electricsheepafrica/africa-health-facilities-eritrea

Eritrea Healthsites

Publisher: Global Healthsites Mapping Project · Source: HDX · License: ODbL · Updated: 2025-10-15

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Abstract

This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-10-15. Geographic scope: ERI.

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

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Dataset Characteristics

Domain	Public health
Unit of observation	Tabular records
Rows (total)	36
Columns	15 (6 numeric, 8 categorical, 0 datetime)
Train split	28 rows
Test split	7 rows
Geographic scope	ERI
Publisher	Global Healthsites Mapping Project
HDX last updated	2025-10-15

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Variables

Geographic — x (range 38.2353–38.9396), y (range 14.6368–17.1095), osm_type (way, node), amenity (hospital, pharmacy, clinic), addr_city (أسمرة, كرن, بارنتو).

Temporal — changeset_timestamp.

Identifier / Metadata — osm_id (range 144941432.0–12734115401.0), name (ፋርማሲ, Pharmacy No. 5 / صيدلية رقم 5, Halibet Referral Hospital), changeset_id (range 53411420.0–167274718.0), uuid (5cb0f41dc5fa404589f7285dbd57b9b6, b418bf6196614e30b148481078d70ee1, f5535e8d0ab04d17abf09379385b6d5a), esa_source (HDX) and 1 others.

Other — completeness (range 6.25–18.75), healthcare (hospital, pharmacy, clinic), changeset_version (range 1.0–8.0).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-health-facilities-eritrea")
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
x	float64	61.1%	38.2353 – 38.9396 (mean 38.8297)
y	float64	61.1%	14.6368 – 17.1095 (mean 15.5132)
osm_id	int64	0.0%	144941432.0 – 12734115401.0 (mean 3277352426.6111)
osm_type	object	0.0%	way, node
completeness	float64	0.0%	6.25 – 18.75 (mean 12.934)
amenity	object	0.0%	hospital, pharmacy, clinic
healthcare	object	30.6%	hospital, pharmacy, clinic
name	object	8.3%	ፋርማሲ, Pharmacy No. 5 / صيدلية رقم 5, Halibet Referral Hospital
addr_city	object	52.8%	أسمرة, كرن, بارنتو
changeset_id	int64	0.0%	53411420.0 – 167274718.0 (mean 106521784.8056)
changeset_version	int64	0.0%	1.0 – 8.0 (mean 2.8611)
changeset_timestamp	datetime64[ns, UTC]	0.0%
uuid	object	0.0%	5cb0f41dc5fa404589f7285dbd57b9b6, b418bf6196614e30b148481078d70ee1, f5535e8d0ab04d17abf09379385b6d5a
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-20

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Numeric Summary

Column	Min	Max	Mean	Median
x	38.2353	38.9396	38.8297	38.9328
y	14.6368	17.1095	15.5132	15.3381
osm_id	144941432.0	12734115401.0	3277352426.6111	818425933.0
completeness	6.25	18.75	12.934	12.5
changeset_id	53411420.0	167274718.0	106521784.8056	85170511.5
changeset_version	1.0	8.0	2.8611	2.0

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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. 22 column(s) with >80% missing values were removed: operator, source, speciality, operator_type, operational_status, opening_hours.... 1 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 Global Healthsites Mapping Project and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• The following columns have >20% missing values and should be treated with caution in modelling: x, y, healthcare, addr_city.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_health_facilities_eritrea,
  title     = {Eritrea Healthsites},
  author    = {Global Healthsites Mapping Project},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/eritrea-healthsites},
  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.