We have all been stuck in airports longer than planned because of the inconvenience of flight delays. What if we could avoid this by using flight data?
The Department of Transportation (DOT) collects departure and arrival times for all US commercial flights. There are over 200 million rows of records spanning 28+ years, beginning in 1987. The raw data is described in detail in here . The goal of this exploratory visualization is to make sense of this massive amount of flight records by aggregating the flights into yearly and weekly averages. This has the double effect of: 1) shrinking our dataset, thus making it easier to map and visualize it, and 2) Loosing an amount of the detail that came with the raw data. This is a compromise that we must accept in order to view a more macroscopic view of the flight data. The chord diagram below represent the arrival and departure flights from the 100 airports with the most traffic in the US. The lines represent the flights, their color the delay in minutes, and their thickness the amount of flights for that path. Airports are represented by the blue arcs along the circumference of the chord, and their traffic represented by length of that arc. Selecting an airport highlights all the flights that come and go from that airport to the rest of the listed airports. Also, selecting year from the drop-down menu or clicking on a week of the calendar display only the flights of the selected date.For a bigger, full-featured version of this visualization head over to the project page. Can you find out when flights get delayed the most? How does Logan Airport perform during Christmas? Last year I took a Data Visualization class with Professor Remco Chang from the Department of Computer Science. This course taught me a great deal about Data Visualization, a field that has caught my attention ever since I started playing with the class’ first assignment. This visualization was crafted by Andrew, Maya and me, for the class’ final project.