electricsheepafrica/africa-morocco-montants-moyens-honoraires-des-agents-immobiliers-region-g-247e7a05

Montants moyens honoraires des agents immobiliers – Région Guelmim - Oued Noun 2001-2022 | Africa (Morocco official open data)

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

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

• Source: Montants moyens honoraires des agents immobiliers – Région Guelmim - Oued Noun 2001-2022
• Publisher: MATNUHPV
• Resource: Honoraires agents immobiliers région Guelmim - Oued Noun 2001-2022.xlsx
• Format: XLSX
• License: Open Data Commons Open Database License
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
MAR	84	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.	e8825c8f-0346-4b82-9892-21fd41c82247:honoraires-par-ville-region-gon: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.	honoraires par ville region GON
guelmim	string	Source column.	``
villa	string	Source column.	``
pt	string	Source column.	MT
d_1042_6151166221514	float64	Source column.	1534.3565476808174
d_1039_2327441760742	float64	Source column.	1539.175300687867
d_1089_0647822416763	float64	Source column.	1514.4721958086998
d_1077_7313651026245	float64	Source column.	1492.339643488729
d_1069_0680369857507	float64	Source column.	1477.66098118451
d_1064_3087280991904	float64	Source column.	1459.7243729116392
d_1039_6213416981748	float64	Source column.	1409.714766700548
d_1080_6140776866227	float64	Source column.	1519.2150506502453
d_1140_9188566609228	float64	Source column.	1701.3099672925198
d_1356_5247084161392	float64	Source column.	1607.4236127208349
d_1404_0157187934103	float64	Source column.	1626.281994956616
d_1444_0951191523131	float64	Source column.	1645.7487121032289
d_1447_4201946761425	float64	Source column.	1646.1542687104495
d_1431_6819324233338	float64	Source column.	1875.6993083975929
d_1462_0624508832452	float64	Source column.	1942.6161485890748
d_1452_568538864523	float64	Source column.	1927.4077758182837
d_1445_393606112148	float64	Source column.	1918.6435178753743
d_1452_1714711696713	float64	Source column.	1913.685499001002
d_1454	float64	Source column.	1910.0
d_1426	float64	Source column.	1824.0
d_1461	float64	Source column.	1840.0
d_1526	float64	Source column.	1917.0
d_100	float64	Source column.	100.0
d_99_67558762652173	float64	Source column.	100.31405692596896
d_104_45511146721255	float64	Source column.	98.7040592421512
d_103_36809316502548	float64	Source column.	97.26159449343132
d_102_53717023107252	float64	Source column.	96.30492882622342
d_102_08069220666218	float64	Source column.	95.13593011468
d_99_71285905256431	float64	Source column.	91.87660904705194
d_103_64458182685667	float64	Source column.	99.01316958868144
d_109_4285742141601	float64	Source column.	110.88100545235416
d_130_10790720270654	float64	Source column.	104.7620655805496
d_134_66289682640695	float64	Source column.	105.99113989605246
d_138_50701914152853	float64	Source column.	107.25986177011993
d_138_8259360141902	float64	Source column.	107.28629347582964
d_137_31643725459068	float64	Source column.	122.24663890754178
d_140_23031390720797	float64	Source column.	126.60787034964868
d_139_31972745326507	float64	Source column.	125.61668138553348
d_138_6315604932827	float64	Source column.	125.04548051594706
d_139_28164363033545	float64	Source column.	124.7223470902862
d_139_45702271329492	float64	Source column.	124.48214874743216
d_136_77146794302513	float64	Source column.	118.87719335880432
d_140_12841140586238	float64	Source column.	119.91997575668856
d_146_36273497970294	float64	Source column.	124.93836604650652
source_provider	string	Publishing organization.	MATNUHPV
source_dataset	string	Source package title.	Montants moyens honoraires des agents immobiliers – Région Guelmim - Oue
source_resource	string	Source resource title.	Honoraires agents immobiliers région Guelmim - Oued Noun 2001-2022.xlsx
source_package_id	string	CKAN package UUID.	e8b2f48e-f643-46ec-aa49-d8d7a4a884a4
source_resource_id	string	CKAN resource UUID.	e8825c8f-0346-4b82-9892-21fd41c82247
source_url	string	Original source resource URL.	https://data.gov.ma/data/fr/dataset/e8b2f48e-f643-46ec-aa49-d8d7a4a884a4
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-montants-moyens-honoraires-des-agents-immobiliers-region-g-247e7a05")
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_montants_moyens_honoraires_des_agents_immobiliers_region_g_247e7a_2026,
  title        = {Montants moyens honoraires des agents immobiliers – Région Guelmim - Oued Noun 2001-2022 | Africa (Morocco official open data)},
  author       = {MATNUHPV},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/montants-moyens-honoraires-des-agents-immobiliers-region-guelmim-oued-noun-2001-2019},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-montants-moyens-honoraires-des-agents-immobiliers-region-g-247e7a05}}
}

License

Released under Open Data Commons Open Database License.

Original data (c) MATNUHPV. 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/e8b2f48e-f643-46ec-aa49-d8d7a4a884a4/resource/e8825c8f-0346-4b82-9892-21fd41c82247/download/honoraires-agents-immobilier-region-gon-2001-2022.xlsx