electricsheepafrica/africa-ourairports-cog

Airports in Congo-Brazzaville

Publisher: OurAirports · Source: HDX · License: cc-by-igo · Updated: 2026-02-01

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Abstract

List of airports in Congo-Brazzaville, with latitude and longitude. Unverified community data from http://ourairports.com/countries/CG/

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-02-01. Geographic scope: COG.

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)	58
Columns	23 (7 numeric, 15 categorical, 0 datetime)
Train split	46 rows
Test split	11 rows
Geographic scope	COG
Publisher	OurAirports
HDX last updated	2026-02-01

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Variables

Geographic — type (small_airport, medium_airport, large_airport), latitude_deg (range -4.816–3.2789), longitude_deg (range 11.3089–18.5144), country_name (Republic of the Congo, #country +name), iso_country (CG, #country +code +iso2) and 4 others.

Temporal — last_updated.

Outcome / Measurement — score (range 0.0–1000.0).

Identifier / Metadata — id (range 2868.0–595634.0), ident (#meta +code, CG-0003, LKC), name (#loc +airport +name, Mokabi Airport, Lekana Airport), gps_code (#loc +airport +code +gps, FCMR, FCMY), icao_code and 3 others.

Other — elevation_ft (range 39.0–2756.0), 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-cog")
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	1.7%	2868.0 – 595634.0 (mean 75364.3509)
ident	object	0.0%	#meta +code, CG-0003, LKC
type	object	0.0%	small_airport, medium_airport, large_airport
name	object	0.0%	#loc +airport +name, Mokabi Airport, Lekana Airport
latitude_deg	float64	1.7%	-4.816 – 3.2789 (mean -2.1287)
longitude_deg	float64	1.7%	11.3089 – 18.5144 (mean 13.9512)
elevation_ft	float64	6.9%	39.0 – 2756.0 (mean 1231.0185)
continent	object	0.0%	AF, #region +continent +code
country_name	object	0.0%	Republic of the Congo, #country +name
iso_country	object	0.0%	CG, #country +code +iso2
region_name	object	0.0%	Niari Department, Cuvette Department, Likouala Department
iso_region	object	0.0%	CG-9, CG-8, CG-7
local_region	float64	1.7%	2.0 – 14.0 (mean 8.8947)
municipality	object	1.7%	#loc +municipality +name, Leganda, Loubetsi
scheduled_service	float64	1.7%	0.0 – 1.0 (mean 0.0351)
gps_code	object	13.8%	#loc +airport +code +gps, FCMR, FCMY
icao_code	object	58.6%
iata_code	object	55.2%
wikipedia_link	object	56.9%
score	float64	1.7%	0.0 – 1000.0 (mean 100.8772)
last_updated	datetime64[ns, UTC]	1.7%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
id	2868.0	595634.0	75364.3509	31096.0
latitude_deg	-4.816	3.2789	-2.1287	-2.867
longitude_deg	11.3089	18.5144	13.9512	13.533
elevation_ft	39.0	2756.0	1231.0185	1195.5
local_region	2.0	14.0	8.8947	9.0
scheduled_service	0.0	1.0	0.0351	0.0
score	0.0	1000.0	100.8772	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. 3 column(s) with >80% missing values were removed: local_code, home_link, keywords. 8 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: icao_code, iata_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_cog,
  title     = {Airports in Congo-Brazzaville},
  author    = {OurAirports},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/ourairports-cog},
  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.