electricsheepafrica/africa-tunisia-entrees-payantes-par-gouvernorat-et-par-site-et-musee-anne-f87dcfd0

Entrées payantes par gouvernorat et par site et musée année 2020 | Africa (Tunisia official open data)

51 rows - 1 Africa country - 2020 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Tunisia as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• Source: Entrées payantes par gouvernorat et par site et musée année 2020
• Publisher: Minstère des affaires culturelles
• Resource: Entrées payantes par gouvernorat et par site et musée année 2020
• Format: CSV
• License: Other open license
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
TUN	51	2020	2020	Tunisia

Indicators or Resource Contents

• This source file is packaged as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier for tabular resources.	32ce60bd-67f8-4c8c-8f80-5fcce90251fb:0
country_iso3	string	ISO3 country code.	TUN
country_name	string	Country name.	Tunisia
year	Int64	Observation year.	2020
gov_name_f	string	Source column.	Tunis
gov_id	int64	Source column.	11
sites_et_musees	string	Source column.	Musée du Bardo
janvier	int64	Source column.	6572
fevrier	int64	Source column.	5431
mars	int64	Source column.	1860
avril	int64	Source column.	0
mai	int64	Source column.	0
juin	int64	Source column.	83
juillet	int64	Source column.	314
aout	int64	Source column.	942
septembre	int64	Source column.	1395
octobre	int64	Source column.	608
novembre	int64	Source column.	260
decembre	int64	Source column.	475
total	int64	Source column.	17940
source_period_start_year	Int64	First year inferred from source resource metadata.	2020
source_period_end_year	Int64	Last year inferred from source resource metadata.	2020
source_period_label	string	Human-readable period inferred from source resource metadata.	2020
source_provider	string	Publishing organization.	Minstère des affaires culturelles
source_dataset	string	Source package title.	Entrées payantes par gouvernorat et par site et musée année 2020
source_resource	string	Source resource title.	Entrées payantes par gouvernorat et par site et musée année 2020
source_package_id	string	CKAN package UUID.	23c80f45-d6c7-4b52-b556-f5cf691b4587
source_resource_id	string	CKAN resource UUID.	32ce60bd-67f8-4c8c-8f80-5fcce90251fb
source_url	string	Original source resource URL.	http://www.openculture.gov.tn/dataset/754906fc-0036-4777-ba06-b6d2db9758
license_id	string	Source license identifier.	other-open
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T23:08:36Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tunisia-entrees-payantes-par-gouvernorat-et-par-site-et-musee-anne-f87dcfd0")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "TUN"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_tunisia_entrees_payantes_par_gouvernorat_et_par_site_et_musee_anne_f87dcf_2020,
  title        = {Entrées payantes par gouvernorat et par site et musée année 2020 | Africa (Tunisia official open data)},
  author       = {Minstère des affaires culturelles},
  year         = {2020},
  url          = {https://catalog.data.gov.tn/dataset/entrees-payantes2020},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-entrees-payantes-par-gouvernorat-et-par-site-et-musee-anne-f87dcfd0}}
}

License

Released under Other open license.

Original data (c) Minstère des affaires culturelles. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

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Provenance: ingested 2026-07-19 via the Electric Sheep pipeline. Source URL: http://www.openculture.gov.tn/dataset/754906fc-0036-4777-ba06-b6d2db9758ec/resource/a16a8cee-ff9c-470c-a568-74e303d93040/download/entrees-payantes-par-site-et-musee-annee-2020.csv