electricsheepafrica/africa-tunisia-subventions-attribuees-par-crac-ariana-de-2017-a-2020-b7696187

Subventions Attribuees Par Crac Ariana De 2017 a 2020 | Africa (Tunisia Open Data)

65 rows - 1 Africa country/area - 2017-2020 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 65 rows from Tunisia Open Data, covering Subventions Attribuees Par Crac Ariana De 2017 a 2020. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: Ce jeu de données contient un tableau de subvention direct et indirect des associations culturel Ariana de 2017 à 2020 Unité : DT

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: not detected.
• Time coverage basis: source metadata.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	65
Countries/areas	1
First period	2017
Last period	2020
Indicators	0
Columns	24
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TUN	65	2017	2020	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.	f0a38acc-1417-4c7b-8624-8a2823334200:0
country_iso3	string	ISO3 country or area code.	TUN
country_name	string	Country or area name.	Tunisia
association	string	Source column from the original resource.	الجمعية الثقافية لبلدية أريانة
projet	string	Source column from the original resource.	سهرة اللباس التقليدي
sub_directe_2017	double	Source column from the original resource.	0.0
sub_indirecte_2017	double	Source column from the original resource.	2500.0
sub_directe_2018	double	Source column from the original resource.	0.0
sub_indirecte_2018	double	Source column from the original resource.	1200.0
sub_directe_2019	double	Source column from the original resource.	0.0
sub_indirecte_2019	double	Source column from the original resource.	0.0
sub_directe_2020	double	Source column from the original resource.	0.0
sub_indirecte_2020	double	Source column from the original resource.	0.0
source_period_start_year	int64	Start year inferred from source metadata.	2017
source_period_end_year	int64	End year inferred from source metadata.	2020
source_period_label	string	Source column from the original resource.	2017-2020
source_provider	string	Publishing organization.	Minstère des affaires culturelles
source_dataset	string	Source dataset or package title.	Subventions attribuées par CRAC Ariana de 2017 à 2020
source_resource	string	Source resource title, table name, or file name.	Subventions attribuées par CRAC Ariana de 2017 à 2020
source_package_id	string	Source package identifier.	9df548b9-e23b-46b6-9328-a6f75d64e938
source_resource_id	string	Source resource identifier.	f0a38acc-1417-4c7b-8624-8a2823334200
source_url	string	Original source URL or download URL.	http://www.openculture.gov.tn/dataset/0322dad8-bb44-4335-a3b8-ca65559...
license_id	string	Source license identifier.	other-open
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-subventions-attribuees-par-crac-ariana-de-2017-a-2020-b7696187")
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 "year" in df.columns:
    trend = df.sort_values("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

• No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• 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: Minstère des affaires culturelles
• Portal: https://catalog.data.gov.tn
• Resource: Subventions attribuées par CRAC Ariana de 2017 à 2020
• License: other-open
• Retrieved/generated: 2026-07-19T00:29:35Z
• Hugging Face repo: electricsheepafrica/africa-tunisia-subventions-attribuees-par-crac-ariana-de-2017-a-2020-b7696187

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

• Profile the distribution of values
• Compare categories or geographies
• Join with complementary public datasets
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_tunisia_subventions_attribuees_par_crac_ariana_de_2017_a_2020_b7696187_2020,
  title        = {Subventions Attribuees Par Crac Ariana De 2017 a 2020 | Africa (Tunisia Open Data)},
  author       = {Minstère des affaires culturelles},
  year         = {2020},
  url          = {https://catalog.data.gov.tn/dataset/c-users-user-desktop-travaille-tarek-tarek-opendata-dossier-de-travaille},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-subventions-attribuees-par-crac-ariana-de-2017-a-2020-b7696187}}
}

License

Released under other-open.

Original data is published by Minstère des affaires culturelles. 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/c-users-user-desktop-travaille-tarek-tarek-opendata-dossier-de-travaille