Calculate the nearest airport of each zipcode using Python.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

Nearest Airport

Calculate the nearest airport of each zipcode using Python. Based on Haversine formula

Keywords: Python, Pandas, Geographical Data, Geography


Nearest Airport

Business Use Case

  1. Sales Territory Planning
  • Determine if any targeted location can easily be accessed.


  1. World Airports - Source:
  2. Zipcodes - Source: AggData.con


  1. CSV file per state/region, which contains the following:
  • All zipcodes
  • Nearest airport (code, lat and long) of each zipcode


  1. Nearest distance is based on Haversine formula
  2. Check out my logs for more

Sample Data: 90210, California

Out of 558 airports in California, what's the nearest airport to Beverly Hills, LA?

zipcode country state state_full county latitude-zip longitude-zip
90210 US CA California Los Angeles 34.0901 -118.4065

Based on the script, the nearest airport to 90210 is: KSMO is Santa Monica Municipal Airport

nearest-airport latitude-air longitude-air distance (km)
KSMO 34.01580048 -118.4509964 9.222835746

Let's validate the model by plotting in Google Maps:

Nearest Airport

  • The black line indicates the distance of 9.20 km from 90210 to the airport, which is close to 9.22km!

  • Note that the formula doesn't consider the actual roads in the location. Haversine simply calculates the distance from point A to point B.

Now, here's the second nearest airport: Bob Hope Airport (KBUR)

nearest-airport latitude-air longitude-air distance (km)
KBUR 34.20069885 -118.3590012 13.05176636

Nearest Airport

  • Distance based on Haversine: 13.05 km
  • Distance based on Google Maps 13.03 km

Possible Enhancements

  1. Add Part 2: travelability scores through Pandas binning