README.md

---
license: other
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: multilingual
size_categories:
- n<1K
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "tunisia"
- "minstere-des-affaires-culturelles"
- "tunisia-open-data"
- "culture"
- "2021"
- "monastir"
- "ressources-humaines"
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Ressources Humaines Crac Monastir En 2021 | Africa (Tunisia Open Data)"
---

# Ressources Humaines Crac Monastir En 2021 | Africa (Tunisia Open Data)

**19 rows** - **1 Africa country/area** - **2021** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-19-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-2021-orange)
![indicators](https://img.shields.io/badge/indicators-0-purple)
![license](https://img.shields.io/badge/license-other-lightgrey)

## TL;DR

This dataset contains **19 rows** from **Tunisia Open Data**, covering **Ressources Humaines Crac Monastir En 2021**. 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 une classification des ressources humaines selon catégories du CRAC Monastir en 2021.

## 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

| Dimension | Value |
|---|---:|
| Rows | 19 |
| Countries/areas | 1 |
| First period | 2021 |
| Last period | 2021 |
| Indicators | 0 |
| Columns | 19 |
| Source format | CSV |

## Geographic Coverage

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

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `TUN` | 19 | 2021 | 2021 | `Tunisia` |

## Indicators, Variables, Or Resource Contents

- This repo preserves one source tabular resource with its usable columns kept together.

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `source_record_id` | `string` | Stable row identifier assigned during Electric Sheep Africa engineering. | `f8dad33f-4777-423b-aadc-ae4f53ae4c44:0` |
| `country_iso3` | `string` | ISO3 country or area code. | `TUN` |
| `country_name` | `string` | Country or area name. | `Tunisia` |
| `year` | `int64` | Observation year. | `2021` |
| `categorie` | `string` | Source column from the original resource. | `إطار` |
| `etat` | `string` | Source column from the original resource. | `قار` |
| `grade` | `string` | Source column from the original resource. | `أ1` |
| `nombre_2021` | `int64` | Source column from the original resource. | `44` |
| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `2021` |
| `source_period_end_year` | `int64` | End year inferred from source metadata. | `2021` |
| `source_period_label` | `string` | Source column from the original resource. | `2021` |
| `source_provider` | `string` | Publishing organization. | `Minstère des affaires culturelles` |
| `source_dataset` | `string` | Source dataset or package title. | `Ressources humaines CRAC Monastir en 2021` |
| `source_resource` | `string` | Source resource title, table name, or file name. | `Ressources humaines CRAC Monastir en 2021` |
| `source_package_id` | `string` | Source package identifier. | `7ea38d35-713f-4d14-a4b6-d4c69b7ce705` |
| `source_resource_id` | `string` | Source resource identifier. | `f8dad33f-4777-423b-aadc-ae4f53ae4c44` |
| `source_url` | `string` | Original source URL or download URL. | `http://www.openculture.gov.tn/dataset/b5b6250d-93a4-4532-98c7-6f0d345...` |
| `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

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-tunisia-ressources-humaines-crac-monastir-en-2021-8464ae56")
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

- **Source:** [Tunisia Open Data](https://catalog.data.gov.tn/dataset/ressources-humaines-crac-monastir-en-2021)
- **Publisher:** Minstère des affaires culturelles
- **Portal:** [https://catalog.data.gov.tn](https://catalog.data.gov.tn)
- **Resource:** [Ressources humaines CRAC Monastir en 2021](http://www.openculture.gov.tn/dataset/b5b6250d-93a4-4532-98c7-6f0d34599f6c/resource/45e54238-86ea-4cfe-b734-15b949b75326/download/ressorce-humaine-monestir-2021.csv)
- **License:** other-open
- **Retrieved/generated:** `2026-07-18T23:13:35Z`
- **Hugging Face repo:** [electricsheepafrica/africa-tunisia-ressources-humaines-crac-monastir-en-2021-8464ae56](https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-ressources-humaines-crac-monastir-en-2021-8464ae56)

## 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
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present

## Citation

```bibtex
@misc{electric_sheep_africa_africa_tunisia_ressources_humaines_crac_monastir_en_2021_8464ae56_2021,
  title        = {Ressources Humaines Crac Monastir En 2021 | Africa (Tunisia Open Data)},
  author       = {Minstère des affaires culturelles},
  year         = {2021},
  url          = {https://catalog.data.gov.tn/dataset/ressources-humaines-crac-monastir-en-2021},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-ressources-humaines-crac-monastir-en-2021-8464ae56}}
}
```

## 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/ressources-humaines-crac-monastir-en-2021