electricsheepafrica/africa-composition-du-gouvernement-du-maroc-2011-2023

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- government
- morocco
- politics
pretty_name: "Composition du gouvernement du Maroc 2011-2023"
dataset_info:
splits:
- name: train
num_examples: 300
- name: test
num_examples: 75
---

# Composition du gouvernement du Maroc 2011-2023

**Publisher:** TAFRA · **Source:** [OpenAfrica](https://open.africa/dataset/composition-du-gouvernement-du-maroc-2011-2023) · **License:** `cc-by` · **Updated:** 2024-02-05

---

## Abstract

Données sur les membres du gouvernement du Royaume du Maroc de 2011 à août 2023. Les données ont été collectées à partir des bulletins officiels publiés sur le site web du Secrétariat général du gouvernement http://www.sgg.gov.ma.

Data on members of the Government of the Kingdom of Morocco from 2011 to August 2023. The data was collected from official bulletins published on the website of the General Secretariat of the Government http://www.sgg.gov.ma.

Each row in this dataset represents time-series observations. Temporal coverage is indicated by the `datedebut`, `datefin` column(s). Geographic scope: **Africa (multiple countries)**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | Time-series observations |
| **Rows (total)** | 376 |
| **Columns** | 19 (6 numeric, 11 categorical, 2 datetime) |
| **Train split** | 300 rows |
| **Test split** | 75 rows |
| **Geographic scope** | Africa (multiple countries) |
| **Publisher** | TAFRA |
| **OpenAfrica last updated** | 2024-02-05 |

---

## Variables

**Temporal** — `datedebut`, `datefin`.

**Demographic** — `idperson` (range 68073.0–155970.0).

**Identifier / Metadata** — `idelection` (range 1.0–7.0), `idgouvernement` (range 1.0–11.0), `idministere` (range 1.0–376.0), `idministereparent` (range 1.0–358.0), `esa_source` (HDX) and 1 others.

**Other** — `nomgouvernement` (Othmani 2, Benkirane 2, Benkirane 5), `numerobo` (6642, 6195, 6442), `langue` (AR, FR), `nomministere` (Chef du gouvernement, Ministère délégué auprès du Ministère de l'intérieur, Ministère de la jeunesse et des sports), `nomministerear` (رئيس الحكومة, وزارة الداخلية, وزارة الأوقاف والشؤون الإسلامية) and 5 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-composition-du-gouvernement-du-maroc-2011-2023")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `idelection` | int64 | 0.0% | 1.0 – 7.0 (mean 1.891) |
| `idgouvernement` | int64 | 0.0% | 1.0 – 11.0 (mean 5.6569) |
| `nomgouvernement` | object | 0.0% | Othmani 2, Benkirane 2, Benkirane 5 |
| `datedebut` | datetime64[ns] | 0.0% | |
| `datefin` | datetime64[ns] | 6.6% | |
| `numerobo` | object | 0.0% | 6642, 6195, 6442 |
| `langue` | object | 0.0% | AR, FR |
| `idministere` | int64 | 0.0% | 1.0 – 376.0 (mean 188.5) |
| `nomministere` | object | 0.0% | Chef du gouvernement, Ministère délégué auprès du Ministère de l'intérieur, Ministère de la jeunesse et des sports |
| `nomministerear` | object | 0.0% | رئيس الحكومة, وزارة الداخلية, وزارة الأوقاف والشؤون الإسلامية |
| `idministereparent` | float64 | 64.6% | 1.0 – 358.0 (mean 178.5338) |
| `nomministereparent` | object | 64.6% | Chef du gouvernement, Ministère de l'industrie, du commerce, de l'investissement et de l'économie numérique, Ministère de l'enseignement supérieur, de la recherche scientifique et de la formation des cadres |
| `idperson` | int64 | 0.0% | 68073.0 – 155970.0 (mean 115747.7527) |
| `prenomnom` | object | 0.0% | ABDELLATIF LOUDIYI, AHMED TOUFIQ, AZIZ AKHANNOUCH |
| `prenomnomar` | object | 0.0% | عبد اللطيف لوديي, أحمد التوفيق, عزيز أخنوش |
| `femme` | int64 | 0.0% | 0.0 – 1.0 (mean 0.1702) |
| `parti` | object | 0.0% | PJD, RNI, SAP |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `idelection` | 1.0 | 7.0 | 1.891 | 2.0 |
| `idgouvernement` | 1.0 | 11.0 | 5.6569 | 6.0 |
| `idministere` | 1.0 | 376.0 | 188.5 | 188.5 |
| `idministereparent` | 1.0 | 358.0 | 178.5338 | 189.0 |
| `idperson` | 68073.0 | 155970.0 | 115747.7527 | 155916.0 |
| `femme` | 0.0 | 1.0 | 0.1702 | 0.0 |

---

## Curation

Raw data was downloaded from OpenAfrica via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from TAFRA and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `idministereparent`, `nomministereparent`.
- Refer to the [original HDX dataset page](https://open.africa/dataset/composition-du-gouvernement-du-maroc-2011-2023) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{openafrica_africa_composition_du_gouvernement_du_maroc_2011_2023,
title = {Composition du gouvernement du Maroc 2011-2023},
author = {TAFRA},
year = {2024},
url = {https://open.africa/dataset/composition-du-gouvernement-du-maroc-2011-2023},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*