Flight Departure Analysis

As I sit here in Pisa Airport after a wonderful break away with the family, I look in despair as my departure time gets more and more delayed.

Looking at the full page of departures for today, I notice many departed late. I also noticed they got later as the day progressed. It raises that question oft noted that every delay has a further knock-in effect for subsequent flights in the day.

Let's test that hypothesis!

I loaded the departure data directly from the Pisa departures page here: https://www.pisa-airport.com/en/the-passengers/departures/real-time-flight-information.html

Using the Web.Contents connector in Power BI, I did a little transformation and created one table with all flights, their planned and actual departure times and the difference in minutes.

With a simple column chart and a trend line, you can see the lateness increasing as the day moves on. Does that prove that myth or bust it? Well one day at one airport isn't enough to confirm, but I'm going to feel a little more confident saying it from now on.

Another take away is that there was too many flights planned around 16:00-18:00 (I've shown these via a red line), and the airport was not able to handle it - nowhere to sit, massive queues for food drinks so the frustrations kick in a little.

Normally I share my code, but in my haste I hard-coded and hacked it so badly it's not quality enough to share. If you really really want it, I'll share it though - so just let me know.