CoolFace
Datasetpublic

electricsheepafrica/africa-morocco-ventilation-des-comptes-debiteurs-et-credits-de-tresorerie-da268f98

Ventilation Des Comptes Debiteurs Et Credits De Tresorerie | Africa (Morocco Open Data) 19 rows - 1 Africa country/area - time not specified - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 19 rows from Morocco Open Data, covering Ventilation Des Comptes Debiteurs Et Credits De Tresorerie. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-morocco-ventilation-des-comptes-debiteurs-et-credits-de-tresorerie-da268f98.

sourceHugging Faceodblupdated 2mo agoView on Hugging Face
0likes10downloads
Dataset Card

Ventilation Des Comptes Debiteurs Et Credits De Tresorerie | Africa (Morocco Open Data)

19 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 19 rows from Morocco Open Data, covering Ventilation Des Comptes Debiteurs Et Credits De Tresorerie. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

Source-provided context: Ce fichier présente la ventilation des comptes débiteurs et crédits de trésorerie par branche d'activité pour la période de décembre 2006 à septembre 2023

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
Rows19
Countries/areas1
First periodn/a
Last periodn/a
Indicators0
Columns81
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MAR19n/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.99af1e6b-a926-4326-8bf3-07f11897bfaf:feuil1:0
country_iso3stringISO3 country or area code.MAR
country_namestringCountry or area name.Morocco
source_sheetstringSource column from the original resource.Feuil1
comptes_debiteurs_et_credits_de_tresoreriestringSource column from the original resource.Secteur primaire
d_101340_81044466216doubleSource column from the original resource.6653.647871446412
d_95966_80838969898doubleSource column from the original resource.5648.657855839975
d_104621_52997076433doubleSource column from the original resource.6649.239120807103
d_105025_67281032451doubleSource column from the original resource.6663.286789612842
d_112840_0799370537doubleSource column from the original resource.7552.731321754256
d_113186_60391786945doubleSource column from the original resource.7222.483550200311
d_128227_0109229889doubleSource column from the original resource.7780.684031721057
d_131767_28038424868doubleSource column from the original resource.9442.532203563673
d_134535_34866792752doubleSource column from the original resource.9594.628145109476
d_132553_84739072813doubleSource column from the original resource.8062.985511648985
d_134779_0825584518doubleSource column from the original resource.8818.17904747776
d_136497_1596843356doubleSource column from the original resource.9743.914244164418
d_135100_15962587335doubleSource column from the original resource.9661.06413640068
d_134039_5811457165doubleSource column from the original resource.8423.000436317427
d_145682_75725831444doubleSource column from the original resource.8440.5008932478
d_141723_47279124596doubleSource column from the original resource.7161.228143272253
d_143031_7977972467doubleSource column from the original resource.11570.185645435844
d_146527_97167359112doubleSource column from the original resource.10890.115471411327
d_165078_78582218027doubleSource column from the original resource.12481.229292877371
d_165819_94187983082doubleSource column from the original resource.12036.29323975196
d_172323_729567837doubleSource column from the original resource.14994.662892430286
d_169962_11032464306doubleSource column from the original resource.13352.257061280568
d_180663_57703714728doubleSource column from the original resource.14277.352550085394
d_181461_09585088206doubleSource column from the original resource.14437.162798850046
d_185713_00303420107doubleSource column from the original resource.14448.851382242385
d_171457_92650507198doubleSource column from the original resource.14420.150300140082
d_183718_89388752973doubleSource column from the original resource.14999.244267705526
d_180683_06894126724doubleSource column from the original resource.15975.252336826185
d_175284_5356437572doubleSource column from the original resource.15573.784994062864
d_171824_81415731666doubleSource column from the original resource.14326.564420556708
d_187501_35663907597doubleSource column from the original resource.14317.057504547707
d_183970_71094794793doubleSource column from the original resource.14398.34781476276
d_180657_35175899768doubleSource column from the original resource.14437.586039404709
d_172130_67096523446doubleSource column from the original resource.14695.000603129009
d_180507_13309552806doubleSource column from the original resource.14914.47501930182
d_174057_11774255976doubleSource column from the original resource.13990.760399830377
d_171830_39475702826doubleSource column from the original resource.15042.50599422548
d_170060_5678884659doubleSource column from the original resource.14729.246931768255
d_179589_15879950707doubleSource column from the original resource.15073.52876979044
d_177104_20173427073doubleSource column from the original resource.15089.078693504922
d_172728_16302306292doubleSource column from the original resource.15478.967796948422
d_164557_04910663728doubleSource column from the original resource.13294.687293239322
d_182527_16665398632doubleSource column from the original resource.13390.14773570441
d_171350_75674382068doubleSource column from the original resource.13757.530259862147
d_167383_2484630037doubleSource column from the original resource.13853.858031850585
d_163445_7263247729doubleSource column from the original resource.14118.416371447292
d_175737_7627191416doubleSource column from the original resource.14079.025567323672
d_176704_44760463887doubleSource column from the original resource.11981.029356660998
d_177725_05906188482doubleSource column from the original resource.13080.329070741824
d_180001_72601093067doubleSource column from the original resource.17061.29251533496
d_186496_92853924702doubleSource column from the original resource.17509.093023421203
d_188665_39227273737doubleSource column from the original resource.18557.39589802836
d_189744_65218062687doubleSource column from the original resource.19732.699762421995
d_194393_46942613725doubleSource column from the original resource.18239.86330066713
d_206649_2607680624doubleSource column from the original resource.18684.012545449503
d_209535_16419441366doubleSource column from the original resource.19505.670292634877
d_206088_47248915094doubleSource column from the original resource.19319.80080675625
d_211098_13941836162doubleSource column from the original resource.19303.02998758663
d_227262_30385095064doubleSource column from the original resource.19946.389742491298
d_228326_18002730384doubleSource column from the original resource.20551.95805895393
d_225741_086944977doubleSource column from the original resource.21063.46850564472
d_226887_28113384932doubleSource column from the original resource.20792.39546168803
d_249581_11762249042doubleSource column from the original resource.22629.43906878858
d_266650_1678412406doubleSource column from the original resource.22906.734425451785
d_264033_596688312doubleSource column from the original resource.23542.006215225545
d_249127_83017700925doubleSource column from the original resource.21908.834793030717
d_256577_9620684064doubleSource column from the original resource.21365.76531785356
d_250453_14720100656doubleSource column from the original resource.21362.473130431703
source_providerstringPublishing organization.Bank Al-Maghrib
source_datasetstringSource dataset or package title.Ventilation des comptes débiteurs et crédits de trésorerie par branch...
source_resourcestringSource resource title, table name, or file name.16-Ventilation des comptes débiteurs et crédits de trésorerie par bra...
source_package_idstringSource package identifier.a774e895-9cfa-47bf-8798-3a7acbf06aed
source_resource_idstringSource resource identifier.99af1e6b-a926-4326-8bf3-07f11897bfaf
source_urlstringOriginal source URL or download URL.https://data.gov.ma/data/fr/dataset/a774e895-9cfa-47bf-8798-3a7acbf06...
license_idstringSource license identifier.odc-odbl
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-ventilation-des-comptes-debiteurs-et-credits-de-tresorerie-da268f98")
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 time-series dashboards
  • —Compare economic indicators
  • —Join with population or sector data
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_morocco_ventilation_des_comptes_debiteurs_et_credits_de_tresorerie_da268f_2026,
  title        = {Ventilation Des Comptes Debiteurs Et Credits De Tresorerie | Africa (Morocco Open Data)},
  author       = {Bank Al-Maghrib},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/ventilation-des-comptes-debiteurs-et-credits-de-tresorerie-par-branche-d-activite},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-ventilation-des-comptes-debiteurs-et-credits-de-tresorerie-da268f98}}
}

License

Released under Open Data Commons Open Database License.

Original data is published by Bank Al-Maghrib. 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/ventilation-des-comptes-debiteurs-et-credits-de-tresorerie-par-branche-d-activite