Check the setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
Community airport, runway, and navaid records for building aviation directories and map layers from a nightly public-domain CSV.
From source to product signal
OurAirports publishes a nightly airports.csv covering worldwide aerodromes. Start with large airports in one country. Community coordinates and names can be incomplete, and the file is not an official aeronautical chart.
Install the packages, then run the notebook cell.
python -m pip install pandas
import pandas as pd
airports = pd.read_csv(
"https://davidmegginson.github.io/ourairports-data/airports.csv"
)
us_large = airports[
(airports["iso_country"] == "US")
& (airports["type"] == "large_airport")
]
print(
us_large[
["ident", "name", "municipality", "latitude_deg", "longitude_deg"]
].head()
)Test a useful signal
Test whether OurAirports can power a bounded aviation directory layer.
OurAirports is a community source. Last verified 2026-08-18. Temporal coverage: continuously updated community airport records.