electricsheepafrica/africa-morocco-liste-des-engagements-des-departements-ministeriels-237f714d

Liste Des Engagements Des Departements Ministeriels | Africa (Morocco Open Data)

2,067 rows - 1 Africa country/area - 2021-2024 - 3 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 2,067 rows from Morocco Open Data, covering Liste Des Engagements Des Departements Ministeriels. 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: Ce fichier présente la liste des engagements des départements ministériels pour la période 2016 à 2024

How To Read This Dataset

• —One row means: one indicator observation for one geography, time period, and optional source dimensions.
• —Primary geography column: country_iso3.
• —Best time column: year.
• —Time coverage basis: year.
• —Recommended join keys: country_iso3, year, indicator_id.

Coverage

Geographic Coverage

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

Indicators, Variables, Or Resource Contents

• —liste-des-engagements-des-departements-ministeriels-num-eng-f996a6ed - Liste des engagements des départements ministériels - num eng(sourceunitsunspecified)
• —liste-des-engagements-des-departements-ministeriels-num-seance-7294bda7 - Liste des engagements des départements ministériels - num seance(sourceunitsunspecified)
• —liste-des-engagements-des-departements-ministeriels-num-question-a2b3d734 - Liste des engagements des départements ministériels - num question(sourceunitsunspecified)

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-liste-des-engagements-des-departements-ministeriels-237f714d")
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"] == "MAR"]

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: Morocco Open Data
• —Publisher: Parlement
• —Portal: https://data.gov.ma/data
• —Resource: Engagements_mi_legislature_2021_2024.xlsx
• —License: Open Data Commons Open Database License
• —Retrieved/generated: 2026-07-16T22:06:25Z
• —Hugging Face repo: electricsheepafrica/africa-morocco-liste-des-engagements-des-departements-ministeriels-237f714d

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
• —Pivot to geography x period or indicator x period matrices
• —Check missingness before modeling
• —Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_morocco_liste_des_engagements_des_departements_ministeriels_237f714d_2024,
  title        = {Liste Des Engagements Des Departements Ministeriels | Africa (Morocco Open Data)},
  author       = {Parlement},
  year         = {2024},
  url          = {https://data.gov.ma/data/dataset/liste-des-engagements-des-departements-ministeriels-2021-2024},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-liste-des-engagements-des-departements-ministeriels-237f714d}}
}

License

Released under Open Data Commons Open Database License.

Original data is published by Parlement. 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 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.gov.ma/data/dataset/liste-des-engagements-des-departements-ministeriels-2021-2024