README.md

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- morocco
- parliament
- politics
- members-of-parliament
pretty_name: "Membres de la Chambre des Représentants du Maroc"
dataset_info:
  splits:
    - name: train
      num_examples: 1323
    - name: test
      num_examples: 330
---

# Membres de la Chambre des Représentants du Maroc

**Publisher:** TAFRA · **Source:** [OpenAfrica](https://open.africa/dataset/membres-de-la-chambre-des-representants-du-maroc-2007-2011-2016-2021) · **License:** `cc-by` · **Updated:** 2024-02-05

---

## Abstract

Données sur les membres de la Chambre des représentant du Royaume du Maroc au titre des législatures 2007-2011, 2011-2016, 2016-2021 et 2021-2026. Les données ont été collectées à partir des annuaires parlementaires des parlements 2007-2011 et 2011-2016, liste des élus des élections parlementaires de 2011 communiquée par le National Democracy Institute, et complété avec arrêts du Conseil Constitutionnel, ainsi qu'une série de sources annexes. Les données correspondant au parlement de 2016-2021 ont été copiées à partir du site http://www.chambredesrepresentants.ma. Les données correspondant au parlement de 2021-2026 ont été copiées à partir du site http://www.elections.ma et du site http://www.chambredesrepresentants.ma, et complétées avec les arrêts de la Cour Constitutionnelle ainsi qu'une sélection de sources annexes. La colonne "parti" contient le premier parti relevé sur les sources consultées pour chaque parlement. Elle ne relève pas les députés transhumants.

Data on members of the House of Representatives of the Kingdom of Morocco for the 2007-2011, 2011-2016, 2016-2021 and 2021-2026 legislatures. Data has been compiled from Parliamentary Directories of Parliaments 2007-2011 and 2011-2016, list of winning candidates of 2011 Parliamentary elections from National Democracy Institute, and completed with rulings from Constitutional Council, as well as a series of additional sources. Data for the 2016-2021 Parliament has been copied from http://www.chambredesrepresentants.ma. Data for the 2021-2026 parliament has been copied from http://www.elections.ma and http://www.chambredesrepresentants.ma and completed with ruling from Constitutional Court rulings and a selection of additional resources. The "party" column records the first recorded party for each Parliament. It does not record within-Parliament switches in party affiliation.

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the `dateentree`, `datesortie` 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** | First-level administrative unit observations |
| **Rows (total)** | 1,654 |
| **Columns** | 23 (7 numeric, 14 categorical, 2 datetime) |
| **Train split** | 1,323 rows |
| **Test split** | 330 rows |
| **Geographic scope** | Africa (multiple countries) |
| **Publisher** | TAFRA |
| **OpenAfrica last updated** | 2024-02-05 |

---

## Variables

**Geographic** — `idregion` (range 606.0–634.0), `idwilaya` (range 2.0–30.0), `region` (Casablanca - Settat, Oriental, Rabat - Salé - Kénitra), `wilaya` (Casablanca - Settat, Oriental, Rabat - Salé - Kénitra).

**Temporal** — `dateentree`, `datesortie`.

**Demographic** — `idperson` (range 68069.0–155912.0).

**Identifier / Metadata** — `idprefprov` (range 171.0–323.0), `idcirconscription` (range 416.0–44392.0), `prefprov` (Casablanca, Marrakech, Salé), `idsiege` (range 1.0–1115.0), `esa_source` and 1 others.

**Other** — `circonscription` (Liste nationale, Béni-Mellal, Settat), `parlement` (2011-2016, 2016-2021, 2021-2026), `prenomnom` (MOHAMED KARIM, ABDELHAQ CHAFIQ, MOHAMED BERNICHI), `prenomnomar` (محمد برنيشي, عبد الحق	الشفيق, محمد كاريم), `femme` (range 0.0–1.0) and 5 others.

---

## Quick Start

```python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-membres-de-la-chambre-des-representants-du-maroc-2007-2011-2016-2021")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `idregion` | float64 | 13.2% | 606.0 – 634.0 (mean 620.789) |
| `idwilaya` | float64 | 18.6% | 2.0 – 30.0 (mean 16.3447) |
| `idprefprov` | float64 | 18.6% | 171.0 – 323.0 (mean 264.4666) |
| `idcirconscription` | int64 | 0.0% | 416.0 – 44392.0 (mean 2930.1391) |
| `region` | object | 13.2% | Casablanca - Settat, Oriental, Rabat - Salé - Kénitra |
| `wilaya` | object | 18.6% | Casablanca - Settat, Oriental, Rabat - Salé - Kénitra |
| `prefprov` | object | 18.6% | Casablanca, Marrakech, Salé |
| `circonscription` | object | 0.0% | Liste nationale, Béni-Mellal, Settat |
| `parlement` | object | 0.0% | 2011-2016, 2016-2021, 2021-2026 |
| `idsiege` | int64 | 0.0% | 1.0 – 1115.0 (mean 551.4607) |
| `idperson` | int64 | 0.0% | 68069.0 – 155912.0 (mean 83331.1475) |
| `prenomnom` | object | 0.0% | MOHAMED KARIM, ABDELHAQ CHAFIQ, MOHAMED BERNICHI |
| `prenomnomar` | object | 0.0% | محمد برنيشي, عبد الحق	الشفيق, محمد كاريم |
| `femme` | int64 | 0.0% | 0.0 – 1.0 (mean 0.1729) |
| `parti` | object | 0.0% | PJD, PAM, PI |
| `dateentree` | datetime64[ns] | 0.0% |  |
| `datesortie` | datetime64[ns] | 23.7% |  |
| `motifentree` | object | 0.0% | Elu, Remplaçant, Elu partiel |
| `motifsortie` | object | 23.7% | Fin de mandat, Incompatibilité, Fraude électorale |
| `groupe` | object | 20.4% |  |
| `groupear` | object | 20.4% |  |
| `esa_source` | object | 0.0% |  |
| `esa_processed` | object | 0.0% |  |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `idregion` | 606.0 | 634.0 | 620.789 | 623.0 |
| `idwilaya` | 2.0 | 30.0 | 16.3447 | 19.0 |
| `idprefprov` | 171.0 | 323.0 | 264.4666 | 270.0 |
| `idcirconscription` | 416.0 | 44392.0 | 2930.1391 | 556.0 |
| `idsiege` | 1.0 | 1115.0 | 551.4607 | 542.0 |
| `idperson` | 68069.0 | 155912.0 | 83331.1475 | 68654.5 |
| `femme` | 0.0 | 1.0 | 0.1729 | 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`. 3 column(s) with >80% missing values were removed: `idsouspref`, `souspref`, `procedureremplacement`. 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: `datesortie`, `motifsortie`, `groupe`, `groupear`.
- Refer to the [original HDX dataset page](https://open.africa/dataset/membres-de-la-chambre-des-representants-du-maroc-2007-2011-2016-2021) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{openafrica_africa_membres_de_la_chambre_des_representants_du_maroc_2007_2011_2016_2021,
  title     = {Membres de la Chambre des Représentants du Maroc},
  author    = {TAFRA},
  year      = {2024},
  url       = {https://open.africa/dataset/membres-de-la-chambre-des-representants-du-maroc-2007-2011-2016-2021},
  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.*