--- 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](https://data.humdata.org/dataset/ourairports-bfa) · **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](https://huggingface.co/electricsheepafrica).* --- ## 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 ```python 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](https://data.humdata.org/dataset/ourairports-bfa) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @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](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*