electricsheepafrica/africa-tunisia-tn-evolution-octroi-des-primes-itp-14c2a50b
Tn Evolution Octroi Des Primes Itp | Africa (Tunisia Open Data) 8 rows - 1 Africa country/area - 2016 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 8 rows from Tunisia Open Data, covering Tn Evolution Octroi Des Primes Itp. 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-tn-evolution-octroi-des-primes-itp-14c2a50b.
Tn Evolution Octroi Des Primes Itp | Africa (Tunisia Open Data)
8 rows - 1 Africa country/area - 2016 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
TL;DR
This dataset contains 8 rows from Tunisia Open Data, covering Tn Evolution Octroi Des Primes Itp. 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: Déboursement ITP csv
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_iso3where available plus source-specific keys.
Coverage
Geographic Coverage
Top areas shown below, sorted by row count when available:
Indicators, Variables, Or Resource Contents
- This repo preserves one source tabular resource with its usable columns kept together.
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-tunisia-tn-evolution-octroi-des-primes-itp-14c2a50b")
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: Ministère de l'Industrie, de l’Energie, des Mines
- Portal: https://catalog.data.gov.tn
- Resource: TN - Evolution de déboursement sectorielle des primes en CSV
- License: otl-data.industrie.gov.tn
- Retrieved/generated:
2026-07-18T23:12:49Z - Hugging Face repo: electricsheepafrica/africa-tunisia-tn-evolution-octroi-des-primes-itp-14c2a50b
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
- Check missingness before modeling
- Use
country_iso3as the safest geography join key when present
Citation
@misc{electric_sheep_africa_africa_tunisia_tn_evolution_octroi_des_primes_itp_14c2a50b_2016,
title = {Tn Evolution Octroi Des Primes Itp | Africa (Tunisia Open Data)},
author = {Ministère de l'Industrie, de l’Energie, des Mines},
year = {2016},
url = {https://catalog.data.gov.tn/dataset/statistiques-relatives-au-deblocage-et-deboursement-de-primes-itp},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-tn-evolution-octroi-des-primes-itp-14c2a50b}}
}License
Released under otl-data.industrie.gov.tn.
Original data is published by Ministère de l'Industrie, de l’Energie, des Mines. 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/statistiques-relatives-au-deblocage-et-deboursement-de-primes-itp
