For this project, I used a handy tool called the Pandas library in Python. It helped me manage and play around with the passenger satisfaction data. I could easily organize and filter the data to find out interesting stuff, like what made passengers happy or if certain factors influenced their satisfaction. With Pandas, I felt like I had a secret code to understand the data better. It made the whole project a lot simpler and enjoyable!
For more : Medium Article
I used Python to answer these questions :
I'm planning to use data visualization libraries to visualize the results I have
Two key datasets for this case study
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airline_passenger_satisfaction.csv: Customer satisfaction scores from 120,000+ airline passengers, including additional information about each passenger, their flight, and type of travel, as well as ther evaluation of different factors like cleanliness, comfort, service, and overall experience.
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data_dictionary.csv: A dictionnary explaining the data in each column.
- Younes AGEGAL
Email : contact@datawithyounes.tech