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Car Specifications and Pricing Dataset
Stock & Market Data
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Free
About
This dataset is designed for regression tasks and contains detailed information about various second-hand cars, including their specifications and corresponding selling prices. Its primary purpose is to facilitate the development of machine learning models capable of accurately predicting a car's fair market value based on its attributes. This predictive tool can significantly assist both potential buyers and sellers in making informed decisions within the used car market.
Columns
- Car_ID: An integer identifier for each car record.
- Brand: Categorical data indicating the car's manufacturer, with common examples including Ford and Hyundai.
- Model: Categorical data representing the specific model of the car, such as Mustang or C-Class.
- Year: An integer indicating the manufacturing year of the car, ranging from 2016 to 2021.
- Kilometers_Driven: An integer representing the total distance the car has travelled, ranging from 10,000 km to 60,000 km, with a mean of approximately 28,100 km.
- Fuel_Type: Categorical data indicating the car's fuel type, primarily Petrol or Diesel.
- Transmission: Categorical data specifying the car's transmission type, either Automatic or Manual.
- Owner_Type: Categorical data describing the car's ownership history, such as First owner or Second owner.
- Mileage: An integer representing the car's fuel efficiency, ranging from 10 to 25, with a mean of about 17.2.
- Engine: An integer representing the car's engine displacement in CC, ranging from 999 to 4951, with a mean of approximately 1,860 CC.
- Power: An integer representing the car's power in BHP, ranging from 68 to 396, with a mean of about 158 BHP.
- Seats: An integer indicating the number of seats in the car, typically 4, 5, or 7.
- Price: An integer representing the selling price of the car, ranging from £450,000 to £4,000,000, with a mean of approximately £1,570,000.
Distribution
The dataset is provided as a CSV file named
cars.csv, with a file size of 7.26 kB. It consists of 13 columns and contains 100 valid records, with no missing data across any of the fields.Usage
This dataset is ideally suited for developing machine learning models aimed at predicting used car prices. It can be employed for regression analysis, particularly for linear regression models. Intended applications include assisting prospective car buyers and sellers in evaluating fair market values, informing pricing strategies, and building analytical tools for the automotive industry.
Coverage
The dataset covers cars manufactured between the years 2016 and 2021. There is no specific geographic or demographic scope mentioned within the provided information.
License
CC BY-SA 4.0
Who Can Use It
This dataset is particularly useful for beginner data scientists and machine learning practitioners interested in regression problems. It will primarily benefit potential car buyers and sellers who wish to estimate the fair market value of vehicles. Researchers and developers in the automotive sector could also utilise it for market analysis and predictive modelling.
Dataset Name Suggestions
- Used Car Price Predictor
- Automotive Sales Value Dataset
- Second-Hand Vehicle Pricing Data
- Car Specifications and Pricing Dataset
Attributes
Original Data Source: Car Specifications and Pricing Dataset
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