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airport-compass

Visualizing airport's traffic on a compass

https://github.com/lucianosrp/airport-compass

Science Score: 57.0%

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    Found 1 DOI reference(s) in README
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    Low similarity (3.8%) to scientific vocabulary

Keywords

aviation data python
Last synced: 6 months ago · JSON representation ·

Repository

Visualizing airport's traffic on a compass

Basic Info
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  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
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Topics
aviation data python
Created almost 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License Citation

README.md

The Airport Compass

Cover

Inspiration

3 years ago I got inspired by a very interesting figure published on a paper by @gboeing called Urban spatial order: street network orientation, configuration, and entropy

Figure

This figure represents the distribution of the orientation of every major street of a city.

I like how it gives a quick representation of each city's layout and how evident are the various levels of entropy.

Shortly after seeing this chart I immediately thought of replicating this view but for airports' traffic worldwide.

Sources

This repository is using two major open-source datasets:

  • The airlines routes data comes from @jpatokal's OpenFlights repository

  • The airports data is from @davidmegginson's OurAirports repository

Dependencies

All dependencies are listed on requirements.txt

Owner

  • Login: lucianosrp
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: "Scarpulla"
    given-names: "Luciano"
title: "Airport Compass"
date-released: 2024-02-24
url: "https://github.com/lucianosrp/airport-compass"

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Dependencies

requirements.txt pypi
  • certifi ==2024.2.2
  • contourpy ==1.2.0
  • cycler ==0.12.1
  • fonttools ==4.49.0
  • kiwisolver ==1.4.5
  • matplotlib ==3.8.3
  • numpy ==1.26.4
  • packaging ==23.2
  • pandas ==2.2.0
  • pillow ==10.2.0
  • pyarrow ==15.0.0
  • pyparsing ==3.1.1
  • pyproj ==3.6.1
  • pyshp ==2.3.1
  • python-dateutil ==2.8.2
  • pytz ==2024.1
  • shapely ==2.0.3
  • six ==1.16.0
  • tzdata ==2024.1