In this project, The aim is to build a predictive model to estimate used vehicle prices based on various attributes such as brand, model, mileage, engine type, transmission, etc. I am utilizing a dataset containing vehicle information that is readily available on Kaggle. This dataset comprises 188,532 data points, each representing a unique vehicle listing, and includes 13 distinct features providing valuable insights into the world of automobiles.
- Project Definition
- Jupyter Notebook and Findings
Business Context
The Used Car Price Prediction Dataset is a rich collection of automotive data extracted from the popular marketplace website, https://www.cars.com. It includes 4 unique vehicle listings and nine key features, offering valuable insights into the automotive market.
This dataset encompasses essential details such as the Brand and Model, identifying the manufacturer and specific model of each vehicle. The Model Year provides the manufacturing year, critical for evaluating depreciation and technological advancements. Mileage indicates wear and tear, helping assess maintenance needs, while Fuel Type reveals whether a vehicle uses gasoline, diesel, electricity, or hybrid fuel.
Additionally, it includes Engine Type, shedding light on performance and efficiency, and Transmission, detailing whether the vehicle is automatic, manual, or another type. Exterior and Interior Colors capture aesthetic preferences, and Accident History reveals prior damages, crucial for informed buying decisions. Lastly, the dataset highlights whether the vehicle holds a Clean Title, impacting resale value, and provides the Price, aiding in budgeting and market analysis.
This dataset is a valuable resource for automotive enthusiasts, buyers, and researchers. It allows for detailed analysis of trends, consumer preferences, and pricing strategies, making it ideal for market studies, price predictions, and decision-making in the automotive industry.
Fields Names and Meanings
- Brand & Model: Identify the brand or company name along with the specific model of each vehicle.
- Model Year: Discover the manufacturing year of the vehicles, crucial for assessing depreciation and technology advancements.
- Mileage: Obtain the mileage of each vehicle, a key indicator of wear and tear and potential maintenance requirements.
- Fuel Type: Learn about the type of fuel the vehicles run on, whether it’s gasoline, diesel, electric, or hybrid.
- Engine Type: Understand the engine specifications, shedding light on performance and efficiency.
- Transmission: Determine the transmission type, whether automatic, manual, or another variant.
- Exterior & Interior Colors: Explore the aesthetic aspects of the vehicles, including exterior and interior color options.
- Accident History: Discover whether a vehicle has a prior history of accidents or damage, crucial for informed decision-making.
- Clean Title: Evaluate the availability of a clean title, which can impact the vehicle’s resale value and legal status.
- Price: Access the listed prices for each vehicle, aiding in price comparison and budgeting.