PakWheels is the largest online marketplace for car shoppers and sellers in Pakistan. It aggregates thousands of new, used, and certified second-hand cars from thousands of dealers and private sellers. The site also provides automotive reviews, shopping advice, and comparison tools for car financing. It serves as an online community of automobile enthusiasts, with over 600,000 registered members on its online forum.

The dataset was scraped from pakwheels.com. It contains almost 90,000 records with 17 different features. The feature names are:

• ad_url: URL of the ad on pakwheels.com
• title: ad title
• location: location where the car is being sold
• model_year: the model of the car
• price: the price of the car
• mileage: mileage of the car
• engine_type: engine type of the car
• transmission: transmission of the car
• registered_in: location where the car is registered
• color: color of the car
• assembly: imported/exported car
• engine_capacity: engine capacity of the car
• body_type: body type of the car
• ad_ last_ updated: the date when the ad was last updated
• car_features: features of the car
• description: extra information being shared by the owner related to the car.

As a data analyst you should explore and analyze the dataset and try to answer the following questions:

1. how do the price of cars varies in different cities?
2. how do different features correlate with each other?
3. does the colour of the car have any effect on its price?
4. does more features of the car indicate that it is the latest model?
5. try some NLP techniques on description to extract some unique features of the car not mentioned in other columns.

Machine learning practitioners can utilize advanced machine learning algorithms to develop a model which predicts the price of the car, which could be deployed and used by the owners to know the worth of their cars.

Good Luck!