By: Lukas Chang (ldc105), Daniel Li (dal279)
The Car Price Estimator is a tool for estimating the price of used cars based on user inputs, recommending similar cars, and predicting depreciation trends. It integrates data preprocessing, machine learning, and a user-friendly GUI for streamlined decision-making.
The main application providing a Tkinter GUI for price estimation, similar car recommendations, and depreciation predictions. Uses SQLite for database operations and a regression model for price predictions.
A preprocessing script that cleans, reduces, and balances the dataset by sampling 70% recent and 30% older records. Outputs a cleaned CSV and metadata for use in the main application.
A utility script for analyzing datasets, providing insights such as record counts and date ranges to validate input files.
Ensure you have the following dependencies installed:
- Python 3.8+
- Required Python libraries:
pip3 install pandas numpy matplotlib scikit-learn sqlite3 hashlib tkinter
1. Run car_price_estimator.py:
python3 car_price_estimator.py
2. The app will launch a GUI where you can:
- Select Car Details: Use the dropdowns and input fields to provide details about the car (e.g., manufacturer, model, year, mileage, fuel type, and transmission).
- Estimate Price: Click the “Estimate Price” button to calculate the car’s estimated market value.
- View Similar Cars: After estimating the price, the app will display a list of similar cars with their details in the output area, including mileage and price.
- Predict Depreciation: Click the “Predict Depreciation” button to generate an interactive graph showing the car’s depreciation over the next 10 years.