Calculate the nearest airport of each zipcode using Python. Based on Haversine formula
Keywords: Python, Pandas, Geographical Data, Geography
- Sales Territory Planning
- Determine if any targeted location can easily be accessed.
- World Airports - Source: Ourairports.com
- Zipcodes - Source: AggData.con
- CSV file per state/region, which contains the following:
- All zipcodes
- Nearest airport (code, lat and long) of each zipcode
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:
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The black line indicates the distance of 9.20 km from 90210 to the airport, which is close to 9.22km!
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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
- Add Part 2: travelability scores through Pandas binning