Flying Free: data analysis with Python for aeronautical planning

Before an aircraft takes off, it is necessary to take into account an immense amount of variables: weather conditions, distance, take-off weight, fuel required, passengers, cargo… And so on. Using this data to plan the individual flight and ensuring a safe trip is part of a Flight Dispatcher’s daily duty. To top that, there is a high chance that the flight has several last-minute changes, which increases its difficulty widely. The most common issue is that the prediction of passengers increases significantly minutes before the flight finally takes off. This means more weight and more fuel to lift the plane: a single error and the passengers and cargo will be left on the ground, with all costs and damages involved. Nowadays it is a manual job, even though there are a lot of areas that can be calculated automatically, but with the expansion of data analysis technologies, this matter can be improved greatly.

This talk aims to display which tools are currently used in this area, for which purpose, and how said new technologies can make a Flight Dispatcher’s life a lot easier and efficient. A proposal will also be presented to make this a reality with Python. This will work as an application that can process all the data involved of the last couple of months and estimate the number of passengers, taking into account the date, time and destination of that exact flight. The main achievement of this presentation is to show how the daily flight operations work and make it accessible for everyone interested in a fascinating sector that is still growing.