electricsheepafrica/africa-morocco-montants-moyens-honoraires-des-agents-immobiliers-region-d-0cb6107b

Montants moyens honoraires des agents immobiliers - Région de l'Oriental 2001-2022 | Africa (Morocco official open data)

152 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 de l'Oriental 2001-2022
• Publisher: MATNUHPV
• Resource: Honoraires agents immobiliers - région orientale 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	152	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.	a08d0bac-2edc-40e0-82d3-118ef830dc7a:honoraires-ville-region-orient: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_ville region orient
oujda	string	Source column.	``
villa	string	Source column.	``
pt	string	Source column.	MT
d_1267_61904110575	float64	Source column.	1422.4999999999998
d_1294_4925224806184	float64	Source column.	1452.9332365748169
d_1295_9588457680477	float64	Source column.	1520.6885391898606
d_1269_3398222330184	float64	Source column.	1540.2194041491198
d_1185_354171521724	float64	Source column.	1514.3381796982055
d_1186_7149349991116	float64	Source column.	1536.4564542351825
d_1254_2799174184063	float64	Source column.	1591.1962321665287
d_1358_7146182870536	float64	Source column.	1678.8003029954984
d_1391_9085409110571	float64	Source column.	1780.632134815169
d_1488_6127526656496	float64	Source column.	1872.829583827553
d_1518_5	float64	Source column.	1909.5
d_1561_5	float64	Source column.	1977.0
d_1582_5	float64	Source column.	2015.0
d_1593_5	float64	Source column.	2052.5
d_1605	float64	Source column.	2105.0
d_1624_1935483870966	float64	Source column.	2092.5925925925926
d_1646_774193548387	float64	Source column.	2143.5185185185182
d_1701_0177476515378	float64	Source column.	2218.760939360931
d_1764_1935483870975	float64	Source column.	2259.230769230769
d_1737_5	float64	Source column.	2243.4615384615386
d_1754_032258064516	float64	Source column.	2269.230769230768
d_1777_2580645161286	float64	Source column.	2293.692307692308
d_100	float64	Source column.	100.0
d_102_1199966633056	float64	Source column.	102.13941909137556
d_102_23567205471896	float64	Source column.	106.9025335107108
d_100_13574907535053	float64	Source column.	108.27552928992056
d_93_5102844848192	float64	Source column.	106.45611105084048
d_93_61763246818496	float64	Source column.	108.01099854025888
d_98_94770248357045	float64	Source column.	111.8591375863992
d_107_18635285738848	float64	Source column.	118.01759599265368
d_109_80495683441997	float64	Source column.	125.17624849315774
d_117_43376396169671	float64	Source column.	131.65761573480165
d_119_7915107582642	float64	Source column.	134.23550087873463
d_123_1836971017646	float64	Source column.	138.98066783831285
d_124_84034624626479	float64	Source column.	141.65202108963095
d_125_7081148457649	float64	Source column.	144.2882249560633
d_126_615327472515	float64	Source column.	147.97891036906856
d_128_12946916372485	float64	Source column.	147.10668489227368
d_129_91081232985408	float64	Source column.	150.68671483434227
d_134_18998078221765	float64	Source column.	155.97616445419553
d_139_17379679372624	float64	Source column.	158.82114370690823
d_137_06799469376625	float64	Source column.	157.71258618358797
d_138_372192368968	float64	Source column.	159.52413140462346
d_140_2044310541295	float64	Source column.	161.2437474651886
source_provider	string	Publishing organization.	MATNUHPV
source_dataset	string	Source package title.	Montants moyens honoraires des agents immobiliers - Région de l'Oriental
source_resource	string	Source resource title.	Honoraires agents immobiliers - région orientale 2001-2022.xlsx
source_package_id	string	CKAN package UUID.	5c381b1f-86d0-4261-98c2-e243b3e01b97
source_resource_id	string	CKAN resource UUID.	a08d0bac-2edc-40e0-82d3-118ef830dc7a
source_url	string	Original source resource URL.	https://data.gov.ma/data/fr/dataset/5c381b1f-86d0-4261-98c2-e243b3e01b97
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-d-0cb6107b")
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_d_0cb610_2026,
  title        = {Montants moyens honoraires des agents immobiliers - Région de l'Oriental 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-de-l-oriental-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-d-0cb6107b}}
}

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

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Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL: https://data.gov.ma/data/fr/dataset/5c381b1f-86d0-4261-98c2-e243b3e01b97/resource/a08d0bac-2edc-40e0-82d3-118ef830dc7a/download/honoraires-agents-immobilier-region-oriental-2001-2022.xlsx