About Dataset

This dataset provides comprehensive details on used car listings, including vehicle specifications, features, #, and more. It's valuable for analyzing car prices, trends, and customer preferences in the automotive market.

Columns Description

• make_model: The brand and model of the vehicle (e.g., 'Audi A1').
• body_type: The body style of the vehicle, such as Sedan, Compact, or Station Wagon.
• price: The listed price of the car in currency.
• vat: Indicates the VAT status for the vehicle's price (e.g., VAT deductible, Price negotiable).
• km: The total mileage (in kilometers) of the vehicle, indicating its usage.
• Type: Condition of the vehicle, whether it's 'Used' or 'New'.
• Fuel: Type of fuel the vehicle uses, such as 'Diesel', 'Benzine', etc.
• Gears: The number of gears in the vehicle's transmission.
• Comfort_Convenience: Comfort and convenience features, such as 'Air conditioning', 'Leather steering wheel', 'Cruise control', and more.
• Entertainment_Media: Media features available in the vehicle, including 'Bluetooth', 'MP3', 'Radio', etc.
• Extras: Additional features like 'Alloy wheels', 'Sport suspension', etc.
• Safety_Security: Safety features like 'ABS', 'Airbags', 'Electronic stability control', 'Isofix', etc.
• age: Age of the car (calculated based on the model year).
• Previous_Owners: The number of previous owners the car has had.
• hp_kW: Engine power in kilowatts (kW), indicating the performance capacity of the engine.
• Inspection_new: Indicates whether the car has recently undergone an inspection (1 for yes, 0 for no).
• Paint_Type: The type of paint on the car, such as 'Metallic', 'Matte', etc.
• Upholstery_type: The material used for the interior upholstery, such as 'Cloth', 'Leather', etc.
• Gearing_Type: The type of transmission the car uses, either 'Automatic' or 'Manual'.
• Displacement_cc: The engine displacement in cubic centimeters (cc), indicating the size of the engine.
• Weight_kg: The total weight of the vehicle in kilograms.
• Drive_chain: The type of drivetrain, indicating whether it's 'Front' or 'Rear' wheel drive.
• cons_comb: The combined fuel consumption in liters per 100 kilometers.

Key Features

• Vehicle Specifications: Covers details like make, model, body type, fuel type, and more.
• Comfort & Safety Features: Includes information on air conditioning, safety features, and other convenience options.
• Performance Metrics: Provides data on mileage, engine power, weight, and fuel consumption.
• # Information: Insights into vehicle #, VAT status, and other cost-related details.

Ideal Use Cases

• Price Prediction: Model car prices based on features like mileage, fuel type, and performance.
• Market Analysis: Explore trends and preferences in the used car market, by type, region, or other metrics.
• Customer Segmentation: Segment the dataset to analyze different customer preferences for car types, features, or price ranges.
• Feature Importance: Identify the most important factors influencing car prices (e.g., fuel type, mileage, age).

How to run?

conda create -n car_price python=3.8 -y

conda activate car_price

pip install -r requirements.txt