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Team Airtraffic is creating insightful visualizations of air traffic from / to Zurich Airport and predicting delays

Have a look at our project-results here: https://openzh.github.io/twist_airtraffic/

So far, we have: - conducted exploratory data analysis and produced many descriptive visualizations to get to know the data and get a first understanding of which aspects of it might be relevant and interesting - experimented with a broad variety of modelling approaches (linear approaches, binary logistic regressions, ridge regression...) to predict delays.

Next steps :

  1. Try further prediction-approaches (bayesian, random forest e.g.)
  2. Create some further insightful visualizations
  3. Discuss what the model could be used for (flight delay prediction app? )

Flight data for ML-prediction challenge at the TWIST2018-Hackdays

This repository contains data of planed and effective flight arrival and departure-times from / to the airport of Zurich for the entire year 2017.

The R-Script data_enrichment.R contains the code used to add the airport coordinates, calculate approximative flight-distances, time-differences between scheduled and effective flight-times as well as information on weather-conditions around the airport provided by meteoswiss. The dataset does not yet contain information on general weather and atmospheric conditions other than those at the local scale.

The RDS-file twist_zrh.RDS contains the resulting R-dataframe. For those relying on other tools than r, a csv-version of the dataset is also available: twist_zrh.csv

metadata.txt contains a detailed description of the variables contained in the file.

Further sources for weather data at global scale or atmospheric conditions:

The most important rule of TWIST 2018 is:

Be Excellent to each other.


As this is an open source event, we will encourage all teams to publish their work under open licenses in open repositories, such as but not restricted to GitHub. The organizers, sponsors, and event staff shall not claim or request any endorsement or special rights and privileges to any work you do at the event. All project documentation created or shared during the event for projects published as above will be republished and promoted under a Creative Commons license as detailed below.


Creative Commons LicenceThe contents of this website, unless otherwise stated, are licensed under a Creative Commons Attribution 4.0 International License.

Latest update: 2018-08-29
Maintainer: thomas_lo_russo

Launched at TWIST 2018 by