That’s a good point, but percentage based wouldn’t show us how many flights airlines are willing to over commit to and then cancel.

That’s a good point. I see the cancellations did go up that year but it might also be that the BTS changed their collection methodology.

• Data Source: https://www.transtats.bts.gov/DL_SelectFields.aspx?gnoyr_VQ=FGK&QO_fu146_anzr=b0-gvzr
• Aggregated Dataset on Kaggle: https://www.kaggle.com/datasets/robikscube/flight-delay-dataset-20182022
• Created in python using the calmap package. https://pythonhosted.org/calmap/
• Code / Notebook used to create the plot: https://www.kaggle.com/code/robikscube/flight-delay-exploratory-data-analysis-twitch
• Video of the creation process: https://youtu.be/xs_L6z9QNYY

Last post was deleted, this version has a legend!

If you are interested in making your own plot or modifying this one (filtering to specific airlines, etc.) feel free to fork the notebook linked above.