electricsheepafrica/africa-morocco-statistiques-des-immatriculations-et-permis-de-conduire-de-ed9838be

Statistiques des immatriculations et permis de conduire délivrés - 2021 | Africa (Morocco official open data)

252 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: Statistiques des immatriculations et permis de conduire délivrés - 2021
• Publisher: NARSA
• Resource: Trans.NARSA2021.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	252	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.	d6b81b35-99e9-402d-bee6-6cde87e3ea10:3-4:0
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.	3-4
genre_et_categorie_du_vehicule	string	Source column.	Motocyclettes
2021	float64	Source column.	291701.0
2020	float64	Source column.	266035.0
2019	float64	Source column.	236415.0
2018	float64	Source column.	191611.0
column	string	Source column.	الدراجات النارية
source_provider	string	Publishing organization.	NARSA
source_dataset	string	Source package title.	Statistiques des immatriculations et permis de conduire délivrés - 2021
source_resource	string	Source resource title.	Trans.NARSA2021.xlsx
source_package_id	string	CKAN package UUID.	05b961fb-f35a-4ced-9c04-0bdd2cd74a1a
source_resource_id	string	CKAN resource UUID.	d6b81b35-99e9-402d-bee6-6cde87e3ea10
source_url	string	Original source resource URL.	https://data.gov.ma/data/fr/dataset/05b961fb-f35a-4ced-9c04-0bdd2cd74a1a
license_id	string	Source license identifier.	odc-odbl
retrieved_at	string	UTC retrieval timestamp.	2026-07-16T21:31:48Z
tanger_tetouan_al_hoceima	string	Source column.	``
d_20911	float64	Source column.	``
d_6487	float64	Source column.	``
d_12106	float64	Source column.	``
d_2318	float64	Source column.	``
total_des_vehicules_neufs	string	Source column.	``
d_211186	float64	Source column.	``
d_58200	float64	Source column.	``
d_132464	float64	Source column.	``
d_20522	float64	Source column.	``
d_78759_87470324503	float64	Source column.	``
d_36838_646294452075	float64	Source column.	``
column_1	float64	Source column.	``
voitures_de_tourisme	string	Source column.	``
vehicules_utilitaires	float64	Source column.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-statistiques-des-immatriculations-et-permis-de-conduire-de-ed9838be")
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_statistiques_des_immatriculations_et_permis_de_conduire_de_ed9838_2026,
  title        = {Statistiques des immatriculations et permis de conduire délivrés - 2021 | Africa (Morocco official open data)},
  author       = {NARSA},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/statistiques-des-immatriculations-et-permis-de-conduire-delivres-2021},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-statistiques-des-immatriculations-et-permis-de-conduire-de-ed9838be}}
}

License

Released under Open Data Commons Open Database License.

Original data (c) NARSA. 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 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.gov.ma/data/fr/dataset/05b961fb-f35a-4ced-9c04-0bdd2cd74a1a/resource/d6b81b35-99e9-402d-bee6-6cde87e3ea10/download/trans.narsa2021.xlsx