In this project, you’ll imagine that you work for a travel agency and need to know the ins and outs of airline prices for your clients. You want to make sure that you can find the best deal for your client and help them to understand how airline prices change based on different factors.
You decide to look into your favorite airline. The data include:
- miles: miles traveled through the flight
- passengers: number of passengers on the flight
- delay: take-off delay in minutes
- inflight_meal: is there a meal included in the flight?
- inflight_entertainment: are there free entertainment systems for each seat?
- inflight_wifi: is there complimentary wifi on the flight?
- day_of_week: day of the week of the flight
- weekend: did this flight take place on a weekend
- coach_price: the average price paid for a coach ticket
- firstclass_price: the average price paid for first-class seats
- hours: how many hours the flight took
- redeye: was this flight a redeye (overnight)?
In this project, you’ll explore a dataset for the first time and get to know each of these features. Keep in mind that there’s no one right way to address each of these questions. The goal is simply to explore and get to know the data using whatever methods come to mind.