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Used Vehicle Market Analysis Dataset
Data Science and Analytics
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About
Approximately 52 used cars is provided, with data collected from autotrader.com and carfax.com. This dataset combines vehicle specifications with historical details like service records and the number of previous owners. Containing 24 explanatory variables, it is designed for creating regression models to forecast the prices of used cars in the Seattle Area. The features cover everything from performance metrics like horsepower and torque to physical attributes such as headroom and legroom.
Columns
- id: A unique identifier for each car.
- brand: The manufacturer of the car (e.g., Honda, Volkswagen).
- model: The specific model of the car (e.g., Civic, Jetta).
- year: The manufacturing year of the vehicle.
- miles: The total miles the car has travelled.
- city_mileage: Fuel efficiency in miles per gallon (MPG) for city driving.
- highway_mileage: Fuel efficiency in miles per gallon (MPG) for highway driving.
- horsepower: The engine's power output.
- torque: The rotational force produced by the engine.
- engine_capacity_litre: The engine's displacement in litres.
- fuel_capacity: The vehicle's fuel tank capacity.
- num_cylinder: The number of cylinders in the engine.
- num_seat: The number of seats in the vehicle.
- num_owners: The count of previous owners.
- price: The listed price of the car.
- link: The URL to the original listing on autotrader.com.
- condition: The car's condition, though this column has 98% missing values.
- type: The body style of the car (e.g., sedan).
- doors: The number of doors on the vehicle.
- wheel_drive: The type of wheel drive.
- engine_type: The fuel type used by the engine (e.g., gas, hybrid).
- speed_levels: The number of speed levels in the transmission.
- front_headroom: Headroom measurement for front passengers.
- front_legroom: Legroom measurement for front passengers.
- rear_headroom: Headroom measurement for rear passengers.
- rear_legroom: Legroom measurement for rear passengers.
- service_records: The total number of available service records for the vehicle.
Distribution
The data is contained within a single CSV file named
used_cars.csv, with a file size of 30.72 kB. The dataset is structured with 27 columns and includes information for approximately 52 used cars.Usage
This dataset is suitable for a range of analytical tasks, including:
- Price Prediction: Building regression models to predict used car prices based on their features.
- Exploratory Data Analysis (EDA): Analysing the relationships between vehicle attributes and market value.
- Data Visualisation: Creating charts and graphs to illustrate trends in the used car market.
- Beginner Projects: Serving as an accessible dataset for individuals new to data science and machine learning.
Coverage
The data focuses on used cars available for sale in the Seattle Area. The vehicles included in this dataset were manufactured between 2014 and 2022.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: Can use this data to develop and test predictive pricing models.
- Data Analysts: Can conduct exploratory data analysis to find insights into the used car market.
- Students and Beginners: Can use this as a practical tool for learning regression, data visualisation, and feature engineering.
- Automotive Market Researchers: Can analyse trends in vehicle features, pricing, and depreciation.
Dataset Name Suggestions
- Seattle Used Car Price Prediction
- Used Vehicle Market Analysis Dataset
- Automobile Pricing Data (Seattle Area)
- CarFax & AutoTrader Used Car Listings
- Predictive Analytics for Used Car Prices
Attributes
Original Data Source:Used Vehicle Market Analysis Dataset
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