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Used Vehicle Price Prediction Data
Retail & Consumer Behavior
Tags and Keywords
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Free
About
This dataset is designed for predicting the price of used vehicles. It offers an in-depth collection of automotive information, primarily extracted from the popular online automotive marketplace, cars.com. With 4,009 unique vehicle listings and a suite of nine distinct features, this resource provides valuable insights for understanding automotive market trends, informing purchasing decisions, and conducting research in the automotive industry. It serves as an excellent foundation for building predictive models and performing analytical studies related to vehicle valuation and consumer preferences.
Columns
- brand: The manufacturer's brand or company name of the vehicle.
- model: The specific model name of the vehicle.
- model_year: The manufacturing year of the vehicle, key for assessing depreciation and technological progression.
- milage: The total mileage accumulated by the vehicle, a primary indicator of wear, tear, and potential maintenance requirements.
- fuel_type: The type of fuel the vehicle operates on, such as gasoline, diesel, electric, or hybrid.
- engine: Detailed specifications of the vehicle's engine, indicating performance characteristics and efficiency.
- transmission: The type of transmission system, whether automatic, manual, or another variant.
- ext_col: The exterior colour options available for the vehicle.
- int_col: The interior colour options available for the vehicle.
- accident: Information regarding any prior history of accidents or damage reported for the vehicle.
- clean_title: Indicates whether the vehicle possesses a clean title, which can affect its resale value and legal standing.
- price: The listed price of the vehicle, enabling price comparison and budgeting.
Distribution
The dataset is typically presented in a CSV data file format. It contains 4,009 individual data points or records, each representing a unique vehicle listing. The file size is approximately 607.82 kB and comprises 12 distinct columns. While a separate sample file may be updated to the platform, the primary dataset maintains this structure and size.
Usage
This dataset is ideal for a variety of applications, including:
- Predicting used car prices: Developing models to forecast vehicle values based on various features.
- Analysing automotive trends: Identifying patterns and shifts in the used car market.
- Informing purchasing decisions: Aiding buyers in making well-informed choices by providing detailed vehicle information.
- Conducting research: Supporting academic or industry studies related to the automotive sector and consumer behaviour.
- Market analysis: Understanding pricing dynamics, depreciation rates, and feature popularity.
Coverage
The data originates from
https://www.cars.com, a prominent automotive marketplace. The model years included in the dataset span from 1974 to 2024, offering a broad historical perspective.
Key data availability notes:- Brand: 4,009 valid entries, with 57 unique brands. Ford and BMW are among the most common.
- Model: 4,009 valid entries, featuring 1,898 unique models.
- Model Year: All 4,009 entries are valid, with the majority of vehicles manufactured between 2014 and 2024.
- Mileage: All 4,009 entries are valid, showing 2,818 unique mileage figures.
- Fuel Type: 96% of entries are valid (3,839 records), with 4% missing (170 records). Gasoline is the predominant fuel type (83%).
- Engine: All 4,009 entries are valid, with 1,146 unique engine types.
- Transmission: All 4,009 entries are valid, offering 62 unique transmission types, with Automatic Transmission (A/T) being the most frequent.
- Exterior Colour: All 4,009 entries are valid, comprising 319 unique colours. Black and White are the most common.
- Interior Colour: All 4,009 entries are valid, with 156 unique colours. Black is the most common (51%).
- Accident History: 97% of entries are valid (3,896 records), with 3% missing (113 records). 73% report no prior accidents.
- Clean Title: 85% of entries are valid (3,413 records), with 15% missing (596 records). 85% of valid entries indicate a clean title.
- Price: All 4,009 entries are valid, featuring 1,569 unique price points.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
This dataset is particularly useful for:
- Data Analysts: For exploring market trends, performing statistical analysis, and building predictive models.
- Car Buyers: To assist in researching vehicle values and making informed purchasing decisions.
- Researchers: For conducting studies on automotive industry dynamics, consumer preferences, and economic factors influencing vehicle prices.
Dataset Name Suggestions
- Used Vehicle Price Prediction Data
- Automotive Market Valuation Dataset
- Second-hand Car Pricing Insights
- Vehicle Sales and Features Data
Attributes
Original Data Source: Used Vehicle Price Prediction Data
QUALITY