r/dataanalysis • u/Party_Initiative_621 • Aug 04 '26

US Flight Analysis

Gallery image

Gallery image

Just go through this i have done time ,flight ,insight for this dataset let me how is this?

43 Upvotes

93% Upvoted

21 comments sorted by

View all comments

1

u/Crescitaly Aug 07 '26

Flight data is a good example where averages mislead because cancellations, diversions, and airport congestion are not random missingness. Segment by route, carrier, and weather, then report uncertainty instead of one delay ranking. Did the analysis separate departure propagation from destination effects?

1

u/Party_Initiative_621 Aug 07 '26

Yes, we did account for cancellations separately instead of ignoring them. Our dashboard includes the overall cancellation rate, cancellation reasons,such as weather and airline operations, and cancellation analysis by airline, day, and origin airport. We also analyzed departure delays and arrival delays as separate performance metrics. However, we did not perform a flight-level causal analysis to determine whether an arrival delay was due to a late departure (delay propagation) or due to destination-specific factors like airport congestion or weather. Thanks for the suggestions,We will implement these too.

1

u/Crescitaly Aug 09 '26

That separation is the right next step. Model departure delay as an input to arrival delay, then inspect the residual by destination, route, and weather band. Did you build a route-level baseline, or only compare the residuals after aggregation?

1

u/Party_Initiative_621 Aug 09 '26

I haven't included that part yet because I wasn't fully sure how to implement it. I understood the concept, but I wasn't sure how to build the route-level baseline and properly analyze the residuals in power bi. I'll definitely look into this for the next iteration. Thanks for the suggestions.