electricsheepafrica/africa-ourairports-cod

Airports in the Democratic Republic of the Congo

Publisher: OurAirports · Source: HDX · License: cc-by-igo · Updated: 2026-01-26

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Abstract

List of airports in the Democratic Republic of the Congo, with latitude and longitude. Unverified community data from http://ourairports.com/countries/CD/

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-01-26. Geographic scope: COD.

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

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	First-level administrative unit observations
Rows (total)	306
Columns	22 (6 numeric, 15 categorical, 0 datetime)
Train split	244 rows
Test split	61 rows
Geographic scope	COD
Publisher	OurAirports
HDX last updated	2026-01-26

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Variables

Geographic — type (small_airport, closed, medium_airport), latitude_deg (range -11.5915–4.7172), longitude_deg (range 12.251–31.0262), country_name (Democratic Republic of the Congo, #country +name), iso_country (CD, #country +code +iso2) and 4 others.

Temporal — last_updated.

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

Identifier / Metadata — id (range 3040.0–525974.0), ident (#meta +code, FZAX, FZVI), name (Matari Airport, Lubondaie Airport, Luiza Airport), gps_code, icao_code and 2 others.

Other — elevation_ft (range 7.0–6562.0), 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-cod")
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	0.3%	3040.0 – 525974.0 (mean 74404.4525)
ident	object	0.0%	#meta +code, FZAX, FZVI
type	object	0.0%	small_airport, closed, medium_airport
name	object	0.0%	Matari Airport, Lubondaie Airport, Luiza Airport
latitude_deg	float64	0.3%	-11.5915 – 4.7172 (mean -3.1403)
longitude_deg	float64	0.3%	12.251 – 31.0262 (mean 22.5703)
elevation_ft	float64	8.5%	7.0 – 6562.0 (mean 2157.0179)
continent	object	0.0%	AF, #region +continent +code
country_name	object	0.0%	Democratic Republic of the Congo, #country +name
iso_country	object	0.0%	CD, #country +code +iso2
region_name	object	0.0%	Kwilu Province, Mai-Ndombe Province, Kongo-Central Province
iso_region	object	0.0%	CD-KL, CD-MN, CD-BC
local_region	object	0.0%	KL, MN, BC
municipality	object	0.7%	Kalima, Beni, Lubondaie
scheduled_service	float64	0.3%	0.0 – 1.0 (mean 0.0689)
gps_code	object	23.9%
icao_code	object	33.7%
wikipedia_link	object	37.9%
score	float64	0.3%	0.0 – 1050.0 (mean 97.541)
last_updated	datetime64[ns, UTC]	0.3%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
id	3040.0	525974.0	74404.4525	31419.0
latitude_deg	-11.5915	4.7172	-3.1403	-3.883
longitude_deg	12.251	31.0262	22.5703	22.5165
elevation_ft	7.0	6562.0	2157.0179	1820.5
scheduled_service	0.0	1.0	0.0689	0.0
score	0.0	1050.0	97.541	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. 4 column(s) with >80% missing values were removed: iata_code, local_code, home_link, keywords. 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: gps_code, icao_code, wikipedia_link.
• 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_cod,
  title     = {Airports in the Democratic Republic of the Congo},
  author    = {OurAirports},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/ourairports-cod},
  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.