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africa-aviation-burkina-faso

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metadata 
annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - en
license: other
multilinguality:
  - monolingual
size_categories:
  - n<1K
source_datasets:
  - original
task_categories:
  - other
task_ids: []
tags:
  - africa
  - humanitarian
  - hdx
  - electric-sheep-africa
  - aviation
  - facilities-infrastructure
  - geodata
  - hxl
  - transportation
  - bfa
pretty_name: Airports in Burkina Faso
dataset_info:
  splits:
    - name: train
      num_examples: 41
    - name: test
      num_examples: 10

Airports in Burkina Faso

Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-04-15

Abstract

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

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-04-15. Geographic scope: BFA.

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

Dataset Characteristics

Domain Humanitarian and development data
Unit of observation First-level administrative unit observations
Rows (total) 52
Columns 23 (6 numeric, 16 categorical, 0 datetime)
Train split 41 rows
Test split 10 rows
Geographic scope BFA
Publisher OurAirports
HDX last updated 2026-04-15

Variables

Geographic — type (small_airport, large_airport, closed), latitude_deg (range 9.883–14.7909), longitude_deg (range -5.35–1.7846), country_name (Burkina Faso, #country +name), iso_country (BF, #country +code +iso2) and 4 others.

Temporal — last_updated.

Outcome / Measurement — score (range 50.0–1000.0).

Identifier / Metadata — id (range 2088.0–597081.0), ident (#meta +code, DFFD, DFCK), name (#loc +airport +name, Ouagadougou Thomas Sankara International Airport, Koudougou Airport), gps_code, icao_code and 3 others.

Other — elevation_ft (range 699.0–1706.0), continent (AF, #region +continent +code), scheduled_service (range 0.0–1.0), wikipedia_link.

Quick Start 

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-aviation-burkina-faso")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Column Type Null % Range / Sample Values
id float64 1.9% 2088.0 – 597081.0 (mean 46965.8431)
ident object 0.0% #meta +code, DFFD, DFCK
type object 0.0% small_airport, large_airport, closed
name object 0.0% #loc +airport +name, Ouagadougou Thomas Sankara International Airport, Koudougou Airport
latitude_deg float64 1.9% 9.883 – 14.7909 (mean 12.2922)
longitude_deg float64 1.9% -5.35 – 1.7846 (mean -1.688)
elevation_ft float64 1.9% 699.0 – 1706.0 (mean 1007.1176)
continent object 0.0% AF, #region +continent +code
country_name object 0.0% Burkina Faso, #country +name
iso_country object 0.0% BF, #country +code +iso2
region_name object 0.0% Oudalan Province, Tapoa Province, Comoe Province
iso_region object 0.0% BF-OUD, BF-TAP, BF-COM
local_region object 0.0% OUD, TAP, COM
municipality object 0.0% #loc +municipality +name, Ouagadougou, Koudougou
scheduled_service float64 1.9% 0.0 – 1.0 (mean 0.0392)
gps_code object 3.8%
icao_code object 28.8%
iata_code object 46.2%
wikipedia_link object 26.9%
score float64 1.9% 50.0 – 1000.0 (mean 87.2549)
last_updated datetime64[ns, UTC] 1.9%
esa_source object 0.0%
esa_processed object 0.0%

Numeric Summary

Column Min Max Mean Median
id 2088.0 597081.0 46965.8431 30908.0
latitude_deg 9.883 14.7909 12.2922 12.2
longitude_deg -5.35 1.7846 -1.688 -1.6247
elevation_ft 699.0 1706.0 1007.1176 984.0
scheduled_service 0.0 1.0 0.0392 0.0
score 50.0 1000.0 87.2549 50.0

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. 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.

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.

Citation 

@dataset{hdx_africa_aviation_burkina_faso,
  title     = {Airports in Burkina Faso},
  author    = {OurAirports},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/ourairports-bfa},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.