electricsheepasia/asia-aviation-ourairports-jordan
Airports in Jordan Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-01-24 Abstract List of airports in Jordan, with latitude and longitude. Unverified community data from http://ourairports.com/countries/JO/ Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-01-24. Geographic scope: JOR. Curated into ML-ready Parquet format by Electric Sheep Africa.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-aviation-ourairports-jordan.
Airports in Jordan
Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-01-24
Abstract
List of airports in Jordan, with latitude and longitude. Unverified community data from http://ourairports.com/countries/JO/
Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-01-24. Geographic scope: JOR.
Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).
Dataset Characteristics
Variables
Geographic — type (smallairport, heliport, largeairport), latitude_deg (range 29.5405–32.7307), longitude_deg (range 34.985–38.9783), country_name (Jordan, #country +name), iso_country (JO, #country +code +iso2) and 4 others.
Temporal — last_updated.
Outcome / Measurement — score (range 0.0–1475.0).
Identifier / Metadata — id (range 3353.0–538908.0), ident (#meta +code, OJAI, OJAQ), name (#loc +airport +name, Queen Alia International Airport, King Hussein International Airport), gps_code, icao_code and 3 others.
Other — elevation_ft (range -1207.0–2939.0), continent (AS, #region +continent +code), scheduled_service (range 0.0–1.0), wikipedia_link.
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/asia-aviation-ourairports-jordan")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()Schema
Numeric Summary
Curation
Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snakecase. 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: `localcode, 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:
elevation_ft,municipality,gps_code,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_asia_aviation_ourairports_jordan,
title = {Airports in Jordan},
author = {OurAirports},
year = {2026},
url = {https://data.humdata.org/dataset/ourairports-jor},
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.
