# eyana-m/py_airports

Calculate the nearest airport of each zipcode using Python.
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# Nearest Airport

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

Keywords: Python, Pandas, Geographical Data, Geography

## Overview

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

## Inputs

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

## Output

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

## Notes

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:

• 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

• 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