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electricsheepafrica/africa-tunisia-les-associations-et-les-espaces-beneficiant-de-subventions-e49d2995

Les Associations Et Les Espaces Beneficiant De Subventions | Africa (Tunisia Open Data) 24 rows - 1 Africa country/area - 2017 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 24 rows from Tunisia Open Data, covering Les Associations Et Les Espaces Beneficiant De Subventions. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-les-associations-et-les-espaces-beneficiant-de-subventions-e49d2995.

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Les Associations Et Les Espaces Beneficiant De Subventions | Africa (Tunisia Open Data)

24 rows - 1 Africa country/area - 2017 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 24 rows from Tunisia Open Data, covering Les Associations Et Les Espaces Beneficiant De Subventions. 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 une liste des associations et des espaces bénéficiant de subventions par le projet cite des arts en 2017, 2018 et 2019. 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: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows24
Countries/areas1
First period2017
Last period2017
Indicators0
Columns18
Source formatCSV

Geographic Coverage

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

AreaRowsFirst yearLast yearName
TUN2420172017Tunisia

Indicators, Variables, Or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.13fc0446-21dc-44a8-8c0b-c8cc3461d688:0
country_iso3stringISO3 country or area code.TUN
country_namestringCountry or area name.Tunisia
yearint64Observation year.2017
gov_name_fstringSource column from the original resource.Tunis
gov_idint64Source column from the original resource.11
subventiondoubleSource column from the original resource.490000.0
source_period_start_yearint64Start year inferred from source metadata.2017
source_period_end_yearint64End year inferred from source metadata.2017
source_period_labelstringSource column from the original resource.2017
source_providerstringPublishing organization.Établissement national pour la promotion des Festivals et des manifes...
source_datasetstringSource dataset or package title.Les associations et Les espaces bénéficiant de subventions par le pro...
source_resourcestringSource resource title, table name, or file name.Les Subventions par le programme ِCités des Arts en 2017
source_package_idstringSource package identifier.f0cb091a-0d25-4c49-836b-6dd2a5aa8175
source_resource_idstringSource resource identifier.13fc0446-21dc-44a8-8c0b-c8cc3461d688
source_urlstringOriginal source URL or download URL.http://www.openculture.gov.tn/dataset/eb3e3587-a46d-4ed3-a471-9929873...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-18T23:08:36Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tunisia-les-associations-et-les-espaces-beneficiant-de-subventions-e49d2995")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

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

Filter By Geography

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

Time-Series Pattern

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

Pivot For Analysis

python
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: 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

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
  • —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

bibtex
@misc{electric_sheep_africa_africa_tunisia_les_associations_et_les_espaces_beneficiant_de_subventions_e49d29_2017,
  title        = {Les Associations Et Les Espaces Beneficiant De Subventions | Africa (Tunisia Open Data)},
  author       = {Établissement national pour la promotion des Festivals et des manifestations culturelles et artistiques},
  year         = {2017},
  url          = {https://catalog.data.gov.tn/dataset/les-associations-et-les-espaces-beneficiant-de-subventions-par-le-projet-cite-des-arts},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-les-associations-et-les-espaces-beneficiant-de-subventions-e49d2995}}
}

License

Released under other-open.

Original data is published by Établissement national pour la promotion des Festivals et des manifestations culturelles et artistiques. 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.


Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://catalog.data.gov.tn/dataset/les-associations-et-les-espaces-beneficiant-de-subventions-par-le-projet-cite-des-arts