electricsheepafrica/africa-tunisia-acquisitions-des-tableaux-d-arts-en-2016-f7d2bc91

Acquisitions Des Tableaux D Arts En 2016 | Africa (Tunisia Open Data)

346 rows - 1 Africa country/area - 2016 - 1 indicator - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 346 rows from Tunisia Open Data, covering Acquisitions Des Tableaux D Arts En 2016. 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 les acquisitions des tableaux d'arts 2016 par le commissariat de Gafsa, ainsi que les informations qui les concernent. Unité :DT

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

Geographic Coverage

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

Indicators, Variables, Or Resource Contents

• —acquisitions-des-tableaux-d-arts-en-2016-208d86d1 - Acquisitions des tableaux d'arts en 2016(sourceunitsunspecified)

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tunisia-acquisitions-des-tableaux-d-arts-en-2016-f7d2bc91")
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: Acquisitions des tableaux d'arts en 2016
• —License: other-open
• —Retrieved/generated: 2026-07-19T00:26:53Z
• —Hugging Face repo: electricsheepafrica/africa-tunisia-acquisitions-des-tableaux-d-arts-en-2016-f7d2bc91

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
• —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_acquisitions_des_tableaux_d_arts_en_2016_f7d2bc91_2016,
  title        = {Acquisitions Des Tableaux D Arts En 2016 | Africa (Tunisia Open Data)},
  author       = {Minstère des affaires culturelles},
  year         = {2016},
  url          = {https://catalog.data.gov.tn/dataset/acquisitions-table-gafsa},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-acquisitions-des-tableaux-d-arts-en-2016-f7d2bc91}}
}

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/acquisitions-table-gafsa