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electricsheepafrica/africa-morocco-liste-des-agences-cnss-8401d6c7

Liste Des Agences Cnss | Africa (Morocco Open Data) 92 rows - 1 Africa country/area - time not specified - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 92 rows from Morocco Open Data, covering Liste Des Agences Cnss. 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-morocco-liste-des-agences-cnss-8401d6c7.

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Liste Des Agences Cnss | Africa (Morocco Open Data)

92 rows - 1 Africa country/area - time not specified - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 92 rows from Morocco Open Data, covering Liste Des Agences Cnss. 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: Listes des agences de la Caisse nationale de sécurité sociale (agence, adresse, code postale).

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: not detected.
  • —Time coverage basis: not detected.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows92
Countries/areas1
First periodn/a
Last periodn/a
Indicators0
Columns17
Source formatXLS

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MAR92n/an/aMorocco

Indicators, Variables, Or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.ab5017f8-0529-49a3-8518-8a814522e804:feuil1:0
country_iso3stringISO3 country or area code.MAR
country_namestringCountry or area name.Morocco
source_sheetstringSource column from the original resource.Feuil1
n_de_l_agencedoubleSource column from the original resource.3.0
nom_de_la_delegationstringSource column from the original resource.BEN MSIK SIDI OTHMAN
adressestringSource column from the original resource.Boulevard 10 Mars N°2 Sidi Othmane
code_postaldoubleSource column from the original resource.20000.0
column_5doubleSource column from the original resource.``
source_providerstringPublishing organization.Ministère de la Santé et de la Protection Sociale
source_datasetstringSource dataset or package title.Liste des agences CNSS
source_resourcestringSource resource title, table name, or file name.Agences CNSS 2011
source_package_idstringSource package identifier.2b54ba83-70a2-46f7-a541-43b83f6913d3
source_resource_idstringSource resource identifier.ab5017f8-0529-49a3-8518-8a814522e804
source_urlstringOriginal source URL or download URL.https://data.gov.ma/data/ar/dataset/2b54ba83-70a2-46f7-a541-43b83f691...
license_idstringSource license identifier.odc-odbl
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-16T21:31:48Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-liste-des-agences-cnss-8401d6c7")
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"] == "MAR"]

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

  • —No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
  • —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

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
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_morocco_liste_des_agences_cnss_8401d6c7_2026,
  title        = {Liste Des Agences Cnss | Africa (Morocco Open Data)},
  author       = {Ministère de la Santé et de la Protection Sociale},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/les-listes-des-agences-cnss},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-liste-des-agences-cnss-8401d6c7}}
}

License

Released under Open Data Commons Open Database License.

Original data is published by Ministère de la Santé et de la Protection Sociale. 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/les-listes-des-agences-cnss