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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.

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Dataset Card

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

DomainHumanitarian and development data
Unit of observationFirst-level administrative unit observations
Rows (total)25
Columns23 (6 numeric, 16 categorical, 0 datetime)
Train split20 rows
Test split5 rows
Geographic scopeJOR
PublisherOurAirports
HDX last updated2026-01-24

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

python
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

ColumnTypeNull %Range / Sample Values
idfloat644.0%3353.0 – 538908.0 (mean 133704.375)
identobject0.0%#meta +code, OJAI, OJAQ
typeobject0.0%smallairport, heliport, largeairport
nameobject0.0%#loc +airport +name, Queen Alia International Airport, King Hussein International Airport
latitude_degfloat644.0%29.5405 – 32.7307 (mean 31.3221)
longitude_degfloat644.0%34.985 – 38.9783 (mean 36.2207)
elevation_ftfloat6436.0%-1207.0 – 2939.0 (mean 1657.3125)
continentobject0.0%AS, #region +continent +code
country_nameobject0.0%Jordan, #country +name
iso_countryobject0.0%JO, #country +code +iso2
region_nameobject0.0%Amman Governorate, Al 'Aqaba Governorate, Az Zarga Governorate
iso_regionobject0.0%JO-AM, JO-AQ, JO-AZ
local_regionobject0.0%AM, AQ, AZ
municipalityobject40.0%Amman, Aqaba, #loc +municipality +name
scheduled_servicefloat644.0%0.0 – 1.0 (mean 0.125)
gps_codeobject56.0%
icao_codeobject60.0%
iata_codeobject80.0%
wikipedia_linkobject56.0%
scorefloat644.0%0.0 – 1475.0 (mean 193.75)
last_updateddatetime64[ns, UTC]4.0%
esa_sourceobject0.0%
esa_processedobject0.0%

Numeric Summary

ColumnMinMaxMeanMedian
id3353.0538908.0133704.37544987.5
latitude_deg29.540532.730731.322131.7793
longitude_deg34.98538.978336.220736.1462
elevation_ft-1207.02939.01657.31252245.0
scheduled_service0.01.00.1250.0
score0.01475.0193.7550.0

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

bibtex
@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.