Transport Reference tableQC clean AI-training-safe

Global Airport Registry

Every airport, heliport and seaplane base on Earth in one clean reference table - enriched, not just a code list. OurAirports publishes the community-maintained global aviation registry (public domain) as three separate CSVs (airports, runways, radio frequencies); we join them into one fat row per airport: identity (ICAO/IATA/GPS/local codes), type and service level, location (country, region, municipality, lat/lon, elevation), PLUS a runway summary (count, longest runway in feet, number of hard-surface runways) and the count of published comm frequencies. The universal join key for any flight, route or logistics dataset - keyed by the airport ident. Public domain, no attribution required.

72K
rows
18
columns
8.1 MB
download
Source
OurAirports
Licence
Redistributable open data
Quality
QC clean · 0 failures
Format
Apache Parquet + dictionary

Safe to train on

Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.

What's included

  • One fat row per airport worldwide - identity, location, service level, runways & comms
  • ICAO/IATA/GPS/local codes; type (large/medium/small/heliport/seaplane); scheduled-service flag
  • Runway summary joined in: count, longest runway (ft), hard-surface runway count
  • Count of published radio/comm frequencies per airport
  • The universal join key for any flight, route or logistics dataset (by ident/ICAO/IATA)
  • Public domain (OurAirports) - free commercial reuse & resale, no attribution required
  • Source: OurAirports (ourairports.com) - public-domain aviation data

Schema

ColumnTypeDescriptionFilledDistinct
ident str Airport identifier - ICAO where assigned (primary key) 100.0% 72,385
type str Airport type (large_airport, medium_airport, small_airport, heliport, …) 100.0% 6
name str Airport name 100.0% 69,073
continent str Continent code 57.7% 6
iso_country str ISO 3166-1 alpha-2 country code 99.6% 246
iso_region str ISO 3166-2 region code 100.0% 2,938
municipality str Served municipality / city 94.3% 34,440
scheduled_service str 'yes' if the airport has scheduled airline service 100.0% 2
gps_code str GPS / ICAO code 61.3% 44,353
iata_code str IATA code (where assigned) 12.5% 9,058
local_code str Local / national code 49.7% 34,474
latitude_deg float Latitude (decimal degrees) 100.0% 71,588
longitude_deg float Longitude (decimal degrees) 100.0% 71,747
elevation_ft float Elevation above sea level (feet) 83.4% 6,167
runway_count int Number of runways at the airport 100.0% 12
longest_runway_ft int Longest runway length (feet) 100.0% 5,167
hard_surface_runways int Number of hard-surface (asphalt/concrete) runways 100.0% 12
comm_frequencies int Number of published communication frequencies 100.0% 22

Sample & preview

Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: OurAirports (redistributable open data; attribution passes through - see our Licence).

Don't trust screenshots - drop the sample into your notebook right now.

import pandas as pd
df = pd.read_parquet("global-airport-registry_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join
⬇ Download free Parquet sample or CSV for Excel

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