#Used-Car-Price-Analysis: What Drives the Value?

Executive Summary:

This project analyzes a dataset of 426K used cars to identify the mathematical "drivers" of price. Using the CRISP-DM framework, we cleaned the data, performed exploratory analysis, and built a Ridge Regression model to predict valuations.

Key Findings:

Top Positive Drivers: The vehicle's Year is the strongest predictor of price. Specific luxury manufacturers like Tesla, Ferrari, and Porsche also command significant premiums.

Top Negative Drivers: High Odometer readings and Front-Wheel Drive (FWD) systems correlate with lower resale values.

Fuel Efficiency: Diesel vehicles were identified as holding a higher market value relative to gasoline counterparts.

Recommendations for Dealers:

Focus Inventory: Prioritize newer, low-mileage vehicles with 4WD or AWD capabilities.

Brand Selection: Target luxury and performance brands which show higher price resilience.

Trade-ins: Use mileage as a primary negotiation lever, as the model shows steep depreciation beyond standard thresholds.