In this project, we will be working with a dataset of used cars from eBay Kleinanzeigen, which is the classifieds section of the German eBay website.
The dataset was originally scraped and uploaded to Kaggle. The version of the dataset we will be working with is a sample of 50,000 data points. It has been prepared by Dataquest, including a simulation of a less-cleaned version of the data.
The dataset includes the following columns:
- dateCrawled: When this ad was first crawled. All field values are taken from this date.
- name: Name of the car.
- seller: Whether the seller is private or a dealer.
- offerType: The type of listing.
- price: The price listed to sell the car.
- abtest: Whether the listing is included in an A/B test.
- vehicleType: The type of vehicle.
- yearOfRegistration: The year in which the car was first registered.
- gearbox: The transmission type.
- powerPS: The power of the car in PS.
- model: The car model name.
- kilometer: The number of kilometers the car has driven.
- monthOfRegistration: The month in which the car was first registered.
- fuelType: The type of fuel the car uses.
- brand: The brand of the car.
- notRepairedDamage: If the car has any damage that is not yet repaired.
- dateCreated: The date on which the eBay listing was created.
- nrOfPictures: The number of pictures in the ad.
- postalCode: The postal code for the location of the vehicle.
- lastSeenOnline: When the crawler last saw this ad online.
The main objective of this project is to clean the data and perform an analysis of the used car listings included in the dataset.
Feel free to explore the code and findings in the project repository. Your feedback and suggestions are highly appreciated!