electricsheepafrica/africa-tunisia-groupements-de-developpement-agricole-actifs-kairouan-d1094ca2

Groupements De Developpement Agricole Actifs Kairouan | Africa (Tunisia Open Data)

13 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 13 rows from Tunisia Open Data, covering Groupements De Developpement Agricole Actifs Kairouan. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Agriculture datasets help analysts examine production, prices, inputs, land use, food systems, and rural economic activity.

Source-provided context: groupements de développements agricoles

How To Read This Dataset

• One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
• Primary geography column: country_iso3.
• Best time column: source_period_start_year.
• Time coverage basis: source_period_start_year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	13
Countries/areas	1
First period	detected
Last period	detected
Indicators	0
Columns	18
Source format	CSV

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
TUN	13	detected	detected	Tunisia

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	bdceeedb-7f30-4bbb-87ea-9852702136f4:0
country_iso3	string	ISO3 country or area code.	TUN
country_name	string	Country or area name.	Tunisia
commune	string	Source column from the original resource.	القيروان الشمالية
eau_potable	int64	Source column from the original resource.	2
eau_irrigation	double	Source column from the original resource.	2.0
mixte	double	Source column from the original resource.	``
source_period_start_year	int64	Start year inferred from source metadata.	``
source_period_end_year	int64	End year inferred from source metadata.	``
source_period_label	string	Source column from the original resource.	``
source_provider	string	Publishing organization.	Ministère de l'Agriculture, des Ressources Hydrauliques et de la Pêche
source_dataset	string	Source dataset or package title.	Groupements de développement agricole actifs (Kairouan)
source_resource	string	Source resource title, table name, or file name.	groupements de développements agricoles
source_package_id	string	Source package identifier.	09435265-3714-403c-9c95-d765d9a11276
source_resource_id	string	Source resource identifier.	bdceeedb-7f30-4bbb-87ea-9852702136f4
source_url	string	Original source URL or download URL.	https://catalog.agridata.tn/dataset/3df5e2d7-d381-4114-850b-634ae8796...
license_id	string	Source license identifier.	licence-nationale-de-données-publiques-ouvertes
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-18T23:08:36Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tunisia-groupements-de-developpement-agricole-actifs-kairouan-d1094ca2")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "TUN"]

Time-Series Pattern

if "value" in df.columns and "source_period_start_year" in df.columns:
    trend = df.sort_values("source_period_start_year")

Pivot For Analysis

if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

• Canonical time field: source_period_start_year.
• Missing values are preserved rather than silently imputed.
• Column names are standardized for machine use; source meanings are preserved where known.
• Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

• Source: Tunisia Open Data
• Publisher: Ministère de l'Agriculture, des Ressources Hydrauliques et de la Pêche
• Portal: https://catalog.data.gov.tn
• Resource: groupements de développements agricoles
• License: licence-nationale-de-données-publiques-ouvertes
• Retrieved/generated: 2026-07-18T23:11:30Z
• Hugging Face repo: electricsheepafrica/africa-tunisia-groupements-de-developpement-agricole-actifs-kairouan-d1094ca2

Transformations Applied

• Converted the source table to Parquet for efficient analytics and ML workflows.
• Added or preserved source provenance columns where available.
• Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
• Preserved source-reported values without analytical imputation.

Suggested Analyses

• Track production or price movements
• Compare regions or commodities
• Join with climate and trade data
• Build time-series views and period-over-period comparisons
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_tunisia_groupements_de_developpement_agricole_actifs_kairouan_d1094ca2_2026,
  title        = {Groupements De Developpement Agricole Actifs Kairouan | Africa (Tunisia Open Data)},
  author       = {Ministère de l'Agriculture, des Ressources Hydrauliques et de la Pêche},
  year         = {2026},
  url          = {https://catalog.data.gov.tn/dataset/groupements-csv},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-groupements-de-developpement-agricole-actifs-kairouan-d1094ca2}}
}

License

Released under licence-nationale-de-données-publiques-ouvertes.

Original data is published by Ministère de l'Agriculture, des Ressources Hydrauliques et de la Pêche. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://catalog.data.gov.tn/dataset/groupements-csv