electricsheepafrica/africa-morocco-liste-des-questions-ecrites-de-la-session-d-octobre-pour-l-603afea5

Liste Des Questions Ecrites De La Session D Octobre Pour L | Africa (Morocco Open Data)

2,089 rows - 1 Africa country/area - 2022-2023 - 1 indicator - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 2,089 rows from Morocco Open Data, covering Liste Des Questions Ecrites De La Session D Octobre Pour L. 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: يعرض هذا الملف قائمة الأسئلة الكتابية لدورة أكتوبر 2022

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

Dimension	Value
Rows	2,089
Countries/areas	1
First period	2022
Last period	2023
Indicators	1
Columns	24
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MAR	2,089	2022	2023	Morocco

Indicators, Variables, Or Resource Contents

• liste-des-questions-ecrites-de-la-session-d-octobre-pour-la-periode-2016-49b79b3f - Liste des questions écrites de la session d'Octobre pour la période 2016 à 2023(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	liste-des-questions-ecrites-de-la-session-d-octobre-pour-la-periode-2...
indicator_name	string	Human-readable indicator name.	Liste des questions écrites de la session d'Octobre pour la période 2...
country_iso3	string	ISO3 country or area code.	MAR
source_sheet	string	Source column from the original resource.	دورة أكتوبر 2022
country_name	string	Country or area name.	Morocco
date	string	Observation date.	2022-10-17
year	int64	Observation year.	2022
value	double	Numeric observation value.	6520.0
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_periode	string	Source dimension retained during long-form normalization.	دورة أكتوبر 2022
dimension_depute	string	Source dimension retained during long-form normalization.	فاطمة التامني
dimension_groupe	string	Source dimension retained during long-form normalization.	النواب غير المنتسبين--
dimension_ministere	string	Source dimension retained during long-form normalization.	التربية الوطنية والتعليم الأولي والرياضة
dimension_sujet	string	Source dimension retained during long-form normalization.	حول عدم إتمام بناء ثانوية الزيتون بإثنين لغياث - المديرية الإقليمية ل...
dimension_observation	string	Source dimension retained during long-form normalization.	السيد الوزير سعيا منا للإسهام في تعميم التعليم بالعالم القروي، وفي ال...
dimension_date_reponse	string	Source dimension retained during long-form normalization.	2022-12-15 00:00:00
source_provider	string	Publishing organization.	Parlement
source_dataset	string	Source dataset or package title.	Liste des questions écrites de la session d'Octobre pour la période 2...
source_resource	string	Source resource title, table name, or file name.	أكتوبر 2022
source_package_id	string	Source package identifier.	ba99bbb6-cd38-4d1f-8ea3-d80f2d4178c7
source_resource_id	string	Source resource identifier.	ff608c77-d742-49d7-aabe-e6774f16f988
source_url	string	Original source URL or download URL.	https://data.gov.ma/data/dataset/ba99bbb6-cd38-4d1f-8ea3-d80f2d4178c7...
license_id	string	Source license identifier.	odc-odbl
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-16T21:31:48Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-liste-des-questions-ecrites-de-la-session-d-octobre-pour-l-603afea5")
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: أكتوبر 2022
• License: Open Data Commons Open Database License
• Retrieved/generated: 2026-07-16T22:05:49Z
• Hugging Face repo: electricsheepafrica/africa-morocco-liste-des-questions-ecrites-de-la-session-d-octobre-pour-l-603afea5

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
• 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_questions_ecrites_de_la_session_d_octobre_pour_l_603afe_2023,
  title        = {Liste Des Questions Ecrites De La Session D Octobre Pour L | Africa (Morocco Open Data)},
  author       = {Parlement},
  year         = {2023},
  url          = {https://data.gov.ma/data/dataset/liste-des-questions-ecrites-au-titre-de-la-10eme-legislature-2016-2020},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-liste-des-questions-ecrites-de-la-session-d-octobre-pour-l-603afea5}}
}

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.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.gov.ma/data/dataset/liste-des-questions-ecrites-au-titre-de-la-10eme-legislature-2016-2020