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electricsheepasia/asia-aviation-ourairports-kazakhstan

Airports in Kazakhstan Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-04-09 Abstract List of airports in Kazakhstan, with latitude and longitude. Unverified community data from http://ourairports.com/countries/KZ/ Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-04-09. Geographic scope: KAZ. 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-kazakhstan.

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Dataset Card

Airports in Kazakhstan

Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-04-09


Abstract

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

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-04-09. Geographic scope: KAZ.

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)216
Columns21 (6 numeric, 14 categorical, 0 datetime)
Train split172 rows
Test split43 rows
Geographic scopeKAZ
PublisherOurAirports
HDX last updated2026-04-09

Variables

Geographic — type (smallairport, heliport, closed), `latitudedeg (range 40.7091–54.9702), longitudedeg` (range 50.2441–84.8877), `countryname (Kazakhstan, #country +name), iso_country` (KZ, #country +code +iso2) and 5 others.

Temporal — last_updated.

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

Identifier / Metadata — id (range 3964.0–607057.0), ident (#meta +code, UAAA, UACC), name (Novotroitskoye Airport, Almaty International Airport, #loc +airport +name), gps_code, esa_source and 1 others.

Other — elevation_ft (range -88.0–6322.0), continent (AS, #region +continent +code), scheduled_service (range 0.0–1.0).


Quick Start

python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-aviation-ourairports-kazakhstan")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

ColumnTypeNull %Range / Sample Values
idfloat640.5%3964.0 – 607057.0 (mean 239280.3349)
identobject0.0%#meta +code, UAAA, UACC
typeobject0.0%small_airport, heliport, closed
nameobject0.0%Novotroitskoye Airport, Almaty International Airport, #loc +airport +name
latitude_degfloat640.5%40.7091 – 54.9702 (mean 46.2239)
longitude_degfloat640.5%50.2441 – 84.8877 (mean 70.5135)
elevation_ftfloat649.3%-88.0 – 6322.0 (mean 1398.648)
continentobject0.0%AS, #region +continent +code
country_nameobject0.0%Kazakhstan, #country +name
iso_countryobject0.0%KZ, #country +code +iso2
region_nameobject0.0%Turkistan Region, Almaty Region, Mangystau Region
iso_regionobject0.0%KZ-YUZ, KZ-ALM, KZ-MAN
local_regionobject0.0%YUZ, ALM, MAN
municipalityobject1.4%Almaty, Astana, Aktau
scheduled_servicefloat640.5%0.0 – 1.0 (mean 0.1116)
gps_codeobject71.8%
keywordsobject67.1%
scorefloat640.5%0.0 – 1275.0 (mean 132.3256)
last_updateddatetime64[ns, UTC]0.5%
esa_sourceobject0.0%
esa_processedobject0.0%

Numeric Summary

ColumnMinMaxMeanMedian
id3964.0607057.0239280.3349317106.0
latitude_deg40.709154.970246.223945.4236
longitude_deg50.244184.887770.513571.4238
elevation_ft-88.06322.01398.6481197.5
scheduled_service0.01.00.11160.0
score0.01275.0132.325650.0

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`. 5 column(s) with >80% missing values were removed: `icaocode, iatacode`, `localcode, homelink`, `wikipedialink`. 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: gps_code, keywords.
  • —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

bibtex
@dataset{hdx_asia_aviation_ourairports_kazakhstan,
  title     = {Airports in Kazakhstan},
  author    = {OurAirports},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/ourairports-kaz},
  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.