Airport Codes

Airports, airfields, heliports and other aviation facilities from around the world, with their IATA codes (three letters, used in passenger reservation, ticketing and baggage handling), ICAO codes (four letters, used by air traffic control) and other identifiers, plus type, location and coordinates. The data comes from OurAirports.

Column definitions and types are in datapackage.json.

Data

• data/airport-codes.csv has one row per facility.
• archive/data.csv is an unchanged copy of the file downloaded from OurAirports, with all of its columns.
• data/type-counts.csv is a small table of counts by facility type, including Closed. It is rebuilt from airport-codes.csv each time the data is updated.

Columns of data/airport-codes.csv:

Known limitations

• Many rows have no iata_code or no icao_code, because many facilities have no such code. Do not use either column as a key.
• The file includes closed facilities (type is closed). Filter on type if you only want facilities that are in use.
• NA is a real value in two columns: continent (North America) and iso_country (Namibia). By default pandas reads NA as missing. Read the file as text and turn that off: pd.read_csv("data/airport-codes.csv", dtype=str, keep_default_na=False). Empty cells are then empty strings.
• coordinates is one text column, not two numbers. To split it: lat_lon = df["coordinates"].str.split(", ", expand=True).astype(float). The original latitude_deg and longitude_deg columns are only in archive/data.csv.

Data sources

• OurAirports (airports.csv): the list of airports, with all columns. OurAirports says it compiles its data from many sources, listed on its About page. Licence: public domain, as stated by OurAirports (see License).

Changes made to the source data: the file airports.csv is downloaded; latitude_deg and longitude_deg are combined into one coordinates column; the columns id, scheduled_service, home_link, wikipedia_link and keywords are removed. No rows are changed, added or removed.

Not endorsed by, or affiliated with, OurAirports.

Preparation

You need Python 3.12 or greater. To rebuild the data from the repository root:

# Install the requirements and run the script
pip install -r scripts/requirements.txt
python3 scripts/process.py

# Or use make
make
make clean

The script downloads airports.csv into archive/data.csv, then writes data/airport-codes.csv. It then counts the facilities by type to write data/type-counts.csv and to update the counts used by the chart in datapackage.json.

A GitHub workflow runs the script every night (at 00:00 UTC) and on every push to main, and commits archive/, data/ and datapackage.json if they changed.

The data is also published on datahub.io.

License

The data comes from OurAirports (https://ourairports.com/data/). OurAirports states: "All data is released to the Public Domain, and comes with no guarantee of accuracy or fitness for use." Credit is not required; OurAirports asks for it as a courtesy, and a credit line is in ATTRIBUTION.txt.

Two things are unclear. We did not find terms that answer either, so this package does not claim more than OurAirports' statement above:

• OurAirports' own sources (for example government airport lists and GeoNames). OurAirports names them but we found no statement from them about reuse.
• Any rights IATA or ICAO may hold in their code lists. The IATA code search page carries "All rights reserved" and we did not read IATA's or ICAO's terms.

The maintainers offer their own work (the selection and formatting of the data) under the Public Domain Dedication and License (PDDL).