electricsheepafrica/africa-tunisia-les-subventions-accordees-aux-films-tunisiens-pour-les-ann-557488e3

Les Subventions Accordees Aux Films Tunisiens Pour Les Ann | Africa (Tunisia Open Data)

34 rows - 1 Africa country/area - 2019 - 2 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 34 rows from Tunisia Open Data, covering Les Subventions Accordees Aux Films Tunisiens Pour Les Ann. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.

Source-provided context: Liste des films subventionnés pour l'année 2019

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	34
Countries/areas	1
First period	2019
Last period	2019
Indicators	2
Columns	23
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
TUN	34	2019	2019	Tunisia

Indicators, Variables, Or Resource Contents

• les-subventions-accordees-aux-films-tunisiens-pour-les-annees-2019-2020-8b81bd79 - Les subventions accordées aux films tunisiens pour les années 2019-2020-2021 - montant de la subvention(source_units_unspecified)
• les-subventions-accordees-aux-films-tunisiens-pour-les-annees-2019-2020-f43ba4b5 - Les subventions accordées aux films tunisiens pour les années 2019-2020-2021 - montant total des tranches(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	les-subventions-accordees-aux-films-tunisiens-pour-les-annees-2019-20...
indicator_name	string	Human-readable indicator name.	Les subventions accordées aux films tunisiens pour les années 2019-20...
country_iso3	string	ISO3 country or area code.	TUN
country_name	string	Country or area name.	Tunisia
year	int64	Observation year.	2019
value	double	Numeric observation value.	500000.0
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_titre_du_film	string	Source dimension retained during long-form normalization.	Les Epouvantails
dimension_genre_du_film	string	Source dimension retained during long-form normalization.	long métrage de fiction
dimension_societe_de_production	string	Source dimension retained during long-form normalization.	Mésanges
dimension_realisateur	string	Source dimension retained during long-form normalization.	Nouri Bouzid
dimension_nombre_de_tranches	string	Source dimension retained during long-form normalization.	toutes les tranches
source_period_start_year	int64	Start year inferred from source metadata.	2019
source_period_end_year	int64	End year inferred from source metadata.	2019
source_period_label	string	Source column from the original resource.	2019
source_provider	string	Publishing organization.	Minstère des affaires culturelles
source_dataset	string	Source dataset or package title.	Les subventions accordées aux films tunisiens pour les années 2019-20...
source_resource	string	Source resource title, table name, or file name.	Liste des films subventionnés pour l'année 2019
source_package_id	string	Source package identifier.	a2bae0cc-3a2a-436e-b175-4010c1743189
source_resource_id	string	Source resource identifier.	5bef7c59-94d9-4055-98f9-ac327dcc418d
source_url	string	Original source URL or download URL.	http://www.openculture.gov.tn/dataset/d3f4a102-494b-4db6-bf30-6900ad4...
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-les-subventions-accordees-aux-films-tunisiens-pour-les-ann-557488e3")
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

• 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

• Source: Tunisia Open Data
• Publisher: Minstère des affaires culturelles
• Portal: https://catalog.data.gov.tn
• Resource: Liste des films subventionnés pour l'année 2019
• License: other-open
• Retrieved/generated: 2026-07-19T00:00:54Z
• Hugging Face repo: electricsheepafrica/africa-tunisia-les-subventions-accordees-aux-films-tunisiens-pour-les-ann-557488e3

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

• Build demographic profiles
• Normalize indicators per capita
• Join with service-delivery datasets
• Build time-series views and period-over-period comparisons
• Pivot to geography x period or indicator x period matrices
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_tunisia_les_subventions_accordees_aux_films_tunisiens_pour_les_ann_557488_2019,
  title        = {Les Subventions Accordees Aux Films Tunisiens Pour Les Ann | Africa (Tunisia Open Data)},
  author       = {Minstère des affaires culturelles},
  year         = {2019},
  url          = {https://catalog.data.gov.tn/dataset/liste-des-films-subventionnes-par-le-cnci-2019-2021},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-les-subventions-accordees-aux-films-tunisiens-pour-les-ann-557488e3}}
}

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/liste-des-films-subventionnes-par-le-cnci-2019-2021