electricsheepafrica/africa-aviation-tunisia

Airports in Tunisia

Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-01-10

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Abstract

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

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-01-10. Geographic scope: TUN.

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)	26
Columns	24 (7 numeric, 16 categorical, 0 datetime)
Train split	20 rows
Test split	5 rows
Geographic scope	TUN
Publisher	OurAirports
HDX last updated	2026-01-10

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Variables

Geographic — type (heliport, medium_airport, large_airport), latitude_deg (range 31.7043–37.3554), longitude_deg (range 8.1106–11.4621), country_name (Tunisia, #country +name), iso_country (TN, #country +code +iso2) and 5 others.

Temporal — last_updated.

Outcome / Measurement — score (range 0.0–1275.0).

Identifier / Metadata — id (range 2131.0–429791.0), ident (#meta +code, DTTA, TN-0010), name (#loc +airport +name, Tunis Carthage International Airport, A1 Turki Heliport), gps_code (#loc +airport +code +gps, DTTA, DTMB), icao_code and 3 others.

Other — elevation_ft (range 3.0–1060.0), 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-aviation-tunisia")
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	3.8%	2131.0 – 429791.0 (mean 148314.92)
ident	object	0.0%	#meta +code, DTTA, TN-0010
type	object	0.0%	heliport, medium_airport, large_airport
name	object	0.0%	#loc +airport +name, Tunis Carthage International Airport, A1 Turki Heliport
latitude_deg	float64	3.8%	31.7043 – 37.3554 (mean 35.0607)
longitude_deg	float64	3.8%	8.1106 – 11.4621 (mean 10.1237)
elevation_ft	float64	15.4%	3.0 – 1060.0 (mean 269.2273)
continent	object	0.0%	AF, #region +continent +code
country_name	object	0.0%	Tunisia, #country +name
iso_country	object	0.0%	TN, #country +code +iso2
region_name	object	0.0%	Medenine Governorate, Bizerte Governorate, Gabès Governorate
iso_region	object	0.0%	TN-82, TN-23, TN-81
local_region	float64	3.8%	11.0 – 83.0 (mean 53.52)
municipality	object	0.0%	#loc +municipality +name, Tunis, Turki
scheduled_service	float64	3.8%	0.0 – 1.0 (mean 0.36)
gps_code	object	42.3%	#loc +airport +code +gps, DTTA, DTMB
icao_code	object	46.2%
iata_code	object	57.7%
wikipedia_link	object	46.2%
keywords	object	76.9%
score	float64	3.8%	0.0 – 1275.0 (mean 326.0)
last_updated	datetime64[ns, UTC]	3.8%
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
id	2131.0	429791.0	148314.92	6401.0
latitude_deg	31.7043	37.3554	35.0607	34.718
longitude_deg	8.1106	11.4621	10.1237	10.3142
elevation_ft	3.0	1060.0	269.2273	179.5
local_region	11.0	83.0	53.52	61.0
scheduled_service	0.0	1.0	0.36	0.0
score	0.0	1275.0	326.0	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. 2 column(s) with >80% missing values were removed: local_code, home_link. 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: gps_code, icao_code, iata_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_aviation_tunisia,
  title     = {Airports in Tunisia},
  author    = {OurAirports},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/ourairports-tun},
  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.