How to find Airline Data for your Data Science project?

Introduction

Airport Data

Operational Data

  • Many of the columns are computed fields. Before trying to compute any number, please check if the number if already present in one of the columns (delay minutes, departure delay minutes, etc.). Many data warehouses charge you by columns you query. So my recommendation is to load all columns or columns until first diversion (skip all columns starting after div2).
  • For departure and arrival times there are both planned and actual times. Columns for planned times begin with “CRS”
  • Air_Time column is time spent in the air. Taxi_Out column is time spent going from gate to runway at origin. Taxi_in column is time spent going from runway to gate at destination. Actual_Elapsed_Time column is sum of air time and taxi times.
  • We have to careful about flights that have been diverted. For most projects it is better to filter them out using Diverted column
  • Only the Tail number of aircraft is recorded — this is unique number given to individual aircraft when it is registered. If we need information about the aircraft type this number can be cross-referenced with aircraft data in the next section.

Aircraft Data

Photo by Lukas Blazek on Unsplash

Working with Data

Project Ideas

EDA

Visualization

Machine Learning

Conclusion

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Data Science | Machine Learning | Operations Research https://www.linkedin.com/in/ramgit/

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Ram Thiruveedhi

Ram Thiruveedhi

Data Science | Machine Learning | Operations Research https://www.linkedin.com/in/ramgit/

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