electricsheepafrica/africa-drc-acces-humanitaire

République Démocratique du Congo : Accès Humanitaire

Publisher: OCHA Democratic Republic of the Congo (DRC) · Source: HDX · License: cc-by · Updated: 2025-10-27

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Abstract

L’analyse des contraintes d’accès à l’est de la RDC a été conduite au travers de consultations séparées avec les acteurs humanitaires - répartis par type d’organisation (ONGI, ONGN, NU). Elle donne une indication des difficultés rencontrées d’une part par les partenaires humanitaires pour atteindre les populations dans le besoin, et d’autre part pour ces populations d’accéder à l’assistance humanitaire et services fournis par ces organisations.

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-10-27. Geographic scope: COD.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Demographics and population
Unit of observation	Tabular records
Rows (total)	115
Columns	10 (4 numeric, 6 categorical, 0 datetime)
Train split	92 rows
Test split	23 rows
Geographic scope	COD
Publisher	OCHA Democratic Republic of the Congo (DRC)
HDX last updated	2025-10-27

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Variables

Geographic — zone_de_santé (Boga, Idjwi, Kalonge).

Identifier / Metadata — pcode (CD5402ZS01, CD6206ZS01, CD6205ZS03), esa_source (HDX), esa_processed (2026-04-18).

Other — provine (Ituri, Nord-Kivu, Sud-Kivu), territoite (Djugu, Lubero, Oïcha), nu (range 2.0–5.0), ongi (range 2.0–5.0), ongn (range 2.0–5.0) and 1 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-drc-acces-humanitaire")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
provine	object	0.0%	Ituri, Nord-Kivu, Sud-Kivu
territoite	object	0.0%	Djugu, Lubero, Oïcha
zone_de_santé	object	0.0%	Boga, Idjwi, Kalonge
pcode	object	0.0%	CD5402ZS01, CD6206ZS01, CD6205ZS03
nu	int64	0.0%	2.0 – 5.0 (mean 3.3913)
ongi	int64	0.0%	2.0 – 5.0 (mean 3.2261)
ongn	int64	0.0%	2.0 – 5.0 (mean 3.3043)
severite_globale	int64	0.0%	2.0 – 5.0 (mean 3.3391)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-18

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Numeric Summary

Column	Min	Max	Mean	Median
nu	2.0	5.0	3.3913	3.0
ongi	2.0	5.0	3.2261	3.0
ongn	2.0	5.0	3.3043	3.0
severite_globale	2.0	5.0	3.3391	3.0

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 8 column(s) with >80% missing values were removed: unnamed_8, unnamed_9, unnamed_10, unnamed_11, unnamed_12, unnamed_13.... The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from OCHA Democratic Republic of the Congo (DRC) and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_drc_acces_humanitaire,
  title     = {République Démocratique du Congo : Accès Humanitaire},
  author    = {OCHA Democratic Republic of the Congo (DRC)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/drc-acces-humanitaire},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.