electricsheepasia/asia-health-facilities-mongolia-healthsites

Mongolia 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: MNG.

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)	1,648
Columns	19 (6 numeric, 12 categorical, 0 datetime)
Train split	1,318 rows
Test split	329 rows
Geographic scope	MNG
Publisher	Global Healthsites Mapping Project
HDX last updated	2025-10-15

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Variables

Geographic — x (range 89.1349–114.5453), y (range 43.4655–50.4416), osm_type (node, way), amenity (pharmacy, hospital, clinic).

Temporal — changeset_timestamp.

Outcome / Measurement — addr_housenumber (13-р байр, 19-р байр, 32-р байр).

Identifier / Metadata — osm_id (range 155458531.0–13232839355.0), name (Эмийн сан, эмийн сан, Монос), changeset_id (range 7871166.0–173277906.0), uuid (1dcb58c590574746993c8eff7797481f, 4312d13fe29f48fc835664ac82ea8950, 67f4955acf374856b31b0e944880d35f), esa_source and 1 others.

Other — completeness (range 6.25–43.75), healthcare (pharmacy, clinic, hospital), operator (монос улаанбаатар трейд ххк, ази фарма ххк, Монос Улаанбаатар ххк), opening_hours (Mo-Fr 08:30-17:30, Mo-Su 09:00-22:00, 24/7), wheelchair (no, yes, limited) and 2 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-health-facilities-mongolia-healthsites")
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	14.2%	89.1349 – 114.5453 (mean 105.9451)
y	float64	14.2%	43.4655 – 50.4416 (mean 47.9765)
osm_id	int64	0.0%	155458531.0 – 13232839355.0 (mean 6589600281.4879)
osm_type	object	0.0%	node, way
completeness	float64	0.0%	6.25 – 43.75 (mean 20.9857)
amenity	object	1.1%	pharmacy, hospital, clinic
healthcare	object	21.5%	pharmacy, clinic, hospital
name	object	14.1%	Эмийн сан, эмийн сан, Монос
operator	object	72.5%	монос улаанбаатар трейд ххк, ази фарма ххк, Монос Улаанбаатар ххк
opening_hours	object	63.9%	Mo-Fr 08:30-17:30, Mo-Su 09:00-22:00, 24/7
wheelchair	object	53.3%	no, yes, limited
addr_housenumber	object	61.0%	13-р байр, 19-р байр, 32-р байр
addr_street	object	53.8%	Энх тайвны өргөн чөлөө, Энх тайваны өргөн чөлөө, Ард Аюушийн өргөн чөлөө
changeset_id	int64	0.0%	7871166.0 – 173277906.0 (mean 121091603.5643)
changeset_version	int64	0.0%	1.0 – 25.0 (mean 2.568)
changeset_timestamp	datetime64[ns, UTC]	0.0%
uuid	object	0.0%	1dcb58c590574746993c8eff7797481f, 4312d13fe29f48fc835664ac82ea8950, 67f4955acf374856b31b0e944880d35f
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
x	89.1349	114.5453	105.9451	106.8858
y	43.4655	50.4416	47.9765	47.9179
osm_id	155458531.0	13232839355.0	6589600281.4879	8301549265.5
completeness	6.25	43.75	20.9857	18.75
changeset_id	7871166.0	173277906.0	121091603.5643	117844959.0
changeset_version	1.0	25.0	2.568	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. 18 column(s) with >80% missing values were removed: source, speciality, operator_type, operational_status, beds, staff_doctors.... 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: healthcare, operator, opening_hours, wheelchair, addr_housenumber, addr_street.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_asia_health_facilities_mongolia_healthsites,
  title     = {Mongolia Healthsites},
  author    = {Global Healthsites Mapping Project},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/mongolia-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.