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Our project objectiveimage Our goal is to analyze a data from January 2018 to December 2018 and extract a meaningful information (how to improve airline customer services) from this data. For this project, we analyzed over 33 different airlines from our data. We then set out to answer the follow questions: How does customer satisfaction distributions look like? How does the average waiting minutes affect customer satisfaction? How does a flight’s cleanliness, safety and boarding area affect customer satisfaction.

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LIBRARIES USED FOR THIS PROJECTimage

NUMPY PANDAS MATPLOTLIB MISSINGNO SEABORN image

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AIRLINES data analysis with python

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