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electricsheepafrica
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africa-morocco-statistiques-hebdomadaires-des-organismes-de-placement-col-d94595a4

Tasks:
Tabular Classification
Tabular Regression
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
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Tags:
tabular
xlsx
africa
morocco
official-statistics
open-data
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metadata 
license: odbl
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
multilinguality: monolingual
size_categories:
  - n<1K
tags:
  - tabular
  - xlsx
  - africa
  - morocco
  - official-statistics
  - open-data
pretty_name: >-
  Statistiques hebdomadaires des Organismes de Placement Collectif en Valeurs
  Mobilières (OPCVM) pour l'année 2026 | Africa (Morocco official open data)

Statistiques hebdomadaires des Organismes de Placement Collectif en Valeurs Mobilières (OPCVM) pour l'année 2026 | Africa (Morocco official open data)

37 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official XLSX resource from Morocco as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

Geographic coverage

1 Africa country:

Country Rows First year Last year Name
MAR 37 n/a n/a Morocco

Indicators or Resource Contents

  • This source file is packaged as a normalized tabular resource.

Schema

Column Type Description Example
source_record_id string Stable row identifier for tabular resources. 82bfa284-a5c0-40dd-9af1-f3e5d04629a0:francais:0
country_iso3 string ISO3 country code. MAR
country_name string Country name. Morocco
source_sheet string Workbook sheet name, when the source is a spreadsheet. Français
categorie string Source column. Actions
nombre_opcvm string Source column. 119
montant string Source column. 75554126814.7118
structure string Source column. 9.13902496925678
variation_hebdomadaire string Source column. -0.634650718309673
variation_mensuelle float64 Source column. -3.47291838883052
variation_annuelle float64 Source column. -2.14814549829833
column_8 string Source column. ``
source_provider string Publishing organization. AMMC
source_dataset string Source package title. Statistiques hebdomadaires des Organismes de Placement Collectif en Vale
source_resource string Source resource title. STAT_OPCVM_HEBDO_AMMC_22-05-2026.xlsx
source_package_id string CKAN package UUID. 05bc218e-19f3-424a-94c6-dd1a79d2f189
source_resource_id string CKAN resource UUID. 82bfa284-a5c0-40dd-9af1-f3e5d04629a0
source_url string Original source resource URL. https://data.gov.ma/data/fr/dataset/05bc218e-19f3-424a-94c6-dd1a79d2f189
license_id string Source license identifier. odc-odbl
retrieved_at string UTC retrieval timestamp. 2026-07-16T21:31:48Z

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-statistiques-hebdomadaires-des-organismes-de-placement-col-d94595a4")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country 

sample_country = df[df["country_iso3"] == "MAR"]

Work with indicators 

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation 

@misc{electric_sheep_africa_africa_morocco_statistiques_hebdomadaires_des_organismes_de_placement_col_d94595_2026,
  title        = {Statistiques hebdomadaires des Organismes de Placement Collectif en Valeurs Mobilières (OPCVM) pour l'année 2026 | Africa (Morocco official open data)},
  author       = {AMMC},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/stat-hebdo-opcvm-2026},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-statistiques-hebdomadaires-des-organismes-de-placement-col-d94595a4}}
}

License

Released under Open Data Commons Open Database License.

Original data (c) AMMC. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.gov.ma/data/fr/dataset/05bc218e-19f3-424a-94c6-dd1a79d2f189/resource/82bfa284-a5c0-40dd-9af1-f3e5d04629a0/download/stat_opcvm_hebdo_ammc_22-05-2026.xlsx