electricsheepafrica/africa-tunisia-liste-des-gdaps-crees-dans-les-zones-d-intervention-de-l-o-4c2eccff

Liste Des Gdaps Crees Dans Les Zones D Intervention De L O | Africa (Tunisia Open Data)

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

TL;DR

This dataset contains 52 rows from Tunisia Open Data, covering Liste Des Gdaps Crees Dans Les Zones D Intervention De L O. 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: Liste des GDAPs crées dans les zones d'intervention de l'ODESYPANO au Gouvernorat de Bizerte

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	52
Countries/areas	1
First period	detected
Last period	detected
Indicators	0
Columns	15
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TUN	52	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.	548804e4-58cc-411e-8aff-2848be2f52d5:0
country_iso3	string	ISO3 country or area code.	TUN
country_name	string	Country or area name.	Tunisia
pk_ei4v_y_content_types_xml_u_tena0_12we_d34vacuu_o_l_my	string	Source column from the original resource.	ßIRP©h$.‰²ÌÛæ%ã鮲É"ï21J‡" —{mÜ*Ÿ‹·Á£H”ÓÊz™ØŠéäöf¼ØÀ„§ f¢$
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.	Odesypano
source_dataset	string	Source dataset or package title.	liste des GDAPs crées dans les zones d'intervention de l ODESYPANO au...
source_resource	string	Source resource title, table name, or file name.	Liste des GDAPs crées dans les zones d'intervention de l'ODESYPANO au...
source_package_id	string	Source package identifier.	100be63b-7974-4135-84bb-58fb86379327
source_resource_id	string	Source resource identifier.	548804e4-58cc-411e-8aff-2848be2f52d5
source_url	string	Original source URL or download URL.	https://catalog.agridata.tn/dataset/491153d9-a36d-4eeb-af0d-4d27d1944...
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-liste-des-gdaps-crees-dans-les-zones-d-intervention-de-l-o-4c2eccff")
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: Odesypano
• Portal: https://catalog.data.gov.tn
• Resource: Liste des GDAPs crées dans les zones d'intervention de l'ODESYPANO au Gouvernorat de Bizerte
• License: licence-nationale-de-données-publiques-ouvertes
• Retrieved/generated: 2026-07-18T23:11:14Z
• Hugging Face repo: electricsheepafrica/africa-tunisia-liste-des-gdaps-crees-dans-les-zones-d-intervention-de-l-o-4c2eccff

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_liste_des_gdaps_crees_dans_les_zones_d_intervention_de_l_o_4c2ecc_2026,
  title        = {Liste Des Gdaps Crees Dans Les Zones D Intervention De L O | Africa (Tunisia Open Data)},
  author       = {Odesypano},
  year         = {2026},
  url          = {https://catalog.data.gov.tn/dataset/gdaps-crees-dans-les-zones-d-intervention-de-l-odesypano-au-gouvernorat-de-bizerte},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-liste-des-gdaps-crees-dans-les-zones-d-intervention-de-l-o-4c2eccff}}
}

License

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

Original data is published by Odesypano. 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/gdaps-crees-dans-les-zones-d-intervention-de-l-odesypano-au-gouvernorat-de-bizerte