (c) CMR. 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

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Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.gov.ma/data/fr/dataset/a9e1b18c-6c4f-4c5f-afc9-3110f8641cff/resource/924bbe37-bbdd-4167-a534-b367bb0f5c1e/download/repartition-retraites-par-region_2022.xlsx