Last week a friend asked on Twitter how to extract some data from Airline On-Time Performance Reports in a Tableau public dashboard. I replied back with some tricks using Tabula, when the raw data or a workbook aren't provided, and turned in.
While the data was interesting, it lacked location reference, thus eliminating the possibility of representing it on a map, not to mention further geospatial analysis. But the idea of visualizing it lived on.
Getting the data
Friday night, destroyed after a hard week. I got home, had some dinner, and started poking at FlightStats Developer Center. I grabbed a RedBull to stay awake, and wrote a script to get the rating for every route in a dataset from OpenFlights.org.
I validated the visualization with a sample of flights departing from Barcelona, with a very simple line visualization: a color ramp corresponding to a 5 star scale (red for 1, green for 5).
Several hours, a couple of
"Authorization failed. usage limits are exceeded", and different API keys later I had the data.
Explore and analyze
Fast forward to this week. We've been working on some new and shiny stuff at CartoDB that has just been presented at MWC — CartoDB for Deep Insights. I had the data ready, so I uploaded it to CartoDB, and created my first Deep Insights dashboard within a couple of minutes. BOOM.
A quick look at the visualization and I can start uncovering stories.
We're continuously working to improve this, so any feedback is welcomed. Go ahead and play with the data. I'm not sure it can be published but ¯\_(ツ)_/¯
You can check the code in GitHub.
Disclaimer: I'm not a Data Scientist, just some guy who knows how to put together a script in Ruby and happens to work at CartoDB. I really, really, really got inspired by this post to share the visualization. I usually tinker a lot but never end up sharing anything because I'm too critical with the results, so please be kind.