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electricsheepafrica/africa-tunisia-subventions-attribuees-aux-associations-5608513f

Subventions Attribuees Aux Associations | Africa (Tunisia Open Data) 24 rows - 1 Africa country/area - 2015 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 24 rows from Tunisia Open Data, covering Subventions Attribuees Aux Associations. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures Transport… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-subventions-attribuees-aux-associations-5608513f.

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Dataset Card

Subventions Attribuees Aux Associations | Africa (Tunisia Open Data)

24 rows - 1 Africa country/area - 2015 - 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 Subventions Attribuees Aux Associations. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Transport datasets help analysts examine mobility, infrastructure, passenger movement, logistics, and access to services.

Source-provided context: Ce jeu de données contient les subventions attribuées aux associations par secteurs et par régions en 2014 et 2015.

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 period2015
Last period2015
Indicators0
Columns19
Source formatCSV

Geographic Coverage

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

AreaRowsFirst yearLast yearName
TUN2420152015Tunisia

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.8b2cdd99-939a-4595-a864-99d6d271704f:0
country_iso3stringISO3 country or area code.TUN
country_namestringCountry or area name.Tunisia
yearint64Observation year.2015
gov_name_fstringSource column from the original resource.Tunis
gov_idint64Source column from the original resource.11
nb_associationdoubleSource column from the original resource.30.0
subventiondoubleSource column from the original resource.474.5
source_period_start_yearint64Start year inferred from source metadata.2015
source_period_end_yearint64End year inferred from source metadata.2015
source_period_labelstringSource column from the original resource.2015
source_providerstringPublishing organization.Minstère des affaires culturelles
source_datasetstringSource dataset or package title.Subventions attribuées aux associations
source_resourcestringSource resource title, table name, or file name.Subventions attribuées aux associations 2015 par Gouvernorat
source_package_idstringSource package identifier.c5f885d0-2913-4850-bbdf-d335eab0eb9f
source_resource_idstringSource resource identifier.8b2cdd99-939a-4595-a864-99d6d271704f
source_urlstringOriginal source URL or download URL.http://www.openculture.gov.tn/dataset/a5414a09-b852-49de-aee7-cbdd948...
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-subventions-attribuees-aux-associations-5608513f")
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

  • —Track mobility over time
  • —Compare routes or geographies
  • —Join with economic and population 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

bibtex
@misc{electric_sheep_africa_africa_tunisia_subventions_attribuees_aux_associations_5608513f_2015,
  title        = {Subventions Attribuees Aux Associations | Africa (Tunisia Open Data)},
  author       = {Minstère des affaires culturelles},
  year         = {2015},
  url          = {https://catalog.data.gov.tn/dataset/subventions-attribuees-aux-associations},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-subventions-attribuees-aux-associations-5608513f}}
}

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.


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