Datasets:

electricsheepafrica
/

africa-tunisia-repartition-regionale-des-pistes-synthetiques-en-2018-140b6cf8

license: cc-by-4.0
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
multilinguality: monolingual
size_categories:
  - n<1K
tags:
  - tabular
  - csv
  - africa
  - tunisia
  - official-statistics
  - open-data
pretty_name: >-
  Répartition régionale des pistes synthétiques en 2018 | Africa (Tunisia
  official open data)

Répartition régionale des pistes synthétiques en 2018 | Africa (Tunisia official open data)

15 rows - 1 Africa country - 2018 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Tunisia 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 régionale des pistes synthétiques en 2018
Publisher: Ministère de la Jeunesse et des Sports
Resource: Répartition régionale des pistes synthétiques en 2018
Format: CSV
License: CC BY 4.0
Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
`TUN`	15	2018	2018	`Tunisia`

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.	`9ffcc3aa-6b96-4a63-8992-1f391b9c13e2:0`
`country_iso3`	`string`	ISO3 country code.	`TUN`
`country_name`	`string`	Country name.	`Tunisia`
`year`	`Int64`	Observation year.	`2018`
`gouvernorat_nb_localisation_annee_de_creation`	`string`	Source column.	`Ben Arous;4;"Cit Olympique Rads";2001`
`source_period_start_year`	`Int64`	First year inferred from source resource metadata.	`2018`
`source_period_end_year`	`Int64`	Last year inferred from source resource metadata.	`2018`
`source_period_label`	`string`	Human-readable period inferred from source resource metadata.	`2018`
`source_provider`	`string`	Publishing organization.	`Ministère de la Jeunesse et des Sports`
`source_dataset`	`string`	Source package title.	`Répartition régionale des pistes synthétiques en 2018`
`source_resource`	`string`	Source resource title.	`Répartition régionale des pistes synthétiques en 2018`
`source_package_id`	`string`	CKAN package UUID.	`207e6023-f66a-40da-b726-c040223c0d3e`
`source_resource_id`	`string`	CKAN resource UUID.	`9ffcc3aa-6b96-4a63-8992-1f391b9c13e2`
`source_url`	`string`	Original source resource URL.	`https://catalog.data.gov.tn/dataset/207e6023-f66a-40da-b726-c040223c0d3e`
`license_id`	`string`	Source license identifier.	`cc-by`
`retrieved_at`	`string`	UTC retrieval timestamp.	`2026-07-18T23:08:36Z`

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tunisia-repartition-regionale-des-pistes-synthetiques-en-2018-140b6cf8")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "TUN"]

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_tunisia_repartition_regionale_des_pistes_synthetiques_en_2018_140b6cf8_2018,
  title        = {Répartition régionale des pistes synthétiques en 2018 | Africa (Tunisia official open data)},
  author       = {Ministère de la Jeunesse et des Sports},
  year         = {2018},
  url          = {https://catalog.data.gov.tn/dataset/repartition-regionale-des-pistes-synthetiques-en-2018},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-repartition-regionale-des-pistes-synthetiques-en-2018-140b6cf8}}
}

License

Released under CC BY 4.0.

Original data (c) Ministère de la Jeunesse et des Sports. 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 2026-07-19 via the Electric Sheep pipeline. Source URL: https://catalog.data.gov.tn/dataset/207e6023-f66a-40da-b726-c040223c0d3e/resource/9ffcc3aa-6b96-4a63-8992-1f391b9c13e2/download/repartition_regionale_des_pistes_synthetiques.csv