electricsheepafrica/africa-structures-de-sante-guinee-vf

Structures de Santé - Guinée

Publisher: American Red Cross (inactive) · Source: HDX · License: other-pd-nr · Updated: 2025-02-06

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Abstract

Cette donnée contient la liste des structures de Santé de la Guinée. Cette donnée contient la liste de 2430 structures de santé dont 1773 avec les coordonnées géographiques (latitude et longitude). Le nombre de structures de santé sans coordonnées GPS est de 666.

Each row in this dataset represents geolocated point observations. Data was last updated on HDX on 2025-02-06. Geographic scope: GIN.

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

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Dataset Characteristics

Domain	Public health
Unit of observation	Geolocated point observations
Rows (total)	2,437
Columns	3 (0 numeric, 3 categorical, 0 datetime)
Train split	1,949 rows
Test split	487 rows
Geographic scope	GIN
Publisher	American Red Cross (inactive)
HDX last updated	2025-02-06

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Variables

Geographic — nom_code_prefecture_latitude_longiture (CSR de Albadariah centre;;CSR524;KISSIDOUGOU;;9.55066709;-10.09971425, PS Dandakara;;;DABOLA;;;, CSR de konendou;;CSR893;DABOLA;;10.68601728;-10.85957025).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-07).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-structures-de-sante-guinee-vf")
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
nom_code_prefecture_latitude_longiture	object	0.0%	CSR de Albadariah centre;;CSR524;KISSIDOUGOU;;9.55066709;-10.09971425, PS Dandakara;;;DABOLA;;;, CSR de konendou;;CSR893;DABOLA;;10.68601728;-10.85957025
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-07

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Numeric Summary

Column	Min	Max	Mean	Median
No numeric columns.

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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. 2 exact duplicate rows were removed. 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 American Red Cross (inactive) 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_structures_de_sante_guinee_vf,
  title     = {Structures de Santé - Guinée},
  author    = {American Red Cross (inactive)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/structures_de_sante_guinee_vf},
  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.