electricsheepafrica/africa-ourairports-lby

Airports in Libya

Publisher: OurAirports · Source: HDX · License: cc-by-igo · Updated: 2026-03-30

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Abstract

List of airports in Libya, with latitude and longitude. Unverified community data from http://ourairports.com/countries/LY/

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-30. Geographic scope: LBY.

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

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Dataset Characteristics

Domain	Natural hazards and disaster risk
Unit of observation	First-level administrative unit observations
Rows (total)	82
Columns	25 (6 numeric, 18 categorical, 0 datetime)
Train split	65 rows
Test split	16 rows
Geographic scope	LBY
Publisher	OurAirports
HDX last updated	2026-03-30

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Variables

Geographic — type (small_airport, medium_airport, closed), latitude_deg (range 21.6877–32.9523), longitude_deg (range 9.7021–24.6061), country_name (Libya, #country +name), iso_country (LY, #country +code +iso2) and 5 others.

Temporal — last_updated.

Outcome / Measurement — score (range 0.0–1050.0).

Identifier / Metadata — id (range 3218.0–602664.0), ident (#meta +code, LY-0011, HLRA), name (#loc +airport +name, Jofra Oilfield Airport, Dahra Airport), gps_code, icao_code and 4 others.

Other — elevation_ft (range -120.0–2674.0), continent (AF, #region +continent +code), scheduled_service (range 0.0–1.0), wikipedia_link.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-ourairports-lby")
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
id	float64	1.2%	3218.0 – 602664.0 (mean 149492.2346)
ident	object	0.0%	#meta +code, LY-0011, HLRA
type	object	0.0%	small_airport, medium_airport, closed
name	object	0.0%	#loc +airport +name, Jofra Oilfield Airport, Dahra Airport
latitude_deg	float64	1.2%	21.6877 – 32.9523 (mean 29.5833)
longitude_deg	float64	1.2%	9.7021 – 24.6061 (mean 17.6512)
elevation_ft	float64	13.4%	-120.0 – 2674.0 (mean 734.4366)
continent	object	0.0%	AF, #region +continent +code
country_name	object	0.0%	Libya, #country +name
iso_country	object	0.0%	LY, #country +code +iso2
region_name	object	0.0%	Al Wahat District, Surt District, Al Jufrah District
iso_region	object	0.0%	LY-WA, LY-SR, LY-JU
local_region	object	0.0%	WA, SR, JU
municipality	object	32.9%	Zillah, Ras Lanuf, Tripoli
scheduled_service	float64	1.2%	0.0 – 1.0 (mean 0.1111)
gps_code	object	25.6%
icao_code	object	76.8%
iata_code	object	76.8%
local_code	object	72.0%
wikipedia_link	object	68.3%
keywords	object	68.3%
score	float64	1.2%	0.0 – 1050.0 (mean 155.5556)
last_updated	datetime64[ns, UTC]	1.2%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
id	3218.0	602664.0	149492.2346	4609.0
latitude_deg	21.6877	32.9523	29.5833	29.5424
longitude_deg	9.7021	24.6061	17.6512	18.3208
elevation_ft	-120.0	2674.0	734.4366	488.0
scheduled_service	0.0	1.0	0.1111	0.0
score	0.0	1050.0	155.5556	50.0

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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. 1 column(s) with >80% missing values were removed: home_link. 7 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 OurAirports 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: municipality, gps_code, icao_code, iata_code, local_code, wikipedia_link, keywords.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_ourairports_lby,
  title     = {Airports in Libya},
  author    = {OurAirports},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/ourairports-lby},
  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.